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and b/__pycache__/demo2.cpython-310.pyc differ diff --git a/__pycache__/gr_demo.cpython-311.pyc b/__pycache__/gr_demo.cpython-311.pyc new file mode 100644 index 0000000000000000000000000000000000000000..e8ed88140b3a026e23b823f7673e18cc80631554 Binary files /dev/null and b/__pycache__/gr_demo.cpython-311.pyc differ diff --git a/best_models.csv b/best_models.csv index 7fe15392244020415d7544d8a9ecacf0ea417833..38c4c2bc650726f3f72a7ccd2feae624c6a35b62 100644 --- a/best_models.csv +++ b/best_models.csv @@ -1,5 +1,7 @@ sku,best_model,characteristic -sku-0,fft_plus,continuous -sku-1,holt_winters_plus,continuous -sku-2,prophet_plus,fuzzy -sku-3,prophet_plus,fuzzy_transient +Item_A,prophet,continuous +Item_B,prophet,continuous +Item_C,fft_i,continuous +Item_D,fft_i,continuous +Item_E,prophet,continuous +Item_F,ceif,fuzzy diff --git a/conda_installs.txt b/conda_installs.txt index 9c884d084a83e69cd5102cfa8b9ec972d2ce40b6..7e844418df34f27c3a6139c4f1e27b63d770cf6c 100644 --- a/conda_installs.txt +++ b/conda_installs.txt @@ -3,6 +3,9 @@ conda install -c anaconda urllib3 -y conda install -c conda-forge prophet -y +conda install -c conda-forge xgboost -y +conda install -c conda-forge sktime -y + conda install -c anaconda pandas -y conda install scikit-learn -y conda install -c intel pyyaml -y diff --git a/data/.gitignore b/data/.gitignore new file mode 100644 index 0000000000000000000000000000000000000000..48ecc30c33a6a7fba5b12ccaebbd9aaabcd81330 --- /dev/null +++ b/data/.gitignore @@ -0,0 +1 @@ +raw \ No newline at end of file diff --git a/data/demand_forecasting_demo_data.csv b/data/demand_forecasting_demo_data.csv index 26a9d925718af2fa689b698dcd9896bce82b38cb..a86e9da13555deb467926cdb50ae50427ea359df 100644 --- a/data/demand_forecasting_demo_data.csv +++ b/data/demand_forecasting_demo_data.csv @@ -1,1019 +1,400 @@ -datetime,y,sku -2018-05-06,2,sku-0 -2018-05-13,1,sku-0 -2018-05-20,7,sku-0 -2018-05-27,9,sku-0 -2018-06-03,2,sku-0 -2018-06-10,3,sku-0 -2018-06-17,9,sku-0 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+2022-02-28,93.0,3.517,0 +2022-03-31,97.0,4.222,3 +2022-04-30,97.0,4.109,5 +2022-05-31,100.0,4.444,1 +2022-06-30,100.0,4.929,3 +2022-07-31,97.0,4.559,6 +2022-08-31,93.0,3.975,2 +2022-09-30,90.0,3.7,4 +2022-10-31,90.0,3.815,0 +2022-11-30,90.0,3.685,2 +2022-12-31,90.0,3.21,5 diff --git a/data/multivariate/resource.md b/data/multivariate/resource.md new file mode 100644 index 0000000000000000000000000000000000000000..91171a8666ec0cd9b9904ecc75f1afb60e1f6e0d --- /dev/null +++ b/data/multivariate/resource.md @@ -0,0 +1 @@ +data source: https://www.kaggle.com/datasets/baravindkumar/predicting-the-price-of-blow-mold-timeseries-multi \ No newline at end of file diff --git a/demo.py b/demo.py index 3f8fb25c538a393bf948666e098bde1da5512e42..7452c0f17f94c093a1529c22cbf63566cf7b40eb 100644 --- a/demo.py +++ b/demo.py @@ -43,7 +43,7 @@ with demo: df_ts_data = gr.DataFrame(**args.df_ts_data) - with gr.Accordion('Data Visualisation', open=False): + with gr.Accordion('Input Data Visualisation', open=False): dropdown_ts_data = gr.Dropdown(**args.dropdown_ts_data) plot_ts_data = gr.Plot() pass @@ -70,9 +70,16 @@ with demo: df_model_data = gr.DataFrame() file_model_data = gr.File() - + + accordion_model_selection = gr.Accordion( + 'Model Selection Visualisation', open=False, visible=False) + + with accordion_model_selection: + dropdown_model_selection = gr.Dropdown(**args.dropdown_model_selection) + plot_model_selection = gr.Plot() + gr.HTML('
') - + gr.Markdown('# Step 3 - Forecasting') with gr.Row(): @@ -90,10 +97,10 @@ with demo: btn_load_demo_result = gr.Button('Load Demo Result') - df_forecast = gr.DataFrame(**args.df_forecast) + df_forecast = gr.Dataframe(**args.df_forecast) file_forecast = gr.File() - with gr.Accordion('Data Visualisation', open=False): + with gr.Accordion('Forecasting Result Visualisation', open=False): dropdown_forecast = gr.Dropdown(**args.dropdown_forecast) plot_forecast = gr.Plot() @@ -132,7 +139,11 @@ with demo: btn_model_selection.click( app.btn_model_selection__click, - [], [df_model_data, file_model_data]) + [], + [df_model_data, + file_model_data, + accordion_model_selection, + dropdown_model_selection]) btn_forecast.click( app.btn_forecast__click, @@ -166,5 +177,10 @@ with demo: [plot_forecast] ) + dropdown_model_selection.select( + app.dropdown_model_selection__select, + [dropdown_model_selection], + [plot_model_selection]) + demo.launch() diff --git a/demo2.py b/demo2.py new file mode 100644 index 0000000000000000000000000000000000000000..4ec03cbf98aa532840acd896573178dbf0b5b689 --- /dev/null +++ b/demo2.py @@ -0,0 +1,275 @@ +import json + +import gradio as gr +from gr_app2 import args, GradioApp + +demo = gr.Blocks(**args.block) + +with demo: + app = GradioApp() + + md__title = gr.Markdown(**args.md__title) + + with gr.Row(): + with gr.Column(): + file__historical = gr.File(**args.file__historical) + + with gr.Column(): + file__future = gr.File(**args.file__future) + md__future = gr.Markdown(**args.md__future) + + with gr.Row(): + btn__load_historical_demo = gr.Button("Load Demo Historical Data") + btn__load_future_demo = gr.Button("Load Demo Future Data") + + with gr.Row(): + number__n_predict = gr.Number( + value=app.n_predict, + **args.number__n_predict) + + number__window_length = gr.Number( + value=app.window_length, + **args.number__window_length + ) + + textbox__target_column = gr.Textbox( + value=app.target_column, + **args.textbox__target_column + ) + + number__n_predict.change( + app.number__n_predict__change, + [number__n_predict] + ) + + number__window_length.change( + app.number__window_length__change, + [number__window_length] + ) + + textbox__target_column.change( + app.textbox__target_column__change, + [textbox__target_column] + ) + + # ---------- # + # Data Views # + # ---------- # + + with gr.Tabs(): + with gr.Tab('Table View'): + df__table_view = gr.Dataframe(**args.df__table_view) + + with gr.Tab('Chart View'): + dropdown__chart_view_filter = gr.Dropdown( + multiselect=True, + label='Filter') + plot__chart_view = gr.Plot() + + with gr.Tab('Seasonality and Auto Correlation'): + dropdown__seasonality_decompose = gr.Dropdown( + label='Please select column to decompose') + + with gr.Row(): + plot__seasonality_decompose = gr.Plot() + plot_acg_pacf = gr.Plot() + + with gr.Tab('Correlations'): + btn__plot_correlation = gr.Button('Plot Correlations') + plot__correlation = gr.Plot() + + btn__plot_correlation.click( + app.btn__plot_correlation__click, + [], + [plot__correlation] + ) + + with gr.Tab("Data Profile"): + btn__profiling = gr.Button('Profile Data') + md__profiling = gr.Markdown() + plot__change_points = gr.Plot() + + dropdown__seasonality_decompose.change( + app.dropdown__seasonality_decompose__change, + [dropdown__seasonality_decompose], + [plot__seasonality_decompose, + plot_acg_pacf] + ) + + btn__profiling.click( + app.btn__profiling__click, + [], + [md__profiling, + plot__change_points] + ) + + # ---------------------- # + # Fit data to forecaster # + # ---------------------- # + + btn__fit_data = gr.Button(**args.btn__fit_data) + + # =========== # + # Forecasting # + # =========== # + + column__models = gr.Column(visible=True) + + with column__models: + md__fit_ready = gr.Markdown(**args.md__fit_ready) + + md__forecast_data_info = gr.Markdown() + + # ------------- # + # Model Configs # + # ------------- # + + with gr.Row(): + checkbox__round_results = gr.Checkbox( + app.round_results, + label='Round Results', + interactive=True) + + checkbox__round_results.change( + app.checkbox__round_results__change, + [checkbox__round_results], + [] + ) + + gr.Markdown('## Models') + # ------- # + # XGBoost # + # ------- # + with gr.Tab('XGBoost'): + + with gr.Row(): + checkbox__xgboost_cv = gr.Checkbox( + app.xgboost_cv, label='Cross Validation') + checkbox__xgboost_round = gr.Checkbox( + app.xgboost.round_result, + label='Round Result', + interactive=True) + + checkbox__xgboost_round.change( + app.checkbox__xgboost_round__change, + [checkbox__xgboost_round], + [] + ) + + with gr.Row(): + with gr.Column(): + textbox__xgboost_params = gr.Textbox( + interactive=True, + value=app.xgboost_params) + + btn__set_xgboost_params = gr.Button("Set Params") + + json_xgboost_params = gr.JSON( + value=app.xgboost_params, + **args.json_xgboost_params) + + btn__set_xgboost_params.click( + app.btn__set_xgboost_params__click, + [textbox__xgboost_params], + [json_xgboost_params]) + + btn__train_xgboost = gr.Button("Forecast with XGBoost Model") + + plot__xgboost_result = gr.Plot() + + with gr.Row(): + df__xgboost_result = gr.Dataframe() + file__xgboost_result = gr.File() + + btn__train_xgboost.click( + app.btn__train_xgboost__click, + [], + [plot__xgboost_result, + file__xgboost_result, + df__xgboost_result]) + + # ------- # + # Prophet # + # ------- # + with gr.Tab('Prophet'): + gr.Markdown('Prophet') + + btn__forecast_with_prophet = gr.Button( + **args.btn__forecast_with_prophet) + + plot__prophet_result = gr.Plot() + + with gr.Row(): + df__prophet_result = gr.DataFrame() + file__prophet_result = gr.File() + + btn__forecast_with_prophet.click( + app.btn__forecast_with_prophet__click, + [], + [plot__prophet_result, + file__prophet_result, + df__prophet_result] + ) + + # --------- # + # Operators # + # --------- # + + file__historical.upload( + app.file__historical__upload, + [file__historical], + [df__table_view, + dropdown__chart_view_filter, + dropdown__seasonality_decompose, + plot__chart_view]) + + file__future.upload( + app.file__future__upload, + [file__future], + [df__table_view, + dropdown__chart_view_filter, + dropdown__seasonality_decompose, + plot__chart_view, + number__n_predict]) + + btn__fit_data.click( + app.btn__fit_data__click, + [], + [ + number__n_predict, + number__window_length, + file__historical, + file__future, + btn__fit_data, + column__models, + btn__load_historical_demo, + btn__load_future_demo, + md__forecast_data_info, + ]) + + btn__load_historical_demo.click( + app.btn__load_historical_demo__click, + [], + [df__table_view, + dropdown__chart_view_filter, + dropdown__seasonality_decompose, + plot__chart_view,] + ) + + btn__load_future_demo.click( + app.btn__load_future_demo__click, + [], + [df__table_view, + dropdown__chart_view_filter, + dropdown__seasonality_decompose, + plot__chart_view, + number__n_predict] + ) + + dropdown__chart_view_filter.change( + app.dropdown__chart_view_filter__change, + [dropdown__chart_view_filter], + [plot__chart_view] + ) + +demo.launch() diff --git a/forecast_result.csv b/forecast_result.csv index 505caca9f93a8d235040801ffff64f5a08505a6a..331781caa1186d1b07e67764441743978cb93fb4 100644 --- a/forecast_result.csv +++ b/forecast_result.csv @@ -1,61 +1,13 @@ datetime,y,sku -2023-04-23,20,sku-0 -2023-04-30,19,sku-0 -2023-05-07,25,sku-0 -2023-05-14,27,sku-0 -2023-05-21,20,sku-0 -2023-05-28,21,sku-0 -2023-06-04,27,sku-0 -2023-06-11,27,sku-0 -2023-06-18,27,sku-0 -2023-06-25,27,sku-0 -2023-07-02,27,sku-0 -2023-07-09,27,sku-0 -2023-07-16,27,sku-0 -2023-07-23,27,sku-0 -2023-07-30,27,sku-0 -2023-04-09,77,sku-1 -2023-04-16,78,sku-1 -2023-04-23,78,sku-1 -2023-04-30,79,sku-1 -2023-05-07,80,sku-1 -2023-05-14,80,sku-1 -2023-05-21,81,sku-1 -2023-05-28,82,sku-1 -2023-06-04,82,sku-1 -2023-06-11,83,sku-1 -2023-06-18,84,sku-1 -2023-06-25,84,sku-1 -2023-07-02,85,sku-1 -2023-07-09,86,sku-1 -2023-07-16,86,sku-1 -2022-12-04,0,sku-2 -2022-12-11,46,sku-2 -2022-12-18,0,sku-2 -2022-12-25,46,sku-2 -2023-01-01,0,sku-2 -2023-01-08,53,sku-2 -2023-01-15,0,sku-2 -2023-01-22,46,sku-2 -2023-01-29,0,sku-2 -2023-02-05,46,sku-2 -2023-02-12,48,sku-2 -2023-02-19,0,sku-2 -2023-02-26,50,sku-2 -2023-03-05,0,sku-2 -2023-03-12,49,sku-2 -2023-04-23,0,sku-3 -2023-04-30,0,sku-3 -2023-05-07,17,sku-3 -2023-05-14,0,sku-3 -2023-05-21,0,sku-3 -2023-05-28,20,sku-3 -2023-06-04,0,sku-3 -2023-06-11,18,sku-3 -2023-06-18,0,sku-3 -2023-06-25,0,sku-3 -2023-07-02,19,sku-3 -2023-07-09,0,sku-3 -2023-07-16,0,sku-3 -2023-07-23,19,sku-3 -2023-07-30,0,sku-3 +2022-12-01,1261.881563271306,Item_A +2023-01-01,1238.1241261473267,Item_A +2022-12-01,67.98226881358575,Item_B +2023-01-01,54.089203200916906,Item_B +2023-01-01,189.0,Item_C +2023-02-01,89.0,Item_C +2022-12-01,574.0,Item_D +2023-01-01,590.0,Item_D +2022-12-01,562.7574409930887,Item_E +2023-01-01,392.3652129393938,Item_E +2022-12-04,0.0,Item_F +2022-12-11,0.0,Item_F diff --git a/gr_app/GradioApp.py b/gr_app/GradioApp.py index d5d73021b44d38cc43d26e032309fa4a11cc1228..d18c34a622942d89a5e438ea990eba1b7eed803f 100644 --- a/gr_app/GradioApp.py +++ b/gr_app/GradioApp.py @@ -31,14 +31,28 @@ class GradioApp(): 'sku': self.skus, 'best_model': '', 'characteristic': '', - # 'RMSE': '' + 'predictability': '', + 'RMSE': '', + 'Intermittent Scores':'' } ) + print('[__set_ts_data] End') def __set_forecast(self, forecast: pd.DataFrame): + print('__set_forecast') self.forecast = forecast.set_index('datetime') self.forecast.index = pd.to_datetime(self.forecast.index) + def __set_model_selection_res(self, model_selection_reses: pd.DataFrame): + ''' + self.model_selection_res will be identical to self.forecast + keep tracking on this just to visualize the model selection result + ''' + print('__set_model_selection_res') + self.model_selection_res = model_selection_reses + # self.model_selection_res = pd.to_datetime( + # self.model_selection_res.index) + def __set_model(self, model_df): if (self.skus is None): raise gr.Error( @@ -96,9 +110,12 @@ class GradioApp(): def btn_model_selection__click(self): print('btn_model_selection__click') + ts_data = reset_index(self.ts_data) + + model_selection_reses = [] for sku in self.skus: print('Selecting model ', sku) - data = self.ts_data[self.ts_data['sku'] == sku] + data = ts_data[ts_data['sku'] == sku] # ----------------- # # Feature Selection # @@ -111,11 +128,28 @@ class GradioApp(): self.model_data.loc[self.model_data['sku'] == sku, 'best_model'] = res['forecast'][0]['model'] - # self.model_data.loc[self.model_data['sku'] == - # sku, 'RMSE'] = round(res['forecast'][0]['RMSE'], 2) + + self.model_data.loc[self.model_data['sku'] == + sku, 'predictability'] = res['predictability'] + + self.model_data.loc[self.model_data['sku'] == + sku, 'RMSE'] = round(res['forecast'][0]['RMSE'], 2) + + self.model_data.loc[self.model_data['sku'] == + sku, 'Intermittent Scores'] = str(res['forecast'][0]['interm_scores']) + + model_selection_res = res['forecast'][0]['test'].drop( + columns='truth').rename(columns={'test': 'y'}) + + model_selection_res['sku'] = sku + model_selection_reses.append(model_selection_res) + + self.__set_model_selection_res(pd.concat(model_selection_reses)) return (self.update__df_model_data(), - self.update__file_model_data()) + self.update__file_model_data(), + self.update__accordion_model_selection(), + self.update__dropdown_model_selection()) def slider_forecast_horizon__update(self, slider): # print('slider_forecast_horizon__update ', slider) @@ -148,12 +182,13 @@ class GradioApp(): print(model, characteristic) res = self.forecaster.forecast( data, self.forecast_horizon, model=model, run_test=False, characteristic=characteristic) + print(res) forecast = pd.DataFrame( res['forecast'][0]['forecast'], columns=['datetime', 'y']) forecast['sku'] = sku forecasts.append(forecast) - self.forecast = self.__set_forecast(pd.concat(forecasts)) + self.__set_forecast(pd.concat(forecasts)) return (self.update__df_forecast(), self.update__file_forecast(), @@ -168,22 +203,27 @@ class GradioApp(): def dropdown_forecast__select(self, sku): return self.update__plot_forecast(sku) + def dropdown_model_selection__select(self, sku): + return self.update__plot_model_selection(sku) + # ======== # # Updaters # # ======== # def update__file_model_data(self): self.model_data.to_csv('./best_models.csv', index=False) - return gr.File.update(value='./best_models.csv') + return gr.File(value='./best_models.csv') def update__df_model_data(self): - return gr.DataFrame.update(value=self.model_data) + return gr.Dataframe(value=self.model_data) def update__df_ts_data(self): - return gr.DataFrame.update(value=reset_index(self.ts_data)) + return gr.Dataframe(value=reset_index(self.ts_data)) def update__df_forecast(self): - return gr.DataFrame.update(reset_index(self.forecast)) + print('upupdate__df_forecastda') + print(self.forecast) + return gr.Dataframe(value = reset_index(self.forecast)) def update__slider_forecast_horizon(self): skus = self.skus @@ -195,27 +235,30 @@ class GradioApp(): # max_horizon = int( # self.ts_data[self.ts_data['sku'] == sku].shape[0] * 0.2) - return gr.Slider.update(maximum=max_horizon) + return gr.Slider(maximum=max_horizon) def update__file_forecast(self): reset_index(self.forecast).to_csv('./forecast_result.csv', index=False) - return gr.File.update(value='./forecast_result.csv') + return gr.File(value='./forecast_result.csv') def update__md_ts_data_info(self): md = f''' ### Data Description - Columns: {self.ts_data.columns.tolist()} - Size: {[str(sku) + ' - ' + str(self.ts_data[self.ts_data["sku"] == sku].shape[0]) for sku in self.skus]} + Columns: **{reset_index(self.ts_data).columns.tolist()}** + Size: {' | '.join([str(sku) + ' : **' + str(self.ts_data[self.ts_data["sku"] == sku].shape[0]) + '**' for sku in self.skus])} ''' - return gr.Markdown.update(md) + return gr.Markdown(md) def update__dropdown_ts_data(self): # print(type(self.skus)) - return gr.Dropdown.update(choices=self.skus) + return gr.Dropdown(choices=self.skus) def update__dropdown_forecast(self): skus = self.forecast['sku'].unique().tolist() - return gr.Dropdown.update(choices=skus) + return gr.Dropdown(choices=skus) + + def update__dropdown_model_selection(self): + return gr.Dropdown(choices=self.skus) def update__plot_ts_data(self, skus): # print('update__plot_ts_data') @@ -227,17 +270,58 @@ class GradioApp(): ax.legend(loc='upper left') fig.tight_layout() - return gr.Plot.update(fig) + return gr.Plot(fig) def update__plot_forecast(self, sku): fig, ax = plt.subplots(figsize=(12, 4)) - ax.plot(self.ts_data[self.ts_data['sku'] == sku]['y'], - label=f'{sku} - historical') + ''' + A trick been used here, + to connect the plotting lines, for the historical part, + have to concat with the 1st data in the forecasting result. + Because the forecasting result already have date time index, + using head(1) to get the first element of the forecasting result + ''' + + ax.plot(pd.concat( + [ + self.ts_data[self.ts_data['sku'] == sku], + self.forecast[self.forecast['sku'] == sku].head(1) + ])['y'], + + label=f'{sku} - historical') + ax.plot(self.forecast[self.forecast['sku'] == sku]['y'], label=f'{sku} - forecast') ax.legend(loc='upper left') fig.tight_layout() - return gr.Plot.update(fig) + return gr.Plot(fig) + + def update__plot_model_selection(self, sku): + fig, ax = plt.subplots(figsize=(12, 4)) + + ''' + Reason need to filter out the last index is - sometimes IDSC model cannot + forecast the full required data size. Have to crop out the tail part. + ''' + idx = self.model_selection_res[self.model_selection_res['sku'] == sku].index + + ax.plot(self.ts_data[ + (self.ts_data['sku'] == sku) & + (self.ts_data.index <= idx[-1]) + ]['y'], label=f'{sku} - ground truth') + + ax.plot(self.model_selection_res[self.model_selection_res['sku'] + == sku]['y'], label=f'{sku} - model result') + + ax.axvline(x=idx[0], ymin=0.05, ymax=0.95, ls='--') + + ax.legend(loc='upper left') + fig.tight_layout() + + return gr.Plot(fig) + + def update__accordion_model_selection(self): + return gr.Accordion(visible=True) diff --git a/gr_app/__init__.py b/gr_app/__init__.py index 8b137891791fe96927ad78e64b0aad7bded08bdc..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 100644 --- a/gr_app/__init__.py +++ b/gr_app/__init__.py @@ -1 +0,0 @@ - diff --git a/gr_app/__pycache__/GradioApp.cpython-310.pyc b/gr_app/__pycache__/GradioApp.cpython-310.pyc index 61e747aa38dad561b9ca9293414d7f5476c92846..84685889e7e399e6ba5b6d46a786b1dd17bf861b 100644 Binary files a/gr_app/__pycache__/GradioApp.cpython-310.pyc and b/gr_app/__pycache__/GradioApp.cpython-310.pyc differ diff --git a/gr_app/__pycache__/GradioApp.cpython-311.pyc b/gr_app/__pycache__/GradioApp.cpython-311.pyc index 1c79b98273731ca7ff522d14a650a1b354786ae1..15422fce2bea7289338aee46bf04e2ed6f195634 100644 Binary files a/gr_app/__pycache__/GradioApp.cpython-311.pyc and b/gr_app/__pycache__/GradioApp.cpython-311.pyc differ diff --git a/gr_app/__pycache__/GradioApp.cpython-39.pyc b/gr_app/__pycache__/GradioApp.cpython-39.pyc index be641a5d5ed72a088f4d8ccebb4d8dc8933fb549..0efa5484358fe87ea3da9742f7009bfd9e16d32e 100644 Binary files a/gr_app/__pycache__/GradioApp.cpython-39.pyc and b/gr_app/__pycache__/GradioApp.cpython-39.pyc differ diff --git a/gr_app/__pycache__/__init__.cpython-310.pyc b/gr_app/__pycache__/__init__.cpython-310.pyc index 714a08927ed2de996818a8322babdf89035d2ea5..3d4f605dd96d19bd51ddfd2eb6102ab86b5e68e6 100644 Binary files a/gr_app/__pycache__/__init__.cpython-310.pyc and b/gr_app/__pycache__/__init__.cpython-310.pyc differ diff --git a/gr_app/__pycache__/__init__.cpython-311.pyc b/gr_app/__pycache__/__init__.cpython-311.pyc index 2b1b37eb4ead56d8632f8808214b5a1b260370ec..d46a0993531324bb591615dfa8f661b68eda786f 100644 Binary files a/gr_app/__pycache__/__init__.cpython-311.pyc and b/gr_app/__pycache__/__init__.cpython-311.pyc differ diff --git a/gr_app/__pycache__/__init__.cpython-39.pyc b/gr_app/__pycache__/__init__.cpython-39.pyc index f3a63c05d5503ac8f41a48293c905a09011ab9dd..afd80a8f40e7e67687be4c4db055e18bdafd4a22 100644 Binary files a/gr_app/__pycache__/__init__.cpython-39.pyc and b/gr_app/__pycache__/__init__.cpython-39.pyc differ diff --git a/gr_app/__pycache__/args.cpython-310.pyc b/gr_app/__pycache__/args.cpython-310.pyc index 42aac679ada7029eb0df8217310fe56c164e2549..06a093221fd7c0bf2ccb514ca57f1467adda2305 100644 Binary files a/gr_app/__pycache__/args.cpython-310.pyc and b/gr_app/__pycache__/args.cpython-310.pyc differ diff --git a/gr_app/__pycache__/args.cpython-311.pyc b/gr_app/__pycache__/args.cpython-311.pyc index 4438d661382e8e1cec4f8f6a5573427e576e2172..bf0705fa2441de69ea6edd8604be80729ee33b01 100644 Binary files a/gr_app/__pycache__/args.cpython-311.pyc and b/gr_app/__pycache__/args.cpython-311.pyc differ diff --git a/gr_app/__pycache__/args.cpython-39.pyc b/gr_app/__pycache__/args.cpython-39.pyc new file mode 100644 index 0000000000000000000000000000000000000000..a648e8efd4e147f11f17289b863bdba01e2c6e76 Binary files /dev/null and b/gr_app/__pycache__/args.cpython-39.pyc differ diff --git a/gr_app/__pycache__/helpers.cpython-310.pyc b/gr_app/__pycache__/helpers.cpython-310.pyc index 22dc3ad76760b7602f186477a18e75891d7e7936..04e372dfa18bc35813d44277126a0e7c3d3ca67a 100644 Binary files a/gr_app/__pycache__/helpers.cpython-310.pyc and b/gr_app/__pycache__/helpers.cpython-310.pyc differ diff --git a/gr_app/args.py b/gr_app/args.py index 031264fc2f900f279d108ad4c5a61ae7144dd397..c7eb2668a2dfd9943be7f2019338eaf29298d09e 100644 --- a/gr_app/args.py +++ b/gr_app/args.py @@ -26,3 +26,7 @@ dropdown_ts_data = { dropdown_forecast = { 'interactive': True } + +dropdown_model_selection = { + 'interactive': True +} diff --git a/gr_app/helpers.py b/gr_app/helpers.py index d488abc3a7a0052824554bb73717e81def2fc17b..1143aa597ec8099ffd29a4a53b56d7faf8e0de5a 100644 --- a/gr_app/helpers.py +++ b/gr_app/helpers.py @@ -3,5 +3,5 @@ import pandas as pd def reset_index(_df: pd.DataFrame): df = _df.reset_index() - df['datetime'] = df['datetime'].dt.strftime('%Y-%m-%d') + df['datetime'] =_df.index.astype(str) return df diff --git a/gr_app2/__init__.py b/gr_app2/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..c3e9a80e1b585da2852fdc9ca43930f73b522873 --- /dev/null +++ b/gr_app2/__init__.py @@ -0,0 +1 @@ +from .gr_app import GradioApp diff --git a/gr_app2/__pycache__/GradioApp.cpython-310.pyc b/gr_app2/__pycache__/GradioApp.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..e471f7a4a15fee1b33c0cea57a2cb5471dfa8378 Binary files /dev/null and b/gr_app2/__pycache__/GradioApp.cpython-310.pyc differ diff --git a/gr_app2/__pycache__/__init__.cpython-310.pyc b/gr_app2/__pycache__/__init__.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..535f51325c15322c5deb9795a2a741bfc53708bd Binary files /dev/null and b/gr_app2/__pycache__/__init__.cpython-310.pyc differ diff --git a/gr_app2/__pycache__/args.cpython-310.pyc b/gr_app2/__pycache__/args.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..e0ad12b62bd1584a3d442bbd649edf8853d1456b Binary files /dev/null and b/gr_app2/__pycache__/args.cpython-310.pyc differ diff --git a/gr_app2/__pycache__/gr_app.cpython-310.pyc b/gr_app2/__pycache__/gr_app.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..4fcadb91fdbb8340b972f2e7c864751eedbf3c3a Binary files /dev/null and b/gr_app2/__pycache__/gr_app.cpython-310.pyc differ diff --git a/gr_app2/args.py b/gr_app2/args.py new file mode 100644 index 0000000000000000000000000000000000000000..603db5e1df040fea429a0022f35366a93000c4d9 --- /dev/null +++ b/gr_app2/args.py @@ -0,0 +1,79 @@ +block = { + 'css': + ''' + footer {visibility: hidden} + + .json_xgboost_params { + max-height: 200px; + overflow: scroll !important; + } + ''' +} + +md__title = { + 'value': + """ + # Sentient.io - Time Series Forecasting + --- + """ +} + +md__fit_ready = { + 'value': + """ + # Data Fitted... + Ready for forecasting + """ +} + +file__historical = { + 'label': 'Historical Data', +} + + +md__future = { + 'value': "Optional. Future data's columns must within historical data's columns, length of future data will determine the N Predict, which is the max model's predictability.", +} + +file__future = { + 'label': 'Future Data (optional)', + + 'show_label': True +} + +number__n_predict = { + 'label': 'N Predict', + 'info': 'Number of future data point to predict, recommend set to 1 seasonal period (max 20). If future data is provided, N Predict will set to exact length of future data.', + 'interactive': True, + 'precision': 0 +} + +number__window_length = { + 'label': 'Window Length', + 'info': 'Window length for sliding window to build feature sets for prediction. Recommend set window length same as auto correlation (AR) lags. But feel free to adjust it.', + 'interactive': True, + 'precision': 0 +} + +textbox__target_column = { + 'label': 'Target Column', + 'info': 'Please provide the target column for forecasting. It must be one of the column in uploaded data. All other columns will be used as exogenous data.', + 'interactive': True, +} + +df__table_view = {} + + +btn__fit_data = { + 'value': 'Fit Data To Models', + 'variant': 'primary' +} + +btn__forecast_with_prophet = { + 'value': 'Forecast with Prophet', + 'variant': 'primary' +} + +json_xgboost_params = { + 'elem_classes': 'json_xgboost_params' +} diff --git a/gr_app2/gr_app.py b/gr_app2/gr_app.py new file mode 100644 index 0000000000000000000000000000000000000000..88b4218d401068fc41264b311bf85d48228a1366 --- /dev/null +++ b/gr_app2/gr_app.py @@ -0,0 +1,500 @@ +import json +import io +import os +import tempfile +import datetime + +import gradio as gr +import pandas as pd +import matplotlib.pyplot as plt +import seaborn as sns +import numpy as np +from sktime.utils.plotting import plot_series +from statsmodels.tsa.seasonal import seasonal_decompose +from statsmodels.graphics.tsaplots import plot_acf, plot_pacf + +from src.forecaster import Forecaster +from src.forecaster.models import XGBoost +from src.analyser import Analyser +from src.idsc import IDSC + +from src.forecaster.models import ProphetForecaster + + +class GradioApp(): + def __init__( + self + ) -> None: + self.forecaster = Forecaster() + self.analyser = Analyser() + self.idsc = IDSC() + + self.historical_demo_data = 'data/multivariate/demo_historical.csv' + self.future_demo_data = 'data/multivariate/demo_future.csv' + + self.data: pd.DataFrame = None + self.n_predict = 3 + self.window_length = 7 + self.target_column = 'y' + self.exog_columns = [] + + # Define if the model's result is going to be rounded + self.round_results = True + + # Delete old temp files oder than n minutes + self.delete_file_old_than_n_minutes = 10 + + self.plot_figsize_full_screen = (20, 4) + + # -------------------- # + # Model Related Params # + # -------------------- # + + # XGBoost # + self.xgboost = XGBoost() + self.xgboost_cv = False + self.xgboost_params = self.xgboost.cv_params + self.xgboost_strategy = 'recursive' + self.xgboost_forecast = None + self.xgboost_test = None + print('Init Gradio app') + + # Prophet # + self.prophet = ProphetForecaster() + self.prophet__seasonality_mode = 'multiplicative' + self.prophet__add_country_holidays = {'country_name': 'Singapore'} + self.prophet__yearly_seasonality = True + self.prophet__weekly_seasonality = False + self.prophet__daily_seasonality = False + + def checkbox__round_results__change(self, val): + self.round_results = val + + def textbox__target_column__change(self, val): + print('Updating textbox__target_column:', val) + self.target_column = val + + def btn__profiling__click(self): + self.analyser.fit(self.data) + self.analyser.profiling() + + return ( + self.update__md__profiling(), + self.update__plot__changepoints()) + + def btn__plot_correlation__click(self): + return (self.update__plot__correlation()) + + def file__historical__upload( + self, + file + ): + self.data = pd.read_csv( + file.name, + index_col='datetime', + parse_dates=['datetime']) + + print('[file__historical__upload]') + + return ( + self.update__df__table_view(), + self.update__dropdown__chart_view_filter(), + self.update__dropdown__seasonality_decompose(), + self.update__plot__chart_view()) + + def file__future__upload( + self, + file + ): + self.__handle_future_data_upload(file.name) + + return ( + self.update__df__table_view(), + self.update__dropdown__chart_view_filter(), + self.update__dropdown__seasonality_decompose(), + self.update__plot__chart_view(), + self.update__number__n_predict()) + + def btn__load_future_demo__click( + self + ): + self.__handle_future_data_upload(self.future_demo_data) + + # [df__table_view, number__n_predict] + + return ( + self.update__df__table_view(), + self.update__dropdown__chart_view_filter(), + self.update__dropdown__seasonality_decompose(), + self.update__plot__chart_view(), + self.update__number__n_predict()) + + def __handle_future_data_upload( + self, + path + ): + data = pd.read_csv( + path, + index_col='datetime', + parse_dates=['datetime']) + self.exog_columns = data.columns.tolist() + self.n_predict = len(data) + + print( + f"[file__future__upload] with {self.exog_columns} columns") + + self.data = pd.concat( + [self.data, data], + axis=0) + + def number__n_predict__change( + self, + val + ): + print(f'[number__n_predict__change], {val}') + self.n_predict = val + + def number__window_length__change( + self, + val): + print(f'[number__window_length__change], {val}') + self.window_length = val + + def btn__fit_data__click( + self): + data = self.data.drop(columns=self.exog_columns).dropna(how='any') + + self.forecaster.fit( + data, + target_col=self.target_column, + n_predict=self.n_predict, + window_length=self.window_length, + exog=None if len( + self.exog_columns) == 0 else self.data[self.exog_columns]) + return ( + gr.Number(interactive=False), # number__n_predict + gr.Number(interactive=False), # number__window_length + gr.File(interactive=False), # file__historical + gr.File(interactive=False), # file__future + gr.Button(visible=False), # btn__fit_data + gr.Column(visible=True), # column__models + gr.Button(visible=False), # btn__load_historical_demo + gr.Button(visible=False), # btn__load_future_demo + self.update__md__forecast_data_info() + ) + + def btn__load_historical_demo__click( + self + ): + self.data = pd.read_csv( + self.historical_demo_data, + index_col='datetime', + parse_dates=['datetime']) + + return ( + self.update__df__table_view(), + self.update__dropdown__chart_view_filter(), + self.update__dropdown__seasonality_decompose(), + self.update__plot__chart_view() + ) + + def dropdown__chart_view_filter__change(self, options): + return (self.update__plot__chart_view(options)) + + def dropdown__seasonality_decompose__change(self, col): + return ( + self.update__plot__seasonality_decompose(col), + self.update__plot_acg_pacf(col)) + + # ------------------------ # + # XGboost Model Operations # + # ------------------------ # + + def btn__train_xgboost__click(self): + (test, forecast, best_params) = self.xgboost.fit_predict( + y=self.forecaster.y, + y_train=self.forecaster.y_train, + window_length=self.forecaster.window_length, + fh=self.forecaster.fh, + fh_test=self.forecaster.fh_test, + params=self.xgboost_params, + X=self.forecaster.X, + X_train=self.forecaster.X_train, + X_test=self.forecaster.X_test, + X_future=self.forecaster.X_future + ) + + print(test, forecast, best_params) + + self.xgboost_forecast = forecast + self.xgboost_test = test + + return ( + self.update__plot__xgboost_result(test, forecast), + self.update__file__xgboost_result(), + self.update__df__xgboost_result()) + + def btn__set_xgboost_params__click(self, text): + params = json.loads(text.replace("'", '"')) + self.xgboost_params = params + + return ( + self.update__json_xgboost_params() + ) + + def checkbox__xgboost_round__change(self, val): + self.xgboost.round_result = val + + # ----------------------------------- # + # Prophet Model Operations & Updaters # + # ----------------------------------- # + + def btn__forecast_with_prophet__click(self): + self.prophet.fit_predict( + self.forecaster.y_train, + self.forecaster.y, + self.forecaster.fh, + self.forecaster.fh_test, + self.forecaster.period, + self.forecaster.freq, + X=self.forecaster.exog, + seasonality_mode=self.prophet__seasonality_mode, + add_country_holidays=self.prophet__add_country_holidays, + yearly_seasonality=self.prophet__yearly_seasonality, + weekly_seasonality=self.prophet__weekly_seasonality, + daily_seasonality=self.prophet__daily_seasonality, + round_val=self.round_results) + + return ( + self.update__plot__prophet_result(), + self.update__file__prophet_result(), + self.update__df__prophet_result()) + + def update__plot__prophet_result(self): + fig, ax = plt.subplots(figsize=self.plot_figsize_full_screen) + + plot_series( + self.forecaster.y_train[-2 * self.forecaster.period:], + self.forecaster.y_test, + self.prophet.predict, + self.prophet.forecast, + pred_interval=self.prophet.forecast_interval, + labels=['Train', 'Test', 'Predicted - Test', 'Forecast'], + ax=ax) + + ax.set_title('Prophet Forecast Result') + ax.legend(loc='upper left') + fig.tight_layout() + + return gr.Plot(fig) + + def update__file__prophet_result(self): + prophet_forecast_df = pd.DataFrame(self.prophet.forecast) + path = self.__create_temp_csv_file(prophet_forecast_df) + return gr.File(path) + + def update__df__prophet_result(self): + prophet_forecast_df = self.prophet.forecast.reset_index() + return gr.Dataframe(value=prophet_forecast_df) + + # =============================== # + # || Gradio Component Updaters || # + # =============================== # + + def update__plot__changepoints(self): + fig, axs = plt.subplots(2, 1, figsize=(20, 8)) + + axs[0].plot(self.data[['y']]) + + axs[0].text(self.data.index[0], + axs[0].get_ylim()[1]*0.9, + self.analyser.quantity_predictability[0], + fontsize=20) + + for i, p in enumerate(self.analyser.quantity_change_points): + axs[0].axvline(x=p) + axs[0].text(p, + axs[0].get_ylim()[1]*0.9, + self.analyser.quantity_predictability[i+1], + fontsize=20) + + axs[1].plot(self.data[['y']]) + + axs[1].text(self.data.index[0], + axs[1].get_ylim()[1]*0.9, + self.analyser.intermittent_predictability[0], + fontsize=20) + + for i, p in enumerate(self.analyser.intermittent_change_points): + axs[1].axvline(x=p) + axs[1].text(p, + axs[1].get_ylim()[1]*0.9, + self.analyser.intermittent_predictability[i+1], + fontsize=20) + + axs[0].set_title('Quantity Change Points & Predictability') + axs[1].set_title('Intermittent Change Points & Predictability') + + fig.tight_layout() + + return gr.Plot(fig) + + def update__md__profiling(self): + + return (f""" + \n### Data Characteristic: + \n # {self.analyser.characteristic} + \n --- + \n### Quantity Change Points: {self.analyser.quantity_change_points.astype(str).tolist()} + \n### Quantity Predictability: {self.analyser.quantity_predictability} + \n### Intermittent Change Points: {self.analyser.intermittent_change_points.astype(str).tolist()} + \n### Intermittent Predictability: {self.analyser.intermittent_predictability} + """) + + def update__md__forecast_data_info(self): + return gr.Markdown(value=f' \ + **Forecasting for these timestamps**: \ + {self.forecaster.fh.to_pandas().astype(str).tolist()} \ + \n **Data Period**: {self.forecaster.period} \ + \n **Data Frequency**: {self.forecaster.freq} \ + ') + + def update__plot__correlation(self): + fig, ax = plt.subplots(figsize=(20, 8)) + corr = self.data.corr(numeric_only=True) + mask = np.triu(np.ones_like(corr, dtype=bool)) + sns.heatmap( + corr, + mask=mask, + square=True, + annot=True, + cmap='coolwarm', + linewidths=.5, + cbar_kws={"shrink": .5}, + ax=ax) + + fig.tight_layout() + + return gr.Plot(fig) + + def update__df__table_view( + self + ): + data = self.data.reset_index() + return gr.Dataframe(value=data) + + def update__number__n_predict( + self + ): + return gr.Number(self.n_predict, interactive=False) + + def update__dropdown__chart_view_filter(self): + options = self.data.columns.tolist() + return gr.Dropdown(options, value=options) + + def update__dropdown__seasonality_decompose(self): + options = self.data.columns.tolist() + return gr.Dropdown(options) + + def update__plot__seasonality_decompose(self, col): + seasonal = seasonal_decompose(self.data[col].dropna()) + + fig = seasonal.plot() + return gr.Plot(fig) + + def update__plot_acg_pacf(self, col): + fig, axs = plt.subplots(2, 1, sharex=True, sharey=True) + + plot_acf(self.data[col].dropna(), ax=axs[0], zero=False) + plot_pacf(self.data[col].dropna(), ax=axs[1], zero=False) + + axs[0].set_title('Auto Correlation') + axs[1].set_title('Partial Auto Correlation') + + return gr.Plot(fig) + + # ---------------------- # + # Update XGboost Results # + # ---------------------- # + + def update__json_xgboost_params(self): + return gr.JSON(value=self.xgboost_params) + + def update__plot__xgboost_result(self, test, predict): + + fig, ax = plt.subplots(figsize=self.plot_figsize_full_screen) + + plot_series( + self.forecaster.y_train[-2*self.forecaster.period:], + self.forecaster.y_test, + test, + predict, + labels=["y_train (part)", "y_test", "y_pred", 'y_forecast'], + x_label='Date', + ax=ax) + + ax.set_xticklabels(ax.get_xticklabels(), rotation=45) + fig.tight_layout() + + return gr.Plot(fig) + + def update__plot__chart_view(self, cols=None): + fig, ax = plt.subplots(figsize=self.plot_figsize_full_screen) + + _cols = cols + + if _cols is None: + _cols = self.data.columns + + print('[update__plot__chart_view]') + + for col in _cols: + ax.plot(self.data[[col]], label=col) + + fig.legend() + fig.tight_layout() + return gr.Plot(fig) + + def update__file__xgboost_result(self): + path = self.__create_temp_csv_file(self.xgboost_forecast) + return gr.File(path) + + def update__df__xgboost_result(self): + + # xgboost_forecast is actually a Series instead of proper DataFrame + # Re constructing a proper dataframe for gradio to take + data = pd.DataFrame( + {"datetime": self.xgboost_forecast.index, + "y": self.xgboost_forecast.values}) + + return gr.Dataframe(value=data) + + # ------------- # + # Util Function # + # ------------- # + + def __create_temp_csv_file(self, df) -> str: + time_format = "%Y%m%d%H%M%S" + directory = 'temp' + now = datetime.datetime.now() + + # Check if there are old files, remove them # + for filename in os.listdir(directory): + file_path = os.path.join(directory, filename) + + file_time = datetime.datetime.strptime( + filename.split('.')[0], time_format) + + # If the file is older than 3 minutes, delete the file + if now > datetime.timedelta( + minutes=self.delete_file_old_than_n_minutes) + file_time: + print('deleting olde file: ', filename) + os.remove(file_path) + + new_file_name = now.strftime(format=time_format) + '.csv' + + new_file_path = os.path.join(directory, new_file_name) + + df.to_csv(new_file_path) + + return new_file_path diff --git a/notebooks/E01-quick_look_multivariate_data.ipynb b/notebooks/E01-quick_look_multivariate_data.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..13ef419a8bfdd091529da996ae7e2fea170d8b57 --- /dev/null +++ b/notebooks/E01-quick_look_multivariate_data.ipynb @@ -0,0 +1,669 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Aim\n", + "- Quick look at the multi variate data\n", + "- Perform necessary transformation, get the data ready for analytic\n", + "\n", + "- Aim for multivariate data analytic is to find Linear relationship between multiple variate and the target value, and explain in what percentage certain variable is affecting the target value?\n", + "- Why linear relationship? Because it is most explainable and straight forward, making more sense to business owners. " + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "# To call functions outside of this folder\n", + "import sys \n", + "sys.path.insert(0, '..')" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "from statsmodels.tsa.stattools import acf, pacf\n", + "from statsmodels.graphics.tsaplots import plot_pacf\n", + "\n", + "import seaborn as sns\n", + "\n", + "import matplotlib.pyplot as plt\n", + "\n", + "from src.analytics.ts_analytics import Ts_Analytics\n", + "\n", + "analytics = Ts_Analytics()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "# Load Data" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "ts = pd.read_excel('../data/multivariate/Predicting_price_blow_mold.xlsx')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "# What is the date range of the data?" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "- Data contains date from 2000-01-01 00:00:00 to 2022-12-01 00:00:00\n", + "- True Data contains full date range between 2000-01-01 00:00:00 and 2022-12-01 00:00:00\n" + ] + } + ], + "source": [ + "start = pd.to_datetime(ts['Date']).iloc[0]\n", + "end = pd.to_datetime(ts['Date']).iloc[-1]\n", + "\n", + "full_date_range = pd.date_range(start=start, end=end, freq='MS')\n", + "\n", + "print(f'- Data contains date from {start} to {end}')\n", + "\n", + "print('-',all(full_date_range == pd.to_datetime(ts['Date'])), \n", + " f'Data contains full date range between {start} and {end}')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "# What is the target column? \n", + "- 'Domestic Market (Contract) Blow Molding, Low' is the target column, based on the instruction" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "- Rename the target column Domestic Market (Contract) Blow Molding, Low to y\n", + "- Rename datetime column and set as index\n" + ] + } + ], + "source": [ + "target_column = 'Domestic Market (Contract) Blow Molding, Low'\n", + "print(f'- Rename the target column {target_column} to y')\n", + "ts = ts.rename(columns={target_column:'y'})\n", + "\n", + "print('- Rename datetime column and set as index')\n", + "ts.index = ts['Date']\n", + "ts.index = pd.to_datetime(ts.index)\n", + "ts = ts.drop(columns='Date')\n", + "\n", + "ts = ts.sort_index()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "# Sort columns name in correlation strong to wake order" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "ts = ts[ts.corr(numeric_only=True)['y'].sort_values(ascending=False).index]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "# What are the ratio of missing columns?" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/var/folders/bq/df5l25m5389gxcql8x_kd8zc0000gn/T/ipykernel_54914/790754012.py:4: UserWarning: Tight layout not applied. The bottom and top margins cannot be made large enough to accommodate all axes decorations.\n", + " fig.tight_layout()\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig,ax = plt.subplots(figsize=(12,6))\n", + "pd.concat([ts.notna().sum(), ts.isna().sum()], axis=1).plot(kind='bar', stacked=True, legend=['Null','Not Null'], ax=ax)\n", + "\n", + "fig.tight_layout()\n", + "ax.legend(labels=['Not null', 'Null'])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "# Which columns are top correlated with target column?" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Top 5 columns that are highly correlated with target column\n" + ] + }, + { + "data": { + "text/plain": [ + "Turkey_import 0.906855\n", + "GASREGM 0.902080\n", + "MCOILBRENTEU 0.881459\n", + "WTISPLC 0.880024\n", + "Producer Price Index by Industry: Plastics Material and Resins Manufacturing: Thermoplastic Resins and Plastics Materials 0.865644\n", + "Name: y, dtype: float64" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "print('Top 5 columns that are highly correlated with target column')\n", + "ts.corr(numeric_only=True)['y'].sort_values(ascending=False)[1:6]\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## For testing purpose, focus on the 3 top correlated target column, and 2 middle range correlation first" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Rename zoomin columns so it is easier to understand\n" + ] + } + ], + "source": [ + "zoom_in_columns = {\n", + " 'y':'y',\n", + " 'GASREGM':'gas_regm', \n", + " 'MCOILBRENTEU':'m_coil_brent_eu', \n", + " 'Producer Price Index by Industry: Plastics Material and Resins Manufacturing: Thermoplastic Resins and Plastics Materials ':'ppi_plastic_resins', \n", + " 'PRUBBUSDM':'global_proce_of_rubber',\n", + " 'PCU32611332611301':'ppi_nonpackaging_plastic'}\n", + "\n", + "ts = ts[zoom_in_columns.keys()]\n", + "ts = ts.rename(columns=zoom_in_columns)\n", + "\n", + "print('Rename zoomin columns so it is easier to understand')\n", + "analytics.analyse(ts)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "# What is the autocorrelation of the target column" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "# analytics.log_transform()" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "analytics.plot_target_pacf()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Set the correlation for target column\n" + ] + } + ], + "source": [ + "print('Set the correlation for target column')\n", + "analytics.set_ar('y', 2)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "create_target_lag_columns\n", + "create_lag_dfs y 2\n", + "drop all null values\n" + ] + } + ], + "source": [ + "analytics.create_target_lag_columns()" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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ygas_regmm_coil_brent_euppi_plastic_resinsglobal_proce_of_rubberppi_nonpackaging_plasticy_t-1y_t-2
Date
2000-01-0141.01.28925.51139.40029.207387106.30041.045.0
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2000-04-0147.01.46522.76151.40031.930148106.90047.047.0
2000-05-0147.01.48727.74155.60031.201702106.30047.047.0
...........................
2022-08-0193.03.975100.45329.27873.304558303.83790.090.0
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2022-11-0190.03.68591.42300.18565.265834307.22690.0NaN
2022-12-0190.03.21080.92291.825NaNNaNNaNNaN
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276 rows × 8 columns

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" + ], + "text/plain": [ + " y gas_regm m_coil_brent_eu ppi_plastic_resins \\\n", + "Date \n", + "2000-01-01 41.0 1.289 25.51 139.400 \n", + "2000-02-01 41.0 1.377 27.78 141.700 \n", + "2000-03-01 45.0 1.516 27.49 146.300 \n", + "2000-04-01 47.0 1.465 22.76 151.400 \n", + "2000-05-01 47.0 1.487 27.74 155.600 \n", + "... ... ... ... ... \n", + "2022-08-01 93.0 3.975 100.45 329.278 \n", + "2022-09-01 90.0 3.700 89.76 326.451 \n", + "2022-10-01 90.0 3.815 93.33 316.901 \n", + "2022-11-01 90.0 3.685 91.42 300.185 \n", + "2022-12-01 90.0 3.210 80.92 291.825 \n", + "\n", + " global_proce_of_rubber ppi_nonpackaging_plastic y_t-1 y_t-2 \n", + "Date \n", + "2000-01-01 29.207387 106.300 41.0 45.0 \n", + "2000-02-01 33.391099 105.600 45.0 47.0 \n", + "2000-03-01 30.941913 106.100 47.0 47.0 \n", + "2000-04-01 31.930148 106.900 47.0 47.0 \n", + "2000-05-01 31.201702 106.300 47.0 47.0 \n", + "... ... ... ... ... \n", + "2022-08-01 73.304558 303.837 90.0 90.0 \n", + "2022-09-01 66.956499 308.976 90.0 90.0 \n", + "2022-10-01 68.535729 312.788 90.0 90.0 \n", + "2022-11-01 65.265834 307.226 90.0 NaN \n", + "2022-12-01 NaN NaN NaN NaN \n", + "\n", + "[276 rows x 8 columns]" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "analytics.ts_df" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "\n", + "# Full null values" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [], + "source": [ + "ts.ffill(inplace=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "\n", + "# Save data" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [ + "ts['datetime'] = ts.index\n", + "ts.to_csv('../data/multivariate/blow_mold_preprocessed.csv', index=False)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "base", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.4" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/E02-ts_analytics.ipynb b/notebooks/E02-ts_analytics.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..9ba6d4d4052b296fb29d1ead707356486d07e8b3 --- /dev/null +++ b/notebooks/E02-ts_analytics.ipynb @@ -0,0 +1,927 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Aims\n", + "\n", + "- Build a class that can perform basic multi variate time series data analytics, and find the linear relationships between different columns" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "# To call functions outside of this folder\n", + "import sys \n", + "sys.path.insert(0, '..')" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "\n", + "import statsmodels.api as sm\n", + "from scipy import stats\n", + "from statsmodels.formula.api import ols\n", + "import statsmodels\n", + "import matplotlib.pyplot as plt\n", + "\n", + "import seaborn as sns\n", + "\n", + "from src.analytics.ts_analytics import Ts_Analytics\n", + "\n", + "analytics = Ts_Analytics()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "# Load data" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "data = pd.read_csv('../data/multivariate/blow_mold_preprocessed.csv')\n", + "\n", + "# data = data.drop(columns=['global_proce_of_rubber', 'ppi_nonpackaging_plastic'])\n", + "\n", + "analytics.analyse(data)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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datetimeygas_regmm_coil_brent_euppi_plastic_resinsglobal_proce_of_rubberppi_nonpackaging_plastic
02000-01-3141.01.28925.51139.40029.207387106.300
12000-02-2941.01.37727.78141.70033.391099105.600
22000-03-3145.01.51627.49146.30030.941913106.100
32000-04-3047.01.46522.76151.40031.930148106.900
42000-05-3147.01.48727.74155.60031.201702106.300
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2712022-08-3193.03.975100.45329.27873.304558303.837
2722022-09-3090.03.70089.76326.45166.956499308.976
2732022-10-3190.03.81593.33316.90168.535729312.788
2742022-11-3090.03.68591.42300.18565.265834307.226
2752022-12-3190.03.21080.92291.82565.265834307.226
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276 rows × 7 columns

\n", + "
" + ], + "text/plain": [ + " datetime y gas_regm m_coil_brent_eu ppi_plastic_resins \\\n", + "0 2000-01-31 41.0 1.289 25.51 139.400 \n", + "1 2000-02-29 41.0 1.377 27.78 141.700 \n", + "2 2000-03-31 45.0 1.516 27.49 146.300 \n", + "3 2000-04-30 47.0 1.465 22.76 151.400 \n", + "4 2000-05-31 47.0 1.487 27.74 155.600 \n", + ".. ... ... ... ... ... \n", + "271 2022-08-31 93.0 3.975 100.45 329.278 \n", + "272 2022-09-30 90.0 3.700 89.76 326.451 \n", + "273 2022-10-31 90.0 3.815 93.33 316.901 \n", + "274 2022-11-30 90.0 3.685 91.42 300.185 \n", + "275 2022-12-31 90.0 3.210 80.92 291.825 \n", + "\n", + " global_proce_of_rubber ppi_nonpackaging_plastic \n", + "0 29.207387 106.300 \n", + "1 33.391099 105.600 \n", + "2 30.941913 106.100 \n", + "3 31.930148 106.900 \n", + "4 31.201702 106.300 \n", + ".. ... ... \n", + "271 73.304558 303.837 \n", + "272 66.956499 308.976 \n", + "273 68.535729 312.788 \n", + "274 65.265834 307.226 \n", + "275 65.265834 307.226 \n", + "\n", + "[276 rows x 7 columns]" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "\n", + "# What is the autocorrelation of the target column?" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "analytics.plot_target_pacf()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "\n", + "# Set auto correlation of target column\n", + "- This is a data transformation process, not at this step" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "# analytics.set_ar('y', 2)\n", + "# analytics.create_target_lag_columns()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "# analytics.ts_df.ffill()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(276, 6)" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "analytics.ts_df.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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ygas_regmm_coil_brent_euppi_plastic_resinsglobal_proce_of_rubberppi_nonpackaging_plastic
datetime
2000-01-3141.01.28925.51139.429.207387106.3
2000-02-2941.01.37727.78141.733.391099105.6
2000-03-3145.01.51627.49146.330.941913106.1
2000-04-3047.01.46522.76151.431.930148106.9
2000-05-3147.01.48727.74155.631.201702106.3
\n", + "
" + ], + "text/plain": [ + " y gas_regm m_coil_brent_eu ppi_plastic_resins \\\n", + "datetime \n", + "2000-01-31 41.0 1.289 25.51 139.4 \n", + "2000-02-29 41.0 1.377 27.78 141.7 \n", + "2000-03-31 45.0 1.516 27.49 146.3 \n", + "2000-04-30 47.0 1.465 22.76 151.4 \n", + "2000-05-31 47.0 1.487 27.74 155.6 \n", + "\n", + " global_proce_of_rubber ppi_nonpackaging_plastic \n", + "datetime \n", + "2000-01-31 29.207387 106.3 \n", + "2000-02-29 33.391099 105.6 \n", + "2000-03-31 30.941913 106.1 \n", + "2000-04-30 31.930148 106.9 \n", + "2000-05-31 31.201702 106.3 " + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "analytics.ts_df.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "\n", + "# What are the correlation across columns?" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "analytics.plot_correlation()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "\n", + "# What is the distribution of each column?\n", + "\n", + "- They are not normal distributed, however, data with strong correlation shows similar distribution" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "analytics.plot_distributions()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "# What is the initial multi regression model?\n", + "- P > |t| column says the chance of a model that built without this variable is same as the model built with this variable\n", + "- If the P value is big, means the variable have minor affect on the model (because the model likely will not change even when remove this column)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "train_multiple_regression\n" + ] + }, + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "
OLS Regression Results
Dep. Variable: y R-squared: 0.908
Model: OLS Adj. R-squared: 0.906
Method: Least Squares F-statistic: 530.2
Date: Sat, 25 Nov 2023 Prob (F-statistic): 2.55e-137
Time: 00:32:56 Log-Likelihood: -881.16
No. Observations: 276 AIC: 1774.
