Kaggle competition: University of Liverpool - Ion Switching
class GP:
def __init__(self):
self.classes = 11
self.class_names = [ 'class_0',
'class_1',
'class_2',
'class_3',
'class_4',
'class_5',
'class_6',
'class_7',
'class_8',
'class_9',
'class_10']
def GrabPredictions(self, data):
oof_preds = np.zeros(( len(data), len(self.class_names)))
 oof_preds[:,0] = self.GP_class_0(data)
 oof_preds[:,1] = self.GP_class_1(data)
 oof_preds[:,2] = self.GP_class_2(data)
 oof_preds[:,3] = self.GP_class_3(data)
 oof_preds[:,4] = self.GP_class_4(data)
 oof_preds[:,5] = self.GP_class_5(data)
 oof_preds[:,6] = self.GP_class_6(data)
 oof_preds[:,7] = self.GP_class_7(data)
 oof_preds[:,8] = self.GP_class_8(data)
 oof_preds[:,9] = self.GP_class_9(data)
 oof_preds[:,10] = self.GP_class_10(data)
 oof_df = pd.DataFrame(oof_preds, columns=self.class_names)
 oof_df =oof_df.div(oof_df.sum(axis=1), axis=0)
 return oof_df
def Output(self, p):
return 1.0/(1.0+np.exp(-p))
def GP_class_0(self,data):
return self.Output(-1.394145 +
0.050000*np.tanh(((np.minimum(((((( np.where(data["abs_maxbatch"] > -998,(( data["minbatch_slices2_msignal"])-(np.minimum(((data["abs_maxbatch"])) ,(( np.where(np.maximum(((data["abs_maxbatch"])) ,(( data["abs_maxbatch_msignal"])))> -998, data["maxtominbatch_slices2_msignal"], data["minbatch_slices2_msignal"])))))) , data["maxtominbatch_slices2_msignal"])) >(((( data["minbatch_slices2_msignal"])<=(np.where(data["abs_maxbatch"] > -998, data["maxtominbatch_slices2"], data["stdbatch_msignal"])))*1.))) *1.))) ,(( data["minbatch_slices2_msignal"])))) +(data["maxtominbatch_slices2_msignal"])))+
0.050000*np.tanh(np.minimum(((data["maxtominbatch_slices2_msignal"])) ,(((( np.where(((data["signal_shift_-1"])* 2.0)> -998,(( data["maxtominbatch_slices2_msignal"])+(data["minbatch_msignal"])) , data["minbatch_msignal"])) * 2.0)))))+
0.050000*np.tanh(np.where(np.where(data["minbatch_msignal"] <= -998, np.cos(( data["meanbatch_msignal"])) , np.cos(( data["abs_minbatch_msignal"])))> -998,(((( data["minbatch_msignal"])-(data["signal_shift_-1"])))* 2.0), data["signal"])) +
0.050000*np.tanh(((np.where(np.maximum(((data["maxtominbatch_msignal"])) ,(( np.minimum(((data["meanbatch_slices2"])) ,(( np.minimum(((((data["minbatch_slices2_msignal"])/ 2.0))),(( np.minimum(((data["abs_maxbatch_slices2"])) ,(( np.sin(((( data["maxtominbatch_msignal"])+(data["maxtominbatch_msignal"])))))))))))))))) > -998, data["minbatch_slices2_msignal"],(( data["signal_shift_+1_msignal"])-(data["mean_abs_chgbatch_msignal"])))) +(data["maxtominbatch_slices2_msignal"])))+
0.050000*np.tanh(((data["abs_minbatch_msignal"])+(np.where(np.where(data["meanbatch_msignal"] <= -998, data["maxtominbatch_msignal"],(((( data["mean_abs_chgbatch_msignal"])+(data["minbatch_msignal"])))-(np.minimum(((((data["maxtominbatch_msignal"])* 2.0))),(( data["maxtominbatch_msignal"])))))) > -998, data["minbatch_msignal"], data["abs_minbatch_msignal"])))) +
0.050000*np.tanh(((data["abs_avgbatch_msignal"])-(np.where(((((data["abs_avgbatch_msignal"])-(np.where(np.minimum(((data["maxtominbatch_slices2"])) ,(((6.20043182373046875)))) > -998,(((6.20043182373046875)) +(data["signal"])) , data["signal"])))) *(((( data["abs_minbatch_slices2_msignal"])<=(( 6.20043182373046875)))*1.))) > -998,(((6.20043182373046875)) +(data["signal"])) ,(((6.20042848587036133)) +(data["signal"])))))) +
0.050000*np.tanh(np.where(data["minbatch_msignal"] <= -998, np.where(( 7.01191520690917969)> -998, data["maxtominbatch_slices2_msignal"], data["maxtominbatch_slices2_msignal"]),(( data["abs_avgbatch_slices2"])*(((np.maximum(((data["minbatch_msignal"])) ,(( data["maxtominbatch_msignal"])))) +(np.where(((data["maxtominbatch_slices2_msignal"])+(data["mean_abs_chgbatch_slices2"])) > -998, data["minbatch_msignal"], np.where(data["maxtominbatch_msignal"] > -998, data["rangebatch_msignal"], data["maxtominbatch_slices2_msignal"])))))))) +
0.050000*np.tanh(np.where(((data["mean_abs_chgbatch_slices2_msignal"])/ 2.0)> -998,(( data["maxtominbatch_msignal"])+(data["minbatch_slices2_msignal"])) ,(((np.where(np.where(((data["abs_maxbatch_msignal"])+(((data["maxtominbatch_slices2_msignal"])+(((data["minbatch_slices2_msignal"])* 2.0)))))> -998,(( data["maxtominbatch_msignal"])+(data["minbatch_slices2_msignal"])) ,(( data["abs_minbatch_slices2_msignal"])+(data["minbatch_slices2_msignal"])))> -998, data["mean_abs_chgbatch_slices2_msignal"], data["minbatch_slices2_msignal"])) <=(data["minbatch_slices2_msignal"])) *1.))) +
0.050000*np.tanh(((((data["minbatch_slices2_msignal"])-(np.tanh(((((( data["abs_maxbatch"])-(data["abs_minbatch_msignal"])))/ 2.0)))))) -(((np.where(data["maxtominbatch_msignal"] <= -998,(( data["abs_maxbatch"])-(((((data["abs_maxbatch"])-(data["abs_minbatch_msignal"])))* 2.0))),(( data["abs_maxbatch"])-(((data["abs_minbatch_msignal"])* 2.0)))))* 2.0)))) +
0.050000*np.tanh(((((data["minbatch_slices2_msignal"])+(((((( data["minbatch_slices2_msignal"])+(((((((( data["maxbatch_msignal"])*(((data["maxtominbatch_msignal"])+(np.cos(( data["rangebatch_slices2"])))))))+(data["minbatch_slices2_msignal"])))+(data["maxtominbatch_msignal"])) /2.0)))) +(((((data["maxbatch_msignal"])*(data["maxtominbatch_slices2_msignal"])))+(data["minbatch_slices2_msignal"])))) /2.0)))) * 2.0)) +
0.050000*np.tanh(((np.where(np.minimum(((np.minimum(((data["medianbatch_slices2"])) ,(( data["maxtominbatch_slices2_msignal"]))))),(( data["maxbatch_slices2"])))<= -998,(((data["maxtominbatch_slices2_msignal"])+(data["maxtominbatch_slices2_msignal"])) /2.0), data["minbatch_slices2_msignal"])) +(data["maxtominbatch_slices2_msignal"])))+
0.050000*np.tanh(((((np.where(data["abs_maxbatch_slices2_msignal"] > -998, data["minbatch_slices2_msignal"], data["meanbatch_slices2_msignal"])) +(data["maxtominbatch_slices2_msignal"])))+(np.where(np.sin(( data["minbatch_slices2"])) > -998, data["minbatch_slices2_msignal"], data["maxtominbatch_slices2_msignal"])))) +
0.050000*np.tanh(np.where(np.where(data["medianbatch_slices2_msignal"] > -998,(( data["minbatch_msignal"])+(data["maxtominbatch_msignal"])) ,(( data["maxtominbatch_msignal"])-(data["signal_shift_+1"])))<= -998,(( data["maxbatch_slices2_msignal"])+(((( -(( data["rangebatch_slices2"])))) +(np.where(data["minbatch"] > -998, data["maxtominbatch_slices2_msignal"], data["minbatch_msignal"]))))),(((( data["minbatch_slices2_msignal"])-(data["signal_shift_+1"])))* 2.0)))+
0.050000*np.tanh(((np.where(((((data["abs_maxbatch"])*(np.where(data["abs_maxbatch"] > -998,(( data["abs_avgbatch_slices2_msignal"])-(data["abs_maxbatch"])) , data["abs_avgbatch_slices2_msignal"])))) * 2.0)> -998,(( data["abs_avgbatch_slices2_msignal"])-(data["abs_maxbatch"])) , np.tanh(((( data["abs_maxbatch"])* 2.0)))))* 2.0)) +
0.050000*np.tanh(((data["maxtominbatch_slices2_msignal"])+(np.where(((((data["stdbatch_slices2"])-(data["stdbatch_slices2_msignal"])))+(((data["minbatch_msignal"])* 2.0)))> -998, data["minbatch_msignal"], data["minbatch_msignal"])))) +
0.050000*np.tanh(((((((( data["maxtominbatch_msignal"])+(np.minimum(((((data["minbatch_msignal"])+(((data["stdbatch_msignal"])+(data["minbatch_msignal"])))))) ,(((( data["maxtominbatch"])*(np.maximum(((((data["maxtominbatch_msignal"])+(data["minbatch_msignal"])))) ,(( data["abs_minbatch_slices2_msignal"])))))))))) /2.0)) +(data["minbatch_msignal"])))+(((data["minbatch_msignal"])+(data["maxtominbatch_msignal"])))))+
0.050000*np.tanh(((((data["minbatch_slices2_msignal"])+(((data["minbatch_slices2_msignal"])+(((( data["abs_minbatch_msignal"])+(np.where(np.where(data["signal"] <= -998, data["minbatch_msignal"],(((((( data["maxtominbatch_slices2_msignal"])* 2.0)) * 2.0)) * 2.0)) > -998, data["maxtominbatch_slices2_msignal"], data["maxbatch_slices2_msignal"])))/2.0)))))) * 2.0)) +
0.050000*np.tanh(((((((( data["maxtominbatch"])+(((((data["mean_abs_chgbatch_slices2_msignal"])* 2.0)) +(data["minbatch_slices2_msignal"])))) /2.0)) * 2.0)) +(((((( data["minbatch_slices2_msignal"])+(((data["abs_minbatch_msignal"])+(data["maxtominbatch_slices2"])))) /2.0)) +(((data["minbatch_slices2_msignal"])* 2.0)))))) +
0.050000*np.tanh(((((data["minbatch_slices2_msignal"])-(((( -(( np.maximum(((data["minbatch_slices2_msignal"])) ,(( np.maximum(((((( -(((( data["maxtominbatch_slices2_msignal"])/ 2.0)))))/ 2.0))),(( np.maximum(((data["abs_minbatch_msignal"])) ,(((( np.maximum(((data["abs_minbatch_slices2_msignal"])) ,(( data["abs_minbatch_slices2_msignal"])))) / 2.0)))))))))))))) / 2.0)))) * 2.0)) +
0.050000*np.tanh(np.where(((data["abs_minbatch_msignal"])*(data["abs_minbatch_msignal"])) <= -998, data["meanbatch_msignal"],(( data["abs_minbatch_slices2_msignal"])-(( -(((((( data["stdbatch_slices2_msignal"])*(data["abs_avgbatch_slices2_msignal"])))-(np.maximum(((( 12.22234630584716797))),(( data["abs_minbatch_slices2_msignal"])))))))))))) +
0.050000*np.tanh(np.where(np.where(data["minbatch_slices2_msignal"] > -998,(((( data["minbatch_slices2_msignal"])+(data["abs_maxbatch"])))-(data["minbatch_slices2_msignal"])) ,(((data["maxtominbatch_slices2_msignal"])<=(data["minbatch_slices2_msignal"])) *1.))<= -998, data["mean_abs_chgbatch_msignal"],(( data["minbatch_slices2_msignal"])+(data["abs_minbatch_slices2_msignal"])))) +
0.050000*np.tanh(((((data["abs_minbatch_msignal"])+(((((data["minbatch_msignal"])+(((( data["abs_minbatch_msignal"])+(((((((data["abs_minbatch_msignal"])+(data["maxtominbatch_slices2_msignal"])) /2.0)) +(((data["minbatch_msignal"])/ 2.0)))/2.0)))/2.0)))) -(data["rangebatch_slices2"])))))* 2.0)) +
0.050000*np.tanh(((((data["maxtominbatch_slices2_msignal"])+(data["minbatch_msignal"])))* 2.0)) +
0.050000*np.tanh(((data["minbatch_slices2_msignal"])-(np.minimum(((np.minimum(((data["signal_shift_+1"])) ,(( data["abs_minbatch_slices2_msignal"]))))),(( np.maximum(((((( data["signal_shift_+1"])<=(data["minbatch_slices2_msignal"])) *1.))) ,(( data["signal_shift_+1"])))))))))+
0.050000*np.tanh(((data["abs_minbatch_slices2_msignal"])+(( -(( np.where(((np.where(((data["maxtominbatch_slices2_msignal"])+(data["abs_maxbatch_msignal"])) > -998, data["abs_minbatch_slices2_msignal"],(((data["signal"])+(np.tanh(( np.where(data["maxtominbatch_msignal"] > -998, data["medianbatch_slices2_msignal"], data["minbatch_msignal"])))))/2.0)))+(data["medianbatch_slices2_msignal"])) <= -998,(((data["abs_minbatch_slices2_msignal"])<=(( -(( data["minbatch_msignal"])))))*1.) , data["rangebatch_slices2"])))))))+
0.050000*np.tanh(((data["abs_minbatch_msignal"])+(((((data["minbatch_slices2"])+(np.where(data["minbatch_slices2_msignal"] > -998, data["mean_abs_chgbatch_msignal"],(( data["maxtominbatch_msignal"])+(np.cos(((( data["minbatch_slices2_msignal"])+(np.minimum(((data["signal_shift_+1_msignal"])) ,(((((np.cos(((( data["minbatch_slices2_msignal"])/ 2.0)))) +(( -(( data["minbatch_slices2"])))))/2.0)))))))))))))) * 2.0)))) +
0.050000*np.tanh(((data["minbatch_slices2_msignal"])+(np.where(data["mean_abs_chgbatch_slices2_msignal"] <= -998, data["minbatch_slices2_msignal"], data["maxtominbatch_slices2_msignal"])))) +
0.050000*np.tanh(((np.minimum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(( np.minimum(((np.where(data["mean_abs_chgbatch_slices2"] > -998,(((data["maxtominbatch_msignal"])+(data["maxtominbatch_slices2_msignal"])) /2.0),(( data["minbatch"])* 2.0)))) ,(( data["minbatch_msignal"])))))))+(((data["maxtominbatch_slices2_msignal"])-(np.sin(( np.tanh(( np.sin(( np.cos(((((((( -(( data["minbatch_slices2_msignal"])))) <=(data["stdbatch_msignal"])) *1.))/ 2.0)))))))))))))) +
0.050000*np.tanh(np.where(((data["stdbatch_msignal"])-(((data["maxtominbatch"])* 2.0)))> -998,(( data["minbatch_msignal"])+(data["maxtominbatch_msignal"])) , np.where(data["medianbatch_slices2"] > -998, data["maxtominbatch_msignal"], np.tanh(( np.where(data["maxtominbatch_msignal"] > -998, np.where(data["abs_minbatch_slices2"] > -998, data["maxtominbatch_msignal"], data["maxbatch_slices2_msignal"]), np.tanh(( np.cos(( np.sin(( np.tanh(( data["stdbatch_slices2_msignal"])))))))))))))) +
0.050000*np.tanh(np.where(np.where(data["signal"] > -998, data["minbatch_slices2_msignal"],(((( data["maxtominbatch_slices2_msignal"])+(data["maxtominbatch_slices2_msignal"])))/ 2.0)) <= -998, np.where(((data["maxtominbatch_slices2_msignal"])*(data["abs_avgbatch_slices2"])) <= -998,(((((data["maxtominbatch_msignal"])+(data["minbatch_slices2_msignal"])) /2.0)) * 2.0), data["signal_shift_-1"]),(( data["maxtominbatch_slices2_msignal"])+(data["minbatch_slices2_msignal"])))) +
0.050000*np.tanh(((((data["abs_minbatch_msignal"])-(data["rangebatch_slices2"])))*(((data["rangebatch_slices2"])+(( -(( np.sin(((((data["rangebatch_slices2"])<=(((((data["abs_maxbatch_slices2_msignal"])+(( -(( data["abs_maxbatch_slices2_msignal"])))))) *(np.cos(((((data["maxtominbatch_msignal"])<=(((((data["abs_minbatch_msignal"])-(data["rangebatch_slices2"])))/ 2.0)))*1.))))))) *1.))))))))))) +
0.050000*np.tanh(((data["maxbatch_msignal"])-(((data["rangebatch_slices2"])-(((data["minbatch_slices2_msignal"])+(data["maxtominbatch_slices2_msignal"])))))))+
0.050000*np.tanh(((np.where(data["maxtominbatch_msignal"] <= -998,(((( np.where(data["signal"] <= -998,(14.39103507995605469), data["abs_minbatch_slices2"])) +(((((data["maxtominbatch_msignal"])*(((((data["signal_shift_+1"])-(data["minbatch_msignal"])))* 2.0)))) * 2.0)))) / 2.0),(((( data["minbatch_msignal"])-(data["signal_shift_+1"])))* 2.0)))* 2.0)) +
0.050000*np.tanh(((data["abs_minbatch_slices2_msignal"])+(data["minbatch_msignal"])))+
0.050000*np.tanh(np.where(np.where(data["minbatch_msignal"] <= -998,(((((( data["maxtominbatch_msignal"])>(((((((data["minbatch_msignal"])-(data["medianbatch_slices2"])))* 2.0)) -(((data["minbatch_msignal"])-(data["medianbatch_slices2"])))))) *1.))>(data["minbatch_slices2_msignal"])) *1.) , data["maxtominbatch_slices2_msignal"])<= -998, data["minbatch_slices2_msignal"],(((((( data["minbatch_msignal"])-(data["medianbatch_slices2"])))* 2.0)) * 2.0)))+
0.050000*np.tanh(np.where(data["minbatch_slices2_msignal"] <= -998,(((( np.cos(( data["abs_maxbatch_slices2_msignal"])))-(data["maxtominbatch_slices2_msignal"])))* 2.0),(( np.where(data["maxtominbatch_slices2_msignal"] > -998, data["maxtominbatch_msignal"], np.where(data["signal_shift_+1_msignal"] <= -998,(((( data["maxtominbatch_slices2_msignal"])-(((((data["abs_minbatch_msignal"])-(data["maxtominbatch_msignal"])))* 2.0)))) * 2.0), data["mean_abs_chgbatch_slices2_msignal"])))*(data["rangebatch_slices2_msignal"])))) +
0.050000*np.tanh(np.where(np.maximum(((((( data["stdbatch_msignal"])>(data["maxtominbatch_msignal"])) *1.))) ,(( data["maxtominbatch_msignal"])))> -998, data["maxtominbatch_slices2_msignal"],(((( np.where(data["minbatch_msignal"] > -998, data["rangebatch_msignal"], data["minbatch"])) * 2.0)) / 2.0)))+
0.050000*np.tanh(((((np.tanh(((( data["meanbatch_msignal"])/ 2.0)))) +(data["maxtominbatch_msignal"])))+(data["abs_avgbatch_slices2"])))+
0.050000*np.tanh(((data["maxtominbatch_slices2_msignal"])+(data["maxtominbatch_slices2"])))+
0.050000*np.tanh(((data["minbatch_msignal"])+(((data["minbatch_msignal"])+(((data["abs_minbatch_msignal"])+(((data["minbatch_msignal"])+(np.maximum(((np.where(data["medianbatch_slices2"] > -998, data["maxtominbatch_slices2_msignal"],(((data["abs_minbatch_msignal"])+(data["minbatch_msignal"])) /2.0)))) ,(( data["minbatch_msignal"])))))))))))) +
0.050000*np.tanh(np.where(((( np.maximum(((data["stdbatch_slices2_msignal"])) ,(((((data["meanbatch_slices2_msignal"])+(( -(((( data["signal"])-(((data["signal"])-(data["minbatch_msignal"])))))))))/2.0)))))>(data["maxtominbatch_slices2_msignal"])) *1.) <= -998, data["medianbatch_slices2_msignal"],(-(((( data["signal"])-(np.minimum(((data["minbatch_msignal"])) ,(( data["maxtominbatch_msignal"])))))))))) +
0.050000*np.tanh(np.minimum(((((data["maxtominbatch_slices2_msignal"])+(((data["maxtominbatch_msignal"])-(data["abs_minbatch_slices2_msignal"])))))) ,(( data["maxtominbatch_slices2_msignal"])))) +
0.050000*np.tanh(data["maxtominbatch_slices2_msignal"])+
0.050000*np.tanh(((data["maxtominbatch"])+(((((((np.maximum(((data["abs_minbatch_msignal"])) ,(( data["abs_minbatch_msignal"])))) +(((data["minbatch_msignal"])* 2.0)))) -(data["signal_shift_+1"])))-(((((data["signal_shift_+1"])+(data["maxtominbatch_slices2_msignal"])))/ 2.0)))))) +
0.050000*np.tanh(((data["abs_maxbatch_msignal"])+(np.minimum(((((((np.minimum(((data["minbatch_slices2_msignal"])) ,(( data["minbatch_slices2_msignal"])))) * 2.0)) * 2.0))),(((( data["maxtominbatch_slices2_msignal"])* 2.0)))))))+
0.050000*np.tanh(((data["minbatch_msignal"])-(np.where(data["abs_minbatch_slices2_msignal"] <= -998, np.where(np.tanh(((( data["maxtominbatch_slices2"])*(data["maxtominbatch_slices2"])))) <= -998, np.where(data["mean_abs_chgbatch_msignal"] <= -998, data["abs_maxbatch_slices2_msignal"], data["signal_shift_-1"]), data["maxbatch_slices2"]), data["signal_shift_+1"])))) +
0.050000*np.tanh(((data["maxtominbatch_slices2_msignal"])-(((( data["minbatch_slices2"])<=(np.where(((( data["abs_minbatch_slices2_msignal"])+(data["abs_maxbatch_slices2_msignal"])) /2.0)> -998, data["maxtominbatch_slices2_msignal"],(( data["maxtominbatch_slices2_msignal"])/ 2.0)))) *1.))))+
0.050000*np.tanh(((((data["maxbatch_msignal"])+(np.where(np.where(((((( data["maxtominbatch_slices2_msignal"])* 2.0)) <=(np.cos(((( np.minimum(((np.sin(( data["abs_avgbatch_slices2"])))) ,(( data["abs_maxbatch"])))) / 2.0)))))*1.) <= -998, data["medianbatch_slices2_msignal"], data["maxtominbatch_slices2_msignal"])<= -998, data["medianbatch_slices2_msignal"],(( data["abs_minbatch_slices2_msignal"])+(data["minbatch_slices2_msignal"])))))) +(data["minbatch_slices2_msignal"])))+
0.050000*np.tanh(((((data["abs_minbatch_slices2_msignal"])+(((data["minbatch_msignal"])+(data["minbatch_msignal"])))))*(np.maximum(((np.tanh(( data["stdbatch_slices2_msignal"])))) ,(( np.where(((data["maxtominbatch_slices2_msignal"])+(np.sin(( data["minbatch_msignal"])))) > -998,(((( 10.0)) +(np.cos(( np.maximum(((data["maxtominbatch_slices2_msignal"])) ,(( data["minbatch_msignal"])))))))/2.0), data["minbatch_slices2_msignal"])))))))+
0.050000*np.tanh(((((np.minimum(((data["minbatch_slices2_msignal"])) ,(( data["minbatch_msignal"])))) +(((((np.where(((data["maxbatch_slices2_msignal"])/ 2.0)<= -998, data["minbatch_slices2_msignal"], data["abs_minbatch_msignal"])) +(data["minbatch_msignal"])))+(( -(((( data["abs_minbatch_slices2_msignal"])-(np.cos(((0.0)))))))))))))+(((data["mean_abs_chgbatch_slices2_msignal"])+(((( data["abs_maxbatch"])>(data["signal_shift_+1"])) *1.))))))+
0.050000*np.tanh(((data["rangebatch_msignal"])*(((( data["maxtominbatch_msignal"])+(np.where(data["medianbatch_slices2"] > -998, data["minbatch_msignal"], data["maxtominbatch_slices2_msignal"])))/2.0)))) +
0.050000*np.tanh(((data["minbatch_msignal"])-(np.where(data["signal_shift_+1_msignal"] > -998, np.minimum(((data["medianbatch_slices2"])) ,(( np.where(np.where(np.tanh(( data["signal_shift_-1"])) > -998, data["signal_shift_-1"], data["minbatch_msignal"])<= -998, data["maxtominbatch_slices2_msignal"],(-(( data["maxtominbatch_slices2_msignal"]))))))), data["signal_shift_-1"])))) +
0.050000*np.tanh(np.minimum(((((np.minimum(((data["minbatch_msignal"])) ,(( np.where(data["maxtominbatch_slices2_msignal"] <= -998,(((( data["maxtominbatch_slices2_msignal"])* 2.0)) / 2.0), data["maxtominbatch_slices2_msignal"])))))+(data["maxtominbatch_msignal"])))) ,(((((( data["maxtominbatch_slices2_msignal"])+(np.cos(( data["signal_shift_+1_msignal"])))))/ 2.0)))))+
0.050000*np.tanh(np.where(((((data["rangebatch_slices2"])*(((data["minbatch_msignal"])+(((data["minbatch_msignal"])+(data["maxtominbatch_slices2_msignal"])))))))+(((data["minbatch_msignal"])-(data["medianbatch_msignal"])))) <= -998,(( data["maxtominbatch_slices2_msignal"])+(data["maxtominbatch_slices2_msignal"])) ,(( data["minbatch_msignal"])+(data["maxtominbatch_slices2_msignal"])))) +
0.050000*np.tanh(np.where(np.tanh(((( np.where(data["stdbatch_slices2_msignal"] > -998, data["maxtominbatch_msignal"], np.where(((data["maxtominbatch_msignal"])-(data["minbatch_slices2"])) > -998, data["maxtominbatch_msignal"],(((data["abs_avgbatch_slices2_msignal"])<=(np.where(data["signal_shift_-1_msignal"] <= -998, data["maxtominbatch_msignal"],(((data["maxtominbatch_msignal"])<=(data["mean_abs_chgbatch_msignal"])) *1.))))*1.))))*(data["signal_shift_+1"])))) > -998, data["maxtominbatch_msignal"], data["abs_maxbatch_slices2_msignal"])) +
0.050000*np.tanh(np.where(data["meanbatch_slices2_msignal"] > -998, data["maxtominbatch_slices2_msignal"],(( data["maxtominbatch_slices2_msignal"])+(data["minbatch_slices2_msignal"])))) +
0.050000*np.tanh(np.maximum(((data["maxtominbatch_slices2_msignal"])) ,(( np.where(np.where(np.minimum(((( 5.04649209976196289))),(( np.tanh(( data["maxtominbatch_slices2_msignal"])))))<= -998, data["stdbatch_msignal"], data["signal_shift_+1"])<= -998, data["signal_shift_+1"], np.where(data["medianbatch_slices2"] > -998, np.where(data["mean_abs_chgbatch_slices2_msignal"] <= -998, data["signal_shift_+1"], data["abs_minbatch_msignal"]), data["maxtominbatch_slices2_msignal"])))))) +
0.050000*np.tanh(data["maxtominbatch_msignal"])+
0.050000*np.tanh(((np.where(((data["abs_avgbatch_slices2_msignal"])-(np.maximum(((((data["abs_avgbatch_slices2"])/ 2.0))),(((((( np.cos(( data["signal_shift_-1"])))*(data["mean_abs_chgbatch_msignal"])))-(data["mean_abs_chgbatch_msignal"])))))))<= -998, np.where(((data["abs_minbatch_msignal"])* 2.0)> -998, data["minbatch_msignal"], data["stdbatch_msignal"]),(( data["maxtominbatch_slices2_msignal"])+(( -(((( np.cos(( data["meanbatch_msignal"])))* 2.0)))))))) * 2.0)) +
0.050000*np.tanh(((((data["minbatch_msignal"])+(data["abs_minbatch_slices2_msignal"])))+(np.where(((data["minbatch_slices2_msignal"])*(np.where(((data["maxtominbatch_msignal"])+(data["stdbatch_slices2_msignal"])) <= -998, data["abs_minbatch_slices2_msignal"], np.cos(( data["mean_abs_chgbatch_msignal"])))))> -998, data["minbatch_msignal"],(((data["abs_minbatch_slices2_msignal"])+(np.cos(( data["abs_maxbatch_slices2"])))) /2.0)))))+
0.050000*np.tanh(((( data["minbatch_slices2_msignal"])+(((np.where(((( data["mean_abs_chgbatch_slices2"])<=(data["maxbatch_slices2"])) *1.) > -998, data["mean_abs_chgbatch_slices2_msignal"], data["maxtominbatch"])) -(((( data["meanbatch_msignal"])<=(((((np.where(data["abs_minbatch_slices2_msignal"] > -998, data["abs_minbatch_msignal"],(((( data["minbatch_slices2_msignal"])-(data["mean_abs_chgbatch_slices2_msignal"])))+(data["abs_avgbatch_msignal"])))) * 2.0)) * 2.0)))*1.))))) /2.0)) +
0.050000*np.tanh(np.where(np.sin(((( np.sin(((((data["abs_avgbatch_slices2_msignal"])+(np.where(data["abs_minbatch_slices2"] > -998, data["maxtominbatch_msignal"], np.sin(( np.minimum(((data["meanbatch_slices2"])) ,(( data["signal_shift_+1"])))))))) /2.0)))) * 2.0)))> -998, data["maxtominbatch_msignal"], data["stdbatch_msignal"])) +
0.050000*np.tanh(np.minimum(((np.where(((((( data["maxtominbatch_slices2_msignal"])+(data["mean_abs_chgbatch_slices2_msignal"])))+(np.cos(( data["abs_minbatch_slices2_msignal"])))) /2.0)> -998, np.minimum(((data["abs_minbatch_slices2_msignal"])) ,(( data["abs_avgbatch_slices2_msignal"]))), data["maxtominbatch_slices2_msignal"]))),(( data["abs_minbatch_slices2_msignal"])))) +
0.050000*np.tanh(((((((((((data["maxtominbatch_slices2_msignal"])* 2.0)) * 2.0)) / 2.0)) / 2.0)) -(data["abs_avgbatch_msignal"])))+
0.050000*np.tanh(np.where(data["maxtominbatch_msignal"] <= -998,(((((data["maxtominbatch_slices2_msignal"])>(((((((data["maxtominbatch_slices2_msignal"])* 2.0)) / 2.0)) * 2.0)))*1.))/ 2.0),(( data["mean_abs_chgbatch_msignal"])+(np.minimum(((data["minbatch_msignal"])) ,(( np.maximum(((( 13.61060047149658203))),(((( data["abs_minbatch_msignal"])-(np.sin(((( data["abs_minbatch_msignal"])+(data["mean_abs_chgbatch_msignal"])))))))))))))))) +
0.050000*np.tanh(((data["minbatch_slices2_msignal"])+(((((data["abs_minbatch_msignal"])/ 2.0)) +(np.minimum(((((((( 4.05654144287109375)) / 2.0)) * 2.0))),(((((((data["abs_minbatch_msignal"])/ 2.0)) >(data["abs_minbatch_slices2_msignal"])) *1.))))))))) +
0.050000*np.tanh(((data["abs_minbatch_msignal"])+(np.where(np.where(data["maxtominbatch_slices2_msignal"] <= -998, data["maxtominbatch_slices2_msignal"], np.where(data["meanbatch_slices2"] > -998,(-(( data["minbatch_slices2_msignal"]))),(((data["stdbatch_msignal"])>(np.where(data["minbatch_slices2_msignal"] > -998, data["minbatch_slices2_msignal"],(((data["mean_abs_chgbatch_msignal"])>(data["minbatch_slices2_msignal"])) *1.))))*1.))) > -998, data["maxtominbatch_slices2_msignal"], data["minbatch_slices2_msignal"])))) +
0.050000*np.tanh(((data["minbatch_msignal"])+(((data["abs_minbatch_msignal"])+(np.where(np.minimum(((((data["meanbatch_slices2"])+(data["minbatch_msignal"])))) ,(( data["minbatch_msignal"])))<= -998,(( data["minbatch_msignal"])/ 2.0),(( np.sin(( data["minbatch_slices2_msignal"])))+(((data["abs_minbatch_msignal"])+(np.where(data["minbatch_slices2_msignal"] <= -998, data["stdbatch_slices2"], data["minbatch_msignal"])))))))))))+
0.050000*np.tanh(((( data["maxtominbatch_msignal"])+(np.minimum(((data["maxtominbatch_msignal"])) ,(( np.maximum(((data["rangebatch_slices2"])) ,(((( data["minbatch_slices2_msignal"])-(data["signal_shift_+1"])))))))))) /2.0)) +
0.050000*np.tanh(np.where(data["maxtominbatch_msignal"] > -998,(( data["minbatch_msignal"])-(data["signal_shift_+1"])) , np.where(data["abs_minbatch_msignal"] > -998, data["abs_avgbatch_msignal"],(( data["abs_minbatch_msignal"])-(data["signal_shift_+1"])))))+
0.050000*np.tanh(np.minimum(((np.where(np.where(data["maxtominbatch_msignal"] > -998, np.sin(((( data["maxtominbatch_msignal"])* 2.0))),(( data["maxtominbatch_msignal"])* 2.0)) > -998, data["abs_minbatch_msignal"], data["maxtominbatch_slices2"]))),(((( np.minimum(((data["rangebatch_slices2"])) ,(( np.cos(((( data["abs_minbatch_msignal"])* 2.0)))))))* 2.0)))))+
0.050000*np.tanh(((data["maxtominbatch_slices2_msignal"])+(np.where(((data["stdbatch_msignal"])/ 2.0)> -998,(-(((((np.sin(( data["abs_avgbatch_slices2_msignal"])))>(((data["maxtominbatch_slices2_msignal"])-(np.sin(((((data["minbatch_slices2"])<=(data["medianbatch_msignal"])) *1.))))))) *1.)))), np.maximum(((np.sin(( data["signal_shift_-1"])))) ,(( data["minbatch_msignal"])))))))+
0.050000*np.tanh(((((data["maxtominbatch_msignal"])* 2.0)) * 2.0)) +
0.050000*np.tanh(((np.where(data["meanbatch_slices2_msignal"] > -998,(( data["abs_minbatch_slices2_msignal"])*(np.cos(((( data["maxtominbatch_slices2_msignal"])+(data["stdbatch_msignal"])))))) ,(((( data["maxtominbatch_slices2_msignal"])*(np.cos(((( data["maxtominbatch_slices2_msignal"])+(data["stdbatch_msignal"])))))))*(((((((data["abs_minbatch_slices2_msignal"])+(data["maxtominbatch_slices2_msignal"])) /2.0)) <=(data["maxtominbatch_slices2_msignal"])) *1.))))) *(data["abs_minbatch_msignal"])))+
0.050000*np.tanh(((data["maxtominbatch_slices2_msignal"])-(((((( data["mean_abs_chgbatch_slices2_msignal"])-(data["maxtominbatch_slices2_msignal"])))>(data["maxtominbatch_slices2_msignal"])) *1.))))+
0.050000*np.tanh(np.where(data["stdbatch_slices2_msignal"] > -998,(( data["maxtominbatch_slices2_msignal"])-(((( np.tanh(((((( data["stdbatch_msignal"])+(data["abs_maxbatch_slices2_msignal"])))* 2.0)))) <=(data["stdbatch_slices2_msignal"])) *1.))) , np.sin(( data["maxtominbatch_slices2_msignal"])))) +
0.050000*np.tanh(np.where(((data["maxtominbatch_slices2_msignal"])+(((( data["minbatch_slices2_msignal"])+(np.where(data["abs_minbatch_msignal"] > -998, data["maxtominbatch_msignal"], np.tanh(( data["abs_minbatch_msignal"])))))/2.0)))<= -998, data["maxtominbatch_slices2_msignal"],(( data["abs_minbatch_msignal"])/ 2.0)))+
0.050000*np.tanh(((np.maximum(((((data["medianbatch_slices2"])+(((((np.maximum(((data["abs_maxbatch_msignal"])) ,(( np.where(data["stdbatch_slices2"] > -998, data["maxtominbatch_msignal"], data["maxtominbatch"])))))* 2.0)) -(data["maxtominbatch_msignal"])))))) ,(( np.where(( 1.0)> -998, data["maxtominbatch_msignal"], np.where(data["maxtominbatch_slices2_msignal"] <= -998, np.sin(( data["rangebatch_slices2_msignal"])) ,(1.0)))))))*(((data["minbatch_msignal"])-(data["signal_shift_-1"])))))+
0.050000*np.tanh(np.where(data["maxtominbatch_msignal"] <= -998, np.minimum(((data["mean_abs_chgbatch_slices2"])) ,(( data["minbatch_msignal"]))),(((np.minimum(((((( data["abs_avgbatch_slices2"])+(data["meanbatch_slices2"])) /2.0))),(( data["minbatch_msignal"])))) +(data["abs_minbatch_slices2_msignal"])) /2.0)))+
0.050000*np.tanh(((data["abs_minbatch_slices2_msignal"])-(((( np.where(data["maxbatch_msignal"] > -998, data["mean_abs_chgbatch_slices2_msignal"], data["maxtominbatch"])) +(data["maxtominbatch"])) /2.0)))) +
0.050000*np.tanh(np.where(data["minbatch"] > -998, np.where(np.sin(((((((((data["signal_shift_-1"])+(data["signal_shift_-1"])) /2.0)) +(data["maxtominbatch_msignal"])))* 2.0)))> -998,(-(((( data["signal_shift_-1"])+(data["mean_abs_chgbatch_slices2"]))))),(((( data["signal_shift_-1"])+(((data["signal_shift_-1"])+(data["rangebatch_slices2"])))))* 2.0)) , np.sin(((( data["abs_minbatch_slices2_msignal"])* 2.0)))))+
0.050000*np.tanh(((np.where(data["rangebatch_slices2"] > -998,(((((((data["minbatch_slices2_msignal"])+(np.minimum(((data["maxtominbatch_msignal"])) ,(( np.where(data["abs_avgbatch_slices2_msignal"] > -998,(9.0), data["minbatch_slices2_msignal"])))))))+(np.tanh(( data["mean_abs_chgbatch_msignal"])))))+(data["minbatch_slices2_msignal"])) /2.0), data["minbatch_msignal"])) * 2.0)) +
0.050000*np.tanh(((((np.where(data["minbatch_slices2_msignal"] > -998,(((data["abs_minbatch_slices2_msignal"])+(((((data["minbatch_slices2_msignal"])* 2.0)) / 2.0)))/2.0), data["rangebatch_slices2"])) +(((((data["rangebatch_slices2"])-(data["mean_abs_chgbatch_slices2_msignal"])))*(((data["minbatch_slices2_msignal"])* 2.0)))))) * 2.0)) +
0.050000*np.tanh(((( data["maxtominbatch_slices2_msignal"])+(((np.tanh(( np.cos(((( data["signal_shift_-1"])* 2.0)))))) *(((data["abs_maxbatch_msignal"])+(np.cos(( np.maximum(((( -(( np.cos(((( data["signal_shift_-1"])* 2.0)))))))) ,(((( np.tanh(( np.minimum(((data["maxbatch_msignal"])) ,(( data["maxtominbatch_msignal"])))))) / 2.0)))))))))))) /2.0)) +
0.050000*np.tanh(np.minimum(((data["maxtominbatch_msignal"])) ,(( np.where(data["abs_avgbatch_slices2_msignal"] <= -998, data["abs_minbatch_slices2"], np.tanh(( data["mean_abs_chgbatch_msignal"])))))))+
0.050000*np.tanh(((((data["abs_minbatch_msignal"])-(data["signal"])))/ 2.0)) +
0.050000*np.tanh(((data["meanbatch_slices2"])*(( -(( data["abs_maxbatch_slices2"])))))) +
0.050000*np.tanh(((data["minbatch_msignal"])+(np.where(data["abs_maxbatch_slices2_msignal"] > -998, data["maxtominbatch_msignal"],(( data["medianbatch_msignal"])+(np.where(data["abs_minbatch_slices2"] <= -998,(((data["meanbatch_msignal"])+(((data["abs_minbatch_msignal"])*(data["abs_minbatch_slices2_msignal"])))) /2.0),(-(((((11.39513206481933594)) +(data["maxtominbatch_msignal"])))))))))))) +
0.050000*np.tanh(np.cos(((( np.where(data["rangebatch_slices2"] <= -998, data["rangebatch_slices2"], np.where(data["mean_abs_chgbatch_slices2"] > -998, np.where(data["abs_maxbatch_slices2_msignal"] > -998, data["signal_shift_+1"],(( np.cos(((( data["signal_shift_+1"])* 2.0)))) *(((data["rangebatch_slices2_msignal"])* 2.0)))) , np.where(data["signal_shift_+1"] <= -998,(-(( data["signal_shift_-1"]))), data["abs_maxbatch_slices2_msignal"])))) * 2.0)))) +
0.050000*np.tanh(((data["abs_minbatch_slices2_msignal"])+(((np.sin(( data["abs_maxbatch_msignal"])))*(((data["abs_maxbatch_msignal"])*(np.cos(((((data["abs_maxbatch_msignal"])<=(((( data["abs_maxbatch_slices2"])<=(((((((np.minimum(((data["mean_abs_chgbatch_slices2"])) ,(( data["abs_maxbatch_msignal"])))) +(((data["signal_shift_-1"])+(data["maxtominbatch_msignal"])))) /2.0)) <=(data["signal_shift_-1"])) *1.))) *1.))) *1.))))))))))+
0.050000*np.tanh(((data["abs_avgbatch_slices2_msignal"])*(((((data["abs_maxbatch_msignal"])*(np.where(data["abs_maxbatch_msignal"] > -998, np.sin(( np.sin(( data["abs_maxbatch_msignal"])))) , np.maximum(((data["abs_avgbatch_slices2_msignal"])) ,(( np.tanh(( data["minbatch_slices2"])))))))))-(data["signal_shift_-1"])))))+
0.050000*np.tanh(((data["maxtominbatch_slices2_msignal"])-(data["medianbatch_slices2_msignal"])))+
0.050000*np.tanh(np.where(((( data["abs_minbatch_msignal"])<=(((( np.where(data["abs_minbatch_slices2_msignal"] <= -998, np.where(( -(( data["maxtominbatch_slices2_msignal"])))> -998, data["abs_minbatch_msignal"], np.tanh(( data["meanbatch_slices2"]))), np.maximum(((data["abs_minbatch_slices2_msignal"])) ,(( data["abs_minbatch_msignal"])))))<=(np.where(data["mean_abs_chgbatch_msignal"] > -998, data["meanbatch_slices2_msignal"], np.tanh(( np.cos(( data["abs_maxbatch"])))))))*1.))) *1.) > -998, data["mean_abs_chgbatch_slices2_msignal"],(( data["mean_abs_chgbatch_slices2_msignal"])/ 2.0)))+
0.050000*np.tanh(data["maxtominbatch_msignal"])+
0.050000*np.tanh(((np.sin(( np.where(data["meanbatch_msignal"] > -998,(( data["signal_shift_+1"])-(((( np.minimum(((data["meanbatch_msignal"])) ,(( data["abs_maxbatch_slices2_msignal"])))) >(data["minbatch_slices2_msignal"])) *1.))) , np.sin(( data["maxtominbatch_msignal"])))))) * 2.0)) +
0.050000*np.tanh(((np.tanh(( np.cos(( np.minimum(((((data["meanbatch_slices2"])* 2.0))),(( data["minbatch_msignal"])))))))) +(((np.cos(( np.minimum(((((data["meanbatch_slices2"])* 2.0))),(((((( data["stdbatch_msignal"])+(((((np.cos(( data["meanbatch_slices2"])))* 2.0)) * 2.0)))) +(data["rangebatch_msignal"])))))))) * 2.0)))) +
0.050000*np.tanh(((data["maxtominbatch_slices2_msignal"])* 2.0)) +
0.050000*np.tanh(np.minimum(((np.minimum(((np.where(data["abs_maxbatch_slices2_msignal"] > -998, data["mean_abs_chgbatch_msignal"],(( data["abs_maxbatch_slices2"])*(((((( data["mean_abs_chgbatch_msignal"])<=(data["abs_minbatch_msignal"])) *1.))+(data["maxbatch_slices2"]))))))),(((( np.minimum(((data["abs_maxbatch_msignal"])) ,(( np.sin(( data["abs_maxbatch_msignal"])))))) * 2.0)))))) ,(( np.sin(( data["abs_maxbatch_msignal"])))))) +
0.050000*np.tanh(( -(( np.cos(( np.minimum(((data["signal_shift_-1"])) ,(((((data["abs_avgbatch_msignal"])>(((( data["abs_avgbatch_msignal"])>(data["signal_shift_-1"])) *1.))) *1.))))))))))+
0.050000*np.tanh(np.sin(( np.where(( -(( np.minimum(((data["minbatch_slices2"])) ,(( data["abs_maxbatch_msignal"])))))) <= -998, np.sin(( data["signal_shift_-1"])) , np.where(((np.sin(( data["abs_maxbatch_msignal"])))*(data["mean_abs_chgbatch_slices2"])) > -998, data["abs_maxbatch_msignal"],(-(( np.where(data["signal_shift_-1_msignal"] <= -998, data["meanbatch_slices2_msignal"], np.where(np.sin(( data["abs_maxbatch_msignal"])) <= -998, np.sin(( data["meanbatch_slices2_msignal"])) , data["abs_maxbatch_msignal"])))))))))) +
0.050000*np.tanh(((((((np.where(data["signal"] > -998, data["stdbatch_msignal"],(4.18577051162719727)))/ 2.0)) +(((np.where(np.tanh(( np.minimum(((np.tanh(( data["abs_minbatch_msignal"])))) ,(((14.12254238128662109)))))) > -998, data["stdbatch_msignal"], np.minimum(((data["minbatch_slices2"])) ,(((( data["stdbatch_msignal"])/ 2.0)))))) / 2.0)))) +(np.sin(( data["minbatch_slices2"])))))+
0.050000*np.tanh(data["abs_maxbatch_slices2_msignal"])+
0.050000*np.tanh(np.where(data["signal"] > -998,(( np.cos(((( data["signal_shift_-1"])* 2.0)))) *(np.maximum(((data["abs_avgbatch_msignal"])) ,(((-(( data["signal_shift_-1"])))))))) ,(((data["abs_avgbatch_msignal"])>(((((data["mean_abs_chgbatch_msignal"])*(data["stdbatch_slices2_msignal"])))* 2.0)))*1.))) +
0.050000*np.tanh(((np.where(np.cos(((( np.cos(( np.cos(((( data["signal_shift_+1"])* 2.0)))))) * 2.0)))<= -998, np.tanh(( np.where(data["mean_abs_chgbatch_msignal"] <= -998, data["signal_shift_-1_msignal"],(-(( np.sin(( data["mean_abs_chgbatch_msignal"])))))))) ,(-(( data["signal_shift_+1"])))))* 2.0)) +
0.050000*np.tanh(((( data["abs_minbatch_msignal"])+(np.where(((( data["maxbatch_slices2_msignal"])+(data["signal_shift_-1_msignal"])) /2.0)<= -998,(( np.tanh(( data["abs_minbatch_slices2"])))*(np.cos(( data["maxtominbatch_slices2_msignal"])))) , data["minbatch_msignal"])))/2.0)) +
0.050000*np.tanh(data["maxtominbatch_slices2"])+
0.050000*np.tanh(np.where(data["maxbatch_msignal"] <= -998, np.where(data["rangebatch_slices2"] > -998, np.where(data["mean_abs_chgbatch_slices2_msignal"] > -998, data["maxtominbatch_slices2_msignal"],(( data["signal_shift_+1_msignal"])*(data["minbatch"]))), data["signal_shift_+1_msignal"]),(( data["signal_shift_+1_msignal"])*(data["minbatch"])))) +
0.050000*np.tanh(((((data["abs_maxbatch_slices2_msignal"])*(np.tanh(( np.cos(((( data["abs_maxbatch_slices2_msignal"])-(np.cos(( np.cos(( np.cos(( np.cos(((( np.cos(( np.cos(( np.minimum(((((data["stdbatch_msignal"])*(data["abs_maxbatch_msignal"])))) ,(( np.cos(( data["abs_maxbatch_msignal"])))))))))) * 2.0)))))))))))))))))) * 2.0)) +
0.050000*np.tanh(((data["signal_shift_-1_msignal"])*(((data["minbatch_slices2"])-(np.where(((((np.sin(( data["signal_shift_-1"])))-(((data["minbatch_slices2"])/ 2.0)))) +(data["signal_shift_-1_msignal"])) > -998, data["abs_maxbatch_slices2"], np.sin(( np.sin(( np.sin(( data["signal_shift_+1"])))))))))))) +
0.050000*np.tanh(((np.maximum(((data["minbatch_msignal"])) ,(( data["minbatch_slices2"])))) -(np.where(data["minbatch_slices2"] > -998, data["signal_shift_-1"],(( data["mean_abs_chgbatch_slices2"])-(((( data["minbatch_slices2"])<=(( -(((((np.maximum(((data["abs_maxbatch"])) ,(((((data["minbatch_msignal"])>(data["signal_shift_-1_msignal"])) *1.))))) <=(( 4.33556270599365234)))*1.))))))*1.))))))) +
0.050000*np.tanh(np.where(data["abs_minbatch_msignal"] <= -998,(2.0),(((( data["minbatch_slices2_msignal"])+(data["abs_minbatch_msignal"])))*(data["mean_abs_chgbatch_msignal"])))) +
0.050000*np.tanh(((((np.where(((( np.cos(((((( np.sin(( data["abs_maxbatch_msignal"])))* 2.0)) +(data["mean_abs_chgbatch_slices2_msignal"])))))+(((data["stdbatch_slices2_msignal"])/ 2.0)))/2.0)<= -998, data["abs_maxbatch_msignal"], np.sin(( data["signal_shift_-1"])))) -(np.sin(( data["abs_avgbatch_msignal"])))))* 2.0)) +
0.050000*np.tanh(np.cos(((( np.where(((( data["abs_minbatch_slices2"])>(np.where(data["signal_shift_-1"] <= -998,(( data["abs_minbatch_msignal"])* 2.0),(( np.where(((data["medianbatch_msignal"])/ 2.0)<= -998,(( np.where(data["signal_shift_-1"] <= -998, data["maxtominbatch_msignal"], data["maxbatch_msignal"])) * 2.0), data["signal_shift_-1"])) * 2.0)))) *1.) <= -998, data["signal_shift_-1"], data["signal_shift_-1"])) * 2.0)))) +
0.050000*np.tanh(((((((np.sin(( data["abs_maxbatch_msignal"])))* 2.0)) +(( -(( np.where(((data["stdbatch_msignal"])-(np.cos(((10.03387546539306641)))))> -998, np.sin(( data["abs_avgbatch_slices2_msignal"])) , np.minimum(((data["abs_maxbatch_msignal"])) ,(( data["abs_maxbatch_slices2"])))))))))) * 2.0)) +
0.050000*np.tanh(np.where(data["maxtominbatch"] <= -998, data["medianbatch_slices2_msignal"],(-(( np.where(data["signal_shift_-1"] > -998,(((( data["signal_shift_-1"])* 2.0)) -(data["minbatch"])) ,(((data["minbatch"])>(np.where(data["rangebatch_msignal"] <= -998,(((( data["signal_shift_-1"])* 2.0)) -(data["minbatch"])) ,(( data["signal_shift_-1"])/ 2.0)))) *1.))))))) +
0.050000*np.tanh(((np.where(data["abs_minbatch_slices2_msignal"] > -998, np.cos(((( np.where(((( data["maxtominbatch_msignal"])>(np.cos(( data["medianbatch_msignal"])))) *1.) > -998, data["abs_minbatch_msignal"],(-(( data["maxtominbatch_msignal"])))))* 2.0))), data["medianbatch_slices2_msignal"])) * 2.0)) +
0.050000*np.tanh(np.cos(( np.maximum(((np.sin(( np.cos(( data["rangebatch_msignal"])))))) ,(( np.maximum(((((( np.maximum(((np.cos(( np.tanh(((-(((( data["maxbatch_slices2_msignal"])+(data["abs_maxbatch_slices2"]))))))))))),(( data["abs_minbatch_slices2"])))) +(data["minbatch"])) /2.0))),(( data["rangebatch_msignal"])))))))))+
0.050000*np.tanh(((((np.sin(( np.sin(((( data["mean_abs_chgbatch_slices2_msignal"])+(np.where(np.sin(( data["maxtominbatch_msignal"])) > -998, data["abs_maxbatch"], np.sin(((( data["mean_abs_chgbatch_slices2_msignal"])+(np.where(data["maxbatch_slices2"] > -998, data["abs_maxbatch"],(( data["mean_abs_chgbatch_slices2_msignal"])+(data["mean_abs_chgbatch_slices2_msignal"])))))))))))))))* 2.0)) * 2.0)) +
0.050000*np.tanh(np.cos(( np.where(( 0.0)<= -998, np.where(data["mean_abs_chgbatch_slices2_msignal"] <= -998,(( data["mean_abs_chgbatch_slices2_msignal"])* 2.0),(( data["mean_abs_chgbatch_slices2_msignal"])* 2.0)) ,(( np.cos(( np.where(((data["mean_abs_chgbatch_slices2_msignal"])* 2.0)<= -998, np.minimum(((((( data["abs_maxbatch_slices2"])+(data["abs_avgbatch_slices2_msignal"])) /2.0))),(( data["signal_shift_+1"]))),(( data["signal_shift_+1"])* 2.0)))))* 2.0)))))+
0.050000*np.tanh(((((data["minbatch_msignal"])-(((((((data["signal_shift_+1"])* 2.0)) / 2.0)) * 2.0)))) * 2.0)) +
0.050000*np.tanh(((((data["rangebatch_msignal"])*(((( data["signal_shift_-1"])+(((data["abs_maxbatch"])/ 2.0)))/2.0)))) *(np.minimum(((np.where(data["signal_shift_+1"] <= -998, data["abs_maxbatch"], data["signal_shift_-1"]))),(((((((1.70269882678985596)) *(data["abs_maxbatch"])))*(data["signal_shift_+1"])))))))) +
0.050000*np.tanh(np.cos(((( np.where(data["signal_shift_+1"] > -998, data["signal_shift_+1"], np.maximum(((data["mean_abs_chgbatch_slices2"])) ,(( np.where(np.cos(( data["medianbatch_slices2_msignal"])) > -998,(-(( np.minimum(((data["stdbatch_slices2_msignal"])) ,(((((( data["rangebatch_slices2_msignal"])-(data["maxtominbatch_slices2"])))* 2.0))))))), np.where(((data["mean_abs_chgbatch_slices2_msignal"])* 2.0)<= -998,(( data["abs_maxbatch_msignal"])* 2.0), data["medianbatch_slices2_msignal"])))))))* 2.0)))) +
0.050000*np.tanh(np.where(((((( np.minimum(((data["abs_avgbatch_slices2"])) ,(( np.sin(((( data["minbatch_slices2_msignal"])*(((data["mean_abs_chgbatch_slices2_msignal"])+(data["mean_abs_chgbatch_slices2_msignal"])))))))))) / 2.0)) +(data["mean_abs_chgbatch_slices2_msignal"])) /2.0)<= -998,(((( -(( data["medianbatch_msignal"])))) <=(np.sin(( data["signal_shift_+1"])))) *1.) , np.cos(((( data["mean_abs_chgbatch_slices2_msignal"])+(data["mean_abs_chgbatch_slices2_msignal"])))))) +
0.050000*np.tanh(((np.sin(((((((((data["abs_maxbatch_slices2_msignal"])/ 2.0)) +(data["abs_maxbatch_slices2_msignal"])) /2.0)) +(( 2.03542518615722656)))))) * 2.0)) +
0.050000*np.tanh(np.where(((((((( np.maximum(((data["abs_minbatch_slices2"])) ,(((((( data["abs_maxbatch_msignal"])-(((data["signal"])* 2.0)))) * 2.0)))))/ 2.0)) / 2.0)) <=(((data["signal"])* 2.0)))*1.) <= -998,(( data["mean_abs_chgbatch_msignal"])* 2.0),(( np.cos(((((data["abs_minbatch_slices2"])+(((data["abs_maxbatch_slices2_msignal"])-(((data["signal"])* 2.0)))))/2.0)))) * 2.0)))+
0.050000*np.tanh(data["maxtominbatch_msignal"])+
0.050000*np.tanh(np.where(data["rangebatch_slices2"] > -998,(( data["minbatch_slices2_msignal"])-(data["signal_shift_-1"])) , np.where(data["rangebatch_slices2"] <= -998, data["minbatch_slices2_msignal"], np.where(((data["signal_shift_-1"])-(data["medianbatch_slices2_msignal"])) <= -998, data["abs_maxbatch_slices2"], data["minbatch_slices2_msignal"])))) +
0.050000*np.tanh(((data["stdbatch_slices2_msignal"])*(np.cos(((( np.maximum(((data["medianbatch_msignal"])) ,(( np.where(data["abs_maxbatch_slices2"] <= -998, data["rangebatch_msignal"], data["minbatch_slices2"])))))-(((np.where(data["maxbatch_slices2_msignal"] <= -998, np.maximum(((data["signal_shift_+1_msignal"])) ,(( data["medianbatch_msignal"]))), data["maxtominbatch_slices2_msignal"])) * 2.0)))))))) +
0.050000*np.tanh(np.minimum(((np.cos(( np.maximum(((np.tanh(( data["signal_shift_-1_msignal"])))) ,(((( data["signal_shift_-1_msignal"])* 2.0)))))))) ,(((((((data["signal_shift_+1_msignal"])<=(data["signal_shift_-1_msignal"])) *1.))* 2.0)))))+
0.050000*np.tanh(np.minimum(((np.sin(((((( np.minimum(((np.minimum(((data["signal_shift_-1"])) ,(((3.79476165771484375)))))) ,(( np.sin(((1.43593347072601318)))))))*(data["maxtominbatch"])))* 2.0))))),(((-(( data["maxtominbatch"])))))))+
0.050000*np.tanh(((np.where(np.minimum(((np.cos(( data["rangebatch_msignal"])))) ,(((((data["abs_avgbatch_msignal"])+(data["maxbatch_slices2_msignal"])) /2.0)))) > -998, np.cos(( data["abs_maxbatch_msignal"])) , np.cos(((((data["abs_avgbatch_msignal"])+(data["signal_shift_-1"])) /2.0)))))* 2.0)) +
0.050000*np.tanh(((((np.sin(((( data["abs_maxbatch_slices2_msignal"])-(np.sin(( np.sin(( data["minbatch_msignal"])))))))))*(data["mean_abs_chgbatch_slices2_msignal"])))*(np.maximum(((((data["maxbatch_slices2"])-(np.sin(((( np.sin(( data["maxtominbatch_slices2"])))-(data["abs_maxbatch_slices2_msignal"])))))))) ,(( np.sin(( np.cos(((( data["abs_maxbatch_slices2_msignal"])-(((data["meanbatch_slices2"])/ 2.0)))))))))))))+
0.050000*np.tanh(np.cos(((((((-(( np.maximum(((data["signal_shift_+1_msignal"])) ,(((-(( np.where(( -(( data["abs_maxbatch_msignal"])))> -998, data["signal_shift_+1_msignal"], np.cos(( data["signal_shift_+1_msignal"])))))))))))))+(data["signal_shift_+1"])))* 2.0)))) +
0.050000*np.tanh(np.sin(( np.cos(((( np.where(np.cos(( data["minbatch_slices2"])) <= -998, data["stdbatch_msignal"], data["stdbatch_slices2_msignal"])) *(((data["signal"])+(np.tanh(( data["stdbatch_msignal"])))))))))))+
0.050000*np.tanh(np.tanh(( data["mean_abs_chgbatch_slices2_msignal"])))+
0.050000*np.tanh(np.cos(( np.cos(((((( data["mean_abs_chgbatch_msignal"])-(((data["maxtominbatch_slices2_msignal"])*(np.where(data["maxtominbatch_msignal"] <= -998, data["abs_maxbatch_msignal"], np.where(data["signal_shift_+1"] <= -998, np.where(np.cos(( data["abs_maxbatch_msignal"])) <= -998, data["abs_maxbatch"],(0.0)) ,(0.0)))))))) * 2.0)))))) +
0.050000*np.tanh(np.cos(((( np.where(data["abs_maxbatch_slices2_msignal"] > -998,(((((data["abs_avgbatch_slices2_msignal"])* 2.0)) +(data["meanbatch_slices2_msignal"])) /2.0), np.cos(( data["minbatch_slices2"])))) -(np.cos(( data["signal_shift_-1"])))))))+
0.050000*np.tanh(( -(((((( np.maximum(((( -(( data["signal_shift_-1"]))))),(((( data["signal_shift_+1"])* 2.0)))))*(( -(((((data["abs_minbatch_slices2"])+(((data["signal_shift_+1"])/ 2.0)))/2.0)))))))*(np.where(data["abs_minbatch_slices2"] > -998,(( np.cos(((-(( np.sin(( data["abs_minbatch_msignal"])))))))) -(data["abs_maxbatch_msignal"])) ,(((data["abs_minbatch_slices2"])+(data["signal_shift_-1_msignal"])) /2.0)))))))) +
0.050000*np.tanh(((((((( data["rangebatch_slices2_msignal"])>(data["rangebatch_slices2_msignal"])) *1.))-(np.where(((( data["minbatch_msignal"])+(np.where(( -(((( data["signal_shift_+1_msignal"])*(data["abs_maxbatch"])))))<= -998, np.cos(( data["maxtominbatch_slices2"])) , data["medianbatch_slices2_msignal"])))/2.0)<= -998, data["signal_shift_+1_msignal"], data["mean_abs_chgbatch_slices2"])))) -(np.sin(((( data["medianbatch_slices2_msignal"])* 2.0)))))) +
0.050000*np.tanh(((np.cos(( np.where(((np.cos(( np.where(np.cos(((( data["mean_abs_chgbatch_slices2_msignal"])*(( -(( np.tanh(( data["signal_shift_-1_msignal"])))))))))> -998, data["abs_maxbatch_msignal"], np.cos(( np.cos(( np.cos(( np.where(data["medianbatch_slices2_msignal"] > -998, data["abs_maxbatch_slices2_msignal"], data["abs_maxbatch_msignal"])))))))))))* 2.0)> -998, data["abs_maxbatch_msignal"], data["abs_maxbatch_slices2_msignal"])))) * 2.0)) +
0.050000*np.tanh(((data["minbatch"])*(((((np.where(data["signal_shift_+1_msignal"] <= -998, data["signal_shift_-1"], data["signal_shift_+1_msignal"])) * 2.0)) * 2.0)))) +
0.050000*np.tanh(((np.maximum(((((data["signal_shift_-1_msignal"])*(np.minimum(((data["abs_maxbatch_slices2"])) ,(( np.cos(((( data["maxtominbatch_msignal"])+(data["abs_maxbatch_slices2"]))))))))))),(( data["mean_abs_chgbatch_msignal"])))) *(np.where(data["minbatch"] <= -998, data["stdbatch_msignal"],(( data["signal_shift_-1_msignal"])*(data["minbatch"])))))) +
0.050000*np.tanh(np.minimum(((((((np.cos(( data["abs_maxbatch_slices2_msignal"])))* 2.0)) * 2.0))),(( data["abs_minbatch_msignal"])))) +
0.050000*np.tanh(( -(((( np.maximum(((data["signal_shift_+1_msignal"])) ,(( np.minimum(((data["stdbatch_slices2"])) ,(( data["minbatch"])))))))+(data["signal_shift_-1_msignal"])))))) +
0.050000*np.tanh(np.where(np.sin(( data["medianbatch_slices2_msignal"])) <= -998,(((3.0)) +(data["mean_abs_chgbatch_slices2_msignal"])) ,(( data["rangebatch_msignal"])*(np.cos(((( data["abs_avgbatch_slices2"])+(np.maximum(((data["stdbatch_msignal"])) ,(((( np.sin(( data["abs_minbatch_slices2_msignal"])))-(np.sin(( data["rangebatch_msignal"])))))))))))))))+
0.050000*np.tanh(( -(((( np.maximum(((( -(((( data["maxbatch_msignal"])*(np.maximum(((np.cos(( data["signal_shift_+1"])))) ,(( np.where(data["signal_shift_-1"] <= -998, data["abs_avgbatch_slices2"], data["maxbatch_slices2_msignal"]))))))))))),(( data["abs_avgbatch_slices2"])))) *(np.maximum(((data["signal_shift_-1"])) ,(( np.maximum(((np.cos(( data["signal_shift_-1"])))) ,(( data["signal_shift_+1"])))))))))))) +
0.050000*np.tanh(((((np.cos(( data["mean_abs_chgbatch_slices2_msignal"])))*(data["signal"])))-(np.cos(( np.cos(( data["mean_abs_chgbatch_slices2_msignal"])))))))+
0.050000*np.tanh(((np.where(((np.where(np.tanh(( data["medianbatch_slices2"])) > -998, data["medianbatch_slices2_msignal"], data["maxbatch_msignal"])) *(data["abs_maxbatch_slices2_msignal"])) <= -998, np.sin(((((data["abs_avgbatch_msignal"])+(((( -(( data["medianbatch_msignal"])))) *(data["minbatch_slices2_msignal"])))) /2.0))),(13.16489601135253906)))*(np.cos(( np.maximum(((data["abs_maxbatch_slices2_msignal"])) ,(( data["signal_shift_+1"])))))))) +
0.050000*np.tanh(((data["signal_shift_+1_msignal"])*(((( -(( np.sin(((-(((-(((-(((-(( np.tanh(((-(((( data["maxtominbatch"])-(data["signal_shift_+1_msignal"])))))))))))))))))))))))))-(((np.maximum(((data["maxtominbatch_slices2_msignal"])) ,(((-(( data["minbatch"])))))))* 2.0)))))) +
0.050000*np.tanh(((data["signal_shift_-1"])*(np.minimum(((np.sin(( data["abs_avgbatch_slices2_msignal"])))) ,(((((data["signal_shift_-1"])+(((( np.where(data["maxbatch_msignal"] <= -998,(((np.sin(( data["abs_avgbatch_slices2_msignal"])))+(np.sin(( data["abs_avgbatch_slices2_msignal"])))) /2.0), data["maxtominbatch_msignal"])) +(data["abs_avgbatch_slices2_msignal"])) /2.0)))/2.0)))))))+
0.050000*np.tanh(((((data["signal_shift_+1"])*(np.where(data["abs_minbatch_slices2"] > -998, data["signal"],(( data["rangebatch_slices2_msignal"])*(data["abs_maxbatch"])))))) -(np.where(data["abs_avgbatch_slices2_msignal"] > -998, data["abs_maxbatch_slices2"], data["stdbatch_slices2"])))) +
0.050000*np.tanh(np.where(((( np.tanh(( data["abs_maxbatch_slices2_msignal"])))<=(((( np.cos(( np.sin(( np.maximum(((data["maxtominbatch_msignal"])) ,(( np.sin(((( data["stdbatch_slices2"])* 2.0)))))))))))<=(data["maxtominbatch_msignal"])) *1.))) *1.) > -998, np.cos(( np.sin(((-(( data["abs_avgbatch_msignal"]))))))), data["abs_maxbatch"])) +
0.050000*np.tanh(np.maximum(((( 7.75069904327392578))),(( np.where(data["minbatch_msignal"] <= -998, data["maxbatch_slices2_msignal"], np.maximum(((data["stdbatch_msignal"])) ,(( data["maxbatch_msignal"])))))))) +
0.050000*np.tanh(((data["maxbatch_msignal"])-(((data["abs_maxbatch"])*(np.where(data["minbatch_slices2"] > -998, data["stdbatch_slices2"], data["maxbatch_msignal"])))))) +
0.050000*np.tanh(np.cos(((( np.minimum(((((((data["rangebatch_msignal"])+(((( np.sin(( data["abs_avgbatch_msignal"])))>(data["maxtominbatch"])) *1.))))*(((( data["maxtominbatch"])+(data["abs_avgbatch_msignal"])) /2.0))))),(( np.cos(((( np.sin(((( data["abs_avgbatch_msignal"])-(data["stdbatch_slices2_msignal"])))))+(data["mean_abs_chgbatch_slices2_msignal"])))))))) +(data["abs_maxbatch_msignal"])))))+
0.050000*np.tanh(np.cos(( np.where(data["abs_maxbatch_msignal"] > -998, np.where(((data["abs_maxbatch_msignal"])+(data["meanbatch_msignal"])) <= -998,(((( data["abs_maxbatch_msignal"])*(data["abs_minbatch_slices2_msignal"])))/ 2.0), data["abs_maxbatch_msignal"]), data["medianbatch_slices2_msignal"])))) +
0.050000*np.tanh(np.maximum(((((np.cos(( data["abs_maxbatch_slices2_msignal"])))* 2.0))),(( np.minimum(((data["maxtominbatch_slices2"])) ,(( np.where(np.minimum(((data["maxtominbatch_slices2"])) ,(( data["maxtominbatch_slices2"])))<= -998, data["abs_maxbatch_slices2_msignal"],(((np.where(((np.cos(( data["abs_maxbatch_slices2_msignal"])))* 2.0)<= -998,(( data["signal_shift_+1"])-(data["signal"])) , data["mean_abs_chgbatch_slices2"])) >(data["stdbatch_msignal"])) *1.))))))))) +
0.050000*np.tanh(np.cos(( np.maximum(((data["abs_maxbatch_msignal"])) ,(( data["abs_maxbatch_msignal"])))))) +
0.050000*np.tanh(np.minimum(((data["maxtominbatch_msignal"])) ,(((( data["stdbatch_slices2"])-(((np.where(data["maxbatch_slices2"] > -998, data["signal_shift_-1"],(( np.where(((( data["signal_shift_-1"])+(((( data["signal_shift_-1"])+(((data["signal_shift_+1_msignal"])/ 2.0)))/2.0)))/2.0)> -998, data["signal_shift_-1"], np.where(data["stdbatch_slices2"] <= -998,(( data["maxtominbatch_slices2_msignal"])-(data["stdbatch_slices2"])) , data["signal_shift_+1"])))* 2.0)))* 2.0)))))))+
0.050000*np.tanh(((((( data["abs_maxbatch"])<=(( -(( data["maxtominbatch"])))))*1.))-(((((( data["signal"])>(np.cos(( np.minimum(((data["abs_maxbatch_msignal"])) ,(( data["stdbatch_msignal"])))))))*1.))-(np.sin(((( data["stdbatch_msignal"])* 2.0)))))))) +
0.050000*np.tanh(np.sin(((( data["abs_maxbatch_msignal"])+(np.maximum(((((( data["stdbatch_msignal"])<=(np.cos(( data["abs_avgbatch_slices2_msignal"])))) *1.))) ,(((((np.sin(((( data["maxtominbatch"])* 2.0)))) <=(data["abs_minbatch_slices2"])) *1.))))))))) +
0.050000*np.tanh(((np.where(np.where(data["maxtominbatch"] <= -998, data["abs_maxbatch_msignal"],(( np.where(( 2.32152748107910156)> -998,(( data["meanbatch_msignal"])*(np.tanh(( data["maxbatch_msignal"])))) , np.tanh(( data["meanbatch_slices2"])))) *(data["medianbatch_slices2_msignal"])))> -998,(( np.sin(( data["meanbatch_msignal"])))*(data["meanbatch_msignal"])) ,(((((( data["abs_avgbatch_slices2_msignal"])<=(data["abs_maxbatch_slices2_msignal"])) *1.))<=(data["maxtominbatch"])) *1.))) * 2.0)) +
0.050000*np.tanh(np.where(data["abs_avgbatch_msignal"] > -998, data["maxtominbatch_slices2"],(( data["minbatch_msignal"])-(((data["minbatch"])*(data["abs_avgbatch_msignal"])))))) +
0.050000*np.tanh(np.where(data["signal"] <= -998, data["stdbatch_msignal"],(-(((( data["rangebatch_msignal"])*(((data["rangebatch_msignal"])*(data["signal_shift_-1_msignal"])))))))))+
0.050000*np.tanh(np.where(data["minbatch_slices2_msignal"] <= -998, data["abs_maxbatch_msignal"],(((( np.cos(( data["stdbatch_slices2"])))* 2.0)) * 2.0)))+
0.050000*np.tanh(( -(( np.where(data["stdbatch_slices2_msignal"] <= -998, np.cos(( np.where(data["stdbatch_slices2_msignal"] > -998, data["stdbatch_slices2_msignal"],(( np.where(data["stdbatch_slices2_msignal"] > -998, data["maxbatch_msignal"], data["rangebatch_slices2_msignal"])) * 2.0)))) ,(( np.cos(( np.where(data["maxtominbatch_msignal"] > -998, np.where(data["stdbatch_slices2_msignal"] > -998, data["stdbatch_slices2_msignal"], np.sin(((( data["maxbatch_slices2_msignal"])/ 2.0)))) , data["maxtominbatch_msignal"])))) * 2.0)))))) +
0.050000*np.tanh(((((( 10.57091808319091797)) -(data["signal_shift_+1"])))*(np.sin(((((((10.57091808319091797)) -(data["signal_shift_+1"])))* 2.0)))))) +
0.050000*np.tanh(((np.sin(((( np.where(data["abs_avgbatch_slices2"] > -998, data["stdbatch_slices2_msignal"],(( data["stdbatch_msignal"])*(((((((np.where(((((np.sin(( data["stdbatch_slices2_msignal"])))* 2.0)) *(data["minbatch_msignal"])) > -998,(( data["medianbatch_slices2"])/ 2.0),(((( data["meanbatch_slices2"])*(data["stdbatch_slices2"])))* 2.0)))* 2.0)) * 2.0)) * 2.0)))))* 2.0)))) * 2.0)) +
0.050000*np.tanh(((np.cos(( data["abs_maxbatch_msignal"])))*(np.where(( -(((((( data["abs_maxbatch_msignal"])*(np.maximum(((((np.cos(( data["abs_avgbatch_msignal"])))*(data["mean_abs_chgbatch_slices2_msignal"])))) ,(( data["meanbatch_slices2_msignal"])))))) *(np.maximum(((data["meanbatch_slices2_msignal"])) ,(( data["medianbatch_slices2_msignal"])))))))) <= -998, data["abs_avgbatch_slices2_msignal"],(( data["rangebatch_slices2_msignal"])-(np.tanh(( data["rangebatch_slices2"])))))))) +
0.050000*np.tanh(((( 13.89447116851806641)) *(np.cos(((( np.minimum(((data["signal_shift_+1"])) ,(((((( data["stdbatch_slices2"])*(data["mean_abs_chgbatch_slices2"])))*(((data["maxtominbatch_slices2_msignal"])+(np.minimum(((((((data["abs_minbatch_msignal"])* 2.0)) * 2.0))),(((3.0)))))))))))) * 2.0)))))) +
0.050000*np.tanh(( -(((( np.where(np.where(data["maxtominbatch_slices2_msignal"] <= -998, np.cos(( data["signal_shift_-1_msignal"])) , data["meanbatch_slices2_msignal"])<= -998,(((data["maxtominbatch"])>(( 5.58624172210693359)))*1.) , data["signal_shift_-1_msignal"])) * 2.0)))))+
0.050000*np.tanh(((np.where(data["mean_abs_chgbatch_slices2"] <= -998, np.where(data["medianbatch_slices2_msignal"] <= -998, np.where(data["signal"] > -998, data["abs_minbatch_msignal"], data["maxtominbatch_msignal"]),(-(( np.cos(( data["stdbatch_slices2_msignal"])))))) ,(-(((( data["abs_avgbatch_slices2_msignal"])*(np.cos(( data["stdbatch_slices2_msignal"])))))))))* 2.0)) +
0.050000*np.tanh(((np.where(((((data["abs_maxbatch_slices2_msignal"])*(data["signal_shift_-1_msignal"])))*(data["minbatch"])) > -998, data["minbatch"],(( data["minbatch_slices2_msignal"])*(np.where(((data["mean_abs_chgbatch_slices2_msignal"])* 2.0)<= -998, data["minbatch_slices2_msignal"],(( data["minbatch"])*(data["minbatch"])))))))*(data["signal_shift_-1_msignal"])))+
0.050000*np.tanh(((np.where(((data["medianbatch_msignal"])*(data["signal"])) > -998, np.where(np.cos(((( np.where(data["medianbatch_msignal"] > -998, np.cos(( data["abs_maxbatch_slices2_msignal"])) , np.cos(((5.81919717788696289)))))*(data["abs_maxbatch_slices2_msignal"])))) > -998, np.cos(( data["abs_maxbatch_slices2_msignal"])) , data["stdbatch_msignal"]), data["maxtominbatch"])) * 2.0)) +
0.050000*np.tanh(np.sin(((( data["stdbatch_slices2"])+(np.maximum(((data["abs_maxbatch_slices2_msignal"])) ,(( np.sin(((( np.sin(((( data["medianbatch_slices2"])+(np.maximum(((data["rangebatch_msignal"])) ,(( np.maximum(((data["abs_maxbatch_slices2_msignal"])) ,(( np.maximum(((data["abs_maxbatch_slices2_msignal"])) ,(((((data["stdbatch_slices2"])>(data["maxtominbatch_slices2"])) *1.))))))))))))))) +(np.cos(( data["signal_shift_+1"])))))))))))))) +
0.050000*np.tanh(( -(( np.where(((( data["abs_avgbatch_msignal"])+(((((data["stdbatch_msignal"])+(( -(( data["abs_minbatch_msignal"])))))) * 2.0)))/2.0)<= -998,(( data["abs_maxbatch_msignal"])*(data["abs_avgbatch_slices2_msignal"])) , data["signal_shift_+1"])))))+
0.050000*np.tanh(((np.maximum(((data["medianbatch_slices2_msignal"])) ,(( data["mean_abs_chgbatch_slices2_msignal"])))) *(np.where(np.where(np.where(data["maxbatch_msignal"] > -998, np.sin(( data["minbatch_slices2"])) , data["medianbatch_slices2_msignal"])> -998, data["rangebatch_slices2_msignal"], data["maxbatch_msignal"])> -998, np.sin(( np.maximum(((data["abs_avgbatch_slices2"])) ,(( data["medianbatch_slices2_msignal"]))))), np.maximum(((data["abs_avgbatch_slices2"])) ,(( data["medianbatch_slices2_msignal"])))))))+
0.050000*np.tanh(np.cos(( np.where(data["abs_minbatch_slices2"] > -998, data["abs_maxbatch_msignal"],(((((np.where(((data["medianbatch_slices2"])+(data["maxbatch_slices2"])) > -998, data["maxbatch_slices2"], data["rangebatch_msignal"])) +(data["abs_maxbatch_msignal"])))<=(np.where(data["minbatch_msignal"] > -998, data["medianbatch_slices2"],(-(( data["maxbatch_slices2"])))))) *1.))))) +
0.050000*np.tanh(((( data["maxtominbatch_slices2_msignal"])+(np.where(np.sin(( data["abs_maxbatch_slices2_msignal"])) <= -998,(( data["abs_maxbatch_msignal"])* 2.0),(( data["abs_maxbatch_slices2_msignal"])*(np.sin(( np.maximum(((np.maximum(((data["abs_maxbatch_msignal"])) ,(( data["abs_maxbatch_slices2"]))))),(( data["stdbatch_msignal"])))))))))) /2.0)) +
0.050000*np.tanh(np.cos(((((( data["signal"])* 2.0)) -(np.cos(( np.tanh(((((((((data["rangebatch_slices2_msignal"])* 2.0)) +(np.sin(( data["signal"])))) /2.0)) / 2.0)))))))))) +
0.050000*np.tanh(((((np.sin(( data["abs_avgbatch_slices2"])))* 2.0)) * 2.0)) +
0.050000*np.tanh(((((np.maximum(((data["abs_minbatch_msignal"])) ,(((( data["abs_maxbatch_msignal"])*(((( data["maxtominbatch_slices2_msignal"])+(np.cos(((( data["mean_abs_chgbatch_slices2_msignal"])/ 2.0)))))/2.0)))))))*(np.cos(( data["abs_maxbatch_msignal"])))))* 2.0)) +
0.050000*np.tanh(((np.cos(((( data["mean_abs_chgbatch_msignal"])* 2.0)))) +(((np.cos(((( data["meanbatch_slices2"])* 2.0)))) +(np.where(np.cos(((( np.cos(((( data["signal"])* 2.0)))) * 2.0)))<= -998, np.sin(( data["maxbatch_slices2"])) ,(((( data["meanbatch_msignal"])*(np.sin(( np.cos(((( data["mean_abs_chgbatch_msignal"])* 2.0)))))))) / 2.0)))))))+
0.050000*np.tanh(np.where(data["stdbatch_slices2"] > -998, np.where(((np.cos(( data["stdbatch_slices2"])))/ 2.0)<= -998, np.where(((( data["maxtominbatch_msignal"])>(data["maxtominbatch_msignal"])) *1.) > -998, data["maxbatch_slices2_msignal"], data["signal_shift_-1"]),(( data["mean_abs_chgbatch_msignal"])*(np.where(data["abs_maxbatch_slices2_msignal"] > -998, np.cos(( data["stdbatch_slices2"])) , data["maxtominbatch_slices2"])))) , data["signal_shift_-1"])) +
0.050000*np.tanh(np.tanh(( np.cos(( np.where(( 10.32619285583496094)> -998, data["abs_maxbatch_slices2_msignal"],(((np.cos(( np.cos(( data["abs_maxbatch_slices2_msignal"])))))<=(np.tanh(( np.sin(( data["stdbatch_slices2_msignal"])))))) *1.))))))) +
0.050000*np.tanh(((((( 8.21495723724365234)) +(( -(( data["maxbatch_slices2_msignal"])))))) *(data["maxbatch_slices2_msignal"])))+
0.050000*np.tanh(((data["signal_shift_-1_msignal"])*(((data["minbatch_slices2"])-(np.cos(((( data["signal_shift_-1_msignal"])*(((((((( np.cos(( data["signal_shift_-1_msignal"])))<=(data["signal_shift_-1_msignal"])) *1.))*(data["rangebatch_slices2"])))-(( -(((( np.tanh(( data["signal_shift_-1_msignal"])))/ 2.0)))))))))))))))+
0.050000*np.tanh(((((data["meanbatch_slices2_msignal"])*(((np.sin(( data["meanbatch_slices2_msignal"])))*(np.maximum(((data["abs_maxbatch_msignal"])) ,(( data["maxtominbatch_msignal"])))))))) *(np.maximum(((data["abs_maxbatch_msignal"])) ,(( data["maxtominbatch_msignal"])))))) +
0.050000*np.tanh(((np.cos(( np.minimum(((((data["signal_shift_-1"])* 2.0))),(( np.where(((data["signal_shift_-1"])* 2.0)> -998,(( data["rangebatch_slices2_msignal"])-(data["abs_maxbatch_msignal"])) , np.sin(( data["signal_shift_-1"])))))))))* 2.0)) +
0.050000*np.tanh(np.cos(((( np.where(data["maxtominbatch_slices2_msignal"] <= -998,(((( data["medianbatch_msignal"])/ 2.0)) -(data["mean_abs_chgbatch_slices2_msignal"])) , np.maximum(((data["signal"])) ,(( data["mean_abs_chgbatch_msignal"])))))* 2.0)))) +
0.050000*np.tanh(np.where(np.where(((data["stdbatch_slices2_msignal"])* 2.0)> -998, data["maxtominbatch_slices2_msignal"], data["maxtominbatch_slices2_msignal"])> -998, data["maxtominbatch_slices2_msignal"],(((data["minbatch_msignal"])+(np.tanh(((((((-(( data["rangebatch_slices2"])))) -(((data["abs_minbatch_slices2_msignal"])*(data["abs_maxbatch_msignal"])))))*(((data["abs_maxbatch"])* 2.0)))))))/2.0)))+
0.050000*np.tanh(np.sin(((-(( np.maximum(((data["abs_avgbatch_slices2_msignal"])) ,(((-(((( np.maximum(((np.maximum(((data["minbatch_msignal"])) ,(( np.tanh(( data["maxtominbatch_msignal"]))))))),(( data["minbatch_slices2"])))) *(np.maximum(((data["abs_avgbatch_slices2_msignal"])) ,(( np.sin(( data["abs_minbatch_msignal"])))))))))))))))))))+
0.050000*np.tanh(( -(( np.where(np.maximum(((np.minimum(((data["signal"])) ,(( data["abs_avgbatch_slices2_msignal"]))))),(((( data["abs_avgbatch_slices2_msignal"])* 2.0)))) <= -998, np.maximum(((np.maximum(((data["abs_avgbatch_msignal"])) ,(( np.minimum(((data["signal_shift_-1_msignal"])) ,(( data["meanbatch_slices2_msignal"])))))))) ,(( data["minbatch_msignal"]))),(( data["mean_abs_chgbatch_msignal"])*(np.cos(( data["stdbatch_slices2_msignal"])))))))))+
0.050000*np.tanh(np.where(data["medianbatch_msignal"] > -998, np.cos(( data["abs_maxbatch_msignal"])) , np.maximum(((data["medianbatch_slices2_msignal"])) ,(((( data["mean_abs_chgbatch_slices2_msignal"])-(((data["stdbatch_slices2_msignal"])*(np.maximum(((data["minbatch_slices2"])) ,(( data["abs_avgbatch_msignal"])))))))))))) +
0.050000*np.tanh(((np.sin(((-(( np.where(((( data["meanbatch_slices2_msignal"])>(data["abs_maxbatch_msignal"])) *1.) <= -998,(((data["signal_shift_-1"])<=(data["maxbatch_slices2"])) *1.) , np.where(((data["signal"])+(data["stdbatch_slices2_msignal"])) <= -998,(( data["abs_minbatch_slices2_msignal"])* 2.0), data["signal_shift_-1"])))))))) -(((((data["medianbatch_slices2"])* 2.0)) * 2.0)))) +
0.050000*np.tanh(np.sin(((( data["stdbatch_slices2_msignal"])* 2.0)))) +
0.050000*np.tanh(((((((((data["rangebatch_msignal"])+(data["mean_abs_chgbatch_msignal"])) /2.0)) -(((data["rangebatch_msignal"])*(data["signal_shift_+1"])))))+(( -(((13.75664520263671875)))))) /2.0)) +
0.050000*np.tanh(data["abs_avgbatch_msignal"])+
0.050000*np.tanh(((data["abs_maxbatch_msignal"])*(np.where(((np.cos(( data["stdbatch_slices2"])))+(( 6.0)))> -998, np.cos(( data["stdbatch_slices2"])) , np.tanh(( data["maxtominbatch_msignal"])))))) +
0.050000*np.tanh(((data["rangebatch_msignal"])*(((((((np.cos(((( data["signal_shift_+1"])+(( -(( data["abs_maxbatch_slices2_msignal"])))))))) -(data["rangebatch_msignal"])))*(np.cos(((( data["signal_shift_+1"])+(( -(( data["abs_maxbatch_slices2_msignal"])))))))))) -(np.cos(( np.cos(( np.cos(( data["medianbatch_slices2_msignal"]))))))))))))
def GP_class_1(self,data):
return self.Output(-1.623856 +
0.050000*np.tanh(((((np.minimum(((data["abs_minbatch_slices2_msignal"])) ,(((-(( np.cos(((( data["maxtominbatch_slices2_msignal"])+(np.where(data["abs_minbatch_msignal"] > -998, data["maxtominbatch_slices2_msignal"], np.where(data["meanbatch_slices2_msignal"] > -998, np.where(data["abs_maxbatch_slices2"] > -998, data["maxtominbatch_slices2_msignal"],(( data["abs_minbatch_slices2"])+(data["maxtominbatch_msignal"]))), np.cos(((-(( data["maxtominbatch_slices2_msignal"])))))))))))))))))) * 2.0)) * 2.0)) +
0.050000*np.tanh(np.where(data["abs_minbatch_msignal"] > -998, np.where(((np.where(data["mean_abs_chgbatch_slices2"] > -998, data["maxtominbatch_slices2_msignal"], data["maxtominbatch_slices2_msignal"])) -(np.tanh(( np.where(data["maxbatch_msignal"] <= -998, data["medianbatch_slices2"],(-(( data["meanbatch_msignal"])))))))) <= -998, data["rangebatch_slices2_msignal"],(((10.0)) *(data["maxtominbatch_slices2_msignal"]))), data["maxtominbatch_slices2_msignal"])) +
0.050000*np.tanh(((data["maxtominbatch_slices2_msignal"])+(np.where(((( data["maxtominbatch_slices2_msignal"])>(np.tanh(( data["abs_minbatch_msignal"])))) *1.) > -998, data["maxtominbatch_slices2_msignal"], np.sin(((( data["signal_shift_-1"])+(((data["maxtominbatch_slices2_msignal"])* 2.0)))))))))+
0.050000*np.tanh(((((data["maxtominbatch_msignal"])-(( -(( data["maxtominbatch_msignal"])))))) -(((((data["maxtominbatch_slices2_msignal"])-(np.tanh(( np.sin(( data["maxtominbatch_msignal"])))))))*(data["maxtominbatch_msignal"])))))+
0.050000*np.tanh(((data["maxtominbatch_msignal"])+(np.where(( 4.0)> -998, data["maxtominbatch_msignal"], np.where(((( data["minbatch_msignal"])>(data["abs_maxbatch_slices2_msignal"])) *1.) <= -998,(((data["minbatch_slices2_msignal"])<=(data["maxtominbatch_msignal"])) *1.) , data["maxtominbatch_msignal"])))))+
0.050000*np.tanh(((((np.where(data["abs_minbatch_slices2_msignal"] > -998,(((( data["abs_minbatch_slices2_msignal"])*(((data["maxbatch_slices2"])-(np.sin(( data["abs_maxbatch_slices2_msignal"])))))))* 2.0), np.minimum(((np.tanh(( data["abs_minbatch_msignal"])))) ,(((((((((data["abs_minbatch_slices2_msignal"])>(data["abs_minbatch_msignal"])) *1.))* 2.0)) -(data["maxbatch_slices2"])))))))-(data["maxbatch_slices2"])))* 2.0)) +
0.050000*np.tanh(((((((np.minimum(((np.sin(( np.maximum(((data["maxtominbatch_slices2_msignal"])) ,(( data["abs_minbatch_slices2_msignal"]))))))),(((((( np.minimum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(( data["maxtominbatch_msignal"])))) +(((( data["maxtominbatch_msignal"])+(( -(( np.where(data["mean_abs_chgbatch_slices2_msignal"] <= -998, data["mean_abs_chgbatch_slices2_msignal"], data["mean_abs_chgbatch_slices2_msignal"])))))) /2.0)))) * 2.0)))))* 2.0)) * 2.0)) * 2.0)) +
0.050000*np.tanh(((( 10.30580806732177734)) *(np.minimum(((data["maxtominbatch_slices2_msignal"])) ,(( np.where(np.where(data["abs_minbatch_msignal"] > -998, np.sin(( np.maximum(((data["abs_minbatch_msignal"])) ,(( np.maximum(((data["abs_minbatch_slices2_msignal"])) ,(( np.sin(( data["mean_abs_chgbatch_slices2_msignal"])))))))))) , np.cos(( data["signal_shift_+1"])))> -998, np.sin(( np.maximum(((data["abs_minbatch_msignal"])) ,(( np.sin(( data["abs_minbatch_slices2_msignal"]))))))), data["maxtominbatch_msignal"])))))))+
0.050000*np.tanh(((((((((data["maxtominbatch_msignal"])*(((((( data["meanbatch_slices2"])+(np.sin(( data["stdbatch_msignal"])))) /2.0)) +(((((((((((data["minbatch_slices2_msignal"])+(data["meanbatch_slices2"])))* 2.0)) +(((np.sin(( data["stdbatch_msignal"])))* 2.0)))/2.0)) <=(np.sin(((( data["stdbatch_msignal"])* 2.0)))))*1.))))))* 2.0)) * 2.0)) * 2.0)) +
0.050000*np.tanh(np.where(data["maxtominbatch_slices2_msignal"] <= -998, data["meanbatch_slices2"],(((((( np.minimum(((np.sin(( np.maximum(((( -(( np.cos(( data["meanbatch_slices2_msignal"]))))))),(( data["abs_minbatch_slices2_msignal"]))))))),(( data["meanbatch_slices2_msignal"])))) +(data["abs_minbatch_msignal"])))+(((( -(( np.cos(((( data["abs_minbatch_msignal"])* 2.0)))))))*(((data["abs_avgbatch_msignal"])+(data["meanbatch_slices2_msignal"])))))))* 2.0)))+
0.050000*np.tanh(((((( 14.95742130279541016)) -(((data["rangebatch_msignal"])*(np.where(data["abs_minbatch_msignal"] > -998, data["maxtominbatch_slices2_msignal"], data["maxtominbatch_slices2_msignal"])))))) *(np.where(data["maxtominbatch_slices2_msignal"] <= -998, data["maxtominbatch_slices2_msignal"], data["maxtominbatch_msignal"])))) +
0.050000*np.tanh(((((((((data["maxtominbatch_msignal"])* 2.0)) *(((data["abs_maxbatch_slices2"])-(((data["maxtominbatch_msignal"])* 2.0)))))) +(data["maxtominbatch_msignal"])))+(data["maxtominbatch_msignal"])))+
0.050000*np.tanh(((np.where(data["maxtominbatch_slices2_msignal"] > -998, np.minimum(((((data["maxtominbatch_msignal"])+(data["maxtominbatch_msignal"])))) ,(( np.sin(((( data["maxtominbatch_slices2_msignal"])+(np.tanh(((( data["maxtominbatch_slices2_msignal"])+(((np.minimum(((np.sin(( data["maxtominbatch_slices2_msignal"])))) ,(( np.minimum(((data["mean_abs_chgbatch_msignal"])) ,(( data["maxtominbatch_msignal"])))))))+(np.sin(( data["maxtominbatch_slices2_msignal"]))))))))))))))), data["maxtominbatch_slices2_msignal"])) * 2.0)) +
0.050000*np.tanh(((data["maxtominbatch_slices2_msignal"])+(np.where(np.where(data["maxtominbatch_slices2_msignal"] > -998, np.cos(( data["maxtominbatch_slices2_msignal"])) , data["minbatch_msignal"])> -998, data["abs_minbatch_msignal"], np.where(data["medianbatch_slices2"] > -998, data["maxtominbatch_slices2_msignal"], data["maxtominbatch_msignal"])))))+
0.050000*np.tanh(((data["rangebatch_slices2"])*(np.where(((np.sin(( data["abs_minbatch_slices2_msignal"])))* 2.0)<= -998, np.sin(( np.where(data["abs_maxbatch_msignal"] <= -998, data["stdbatch_slices2_msignal"], np.minimum(((data["stdbatch_msignal"])) ,(((( np.sin(( np.sin(( data["abs_minbatch_slices2_msignal"])))))* 2.0))))))), np.minimum(((data["maxtominbatch_slices2_msignal"])) ,(((( np.sin(( data["abs_minbatch_slices2_msignal"])))* 2.0)))))))) +
0.050000*np.tanh(np.where(np.minimum(((data["abs_avgbatch_slices2_msignal"])) ,(( data["rangebatch_slices2"])))> -998, np.where(data["minbatch"] > -998, data["maxtominbatch_msignal"], np.maximum(((np.where(data["abs_minbatch_slices2_msignal"] > -998, data["maxtominbatch_msignal"], data["rangebatch_msignal"]))),(( data["maxbatch_msignal"])))) , np.minimum(((data["maxtominbatch_msignal"])) ,(( np.maximum(((np.where(data["abs_minbatch_slices2_msignal"] > -998, data["minbatch_slices2"], data["rangebatch_msignal"]))),(( data["maxbatch_msignal"])))))))) +
0.050000*np.tanh(((np.where(((( data["signal"])+(np.tanh(((( data["maxtominbatch_slices2_msignal"])-(np.where(data["abs_minbatch_msignal"] <= -998, np.cos(( data["maxtominbatch_slices2_msignal"])) , data["maxtominbatch_msignal"])))))))/2.0)> -998, data["maxtominbatch_slices2_msignal"],(((( data["maxtominbatch_slices2_msignal"])* 2.0)) *(data["mean_abs_chgbatch_slices2"])))) * 2.0)) +
0.050000*np.tanh(((data["abs_maxbatch_msignal"])*(((data["abs_maxbatch_msignal"])*(np.minimum(((((np.sin(( np.where(((((( np.sin(( np.where(data["abs_maxbatch_msignal"] > -998, data["abs_minbatch_slices2_msignal"], data["abs_minbatch_msignal"])))) +(data["mean_abs_chgbatch_slices2_msignal"])))<=(data["signal_shift_-1"])) *1.) > -998, data["abs_minbatch_slices2_msignal"], data["abs_minbatch_msignal"])))) * 2.0))),(( data["abs_maxbatch_msignal"])))))))) +
0.050000*np.tanh(((np.sin(( data["medianbatch_msignal"])))+(np.minimum(((data["maxtominbatch_slices2_msignal"])) ,(((((( np.where(data["maxtominbatch_slices2_msignal"] <= -998, np.maximum(((data["abs_minbatch_slices2_msignal"])) ,(( data["maxtominbatch_slices2_msignal"]))),(( np.where(((( data["maxtominbatch_slices2_msignal"])+(data["maxtominbatch_slices2_msignal"])) /2.0)> -998, data["abs_minbatch_msignal"], data["abs_minbatch_slices2_msignal"])) +(data["rangebatch_slices2"])))) *(np.sin(( data["abs_minbatch_slices2_msignal"])))))* 2.0)))))))+
0.050000*np.tanh(((np.minimum(((((np.where(data["maxtominbatch_slices2_msignal"] > -998, data["abs_minbatch_slices2_msignal"], data["abs_minbatch_slices2_msignal"])) +(((((data["abs_minbatch_slices2_msignal"])+(data["abs_minbatch_slices2_msignal"])))*(np.cos(( data["maxtominbatch_slices2_msignal"])))))))) ,(( np.tanh(((( np.minimum(((data["abs_minbatch_slices2_msignal"])) ,(( data["abs_avgbatch_msignal"])))) +(((data["abs_minbatch_slices2_msignal"])+(data["minbatch_slices2_msignal"])))))))))) * 2.0)) +
0.050000*np.tanh(((np.sin(( data["abs_avgbatch_slices2_msignal"])))+(((data["minbatch_slices2_msignal"])+(((np.sin(( data["abs_minbatch_msignal"])))*(np.maximum(((data["maxtominbatch_msignal"])) ,(((( data["abs_maxbatch_msignal"])* 2.0)))))))))))+
0.050000*np.tanh(((((np.sin(( np.where(((data["maxtominbatch_slices2_msignal"])+(data["maxtominbatch_slices2_msignal"])) <= -998, data["signal_shift_+1_msignal"], data["maxtominbatch_slices2_msignal"])))) *(data["rangebatch_slices2_msignal"])))-(((( np.sin(( data["abs_avgbatch_msignal"])))+(((((data["maxtominbatch_slices2_msignal"])*(data["maxtominbatch_slices2_msignal"])))* 2.0)))/2.0)))) +
0.050000*np.tanh(((data["maxtominbatch_msignal"])+(np.where(data["abs_avgbatch_msignal"] > -998,(( data["maxtominbatch_msignal"])+(data["maxtominbatch_slices2_msignal"])) ,(( data["rangebatch_msignal"])*(((data["meanbatch_slices2_msignal"])*(data["signal_shift_+1_msignal"])))))))) +
0.050000*np.tanh(np.where(np.where(data["signal_shift_-1_msignal"] > -998, np.sin(( np.minimum(((data["maxtominbatch_msignal"])) ,(( data["abs_minbatch_slices2_msignal"]))))), data["maxtominbatch"])<= -998, np.minimum(((data["maxtominbatch_slices2_msignal"])) ,(((( data["abs_maxbatch"])-(data["abs_minbatch_slices2_msignal"]))))), np.minimum(((data["maxtominbatch_msignal"])) ,(((( data["abs_maxbatch"])-(data["abs_minbatch_slices2_msignal"])))))))+
0.050000*np.tanh(np.where(((data["maxtominbatch_msignal"])+(data["maxtominbatch"])) > -998, data["maxtominbatch_msignal"], data["maxtominbatch_msignal"])) +
0.050000*np.tanh(((((((data["stdbatch_msignal"])-(((( np.maximum(((data["abs_minbatch_slices2"])) ,(( np.maximum(((data["stdbatch_msignal"])) ,(((7.0)))))))) <=(data["mean_abs_chgbatch_slices2_msignal"])) *1.))))*(data["maxtominbatch_msignal"])))*(((((( -(( np.cos(( data["minbatch_msignal"])))))) *(np.where(data["minbatch_msignal"] > -998, data["maxtominbatch_msignal"],(( data["rangebatch_slices2"])* 2.0)))))*(data["abs_minbatch_msignal"])))))+
0.050000*np.tanh(((data["maxtominbatch_slices2_msignal"])+(((data["maxtominbatch_msignal"])* 2.0)))) +
0.050000*np.tanh(((((data["maxtominbatch_msignal"])*(np.cos(((( np.cos(( np.where(((np.tanh(( data["maxtominbatch_slices2_msignal"])))-(( -(((( data["maxtominbatch_slices2_msignal"])/ 2.0)))))) <= -998,(((data["rangebatch_slices2_msignal"])+(np.minimum(((((data["mean_abs_chgbatch_msignal"])/ 2.0))),(( data["maxtominbatch_slices2_msignal"])))))/2.0), data["mean_abs_chgbatch_msignal"])))) *(data["mean_abs_chgbatch_msignal"])))))))* 2.0)) +
0.050000*np.tanh(((((np.where(data["maxtominbatch_msignal"] > -998, data["abs_minbatch_slices2_msignal"],(( data["mean_abs_chgbatch_slices2_msignal"])* 2.0)))* 2.0)) -(((( data["maxtominbatch"])<=(np.where(data["maxtominbatch_msignal"] > -998,(( np.where(data["maxtominbatch_msignal"] > -998, data["abs_minbatch_slices2_msignal"],(( data["mean_abs_chgbatch_slices2_msignal"])* 2.0)))-(data["maxtominbatch_msignal"])) , data["abs_minbatch_slices2_msignal"])))*1.))))+
0.050000*np.tanh(np.minimum(((((((np.sin(( np.where(((np.sin(((-(( data["rangebatch_msignal"])))))) * 2.0)> -998, data["abs_minbatch_msignal"], data["mean_abs_chgbatch_msignal"])))) * 2.0)) * 2.0))),(( data["maxtominbatch_slices2_msignal"])))) +
0.050000*np.tanh(np.where(data["abs_maxbatch_slices2_msignal"] <= -998, data["maxtominbatch_msignal"], np.where(data["mean_abs_chgbatch_slices2_msignal"] <= -998,(( data["minbatch_slices2"])/ 2.0),(((((( data["abs_maxbatch_msignal"])-(data["mean_abs_chgbatch_msignal"])))+(((( 11.96386051177978516)) +(data["maxbatch_slices2"])))))*(np.maximum(((data["minbatch_slices2"])) ,(( np.minimum(((((np.sin(( data["maxtominbatch_msignal"])))+(data["maxbatch_slices2"])))) ,(( data["maxtominbatch_msignal"])))))))))))+
0.050000*np.tanh(((np.where(data["abs_minbatch_msignal"] > -998, np.minimum(((np.minimum(((((data["stdbatch_slices2"])-(((np.cos(((( np.maximum(((data["mean_abs_chgbatch_msignal"])) ,(( data["maxtominbatch_slices2_msignal"])))) * 2.0)))) * 2.0))))),(((( data["abs_minbatch_msignal"])*(data["maxtominbatch_slices2_msignal"]))))))),(( data["abs_minbatch_msignal"]))),(( np.cos(((( np.maximum(((data["maxtominbatch_slices2_msignal"])) ,(( data["maxtominbatch_slices2_msignal"])))) * 2.0)))) * 2.0)))* 2.0)) +
0.050000*np.tanh(((((data["maxtominbatch_msignal"])*(((data["rangebatch_slices2"])+(np.where(data["maxtominbatch_slices2_msignal"] <= -998,(( data["signal_shift_+1"])* 2.0), data["signal_shift_+1"])))))) * 2.0)) +
0.050000*np.tanh(np.minimum(((((np.minimum(((data["maxtominbatch_msignal"])) ,(( np.tanh(( np.where(data["rangebatch_slices2_msignal"] <= -998,(( data["maxbatch_slices2"])-(data["meanbatch_slices2_msignal"])) , np.sin(( data["abs_minbatch_msignal"])))))))))* 2.0))),(((((data["abs_maxbatch_slices2_msignal"])+(((data["maxbatch_slices2"])-(data["meanbatch_slices2_msignal"])))) /2.0)))))+
0.050000*np.tanh(np.where(((((( data["maxtominbatch"])* 2.0)) <=(((data["rangebatch_msignal"])* 2.0)))*1.) > -998,(((( data["maxtominbatch_msignal"])* 2.0)) * 2.0), data["maxtominbatch_msignal"])) +
0.050000*np.tanh(((data["abs_minbatch_msignal"])+(np.maximum(((data["maxtominbatch_msignal"])) ,(( data["abs_minbatch_msignal"])))))) +
0.050000*np.tanh(((((data["maxtominbatch_slices2_msignal"])*(np.maximum(((np.where(data["abs_minbatch_slices2"] > -998, data["abs_maxbatch_msignal"],(( data["maxtominbatch"])+(data["maxtominbatch_slices2_msignal"]))))),(( np.where(data["maxtominbatch_slices2_msignal"] <= -998, np.tanh(( data["abs_maxbatch_slices2_msignal"])) ,(((data["abs_avgbatch_slices2"])>(np.where(np.where(data["maxtominbatch_msignal"] <= -998, data["stdbatch_msignal"], data["abs_avgbatch_msignal"])<= -998, data["signal_shift_+1"], data["stdbatch_msignal"])))*1.))))))))* 2.0)) +
0.050000*np.tanh(((np.where(np.cos(( data["signal"])) > -998, data["maxtominbatch_msignal"],(( np.where(np.where(((data["abs_minbatch_slices2_msignal"])* 2.0)> -998, data["maxtominbatch_msignal"],(( data["stdbatch_slices2"])* 2.0)) <= -998,(-(( data["maxtominbatch_msignal"]))),(( data["maxtominbatch_msignal"])* 2.0)))* 2.0)))* 2.0)) +
0.050000*np.tanh(np.minimum(((data["abs_minbatch_msignal"])) ,(((((( np.cos(( data["abs_avgbatch_msignal"])))*(np.minimum(((np.minimum(((((np.cos(( data["abs_avgbatch_msignal"])))*(np.minimum(((data["abs_avgbatch_msignal"])) ,(( data["signal"]))))))),(((( data["abs_avgbatch_slices2"])* 2.0)))))) ,(( data["signal"])))))) * 2.0)))))+
0.050000*np.tanh(data["maxtominbatch_slices2_msignal"])+
0.050000*np.tanh(np.where(data["maxtominbatch_msignal"] <= -998, data["maxtominbatch_slices2_msignal"],(((( np.maximum(((np.cos(( data["maxtominbatch_msignal"])))) ,(( data["abs_maxbatch"])))) * 2.0)) *(np.sin(( data["abs_minbatch_slices2_msignal"])))))) +
0.050000*np.tanh(np.where(((data["stdbatch_msignal"])*(np.sin(( data["abs_minbatch_slices2_msignal"])))) <= -998, data["maxtominbatch_slices2"],(((( data["mean_abs_chgbatch_slices2_msignal"])* 2.0)) +(np.minimum(((data["medianbatch_slices2_msignal"])) ,(((( data["abs_maxbatch_slices2_msignal"])*(np.where(np.sin(( data["minbatch_msignal"])) > -998,(( data["maxtominbatch_slices2_msignal"])*(((data["abs_maxbatch_slices2_msignal"])-(((data["maxtominbatch_slices2_msignal"])*(data["mean_abs_chgbatch_slices2_msignal"])))))) , data["abs_minbatch_msignal"])))))))))) +
0.050000*np.tanh(((np.sin(( data["abs_minbatch_msignal"])))+(np.where(data["maxtominbatch"] > -998, np.where(data["signal_shift_+1_msignal"] > -998, data["maxtominbatch"], np.where(np.where(data["maxtominbatch"] > -998, data["abs_minbatch_msignal"], data["abs_minbatch_msignal"])<= -998,(( np.sin(( data["meanbatch_slices2_msignal"])))-(data["abs_minbatch_slices2_msignal"])) , data["maxtominbatch"])) , np.cos(( data["abs_minbatch_msignal"])))))) +
0.050000*np.tanh(np.where(np.tanh(( data["meanbatch_slices2_msignal"])) > -998, np.minimum(((data["abs_minbatch_slices2_msignal"])) ,(( np.where(data["abs_minbatch_msignal"] > -998, data["maxtominbatch_slices2_msignal"], data["abs_minbatch_slices2_msignal"])))) , np.tanh(( np.where(data["meanbatch_msignal"] > -998, data["abs_minbatch_slices2_msignal"], data["abs_minbatch_slices2_msignal"])))))+
0.050000*np.tanh(((data["abs_maxbatch_slices2"])*(( -(( np.cos(((( data["abs_avgbatch_slices2_msignal"])+(( -(( np.sin(( data["abs_avgbatch_slices2_msignal"])))))))))))))))+
0.050000*np.tanh(((np.where(np.minimum(((((data["minbatch_msignal"])* 2.0))),(( data["signal_shift_-1_msignal"])))<= -998,(((data["mean_abs_chgbatch_msignal"])>(np.minimum(((data["abs_minbatch_msignal"])) ,(( np.tanh(( data["minbatch_slices2"])))))))*1.) , data["abs_minbatch_slices2_msignal"])) *(((( -(((( data["minbatch_msignal"])* 2.0)))))-(data["abs_minbatch_slices2_msignal"])))))+
0.050000*np.tanh(((np.cos(((( np.where(data["rangebatch_msignal"] > -998, data["abs_avgbatch_msignal"], np.where(((((7.0)) <=(data["signal"])) *1.) > -998, data["rangebatch_msignal"], data["maxtominbatch_slices2"])))* 2.0)))) * 2.0)) +
0.050000*np.tanh(((((data["maxtominbatch_msignal"])* 2.0)) -(np.cos(( data["signal_shift_+1_msignal"])))))+
0.050000*np.tanh(np.where(data["signal_shift_+1_msignal"] > -998, data["maxtominbatch_slices2_msignal"],(((data["abs_minbatch_msignal"])<=(((( np.tanh(((( data["signal_shift_-1_msignal"])* 2.0)))) <=(data["abs_minbatch_slices2_msignal"])) *1.))) *1.))) +
0.050000*np.tanh(np.sin(( np.sin(( np.tanh(( np.minimum(((((data["maxtominbatch_msignal"])/ 2.0))),(((((( np.minimum(((((((np.sin(( data["abs_minbatch_slices2_msignal"])))* 2.0)) / 2.0))),(((( np.tanh(( np.minimum(((np.tanh(((((( np.sin(( data["abs_minbatch_msignal"])))* 2.0)) / 2.0))))),(( data["maxtominbatch_msignal"])))))) * 2.0)))))* 2.0)) / 2.0)))))))))))+
0.050000*np.tanh(np.where(data["signal"] > -998, np.minimum(((data["rangebatch_msignal"])) ,(((( np.sin(( data["abs_minbatch_slices2_msignal"])))* 2.0)))) , np.tanh(( np.where(data["maxtominbatch_msignal"] <= -998, data["stdbatch_slices2_msignal"], data["maxtominbatch"])))))+
0.050000*np.tanh(np.where(((data["maxtominbatch_slices2_msignal"])/ 2.0)> -998,(( np.minimum(((data["abs_minbatch_msignal"])) ,(( np.tanh(( np.sin(( data["abs_minbatch_msignal"])))))))) +(data["abs_avgbatch_slices2_msignal"])) , data["abs_minbatch_msignal"])) +
0.050000*np.tanh(np.minimum(((data["maxtominbatch_slices2_msignal"])) ,(( data["abs_minbatch_slices2_msignal"])))) +
0.050000*np.tanh(((np.where(data["meanbatch_slices2"] <= -998, data["mean_abs_chgbatch_msignal"], data["maxtominbatch_msignal"])) * 2.0)) +
