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| from matplotlib import pyplot as plt | |
| from utils import * | |
| import warnings | |
| #### Define outputs #### | |
| write_file = True | |
| plot_profile = True | |
| #### Define outputs #### | |
| with open('numpy_networks/mlp_[128, 128, 128, 128, 128].pkl', 'rb') as file: | |
| mlp = pickle.load(file) | |
| f_nn = "my_simulation_parameters.txt" | |
| with open(f_nn) as fw: | |
| lines = fw.readlines() | |
| for line in lines: | |
| l = line.rstrip() | |
| if "r_list" in l: | |
| if not l[-1] == ",": | |
| raise Exception("Ensure there is a comma after last parameter value in " + f_nn) | |
| r_list = [float(p) for p in l.split("=")[1].split(",")[:-1]] | |
| elif "t_list" in line: | |
| if not l[-1] == ",": | |
| raise Exception("Ensure there is a comma after last parameter value in " + f_nn) | |
| t_list = [float(p) for p in l.split("=")[1].split(",")[:-1]] | |
| elif "v_list" in line: | |
| if not l[-1] == ",": | |
| raise Exception("Ensure there is a comma after last parameter value in " + f_nn) | |
| v_list = [float(p) for p in l.split("=")[1].split(",")[:-1]] | |
| if not len(r_list) == len(v_list) and len(r_list) == len(t_list): | |
| raise Exception("Ensure equal number of values for all parameters in " + f_nn) | |
| for i in range(len(r_list)): | |
| if r_list[i]<0 or r_list[i]>9.5: | |
| warnings.warn('RaQ/Ra is outside the range of the training dataset') | |
| if t_list[i]<1e+6 or t_list[i]>5e+9: | |
| warnings.warn('FKT is outside the range of the training dataset') | |
| if v_list[i]<1 or v_list[i]>95: | |
| warnings.warn('FKV is outside the range of the training dataset') | |
| ### calculates y points ### | |
| num_points = 128 | |
| y_prof = np.concatenate(([1], np.linspace(0+1/(num_points*2),1-1/(num_points*2),num_points-2)[::-1], [0])) | |
| ### calculates y points ### | |
| ### calculates temperature profile ### | |
| x_in = get_input(r_list, t_list, v_list, y_prof) | |
| y_pred_nn_pointwise = get_profile(x_in, mlp, num_sims=len(r_list)) | |
| ### calculates temperature profile ### | |
| ### writes out temperature profile ### | |
| if write_file: | |
| for i in range(len(r_list)): | |
| fname = "outputs/profile_raq_ra" + str(r_list[i]) + "_fkt" + str(t_list[i]) + "_fkv" + str(v_list[i]) | |
| f = open(fname + ".txt", "wb") | |
| for j in range(len(y_prof)): | |
| f.writelines([str(y_prof[j]).encode('ascii'), | |
| " ".encode('ascii'), | |
| str(y_pred_nn_pointwise[i,j]).encode('ascii'), | |
| "\n".encode('ascii')]) | |
| f.close() | |
| ### writes out temperature profile ### | |
| ### plots temperature profile ### | |
| for i in range(len(r_list)): | |
| fname = "outputs/profile_raq_ra" + str(r_list[i]) + "_fkt" + str(t_list[i]) + "_fkv" + str(v_list[i]) | |
| plt.figure() | |
| plt.plot(y_pred_nn_pointwise[i,:], y_prof, 'k-', linewidth=3.0, label="pointwise neural network") | |
| plt.ylim([1,0]) | |
| plt.xlabel("Temperature") | |
| plt.ylabel("Depth") | |
| plt.legend() | |
| plt.grid() | |
| plt.savefig(fname + ".png") | |
| ### plots temperature profile ### |