Df Residuals: 270 BIC: 1796.
Df Model: 5
Covariance Type: nonrobust
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coef std err t P>|t| [0.025 0.975]
const 11.2549 1.864 6.037 0.000 7.584 14.925
gas_regm -8.4979 2.283 -3.722 0.000 -12.993 -4.003
m_coil_brent_eu 0.5358 0.055 9.727 0.000 0.427 0.644
ppi_plastic_resins 0.2139 0.017 12.627 0.000 0.181 0.247
global_proce_of_rubber -0.0004 0.014 -0.025 0.980 -0.029 0.028
ppi_nonpackaging_plastic 0.0027 0.006 0.421 0.674 -0.010 0.015
\n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "
Omnibus: 22.574 Durbin-Watson: 0.408
Prob(Omnibus): 0.000 Jarque-Bera (JB): 57.291
Skew: -0.336 Prob(JB): 3.63e-13
Kurtosis: 5.129 Cond. No. 2.11e+03


Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
[2] The condition number is large, 2.11e+03. This might indicate that there are
strong multicollinearity or other numerical problems." + ], + "text/latex": [ + "\\begin{center}\n", + "\\begin{tabular}{lclc}\n", + "\\toprule\n", + "\\textbf{Dep. Variable:} & y & \\textbf{ R-squared: } & 0.908 \\\\\n", + "\\textbf{Model:} & OLS & \\textbf{ Adj. R-squared: } & 0.906 \\\\\n", + "\\textbf{Method:} & Least Squares & \\textbf{ F-statistic: } & 530.2 \\\\\n", + "\\textbf{Date:} & Sat, 25 Nov 2023 & \\textbf{ Prob (F-statistic):} & 2.55e-137 \\\\\n", + "\\textbf{Time:} & 00:32:56 & \\textbf{ Log-Likelihood: } & -881.16 \\\\\n", + "\\textbf{No. Observations:} & 276 & \\textbf{ AIC: } & 1774. \\\\\n", + "\\textbf{Df Residuals:} & 270 & \\textbf{ BIC: } & 1796. \\\\\n", + "\\textbf{Df Model:} & 5 & \\textbf{ } & \\\\\n", + "\\textbf{Covariance Type:} & nonrobust & \\textbf{ } & \\\\\n", + "\\bottomrule\n", + "\\end{tabular}\n", + "\\begin{tabular}{lcccccc}\n", + " & \\textbf{coef} & \\textbf{std err} & \\textbf{t} & \\textbf{P$> |$t$|$} & \\textbf{[0.025} & \\textbf{0.975]} \\\\\n", + "\\midrule\n", + "\\textbf{const} & 11.2549 & 1.864 & 6.037 & 0.000 & 7.584 & 14.925 \\\\\n", + "\\textbf{gas\\_regm} & -8.4979 & 2.283 & -3.722 & 0.000 & -12.993 & -4.003 \\\\\n", + "\\textbf{m\\_coil\\_brent\\_eu} & 0.5358 & 0.055 & 9.727 & 0.000 & 0.427 & 0.644 \\\\\n", + "\\textbf{ppi\\_plastic\\_resins} & 0.2139 & 0.017 & 12.627 & 0.000 & 0.181 & 0.247 \\\\\n", + "\\textbf{global\\_proce\\_of\\_rubber} & -0.0004 & 0.014 & -0.025 & 0.980 & -0.029 & 0.028 \\\\\n", + "\\textbf{ppi\\_nonpackaging\\_plastic} & 0.0027 & 0.006 & 0.421 & 0.674 & -0.010 & 0.015 \\\\\n", + "\\bottomrule\n", + "\\end{tabular}\n", + "\\begin{tabular}{lclc}\n", + "\\textbf{Omnibus:} & 22.574 & \\textbf{ Durbin-Watson: } & 0.408 \\\\\n", + "\\textbf{Prob(Omnibus):} & 0.000 & \\textbf{ Jarque-Bera (JB): } & 57.291 \\\\\n", + "\\textbf{Skew:} & -0.336 & \\textbf{ Prob(JB): } & 3.63e-13 \\\\\n", + "\\textbf{Kurtosis:} & 5.129 & \\textbf{ Cond. No. } & 2.11e+03 \\\\\n", + "\\bottomrule\n", + "\\end{tabular}\n", + "%\\caption{OLS Regression Results}\n", + "\\end{center}\n", + "\n", + "Notes: \\newline\n", + " [1] Standard Errors assume that the covariance matrix of the errors is correctly specified. \\newline\n", + " [2] The condition number is large, 2.11e+03. This might indicate that there are \\newline\n", + " strong multicollinearity or other numerical problems." + ], + "text/plain": [ + "\n", + "\"\"\"\n", + " OLS Regression Results \n", + "==============================================================================\n", + "Dep. Variable: y R-squared: 0.908\n", + "Model: OLS Adj. R-squared: 0.906\n", + "Method: Least Squares F-statistic: 530.2\n", + "Date: Sat, 25 Nov 2023 Prob (F-statistic): 2.55e-137\n", + "Time: 00:32:56 Log-Likelihood: -881.16\n", + "No. Observations: 276 AIC: 1774.\n", + "Df Residuals: 270 BIC: 1796.\n", + "Df Model: 5 \n", + "Covariance Type: nonrobust \n", + "============================================================================================\n", + " coef std err t P>|t| [0.025 0.975]\n", + "--------------------------------------------------------------------------------------------\n", + "const 11.2549 1.864 6.037 0.000 7.584 14.925\n", + "gas_regm -8.4979 2.283 -3.722 0.000 -12.993 -4.003\n", + "m_coil_brent_eu 0.5358 0.055 9.727 0.000 0.427 0.644\n", + "ppi_plastic_resins 0.2139 0.017 12.627 0.000 0.181 0.247\n", + "global_proce_of_rubber -0.0004 0.014 -0.025 0.980 -0.029 0.028\n", + "ppi_nonpackaging_plastic 0.0027 0.006 0.421 0.674 -0.010 0.015\n", + "==============================================================================\n", + "Omnibus: 22.574 Durbin-Watson: 0.408\n", + "Prob(Omnibus): 0.000 Jarque-Bera (JB): 57.291\n", + "Skew: -0.336 Prob(JB): 3.63e-13\n", + "Kurtosis: 5.129 Cond. No. 2.11e+03\n", + "==============================================================================\n", + "\n", + "Notes:\n", + "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n", + "[2] The condition number is large, 2.11e+03. This might indicate that there are\n", + "strong multicollinearity or other numerical problems.\n", + "\"\"\"" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "analytics.train_multiple_regression()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "# What is the effect size of each columns? How to perform ANOVA ?" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "# What is the ordinal least squared regression model formula? " + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'11.25487003334793 + gas_regm * -8.498 + m_coil_brent_eu * 0.536 + ppi_plastic_resins * 0.214 + global_proce_of_rubber * -0.0 + ppi_nonpackaging_plastic * 0.003'" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "analytics.multiple_regression_formula" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "# What is the coefficient of determination (r-squared) for each independent variable?\n", + "- Meaning, in what percentage each independent variable can explain the target columns?" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/qiaozhang/Desktop/sentient-dev/snr_demand-forecasting/notebooks/../src/analytics/ts_analytics.py:173: UserWarning: set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.\n", + " beta_plot.set_xticklabels(beta_plot.get_xticklabels(), rotation=45)\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "analytics.plot_beta()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "# How to measure the Shared variance (multicollinearity) between independent variables? " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "\n", + "# What is the seasonality of the target column?\n", + "\n", + "- Trend is not presenting with the default seasonality period\n", + "- Not recommended to use statistical models, because the seasonality is not strong\n", + "- However, because of the strong auto currelation, we can build a model that predict next 2 values relatively accurate. " + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "analytics.plot_target_seasonality().plot()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "\n", + "# What is the default seasonality period and frequency for the provided data?" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "12" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "analytics.period" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'M'" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "analytics.freq" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "\n", + "# Can more seasonality been extracted from the data?" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "analytics.set_period([12])" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "analytics.plot_target_seasonality().plot()\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "demand-forecasting", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.5" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/E03-multivariate_forecasting.ipynb b/notebooks/E03-multivariate_forecasting.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..6ac1ef8aa0bf98c485344981d2cb1239d539279a --- /dev/null +++ b/notebooks/E03-multivariate_forecasting.ipynb @@ -0,0 +1,361 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Aims\n", + "\n", + "- Test multivariate forecasting pipeline" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "# To call functions outside of this folder\n", + "import sys \n", + "sys.path.insert(0, '..')" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "\n", + "from src.forecast.multivariate import MultivariateForecasting" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "\n", + "# Load Data" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "data = pd.read_csv('../data/multivariate/blow_mold_preprocessed.csv')\n", + "\n", + "train = data[:252]\n", + "exog = data[252:].drop(columns='y')\n", + "\n", + "test = data[252:].set_index('datetime')\n", + "test.index = pd.to_datetime(test.index)\n", + "test = test[['y']]\n", + "\n", + "mf = MultivariateForecasting(train, exog)\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "\n", + "# How does train test been splitted?\n", + "\n", + "- Test size is same as forecast horizon size\n", + "- No sliding window for cross validation at this moment" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "24" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(mf.fh)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(24, 5)" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mf.X_test.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "\n", + "# What is exog data?" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- For example, using 3 different independent variable A, B, C to forecast y\n", + "- if the goal is to forecast next 4 y values, y_t+1, y_t+2, y_t+3, y_t+4\n", + "- both A, B and C must have the future 4 values in the first place, and these \"future\" values of A, B, C are exogenous data, which could be hard to collect\n", + "- Likely, these exogenous data are also forecasted by some other method, and any forecasting will carry error, these error will be accumulated in multivariate forecasting" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "\n", + "# How does the forecast horizon been defined ?\n", + "\n", + "- Forecast horizon is same size as exog " + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(24, 5)" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mf.exog.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "ForecastingHorizon(['2021-01-31', '2021-02-28', '2021-03-31', '2021-04-30',\n", + " '2021-05-31', '2021-06-30', '2021-07-31', '2021-08-31',\n", + " '2021-09-30', '2021-10-31', '2021-11-30', '2021-12-31',\n", + " '2022-01-31', '2022-02-28', '2022-03-31', '2022-04-30',\n", + " '2022-05-31', '2022-06-30', '2022-07-31', '2022-08-31',\n", + " '2022-09-30', '2022-10-31', '2022-11-30', '2022-12-31'],\n", + " dtype='datetime64[ns]', name='datetime', freq=None, is_relative=False)" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mf.fh" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "mf.train_xgboost()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "\n", + "# Forecast result" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+8XP4yQ2qBo9TQ4e9HmONbH7Q+zcw5DGXrl8lIiZLgsmoUaOIi4vjjTfecO675pprCAsL45133sEwDBITE5kyZQq///3vAbDb7cTFxfHss89y9913/+pruC2YZO+Hv1dzXb5FuxMhZKD5NaqN616zDv74cSrz1hwkMtScRC0punFPotYQLy7eyd+/3kVQgB//vvtCzk2K8swLlxbB13+Bta8Chnmb8Zh/QoehDTtvdYEk9mzzck3XK6sPHLmH4ZP7Yc/X5s/JA+CqV1y6DMIZZe0xx+Fs/o/5s80fOl1mBn17gblEQ2m++dVeABV219dg84dmLc3Lq80qt1an7DvxvX8grHzxZE9TaAsY8jj0uk2XwkRcyJJg8swzz/Dqq6/y1VdfkZKSwo8//siwYcN46aWXGDduHHv37qVDhw5s3LiR8847OfvpmDFjiIqKYu7cub/6Gu4KJhUVDsqe60RZUCTHW/Ymq2UfjrfsTUlonMteo772ZBby4pKd2Gzw5sQ+DOkca3VJXs3hMLjrnQ0s2XaU+IgQPr1/IK3CPbj2zf7vzN6T7P3mz70mmgOhg6v2CO79uYCt6Xk1niawNJd2u+fSbvc7BJYXAJAX0YldXSeTnniZ+Rv+KWzYuLBDzMlZcA0DNsyBRX+EskKzx+Hyp82p9t3Vy5eXDsufNdciqrzs2f0a84M+pkPNzysvhdICM3g5g0t1P+ef3DDMcPHL4FH5c0hU3XqJ9i6H//0BMreaP7fqCiOegfaD6/mHISKnsiSYGIbBY489xrPPPou/vz8VFRU8/fTTPProowCsWrWKAQMGcPjwYRITE53Pu+uuuzhw4ACLFi067Zx2ux27/eRvU3l5eSQlJbk8mJSWO+j5x4UU4b3Tjj94SSd+e5nWbqmN/JIyrnr5O/b8XEifti2Yf0c/ggI8eCmjtBCWTIN1r5k/R7Yxe09OfMh9u+tnJry5Dkc1765ICrg94Etu8/8fETbzLq9tjiT+Xn4Nixy9Mc5wF390syA+vX8graNCT+48vg8+vhcOrjJ/7niZOQ4mIsEVLTUVZ8PKl2DtayfvTOt4GVzyJ9+6Q6iiHDa+ZY4bqrwNvMsoM1hGt7O0NBFf56pgUqd+zPfff5958+bx7rvv0q1bN3744QemTJlCYmIiEyZMcB5n+8Vva4ZhnLav0owZM5g2bVo9Sq8bmw3OaZ/46wda5IJ2MTx4SSery/AZ4SGBzL61N1fN/I71+7N58rOtPHlVd88VENQMrnjOXGPnv/dCzkF4ewz0uYMjfR7lgfc24TAgJa65s4ejmSOfKwoWMqLwY8KMIgAOBLTlw/CbWR/SH8PmR98zvOSBrCLSc0u4d/5GPri7H8EBJ8YgRbeDiZ/Bmlfg6yfNhQtf6QdX/A16XNuw3pPSQvPS1cq/nxzXkdQXLnnC5TMde4R/APS5A7qNhWXPwPp/mQOKd30FF94HF/2fOeZFRCxTpx6TpKQk/vCHPzB58mTnvqeeeop58+axffv2el3K8VSPiTROS7cf5Tdzv8cw4NlrenBDHwvGCNkLYMkT5occkOEXx5SSOylMuNAcxFyWa4aGNa+a4y4A4rqbY0i6jKr15Yi040WM+udKcovLuLlfG566qsfpB2Vuh4V3m3eYgTlGZdSL5qWPuigvhY1zYflzUJhp7ovtZg60TbncIwPCPSJzm3l5Z+8y8+fm8XDZNOhxvTWDiUV8mCVr5RQVFTlvC67k7++Pw2He2dKuXTvi4+NZvHix8/HS0lKWL19O//79qz1ncHAwERERVTaR2hraJY6HLjUvf/3p4y1sPGjBLK3BzWHk83DrJ2QHxhPvOMqCoKd4t/WHhHw7A146B1b81Qwlcd3hhnlw97dwdg0DW2uQFB3GSzf2xGaDeWsOVj9Ff2wXuGOJuQaQXwBs+6Ru0+s7KuDH92Fmb3MtqMJMiEqGsa/DpG/NdYYaSygBiO0Kt3wMN75nDoQvyDCD3RuXmZMriojH1SmYjB49mqeffprPP/+c/fv3s3DhQl544QWuvvpqwLyEM2XKFKZPn87ChQvZvHkzEydOJCwsjPHjx7ulASKTh3RkeLd4SiscTHpnA5l5JZbU8WF2BwbmP838iksACP/pzVMCSY+TgaTr6Hr/Nj6kcywPDDUv+T22MJVt1Q2u9Q80bzG+Y4k5wLPw5xPT699jzt1THcOAHf+DVy+ChXdBzgFoFmteDrrvezjnenPq/sbIZoMuV8DktXDpVHMQ8eHv4V+XmH9m+RlWVyjSpNTpUk5+fj5/+tOfWLhwIZmZmSQmJjJu3Dj+/Oc/ExRkXkevnGDttddeqzLBWvfutbv+71VT0ovPKLCXc/XL37Ers4Dz20Tx3l2njMHwgK1H8rj6le+wlzuYcmknprQ7BJ//nzlPx8UPmwsEuujSgMNhcNtb61m+82eSY8L45L6BRIYGVn9wWQl88/TJ6fUjzoIxM6HDkJPH7P8Ovp5mznoMEBwJAx+EvpPMsTRNTX6GeVv4D/PNn4Oam2NP+t0Lgd47eF7EapqSXuQX9h8r5MqZK8krKWfcBW2YMbaaMRhukFtcxpUzV3Igq4jBnVvx5oQ+bl90MbuwlFH/XMnhnGIu7RrH7Ft6nfk1D64xFyTM3mf+3OdOsxdk+XPmYFkwJ2vrOwkGPKgJyAAObYAvHzF7T8CcI+by6dD5isZ1OUvERRRMRKqxbEcmt721HsOAp6/uzk19k936euacKt+zZFsmraNC+fyBgUSFBbn1NSulHsrlmlmrKK1w8LvLOzN5SMczP6G0EBb/2TlI18kvAM6/FS5+xLW3GDcGDgek/tsc3Jyfbu5rPxgG/QGSLmi8l7dE6kHBRKQGryzbzXP/20Ggv4337uxH77bu++3/5W9289dFOwgK8OPDSf3pcZZnV4J+b91BHv0oFT8bvPObvgzoWIu7b/Yshf/eB3mHofu15hTtZ5ocTcw7r1a+AKtmnpzFtlksdB5hjhlqdzEEeHCSPxEvpGAiUgPDMLjv3U18nppOy+bBfHb/QOIjXT824Lvdx7jljbU4DHhmbA9uvMDztyobhsEj//mJf284REyzID57YCAJkaG//sSyYnPtqMjW7i+yMTm+z7z8tf3zquv1BIWbU/J3HWVOPBei/7uk6VEwETmDQns518xaxfaMfM5NiuL9u/q5dFHEIznFjPrnSo4XlnJ977N47lrrZj8tKavgmlmr2HIkj/PaRPH+XRd6dhbcpqi81FwIdNtnZkgpOOXOHf8gaDcIuow0t+ZaYkKaBgUTkV9xMKuI0TPNCcmu730Wz15zTo0zENeFvbyCG15bww9pOXRLjODDe/pbvhL0wawiRv3zW/JKyrn1wmT+MsaDs+A2dQ4HHNloLhK4/TPI2n3KgzZzptwuI83elOj2lpUp4m4KJiK1sGLnz0ycY65Z8+SYbtxyYdsGn/NPH2/mnTUHvG4l6KXbj3L7W+YdJC/d0JOrztNlGkv8vONESPncDCynij3bnO236yiIP0d390ijomAiUkuvLd/DjC+3E+BnY/4dfenbPqbe51q46RC/ff9HcyXoCX0Y0sW7uulf+GoH/1i6m5BAPz6ePIAu8XoPWSr3kDnr7vbPYP9KMCpOPhbZxuxJOfcGSDyv5nOI+AgFE5FaMgyDBxb8wKc/HqFl8yA+uW8giVG1GCD6C9vSzUnUSsocPHBJJx7ywpWgKxwGE+es49tdx2gbE8Yn9w8kIqSGydfEs4qOw85FZkjZ/fXJVZptfnDDfHP2WREfZslaOSK+yGaz8dw159A1IYJjBaVMmreBkrKKX3/iKXKLy7hn3gZKyhxcnNLKa1eC9vez8Y8bz6N1VCj7s4p4+IMf8bLfPZqusGjoOQ5unA+P7IUb3zXv4DEc8OFv4MgmqysU8QoKJtIkhAb5M/uWXrQIC+SnQ7k8vnBzrT+wDcPg4X//yP6sIlpHhfL3G3ri7+aZXRuiRbMgXrnpfIL8/fhq61FeXb7X6pLkl4LCzMs4496DDkOhrAjevQFyDlpdmYjlFEykyUiKDmPm+PPxs8GHGw/x1qr9tXreq8v3snjrUYL8/Zh18/m0aOaZmV0b4tykKKZe2Q2Avy7azqrdxyyuSKrlHwjXvWUOii04aoaTmhZaFGkiFEykSRnQsSWPXdEVgKc+38bqPVlnPH7V7mP8ddF2AKaN6cY5Z0W5u0SXGXdBEtf2OguHAfe/t4n03GKrS5LqhETC+A+geRxkboUPJkBFmdVViVhGwUSanN8MbMdVPROpcBhMfncjh7KLqj0uPbeY+9/bhMOAa3udxY19kjxcacPYbDaeHNOdrgkRZBWWMnn+RkrLHVaXJdWJSoLx70NgGOz9Bj5/CDQ2SJooBRNpcmw2G89ccw7dW0dwvLCUu9/ZQHFp1cGwpeUO7p2/kazCUs5OiOCpq7q7ZHI2TwsN8ufVm88nPCSAjQdzmP7FNqtLkpokngfXvmnepbPxbVj5otUViVhCwUSapJBAf167pTfRzYLYciSPRz/6qcpg2Kc/38qmgzlEhATw6s29LJ/ZtSGSY5rx0g09AXhr1X7++8NhawuSmnUeAcOfMb//ehps/tDaekQsoGAiTVbrqFBeHn8+/n42Pv7hCG+s3AfAx5sOM3f1AQBevKEnbWK8Y2bXhrikaxz3DekIwB8+TGVHRr7FFUmN+t4Nfe8xv194DxxcY209Ih6mYCJN2oUdYvjTSHMw7PQvtvHWd/t49KNUAO4f2pFLusZZWZ5L/fayFC7q1JLisgrumbeB/BINsPRalz8Nna+ACju8Nw6y9lhdkYjHaOZXafLMeUp+4sONh5z7LurUkrduu8Cr5yupj+OFpYz6x7ccyS1hQMcYBnZs5bJzt2vZjOHd4112viavtBDmXAHpP0BMR/jNYnOSNhEvpSnpRVyopKyCG15bzY+HcmkdFcqn9w8k2gfmK6mPH9JyuP7V1ZRWuP4OnSUPDaJjbHOXn7fJys+Af10KuWnQpj/c+jEEBFtdlUi1FExEXOznfDvz1x5gTM/WtGvZzOpy3Gr1niwWbjqEw0Xv/qXbMzleWMpbt/VhcGfvWtjQ5x3dCm9eDvY86HEdjH1dqxKLV3LV53eAC2sS8WmtwoOZcqn3LcznDhd2iOHCDvVfZfmXbv7XWlbuPsbxwlKXnVNOiDsbrp8L86+D1H9Di3Yw9HGrqxJxGw1+FZEGq7zspWDiJh2GwqgT85qseA42zbe2HhE3UjARkQZTMPGA82+FgQ+Z33/6AOxdbm09Im6iYCIiDaZg4iFD/wTdxoKjHN6/BX7eYXVFIi6nYCIiDaZg4iF+fnDVLEjqC/ZcmH8tFGRaXZWISymYiEiDKZh4UGAI3PieOQg25yC8dyOUVr8QpYgvUjARkQZzBpMiBROPaBYDN/0HQlvA4Q2w8C5waOVoaRwUTESkwdRjYoGWHeHGd8E/CLZ9Cov/ZHVFIi6hYCIiDVYZTHKLyyh3w4yyUoPk/jDmFfP71TNh/b+srUfEBRRMRKTBokIDATAMyCnW4oAedc51MOSP5vdf/A52fmVtPSINpGAiIg0W4O9HVJgZTnQ5xwIXPww9bwLDAf+eCGnrra5IpN7qFEzatm2LzWY7bZs8eTIAEydOPO2xfv36uaVwEfEu0WEaZ2IZmw1GvQTtB0NZIcy7BtJ/tLoqkXqpUzBZv3496enpzm3x4sUAXHfddc5jhg8fXuWYL774wrUVi4hX0gBYiwUEmYNhk/qZc5y8czVkbre6KpE6q1MwadWqFfHx8c7ts88+o0OHDgwaNMh5THBwcJVjoqOjXV60iHgfBRMvENQMbvoAEs+Doix4ewxk7bG6KpE6qfcYk9LSUubNm8ftt9+O7ZQluJctW0ZsbCwpKSnceeedZGaeeVZCu91OXl5elU1EfI+CiZcIiYSbP4LYblCQYYaTnINWVyVSa/UOJh9//DE5OTlMnDjRuW/EiBHMnz+fpUuX8vzzz7N+/XqGDh2K3W6v8TwzZswgMjLSuSUlJdW3JBGxkIKJFwmLhls/hphOkJsGc6+EvHSrqxKpFZthGEZ9nnj55ZcTFBTEp59+WuMx6enpJCcns2DBAsaOHVvtMXa7vUpwycvLIykpidzcXCIiIupTmohY4F/f7uWpz7dx5bmJ/GPceVaXIwC5h2HOCMg5AC07w21fQLOWVlcljVReXh6RkZEN/vyuV4/JgQMHWLJkCXfccccZj0tISCA5OZldu3bVeExwcDARERFVNhHxPZU9Jtmalt57RLaGCZ9AeCIc2wHvXAXF2VZXJXJG9Qomc+bMITY2lpEjR57xuKysLNLS0khISKhXcSLiO1qcCCZZBQomXqVFWzOcNGsFGakw71qw51tdlUiN6hxMHA4Hc+bMYcKECQQEBDj3FxQU8PDDD7N69Wr279/PsmXLGD16NC1btuTqq692adEi4n1iNMbEe7XsBLf+98Sif9/Du1qRWLxXnYPJkiVLOHjwILfffnuV/f7+/qSmpjJmzBhSUlKYMGECKSkprF69mvDwcJcVLCLeqUXYyRWG6zl0Tdwprpt5t05wBBxYCe/fBOU135ggYpWAXz+kqmHDhlX7n05oaCiLFi1ySVEi4ntimpvBpLTcQWFpBc2D6/zfi7hb6/Phpn+bk6/tWQr/vg2unwv+gVZXJuKktXJExCVCA/0JDjD/S8nW5Rzv1aYfjHsP/INhx+ew8G5wVFhdlYiTgomIuITNZnOOM8lSMPFu7QfDDe+AXyBs/hA+fQAcDqurEgEUTETEhaJPXM5Rj4kPSLkcrvkX2Pxg0zz43+9BY4PECyiYiIjLVA6AVY+Jj+h2FVw1C7DButmw5AmFE7GcgomIuEzlpRz1mPiQc2+EUS+a33/3d1j+nLX1SJOnYCIiLtNCY0x8U+/b4PIZ5vfLpsOqf1pbjzRpCiYi4jInJ1nT/Bg+58J7Yegfze+/+iOse93aeqTJUjAREZdp4QwmZRZXIvVy8e9g4EPm9188DJvmW1uPNEkKJiLiMuoxaQQu+TP0vcf8/pP74Ou/QGmhtTVJk6JgIiIuU3lXTnaRekx8ls0Gw2dA79vBcMC3z8PMC2DLx7pjRzxCwUREXKZyWvqsAvWY+DSbDUa+ADfMh8g2kHcI/j0B3h4DP++wujpp5LSYhYi4THSzYADySsopq3AQ6K/ffXyWzQZdR0HHS2DlS7DyRdi3HGb1h76TYNDvISTCmtocFbBrMRxcBYHNIDQKQqJOfI2s+n1gqDU1Sr0pmIiIy0SGBmKzmT3+2UWlxIaHWF2SNFRgKAx51JzvZNFjsOMLWD0TUv8Dw56EHteZIcYTio6bs9Su/xfkHKjdc/yDTwaXkMjqvw+NgtAWcFYfaB7rpuKlthRMRMRl/P1stAgL4nhhKdmFZQomjUl0O3Pxv51fmdPXH98LH90J38+BK56D+B7ue+30n8yZaVP/DeUl5r6QSDh7DGCDkhwozoGS3KrfY0CFHQqOmtuvsflBu4uh+zXQZRSERburRXIGCiYi4lItwgI5XlhKVqEdCLe6HHG1lGHQfpDZa7Lib+bllNcuhj53wJDHzd4HV6gog22fmPOpHFx9cn9cD+h7F3S/FoLCan6+wwGl+dUHFuf3J34uzoH8dDi6GfYuM7fPHjIvY3UbC12ugGD9W/YUBRMRcamYZsHs+bmQ45r9tfEKCIaL/g/OucGcjG3LQrNHY/NHcOlU6HkT+NVzfFF+Bmx4y+yJKcgw9/kFQNcr4YK7oE2/2l068vM7Md4ksvavfXyv2ZbNH5khZef/zC0gBDoNM3tSUi7XuBU3sxmGd93/lZeXR2RkJLm5uUREWDSwSkTq7e53vmfRlqM8OaYbt1zY1upyxBP2LocvH4Gft5s/t+4FV/wNWp9fu+cbBqStNcPN1v+Co9zc3zwOet0GvSZCRIJbSq9R5nbY8hFs/hCydp/cH9QcOl9hhpQOQyEgyLN1eTFXfX6rx0REXKryzhytl9OEtB8Ek1bC2tdg2TNweAO8PhR6TYChf4ZmMdU/r6zYHDeybjZkpJ7cn9QPLrjT7CWx6oM/tgvEPgaDH4WMn8xelM0fQe5BSP3A3EIizRq7j4W2F4O/PlJdQX+KIuJS0c0CAa0w3OT4B0L/+6DHtbD4CfhpgXlJZsvHcMmfzJ4PP3/z2Oz9sP4N2PQOFGeb+wJCzDt8LrgTEs61qBHVsNnMehLONS9THfre7EXZstC81LTpHXMLawndrjJ7UpL61f9SluhSjoi41hsr9/HkZ1sZdU4CM8fXsitfGp8Dq+GL38HREz0h8T3M+U+2fWaO2+DER09Usjlw9rybfesuGEcFHFhlhpSt/4Xi4ycfC080e1E6XQZJfZvMmBRXfX4rmIiIS3286TBT3v+BAR1jmH9HP6vLEStVlMOGObD0yRO3756iwyXmYNZOl53sSfFVFWXmOJstH8G2T8Ged/Ix/yBzfpS2F0G7i8zvA4Ktq9WNFExExCst3/kzE95cR5f4cP435WKryxFvUHgMvp4Gu5aYc4/0uQNadrS6KvcoK4E9X5u9KPtWmLchnyogBJIuMMektLsIEs9vNANoNfhVRLxS5QrD2UUaYyInNGsJV/7T6io8IzAEuow0N8Mwb0HetwL2fwv7voXCTPPnfSvgGyAwzLwFuu1F5uRuCT2b/CDapt16EXG5FieCyfHCUgzDwOap6cpFvI3NBjEdzK33bWZQObbzZFDZvxKKsmDPUnMD83bkNheavSltLzIH3fr6pa46UjAREZeKDjODSVmFQb69nIiQQIsrEvESNhu06mxuF9xpzk778zazJ6UyqJTkwO7F5gYQHAnJ/c3Bw2ExJ7YWJ78PjYagZp5br8gDFExExKVCg/wJDfSnuKyC7MJSBRORmvj5QVw3c+s3yQwqRzefvOxzYBXYc2Hnl+ZWE/9g846msBjza+gp358aYMKiT+4Lau61YUbBRERcLrpZEIdziskqLCU5ppnV5Yj4Bj8/SDjH3C6cbN6SnP6j2ZOSvd+8Jbkoy1xluejE9xV2c8tPP32g7Zn4B8NjR7xyPIv3VSQiPq8ymGiSNZEG8PM3p/WvaWp/w4DSwuoDS5V9J74WHzfvkKqwm4N0vTCUgIKJiLhB9IkBsJqWXsSNbDYIbm5uUW1q9xzDgLIiKMn79WMtomAiIi7nvGVYwUTEu9hs5mDZIO+9xFqnyfzbtm2LzWY7bZs8eTIAhmEwdepUEhMTCQ0NZfDgwWzZssUthYuI9zr1lmERkbqoUzBZv3496enpzm3xYvN2puuuuw6A5557jhdeeIGZM2eyfv164uPjueyyy8jPz3d95SLitaIVTESknuoUTFq1akV8fLxz++yzz+jQoQODBg3CMAxeeuklHn/8ccaOHUv37t2ZO3cuRUVFvPvuu+6qX0S8kIKJiNRXvddlLi0tZd68edx+++3YbDb27dtHRkYGw4YNcx4THBzMoEGDWLVqlUuKFRHf4AwmmpZeROqo3oNfP/74Y3Jycpg4cSIAGRkZAMTFxVU5Li4ujgMHDtR4Hrvdjt1ud/6cl+e9I4VFpHbUYyIi9VXvHpM33niDESNGkJiYWGX/L9fF+LW1MmbMmEFkZKRzS0pKqm9JIuIlnMGkQMFEROqmXsHkwIEDLFmyhDvuuMO5Lz4+HjjZc1IpMzPztF6UUz366KPk5uY6t7S0tPqUJCJepHK9nHx7OaXlDourERFfUq9gMmfOHGJjYxk5cqRzX7t27YiPj3feqQPmOJTly5fTv3//Gs8VHBxMRERElU1EfFtkaCD+fmZPabbGmYhIHdQ5mDgcDubMmcOECRMICDg5RMVmszFlyhSmT5/OwoUL2bx5MxMnTiQsLIzx48e7tGgR8W5+fjZahJmL92mciYjURZ0Hvy5ZsoSDBw9y++23n/bYI488QnFxMffeey/Z2dn07duXr776ivDwcJcUKyK+o0VYEMcKShVMRKRO6hxMhg0bhmEY1T5ms9mYOnUqU6dObWhdIuLjdGeOiNRHve/KERE5EwUTEakPBRMRcQsFExGpDwUTEXELBRMRqQ8FExFxCwUTEakPBRMRcQsFExGpDwUTEXELBRMRqQ8FExFxC60wLCL1oWAiIm5RGUyyC0trnPtIROSXFExExC1anFjIr9xhkFdSbnE1IuIrFExExC1CAv1pFuQPaJyJiNSegomIuE10cw2AFZG6UTAREbeJDlMwEZG6UTAREbc5ecuw3eJKRMRXKJiIiNu0cAaTMosrERFfoWAiIm4Tox4TEakjBRMRcZvoZsGAekxEpPYUTETEbaKbBQLqMRGR2lMwERG3cfaYFKnHRMRbPPTBDyxYd5DScofVpVRLwURE3EY9JiLeZd2+43y08TB//u8Wr72NX8FERNymssckW2NMRLzCzG92A3Bt77OIjwyxuJrqKZiIiNtUTrBWYC/HXl5hcTUiTdtPh3JYsfNn/P1s3DOog9Xl1EjBRETcJiI0AH8/G6DZX0WsNnOp2Vsy5txEkqLDLK6mZgomIuI2NpvNucqwgomIdXZk5PPV1qPYbHDvEO/tLQEFExFxs5OTrCmYiFjllWVmb8mI7vF0jA23uJozUzAREbeKVjARsdT+Y4V8+uMRAO4d3NHian6dgomIuJWCiYi1Zi3bg8OAoV1i6d460upyfpWCiYi4VWUwyVYwEfG4wznFfLTpEACTh3h/bwkomIiIm1WuMJylYCLicbOX76GswuDC9jH0Sm5hdTm1omAiIm5VOfg1u0jBRMSTfs63s2B9GgD3D/WN3hJQMBERN3P2mBQomIh40r9W7sVe7uC8NlFc2CHG6nJqTcFERNxKtwuLeF5OUSnzVh8A4L4hHbHZbBZXVHt1DiaHDx/m5ptvJiYmhrCwMHr27MmGDRucj0+cOBGbzVZl69evn0uLFhHfUTnBmi7liHjOnO/2U1haQdeECIZ2ibW6nDoJqMvB2dnZDBgwgCFDhvDll18SGxvLnj17iIqKqnLc8OHDmTNnjvPnoKAglxQrIr4npnllMCnD4TDw8/Od39xEfFGBvZy3Vu0HfK+3BOoYTJ599lmSkpKqhI62bduedlxwcDDx8fENLk5EfF9lj0mFwyCvpIyoMP2iIuJO89YcILe4jPatmjG8u+99FtfpUs4nn3xC7969ue6664iNjeW8887j9ddfP+24ZcuWERsbS0pKCnfeeSeZmZk1ntNut5OXl1dlE5HGIyjAj/Bg83cg3TIs4l4lZRX869u9gDnLq78P9lDWKZjs3buXWbNm0alTJxYtWsSkSZN44IEHePvtt53HjBgxgvnz57N06VKef/551q9fz9ChQ7Hb7dWec8aMGURGRjq3pKSkhrVIRLxOdHNNsibiCQvWHeRYQSlntQhlTM9Eq8upF5thGEZtDw4KCqJ3796sWrXKue+BBx5g/fr1rF69utrnpKenk5yczIIFCxg7duxpj9vt9iqhJS8vj6SkJHJzc4mIiKhLW0TES1318nf8kJbDa7f04vJuvte1LOILSssdDPrrN6TnlvDUVd25uV+yR18/Ly+PyMjIBn9+16nHJCEhgbPPPrvKvq5du3Lw4MEzPic5OZldu3ZV+3hwcDARERFVNhFpXGI0Lb2I23208RDpuSXEhgdzba+zrC6n3uoUTAYMGMCOHTuq7Nu5cyfJyTWnsqysLNLS0khISKhfhSLi8zQtvYh7lVc4mLV8DwB3XdyekEB/iyuqvzoFk9/+9resWbOG6dOns3v3bt59911mz57N5MmTASgoKODhhx9m9erV7N+/n2XLljF69GhatmzJ1Vdf7ZYGiIj30yRrIu71eWo6B7KKiG4WxPi+bawup0HqFEz69OnDwoULee+99+jevTtPPvkkL730EjfddBMA/v7+pKamMmbMGFJSUpgwYQIpKSmsXr2a8PBwtzRARLxfC13KEXEbh8Ng5tLdANw+oC1hQXWaCcTr1Ln6UaNGMWrUqGofCw0NZdGiRQ0uSkQal2hdyhFxm6+2HmVXZgHhIQHc2r+t1eU0mNbKERG30wrDIu5hGAYvf2P2lky4sC0RIYEWV9RwCiYi4nZaYVjEPZbv/JnUw7mEBvpz+8B2VpfjEgomIuJ26jERcY/K3pKb+rZxXjL1dQomIuJ2lT0mRaUVlJRVWFyNSOOwdm8W6/dnE+Tvx50Xt7e6HJdRMBERtwsPDiDQ31yzQ7cMi7jGzBO9Jdf1Pou4iBCLq3EdBRMRcTubzeZcZVjBRKThfkzL4dtdx/D3szFpUAery3EpBRMR8QjdMiziOpW9JVf1bE1SdJjF1biWgomIeES0JlkTcYntGXks3noUmw3uHdK4ektAwUREPEQ9JiKu8fI35po4V/RIoEOr5hZX43oKJiLiEVphWKTh9h0r5POfjgAweXBHi6txDwUTEfEIrTAs0nCzlu3GYcAlXWI5OzHC6nLcQsFERDxCPSYiDXMou4iPNh4GYPLQxtlbAgomIuIhlT0mul1YpH5mr9hLucNgQMcYzm/Twupy3EbBREQ8onLw63FNSy9SZ5n5JSxYnwbA5CGNt7cEFExExEOi1WMiUm//+nYfpeUOzm8TxYXtY6wux60UTETEI6JPWcivwmFYXI2I78guLGXemgMA3D+0EzabzeKK3CvA6gJEpGmonJLeMCC3uKzRrIQqjUOBvZwie7nVZVTrze/2U1RaQbfECAZ3bmV1OW6nYCIiHhHo70dESAB5JeUcL7QrmIjXWLM3i5v/tZZyL+/JmzykY6PvLQEFExHxoJjmwSeCSZnVpYg4vbh4J+UOA5sNvPVjf0DHlgzvFm91GR6hYCIiHtMiLJB9wPFCu9WliACw6WA2a/cdJ8DPxopHhpAYFWp1SU2eBr+KiMdENwsGUI+JeI1Xl5vrzlx1XmuFEi+hYCIiHhPdLBBQj4l4h92ZBXy19SgAkwa1t7gaqaRgIiIeox4T8SazV+zBMODSrnF0jA23uhw5QcFERDxGPSbiLTJyS1i4yVx35p7BHSyuRk6lYCIiHlPZY6IVhsVqb6zcS1mFwQVto+mV3HjXnfFFCiYi4jGVPSbZWi9HLJRbVMa7aw8CMGmwxpZ4GwUTEfEY5xiTAgUTsc68tQcoLK2gc1w4QzrHWl2O/IKCiYh4TIxWGBaLlZRV8ObKfYDZW9IUZlL1NQomIuIxLU4Ek5IyB0Wl3rkuiTRu/95wiKzCUlpHhTLqnESry5FqKJiIiMc0C/InKMD8b+e4BsCKh5VXOHh9xV4A7ryoHYH++gj0RnX+Wzl8+DA333wzMTExhIWF0bNnTzZs2OB83DAMpk6dSmJiIqGhoQwePJgtW7a4tGgR8U02m43oE6sMK5iIp325OYODx4toERbI9X2SrC5HalCnYJKdnc2AAQMIDAzkyy+/ZOvWrTz//PNERUU5j3nuued44YUXmDlzJuvXryc+Pp7LLruM/Px8V9cuIj6oclVhBRPxJMMwmLXMnH5+Qv+2hAVpqThvVae/mWeffZakpCTmzJnj3Ne2bVvn94Zh8NJLL/H4448zduxYAObOnUtcXBzvvvsud999t2uqFhGfpWAiVvh21zG2pucRGujPhAvbWl2OnEGdekw++eQTevfuzXXXXUdsbCznnXcer7/+uvPxffv2kZGRwbBhw5z7goODGTRoEKtWrXJd1SLisxRMxAqVi/XdeEGScxC2eKc6BZO9e/cya9YsOnXqxKJFi5g0aRIPPPAAb7/9NgAZGRkAxMXFVXleXFyc87Ffstvt5OXlVdlEpPFSMBFP+zEth1V7sgjws3HHRZpQzdvV6VKOw+Ggd+/eTJ8+HYDzzjuPLVu2MGvWLG699Vbncb+8L9wwjBrvFZ8xYwbTpk2ra90i4qMUTMTTKntLruyZSOuoUIurkV9Tpx6ThIQEzj777Cr7unbtysGD5tS+8fHxAKf1jmRmZp7Wi1Lp0UcfJTc317mlpaXVpSQR8TEKJuJJe38u4H9bzM+kSYO0WJ8vqFMwGTBgADt27Kiyb+fOnSQnJwPQrl074uPjWbx4sfPx0tJSli9fTv/+/as9Z3BwMBEREVU2EWm8FEzEk2av2IthwCVdYkmJC7e6HKmFOl3K+e1vf0v//v2ZPn06119/PevWrWP27NnMnj0bMC/hTJkyhenTp9OpUyc6derE9OnTCQsLY/z48W5pgIj4lmhNSy8ekplXwkcbDwNwz2D1lviKOgWTPn36sHDhQh599FH+8pe/0K5dO1566SVuuukm5zGPPPIIxcXF3HvvvWRnZ9O3b1+++uorwsOVVEVEPSbiOW98t4/SCge9k1vQu2201eVILdkMwzCsLuJUeXl5REZGkpubq8s6Io3QsQI7vZ9ags0Gu54aQYCmBRc3yC0uY8AzSymwl/OvW3tz6dnVj3MU13HV57f+RxARj4oKDQTAMCCnuMziaqSxmr/2AAX2clLimjO0S6zV5UgdKJiIiEcF+PsRFWaGE13OEXcoKavgzZX7Abj74g74+VU/XYV4JwUTEfE4LeQn7vThxkMcK7CTGBnClT0TrS5H6kjBREQ8TgNgxV0qHAavr9gLwB0XtSdQY5h8jv7GRMTjFEzEXf63OYP9WUVEhQVy4wVJVpcj9aBgIiIep2Ai7mAYBrOW7wbg1gvbEhZUpxkxxEsomIiIxymYiDt8tzuLzYfzCAn0Y2L/tlaXI/WkYCIiHqdgIu5QuVjfjX3aOP+Nie9RMBERj6v80MjWtPTiIqmHclm5+xj+fjZ+M7Cd1eVIAyiYiIjHtTgRTLIKFEzENSp7S648N5Gk6DCLq5GGUDAREY+L0aUccaH9xwr5cnM6AHcPam9xNdJQCiYi4nEtwk6uMOxly3WJD5r97V4cBgzp3Iou8VpjzdcpmIiIx8U0N4NJabmDwtIKi6sRX5aZX8J/NhwC4J7BHS2uRlxBwUREPC4sKICQQPO/n2xdzpEGmPPdfkrLHZzfJoo+bVtYXY64gIKJiFiicr2cLAUTqae8kjLmrT4AwKRBHbDZtFhfY6BgIiKWiD5xOUc9JlJf7649SL69nI6xzbm0a5zV5YiLKJiIiCVaqMdEGsBeXsGbK/cBcPfF7fHzU29JY6FgIiKWqLxlWD0mUh8LNx4mM99OQmQIY3q2troccSEFExGxhHOSNQUTqaPyCodzQrXfDGxHUIA+yhoT/W2KiCVOTrJmt7gS8TWfp6azP6uIFmGBjLugjdXliIspmIiIJVo4g0mZxZWIL3E4DF75xuwtuX1AO5oFB1hckbiagomIWEI9JlIfi7cdZcfRfMKDA7i1f1uryxE3UDAREUtENwsGILtIPSZSO4Zh8PI3uwG45cJkIkMDLa5I3EHBREQsEd3M/FDJKlCPidTOt7uO8dOhXEIC/fjNwHZWlyNuomAiIpao7DHJKymnrMJhcTXiC2YuNXtLxl+QTEzzYIurEXdRMBERS0SGBlI5g3h2kW4ZljNbt+846/YfJ8jfj7subm91OeJGCiYiYgl/P5tz9tds3Zkjv2LmibEl1/Y+i/jIEIurEXdSMBERy7QIOzHORHfmyBn8mJbDip0/4+9n455BHawuR9xMwURELBNzYpzJcc3+KmdQeSfOmHMTSYoOs7gacTcFExGxTIsTd+ZovRypyY6MfL7aehSbDe4dot6SpkDBREQsU3lnjtbLkZpU9paM6B5Px9hwi6sRT6hTMJk6dSo2m63KFh8f73x84sSJpz3er18/lxctIo2DVhiWM9l/rJDPfjoCwL2DO1pcjXhKnRcZ6NatG0uWLHH+7O/vX+Xx4cOHM2fOHOfPQUFBDShPRBozrTAsZzJr2R4cBgztEkv31pFWlyMeUudgEhAQUKWX5JeCg4PP+LiISCVnj4nmMZFfOJxTzIcbDwEweYh6S5qSOo8x2bVrF4mJibRr144bb7yRvXv3Vnl82bJlxMbGkpKSwp133klmZuYZz2e328nLy6uyiUjT4OwxKVAwkapmL99DucPgwvYx9EpuYXU54kF1CiZ9+/bl7bffZtGiRbz++utkZGTQv39/srKyABgxYgTz589n6dKlPP/886xfv56hQ4dit9c8R8GMGTOIjIx0bklJSQ1rkYj4DPWYSHV+zrezYH0aAPcNVW9JU2MzDMOo75MLCwvp0KEDjzzyCA899NBpj6enp5OcnMyCBQsYO3Zsteew2+1VgkteXh5JSUnk5uYSERFR39JExAcczilmwDNLCfS3sfOpEdgq56iXJm3Gl9t4bflezmsTxUf39Ne/Cx+Rl5dHZGRkgz+/6zzG5FTNmjWjR48e7Nq1q9rHExISSE5OrvFxMMekBAdrMSaRpij6xJT0ZRUG+fZyIkK0jH1Tl1NUyrzVBwC4b0hHhZImqEHzmNjtdrZt20ZCQkK1j2dlZZGWllbj4yLStIUG+RMaaN7Zp1uGBWDOd/spLK2ga0IEQ7vEWl2OWKBOweThhx9m+fLl7Nu3j7Vr13LttdeSl5fHhAkTKCgo4OGHH2b16tXs37+fZcuWMXr0aFq2bMnVV1/trvpFxMdF65ZhOSG/pIy3Vu0H1FvSlNXpUs6hQ4cYN24cx44do1WrVvTr1481a9aQnJxMcXExqampvP322+Tk5JCQkMCQIUN4//33CQ/XbH0iUr2Y5kEczilWj4kwb81BcovLaN+qGcO7a9qJpqpOwWTBggU1PhYaGsqiRYsaXJCINC0twtRjIlBSVsEbK83pJ+4d3BF/P/WWNFVaK0dELKVp6QVgwbqDHCso5awWoYzpmWh1OWIhBRMRsVTlJGvHFUyarNJyB6+tMHtLJg3qQKC/PpqaMv3ti4ilohVMmryPNh4iPbeE2PBgru11ltXliMUUTETEUgomTVt5hYNZy/cAcNfF7QkJ9P+VZ0hjp2AiIpbS7cJN22c/pXMgq4gWYYGM79vG6nLECyiYiIilorVeTpPlcBi8/M1uAH4zsB1hQQ2ajFwaCQUTEbGU81KOVhhucr7aepRdmQWEBwdwy4VtrS5HvISCiYhYqvJ24Xx7OaXlDourEU8xDIOZ35jrqE3o35bIUK2TJCYFExGxVERIoHMyLV3OaTqW7/yZzYfzCA305/aB7awuR7yIgomIWMrPz0aLMPO3Zd2Z03RUji0Z37eN83KeCCiYiIgXqJyWXsGkaVi7N4v1+7MJ8vfjrovbW12OeBkFExGxnOYyaVpmnugtua73WcRFhFhcjXgbBRMRsZyCSdPxY1oO3+46hr+fjUmDOlhdjnghBRMRsZwmWWs6KntLrurZmqToMIurEW+kYCIilovWCsNNwvaMPBZvPYrNBvcOUW+JVE/BREQsp0s5TcPL35hr4lzRPYEOrZpbXI14KwUTEbGcgknjt+9YIZ//dARQb4mcmYKJiFhOwaTxe+Wb3TgMGNollm6JkVaXI15MwURELOcMJpr5tVE6lF3Ewk2HAbhvaEeLqxFvp2AiIpY7dfCrYRgWVyOuNnvFXsodBv07xHB+mxZWlyNeTsFERCxXOfNrucMgr6Tc4mrElTLzSliwPg1Qb4nUjoKJiFguJNCfZkH+gMaZNDb/WrmP0nIH57eJ4sL2MVaXIz5AwUREvEJ088oBsHaLKxFXyS4sZd6aA4DZW2Kz2SyuSHyBgomIeIVo50J+ZRZXIq4y57t9FJVWcHZCBEM6x1pdjvgIBRMR8QonbxlWj0ljkF9Sxlur9gPqLZG6UTAREa8Q3SwYUI9JY/HOmgPklZTToVUzhneLt7oc8SEKJiLiFaKbBQLqMWkMiksreOPbfQBMHtIRPz/1lkjtKZiIiFdQj0nj8d66g2QVlpIUHcqV5yZaXY74GAUTEfEK6jFpHOzlFcxesReASYM6EOCvjxmpG/2LERGv4OwxKVKPiS/7cMNhMvJKiIsI5tpeZ1ldjvigOgWTqVOnYrPZqmzx8ScHNRmGwdSpU0lMTCQ0NJTBgwezZcsWlxctIo2Pekx8X3mFg1eX7wHgros7EBzgb3FF4ovq3GPSrVs30tPTnVtqaqrzseeee44XXniBmTNnsn79euLj47nsssvIz893adEi0vg4e0wKNPOrr/r0pyMcPF5EdLMgxl2QZHU54qPqHEwCAgKIj493bq1atQLM3pKXXnqJxx9/nLFjx9K9e3fmzp1LUVER7777rssLF5HGpXKCtcLSCkrKKiyuRurK4TB4+Ruzt+Q3A9sRFhRgcUXiq+ocTHbt2kViYiLt2rXjxhtvZO9ec5DTvn37yMjIYNiwYc5jg4ODGTRoEKtWrarxfHa7nby8vCqbiDQ9EaEBBJy4rTS7SL0mvmbRlgx2ZxYQHhLALRcmW12O+LA6BZO+ffvy9ttvs2jRIl5//XUyMjLo378/WVlZZGRkABAXF1flOXFxcc7HqjNjxgwiIyOdW1KSuv9EmiKbzUYL5+yvCia+xDAMZn6zG4CJ/dsSERJocUXiy+oUTEaMGME111xDjx49uPTSS/n8888BmDt3rvOYX047bBjGGacifvTRR8nNzXVuaWlpdSlJRBqRk+vlKJj4kmU7f2bLkTxCA/25bUA7q8sRH9eg24WbNWtGjx492LVrl/PunF/2jmRmZp7Wi3Kq4OBgIiIiqmwi0jRFq8fE5xiGwcylZm/Jzf3aOP8OReqrQcHEbrezbds2EhISaNeuHfHx8SxevNj5eGlpKcuXL6d///4NLlREGj8FE9+zZu9xNhzIJijAjzsvam91OdII1GnY9MMPP8zo0aNp06YNmZmZPPXUU+Tl5TFhwgRsNhtTpkxh+vTpdOrUiU6dOjF9+nTCwsIYP368u+oXkUakMphkK5j4jJdPjC25vvdZxEaEWFyNNAZ1CiaHDh1i3LhxHDt2jFatWtGvXz/WrFlDcrI5AvuRRx6huLiYe++9l+zsbPr27ctXX31FeHi4W4oXkcalcvBrloKJT9h0MJuVu48R4Gfj7os7WF2ONBJ1CiYLFiw44+M2m42pU6cyderUhtQkIk1UjC7l+JTK3pKrzmtNUnSYxdVIY6G1ckTEa+h2Yd+x9UgeS7ZlYrPBPYPVWyKuo2AiIl5DPSa+4+VlZm/JyB4JdGjV3OJqpDFRMBERr+Ec/KqZX73anp8L+CI1HYDJQzpaXI00NgomIuI1TgaTMhwOw+JqpCazlu3BMODSrrF0TdDcU+JaCiYi4jVanJj5tcJhkFdSZnE1Up2040Us3HQYUG+JuIeCiYh4jaAAP8KDzZsFdcuwd3ptxR4qHAYDO7bkvDYtrC5HGiEFExHxKtHNNcmatzqaV8IH3x8C1Fsi7qNgIiJepfJyjnpMvM/rK/ZSWu6gd3IL+rWPtrocaaQUTETEq+iWYe90vLCU+WsPAjB5aMczrhov0hAKJiLiVTTJmnea890+issq6N46gsEprawuRxoxBRMR8SrqMfE+eSVlvLVqPwD3DVFvibiXgomIeBWtMOx93ll9gPyScjrFNmfY2fFWlyONnIKJiHgVrTDsXYpKy3lj5T4A7h3SAT8/9ZaIeymYiIhXidG09F7l3bUHOV5YSpvoMEafk2h1OdIEKJiIiFdx9pgUKJhYzV5ewevf7gXMFYQD/PWRIe6nf2Ui4lXUY+I9/rPhEEfz7MRHhDD2/NZWlyNNhIKJiHiVyh6TotIKSsoqLK6m6SqrcDBr2R4A7rq4PcEB/hZXJE1FgNUFiIicKjw4gEB/G2UVBre+uY4gL7t8YLPB2PNbc/V5Z1ldilt98sMRDmUXE9MsiHEXtLG6HGlCFExExKvYbDbat2zOjqP5rNt33OpyqrV233F6tYmmTUyY1aW4RXFpBc9/tQOA31zUjtAg9ZaI5yiYiIjXmXNbH68NJfPXHmD9/mye/mIrr93S2+py3OLV5Xs4kltCYmQIt/VvZ3U50sQomIiI10mMCuWq87xzsOXZiRGM+Pu3LNpylO92H2NAx5ZWl+RSh7KLeHW5Obbk8ZFnq7dEPM67Lt6KiHi5lLhwbumXDMC0T7dQVuGwuCLXmvHFduzlDvq2i+aKHprlVTxPwUREpI5+e2kKLcIC2Xm0gHlrDlhdjsus3pPF56np+Nlg6pXdtCaOWELBRESkjiLDAvm/YZ0BeHHxTrIK7BZX1HDlFQ6mfboFgPF929A1IcLiiqSpUjAREamHcReYH955JeU8v3in1eU02HvrDrI9I5/I0ED+77LOVpcjTZiCiYhIPfj72Zg6+mzA/FDfciTX4orqL6eo1BmuHrosxTnJnYgVFExEROqpb/sYRp2TgGHAtE+2YhiG1SXVywuLd5JTVEbnuHBu6qvJ1MRaCiYiIg3w2BVdCQn0Y93+43z2U7rV5dTZ9ow85wDeJ648Wwv1ieX0L1BEpAESo0K5Z1BHAKZ/sY2i0nKLK6o9wzCY9slWHAaM6B5P/w6Na04W8U0KJiIiDXT3oPa0jgolPbeEV08sfOcL/rc5g9V7swgO8OOxK7paXY4IoGAiItJgIYH+PD7S/GB/bcVe0o4XWVzRryspq+Cpz7cBcPfF7UmKbpzr/ojvaVAwmTFjBjabjSlTpjj3TZw4EZvNVmXr169fQ+sUEfFqI7rHc2H7GOzlDqZ/sc3qcn7Va8v3cjinmITIECYN7mB1OSJO9Q4m69evZ/bs2ZxzzjmnPTZ8+HDS09Od2xdffNGgIkVEvJ3NZuOJK8/GzwZfbs5g1Z5jVpdUo8M5xcxavhswB++GBWnZNPEe9QomBQUF3HTTTbz++uu0aNHitMeDg4OJj493btHR0Q0uVETE23WJj+DmynV0PtlKuZeuozPji22UlDm4oF00o85JsLockSrqFUwmT57MyJEjufTSS6t9fNmyZcTGxpKSksKdd95JZmZmjeey2+3k5eVV2UREfNVDl6UQFRbIjqP5zF970OpyTrN2bxaf/WSuh/PE6LO1Ho54nToHkwULFrBx40ZmzJhR7eMjRoxg/vz5LF26lOeff57169czdOhQ7Pbq15KYMWMGkZGRzi0pKamuJYmIeI2osCD+77IUwJy4LLuw1OKKTqpwGEz9dCsAN17Qhm6JkRZXJHK6OgWTtLQ0HnzwQebNm0dISEi1x9xwww2MHDmS7t27M3r0aL788kt27tzJ559/Xu3xjz76KLm5uc4tLS2t7q0QEfEi4y5oQ5f4cHKLy3h+8Q6ry3FasP4g29LziAgJ4OFhWg9HvFOdgsmGDRvIzMykV69eBAQEEBAQwPLly/nHP/5BQEAAFRUVpz0nISGB5ORkdu3aVe05g4ODiYiIqLKJiPiyAH8/nhjdDYB31x5k6xHrL1HnFpXxt0VmSPrtZSlEaz0c8VJ1CiaXXHIJqamp/PDDD86td+/e3HTTTfzwww/4+/uf9pysrCzS0tJISNAAKxFpOi7sEMPIHgk4DJj26RbL19F5cclOsovKSIlr7hygK+KN6hRMwsPD6d69e5WtWbNmxMTE0L17dwoKCnj44YdZvXo1+/fvZ9myZYwePZqWLVty9dVXu6sNIiJe6dEruhAc4Mfafcf5IjXDsjp2ZOTzTuV6OKO7Eaj1cMSLufRfp7+/P6mpqYwZM4aUlBQmTJhASkoKq1evJjw83JUvJSLi9c5qEcakQebkZU9/vpXi0tMvd7ubYRj85bMtVDgMLu8Wx4COWg9HvFuDZ9VZtmyZ8/vQ0FAWLVrU0FOKiDQakwZ14N/fp3Ekt4RXl+/htyfu2PGURVuO8t3uLIIC/PjjyLM9+toi9aH+PBERNwoN8uexE+vovLp8D4eyPbeOTklZBU9/Yd4efNdFWg9HfIOCiYiIm43skUDfdtHYyx3M+GK7x173X9/uJe14MfERIdw7ROvhiG9QMBERcTObzcbUK7vhZ4PPU9NZvSfL7a+ZnlvMy9/sAcxBuFoPR3yFgomIiAd0TYhgfN82gHn7sLvX0ZnxxXaKyyro07YFV56b6NbXEnElBRMREQ/5v8s6ExkayPaMfN5b5751dNbvP84nPx7BZjNvD9Z6OOJLFExERDykRbMgHjpxV87zi3eSU+T6dXQqHAZTP9kCwI19kujeWuvhiG9RMBER8aCb+rahc1w4OUVlvLB4p8vP/8H3aWw5kke41sMRH6VgIiLiQeY6OuZ8IvPWHGB7huvW0cktLuOvlevhXJpCTPNgl51bxFM0TFtExMP6d2zJiO7xfLk5gykLfuDCDjEuOe/Oo/kcLyylU2xzbrlQ6+GIb1IwERGxwGNXdGXp9ky2Z+SzPSPfpef+8+iztR6O+CwFExERCyRFhzHntj58t/uYS8+bEhfORZ1aufScIp6kYCIiYpH+HVrSv4MW1RM5lfr6RERExGsomIiIiIjXUDARERERr6FgIiIiIl5DwURERES8hoKJiIiIeA0FExEREfEaCiYiIiLiNRRMRERExGsomIiIiIjXUDARERERr6FgIiIiIl5DwURERES8htetLmwYBgB5eXkWVyIiIiK1Vfm5Xfk5Xl9eF0zy8/MBSEpKsrgSERERqav8/HwiIyPr/Xyb0dBo42IOh4MjR44QHh6OzWYjLy+PpKQk0tLSiIiIsLo8t1E7G6em1N6m0tam0k5QWxszd7TXMAzy8/NJTEzEz6/+I0W8rsfEz8+Ps84667T9ERERTeIfi9rZODWl9jaVtjaVdoLa2pi5ur0N6SmppMGvIiIi4jUUTERERMRreH0wCQ4O5oknniA4ONjqUtxK7WycmlJ7m0pbm0o7QW1tzLy5vV43+FVERESaLq/vMREREZGmQ8FEREREvIaCiYiIiHgNBRMRERHxGvUKJjNmzKBPnz6Eh4cTGxvLVVddxY4dO6ocYxgGU6dOJTExkdDQUAYPHsyWLVuqHDN79mwGDx5MREQENpuNnJyc015r48aNXHbZZURFRRETE8Ndd91FQUHBr9aYmprKoEGDCA0NpXXr1vzlL3+pMn9/eno648ePp3Pnzvj5+TFlypRG2c5TfffddwQEBNCzZ89G186JEydis9lO27p16+ZTbS0pKWHixIn06NGDgIAArrrqqmqPW758Ob169SIkJIT27dvz6quvVnucK9p7/Phx7r//fjp37kxYWBht2rThgQceIDc3t8p5srOzueWWW4iMjCQyMpJbbrml2j+XX/KW96rV7TxVTe/VxtJWT75f3dlWX36/Pv300/Tv35+wsDCioqLO2M5TueL9+quMerj88suNOXPmGJs3bzZ++OEHY+TIkUabNm2MgoIC5zHPPPOMER4ebnz44YdGamqqccMNNxgJCQlGXl6e85gXX3zRmDFjhjFjxgwDMLKzs6u8zuHDh40WLVoYkyZNMrZv326sW7fO6N+/v3HNNdecsb7c3FwjLi7OuPHGG43U1FTjww8/NMLDw42//e1vzmP27dtnPPDAA8bcuXONnj17Gg8++GCjbGelnJwco3379sawYcOMc889t9G1Mycnx0hPT3duaWlpRnR0tPHEE0/4VFsLCgqMSZMmGbNnzzYuv/xyY8yYMacds3fvXiMsLMx48MEHja1btxqvv/66ERgYaPznP/857VhXtDc1NdUYO3as8cknnxi7d+82vv76a6NTp06ntWX48OFG9+7djVWrVhmrVq0yunfvbowaNeqM7fWm96rV7ax0pvdqY2mrJ9+v7myrL79f//znPxsvvPCC8dBDDxmRkZFnbGclV71ff029gskvZWZmGoCxfPlywzAMw+FwGPHx8cYzzzzjPKakpMSIjIw0Xn311dOe/80331T7n/trr71mxMbGGhUVFc59mzZtMgBj165dNdbzyiuvGJGRkUZJSYlz34wZM4zExETD4XCcdvygQYNq9Yfny+284YYbjD/+8Y/GE088Ue1/do2lnZUWLlxo2Gw2Y//+/T7V1lNNmDCh2v/oHnnkEaNLly5V9t19991Gv379fvWcDW1vpQ8++MAICgoyysrKDMMwjK1btxqAsWbNGucxq1evNgBj+/btNZ7HW9+rVrazLu9VX29rJU+9X13d1lP50vv1VHPmzKl1MHHX+/WXXDLGpLKLKDo6GoB9+/aRkZHBsGHDnMcEBwczaNAgVq1aVevz2u12goKCqiwGFBoaCsDKlStrfN7q1asZNGhQlYljLr/8co4cOcL+/ftr/fq/5KvtnDNnDnv27OGJJ56oVT2+2s5TvfHGG1x66aUkJyefsSZva2ttrF69ukp9YP55fP/995SVlZ3xua5qb25uLhEREQQEBDhrioyMpG/fvs5j+vXrR2Rk5BnP4+3vVU+3s67vVV9u66k8/X51VVtrwxvfr/XlrvfrLzU4mBiGwUMPPcTAgQPp3r07ABkZGQDExcVVOTYuLs75WG0MHTqUjIwM/vrXv1JaWkp2djaPPfYYYF7HqklGRka1r31qbXXlq+3ctWsXf/jDH5g/f36t/lH6ajtPlZ6ezpdffskdd9xxxnq8sa21UdOfR3l5OceOHavxea5qb1ZWFk8++SR33313lZpiY2NPOzY2NvaMf27e/F71dDvr+l4F323rqTz9fnVlW2vDG9+v9eWO92t1GhxM7rvvPn766Sfee++90x6z2WxVfjYM47R9Z9KtWzfmzp3L888/T1hYGPHx8bRv3564uDj8/f2dxzRv3pzmzZszYsSIM752dftryxfbWVFRwfjx45k2bRopKSmNtp2/9NZbbxEVFVXjQLRK3trW2qjPv29XtDcvL4+RI0dy9tlnn/ZbfXXHn3oeX3qverqd9Xmvgm+29Zc8+X51R1trwxvfr7/GU+/X6jSoX+f+++/nk08+YcWKFZx11lnO/fHx8YCZoBISEpz7MzMzT0tbv2b8+PGMHz+eo0eP0qxZM2w2Gy+88ALt2rUD4IsvvnB2h1V2lcfHx5+W3jIzM4HTk2Zt+Go78/Pz+f7779m0aRP33XcfAA6HA8MwCAgI4KuvvmLo0KE+385TGYbBm2++yS233EJQUFCNdXhrW2ujpj+PgIAAYmJiqn2OK9qbn5/P8OHDad68OQsXLiQwMLDKeY4ePXra6/7888/O8/jKe9WKdtb1verLbT2VJ9+v7mhrbXjj+7U2PPF+rVGdR6UY5gCcyZMnG4mJicbOnTurfTw+Pt549tlnnfvsdnudBxBW54033jDCwsLOeOwrr7xiREVFGXa73bnvmWeeqfMAHV9vZ0VFhZGamlplu+eee4zOnTsbqampzpHevt7O6l47NTW12nN5e1tPdabBdF27dq2yb9KkSdUOpnNVe3Nzc41+/foZgwYNMgoLC087T+XgwbVr1zr3rVmzplYDJb3pvWpVO2v7Xm0MbT2Vp96v7mrrqXzp/Xqqug5+dcX79dfUK5jcc889RmRkpLFs2bIqt3wVFRVVKTYyMtL46KOPjNTUVGPcuHGn3XKZnp5ubNq0yXj99dcNwFixYoWxadMmIysry3nMP//5T2PDhg3Gjh07jJkzZxqhoaHG3//+9zPWl5OTY8TFxRnjxo0zUlNTjY8++siIiIg47da8TZs2GZs2bTJ69epljB8/3ti0aZOxZcuWRtfOU1U30r8xtfPmm282+vbtW+O5vL2thmEYW7ZsMTZt2mSMHj3aGDx4sPPfaaXK2w9/+9vfGlu3bjXeeOONGm8/dEV78/LyjL59+xo9evQwdu/eXeU85eXlzvMMHz7cOOecc4zVq1cbq1evNnr06PGrt1t603vVG9p5qpruymlMbfXE+9WdbTUM332/HjhwwNi0aZMxbdo0o3nz5s668/Pza2yrq96vv6ZewQSodpszZ47zGIfDYTzxxBNGfHy8ERwcbFx88cWnpeInnnjiV89zyy23GNHR0UZQUJBxzjnnGG+//Xatavzpp5+Miy66yAgODjbi4+ONqVOnnpboqnvt5OTkRtfOX9byy//sGks7c3JyjNDQUGP27Nk1nscX2pqcnFztuU+1bNky47zzzjOCgoKMtm3bGrNmzXJbeyt/q61u27dvn/O4rKws46abbjLCw8ON8PBw46abbqpV75C3vFe9oZ2nqimYNJa2eur96u62+ur7dcKECdUe880335yxva54v/4a24mTiIiIiFhOa+WIiIiI11AwEREREa+hYCIiIiJeQ8FEREREvIaCiYiIiHgNBRMRERHxGgomIiIi4jUUTERERMRrKJiIiIiI11AwEREREa+hYCIiIiJeQ8FEREREvMb/A1MoQS8Ri3VwAAAAAElFTkSuQmCC", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(mf.y_test)\n", + "plt.plot(mf.models['xgboost']['test'])" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(test)\n", + "plt.plot(mf.models['xgboost']['forecast'])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "\n", + "# What is the forecast accuracy?" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.23537933276005385" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mf.models['xgboost']['mape']" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "\n", + "# Can MAPE handle zeros?\n", + "\n", + "- MAPE cannot handle inaccurate zero, zero, or very small value on true value will cause huge error size\n", + "- MAPE is not suitable for evaluating intermittent data" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "200.0" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from sktime.performance_metrics.forecasting import mean_absolute_percentage_error\n", + "\n", + "mean_absolute_percentage_error([1,0,1,1,0.001], [1,0,1,0,1])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "base", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.5" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/E04-forecaster.ipynb b/notebooks/E04-forecaster.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..9d9a382900f8eed72453a86f3704bd30cb74946e --- /dev/null +++ b/notebooks/E04-forecaster.ipynb @@ -0,0 +1,1509 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "# [Load packages]\n", + "\n", + "# To call functions outside of this folder\n", + "import sys \n", + "sys.path.insert(0, '..')\n", + "\n", + "import pandas as pd\n", + "from src.forecaster import Forecaster\n", + "from src.analyser import Analyser\n", + "import logging\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Load data and fit forecaster" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Filtered out only y and gas_regm columns\n" + ] + }, + { + "data": { + "text/html": [ + "
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ygas_regm
datetime
2000-01-3141.01.289
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" + ], + "text/plain": [ + " y gas_regm\n", + "datetime \n", + "2000-01-31 41.0 1.289\n", + "2000-02-29 41.0 1.377\n", + "2000-03-31 45.0 1.516" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# [Load data]\n", + "data = pd.read_csv(\n", + " '../data/multivariate/blow_mold_preprocessed.csv', \n", + " index_col='datetime', \n", + " parse_dates=['datetime'])\n", + "\n", + "print('Filtered out only y and gas_regm columns')\n", + "data = data[['y', 'gas_regm']]\n", + "\n", + "data.head(3)" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[Forecaster - fit] ----- START -----\n", + "[Forecaster - fit] Train test split\n", + "[Forecaster - fit] Test size: 12\n", + "[Forecaster - fit] Sliding window splitter, with window_length 276 and fh 12\n", + "[Forecaster - fit] ----- END -----\n" + ] + } + ], + "source": [ + "# [Init forecaster]\n", + "\n", + "window_length = 12 # Auto correlation, lags\n", + "n_predict = 12 # Forecast horizon\n", + "\n", + "forecaster = Forecaster()\n", + "forecaster.fit(data, n_predict=n_predict, window_length=window_length)" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " y gas_regm\n", + "datetime \n", + "2000-01-31 41.0 1.289\n", + "2000-02-29 41.0 1.377\n", + "2000-03-31 45.0 1.516\n", + "2000-04-30 47.0 1.465\n", + "2000-05-31 47.0 1.487\n", + "... ... ...\n", + "2022-08-31 93.0 3.975\n", + "2022-09-30 90.0 3.700\n", + "2022-10-31 90.0 3.815\n", + "2022-11-30 90.0 3.685\n", + "2022-12-31 90.0 3.210\n", + "\n", + "[276 rows x 2 columns]" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "forecaster.data" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [], + "source": [ + "# [Build exogenous data for testing, with weekday and datetime column]\n", + "\n", + "exog_index = pd.date_range(\"2000-01-31\", \"2023-12-31\", freq='M')\n", + "exog_weekday = exog_index.weekday\n", + "exog = pd.DataFrame({'weekday':exog_weekday}, index=exog_index)" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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288 rows × 1 columns

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" + ], + "text/plain": [ + " weekday\n", + "2000-01-31 0\n", + "2000-02-29 1\n", + "2000-03-31 4\n", + "2000-04-30 6\n", + "2000-05-31 2\n", + "... ...\n", + "2023-08-31 3\n", + "2023-09-30 5\n", + "2023-10-31 1\n", + "2023-11-30 3\n", + "2023-12-31 6\n", + "\n", + "[288 rows x 1 columns]" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "exog" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[Forecaster - fit] ----- START -----\n", + "[Forecaster - fit] - exogenous data provided\n", + "[Forecaster - fit] - merge exogenous data with features\n", + "[Forecaster - fit] Train test split\n", + "[Forecaster - fit] Test size: 12\n", + "[Forecaster - fit] Sliding window splitter, with window_length 276 and fh 12\n", + "[Forecaster - fit] ----- END -----\n" + ] + } + ], + "source": [ + "# [Fit forecaster with new exog column]\n", + "\n", + "forecaster.fit(data, n_predict=n_predict, window_length=window_length, exog=exog)" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [], + "source": [ + "data.merge(exog, left_index=True, right_index=True).reset_index().rename(columns={'index':'datetime'}).to_csv('../data/multivariate/demo_historical.csv', index=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [], + "source": [ + "exog[-12:-8].reset_index().rename(columns={'index':'datetime'}).to_csv('../data/multivariate/demo_future.csv', index=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "DatetimeIndex(['2023-01-31', '2023-02-28', '2023-03-31', '2023-04-30',\n", + " '2023-05-31', '2023-06-30', '2023-07-31', '2023-08-31',\n", + " '2023-09-30', '2023-10-31', '2023-11-30', '2023-12-31'],\n", + " dtype='datetime64[ns]', freq='M')" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "forecaster.fh.to_pandas()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Init model ...\n", + "Init model ...\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/zq/miniconda3/lib/python3.10/site-packages/sktime/forecasting/model_selection/_tune.py:198: UserWarning: in ForecastingRandomizedSearchCV, n_jobs and pre_dispatch parameters are deprecated and will be removed in 0.26.0. Please use n_jobs and pre_dispatch directly in the backend_params argument instead.\n", + " warn(\n", + "/home/zq/miniconda3/lib/python3.10/site-packages/sktime/forecasting/model_selection/_tune.py:198: UserWarning: in ForecastingRandomizedSearchCV, n_jobs and pre_dispatch parameters are deprecated and will be removed in 0.26.0. Please use n_jobs and pre_dispatch directly in the backend_params argument instead.\n", + " warn(\n", + "/home/zq/.local/lib/python3.10/site-packages/sklearn/model_selection/_search.py:305: UserWarning: The total space of parameters 70 is smaller than n_iter=100. Running 70 iterations. For exhaustive searches, use GridSearchCV.\n", + " warnings.warn(\n", + "/home/zq/.local/lib/python3.10/site-packages/sklearn/linear_model/_sag.py:350: ConvergenceWarning: The max_iter was reached which means the coef_ did not converge\n", + " warnings.warn(\n", + "/home/zq/.local/lib/python3.10/site-packages/sklearn/linear_model/_sag.py:350: ConvergenceWarning: The max_iter was reached which means the coef_ did not converge\n", + " warnings.warn(\n", + "/home/zq/.local/lib/python3.10/site-packages/sklearn/linear_model/_sag.py:350: ConvergenceWarning: The max_iter was reached which means the coef_ did not converge\n", + " warnings.warn(\n", + "/home/zq/.local/lib/python3.10/site-packages/sklearn/linear_model/_sag.py:350: ConvergenceWarning: The max_iter was reached which means the coef_ did not converge\n", + " warnings.warn(\n", + "/home/zq/.local/lib/python3.10/site-packages/sklearn/linear_model/_sag.py:350: ConvergenceWarning: The max_iter was reached which means the coef_ did not converge\n", + " warnings.warn(\n", + "/home/zq/.local/lib/python3.10/site-packages/sklearn/linear_model/_sag.py:350: ConvergenceWarning: The max_iter was reached which means the coef_ did not converge\n", + " warnings.warn(\n", + "/home/zq/.local/lib/python3.10/site-packages/sklearn/linear_model/_sag.py:350: ConvergenceWarning: The max_iter was reached which means the coef_ did not converge\n", + " warnings.warn(\n", + "/home/zq/.local/lib/python3.10/site-packages/sklearn/linear_model/_sag.py:350: ConvergenceWarning: The max_iter was reached which means the coef_ did not converge\n", + " warnings.warn(\n", + "/home/zq/.local/lib/python3.10/site-packages/sklearn/linear_model/_sag.py:350: ConvergenceWarning: The max_iter was reached which means the coef_ did not converge\n", + " warnings.warn(\n", + "/home/zq/.local/lib/python3.10/site-packages/sklearn/linear_model/_sag.py:350: ConvergenceWarning: The max_iter was reached which means the coef_ did not converge\n", + " warnings.warn(\n" + ] + }, + { + "data": { + "text/plain": [ + "[{'model': 'xgbreg',\n", + " 'results': {'forecast': datetime\n", + " 2022-09-30 84.053032\n", + " 2022-10-31 68.322166\n", + " 2022-11-30 66.457939\n", + " 2022-12-31 66.370132\n", + " Freq: M, Name: y, dtype: float64,\n", + " 'best_score': 0.02539743402952789,\n", + " 'best_params': {'estimator__subsample': 0.5,\n", + " 'estimator__n_estimators': 500,\n", + " 'estimator__max_depth': 15,\n", + " 'estimator__learning_rate': 0.2,\n", + " 'estimator__colsample_bytree': 0.7999999999999999,\n", + " 'estimator__colsample_bylevel': 0.4}}},\n", + " {'model': 'mlr',\n", + " 'results': {'forecast': datetime\n", + " 2022-09-30 88.663381\n", + " 2022-10-31 84.754162\n", + " 2022-11-30 82.534963\n", + " 2022-12-31 81.363169\n", + " Freq: M, Name: y, dtype: float64,\n", + " 'best_score': 0.12320369211901486,\n", + " 'best_params': {'estimator__solver': 'sparse_cg',\n", + " 'estimator__fit_intercept': False,\n", + " 'estimator__alpha': 10}}}]" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# [Predict without exog golumns]\n", + "\n", + "forecaster.forecast(test=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from sktime.utils.plotting import plot_series\n", + "\n", + "plot_series(\n", + " forecaster.y_train, \n", + " forecaster.y_test, \n", + " forecaster.results[0]['results']['forecast'], \n", + " labels=[\"y_train\", \"y_test\", \"y_pred\"], \n", + " x_label='Date', \n", + " y_label='Count pedestrians');" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from sktime.utils.plotting import plot_series\n", + "\n", + "plot_series(\n", + " forecaster.y_train, \n", + " forecaster.y_test, \n", + " forecaster.results[1]['results']['forecast'], \n", + " labels=[\"y_train\", \"y_test\", \"y_pred\"], \n", + " x_label='Date', \n", + " y_label='Count pedestrians');" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Config XGBoostRegressor model and perform random search CV\n", + "\n", + "[Reference](https://towardsdatascience.com/build-complex-time-series-regression-pipelines-with-sktime-910bc25c96b6)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "# [Build the Linear Regression Model]\n", + "\n", + "from sklearn.linear_model import LinearRegression\n", + "from sktime.forecasting.compose import make_reduction\n", + "from sktime.forecasting.base import ForecastingHorizon\n", + "\n", + "regressor = LinearRegression()\n", + "lr_forecastor = make_reduction(regressor, window_length=window_length, strategy=\"recursive\")\n", + "\n", + "lr_forecastor.fit(forecaster.y_train, forecaster.X_train)\n", + "y_pred = lr_forecastor.predict(forecaster.fh_test, forecaster.X_test)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'y_pred' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[8], line 6\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39msktime\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mutils\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mplotting\u001b[39;00m \u001b[39mimport\u001b[39;00m plot_series\n\u001b[1;32m 4\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39msktime\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mperformance_metrics\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mforecasting\u001b[39;00m \u001b[39mimport\u001b[39;00m mean_absolute_percentage_error\n\u001b[0;32m----> 6\u001b[0m plot_series(forecaster\u001b[39m.\u001b[39my_train[\u001b[39m'\u001b[39m\u001b[39m2018-07-01\u001b[39m\u001b[39m'\u001b[39m:], forecaster\u001b[39m.\u001b[39my_test, y_pred, labels\u001b[39m=\u001b[39m[\u001b[39m\"\u001b[39m\u001b[39my_train\u001b[39m\u001b[39m\"\u001b[39m, \u001b[39m\"\u001b[39m\u001b[39my_test\u001b[39m\u001b[39m\"\u001b[39m, \u001b[39m\"\u001b[39m\u001b[39my_pred\u001b[39m\u001b[39m\"\u001b[39m], x_label\u001b[39m=\u001b[39m\u001b[39m'\u001b[39m\u001b[39mDate\u001b[39m\u001b[39m'\u001b[39m, y_label\u001b[39m=\u001b[39m\u001b[39m'\u001b[39m\u001b[39mCount pedestrians\u001b[39m\u001b[39m'\u001b[39m);\n\u001b[1;32m 8\u001b[0m \u001b[39mprint\u001b[39m(\u001b[39m'\u001b[39m\u001b[39mMAPE: \u001b[39m\u001b[39m%.4f\u001b[39;00m\u001b[39m'\u001b[39m \u001b[39m%\u001b[39m mean_absolute_percentage_error(forecaster\u001b[39m.\u001b[39my_test, y_pred, symmetric\u001b[39m=\u001b[39m\u001b[39mFalse\u001b[39;00m))\n", + "\u001b[0;31mNameError\u001b[0m: name 'y_pred' is not defined" + ] + } + ], + "source": [ + "# [Plot forecasting result, evaluate MAPE]\n", + "\n", + "from sktime.utils.plotting import plot_series\n", + "from sktime.performance_metrics.forecasting import mean_absolute_percentage_error\n", + "\n", + "plot_series(forecaster.y_train['2018-07-01':], forecaster.y_test, y_pred, labels=[\"y_train\", \"y_test\", \"y_pred\"], x_label='Date', y_label='Count pedestrians');\n", + "\n", + "print('MAPE: %.4f' % mean_absolute_percentage_error(forecaster.y_test, y_pred, symmetric=False))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MAPE: 0.2268\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# [Build XGBoost model with grid search for best parameters]\n", + "\n", + "from xgboost import XGBRegressor\n", + "regressor = XGBRegressor(objective='reg:squarederror', random_state=42)\n", + "xgb_forecaster = make_reduction(regressor, window_length=window_length, strategy=\"recursive\")\n", + "\n", + "xgb_forecaster.fit(forecaster.y_train, forecaster.X_train)\n", + "y_pred = xgb_forecaster.predict(forecaster.fh_test, forecaster.X_test)\n", + "\n", + "plot_series(forecaster.y_train['2018-07-01':], forecaster.y_test, y_pred, labels=[\"y_train\", \"y_test\", \"y_pred\"], x_label='Date', y_label='Count pedestrians');\n", + "\n", + "print('MAPE: %.4f' % mean_absolute_percentage_error(forecaster.y_test, y_pred, symmetric=False))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Hyperparameters Tuning" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/zq/miniconda3/lib/python3.10/site-packages/sktime/forecasting/model_selection/_tune.py:198: UserWarning: in ForecastingRandomizedSearchCV, n_jobs and pre_dispatch parameters are deprecated and will be removed in 0.26.0. Please use n_jobs and pre_dispatch directly in the backend_params argument instead.\n", + " warn(\n" + ] + } + ], + "source": [ + "# [Perform grid search]\n", + "from xgboost import XGBRegressor\n", + "from sktime.forecasting.compose import make_reduction\n", + "\n", + "from sktime.forecasting.model_selection import SingleWindowSplitter\n", + "from sktime.forecasting.model_selection import ForecastingRandomizedSearchCV\n", + "import numpy as np\n", + "\n", + "# Create validation set\n", + "validation_size = 12\n", + "cv = SingleWindowSplitter(window_length= 24, fh=len(forecaster.fh))\n", + "\n", + "param_grid = {\n", + " # 'estimator__max_depth': [3, 5, 6, 10, 15, 20],\n", + " # 'estimator__learning_rate': [0.01, 0.1, 0.2, 0.3],\n", + " 'estimator__subsample': np.arange(0.5, 1.0, 0.1),\n", + " 'estimator__colsample_bytree': np.arange(0.4, 1.0, 0.1),\n", + " 'estimator__colsample_bylevel': np.arange(0.4, 1.0, 0.1),\n", + " 'estimator__n_estimators': [100, 500, 1000]\n", + "}\n", + "\n", + "regressor = XGBRegressor(objective='reg:squarederror', random_state=42)\n", + "\n", + "xgb_forecaster = make_reduction(\n", + " regressor, \n", + " window_length=window_length, \n", + " strategy=\"recursive\")\n", + "\n", + "gscv = ForecastingRandomizedSearchCV(\n", + " xgb_forecaster, \n", + " cv=cv, \n", + " param_distributions=param_grid, \n", + " n_iter=100, \n", + " random_state=42,\n", + " error_score=\"raise\")\n", + "\n", + "gscv.fit(y = forecaster.y_train, X=forecaster.X_train)\n", + "\n", + "y_pred = gscv.predict(fh=forecaster.fh_test, X=forecaster.X_test)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "12" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(forecaster.fh_test)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "12" + ] + }, + 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48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58]), array([82])),\n", + " (array([48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59]), array([83])),\n", + " (array([49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60]), array([84])),\n", + " (array([50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61]), array([85])),\n", + " (array([51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62]), array([86])),\n", + " (array([52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63]), array([87])),\n", + " (array([53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64]), array([88])),\n", + " (array([54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65]), array([89])),\n", + " (array([55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66]), array([90])),\n", + " (array([56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67]), array([91])),\n", + " (array([57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68]), array([92])),\n", + " (array([58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69]), array([93])),\n", + " (array([59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70]), array([94])),\n", + " (array([60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71]), array([95])),\n", + " (array([61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72]), array([96])),\n", + " (array([62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73]), array([97])),\n", + " (array([63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74]), array([98])),\n", + " (array([64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75]), array([99])),\n", + " (array([65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76]), array([100])),\n", + " (array([66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77]), array([101])),\n", + " (array([67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78]), array([102])),\n", + " (array([68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79]), array([103])),\n", + " (array([69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80]), array([104])),\n", + " (array([70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81]), array([105])),\n", + " (array([71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82]), array([106])),\n", + " (array([72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83]), array([107])),\n", + " (array([73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84]), array([108])),\n", + " (array([74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85]), array([109])),\n", + " (array([75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86]), array([110])),\n", + " (array([76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87]), array([111])),\n", + " (array([77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88]), array([112])),\n", + " (array([78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89]), array([113])),\n", + " (array([79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90]), array([114])),\n", + " (array([80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91]), array([115])),\n", + " (array([81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92]), array([116])),\n", + " (array([82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93]), array([117])),\n", + " (array([83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94]), array([118])),\n", + " (array([84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95]), array([119])),\n", + " (array([85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96]), array([120])),\n", + " (array([86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97]), array([121])),\n", + " (array([87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98]), array([122])),\n", + " (array([88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99]), array([123])),\n", + " (array([ 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100]),\n", + " array([124])),\n", + " (array([ 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101]),\n", + " array([125])),\n", + " (array([ 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102]),\n", + " array([126])),\n", + " (array([ 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103]),\n", + " array([127])),\n", + " (array([ 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104]),\n", + " array([128])),\n", + " (array([ 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105]),\n", + " array([129])),\n", + " (array([ 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106]),\n", + " array([130])),\n", + " (array([ 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107]),\n", + " array([131])),\n", + " (array([ 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108]),\n", + " array([132])),\n", + " (array([ 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109]),\n", + " array([133])),\n", + " (array([ 