0.050000*np.tanh(np.minimum(((data["abs_minbatch_msignal"])) ,(((( np.sin(( np.where(data["abs_maxbatch_slices2_msignal"] > -998,(( np.minimum(((np.sin(( data["abs_minbatch_msignal"])))) ,(( data["maxtominbatch_slices2_msignal"])))) * 2.0), data["maxtominbatch_slices2_msignal"])))) -(np.cos(((( data["abs_minbatch_msignal"])* 2.0)))))))))+
0.050000*np.tanh(((np.minimum(((np.sin(( data["stdbatch_slices2_msignal"])))) ,(( np.sin(((( np.sin(( data["abs_minbatch_msignal"])))*(((( data["mean_abs_chgbatch_slices2"])+(data["maxtominbatch_msignal"])) /2.0)))))))))* 2.0)) +
0.050000*np.tanh(((np.sin(((((((((data["stdbatch_slices2_msignal"])<=(((( np.sin(((( np.sin(( data["maxtominbatch_msignal"])))-(((data["stdbatch_slices2_msignal"])-(data["abs_avgbatch_msignal"])))))))<=(((( data["stdbatch_slices2_msignal"])<=(((np.sin(( data["abs_avgbatch_msignal"])))* 2.0)))*1.))) *1.))) *1.))-(data["maxtominbatch_msignal"])))-(data["abs_avgbatch_msignal"])))))* 2.0)) +
0.050000*np.tanh(np.where(((data["maxtominbatch"])*(data["mean_abs_chgbatch_slices2_msignal"])) > -998,(( np.sin(( data["abs_minbatch_slices2_msignal"])))*(data["abs_avgbatch_slices2_msignal"])) ,(((( np.where(data["minbatch_slices2_msignal"] > -998, data["abs_avgbatch_slices2_msignal"],(( data["maxtominbatch"])*(data["abs_maxbatch_msignal"])))) *(np.sin(( data["abs_minbatch_slices2_msignal"])))))*(data["maxtominbatch_msignal"])))) +
0.050000*np.tanh(np.minimum(((np.maximum(((data["maxtominbatch_msignal"])) ,(( data["maxtominbatch_slices2"]))))),(((( np.where(data["abs_minbatch_msignal"] > -998, np.where(data["stdbatch_msignal"] > -998, np.sin(( data["abs_minbatch_msignal"])) , data["maxtominbatch_slices2_msignal"]), np.where(data["abs_minbatch_msignal"] <= -998, data["maxtominbatch_msignal"], data["maxtominbatch_msignal"])))* 2.0)))))+
0.050000*np.tanh(((np.sin(((( data["signal_shift_+1"])-(np.minimum(((data["abs_avgbatch_slices2_msignal"])) ,(( np.maximum(((((data["signal_shift_+1"])-(((data["signal_shift_+1"])-(np.minimum(((data["abs_avgbatch_slices2_msignal"])) ,(( data["abs_avgbatch_slices2_msignal"]))))))))),(((( data["abs_avgbatch_slices2_msignal"])* 2.0)))))))))))) * 2.0)) +
0.050000*np.tanh(((np.minimum(((((((( np.minimum(((np.cos(((( data["abs_avgbatch_msignal"])* 2.0))))),(( np.where(data["medianbatch_slices2"] <= -998, data["signal_shift_-1_msignal"], np.where(data["maxtominbatch_msignal"] > -998, np.sin(( data["abs_minbatch_msignal"])) ,(((np.maximum(((data["maxtominbatch_msignal"])) ,(( data["maxtominbatch_msignal"])))) +(data["minbatch_slices2_msignal"])) /2.0)))))))*(data["abs_avgbatch_msignal"])))+(data["medianbatch_slices2"])) /2.0))),(( data["abs_minbatch_msignal"])))) *(data["abs_maxbatch_slices2_msignal"])))+
0.050000*np.tanh(((( np.minimum(((data["maxtominbatch_msignal"])) ,(((( data["maxtominbatch_slices2_msignal"])/ 2.0)))))+(data["maxtominbatch_slices2_msignal"])) /2.0)) +
0.050000*np.tanh(((np.where(((np.where(data["maxtominbatch"] > -998, np.cos(((((( data["maxtominbatch_slices2_msignal"])+(data["abs_maxbatch_msignal"])))+(data["abs_maxbatch_msignal"])))) , data["maxbatch_slices2_msignal"])) * 2.0)> -998, np.cos(((( data["maxtominbatch_slices2_msignal"])+(data["abs_maxbatch_msignal"])))) ,(((((np.cos(((( data["maxtominbatch_msignal"])+(data["maxtominbatch_slices2_msignal"])))))* 2.0)) <=(data["abs_maxbatch_msignal"])) *1.))) * 2.0)) +
0.050000*np.tanh(((data["maxtominbatch_msignal"])+(np.cos(( np.sin(((( np.sin(((( data["rangebatch_msignal"])/ 2.0)))) -(data["abs_minbatch_slices2_msignal"])))))))))+
0.050000*np.tanh(((np.minimum(((data["maxtominbatch_msignal"])) ,(( np.sin(( np.maximum(((np.maximum(((np.tanh(( data["maxtominbatch_slices2_msignal"])))) ,(( data["abs_minbatch_msignal"]))))),(( np.maximum(((np.minimum(((data["mean_abs_chgbatch_msignal"])) ,(((( data["rangebatch_slices2"])+(np.where(np.sin(( data["maxtominbatch_msignal"])) > -998, np.sin(( data["abs_minbatch_msignal"])) ,(( data["maxtominbatch"])* 2.0))))))))),(( data["mean_abs_chgbatch_slices2_msignal"])))))))))))) * 2.0)) +
0.050000*np.tanh(np.where(np.where(data["maxtominbatch_slices2_msignal"] <= -998, data["abs_maxbatch_msignal"],(( data["abs_minbatch_msignal"])* 2.0)) > -998, data["maxtominbatch_msignal"], data["medianbatch_slices2_msignal"])) +
0.050000*np.tanh(((data["abs_minbatch_slices2_msignal"])*(np.sin(( np.maximum(((((( np.where(np.where(data["abs_minbatch_slices2"] > -998, data["maxtominbatch_slices2_msignal"],(( data["abs_minbatch_slices2_msignal"])+(data["abs_minbatch_slices2_msignal"])))> -998,(((((data["abs_minbatch_slices2_msignal"])/ 2.0)) +(((data["maxtominbatch_slices2_msignal"])*(np.sin(( np.maximum(((data["maxtominbatch_slices2_msignal"])) ,(( data["abs_minbatch_slices2"])))))))))/2.0), data["abs_minbatch_slices2_msignal"])) >(data["medianbatch_msignal"])) *1.))) ,(( data["abs_minbatch_slices2_msignal"])))))))) +
0.050000*np.tanh(((data["maxtominbatch_msignal"])* 2.0)) +
0.050000*np.tanh(((np.sin(( np.minimum(((((( -(( data["stdbatch_msignal"])))) * 2.0))),(( np.sin(( data["maxtominbatch"])))))))) * 2.0)) +
0.050000*np.tanh(( -(( np.cos(( np.maximum(((data["abs_avgbatch_slices2_msignal"])) ,(( data["signal_shift_+1_msignal"])))))))))+
0.050000*np.tanh(np.sin(( np.where(np.where(np.sin(( data["abs_minbatch_msignal"])) > -998, data["mean_abs_chgbatch_msignal"], data["mean_abs_chgbatch_msignal"])> -998, data["abs_minbatch_msignal"], data["mean_abs_chgbatch_slices2_msignal"])))) +
0.050000*np.tanh(np.minimum(((data["maxtominbatch_slices2_msignal"])) ,(( data["maxtominbatch_slices2_msignal"])))) +
0.050000*np.tanh(np.minimum(((np.sin(( data["maxtominbatch_msignal"])))) ,(((( np.sin(((( data["mean_abs_chgbatch_msignal"])+(np.where(((data["stdbatch_msignal"])*(np.sin(((( data["mean_abs_chgbatch_msignal"])+(np.where(((data["mean_abs_chgbatch_msignal"])* 2.0)> -998, data["abs_minbatch_slices2"], np.cos(( data["mean_abs_chgbatch_msignal"])))))))))> -998, data["abs_minbatch_slices2"], data["medianbatch_msignal"])))))) * 2.0)))))+
0.050000*np.tanh(np.cos(((( np.where(np.cos(( np.tanh(( np.sin(((((np.tanh(((( data["stdbatch_msignal"])* 2.0)))) +(data["abs_minbatch_msignal"])) /2.0)))))))<= -998, data["minbatch_slices2_msignal"], np.cos(( data["signal_shift_-1"])))) * 2.0)))) +
0.050000*np.tanh(((np.sin(( np.where(((( -(( data["rangebatch_slices2_msignal"])))) * 2.0)<= -998, np.where(data["stdbatch_msignal"] <= -998, np.sin(( data["abs_avgbatch_slices2_msignal"])) ,(( data["abs_avgbatch_slices2_msignal"])* 2.0)) ,(( data["abs_avgbatch_slices2_msignal"])* 2.0)))))* 2.0)) +
0.050000*np.tanh(((np.where(np.cos(( data["maxtominbatch_slices2_msignal"])) > -998,(-(( np.cos(( data["abs_avgbatch_msignal"]))))),(-(((( data["stdbatch_slices2_msignal"])-(data["abs_avgbatch_msignal"])))))))* 2.0)) +
0.050000*np.tanh(((np.minimum(((np.minimum(((((data["maxtominbatch_slices2_msignal"])/ 2.0))),(((0.0)))))) ,(( data["stdbatch_slices2"])))) +(((np.sin(( data["abs_minbatch_msignal"])))*(((np.sin(( np.maximum(((data["abs_minbatch_msignal"])) ,(((( data["abs_minbatch_msignal"])/ 2.0)))))))+(((data["abs_minbatch_msignal"])*(np.tanh(( data["abs_minbatch_msignal"])))))))))))+
0.050000*np.tanh(np.minimum(((((data["abs_avgbatch_msignal"])* 2.0))),(((( np.minimum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(((((9.0)) *(np.sin(((( np.minimum(((( 9.0))),(( np.where(data["abs_minbatch_slices2"] <= -998, np.minimum(((data["maxtominbatch_slices2_msignal"])) ,(( data["abs_avgbatch_msignal"]))), data["abs_avgbatch_slices2_msignal"])))))-(((( data["abs_avgbatch_slices2"])>(data["minbatch_msignal"])) *1.))))))))))) * 2.0)))))+
0.050000*np.tanh(((np.minimum(((np.where(data["maxbatch_msignal"] <= -998, data["maxtominbatch_msignal"], data["abs_minbatch_msignal"]))),(((( data["abs_minbatch_msignal"])-(((((( data["maxtominbatch_msignal"])<=(np.where(data["maxtominbatch_msignal"] <= -998, np.minimum(((data["abs_minbatch_msignal"])) ,(( data["signal_shift_-1"]))), data["mean_abs_chgbatch_msignal"])))*1.))*(((data["minbatch_slices2_msignal"])+(((data["signal_shift_-1"])*(np.minimum(((data["signal"])) ,(( data["maxtominbatch_msignal"])))))))))))))))* 2.0)) +
0.050000*np.tanh(np.where(((data["signal"])* 2.0)<= -998, data["abs_minbatch_slices2_msignal"], np.sin(( np.where(np.tanh(( data["abs_avgbatch_msignal"])) <= -998, data["stdbatch_slices2_msignal"], np.where(data["minbatch_msignal"] <= -998,(((-(((( np.sin(((( data["abs_minbatch_slices2_msignal"])* 2.0)))) +(data["mean_abs_chgbatch_slices2_msignal"])))))) * 2.0), data["maxtominbatch_msignal"])))))) +
0.050000*np.tanh(((np.sin(( np.where(((( np.minimum(((data["maxtominbatch_msignal"])) ,(( data["abs_minbatch_slices2_msignal"])))) +(np.cos(( data["maxtominbatch_slices2_msignal"])))) /2.0)<= -998, data["abs_minbatch_slices2_msignal"], data["abs_minbatch_slices2_msignal"])))) * 2.0)) +
0.050000*np.tanh(np.minimum(((np.minimum(((data["maxtominbatch_slices2_msignal"])) ,(((( data["maxtominbatch_slices2_msignal"])+(((( np.cos(((-(( data["rangebatch_slices2_msignal"])))))) >(data["abs_minbatch_msignal"])) *1.)))))))),(( data["maxtominbatch_slices2_msignal"])))) +
0.050000*np.tanh(np.where(data["medianbatch_slices2_msignal"] > -998, data["mean_abs_chgbatch_slices2_msignal"], data["maxtominbatch_slices2_msignal"])) +
0.050000*np.tanh(((np.minimum(((data["maxtominbatch_msignal"])) ,(( np.cos(((( np.where(data["maxtominbatch_slices2_msignal"] <= -998, np.where(data["maxtominbatch"] <= -998,(2.0), data["abs_avgbatch_msignal"]), data["abs_avgbatch_msignal"])) * 2.0)))))))* 2.0)) +
0.050000*np.tanh(((data["abs_minbatch_slices2_msignal"])*(np.sin(( np.where(((np.sin(( data["abs_minbatch_slices2_msignal"])))* 2.0)<= -998, np.minimum(((np.where(np.minimum(((np.sin(( data["stdbatch_slices2"])))) ,(((((data["abs_maxbatch"])+(data["signal_shift_-1"])) /2.0)))) <= -998, data["abs_minbatch_slices2_msignal"], data["abs_maxbatch"]))),(( np.sin(( data["abs_minbatch_slices2_msignal"]))))), data["abs_minbatch_slices2_msignal"])))))) +
0.050000*np.tanh(((((np.where(data["medianbatch_slices2_msignal"] <= -998, data["abs_minbatch_slices2_msignal"], np.sin(((((((np.cos(( data["abs_minbatch_msignal"])))<=(data["rangebatch_slices2"])) *1.))+(((np.where(data["abs_avgbatch_slices2_msignal"] > -998, data["abs_avgbatch_slices2_msignal"], data["maxtominbatch"])) * 2.0)))))))* 2.0)) * 2.0)) +
0.050000*np.tanh(((data["stdbatch_msignal"])* 2.0)) +
0.050000*np.tanh(np.minimum(((data["abs_minbatch_msignal"])) ,(((( data["abs_minbatch_slices2_msignal"])*(np.sin(( data["abs_minbatch_msignal"])))))))) +
0.050000*np.tanh(((( data["medianbatch_msignal"])+(((data["maxtominbatch_slices2_msignal"])*(np.where(((( data["abs_minbatch_msignal"])>(((data["abs_avgbatch_slices2_msignal"])/ 2.0)))*1.) > -998, data["abs_avgbatch_slices2_msignal"], np.tanh(( data["rangebatch_slices2_msignal"])))))))/2.0)) +
0.050000*np.tanh(((np.sin(( data["mean_abs_chgbatch_slices2_msignal"])))*(np.sin(( data["abs_avgbatch_slices2"])))))+
0.050000*np.tanh(np.minimum(((np.sin(( data["mean_abs_chgbatch_slices2_msignal"])))) ,(( data["mean_abs_chgbatch_slices2_msignal"])))) +
0.050000*np.tanh(((np.cos(( np.where(((data["signal_shift_+1"])/ 2.0)> -998,(( data["abs_maxbatch_msignal"])+(np.where(np.cos(((( data["abs_maxbatch_msignal"])+(((data["maxbatch_slices2"])* 2.0)))))> -998, data["maxtominbatch_msignal"],(( data["signal_shift_-1"])+(data["abs_maxbatch_msignal"]))))), data["abs_maxbatch_msignal"])))) * 2.0)) +
0.050000*np.tanh(np.sin(((( data["abs_minbatch_slices2"])+(np.where(data["maxtominbatch_slices2_msignal"] > -998,(( data["abs_minbatch_slices2"])+(np.maximum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(( np.where(((( data["rangebatch_slices2"])<=(((data["abs_minbatch_slices2_msignal"])*(((data["abs_minbatch_msignal"])-(data["mean_abs_chgbatch_slices2_msignal"])))))) *1.) > -998,(( data["abs_avgbatch_msignal"])* 2.0),(( data["minbatch_msignal"])*(data["medianbatch_slices2"])))))))) , data["medianbatch_msignal"])))))) +
0.050000*np.tanh(np.sin(((( np.sin(((( np.where(((((((((((( data["minbatch_msignal"])+(data["medianbatch_slices2"])) /2.0)) >(data["stdbatch_slices2_msignal"])) *1.))+(data["mean_abs_chgbatch_msignal"])))<=(data["medianbatch_slices2"])) *1.) > -998, data["minbatch_msignal"],(((data["minbatch_msignal"])<=(data["stdbatch_msignal"])) *1.))) * 2.0)))) * 2.0)))) +
0.050000*np.tanh(np.where(data["rangebatch_slices2"] <= -998,(( data["mean_abs_chgbatch_slices2_msignal"])/ 2.0),(( data["maxtominbatch_msignal"])-(np.where(np.minimum(((data["maxtominbatch_msignal"])) ,(( data["minbatch"])))> -998, data["signal_shift_-1"], np.sin(( np.where(data["maxtominbatch_msignal"] <= -998, data["abs_minbatch_msignal"], data["maxtominbatch_msignal"])))))))) +
0.050000*np.tanh(np.sin(( np.where(data["stdbatch_msignal"] <= -998, data["stdbatch_msignal"], data["rangebatch_slices2"])))) +
0.050000*np.tanh(((( -(( np.cos(( np.maximum(((np.minimum(((data["maxbatch_msignal"])) ,(( np.tanh(((((((data["minbatch_slices2_msignal"])<=(((data["abs_avgbatch_slices2_msignal"])* 2.0)))*1.))* 2.0)))))))) ,(((((( data["abs_avgbatch_slices2_msignal"])*(np.sin(((((( -(( np.maximum(((data["mean_abs_chgbatch_msignal"])) ,(( data["abs_avgbatch_slices2_msignal"])))))))<=(data["abs_avgbatch_slices2"])) *1.))))))*(((data["mean_abs_chgbatch_msignal"])/ 2.0)))))))))))) * 2.0)) +
0.050000*np.tanh(np.where(((( data["maxtominbatch_msignal"])<=(((data["maxtominbatch_msignal"])* 2.0)))*1.) <= -998, np.where(np.cos(( data["stdbatch_slices2_msignal"])) <= -998, data["maxbatch_slices2_msignal"], data["stdbatch_slices2_msignal"]),(( np.sin(((( data["mean_abs_chgbatch_msignal"])-(((np.cos(((-(( data["signal_shift_-1"])))))) / 2.0)))))) * 2.0)))+
0.050000*np.tanh(((np.sin(( np.maximum(((data["stdbatch_slices2_msignal"])) ,(( np.where(((data["maxbatch_msignal"])-(data["mean_abs_chgbatch_slices2"])) <= -998, data["maxtominbatch"], np.where(np.cos(( data["abs_minbatch_slices2_msignal"])) <= -998,(((( -(( np.sin(( data["abs_avgbatch_msignal"])))))) >(data["minbatch"])) *1.) , data["maxtominbatch"])))))))) * 2.0)) +
0.050000*np.tanh(np.where(np.sin(( data["stdbatch_msignal"])) <= -998,(( np.where(((np.sin(((((( np.sin(( data["stdbatch_msignal"])))* 2.0)) * 2.0)))) *(data["stdbatch_msignal"])) > -998, data["medianbatch_msignal"], np.maximum(((np.sin(( data["stdbatch_msignal"])))) ,(( data["stdbatch_msignal"])))))* 2.0),(((( np.sin(( data["stdbatch_msignal"])))* 2.0)) * 2.0)))+
0.050000*np.tanh(np.where(data["mean_abs_chgbatch_slices2"] <= -998, data["abs_avgbatch_msignal"],(((6.0)) *(np.cos(( np.where(data["abs_maxbatch_slices2_msignal"] <= -998,(( np.cos(( np.cos(( np.where(np.where(data["abs_avgbatch_msignal"] <= -998,(( data["mean_abs_chgbatch_slices2_msignal"])*(np.cos(((6.0))))), data["maxtominbatch"])<= -998, data["abs_avgbatch_slices2_msignal"],(( data["abs_avgbatch_slices2_msignal"])* 2.0)))))))* 2.0),(( data["abs_avgbatch_slices2_msignal"])* 2.0)))))))) +
0.050000*np.tanh(((np.where(np.cos(( data["maxtominbatch"])) > -998, data["maxtominbatch"], np.minimum(((np.cos(( np.sin(( data["abs_avgbatch_msignal"])))))) ,(( data["medianbatch_slices2_msignal"])))))+(((np.sin(((( data["signal_shift_-1"])-(data["abs_avgbatch_msignal"])))))* 2.0)))) +
0.050000*np.tanh(((( 7.0)) *(np.cos(((( np.minimum(((((data["mean_abs_chgbatch_msignal"])*(np.cos(( data["mean_abs_chgbatch_msignal"])))))) ,(( data["signal_shift_-1"])))) *(np.where(data["abs_maxbatch_slices2"] <= -998, data["maxtominbatch_slices2"], np.where(data["maxbatch_slices2_msignal"] <= -998, data["mean_abs_chgbatch_msignal"], np.cos(( data["mean_abs_chgbatch_msignal"])))))))))))+
0.050000*np.tanh(((data["abs_minbatch_slices2_msignal"])-(data["signal_shift_-1"])))+
0.050000*np.tanh(((data["minbatch"])*(np.cos(((((( np.maximum(((((data["maxtominbatch_slices2_msignal"])/ 2.0))),(((((np.where(((((data["signal_shift_+1"])/ 2.0)) * 2.0)> -998,(((((data["maxbatch_msignal"])+(((data["maxtominbatch_slices2_msignal"])* 2.0)))/2.0)) * 2.0), data["abs_avgbatch_msignal"])) +(data["maxtominbatch_slices2_msignal"])) /2.0)))))* 2.0)) / 2.0)))))) +
0.050000*np.tanh(((data["maxtominbatch"])-(np.cos(((( np.where(np.cos(( data["stdbatch_msignal"])) <= -998, data["minbatch_slices2"], np.where(np.cos(( data["maxtominbatch"])) > -998, data["signal_shift_+1"], data["signal_shift_-1"])))* 2.0)))))) +
0.050000*np.tanh(((((np.where(np.sin(( data["stdbatch_slices2_msignal"])) > -998, data["mean_abs_chgbatch_slices2_msignal"], data["signal"])) -(np.tanh(((( data["abs_avgbatch_msignal"])*(((data["abs_maxbatch_slices2"])*(np.sin(((( data["mean_abs_chgbatch_slices2_msignal"])-(np.cos(( data["maxbatch_slices2_msignal"])))))))))))))))*(np.sin(((( data["mean_abs_chgbatch_slices2_msignal"])-(np.minimum(((data["maxbatch_slices2_msignal"])) ,(( np.cos(( data["mean_abs_chgbatch_slices2_msignal"])))))))))))) +
0.050000*np.tanh(((((np.where(data["abs_avgbatch_slices2_msignal"] > -998, np.sin(( data["minbatch_msignal"])) ,(((( data["rangebatch_slices2_msignal"])*(data["medianbatch_msignal"])))-(data["maxbatch_slices2_msignal"])))) +(np.where(data["rangebatch_slices2"] > -998,(( data["rangebatch_slices2_msignal"])*(( -(( np.cos(((-(( data["abs_avgbatch_slices2_msignal"])))))))))) , data["signal_shift_-1"])))) -(data["maxbatch_slices2_msignal"])))+
0.050000*np.tanh(((data["abs_maxbatch_slices2_msignal"])*(np.sin(((-(( np.cos(( np.where(data["mean_abs_chgbatch_msignal"] > -998,(( data["signal_shift_-1"])-(np.where(data["signal_shift_-1"] <= -998, np.where(((( data["maxbatch_slices2"])<=(data["mean_abs_chgbatch_msignal"])) *1.) <= -998, data["mean_abs_chgbatch_msignal"], data["abs_minbatch_slices2_msignal"]), np.where(data["stdbatch_slices2_msignal"] <= -998, data["abs_minbatch_slices2_msignal"], data["abs_minbatch_slices2_msignal"])))) ,(( np.sin(((5.0)))) * 2.0)))))))))))) +
0.050000*np.tanh(((data["minbatch_msignal"])*(np.cos(((( np.minimum(((((((( np.minimum(((data["signal_shift_+1"])) ,(( data["meanbatch_slices2"])))) * 2.0)) >(data["signal_shift_-1"])) *1.))) ,(( np.minimum(((np.minimum(((data["signal_shift_-1"])) ,(( np.minimum(((data["signal_shift_+1"])) ,(( data["abs_minbatch_slices2"])))))))) ,(( data["abs_minbatch_slices2"])))))))* 2.0)))))) +
0.050000*np.tanh(( -(( np.where(np.minimum(((data["stdbatch_slices2_msignal"])) ,(( np.minimum(((data["mean_abs_chgbatch_msignal"])) ,(((((data["maxtominbatch_msignal"])+(np.sin(( data["maxtominbatch_slices2"])))) /2.0)))))))<= -998, data["mean_abs_chgbatch_msignal"], np.where(data["minbatch"] <= -998,(( data["abs_minbatch_slices2"])* 2.0),(( data["minbatch"])*(np.minimum(((data["mean_abs_chgbatch_msignal"])) ,(( np.sin(( data["stdbatch_slices2_msignal"])))))))))))))+
0.050000*np.tanh(((data["meanbatch_slices2"])+(((data["maxtominbatch_slices2_msignal"])+(( -(((( np.cos(((((9.0)) -(data["abs_avgbatch_slices2_msignal"])))))*(((((((data["maxtominbatch"])*(((np.minimum(((data["abs_minbatch_slices2_msignal"])) ,(((-(((( np.sin(( data["stdbatch_slices2_msignal"])))* 2.0)))))))) / 2.0)))) *(((data["mean_abs_chgbatch_msignal"])* 2.0)))) -(( 9.0)))))))))))))+
0.050000*np.tanh(((np.where(data["abs_avgbatch_msignal"] <= -998,(( data["abs_minbatch_slices2_msignal"])-(np.where(data["medianbatch_slices2_msignal"] > -998, data["minbatch"],(( data["abs_avgbatch_msignal"])/ 2.0)))) , np.cos(( np.maximum(((data["maxtominbatch_msignal"])) ,(((( data["abs_avgbatch_msignal"])-(np.where(data["medianbatch_slices2_msignal"] > -998, data["minbatch"], data["maxtominbatch"])))))))))) * 2.0)) +
0.050000*np.tanh(np.minimum(((data["abs_minbatch_slices2_msignal"])) ,(((( np.sin(((( data["stdbatch_slices2_msignal"])-(((((( data["signal_shift_+1"])* 2.0)) >(((( 2.0)) +(((np.where(( 4.0)> -998,(( np.sin(((((data["maxtominbatch_slices2_msignal"])>(data["stdbatch_msignal"])) *1.))))* 2.0), np.tanh(( data["stdbatch_slices2_msignal"])))) *(data["stdbatch_slices2_msignal"])))))) *1.))))))* 2.0)))))+
0.050000*np.tanh(np.minimum(((data["maxbatch_msignal"])) ,(( np.minimum(((data["stdbatch_slices2_msignal"])) ,(((( np.sin(( np.sin(( data["stdbatch_slices2_msignal"])))))*(data["stdbatch_slices2_msignal"])))))))))+
0.050000*np.tanh(np.where(np.sin(((( np.maximum(((data["abs_avgbatch_slices2_msignal"])) ,(( data["abs_avgbatch_slices2_msignal"])))) -(((np.tanh(( data["signal_shift_+1"])))/ 2.0)))))<= -998, data["mean_abs_chgbatch_slices2_msignal"], np.where(data["rangebatch_msignal"] <= -998,(( data["abs_minbatch_slices2_msignal"])-(data["abs_minbatch_msignal"])) , np.sin(((( data["signal_shift_+1"])-(data["abs_avgbatch_slices2_msignal"])))))))+
0.050000*np.tanh(np.sin(((( data["abs_avgbatch_slices2_msignal"])+(((data["minbatch_slices2_msignal"])-(((((np.maximum(((data["signal_shift_+1"])) ,(( np.sin(((( np.sin(((( data["minbatch_slices2_msignal"])+(data["minbatch_slices2_msignal"])))))+(data["minbatch_slices2_msignal"])))))))) *(((( data["medianbatch_slices2_msignal"])<=(np.where(data["abs_minbatch_slices2"] <= -998, data["medianbatch_slices2_msignal"],(( data["medianbatch_slices2"])* 2.0)))) *1.))))/ 2.0)))))))) +
0.050000*np.tanh(np.cos(((((( data["stdbatch_msignal"])-(data["signal_shift_-1_msignal"])))+(np.where(data["maxtominbatch_slices2_msignal"] <= -998, data["mean_abs_chgbatch_msignal"],(((( data["mean_abs_chgbatch_msignal"])* 2.0)) -(((( data["mean_abs_chgbatch_msignal"])<=(((np.tanh(((((((data["minbatch_msignal"])+(np.maximum(((data["maxtominbatch_msignal"])) ,(( np.sin(( np.sin(( data["signal_shift_-1_msignal"])))))))))/2.0)) / 2.0)))) / 2.0)))*1.))))))))) +
0.050000*np.tanh(np.sin(( np.maximum(((data["stdbatch_slices2_msignal"])) ,(( np.minimum(((( 1.0))),(( np.where(np.maximum(((data["stdbatch_slices2_msignal"])) ,(( data["mean_abs_chgbatch_msignal"])))> -998, data["maxtominbatch_msignal"], data["maxtominbatch"])))))))))) +
0.050000*np.tanh(((np.sin(((((3.79419302940368652)) *(data["mean_abs_chgbatch_msignal"])))))-(((( np.maximum(((((data["mean_abs_chgbatch_slices2_msignal"])/ 2.0))),(((( data["abs_minbatch_msignal"])* 2.0)))))<=(((( np.maximum(((data["signal_shift_-1"])) ,(((((((3.79419302940368652)) *(np.sin(( data["mean_abs_chgbatch_msignal"])))))* 2.0)))))<=(data["stdbatch_slices2"])) *1.))) *1.))))+
0.050000*np.tanh(np.where(((((((data["mean_abs_chgbatch_msignal"])*(np.maximum(((data["stdbatch_slices2_msignal"])) ,(( data["stdbatch_slices2_msignal"])))))) * 2.0)) / 2.0)<= -998, data["signal_shift_+1"],(((( np.sin(( data["stdbatch_slices2_msignal"])))* 2.0)) * 2.0)))+
0.050000*np.tanh(((((((data["stdbatch_slices2_msignal"])*(data["abs_minbatch_slices2_msignal"])))+(np.where(((np.where(data["stdbatch_slices2_msignal"] > -998, np.sin(((10.0))), np.sin(( np.sin(( data["stdbatch_msignal"])))))) +(((data["abs_minbatch_slices2_msignal"])*(np.sin(( data["abs_avgbatch_slices2_msignal"])))))) > -998, data["maxtominbatch_slices2_msignal"], data["abs_maxbatch_slices2"])))) *(np.sin(( data["stdbatch_slices2_msignal"])))))+
0.050000*np.tanh(((((np.maximum(((data["abs_avgbatch_slices2_msignal"])) ,(((((((data["abs_minbatch_msignal"])*(data["abs_avgbatch_slices2_msignal"])))+(data["maxtominbatch_slices2"])) /2.0)))))*(( -(( data["signal_shift_+1"])))))) +(((((( data["abs_maxbatch_slices2_msignal"])<=(((( -(((((( data["abs_minbatch_slices2"])-(data["mean_abs_chgbatch_slices2_msignal"])))/ 2.0)))))* 2.0)))*1.))-(data["abs_avgbatch_slices2"])))))+
0.050000*np.tanh(((((data["maxtominbatch"])-(np.where(((np.where(data["stdbatch_slices2_msignal"] > -998, data["signal_shift_-1"], data["abs_avgbatch_msignal"])) * 2.0)> -998, data["signal_shift_-1"], data["stdbatch_slices2_msignal"])))) * 2.0)) +
0.050000*np.tanh(((((np.sin(( np.cos(((( data["abs_maxbatch_slices2_msignal"])-(data["signal_shift_-1"])))))))*(((data["stdbatch_slices2_msignal"])*(((((np.sin(( np.cos(((( data["abs_maxbatch_slices2_msignal"])-(data["signal_shift_-1"])))))))+(data["stdbatch_msignal"])))*(data["rangebatch_slices2_msignal"])))))))+(np.sin(( np.cos(( np.maximum(((data["medianbatch_slices2"])) ,(( data["stdbatch_msignal"])))))))))) +
0.050000*np.tanh(((((np.sin(( np.maximum(((np.sin(( np.sin(( np.maximum(((data["stdbatch_slices2_msignal"])) ,(( data["signal_shift_+1"]))))))))),(( np.maximum(((data["stdbatch_slices2_msignal"])) ,(( np.where(((np.where(np.sin(( np.maximum(((data["stdbatch_slices2_msignal"])) ,(( np.maximum(((data["abs_avgbatch_slices2"])) ,(( data["abs_avgbatch_slices2"])))))))) <= -998, data["minbatch"], data["abs_minbatch_slices2"])) * 2.0)<= -998, data["meanbatch_slices2"], data["abs_minbatch_slices2_msignal"])))))))))) * 2.0)) * 2.0)) +
0.050000*np.tanh(((((( np.where(data["maxbatch_msignal"] <= -998, data["stdbatch_slices2"],(((-(( data["mean_abs_chgbatch_slices2"])))) * 2.0)))+(np.minimum(((data["abs_minbatch_slices2_msignal"])) ,(((( data["signal_shift_+1"])*(((np.cos(( data["abs_minbatch_slices2_msignal"])))-(data["mean_abs_chgbatch_slices2"])))))))))/2.0)) *(((data["signal_shift_-1_msignal"])*(data["rangebatch_slices2"])))))+
0.050000*np.tanh(((np.sin(( np.where(np.sin(( np.maximum(((np.sin(( np.maximum(((data["abs_avgbatch_slices2"])) ,(((((np.where(data["maxtominbatch"] <= -998, data["minbatch_slices2"], data["abs_maxbatch_slices2_msignal"])) >(data["abs_maxbatch_slices2_msignal"])) *1.)))))))),(( data["stdbatch_msignal"])))))> -998, data["stdbatch_slices2_msignal"], np.where(data["stdbatch_slices2_msignal"] > -998, data["stdbatch_slices2_msignal"], np.where(data["mean_abs_chgbatch_slices2"] <= -998, data["maxtominbatch_slices2_msignal"], data["maxtominbatch_slices2_msignal"])))))) * 2.0)) +
0.050000*np.tanh(np.where(data["maxtominbatch_msignal"] > -998, np.sin(( np.where(data["mean_abs_chgbatch_slices2_msignal"] > -998, data["mean_abs_chgbatch_slices2_msignal"], data["rangebatch_slices2"]))), data["signal_shift_+1"])) +
0.050000*np.tanh(((((np.cos(((( np.where(((data["abs_maxbatch_slices2_msignal"])* 2.0)<= -998, np.where(((( 7.0)) +(np.cos(( data["meanbatch_slices2"])))) > -998, data["abs_maxbatch_msignal"], np.where(data["mean_abs_chgbatch_msignal"] <= -998, data["maxtominbatch_msignal"], data["maxtominbatch_msignal"])) , data["maxtominbatch_msignal"])) +(data["abs_maxbatch_slices2_msignal"])))))* 2.0)) * 2.0)) +
0.050000*np.tanh(((( 8.0)) *(np.where(np.tanh(((((data["maxtominbatch_msignal"])+(( -(( data["stdbatch_slices2_msignal"])))))/2.0)))<= -998,(( data["stdbatch_slices2"])+(((data["abs_maxbatch_msignal"])+(np.sin(( data["abs_avgbatch_slices2"])))))) , np.where(data["rangebatch_slices2_msignal"] <= -998, data["minbatch_slices2"], np.tanh(( np.sin(( data["stdbatch_slices2_msignal"])))))))))+
0.050000*np.tanh(((((np.cos(((( np.where(np.tanh(( data["stdbatch_slices2_msignal"])) > -998,(( data["medianbatch_slices2"])* 2.0), data["medianbatch_slices2"])) +(((np.cos(( np.maximum(((data["mean_abs_chgbatch_msignal"])) ,(((((data["maxtominbatch_slices2_msignal"])>(((data["rangebatch_slices2"])* 2.0)))*1.))))))) +(data["stdbatch_slices2_msignal"])))))))* 2.0)) * 2.0)) +
0.050000*np.tanh(((( data["maxtominbatch_msignal"])+(np.sin(( np.where(data["abs_maxbatch_msignal"] <= -998, np.cos(((-(( data["rangebatch_slices2"]))))), data["minbatch_slices2"])))))/2.0)) +
0.050000*np.tanh(( -(((((( data["abs_avgbatch_msignal"])-(((( data["abs_minbatch_slices2"])+(np.cos(((( data["signal"])*(data["signal_shift_+1"])))))) /2.0)))) *(np.cos(((( data["signal"])*(data["signal_shift_+1"])))))))))) +
0.050000*np.tanh(np.where(data["signal_shift_+1_msignal"] <= -998, data["maxbatch_msignal"], np.where(data["mean_abs_chgbatch_slices2"] <= -998, data["mean_abs_chgbatch_slices2"], np.sin(( data["stdbatch_msignal"])))))+
0.050000*np.tanh(((( -(((((( data["rangebatch_slices2"])*(((np.cos(( np.where(((data["medianbatch_slices2"])* 2.0)<= -998, np.tanh(((( data["signal_shift_+1_msignal"])/ 2.0))),(( data["medianbatch_slices2"])+(data["medianbatch_slices2"])))))) / 2.0)))) / 2.0)))))* 2.0)) +
0.050000*np.tanh(((np.minimum(((np.minimum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(( np.where(data["medianbatch_slices2_msignal"] <= -998,(( data["abs_avgbatch_msignal"])*(data["maxtominbatch_slices2_msignal"])) , data["mean_abs_chgbatch_slices2_msignal"])))))) ,(( np.where(((( np.sin(((( data["meanbatch_slices2_msignal"])+(data["meanbatch_msignal"])))))+(data["maxtominbatch_slices2_msignal"])) /2.0)<= -998, data["maxtominbatch_slices2_msignal"], np.sin(((( data["maxtominbatch_slices2_msignal"])+(data["meanbatch_msignal"])))))))))* 2.0)) +
0.050000*np.tanh(((np.cos(((( np.where(data["meanbatch_msignal"] <= -998,(( np.where(data["signal_shift_-1"] > -998, data["minbatch_slices2"], np.cos(((-(( data["rangebatch_slices2"])))))))*(((data["abs_maxbatch"])-(np.where(( 6.0)<= -998, data["minbatch_slices2_msignal"], np.tanh(( data["abs_maxbatch"]))))))), data["maxbatch_msignal"])) * 2.0)))) * 2.0)) +
0.050000*np.tanh(((np.sin(((( data["stdbatch_slices2_msignal"])+(np.sin(( data["minbatch_slices2"])))))))*(((((data["stdbatch_slices2_msignal"])+(np.maximum(((data["medianbatch_slices2"])) ,(((2.0)))))))*(np.where(data["minbatch_slices2"] > -998,(( data["stdbatch_slices2_msignal"])+(np.sin(( data["minbatch_slices2"])))) , data["stdbatch_slices2_msignal"])))))) +
0.050000*np.tanh(np.sin(( np.where(np.where(data["rangebatch_msignal"] > -998, data["stdbatch_slices2_msignal"], np.minimum(((data["maxtominbatch_msignal"])) ,(((-(( data["meanbatch_msignal"])))))))> -998, data["stdbatch_slices2_msignal"],(11.81794071197509766)))))+
0.050000*np.tanh(((np.sin(( np.minimum(((np.minimum(((( -(( data["maxbatch_slices2"]))))),(((( data["minbatch_msignal"])* 2.0)))))) ,(( np.where(np.where(data["rangebatch_msignal"] > -998, data["maxbatch_msignal"], np.sin(( np.minimum(((( -(( data["maxbatch_slices2"]))))),(( data["minbatch_msignal"])))))) > -998,(( data["signal_shift_+1_msignal"])* 2.0), data["meanbatch_slices2_msignal"])))))))* 2.0)) +
0.050000*np.tanh(np.minimum(((((((np.sin(( np.tanh(((( np.sin(((( data["abs_avgbatch_msignal"])* 2.0)))) * 2.0)))))) * 2.0)) * 2.0))),(((( np.sin(( data["stdbatch_msignal"])))+(np.sin(((-(( data["maxbatch_slices2"])))))))))))+
0.050000*np.tanh(((data["signal_shift_+1"])*(( -(((((np.sin(((((data["rangebatch_slices2"])>(data["signal_shift_+1"])) *1.))))<=(((((( np.where(data["signal_shift_+1"] > -998, data["rangebatch_msignal"], data["stdbatch_msignal"])) * 2.0)) +(((np.cos(((((data["maxtominbatch"])<=(data["maxtominbatch"])) *1.))))/ 2.0)))/2.0)))*1.))))))) +
0.050000*np.tanh(((np.cos(((((((( np.minimum(((np.cos(( data["signal_shift_-1"])))) ,(( np.cos(((((((( np.sin(((( np.cos(((9.0)))) * 2.0)))) * 2.0)) * 2.0)) *(np.cos(( data["signal_shift_-1"])))))))))) * 2.0)) * 2.0)) *(np.cos(( data["signal_shift_-1"])))))))* 2.0)) +
0.050000*np.tanh(np.minimum(((data["abs_minbatch_msignal"])) ,(((((4.0)) *(np.sin(( data["stdbatch_msignal"])))))))) +
0.050000*np.tanh(np.sin(((( data["signal_shift_+1"])-(np.where(data["signal_shift_+1"] > -998, np.where(data["signal_shift_+1"] > -998, data["abs_avgbatch_msignal"], data["signal_shift_+1"]), np.cos(((( data["abs_avgbatch_msignal"])+(np.sin(((( data["abs_minbatch_slices2"])-(data["abs_avgbatch_msignal"])))))))))))))) +
0.050000*np.tanh(np.maximum(((np.cos(( np.maximum(((data["meanbatch_slices2"])) ,(( np.cos(((( data["medianbatch_slices2"])*(np.cos(((( data["medianbatch_slices2"])*(np.cos(( data["medianbatch_slices2"]))))))))))))))))),(( data["stdbatch_msignal"])))) +
0.050000*np.tanh(np.sin(( np.maximum(((np.maximum(((np.where(data["rangebatch_slices2"] <= -998, np.minimum(((data["maxtominbatch_slices2"])) ,(( data["stdbatch_slices2_msignal"]))), data["abs_minbatch_msignal"]))),(((( data["rangebatch_slices2"])/ 2.0)))))) ,(( data["stdbatch_slices2_msignal"])))))) +
0.050000*np.tanh(( -(( np.where(data["maxbatch_slices2_msignal"] <= -998,(( data["meanbatch_msignal"])+(np.sin(( np.sin(((( np.sin(((-(((( np.sin(( data["signal_shift_+1"])))* 2.0)))))))+(data["meanbatch_msignal"])))))))) , data["signal_shift_+1"])))))+
0.050000*np.tanh(((((data["abs_avgbatch_slices2_msignal"])-(( -(( np.cos(((( data["signal"])-(( -(((-(( np.cos(( data["abs_avgbatch_msignal"])))))))))))))))))) *(( -(( np.cos(( data["abs_avgbatch_slices2_msignal"])))))))) +
0.050000*np.tanh(((data["abs_avgbatch_msignal"])+(np.minimum(((data["minbatch_slices2_msignal"])) ,(((((((( data["maxbatch_slices2"])*(np.where(np.sin(((( data["maxbatch_slices2"])*(np.where(((data["abs_avgbatch_msignal"])/ 2.0)> -998, data["abs_avgbatch_slices2"], data["maxbatch_slices2"])))))> -998, data["minbatch_slices2"], np.sin(( data["abs_avgbatch_slices2"])))))) / 2.0)) / 2.0)))))))+
0.050000*np.tanh(((np.cos(( data["medianbatch_slices2"])))+(data["maxbatch_slices2_msignal"])))+
0.050000*np.tanh(((((((data["abs_minbatch_msignal"])*(((((data["abs_minbatch_msignal"])*(((data["medianbatch_msignal"])*(np.sin(( data["stdbatch_slices2_msignal"])))))))*(data["abs_minbatch_msignal"])))))* 2.0)) * 2.0)) +
0.050000*np.tanh(np.sin(((( data["minbatch_msignal"])+(np.maximum(((data["abs_avgbatch_slices2_msignal"])) ,(( np.maximum(((( -(( data["abs_avgbatch_slices2_msignal"]))))),(((( data["signal"])+(((data["signal_shift_+1_msignal"])-(np.maximum(((data["abs_avgbatch_slices2_msignal"])) ,(( data["signal"])))))))))))))))))) +
0.050000*np.tanh(np.minimum(((((np.sin(( data["stdbatch_slices2_msignal"])))*(( 9.0))))),(((((( np.where(data["abs_maxbatch_slices2_msignal"] <= -998, data["meanbatch_slices2_msignal"], data["signal_shift_+1"])) *(data["mean_abs_chgbatch_slices2_msignal"])))+(np.maximum(((np.where(data["meanbatch_slices2_msignal"] <= -998, np.tanh(( data["abs_maxbatch_msignal"])) , data["abs_maxbatch_slices2_msignal"]))),(( np.maximum(((data["abs_maxbatch_slices2_msignal"])) ,(((((data["signal_shift_+1"])+(data["maxtominbatch_slices2_msignal"])) /2.0)))))))))))))+
0.050000*np.tanh(np.minimum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(( np.cos(((( data["signal_shift_+1"])+(np.cos(((((((((((( -(((4.55383777618408203)))))<=(data["signal_shift_+1"])) *1.))+(( 4.55383777618408203)))/2.0)) <=(data["signal_shift_+1"])) *1.))))))))))) +
0.050000*np.tanh(( -(( np.cos(((((((-(( data["signal_shift_+1"])))) * 2.0)) +(((( data["maxtominbatch"])>(((( np.cos(((( data["signal_shift_+1_msignal"])+(((( data["maxtominbatch"])>(np.cos(((((-(( data["signal_shift_+1"])))) * 2.0)))))*1.))))))+(np.sin(((((((-(( np.cos(((3.0)))))))/ 2.0)) * 2.0)))))/2.0)))*1.))))))))) +
0.050000*np.tanh(((np.where(data["signal"] > -998, np.where(((data["signal"])* 2.0)> -998, data["minbatch_slices2"], np.minimum(((data["stdbatch_slices2"])) ,(( data["maxbatch_slices2"])))) , np.where(((data["minbatch_msignal"])* 2.0)> -998, data["meanbatch_slices2_msignal"],(( data["signal"])* 2.0)))) *(np.cos(((( data["signal"])* 2.0)))))) +
0.050000*np.tanh(np.cos(((( data["signal_shift_-1"])-(data["abs_maxbatch_slices2_msignal"])))))+
0.050000*np.tanh(np.maximum(((data["abs_maxbatch_msignal"])) ,(( np.maximum(((np.tanh(((( data["mean_abs_chgbatch_slices2_msignal"])* 2.0))))),(( data["meanbatch_msignal"])))))))+
0.050000*np.tanh(((((data["abs_avgbatch_slices2"])*(((np.sin(( data["abs_avgbatch_slices2"])))*(((( data["maxbatch_slices2"])+(((np.sin(( data["abs_avgbatch_slices2"])))*(((( data["signal_shift_-1_msignal"])+(data["abs_avgbatch_slices2"])) /2.0)))))/2.0)))))) *(( 6.0)))) +
0.050000*np.tanh(np.cos(((((( np.cos(( np.where(((( np.cos(( data["signal_shift_-1"])))>(np.cos(((( data["maxbatch_msignal"])*(((np.cos(((( data["signal_shift_-1"])* 2.0)))) * 2.0)))))))*1.) <= -998, data["meanbatch_msignal"], data["signal_shift_-1"])))) * 2.0)) * 2.0)))) +
0.050000*np.tanh(((np.sin(((-(( np.sin(( np.sin(( data["abs_maxbatch"])))))))))) +(np.sin(( np.cos(((( data["maxtominbatch_msignal"])+(np.maximum(((data["abs_maxbatch_slices2_msignal"])) ,(((-(( np.sin(( np.tanh(( data["mean_abs_chgbatch_slices2_msignal"])))))))))))))))))))+
0.050000*np.tanh(np.where(data["signal_shift_-1"] <= -998,(((( -(((( data["maxtominbatch_slices2_msignal"])/ 2.0)))))+(((((((((((((data["minbatch_msignal"])/ 2.0)) / 2.0)) >(data["maxbatch_msignal"])) *1.))/ 2.0)) +(np.sin(( data["stdbatch_slices2"])))) /2.0)))/2.0),(-(( data["signal_shift_-1"])))))+
0.050000*np.tanh(((np.where(((((data["abs_avgbatch_slices2_msignal"])* 2.0)) +(np.where(data["rangebatch_slices2"] > -998, np.tanh(( data["minbatch"])) , np.tanh(((( data["abs_avgbatch_slices2_msignal"])-(data["abs_avgbatch_slices2_msignal"])))))))> -998, data["abs_maxbatch"],(((( data["abs_avgbatch_slices2_msignal"])-(data["minbatch"])))/ 2.0)))*(np.cos(((( data["abs_avgbatch_slices2_msignal"])-(data["minbatch"])))))))+
0.050000*np.tanh(np.sin(( np.maximum(((data["stdbatch_slices2_msignal"])) ,(( np.where(((( data["maxbatch_slices2_msignal"])+(data["maxbatch_slices2_msignal"])) /2.0)<= -998,(( data["medianbatch_msignal"])-(( -(((( data["maxtominbatch"])* 2.0)))))) ,(-(( np.cos(( data["minbatch_slices2"])))))))))))) +
0.050000*np.tanh(np.cos(((( np.cos(((((data["signal_shift_+1_msignal"])+(data["meanbatch_msignal"])) /2.0)))) *(np.maximum(((data["meanbatch_slices2"])) ,(( data["meanbatch_slices2"])))))))) +
0.050000*np.tanh(np.sin(( np.where(data["signal_shift_+1_msignal"] <= -998, np.cos(( np.sin(((( np.where(data["signal_shift_+1_msignal"] <= -998, data["mean_abs_chgbatch_slices2_msignal"], data["minbatch"])) * 2.0))))),(((data["medianbatch_slices2_msignal"])>(((data["signal_shift_-1"])* 2.0)))*1.))))) +
0.050000*np.tanh(((np.where(((( np.where(np.where(data["mean_abs_chgbatch_msignal"] > -998,(10.0), data["rangebatch_msignal"])> -998,(10.0),(( np.sin(((((data["abs_avgbatch_msignal"])+(data["mean_abs_chgbatch_msignal"])) /2.0)))) * 2.0)))+(( 2.0)))/2.0)> -998,(10.0), data["abs_avgbatch_msignal"])) *(np.sin(((((data["abs_avgbatch_msignal"])+(data["mean_abs_chgbatch_msignal"])) /2.0)))))) +
0.050000*np.tanh(((np.sin(( np.maximum(((np.maximum(((data["abs_avgbatch_slices2"])) ,(( data["stdbatch_msignal"]))))),(( data["signal_shift_-1"])))))) * 2.0)) +
0.050000*np.tanh(((data["signal_shift_+1_msignal"])*(((np.where(np.tanh(( data["mean_abs_chgbatch_msignal"])) <= -998,(( data["abs_avgbatch_slices2_msignal"])-(( -(( data["mean_abs_chgbatch_msignal"]))))),(((((((((( data["maxbatch_slices2"])* 2.0)) *(data["minbatch_slices2_msignal"])))+(data["mean_abs_chgbatch_msignal"])) /2.0)) +(((data["minbatch_slices2_msignal"])-(( -(((((data["mean_abs_chgbatch_msignal"])<=(data["maxtominbatch_slices2_msignal"])) *1.))))))))/2.0)))* 2.0)))) +
0.050000*np.tanh(((data["maxtominbatch_msignal"])*(data["medianbatch_slices2_msignal"])))+
0.050000*np.tanh(((np.tanh(( data["medianbatch_msignal"])))*(np.where(((((( data["abs_maxbatch_msignal"])+(data["signal_shift_+1"])) /2.0)) +(np.sin(( data["rangebatch_slices2_msignal"])))) <= -998, data["maxtominbatch_msignal"], np.where(data["abs_avgbatch_slices2"] <= -998, data["signal"],(( np.tanh(( data["maxtominbatch_msignal"])))+(data["maxtominbatch_msignal"])))))))+
0.050000*np.tanh(np.sin(( np.cos(((((((data["minbatch"])<=(np.where(data["abs_avgbatch_slices2"] <= -998,(( np.sin(((((( np.cos(( np.cos(( np.sin(( data["abs_avgbatch_slices2"])))))))/ 2.0)) / 2.0)))) / 2.0),(( np.cos(( data["abs_avgbatch_slices2"])))/ 2.0)))) *1.))/ 2.0)))))) +
0.050000*np.tanh(((((((9.67606735229492188)) +(((( data["minbatch_slices2"])<=(data["abs_maxbatch_slices2"])) *1.))) /2.0)) -(((data["abs_maxbatch_slices2_msignal"])-(np.cos(((((data["abs_avgbatch_slices2"])<=(data["abs_maxbatch_slices2_msignal"])) *1.))))))))+
0.050000*np.tanh(((( data["signal"])<=(((( data["rangebatch_slices2_msignal"])+(data["abs_maxbatch"])) /2.0)))*1.))+
0.050000*np.tanh(np.cos(((( data["minbatch_slices2_msignal"])+(((( np.where(data["stdbatch_slices2"] > -998,(( data["meanbatch_slices2"])-(((( data["mean_abs_chgbatch_slices2"])>(((np.tanh(( data["maxbatch_slices2_msignal"])))*(data["meanbatch_msignal"])))) *1.))) , np.where(data["rangebatch_slices2"] > -998, data["signal_shift_+1_msignal"], data["meanbatch_msignal"])))<=(data["meanbatch_slices2"])) *1.))))))+
0.050000*np.tanh(np.maximum(((( -(((( np.where(((data["rangebatch_msignal"])+(((np.tanh(( data["abs_minbatch_msignal"])))+(np.sin(( data["stdbatch_slices2_msignal"])))))) > -998, data["meanbatch_slices2"], data["rangebatch_msignal"])) +(np.sin(( data["maxbatch_slices2"]))))))))),(( np.sin(( data["stdbatch_slices2_msignal"])))))) +
0.050000*np.tanh(np.cos(((( data["abs_maxbatch"])-(((data["abs_avgbatch_msignal"])*(((( data["mean_abs_chgbatch_msignal"])+(((((-(( data["minbatch_msignal"])))) <=(((( data["signal_shift_-1"])>(( -(( data["abs_maxbatch"])))))*1.))) *1.))) /2.0)))))))) +
0.050000*np.tanh(np.sin(( np.sin(((( data["signal_shift_-1"])-(np.minimum(((data["abs_avgbatch_slices2_msignal"])) ,(( np.where(np.where(((data["signal"])-(data["rangebatch_slices2_msignal"])) <= -998, data["abs_maxbatch_slices2_msignal"],(( data["signal"])-(np.sin(( data["signal"])))))<= -998, data["rangebatch_slices2_msignal"], data["abs_maxbatch_slices2"])))))))))))+
0.050000*np.tanh(((((data["abs_avgbatch_slices2"])*(np.where(( 1.0)> -998, data["medianbatch_slices2_msignal"],(( np.sin(( data["abs_maxbatch_msignal"])))*(( 1.0)))))))*(np.sin(( np.sin(( data["stdbatch_slices2_msignal"])))))))+
0.050000*np.tanh(((data["medianbatch_slices2_msignal"])*(((((((data["medianbatch_slices2_msignal"])+(( -(( data["signal_shift_+1"])))))/2.0)) +(np.where(data["medianbatch_slices2_msignal"] <= -998, data["mean_abs_chgbatch_slices2"], data["maxtominbatch_slices2_msignal"])))/2.0)))) +
0.050000*np.tanh(np.maximum(((np.sin(( data["maxbatch_slices2"])))) ,(( np.maximum(((np.where(data["maxbatch_msignal"] <= -998, data["rangebatch_slices2_msignal"],(((( 9.07463359832763672)) >(data["abs_maxbatch"])) *1.)))),(( data["abs_maxbatch_msignal"])))))))+
0.050000*np.tanh(((((np.sin(( np.sin(( np.where(np.where(np.sin(( np.where(data["abs_minbatch_slices2"] > -998, data["abs_avgbatch_slices2"], data["abs_avgbatch_slices2"])))> -998, data["abs_avgbatch_slices2"], data["abs_avgbatch_slices2"])> -998, data["abs_avgbatch_slices2"], data["abs_avgbatch_slices2"])))))) * 2.0)) * 2.0)) +
0.050000*np.tanh(np.sin(((((((( data["minbatch_slices2_msignal"])-(((( data["mean_abs_chgbatch_msignal"])>(np.sin(((((( np.sin(( data["medianbatch_msignal"])))/ 2.0)) * 2.0)))))*1.))))* 2.0)) * 2.0)))) +
0.050000*np.tanh(np.maximum(((data["stdbatch_slices2"])) ,(((((np.where(((((( data["mean_abs_chgbatch_slices2"])+(np.cos(( np.cos(((((((data["rangebatch_slices2"])* 2.0)) +(np.cos(( data["abs_maxbatch"])))) /2.0)))))))/2.0)) *(data["abs_maxbatch_slices2"])) > -998, data["rangebatch_msignal"], np.cos(( data["rangebatch_msignal"])))) +(data["stdbatch_slices2"])) /2.0)))))+
0.050000*np.tanh(((((( data["signal_shift_+1"])<=(np.sin(( np.maximum(((np.sin(((3.0))))),(((4.44015836715698242)))))))) *1.))* 2.0)) +
0.050000*np.tanh(np.where(np.sin(( data["minbatch_msignal"])) <= -998,(( data["maxbatch_msignal"])* 2.0), np.sin(((((( np.cos(( np.cos(((( np.cos(( np.minimum(((((data["mean_abs_chgbatch_msignal"])/ 2.0))),(( data["abs_minbatch_msignal"])))))) +(data["abs_minbatch_slices2_msignal"])))))))+(data["abs_minbatch_slices2_msignal"])))-(data["maxbatch_msignal"])))))) +
0.050000*np.tanh(data["rangebatch_slices2"])+
0.050000*np.tanh(((((np.cos(((( data["minbatch_slices2"])-(data["abs_avgbatch_msignal"])))))*(np.where(np.sin(((((((data["minbatch_slices2"])-(data["maxtominbatch_slices2_msignal"])))+(np.cos(((((( data["minbatch_slices2"])-(data["abs_avgbatch_msignal"])))-(((data["abs_avgbatch_slices2"])-(data["abs_avgbatch_msignal"])))))))) /2.0)))> -998, data["abs_avgbatch_msignal"], data["minbatch_slices2"])))) * 2.0)) +
0.050000*np.tanh(((( 4.0)) *(np.sin(( np.where(((np.sin(((( np.sin(( data["abs_avgbatch_slices2"])))+(( -(((( data["signal_shift_+1"])/ 2.0)))))))))+(( -(((( data["signal_shift_+1"])/ 2.0)))))) <= -998,(( data["abs_avgbatch_msignal"])+(data["mean_abs_chgbatch_slices2"])) ,(( data["minbatch_slices2_msignal"])+(data["abs_avgbatch_msignal"])))))))) +
0.050000*np.tanh(((((np.cos(( data["stdbatch_msignal"])))*(((np.cos(( data["meanbatch_slices2"])))-(( -(( data["stdbatch_msignal"])))))))) -(data["meanbatch_slices2"])))+
0.050000*np.tanh(np.where(data["maxbatch_slices2_msignal"] > -998, np.maximum(((((np.maximum(((data["abs_minbatch_slices2_msignal"])) ,(( np.where(np.tanh(((( data["abs_maxbatch_slices2_msignal"])-(((data["mean_abs_chgbatch_slices2_msignal"])/ 2.0)))))<= -998, data["maxbatch_slices2"], data["abs_maxbatch"])))))* 2.0))),(( np.tanh(((( data["abs_maxbatch"])/ 2.0)))))) , np.where(data["abs_minbatch_msignal"] > -998, data["abs_avgbatch_slices2"], data["maxbatch_msignal"])))+
0.050000*np.tanh(((np.minimum(((np.minimum(((data["abs_avgbatch_slices2"])) ,(((( np.sin(( data["abs_avgbatch_slices2"])))* 2.0)))))) ,(( data["abs_avgbatch_slices2"])))) * 2.0)) +
0.050000*np.tanh(( -(( np.sin(( data["maxbatch_slices2"])))))) +
0.050000*np.tanh(((( 6.0)) -(np.maximum(((data["abs_maxbatch_slices2"])) ,(( np.maximum(((np.maximum(((np.tanh(((( data["signal_shift_+1"])* 2.0))))),(( np.maximum(((data["abs_avgbatch_slices2"])) ,(( data["abs_maxbatch_slices2"])))))))) ,(( data["abs_maxbatch_slices2"])))))))))+
0.050000*np.tanh(((data["signal_shift_-1"])+(np.maximum(((data["rangebatch_slices2"])) ,(( np.where(((np.cos(( np.where(np.cos(( data["stdbatch_slices2_msignal"])) > -998, data["signal"], np.maximum(((data["maxbatch_slices2_msignal"])) ,(((((((( 3.20188593864440918)) +(data["meanbatch_msignal"])))<=(data["abs_minbatch_slices2"])) *1.))))))))/ 2.0)<= -998,(( data["rangebatch_slices2"])* 2.0), data["mean_abs_chgbatch_slices2_msignal"])))))))+
0.050000*np.tanh(((np.where(((((np.where(data["signal_shift_-1_msignal"] > -998,(( data["minbatch_msignal"])+(data["stdbatch_slices2_msignal"])) , data["signal_shift_-1_msignal"])) *(((data["minbatch_msignal"])+(data["stdbatch_slices2_msignal"])))))* 2.0)> -998,(( data["signal_shift_-1_msignal"])* 2.0),(((( data["mean_abs_chgbatch_msignal"])*(data["abs_avgbatch_slices2_msignal"])))* 2.0)))*(((data["minbatch_msignal"])+(data["stdbatch_slices2_msignal"])))))+
0.050000*np.tanh(np.cos(( np.where(((np.cos(( data["signal_shift_-1"])))/ 2.0)> -998,(((( np.cos(( data["abs_minbatch_msignal"])))* 2.0)) +(((np.tanh(((( data["signal_shift_+1_msignal"])*(data["rangebatch_slices2_msignal"])))))/ 2.0))),(( np.sin(((11.49898338317871094)))) / 2.0)))))+
0.050000*np.tanh(np.where(data["abs_maxbatch_slices2_msignal"] > -998,(((data["meanbatch_slices2_msignal"])<=(data["abs_avgbatch_msignal"])) *1.) ,(( data["medianbatch_slices2_msignal"])-(np.cos(((( data["medianbatch_slices2_msignal"])-(data["minbatch_slices2_msignal"])))))))))
 def GP_class_2(self,data):
return self.Output(-2.199090 +
0.050000*np.tanh(np.minimum(((data["stdbatch_msignal"])) ,(( np.where(np.minimum(((np.where(((np.where(data["maxbatch_slices2"] <= -998, data["stdbatch_msignal"],(( data["stdbatch_msignal"])* 2.0)))-(data["abs_minbatch_msignal"])) <= -998, np.minimum(((np.cos(( data["meanbatch_slices2"])))) ,(( np.cos(( data["meanbatch_slices2"]))))), np.cos(( data["maxbatch_slices2"]))))),(( data["abs_minbatch_msignal"])))<= -998, data["abs_avgbatch_msignal"],(( data["maxbatch_slices2"])-(data["abs_minbatch_msignal"])))))))+
0.050000*np.tanh(np.where(((data["signal_shift_+1"])-(data["minbatch_msignal"])) <= -998,(((((( np.minimum(((data["stdbatch_msignal"])) ,(( data["maxbatch_slices2"])))) * 2.0)) *(np.cos(( data["abs_avgbatch_slices2"])))))* 2.0),(( np.minimum(((data["stdbatch_msignal"])) ,(( data["maxbatch_slices2"])))) * 2.0)))+
0.050000*np.tanh(((data["maxbatch_slices2"])*(((data["abs_maxbatch_slices2_msignal"])*(np.where(data["mean_abs_chgbatch_msignal"] > -998, data["mean_abs_chgbatch_msignal"], data["mean_abs_chgbatch_msignal"])))))) +
0.050000*np.tanh(((np.minimum(((data["mean_abs_chgbatch_msignal"])) ,(((( np.minimum(((data["mean_abs_chgbatch_msignal"])) ,(((( np.minimum(((data["mean_abs_chgbatch_msignal"])) ,(( np.tanh(((((((((data["meanbatch_slices2"])+(np.where(data["maxtominbatch_slices2_msignal"] <= -998, data["minbatch"],(9.20059394836425781)))))>(data["stdbatch_slices2_msignal"])) *1.))-(data["maxtominbatch_slices2_msignal"])))))))) -(data["maxtominbatch_slices2_msignal"])))))) -(data["maxtominbatch_slices2_msignal"])))))) * 2.0)) +
0.050000*np.tanh(((data["mean_abs_chgbatch_msignal"])*(((((data["maxbatch_slices2"])+(data["maxbatch_slices2"])))* 2.0)))) +
0.050000*np.tanh(((data["maxbatch_slices2"])*(((( data["abs_minbatch_slices2_msignal"])+(((( data["abs_minbatch_slices2_msignal"])+(((data["abs_maxbatch_slices2_msignal"])*(data["stdbatch_slices2_msignal"])))) /2.0)))/2.0)))) +
0.050000*np.tanh(((((data["minbatch"])*(((data["mean_abs_chgbatch_slices2_msignal"])*(np.where(np.where(data["medianbatch_msignal"] <= -998, data["meanbatch_msignal"], data["maxbatch_slices2"])> -998, data["maxtominbatch_slices2_msignal"], np.where(data["signal_shift_+1"] > -998, data["maxtominbatch_slices2_msignal"], data["stdbatch_msignal"])))))))+(data["maxbatch_slices2"])))+
0.050000*np.tanh(((((np.sin(( np.sin(( np.where(data["stdbatch_slices2_msignal"] > -998, data["abs_avgbatch_msignal"], np.cos(((10.52720451354980469)))))))))*(( 10.52720451354980469)))) *(((((((( 10.52720451354980469)) +(((np.sin(( np.cos(((10.52720451354980469)))))) *(((((10.52720451354980469)) +(np.sin(((10.52720451354980469)))))/2.0)))))/2.0)) +(data["abs_avgbatch_msignal"])) /2.0)))) +
0.050000*np.tanh(np.minimum(((((np.minimum(((((data["abs_avgbatch_slices2_msignal"])*(data["abs_avgbatch_slices2_msignal"])))) ,(((((( data["mean_abs_chgbatch_msignal"])*(data["meanbatch_slices2"])))+(np.tanh(( data["maxbatch_slices2"])))))))) * 2.0))),(((( data["stdbatch_slices2_msignal"])* 2.0)))))+
0.050000*np.tanh(np.minimum(((((( data["abs_maxbatch_msignal"])+(data["stdbatch_slices2"])) /2.0))),(((( np.where(np.cos(( data["maxbatch_slices2"])) > -998, data["maxbatch_slices2"],(( np.tanh(( data["minbatch_msignal"])))*(data["maxbatch_slices2"])))) *(data["mean_abs_chgbatch_msignal"])))))) +
0.050000*np.tanh(((((data["maxbatch_slices2"])* 2.0)) *(np.where(data["maxbatch_slices2"] <= -998, np.cos(( np.where(data["stdbatch_slices2_msignal"] <= -998, np.tanh(( data["rangebatch_slices2"])) , data["stdbatch_slices2_msignal"]))), data["mean_abs_chgbatch_msignal"])))) +
0.050000*np.tanh(((data["stdbatch_msignal"])*(np.where(data["rangebatch_slices2"] > -998, data["maxbatch_slices2"],(((( data["meanbatch_slices2_msignal"])*(np.cos(( data["maxbatch_slices2"])))))/ 2.0)))))+
0.050000*np.tanh(((( 2.0)) *(np.cos(( np.where(np.where(((( data["rangebatch_msignal"])<=(((( data["rangebatch_msignal"])<=(np.maximum(((data["abs_minbatch_msignal"])) ,(( np.where(( 11.72177124023437500)> -998, data["signal"],(-(( data["rangebatch_msignal"])))))))))*1.))) *1.) > -998, data["abs_minbatch_msignal"],(((np.cos(( data["maxbatch_slices2"])))+(data["medianbatch_slices2_msignal"])) /2.0)) > -998, data["abs_minbatch_msignal"], data["stdbatch_msignal"])))))) +
0.050000*np.tanh(np.minimum(((((data["maxbatch_slices2"])* 2.0))),(((( data["abs_avgbatch_slices2_msignal"])+(((((data["stdbatch_slices2_msignal"])+(((((( data["stdbatch_slices2_msignal"])*(np.minimum(((data["stdbatch_slices2_msignal"])) ,(( data["mean_abs_chgbatch_msignal"])))))) +(data["abs_minbatch_slices2_msignal"])) /2.0)))) +(((np.minimum(((((((data["abs_minbatch_msignal"])* 2.0)) / 2.0))),(( data["abs_minbatch_slices2_msignal"])))) *(data["maxbatch_slices2"])))))))))) +
0.050000*np.tanh(((((((data["stdbatch_msignal"])+(((data["abs_maxbatch_msignal"])*(((((data["abs_minbatch_slices2_msignal"])*(data["signal_shift_-1"])))/ 2.0)))))) +(np.where(data["abs_avgbatch_msignal"] > -998, data["stdbatch_slices2"], np.cos(( data["mean_abs_chgbatch_msignal"])))))) * 2.0)) +
0.050000*np.tanh(((((data["mean_abs_chgbatch_slices2_msignal"])* 2.0)) *(np.where(np.where(((data["maxbatch_slices2"])*(data["maxtominbatch_msignal"])) > -998, np.where(((((data["mean_abs_chgbatch_slices2_msignal"])* 2.0)) * 2.0)> -998, data["maxbatch_slices2"], data["meanbatch_slices2_msignal"]), data["rangebatch_slices2"])> -998, np.where(data["mean_abs_chgbatch_slices2_msignal"] > -998, data["maxbatch_slices2"],(( data["mean_abs_chgbatch_slices2_msignal"])* 2.0)) ,(((data["maxbatch_slices2"])+(data["abs_minbatch_slices2_msignal"])) /2.0)))))+
0.050000*np.tanh(((np.cos(((( data["abs_minbatch_msignal"])-(((( data["abs_minbatch_msignal"])<=(((( data["stdbatch_slices2_msignal"])>(((((((((( data["maxtominbatch"])+(data["abs_maxbatch"])))*(data["mean_abs_chgbatch_slices2_msignal"])))<=(data["mean_abs_chgbatch_slices2_msignal"])) *1.))* 2.0)))*1.))) *1.))))))* 2.0)) +
0.050000*np.tanh(((((data["maxbatch_slices2"])*(data["mean_abs_chgbatch_msignal"])))* 2.0)) +
0.050000*np.tanh(np.where(np.sin(( np.maximum(((data["abs_avgbatch_slices2_msignal"])) ,(( data["abs_avgbatch_slices2_msignal"])))))<= -998, data["maxbatch_slices2"],(( data["mean_abs_chgbatch_slices2_msignal"])*(data["maxbatch_slices2"])))) +
0.050000*np.tanh(((data["maxbatch_slices2"])*(np.where(data["maxbatch_slices2"] <= -998,(((((np.minimum(((data["mean_abs_chgbatch_msignal"])) ,(( data["maxbatch_slices2"])))) +(((data["abs_minbatch_msignal"])* 2.0)))/2.0)) * 2.0), np.where(((((( data["mean_abs_chgbatch_msignal"])* 2.0)) <=(np.where(data["abs_maxbatch"] <= -998, data["signal_shift_-1_msignal"], data["abs_minbatch_msignal"])))*1.) <= -998, data["maxbatch_slices2"],(( data["mean_abs_chgbatch_slices2_msignal"])* 2.0)))))) +
0.050000*np.tanh(((data["maxbatch_slices2"])*(np.where(data["mean_abs_chgbatch_msignal"] <= -998, data["maxbatch_slices2"], data["mean_abs_chgbatch_msignal"])))) +
0.050000*np.tanh(np.minimum(((((np.minimum(((data["rangebatch_slices2"])) ,(((( data["mean_abs_chgbatch_msignal"])* 2.0)))))* 2.0))),(((( np.minimum(((((data["mean_abs_chgbatch_msignal"])* 2.0))),(((( np.sin(( np.where(np.cos(((( data["abs_avgbatch_msignal"])* 2.0)))> -998, data["abs_avgbatch_msignal"],(((((data["medianbatch_msignal"])+(data["stdbatch_slices2_msignal"])) /2.0)) / 2.0)))))* 2.0)))))* 2.0)))))+
0.050000*np.tanh(((np.where(( 3.88836002349853516)<= -998, data["minbatch_msignal"], np.cos(((-(( data["maxtominbatch_msignal"])))))))* 2.0)) +
0.050000*np.tanh(((( -(( np.maximum(((np.minimum(((((data["abs_maxbatch_msignal"])* 2.0))),(((((data["abs_maxbatch"])+(np.where(np.cos(( data["abs_minbatch_slices2"])) > -998, data["maxtominbatch_slices2_msignal"],(5.19431018829345703)))) /2.0)))))) ,(((( data["maxtominbatch_slices2_msignal"])*(np.minimum(((((data["maxtominbatch_msignal"])* 2.0))),(( data["stdbatch_msignal"])))))))))))) +(( 3.0)))) +
0.050000*np.tanh(np.where(((np.cos(( data["stdbatch_msignal"])))-(((data["abs_maxbatch_slices2"])+(((data["abs_maxbatch"])*(((np.tanh(( data["abs_avgbatch_slices2_msignal"])))*(data["maxbatch_msignal"])))))))) <= -998,(-(( np.tanh(( data["medianbatch_slices2"]))))),(( np.cos(( np.where(np.cos(( data["abs_maxbatch"])) <= -998, data["maxtominbatch_slices2"], data["maxtominbatch_slices2_msignal"])))) *(data["rangebatch_slices2_msignal"])))) +
0.050000*np.tanh(((np.maximum(((np.cos(( np.tanh(( data["stdbatch_slices2_msignal"])))))) ,(( data["maxbatch_msignal"])))) *(((((np.where(np.sin(((( data["mean_abs_chgbatch_slices2_msignal"])*(data["maxtominbatch_msignal"])))) > -998,(( np.sin(( data["abs_avgbatch_slices2_msignal"])))*(data["mean_abs_chgbatch_slices2_msignal"])) , data["mean_abs_chgbatch_slices2_msignal"])) * 2.0)) * 2.0)))) +
0.050000*np.tanh(((data["maxbatch_slices2"])*(np.where(data["stdbatch_msignal"] <= -998, data["mean_abs_chgbatch_slices2_msignal"], np.where(np.where(((((data["maxbatch_slices2"])*(data["abs_minbatch_slices2_msignal"])))-(data["medianbatch_msignal"])) <= -998, data["maxbatch_slices2"],(( data["maxtominbatch_slices2_msignal"])*(data["medianbatch_slices2_msignal"])))<= -998, data["medianbatch_slices2"], data["mean_abs_chgbatch_slices2_msignal"])))))+
0.050000*np.tanh(((data["maxbatch_slices2"])*(((((((data["mean_abs_chgbatch_slices2_msignal"])+(((data["stdbatch_msignal"])*(data["abs_minbatch_slices2"])))))-(( -(((( data["maxtominbatch_slices2_msignal"])+(np.where(np.where(data["maxbatch_slices2"] > -998,(7.0), data["maxbatch_slices2"])> -998, np.sin(( data["stdbatch_msignal"])) , data["maxbatch_slices2"])))))))))* 2.0)))) +
0.050000*np.tanh(((np.minimum(((((((data["mean_abs_chgbatch_slices2_msignal"])* 2.0)) * 2.0))),(( data["maxbatch_slices2"])))) * 2.0)) +
0.050000*np.tanh(((((np.where(data["abs_minbatch_msignal"] > -998,(( np.where(np.cos(( data["maxbatch_slices2"])) <= -998, data["abs_minbatch_msignal"], np.cos(((-(( data["abs_minbatch_msignal"])))))))* 2.0), data["maxtominbatch_slices2_msignal"])) +(((((data["maxtominbatch_slices2_msignal"])*(( -(( data["abs_minbatch_msignal"])))))) * 2.0)))) * 2.0)) +
0.050000*np.tanh(((np.where(data["abs_minbatch_msignal"] > -998, data["mean_abs_chgbatch_msignal"], data["stdbatch_msignal"])) * 2.0)) +
0.050000*np.tanh(np.where(data["abs_minbatch_msignal"] <= -998, np.where(((( data["maxbatch_slices2"])+(data["stdbatch_slices2"])) /2.0)<= -998,(((data["mean_abs_chgbatch_slices2_msignal"])>(np.tanh(( data["mean_abs_chgbatch_slices2_msignal"])))) *1.) , data["mean_abs_chgbatch_slices2_msignal"]), np.where(data["minbatch"] <= -998, data["rangebatch_slices2_msignal"],(((( data["maxbatch_slices2"])*(data["mean_abs_chgbatch_slices2_msignal"])))* 2.0)))) +
0.050000*np.tanh(((((data["signal"])*(data["maxtominbatch_slices2_msignal"])))+(((np.sin(( np.where(((( 7.0)) +(np.sin(( data["mean_abs_chgbatch_msignal"])))) <= -998, data["maxtominbatch_slices2_msignal"],(( data["mean_abs_chgbatch_msignal"])*(data["abs_minbatch_msignal"])))))) * 2.0)))) +
0.050000*np.tanh(((((data["mean_abs_chgbatch_msignal"])*(np.where(((( np.where(((((2.0)) >(np.where(data["abs_avgbatch_slices2_msignal"] <= -998,(2.0), np.tanh(( data["maxbatch_slices2"])))))*1.) > -998, data["maxbatch_slices2"], data["maxbatch_slices2"])) >(data["signal_shift_+1"])) *1.) > -998, data["maxbatch_slices2"], data["maxbatch_slices2"])))) * 2.0)) +
0.050000*np.tanh(((((np.where(data["abs_avgbatch_slices2"] <= -998, np.maximum(((((( data["abs_avgbatch_slices2"])>(data["maxbatch_slices2_msignal"])) *1.))) ,(( np.cos(( data["abs_maxbatch_msignal"]))))), np.sin(( data["abs_avgbatch_slices2_msignal"])))) * 2.0)) * 2.0)) +
0.050000*np.tanh(((((((data["abs_avgbatch_msignal"])*(np.sin(( data["abs_avgbatch_msignal"])))))*(((((np.sin(( data["abs_avgbatch_msignal"])))+(((data["abs_minbatch_slices2_msignal"])+(data["abs_avgbatch_msignal"])))))+(data["rangebatch_slices2_msignal"])))))*(data["mean_abs_chgbatch_msignal"])))+
0.050000*np.tanh(((np.cos(( np.minimum(((data["abs_minbatch_msignal"])) ,(((( data["stdbatch_slices2_msignal"])-(np.cos(((( np.cos(( np.where(np.minimum(((data["maxtominbatch_slices2_msignal"])) ,(( data["maxbatch_msignal"])))> -998, data["meanbatch_slices2"], data["abs_avgbatch_msignal"])))) * 2.0)))))))))))* 2.0)) +
0.050000*np.tanh(((( 4.65593338012695312)) *(np.where(((np.cos(( data["mean_abs_chgbatch_msignal"])))*(data["mean_abs_chgbatch_msignal"])) > -998, np.cos(((( np.cos(( data["mean_abs_chgbatch_msignal"])))-(data["abs_minbatch_msignal"])))) ,(( data["abs_minbatch_msignal"])+(( 11.16297435760498047)))))))+
0.050000*np.tanh(np.where(data["stdbatch_slices2_msignal"] <= -998,(-(((-(((( data["maxbatch_slices2_msignal"])+(np.cos(( data["maxtominbatch_msignal"])))))))))) ,(( data["abs_minbatch_msignal"])+(((data["mean_abs_chgbatch_slices2_msignal"])* 2.0)))))+
0.050000*np.tanh(((( 4.0)) *(((data["mean_abs_chgbatch_msignal"])+(np.where(data["minbatch_msignal"] > -998,(( data["signal"])*(((data["mean_abs_chgbatch_slices2_msignal"])+(data["maxtominbatch_msignal"])))) , np.minimum(((data["mean_abs_chgbatch_msignal"])) ,(( np.cos(((4.0)))))))))))) +
0.050000*np.tanh(((((np.cos(( np.minimum(((data["maxtominbatch_msignal"])) ,(( np.maximum(((( 5.92805910110473633))),(( np.minimum(((((((np.cos(( np.minimum(((data["signal"])) ,(( np.maximum(((data["maxtominbatch_msignal"])) ,(( np.minimum(((data["mean_abs_chgbatch_msignal"])) ,(( data["medianbatch_slices2"])))))))))))) * 2.0)) * 2.0))),(( data["maxtominbatch_msignal"])))))))))))) * 2.0)) * 2.0)) +
0.050000*np.tanh(np.sin(( np.where(np.where(data["stdbatch_msignal"] > -998, data["rangebatch_slices2_msignal"], data["stdbatch_msignal"])> -998, data["abs_avgbatch_slices2_msignal"],(( data["abs_minbatch_slices2"])* 2.0)))))+
0.050000*np.tanh(((np.sin(( np.where(data["maxbatch_slices2"] <= -998, np.maximum(((((((((( data["mean_abs_chgbatch_msignal"])+(data["mean_abs_chgbatch_slices2_msignal"])))+(np.cos(( data["signal_shift_+1"])))))+(np.sin(( data["maxtominbatch_slices2_msignal"])))) /2.0))),(( np.cos(( data["abs_minbatch_msignal"]))))),(( data["mean_abs_chgbatch_msignal"])* 2.0)))))* 2.0)) +
0.050000*np.tanh(((np.sin(( data["abs_avgbatch_msignal"])))*(((( 9.0)) +(data["abs_minbatch_msignal"])))))+
0.050000*np.tanh(((np.sin(( np.where(np.sin(( np.where(data["abs_avgbatch_slices2_msignal"] > -998, data["abs_avgbatch_slices2_msignal"], np.where(data["maxtominbatch"] > -998,(( data["mean_abs_chgbatch_slices2"])/ 2.0), np.sin(( data["mean_abs_chgbatch_slices2"])))))) > -998, data["abs_avgbatch_msignal"], data["rangebatch_msignal"])))) * 2.0)) +
0.050000*np.tanh(((data["maxbatch_slices2_msignal"])*(np.minimum(((np.sin(( data["abs_avgbatch_msignal"])))) ,(( np.where(np.minimum(((np.sin(( data["abs_avgbatch_msignal"])))) ,(( data["mean_abs_chgbatch_slices2_msignal"])))> -998,(( data["abs_maxbatch_slices2"])*(data["abs_minbatch_msignal"])) , np.sin(((( data["mean_abs_chgbatch_slices2_msignal"])*(data["rangebatch_msignal"])))))))))))+
0.050000*np.tanh(((np.where(data["signal"] <= -998, data["meanbatch_slices2"], np.cos(((10.54172039031982422)))))+(np.cos(( data["meanbatch_slices2"])))))+
0.050000*np.tanh(((np.maximum(((np.maximum(((data["maxbatch_slices2"])) ,(( np.where(np.tanh(( data["abs_avgbatch_slices2_msignal"])) > -998, np.sin(( data["abs_minbatch_msignal"])) , np.sin(( data["maxbatch_slices2"])))))))) ,(( data["abs_avgbatch_slices2_msignal"])))) *(np.sin(( data["abs_avgbatch_slices2_msignal"])))))+
0.050000*np.tanh(((data["stdbatch_msignal"])-(np.where(((data["stdbatch_msignal"])/ 2.0)> -998, data["signal_shift_+1"],(((((((((( data["abs_minbatch_msignal"])-(data["stdbatch_slices2"])))/ 2.0)) <=(np.sin(( data["signal_shift_+1"])))) *1.))<=(data["rangebatch_slices2_msignal"])) *1.))))) +
0.050000*np.tanh(((data["rangebatch_msignal"])*(np.sin(((( data["abs_avgbatch_slices2"])+(np.where(((np.cos(( data["mean_abs_chgbatch_slices2_msignal"])))* 2.0)<= -998, data["signal"], np.where(data["abs_minbatch_slices2_msignal"] <= -998, data["abs_avgbatch_slices2_msignal"],(( data["signal"])* 2.0)))))))))) +
0.050000*np.tanh(((((np.cos(((( data["abs_minbatch_slices2_msignal"])*(data["abs_avgbatch_slices2"])))))+(((data["signal"])*(((( -(((((-(((((((( data["abs_minbatch_slices2_msignal"])* 2.0)) *(data["mean_abs_chgbatch_msignal"])))* 2.0)))))-(data["minbatch_msignal"])))))) / 2.0)))))) / 2.0)) +
0.050000*np.tanh(np.cos(( np.where(((np.minimum(((np.cos(( data["medianbatch_slices2"])))) ,(( np.sin(( np.where(((( data["abs_avgbatch_slices2"])>(((( data["abs_maxbatch"])+(data["stdbatch_msignal"])) /2.0)))*1.) > -998, data["abs_avgbatch_slices2"],(((((10.0)) / 2.0)) +(np.cos(( data["maxtominbatch"])))))))))))* 2.0)> -998, data["medianbatch_slices2"], data["meanbatch_slices2_msignal"])))) +
0.050000*np.tanh(((((np.where(data["abs_minbatch_msignal"] > -998, data["mean_abs_chgbatch_msignal"], data["abs_avgbatch_msignal"])) +(((np.cos(( data["abs_minbatch_msignal"])))+(np.minimum(((np.cos(( data["abs_minbatch_msignal"])))) ,(((( data["maxtominbatch_slices2_msignal"])+(((( data["abs_minbatch_msignal"])<=(data["abs_minbatch_msignal"])) *1.))))))))))) +(((data["abs_avgbatch_msignal"])*(np.cos(( data["meanbatch_slices2"])))))))+
0.050000*np.tanh(((np.where(((( data["abs_minbatch_slices2_msignal"])+(data["mean_abs_chgbatch_slices2_msignal"])) /2.0)> -998,(4.0),(6.0)))*(((np.cos(( np.where(data["mean_abs_chgbatch_slices2_msignal"] > -998, data["mean_abs_chgbatch_slices2_msignal"],(6.0)))))*(((( data["abs_minbatch_slices2_msignal"])+(data["mean_abs_chgbatch_slices2_msignal"])) /2.0)))))) +
0.050000*np.tanh(np.where(data["stdbatch_msignal"] > -998,(((( np.cos(( data["mean_abs_chgbatch_slices2_msignal"])))*(((data["stdbatch_msignal"])+(data["abs_maxbatch_msignal"])))))+(data["mean_abs_chgbatch_slices2_msignal"])) ,(( data["maxbatch_slices2_msignal"])+(data["maxtominbatch"])))) +
0.050000*np.tanh(((((((((((data["abs_maxbatch_slices2_msignal"])*(( 3.0)))) *(np.minimum(((data["abs_maxbatch_slices2"])) ,(((( np.where(data["abs_maxbatch_slices2_msignal"] <= -998, np.where(((data["mean_abs_chgbatch_slices2_msignal"])* 2.0)<= -998, data["mean_abs_chgbatch_msignal"], data["abs_maxbatch_slices2"]),(((( 3.0)) >(data["abs_avgbatch_slices2_msignal"])) *1.))) *(data["abs_maxbatch_slices2"])))))))) * 2.0)) *(data["mean_abs_chgbatch_slices2_msignal"])))* 2.0)) +
0.050000*np.tanh(((((((np.minimum(((((data["abs_minbatch_msignal"])* 2.0))),(((( np.sin(( np.sin(( np.maximum(((data["abs_avgbatch_slices2_msignal"])) ,(( data["abs_avgbatch_slices2_msignal"])))))))) * 2.0)))))* 2.0)) +(np.where(data["abs_avgbatch_slices2_msignal"] > -998,(( np.sin(( np.maximum(((data["abs_avgbatch_slices2_msignal"])) ,(( np.tanh(( np.sin(( np.maximum(((data["abs_avgbatch_slices2_msignal"])) ,(( data["signal_shift_+1"])))))))))))))* 2.0), data["signal_shift_+1"])))) * 2.0)) +
0.050000*np.tanh(((np.minimum(((np.cos(( data["mean_abs_chgbatch_msignal"])))) ,(((( data["abs_maxbatch"])*(np.where(data["mean_abs_chgbatch_msignal"] > -998, data["mean_abs_chgbatch_msignal"],(-(((((data["mean_abs_chgbatch_slices2_msignal"])+(data["medianbatch_slices2"])) /2.0)))))))))))*(data["abs_maxbatch_slices2_msignal"])))+
0.050000*np.tanh(((((data["mean_abs_chgbatch_slices2_msignal"])-(((( data["mean_abs_chgbatch_msignal"])<=(data["signal_shift_+1_msignal"])) *1.))))+(np.tanh(( np.where(((( data["meanbatch_msignal"])+(data["meanbatch_msignal"])) /2.0)> -998, data["stdbatch_msignal"],(((((( data["maxtominbatch_msignal"])>(data["abs_minbatch_msignal"])) *1.))+(data["stdbatch_slices2"])) /2.0)))))))+
0.050000*np.tanh(((np.sin(((((((data["meanbatch_slices2_msignal"])+(np.tanh(( np.cos(( data["signal_shift_-1_msignal"])))))))+(data["mean_abs_chgbatch_msignal"])) /2.0)))) +(np.cos(( np.where(np.minimum(((np.maximum(((data["mean_abs_chgbatch_msignal"])) ,(( np.minimum(((np.cos(( data["maxtominbatch_msignal"])))) ,(( np.sin(((( data["abs_minbatch_slices2_msignal"])* 2.0))))))))))),(( data["signal_shift_-1_msignal"])))> -998, data["medianbatch_slices2"], np.cos(( data["maxtominbatch_msignal"])))))))) +
0.050000*np.tanh(((np.where(data["stdbatch_msignal"] <= -998, np.cos(( np.cos(( data["abs_avgbatch_msignal"])))) ,(5.0)))*(np.sin(( data["abs_avgbatch_msignal"])))))+
0.050000*np.tanh(np.where(np.where(np.sin(((( data["rangebatch_slices2_msignal"])-(data["signal_shift_-1"])))) <= -998, data["abs_maxbatch"],(( data["abs_minbatch_slices2_msignal"])* 2.0)) <= -998, np.tanh(( data["abs_minbatch_slices2_msignal"])) , np.where(( -(( data["signal_shift_-1"])))<= -998, data["rangebatch_msignal"],(( data["mean_abs_chgbatch_slices2_msignal"])*(data["abs_maxbatch"])))))+
0.050000*np.tanh(((((data["mean_abs_chgbatch_msignal"])+(((np.cos(( data["stdbatch_slices2_msignal"])))-(data["meanbatch_msignal"])))))* 2.0)) +
0.050000*np.tanh(((np.minimum(((( 3.0))),(( np.cos(( np.where(np.cos(( data["mean_abs_chgbatch_slices2_msignal"])) <= -998,(( np.cos(( np.where(data["mean_abs_chgbatch_msignal"] <= -998, data["mean_abs_chgbatch_msignal"], np.cos(( data["abs_minbatch_slices2"])))))) +(( -(( np.cos(( data["signal_shift_-1_msignal"]))))))),(( data["signal_shift_-1"])+(np.sin(( data["minbatch_slices2_msignal"])))))))))))* 2.0)) +
0.050000*np.tanh(((data["rangebatch_slices2_msignal"])*(((np.cos(((( data["maxtominbatch_msignal"])-(np.where(((data["abs_minbatch_msignal"])*(((((10.0)) <=(np.cos(((10.0)))))*1.))) > -998,(-(( data["mean_abs_chgbatch_slices2_msignal"]))),(( data["signal_shift_-1"])* 2.0)))))))* 2.0)))) +
0.050000*np.tanh(((data["mean_abs_chgbatch_msignal"])+(np.where(((((data["signal_shift_+1_msignal"])* 2.0)) +(data["signal_shift_+1"])) > -998,(( data["abs_maxbatch_slices2"])*(data["abs_minbatch_msignal"])) , data["signal_shift_+1_msignal"])))) +
0.050000*np.tanh(np.minimum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(((( np.where(np.sin(( data["abs_avgbatch_msignal"])) <= -998,(( data["rangebatch_slices2"])-(((( np.tanh(( np.where(((((( data["medianbatch_slices2"])/ 2.0)) <=(data["stdbatch_msignal"])) *1.) > -998, data["abs_minbatch_slices2_msignal"],(3.0)))))+(data["abs_minbatch_msignal"])) /2.0))), np.sin(( data["abs_avgbatch_msignal"])))) * 2.0)))))+
0.050000*np.tanh(np.cos(( np.minimum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(( data["maxtominbatch_msignal"])))))) +
0.050000*np.tanh(((data["rangebatch_slices2_msignal"])*(((((data["maxtominbatch_slices2_msignal"])*(np.where(np.where(data["medianbatch_msignal"] > -998, data["minbatch_slices2_msignal"], data["maxtominbatch_slices2_msignal"])> -998, data["signal_shift_+1"], np.sin(((((( data["abs_avgbatch_msignal"])/ 2.0)) -(data["maxbatch_slices2"])))))))) +(np.where(np.cos(( data["minbatch_slices2_msignal"])) > -998, np.cos(( data["mean_abs_chgbatch_msignal"])) , data["maxbatch_slices2"])))))) +
0.050000*np.tanh(((((np.where(np.sin(( data["abs_avgbatch_slices2_msignal"])) > -998, np.where(np.sin(( np.minimum(((data["signal_shift_+1"])) ,(( np.maximum(((np.minimum(((data["abs_avgbatch_slices2_msignal"])) ,(( data["abs_avgbatch_msignal"]))))),(( data["abs_avgbatch_slices2_msignal"])))))))) > -998, np.sin(( data["abs_avgbatch_slices2_msignal"])) ,(( data["abs_avgbatch_slices2_msignal"])* 2.0)) , np.sin(((( data["signal_shift_+1"])/ 2.0)))))* 2.0)) * 2.0)) +
0.050000*np.tanh(((np.where(data["signal_shift_-1_msignal"] <= -998, np.minimum(((data["rangebatch_msignal"])) ,(((-(((( np.cos(( data["mean_abs_chgbatch_slices2_msignal"])))* 2.0))))))), data["maxbatch_slices2_msignal"])) *(np.minimum(((np.minimum(((np.sin(( data["abs_avgbatch_slices2"])))) ,(( np.cos(( data["mean_abs_chgbatch_msignal"]))))))),(( np.minimum(((data["mean_abs_chgbatch_msignal"])) ,(((7.0)))))))))) +
0.050000*np.tanh(((np.sin(( np.maximum(((data["abs_avgbatch_msignal"])) ,(( data["abs_avgbatch_slices2"])))))) * 2.0)) +
0.050000*np.tanh(np.minimum(((((np.minimum(((np.cos(( data["mean_abs_chgbatch_msignal"])))) ,(( np.maximum(((data["maxtominbatch_slices2"])) ,(( data["abs_maxbatch_slices2"])))))))*(data["abs_maxbatch_slices2"])))) ,(( np.cos(( np.maximum(((np.maximum(((data["mean_abs_chgbatch_msignal"])) ,(((( data["medianbatch_slices2"])*(np.minimum(((np.cos(( data["mean_abs_chgbatch_msignal"])))) ,(( np.maximum(((data["maxtominbatch_slices2"])) ,(( data["mean_abs_chgbatch_msignal"]))))))))))))),(( data["mean_abs_chgbatch_msignal"])))))))))+
0.050000*np.tanh(((np.tanh(( np.minimum(((data["maxtominbatch"])) ,(( np.tanh(( data["abs_avgbatch_slices2"])))))))) +(((data["mean_abs_chgbatch_slices2_msignal"])* 2.0)))) +
0.050000*np.tanh(((((data["mean_abs_chgbatch_slices2_msignal"])-(np.where(((( data["abs_avgbatch_slices2_msignal"])+(np.cos(((6.17451095581054688)))))/2.0)> -998, data["signal_shift_+1"],(((((np.sin(((((data["minbatch_msignal"])+(data["minbatch"])) /2.0)))) * 2.0)) >(data["stdbatch_msignal"])) *1.))))) * 2.0)) +
0.050000*np.tanh(((np.minimum(((((((data["mean_abs_chgbatch_msignal"])+(( 6.0)))) +(((((((10.86887836456298828)) +(( -(( data["maxtominbatch"])))))) <=(((( data["abs_avgbatch_slices2_msignal"])>(((data["abs_maxbatch"])* 2.0)))*1.))) *1.))))) ,(( np.maximum(((data["abs_avgbatch_slices2_msignal"])) ,(( np.maximum(((data["abs_avgbatch_slices2"])) ,(( np.cos(( data["mean_abs_chgbatch_slices2_msignal"])))))))))))) *(np.cos(( data["maxtominbatch_msignal"])))))+
0.050000*np.tanh(((np.sin(( np.where(( -(( data["medianbatch_slices2"])))<= -998, data["maxtominbatch_slices2"],(( data["mean_abs_chgbatch_slices2_msignal"])* 2.0)))))*(((((np.maximum(((np.cos(( data["abs_minbatch_slices2"])))) ,(((8.0)))))-(data["maxbatch_msignal"])))+(((data["mean_abs_chgbatch_msignal"])+(np.where(np.maximum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(( data["mean_abs_chgbatch_msignal"])))<= -998, data["signal_shift_+1_msignal"], data["mean_abs_chgbatch_slices2_msignal"])))))))) +
0.050000*np.tanh(((np.sin(( np.where(np.where(data["abs_minbatch_msignal"] > -998, np.cos(( np.minimum(((data["abs_minbatch_msignal"])) ,(((-(( data["maxtominbatch"])))))))) , data["meanbatch_slices2_msignal"])> -998, data["abs_avgbatch_slices2_msignal"], data["abs_minbatch_msignal"])))) *(np.maximum(((((data["abs_avgbatch_slices2_msignal"])*(np.sin(( data["abs_avgbatch_msignal"])))))) ,(( data["mean_abs_chgbatch_msignal"])))))) +
0.050000*np.tanh(((data["rangebatch_slices2_msignal"])*(np.cos(( np.where(((np.tanh(( np.cos(( np.where(data["mean_abs_chgbatch_slices2"] > -998, np.where(data["meanbatch_slices2"] > -998, data["meanbatch_slices2"],(( np.cos(( data["mean_abs_chgbatch_slices2_msignal"])))* 2.0)) , data["signal"])))))) -(data["abs_minbatch_slices2_msignal"])) > -998, data["meanbatch_slices2"], data["meanbatch_slices2"])))))) +
0.050000*np.tanh(((np.cos(( np.where(data["meanbatch_msignal"] > -998, data["meanbatch_msignal"], np.minimum(((data["signal"])) ,(( np.tanh(((( np.minimum(((((np.minimum(((( 4.0))),(( data["abs_maxbatch_msignal"])))) *(np.cos(( np.minimum(((data["medianbatch_slices2"])) ,(((( data["meanbatch_slices2_msignal"])+(data["meanbatch_msignal"]))))))))))),(( np.sin(( data["signal_shift_+1"])))))) *(data["signal_shift_+1"])))))))))))* 2.0)) +
0.050000*np.tanh(((data["maxtominbatch_msignal"])+(((((( data["stdbatch_msignal"])>(((((data["meanbatch_msignal"])-(data["abs_avgbatch_msignal"])))-(data["abs_avgbatch_slices2"])))) *1.))* 2.0)))) +
0.050000*np.tanh(((((np.sin(( np.where(((data["stdbatch_slices2_msignal"])*(np.tanh(( data["medianbatch_msignal"])))) <= -998,(((data["rangebatch_slices2"])+(np.cos(( data["mean_abs_chgbatch_msignal"])))) /2.0),(( data["mean_abs_chgbatch_slices2_msignal"])* 2.0)))))* 2.0)) * 2.0)) +
0.050000*np.tanh(((np.sin(( np.sin(((( data["abs_maxbatch_slices2_msignal"])/ 2.0)))))) +(((((((np.cos(( data["maxbatch_msignal"])))*(data["abs_maxbatch_slices2_msignal"])))+(data["abs_maxbatch_slices2_msignal"])))+(((((data["maxbatch_msignal"])*(data["maxtominbatch_slices2_msignal"])))+(data["maxbatch_msignal"])))))))+
0.050000*np.tanh(np.where(np.where(np.sin(( data["abs_maxbatch_msignal"])) <= -998, data["mean_abs_chgbatch_slices2_msignal"], np.cos(( np.maximum(((np.minimum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(( data["minbatch_msignal"]))))),(( data["abs_avgbatch_slices2_msignal"])))))) > -998, np.cos(( np.maximum(((np.minimum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(( data["stdbatch_slices2_msignal"]))))),(( data["meanbatch_slices2"]))))), np.cos(( np.sin(( data["abs_avgbatch_slices2"])))))) +
0.050000*np.tanh(((np.cos(( data["maxtominbatch_msignal"])))+(np.cos(( data["maxtominbatch"])))))+
0.050000*np.tanh(((((np.cos(((( np.where(data["abs_avgbatch_slices2_msignal"] > -998, data["minbatch_msignal"], np.where(data["minbatch_msignal"] > -998, data["minbatch_msignal"],(((data["abs_minbatch_slices2"])+(((((( data["signal"])*(data["minbatch"])))>(((((data["minbatch"])* 2.0)) * 2.0)))*1.))) /2.0)))) * 2.0)))) * 2.0)) * 2.0)) +
0.050000*np.tanh(np.where(data["medianbatch_msignal"] <= -998,(3.54091382026672363),(( np.tanh(((((( data["abs_avgbatch_slices2_msignal"])*(((np.sin(( data["abs_avgbatch_slices2_msignal"])))* 2.0)))) -(data["mean_abs_chgbatch_slices2_msignal"])))))* 2.0)))+
0.050000*np.tanh(((np.sin(( np.where(np.sin(( np.cos(( data["meanbatch_slices2"])))) <= -998, np.sin(( np.where(data["meanbatch_slices2"] > -998, data["maxtominbatch_msignal"], data["meanbatch_slices2"]))), data["abs_avgbatch_msignal"])))) * 2.0)) +
0.050000*np.tanh(((data["maxtominbatch_msignal"])+(((np.cos(((( data["maxtominbatch_slices2_msignal"])-(np.where(data["maxtominbatch_msignal"] <= -998,(( data["abs_minbatch_slices2_msignal"])/ 2.0), data["signal"])))))) * 2.0)))) +
0.050000*np.tanh(((np.minimum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(( np.where(np.sin(((((((( data["abs_minbatch_slices2_msignal"])*(data["abs_minbatch_slices2_msignal"])))-(data["maxbatch_slices2"])))*(data["abs_maxbatch_slices2_msignal"])))) <= -998,(( data["maxbatch_slices2"])* 2.0), np.cos(( data["meanbatch_slices2"])))))))*(data["abs_maxbatch_slices2_msignal"])))+
0.050000*np.tanh(((np.minimum(((np.minimum(((np.where(data["mean_abs_chgbatch_slices2_msignal"] <= -998, np.sin(( np.minimum(((np.where(data["meanbatch_msignal"] <= -998,(13.98129940032958984),(( np.sin(( data["abs_avgbatch_slices2_msignal"])))*(data["abs_avgbatch_msignal"]))))),(( data["mean_abs_chgbatch_msignal"]))))),(( np.sin(( data["abs_avgbatch_slices2_msignal"])))*(data["abs_avgbatch_msignal"]))))),(( data["stdbatch_msignal"]))))),(( data["mean_abs_chgbatch_msignal"])))) * 2.0)) +
0.050000*np.tanh(((np.cos(( data["mean_abs_chgbatch_slices2_msignal"])))*(((((np.cos(( data["maxtominbatch_msignal"])))*(data["mean_abs_chgbatch_slices2_msignal"])))*(((data["abs_maxbatch"])+(data["mean_abs_chgbatch_slices2_msignal"])))))))+
0.050000*np.tanh(((((((((np.sin(( data["mean_abs_chgbatch_msignal"])))* 2.0)) +(data["abs_minbatch_slices2_msignal"])))+(data["abs_minbatch_slices2_msignal"])))* 2.0)) +
0.050000*np.tanh(((((( 3.0)) +(data["mean_abs_chgbatch_msignal"])))-(( 3.0)))) +
0.050000*np.tanh(((np.cos(( np.minimum(((data["maxtominbatch_msignal"])) ,(((( data["signal"])*(np.minimum(((data["abs_minbatch_slices2_msignal"])) ,(((( data["abs_avgbatch_slices2_msignal"])-(((((((( data["abs_avgbatch_slices2_msignal"])-(((((((( data["stdbatch_msignal"])* 2.0)) * 2.0)) >(((( data["meanbatch_msignal"])<=(data["abs_maxbatch"])) *1.))) *1.))))* 2.0)) >(data["abs_maxbatch"])) *1.))))))))))))))* 2.0)) +
0.050000*np.tanh(np.where(((((((data["maxtominbatch_slices2_msignal"])*(((data["signal_shift_-1"])/ 2.0)))) * 2.0)) * 2.0)<= -998, data["signal_shift_-1"],(((( data["maxtominbatch_slices2_msignal"])*(((((data["signal_shift_-1"])* 2.0)) / 2.0)))) * 2.0)))+
0.050000*np.tanh(np.where(data["abs_avgbatch_msignal"] > -998, np.cos(( np.where(data["signal_shift_+1"] <= -998, data["abs_maxbatch"], data["meanbatch_slices2"]))), data["signal"])) +
0.050000*np.tanh(((((np.minimum(((np.sin(( data["abs_avgbatch_msignal"])))) ,(( data["mean_abs_chgbatch_msignal"])))) *(((((data["abs_maxbatch_slices2_msignal"])-(((np.sin(( data["abs_avgbatch_msignal"])))*(np.sin(( np.sin(( data["abs_maxbatch_slices2_msignal"])))))))))* 2.0)))) * 2.0)) +
0.050000*np.tanh(((np.where(data["abs_maxbatch"] > -998,(8.97018146514892578),(( data["maxtominbatch"])*(data["maxtominbatch_msignal"])))) +(((data["abs_maxbatch"])*(data["maxtominbatch"])))))+
0.050000*np.tanh(((data["abs_avgbatch_slices2_msignal"])*(np.sin(( np.where(np.cos(((( data["abs_avgbatch_slices2_msignal"])-(data["minbatch_msignal"])))) > -998, np.sin(( data["abs_avgbatch_slices2_msignal"])) ,(( data["meanbatch_slices2_msignal"])/ 2.0)))))))+
0.050000*np.tanh(((np.sin(( np.maximum(((data["abs_avgbatch_slices2"])) ,(((( data["maxtominbatch_msignal"])+(np.where(data["minbatch_slices2"] <= -998, data["stdbatch_slices2"],(((((data["stdbatch_slices2_msignal"])>(((( np.maximum(((np.sin(( data["stdbatch_slices2_msignal"])))) ,(( data["maxtominbatch_slices2_msignal"])))) <=(data["stdbatch_slices2_msignal"])) *1.))) *1.))-(((data["signal"])* 2.0)))))))))))) * 2.0)) +
0.050000*np.tanh(((((2.40803050994873047)) +(data["stdbatch_msignal"])) /2.0)) +
0.050000*np.tanh(((((np.maximum(((data["abs_maxbatch_slices2_msignal"])) ,(( data["abs_minbatch_slices2"])))) * 2.0)) *(np.cos(((((((data["abs_maxbatch"])>(np.maximum(((data["abs_avgbatch_slices2"])) ,(( data["abs_minbatch_msignal"])))))*1.))-(np.minimum(((((( 13.53835296630859375)) / 2.0))),(((( data["abs_minbatch_msignal"])* 2.0)))))))))))+
0.050000*np.tanh(((((np.cos(( np.where(np.maximum(((data["abs_avgbatch_slices2"])) ,(( np.cos(( data["abs_minbatch_slices2_msignal"])))))> -998, data["mean_abs_chgbatch_slices2_msignal"],(((data["signal"])+(( 14.09535217285156250)))/2.0)))))*(data["abs_minbatch_slices2_msignal"])))*(((( 14.09535217285156250)) -(data["mean_abs_chgbatch_slices2_msignal"])))))+
0.050000*np.tanh(np.cos(( np.where(np.where(data["abs_avgbatch_msignal"] > -998,(0.0), data["maxbatch_slices2"])> -998, data["meanbatch_slices2"], np.sin(( np.where(np.where(data["abs_minbatch_slices2_msignal"] > -998, np.where(data["signal_shift_+1_msignal"] <= -998, data["mean_abs_chgbatch_msignal"], np.cos(((( np.sin(( data["maxbatch_slices2"])))* 2.0)))) , data["meanbatch_slices2"])> -998, data["meanbatch_slices2"], data["abs_minbatch_slices2_msignal"])))))))+
0.050000*np.tanh(((np.sin(((( data["meanbatch_slices2"])+(np.cos(( np.cos(((((((data["medianbatch_slices2"])*(((( data["signal_shift_+1_msignal"])>(data["maxtominbatch"])) *1.))))<=(np.where(((( data["maxbatch_slices2_msignal"])>(data["meanbatch_slices2"])) *1.) <= -998, data["medianbatch_slices2_msignal"], data["abs_avgbatch_slices2_msignal"])))*1.))))))))))* 2.0)) +
0.050000*np.tanh(((((((data["rangebatch_msignal"])*(( -(((((( data["abs_avgbatch_slices2"])+(( 4.62214088439941406)))) *(np.where(data["maxbatch_slices2_msignal"] > -998, np.where(data["maxtominbatch"] > -998, np.sin(((( data["signal_shift_-1"])-(data["mean_abs_chgbatch_msignal"])))) , np.tanh(((1.0)))) , data["stdbatch_slices2"])))))))))* 2.0)) * 2.0)) +
0.050000*np.tanh(((np.sin(( np.sin(( data["abs_avgbatch_slices2_msignal"])))))+(((((np.sin(( data["abs_avgbatch_slices2_msignal"])))+(np.sin(( data["abs_avgbatch_slices2_msignal"])))))+(((( np.sin(( data["abs_avgbatch_slices2_msignal"])))>(np.where(np.cos(((( data["meanbatch_slices2"])* 2.0)))> -998, data["abs_maxbatch"], np.sin(( data["abs_avgbatch_slices2_msignal"])))))*1.))))))+
0.050000*np.tanh(((np.sin(((( np.where(( -(( np.maximum(((data["rangebatch_slices2"])) ,(( np.cos(( data["maxbatch_slices2_msignal"])))))))) > -998, data["mean_abs_chgbatch_slices2_msignal"], data["mean_abs_chgbatch_slices2_msignal"])) * 2.0)))) *(np.where(( 10.0)<= -998,(( data["signal_shift_-1"])* 2.0), np.maximum(((data["rangebatch_slices2"])) ,(( data["signal_shift_+1"])))))))+
0.050000*np.tanh(np.sin(((( np.maximum(((data["abs_maxbatch_slices2"])) ,(((( np.where(data["stdbatch_msignal"] > -998, data["minbatch"], data["abs_maxbatch_slices2"])) / 2.0)))))/ 2.0)))) +
0.050000*np.tanh(np.minimum(((data["rangebatch_msignal"])) ,(((( data["stdbatch_slices2"])-(((np.where(((((np.minimum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(( np.maximum(((np.maximum(((data["stdbatch_slices2_msignal"])) ,(((( data["medianbatch_slices2"])-(data["rangebatch_slices2"]))))))),(( data["abs_minbatch_slices2"])))))))* 2.0)) * 2.0)<= -998,(( data["minbatch"])-(data["abs_minbatch_msignal"])) ,(( data["signal_shift_-1"])*(data["signal_shift_+1"])))) * 2.0)))))))+
0.050000*np.tanh(np.where(data["mean_abs_chgbatch_msignal"] <= -998,(((data["abs_maxbatch_slices2"])+(((data["abs_avgbatch_msignal"])* 2.0)))/2.0),(( np.sin(( np.sin(( data["abs_avgbatch_msignal"])))))* 2.0)))+
0.050000*np.tanh(((((np.cos(( np.where(np.minimum(((data["medianbatch_slices2"])) ,(( data["maxtominbatch_slices2_msignal"])))> -998, data["maxtominbatch_msignal"], data["abs_minbatch_slices2"])))) * 2.0)) +(((np.sin(( data["abs_avgbatch_slices2"])))*(np.maximum(((data["maxbatch_slices2"])) ,(( np.cos(((( data["maxtominbatch_slices2"])+(( -(((( data["maxbatch_slices2_msignal"])+(data["mean_abs_chgbatch_slices2_msignal"])))))))))))))))))+
0.050000*np.tanh(np.where(data["abs_avgbatch_slices2_msignal"] > -998, np.where(np.cos(((8.0)))> -998,(( data["abs_avgbatch_msignal"])*(np.sin(( data["abs_avgbatch_slices2_msignal"])))) , data["medianbatch_slices2"]), data["abs_avgbatch_msignal"])) +
0.050000*np.tanh(((((((((data["signal"])*(((np.minimum(((np.sin(((( data["signal_shift_-1"])* 2.0))))),(( data["abs_maxbatch"])))) -(data["signal_shift_-1"])))))* 2.0)) +(np.cos(((-(( np.sin(((((((np.sin(( data["abs_avgbatch_slices2_msignal"])))-(data["maxtominbatch_slices2_msignal"])))>(np.cos(( data["maxbatch_slices2"])))) *1.))))))))))) * 2.0)) +
0.050000*np.tanh(((((((data["abs_avgbatch_slices2_msignal"])* 2.0)) -(data["abs_minbatch_slices2"])))*(((data["mean_abs_chgbatch_msignal"])-(((((np.minimum(((data["signal"])) ,(( data["signal_shift_-1"])))) * 2.0)) *(data["signal_shift_-1"])))))))+