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110]),\n", + " array([134])),\n", + " (array([100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111]),\n", + " array([135])),\n", + " (array([101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112]),\n", + " array([136])),\n", + " (array([102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113]),\n", + " array([137])),\n", + " (array([103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114]),\n", + " array([138])),\n", + " (array([104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115]),\n", + " array([139])),\n", + " (array([105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116]),\n", + " array([140])),\n", + " (array([106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117]),\n", + " array([141])),\n", + " (array([107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118]),\n", + " array([142])),\n", + " (array([108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119]),\n", + " array([143])),\n", + " (array([109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120]),\n", + " array([144])),\n", + " (array([110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121]),\n", + " array([145])),\n", + " (array([111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122]),\n", + " array([146])),\n", + " (array([112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123]),\n", + " array([147])),\n", + " (array([113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124]),\n", + " array([148])),\n", + " (array([114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125]),\n", + " array([149])),\n", + " (array([115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126]),\n", + " array([150])),\n", + " (array([116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127]),\n", + " array([151])),\n", + " (array([117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128]),\n", + " array([152])),\n", + " (array([118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129]),\n", + " array([153])),\n", + " (array([119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130]),\n", + " array([154])),\n", + " (array([120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131]),\n", + " array([155])),\n", + " (array([121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132]),\n", + " array([156])),\n", + " (array([122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133]),\n", + " array([157])),\n", + " (array([123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134]),\n", + " array([158])),\n", + " (array([124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135]),\n", + " array([159])),\n", + " (array([125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136]),\n", + " array([160])),\n", + " (array([126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137]),\n", + " array([161])),\n", + " (array([127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138]),\n", + " array([162])),\n", + " (array([128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139]),\n", + " array([163])),\n", + " (array([129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140]),\n", + " array([164])),\n", + " (array([130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141]),\n", + " array([165])),\n", + " (array([131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142]),\n", + " array([166])),\n", + " (array([132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143]),\n", + " array([167])),\n", + " (array([133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144]),\n", + " array([168])),\n", + " (array([134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145]),\n", + " array([169])),\n", + " (array([135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146]),\n", + " array([170])),\n", + " (array([136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147]),\n", + " array([171])),\n", + " (array([137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148]),\n", + " array([172])),\n", + " (array([138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149]),\n", + " array([173])),\n", + " (array([139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150]),\n", + " array([174])),\n", + " (array([140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151]),\n", + " array([175])),\n", + " (array([141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152]),\n", + " array([176])),\n", + " (array([142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153]),\n", + " array([177])),\n", + " (array([143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154]),\n", + " array([178])),\n", + " (array([144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155]),\n", + " array([179])),\n", + " (array([145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156]),\n", + " array([180])),\n", + " (array([146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157]),\n", + " array([181])),\n", + " (array([147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158]),\n", + " array([182])),\n", + " (array([148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159]),\n", + " array([183])),\n", + " (array([149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160]),\n", + " array([184])),\n", + " (array([150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161]),\n", + " array([185])),\n", + " (array([151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162]),\n", + " array([186])),\n", + " (array([152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163]),\n", + " array([187])),\n", + " (array([153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164]),\n", + " array([188])),\n", + " (array([154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165]),\n", + " array([189])),\n", + " (array([155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166]),\n", + " array([190])),\n", + " (array([156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167]),\n", + " array([191])),\n", + " (array([157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168]),\n", + " array([192])),\n", + " (array([158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169]),\n", + " array([193])),\n", + " (array([159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170]),\n", + " array([194])),\n", + " (array([160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171]),\n", + " array([195])),\n", + " (array([161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172]),\n", + " array([196])),\n", + " (array([162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173]),\n", + " array([197])),\n", + " (array([163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174]),\n", + " array([198])),\n", + " (array([164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175]),\n", + " array([199])),\n", + " (array([165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176]),\n", + " array([200])),\n", + " (array([166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177]),\n", + " array([201])),\n", + " (array([167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178]),\n", + " array([202])),\n", + " (array([168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179]),\n", + " array([203])),\n", + " (array([169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180]),\n", + " array([204])),\n", + " (array([170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181]),\n", + " array([205])),\n", + " (array([171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182]),\n", + " array([206])),\n", + " (array([172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183]),\n", + " array([207])),\n", + " (array([173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184]),\n", + " array([208])),\n", + " (array([174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185]),\n", + " array([209])),\n", + " (array([175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186]),\n", + " array([210])),\n", + " (array([176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187]),\n", + " array([211])),\n", + " (array([177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188]),\n", + " array([212])),\n", + " (array([178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189]),\n", + " array([213])),\n", + " (array([179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190]),\n", + " array([214])),\n", + " (array([180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191]),\n", + " array([215])),\n", + " (array([181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192]),\n", + " array([216])),\n", + " (array([182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193]),\n", + " array([217])),\n", + " (array([183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194]),\n", + " array([218])),\n", + " (array([184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195]),\n", + " array([219])),\n", + " (array([185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196]),\n", + " array([220])),\n", + " (array([186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197]),\n", + " array([221])),\n", + " (array([187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198]),\n", + " array([222])),\n", + " (array([188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199]),\n", + " array([223])),\n", + " (array([189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200]),\n", + " array([224])),\n", + " (array([190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201]),\n", + " array([225])),\n", + " (array([191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202]),\n", + " array([226])),\n", + " (array([192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203]),\n", + " array([227])),\n", + " (array([193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204]),\n", + " array([228])),\n", + " (array([194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205]),\n", + " array([229])),\n", + " (array([195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206]),\n", + " array([230])),\n", + " (array([196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207]),\n", + " array([231])),\n", + " (array([197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208]),\n", + " array([232])),\n", + " (array([198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209]),\n", + " array([233])),\n", + " (array([199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210]),\n", + " array([234])),\n", + " (array([200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211]),\n", + " array([235])),\n", + " (array([201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212]),\n", + " array([236])),\n", + " (array([202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213]),\n", + " array([237])),\n", + " (array([203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214]),\n", + " array([238])),\n", + " (array([204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215]),\n", + " array([239]))]" + ] + }, + "execution_count": 82, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from sktime.forecasting.model_selection import SlidingWindowSplitter\n", + "cv = SlidingWindowSplitter(window_length= window_length, fh=len(forecaster.fh_test))\n", + "\n", + "[i for i in cv.split(forecaster.y_train)]\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'estimator__n_estimators': 100}\n", + "0.15297129616808536\n" + ] + } + ], + "source": [ + "# [Grid search cv results]\n", + "\n", + "print(gscv.best_params_)\n", + "print(gscv.best_score_)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(
,\n", + " )" + ] + }, + "execution_count": 58, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# [Plot grid search cv results]\n", + "\n", + "y_pred = gscv.predict(forecaster.fh_test, forecaster.X_test)\n", + "\n", + "plot_series(forecaster.y_train['2018-07-01':], forecaster.y_test, y_pred, labels=[\"y_train\", \"y_test\", \"y_pred\"], x_label='Date', y_label='Count pedestrians')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# [Perform seasonal decompose]\n", + "\n", + "import matplotlib.pyplot as plt\n", + "from statsmodels.tsa.seasonal import seasonal_decompose\n", + "result = seasonal_decompose(forecaster.y_train, model='multiplicative')\n", + "result.plot()\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/zq/miniconda3/lib/python3.10/site-packages/sktime/forecasting/model_selection/_tune.py:198: UserWarning: in ForecastingRandomizedSearchCV, n_jobs and pre_dispatch parameters are deprecated and will be removed in 0.26.0. Please use n_jobs and pre_dispatch directly in the backend_params argument instead.\n", + " warn(\n" + ] + } + ], + "source": [ + "from sktime.forecasting.compose import TransformedTargetForecaster\n", + "from sktime.transformations.series.detrend import Deseasonalizer, Detrender\n", + "from sktime.forecasting.trend import PolynomialTrendForecaster\n", + "\n", + "regressor = XGBRegressor(objective='reg:squarederror', random_state=42)\n", + "transformer_forecaster = TransformedTargetForecaster(\n", + " [\n", + " # (\"deseasonalize\", Deseasonalizer(model=\"additive\", sp=forecaster.period)),\n", + " # (\"detrend\", Detrender(forecaster=PolynomialTrendForecaster(degree=1))),\n", + " (\"forecast\", make_reduction(regressor, window_length=window_length, strategy=\"recursive\"),\n", + " ),\n", + " ]\n", + ")\n", + "\n", + "param_grid = {\n", + " # 'deseasonalize__model': ['multiplicative', 'additive'],\n", + " # 'detrend__forecaster__degree': [1, 2, 3],\n", + " 'forecast__estimator__max_depth': [3, 5, 6, 10, 15, 20],\n", + " 'forecast__estimator__learning_rate': [0.01, 0.1, 0.2, 0.3],\n", + " 'forecast__estimator__subsample': np.arange(0.5, 1.0, 0.1),\n", + " 'forecast__estimator__colsample_bytree': np.arange(0.4, 1.0, 0.1),\n", + " 'forecast__estimator__colsample_bylevel': np.arange(0.4, 1.0, 0.1),\n", + " 'forecast__estimator__n_estimators': [100, 500, 1000]\n", + "}\n", + "gscv = ForecastingRandomizedSearchCV(transformer_forecaster, cv=cv, param_distributions=param_grid, n_iter=2, random_state=42, error_score='raise')\n", + "\n", + "gscv.fit(y=forecaster.y_train, X=forecaster.X_train)\n", + "\n", + "y_pred = gscv.predict(fh=forecaster.fh_test, X=forecaster.X_test)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MAPE: 0.2330\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_series(forecaster.y_train['2018-07-01':], forecaster.y_test, y_pred, labels=[\"y_train\", \"y_test\", \"y_pred\"], x_label='Date', y_label='Count pedestrians')\n", + "\n", + "print('MAPE: %.4f' % mean_absolute_percentage_error(forecaster.y_test, y_pred, symmetric=False))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MAPE: 0.3751\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_series(forecaster.y_train['2018-07-01':], forecaster.y_test, y_pred, labels=[\"y_train\", \"y_test\", \"y_pred\"], x_label='Date', y_label='Count pedestrians')\n", + "\n", + "print('MAPE: %.4f' % mean_absolute_percentage_error(forecaster.y_test, y_pred, symmetric=False))" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "base", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.10" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/E05-analyser.ipynb b/notebooks/E05-analyser.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..33914b051494ab871595bc0687381dd2711efa7d --- /dev/null +++ b/notebooks/E05-analyser.ipynb @@ -0,0 +1,173 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "# To call functions outside of this folder\n", + "import sys \n", + "sys.path.insert(0, '..')\n", + "\n", + "import pandas as pd\n", + "from src.analyser import Analyser\n", + "import logging\n", + "import matplotlib.pyplot as plt\n", + "\n", + "# logging.basicConfig(level=logging.DEBUG)\n", + "\n", + "data = pd.read_csv(\n", + " '../data/multivariate/blow_mold_preprocessed.csv', \n", + " index_col='datetime', \n", + " parse_dates=['datetime'])" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "apikey still available, logged in\n" + ] + } + ], + "source": [ + "analyser = Analyser()" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'freq': 'M',\n", + " 'period': 12,\n", + " 'change_points': [],\n", + " 'predictability': [],\n", + " 'characteristic': None}" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "analyser.analyse(data)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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KztuFdqVnq/sb/5YkDWvfSA+1bUhSAQAAgApVlnPra25UqOrq0iFlU+5opgBfvhoAAABUHtdU520AAAAAlROJBQAAAADLSCwAAAAAWEZiAQAAAMAyEgsAAAAAlpFYAAAAALCMxAIAAACAZSQWAAAAACwjsQAAAABgGYkFAAAAAMtILAAAAABYRmIBAAAAwDISCwAAAACWkVgAAAAAsIzEAgAAAIBlJBYAAAAALCOxAAAAAGAZiQUAAAAAy0gsAAAAAFhGYgEAAADAMhILAAAAAJaRWAAAAACwjMQCAAAAgGUkFgAAAAAsI7EAAAAAYBmJBQAAAADL3J5YvPvuu2rUqJH8/PzUunVrrV+/vti6a9askc1mc3n95z//cXeYAAAAACxwa2KxcOFCPfHEE3r22We1detWtW/fXt27d9fBgwdLnG737t1KT093vJo2berOMAEAAABY5NbE4vXXX9cjjzyiYcOGqUWLFpo+fbpiYmL03nvvlThdeHi4IiMjHS8vL69i6+bm5ionJ8fpBQAAAMCz3JZYnD9/Xt9++626du3qVN61a1dt2LChxGlbtWqlqKgodenSRatXry6x7pQpUxQcHOx4xcTEWI4dAAAAQNm4LbHIzMxUfn6+IiIinMojIiKUkZFR5DRRUVGaOXOmFi1apM8//1xxcXHq0qWL1q1bV+xyxo0bp+zsbMcrLS2tXNcDAAAAwJV5u3sBNpvN6b0xxqWsUFxcnOLi4hzvk5KSlJaWpldffVUdOnQochq73S673V5+AQMAAAAoM7e1WISGhsrLy8uldeLo0aMurRgladeunfbs2VPe4QEAAAAoR25LLHx9fdW6dWutWLHCqXzFihVKTk4u9Xy2bt2qqKio8g4PAAAAQDly661QKSkpGjhwoBITE5WUlKSZM2fq4MGDGjFihKSL/SMOHz6sDz74QJI0ffp0xcbGqmXLljp//rzmz5+vRYsWadGiRe4MEwAAAIBFbk0s+vfvr6ysLD3//PNKT09XfHy8li1bpoYNG0qS0tPTnZ5pcf78eT399NM6fPiw/P391bJlS33xxRfq0aOHO8MEAAAAYJHNGGMqOojylJOTo+DgYGVnZysoKKiiwym1X8/n6brnvpIk/fh8NwX4ur1fPQAAAFCispxbu/UBeQAAAACqBxILAAAAAJaRWAAAAACwjMQCAAAAgGUkFgAAAAAsI7EAAAAAYBmJBQAAAADLSCwAAAAAWEZiAQAAAMAyEgsAAAAAlpFYAAAAALCMxAIAAACAZSQWAAAAACwjsQAAAABgGYkFAAAAAMtILAAAAABYRmIBAAAAwDISCwAAAACWeVd0AEBlsS/zjD7ZkqZDJ86qfh1/3ZcYo0ahNSs6LAAAgGsCiQVQCp9sSdMzi3bIZrPJGCObzab31/5XU/smqF9iTEWHBwAAUOG4FQq4gn2ZZ/TMoh0qMFJ+gXH6d+yiHdqfeaaiQwQAAKhwtFi4Sep/s8pU/9yFfMf/N+09Lj8fr/IOCVdpwTcHS/z89RU/6YGbG3goGgDwjPTss1qz+5iOnc5VWKBdneLCFBXsX9Fh4TJ8T1VfUpOQig6h1EgsUOm5+6B67HSuTDGfmf/7HAA8dYLnieWs2X1UM9fvlU0Xj3M2SUt3HNFjHRqrY7Pwcl0Wrh7fE641JBao1DxxUA0LtDvmfznb/30O4NrkqZN9T53geWI56dlnNXP9Xhnzv+Ne4b/vr9uruIggRQb7lcuycPX4nnAtoo8FKq1LD6oFRk7/vr9urzKyz5XLcjrFhZXYYnFbHFeFgGvRmt1H9dSn2/WPHUe0cW+W/rHjiJ76dLvW/nS0XJfjqWORp5azZvcx2Yr5zCZp9e7y3X64OnxPuBaRWKDS8tRBNSrYX491aCzbJQurYZNsNumxDo25IgRcgzx1Ei557ljkqeVU5ds/07PPasE3B/Xmqj1a8M1BpWefrbTLqsrfEyovtycW7777rho1aiQ/Pz+1bt1a69evL7H+2rVr1bp1a/n5+alx48aaMWOGu0OEm1Slg2rHZuGa0ud6x/s74yP1er8buYcVuEZ58mqup45FnlpO4e2fRXHX7Z+eOOH3VAuWp5ZVEd8TcCVu7WOxcOFCPfHEE3r33Xd1yy236P3331f37t31448/qkED11F09u3bpx49emj48OGaP3++vv76a40aNUphYWHq27evO0NFOauKfR8igv7XMtGvdUyVGLmrKo4mUhXXCWXnyQsPnjoWeWo5neLCtHTHkSI/c8ftn1Wt34inluXp76kq4vei/Lk1sXj99df1yCOPaNiwYZKk6dOn66uvvtJ7772nKVOmuNSfMWOGGjRooOnTp0uSWrRooS1btujVV18tc2Lx6/k8eZ/Ps7wOV+vS4WNLI/eS+rllnPZak5FzrsSDamxITaeT9KuV1CSkxINqcpOQMn8PJfHkd5SRc07r9xxT1unzCgn0VfumYYosh212qfV7jmnOhv0uP+ZDkxvp1qah5bosqWquk6d4Ytt5cjmeWFadAJ8ST8LrBPiU2/HBU8ciTy2nToCvhiY30uyv9zm2Xw3bxWUMTW6k2uW47Tz1e/GvXb+UuD+s2JWhfq3L52GnnlqWJ7+nqqgy/Qb+WoHns2Vdvs0YU9xFHUvOnz+vgIAAffrpp+rTp4+j/PHHH9e2bdu0du1al2k6dOigVq1a6Y033nCULV68WPfdd59+/fVX+fj4uEyTm5ur3Nz/XXnKyclRTEyMYp74RDXsAeW8VgAAAED1UZD7q9Km36fs7GwFBQWVWNdtfSwyMzOVn5+viIgIp/KIiAhlZGQUOU1GRkaR9fPy8pSZmVnkNFOmTFFwcLDjFRNTPlccAAAAAJSe259jYbM5dy0yxriUXal+UeWFxo0bp5SUFMf7whaLb57tcsWsyp027T1eYcsuSe6FfI348DtJ0owHb5LdDf0EPv02Tct/yFBBEW1hNWwXOz6XV5NzVeOpbTdj7X/1zf7jKqq90maTbo6tqxEdm1hejlT11ikj55zGL/6+2OVM6XN9udy6IXlu23nyb9bTx4dfcs5p3SW3H3RoGlZu3w+s89T+4Mm/W08uy1M8tU6eWk5l+w1s27huucRytXJychQ1vXR13ZZYhIaGysvLy6V14ujRoy6tEoUiIyOLrO/t7a2QkKIfZ26322W3u3ZYC/D1VoBvxT3/rzJ07LX7eLklzttbROjLH4pulTKS7mgRWSm2T0U48euFEjucnvj1Qrlsu4ggvxLvAY4I8iu376iqrVPqf7NKXM6G/2bpgZtdB6e4Gp7adp5ajqeXJUkNQ2pqYEjNcpsfypenfi9iQ2rqsQ6N9f46507iRheHDW9YjvuIJ5flKZ467nlqOZXtN7Aiz2clKa8My3fbrVC+vr5q3bq1VqxY4VS+YsUKJScnFzlNUlKSS/1//vOfSkxMLLJ/Ba5Nlz73ofB5Dzz3oXQ8NXygJx/6V9XWqSJGGyqKO0YbcvdyPL0sXPs8+XvRsVm4Xu93o3olRKtd4xD1Soh227DhnlyWJ1S1IZWr4m/gtcKtKVBKSooGDhyoxMREJSUlaebMmTp48KBGjBgh6eJtTIcPH9YHH3wgSRoxYoTefvttpaSkaPjw4UpNTdWsWbO0YMECd4YJN+jYLFxxEUFavfuoYxi32+LCSSquwFPDBxb+mBd3Ra08v6eqtk6eHObYU9vOk8NWMkQmLufJ34vIYL9ya1G8lpblblVtSOWq+Bt4rXBrYtG/f39lZWXp+eefV3p6uuLj47Vs2TI1bNhQkpSenq6DBw866jdq1EjLli3Tk08+qXfeeUfR0dF68803eYZFJVWVDqqe4smDnad+zKvaOnnyR8JT286T35Enl4XKg9+La1tVvMhRFX8DrwVuG262ouTk5Cg4OLhUQ2K5U+p/syps2SU5dyFfD8/dLEmaM6QNfR2uURnZ56pca09VWqe1Px0t9kfCHbc6eGrbefI7qkr7A1AdeOq45+njq6dYOeYlNSm6n7GnlOXcmsTCTUgsgKqNE2MA1U1VvMhRGVSmxKJiu5kDQCXFrRsAqhtPHfc4vlZeJBZuUtHZZXEufSx728Z1K3wIMwAAAFQNbhtuFgAAAED1QWIBAAAAwDISCwAAAACWkVgAAAAAsIzEAgAAAIBlJBYAAAAALCOxAAAAAGAZiQUAAAAAy0gsAAAAAFhGYgEAAADAMhILAAAAAJaRWFQz+7POOP7/+oqftC/zTAm1AQAAgNIhsahGPtmSpl5v/tvxfs6/96vLa2v06Za0CowKAAAAVQGJRTWxL/OMnlm0QwXmf2X5xqjASGMX7dB+Wi4AAABgAYlFNfHJljTZbLYiP7PZbFpIqwUAAAAsILGoJg6dOCtjTJGfGWN06MRZD0cEAACAqoTEopqoX8e/xBaL+nX8PRwRAAAAqhISi2rivsSYElss+ifGeDgiAAAAVCUkFtVEo9Camto3QTVsklcNm9O/U/smKDa0ZkWHCAAAgErMu6IDgOf0S4xRm9i6WrglTYdOnFX9Ov7qnxhDUgEAAADLSCyqmdjQmhp7Z/OKDgMAAABVDLdCAQAAALCMxAIAAACAZSQWAAAAACxza2Jx4sQJDRw4UMHBwQoODtbAgQN18uTJEqcZMmSIbDab06tdu3buDBMAAACARW7tvD1gwAAdOnRIy5cvlyQ9+uijGjhwoJYuXVridHfeeafmzJnjeO/r6+vOMAEAAABY5LbEYteuXVq+fLk2btyotm3bSpL+/Oc/KykpSbt371ZcXFyx09rtdkVGRrorNAAAAADlzG23QqWmpio4ONiRVEhSu3btFBwcrA0bNpQ47Zo1axQeHq5mzZpp+PDhOnr0aLF1c3NzlZOT4/QCAAAA4FluSywyMjIUHh7uUh4eHq6MjIxip+vevbs+/PBDrVq1Sq+99po2b96szp07Kzc3t8j6U6ZMcfThCA4OVkxMTLmtAwAAAIDSKXNiMWnSJJfO1Ze/tmzZIkmy2Wwu0xtjiiwv1L9/f/Xs2VPx8fG666679OWXX+qnn37SF198UWT9cePGKTs72/FKS0sr6yoBAAAAsKjMfSzGjBmj+++/v8Q6sbGx2rFjh3755ReXz44dO6aIiIhSLy8qKkoNGzbUnj17ivzcbrfLbreXen4AAAAAyl+ZE4vQ0FCFhoZesV5SUpKys7P1zTff6Oabb5Ykbdq0SdnZ2UpOTi718rKyspSWlqaoqKiyhgoAAADAQ9zWx6JFixa68847NXz4cG3cuFEbN27U8OHD1atXL6cRoZo3b67FixdLkk6fPq2nn35aqamp2r9/v9asWaO77rpLoaGh6tOnj7tCBQAAAGCRWx+Q9+GHH+r6669X165d1bVrVyUkJOivf/2rU53du3crOztbkuTl5aXvv/9e99xzj5o1a6bBgwerWbNmSk1NVa1atdwZKgAAAAALbMYYU9FBlKecnBwFBwcrOztbQUFBFR0OAAAAUGmV5dzarS0WAAAAAKoHEgsAAAAAlpFYAAAAALCMxAIAAACAZSQWAAAAACwjsQAAAABgGYkFAAAAAMtILAAAAABYRmIBAAAAwDISCwAAAACWkVgAAAAAsIzEAgAAAIBlJBYAAAAALCOxAAAAAGAZiQUAAAAAy0gsAAAAAFhGYgEAAADAMhILAAAAAJaRWAAAAACwjMQCAAAAgGUkFgAAAAAsI7EAAAAAYBmJBQAAAADLSCwAAAAAWEZiAQAAAMAyEgsAAAAAlpFYAAAAALDMrYnFH//4RyUnJysgIEC1a9cu1TTGGE2aNEnR0dHy9/dXp06dtHPnTneGCQAAAMAityYW58+fV79+/TRy5MhSTzNt2jS9/vrrevvtt7V582ZFRkbqjjvu0KlTp9wYKQAAAAArvN0588mTJ0uS5s6dW6r6xhhNnz5dzz77rH77299KkubNm6eIiAh99NFHeuyxx1ymyc3NVW5uruN9dna2JCknJ8di9AAAAED1VnhObYy5Yl23JhZltW/fPmVkZKhr166OMrvdro4dO2rDhg1FJhZTpkxxJDCXiomJcWusAAAAQHVx6tQpBQcHl1jnmkosMjIyJEkRERFO5RERETpw4ECR04wbN04pKSmO9wUFBTp+/LhCQkJks9ksx5STk6OYmBilpaUpKCjI8vxQubE/4FLsD7gc+wQuxf6AS1XW/cEYo1OnTik6OvqKdcucWEyaNKnIFoJLbd68WYmJiWWdtcPlCYExptgkwW63y263O5WVtqN4WQQFBVWqnQDuxf6AS7E/4HLsE7gU+wMuVRn3hyu1VBQqc2IxZswY3X///SXWiY2NLetsJUmRkZGSLrZcREVFOcqPHj3q0ooBAAAA4NpR5sQiNDRUoaGh7ohFjRo1UmRkpFasWKFWrVpJujiy1Nq1azV16lS3LBMAAACAdW4dbvbgwYPatm2bDh48qPz8fG3btk3btm3T6dOnHXWaN2+uxYsXS7p4C9QTTzyhl156SYsXL9YPP/ygIUOGKCAgQAMGDHBnqMWy2+2aOHGiy+1WqJ7YH3Ap9gdcjn0Cl2J/wKWqw/5gM6UZO+oqDRkyRPPmzXMpX716tTp16nQxAJtNc+bM0ZAhQyRd7E8xefJkvf/++zpx4oTatm2rd955R/Hx8e4KEwAAAIBFbk0sAAAAAFQPbr0VCgAAAED1QGIBAAAAwDISCwAAAACWkVgAAAAAsIzEAgAAAIBlJBYAAAAALCOxAAAAAGAZiQUAAAAAy0gsAAAAAFhGYgEAAADAMhILAAAAAJaRWAAAAACwjMQCAAAAgGUkFgAAAAAsI7EAAAAAYBmJBQAAAADLSCwAAAAAWEZiAaDKePPNN2Wz2RQfH295XsuWLdOkSZOsB1UJ7N+/XzabTXPnzi3ztEeOHNGkSZO0bds2l88mTZokm81mPUAAQKVAYgGgypg9e7YkaefOndq0aZOleS1btkyTJ08uj7CqtCNHjmjy5MlFJhbDhg1Tamqq54MCAFQIEgsAVcKWLVu0fft29ezZU5I0a9asCo7I/X799dciy40xOnv2rIejcVW/fn21a9euosOoUor7zgHgWkBiAaBKKEwkXn75ZSUnJ+vjjz92OQlbs2aNbDab1qxZ41R++a1AQ4YM0TvvvCNJstlsjtf+/fslSefOndO4cePUqFEj+fr6ql69eho9erROnjzpEtdHH32kpKQkBQYGKjAwUDfeeKNL0jN79mzdcMMN8vPzU926ddWnTx/t2rXLqc6QIUMUGBio77//Xl27dlWtWrXUpUsXR4xjxozRjBkz1KJFC9ntds2bN0+StGfPHg0YMEDh4eGy2+1q0aKFY91K8vPPP+vhhx9W06ZNFRAQoHr16umuu+7S999/77Q927RpI0l6+OGHHdup8Bayom6FKigo0LRp09S8eXPZ7XaFh4dr0KBBOnTokFO9Tp06KT4+Xps3b1b79u0VEBCgxo0b6+WXX1ZBQcEV4y+rP//5z2rWrJnsdruuu+46ffTRRxoyZIhiY2Od6k2ePFlt27ZV3bp1FRQUpJtuukmzZs2SMcap3qpVq9SpUyeFhITI399fDRo0UN++fcuUGBRug3Xr1ik5OVkBAQEaOnSoJCknJ0dPP/200z74xBNP6MyZM07zOHnypB555BHVrVtXgYGB6tmzp/bu3ev0PUn/+6527Nihfv36KTg4WHXr1lVKSory8vK0e/du3XnnnapVq5ZiY2M1bdq0sm1gANWCd0UHAABWnT17VgsWLFCbNm0UHx+voUOHatiwYfr00081ePDgMs9vwoQJOnPmjD777DOnW3mioqJkjFHv3r21cuVKjRs3Tu3bt9eOHTs0ceJEpaamKjU1VXa7XZL03HPP6YUXXtBvf/tbPfXUUwoODtYPP/ygAwcOOOY5ZcoUjR8/Xg888ICmTJmirKwsTZo0SUlJSdq8ebOaNm3qqHv+/Hndfffdeuyxx/TMM88oLy/P8dnf/vY3rV+/Xs8995wiIyMVHh6uH3/8UcnJyWrQoIFee+01RUZG6quvvtLvfvc7ZWZmauLEicVugyNHjigkJEQvv/yywsLCdPz4cc2bN09t27bV1q1bFRcXp5tuuklz5szRww8/rD/84Q+O1qL69esXO9+RI0dq5syZGjNmjHr16qX9+/drwoQJWrNmjb777juFhoY66mZkZOjBBx/UU089pYkTJ2rx4sUaN26coqOjNWjQoDJ8oyWbOXOmHnvsMfXt21d/+tOflJ2drcmTJys3N9el7v79+/XYY4+pQYMGkqSNGzfq//2//6fDhw/rueeec9Tp2bOn2rdvr9mzZ6t27do6fPiwli9frvPnzysgIKDUsaWnp+uhhx7S73//e7300kuqUaOGfv31V3Xs2FGHDh3S+PHjlZCQoJ07d+q5557T999/r3/961+y2WwqKCjQXXfdpS1btmjSpEm66aablJqaqjvvvLPY5d1333166KGH9Nhjj2nFihWaNm2aLly4oH/9618aNWqUnn76aX300UcaO3asfvOb3+i3v/1tGbc2gCrNAEAl98EHHxhJZsaMGcYYY06dOmUCAwNN+/btneqtXr3aSDKrV692Kt+3b5+RZObMmeMoGz16tCnqELl8+XIjyUybNs2pfOHChUaSmTlzpjHGmL179xovLy/z4IMPFhv3iRMnjL+/v+nRo4dT+cGDB43dbjcDBgxwlA0ePNhIMrNnz3aZjyQTHBxsjh8/7lTerVs3U79+fZOdne1UPmbMGOPn5+eoX9T6Xy4vL8+cP3/eNG3a1Dz55JOO8s2bNxc77cSJE5224a5du4wkM2rUKKd6mzZtMpLM+PHjHWUdO3Y0ksymTZuc6l533XWmW7duxcZZVvn5+SYyMtK0bdvWqfzAgQPGx8fHNGzYsMRpL1y4YJ5//nkTEhJiCgoKjDHGfPbZZ0aS2bZtm6XYCrfBypUrncqnTJliatSoYTZv3uxUXrjcZcuWGWOM+eKLL4wk895777lML8lMnDjRUVb4Xb322mtOdW+88UYjyXz++eeOsgsXLpiwsDDz29/+1tL6Aah6uBUKQKU3a9Ys+fv76/7775ckBQYGql+/flq/fr327NlTrstatWqVpIu3Jl2qX79+qlmzplauXClJWrFihfLz8zV69Ohi55WamqqzZ8+6zCsmJkadO3d2zOtSffv2LXJenTt3Vp06dRzvz507p5UrV6pPnz4KCAhQXl6e49WjRw+dO3dOGzduLDa2vLw8vfTSS7ruuuvk6+srb29v+fr6as+ePS63aZXW6tWrJbluu5tvvlktWrRwWd/IyEjdfPPNTmUJCQlOLT5FKSgocFrf/Pz8Yuvu3r1bGRkZuu+++5zKGzRooFtuucWl/qpVq3T77bcrODhYXl5e8vHx0XPPPaesrCwdPXpUknTjjTfK19dXjz76qObNm6e9e/eWGG9J6tSpo86dOzuV/eMf/1B8fLxuvPFGp/Xs1q2b061+a9eulSSXdXvggQeKXV6vXr2c3rdo0UI2m03du3d3lHl7e+s3v/nNFb8HANUPiQWASu3nn3/WunXr1LNnTxljdPLkSZ08eVL33nuvpP+NFFVesrKy5O3trbCwMKdym82myMhIZWVlSZKOHTsmqeTbggrrRkVFuXwWHR3t+LxQQECAgoKCipzX5fPIyspSXl6e3nrrLfn4+Di9evToIUnKzMwsNraUlBRNmDBBvXv31tKlS7Vp0yZt3rxZN9xww1V3DC/r+oaEhLjUs9vtV1z+0KFDnda3sC9KSTFFRES4fHZ52TfffKOuXbtKutgn4+uvv9bmzZv17LPPSpIjriZNmuhf//qXwsPDNXr0aDVp0kRNmjTRG2+8UWLcRSlqW/3yyy/asWOHy/daq1YtGWMc32vhvlq3bt0S1+tSl9f19fVVQECA/Pz8XMrPnTtX5vUBULXRxwJApTZ79mwZY/TZZ5/ps88+c/l83rx5evHFF+Xl5eU4Obr83vmSTrAvFxISory8PB07dswpuTDGKCMjw9GZufCzQ4cOKSYmpth5SRfvo7/ckSNHnPobSCrxmRCXf1anTh15eXlp4MCBxbaaNGrUqNj5zZ8/X4MGDdJLL73kVJ6ZmanatWsXO11JLl3fyxOuotb3ak2aNEljxoxxvK9Vq9YVY/rll19cPsvIyHB6//HHH8vHx0f/+Mc/nE60//a3v7lM2759e7Vv3175+fnasmWL3nrrLT3xxBOKiIhwtKyVRlHfeWhoqPz9/YtNmgu3Y+G+evz4caeE4fL1AoDyQosFgEorPz9f8+bNU5MmTbR69WqX11NPPaX09HR9+eWXkuQY4WfHjh1O81myZInLvAs7YF9+dbzw6vf8+fOdyhctWqQzZ844Pu/atau8vLz03nvvFRt/UlKS/P39XeZ16NAhrVq1qsQr7VcSEBCg2267TVu3blVCQoISExNdXkW1CBSy2WyObVDoiy++0OHDh53KittORSm8pefy9d28ebN27dplaX0vFRsb67SecXFxxdaNi4tTZGSkPvnkE6fygwcPasOGDU5lNptN3t7e8vLycpSdPXtWf/3rX4udv5eXl9q2besYieu77767mlVy0qtXL/33v/9VSEhIkd9r4X7esWNHSdLChQudpv/4448txwAARaHFAkCl9eWXX+rIkSOaOnWqOnXq5PJ5fHy83n77bc2aNUu9evVSZGSkbr/9dk2ZMkV16tRRw4YNtXLlSn3++ecu015//fWSpKlTp6p79+7y8vJSQkKC7rjjDnXr1k1jx45VTk6ObrnlFseoUK1atdLAgQMlXTy5HT9+vF544QWdPXtWDzzwgIKDg/Xjjz8qMzNTkydPVu3atTVhwgSNHz9egwYN0gMPPKCsrCxNnjxZfn5+JY7aVBpvvPGGbr31VrVv314jR45UbGysTp06pZ9//llLly519BcpSq9evTR37lw1b95cCQkJ+vbbb/XKK6+4tDQ0adJE/v7++vDDD9WiRQsFBgYqOjpa0dHRLvOMi4vTo48+qrfeeks1atRQ9+7dHaNCxcTE6Mknn7S0vlejRo0amjx5sh577DHde++9Gjp0qE6ePKnJkycrKipKNWr87/pbz5499frrr2vAgAF69NFHlZWVpVdffdUlAZsxY4ZWrVqlnj17qkGDBjp37pyjdeH222+3HPMTTzyhRYsWqUOHDnryySeVkJCggoICHTx4UP/85z/11FNPqW3btrrzzjt1yy236KmnnlJOTo5at26t1NRUffDBB451B4ByVbF9xwHg6vXu3dv4+vqao0ePFlvn/vvvN97e3iYjI8MYY0x6erq59957Td26dU1wcLB56KGHzJYtW1xGNsrNzTXDhg0zYWFhxmazGUlm3759xhhjzp49a8aOHWsaNmxofHx8TFRUlBk5cqQ5ceKEy/I/+OAD06ZNG+Pn52cCAwNNq1atXEZQ+stf/mISEhKMr6+vCQ4ONvfcc4/ZuXOnU53BgwebmjVrFrmOkszo0aOL/Gzfvn1m6NChpl69esbHx8eEhYWZ5ORk8+KLLzrVuXz9T5w4YR555BETHh5uAgICzK233mrWr19vOnbsaDp27Oi0jAULFpjmzZsbHx8fp9GGLh8VypiLIylNnTrVNGvWzPj4+JjQ0FDz0EMPmbS0NKd6HTt2NC1btnRZn8GDB5c4UtPVmjlzpvnNb35jfH19TbNmzczs2bPNPffcY1q1auVUb/bs2SYuLs7Y7XbTuHFjM2XKFDNr1iyn/SM1NdX06dPHNGzY0NjtdhMSEmI6duxolixZUqaYitsGxhhz+vRp84c//MHExcU59pvrr7/ePPnkk4593Rhjjh8/bh5++GFTu3ZtExAQYO644w6zceNGI8m88cYbjnqF39WxY8ecllPcfldSbACqL5sxlz3VBwCAau7kyZNq1qyZevfurZkzZ1Z0OOXqo48+0oMPPqivv/5aycnJFR0OgCqEW6EAANVaRkaG/vjHP+q2225TSEiIDhw4oD/96U86deqUHn/88YoOz5IFCxbo8OHDuv7661WjRg1t3LhRr7zyijp06EBSAaDckVgAAKo1u92u/fv3a9SoUTp+/LgCAgLUrl07zZgxQy1btiz35eXn56ukmwVsNptTB3EratWqpY8//lgvvviizpw5o6ioKA0ZMkQvvvhiucwfAC7FrVAAAHhQp06dHA+vK0rDhg21f/9+zwUEAOXErYnFunXr9Morr+jbb79Venq6Fi9erN69e5c4zdq1a5WSkqKdO3cqOjpav//97zVixAh3hQgAgEft3r1bp06dKvZzu93uGJUMACoTt94KdebMGd1www16+OGH1bdv3yvW37dvn3r06KHhw4dr/vz5+vrrrzVq1CiFhYWVanoAAK51JT1XAwAqM4/dCmWz2a7YYjF27FgtWbJEu3btcpSNGDFC27dvV2pqapHT5ObmOj1Ft6CgQMePH1dISEiJT6kFAAAAUDJjjE6dOqXo6OgrPv/mmuq8nZqaqq5duzqVdevWTbNmzdKFCxfk4+PjMs2UKVM0efJkT4UIAAAAVDtpaWkuD0m93DWVWGRkZCgiIsKpLCIiQnl5ecrMzFRUVJTLNOPGjVNKSorjfXZ2tho0aKC0tDQFBQW5PWar9med0d1v/VsFRbQb1bBJS//frWoYUtPzgQEAAKDay8nJUUxMjGrVqnXFutdUYiHJ5falwju1irutyW63y263u5QHBQVVisTiyw1H5OVXU0VlFl41bFq2O1tj73RNqAAAAABPKU0Xg5JvlPKwyMhIZWRkOJUdPXpU3t7eCgkJqaCo3OvQibPFjmdujNGhE2c9HBEAAABQdtdUYpGUlKQVK1Y4lf3zn/9UYmJikf0rqoL6dfyLzQBtNpvq1/H3cEQAAABA2bk1sTh9+rS2bdumbdu2Sbo4nOy2bdt08OBBSRf7RwwaNMhRf8SIETpw4IBSUlK0a9cuzZ49W7NmzdLTTz/tzjAr1H2JMSW2WPRPjPFwRAAAAEDZuTWx2LJli1q1aqVWrVpJklJSUtSqVSs999xzkqT09HRHkiFJjRo10rJly7RmzRrdeOONeuGFF/Tmm29W6WdYNAqtqal9E1TjkkYLL5tNNWzS1L4Jig2l4zYAAACufR57joWn5OTkKDg4WNnZ2ZWi83ahXenZ6v7GvyVJw9o30kNtG5JUAAAAoEKV5dz6mhsVqrq6dEjZlDuaKcCXrwYAAACVxzXVeRsAAABA5URiAQAAAMAyEgsAAAAAlpFYAAAAALCMxAIAAACAZSQWAAAAACwjsQAAAABgGYkFAAAAAMtILAAAAABYRmIBAAAAwDISCwAAAACWkVgAAAAAsIzEAgAAAIBlJBYAAAAALCOxAAAAAGAZiQUAAAAAy0gsAAAAAFhGYgEAAADAMhILAAAAAJaRWAAAAACwjMQCAAAAgGUkFgAAAAAsI7EAAAAAYBmJBQAAAADLSCwAAAAAWEZiAQAAAMAytycW7777rho1aiQ/Pz+1bt1a69evL7bumjVrZLPZXF7/+c9/3B0mAAAAAAvcmlgsXLhQTzzxhJ599llt3bpV7du3V/fu3XXw4MESp9u9e7fS09Mdr6ZNm7ozTAAAAAAWuTWxeP311/XII49o2LBhatGihaZPn66YmBi99957JU4XHh6uyMhIx8vLy6vYurm5ucrJyXF6AQAAAPAstyUW58+f17fffquuXbs6lXft2lUbNmwocdpWrVopKipKXbp00erVq0usO2XKFAUHBzteMTExlmMHAAAAUDZuSywyMzOVn5+viIgIp/KIiAhlZGQUOU1UVJRmzpypRYsW6fPPP1dcXJy6dOmidevWFbuccePGKTs72/FKS0sr1/UAAAAAcGXe7l6AzWZzem+McSkrFBcXp7i4OMf7pKQkpaWl6dVXX1WHDh2KnMZut8tut5dfwAAAAADKzG0tFqGhofLy8nJpnTh69KhLK0ZJ2rVrpz179pR3eAAAAADKkdsSC19fX7Vu3VorVqxwKl+xYoWSk5NLPZ+tW7cqKiqqvMMDAAAAUI7ceitUSkqKBg4cqMTERCUlJWnmzJk6ePCgRowYIeli/4jDhw/rgw8+kCRNnz5dsbGxatmypc6fP6/58+dr0aJFWrRokTvDBAAAAGCRWxOL/v37KysrS88//7zS09MVHx+vZcuWqWHDhpKk9PR0p2danD9/Xk8//bQOHz4sf39/tWzZUl988YV69OjhzjABAAAAWGQzxpiKDqI85eTkKDg4WNnZ2QoKCqrocErt1/N5uu65ryRJPz7fTQG+bu9XDwAAAJSoLOfWbn1AHgAAAIDqgcQCAAAAgGUkFgAAAAAsI7EAAAAAYBmJBQAAAADLSCwAAAAAWEZiAQAAAMAyEgsAAAAAlpFYAAAAALCMxAIAAACAZSQWAAAAACwjsQAAAABgGYkFAAAAAMtILAAAAABYRmIBAAAAwDISCwAAAACWkVgAAAAAsMy7ogNA1bUv84w+2ZKmQyfOqn4df92XGKNGoTUrOiwAAAC4AYkF3OKTLWl6ZtEO2Ww2GWNks9n0/tr/amrfBPVLjKno8AAAAFDOSCxQ7vZlntEzi3aowEgy5mLh//07dtEOtYmtq1haLkpEaw8AAKhsSCxQ7j7Zkiabzfa/pOISNptNC7ekaeydzSsgssqB1h4AAFAZkVi4Sep/s8pU/9yFfMf/N+09Lj8fr/IOyWO2pZ1UQRFJhSQVGKNtaSfLvH2qi/Tssxq7aMfFnOyy1p7fL9oh7xo1FBnsV67LW7P7mI6dzlVYoF2d4sIUFexfbvOvCFVxnQAA1VdSk5CKDqHUSCxQ7sIC7bJJKiq1sP3f5yjamt3HStx2q3cf1QM3NyinZR3VzPV7HcuzSVq644ge69BYHZuFl8syLuWJE35PrxMAFIeLHKiOSCxQ7jrFhWnpjiNFfmYk3RbHCV5xjp3OLTKpkC5uu2Onc8tlOenZZzVz/V4Z878kpvDf99ftVVxEULm2jHjihN/T6wQAxeEiB6orEguUu6hgfz3WobHeX7fXcTdPDdvFg+tjHRpzclcCT7X2eLJlxFMn/J5cJ4mrkUB58tTfkyeWw0WOyoPjePkjsYBbdGwWrtiQmnrm8+8lSXfGR+qOFpEcTK/AU609nmoZkTx3wu/ZdeJqJKo+T510eervyXPL8exFDlwdjuPu4fYnb7/77rtq1KiR/Pz81Lp1a61fv77E+mvXrlXr1q3l5+enxo0ba8aMGe4OEW4SEfS/JKJf65hKn1SkZ5/Vgm8O6s1Ve7Tgm4NKzz5b7ssobO2x2f5XVsMm2Wzl29pT2DJSlPLuB+OpE35PrdOlVyMLjJz+fX/dXmVknyuX5VR1nvh7qqo8se3W7D6qpz7drn/sOKKNe7P0jx1H9NSn27X2p6PluhxP/T158u/Wkxc5pKr5t+TudeI47j5ubbFYuHChnnjiCb377ru65ZZb9P7776t79+768ccf1aCBa7a+b98+9ejRQ8OHD9f8+fP19ddfa9SoUQoLC1Pfvn3dGSpQIk9e2fBEa48n+8F46vYuT60TVyOt40rh1atq/ZU89ffkyb9bTw5gUhX/ljyxThzH3ceticXrr7+uRx55RMOGDZMkTZ8+XV999ZXee+89TZkyxaX+jBkz1KBBA02fPl2S1KJFC23ZskWvvvpqmROLX8/nyft8nuV1uFqXDh9bGrmX1M8t47TXqqqyThk550r8kY0NqenUOlMeavv7OP5/d0K07D5eZd6nSlInwFdDkxtp9tf7HOtS2A9maHIj1Q7wKbflJTUJKfGEP7lJSLksy1Pr9EvOuRKvRv6Sc65cv6uqxtN/Txk557R+zzFlnT6vkEBftW8apshy/nv1FE9tu3/t+qXEk64VuzLUr3X5PFPHU39Pnvy79dQxryJ+m9zNU+tU2Y7jv1bg+WxZl28zppgHDlh0/vx5BQQE6NNPP1WfPn0c5Y8//ri2bdumtWvXukzToUMHtWrVSm+88YajbPHixbrvvvv066+/ysfHx2Wa3Nxc5eb+r1kxJydHMTExinniE9WwB5TzWgEAAADVR0Hur0qbfp+ys7MVFBRUYl239bHIzMxUfn6+IiIinMojIiKUkZFR5DQZGRlF1s/Ly1NmZmaR00yZMkXBwcGOV0wMTyYGAAAAPM3to0LZbM7dKY0xLmVXql9UeaFx48YpJSXF8b6wxeKbZ7tcMatyp017j1fYskuSeyFfIz78TpI048GbZK/ET/jOyDmn8Yu/V1FtbjabNKXP9eXSZPrpt2la/kOGCopYTg3bxT4Q5XVbACqHf+/J1OwN+5zuAS685erWpqHlthxP7eOFPHF88NTfkyf/bqvascjT+52n/p48tRxP8fRv0/o9xzTn6/1F3mpaXtvPk+vkyf3B6rZr27huucZTVjk5OYqaXrq6bkssQkND5eXl5dI6cfToUZdWiUKRkZFF1vf29lZISNGPM7fb7bLbXTtCBfh6K8C34kbT9asEJ+x2H69KEWdxUv+bVeJ9wBv+m1Uuna9ubxGhL38oupXNSLqjRWSl3o4ou9uvi1B8vWCt3n3UMRTnbXHh5T7ymaf28aK46/jgqb+nE79eKPEe6hO/Xii39atqx6LYkJqOZxFdftL1WIfGahhS0/IyLuWpvydPLcdTPPnblJ59VnM27HfaxwtP/mdv2Kf4esHlsh09uU6e2h/KY9tV5PmsJOWVYflui9TX11etW7fWihUrnPpYrFixQvfcc0+R0yQlJWnp0qVOZf/85z+VmJhYZP8KVG+eGtLv0gf+FfUjW1l/lGBNZLCf20cN8fSwlZ7gqb8nT47MUxWPRR2bhSsuIshjJ+Ge+Hvy5HI8wZP7g6dGUfL0760n9ofqNgKVW1OglJQUDRw4UImJiUpKStLMmTN18OBBjRgxQtLF25gOHz6sDz74QJI0YsQIvf3220pJSdHw4cOVmpqqWbNmacGCBe4ME5WUJ08cPP0jC0ie3cc9yRN/T1VxSGXJs8eiqnQSXlV5an/w5EWOqvZ7WxUvEJXErYlF//79lZWVpeeff17p6emKj4/XsmXL1LBhQ0lSenq6Dh486KjfqFEjLVu2TE8++aTeeecdRUdH68033+QZFiiSJ08cJH5k4Xme3sczcv73UKhPv03T7S0i3PKkZcn9f0+evPLJsQgVyRP7g6cvclSlfbyqXiAqjtuGm60oOTk5Cg4OLtWQWO6U+t+sClt2Sc5dyNfDczdLkuYMaVPp+was/elosScOlfXhQMClPLWPFz6UqvAXobBzYWX/W8rIPueRK58ci1CVpWef1VOfbi+2Q//r/W6stC0K7lYe2y6pSdH9jD2lLOfWFdsbBLCoqjWZApfzxD5+6ZOWCxV2LizvJy17mqeufHIsQlVGX8OrV922HYkFKr2q1GQKFMXd+3h161zoLhyLUJWRPF+96rTtSCzcpKKbrYpz6WPZ2zauW+FDmAGoeB99c7DEz42u3WMaAM/qc1O9ig6h0qoO285tT94GAFQO9ev4F/sQUpvNpvp13NOBGwBQtZBYAEA1d19ijIobx8MYo/6JPFkeAHBlJBYAUM01Cq2pqX0TVMMmedWwOf07tW+CYkPL90nLAICqiRvsAQDqlxijNrF1tXBLmg6dOKv6dfzVPzGGpAIAUGokFgAASVJsaE2NvbN5RYcBAKikuBUKAAAAgGUkFgAAAAAsI7EAAAAAYBmJBQAAAADLSCwAAAAAWEZiAQAAAMAyEgsAAAAAlpFYAAAAALCMxAIAAACAZSQWAAAAACwjsahm9medcfz/9RU/aV/mmRJqAwAAAKVDYlGNfLIlTb3e/Lfj/Zx/71eX19bo0y1pFRgVAAAAqgISi2piX+YZPbNohwrM/8ryjVGBkcYu2qH9tFwAAADAAhKLauKTLWmy2WxFfmaz2bSQVgsAAABYQGJRTRw6cVbGmCI/M8bo0ImzHo4IAAAAVQmJRTVRv45/iS0W9ev4ezgiAAAAVCUkFtXEfYkxJbZY9E+M8XBEAAAAqEpILKqJRqE1NbVvgmrYJK8aNqd/p/ZNUGxozYoOEQAAAJWYd0UHAM/plxijNrF1tXBLmg6dOKv6dfzVPzGGpAIAAACWubXF4sSJExo4cKCCg4MVHBysgQMH6uTJkyVOM2TIENlsNqdXu3bt3BlmtRIbWlNj72yutx5opbF3NiepAAAAQLlwa4vFgAEDdOjQIS1fvlyS9Oijj2rgwIFaunRpidPdeeedmjNnjuO9r6+vO8MEAAAAYJHbEotdu3Zp+fLl2rhxo9q2bStJ+vOf/6ykpCTt3r1bcXFxxU5rt9sVGRnprtAAAAAAlDO33QqVmpqq4OBgR1IhSe3atVNwcLA2bNhQ4rRr1qxReHi4mjVrpuHDh+vo0aPF1s3NzVVOTo7TCwAAAIBnuS2xyMjIUHh4uEt5eHi4MjIyip2ue/fu+vDDD7Vq1Sq99tpr2rx5szp37qzc3Nwi60+ZMsXRhyM4OFgxMQybCgAAAHhamROLSZMmuXSuvvy1ZcsWSSrygWzGmGIf1CZJ/fv3V8+ePRUfH6+77rpLX375pX766Sd98cUXRdYfN26csrOzHa+0tLSyrhIAAAAAi8rcx2LMmDG6//77S6wTGxurHTt26JdffnH57NixY4qIiCj18qKiotSwYUPt2bOnyM/tdrvsdnup5wcAAACg/JU5sQgNDVVoaOgV6yUlJSk7O1vffPONbr75ZknSpk2blJ2dreTk5FIvLysrS2lpaYqKiiprqAAAAAA8xG19LFq0aKE777xTw4cP18aNG7Vx40YNHz5cvXr1choRqnnz5lq8eLEk6fTp03r66aeVmpqq/fv3a82aNbrrrrsUGhqqPn36uCtUAAAAABa59QF5H374oa6//np17dpVXbt2VUJCgv7617861dm9e7eys7MlSV5eXvr+++91zz33qFmzZho8eLCaNWum1NRU1apVy52hAgAAALDAZowxFR1EecrJyVFwcLCys7MVFBRU0eEAAAAAlVZZzq3d2mIBAAAAoHogsQAAAABgGYkFAAAAAMtILAAAAABYRmIBAAAAwDISCwAAAACWkVgAAAAAsIzEAgAAAIBlJBYAAAAALCOxAAAAAGAZiQUAAAAAy0gsAAAAAFhGYgEAAADAMhILAAAAAJaRWAAAAACwjMQCAAAAgGUkFgAAAAAsI7EAAAAAYBmJBQAAAADLSCwAAAAAWEZiAQAAAMAyEgsAAAAAlpFYAAAAALCMxAIAAACAZSQWAAAAACwjsQAAAABgGYkFAAAAAMvcmlj88Y9/VHJysgICAlS7du1STWOM0aRJkxQdHS1/f3916tRJO3fudGeYAAAAACxya2Jx/vx59evXTyNHjiz1NNOmTdPrr7+ut99+W5s3b1ZkZKTuuOMOnTp1yo2RAgAAALDC250znzx5siRp7ty5papvjNH06dP17LPP6re//a0kad68eYqIiNBHH32kxx57zGWa3Nxc5ebmOt5nZ2dLknJycixGDwAAAFRvhefUxpgr1nVrYlFW+/btU0ZGhrp27eoos9vt6tixozZs2FBkYjFlyhRHAnOpmJgYt8YKAAAAVBenTp1ScHBwiXWuqcQiIyNDkhQREeFUHhERoQMHDhQ5zbhx45SSkuJ4X1BQoOPHjyskJEQ2m81yTDk5OYqJiVFaWpqCgoIszw+VG/sDLsX+gMuxT+BS7A+4VGXdH4wxOnXqlKKjo69Yt8yJxaRJk4psIbjU5s2blZiYWNZZO1yeEBhjik0S7Ha77Ha7U1lpO4qXRVBQUKXaCeBe7A+4FPsDLsc+gUuxP+BSlXF/uFJLRaEyJxZjxozR/fffX2Kd2NjYss5WkhQZGSnpYstFVFSUo/zo0aMurRgAAAAArh1lTixCQ0MVGhrqjljUqFEjRUZGasWKFWrVqpWkiyNLrV27VlOnTnXLMgEAAABY59bhZg8ePKht27bp4MGDys/P17Zt27Rt2zadPn3aUad58+ZavHixpIu3QD3xxBN66aWXtHjxYv3www8aMmSIAgICNGDAAHeGWiy73a6JEye63G6F6on9AZdif8Dl2CdwKfYHXKo67A82U5qxo67SkCFDNG/ePJfy1atXq1OnThcDsNk0Z84cDRkyRNLF/hSTJ0/W+++/rxMnTqht27Z65513FB8f764wAQAAAFjk1sQCAAAAQPXg1luhAAAAAFQPJBYAAAAALCOxAAAAAGAZiQUAAAAAy0gsAAAAAFhGYgEAAADAMhILAAAAAJaRWAAAAACwjMQCAAAAgGUkFgAAAAAsI7EAAAAAYBmJBQAAAADLSCwAAAAAWEZiAQAAAMAyEgsAAAAAlpFYAAAAALCMxAIAAACAZSQWANzqzTfflM1mU3x8vOV5LVu2TJMmTbIeVCWwf/9+2Ww2zZ07t8zTHjlyRJMmTdK2bdtcPps0aZJsNpv1AOFkyJAhio2NdSqLjY3VkCFDyjSf2NhY9erVq/wCKycvvfSS/va3v1V0GACucSQWANxq9uzZkqSdO3dq06ZNlua1bNkyTZ48uTzCqtKOHDmiyZMnF5lYDBs2TKmpqZ4PqoqbMGGCFi9eXNFhuA2JBYDSILEA4DZbtmzR9u3b1bNnT0nSrFmzKjgi9/v111+LLDfG6OzZsx6OxlX9+vXVrl27ig6jymnSpIlatWpVoTFcuHBBeXl5FRoDgOqNxAKA2xQmEi+//LKSk5P18ccfu5x4r1mzRjabTWvWrHEqv/xWoCFDhuidd96RJNlsNsdr//79kqRz585p3LhxatSokXx9fVWvXj2NHj1aJ0+edInro48+UlJSkgIDAxUYGKgbb7zRJemZPXu2brjhBvn5+alu3brq06ePdu3a5VRnyJAhCgwM1Pfff6+uXbuqVq1a6tKliyPGMWPGaMaMGWrRooXsdrvmzZsnSdqzZ48GDBig8PBw2e12tWjRwrFuJfn555/18MMPq2nTpgoICFC9evV011136fvvv3fanm3atJEkPfzww47tVHgLWVG3QhUUFGjatGlq3ry57Ha7wsPDNWjQIB06dMipXqdOnRQfH6/Nmzerffv2CggIUOPGjfXyyy+roKDgivGXReG2/c9//qNu3bqpZs2aioqK0ssvvyxJ2rhxo2699VbVrFlTzZo1c2zbsigoKNBbb72lG2+8Uf7+/qpdu7batWunJUuWONUpzbYp6lYoKxYvXqyEhAT5+fmpcePGevPNN50+L/y7+etf/6qnnnpK9erVk91u188//yxJ+te//qUuXbooKChIAQEBuuWWW7Ry5UqneRTuCzt37tQDDzyg4OBgRUREaOjQocrOznbUs9lsOnPmjObNm+fYnzp16lTqdTHG6N1333Vs5zp16ujee+/V3r17neoVd+tYp06dyrQ8ABWHxAKAW5w9e1YLFixQmzZtFB8fr6FDh+rUqVP69NNPr2p+EyZM0L333itJSk1NdbyioqJkjFHv3r316quvauDAgfriiy+UkpKiefPmqXPnzsrNzXXM57nnntODDz6o6OhozZ07V4sXL9bgwYN14MABR50pU6bokUceUcuWLfX555/rjTfe0I4dO5SUlKQ9e/Y4xXX+/Hndfffd6ty5s/7+97873ar1t7/9Te+9956ee+45ffXVV2rfvr1+/PFHtWnTRj/88INee+01/eMf/1DPnj31u9/97oq3eR05ckQhISF6+eWXtXz5cr3zzjvy9vZW27ZttXv3bknSTTfdpDlz5kiS/vCHPzi207Bhw4qd78iRIzV27FjdcccdWrJkiV544QUtX75cycnJyszMdKqbkZGhBx98UA899JCWLFmi7t27a9y4cZo/f36JsV+NCxcu6Le//a169uypv//9745ljR8/XoMHD9bQoUO1ePFixcXFaciQIfr222/LNP8hQ4bo8ccfV5s2bbRw4UJ9/PHHuvvuux3JqlS2bVNetm3bpieeeEJPPvmkFi9erOTkZD3++ON69dVXXeqOGzdOBw8e1IwZM7R06VKFh4dr/vz56tq1q4KCgjRv3jx98sknqlu3rrp16+aSXEhS37591axZMy1atEjPPPOMPvroIz355JOOz1NTU+Xv768ePXo49qd333231Ovz2GOP6YknntDtt9+uv/3tb3r33Xe1c+dOJScn65dffrm6jQTg2mQAwA0++OADI8nMmDHDGGPMqVOnTGBgoGnfvr1TvdWrVxtJZvXq1U7l+/btM5LMnDlzHGWjR482RR22li9fbiSZadOmOZUvXLjQSDIzZ840xhizd+9e4+XlZR588MFi4z5x4oTx9/c3PXr0cCo/ePCgsdvtZsCAAY6ywYMHG0lm9uzZLvORZIKDg83x48edyrt162bq169vsrOzncrHjBlj/Pz8HPWLWv/L5eXlmfPnz5umTZuaJ5980lG+efPmYqedOHGi0zbctWuXkWRGjRrlVG/Tpk1Gkhk/fryjrGPHjkaS2bRpk1Pd6667znTr1q3YOK9G4bZdtGiRo+zChQsmLCzMSDLfffedozwrK8t4eXmZlJSUUs9/3bp1RpJ59tlni61Tlm0zePBg07BhQ6d6DRs2NIMHDy51TIXT2Gw2s23bNqfyO+64wwQFBZkzZ84YY/73d9OhQwenemfOnDF169Y1d911l1N5fn6+ueGGG8zNN9/sKCvcFy7/uxk1apTx8/MzBQUFjrKaNWuWeV2MMSY1NdVIMq+99ppTeVpamvH39ze///3vnda9qGV07NjRdOzYsczLBuB5tFgAcItZs2bJ399f999/vyQpMDBQ/fr10/r1612u+lu1atUqSXK5jaJfv36qWbOm4yrtihUrlJ+fr9GjRxc7r9TUVJ09e9ZlXjExMercuXOxV3yL0rlzZ9WpU8fx/ty5c1q5cqX69OmjgIAA5eXlOV49evTQuXPntHHjxmJjy8vL00svvaTrrrtOvr6+8vb2lq+vr/bs2eNym1ZprV69WpLrtrv55pvVokULl/WNjIzUzTff7FSWkJDg1OJTlIKCAqf1zc/Pv2JsNptNPXr0cLz39vbWb37zG0VFRTn1Z6hbt67Cw8OvGMOlvvzyS0kqcV8o67YpLy1bttQNN9zgVDZgwADl5OTou+++cyq/fN/bsGGDjh8/rsGDBztt74KCAt15553avHmzzpw54zTN3Xff7fQ+ISFB586d09GjRy2vyz/+8Q/ZbDY99NBDTvFERkbqhhtucLkFEkDlRmIBoNz9/PPPWrdunXr27CljjE6ePKmTJ086bmUqHCmqvGRlZcnb21thYWFO5TabTZGRkcrKypIkHTt2TNLFDswlzUuSoqKiXD6Ljo52fF4oICBAQUFBRc7r8nlkZWUpLy9Pb731lnx8fJxehSfQJd1ek5KSogkTJqh3795aunSpNm3apM2bN+uGG2646o7hZV3fkJAQl3p2u/2Kyx86dKjT+hb2RSlJQECA/Pz8nMp8fX1Vt25dl7q+vr46d+7cFedZ6NixY/Ly8lJkZGSxdcq6bcpLUTEVll2+zMtjK7y16N5773XZx6ZOnSpjjI4fP+40zeXfqd1ul6RyGWzgl19+kTFGERERLvFs3LjRbbeTAagY3hUdAICqZ/bs2TLG6LPPPtNnn33m8vm8efP04osvysvLy3HieGk/CKnkE+zLhYSEKC8vT8eOHXNKLowxysjIcHRmLvzs0KFDiomJKXZekpSenu7y2ZEjRxQaGupUVtIzIS7/rE6dOvLy8tLAgQOLvVLeqFGjYuc3f/58DRo0SC+99JJTeWZmpmrXrl3sdCW5dH0vT7iKWt+rNWnSJI0ZM8bxvlatWuUy36sVFham/Px8ZWRkFJk4SJ7bNpfLyMgotuzyJODyfawwprfeeqvY0b8iIiLKI8xSCQ0Nlc1m0/r16x0Jy6UuLfPz83M5DkgX9293bWsA5YsWCwDlKj8/X/PmzVOTJk20evVql9dTTz2l9PR0x60ohSPp7Nixw2k+l47MU6i4K6mFV78v70C8aNEinTlzxvF5165d5eXlpffee6/Y+JOSkuTv7+8yr0OHDmnVqlWlutJenICAAN12223aunWrEhISlJiY6PIqqkWgkM1mczk5++KLL3T48GGnsrJcce7cubMk1223efNm7dq1y9L6Xio2NtZpPePi4splvlere/fuklTivuCpbXO5nTt3avv27U5lH330kWrVqqWbbrqpxGlvueUW1a5dWz/++GOR+1diYqJ8fX3LHFNpWqWK0qtXLxljdPjw4SJjuf766x11Y2NjXY4DP/30k2NgAgDXPlosAJSrL7/8UkeOHNHUqVOLHCIyPj5eb7/9tmbNmqVevXopMjJSt99+u6ZMmaI6deqoYcOGWrlypT7//HOXaQtPQqZOnaru3bvLy8tLCQkJuuOOO9StWzeNHTtWOTk5uuWWW7Rjxw5NnDhRrVq10sCBAyVdPHEZP368XnjhBZ09e9YxxOaPP/6ozMxMTZ48WbVr19aECRM0fvx4DRo0SA888ICysrI0efJk+fn5aeLEiZa2zxtvvKFbb71V7du318iRIxUbG6tTp07p559/1tKlSx39RYrSq1cvzZ07V82bN1dCQoK+/fZbvfLKKy5X05s0aSJ/f399+OGHatGihQIDAxUdHa3o6GiXecbFxenRRx/VW2+9pRo1aqh79+7av3+/JkyYoJiYGKfRgaqS9u3ba+DAgXrxxRf1yy+/qFevXrLb7dq6dasCAgL0//7f/6uwbRMdHa27775bkyZNUlRUlObPn68VK1Zo6tSpCggIKHHawMBAvfXWWxo8eLCOHz+ue++9V+Hh4Tp27Ji2b9+uY8eOlZhMFef666/XmjVrtHTpUkVFRalWrVqlSg5vueUWPfroo3r44Ye1ZcsWdejQQTVr1lR6err+/e9/6/rrr9fIkSMlSQMHDtRDDz2kUaNGqW/fvjpw4ICmTZvmcosjgGtYRfYcB1D19O7d2/j6+pqjR48WW+f+++833t7eJiMjwxhjTHp6urn33ntN3bp1TXBwsHnooYfMli1bXEY2ys3NNcOGDTNhYWHGZrMZSWbfvn3GGGPOnj1rxo4daxo2bGh8fHxMVFSUGTlypDlx4oTL8j/44APTpk0b4+fnZwIDA02rVq1cRlD6y1/+YhISEoyvr68JDg4299xzj9m5c6dTncGDB5uaNWsWuY6SzOjRo4v8bN++fWbo0KGmXr16xsfHx4SFhZnk5GTz4osvOtW5fP1PnDhhHnnkERMeHm4CAgLMrbfeatavX1/kqDkLFiwwzZs3Nz4+PkaSmThxojHGdVQoYy6OGDR16lTTrFkz4+PjY0JDQ81DDz1k0tLSnOp17NjRtGzZ0mV9ihoRyaritm1xMTRs2ND07NmzTMvIz883f/rTn0x8fLzje05KSjJLly51qlOabVOeo0L17NnTfPbZZ6Zly5bG19fXxMbGmtdff92pXuGoUJ9++mmR81m7dq3p2bOnqVu3rvHx8TH16tUzPXv2dKpfuC8cO3bMado5c+Y4/W0ZY8y2bdvMLbfcYgICAoykMo/SNHv2bNO2bVtTs2ZN4+/vb5o0aWIGDRpktmzZ4qhTUFBgpk2bZho3bmz8/PxMYmKiWbVqFaNCAZWIzRhjKiqpAQAAAFA10McCAAAAgGX0sQAAVCl5eXklfl6jRg3VqOHZ62r5+fkq6QYBm80mLy8vD0Zk3bW4nQFULP7iAQBVyuXPS7j8NXToUI/H1KRJkxJjctcIU+50LW5nABXLrS0W69at0yuvvKJvv/1W6enpWrx4sXr37l3iNGvXrlVKSop27typ6Oho/f73v9eIESPcGSYAoArZvHlziZ9XxDMRli5dWuQzGgpV9HM9rsa1uJ0BVCy3JhZnzpzRDTfcoIcfflh9+/a9Yv19+/apR48eGj58uObPn6+vv/5ao0aNUlhYWKmmBwAgMTGxokNwcenzGqqKa3E7A6hYHhsVymazXbHFYuzYsVqyZIl27drlKBsxYoS2b9+u1NTUIqfJzc11ugpUUFCg48ePKyQkpMQn4gIAAAAomTFGp06dUnR09BX7TV1TnbdTU1PVtWtXp7Ju3bpp1qxZunDhgnx8fFymmTJliiZPnuypEAEAAIBqJy0tzeWBrJe7phKLjIwMRUREOJVFREQoLy9PmZmZioqKcplm3LhxSklJcbzPzs5WgwYNlJaWpqCgILfHbNWfVvykuRv2K7/AteHIq4ZNQ5Jj9eQdzSogMgAAAFR3OTk5iomJKVVfsGsqsZDkcvtS4Z1axd3WZLfbZbfbXcqDgoIqRWKRed5LNl9/1SjihjSb7eLnlWE9AAAAUHWVpovBNTXcbGRkpDIyMpzKjh49Km9vb4WEhFRQVO5Vv45/sV+UzWZT/Tr+Ho4IAAAAKLtrKrFISkrSihUrnMr++c9/KjExscj+FVXBfYkxxT40yRij/okxHo4IAAAAKDu3JhanT5/Wtm3btG3bNkkXh5Pdtm2bDh48KOli/4hBgwY56o8YMUIHDhxQSkqKdu3apdmzZ2vWrFl6+umn3RlmhWoUWlNT+yaoxiWNFl42m2rYpKl9ExQbWrPiggMAAABKya19LLZs2aLbbrvN8b6wk/XgwYM1d+5cpaenO5IMSWrUqJGWLVumJ598Uu+8846io6P15ptvVvlnWPRLjFF8vSB1f+PfkqSHb43VQ20bklQAAACg0vDYcyw8JScnR8HBwcrOzq5UnZ5/PZ+n6577SpL04/PdFOB7zfWrBwAAQDVTlnPra6qPBQAAAIDKicQCAAAAgGUkFgAAAAAsI7EAAAAAYBmJBQAAAADLSCwAAAAAWEZiAQAAAMAyEgsAAAAAlpFYAAAAALCMxAIAAACAZSQWAAAAACwjsQAAAABgGYkFAAAAAMtILAAAAABYRmIBAAAAwDISCwAAAACWkVgAAAAAsIzEAgAAAIBlJBYAAAAALCOxAAAAAGAZiQUAAAAAy0gsAAAAAFhGYgEAAADAMhILAAAAAJaRWAAAAACwjMQCAAAAgGUkFgAAAAAsc3ti8e6776pRo0by8/NT69attX79+mLrrlmzRjabzeX1n//8x91hAgAAALDArYnFwoUL9cQTT+jZZ5/V1q1b1b59e3Xv3l0HDx4scbrdu3crPT3d8WratKk7wwQAAABgkVsTi9dff12PPPKIhg0bphYtWmj69OmKiYnRe++9V+J04eHhioyMdLy8vLyKrZubm6ucnBynFwAAAADPclticf78eX377bfq2rWrU3nXrl21YcOGEqdt1aqVoqKi1KVLF61evbrEulOmTFFwcLDjFRMTYzl2AAAAAGXjtsQiMzNT+fn5ioiIcCqPiIhQRkZGkdNERUVp5syZWrRokT7//HPFxcWpS5cuWrduXbHLGTdunLKzsx2vtLS0cl0PAAAAAFfm7e4F2Gw2p/fGGJeyQnFxcYqLi3O8T0pKUlpaml599VV16NChyGnsdrvsdnv5BQwAAACgzNzWYhEaGiovLy+X1omjR4+6tGKUpF27dtqzZ095hwcAAACgHLktsfD19VXr1q21YsUKp/IVK1YoOTm51PPZunWroqKiyjs8AAAAAOXIrbdCpaSkaODAgUpMTFRSUpJmzpypgwcPasSIEZIu9o84fPiwPvjgA0nS9OnTFRsbq5YtW+r8+fOaP3++Fi1apEWLFrkzTAAAAAAWuTWx6N+/v7KysvT8888rPT1d8fHxWrZsmRo2bChJSk9Pd3qmxfnz5/X000/r8OHD8vf3V8uWLfXFF1+oR48e7gwTAAAAgEU2Y4yp6CDKU05OjoKDg5Wdna2goKCKDqfUfj2fp+ue+0qS9OPz3RTg6/Z+9QAAAECJynJu7dYH5AEAAACoHkgsAAAAAFhGYgEAAADAMhILAAAAAJaRWAAAAACwjMQCAAAAgGUkFgAAAAAsI7EAAAAAYBmJBQAAAADLSCwAAAAAWEZiAQAAAMAyEgsAAAAAlpFYAAAAALCMxAIAAACAZSQWAAAAACwjsQAAAABgGYkFAAAAAMtILAAAAABY5l3RAQCoOPsyz+iTLWk6dOKs6tfx132JMWoUWrOiwwIAAJUQiQVQTX2yJU3PLNohm80mY4xsNpveX/tfTe2boH6JMRUdHgAAqGRILIBqaF/mGT2zaIcKjCRjLhb+379jF+1Qm9i6iqXlAgBQhdFqX/5ILNwk9b9ZZap/7kK+4/+b9h6Xn49XeYcEOCz45mCJn7++4ic9cHMDD0UDAJ6Rnn1Wa3Yf07HTuQoLtKtTXJiigv0rOixUgDW7j2rm+r2ySTKSbJJmrP2vHuvQWB2bhZf78qzse0lNQso9HnchsQCqoWOnc2WK+cz83+cAUJUUdSK5dMcRt51I4tqVnn1WM9fvlTFy/BYW/vv+ur2KiwhSZLBfuS2vOu17JBZANRQWaHcc4C5n+7/Pce3gKmvlwPd07fL0iSSubWt2HyvxN3D17qPl1mpf3fY9EgugGuoUF6alO44U+ZmRdFtc1bqC4g6eOomsTle63IHvCZJnTyRx7fNkq3112/dILOA2nvpB5yph2UUF++uxDo31/rq9jr7bNWwXD3yPdWhcpa6euIOnTiKr25Wu8sb3ZE1VOrZy+ycu5clW++q277n9AXnvvvuuGjVqJD8/P7Vu3Vrr168vsf7atWvVunVr+fn5qXHjxpoxY4a7Q4QbrNl9VE99ul3/2HFEG/dm6R87juipT7dr7U9HK+VypIs/sgu+Oag3V+3Rgm8OKj37bLkvw5M6NgvXlD7XO97fGR+p1/vdWOmvrrr7e7r0JLLAyOnf99ftVUb2uXJbVuGVrqIUXumqrPierm2ePLZ6QuGJZFG4/bP66RQXVuLJfnm22le3fc+tLRYLFy7UE088oXfffVe33HKL3n//fXXv3l0//vijGjRwbfbZt2+fevTooeHDh2v+/Pn6+uuvNWrUKIWFhalv377uDBXlyFNX7zx5lbCq3uYQEfS/7dOvdYxbRyPzxNVPT3xPnmzWrqpXuvierm0V0QLj7uMDt39WLu7eHzzZal/d9j23Jhavv/66HnnkEQ0bNkySNH36dH311Vd67733NGXKFJf6M2bMUIMGDTR9+nRJUosWLbRlyxa9+uqrZU4sfj2fJ+/zeZbX4WpdOnxsaeReUj+3jNNea/6165cSf9BX7MpQv9bWH8DmqeVk5Jwr8Uc2NqSm0wl6ecjIOaf1e44p6/R5hQT6qn3TMEWW8zIkz+136/cc05wN+11OJIcmN9KtTUPLZRme+p5+yTlX4knkLznnyvz3X5w6AT4l7uN1AnzKbVmewvd07fPUsbWQJ44PdQJ8NTS5kWZ/vc+xXoUnkkOTG6m2G74jTx3HPbUcT/HE/iBJbRuFKDrYT88t+VGSdEeLCN3WPFwRQX7lui+Ux773awWez5Z1+TZjTHHHXkvOnz+vgIAAffrpp+rTp4+j/PHHH9e2bdu0du1al2k6dOigVq1a6Y033nCULV68WPfdd59+/fVX+fj4uEyTm5ur3Nz/XQ3KyclRTEyMYp74RDXsAeW8VgAAAED1UZD7q9Km36fs7GwFBQWVWNdtfSwyMzOVn5+viIgIp/KIiAhlZGQUOU1GRkaR9fPy8pSZmVnkNFOmTFFwcLDjFRNTfldRAAAAAJSO20eFstmcu6wYY1zKrlS/qPJC48aNU0pKiuN9YYvFN892uWJW5U6b9h6vsGWXJPdCvkZ8+J0kacaDN8nuhnvqM3LOafzi71VUW5jNJk3pc3253OrgqeV8+m2alv+QoYIillPDdrHTc3ndFuDJZXnKjLX/1Tf7jxf7Pd0cW1cjOjaxvBxPbrt/78nU7A37nJrqC5u1y7OpvtAvOee07pJbHTo0DSv32+8kzxwf+J6sO5h1RhOXXrx9o9t1EerUPLxcb33x1LFV8tzxwZM8tY9XxO+Fu48RVXF/KA9tG9et0OXn5OQoanrp6rotsQgNDZWXl5dL68TRo0ddWiUKRUZGFlnf29tbISFFP87cbrfLbnftUR/g660A34obTdednWDLi93Hyy1xxobUdHSKuvwH/bEOjdUwpGalWs7tLSL05Q9Ft7IZSXe0iCy37Xji1wsl3hd+4tcLlWLfulREkF+J92tHBPmVyzp58nu6/boIxdcL1urdRx2dC2+LC3fbkKINQ2pqYDntzyXJyPnfSElLdhzR7S0iyr2DPd+TNYUd3wut2PWL/rnrl3Lt+O6pY6vkueODJ3nqOF7RvxfuOIeoivtDeajI81lJyivD8t0Wqa+vr1q3bq0VK1Y49bFYsWKF7rnnniKnSUpK0tKlS53K/vnPfyoxMbHI/hW4dnVsFq64iCC3/6B7YjmXjh5R1I9seS6rKj4R21MjYnjye5KkyGC/KvVQo8tPWJf/kKEvf8go95HP+J6u3qWjNRUqvFpd3qM1eeoYXhVHzPHUcbwifi8uvfjw6bdp5X7xoSruD9WNW1OglJQUDRw4UImJiUpKStLMmTN18OBBjRgxQtLF25gOHz6sDz74QJI0YsQIvf3220pJSdHw4cOVmpqqWbNmacGCBe4ME27iqR90TyyHH9mr58kTSU99T1WNJ09YJb6nq+XpJ/h64tjq6UTTEzx1HPf074UnLj5Uxf2hunFrYtG/f39lZWXp+eefV3p6uuLj47Vs2TI1bNhQkpSenq6DBw866jdq1EjLli3Tk08+qXfeeUfR0dF68803eYYFrgn8yF49T55IVqUr1J7i6RNWie/palS152UUqmqJpqeO4578vaiKrWVwD7fftDVq1CiNGjWqyM/mzp3rUtaxY0d99913bo4KuHZV1YMqJ5LXrqp6wlrVVMVbJQtVteNDVbodWKqarWVwj4rtDQKgSBxU4UlV+YS1KqmKt0pWZVXpdmAuPqC03PYcCwBA5dApLqzEkwZOWK8Nhbe+2GwXhxO99N/KfKskrn2FFx+KwsUHXIoWCzdJalL08LgV7dLHsrdtXLfChzADcG3ILzAau2iHbDab43lDxhhN7ZugPjfVq+jw8H+SmoTo/jYNtHBLmg6dOKv6dfzVPzFGsaHuH44Y1VdksJ/+UUxrmSSl3NGMfRCSSCwAAJL6JcaoTWxdTlgrgdjQmhp7Z/OKDgPVSKPQmpraN6HYiw8cJ1CIxAIAIIkTVgDF4+IDSoPEAgAAAFfExQdcCZ23AQAAAFhGYgEAAADAMhILAAAAAJaRWAAAAACwjMQCAAAAgGUkFtXM/qwzjv+/vuIn7cs8U0JtAAAAoHRILKqRT7akqdeb/3a8n/Pv/ery2hp9uiWtAqMCAABAVUBiUU3syzyjZxbtUIH5X1m+MSow0thFO7SflgsAAABYQGJRTXyyJU02m63Iz2w2mxbSagEAAAALSCyqiUMnzsoYU+RnxhgdOnHWwxEBAACgKiGxqCbq1/EvscWifh1/D0cEAACAqoTEopq4LzGmxBaL/okxHo4IAAAAVQmJRTXRKLSmpvZNUA2b5FXD5vTv1L4Jig2tWdEhAgAAoBLzrugA4Dn9EmPUJrauFm5J06ETZ1W/jr/6J8aQVAAAAMAyEotqJja0psbe2byiwwAAAEAVw61QAAAAACwjsQAAAABgGYkFAAAAAMtILAAAAABYRmIBAAAAwDISCwAAAACWuTWxOHHihAYOHKjg4GAFBwdr4MCBOnnyZInTDBkyRDabzenVrl07d4YJAAAAwCK3PsdiwIABOnTokJYvXy5JevTRRzVw4EAtXbq0xOnuvPNOzZkzx/He19fXnWECAAAAsMhticWuXbu0fPlybdy4UW3btpUk/fnPf1ZSUpJ2796tuLi4Yqe12+2KjIx0V2gAAAAAypnbboVKTU1VcHCwI6mQpHbt2ik4OFgbNmwocdo1a9YoPDxczZo10/Dhw3X06NFi6+bm5ionJ8fpBQAAAMCz3JZYZGRkKDw83KU8PDxcGRkZxU7XvXt3ffjhh1q1apVee+01bd68WZ07d1Zubm6R9adMmeLowxEcHKyYmJhyWwcAAAAApVPmxGLSpEkunasvf23ZskWSZLPZXKY3xhRZXqh///7q2bOn4uPjddddd+nLL7/UTz/9pC+++KLI+uPGjVN2drbjlZaWVtZVAgAAAGBRmftYjBkzRvfff3+JdWJjY7Vjxw798ssvLp8dO3ZMERERpV5eVFSUGjZsqD179hT5ud1ul91uL/X8AAAAAJS/MicWoaGhCg0NvWK9pKQkZWdn65tvvtHNN98sSdq0aZOys7OVnJxc6uVlZWUpLS1NUVFRZQ0VAAAAgIe4rY9FixYtdOedd2r48OHauHGjNm7cqOHDh6tXr15OI0I1b95cixcvliSdPn1aTz/9tFJTU7V//36tWbNGd911l0JDQ9WnTx93hQoAAADAIrc+IO/DDz/U9ddfr65du6pr165KSEjQX//6V6c6u3fvVnZ2tiTJy8tL33//ve655x41a9ZMgwcPVrNmzZSamqpatWq5M1QAAAAAFtiMMaaigyhPOTk5Cg4OVnZ2toKCgio6HAAAAKDSKsu5tVtbLAAAAABUDyQWAAAAACwjsQAAAABgGYkFAAAAAMtILAAAAABYRmIBAAAAwDISCwAAAACWkVgAAAAAsIzEAgAAAIBlJBYAAAAALCOxAAAAAGAZiQUAAAAAy0gsAAAAAFhGYgEAAADAMhILAAAAAJaRWAAAAACwjMQCAAAAgGUkFgAAAAAsI7EAAAAAYBmJBQAAAADLSCwAAAAAWEZiAQAAAMAyEgsAAAAAlpFYAAAAALCMxAIAAACAZSQWAAAAACwjsQAAAABgmVsTiz/+8Y9KTk5WQECAateuXappjDGaNGmSoqOj5e/vr06dOmnnzp3uDBMAAACARW5NLM6fP69+/fpp5MiRpZ5m2rRpev311/X2229r8+bNioyM1B133KFTp065MVIAAAAAVni7c+aTJ0+WJM2dO7dU9Y0xmj59up599ln99re/lSTNmzdPERER+uijj/TYY4+5TJObm6vc3FzH++zsbElSTk6OxegBAACA6q3wnNoYc8W6bk0symrfvn3KyMhQ165dHWV2u10dO3bUhg0bikwspkyZ4khgLhUTE+PWWAEAAIDq4tSpUwoODi6xzjWVWGRkZEiSIiIinMojIiJ04MCBIqcZN26cUlJSHO8LCgp0/PhxhYSEyGazWY4pJydHMTExSktLU1BQkOX5oXJjf8Cl2B9wOfYJXIr9AZeqrPuDMUanTp1SdHT0FeuWObGYNGlSkS0El9q8ebMSExPLOmuHyxMCY0yxSYLdbpfdbncqK21H8bIICgqqVDsB3Iv9AZdif8Dl2CdwKfYHXKoy7g9XaqkoVObEYsyYMbr//vtLrBMbG1vW2UqSIiMjJV1suYiKinKUHz161KUVAwAAAMC1o8yJRWhoqEJDQ90Rixo1aqTIyEitWLFCrVq1knRxZKm1a9dq6tSpblkmAAAAAOvcOtzswYMHtW3bNh08eFD5+fnatm2btm3bptOnTzvqNG/eXIsXL5Z08RaoJ554Qi+99JIWL16sH374QUOGDFFAQIAGDBjgzlCLZbfbNXHiRJfbrVA9sT/gUuwPuBz7BC7F/oBLVYf9wWZKM3bUVRoyZIjmzZvnUr569Wp16tTpYgA2m+bMmaMhQ4ZIutifYvLkyXr//fd14sQJtW3bVu+8847i4+PdFSYAAAAAi9yaWAAAAACoHtx6KxQAAACA6oHEAgAAAIBlJBYAAAAALCOxAAAAAGAZiQUAAAAAy0gsAAAAAFhGYgEAAADAMhILAAAAAJaRWAAAAACwjMQCAAAAgGUkFgAAAAAsI7EAAAAAYBmJBQAAAADLSCwAAAAAWEZiAQAAAMAyEgsAAAAAlpFYAAAAALCMxAJAuXjzzTdls9kUHx9veV7Lli3TpEmTrAdVCezfv182m01z584t87RHjhzRpEmTtG3bNpfPJk2aJJvNZj3ASmjNmjWy2Wxas2aNW+bv7m377rvvFrk/WNlXrgVz586VzWbT/v37KzoUAG5CYgGgXMyePVuStHPnTm3atMnSvJYtW6bJkyeXR1hV2pEjRzR58uQiE4thw4YpNTXV80FdA2666SalpqbqpptuquhQrkpxiUVUVJRSU1PVs2dPzwdVDnr27KnU1FRFRUVVdCgA3ITEAoBlW7Zs0fbt2x0nPLNmzargiNzv119/LbLcGKOzZ896OBpX9evXV7t27So6jAoRFBSkdu3aKSgoqKJDKVd2u13t2rVTWFiY25fljv04LCxM7dq1k91uL9f5Arh2kFgAsKwwkXj55ZeVnJysjz/+2OXEu7jbUy6/vWPIkCF65513JEk2m83xKrx94ty5cxo3bpwaNWokX19f1atXT6NHj9bJkydd4vroo4+UlJSkwMBABQYG6sYbb3RJembPnq0bbrhBfn5+qlu3rvr06aNdu3Y51RkyZIgCAwP1/fffq2vXrqpVq5a6dOniiHHMmDGaMWOGWrRoIbvdrnnz5kmS9uzZowEDBig8PFx2u10tWrRwrFtJfv75Zz388MNq2rSpAgICVK9ePd111136/vvvnbZnmzZtJEkPP/ywYzsV3kJW1O06BQUFmjZtmpo3by673a7w8HANGjRIhw4dcqrXqVMnxcfHa/PmzWrfvr0CAgLUuHFjvfzyyyooKLhi/GVRuG137typLl26qGbNmgoLC9OYMWNc9qHCbf3++++rWbNmstvtuu666/Txxx871buaW6EKp5k/f75SUlIUGRkpf39/dezYUVu3br3i9AsXLlTXrl0VFRUlf39/tWjRQs8884zOnDnjVG/v3r26//77FR0dLbvdroiICHXp0sXR6hQbG6udO3dq7dq1ju80NjZWUvG3Qv3nP//RAw88oIiICNntdjVo0ECDBg1Sbm5uqdff6n5cUFCgF198UXFxcfL391ft2rWVkJCgN954w1GnqFuhSruvlWb+ACqed0UHAKByO3v2rBYsWKA2bdooPj5eQ4cO1bBhw/Tpp59q8ODBZZ7fhAkTdObMGX322WdOt/JERUXJGKPevXtr5cqVGjdunNq3b68dO3Zo4sSJSk1NVWpqquNq6HPPPacXXnhBv/3tb/XUU08pODhYP/zwgw4cOOCY55QpUzR+/Hg98MADmjJlirKysjRp0iQlJSVp8+bNatq0qaPu+fPndffdd+uxxx7TM888o7y8PMdnf/vb37R+/Xo999xzioyMVHh4uH788UclJyerQYMGeu211xQZGamvvvpKv/vd75SZmamJEycWuw2OHDmikJAQvfzyywoLC9Px48c1b948tW3bVlu3blVcXJxuuukmzZkzRw8//LD+8Ic/OFqL6tevX+x8R44cqZkzZ2rMmDHq1auX9u/frwkTJmjNmjX67rvvFBoa6qibkZGhBx98UE899ZQmTpyoxYsXa9y4cYqOjtagQYPK8I1e2YULF9SjRw/Htt2wYYNefPFFHThwQEuXLnWqu2TJEq1evVrPP/+8atasqXfffVcPPPCAvL29de+991qOZfz48brpppv0l7/8RdnZ2Zo0aZI6deqkrVu3qnHjxsVOt2fPHvXo0UNPPPGEatasqf/85z+aOnWqvvnmG61atcpRr0ePHsrPz9e0adPUoEEDZWZmasOGDY7EePHixbr33nsVHBysd999V5JKvMK/fft23XrrrQoNDdXzzz+vpk2bKj09XUuWLNH58+fL1DpgZT+eNm2aJk2apD/84Q/q0KGDLly4oP/85z9FJvyXK82+ZmX+ADzIAIAFH3zwgZFkZsyYYYwx5tSpUyYwMNC0b9/eqd7q1auNJLN69Wqn8n379hlJZs6cOY6y0aNHm6IOT8uXLzeSzLRp05zKFy5caCSZmTNnGmOM2bt3r/Hy8jIPPvhgsXGfOHHC+Pv7mx49ejiVHzx40NjtdjNgwABH2eDBg40kM3v2bJf5SDLBwcHm+PHjTuXdunUz9evXN9nZ2U7lY8aMMX5+fo76Ra3/5fLy8sz58+dN06ZNzZNPPuko37x5c7HTTpw40Wkb7tq1y0gyo0aNcqq3adMmI8mMHz/eUdaxY0cjyWzatMmp7nXXXWe6detWbJxXo3DbvvHGG07lf/zjH40k8+9//9tRJsn4+/ubjIwMR1leXp5p3ry5+c1vfuMoK25fK0nhNDfddJMpKChwlO/fv9/4+PiYYcOGOcou37aXKygoMBcuXDBr1641ksz27duNMcZkZmYaSWb69OklxtKyZUvTsWNHl/Ki9pXOnTub2rVrm6NHj5ZyTYtmdT/u1auXufHGG0tcxpw5c4wks2/fPkdZafe10swfQMXjVigAlsyaNUv+/v66//77JUmBgYHq16+f1q9frz179pTrsgqv/A4ZMsSpvF+/fqpZs6ZWrlwpSVqxYoXy8/M1evToYueVmpqqs2fPuswrJiZGnTt3dszrUn379i1yXp07d1adOnUc78+dO6eVK1eqT58+CggIUF5enuPVo0cPnTt3Ths3biw2try8PL300ku67rrr5OvrK29vb/n6+mrPnj0ut2mV1urVqyW5brubb75ZLVq0cFnfyMhI3XzzzU5lCQkJTi0+RSkoKHBa3/z8/FLF9+CDDzq9HzBggFPchbp06aKIiAjHey8vL/Xv318///yzyy1dV2PAgAFOt5A1bNhQycnJLnFcbu/evRowYIAiIyPl5eUlHx8fdezYUZIc31ndunXVpEkTvfLKK3r99de1detWS7eW/frrr1q7dq3uu+++cul3YWU/vvnmm7V9+3aNGjVKX331lXJyckq93NLsa1bmD8BzSCwAXLWff/5Z69atU8+ePWWM0cmTJ3Xy5EnHLSmFI0WVl6ysLHl7e7ucRNlsNkVGRiorK0uSdOzYMUkl3xZUWLeoEWqio6MdnxcKCAgotjPw5fPIyspSXl6e3nrrLfn4+Di9evToIUnKzMwsNraUlBRNmDBBvXv31tKlS7Vp0yZt3rxZN9xww1V3qC3r+oaEhLjUs9vtV1z+0KFDnda3sC9KSby9vV2WFxkZ6RT35eWlqXs1ipt/SfM+ffq02rdvr02bNunFF1/UmjVrtHnzZn3++eeS5NhmNptNK1euVLdu3TRt2jTddNNNCgsL0+9+9zudOnWqzLGeOHFC+fn5Je7nZWFlPx43bpxeffVVbdy4Ud27d1dISIi6dOmiLVu2XHG5pdnXrMwfgOfQxwLAVZs9e7aMMfrss8/02WefuXw+b948vfjii/Ly8pKfn58kuXQoLekE+3IhISHKy8vTsWPHnJILY4wyMjIcnZkLPzt06JBiYmKKnZckpaenu3x25MgRp/4Gkkp8bsHln9WpU0deXl4aOHBgsa0mjRo1KnZ+8+fP16BBg/TSSy85lWdmZqp27drFTleSS9f38hPRotb3ak2aNEljxoxxvK9Vq9YVp8nLy1NWVpbTCWZGRoYk15POwvKiyoo6QS2r4uZf0rxXrVqlI0eOaM2aNY5WCklF3v/fsGFDxwACP/30kz755BNNmjRJ58+f14wZM8oUa926deXl5VUuLTWStf3Y29tbKSkpSklJ0cmTJ/Wvf/1L48ePV7du3ZSWlqaAgABLsbl7/gDKBy0WAK5Kfn6+5s2bpyZNmmj16tUur6eeekrp6en68ssvJckxss2OHTuc5rNkyRKXeRd2OL386njh1e/58+c7lS9atEhnzpxxfN61a1d5eXnpvffeKzb+pKQk+fv7u8zr0KFDWrVqVamutBcnICBAt912m7Zu3aqEhAQlJia6vEo6UbXZbC6dbr/44gsdPnzYqay47VSUzp07S3Lddps3b9auXbssre+lYmNjndYzLi6uVNN9+OGHTu8/+ugjSRdHDbrUypUr9csvvzje5+fna+HChWrSpEm5XLlfsGCBjDGO9wcOHNCGDRtc4rhU4Qn55d/Z+++/X+KymjVrpj/84Q+6/vrr9d133znKS9MyJMkxatWnn35apgS9tK52P65du7buvfdejR49WsePHy/3B+K5e/4Arh4tFgCuypdffqkjR45o6tSpRZ50xcfH6+2339asWbPUq1cvRUZG6vbbb9eUKVNUp04dNWzYUCtXrnTcLnKp66+/XpI0depUde/eXV5eXkpISNAdd9yhbt26aezYscrJydEtt9ziGBWqVatWGjhwoKSLJ7fjx4/XCy+8oLNnz+qBBx5QcHCwfvzxR2VmZmry5MmqXbu2JkyYoPHjx2vQoEF64IEHlJWVpcmTJ8vPz6/EUZtK44033tCtt96q9u3ba+TIkYqNjdWpU6f0888/a+nSpU4jBV2uV69emjt3rpo3b66EhAR9++23euWVV1xOnJs0aSJ/f399+OGHatGihQIDAxUdHa3o6GiXecbFxenRRx/VW2+9pRo1aqh79+6OUaFiYmL05JNPWlpfK3x9ffXaa6/p9OnTatOmjWNUqO7du+vWW291qhsaGqrOnTtrwoQJjlGh/vOf/7gMOXu1jh49qj59+mj48OHKzs7WxIkT5efnp3HjxhU7TXJysurUqaMRI0Zo4sSJ8vHx0Ycffqjt27c71duxY4fGjBmjfv36qWnTpvL19dWqVau0Y8cOPfPMM456119/vT7++GMtXLhQjRs3lp+fn+Nv4nKvv/66br31VrVt21bPPPOMfvOb3+iXX37RkiVL9P7775eqxagkpd2P77rrLsXHxysxMVFhYWE6cOCApk+froYNGzqNrna13D1/AOWkYvuOA6isevfubXx9fUscjeb+++833t7ejlF80tPTzb333mvq1q1rgoODzUMPPWS2bNniMtJNbm6uGTZsmAkLCzM2m81pJJmzZ8+asWPHmoYNGxofHx8TFRVlRo4caU6cOOGy/A8++MC0adPG+Pn5mcDAQNOqVSuXEZT+8pe/mISEBOPr62uCg4PNPffcY3bu3OlUZ/DgwaZmzZpFrqMkM3r06CI/27dvnxk6dKipV6+e8fHxMWFhYSY5Odm8+OKLTnUuX/8TJ06YRx55xISHh5uAgABz6623mvXr15uOHTu6jBa0YMEC07x5c+Pj42MkmYkTJxpjih65KD8/30ydOtU0a9bM+Pj4mNDQUPPQQw+ZtLQ0p3odO3Y0LVu2dFmfwYMHm4YNGxa5rlercNvu2LHDdOrUyfj7+5u6deuakSNHmtOnTzvVLdzW7777rmnSpInx8fExzZs3Nx9++KFTPSujQv31r381v/vd70xYWJix2+2mffv2ZsuWLU51i9q2GzZsMElJSSYgIMCEhYWZYcOGme+++87pu/3ll1/MkCFDTPPmzU3NmjVNYGCgSUhIMH/6059MXl6eY1779+83Xbt2NbVq1TKSHNu8uBHEfvzxR9OvXz8TEhJifH19TYMGDcyQIUPMuXPnSr3+Vvfj1157zSQnJ5vQ0FBHDI888ojZv3+/o05xo0KVZl8rzfwBVDybMZe0+QIA4EFDhgzRZ599ptOnT1+xrs1m0+jRo/X222+Xexxr1qzRbbfdpk8//bRcnocBANURfSwAAAAAWEYfCwBAlWWMueKzNLy8vDwUjedd+oT4otSoUUM1anCNEUD54FYoAECVVXiLU0nmzJnj8uDAqqKkYZIlafDgwZo7d65nggFQ5bk1sVi3bp1eeeUVffvtt0pPT9fixYvVu3fvEqdZu3atUlJStHPnTkVHR+v3v/+9RowY4a4QAQBV2KlTp7R79+4S6zRq1KhcnoFxLbrSA+RCQ0MdQ0EDgFVuvRXqzJkzuuGGG/Twww+rb9++V6y/b98+9ejRQ8OHD9f8+fP19ddfa9SoUQoLCyvV9AAAXKpWrVpKTEys6DAqTHVedwCe57FboWw22xVbLMaOHaslS5Zo165djrIRI0Zo+/btSk1NLXKa3Nxcpyf5FhQU6Pjx4woJCbliEzAAAACA4hljdOrUKUVHR1+xT9Y11Xk7NTVVXbt2dSrr1q2bZs2apQsXLsjHx8dlmilTpmjy5MmeChEAAACodtLS0lwe1Hq5ayqxyMjIUEREhFNZRESE8vLylJmZqaioKJdpxo0bp5SUFMf77OxsNWjQQGlpaQoKCnJ7zFb9f59u11c7M1RQRLtRDZvUrWWkXul3g+cDAwAAQLWXk5OjmJgY1apV64p1r6nEQnIdwaLwTq3ibmuy2+2y2+0u5UFBQZUisWhcL0xe/z2lojILrxo2Na4XVinWAwAAAFVXaboYXFODV0dGRiojI8Op7OjRo/L29q6yI3bclxij4rq5GGPU//9v797Do6gO/49/llw2CZAVcg+GJFAJl4giUQjKRVAQhCoiiiiCChWQVoi2FikCVqV4oWi9IMq1oEVFqgii+cq1BRGsFEVEVCCoCYEACdfEhPP7g1+2WTYJCbO7IZv363n2gZ09M3NmcjI5n50zM2kJPq4RAAAAUH0XVLBIT09XZmamy7SPP/5YaWlp5V5f4Q+SI+tr2oC2qlcmBAbYbKpnk6YNaKukyPo1VzkAAACgirwaLI4dO6atW7dq69atks7cTnbr1q3KysqSdOb6iLvvvttZfuTIkdq7d68yMjK0Y8cOzZkzR7Nnz9bDDz/szWrWuIFpCVr+u2uc7++5JkmrHuqmgZytAAAAQC3h1WsstmzZ4vLE09KLrEuf9Jmdne0MGdKZhxStWLFC48aN00svvaT4+Hi98MILdeIZFokR/zszkXF9C4UFX3CXvwAAAAAV8mrvtVu3bhVePyBJ8+bNc5vWtWtX/ec///FirQAAAAB42gV1jQUAAACA2olgAQAAAMAyggUAAAAAywgWAAAAACwjWAAAAACwjGABAAAAwDKCBQAAAADLCBYAAAAALCNYAAAAALCMYAEAAADAMoIFAAAAAMsIFgAAAAAsI1gAAAAAsIxgAQAAAMAyggUAAAAAywgWAAAAACwjWAAAAACwjGABAAAAwDKCBQAAAADLCBYAAAAALCNYAAAAALCMYAEAAADAMoIFAAAAAMsIFgAAAAAsI1gAAAAAsIxgAQAAAMAyggUAAAAAy7weLF5++WUlJycrJCRE7du31/r16yssu2bNGtlsNrfXN9984+1qAgAAALDAq8Fi8eLFGjt2rCZMmKAvvvhCnTt3Vu/evZWVlVXpfDt37lR2drbzdckll3izmgAAAAAs8mqwmD59uu677z4NHz5crVq10owZM5SQkKBXXnml0vmio6MVGxvrfAUEBFRYtrCwUAUFBS4vAAAAAL7ltWBRVFSkzz//XD179nSZ3rNnT23YsKHSedu1a6e4uDj16NFDq1evrrTs1KlT5XA4nK+EhATLdQcAAABQPV4LFgcPHlRJSYliYmJcpsfExCgnJ6fceeLi4jRr1iwtWbJE7777rlJSUtSjRw+tW7euwvWMHz9e+fn5zte+ffs8uh0AAAAAzi3Q2yuw2Wwu740xbtNKpaSkKCUlxfk+PT1d+/bt07PPPqsuXbqUO4/dbpfdbvdchQEAAABUm9fOWERGRiogIMDt7ERubq7bWYzKdOzYUbt27fJ09QAAAAB4kNeCRXBwsNq3b6/MzEyX6ZmZmerUqVOVl/PFF18oLi7O09UDAAAA4EFeHQqVkZGhIUOGKC0tTenp6Zo1a5aysrI0cuRISWeuj/jpp5+0YMECSdKMGTOUlJSkNm3aqKioSAsXLtSSJUu0ZMkSb1YTAAAAgEVeDRa333678vLy9Pjjjys7O1upqalasWKFEhMTJUnZ2dkuz7QoKirSww8/rJ9++kmhoaFq06aNli9frj59+nizmgAAAAAsshljTE1XwpMKCgrkcDiUn5+v8PDwmq5OlZ0oKlbrxz6SJH39eC+FBXv9unoAAACgUtXpW3v1AXkAAAAA6gaCBQAAAADLCBYAAAAALCNYAAAAALCMYAEAAADAMoIFAAAAAMsIFgAAAAAsI1gAAAAAsIxgAQAAAMAyggUAAAAAywgWAAAAACwjWAAAAACwjGABAAAAwDKCBQAAAADLCBYAAAAALCNYAAAAALCMYAEAAADAMoIFAAAAAMsIFgAAAAAsI1gAAAAAsCywpisAAACqbvfB43pryz79ePikLm4UqtvSEpQcWb+mqwV4DG289iJYeMnG7/OqVf7ULyXO/2/64ZBCggI8XSUAQC23ZmeuZq3/QTZJRpJN0sy13+v+Ls3UtUV0DdcOsI427i69eURNV6HKGAoFAEAtkJ1/UrPW/yBjpNNGLv++uu4H5eSfqukqApbQxms/zlgAVZSdf1Jrdh7QgWOFimpgV7eUKMU5Qmu6WgDqiDU7Dzi/xT2bTdLqnbm646qmPq4V6hJv/x2kjdd+BAugCso7Nbts2891+tQsAFfe7nQdOFZYbodLOnNcOnCs0GPr8jV//OLG37bJF38H/bmN1xUEC9R63j54lz01W3rAK/331XU/KCUmXLGOEI+tD0Dt44tOV1QDe6Xf5kY1sHtkPaV81TH25Rc3/rhNvuCrv4O+buPwPK9fY/Hyyy8rOTlZISEhat++vdavX19p+bVr16p9+/YKCQlRs2bNNHPmTG9XEbXYmp25eujt/+qDbT/r0x/y9MG2n/XQ2//V2m9zPbiOM6dmy1N6ahYXjuz8k3rzsyy9sGqX3vwsS9n5J2v1enDh89W48G4pUZV+m3ttiuc6rL44tkq+HVPvj9tUuj5vH4t89XfQl20c3uHVMxaLFy/W2LFj9fLLL+vqq6/Wq6++qt69e+vrr79W06buY+R2796tPn36aMSIEVq4cKH+/e9/a/To0YqKitKAAQO8WVXUQr76BoVTs57hi28KffUtob99GwlrfDUuPM4Rqvu7NNOr684c9ySpnu3Meu/v0sxjZ059eZbWV/vOH7fpzLp8cyzy1d9BX7XxmuBvQ+Mq4tVgMX36dN13330aPny4JGnGjBn66KOP9Morr2jq1Klu5WfOnKmmTZtqxowZkqRWrVppy5YtevbZZ6sdLE4UFSuwqNjyNpyvsrePrYrCMuULqzlvXfV/O/ZXevDO3JGjge0TLK+nUVhQpetpFBZU7Z/3hSKn4JTW7zqgvGNFimgQrM6XRCk23PMH7vW7Dmjuhj1uf/zu7ZSsay6J9Mg6cgpOVdpxSIqorxgPbJuv1lMTfNUefMkX27S/4FSlna79Bac8dozokByheEeIHnv/a0nS9a1idG3LaMWEh3hsHb46tkq+23f+uE2+PBb58u+gL9p4qdryN/BEDfZnq7t+mzGmovZvSVFRkcLCwvT222+rf//+zukPPvigtm7dqrVr17rN06VLF7Vr107PP/+8c9rSpUt122236cSJEwoKCnKbp7CwUIWF/0vKBQUFSkhIUMLYt1TPHubhrQIAAADqjtOFJ7Rvxm3Kz89XeHh4pWW9do3FwYMHVVJSopiYGJfpMTExysnJKXeenJyccssXFxfr4MGD5c4zdepUORwO5yshwTPfOAAAAACoOq/fFcpmc73cxxjjNu1c5cubXmr8+PHKyMhwvi89Y/HZhB7nTFXetOmHQzW27soU/lKikYv+I0maeecVsnvxCd/eXldOwSk9uvRLlXfOzWaTpva/1KNDUvYXnNK6MqdMu1wS5bUhL1l5xzVp2ZnTwL1ax6hby2iPnp59+/N9WvlVjk6Xs+/q2aQbUmM9Nixg5trv9dmeQxX+nK5KaqyRXZtbXo+vtsmX+85XbdyX2yT9/2EB/97jHFZROobak0PjfL1N/9p1UHM27HYZ6uDpbfIVXx9bfbHv/HGbfN3GJd/+HfSm2vY3sEOzxh6py/kqKChQ3IyqlfVasIiMjFRAQIDb2Ync3Fy3sxKlYmNjyy0fGBioiIjyH2dut9tlt7vffiwsOFBhwTV3N90QL3bYPcUeFOCzenpjXUkR9Z0XeZ198L6/SzMlRtT36PoSI+priIeXWZ7Si/FKZe7Yr4937PfoxXiHT/xS6Rjgwyd+8djPKyY8pNKxuTHhIR5Z13WtYvThV+WfDTWSrm8VW6vWI0kbv8+rdN9t+D7PIxeB+rI9ZOef1NwNe1zWV/rHfc6G3Upt4vDIBZq+3CZJuq51jFKbOLR6Z67z4sxrU6Jr5cWmvj62+mLf+eM2+fJYVMpXfwe9rbb9DazJ/qwkFVdj/V6raXBwsNq3b6/MzEyXaywyMzN10003lTtPenq6li1b5jLt448/VlpaWrnXVwBdW0QrJSbcL/6YS653LilV2umqrfcK75YSpWXbfi73M0/ePrDs3UTK6zh4qk34aj2S7+7E4sv24Ks75tTE/fBjHSF+81RgXx9bfbHv/G2bfHks8jf++DfwQuHVCJSRkaEhQ4YoLS1N6enpmjVrlrKysjRy5EhJZ4Yx/fTTT1qwYIEkaeTIkXrxxReVkZGhESNGaOPGjZo9e7befPNNb1YTtZw//TH3VafLlwc6X/7x81XHwVfr8dUfP1+2B1+Fpbr2x9wb/OnYWsrftsnfvlzzFX/9G3gh8GqwuP3225WXl6fHH39c2dnZSk1N1YoVK5SYmChJys7OVlZWlrN8cnKyVqxYoXHjxumll15SfHy8XnjhBZ5hgTqjJu4V7osDnS//+Pmq4+CL9fjb2R7Jd2Gprv0xR93lb2HJF/z5b2BN89rtZmtKQUGBHA5HlW6J5U0bv8+rsXVX5tQvJbpn3mZJ0txhV3r1Gos9ecc1/t0vJUl9Lo3Vda1i/PJhMJ705mdZ+mDbzxVeUNa3bbxH/4Dk5J+qEwe62mztt7kV/vHz9MP4fNEesvNP6qG3/1vhhYzTB17u0XXSxgFUpLYcH9Kbl3+dsa9Up29NsPCSuh4sSi9ALu/JmTyZuGK+7nShdqgtf/yqypdhCQBqu9oULGr2MnP4JV9dgOyPGL6B8vjbUIe6NCwAAOoSgoWX1HS6rEjZx7J3aNbYK7cwm7byG9Wz2VRSztfu9Ww2fZt7VP2vaOLx9fqL9OYRGnRlUy3esk8/Hj6pixuF6va0BCVF1v5b/AFlcRwAAP9CsIDH/Xj4pCoaYWeM0Y+HT/q4RrVPUmR9PXJDy5quBgAAQJXVq+kKwP9c3Ci0wiel22w2XdyIC7gBAAD8DcECHndbWkKlZyxuT0vwcY0AAADgbQQLeFxyZH1NG9BW9WxSQD2by7/TBrTlWgEAAAA/xDUWdcyevOPO/0/P/FZ3dkhUshc6+gPTEnRlUmMuQAYAAKgjeI5FHfLWln3645Jtzlu/BthsMjKaNqCtBjI8CQAAAGepTt+aoVB1xO6Dx11ChSSVGKPTRnpkyTbtOXi84pkBAACAcyBY1BFvbdlX6Z2aFm/Z5+MaAQAAwJ8QLOoIni0BAAAAbyJY1BE8WwIAAADeRLCoI3i2BAAAALyJYFFH8GwJAAAAeBPPsahDeLYEAAAAvIVgUcckRdbXIze0rOlqAAAAwM8wFAoAAACAZQQLAAAAAJYRLAAAAABYRrAAAAAAYBnBAgAAAIBlBAsAAAAAlhEsAAAAAFhGsAAAAABgGcECAAAAgGUECwAAAACWeTVYHD58WEOGDJHD4ZDD4dCQIUN05MiRSucZNmyYbDaby6tjx47erCYAAAAAiwK9ufDBgwfrxx9/1MqVKyVJv/nNbzRkyBAtW7as0vluuOEGzZ071/k+ODjYm9UEAAAAYJHXgsWOHTu0cuVKffrpp+rQoYMk6bXXXlN6erp27typlJSUCue12+2KjY31VtUAAAAAeJjXhkJt3LhRDofDGSokqWPHjnI4HNqwYUOl865Zs0bR0dFq0aKFRowYodzc3ArLFhYWqqCgwOUFAAAAwLe8FixycnIUHR3tNj06Olo5OTkVzte7d28tWrRIq1at0nPPPafNmzere/fuKiwsLLf81KlTnddwOBwOJSQkeGwbAAAAAFRNtYPF5MmT3S6uPvu1ZcsWSZLNZnOb3xhT7vRSt99+u2688UalpqaqX79++vDDD/Xtt99q+fLl5ZYfP3688vPzna99+/ZVd5MAAAAAWFTtayzGjBmjQYMGVVomKSlJ27Zt0/79+90+O3DggGJiYqq8vri4OCUmJmrXrl3lfm6322W326u8PAAAAACeV+1gERkZqcjIyHOWS09PV35+vj777DNdddVVkqRNmzYpPz9fnTp1qvL68vLytG/fPsXFxVW3qgAAAAB8xGvXWLRq1Uo33HCDRowYoU8//VSffvqpRowYob59+7rcEaply5ZaunSpJOnYsWN6+OGHtXHjRu3Zs0dr1qxRv379FBkZqf79+3urqgAAAAAs8uoD8hYtWqRLL71UPXv2VM+ePdW2bVv9/e9/dymzc+dO5efnS5ICAgL05Zdf6qabblKLFi00dOhQtWjRQhs3blTDhg29WVUAAAAAFtiMMaamK+FJBQUFcjgcys/PV3h4eE1XBwAAAKi1qtO39uoZCwAAAAB1A8ECAAAAgGUECwAAAACWESwAAAAAWEawAAAAAGAZwQIAAACAZQQLAAAAAJYRLAAAAABYRrAAAAAAYBnBAgAAAIBlBAsAAAAAlhEsAAAAAFhGsAAAAABgGcECAAAAgGUECwAAAACWESwAAAAAWEawAAAAAGAZwQIAAACAZQQLAAAAAJYRLAAAAABYRrAAAAAAYBnBAgAAAIBlBAsAAAAAlhEsAAAAAFhGsAAAAABgGcECAAAAgGUECwAAAACWeTVYPPnkk+rUqZPCwsJ00UUXVWkeY4wmT56s+Ph4hYaGqlu3btq+fbs3qwkAAADAIq8Gi6KiIg0cOFCjRo2q8jxPP/20pk+frhdffFGbN29WbGysrr/+eh09etSLNQUAAABgRaA3Fz5lyhRJ0rx586pU3hijGTNmaMKECbrlllskSfPnz1dMTIzeeOMN3X///W7zFBYWqrCw0Pk+Pz9fklRQUGCx9gAAAEDdVtqnNsacs6xXg0V17d69Wzk5OerZs6dzmt1uV9euXbVhw4Zyg8XUqVOdAaashIQEr9YVAAAAqCuOHj0qh8NRaZkLKljk5