0.050000*np.tanh(((np.cos(((( np.sin(( data["medianbatch_slices2_msignal"])))-(np.where(np.cos(( data["meanbatch_slices2"])) > -998, data["meanbatch_slices2"],(( data["medianbatch_slices2_msignal"])-(np.sin(( data["abs_maxbatch_slices2_msignal"])))))))))) * 2.0)) +
0.050000*np.tanh(((((np.where(np.minimum(((data["medianbatch_slices2"])) ,(( data["stdbatch_msignal"])))> -998, np.cos(( np.where(((( np.tanh(( data["medianbatch_slices2_msignal"])))>(data["maxbatch_msignal"])) *1.) > -998, data["maxtominbatch_slices2"], np.where(data["maxtominbatch_slices2"] > -998,(( data["signal_shift_+1"])-(data["maxtominbatch_slices2"])) ,(((data["abs_avgbatch_slices2"])+(data["medianbatch_slices2"])) /2.0))))), data["abs_avgbatch_slices2"])) * 2.0)) * 2.0)) +
0.050000*np.tanh(((data["maxtominbatch_msignal"])*(((np.where(data["maxtominbatch_slices2"] <= -998, data["meanbatch_slices2"], data["signal_shift_+1"])) * 2.0)))) +
0.050000*np.tanh(((((( np.where(((data["abs_maxbatch"])*(data["meanbatch_slices2"])) > -998, data["stdbatch_slices2_msignal"], np.where(((data["rangebatch_slices2"])/ 2.0)> -998, data["meanbatch_slices2"], data["meanbatch_slices2"])))-(((data["minbatch_slices2"])/ 2.0)))) +(((data["signal_shift_-1"])*(((data["minbatch_slices2"])*(np.maximum(((data["abs_maxbatch"])) ,(( data["abs_minbatch_msignal"])))))))))/2.0)) +
0.050000*np.tanh(((np.sin(( data["abs_avgbatch_msignal"])))*(np.where(((( data["maxtominbatch_msignal"])+(data["stdbatch_slices2"])) /2.0)> -998,(( data["stdbatch_slices2_msignal"])*(( 8.0))),(( data["stdbatch_slices2"])*(data["stdbatch_msignal"])))))) +
0.050000*np.tanh(((np.where(( 4.60696315765380859)<= -998, np.where(np.sin(( np.sin(( np.where(np.where(data["medianbatch_msignal"] > -998, data["abs_minbatch_slices2_msignal"], np.maximum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(( data["abs_minbatch_slices2_msignal"])))) > -998, data["medianbatch_slices2_msignal"], data["mean_abs_chgbatch_slices2_msignal"])))))> -998, data["mean_abs_chgbatch_slices2_msignal"], data["minbatch_slices2"]),(( np.sin(((( data["mean_abs_chgbatch_slices2_msignal"])* 2.0)))) * 2.0)))* 2.0)) +
0.050000*np.tanh(((((data["maxbatch_msignal"])*(((data["maxbatch_msignal"])*(np.minimum(((((((np.minimum(((data["stdbatch_slices2"])) ,(( data["abs_minbatch_msignal"])))) * 2.0)) / 2.0))),(( data["abs_minbatch_msignal"])))))))) +(data["stdbatch_slices2"])))+
0.050000*np.tanh(((np.where(((( data["rangebatch_slices2"])+(data["rangebatch_slices2"])) /2.0)> -998,(((( np.cos(((( np.tanh(( data["meanbatch_slices2_msignal"])))-(data["signal_shift_+1"])))))*(np.maximum(((data["mean_abs_chgbatch_msignal"])) ,(((( np.tanh(( data["meanbatch_slices2_msignal"])))-(data["signal_shift_+1"])))))))) * 2.0), np.cos(( np.cos(( data["signal_shift_+1"])))))) *(data["medianbatch_msignal"])))+
0.050000*np.tanh(np.cos(( np.where(((((( data["mean_abs_chgbatch_slices2_msignal"])+(( 2.0)))) <=(data["medianbatch_slices2"])) *1.) <= -998, data["maxtominbatch_slices2"], np.cos(((-(( np.where(((data["abs_avgbatch_slices2_msignal"])*(data["abs_maxbatch_slices2_msignal"])) <= -998, data["medianbatch_slices2"],(((( data["mean_abs_chgbatch_slices2_msignal"])* 2.0)) *(data["stdbatch_msignal"])))))))))))) +
0.050000*np.tanh(np.cos(( np.where(np.cos(( data["meanbatch_slices2"])) <= -998, np.sin(( np.where(data["maxtominbatch_msignal"] <= -998,(( data["minbatch_slices2_msignal"])+(data["maxtominbatch"])) ,(( data["signal_shift_+1"])* 2.0)))) ,(( data["minbatch_slices2_msignal"])* 2.0)))))+
0.050000*np.tanh(((data["rangebatch_slices2"])*(np.sin(((((data["stdbatch_slices2_msignal"])+(np.maximum(((data["abs_maxbatch_slices2"])) ,(( np.sin(( np.tanh(( np.cos(((( np.where(np.cos(( data["medianbatch_msignal"])) > -998, data["abs_maxbatch"], np.sin(( np.where(((data["rangebatch_slices2_msignal"])* 2.0)> -998, data["mean_abs_chgbatch_slices2_msignal"], data["stdbatch_slices2_msignal"])))))* 2.0)))))))))))) /2.0)))))) +
0.050000*np.tanh(((((( 10.0)) +(data["mean_abs_chgbatch_slices2_msignal"])))*(np.where(data["abs_avgbatch_slices2"] <= -998, data["signal_shift_+1_msignal"], np.sin(((( np.where(data["abs_avgbatch_slices2"] > -998, data["mean_abs_chgbatch_slices2_msignal"],(((10.0)) +(((np.where(data["signal"] > -998, data["mean_abs_chgbatch_slices2_msignal"],(( data["abs_avgbatch_slices2"])+(((data["stdbatch_slices2"])+(data["stdbatch_msignal"])))))) * 2.0)))))* 2.0)))))))+
0.050000*np.tanh(np.cos(( np.where(((((( data["maxtominbatch_slices2_msignal"])<=(data["meanbatch_slices2"])) *1.))/ 2.0)> -998, data["meanbatch_slices2"],(((data["abs_maxbatch_slices2"])+(((((data["meanbatch_slices2"])+(data["medianbatch_slices2"])))+(((np.sin(( np.sin(( data["minbatch_slices2_msignal"])))))+(data["rangebatch_slices2_msignal"])))))) /2.0)))))+
0.050000*np.tanh(np.cos(((( np.where(((data["abs_maxbatch_slices2"])*(np.where(data["abs_minbatch_msignal"] > -998, data["maxtominbatch_msignal"],(( np.where(data["maxtominbatch"] <= -998, data["minbatch_slices2"], data["abs_minbatch_msignal"])) *(data["abs_maxbatch_slices2_msignal"])))))<= -998, data["abs_avgbatch_slices2"], data["abs_minbatch_msignal"])) *(np.where(data["mean_abs_chgbatch_msignal"] > -998, data["minbatch_slices2_msignal"], data["minbatch_slices2_msignal"])))))) +
0.050000*np.tanh(((np.cos(( np.where(data["mean_abs_chgbatch_slices2"] <= -998, np.cos(( data["rangebatch_msignal"])) ,(( np.tanh(((( data["abs_minbatch_msignal"])*(data["signal_shift_+1"])))))*(data["minbatch"])))))) * 2.0)) +
0.050000*np.tanh(((np.sin(((( np.where(np.minimum(((data["minbatch_msignal"])) ,(( np.where(np.cos(((( data["mean_abs_chgbatch_slices2_msignal"])+(np.tanh(((( np.cos(((( data["meanbatch_slices2"])+(( 1.0)))))) * 2.0)))))))> -998,(2.0), data["mean_abs_chgbatch_slices2_msignal"])))) > -998, data["mean_abs_chgbatch_slices2_msignal"], data["abs_avgbatch_slices2_msignal"])) * 2.0)))) * 2.0)) +
0.050000*np.tanh(((((np.where(((((( data["maxbatch_slices2"])* 2.0)) <=(((data["maxbatch_slices2"])* 2.0)))*1.) <= -998, np.sin(( data["maxbatch_msignal"])) , np.sin(((( data["medianbatch_slices2_msignal"])+(((np.sin(( data["maxbatch_slices2"])))+(np.minimum(((data["rangebatch_slices2_msignal"])) ,(( data["abs_minbatch_msignal"])))))))))))* 2.0)) * 2.0)) +
0.050000*np.tanh(((((( 2.0)) -(np.where(((np.maximum(((np.cos(( data["signal_shift_+1"])))) ,(((-(((( np.cos(( data["abs_avgbatch_slices2"])))*(data["meanbatch_slices2"])))))))))*(data["abs_avgbatch_slices2"])) <= -998,(1.21975803375244141),(( data["minbatch"])+(data["meanbatch_slices2"])))))) / 2.0)) +
0.050000*np.tanh(((( data["abs_maxbatch_slices2_msignal"])+(((((data["maxbatch_slices2"])*(((data["maxbatch_slices2"])*(np.where(((data["signal_shift_+1"])* 2.0)> -998,(-(((((-(( np.where(np.minimum(((((data["abs_minbatch_slices2_msignal"])* 2.0))),(( data["medianbatch_slices2_msignal"])))<= -998, data["abs_avgbatch_slices2"],(( data["signal_shift_-1"])+(data["signal_shift_+1"])))))))*(data["abs_minbatch_slices2_msignal"]))))), data["signal_shift_-1"])))))) * 2.0)))/2.0)) +
0.050000*np.tanh(((((((((data["meanbatch_slices2_msignal"])+(data["maxtominbatch_msignal"])))*(data["signal_shift_-1"])))+(np.cos(( np.where(data["rangebatch_slices2_msignal"] <= -998, np.where(data["abs_avgbatch_msignal"] <= -998, data["abs_avgbatch_slices2_msignal"], np.cos(((( data["mean_abs_chgbatch_msignal"])*(data["signal_shift_-1"]))))), np.cos(( np.tanh(( data["signal_shift_+1"])))))))))) * 2.0)) +
0.050000*np.tanh(((np.sin(((( data["stdbatch_slices2"])* 2.0)))) *(((data["stdbatch_slices2_msignal"])+(((np.sin(( np.maximum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(( np.tanh(( data["abs_minbatch_msignal"])))))))) *(((data["abs_maxbatch_slices2_msignal"])+(np.maximum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(( np.tanh(( data["mean_abs_chgbatch_slices2_msignal"])))))))))))))) +
0.050000*np.tanh(np.cos(( np.maximum(((((data["mean_abs_chgbatch_msignal"])+(np.cos(( data["minbatch"])))))) ,(( np.where(data["stdbatch_msignal"] > -998, np.maximum(((data["meanbatch_slices2"])) ,(( np.cos(( np.minimum(((data["meanbatch_slices2"])) ,(((( data["stdbatch_slices2"])-(np.cos(( data["stdbatch_msignal"])))))))))))) , data["mean_abs_chgbatch_msignal"])))))))+
0.050000*np.tanh(((data["rangebatch_slices2_msignal"])-(((data["medianbatch_slices2"])*(np.minimum(((data["medianbatch_slices2"])) ,(( data["rangebatch_slices2_msignal"])))))))) +
0.050000*np.tanh(((data["maxtominbatch_msignal"])-(np.where(data["minbatch_msignal"] <= -998, data["maxtominbatch_msignal"],(( np.sin(((-(((((( data["minbatch_msignal"])-(( -(((( np.tanh(( data["maxtominbatch_slices2_msignal"])))/ 2.0)))))))* 2.0)))))))*(( -(((12.54640769958496094)))))))))) +
0.050000*np.tanh(np.where(np.where(data["maxbatch_slices2_msignal"] <= -998, data["mean_abs_chgbatch_slices2_msignal"],(-(((((data["minbatch"])+(np.maximum(((data["maxtominbatch_slices2_msignal"])) ,(((((data["maxbatch_slices2"])<=(((data["meanbatch_slices2"])-(data["signal"])))) *1.))))))/2.0)))))<= -998,(( data["meanbatch_slices2_msignal"])+(((data["rangebatch_slices2_msignal"])* 2.0))),(9.0)))+
0.050000*np.tanh(((((data["rangebatch_slices2_msignal"])*(np.minimum(((((np.sin(((( data["mean_abs_chgbatch_slices2_msignal"])* 2.0)))) * 2.0))),(((( np.where(data["mean_abs_chgbatch_slices2_msignal"] > -998, data["maxbatch_slices2"], np.maximum(((data["medianbatch_msignal"])) ,(((((-(( data["minbatch_slices2"])))) / 2.0)))))) * 2.0)))))))* 2.0)) +
0.050000*np.tanh(np.where(np.sin(( np.cos(( np.sin(((( np.tanh(( data["mean_abs_chgbatch_msignal"])))-(((data["abs_maxbatch"])-(((np.cos(( data["maxtominbatch_slices2"])))+(data["maxtominbatch_slices2"])))))))))))) > -998, np.cos(( data["signal_shift_+1"])) ,(( np.minimum(((((( data["abs_minbatch_slices2_msignal"])+(data["meanbatch_slices2"])) /2.0))),(((-(( data["signal_shift_+1"])))))))-(data["signal_shift_+1"])))) +
0.050000*np.tanh(((np.cos(((-(( data["maxtominbatch_msignal"])))))) *(((np.tanh(((( data["rangebatch_slices2"])-(((data["abs_avgbatch_msignal"])* 2.0)))))) *(np.where(np.minimum(((data["rangebatch_slices2"])) ,(((( np.minimum(((np.tanh(( data["mean_abs_chgbatch_slices2"])))) ,(((((data["rangebatch_slices2"])<=(data["stdbatch_slices2"])) *1.))))) / 2.0)))) > -998, data["rangebatch_slices2"], np.maximum(((data["medianbatch_slices2_msignal"])) ,(( data["maxtominbatch_msignal"])))))))))+
0.050000*np.tanh(np.cos(( np.maximum(((np.where(((((( data["maxtominbatch_msignal"])-(( -(( data["maxbatch_slices2"])))))) >(((((( data["medianbatch_msignal"])>(np.tanh(( data["minbatch"])))) *1.))/ 2.0)))*1.) <= -998, data["stdbatch_msignal"],(-(((-(((( data["signal_shift_-1"])-(( -(((( data["signal_shift_-1"])-(((data["abs_minbatch_slices2_msignal"])* 2.0))))))))))))))))),(( data["medianbatch_slices2"])))))) +
0.050000*np.tanh(np.cos(( np.where(np.where(((( np.sin(( data["abs_minbatch_msignal"])))<=(data["abs_minbatch_msignal"])) *1.) > -998, data["signal_shift_+1"], np.minimum(((data["signal_shift_-1"])) ,(( data["abs_minbatch_msignal"])))) > -998, data["medianbatch_slices2"], data["medianbatch_slices2"])))) +
0.050000*np.tanh(((((((-(((((( data["maxtominbatch_msignal"])*(((data["signal_shift_+1"])* 2.0)))) *(data["signal_shift_+1"])))))) <=(np.cos(( data["maxtominbatch_msignal"])))) *1.))-(( -(((( data["maxtominbatch_msignal"])*(((data["signal_shift_+1"])* 2.0)))))))))+
0.050000*np.tanh(((data["medianbatch_slices2"])+(data["maxbatch_msignal"])))+
0.050000*np.tanh(np.minimum(((((( np.where(data["stdbatch_slices2"] > -998, data["abs_avgbatch_slices2"],(( np.sin(( np.sin(( data["abs_minbatch_slices2_msignal"])))))* 2.0)))+(((( data["maxtominbatch_slices2_msignal"])<=(data["mean_abs_chgbatch_slices2_msignal"])) *1.))) /2.0))),(( np.where(data["maxtominbatch_slices2_msignal"] > -998, np.sin(( np.sin(( data["meanbatch_msignal"])))) ,(( data["abs_avgbatch_slices2"])+(data["rangebatch_slices2"])))))))+
0.050000*np.tanh(((( 6.81191825866699219)) -(((data["abs_maxbatch"])*(((data["stdbatch_msignal"])*(data["mean_abs_chgbatch_slices2"])))))))+
0.050000*np.tanh(((np.sin(( np.where(np.sin(( np.where(data["abs_avgbatch_slices2"] > -998, data["minbatch_msignal"],(( np.sin(( data["stdbatch_slices2"])))* 2.0)))) > -998,(( data["minbatch_msignal"])-(data["stdbatch_slices2"])) ,(((( -(( np.tanh(((( data["stdbatch_slices2"])+(data["stdbatch_slices2"])))))))) <=(data["abs_avgbatch_slices2_msignal"])) *1.))))) * 2.0)) +
0.050000*np.tanh(((( 8.49771595001220703)) *(np.sin(((( data["maxbatch_slices2"])+(((np.sin(( data["abs_minbatch_msignal"])))+(np.where(( 2.64441561698913574)> -998, data["meanbatch_msignal"], np.where(data["abs_minbatch_msignal"] > -998, data["maxtominbatch_slices2"], np.cos(( data["medianbatch_slices2"])))))))))))))+
0.050000*np.tanh(np.cos(( np.where(np.cos(( data["minbatch"])) > -998, data["meanbatch_slices2"], np.where(data["mean_abs_chgbatch_slices2"] > -998,(( data["signal_shift_-1_msignal"])* 2.0), np.sin(( np.cos(( data["meanbatch_slices2_msignal"])))))))))+
0.050000*np.tanh(np.cos(( np.where(( -(((((( -(( data["abs_minbatch_slices2"])))) >(np.cos(( np.where(((((np.sin(((( np.tanh(( data["maxbatch_slices2"])))+(data["stdbatch_slices2_msignal"])))))* 2.0)) / 2.0)> -998, data["rangebatch_slices2_msignal"], data["abs_maxbatch_msignal"])))))*1.))))> -998,(-(( data["meanbatch_slices2"]))),(((data["stdbatch_slices2_msignal"])+(((data["signal"])-(data["rangebatch_slices2_msignal"])))) /2.0)))))+
0.050000*np.tanh(np.where(data["signal_shift_+1"] <= -998, np.where(np.where(data["medianbatch_msignal"] > -998, np.cos(( data["signal_shift_+1"])) , data["medianbatch_msignal"])> -998, np.maximum(((data["medianbatch_msignal"])) ,(( data["abs_avgbatch_slices2"]))), np.tanh(( data["minbatch"]))), data["abs_avgbatch_slices2"])) +
0.050000*np.tanh(((((((((((data["signal_shift_+1"])+(np.tanh(((9.14462471008300781)))))) * 2.0)) * 2.0)) * 2.0)) *(np.where(np.tanh(( data["signal_shift_+1"])) > -998, np.tanh(( np.tanh(((9.14462471008300781))))),(((9.14462471008300781)) +(np.tanh(((((((((np.tanh(((9.14462471008300781)))) / 2.0)) >(data["rangebatch_slices2_msignal"])) *1.))+(data["maxbatch_slices2_msignal"])))))))))) +
0.050000*np.tanh(( -(((((( data["signal_shift_+1"])*(((data["maxbatch_slices2_msignal"])+(np.where(data["signal_shift_+1"] <= -998, data["rangebatch_slices2_msignal"],(((-(( data["minbatch_msignal"])))) +(((((( data["meanbatch_slices2_msignal"])>(((( data["mean_abs_chgbatch_slices2"])>(( 14.58663940429687500)))*1.))) *1.))-(( -(( data["rangebatch_slices2_msignal"])))))))))))))* 2.0)))))+
0.050000*np.tanh(np.tanh(( np.sin(( np.where(((np.where(((( data["abs_avgbatch_msignal"])+(((( data["abs_maxbatch_slices2"])<=(data["meanbatch_slices2_msignal"])) *1.))) /2.0)> -998, data["signal_shift_-1_msignal"],(-(((((((np.where(data["maxtominbatch_msignal"] > -998, data["meanbatch_msignal"], data["meanbatch_slices2_msignal"])) * 2.0)) +(data["meanbatch_msignal"])) /2.0)))))) * 2.0)> -998, data["meanbatch_msignal"], data["meanbatch_msignal"])))))) +
0.050000*np.tanh(np.where(np.sin(((( data["abs_maxbatch_slices2"])-(data["abs_maxbatch_slices2"])))) <= -998, data["meanbatch_msignal"],(((data["medianbatch_msignal"])<=(np.sin(( data["maxbatch_slices2"])))) *1.))) +
0.050000*np.tanh(np.sin(( np.where(np.cos(( data["signal_shift_-1"])) <= -998, np.where(data["abs_avgbatch_msignal"] <= -998, data["abs_maxbatch_slices2_msignal"],(((((((0.0)) <=(((( data["minbatch_slices2_msignal"])<=(data["rangebatch_slices2_msignal"])) *1.))) *1.))<=(data["abs_minbatch_slices2"])) *1.)), np.minimum(((data["stdbatch_slices2_msignal"])) ,(((((((((data["abs_maxbatch_slices2"])>(np.sin(((9.0)))))*1.))+(data["minbatch_msignal"])))* 2.0)))))))) +
0.050000*np.tanh(data["abs_maxbatch_slices2"])+
0.050000*np.tanh(((((( 7.0)) -(data["abs_maxbatch"])))-(np.where(data["rangebatch_slices2"] <= -998,(( np.tanh(( np.sin(((((7.0)) -(np.where(data["abs_minbatch_slices2"] <= -998,(( data["abs_minbatch_slices2"])/ 2.0), data["abs_maxbatch_slices2"])))))))) / 2.0), np.sin(( data["abs_maxbatch"])))))) +
0.050000*np.tanh(((np.cos(( data["mean_abs_chgbatch_slices2_msignal"])))+(np.where(data["rangebatch_slices2_msignal"] > -998,(( data["signal_shift_-1_msignal"])*(data["abs_avgbatch_slices2"])) , np.sin(((( np.sin(( np.minimum(((data["signal_shift_-1_msignal"])) ,(( data["abs_maxbatch_slices2"])))))) *(( 10.54265403747558594)))))))))+
0.050000*np.tanh(((np.cos(( data["meanbatch_slices2"])))*(((data["minbatch_msignal"])*(np.where(np.minimum(((data["stdbatch_msignal"])) ,(( data["signal_shift_-1_msignal"])))<= -998, np.minimum(((data["meanbatch_slices2"])) ,(( data["signal_shift_-1_msignal"]))), np.where(data["minbatch_slices2_msignal"] <= -998, data["rangebatch_slices2"], np.tanh(((( data["minbatch_slices2_msignal"])+(data["stdbatch_msignal"])))))))))))+
0.050000*np.tanh(((np.sin(( np.where(np.where(data["medianbatch_slices2_msignal"] <= -998, data["minbatch_msignal"], data["meanbatch_slices2"])> -998, data["abs_avgbatch_slices2_msignal"], np.tanh(((( data["meanbatch_slices2"])+(data["signal_shift_-1"])))))))) *(np.maximum(((data["maxtominbatch_slices2_msignal"])) ,(( data["medianbatch_slices2_msignal"])))))) +
0.050000*np.tanh(((np.sin(( np.cos(((((( data["abs_minbatch_slices2_msignal"])*(np.where(np.minimum(((((data["abs_minbatch_slices2_msignal"])*(np.where(( 14.50428867340087891)> -998, data["abs_avgbatch_slices2_msignal"], data["medianbatch_slices2"]))))),(( data["meanbatch_msignal"])))> -998, data["signal_shift_-1"], data["abs_maxbatch"])))) -(data["stdbatch_slices2"])))))))* 2.0)) +
0.050000*np.tanh(((np.cos(( np.where(data["maxbatch_slices2_msignal"] <= -998, data["medianbatch_slices2_msignal"], np.tanh(( data["maxbatch_slices2"])))))) +(((data["abs_maxbatch_msignal"])*(np.sin(( data["medianbatch_msignal"])))))))+
0.050000*np.tanh(((((((np.tanh(( np.sin(( data["meanbatch_slices2_msignal"])))))+(((np.cos(( np.maximum(((data["stdbatch_slices2_msignal"])) ,(( np.maximum(((data["abs_minbatch_slices2"])) ,(( data["stdbatch_msignal"])))))))))* 2.0)))) * 2.0)) * 2.0)) +
0.050000*np.tanh(((np.where(( -(( np.where(data["abs_minbatch_slices2_msignal"] > -998, data["abs_minbatch_slices2_msignal"],(((( np.sin(( data["medianbatch_msignal"])))* 2.0)) * 2.0)))))<= -998,(( data["abs_minbatch_slices2_msignal"])/ 2.0),(( np.where(((( data["signal_shift_-1"])<=(((( data["medianbatch_msignal"])<=(data["signal_shift_-1"])) *1.))) *1.) > -998, np.sin(( data["medianbatch_msignal"])) , np.sin(( data["medianbatch_msignal"])))) * 2.0)))-(data["signal_shift_+1"])))+
0.050000*np.tanh(((data["abs_avgbatch_slices2_msignal"])-(((np.where(data["maxtominbatch_slices2_msignal"] > -998,(( np.where(( 1.0)> -998, data["signal"], data["mean_abs_chgbatch_slices2"])) * 2.0), np.where(( -(( data["rangebatch_msignal"])))<= -998, data["maxbatch_slices2"],(((( data["abs_maxbatch_slices2_msignal"])+(data["abs_maxbatch_slices2_msignal"])))*(np.tanh(((-(( data["maxtominbatch_slices2_msignal"])))))))))) *(((data["maxtominbatch_msignal"])+(data["abs_maxbatch_slices2_msignal"])))))))+
0.050000*np.tanh(data["maxbatch_slices2"])+
0.050000*np.tanh(((((data["abs_minbatch_slices2"])+(data["abs_minbatch_msignal"])))*(((np.maximum(((data["abs_minbatch_msignal"])) ,(( np.maximum(((data["signal"])) ,(( data["abs_avgbatch_slices2_msignal"])))))))*(data["meanbatch_slices2"])))))+
0.050000*np.tanh(np.sin(( np.sin(((((( data["medianbatch_slices2_msignal"])-(np.minimum(((data["maxtominbatch_slices2_msignal"])) ,(( np.minimum(((data["maxtominbatch_slices2_msignal"])) ,(( np.minimum(((np.sin(((( np.cos(( np.sin(((( data["abs_maxbatch_msignal"])+(( 13.72685527801513672)))))))) +(data["mean_abs_chgbatch_slices2_msignal"])))))) ,(( np.sin(( np.sin(( data["signal_shift_+1_msignal"])))))))))))))))) * 2.0)))))) +
0.050000*np.tanh(np.cos(((( np.where(((data["maxbatch_slices2"])+(np.sin(( np.cos(((-(( np.cos(( data["meanbatch_slices2"])))))))))))<= -998,(((data["minbatch_slices2_msignal"])<=(((np.maximum(((data["abs_avgbatch_slices2"])) ,(( np.cos(( data["meanbatch_slices2"])))))) +(((data["medianbatch_slices2"])* 2.0)))))*1.) , np.minimum(((((data["meanbatch_slices2"])/ 2.0))),(((-(( data["abs_minbatch_msignal"])))))))) * 2.0)))) +
0.050000*np.tanh(((((data["stdbatch_slices2_msignal"])* 2.0)) +(np.tanh(((((((( np.maximum(((data["abs_avgbatch_msignal"])) ,(( np.sin(( np.maximum(((data["abs_avgbatch_msignal"])) ,(( data["abs_avgbatch_slices2"])))))))))+(data["signal"])) /2.0)) +(data["stdbatch_slices2_msignal"])) /2.0)))))) +
0.050000*np.tanh(np.cos(((( data["maxtominbatch_msignal"])+(np.where(data["signal"] <= -998, np.where(((((( data["medianbatch_slices2"])<=(((data["abs_minbatch_msignal"])-(( -(( np.maximum(((data["signal_shift_+1"])) ,(( data["minbatch_slices2"])))))))))) *1.))-(( -(( np.cos(( data["medianbatch_msignal"])))))))<= -998,(((((data["abs_minbatch_slices2_msignal"])+(data["medianbatch_msignal"])) /2.0)) / 2.0), data["minbatch_slices2"]), data["medianbatch_msignal"])))))) +
0.050000*np.tanh(np.maximum(((((data["meanbatch_msignal"])*(((((( data["meanbatch_slices2_msignal"])+(((data["meanbatch_msignal"])*(((((( data["maxtominbatch_slices2_msignal"])+(data["maxtominbatch_slices2_msignal"])) /2.0)) / 2.0)))))/2.0)) / 2.0))))),(( np.cos(((( data["signal_shift_-1"])-(np.where(data["signal_shift_-1"] <= -998, data["rangebatch_slices2_msignal"], np.tanh(( data["maxtominbatch_slices2_msignal"])))))))))))+
0.050000*np.tanh(np.cos(( np.where(( 0.56028139591217041)> -998,(( data["stdbatch_msignal"])-(((np.tanh(( data["rangebatch_slices2_msignal"])))-(data["rangebatch_slices2_msignal"])))) ,(( data["stdbatch_slices2"])*(((np.cos(((((((( np.tanh(( data["signal_shift_-1_msignal"])))* 2.0)) *(data["stdbatch_msignal"])))-(data["medianbatch_slices2"])))))-(((data["meanbatch_slices2_msignal"])*(data["minbatch"])))))))))) +
0.050000*np.tanh(np.where(data["stdbatch_slices2"] > -998,(( data["maxbatch_slices2_msignal"])-(((((data["maxbatch_slices2"])*(((((( 4.00822257995605469)) *(data["signal_shift_-1"])))*(data["signal"])))))*(data["maxbatch_msignal"])))) ,(((( data["meanbatch_slices2_msignal"])*(((data["abs_maxbatch_slices2"])*(np.tanh(( np.cos(( data["abs_maxbatch_slices2"])))))))))+(((data["abs_maxbatch_slices2"])-(data["stdbatch_slices2"])))))) +
0.050000*np.tanh(np.where(np.where(( -(((((np.sin(( np.sin(( data["meanbatch_msignal"])))))>(data["signal_shift_+1_msignal"])) *1.))))<= -998, data["meanbatch_msignal"],(((((( np.sin(( data["meanbatch_msignal"])))-(np.sin(( data["meanbatch_slices2"])))))* 2.0)) * 2.0)) <= -998, np.sin(( np.where(data["abs_maxbatch_slices2_msignal"] <= -998, data["signal_shift_+1"], data["signal_shift_+1"]))),(( np.sin(( data["meanbatch_msignal"])))* 2.0)))+
0.050000*np.tanh(((data["rangebatch_slices2_msignal"])+(np.where(((data["abs_minbatch_msignal"])*(((data["maxtominbatch_slices2_msignal"])-(data["meanbatch_msignal"])))) > -998,(((( data["maxtominbatch_slices2_msignal"])-(data["meanbatch_msignal"])))* 2.0),(( data["rangebatch_slices2_msignal"])-(np.where(data["meanbatch_msignal"] > -998,(((( data["maxtominbatch_slices2_msignal"])-(data["meanbatch_msignal"])))* 2.0),(( data["meanbatch_msignal"])-(data["maxtominbatch_slices2_msignal"])))))))))+
0.050000*np.tanh(((((( data["meanbatch_msignal"])+(np.where(((data["maxbatch_slices2"])* 2.0)<= -998, data["meanbatch_slices2_msignal"], data["medianbatch_slices2"])))) +(((((((data["maxtominbatch_slices2_msignal"])*(((data["mean_abs_chgbatch_slices2_msignal"])-(data["meanbatch_slices2_msignal"])))))*(data["minbatch"])))* 2.0)))/2.0)) +
0.050000*np.tanh(data["maxbatch_slices2_msignal"])+
0.050000*np.tanh(((( np.maximum(((data["maxbatch_slices2"])) ,(( np.where(np.sin(( np.where(data["signal_shift_-1"] <= -998,(2.78504920005798340),(((np.where(data["maxbatch_slices2"] > -998, data["rangebatch_slices2_msignal"], np.tanh(((12.91273593902587891)))))+(data["rangebatch_slices2_msignal"])) /2.0)))) > -998, data["stdbatch_slices2"], data["maxbatch_slices2"])))))+(np.maximum(((data["maxbatch_slices2_msignal"])) ,(( data["mean_abs_chgbatch_slices2"])))))/2.0)) +
0.050000*np.tanh(((data["abs_avgbatch_msignal"])-(np.where(data["stdbatch_slices2_msignal"] > -998, data["minbatch_slices2"],(-(( np.minimum(((data["maxbatch_slices2"])) ,(( np.minimum(((data["abs_minbatch_slices2"])) ,(( data["signal"])))))))))))))+
0.050000*np.tanh(((data["medianbatch_slices2"])*(np.where(np.maximum(((((data["abs_minbatch_slices2_msignal"])*(data["medianbatch_slices2"])))) ,(( data["medianbatch_slices2_msignal"])))<= -998, data["maxtominbatch_slices2_msignal"], data["maxtominbatch_msignal"])))) +
0.050000*np.tanh(((((np.sin(((( np.maximum(((data["abs_maxbatch_slices2"])) ,(((-(( data["meanbatch_slices2"])))))))-(data["minbatch_msignal"])))))*(np.maximum(((np.sin(((-(( data["meanbatch_slices2"]))))))),(( data["maxbatch_msignal"])))))) * 2.0)) +
0.050000*np.tanh(((np.sin(((( data["meanbatch_msignal"])-(np.tanh(((((data["maxtominbatch"])+(((( data["stdbatch_msignal"])<=(((data["signal_shift_+1_msignal"])-(((np.cos(((( data["rangebatch_msignal"])-(np.sin(( data["signal_shift_+1"])))))))* 2.0)))))*1.))) /2.0)))))))) * 2.0)) +
0.050000*np.tanh(np.where(np.where(((( data["medianbatch_msignal"])>(data["signal_shift_-1"])) *1.) > -998, data["maxbatch_msignal"], data["stdbatch_slices2_msignal"])> -998, np.where(np.maximum(((data["maxbatch_msignal"])) ,(( data["mean_abs_chgbatch_slices2"])))<= -998, np.where(data["abs_maxbatch_slices2"] <= -998,(0.0), data["rangebatch_slices2_msignal"]), data["abs_maxbatch_msignal"]), np.where(data["rangebatch_msignal"] <= -998, np.cos(( data["signal_shift_-1"])) , data["maxbatch_msignal"])))+
0.050000*np.tanh(np.cos(((( data["maxtominbatch_msignal"])-(np.where(((( np.where(data["mean_abs_chgbatch_slices2_msignal"] <= -998, data["abs_maxbatch"], data["maxtominbatch_msignal"])) +(((((((data["maxtominbatch_msignal"])>(np.sin(( data["abs_avgbatch_slices2"])))) *1.))<=(data["abs_avgbatch_slices2"])) *1.))) /2.0)> -998, data["signal_shift_+1"], np.maximum(((((( data["abs_avgbatch_msignal"])<=(data["maxbatch_msignal"])) *1.))) ,(( data["medianbatch_slices2"])))))))))+
0.050000*np.tanh(np.cos(((((( data["abs_maxbatch_slices2"])/ 2.0)) *(np.minimum(((data["signal_shift_+1"])) ,(((((np.cos(((((data["medianbatch_slices2"])<=(np.cos(((((data["rangebatch_slices2"])<=(data["abs_maxbatch_slices2"])) *1.))))) *1.))))+(np.cos(( data["medianbatch_msignal"])))) /2.0)))))))))+
0.050000*np.tanh(data["maxbatch_slices2"])+
0.050000*np.tanh(np.cos(((( data["rangebatch_slices2_msignal"])-(np.where(((data["rangebatch_slices2_msignal"])+(data["maxtominbatch_slices2_msignal"])) > -998,(-(( data["abs_minbatch_slices2_msignal"]))), data["maxtominbatch_msignal"])))))) +
0.050000*np.tanh(np.where(data["minbatch"] <= -998, np.cos(( np.tanh(((( data["maxtominbatch_slices2_msignal"])*(data["signal_shift_+1_msignal"])))))) ,(((((( 4.0)) +(np.tanh(( np.tanh(( data["minbatch"])))))) /2.0)) *(np.cos(((( data["maxtominbatch_slices2_msignal"])+(data["medianbatch_slices2_msignal"])))))))) +
0.050000*np.tanh(((np.maximum(((data["signal_shift_+1_msignal"])) ,(( np.where(((data["rangebatch_slices2_msignal"])+(data["meanbatch_slices2"])) <= -998,(( data["rangebatch_slices2_msignal"])+(data["abs_maxbatch_msignal"])) , data["rangebatch_slices2_msignal"])))))*(np.maximum(((( 0.0))),(( data["rangebatch_slices2_msignal"])))))) +
0.050000*np.tanh(((data["maxtominbatch_msignal"])*(np.sin(( np.minimum(((data["minbatch_slices2_msignal"])) ,(( np.minimum(((data["abs_maxbatch_slices2_msignal"])) ,(((-(( np.maximum(((np.minimum(((np.minimum(((data["minbatch_slices2_msignal"])) ,(((-(( np.minimum(((data["medianbatch_slices2"])) ,(( np.minimum(((data["abs_avgbatch_slices2"])) ,(( data["maxtominbatch_msignal"])))))))))))))) ,(((-(( np.maximum(((data["maxtominbatch_msignal"])) ,(( data["abs_avgbatch_slices2"]))))))))))),(( data["abs_avgbatch_slices2"])))))))))))))))))+
0.050000*np.tanh(np.where(data["meanbatch_slices2_msignal"] > -998, np.sin(((((((( -(( np.minimum(((data["minbatch_msignal"])) ,(( data["stdbatch_slices2_msignal"])))))))*(data["maxbatch_msignal"])))+(((data["mean_abs_chgbatch_slices2_msignal"])-(((((( 7.0)) / 2.0)) +(((( data["maxbatch_msignal"])<=(data["abs_maxbatch_slices2_msignal"])) *1.))))))) /2.0))), data["mean_abs_chgbatch_slices2_msignal"])) +
0.050000*np.tanh(np.maximum(((((((( data["maxbatch_slices2_msignal"])*(( 7.0)))) >(((( data["abs_avgbatch_slices2_msignal"])+(data["stdbatch_slices2"])) /2.0)))*1.))) ,(( data["maxtominbatch_slices2"])))) +
0.050000*np.tanh(((((( np.sin(( np.tanh(( data["mean_abs_chgbatch_msignal"])))))<=(((((((((data["signal_shift_-1"])<=(data["signal_shift_-1"])) *1.))<=(data["abs_minbatch_slices2"])) *1.))* 2.0)))*1.))/ 2.0)) +
0.050000*np.tanh(((data["signal_shift_+1_msignal"])*(((((data["mean_abs_chgbatch_msignal"])*(data["abs_maxbatch"])))+(np.cos(( data["abs_maxbatch_slices2"]))))))))
def GP_class_3(self,data):
return self.Output(-2.012666 +
0.050000*np.tanh(((np.cos(( data["abs_maxbatch_msignal"])))+(((data["abs_maxbatch_msignal"])*(np.cos(( np.where(np.where(((data["abs_maxbatch_msignal"])*(np.cos(( data["rangebatch_slices2"])))) > -998, data["mean_abs_chgbatch_msignal"],(( data["stdbatch_msignal"])*(np.maximum(((( 3.29916071891784668))),(( data["mean_abs_chgbatch_slices2_msignal"])))))) > -998, data["stdbatch_msignal"],(-(((((-(( data["stdbatch_msignal"])))) * 2.0)))))))))))) +
0.050000*np.tanh(((((np.where(( -(((14.68631076812744141)))) > -998, np.where(data["minbatch"] > -998, data["abs_avgbatch_slices2_msignal"], np.where(np.minimum(((data["abs_minbatch_msignal"])) ,(( data["signal"])))<= -998,(( data["abs_maxbatch_slices2"])+(( 2.92223882675170898))), data["abs_avgbatch_slices2_msignal"])) , data["signal"])) *(np.where(np.tanh(( data["signal"])) <= -998, data["rangebatch_slices2_msignal"], data["signal"])))) * 2.0)) +
0.050000*np.tanh(((((data["abs_avgbatch_msignal"])*(((data["signal"])*(( 4.58320951461791992)))))) -(((((((( data["abs_avgbatch_msignal"])+(data["medianbatch_slices2"])))>(np.where(data["minbatch_msignal"] <= -998,(4.58320951461791992), data["signal"])))*1.))+(data["signal"])))))+
0.050000*np.tanh(((((data["abs_avgbatch_msignal"])*(np.where(np.minimum(((data["signal"])) ,(((( data["abs_avgbatch_msignal"])*(data["maxtominbatch_msignal"])))))> -998, data["signal"], np.minimum(((data["abs_avgbatch_slices2"])) ,(( np.where(data["signal_shift_-1"] <= -998,(( np.minimum(((data["abs_minbatch_slices2_msignal"])) ,(( data["mean_abs_chgbatch_msignal"])))) *(data["signal"])) ,(-(( data["signal"])))))))))))* 2.0)) +
0.050000*np.tanh(((((( 3.0)) *(data["signal"])))*(np.cos(((((((np.minimum(((((np.cos(( np.tanh(( data["signal"])))))*(data["signal"])))) ,(((3.0)))))<=(((data["signal_shift_+1"])*(((( 3.0)) *(data["signal"])))))) *1.))+(np.sin(( data["abs_maxbatch"])))))))))+
0.050000*np.tanh(((((data["signal"])*(((data["abs_avgbatch_msignal"])*(np.maximum(((((( 9.0)) * 2.0))),(((( np.maximum(((((data["abs_minbatch_msignal"])-(data["abs_maxbatch_slices2"])))) ,(( data["abs_avgbatch_msignal"])))) * 2.0)))))))))-(((data["signal"])+(np.maximum(((np.cos(( data["signal_shift_+1"])))) ,(( data["medianbatch_slices2"])))))))) +
0.050000*np.tanh(np.where(data["abs_avgbatch_msignal"] <= -998, data["abs_avgbatch_msignal"],(( data["signal"])*(((np.cos(( data["stdbatch_slices2_msignal"])))+(((data["stdbatch_msignal"])+(np.cos(( data["stdbatch_msignal"])))))))))) +
0.050000*np.tanh(((data["minbatch_slices2"])*(((data["abs_minbatch_slices2_msignal"])-(((((((( data["meanbatch_slices2"])*(((( data["abs_minbatch_slices2_msignal"])+(np.sin(((((0.0)) *(data["abs_minbatch_msignal"])))))) /2.0)))) <=(np.cos(( data["abs_avgbatch_msignal"])))) *1.))+(((data["signal"])*(((( data["mean_abs_chgbatch_slices2_msignal"])+(( -(( data["meanbatch_slices2"])))))/2.0)))))))))) +
0.050000*np.tanh(((((np.sin(( np.where(data["abs_maxbatch_msignal"] <= -998,(( np.where(data["maxbatch_slices2"] > -998, np.cos(( data["mean_abs_chgbatch_slices2_msignal"])) , data["signal_shift_-1"])) *(((np.cos(( data["mean_abs_chgbatch_slices2_msignal"])))/ 2.0))), data["signal"])))) * 2.0)) * 2.0)) +
0.050000*np.tanh(((((np.cos(((((data["stdbatch_msignal"])+(((( data["stdbatch_msignal"])+(((data["stdbatch_msignal"])* 2.0)))/2.0)))/2.0)))) * 2.0)) * 2.0)) +
0.050000*np.tanh(((np.where(data["minbatch_msignal"] <= -998, data["maxtominbatch_msignal"], np.minimum(((((data["signal"])-(((np.where(np.sin(( data["minbatch_msignal"])) > -998, data["abs_minbatch_msignal"], data["stdbatch_msignal"])) / 2.0))))),(((((((( np.minimum(((data["signal"])) ,(( np.sin(( data["signal"])))))) * 2.0)) * 2.0)) -(data["abs_minbatch_slices2"])))))))* 2.0)) +
0.050000*np.tanh(np.minimum(((np.sin(( np.maximum(((data["signal"])) ,(( np.maximum(((((((data["stdbatch_slices2"])/ 2.0)) / 2.0))),(( np.sin(( data["signal"])))))))))))) ,(( data["signal"])))) +
0.050000*np.tanh(((((((np.where(np.tanh(( data["signal"])) > -998, np.cos(( data["stdbatch_slices2"])) ,(-(( data["abs_minbatch_slices2"])))))* 2.0)) *(data["maxbatch_msignal"])))*(np.where(data["signal"] > -998, data["signal"], data["maxtominbatch_slices2_msignal"])))) +
0.050000*np.tanh(((((np.minimum(((np.cos(( np.where(data["rangebatch_msignal"] > -998, data["stdbatch_slices2_msignal"],(( np.minimum(((((np.sin(( data["maxbatch_slices2"])))* 2.0))),(( np.cos(((((( data["rangebatch_slices2"])/ 2.0)) / 2.0)))))))* 2.0)))))) ,(( np.cos(( data["abs_minbatch_msignal"])))))) * 2.0)) * 2.0)) +
0.050000*np.tanh(((data["signal"])*(((np.where(((data["signal"])*(np.maximum(((np.sin(((( data["abs_avgbatch_slices2_msignal"])*(data["abs_avgbatch_slices2_msignal"])))))) ,(( data["maxtominbatch"])))))> -998,(( np.where(data["abs_avgbatch_slices2_msignal"] > -998, data["abs_avgbatch_slices2_msignal"], data["signal_shift_-1"])) * 2.0),(( data["mean_abs_chgbatch_slices2"])/ 2.0)))* 2.0)))) +
0.050000*np.tanh(((((((((np.minimum(((((((np.minimum(((data["signal"])) ,(( np.cos(( np.minimum(((data["signal"])) ,(( np.minimum(((data["abs_minbatch_slices2_msignal"])) ,(( np.cos(( np.minimum(((data["abs_avgbatch_slices2_msignal"])) ,(( np.cos(((-(( data["abs_minbatch_slices2_msignal"])))))))))))))))))))))) * 2.0)) * 2.0))),(((( data["rangebatch_slices2_msignal"])* 2.0)))))* 2.0)) * 2.0)) * 2.0)) -(np.cos(( data["signal"])))))+
0.050000*np.tanh(((((data["signal"])*(((np.maximum(((data["mean_abs_chgbatch_msignal"])) ,(( np.cos(((( data["signal"])-(np.cos(((((data["signal"])+(np.minimum(((((data["signal"])*(data["abs_maxbatch"])))) ,(((( data["signal"])* 2.0)))))) /2.0)))))))))))* 2.0)))) * 2.0)) +
0.050000*np.tanh(((np.minimum(((((np.minimum(((((((((np.minimum(((((np.cos(( np.maximum(((data["signal"])) ,(( data["abs_maxbatch"])))))) -(np.sin(( data["maxtominbatch_msignal"])))))) ,(( np.sin(( data["maxtominbatch_msignal"])))))) -(np.sin(( data["maxtominbatch_msignal"])))))* 2.0)) -(np.sin(( data["maxtominbatch_msignal"])))))) ,(( np.sin(( data["signal"])))))) * 2.0))),(( data["signal"])))) * 2.0)) +
0.050000*np.tanh(((np.where(((((data["maxbatch_slices2"])-(data["maxtominbatch_slices2_msignal"])))-(data["maxtominbatch"])) <= -998, np.maximum(((data["signal"])) ,(( data["rangebatch_slices2_msignal"]))), data["abs_minbatch_msignal"])) *(((((data["signal"])-(data["mean_abs_chgbatch_slices2"])))-(data["abs_maxbatch_slices2"])))))+
0.050000*np.tanh(((((np.where(data["maxtominbatch_slices2_msignal"] <= -998, np.where(data["maxtominbatch_slices2_msignal"] <= -998,(( np.where(data["maxtominbatch_slices2_msignal"] <= -998,(((data["abs_avgbatch_msignal"])<=(((((np.where(data["abs_minbatch_slices2_msignal"] <= -998, data["abs_minbatch_slices2_msignal"], np.cos(( data["abs_minbatch_slices2_msignal"])))) * 2.0)) * 2.0)))*1.) , np.cos(( data["abs_minbatch_slices2_msignal"])))) * 2.0), np.cos(( data["abs_minbatch_slices2_msignal"]))), np.cos(( data["abs_minbatch_slices2_msignal"])))) * 2.0)) * 2.0)) +
0.050000*np.tanh(((data["minbatch_msignal"])*(np.sin(( data["maxtominbatch_msignal"])))))+
0.050000*np.tanh(((np.sin(( np.minimum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(( np.minimum(((((np.where(data["signal"] > -998, data["minbatch_msignal"], data["maxbatch_msignal"])) +(data["mean_abs_chgbatch_slices2_msignal"])))) ,(((( np.sin(( data["minbatch_msignal"])))* 2.0)))))))))) * 2.0)) +
0.050000*np.tanh(((data["medianbatch_slices2"])+(((data["medianbatch_slices2"])+(((data["rangebatch_msignal"])*(np.minimum(((data["signal"])) ,(((((((((data["stdbatch_slices2_msignal"])*(np.cos(((( data["stdbatch_slices2_msignal"])/ 2.0)))))) <=(np.sin(( data["rangebatch_msignal"])))) *1.))+(((data["rangebatch_msignal"])*(np.minimum(((np.cos(( data["abs_avgbatch_msignal"])))) ,(( np.cos(( data["signal"])))))))))))))))))))+
0.050000*np.tanh(((np.where(data["medianbatch_slices2"] > -998, data["rangebatch_slices2"],(( data["abs_avgbatch_slices2"])*(((np.sin(( data["abs_avgbatch_slices2"])))* 2.0)))))*(((((data["signal"])*(((np.sin(( data["abs_avgbatch_slices2"])))* 2.0)))) * 2.0)))) +
0.050000*np.tanh(((((data["rangebatch_slices2_msignal"])+(((data["stdbatch_slices2_msignal"])-(np.maximum(((data["maxtominbatch_msignal"])) ,(((( np.maximum(((data["mean_abs_chgbatch_msignal"])) ,(( data["medianbatch_slices2_msignal"])))) * 2.0)))))))))+(((data["stdbatch_slices2_msignal"])-(((data["mean_abs_chgbatch_msignal"])*(data["maxtominbatch_msignal"])))))))+
0.050000*np.tanh(np.where(((((( data["signal_shift_-1"])* 2.0)) >(((np.cos(( data["stdbatch_slices2_msignal"])))* 2.0)))*1.) <= -998, data["minbatch_slices2"], np.maximum(((data["minbatch_slices2"])) ,(( np.where(data["stdbatch_slices2_msignal"] <= -998, data["mean_abs_chgbatch_msignal"],(((( np.cos(( data["stdbatch_slices2_msignal"])))* 2.0)) * 2.0)))))))+
0.050000*np.tanh(np.where(((((data["stdbatch_msignal"])*(data["medianbatch_slices2"])))* 2.0)<= -998, data["maxtominbatch_msignal"],(((((( data["stdbatch_slices2_msignal"])*(data["medianbatch_slices2"])))-(np.where(data["abs_minbatch_msignal"] <= -998,(( data["stdbatch_msignal"])* 2.0), np.where(((np.sin(( data["maxtominbatch_msignal"])))* 2.0)<= -998, data["stdbatch_slices2_msignal"], np.sin(( data["maxtominbatch_msignal"])))))))* 2.0)))+
0.050000*np.tanh(((((np.minimum(((( -(( data["mean_abs_chgbatch_slices2_msignal"]))))),(((( np.minimum(((((data["signal"])*(np.minimum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(((( data["stdbatch_msignal"])*(data["maxbatch_slices2"]))))))))),(( data["signal"])))) *(data["maxbatch_slices2"])))))) +(data["maxbatch_slices2"])))+(data["stdbatch_slices2"])))+
0.050000*np.tanh(np.where(((((np.where(np.tanh(( data["abs_minbatch_msignal"])) > -998, data["signal_shift_-1"], data["mean_abs_chgbatch_slices2"])) * 2.0)) *(data["mean_abs_chgbatch_slices2"])) <= -998, np.where(data["maxbatch_slices2"] <= -998, np.minimum(((np.minimum(((( 6.92917728424072266))),(( data["signal_shift_-1_msignal"]))))),(( data["stdbatch_msignal"]))), data["minbatch_slices2"]),(((((( data["signal"])*(np.cos(( data["stdbatch_slices2"])))))* 2.0)) *(data["abs_maxbatch"])))) +
0.050000*np.tanh(( -(((( np.where(((((((( 3.0)) <=(((((((np.cos(((-(((( data["meanbatch_slices2"])* 2.0)))))))+(data["minbatch_msignal"])) /2.0)) >(data["maxtominbatch_msignal"])) *1.))) *1.))+(( 6.0)))/2.0)> -998, np.sin(( data["maxtominbatch_msignal"])) , data["meanbatch_slices2"])) * 2.0)))))+
0.050000*np.tanh(((( 5.61153316497802734)) *(((np.minimum(((( -(( data["mean_abs_chgbatch_slices2_msignal"]))))),(( data["mean_abs_chgbatch_slices2_msignal"])))) +(((np.cos(( data["abs_minbatch_slices2_msignal"])))+(np.cos(( data["abs_avgbatch_slices2_msignal"])))))))))+
0.050000*np.tanh(((np.where(data["abs_maxbatch_slices2"] <= -998, data["abs_minbatch_msignal"], np.cos(( data["abs_minbatch_msignal"])))) * 2.0)) +
0.050000*np.tanh(np.sin(((( np.where(np.minimum(((((data["mean_abs_chgbatch_slices2"])* 2.0))),(( np.sin(( np.sin(((((data["abs_maxbatch"])+(data["rangebatch_msignal"])) /2.0)))))))) > -998, data["signal"], data["abs_maxbatch"])) * 2.0)))) +
0.050000*np.tanh(((np.where(((data["signal"])*(( -(((( data["rangebatch_slices2"])* 2.0)))))) > -998,(( data["signal"])* 2.0),(( data["rangebatch_slices2"])*(data["maxtominbatch"])))) *(np.tanh(( np.where(((((data["maxtominbatch_msignal"])* 2.0)) * 2.0)<= -998, np.cos(( data["minbatch_msignal"])) ,(((11.20401573181152344)) +(((((data["maxtominbatch_msignal"])* 2.0)) * 2.0)))))))))+
0.050000*np.tanh(((((data["abs_avgbatch_slices2"])*(((np.sin(( data["minbatch_msignal"])))-(np.maximum(((data["abs_avgbatch_slices2_msignal"])) ,(( data["signal_shift_-1"])))))))) +(((((( np.sin(( data["abs_avgbatch_slices2_msignal"])))+(data["abs_avgbatch_slices2"])) /2.0)) *(((np.sin(( data["abs_avgbatch_slices2"])))* 2.0)))))) +
0.050000*np.tanh(((( 6.0)) *(np.where(data["stdbatch_slices2"] <= -998, data["signal_shift_+1"], np.where(data["abs_maxbatch_slices2_msignal"] <= -998,(6.0), np.sin(( np.where(data["signal"] > -998, data["signal"], data["signal"])))))))) +
0.050000*np.tanh(((np.minimum(((((data["abs_maxbatch_slices2"])*(data["signal"])))) ,(( data["abs_avgbatch_slices2"])))) -(((((((((((( np.sin(( data["stdbatch_slices2_msignal"])))<=(data["abs_avgbatch_slices2_msignal"])) *1.))/ 2.0)) +(((data["signal_shift_+1"])*(data["abs_avgbatch_slices2_msignal"])))) /2.0)) +(((data["minbatch"])*(((data["signal_shift_+1"])*(data["stdbatch_slices2_msignal"])))))) /2.0)))) +
0.050000*np.tanh(((( 14.12239265441894531)) *(((np.minimum(((data["abs_avgbatch_slices2_msignal"])) ,(( np.cos(( np.where(np.maximum(((data["stdbatch_slices2"])) ,(( np.cos(( data["minbatch"])))))> -998,(( data["stdbatch_slices2_msignal"])* 2.0),(( data["stdbatch_slices2_msignal"])* 2.0)))))))) / 2.0)))) +
0.050000*np.tanh(((data["signal"])-(( -(((( data["maxbatch_slices2"])*(np.where(( -(( data["stdbatch_msignal"])))<= -998,(( np.cos(( data["signal"])))*(data["abs_maxbatch_slices2"])) ,(((data["abs_minbatch_slices2_msignal"])+(np.cos(((( data["stdbatch_msignal"])* 2.0)))))/2.0)))))))))) +
0.050000*np.tanh(np.where(( -(( data["maxtominbatch_msignal"])))<= -998,(((( data["signal"])* 2.0)) +(((data["stdbatch_msignal"])*(((data["signal"])*(data["signal"])))))) ,(((10.0)) *(np.cos(( data["abs_minbatch_slices2_msignal"])))))) +
0.050000*np.tanh(((np.sin(( np.maximum(((data["meanbatch_slices2"])) ,(((( np.sin(( np.maximum(((data["meanbatch_slices2"])) ,(( np.where(np.maximum(((data["meanbatch_slices2"])) ,(( np.where(((data["stdbatch_slices2_msignal"])*(data["minbatch_slices2"])) <= -998,(( data["meanbatch_slices2"])/ 2.0), data["signal"])))) <= -998, np.sin(((((-(((( data["meanbatch_slices2"])* 2.0)))))/ 2.0))), data["signal"])))))))* 2.0)))))))* 2.0)) +
0.050000*np.tanh(((((data["signal"])*(((data["rangebatch_slices2_msignal"])*(((data["signal"])*(((data["rangebatch_slices2_msignal"])*(np.sin(( np.cos(( np.where(data["rangebatch_slices2_msignal"] <= -998, np.tanh(( data["signal"])) , data["signal"])))))))))))))) *(((data["signal"])+(((data["signal"])*(np.sin(((6.0)))))))))) +
0.050000*np.tanh(np.minimum(((np.minimum(((np.tanh(( np.where(np.sin(( np.cos(((( data["abs_avgbatch_slices2_msignal"])*(np.where(data["mean_abs_chgbatch_slices2_msignal"] <= -998, data["abs_maxbatch_slices2_msignal"],(0.62379610538482666)))))))) > -998,(( data["abs_avgbatch_slices2_msignal"])* 2.0), np.cos(( data["stdbatch_slices2"]))))))),(( np.minimum(((data["signal"])) ,(((( np.cos(( data["medianbatch_slices2"])))* 2.0))))))))),(((7.0)))))+
0.050000*np.tanh(np.minimum(((np.sin(((-(( data["maxtominbatch_slices2_msignal"]))))))),(((((((np.where(((np.sin(( data["abs_avgbatch_msignal"])))+(((( data["maxbatch_slices2"])+(((( data["abs_avgbatch_msignal"])<=(np.cos(( data["maxtominbatch_slices2_msignal"])))) *1.))) /2.0)))<= -998, data["meanbatch_msignal"],(( data["maxbatch_slices2"])* 2.0)))* 2.0)) +(np.where(data["abs_avgbatch_msignal"] <= -998, data["meanbatch_msignal"], np.sin(( data["abs_avgbatch_msignal"])))))/2.0)))))+
0.050000*np.tanh(np.where(((( data["abs_avgbatch_msignal"])<=(data["maxtominbatch_slices2_msignal"])) *1.) <= -998,(( data["minbatch"])+(data["abs_maxbatch_slices2_msignal"])) ,(( np.sin(((( np.where(data["abs_maxbatch_msignal"] > -998, data["abs_maxbatch_msignal"], data["stdbatch_msignal"])) +(((data["maxtominbatch_msignal"])+(((((( data["mean_abs_chgbatch_slices2_msignal"])* 2.0)) >(((((( data["maxtominbatch_slices2"])/ 2.0)) <=(data["abs_maxbatch_slices2_msignal"])) *1.))) *1.))))))))* 2.0)))+
0.050000*np.tanh(( -(( np.sin(((( np.sin(( data["mean_abs_chgbatch_msignal"])))+(np.minimum(((data["abs_minbatch_slices2_msignal"])) ,(( np.sin(( data["signal_shift_+1"])))))))))))))+
0.050000*np.tanh(np.where(np.where(np.minimum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(( data["signal_shift_+1"])))> -998, data["abs_avgbatch_slices2"], data["maxbatch_slices2_msignal"])<= -998, data["rangebatch_msignal"],(( np.maximum(((( -(( np.sin(((9.0)))))))) ,(( data["abs_maxbatch"])))) *(np.where(data["signal_shift_-1"] <= -998,(8.73901081085205078),(((8.73901081085205078)) *(np.sin(( np.where(data["abs_avgbatch_slices2"] > -998, data["abs_avgbatch_slices2"], data["minbatch_slices2"])))))))))) +
0.050000*np.tanh(((data["abs_maxbatch_slices2"])*(np.where(((( data["abs_maxbatch_msignal"])>(data["meanbatch_slices2"])) *1.) <= -998,(((( data["maxbatch_slices2_msignal"])* 2.0)) * 2.0),(( np.cos(( np.where(data["abs_maxbatch_slices2_msignal"] <= -998, data["abs_maxbatch_slices2"],(( np.cos(( data["maxbatch_msignal"])))+(data["meanbatch_slices2"])))))) * 2.0)))))+
0.050000*np.tanh(((np.minimum(((np.cos(( data["stdbatch_msignal"])))) ,(((( np.minimum(((((np.minimum(((((np.cos(((( data["stdbatch_msignal"])* 2.0)))) * 2.0))),(( np.cos(((((data["abs_avgbatch_slices2_msignal"])>(data["abs_avgbatch_slices2_msignal"])) *1.))))))) * 2.0))),(( np.cos(((( data["mean_abs_chgbatch_slices2_msignal"])* 2.0)))))))* 2.0)))))* 2.0)) +
0.050000*np.tanh(np.minimum(((((((( data["maxbatch_slices2"])*(data["stdbatch_slices2_msignal"])))+(((((( np.cos(((((((((data["stdbatch_slices2_msignal"])+(data["abs_avgbatch_slices2_msignal"])) /2.0)) *(np.cos(( data["abs_avgbatch_slices2_msignal"])))))/ 2.0)))) *(data["maxbatch_slices2"])))>(data["abs_avgbatch_slices2_msignal"])) *1.))) /2.0))),(( np.cos(( data["abs_avgbatch_slices2_msignal"])))))) +
0.050000*np.tanh(((np.minimum(((np.sin(((( data["maxbatch_msignal"])* 2.0))))),(((( np.maximum(((data["maxtominbatch"])) ,(((( np.sin(( np.cos(((( data["stdbatch_msignal"])* 2.0)))))) * 2.0)))))*(np.sin(((( data["maxbatch_slices2"])/ 2.0)))))))))* 2.0)) +
0.050000*np.tanh(((np.minimum(((( 4.0))),(( data["abs_maxbatch_slices2_msignal"])))) *(((((np.sin(((( data["signal"])* 2.0)))) * 2.0)) -(((((((( data["abs_avgbatch_msignal"])*(data["abs_maxbatch_slices2_msignal"])))+(((data["minbatch_slices2_msignal"])-(np.where(data["abs_avgbatch_slices2_msignal"] > -998, data["signal_shift_+1"], data["signal_shift_+1_msignal"])))))/2.0)) / 2.0)))))) +
0.050000*np.tanh(np.sin(( np.where(np.cos(( data["stdbatch_slices2_msignal"])) <= -998, np.cos(( data["meanbatch_slices2"])) , np.maximum(((data["medianbatch_slices2_msignal"])) ,(((( data["maxbatch_msignal"])* 2.0)))))))) +
0.050000*np.tanh(((( -(( np.cos(((-(( np.maximum(((data["abs_maxbatch_msignal"])) ,(( data["abs_avgbatch_slices2_msignal"])))))))))))) * 2.0)) +
0.050000*np.tanh(np.where(np.where(data["abs_maxbatch_slices2"] > -998,(((7.36041975021362305)) -(data["abs_maxbatch"])) ,(( np.where(data["signal"] > -998,(7.36041975021362305), data["signal_shift_-1"])) * 2.0)) > -998,(((7.36041975021362305)) -(data["abs_maxbatch"])) , np.tanh(( np.where(data["stdbatch_slices2"] > -998,(((7.36041975021362305)) -(data["abs_maxbatch"])) , data["abs_maxbatch_slices2"])))))+
0.050000*np.tanh(np.sin(( np.maximum(((np.where(data["abs_avgbatch_msignal"] <= -998, data["signal_shift_+1"], data["signal_shift_+1"]))),(( np.maximum(((data["abs_avgbatch_msignal"])) ,(( np.maximum(((np.sin(( data["signal"])))) ,(( np.maximum(((data["abs_avgbatch_slices2"])) ,(( data["abs_avgbatch_msignal"])))))))))))))))+
0.050000*np.tanh(((np.sin(((( np.where(np.cos(((( np.where(data["maxtominbatch"] > -998, data["maxbatch_msignal"], np.where(( -(( data["maxtominbatch"])))> -998, np.where(data["maxtominbatch"] > -998, data["rangebatch_msignal"], data["signal"]), np.where(data["abs_maxbatch_msignal"] > -998, data["stdbatch_slices2_msignal"],(( np.sin(( data["maxbatch_msignal"])))* 2.0)))))* 2.0)))> -998, data["maxbatch_msignal"], data["maxbatch_msignal"])) * 2.0)))) * 2.0)) +
0.050000*np.tanh(((data["maxtominbatch_slices2"])+(((np.cos(((((( data["stdbatch_msignal"])+(data["stdbatch_slices2_msignal"])))*(np.cos(((((((data["abs_avgbatch_msignal"])+(data["medianbatch_slices2"])))<=(( -(( data["abs_maxbatch_slices2_msignal"])))))*1.))))))))*(((( 7.74140071868896484)) +(np.tanh(( np.cos(( data["abs_minbatch_msignal"])))))))))))+
0.050000*np.tanh(((np.cos(( data["abs_minbatch_msignal"])))*(((( 10.0)) *(np.cos(( np.where(np.cos(( data["mean_abs_chgbatch_slices2_msignal"])) > -998, data["medianbatch_slices2_msignal"],(((((9.0)) +(np.cos(( np.cos(( data["abs_minbatch_msignal"])))))))+(np.cos(( data["abs_maxbatch_slices2"])))))))))))) +
0.050000*np.tanh(np.sin(( np.where(data["maxtominbatch_msignal"] <= -998, np.where(data["rangebatch_slices2"] > -998, data["signal_shift_-1"],(((((data["rangebatch_slices2_msignal"])<=(np.cos(((( np.maximum(((data["medianbatch_slices2"])) ,(( data["minbatch_msignal"])))) *(data["abs_maxbatch_msignal"])))))) *1.))/ 2.0)) ,(( data["medianbatch_slices2"])-(data["abs_minbatch_slices2_msignal"])))))) +
0.050000*np.tanh(((np.cos(((( data["stdbatch_msignal"])+(data["mean_abs_chgbatch_slices2_msignal"])))))*(((data["rangebatch_slices2"])+(((data["meanbatch_slices2"])*(((((data["mean_abs_chgbatch_slices2_msignal"])+(((((data["abs_avgbatch_slices2_msignal"])+(((np.sin(((( data["mean_abs_chgbatch_slices2_msignal"])+(data["mean_abs_chgbatch_slices2_msignal"])))))*(data["signal_shift_+1"])))))+(data["meanbatch_msignal"])))))+(data["signal_shift_+1"])))))))))+
0.050000*np.tanh(np.where(data["meanbatch_slices2_msignal"] <= -998,(9.69016170501708984), np.cos(( np.where(np.cos(( data["abs_avgbatch_slices2_msignal"])) <= -998, data["abs_avgbatch_slices2"], np.where(data["stdbatch_slices2_msignal"] <= -998,(( data["minbatch_msignal"])-(np.cos(( np.maximum(((data["abs_avgbatch_slices2"])) ,(( data["mean_abs_chgbatch_slices2_msignal"]))))))), data["medianbatch_slices2"])))))) +
0.050000*np.tanh(((np.where(((data["rangebatch_slices2_msignal"])*(data["rangebatch_slices2_msignal"])) <= -998, data["medianbatch_slices2"], np.cos(( np.sin(( data["abs_avgbatch_slices2"])))))) -(((data["maxtominbatch_msignal"])+(((((data["rangebatch_slices2_msignal"])*(np.sin(( data["abs_avgbatch_slices2"])))))*(data["maxtominbatch_msignal"])))))))+
0.050000*np.tanh(((data["signal_shift_-1"])*(((((data["stdbatch_slices2_msignal"])+(((data["maxbatch_msignal"])*(((((( data["mean_abs_chgbatch_msignal"])+(data["abs_minbatch_slices2"])) /2.0)) +(np.cos(( data["abs_avgbatch_slices2_msignal"])))))))))+(((data["abs_maxbatch_slices2"])*(((data["mean_abs_chgbatch_msignal"])+(np.tanh(((( np.sin(( data["abs_avgbatch_slices2_msignal"])))+(np.cos(( data["abs_avgbatch_slices2_msignal"])))))))))))))))+
0.050000*np.tanh(((np.where(( 13.25574779510498047)<= -998, data["medianbatch_slices2"], np.minimum(((((( data["mean_abs_chgbatch_msignal"])+(((((((( 4.63609886169433594)) +(data["signal_shift_-1"])) /2.0)) >(data["maxtominbatch_msignal"])) *1.))) /2.0))),(( np.where(((data["medianbatch_slices2"])* 2.0)<= -998, data["maxtominbatch_msignal"], np.minimum(((np.sin(( data["abs_avgbatch_slices2"])))) ,(( data["signal_shift_-1"])))))))))* 2.0)) +
0.050000*np.tanh(((( -(( data["rangebatch_slices2"])))) *(((( np.cos(( np.where(((((data["abs_avgbatch_slices2"])/ 2.0)) / 2.0)> -998, np.sin(((((( np.sin(( np.cos(((( data["abs_avgbatch_slices2_msignal"])* 2.0)))))) * 2.0)) * 2.0))), data["minbatch_slices2_msignal"])))) +(((((data["abs_minbatch_slices2_msignal"])* 2.0)) *(np.sin(( data["abs_avgbatch_slices2"])))))) /2.0)))) +
0.050000*np.tanh(np.minimum(((np.where(((np.sin(( np.minimum(((data["maxbatch_slices2"])) ,(( data["maxbatch_slices2"])))))) * 2.0)> -998, np.sin(( data["abs_avgbatch_slices2"])) , data["abs_avgbatch_slices2"]))),(( np.sin(( data["abs_avgbatch_slices2"])))))) +
0.050000*np.tanh(((np.where(((( data["maxtominbatch"])>(data["maxtominbatch"])) *1.) > -998, np.maximum(((np.where(( -(( data["rangebatch_slices2"])))> -998,(10.04239368438720703), data["abs_minbatch_slices2_msignal"]))),(((-(((-(((10.04239368438720703)))))))))) , data["rangebatch_slices2"])) *(np.cos(( data["abs_minbatch_slices2_msignal"])))))+
0.050000*np.tanh(np.where(data["rangebatch_slices2"] <= -998, data["abs_avgbatch_msignal"],(( data["abs_avgbatch_msignal"])*(((((((np.cos(( data["abs_avgbatch_msignal"])))*(((data["meanbatch_msignal"])+(data["stdbatch_slices2_msignal"])))))+(data["abs_minbatch_slices2_msignal"])))+(((np.cos(( data["abs_avgbatch_msignal"])))*(data["abs_maxbatch"])))))))) +
0.050000*np.tanh(((np.cos(( data["medianbatch_slices2_msignal"])))*(np.where(data["abs_avgbatch_slices2_msignal"] > -998, np.where(( 8.0)<= -998, data["signal_shift_-1_msignal"],(( data["abs_maxbatch"])*(((((((14.30874156951904297)) >(((data["maxbatch_slices2_msignal"])* 2.0)))*1.))+(data["mean_abs_chgbatch_slices2_msignal"]))))),(( data["maxbatch_slices2_msignal"])* 2.0)))))+
0.050000*np.tanh(((np.sin(( np.where(np.sin(( data["stdbatch_slices2_msignal"])) <= -998, data["abs_maxbatch"],(( data["mean_abs_chgbatch_slices2_msignal"])-(data["abs_maxbatch"])))))) * 2.0)) +
0.050000*np.tanh(((((np.cos(( data["signal_shift_+1"])))+(np.sin(( data["abs_avgbatch_msignal"])))))+(((((( np.sin(( data["abs_avgbatch_msignal"])))+(np.minimum(((data["abs_avgbatch_msignal"])) ,(( np.cos(( data["mean_abs_chgbatch_slices2"])))))))/2.0)) +(((((data["stdbatch_msignal"])-(data["signal_shift_+1"])))*(data["signal_shift_-1"])))))))+
0.050000*np.tanh(((data["rangebatch_msignal"])+(((data["rangebatch_msignal"])+(((np.where(data["rangebatch_msignal"] <= -998, np.sin(( data["mean_abs_chgbatch_slices2_msignal"])) ,(( np.where(data["rangebatch_msignal"] > -998, data["abs_minbatch_slices2_msignal"], data["rangebatch_slices2"])) *(((data["rangebatch_slices2"])/ 2.0)))))* 2.0)))))) +
0.050000*np.tanh(( -(((( data["rangebatch_msignal"])*(np.sin(( data["maxtominbatch_msignal"])))))))) +
0.050000*np.tanh(((np.where(((((((( data["maxtominbatch_msignal"])*(np.where(data["abs_avgbatch_slices2_msignal"] > -998, data["stdbatch_slices2"], data["rangebatch_slices2"])))) * 2.0)) +(data["stdbatch_slices2"])) /2.0)<= -998, np.cos(( data["maxtominbatch_msignal"])) ,(( np.sin(( data["abs_avgbatch_slices2"])))* 2.0)))*(data["signal"])))+
0.050000*np.tanh(np.where(np.minimum(((np.where(data["abs_maxbatch_slices2_msignal"] > -998, np.cos(( data["medianbatch_slices2"])) , data["abs_avgbatch_slices2_msignal"]))),(( data["abs_avgbatch_msignal"])))> -998, data["signal"], data["meanbatch_slices2_msignal"])) +
0.050000*np.tanh(((np.minimum(((data["abs_avgbatch_slices2_msignal"])) ,(( np.minimum(((np.sin(( np.minimum(((data["abs_avgbatch_slices2_msignal"])) ,(( np.sin(( np.cos(( data["mean_abs_chgbatch_msignal"]))))))))))),(( np.sin(( data["abs_avgbatch_slices2"])))))))))* 2.0)) +
0.050000*np.tanh(data["abs_avgbatch_slices2_msignal"])+
0.050000*np.tanh(((np.sin(((( data["maxbatch_msignal"])*(np.where(((( data["abs_maxbatch_slices2"])<=(((data["abs_avgbatch_msignal"])-(np.where(data["maxbatch_msignal"] > -998, np.maximum(((np.sin(( data["abs_minbatch_msignal"])))) ,(( data["medianbatch_slices2_msignal"]))), data["abs_avgbatch_msignal"])))))*1.) > -998, data["abs_avgbatch_slices2"],(( np.tanh(( data["signal"])))-(data["abs_avgbatch_slices2_msignal"])))))))) *(data["rangebatch_slices2_msignal"])))+
0.050000*np.tanh(((((np.where(data["minbatch"] > -998, np.where(( 6.0)> -998, np.sin(( data["abs_avgbatch_slices2"])) , data["signal_shift_-1"]), np.where(data["signal_shift_+1"] > -998, np.maximum(((data["signal_shift_+1"])) ,(( data["abs_avgbatch_slices2"]))),(( data["maxbatch_slices2"])+(data["signal_shift_+1"])))))*(data["signal_shift_+1"])))* 2.0)) +
0.050000*np.tanh(((((data["abs_maxbatch_msignal"])*(np.cos(((( np.where(data["signal_shift_+1"] > -998, data["abs_avgbatch_slices2"], np.where(data["abs_maxbatch_slices2_msignal"] > -998, data["stdbatch_slices2"],(((np.sin(( np.maximum(((data["stdbatch_msignal"])) ,(( np.minimum(((data["abs_avgbatch_slices2"])) ,(( data["signal_shift_+1_msignal"])))))))))>(data["abs_minbatch_msignal"])) *1.))))/ 2.0)))))) *(data["signal_shift_+1"])))+
0.050000*np.tanh(((((((((np.tanh(((((6.0)) * 2.0)))) +(np.cos(( np.maximum(((((data["stdbatch_slices2"])*(data["signal_shift_-1"])))) ,(( data["stdbatch_slices2"])))))))) * 2.0)) +(data["stdbatch_msignal"])))* 2.0)) +
0.050000*np.tanh(((((np.sin(( data["rangebatch_msignal"])))* 2.0)) * 2.0)) +
0.050000*np.tanh(np.sin(( np.where(((np.sin(( data["maxbatch_msignal"])))* 2.0)> -998, data["abs_avgbatch_msignal"],(3.0)))))+
0.050000*np.tanh(((((data["minbatch_msignal"])-(((((data["medianbatch_slices2"])/ 2.0)) +(np.sin(( np.minimum(((data["medianbatch_slices2"])) ,(((( data["abs_avgbatch_slices2_msignal"])* 2.0)))))))))))*(np.sin(((( data["maxtominbatch_msignal"])+(np.cos(( data["medianbatch_slices2"])))))))))+
0.050000*np.tanh(((((((np.sin(((( data["rangebatch_msignal"])* 2.0)))) *(data["rangebatch_msignal"])))* 2.0)) * 2.0)) +
0.050000*np.tanh(((np.cos(( np.where(((data["signal_shift_-1"])-(np.cos(( data["signal_shift_-1"])))) > -998,(( data["stdbatch_slices2_msignal"])* 2.0), np.cos(( data["minbatch"])))))) * 2.0)) +
0.050000*np.tanh(((((data["mean_abs_chgbatch_msignal"])+(((np.sin(((((( data["signal_shift_-1"])-(data["stdbatch_msignal"])))* 2.0)))) *(data["abs_avgbatch_slices2_msignal"])))))*(((((( 4.0)) * 2.0)) * 2.0)))) +
0.050000*np.tanh(((((( -(((-(( np.sin(((( data["abs_avgbatch_msignal"])+(((((-(((-(( data["maxbatch_slices2_msignal"])))))))>(np.where(((data["abs_avgbatch_slices2"])*(np.sin(( data["abs_avgbatch_slices2"])))) <= -998, data["abs_avgbatch_slices2"], data["mean_abs_chgbatch_slices2"])))*1.))))))))))))* 2.0)) * 2.0)) +
0.050000*np.tanh(np.sin(( np.where(((data["signal"])-(data["mean_abs_chgbatch_msignal"])) <= -998,(( data["stdbatch_msignal"])* 2.0), np.where(data["mean_abs_chgbatch_msignal"] <= -998, data["abs_avgbatch_slices2"],(( data["signal_shift_-1"])-(np.where(data["abs_minbatch_msignal"] > -998, data["mean_abs_chgbatch_msignal"], data["abs_avgbatch_msignal"])))))))) +
0.050000*np.tanh(np.minimum(((np.minimum(((np.minimum(((np.cos(( data["abs_avgbatch_slices2_msignal"])))) ,(((( data["abs_avgbatch_slices2"])*(np.cos(((((data["mean_abs_chgbatch_slices2"])<=(data["signal_shift_+1"])) *1.)))))))))),(( data["abs_avgbatch_msignal"]))))),(( data["abs_avgbatch_slices2_msignal"])))) +
0.050000*np.tanh(((np.where(data["stdbatch_msignal"] > -998, data["signal_shift_-1"], data["maxtominbatch_msignal"])) *(((np.cos(((((( data["meanbatch_slices2"])/ 2.0)) *(data["signal"])))))* 2.0)))) +
0.050000*np.tanh(((np.cos(( np.where(np.where(((data["stdbatch_slices2_msignal"])* 2.0)> -998, data["abs_avgbatch_msignal"], data["abs_avgbatch_msignal"])> -998, np.where(((( np.sin(((( data["meanbatch_slices2_msignal"])* 2.0)))) >(((( data["stdbatch_slices2"])+(data["mean_abs_chgbatch_slices2"])) /2.0)))*1.) <= -998, np.cos(( np.where(data["abs_minbatch_slices2"] > -998,(-(( data["mean_abs_chgbatch_slices2"]))), data["signal_shift_+1_msignal"]))), data["abs_avgbatch_msignal"]), data["abs_avgbatch_msignal"])))) * 2.0)) +
0.050000*np.tanh(((((np.maximum(((( 6.08415985107421875))),(((((np.cos(( data["medianbatch_slices2"])))<=(data["maxtominbatch_msignal"])) *1.))))) +(data["maxtominbatch_msignal"])))+(data["maxtominbatch_slices2_msignal"])))+
0.050000*np.tanh(((((np.cos(((( data["abs_avgbatch_msignal"])-(np.where(data["signal_shift_+1"] > -998, np.tanh(( data["signal_shift_+1"])) , np.where(((data["abs_avgbatch_msignal"])/ 2.0)> -998, np.tanh(( data["abs_avgbatch_msignal"])) , data["signal_shift_-1"])))))))* 2.0)) * 2.0)) +
0.050000*np.tanh(((data["mean_abs_chgbatch_msignal"])+(((np.sin(( data["signal_shift_-1"])))+(((((np.where(((data["abs_avgbatch_slices2"])* 2.0)> -998, np.sin(( np.where(data["abs_avgbatch_slices2"] > -998, data["abs_avgbatch_slices2"], data["abs_avgbatch_slices2"]))),(((((data["mean_abs_chgbatch_msignal"])+(data["abs_avgbatch_slices2"])))+(data["rangebatch_slices2"])) /2.0)))* 2.0)) * 2.0)))))) +
0.050000*np.tanh(((( data["abs_avgbatch_msignal"])+(((data["abs_maxbatch_slices2_msignal"])*(((data["signal"])*(np.sin(((-(( data["rangebatch_slices2_msignal"])))))))))))/2.0)) +
0.050000*np.tanh(((data["abs_avgbatch_slices2_msignal"])*(np.where(np.where(np.cos(( data["maxbatch_slices2_msignal"])) <= -998,(( data["signal_shift_+1"])/ 2.0), data["meanbatch_msignal"])<= -998, np.where(data["medianbatch_msignal"] <= -998, data["abs_maxbatch_slices2"], data["signal_shift_-1"]), np.cos(( data["abs_avgbatch_msignal"])))))) +
0.050000*np.tanh(((((( 5.29374170303344727)) *(((data["stdbatch_msignal"])+(np.cos(((( data["signal_shift_+1"])*(((data["stdbatch_slices2_msignal"])+(data["stdbatch_slices2_msignal"])))))))))))+(np.cos(((5.29374170303344727)))))) +
0.050000*np.tanh(np.where(data["mean_abs_chgbatch_slices2"] > -998,(( np.where(((data["signal"])*(np.sin(( data["abs_avgbatch_slices2"])))) > -998,(( np.where(((data["stdbatch_slices2"])* 2.0)> -998,(( data["signal"])*(np.sin(( data["abs_avgbatch_slices2"])))) , np.sin(( data["abs_avgbatch_slices2"])))) * 2.0), data["medianbatch_slices2"])) * 2.0), np.where(np.sin(( data["abs_avgbatch_slices2"])) > -998, data["abs_avgbatch_slices2"], data["abs_avgbatch_slices2_msignal"])))+
0.050000*np.tanh(((((data["abs_avgbatch_msignal"])+(data["abs_avgbatch_slices2_msignal"])))+(((( data["abs_avgbatch_slices2_msignal"])+(np.tanh(( data["rangebatch_slices2"])))) /2.0)))) +
0.050000*np.tanh(((np.sin(((( np.minimum(((np.sin(( data["abs_avgbatch_slices2"])))) ,(( np.minimum(((((( np.cos(((( np.where(data["signal_shift_+1"] > -998, data["meanbatch_slices2"], np.sin(((5.0)))))* 2.0)))) +(((((np.sin(( data["signal_shift_+1"])))* 2.0)) * 2.0)))/2.0))),(( data["signal_shift_+1"])))))))* 2.0)))) * 2.0)) +
0.050000*np.tanh(((data["signal_shift_-1"])+(((data["signal"])*(((((( data["meanbatch_slices2"])>(data["meanbatch_slices2"])) *1.))+(((((( data["signal_shift_+1"])<=(data["abs_avgbatch_slices2"])) *1.))+(( -(( np.where(np.minimum(((data["signal_shift_-1"])) ,(( data["signal"])))> -998, data["meanbatch_slices2"],(( np.sin(( data["maxtominbatch"])))* 2.0)))))))))))))) +
0.050000*np.tanh(((np.minimum(((np.maximum(((data["mean_abs_chgbatch_slices2"])) ,(( np.maximum(((( 9.0))),(( np.cos(((( data["abs_minbatch_msignal"])* 2.0))))))))))),(((-(( np.sin(((( data["abs_minbatch_msignal"])* 2.0)))))))))) * 2.0)) +
0.050000*np.tanh(data["abs_avgbatch_msignal"])+
0.050000*np.tanh(((data["minbatch_slices2"])*(np.cos(( np.where(data["abs_minbatch_slices2"] > -998, np.where(np.where(data["abs_maxbatch_msignal"] > -998, data["abs_minbatch_slices2_msignal"],(((data["signal_shift_-1"])<=(data["abs_maxbatch_msignal"])) *1.))> -998, data["abs_maxbatch_msignal"], data["meanbatch_slices2_msignal"]),(((((( data["signal_shift_-1"])<=(((data["minbatch"])-(np.sin(( data["minbatch_slices2"])))))) *1.))<=(data["meanbatch_slices2_msignal"])) *1.))))))) +
0.050000*np.tanh(((data["maxtominbatch_slices2_msignal"])-(np.minimum(((data["minbatch"])) ,(( np.where(data["rangebatch_slices2"] <= -998, np.maximum(((data["minbatch"])) ,(((((( data["abs_avgbatch_msignal"])+(((data["stdbatch_msignal"])* 2.0)))) / 2.0)))) , data["mean_abs_chgbatch_slices2_msignal"])))))))+
0.050000*np.tanh(((np.where(data["abs_avgbatch_slices2_msignal"] > -998, np.cos(( data["abs_avgbatch_slices2_msignal"])) ,(((((( np.tanh(( np.tanh(( np.cos(( data["abs_avgbatch_slices2_msignal"])))))))* 2.0)) * 2.0)) *(np.cos(( data["medianbatch_slices2"])))))) * 2.0)) +
0.050000*np.tanh(((((((((data["abs_avgbatch_msignal"])* 2.0)) * 2.0)) *(np.cos(( np.maximum(((data["signal_shift_+1"])) ,(( np.where(((((( np.cos(((( data["abs_avgbatch_msignal"])+(((np.tanh(( np.where(data["abs_avgbatch_slices2_msignal"] > -998, data["abs_avgbatch_msignal"], data["meanbatch_slices2_msignal"])))) / 2.0)))))) +(data["maxtominbatch_msignal"])) /2.0)) *(data["maxbatch_slices2"])) > -998, data["meanbatch_msignal"], data["meanbatch_slices2_msignal"])))))))))* 2.0)) +
0.050000*np.tanh(((data["abs_avgbatch_slices2"])+(((np.where(data["stdbatch_msignal"] > -998,(( data["meanbatch_slices2"])+(np.where(data["stdbatch_slices2_msignal"] <= -998, data["meanbatch_slices2"], data["signal_shift_-1"]))), data["rangebatch_slices2_msignal"])) *(np.tanh(( np.tanh(((( np.minimum(((((data["stdbatch_msignal"])*(data["abs_minbatch_slices2"])))) ,(((-(( data["minbatch_slices2"])))))))+(np.tanh(((( data["stdbatch_slices2_msignal"])* 2.0)))))))))))))) +
0.050000*np.tanh(((data["signal_shift_+1"])*(np.where(data["meanbatch_slices2_msignal"] <= -998, data["rangebatch_slices2_msignal"],(( np.where(((((data["minbatch_slices2_msignal"])* 2.0)) *(data["rangebatch_msignal"])) > -998,(( data["stdbatch_msignal"])-(data["meanbatch_msignal"])) ,(( np.where(data["stdbatch_slices2_msignal"] > -998,(( np.sin(((14.30072021484375000)))) -(np.sin(( data["stdbatch_msignal"])))) , data["meanbatch_slices2_msignal"])) * 2.0)))* 2.0)))))+
0.050000*np.tanh(((data["abs_maxbatch_slices2"])*(np.tanh(((-(( np.cos(((( data["maxtominbatch_msignal"])-(np.where(data["maxbatch_msignal"] > -998, np.where(np.tanh(((( data["signal_shift_-1_msignal"])* 2.0)))> -998, data["signal"], np.cos(((((np.sin(( data["signal_shift_+1"])))>(data["meanbatch_msignal"])) *1.)))),(( data["medianbatch_msignal"])*(data["maxbatch_msignal"])))))))))))))))+
0.050000*np.tanh(((np.sin(((( data["maxbatch_msignal"])* 2.0)))) *(np.where(np.sin(( data["signal_shift_-1"])) > -998,(( data["rangebatch_slices2_msignal"])-(data["medianbatch_slices2_msignal"])) , np.sin(( data["rangebatch_slices2_msignal"])))))) +
0.050000*np.tanh(np.minimum(((data["abs_maxbatch_msignal"])) ,(( np.sin(( np.where(((((((data["maxbatch_msignal"])/ 2.0)) / 2.0)) * 2.0)<= -998,(((data["abs_avgbatch_slices2"])>(((((data["maxbatch_msignal"])/ 2.0)) * 2.0)))*1.) ,(( data["maxbatch_msignal"])* 2.0)))))))) +
0.050000*np.tanh(((data["abs_maxbatch_slices2_msignal"])* 2.0)) +
0.050000*np.tanh(((((np.maximum(((data["abs_avgbatch_msignal"])) ,(((( np.maximum(((data["stdbatch_slices2_msignal"])) ,(( np.cos(((( data["stdbatch_slices2_msignal"])-(data["mean_abs_chgbatch_msignal"])))))))) +(data["signal_shift_-1"])))))) *(np.minimum(((((((np.sin(( data["signal_shift_-1"])))* 2.0)) * 2.0))),(( np.sin(( np.cos(((( data["abs_avgbatch_msignal"])-(data["signal_shift_-1"])))))))))))) * 2.0)) +
0.050000*np.tanh(((np.where(((((np.where(data["stdbatch_msignal"] > -998, data["minbatch_msignal"], data["abs_avgbatch_slices2_msignal"])) * 2.0)) +(( -(( data["stdbatch_slices2_msignal"])))))> -998,(( np.sin(( data["abs_avgbatch_slices2"])))+(data["stdbatch_msignal"])) ,(((data["abs_avgbatch_slices2_msignal"])<=(((np.sin(((( data["mean_abs_chgbatch_slices2_msignal"])* 2.0)))) -(((data["stdbatch_msignal"])*(data["abs_avgbatch_slices2_msignal"])))))) *1.))) * 2.0)) +
0.050000*np.tanh(np.cos(( np.sin(( np.cos(( data["abs_avgbatch_slices2_msignal"])))))))+
0.050000*np.tanh(np.where(data["signal_shift_+1_msignal"] > -998, np.cos(((( data["signal_shift_-1"])-(np.where(np.tanh(( data["abs_avgbatch_slices2_msignal"])) <= -998, np.cos(( data["abs_avgbatch_slices2_msignal"])) , np.where(data["signal_shift_-1"] > -998, data["abs_avgbatch_slices2_msignal"],(((data["abs_avgbatch_slices2_msignal"])+(data["minbatch_slices2"])) /2.0))))))), np.tanh(( data["minbatch_slices2"])))) +
0.050000*np.tanh(((((np.minimum(((((np.cos(( data["abs_avgbatch_slices2_msignal"])))* 2.0))),(( data["abs_avgbatch_slices2_msignal"])))) +(np.minimum(((np.minimum(((data["abs_maxbatch_msignal"])) ,(( np.minimum(((data["mean_abs_chgbatch_slices2"])) ,(((( data["stdbatch_slices2_msignal"])*(((data["signal_shift_-1"])+(data["medianbatch_slices2_msignal"])))))))))))) ,(( np.where(data["meanbatch_msignal"] <= -998, data["signal_shift_+1"], data["abs_maxbatch_msignal"])))))))* 2.0)) +
0.050000*np.tanh(((((data["abs_maxbatch"])*(data["stdbatch_msignal"])))*(np.where(data["signal_shift_+1"] > -998,(( np.maximum(((data["signal_shift_+1"])) ,(((( data["meanbatch_msignal"])* 2.0)))))+(data["medianbatch_slices2_msignal"])) ,(( data["abs_maxbatch"])*(np.sin(( data["rangebatch_msignal"])))))))) +
0.050000*np.tanh(((np.minimum(((data["stdbatch_slices2_msignal"])) ,(( data["stdbatch_slices2_msignal"])))) *(np.where(((data["meanbatch_msignal"])+(data["stdbatch_msignal"])) > -998,(((10.0)) *(np.minimum(((((np.cos(( data["meanbatch_msignal"])))* 2.0))),(( data["signal_shift_-1_msignal"]))))),(10.0)))))+
0.050000*np.tanh(((((data["abs_maxbatch"])*(((((((((( np.cos(((-(( data["abs_avgbatch_msignal"])))))) +(np.cos(( data["stdbatch_msignal"])))) /2.0)) +(np.cos(( data["abs_avgbatch_slices2_msignal"])))) /2.0)) +(np.cos(((-(( data["meanbatch_slices2"])))))))/2.0)))) +(data["abs_avgbatch_msignal"])))+
0.050000*np.tanh(((( 14.70708179473876953)) +(((data["abs_maxbatch"])*(data["maxtominbatch_slices2_msignal"])))))+
0.050000*np.tanh(((np.sin(( data["abs_maxbatch_slices2"])))*(np.where(np.minimum(((np.sin(( data["abs_maxbatch_slices2"])))) ,(( data["rangebatch_slices2_msignal"])))<= -998, data["mean_abs_chgbatch_slices2"],(( data["abs_minbatch_slices2_msignal"])* 2.0)))))+
0.050000*np.tanh(( -(( np.cos(((((( data["abs_minbatch_slices2_msignal"])* 2.0)) -(((( data["medianbatch_slices2_msignal"])>(data["abs_minbatch_slices2_msignal"])) *1.))))))))) +
0.050000*np.tanh(np.where(data["mean_abs_chgbatch_slices2"] > -998,(( data["maxbatch_slices2"])*(np.sin(( np.cos(( np.maximum(((data["medianbatch_msignal"])) ,(( np.where(data["stdbatch_msignal"] <= -998, np.maximum(((np.cos(( np.sin(( data["abs_avgbatch_slices2"])))))) ,(( np.sin(( data["medianbatch_msignal"]))))), data["signal_shift_+1"])))))))))) , data["abs_avgbatch_slices2"])) +
0.050000*np.tanh(( 14.91276741027832031)) +
0.050000*np.tanh(( -(((((((( data["signal"])-(((( data["signal_shift_-1"])>(((data["meanbatch_slices2"])*(((((( data["signal_shift_-1"])>(data["signal"])) *1.))* 2.0)))))*1.))))-(((( np.maximum(((np.tanh(( data["medianbatch_slices2"])))) ,(((( data["signal_shift_-1"])* 2.0)))))>(((data["rangebatch_slices2"])*(data["mean_abs_chgbatch_slices2_msignal"])))) *1.))))* 2.0)))))+
0.050000*np.tanh(((((( 3.0)) +(np.minimum(((((data["maxtominbatch_slices2_msignal"])*(data["signal_shift_-1"])))) ,(((( data["stdbatch_slices2_msignal"])+(data["maxbatch_slices2"])))))))) +(np.tanh(( data["signal_shift_+1"])))))+
0.050000*np.tanh(data["signal_shift_-1"])+
0.050000*np.tanh(((data["rangebatch_slices2_msignal"])*(((data["abs_minbatch_msignal"])*(((data["meanbatch_msignal"])-(((( data["abs_avgbatch_slices2_msignal"])>(( -(((((np.maximum(((data["maxbatch_slices2"])) ,(( data["abs_avgbatch_slices2"])))) <=(data["abs_minbatch_slices2"])) *1.))))))*1.))))))))+
0.050000*np.tanh(((((((np.sin(((( np.sin(( data["mean_abs_chgbatch_msignal"])))-(data["signal_shift_+1"])))))-(((((data["signal_shift_-1"])* 2.0)) *(data["medianbatch_slices2"])))))+(np.where(data["signal_shift_+1"] <= -998, data["medianbatch_slices2_msignal"], data["rangebatch_slices2_msignal"])))) * 2.0)) +
0.050000*np.tanh(np.where(data["abs_avgbatch_msignal"] <= -998,(((data["rangebatch_slices2_msignal"])+(data["medianbatch_slices2_msignal"])) /2.0),(((-(( np.sin(( data["maxbatch_msignal"])))))) * 2.0)))+
0.050000*np.tanh(((np.cos(( data["abs_avgbatch_msignal"])))+(np.minimum(((np.where(data["abs_avgbatch_msignal"] > -998, data["stdbatch_slices2_msignal"], data["maxbatch_slices2"]))),(( np.where(data["abs_avgbatch_msignal"] <= -998, data["abs_maxbatch"], data["rangebatch_slices2_msignal"])))))))+
0.050000*np.tanh(((data["mean_abs_chgbatch_msignal"])-(np.minimum(((((data["signal_shift_+1"])+(data["minbatch_slices2"])))) ,(((((( np.minimum(((data["abs_maxbatch_slices2_msignal"])) ,(( data["abs_avgbatch_msignal"])))) -(data["mean_abs_chgbatch_msignal"])))-(np.sin(((((((((((data["signal_shift_+1"])+(data["minbatch_slices2_msignal"])))+(data["mean_abs_chgbatch_slices2_msignal"])))>(data["mean_abs_chgbatch_slices2"])) *1.))+(data["minbatch_slices2"])))))))))))) +
0.050000*np.tanh(((((data["signal_shift_+1_msignal"])* 2.0)) *(np.where(np.where(((((data["signal_shift_+1_msignal"])* 2.0)) *(np.where(data["mean_abs_chgbatch_msignal"] > -998, data["stdbatch_slices2_msignal"], data["abs_avgbatch_slices2_msignal"])))> -998, data["stdbatch_slices2_msignal"], data["signal_shift_+1_msignal"])> -998,(( data["stdbatch_slices2_msignal"])* 2.0),(( data["signal_shift_+1_msignal"])*(np.where(data["stdbatch_slices2_msignal"] > -998, data["stdbatch_slices2_msignal"], data["abs_avgbatch_msignal"])))))))+
0.050000*np.tanh(((((( data["signal_shift_-1"])* 2.0)) +(((data["meanbatch_msignal"])*(np.where(((np.tanh(((( data["meanbatch_msignal"])*(np.where(((( data["abs_minbatch_slices2_msignal"])<=(((( data["abs_minbatch_slices2_msignal"])+(data["meanbatch_msignal"])) /2.0)))*1.) > -998, data["abs_minbatch_slices2_msignal"], np.where(data["signal"] > -998, data["abs_minbatch_slices2_msignal"], data["medianbatch_msignal"])))))))*(data["stdbatch_msignal"])) > -998, data["abs_minbatch_slices2_msignal"], data["signal"])))))/2.0)) +
0.050000*np.tanh(((data["stdbatch_slices2_msignal"])+(((( data["stdbatch_slices2"])<=(((np.maximum(((( 6.0))),(( np.maximum(((np.where(data["stdbatch_slices2_msignal"] > -998,(3.87789225578308105), data["stdbatch_slices2_msignal"]))),(( data["maxtominbatch_slices2_msignal"])))))))+(((data["rangebatch_slices2"])-(data["stdbatch_slices2_msignal"])))))) *1.))))+
0.050000*np.tanh(((((np.cos(( data["meanbatch_slices2"])))+(np.maximum(((data["abs_minbatch_slices2_msignal"])) ,(( np.cos(( np.minimum(((((data["stdbatch_slices2"])/ 2.0))),(((( np.cos(((( data["stdbatch_slices2_msignal"])* 2.0)))) -(( 9.0)))))))))))))) *(data["abs_maxbatch"])))+
0.050000*np.tanh(((data["rangebatch_slices2_msignal"])-(((((data["meanbatch_slices2"])-(((np.where(np.tanh(((( data["abs_maxbatch_msignal"])-(data["meanbatch_slices2"])))) <= -998, data["abs_avgbatch_slices2_msignal"], np.cos(( data["rangebatch_slices2_msignal"])))) -(data["meanbatch_slices2"])))))-(data["abs_avgbatch_slices2_msignal"])))))+
0.050000*np.tanh(((data["signal"])+(((((np.cos(( np.maximum(((data["signal"])) ,(( np.maximum(((np.tanh(((((( data["medianbatch_msignal"])+(np.minimum(((( 4.23611021041870117))),(( data["mean_abs_chgbatch_msignal"])))))) / 2.0))))),(( data["medianbatch_msignal"])))))))))*(((data["maxbatch_slices2"])*(data["rangebatch_slices2_msignal"])))))+(data["signal"])))))+
0.050000*np.tanh(((( 2.0)) +(( -(( np.where(data["maxtominbatch_msignal"] > -998,(( data["abs_minbatch_slices2_msignal"])*(((np.maximum(((data["signal_shift_+1"])) ,(( data["abs_avgbatch_msignal"])))) *(data["maxtominbatch"])))) ,(-(((-(( np.where(((( 2.0)) +(data["signal_shift_+1"])) > -998, data["maxtominbatch"], data["minbatch_msignal"])))))))))))))) +
0.050000*np.tanh(np.where(data["stdbatch_slices2_msignal"] <= -998, data["rangebatch_slices2"],(( data["abs_maxbatch_slices2_msignal"])*(((data["stdbatch_slices2_msignal"])*(((np.maximum(((((((data["signal_shift_+1_msignal"])*(data["abs_maxbatch_slices2_msignal"])))-(np.minimum(((data["medianbatch_slices2_msignal"])) ,(( data["abs_maxbatch"]))))))),(((( data["minbatch_slices2"])-(((data["abs_maxbatch_slices2_msignal"])* 2.0)))))))* 2.0)))))))+
0.050000*np.tanh(((((( data["rangebatch_msignal"])+(data["signal_shift_-1"])) /2.0)) *(np.minimum(((np.where(data["signal_shift_-1"] <= -998,(((data["rangebatch_msignal"])+(( 3.66988515853881836)))/2.0), np.tanh(( np.sin(((( data["signal_shift_-1"])-(np.minimum(((data["meanbatch_msignal"])) ,(((( data["mean_abs_chgbatch_slices2_msignal"])* 2.0))))))))))))),(( np.tanh(( data["abs_maxbatch_msignal"])))))))) +
0.050000*np.tanh(((np.sin(( np.where(data["abs_maxbatch"] <= -998, data["maxbatch_slices2"], np.minimum(((data["maxbatch_slices2"])) ,(( data["stdbatch_slices2"])))))))* 2.0)) +
0.050000*np.tanh(((data["abs_maxbatch_slices2_msignal"])-(((data["medianbatch_slices2"])*(np.where(np.where(data["medianbatch_slices2"] <= -998,(( data["mean_abs_chgbatch_slices2_msignal"])/ 2.0), data["mean_abs_chgbatch_slices2_msignal"])<= -998, data["signal_shift_-1"], data["signal_shift_-1"])))))) +
0.050000*np.tanh(((((np.sin(( data["signal_shift_-1"])))+(((data["maxbatch_slices2_msignal"])*(((data["abs_avgbatch_msignal"])*(((np.sin(( data["signal_shift_-1"])))+(((np.sin(( np.cos(( data["abs_avgbatch_msignal"])))))*(np.where(np.cos(( data["abs_avgbatch_msignal"])) > -998, data["medianbatch_msignal"],(( data["maxbatch_slices2_msignal"])*(data["signal"])))))))))))))) * 2.0)) +
0.050000*np.tanh(((((((12.09984111785888672)) +(((data["maxtominbatch_slices2_msignal"])*(((data["meanbatch_slices2"])* 2.0)))))/2.0)) *(((((( data["mean_abs_chgbatch_slices2"])>(((data["rangebatch_slices2_msignal"])*(( 12.09984111785888672)))))*1.))+(( 12.09984111785888672)))))) +
0.050000*np.tanh(np.where(np.where(data["abs_avgbatch_msignal"] > -998, data["minbatch_slices2_msignal"], np.where(( 2.26455736160278320)> -998, np.where(data["meanbatch_slices2"] > -998,(((( data["meanbatch_slices2"])+(np.tanh(( data["medianbatch_slices2"])))))*(data["abs_avgbatch_msignal"])) , data["abs_maxbatch_msignal"]), data["rangebatch_slices2"])) > -998,(( data["abs_avgbatch_msignal"])*(((data["abs_maxbatch"])*(np.cos(( data["abs_avgbatch_msignal"])))))) , data["medianbatch_slices2_msignal"])) +
0.050000*np.tanh(((data["stdbatch_slices2_msignal"])+(np.where(data["stdbatch_slices2_msignal"] <= -998, data["stdbatch_msignal"], np.cos(((((np.maximum(((data["signal_shift_+1"])) ,(( np.where(data["stdbatch_slices2_msignal"] <= -998, data["stdbatch_msignal"],(( data["maxbatch_slices2"])-(((data["maxbatch_slices2"])*(np.sin(( data["stdbatch_msignal"])))))))))))>(data["minbatch"])) *1.))))))) +
0.050000*np.tanh(((((( 1.24717736244201660)) +(((((((((( 1.24717736244201660)) +(((((np.where(((data["stdbatch_slices2"])* 2.0)<= -998,(((data["abs_minbatch_slices2_msignal"])+(data["signal_shift_-1"])) /2.0), np.cos(( np.maximum(((data["signal_shift_-1"])) ,(( data["abs_avgbatch_msignal"])))))))+(((np.cos(( data["abs_maxbatch"])))* 2.0)))) * 2.0)))) * 2.0)) * 2.0)) * 2.0)))) * 2.0)) +
0.050000*np.tanh(((( -(((( data["stdbatch_slices2"])*(((data["abs_maxbatch_slices2"])*(((np.sin(( data["mean_abs_chgbatch_msignal"])))+(((((np.sin(( np.maximum(((np.sin(( np.maximum(((((np.sin(( data["medianbatch_slices2_msignal"])))*(data["stdbatch_slices2"])))) ,(( data["abs_maxbatch_slices2"]))))))),(( data["abs_maxbatch_slices2"])))))) *(data["signal_shift_-1"])))* 2.0)))))))))))* 2.0)) +
0.050000*np.tanh(((np.cos(( np.maximum(((data["signal_shift_+1"])) ,(((((((data["maxbatch_msignal"])* 2.0)) <=(((((-(( np.where(data["mean_abs_chgbatch_slices2"] > -998,(((( np.cos(( data["signal_shift_+1"])))/ 2.0)) * 2.0), data["signal_shift_-1_msignal"])))))<=(data["mean_abs_chgbatch_slices2"])) *1.))) *1.))))))) * 2.0)) +
0.050000*np.tanh(((np.where(data["stdbatch_slices2_msignal"] <= -998, np.maximum(((((data["rangebatch_slices2"])*(data["minbatch"])))) ,(( data["abs_maxbatch_msignal"]))),(( np.maximum(((data["meanbatch_msignal"])) ,(( data["signal_shift_+1"])))) *(data["stdbatch_slices2_msignal"])))) *(((np.cos(( data["meanbatch_msignal"])))* 2.0)))) +
0.050000*np.tanh(((data["abs_avgbatch_slices2_msignal"])*(((np.where(data["abs_avgbatch_slices2_msignal"] <= -998,(( data["meanbatch_slices2"])+(data["stdbatch_msignal"])) , np.where(data["signal_shift_+1"] > -998, np.where(( 3.0)> -998, data["signal_shift_+1"], data["signal"]),(( data["abs_avgbatch_slices2_msignal"])*(((data["meanbatch_slices2"])-(data["signal_shift_+1"])))))))-(( -(( data["meanbatch_slices2"])))))))) +
0.050000*np.tanh(((data["stdbatch_slices2"])+(((((((((( data["maxtominbatch_msignal"])* 2.0)) *(data["medianbatch_slices2"])))+(( 7.87292909622192383)))) +(data["medianbatch_slices2"])) /2.0)))) +
0.050000*np.tanh(((((np.cos(( np.maximum(((((((((((((np.cos(( np.maximum(((data["meanbatch_msignal"])) ,(( data["meanbatch_msignal"])))))) +(data["meanbatch_msignal"])) /2.0)) >(((data["meanbatch_msignal"])+(( -(( data["maxtominbatch"])))))))*1.))* 2.0)) * 2.0))),(( np.maximum(((((((-(( data["medianbatch_slices2"])))) +(data["rangebatch_slices2"])) /2.0))),(( data["meanbatch_msignal"])))))))))*(data["abs_maxbatch_slices2"])))* 2.0)) +
0.050000*np.tanh(((data["maxbatch_slices2"])+(np.maximum(((np.cos(( data["abs_maxbatch_slices2"])))) ,(( data["maxbatch_slices2"])))))) +
0.050000*np.tanh(np.where(data["meanbatch_slices2"] <= -998, np.minimum(((((((data["minbatch_msignal"])+(((data["abs_maxbatch_slices2"])+(np.sin(( data["mean_abs_chgbatch_msignal"])))))))*(data["minbatch_slices2"])))) ,(( data["mean_abs_chgbatch_msignal"]))),(((12.16635227203369141)) *(np.sin(((( data["mean_abs_chgbatch_msignal"])-(((data["abs_maxbatch_slices2"])+(np.sin(( data["abs_maxbatch_slices2_msignal"])))))))))))) +
0.050000*np.tanh(((((( np.maximum(((np.where(data["stdbatch_slices2"] <= -998, np.cos(((( np.maximum(((np.tanh(( data["stdbatch_slices2"])))) ,(( data["maxbatch_msignal"])))) * 2.0))), data["rangebatch_slices2_msignal"]))),(((( np.where(data["abs_minbatch_slices2_msignal"] > -998, data["rangebatch_slices2_msignal"], data["meanbatch_msignal"])) * 2.0)))))* 2.0)) +(data["maxbatch_slices2"])) /2.0)) +
0.050000*np.tanh(np.cos(((( data["maxtominbatch"])+(np.minimum(((data["abs_maxbatch"])) ,(( data["stdbatch_msignal"])))))))) +
0.050000*np.tanh(((np.where(np.where(((np.cos(( data["medianbatch_msignal"])))*(data["abs_maxbatch_msignal"])) <= -998, data["medianbatch_msignal"],(( data["medianbatch_slices2_msignal"])* 2.0)) > -998,(((3.15710377693176270)) +(data["medianbatch_msignal"])) , np.cos(( data["medianbatch_msignal"])))) *(((((((np.cos(( data["medianbatch_msignal"])))*(data["abs_maxbatch_msignal"])))* 2.0)) +(data["medianbatch_msignal"])))))+
0.050000*np.tanh(np.where(data["meanbatch_slices2_msignal"] <= -998, data["abs_maxbatch"], np.maximum(((data["signal_shift_+1"])) ,(( np.tanh(( np.cos(( np.where(((data["rangebatch_msignal"])*(data["signal_shift_+1"])) <= -998,(((data["maxtominbatch_slices2_msignal"])+(data["abs_maxbatch"])) /2.0),(((data["stdbatch_msignal"])+(data["abs_maxbatch"])) /2.0)))))))))))+
0.050000*np.tanh(np.maximum(((np.where(((data["stdbatch_msignal"])* 2.0)<= -998, data["rangebatch_slices2"],(( data["signal_shift_-1"])*(np.cos(( data["medianbatch_slices2"]))))))),(( data["medianbatch_slices2_msignal"])))) +
0.050000*np.tanh(np.where(( -(( data["maxbatch_msignal"])))<= -998,(( data["maxbatch_msignal"])*(((((data["signal_shift_+1"])+(data["medianbatch_slices2_msignal"])))*(data["medianbatch_slices2_msignal"])))) ,(((( np.cos(( data["abs_avgbatch_slices2_msignal"])))*(data["medianbatch_slices2_msignal"])))*(((data["signal_shift_+1"])+(( 5.0)))))))+
0.050000*np.tanh(np.where(data["meanbatch_msignal"] <= -998,(((data["maxtominbatch"])<=(((np.minimum(((np.maximum(((data["meanbatch_msignal"])) ,(( data["abs_maxbatch_slices2"]))))),(((-(( data["meanbatch_slices2_msignal"])))))))*(np.minimum(((data["medianbatch_msignal"])) ,(( data["mean_abs_chgbatch_slices2"])))))))*1.) ,(( np.sin(( data["rangebatch_msignal"])))*(data["meanbatch_msignal"])))) +
0.050000*np.tanh(((np.cos(( np.where(data["mean_abs_chgbatch_slices2_msignal"] > -998, np.where(np.where(data["minbatch_slices2_msignal"] <= -998, data["rangebatch_slices2"], np.where(data["mean_abs_chgbatch_slices2_msignal"] <= -998,(2.75588107109069824),(( data["signal"])*(( -(( data["abs_avgbatch_slices2_msignal"])))))))<= -998, data["mean_abs_chgbatch_msignal"], data["abs_avgbatch_slices2_msignal"]),(((data["maxtominbatch_slices2"])+(data["minbatch_slices2_msignal"])) /2.0)))))*(data["meanbatch_slices2_msignal"])))+
0.050000*np.tanh(((( np.where(data["abs_maxbatch_slices2"] <= -998,(( data["abs_maxbatch"])-(((( np.tanh(( data["abs_maxbatch"])))+(data["rangebatch_slices2"])) /2.0))),(8.0)))+(np.maximum(((data["signal_shift_+1"])) ,(( np.where(data["rangebatch_slices2"] > -998,(((-(( data["rangebatch_slices2"])))) *(data["stdbatch_msignal"])) , data["abs_maxbatch_slices2"])))))) /2.0)) +