ORIkmJiYlymx8TEaO/eveXOM378eGVkZDjfnz59WocOHVJERIRsNpvlOhUUFCghIUH79u1TeHi45eWhdqM9oCzaA85Gm0BZtAeUVVvbgzFGR48eVXx8/DnLVjtYTJ48udwzBGVt3rxZaWlp1V2009mBwBhTYUiw2+2y2+0u06p6oXh1hIeH16pGAO+iPaAs2gPORptAWbQHlFUb28O5zlSUqnawGDNmjAYNGlRpmaSkpOouVpIUGxsr6cyZi7i4OOf03Nxct7MYAAAAAC4c1Q4WkZGRioyM9EZdlJycrNjYWGVmZqpdu3aSztxZau3atZo2bZpX1gkAAADAOq/ebjYrK0tbt25VVlaWSkpKtHXrVm3dulXHjh1zlmnZsqWWLl0q6cwQqLFjx+qpp57S0qVL9dVXX2nYsGEKCwvT4MGDvVnVCtntdk2aNMltuBXqJtoDyqI94Gy0CZRFe0BZdaE92ExV7h11noYNG6b58+e7TV+9erW6det2pgI2m+bOnathw4ZJOnM9xZQpU/Tqq6/q8OHD6tChg1566SWlpqZ6q5oAAAAALPJqsAAAAABQN3h1KBQAAACAuoFgAQAAAMAyggUAAAAAywgWAAAAACwjWAAAAACwjGABAAAAwDKCBQAAAADLCBYAAAAALCNYAAAAALCMYAEAAADAMoIFAAAAAMsIFgAAAAAsI1gAAAAAsIxgAQAAAMAyggUAAAAAywgWAAAAACwjWAAAAACwjGAB1BEvvPCCbDabUlNTLS9rxYoVmjx5svVK1QJ79uyRzWbTvHnzqj3vzz//rMmTJ2vr1q1un02ePFk2m816BS8gNpvtvNrFmjVrZLPZ9M4773isLqXLXLNmjceWWVfs2bNHN954oxo3biybzaaxY8f6bN2lvxcHDx48Z9mkpCT17dvXB7UCUFUEC6COmDNnjiRp+/bt2rRpk6VlrVixQlOmTPFEtfzazz//rClTppQbLIYPH66NGzf6vlLAOYwbN06bNm3SnDlztHHjRo0bN66mqwSgliBYAHXAli1b9N///lc33nijJGn27Nk1XCPvO3HiRLnTjTE6efKkj2vj7uKLL1bHjh1ruhrwoIraXG3z1Vdf6aqrrtLNN9+sjh07KjEx8byXdSH8rllxoRwvgNqCYAHUAaVB4i9/+Ys6deqkf/zjH26doIqGjpw9FGjYsGF66aWXJJ0Z+lL62rNnjyTp1KlTGj9+vJKTkxUcHKwmTZrogQce0JEjR9zq9cYbbyg9PV0NGjRQgwYNdPnll7uFnjlz5uiyyy5TSEiIGjdurP79+2vHjh0uZYYNG6YGDRroyy+/VM+ePdWwYUP16NHDWccxY8Zo5syZatWqlex2u+bPny9J2rVrlwYPHqzo6GjZ7Xa1atXKuW2V+e6773TPPffokksuUVhYmJo0aaJ+/frpyy+/dNmfV155pSTpnnvuce6n0qFC5Q2FOn36tJ5++mm1bNlSdrtd0dHRuvvuu/Xjjz+6lOvWrZtSU1O1efNmde7cWWFhYWrWrJn+8pe/6PTp0+esf3W99tpratGihex2u1q3bq033nhDw4YNU1JS0jnn/eqrr3TTTTepUaNGCgkJ0eWXX+7c/2c7deqUMjIyFBsbq9DQUHXt2lVffPGFS5ktW7Zo0KBBSkpKUmhoqJKSknTHHXdo7969lrez9Hdg4cKF56xHZW3u0KFDGj16tJo0aaLg4GA1a9ZMEyZMUGFhocsyTp8+rb/97W+6/PLLFRoaqosuukgdO3bU+++/71Ju8eLFSk9PV/369dWgQQP16tXLrT5VkZWVpbvuusulvT/33HPONlO6/d99950+/PBDt9/tcykdmvTuu++qXbt2CgkJ0ZQpUyodTljR8Ll9+/bplltuUXh4uBwOh+666y4dOHCg3PUuXbpUbdu2VUhIiJo1a6YXXnjBrUxBQYEefvhhl+PS2LFjdfz4cbf6VHS8AFAFBoBfO3HihHE4HObKK680xhjz+uuvG0lm3rx5LuVWr15tJJnVq1e7TN+9e7eRZObOnWuMMea7774zt956q5FkNm7c6HydOnXKnD592vTq1csEBgaaiRMnmo8//tg8++yzpn79+qZdu3bm1KlTzuVOnDjRSDK33HKLefvtt83HH39spk+fbiZOnOgs89RTTxlJ5o477jDLly83CxYsMM2aNTMOh8N8++23znJDhw41QUFBJikpyUydOtV88skn5qOPPjLGGCPJNGnSxLRt29a88cYbZtWqVearr74y27dvNw6Hw1x66aVmwYIF5uOPPzYPPfSQqVevnpk8eXKF22+MMWvXrjUPPfSQeeedd8zatWvN0qVLzc0332xCQ0PNN998Y4wxJj8/38ydO9dIMn/605+c+2nfvn3GGGMmTZpkzj4E/+Y3vzGSzJgxY8zKlSvNzJkzTVRUlElISDAHDhxwluvatauJiIgwl1xyiZk5c6bJzMw0o0ePNpLM/Pnzq9QuqurVV181ksyAAQPMBx98YBYtWmRatGhhEhMTTWJioktZSWbSpEnO9998841p2LChad68uVmwYIFZvny5ueOOO4wkM23aNGe50raXkJBgbrrpJrNs2TKzcOFC86tf/cqEh4eb77//3ln27bffNo899phZunSpWbt2rfnHP/5hunbtaqKiolz2UUXtuTLVqUdFbe7kyZOmbdu2pn79+ubZZ581H3/8sZk4caIJDAw0ffr0cVnfkCFDjM1mM8OHDzfvvfee+fDDD82TTz5pnn/+eWeZJ5980thsNnPvvfeaDz74wLz77rsmPT3d1K9f32zfvr3K25abm2uaNGlioqKizMyZM83KlSvNmDFjjCQzatQoY8yZNrtx40YTGxtrrr76apff7apITEw0cXFxplmzZmbOnDlm9erV5rPPPiv3d6jU2W2m9PciMTHR/P73vzcfffSRmT59uvMYUlRU5LK+Jk2amKZNm5o5c+aYFStWmDvvvNNIMs8884yz3PHjx83ll19uIiMjzfTp083//d//meeff944HA7TvXt3c/r0aZf6lHe8AFA1BAvAzy1YsMBIMjNnzjTGGHP06FHToEED07lzZ5dyVQ0WxhjzwAMPuHWKjTFm5cqVRpJ5+umnXaYvXrzYSDKzZs0yxhjzww8/mICAAHPnnXdWWO/Dhw+b0NBQt85YVlaWsdvtZvDgwc5pQ4cONZLMnDlz3JYjyTgcDnPo0CGX6b169TIXX3yxyc/Pd5k+ZswYExIS4ixfWaeoVHFxsSkqKjKXXHKJGTdunHP65s2bK5z37GCxY8cOI8mMHj3apdymTZuMJPPoo486p3Xt2tVIMps2bXIp27p1a9OrV68K61ldJSUlJjY21nTo0MFl+t69e01QUNA5g8WgQYOM3W43WVlZLuV69+5twsLCzJEjR4wx/2t7V1xxhUsnb8+ePSYoKMgMHz68wjoWFxebY8eOmfr167t0yK0Ei6rUo6I2N3PmTCPJvPXWWy7Tp02bZiSZjz/+2BhjzLp164wkM2HChArrk5WVZQIDA81vf/tbl+lHjx41sbGx5rbbbqvytv3xj38st82MGjXK2Gw2s3PnTue0xMREc+ONN1Z52WXnCwgIcFmWMZX/DlUULMr+HhljzKJFi4wks3DhQpf12Ww2s3XrVpey119/vQkPDzfHjx83xhgzdepUU69ePbN582aXcu+8846RZFasWOFSn/KOFwCqhqFQgJ+bPXu2QkNDNWjQIElSgwYNNHDgQK1fv167du3y6LpWrVol6cwwkbIGDhyo+vXr65NPPpEkZWZmqqSkRA888ECFy9q4caNOnjzptqyEhAR1797duayyBgwYUO6yunfvrkaNGjnfnzp1Sp988on69++vsLAwFRcXO199+vTRqVOn9Omnn1ZYt+LiYj311FNq3bq1goODFRgYqODgYO3atcttmFZVrV69WpL7vrvqqqvUqlUrt+2NjY3VVVdd5TKtbdu25xwSdPr0aZftLSkpqbDszp07lZOTo9tuu81letOmTXX11Vefa5O0atUq9ejRQwkJCS7Thw0bphMnTrhdvD548GCX4WGJiYnq1KmTc99I0rFjx/TII4/oV7/6lQIDAxUYGKgGDRro+PHj573vz1aVepQ6u82tWrVK9evX16233uoyvfTnWvpz/PDDDyWp0t+Bjz76SMXFxbr77rtdfmYhISHq2rVrte54tWrVKrVu3dqtzQwbNkzGGOfvrlVt27ZVixYtLC/nzjvvdHl/2223KTAw0O1n0KZNG1122WUu0wYPHqyCggL95z//kSR98MEHSk1N1eWXX+6yH3v16lXu8M+zjxcAqo5gAfix7777TuvWrdONN94oY4yOHDmiI0eOODs9pXeK8pS8vDwFBgYqKirKZbrNZlNsbKzy8vIkyTlW+uKLL650WZIUFxfn9ll8fLzz81JhYWEKDw8vd1lnLyMvL0/FxcX629/+pqCgIJdXnz59JKnS211mZGRo4sSJuvnmm7Vs2TJt2rRJmzdv1mWXXXbeF3pWd3sjIiLcytnt9nOu/95773XZ3tLrAiqrU0xMjNtn5U0rb/6Ktqfs8kvFxsa6lS3bbqQzncYXX3xRw4cP10cffaTPPvtMmzdvVlRUlMcusq1KPaTy21xeXp5iY2Pdrp+Jjo5WYGCgy+9AQEBAuesqtX//fknSlVde6dZOFy9eXKVbspatV3V+FuervHWcj7P3S2BgoCIiIqrcZqT/bdP+/fu1bds2t33YsGFDGWPc9qOntgGoiwJrugIAvGfOnDkyxuidd94p9xkB8+fP1xNPPKGAgACFhIRIktsFptXpvERERKi4uFgHDhxwCRfGGOXk5DgvZi797Mcff3T7NrvssiQpOzvb7bOff/5ZkZGRLtMqeybE2Z81atRIAQEBGjJkSIXfGCcnJ1e4vIULF+ruu+/WU0895TL94MGDuuiiiyqcrzJlt/fswFXe9p6vyZMna8yYMc73DRs2PGedSju4ZeXk5JxzXRERERX+/CS5bVN5y8zJyXHWIz8/Xx988IEmTZqkP/7xj84yhYWFOnTo0DnrU1Xnqkep8tpcRESENm3aJGOMy+e5ubkqLi52bnNUVJRKSkqUk5NTYUe2tOw777xj6c5MpfWqzs/ifJW3Tyo6tlQWZnJyctSkSRPn++LiYuXl5bn9DCr6WUn/a7+RkZEKDQ2t8IuU6hxLAFSOMxaAnyopKdH8+fPVvHlzrV692u310EMPKTs72zkko/QOP9u2bXNZztl3qJHOfDMuud9KsvTb74ULF7pMX7JkiY4fP+78vGfPngoICNArr7xSYf3T09MVGhrqtqwff/zROcTmfIWFhenaa6/VF198obZt2yotLc3tVd4ZgVI2m825D0otX75cP/30k8u0ivZTebp37y7Jfd9t3rxZO3bssLS9ZSUlJblsZ0pKSoVlU1JSFBsbq7feestlelZWljZs2HDOdfXo0UOrVq1ydl5LLViwQGFhYW63233zzTdljHG+37t3rzZs2KBu3bpJOrPfjTFu+/7111+vdEhXdZ2rHpXp0aOHjh07pn/+858u0xcsWOD8XJJ69+4tSZX+DvTq1UuBgYH6/vvvy22jaWlpVd6mHj166Ouvv3YODypbL5vNpmuvvbbKy6qumJgYhYSEuB1b3nvvvQrnWbRokcv7t956S8XFxW4/g+3bt+u///2vy7Q33nhDDRs21BVXXCFJ6tu3r77//ntFRESUuw+rcnczAFXDGQvAT3344Yf6+eefNW3atHI7RKmpqXrxxRc1e/Zs9e3bV7Gxsbruuus0depUNWrUSImJifrkk0/07rvvus176aWXSpKmTZum3r17KyAgQG3bttX111+vXr166ZFHHlFBQYGuvvpqbdu2TZMmTVK7du00ZMgQSWc6t48++qj+/Oc/6+TJk7rjjjvkcDj09ddf6+DBg5oyZYouuugiTZw4UY8++qjuvvtu3XHHHcrLy9OUKVMUEhKiSZMmWdo/zz//vK655hp17txZo0aNUlJSko4eParvvvtOy5Ytq3TMed++fTVv3jy1bNlSbdu21eeff65nnnnG7UxD8+bNFRoaqkWLFqlVq1Zq0KCB4uPjncNPykpJSdFvfvMb/e1vf1O9evXUu3dv7dmzRxMnTlRCQkKNPKSsXr16mjJliu6//37deuutuvfee3XkyBFNmTJFcXFxqlev8u+mJk2apA8++EDXXnutHnvsMTVu3FiLFi3S8uXL9fTTT8vhcLiUz83NVf/+/TVixAjl5+dr0qRJCgkJ0fjx4yVJ4eHh6tKli5555hlFRkYqKSlJa9eu1ezZs8/7TFF5zlWPytx999166aWXNHToUO3Zs0eXXnqp/vWvf+mpp55Snz59dN1110mSOnfurCFDhuiJJ57Q/v371bdvX9ntdn3xxRcKCwvTb3/7WyUlJenxxx/XhAkT9MMPP+iGG25Qo0aNtH//fn322WeqX79+lR9UOW7cOC1YsEA33nijHn/8cSUmJmr58uV6+eWXNWrUKI9cF1ERm82mu+66S3PmzFHz5s112WWX6bPPPtMbb7xR4TzvvvuuAgMDdf3112v79u2aOHGiLrvsMrfrfeLj4/XrX/9akydPVlxcnBYuXKjMzExNmzZNYWFhkqSxY8dqyZIl6tKli8aNG6e2bdvq9OnTysrK0scff6yHHnpIHTp08Nr2A3VKjV02DsCrbr75ZhMcHGxyc3MrLDNo0CATGBhocnJyjDHGZGdnm1tvvdU0btzYOBwOc9ddd5ktW7a43dGlsLDQDB8+3ERFRRmbzWYkmd27dxtjjDl58qR55JFHTGJiogkKCjJxcXFm1KhR5vDhw27rX7BggbnyyitNSEiIadCggWnXrp3bnWNef/1107ZtWxMcHGwcDoe56aab3G6zOXToUFO/fv1yt1GSeeCBB8r9bPfu3ebee+81TZo0MUFBQSYqKsp06tTJPPHEEy5lzt7+w4cPm/vuu89ER0ebsLAwc80115j169ebrl27mq5du7qs48033zQtW7Y0QUFBLnfAKe92syUlJWbatGmmRYsWJigoyERGRpq77rrLeYvaUl27djVt2rRx256hQ4e63anJE2bNmmV+9atfmeDgYNOiRQszZ84cc9NNN5l27dq5lNNZd/gxxpgvv/zS9OvXzzgcDhMcHGwuu+wyt59x6d2Y/v73v5vf/e53JioqytjtdtO5c2ezZcsWl7I//vijGTBggGnUqJFp2LChueGGG8xXX31lEhMTzdChQ92WeT53hapKPSprc3l5eWbkyJEmLi7OBAYGmsTERDN+/Hi327aWlJSYv/71ryY1NdXZvtPT082yZctcyv3zn/801157rQkPDzd2u90kJiaaW2+91fzf//1flbfNmDN38xo8eLCJiIgwQUFBJiUlxTzzzDOmpKTEpZyVu0JVNF9+fr4ZPny4iYmJMfXr1zf9+vUze/bsqfCuUJ9//rnp16+fadCggWnYsKG54447zP79+8td3zvvvGPatGljgoODTVJSkpk+fbrb+o8dO2b+9Kc/mZSUFOe+vvTSS824ceOcxz9jKj9eADg3mzFlzvcCAHAOR44cUYsWLXTzzTdr1qxZNV0dj1mzZo2uvfZavf322253dQIAnBtDoQAAFcrJydGTTz6pa6+9VhEREdq7d6/++te/6ujRo3rwwQdrunoAgAsIwQIAUCG73a49e/Zo9OjROnTokPOi65kzZ6pNmzY1Xb0qMcac8+LugIAAH9XGs6q6bVbudFRSUqLKBjfYbLZau/8AeBZDoQAAfq10iFNl5s6d6/ZwwtrAF9uWlJRU6YMXq/uwPgD+y6vBYt26dXrmmWf0+eefKzs7W0uXLtXNN99c6Txr165VRkaGtm/frvj4eP3hD3/QyJEjvVVFAICfO3r0qHbu3FlpmeTk5EpvMXyh8sW2ffnll27PoCirYcOGld62GEDd4dWhUMePH9dll12me+65RwMGDDhn+d27d6tPnz4aMWKEFi5cqH//+98aPXq0oqKiqjQ/AABna9iwYbWe+VCb+GLbSm8vDQDn4rOhUDab7ZxnLB555BG9//772rFjh3PayJEj9d///lcbN24sd57CwkKXb1JOnz6tQ4cOKSIigqdnAgAAABYYY3T06FHFx8ef8/lFF9TF2xs3blTPnj1dpvXq1UuzZ8/WL7/8oqCgILd5pk6dWuUHBAEAAACovn379rk9CPZsF1SwyMnJUUxMjMu0mJgYFRcX6+DBg4qLi3ObZ/z48crIyHC+z8/PV9OmTbVv3z6Fh4d7vc5W/TXzW83bsEclp91PHAXUs2lYpySNu957T0QFAAAAKlJQUKCEhAQ1bNjwnGUvqGAhyW34UulIrYqGNdntdtntdrfp4eHhtSJYHCwKkC04VPXKGZBms535vDZsBwAAAPxXVS4xqHyglI/FxsYqJyfHZVpubq4CAwNr5d06quLiRqEV/qBsNpsubhTq4xoBAAAA1XdBBYv09HRlZma6TPv444+VlpZW7vUV/uC2tIQKHzxkjNHtaQk+rhEAAABQfV4NFseOHdPWrVu1detWSWduJ7t161ZlZWVJOnN9xN133+0sP3LkSO3du1cZGRnasWOH5syZo9mzZ+vhhx/2ZjVrVHJkfU0b0Fb1ypy0CLDZVM8mTRvQVkmR9WuucgAAAEAVefUaiy1btrg8EbT0IuuhQ4dq3rx5ys7OdoYM6cxDfFasWKFx48bppZdeUnx8vF544QW/f4bFwLQEpTYJV+/n/yVJuueaJN3VIZFQAQAAgFrDZ8+x8JWCggI5HA7l5+fXqoueTxQVq/VjH0mSvn68l8KCL7jr6gEAAFDHVKdvfUFdYwEAAACgdiJYAAAAALCMYAEAAADAMoIFAAAAAMsIFgAAAAAsI1gAAAAAsIxgAQAAAMAyggUAAAAAywgWAAAAACwjWAAAAACwjGABAAAAwDKCBQAAAADLCBYAAAAALCNYAAAAALCMYAEAAADAMoIFAAAAAMsIFgAAAAAsI1gAAAAAsIxgAQAAAMAyggUAAAAAywgWAAAAACwjWAAAAACwjGABAAAAwDKCBQAAAADLCBYAAAAALCNYAAAAALDM68Hi5ZdfVnJyskJCQtS+fXutX7++wrJr1qyRzWZze33zzTferiYAAAAAC7waLBYvXqyxY8dqwoQJ+uKLL9S5c2f17t1bWVlZlc63c+dOZWdnO1+XXHKJN6sJAAAAwCKvBovp06frvvvu0/Dhw9WqVSvNmDFDCQkJeuWVVyqdLzo6WrGxsc5XQECAN6sJAAAAwCKvBYuioiJ9/vnn6tmzp8v0nj17asOGDZXO265dO8XFxalHjx5avXp1pWULCwtVUFDg8gIAAADgW14LFgcPHlRJSYliYmJcpsfExCgnJ6fceeLi4jRr1iwtWbJE7777rlJSUtSjRw+tW7euwvVMnTpVDofD+UpISPDodgAAAAA4t0Bvr8Bms7m8N8a4TSuVkpKilJQU5/v09HTt27dPzz77rLp06VLuPOPHj1dGRobzfUFBAeECAAAA8DGvnbGIjIxUQECA29mJ3Nxct7MYlenYsaN27dpV4ed2u13h4eEuLwAAAAC+5bVgERwcrPbt2yszM9NlemZmpjp16lTl5XzxxReKi4vzdPUAAAAAeJBXh0JlZGRoyJAhSktLU3p6umbNmqWsrCyNHDlS0plhTD/99JMWLFggSZoxY4aSkpLUpk0bFRUVaeHChVqyZImWLFnizWoCAAAAsMirweL2229XXl6eHn/8cWVnZys1NVUrVqxQYmKiJCk7O9vlmRZFRUV6+OGH9dNPPyk0NFRt2rTR8uXL1adPH29WEwAAAIBFNmOMqelKeFJBQYEcDofy8/Nr1fUWJ4qK1fqxjyRJXz/eS2HBXr+uHgAAAKhUdfrWXn1AHgAAAIC6gWABAAAAwDKCBQAAAADLCBYAAAAALCNYAAAAALCMYAEAAADAMoIFAAAAAMsIFgAAAAAsI1gAAAAAsIxgAQAAAMAyggUAAAAAywgWAAAAACwjWAAAAACwjGABAAAAwDKCBQAAAADLCBYAAAAALCNYAAAAALCMYAEAAADAMoIFAAAAAMsCa7oCAAAAvrD74HG9tWWffjx8Uhc3CtVtaQlKjqxf09UC/AbBAgDOAx0UoHZ5a8s+/XHJNtlsNhljZLPZ9Ora7zVtQFsNTEuo6eoBfoFgAVyA6LRe2OigALXL7oPH9ccl23TaSDLmzMT//+8jS7bpyqTGSuIYC1hGsPCSjd/nVav8qV9KnP/f9MMhhQQFeLpKqCXW7MzVrPU/yCbJSLJJmrn2e93fpZm6toj26Lqy809qzc4DOnCsUFEN7OqWEqU4R6hH1+FvsvNP6pEl2870Sc7qoPxhyTYF1qunWEdIzVUQgJs3P8uq9PPpmd/qjquaenSdHF/PH/vOVXrziJquQpURLIAq8sWBLjv/pGat/0HGnAkV0v/+fXXdD0qJCfdYp7W8ALNs289eCTD+ZM3OA859djabpNU7cz3eQUHt4G+dIX/angPHCsv9nZXO/C4fOFbo0fVxfD1/7LvajWABVIGvDnS+6rT6MsD4G193UHzJnzqSvuZvnSF/256oBvZKj61RDeweWxfH1/PHvqv9uN0scA5lD3SnjVz+fXXdD8rJP+Wxdfmq01oaYMpTGmBQvtIOSnk83UHxpTU7c/XQ2//VB9t+1qc/5OmDbT/robf/q7Xf0hbOxZfHCF/wt+2RpG4pUZUeW69N8fwXROXh+Fo59l3tR7BArZedf1JvfpalF1bt0pufZSk7/6RHl+/LA52vOq3+/K27t/myg+Ir/tiR9CV/6wz52/ZIUpwjVPd3aSZbmQ2rZ5NsNun+Ls08+i04x9fz58/7ztt9lQuF14PFyy+/rOTkZIWEhKh9+/Zav359peXXrl2r9u3bKyQkRM2aNdPMmTO9XUXUYr74ltWXBzpfdVr99Vt3X/BlB8VX/LEj6Uv+1hnyt+0p1bVFtKb2v9T5/obUWE0feLnHh3ZxfD1/vt53vurs16Uzwl4NFosXL9bYsWM1YcIEffHFF+rcubN69+6trKzy786we/du9enTR507d9YXX3yhRx99VL/73e+0ZMkSb1YTtZSvvmX15YHOV51Wf/zW3Zd81UHxFX/tSEq+6Tj4W0fS37anrJjw/x1DB7ZP8MoXARxfz59vh6z5prNf184Ie/Xi7enTp+u+++7T8OHDJUkzZszQRx99pFdeeUVTp051Kz9z5kw1bdpUM2bMkCS1atVKW7Zs0bPPPqsBAwZUa90niooVWFRseRvOV9nbx1ZFYZnyhdWct676vx37K70YL3NHjga2t/5MgfTmEVq27edyPzOSOjWPqPbPuzIdkiMU7wjRY+9/LUm6vlWMrm0ZrZjwEI+tp1FYsO7tlKw5/97t3H/1bGe2595OybooLMij2+SPLgoNcv7/123jZQ8K8No+yyk4pfW7DijvWJEiGgSr8yVRig33XIeoUVhQpb9LjWppe1i/64DmbtjjdgHyvZ2Sdc0lkR5bj6+PEd7mb9tTli/+1nJ8PX++2nc5BacqvUg8KaK+Swi1whN9lRM12J+t7vptxpiKwqElRUVFCgsL09tvv63+/fs7pz/44IPaunWr1q5d6zZPly5d1K5dOz3//PPOaUuXLtVtt92mEydOKCgoyG2ewsJCFRb+79u0goICJSQkKGHsW6pnD/PwVgEAAAB1x+nCE9o34zbl5+crPDy80rJeGwp18OBBlZSUKCYmxmV6TEyMcnJyyp0nJyen3PLFxcU6ePBgufNMnTpVDofD+UpI4Km3AAAAgK95/TkWNpvrSE1jjNu0c5Uvb3qp8ePHKyMjw/m+9IzFZxN6nDNVedOmHw7V2LorU/hLiUYu+o8kaeadV8juxSd8e3tdOQWn9OjSL1XeOTebTZra/1KPncqENet3HdDcf+8p99S2J4ekSL5t49729uf7tPKrHJ0up43Xs525tsMTw/1K7S84pXVlhlx1uSTKa79D3v45zVz7vT7bc6jC48NVSY01smtzj67TV/ypjXMct86X7SEr77gmLTszTLdX6xh1axnt0WGZvuLLY6sn2niHZo09UpfzVVBQoLgZVSvrtWARGRmpgIAAt7MTubm5bmclSsXGxpZbPjAwUBER5T/O3G63y253v5AsLDhQYcE19/y/kFpwoLcHBfisnt5YV1JEfd3fpZleXef6ECejMxc6J0bU9+j6cH6y809q7oY9LuNLSw/mczbsVmoTh0cvoMwp+N+FcO9v+1nXtYqptQ95O3zil0ovZDx84heP/l4lRtTXkBr4vfHG8SEmPKTScc0x4SG14jhdHn9q4xu/z6v057Th+zyeZF8N3vy7XvrQxFKZO/br4x37a+VDE69rFaMPvyp/9IyRdH2rWI/tR0/0VWqyPytJxdVYv9eGQgUHB6t9+/bKzMx0mZ6ZmalOnTqVO096erpb+Y8//lhpaWnlXl8BdG0RrekDL1fftvHq2CxCfdvG1+q78/gjX97KdM3OXD269Evn+5Vf5dTqW/r58915vM1f78zjb23cn+9I5itlg+bbn+/zyp3Pyt7ZqFRtvrNR2Tswlt550Zu3Da9LfRWvRqCMjAwNGTJEaWlpSk9P16xZs5SVlaWRI0dKOjOM6aefftKCBQskSSNHjtSLL76ojIwMjRgxQhs3btTs2bP15ptverOaqOViHSF8o3UB81XHoaI/fNKZP3wpMeG17hkT3VKiKr07T23tHPtCacehom8Ja1tbkPyzjZeG54rOWBCeK3f2WYSVX+Xow69yPH4WofQLoop+Tqt35ta6v8NdW0QrJSZcq3fm6sCxQkU1sOvalGiv/Q7Vlb6KV4PF7bffrry8PD3++OPKzs5WamqqVqxYocTERElSdna2yzMtkpOTtWLFCo0bN04vvfSS4uPj9cILL1T7VrMALhy+6jj44x8+f+wclzr7W1ZvDOfxdcfB2/yxjROez58vg6a/nlmqK519X/L6oK3Ro0dr9OjR5X42b948t2ldu3bVf/7zHy/XCr7gi44DLny+6jj46x8+f+scS777llXyr46DP7Zxfw7P3ubLoMmZJVRVzV4NAr/ly44DLmy+6jj48x8+f+oc++NwHl/x1zbuj+HZF3wZNDmzhKoiWMDj6DjgbL7oOPCHr3bwx+E8vuLPbdyfwrOv+DJocmYJVUWw8JL05uXfHremlX0se4dmjb1yC7NpK79RPZtNJeXctLmezaZvc4+q/xVNPL5eXPi8/XMvOW30yJJtstlszmfmGGM0bUBb2twF4o3Psir93OjCPX5eCGjjKBXrCNEHFQRNScq4voWSIj13++j05hEadGVTLd6yTz8ePqmLG4Xq9rQEj64DtR/BAh734+GTzgcbns0Yox8Pe/5WeIAkDUxL0JVJjfnDdwG7uFHomQeelnOMsNlsurgR12FVhjaOUsmR9TVtQNsKg6Y32kRSZH09ckNLjy8X/oNgAY+j44CaxB++C9ttaQl6de335X5mjNHtaZ57kri/oo2jFEETFxqCBTyOjgOAitTEt6yAPyNo4kJCsKhj9uQdd/5/eua3urNDopI9/IecjgOAyvAtKwD4J5upaDB8LVVQUCCHw6H8/HyFh4fXdHUuKG9t2ac/LtnmvENTgM0mozOd/YFeOIuw5+BxOg4AAAC1WHX61gSLOmL3wePq8dwaZ6goq55NWvVQNzr9AAAAcFGdvnU9H9UJNeytLfvOXFBdDpvNpsVb9vm4RgAAAPAnBIs6glvAAgAAwJsIFnWE8xaw5eAWsAAAALCKYFFH3JaWUOkZC24BCwAAACsIFnVE6S1g69mkgHo2l3+5BSwAAACs4jkWdQj3jgcAAIC3ECzqGJ7QCQAAAG9gKBQAAAAAywgWAAAAACwjWAAAAACwjGABAAAAwDKCBQAAAADLCBYAAAAALCNYAAAAALCMYAEAAADAMoIFAAAAAMsIFgAAAAAsI1gAAAAAsMyrweLw4cMaMmSIHA6HHA6HhgwZoiNHjlQ6z7Bhw2Sz2VxeHTt29GY1AQAAAFgU6M2FDx48WD/++KNWrlwpSfrNb36jIUOGaNmyZZXOd8MNN2ju3LnO98HBwd6sJgAAAACLvBYsduzYoZUrV+rTTz9Vhw4dJEmvvfaa0tPTtXPnTqWkpFQ4r91uV2xsrLeqBgAAAMDDvDYUauPGjXI4HM5QIUkdO3aUw+HQhg0bKp13zZo1io6OVosWLTRixAjl5uZWWLawsFAFBQUuLwAAAAC+5bVgkZOTo+joaLfp0dHRysnJqXC+3r17a9GiRVq1apWee+45bd68Wd27d1dhYWG55adOneq8hsPhcCghIcFj2wAAAACgaqodLCZPnux2cfXZry1btkiSbDab2/zGmHKnl7r99tt14403KjU1Vf369dOHH36ob7/9VsuXLy+3/Pjx45Wfn+987du3r7qbBAAAAMCial9jMWbMGA0aNKjSMklJSdq2bZv279/v9tmBAwcUExNT5fXFxcUpMTFRu3btKvdzu90uu91e5eUBAAAA8LxqB4vIyEhFRkaes1x6erry8/P12Wef6aqrrpIkbdq0Sfn5+erUqVOV15eXl6d9+/YpLi6uulUFAAAA4CNeu8aiVatWuuGGGzRixAh9+umn+vTTTzVixAj17dvX5Y5QLVu21NKlSyVJx44d08MPP6yNGzdqz549WrNmjfr166fIyEj179/fW1UFAAAAYJFXH5C3aNEiXXrpperZs6d69uyptm3b6u9//7tLmZ07dyo/P1+SFBAQoC+//FI33XSTWrRooaFDh6pFixbauHGjGjZs6M2qAgAAALDAZowxNV0JTyooKJDD4VB+fr7Cw8NrujoAAABArVWdvrVXz1gAAAAAqBsIFgAAAAAsI1gAAAAAsIxgAQAAAMAyggUAAAAAywgWAAAAACwjWAAAAACwjGABAAAAwDKCBQAAAADLCBYAAAAALCNYAAAAALCMYAEAAADAMoIFAAAAAMsIFgAAAAAsI1gAAAAAsIxgAQAAAMAyggUAAAAAywgWAAAAACwjWAAAAACwjGABAAAAwDKCBQAAAADLCBYAAAAALCNYAAAAALCMYAEAAADAMoIFAAAAAMsIFgAAAAAsI1gAAAAAsMyrweLJJ59Up06dFBYWposuuqhK8xhjNHnyZMXHxys0NFTdunXT9u3bvVlNAAAAABZ5NVgUFRVp4MCBGjVqVJXnefrppzV9+nS9+OKL2rx5s2JjY3X99dfr6NGjXqwpAAAAACsCvbnwKVOmSJLmzZtXpfLGGM2YMUMTJkzQLbfcIkmaP3++YmJi9MYbb+j+++93m6ewsFCFhYXO9/n5+ZKkgoICi7UHAAAA6rbSPrUx5pxlvRosqmv37t3KyclRz549ndPsdru6du2qDRs2lBsspk6d6gwwZSUkJHi1rgAAAEBdcfToUTkcjkrLXFDBIicnR5IUExPjMj0mJkZ79+4td57x48crIyPD+f706dM6dOiQIiIiZLPZLNepoKBACQkJ2rdvn8LDwy0vD7Ub7QFl0R5wNtoEyqI9oKza2h6MMTp69Kji4+PPWbbawWLy5MnlniEoa/PmzUpLS6vuop3ODgTGmApDgt1ul91ud5lW1QvFqyM8PLxWNQJ4F+0BZdEecDbaBMqiPaCs2tgeznWmolS1g8WYMWM0aNCgSsskJSVVd7GSpNjYWElnzlzExcU5p+fm5rqdxQAAAABw4ah2sIiMjFRkZKQ36qLk5GTFxsYqMzNT7dq1k3TmzlJr167VtGnTvLJOAAAAANZ59XazWVlZ2rp1q7KyslRSUqKtW7dq69atOnbsmLNMy5YttXTpUklnhkCNHTtWTz31lJYuXaqvvvpKw4YNU1hYmAYPHuzNqlbIbrdr0qRJbsOtUDfRHlAW7QFno02gLNoDyqoL7cFmqnLvqPM0bNgwzZ8/32366tWr1a1btzMVsNk0d+5cDRs2TNKZ6ymmTJmiV199VYcPH1aHDh300ksvKTU11VvVBAAAAGCRV4MFAAAAgLrBq0OhAAAAANQNBAsAAAAAlhEsAAAAAFhGsAAAAABgGcECAAAAgGUECwAAAACWESwAAAAAWEawAAAAAGAZwQIAAACAZQQLAAAAAJYRLAAAAABYRrAAAAAAYBnBAgAAAIBlBAsAAAAAlhEsAAAAAFhGsAAAAABgGcECAAAAgGUEC6CWe+GFF2Sz2ZSammp5WStWrNDkyZOtV6oW2LNnj2w2m+bNm1fteX/++WdNnjxZW7dudfts8uTJstls1itYC61Zs0Y2m01r1qyp6apc0Erb3rPPPuvzdXfr1k3dunXz+XqtsNlsXjsuff3115o8ebL27Nnj9tmwYcOUlJTklfUC/opgAdRyc+bMkSRt375dmzZtsrSsFStWaMqUKZ6oll/7+eefNWXKlHKDxfDhw7Vx40bfV+oCcMUVV2jjxo264ooraroqqMDLL7+sl19+uaarccH4+uuvNWXKlHKDxcSJE7V06VLfVwqoxQgWQC22ZcsW/fe//9WNN94oSZo9e3YN18j7Tpw4Ue50Y4xOnjzp49q4u/jii9WxY8earkaNCA8PV8eOHRUeHl7TVUEFWrdurdatW9d0NWqF5s2bq127djVdDaBWIVgAtVhpkPjLX/6iTp066R//+Idbx7ui4SlnDwUaNmyYXnrpJUlnhh6Uvkq/yTt16pTGjx+v5ORkBQcHq0mTJnrggQd05MgRt3q98cYbSk9PV4MGDdSgQQNdfvnlbqFnzpw5uuyyyxQSEqLGjRurf//+2rFjh0uZYcOGqUGDBvryyy/Vs2dPNWzYUD169HDWccyYMZo5c6ZatWolu92u+fPnS5J27dqlwYMHKzo6Wna7Xa1atXJuW2W+++473XPPPbrkkksUFhamJk2aqF+/fvryyy9d9ueVV14pSbrnnnuc+6l0qEZ5Q6FOnz6tp59+Wi1btpTdbld0dLTuvvtu/fjjjy7lunXrptTUVG3evFmdO3dWWFiYmjVrpr/85S86ffr0OetfHaX7dvv27erRo4fq16+vqKgojRkzxq0Nle7rV199VS1atJDdblfr1q31j3/8w6Xc+QyFKp3nzTff1IQJExQfH6/w8HBdd9112rlzp1v56rSb7777Tn369FGDBg2UkJCghx56SIWFhc5ypb8DTz/9tJ588kk1bdpUISEhSktL0yeffOKyzKq0jVJHjhzRQw89pGbNmjl/3n369NE333xT4X745ZdfNHToUDVo0EAffPCBpDNfHAwaNEhJSUkKDQ1VUlKS7rjjDu3du9dt/n/9619KT09XSEiImjRpookTJ+r11193+R2W3IdClR2WNX36dCUnJ6tBgwZKT0/Xp59+6rae1157zaUNvPHGG+c1ZKi0ra9fv14dO3ZUaGios94lJSWVznvgwAGNHj1arVu3VoMGDRQdHa3u3btr/fr1bmVfeeUVXXbZZWrQoIEaNmyoli1b6tFHH5UkzZs3TwMHDpQkXXvttc7f5bLHxLO36/Tp0/rb3/6myy+/XKGhobrooovUsWNHvf/++9XafsBfESyAWurkyZN68803deWVVyo1NVX33nuvjh49qrfffvu8ljdx4kTdeuutkqSNGzc6X3FxcTLG6Oabb9azzz6rIUOGaPny5crIyND8+fPVvXt3l87aY489pjvvvFPx8fGaN2+eli5dqqFDh7p0hqZOnar77rtPbdq00bvvvqvnn39e27ZtU3p6unbt2uVSr6KiIv36179W9+7d9d5777kM1frnP/+pV155RY899pg++ugjde7cWV9//bWuvPJKffXVV3ruuef0wQcf6MYbb9Tvfve7cw7z+vnnnxUREaG//OUvWrlypV566SUFBgaqQ4cOzk7uFVdcoblz50qS/vSnPzn30/Dhwytc7qhRo/TII4/o+uuv1/vvv68///nPWrlypTp16qSDBw+6lM3JydGdd96pu+66S++//7569+6t8ePHa+HChZXW/Xz88ssv6tOnj3r06KF//vOfzvBw++23u5V9//339cILL+jxxx/XO++8o8TERN1xxx165513PFKXRx99VHv37tXrr7+uWbNmadeuXerXr59LJ7M67eaXX37Rr3/9a/Xo0UPvvfee7r33Xv31r3/VtGnT3Nb94osvauXKlZoxY4YWLlyoevXqqXfv3i5D2qrSNiTp6NGjuuaaa/Tqq6/qnnvu0bJlyzRz5ky1aNFC2dnZ5W77kSNH1KtXL3388cdau3at+vbtK+lMpz8lJUUzZszQRx99pGnTpik7O1tXXnmlS7vZtm2brr/+ep04cULz58/XzJkz9Z///EdPPvlklff/Sy+9pMzMTM2YMUOLFi3S8ePH1adPH+Xn5zvLzJo1S7/5zW/Utm1bvfvuu/rTn/6kKVOmnPc1NTk5ORo0aJDuvPNOvffee7r11lv1xBNP6MEHH6x0vkOHDkmSJk2apOXLl2vu3Llq1qyZunXr5lKXf/zjHxo9erS6du2qpUuX6p///KfGjRun48ePS5JuvPFGPfXUU87tL/1dLj0DXJ5hw4bpwQcf1JVXXqnFixfrH//4h37961+XO5QKqJMMgFppwYIFRpKZOXOmMcaYo0ePmgYNGpjOnTu7lFu9erWRZFavXu0yfffu3UaSmTt3rnPaAw88YMo7LKxcudJIMk8//bTL9MWLFxtJZtasWcYYY3744QcTEBBg7rzzzgrrffjwYRMaGmr69OnjMj0rK8vY7XYzePBg57ShQ4caSWbOnDluy5FkHA6HOXTokMv0Xr16mYsvvtjk5+e7TB8zZowJCQlxli9v+89WXFxsioqKzCWXXGLGjRvnnL558+YK5500aZLLPtyxY4eRZEaPHu1SbtOmTUaSefTRR53TunbtaiSZTZs2uZRt3bq16dWrV4X1PB+l+/b55593mf7kk08aSeZf//qXc5okExoaanJycpzTiouLTcuWLc2vfvUr57SK2lplSuc5uz289dZbRpLZuHGjMeb82s1bb73lUrZPnz4mJSXF+b60DcTHx5uTJ086pxcUFJjGjRub6667rsJ6V9Q2Hn/8cSPJZGZmVjhv6XqfeeYZs3v3btO6dWvTunVrs2fPngrnKV3nsWPHTP369V1+bgMHDjT169c3Bw4ccE4rKSkxrVu3NpLM7t27ndO7du1qunbt6laXSy+91BQXFzunf/bZZ0aSefPNN53Li42NNR06dHCp0969e01QUJBJTEystO5nK23r7733nsv0ESNGmHr16pm9e/c6p0kykyZNqnBZxcXF5pdffjE9evQw/fv3d04fM2aMueiiiyqtx9tvv11hmx06dKjLdq1bt85IMhMmTKh844A6jDMWQC01e/ZshYaGatCgQZKkBg0aaODAgVq/fr3bt7dWrVq1StKZb+vKGjhwoOrXr+8cNpKZmamSkhI98MADFS5r48aNOnnypNuyEhIS1L17d7chKJI0YMCAcpfVvXt3NWrUyPn+1KlT+uSTT9S/f3+FhYWpuLjY+erTp49OnTpV7vCOUsXFxXrqqafUunVrBQcHKzAwUMHBwdq1a5fbcJuqWr16tST3fXfVVVepVatWbtsbGxurq666ymVa27Ztyx3+Utbp06ddtvdcw0lK3XnnnS7vBw8e7FLvUj169FBMTIzzfUBAgG6//XZ99913bkO6zsevf/1rl/dt27aVJOd2V7fd2Gw29evXz22Z5e3HW265RSEhIc73DRs2VL9+/bRu3Trnfqxq2/jwww/VokULXXfddefc5v/85z/q2LGjYmJi9O9//1uJiYkunx87dkyPPPKIfvWrXykwMFCBgYFq0KCBjh8/7rLOtWvXqnv37oqMjHROq1evnm677bZz1qHUjTfeqICAAOf7s/f/zp07lZOT47bMpk2b6uqrr67yespq2LCh28998ODBOn36tNatW1fpvDNnztQVV1yhkJAQBQYGKigoSJ988onLfrnqqqt05MgR3XHHHXrvvffczg5W14cffihJlR7fgLqOYAHUQt99953WrVunG2+8UcYYHTlyREeOHHEOZSq9U5Sn5OXlKTAwUFFRUS7TbTabYmNjlZeXJ+nM2GfpzAXMlS1LkuLi4tw+i4+Pd35eKiwsrMKLgc9eRl5enoqLi/W3v/1NQUFBLq8+ffpIUqWdi4yMDE2cOFE333yzli1bpk2bNmnz5s267LLLzvvC8Opub0REhFs5u91+zvXfe++9Lttbei1KZQIDA93WFxsb61Lvs6dXpez5OLsedrtdkpzbfT7tpmxYKF3mqVOn3OavaNuKiop07NgxSVVvGwcOHKi0/ZeVmZmp/fv3a/jw4brooovcPh88eLBefPFFDR8+XB999JE+++wzbd68WVFRUS7rzMvLcwl9pcqbVpGq7n+r6znXfFVpU9OnT9eoUaPUoUMHLVmyRJ9++qk2b96sG264wWW/DBkyRHPmzNHevXs1YMAARUdHq0OHDsrMzDyv+h44cEABAQHlthcAZwTWdAUAVN+cOXNkjNE777xT7hj3+fPn64knnlBAQICzc1X2Ogip8g722SIiIlRcXKwDBw64hAtjjHJycpwXM5d+9uOPPyohIaHCZUkqd7z5zz//7PKtq6RKnwlx9meNGjVSQECAhgwZUuG3isnJyRUub+HChbr77rud465LHTx4sNyOX1WU3d6zO5zlbe/5mjx5ssaMGeN837Bhw3POU1xcrLy8PJdOZU5OjiT3jmbp9PKmlReGPK267aY6Ktq24OBgNWjQQFLV20ZUVFSVz+D8/ve/1/fff6+7775bxcXFuvvuu52f5efn64MPPtCkSZP0xz/+0Tm9sLDQeY1BqYiICO3fv79K23W+Sve/J9dT2bIqa1MLFy5Ut27d9Morr7hMP3r0qFvZe+65R/fcc4+OHz+udevWadKkSerbt6++/fZbtzNE5xIVFaWSkhLl5OSUG3ABcMYCqHVKSko0f/58NW/eXKtXr3Z7PfTQQ8rOznaeti+9q8m2bdtcllPeXUzO/payVOm332dfQLxkyRIdP37c+XnPnj0VEBDg9ge/rPT0dIWGhrot68cff9SqVauq9E17RcLCwnTttdfqiy++UNu2bZWWlub2qqzDYrPZnPug1PLly/XTTz+5TKtoP5Wne/fuktz33ebNm7Vjxw5L21tWUlKSy3ampKRUab5Fixa5vH/jjTckye0hap988olLR7CkpESLFy9W8+bNq/wNvRXebDfvvvuuy5mMo0ePatmyZercubNzeFBV20bv3r317bffOocPVqZevXp69dVX9eCDD2rYsGEuvzc2m03GGLd1vv76627D3Lp27apVq1a5fFlw+vTp876RQ3lSUlIUGxurt956y2V6VlaWNmzYcF7LPHr0qNtx6I033lC9evXUpUuXCucr72exbdu2Sp8fU79+ffXu3VsTJkxQUVGRtm/fLql6v8u9e/eWpEqPb0BdxxkLoJb58MMP9fPPP2vatGnlPkE3NTVVL774ombPnq2+ffsqNjZW1113naZOnapGjRopMTFRn3zyid599123eS+99FJJ0rRp09S7d28FBASobdu2uv7669WrVy898sgjKigo0NVXX61t27Zp0qRJateunYYMGSLpTOf20Ucf1Z///GedPHlSd9xxhxwOh77++msdPHhQU6ZM0UUXXaSJEyfq0Ucf1d1336077rhDeXl5mjJlikJCQjRp0iRL++f555/XNddco86dO2vUqFFKSkrS0aNH9d1332nZsmWVdvj69u2refPmqWXLlmrbtq0+//xzPfPMM24d5+bNmys0NFSLFi1Sq1at1KBBA8XHxys+Pt5tmSkpKfrNb36jv/3tb867De3Zs0cTJ05UQkKCxo0bZ2l7rQgODtZzzz2nY8eO6corr9SGDRv0xBNPqHfv3rrmmmtcykZGRqp79+6aOHGi6tevr5dfflnffPON2y1nvcWb7SYgIEDXX3+9MjIydPr0aU2bNk0FBQUudxGratsYO3asFi9erJtuukl//OMfddVVV+nkyZPOuz1de+21but/7rnn1LBhQ40ePVrHjh3T73//e4WHh6tLly565plnFBkZqaSkJK1du1azZ892O3s2YcIELVu2TD169NCECRMUGhqqmTNnOu9+VK+e9e8Q69WrpylTpuj+++/XrbfeqnvvvVdHjhzRlClTFBcXd17riIiI0KhRo5SVlaUWLVpoxYoVeu211zRq1Cg1bdq0wvn69u2rP//5z5o0aZK6du2qnTt36vHHH1dycrKKi4ud5UaMGKHQ0FBdffXViouLU05OjqZOnSqHw+E8y5qamirpzB2vGjZsqJCQECUnJ5f7BUTnzp01ZMgQPfHEE9q/f7/69u0ru92uL774QmFhYfrtb39b7X0A+J2avXYcQHXdfPPNJjg42OTm5lZYZtCgQSYwMNB5F5/s7Gxz6623msaNGxuHw2Huuusus2XLFrc7GxUWFprhw4ebqKgoY7PZXO4oc/LkSfPII4+YxMREExQUZOLi4syoUaPM4cOH3da/YMECc+WVV5qQkBDToEED065dO7c7KL3++uumbdu2Jjg42DgcDnPTTTeZ7du3u5QZOnSoqV+/frnbKMk88MAD5X62e/duc++995omTZqYoKAgExUVZTp16mSeeOIJlzJnb//hw4fNfffdZ6Kjo01YWJi55pprzPr1693upGOMMW+++aZp2bKlCQoKcrlrzdl3hTLmzB11pk2bZlq0aGGCgoJMZGSkueuuu8y+fftcynXt2tW0adPGbXvOvjuNJ5Tu223btplu3bqZ0NBQ07hxYzNq1Chz7Ngxl7Kl+/rll182zZs3N0FBQaZly5Zm0aJFLuWs3BXq7bffdple0V27rLSbs382peuYNm2amTJlirn44otNcHCwadeunfnoo49c5q1O2zh8+LB58MEHTdOmTU1QUJCJjo42N954o/nmm29c1vvMM8+4zPfMM88YSeaxxx4zxhjz448/mgEDBphGjRqZhg0bmhtuuMF89dVXJjEx0QwdOtRl3vXr15sOHToYu91uYmNjze9//3szbdo0I8kcOXLEWa6iu0KdXRdjyr8b06xZs8yvfvUrExwcbFq0aGHmzJljbrrpJtOuXTu3+StT2tbXrFlj0tLSjN1uN3FxcebRRx81v/zyS6X1KCwsNA8//LBp0qSJCQkJMVdccYX55z//6fZ7Mn/+fHPttdeamJgYExwcbOLj481tt91mtm3b5rL8GTNmmOTkZBMQEODS5sr7vSspKTF//etfTWpqqrMNpqenm2XLllVr+wF/ZTPGGB9nGQBADRs2bJjeeecd58XJlbHZbHrggQf04osv+qBmvrNnzx4lJyfrmWee0cMPP1zT1fG4nj17as+ePfr222+9to4jR46oRYsWuvnmmzVr1qwqz9etWzcdPHhQX331ldfqBsD3GAoFAEAtl5GRoXbt2ikhIUGHDh3SokWLlJmZ6fbEeytycnL05JNP6tprr1VERIT27t2rv/71rzp69Og5H2oHoG4gWAAAPM4Yc85naQQEBFR61y9UXUlJiR577DHl5OTIZrOpdevW+vvf/6677rrLY+uw2+3as2ePRo8erUOHDiksLEwdO3bUzJkz1aZNG2c9KhsIYbPZXJ6XAcC/MBQKAOBxa9asKfdC5bLmzp3r9sA71G7dunXT2rVrK/w8MTFRe/bs8V2FAPiUV4PFunXr9Mwzz+jzzz9Xdna2li5dqptvvrnSedauXauMjAxt375d8fHx+sMf/qCRI0d6q4oAAC84evSodu7cWWmZiu6+g9pr586d5T5PopTdbnfefQ6A//HqUKjjx4/rsssu0z333KMBAwacs/zu3bvVp08fjRgxQgsXLtS///1vjR49WlFRUVWaHwBwYWjYsKHS0tJquhrwsao+PwWAf/LZUCibzXbOMxaPPPKI3n//fe3YscM5beTIkfrvf/9b4YNvCgsLXZ4ofPr0aR06dEgRERGM3QUAAAAsMMbo6NGjio+PP+czay6oi7c3btyonj17ukzr1auXZs+erV9++UVBQUFu80ydOtXlIUYAAAAAPGvfvn1uDwU92wUVLHJychQTE+MyLSYmRsXFxTp48KDi4uLc5hk/frwyMjKc7/Pz89W0aVPt27dP4eHhXq+zVX/N/FbzNuxRyWn3E0cB9Wwa1ilJ465vUQM1AwAAQF1XUFCghIQENWzY8JxlL6hgIclt+FLpSK2KhjXZ7XbZ7Xa36eHh4bUiWBwsCpAtOFT1yhmQZrOd+bw2bAcAAAD8V1UuMah8oJSPxcbGKicnx2Vabm6uAgMD/fbOIRc3Cq3wB2Wz2XRxo1Af1wgAAACovgsqWKSnpyszM9Nl2scff6y0tLRyr6/wB7elJVT4MCFjjG5PS/BxjQAAAIDq82qwOHbsmLZu3aqtW7dKOnM72a1btyorK0vSmesj7r77bmf5kSNHau/evcrIyNCOHTs0Z84czZ49Ww8//LA3q1mjkiPra9qAtqpX5qRFgM2mejZp2oC2SoqsX3OVAwAAAKrIq9dYbNmyxeXJq6UXWQ8dOlTz5s1Tdna2M2RIZx6WtGLFCo0bN04vvfSS4uPj9cILL/j9MywGpiUotUm4ej//L0nSPdck6a4OiYQKAAAA1Bo+e46FrxQUFMjhcCg/P79WXfR8oqhYrR/7SJL09eO9FBZ8wV1XDwAAgDqmOn3rC+oaCwAAAAC1E8ECAAAAgGUECwAAAACWESwAAAAAWEawAAAAAGAZwQIAAACAZQQLAAAAAJYRLAAAAABYRrAAAAAAYBnBAgAAAIBlBAsAAAAAlhEsAAAAAFhGsAAAAABgGcECAAAAgGUECwAAAACWESwAAAAAWEawAAAAAGAZwQIAAACAZQQLAAAAAJYRLAAAAABYRrAAAAAAYBnBAgAAAIBlBAsAAAAAlhEsAAAAAFhGsAAAAABgGcECAAAAgGVeDxYvv/yykpOTFRISovbt22v9+vUVll2zZo1sNpvb65tvvvF2NQEAAABY4NVgsXjxYo0dO1YTJkzQF198oc6dO6t3797KysqqdL6dO3cqOzvb+brkkku8WU0AAAAAFnk1WEyfPl333Xefhg8frlatWmnGjBlKSEjQK6+8Uul80dHRio2Ndb4CAgK8WU0AAAAAFnktWBQVFenzzz9Xz549Xab37NlTGzZsqHTedu3aKS4uTj169NDq1asrLVtYWKiCggKXFwAAAADf8lqwOHjwoEpKShQTE+MyPSYmRjk5OeXOExcXp1mzZmnJkiV69913lZKSoh49emjdunUVrmfq1KlyOBzOV0JCgke3AwAAAMC5BXp7BTabzeW9McZtWqmUlBSlpKQ436enp2vfvn169tln1aVLl3LnGT9+vDIyMpzvCwoKCBcAAACAj3ntjEVkZKQCAgLczk7k5ua6ncWoTMeOHbVr164KP7fb7QoPD3d5AQAAAPAtrwWL4OBgtW/fXpmZmS7TMzMz1alTpyov54svvlBcXJynqwcAAADAg7w6FCojI0NDhgxRWlqa0tPTNWvWLGVlZWnkyJGSzgxj+umnn7RgwQJJ0owZM5SUlKQ2bdqoqKhICxcu1JIlS7RkyRJvVhMAAACARV4NFrfffrvy8vL0+OOPKzs7W6mpqVqxYoUSExMlSdnZ2S7PtCgqKtLDDz+sn376SaGhoWrTpo2WL1+uPn36eLOaAAAAACyyGWNMTVfCkwoKCuRwOJSfn1+rrrc4UVSs1o99JEn6+vFeCgv2+nX1AAAAQKWq07f26gPyAAAAANQNBAsAAAAAlhEsAAAAAFhGsAAAAABgGcECAAAAgGUECwAAAACWESwAAAAAWEawAAAAAGAZwQIAAACAZQQLAAAAAJYRLAAAAABYRrAAAAAAYBnBAgAAAIBlBAsAAAAAlhEsAAAAAFhGsAAAAABgGcECAAAAgGUECwAAAACWESwAAAAAWEawAAAAAGAZwQIAAACAZQQLAAAAAJYF1nQF/NXG7/OqVf7ULyXO/2/64ZBCggI8XSUAAADUMunNI2q6ClXGGQsAAAAAlnHGAgAAoJbKzj+pNTsP6MCxQkU1sKtbSpTiHKE1XS3UUQQLAACAWmjNzlzNWv+DbJKMJJukZdt+1v1dmqlri2iPr48Qg3MhWAAAgBrljx1Wb29Tdv5JzVr/g4w5Eyqk//376roflBITrlhHiMfW58sQ44/toa7werB4+eWX9cwzzyg7O1tt2rTRjBkz1Llz5wrLr127VhkZGdq+fbvi4+P1hz/8QSNHjvR2NYFz4kBnjb/tP19uj7/tO9QOvmp3/thh9cU2rdl5wLn8s9kkrd6ZqzuuauqRdfkyxPj6LAw8y6vBYvHixRo7dqxefvllXX311Xr11VfVu3dvff3112ra1L2x7969W3369NGIESO0cOFC/fvf/9bo0aMVFRWlAQMGeLOqdYY/dlB8sU3+eqDzpz+ypfytPfjbvquJdfmKP22Tr9qdP3ZYfbVNB44VlhsqStd34Fih5XWU8lWI8fVZGI55nufVYDF9+nTdd999Gj58uCRpxowZ+uijj/TKK69o6tSpbuVnzpyppk2basaMGZKkVq1aacuWLXr22WerHSxOFBUrsKjY8jacr7K3j62KwjLlC6s5b1Wt33VAczfscTuo3tspWddcEunx9eUUnNL6XQeUd6xIEQ2C1fmSKMWGe+6AIPlmm3IKTlV6oEuKqK8YD2+XL/iqPfhy//lbe/C3fVcT6/LFcUjyr23yZbv7vx37K+2wZu7I0cD2CZbX44/b1CgsqNL1NAoLqnZfpCL7C05VGmL2F5zyyLp8te+k2nXMO1GD/dnqrt9mjKmorVhSVFSksLAwvf322+rfv79z+oMPPqitW7dq7dq1bvN06dJF7dq10/PPP++ctnTpUt122206ceKEgoKC3OYpLCxUYeH/UnlBQYESEhKUMPYt1bOHeXirAAAAgLrjdOEJ7Ztxm/Lz8xUeHl5pWa89x+LgwYMqKSlRTEyMy/SYmBjl5OSUO09OTk655YuLi3Xw4MFy55k6daocDofzlZDgmSQLAAAAoOq8fvG2zWZzeW+McZt2rvLlTS81fvx4ZWRkON+XnrH4bEKPc6Yqb9r0w6EaW3d5Zq79Xp/tOaTyzk/ZbNJVSY01smtzj6zr7c/3aeVXOTpdzrrq2aQbUmM9cirTV9vkq+2Rzpyuf3TplxVu09T+l3rkdD3t4fz5sj34277z5bp8+XPyt23yx2OeP25Tqf0Fp7SuzNC4LpdEeWV47r92HdScDbtdhvMYyeNDTf3tb6An1tWhWWOP1OV8FRQUKG5G1cp6LVhERkYqICDA7exEbm6u21mJUrGxseWWDwwMVERE+Y8zt9vtstvtbtPDggMVFlxzd9MNCQqosXWXJyY8pNJxizHhIR6r8+ETv1Q6FvPwiV88si5fbdN1rWL04Vfln2Uzkq5vFeuxfbfx+7xKt2nD93keuUDOl+3BV/vPH9uDv+07X67LV8chyf+2yZdtPCmivu7v0kyvrvvBrcN6f5dmSoyo75H1+OM2lUqMqK8hHl5mea5rHaPUJg6t3pnrvAD52pRoj15M7at9V9uOeTXZn5Wk4mqs32tDoYKDg9W+fXtlZma6TM/MzFSnTp3KnSc9Pd2t/Mcff6y0tLRyr69A1XVLiar0D9K1KZ67I0ZUA7sqOidl+/+fe4KvtinOEar7uzSTzXbmm62y/97fpZlHD6q+usuHL9uDr/afP7YHf9t3vlyXr45Dkv9tky/buCR1bRGt6QMvV9+28erYLEJ928Zr+sDLPXqnJn/cppoQ6wjRHVc11e+6X6I7rmrq8f0m+Wbf+eMx70LhtYu3pTO3mx0yZIhmzpyp9PR0zZo1S6+99pq2b9+uxMREjR8/Xj/99JMWLFgg6cztZlNTU3X//fdrxIgR2rhxo0aOHKk333yzyneFKigokMPhqNIFJt608fu8Glt3RdZ+m1vhtwCevtXeQ2//t8LTftMHXu6xg5GvtkmScvJPefWbGkl687MsfbDt5wpP1/dtG++x+5L7ct9Jvtl//tYefLkuX+47X6zLl8chyT+3yZdt3Ff8cZtwfmrTMS+9efmjdnylOn1rrwYL6cwD8p5++mllZ2crNTVVf/3rX9WlSxdJ0rBhw7Rnzx6tWbPGWX7t2rUaN26c8wF5jzzySLUekEewqJyvDqr+2sHzNjoO1vnjNvkKYckaf9wmwJ/VlmMewaIGESwuHHTwzg8dB8Bz/PE45I/bBKBiBIsaRLCAP6DjAAAApNoVLGr2MnMA5Sq9QA4AAKC2IFh4SU2nSwAAAMCXvHa7WQAAAAB1B8ECAAAAgGUECwAAAACWESwAAAAAWEawAAAAAGAZwQIAAACAZQQLAAAAAJYRLAAAAABYRrAAAAAAYBnBAgAAAIBlBAsAAAAAlhEsAAAAAFhGsAAAAABgGcECAAAAgGUECwAAAACWESwAAAAAWEawAAAAAGAZwQIAAACAZQQLAAAAAJYRLAAAAABYRrAAAAAAYBnBAgAAAIBlBAsAAAAAlhEsAAAAAFjm1WBx+PBhDRkyRA6HQw6HQ0OGDNGRI0cqnWfYsGGy2Wwur44dO3qzmgAAAAAsCvTmwgcPHqwff/xRK1eulCT95je/0ZAhQ7Rs2bJK57vhhhs0d+5c5/vg4GBvVhMAAACARV4LFjt27NDKlSv16aefqkOHDpKk1157Tenp6dq5c6dSUlIqnNdutys2NrZK6yksLFRhYaHzfUFBgbWKAwAAAKg2rw2F2rhxoxwOhzNUSFLHjh3lcDi0YcOGSudds2aNoqOj1aJFC40YMUK5ubkVlp06dapzqJXD4VBCQoLHtgEAAABA1XgtWOTk5Cg6OtptenR0tHJyciqcr3fv3lq0aJFWrVql5557Tps3b1b37t1dzkqUNX78eOXn5ztf+/bt89g2AAAAAKiaag+Fmjx5sqZMmVJpmc2bN0uSbDab22fGmHKnl7r99tud/09NTVVaWpoSExO1fPly3XLLLW7l7Xa77HZ7VasPAAAAwAuqHSzGjBmjQYMGVVomKSlJ27Zt0/79+90+O3DggGJiYqq8vri4OCUmJmrXrl3VrSoAAAAAH6l2sIiMjFRkZOQ5y6Wnpys/P1+fffaZrrrqKknSpk2blJ+fr06dOlV5fXl5edq3b5/i4uKqW1UAAAAAPuK1ayxatWqlG264QSNGjNCnn36qTz/9VCNGjFDfvn1d7gjVsmVLLV26VJJ07NgxPfzww9q4caP27NmjNWvWqF+/foqMjFT//v29VVUAAAAAFnn1AXmLFi3SpZdeqp49e6pnz55q27at/v73v7uU2blzp/Lz8yVJAQEB+vLLL3XTTTepRYsWGjp0qFq0aKGNGzeqYcOG3qwqAAAAAAtsxhhT05XwpIKCAjkcDuXn5ys8PLymqwMAAADUWtXpW3v1jAUAAACAuoFgAQAAAMAyggUAAAAAywgWAAAAACwjWAAAAACwjGABAAAAwDKCBQAAAADLCBYAAAAALCNYAAAAALCMYAEAAADAMoIFAAAAAMsIFgAAAAAsI1gAAAAAsIxgAQAAAMAyggUAAAAAywgWAAAAACwjWAAAAACwjGABAAAAwDKCBQAAAADLCBYAAAAALCNYAAAAALCMYAEAAADAMoIFAAAAAMsIFgAAAAAsI1gAAAAAsIxgAQAAAMAyggUAAAAAy7waLJ588kl16tRJYWFhuuiii6o0jzFGkydPVnx8vEJDQ9WtWzdt377dm9UEAAAAYJFXg0VRUZEGDhyoUaNGVXmep59+WtOnT9eLL76ozZs3KzY2Vtdff72OHj3qxZoCAAAAsCLQmwufMmWKJGnevHlVKm+M0YwZMzRhwgTdcsstkqT58+crJiZGb7zxhu6//363eQoLC1VYWOh8n5+fL0kqKCiwWHsAAACgbivtUxtjzlnWq8Giunbv3q2cnBz17NnTOc1ut6tr167asGFDucFi6tSpzgBTVkJCglfrCgAAANQVR48elcPhqLTMBRUscnJyJEkxMTEu02NiYrR3795y5xk/frwyMjKc70+fPq1Dhw4pIiJCNpvNcp0KCgqUkJCgffv2KTw83PLyULvRHlAW7QFno02gLNoDyqqt7cEYo6NHjyo+Pv6cZasdLCZPnlzuGYKyNm/erLS0tOou2unsQGCMqTAk2O122e12l2lVvVC8OsLDw2tVI4B30R5QFu0BZ6NNoCzaA8qqje3hXGcqSlU7WIwZM0aDBg2qtExSUlJ1FytJio2NlXTmzEVcXJxzem5urttZDAAAAAAXjmoHi8jISEVGRnqjLkpOTlZsbKwyMzPVrl07SWfuLLV27VpNmzbNK+sEAAAAYJ1XbzeblZWlrVu3KisrSyUlJdq6dau2bt2qY8eOOcu0bNlSS5culXRmCNTYsWP11FNPaenSpfrqq680bNgwhYWFafDgwd6saoXsdrsmTZrkNtwKdRPtAWXRHnA22gTKoj2grLrQHmymKveOOk/Dhg3T/Pnz3aavXr1a3bp1O1MBm01z587VsGHDJJ25nmLKlCl69dVXdfjwYXXo0EEvvfSSUlNTvVVNAAAAABZ5NVgAAAAAqBu8OhQKAAAAQN1AsAAAAABgGcECAAAAgGUECwAAAACWESzO4eWXX1ZycrJCQkLUvn17rV+/vqarhBowefJk2Ww2l1fpAx3h/9atW6d+/fopPj5eNptN//znP10+N8Zo8uTJio+PV2hoqLp166bt27fXTGXhdedqD8OGDXM7XnTs2LFmKguvmzp1qq688ko1bNhQ0dHRuvnmm7Vz506XMhwj6o6qtAd/PkYQLCqxePFijR07VhMmTNAXX3yhzp07q3fv3srKyqrpqqEGtGnTRtnZ2c7Xl19+WdNVgo8cP35cl112mV588cVyP3/66ac1ffp0vfjii9q8ebNiY2N1/fXX6+jRoz6uKXzhXO1Bkm644QaX48WKFSt8WEP40tq1a/XAAw/o008/VWZmpoqLi9WzZ08dP37cWYZjRN1RlfYg+fExwqBCV111lRk5cqTLtJYtW5o//vGPNVQj1JRJkyaZyy67rKargQuAJLN06VLn+9OnT5vY2Fjzl7/8xTnt1KlTxuFwmJkzZ9ZADeFLZ7cHY4wZOnSouemmm2qkPqh5ubm5RpJZu3atMYZjRF13dnswxr+PEZyxqEBRUZE+//xz9ezZ02V6z549tWHDhhqqFWrSrl27FB8fr+TkZA0aNEg//PBDTVcJF4Ddu3crJyfH5Vhht9vVtWtXjhV12Jo1axQdHa0WLVpoxIgRys3NrekqwUfy8/MlSY0bN5bEMaKuO7s9lPLXYwTBogIHDx5USUmJYmJiXKbHxMQoJyenhmqFmtKhQwctWLBAH330kV577TXl5OSoU6dOysvLq+mqoYaVHg84VqBU7969tWjRIq1atUrPPfecNm/erO7du6uwsLCmqwYvM8YoIyND11xzjVJTUyVxjKjLymsPkn8fIwJrugIXOpvN5vLeGOM2Df6vd+/ezv9feumlSk9PV/PmzTV//nxlZGTUYM1woeBYgVK333678/+pqalKS0tTYmKili9frltuuaUGawZvGzNmjLZt26Z//etfbp9xjKh7KmoP/nyM4IxFBSIjIxUQEOD2bUJubq7btw6oe+rXr69LL71Uu3btqumqoIaV3h2MYwUqEhcXp8TERI4Xfu63v/2t3n//fa1evVoXX3yxczrHiLqpovZQHn86RhAsKhAcHKz27dsrMzPTZXpmZqY6depUQ7XChaKwsFA7duxQXFxcTVcFNSw5OVmxsbEux4qioiKtXbuWYwUkSXl5edq3bx/HCz9ljNGYMWP07rvvatWqVUpOTnb5nGNE3XKu9lAefzpGMBSqEhkZGRoyZIjS0tKUnp6uWbNmKSsrSyNHjqzpqsHHHn74YfXr109NmzZVbm6unnjiCRUUFGjo0KE1XTX4wLFjx/Tdd9853+/evVtbt25V48aN1bRpU40dO1ZPPfWULrnkEl1yySV66qmnFBYWpsGDB9dgreEtlbWHxo0ba/LkyRowYIDi4uK0Z88ePfroo4qMjFT//v1rsNbwlgceeEBvvPGG3nvvPTVs2NB5ZsLhcCg0NFQ2m41jRB1yrvZw7Ngx/z5G1OAdqWqFl156ySQmJprg4GBzxRVXuNwuDHXH7bffbuLi4kxQUJCJj483t9xyi9m+fXtNVws+snr1aiPJ7TV06FBjzJnbSU6aNMnExsYau91uunTpYr788suarTS8prL2cOLECdOzZ08TFRVlgoKCTNOmTc3QoUNNVlZWTVcbXlJeW5Bk5s6d6yzDMaLuOFd78PdjhM0YY3wZZAAAAAD4H66xAAAAAGAZwQIAAACAZQQLAAAAAJYRLAAAAABYRrAAAAAAYBnBAgAAAIBlBAsAAAAAlhEsAAAAAFhGsAAAAABgGcECAAAAgGUECwAAAACW/T80Gwjzsctz4gAAAABJRU5ErkJggg==", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "analyser.viz.pacf()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "analyser.viz.distributions(norm=True)\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "base", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.5" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/E06-sktime.ipynb b/notebooks/E06-sktime.