0.050000*np.tanh(np.where(((data["medianbatch_slices2"])* 2.0)<= -998, np.where(data["signal_shift_+1_msignal"] > -998,(( np.where(data["abs_maxbatch_slices2_msignal"] <= -998, np.maximum(((((( data["signal_shift_+1"])<=(data["maxbatch_slices2"])) *1.))) ,(( data["signal_shift_+1"]))), data["mean_abs_chgbatch_msignal"])) -(data["meanbatch_msignal"])) , np.sin(( data["stdbatch_slices2"]))),(( data["medianbatch_slices2"])*(np.minimum(((data["meanbatch_msignal"])) ,(( np.cos(( data["meanbatch_msignal"])))))))))+
0.050000*np.tanh(((np.where(data["abs_minbatch_msignal"] > -998, np.where(data["signal_shift_+1"] > -998, data["rangebatch_msignal"], data["meanbatch_slices2_msignal"]), data["signal_shift_+1"])) *(data["signal_shift_+1"])))+
0.050000*np.tanh(((data["meanbatch_msignal"])*(np.tanh(( np.sin(( np.where(((( data["meanbatch_msignal"])+(data["abs_avgbatch_slices2"])) /2.0)<= -998, data["meanbatch_msignal"], np.where(np.sin(( data["medianbatch_msignal"])) <= -998,(( data["meanbatch_msignal"])*(data["signal"])) , data["rangebatch_msignal"])))))))))+
0.050000*np.tanh(((((data["maxbatch_slices2_msignal"])-(data["abs_avgbatch_slices2_msignal"])))-(((data["meanbatch_slices2"])*(np.where(((data["signal_shift_+1"])-(data["abs_avgbatch_slices2_msignal"])) > -998, data["signal_shift_+1"],(((3.0)) * 2.0)))))))+
0.050000*np.tanh(((np.maximum(((((data["signal_shift_-1"])*(data["stdbatch_msignal"])))) ,(( np.where(((data["minbatch_slices2"])* 2.0)<= -998, data["abs_maxbatch_slices2"], data["medianbatch_slices2_msignal"])))))* 2.0)) +
0.050000*np.tanh(((np.where(data["abs_avgbatch_slices2"] > -998,(( np.cos(((( np.where(( 9.74521446228027344)> -998, data["stdbatch_slices2_msignal"], data["abs_avgbatch_msignal"])) * 2.0)))) * 2.0), np.where(data["abs_avgbatch_slices2"] <= -998, data["stdbatch_slices2"], data["signal_shift_+1"])))* 2.0)) +
0.050000*np.tanh(((((((( np.cos(( np.where(((np.cos(( data["signal_shift_-1"])))* 2.0)> -998,(((data["mean_abs_chgbatch_msignal"])+(((data["meanbatch_slices2_msignal"])* 2.0)))/2.0), data["mean_abs_chgbatch_slices2"])))) +(np.maximum(((np.sin(((0.0))))),(( np.sin(( np.minimum(((data["meanbatch_slices2_msignal"])) ,(( data["minbatch_slices2_msignal"])))))))))) /2.0)) * 2.0)) * 2.0)) +
0.050000*np.tanh(((((((( data["medianbatch_slices2_msignal"])*(np.where(((( np.where(np.cos(( data["abs_avgbatch_msignal"])) <= -998,(( data["abs_avgbatch_msignal"])*(data["stdbatch_slices2"])) , data["maxbatch_msignal"])) +(data["abs_maxbatch_msignal"])) /2.0)<= -998,(((data["maxbatch_slices2_msignal"])>(data["mean_abs_chgbatch_slices2_msignal"])) *1.) , data["stdbatch_slices2_msignal"])))) / 2.0)) +(data["stdbatch_msignal"])) /2.0)) +
0.050000*np.tanh(np.maximum(((((data["signal_shift_+1"])* 2.0))),(( np.cos(( data["rangebatch_slices2_msignal"])))))) +
0.050000*np.tanh(((((data["rangebatch_slices2_msignal"])-(data["abs_maxbatch_msignal"])))*(np.cos(((( data["abs_maxbatch_msignal"])*(np.minimum(((np.maximum(((np.cos(( data["medianbatch_slices2"])))) ,(( data["mean_abs_chgbatch_slices2"]))))),(( np.where(data["maxtominbatch_msignal"] <= -998, np.minimum(((data["medianbatch_slices2"])) ,(( data["meanbatch_msignal"]))), data["maxtominbatch_slices2"])))))))))))+
0.050000*np.tanh(((np.sin(( np.maximum(((data["abs_avgbatch_slices2"])) ,(( data["signal_shift_-1"])))))) *(((np.where(data["abs_avgbatch_slices2"] <= -998,(( data["abs_maxbatch"])/ 2.0), data["signal_shift_-1"])) +(((data["signal_shift_-1"])+(((((data["signal_shift_-1"])+(((np.sin(( data["maxbatch_slices2"])))*(data["signal_shift_-1"])))))+(np.cos(( data["minbatch_slices2"])))))))))))+
0.050000*np.tanh(((((((( data["maxtominbatch_slices2_msignal"])/ 2.0)) *(data["maxbatch_msignal"])))+(((((((( data["medianbatch_slices2_msignal"])+(((data["abs_minbatch_slices2_msignal"])*(data["medianbatch_slices2"])))) /2.0)) +(data["abs_maxbatch"])))+(np.cos(( data["medianbatch_slices2_msignal"])))))) /2.0)) +
0.050000*np.tanh(np.maximum(((((((data["signal_shift_-1"])*(data["abs_minbatch_slices2_msignal"])))+(((np.cos(( np.maximum(((data["meanbatch_msignal"])) ,(((((data["maxbatch_slices2"])<=(data["abs_minbatch_slices2_msignal"])) *1.))))))) * 2.0))))),(( data["abs_minbatch_msignal"])))) +
0.050000*np.tanh(((data["signal_shift_+1"])*(((np.minimum(((((((((6.0)) -(data["abs_maxbatch"])))<=(data["abs_maxbatch"])) *1.))) ,(((((6.0)) -(data["abs_maxbatch"])))))) +(np.minimum(((data["signal_shift_+1"])) ,(( np.tanh(( data["signal_shift_+1"])))))))))) +
0.050000*np.tanh(((( 7.0)) *(((np.where(data["abs_maxbatch_slices2_msignal"] <= -998, np.maximum(((data["maxbatch_msignal"])) ,(( np.sin(((((( 6.0)) +(((( np.cos(( data["signal_shift_-1"])))<=(( 7.0)))*1.))) /2.0)))))) ,(( np.cos(( data["signal_shift_-1"])))/ 2.0)))* 2.0)))) +
0.050000*np.tanh(np.tanh(( data["rangebatch_slices2_msignal"])))+
0.050000*np.tanh(((np.maximum(((np.where(data["abs_minbatch_slices2_msignal"] <= -998, data["signal_shift_-1"],(( np.cos(( data["meanbatch_msignal"])))* 2.0)))) ,(((( np.where(data["medianbatch_slices2_msignal"] <= -998,(( np.sin(( data["stdbatch_msignal"])))+(data["medianbatch_slices2_msignal"])) ,(( np.cos(( data["meanbatch_msignal"])))* 2.0)))+(data["abs_minbatch_slices2_msignal"])))))) * 2.0)) +
0.050000*np.tanh(np.maximum(((((np.where(((data["mean_abs_chgbatch_msignal"])+(np.cos(((( np.sin(( data["abs_avgbatch_msignal"])))* 2.0)))))<= -998, data["maxbatch_slices2_msignal"], np.where(np.where(data["minbatch_msignal"] > -998, data["maxbatch_slices2_msignal"], data["abs_avgbatch_msignal"])<= -998, data["abs_avgbatch_msignal"], data["abs_minbatch_msignal"])))* 2.0))),(( np.sin(((( data["signal_shift_+1"])* 2.0)))))))+
0.050000*np.tanh(((np.where(( 0.67817705869674683)<= -998,(0.67817705869674683),(( np.sin(( np.minimum(((data["minbatch_slices2_msignal"])) ,(((-(( data["stdbatch_msignal"])))))))))* 2.0)))* 2.0)) +
0.050000*np.tanh(np.where(data["stdbatch_slices2_msignal"] > -998, data["signal_shift_-1"], data["medianbatch_slices2"])) +
0.050000*np.tanh(((np.maximum(((data["signal_shift_+1"])) ,(( data["medianbatch_msignal"])))) * 2.0)) +
0.050000*np.tanh(((((np.where(data["rangebatch_slices2"] <= -998,(( data["meanbatch_slices2_msignal"])-(data["medianbatch_msignal"])) , data["meanbatch_slices2_msignal"])) -(((((np.sin(( data["medianbatch_msignal"])))* 2.0)) *(data["rangebatch_slices2"])))))*(data["abs_minbatch_msignal"])))+
0.050000*np.tanh(np.sin(((( data["maxtominbatch"])+(np.where(((((((data["abs_maxbatch_slices2"])+(((data["maxtominbatch"])-(data["abs_minbatch_slices2_msignal"])))) /2.0)) +(data["minbatch_slices2_msignal"])) /2.0)<= -998, data["abs_minbatch_slices2_msignal"], np.where(np.where(data["abs_maxbatch_slices2"] <= -998, data["signal"], data["minbatch_slices2_msignal"])<= -998, data["minbatch_slices2_msignal"], data["minbatch_slices2_msignal"])))))))+
0.050000*np.tanh(((np.cos(( data["maxbatch_msignal"])))*(np.where(((data["medianbatch_slices2_msignal"])-(data["medianbatch_slices2_msignal"])) <= -998, np.where(data["maxtominbatch_slices2_msignal"] <= -998, np.cos(((( data["medianbatch_slices2_msignal"])* 2.0))),(-(( data["maxbatch_msignal"])))) ,(-(( data["medianbatch_slices2_msignal"])))))))+
0.050000*np.tanh(((np.cos(( np.where(((data["signal_shift_-1"])*(((data["maxtominbatch_msignal"])/ 2.0)))<= -998, data["signal_shift_-1"], np.maximum(((((( -(( data["signal_shift_-1"])))) *(((data["signal_shift_-1"])/ 2.0))))),(( data["maxtominbatch_msignal"])))))))* 2.0)) +
0.050000*np.tanh(np.sin(( np.minimum(((np.minimum(((((((( np.tanh(( data["stdbatch_msignal"])))*(np.cos(( data["medianbatch_slices2"])))))>(data["abs_avgbatch_msignal"])) *1.))) ,(( data["minbatch_msignal"]))))),(( data["minbatch_msignal"])))))) +
0.050000*np.tanh(((((data["abs_avgbatch_slices2"])+(data["medianbatch_msignal"])))*(np.where(data["minbatch_msignal"] > -998, data["medianbatch_msignal"],(( np.minimum(((np.where(data["signal_shift_-1_msignal"] > -998, data["abs_avgbatch_slices2"],(( data["abs_avgbatch_slices2"])*(data["medianbatch_msignal"]))))),(( data["medianbatch_msignal"])))) -(( 6.0)))))))+
0.050000*np.tanh(np.sin(( np.where(np.sin(( np.where(((data["rangebatch_slices2"])*(((data["maxbatch_slices2"])-(data["signal_shift_-1"])))) > -998,(( data["stdbatch_slices2"])*(data["meanbatch_msignal"])) ,(( data["stdbatch_msignal"])*(data["mean_abs_chgbatch_msignal"])))))> -998, data["minbatch_msignal"],(( data["stdbatch_msignal"])*(data["mean_abs_chgbatch_msignal"])))))) +
0.050000*np.tanh(np.cos(( np.maximum(((np.where(data["abs_avgbatch_slices2_msignal"] <= -998,(( np.sin(( data["medianbatch_msignal"])))+(data["mean_abs_chgbatch_slices2_msignal"])) , data["signal_shift_-1"]))),(( np.where(data["mean_abs_chgbatch_slices2_msignal"] <= -998, np.cos(((( data["medianbatch_msignal"])/ 2.0))), data["abs_avgbatch_slices2_msignal"])))))))+
0.050000*np.tanh(np.maximum(((((np.where(np.minimum(((data["minbatch_msignal"])) ,(( np.minimum(((np.maximum(((data["stdbatch_slices2_msignal"])) ,(( data["abs_maxbatch"]))))),(( np.maximum(((data["minbatch_msignal"])) ,(( data["medianbatch_msignal"])))))))))> -998, np.sin(( data["abs_avgbatch_slices2"])) , np.where(np.minimum(((data["maxbatch_msignal"])) ,(((( data["abs_avgbatch_slices2"])* 2.0)))) <= -998,(4.27560997009277344), np.sin(( data["abs_avgbatch_slices2"])))))* 2.0))),(( np.sin(( data["abs_avgbatch_slices2"])))))) +
0.050000*np.tanh(((((np.sin(((((((( data["abs_minbatch_slices2_msignal"])>(np.sin(( data["meanbatch_slices2_msignal"])))) *1.))+(data["rangebatch_msignal"])) /2.0)))) +(np.maximum(((np.sin(( data["medianbatch_msignal"])))) ,(( np.minimum(((data["maxbatch_msignal"])) ,(((( np.sin(( np.maximum(((data["abs_minbatch_slices2_msignal"])) ,(( data["abs_minbatch_slices2_msignal"])))))) * 2.0)))))))))) * 2.0)))
 def GP_class_4(self,data):
return self.Output(-2.516509 +
0.050000*np.tanh(((np.where(data["meanbatch_msignal"] > -998, data["meanbatch_slices2"],(( np.where(data["meanbatch_msignal"] > -998, data["meanbatch_slices2"],(( np.minimum(((np.maximum(((data["medianbatch_slices2"])) ,(((((( data["abs_maxbatch_slices2"])* 2.0)) / 2.0)))))) ,(((-(((((data["medianbatch_slices2"])+(( -(( data["meanbatch_slices2"])))))/2.0)))))))) / 2.0)))/ 2.0)))+(data["medianbatch_slices2"])))+
0.050000*np.tanh(np.where(data["medianbatch_slices2"] > -998, data["medianbatch_slices2"], np.where(data["signal"] > -998, data["signal_shift_+1"], data["abs_avgbatch_slices2_msignal"])))+
0.050000*np.tanh(np.where(np.maximum(((data["signal_shift_-1"])) ,(((((data["mean_abs_chgbatch_slices2_msignal"])+(data["abs_avgbatch_msignal"])) /2.0)))) <= -998, np.tanh(( data["signal_shift_-1"])) , data["signal"])) +
0.050000*np.tanh(np.where(((data["signal_shift_+1"])+(data["meanbatch_slices2"])) > -998, data["meanbatch_slices2"], np.where(np.maximum(((((( data["meanbatch_slices2"])>(data["abs_maxbatch_msignal"])) *1.))) ,(( data["stdbatch_slices2"])))> -998, np.where(( 5.59334421157836914)> -998, data["medianbatch_slices2"], data["maxbatch_msignal"]), data["medianbatch_slices2"])))+
0.050000*np.tanh(((((((( 8.0)) *(data["abs_avgbatch_slices2"])))/ 2.0)) *(np.where(data["signal"] > -998, np.sin(( data["medianbatch_slices2"])) , np.where(data["meanbatch_slices2"] > -998, np.tanh(( np.sin(((( np.where(data["maxtominbatch_msignal"] > -998, data["signal"], data["medianbatch_slices2"])) * 2.0))))), np.cos(( data["maxbatch_msignal"])))))))+
0.050000*np.tanh(np.where(( -(( data["minbatch_slices2_msignal"])))> -998, data["medianbatch_slices2"], np.where(((data["rangebatch_slices2"])-(data["maxbatch_slices2_msignal"])) <= -998, np.minimum(((data["signal"])) ,(( data["abs_minbatch_msignal"]))),(( np.where(data["signal_shift_+1"] > -998,(( data["mean_abs_chgbatch_slices2"])*(data["signal_shift_-1_msignal"])) , data["signal_shift_+1"])) / 2.0)))) +
0.050000*np.tanh(np.where(np.sin(((((data["signal"])>(np.where(((( data["signal_shift_+1"])>(data["signal_shift_+1"])) *1.) <= -998, data["signal"], np.minimum(((data["rangebatch_msignal"])) ,(((( data["meanbatch_slices2"])/ 2.0)))))))*1.))) <= -998,(((((( data["signal_shift_+1"])+(data["medianbatch_slices2"])) /2.0)) +(data["signal_shift_+1"])) /2.0), data["medianbatch_slices2"])) +
0.050000*np.tanh(np.where(data["signal_shift_-1"] <= -998, data["abs_avgbatch_slices2_msignal"], np.minimum(((data["signal_shift_-1"])) ,(((((data["medianbatch_slices2"])+(np.minimum(((np.sin(( np.where(data["signal"] <= -998,(( data["stdbatch_msignal"])/ 2.0), data["signal"]))))),(( data["abs_maxbatch"])))))/2.0)))))) +
0.050000*np.tanh(np.sin(( np.where(((data["meanbatch_slices2_msignal"])*(np.minimum(((data["meanbatch_slices2"])) ,(( np.sin(( data["meanbatch_slices2"])))))))> -998,(( np.sin(( np.where(data["stdbatch_slices2_msignal"] > -998, data["meanbatch_slices2"], data["abs_maxbatch"])))) * 2.0), data["abs_maxbatch_slices2"])))) +
0.050000*np.tanh(((((np.sin(( data["abs_maxbatch_slices2_msignal"])))* 2.0)) +(((( data["minbatch_slices2_msignal"])>(((data["meanbatch_slices2"])-(np.minimum(((data["abs_maxbatch"])) ,(( data["minbatch_slices2_msignal"])))))))*1.))))+
0.050000*np.tanh(((data["maxtominbatch_msignal"])*(np.cos(((( data["abs_minbatch_msignal"])-(((( np.where(np.where(((( data["maxtominbatch_msignal"])>(data["minbatch_msignal"])) *1.) <= -998, data["maxbatch_slices2_msignal"], data["signal_shift_-1"])> -998, data["maxtominbatch"], np.sin(( data["abs_maxbatch_slices2"])))) >(((( data["signal_shift_-1"])+(((data["maxbatch_slices2_msignal"])+(data["maxtominbatch_msignal"])))) /2.0)))*1.))))))))+
0.050000*np.tanh(((((np.sin(( np.maximum(((np.maximum(((np.maximum(((data["abs_maxbatch_msignal"])) ,(( data["signal"]))))),(( data["abs_maxbatch_msignal"]))))),(( data["medianbatch_msignal"])))))) *(((data["abs_maxbatch_msignal"])*(data["stdbatch_slices2"])))))-(np.cos(( data["signal_shift_+1"])))))+
0.050000*np.tanh(np.where(((data["abs_maxbatch"])*(((data["medianbatch_slices2"])*(data["stdbatch_slices2"])))) <= -998, np.where(np.sin(( data["medianbatch_slices2"])) <= -998, data["rangebatch_slices2_msignal"],(( data["meanbatch_msignal"])* 2.0)) ,(( data["rangebatch_slices2_msignal"])*(np.sin(( np.where(((data["minbatch"])* 2.0)> -998, data["medianbatch_slices2"], data["signal"])))))))+
0.050000*np.tanh(((data["abs_maxbatch_slices2_msignal"])*(np.sin(( np.where(data["abs_maxbatch_msignal"] > -998, data["medianbatch_slices2"],(( np.maximum(((data["minbatch"])) ,(((((( data["signal_shift_+1_msignal"])/ 2.0)) / 2.0)))))/ 2.0)))))))+
0.050000*np.tanh(((((data["minbatch_slices2_msignal"])*(np.where(data["meanbatch_msignal"] > -998, data["stdbatch_slices2_msignal"], np.minimum(((data["signal_shift_+1_msignal"])) ,(((((((((data["signal_shift_-1_msignal"])*(data["minbatch_slices2_msignal"])))* 2.0)) >(np.where(np.cos(( data["stdbatch_slices2_msignal"])) <= -998,(( data["minbatch_slices2"])* 2.0), data["stdbatch_slices2"])))*1.))))))))* 2.0)) +
0.050000*np.tanh(((data["stdbatch_msignal"])*(((np.sin(( np.where(((np.sin(((((( data["stdbatch_msignal"])*(np.where(data["maxbatch_msignal"] > -998, data["minbatch_msignal"], np.maximum(((data["minbatch_msignal"])) ,(( np.tanh(( data["abs_maxbatch_slices2"])))))))))* 2.0)))) * 2.0)> -998, data["abs_maxbatch_slices2"], data["stdbatch_msignal"])))) * 2.0)))) +
0.050000*np.tanh(((( np.sin(((((data["minbatch_slices2"])<=(np.sin(( data["minbatch_slices2"])))) *1.))))+(data["signal"])) /2.0)) +
0.050000*np.tanh(((((( -(( np.where(((((((data["abs_avgbatch_slices2_msignal"])* 2.0)) * 2.0)) * 2.0)> -998, data["abs_minbatch_msignal"], np.where(data["meanbatch_slices2"] > -998,(( np.minimum(((((np.tanh(( data["abs_avgbatch_slices2_msignal"])))* 2.0))),(( data["abs_minbatch_msignal"])))) -(data["abs_avgbatch_slices2_msignal"])) ,(( data["abs_avgbatch_slices2_msignal"])* 2.0)))))))-(((data["abs_avgbatch_slices2_msignal"])* 2.0)))) * 2.0)) +
0.050000*np.tanh(((((( 10.0)) *(np.tanh(( np.tanh(((( data["mean_abs_chgbatch_slices2"])-(np.maximum(((data["abs_avgbatch_msignal"])) ,(((((np.sin(( np.maximum(((data["minbatch_slices2"])) ,(( data["abs_avgbatch_msignal"])))))) +(((data["minbatch_slices2"])*(data["abs_avgbatch_msignal"])))) /2.0)))))))))))))* 2.0)) +
0.050000*np.tanh(np.where(data["abs_avgbatch_msignal"] <= -998,(((((( np.sin(( data["medianbatch_slices2"])))>(((((( np.cos(((-(( data["medianbatch_slices2"])))))) *(data["medianbatch_slices2"])))>(((data["meanbatch_slices2"])/ 2.0)))*1.))) *1.))<=(np.maximum(((data["abs_avgbatch_msignal"])) ,(((( data["abs_avgbatch_msignal"])* 2.0)))))) *1.) , np.sin(( data["meanbatch_slices2"])))) +
0.050000*np.tanh(np.minimum(((np.sin(( data["signal"])))) ,(( np.where(data["abs_avgbatch_slices2_msignal"] > -998, data["meanbatch_slices2"], np.where(data["abs_maxbatch"] > -998, data["meanbatch_slices2"], np.where(data["meanbatch_slices2"] <= -998, data["maxtominbatch"], data["signal_shift_-1"])))))))+
0.050000*np.tanh(((((np.sin(( data["abs_maxbatch_msignal"])))-(data["abs_avgbatch_msignal"])))*(((( np.maximum(((((((np.sin(( data["abs_maxbatch_slices2_msignal"])))-(data["abs_avgbatch_msignal"])))-(np.cos(( np.where(data["rangebatch_slices2_msignal"] <= -998, data["abs_maxbatch_msignal"],(( data["medianbatch_slices2_msignal"])+(data["abs_avgbatch_slices2_msignal"]))))))))),(( data["medianbatch_msignal"])))) +(((data["rangebatch_slices2_msignal"])* 2.0)))/2.0)))) +
0.050000*np.tanh(np.minimum(((np.minimum(((np.minimum(((((np.minimum(((data["medianbatch_slices2"])) ,(((( data["medianbatch_slices2"])*(((data["abs_maxbatch"])*(np.sin(( np.sin(( data["signal"])))))))))))) *(data["abs_maxbatch_msignal"])))) ,(( np.minimum(((data["medianbatch_slices2"])) ,(((((6.26549148559570312)) *(np.sin(( data["abs_maxbatch_msignal"])))))))))))) ,(( data["signal"]))))),(((((6.26549148559570312)) *(data["signal"])))))) +
0.050000*np.tanh(np.where(((( data["medianbatch_msignal"])<=(data["signal_shift_+1_msignal"])) *1.) > -998, data["medianbatch_slices2"],(((( np.sin(( data["medianbatch_slices2"])))/ 2.0)) * 2.0)))+
0.050000*np.tanh(((np.where(data["minbatch_msignal"] <= -998, data["abs_minbatch_slices2"], np.where(data["abs_maxbatch_msignal"] <= -998, data["abs_maxbatch_msignal"], np.where(data["abs_minbatch_slices2"] <= -998, np.sin(( data["signal"])) , np.where(np.sin(( data["signal_shift_-1"])) <= -998, data["rangebatch_slices2_msignal"], np.where(data["abs_maxbatch_msignal"] <= -998, np.where(data["abs_minbatch_slices2"] <= -998, np.cos(( data["signal_shift_+1"])) , data["signal"]), np.sin(( data["abs_maxbatch_msignal"])))))))) * 2.0)) +
0.050000*np.tanh(np.sin(( np.where(np.sin(( data["meanbatch_slices2"])) > -998, data["meanbatch_slices2"],(((data["rangebatch_slices2"])>(((np.sin(( np.sin(( data["meanbatch_msignal"])))))/ 2.0)))*1.))))) +
0.050000*np.tanh(((data["abs_maxbatch_slices2_msignal"])*(np.where(np.tanh(( data["maxbatch_slices2"])) <= -998,(( data["meanbatch_slices2"])* 2.0), np.sin(( data["abs_maxbatch_msignal"])))))) +
0.050000*np.tanh(np.sin(( np.where(np.where(np.maximum(((data["abs_maxbatch_msignal"])) ,(( np.where(( 9.63134956359863281)<= -998, np.sin(( data["medianbatch_slices2_msignal"])) ,(9.63134956359863281)))))<= -998, data["abs_maxbatch_msignal"],(-(( np.maximum(((data["abs_maxbatch_msignal"])) ,(( np.where(( 10.77424335479736328)<= -998,(9.63134956359863281), data["medianbatch_slices2_msignal"])))))))) <= -998, data["signal_shift_+1"], data["abs_maxbatch_msignal"])))) +
0.050000*np.tanh(np.where(( -(( np.sin(( data["maxtominbatch_slices2"])))))<= -998, data["signal_shift_-1"],(( np.sin(((( data["abs_minbatch_slices2_msignal"])+(data["abs_minbatch_msignal"])))))* 2.0)))+
0.050000*np.tanh(((np.where(data["abs_avgbatch_slices2_msignal"] <= -998, data["medianbatch_slices2"],(((((( data["stdbatch_msignal"])*(np.sin(( data["abs_minbatch_msignal"])))))-(((data["abs_avgbatch_slices2_msignal"])*(np.where(data["minbatch_msignal"] <= -998, data["minbatch_msignal"], data["abs_avgbatch_slices2_msignal"])))))) * 2.0)))* 2.0)) +
0.050000*np.tanh(((np.where(np.sin(( data["abs_maxbatch"])) <= -998, data["mean_abs_chgbatch_msignal"], np.where(data["signal_shift_+1"] <= -998,(((( data["mean_abs_chgbatch_msignal"])*(np.sin(( np.sin(( data["abs_maxbatch"])))))))* 2.0),(( data["abs_minbatch_msignal"])-(( -(( data["stdbatch_msignal"])))))))) *(np.sin(( data["abs_maxbatch"])))))+
0.050000*np.tanh(((((((((((((np.cos(((((( data["abs_avgbatch_msignal"])* 2.0)) -(data["abs_avgbatch_msignal"])))))-(data["abs_avgbatch_msignal"])))* 2.0)) -(((data["meanbatch_slices2_msignal"])*(data["medianbatch_msignal"])))))-(( -(( data["medianbatch_msignal"])))))) * 2.0)) * 2.0)) +
0.050000*np.tanh(((np.cos(( np.where(np.maximum(((data["medianbatch_msignal"])) ,(((( data["minbatch_msignal"])+(( 5.0)))))) > -998, data["rangebatch_msignal"], np.cos(( np.minimum(((data["signal"])) ,(( data["abs_maxbatch_slices2_msignal"])))))))))* 2.0)) +
0.050000*np.tanh(((((data["signal"])*(np.sin(( np.maximum(((((data["signal_shift_-1_msignal"])* 2.0))),(( np.maximum(((data["signal"])) ,(( data["abs_maxbatch_slices2_msignal"])))))))))))*(((( np.sin(( data["signal_shift_-1_msignal"])))+(data["signal"])) /2.0)))) +
0.050000*np.tanh(((np.where(np.tanh(((((( np.where(data["rangebatch_slices2"] > -998, np.sin(( data["abs_maxbatch_slices2_msignal"])) ,(( data["signal_shift_+1"])/ 2.0)))* 2.0)) * 2.0)))> -998, np.sin(( data["rangebatch_slices2"])) ,(( data["maxbatch_slices2"])* 2.0)))* 2.0)) +
0.050000*np.tanh(((( data["minbatch_slices2"])+(((data["maxbatch_slices2_msignal"])*(((( np.minimum(((data["minbatch_slices2"])) ,(( data["stdbatch_slices2_msignal"])))) +(((data["maxbatch_slices2_msignal"])*(((( -(( data["rangebatch_slices2"])))) *(np.sin(((( data["abs_maxbatch_msignal"])* 2.0)))))))))/2.0)))))/2.0)) +
0.050000*np.tanh(((((data["abs_maxbatch_slices2"])*(np.minimum(((data["minbatch"])) ,(( data["abs_maxbatch_msignal"])))))) *(np.sin(( np.where(data["maxbatch_slices2_msignal"] > -998,(( data["maxbatch_slices2_msignal"])* 2.0), data["maxtominbatch_slices2"])))))) +
0.050000*np.tanh(np.where(data["abs_minbatch_slices2_msignal"] > -998,(( np.sin(( data["minbatch_msignal"])))* 2.0),(((( np.sin(( np.sin(((-(( np.sin(( data["rangebatch_msignal"])))))))))) * 2.0)) +(np.minimum(((data["stdbatch_slices2_msignal"])) ,(( data["stdbatch_slices2_msignal"])))))))+
0.050000*np.tanh(np.where(((data["abs_maxbatch"])/ 2.0)> -998,(( np.where(( 7.26189327239990234)> -998, data["stdbatch_msignal"], data["maxtominbatch_slices2_msignal"])) *(np.minimum(((((( 7.26189327239990234)) *(( -(( np.sin(((( data["abs_maxbatch"])/ 2.0)))))))))) ,(( data["maxbatch_slices2_msignal"]))))),(((((((data["abs_maxbatch"])/ 2.0)) * 2.0)) <=(( 7.26189327239990234)))*1.))) +
0.050000*np.tanh(((data["abs_maxbatch_msignal"])*(np.sin(( np.where(data["abs_maxbatch_msignal"] <= -998, data["abs_maxbatch_msignal"],(( np.sin(( np.where(data["signal_shift_+1"] <= -998, data["abs_maxbatch_msignal"],(( data["abs_minbatch_msignal"])* 2.0)))))* 2.0)))))))+
0.050000*np.tanh(((((np.sin(( np.where(np.maximum(((np.where(((data["rangebatch_slices2_msignal"])-(np.sin(( data["minbatch_slices2_msignal"])))) > -998, np.sin(((( np.sin(( data["abs_maxbatch_slices2_msignal"])))* 2.0))),(((np.tanh(( data["medianbatch_slices2"])))+(((( data["signal_shift_-1"])+(data["abs_maxbatch_slices2_msignal"])) /2.0)))/2.0)))) ,(( data["abs_maxbatch_msignal"])))> -998, np.sin(( data["abs_maxbatch_slices2_msignal"])) , data["signal_shift_-1"])))) * 2.0)) * 2.0)) +
0.050000*np.tanh(((((np.where(np.sin(((( np.sin(( np.sin(( data["maxbatch_msignal"])))))* 2.0)))<= -998,(( np.sin(((( data["minbatch_msignal"])* 2.0)))) * 2.0), np.sin(((( np.sin(( data["minbatch_msignal"])))* 2.0)))))* 2.0)) * 2.0)) +
0.050000*np.tanh(((data["abs_maxbatch"])*(np.cos(( np.where(( 7.0)<= -998, data["stdbatch_msignal"],(((((np.cos(((-(((( data["signal_shift_-1"])+(data["abs_maxbatch_slices2"])))))))) >(((np.cos(( data["meanbatch_msignal"])))*(( -(( data["abs_maxbatch_slices2_msignal"])))))))*1.))+(data["abs_maxbatch_slices2"])))))))) +
0.050000*np.tanh(((np.where(np.where(np.minimum(((data["maxbatch_slices2"])) ,(( np.tanh(( data["medianbatch_slices2_msignal"])))))<= -998, data["stdbatch_msignal"],(( data["abs_maxbatch_slices2"])/ 2.0)) <= -998, data["medianbatch_slices2_msignal"],(( np.where(data["rangebatch_slices2"] <= -998, np.where(data["signal_shift_-1"] <= -998, data["minbatch_msignal"],(( data["abs_minbatch_msignal"])* 2.0)) , np.cos(((( np.tanh(( data["stdbatch_msignal"])))-(data["abs_maxbatch"])))))) * 2.0)))* 2.0)) +
0.050000*np.tanh(((((data["meanbatch_slices2"])+(((data["medianbatch_msignal"])*(data["medianbatch_msignal"])))))+(((((data["meanbatch_slices2"])+(((data["meanbatch_msignal"])*(data["meanbatch_slices2"])))))*(((data["medianbatch_msignal"])*(data["abs_minbatch_slices2_msignal"])))))))+
0.050000*np.tanh(np.where(np.sin(( data["maxtominbatch_slices2"])) <= -998,(( data["maxbatch_msignal"])*(np.tanh(((5.0))))),(((5.0)) +(((data["abs_avgbatch_slices2"])*(np.where(data["medianbatch_msignal"] > -998,(((( data["mean_abs_chgbatch_msignal"])+(data["abs_minbatch_slices2"])))+(np.tanh(( data["abs_avgbatch_msignal"])))) , np.tanh(( data["abs_avgbatch_msignal"])))))))))+
0.050000*np.tanh(((np.where(data["abs_avgbatch_slices2"] > -998,(((data["rangebatch_msignal"])+(np.maximum(((data["maxbatch_slices2_msignal"])) ,(((((data["signal_shift_+1_msignal"])+(((( data["signal_shift_-1"])>(data["abs_maxbatch_msignal"])) *1.))) /2.0)))))) /2.0), data["rangebatch_slices2_msignal"])) *(np.sin(( data["abs_maxbatch_msignal"])))))+
0.050000*np.tanh(((((((np.where(data["minbatch"] <= -998, data["abs_avgbatch_slices2"], np.cos(( data["maxbatch_slices2_msignal"])))) +(np.where(data["medianbatch_slices2"] <= -998, data["abs_avgbatch_slices2"], np.cos(( data["maxbatch_slices2_msignal"])))))) *(( -(((10.0)))))))-(np.sin(( data["abs_avgbatch_slices2"])))))+
0.050000*np.tanh(((((np.where(( -(((7.23746728897094727)))) <= -998, data["abs_minbatch_slices2_msignal"], np.tanh(((( np.where(((( data["medianbatch_msignal"])>(data["signal"])) *1.) <= -998, data["medianbatch_msignal"], np.tanh(( np.sin(( data["abs_minbatch_slices2_msignal"])))))) * 2.0)))))* 2.0)) *(data["stdbatch_msignal"])))+
0.050000*np.tanh(((np.sin(( np.maximum(((data["abs_maxbatch_msignal"])) ,(( np.maximum(((data["signal"])) ,(((( np.sin(( np.maximum(((data["abs_maxbatch_msignal"])) ,(( np.sin(( np.maximum(((np.sin(( data["abs_maxbatch"])))) ,(( np.minimum(((data["rangebatch_slices2_msignal"])) ,(( data["maxbatch_msignal"])))))))))))))) *(((( data["signal"])>(data["rangebatch_slices2_msignal"])) *1.))))))))))))*(data["rangebatch_slices2_msignal"])))+
0.050000*np.tanh(np.cos(((( data["maxtominbatch"])-(((np.where(data["minbatch_slices2"] > -998, data["maxbatch_msignal"], data["meanbatch_slices2"])) * 2.0)))))) +
0.050000*np.tanh(((((np.sin(( np.where(data["abs_maxbatch"] > -998, data["minbatch_msignal"], np.where(np.where(data["minbatch_slices2_msignal"] > -998, data["signal_shift_+1"], data["medianbatch_slices2"])> -998, np.sin(( np.where(( 10.0)> -998, data["maxbatch_slices2_msignal"], data["abs_maxbatch"]))), np.tanh(( data["minbatch_msignal"])))))))* 2.0)) * 2.0)) +
0.050000*np.tanh(((((np.sin(((-(( np.where(((((np.sin(((((-(( data["minbatch_msignal"])))) * 2.0)))) * 2.0)) * 2.0)<= -998,(( np.sin(( data["maxbatch_msignal"])))* 2.0),(( data["maxbatch_msignal"])* 2.0)))))))) * 2.0)) * 2.0)) +
0.050000*np.tanh(np.minimum(((np.sin(( np.sin(( np.where(data["medianbatch_slices2_msignal"] > -998, data["maxbatch_slices2_msignal"], data["abs_maxbatch_slices2_msignal"]))))))),(( np.where(data["maxbatch_slices2_msignal"] <= -998, np.sin(((-(( np.sin(( data["abs_avgbatch_slices2_msignal"]))))))),(( np.sin(((-(( data["mean_abs_chgbatch_slices2_msignal"])))))) * 2.0)))))) +
0.050000*np.tanh(((np.where(((np.sin(( data["rangebatch_slices2"])))* 2.0)<= -998,(( data["abs_minbatch_msignal"])* 2.0), np.where(data["minbatch"] <= -998, data["stdbatch_slices2"], np.sin(((( data["abs_minbatch_msignal"])* 2.0)))))) * 2.0)) +
0.050000*np.tanh(np.sin(( np.minimum(((np.where(data["maxtominbatch_slices2"] <= -998, data["abs_maxbatch_slices2_msignal"],(((((data["maxtominbatch_msignal"])+(data["mean_abs_chgbatch_msignal"])) /2.0)) * 2.0)))) ,(( np.where(np.tanh(((( np.cos(( data["medianbatch_slices2_msignal"])))/ 2.0)))<= -998, data["medianbatch_slices2_msignal"],(((( data["mean_abs_chgbatch_msignal"])/ 2.0)) * 2.0)))))))) +
0.050000*np.tanh(np.minimum(((np.where(((data["abs_avgbatch_msignal"])-(data["abs_avgbatch_msignal"])) <= -998, np.where(data["stdbatch_slices2_msignal"] <= -998, data["abs_avgbatch_msignal"], data["abs_avgbatch_msignal"]),(10.01193141937255859)))) ,(((( np.where(data["signal_shift_+1"] <= -998, data["abs_maxbatch_slices2"], np.sin(( data["signal"])))) * 2.0)))))+
0.050000*np.tanh(((np.cos(((( data["maxbatch_slices2"])-(np.minimum(((data["mean_abs_chgbatch_msignal"])) ,(((( data["meanbatch_msignal"])*(((data["maxbatch_msignal"])+(((( np.minimum(((data["mean_abs_chgbatch_msignal"])) ,(( np.minimum(((((data["meanbatch_slices2"])* 2.0))),(((-(( np.cos(( data["maxbatch_slices2"])))))))))))) <=(data["maxbatch_slices2_msignal"])) *1.))))))))))))) * 2.0)) +
0.050000*np.tanh(((np.sin(( data["meanbatch_msignal"])))-(((((np.maximum(((data["abs_minbatch_msignal"])) ,(( np.cos(( np.where(data["abs_minbatch_msignal"] <= -998,(( data["meanbatch_msignal"])-(np.maximum(((data["abs_minbatch_msignal"])) ,(( np.cos(( data["maxbatch_msignal"]))))))), data["maxbatch_msignal"])))))))* 2.0)) * 2.0)))) +
0.050000*np.tanh(((data["signal"])*(((data["minbatch_msignal"])*(np.where(np.where(data["medianbatch_slices2_msignal"] > -998,(( np.where(data["medianbatch_slices2"] > -998, np.where(data["maxbatch_slices2"] > -998, np.sin(( data["maxbatch_slices2"])) , data["signal_shift_-1_msignal"]), data["maxbatch_slices2"])) * 2.0), data["maxbatch_slices2"])> -998, np.sin(( data["maxbatch_slices2"])) , data["mean_abs_chgbatch_msignal"])))))) +
0.050000*np.tanh(((np.cos(((( data["abs_avgbatch_msignal"])+(np.tanh(( np.where(((np.cos(((( np.tanh(( data["abs_avgbatch_msignal"])))+(data["abs_avgbatch_msignal"])))))* 2.0)> -998, data["abs_avgbatch_slices2_msignal"],(( data["abs_avgbatch_msignal"])+(np.tanh(( data["abs_avgbatch_msignal"])))))))))))) * 2.0)) +
0.050000*np.tanh(((np.maximum(((data["abs_maxbatch_msignal"])) ,(( data["abs_maxbatch_msignal"])))) *(np.minimum(((np.cos(((( data["abs_minbatch_slices2_msignal"])+(((( np.maximum(((((((data["abs_minbatch_slices2_msignal"])+(((( np.maximum(((np.cos(( np.sin(( data["maxtominbatch"])))))) ,(( data["abs_maxbatch_msignal"])))) +(data["abs_maxbatch_msignal"])) /2.0)))) -(data["maxbatch_msignal"])))) ,(( data["maxbatch_msignal"])))) +(data["medianbatch_slices2"])) /2.0))))))),(( data["signal_shift_+1"])))))) +
0.050000*np.tanh(((np.where(np.sin(((( data["maxtominbatch"])* 2.0)))<= -998, data["rangebatch_msignal"],(( data["medianbatch_slices2_msignal"])+(np.where(data["minbatch_msignal"] > -998,(( np.sin(( data["minbatch_msignal"])))* 2.0), np.where(data["maxbatch_slices2_msignal"] > -998, data["rangebatch_msignal"], np.sin(( data["abs_avgbatch_slices2"])))))))) * 2.0)) +
0.050000*np.tanh(((( -(((( np.cos(( data["stdbatch_msignal"])))*(np.where(((( data["medianbatch_msignal"])+(data["abs_maxbatch"])) /2.0)<= -998, data["medianbatch_msignal"],(((( data["rangebatch_msignal"])+(data["stdbatch_slices2"])))+(data["meanbatch_slices2_msignal"])))))))))*(np.where(data["rangebatch_slices2_msignal"] <= -998, data["rangebatch_slices2_msignal"], data["meanbatch_slices2_msignal"])))) +
0.050000*np.tanh(((data["medianbatch_msignal"])+(np.minimum(((data["signal_shift_-1"])) ,(( np.where(data["minbatch_slices2_msignal"] <= -998, np.where(np.minimum(((data["signal_shift_-1_msignal"])) ,(( data["maxtominbatch"])))> -998, data["rangebatch_slices2"], np.sin(( data["medianbatch_msignal"]))), np.sin(( np.where(np.where(np.cos(( np.tanh(( data["medianbatch_slices2_msignal"])))) > -998, data["medianbatch_slices2"], np.sin(( data["mean_abs_chgbatch_slices2"])))> -998, data["minbatch_slices2_msignal"], data["maxbatch_slices2_msignal"])))))))))) +
0.050000*np.tanh(np.minimum(((np.sin(((( data["abs_avgbatch_msignal"])+(data["meanbatch_slices2"])))))) ,(((((data["meanbatch_slices2"])+(((data["minbatch_msignal"])*(np.tanh(((( data["abs_avgbatch_msignal"])*(data["abs_avgbatch_msignal"])))))))) /2.0)))))+
0.050000*np.tanh(((np.minimum(((np.where(((((((data["meanbatch_slices2"])<=(data["signal"])) *1.))>(((((data["medianbatch_msignal"])+(np.sin(((( np.sin(( data["mean_abs_chgbatch_msignal"])))* 2.0)))))) * 2.0)))*1.) <= -998, np.sin(( data["meanbatch_slices2"])) , np.sin(( data["signal"]))))),(((((( data["medianbatch_msignal"])+(np.sin(( data["abs_avgbatch_slices2"])))))* 2.0)))))* 2.0)) +
0.050000*np.tanh(((((((data["abs_minbatch_msignal"])+(np.sin(( data["abs_minbatch_msignal"])))))+(((( np.sin(( np.maximum(((np.sin(( np.maximum(((data["maxbatch_slices2"])) ,(( data["abs_minbatch_msignal"]))))))),(( np.cos(( data["abs_minbatch_msignal"])))))))) <=(data["abs_maxbatch_slices2_msignal"])) *1.))))*(np.sin(( np.maximum(((data["abs_maxbatch"])) ,(( data["abs_maxbatch"])))))))) +
0.050000*np.tanh(((data["medianbatch_msignal"])+(np.minimum(((((data["medianbatch_msignal"])+(np.tanh(((( data["medianbatch_slices2_msignal"])+(data["abs_maxbatch_slices2_msignal"])))))))) ,(((((((( data["rangebatch_slices2_msignal"])-(( -(( np.sin(( np.cos(( data["medianbatch_msignal"])))))))))) *(data["rangebatch_slices2"])))*(np.tanh(( np.sin(( data["maxbatch_slices2_msignal"])))))))))))) +
0.050000*np.tanh(((((data["minbatch_msignal"])* 2.0)) *(np.cos(( np.maximum(((data["maxbatch_slices2_msignal"])) ,(( np.maximum(((np.cos(( np.maximum(((data["maxbatch_slices2_msignal"])) ,(( np.sin(( np.maximum(((data["abs_maxbatch_slices2_msignal"])) ,(( np.cos(( np.cos(( data["medianbatch_msignal"])))))))))))))))) ,(( np.sin(((((( data["minbatch_msignal"])* 2.0)) *(np.cos(( data["maxbatch_slices2_msignal"])))))))))))))))))+
0.050000*np.tanh(((np.where(data["maxtominbatch_slices2"] > -998, data["abs_minbatch_slices2_msignal"], np.sin(( data["abs_maxbatch"])))) *(np.sin(( data["abs_maxbatch"])))))+
0.050000*np.tanh(((data["rangebatch_slices2_msignal"])*(np.where(((np.cos(( np.maximum(((data["maxtominbatch_msignal"])) ,(( data["maxbatch_msignal"])))))) *(data["maxtominbatch_msignal"])) <= -998, np.minimum(((((np.cos(( data["maxbatch_msignal"])))*(data["maxtominbatch_msignal"])))) ,(( data["maxtominbatch_msignal"]))), np.minimum(((((np.cos(( data["maxbatch_msignal"])))*(data["maxtominbatch_msignal"])))) ,(( data["maxbatch_msignal"])))))))+
0.050000*np.tanh(( -(((( data["abs_maxbatch"])*(((np.sin(((( np.sin(((( np.where(((data["signal"])-(( -(( data["signal"])))))> -998, data["signal"], data["signal"])) * 2.0)))) * 2.0)))) * 2.0)))))))+
0.050000*np.tanh(((((( -(((( data["minbatch_slices2_msignal"])*(np.where(data["minbatch_slices2"] <= -998,(( data["mean_abs_chgbatch_msignal"])*(data["mean_abs_chgbatch_slices2_msignal"])) ,(((np.sin(( data["abs_maxbatch_slices2_msignal"])))+(data["medianbatch_msignal"])) /2.0)))))))) * 2.0)) -(data["medianbatch_msignal"])))+
0.050000*np.tanh(((data["rangebatch_msignal"])*(np.minimum(((np.cos(( np.where(( -(( data["maxtominbatch_msignal"])))> -998, data["rangebatch_msignal"], np.minimum(((data["minbatch"])) ,(((( np.maximum(((data["rangebatch_msignal"])) ,(( data["minbatch_slices2_msignal"])))) *(( 8.39901733398437500))))))))))),(( np.sin(( data["minbatch_msignal"])))))))) +
0.050000*np.tanh(((np.sin(( data["medianbatch_slices2"])))*(((data["rangebatch_msignal"])-(((data["abs_maxbatch_msignal"])-(np.tanh(((((( data["abs_maxbatch_slices2_msignal"])+(np.sin(( np.sin(( data["rangebatch_msignal"])))))))+(( 10.0)))))))))))) +
0.050000*np.tanh(((((((((data["medianbatch_msignal"])-(((np.cos(( data["maxbatch_msignal"])))* 2.0)))) *(((((data["rangebatch_slices2"])-(np.sin(( data["minbatch_slices2_msignal"])))))-(((data["signal"])+(np.cos(((((( data["minbatch_slices2_msignal"])-(np.cos(( data["meanbatch_slices2_msignal"])))))* 2.0)))))))))) *(data["abs_maxbatch"])))-(data["abs_minbatch_msignal"])))+
0.050000*np.tanh(np.where(data["abs_minbatch_slices2"] > -998,(((data["meanbatch_slices2_msignal"])+(data["minbatch_slices2"])) /2.0),(-(( np.tanh(( data["abs_minbatch_slices2"])))))))+
0.050000*np.tanh(((((((np.sin(( np.sin(( data["abs_minbatch_slices2_msignal"])))))*(data["meanbatch_msignal"])))* 2.0)) * 2.0)) +
0.050000*np.tanh(np.where(data["maxbatch_slices2"] <= -998, data["maxtominbatch"],(((( np.sin(( data["abs_maxbatch_slices2_msignal"])))*(((( data["maxbatch_slices2_msignal"])+(((np.where(np.cos(( data["abs_maxbatch_slices2_msignal"])) > -998,(( np.minimum(((((( data["maxtominbatch"])+(data["signal_shift_-1_msignal"])) /2.0))),(((( data["medianbatch_msignal"])* 2.0)))))+(data["maxbatch_msignal"])) , data["abs_maxbatch_slices2_msignal"])) * 2.0)))/2.0)))) * 2.0)))+
0.050000*np.tanh(((np.minimum(((np.sin(( data["abs_maxbatch_slices2_msignal"])))) ,(( np.where(((( data["abs_minbatch_slices2_msignal"])+(np.minimum(((data["abs_maxbatch_slices2_msignal"])) ,(( np.sin(( data["abs_maxbatch_msignal"])))))))/2.0)> -998, data["abs_minbatch_slices2_msignal"], data["stdbatch_slices2"])))))+(((((np.where(data["abs_maxbatch_slices2_msignal"] > -998, np.sin(( data["abs_maxbatch_slices2_msignal"])) , np.where(data["meanbatch_slices2_msignal"] > -998, data["abs_maxbatch_slices2_msignal"], data["abs_minbatch_msignal"])))* 2.0)) * 2.0)))) +
0.050000*np.tanh(np.where(data["maxtominbatch"] > -998,(( data["meanbatch_slices2"])*(np.minimum(((np.sin(( np.maximum(((data["signal_shift_+1"])) ,(( data["maxbatch_msignal"]))))))),(((((np.minimum(((data["maxtominbatch"])) ,(( data["minbatch_slices2"])))) <=(np.minimum(((( 12.09745597839355469))),(( np.cos(( data["maxtominbatch"])))))))*1.)))))),(14.58901405334472656)))+
0.050000*np.tanh(((np.minimum(((np.where(data["medianbatch_slices2_msignal"] > -998, data["medianbatch_slices2_msignal"], data["meanbatch_msignal"]))),(((( data["minbatch"])*(np.sin(( data["medianbatch_slices2_msignal"])))))))) * 2.0)) +
0.050000*np.tanh(np.sin(((( np.minimum(((data["maxbatch_msignal"])) ,(( np.sin(((( np.minimum(((np.where(data["stdbatch_slices2"] > -998, data["signal_shift_+1"],(( data["rangebatch_slices2_msignal"])/ 2.0)))) ,(( np.where(np.where(data["abs_minbatch_msignal"] > -998, np.sin(( data["abs_minbatch_msignal"])) , data["meanbatch_slices2_msignal"])> -998, data["abs_minbatch_msignal"], data["rangebatch_slices2"])))))* 2.0)))))))* 2.0)))) +
0.050000*np.tanh(((((data["mean_abs_chgbatch_msignal"])*(data["abs_maxbatch_slices2"])))*(np.sin(((( data["abs_maxbatch_slices2"])+(((( np.minimum(((data["abs_maxbatch_slices2"])) ,(( data["maxbatch_slices2_msignal"])))) <=(np.cos(( np.where(( -(( data["abs_minbatch_slices2_msignal"])))<= -998,(7.36450386047363281), data["maxbatch_msignal"])))))*1.))))))))+
0.050000*np.tanh(((data["abs_minbatch_slices2_msignal"])*(np.sin(( data["abs_maxbatch"])))))+
0.050000*np.tanh(np.where(data["mean_abs_chgbatch_msignal"] <= -998, data["mean_abs_chgbatch_slices2"],(((( data["abs_minbatch_slices2"])+(data["minbatch_msignal"])))*(np.sin(((( np.sin(((( np.where(np.sin(( np.cos(( data["signal"])))) <= -998, data["meanbatch_slices2"], data["maxbatch_msignal"])) * 2.0)))) * 2.0)))))))+
0.050000*np.tanh(((((data["abs_minbatch_slices2_msignal"])+(((( 7.25954723358154297)) *(( -(( np.cos(((( np.where(((data["mean_abs_chgbatch_msignal"])*(data["abs_minbatch_slices2_msignal"])) <= -998, np.where(((data["mean_abs_chgbatch_msignal"])-(data["abs_avgbatch_slices2_msignal"])) > -998, data["abs_minbatch_slices2_msignal"],(7.25954723358154297)) , data["mean_abs_chgbatch_msignal"])) * 2.0)))))))))))+(data["mean_abs_chgbatch_msignal"])))+
0.050000*np.tanh(((np.sin(( np.sin(((( np.sin(((( np.where(data["meanbatch_slices2_msignal"] > -998, np.where(data["abs_avgbatch_slices2_msignal"] > -998, data["abs_minbatch_slices2_msignal"], data["meanbatch_slices2_msignal"]), data["abs_minbatch_msignal"])) * 2.0)))) * 2.0)))))) * 2.0)) +
0.050000*np.tanh(( -(((((((((data["stdbatch_slices2_msignal"])+(((data["maxbatch_msignal"])+(data["abs_maxbatch_slices2_msignal"])))) /2.0)) +(np.where(( -(( np.sin(((( data["abs_maxbatch_slices2_msignal"])* 2.0)))))) <= -998,(( data["stdbatch_slices2_msignal"])+(data["abs_maxbatch_slices2_msignal"])) , data["meanbatch_slices2"])))) *(np.sin(((( data["stdbatch_slices2_msignal"])* 2.0)))))))))+
0.050000*np.tanh(np.sin(( np.cos(( np.where(((((data["stdbatch_slices2"])* 2.0)) * 2.0)> -998, data["abs_avgbatch_msignal"],(((( data["minbatch_slices2_msignal"])-(((data["abs_avgbatch_msignal"])/ 2.0)))) * 2.0)))))))+
0.050000*np.tanh(((np.maximum(((np.where(np.where(data["maxtominbatch_slices2_msignal"] <= -998, data["meanbatch_msignal"], data["medianbatch_slices2_msignal"])> -998, data["minbatch_msignal"], np.sin(( data["maxtominbatch_slices2_msignal"]))))),(((( np.where(np.tanh(( np.cos(( data["abs_avgbatch_slices2_msignal"])))) > -998,(-(((( np.sin(( data["meanbatch_msignal"])))* 2.0)))) ,(( np.tanh(( data["rangebatch_slices2"])))* 2.0)))* 2.0)))))* 2.0)) +
0.050000*np.tanh(((((np.where(data["abs_minbatch_msignal"] <= -998, data["medianbatch_slices2_msignal"], data["abs_minbatch_slices2_msignal"])) * 2.0)) *(np.where(np.maximum(((data["abs_maxbatch_slices2_msignal"])) ,(( np.where(np.maximum(((data["abs_minbatch_msignal"])) ,(( np.sin(( data["medianbatch_slices2_msignal"])))))> -998, np.cos(( data["mean_abs_chgbatch_slices2"])) ,(-(( data["mean_abs_chgbatch_slices2_msignal"])))))))> -998, np.cos(( data["abs_minbatch_msignal"])) , data["medianbatch_slices2_msignal"])))) +
0.050000*np.tanh(np.where(((data["abs_minbatch_msignal"])+(data["abs_minbatch_msignal"])) <= -998,(10.07492733001708984),(( data["medianbatch_msignal"])+(((np.sin(( data["abs_minbatch_msignal"])))*(np.where(data["medianbatch_msignal"] <= -998,(( data["medianbatch_msignal"])+(data["medianbatch_msignal"])) , data["abs_minbatch_msignal"])))))))+
0.050000*np.tanh(((( data["medianbatch_msignal"])+(np.where(( -(((( data["medianbatch_slices2_msignal"])+(np.where(np.sin(( data["minbatch_slices2_msignal"])) > -998, data["abs_avgbatch_slices2_msignal"], np.sin(( data["medianbatch_msignal"])))))))) <= -998, np.tanh(( np.sin(( data["maxbatch_slices2_msignal"])))) ,(((((np.sin(( data["minbatch_slices2_msignal"])))* 2.0)) <=(data["maxbatch_slices2_msignal"])) *1.))))/2.0)) +
0.050000*np.tanh(((np.where(( 5.81791639328002930)<= -998, data["maxbatch_msignal"], np.sin(( np.sin(( np.where(np.sin(( data["maxbatch_slices2"])) > -998, np.sin(( data["maxbatch_slices2"])) , data["mean_abs_chgbatch_slices2"])))))))*(data["mean_abs_chgbatch_msignal"])))+
0.050000*np.tanh(((((np.sin(( np.where(np.where(np.tanh(( data["mean_abs_chgbatch_slices2_msignal"])) <= -998, data["minbatch_slices2_msignal"], data["abs_maxbatch_msignal"])<= -998, data["minbatch_slices2_msignal"], data["abs_maxbatch_msignal"])))) * 2.0)) +(((data["mean_abs_chgbatch_msignal"])-(( -(((((((data["mean_abs_chgbatch_msignal"])>(((data["abs_maxbatch"])*(data["stdbatch_msignal"])))) *1.))* 2.0)))))))))+
0.050000*np.tanh(((((np.where(data["abs_minbatch_msignal"] > -998,(( data["abs_maxbatch_slices2"])*(data["meanbatch_slices2"])) , np.where(data["meanbatch_slices2"] <= -998, data["mean_abs_chgbatch_slices2"], np.sin(( data["minbatch_slices2_msignal"])))))*(np.cos(((((np.sin(( data["minbatch_slices2_msignal"])))+(data["abs_minbatch_msignal"])) /2.0)))))) -(np.maximum(((data["signal_shift_-1"])) ,(( data["abs_minbatch_msignal"])))))) +
0.050000*np.tanh(np.where(data["medianbatch_msignal"] <= -998,(( data["signal_shift_-1_msignal"])+(np.cos(( np.where(np.where(((np.maximum(((data["maxtominbatch_msignal"])) ,(( data["abs_avgbatch_msignal"])))) * 2.0)<= -998, data["stdbatch_slices2_msignal"],(( np.maximum(((data["maxtominbatch_msignal"])) ,(( data["rangebatch_slices2"])))) * 2.0)) <= -998, data["signal_shift_+1"],(( data["maxtominbatch"])* 2.0)))))) , np.sin(( data["abs_maxbatch_slices2_msignal"])))) +
0.050000*np.tanh(((((data["abs_maxbatch_slices2"])-(data["mean_abs_chgbatch_slices2_msignal"])))*(((np.where(( -(((((((data["meanbatch_msignal"])+(data["meanbatch_msignal"])) /2.0)) +(data["medianbatch_msignal"])))))<= -998, data["medianbatch_msignal"], np.cos(((((data["medianbatch_msignal"])+(((((( data["meanbatch_msignal"])+(data["meanbatch_msignal"])) /2.0)) +(data["medianbatch_msignal"])))) /2.0)))))* 2.0)))) +
0.050000*np.tanh(((data["mean_abs_chgbatch_slices2_msignal"])*(( -(( np.cos(( np.minimum(((data["meanbatch_slices2_msignal"])) ,(((((( data["mean_abs_chgbatch_slices2_msignal"])*(( -(( np.cos(( np.minimum(((data["meanbatch_slices2_msignal"])) ,(( data["stdbatch_slices2_msignal"])))))))))))-(np.cos(( np.sin(( data["meanbatch_slices2_msignal"])))))))))))))))))+
0.050000*np.tanh(((data["medianbatch_msignal"])-(((((((data["maxtominbatch"])-(np.where(np.where(data["mean_abs_chgbatch_slices2_msignal"] <= -998, data["abs_maxbatch_slices2"],(( data["abs_minbatch_msignal"])* 2.0)) > -998,(( data["mean_abs_chgbatch_slices2_msignal"])*(data["signal_shift_-1"])) ,(( data["mean_abs_chgbatch_slices2_msignal"])* 2.0)))))+(((data["mean_abs_chgbatch_msignal"])-(data["signal_shift_-1"])))))+(data["maxtominbatch"])))))+
0.050000*np.tanh(((( 4.67500543594360352)) *(np.cos(((( np.maximum(((data["maxbatch_msignal"])) ,(( data["signal_shift_-1"])))) +(np.minimum(((data["maxtominbatch"])) ,(( np.minimum(((np.maximum(((data["abs_maxbatch_slices2_msignal"])) ,(( data["signal_shift_-1"]))))),(( np.minimum(((data["maxtominbatch"])) ,(( data["maxtominbatch"])))))))))))))))) +
0.050000*np.tanh(((((((((((((((data["abs_minbatch_slices2_msignal"])* 2.0)) +(np.minimum(((((((np.sin(( data["minbatch_msignal"])))* 2.0)) * 2.0))),(((( data["abs_minbatch_slices2_msignal"])* 2.0)))))) /2.0)) >(data["rangebatch_msignal"])) *1.))+(np.sin(((( data["abs_minbatch_slices2_msignal"])* 2.0)))))) * 2.0)) * 2.0)) +
0.050000*np.tanh(np.where(np.cos(( data["abs_minbatch_msignal"])) > -998,(( data["abs_minbatch_slices2_msignal"])*(np.cos(((( data["maxtominbatch_slices2_msignal"])-(data["meanbatch_slices2_msignal"])))))) , data["mean_abs_chgbatch_msignal"])) +
0.050000*np.tanh(np.sin(( np.where(data["abs_maxbatch_slices2_msignal"] > -998, np.where(np.where(data["meanbatch_slices2_msignal"] <= -998, np.maximum(((data["medianbatch_slices2"])) ,(((((data["abs_minbatch_slices2_msignal"])+(data["maxbatch_slices2_msignal"])) /2.0)))) , np.sin(( np.where(data["maxbatch_slices2_msignal"] > -998, data["abs_maxbatch_slices2_msignal"], np.maximum(((data["medianbatch_slices2"])) ,(( np.sin(( data["meanbatch_slices2"])))))))))> -998, data["abs_maxbatch_slices2_msignal"], np.sin(( data["abs_maxbatch_slices2_msignal"]))), data["medianbatch_slices2"])))) +
0.050000*np.tanh(((((( data["meanbatch_slices2_msignal"])+(((data["meanbatch_slices2"])*(np.sin(( data["meanbatch_slices2"])))))))+(np.where(((data["meanbatch_slices2"])*(data["meanbatch_slices2"])) <= -998,(((data["rangebatch_slices2"])+(((data["rangebatch_slices2"])*(np.minimum(((data["meanbatch_slices2_msignal"])) ,(((( data["meanbatch_slices2_msignal"])* 2.0)))))))) /2.0), np.cos(((( data["meanbatch_slices2_msignal"])+(np.cos(( data["abs_minbatch_slices2_msignal"])))))))))/2.0)) +
0.050000*np.tanh(np.minimum(((((np.sin(((( np.minimum(((((( data["abs_minbatch_slices2_msignal"])+(data["medianbatch_msignal"])) /2.0))),(( data["stdbatch_slices2_msignal"])))) +(np.where(np.where(data["meanbatch_slices2"] > -998, data["medianbatch_slices2_msignal"], data["rangebatch_slices2_msignal"])<= -998, data["maxbatch_msignal"], data["maxtominbatch_msignal"])))))) * 2.0))),(( np.where(np.cos(( data["signal"])) <= -998,(((data["meanbatch_slices2"])<=(data["abs_maxbatch_slices2_msignal"])) *1.) ,(5.01787090301513672)))))) +
0.050000*np.tanh(np.where(data["meanbatch_slices2_msignal"] <= -998, np.sin(((( data["abs_minbatch_slices2_msignal"])-(np.sin(((( np.sin(( data["rangebatch_slices2"])))-(data["rangebatch_slices2"])))))))) ,(((((( np.sin(( data["rangebatch_slices2"])))-(np.sin(( data["meanbatch_slices2_msignal"])))))* 2.0)) +(data["meanbatch_slices2_msignal"])))) +
0.050000*np.tanh(( -(( np.where(( -(((-(( data["mean_abs_chgbatch_slices2_msignal"])))))) > -998, np.where(((( data["signal"])+(((np.sin(( data["abs_minbatch_slices2"])))* 2.0)))/2.0)<= -998, data["abs_maxbatch_slices2"],(( data["rangebatch_msignal"])*(np.cos(((( np.sin(((-(( data["mean_abs_chgbatch_slices2_msignal"])))))) * 2.0)))))) , data["stdbatch_slices2_msignal"])))))+
0.050000*np.tanh(((( data["stdbatch_msignal"])+(((((np.where(data["minbatch"] <= -998,(((((data["stdbatch_msignal"])<=(data["stdbatch_msignal"])) *1.))+(((data["stdbatch_msignal"])+(data["minbatch_slices2"])))) , np.cos(( data["rangebatch_msignal"])))) * 2.0)) * 2.0)))/2.0)) +
0.050000*np.tanh(data["abs_minbatch_slices2_msignal"])+
0.050000*np.tanh(np.where(np.maximum(((data["abs_minbatch_msignal"])) ,(( data["maxtominbatch_slices2_msignal"])))<= -998, data["abs_minbatch_msignal"], np.sin(((((((data["abs_maxbatch_msignal"])+(np.cos(( np.where(data["abs_minbatch_msignal"] > -998, data["medianbatch_slices2"], data["abs_avgbatch_msignal"])))))/2.0)) * 2.0)))))+
0.050000*np.tanh(((np.sin(( data["maxbatch_slices2_msignal"])))*(((data["medianbatch_slices2"])+(np.sin(((-(((( data["abs_minbatch_msignal"])+(data["signal_shift_+1_msignal"])))))))))))) +
0.050000*np.tanh(data["medianbatch_msignal"])+
0.050000*np.tanh(((np.maximum(((data["maxbatch_msignal"])) ,(( data["abs_avgbatch_slices2"])))) *(((((( np.where(data["maxbatch_slices2_msignal"] > -998, data["meanbatch_msignal"], data["medianbatch_msignal"])) <=(data["signal_shift_-1_msignal"])) *1.))+(np.minimum(((data["medianbatch_msignal"])) ,(((((( np.tanh(( data["medianbatch_msignal"])))-(data["maxbatch_msignal"])))*(np.sin(( data["medianbatch_msignal"])))))))))))) +
0.050000*np.tanh(((( np.minimum(((data["signal_shift_-1"])) ,(((( np.sin(( np.where(((np.sin(( data["maxtominbatch_slices2"])))/ 2.0)> -998,(((((data["medianbatch_msignal"])+(((data["mean_abs_chgbatch_slices2"])* 2.0)))/2.0)) * 2.0),(((data["abs_minbatch_slices2"])+(np.sin(( data["minbatch_msignal"])))) /2.0)))))* 2.0)))))+(data["meanbatch_slices2_msignal"])) /2.0)) +
0.050000*np.tanh(((( -(( np.where(( -(( np.cos(( np.minimum(((np.sin(((((data["abs_minbatch_slices2_msignal"])>(data["abs_maxbatch_msignal"])) *1.))))) ,(( data["meanbatch_msignal"])))))))) <= -998, data["stdbatch_slices2_msignal"], data["maxbatch_slices2_msignal"])))))*(((data["abs_minbatch_slices2_msignal"])*(np.cos(((((((data["maxbatch_msignal"])>(data["maxtominbatch"])) *1.))-(data["medianbatch_slices2"])))))))))+
0.050000*np.tanh(((data["stdbatch_slices2_msignal"])*(((np.cos(((( data["maxtominbatch"])+(np.where(( -(( data["rangebatch_msignal"])))> -998, data["abs_maxbatch_slices2"],(((((( data["minbatch_slices2"])+(np.tanh(( data["abs_avgbatch_slices2_msignal"])))))+(np.cos(((( data["rangebatch_slices2"])*(np.cos(((( data["rangebatch_slices2"])*(data["minbatch_slices2"])))))))))))+(data["stdbatch_slices2_msignal"])))))))) * 2.0)))) +
0.050000*np.tanh(((np.sin(( data["abs_maxbatch_slices2_msignal"])))* 2.0)) +
0.050000*np.tanh(np.minimum(((((((((3.0)) *(np.tanh(( np.minimum(((np.minimum(((data["minbatch"])) ,(((((data["stdbatch_msignal"])<=(np.minimum(((data["minbatch_msignal"])) ,(( data["meanbatch_slices2"])))))*1.)))))),(( data["signal_shift_-1_msignal"])))))))) +(((data["meanbatch_slices2"])*(data["stdbatch_msignal"])))) /2.0))),(( data["abs_maxbatch"])))) +
0.050000*np.tanh(np.minimum(((((np.tanh(((-(((( data["signal"])* 2.0)))))))-(((data["signal"])*(np.sin(( data["abs_maxbatch"])))))))) ,(( np.cos(( np.cos(( np.minimum(((data["abs_minbatch_msignal"])) ,(( data["mean_abs_chgbatch_slices2_msignal"])))))))))))+
0.050000*np.tanh(np.minimum(((np.sin(( np.where(data["abs_avgbatch_slices2_msignal"] <= -998, np.minimum(((((((data["minbatch"])/ 2.0)) -(np.cos(( data["abs_avgbatch_slices2_msignal"])))))) ,(( data["signal_shift_+1_msignal"]))), data["minbatch_msignal"]))))),(((( data["abs_avgbatch_slices2"])*(data["rangebatch_msignal"])))))) +
0.050000*np.tanh(((np.tanh(( np.where(data["rangebatch_msignal"] > -998, np.where(((( data["signal_shift_-1"])+(data["abs_maxbatch_slices2"])) /2.0)> -998, np.sin(( data["signal_shift_-1"])) , np.where(((( data["maxtominbatch_slices2"])+(((np.tanh(( data["abs_avgbatch_slices2_msignal"])))/ 2.0)))/2.0)> -998, data["signal_shift_-1_msignal"], data["signal_shift_-1"])) ,(( np.cos(( np.maximum(((data["rangebatch_msignal"])) ,(( data["abs_minbatch_slices2"])))))) / 2.0)))))* 2.0)) +
0.050000*np.tanh(((np.where(((( data["mean_abs_chgbatch_msignal"])>(np.minimum(((data["mean_abs_chgbatch_msignal"])) ,(( data["signal_shift_-1"])))))*1.) > -998, data["signal_shift_-1"], data["medianbatch_msignal"])) *(np.cos(( data["medianbatch_msignal"])))))+
0.050000*np.tanh(np.sin(( np.where(data["signal_shift_-1"] <= -998,(( data["minbatch_msignal"])-(np.where(( -(( np.where(data["maxbatch_slices2_msignal"] > -998, data["abs_avgbatch_msignal"], np.where(np.sin(( data["signal_shift_-1"])) <= -998, data["meanbatch_slices2_msignal"], data["medianbatch_slices2_msignal"])))))> -998, data["abs_avgbatch_msignal"], np.cos(((-(( np.sin(( np.sin(( np.cos(( np.sin(( data["signal_shift_-1"])))))))))))))))) , data["signal_shift_-1"])))) +
0.050000*np.tanh(( -(( np.cos(((( np.where(((((data["mean_abs_chgbatch_slices2_msignal"])* 2.0)) * 2.0)<= -998,(( data["signal_shift_-1_msignal"])/ 2.0), data["mean_abs_chgbatch_slices2_msignal"])) * 2.0)))))))+
0.050000*np.tanh(( -(((( np.cos(( data["signal_shift_-1_msignal"])))* 2.0)))))+
0.050000*np.tanh(((np.sin(( np.sin(( data["meanbatch_slices2_msignal"])))))*(np.where(( 9.0)> -998, data["minbatch_msignal"], np.maximum(((((data["medianbatch_msignal"])* 2.0))),(( np.sin(((9.0)))))))))) +
0.050000*np.tanh(((((np.sin(((( data["maxbatch_slices2"])-(((data["mean_abs_chgbatch_msignal"])-(np.maximum(((data["signal_shift_-1"])) ,(( np.maximum(((data["signal_shift_-1"])) ,(((((((np.sin(( data["signal_shift_-1"])))+(((( data["signal_shift_+1"])>(data["abs_minbatch_msignal"])) *1.))) /2.0)) -(data["signal_shift_-1"])))))))))))))))* 2.0)) * 2.0)) +
0.050000*np.tanh(((np.cos(( data["maxtominbatch_slices2_msignal"])))*(np.minimum(((data["minbatch_slices2"])) ,(( np.where(np.sin(( data["stdbatch_slices2"])) <= -998,(( np.cos(( data["maxtominbatch_slices2_msignal"])))+(((np.minimum(((data["signal_shift_+1"])) ,(( data["minbatch_slices2"])))) -(data["maxtominbatch_slices2_msignal"])))) , data["abs_avgbatch_msignal"])))))))+
0.050000*np.tanh(((data["medianbatch_slices2"])*(np.sin(( np.where(data["abs_minbatch_slices2_msignal"] > -998, data["abs_maxbatch_slices2_msignal"],(( np.where(np.cos(( np.sin(( data["mean_abs_chgbatch_slices2_msignal"])))) > -998, data["medianbatch_slices2"], data["mean_abs_chgbatch_slices2_msignal"])) *(np.cos(((((data["abs_minbatch_slices2_msignal"])+(((((( data["maxtominbatch_msignal"])>(((( 12.99664306640625000)) +(data["maxbatch_slices2_msignal"])))) *1.))*(data["maxbatch_slices2"])))) /2.0)))))))))))+
0.050000*np.tanh(data["medianbatch_msignal"])+
0.050000*np.tanh(((np.sin(((( data["stdbatch_slices2_msignal"])*(data["maxtominbatch_slices2"])))))* 2.0)) +
0.050000*np.tanh(np.cos(((((( data["abs_maxbatch_msignal"])+(data["abs_avgbatch_slices2_msignal"])))-(np.where(((np.cos(((((( data["abs_maxbatch_msignal"])+(data["abs_avgbatch_slices2_msignal"])))-(np.where(data["abs_maxbatch_msignal"] > -998, data["signal_shift_-1"], data["maxtominbatch"])))))) *(((np.tanh(( data["abs_maxbatch_msignal"])))* 2.0)))> -998, data["signal_shift_-1"], data["abs_avgbatch_slices2_msignal"])))))) +
0.050000*np.tanh(((np.sin(((((( data["abs_maxbatch_slices2_msignal"])-(np.where(np.tanh(((( data["maxbatch_msignal"])/ 2.0)))> -998,(( np.minimum(((data["medianbatch_slices2_msignal"])) ,(( np.tanh(( data["signal_shift_+1_msignal"])))))) -(( -(( np.tanh(((( data["rangebatch_msignal"])* 2.0)))))))) , data["abs_maxbatch_slices2_msignal"])))) +(np.tanh(((( data["rangebatch_msignal"])* 2.0)))))))) * 2.0)) +
0.050000*np.tanh(((((((((data["medianbatch_msignal"])+(((data["abs_minbatch_slices2"])* 2.0)))) +(((( data["mean_abs_chgbatch_msignal"])+(data["minbatch_slices2"])) /2.0)))) * 2.0)) * 2.0)) +
0.050000*np.tanh(((data["minbatch"])*(np.cos(( np.where(((( np.minimum(((data["maxbatch_msignal"])) ,(( data["maxbatch_msignal"])))) <=(np.tanh(( data["abs_minbatch_msignal"])))) *1.) > -998, data["maxbatch_msignal"], np.tanh(( np.tanh(( np.maximum(((data["abs_minbatch_slices2_msignal"])) ,(( np.tanh(( data["minbatch_slices2"])))))))))))))))+
0.050000*np.tanh(((np.sin(( data["abs_maxbatch_msignal"])))*(((np.sin(( data["rangebatch_slices2"])))+(((data["abs_maxbatch_msignal"])*(((np.sin(( np.sin(((((((( data["stdbatch_slices2_msignal"])* 2.0)) -(((data["abs_avgbatch_slices2_msignal"])/ 2.0)))) * 2.0)))))) +(((np.sin(( np.sin(( data["signal_shift_+1"])))))+(data["medianbatch_msignal"])))))))))))+
0.050000*np.tanh(np.sin(((((( data["minbatch_msignal"])* 2.0)) -(np.where(data["stdbatch_slices2"] > -998, data["meanbatch_slices2_msignal"], np.cos(( np.where(((data["minbatch_msignal"])* 2.0)> -998, data["meanbatch_slices2_msignal"], data["abs_maxbatch_slices2"])))))))))+
0.050000*np.tanh(((data["abs_minbatch_msignal"])+(((np.where(data["abs_avgbatch_msignal"] > -998,(((12.93795680999755859)) *(np.tanh(( np.cos(( data["rangebatch_msignal"])))))) , np.where(((data["meanbatch_msignal"])-(((data["minbatch_slices2_msignal"])+(data["meanbatch_slices2"])))) > -998,(5.0), data["minbatch_slices2_msignal"])))+(data["minbatch"])))))+
0.050000*np.tanh(((data["minbatch_msignal"])* 2.0)) +
0.050000*np.tanh(((data["mean_abs_chgbatch_slices2_msignal"])*(np.sin(( np.sin(( np.where(data["maxbatch_slices2"] > -998, data["maxbatch_slices2"], np.where(((data["mean_abs_chgbatch_slices2_msignal"])/ 2.0)<= -998,(4.0), np.maximum(((np.sin(( data["maxbatch_slices2"])))) ,(( data["abs_avgbatch_msignal"])))))))))))) +
0.050000*np.tanh(((data["rangebatch_slices2"])*(((data["minbatch_slices2_msignal"])*(((np.cos(((( data["signal_shift_+1_msignal"])-(data["maxbatch_msignal"])))))/ 2.0)))))) +
0.050000*np.tanh(((((data["stdbatch_msignal"])-(np.sin(( np.where(data["meanbatch_msignal"] <= -998,(((5.37529850006103516)) -(data["abs_avgbatch_slices2"])) ,(((( data["mean_abs_chgbatch_slices2_msignal"])* 2.0)) * 2.0)))))))+(((np.sin(( data["mean_abs_chgbatch_slices2_msignal"])))*(data["mean_abs_chgbatch_slices2_msignal"])))))+
0.050000*np.tanh(data["medianbatch_msignal"])+
0.050000*np.tanh(np.sin(( np.sin(( data["minbatch_slices2_msignal"])))))+
0.050000*np.tanh(((data["minbatch_msignal"])-(np.sin(( np.where(((data["rangebatch_slices2"])+(data["minbatch_slices2"])) > -998, data["maxbatch_msignal"], data["meanbatch_slices2_msignal"])))))) +
0.050000*np.tanh(np.minimum(((np.sin(( np.minimum(((data["maxtominbatch_slices2_msignal"])) ,(( data["minbatch_slices2_msignal"]))))))),(( data["maxbatch_slices2_msignal"])))) +
0.050000*np.tanh(np.where(data["signal_shift_-1"] <= -998, np.cos(( data["signal_shift_+1"])) , np.sin(((( np.where(data["signal_shift_-1"] <= -998, data["signal_shift_+1"], np.sin(( np.sin(((((( data["signal_shift_-1"])/ 2.0)) -(data["abs_avgbatch_msignal"])))))))) * 2.0)))))+
0.050000*np.tanh(((np.sin(( np.where(np.where(np.sin(((( np.sin(( np.sin(( np.where(data["stdbatch_slices2"] > -998, data["signal_shift_-1"], data["maxbatch_msignal"])))))) * 2.0)))<= -998, data["minbatch_slices2_msignal"],(( data["maxtominbatch_slices2_msignal"])* 2.0)) > -998, data["signal_shift_-1"], np.sin(( np.minimum(((((data["signal_shift_-1_msignal"])* 2.0))),(( data["abs_minbatch_slices2_msignal"])))))))))* 2.0)) +
0.050000*np.tanh(((data["medianbatch_msignal"])-(((data["signal_shift_-1"])*(np.sin(((( np.maximum(((data["minbatch_slices2"])) ,(((1.47495067119598389)))))*(((np.minimum(((np.minimum(((data["mean_abs_chgbatch_msignal"])) ,(( np.where(data["signal_shift_-1"] <= -998,(( data["medianbatch_slices2"])* 2.0),(( np.maximum(((data["signal_shift_+1"])) ,(( data["abs_minbatch_slices2_msignal"])))) * 2.0))))))),(( data["signal_shift_-1"])))) / 2.0)))))))))) +
0.050000*np.tanh(np.cos(( np.where(data["stdbatch_slices2_msignal"] <= -998, np.cos(((-(((( data["signal_shift_-1"])+(((data["abs_maxbatch"])* 2.0)))))))) , np.where(data["signal_shift_-1"] <= -998,(( data["abs_maxbatch"])-(data["meanbatch_slices2"])) ,(( data["maxtominbatch_slices2"])-(((data["signal_shift_-1"])+(((data["abs_maxbatch"])* 2.0)))))))))) +
0.050000*np.tanh(((((np.sin(( np.maximum(((data["abs_maxbatch_slices2_msignal"])) ,(( np.maximum(((data["abs_maxbatch_slices2_msignal"])) ,(( np.where(data["abs_maxbatch_slices2_msignal"] > -998, np.maximum(((data["abs_maxbatch_slices2_msignal"])) ,(( data["signal_shift_-1"]))),(((( np.sin(( np.maximum(((data["abs_maxbatch_slices2_msignal"])) ,(( data["signal_shift_-1"])))))) * 2.0)) *(((data["medianbatch_slices2"])* 2.0)))))))))))))* 2.0)) * 2.0)) +
0.050000*np.tanh(np.where(( -(((( data["abs_minbatch_slices2_msignal"])+(data["meanbatch_msignal"])))))<= -998, data["meanbatch_slices2_msignal"], data["meanbatch_msignal"])) +
0.050000*np.tanh(np.where(( -(( data["maxtominbatch"])))<= -998,(( data["stdbatch_slices2_msignal"])+(np.maximum(((data["minbatch_slices2"])) ,(( data["medianbatch_slices2"]))))), np.where(np.sin(( np.sin(( data["maxbatch_slices2_msignal"])))) <= -998, data["meanbatch_msignal"],(( np.sin(((-(( np.maximum(((((data["maxbatch_slices2_msignal"])/ 2.0))),(((( data["signal_shift_+1"])* 2.0)))))))))) * 2.0)))) +
0.050000*np.tanh(data["medianbatch_msignal"])+
0.050000*np.tanh(np.where(np.sin(( data["signal_shift_+1"])) > -998,(((( data["abs_maxbatch_slices2_msignal"])+(((((( data["abs_avgbatch_msignal"])/ 2.0)) <=(np.sin(( data["abs_maxbatch_slices2_msignal"])))) *1.))))*(np.sin(( np.sin(( data["signal_shift_+1"])))))) , data["abs_avgbatch_msignal"])) +
0.050000*np.tanh(np.sin(( np.minimum(((( -(((( data["signal"])+(np.maximum(((data["abs_avgbatch_msignal"])) ,(( data["signal_shift_-1"])))))))))) ,(( np.minimum(((np.maximum(((((data["signal_shift_-1"])+(data["minbatch_slices2"])))) ,(( data["abs_avgbatch_slices2_msignal"]))))),(( np.sin(( data["signal"])))))))))))+
0.050000*np.tanh(((np.cos(( np.where(data["abs_maxbatch_msignal"] <= -998, data["signal_shift_-1"], data["abs_avgbatch_msignal"])))) *(np.where(data["abs_avgbatch_msignal"] > -998, data["signal_shift_-1"],(( np.tanh(( data["maxtominbatch"])))/ 2.0)))))+
0.050000*np.tanh(((np.sin(( np.where(np.where(np.maximum(((data["signal_shift_+1"])) ,(( data["maxbatch_slices2_msignal"])))<= -998, data["abs_avgbatch_slices2"], np.maximum(((data["signal_shift_+1"])) ,(( data["maxbatch_slices2_msignal"])))) <= -998, data["stdbatch_slices2"], np.maximum(((data["signal_shift_+1"])) ,(( data["maxbatch_slices2_msignal"])))))))* 2.0)) +
0.050000*np.tanh(((((((np.sin(( data["abs_maxbatch_slices2_msignal"])))-(((( data["mean_abs_chgbatch_msignal"])>(data["medianbatch_msignal"])) *1.))))-(((( np.cos(( np.sin(( data["abs_maxbatch_slices2_msignal"])))))>(data["medianbatch_slices2"])) *1.))))*(np.where(data["minbatch_msignal"] > -998, data["abs_maxbatch_slices2_msignal"], np.minimum(((data["medianbatch_msignal"])) ,(( data["abs_maxbatch_slices2_msignal"])))))))+
0.050000*np.tanh(((np.sin(( np.where(((np.minimum(((data["meanbatch_msignal"])) ,(( data["abs_minbatch_slices2"])))) *(data["abs_maxbatch_slices2_msignal"])) > -998,(( np.sin(((( np.cos(( np.minimum(((data["meanbatch_msignal"])) ,(( data["abs_minbatch_slices2"])))))) *(data["abs_maxbatch_slices2_msignal"])))))* 2.0), data["medianbatch_msignal"])))) * 2.0)) +
0.050000*np.tanh(np.sin(( data["minbatch_msignal"])))+
0.050000*np.tanh(np.where(data["maxtominbatch_msignal"] <= -998, data["minbatch"], np.sin(( data["rangebatch_slices2"])))) +
0.050000*np.tanh(np.sin(( np.minimum(((((np.sin(( data["maxbatch_slices2_msignal"])))* 2.0))),(((8.0)))))))+
0.050000*np.tanh(np.cos(((((( data["meanbatch_msignal"])/ 2.0)) +(np.where(data["meanbatch_slices2"] > -998, data["meanbatch_msignal"], data["abs_maxbatch_slices2"])))))) +
0.050000*np.tanh(np.minimum(((np.tanh(((((((((( data["abs_avgbatch_slices2"])+(data["stdbatch_msignal"])))* 2.0)) +(data["signal_shift_-1_msignal"])))-(data["minbatch_slices2_msignal"])))))) ,(( np.minimum(((data["stdbatch_msignal"])) ,(( np.minimum(((((((data["medianbatch_slices2"])* 2.0)) +(data["stdbatch_slices2"])))) ,(( data["meanbatch_msignal"])))))))))) +
0.050000*np.tanh(np.sin(( np.sin(((((( data["rangebatch_slices2"])+(np.minimum(((data["mean_abs_chgbatch_msignal"])) ,(( np.sin(( np.minimum(((data["rangebatch_slices2"])) ,(( np.sin(((-(( data["abs_minbatch_msignal"])))))))))))))))) -(data["abs_minbatch_msignal"])))))))+
0.050000*np.tanh(((((((((((np.sin(((-(((( np.sin(( data["medianbatch_msignal"])))-(data["signal_shift_+1"])))))))) -(np.sin(((( data["signal_shift_+1"])* 2.0)))))) * 2.0)) -(np.sin(((((( np.sin(((( data["signal_shift_+1"])* 2.0)))) * 2.0)) * 2.0)))))) * 2.0)) * 2.0)) +
0.050000*np.tanh(np.sin(((( data["mean_abs_chgbatch_slices2_msignal"])*(((((( data["stdbatch_slices2_msignal"])+(np.minimum(((np.where(np.sin(((((((data["meanbatch_msignal"])+(data["mean_abs_chgbatch_slices2_msignal"])) /2.0)) * 2.0)))<= -998,(7.0), data["mean_abs_chgbatch_slices2_msignal"]))),(( data["signal_shift_-1_msignal"])))))/2.0)) -(data["signal_shift_-1_msignal"])))))))+
0.050000*np.tanh(np.sin(( np.where(np.where(np.sin(( data["meanbatch_slices2"])) <= -998,(( data["abs_minbatch_slices2_msignal"])*(data["stdbatch_msignal"])) , np.sin(( data["minbatch_msignal"])))<= -998, data["signal_shift_-1_msignal"], data["minbatch_msignal"])))) +
0.050000*np.tanh(np.minimum(((data["medianbatch_msignal"])) ,(( np.tanh(( data["signal_shift_-1_msignal"])))))) +
0.050000*np.tanh(((data["abs_minbatch_slices2"])+(((((np.cos(((( data["signal_shift_-1"])+(( -(((((np.maximum(((data["maxbatch_slices2"])) ,(( data["abs_maxbatch_msignal"])))) +(np.maximum(((data["meanbatch_slices2"])) ,(((((((( np.maximum(((data["signal_shift_-1"])) ,(( data["meanbatch_slices2"])))) +(np.maximum(((data["maxtominbatch_msignal"])) ,(( data["abs_maxbatch_msignal"])))))/2.0)) +(data["signal_shift_-1"])) /2.0)))))) /2.0)))))))))* 2.0)) * 2.0)))) +
0.050000*np.tanh(((np.sin(((( np.where(np.sin(((( np.sin(((( data["maxbatch_slices2"])* 2.0)))) * 2.0)))> -998, data["maxbatch_slices2"], np.where(data["mean_abs_chgbatch_slices2"] > -998, data["maxbatch_slices2"], data["maxbatch_slices2"])))* 2.0)))) * 2.0)) +
0.050000*np.tanh(((data["medianbatch_msignal"])+(np.tanh(( np.maximum(((np.where(np.minimum(((((( data["minbatch_msignal"])<=(data["medianbatch_slices2"])) *1.))) ,(( data["mean_abs_chgbatch_slices2_msignal"])))> -998, data["medianbatch_slices2_msignal"], data["stdbatch_slices2"]))),(( np.where(((data["medianbatch_slices2_msignal"])+(np.tanh(( data["abs_avgbatch_slices2_msignal"])))) > -998,(( data["rangebatch_slices2"])/ 2.0),(( data["medianbatch_slices2_msignal"])+(data["mean_abs_chgbatch_slices2_msignal"])))))))))))+
0.050000*np.tanh(((np.where(data["medianbatch_slices2_msignal"] <= -998, np.tanh(( data["medianbatch_slices2"])) , data["medianbatch_slices2"])) / 2.0)) +
0.050000*np.tanh(data["meanbatch_slices2"])+
0.050000*np.tanh(np.where(data["meanbatch_msignal"] > -998, np.minimum(((((np.sin(( data["abs_maxbatch"])))*(np.where(data["medianbatch_slices2_msignal"] > -998,(( data["mean_abs_chgbatch_msignal"])* 2.0),(( data["abs_avgbatch_slices2_msignal"])/ 2.0)))))) ,(( data["abs_avgbatch_slices2_msignal"]))), data["medianbatch_slices2_msignal"])) +
0.050000*np.tanh(np.minimum(((np.where(data["abs_minbatch_msignal"] <= -998, data["mean_abs_chgbatch_msignal"], data["meanbatch_slices2"]))),(((( data["abs_minbatch_msignal"])/ 2.0)))))+
0.050000*np.tanh(((data["rangebatch_slices2_msignal"])*(np.sin(( np.maximum(((((data["maxbatch_slices2_msignal"])* 2.0))),(( np.where(data["abs_minbatch_msignal"] > -998, data["signal_shift_+1"],(( data["signal"])*(np.sin(( data["stdbatch_slices2"])))))))))))))+
0.050000*np.tanh(np.minimum(((np.minimum(((((data["rangebatch_slices2"])-(data["stdbatch_slices2_msignal"])))) ,(( np.sin(((( data["rangebatch_slices2"])-(data["stdbatch_slices2_msignal"]))))))))),(((( data["medianbatch_slices2_msignal"])+(( 4.06319332122802734)))))))+
0.050000*np.tanh(((np.sin(( data["abs_maxbatch"])))*(np.where(((data["rangebatch_slices2"])* 2.0)> -998, data["mean_abs_chgbatch_slices2_msignal"],(( np.where(data["rangebatch_msignal"] > -998, np.where(((data["abs_maxbatch"])* 2.0)<= -998,(( np.sin(( data["abs_maxbatch"])))* 2.0), data["abs_avgbatch_slices2_msignal"]), data["abs_minbatch_msignal"])) +(np.sin(( data["abs_maxbatch"])))))))) +
0.050000*np.tanh(((((((np.minimum(((np.sin(( data["medianbatch_slices2"])))) ,(( np.cos(( np.tanh(( data["meanbatch_msignal"])))))))) * 2.0)) * 2.0)) +(np.minimum(((data["stdbatch_msignal"])) ,(( data["meanbatch_msignal"])))))) +
0.050000*np.tanh(np.minimum(((data["abs_avgbatch_msignal"])) ,(( np.minimum(((data["abs_maxbatch"])) ,(((( data["meanbatch_msignal"])+(data["minbatch_slices2_msignal"])))))))))+
0.050000*np.tanh(((data["medianbatch_slices2"])+(data["meanbatch_slices2"])))+
0.050000*np.tanh(np.where(((( data["medianbatch_msignal"])<=(((( np.tanh(( data["medianbatch_slices2"])))+(((((data["abs_avgbatch_msignal"])/ 2.0)) / 2.0)))/2.0)))*1.) > -998,(((np.minimum(((data["signal"])) ,(( np.cos(( np.tanh(( data["abs_avgbatch_msignal"])))))))) +(((np.cos(((( data["medianbatch_msignal"])+(data["meanbatch_msignal"])))))/ 2.0)))/2.0), data["medianbatch_msignal"])) +
0.050000*np.tanh(((np.where(((( data["abs_avgbatch_slices2_msignal"])+(data["meanbatch_slices2"])) /2.0)<= -998, np.sin(( np.sin(((6.0))))),(( np.where(data["medianbatch_msignal"] > -998, data["meanbatch_slices2"], data["meanbatch_slices2"])) * 2.0)))*(((data["abs_avgbatch_slices2_msignal"])+(((( np.sin(( np.tanh(((((data["abs_avgbatch_slices2_msignal"])<=(np.sin(( data["abs_avgbatch_slices2"])))) *1.))))))<=(data["meanbatch_slices2"])) *1.))))))+
0.050000*np.tanh(((data["medianbatch_msignal"])+(((((((((((data["medianbatch_msignal"])+(data["maxtominbatch_slices2_msignal"])) /2.0)) >(data["maxbatch_slices2"])) *1.))* 2.0)) +(np.sin(( data["abs_avgbatch_slices2"])))))))+
0.050000*np.tanh(np.where(((( data["stdbatch_slices2_msignal"])>(np.minimum(((data["rangebatch_slices2"])) ,(( np.cos(( np.minimum(((((np.cos(( data["meanbatch_slices2_msignal"])))+(np.sin(( np.sin(( data["meanbatch_msignal"])))))))) ,(( data["signal"])))))))))) *1.) > -998, np.cos(( data["minbatch_msignal"])) ,(( data["medianbatch_slices2"])* 2.0)))+
0.050000*np.tanh(data["abs_avgbatch_slices2_msignal"])+
0.050000*np.tanh(((((((data["minbatch"])*(data["abs_minbatch_msignal"])))* 2.0)) *(np.where(np.where(np.sin(((((np.cos(((((data["abs_minbatch_msignal"])<=(data["minbatch"])) *1.))))+(data["minbatch"])) /2.0)))<= -998, data["stdbatch_slices2"], np.cos(( data["stdbatch_slices2"])))<= -998,(-(( np.sin(( data["stdbatch_slices2"]))))), np.cos(( data["stdbatch_slices2"])))))) +
0.050000*np.tanh(((((data["mean_abs_chgbatch_msignal"])*(np.cos(( np.minimum(((((data["maxtominbatch_slices2"])-(data["rangebatch_slices2"])))) ,(((((data["medianbatch_slices2_msignal"])>(np.minimum(((((data["medianbatch_slices2_msignal"])*(np.cos(( np.tanh(((( np.tanh(((( data["maxtominbatch_slices2"])-(data["mean_abs_chgbatch_msignal"])))))-(data["rangebatch_slices2"])))))))))) ,(( data["meanbatch_msignal"])))))*1.))))))))) * 2.0)) +
0.050000*np.tanh(np.where(data["mean_abs_chgbatch_msignal"] > -998, data["stdbatch_slices2_msignal"], np.sin(( data["stdbatch_slices2_msignal"])))) +
0.050000*np.tanh(np.minimum(((( -(( data["minbatch_slices2"]))))),(((( data["medianbatch_msignal"])+(np.maximum(((data["medianbatch_msignal"])) ,(( np.sin(( np.minimum(((data["rangebatch_msignal"])) ,(((( data["abs_maxbatch_msignal"])+(np.sin(( np.cos(( data["maxbatch_slices2_msignal"])))))))))))))))))))) +
0.050000*np.tanh(np.sin(( np.where(data["signal_shift_-1"] > -998, np.where(data["rangebatch_msignal"] > -998, data["minbatch_msignal"],(( data["abs_maxbatch_slices2_msignal"])+(data["rangebatch_msignal"]))), np.sin(( data["abs_maxbatch_slices2_msignal"])))))) +
0.050000*np.tanh(((( data["meanbatch_msignal"])+(( -(((( data["minbatch"])*(np.sin(((( np.where(((((((data["maxbatch_slices2_msignal"])+(np.sin(( data["abs_maxbatch_slices2"])))) /2.0)) <=(((((( data["abs_maxbatch_slices2"])*(((( data["meanbatch_msignal"])+(data["abs_maxbatch_slices2"])) /2.0)))) >(data["maxbatch_slices2_msignal"])) *1.))) *1.) > -998, data["abs_maxbatch_slices2"], data["minbatch"])) * 2.0)))))))))) /2.0)) +
0.050000*np.tanh(((np.where(np.tanh(( np.tanh(((( data["rangebatch_msignal"])/ 2.0)))))<= -998, data["rangebatch_slices2"], np.sin(( np.sin(( data["minbatch_msignal"])))))) -(np.cos(((( np.tanh(( data["signal_shift_-1_msignal"])))-(((data["mean_abs_chgbatch_msignal"])* 2.0)))))))) +
0.050000*np.tanh(np.sin(((( data["signal_shift_+1_msignal"])+(np.where(np.minimum(((data["abs_maxbatch_slices2_msignal"])) ,(( np.minimum(((data["rangebatch_msignal"])) ,(( np.maximum(((np.where(data["minbatch_msignal"] <= -998,(( data["signal_shift_+1_msignal"])* 2.0), data["signal_shift_-1"]))),(( data["signal_shift_-1_msignal"])))))))))<= -998, data["abs_minbatch_slices2_msignal"],(( data["abs_maxbatch_msignal"])+(data["abs_maxbatch_slices2_msignal"])))))))) +
0.050000*np.tanh(((((( data["medianbatch_slices2_msignal"])+(np.sin(( np.sin(( np.where(np.sin(( data["abs_maxbatch_slices2_msignal"])) <= -998, data["meanbatch_slices2"],(( data["medianbatch_msignal"])+(np.sin(( np.cos(( data["rangebatch_msignal"])))))))))))))/2.0)) +(np.sin(( data["meanbatch_slices2"]))))))
def GP_class_5(self,data):
return self.Output(-2.889212 +
0.050000*np.tanh(((( data["meanbatch_slices2"])+(data["signal"])) /2.0)) +
0.050000*np.tanh(np.where(data["minbatch_slices2"] <= -998,(( data["maxtominbatch"])-(((( data["signal_shift_-1"])<=(((( data["signal"])<=(((((( np.where(data["medianbatch_slices2_msignal"] <= -998, np.where(( 4.0)<= -998, data["medianbatch_slices2"], data["abs_maxbatch_slices2_msignal"]), data["signal_shift_-1"])) <=(data["abs_maxbatch_slices2_msignal"])) *1.))+(data["medianbatch_slices2"])))) *1.))) *1.))) , data["signal"])) +
0.050000*np.tanh(( -(( data["abs_minbatch_msignal"])))) +
0.050000*np.tanh(np.where(((((np.cos(((( data["signal"])-(((( data["medianbatch_slices2"])<=(np.cos(( np.where(((( data["minbatch_slices2_msignal"])<=(data["mean_abs_chgbatch_slices2"])) *1.) <= -998,(((( data["signal"])-(data["medianbatch_slices2"])))*(data["signal"])) , data["medianbatch_slices2"])))))*1.))))))+(data["abs_minbatch_slices2"])))*(data["minbatch_slices2"])) <= -998, data["medianbatch_slices2"],(( data["medianbatch_slices2"])* 2.0)))+
0.050000*np.tanh(((data["signal"])-(((((((( data["signal_shift_+1"])-(np.maximum(((data["meanbatch_slices2"])) ,(( data["medianbatch_slices2"])))))) -(np.cos(((( data["signal_shift_+1"])*(data["stdbatch_msignal"])))))))+(data["abs_avgbatch_slices2"])) /2.0)))) +
0.050000*np.tanh(((data["abs_minbatch_msignal"])*(np.minimum(((np.where(data["rangebatch_msignal"] <= -998, np.sin(( data["minbatch_msignal"])) , data["abs_avgbatch_slices2_msignal"]))),(((( data["signal"])-(((np.tanh(( data["signal"])))+(((((((data["maxtominbatch_slices2"])+(data["medianbatch_slices2"])) /2.0)) >(((( data["medianbatch_slices2"])+(data["minbatch_msignal"])) /2.0)))*1.))))))))))) +
0.050000*np.tanh(np.where(np.sin(( np.where(data["meanbatch_slices2"] > -998, np.maximum(((data["signal_shift_-1"])) ,(( data["minbatch_msignal"]))), data["signal_shift_-1"])))> -998, data["meanbatch_slices2"], np.cos(( np.where(data["meanbatch_slices2"] > -998, data["signal_shift_-1"], data["meanbatch_slices2"])))))+
0.050000*np.tanh(data["meanbatch_slices2"])+
0.050000*np.tanh(np.minimum(((data["signal_shift_+1"])) ,(( np.where(np.tanh(((5.89498901367187500)))<= -998, data["rangebatch_slices2_msignal"], data["signal_shift_+1"])))))+
0.050000*np.tanh(((data["medianbatch_slices2_msignal"])-(np.where(np.where(data["medianbatch_slices2"] > -998, np.maximum(((data["signal"])) ,(( np.sin(( np.cos(( data["abs_minbatch_slices2"]))))))), np.tanh(( data["signal_shift_+1"])))> -998, data["abs_minbatch_msignal"], data["abs_minbatch_msignal"])))) +
0.050000*np.tanh(np.minimum(((( -(( data["abs_avgbatch_msignal"]))))),(( np.where(((data["abs_avgbatch_slices2_msignal"])+(np.cos(( data["meanbatch_slices2_msignal"])))) <= -998, data["mean_abs_chgbatch_msignal"], data["signal_shift_-1"])))))+
0.050000*np.tanh(((((((((data["stdbatch_slices2"])-(data["maxtominbatch_slices2_msignal"])))* 2.0)) *(np.cos(( np.maximum(((data["abs_maxbatch_slices2_msignal"])) ,(((((np.maximum(((np.cos(( np.maximum(((data["abs_maxbatch_slices2_msignal"])) ,(((((data["signal"])>(((data["maxbatch_slices2"])*(data["signal"])))) *1.)))))))),(( data["meanbatch_msignal"])))) >(data["maxtominbatch_msignal"])) *1.))))))))) * 2.0)) +
0.050000*np.tanh(np.where(data["mean_abs_chgbatch_slices2"] > -998, data["medianbatch_slices2"], np.maximum(((data["signal_shift_+1"])) ,(((((7.0)) * 2.0)))))) +
0.050000*np.tanh(data["medianbatch_slices2"])+
0.050000*np.tanh(((((((( data["abs_minbatch_msignal"])>(((((( data["signal_shift_-1_msignal"])* 2.0)) >(((( data["abs_maxbatch_msignal"])>(data["signal_shift_-1_msignal"])) *1.))) *1.))) *1.))/ 2.0)) -(((np.where(((( data["signal_shift_-1_msignal"])>(((( -(( np.maximum(((( 8.0))),(((((data["meanbatch_slices2_msignal"])>(data["signal_shift_-1_msignal"])) *1.))))))))-(data["abs_avgbatch_msignal"])))) *1.) > -998, data["abs_avgbatch_msignal"], data["meanbatch_slices2_msignal"])) * 2.0)))) +
0.050000*np.tanh(np.cos(((((((((( data["abs_maxbatch"])+(data["abs_maxbatch_slices2"])) /2.0)) +(data["abs_maxbatch_slices2"])) /2.0)) -(np.where(data["meanbatch_msignal"] > -998, data["medianbatch_msignal"], np.where(data["minbatch_slices2"] <= -998, data["mean_abs_chgbatch_slices2"],(-(((( data["stdbatch_slices2_msignal"])-(((data["stdbatch_slices2_msignal"])-(data["meanbatch_msignal"])))))))))))))) +
0.050000*np.tanh(((((((data["signal_shift_+1"])-(data["abs_maxbatch_slices2_msignal"])))*(( -(( data["minbatch_slices2"])))))) -(((((-(((( data["abs_maxbatch"])+(((( data["stdbatch_slices2"])<=(((((( data["signal_shift_+1_msignal"])-(( -(( data["minbatch_slices2"])))))) +(( 10.0)))/2.0)))*1.))))))) <=(( -(((( data["signal_shift_+1_msignal"])-(( -(( data["minbatch_slices2"])))))))))) *1.))))+
0.050000*np.tanh(((np.minimum(((data["signal"])) ,(( np.sin(( np.maximum(((data["abs_maxbatch_slices2_msignal"])) ,(((-(((((9.0)) +(data["signal"])))))))))))))) * 2.0)) +
0.050000*np.tanh(((data["medianbatch_slices2"])-(((( data["signal_shift_-1"])<=(((data["rangebatch_slices2_msignal"])*(data["maxbatch_slices2"])))) *1.))))+
0.050000*np.tanh(((data["meanbatch_slices2_msignal"])-(((data["abs_avgbatch_msignal"])*(np.where(( -(( data["abs_avgbatch_slices2_msignal"])))> -998,(( data["rangebatch_slices2_msignal"])+(data["rangebatch_slices2_msignal"])) ,(((data["signal_shift_-1"])>(data["meanbatch_slices2"])) *1.))))))) +
0.050000*np.tanh(((((np.sin(( data["maxbatch_msignal"])))*(np.where(((np.tanh(( np.tanh(( data["medianbatch_slices2"])))))/ 2.0)> -998, data["signal_shift_-1"],(( data["maxtominbatch_msignal"])* 2.0)))))* 2.0)) +
0.050000*np.tanh(np.where(np.cos(((( np.maximum(((data["medianbatch_slices2"])) ,(( np.maximum(((data["abs_maxbatch_msignal"])) ,(( np.cos(( data["signal"])))))))))*(np.maximum(((np.cos(((( data["maxtominbatch_slices2_msignal"])+(data["maxbatch_msignal"])))))) ,(( data["mean_abs_chgbatch_slices2_msignal"])))))))<= -998,(((np.tanh(( np.cos(( data["medianbatch_slices2"])))))<=(( -(( data["abs_avgbatch_slices2_msignal"])))))*1.) , np.sin(( data["maxbatch_msignal"])))) +
0.050000*np.tanh(((np.where(np.maximum(((np.cos(( np.sin(( data["maxbatch_slices2"])))))) ,(((( data["abs_maxbatch_msignal"])* 2.0)))) > -998, np.sin(( np.maximum(((((np.sin(((( np.sin(( data["meanbatch_msignal"])))* 2.0)))) * 2.0))),(((( data["abs_maxbatch_msignal"])* 2.0)))))) , np.maximum(((((data["rangebatch_msignal"])* 2.0))),(((( data["abs_maxbatch_msignal"])/ 2.0)))))) -(data["abs_avgbatch_slices2_msignal"])))+
0.050000*np.tanh(( -(((( np.cos(( data["meanbatch_slices2_msignal"])))*(np.where(data["minbatch"] > -998, data["abs_maxbatch"],(( data["maxbatch_msignal"])*(( -(((( np.cos(( data["meanbatch_slices2_msignal"])))*(data["abs_maxbatch_msignal"])))))))))))))) +
0.050000*np.tanh(np.where(data["stdbatch_slices2"] <= -998, data["meanbatch_slices2"],(( data["signal"])*(((np.where(((np.minimum(((( -(( data["abs_maxbatch"]))))),(( data["rangebatch_slices2_msignal"])))) * 2.0)<= -998, np.cos(( data["meanbatch_slices2"])) ,(( np.minimum(((data["rangebatch_slices2"])) ,(( np.cos(( data["maxbatch_msignal"])))))) * 2.0)))* 2.0)))))+
0.050000*np.tanh(((np.where(np.cos(( data["meanbatch_slices2"])) <= -998, np.maximum(((np.cos(( np.cos(( data["maxtominbatch"])))))) ,(( np.sin(( data["maxtominbatch"]))))), np.sin(((( np.maximum(((data["maxbatch_slices2_msignal"])) ,(( np.where(np.maximum(((((np.sin(( data["abs_maxbatch_slices2_msignal"])))* 2.0))),(( data["stdbatch_slices2_msignal"])))> -998, data["stdbatch_slices2_msignal"], data["abs_minbatch_slices2"])))))* 2.0)))))* 2.0)) +
0.050000*np.tanh(np.sin(( np.where(np.sin(( np.where(data["signal"] > -998,(( data["mean_abs_chgbatch_slices2_msignal"])+(data["mean_abs_chgbatch_slices2_msignal"])) ,(((data["abs_maxbatch_slices2"])>(((data["mean_abs_chgbatch_slices2_msignal"])+(data["abs_maxbatch_slices2"])))) *1.))))> -998,(( data["mean_abs_chgbatch_slices2_msignal"])+(data["abs_maxbatch_slices2"])) , np.where(data["mean_abs_chgbatch_slices2_msignal"] > -998,(( data["mean_abs_chgbatch_slices2_msignal"])+(data["meanbatch_slices2"])) , data["mean_abs_chgbatch_slices2_msignal"])))))+
0.050000*np.tanh(((((np.tanh(( np.sin(((((2.0)) +(((( data["abs_maxbatch_slices2_msignal"])+(((( data["medianbatch_slices2_msignal"])+(((( data["rangebatch_slices2_msignal"])+(np.sin(( data["minbatch_slices2_msignal"])))) /2.0)))/2.0)))/2.0)))))))) * 2.0)) * 2.0)) +
0.050000*np.tanh(((np.minimum(((((np.cos(( data["maxbatch_slices2_msignal"])))* 2.0))),(((((((((( np.where(((data["meanbatch_slices2"])* 2.0)<= -998, data["stdbatch_slices2_msignal"],(( data["signal"])* 2.0)))+(((np.cos(( data["maxbatch_slices2_msignal"])))* 2.0)))) +(data["abs_maxbatch_slices2_msignal"])) /2.0)) +(((data["signal"])* 2.0)))/2.0)))))*(( 9.0)))) +
0.050000*np.tanh(data["medianbatch_slices2"])+
0.050000*np.tanh(((np.cos(( data["abs_maxbatch_slices2_msignal"])))*(np.where(((np.where(data["maxbatch_slices2"] <= -998, data["abs_maxbatch"], data["medianbatch_slices2_msignal"])) *(np.maximum(((data["abs_maxbatch_slices2_msignal"])) ,(( np.cos(((( data["abs_maxbatch_msignal"])/ 2.0)))))))) > -998,(((data["abs_maxbatch_slices2"])+(((( data["maxbatch_slices2"])<=(( 1.22195386886596680)))*1.))) /2.0),(-(( np.where(data["medianbatch_slices2"] <= -998, data["abs_maxbatch"], data["medianbatch_slices2_msignal"])))))))) +
0.050000*np.tanh(((((data["maxbatch_msignal"])* 2.0)) +(((((np.where(data["minbatch_slices2"] <= -998,(( np.sin(( np.sin(( np.cos(( data["maxbatch_msignal"])))))))* 2.0),(( np.tanh(( data["maxbatch_msignal"])))*(((data["abs_maxbatch_slices2"])*(data["abs_avgbatch_slices2"])))))) * 2.0)) *(np.cos(( data["maxbatch_msignal"])))))))+
0.050000*np.tanh(np.sin(( np.maximum(((data["abs_minbatch_msignal"])) ,(( np.maximum(((data["abs_maxbatch_msignal"])) ,(((( np.sin(( np.sin(( data["maxbatch_slices2_msignal"])))))* 2.0)))))))))) +
0.050000*np.tanh(((np.sin(( np.where(((data["maxtominbatch"])+(np.sin(((((((np.sin(( data["abs_maxbatch_slices2_msignal"])))* 2.0)) <=(data["abs_maxbatch_msignal"])) *1.))))) > -998,(( data["abs_maxbatch_slices2_msignal"])* 2.0), np.where(data["mean_abs_chgbatch_slices2"] <= -998, np.sin(( np.where(data["abs_maxbatch_slices2_msignal"] > -998, np.sin(( data["maxbatch_slices2_msignal"])) , data["signal_shift_+1_msignal"]))), data["stdbatch_msignal"])))))* 2.0)) +
0.050000*np.tanh(((data["meanbatch_msignal"])*(( -(( np.where(data["rangebatch_slices2_msignal"] > -998, np.sin(( data["abs_avgbatch_slices2"])) ,(( np.where(((( 2.0)) *(data["meanbatch_msignal"])) > -998, data["meanbatch_msignal"],(( data["signal_shift_+1"])-(data["mean_abs_chgbatch_msignal"])))) *(((data["mean_abs_chgbatch_msignal"])/ 2.0)))))))))) +
0.050000*np.tanh(((np.cos(( data["maxbatch_msignal"])))*(((np.maximum(((np.minimum(((data["mean_abs_chgbatch_msignal"])) ,(( data["minbatch_msignal"]))))),(((( data["medianbatch_slices2"])-(((( data["signal"])>(np.minimum(((data["medianbatch_slices2"])) ,(( data["signal_shift_+1_msignal"])))))*1.))))))) *(data["signal"])))))+
0.050000*np.tanh(((((np.cos(( data["signal"])))*(data["meanbatch_slices2_msignal"])))-(((( np.sin(( np.sin(( data["mean_abs_chgbatch_msignal"])))))>(((np.cos(( np.tanh(( data["meanbatch_slices2_msignal"])))))*(((((((( np.cos(( data["mean_abs_chgbatch_msignal"])))<=(data["minbatch"])) *1.))*(data["medianbatch_msignal"])))*(data["medianbatch_msignal"])))))) *1.))))+
0.050000*np.tanh(((( 13.67484474182128906)) *(np.where(np.where(( 13.67484474182128906)> -998, data["abs_maxbatch_slices2_msignal"], np.sin(( data["abs_maxbatch_slices2_msignal"])))<= -998, np.tanh(( np.sin(( data["abs_maxbatch_msignal"])))) , np.sin(( np.maximum(((data["abs_maxbatch_msignal"])) ,(((( data["abs_maxbatch"])/ 2.0)))))))))) +
0.050000*np.tanh(((((np.sin(( data["abs_maxbatch"])))*(((data["stdbatch_msignal"])* 2.0)))) -(np.tanh(((((data["medianbatch_msignal"])<=(((data["abs_maxbatch"])-(((data["abs_maxbatch"])*(((data["stdbatch_msignal"])* 2.0)))))))*1.))))))+
0.050000*np.tanh(((np.cos(((-(( np.where(data["abs_maxbatch_slices2_msignal"] > -998, data["abs_maxbatch_slices2_msignal"], np.where(data["abs_maxbatch_msignal"] > -998, data["abs_maxbatch_slices2_msignal"], np.where(data["abs_maxbatch_slices2_msignal"] > -998, data["mean_abs_chgbatch_msignal"],(( data["medianbatch_slices2"])/ 2.0)))))))))) * 2.0)) +
0.050000*np.tanh(((( 8.75535774230957031)) -(((((((10.0)) *(data["abs_maxbatch_slices2_msignal"])))+(np.sin(((( np.where(np.tanh(( data["signal_shift_+1"])) <= -998, np.where(data["mean_abs_chgbatch_msignal"] <= -998, data["abs_maxbatch_slices2_msignal"], data["mean_abs_chgbatch_msignal"]),(10.0)))* 2.0)))))/2.0)))) +
0.050000*np.tanh(((((( data["abs_maxbatch_msignal"])+(((data["maxtominbatch_slices2_msignal"])/ 2.0)))/2.0)) *(((data["meanbatch_msignal"])-(np.cos(( data["meanbatch_msignal"])))))))+
0.050000*np.tanh(((data["maxbatch_slices2"])*(np.sin(( np.where(np.cos(( data["maxbatch_slices2_msignal"])) > -998, np.where(np.where(data["stdbatch_slices2"] > -998, data["maxbatch_msignal"], data["meanbatch_msignal"])> -998,(((np.where(data["maxbatch_slices2_msignal"] > -998, data["maxbatch_msignal"], data["maxbatch_slices2_msignal"])) +(data["abs_maxbatch_msignal"])) /2.0), np.sin(( data["maxbatch_slices2"]))), data["maxbatch_slices2"])))))) +
0.050000*np.tanh(((((((( data["maxtominbatch"])<=(np.cos(( data["meanbatch_msignal"])))) *1.))-(((np.tanh(( np.cos(( data["abs_maxbatch_slices2_msignal"])))))*(np.where(np.cos(( data["meanbatch_msignal"])) > -998, data["maxtominbatch_slices2_msignal"],(( data["maxbatch_msignal"])+(data["signal_shift_-1_msignal"])))))))) -(((((np.cos(( data["meanbatch_msignal"])))* 2.0)) * 2.0)))) +
0.050000*np.tanh(np.where(np.tanh(((((np.where(data["signal_shift_+1"] <= -998, np.sin(( data["minbatch"])) ,(( np.maximum(((data["rangebatch_msignal"])) ,(( data["medianbatch_slices2"])))) +(data["medianbatch_slices2"])))) <=(data["meanbatch_slices2_msignal"])) *1.))) > -998, np.cos(( data["abs_maxbatch_slices2_msignal"])) , data["medianbatch_slices2"])) +
0.050000*np.tanh(np.cos(( np.where(((np.where(np.sin(( data["minbatch"])) <= -998, data["minbatch"], data["maxbatch_msignal"])) +(data["abs_avgbatch_slices2_msignal"])) > -998, data["abs_maxbatch_slices2_msignal"],(((data["signal_shift_+1"])+(data["meanbatch_msignal"])) /2.0)))))+
0.050000*np.tanh(((np.cos(( data["abs_maxbatch_slices2_msignal"])))* 2.0)) +
0.050000*np.tanh(((np.where(((data["medianbatch_slices2"])+(np.sin(( data["abs_maxbatch_msignal"])))) <= -998, data["abs_maxbatch_msignal"], np.where(np.maximum(((data["abs_maxbatch_msignal"])) ,(((-(((( data["maxbatch_slices2"])-(data["abs_maxbatch_msignal"])))))))) <= -998, data["maxtominbatch_msignal"], np.minimum(((np.sin(( data["abs_maxbatch_msignal"])))) ,(( data["medianbatch_slices2"])))))) * 2.0)) +
0.050000*np.tanh(np.where(np.cos(( np.cos(( data["medianbatch_slices2_msignal"])))) <= -998,(( data["abs_maxbatch_slices2"])-(np.where(data["medianbatch_slices2_msignal"] <= -998, data["minbatch_slices2"],(( data["abs_minbatch_slices2_msignal"])*(data["medianbatch_slices2_msignal"]))))),(( np.cos(( data["abs_minbatch_slices2_msignal"])))*(data["medianbatch_slices2_msignal"])))) +
0.050000*np.tanh(((np.where(data["maxbatch_slices2_msignal"] <= -998, data["minbatch_slices2"], np.cos(( data["maxbatch_slices2_msignal"])))) * 2.0)) +
0.050000*np.tanh(((np.cos(( data["meanbatch_msignal"])))*(np.minimum(((data["minbatch_msignal"])) ,(((-(( data["meanbatch_msignal"])))))))))+
0.050000*np.tanh(((((data["maxbatch_slices2_msignal"])*(np.cos(((( np.minimum(((data["rangebatch_slices2"])) ,(( np.cos(( data["abs_minbatch_msignal"])))))) -(np.maximum(((data["abs_maxbatch_slices2"])) ,(( np.sin(( np.where(data["abs_avgbatch_msignal"] > -998, data["maxbatch_slices2_msignal"], data["signal"])))))))))))))*(data["maxbatch_slices2"])))+
0.050000*np.tanh(np.cos(((( np.minimum(((((((((data["medianbatch_slices2"])>(np.tanh(( data["signal_shift_-1"])))) *1.))>(((np.where(data["signal_shift_+1"] > -998, np.sin(((((data["medianbatch_slices2"])>(data["minbatch_slices2"])) *1.))) , data["mean_abs_chgbatch_slices2_msignal"])) * 2.0)))*1.))) ,(( np.where(data["medianbatch_slices2"] > -998, data["mean_abs_chgbatch_slices2_msignal"], data["medianbatch_slices2"])))))* 2.0)))) +
0.050000*np.tanh(((((np.sin(( np.maximum(((np.maximum(((data["abs_maxbatch_slices2_msignal"])) ,(( data["abs_avgbatch_slices2"]))))),(( np.cos(( data["abs_avgbatch_slices2"])))))))) * 2.0)) * 2.0)) +
0.050000*np.tanh(((data["maxbatch_slices2"])*(np.sin(( np.maximum(((data["maxbatch_msignal"])) ,(((-(( np.where(np.sin(( data["abs_maxbatch_slices2_msignal"])) <= -998,(( data["maxbatch_msignal"])/ 2.0), data["stdbatch_msignal"])))))))))))) +
0.050000*np.tanh(((data["abs_maxbatch"])*(((data["abs_maxbatch"])*(((data["mean_abs_chgbatch_msignal"])*(np.where(np.sin(( data["maxbatch_slices2_msignal"])) > -998,(( np.sin(( np.maximum(((data["maxbatch_slices2"])) ,(((-(( data["abs_maxbatch_slices2_msignal"])))))))))+(np.tanh(( np.tanh(( np.where(data["abs_minbatch_msignal"] > -998, data["abs_minbatch_slices2"], data["signal"]))))))), data["abs_avgbatch_msignal"])))))))) +
0.050000*np.tanh(((data["stdbatch_slices2_msignal"])*(np.cos(( np.where(( 13.96799564361572266)<= -998, np.where(((data["signal_shift_+1_msignal"])* 2.0)<= -998, data["meanbatch_msignal"], np.where(data["stdbatch_slices2_msignal"] > -998, data["mean_abs_chgbatch_msignal"], data["abs_avgbatch_msignal"])) , np.where(data["signal_shift_+1_msignal"] > -998, data["mean_abs_chgbatch_msignal"],(((( data["stdbatch_slices2_msignal"])*(((data["medianbatch_slices2_msignal"])+(data["mean_abs_chgbatch_msignal"])))))*(data["minbatch_slices2_msignal"])))))))))+
0.050000*np.tanh(np.where(data["abs_maxbatch_slices2_msignal"] <= -998, np.sin(( np.maximum(((((np.maximum(((((( data["abs_maxbatch_slices2_msignal"])>(data["abs_maxbatch"])) *1.))) ,(( data["abs_maxbatch"])))) * 2.0))),(((((( data["medianbatch_slices2"])* 2.0)) * 2.0)))))) ,(( np.sin(((( data["abs_maxbatch_slices2_msignal"])* 2.0)))) * 2.0)))+
0.050000*np.tanh(((data["medianbatch_slices2_msignal"])*(np.where(data["medianbatch_slices2_msignal"] <= -998, np.where(data["minbatch_slices2"] <= -998,(((((( data["medianbatch_slices2_msignal"])+(data["maxbatch_slices2"])) /2.0)) <=(((( data["medianbatch_slices2_msignal"])+(((( np.sin(( data["mean_abs_chgbatch_msignal"])))<=(( 9.99973869323730469)))*1.))) /2.0)))*1.) , np.sin(( data["maxbatch_slices2"]))), np.sin(( data["maxbatch_slices2"])))))) +
0.050000*np.tanh(((((data["abs_avgbatch_slices2_msignal"])*(np.where(np.sin(( data["abs_maxbatch_slices2"])) > -998, np.sin(( data["abs_maxbatch_slices2"])) ,(( data["stdbatch_slices2_msignal"])*(data["abs_avgbatch_slices2_msignal"])))))) * 2.0)) +
0.050000*np.tanh(((((data["meanbatch_msignal"])*(np.cos(( data["signal"])))))-(np.sin(((((data["meanbatch_slices2"])>(np.where(((data["meanbatch_msignal"])*(data["mean_abs_chgbatch_slices2_msignal"])) > -998,(( data["meanbatch_msignal"])*(np.cos(( data["mean_abs_chgbatch_slices2_msignal"])))) , data["mean_abs_chgbatch_slices2_msignal"])))*1.))))))+
0.050000*np.tanh(((((data["mean_abs_chgbatch_slices2_msignal"])*(((np.where(((data["meanbatch_msignal"])* 2.0)> -998, data["abs_maxbatch_msignal"], data["medianbatch_slices2"])) *(np.sin(( data["maxbatch_slices2"])))))))* 2.0)) +
0.050000*np.tanh(((np.sin(( np.maximum(((np.maximum(((data["maxbatch_slices2_msignal"])) ,(( np.maximum(((np.maximum(((data["maxbatch_slices2_msignal"])) ,(( data["abs_minbatch_slices2"]))))),(( data["abs_avgbatch_slices2"])))))))) ,(( np.maximum(((( -(( np.maximum(((data["maxtominbatch_msignal"])) ,(( data["abs_maxbatch_msignal"])))))))) ,(( data["abs_avgbatch_slices2"])))))))))* 2.0)) +
0.050000*np.tanh(((((data["maxbatch_slices2"])*(np.sin(( np.sin(( np.sin(( np.minimum(((((np.sin(((( data["abs_maxbatch_slices2_msignal"])* 2.0)))) * 2.0))),(( np.sin(((( data["abs_maxbatch_slices2_msignal"])* 2.0)))))))))))))))* 2.0)) +
0.050000*np.tanh(((((((((np.cos(( data["maxbatch_slices2_msignal"])))*(((data["abs_maxbatch"])+(((data["signal_shift_-1"])-(((np.where(((((np.cos(( data["maxbatch_slices2_msignal"])))* 2.0)) *(np.cos(( data["maxbatch_slices2_msignal"])))) > -998, data["rangebatch_slices2_msignal"], data["stdbatch_slices2"])) / 2.0)))))))) *(data["maxbatch_slices2_msignal"])))*(( 10.12534904479980469)))) *(data["maxbatch_slices2_msignal"])))+
0.050000*np.tanh(np.where(((data["abs_avgbatch_slices2_msignal"])*(np.cos(((-(((-(( data["abs_minbatch_msignal"])))))))))) <= -998, data["abs_avgbatch_slices2_msignal"],(( data["abs_avgbatch_slices2_msignal"])*(np.cos(((-(( data["abs_minbatch_slices2_msignal"])))))))))+
0.050000*np.tanh(np.minimum(((data["medianbatch_slices2"])) ,(( np.where(np.where(np.where(data["abs_maxbatch"] > -998, data["medianbatch_slices2"], data["medianbatch_slices2"])> -998, data["medianbatch_slices2"], data["medianbatch_slices2"])> -998,(((( np.cos(( data["signal"])))*(((data["abs_minbatch_slices2_msignal"])+(data["medianbatch_slices2"])))))* 2.0), data["medianbatch_slices2"])))))+
0.050000*np.tanh(((np.where(np.tanh(((( np.cos(( data["abs_maxbatch_slices2_msignal"])))* 2.0)))<= -998,(( np.cos(((( data["meanbatch_slices2"])-(data["abs_maxbatch_slices2_msignal"])))))-(data["abs_maxbatch_slices2_msignal"])) ,(( np.maximum(((data["mean_abs_chgbatch_msignal"])) ,(( data["abs_maxbatch"])))) +(( 8.0)))))*(np.cos(( data["abs_maxbatch_slices2_msignal"])))))+
0.050000*np.tanh(((((((np.maximum(((((data["meanbatch_slices2"])*(np.sin(( data["maxbatch_slices2_msignal"])))))) ,(( data["signal_shift_+1_msignal"])))) -(data["stdbatch_msignal"])))*(data["stdbatch_msignal"])))*(data["abs_avgbatch_slices2"])))+
0.050000*np.tanh(((np.sin(( np.where(np.sin(( data["abs_maxbatch_msignal"])) > -998, np.sin(( np.where(data["abs_maxbatch_msignal"] > -998, data["abs_maxbatch_msignal"],(( np.where(np.sin(( data["mean_abs_chgbatch_msignal"])) > -998,(( data["abs_maxbatch_msignal"])* 2.0), np.sin(( data["maxbatch_slices2_msignal"])))) * 2.0)))) , data["abs_avgbatch_msignal"])))) * 2.0)) +
0.050000*np.tanh(np.where(np.sin(( data["abs_maxbatch_slices2"])) <= -998, np.sin(( data["abs_maxbatch_slices2"])) ,(( data["meanbatch_slices2_msignal"])*(np.sin(( data["abs_maxbatch_slices2"])))))) +
0.050000*np.tanh(np.where(data["maxbatch_slices2"] > -998,(( data["stdbatch_msignal"])*(np.sin(( data["maxbatch_slices2"])))) , np.where(((data["mean_abs_chgbatch_slices2_msignal"])*(np.sin(( data["maxbatch_slices2"])))) > -998, data["abs_avgbatch_msignal"], data["stdbatch_slices2"])))+
0.050000*np.tanh(((data["medianbatch_slices2_msignal"])*(np.where(((data["medianbatch_slices2_msignal"])*(np.cos(( np.where(data["stdbatch_msignal"] > -998, data["mean_abs_chgbatch_msignal"], np.cos(( np.where(data["signal"] > -998, data["medianbatch_msignal"], np.cos(( data["signal"])))))))))) > -998, np.cos(( data["signal"])) , data["mean_abs_chgbatch_msignal"])))) +
0.050000*np.tanh(((np.where(data["abs_maxbatch_slices2_msignal"] <= -998, data["meanbatch_slices2_msignal"], np.cos(( np.where(np.where(data["abs_maxbatch"] <= -998,(((data["abs_maxbatch_slices2_msignal"])+(data["maxtominbatch_slices2_msignal"])) /2.0), data["abs_maxbatch_msignal"])<= -998, data["abs_maxbatch"], data["abs_maxbatch_slices2_msignal"])))))* 2.0)) +
0.050000*np.tanh(((((data["maxbatch_slices2_msignal"])+(data["stdbatch_msignal"])))*(np.sin(( np.where(((( data["mean_abs_chgbatch_msignal"])<=(((data["mean_abs_chgbatch_msignal"])+(data["mean_abs_chgbatch_msignal"])))) *1.) > -998, data["stdbatch_msignal"], data["maxbatch_slices2_msignal"])))))) +
0.050000*np.tanh(np.where(data["signal_shift_+1_msignal"] <= -998,(( np.cos(((((( data["minbatch_msignal"])*(np.cos(((((-(( np.cos(( data["minbatch_msignal"])))))) +(data["medianbatch_slices2_msignal"])))))))+(data["abs_avgbatch_slices2_msignal"])))))+(data["medianbatch_slices2_msignal"])) ,(( data["minbatch_msignal"])*(np.cos(((((-(( np.cos(( data["minbatch_msignal"])))))) +(data["abs_avgbatch_slices2_msignal"])))))))) +
0.050000*np.tanh(((np.sin(( np.maximum(((data["meanbatch_slices2"])) ,(( data["abs_maxbatch_msignal"])))))) *(np.maximum(((((data["rangebatch_msignal"])-(((((data["abs_avgbatch_slices2"])+(data["rangebatch_slices2"])))+(data["abs_maxbatch_msignal"])))))) ,(( data["abs_avgbatch_slices2"])))))) +
0.050000*np.tanh(np.where(np.maximum(((data["signal_shift_+1_msignal"])) ,(((( np.sin(( np.maximum(((data["signal_shift_+1_msignal"])) ,(((( data["abs_maxbatch_msignal"])* 2.0)))))))* 2.0)))) <= -998,(( data["signal"])* 2.0),(( np.where(( 2.0)<= -998, data["signal"], np.sin(( np.maximum(((np.sin(((( data["signal"])/ 2.0))))),(((( data["signal"])* 2.0)))))))) * 2.0)))+
0.050000*np.tanh(np.where(np.sin(( data["stdbatch_msignal"])) > -998, np.sin(((( data["stdbatch_msignal"])* 2.0))), data["stdbatch_msignal"])) +
0.050000*np.tanh(((np.where(np.where(data["signal_shift_-1_msignal"] > -998, data["abs_minbatch_slices2_msignal"], data["stdbatch_slices2_msignal"])<= -998, np.cos(( np.where(((data["abs_maxbatch_slices2_msignal"])* 2.0)<= -998, data["abs_maxbatch_slices2_msignal"], np.where(((data["abs_maxbatch_slices2_msignal"])* 2.0)<= -998, data["abs_minbatch_slices2_msignal"], data["abs_maxbatch_slices2_msignal"])))) , np.sin(((( np.maximum(((data["abs_maxbatch_slices2_msignal"])) ,(( data["abs_maxbatch_msignal"])))) * 2.0)))))* 2.0)) +
0.050000*np.tanh(((np.sin(( np.where(np.sin(( data["abs_avgbatch_msignal"])) > -998, np.sin(( data["abs_avgbatch_msignal"])) , data["signal_shift_+1"])))) *(((((np.sin(( data["abs_avgbatch_msignal"])))* 2.0)) +(((data["minbatch_msignal"])-(np.where(data["rangebatch_slices2"] > -998, np.sin(( np.sin(( data["abs_avgbatch_msignal"])))) ,(((np.sin(( data["meanbatch_msignal"])))<=(data["stdbatch_slices2"])) *1.))))))))) +
0.050000*np.tanh(((((( data["stdbatch_msignal"])+(data["mean_abs_chgbatch_slices2_msignal"])) /2.0)) *(((data["maxbatch_msignal"])-(((np.sin(( data["maxbatch_msignal"])))* 2.0)))))) +
0.050000*np.tanh(data["meanbatch_msignal"])+
0.050000*np.tanh(((((np.where(data["minbatch"] <= -998,(( data["rangebatch_slices2"])-(data["mean_abs_chgbatch_slices2"])) ,(( np.sin(( np.sin(( data["abs_maxbatch"])))))* 2.0)))*(((data["stdbatch_msignal"])*(data["medianbatch_slices2"])))))* 2.0)) +
0.050000*np.tanh(((np.where(np.tanh(((((data["abs_minbatch_slices2"])+(data["mean_abs_chgbatch_slices2_msignal"])) /2.0)))<= -998, np.cos(( data["minbatch_slices2_msignal"])) , np.cos(( np.where(((( data["abs_maxbatch_msignal"])<=(data["meanbatch_msignal"])) *1.) > -998, data["mean_abs_chgbatch_msignal"], np.cos(( data["rangebatch_slices2"])))))))*(data["meanbatch_msignal"])))+
0.050000*np.tanh(((data["maxtominbatch_msignal"])+(((data["rangebatch_slices2"])*(((((data["stdbatch_slices2_msignal"])*(np.cos(( data["mean_abs_chgbatch_slices2_msignal"])))))*(np.cos(( np.where(np.sin(( np.maximum(((data["stdbatch_slices2"])) ,(( data["abs_maxbatch"])))))> -998,(((data["maxtominbatch_msignal"])>(data["maxbatch_slices2_msignal"])) *1.) , np.cos(( data["mean_abs_chgbatch_slices2_msignal"])))))))))))) +
0.050000*np.tanh(((np.where(data["meanbatch_slices2_msignal"] <= -998, np.where(data["abs_maxbatch_slices2_msignal"] > -998, data["abs_maxbatch_slices2_msignal"], np.sin(((( data["maxbatch_msignal"])* 2.0)))) , data["meanbatch_msignal"])) *(np.cos(( data["abs_minbatch_slices2_msignal"])))))+
0.050000*np.tanh(((((np.minimum(((np.cos(( data["abs_maxbatch_slices2_msignal"])))) ,(( np.sin(((( data["abs_maxbatch_slices2_msignal"])* 2.0)))))))* 2.0)) * 2.0)) +
0.050000*np.tanh(((data["meanbatch_msignal"])*(np.minimum(((np.where(data["meanbatch_msignal"] <= -998, np.cos(( data["meanbatch_msignal"])) , np.sin(( np.where(data["meanbatch_msignal"] <= -998, np.cos(( data["meanbatch_msignal"])) , np.sin(( data["stdbatch_slices2_msignal"])))))))) ,(( np.where(data["abs_maxbatch"] <= -998, np.maximum(((np.sin(( data["meanbatch_msignal"])))) ,(((( data["maxbatch_msignal"])/ 2.0)))) , np.sin(( data["maxbatch_slices2"])))))))))+
0.050000*np.tanh(((data["medianbatch_msignal"])*(((np.cos(( np.minimum(((data["stdbatch_slices2"])) ,(( np.where(data["medianbatch_slices2"] > -998, np.where(data["stdbatch_slices2"] > -998, data["abs_minbatch_slices2_msignal"],(( data["abs_minbatch_slices2_msignal"])*(((np.cos(( data["stdbatch_slices2"])))* 2.0)))) , data["medianbatch_msignal"])))))))* 2.0)))) +
0.050000*np.tanh(((((np.where(( 7.0)> -998,(( data["meanbatch_slices2_msignal"])+(((data["abs_minbatch_msignal"])*(np.cos(( data["mean_abs_chgbatch_msignal"])))))) ,(( data["meanbatch_slices2_msignal"])+(((data["meanbatch_slices2_msignal"])*(np.cos(( data["stdbatch_msignal"])))))))) * 2.0)) * 2.0)) +
0.050000*np.tanh(np.cos(((((((data["abs_avgbatch_slices2_msignal"])+(data["rangebatch_slices2"])) /2.0)) -(np.where(np.sin(( np.minimum(((data["rangebatch_slices2"])) ,(( np.where(data["abs_maxbatch_msignal"] > -998, data["stdbatch_slices2"],(3.0)))))))> -998, data["stdbatch_slices2"], np.sin(( data["abs_avgbatch_slices2_msignal"])))))))) +
0.050000*np.tanh(((np.cos(( data["mean_abs_chgbatch_msignal"])))*(np.where(np.tanh(((( data["mean_abs_chgbatch_msignal"])*(np.where(data["signal_shift_+1_msignal"] > -998, data["mean_abs_chgbatch_msignal"],(( np.cos(( data["mean_abs_chgbatch_msignal"])))*(data["meanbatch_slices2_msignal"])))))))> -998, data["medianbatch_slices2_msignal"], data["mean_abs_chgbatch_msignal"])))) +
0.050000*np.tanh(((np.where(data["medianbatch_slices2"] <= -998, np.where(data["abs_minbatch_slices2_msignal"] <= -998, data["maxbatch_slices2"],(( data["stdbatch_msignal"])*(np.where(data["signal_shift_-1_msignal"] <= -998, data["maxtominbatch_msignal"],(( np.cos(( data["maxtominbatch_msignal"])))-(data["minbatch_msignal"])))))) ,(( data["abs_avgbatch_msignal"])*(np.cos(((( data["medianbatch_msignal"])* 2.0)))))))* 2.0)) +
0.050000*np.tanh(((np.where(((data["mean_abs_chgbatch_slices2_msignal"])-(((data["maxtominbatch_slices2_msignal"])/ 2.0)))> -998, np.cos(( np.maximum(((data["stdbatch_msignal"])) ,(( data["maxtominbatch_slices2_msignal"]))))),(( data["mean_abs_chgbatch_slices2_msignal"])+(data["medianbatch_slices2_msignal"])))) *(((data["mean_abs_chgbatch_slices2_msignal"])+(data["medianbatch_slices2_msignal"])))))+
0.050000*np.tanh(((data["meanbatch_slices2_msignal"])*(np.where(np.where(data["mean_abs_chgbatch_msignal"] > -998, data["medianbatch_slices2_msignal"],(-(( data["rangebatch_msignal"])))) <= -998, np.where(((( np.cos(( np.where(data["meanbatch_slices2_msignal"] <= -998,(((data["medianbatch_slices2_msignal"])>(data["signal_shift_-1"])) *1.) , np.cos(( data["abs_minbatch_msignal"])))))) >(data["signal_shift_-1"])) *1.) <= -998, data["abs_minbatch_msignal"], data["stdbatch_slices2"]), np.cos(( data["abs_minbatch_msignal"])))))) +
0.050000*np.tanh(((data["stdbatch_msignal"])*(np.sin(((( data["abs_maxbatch_slices2"])+(np.sin(((( data["abs_maxbatch_slices2"])*(np.sin(( data["signal_shift_+1"])))))))))))))+
0.050000*np.tanh(((( data["meanbatch_msignal"])+(((((data["medianbatch_slices2"])+(((((((((data["abs_minbatch_msignal"])+(np.sin(( data["meanbatch_msignal"])))))+(data["abs_avgbatch_slices2_msignal"])))+(((np.cos(( data["signal"])))+(((( data["abs_avgbatch_slices2_msignal"])<=(((((np.cos(( data["stdbatch_slices2_msignal"])))/ 2.0)) * 2.0)))*1.))))))* 2.0)))) *(np.cos(( data["stdbatch_slices2_msignal"])))))) /2.0)) +
0.050000*np.tanh(np.where(data["meanbatch_slices2_msignal"] <= -998, np.maximum(((( -(( np.maximum(((( -(( data["meanbatch_slices2_msignal"]))))),(( data["abs_maxbatch_slices2_msignal"])))))))) ,(( data["abs_maxbatch_slices2_msignal"]))), np.minimum(((np.maximum(((( 8.0))),(( np.sin(( data["maxtominbatch_slices2"]))))))),(((( np.minimum(((( 8.0))),(( np.sin(( np.maximum(((( -(( data["meanbatch_msignal"]))))),(( data["abs_maxbatch_slices2_msignal"])))))))))* 2.0)))))) +
0.050000*np.tanh(np.minimum(((((((data["stdbatch_msignal"])*(((data["signal"])+(((data["abs_avgbatch_slices2_msignal"])*(np.sin(( data["signal"])))))))))*(np.sin(( data["maxbatch_slices2"])))))) ,(((( np.sin(( np.where(data["stdbatch_msignal"] <= -998, data["signal"],(( np.where(((data["maxbatch_slices2"])*(data["abs_maxbatch_msignal"])) > -998, data["signal"], data["abs_maxbatch"])) * 2.0)))))* 2.0)))))+
0.050000*np.tanh(((np.sin(( data["meanbatch_msignal"])))*(((data["stdbatch_slices2_msignal"])+(((np.sin(( np.sin(( data["stdbatch_slices2_msignal"])))))-(np.sin(((( data["abs_avgbatch_slices2"])-(np.sin(( data["rangebatch_slices2"])))))))))))))+
0.050000*np.tanh(((((data["stdbatch_msignal"])*(((((((np.sin(( data["abs_maxbatch_slices2"])))*(((((data["abs_maxbatch_slices2"])+(data["mean_abs_chgbatch_msignal"])))* 2.0)))) * 2.0)) * 2.0)))) +(((((3.0)) +(np.minimum(((data["abs_maxbatch_slices2"])) ,(( data["stdbatch_msignal"])))))/2.0)))) +
0.050000*np.tanh(((np.cos(( data["signal"])))*(np.where(( 4.17584276199340820)> -998,(( np.tanh(( data["meanbatch_msignal"])))+(data["meanbatch_msignal"])) , np.sin(((( data["meanbatch_msignal"])+(data["meanbatch_msignal"])))))))) +
0.050000*np.tanh(((((data["signal_shift_+1"])*(data["meanbatch_msignal"])))*(np.minimum(((np.sin(((( np.sin(( data["minbatch_msignal"])))* 2.0))))),(((( np.where(np.where(data["minbatch_msignal"] <= -998, data["signal_shift_+1"],(((( data["signal_shift_+1"])*(data["abs_avgbatch_slices2_msignal"])))*(np.cos(( data["signal"])))))<= -998, data["signal"], data["signal_shift_+1"])) * 2.0)))))))+
0.050000*np.tanh(((np.cos(((( np.where(data["minbatch"] <= -998, data["medianbatch_msignal"], data["medianbatch_slices2_msignal"])) -(( -(((( data["maxtominbatch_slices2"])-(((( data["stdbatch_slices2"])+(((data["rangebatch_slices2_msignal"])+(np.cos(( np.tanh(((((data["medianbatch_msignal"])<=(data["meanbatch_slices2_msignal"])) *1.))))))))) /2.0)))))))))))* 2.0)) +
0.050000*np.tanh(((data["minbatch_msignal"])*(np.tanh(((((((((data["stdbatch_slices2_msignal"])+(( 10.58995056152343750)))) >(data["abs_maxbatch"])) *1.))-(((data["meanbatch_slices2_msignal"])*(np.sin(( data["abs_maxbatch"])))))))))))+
0.050000*np.tanh(np.where(((((data["medianbatch_slices2_msignal"])* 2.0)) / 2.0)<= -998,(((data["stdbatch_slices2_msignal"])+(np.sin(( data["stdbatch_slices2"])))) /2.0), np.minimum(((data["stdbatch_slices2_msignal"])) ,(( np.maximum(((( 13.43751239776611328))),(((( data["stdbatch_msignal"])*(np.sin(( np.minimum(((data["abs_maxbatch"])) ,(( data["medianbatch_msignal"])))))))))))))))+
0.050000*np.tanh(((((np.maximum(((np.maximum(((np.cos(( data["maxtominbatch_msignal"])))) ,(((13.34599208831787109)))))) ,(( data["maxtominbatch_slices2"])))) -(data["medianbatch_slices2"])))*(np.where(np.cos(( np.cos(( data["maxbatch_slices2_msignal"])))) <= -998, data["abs_minbatch_slices2"], np.cos(( data["maxbatch_slices2_msignal"])))))) +
0.050000*np.tanh(((data["medianbatch_msignal"])+(np.where(((((( np.sin(( data["meanbatch_msignal"])))+(( 14.61012458801269531)))/2.0)) *(data["signal_shift_-1"])) > -998, data["abs_minbatch_msignal"],(( data["abs_minbatch_msignal"])* 2.0)))))+
0.050000*np.tanh(np.where(data["minbatch"] > -998,(( np.sin(((((data["maxtominbatch_slices2_msignal"])+(((np.minimum(((data["abs_maxbatch"])) ,(((( np.minimum(((data["mean_abs_chgbatch_slices2"])) ,(( data["rangebatch_slices2_msignal"])))) *(data["minbatch_msignal"])))))) / 2.0)))/2.0)))) * 2.0),(((data["abs_maxbatch"])>(data["meanbatch_slices2_msignal"])) *1.))) +
0.050000*np.tanh(((np.where(data["signal_shift_-1"] <= -998, np.where(np.tanh(( np.minimum(((data["mean_abs_chgbatch_msignal"])) ,(( data["stdbatch_slices2_msignal"])))))> -998, data["maxtominbatch"], data["stdbatch_slices2_msignal"]),(( data["stdbatch_msignal"])* 2.0)))*(np.cos(( data["mean_abs_chgbatch_msignal"])))))+
0.050000*np.tanh(((np.minimum(((((( data["stdbatch_slices2"])>(np.cos(( data["signal"])))) *1.))) ,(( data["signal_shift_+1_msignal"])))) * 2.0)) +
0.050000*np.tanh(((np.cos(( data["abs_minbatch_msignal"])))*(np.where(data["abs_avgbatch_slices2"] > -998, data["meanbatch_msignal"],(((( np.cos(( data["abs_minbatch_msignal"])))*(np.where(data["minbatch_slices2_msignal"] > -998, data["meanbatch_msignal"], np.cos(( data["abs_minbatch_msignal"])))))) *(((data["maxbatch_slices2_msignal"])*(data["meanbatch_msignal"])))))))) +
0.050000*np.tanh(((data["medianbatch_msignal"])*(np.where(data["abs_avgbatch_slices2"] <= -998, data["medianbatch_msignal"], np.minimum(((np.where(data["medianbatch_msignal"] <= -998, data["medianbatch_msignal"], np.cos(( data["mean_abs_chgbatch_msignal"]))))),(( data["rangebatch_slices2"])))))))+
0.050000*np.tanh(np.where(np.where(data["signal_shift_+1"] <= -998, np.maximum(((data["signal_shift_-1_msignal"])) ,(((((( data["medianbatch_msignal"])*(data["abs_maxbatch_slices2"])))-(data["maxbatch_msignal"]))))), data["medianbatch_slices2"])<= -998, np.sin(( data["minbatch_msignal"])) , np.minimum(((np.sin(( data["maxbatch_msignal"])))) ,(((( data["medianbatch_msignal"])*(np.sin(( data["minbatch_msignal"])))))))))+
0.050000*np.tanh(np.sin(( np.maximum(((data["meanbatch_msignal"])) ,(( np.maximum(((((data["abs_maxbatch_msignal"])-(data["meanbatch_msignal"])))) ,(( data["abs_maxbatch_msignal"])))))))))+
0.050000*np.tanh(((np.tanh(( np.sin(((( data["meanbatch_msignal"])-(data["signal_shift_-1"])))))))+(np.minimum(((((np.sin(( np.sin(((( data["medianbatch_slices2_msignal"])-(data["signal_shift_-1"])))))))* 2.0))),(((( data["signal_shift_-1"])/ 2.0)))))))+
0.050000*np.tanh(((((data["medianbatch_slices2_msignal"])*(((data["maxtominbatch"])*(((data["abs_minbatch_slices2_msignal"])*(data["medianbatch_slices2"])))))))*(np.cos(( data["abs_minbatch_slices2_msignal"])))))+
0.050000*np.tanh(((np.sin(( np.where(np.minimum(((np.maximum(((np.sin(( np.minimum(((np.sin(( data["abs_maxbatch_msignal"])))) ,(( data["minbatch_msignal"]))))))),(((((((data["medianbatch_slices2_msignal"])* 2.0)) +(data["signal_shift_-1"])) /2.0)))))) ,(( data["meanbatch_slices2"])))> -998, data["minbatch_msignal"], data["meanbatch_slices2_msignal"])))) *(((data["meanbatch_slices2_msignal"])* 2.0)))) +
0.050000*np.tanh(((np.sin(((10.50283241271972656)))) +(((np.cos(( data["mean_abs_chgbatch_msignal"])))*(((((data["mean_abs_chgbatch_slices2"])+(data["mean_abs_chgbatch_msignal"])))+(((data["abs_minbatch_msignal"])+(data["meanbatch_msignal"])))))))))+
0.050000*np.tanh(((np.cos(( np.where(((data["minbatch_msignal"])* 2.0)> -998, data["minbatch_msignal"], np.where(data["minbatch_msignal"] > -998, np.sin(( data["signal_shift_-1_msignal"])) , data["minbatch_msignal"])))))* 2.0)) +
0.050000*np.tanh(((data["medianbatch_slices2_msignal"])+(((((data["abs_maxbatch"])+(data["medianbatch_slices2_msignal"])))*(np.sin(( np.where(((data["stdbatch_slices2_msignal"])+(np.sin(( np.sin(( np.where(data["maxbatch_slices2"] > -998, data["abs_maxbatch_msignal"],(( data["maxtominbatch"])* 2.0)))))))) > -998, data["abs_maxbatch_msignal"],(( data["meanbatch_msignal"])+(data["minbatch_slices2_msignal"])))))))))) +
0.050000*np.tanh(((data["stdbatch_msignal"])*(np.sin(( data["abs_maxbatch"])))))+
0.050000*np.tanh(((data["signal"])*(((data["mean_abs_chgbatch_msignal"])*(((( data["abs_maxbatch_slices2"])+(np.minimum(((np.minimum(((data["medianbatch_msignal"])) ,(((( data["mean_abs_chgbatch_msignal"])*(data["meanbatch_msignal"]))))))),(( data["rangebatch_slices2"])))))/2.0)))))) +
0.050000*np.tanh(((np.where(data["medianbatch_msignal"] <= -998, np.maximum(((data["meanbatch_slices2_msignal"])) ,(( np.where(np.maximum(((data["abs_minbatch_slices2_msignal"])) ,(((( data["stdbatch_slices2_msignal"])* 2.0)))) <= -998, np.maximum(((((data["mean_abs_chgbatch_slices2_msignal"])* 2.0))),(( data["meanbatch_msignal"]))), data["stdbatch_msignal"])))) , np.maximum(((data["stdbatch_msignal"])) ,(( data["meanbatch_msignal"])))))*(np.sin(( data["stdbatch_msignal"])))))+
0.050000*np.tanh(( -(( np.cos(( np.where(data["abs_minbatch_slices2_msignal"] > -998, data["rangebatch_slices2_msignal"], np.cos(( data["meanbatch_slices2_msignal"])))))))))+
0.050000*np.tanh(np.sin(( np.where(( -(( np.where(data["abs_minbatch_msignal"] > -998, np.minimum(((data["medianbatch_slices2_msignal"])) ,(( data["minbatch"]))), data["abs_avgbatch_slices2_msignal"])))) > -998,(( np.maximum(((data["medianbatch_slices2_msignal"])) ,(( data["medianbatch_slices2_msignal"])))) -(data["signal_shift_+1"])) ,(( data["abs_avgbatch_msignal"])* 2.0)))))+
0.050000*np.tanh(((data["stdbatch_msignal"])*(np.where(((data["signal"])*(((data["stdbatch_msignal"])/ 2.0)))<= -998, data["minbatch_slices2"], data["signal"])))) +
0.050000*np.tanh(((np.cos(((( data["abs_maxbatch"])-(np.where(np.where(((data["minbatch_slices2"])-(( 5.48352003097534180)))> -998, data["maxbatch_slices2"],(((data["medianbatch_slices2_msignal"])<=(data["maxbatch_slices2"])) *1.))> -998, data["medianbatch_slices2_msignal"],(( data["medianbatch_slices2_msignal"])* 2.0)))))))* 2.0)) +
0.050000*np.tanh(((((data["mean_abs_chgbatch_slices2"])-(((((data["mean_abs_chgbatch_slices2"])-(np.where(data["mean_abs_chgbatch_slices2_msignal"] > -998,(((((data["mean_abs_chgbatch_slices2_msignal"])* 2.0)) <=(data["signal_shift_-1_msignal"])) *1.) , data["mean_abs_chgbatch_slices2_msignal"])))) *(((data["mean_abs_chgbatch_slices2_msignal"])* 2.0)))))) *(((data["mean_abs_chgbatch_slices2_msignal"])* 2.0)))) +
0.050000*np.tanh(((((np.minimum(((data["meanbatch_slices2"])) ,(( np.minimum(((data["abs_maxbatch"])) ,(( np.sin(( np.where(((((data["maxbatch_slices2_msignal"])* 2.0)) +(( -(( data["signal_shift_-1_msignal"])))))<= -998, data["medianbatch_slices2"],(((( data["maxbatch_slices2_msignal"])* 2.0)) +(( -(( data["signal_shift_-1_msignal"])))))))))))))))* 2.0)) * 2.0)) +
0.050000*np.tanh(((data["meanbatch_slices2_msignal"])*(((np.minimum(((np.sin(( np.sin(( data["minbatch_msignal"])))))) ,(( np.sin(( np.sin(( data["minbatch_msignal"])))))))) *(((( 11.18099498748779297)) -(((np.minimum(((( 11.18099498748779297))),(( np.sin(( data["minbatch_msignal"])))))) *(np.minimum(((data["mean_abs_chgbatch_msignal"])) ,(((11.18099498748779297)))))))))))))+
0.050000*np.tanh(((((np.where(np.sin(((( data["abs_avgbatch_msignal"])-(data["signal_shift_-1"])))) <= -998, data["stdbatch_msignal"], np.sin(((( data["abs_avgbatch_msignal"])-(data["signal_shift_-1"])))))) * 2.0)) * 2.0)) +
0.050000*np.tanh(( -(( np.where(data["abs_minbatch_slices2_msignal"] <= -998,(( data["signal_shift_-1"])+(np.where(data["mean_abs_chgbatch_slices2_msignal"] <= -998, data["stdbatch_slices2"], data["abs_minbatch_msignal"]))),(((( np.sin(( data["signal_shift_-1"])))* 2.0)) *(((data["minbatch_slices2"])*(data["stdbatch_slices2_msignal"])))))))))+
0.050000*np.tanh(np.where(data["stdbatch_msignal"] <= -998,(((( np.where(data["abs_maxbatch"] <= -998, data["medianbatch_slices2_msignal"], data["maxbatch_msignal"])) * 2.0)) * 2.0),(( np.minimum(((((data["mean_abs_chgbatch_msignal"])* 2.0))),(((( data["stdbatch_msignal"])*(np.where(data["signal_shift_-1"] > -998, data["abs_avgbatch_slices2_msignal"],(( data["maxbatch_slices2_msignal"])*(((data["meanbatch_slices2_msignal"])* 2.0)))))))))) * 2.0)))+
0.050000*np.tanh(((((data["medianbatch_msignal"])+(np.where(data["maxtominbatch"] > -998,(( np.cos(((( data["signal"])* 2.0)))) *(data["signal_shift_+1"])) ,(( np.cos(((( data["signal"])* 2.0)))) *(data["rangebatch_slices2_msignal"])))))) * 2.0)) +
0.050000*np.tanh(((np.minimum(((data["meanbatch_slices2"])) ,(( np.cos(( np.where(np.sin(( data["abs_maxbatch_msignal"])) > -998, np.maximum(((data["abs_minbatch_msignal"])) ,(((( data["signal_shift_-1_msignal"])-(data["abs_maxbatch_slices2_msignal"]))))), np.where(data["abs_maxbatch_msignal"] <= -998,(((data["abs_maxbatch_msignal"])+(data["abs_maxbatch_msignal"])) /2.0), np.sin(( data["abs_maxbatch_msignal"])))))))))) * 2.0)) +
0.050000*np.tanh(np.where(np.minimum(((data["signal_shift_+1"])) ,(((( np.tanh(( data["meanbatch_slices2_msignal"])))* 2.0)))) <= -998,(-(( data["rangebatch_msignal"]))),(( data["meanbatch_slices2_msignal"])*(np.cos(((( data["signal_shift_+1"])-(data["abs_maxbatch_slices2_msignal"])))))))) +
0.050000*np.tanh(np.where(np.tanh(( np.sin(((-(((((data["rangebatch_slices2"])+(((( np.sin(((-(( data["signal_shift_-1"])))))) +(np.cos(( data["minbatch_msignal"])))) /2.0)))/2.0)))))))) > -998,(( np.cos(( data["minbatch_msignal"])))* 2.0),(((data["signal_shift_-1"])+(data["stdbatch_slices2_msignal"])) /2.0)))+
0.050000*np.tanh(np.sin(((( data["abs_avgbatch_slices2_msignal"])-(np.maximum(((data["signal_shift_-1"])) ,(( np.sin(( np.minimum(((np.maximum(((((data["abs_avgbatch_slices2_msignal"])-(np.maximum(((data["signal_shift_-1"])) ,(((((data["signal_shift_-1"])<=(data["signal_shift_-1"])) *1.)))))))),(( data["signal_shift_-1"]))))),(( data["signal"])))))))))))))+
0.050000*np.tanh(( -(( np.where(data["stdbatch_slices2_msignal"] > -998, np.cos(( data["rangebatch_slices2_msignal"])) ,(((data["minbatch_msignal"])>(np.maximum(((data["minbatch_msignal"])) ,(( data["maxbatch_slices2"])))))*1.))))))+
0.050000*np.tanh(((( np.where(( -(( np.cos(( np.maximum(((np.cos(((( data["maxtominbatch_slices2"])* 2.0))))),(( np.where(data["abs_avgbatch_msignal"] > -998, data["meanbatch_msignal"], data["meanbatch_msignal"])))))))))> -998,(( data["medianbatch_slices2_msignal"])/ 2.0),(( np.where(data["meanbatch_msignal"] > -998, data["medianbatch_slices2_msignal"], data["meanbatch_msignal"])) / 2.0)))+(data["medianbatch_msignal"])) /2.0)) +
0.050000*np.tanh(np.cos(((((data["maxbatch_msignal"])+(((np.cos(( np.maximum(((data["maxtominbatch_slices2_msignal"])) ,(( data["rangebatch_msignal"])))))) -(data["minbatch_slices2"])))) /2.0)))) +
0.050000*np.tanh(((data["stdbatch_slices2_msignal"])*(( -(( np.where(np.minimum(((data["rangebatch_slices2"])) ,(( data["signal_shift_+1_msignal"])))<= -998, data["abs_minbatch_msignal"], np.minimum(((np.sin(( data["rangebatch_slices2"])))) ,(((-(((-(((((14.85157394409179688)) -(data["signal_shift_-1"])))))))))))))))))) +
0.050000*np.tanh(((( -(( data["mean_abs_chgbatch_msignal"])))) *(np.sin(((-(((( data["minbatch"])-(( -(( data["mean_abs_chgbatch_msignal"])))))))))))))+
0.050000*np.tanh(np.where(np.tanh(( data["medianbatch_slices2_msignal"])) > -998, np.where(((data["medianbatch_msignal"])* 2.0)> -998, np.where(data["meanbatch_slices2_msignal"] > -998, data["medianbatch_slices2"], data["meanbatch_slices2_msignal"]), np.cos(((( data["medianbatch_slices2_msignal"])-(np.where(((data["medianbatch_msignal"])/ 2.0)> -998, data["medianbatch_slices2"], data["medianbatch_slices2_msignal"])))))) , data["meanbatch_slices2_msignal"])) +
0.050000*np.tanh(((data["stdbatch_msignal"])*(((np.maximum(((np.maximum(((data["rangebatch_slices2"])) ,(((((( np.sin(( data["abs_maxbatch"])))*(data["stdbatch_msignal"])))* 2.0)))))) ,(( np.sin(((-(( data["rangebatch_slices2"])))))))))*(np.sin(((( np.sin(((-(( data["rangebatch_slices2"])))))) * 2.0)))))))) +
0.050000*np.tanh(((data["maxbatch_slices2"])*(np.where(data["maxbatch_slices2_msignal"] > -998,(((((( data["meanbatch_msignal"])+(data["maxtominbatch_slices2"])))*(data["medianbatch_slices2_msignal"])))*(data["signal_shift_-1_msignal"])) ,(((((((((( data["medianbatch_slices2_msignal"])+(data["maxtominbatch_slices2"])))*(data["medianbatch_slices2_msignal"])))+(data["maxtominbatch_slices2"])))*(data["medianbatch_slices2_msignal"])))*(data["signal_shift_-1_msignal"])))))) +
0.050000*np.tanh(((((np.sin(((( data["medianbatch_slices2_msignal"])-(np.maximum(((data["signal_shift_-1"])) ,(((((np.where(( 3.0)<= -998, data["abs_avgbatch_slices2"], data["medianbatch_msignal"])) +(data["signal_shift_-1"])) /2.0)))))))))*(( 13.39701461791992188)))) +(data["medianbatch_slices2_msignal"])))+
0.050000*np.tanh(((((data["signal"])*(data["stdbatch_msignal"])))*(np.where(data["signal_shift_+1"] > -998,(((( data["abs_maxbatch_slices2_msignal"])-(data["medianbatch_slices2_msignal"])))-(data["signal_shift_+1_msignal"])) , np.cos(((( data["signal_shift_+1_msignal"])*(data["stdbatch_msignal"])))))))) +
0.050000*np.tanh(np.where(np.where(data["minbatch_msignal"] > -998, data["abs_avgbatch_slices2"], np.sin(( np.where(((data["minbatch_msignal"])* 2.0)> -998, np.minimum(((data["signal"])) ,(( data["rangebatch_slices2"]))),(( np.cos(( np.maximum(((data["rangebatch_slices2"])) ,(( data["meanbatch_slices2"])))))) * 2.0)))))> -998,(( data["stdbatch_slices2_msignal"])*(np.sin(( np.sin(( data["abs_maxbatch"])))))) ,(((( data["rangebatch_slices2"])* 2.0)) * 2.0)))+
0.050000*np.tanh(((np.cos(( np.minimum(((np.minimum(((np.cos(( data["signal_shift_+1_msignal"])))) ,(( np.minimum(((data["minbatch_msignal"])) ,(( np.cos(( data["maxbatch_slices2_msignal"])))))))))) ,(( np.minimum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(( data["signal_shift_-1"])))))))))* 2.0)) +
0.050000*np.tanh(((data["minbatch_slices2_msignal"])*(np.where(np.tanh(( data["maxtominbatch_slices2"])) <= -998, data["stdbatch_slices2_msignal"], np.cos(( np.where(((data["maxtominbatch_slices2"])*(np.where(data["minbatch_slices2_msignal"] <= -998, data["maxtominbatch_slices2"], np.cos(( data["maxtominbatch_msignal"])))))<= -998, data["mean_abs_chgbatch_slices2"], data["medianbatch_slices2"])))))))+
0.050000*np.tanh(np.sin(((( data["maxbatch_slices2"])+(np.where(((((data["signal_shift_+1"])+(np.sin(( data["stdbatch_slices2_msignal"])))))+(( 9.0)))> -998, data["signal_shift_+1"], data["abs_minbatch_slices2_msignal"])))))) +
0.050000*np.tanh(np.minimum(((np.where(np.where(data["medianbatch_msignal"] > -998, data["meanbatch_msignal"], data["stdbatch_msignal"])<= -998,(( np.maximum(((data["minbatch"])) ,(( data["stdbatch_msignal"])))) / 2.0), data["medianbatch_slices2_msignal"]))),(( np.minimum(((data["meanbatch_msignal"])) ,(( np.sin(( np.where(data["stdbatch_slices2_msignal"] <= -998,(6.52855157852172852), data["abs_maxbatch_msignal"])))))))))) +
0.050000*np.tanh(((np.where(np.sin(((((data["signal_shift_+1"])+(data["minbatch_msignal"])) /2.0)))> -998, np.cos(((((data["minbatch_msignal"])+(data["minbatch_msignal"])) /2.0))), data["minbatch_msignal"])) * 2.0)) +
0.050000*np.tanh(((np.where(data["signal"] > -998, data["meanbatch_msignal"], data["maxbatch_slices2"])) -(((data["abs_minbatch_msignal"])*(np.maximum(((((data["meanbatch_msignal"])* 2.0))),(((( data["maxtominbatch_slices2"])*(((data["abs_minbatch_msignal"])*(np.maximum(((((data["signal_shift_+1_msignal"])* 2.0))),(( data["mean_abs_chgbatch_slices2_msignal"])))))))))))))))+
0.050000*np.tanh(np.where(((data["abs_maxbatch_slices2_msignal"])/ 2.0)<= -998, data["medianbatch_slices2"], data["medianbatch_slices2"])) +
0.050000*np.tanh(np.minimum(((((np.minimum(((data["medianbatch_slices2_msignal"])) ,(((((((4.0)) -(( 4.0)))) -(( -(( np.minimum(((data["stdbatch_msignal"])) ,(( data["medianbatch_msignal"])))))))))))) * 2.0))),(((( data["medianbatch_slices2_msignal"])* 2.0)))))+
0.050000*np.tanh(np.where(np.tanh(( data["signal_shift_+1"])) <= -998,(( data["signal_shift_+1"])+(data["signal_shift_+1"])) , data["signal_shift_-1"])) +
0.050000*np.tanh(np.cos(( np.where(((((( data["medianbatch_slices2"])+(np.cos(( data["medianbatch_slices2"])))))+(np.where(((data["abs_avgbatch_slices2"])+(data["meanbatch_msignal"])) <= -998, data["signal"], data["abs_avgbatch_slices2"])))/2.0)> -998,(( np.sin(( data["abs_maxbatch_slices2"])))-(data["minbatch_msignal"])) , data["abs_maxbatch_slices2"])))) +
0.050000*np.tanh(np.minimum(((((np.minimum(((((np.minimum(((((data["signal_shift_-1"])* 2.0))),(( data["minbatch_msignal"])))) *(np.cos(( data["meanbatch_slices2"])))))) ,(((((( data["signal_shift_-1"])*(data["meanbatch_slices2"])))*(np.sin(( data["abs_maxbatch_msignal"])))))))) +(data["meanbatch_slices2"])))) ,(((( data["rangebatch_slices2_msignal"])*(np.sin(( np.sin(( data["abs_maxbatch_msignal"])))))))))) +
0.050000*np.tanh(np.minimum(((np.minimum(((((((((( np.cos(( np.where(np.minimum(((data["medianbatch_slices2"])) ,(( data["signal_shift_+1"])))> -998, np.sin(( data["maxtominbatch_slices2_msignal"])) , data["medianbatch_slices2"])))) >(data["medianbatch_slices2"])) *1.))*(data["minbatch"])))/ 2.0))),(( data["stdbatch_slices2"]))))),(((2.77612638473510742)))))+
0.050000*np.tanh(((data["signal_shift_-1_msignal"])+(np.where(data["minbatch_msignal"] > -998,(( np.cos(((( data["signal_shift_-1"])* 2.0)))) *(data["abs_maxbatch_slices2_msignal"])) , data["meanbatch_msignal"])))) +
0.050000*np.tanh(((((np.sin(((( data["medianbatch_slices2"])-(data["abs_maxbatch_msignal"])))))* 2.0)) * 2.0)) +
0.050000*np.tanh(np.minimum(((((((((((( data["signal_shift_-1"])+(data["mean_abs_chgbatch_slices2_msignal"])) /2.0)) * 2.0)) *(data["signal_shift_-1"])))/ 2.0))),(( np.sin(((((( data["mean_abs_chgbatch_slices2_msignal"])+(((( np.where(np.maximum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(( np.cos(( data["mean_abs_chgbatch_slices2_msignal"])))))> -998, data["signal_shift_-1"], data["mean_abs_chgbatch_slices2_msignal"])) <=(np.cos(( data["rangebatch_slices2"])))) *1.))))* 2.0)))))))+
0.050000*np.tanh(np.where(( 4.46286773681640625)<= -998, data["abs_minbatch_slices2"], np.sin(((( data["maxbatch_msignal"])+(np.tanh(((((((data["medianbatch_msignal"])*(np.sin(((((data["maxbatch_msignal"])+(data["medianbatch_slices2_msignal"])) /2.0)))))) <=(((( 4.46286773681640625)) +(((( data["meanbatch_slices2_msignal"])<=(((( data["meanbatch_slices2_msignal"])<=(((data["abs_minbatch_slices2"])*(data["signal_shift_+1"])))) *1.))) *1.))))) *1.))))))))) +
0.050000*np.tanh(((data["abs_minbatch_msignal"])*(np.minimum(((data["abs_avgbatch_slices2"])) ,(( np.cos(( np.where(((((data["medianbatch_msignal"])+(((np.tanh(( data["meanbatch_slices2_msignal"])))+(np.maximum(((data["stdbatch_slices2"])) ,(( data["abs_minbatch_msignal"])))))))) * 2.0)<= -998, data["abs_minbatch_slices2"], np.maximum(((data["medianbatch_slices2"])) ,(((( data["signal_shift_-1"])+(data["meanbatch_slices2_msignal"])))))))))))))) +
0.050000*np.tanh(((data["medianbatch_slices2_msignal"])+(np.minimum(((np.sin(( data["abs_maxbatch_msignal"])))) ,(( np.minimum(((np.maximum(((((((( np.sin(( data["abs_maxbatch_msignal"])))/ 2.0)) <=(data["abs_minbatch_slices2"])) *1.))) ,(( np.cos(( np.maximum(((np.tanh(( np.tanh(( np.maximum(((data["stdbatch_slices2_msignal"])) ,(( data["stdbatch_slices2_msignal"]))))))))),(( np.tanh(( data["rangebatch_msignal"])))))))))))) ,(( np.sin(( data["signal_shift_+1_msignal"])))))))))))+
0.050000*np.tanh(((data["minbatch_msignal"])*(np.sin(((( np.maximum(((data["meanbatch_slices2"])) ,(( np.maximum(((np.sin(((( np.maximum(((data["meanbatch_slices2"])) ,(( np.cos(( np.sin(((( data["meanbatch_slices2"])*(data["meanbatch_slices2"])))))))))) * 2.0))))),(( data["meanbatch_slices2_msignal"])))))))* 2.0)))))) +
0.050000*np.tanh(((np.where(data["signal_shift_-1"] <= -998, np.cos(( np.tanh(((( data["stdbatch_slices2_msignal"])* 2.0))))),(( np.cos(((( data["mean_abs_chgbatch_msignal"])-(data["signal_shift_-1"])))))* 2.0)))*(data["abs_maxbatch_slices2_msignal"])))+
0.050000*np.tanh(np.sin(( np.maximum(((((data["rangebatch_msignal"])-(data["abs_avgbatch_slices2"])))) ,(( np.maximum(((((data["rangebatch_msignal"])-(data["abs_avgbatch_slices2"])))) ,(( data["abs_avgbatch_slices2"])))))))))+
0.050000*np.tanh(np.where(data["stdbatch_slices2"] <= -998,(((( np.minimum(((data["maxtominbatch_msignal"])) ,(((( np.maximum(((data["maxtominbatch"])) ,(( data["medianbatch_msignal"])))) / 2.0)))))+(data["medianbatch_slices2"])))+(data["mean_abs_chgbatch_msignal"])) , data["medianbatch_msignal"])) +
0.050000*np.tanh(np.where(np.maximum(((np.cos(( data["signal_shift_+1_msignal"])))) ,(( np.where(np.maximum(((data["signal_shift_-1_msignal"])) ,(((((((data["abs_maxbatch_slices2"])*(data["meanbatch_slices2_msignal"])))<=(data["maxtominbatch_slices2"])) *1.))))<= -998, np.cos(( data["minbatch_msignal"])) , np.tanh(( data["signal_shift_-1_msignal"])))))) <= -998, np.cos(( data["minbatch_msignal"])) , np.tanh(((( np.cos(( data["minbatch_msignal"])))* 2.0)))))+
0.050000*np.tanh(np.sin(( np.where(data["signal_shift_+1"] <= -998, np.cos(( data["meanbatch_slices2"])) , np.minimum(((data["signal_shift_+1"])) ,(( np.maximum(((data["meanbatch_slices2"])) ,(( data["medianbatch_slices2_msignal"])))))))))) +
0.050000*np.tanh(np.sin(((( data["medianbatch_slices2"])-(np.where(((data["meanbatch_slices2"])* 2.0)> -998, data["maxtominbatch_slices2_msignal"], np.cos(( np.where(data["rangebatch_msignal"] > -998, np.where(data["meanbatch_slices2_msignal"] > -998, data["medianbatch_slices2"], np.maximum(((data["signal_shift_-1_msignal"])) ,(( data["signal_shift_-1"])))) , np.sin(( data["minbatch"])))))))))))+
0.050000*np.tanh(((np.where(((data["medianbatch_slices2"])/ 2.0)> -998, np.where(data["meanbatch_slices2"] <= -998, data["abs_avgbatch_msignal"],(( data["stdbatch_msignal"])*(np.sin(( np.minimum(((data["maxtominbatch_slices2"])) ,(( data["meanbatch_msignal"])))))))) , data["maxtominbatch_slices2_msignal"])) +(data["meanbatch_msignal"])))+
0.050000*np.tanh(((data["abs_minbatch_slices2"])+(((( data["meanbatch_slices2_msignal"])+(((data["signal_shift_+1_msignal"])+(np.tanh(( data["mean_abs_chgbatch_msignal"])))))) /2.0)))) +
0.050000*np.tanh(np.where(np.where(((( data["minbatch_msignal"])<=(((((((((data["minbatch_msignal"])<=(data["minbatch_msignal"])) *1.))/ 2.0)) <=(data["abs_maxbatch_slices2_msignal"])) *1.))) *1.) > -998, data["abs_maxbatch_slices2_msignal"], data["signal"])<= -998, data["meanbatch_slices2"],(( data["meanbatch_slices2"])*(((data["maxbatch_slices2"])*(np.cos(((( data["abs_maxbatch_slices2_msignal"])-(((((( data["signal_shift_-1"])<=(data["maxbatch_slices2"])) *1.))/ 2.0)))))))))))+
0.050000*np.tanh(((((data["abs_avgbatch_slices2_msignal"])*(data["meanbatch_slices2_msignal"])))*(np.where(np.tanh(( data["signal_shift_-1"])) > -998, data["signal_shift_-1"],(( np.maximum(((data["meanbatch_slices2"])) ,(( data["minbatch"])))) / 2.0)))))+
0.050000*np.tanh(np.maximum(((data["signal_shift_+1_msignal"])) ,(( np.minimum(((np.sin(((( data["medianbatch_slices2_msignal"])+(data["medianbatch_slices2_msignal"])))))) ,(( data["medianbatch_slices2_msignal"])))))))+
0.050000*np.tanh(data["medianbatch_slices2_msignal"])+
0.050000*np.tanh(((data["abs_maxbatch_slices2"])*(np.tanh(( np.sin(( np.where(data["medianbatch_slices2"] <= -998, np.maximum(((((((( data["maxtominbatch"])<=(((data["meanbatch_slices2"])* 2.0)))*1.))/ 2.0))),(( data["abs_minbatch_msignal"]))),(((( data["maxbatch_msignal"])* 2.0)) * 2.0)))))))))+
0.050000*np.tanh(((np.cos(((( np.cos(( data["signal_shift_-1"])))+(((data["medianbatch_msignal"])-(data["abs_maxbatch"])))))))* 2.0)) +
0.050000*np.tanh(np.sin(((( np.where(np.where(data["abs_maxbatch"] > -998,(( data["signal"])+(data["medianbatch_slices2"])) , data["medianbatch_slices2"])<= -998, data["rangebatch_slices2_msignal"], np.where(data["rangebatch_msignal"] <= -998,(( data["minbatch_slices2"])-(data["abs_maxbatch_msignal"])) , data["rangebatch_msignal"])))-(np.maximum(((data["signal"])) ,(( data["meanbatch_msignal"])))))))) +
0.050000*np.tanh(((data["medianbatch_slices2"])+(np.minimum(((np.where(data["maxtominbatch_slices2_msignal"] <= -998, np.tanh(( np.sin(( data["maxbatch_msignal"])))) , data["medianbatch_slices2"]))),(( np.maximum(((data["maxtominbatch_msignal"])) ,(( np.maximum(((data["maxtominbatch_msignal"])) ,(( data["maxtominbatch"])))))))))))) +
0.050000*np.tanh(np.cos(( np.maximum(((((data["signal_shift_+1"])-(np.tanh(((((((np.cos(( data["signal_shift_+1"])))/ 2.0)) +(((data["abs_minbatch_slices2"])* 2.0)))/2.0))))))),(( data["rangebatch_slices2"])))))) +
0.050000*np.tanh(data["medianbatch_slices2"])+
0.050000*np.tanh(((data["medianbatch_msignal"])-(np.where(np.sin(((12.89390754699707031)))> -998, data["signal_shift_+1"], data["maxtominbatch"])))) +
0.050000*np.tanh(((((((((data["signal_shift_+1"])* 2.0)) *(np.sin(( np.sin(( np.where(np.minimum(((data["medianbatch_msignal"])) ,(((((((6.0)) *(np.sin(((( data["signal_shift_+1"])* 2.0)))))) *(( -(( data["signal_shift_-1_msignal"])))))))) > -998, data["medianbatch_msignal"], data["stdbatch_slices2"])))))))) *(( -(( data["signal_shift_-1_msignal"])))))) * 2.0)) +
0.050000*np.tanh(((data["medianbatch_msignal"])-(np.where(((( np.tanh(( np.tanh(( np.sin(( data["medianbatch_msignal"])))))))<=(np.where(data["abs_avgbatch_slices2_msignal"] <= -998, data["maxtominbatch"], data["stdbatch_slices2_msignal"])))*1.) <= -998,(((( data["abs_maxbatch_msignal"])*(data["medianbatch_msignal"])))*(np.where(data["signal_shift_-1"] <= -998,(-(( data["medianbatch_slices2"]))), data["abs_avgbatch_slices2_msignal"]))), data["stdbatch_slices2_msignal"])))) +
0.050000*np.tanh(((data["signal_shift_+1"])*(((data["rangebatch_msignal"])*(np.sin(( data["abs_maxbatch_msignal"])))))))+
0.050000*np.tanh(np.where(data["maxtominbatch_slices2"] > -998, np.where(data["minbatch"] > -998, np.minimum(((data["signal_shift_-1"])) ,(( np.where(data["stdbatch_msignal"] > -998, data["stdbatch_msignal"], data["medianbatch_slices2_msignal"])))) ,(((data["medianbatch_msignal"])<=(data["stdbatch_msignal"])) *1.)),(( data["abs_minbatch_msignal"])/ 2.0)))+
0.050000*np.tanh(((data["meanbatch_slices2"])-(((( np.where(((( data["meanbatch_slices2"])>(((data["signal_shift_+1"])+(data["meanbatch_slices2"])))) *1.) > -998, data["abs_maxbatch_msignal"],(( data["signal_shift_+1"])+(( -(( np.tanh(( data["meanbatch_slices2"])))))))))>(((data["medianbatch_msignal"])+(data["signal_shift_-1"])))) *1.))))+
0.050000*np.tanh(np.cos(( np.minimum(((np.minimum(((data["minbatch_msignal"])) ,(( np.maximum(((data["meanbatch_slices2_msignal"])) ,(( np.cos(( np.minimum(((data["minbatch_msignal"])) ,(( np.maximum(((np.sin(( np.cos(( data["minbatch"])))))) ,(( data["mean_abs_chgbatch_msignal"])))))))))))))))) ,(( np.cos(( np.minimum(((np.cos(( data["maxbatch_slices2"])))) ,(( data["meanbatch_slices2_msignal"])))))))))))+
0.050000*np.tanh(np.where(((( data["meanbatch_slices2_msignal"])>(((np.maximum(((data["meanbatch_slices2_msignal"])) ,(( data["meanbatch_slices2_msignal"])))) -(data["meanbatch_slices2"])))) *1.) <= -998,(((data["medianbatch_slices2_msignal"])<=(((( data["signal_shift_+1_msignal"])<=(data["meanbatch_slices2"])) *1.))) *1.) , np.maximum(((data["signal_shift_-1_msignal"])) ,(( data["meanbatch_slices2_msignal"])))))+
0.050000*np.tanh(((( data["signal_shift_+1"])+(np.maximum(((np.where(data["abs_maxbatch_slices2_msignal"] > -998, np.sin(((((((((np.maximum(((data["mean_abs_chgbatch_msignal"])) ,(( data["abs_maxbatch_slices2_msignal"])))) >(data["abs_avgbatch_slices2_msignal"])) *1.))+(data["abs_avgbatch_msignal"])))/ 2.0))), data["minbatch_msignal"]))),(( data["meanbatch_slices2_msignal"])))))/2.0)) +
0.050000*np.tanh(np.minimum(((data["maxbatch_slices2_msignal"])) ,(( data["medianbatch_slices2_msignal"])))) +
0.050000*np.tanh(((( -(((((( data["abs_maxbatch"])*(np.sin(( np.where(data["medianbatch_msignal"] > -998, data["medianbatch_msignal"],(-(( np.where(((((data["abs_maxbatch"])*(( 1.0)))) * 2.0)> -998, data["medianbatch_msignal"], data["medianbatch_msignal"])))))))))) * 2.0)))))* 2.0)) +
0.050000*np.tanh(np.minimum(((data["medianbatch_slices2_msignal"])) ,(((((np.where(data["signal_shift_-1_msignal"] > -998, data["mean_abs_chgbatch_slices2"], data["meanbatch_slices2"])) >(data["maxtominbatch"])) *1.))))))
 def GP_class_6(self,data):
return self.Output(-3.281070 +
0.050000*np.tanh(((((np.where(data["meanbatch_msignal"] > -998, data["maxbatch_msignal"], np.sin(( np.maximum(((data["signal_shift_-1_msignal"])) ,(( data["meanbatch_slices2"])))))))*(data["meanbatch_slices2"])))-(((data["abs_maxbatch"])-(data["minbatch_slices2_msignal"])))))+
0.050000*np.tanh(np.minimum(((np.minimum(((data["abs_maxbatch"])) ,(((( data["stdbatch_slices2"])+(((((data["mean_abs_chgbatch_slices2"])* 2.0)) / 2.0)))))))) ,(( np.maximum(((data["minbatch_slices2_msignal"])) ,(( data["signal"])))))))+
0.050000*np.tanh(data["meanbatch_slices2"])+
0.050000*np.tanh(np.where(((( data["meanbatch_slices2_msignal"])<=(data["rangebatch_msignal"])) *1.) <= -998,(((data["stdbatch_slices2_msignal"])+(((( data["rangebatch_slices2"])<=(((((( data["meanbatch_slices2_msignal"])-(data["meanbatch_msignal"])))+(((( data["maxtominbatch_slices2_msignal"])>(((data["abs_avgbatch_msignal"])+(np.minimum(((data["meanbatch_slices2"])) ,(( data["meanbatch_slices2_msignal"])))))))*1.))) /2.0)))*1.))) /2.0), data["meanbatch_slices2_msignal"])) +
0.050000*np.tanh(np.where(data["abs_minbatch_msignal"] > -998, data["signal"], np.where(data["medianbatch_msignal"] > -998, data["maxbatch_msignal"], np.where(data["stdbatch_slices2"] > -998, np.maximum(((np.where(((data["meanbatch_slices2"])* 2.0)> -998, data["signal_shift_+1"], data["meanbatch_slices2"]))),(( data["medianbatch_msignal"]))), np.tanh(((( data["meanbatch_slices2"])/ 2.0)))))))+
0.050000*np.tanh(data["signal_shift_+1"])+
0.050000*np.tanh(np.tanh(( np.where(data["meanbatch_slices2"] <= -998, data["abs_avgbatch_slices2"],(((np.sin(( data["stdbatch_slices2"])))+(data["signal"])) /2.0)))))+
0.050000*np.tanh(((np.where(data["minbatch_slices2"] <= -998, np.where(((((data["meanbatch_msignal"])/ 2.0)) / 2.0)> -998, data["meanbatch_msignal"], data["medianbatch_slices2"]), data["minbatch_slices2"])) +(data["maxbatch_slices2_msignal"])))+
0.050000*np.tanh(np.where(data["meanbatch_slices2_msignal"] > -998, data["meanbatch_slices2_msignal"], np.where(data["abs_minbatch_slices2"] > -998,(((( data["maxbatch_slices2"])+(data["meanbatch_slices2_msignal"])))*(np.maximum(((((((data["maxbatch_slices2"])+(data["signal_shift_+1_msignal"])))* 2.0))),(( np.maximum(((((( 9.0)) * 2.0))),(( data["meanbatch_slices2_msignal"])))))))) , data["signal_shift_-1"])))+
0.050000*np.tanh(np.where(data["stdbatch_slices2_msignal"] > -998, data["meanbatch_slices2_msignal"], np.tanh(( np.sin(((( np.where(data["stdbatch_slices2_msignal"] > -998, data["medianbatch_slices2"], np.where(data["meanbatch_slices2"] > -998,(( data["medianbatch_slices2"])* 2.0),(-(( data["abs_avgbatch_msignal"])))))) +(data["meanbatch_slices2_msignal"])))))))) +
0.050000*np.tanh(data["meanbatch_slices2_msignal"])+
0.050000*np.tanh(((((( data["medianbatch_slices2_msignal"])+(((((( 12.08343982696533203)) *(np.tanh(( data["meanbatch_msignal"])))))*(((((((data["signal"])/ 2.0)) * 2.0)) * 2.0)))))) +(((data["minbatch_slices2_msignal"])* 2.0)))/2.0)) +
0.050000*np.tanh(((data["signal"])*(np.maximum(((data["meanbatch_slices2_msignal"])) ,(((((((( data["medianbatch_msignal"])/ 2.0)) * 2.0)) *(np.where(((np.cos(( data["maxbatch_slices2_msignal"])))-(((((data["signal_shift_+1"])*(data["medianbatch_slices2"])))+(data["abs_minbatch_slices2"])))) > -998, data["abs_maxbatch_slices2_msignal"], data["meanbatch_slices2_msignal"])))))))))+
0.050000*np.tanh(np.where(data["medianbatch_slices2_msignal"] > -998, np.minimum(((((data["signal_shift_+1"])+(np.where(((data["medianbatch_slices2"])+(data["maxtominbatch_slices2_msignal"])) > -998, np.minimum(((data["signal_shift_+1"])) ,(( data["abs_avgbatch_slices2_msignal"]))), data["maxtominbatch_slices2"]))))),(( data["medianbatch_msignal"]))), data["medianbatch_msignal"])) +
0.050000*np.tanh(np.sin(( np.sin(( data["meanbatch_msignal"])))))+
0.050000*np.tanh(np.minimum(((data["signal_shift_-1"])) ,(( np.minimum(((data["abs_avgbatch_slices2_msignal"])) ,(( np.where(np.minimum(((data["signal_shift_+1"])) ,(( data["abs_avgbatch_slices2"])))<= -998, data["signal_shift_-1"], np.minimum(((data["meanbatch_slices2"])) ,(( data["medianbatch_msignal"])))))))))))+
0.050000*np.tanh(np.minimum(((np.where(data["meanbatch_msignal"] > -998, np.where(data["maxbatch_slices2_msignal"] <= -998, data["meanbatch_slices2_msignal"], data["medianbatch_slices2_msignal"]),(((((data["signal"])*(((((((1.0)) *(((( data["stdbatch_msignal"])+(data["medianbatch_slices2_msignal"])) /2.0)))) +(data["medianbatch_msignal"])) /2.0)))) +(data["medianbatch_msignal"])) /2.0)))) ,(( data["signal"])))) +
0.050000*np.tanh(np.where(((( data["meanbatch_slices2"])+(np.cos(( data["signal_shift_+1"])))) /2.0)> -998, data["signal_shift_+1"], np.cos(( data["rangebatch_msignal"])))) +
0.050000*np.tanh(((data["medianbatch_slices2"])-(((np.where(data["abs_maxbatch_slices2_msignal"] > -998,(((np.where(data["medianbatch_slices2"] > -998, data["meanbatch_msignal"], data["meanbatch_msignal"])) >(data["signal_shift_-1_msignal"])) *1.) , data["maxbatch_msignal"])) * 2.0)))) +
0.050000*np.tanh(np.where(((((np.tanh(( np.tanh(((( np.where(((( data["meanbatch_msignal"])+(((data["meanbatch_slices2_msignal"])/ 2.0)))/2.0)> -998,(( data["abs_maxbatch"])*(data["abs_maxbatch"])) , np.tanh(((((( data["medianbatch_slices2_msignal"])* 2.0)) *(data["medianbatch_msignal"])))))) *(data["rangebatch_slices2"])))))))/ 2.0)) * 2.0)> -998, data["medianbatch_msignal"], data["medianbatch_msignal"])) +
0.050000*np.tanh(np.where(((data["minbatch_msignal"])*(data["signal_shift_+1"])) > -998, data["medianbatch_slices2"], data["meanbatch_slices2_msignal"])) +
0.050000*np.tanh(((np.where(np.where(np.cos(( data["maxbatch_msignal"])) > -998, data["medianbatch_msignal"], data["medianbatch_slices2_msignal"])> -998, data["signal"], data["mean_abs_chgbatch_slices2"])) *(data["medianbatch_msignal"])))+
0.050000*np.tanh(np.minimum(((data["medianbatch_slices2"])) ,(( data["signal"])))) +
0.050000*np.tanh(((np.where(np.maximum(((((data["signal"])/ 2.0))),(( data["signal"])))> -998, data["meanbatch_msignal"],(((((((np.where(np.where(data["rangebatch_slices2"] > -998,(-(( np.maximum(((np.sin(( data["meanbatch_msignal"])))) ,(( data["stdbatch_slices2_msignal"])))))) ,(( data["meanbatch_msignal"])* 2.0)) > -998, data["meanbatch_slices2"], data["signal"])) * 2.0)) +(data["meanbatch_msignal"])) /2.0)) * 2.0)))* 2.0)) +
0.050000*np.tanh(((np.cos(( data["maxtominbatch"])))*(( -(( np.where(data["signal"] > -998,(14.11495685577392578),(((((np.cos(( np.where(((data["rangebatch_slices2"])*(( -(((((( data["minbatch_slices2"])*(( -(( data["maxbatch_slices2_msignal"])))))) +(data["signal_shift_+1_msignal"])))))))<= -998, data["meanbatch_slices2_msignal"], data["signal_shift_+1_msignal"])))) +(data["stdbatch_slices2"])) /2.0)) +(data["meanbatch_slices2"])))))))))+
0.050000*np.tanh(np.where(np.where(np.tanh(( data["rangebatch_slices2"])) <= -998, np.tanh(( data["stdbatch_slices2_msignal"])) , np.tanh(( np.tanh(( data["signal_shift_+1"])))))> -998, data["meanbatch_slices2_msignal"], data["minbatch_slices2_msignal"])) +
0.050000*np.tanh(np.minimum(((((data["signal"])*(( 6.30654382705688477))))),(((( data["meanbatch_msignal"])+(((np.tanh(( data["meanbatch_slices2"])))*(((data["medianbatch_slices2_msignal"])/ 2.0)))))))))+
0.050000*np.tanh(np.minimum(((( 9.0))),(((( data["abs_maxbatch_slices2"])* 2.0)))))+
0.050000*np.tanh(((np.where(data["meanbatch_slices2_msignal"] > -998, data["meanbatch_slices2_msignal"], data["abs_avgbatch_slices2"])) * 2.0)) +
0.050000*np.tanh(np.sin(( np.maximum(((data["abs_maxbatch_slices2"])) ,(( np.minimum(((((( data["maxtominbatch"])>(np.cos(( data["maxbatch_msignal"])))) *1.))) ,(((3.0)))))))))) +
0.050000*np.tanh(np.minimum(((data["mean_abs_chgbatch_slices2"])) ,(( data["medianbatch_msignal"])))) +
0.050000*np.tanh(((data["meanbatch_slices2_msignal"])*(data["meanbatch_slices2_msignal"])))+
0.050000*np.tanh(((((data["signal"])-(( 1.03515052795410156)))) *(((((data["maxtominbatch_slices2"])+(((((np.tanh(((((( data["maxbatch_slices2_msignal"])/ 2.0)) +(data["maxbatch_slices2_msignal"])))))/ 2.0)) +(((data["abs_avgbatch_slices2_msignal"])* 2.0)))))) * 2.0)))) +
0.050000*np.tanh(np.where(((( data["signal_shift_-1"])>(( -(( data["maxbatch_slices2"])))))*1.) <= -998, data["rangebatch_msignal"],(( np.minimum(((data["abs_maxbatch"])) ,(( data["maxbatch_slices2_msignal"])))) *(np.sin(( np.where(np.sin(( data["abs_minbatch_slices2_msignal"])) <= -998, data["maxbatch_slices2_msignal"], np.sin(( data["abs_maxbatch"])))))))))+
0.050000*np.tanh(np.where(np.where(data["meanbatch_slices2_msignal"] > -998,(( data["abs_avgbatch_slices2_msignal"])*(data["rangebatch_slices2"])) , data["signal_shift_-1"])> -998, np.minimum(((np.sin(( data["meanbatch_msignal"])))) ,(( data["meanbatch_msignal"]))), data["abs_avgbatch_slices2_msignal"])) +
0.050000*np.tanh(((np.where(data["abs_avgbatch_msignal"] <= -998, data["mean_abs_chgbatch_slices2_msignal"], data["meanbatch_slices2_msignal"])) * 2.0)) +
0.050000*np.tanh(((np.where(data["meanbatch_slices2_msignal"] <= -998, np.cos(( data["maxbatch_msignal"])) , np.cos(( data["maxbatch_msignal"])))) * 2.0)) +
0.050000*np.tanh(((data["medianbatch_msignal"])+(np.minimum(((((np.where(data["medianbatch_slices2_msignal"] > -998, np.where(data["abs_maxbatch_msignal"] <= -998, data["medianbatch_slices2"], np.sin(( data["abs_maxbatch"]))), data["stdbatch_slices2"])) * 2.0))),(((( data["medianbatch_msignal"])* 2.0)))))))+
0.050000*np.tanh(np.where(((np.maximum(((np.where(data["maxbatch_slices2"] > -998, data["meanbatch_slices2_msignal"], np.maximum(((data["meanbatch_slices2_msignal"])) ,(( data["meanbatch_slices2_msignal"])))))) ,(( data["meanbatch_slices2_msignal"])))) *(data["rangebatch_msignal"])) <= -998,(-(( np.where(data["signal"] > -998,(8.77815341949462891), data["minbatch"])))) , data["medianbatch_msignal"])) +
0.050000*np.tanh(np.cos(( np.where(((( np.maximum(((data["medianbatch_msignal"])) ,(( data["signal_shift_+1"])))) >(data["meanbatch_slices2"])) *1.) > -998, data["stdbatch_msignal"],(-(( np.tanh(( np.where(np.cos(( np.where(data["meanbatch_slices2"] > -998, np.sin(( data["abs_avgbatch_slices2"])) ,(-(( data["stdbatch_msignal"])))))) > -998, data["meanbatch_msignal"], data["abs_minbatch_msignal"])))))))))) +
0.050000*np.tanh(np.maximum(((np.cos(( data["maxbatch_slices2_msignal"])))) ,(( data["minbatch_slices2_msignal"])))) +
0.050000*np.tanh(((((data["medianbatch_slices2_msignal"])*(data["signal"])))-(np.cos(( np.where(data["minbatch_slices2_msignal"] <= -998,(( data["signal"])/ 2.0), data["meanbatch_slices2_msignal"])))))) +
0.050000*np.tanh(np.cos(( np.maximum(((data["maxbatch_msignal"])) ,(((( np.sin(( data["maxbatch_msignal"])))-(data["meanbatch_msignal"])))))))) +
0.050000*np.tanh(data["signal_shift_-1"])+
0.050000*np.tanh(data["meanbatch_msignal"])+
0.050000*np.tanh(((((np.cos(( data["maxbatch_msignal"])))+(data["medianbatch_msignal"])))-(((( np.cos(( np.maximum(((( -(( data["medianbatch_msignal"]))))),(((-(( data["medianbatch_msignal"])))))))))>(data["maxtominbatch_slices2"])) *1.))))+
0.050000*np.tanh(((np.where(np.maximum(((data["abs_minbatch_slices2_msignal"])) ,(( data["maxbatch_slices2_msignal"])))<= -998, data["maxbatch_slices2_msignal"], np.cos(( np.maximum(((data["meanbatch_slices2"])) ,(( np.maximum(((data["maxbatch_slices2_msignal"])) ,(((( np.tanh(( data["abs_maxbatch_slices2"])))* 2.0)))))))))))*(np.where(data["medianbatch_slices2"] > -998, data["abs_maxbatch_slices2"],(( np.cos(( np.maximum(((data["medianbatch_slices2_msignal"])) ,(( data["medianbatch_slices2"])))))) * 2.0)))))+
0.050000*np.tanh(np.sin(( np.minimum(((data["abs_avgbatch_slices2_msignal"])) ,(( data["medianbatch_msignal"])))))) +
0.050000*np.tanh(((data["medianbatch_msignal"])*(np.where(data["mean_abs_chgbatch_msignal"] <= -998, np.cos(( data["signal"])) ,(( np.minimum(((( -(( data["mean_abs_chgbatch_slices2_msignal"]))))),(((( data["maxbatch_msignal"])* 2.0)))))*(data["medianbatch_slices2_msignal"])))))) +
0.050000*np.tanh(np.minimum(((data["meanbatch_slices2_msignal"])) ,(( np.where(np.where(data["maxbatch_slices2_msignal"] <= -998, np.sin(( data["meanbatch_slices2_msignal"])) ,(( data["meanbatch_slices2_msignal"])*(((data["medianbatch_msignal"])*(data["meanbatch_msignal"])))))<= -998, data["meanbatch_slices2_msignal"],(( data["abs_maxbatch"])*(np.sin(( data["abs_avgbatch_slices2_msignal"])))))))))+
0.050000*np.tanh(((np.sin(((4.0)))) *(np.where(data["signal"] > -998,(-(( data["signal"]))), np.maximum(((( 7.53076505661010742))),(( data["abs_minbatch_slices2_msignal"])))))))+
0.050000*np.tanh(((np.cos(( data["maxbatch_msignal"])))+(np.cos(((( data["maxbatch_msignal"])+(data["maxbatch_msignal"])))))))+
0.050000*np.tanh(np.cos(( np.where(( -(( np.tanh(((((np.tanh(( np.sin(((( np.maximum(((((data["medianbatch_msignal"])* 2.0))),(( data["mean_abs_chgbatch_slices2_msignal"])))) -(data["medianbatch_msignal"])))))))>(np.cos(((((data["rangebatch_msignal"])+(np.cos(( data["medianbatch_msignal"])))) /2.0)))))*1.))))))> -998, data["abs_maxbatch_slices2_msignal"], data["abs_maxbatch_slices2"])))) +
0.050000*np.tanh(np.minimum(((((data["meanbatch_msignal"])* 2.0))),(((( np.minimum(((( -(( np.tanh(( data["mean_abs_chgbatch_msignal"]))))))),(( data["signal"])))) *(data["abs_maxbatch_slices2"])))))) +
0.050000*np.tanh(np.minimum(((data["meanbatch_msignal"])) ,(( np.cos(( np.maximum(((data["maxbatch_slices2_msignal"])) ,(( data["maxbatch_slices2_msignal"])))))))))+
0.050000*np.tanh(((((np.cos(( np.where(data["abs_maxbatch_msignal"] > -998, data["maxbatch_msignal"], data["meanbatch_slices2_msignal"])))) *(np.where(data["maxbatch_msignal"] > -998, data["abs_maxbatch_msignal"], np.tanh(((( np.where(data["minbatch_slices2_msignal"] > -998, data["stdbatch_slices2_msignal"], data["abs_maxbatch_slices2_msignal"])) / 2.0)))))))* 2.0)) +
0.050000*np.tanh(np.minimum(((np.minimum(((( 12.71473979949951172))),(( np.where(data["medianbatch_msignal"] > -998, np.where(data["rangebatch_slices2_msignal"] > -998, np.minimum(((data["meanbatch_slices2_msignal"])) ,(( np.cos(( data["maxbatch_msignal"]))))),(10.0)) , np.maximum(((data["signal"])) ,(( np.where(data["medianbatch_msignal"] <= -998, data["signal"], data["signal"])))))))))) ,(( data["signal"])))) +
0.050000*np.tanh(((np.where(data["meanbatch_msignal"] <= -998, data["maxbatch_slices2"], np.minimum(((((np.where(data["signal_shift_-1"] <= -998,(( np.sin(( np.maximum(((np.maximum(((data["maxtominbatch_slices2_msignal"])) ,(( data["abs_maxbatch_slices2_msignal"]))))),(( np.cos(( data["maxbatch_slices2_msignal"])))))))) * 2.0), np.minimum(((data["meanbatch_slices2_msignal"])) ,(( np.cos(( data["maxbatch_slices2_msignal"])))))))* 2.0))),(( data["abs_minbatch_slices2"])))))* 2.0)) +
0.050000*np.tanh(np.minimum(((((( -(( data["mean_abs_chgbatch_msignal"])))) * 2.0))),(((( data["abs_avgbatch_msignal"])+(data["abs_avgbatch_slices2_msignal"])))))) +
0.050000*np.tanh(((np.tanh(( data["meanbatch_slices2_msignal"])))*(np.where(data["minbatch_msignal"] > -998,(( data["abs_maxbatch_msignal"])*(np.where(data["signal_shift_+1_msignal"] > -998,(6.65409708023071289),(((( data["signal_shift_+1_msignal"])* 2.0)) *(data["abs_maxbatch_slices2_msignal"]))))), np.cos(( data["meanbatch_slices2_msignal"])))))) +
0.050000*np.tanh(((((data["abs_maxbatch_slices2_msignal"])*(np.cos(( np.cos(( np.where(np.sin(( data["abs_avgbatch_slices2_msignal"])) > -998, np.cos(((( data["abs_maxbatch_msignal"])-(np.where(data["medianbatch_slices2_msignal"] > -998, data["meanbatch_msignal"], np.sin(( data["maxtominbatch_msignal"]))))))), data["meanbatch_msignal"])))))))) * 2.0)) +
0.050000*np.tanh(((np.where(np.cos(( data["maxbatch_msignal"])) <= -998, data["maxbatch_msignal"],(((( np.cos(( data["minbatch_msignal"])))*(((((( data["abs_maxbatch_msignal"])/ 2.0)) +(data["abs_maxbatch_msignal"])) /2.0)))) * 2.0)))-(((data["maxbatch_msignal"])/ 2.0)))) +
0.050000*np.tanh(( -(( np.where(((np.sin(((( data["maxbatch_slices2_msignal"])*(data["maxbatch_slices2"])))))-(((( data["meanbatch_msignal"])<=(((data["signal"])-(data["abs_avgbatch_slices2_msignal"])))) *1.))) <= -998,(( data["maxbatch_slices2_msignal"])+(data["stdbatch_msignal"])) ,(( data["mean_abs_chgbatch_slices2_msignal"])*(data["abs_avgbatch_slices2_msignal"])))))))+
0.050000*np.tanh(((data["maxtominbatch_msignal"])*(np.where(data["stdbatch_msignal"] > -998, np.cos(( data["abs_avgbatch_msignal"])) , np.where(data["maxtominbatch_slices2"] <= -998, data["abs_minbatch_msignal"], data["maxtominbatch_msignal"])))))+
0.050000*np.tanh(np.where(data["medianbatch_msignal"] <= -998,(((((( np.cos(( data["maxbatch_msignal"])))*(data["maxbatch_slices2"])))*(np.sin(( data["signal_shift_+1_msignal"])))))*(data["maxbatch_msignal"])) ,(( data["minbatch_slices2_msignal"])+(np.where(data["maxbatch_slices2"] <= -998, data["medianbatch_msignal"],(( data["meanbatch_msignal"])*(data["maxbatch_slices2"])))))))+
0.050000*np.tanh(((np.where(np.cos(( data["abs_maxbatch_msignal"])) > -998,(( data["rangebatch_slices2"])* 2.0),(-(( data["abs_maxbatch_msignal"])))))* 2.0)) +
0.050000*np.tanh(((data["signal"])*(np.cos(((( np.where(data["stdbatch_msignal"] <= -998, np.maximum(((np.where(np.tanh(( data["minbatch_slices2_msignal"])) <= -998, data["minbatch_msignal"], data["signal"]))),(( data["signal"]))), data["stdbatch_msignal"])) * 2.0)))))) +
0.050000*np.tanh(np.where(((((8.0)) +(np.minimum(((data["rangebatch_slices2_msignal"])) ,(( data["meanbatch_slices2"])))))/2.0)> -998,(( np.where(data["meanbatch_slices2_msignal"] <= -998, data["maxbatch_msignal"],(-(((( data["mean_abs_chgbatch_slices2_msignal"])*(data["medianbatch_slices2_msignal"])))))))* 2.0), np.cos(( data["mean_abs_chgbatch_slices2_msignal"])))) +
0.050000*np.tanh(((((np.minimum(((data["signal_shift_-1"])) ,(((( np.sin(( data["medianbatch_msignal"])))-(np.where(((np.cos(( data["stdbatch_msignal"])))*(np.tanh(( data["mean_abs_chgbatch_msignal"])))) <= -998,(( data["abs_avgbatch_msignal"])*(data["abs_maxbatch_slices2_msignal"])) ,(( data["meanbatch_slices2"])*(np.tanh(( data["mean_abs_chgbatch_msignal"])))))))))))*(((np.cos(( data["abs_maxbatch_slices2_msignal"])))* 2.0)))) * 2.0)) +
0.050000*np.tanh(((data["mean_abs_chgbatch_msignal"])*(np.where(data["abs_avgbatch_msignal"] <= -998,(((( data["stdbatch_msignal"])*(data["minbatch_msignal"])))*(((data["mean_abs_chgbatch_msignal"])*(np.sin(( data["abs_maxbatch"])))))) ,(-(( np.where(((( data["abs_minbatch_msignal"])+(np.maximum(((data["signal"])) ,(( np.where(data["rangebatch_slices2_msignal"] > -998, data["medianbatch_msignal"], data["minbatch_msignal"])))))) /2.0)> -998, data["medianbatch_msignal"], data["abs_minbatch_msignal"])))))))) +
0.050000*np.tanh(((( 2.66262960433959961)) *(np.cos(( np.minimum(((np.maximum(((np.minimum(((data["stdbatch_slices2_msignal"])) ,(((( data["signal"])* 2.0)))))) ,(( data["abs_minbatch_slices2_msignal"]))))),(( np.where(data["abs_maxbatch"] <= -998, data["abs_minbatch_slices2_msignal"],(( data["stdbatch_slices2_msignal"])* 2.0)))))))))) +
0.050000*np.tanh(((np.sin(((( data["abs_maxbatch_slices2"])-(np.minimum(((np.minimum(((np.sin(( data["meanbatch_slices2_msignal"])))) ,(( np.minimum(((data["abs_maxbatch_msignal"])) ,(( data["mean_abs_chgbatch_slices2_msignal"])))))))) ,(( np.minimum(((np.minimum(((((data["signal"])+(data["signal_shift_+1"])))) ,(( np.minimum(((data["signal"])) ,(( data["mean_abs_chgbatch_slices2_msignal"])))))))) ,(( data["mean_abs_chgbatch_slices2_msignal"])))))))))))*(data["abs_maxbatch_msignal"])))+
0.050000*np.tanh(((np.cos(( data["abs_avgbatch_msignal"])))*(((data["mean_abs_chgbatch_slices2_msignal"])*(np.where(((((( data["minbatch"])+(data["rangebatch_msignal"])))<=(np.minimum(((np.minimum(((((data["abs_avgbatch_msignal"])*(data["medianbatch_slices2_msignal"])))) ,(( data["abs_avgbatch_msignal"]))))),(( data["mean_abs_chgbatch_slices2_msignal"])))))*1.) > -998, data["rangebatch_msignal"], np.cos(( np.cos(( data["abs_avgbatch_msignal"])))))))))) +
0.050000*np.tanh(np.where(data["abs_avgbatch_slices2"] <= -998, np.where(data["maxbatch_msignal"] <= -998, np.cos(( data["medianbatch_msignal"])) , data["maxbatch_msignal"]), np.cos(( np.where(np.where(data["abs_avgbatch_slices2"] > -998, data["maxbatch_slices2_msignal"], np.cos(( np.cos(( data["abs_avgbatch_slices2"])))))<= -998, data["signal"], data["maxbatch_msignal"])))))+
0.050000*np.tanh(((( data["signal"])+(( -(((( data["abs_maxbatch_slices2"])*(data["mean_abs_chgbatch_msignal"])))))))/2.0)) +
0.050000*np.tanh(((((((data["mean_abs_chgbatch_slices2"])*(((((np.sin(((( np.cos(( data["meanbatch_msignal"])))-(data["abs_minbatch_msignal"])))))*(np.maximum(((data["meanbatch_msignal"])) ,(( data["stdbatch_msignal"])))))) * 2.0)))) *(data["meanbatch_msignal"])))-(((((( np.sin(( data["meanbatch_msignal"])))*(data["abs_minbatch_msignal"])))<=(data["abs_maxbatch_slices2_msignal"])) *1.))))+
0.050000*np.tanh(((((np.sin(( np.minimum(((np.sin(((( np.maximum(((((( data["abs_maxbatch_msignal"])+(np.where(data["abs_maxbatch_msignal"] > -998, data["maxtominbatch_slices2_msignal"], data["maxtominbatch_msignal"])))/2.0))),(( data["abs_maxbatch_msignal"])))) +(data["medianbatch_msignal"])))))) ,(( data["meanbatch_slices2"])))))) * 2.0)) * 2.0)) +
0.050000*np.tanh(((((data["medianbatch_msignal"])*(data["signal"])))-(((((((np.cos(( np.sin(( data["maxtominbatch_msignal"])))))>(data["signal_shift_+1_msignal"])) *1.))<=(( -(( np.minimum(((data["abs_avgbatch_msignal"])) ,(( data["maxbatch_msignal"])))))))) *1.))))+
0.050000*np.tanh(((((data["meanbatch_msignal"])*(( -(( np.tanh(( np.where(data["stdbatch_msignal"] > -998, data["mean_abs_chgbatch_msignal"],(((( data["medianbatch_slices2_msignal"])+(data["mean_abs_chgbatch_msignal"])))* 2.0)))))))))) * 2.0)) +
0.050000*np.tanh(np.where(((( data["meanbatch_msignal"])<=(data["abs_avgbatch_msignal"])) *1.) > -998,(((( data["medianbatch_slices2_msignal"])* 2.0)) *(( -(( data["mean_abs_chgbatch_slices2_msignal"]))))), data["abs_maxbatch"])) +
0.050000*np.tanh(np.where(((((((( data["signal"])* 2.0)) >(data["maxtominbatch_slices2_msignal"])) *1.))+(data["signal"])) <= -998,(( data["rangebatch_slices2"])-(((( np.minimum(((((( data["signal"])<=(data["stdbatch_slices2_msignal"])) *1.))) ,(( data["stdbatch_slices2_msignal"])))) +(data["rangebatch_slices2"])) /2.0))),(( data["rangebatch_slices2"])*(np.cos(((( data["stdbatch_slices2_msignal"])* 2.0)))))))+
0.050000*np.tanh(np.where(((data["signal_shift_+1"])*(data["signal_shift_-1"])) <= -998, data["abs_minbatch_slices2_msignal"],(( data["mean_abs_chgbatch_slices2_msignal"])*(((( np.minimum(((data["minbatch_slices2"])) ,(( data["minbatch_slices2"])))) +(( -(( data["stdbatch_slices2_msignal"])))))/2.0)))))+
0.050000*np.tanh(((((data["mean_abs_chgbatch_slices2_msignal"])+(data["mean_abs_chgbatch_msignal"])))*(((data["minbatch_slices2_msignal"])-(((((((data["medianbatch_msignal"])+(np.cos(( data["maxbatch_msignal"])))))-(data["signal_shift_-1"])))* 2.0)))))) +
0.050000*np.tanh(((np.cos(((( np.where(data["stdbatch_msignal"] <= -998,(((np.where(data["meanbatch_slices2_msignal"] <= -998, data["meanbatch_msignal"], data["abs_maxbatch_msignal"])) +(( -(( data["abs_avgbatch_msignal"])))))/2.0), data["abs_maxbatch_msignal"])) +(data["stdbatch_msignal"])))))* 2.0)) +
0.050000*np.tanh(((np.sin(((( np.where(((data["maxbatch_msignal"])* 2.0)> -998, data["abs_maxbatch_msignal"], data["abs_avgbatch_slices2"])) +(data["meanbatch_msignal"])))))* 2.0)) +
0.050000*np.tanh(np.cos(( np.where(data["abs_maxbatch_msignal"] > -998, data["maxbatch_slices2_msignal"], np.where(data["minbatch_msignal"] <= -998,(-(( np.where(((np.cos(( data["abs_maxbatch_slices2_msignal"])))* 2.0)<= -998, data["abs_maxbatch"], data["minbatch_slices2_msignal"])))) , np.cos(( np.tanh(( data["maxbatch_slices2_msignal"])))))))))+
0.050000*np.tanh(((np.where(data["signal_shift_-1"] <= -998, np.cos(((( data["meanbatch_slices2"])* 2.0))), np.where(((( np.where(((data["stdbatch_msignal"])*(( -(((( np.cos(((-(( data["minbatch_msignal"])))))) * 2.0)))))) <= -998, np.tanh(( data["minbatch_msignal"])) , data["meanbatch_msignal"])) +(data["signal_shift_-1"])) /2.0)<= -998, data["mean_abs_chgbatch_slices2"], data["meanbatch_msignal"])))/ 2.0)) +
0.050000*np.tanh(np.where(data["meanbatch_msignal"] > -998, np.where(np.sin(((3.0)))<= -998, data["abs_maxbatch_slices2_msignal"],(((((((data["medianbatch_slices2_msignal"])>(data["maxtominbatch_msignal"])) *1.))+(data["abs_maxbatch_slices2_msignal"])))*(np.sin(( data["maxtominbatch_msignal"]))))), np.sin(( data["maxtominbatch_msignal"])))) +
0.050000*np.tanh(((data["rangebatch_slices2_msignal"])*(((((((( -(( data["mean_abs_chgbatch_msignal"])))) * 2.0)) *(((data["mean_abs_chgbatch_msignal"])+(data["meanbatch_msignal"])))))+(np.tanh(( data["signal_shift_-1"])))))))+
0.050000*np.tanh(((np.minimum(((((data["signal_shift_+1"])-(np.tanh(((( data["abs_minbatch_slices2_msignal"])+(data["rangebatch_msignal"])))))))) ,(((( np.where(data["maxtominbatch_slices2_msignal"] > -998, np.tanh(( np.cos(( data["minbatch_msignal"])))) , data["meanbatch_slices2_msignal"])) *(((((((((data["mean_abs_chgbatch_msignal"])-(data["maxtominbatch"])))<=(data["abs_maxbatch_msignal"])) *1.))+(data["stdbatch_slices2"])) /2.0)))))))* 2.0)) +
0.050000*np.tanh(np.minimum(((((((data["signal_shift_+1"])+(np.minimum(((data["abs_maxbatch_msignal"])) ,(( data["meanbatch_msignal"])))))) *(np.where(data["abs_avgbatch_msignal"] > -998,(((( np.cos(( data["abs_maxbatch_msignal"])))* 2.0)) * 2.0), data["meanbatch_msignal"]))))),(( np.where(data["abs_maxbatch_msignal"] > -998, data["meanbatch_msignal"], np.cos(( data["abs_maxbatch_msignal"])))))))+
0.050000*np.tanh(np.sin(( np.minimum(((data["meanbatch_msignal"])) ,(( np.minimum(((((( data["rangebatch_slices2_msignal"])<=(((np.sin(( np.sin(( data["abs_maxbatch"])))))* 2.0)))*1.))) ,(((-(( data["rangebatch_slices2"])))))))))))) +
0.050000*np.tanh(((((((data["mean_abs_chgbatch_slices2_msignal"])-(data["abs_maxbatch_msignal"])))* 2.0)) *(((((np.cos(( np.where(data["abs_avgbatch_slices2"] <= -998, data["mean_abs_chgbatch_slices2"], data["medianbatch_msignal"])))) -(np.where(data["abs_avgbatch_slices2"] <= -998,(((( np.cos(((( data["abs_maxbatch_slices2_msignal"])/ 2.0)))) -(data["medianbatch_msignal"])))* 2.0), data["medianbatch_msignal"])))) * 2.0)))) +
0.050000*np.tanh(((np.minimum(((data["medianbatch_msignal"])) ,(((( np.sin(( data["maxtominbatch_msignal"])))*(np.maximum(((data["abs_minbatch_slices2"])) ,(( np.where(((np.cos(( data["stdbatch_slices2"])))/ 2.0)<= -998, data["signal_shift_+1"], data["maxbatch_slices2"])))))))))) * 2.0)) +
0.050000*np.tanh(np.cos(( np.where(np.where(data["minbatch_slices2_msignal"] > -998, np.tanh(( data["signal_shift_+1"])) ,(((( np.cos(( data["maxtominbatch_msignal"])))/ 2.0)) *(data["abs_minbatch_msignal"])))> -998, data["abs_maxbatch_slices2_msignal"],(((data["signal"])>(data["abs_minbatch_msignal"])) *1.))))) +
0.050000*np.tanh(np.cos(( np.where(((data["meanbatch_slices2_msignal"])+(data["maxtominbatch_slices2_msignal"])) > -998,(( data["maxbatch_slices2_msignal"])* 2.0), np.sin(( np.where(data["rangebatch_msignal"] <= -998,(((( np.sin(( data["meanbatch_msignal"])))+(data["stdbatch_slices2"])))*(np.minimum(((data["maxbatch_msignal"])) ,(( data["minbatch_slices2_msignal"]))))), np.sin(( data["meanbatch_slices2_msignal"])))))))))+
0.050000*np.tanh(np.minimum(((np.where(np.cos(( data["maxbatch_slices2"])) > -998, np.cos(( data["maxbatch_msignal"])) , data["meanbatch_msignal"]))),(((( data["mean_abs_chgbatch_slices2_msignal"])*(((np.where(data["maxbatch_slices2"] > -998, data["medianbatch_msignal"],(((data["maxbatch_msignal"])<=(data["minbatch_slices2_msignal"])) *1.))) *(data["minbatch_slices2_msignal"])))))))) +
0.050000*np.tanh(np.minimum(((data["meanbatch_msignal"])) ,(( np.minimum(((data["meanbatch_msignal"])) ,(( data["signal"])))))))+
0.050000*np.tanh(((np.maximum(((data["signal"])) ,(( np.where(data["signal_shift_+1"] > -998, data["signal"], np.maximum(((((((np.maximum(((data["minbatch_msignal"])) ,(( data["abs_maxbatch_msignal"])))) *(np.cos(( np.sin(( data["abs_maxbatch_slices2"])))))))/ 2.0))),(( data["abs_maxbatch_slices2_msignal"])))))))) *(((np.cos(( np.sin(((0.0)))))) *(data["meanbatch_msignal"])))))+
0.050000*np.tanh(np.cos(((( np.where(np.sin(( data["abs_maxbatch_slices2"])) <= -998, data["minbatch"], data["stdbatch_msignal"])) * 2.0)))) +
0.050000*np.tanh(((((np.tanh(( np.where(( -(( data["medianbatch_slices2_msignal"])))<= -998, data["abs_avgbatch_slices2"], data["mean_abs_chgbatch_slices2_msignal"])))) *(( -(( np.where(data["minbatch_msignal"] > -998,(( data["mean_abs_chgbatch_slices2_msignal"])+(data["abs_avgbatch_slices2_msignal"])) , np.tanh(( data["meanbatch_slices2_msignal"])))))))))* 2.0)) +
0.050000*np.tanh(np.where(np.where(np.sin(( data["signal_shift_+1"])) > -998,(( np.where(((( data["maxbatch_slices2"])<=(np.where(data["maxtominbatch_slices2"] > -998, data["meanbatch_msignal"], np.sin(( data["meanbatch_msignal"])))))*1.) > -998, np.cos(( data["meanbatch_slices2_msignal"])) , data["stdbatch_slices2"])) * 2.0), data["minbatch"])<= -998, data["minbatch"], np.cos(((( data["stdbatch_msignal"])* 2.0)))))+
0.050000*np.tanh(np.cos(( np.maximum(((data["maxbatch_slices2_msignal"])) ,(( data["signal"])))))) +
0.050000*np.tanh(np.where(np.sin(( np.sin(( data["meanbatch_msignal"])))) <= -998,(( data["signal"])* 2.0),(( data["meanbatch_msignal"])*(( -(( np.where(np.where(data["abs_avgbatch_msignal"] <= -998, data["signal_shift_-1"],(((( data["abs_avgbatch_msignal"])*(( -(( np.where(np.tanh(( data["abs_avgbatch_msignal"])) > -998, data["mean_abs_chgbatch_msignal"], data["abs_avgbatch_msignal"])))))))* 2.0)) > -998, data["mean_abs_chgbatch_msignal"], data["medianbatch_slices2"])))))))) +
0.050000*np.tanh(np.minimum(((np.minimum(((np.sin(( np.sin(((-(( np.sin(((( np.cos(( data["minbatch_slices2"])))+(np.where(((data["maxtominbatch_slices2_msignal"])* 2.0)<= -998, data["signal_shift_+1"], np.sin(((( data["abs_avgbatch_msignal"])-(np.cos(((-(( data["meanbatch_slices2"]))))))))))))))))))))))),(( data["abs_maxbatch"]))))),(( np.sin(( np.sin(( data["maxtominbatch_slices2_msignal"])))))))) +
0.050000*np.tanh(np.sin(( data["signal"])))+
0.050000*np.tanh(((data["medianbatch_slices2_msignal"])*(np.tanh(( np.cos(( np.maximum(((data["maxbatch_msignal"])) ,(((( np.cos(((2.39422607421875000)))) +(np.tanh(( data["signal"])))))))))))))) +
0.050000*np.tanh(((np.minimum(((np.sin(( data["abs_maxbatch"])))) ,(( np.sin(((( np.maximum(((np.sin(((( np.minimum(((data["maxbatch_msignal"])) ,(( data["abs_maxbatch_slices2_msignal"])))) -(((np.sin(( data["stdbatch_slices2_msignal"])))/ 2.0))))))),(( data["meanbatch_slices2"])))) -(np.sin(( np.sin(( data["signal"])))))))))))) * 2.0)) +
0.050000*np.tanh(np.sin(( data["signal_shift_-1"])))+
0.050000*np.tanh(np.where(np.where(np.cos(( data["signal"])) <= -998, np.where(((( data["meanbatch_slices2"])>(((data["meanbatch_slices2_msignal"])/ 2.0)))*1.) > -998, data["minbatch"],(( data["medianbatch_slices2"])* 2.0)) , np.maximum(((( 7.32007217407226562))),(( data["rangebatch_msignal"])))) <= -998, data["medianbatch_slices2_msignal"],(( data["maxtominbatch_slices2_msignal"])*(np.sin(( np.maximum(((data["medianbatch_slices2"])) ,(( data["rangebatch_msignal"])))))))))+
0.050000*np.tanh(np.sin(((( data["maxtominbatch_msignal"])-(data["signal_shift_+1_msignal"])))))+
0.050000*np.tanh(np.where(data["maxtominbatch"] > -998, np.cos(( data["maxbatch_slices2_msignal"])) ,(-(( data["abs_minbatch_msignal"])))))+
0.050000*np.tanh(((data["signal_shift_+1"])*(((((( data["mean_abs_chgbatch_msignal"])-(np.tanh(((( data["minbatch_slices2_msignal"])/ 2.0)))))) <=(data["mean_abs_chgbatch_msignal"])) *1.))))+
0.050000*np.tanh(np.tanh(((( np.where(np.maximum(((((data["meanbatch_msignal"])* 2.0))),(( data["abs_avgbatch_slices2"])))> -998,(( np.cos(( data["maxbatch_msignal"])))* 2.0), np.sin(( np.sin(( data["rangebatch_slices2"])))))) * 2.0)))) +
0.050000*np.tanh(np.minimum(((data["medianbatch_msignal"])) ,(( data["signal_shift_-1"])))) +
0.050000*np.tanh(np.where(np.where(((( data["abs_avgbatch_slices2_msignal"])>(data["mean_abs_chgbatch_slices2_msignal"])) *1.) > -998, np.sin(( data["mean_abs_chgbatch_slices2_msignal"])) ,(((np.cos(((((data["signal"])<=(data["minbatch_slices2_msignal"])) *1.))))<=(data["mean_abs_chgbatch_slices2_msignal"])) *1.))> -998,(-(((( data["mean_abs_chgbatch_slices2_msignal"])*(data["meanbatch_msignal"]))))), data["meanbatch_slices2_msignal"])) +
0.050000*np.tanh(np.where(( -(( data["medianbatch_slices2_msignal"])))> -998, np.cos(( data["minbatch_msignal"])) , np.where(((data["signal_shift_-1"])/ 2.0)<= -998,(-(( np.cos(( data["meanbatch_slices2"]))))), np.tanh(((( np.where(np.sin(( data["maxbatch_msignal"])) > -998, np.cos(( data["minbatch_msignal"])) , np.where(data["stdbatch_slices2_msignal"] <= -998, data["meanbatch_msignal"], np.tanh(( data["meanbatch_msignal"])))))+(data["minbatch_msignal"])))))))+
0.050000*np.tanh(( -(((((( data["mean_abs_chgbatch_slices2_msignal"])*(data["rangebatch_slices2"])))* 2.0)))))+
0.050000*np.tanh(data["medianbatch_msignal"])+
0.050000*np.tanh(np.where(np.minimum(((data["stdbatch_slices2_msignal"])) ,(( np.where(np.where(data["maxtominbatch_msignal"] <= -998, np.tanh(( data["minbatch_slices2_msignal"])) , data["minbatch"])<= -998, data["meanbatch_msignal"], data["meanbatch_slices2_msignal"])))) <= -998, data["minbatch"], np.minimum(((( 6.63431692123413086))),(( data["minbatch_slices2_msignal"])))))+
0.050000*np.tanh(np.where(data["rangebatch_slices2"] <= -998, np.cos(( np.sin(( np.sin(( data["meanbatch_msignal"])))))) , data["medianbatch_slices2_msignal"])) +
0.050000*np.tanh(np.cos(( np.where(((( data["minbatch_msignal"])<=(data["medianbatch_msignal"])) *1.) <= -998,(((np.tanh(( data["signal_shift_+1"])))+(np.cos(( np.minimum(((data["signal_shift_+1"])) ,(( np.tanh(( np.sin(( data["medianbatch_slices2"])))))))))))/2.0),(( data["signal_shift_+1"])+(np.where(data["signal_shift_+1"] <= -998, np.minimum(((data["meanbatch_msignal"])) ,(( data["maxtominbatch_msignal"]))),(( data["medianbatch_msignal"])*(data["abs_minbatch_msignal"])))))))))+
0.050000*np.tanh(((np.minimum(((np.where(np.sin(((( np.sin(((( data["medianbatch_msignal"])/ 2.0)))) * 2.0)))<= -998,(((np.maximum(((data["minbatch_slices2"])) ,(( np.cos(( data["maxbatch_slices2_msignal"])))))) +(data["abs_avgbatch_slices2_msignal"])) /2.0),(((( data["abs_minbatch_slices2"])-(( -(( data["signal_shift_+1"])))))) / 2.0)))) ,(( np.cos(( np.cos(( data["mean_abs_chgbatch_msignal"])))))))) * 2.0)) +
0.050000*np.tanh(np.minimum(((((np.cos(( data["stdbatch_slices2_msignal"])))*(data["signal_shift_-1"])))) ,(( data["signal_shift_-1"])))) +
0.050000*np.tanh(( -(((( data["abs_minbatch_slices2_msignal"])*(data["maxtominbatch_slices2"])))))) +
0.050000*np.tanh(np.cos(((( data["signal_shift_-1"])* 2.0)))) +
0.050000*np.tanh(np.cos(( np.where(data["abs_avgbatch_slices2"] > -998, data["maxbatch_slices2_msignal"], data["medianbatch_msignal"])))) +
0.050000*np.tanh(np.minimum(((data["meanbatch_msignal"])) ,(((( np.sin(( np.where(((( data["minbatch_slices2"])<=(((data["abs_maxbatch"])* 2.0)))*1.) <= -998, np.where(data["meanbatch_slices2_msignal"] <= -998,(0.25848990678787231), np.sin(( data["signal"]))), np.sin(( np.where(np.sin(( data["minbatch_msignal"])) <= -998, data["maxbatch_slices2_msignal"], data["abs_maxbatch"])))))))* 2.0)))))+
0.050000*np.tanh(np.minimum(((((np.where(data["signal_shift_-1"] <= -998,(( data["signal_shift_+1"])-(((((np.sin(( np.tanh(( data["medianbatch_slices2_msignal"])))))/ 2.0)) -(((data["medianbatch_msignal"])+(data["abs_minbatch_msignal"])))))) ,(( np.cos(( data["signal_shift_+1"])))*(np.sin(( data["signal_shift_-1"])))))) +(data["signal_shift_-1"])))) ,(( data["rangebatch_slices2"])))) +
0.050000*np.tanh(np.where(data["abs_maxbatch_slices2_msignal"] <= -998, data["minbatch_msignal"], np.minimum(((data["signal_shift_-1"])) ,(( np.tanh(( data["abs_minbatch_slices2_msignal"])))))))+
0.050000*np.tanh(((((((np.where(data["stdbatch_slices2_msignal"] > -998, data["signal_shift_-1"],(( data["rangebatch_slices2_msignal"])* 2.0)))* 2.0)) * 2.0)) * 2.0)) +
0.050000*np.tanh(((np.where(data["stdbatch_slices2_msignal"] <= -998, np.cos(((( np.sin(( data["minbatch"])))* 2.0))), data["medianbatch_slices2"])) *(np.cos(( data["stdbatch_slices2_msignal"])))))+
0.050000*np.tanh(np.sin(( np.minimum(((np.minimum(((data["maxtominbatch_msignal"])) ,(( data["mean_abs_chgbatch_slices2"]))))),(((-(( np.where(data["signal_shift_-1"] <= -998,(( data["rangebatch_msignal"])* 2.0), np.tanh(( data["abs_avgbatch_msignal"])))))))))))) +
0.050000*np.tanh(np.where(data["meanbatch_msignal"] > -998, data["minbatch_slices2"],(((np.cos(( data["abs_minbatch_slices2"])))+(((((data["maxtominbatch_msignal"])+(data["maxbatch_msignal"])))-(data["signal_shift_-1"])))) /2.0)))+
0.050000*np.tanh(( -(((((((((((((( data["signal_shift_-1"])-(data["abs_maxbatch_slices2_msignal"])))/ 2.0)) +(data["rangebatch_msignal"])))*(np.cos(((( data["abs_maxbatch_slices2_msignal"])-(np.where(data["abs_maxbatch_slices2_msignal"] > -998, data["medianbatch_slices2"], np.cos(((( data["medianbatch_msignal"])-(data["maxbatch_slices2_msignal"])))))))))))) / 2.0)) * 2.0)))))+
0.050000*np.tanh(((np.tanh(( data["signal"])))*(np.where(data["signal_shift_-1"] <= -998, data["abs_minbatch_msignal"], data["abs_maxbatch_slices2_msignal"])))) +
0.050000*np.tanh(np.minimum(((np.tanh(( np.sin(( np.sin(((( data["signal_shift_-1"])-(((( np.maximum(((data["abs_avgbatch_slices2_msignal"])) ,(( np.sin(( np.sin(( data["abs_avgbatch_slices2_msignal"])))))))) +(np.where(data["abs_avgbatch_slices2_msignal"] <= -998, data["signal_shift_-1"], data["abs_avgbatch_slices2_msignal"])))/2.0))))))))))),(((((( data["signal_shift_-1"])/ 2.0)) +(data["signal_shift_-1"])))))) +
0.050000*np.tanh(((data["minbatch_slices2_msignal"])*(np.sin(((((( np.maximum(((data["signal"])) ,(((((( 4.24774360656738281)) <=(((((((( data["signal_shift_+1"])* 2.0)) *(np.cos(( data["rangebatch_msignal"])))))<=(data["signal_shift_+1"])) *1.))) *1.))))) * 2.0)) +(((data["signal_shift_-1"])/ 2.0)))))))) +
0.050000*np.tanh(np.sin(( np.where(data["maxtominbatch_slices2_msignal"] <= -998, np.where(data["abs_maxbatch"] <= -998,(9.0), np.where(data["maxtominbatch_slices2_msignal"] <= -998, data["signal_shift_-1"], data["rangebatch_slices2"])) , np.sin(( np.where(data["medianbatch_slices2"] <= -998, np.where(np.tanh(( data["signal_shift_+1"])) <= -998, np.sin(( np.cos(( np.cos(((((data["stdbatch_slices2"])+(data["medianbatch_slices2_msignal"])) /2.0))))))), data["abs_avgbatch_msignal"]), data["abs_maxbatch"])))))))+
0.050000*np.tanh(np.cos(( data["maxbatch_msignal"])))+
0.050000*np.tanh(np.minimum(((np.where(np.sin(( np.tanh(((( data["signal"])+(np.minimum(((data["abs_maxbatch"])) ,(( data["abs_avgbatch_slices2_msignal"])))))))))> -998, data["signal"],(( data["abs_minbatch_slices2_msignal"])*(data["stdbatch_slices2_msignal"]))))),(((( data["signal_shift_-1_msignal"])*(data["stdbatch_slices2_msignal"])))))) +
0.050000*np.tanh(((data["signal_shift_+1_msignal"])*(((np.cos(( np.where(data["stdbatch_msignal"] > -998, data["minbatch_msignal"], data["stdbatch_msignal"])))) -(np.maximum(((np.minimum(((np.minimum(((np.maximum(((((data["signal_shift_+1"])-(data["medianbatch_msignal"])))) ,(((( data["minbatch_msignal"])*(data["minbatch_msignal"]))))))),(( data["maxtominbatch_msignal"]))))),(( data["signal_shift_+1_msignal"]))))),(((( data["minbatch_msignal"])*(np.tanh(( data["stdbatch_msignal"])))))))))))) +
0.050000*np.tanh(np.minimum(((data["meanbatch_slices2_msignal"])) ,(( np.cos(( data["meanbatch_slices2_msignal"])))))) +
0.050000*np.tanh(data["meanbatch_msignal"])+
0.050000*np.tanh(((data["medianbatch_msignal"])-(data["abs_minbatch_slices2"])))+
0.050000*np.tanh(((np.sin(( np.sin(( data["signal_shift_-1"])))))+(np.where(np.cos(( data["rangebatch_slices2"])) > -998, np.sin(( data["abs_maxbatch_slices2"])) ,(( np.sin(( data["maxtominbatch_msignal"])))*(( 1.0)))))))+
0.050000*np.tanh(((data["meanbatch_slices2"])*(data["meanbatch_slices2_msignal"])))+
0.050000*np.tanh(( -(( np.maximum(((data["rangebatch_msignal"])) ,(( np.sin(((7.61515092849731445)))))))))) +
0.050000*np.tanh(np.sin(( np.where(((( np.sin(( data["abs_minbatch_msignal"])))+(( 0.53171408176422119)))/2.0)> -998, data["maxtominbatch_slices2_msignal"],(((((((np.where(data["maxtominbatch_slices2_msignal"] <= -998, data["abs_maxbatch_slices2"], np.cos(( data["medianbatch_msignal"])))) * 2.0)) +(np.cos(( data["abs_maxbatch_slices2"])))) /2.0)) *(data["abs_maxbatch_slices2"])))))) +
0.050000*np.tanh(((data["stdbatch_msignal"])*(((np.minimum(((data["signal_shift_-1"])) ,(((( data["signal_shift_+1"])-(((data["signal_shift_-1"])-(data["signal_shift_-1"])))))))) -(data["stdbatch_slices2"])))))+
0.050000*np.tanh(np.sin(( np.sin(( np.where(data["abs_avgbatch_slices2_msignal"] > -998, data["abs_maxbatch_slices2"],(((data["rangebatch_slices2"])+(data["meanbatch_slices2_msignal"])) /2.0)))))))+
0.050000*np.tanh(np.where(np.cos(( data["minbatch_msignal"])) <= -998, data["minbatch_msignal"],(((( data["abs_maxbatch_slices2_msignal"])-(((data["maxtominbatch_slices2"])-(data["abs_maxbatch_slices2_msignal"])))))*(np.cos(( data["minbatch_msignal"])))))) +
0.050000*np.tanh(((((data["signal_shift_-1"])* 2.0)) *(np.where(data["abs_maxbatch"] <= -998,(( data["medianbatch_msignal"])-(np.sin(( data["maxtominbatch"])))) ,(( np.tanh(( data["medianbatch_msignal"])))/ 2.0)))))+
0.050000*np.tanh(np.minimum(((((((np.cos(( data["abs_maxbatch_msignal"])))/ 2.0)) *(np.where(data["abs_avgbatch_slices2_msignal"] > -998, data["rangebatch_slices2_msignal"], np.sin(((((((( data["maxtominbatch_slices2"])>(data["mean_abs_chgbatch_slices2_msignal"])) *1.))<=(data["maxbatch_slices2"])) *1.)))))))),(( np.where(data["abs_avgbatch_slices2_msignal"] > -998, data["rangebatch_slices2_msignal"], data["abs_maxbatch_msignal"])))))+
0.050000*np.tanh(np.minimum(((((((( data["maxtominbatch"])+(np.cos(((( data["abs_maxbatch_msignal"])+(data["signal_shift_+1_msignal"])))))) /2.0)) *(np.where(((np.sin(( data["signal_shift_+1"])))*(data["stdbatch_slices2_msignal"])) > -998, data["abs_minbatch_slices2_msignal"], data["mean_abs_chgbatch_slices2"]))))),(( data["abs_avgbatch_slices2_msignal"])))) +
0.050000*np.tanh(((data["abs_maxbatch"])*(((np.cos(( data["medianbatch_msignal"])))*(np.tanh(( np.where(np.minimum(((data["signal_shift_-1"])) ,(((((8.06406688690185547)) *(((data["maxbatch_slices2"])*(np.tanh(( np.where(data["maxbatch_msignal"] <= -998, np.cos(((8.0))),(((8.06406688690185547)) *(data["mean_abs_chgbatch_slices2_msignal"])))))))))))) <= -998, data["abs_maxbatch_slices2_msignal"], np.cos(( data["maxbatch_slices2"])))))))))) +
0.050000*np.tanh(((np.where(((( np.maximum(((data["abs_maxbatch_msignal"])) ,(( data["abs_maxbatch_msignal"])))) +(np.sin(( np.tanh(( np.maximum(((((data["abs_maxbatch_msignal"])+(data["abs_maxbatch_msignal"])))) ,(( np.minimum(((data["abs_avgbatch_msignal"])) ,(((-(( data["abs_avgbatch_slices2_msignal"])))))))))))))))/2.0)> -998, np.sin(( data["abs_maxbatch_slices2"])) , np.tanh(( np.tanh(( data["abs_maxbatch_slices2_msignal"])))))) * 2.0)) +
0.050000*np.tanh(np.where(data["stdbatch_slices2"] > -998, data["meanbatch_msignal"],(((((data["meanbatch_msignal"])*(data["meanbatch_msignal"])))<=(np.sin(( data["meanbatch_msignal"])))) *1.))) +
0.050000*np.tanh(((((data["signal"])*(data["meanbatch_msignal"])))-(((((( data["meanbatch_msignal"])*(data["signal"])))>(( -(((((( data["signal"])*(data["meanbatch_msignal"])))-(((( data["signal"])>(data["medianbatch_msignal"])) *1.))))))))*1.))))+
0.050000*np.tanh(np.where(data["signal"] <= -998, data["signal"], data["signal"])) +
0.050000*np.tanh(((data["signal_shift_-1_msignal"])*(np.sin(((( np.maximum(((data["stdbatch_msignal"])) ,(( np.minimum(((((((data["stdbatch_msignal"])-(((((data["stdbatch_msignal"])* 2.0)) * 2.0)))) -(data["abs_maxbatch_slices2"])))) ,(( np.minimum(((data["stdbatch_msignal"])) ,(((((( data["signal_shift_-1_msignal"])*(np.sin(((( data["stdbatch_msignal"])* 2.0)))))) *(data["stdbatch_msignal"])))))))))))) * 2.0)))))) +
0.050000*np.tanh(data["meanbatch_msignal"])+
0.050000*np.tanh(np.sin(( data["medianbatch_slices2"])))+
0.050000*np.tanh(np.where(data["abs_maxbatch_slices2_msignal"] <= -998,(((np.where(data["signal_shift_-1"] <= -998, data["abs_maxbatch_slices2_msignal"], data["signal_shift_-1"])) +(data["maxbatch_msignal"])) /2.0),(( data["meanbatch_msignal"])*(np.where(np.sin(( data["abs_avgbatch_msignal"])) <= -998, data["abs_maxbatch_slices2_msignal"],(( data["signal_shift_-1"])/ 2.0)))))) +
0.050000*np.tanh(((( np.where(data["abs_avgbatch_msignal"] <= -998, data["abs_minbatch_slices2"], np.sin(((( data["signal_shift_-1"])-(data["abs_avgbatch_slices2_msignal"])))))) +(data["meanbatch_msignal"])) /2.0)) +
0.050000*np.tanh(np.where(np.sin(( np.where(((np.cos(( np.cos(( data["maxtominbatch_slices2_msignal"])))))*(data["minbatch_msignal"])) > -998, data["abs_avgbatch_slices2"], data["mean_abs_chgbatch_slices2_msignal"])))<= -998, np.cos(((-(( data["stdbatch_msignal"]))))), data["maxtominbatch_slices2_msignal"])) +
0.050000*np.tanh(((( np.maximum(((data["maxbatch_slices2"])) ,(( data["mean_abs_chgbatch_slices2"])))) +(np.cos(((-(( np.where(np.maximum(((data["meanbatch_msignal"])) ,(( np.sin(((9.0)))))) > -998, data["signal_shift_-1"],(-(( data["signal_shift_+1"])))))))))))/2.0)) +
0.050000*np.tanh(np.minimum(((np.where(((np.where(data["signal_shift_-1_msignal"] <= -998,(( data["stdbatch_slices2_msignal"])*(((data["signal"])*(np.tanh(( data["signal"])))))) , data["abs_avgbatch_slices2_msignal"])) +(((data["signal"])*(data["stdbatch_msignal"])))) <= -998,(((( data["signal_shift_-1_msignal"])*(data["stdbatch_msignal"])))*(data["signal_shift_-1_msignal"])) ,(( data["signal_shift_-1_msignal"])*(data["stdbatch_slices2_msignal"]))))),(( data["signal"])))) +
0.050000*np.tanh(np.minimum(((data["signal_shift_-1"])) ,(( data["medianbatch_msignal"])))) +
0.050000*np.tanh(np.where(data["medianbatch_msignal"] > -998, data["meanbatch_msignal"], data["meanbatch_msignal"])) +
0.050000*np.tanh(np.sin(((( data["mean_abs_chgbatch_slices2_msignal"])*(((data["maxbatch_slices2_msignal"])+(((data["stdbatch_msignal"])*(np.minimum(((data["maxbatch_msignal"])) ,(((( data["mean_abs_chgbatch_slices2_msignal"])/ 2.0)))))))))))))+
0.050000*np.tanh(((((np.sin(( data["signal_shift_+1"])))* 2.0)) *(data["medianbatch_msignal"])))+
0.050000*np.tanh(np.where(np.where(np.minimum(((data["abs_avgbatch_slices2_msignal"])) ,(((-(( data["abs_avgbatch_slices2"])))))) <= -998, data["maxbatch_slices2_msignal"], np.sin(( data["maxbatch_slices2_msignal"])))<= -998,(((( data["medianbatch_slices2_msignal"])* 2.0)) -(data["mean_abs_chgbatch_slices2_msignal"])) ,(( np.cos(((((((5.27607488632202148)) -(((data["maxtominbatch"])*(np.sin(( data["maxbatch_slices2_msignal"])))))))* 2.0)))) *(data["abs_avgbatch_slices2"])))) +
0.050000*np.tanh(np.sin(( np.maximum(((data["maxbatch_slices2"])) ,(( np.maximum(((np.maximum(((((( data["maxtominbatch"])<=(data["minbatch_slices2"])) *1.))) ,(( np.where(((data["abs_maxbatch_slices2_msignal"])+(((data["minbatch"])*(data["abs_maxbatch_slices2"])))) > -998, data["abs_maxbatch_slices2"], data["abs_avgbatch_msignal"])))))) ,(( data["minbatch_slices2_msignal"])))))))))+
0.050000*np.tanh(np.where(data["maxbatch_msignal"] <= -998,(10.0), data["signal"])) +
0.050000*np.tanh(np.cos(((( data["stdbatch_msignal"])-(((data["rangebatch_slices2"])-(((data["abs_minbatch_slices2_msignal"])-(((( np.minimum(((data["stdbatch_slices2"])) ,(( np.where(((((np.where(data["rangebatch_slices2"] > -998, data["rangebatch_msignal"],(( data["abs_minbatch_slices2"])+(data["abs_minbatch_slices2_msignal"])))) *(data["maxtominbatch"])))+(data["mean_abs_chgbatch_slices2_msignal"])) > -998, data["signal"], data["maxtominbatch"])))))>(data["rangebatch_slices2"])) *1.))))))))))+
0.050000*np.tanh(np.minimum(((((np.minimum(((data["medianbatch_slices2"])) ,(((( np.cos(((( np.minimum(((((((data["medianbatch_slices2"])* 2.0)) / 2.0))),(( data["medianbatch_slices2"])))) * 2.0)))) * 2.0)))))* 2.0))),(((( np.cos(((( data["medianbatch_slices2"])* 2.0)))) * 2.0)))))+
0.050000*np.tanh(((data["minbatch"])*(np.sin(((( np.maximum(((data["minbatch"])) ,(( data["rangebatch_slices2"])))) +(np.cos(((((data["maxtominbatch"])<=(np.sin(((( np.cos(((((7.44715881347656250)) -(np.cos(( np.cos(( data["medianbatch_slices2_msignal"])))))))))+(data["minbatch"])))))) *1.))))))))))+
0.050000*np.tanh(np.where(data["stdbatch_slices2_msignal"] <= -998,(( np.maximum(((data["stdbatch_slices2_msignal"])) ,(( np.cos(( np.tanh(( np.tanh(( data["abs_maxbatch_msignal"])))))))))) / 2.0), np.cos(( np.where(np.where(data["mean_abs_chgbatch_msignal"] <= -998,(( np.sin(( data["stdbatch_slices2_msignal"])))* 2.0), np.cos(( data["minbatch_msignal"])))<= -998, data["maxtominbatch_slices2"], data["stdbatch_slices2_msignal"])))))+
0.050000*np.tanh(np.sin(( data["abs_maxbatch"])))+
0.050000*np.tanh(((((( data["minbatch_msignal"])* 2.0)) <=(data["abs_minbatch_slices2"])) *1.))+
0.050000*np.tanh(np.where(np.where(( -(((((((data["maxbatch_slices2"])+(data["meanbatch_slices2_msignal"])) /2.0)) * 2.0)))) > -998, data["maxbatch_msignal"], np.minimum(((np.sin(((-(( data["rangebatch_msignal"]))))))),(( data["maxbatch_slices2"])))) > -998, np.sin(( data["abs_maxbatch_slices2"])) , np.minimum(((data["signal_shift_+1_msignal"])) ,(( np.sin(( data["abs_minbatch_slices2_msignal"])))))))+
0.050000*np.tanh(np.minimum(((((((data["maxbatch_slices2_msignal"])*(((data["abs_avgbatch_slices2_msignal"])+(((( np.tanh(((8.0)))) <=(data["signal_shift_+1"])) *1.))))))/ 2.0))),(((( np.cos(( data["maxbatch_slices2_msignal"])))/ 2.0)))))+
0.050000*np.tanh(((np.where(np.sin(( data["abs_maxbatch"])) > -998,(((( data["abs_maxbatch_slices2_msignal"])* 2.0)) * 2.0),(((((data["meanbatch_msignal"])+(((np.minimum(((np.sin(( data["abs_avgbatch_slices2_msignal"])))) ,(( np.where(np.tanh(( data["minbatch"])) > -998, data["signal_shift_+1"], data["abs_minbatch_slices2"])))))* 2.0)))) <=(data["abs_minbatch_slices2"])) *1.))) / 2.0)) +
0.050000*np.tanh(( -(((( np.where(((np.sin(((((data["abs_maxbatch"])<=(data["abs_minbatch_slices2"])) *1.))))*(data["abs_minbatch_slices2"])) <= -998,(-(( data["maxbatch_msignal"]))),(-(( np.cos(( data["abs_maxbatch_slices2"])))))))* 2.0)))))+
0.050000*np.tanh(np.minimum(((np.where(np.where(data["meanbatch_msignal"] <= -998,(((data["medianbatch_slices2_msignal"])+(data["abs_avgbatch_slices2"])) /2.0),(( data["abs_avgbatch_msignal"])*(np.minimum(((data["signal_shift_+1"])) ,(( data["abs_avgbatch_slices2"])))))) > -998, data["signal_shift_+1"],(((data["medianbatch_slices2_msignal"])+(data["abs_avgbatch_slices2"])) /2.0)))) ,(( data["medianbatch_msignal"])))) +
0.050000*np.tanh(data["stdbatch_msignal"])+
0.050000*np.tanh(((((((data["stdbatch_slices2_msignal"])>(np.maximum(((((( data["stdbatch_slices2_msignal"])+(np.cos(( np.minimum(((((((((data["abs_avgbatch_slices2_msignal"])/ 2.0)) -(((data["mean_abs_chgbatch_slices2_msignal"])-(data["meanbatch_msignal"])))))/ 2.0))),(( data["minbatch_slices2_msignal"])))))))/2.0))),(( data["abs_maxbatch"])))))*1.))+(np.cos(( np.minimum(((((((data["abs_maxbatch"])-(data["mean_abs_chgbatch_msignal"])))/ 2.0))),(( data["minbatch_slices2_msignal"])))))))/2.0)) +
0.050000*np.tanh(((np.where(((((( data["medianbatch_slices2"])+(data["abs_maxbatch_msignal"])))<=(data["stdbatch_slices2_msignal"])) *1.) <= -998,(2.51731467247009277),(( data["medianbatch_slices2"])*(np.cos(((( data["abs_maxbatch_msignal"])+(np.where(data["signal_shift_+1_msignal"] <= -998, data["medianbatch_msignal"], np.sin(( data["medianbatch_slices2"])))))))))))*(data["abs_maxbatch_msignal"])))+
0.050000*np.tanh(np.sin(( np.sin(( data["abs_minbatch_slices2"])))))+
0.050000*np.tanh(np.where(( 7.47483921051025391)> -998, np.cos(( data["maxbatch_slices2_msignal"])) , data["medianbatch_slices2"])) +
0.050000*np.tanh(np.sin(((( data["signal_shift_-1_msignal"])*(((( np.sin(( np.sin(( data["maxbatch_msignal"])))))+(((( data["meanbatch_slices2_msignal"])>(np.maximum(((data["stdbatch_slices2"])) ,(((-(((-(((((( 0.0)) >(( 0.0)))*1.))))))))))))*1.))) /2.0)))))) +
0.050000*np.tanh(((((((((data["medianbatch_slices2_msignal"])+(( -(( data["meanbatch_slices2_msignal"])))))/2.0)) * 2.0)) <=(np.sin(( np.sin(( data["signal"])))))) *1.))+
0.050000*np.tanh(np.cos(( np.maximum(((np.where(((( data["abs_maxbatch_msignal"])<=(((data["signal_shift_-1_msignal"])*(data["medianbatch_msignal"])))) *1.) > -998, data["signal_shift_-1_msignal"], data["stdbatch_slices2"]))),(( np.where(((data["signal_shift_-1_msignal"])*(data["mean_abs_chgbatch_slices2_msignal"])) > -998, data["abs_maxbatch_msignal"],(((data["maxtominbatch_slices2"])<=(data["maxtominbatch_msignal"])) *1.))))))))+
0.050000*np.tanh(np.where(( 5.0)> -998,(( data["stdbatch_msignal"])*(data["signal_shift_+1_msignal"])) , np.cos(( np.minimum(((data["signal_shift_+1_msignal"])) ,(( np.where(np.tanh(((( data["medianbatch_slices2_msignal"])* 2.0)))<= -998, data["abs_minbatch_slices2_msignal"], np.where(data["stdbatch_slices2"] > -998,(( data["stdbatch_msignal"])/ 2.0), np.maximum(((data["meanbatch_msignal"])) ,(((( data["minbatch_slices2_msignal"])/ 2.0)))))))))))))+
0.050000*np.tanh(((data["signal_shift_-1"])* 2.0)) +
0.050000*np.tanh(np.where(((((( data["meanbatch_msignal"])/ 2.0)) <=(((( data["maxbatch_msignal"])+(((data["maxbatch_slices2"])/ 2.0)))/2.0)))*1.) > -998, data["abs_avgbatch_msignal"], data["maxbatch_slices2_msignal"])) +
0.050000*np.tanh(np.minimum(((data["medianbatch_msignal"])) ,(((( data["signal"])+(np.minimum(((data["stdbatch_slices2_msignal"])) ,(( np.sin(( np.where(data["signal"] <= -998,(( data["medianbatch_msignal"])+(data["medianbatch_msignal"])) , np.sin(( np.where(data["meanbatch_msignal"] > -998, data["maxtominbatch_slices2_msignal"], np.where(data["abs_maxbatch_slices2"] > -998, data["abs_maxbatch_slices2"], data["abs_minbatch_slices2"])))))))))))))))) +
0.050000*np.tanh(((np.cos(((((( data["meanbatch_slices2_msignal"])* 2.0)) +(((( data["signal_shift_-1_msignal"])>(np.sin(((((data["medianbatch_slices2"])>(np.where(data["medianbatch_slices2_msignal"] <= -998, data["signal"],(((((((data["meanbatch_slices2_msignal"])* 2.0)) * 2.0)) >(data["signal_shift_+1_msignal"])) *1.))))*1.))))) *1.))))))* 2.0)) +
0.050000*np.tanh(data["meanbatch_slices2"]))
def GP_class_7(self,data):
return self.Output(-2.939938 +
0.050000*np.tanh(np.where(((data["signal_shift_-1"])*(np.tanh(((((np.sin(( data["maxtominbatch_slices2"])))+(((data["abs_avgbatch_slices2_msignal"])-(((( np.sin(( data["maxtominbatch_slices2"])))+(((data["abs_avgbatch_slices2_msignal"])-(data["abs_maxbatch_msignal"])))) /2.0)))))/2.0)))))<= -998, data["meanbatch_slices2"], data["signal_shift_-1"])) +
0.050000*np.tanh(np.minimum(((np.where(((data["mean_abs_chgbatch_slices2"])*(data["maxbatch_slices2_msignal"])) > -998, data["medianbatch_slices2"], data["medianbatch_slices2_msignal"]))),(((( np.maximum(((data["mean_abs_chgbatch_slices2"])) ,(( data["signal_shift_+1"])))) +(((data["stdbatch_slices2"])+(data["medianbatch_slices2"])))))))) +
0.050000*np.tanh(((((( data["signal"])+(((data["meanbatch_slices2_msignal"])*(((((((data["signal_shift_+1"])-(((( data["minbatch_slices2_msignal"])+(data["meanbatch_msignal"])) /2.0)))) -(np.where(((np.cos(( data["meanbatch_slices2"])))-(data["maxbatch_slices2"])) <= -998, data["signal_shift_+1"], data["meanbatch_slices2_msignal"])))) -(data["maxbatch_slices2"])))))) /2.0)) * 2.0)) +
0.050000*np.tanh(((((((data["abs_maxbatch_msignal"])*(np.sin(( data["abs_maxbatch_slices2"])))))-(( 3.22629404067993164)))) -(np.maximum(((((( -(( data["abs_maxbatch_msignal"])))) +(((((data["mean_abs_chgbatch_slices2"])*(data["medianbatch_slices2"])))-(data["abs_maxbatch_slices2_msignal"])))))) ,(( np.where(data["rangebatch_msignal"] <= -998, data["medianbatch_slices2_msignal"], np.minimum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(( data["abs_maxbatch_msignal"])))))))))) +
0.050000*np.tanh(((((data["meanbatch_slices2"])+(data["signal"])))+(((data["abs_avgbatch_slices2_msignal"])*(np.where(((data["maxbatch_slices2"])/ 2.0)> -998, data["signal"], data["stdbatch_msignal"])))))) +
0.050000*np.tanh(((data["signal"])-(((( data["meanbatch_slices2_msignal"])+(data["stdbatch_slices2"])) /2.0)))) +
0.050000*np.tanh(((np.minimum(((((data["stdbatch_slices2"])*(data["medianbatch_slices2"])))) ,(( data["mean_abs_chgbatch_slices2_msignal"])))) +(((data["maxtominbatch"])+(( -(((( np.where(data["signal_shift_+1"] > -998, data["stdbatch_slices2_msignal"], np.where(( -(( data["signal"])))<= -998, data["signal"],(( data["signal_shift_-1_msignal"])* 2.0)))) *(data["maxbatch_msignal"])))))))))) +
0.050000*np.tanh(np.where(data["abs_maxbatch_slices2"] > -998, data["signal_shift_+1"],(((data["medianbatch_slices2"])>(((( data["signal_shift_-1"])>(data["signal_shift_+1_msignal"])) *1.))) *1.))) +
0.050000*np.tanh(np.where(data["signal"] <= -998, np.where(data["signal"] <= -998, data["meanbatch_slices2"], np.where(data["meanbatch_slices2"] <= -998, data["mean_abs_chgbatch_slices2"], data["abs_minbatch_msignal"])) , data["signal"])) +
0.050000*np.tanh(np.minimum(((np.minimum(((data["abs_maxbatch_slices2"])) ,(( np.where(( -(( data["abs_avgbatch_slices2_msignal"])))> -998, data["signal_shift_+1"], np.minimum(((data["medianbatch_slices2"])) ,(( np.minimum(((data["stdbatch_slices2"])) ,(( data["medianbatch_slices2"])))))))))))) ,(( data["medianbatch_slices2"])))) +
0.050000*np.tanh(((data["signal"])-(((( np.where(((((( data["signal_shift_+1"])-(( -(( data["signal_shift_+1"])))))) <=(np.cos(( np.cos(( data["signal"])))))) *1.) <= -998, data["signal_shift_+1_msignal"],(( data["signal_shift_+1"])/ 2.0)))<=(((data["signal_shift_+1"])/ 2.0)))*1.))))+
0.050000*np.tanh(( -(( np.where(data["signal_shift_+1"] > -998, data["stdbatch_msignal"], data["signal_shift_+1"])))))+
0.050000*np.tanh(((( data["maxbatch_slices2"])+(((np.where(((data["medianbatch_slices2"])/ 2.0)<= -998, np.cos(((((data["abs_maxbatch"])+(data["maxtominbatch_msignal"])) /2.0))), data["abs_maxbatch"])) -(( 12.97748088836669922)))))/2.0)) +
0.050000*np.tanh(np.minimum(((np.sin(( data["maxbatch_slices2"])))) ,(((( np.cos(( np.where(data["medianbatch_slices2_msignal"] > -998, data["maxbatch_slices2"], data["meanbatch_slices2_msignal"])))) -(data["abs_minbatch_slices2_msignal"])))))) +
0.050000*np.tanh(((data["signal"])+(np.minimum(((((data["abs_maxbatch_slices2"])*(data["meanbatch_slices2_msignal"])))) ,(( data["maxtominbatch"])))))) +
0.050000*np.tanh(((data["medianbatch_slices2"])* 2.0)) +
0.050000*np.tanh(((data["abs_avgbatch_slices2_msignal"])*(( -(( np.where(np.where(data["stdbatch_slices2_msignal"] > -998, data["minbatch_slices2_msignal"],(( np.tanh(( data["abs_avgbatch_slices2_msignal"])))/ 2.0)) <= -998, data["stdbatch_msignal"], data["stdbatch_slices2_msignal"])))))))+
0.050000*np.tanh(((((data["abs_maxbatch_slices2"])*(data["medianbatch_slices2"])))+(np.minimum(((np.minimum(((np.minimum(((((data["meanbatch_slices2"])*(data["abs_avgbatch_msignal"])))) ,(( np.minimum(((data["meanbatch_msignal"])) ,(((( np.tanh(( data["signal"])))* 2.0))))))))),(( np.minimum(((np.cos(((( data["rangebatch_msignal"])*(data["abs_maxbatch_slices2"])))))) ,(( data["meanbatch_slices2"])))))))) ,(( data["meanbatch_slices2"])))))) +
0.050000*np.tanh(((data["abs_avgbatch_slices2_msignal"])*(((data["signal"])+(np.minimum(((((( np.sin(( data["maxbatch_msignal"])))<=(data["signal"])) *1.))) ,(( np.sin(((( np.tanh(((( data["medianbatch_slices2"])/ 2.0)))) *(((( data["medianbatch_slices2"])>(((( data["minbatch_slices2_msignal"])+(data["medianbatch_slices2"])) /2.0)))*1.))))))))))))) +
0.050000*np.tanh(np.where(data["abs_minbatch_slices2"] <= -998, np.where(data["abs_avgbatch_slices2"] <= -998,(-(( data["mean_abs_chgbatch_slices2_msignal"]))),(( data["rangebatch_slices2"])* 2.0)) ,(-(( data["mean_abs_chgbatch_slices2_msignal"])))))+
0.050000*np.tanh(((((data["minbatch_slices2"])*(np.cos(((( data["signal"])/ 2.0)))))) +(np.cos(( data["meanbatch_slices2_msignal"])))))+
0.050000*np.tanh(((data["medianbatch_slices2_msignal"])-(((((( data["abs_minbatch_msignal"])-(np.tanh(( data["maxtominbatch_slices2_msignal"])))))+(((((data["meanbatch_msignal"])* 2.0)) *(np.minimum(((data["abs_avgbatch_msignal"])) ,(( np.minimum(((data["maxbatch_slices2_msignal"])) ,(( data["abs_avgbatch_msignal"])))))))))) /2.0)))) +
0.050000*np.tanh(((((((data["medianbatch_slices2_msignal"])* 2.0)) -(((data["mean_abs_chgbatch_msignal"])*(( 10.36975574493408203)))))) -(((data["mean_abs_chgbatch_msignal"])*(data["abs_avgbatch_msignal"])))))+
0.050000*np.tanh(((np.sin(((( np.where(data["stdbatch_slices2_msignal"] > -998, np.sin(( data["abs_avgbatch_msignal"])) ,(( data["maxbatch_slices2_msignal"])*(np.sin(( data["signal_shift_-1_msignal"])))))) * 2.0)))) * 2.0)) +
0.050000*np.tanh(((((data["meanbatch_slices2"])*(np.sin(( np.where(np.where(data["medianbatch_slices2_msignal"] > -998, data["abs_maxbatch_slices2"], np.maximum(((np.tanh(( data["signal"])))) ,(( data["abs_maxbatch_slices2"])))) > -998,(-(( data["minbatch_msignal"]))),(( data["minbatch_msignal"])* 2.0)))))))-(((data["medianbatch_slices2_msignal"])*(data["meanbatch_slices2_msignal"])))))+
0.050000*np.tanh(np.minimum(((((data["maxbatch_slices2_msignal"])-(( 4.0))))),(( np.maximum(((((np.where(data["mean_abs_chgbatch_msignal"] > -998,(((((( data["maxbatch_slices2_msignal"])*(((data["maxbatch_slices2_msignal"])-(( 4.0)))))) * 2.0)) *(data["meanbatch_slices2_msignal"])) , data["meanbatch_slices2"])) *(data["mean_abs_chgbatch_msignal"])))) ,(((((data["meanbatch_slices2_msignal"])+(((data["signal_shift_+1"])* 2.0)))/2.0)))))))) +
0.050000*np.tanh(((data["abs_maxbatch"])*(((np.where(((np.where(( -(( data["abs_maxbatch"])))> -998,(( data["abs_minbatch_slices2"])+(data["signal"])) , data["minbatch_msignal"])) +(data["signal"])) <= -998, data["abs_maxbatch"], np.sin(( data["abs_maxbatch"])))) * 2.0)))) +
0.050000*np.tanh(np.where(((((( 12.75586605072021484)) / 2.0)) * 2.0)<= -998, np.minimum(((data["signal_shift_-1"])) ,(( np.minimum(((data["signal"])) ,(( np.minimum(((np.where(( 12.75586605072021484)<= -998, data["signal_shift_+1"],(( np.sin(( data["abs_maxbatch_slices2"])))* 2.0)))) ,(( data["minbatch"]))))))))),(( np.sin(( data["abs_maxbatch_slices2"])))* 2.0)))+
0.050000*np.tanh(((np.minimum(((np.maximum(((((np.minimum(((data["abs_avgbatch_msignal"])) ,(( data["meanbatch_slices2"])))) * 2.0))),(( data["meanbatch_slices2"]))))),(((( data["signal_shift_-1_msignal"])+(data["abs_avgbatch_slices2_msignal"])))))) +(np.sin(((((data["abs_minbatch_slices2"])<=(data["minbatch"])) *1.))))))+
0.050000*np.tanh(np.where(data["abs_maxbatch_slices2_msignal"] > -998, np.where(( -(( data["maxtominbatch_msignal"])))<= -998, data["abs_avgbatch_msignal"], np.where(((data["abs_avgbatch_slices2_msignal"])*(data["meanbatch_slices2"])) > -998, data["signal_shift_-1"], np.tanh(((((data["stdbatch_msignal"])>(data["abs_maxbatch"])) *1.))))) , np.sin(((((data["abs_avgbatch_slices2_msignal"])<=(data["maxtominbatch_slices2_msignal"])) *1.))))) +
0.050000*np.tanh(np.tanh(((( np.sin(( np.where(data["meanbatch_slices2_msignal"] > -998, data["rangebatch_slices2_msignal"], data["meanbatch_msignal"])))) * 2.0)))) +
0.050000*np.tanh(np.minimum(((data["signal"])) ,(((( np.cos(( np.cos(((( np.minimum(((data["abs_minbatch_msignal"])) ,(((( data["medianbatch_slices2"])-(data["medianbatch_slices2"])))))) * 2.0)))))) +(((np.minimum(((np.minimum(((data["signal_shift_+1"])) ,(( np.cos(( data["medianbatch_slices2_msignal"]))))))),(( data["rangebatch_slices2_msignal"])))) * 2.0)))))))+
0.050000*np.tanh(data["abs_avgbatch_msignal"])+
0.050000*np.tanh(((data["medianbatch_slices2"])*(np.maximum(((data["abs_minbatch_msignal"])) ,(( np.where(((( data["abs_avgbatch_slices2_msignal"])+(data["abs_avgbatch_msignal"])) /2.0)> -998, data["abs_avgbatch_msignal"], np.minimum(((data["minbatch_slices2"])) ,(( data["abs_avgbatch_msignal"])))))))))) +
0.050000*np.tanh(((data["abs_avgbatch_msignal"])*(np.where(((( data["minbatch_slices2"])<=(np.cos(( data["meanbatch_msignal"])))) *1.) > -998, data["medianbatch_slices2"],(-(((( np.where(((data["abs_avgbatch_msignal"])*(data["meanbatch_slices2"])) <= -998,(-(( data["abs_avgbatch_msignal"]))), data["abs_avgbatch_msignal"])) *(( -(((((( data["abs_maxbatch_slices2_msignal"])-(( -(((-(( data["meanbatch_slices2"])))))))))* 2.0)))))))))))))+
0.050000*np.tanh(((np.sin(( np.minimum(((data["abs_avgbatch_slices2_msignal"])) ,(((( np.sin(( np.where(data["abs_avgbatch_slices2_msignal"] > -998, data["rangebatch_slices2_msignal"], np.where(data["abs_minbatch_slices2_msignal"] > -998, data["maxbatch_slices2"], data["signal_shift_+1_msignal"])))))* 2.0)))))))* 2.0)) +
0.050000*np.tanh(((np.sin(( data["rangebatch_slices2_msignal"])))*(((np.where(data["meanbatch_slices2_msignal"] <= -998, np.minimum(((data["maxbatch_msignal"])) ,(( data["maxtominbatch_msignal"]))), data["abs_maxbatch_slices2"])) +(data["rangebatch_msignal"])))))+
0.050000*np.tanh(np.where(np.where(((( -(( data["stdbatch_slices2_msignal"])))) *(data["abs_maxbatch_slices2"])) > -998, data["abs_minbatch_slices2_msignal"], data["abs_minbatch_slices2_msignal"])> -998, np.sin(( data["abs_maxbatch_slices2"])) , data["abs_avgbatch_slices2_msignal"])) +
0.050000*np.tanh(((((((np.sin(( data["signal"])))*(((( data["minbatch_slices2_msignal"])+(data["maxbatch_slices2"])) /2.0)))) +(data["abs_avgbatch_msignal"])))*(((( -(((-(( data["medianbatch_msignal"])))))))+(data["abs_maxbatch_slices2"])))))+
0.050000*np.tanh(((np.cos(((( data["maxbatch_msignal"])-(np.sin(( np.where(((data["maxbatch_msignal"])*(((data["minbatch_slices2_msignal"])+(data["mean_abs_chgbatch_slices2_msignal"])))) > -998,(4.10039758682250977),(((( np.where(data["minbatch_slices2_msignal"] > -998,(4.10039758682250977),(( data["abs_avgbatch_msignal"])/ 2.0)))* 2.0)) *(( -(( np.tanh(( data["abs_avgbatch_msignal"])))))))))))))))* 2.0)) +
0.050000*np.tanh(((((np.sin(( data["rangebatch_slices2_msignal"])))*(np.maximum(((((((((data["signal"])-(data["rangebatch_slices2_msignal"])))/ 2.0)) -(np.sin(( data["rangebatch_slices2_msignal"])))))) ,(( data["rangebatch_slices2_msignal"])))))) *(np.maximum(((data["abs_maxbatch_slices2_msignal"])) ,(( np.maximum(((data["maxbatch_msignal"])) ,(( np.sin(((( data["signal"])-(data["minbatch_msignal"])))))))))))))+
0.050000*np.tanh(((np.where(data["meanbatch_slices2_msignal"] <= -998, data["mean_abs_chgbatch_slices2_msignal"],(( np.where(data["signal"] > -998, data["stdbatch_slices2_msignal"],(( np.where(data["signal"] > -998, data["stdbatch_slices2_msignal"], data["meanbatch_slices2_msignal"])) *(data["abs_maxbatch_msignal"])))) *(data["signal_shift_+1"])))) -(((np.where(data["stdbatch_slices2_msignal"] > -998, data["stdbatch_slices2_msignal"], data["abs_maxbatch_msignal"])) *(((data["meanbatch_slices2_msignal"])+(data["abs_maxbatch_msignal"])))))))+
0.050000*np.tanh(((((np.tanh(( np.minimum(((data["abs_maxbatch_slices2"])) ,(( np.cos(( np.where(data["abs_maxbatch_slices2"] > -998,(( data["abs_minbatch_slices2_msignal"])* 2.0), np.tanh(( np.minimum(((data["meanbatch_msignal"])) ,(( np.cos(( np.sin(( np.cos(( np.minimum(((((data["abs_maxbatch_slices2"])/ 2.0))),(( np.cos(( data["abs_maxbatch_slices2"])))))))))))))))))))))))))* 2.0)) * 2.0)) +
0.050000*np.tanh(np.where(np.where(data["medianbatch_slices2_msignal"] <= -998,(( np.sin(( data["signal_shift_-1"])))/ 2.0), data["signal_shift_-1"])<= -998, data["signal_shift_-1"],(( data["abs_avgbatch_slices2_msignal"])*(data["signal_shift_+1"])))) +
0.050000*np.tanh(np.where(data["abs_maxbatch_msignal"] <= -998, np.maximum(((data["stdbatch_slices2_msignal"])) ,(( data["minbatch_slices2_msignal"]))),(( data["meanbatch_slices2_msignal"])+(np.sin(( np.sin(( data["rangebatch_slices2_msignal"])))))))) +
0.050000*np.tanh(np.sin(( np.maximum(((data["minbatch_msignal"])) ,(((( np.sin(( np.maximum(((( -(( data["minbatch_msignal"]))))),(((-(( data["minbatch_msignal"])))))))))+(np.sin(( np.tanh(( np.minimum(((data["abs_avgbatch_msignal"])) ,(( np.sin(((-(( data["minbatch_msignal"])))))))))))))))))))) +
0.050000*np.tanh(np.minimum(((((data["signal_shift_+1"])*(((data["abs_minbatch_slices2_msignal"])*(np.where(data["signal_shift_-1"] <= -998, data["abs_minbatch_slices2_msignal"], np.where(np.where(data["abs_minbatch_slices2_msignal"] <= -998, data["abs_maxbatch_slices2_msignal"], np.cos(((((-(( data["meanbatch_slices2"])))) * 2.0)))) <= -998, data["signal"], np.cos(( data["mean_abs_chgbatch_slices2_msignal"])))))))))) ,(((( data["abs_avgbatch_msignal"])* 2.0)))))+
0.050000*np.tanh(np.minimum(((((data["abs_avgbatch_slices2_msignal"])*(data["rangebatch_slices2_msignal"])))) ,(((((((-(( data["stdbatch_slices2_msignal"])))) -(np.sin(((((( data["abs_avgbatch_slices2_msignal"])* 2.0)) * 2.0)))))) -(np.sin(( np.maximum(((( -(( data["stdbatch_slices2_msignal"]))))),(( data["meanbatch_slices2"])))))))))))+
0.050000*np.tanh(((data["minbatch_slices2"])-(((((data["minbatch_slices2_msignal"])+(data["abs_avgbatch_slices2_msignal"])))*(np.cos(( np.where(np.where(np.maximum(((((data["abs_avgbatch_slices2_msignal"])* 2.0))),(( np.where(data["maxbatch_slices2_msignal"] > -998, data["abs_maxbatch_msignal"], data["stdbatch_slices2"])))) > -998, data["minbatch_slices2_msignal"], data["maxtominbatch"])> -998, data["minbatch_slices2_msignal"], data["minbatch_slices2_msignal"])))))))) +
0.050000*np.tanh(np.where(( 5.0)<= -998,(((-(( np.where(data["maxbatch_msignal"] <= -998, data["maxbatch_msignal"],(( data["rangebatch_msignal"])/ 2.0)))))) *(np.sin(( data["meanbatch_msignal"])))) ,(-(( np.where(data["minbatch_msignal"] <= -998, data["maxbatch_msignal"],(((( data["abs_avgbatch_slices2_msignal"])*(data["stdbatch_slices2_msignal"])))* 2.0)))))))+
0.050000*np.tanh(np.where(data["abs_maxbatch_slices2_msignal"] <= -998,(( data["maxtominbatch_slices2_msignal"])-(( -(( np.sin(( data["maxbatch_slices2_msignal"]))))))),(( data["abs_maxbatch_slices2_msignal"])*(( -(( np.sin(( np.maximum(((data["maxbatch_msignal"])) ,(((2.0)))))))))))))+
0.050000*np.tanh(np.where(((( data["rangebatch_slices2"])+(np.maximum(((data["rangebatch_slices2"])) ,(( data["rangebatch_msignal"])))))/2.0)<= -998, data["mean_abs_chgbatch_slices2"],(( np.cos(( data["maxtominbatch_slices2_msignal"])))* 2.0)))+
0.050000*np.tanh(((( -(( data["rangebatch_slices2_msignal"])))) +(((data["maxbatch_slices2_msignal"])+(((data["minbatch_msignal"])*(np.sin(( np.sin(( np.where(data["abs_avgbatch_msignal"] > -998, data["abs_maxbatch_slices2_msignal"],(((data["signal_shift_+1"])>(( -(((((np.tanh(( data["minbatch_msignal"])))+(np.sin(( data["signal_shift_+1"])))) /2.0)))))) *1.))))))))))))) +
0.050000*np.tanh(np.where(data["maxbatch_msignal"] <= -998,(( data["maxbatch_msignal"])/ 2.0),(( data["maxtominbatch_msignal"])*(np.cos(( np.where(np.where(data["medianbatch_slices2"] <= -998, data["maxtominbatch_msignal"], np.where(np.cos(((-(( np.minimum(((data["maxtominbatch_msignal"])) ,(( data["mean_abs_chgbatch_msignal"])))))))) <= -998, data["maxbatch_slices2_msignal"],(( data["mean_abs_chgbatch_msignal"])*(((data["medianbatch_slices2"])/ 2.0)))))<= -998, data["maxbatch_msignal"], data["mean_abs_chgbatch_msignal"])))))))+
0.050000*np.tanh(( -(((( data["mean_abs_chgbatch_slices2"])-(((data["maxtominbatch_slices2_msignal"])*(np.maximum(((np.sin(( data["maxbatch_slices2_msignal"])))) ,(( np.minimum(((np.minimum(((np.sin(( data["mean_abs_chgbatch_slices2_msignal"])))) ,(( data["mean_abs_chgbatch_slices2"]))))),(((( data["mean_abs_chgbatch_slices2_msignal"])-(((data["maxtominbatch_slices2_msignal"])+(data["medianbatch_slices2"])))))))))))))))))) +
0.050000*np.tanh(((((np.cos(((( np.maximum(((data["signal"])) ,(( data["signal"])))) * 2.0)))) * 2.0)) *(data["signal"])))+
0.050000*np.tanh(( -(((( data["mean_abs_chgbatch_slices2_msignal"])*(((data["abs_avgbatch_msignal"])-(((((((((((data["abs_avgbatch_msignal"])*(data["mean_abs_chgbatch_slices2_msignal"])))-(((data["mean_abs_chgbatch_slices2_msignal"])*(np.sin(((( data["mean_abs_chgbatch_slices2_msignal"])* 2.0)))))))) -(((((( data["signal_shift_-1_msignal"])>(((( 3.0)) * 2.0)))*1.))/ 2.0)))) / 2.0)) / 2.0)))))))))+
0.050000*np.tanh(((data["mean_abs_chgbatch_slices2_msignal"])*(((data["abs_avgbatch_slices2_msignal"])*(np.minimum(((((np.minimum(((data["stdbatch_msignal"])) ,(( data["meanbatch_slices2"])))) * 2.0))),(((((( -(( data["abs_maxbatch_slices2_msignal"])))) +(((( np.minimum(((data["maxtominbatch_msignal"])) ,(((((data["mean_abs_chgbatch_msignal"])+(data["mean_abs_chgbatch_msignal"])) /2.0)))))<=(np.cos(( np.where(data["meanbatch_slices2_msignal"] <= -998, data["maxbatch_msignal"], np.tanh(( data["maxtominbatch_msignal"])))))))*1.))) /2.0)))))))))+
0.050000*np.tanh(((((data["maxtominbatch_slices2_msignal"])*(np.sin(( data["minbatch_msignal"])))))-(np.tanh(((((((( data["stdbatch_msignal"])>(data["minbatch_msignal"])) *1.))>(np.where(data["abs_maxbatch_slices2_msignal"] <= -998, data["minbatch_msignal"],(-(( np.maximum(((data["maxtominbatch_slices2_msignal"])) ,(( data["abs_avgbatch_slices2_msignal"])))))))))*1.))))))+
0.050000*np.tanh(((np.where(((((((((np.sin(((( data["medianbatch_slices2"])* 2.0)))) *(data["abs_maxbatch_slices2"])))* 2.0)) -(((( np.tanh(( np.tanh(((( data["abs_maxbatch_slices2"])*(( 7.0)))))))) +(data["rangebatch_slices2"])) /2.0)))) * 2.0)> -998,(( data["abs_avgbatch_slices2_msignal"])*(data["medianbatch_slices2"])) ,(-(( data["maxtominbatch_msignal"])))))* 2.0)) +
0.050000*np.tanh(((np.where(data["stdbatch_msignal"] > -998,(((( np.where(np.sin(((( data["abs_avgbatch_slices2_msignal"])* 2.0)))<= -998,(( np.cos(( data["maxbatch_msignal"])))*(data["maxbatch_msignal"])) , np.sin(( data["abs_avgbatch_slices2_msignal"])))) -(np.sin(( data["maxbatch_slices2_msignal"])))))-(((( data["mean_abs_chgbatch_slices2_msignal"])>(data["signal_shift_+1_msignal"])) *1.))) , np.sin(( data["maxbatch_slices2"])))) *(data["rangebatch_msignal"])))+
0.050000*np.tanh(np.where(np.tanh(( data["maxtominbatch"])) <= -998, np.where(((( data["maxbatch_slices2_msignal"])>(data["stdbatch_slices2_msignal"])) *1.) > -998, data["stdbatch_msignal"], data["maxbatch_slices2_msignal"]),(-(((( np.cos(((( data["stdbatch_slices2_msignal"])* 2.0)))) * 2.0)))))) +
0.050000*np.tanh(((np.cos(( np.where(((((((( data["rangebatch_msignal"])* 2.0)) >(data["maxtominbatch_slices2"])) *1.))*(data["medianbatch_slices2"])) <= -998, np.cos(( np.where(data["abs_maxbatch_slices2_msignal"] <= -998, data["rangebatch_msignal"], data["medianbatch_slices2"]))),(( data["abs_minbatch_msignal"])* 2.0)))))*(((data["abs_maxbatch_slices2_msignal"])* 2.0)))) +
0.050000*np.tanh(((data["maxtominbatch_msignal"])*(np.cos(( np.where(np.sin(( data["maxbatch_slices2_msignal"])) > -998, data["mean_abs_chgbatch_msignal"], data["maxtominbatch_msignal"])))))) +
0.050000*np.tanh(np.sin(( np.minimum(((((np.where(((data["medianbatch_slices2_msignal"])* 2.0)> -998, data["mean_abs_chgbatch_msignal"],(-(( data["mean_abs_chgbatch_msignal"])))))* 2.0))),(( data["maxtominbatch_msignal"])))))) +
0.050000*np.tanh(( -(((( np.sin(( data["minbatch_msignal"])))*(((((( data["abs_maxbatch_slices2"])<=(((( -(((( np.sin(( data["minbatch_msignal"])))/ 2.0)))))-(( -(((((( data["abs_minbatch_msignal"])* 2.0)) +(data["minbatch_msignal"])))))))))*1.))+(data["abs_maxbatch_slices2"])))))))) +
0.050000*np.tanh(((np.sin(((( data["abs_minbatch_msignal"])+(((((( np.sin(( np.cos(( data["abs_maxbatch"])))))* 2.0)) +(data["abs_minbatch_msignal"])) /2.0)))))) *(data["rangebatch_slices2_msignal"])))+
0.050000*np.tanh(np.cos(((( np.maximum(((data["signal"])) ,(( np.cos(((( np.maximum(((np.cos(( data["signal"])))) ,(( np.where(((np.cos(( np.sin(( data["signal"])))))* 2.0)> -998, data["signal"], np.where(data["abs_avgbatch_slices2_msignal"] > -998, data["meanbatch_slices2"], np.cos(( np.cos(( data["medianbatch_msignal"])))))))))) * 2.0)))))))* 2.0)))) +
0.050000*np.tanh(((((np.minimum(((((((((np.minimum(((data["signal_shift_+1"])) ,(((((((data["rangebatch_slices2"])+(((( data["maxtominbatch_msignal"])+(data["stdbatch_slices2_msignal"])) /2.0)))) <=(((data["medianbatch_msignal"])* 2.0)))*1.))))) * 2.0)) -(data["stdbatch_msignal"])))* 2.0))),(((( data["medianbatch_msignal"])*(data["signal_shift_+1"])))))) * 2.0)) -(((( data["mean_abs_chgbatch_msignal"])+(data["medianbatch_msignal"])) /2.0)))) +
0.050000*np.tanh(((np.minimum(((((np.tanh(( np.minimum(((data["abs_avgbatch_slices2_msignal"])) ,(( np.cos(( np.maximum(((data["abs_avgbatch_slices2_msignal"])) ,(( data["medianbatch_slices2_msignal"])))))))))))* 2.0))),(((((((((((((( data["abs_maxbatch_slices2"])<=(np.minimum(((((((((( data["medianbatch_slices2_msignal"])/ 2.0)) * 2.0)) +(data["maxtominbatch_msignal"])) /2.0))),(( data["minbatch_slices2_msignal"])))))*1.))/ 2.0)) * 2.0)) / 2.0)) >(data["maxtominbatch_msignal"])) *1.))))) * 2.0)) +
0.050000*np.tanh(((((data["rangebatch_slices2_msignal"])*(( -(( data["stdbatch_msignal"])))))) * 2.0)) +
0.050000*np.tanh(((((data["abs_maxbatch_slices2"])*(np.sin(( np.minimum(((data["maxtominbatch_msignal"])) ,(((((np.sin(( np.sin(((( np.sin(( data["maxtominbatch_msignal"])))-(data["abs_maxbatch_slices2"])))))))>(np.sin(( data["maxtominbatch_msignal"])))) *1.))))))))) -(data["abs_maxbatch_slices2"])))+
0.050000*np.tanh(((data["abs_maxbatch_slices2_msignal"])*(np.cos(((( data["abs_minbatch_msignal"])* 2.0)))))) +
0.050000*np.tanh(((data["abs_avgbatch_slices2_msignal"])* 2.0)) +
0.050000*np.tanh(((np.cos(( np.minimum(((( 0.54778587818145752))),(( np.where(data["maxtominbatch_msignal"] > -998, data["maxtominbatch_msignal"],(((data["stdbatch_slices2"])+(data["abs_avgbatch_slices2_msignal"])) /2.0)))))))) * 2.0)) +
0.050000*np.tanh(np.minimum(((data["signal_shift_-1"])) ,(((((((-(( data["mean_abs_chgbatch_msignal"])))) -(((data["meanbatch_msignal"])*(np.minimum(((data["minbatch"])) ,(( np.minimum(((np.sin(((( data["abs_avgbatch_slices2_msignal"])* 2.0))))),(((( data["maxtominbatch_slices2_msignal"])/ 2.0)))))))))))) * 2.0)))))+
0.050000*np.tanh(((((np.where(data["minbatch"] <= -998, data["signal"], np.where(data["abs_maxbatch_msignal"] > -998, data["minbatch"], np.where(data["stdbatch_slices2"] > -998,(6.60688304901123047), np.cos(( data["maxtominbatch_msignal"])))))) * 2.0)) * 2.0)) +
0.050000*np.tanh(np.where(((data["signal"])*(data["abs_avgbatch_slices2_msignal"])) > -998,(( np.sin(((( data["abs_minbatch_msignal"])+(((( data["rangebatch_msignal"])+(((( data["medianbatch_msignal"])<=(((data["abs_avgbatch_slices2_msignal"])* 2.0)))*1.))) /2.0)))))) * 2.0), np.tanh(( data["abs_maxbatch_msignal"])))) +
0.050000*np.tanh(np.where(data["minbatch_msignal"] <= -998,(((np.tanh(((((((data["abs_minbatch_slices2_msignal"])* 2.0)) +(np.minimum(((data["meanbatch_msignal"])) ,(( data["abs_minbatch_slices2_msignal"])))))/2.0)))) +(data["abs_minbatch_slices2_msignal"])) /2.0), np.sin(( np.where(data["abs_minbatch_msignal"] <= -998, data["abs_avgbatch_slices2_msignal"],(( data["maxtominbatch_msignal"])* 2.0)))))) +
0.050000*np.tanh(((((data["maxtominbatch_msignal"])*(np.sin(( data["abs_maxbatch_slices2_msignal"])))))-(((( np.sin(( data["medianbatch_msignal"])))<=(np.maximum(((((data["maxtominbatch_msignal"])*(data["abs_maxbatch_slices2_msignal"])))) ,(( data["abs_maxbatch_slices2_msignal"])))))*1.))))+
0.050000*np.tanh(np.sin(((-(( np.where(np.where(data["mean_abs_chgbatch_msignal"] > -998, np.where(np.sin(( np.sin(((-(( np.cos(((( data["abs_minbatch_msignal"])/ 2.0)))))))))) <= -998, data["abs_minbatch_msignal"], data["maxbatch_slices2_msignal"]), data["stdbatch_slices2"])<= -998, data["abs_minbatch_msignal"], data["maxbatch_slices2_msignal"])))))))+
0.050000*np.tanh(((np.maximum(((((data["abs_avgbatch_msignal"])*(((data["mean_abs_chgbatch_msignal"])*(data["mean_abs_chgbatch_msignal"])))))) ,(( np.where(np.cos(((-(( data["minbatch_slices2"])))))> -998, np.minimum(((data["mean_abs_chgbatch_msignal"])) ,(( data["mean_abs_chgbatch_slices2_msignal"]))), np.where(np.cos(( np.cos(( data["abs_maxbatch"])))) <= -998, data["signal_shift_-1"],(3.0)))))))+(data["maxtominbatch"])))+
0.050000*np.tanh(((np.sin(( data["maxbatch_msignal"])))*(((data["minbatch"])-(np.minimum(((data["signal_shift_-1"])) ,(( np.minimum(((data["medianbatch_slices2_msignal"])) ,(( np.sin(( data["abs_maxbatch"])))))))))))))+
0.050000*np.tanh(np.minimum(((data["abs_avgbatch_msignal"])) ,(( np.cos(( np.where(np.minimum(((((( 10.31050777435302734)) *(data["abs_avgbatch_slices2_msignal"])))) ,(((((10.31050777435302734)) *(np.cos(((( data["rangebatch_slices2"])*(data["minbatch_slices2"])))))))))> -998, data["maxtominbatch_slices2_msignal"],(( data["minbatch"])-(data["minbatch"])))))))))+
0.050000*np.tanh(((((np.sin(((((data["mean_abs_chgbatch_slices2_msignal"])>(np.where(data["stdbatch_msignal"] <= -998, np.sin(((( data["abs_maxbatch"])-(data["mean_abs_chgbatch_slices2_msignal"])))) , data["stdbatch_msignal"])))*1.))))-(np.sin(( data["minbatch_msignal"])))))* 2.0)) +
0.050000*np.tanh(((data["stdbatch_slices2"])+(( -(( np.minimum(((data["medianbatch_slices2_msignal"])) ,(((-(( data["maxtominbatch_msignal"])))))))))))) +
0.050000*np.tanh(((np.tanh(( np.sin(( data["abs_minbatch_slices2_msignal"])))))-(np.maximum(((data["minbatch"])) ,(( np.where(data["minbatch"] <= -998, data["medianbatch_slices2_msignal"],(( data["stdbatch_msignal"])*(data["abs_avgbatch_slices2_msignal"])))))))))+
0.050000*np.tanh(((np.sin(( data["maxbatch_slices2_msignal"])))*(np.where(np.cos(( data["abs_maxbatch_slices2_msignal"])) > -998, data["abs_minbatch_slices2_msignal"],(((( np.sin(( np.sin(( data["abs_maxbatch_slices2_msignal"])))))*(np.where(np.cos(((((( data["meanbatch_slices2_msignal"])/ 2.0)) / 2.0)))> -998, data["stdbatch_msignal"], data["abs_avgbatch_slices2_msignal"])))) -(data["signal_shift_+1_msignal"])))))) +
0.050000*np.tanh(((np.cos(( data["abs_avgbatch_slices2_msignal"])))*(np.sin(((-(( np.where(data["abs_maxbatch"] <= -998, np.sin(( np.sin(((-(( np.sin(( np.cos(((( data["minbatch_slices2"])*(data["abs_maxbatch"]))))))))))))), data["minbatch_msignal"])))))))))+
0.050000*np.tanh(((((data["maxtominbatch_msignal"])+(np.sin(( np.cos(((( data["maxbatch_slices2"])* 2.0)))))))) *(np.where(np.cos(((((np.minimum(((data["minbatch_msignal"])) ,(( data["abs_maxbatch_msignal"])))) >(data["maxtominbatch"])) *1.))) <= -998, data["abs_minbatch_msignal"], data["meanbatch_slices2"])))) +
0.050000*np.tanh(((data["stdbatch_msignal"])*(data["minbatch"])))+
0.050000*np.tanh(((np.where(data["meanbatch_msignal"] > -998, data["abs_avgbatch_slices2_msignal"], data["minbatch"])) *(((data["signal_shift_-1"])+(( -(( np.maximum(((np.sin(((((data["stdbatch_slices2_msignal"])>(np.where(np.where(data["maxbatch_slices2_msignal"] > -998,(( data["mean_abs_chgbatch_slices2_msignal"])+(np.cos(( data["signal_shift_-1"])))) , data["abs_avgbatch_slices2_msignal"])> -998, data["signal_shift_-1"], data["minbatch"])))*1.))))) ,(((( data["abs_avgbatch_slices2_msignal"])* 2.0)))))))))))) +
0.050000*np.tanh(((data["maxtominbatch"])*(np.cos(((( data["maxtominbatch"])*(np.minimum(((data["stdbatch_slices2_msignal"])) ,(((-(((( np.sin(( np.sin(((( data["medianbatch_msignal"])+(((( np.cos(((( data["maxtominbatch"])*(data["maxtominbatch"])))))>(np.sin(((( data["medianbatch_msignal"])+(data["minbatch_msignal"])))))) *1.))))))))*(data["mean_abs_chgbatch_slices2_msignal"])))))))))))))))+
0.050000*np.tanh(( -(((( np.where(( 9.0)<= -998, np.where(data["abs_avgbatch_slices2_msignal"] > -998, data["minbatch_msignal"], data["stdbatch_slices2_msignal"]), data["mean_abs_chgbatch_msignal"])) *(data["maxbatch_msignal"])))))) +
0.050000*np.tanh(np.sin(( np.where(((data["medianbatch_slices2_msignal"])-(np.tanh(( data["mean_abs_chgbatch_slices2_msignal"])))) > -998, data["abs_avgbatch_msignal"], np.minimum(((np.sin(( data["signal_shift_+1"])))) ,(( data["abs_maxbatch"])))))))+
0.050000*np.tanh(((data["minbatch_msignal"])*(((np.sin(( data["stdbatch_msignal"])))+(np.cos(( np.where(data["signal_shift_+1_msignal"] > -998, data["mean_abs_chgbatch_slices2"], np.where(np.sin(( data["maxbatch_slices2"])) <= -998, data["mean_abs_chgbatch_msignal"], data["rangebatch_slices2"])))))))))+
0.050000*np.tanh(( -(((( data["abs_avgbatch_slices2_msignal"])*(np.minimum(((((data["abs_maxbatch_slices2_msignal"])*(np.minimum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(( data["abs_avgbatch_slices2_msignal"]))))))),(((( data["abs_avgbatch_msignal"])*(((( np.cos(( data["medianbatch_msignal"])))>(data["mean_abs_chgbatch_slices2_msignal"])) *1.))))))))))))+
0.050000*np.tanh(((np.where(data["medianbatch_slices2"] <= -998, np.where(data["abs_avgbatch_msignal"] <= -998,(( data["stdbatch_slices2_msignal"])*(data["abs_avgbatch_msignal"])) , np.cos(( data["minbatch_msignal"]))), np.minimum(((( -(( data["stdbatch_msignal"]))))),(( np.sin(( data["abs_avgbatch_msignal"])))))))* 2.0)) +
0.050000*np.tanh(np.minimum(((data["meanbatch_slices2_msignal"])) ,(((( np.minimum(((data["mean_abs_chgbatch_slices2"])) ,(((((((((( data["mean_abs_chgbatch_slices2"])/ 2.0)) * 2.0)) * 2.0)) * 2.0)))))/ 2.0)))))+
0.050000*np.tanh(np.sin(((( np.sin(( np.where(((((((np.cos(( data["maxbatch_slices2"])))+(data["maxbatch_slices2"])) /2.0)) <=(data["signal_shift_-1_msignal"])) *1.) > -998,(-(( data["maxbatch_slices2_msignal"]))),(( data["meanbatch_slices2_msignal"])*(( 0.0)))))))-(np.where(data["stdbatch_msignal"] <= -998, np.sin(((-(( data["medianbatch_slices2"]))))), data["maxbatch_msignal"])))))) +
0.050000*np.tanh(((np.cos(( data["medianbatch_msignal"])))+(np.minimum(((np.sin(( np.where(data["maxtominbatch_slices2_msignal"] > -998, data["meanbatch_slices2_msignal"], data["abs_maxbatch_slices2"]))))),(((( data["abs_avgbatch_msignal"])* 2.0)))))))+
0.050000*np.tanh(((((((( data["rangebatch_slices2"])*(data["abs_avgbatch_msignal"])))* 2.0)) +(data["minbatch"])) /2.0)) +
0.050000*np.tanh(np.minimum(((np.where(data["maxbatch_slices2_msignal"] <= -998,(( np.minimum(((np.sin(((-(( data["stdbatch_slices2_msignal"]))))))),(( data["meanbatch_slices2"])))) * 2.0), np.sin(((-(( data["abs_minbatch_slices2"])))))))) ,(((((data["rangebatch_slices2"])>(data["maxbatch_msignal"])) *1.))))) +
0.050000*np.tanh(np.where(np.minimum(((data["abs_avgbatch_slices2_msignal"])) ,(( data["mean_abs_chgbatch_slices2_msignal"])))> -998, data["signal"], np.where(data["signal_shift_-1_msignal"] <= -998, data["abs_avgbatch_slices2"],(( data["abs_avgbatch_msignal"])*(data["minbatch_msignal"])))))+
0.050000*np.tanh(np.where(np.cos(( data["minbatch"])) > -998, data["maxtominbatch"], np.minimum(((data["abs_minbatch_slices2_msignal"])) ,(( data["signal_shift_-1"])))))+
0.050000*np.tanh(np.sin(( data["abs_minbatch_slices2_msignal"])))+
0.050000*np.tanh(((np.where(data["abs_maxbatch"] > -998, data["rangebatch_msignal"], np.where(data["meanbatch_slices2_msignal"] > -998, np.sin(( data["signal_shift_-1"])) , data["abs_minbatch_slices2_msignal"])))*(np.cos(((( np.where(data["abs_minbatch_slices2_msignal"] > -998, data["signal_shift_-1"], data["signal_shift_-1"])) -(data["abs_minbatch_slices2_msignal"])))))))+
0.050000*np.tanh(((((( np.where(((((data["signal_shift_-1"])+(data["maxbatch_slices2"])))*(data["stdbatch_slices2_msignal"])) <= -998,(-(((((data["stdbatch_slices2_msignal"])<=(((data["minbatch"])+(data["signal_shift_-1"])))) *1.)))), data["minbatch"])) * 2.0)) +(((data["signal_shift_-1"])-(((((data["signal_shift_-1"])+(((data["signal_shift_-1"])+(data["maxbatch_slices2"])))))*(data["stdbatch_slices2_msignal"])))))) /2.0)) +
0.050000*np.tanh(((np.where(np.where(data["maxbatch_slices2"] <= -998, data["maxtominbatch_msignal"],(((np.where(data["signal_shift_-1"] > -998, np.cos(( data["rangebatch_msignal"])) , data["abs_avgbatch_msignal"])) >(np.where(((data["maxtominbatch_msignal"])*(np.sin(( data["maxtominbatch"])))) <= -998, data["rangebatch_msignal"], data["minbatch_slices2_msignal"])))*1.))> -998, np.cos(( data["rangebatch_msignal"])) , np.cos(( data["abs_maxbatch"])))) *(data["maxtominbatch_msignal"])))+
0.050000*np.tanh(np.sin(( np.maximum(((data["minbatch_slices2"])) ,(((-(( np.maximum(((data["minbatch_msignal"])) ,(((-(((( np.cos(( data["medianbatch_slices2_msignal"])))* 2.0)))))))))))))))) +
0.050000*np.tanh(np.minimum(((np.cos(( data["minbatch_slices2"])))) ,(((-(( data["minbatch_slices2_msignal"])))))))+
0.050000*np.tanh(np.minimum(((np.sin(((1.85122179985046387))))),(((( np.cos(( np.maximum(((data["signal_shift_+1"])) ,(( np.where(np.cos(( np.cos(( data["abs_avgbatch_msignal"])))) > -998, np.cos(( data["rangebatch_slices2_msignal"])) , np.where(data["meanbatch_slices2_msignal"] > -998, np.cos(( data["abs_maxbatch_msignal"])) , data["mean_abs_chgbatch_slices2"])))))))) *(data["maxtominbatch_slices2_msignal"])))))) +
0.050000*np.tanh(((( -(( np.where(data["medianbatch_msignal"] > -998, np.cos(( data["signal_shift_-1"])) ,(( data["signal_shift_-1_msignal"])* 2.0)))))) +(((data["signal_shift_-1_msignal"])*(((data["meanbatch_slices2_msignal"])* 2.0)))))) +
0.050000*np.tanh(np.tanh(( np.tanh(( data["signal"])))))+
0.050000*np.tanh(np.minimum(((np.minimum(((np.sin(( data["medianbatch_msignal"])))) ,(( np.sin(( data["maxbatch_slices2"]))))))),(( np.where(( -(( data["medianbatch_slices2"])))> -998, data["abs_avgbatch_slices2_msignal"],(( np.sin(( data["abs_avgbatch_slices2_msignal"])))* 2.0)))))) +
0.050000*np.tanh(((( -(( data["signal"])))) / 2.0)) +
0.050000*np.tanh(np.where(data["signal_shift_+1_msignal"] > -998, np.sin(( np.where(np.sin(((( data["signal_shift_+1_msignal"])* 2.0)))> -998, np.sin(( np.sin(( np.sin(( np.sin(( data["abs_maxbatch_slices2"])))))))) ,(((data["maxbatch_msignal"])>(((( data["abs_maxbatch_slices2_msignal"])+(np.sin(( data["abs_maxbatch_slices2"])))) /2.0)))*1.)))), data["abs_maxbatch_slices2"])) +
0.050000*np.tanh(((np.where(np.cos(( data["maxbatch_slices2_msignal"])) <= -998, np.cos(( data["meanbatch_msignal"])) , data["signal_shift_-1"])) *(((np.sin(( data["maxtominbatch_msignal"])))* 2.0)))) +
0.050000*np.tanh(((data["minbatch_slices2_msignal"])+(((np.maximum(((np.where(np.minimum(((data["minbatch_slices2_msignal"])) ,(( data["minbatch_slices2_msignal"])))> -998, data["signal"],(( data["signal_shift_-1"])+(data["signal_shift_+1"]))))),(( np.tanh(( data["maxbatch_slices2_msignal"])))))) *(((((( data["signal_shift_-1"])<=(np.maximum(((data["abs_maxbatch_msignal"])) ,(( np.tanh(( data["minbatch_slices2_msignal"])))))))*1.))*(data["signal_shift_+1"])))))))+
0.050000*np.tanh(np.cos(( data["abs_avgbatch_slices2_msignal"])))+
0.050000*np.tanh(data["abs_avgbatch_msignal"])+
0.050000*np.tanh(np.where(np.maximum(((np.maximum(((np.maximum(((data["meanbatch_msignal"])) ,(( data["rangebatch_msignal"]))))),(( np.maximum(((data["abs_maxbatch_msignal"])) ,(( data["signal"])))))))) ,(( np.minimum(((( 10.0))),(( data["maxtominbatch_slices2"])))))) <= -998, data["rangebatch_msignal"],(((((( data["signal_shift_-1_msignal"])*(data["meanbatch_msignal"])))* 2.0)) * 2.0)))+
0.050000*np.tanh(((np.where(data["minbatch_slices2"] > -998, data["signal_shift_+1"],(( np.minimum(((data["rangebatch_slices2"])) ,(( np.sin(( data["abs_avgbatch_slices2_msignal"])))))) +(((((( -(( data["minbatch"])))) -(((data["abs_minbatch_slices2"])* 2.0)))) * 2.0)))))-(data["abs_avgbatch_msignal"])))+
0.050000*np.tanh(((np.cos(( np.maximum(((np.sin(( np.cos(( np.maximum(((data["signal_shift_-1"])) ,(( np.maximum(((np.maximum(((((((data["signal"])+(data["signal_shift_-1"])))+(data["signal_shift_+1"])))) ,(( data["signal"]))))),(((( data["signal"])+(data["signal_shift_-1"])))))))))))))) ,(((( data["signal"])+(data["signal_shift_-1"])))))))) * 2.0)) +
0.050000*np.tanh(np.where(((( data["stdbatch_msignal"])<=(data["abs_maxbatch"])) *1.) <= -998,(((( data["stdbatch_msignal"])* 2.0)) * 2.0),(((( data["medianbatch_msignal"])*(data["signal_shift_-1_msignal"])))*(np.maximum(((data["medianbatch_msignal"])) ,(((( np.where(data["maxtominbatch_slices2_msignal"] <= -998, data["signal_shift_-1_msignal"],(-(((-(((( data["maxbatch_slices2"])*(( -(((-(( data["medianbatch_slices2"])))))))))))))))) / 2.0)))))))) +
0.050000*np.tanh(((( -(( np.sin(( np.sin(( np.where(data["stdbatch_slices2_msignal"] > -998, data["abs_maxbatch_msignal"],(( np.cos(((((-(( data["abs_maxbatch_msignal"])))) * 2.0)))) +(((( -(( np.sin(( data["abs_avgbatch_msignal"])))))) * 2.0)))))))))))) * 2.0)) +
0.050000*np.tanh(((data["meanbatch_msignal"])-(((((data["maxbatch_msignal"])*(((np.where(data["abs_avgbatch_slices2_msignal"] <= -998, np.minimum(((data["signal_shift_-1_msignal"])) ,(( np.where(data["abs_avgbatch_slices2_msignal"] <= -998, data["meanbatch_msignal"], np.minimum(((data["medianbatch_slices2_msignal"])) ,(( data["abs_minbatch_msignal"]))))))), np.sin(( data["abs_minbatch_msignal"])))) *(data["signal_shift_+1_msignal"])))))* 2.0)))) +
0.050000*np.tanh(np.sin(((( data["stdbatch_slices2_msignal"])-(np.maximum(((np.maximum(((np.maximum(((data["signal_shift_+1"])) ,(( np.sin(( np.maximum(((data["stdbatch_slices2_msignal"])) ,(( np.maximum(((np.maximum(((data["signal_shift_+1"])) ,(( np.sin(( np.sin(( data["stdbatch_slices2_msignal"]))))))))),(( data["signal_shift_+1"]))))))))))))),(( data["minbatch_slices2"]))))),(( np.sin(( data["stdbatch_slices2_msignal"])))))))))) +
0.050000*np.tanh(np.sin(( np.where(data["maxbatch_slices2_msignal"] > -998,(((-(( data["rangebatch_msignal"])))) -(data["signal_shift_-1"])) , np.minimum(((data["abs_maxbatch_msignal"])) ,(((( data["maxbatch_slices2_msignal"])-(np.where(data["maxtominbatch_slices2_msignal"] > -998, data["maxtominbatch_slices2_msignal"],(( data["maxbatch_slices2_msignal"])-(data["abs_maxbatch_msignal"])))))))))))) +
0.050000*np.tanh(np.sin(( np.where(((np.where(np.tanh(( data["abs_maxbatch_msignal"])) <= -998, data["mean_abs_chgbatch_msignal"],(( data["signal_shift_-1"])-(((data["abs_maxbatch_msignal"])* 2.0)))))* 2.0)<= -998, data["mean_abs_chgbatch_msignal"],(( data["abs_maxbatch_msignal"])-(data["signal_shift_-1"])))))) +
0.050000*np.tanh(((((data["signal_shift_+1"])* 2.0)) *(((data["medianbatch_msignal"])*(np.where(data["medianbatch_msignal"] > -998, data["signal_shift_-1_msignal"], np.where(data["meanbatch_slices2"] > -998, data["signal_shift_+1"],(( data["medianbatch_msignal"])*(np.where(((( data["abs_minbatch_slices2_msignal"])+(data["rangebatch_slices2_msignal"])) /2.0)> -998, data["signal_shift_-1"],(((data["medianbatch_msignal"])<=(((( data["medianbatch_msignal"])+(data["abs_maxbatch"])) /2.0)))*1.))))))))))) +
0.050000*np.tanh(((data["stdbatch_msignal"])*(np.where(((data["stdbatch_msignal"])*(((data["abs_avgbatch_msignal"])*(data["stdbatch_slices2_msignal"])))) <= -998, data["abs_avgbatch_slices2_msignal"], data["minbatch_slices2"])))) +
0.050000*np.tanh(((((data["stdbatch_msignal"])*(((data["signal_shift_+1"])-(((((((data["abs_maxbatch_slices2_msignal"])+(data["medianbatch_msignal"])))+(data["stdbatch_slices2_msignal"])))+(data["medianbatch_slices2"])))))))-(np.tanh(( np.minimum(((((((( data["meanbatch_slices2"])+(data["abs_maxbatch_slices2_msignal"])) /2.0)) -(( 10.77968311309814453))))),(( data["minbatch"])))))))) +
0.050000*np.tanh(((((np.where(data["stdbatch_msignal"] <= -998, data["abs_avgbatch_slices2"], data["maxbatch_slices2_msignal"])) *(((np.sin(((-(( data["maxbatch_slices2_msignal"])))))) *(((( np.sin(( data["maxbatch_slices2_msignal"])))<=(data["signal_shift_-1"])) *1.))))))+(np.where(data["maxtominbatch_slices2"] > -998,(( np.sin(( data["maxbatch_slices2_msignal"])))*(((data["minbatch_slices2"])+(data["maxtominbatch_msignal"])))) , data["abs_maxbatch_slices2"])))) +
0.050000*np.tanh(np.where(data["abs_avgbatch_slices2_msignal"] <= -998, data["minbatch_slices2"], np.minimum(((np.where(((((( -(( data["mean_abs_chgbatch_msignal"])))) -(data["abs_minbatch_slices2_msignal"])))/ 2.0)<= -998, np.maximum(((np.sin(((( np.sin(( data["maxtominbatch_msignal"])))* 2.0))))),(( np.sin(( data["minbatch_slices2"]))))), np.minimum(((data["signal_shift_+1"])) ,(((-(( np.sin(( data["minbatch_msignal"]))))))))))),(( data["stdbatch_slices2"])))))+
0.050000*np.tanh(np.minimum(((np.where(data["signal_shift_+1_msignal"] <= -998, np.sin(( np.cos(((((data["signal_shift_-1"])<=(data["mean_abs_chgbatch_slices2"])) *1.))))) ,(((data["maxtominbatch_slices2"])>(data["abs_avgbatch_msignal"])) *1.)))),(( data["signal_shift_+1"])))) +
0.050000*np.tanh(np.sin(((( np.sin(( data["abs_maxbatch"])))/ 2.0)))) +
0.050000*np.tanh(((data["signal_shift_-1_msignal"])*(np.where(((( np.tanh(( data["signal"])))<=(((data["abs_avgbatch_slices2_msignal"])* 2.0)))*1.) <= -998, np.tanh(( data["meanbatch_msignal"])) , np.minimum(((data["signal"])) ,(( data["meanbatch_msignal"])))))))+
0.050000*np.tanh(((data["signal_shift_+1_msignal"])*(np.minimum(((np.where(((data["maxtominbatch_msignal"])+(data["abs_avgbatch_slices2_msignal"])) > -998, np.cos(( data["stdbatch_slices2_msignal"])) , data["meanbatch_slices2_msignal"]))),(((( data["signal_shift_+1"])*(np.cos(( np.cos(( data["stdbatch_slices2_msignal"])))))))))))) +
0.050000*np.tanh(np.sin(( np.where(data["minbatch_msignal"] > -998, np.sin(((-(((( np.sin(((((( 7.0)) +(data["medianbatch_slices2_msignal"])) /2.0)))) / 2.0)))))) , np.minimum(((data["maxbatch_slices2"])) ,(( np.sin(( data["abs_avgbatch_slices2_msignal"])))))))))+
0.050000*np.tanh(np.tanh(( np.minimum(((data["medianbatch_msignal"])) ,(( np.where(( -(( data["abs_minbatch_msignal"])))<= -998, data["abs_maxbatch_msignal"], np.minimum(((np.cos(((( np.minimum(((data["signal_shift_-1_msignal"])) ,(( np.maximum(((data["signal_shift_-1"])) ,(((-(( data["signal_shift_+1"])))))))))) *(data["abs_maxbatch"])))))) ,(( np.sin(( data["meanbatch_msignal"])))))))))))) +
0.050000*np.tanh(np.minimum(((((np.minimum(((data["minbatch"])) ,(( np.sin(( np.maximum(((data["mean_abs_chgbatch_msignal"])) ,(( data["abs_maxbatch"])))))))))-(data["maxtominbatch_msignal"])))) ,(( np.cos(((((( np.sin(( np.sin(((( data["mean_abs_chgbatch_msignal"])+(np.where(data["stdbatch_slices2"] <= -998, data["maxtominbatch_msignal"], data["mean_abs_chgbatch_msignal"])))))))) * 2.0)) -(data["maxtominbatch_msignal"])))))))) +
0.050000*np.tanh(np.cos(( np.minimum(((data["maxtominbatch_msignal"])) ,(((( data["rangebatch_slices2_msignal"])-(np.cos(( data["abs_avgbatch_msignal"])))))))))) +
0.050000*np.tanh(data["meanbatch_msignal"])+
0.050000*np.tanh(((((data["abs_maxbatch_slices2_msignal"])*(np.cos(( np.where(np.cos(( data["signal_shift_-1_msignal"])) > -998, data["abs_maxbatch_slices2_msignal"],(( data["minbatch"])*(data["signal_shift_-1_msignal"])))))))) +(((data["signal_shift_-1_msignal"])*(((( 5.82869577407836914)) *(np.cos(( np.where(np.tanh(( data["medianbatch_msignal"])) > -998, data["mean_abs_chgbatch_msignal"], np.tanh(( data["maxbatch_slices2_msignal"])))))))))))) +
0.050000*np.tanh(((np.where(data["maxbatch_slices2"] > -998, np.sin(( data["maxbatch_slices2"])) ,(((( np.where(( 6.96738290786743164)> -998, data["maxbatch_slices2"],(( data["maxbatch_slices2"])-(np.where(data["mean_abs_chgbatch_slices2_msignal"] > -998, np.sin(( data["maxbatch_slices2"])) ,(8.34637451171875000)))))) * 2.0)) -(np.where(data["abs_avgbatch_msignal"] > -998, data["abs_avgbatch_msignal"],(0.0)))))) * 2.0)) +
0.050000*np.tanh(((data["abs_maxbatch"])-(np.where(data["abs_maxbatch"] > -998,(((( 13.51512145996093750)) +(np.sin(((((data["abs_maxbatch"])+(data["maxtominbatch"])) /2.0)))))/2.0), data["medianbatch_slices2_msignal"])))) +
0.050000*np.tanh(np.where(data["signal_shift_-1"] <= -998,(( data["abs_avgbatch_msignal"])-(data["rangebatch_slices2"])) , np.minimum(((np.cos(( data["meanbatch_msignal"])))) ,(((( data["meanbatch_msignal"])+(((((data["signal_shift_+1_msignal"])+(np.maximum(((np.sin(( data["abs_avgbatch_msignal"])))) ,(( np.cos(( data["meanbatch_msignal"])))))))) *(np.tanh(( data["meanbatch_msignal"])))))))))))+
0.050000*np.tanh(((data["signal_shift_-1_msignal"])*(((np.cos(( np.where(((data["abs_maxbatch_slices2_msignal"])* 2.0)<= -998, data["abs_maxbatch_slices2_msignal"], np.where(np.minimum(((np.maximum(((data["abs_minbatch_slices2"])) ,(( data["signal_shift_-1_msignal"]))))),(( np.sin(( np.sin(( data["rangebatch_msignal"])))))))> -998, data["abs_maxbatch_slices2_msignal"], data["abs_maxbatch_slices2_msignal"])))))*(((data["maxbatch_msignal"])/ 2.0)))))) +
0.050000*np.tanh(((((data["signal_shift_-1_msignal"])*(np.where(((data["signal_shift_-1_msignal"])/ 2.0)> -998, data["meanbatch_msignal"],(( np.where(np.cos(( data["signal_shift_+1"])) > -998, data["meanbatch_msignal"],(( data["signal_shift_-1_msignal"])*(data["maxtominbatch_slices2_msignal"])))) *(data["abs_minbatch_slices2"])))))) *(data["signal_shift_+1"])))+
0.050000*np.tanh(np.minimum(((((data["medianbatch_msignal"])+(np.maximum(((np.minimum(((data["stdbatch_slices2"])) ,(((-(( data["abs_minbatch_slices2"])))))))) ,(( data["abs_avgbatch_slices2_msignal"]))))))),(( data["signal_shift_+1"])))) +
0.050000*np.tanh(np.where(np.maximum(((np.cos(((-(( data["maxtominbatch_slices2"]))))))),(( np.where(((( data["minbatch_msignal"])>(data["maxbatch_slices2_msignal"])) *1.) > -998, data["stdbatch_slices2"], np.where(data["signal_shift_+1"] <= -998,(( data["maxbatch_slices2"])/ 2.0), data["rangebatch_slices2"])))))<= -998, np.tanh(( data["meanbatch_slices2_msignal"])) , np.sin(((( data["medianbatch_slices2"])-(((data["abs_minbatch_slices2_msignal"])-(data["maxbatch_slices2"])))))))) +
0.050000*np.tanh(np.minimum(((((np.cos(( data["maxtominbatch_msignal"])))+(data["meanbatch_msignal"])))) ,(((( np.sin(( np.sin(( data["maxtominbatch_msignal"])))))+(np.minimum(((((np.minimum(((np.cos(( data["mean_abs_chgbatch_slices2"])))) ,(( data["mean_abs_chgbatch_slices2"])))) / 2.0))),(( np.sin(((((data["minbatch_msignal"])+(np.sin(( data["minbatch_msignal"])))) /2.0)))))))))))) +
0.050000*np.tanh(np.tanh(((( np.maximum(((data["meanbatch_slices2_msignal"])) ,(( data["medianbatch_slices2"])))) *(np.sin(((((data["signal"])+(data["abs_minbatch_slices2"])) /2.0)))))))) +
0.050000*np.tanh(((data["meanbatch_msignal"])*(((np.where(data["signal_shift_+1"] > -998,(((( np.where(data["meanbatch_msignal"] > -998, np.tanh(( data["signal_shift_+1_msignal"])) , data["medianbatch_slices2_msignal"])) * 2.0)) / 2.0), data["mean_abs_chgbatch_msignal"])) * 2.0)))) +
0.050000*np.tanh(((np.minimum(((((data["signal_shift_+1"])* 2.0))),(( np.sin(((((data["meanbatch_slices2_msignal"])<=(data["signal_shift_+1"])) *1.))))))) +(data["abs_maxbatch"])))+
0.050000*np.tanh(np.where(((( np.sin(( np.sin(( np.tanh(( data["abs_avgbatch_slices2"])))))))+(data["rangebatch_slices2_msignal"])) /2.0)> -998, np.sin(( np.sin(( np.maximum(((data["abs_maxbatch"])) ,(( data["medianbatch_slices2_msignal"]))))))), data["minbatch_slices2"])) +
0.050000*np.tanh(((data["abs_maxbatch_msignal"])*(np.cos(( np.where(data["stdbatch_slices2"] > -998, data["minbatch_slices2_msignal"], data["mean_abs_chgbatch_slices2_msignal"])))))) +
0.050000*np.tanh(np.minimum(((((data["meanbatch_msignal"])+(data["medianbatch_slices2"])))) ,(((( data["stdbatch_slices2_msignal"])*(((data["maxtominbatch_slices2_msignal"])-(((( data["abs_maxbatch_slices2_msignal"])+(((((( np.sin(( data["meanbatch_slices2"])))+(np.minimum(((data["signal"])) ,(( data["abs_avgbatch_msignal"])))))) +(data["abs_maxbatch_slices2_msignal"])) /2.0)))/2.0)))))))))+
0.050000*np.tanh(np.minimum(((np.minimum(((data["maxbatch_slices2_msignal"])) ,(((( np.minimum(((((((np.minimum(((data["mean_abs_chgbatch_slices2"])) ,(((((data["abs_avgbatch_slices2"])>(data["maxtominbatch_slices2_msignal"])) *1.))))) * 2.0)) / 2.0))),(((( data["signal_shift_-1"])* 2.0)))))/ 2.0)))))) ,(( np.tanh(( np.minimum(((np.minimum(((((data["mean_abs_chgbatch_slices2"])* 2.0))),(((((data["minbatch"])>(data["abs_avgbatch_msignal"])) *1.)))))),(( np.cos(( data["maxtominbatch_slices2_msignal"])))))))))))+
0.050000*np.tanh(np.sin(( np.sin(( np.maximum(((data["abs_maxbatch_slices2"])) ,(((((np.maximum(((data["abs_maxbatch_slices2"])) ,(( data["abs_maxbatch_slices2"])))) <=(np.maximum(((np.maximum(((data["abs_maxbatch"])) ,(( data["abs_maxbatch_slices2"]))))),(( np.maximum(((data["abs_maxbatch_slices2"])) ,(( data["abs_maxbatch_slices2"])))))))) *1.))))))))) +
0.050000*np.tanh(np.sin(((( data["abs_minbatch_slices2_msignal"])-(((np.maximum(((((( np.sin(((( data["abs_minbatch_slices2_msignal"])-(data["abs_minbatch_slices2_msignal"])))))+(data["maxbatch_slices2"])) /2.0))),(((((0.11005285382270813)) / 2.0)))))* 2.0)))))) +
0.050000*np.tanh(np.where(data["abs_maxbatch_slices2"] > -998, np.sin(((( data["abs_maxbatch_slices2"])* 2.0))), data["abs_maxbatch_slices2"])) +
0.050000*np.tanh(np.where(np.minimum(((data["meanbatch_msignal"])) ,(( data["maxtominbatch_slices2_msignal"])))<= -998, data["meanbatch_slices2"], np.where(data["abs_avgbatch_msignal"] > -998,(( np.sin(((( data["abs_maxbatch_slices2_msignal"])*(data["signal"])))))*(data["signal_shift_-1"])) , data["maxtominbatch_slices2_msignal"])))+
0.050000*np.tanh(np.cos(((( data["rangebatch_slices2_msignal"])+(((((( data["abs_maxbatch_msignal"])+(np.maximum(((data["signal"])) ,(( np.minimum(((data["meanbatch_slices2_msignal"])) ,(( np.where(np.cos(( np.cos(( data["signal_shift_-1"])))) <= -998,(( data["maxbatch_slices2"])* 2.0), data["abs_avgbatch_slices2"])))))))))/2.0)) *(data["medianbatch_slices2"])))))))+
0.050000*np.tanh(((np.where(((( np.where(data["medianbatch_msignal"] <= -998,(((data["stdbatch_slices2"])>(data["rangebatch_slices2"])) *1.) , data["medianbatch_msignal"])) >(data["maxbatch_slices2_msignal"])) *1.) <= -998, data["minbatch_slices2_msignal"], data["medianbatch_msignal"])) -(((data["medianbatch_msignal"])+(((np.where(((( data["medianbatch_msignal"])+(data["medianbatch_msignal"])) /2.0)<= -998, data["abs_avgbatch_slices2"], data["medianbatch_msignal"])) *(data["stdbatch_msignal"])))))))+
0.050000*np.tanh(( -(((( data["maxtominbatch_msignal"])-(np.where(((( data["signal_shift_+1"])>(((np.minimum(((data["signal_shift_+1"])) ,(((( data["maxtominbatch_msignal"])/ 2.0)))))/ 2.0)))*1.) > -998, data["minbatch"],(((((data["minbatch"])/ 2.0)) <=(((data["maxtominbatch_msignal"])-(( -(((( data["minbatch"])-(data["signal_shift_+1"])))))))))*1.))))))))+
0.050000*np.tanh(np.sin(((( data["signal_shift_+1"])* 2.0)))) +
0.050000*np.tanh(((np.sin(((( data["abs_maxbatch"])*(((( data["medianbatch_slices2_msignal"])<=(data["abs_maxbatch"])) *1.))))))* 2.0)) +
0.050000*np.tanh(((np.where(data["mean_abs_chgbatch_msignal"] <= -998,(-(( data["meanbatch_msignal"]))), data["signal_shift_-1_msignal"])) / 2.0)) +
0.050000*np.tanh(((((((( 0.0)) <=(data["abs_maxbatch_msignal"])) *1.))>(( -(( data["meanbatch_msignal"])))))*1.))+
0.050000*np.tanh(np.cos(((-(((( data["abs_maxbatch_slices2_msignal"])+(((data["meanbatch_msignal"])*(np.maximum(((data["abs_maxbatch_msignal"])) ,(( np.sin(( np.minimum(((((data["minbatch_slices2"])+(data["abs_maxbatch_slices2_msignal"])))) ,(( data["meanbatch_msignal"])))))))))))))))))) +
0.050000*np.tanh(data["medianbatch_msignal"])+
0.050000*np.tanh(np.cos(( np.where(data["meanbatch_slices2_msignal"] > -998, data["maxtominbatch_msignal"], np.where(data["minbatch_slices2"] <= -998, np.where(data["abs_maxbatch"] <= -998, data["minbatch_slices2"], np.cos(((((np.cos(( data["abs_minbatch_slices2"])))<=(data["maxtominbatch_msignal"])) *1.)))), data["signal_shift_-1_msignal"])))))+
0.050000*np.tanh(np.minimum(((data["abs_avgbatch_msignal"])) ,(( np.sin(( np.where(data["maxtominbatch_msignal"] <= -998,(( np.where(data["meanbatch_slices2"] > -998, np.sin(( data["maxtominbatch_msignal"])) , np.sin(( data["abs_avgbatch_msignal"])))) * 2.0), data["abs_avgbatch_msignal"])))))))+
0.050000*np.tanh(np.sin(( np.where(data["medianbatch_slices2"] <= -998, data["meanbatch_slices2"], data["maxtominbatch_msignal"])))) +
0.050000*np.tanh(((((((np.cos(((( np.where(data["abs_minbatch_msignal"] <= -998, data["signal_shift_+1_msignal"], data["meanbatch_msignal"])) *(data["minbatch_msignal"])))))*(np.where(data["abs_minbatch_msignal"] > -998, data["maxtominbatch_slices2_msignal"],(-(( data["abs_minbatch_msignal"])))))))* 2.0)) *(data["minbatch_slices2_msignal"])))+
0.050000*np.tanh(((data["signal_shift_-1"])*(np.cos(((((((data["maxtominbatch_msignal"])* 2.0)) +(np.where(((data["meanbatch_slices2"])+(data["maxtominbatch_msignal"])) > -998, data["minbatch_slices2"],(6.0)))) /2.0)))))) +
0.050000*np.tanh(((data["minbatch_msignal"])*(np.sin(( np.maximum(((data["maxbatch_slices2_msignal"])) ,(( np.sin(((((np.cos(( data["maxbatch_slices2"])))+(np.maximum(((((((( data["minbatch_msignal"])<=(data["minbatch_msignal"])) *1.))*(data["maxbatch_msignal"])))) ,(( data["abs_avgbatch_slices2"])))))/2.0)))))))))))+
0.050000*np.tanh(( -(((( np.minimum(((data["abs_minbatch_slices2"])) ,(((-(((( data["abs_avgbatch_slices2_msignal"])/ 2.0)))))))) / 2.0)))))+
0.050000*np.tanh(np.minimum(((data["abs_avgbatch_msignal"])) ,(( data["abs_avgbatch_msignal"])))) +
0.050000*np.tanh(np.where(((np.tanh(( data["signal"])))-(np.where(data["abs_minbatch_slices2"] <= -998,(((data["mean_abs_chgbatch_slices2"])>(((( data["medianbatch_slices2_msignal"])>(np.sin(( data["maxbatch_slices2"])))) *1.))) *1.) , data["meanbatch_msignal"])))> -998, np.sin(( data["maxbatch_slices2"])) , np.where(data["maxbatch_slices2"] > -998, np.sin(( data["maxbatch_slices2"])) , np.cos(( data["abs_maxbatch_msignal"])))))+
0.050000*np.tanh(np.maximum(((((np.sin(( data["minbatch_slices2"])))+(((data["abs_minbatch_msignal"])* 2.0))))),(( np.where(data["meanbatch_slices2_msignal"] > -998, np.where(data["maxtominbatch_slices2"] > -998, data["meanbatch_slices2_msignal"],(11.69006729125976562)) , np.sin(((( np.where(data["abs_maxbatch_msignal"] > -998, data["meanbatch_msignal"], data["maxtominbatch"])) *(np.sin(( np.sin(( data["abs_minbatch_msignal"])))))))))))))+
0.050000*np.tanh(np.cos(((( np.where(((data["abs_maxbatch"])-(np.maximum(((data["rangebatch_slices2_msignal"])) ,(( data["mean_abs_chgbatch_slices2"])))))<= -998, data["abs_maxbatch"], data["abs_maxbatch"])) -(((((( data["abs_minbatch_slices2"])/ 2.0)) >(data["maxtominbatch_msignal"])) *1.))))))+
0.050000*np.tanh(((np.minimum(((np.cos(( data["maxbatch_slices2_msignal"])))) ,(((( data["meanbatch_slices2_msignal"])*(((((data["meanbatch_slices2_msignal"])*(((data["signal_shift_-1"])+(np.tanh(((((( data["meanbatch_slices2_msignal"])/ 2.0)) * 2.0)))))))) *(((( 10.02487373352050781)) * 2.0)))))))))*(np.cos(( data["maxbatch_slices2_msignal"])))))+
0.050000*np.tanh(np.where(((((( np.minimum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(( data["abs_minbatch_msignal"])))) +(np.sin(( data["abs_avgbatch_msignal"])))) /2.0)) +(data["mean_abs_chgbatch_slices2_msignal"])) <= -998, data["abs_maxbatch_slices2"], np.cos(((( data["meanbatch_slices2"])*(data["abs_avgbatch_msignal"])))))) +
0.050000*np.tanh(np.cos(( np.minimum(((((np.sin(( np.tanh(( data["abs_avgbatch_msignal"])))))*(data["minbatch_slices2_msignal"])))) ,(((( data["minbatch"])*(((np.minimum(((np.cos(( np.minimum(((np.where(data["abs_maxbatch"] <= -998, data["mean_abs_chgbatch_slices2_msignal"], data["minbatch"]))),(( data["medianbatch_msignal"]))))))),(( data["abs_avgbatch_slices2_msignal"])))) *(data["abs_avgbatch_slices2_msignal"])))))))))) +
0.050000*np.tanh(np.sin(( np.where(np.minimum(((((( data["abs_maxbatch_slices2"])>(data["minbatch_slices2"])) *1.))) ,(((( data["abs_avgbatch_slices2"])/ 2.0)))) > -998, data["abs_maxbatch"], np.cos(( np.sin(( data["signal_shift_-1"])))))))) +
0.050000*np.tanh(np.sin(( np.maximum(((np.minimum(((((( data["signal"])>(data["signal"])) *1.))) ,(( np.minimum(((np.sin(( data["abs_avgbatch_msignal"])))) ,(( np.minimum(((np.cos(( np.sin(( data["abs_minbatch_slices2_msignal"])))))) ,(( data["meanbatch_slices2_msignal"]))))))))))),(( np.sin(( data["abs_avgbatch_msignal"])))))))) +
0.050000*np.tanh(np.where(((data["abs_avgbatch_msignal"])/ 2.0)<= -998,(( data["meanbatch_slices2_msignal"])* 2.0), np.minimum(((np.tanh(((( data["abs_avgbatch_msignal"])/ 2.0))))),(( data["signal_shift_+1"])))))+
0.050000*np.tanh(((data["minbatch"])* 2.0)) +
0.050000*np.tanh(np.where(data["signal_shift_+1_msignal"] > -998,(((data["abs_avgbatch_msignal"])+(((((data["abs_avgbatch_slices2_msignal"])/ 2.0)) / 2.0)))/2.0), np.sin(( data["abs_avgbatch_msignal"])))) +
0.050000*np.tanh(np.cos(( np.where(data["rangebatch_slices2_msignal"] <= -998, np.cos(( data["medianbatch_slices2_msignal"])) , np.where(((data["mean_abs_chgbatch_slices2_msignal"])* 2.0)> -998, data["signal_shift_+1_msignal"], data["abs_minbatch_msignal"])))))+
0.050000*np.tanh(np.where(data["signal"] <= -998,(((data["mean_abs_chgbatch_slices2_msignal"])<=(data["signal"])) *1.) ,(( data["signal"])* 2.0)))+
0.050000*np.tanh(((np.cos(( np.minimum(((np.where(((( 6.0)) * 2.0)<= -998, data["mean_abs_chgbatch_msignal"], data["medianbatch_slices2_msignal"]))),(((( data["mean_abs_chgbatch_msignal"])*(( 6.0)))))))))* 2.0)) +
0.050000*np.tanh(((((((( np.sin(( np.where(np.tanh(( data["abs_maxbatch"])) <= -998,(((( data["mean_abs_chgbatch_slices2"])-(data["signal_shift_-1"])))* 2.0), data["abs_maxbatch_slices2_msignal"])))) -(( -(((((data["abs_maxbatch"])>(((data["medianbatch_msignal"])* 2.0)))*1.))))))) / 2.0)) <=(( 0.83761829137802124)))*1.))+
0.050000*np.tanh(np.sin(((( data["abs_maxbatch_slices2"])-(np.where(((np.where(data["abs_maxbatch_slices2"] > -998, data["medianbatch_msignal"],(5.0)))-(((data["abs_maxbatch_slices2"])-(data["abs_avgbatch_slices2_msignal"])))) > -998, np.where(np.sin(( data["meanbatch_msignal"])) > -998, data["meanbatch_msignal"], data["abs_avgbatch_slices2_msignal"]), data["abs_maxbatch_slices2_msignal"])))))) +
0.050000*np.tanh(np.minimum(((data["signal_shift_-1"])) ,(( np.where(data["signal_shift_-1"] > -998, data["abs_avgbatch_slices2_msignal"], data["rangebatch_slices2"])))))+
0.050000*np.tanh(((((( data["rangebatch_slices2_msignal"])/ 2.0)) <=(data["abs_maxbatch_msignal"])) *1.))+
0.050000*np.tanh(((((( np.sin(((((((-(( np.minimum(((np.maximum(((data["signal_shift_-1_msignal"])) ,(((((data["maxbatch_slices2_msignal"])<=(data["maxtominbatch_msignal"])) *1.)))))),(( data["maxbatch_slices2"])))))))* 2.0)) * 2.0)))) <=(np.maximum(((data["maxtominbatch"])) ,(( data["meanbatch_slices2_msignal"])))))*1.))* 2.0)))
 def GP_class_8(self,data):
return self.Output(-3.014039 +
0.050000*np.tanh(((np.cos(( np.where(data["mean_abs_chgbatch_slices2"] > -998, data["abs_maxbatch_slices2_msignal"],(((np.where(np.cos(( data["signal_shift_+1"])) > -998, data["signal_shift_+1"], data["signal_shift_-1"])) <=(((data["medianbatch_slices2"])* 2.0)))*1.))))) +(( -(( data["stdbatch_slices2_msignal"])))))) +
0.050000*np.tanh(((((np.minimum(((np.maximum(((((np.sin(((((data["mean_abs_chgbatch_slices2"])<=(((data["signal"])*(data["rangebatch_slices2_msignal"])))) *1.))))* 2.0))),(( np.sin(( data["maxbatch_slices2_msignal"]))))))),(( np.minimum(((((data["maxtominbatch_slices2"])/ 2.0))),(( data["minbatch"])))))))+(np.minimum(((np.tanh(( data["minbatch_msignal"])))) ,(( data["stdbatch_msignal"])))))) -(((data["stdbatch_msignal"])*(data["rangebatch_slices2_msignal"])))))+
0.050000*np.tanh(np.where(data["abs_minbatch_slices2"] <= -998,(-(((( data["signal_shift_-1"])+(data["medianbatch_slices2"]))))),(( data["signal"])/ 2.0)))+
0.050000*np.tanh(data["medianbatch_slices2"])+
0.050000*np.tanh(((( -(( data["stdbatch_msignal"])))) -(((((((((( -(( data["stdbatch_msignal"])))) +(data["signal"])))<=(((data["abs_maxbatch_slices2_msignal"])-(data["abs_maxbatch_msignal"])))) *1.))>(data["mean_abs_chgbatch_slices2_msignal"])) *1.))))+
0.050000*np.tanh(((data["maxtominbatch"])+(np.where(data["medianbatch_slices2"] > -998, data["signal"],(( np.where(((((( data["medianbatch_slices2_msignal"])/ 2.0)) <=(np.tanh(( data["stdbatch_slices2"])))) *1.) > -998, data["medianbatch_slices2"], np.where(data["medianbatch_slices2"] <= -998, data["stdbatch_slices2"], data["medianbatch_slices2"])))* 2.0)))))+
0.050000*np.tanh(np.cos(( np.where(np.where(data["abs_maxbatch_slices2"] > -998,(((data["minbatch_slices2"])+(np.cos(((((data["minbatch_slices2"])>(data["signal_shift_+1"])) *1.))))) /2.0), np.sin(( data["abs_avgbatch_slices2"])))> -998, data["maxtominbatch_msignal"], data["signal_shift_+1"])))) +
0.050000*np.tanh(np.where(((( data["signal"])<=(((( data["rangebatch_slices2"])+(np.minimum(((data["medianbatch_slices2"])) ,(( data["signal_shift_+1"])))))/2.0)))*1.) > -998, data["signal_shift_-1"],(((data["medianbatch_slices2"])+(((np.where(data["signal"] <= -998, np.cos(( data["abs_maxbatch_slices2"])) , data["signal_shift_+1"])) -(data["signal"])))) /2.0)))+
0.050000*np.tanh(((data["abs_avgbatch_slices2_msignal"])*(((data["minbatch_slices2_msignal"])-(np.where(((data["abs_minbatch_slices2"])*(np.sin(( data["signal_shift_-1_msignal"])))) > -998, data["abs_maxbatch_slices2_msignal"],(11.76613903045654297)))))))+
0.050000*np.tanh(((data["signal_shift_+1"])+(np.where(data["abs_maxbatch_msignal"] <= -998, np.sin(((-(( data["abs_maxbatch_msignal"]))))), data["signal_shift_+1"])))) +
0.050000*np.tanh(((((data["medianbatch_slices2"])-(((( data["signal_shift_+1"])>(((data["signal_shift_+1"])+(data["medianbatch_slices2"])))) *1.))))-(((( data["abs_avgbatch_slices2"])<=(np.minimum(((data["rangebatch_msignal"])) ,(( data["mean_abs_chgbatch_slices2"])))))*1.))))+
0.050000*np.tanh(np.where(((((((9.66260623931884766)) >(( 1.0)))*1.))/ 2.0)> -998, data["signal"], np.sin(( data["abs_maxbatch_slices2"])))) +
0.050000*np.tanh(np.where(((np.minimum(((data["mean_abs_chgbatch_msignal"])) ,(( np.where(((data["signal_shift_+1"])-(((( data["maxbatch_slices2_msignal"])>(data["abs_maxbatch"])) *1.))) > -998, data["abs_avgbatch_slices2_msignal"], np.sin(( data["maxbatch_slices2_msignal"])))))))+(data["abs_avgbatch_slices2"])) > -998,(( data["meanbatch_slices2"])* 2.0),(((data["signal_shift_+1"])+(((data["maxtominbatch_msignal"])* 2.0)))/2.0)))+
0.050000*np.tanh(((np.sin(( data["rangebatch_msignal"])))*(( -(((((data["abs_minbatch_msignal"])+(data["signal_shift_-1_msignal"])) /2.0)))))))+
0.050000*np.tanh(( -(((( data["stdbatch_msignal"])-(( -(( np.where(((data["abs_avgbatch_slices2_msignal"])* 2.0)> -998, data["stdbatch_slices2_msignal"], np.maximum(((((( data["signal"])>(( 10.39941024780273438)))*1.))) ,(( np.maximum(((data["stdbatch_msignal"])) ,(((( data["abs_maxbatch_slices2"])* 2.0)))))))))))))))))+
0.050000*np.tanh(np.where(data["signal_shift_+1"] > -998,(-(( data["stdbatch_slices2_msignal"]))), np.tanh(( np.sin(( np.cos(( data["medianbatch_slices2"])))))))) +
0.050000*np.tanh(np.where(np.where(data["abs_maxbatch"] <= -998, data["signal_shift_+1_msignal"], data["rangebatch_slices2"])<= -998, np.cos(( np.sin(( data["meanbatch_slices2"])))) ,(( np.sin(((-(( data["abs_avgbatch_slices2"])))))) * 2.0)))+
0.050000*np.tanh(np.where(((( data["signal_shift_-1"])>(np.sin(( data["maxtominbatch_slices2_msignal"])))) *1.) <= -998,(( data["medianbatch_slices2"])+(data["abs_avgbatch_slices2_msignal"])) ,(((((( data["signal_shift_-1"])/ 2.0)) +(((( data["medianbatch_slices2"])<=(data["stdbatch_slices2"])) *1.))))-(((((((((data["stdbatch_msignal"])+(data["stdbatch_msignal"])))/ 2.0)) +(data["abs_avgbatch_slices2_msignal"])))+(data["abs_avgbatch_slices2_msignal"])))))) +
0.050000*np.tanh(np.where(data["abs_minbatch_msignal"] <= -998,(( data["maxbatch_slices2_msignal"])-(((( np.where(((data["stdbatch_slices2"])* 2.0)<= -998, data["maxbatch_msignal"], np.sin(( data["rangebatch_msignal"])))) >(data["medianbatch_slices2"])) *1.))) , data["signal_shift_+1"])) +
0.050000*np.tanh(np.sin(( np.maximum(((data["rangebatch_msignal"])) ,(( np.sin(( np.maximum(((((np.maximum(((data["rangebatch_msignal"])) ,(( data["rangebatch_msignal"])))) / 2.0))),(( np.sin(( np.maximum(((data["medianbatch_slices2_msignal"])) ,(( np.maximum(((np.where(data["mean_abs_chgbatch_slices2"] <= -998, data["mean_abs_chgbatch_slices2"], np.maximum(((data["mean_abs_chgbatch_slices2"])) ,(( data["rangebatch_msignal"])))))) ,(( data["rangebatch_msignal"])))))))))))))))))))+
0.050000*np.tanh(((data["minbatch"])-(((data["maxtominbatch_msignal"])+(((( data["medianbatch_slices2"])>(((data["maxtominbatch_msignal"])-(data["minbatch"])))) *1.))))))+
0.050000*np.tanh(((((data["medianbatch_slices2"])-(np.where(data["maxbatch_msignal"] > -998,(( np.where(data["stdbatch_msignal"] <= -998, data["abs_avgbatch_msignal"], data["abs_avgbatch_slices2_msignal"])) * 2.0), data["signal_shift_+1_msignal"])))) +(np.minimum(((data["medianbatch_slices2"])) ,(( data["signal_shift_-1_msignal"])))))) +
0.050000*np.tanh(np.where(((((data["mean_abs_chgbatch_msignal"])/ 2.0)) / 2.0)> -998,(((-(( data["mean_abs_chgbatch_msignal"])))) -(( 2.0))),(((((-(( data["mean_abs_chgbatch_msignal"])))) -(((data["mean_abs_chgbatch_msignal"])* 2.0)))) -(((np.where(((data["signal"])*(data["abs_avgbatch_msignal"])) <= -998,(2.55029869079589844), data["signal_shift_-1_msignal"])) -(data["stdbatch_slices2_msignal"])))))) +
0.050000*np.tanh(np.where(((data["minbatch_slices2_msignal"])/ 2.0)<= -998, data["minbatch_slices2"],(( np.sin(( np.where(np.where(((data["signal"])/ 2.0)> -998, np.where(data["stdbatch_msignal"] <= -998,(( data["medianbatch_msignal"])* 2.0),(( np.sin(( np.sin(( data["abs_maxbatch"])))))* 2.0)) , data["minbatch_slices2"])> -998, data["abs_maxbatch"],(( data["maxbatch_msignal"])* 2.0)))))* 2.0)))+
0.050000*np.tanh(( -(( np.where(data["maxtominbatch_slices2_msignal"] > -998, data["stdbatch_slices2_msignal"],(( np.where(data["minbatch_slices2"] <= -998, data["signal_shift_+1"], np.where(( -(( data["stdbatch_slices2_msignal"])))> -998,(-(( data["mean_abs_chgbatch_slices2_msignal"]))),(( data["medianbatch_slices2"])/ 2.0)))) +(data["minbatch_msignal"])))))))+
0.050000*np.tanh(((np.sin(( data["abs_maxbatch"])))*(np.where(((( data["stdbatch_slices2"])+(np.where(np.minimum(((np.cos(( data["minbatch_msignal"])))) ,(( data["mean_abs_chgbatch_slices2_msignal"])))> -998, data["abs_avgbatch_slices2_msignal"],(((2.0)) / 2.0)))) /2.0)> -998, np.maximum(((np.sin(( data["abs_maxbatch"])))) ,(( data["abs_maxbatch_slices2_msignal"]))),(((data["minbatch_slices2_msignal"])>(data["mean_abs_chgbatch_msignal"])) *1.))))) +
0.050000*np.tanh(((np.sin(( np.where(np.where(data["abs_maxbatch_slices2_msignal"] > -998, np.where(np.where(np.sin(( data["abs_minbatch_msignal"])) > -998, data["mean_abs_chgbatch_slices2_msignal"], data["mean_abs_chgbatch_slices2_msignal"])> -998, data["minbatch_slices2"], data["minbatch_slices2"]),(( data["signal_shift_-1_msignal"])-(np.maximum(((np.where(data["abs_maxbatch_slices2_msignal"] > -998, data["minbatch_slices2"], data["medianbatch_msignal"]))),(( data["stdbatch_msignal"])))))) > -998, data["abs_maxbatch_slices2"], data["minbatch_slices2"])))) -(data["abs_avgbatch_slices2_msignal"])))+
0.050000*np.tanh(np.maximum(((data["minbatch_slices2"])) ,(((( data["minbatch"])*(np.minimum(((data["stdbatch_msignal"])) ,(( data["rangebatch_msignal"])))))))))+
0.050000*np.tanh(np.sin(( data["abs_maxbatch"])))+
0.050000*np.tanh(np.sin(( np.where(((data["rangebatch_slices2"])* 2.0)<= -998, data["minbatch_msignal"], np.where(((((((( data["abs_avgbatch_slices2"])+(( 6.0)))) * 2.0)) <=(((data["maxbatch_slices2"])* 2.0)))*1.) > -998, data["abs_minbatch_slices2_msignal"], data["abs_maxbatch_slices2"])))))+
0.050000*np.tanh(np.minimum(((np.minimum(((np.cos(( np.where(data["mean_abs_chgbatch_slices2"] > -998, data["maxtominbatch_msignal"],(11.48959922790527344)))))) ,(( np.maximum(((((( data["abs_maxbatch_msignal"])<=(np.where(data["abs_minbatch_slices2_msignal"] > -998, data["maxbatch_msignal"], data["minbatch"])))*1.))) ,(((( np.where(data["medianbatch_slices2"] > -998, data["maxtominbatch_msignal"], data["minbatch"])) *(((data["rangebatch_msignal"])/ 2.0))))))))))),(((-(( data["minbatch"])))))))+
0.050000*np.tanh(np.sin(( np.sin(( np.maximum(((np.maximum(((np.maximum(((data["minbatch"])) ,(( data["rangebatch_msignal"]))))),(( data["mean_abs_chgbatch_slices2_msignal"]))))),(( data["rangebatch_msignal"])))))))) +
0.050000*np.tanh(np.sin(((( data["rangebatch_msignal"])-(((( data["minbatch_slices2_msignal"])<=(np.cos(( np.tanh(( data["maxtominbatch_slices2_msignal"])))))) *1.))))))+
0.050000*np.tanh(((data["minbatch"])*(np.maximum(((data["meanbatch_msignal"])) ,(((((( data["medianbatch_slices2_msignal"])*(( -(( data["signal"])))))) +(((np.sin(( data["minbatch_slices2_msignal"])))-(data["abs_maxbatch_slices2_msignal"])))))))))) +
0.050000*np.tanh(np.where(np.maximum(((np.sin(((((( data["rangebatch_msignal"])* 2.0)) *(data["minbatch_msignal"])))))) ,(( data["maxbatch_slices2"])))> -998,(( data["abs_avgbatch_slices2_msignal"])*(data["minbatch_msignal"])) ,(((data["abs_avgbatch_msignal"])+(((data["medianbatch_msignal"])*(data["maxtominbatch_slices2"])))) /2.0)))+
0.050000*np.tanh(np.where(np.where(((np.sin(( np.where(data["rangebatch_msignal"] <= -998, data["minbatch_slices2"],(-(((( data["mean_abs_chgbatch_slices2_msignal"])*(np.cos(( data["mean_abs_chgbatch_slices2_msignal"])))))))))))*(data["abs_minbatch_slices2_msignal"])) <= -998, data["maxtominbatch_slices2_msignal"], data["maxbatch_slices2_msignal"])<= -998, data["maxbatch_slices2_msignal"],(-(((( data["maxbatch_slices2_msignal"])*(np.cos(( data["mean_abs_chgbatch_slices2_msignal"])))))))))+
0.050000*np.tanh(((((((np.sin(( data["maxbatch_msignal"])))*(np.minimum(((np.minimum(((np.maximum(((data["minbatch_slices2"])) ,(((( np.where(data["abs_minbatch_msignal"] <= -998, data["abs_maxbatch_msignal"],(((data["maxtominbatch_slices2"])<=(np.cos(( data["signal"])))) *1.))) -(data["abs_maxbatch_msignal"]))))))),(( np.cos(( data["abs_maxbatch_msignal"]))))))),(( data["abs_minbatch_msignal"])))))) * 2.0)) * 2.0)) +
0.050000*np.tanh(( -(((( data["abs_minbatch_slices2_msignal"])*(((np.minimum(((((data["minbatch"])-(data["abs_minbatch_slices2_msignal"])))) ,(((( data["minbatch"])-(np.tanh(((( data["abs_avgbatch_slices2_msignal"])-(((((( data["abs_maxbatch_slices2_msignal"])*(data["stdbatch_slices2_msignal"])))>(np.cos(( np.sin(( data["abs_minbatch_slices2_msignal"])))))) *1.))))))))))) *(np.cos(( data["minbatch_msignal"])))))))))) +
0.050000*np.tanh(np.where(np.minimum(((np.sin(( np.sin(( data["abs_maxbatch"])))))) ,(( np.where(((data["meanbatch_msignal"])+(np.cos(( data["abs_minbatch_msignal"])))) <= -998,(( data["maxtominbatch_msignal"])* 2.0), np.cos(( data["maxtominbatch_msignal"])))))) > -998, np.sin(( data["abs_minbatch_msignal"])) , data["signal_shift_+1_msignal"])) +
0.050000*np.tanh(((np.cos(( data["maxtominbatch_msignal"])))* 2.0)) +
0.050000*np.tanh(((np.cos(( data["maxtominbatch_msignal"])))* 2.0)) +
0.050000*np.tanh(((((data["maxtominbatch_slices2_msignal"])*(np.sin(( data["signal"])))))+(np.where(( -(( data["minbatch"])))> -998, data["minbatch"], np.where(( -(( data["minbatch"])))<= -998, np.tanh(( np.where(data["signal"] > -998,(-(( np.sin(( data["signal"]))))), data["stdbatch_slices2"]))),(( data["maxtominbatch_slices2_msignal"])*(np.sin(( data["signal"])))))))))+
0.050000*np.tanh(((((((np.minimum(((data["maxbatch_msignal"])) ,(( data["abs_maxbatch_msignal"])))) +(np.sin(((( np.sin(( data["maxbatch_msignal"])))+(((((((data["maxbatch_msignal"])>(data["signal"])) *1.))<=(data["signal_shift_-1"])) *1.))))))))+(((data["maxtominbatch_slices2"])-(data["rangebatch_slices2"])))))*(np.sin(( data["maxbatch_msignal"])))))+
0.050000*np.tanh(np.minimum(((((((data["minbatch_msignal"])*(data["abs_avgbatch_msignal"])))*(np.maximum(((((( data["abs_maxbatch"])+(data["stdbatch_slices2"])) /2.0))),(( np.where(((data["minbatch_msignal"])*(data["meanbatch_msignal"])) <= -998,(((data["abs_minbatch_slices2_msignal"])+(data["stdbatch_slices2"])) /2.0), data["stdbatch_slices2"])))))))) ,(( np.maximum(((data["signal_shift_-1"])) ,(((-(( np.where(data["stdbatch_slices2"] > -998, data["medianbatch_msignal"], data["meanbatch_msignal"])))))))))))+
0.050000*np.tanh(((np.sin(( np.where(np.tanh(( np.sin(( np.where(data["abs_maxbatch_msignal"] > -998, data["abs_minbatch_slices2_msignal"], data["maxtominbatch_slices2_msignal"])))))> -998, data["rangebatch_msignal"],(( data["abs_maxbatch_slices2_msignal"])/ 2.0)))))* 2.0)) +
0.050000*np.tanh(((np.where(data["maxtominbatch"] > -998, np.sin(( np.where(( -(( data["abs_maxbatch_slices2_msignal"])))<= -998, np.where(data["maxtominbatch"] > -998, np.cos(( data["abs_minbatch_msignal"])) , data["meanbatch_msignal"]), np.where(np.cos(( data["meanbatch_msignal"])) <= -998, data["abs_minbatch_slices2"], data["rangebatch_msignal"])))) ,(( data["abs_minbatch_slices2"])-(data["abs_minbatch_msignal"])))) * 2.0)) +
0.050000*np.tanh(((((((data["abs_maxbatch"])*(np.cos(((( np.where(((data["meanbatch_slices2"])* 2.0)> -998, data["abs_maxbatch_slices2_msignal"], data["signal_shift_+1"])) * 2.0)))))) -(np.where(((((data["minbatch_slices2_msignal"])* 2.0)) *(data["minbatch"])) > -998, data["abs_maxbatch_slices2_msignal"], np.where(data["signal_shift_-1"] <= -998, data["stdbatch_slices2_msignal"], data["rangebatch_msignal"])))))* 2.0)) +
0.050000*np.tanh(np.sin(( np.where(np.sin(( np.cos(( data["mean_abs_chgbatch_slices2"])))) <= -998, data["rangebatch_slices2"], data["abs_maxbatch_slices2"])))) +
0.050000*np.tanh(np.where(data["medianbatch_slices2_msignal"] > -998,(( data["abs_maxbatch"])*(np.sin(( np.sin(( np.sin(((((( np.minimum(((data["medianbatch_slices2"])) ,(( data["abs_minbatch_slices2_msignal"])))) * 2.0)) / 2.0))))))))), np.maximum(((data["abs_minbatch_msignal"])) ,(((( data["maxbatch_slices2_msignal"])*(((data["signal_shift_-1"])/ 2.0)))))))) +
0.050000*np.tanh(np.sin(( data["abs_minbatch_msignal"])))+
0.050000*np.tanh(((((np.where(data["abs_maxbatch_slices2_msignal"] <= -998, np.where(data["maxtominbatch"] <= -998, data["rangebatch_msignal"], data["minbatch_msignal"]),(( np.cos(( np.where(data["rangebatch_msignal"] > -998, data["stdbatch_msignal"],(10.96751308441162109)))))* 2.0)))/ 2.0)) *(np.where(data["minbatch_slices2"] > -998, data["minbatch_slices2"], data["abs_maxbatch_slices2_msignal"])))) +
0.050000*np.tanh(np.minimum(((((data["medianbatch_slices2_msignal"])*(data["maxtominbatch_msignal"])))) ,(( np.minimum(((((data["medianbatch_msignal"])*(data["meanbatch_slices2_msignal"])))) ,(( np.where(((( data["meanbatch_slices2_msignal"])+(data["meanbatch_slices2_msignal"])) /2.0)> -998,(((( data["abs_maxbatch_slices2_msignal"])+(data["medianbatch_slices2_msignal"])))+(data["medianbatch_slices2_msignal"])) , data["meanbatch_slices2"])))))))) +
0.050000*np.tanh(((data["medianbatch_slices2"])+(( -(( np.where(data["abs_avgbatch_msignal"] > -998,(((( data["abs_maxbatch_slices2"])*(data["abs_avgbatch_msignal"])))*(data["abs_avgbatch_msignal"])) ,(((data["medianbatch_slices2"])+(data["medianbatch_slices2"])) /2.0)))))))) +
0.050000*np.tanh(np.where(data["signal"] <= -998, np.maximum(((data["maxbatch_msignal"])) ,(((((data["abs_avgbatch_slices2_msignal"])<=(((data["maxtominbatch_msignal"])/ 2.0)))*1.)))), np.where(data["rangebatch_slices2_msignal"] <= -998, data["maxtominbatch_msignal"], np.cos(( data["maxtominbatch_msignal"])))))+
0.050000*np.tanh(((np.where(np.where(data["stdbatch_msignal"] > -998, data["stdbatch_msignal"],(( np.sin(((2.0)))) * 2.0)) > -998, np.sin(((( np.where(np.sin(((((( data["stdbatch_msignal"])* 2.0)) +(((np.where(data["stdbatch_msignal"] > -998, data["rangebatch_slices2"], data["stdbatch_msignal"])) / 2.0)))))> -998, data["stdbatch_msignal"], np.cos(( data["maxtominbatch"])))) * 2.0))),(2.0)))* 2.0)) +
0.050000*np.tanh(((np.cos(((((data["stdbatch_slices2_msignal"])+(((np.where(np.where(data["signal_shift_-1"] > -998, data["abs_minbatch_slices2_msignal"], data["minbatch_slices2_msignal"])> -998, data["abs_minbatch_slices2_msignal"], np.where(( 2.0)<= -998, data["abs_minbatch_slices2_msignal"],(((( data["stdbatch_slices2"])*(np.minimum(((data["abs_minbatch_msignal"])) ,(( np.cos(( data["abs_minbatch_slices2_msignal"])))))))) * 2.0)))) * 2.0)))/2.0)))) *(np.maximum(((data["signal_shift_-1"])) ,(( data["signal_shift_-1"])))))) +
0.050000*np.tanh(((np.sin(( np.where(np.sin(( np.where(data["maxtominbatch_slices2"] > -998, np.tanh(( data["medianbatch_msignal"])) , np.tanh(((((((( data["abs_avgbatch_msignal"])+(data["medianbatch_msignal"])))-(data["rangebatch_msignal"])))+(data["abs_maxbatch"])))))))> -998, data["rangebatch_msignal"],(( data["abs_avgbatch_msignal"])-(data["medianbatch_msignal"])))))) * 2.0)) +
0.050000*np.tanh(np.minimum(((np.where(( 1.77388834953308105)<= -998, data["abs_avgbatch_msignal"], np.sin(( np.where(((data["abs_minbatch_slices2_msignal"])+(data["signal_shift_-1"])) > -998, np.maximum(((np.where(data["signal_shift_-1"] > -998, np.sin(( data["abs_minbatch_slices2_msignal"])) , data["mean_abs_chgbatch_slices2"]))),(( np.sin(( data["abs_minbatch_slices2_msignal"]))))),(( data["rangebatch_msignal"])*(np.sin(( data["rangebatch_msignal"])))))))))) ,(( data["rangebatch_msignal"])))) +
0.050000*np.tanh(np.where(data["minbatch_slices2"] <= -998, np.where(data["signal_shift_+1"] > -998, data["maxtominbatch_msignal"],(((np.cos(( np.where(np.minimum(((data["maxtominbatch_msignal"])) ,(((9.0)))) <= -998, data["mean_abs_chgbatch_slices2"], data["abs_avgbatch_msignal"])))) <=(data["signal_shift_-1"])) *1.)), np.cos(((( np.where(data["maxtominbatch_msignal"] > -998, data["abs_avgbatch_msignal"], data["maxtominbatch_slices2"])) * 2.0)))))+
0.050000*np.tanh(np.sin(( np.maximum(((( 4.23392868041992188))),(( np.where(data["signal_shift_+1"] > -998, data["rangebatch_msignal"],(((np.maximum(((data["rangebatch_msignal"])) ,(( np.where(data["signal_shift_+1"] > -998, data["rangebatch_msignal"],(-(( data["maxbatch_slices2"])))))))) <=(np.cos(( np.tanh(((((((data["signal_shift_-1_msignal"])<=(data["signal_shift_-1"])) *1.))/ 2.0)))))))*1.))))))))+
0.050000*np.tanh(((data["signal_shift_-1"])*(np.where(np.cos(( data["mean_abs_chgbatch_slices2_msignal"])) > -998, np.cos(( data["abs_avgbatch_slices2_msignal"])) , data["minbatch_slices2_msignal"])))) +
0.050000*np.tanh(((data["stdbatch_slices2_msignal"])*(np.cos(( np.where(np.where(data["medianbatch_slices2"] > -998, data["minbatch_msignal"],(((data["maxbatch_slices2_msignal"])+(np.cos(( np.where(data["stdbatch_slices2_msignal"] > -998, np.cos(( data["stdbatch_slices2_msignal"])) , data["minbatch_msignal"])))))/2.0)) > -998, data["minbatch_msignal"], data["meanbatch_slices2"])))))) +
0.050000*np.tanh(((np.cos(((( np.minimum(((data["abs_minbatch_slices2_msignal"])) ,(( np.cos(((( np.minimum(((data["abs_minbatch_slices2_msignal"])) ,(( data["rangebatch_msignal"])))) * 2.0)))))))* 2.0)))) *(np.where(data["maxbatch_slices2_msignal"] > -998,(( data["stdbatch_slices2_msignal"])* 2.0), np.maximum(((np.cos(( data["abs_minbatch_slices2_msignal"])))) ,(( data["minbatch_slices2_msignal"])))))))+
0.050000*np.tanh(((data["medianbatch_slices2"])*(np.cos(((( np.where(data["abs_minbatch_slices2_msignal"] <= -998,(( data["signal_shift_-1_msignal"])/ 2.0), data["maxtominbatch_msignal"])) * 2.0)))))) +
0.050000*np.tanh(((((data["minbatch"])/ 2.0)) *(((np.cos(((( data["maxtominbatch_msignal"])+(data["abs_maxbatch_msignal"])))))* 2.0)))) +
0.050000*np.tanh(((np.sin(((( np.sin(( data["abs_maxbatch_msignal"])))* 2.0)))) *(((data["abs_maxbatch_msignal"])*(np.minimum(((data["rangebatch_msignal"])) ,(( data["minbatch_msignal"])))))))) +
0.050000*np.tanh(((np.where(np.where(data["maxbatch_slices2"] > -998, data["abs_minbatch_slices2_msignal"], data["stdbatch_msignal"])<= -998, data["maxbatch_slices2"], data["maxtominbatch_slices2"])) *(np.maximum(((np.sin(( np.sin(( data["abs_avgbatch_slices2"])))))) ,(( np.sin(( data["minbatch_msignal"])))))))) +
0.050000*np.tanh(((((np.sin(( np.sin(((( np.maximum(((data["maxbatch_msignal"])) ,(( np.sin(((( np.maximum(((data["abs_maxbatch_slices2_msignal"])) ,(((( np.sin(( data["mean_abs_chgbatch_msignal"])))-(((( np.sin(( np.cos(( data["maxtominbatch_msignal"])))))+(((data["abs_maxbatch_slices2_msignal"])+(np.sin(( data["abs_minbatch_slices2_msignal"])))))) /2.0)))))))* 2.0)))))))* 2.0)))))) * 2.0)) * 2.0)) +
0.050000*np.tanh(np.cos(((( np.where(np.maximum(((np.sin(((( data["minbatch_slices2"])/ 2.0))))),(((( data["maxbatch_slices2"])-(data["minbatch_msignal"])))))> -998, data["abs_maxbatch_slices2_msignal"],(( np.sin(((((( data["minbatch_slices2"])* 2.0)) -(data["minbatch_slices2"])))))/ 2.0)))* 2.0)))) +
0.050000*np.tanh(( -(( np.sin(( np.cos(( np.minimum(((((( -(( data["medianbatch_slices2_msignal"])))) -(((data["maxtominbatch"])/ 2.0))))),(((( data["mean_abs_chgbatch_slices2_msignal"])+(np.minimum(((data["maxtominbatch_msignal"])) ,(((((data["minbatch_msignal"])+(((np.sin(( np.cos(( np.minimum(((data["signal"])) ,(((-(((( data["abs_avgbatch_msignal"])-(data["mean_abs_chgbatch_slices2_msignal"])))))))))))))/ 2.0)))/2.0)))))))))))))))))+
0.050000*np.tanh(((((data["meanbatch_msignal"])*(np.maximum(((data["rangebatch_slices2_msignal"])) ,(((( np.sin(( data["maxbatch_msignal"])))*(((np.sin(((( data["rangebatch_msignal"])* 2.0)))) *(((np.sin(( data["maxbatch_msignal"])))* 2.0)))))))))))*(np.sin(( data["maxbatch_msignal"])))))+
0.050000*np.tanh(np.where(np.where(( 3.11168861389160156)<= -998, data["signal_shift_-1_msignal"],(( data["rangebatch_slices2_msignal"])*(np.cos(((( data["mean_abs_chgbatch_slices2_msignal"])* 2.0)))))) <= -998, np.cos(((( data["mean_abs_chgbatch_slices2_msignal"])* 2.0))),(((((14.36763572692871094)) *(np.cos(( np.where(data["abs_avgbatch_msignal"] <= -998, data["rangebatch_slices2_msignal"],(( np.sin(( data["maxtominbatch_msignal"])))* 2.0)))))))* 2.0)))+
0.050000*np.tanh(((((((data["abs_minbatch_slices2_msignal"])*(data["meanbatch_slices2"])))*(np.sin(( np.maximum(((((data["abs_minbatch_slices2_msignal"])*(data["meanbatch_slices2"])))) ,(( data["maxbatch_msignal"])))))))) -(((( data["meanbatch_slices2"])>(data["abs_maxbatch_slices2_msignal"])) *1.))))+
0.050000*np.tanh(np.sin(( np.sin(((( data["abs_minbatch_slices2_msignal"])-(np.cos(((((((data["signal_shift_-1"])<=(np.tanh(( np.tanh(( np.tanh(( data["maxtominbatch_slices2_msignal"])))))))) *1.))* 2.0)))))))))) +
0.050000*np.tanh(((((( -(( np.where(((data["maxtominbatch_slices2_msignal"])*(np.tanh(((( data["stdbatch_msignal"])* 2.0)))))<= -998,(( data["stdbatch_msignal"])* 2.0),(( data["abs_minbatch_msignal"])* 2.0)))))) * 2.0)) *(np.sin(( np.where(np.sin(((( data["stdbatch_msignal"])* 2.0)))<= -998, data["signal_shift_-1_msignal"],(( data["stdbatch_msignal"])* 2.0)))))))+
0.050000*np.tanh(( -(((( np.sin(( data["stdbatch_msignal"])))+(np.where(data["signal_shift_+1"] <= -998,(-(( np.where(data["stdbatch_slices2"] > -998,(((data["stdbatch_slices2"])>(data["minbatch_slices2_msignal"])) *1.) , np.where(data["minbatch_msignal"] <= -998, np.sin(( np.cos(( data["abs_maxbatch_slices2"])))) , data["stdbatch_msignal"]))))),(( data["abs_maxbatch_slices2_msignal"])-(data["signal"])))))))))+
0.050000*np.tanh(np.minimum(((((np.where(( -(((-(( data["abs_minbatch_msignal"])))))) <= -998, data["minbatch_slices2"], np.minimum(((np.sin(( np.where(data["rangebatch_msignal"] <= -998, data["minbatch_slices2"], data["maxbatch_slices2"]))))),(( np.sin(( data["maxtominbatch_slices2"])))))))+(data["rangebatch_msignal"])))) ,(( data["abs_minbatch_msignal"])))) +
0.050000*np.tanh(((np.minimum(((data["maxtominbatch_slices2"])) ,(( data["minbatch_msignal"])))) / 2.0)) +
0.050000*np.tanh(((np.where(np.sin(((( data["maxtominbatch_msignal"])* 2.0)))<= -998, np.tanh(( np.cos(( np.minimum(((data["maxtominbatch_msignal"])) ,(((((((-(( data["abs_avgbatch_slices2_msignal"])))) -(data["maxtominbatch_msignal"])))-(((data["abs_avgbatch_slices2"])* 2.0)))))))))) , np.where(((data["mean_abs_chgbatch_slices2_msignal"])* 2.0)<= -998, data["abs_avgbatch_slices2_msignal"], np.cos(((-(( data["abs_avgbatch_slices2_msignal"])))))))) * 2.0)) +
0.050000*np.tanh(((((np.sin(( np.where(data["medianbatch_msignal"] > -998, data["abs_maxbatch_msignal"], data["maxbatch_msignal"])))) *(data["medianbatch_msignal"])))*(data["rangebatch_slices2_msignal"])))+
0.050000*np.tanh(((np.sin(((( np.where(np.where(data["medianbatch_slices2"] > -998, data["stdbatch_msignal"],(((( np.maximum(((data["abs_minbatch_msignal"])) ,(( data["minbatch"])))) +(data["stdbatch_slices2"])))+(np.where(data["maxbatch_slices2"] > -998, data["stdbatch_msignal"], data["minbatch"])))) > -998,(-(((( data["stdbatch_slices2"])+(data["stdbatch_msignal"]))))),(( data["signal_shift_-1"])+(data["stdbatch_slices2"])))) * 2.0)))) * 2.0)) +
0.050000*np.tanh(((data["abs_minbatch_slices2_msignal"])*(np.cos(((( data["minbatch_msignal"])+(np.sin(((( data["minbatch"])*(( -(( data["maxtominbatch"])))))))))))))) +
0.050000*np.tanh(((data["abs_minbatch_slices2_msignal"])*(np.cos(((( data["abs_maxbatch_msignal"])-(((( np.maximum(((data["maxtominbatch_slices2_msignal"])) ,(( data["mean_abs_chgbatch_slices2"])))) >(((np.where(np.cos(((( data["rangebatch_slices2_msignal"])-(data["abs_minbatch_slices2_msignal"])))) <= -998, np.sin(( data["signal"])) ,(( data["abs_minbatch_slices2_msignal"])*(data["signal"])))) +(data["minbatch_slices2"])))) *1.))))))))+
0.050000*np.tanh(np.where(np.sin(( data["abs_minbatch_msignal"])) > -998,(( data["mean_abs_chgbatch_slices2"])-(((( -(((( data["minbatch_slices2"])*(np.cos(( data["rangebatch_slices2_msignal"])))))))) *(data["stdbatch_msignal"])))) ,(( np.where(data["maxtominbatch"] <= -998, data["abs_minbatch_msignal"],(( np.sin(( data["mean_abs_chgbatch_msignal"])))* 2.0)))+(np.cos(( data["signal_shift_+1"])))))) +
0.050000*np.tanh(np.sin(( np.where(data["abs_minbatch_msignal"] > -998, data["abs_minbatch_msignal"], np.maximum(((data["rangebatch_msignal"])) ,(( np.minimum(((np.sin(( data["abs_minbatch_slices2_msignal"])))) ,(( np.where(np.maximum(((data["abs_maxbatch_msignal"])) ,(( np.sin(( data["maxtominbatch_slices2"])))))<= -998, np.sin(( data["abs_minbatch_msignal"])) , data["abs_minbatch_msignal"])))))))))))+
0.050000*np.tanh(((( -(( np.cos(( np.where(data["abs_minbatch_slices2"] <= -998, data["abs_avgbatch_slices2_msignal"], np.where(np.cos(( np.cos(( np.sin(( data["maxtominbatch_slices2_msignal"])))))) > -998,(-(((( np.where(data["maxtominbatch_slices2_msignal"] <= -998, data["medianbatch_msignal"], data["abs_minbatch_msignal"])) * 2.0)))) , data["maxtominbatch_slices2_msignal"])))))))) * 2.0)) +
0.050000*np.tanh(((np.sin(( data["maxbatch_msignal"])))*(np.where(np.sin(( data["maxbatch_msignal"])) <= -998, np.where(data["abs_minbatch_msignal"] <= -998, np.sin(( data["abs_maxbatch"])) , np.sin(( np.sin(( np.minimum(((np.cos(((( np.sin(( np.sin(( data["maxbatch_msignal"])))))*(data["minbatch_msignal"])))))) ,(( data["signal_shift_-1"])))))))) , data["mean_abs_chgbatch_msignal"])))) +
0.050000*np.tanh(np.sin(( np.where(data["mean_abs_chgbatch_msignal"] <= -998, np.where(np.tanh(( data["abs_minbatch_msignal"])) <= -998, data["abs_maxbatch_slices2_msignal"], np.where(np.where(data["rangebatch_slices2"] <= -998,(( np.where(np.where(data["mean_abs_chgbatch_msignal"] <= -998, data["abs_maxbatch"], data["abs_maxbatch"])<= -998, data["abs_avgbatch_slices2_msignal"], np.minimum(((data["maxbatch_slices2"])) ,(( data["meanbatch_slices2"])))))* 2.0), data["minbatch"])<= -998, data["abs_maxbatch"], data["abs_maxbatch"])) , data["abs_maxbatch"])))) +
0.050000*np.tanh(((data["minbatch"])*(np.where(((( data["minbatch"])<=(data["rangebatch_slices2"])) *1.) <= -998, np.where(data["maxtominbatch_slices2"] <= -998,(( np.where(data["maxbatch_slices2"] <= -998,(( np.where(data["maxbatch_msignal"] <= -998, data["minbatch"], data["meanbatch_msignal"])) +(data["meanbatch_msignal"])) , data["maxbatch_slices2"])) * 2.0), data["maxbatch_msignal"]),(( data["abs_avgbatch_slices2_msignal"])+(data["meanbatch_msignal"])))))) +
0.050000*np.tanh(((data["abs_maxbatch_slices2_msignal"])*(np.tanh(( np.sin(( np.where(np.tanh(( data["minbatch_slices2_msignal"])) > -998, data["abs_minbatch_slices2_msignal"],(( np.cos(( data["maxtominbatch_msignal"])))*(np.tanh(( data["abs_minbatch_slices2_msignal"])))))))))))) +
0.050000*np.tanh(np.where(data["minbatch"] <= -998,(0.0), data["stdbatch_slices2"])) +
0.050000*np.tanh(((((data["minbatch"])/ 2.0)) *(np.maximum(((np.minimum(((data["minbatch_slices2"])) ,(((((( data["minbatch_msignal"])* 2.0)) / 2.0)))))) ,(((( data["signal_shift_+1"])-(np.minimum(((np.where(np.minimum(((data["abs_maxbatch_msignal"])) ,(( data["mean_abs_chgbatch_msignal"])))> -998, np.minimum(((((np.tanh(( data["stdbatch_slices2_msignal"])))* 2.0))),(((-(( data["maxbatch_msignal"])))))) , data["maxtominbatch_slices2"]))),(( data["abs_avgbatch_slices2_msignal"])))))))))))+
0.050000*np.tanh(((np.minimum(((((np.sin(((( data["signal_shift_+1"])/ 2.0)))) -(np.minimum(((data["abs_avgbatch_slices2"])) ,(((((( data["abs_avgbatch_msignal"])* 2.0)) +(np.tanh(((((data["abs_maxbatch_slices2_msignal"])>(data["abs_avgbatch_msignal"])) *1.)))))))))))),(((( data["abs_avgbatch_msignal"])+(np.tanh(((( data["abs_maxbatch"])+(data["minbatch"])))))))))) * 2.0)) +
0.050000*np.tanh(((np.cos(( np.where(np.cos(((( np.cos(( np.where(((((13.23457622528076172)) <=(np.cos(((( data["mean_abs_chgbatch_slices2_msignal"])* 2.0)))))*1.) > -998, data["abs_avgbatch_slices2_msignal"],(-(( np.cos(((( data["mean_abs_chgbatch_slices2_msignal"])* 2.0)))))))))) * 2.0)))> -998,(( data["mean_abs_chgbatch_slices2_msignal"])* 2.0),(13.23457622528076172)))))* 2.0)) +
0.050000*np.tanh(((np.cos(((( data["abs_avgbatch_slices2_msignal"])-(((( data["maxtominbatch_msignal"])>(np.maximum(((((( np.tanh(((((( data["mean_abs_chgbatch_slices2"])-(((( np.tanh(( data["abs_avgbatch_slices2_msignal"])))>(data["medianbatch_slices2_msignal"])) *1.))))* 2.0)))) >(data["maxbatch_slices2_msignal"])) *1.))) ,(( np.cos(((( data["minbatch_slices2"])+(data["abs_avgbatch_slices2_msignal"])))))))))*1.))))))* 2.0)) +
0.050000*np.tanh(((np.where(np.where(((( data["meanbatch_slices2_msignal"])>(((( data["meanbatch_slices2"])>(data["abs_maxbatch_slices2"])) *1.))) *1.) <= -998, data["minbatch_slices2_msignal"], np.sin(((((data["rangebatch_slices2"])>(( 3.0)))*1.))))<= -998, data["abs_maxbatch_slices2_msignal"], np.sin(( data["abs_minbatch_msignal"])))) *(data["abs_maxbatch_slices2"])))+
0.050000*np.tanh(np.cos(( np.minimum(((np.minimum(((data["maxtominbatch_msignal"])) ,(( np.cos(( np.minimum(((np.cos(( data["maxtominbatch_msignal"])))) ,(( data["maxtominbatch_msignal"])))))))))) ,(( np.minimum(((np.minimum(((data["maxtominbatch_msignal"])) ,(( np.tanh(( data["medianbatch_slices2"]))))))),(( np.where(np.cos(( np.minimum(((data["signal"])) ,(( data["maxtominbatch_msignal"])))))> -998, data["medianbatch_msignal"], data["signal_shift_+1"])))))))))) +
0.050000*np.tanh(((data["signal_shift_-1_msignal"])-(np.where(data["maxtominbatch"] > -998, np.where(((data["stdbatch_msignal"])* 2.0)> -998, data["abs_minbatch_msignal"], data["minbatch_slices2_msignal"]), np.minimum(((np.sin(( data["mean_abs_chgbatch_slices2"])))) ,(((( data["signal_shift_-1_msignal"])+(( -(( data["stdbatch_msignal"])))))))))))) +
0.050000*np.tanh(np.sin(((( np.where(((data["meanbatch_msignal"])*(((((((((((np.sin(( data["maxbatch_msignal"])))/ 2.0)) >(((np.where(data["maxbatch_slices2_msignal"] > -998, data["maxbatch_msignal"], data["maxbatch_msignal"])) +(data["abs_minbatch_slices2"])))) *1.))+(data["maxbatch_msignal"])))+(data["minbatch"])) /2.0)))> -998, data["minbatch_msignal"], np.tanh(((( data["abs_minbatch_slices2"])+(data["maxbatch_msignal"])))))) * 2.0)))) +
0.050000*np.tanh(np.where(( -(((( data["minbatch_msignal"])+(data["minbatch_msignal"])))))> -998, np.cos(( data["minbatch"])) , np.sin(((((((np.minimum(((data["abs_avgbatch_slices2_msignal"])) ,(( data["abs_avgbatch_slices2_msignal"])))) +(((((( data["minbatch_slices2_msignal"])*(((data["signal_shift_-1_msignal"])+(data["meanbatch_slices2_msignal"])))))<=(data["abs_minbatch_msignal"])) *1.))))+(np.cos(( data["abs_avgbatch_slices2_msignal"])))) /2.0)))))+
0.050000*np.tanh(np.minimum(((((data["stdbatch_slices2_msignal"])+(data["abs_avgbatch_slices2"])))) ,(((( data["signal_shift_-1"])+(np.where(data["stdbatch_slices2_msignal"] > -998, data["minbatch_slices2"], data["stdbatch_slices2"])))))))+
0.050000*np.tanh(((np.cos(( data["abs_avgbatch_msignal"])))-(np.cos(( np.where(data["abs_avgbatch_slices2_msignal"] > -998, np.sin(( data["abs_avgbatch_msignal"])) , data["signal"])))))) +
0.050000*np.tanh(((np.sin(((( data["rangebatch_msignal"])-(np.sin(( data["abs_maxbatch"])))))))* 2.0)) +
0.050000*np.tanh(np.sin(( np.minimum(((np.where(data["meanbatch_msignal"] > -998, np.sin(( np.minimum(((( -(( data["abs_maxbatch_msignal"]))))),(((-(( np.cos(( np.minimum(((data["abs_minbatch_msignal"])) ,(( np.minimum(((data["maxtominbatch_msignal"])) ,(( data["signal_shift_-1"])))))))))))))))) , data["rangebatch_msignal"]))),(( data["abs_minbatch_slices2_msignal"])))))) +
0.050000*np.tanh(((((data["signal_shift_-1"])-(np.where(np.cos(( data["signal_shift_-1"])) > -998, data["medianbatch_msignal"],(( data["minbatch"])*(data["meanbatch_slices2_msignal"])))))) +(( -(( data["maxbatch_slices2_msignal"])))))) +
0.050000*np.tanh(((np.sin(( np.where(np.sin(( np.where(data["maxtominbatch_slices2_msignal"] <= -998, data["maxbatch_slices2_msignal"], data["abs_minbatch_slices2_msignal"])))<= -998, data["minbatch_slices2"], np.minimum(((data["abs_minbatch_slices2_msignal"])) ,(( np.maximum(((data["maxbatch_slices2_msignal"])) ,(((( data["signal_shift_+1"])* 2.0)))))))))))* 2.0)) +
0.050000*np.tanh(((data["maxtominbatch_slices2_msignal"])*(data["maxtominbatch_slices2_msignal"])))+
0.050000*np.tanh(( -(( np.where(np.where(np.cos(( data["abs_avgbatch_slices2_msignal"])) <= -998, data["maxtominbatch"], data["minbatch_slices2_msignal"])<= -998, np.cos(( np.cos(( data["signal_shift_-1"])))) , data["stdbatch_slices2_msignal"])))))+
0.050000*np.tanh(np.where(np.minimum(((((data["meanbatch_slices2_msignal"])-(data["meanbatch_slices2_msignal"])))) ,(( data["signal_shift_+1_msignal"])))> -998, np.where(data["mean_abs_chgbatch_slices2_msignal"] > -998, np.sin(((( data["abs_avgbatch_msignal"])-(data["signal_shift_-1"])))) ,(( data["abs_avgbatch_msignal"])-(data["signal_shift_-1"]))), np.sin(((-(((( data["signal_shift_-1"])-(data["signal_shift_-1"])))))))))+
0.050000*np.tanh(((np.where(data["mean_abs_chgbatch_slices2_msignal"] > -998, data["maxtominbatch"], data["meanbatch_slices2_msignal"])) * 2.0)) +
0.050000*np.tanh(np.minimum(((np.where(np.cos(( np.minimum(((data["abs_maxbatch_slices2"])) ,(( np.sin(( data["maxbatch_slices2_msignal"])))))))<= -998, data["minbatch"],(( data["maxbatch_slices2_msignal"])-(((data["signal_shift_+1"])/ 2.0)))))) ,(( np.sin(((( np.maximum(((np.sin(( data["stdbatch_msignal"])))) ,(( data["signal_shift_-1"])))) -(((data["maxbatch_slices2_msignal"])-(((np.cos(( np.sin(( data["rangebatch_slices2_msignal"])))))/ 2.0)))))))))))+
0.050000*np.tanh(np.where(((( -(( np.minimum(((data["mean_abs_chgbatch_msignal"])) ,(((13.93050289154052734)))))))) * 2.0)> -998, np.cos(( data["maxtominbatch_msignal"])) , np.where(data["abs_minbatch_slices2_msignal"] > -998, data["abs_minbatch_slices2_msignal"], data["medianbatch_slices2"])))+
0.050000*np.tanh(np.cos(( np.where(data["abs_avgbatch_msignal"] <= -998, np.maximum(((data["abs_avgbatch_msignal"])) ,(( data["stdbatch_slices2"]))), np.where(data["abs_avgbatch_slices2"] > -998, data["abs_avgbatch_msignal"], np.cos(( data["meanbatch_slices2"])))))))+
0.050000*np.tanh(np.cos(((((((data["signal_shift_+1"])* 2.0)) +(np.where(((((data["minbatch_slices2"])-(np.where(data["maxtominbatch"] > -998, data["signal"],(( data["signal_shift_+1"])*(((data["maxtominbatch_slices2"])/ 2.0)))))))* 2.0)> -998, data["signal_shift_+1"], np.tanh(((( data["maxtominbatch"])*(((((( data["signal_shift_+1"])* 2.0)) +(data["signal"])) /2.0)))))))) /2.0)))) +
0.050000*np.tanh(((np.minimum(((((data["maxtominbatch_slices2"])-(np.sin(( np.maximum(((data["maxbatch_slices2_msignal"])) ,(( data["minbatch_msignal"]))))))))),(( data["signal_shift_-1"])))) +(np.minimum(((np.where(data["abs_maxbatch"] > -998, np.maximum(((data["signal_shift_-1"])) ,(( data["signal_shift_-1"]))),(( data["maxtominbatch_slices2"])-(np.sin(( data["abs_maxbatch_slices2_msignal"]))))))),(( np.maximum(((data["maxbatch_slices2_msignal"])) ,(( data["maxbatch_slices2_msignal"])))))))))+
0.050000*np.tanh(np.sin(( np.where(data["signal_shift_+1"] <= -998, data["signal_shift_+1_msignal"], np.sin(((( np.sin(( data["mean_abs_chgbatch_msignal"])))+(data["minbatch_slices2"])))))))) +
0.050000*np.tanh(((((np.sin(( np.where(((data["meanbatch_msignal"])* 2.0)<= -998,(( data["mean_abs_chgbatch_slices2_msignal"])+(data["mean_abs_chgbatch_slices2"])) , np.where(np.cos(( data["minbatch_slices2_msignal"])) <= -998, np.maximum(((((data["signal_shift_+1"])-(data["meanbatch_slices2_msignal"])))) ,(( data["mean_abs_chgbatch_slices2"]))),(-(((( data["signal_shift_+1"])-(np.cos(( data["minbatch_msignal"])))))))))))) * 2.0)) * 2.0)) +
0.050000*np.tanh(np.sin(((-(( np.where(((data["maxtominbatch_msignal"])*(((((( np.tanh(( np.minimum(((data["rangebatch_slices2"])) ,(( np.where(data["mean_abs_chgbatch_msignal"] > -998, data["abs_maxbatch"], data["maxtominbatch_slices2_msignal"])))))))+(np.minimum(((data["signal_shift_-1"])) ,(( data["maxbatch_slices2"])))))) >(np.tanh(( data["signal_shift_-1"])))) *1.))) > -998, data["maxtominbatch_slices2_msignal"], data["medianbatch_slices2"])))))))+
0.050000*np.tanh(((data["signal_shift_-1"])-(((data["maxbatch_msignal"])*(((((((((( np.maximum(((((( data["stdbatch_slices2_msignal"])>(data["abs_maxbatch_slices2_msignal"])) *1.))) ,(( np.sin(( data["signal_shift_-1"])))))) +(data["maxtominbatch_slices2_msignal"])))*(data["signal_shift_-1"])))+(data["rangebatch_msignal"])))>(data["rangebatch_msignal"])) *1.))))))+
0.050000*np.tanh(((np.sin(( data["abs_avgbatch_slices2_msignal"])))*(data["signal_shift_-1_msignal"])))+
0.050000*np.tanh(((np.where(data["meanbatch_slices2"] > -998, np.where(((np.where(data["maxtominbatch_msignal"] > -998, data["minbatch_slices2_msignal"], data["signal"])) * 2.0)> -998, data["minbatch_slices2_msignal"],(( data["minbatch_slices2_msignal"])/ 2.0)) , np.sin(( np.cos(( data["maxtominbatch_msignal"])))))) +(((data["signal"])*(((( np.sin(( np.cos(( data["maxtominbatch_msignal"])))))+(data["maxbatch_msignal"])) /2.0)))))) +
0.050000*np.tanh(((data["minbatch_slices2_msignal"])*(np.maximum(((((data["medianbatch_msignal"])/ 2.0))),(((((( data["abs_minbatch_slices2"])* 2.0)) +(((((( data["minbatch_msignal"])+(( -(((( data["minbatch_msignal"])*(((data["minbatch_slices2"])/ 2.0)))))))) /2.0)) -(((( data["medianbatch_msignal"])<=(data["abs_minbatch_slices2"])) *1.))))))))))) +
0.050000*np.tanh(np.minimum(((data["signal_shift_-1_msignal"])) ,(((( np.where(data["signal_shift_+1_msignal"] <= -998, data["minbatch"], np.minimum(((((np.minimum(((data["maxbatch_msignal"])) ,(( data["maxbatch_slices2_msignal"])))) *(data["rangebatch_msignal"])))) ,(( data["signal_shift_-1_msignal"])))))* 2.0)))))+
0.050000*np.tanh(((np.tanh(((( data["minbatch_slices2"])+(np.where(data["stdbatch_slices2"] > -998, data["abs_minbatch_msignal"], np.cos(( data["abs_minbatch_msignal"])))))))) -(((np.sin(((( np.cos(( data["mean_abs_chgbatch_slices2_msignal"])))* 2.0)))) * 2.0)))) +
0.050000*np.tanh(np.where(data["signal"] <= -998,(((( -(( data["minbatch"])))) +(( 1.68646967411041260)))/2.0),(((( data["abs_avgbatch_slices2_msignal"])*(data["medianbatch_msignal"])))*(data["maxtominbatch_slices2"])))) +
0.050000*np.tanh(np.minimum(((data["abs_maxbatch_msignal"])) ,(((( np.minimum(((np.sin(((( data["signal"])+(((( np.maximum(((np.tanh(( data["abs_avgbatch_slices2"])))) ,(((( data["signal_shift_+1"])/ 2.0)))))+(data["signal_shift_+1"])) /2.0))))))),(((( np.minimum(((data["signal_shift_-1"])) ,(((((( data["signal_shift_+1"])/ 2.0)) * 2.0)))))-(np.tanh(( data["stdbatch_slices2"])))))))) * 2.0)))))+
0.050000*np.tanh(( -(( data["abs_minbatch_msignal"])))) +
0.050000*np.tanh(((np.sin(((((np.minimum(((data["maxtominbatch_msignal"])) ,(( np.minimum(((((data["minbatch_slices2"])/ 2.0))),(( data["meanbatch_slices2_msignal"])))))))+(data["minbatch_slices2_msignal"])) /2.0)))) -(data["rangebatch_slices2_msignal"])))+
0.050000*np.tanh(((data["medianbatch_msignal"])*(((((( data["signal_shift_-1"])+(data["signal_shift_-1"])))+(((data["medianbatch_slices2"])-(np.maximum(((data["medianbatch_msignal"])) ,(((( data["abs_maxbatch_slices2_msignal"])*(((( np.maximum(((((data["maxbatch_slices2_msignal"])-(data["abs_minbatch_slices2_msignal"])))) ,(((( data["abs_maxbatch_slices2_msignal"])*(((data["medianbatch_msignal"])*(data["maxbatch_slices2_msignal"])))))))) +(data["maxbatch_msignal"])) /2.0)))))))))) /2.0)))) +
0.050000*np.tanh(np.sin(( np.where(np.tanh(( data["abs_minbatch_slices2"])) > -998, data["signal_shift_-1_msignal"], np.tanh(( np.where(data["signal"] > -998, data["abs_minbatch_slices2"], data["abs_minbatch_msignal"])))))))+
0.050000*np.tanh(((data["minbatch_slices2_msignal"])*(np.cos(((((( data["minbatch"])-(np.maximum(((((np.where(((((( data["abs_minbatch_slices2_msignal"])>(data["minbatch"])) *1.))*(data["minbatch_slices2_msignal"])) <= -998, data["minbatch"], data["stdbatch_slices2"])) / 2.0))),(((((data["minbatch_slices2_msignal"])>(( -(( data["signal_shift_+1"])))))*1.))))))) -(data["signal_shift_+1"])))))))+
0.050000*np.tanh(((((data["maxtominbatch_msignal"])*(np.cos(( data["minbatch_msignal"])))))*(np.where(np.maximum(((((data["signal"])*(((( data["mean_abs_chgbatch_msignal"])<=(np.where(data["mean_abs_chgbatch_slices2_msignal"] <= -998, data["signal_shift_+1"], data["abs_maxbatch_msignal"])))*1.))))) ,(( data["minbatch"])))<= -998, data["maxbatch_slices2"], data["signal_shift_+1"])))) +
0.050000*np.tanh(np.where(np.cos(( data["abs_avgbatch_msignal"])) <= -998, data["abs_avgbatch_msignal"], np.sin(( np.maximum(((data["abs_avgbatch_msignal"])) ,(( data["mean_abs_chgbatch_slices2"])))))))+
0.050000*np.tanh(((((data["maxbatch_slices2_msignal"])-(((( data["signal_shift_-1"])+(np.where(data["abs_maxbatch_slices2"] > -998,(((data["signal"])>(( 2.0)))*1.) , data["mean_abs_chgbatch_slices2_msignal"])))/2.0)))) *(data["meanbatch_slices2"])))+
0.050000*np.tanh(((((((np.sin(( data["abs_minbatch_msignal"])))*(data["abs_maxbatch_msignal"])))+(data["stdbatch_slices2_msignal"])))+(np.tanh(( np.sin(((((((data["signal_shift_+1"])/ 2.0)) <=(((( data["abs_maxbatch_msignal"])+(( 6.15981245040893555)))/2.0)))*1.))))))))+
0.050000*np.tanh(((np.where(data["minbatch_slices2"] > -998, data["signal_shift_+1"], np.where(np.where(data["signal"] <= -998, np.tanh(( data["minbatch_slices2"])) , data["abs_minbatch_slices2"])<= -998, data["minbatch_slices2"], np.maximum(((data["abs_maxbatch_msignal"])) ,(( data["abs_maxbatch"])))))) +(data["minbatch_slices2"])))+
0.050000*np.tanh(((( data["medianbatch_slices2_msignal"])+(((data["maxbatch_slices2_msignal"])*(np.where(np.minimum(((((data["abs_maxbatch_slices2"])-(data["signal_shift_-1_msignal"])))) ,(((-(((((data["minbatch_slices2"])<=(np.sin(( data["medianbatch_slices2_msignal"])))) *1.))))))) <= -998, data["maxbatch_slices2_msignal"], np.sin(( np.minimum(((data["abs_maxbatch_slices2"])) ,(( data["abs_minbatch_slices2_msignal"])))))))))) /2.0)) +
0.050000*np.tanh(( -(( np.maximum(((np.sin(( data["signal_shift_-1"])))) ,(((( data["abs_avgbatch_slices2_msignal"])-(np.sin(((((-(( np.maximum(((( -(( np.minimum(((data["maxtominbatch"])) ,(((-(((((((data["signal_shift_-1_msignal"])-(data["abs_avgbatch_slices2_msignal"])))+(np.tanh(((( data["signal_shift_-1"])* 2.0)))))/2.0)))))))))))) ,(( data["maxtominbatch"])))))))*(( 5.0)))))))))))))) +
0.050000*np.tanh(np.minimum(((((data["meanbatch_msignal"])-(data["abs_maxbatch"])))) ,(( np.cos(( data["signal_shift_-1"])))))) +
0.050000*np.tanh(np.where(data["signal_shift_-1"] > -998,(( np.sin(((-(((( data["signal_shift_-1"])-(data["maxtominbatch_msignal"])))))))) * 2.0),(-(((( data["signal_shift_-1"])-(data["maxtominbatch_msignal"])))))))+
0.050000*np.tanh(np.sin(((( data["signal_shift_-1_msignal"])-(np.where(((( data["abs_maxbatch_slices2"])>(np.sin(((( data["meanbatch_slices2"])+(data["signal_shift_-1"])))))) *1.) > -998, data["maxbatch_msignal"], np.where(np.sin(( np.minimum(((data["abs_maxbatch_slices2"])) ,(((((data["abs_maxbatch_slices2"])>(data["abs_maxbatch_msignal"])) *1.))))))<= -998,(( data["rangebatch_slices2_msignal"])-(data["rangebatch_slices2_msignal"])) , data["stdbatch_slices2"])))))))+
0.050000*np.tanh(((((data["signal"])*(data["abs_minbatch_slices2_msignal"])))*(np.cos(( np.where(data["maxtominbatch"] <= -998, data["abs_minbatch_slices2_msignal"],(((data["abs_maxbatch_msignal"])+(np.cos(( np.where(((( data["abs_avgbatch_msignal"])<=(data["maxtominbatch"])) *1.) <= -998, data["abs_maxbatch_msignal"],(((data["signal_shift_+1"])+(data["stdbatch_msignal"])) /2.0)))))) /2.0)))))))+
0.050000*np.tanh(np.sin(( np.where(( -(((( data["mean_abs_chgbatch_slices2"])* 2.0)))) > -998, data["abs_maxbatch"],(((data["mean_abs_chgbatch_slices2"])<=(data["maxtominbatch_msignal"])) *1.))))) +
0.050000*np.tanh(data["mean_abs_chgbatch_msignal"])+
0.050000*np.tanh(np.cos(( np.sin(( np.cos(( data["abs_maxbatch_slices2_msignal"])))))))+
0.050000*np.tanh(((np.sin(((((((-(( data["abs_maxbatch_slices2_msignal"])))) * 2.0)) * 2.0)))) *(((( 4.24157476425170898)) *(np.minimum(((data["abs_maxbatch"])) ,(((((( data["abs_maxbatch_slices2_msignal"])+(((( data["medianbatch_msignal"])<=(np.tanh(( data["medianbatch_msignal"])))) *1.))))-(((data["medianbatch_msignal"])*(np.sin(( data["medianbatch_msignal"])))))))))))))) +
0.050000*np.tanh(np.where(np.where(((data["signal_shift_-1"])*(data["abs_avgbatch_slices2_msignal"])) <= -998, data["mean_abs_chgbatch_slices2"], data["signal_shift_-1"])<= -998, np.where(data["minbatch_slices2_msignal"] <= -998, data["minbatch_slices2_msignal"],(( data["maxbatch_slices2_msignal"])/ 2.0)) ,(( data["minbatch_slices2"])*(np.cos(( data["signal_shift_-1"])))))) +
0.050000*np.tanh(( -(((3.67669796943664551)))))+
0.050000*np.tanh(np.sin(((((data["abs_maxbatch_slices2"])+(np.maximum(((data["mean_abs_chgbatch_msignal"])) ,(( np.where(data["abs_maxbatch"] > -998,(( data["signal_shift_+1"])-(data["mean_abs_chgbatch_slices2_msignal"])) ,(((((np.where(data["signal"] > -998, data["stdbatch_slices2"], data["stdbatch_msignal"])) >(data["mean_abs_chgbatch_slices2_msignal"])) *1.))-(data["mean_abs_chgbatch_msignal"])))))))) /2.0)))) +
0.050000*np.tanh(np.where(((data["mean_abs_chgbatch_slices2"])*(data["signal_shift_+1"])) <= -998, data["signal_shift_-1_msignal"], data["signal_shift_+1"])) +
0.050000*np.tanh(((data["maxbatch_slices2"])*(np.sin(( np.where(np.where(data["signal_shift_+1"] > -998,(( data["abs_avgbatch_slices2_msignal"])-(data["abs_avgbatch_slices2_msignal"])) , data["abs_avgbatch_slices2"])<= -998, data["minbatch_slices2_msignal"],(( data["abs_avgbatch_slices2_msignal"])-(np.where(data["signal_shift_-1"] <= -998, data["mean_abs_chgbatch_msignal"], data["signal_shift_+1"])))))))))+
0.050000*np.tanh(np.where(((data["minbatch_msignal"])* 2.0)<= -998, data["stdbatch_slices2"], np.minimum(((np.minimum(((data["rangebatch_msignal"])) ,(( np.minimum(((data["maxtominbatch_msignal"])) ,(( data["minbatch"])))))))) ,(( np.tanh(( data["minbatch_slices2"])))))))+
0.050000*np.tanh(np.sin(( np.where(data["signal_shift_-1"] > -998, np.sin(( np.tanh(( np.sin(( np.sin(( np.where(np.sin(( np.sin(( data["signal_shift_-1_msignal"])))) > -998, data["abs_maxbatch"], np.where(data["stdbatch_msignal"] > -998, np.sin(((( data["abs_maxbatch"])+(data["abs_maxbatch"])))) , data["mean_abs_chgbatch_msignal"])))))))))) , data["meanbatch_slices2"])))) +
0.050000*np.tanh(((data["abs_avgbatch_slices2_msignal"])*(((data["signal_shift_-1_msignal"])*(((np.where(np.sin(( np.where(np.sin(( data["signal_shift_-1"])) > -998, data["abs_minbatch_slices2"], data["abs_avgbatch_slices2_msignal"])))> -998, data["abs_minbatch_slices2"], data["meanbatch_slices2"])) +(((np.sin(((( data["abs_maxbatch"])-(((( data["abs_maxbatch_msignal"])>(data["abs_maxbatch_slices2_msignal"])) *1.))))))* 2.0)))))))) +
0.050000*np.tanh(((np.sin(((( np.maximum(((data["abs_maxbatch_msignal"])) ,(((( np.sin(( data["abs_minbatch_slices2_msignal"])))*(data["abs_maxbatch_msignal"])))))) *(data["abs_avgbatch_slices2_msignal"])))))*(np.where(( 9.0)<= -998,(( data["abs_maxbatch"])-(data["abs_maxbatch_msignal"])) , data["stdbatch_slices2"])))) +
0.050000*np.tanh(((np.tanh(( np.minimum(((data["signal"])) ,(( np.minimum(((data["maxbatch_msignal"])) ,(( np.where(((((data["medianbatch_msignal"])-(data["maxtominbatch_slices2"])))* 2.0)<= -998,(((((((( data["medianbatch_msignal"])-(data["maxtominbatch_slices2"])))* 2.0)) -(data["minbatch_slices2"])))* 2.0),(((( data["medianbatch_msignal"])-(data["maxtominbatch_slices2"])))* 2.0)))))))))))* 2.0)) +
0.050000*np.tanh(((data["signal"])*(np.cos(((-(( np.minimum(((data["maxtominbatch_msignal"])) ,(( np.sin(((((4.57688331604003906)) -(data["maxtominbatch_msignal"])))))))))))))))+
0.050000*np.tanh(((np.cos(( data["abs_avgbatch_msignal"])))*(((( 8.0)) -(((((data["maxtominbatch_msignal"])-(np.sin(((( data["abs_minbatch_slices2_msignal"])* 2.0)))))) +(( -(((-(( data["maxbatch_slices2_msignal"])))))))))))))+
0.050000*np.tanh(((np.maximum(((data["abs_avgbatch_msignal"])) ,(((8.78546714782714844)))))*(np.sin(((( np.where(np.where(np.sin(((( data["abs_avgbatch_slices2_msignal"])*(data["abs_maxbatch_slices2_msignal"])))) > -998, data["abs_maxbatch"], data["abs_avgbatch_slices2_msignal"])<= -998, data["minbatch_slices2_msignal"], np.where(data["stdbatch_slices2"] > -998, data["meanbatch_slices2"], np.minimum(((((data["abs_avgbatch_slices2_msignal"])*(data["abs_maxbatch_slices2_msignal"])))) ,(( data["abs_maxbatch_slices2_msignal"])))))) *(data["abs_avgbatch_slices2_msignal"])))))))+
0.050000*np.tanh(np.sin(( np.maximum(((data["abs_maxbatch"])) ,(((( data["abs_maxbatch_msignal"])/ 2.0)))))))+
0.050000*np.tanh(np.minimum(((np.tanh(( np.where(data["rangebatch_slices2_msignal"] > -998, np.where(np.sin(( np.where(data["abs_maxbatch"] > -998, data["mean_abs_chgbatch_slices2"], np.sin(( data["abs_maxbatch"])))))<= -998, data["signal_shift_+1_msignal"],(((data["abs_maxbatch"])+(data["rangebatch_slices2_msignal"])) /2.0)) ,(((( data["signal_shift_+1"])/ 2.0)) * 2.0)))))) ,(( np.sin(( data["abs_maxbatch"])))))) +
0.050000*np.tanh(((np.where(data["meanbatch_slices2_msignal"] > -998, data["signal_shift_-1"], data["abs_maxbatch"])) +(data["maxbatch_slices2"])))+
0.050000*np.tanh(np.minimum(((np.minimum(((np.where(np.maximum(((data["signal_shift_-1_msignal"])) ,(((((( -(( data["medianbatch_msignal"])))) +(data["abs_minbatch_slices2_msignal"])) /2.0)))) > -998, data["meanbatch_slices2_msignal"], np.where(data["minbatch_msignal"] > -998, data["meanbatch_slices2_msignal"], data["minbatch_msignal"])))) ,(((-(( np.where(data["meanbatch_slices2_msignal"] <= -998, data["medianbatch_slices2"], data["meanbatch_slices2_msignal"]))))))))),(( data["abs_minbatch_slices2"])))) +
0.050000*np.tanh(np.sin(( np.minimum(((np.minimum(((((data["signal_shift_-1"])* 2.0))),(( data["abs_minbatch_slices2_msignal"]))))),(((( data["signal_shift_+1"])/ 2.0)))))))+
0.050000*np.tanh(((( np.minimum(((((( data["abs_avgbatch_msignal"])<=(data["minbatch_msignal"])) *1.))) ,(((((data["meanbatch_slices2"])>(data["abs_minbatch_slices2"])) *1.))))) <=(( -(( data["meanbatch_msignal"])))))*1.))+
0.050000*np.tanh(np.where(np.minimum(((data["minbatch_msignal"])) ,(( np.tanh(((-(( data["abs_maxbatch_slices2"])))))))) > -998, data["medianbatch_slices2_msignal"], data["minbatch"])) +
0.050000*np.tanh(((( -(((( np.maximum(((data["stdbatch_slices2"])) ,(((((( np.sin(((( data["maxbatch_msignal"])* 2.0)))) * 2.0)) * 2.0)))))-(data["minbatch_msignal"])))))) *(np.sin(((( data["maxbatch_msignal"])* 2.0)))))) +
0.050000*np.tanh(np.minimum(((np.cos(((((data["signal_shift_-1"])+(np.maximum(((np.minimum(((( -(((( data["stdbatch_msignal"])-(data["signal_shift_-1_msignal"]))))))),(( np.minimum(((data["meanbatch_slices2"])) ,(( data["meanbatch_slices2"])))))))) ,(((( data["signal"])* 2.0)))))) /2.0))))),(( data["abs_maxbatch"])))) +
0.050000*np.tanh(np.where(data["medianbatch_slices2"] > -998, np.sin(((-(( np.sin(( data["minbatch"]))))))), np.cos(( data["abs_avgbatch_slices2_msignal"])))) +
0.050000*np.tanh(np.sin(( np.minimum(((np.maximum(((data["meanbatch_msignal"])) ,(( data["abs_maxbatch"]))))),(((((( np.where(data["mean_abs_chgbatch_slices2"] <= -998, data["abs_minbatch_slices2"],(-(( np.where(data["minbatch"] > -998, data["abs_maxbatch_slices2_msignal"], data["signal_shift_-1"])))))) * 2.0)) * 2.0)))))))+
0.050000*np.tanh(np.cos(( np.where(((data["abs_maxbatch_slices2"])-(np.cos(( data["abs_avgbatch_msignal"])))) > -998, data["abs_avgbatch_msignal"], data["rangebatch_slices2_msignal"])))) +
0.050000*np.tanh(((np.minimum(((((((( np.sin(( data["stdbatch_slices2_msignal"])))<=(data["signal_shift_+1_msignal"])) *1.))*(np.sin(( data["medianbatch_slices2_msignal"])))))) ,(((-(( np.cos(( data["signal_shift_+1"])))))))))* 2.0)) +
0.050000*np.tanh(np.where(data["abs_avgbatch_slices2"] > -998, data["signal_shift_+1"],(((((( data["stdbatch_slices2"])+(data["signal_shift_+1"])) /2.0)) <=(data["maxbatch_slices2_msignal"])) *1.))) +
0.050000*np.tanh(((np.sin(((( data["rangebatch_slices2"])+(((np.sin(((9.0)))) -(((np.where(((((( np.tanh(((12.98753833770751953)))) -(data["maxtominbatch"])))<=(np.tanh(( data["rangebatch_slices2"])))) *1.) <= -998, data["signal_shift_-1"], data["abs_maxbatch_msignal"])) *(np.tanh(( data["meanbatch_slices2"])))))))))))* 2.0)) +
0.050000*np.tanh(((np.minimum(((data["abs_avgbatch_slices2_msignal"])) ,(( np.where(((data["minbatch_slices2_msignal"])*(data["minbatch_slices2_msignal"])) <= -998,(( np.where(data["abs_avgbatch_slices2_msignal"] <= -998,(6.0), data["abs_avgbatch_msignal"])) *(data["abs_avgbatch_slices2_msignal"])) , np.where(data["abs_avgbatch_slices2_msignal"] <= -998, data["signal"], np.sin(( np.sin(( data["abs_minbatch_slices2_msignal"])))))))))) *(((( 6.0)) *(data["signal"])))))+
0.050000*np.tanh(((np.where(np.where(data["maxtominbatch_slices2"] > -998, data["abs_minbatch_slices2_msignal"],(((((np.sin(( np.sin(( np.sin(( np.tanh(((-(((((8.85292625427246094)) * 2.0)))))))))))))+(np.minimum(((data["abs_avgbatch_slices2_msignal"])) ,(( data["abs_avgbatch_slices2_msignal"])))))/2.0)) *(data["abs_minbatch_slices2_msignal"])))<= -998, data["signal_shift_+1"],(( np.sin(( data["abs_maxbatch_slices2"])))* 2.0)))* 2.0)) +
0.050000*np.tanh(np.where(np.minimum(((np.minimum(((((data["medianbatch_slices2_msignal"])* 2.0))),(( data["medianbatch_slices2_msignal"]))))),(( data["rangebatch_slices2"])))<= -998, data["medianbatch_slices2_msignal"], data["meanbatch_slices2_msignal"])) +
0.050000*np.tanh(np.cos(( np.where(((((((((data["abs_minbatch_msignal"])>(data["maxbatch_slices2"])) *1.))*(((np.sin(( data["minbatch_msignal"])))* 2.0)))) +(data["mean_abs_chgbatch_msignal"])) /2.0)> -998,(( data["minbatch_msignal"])* 2.0), np.sin(( data["minbatch_msignal"])))))) +
0.050000*np.tanh(np.where(data["abs_maxbatch_slices2"] > -998, data["signal_shift_-1"], np.sin(( data["abs_maxbatch_slices2"])))) +
0.050000*np.tanh(np.where(data["abs_avgbatch_slices2_msignal"] <= -998, np.tanh(( np.minimum(((data["meanbatch_slices2_msignal"])) ,(((((( data["meanbatch_slices2_msignal"])*(data["abs_avgbatch_slices2"])))/ 2.0)))))) , np.sin(((((data["abs_avgbatch_slices2"])+(data["abs_minbatch_msignal"])) /2.0)))))+
0.050000*np.tanh(((data["maxbatch_slices2_msignal"])-(((( data["signal_shift_+1"])>(((data["signal_shift_+1"])/ 2.0)))*1.))))+
0.050000*np.tanh(np.sin(((((( data["signal"])+(data["signal_shift_-1"])))-(((( np.cos(( np.where(data["rangebatch_slices2"] > -998,(((data["signal"])+(np.sin(( data["signal_shift_-1"])))) /2.0), data["maxbatch_slices2_msignal"])))) <=(((data["signal"])+(data["signal_shift_-1"])))) *1.))))))+
0.050000*np.tanh(np.cos(((( np.maximum(((data["meanbatch_slices2"])) ,(( data["meanbatch_slices2"])))) -(data["stdbatch_msignal"])))))+
0.050000*np.tanh(( -(( np.cos(( np.where(data["meanbatch_slices2_msignal"] > -998, data["minbatch_msignal"], data["abs_avgbatch_slices2_msignal"])))))))+
0.050000*np.tanh(((np.where(data["medianbatch_slices2"] <= -998, np.sin(( data["meanbatch_slices2_msignal"])) ,(((( np.sin(( data["meanbatch_slices2_msignal"])))+(np.cos(( np.sin(( data["maxtominbatch_slices2_msignal"])))))))*(data["signal_shift_-1_msignal"])))) *(data["signal"])))+
0.050000*np.tanh(((np.minimum(((np.sin(( data["mean_abs_chgbatch_slices2_msignal"])))) ,(( np.minimum(((data["meanbatch_msignal"])) ,(( np.sin(( np.cos(((((data["mean_abs_chgbatch_slices2_msignal"])+(((( data["maxtominbatch_slices2"])+(data["stdbatch_msignal"])) /2.0)))/2.0)))))))))))) -(((np.minimum(((data["meanbatch_slices2"])) ,(( np.sin(( data["signal_shift_+1"])))))) * 2.0)))) +
0.050000*np.tanh(np.sin(((( np.sin(( data["meanbatch_msignal"])))*(((( np.sin(((((((data["abs_avgbatch_msignal"])/ 2.0)) +(np.where(((( data["mean_abs_chgbatch_slices2"])+(np.sin(( np.sin(( data["minbatch"])))))) /2.0)> -998, data["maxtominbatch_slices2"], np.sin(((-(( np.minimum(((data["signal_shift_+1"])) ,(( data["meanbatch_msignal"])))))))))))/2.0)))) +(data["signal_shift_-1_msignal"])) /2.0)))))) +
0.050000*np.tanh(np.sin(( np.sin(((( data["meanbatch_slices2"])-(np.minimum(((data["abs_minbatch_msignal"])) ,(( data["abs_minbatch_msignal"])))))))))) +
0.050000*np.tanh(np.cos(((( data["medianbatch_slices2"])-(np.where(((data["medianbatch_slices2"])+(data["abs_avgbatch_msignal"])) > -998, data["minbatch_msignal"], np.minimum(((data["medianbatch_msignal"])) ,(((-(( np.minimum(((((data["medianbatch_slices2"])*(np.minimum(((data["medianbatch_msignal"])) ,(( data["medianbatch_slices2"]))))))),(( np.minimum(((data["abs_maxbatch_msignal"])) ,(( data["maxbatch_msignal"])))))))))))))))))) +
0.050000*np.tanh(((np.cos(((( np.minimum(((np.where(data["mean_abs_chgbatch_slices2"] > -998, data["medianbatch_slices2"], data["maxbatch_msignal"]))),(( np.minimum(((data["meanbatch_slices2_msignal"])) ,(( data["meanbatch_slices2_msignal"])))))))*(np.where(np.maximum(((data["rangebatch_slices2_msignal"])) ,(( data["medianbatch_slices2"])))> -998, np.maximum(((data["mean_abs_chgbatch_slices2"])) ,(( data["medianbatch_slices2"]))), np.cos(( np.tanh(( data["abs_maxbatch"])))))))))) * 2.0)) +
0.050000*np.tanh(np.tanh(( np.where(np.minimum(((np.minimum(((np.tanh(( data["meanbatch_slices2_msignal"])))) ,(( data["minbatch_slices2_msignal"]))))),(( data["stdbatch_slices2_msignal"])))> -998, np.tanh(( data["maxtominbatch"])) , np.minimum(((data["meanbatch_slices2_msignal"])) ,(( data["meanbatch_slices2_msignal"])))))))+
0.050000*np.tanh(np.sin(((3.0)))) +
0.050000*np.tanh(np.where(data["abs_avgbatch_slices2"] > -998, np.sin(( data["abs_maxbatch"])) , data["maxtominbatch_slices2_msignal"])) +
0.050000*np.tanh(((((((((data["medianbatch_msignal"])-(np.sin(( np.tanh(( data["medianbatch_msignal"])))))))<=(((np.cos(((((data["minbatch_slices2_msignal"])>(np.tanh(( data["stdbatch_slices2"])))) *1.))))*(((( data["mean_abs_chgbatch_slices2"])+(data["signal"])) /2.0)))))*1.))+(np.cos(( data["maxtominbatch_msignal"])))) /2.0)) +
0.050000*np.tanh(np.minimum(((data["meanbatch_msignal"])) ,(( data["signal"])))) +
0.050000*np.tanh(np.minimum(((data["signal_shift_-1"])) ,(( np.maximum(((((data["signal_shift_+1"])* 2.0))),(( np.minimum(((data["stdbatch_slices2"])) ,(((((((data["abs_minbatch_msignal"])/ 2.0)) >(data["abs_avgbatch_slices2_msignal"])) *1.))))))))))) +
0.050000*np.tanh(( -(((((data["abs_avgbatch_msignal"])>(data["signal_shift_+1"])) *1.))))) +
0.050000*np.tanh(((data["abs_maxbatch_slices2"])+(np.where(((( data["maxbatch_slices2"])+(data["abs_maxbatch_slices2"])) /2.0)<= -998,(((data["abs_maxbatch"])<=(data["maxtominbatch_msignal"])) *1.) ,(-(( np.maximum(((( 7.0))),(((((data["maxbatch_slices2"])+(data["mean_abs_chgbatch_msignal"])) /2.0)))))))))))+
0.050000*np.tanh(np.tanh(( data["meanbatch_slices2_msignal"])))+
0.050000*np.tanh(np.where(data["signal_shift_-1"] <= -998, np.where(data["signal_shift_-1"] <= -998, data["maxbatch_slices2"], np.sin(( np.where(data["meanbatch_slices2_msignal"] > -998, data["abs_maxbatch"],(( data["stdbatch_slices2"])* 2.0))))), np.sin(( np.where(np.sin(( data["abs_maxbatch"])) > -998, data["abs_maxbatch"],(( data["maxtominbatch_slices2"])* 2.0)))))))
 def GP_class_9(self,data):
return self.Output(-3.603840 +
0.050000*np.tanh(np.where(data["meanbatch_msignal"] <= -998, np.minimum(((( -(((((-(( data["stdbatch_msignal"])))) * 2.0)))))) ,(( data["signal_shift_+1"]))),(-(( data["stdbatch_msignal"])))))+
0.050000*np.tanh(((data["stdbatch_msignal"])*(data["minbatch_msignal"])))+
0.050000*np.tanh(((((data["signal"])-(data["medianbatch_slices2_msignal"])))-(((data["maxbatch_msignal"])+(data["meanbatch_slices2"])))))+
0.050000*np.tanh(np.where(np.tanh(((((((data["medianbatch_slices2"])/ 2.0)) >(data["rangebatch_msignal"])) *1.))) > -998, data["signal"], data["mean_abs_chgbatch_msignal"])) +
0.050000*np.tanh(np.tanh(( np.where(data["signal"] > -998,(-(( data["abs_avgbatch_slices2_msignal"]))),(((((data["signal_shift_+1"])-(((( data["maxbatch_slices2"])>(data["abs_avgbatch_slices2"])) *1.))))+(((np.cos(( data["signal"])))+(((np.cos(( data["signal"])))+(np.tanh(( data["signal_shift_+1"])))))))) /2.0)))))+
0.050000*np.tanh(((data["medianbatch_slices2"])*(((( data["rangebatch_msignal"])+(np.maximum(((np.minimum(((data["abs_maxbatch"])) ,(((( data["signal_shift_+1"])+(data["minbatch_msignal"]))))))),(( np.minimum(((( 4.0))),(( np.where(data["maxbatch_slices2_msignal"] <= -998, data["medianbatch_slices2"], np.minimum(((data["maxbatch_slices2"])) ,(( data["abs_minbatch_msignal"])))))))))))) /2.0)))) +
0.050000*np.tanh(np.where(data["signal_shift_+1"] > -998, data["medianbatch_slices2"], data["signal_shift_+1"])) +
0.050000*np.tanh(((np.where(data["stdbatch_slices2"] > -998, data["abs_avgbatch_msignal"], np.maximum(((data["abs_avgbatch_msignal"])) ,(((-(( np.cos(((((data["rangebatch_slices2"])>(data["maxtominbatch_msignal"])) *1.))))))))))) *(np.minimum(((data["minbatch"])) ,(((((data["medianbatch_slices2"])+(((((( data["minbatch_slices2"])-(np.cos(( data["minbatch"])))))+(data["abs_avgbatch_msignal"])) /2.0)))/2.0)))))))+
0.050000*np.tanh(((((( np.where(np.where(data["meanbatch_slices2"] <= -998, data["meanbatch_msignal"],(( data["signal"])-(((data["rangebatch_msignal"])/ 2.0)))) > -998, data["meanbatch_slices2"],(((data["meanbatch_slices2"])<=(((data["abs_maxbatch_slices2"])-(data["maxtominbatch_msignal"])))) *1.))) +(data["signal"])) /2.0)) -(np.sin(( data["medianbatch_msignal"])))))+
0.050000*np.tanh(np.minimum(((np.where(data["signal"] > -998, data["signal_shift_-1"], data["signal_shift_+1_msignal"]))),(((( np.where(((((data["maxbatch_slices2_msignal"])*(np.minimum(((( -(( data["maxtominbatch"]))))),(( data["meanbatch_slices2"])))))) / 2.0)> -998,(((data["signal"])<=(data["abs_maxbatch"])) *1.) ,(( np.where(data["rangebatch_slices2"] <= -998,(( data["signal_shift_-1"])-(data["abs_avgbatch_msignal"])) , data["signal"])) / 2.0)))* 2.0)))))+
0.050000*np.tanh(((data["signal_shift_-1_msignal"])-(data["stdbatch_msignal"])))+
0.050000*np.tanh(np.minimum(((((((data["rangebatch_msignal"])-(data["abs_maxbatch_slices2"])))*(data["abs_avgbatch_msignal"])))) ,(((-(( np.minimum(((( -(( np.where(data["rangebatch_slices2"] > -998, data["meanbatch_msignal"], data["signal"])))))) ,(( np.minimum(((data["abs_avgbatch_msignal"])) ,(( data["abs_avgbatch_msignal"])))))))))))))+
0.050000*np.tanh(((((data["signal"])-(np.maximum(((np.where(data["signal"] > -998, data["signal_shift_+1"], np.cos(( data["signal"]))))),(((-(( np.where(data["maxtominbatch"] > -998, data["abs_avgbatch_slices2_msignal"], np.sin(( data["signal_shift_-1"])))))))))))) / 2.0)) +
0.050000*np.tanh(((((data["maxbatch_slices2"])* 2.0)) +(np.cos(((6.0)))))) +
0.050000*np.tanh(np.where(((((( data["abs_maxbatch_msignal"])<=(((np.sin(( data["stdbatch_slices2"])))* 2.0)))*1.))* 2.0)<= -998, np.sin(((( np.where(data["abs_minbatch_slices2_msignal"] <= -998,(((( data["signal"])-(data["maxbatch_msignal"])))* 2.0),(( data["minbatch_msignal"])* 2.0)))*(data["signal_shift_-1"])))) ,(( data["minbatch_slices2"])-(np.where(data["mean_abs_chgbatch_msignal"] > -998, data["maxtominbatch_slices2_msignal"], data["signal_shift_-1"])))))+
0.050000*np.tanh(np.maximum(((((data["signal_shift_-1_msignal"])+(((data["maxbatch_slices2"])-(np.where(data["meanbatch_slices2"] > -998, data["mean_abs_chgbatch_msignal"],(12.20609951019287109)))))))) ,(( np.minimum(((data["maxtominbatch_slices2"])) ,(((((( -(( data["maxbatch_slices2"])))) <=(( -(((((data["meanbatch_slices2"])<=(np.sin(((-(( data["signal_shift_-1_msignal"])))))))*1.))))))*1.))))))))+
0.050000*np.tanh(( -(( np.where(( -(((((-(( np.where(( -(( data["minbatch_slices2_msignal"])))> -998, data["abs_avgbatch_msignal"], np.where(data["maxtominbatch_slices2"] > -998, np.where(data["abs_minbatch_msignal"] > -998, data["abs_avgbatch_msignal"], data["signal"]), np.where(((data["minbatch_slices2_msignal"])-(data["signal"])) <= -998, data["maxbatch_msignal"], data["meanbatch_slices2"])))))))* 2.0)))) > -998, data["abs_avgbatch_msignal"], data["abs_avgbatch_msignal"])))))+
0.050000*np.tanh(np.where(np.sin(( data["maxtominbatch_msignal"])) <= -998,(( data["maxbatch_slices2"])/ 2.0), data["medianbatch_slices2"])) +
0.050000*np.tanh(data["signal_shift_+1"])+
0.050000*np.tanh(np.where(data["meanbatch_slices2"] <= -998, data["meanbatch_msignal"],(((-(((((data["minbatch"])>(data["meanbatch_slices2_msignal"])) *1.))))) -(((data["abs_avgbatch_slices2_msignal"])* 2.0)))))+
0.050000*np.tanh(((np.minimum(((data["minbatch_slices2"])) ,(( data["maxtominbatch_slices2_msignal"])))) *(np.cos(( np.where(data["maxtominbatch"] > -998, data["meanbatch_slices2_msignal"],(((-(( data["signal_shift_+1_msignal"])))) *(data["abs_minbatch_slices2_msignal"])))))))) +
0.050000*np.tanh(((((((np.sin(( data["maxbatch_slices2_msignal"])))<=(( -(( data["medianbatch_msignal"])))))*1.))<=(((data["signal_shift_+1_msignal"])*(data["medianbatch_msignal"])))) *1.))+
0.050000*np.tanh(( -(( np.where(data["maxtominbatch_slices2_msignal"] <= -998, np.minimum(((data["minbatch_msignal"])) ,(( np.cos(( data["medianbatch_slices2_msignal"]))))),(( data["abs_minbatch_slices2_msignal"])*(np.sin(( data["mean_abs_chgbatch_msignal"])))))))))+
0.050000*np.tanh(((data["abs_avgbatch_msignal"])*(np.minimum(((data["abs_avgbatch_msignal"])) ,(((((((((data["minbatch"])+(data["maxtominbatch"])) /2.0)) *(data["medianbatch_msignal"])))-(np.maximum(((np.where(data["maxbatch_slices2_msignal"] > -998,(((((( data["stdbatch_slices2"])>(data["maxtominbatch"])) *1.))>(data["minbatch"])) *1.) , data["abs_avgbatch_slices2"]))),(( data["rangebatch_slices2_msignal"])))))))))))+
0.050000*np.tanh(((data["minbatch_msignal"])*(np.sin(( data["signal"])))))+
0.050000*np.tanh(((( -(( data["abs_avgbatch_slices2_msignal"])))) -(((((( data["abs_avgbatch_slices2_msignal"])/ 2.0)) +(np.cos(((((-(( data["rangebatch_msignal"])))) -(((( data["minbatch_slices2_msignal"])+(data["signal_shift_-1"])) /2.0)))))))/2.0)))) +
0.050000*np.tanh(np.where(np.sin(( data["abs_avgbatch_slices2"])) <= -998, data["abs_avgbatch_slices2"], np.sin(( data["maxbatch_slices2"])))) +
0.050000*np.tanh(((data["signal_shift_+1"])-(((((((np.tanh(((((((((np.sin(( data["mean_abs_chgbatch_slices2_msignal"])))* 2.0)) *(np.where(data["medianbatch_slices2_msignal"] > -998, data["signal"],(( data["signal"])-(data["abs_maxbatch"])))))) <=(((data["abs_maxbatch_msignal"])-(((((0.31871804594993591)) <=(data["abs_maxbatch"])) *1.))))) *1.))))* 2.0)) *(data["abs_maxbatch"])))* 2.0)))) +
0.050000*np.tanh(((data["signal_shift_+1"])-(((data["abs_avgbatch_slices2_msignal"])+(data["signal_shift_-1"])))))+
0.050000*np.tanh(( -(((( data["abs_avgbatch_msignal"])-(((np.tanh(((( data["abs_avgbatch_msignal"])-(((np.tanh(((( data["minbatch_slices2"])*(((((((data["maxbatch_slices2"])/ 2.0)) / 2.0)) -(np.sin(( np.sin(( data["abs_maxbatch_slices2"])))))))))))/ 2.0)))))) / 2.0)))))))+
0.050000*np.tanh(data["signal"])+
0.050000*np.tanh(np.where(((((( data["abs_maxbatch"])>(((((data["abs_avgbatch_msignal"])/ 2.0)) +(data["abs_avgbatch_slices2_msignal"])))) *1.))* 2.0)> -998, np.where(data["medianbatch_msignal"] > -998,(-(( data["abs_avgbatch_msignal"]))), np.where(np.where(data["meanbatch_slices2_msignal"] > -998, data["mean_abs_chgbatch_msignal"], data["meanbatch_msignal"])<= -998, np.where(data["meanbatch_msignal"] <= -998, data["rangebatch_slices2"], np.cos(( data["medianbatch_msignal"]))), data["maxtominbatch_slices2"])) , data["stdbatch_slices2"])) +
0.050000*np.tanh(np.sin(( np.where(np.sin(( np.where(((( np.sin(( data["mean_abs_chgbatch_msignal"])))<=(data["medianbatch_msignal"])) *1.) > -998, data["mean_abs_chgbatch_msignal"], data["abs_maxbatch_slices2_msignal"])))<= -998,(((data["medianbatch_msignal"])+(np.cos(( np.cos(( data["medianbatch_slices2"])))))) /2.0), data["mean_abs_chgbatch_msignal"])))) +
0.050000*np.tanh(data["signal_shift_+1"])+
0.050000*np.tanh(( -(( data["medianbatch_msignal"])))) +
0.050000*np.tanh(np.minimum(((data["signal_shift_-1"])) ,(( np.where(data["minbatch"] <= -998,(((np.where(data["abs_avgbatch_slices2_msignal"] <= -998,(-(( data["abs_avgbatch_slices2_msignal"]))),(((data["abs_avgbatch_slices2_msignal"])>(data["medianbatch_slices2"])) *1.))) >(data["medianbatch_slices2"])) *1.) ,(( data["abs_avgbatch_slices2_msignal"])*(data["abs_minbatch_msignal"])))))))+
0.050000*np.tanh(((data["signal_shift_+1"])*(np.sin(( np.where(data["abs_minbatch_msignal"] > -998, data["abs_maxbatch_slices2_msignal"], data["rangebatch_slices2_msignal"])))))) +
0.050000*np.tanh(((data["minbatch"])+(( -(((-(( np.where(((data["minbatch"])-(((((( data["abs_maxbatch_msignal"])-(data["minbatch"])))<=(data["abs_minbatch_slices2_msignal"])) *1.))) > -998, data["signal"], data["abs_maxbatch"])))))))))) +
0.050000*np.tanh(np.where(( 10.0)> -998, np.cos(( data["abs_minbatch_slices2_msignal"])) , np.cos(( np.sin(( np.where(data["maxbatch_slices2"] > -998, data["stdbatch_msignal"], np.sin(( np.cos(( data["abs_avgbatch_msignal"])))))))))))+
0.050000*np.tanh(((np.cos(( np.maximum(((data["medianbatch_slices2_msignal"])) ,(( data["stdbatch_msignal"])))))) *(((((((( -(((((data["stdbatch_msignal"])+(( -(((( data["maxbatch_msignal"])/ 2.0)))))) /2.0)))))<=(data["maxbatch_msignal"])) *1.))+(data["mean_abs_chgbatch_msignal"])) /2.0)))) +
0.050000*np.tanh(((( -(( np.where(data["rangebatch_slices2_msignal"] > -998, data["abs_avgbatch_msignal"],(-(( np.where(((data["rangebatch_msignal"])+(((( data["abs_maxbatch_msignal"])>(np.where(data["abs_maxbatch_slices2_msignal"] > -998, data["abs_avgbatch_slices2_msignal"], np.minimum(((np.where(data["minbatch_slices2_msignal"] > -998,(((data["stdbatch_slices2_msignal"])>(data["minbatch_slices2"])) *1.) , data["abs_avgbatch_msignal"]))),(( data["rangebatch_msignal"])))))) *1.))) > -998, data["maxbatch_slices2_msignal"], data["abs_avgbatch_msignal"])))))))))* 2.0)) +
0.050000*np.tanh(np.where(data["stdbatch_slices2"] <= -998, data["maxtominbatch_slices2_msignal"],(((((( data["minbatch_msignal"])* 2.0)) +(((( np.cos(((( data["maxtominbatch_slices2_msignal"])/ 2.0)))) +(((data["abs_avgbatch_msignal"])* 2.0)))/2.0)))) *(np.cos(( data["meanbatch_msignal"])))))) +
0.050000*np.tanh(((np.where(data["maxbatch_slices2_msignal"] <= -998,(( data["abs_avgbatch_slices2_msignal"])*(data["maxbatch_slices2_msignal"])) , data["minbatch_slices2"])) +(((np.sin(( np.where(np.maximum(((data["signal_shift_-1"])) ,(( np.where(data["stdbatch_slices2"] > -998, data["maxbatch_slices2_msignal"], data["mean_abs_chgbatch_msignal"])))) > -998, data["maxbatch_msignal"], np.sin(( data["mean_abs_chgbatch_msignal"])))))) -(((data["abs_avgbatch_slices2_msignal"])*(data["maxbatch_slices2_msignal"])))))))+
0.050000*np.tanh(((np.where(np.where(np.cos(( np.minimum(((data["abs_avgbatch_msignal"])) ,(((( data["mean_abs_chgbatch_slices2"])*(data["meanbatch_slices2_msignal"])))))))> -998, data["medianbatch_slices2_msignal"], data["meanbatch_msignal"])> -998,(( data["abs_avgbatch_slices2_msignal"])*(data["minbatch"])) ,(((-(( data["meanbatch_msignal"])))) -(data["signal_shift_+1"])))) +(((( data["medianbatch_msignal"])+(np.sin(( data["medianbatch_msignal"])))) /2.0)))) +
0.050000*np.tanh(np.sin(((((-(( np.where(((data["maxtominbatch_slices2"])-(data["abs_avgbatch_msignal"])) <= -998,(( np.minimum(((( 8.0))),(( data["signal_shift_+1_msignal"])))) +(data["maxtominbatch_slices2"])) , data["abs_avgbatch_slices2_msignal"])))))*(((((-(((-(( data["abs_avgbatch_msignal"])))))))>(data["medianbatch_msignal"])) *1.))))))+
0.050000*np.tanh(((np.where(((( np.where(data["mean_abs_chgbatch_slices2_msignal"] > -998, data["mean_abs_chgbatch_slices2_msignal"], data["minbatch_msignal"])) >(((data["mean_abs_chgbatch_slices2_msignal"])/ 2.0)))*1.) <= -998, np.sin(( data["mean_abs_chgbatch_slices2_msignal"])) ,(( np.sin(( np.where(( 11.62695693969726562)> -998, data["mean_abs_chgbatch_slices2_msignal"],(-(( data["maxbatch_msignal"])))))))* 2.0)))* 2.0)) +
0.050000*np.tanh(((np.where(data["minbatch"] <= -998,(( data["minbatch_msignal"])/ 2.0),(-(( data["abs_avgbatch_msignal"])))))-(((( data["medianbatch_msignal"])>(np.tanh(((( np.where(data["abs_maxbatch_msignal"] <= -998,(3.0),(-(( data["abs_avgbatch_msignal"])))))*(data["minbatch_msignal"])))))) *1.))))+
0.050000*np.tanh(((np.where(data["abs_minbatch_slices2_msignal"] <= -998,(((( data["maxbatch_msignal"])+(((np.where(np.where(data["mean_abs_chgbatch_slices2"] <= -998, np.maximum(((((data["maxtominbatch_slices2"])* 2.0))),(( data["abs_maxbatch_slices2_msignal"]))), data["abs_maxbatch_slices2"])> -998,(( data["abs_minbatch_slices2_msignal"])-(data["abs_avgbatch_slices2"])) , data["abs_maxbatch"])) / 2.0)))) / 2.0), np.cos(( data["abs_minbatch_slices2_msignal"])))) * 2.0)) +
0.050000*np.tanh(((( data["minbatch"])+(np.where(((data["mean_abs_chgbatch_msignal"])*(((( data["minbatch"])+(((data["medianbatch_msignal"])*(data["abs_minbatch_slices2_msignal"])))) /2.0)))> -998,(( data["stdbatch_msignal"])*(data["stdbatch_msignal"])) , data["medianbatch_msignal"])))/2.0)) +
0.050000*np.tanh(np.where(data["abs_minbatch_slices2_msignal"] <= -998, np.where(data["abs_maxbatch_slices2_msignal"] <= -998,(((( np.cos(( data["signal"])))* 2.0)) *(( -(((((data["abs_maxbatch_msignal"])<=(np.maximum(((data["signal"])) ,(((((7.0)) +(data["signal"])))))))*1.)))))),(( np.cos(( data["signal_shift_-1_msignal"])))* 2.0)) ,(( np.cos(( data["signal"])))* 2.0)))+
0.050000*np.tanh(((data["minbatch"])*(np.where(np.sin(( data["rangebatch_slices2_msignal"])) <= -998, data["stdbatch_msignal"], np.cos(( data["meanbatch_msignal"])))))) +
0.050000*np.tanh(((data["abs_maxbatch"])-(np.where(data["maxbatch_slices2_msignal"] > -998, np.where(((( -(( data["abs_maxbatch"])))) +(data["signal"])) > -998, data["rangebatch_msignal"], data["maxbatch_slices2"]), data["meanbatch_slices2"])))) +
0.050000*np.tanh(np.where(np.where(np.sin(( data["stdbatch_slices2_msignal"])) <= -998, np.sin(( np.minimum(((np.cos(((((( np.sin(( data["stdbatch_slices2_msignal"])))* 2.0)) +(np.sin(( data["meanbatch_slices2"])))))))) ,(( data["mean_abs_chgbatch_msignal"]))))), np.tanh(( np.sin(( np.minimum(((data["rangebatch_msignal"])) ,(( data["mean_abs_chgbatch_msignal"])))))))) <= -998, data["stdbatch_slices2_msignal"],(( np.sin(( np.sin(( data["stdbatch_slices2_msignal"])))))* 2.0)))+
0.050000*np.tanh(np.sin(( np.where(((( data["meanbatch_slices2"])+(np.sin(( np.minimum(((data["stdbatch_msignal"])) ,(( np.sin(( np.where(( 6.0)> -998, data["mean_abs_chgbatch_msignal"],(( data["rangebatch_slices2_msignal"])-(data["signal"])))))))))))) /2.0)> -998, data["mean_abs_chgbatch_msignal"], data["abs_maxbatch"])))) +
0.050000*np.tanh(((data["minbatch"])+(np.where(np.sin(((( data["minbatch"])+(np.where(data["abs_maxbatch_slices2"] > -998, data["signal"], data["minbatch"])))))> -998, np.maximum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(( data["signal"]))),(((( data["minbatch"])+(data["minbatch"])))/ 2.0)))))+
0.050000*np.tanh(np.sin(( np.sin(((((( np.sin(((((data["abs_maxbatch_msignal"])+(np.maximum(((data["maxbatch_slices2"])) ,(( data["medianbatch_slices2"])))))/2.0)))) / 2.0)) / 2.0)))))) +
0.050000*np.tanh(( -(((( data["signal"])*(np.cos(( np.minimum(((((((-(((( data["maxbatch_slices2_msignal"])* 2.0)))))>(((( data["abs_maxbatch_msignal"])>(((( np.where(np.sin(( data["maxbatch_slices2_msignal"])) > -998, data["abs_maxbatch_slices2"], data["maxbatch_msignal"])) +(data["maxbatch_slices2"])) /2.0)))*1.))) *1.))) ,(( data["minbatch_msignal"])))))))))))+
0.050000*np.tanh(np.where(np.minimum(((np.sin(( data["stdbatch_slices2_msignal"])))) ,(((((0.67998307943344116)) +(np.sin(( data["stdbatch_slices2_msignal"])))))))> -998,(( np.sin(( data["stdbatch_slices2_msignal"])))* 2.0), np.sin(( np.sin(( data["stdbatch_slices2_msignal"])))))) +
0.050000*np.tanh(((np.sin(( data["mean_abs_chgbatch_slices2_msignal"])))*(np.where(np.sin(( data["mean_abs_chgbatch_slices2_msignal"])) > -998,(2.0), np.where(( -(( np.where(( 2.0)> -998, np.where(np.sin(( data["mean_abs_chgbatch_slices2_msignal"])) > -998,(2.0),(( data["abs_maxbatch_slices2"])/ 2.0)) , data["maxbatch_slices2_msignal"])))) > -998, data["maxbatch_slices2_msignal"], data["abs_avgbatch_msignal"])))))+
0.050000*np.tanh(((( -(( np.where(np.cos(((( data["maxtominbatch"])* 2.0)))<= -998,(-(( data["abs_maxbatch_slices2"]))),(( np.minimum(((np.cos(( data["abs_maxbatch_slices2_msignal"])))) ,(( np.cos(( np.maximum(((np.maximum(((np.tanh(( data["abs_avgbatch_slices2_msignal"])))) ,(( data["abs_maxbatch_slices2"]))))),(( data["meanbatch_slices2_msignal"])))))))))+(((data["abs_avgbatch_slices2_msignal"])*(data["signal_shift_-1"])))))))))+(data["minbatch"])))+
0.050000*np.tanh(((np.sin(( data["mean_abs_chgbatch_slices2_msignal"])))* 2.0)) +
0.050000*np.tanh(((data["minbatch_slices2_msignal"])-(((data["medianbatch_slices2"])*(np.minimum(((data["stdbatch_msignal"])) ,(((( data["abs_maxbatch_slices2_msignal"])+(data["abs_maxbatch_slices2_msignal"])))))))))) +
0.050000*np.tanh(((np.minimum(((np.where(np.where(data["rangebatch_slices2_msignal"] <= -998, data["minbatch_msignal"], data["abs_maxbatch_msignal"])<= -998,(-(((( np.sin(( data["mean_abs_chgbatch_msignal"])))* 2.0)))) , np.cos(( data["signal"]))))),(( np.where(np.where(data["rangebatch_slices2_msignal"] <= -998, data["minbatch_slices2_msignal"], np.tanh(( data["signal_shift_+1"])))<= -998, data["mean_abs_chgbatch_msignal"], np.cos(( data["signal"])))))))* 2.0)) +
0.050000*np.tanh(np.minimum(((((data["signal"])* 2.0))),(( np.where(data["medianbatch_msignal"] > -998, np.sin(( data["mean_abs_chgbatch_slices2_msignal"])) ,(( data["rangebatch_msignal"])+(((data["maxtominbatch_slices2"])-(np.where(((data["maxbatch_slices2"])/ 2.0)<= -998, data["maxtominbatch_slices2_msignal"], data["mean_abs_chgbatch_slices2_msignal"])))))))))) +
0.050000*np.tanh(np.minimum(((np.sin(( np.where(data["maxbatch_slices2"] <= -998, data["mean_abs_chgbatch_msignal"], np.sin(( np.where(np.tanh(( np.tanh(( data["maxbatch_msignal"])))) <= -998,(3.0), data["mean_abs_chgbatch_slices2_msignal"])))))))) ,(( data["maxbatch_msignal"])))) +
0.050000*np.tanh(((np.sin(( data["stdbatch_slices2_msignal"])))*(np.where(np.sin(((( np.sin(( np.sin(( data["stdbatch_slices2_msignal"])))))*(np.where(data["abs_avgbatch_msignal"] <= -998, np.sin(( np.minimum(((data["rangebatch_slices2"])) ,(( data["abs_avgbatch_msignal"]))))), data["signal_shift_-1"])))))<= -998,(( data["stdbatch_slices2_msignal"])/ 2.0), data["signal_shift_-1"])))) +
0.050000*np.tanh(((((np.sin(( np.where(data["rangebatch_msignal"] <= -998, np.tanh(( np.tanh(( data["mean_abs_chgbatch_slices2_msignal"])))) , data["mean_abs_chgbatch_slices2_msignal"])))) * 2.0)) * 2.0)) +
0.050000*np.tanh(np.where(((np.where(data["mean_abs_chgbatch_slices2"] > -998, data["signal"],(( np.cos(( data["abs_minbatch_slices2_msignal"])))* 2.0)))*(np.sin(( np.sin(( data["signal_shift_-1"])))))) <= -998,(-(( data["abs_maxbatch_slices2_msignal"]))),(( data["signal"])*(np.cos(( data["abs_minbatch_slices2_msignal"])))))) +
0.050000*np.tanh(np.where(data["minbatch_slices2"] > -998,(( data["minbatch_slices2"])+(data["signal_shift_+1"])) ,(((np.minimum(((data["medianbatch_slices2"])) ,(( data["meanbatch_slices2"])))) >(np.where(((data["maxbatch_slices2_msignal"])+(((data["medianbatch_msignal"])+(( 4.0)))))<= -998, data["maxbatch_slices2"], data["meanbatch_slices2"])))*1.))) +
0.050000*np.tanh(((((-(( data["abs_avgbatch_slices2_msignal"])))) +(np.tanh(( data["maxbatch_slices2"])))) /2.0)) +
0.050000*np.tanh(((np.where(((data["mean_abs_chgbatch_slices2_msignal"])* 2.0)<= -998,(5.0), np.sin(((( np.maximum(((data["stdbatch_msignal"])) ,(( np.cos(( data["abs_minbatch_msignal"])))))) * 2.0)))))* 2.0)) +
0.050000*np.tanh(((np.maximum(((( 10.0))),(( data["mean_abs_chgbatch_slices2_msignal"])))) *(np.sin(( data["stdbatch_msignal"])))))+
0.050000*np.tanh(data["signal"])+
0.050000*np.tanh(((np.sin(( np.minimum(((((((((( np.sin(( np.tanh(((( np.sin(( data["maxbatch_slices2"])))* 2.0)))))) >(data["abs_maxbatch"])) *1.))/ 2.0)) *(((np.tanh(( data["stdbatch_msignal"])))*(data["maxtominbatch"])))))) ,(( data["minbatch_slices2"])))))) +(((np.sin(( np.sin(( data["mean_abs_chgbatch_slices2_msignal"])))))* 2.0)))) +
0.050000*np.tanh(np.where(data["rangebatch_msignal"] > -998, np.tanh(( data["maxtominbatch"])) , np.sin(((( data["rangebatch_msignal"])*(( -(( np.maximum(((np.cos(( np.where(np.sin(( np.minimum(((( -(( data["maxtominbatch_msignal"]))))),(( data["signal"])))))<= -998, np.cos(( data["maxtominbatch_msignal"])) , data["abs_maxbatch_slices2"]))))),(((( data["maxtominbatch"])+(data["signal"])))))))))))))) +
0.050000*np.tanh(( -(( np.sin(( np.where(((data["maxtominbatch_slices2_msignal"])*(np.where(((data["stdbatch_msignal"])*(np.sin(( data["maxtominbatch"])))) <= -998, np.sin(( data["signal_shift_+1"])) ,(( data["signal_shift_-1"])* 2.0)))) <= -998, np.sin(((( data["abs_maxbatch"])/ 2.0))),(( data["abs_maxbatch_slices2_msignal"])* 2.0)))))))) +
0.050000*np.tanh(((((((np.tanh(( data["abs_minbatch_slices2"])))-(np.maximum(((data["medianbatch_slices2"])) ,(( np.tanh(((( data["minbatch_slices2_msignal"])*(data["medianbatch_msignal"])))))))))) * 2.0)) *(np.sin(((( data["maxtominbatch"])*(np.minimum(((data["medianbatch_msignal"])) ,(((((( np.sin(( data["medianbatch_msignal"])))+(data["rangebatch_msignal"])))+(data["maxtominbatch"])))))))))))) +
0.050000*np.tanh(((((((((data["abs_maxbatch_msignal"])+(np.cos(( data["signal"])))))*(( -(( np.sin(( data["mean_abs_chgbatch_msignal"])))))))) *(((data["mean_abs_chgbatch_slices2_msignal"])/ 2.0)))) -(data["maxbatch_slices2_msignal"])))+
0.050000*np.tanh(((data["mean_abs_chgbatch_msignal"])*(np.sin(( np.sin(( np.maximum(((np.maximum(((data["signal"])) ,(( np.sin(( np.sin(( np.maximum(((data["signal"])) ,(( np.sin(( np.minimum(((data["stdbatch_slices2"])) ,(( data["minbatch_msignal"]))))))))))))))))),(((((( data["meanbatch_msignal"])*(np.maximum(((data["signal"])) ,(((( data["abs_avgbatch_slices2_msignal"])* 2.0)))))))+(np.sin(( data["rangebatch_slices2_msignal"])))))))))))))) +
0.050000*np.tanh(((np.sin(((( np.where(data["abs_minbatch_slices2_msignal"] > -998, np.where(data["abs_minbatch_slices2_msignal"] > -998,(-(( data["stdbatch_slices2_msignal"]))), data["rangebatch_slices2_msignal"]), data["maxtominbatch"])) * 2.0)))) *(data["medianbatch_slices2"])))+
0.050000*np.tanh(np.sin(( np.where(np.cos(( data["maxbatch_slices2"])) > -998, data["stdbatch_slices2_msignal"], np.cos(((( data["signal_shift_+1_msignal"])/ 2.0)))))))+
0.050000*np.tanh(((( -(((((((np.tanh(( data["rangebatch_slices2"])))<=(data["meanbatch_slices2_msignal"])) *1.))+(((((( data["signal"])<=(np.tanh(( data["rangebatch_slices2"])))) *1.))* 2.0)))))))-(((np.cos(( data["minbatch_msignal"])))* 2.0)))) +
0.050000*np.tanh(((( data["signal_shift_+1"])+(np.where(( -(((((data["signal_shift_+1_msignal"])<=(((( data["mean_abs_chgbatch_slices2"])>(data["rangebatch_slices2_msignal"])) *1.))) *1.))))<= -998,(((-(( data["abs_maxbatch_slices2_msignal"])))) +(data["meanbatch_msignal"])) ,(((-(( np.cos(((((((np.tanh(( data["abs_maxbatch"])))/ 2.0)) >(data["rangebatch_slices2"])) *1.))))))) * 2.0)))) /2.0)) +
0.050000*np.tanh(((np.sin(((-(( np.cos(((( np.where(data["signal_shift_+1_msignal"] > -998, data["mean_abs_chgbatch_slices2_msignal"], np.sin(( np.sin(( data["minbatch_slices2"])))))) * 2.0)))))))))*(data["rangebatch_msignal"])))+
0.050000*np.tanh(((np.where(data["mean_abs_chgbatch_slices2_msignal"] > -998, np.sin(( data["abs_minbatch_slices2_msignal"])) ,(( np.maximum(((( -(( np.sin(( np.maximum(((( -(( np.sin(( np.maximum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(( data["meanbatch_slices2_msignal"])))))))))) ,(( data["rangebatch_msignal"])))))))))) ,(( data["minbatch_slices2_msignal"])))) * 2.0)))*(data["signal_shift_-1"])))+
0.050000*np.tanh(( -(((((((((data["minbatch_slices2_msignal"])/ 2.0)) +(((((((np.maximum(((data["maxtominbatch_slices2_msignal"])) ,(( data["stdbatch_slices2"])))) +(( -(( np.maximum(((((( data["stdbatch_slices2_msignal"])+(np.cos(( data["abs_minbatch_slices2_msignal"])))) /2.0))),(( data["stdbatch_slices2"])))))))) /2.0)) +(np.sin(( data["abs_minbatch_msignal"])))) /2.0)))) <=(data["minbatch_slices2"])) *1.))))) +
0.050000*np.tanh(((np.where(data["minbatch"] <= -998,(( data["minbatch"])* 2.0), data["minbatch"])) *(( -(( np.sin(( np.sin(((( data["meanbatch_msignal"])* 2.0)))))))))))+
0.050000*np.tanh(((data["signal_shift_-1"])*(np.sin(((((( data["abs_minbatch_slices2_msignal"])* 2.0)) -(np.where(data["abs_avgbatch_slices2_msignal"] <= -998, np.minimum(((((np.sin(( data["abs_minbatch_slices2"])))-(np.sin(( data["abs_minbatch_slices2_msignal"])))))) ,(( data["abs_minbatch_slices2"]))), np.where(data["meanbatch_slices2"] <= -998,(( data["abs_minbatch_msignal"])* 2.0), np.sin(( data["abs_minbatch_slices2"])))))))))))+
0.050000*np.tanh(np.sin(((( data["abs_minbatch_slices2_msignal"])+(np.where(((data["abs_minbatch_slices2_msignal"])+(data["minbatch"])) <= -998, np.maximum(((data["abs_minbatch_msignal"])) ,(((( data["mean_abs_chgbatch_msignal"])*(data["rangebatch_slices2"]))))), data["abs_minbatch_msignal"])))))) +
0.050000*np.tanh(((((((data["abs_minbatch_slices2"])-(data["rangebatch_msignal"])))-(((((((data["meanbatch_slices2"])-(data["rangebatch_msignal"])))* 2.0)) *(np.sin(( np.sin(( data["rangebatch_msignal"])))))))))*(np.cos(( data["abs_maxbatch_slices2_msignal"])))))+
0.050000*np.tanh(((np.sin(( data["rangebatch_msignal"])))*(((data["maxbatch_msignal"])-(np.where(np.sin(( np.minimum(((data["minbatch"])) ,(( data["stdbatch_slices2"])))))> -998, np.where(data["minbatch_slices2_msignal"] <= -998, np.cos(( np.sin(((-(( data["maxbatch_slices2"]))))))), data["minbatch"]), data["stdbatch_slices2_msignal"])))))) +
0.050000*np.tanh(( -(( np.where(data["maxbatch_slices2_msignal"] <= -998, np.maximum(((np.minimum(((data["maxbatch_slices2_msignal"])) ,(( data["minbatch_msignal"]))))),(( data["meanbatch_slices2_msignal"]))), np.sin(((( data["maxbatch_slices2_msignal"])* 2.0)))))))) +
0.050000*np.tanh(((np.sin(((((-(((-(( data["meanbatch_slices2_msignal"])))))))+(((data["signal"])*(np.sin(((( data["mean_abs_chgbatch_msignal"])*(data["mean_abs_chgbatch_msignal"])))))))))))+(((data["minbatch_msignal"])+(((data["signal"])*(data["abs_maxbatch_msignal"])))))))+
0.050000*np.tanh(((np.sin(((( data["abs_minbatch_slices2_msignal"])* 2.0)))) * 2.0)) +
0.050000*np.tanh(np.sin(( np.where(data["abs_minbatch_slices2_msignal"] <= -998, data["minbatch_slices2_msignal"],(( np.sin(( data["abs_minbatch_msignal"])))* 2.0)))))+
0.050000*np.tanh(np.cos(((( data["stdbatch_slices2_msignal"])+(np.where(data["minbatch"] > -998, data["meanbatch_msignal"],(((( np.sin(( data["meanbatch_msignal"])))*(np.cos(((( data["stdbatch_msignal"])+(np.where(data["minbatch_slices2_msignal"] > -998, data["minbatch"], data["mean_abs_chgbatch_msignal"])))))))) * 2.0)))))))+
0.050000*np.tanh(np.where(((((( data["minbatch_slices2"])* 2.0)) <=(np.minimum(((data["abs_minbatch_slices2"])) ,(((-(( np.maximum(((data["rangebatch_msignal"])) ,(((-(( data["rangebatch_msignal"])))))))))))))) *1.) <= -998, np.tanh(( data["rangebatch_msignal"])) ,(( data["abs_maxbatch_slices2"])*(np.tanh(( np.sin(( data["rangebatch_msignal"])))))))) +
0.050000*np.tanh(((data["maxtominbatch"])-(data["meanbatch_slices2"])))+
0.050000*np.tanh(((((np.sin(( np.where(np.minimum(((data["rangebatch_msignal"])) ,(( data["signal"])))> -998, np.where(np.minimum(((data["rangebatch_msignal"])) ,(( data["signal"])))> -998, data["rangebatch_msignal"], np.cos(((( data["mean_abs_chgbatch_slices2_msignal"])* 2.0)))) , data["abs_avgbatch_msignal"])))) * 2.0)) -(((np.cos(((( data["mean_abs_chgbatch_slices2_msignal"])* 2.0)))) * 2.0)))) +
0.050000*np.tanh(np.cos(((( data["meanbatch_msignal"])+(np.where(((data["maxbatch_msignal"])*(np.cos(((((7.0)) +(data["medianbatch_msignal"])))))) <= -998,(7.0), data["minbatch_msignal"])))))) +
0.050000*np.tanh(((((((((((np.minimum(((data["maxtominbatch"])) ,(((-(( np.sin(( data["signal"])))))))))>(np.maximum(((((( data["rangebatch_slices2"])>(( -(( np.sin(( data["rangebatch_slices2"])))))))*1.))) ,(( data["signal"])))))*1.))-(data["stdbatch_slices2_msignal"])))+(data["signal_shift_-1_msignal"])) /2.0)) *(((data["rangebatch_slices2"])*(( -(( np.sin(( data["signal"])))))))))) +
0.050000*np.tanh(np.where(np.sin(( data["minbatch_slices2_msignal"])) > -998,(( data["mean_abs_chgbatch_slices2_msignal"])*(np.sin(( data["signal"])))) , np.maximum(((((np.tanh(( data["minbatch_slices2_msignal"])))/ 2.0))),(( np.tanh(( np.maximum(((data["abs_avgbatch_slices2"])) ,(( np.tanh(( data["abs_maxbatch"])))))))))))) +
0.050000*np.tanh(np.sin(( np.where(((np.cos(( data["stdbatch_slices2_msignal"])))*(np.minimum(((np.minimum(((np.cos(((5.0))))),(((5.0)))))) ,(((( data["abs_minbatch_msignal"])* 2.0)))))) <= -998, np.sin(((( np.cos(((5.0)))) * 2.0))),(( data["abs_minbatch_msignal"])* 2.0)))))+
0.050000*np.tanh(((np.sin(((( np.where(( -(( data["meanbatch_msignal"])))<= -998, data["meanbatch_msignal"], np.minimum(((data["stdbatch_msignal"])) ,(((( data["minbatch"])/ 2.0)))))) * 2.0)))) *(np.where(( -(( data["meanbatch_msignal"])))<= -998,(( np.sin(( np.sin(((( data["stdbatch_msignal"])* 2.0)))))) *(data["meanbatch_slices2"])) , np.minimum(((data["stdbatch_msignal"])) ,(( data["maxtominbatch_msignal"])))))))+
0.050000*np.tanh(((data["rangebatch_msignal"])*(np.sin(((( np.sin(((( np.minimum(((np.where(np.sin(( np.sin(( data["rangebatch_msignal"])))) <= -998, data["maxbatch_slices2"], data["abs_minbatch_slices2_msignal"]))),(( data["minbatch"])))) * 2.0)))) * 2.0)))))) +
0.050000*np.tanh(((( -(((((( data["abs_maxbatch_slices2_msignal"])*(data["abs_avgbatch_slices2_msignal"])))-(((( -(((((( data["abs_maxbatch_slices2_msignal"])*(data["abs_avgbatch_slices2_msignal"])))-(np.minimum(((np.cos(( data["meanbatch_slices2"])))) ,(((( np.where(data["meanbatch_slices2_msignal"] > -998, data["maxtominbatch"], data["maxtominbatch_slices2_msignal"])) * 2.0)))))))))) / 2.0)))))))/ 2.0)) +
0.050000*np.tanh(((((data["signal_shift_-1"])-(( 12.30045986175537109)))) -(np.minimum(((data["abs_maxbatch"])) ,(( np.minimum(((data["maxtominbatch_slices2_msignal"])) ,(( np.where(np.where(data["mean_abs_chgbatch_slices2"] <= -998, data["mean_abs_chgbatch_slices2_msignal"], data["mean_abs_chgbatch_msignal"])> -998, np.maximum(((data["abs_maxbatch"])) ,(( np.maximum(((( 12.30045986175537109))),(( np.sin(( data["signal_shift_-1"])))))))) ,(-(( data["minbatch"])))))))))))))+
0.050000*np.tanh(((np.where(np.maximum(((((np.where(data["abs_minbatch_slices2_msignal"] <= -998,(0.0), np.cos(( np.cos(( data["abs_minbatch_slices2_msignal"])))))) *(data["stdbatch_msignal"])))) ,(((((data["signal_shift_-1_msignal"])>(( -(( data["stdbatch_msignal"])))))*1.))))<= -998, data["minbatch"],(-(( data["medianbatch_slices2"])))))*(np.cos(( data["stdbatch_msignal"])))))+
0.050000*np.tanh(data["stdbatch_slices2_msignal"])+
0.050000*np.tanh(((data["rangebatch_msignal"])* 2.0)) +
0.050000*np.tanh(data["signal_shift_+1_msignal"])+
0.050000*np.tanh(((data["signal_shift_-1_msignal"])-(np.where(data["signal_shift_-1_msignal"] > -998, data["medianbatch_msignal"], data["mean_abs_chgbatch_slices2_msignal"])))) +
0.050000*np.tanh(data["minbatch_slices2_msignal"])+
0.050000*np.tanh(((( -(( data["abs_maxbatch_slices2"])))) *(np.cos(( data["maxbatch_slices2_msignal"])))))+
0.050000*np.tanh(np.minimum(((np.where(data["minbatch_msignal"] <= -998,(((( data["stdbatch_slices2_msignal"])*(data["signal"])))+(data["signal_shift_-1_msignal"])) ,(-(( np.sin(( data["signal"])))))))) ,(((( np.sin(( np.where(data["signal_shift_-1_msignal"] <= -998, np.cos(( np.cos(( data["maxtominbatch_msignal"])))) , data["signal_shift_-1_msignal"])))) +(((data["abs_minbatch_slices2"])+(np.cos(( data["maxtominbatch_msignal"])))))))))) +
0.050000*np.tanh(((np.sin(((( np.sin(( data["abs_minbatch_slices2_msignal"])))-(np.sin(( data["signal_shift_+1"])))))))* 2.0)) +
0.050000*np.tanh(((((data["mean_abs_chgbatch_msignal"])+(data["signal_shift_+1_msignal"])))*(((np.sin(( data["maxtominbatch"])))-(np.maximum(((((((((( data["minbatch_slices2_msignal"])>(np.sin(( np.sin(((( data["abs_minbatch_slices2_msignal"])/ 2.0)))))))*1.))* 2.0)) -(data["minbatch_slices2_msignal"])))) ,(( data["meanbatch_msignal"])))))))) +
0.050000*np.tanh(np.sin(( np.minimum(((( 11.73060512542724609))),(((-(((( data["signal_shift_-1"])+(np.cos(( np.where(data["abs_maxbatch_msignal"] > -998, data["mean_abs_chgbatch_msignal"], np.where(data["mean_abs_chgbatch_slices2_msignal"] > -998, data["mean_abs_chgbatch_msignal"], data["maxbatch_slices2_msignal"])))))))))))))))+
0.050000*np.tanh(np.cos(( np.maximum(((data["abs_avgbatch_slices2_msignal"])) ,(((((((data["signal"])+(data["signal_shift_+1"])) /2.0)) -(data["abs_avgbatch_slices2_msignal"])))))))) +
0.050000*np.tanh(np.where(data["signal_shift_-1_msignal"] > -998, data["signal_shift_-1_msignal"], np.where(np.minimum(((np.minimum(((np.cos(( data["rangebatch_msignal"])))) ,(( data["minbatch_msignal"]))))),(( np.where(( -(( np.minimum(((data["minbatch_slices2_msignal"])) ,(( data["medianbatch_slices2"])))))) > -998, data["signal_shift_-1_msignal"], data["signal_shift_+1"])))) <= -998, np.sin(((((data["meanbatch_slices2"])>(data["rangebatch_slices2_msignal"])) *1.))) , data["rangebatch_msignal"])))+
0.050000*np.tanh(((np.cos(( data["signal_shift_-1"])))* 2.0)) +
0.050000*np.tanh(( -(((( np.sin(((( data["signal"])+(((data["signal"])+(np.sin(( data["signal_shift_-1_msignal"])))))))))*(((((((data["signal"])+(( -(( data["signal_shift_+1"])))))) +(np.sin(( data["signal_shift_+1"])))))+(((data["signal"])+(data["signal_shift_+1"])))))))))) +
0.050000*np.tanh(((((((data["signal_shift_-1_msignal"])+(((data["minbatch_msignal"])*(np.cos(((((-(( data["signal_shift_+1"])))) +(data["abs_maxbatch_slices2_msignal"])))))))) /2.0)) +(((data["mean_abs_chgbatch_slices2_msignal"])*(np.cos(((((-(( data["signal_shift_+1"])))) +(data["abs_maxbatch_slices2_msignal"])))))))) /2.0)) +
0.050000*np.tanh(np.minimum(((np.sin(( np.where(np.maximum(((data["abs_minbatch_msignal"])) ,(((((data["stdbatch_slices2_msignal"])+(data["maxtominbatch_slices2"])) /2.0)))) > -998, data["mean_abs_chgbatch_msignal"], np.tanh(((((( np.sin(( data["rangebatch_msignal"])))*(data["stdbatch_slices2"])))-(data["medianbatch_slices2"]))))))))),(( np.maximum(((np.maximum(((data["mean_abs_chgbatch_msignal"])) ,(( data["medianbatch_slices2"]))))),(( data["abs_avgbatch_slices2_msignal"])))))))+
0.050000*np.tanh(((np.minimum(((data["stdbatch_slices2_msignal"])) ,(( np.cos(( np.sin(((( np.minimum(((data["stdbatch_slices2_msignal"])) ,(( data["stdbatch_slices2_msignal"])))) * 2.0)))))))))*(np.sin(((( np.minimum(((data["stdbatch_slices2_msignal"])) ,(( data["stdbatch_slices2_msignal"])))) * 2.0)))))) +
0.050000*np.tanh(((np.cos(((((( data["stdbatch_slices2_msignal"])+(((((( data["minbatch_slices2"])-(( 3.65924572944641113)))) <=(((np.cos(((((( data["stdbatch_slices2_msignal"])+(((( data["maxtominbatch_slices2"])<=(np.cos(((((data["signal_shift_+1"])>(data["maxbatch_slices2_msignal"])) *1.))))) *1.))))* 2.0)))) * 2.0)))*1.))))* 2.0)))) * 2.0)) +
0.050000*np.tanh(np.where(data["abs_maxbatch_slices2"] <= -998,(((data["abs_avgbatch_slices2_msignal"])+(( -(( data["maxtominbatch_slices2_msignal"])))))/2.0),(( data["signal_shift_+1_msignal"])-(np.minimum(((data["abs_avgbatch_slices2"])) ,(( data["abs_avgbatch_msignal"])))))))+
0.050000*np.tanh(data["signal_shift_-1_msignal"])+
0.050000*np.tanh(np.cos(( np.where(( -(((( np.cos(( np.where(data["stdbatch_slices2_msignal"] > -998, data["signal"],(( data["signal"])*(data["maxbatch_slices2_msignal"])))))) / 2.0)))) > -998, data["signal"], np.maximum(((( 1.0))),(((((( 1.0)) +(((np.cos(((-(( data["signal_shift_+1_msignal"])))))) * 2.0)))/2.0)))))))) +
0.050000*np.tanh(np.minimum(((data["signal_shift_-1"])) ,(((-(((( np.sin(( data["signal_shift_+1"])))*(np.maximum(((data["abs_maxbatch"])) ,(( np.where(data["abs_maxbatch"] <= -998,(((((-(((-(( np.cos(( data["signal_shift_+1"])))))))))*(data["abs_maxbatch"])))+(data["signal_shift_-1_msignal"])) , data["meanbatch_msignal"])))))))))))))+
0.050000*np.tanh(((data["signal_shift_-1_msignal"])+(np.where(data["signal_shift_+1"] > -998, np.cos(( np.where(data["abs_avgbatch_slices2_msignal"] <= -998,(( data["stdbatch_msignal"])*(data["maxtominbatch_slices2_msignal"])) , data["minbatch"]))), data["maxtominbatch_slices2"])))) +
0.050000*np.tanh(np.sin(( np.sin(( np.where(((np.where(np.sin(( data["rangebatch_msignal"])) > -998, data["stdbatch_slices2"],(((((((((((data["minbatch_slices2"])* 2.0)) -(data["mean_abs_chgbatch_slices2_msignal"])))+(data["minbatch_msignal"])) /2.0)) * 2.0)) -(data["mean_abs_chgbatch_slices2_msignal"])))) -(( 9.0)))> -998,(-(( np.sin(( data["signal_shift_-1_msignal"]))))), data["maxbatch_slices2_msignal"])))))) +
0.050000*np.tanh(np.sin(((( data["minbatch"])+(((data["meanbatch_slices2_msignal"])/ 2.0)))))) +
0.050000*np.tanh(np.cos(((( data["signal_shift_-1"])-(np.where(data["stdbatch_msignal"] <= -998,(((data["signal_shift_-1"])>(data["rangebatch_slices2_msignal"])) *1.) , np.where(data["stdbatch_msignal"] > -998, data["maxtominbatch_msignal"], data["mean_abs_chgbatch_slices2_msignal"])))))))+
0.050000*np.tanh(((np.where(data["mean_abs_chgbatch_msignal"] <= -998,(((np.tanh(((-(( np.maximum(((((data["medianbatch_slices2"])*(data["abs_maxbatch_msignal"])))) ,(( data["abs_avgbatch_slices2"])))))))))>(data["maxbatch_msignal"])) *1.) , data["signal_shift_+1"])) -(data["abs_avgbatch_slices2"])))+
0.050000*np.tanh(((((((data["meanbatch_slices2_msignal"])+(( -(( data["maxbatch_slices2_msignal"])))))/2.0)) +(( -(( np.where(data["rangebatch_msignal"] <= -998, data["meanbatch_slices2_msignal"],(( data["abs_avgbatch_msignal"])*(np.where(data["meanbatch_slices2_msignal"] > -998, data["abs_maxbatch_msignal"], data["minbatch_slices2"])))))))))/2.0)) +
0.050000*np.tanh(((data["signal_shift_-1"])-(np.tanh(( np.tanh(((((data["abs_maxbatch_msignal"])>(np.maximum(((np.sin(( data["mean_abs_chgbatch_msignal"])))) ,(( data["maxbatch_slices2_msignal"])))))*1.))))))))+
0.050000*np.tanh(np.cos(( data["abs_minbatch_msignal"])))+
0.050000*np.tanh(np.sin(((((( np.minimum(((((np.where(data["mean_abs_chgbatch_slices2"] > -998, data["mean_abs_chgbatch_slices2_msignal"], data["minbatch_slices2"])) * 2.0))),(((((( np.cos(( data["minbatch_slices2"])))* 2.0)) * 2.0)))))-(data["abs_maxbatch_msignal"])))* 2.0)))) +
0.050000*np.tanh(np.minimum(((data["medianbatch_slices2_msignal"])) ,(((( data["minbatch_slices2"])* 2.0)))))+
0.050000*np.tanh(((data["minbatch_slices2"])*(((np.where(np.minimum(((data["signal_shift_-1_msignal"])) ,(( np.cos(( data["minbatch_slices2_msignal"])))))> -998, data["signal_shift_-1"], data["maxtominbatch_slices2_msignal"])) *(np.sin(( np.sin(( data["signal_shift_-1"])))))))))+
0.050000*np.tanh(np.where(data["medianbatch_slices2_msignal"] <= -998,(( data["minbatch_msignal"])-(np.tanh(((((((data["signal_shift_-1_msignal"])*(data["abs_maxbatch_slices2_msignal"])))+(np.sin(((( np.where(data["signal_shift_-1_msignal"] > -998, np.where(data["abs_maxbatch_slices2_msignal"] > -998, data["mean_abs_chgbatch_slices2"], data["signal_shift_-1_msignal"]), np.maximum(((data["abs_avgbatch_msignal"])) ,(( data["signal_shift_-1_msignal"])))))/ 2.0)))))/2.0))))), data["signal_shift_+1_msignal"])) +
0.050000*np.tanh(((np.sin(( data["abs_maxbatch"])))/ 2.0)) +
0.050000*np.tanh(np.where(((( np.where(data["mean_abs_chgbatch_slices2"] <= -998,(( data["abs_avgbatch_slices2_msignal"])/ 2.0), np.where(((((data["abs_avgbatch_slices2_msignal"])-(data["signal_shift_-1_msignal"])))/ 2.0)<= -998, data["mean_abs_chgbatch_slices2"], data["mean_abs_chgbatch_slices2_msignal"])))>(((( data["abs_avgbatch_slices2_msignal"])+(data["medianbatch_slices2"])) /2.0)))*1.) <= -998, data["signal_shift_-1_msignal"],(-(((( data["abs_avgbatch_slices2_msignal"])-(((data["signal_shift_-1_msignal"])/ 2.0)))))))) +
0.050000*np.tanh(((((( -(( data["maxbatch_slices2_msignal"])))) *(((data["signal_shift_-1_msignal"])*(np.sin(((( data["stdbatch_msignal"])-(((np.where(np.tanh(((-(((7.0)))))) <= -998, data["stdbatch_msignal"], np.tanh(( data["maxtominbatch"])))) / 2.0)))))))))) * 2.0)) +
0.050000*np.tanh(((np.cos(((( np.where(np.maximum(((( 10.35262870788574219))),(( np.cos(( data["maxbatch_msignal"])))))<= -998, np.sin(( data["maxbatch_msignal"])) , data["maxbatch_msignal"])) -(data["signal_shift_+1"])))))*(((data["abs_minbatch_msignal"])+(np.cos(( data["maxbatch_msignal"])))))))+
0.050000*np.tanh(((np.cos(((( data["maxbatch_slices2_msignal"])* 2.0)))) *(np.where(np.minimum(((((data["medianbatch_slices2"])*(data["maxtominbatch"])))) ,(( data["abs_maxbatch"])))> -998, data["signal_shift_-1_msignal"],(((2.0)) +(data["signal_shift_-1"])))))) +
0.050000*np.tanh(((( 0.0)) -(np.cos(((((( np.where(data["abs_minbatch_slices2"] > -998, data["signal_shift_+1"],(((( 0.0)) <=(((np.where(data["signal_shift_+1"] > -998, data["signal_shift_+1"],(((data["maxbatch_slices2"])<=(np.maximum(((data["maxtominbatch_slices2_msignal"])) ,(( data["signal_shift_-1_msignal"])))))*1.))) * 2.0)))*1.))) *(((( data["medianbatch_msignal"])+(((( data["signal"])<=(data["stdbatch_msignal"])) *1.))) /2.0)))) / 2.0)))))) +
0.050000*np.tanh(np.where(data["meanbatch_slices2_msignal"] > -998, np.sin(( data["minbatch_msignal"])) ,(( np.where(data["maxbatch_msignal"] > -998, data["meanbatch_slices2_msignal"],(( np.sin(( data["minbatch"])))-(data["mean_abs_chgbatch_msignal"])))) -(np.cos(( np.where(data["maxbatch_msignal"] > -998, data["abs_minbatch_slices2"], data["maxbatch_slices2_msignal"])))))))+
0.050000*np.tanh(data["minbatch_msignal"])+
0.050000*np.tanh(((data["signal_shift_-1_msignal"])-(np.maximum(((data["abs_minbatch_msignal"])) ,(( np.maximum(((((data["abs_avgbatch_slices2"])*(((data["maxbatch_msignal"])-(( -(( data["abs_minbatch_msignal"]))))))))),(((((((( data["maxtominbatch_slices2_msignal"])+(((((data["abs_minbatch_slices2_msignal"])/ 2.0)) * 2.0)))/2.0)) +(data["stdbatch_msignal"])) /2.0)))))))))) +
0.050000*np.tanh(((data["maxtominbatch_slices2"])*(np.sin(((( np.where(((( -(( data["stdbatch_slices2"])))) *(np.cos(( np.minimum(((np.cos(( np.sin(( data["abs_maxbatch"])))))) ,(((((( np.cos(( data["medianbatch_slices2"])))* 2.0)) -(data["rangebatch_slices2_msignal"])))))))))<= -998, np.maximum(((((( data["maxtominbatch_msignal"])<=(data["maxtominbatch_msignal"])) *1.))) ,(( data["signal_shift_-1_msignal"]))), data["minbatch_msignal"])) * 2.0)))))) +
0.050000*np.tanh(np.where(np.where(data["maxtominbatch"] > -998, data["abs_maxbatch_slices2"], np.cos(( data["maxbatch_slices2_msignal"])))<= -998, np.sin(( data["maxtominbatch"])) , np.sin(( data["minbatch_msignal"])))) +
0.050000*np.tanh(np.sin(( data["abs_maxbatch"])))+
0.050000*np.tanh(((np.sin(( data["signal_shift_+1"])))*(np.where(np.where(np.cos(((( np.sin(( data["signal_shift_+1"])))*(((((np.tanh(( np.cos(( np.cos(( data["rangebatch_slices2"])))))))-(data["minbatch"])))-(np.sin(( data["signal_shift_+1"])))))))) > -998, data["maxtominbatch_slices2_msignal"], data["abs_maxbatch"])> -998, data["maxtominbatch_msignal"],(( data["maxbatch_slices2"])/ 2.0)))))+
0.050000*np.tanh(np.sin(( np.where(data["abs_maxbatch_slices2_msignal"] > -998, np.sin(( np.where(np.where(data["abs_avgbatch_msignal"] > -998, data["abs_avgbatch_slices2_msignal"], np.where(np.cos(((5.75612592697143555)))> -998, data["abs_avgbatch_slices2"],(( data["abs_maxbatch_slices2_msignal"])*(data["abs_avgbatch_msignal"])))) > -998, data["abs_maxbatch"], data["stdbatch_slices2_msignal"]))), np.minimum(((data["abs_avgbatch_slices2_msignal"])) ,(( np.minimum(((data["abs_avgbatch_msignal"])) ,(( np.cos(( data["signal_shift_+1"])))))))))))) +
0.050000*np.tanh(np.sin(((((((data["signal"])-(np.sin(( data["signal"])))))>(( -(( data["signal_shift_+1_msignal"])))))*1.))))+
0.050000*np.tanh(((np.cos(( np.sin(( data["maxtominbatch_msignal"])))))-(((np.sin(( np.sin(( np.sin(( np.sin(( data["maxtominbatch_msignal"])))))))))*(np.where(data["abs_avgbatch_slices2_msignal"] > -998,(9.0), np.cos(((( data["signal_shift_-1_msignal"])-(np.sin(( data["maxtominbatch_msignal"])))))))))))) +
0.050000*np.tanh(np.sin(( np.tanh(((((( data["stdbatch_slices2"])*(((np.cos(( data["stdbatch_slices2"])))*(((data["medianbatch_slices2_msignal"])* 2.0)))))) * 2.0)))))) +
0.050000*np.tanh(((((data["signal_shift_-1"])-(data["maxbatch_slices2_msignal"])))*(np.sin(((( data["signal_shift_-1"])-(np.minimum(((np.where(data["abs_avgbatch_msignal"] <= -998, np.sin(((( data["signal_shift_-1"])-(np.minimum(((data["signal_shift_-1"])) ,(((((data["mean_abs_chgbatch_msignal"])<=(((data["signal_shift_-1"])-(data["signal_shift_-1"])))) *1.)))))))), data["meanbatch_msignal"]))),(( data["abs_maxbatch_msignal"])))))))))) +
0.050000*np.tanh(((np.maximum(((np.sin(( data["stdbatch_slices2"])))) ,(((( data["mean_abs_chgbatch_slices2_msignal"])/ 2.0)))))+(((( -(( data["meanbatch_msignal"])))) * 2.0)))) +
0.050000*np.tanh(np.where(np.sin(( np.minimum(((np.sin(((((((data["abs_avgbatch_slices2"])+(( -(((( data["signal_shift_-1"])+(data["abs_minbatch_slices2"])))))))/2.0)) *(data["maxtominbatch_msignal"])))))) ,(((14.36639404296875000)))))) > -998, np.sin(( data["abs_maxbatch_slices2"])) ,(((((data["rangebatch_slices2"])+(np.sin(( data["maxtominbatch"])))) /2.0)) -(np.maximum(((np.tanh(( data["abs_maxbatch_msignal"])))) ,(( data["minbatch_slices2"])))))))+
0.050000*np.tanh(np.where(data["maxtominbatch_slices2"] <= -998, data["signal_shift_-1_msignal"], np.sin(((( data["stdbatch_msignal"])*(np.maximum(((data["abs_maxbatch_slices2"])) ,(( data["stdbatch_msignal"])))))))))+
0.050000*np.tanh(np.where(np.cos(( np.cos(( data["signal_shift_-1_msignal"])))) > -998, np.cos(((((6.0)) *(((( data["maxbatch_msignal"])+(data["mean_abs_chgbatch_slices2_msignal"])) /2.0))))), np.maximum(((data["signal_shift_+1_msignal"])) ,(((( data["mean_abs_chgbatch_slices2_msignal"])+(((((( data["minbatch_msignal"])* 2.0)) <=(data["signal_shift_+1_msignal"])) *1.))))))))+
0.050000*np.tanh(np.sin(( np.sin(((( np.sin(( np.minimum(((((( data["medianbatch_slices2_msignal"])<=(((( -(((-(( data["signal_shift_+1_msignal"])))))))* 2.0)))*1.))) ,(( np.tanh(( data["medianbatch_slices2"])))))))) -(data["signal_shift_+1"])))))))+
0.050000*np.tanh(np.cos(( np.minimum(((np.sin(( data["maxtominbatch_msignal"])))) ,(((( np.where(( -(( np.minimum(((( 9.0))),(( data["stdbatch_msignal"])))))) > -998, data["minbatch_msignal"], data["maxbatch_slices2"])) +(data["meanbatch_msignal"])))))))) +
0.050000*np.tanh(((( data["maxbatch_slices2"])<=(((( -(( np.maximum(((np.cos(( np.minimum(((np.where(data["maxbatch_msignal"] > -998, np.sin(( data["maxbatch_slices2"])) ,(( data["meanbatch_slices2_msignal"])* 2.0)))) ,(((( data["minbatch"])-(data["signal"]))))))))),(((4.0)))))))) * 2.0)))*1.))+
0.050000*np.tanh(np.where(((( data["meanbatch_slices2_msignal"])<=(np.cos(( data["mean_abs_chgbatch_slices2_msignal"])))) *1.) > -998,(( data["maxtominbatch_msignal"])+(np.minimum(((( -(( data["abs_maxbatch"]))))),(((( data["signal_shift_+1_msignal"])* 2.0)))))) , data["maxbatch_slices2_msignal"])) +
0.050000*np.tanh(((np.minimum(((np.where(((( data["signal_shift_-1"])+(data["signal_shift_-1_msignal"])) /2.0)> -998, data["abs_maxbatch_slices2_msignal"],(-(( np.where(((( data["maxbatch_slices2_msignal"])<=(((np.tanh(( data["signal"])))+(( -(( data["abs_minbatch_slices2_msignal"])))))))*1.) <= -998, np.cos(( data["abs_maxbatch_slices2_msignal"])) , data["signal_shift_+1"]))))))),(( data["signal_shift_+1"])))) -(np.cos(( data["abs_maxbatch_slices2_msignal"])))))+
0.050000*np.tanh(((data["maxtominbatch_slices2_msignal"])* 2.0)) +
0.050000*np.tanh(((np.sin(( np.where(((data["maxtominbatch_slices2_msignal"])+(data["maxtominbatch"])) > -998, np.where(data["abs_avgbatch_slices2_msignal"] > -998, data["abs_maxbatch"], data["abs_maxbatch"]), data["abs_maxbatch_slices2"])))) *(np.where(((((( -(( data["abs_avgbatch_slices2_msignal"])))) -(np.sin(((-(( data["maxbatch_msignal"])))))))) -(data["abs_maxbatch"])) > -998,(-(( data["medianbatch_msignal"]))), data["abs_maxbatch_slices2"])))) +
0.050000*np.tanh(((data["signal_shift_+1"])*(((( data["abs_avgbatch_slices2_msignal"])+(((data["abs_maxbatch_slices2_msignal"])-(( -(((((( data["abs_maxbatch_msignal"])/ 2.0)) * 2.0)))))))) /2.0)))) +
0.050000*np.tanh(np.tanh(( np.cos(( data["signal_shift_+1"])))))+
0.050000*np.tanh(np.cos(( np.where(np.sin(( np.cos(( data["signal_shift_-1_msignal"])))) > -998, np.maximum(((data["signal_shift_-1"])) ,(( data["signal"]))),(( np.sin(( data["mean_abs_chgbatch_msignal"])))+(( -(((-(( np.maximum(((( -(((( data["minbatch_msignal"])* 2.0)))))) ,(( data["signal"])))))))))))))))+
0.050000*np.tanh(np.minimum(((((data["maxtominbatch_slices2_msignal"])-(np.where(data["maxbatch_slices2_msignal"] <= -998, data["rangebatch_slices2"], np.where(data["abs_minbatch_slices2"] > -998, data["rangebatch_slices2"],(( np.maximum(((np.sin(((((data["maxtominbatch"])+(( -(( data["rangebatch_slices2"])))))/2.0))))),(( data["meanbatch_msignal"])))) / 2.0))))))),(( data["maxtominbatch"])))) +
0.050000*np.tanh(((data["minbatch"])*(np.cos(( np.where(data["abs_minbatch_msignal"] > -998,(( data["abs_minbatch_msignal"])*(data["abs_avgbatch_msignal"])) ,(( data["abs_avgbatch_slices2_msignal"])*(np.cos(( np.where(data["meanbatch_slices2"] > -998,(( data["abs_minbatch_msignal"])*(data["rangebatch_slices2"])) , data["rangebatch_slices2"])))))))))))+
0.050000*np.tanh(np.sin(( np.cos(( np.where(((((data["abs_minbatch_msignal"])+(np.where(np.sin(( np.cos(((((data["signal"])+(data["stdbatch_slices2"])) /2.0)))))> -998, data["stdbatch_msignal"],(((data["signal_shift_-1"])+(data["medianbatch_slices2"])) /2.0)))))+(np.minimum(((data["maxtominbatch_slices2"])) ,(( np.sin(( data["maxtominbatch_slices2"])))))))<= -998, data["stdbatch_msignal"], data["abs_minbatch_slices2_msignal"])))))) +
0.050000*np.tanh(((data["abs_minbatch_slices2"])-(((np.sin(( data["signal_shift_-1"])))*(np.where(np.maximum(((( 11.95872116088867188))),(( data["signal_shift_-1_msignal"])))<= -998, np.minimum(((((((data["signal_shift_-1_msignal"])+(( -(( data["maxbatch_slices2"])))))) -(data["rangebatch_msignal"])))) ,(((( np.sin(( data["signal_shift_-1"])))*(data["signal"]))))), data["meanbatch_slices2"])))))) +
0.050000*np.tanh(((( -(( np.tanh(( np.sin(( np.where(np.cos(((-(( data["rangebatch_slices2_msignal"])))))> -998,(((np.tanh(( data["abs_maxbatch_msignal"])))>(np.tanh(( np.minimum(((data["meanbatch_slices2_msignal"])) ,(( data["rangebatch_slices2_msignal"])))))))*1.) , np.tanh(( np.sin(( np.where(data["minbatch_slices2"] > -998, np.tanh(( data["rangebatch_slices2_msignal"])) , data["signal_shift_-1"])))))))))))))) * 2.0)) +
0.050000*np.tanh(np.where(((( -(( data["meanbatch_msignal"])))) * 2.0)> -998,(( data["signal_shift_-1"])-(( 3.0))), np.where(data["maxtominbatch_slices2"] > -998, data["signal_shift_+1"],(((data["abs_maxbatch_slices2_msignal"])<=(((( data["signal_shift_-1"])>(((data["signal_shift_+1"])/ 2.0)))*1.))) *1.))))+
0.050000*np.tanh(((np.sin(( data["maxtominbatch_msignal"])))*(((( data["mean_abs_chgbatch_msignal"])+(np.minimum(((data["maxtominbatch_msignal"])) ,(((((( np.sin(( np.where(data["maxtominbatch_msignal"] > -998, data["maxtominbatch_msignal"], data["mean_abs_chgbatch_msignal"])))) +(((data["stdbatch_slices2"])-(data["maxtominbatch_msignal"])))))+(data["maxtominbatch_msignal"])))))))/2.0)))) +
0.050000*np.tanh(np.sin(( np.where(((data["minbatch"])-(np.where(data["meanbatch_slices2_msignal"] <= -998, data["maxbatch_msignal"], np.sin(( data["medianbatch_slices2_msignal"])))))<= -998, np.sin(((( data["rangebatch_slices2_msignal"])* 2.0))), np.where(np.cos(( data["rangebatch_slices2_msignal"])) <= -998, data["abs_minbatch_msignal"], data["mean_abs_chgbatch_slices2_msignal"])))))+
0.050000*np.tanh(np.minimum(((np.tanh(( np.sin(((((((( data["minbatch_slices2_msignal"])>(((((data["stdbatch_slices2_msignal"])/ 2.0)) * 2.0)))*1.))<=(data["stdbatch_msignal"])) *1.))))))) ,(((((data["minbatch"])>(( -(( np.maximum(((data["maxtominbatch_msignal"])) ,(((((data["stdbatch_msignal"])<=(( -(( data["signal_shift_+1"])))))*1.))))))))) *1.))))) +
0.050000*np.tanh(((( data["abs_maxbatch"])>(data["meanbatch_msignal"])) *1.))+
0.050000*np.tanh(np.sin(((( data["mean_abs_chgbatch_msignal"])*(np.sin(( data["rangebatch_msignal"])))))))+
0.050000*np.tanh(np.sin(((((((( -(( np.cos(( data["medianbatch_slices2"])))))) +(((((( data["maxbatch_slices2"])+(data["mean_abs_chgbatch_slices2_msignal"])) /2.0)) +(data["medianbatch_slices2_msignal"])))) /2.0)) *(data["rangebatch_slices2"])))))+
0.050000*np.tanh(np.where(np.where(np.where(data["signal_shift_+1_msignal"] > -998, data["meanbatch_msignal"],(( data["medianbatch_slices2"])/ 2.0)) <= -998, data["maxtominbatch_msignal"], np.minimum(((data["abs_maxbatch"])) ,(((( data["minbatch_slices2"])/ 2.0)))))<= -998,(-(((( data["abs_maxbatch"])* 2.0)))) , np.sin(( np.maximum(((data["abs_maxbatch"])) ,(( np.cos(( np.maximum(((data["minbatch_slices2_msignal"])) ,(( data["meanbatch_msignal"])))))))))))) +
0.050000*np.tanh(np.sin(((((( np.minimum(((data["meanbatch_msignal"])) ,(((((((data["abs_avgbatch_slices2_msignal"])-(( 1.46488344669342041)))) <=(data["mean_abs_chgbatch_slices2"])) *1.))))) * 2.0)) *(( -(( data["mean_abs_chgbatch_msignal"])))))))) +
0.050000*np.tanh(((np.where(data["signal_shift_+1"] <= -998, data["rangebatch_msignal"], np.sin(( data["abs_maxbatch_slices2"])))) * 2.0)) +
0.050000*np.tanh(np.where(((data["signal_shift_+1"])*(((data["signal"])*(data["maxbatch_slices2_msignal"])))) <= -998, data["meanbatch_slices2_msignal"], np.sin(((-(( np.where(np.minimum(((data["abs_avgbatch_slices2"])) ,(( data["minbatch"])))<= -998, data["rangebatch_slices2"], data["mean_abs_chgbatch_slices2"])))))))) +
0.050000*np.tanh(np.where(data["signal"] > -998, data["abs_maxbatch"], np.maximum(((((((data["maxbatch_slices2"])/ 2.0)) / 2.0))),(( data["abs_avgbatch_slices2_msignal"])))))+
0.050000*np.tanh(((np.maximum(((((((np.where(data["minbatch"] <= -998, data["minbatch"],(((data["minbatch_msignal"])+(data["mean_abs_chgbatch_msignal"])) /2.0)))*(np.sin(( np.where(data["signal_shift_-1"] > -998, data["abs_maxbatch_msignal"], np.where(data["maxtominbatch"] > -998, data["abs_maxbatch_msignal"],(( data["maxtominbatch"])-(( 5.0)))))))))) * 2.0))),(( data["minbatch"])))) * 2.0)) +
0.050000*np.tanh(np.cos(( np.maximum(((data["signal"])) ,(( np.where(data["medianbatch_slices2"] <= -998, np.where(((((( data["meanbatch_slices2"])>(data["meanbatch_slices2"])) *1.))*(((( 7.0)) *(data["meanbatch_msignal"])))) <= -998, np.maximum(((data["minbatch_slices2_msignal"])) ,(( data["signal"]))), data["signal"]), data["abs_avgbatch_slices2"])))))))+
0.050000*np.tanh(( -(( np.sin(( np.minimum(((((data["abs_maxbatch"])*(np.sin(( data["abs_avgbatch_msignal"])))))) ,(( data["maxtominbatch_msignal"])))))))))+
0.050000*np.tanh(np.sin(( data["signal_shift_-1"])))+
0.050000*np.tanh(np.sin(( np.where(np.cos(( np.minimum(((data["abs_maxbatch_slices2_msignal"])) ,(( data["medianbatch_slices2"])))))> -998, np.sin(( data["maxbatch_slices2"])) ,(-(((((( np.where(data["maxtominbatch_slices2"] > -998, data["minbatch_slices2"], data["abs_maxbatch_msignal"])) -(data["meanbatch_slices2"])))+(np.where(data["rangebatch_slices2"] <= -998, data["minbatch_slices2"], data["signal_shift_-1"])))))))))) +
0.050000*np.tanh(np.where(np.where(data["abs_minbatch_msignal"] <= -998, np.cos(( data["abs_avgbatch_slices2_msignal"])) , np.where(data["rangebatch_msignal"] > -998, data["abs_avgbatch_slices2_msignal"], np.tanh(((( data["abs_minbatch_msignal"])+(((np.sin(( data["minbatch_msignal"])))-(((np.sin(( data["meanbatch_slices2_msignal"])))* 2.0)))))))))> -998, np.sin(( data["minbatch_msignal"])) , data["abs_minbatch_msignal"])) +
0.050000*np.tanh(((data["meanbatch_slices2"])-(((np.where(((( data["medianbatch_msignal"])+(data["meanbatch_slices2_msignal"])) /2.0)> -998,(9.0), np.maximum(((((( data["medianbatch_slices2"])<=(( 9.0)))*1.))) ,(((((data["signal_shift_-1_msignal"])>(data["medianbatch_slices2_msignal"])) *1.))))))*(np.cos(((( data["medianbatch_slices2"])*(((data["medianbatch_slices2_msignal"])+(data["medianbatch_slices2_msignal"])))))))))))+
0.050000*np.tanh(np.minimum(((np.minimum(((data["signal"])) ,(( np.tanh(( np.cos(( data["signal"]))))))))),(( data["maxbatch_msignal"])))) +
0.050000*np.tanh(((( data["abs_avgbatch_msignal"])>(((np.tanh(( data["stdbatch_slices2"])))*(np.tanh(( np.tanh(((-(( data["signal_shift_-1_msignal"])))))))))))*1.)))
def GP_class_10(self,data):
return self.Output(-4.940363 +
0.050000*np.tanh(np.cos(( np.tanh(((((-(( np.sin(((((( data["abs_minbatch_slices2"])* 2.0)) +(((( data["stdbatch_slices2_msignal"])+(data["signal"])) /2.0)))))))))-(data["signal_shift_-1_msignal"])))))))+
0.050000*np.tanh(( -(( np.where(((np.cos(( np.sin(( data["abs_avgbatch_msignal"])))))/ 2.0)<= -998,(((( data["meanbatch_msignal"])/ 2.0)) -(data["maxbatch_slices2_msignal"])) , np.cos(( data["medianbatch_slices2_msignal"])))))))+
0.050000*np.tanh(np.minimum(((np.where(data["rangebatch_slices2"] <= -998, np.cos(((( np.tanh(( data["abs_minbatch_msignal"])))/ 2.0))), data["minbatch_msignal"]))),(( data["minbatch_msignal"])))) +
0.050000*np.tanh(((((((((data["abs_minbatch_slices2_msignal"])>(((((((((data["maxbatch_slices2_msignal"])+(data["mean_abs_chgbatch_slices2"])))<=(np.tanh(((((np.tanh(( np.sin(((( data["signal"])* 2.0)))))) >(data["meanbatch_slices2"])) *1.))))) *1.))+(( 14.98032379150390625)))/2.0)))*1.))<=(data["signal"])) *1.))-(data["signal_shift_+1_msignal"])))+
0.050000*np.tanh(data["rangebatch_slices2"])+
0.050000*np.tanh(((( data["medianbatch_slices2"])+(((( np.tanh(( data["rangebatch_slices2_msignal"])))+(np.where(np.sin(( data["mean_abs_chgbatch_slices2"])) > -998, data["abs_maxbatch_msignal"], data["minbatch_slices2_msignal"])))/2.0)))/2.0)) +
0.050000*np.tanh(np.where(data["maxtominbatch"] <= -998,(( np.cos(( data["minbatch_slices2"])))/ 2.0),(-(((( data["minbatch_slices2"])* 2.0)))))) +
0.050000*np.tanh(((data["abs_maxbatch_slices2_msignal"])*(data["minbatch_slices2"])))+
0.050000*np.tanh(np.maximum(((data["mean_abs_chgbatch_slices2"])) ,(( np.sin(( data["abs_maxbatch"])))))) +
0.050000*np.tanh(((((( data["signal_shift_+1_msignal"])<=(data["rangebatch_slices2"])) *1.))*(data["signal_shift_+1"])))+
0.050000*np.tanh(((((((np.where(data["meanbatch_slices2_msignal"] <= -998, data["signal_shift_+1"], np.tanh(( data["minbatch_msignal"])))) * 2.0)) * 2.0)) * 2.0)) +
0.050000*np.tanh(( -(( data["maxtominbatch_slices2_msignal"])))) +
0.050000*np.tanh(((( data["medianbatch_slices2"])+(((data["abs_maxbatch"])* 2.0)))/2.0)) +
0.050000*np.tanh(data["abs_minbatch_msignal"])+
0.050000*np.tanh(data["rangebatch_slices2"])+
0.050000*np.tanh(np.maximum(((np.minimum(((( -(( data["abs_minbatch_slices2_msignal"]))))),(((0.0)))))) ,(( np.cos(((( np.cos(( data["abs_minbatch_slices2_msignal"])))-(((( np.tanh(( np.where(( 7.0)> -998,(( data["signal"])/ 2.0), data["maxtominbatch"])))) +(data["abs_maxbatch_slices2_msignal"])) /2.0)))))))))+
0.050000*np.tanh(data["signal_shift_+1"])+
0.050000*np.tanh(((((((((((data["signal"])-(((((( data["abs_maxbatch_msignal"])+(((((((( data["signal"])+(data["signal"])) /2.0)) * 2.0)) * 2.0)))/2.0)) * 2.0)))) >(data["mean_abs_chgbatch_slices2"])) *1.))+(data["signal"])) /2.0)) * 2.0)) +
0.050000*np.tanh(((( -(( data["minbatch_slices2"])))) *(((( data["minbatch_slices2_msignal"])>(((( data["abs_avgbatch_msignal"])<=(data["stdbatch_slices2"])) *1.))) *1.))))+
0.050000*np.tanh(np.sin(( data["signal_shift_-1"])))+
0.050000*np.tanh(np.cos(((( data["rangebatch_slices2"])+(((np.where(data["signal"] > -998, np.where(data["meanbatch_slices2_msignal"] > -998, np.where(data["signal"] > -998,(((np.maximum(((data["abs_maxbatch"])) ,(( data["rangebatch_slices2"])))) <=(np.tanh(( data["signal_shift_+1_msignal"])))) *1.) , np.minimum(((((( data["abs_maxbatch_slices2"])>(data["maxbatch_msignal"])) *1.))) ,(((-(( data["signal_shift_+1_msignal"]))))))), data["rangebatch_slices2_msignal"]), data["rangebatch_slices2"])) / 2.0)))))) +
0.050000*np.tanh(data["maxbatch_slices2_msignal"])+
0.050000*np.tanh(((((((data["maxtominbatch_slices2_msignal"])<=(((((data["abs_minbatch_slices2"])+(np.minimum(((data["abs_maxbatch_msignal"])) ,(((((-(( np.maximum(((data["maxbatch_slices2"])) ,(( data["abs_minbatch_slices2_msignal"])))))))+(data["maxbatch_slices2"])))))))) / 2.0)))*1.))<=(data["maxbatch_msignal"])) *1.))+
0.050000*np.tanh(data["maxtominbatch_slices2_msignal"])+
0.050000*np.tanh(np.sin(( np.cos(((-(( data["abs_maxbatch_slices2"])))))))) +
0.050000*np.tanh(((data["rangebatch_slices2"])/ 2.0)) +
0.050000*np.tanh(np.where(( 5.0)> -998, data["medianbatch_msignal"], data["abs_avgbatch_slices2"])) +
0.050000*np.tanh(((np.maximum(((((np.maximum(((data["rangebatch_slices2_msignal"])) ,(( data["mean_abs_chgbatch_msignal"])))) * 2.0))),(( data["signal"])))) * 2.0)) +
0.050000*np.tanh(np.where(np.cos(( data["maxbatch_slices2"])) <= -998, data["meanbatch_slices2_msignal"], data["signal"])) +
0.050000*np.tanh(( -(((((5.0)) +(data["abs_minbatch_slices2_msignal"])))))) +
0.050000*np.tanh(data["maxtominbatch_slices2"])+
0.050000*np.tanh(np.cos(( data["mean_abs_chgbatch_msignal"])))+
0.050000*np.tanh(data["minbatch_slices2_msignal"])+
0.050000*np.tanh(( -(((( data["signal_shift_-1_msignal"])+(data["abs_avgbatch_slices2_msignal"])))))) +
0.050000*np.tanh(((((data["signal_shift_-1"])-(data["meanbatch_msignal"])))/ 2.0)) +
0.050000*np.tanh(((data["rangebatch_slices2"])/ 2.0)) +
0.050000*np.tanh(((( data["rangebatch_slices2_msignal"])<=(np.where(((( data["abs_avgbatch_msignal"])<=(np.where(data["stdbatch_slices2"] > -998,(9.0), data["signal"])))*1.) > -998, data["signal_shift_+1"], np.maximum(((data["maxtominbatch_msignal"])) ,(( data["stdbatch_slices2"])))))) *1.))+
0.050000*np.tanh(((((((((( data["maxtominbatch_slices2"])+(((data["signal_shift_+1"])*(data["rangebatch_msignal"])))) /2.0)) +(data["signal"])) /2.0)) >(((((data["signal"])/ 2.0)) -(data["abs_maxbatch_msignal"])))) *1.))+
0.050000*np.tanh(data["abs_maxbatch_slices2_msignal"])+
0.050000*np.tanh(np.where(np.cos(((( data["signal"])*(np.where(data["minbatch"] > -998, data["signal_shift_+1"], data["meanbatch_msignal"])))))> -998,(-(( data["abs_avgbatch_msignal"]))), data["meanbatch_msignal"])) +
0.050000*np.tanh(np.cos(( data["maxbatch_msignal"])))+
0.050000*np.tanh(((( data["abs_minbatch_msignal"])<=(((data["abs_minbatch_slices2_msignal"])/ 2.0)))*1.))+
0.050000*np.tanh(np.where(((((-(((11.69715595245361328)))))<=(data["stdbatch_slices2_msignal"])) *1.) <= -998, data["signal_shift_-1"], np.where(data["signal_shift_-1"] <= -998,(((( 6.0)) <=(data["meanbatch_msignal"])) *1.) ,(-(( data["stdbatch_slices2_msignal"])))))) +
0.050000*np.tanh(((data["signal_shift_-1_msignal"])-(data["minbatch"])))+
0.050000*np.tanh(data["rangebatch_msignal"])+
0.050000*np.tanh(( -(((((-(((-(( data["abs_maxbatch_slices2"])))))))+(((((((((data["signal_shift_-1"])-(np.maximum(((data["abs_maxbatch_slices2"])) ,(((( data["signal_shift_-1_msignal"])/ 2.0)))))))/ 2.0)) -(data["maxtominbatch_slices2"])))*(((((( 4.0)) -(data["signal_shift_-1_msignal"])))*(data["meanbatch_msignal"])))))))))) +
0.050000*np.tanh(data["signal"])+
0.050000*np.tanh(( -(( np.where(data["maxtominbatch_slices2_msignal"] > -998, np.cos(((( data["stdbatch_slices2_msignal"])/ 2.0))),(((((((data["minbatch"])<=(data["abs_maxbatch_msignal"])) *1.))+(np.where(data["abs_avgbatch_slices2"] <= -998, np.cos(((( data["stdbatch_slices2_msignal"])/ 2.0))),(( data["stdbatch_slices2_msignal"])/ 2.0)))))/ 2.0)))))) +
0.050000*np.tanh(((((data["medianbatch_slices2"])-(np.sin(((((((((( data["signal_shift_-1"])-(data["signal_shift_+1"])))/ 2.0)) / 2.0)) -(((((data["abs_maxbatch_slices2"])-(data["maxbatch_msignal"])))*(((((((( data["maxbatch_msignal"])+(( -(( data["rangebatch_msignal"])))))/2.0)) / 2.0)) / 2.0)))))))))) -(data["maxbatch_msignal"])))+
0.050000*np.tanh(((np.maximum(((((np.cos(( data["mean_abs_chgbatch_slices2_msignal"])))*(( 1.19759941101074219))))),(((( np.cos(((( data["signal_shift_+1"])*(((( -(( data["meanbatch_slices2_msignal"])))) *(data["abs_maxbatch_msignal"])))))))/ 2.0)))))*(data["signal"])))+
0.050000*np.tanh(((( -(((( data["stdbatch_msignal"])-(data["minbatch"])))))) -(data["minbatch"])))+
0.050000*np.tanh(((((( -(((((((((((( np.sin(((((((((((np.cos(((( data["maxbatch_slices2"])/ 2.0)))) * 2.0)) >(data["meanbatch_slices2_msignal"])) *1.))* 2.0)) * 2.0)))) * 2.0)) >(data["signal_shift_+1"])) *1.))<=(data["abs_avgbatch_msignal"])) *1.))+(data["abs_avgbatch_msignal"])))))) * 2.0)) * 2.0)) +
0.050000*np.tanh(data["stdbatch_slices2"])+
0.050000*np.tanh(np.where(((data["medianbatch_slices2"])/ 2.0)<= -998, data["maxbatch_slices2_msignal"], np.where(np.minimum(((((data["signal"])*(np.sin(((((-(( np.sin(( data["mean_abs_chgbatch_msignal"])))))) / 2.0))))))),(((((((data["rangebatch_msignal"])+(data["mean_abs_chgbatch_msignal"])))<=(data["maxbatch_slices2_msignal"])) *1.))))> -998, np.sin(( np.sin(( data["abs_maxbatch"])))) , data["minbatch_slices2"])))+
0.050000*np.tanh(((np.maximum(((np.cos(( np.cos(((((data["stdbatch_slices2_msignal"])<=(data["signal"])) *1.))))))) ,(( data["minbatch_slices2"])))) *(data["abs_maxbatch_slices2"])))+
0.050000*np.tanh(((((((( data["abs_maxbatch"])+(data["abs_maxbatch_slices2"])))>(((((((((-(((( data["signal"])* 2.0)))))* 2.0)) >(((data["abs_maxbatch_slices2"])/ 2.0)))*1.))-(( -(((4.97659683227539062)))))))) *1.))-(((data["mean_abs_chgbatch_slices2_msignal"])-(( -(( np.where(data["maxtominbatch_msignal"] <= -998,(( data["stdbatch_slices2_msignal"])*(data["mean_abs_chgbatch_msignal"])) , data["abs_maxbatch_slices2_msignal"])))))))))+
0.050000*np.tanh(((((((( -(( data["signal_shift_+1"])))) >(data["stdbatch_slices2_msignal"])) *1.))<=(((data["maxbatch_slices2_msignal"])*(( -(((((( data["maxbatch_msignal"])*(np.tanh(( data["maxtominbatch"])))))-(data["maxbatch_msignal"])))))))))*1.))+
0.050000*np.tanh(np.maximum(((data["abs_minbatch_msignal"])) ,(((((data["meanbatch_slices2"])>(((((( data["stdbatch_slices2_msignal"])/ 2.0)) +(data["abs_minbatch_slices2"])) /2.0)))*1.))))) +
0.050000*np.tanh(((( data["maxtominbatch"])<=(( -(((( data["signal_shift_+1"])+(np.tanh(( np.minimum(((data["mean_abs_chgbatch_slices2"])) ,(( np.minimum(((np.minimum(((data["signal_shift_+1"])) ,(( data["mean_abs_chgbatch_slices2"]))))),(( data["abs_minbatch_slices2"])))))))))))))))*1.))+
0.050000*np.tanh(((data["signal_shift_+1"])-(((data["signal_shift_+1"])/ 2.0)))) +
0.050000*np.tanh(((((data["abs_minbatch_slices2_msignal"])*(data["meanbatch_msignal"])))-(np.where(((data["mean_abs_chgbatch_slices2"])+(((data["stdbatch_slices2"])+(data["minbatch_slices2_msignal"])))) > -998, data["abs_avgbatch_slices2_msignal"],(( data["signal_shift_-1_msignal"])+(((data["abs_avgbatch_msignal"])*(data["stdbatch_msignal"])))))))) +
0.050000*np.tanh(((((((((data["abs_avgbatch_slices2_msignal"])*(data["meanbatch_msignal"])))* 2.0)) -(data["abs_avgbatch_slices2_msignal"])))-(data["abs_avgbatch_slices2"])))+
0.050000*np.tanh(np.where(data["abs_minbatch_slices2_msignal"] <= -998, np.sin(((9.93030166625976562))),(( np.tanh(( np.sin(((((3.0)) -(np.maximum(((data["abs_maxbatch_slices2_msignal"])) ,(((-(( np.maximum(((data["maxtominbatch_slices2_msignal"])) ,(( data["abs_minbatch_slices2"])))))))))))))))) *(((data["abs_maxbatch_slices2_msignal"])* 2.0)))))+
0.050000*np.tanh(((np.where(( -(( data["abs_minbatch_slices2"])))> -998, np.where(data["medianbatch_msignal"] <= -998, data["meanbatch_slices2_msignal"],(-(( data["meanbatch_slices2_msignal"])))) , data["abs_minbatch_msignal"])) / 2.0)) +
0.050000*np.tanh(( -(((( data["maxbatch_msignal"])-(((data["signal_shift_+1_msignal"])-(data["mean_abs_chgbatch_slices2_msignal"])))))))) +
0.050000*np.tanh(((data["abs_minbatch_slices2"])-(np.where(((( np.sin(( np.where(data["signal_shift_-1"] > -998, data["abs_avgbatch_slices2_msignal"], data["abs_minbatch_slices2"])))) <=(((data["signal_shift_+1"])/ 2.0)))*1.) > -998, data["abs_avgbatch_slices2_msignal"], np.where(((np.cos(((( data["abs_maxbatch_slices2"])/ 2.0)))) / 2.0)<= -998,(( data["rangebatch_slices2_msignal"])-(np.where(data["abs_minbatch_slices2"] <= -998, data["signal_shift_-1"], data["abs_minbatch_slices2"]))), data["meanbatch_slices2"])))))+
0.050000*np.tanh(data["stdbatch_slices2"])+
0.050000*np.tanh(((((((((((( data["mean_abs_chgbatch_slices2_msignal"])>(data["signal_shift_-1_msignal"])) *1.))>(data["signal_shift_-1_msignal"])) *1.))+(data["maxtominbatch_slices2"])) /2.0)) -(data["mean_abs_chgbatch_msignal"])))+
0.050000*np.tanh(((((((data["medianbatch_msignal"])*(data["medianbatch_msignal"])))+(np.where(((data["maxbatch_slices2_msignal"])+(np.minimum(((((data["abs_avgbatch_slices2"])* 2.0))),(( data["abs_avgbatch_slices2"])))))> -998,(-(((((data["abs_avgbatch_slices2"])+(data["abs_avgbatch_msignal"])) /2.0)))) , np.where(data["maxtominbatch_slices2"] > -998, data["maxtominbatch"], data["maxbatch_slices2_msignal"])))))-(np.minimum(((data["maxbatch_slices2_msignal"])) ,(( data["abs_avgbatch_slices2"])))))) +
0.050000*np.tanh(((((( data["abs_avgbatch_slices2_msignal"])*(data["minbatch_slices2"])))+(np.minimum(((data["abs_maxbatch_slices2"])) ,(((((np.where(((((((( data["minbatch_slices2"])/ 2.0)) / 2.0)) +(( 9.89667701721191406)))/2.0)> -998, data["minbatch_slices2"],(((( data["abs_avgbatch_slices2_msignal"])*(data["minbatch_slices2"])))* 2.0)))<=(np.where(data["abs_minbatch_slices2_msignal"] > -998, data["abs_avgbatch_slices2_msignal"],(( data["abs_avgbatch_slices2_msignal"])* 2.0)))) *1.))))))/2.0)) +
0.050000*np.tanh(np.cos(( np.where(np.where(data["signal_shift_-1"] > -998,(((data["rangebatch_msignal"])+(np.minimum(((np.tanh(((((( data["abs_maxbatch_slices2"])-(( -(( data["signal_shift_+1"])))))) * 2.0))))),(( data["abs_minbatch_slices2_msignal"])))))/2.0), np.tanh(( data["signal_shift_+1"])))> -998, data["abs_minbatch_slices2_msignal"], data["stdbatch_slices2_msignal"])))) +
0.050000*np.tanh(( -(((((( data["abs_avgbatch_slices2_msignal"])+(data["abs_avgbatch_slices2_msignal"])))+(np.maximum(((((((data["stdbatch_msignal"])+(data["abs_avgbatch_slices2_msignal"])))/ 2.0))),(( np.cos(( np.minimum(((((( -(((( data["mean_abs_chgbatch_slices2_msignal"])+(np.cos(( np.minimum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(( data["abs_avgbatch_slices2_msignal"])))))))))))/ 2.0))),(( data["signal_shift_-1"])))))))))))))) +
0.050000*np.tanh(((((data["stdbatch_slices2"])-(data["maxbatch_msignal"])))* 2.0)) +
0.050000*np.tanh(((data["signal_shift_-1"])-(((((( data["abs_maxbatch_slices2_msignal"])>(((np.tanh(( np.cos(( np.where(data["rangebatch_msignal"] > -998, np.cos(( data["mean_abs_chgbatch_msignal"])) ,(( data["stdbatch_slices2"])*(((np.sin(( data["mean_abs_chgbatch_msignal"])))-(data["rangebatch_msignal"])))))))))) -(data["signal_shift_-1"])))) *1.))-(((data["abs_avgbatch_slices2"])*(((( data["maxbatch_slices2"])>(data["abs_maxbatch_slices2"])) *1.))))))))+
0.050000*np.tanh(((( data["maxtominbatch_msignal"])+(((data["mean_abs_chgbatch_slices2_msignal"])*(((data["medianbatch_slices2_msignal"])+(((( data["maxtominbatch"])<=(data["rangebatch_slices2_msignal"])) *1.))))))) /2.0)) +
0.050000*np.tanh(((data["abs_minbatch_msignal"])*(((( data["abs_maxbatch"])+(np.minimum(((data["maxtominbatch_msignal"])) ,(((( data["meanbatch_msignal"])-(((( -(( np.where(data["signal_shift_-1_msignal"] <= -998, data["medianbatch_slices2_msignal"], data["abs_avgbatch_slices2_msignal"])))))-(data["stdbatch_msignal"])))))))))/2.0)))) +
0.050000*np.tanh(((np.where(((data["maxbatch_msignal"])* 2.0)<= -998, data["signal_shift_-1"], np.sin(( np.cos(( data["mean_abs_chgbatch_slices2_msignal"])))))) * 2.0)) +
0.050000*np.tanh(np.where(np.where(data["minbatch"] > -998, data["abs_avgbatch_slices2_msignal"], data["abs_avgbatch_slices2_msignal"])> -998,(-(( data["abs_avgbatch_slices2_msignal"]))),(-(((((data["abs_maxbatch_slices2"])+(np.where(data["medianbatch_slices2"] > -998, np.where(data["minbatch_slices2_msignal"] > -998, data["abs_avgbatch_slices2_msignal"], np.sin(( data["stdbatch_slices2_msignal"]))), data["medianbatch_slices2"])))/2.0)))))) +
0.050000*np.tanh(np.where(((np.maximum(((((np.cos(( data["meanbatch_msignal"])))/ 2.0))),(( data["signal_shift_-1"])))) * 2.0)<= -998, data["minbatch_msignal"], data["rangebatch_slices2_msignal"])) +
0.050000*np.tanh(np.where(((((-(( data["signal"])))) >(data["signal_shift_+1"])) *1.) > -998,(( data["signal_shift_+1"])+(data["minbatch_slices2"])) , data["signal_shift_+1"])) +
0.050000*np.tanh(np.sin(( np.where(data["signal_shift_-1"] > -998, data["stdbatch_msignal"], np.where(data["signal_shift_-1"] > -998, data["stdbatch_msignal"],(((np.where(data["mean_abs_chgbatch_slices2"] > -998, data["stdbatch_msignal"], np.tanh(( np.cos(( data["abs_minbatch_slices2_msignal"])))))) <=(np.where(data["stdbatch_slices2"] <= -998, data["abs_maxbatch_msignal"], data["mean_abs_chgbatch_slices2"])))*1.))))))+
0.050000*np.tanh(( -(( data["abs_avgbatch_msignal"])))) +
0.050000*np.tanh(((np.where(np.where(data["abs_maxbatch_msignal"] <= -998,(((np.where(data["abs_avgbatch_slices2"] > -998, data["mean_abs_chgbatch_msignal"], data["maxbatch_msignal"])) +(data["abs_maxbatch_msignal"])) /2.0), data["abs_maxbatch_msignal"])<= -998, np.where(((data["abs_maxbatch_msignal"])-(data["abs_maxbatch_msignal"])) <= -998, data["abs_avgbatch_slices2"], data["minbatch_slices2"]), data["minbatch_slices2"])) -(data["stdbatch_slices2_msignal"])))+
0.050000*np.tanh(np.where(np.where(np.minimum(((data["stdbatch_msignal"])) ,(((( data["minbatch_slices2"])* 2.0)))) > -998, np.cos(((-(( np.sin(( data["rangebatch_msignal"]))))))), np.sin(( data["abs_avgbatch_msignal"])))<= -998, data["abs_maxbatch_slices2_msignal"],(( data["maxtominbatch"])+(((( -(( data["abs_avgbatch_slices2_msignal"])))) * 2.0)))))+
0.050000*np.tanh(data["abs_maxbatch_slices2"])+
0.050000*np.tanh(np.where(((((((( data["medianbatch_msignal"])+(data["abs_maxbatch_msignal"])))>(((( -(((( data["abs_maxbatch_msignal"])/ 2.0)))))* 2.0)))*1.))-(((data["stdbatch_slices2_msignal"])*(data["minbatch"])))) <= -998,(( np.tanh(( data["minbatch"])))/ 2.0),(((( data["medianbatch_msignal"])+(data["abs_maxbatch_msignal"])))*(data["medianbatch_slices2_msignal"])))) +
0.050000*np.tanh(np.where(((data["abs_avgbatch_slices2_msignal"])+(np.where(data["mean_abs_chgbatch_slices2_msignal"] <= -998, data["medianbatch_slices2_msignal"], data["maxbatch_msignal"])))<= -998, np.where(data["abs_avgbatch_slices2"] <= -998, data["minbatch_slices2"],(( data["minbatch"])-(((((( data["abs_avgbatch_slices2"])+(data["abs_avgbatch_slices2_msignal"])))+(data["mean_abs_chgbatch_slices2_msignal"])) /2.0)))) ,(( data["minbatch"])-(((( data["mean_abs_chgbatch_slices2_msignal"])+(data["mean_abs_chgbatch_slices2_msignal"])) /2.0)))))+
0.050000*np.tanh(((data["maxbatch_msignal"])+(((( np.minimum(((( -(( data["abs_avgbatch_msignal"]))))),(( np.maximum(((data["maxbatch_slices2_msignal"])) ,(( data["maxbatch_slices2_msignal"])))))))<=(((((data["maxtominbatch"])*(data["abs_avgbatch_msignal"])))+(data["maxbatch_msignal"])))) *1.))))+
0.050000*np.tanh(((data["abs_minbatch_slices2_msignal"])*(((data["maxbatch_slices2_msignal"])+(((data["abs_avgbatch_slices2_msignal"])-(np.cos(((((data["minbatch_slices2"])>(((np.where(data["maxtominbatch_slices2"] <= -998, data["meanbatch_msignal"], data["abs_minbatch_msignal"])) -(((( np.where(data["abs_maxbatch_msignal"] > -998, data["stdbatch_slices2_msignal"], data["maxtominbatch"])) +(np.cos(((( data["abs_avgbatch_slices2_msignal"])* 2.0)))))/2.0)))))*1.))))))))))+
0.050000*np.tanh(((np.where(data["mean_abs_chgbatch_slices2_msignal"] > -998, data["medianbatch_slices2"],(0.31864652037620544)))+(( -(((( np.where(data["abs_minbatch_slices2_msignal"] <= -998, np.minimum(((data["meanbatch_slices2_msignal"])) ,(( np.where(np.where(np.minimum(((data["abs_avgbatch_slices2"])) ,(( np.cos(( data["mean_abs_chgbatch_slices2_msignal"])))))<= -998, data["abs_avgbatch_slices2"], data["maxbatch_msignal"])> -998, data["abs_minbatch_slices2"], data["abs_maxbatch"])))) , data["abs_maxbatch_slices2_msignal"])) * 2.0)))))))+
0.050000*np.tanh(((( data["meanbatch_msignal"])+(((data["minbatch_slices2_msignal"])+(((((np.where(( -(( data["mean_abs_chgbatch_slices2"])))> -998, data["stdbatch_slices2_msignal"], data["rangebatch_slices2_msignal"])) * 2.0)) *(((data["meanbatch_msignal"])/ 2.0)))))))/2.0)) +
0.050000*np.tanh(((data["minbatch_msignal"])*(((((((((data["maxtominbatch_slices2"])<=(data["rangebatch_slices2_msignal"])) *1.))+(data["abs_avgbatch_slices2_msignal"])))+(((((-(( np.minimum(((data["rangebatch_slices2_msignal"])) ,(((((data["medianbatch_slices2_msignal"])+(((( data["stdbatch_slices2_msignal"])<=(( -(((-(( data["medianbatch_msignal"])))))))) *1.))) /2.0)))))))) <=(((data["abs_maxbatch_slices2"])-(((data["minbatch_slices2"])+(data["signal_shift_+1"])))))) *1.))) /2.0)))) +
0.050000*np.tanh(((((np.where(((((( -(( data["abs_avgbatch_msignal"])))) +(data["medianbatch_msignal"])))+(np.where(data["rangebatch_slices2_msignal"] <= -998,(((((( data["rangebatch_slices2_msignal"])+(np.cos(((( data["signal"])-(data["stdbatch_slices2_msignal"])))))) /2.0)) +(data["rangebatch_slices2_msignal"])) /2.0), data["abs_avgbatch_msignal"])))<= -998, data["abs_maxbatch"], np.sin(( data["stdbatch_slices2_msignal"])))) * 2.0)) * 2.0)) +
0.050000*np.tanh(( -(((( data["rangebatch_msignal"])-(((np.where(data["signal_shift_-1_msignal"] <= -998, np.maximum(((np.maximum(((data["medianbatch_slices2_msignal"])) ,(((( data["meanbatch_slices2_msignal"])*(((data["abs_avgbatch_slices2_msignal"])* 2.0)))))))) ,(((((( data["meanbatch_slices2_msignal"])* 2.0)) *(data["rangebatch_msignal"]))))),(( data["meanbatch_slices2_msignal"])*(data["stdbatch_slices2_msignal"])))) / 2.0)))))))+
0.050000*np.tanh(((np.cos(( data["maxtominbatch_msignal"])))*(((data["abs_minbatch_slices2_msignal"])+(np.where(data["stdbatch_slices2"] <= -998,(( data["minbatch_slices2"])+(data["medianbatch_slices2_msignal"])) , np.cos(( data["maxtominbatch_msignal"])))))))) +
0.050000*np.tanh(np.where(((np.cos(((((((( data["abs_maxbatch"])*(data["meanbatch_msignal"])))+(data["maxbatch_msignal"])))* 2.0)))) * 2.0)<= -998,(( data["maxbatch_msignal"])+(((data["maxbatch_msignal"])+(data["meanbatch_msignal"])))) ,(-(((((( data["maxbatch_msignal"])+(data["meanbatch_msignal"])))*(np.where(data["signal_shift_-1"] <= -998, data["minbatch_slices2_msignal"], data["abs_maxbatch"])))))))) +
0.050000*np.tanh(np.where(data["meanbatch_slices2_msignal"] > -998,(( data["signal"])+(((data["signal"])-(np.maximum(((np.where(data["signal"] > -998, data["medianbatch_slices2"], data["abs_minbatch_slices2"]))),(((8.37151908874511719)))))))) , np.cos(( data["stdbatch_msignal"])))) +
0.050000*np.tanh(( -(((( data["abs_maxbatch_msignal"])+(np.where(np.where(data["abs_maxbatch_msignal"] <= -998, data["abs_maxbatch_msignal"],(( data["abs_avgbatch_slices2"])/ 2.0)) > -998, data["meanbatch_msignal"],(((( -(((( data["abs_maxbatch_msignal"])+(data["stdbatch_slices2_msignal"])))))) >(((np.where(data["meanbatch_msignal"] > -998, data["abs_maxbatch_slices2"], np.where(data["abs_maxbatch_msignal"] <= -998, data["mean_abs_chgbatch_msignal"],(9.0)))) *(data["meanbatch_slices2"])))) *1.))))))))+
0.050000*np.tanh(((data["minbatch_msignal"])*(np.where(data["abs_avgbatch_msignal"] > -998, np.where(np.where(data["abs_maxbatch_slices2_msignal"] > -998, data["stdbatch_slices2_msignal"],(((data["signal_shift_-1"])>(data["stdbatch_msignal"])) *1.))<= -998,(( data["abs_avgbatch_msignal"])-(np.cos(( data["abs_avgbatch_msignal"])))) , np.cos(( data["abs_avgbatch_msignal"]))), data["abs_maxbatch_slices2_msignal"])))) +
0.050000*np.tanh(np.where(data["mean_abs_chgbatch_slices2_msignal"] <= -998, data["signal_shift_+1"],(( np.sin(((((( np.sin(( np.where(data["signal_shift_-1"] > -998, data["minbatch_slices2"], data["signal_shift_-1"])))) * 2.0)) * 2.0)))) -(((data["meanbatch_msignal"])+(np.cos(( np.sin(((((data["signal_shift_-1_msignal"])+(data["signal_shift_-1"])) /2.0)))))))))))+
0.050000*np.tanh(((np.sin(( data["signal"])))*(data["signal"])))+
0.050000*np.tanh(((data["signal_shift_-1"])-(((np.where(np.where(( 3.0)<= -998, data["meanbatch_slices2"], data["abs_minbatch_slices2"])> -998, np.where(((((((((( data["signal_shift_-1"])+(np.where(data["signal_shift_-1"] > -998, data["abs_avgbatch_slices2"], data["signal"])))) / 2.0)) <=(data["maxbatch_slices2_msignal"])) *1.))-(data["stdbatch_slices2"])) <= -998, data["abs_maxbatch"], data["maxbatch_msignal"]), data["signal_shift_+1"])) * 2.0)))) +
0.050000*np.tanh(( -(( np.where(np.maximum(((data["stdbatch_slices2"])) ,(( data["abs_maxbatch_slices2"])))> -998, data["medianbatch_msignal"], data["maxbatch_slices2"])))))+
0.050000*np.tanh(np.where(( 5.29157781600952148)> -998,(-(( data["abs_avgbatch_msignal"]))),(((((( data["signal_shift_-1"])+(data["abs_avgbatch_msignal"])))+(np.sin(( data["abs_avgbatch_msignal"])))))-(data["abs_avgbatch_msignal"])))) +
0.050000*np.tanh(((( -(( data["abs_avgbatch_msignal"])))) -(((( data["maxbatch_msignal"])+(((np.tanh(((((((( -(( data["abs_avgbatch_msignal"])))) * 2.0)) +(data["rangebatch_slices2"])) /2.0)))) -(( -(( np.where(( -(( data["abs_avgbatch_msignal"])))<= -998, data["meanbatch_slices2_msignal"], np.minimum(((data["abs_avgbatch_slices2_msignal"])) ,(((-(( data["abs_avgbatch_msignal"])))))))))))))) /2.0)))) +
0.050000*np.tanh(np.where(data["signal_shift_-1"] <= -998, np.minimum(((data["abs_maxbatch_slices2_msignal"])) ,(((( data["signal_shift_+1"])*(data["signal_shift_-1"]))))),(((((((((((((data["medianbatch_slices2"])>(( -(( data["medianbatch_slices2"])))))*1.))+(data["medianbatch_slices2"])) /2.0)) -(data["abs_maxbatch_msignal"])))+(data["signal_shift_-1"])) /2.0)) -(data["abs_maxbatch_msignal"])))) +
0.050000*np.tanh(((((np.where(np.cos(( data["mean_abs_chgbatch_msignal"])) <= -998, data["abs_maxbatch_slices2"], np.cos(( np.where(((data["rangebatch_slices2_msignal"])+(data["signal_shift_-1"])) > -998, data["mean_abs_chgbatch_slices2_msignal"],(( data["abs_maxbatch_slices2"])-(( -(( np.maximum(((data["rangebatch_slices2_msignal"])) ,(( data["signal_shift_-1"])))))))))))))-(np.where(data["stdbatch_slices2_msignal"] > -998, data["mean_abs_chgbatch_slices2_msignal"], data["mean_abs_chgbatch_slices2_msignal"])))) -(data["rangebatch_slices2_msignal"])))+
0.050000*np.tanh(np.where(((( data["rangebatch_slices2_msignal"])+(data["signal"])) /2.0)<= -998, np.maximum(((((np.cos(( data["abs_minbatch_slices2_msignal"])))* 2.0))),(((-(( np.sin(( data["rangebatch_slices2_msignal"])))))))) , np.where(np.maximum(((data["signal"])) ,(((-(( data["signal"])))))) <= -998, data["meanbatch_slices2"],(((data["signal"])+(( -(( data["rangebatch_slices2_msignal"])))))/2.0)))) +
0.050000*np.tanh(((np.minimum(((((((np.sin(((( data["maxtominbatch_msignal"])-(data["maxtominbatch_msignal"])))))-(( -(( data["mean_abs_chgbatch_slices2_msignal"])))))) +(((((data["abs_minbatch_msignal"])+(((data["minbatch_slices2"])*(( 2.14036393165588379)))))) +(((data["stdbatch_slices2_msignal"])+(( -(( data["abs_minbatch_msignal"]))))))))))),(( data["abs_minbatch_msignal"])))) *(np.sin(( data["abs_minbatch_msignal"])))))+
0.050000*np.tanh(((np.sin(( data["stdbatch_msignal"])))*(np.maximum(((data["signal_shift_+1"])) ,(( data["abs_maxbatch_slices2_msignal"])))))) +
0.050000*np.tanh(((data["maxbatch_slices2"])*(np.cos(( np.where(((( data["signal_shift_+1_msignal"])>(data["abs_maxbatch"])) *1.) > -998, data["mean_abs_chgbatch_msignal"], np.where(np.maximum(((((( -(( data["abs_maxbatch"])))) * 2.0))),(( data["rangebatch_msignal"])))<= -998, data["maxbatch_slices2"], np.where(data["medianbatch_slices2"] > -998,(((( data["mean_abs_chgbatch_msignal"])+(data["rangebatch_slices2"])))*(np.cos(( data["abs_maxbatch"])))) , data["medianbatch_slices2_msignal"])))))))) +
0.050000*np.tanh(((data["signal_shift_+1"])-(((( data["rangebatch_slices2_msignal"])+(np.tanh(( np.maximum(((((((((((-(((((( 12.83940505981445312)) +(data["signal_shift_+1"])) /2.0)))))+(data["minbatch_slices2_msignal"])) /2.0)) -(((data["signal_shift_+1_msignal"])-(data["rangebatch_slices2_msignal"])))))-(data["signal_shift_+1"])))) ,(( data["abs_avgbatch_slices2_msignal"])))))))/2.0)))) +
0.050000*np.tanh(((np.where(data["minbatch"] > -998, data["minbatch"], np.maximum(((((np.where(data["stdbatch_slices2"] <= -998, data["medianbatch_slices2"], data["mean_abs_chgbatch_slices2_msignal"])) / 2.0))),(( data["mean_abs_chgbatch_slices2"])))))-(np.where(data["abs_minbatch_msignal"] > -998, np.where(np.maximum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(( data["minbatch"])))<= -998, data["signal_shift_-1"], data["mean_abs_chgbatch_msignal"]), data["mean_abs_chgbatch_slices2_msignal"])))) +
0.050000*np.tanh(((( -(((((((data["abs_maxbatch_slices2_msignal"])* 2.0)) +(np.where(((((data["maxbatch_msignal"])* 2.0)) -(data["abs_avgbatch_slices2"])) > -998, data["medianbatch_msignal"],(((((((( data["medianbatch_msignal"])* 2.0)) +(data["maxbatch_msignal"])) /2.0)) +(((( 8.0)) -(data["maxbatch_msignal"])))) /2.0)))) /2.0)))))* 2.0)) +
0.050000*np.tanh(((data["minbatch_slices2"])*(((data["abs_avgbatch_slices2_msignal"])+(((np.tanh(( np.where(np.where(data["minbatch_slices2"] > -998, np.maximum(((((( data["mean_abs_chgbatch_slices2_msignal"])<=(data["minbatch_slices2"])) *1.))) ,(( np.maximum(((data["signal"])) ,(( np.maximum(((data["signal"])) ,(( data["minbatch_slices2"]))))))))), data["medianbatch_slices2"])<= -998, data["maxtominbatch_slices2"], data["signal_shift_+1"])))) * 2.0)))))) +
0.050000*np.tanh(((data["signal_shift_+1"])-(np.where(( -(( np.maximum(((data["abs_avgbatch_msignal"])) ,(((-(( data["abs_avgbatch_msignal"])))))))))> -998, data["rangebatch_slices2_msignal"], data["medianbatch_slices2"])))) +
0.050000*np.tanh(np.cos(((((((data["signal_shift_-1"])+(((( data["abs_maxbatch_slices2_msignal"])+(data["meanbatch_slices2"])) /2.0)))/2.0)) +(np.tanh(( np.where(np.where(data["abs_maxbatch_slices2"] <= -998, data["minbatch"], data["medianbatch_msignal"])<= -998,(( np.where(( 3.0)> -998,(3.0), data["meanbatch_msignal"])) -(data["mean_abs_chgbatch_slices2_msignal"])) ,(-(( data["minbatch"])))))))))))+
0.050000*np.tanh(((((( np.minimum(((data["meanbatch_slices2"])) ,(( data["medianbatch_slices2_msignal"])))) *(((data["stdbatch_msignal"])*(np.where(data["mean_abs_chgbatch_msignal"] > -998, data["signal"],(((-(( data["signal_shift_+1"])))) * 2.0)))))))+(((data["medianbatch_slices2_msignal"])*(((np.minimum(((data["medianbatch_slices2_msignal"])) ,(( data["signal"])))) *(np.sin(( np.maximum(((data["signal"])) ,(( data["maxbatch_slices2"])))))))))))/2.0)) +
0.050000*np.tanh(((data["signal_shift_-1"])+(( -(((( data["rangebatch_msignal"])+(np.where(np.where(data["abs_maxbatch_slices2_msignal"] <= -998,(((((((data["signal"])<=(data["signal_shift_-1"])) *1.))+(( -(( data["maxbatch_msignal"])))))) -(data["mean_abs_chgbatch_slices2_msignal"])) ,(((data["maxbatch_slices2"])<=(((data["abs_maxbatch_slices2"])/ 2.0)))*1.))> -998, data["abs_avgbatch_slices2_msignal"], data["signal"])))))))))+
0.050000*np.tanh(((( -(( np.where(((data["mean_abs_chgbatch_slices2_msignal"])+(data["rangebatch_slices2_msignal"])) > -998,(( data["mean_abs_chgbatch_slices2_msignal"])+(data["rangebatch_slices2_msignal"])) , np.maximum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(( np.maximum(((np.cos(( data["minbatch_slices2_msignal"])))) ,(( data["mean_abs_chgbatch_slices2_msignal"])))))))))))* 2.0)) +
0.050000*np.tanh(((data["signal_shift_-1"])-(((((data["maxbatch_slices2_msignal"])-(np.cos(( data["signal_shift_-1"])))))+(((( data["signal_shift_+1"])>(np.sin(( np.minimum(((((data["maxtominbatch_slices2"])-(((( data["signal_shift_-1"])<=(( -(( data["signal_shift_-1"])))))*1.))))) ,(((-(( data["maxbatch_slices2_msignal"])))))))))) *1.))))))+
0.050000*np.tanh(np.minimum(((np.minimum(((data["medianbatch_slices2"])) ,(( np.maximum(((data["abs_avgbatch_msignal"])) ,(( data["medianbatch_slices2"])))))))) ,(( np.maximum(((((( data["signal_shift_+1"])+(((( data["maxtominbatch_slices2"])+(data["maxbatch_slices2"])) /2.0)))/2.0))),(( data["maxtominbatch_slices2"])))))))+
0.050000*np.tanh(((data["abs_avgbatch_slices2"])*(((((((((((-(( data["minbatch_msignal"])))) +(data["meanbatch_slices2"])) /2.0)) -(data["signal_shift_-1_msignal"])))-(data["stdbatch_msignal"])))*(np.sin(( data["signal"])))))))+
0.050000*np.tanh(np.cos(( np.where(data["rangebatch_slices2_msignal"] <= -998, data["maxtominbatch_slices2_msignal"], np.minimum(((data["mean_abs_chgbatch_msignal"])) ,(( data["abs_maxbatch"])))))))+
0.050000*np.tanh(data["abs_maxbatch_slices2"])+
0.050000*np.tanh(((np.sin(( data["stdbatch_msignal"])))-(np.where(((data["abs_minbatch_msignal"])+(data["maxtominbatch_slices2_msignal"])) > -998,(( data["rangebatch_slices2_msignal"])+(data["stdbatch_msignal"])) ,(((1.03578352928161621)) +(data["stdbatch_slices2_msignal"])))))) +
0.050000*np.tanh(np.sin(( np.where(((np.sin(( np.where(data["maxtominbatch_msignal"] <= -998, data["medianbatch_msignal"], data["medianbatch_msignal"])))) * 2.0)<= -998, data["signal_shift_-1"], data["medianbatch_msignal"])))) +
0.050000*np.tanh(((( -(( np.minimum(((((( np.minimum(((((data["rangebatch_slices2_msignal"])+(np.sin(((( data["maxtominbatch_slices2_msignal"])-(data["maxtominbatch_slices2_msignal"])))))))) ,(( data["rangebatch_slices2_msignal"])))) +(np.tanh(( np.maximum(((data["maxbatch_msignal"])) ,(( data["minbatch_msignal"])))))))/2.0))),(( data["rangebatch_slices2_msignal"])))))))-(data["stdbatch_msignal"])))+
0.050000*np.tanh(((((((( data["signal"])*(((np.sin(( np.where(data["maxtominbatch_msignal"] <= -998, np.sin(( data["rangebatch_msignal"])) , data["signal"])))) * 2.0)))) +(((np.sin(( np.where(data["maxbatch_slices2"] <= -998, data["abs_minbatch_msignal"],(-(( data["mean_abs_chgbatch_slices2"])))))))-(data["stdbatch_slices2_msignal"])))) /2.0)) * 2.0)) +
0.050000*np.tanh(((((np.where(np.cos(((((( np.where(((((data["mean_abs_chgbatch_msignal"])* 2.0)) * 2.0)> -998, np.cos(( data["stdbatch_slices2_msignal"])) , data["stdbatch_slices2_msignal"])) * 2.0)) * 2.0)))> -998, np.cos(( data["stdbatch_slices2_msignal"])) ,(( np.cos(( data["stdbatch_slices2_msignal"])))* 2.0)))* 2.0)) * 2.0)) +
0.050000*np.tanh(np.cos(( np.minimum(((data["mean_abs_chgbatch_msignal"])) ,(((((data["signal_shift_-1"])<=(((np.cos(( np.minimum(((np.minimum(((data["signal_shift_-1"])) ,(( data["abs_minbatch_slices2_msignal"]))))),(( data["maxbatch_slices2_msignal"])))))) +(np.cos(( np.minimum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(((((((data["medianbatch_msignal"])+(( -(((( data["signal_shift_-1"])*(data["rangebatch_slices2_msignal"])))))))) <=(data["mean_abs_chgbatch_msignal"])) *1.))))))))))*1.))))))) +
0.050000*np.tanh(((data["stdbatch_slices2_msignal"])*(np.where(np.sin(( np.sin(( data["abs_minbatch_msignal"])))) <= -998,(( data["stdbatch_slices2_msignal"])*(np.sin(( data["abs_minbatch_msignal"])))) ,(( np.sin(( data["abs_minbatch_msignal"])))/ 2.0)))))+
0.050000*np.tanh(((((( data["stdbatch_slices2_msignal"])*(data["meanbatch_msignal"])))+(( -(( np.where(np.sin(( data["meanbatch_msignal"])) > -998,(8.85711002349853516),(-(( data["meanbatch_msignal"])))))))))/2.0)) +
0.050000*np.tanh(np.cos(( np.maximum(((np.minimum(((data["maxtominbatch_msignal"])) ,(( data["medianbatch_slices2_msignal"]))))),(( data["signal_shift_-1"])))))) +
0.050000*np.tanh(np.where(data["abs_maxbatch_msignal"] <= -998, data["minbatch_slices2"], np.minimum(((np.where(data["abs_maxbatch_msignal"] <= -998,(( data["minbatch_slices2"])-(data["rangebatch_msignal"])) , np.minimum(((((np.maximum(((data["maxbatch_slices2"])) ,(( data["signal"])))) -(((( data["rangebatch_msignal"])+(((data["abs_minbatch_slices2_msignal"])-(data["rangebatch_msignal"])))) /2.0))))),(( data["signal_shift_+1"])))))) ,(( data["rangebatch_msignal"])))))+
0.050000*np.tanh(np.maximum(((((((np.where(((data["mean_abs_chgbatch_slices2"])-(data["minbatch_slices2_msignal"])) > -998, np.cos(( data["mean_abs_chgbatch_slices2_msignal"])) ,(-(( data["rangebatch_slices2"])))))/ 2.0)) * 2.0))),(( data["minbatch_slices2_msignal"])))) +
0.050000*np.tanh(((((data["signal_shift_-1"])-(data["abs_maxbatch"])))-(np.where(((((data["signal_shift_+1"])-(((data["maxbatch_msignal"])-(data["meanbatch_msignal"])))))* 2.0)<= -998, data["signal_shift_-1"],(((( data["maxbatch_msignal"])-(data["signal_shift_+1"])))+(((( np.sin(( data["meanbatch_msignal"])))<=(data["medianbatch_msignal"])) *1.))))))) +
0.050000*np.tanh(((np.sin(( data["abs_minbatch_msignal"])))*(((data["mean_abs_chgbatch_slices2_msignal"])-(np.sin(( data["maxbatch_msignal"])))))))+
0.050000*np.tanh(((data["signal_shift_-1"])*(((((( data["medianbatch_msignal"])*(data["abs_avgbatch_msignal"])))+(data["mean_abs_chgbatch_slices2_msignal"])) /2.0)))) +
0.050000*np.tanh(((((np.where(((np.sin(( data["signal_shift_-1"])))* 2.0)> -998, data["signal_shift_-1"], data["signal_shift_-1"])) -(data["rangebatch_msignal"])))* 2.0)) +
0.050000*np.tanh(((data["signal_shift_+1"])-(np.where(((data["meanbatch_msignal"])* 2.0)> -998,(6.0),(((6.0)) -(data["abs_maxbatch_slices2"])))))) +
0.050000*np.tanh(((((((np.where(np.cos(( data["mean_abs_chgbatch_slices2"])) > -998,(( data["signal_shift_-1_msignal"])-(data["medianbatch_msignal"])) , data["abs_minbatch_slices2"])) -(data["abs_avgbatch_msignal"])))*(np.where(((( data["signal_shift_+1"])+(data["mean_abs_chgbatch_slices2"])) /2.0)> -998,(( data["signal_shift_-1_msignal"])-(data["medianbatch_msignal"])) , data["abs_maxbatch_slices2_msignal"])))) -(np.where(data["signal_shift_-1_msignal"] > -998, data["rangebatch_slices2_msignal"], data["medianbatch_slices2_msignal"])))) +
0.050000*np.tanh(((((((data["abs_avgbatch_msignal"])-(data["maxtominbatch"])))*(data["mean_abs_chgbatch_msignal"])))*(( 5.33403539657592773)))) +
0.050000*np.tanh(np.sin(( np.where(np.sin(( np.where(((data["maxtominbatch_slices2_msignal"])-(data["abs_maxbatch_slices2_msignal"])) > -998, np.sin(( data["signal"])) ,(( data["signal"])+(data["abs_maxbatch"])))))> -998, np.where(data["mean_abs_chgbatch_msignal"] > -998, data["maxbatch_slices2"], data["stdbatch_slices2_msignal"]), data["signal_shift_+1_msignal"])))) +
0.050000*np.tanh(((data["maxbatch_slices2"])*(np.where(data["signal_shift_-1_msignal"] <= -998,(( data["medianbatch_slices2"])+(np.where(((data["signal_shift_-1"])+(data["signal_shift_-1"])) <= -998, data["abs_minbatch_slices2_msignal"],(( data["signal_shift_-1"])+(data["signal_shift_-1"]))))), np.sin(( data["medianbatch_msignal"])))))) +
0.050000*np.tanh(np.maximum(((((data["medianbatch_msignal"])* 2.0))),(( np.cos(( data["abs_maxbatch_slices2_msignal"])))))) +
0.050000*np.tanh(np.where(np.where(data["signal_shift_-1"] > -998, data["abs_maxbatch_slices2"], np.minimum(((((data["medianbatch_slices2"])*(((( 0.20071868598461151)) / 2.0))))),(( data["maxtominbatch"])))) > -998, data["signal_shift_-1"], np.minimum(((((data["maxtominbatch_slices2"])/ 2.0))),(( data["maxtominbatch"])))))+
0.050000*np.tanh(( -(((( np.sin(( np.where(data["stdbatch_msignal"] > -998, data["abs_minbatch_slices2_msignal"], np.where(data["minbatch"] > -998, data["abs_minbatch_slices2_msignal"], data["maxbatch_msignal"])))))* 2.0)))))+
0.050000*np.tanh(((data["signal_shift_+1"])-(np.maximum(((data["signal_shift_+1"])) ,(((( np.maximum(((data["maxbatch_slices2_msignal"])) ,(((( np.cos(( data["signal_shift_-1"])))*(np.sin(( np.cos(( data["stdbatch_msignal"])))))))))) * 2.0)))))))+
0.050000*np.tanh(((np.cos(( np.where(data["signal"] > -998, data["signal_shift_-1"], np.maximum(((np.where(( 3.0)> -998, data["signal_shift_-1"], data["minbatch_slices2_msignal"]))),(( data["medianbatch_slices2"])))))))*(data["signal_shift_-1"])))+
0.050000*np.tanh(np.where(((data["signal"])* 2.0)<= -998, data["abs_maxbatch_msignal"], np.where(((data["abs_maxbatch"])+(((( data["signal"])<=(data["rangebatch_msignal"])) *1.))) <= -998, data["minbatch_slices2"],(( data["signal"])-(np.minimum(((data["rangebatch_msignal"])) ,(( data["rangebatch_msignal"])))))))) +
0.050000*np.tanh(np.maximum(((np.minimum(((data["abs_maxbatch"])) ,(( data["signal_shift_-1"]))))),(( data["abs_maxbatch_slices2_msignal"])))) +
0.050000*np.tanh(((((((((( -(((-(( np.minimum(((((( -(( data["rangebatch_slices2_msignal"])))) * 2.0))),(((11.00670146942138672)))))))))))/ 2.0)) <=(np.cos(( data["stdbatch_slices2"])))) *1.))<=(np.where(( 9.0)<= -998,(((((( data["stdbatch_slices2"])>(data["meanbatch_msignal"])) *1.))+(data["signal_shift_-1_msignal"])) /2.0), data["abs_minbatch_msignal"])))*1.))+
0.050000*np.tanh(np.where(data["abs_maxbatch_slices2_msignal"] > -998,(((( 9.0)) +(data["maxtominbatch"])) /2.0),(( np.cos(( np.where(data["signal_shift_+1"] <= -998, data["meanbatch_slices2"], data["abs_maxbatch_slices2_msignal"])))) * 2.0)))+
0.050000*np.tanh(np.cos(( np.where(np.cos(((((( data["mean_abs_chgbatch_msignal"])/ 2.0)) +(((((data["signal_shift_+1_msignal"])+(data["signal_shift_+1_msignal"])))/ 2.0)))))<= -998, np.where(((((10.83226490020751953)) +(data["abs_avgbatch_msignal"])) /2.0)> -998, data["mean_abs_chgbatch_slices2_msignal"], np.tanh(((( data["abs_maxbatch"])*(np.minimum(((data["abs_avgbatch_slices2"])) ,(( np.cos(( data["signal_shift_+1"])))))))))) , data["mean_abs_chgbatch_slices2_msignal"])))) +
0.050000*np.tanh(((np.sin(((( data["abs_maxbatch"])-(np.where(data["meanbatch_slices2"] > -998, data["signal_shift_+1"],(( np.where(data["abs_maxbatch_slices2"] > -998, data["signal_shift_+1"],(( np.maximum(((( -(( data["meanbatch_slices2"]))))),(((-(( data["minbatch_slices2"])))))))/ 2.0)))/ 2.0)))))))* 2.0)) +
0.050000*np.tanh(data["meanbatch_slices2"])+
0.050000*np.tanh(np.where(data["mean_abs_chgbatch_slices2_msignal"] <= -998,(((data["meanbatch_slices2"])>(np.where(np.where(np.cos(( np.cos(( data["mean_abs_chgbatch_slices2_msignal"])))) > -998, np.tanh(( data["medianbatch_slices2"])) , data["minbatch_slices2_msignal"])<= -998, np.cos(( data["minbatch_slices2"])) , data["meanbatch_msignal"])))*1.) , np.cos(((((data["mean_abs_chgbatch_slices2_msignal"])>(data["signal_shift_-1_msignal"])) *1.))))) +
0.050000*np.tanh(np.where(np.cos(((((data["maxtominbatch"])+(((((data["abs_avgbatch_slices2_msignal"])-(( -(((( data["minbatch_slices2_msignal"])+(( -(( np.tanh(( data["abs_avgbatch_slices2_msignal"])))))))))))))*(data["signal"])))) /2.0)))> -998,(( np.sin(( data["signal"])))*(data["rangebatch_slices2_msignal"])) , data["rangebatch_msignal"])) +
0.050000*np.tanh(((data["signal_shift_-1"])-(((((7.94279861450195312)) +(((((( data["signal_shift_-1_msignal"])-(np.sin(( np.cos(( np.cos(( data["abs_avgbatch_msignal"])))))))))+(np.maximum(((data["signal_shift_+1"])) ,(( data["signal_shift_-1_msignal"])))))/2.0)))/2.0)))) +
0.050000*np.tanh(((((np.maximum(((np.maximum(((data["signal_shift_+1"])) ,(( data["minbatch"]))))),(((2.0)))))+(data["minbatch"])))-(((((( -(( data["meanbatch_msignal"])))) / 2.0)) *(((((( data["minbatch"])<=(( -(( data["abs_maxbatch"])))))*1.))/ 2.0)))))) +
0.050000*np.tanh(np.sin(( np.where(data["maxbatch_slices2"] <= -998,(( data["maxbatch_msignal"])+(data["abs_maxbatch_slices2_msignal"])) , data["abs_maxbatch"])))) +
0.050000*np.tanh(( -(( np.maximum(((data["mean_abs_chgbatch_msignal"])) ,(((( np.cos(( data["signal_shift_+1"])))*(np.where(np.maximum(((data["abs_maxbatch_slices2_msignal"])) ,(((((data["abs_maxbatch_slices2_msignal"])>(data["minbatch_slices2"])) *1.))))> -998,(( data["minbatch_slices2"])+(data["mean_abs_chgbatch_msignal"])) , np.sin(( data["maxbatch_slices2"])))))))))))) +
0.050000*np.tanh(np.where(((np.tanh(((((((((data["abs_maxbatch"])* 2.0)) / 2.0)) <=(data["medianbatch_slices2"])) *1.))))* 2.0)> -998, np.cos(( data["mean_abs_chgbatch_msignal"])) , data["abs_maxbatch_slices2_msignal"])) +
0.050000*np.tanh(data["signal_shift_+1"])+
0.050000*np.tanh(((((np.cos(( data["signal_shift_-1"])))*(data["abs_minbatch_slices2_msignal"])))*(data["minbatch_slices2_msignal"])))+
0.050000*np.tanh(np.where(data["abs_minbatch_msignal"] <= -998, data["signal_shift_+1_msignal"], data["signal_shift_-1_msignal"])) +
0.050000*np.tanh(np.where(((np.where(np.sin(( data["maxbatch_msignal"])) <= -998, data["maxbatch_slices2_msignal"], data["medianbatch_slices2"])) +(data["maxbatch_slices2"])) <= -998, data["abs_maxbatch"], np.where(data["maxbatch_slices2_msignal"] > -998, data["signal_shift_-1_msignal"], np.minimum(((((((((((((data["minbatch_slices2_msignal"])+(np.maximum(((data["signal_shift_+1_msignal"])) ,(( data["signal_shift_-1_msignal"])))))) +(data["abs_minbatch_slices2"])) /2.0)) +(data["meanbatch_slices2"])) /2.0)) / 2.0))),(( data["stdbatch_msignal"])))))) +
0.050000*np.tanh(np.cos(( np.where(data["rangebatch_slices2_msignal"] <= -998,(((( np.where(np.where(((data["minbatch_slices2"])/ 2.0)> -998, np.cos(( data["mean_abs_chgbatch_msignal"])) , np.where(data["rangebatch_slices2_msignal"] <= -998, data["mean_abs_chgbatch_msignal"], data["mean_abs_chgbatch_slices2_msignal"])) <= -998,(( data["signal"])*(data["signal_shift_-1"])) , data["mean_abs_chgbatch_slices2_msignal"])) / 2.0)) +(np.cos(( np.cos(( np.cos(( data["maxtominbatch_msignal"])))))))) , data["mean_abs_chgbatch_slices2_msignal"])))) +
0.050000*np.tanh(data["rangebatch_slices2_msignal"])+
0.050000*np.tanh(np.sin(( np.sin(( np.where(data["meanbatch_msignal"] > -998,(-(( np.where(data["maxtominbatch_msignal"] > -998, data["abs_minbatch_slices2_msignal"], data["minbatch_slices2_msignal"])))) , data["meanbatch_msignal"])))))) +
0.050000*np.tanh(((np.where(data["abs_minbatch_slices2_msignal"] <= -998,(( np.where(np.where(data["abs_maxbatch_slices2_msignal"] <= -998, data["rangebatch_slices2"], data["minbatch_msignal"])<= -998, data["signal_shift_-1_msignal"], data["abs_avgbatch_slices2"])) *(((data["meanbatch_slices2_msignal"])-(data["signal_shift_-1"])))) ,(-(((( data["rangebatch_msignal"])-(data["signal_shift_-1"])))))))* 2.0)) +
0.050000*np.tanh(((((((data["signal_shift_+1"])* 2.0)) -(( 12.72679519653320312)))) -(np.maximum(((np.where(data["mean_abs_chgbatch_slices2_msignal"] > -998, data["signal_shift_+1_msignal"], data["maxtominbatch"]))),(((((((((( data["signal_shift_+1"])* 2.0)) -(( 12.72679519653320312)))) -(np.maximum(((data["signal_shift_+1"])) ,(( data["maxtominbatch"])))))) * 2.0)))))))+
0.050000*np.tanh(((np.minimum(((data["signal_shift_+1_msignal"])) ,(( data["signal_shift_-1"])))) * 2.0)) +
0.050000*np.tanh(np.where(data["signal_shift_+1"] > -998,(((np.cos(( data["signal_shift_+1_msignal"])))+(data["rangebatch_slices2"])) /2.0),(-(( np.cos(((-(( data["signal_shift_+1_msignal"])))))))))) +
0.050000*np.tanh(((((data["signal_shift_-1"])-(((((( data["abs_maxbatch"])+(np.where(data["maxbatch_msignal"] > -998, np.sin(( np.sin(( data["abs_maxbatch"])))) , data["minbatch_msignal"])))/2.0)) * 2.0)))) -(((data["abs_avgbatch_msignal"])-(np.sin(( data["abs_maxbatch"])))))))+
0.050000*np.tanh(((np.sin(( np.cos(( data["stdbatch_slices2_msignal"])))))*(((data["signal"])* 2.0)))) +
0.050000*np.tanh(np.where(np.sin(((( np.minimum(((((data["signal_shift_+1_msignal"])/ 2.0))),(( data["rangebatch_slices2"])))) *(((( data["maxtominbatch_slices2_msignal"])<=(data["minbatch_slices2"])) *1.))))) <= -998, data["rangebatch_slices2"], np.sin(( np.where(data["signal_shift_+1"] > -998,(((np.sin(((( np.cos(( data["stdbatch_msignal"])))* 2.0)))) +(((( data["minbatch_msignal"])>(data["rangebatch_slices2"])) *1.))) /2.0), data["minbatch_msignal"])))))+
0.050000*np.tanh(((data["maxbatch_slices2"])+(((((((((3.92767763137817383)) >(((( data["abs_maxbatch_msignal"])>(np.sin(( np.sin(( data["maxtominbatch_msignal"])))))) *1.))) *1.))-(( 7.16431427001953125)))) +(data["meanbatch_slices2"])))))+
0.050000*np.tanh(np.sin(((((np.sin(( data["abs_minbatch_msignal"])))+(np.where(((((( 6.67216062545776367)) -(data["signal_shift_-1"])))+(data["stdbatch_msignal"])) <= -998, np.cos(( np.maximum(((np.sin(( data["signal"])))) ,(((((( data["minbatch_slices2"])-(np.tanh(((( data["abs_minbatch_msignal"])/ 2.0)))))) +(data["abs_maxbatch"]))))))), np.minimum(((data["abs_minbatch_slices2_msignal"])) ,(( data["stdbatch_msignal"])))))) /2.0)))) +
0.050000*np.tanh(((((( data["minbatch_slices2_msignal"])+(np.maximum(((((( data["abs_avgbatch_msignal"])+(data["meanbatch_slices2"])) /2.0))),(((((data["mean_abs_chgbatch_slices2_msignal"])+(np.sin(((( data["mean_abs_chgbatch_slices2_msignal"])-(((data["minbatch_slices2_msignal"])*(data["meanbatch_slices2"])))))))) /2.0)))))))+(((data["mean_abs_chgbatch_slices2_msignal"])*(data["abs_avgbatch_msignal"])))) /2.0)) +
0.050000*np.tanh(np.cos(( np.minimum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(((((((( np.minimum(((data["mean_abs_chgbatch_slices2_msignal"])) ,(((((data["signal_shift_+1_msignal"])<=(((data["signal_shift_+1_msignal"])/ 2.0)))*1.))))) >(data["signal_shift_+1_msignal"])) *1.))<=(data["rangebatch_slices2_msignal"])) *1.))))))) +
0.050000*np.tanh(((np.where(np.sin(( data["mean_abs_chgbatch_slices2_msignal"])) > -998,(( np.where(data["signal_shift_+1"] > -998, np.sin(( data["signal"])) ,(( data["meanbatch_slices2_msignal"])-(data["maxtominbatch_slices2"])))) * 2.0), data["meanbatch_slices2_msignal"])) * 2.0)) +
0.050000*np.tanh(np.where(data["maxbatch_slices2_msignal"] <= -998, np.cos(( data["maxbatch_slices2_msignal"])) , np.cos(( data["signal_shift_+1"])))) +
0.050000*np.tanh(np.where(data["signal_shift_-1_msignal"] <= -998, data["signal_shift_-1_msignal"], data["signal_shift_-1_msignal"])) +
0.050000*np.tanh(((((-(( data["abs_minbatch_slices2"])))) <=(np.where(data["abs_maxbatch_slices2"] <= -998, data["minbatch"], np.cos(( data["signal_shift_+1"])))))*1.))+
0.050000*np.tanh(((data["signal_shift_-1_msignal"])*(np.where(np.where(((((( data["signal"])+(data["maxbatch_msignal"])) /2.0)) * 2.0)<= -998, data["signal"], data["maxbatch_msignal"])<= -998, np.sin(( data["signal_shift_+1_msignal"])) , data["signal"])))) +
0.050000*np.tanh(((((((( data["signal_shift_+1"])>(( -(((( data["abs_avgbatch_slices2_msignal"])* 2.0)))))) *1.))* 2.0)) * 2.0)) +
0.050000*np.tanh(((data["signal_shift_+1"])-(np.where(((data["medianbatch_slices2_msignal"])-(np.cos(( np.maximum(((data["signal_shift_+1"])) ,(( data["signal_shift_+1"])))))))<= -998,(((((data["signal"])* 2.0)) <=(((((data["signal"])+(data["signal"])))-(np.where(np.sin(( data["maxtominbatch_slices2"])) <= -998, data["mean_abs_chgbatch_msignal"],(4.0)))))) *1.) ,(4.0)))))+
0.050000*np.tanh(((( data["medianbatch_slices2"])>(((((((((((((np.cos(((1.0)))) * 2.0)) / 2.0)) * 2.0)) * 2.0)) * 2.0)) * 2.0)))*1.))+
0.050000*np.tanh(np.cos(( np.minimum(((np.minimum(((data["minbatch_msignal"])) ,(((((( 13.14470481872558594)) <=(((np.cos(( data["abs_minbatch_slices2"])))* 2.0)))*1.)))))),(( np.sin(( data["abs_maxbatch_msignal"])))))))) +
0.050000*np.tanh(np.where(data["minbatch_slices2"] <= -998, data["signal_shift_-1_msignal"], np.where(np.sin(( data["signal_shift_-1_msignal"])) <= -998, data["signal_shift_-1_msignal"],(( np.sin(( np.where(np.sin(( data["stdbatch_msignal"])) > -998, data["stdbatch_msignal"], data["meanbatch_slices2_msignal"])))) * 2.0)))) +
0.050000*np.tanh(( -(((((((( -(( data["abs_avgbatch_slices2"])))) +(np.cos(( data["signal"])))) /2.0)) -(data["signal_shift_+1_msignal"])))))) +
0.050000*np.tanh(np.sin(((5.0)))) +
0.050000*np.tanh(np.maximum(((( -(((((12.85178279876708984)) +(np.where(((( 12.85178279876708984)) +(np.where(data["abs_maxbatch"] > -998, data["medianbatch_slices2"],(( data["medianbatch_slices2"])* 2.0)))) > -998,(( data["meanbatch_slices2"])*(data["stdbatch_msignal"])) ,(12.85178279876708984))))))))),(( data["minbatch_slices2"])))) +
0.050000*np.tanh(np.where(data["stdbatch_slices2"] > -998, data["signal_shift_-1_msignal"], np.where(np.maximum(((data["minbatch_slices2"])) ,(( np.where(data["maxtominbatch_msignal"] > -998, data["abs_maxbatch"], data["maxbatch_slices2"])))) > -998, data["meanbatch_slices2"], np.maximum(((((data["signal_shift_+1"])* 2.0))),(((( data["stdbatch_slices2_msignal"])/ 2.0)))))))+
0.050000*np.tanh(data["meanbatch_slices2"])+
0.050000*np.tanh(((np.sin(( np.where(data["minbatch_slices2"] > -998, data["signal_shift_+1"],(((data["maxbatch_slices2_msignal"])+(np.sin(( np.where(data["meanbatch_slices2"] > -998, data["stdbatch_slices2_msignal"], data["signal_shift_+1_msignal"])))))/2.0)))))* 2.0)) +
0.050000*np.tanh(((data["signal_shift_+1_msignal"])+(np.where(data["signal_shift_+1"] > -998, data["abs_maxbatch"], np.cos(((-(( data["abs_minbatch_slices2_msignal"])))))))))+
0.050000*np.tanh(np.sin(((((data["abs_maxbatch"])+(data["signal_shift_-1"])) /2.0)))) )<choose_model_class>
train, test, train_tr, new_splits = split()