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..b7edb0dbfd670bbb02f20302ed12ae1fda327f0e --- /dev/null +++ b/notebooks/E06-sktime.ipynb @@ -0,0 +1,1235 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "from sktime.forecasting.fbprophet import Prophet \n", + "import numpy as np\n", + "from statsmodels.tsa.seasonal import seasonal_decompose" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "data = pd.read_csv('../data/multivariate/blow_mold_preprocessed.csv', index_col='datetime', parse_dates=['datetime'])" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "276" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# [Double check if the datetime index is complete]\n", + "\n", + "(data.index == pd.date_range(data.index[0], data.index[-1], freq='M')).sum()" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "seasonal_decompose(data['y']).plot()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "# [Train test split]\n", + "from sktime.forecasting.model_selection import temporal_train_test_split\n", + "\n", + "train, test =temporal_train_test_split(data, test_size=24) \n", + "\n", + "fh = np.arange(1, 25)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/zq/.local/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", + " from .autonotebook import tqdm as notebook_tqdm\n", + "Importing plotly failed. Interactive plots will not work.\n", + "INFO:cmdstanpy:start chain 1\n", + "INFO:cmdstanpy:finish chain 1\n", + "INFO:cmdstanpy:start chain 1\n", + "INFO:cmdstanpy:finish chain 1\n", + "INFO:cmdstanpy:start chain 1\n", + "INFO:cmdstanpy:finish chain 1\n", + "INFO:cmdstanpy:start chain 1\n", + "INFO:cmdstanpy:finish chain 1\n", + "INFO:cmdstanpy:start chain 1\n", + "INFO:cmdstanpy:finish chain 1\n", + "INFO:cmdstanpy:start chain 1\n", + "INFO:cmdstanpy:finish chain 1\n" + ] + } + ], + "source": [ + "forecaster = Prophet(\n", + " seasonality_mode='additive',\n", + " yearly_seasonality=True,\n", + " weekly_seasonality=False,\n", + " daily_seasonality=False,\n", + ")\n", + "\n", + "forecaster.fit(train)\n", + "\n", + "fh = np.arange(1, 25)\n", + "\n", + "y_pred_interval = forecaster.predict_interval(fh=fh, coverage=0.9)\n", + "y_pred = forecaster.predict(fh=fh)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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ygas_regmm_coil_brent_euppi_plastic_resinsglobal_proce_of_rubberppi_nonpackaging_plastic
datetime
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2000-02-2941.01.37727.78141.733.391099105.6
2000-03-3145.01.51627.49146.330.941913106.1
2000-04-3047.01.46522.76151.431.930148106.9
2000-05-3147.01.48727.74155.631.201702106.3
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2020-08-3157.02.18244.74225.179.961626214.3
2020-09-3062.02.18340.91226.089.312444220.9
2020-10-3162.02.15840.19238.2101.520278224.0
2020-11-3062.02.10842.69240.0110.151798222.4
2020-12-3167.02.19549.99246.3107.745596228.4
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" + ], + "text/plain": [ + " y gas_regm m_coil_brent_eu ppi_plastic_resins \n", + "datetime \n", + "2000-01-31 41.0 1.289 25.51 139.4 \\\n", + "2000-02-29 41.0 1.377 27.78 141.7 \n", + "2000-03-31 45.0 1.516 27.49 146.3 \n", + "2000-04-30 47.0 1.465 22.76 151.4 \n", + "2000-05-31 47.0 1.487 27.74 155.6 \n", + "... ... ... ... ... \n", + "2020-08-31 57.0 2.182 44.74 225.1 \n", + "2020-09-30 62.0 2.183 40.91 226.0 \n", + "2020-10-31 62.0 2.158 40.19 238.2 \n", + "2020-11-30 62.0 2.108 42.69 240.0 \n", + "2020-12-31 67.0 2.195 49.99 246.3 \n", + "\n", + " global_proce_of_rubber ppi_nonpackaging_plastic \n", + "datetime \n", + "2000-01-31 29.207387 106.3 \n", + "2000-02-29 33.391099 105.6 \n", + "2000-03-31 30.941913 106.1 \n", + "2000-04-30 31.930148 106.9 \n", + "2000-05-31 31.201702 106.3 \n", + "... ... ... \n", + "2020-08-31 79.961626 214.3 \n", + "2020-09-30 89.312444 220.9 \n", + "2020-10-31 101.520278 224.0 \n", + "2020-11-30 110.151798 222.4 \n", + "2020-12-31 107.745596 228.4 \n", + "\n", + "[252 rows x 6 columns]" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "train" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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ygas_regmm_coil_brent_euppi_plastic_resinsglobal_proce_of_rubberppi_nonpackaging_plastic
datetime
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2021-04-3064.3145602.16074641.936187232.33573156.297387262.183009
2021-05-3163.6283612.22492342.911942232.23851054.856219262.229160
2021-06-3062.8752292.23760742.895561231.51067251.488737262.649328
2021-07-3162.8561612.18673443.166247232.09636447.694820265.383894
2021-08-3163.3891672.15778942.392466232.21487444.505225266.178068
2021-09-3064.4974342.16008640.868551230.81812744.036854267.696240
2021-10-3163.8891882.04158138.617204232.41930141.783832270.536547
2021-11-3062.4618881.89447835.856109229.63177739.779445274.264899
2021-12-3161.1251991.79646934.456708226.81079341.215203275.409212
2022-01-3158.6981101.79177634.397434225.06432944.484229276.394033
2022-02-2859.8323821.81089134.793385227.35071448.289206276.956695
2022-03-3160.9737871.93847335.345039228.14983545.012009278.740158
2022-04-3061.0032072.03777336.536566229.28894746.688832280.037818
2022-05-3160.5538082.11235436.901070229.83377944.720607280.056975
2022-06-3059.8122302.09086536.597267228.69039842.391046280.944455
2022-07-3159.6190582.05470836.905036228.91036037.938332282.393380
2022-08-3159.7717022.01747735.340195228.54073834.924627283.883950
2022-09-3060.9984721.98871034.378336227.98938634.036031286.052102
2022-10-3160.5264081.88014332.414343228.74055232.388463289.091358
2022-11-3059.5947361.78077130.197327227.19578929.776547292.391035
2022-12-3158.4447631.68300328.554202223.35907331.186107292.907592
\n", + "
" + ], + "text/plain": [ + " y gas_regm m_coil_brent_eu ppi_plastic_resins \n", + "datetime \n", + "2021-01-31 62.685334 1.903960 40.687691 227.360053 \\\n", + "2021-02-28 62.989694 2.004521 42.041232 230.720288 \n", + "2021-03-31 64.360850 2.103394 42.033218 232.234552 \n", + "2021-04-30 64.314560 2.160746 41.936187 232.335731 \n", + "2021-05-31 63.628361 2.224923 42.911942 232.238510 \n", + "2021-06-30 62.875229 2.237607 42.895561 231.510672 \n", + "2021-07-31 62.856161 2.186734 43.166247 232.096364 \n", + "2021-08-31 63.389167 2.157789 42.392466 232.214874 \n", + "2021-09-30 64.497434 2.160086 40.868551 230.818127 \n", + "2021-10-31 63.889188 2.041581 38.617204 232.419301 \n", + "2021-11-30 62.461888 1.894478 35.856109 229.631777 \n", + "2021-12-31 61.125199 1.796469 34.456708 226.810793 \n", + "2022-01-31 58.698110 1.791776 34.397434 225.064329 \n", + "2022-02-28 59.832382 1.810891 34.793385 227.350714 \n", + "2022-03-31 60.973787 1.938473 35.345039 228.149835 \n", + "2022-04-30 61.003207 2.037773 36.536566 229.288947 \n", + "2022-05-31 60.553808 2.112354 36.901070 229.833779 \n", + "2022-06-30 59.812230 2.090865 36.597267 228.690398 \n", + "2022-07-31 59.619058 2.054708 36.905036 228.910360 \n", + "2022-08-31 59.771702 2.017477 35.340195 228.540738 \n", + "2022-09-30 60.998472 1.988710 34.378336 227.989386 \n", + "2022-10-31 60.526408 1.880143 32.414343 228.740552 \n", + "2022-11-30 59.594736 1.780771 30.197327 227.195789 \n", + "2022-12-31 58.444763 1.683003 28.554202 223.359073 \n", + "\n", + " global_proce_of_rubber ppi_nonpackaging_plastic \n", + "datetime \n", + "2021-01-31 53.775624 259.742879 \n", + "2021-02-28 57.741776 258.022503 \n", + "2021-03-31 55.231873 260.508172 \n", + "2021-04-30 56.297387 262.183009 \n", + "2021-05-31 54.856219 262.229160 \n", + "2021-06-30 51.488737 262.649328 \n", + "2021-07-31 47.694820 265.383894 \n", + "2021-08-31 44.505225 266.178068 \n", + "2021-09-30 44.036854 267.696240 \n", + "2021-10-31 41.783832 270.536547 \n", + "2021-11-30 39.779445 274.264899 \n", + "2021-12-31 41.215203 275.409212 \n", + "2022-01-31 44.484229 276.394033 \n", + "2022-02-28 48.289206 276.956695 \n", + "2022-03-31 45.012009 278.740158 \n", + "2022-04-30 46.688832 280.037818 \n", + "2022-05-31 44.720607 280.056975 \n", + "2022-06-30 42.391046 280.944455 \n", + "2022-07-31 37.938332 282.393380 \n", + "2022-08-31 34.924627 283.883950 \n", + "2022-09-30 34.036031 286.052102 \n", + "2022-10-31 32.388463 289.091358 \n", + "2022-11-30 29.776547 292.391035 \n", + "2022-12-31 31.186107 292.907592 " + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y_pred" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(
, )" + ] + }, + "execution_count": 44, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# [visualise result]\n", + "\n", + "from sktime.utils.plotting import plot_series\n", + "\n", + "plot_series(train['y'], test['y'], y_pred, labels=['train', 'test', 'predict'],pred_interval=y_pred_interval)" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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y
0.9
lowerupper
2021-01-3145.64738980.332514
2021-02-2844.99650579.720147
2021-03-3147.80618081.946651
2021-04-3046.91670781.717843
2021-05-3146.71728581.897287
2021-06-3046.15509980.388300
2021-07-3145.40012780.704215
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2022-05-3143.39345278.458045
2022-06-3041.19004576.874196
2022-07-3142.47326276.948974
2022-08-3141.55535876.598085
2022-09-3044.26791077.547905
2022-10-3143.33356778.796261
2022-11-3042.15518177.192508
2022-12-3141.76503676.426520
\n", + "
" + ], + "text/plain": [ + " y \n", + " 0.9 \n", + " lower upper\n", + "2021-01-31 45.647389 80.332514\n", + "2021-02-28 44.996505 79.720147\n", + "2021-03-31 47.806180 81.946651\n", + "2021-04-30 46.916707 81.717843\n", + "2021-05-31 46.717285 81.897287\n", + "2021-06-30 46.155099 80.388300\n", + "2021-07-31 45.400127 80.704215\n", + "2021-08-31 47.728975 80.796491\n", + "2021-09-30 46.855388 80.944569\n", + "2021-10-31 47.166807 80.699257\n", + "2021-11-30 46.201201 79.818007\n", + "2021-12-31 43.610934 77.577151\n", + "2022-01-31 40.137022 75.430733\n", + "2022-02-28 42.660278 77.719283\n", + "2022-03-31 44.071521 77.503215\n", + "2022-04-30 44.788133 77.706937\n", + "2022-05-31 43.393452 78.458045\n", + "2022-06-30 41.190045 76.874196\n", + "2022-07-31 42.473262 76.948974\n", + "2022-08-31 41.555358 76.598085\n", + "2022-09-30 44.267910 77.547905\n", + "2022-10-31 43.333567 78.796261\n", + "2022-11-30 42.155181 77.192508\n", + "2022-12-31 41.765036 76.426520" + ] + }, + "execution_count": 45, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y_pred_interval" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['y', 'gas_regm', 'm_coil_brent_eu', 'ppi_plastic_resins',\n", + " 'global_proce_of_rubber', 'ppi_nonpackaging_plastic'],\n", + " dtype='object')" + ] + }, + "execution_count": 72, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y_pred_interval.columns.levels[0]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": {}, + "outputs": [], + "source": [ + "interval = y_pred_interval.drop(columns=y_pred_interval.columns.levels[0].drop('y'))[['y']]" + ] + }, + { + "cell_type": "code", + "execution_count": 111, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(
, )" + ] + }, + "execution_count": 111, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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FCWm3tmBGMT5V7bBPsW4jhBDpSPW5qN36JI7Nj6J6HKHHPA4cm5dQu3Upqs8V2/ZbHuvW9qLvkmCkEEIIIeKuozpvrUmNNSFEeywGHffMHMn9c0qwm/Xc++9dLJhRzANzE9OGUHbjg3NHs2jWqKhlJCwGHYtmjeLBuaNj3kYIIdKRRtHj3PFC1GXOHSvQKB1nivd0e9F3aYLBYDDZnUg2p9OJzWajtrYWq9XaYpnb7aasrIzi4mJMJkkRFqIn5PUkRP9RVe+h4KF3ATijIIu3bp7CyMdWt7v+sYfmSY01IURUv992iCyTnnmjc3F5/dia1Z+tdfsS0o6lnm24Ju5Rp5vcTAONPpUci6GXrooQQiRfoKGKg78a0u7yYbccQZuRm7DtRerpKL7WnKQhCCGEECLuwjXVgBZ12aKuKzXWhBAdeG3HUa56eSsvbT1IbqYRg07BatJj0CkJa8eS3Wgx6DDoFH76zucUP7qa1z8+2gtXQwghUoditKMY7R0ssyV0e9F3STAyjV100UXccccdcdvfjTfeyJVXXhm3/QkhhEhfHdV5a01qrAkh2uP2BVhbWg3ABSMGJrk30Y3KyaTa5eXd3ceT3RUhhOhVQdWHdcL8qMusE+YTVNtO9BXP7UXfJcHIXqL6XAQDXgINVQQDXinEKoQQIq2Fa6r1pC6bEEJsKDtJo0+l0GrijIKsZHcnqkvG5AGwel81voD8sCKE6D8UvQXbOXdin/KTSIajYrRjP/f+0GzYekvn20++B/u593dre9F3yZ1/L+jpVPfdceONN7Ju3TrWrVvH888/D0BZWRn19fUsXLiQ//73v1gsFubNm8ezzz5LTk4OAP/3f//Hww8/zL59+8jIyGDixIm89dZbPPXUU7zyyisAaDQaANauXctFF12UkP4LIYTo+0x6LVecXsA9M0fhaPRhNem568KR3Dd7dKTGWp3Hj0mvTXZXhRAp6p2mbMN5o3Mj96Cp5uwhNgZm6DnR4GPzwRpmFKdmBqcQQiRC3f9ewpB/NkO/e4Cgtx7FaCOo+mKOdSg6E7ZJd2Gfsgi/qwKtOQfV50pYrESkBsmM7KJgMIjqc8X8L+Ct63Cq+4DXGfO+ujLX0PPPP8+0adP47ne/S0VFBRUVFWRlZTFr1iwmTpzItm3bePvttzl27BjXXHMNABUVFVx33XXcfPPN7Nq1i/fee4+rrrqKYDDI3XffzTXXXMMll1wS2d/06dMTcYmFEEKkkXv/vYviR1ez+YCjRV22+98O1Vj77/6Tye6iECKFvbunCoB5Y1J3AgOtomHu6FD/3v5chmoLIfqXhv3/ouofX8G1+69oM3LRaA1dzmhU9BY0WgOOTYs59GIJjWX/TlBvRaqQzMguCvobOPDCgJjWVcw5DL15b4dT1dsm3cWhF0tQG6s73d/w22rQxPiittlsGAwGMjIyKCgoAGDJkiVMnDiRxx57LLLeiy++yNChQ9mzZw/19fX4/X6uuuoqhg8fDsCZZ54ZWddsNuPxeCL7E0IIITrzeVU91S4v+VktZ8o2KArVLi+7jtUnqWdCiFRX6XQTDEJupiES7EtVF4/J49UdR9lysCbZXRFCiF4TVAN4KrcAYMgb3+P9aS15qI3VuCs+IOv0G3u8P5G6kpoZuX79ei6//HIKCwvRaDS8+eabLZYHg0EefPBBBg0ahNlsZs6cOezdu7fFOidPnuT666/HarVit9v59re/TX19anyx0WYUEGioimREtqZ6HAQaj6PN6J3g3s6dO1m7di2ZmZmRf2PHjgWgtLSU8ePHM3v2bM4880y++tWv8utf/5qaGrmhEkII0T31Hj+HHG4AxuVntlg2tqn9eVVdr/dLCJFYLq8fr1+lqt6D16/S4PW3eczp9nXatpv1vHXzFMp+MgeTPrUHdF02Lo83bpzMGzdN5lhd6BxcXn+yuyWEEAnlO/E/gr56NPpMDAPP6PH+jIOmAuCp+KDH++pM63k9At46meejFyU1M9LlcjF+/HhuvvlmrrrqqjbLly5dyrJly3jllVcoLi7mgQce4OKLL+azzz7DZArVD7j++uupqKhg5cqV+Hw+brrpJm655Rb+9Kc/JaTPGl0Gw2+LPUCnUfQoRnvUgKRitKOzFFL4tf/GfOyeqK+v5/LLL+fJJ59ss2zQoEFotVpWrlzJ+++/z7vvvsvy5cu577772Lx5M8XFxT06thBCiP7n86rQj4N5mQayMwwtlo3Ly2yxjhAiPbh9AZauLWX5hjIcjT6mDLPzzi1TeWbdfpZvKKMgy8j6W6ezbGMZKzaUd9p2NIaCkgtmFLNo1qiUrTGbZdSx/bCDm17b0Wf6LIQQPeWu2AyAsWAyGqXn73WmpmCk78QuVE8titHW431G03xeD21GAYOuWYPzoxU4d/681+b56O+SGoy89NJLufTSS6MuCwaDPPfcc9x///1cccUVAPzud78jPz+fN998k6997Wvs2rWLt99+m61btzJp0iQAli9fzmWXXcbTTz9NYWFh3Pus0WhiHioNoWi7dcJ8HJuXtFkWnqo+UTNEGQwGAoFApH322Wfz+uuvU1RUhE4X/U+v0Wg477zzOO+883jwwQcZPnw4b7zxBnfeeWeb/QkhhBAdCQcax+ZltlkWfmz38XpUNYiipObEFEKI2Lm8fpauLWXxyj2Rx+6dVcLP3itlyarQ6KaXrp3Asg1lMbcBHI0+Hmna58KZI7EYUqvSVPi8+1KfhRAiHsIZjMZB58Zlf9qMPHS2Efhr9+Ou3ELG8Llx2W9zqs9F7bancWx+FICceb/F+dEKHFtOlbMLz/MBYJt0l8zqnQApO96hrKyMyspK5syZE3nMZrNx7rnnsmnTJgA2bdqE3W6PBCIB5syZg6IobN68ud19ezwenE5ni3+Jksyp6ouKiti8eTPl5eVUV1dz2223cfLkSa677jq2bt1KaWkp77zzDjfddBOBQIDNmzfz2GOPsW3bNg4ePMjf/vY3jh8/zrhx4yL7+/jjj9m9ezfV1dX4fL6E9V0IIUTft6tpCPbYvKw2y4qzMzBoFRp9KgdqGnu7a0KIBNArCss3lEXaORYDc0bnsGJjebfarS3bUIZeSb2vL63Pu7lU7bMQQsSDpzIUjAxnNMZDOLCZqKHaGkUfmddDMedgHjYL586fR13XuWMFGkWfkH70dyn7yVhZWQlAfn5+i8fz8/MjyyorK8nLy2uxXKfTkZ2dHVknmscffxybzRb5N3To0Dj3vqXwVPXDbjnMsFuOMOyWw6HoeoLTfe+++260Wi2nnXYaubm5eL1eNm7cSCAQYN68eZx55pnccccd2O12FEXBarWyfv16LrvsMkaPHs3999/Pz372s0j26ne/+13GjBnDpEmTyM3NZePGjQntvxBCiL7t86bJaVrXiwTQaRVG54Z+kJO6kUKkB4fbh6Px1I/VBVlGquq9kce62m6z/0Yfte7U+zG89Xm3WJaifRZCiJ4KNJ7AVxPKCDcWxCczEk4FNj0V7SeY9YTqcUTK6MUyz4fqqU1IP/q7fjle4N577+XOO++MtJ1OZ+IDkk0ZkNqM0EyAGq2ho9XjYvTo0ZEs0ub+9re/RV1/3LhxvP322+3uLzc3l3fffTdu/RNCCJHeOhqmHX7808o6dlXVc+m4/KjrCCH6DrtJj92sjwTmKus85GUaIo91td1m/2Y9NlPqZai0Pu8Wy1K0z0II0VOeylCwUD+gBK15YNz2a2wWjAwGVTSa+ObQKUZ7ZF6PQEMl2oy8Duf5SFTdyv4uZTMjCwpCM0wfO3asxePHjh2LLCsoKKCqqqrFcr/fz8mTJyPrRGM0GrFarS3+CSGEECJ+fAGVvdWhWQjHdRCMBNglk9gIkRZ8qsqCGacmPax2eVm1p5r55xV1q93aghnF+FQ1gWfQPa3Pu7lU7bMQQvSU5/jH6AeegWnonM5X7gJDzpmhyXu1evy10Utg9ERQ9WGdcBsAamM1jQfXYB1/a9R1w/N8iPhL2czI4uJiCgoKWL16NRMmTABCGYybN2/mBz/4AQDTpk3D4XCwfft2zjnnHADWrFmDqqqce2780oSFEEII0TWlJ1z41SAWg5YhNnPUdcblh2pJ7pZgpBBpwWLQsWjWKIIEWd40E/bja/byzi1TUTQalm0o495/72L9rdPRaGD5hvJO231hZurweUOoRmRf6LMQQvSE6nNhm7iAzDHXorUMQvW54jYfhkbRkX/lPzDmn43qqSUY8MZ14l9Fb8E64XYIBnHu/Dk1G+5j0DVrQKPBueOFZrNp3yazaSeQJhgMBpN18Pr6evbt2wfAxIkTeeaZZ5g5cybZ2dkMGzaMJ598kieeeIJXXnmF4uJiHnjgAT7++GM+++wzTKbQE+LSSy/l2LFj/PKXv8Tn83HTTTcxadIk/vSnP8XcD6fTic1mo7a2tk2WpNvtpqysjOLi4sgxhRDdI68nIfqPNz+t4KqXt3H2YBvbfnRB1HU+OlLLOc+uZ2CGnuOPXNLLPRRCJMp/95/g7CE2at1+cjIM+FWVIKGJXmrdPmwmPW5/AJNOG3Pbp6opPyO1y+sH4Hi9l0FWE/4+0GchhOgq1e+mduuTrQJ38+MWuFP9bmq3PIFz588Tsn/vyc+p+sc1DJixhIyii1E9ThSjDTXgRtGaCDQeRzHa8VbtwDT4vB4fr7/pKL7WXFI/Hbdt28bMmTMj7XAdx29961u8/PLL3HPPPbhcLm655RYcDgczZszg7bffbhHE+OMf/8j8+fOZPXs2iqJw9dVXs2zZsl4/FyGEEEKcsquDyWvCxuRa0GjgRIOP4/UecjONvdU9IUSCqGqQL724Bb1W4b0fTKPQasLQrDJU+HVu0Clda6dudakIi0HH2CdWY9Bp+esNkxjTwfufEEL0RarPRe22p3FsfvTUYx4Hjs1LAEIT9fYggzGy/y2PJWT/APWf/R5fzefUffoilpFfiszroW2a1yPod3PojyWoHgfDvnMgslzEV1KDkRdddBEdJWZqNBoeeeQRHnnkkXbXyc7O7lIWpBBCCCESLzx5zZh26kUCZBh0DLebKa9p5POqeglGCpEGPq+qp9btJ0OvZXRu/wvGNfpV9lQ3UNeUJSmEEOlEo+hx7ngh6jLnjhXYpyxK6f0H1QCeY9tRzDlknXZD1HX09pHorMPxHqvGVfom1jO/26Njiuhk3IAQQggh4i4cjGxv8pqwsXmZlNc0squqnvNHxG8mRiFEcmw6UAPA5KF2dNrUz2aMt/Cw7AZvIMk9EUKI+FM9jqizTp9aVtujTMJ47l/1udAo+shQbzXgQVEM5Mz5BdqMPAi2P7mYbcICNIZMzMNmE2ioQjHa41q3UqTwbNpCCCGE6JuCwWCzYGRWh+uObZrEZtexuoT3SwiReOFg5NSiAUnuSXJkNE1W0+CTYKQQIv0oRjuK0d7BMltK7F/1u6nd9jQHfzWEir/OQfU6cW77GQd/PZTDL43h0G+Kqd3+LKrfHXX7jJIr8R7bzqHfFHHwV0M4+Ksh1G77Wbvri66TYKQQQggh4qrC6Wb4ADP5WUZG5XT8C/K4vExyLAY88sVdiLTwwYGTAEwb3k+DkQYJRgoh0ldQ9WGdMD/qMuuE+QRVX9L3r/pc1G59EsfmR1E9DgbMeBTnRytwbHksknUZrkNZu3Upqs8VZfulMa8vukeGaQshhBAiblxeP9kWA2/dPIW8TAM+Ve1w4onLxuXx9bMHc7zei9ev9okZc0X8uLx+9IqCw+3D3mwG5XBbng99i6PRx2dNk1dNHdZPg5HhzEgZpi2ESEOK3oLtnDshqCZktmtFb8E2+R4gVCOyO/tvXndSMedgHjaL6ne/HXXdaHUoE123UoTI3Z3osaKiIu644w7uuOMOIDTx0BtvvMGVV16Z1H4JIYToXW5fgKVrS1m+oQxHow+7Wc+CGcUsmjUKU9MX9Nbr/+qDgzGvL9JL8+dLQZaR9bdOZ9nGMlZsKJfnQx+1+WBoiPbIgRnkZfXPCanCmZEumcBGCJGmnP97EUP+2Qz97gGC3noUoy1UT7GHgcgwRWfCNuku7FMW4XdVoDXnoHpdMe+/ed1JbUYBgYaqLtWhTHRdTBEiw7RF3FVUVHDppZfGtO5DDz3EhAkTEtshIYQQCefy+nl8zT4Wr9yDozE0hMbR6OORlXt4Ys2+Nl/Mu7q+SC+t//6PXzaOZRvKWLJyrzwf+rBN5aFgZH8dog1SM1IIkf4a9/+Lqn98Bdee19Fm5KLRGuI+sYuit6DRGnBsWsKhF0toLPtX7Ns2qzsZaKhEm5HXpTqUia6LKUIkGNlLXD4v3oCfqsZ6vAE/Lp832V1qweuNX38KCgowGvvnr+FCCNFf6RWF5RvKoi5btqEMvaL0aH2RXpr//XMsBuaMzmHFxvKo68rzoe+odLrJsRiYOjw72V1JmkjNSBmmLYRIQ0E1gKdyKwDGvPEJP57WkofaWI274oOYtwnVnbwNALWxmsaDa7COvzXqutHqUCa6LqYIkTu7XuD2+3jqk7UMevVhBr36EINefZinPlmL25+4J/FFF13E/PnzmT9/PjabjZycHB544AGCwSAQGlq9ePFivvnNb2K1WrnlllsA2LBhA+effz5ms5mhQ4eyYMECXK5TBVqrqqq4/PLLMZvNFBcX88c//rHNsTUaDW+++WakffjwYa677jqys7OxWCxMmjSJzZs38/LLL/Pwww+zc+dONBoNGo2Gl19+OWHXRAghROI43L5IRlubZY0+at2+Hq0v0kvzv39BlpGqem+feT64vH68fpWqeg9ev4rT7WvRTscszs7OOdxeNLuEsvtmc9WZBcnuctLIBDZCiHTmPfEpQV89GkMW+uzTEn4846CpAHi6EIxU9BasZ/8Q+5SfoBjt1Gy4D+vE+djPvS+S8agY7djPvT9Uh7JVVme4bqX93PtjWl90j9SM7KJgMEiDP/YswkAwyDOfrmPxzpWRxxzexkj7zjMuRKvRxLSvDJ0BTYzrArzyyit8+9vfZsuWLWzbto1bbrmFYcOG8d3vfheAp59+mgcffJCf/vSnAJSWlnLJJZewZMkSXnzxRY4fPx4JaL700ksA3HjjjRw9epS1a9ei1+tZsGABVVVV7fahvr6eCy+8kMGDB/P3v/+dgoICPvzwQ1RV5dprr+XTTz/l7bffZtWqVQDYbJLyLIQQfZHdpMdu1kcNKNnNemwmfY/WF+ml+d+/ss5DXqahTzwf+mOdy47Oub9cg66QCWyEEOnMU7EZAGPBFDRK4t/jTYPOBcB3chcBtwOtyd7pNsFgkKp/Xod1wg8Y9t2DqN46FIMV6zk/wj7lXlRPbad1LpvXrQy4KlHMAwk0HI9bXUwhwcgua/B7sf7hvpjWzTFa2P/V+1i+a0PU5ct3bWDhmTMZ8ddHqfZ0Pj288xuPYtHHPvx56NChPPvss2g0GsaMGcMnn3zCs88+GwlGzpo1i7vuuiuy/ne+8x2uv/76yEQ0JSUlLFu2jAsvvJBf/OIXHDx4kP/85z9s2bKFyZMnA/Db3/6WcePGtduHP/3pTxw/fpytW7eSnR0asjNq1KjI8szMTHQ6HQUF/fcXdCGESAc+VWXBjGIeWbmnzbIFM4rbzKrd1fVFemn+9692eVm1p5r55xWxZNXeNuumyvPB5fWzdG0pi5uesy9dOyFU57JZn8N1LgEWzhzZ52cC7+yc+8M16CrJjBRCpLNwhmI4SJho2ow8dLaR+GtL8VRuIaNoXqfb+B37cB9ajfvIeoZ//1hkshmt1tC0z1Bb09RuTzgDsm7XH3HuWI6l5CvkzFrWk9MRzchdfgIVZGRR5a7H4W2MutzhbeS4u56CjKyEHH/q1KktMimnTZvG3r17CQRCN0eTJk1qsf7OnTt5+eWXyczMjPy7+OKLUVWVsrIydu3ahU6n45xzzolsM3bsWOx2e7t92LFjBxMnTowEIoUQQqQni0HHolmjeGBuCXZzKIvNbtbz4NzRLJo1qk1AIrz+g3NHx7S+SC8Wg44fzxrF/XNCz5d7/72LBTOKY37+JEN/rHPZ0Tn3l2vQVZIZKYRIZ+HajcaCqb12TGNT4DPWodoNB94FwDR4Boohs8fHN+ScEao9eWBl5yuLmCX/zq6PydAZcH7j0ZjX1yta7AZz1ICk3WCmMMPK+1+4PeZjx5PF0rLWQX19Pd/73vdYsGBBm3WHDRvGnj1ts1c6Yzabu90/IYQQfYtJr+WCEQO5Z+YonG4/AzMM+FS13aGaJr2WhTNHcu/sUVQ4PeRmGiKPi/S3/bCDs4fYOfTAHBq8AawmPXddOJL7Zo/mqNNNbqYBR6MvZZ4P3alzmZvZtyf06+ic+8s16CoJRgoh0lWgsRq/Yx9wKkDYG0yDpuL6/E+RIeKdCQcNzcPnxuX45qEXgaLHX1uKz7EPvX1Up9uIzvW/nyt7SKPRYNEbY/7nU1VuHzcj6r5uHzcDn6rGvK+u1IsE2Ly55Yv1gw8+oKSkBK02+k392WefzWeffcaoUaPa/DMYDIwdOxa/38/27dsj2+zevRuHw9FuH8466yx27NjByZMnoy43GAyRTE0hhBB9m8vj55Jfb6b40dVoAINO6TSjzWLQ4XT7+dKLWxjx2GoMWrk16S82ltVw1ctb+dFb/yM304hBp2A16THoFH67+QDFj66OOow/WcJ1LoEWdS6jrptCdS57oqNz7i/XoKssRhmmLYRIT+FgoH7AGLSmAb123EhmZOUWgkG1w3WDfg/uQ+8B8QtGKoYsTIXTASQ7Mo7kjj/BLHoDi86axQPj52I3hLIE7QYzD4yfy6Lxs7Do45vt2NzBgwe588472b17N3/+859Zvnw5P/zhD9td/8c//jHvv/8+8+fPZ8eOHezdu5e33nqL+fND09qPGTOGSy65hO9973ts3ryZ7du3853vfKfD7MfrrruOgoICrrzySjZu3Mj+/ft5/fXX2bRpExCa1busrIwdO3ZQXV2Nx+OJ70UQQgjRa7YechBQg5h0CgXW2At8D8ww8HlVPcfrvRyrk8+B/uLjCicAxdkZbZbNKsml2uXlLzuO0pgiQR2fqnL7jCKAFnUuownXuezrOjrn/nINukoyI4UQ6SoyRHtQ7w3RBjDknIlGb0H11uI7uavDdd0V7xP0N6DNKMCQc1bc+hAObDY2DQEXPSfByF5g0ulZeOZMKr72Uyqve4iKr/2UhWfOxKRN7K/F3/zmN2lsbGTKlCncdttt/PCHP+SWW25pd/2zzjqLdevWsWfPHs4//3wmTpzIgw8+SGFhYWSdl156icLCQi688EKuuuoqbrnlFvLy8trdp8Fg4N133yUvL4/LLruMM888kyeeeCKSnXn11VdzySWXMHPmTHJzc/nzn/8cvwsghBCiV206UAPAtOFd+7VcUTQMsoaGch51uuPeL5GadhypBWBCobXNsgtHDGT4ADO1bj/vfF7V212LymLQ8cPzR/SpOpc9pQALZrR/zv3hGnRVJBiZIkF0IYSIl4DrGIo5p9eDkRpFhzF/Eoo5B9/JjkdMeKt2ophzMA+f0+WRpR0JByM9xz8lGIhenkR0jSYYDAaT3Ylkczqd2Gw2amtrsVpb3hC73W7KysooLi7GZOo707hfdNFFTJgwgeeeey7ZXREioq++noQQsbnixS3847Nj/OxLp/GjC0Z2adupz/+XLYccvHHjZK44oyBBPRSpotEXIOsn/0YNwuEH5lJoa/uZsOy/+xk+IIO5o3Op9/qxm/Sh8jZJCnAddjRy8a8/4NFLx3Hp2Dycbh82kx63P4Beq3CszkN+lhE1GEy5IJzL60evKDjcPuxNfTbptJ22j7s8DDDrqXZ5KcgyUdvsnE06bbvtZP6dkm1daTUzf7GJsXmZfHbPzGR3Rwghekz1udAoevz1R9Fm5KL66tFl5PdqHzzHP0ZvH4nqrkGbkYca8KBojageB4rRHmkHXBUo5hwCrmPo7SPidvxgUKWxfCWmITNQvXVoTdkEVV9kxm1xSkfxteb6512CEEIIIeIqGAw2y4zM7vL2hTYTHJLMyP7if5V1qEHItRgiWbGtfefcYTyxZh83vbYDR6MPu1nPghnFLJo1KimT2vzhw8PsOlbPc+tLufKMgsjELAadws/eK+WVbYeYOXIgz3/5zF7vW0fcvgBL15ayfEMZBVlG1t86nWUby1ixobzTdvi63z6jiHtnlbQ4Z6D9dj8efJWhD329kmHaQoh0oPrd1G57GueOFyKBP+uE+dgm34Oi653kEtXvpmHfGzh3vIA2o4BB16zB+dEKnDt/3qadqD4GA148FZs4/vYNSbsO6UaCkUIIIYTosdITDVS7vBi0ChMHt/8raHsGNdWYlGBk/7DjaGiI9vhCa9RhVC6vn6VrS1myam/kMUejLzKhzcKZI3s18y4YDLKpvIYci4FvThraZvmwAWY+razDYkiNmb/DwtdxcdN1e+naCSzbUBa5rp21IXTdF6/ciwZNr1/3vijDIMO0hRDpQfW5qN32NI7Nj556zOPAsXkJALZJdyU8M7B1H3Lm/RbnRytwbHksajsRfYz0IYHH6I/678+Wae69996TIdpCCCF6zaYDJwE4Z4gNo67rAZlCqRnZr+w8Gpq85qwo9SIB9IrC8g1lUZct21CGXum9W1iX1483oPLclWdQdt9srj5zUJt1xuVlArCrqp5UqoDU/DrmWAzMGZ3Dio3lMbVb6+3r3leFA9KSGSmE6Os0ih7njheiLnPuWIFGSewcGK37oJhzMA+bhXPnz6O2E9XHVLgO6UjuKIQQQgjRY5vKQ0O0p3Zx8pqwwqbMyIpaCUb2B+Fg5IRCW9TlDrcPR2P0AvGORh+17t4pHh8e4jzo4ZWMfGw1Qxev4tn1+3G3ynorybWgaMDp9lOZQjPCN7+OBVlGquq9Mbfb7KsXr3tf1nwCm1QKTAshRFepHgeqx9HBstpe7YM2o4BAQ1W77UT1MRWuQzqSYKQQQggheuyDbs6kHRaewOSoM3UCOSIxVDUYCUaObycz0m7SR2ZnbrPMrMdmSnwWgsvr5/E1+1i8ck8kQBceKv7Emn24vP7IukadlhEDQ0O0dh2rT3jfYtX8OlbWecjLNMTcbrOvXrrufV1Gs6H6br+axJ4IIUTPKEY7itHewbLoPygmqg+Bhkq0GXntthPVx1S4DulIgpFCCCGE6JF6jx81GCTHYmBaUc8yI2WYdvorr2mgzuPHoFUY2zS8uTWfqrJgRnHUZQtmFONTEx/k6epQ8VNDtesS3rdY+VSV25uuY7XLy6o91cw/ryimdmu9dd37OnOzyZWaB6yFEKKvCao+rBPmR11mnTCfoJr4bPnmfVAbq2k8uAbr+FujthPVx1S4DulIKlALIYQQottcXj86rYY3bppCXqah2/sJByOrXV48/kC36k6KviGcFXl6QSZ6bfTfxS0GHYtmjQJCgb9kzKYdy1Dx8OzRAGPzMvnHZ8f4vCp1MiMtBh13XjiCYDDIio3l3PvvXay/dToaDSzf0Hk7FWYx72u0igajTsHjV0N1I2VOAyFEH6XoLdgm3wMEkzab9qk+hOoz1my4j0HXrAGNBueOF9q0E9HH1n2IHGP8rTKbdg9IMFIIIYQQ3RKup7c8DsGi7Aw9Bq2CN6BS6fQwPDsjQb0WybYjMkS742FNJr2WhTNH8pPZJRx1usnNNFDn9vdaQCw8xDlaQDLakOVwlmcqBSMBbn/jE646s5CjD86lzuPHatJz14UjuW/2aGrdvk7bNpMen6pKILILLAZtKBgpM2oLIfo4RWfCMuZr2CbdjequQZuRR1D19WoATtGZsE26C/uURaieWhSDFes5P8I+5d7obaMt7n1s3oeA+ySKIYvGQ+8Bmrgdo7+RYdpCCCGE6LKu1NOLhUajYZDMqN0vfHw0VOi9vXqRzVkMOgw6hZ+9V0rxo6t5ZdvhRHcvIjTEuSjqsmhDlsflZwGpVTPS6fbx6kdHuerlrVQ43eRmGjHoFKwmPQadEnPbYpD8ha6ITGIjM2oLIdJA3c5fcOjFElx7/g+N1oCi7/2Ub0VvQaM1oM3IDf3XYO2wnYg+nupDHkf/MpOqv3+Zhv1/j/tx+gsJRnaTN+Cnwe/ttX/egNScidVFF13EHXfcEWkXFRXx3HPP9Wif8dhHZ15++WXsdntCj5Fo5eXlaDQaduzYkeyuCCESrKv19GIhdSP7h0ZfgByLgQkxBCPDxuRlUu3y8u7uqgT2rCWLQceCGSO4f05JZFIXu1nPg3NHs2jWqDYBunBm5FGnG2eKzDq9dt8J/GqQkQMzKB4o44V7S3gSG8mMFEKkA+/Jz1Ebq1FM3asLnm40GoWM4ksAcO2TYGR3pfzPnHV1dTzwwAO88cYbVFVVMXHiRJ5//nkmT54MQDAY5Kc//Sm//vWvcTgcnHfeefziF7+gpKQkYX3yBvxsqT5Ivc+bsGO0lqk3MCVnGAZtbH+yzq4bdH7tPB4P3/nOd3jrrbcoKCjg5z//OXPmzIls/9RTT3Hw4EGWL18e35ONs61bt2KxxHYD/vLLL3PHHXfgcDi6vY/uuvbaa7nsssu6tM1FF13EhAkTEh4oFUKI1rpaTy8W4WBkhcyo3YbL60evKDjcPuwmPW5/AJNOG2n7VDXls9fC5/CLr4wnL9OAPxCMedtLxuYBsKH8JPUeP5nGxJ/rx0edfO0P23nisnFU/HQezk6GLNvNegqyjFTWefi8qp4pw5L/pe2dpuDtxWPyktyT/iWcGemSzEghRBrwnfwcAH322CT3JHVknX4zxvzJmIfNItBwDMU4ADXgQdEaIzUlO2sHVV9SskxTRcpnRn7nO99h5cqV/P73v+eTTz5h3rx5zJkzhyNHjgCwdOlSli1bxi9/+Us2b96MxWLh4osvxu1OXFaFP6hS7/NiUHRk6YwJ/2dQdNT7vPiDsc9g2Nl1g86v3a9+9Su2b9/Opk2buOWWW/j6179OMBj64lBWVsavf/1rHn300fhe3CZeb/wCvbm5uWRk9Kz2WDz20Rmz2UxeXnK+LMTzegsh+odwPb2oy6LU04vFIJtkRkYTrs1Z8PC7XPTz93G6fTy9LtQueOhdCh5+l6fWluJO4Sys5ucw8rHVDF28imfX74+5z6NyLIwYmIEvEGTtvuoE9zbklW2H+Lyqnt9tP4QxxiHLkRm1U2CodjAY5J3dxwG4eExuknvTv0QyIyUYKYTo41SPk4DrKAAGCUZGaC0FeI9t59Bviqn461xUrxPntp9x8FdDqPjrnA7b4X+1236G6u+/97wpHYxsbGzk9ddfZ+nSpVxwwQWMGjWKhx56iFGjRvGLX/yCYDDIc889x/33388VV1zBWWedxe9+9zuOHj3Km2++mfD+GRUtJp0+4f+MStcKhnd23YCYrt2uXbv40pe+xOmnn85tt93G8ePHqa4OfQH4wQ9+wJNPPonV2vkQqxtvvJErr7yShx9+mNzcXKxWK9///vdbBMAuuugi5s+fzx133EFOTg4XX3wxAJ9++imXXnopmZmZ5Ofnc8MNN0T6AOByufjmN79JZmYmgwYN4mc/+1mb47ceYu1wOPje975Hfn4+JpOJM844g3/+85+899573HTTTdTW1qLRaNBoNDz00ENR93Hw4EGuuOIKMjMzsVqtXHPNNRw7diyy/KGHHmLChAn8/ve/p6ioCJvNxte+9jXq6uravU6th2l3to8bb7yRdevW8fzzz0f6W15eHtN1i3a9v/71r3Pttde26JPP5yMnJ4ff/e53ALz99tvMmDEDu93OwIED+eIXv0hpaWm75ySESF8+VWXBjOKoy6LV04tFYVPNyAoJRka0rs35+GXjWLahjCUr98alVmdviFd90XmjQwG1jWUnE9bXMH9AjWQVfnPS0Ji3GxuuG5kCk9iUnXBhMWgZZDUyc1ROsrvTr0RqRqbwDwRCCBELX81uALSWQSjGjiee6y9Un4varU/i2PIYqsfBgBmP4vxoRcxtANXjwLF5CbVbl6L6XMk9oSRJ6WCk3+8nEAhgMrWcBclsNrNhwwbKysqorKxsMXTYZrNx7rnnsmnTpnb36/F4cDqdLf6lk86uGxDTtRs/fjwbNmygsbGRd955h0GDBpGTk8Mf//hHTCYTX/7yl2Pu0+rVq9m1axfvvfcef/7zn/nb3/7Gww8/3GKdV155BYPBwMaNG/nlL3+Jw+Fg1qxZTJw4kW3btvH2229z7Ngxrrnmmsg2CxcuZN26dbz11lu8++67vPfee3z44Yft9kNVVS699FI2btzIH/7wBz777DOeeOIJtFot06dP57nnnsNqtVJRUUFFRQV333131H1cccUVnDx5knXr1rFy5Ur279/fJpBXWlrKm2++yT//+U/++c9/sm7dOp544omYr1ln+3j++eeZNm0a3/3udyP9HTp0aEzXLdr1vv766/nHP/5Bff2pL1DvvPMODQ0Nkb+1y+XizjvvZNu2baxevRpFUfjyl7+M2o2ggxCib7MYdNx14ciY6+nFQmpGttW8NmeOxcCc0Tms2Fgedd3u1upMtHjVF736rEG8ceNkHpg3mqp6D16/itPtw+tX2213Fuh0ef1Rtz/u8rL5h+fzz29P4dKxsY9aCGdG7q5q/8fH3uDy+im0mXnr5insXTQbjUz22asskhkphEgT3pO7ANAPGJPknqQOjaLHueMFABRzDuZhs3Du/HlM7dacO1agUbo+migdpHRxoaysLKZNm8bixYsZN24c+fn5/PnPf2bTpk2MGjWKyspKAPLz81tsl5+fH1kWzeOPP94mEJZOOrtuQEzX7uabb+bjjz/mtNNOIycnh7/85S/U1NTw4IMP8t5773H//ffz6quvMnLkSF588UUGDx7cbp8MBgMvvvgiGRkZnH766TzyyCMsXLiQxYsXozR9CSkpKWHp0qWRbZYsWcLEiRN57LHHIo+9+OKLDB06lD179lBYWMhvf/tb/vCHPzB79mwgFGAbMmRIu/1YtWoVW7ZsYdeuXYwePRqAESNGRJbbbDY0Gg0FBQXt7mP16tV88sknlJWVMXRoKFvid7/7Haeffjpbt26N1OVUVZWXX36ZrKxQlsQNN9zA6tWruzS0vaN92Gw2DAYDGRkZLfq7YsWKDq9b+LxbX++RI0disVh44403uOGGGwD405/+xJe+9KXI8a+++uoW/XvxxRfJzc3ls88+44wzzoj5vIQQ6eG2v33MVWcVcuTBudR7/B3W04tFJBhZKzUjw5rX5izIMlJV7417rc5Ei1d90elF2Ty+ei83vbaDgiwj62+dzrKNZazYUN6m7Wj0YTfrWTCjmEWzRkV9ToaHji/fUNbu9rfPKGLWqBxifUqHJ7FJZmZk8/OK5TqI+Mto+jFGMiOFEH2d72QoM1LqRZ6iehyRDEdtRgGBhqqY29H3VYs2o/+VU0m9n89b+f3vf08wGGTw4MEYjUaWLVvGddddFwlgdce9995LbW1t5N+hQ4fi2OPUEI/rptfreeGFFygrK2Pr1q3MmDGDu+66iwULFvDRRx/x5ptvsnPnTqZOncqCBQs63Nf48eNb1FycNm0a9fX1La79Oeec02KbnTt3snbtWjIzMyP/xo4NvQmWlpZSWlqK1+vl3HPPjWyTnZ3NmDHt/2qzY8cOhgwZEgnIdceuXbsYOnRoJBAJcNppp2G329m1a1fksaKiokgQD2DQoEFUVXVtFtDu7KOz6xbW+nrrdDquueYa/vjHPwKhLMi33nqL66+/PrLO3r17ue666xgxYgRWq5WioiIgNGxdCNG/7D/h4g8fHuHqV7ZS0+CNqZ5eZyQzsq3mtTkr6zzkZRriXqsz0eJRX9Tl9fPEmn0sWbU36nD1rg5fj3X4++KVe7s0lHxcfigYWXqiAa+/90cNxGtIvOgZs14yI4UQ6SE8eY3UizxFMdpRjHYAAg2VaDPyYm5H31f/HP6e8sHIkSNHsm7dukjgasuWLfh8PkaMGBHJBmteqy/c7iizzWg0YrVaW/xLNx1dN6Bb127t2rX873//Y/78+bz33ntcdtllWCwWrrnmGt57770e97n1bNX19fVcfvnl7Nixo8W/vXv3csEFF3TrGGazucf9jJVe3/LLlUaj6fJw5u7sI9brFm128Ouvv57Vq1dTVVXFm2++idls5pJLLoksv/zyyzl58iS//vWv2bx5M5s3bwZkAhwh+qO3P68KDRsuyaHQFp/31sKmCWxqGn00SkYR0LI2Z7XLy6o91cw/ryjqut2t1ZloPlXl9hlFUZfF2ueOhqt3Z/h6ooa/F1pNZBl1DDDrOeRojGmbeIrXkHjRM+EJbGQ2bSFEX+erCc+kLcO0w4KqD+uE+QCojdU0HlyDdfytMbVbs06YT1CNPnok3aX0MO3mLBYLFouFmpoa3nnnHZYuXUpxcTEFBQWsXr2aCRMmAOB0Otm8eTM/+MEPktvhFBHtugFdvnZut5vbbruNP/7xj2i1WgKBQGRmbZ/PRyDQ8c3Wzp07aWxsjAQDP/jgAzIzM1tkF7Z29tln8/rrr1NUVIRO1/apOnLkSPR6PZs3b2bYsGEA1NTUsGfPHi688MKo+zzrrLM4fPhwi+HKzRkMhk7PZdy4cRw6dIhDhw5F+v/ZZ5/hcDg47bTTOtw23qL1t7Pr1pHp06czdOhQXnvtNf7zn//w1a9+NRIQPXHiBLt37+bXv/41559/PkCkBqkQov9wef3oFYXLxuXzrclDqXDGb0i1zaTDpFNw+1UqnG5GDGz7o0l/YzHoWDRrFEGCLN9Qzr3/3sX6W6ej0cDyGIcjJ0v4ueL2qSyaVQJouj10uKPh6t0Zvp6o4e8ajYY3b5rMlGF2at2hepQ+Ve1RxnBXxGtIvOgZmcBGCJEOggEvPsd+QIZpN6foLdgm3wOEaj7WbLiPQdesAY0G544XOm2rHgeK0Y51wnxsk+9B0Zk6OWJ6Svlg5DvvvEMwGGTMmDHs27ePhQsXMnbsWG666SY0Gg133HEHS5YsoaSkhOLiYh544AEKCwu58sork931pOrougFdvnaLFy/msssuY+LEiQCcd955LFy4kJtuuokVK1Zw3nnnddgfr9fLt7/9be6//37Ky8v56U9/yvz58zscNn7bbbfx61//muuuu4577rmH7Oxs9u3bx6uvvspvfvMbMjMz+fa3v83ChQsZOHAgeXl53HfffR3u88ILL+SCCy7g6quv5plnnmHUqFF8/vnnaDQaLrnkEoqKiqivr2f16tWRoeXNh5cDzJkzhzPPPJPrr7+e5557Dr/fz6233sqFF17IpEmTOrwO8VZUVMTmzZspLy8nMzOT7OzsTq+bVtvxl76vf/3r/PKXv2TPnj2sXbs28viAAQMYOHAgv/rVrxg0aBAHDx5k0aJFiT5FIUQKSXQtOo1GQ6HNxP4TDRyVYGSESa9ldkku98wchdPtx2rSc9eFI7lv9mgq69wMtBioqvemVCCy9XNlyjA7v/rKWdw3u4Rat6/L9UXDQ70djb4Ww9WjtdtsG2UoeEf7i2X7js577b5qrn5lW1ICxc3Pq82yFB3Gn44yZJi2ECIN+Bz7IBhAY8hCaylMdndSiqIzYZt0F/Ypi1A9tSgGK9ZzfoR9yr2xtY02gqqv3wYioQ8M066treW2225j7NixfPOb32TGjBm88847kWyte+65h9tvv51bbrmFyZMnU19fz9tvv91mJulE8KgB3H5fwv951K7fyHR23SD2a/fpp5/yl7/8pcWkP1/5ylf4whe+wPnnn8/HH3/M888/32F/Zs+eTUlJCRdccAHXXnstX/rSl3jooYc63KawsJCNGzcSCASYN28eZ555JnfccQd2uz0ScHzqqac4//zzufzyy5kzZw4zZsxoUwuxtddff53Jkydz3XXXcdppp3HPPfdEsgunT5/O97//fa699lpyc3NbTPASptFoeOuttxgwYAAXXHABc+bMYcSIEbz22msdHjcR7r77brRaLaeddhq5ubkcPHgwpuvWkeuvv57PPvuMwYMHtwgyK4rCq6++yvbt2znjjDP40Y9+xFNPPZXI0xNCpJDeqkUnk9i0FQwG+cor2yh+dDUnG7wYdApWkx6DTuFXmw5Q/Ohqfr/tcLK7GRHtubLloIMJz6znufX7sRi1Xa4v2tFw9e4MX0/E8PfweYfrWkLv12tsfl6tpeow/nQUnk1byk0IIfqycL1I/YAxaDSaJPcm9Sh6CxqtAW1Gbui/BmuX2oq+f//orgmGx9r2Y06nE5vNRm1tbZv6kW63m7KyMoqLiyNBOm/Az5bqg9T7eq9OXqbewJScYRi0KZ/M2saNN96Iw+HgzTffTHZXRJJFez0JIfoGr1+l4OF32824qvzpPAy6nv/G+bXfb+cvO4/y7BWn88PzR/R4f+ngSG0jQxevQqtocD56aWRyDIBn15dy198/48tnFPD6jZOT2MtTEvVccfsCPLFmH8uazX69fGMZy5vNph1uxzqb9uNr9nZ7+946765yef08uWYfKzam9jD+dPaL98u57W+fcPWZg/jrt3p31IwQQsRLzebHcGx6iMxx3yD34heT3R3RR3QUX2uu70W2UoBBq2NKzjD8wd77dVmnUfpkIFII0T+Fa8U53D7sTcMxe6tmmkiM3qpFN8ga2sfRWplRO2znUScAY3ItLQKRAOMHhWZg3Fnh7PV+tSdRzxWTXsvCmSP5SdNQ7+bD1Zu3fzJ7NBVON7mZBgJqsN0AnEmv5eLRedwzcxS1jf42++vqUPJUqdf4r8+OcfYQO4cfmIvL6+/yeYiek5qRQoh04KvZDUi9SJEY8s2wmwxaHYZkd0IIIVJQousKiuTorVp04WHaFU4JRoaFg5ETCm1tlo0vDP3ivP9EA86mgFyyJfK5Ev5RIxzUC2catm7f8ted7Djq5LUbzmHmqJyo+woGg1z1ylbUILzz3akU2kxt99eFikapUq/x7c+P8/K2Qyy+dAz3zQ5N1teV8xA9d2o27cQPzRdCiERpPkxbiHiTOxORcC+//LIM0Rain+ituoKi9/VWLbpCW1PNyDjO0t3XhYORZxW2Heoy0GJgSNM1+zhFsiNToW5hdoaBapeXTQdq2l2n7GQDVfVeat0+xuVn9viYqXDeAJsOnAROZc2K3icT2Agh+rpgUAWNFsWcI5mRIiEkGCmEECJu9IrC8g1lUZct21CGPoZJlERqshh03HnhCO6fU4LdHMrwspv1PDh3NItmjYrbMPzIBDaSGRmx82gtABOiBCNDj4eCTjuOpEYw0mLQcc/MUQl/rnRk6vABAHxQ3n4wMhyonFhoi0vWtsWgY9GsUTw4d3SXztvl9eP1q1TVe/D6VZxuX4ftjn7UOdngZfdxFwBTh9t7fE6ie8KZkTJMW6STzt6r5Afn9KH6XKD6yLvsjwy9eS+6zMHJ7pJIQzJMO0Yyz48QPSevo/SXKjXTRPwFg0Gu/8OHfHvqcI4+OJc6T2Jq0UkwsiWXx8+e6lBwaXyUYdoQypj8565jKVU38k8fHk5q3cJp4WDkwRqCwWDUWUA3NQUqpxYNiNtxw3UtfzxrFMfqPORnGVGD7detbF7WIjyJzrKNZaxoNqlOuB1L2YsPmgKsJTkWcizyXpss4dm0JTNSpIuO3qukJE96Uf1uarc9jXPHC6geB4rRjnXCfGyT70HRyQSkIn4kRaUTWm3ozdTr7b2Zs4VIVw0NDQDo9cmvaSYSI1wzLeqyXqyZJuJv26Fa/vV5Fdf/cTu+gEpuphGDTol7lls4GOl0+6n3SJbFp5V1BIOQn2UkPyt6cCmcMbnzSG1vdq1dwWCQZ9fv56qXt/LGJxUJe650ZOJgG0adQrXLy76mYG5r4cBdOHAZLxaDjn9+dowvvbiFr/1+W4cZkc3LWjx+2TiWbShjycq9UdvQedmLTQk6J9E1MoGNSCedvVeBlORJF6rPRe3WJ3FsfhTV4wg95nHg2LyE2q1LQxmTQsSJZEZ2QqfTkZGRwfHjx9Hr9SgyxFCILgsGgzQ0NFBVVYXdbo8E+UX6CddMe2TlnjbLwjXTZCKFvmnlnipyLAbmjc4lK4FB5SyTDotBi1mv5YTLS6axf9+q7OhkiDacmsTm08o6/AEVnTa5r7H/VdZx3OXFrFe4/PT8pPTBoFM4Z4iN98tr2HSghpLcljUhXR5/JJM0EYG7EQMz+LSyjmN17dc+bV7WIsdiYM7oHG56bUfUdmvLNpTxk9klbR7f3BSMnCrByKQ6NYGNBCNF39fRe1Vr7b03ib5Bo+hx7ngh6jLnjhXYpyzq5R6JdNa/7/BjoNFoGDRoEGVlZRw4cCDZ3RGiT7Pb7RQUFCS7GyKBwjXTggRZ3mzozu0ydCcpXF4/ekXB4fZhN+nxqypBaPGY2x/ApNN22v762UP44QUjOOFK/EiBv904melFA3C6Q/WpfKraq1l1qSQyec2g9oORIwdasBi0uLwB9hx3cVpBVkL60vr51N5zxWbWU3bfbD6tqEvq7N5Thw+IBCO/OWloi2XbDjsIqEEKrSaG2s1xP/bYpuDncZeXEy4vAy2GNus0L2tRkGWkqt7bbrvNtlHKXgTUIJsPOgCYFseh56LrmmdGtlcmQIi+oqP3qjbrSkmePk31OCIZkdGX1aLNyO3dTom01T/v7LvIYDBQUlIiQ7WF6AG9Xi8Zkf2ESa/l0rH53DNzFMfrveRmGthX7ZJAZC9rXt/J0ehjyjA779wylWfW7Y+pPl2yakK5fQH+u/8E1/5+u9Sh4lQwcsLg9mdGVhQNZw2ysulADTsrnAkJRnantuHtM4oZX2hN2t8tUjcyyozaHxxwRNZJRKDIYtQxzG7moKORz6vqOa84u8064bIWjkYflXUe8jIN7bbbbBul7MVnx+qo8/jJNGo5o6D94LVIvHBmZDAIHn/v1UoVIhE6eq9qs66U5OnTFKMdxWiPGpAMLWv/XkSIrpJgZIwURcFkkoKtQggRizve/JT9Jxu4bmIhf/7oKEUDzGy544Jkd6vfcHn9LF1byuJmw+XvnVXCz94rZcmqvQC8dO2EUM2nGNtwqiYUwMKZI+OerRjud28eM5WpapCPm4YSj+8gMxJCQ7U3Hahh51En102M76yXrZ9PsT5XFq/cg4bk/d2mDQ8FAD+pcFLn9pNlOtWHDw6cBBI7nHlsXiYHHY3sqqqLGoxsXtai2uVl1Z5q5p9XxJJVe9u0W4tW9iJcL3LK0AFoFcnES6aMZsHHBl9AgpGiT+vovao1KcnTtwVVH9YJ83FsXtJmmXXCfIKqD422baa/EN0h7xJCCCHibt8JF9UuL5eNy6fa5WX7kVqqXe3XThPx1by+E5yq8bRiY3m32q0t21CGPgE1lFv3uzeOmcrKaxoozs5giM3E6FxLh+uOL7SSYzFQ2xj/URzR6oUl+7kSi0KbiWF2M9kZBj47Vhd5PBgMUtPoI8diSOhw5rH5oaHau47VR10eLmtx/5wS7GY99/57FwtmFPPA3OhtCGUd3T+nhLsvahvg/V+FkzMKsphVkpOwcxKx0WkVDE21W2VGbdHXWQw6ftzBexWcem9aNGtUv/rRMN0oegu2yfdgP/c+FKM99JjRjv3c+0Ozaes7vhcRoivknUIIIURc1TR4OdkQGrpzXlE2Zw2y8nGFk5V7quOesSWia17fCTqvRxePenWJ6HdvHDNVubx+Cq0m3rp5CvmZRjydTEzzpdMK+MY5Qzhe7417nc141zbsTa/ecA5nDsrC0ejD61dx+wMYdVpe+tpE8jINqGowYccelxcKRu6uih6MhFBZi+lF2fx41ijqPH6sJj13XTiS+2aPptbta9POMuqoqPOgaDRU1Xta1IJ97AvjqKr3MijLiMvrl4BAkmUYtHgbVZlRW6SFTeUnOXuInUMPzKHBG2jx3uRo9GExanl393FOuLwMTkAdXtF7FJ2JzLFfxzbpblT3SbQZ+QRVH4pORomK+OpfKQZCCCESrvREAxAKUmQadVw8JlTo+t3dVcnsVr8Sru8U1rzGU3fabfafoJpQrfvdG8dMReH6jIWPrGTkY6sZsnglT60txd1OUMPtC/DLDw4wdPEqRjy2moKH3+1w/a5q/ndJledKLNy+AP/5/BhDF69i7v/7AKfbx9PrShn08LuMfGw1Qxev4mfr9sftOrU2tikYuauDYOTRWjeX/WYzIx9bjdWow6BTsJr0GHQKuZnGNu0g8NKWgwxZvJKCh97lgp9vxKcGWbq2lKGLVzHysdUUPtLx80X0jvBQbZlRW6SDn79fzlUvb+XJNfvavDflZRm54Y8fcvUr23hp26Fkd1XEgfOTX3PoxRLqP38VjdYgGZEiISQYKYQQIq5KT7gAGDkwA4CLx+QBsPWQg2AwcVlI4pRwfaew5jWeutNuLVwTKtH97o1jphqX18/ja/axeOWeSLZhuG7mE2v24fL6e7R+dzT/u6TKc6Uzp67LXhyNPh6/bFyormVTG+J/nVoblxeaSKi8poHGdgKDm5pqVw6ymsjoJJPR5fXzxJp9LFl16hzCtWAT+fcX3ROexEaGaYu+ztHgi9Sk/cpZhVHXueKMQQD8ftthuddLA76Tu1EbqyNDtYVIBAlGCiGEiKt91aFg5Kic0K+oM4oH8PebJ7P5h+dzrN6D16/KF+QEC9eia17P6fE1e7nropE8OHd0TPXp2qsJ9eDc0QmrCXWq36N77Zippqt1M3ujzmZn9cKS8VzpTEd1LltLVF3L3EwD2Rl6gkHYczx6dmT4C34sE+l0Vgu2tf5YZzWVhDMjZZi2SBSX14/Xr1LVdG/ldPsS0nb5AuxZNIuV35vKWYXRJ1O7+qxBnD3YytIvnoY3cGofPb3f6+o5yv1lfPhOfg6APntMknsi0ln639ULIYToVaXVoWHaI5uCkWoQthx08M0/78DR6MNu1rNgRjGLZo2SGUYTyKTX8sXTCrhn5igcjT5yLUb8qsrCmSP5yeySqPXoOmvbTHp8qprQv5tJr+W75w7jnpkjqXZ5GZRlSvgxU0lX62b2Vp3NzQdq2q0XlqznSkc6qnPZZt0E1bXUaDSMzcvk/fIadh2rZ3yhrc06HzQFI6fFEIzsrBZsm/X7WZ3VVCOZkSKRwuU8lm8ooyDLyPpbp7NsYxkrNpTHvR2+d7t9RhHnFWVHfV/PNOpY9f3pPLOulJtei8/9XlfOUe4v40f1N+J3lgNgyB6b3M6ItCbBSCGEEHF1api2BZfXz9K1pSxZtTeyPDyEEGDhzLYzwor4ufnVHRyr9/DqN85mcIkZQ7MBEeEAhUGndK3dC4Mqql1ezn52PWcUZLHmB9N75ZipIlyfMVqAKVr9xa6u312vf1LBCxvLufvCESy9/HQgNZ4r7Wl+XZrXtUz0dWptbF5WKBgZpW6k16+y/XAtEFswsvXfOpnnJTpnMUhmpEiM8L3V4qZ7qZeunRAqQ9F0rxXvNoTu3Rav3IsGTdR7N5fXz7Pr43e/19Vz7OnxxCm+mj1AEMWUjWLOTXZ3RBrrP3f3QgghesW+pmDk2NzMXhlCKqKrbfTxWVUd1S4vpxdEH1aVqmwmPdUuL1sOOpLdlV7X1bqZvVVn853dxwE4r3hgXPaXaB3VuWwtkXUtO5pR+6MjtXj8KjkWQ6SsRUc6qwXbWn+ps5qqIsO0JTNSxFlHZSji3W6tvXu3UJ+6tk28zjEexxOnRIZoDxiDRqNJcm9EOpOfC4QQQsSNy+OnwukBYMTAjF4bQira2nywhmAQirMzyM/qW9fYagrdnjT4AvgDKjpt//lSEa6bGSTI8hiGnoXXh9AXsFPD6eI3VG3/CRf7ql3oFA0zR/WNYGTr63Lvv3ex/tbpaDTEdF3j5dSM2nVtlkXqRQ4bENMXvmh/68fX7OWdW6aiaDQt/v4yVDH5wsO0pYadiIXL60evKDjcPuwmPW5/AJNOG2n7VDWS6ddRGYp4t1tr794t3vd7XTnHeBxPnHKqXqQM0RaJJcFIIYQQcbP/ZKhe5ACzHptZj9evyhDCJNnUhVp0qSbLeOr2xOnxk51hSGJvep9Jr+VLrep9dlR/0aTXRmqBHqv3kJ2h50itO26BqHBW5PSiAVj70Gu2+XVJVl3LcfmhYOSe4y4CahCtciroGK4XObUo9tdo63OymfRtasEmu16nCDHLBDYiRh3VRoz2A0NHZSji3W6tvXu3eJcM6co5xuN44hTfyd2A1IsUidd/Ug2EEEIkXOuZtHtrCKlo64MuzNKbagw6BVNT/UGnu39mFd3/9ucUP7qaLQcdGHRKp7WvLAYdBp3CazuOUPzo6nbLI3THu7urAJg3Ji9u++wt4euSm2nEoFOwmvQt2omuKTZ8QAYmnYLHr1LW9GNN2KYDJ4Gu/2DQ+pwyDLo2j0mttOSTYdoiFi6vn8fX7GPxyj2hbOfLxoVqIa7cGwm0hWshPrFmHy6vv8MyFPFut9bevVu87/e6co7xOJ44xVsjM2mL3iF3KkIIIeKm9ETTTNoDM4D2h5DKEMLEUtXgqVl6u5B1lUpsZj3uOk+/DUbuq3ZR7fKSndG17I6CLBPVLi8fH3XGpR9ev0plnYcci4FLxkgh+67SKhrG5GVypNbNkVp35IeaCmcjNpMeT6bK5KH25HZSJIRMYCNiEa024k2v7Yi67rINZfxkdgkGncLdF41EDQZZsbG8TRmKeLdjuXeL9/2exaBj4czYz7H5jN9yf9l9QTWAvyY0KZA+eyxOr5sgQax6k9SPFHEnwUghhBBxE86MHNlsMobmwwor6zwMtOg55IjfEFLR1udV9dS6/Zj1CmcN6luT14RZjTqO1XlweqLXhEpnvoDKgZpGgJgmNmlufGHo772zwkkwGOzSl4doNcuMOoU/feMc8jINEOxSV0STX1x9FmcOysLR6MPrV3H7AwzIMPDWzVPIzzTIZU1T4ZqRkhkpOtJRbcQ26zarhbjsv2WcPcTOkQfnUu/xtylDEe92LOUfwvd7984uocLpJjfTQJ3b3+37vaffK435HE80eLGadPy39ASGflRnOt78znKCAQ8arQk1YzA7Thym3ufFbjBRmGFjgNEc18BkMBjEHfBj0uok2NkPSTBSCCFE3Oxvmkl71MCWAZTwkMF3dldx338+57yiAbxx05Re719/8cHBUFbk5KF29H30pjw8iU1tY//LjDxY04hfDWLWKwzKMnVp27F5mRi0Ck63n/KTjRQ3ZSl3pqs1y0Rs3L4A//78GJf9ZrNc135GhmmLWHRUG7HNus1qIf5++yF2H3fx95un8MXT8oFQiRMgMnFL3NsxVHgL3++t2FDG77Yf5utnD+a5K86I8Wqc4vYFeP6/oQzL926dxgUjcjrsY7ZZz+lPvcf+kw2s+t40ZpXkdPmYovlM2iVUelyc8LjINWbh9Hk4duIIRq2OoRYbY2x5GLTdDyX51QDVbheHXbXUeBuw6Azkm7OwG8xYDSb0inwe9gd98xuKEEKIlHQqMzJ6AOTsITaqXV7W7DuBLyD1fBLlYE0jORYDU4dnJ7sr3WZtmsTG6el/wch9TUH9EdkWFKVrmQJ6rcLpBaFJU3YcrY1pm+7ULBOdC1/X8HWU69q/ZMgwbdEBl9eP16/i8vnbrY3YWrgWYvnJBnYfd6FVNJxfnJqf8zNH5VDt8vLnD490635v3f4T6BQNQ2wmzisa2On6Rr2W2aNDAcg3Pqno8vFEiLcpGKkMGMP+upNk6kyYdXpyTZkMyxyAVW9in7OanSeP4vJ5Ot2fy+eh1FlNed1JDtU7OOKqpbzuJJuqytl8/CCVjXUYFB11Pi+f1FTyflUZH1QdoMHvTfSpihQgmZFCCCHiwutXOehoGlo6MPrQ0omFNnItBo67vGwqr+GCkZ3fYIrYhYfZ3jR5KAtnjuR4fd+9mbOZQ9kfTnf/G6ZdWh2qvTqqnaB+Z8YPsvHRESc7jzr58pmDOl2/OzXLROfkuvZvkhkp2hMtEz1IsMNaiPPPO1UL8Q+7DwOhya/Cn5Wp5uIxucwozuauC0cSUIPUNHoi5T9MOm2LciDR2uPysii7bzb7qkNB11h8f9pwLhubz5zROVTVebCbQ0PLW0/oFa0kSfM+RNumv/DVhGbSbswswuFpZIjF3mK5WaenMMPOkYZaGgM+TrcXMNDUfjmZ8voaPnMcQ68oENSgUYKoKmToDBSYreiUUG5cpj6U6epXVY421FLR4GSkVbJb011KZ0YGAgEeeOABiouLMZvNjBw5ksWLFxMMnqquEwwGefDBBxk0aBBms5k5c+awd+/eJPZaCCH6p/KaBtRgqGh/fpYx6jqKomHu6NAkGO/sqerN7qW98Jebgoffpfix1QxdvIqXtx7C3UezciKZkf1wAptIZmQ7Qf3OjB/cVDcyxszI7tQsE52T69q/SWakiKZ1JvrnVfVc8PP3mTg4VBvxvVunR2ohVv50HpUPzePQA3OYONjG51X1ALy7+zgA81J4UjGdVuHvN09h+2EHhY+s5KKfv4/T7ePpdaH7lM7aRY+uYujiVbzxSWXM9zHj8rLYftjB0MWrKHj4XQoefpen1pa22L75vVLrYxY8FH2b/iQ8TPu4sYAsvRElSh1HnaIwJMNOrdfN9upDVDZEnzCvzufmsMtBnimToZYBDM20MyRjAMMyB5BjskQCka33naU3ctDlwBPof/d//U1KByOffPJJfvGLX7BixQp27drFk08+ydKlS1m+fHlknaVLl7Js2TJ++ctfsnnzZiwWCxdffDFutzuJPRdCiP4nMkR7oKXDItThm+d3Pj/eK/3qD1p/uYG+P/wzy9R/h2mXNr2Wujp5Tdj4QeFgZGwzaodrlgEtapZFXbdZzTLRMbmu/Vs4s0oyI0VzzTOmwz6vqueql7dy1tPvMcCkx6BTsDb9Ny/TyD3/+IyrX9nG//vgAL6Ayup91QBcPDovGacQE5fXz7PrS1myKnqZis7a0LX7mEhZjFXtby8lSToWDAYjwciT5iHYDeZ219VoNBRm2AgEYVdtVdRh1UdctTQEfJGsx1jZDGYc3kaqGuu7dgKiz0npYOT777/PFVdcwRe+8AWKior4yle+wrx589iyZQsQesE899xz3H///VxxxRWcddZZ/O53v+Po0aO8+eab7e7X4/HgdDpb/BNCCNEzR2rdnFGQxdmDO569eV5TZuRBRyMnXH13GHEqifblJmzZhrLQ8Jg+JjKBTT/MjCw9EQ7sd3OYdtOM2uU1je1m4jXnU9Uu1ywTnZPr2r9Fhmn30wwrEV3zjOnWSk804IiSIR0ut/HajqO8X36SYXYzo3MyOHuILaF97YnQfUk5cKpMxYqNsbVbi+U+Jpb7oGilM3pyzHQTaKhCmzkEjTkXY/bomGa3zjVZcHgaKas72WL0qsvn4ZDLwYAOAprtUTQazFo9B101BORzMa2l9Cts+vTprF69mj179gCwc+dONmzYwKWXXgpAWVkZlZWVzJkzJ7KNzWbj3HPPZdOmTe3u9/HHH8dms0X+DR06NLEnIoQQac7l9fONc4bw1s1TeOHqszr8NbnAamLV96ZSdt9sPH41VMC9n/36HG8dfbnpq8M/w1lidX2w7z2hqkFKT4RrRnYvM3JAhoFh9tAXgI9jyI60GHT8eNYo7p9Tgt2s595/72LBjGIemFsSyeSzm/U8OHc0i2aN6re1tLrKYtCxaNYoHpw7Wq5rPxQepu2SzEjRTPOM6TbL2smQnjkqh4tGDuSlaycweaidt26ewod3XoTbn7rPrY7KVHTWbrOvGO5jOrsPqvf6pXRGB1SfC63RTv6XXmfYzXs4O3sQphhmy9ZoNOSYLJTXn6Ta44o8frTBSb3PQ5be1K3+DDCYOeF2tdinSD8pfdezaNEinE4nY8eORavVEggEePTRR7n++usBqKysBCA/P7/Fdvn5+ZFl0dx7773ceeedkbbT6ZSApBBCdFPzQuzhQusLZhRHCq1HW/+9/Sf4yu+2x7S+6Fz4y020m+q+Ovyzv9aMPOp04/Gr6BRNJKDYHRMGWznoaGTH0dqYJoracqCGs4fYOfTAHBq8gUjNsvtmj6bW7cPWVNRfXqNdY9JrWThzJD+ZXUKt2yfXtR+RzEgRTThj+pGVe9osC2dIG1rlC2kVDW/cOJmfrSvlptd29Il7p+b3Jc3LVMTSbrOvGO5jOrsPymz6sSeex0wXqt9N7bance54AdXjQDHayZownzGT7mZ3vRN3J7UbM3QGar1u9tUex24w41dVDrhqsHYjKzJMp2jRaDQcdtWSZ8qMKUtT9D0pnRn5l7/8hT/+8Y/86U9/4sMPP+SVV17h6aef5pVXXunRfo1GI1artcU/IYQQXdfVWoWRmj5Snyeumg8Hba2vDv+09tOakeHaq0XZGei03b9NOytcN7IitlI0q/ZVc9XLW7n3X7vIzTS2qFkWbkvmXvdYDLoW11Gua/8QmcBGMiNFM60z0aHzDGmX188z6/d3WA8x1XRUpqKzdmux3MfEch/kU1VunxG/Y/Z1wWCQusYaHFufxLH5UVSPAwDV46B28xKc255msNEQ075yTZlUuus4WF/D0YZa6rxubN3MigzLNlqobHRS423s0X5E6krpu5+FCxeyaNEivva1rwFw5plncuDAAR5//HG+9a1vUVBQAMCxY8cYNGhQZLtjx44xYcKEZHRZCCH6lc5q9PxkdkmP1hexCQ8HDRJk+YbyPpE10RlrU0ZCbQw1D9NJeCbtUd2sFxk2YXColtjBmthu4j84UAPA6QVZPTquECKkeWZkMBiUzB4R8a/PKjl7iJ3DD8zF5fV3miHdF++dwvclEOrjvf/exfpbp6PRwPIN5Z22u3of0/p44e3nzyhqsf0Pzx9BMAgrNvb8mH2dGgySoc/g8I4Xoi6v27GCoVN+jK7RjT/YcWBWpyjY9BmUOqvRKVqy9KYev+eZtDr8qsoRl4NsY8/uiURqSulgZENDA0qrwrFarRa16VeK4uJiCgoKWL16dST46HQ62bx5Mz/4wQ96u7tCCNHvxFKrMDfT2O3148nl9aNXFBxuH/amG/90ykgy6bWcV5TNPTNH4XT7GZhh6NPDP239NDMyXC9yxMDu1YsMmzTExhs3TmbO6Byq6j0dPucDapDNB0PByGnDs3t0XCFEiKUpMzKgBvEFghh0EowUIS9vPcy/P6/iZ5efxo8uHAnQZmh2c8m8d+qJzspUdNbuahmL5sc72egly6hjzb5qwq+8Sqebub/6gMWXjKXip/NwtjrmUaeb3EwDJ1zePnvv1FUBjyOSEdma6nEQ8NSiUxT8gc6zRG0GE4ddDgJ+L0MtA+LSP7vBzNEGJ8MyB2DrwbBvkZpS+lvY5ZdfzqOPPsqwYcM4/fTT+eijj3jmmWe4+eabgVDB1DvuuIMlS5ZQUlJCcXExDzzwAIWFhVx55ZXJ7bwQQvQDXa1VmKzahl2ta9kXlZ1o4JJfb6Ygy8juH8/EoFM6/HKT6iLDtPtZzcjSpmHa3Z28Jiwv08j2w46Y6ov9r7KOek+ALKNOMiOFiJPwMG0I/Rhm0MU23FGkN6fbx6q91QBcPCYvpm36cl3o8A9g4WCpQad0rd3F+5jw8fIsRs55bh07j9bx6jfO4ZoJhfzxwyP8r7KOpWv3ceUZBW2O+fvth1m+oYxLx+bxynUTu3fCfYzWaEcx2qMGJBWjHa3Rhr/xRMz7K8ywoQaDKHHKBM/UG3F4G9ntOM6EgYUYYphUR/QdKf0tZfny5XzlK1/h1ltvZdy4cdx9991873vfY/HixZF17rnnHm6//XZuueUWJk+eTH19PW+//TYmU89qFAghhOhcV2sVJqO2YVfrWvZV7+yuAqAkx0JWCn8xiZXVGDqHfheMPNHzYGSkNmuM9cU2HTgJwJRhdrSKZG8JEQ96rYKu6fUkk9iIsI1lJ7GadIzOtTAuPzOmbdKxLnSiKYqGy8aFJrl989MKgsEg//gsNMHtN88ZEnWbuaNzqXZ5ef3jCur7yb1HjdtJ1oT5UZdlTZiP0+PqdIh2c4pGg06Jb4ipwGzlSIODvc5qgsFgj/fnCfhp9PevEkCpKqVDy1lZWTz33HM899xz7a6j0Wh45JFHeOSRR3qvY0IIIYCu1ypsr6bP7QnMUuyLtZa64909xwGYNyY3yT2Jj3BmZIMvgC+gou/BZC59RTAYZF91aJj2yB7UjOzqcz5cL3Lq8PgMqxJChGQYtDjdfpnERkRKxZwxyErZfbPZW+2KuaZee/dO6TbCI96+M2UYU4YOYM7oHCrrPPzrO+eyek81F4yMXo7k3GF2Lhmby/emFqHTaiIlTtz+ACadNi3L/OxrcHHOpLuBIHWtZtO2TlrI7vraZHcRnaKQa8qi1FmNVW9iaKa9W/vxqQEqGpzsrzuBVqMwceBgMvWpV96gP0mPV5EQQoikMem1XDY2n3tmjqK20U+OpeNahc1r+lTVexiQoWfXsfqE3Uz31VpLXeELqKzu4rCvVBcORgLUefxkZ6T/EMfj9V7qPH40GijO7n4wsqvP+U0HwvUiJRgpRDxl6JuCkZIZ2a9FKxVz+4xixuZmdqseYnfqKfZHg6wmXtp6qEW5kvnnFbX7o61Go+HP3ziHn71Xyk2v7aAgy8j6W6ezbGMZK9J0gpsGv48Pa45zWvHlDJ10NwF3DdqMXJxuF7vra3EHUiND1KzTYw4Y+Lz2GJl6AwO6MKFNQFU55q5jf90Jjje6sOgNNPjdfFpTwYTswZh0PRtNFFBVGgJejIpOhpF3kVwtIYQQPXbn3//H3moXf/j6ROaNyeu0xk/4F+W91S6u/f12bCYde++dnZC+9eVaS7HaVF5DnScUCD67aRblvk6vVTDrFRp9Kk53/whGhodoD7GZevQlpyvP+RMuL3uOh44rmZFCxFe4bqRkRvZfLq+fpWtLWbxyT+QxR6OPxSv3oAEWzhwZc5Zdm/qLqV1xLanC133Jqr2RxxyNPpas2oui0US97i6vn2fW7Y9s89K1E1i2oazNPh5p+lt25W+Xyhr8Po5uehBT9Yd4J/+UhuGXd2lodm/JNmZwtKGWzxzHOGfgkJiCiAFV5TNHJWX1J9FrdAy22NBqFOwGlSOuWvTKMc7KHoRe6do9V623EafXQ423gROeBtx+H3qtFqveSLYhgyyDiYHGDHRd3G9/I+9gQggheqzsZAPVLi8DLV0LGE0aYsfR6KP0RENk4o5466jW0qKZo1LyhqurdhytJcdiYN7oXJQ0qvlnNfWvupGHahs5oyCLc3oYUO7Kc/7Dww7OKMhi6jB7vwj4CtGbwjNqS2Zk/9VZ2Qx9nOvriZDuXPfm2+RYDMwZncOKjeVd2kdfpa0tRW2spkFnTen74gKzlarGesrrT3a6bjAYZK/zOPucJxhozCTPnIlWE/qbaTUKgzKsHKg/yeeOYwRUFbffx7HGOnbXHuPjk0dx+TxR91led5JNVQfYduIQB+prUINBrAYzeo2WE+5GPnUc44OqA3x04ghOrzvu1yCd9P1QvhBCiKRq8PqprAt9YI/o4tDSLJOO84qyWbf/BO/sPs6tPZxBOJpwrSU1GGTFxtAwmynD7Pzqq+MZm5uJw+1Dp1FSsgZQuMZUuE5R67pF4fYVZxTw7XOHUeFMr5seq1HHsToPte70LzTu8vq5/LQCJg8dQEGWEZfX3+3nY7T6YtGe825/gPNHDOStm6f0+JhCiLYymjKcXZIZ2W/1h1Ixqag71735NgVZRqrqvf3jb6f6UOoOhP7XNjLJnemYotGQbcygvL6GArMVu9Hc7rpldSfZXXucHJMFU5Th03pFS77Zyj7nCVx+H3U+Ny6fF41GgxoM4vA2crq9gIGm0HcTNaiy13mc3Y7jZOpN5JpaTUCl1UVqUPrVAEcbnNT63Iyx5jHYYkXRpE/wOl7kjlMIIUSPlJ9sBMBm0jGgG5lV88bkNgUjq7j1vKI49y6kqt7D2UPsHHpgDh6fitmg5Yk1e2OadCdZmteYal23qD/UMYLQcwrSPzMyWj2xnv4tm9cXq/P4yWj2nO8vzx8hki0cjJRh2v1XfygVk4q6c92bb1NZ5yEv09Av/nb6+kNogn6CugzUjEHJ7k6nMvVGHN5GyupOMN5QGDXId9jl4LPaSqx6Exm69r+bmLQ6ckwWTnoasOgM2C0ZKBoNwWCQysY6tlcf4rQBBeSbs9hTe5w9zuNkGzI6nfhGp2gZYrFzwuPiwxOHcXizGW3Lwyg1JVuQ8KwQQoge2X8yNPvviG7O/ntxUyHxtaXVeP2JGRqyfv9Jrnp5K199ZRtGvcITa/axeOXeyA1muAbQE2v24fImP/Dl8vp5fM0+Fq/cg6PRx+OXjQvVLWrqc+s2pN45xENkmLYnPc4nmtZ/a4jf39Ji0GHQKZj0Ck+s2Rt5zveX548QyZYhw7T7vY7KZiyYUYxPTd0hsX1Zd657822qXV5W7almfjs/kqfT307v3A9AwDoCYpzhPdlyTZkcbqilqrG+zbJjjXX8r6YSo6LHajB1uq8MnYF8cxaZeiNK0/lrNBoGZVjRaBQ+OnGE7dWH2eOsIs+Y2aUZuAcaLeQYLex1VlNefyL2E+wnJBgphBCiR8qagpHdnf13QqGNvEwDJp2WnUdr49m1iPBswecMtfeJ+k0d1S3qT3WMrJHMyPQdpt0bz8fQMcqB/vX8ESLZJDNSWAw6fnjBCO6fU4LdHPqBzW7W8+Dc0SyaNUpKYyRIuFzJg3NHx3zdW29z7793sWBGMQ/MTe+/nd5ZCkDANirJPYmdUatDq1HYV1eNTw29vwZUlVJnNR9WH0ENhia86alsYwY2g5ljjXUUmKzdmnnbpNMzwJDBwXoH9VHqUPZn6fEKEkIIkTT7m2YALs7uXr1HRdHw95uncHpBFjUNPrx+Ne71Gz84ECp0PaM4u0/Ub+qoblF/qmNkNYaeA7VpPEy7N56P/bYOlhBJJpmRfUdnNZq7el8S3t+JBi82k46bpwzjvjmjcbp92Jr2JyUxEqt5uZLaGK97622sJj13XjCSe2aO4ni9l0KrKe3+dvq60A+iAWtq14tsLcdk4UiDg8P1DvIzstjtqOKAqwab3hxTRmSsLDoDlg6GesfCajBx0FXDYZeDsfb8OPWs75NgpBBCiB4p72FmpNsX4F+7jnHJrzcnpHady+Pn44o6AM4syOoT9Zs6qlvUn+oYWc3pP5t2bzwf+2sdLCGSLaMpeCWZkamtoxrN3bkviVYH+PYZRdw7qyTyQ49BBij2inAAuSvXvfU2Gg0MfmQlBVlG3vvBdLItPQtMpZrIMO0Un7ymNa1GwaozU1p/gkMNDk54GigwZWFI0bqM2YYMDtTXMNhiI0sfv2BpXybvgkIIIXqkJzUjT9XLS1ztuq2HHATUIENsJgpt5j5Rv6mjukX9qY5RODMynWtG9sbzsb/WwRIi2WQ27dTXWY1m6Np9SXt1gBev3Cs1efsovVbB0ejj08q69MtyDgbR14WDkX1nmHaYzWCiweej3udlSIY9ZQOREJp4p8Hv42C9I9ldSRkSjBRCCNFtwWAwUjOyO8HI3qiXF64XOW34AKB7dYR6W7iP4RpTresW9Zc6RuGakXVpXDPSYtDx42Z/a4j/37K/1sESItlkmHbq66hGc2ux3Jf0hbrUouvS9bWsbaxE8TcQ1GhRM4cluztdptFoGGyxkW/Oikw+k8qyjRkccjmo9TYmuyspQe42hRBCdFu1y0u9J4BGA8MHmLu8fW/Uy/ugKRg5tWhA5LFwTaB7Z4+iwukhN9MQeTxV6BQNk4faOfTAHOo9AawmPXddOJL7Zo+O1DFq3k7HGlSRzMg0HqYN8GmFk7OHhP7WDd5AQv6W0epgpfvzR4hkC2dGNkpmZMqKd03dvlCXWnSdWa/F6fbTmGbBSL0zFDhXs4aDNr2Gn6eiTL2RGm8DB+trODO769+b0o38NCOEEKLbwlmRg60mjLquBzHCteyiLotD7bpgMNgsMzK7xTKLQYcGDVe9spXiR1dTXe/t0bHi7dPKOq54aStnPb2OXIsBg07BatJj0CnkZhqjttMto83W9NxI5wlsAN74tJKrXt7Kwn98ltC/pcWg61fPHyGSLV2zqdJJ8/uQ5jV1o64bw31Jou9rRHKEf1hIt/qvBmffHaLdV2UbLRx2OXF4JDtSgpFCCCG6bf+Jnk1ek+h6eWUnGyjIMlJoNTFxsLXNcoNOIRgMZXjurHD26FjxFg6ijsrJQFFSf+hJIpzKjEzfYdoA7+4+DsC0Ztm7Qoi+L10DGOnEp6rcPqMIiE9N3b5Ql1p0nVkfCps0+tLr7xepF9nHZtLuyyw6A+6Aj1qfBCPlJ3AhhBDd1pN6kXCqlh2Eaik1n3Wyq7Npu7x+9IqCw+3DbtLj9gcotJp46+Yp5Gca8atBog2MGj/Iys6jTnYccfKl0wu6dR6JEBle3iqjsz8J14xM5wlsjtV5+PBILQDzRucluTdCiHiyGMIT2KTve1hfZ9JpuX3GCIJBWLGxnHv/vYv1t05Ho4Hl3ZhN22LQcdeFI1CDQVZs7N5s3CL1RH5YSLMs5746k3Zfp+kD9S17gwQjhRBCdFt4Ju2ibmZGQstadtUNXmwmHVsPOrp0w+72BVi6tpTlG8ooyDKy/tbpLNtYxooYvkiMH2yF7fBxRW23zyERWk+80x9FgpFpPEx75Z5QVuTEwVbys6SOmBDpRIZpp761+6pZ8OanLP3iaVTOaVuT+Vi9h+wMPfuqG2K+L/n+6x/z1fGDOfLgXOo9fqnJmwbM4fqvafZalsxIkUwyTFsIIUS3lfcwMzIsXMsuoKoUP7qaeb/6IOahuS6vn8fX7GPxyj04Gn08ftk4lm0oY8nKvZEi8o5GH4+s3MMTa/a1yVAZP8gGwI6jqTNM+3i9h33VLgDOHWZPbmeSKFxbqzaNh2m/u7sKgHljJCtSiHSTrtlU6eR32w7xeVU9/9p1LGpN3Y+P1lL86Gq+/NIWVDXY6f72Hq/nzx8d5SuvbMXZNFmN1OTt+yI/LKRRyQXVXYPOfQKQzEiRHBKMFEII0W09rRnZ2lB7BnazHr8aZO2+EzFto1cUlm8IzQaYYzEwZ3QOKzaWR1132YYy9ErLj77xhaFakvtPNKRMbcLwEO1xeZkMyOi/sxuGMyMbfSq+QHrVaQJQ1SAHHY3kWAxcPDo32d0RQsRZhkFLjsXAEJsp2V0RUbg8ftbvPwnAtyYNjbrOzFE5ePwq5TWNfHDgZKf7fGf3cXIsBuaNziU/S/7u6SIdMyN9taXoB55BcMA40GcmuzuiH5KfaIQQQnSLP6By0BEqvjwi2xK3/c4bncu+ahdv767iijM6r+HocPsiGZAFWUaq6r2Rdpt1G33UNmUqhA1s+qJ4uNbNxxVOZhQPjM+J9EB4iPbUfj6hSZbx1G1KncdPdgoHZqPVLDXptB22jTqFl742kbxMAzEk3Agh+pgRAzMou282x+u9eP0qPlXtUoZcZ+8rflUlCC3W6eox+oLOrkN3r2ut28//7rmI98tOtjsKIcOgY8GMYiYNtTNxiJ2qek+H7/FfPC2fm6YMpdLpidPZi1SQblnOqs+FKfcs8r/0OtqMfLJ9bo54vLgD6VsWR6Se9PqkEkII0WsOOdwE1CBGnUJBHGvdXTwml5+/X867u48TDAY7LfJsN+mxm/U4Gn1U1nnIyzRE2m3WNesjQ3+bG19o5XCtm51HUyMY+YHUiwRAr1Uw6xUafSpOd+oGIzuqWdpZWyY3ECI9uX0BfvH+AZY3m5ytK6/zzmohTxlm551bpvLMuv3dPkZf0JOa0J3tr/mkeeePGNju9otmjeLJtfu46bUd8p7eT5nSKDNS9bup3fY0zh0voHocKEY7WRPmM2bS3eyud0pAUvQaGaYthBCiW/afDNU0LM7OQFHiNyvczFE56LUayk42ROomdsSnqiyYUQxAtcvLqj3VzD+vKOq6C2YU41PbDvcdX5g6dSP9AZUtBx0ATOvHM2mHpXrdyM5qlnbWho5rmgoh+p7W7wvQtdd5LLWQ751Vws/eK+32MfqCntaE7mx/4e0Xr9zb7vYur5+l75WyZJW8p/dn6TIZlepzUbv1SRybH0X1OEKPeRzUbl6Cc9vTDDam5o++Ij1JMFIIIUS3lJ2Mb73IsEyjjhlF2eRYDGw75Oh0fYtBxx0XjOD+OSXYzXru/fcuFswo5oG5oTaEMiIfnDuaRbNGRR3KFa4b+XEKBCN3VdUzYmAGI7IzGJcnNXxSfUbtjmqWdtZuLVpNUyFE39P8faG1WF7nndVC7i/vJT2tCd3R/mLdvivv8d3pk+gbzLrQ37HR17frV2sUPc4dL0RdVrdjBVajBZ1GnrOid8gwbSGEEN1yrM7DGQVZnFmQFfd9L/vymRRlmznh8nVaZ8sfUPnSi1u488KRHH1wLnUeP1aTnrsuHMl9s0dT6/Zha6op1d5wqQlNwchPKpz4Ayo6be/ciEWrg1WSY+Gtm6eQn2mk0R9Iu9pfXWU1pnYwsqOapZ212+wrSk1TIUTf0/x9oc2yGF7nndVC7i/vJT2tCd3R/mLdvivv8d3pk+gbwpmRfX2YtupxRDIioy0LeGrRKQr+NJw0UKSe/v0NRwghRLe4vH5+dMFIvn72EAqyjLi8/rgFzdy+AH/ZeYTlMdZeemf3cTaUnWR3VT2HH5wbuek3NP2KHWl3MBhg5EALFoMWlzfA3moX4/LjH2BtLd51sNKVtWmYttOTmsHIjmqWdtZus692apoKIfqW5u8LbZbF8DrvrBZyf3kviUdN6Pb2F+v2XXmP706fRN8QmU3b27eDkYrRjmK0Rw1IKkY7WqMNf+OJ3u+Y6JckB1cIIUSXhINoQxavZORjqxn8yEqeWluKOw6/Fp+q5xR77aW1+6rJsRi47uzB6LuZ0agoGs4aZCXHYqC8afh5IsW7DlY6szUN065tJ/Mk2TqqWdpZu7X2apoKIfqW5u8LrcXyOu+sFnJ/eS+JR03o9vYX6/ZdeY/vTp9E35CRJhPYBFUf1gnzoy7LmjAfp8eFPyjPWdE7JDNSCCFEzFxeP0vXhgrmh4WDZgALZ47sUYZkZ/WcfjK7pEVfdIrCbTOKefiSMdT1cBjvsivPYGx+JjUNnQ8N76loNahuem1H9H61Ou/+JlIzMkUzIy0GHXdeOAI1GGTFxnLu/fcu1t86HY0Glm/ovC1ZsEKkH4tBx6JZo4DQe3hXX+fh7YME233feHzNXt65ZSqKRtOtY/QF4evQ3vtr89mwu3NdY7lmrf+W8p7eP4UzI/v6BDaK3oJt8j0AOHesaDGbtnXSQnbX1ya5h6I/0QSDwWCyO9GRoqIiDhw40ObxW2+9lRdeeAG3281dd93Fq6++isfj4eKLL+bnP/85+fn5MR/D6XRis9mora3FarXGs/tCCJFWvH6VgoffbXc4UuVP50WGR3dHVb2HgofebXf5sYfmkZtpxO0L8PiafSyP0xew0P729toXiebneUZBFm/dPIWRj61ud/3wefdHC978lBVNAdkll45NdneiuuWvO7hsXAEXj8ml3uPH1lT/06TTRmqWdtZOZPBbCJEc4R/NKpxucjMNeP0qAzJin612Y9kJJgy2UdvoJ8diaPO+4VdVgoCi0XCszkNeppEgwbR6L6lwutl80MHc0Tm4vIFIfWWTTsuJBi9Wk471pSe4eEweiqKJaZ9bDtZwekEWjkYfuRZjTO+/4RrP8p7eP/35oyNc/8cPmTUqh1Xfn5bs7vSY6nOhUfT43A60Rht1HhdHvF7cgdT84TfdHHI5mDiwkOGZ2cnuSkLEGl/r8jfGb33rW6xfv75HneuKrVu3UlFREfm3cuVKAL761a8C8KMf/Yh//OMf/PWvf2XdunUcPXqUq666qtf6J4QQ/Uksxd97IlybKeqyptpLrYc4h4/d3SHN3Rka3lPNz7N5zamo6/bzmlORCWxSNDOy0RfgD9uPcNXLWyk/2UBuphGDTsFq0mPQKTG35UurEOnHYtBh1Cnc8eanFD+6mv+WnYx522AwyJUvbaX40dVUuzxR3zcyDDosBh07j9TypRe3cO6y9ZHhpOniv/tPctXLW7nixa3ktXr/zDbrmfCzdXzht1tYW1od8z5vfHUHxY+uprS6Ieb3X4tBJ+/p/ZhZHwqb9PXMyDBFb0HV6PjI1cim6iOUNjZIIFL0ui4HI2tra5kzZw4lJSU89thjHDlyJBH9isjNzaWgoCDy75///CcjR47kwgsvpLa2lt/+9rc888wzzJo1i3POOYeXXnqJ999/nw8++KDdfXo8HpxOZ4t/QgghOhdLsLAnYqnn1NlQbr3StY+2eO8vFvGug5XOwjUj63oY6E6U/+4/gduvMthmYmxeZrK7I4RIQQMzDVS7vGw6UBPzNnurXZxo8FHn8TM2r+NJ1cYPtvF5VT3/q6znYE1jT7ubUjYdCAVwo72/GvVaZpfkAvDGJ5Ux7e9kg5fPq+qpdnk5vSDxk9WJ9JAuNSNbc/m9/foeUyRXl79hvfnmmxw5coQf/OAHvPbaaxQVFXHppZfyf//3f/h8if2i4PV6+cMf/sDNN9+MRqNh+/bt+Hw+5syZE1ln7NixDBs2jE2bNrW7n8cffxybzRb5N3To0IT2Wwgh0kVPi/J3Jlyb6cG5oyNBT7tZz/1zSlg0axQWgy7u2ZmJzvaMxmLQcfdFI7l/Tgl2s557/72LBTOKeWBuSYvzfnDu6Mh591fhmpG1PawJmijv7D4OwNzRuWg0sQ0RFEL0L9OGDwDgg/LYg5GbmtY9Z4it0/InZr2WCYWhoXBdCXj2BR80nc+0ogFRl39/2jDeuHEyT35xHFV1Hrx+tcMRDZub9leSY2GgJfYh86J/i9SM7OOzaQuRSrr17SY3N5c777yTO++8kw8//JCXXnqJG264gczMTL7xjW9w6623UlIS/2L7b775Jg6HgxtvvBGAyspKDAYDdru9xXr5+flUVrb/69i9997LnXfeGWk7nU4JSAohRAy6U/y9q0x6LQtnjuQns0s42egly6hj7b7qyEzZ4ezM9upWdjU7M977i9Uz6/dz9hA7Rx6cS73Hj9Wk564LR3Lf7NEtak719+L31qbr70zRYOS7TcHIS8bkJbknQohUNW14qC7Y1kMO/AEVnbbzfJBwUHHq8OhBuNamFmWz7XAtmw7U8LWJg7vf2RTi9gX48EhoQo1p7VyHsXlZ/O2TSm56bUdM9yTh69re/oSIJsOQnpmRQiRTj8aehWs4rly5Eq1Wy2WXXcYnn3zCaaedxrPPPhuvPkb89re/5dJLL6WwsLBH+zEajVit1hb/hBBCxMak13LZ2HwOPTCHww/MpfKn81g4c2Rcg2bh2kwDMwyc+dQ6vvTiVj48HPpC4lNVbo9jdmaisz3b8/tth7jq5a28t69aak51IFIzMgWHaR9yNPK/Y3UoGpgzOifZ3RFCpKhxeZnYTDoafAE+roitPNQHXQyaRbIv0ygz8sMjtfgCQfIyDRRnZ7RZHq75vGRV7DWfP+hikFcIALMuPWbTFiKVdDkY6fP5eP311/niF7/I8OHD+etf/8odd9zB0aNHeeWVV1i1ahV/+ctfeOSRR+La0QMHDrBq1Sq+853vRB4rKCjA6/XicDharHvs2DEKCgrienwhhBCn3PPPzyh+dDUfV9QmNGim1ypMGBz6weidPVVAKFD5owtGRIY4Q8+GNLc3NDyRQ6T3VbsoPdGATtEwo3hg3PefTmzm1J3AZn3pCc4oyGLu6FyyuzBDrhCif1EUDecOCwW/YhlGXef282llKGgZzqrsTDgY+dGR2rTJ3goPVZ82fEDUMhhdrfkcUINsPugI7bOdYd9CRCOZkULEX5e/YQ0aNAhVVbnuuuvYsmULEyZMaLPOzJkz2wyd7qmXXnqJvLw8vvCFL0QeO+ecc9Dr9axevZqrr74agN27d3Pw4EGmTZsW1+MLIYQ45aCjkWqXt1dmeZ43Opc3P63k3d3HuX/OaOo9fub88n3unzuGip/Oxen293hIc3ho+L2zS6hwusnNNKCqwYQNkX5ndyiwel5RNlkmyX7siNUYeo71Zs1Il9ePXlFwuH3YTXrc/gAmnTbS9qsqQeDLZw5ienE2BVlGXF6/ZLIKIdo1dfgA3t1znM0HarjtvOjZ+GFbDtWgBmGY3UyhzRTT/ocPMFOQZaSyzsP2w460+KHrVBZj9IBsLDWfczONkcc+O1ZHncdPplHLGQUyMk7EzhyZwEYlGAxKjWgh4qDLd83PPvssX/3qVzGZ2v9gtNvtlJVF/5WqO1RV5aWXXuJb3/oWOt2pLttsNr797W9z5513kp2djdVq5fbbb2fatGlMnTo1bscXQghxSkANcrjWDcCwAeaEH+/iplp8mw7UUNvo481PK/nwiJMf//Mzrjh9ZuSLhqFnlUewGHQEg0G+9eeP2FVVz3++ey7nDLH3tPtRhesMzhuTm5D9p5PwBDa9NUzb7QuwdG0pyzeUUZBlZP2t01m2sYwVTTVSpwyz884tU3lm3X6WbyhLSN1UIUT6CWfixZIZuamTSVui0Wg0TBs+gDc+rWRTeU2fD0YGg8FO6zt2teZzeH9Thg5Aq0gwScQuo9lnu9uvRoKTQoju6/I3txtuuKHDQGQirFq1ioMHD3LzzTe3Wfbss8/yxS9+kauvvpoLLriAgoIC/va3v/Vq/4QQoj+pcLoJqEF0ioaCrMR/HhQPzKAkx0JADbKh7CT/3X+CHIuBb04aEvdfpjUaDQadQrXLy44jsdX16iqvX+VYvYcci4GLJRjZqXAwstGn4gskpn5nWLj+2OKVe3A0+nj8snEs21DGkpWn6pHdO6uEn71XGlkHOq9RJoQQ4WHatW4/J1zeDtetqHWTYzF0ua5heP3PKuu618kUcqS2kewMPQVZRiYNtUVdp6Oaz4tmjsIfbPmZcaimsVvXVQiz/lTYRGbUFiI++sR4onnz5hEMBqMuM5lMvPDCC7zwwgu93CshhOifDjoaARhiM/VaZsE3Jw3ljIIsZo7K4bSCLJ7/8hm4fYkJTI0vtLJ6bzU7Y5xkoCPRhvsadQp//sY55GUaIPpHm2gmPIENQJ3Hn9DajM3rj+VYDMwZncNNr+2ILI/2WHPLNpTxk9klCeufEKLvspv1vPu9qUwbPgCn24/Xr7YpARFuL5w5iqWXn4azsWs/bswqyeGNGyczZ3QOVfUe7E0lTHqzhETrz71wWYuOSl9Ea+dkGnnr5inkZxoJtvNhGa75DKH333D2+q++Op6xuZk43D50GiWy/++cO4xFs0dRXd9xMFiI1nRaBb1Wgy8Q7JN1I1u/Ln2qiknXsxFFQvRUnwhGCiGESB0Ha0LByN4Yoh32w/OLWbp2Hze9tiPhw2LHF4bqSO08Utuj/XQ23FeG9sZGp1XI0Gtp8AWobUxsMLJ5/bGCLCNV9d4Ww/+iPdZi+yg1yoQQAkKfCetLT3DN77a3+UyI12fEaflZvPVpZa98VkbT/HMvWlmLzs67O9chXPP5J7NLqPf4MRu0PLFmL8vjeF2FgFDdSF/A3+dm1G79umz+GsjQ6Wn0y4gOkRwSjBRCCNEl4czIYfbeCUa6vH6eeq+UJav2Rh4LD4sFWDhzZFyzPiYUhoaD7axwdrtIucvrZ+na0FBegJeunRAa7ttL55BurCYdDb4ATk9i60Y2rz9WWechL9PQoh5ZtMdabB+lRpkQQoQ/E8KfAa0/E+LxGdH6GN3ZR0+0/tyDU2UtYj3v7l6H8GNGVeGJNftYvDJ+11WIsAy9Fqfb36cyI6O9Lpu/Br49fRD76qqS1T3Rz0lurhBCiC4JZ0YO7aXMyOZDZ1tbtqEMvRLfj7KxeZkYtApOt5/yk43d2ke04b4rNpZHXTcR55BuTk1ik9hf75vXH6t2eVm1p5r55xVFlkd7rLkFM4rxqYmtaymE6Hs6+kyI12dEb39Wdnb8zs4zEddBPntFIoUnrelLNSM7e1/INVvkdSCSRp55QgghuuRQL2dGNh8622ZZ07DYeNJrFU7LzwRgZ0X3hmp3Nty3xboJOId0E842THQw0mLQsXDmSO6fU4LdrOfef+9iwYxiHpgbagM8vmYvd100kgfnjo48ZjfreXDuaBbNGiVZNkKINjr6TIjXZ0Rvf1Z2dvzOzjMR10E+e0UihWfUbkxQzfJE6Ox9wdHow6DIfYtIDnnmCSGE6JLeHqbdfOhsm2UJGhY7odDGjqNOdhxxcuUZg7q8fWfDfVusK0N7OxXOjOyNL47Pry/j7CF2Dj8wF5fXj9Wk564LR3Lf7NHUun3YmiZkCNcoCz/mU1WpPyaEiKqjz4R4fUYk47Oyo+N3dp6JuA7y2SsSKTyjdl+qGdnZ+4LdrGefy49ZSVw9biHaI5mRQgghuuTUBDYZvXK85kNnW0vUsNizmiax+bibM2r7VJXbOxju25wM7e1ceEbtRGdGev0qz/13P1e9vJX3y0+Qm2nEoFOwmvQYdEqknWHQYTHoWjwmGZFCiPZ0VAIiXp8Ryfis7Oj4nZ1nIq5DZ6U2uro/IZrLMIQzI/tOMLKz94XjjS55HYikkTtnIYQQMatz+6lp+nV1qN3UK8e0GHQsmjUKCNW36Y3ZMCc0BSN3dHNGbYtBx48uGEEwGGTFxnLu/fcu1t86HY0GlsuMnl1mNenIsRgw6BL7G+qGspNAaHjfRSNzEnosIUT/0fpzrPVnQjw+I5LxWRnt+EGCkXN4fM1e3rllKopGE9N59/Q6dHad5bNX9ERfrBkZfk2oTfejrV8DO2oOJbuLoh/TBIPBYLI7kWxOpxObzUZtbS1WqzXZ3RFC9HMurx+9ouBw+7Cb9Lj9AUw6bbfbPlWNW9bWZ5V1nPH0e9jNek4uviQu+4xV+Lo0HxabqGy0mgYvAx98B4CTiy+J1AaMlcvj58JfbOT+OWO4dGwuTrcfW7O/TW+cQzr58LCDMXmZ1DT4yMs0xv26hZ9blXUeBlr07DnuYuJgW9z2L4QQ0PZzrPVnQjw+I1xePzpFQ4XTQ26mgWAQMo299znz3r5qJg+zU+v2k5NhwK+qBKFL593T69DZdZbPXtEdV7+8lTc+reTnV53J96cXJbs7MfMHVP7zeRWzSnKo9wQYYG4qLaNTWFdZigYNVkPvJBiIkEMuBxMHFjI8MzvZXUmIWONr8i4shBApxO0LsHRtKcs3lFGQZWT9rdNZtrGMFRvKu9xORAZAb9eLbC78xSE30wiAIYGVRgZkGBhmN3PQ0cjHR51cMHJgl7Z/49NKPjzsZOE//scVp8861eemzL7eOId04fYFePN/laz4f4l5Tjd/zTXf/7i8TMmaEULEVZvPsdafCXH4jLAYdPgCKtf9YTulJxr417fPZfIwe0+7HpPaRh9zf/UBA8x6PrrzAgw6pcU5xHzePbwOnV5n+ewV3RDJjOxDw7QBPq2s44qXtlKcncHeRbNQFA0GFAKdDM/WaRR0ioJfVfEH1TbteEjEPkXfIcFIIYRIES6vn6VrS1m8cg8AL107gWUbyliyam+32hCaKe+Rpv0tnDmyx5kAyQxG9rbxhVYafAEO1zZ2edv1+0+QYzFwwzlD0Wg0Cehd/xB+TSxZmZjndOvXXLz3L4QQyaDXKgyymth80ME7e6p6LRi5el81ATXIwAw9g23pf58g+hdzH6wZCbDpQA0AIwdmoCid35OatDqyjRlkGzOo8TSQbczA5feSoTNQ42lggDGDk54GTnoacAe6V8u79THisU/R98jPQkIIkSL0isLyDWUA5FgMzBmdw4qN5d1qt7ZsQxl6pedv+eHJa4YOSP8vGYsvHUvZfbM5f8RAvH4Vl7fzmyOX14/Hr3Lv7BLK7pvNre0Uzhexaf6aaC0ez+lE718IIZLl4jG5ALy7+3ivHfOd3VUAzBuT12vHFKK39NXMyA+agpFThw/odF2TVkdRZjb/7/NNFL76MLPf/iVOn5vn/vdfCl99mMGvPULhqw/z/z7fRFFmNiZt13+wbX2M1vu06U3oNHL/1R/Iz/3i/7d35/FRVXf/wD+zL5nMDNkDCRACIVE2QcGwiIEASp9qXdo+Vlvr01YtClUUFVERUaHaqiVon25CbbVYf4/WtlKVJYpBUEAQkD0EAUMSIEyWSWY/vz+SO8xMJskkmS3J5/168Xp5Z+6ce2bu8Wbud873e4goTlhsTlhaF4fJSNSgptHR7e02bTc7UWdzelOUuutUP5kZaXO68X97K7tU8L69dF8Wye8+3/8n2jwXhjEd6faJiGJlTmtAcNvXF1DX7ISpi7WPu0oI4Q18SoFQor5Er5JmRvaudGJpZmRhCMHIJI0ez+8rxfIvNwAA1kz7PlYdKMMzX2707mNxNHuf/3n+ZJyzW7uUZh14DADI0CVifMogyGUyJKo1yDaYOVOyH2DImYgoTpi1Ku9CKVUNdqQZ1N3ebtO2TgWTtuc3ItLMyMF9eGak1eHCis3HsHzDUW+gSkrdXbn5WNAZkhdfcyTk11DnfP+faPNcGMZ0pNsnIoqVoUl65KUmwO0R2HTsXMSPd/hsI76+0Ay1Qo7pw7pWZ5moN9CpWkInvWk17bONdhw7ZwXQ+cxIpUyOJI0eJQfLAAApmgTMzMzDywe3ttk335SGiamDMUCjQ7I2AfnmNAzUGzudKamRK/2OIbX10dx52HnuNLJaZ0n2dPYl9Q4MRhIRxQmnx4MFU3MAAOesDmw8cg73tqb5dnU70CNFw8NSGLo/1IzsTuou030jw/f/iUALpubA2Unx9Vi3T0QUS1K69NaK8xE/1s5TFqQkqHHVsCQkRHH1bqJokWZG2npRmraUop2fZsAAvbrDfbUKJS44mmFxtHzXz9AnosbW6N2WSMHD7We/Rua6ZRgUQvBQq1BioN6IPFMKLD7HAIAVl89FSevsS+lxafbl8/tKkaTR9+gzoPjFvxRERHEiQa3EIzOGwyMEVm89gcXrD2LLvMmQyYCSsq5vW5qdmDjYjN9/dyzyUw2w2JxQyuRwejzdWpTD7RHexVz68szI7qTuMt03MqT/J4CWoG64098T1Eo8eHWu9/85ptcTUV9y06gMzByeguK8FNQ02mHWqmBzuaFVKmCxOUPa7uw7g9Xhgkoux1XDUlCxZCa+ru36om9EvUFvrBm5rZN6kQlKNZQyOQbqjd6gn1mtg8XRjKqmBqRpDd5tiW/wUCIFD/VKFe4YMRGVTfXeFbj1ShUG6k14fl8p3jj+BXZf/4C3TWn25R2fvBm0fyUHy7B47EzUNDdyte0+iMFIIqI44nB7MD7LjFOPF8PqcMOoVeGB6blYMjMPdTZnl7Yb7S7o1Aqs3Hy0S7UP21PdYIfTLaCQy5CZ2HcDa1LqbrDgYnupu915DYVGq1JgUVEuFhXl4myjA5lGDVweEbZA4VMfHsHknCR888QsNNpdMLXefDMQSUS93cQhA7Bi01Hc8eYeZCRqsGXeZKzaWoHVZSc63Q7lO0O7tZKT+WMO9T36Xria9vZ26kVanQ6o5HIMS0yGQaXBL/duRsnBMqyZ9n3cUzAFz3y5EefsVmw6c8S7DaDd4GG+KQ0rLp+LmZl5sLocKDCneVfgbnI5/GpE+rbZ3uxLiVImR6PTDo1CAZeLwci+hnljRERxZM839bhx7Q5c9fJWpBk0UCvlMGpVUCvlSO3itkYlx8ou1j7siJSiPciohVLRd/98dCd11+nxYP7UoV16DYUuQa3ErX/9Ate9+jnWH6zp1szeYOptTrz8aQVuXLsDh6obvf8Phat9IqJYsTpcWLn5GJ7e2PIdYMXcAqwqq8DTG0LbBjr+zsBaydTfeGdG9pKakS63B5+ftADwD0baXE48v68UmeuWYdvZE1ixdxOWf7kBFkczFu9cj/mXTMWSscUwq3VYvHM9FlwyFY+NnQWzWocMfSLOBgQPfWs+Dv77chT95xXvCtyj33kearnSr0ak7zGaXU7v7Etf+aY0vDPzxzj+3SVwC4GcxOSQalJS79J37yaJiHqhPZV1AIDsMNRkDHcdw/6weA1wMTX4iVl53sVNzDoVHp81Ao/MGB40UJWgVuK+acPwWPEIv9c8MSuv3ddQ1yRqldhf1eAtxB4OG4+cQ4JaiYI0A8YNMoatXSKiWPP9DpCSoEZxXgpWbz0R0nagYN8ZWCuZ+hvvatq9ZIbewZpGDEvWIydJj0vSEwG0zIhcuXczln+5AUqZvM0CNYfqanD1+lcwITkLJ7/3OD66dh6MKi1+cek0VP73UmyYczcG6o1+wcPAmo8rLp+LVQfK8PSXG6BTqtrMfPQ9xu7rH4DD48b8gqne5wODm5nrnuSCNn0UzyQRURz58kw9AGDsQFOP2wp3HcP+sHiNREoNfnTmCJxvcsCoVeLj8vNQymVB969usKP4d9uw/Jp8nFk6C/U2pvuGW1bruDtdZ+t0X6mGWWc10S7PNqFiyUycqG2CTBb83BIR9Ua+3wEyEjWoaXSEvN2mrSDfGVgrmfqbeFpNO5TvOSNSEvDu/0xEukGDZpcbCWply48IrbMU20uRPlRXgxs3r0WKJgEHbnwIxxvOw+pqqTuvlMshhMD8gqlY/uWGNmnbgdvt1Z2UjpGbmIz9NyzCQ2OKALTUiOyoJiUA3JVfiMqm+sh9uBQ1DEYSEcWRL7+RgpE9n6UV7jqGUjAyu4/PjJRIsxlT9GqM/lUpjpxrwvqfTsI1+Wlt9n1j92l8VdWAlZuO4jujMpBqaAlAqpmAEDZZJi0A4LSl48URfGuYdaUmWm5yAgPHRNRn+H4HqGqwI82gDnm7TVtBvjOwVjL1N/FSM7K733MWzxiOOpfNGxRsL1AocQkPDCoNTlvrvNsutwfn7FYsGt0SPNx45qhfQDMwwBms7qSvHwwbj/P2JtTam3BXfiEWj50JAFzQpp/gXRIRUZxwuj34qroBADAuDMHI7tQ+7EhdkwOjMhKRl5LQ4771JiqlHLNGtgQg39l3Jug+//qqGgDwo8uzo9av/iY7hJmRgTXMeloTjYiot/L9DnDO6sDGI+dw75ShIW0HCvadIdzfMYjiXTyspt2T7zm/+aQCZrXWm2LtGygMZn7BVNTam9oE/WxuF0401uKu/EJsusY/bds3wCkJrEMJtKzY/fjYWVg0ugi19ibY3C5UNtXjREMtLjiaQ1rQpruUMjm0CiWUsvCEwsLdXn/CmZFERHHicE0j7C4PEjVKDB2g73F7Uu1DoKV+k/Tr6PypQ7u8mrbV4cJvbx6D6kYHMhM1sDpc/aoO4l1XDkHxiFQU56WgusGOAbqLKTG1zQ786ycTsenIOVyVmxTrrvZZ0szIUx3MjAxWI+2ON/cE3Q60qqwCj84cEdY+ExHFSuB3gMXrD2LLvMmQyYCSshOdbnf2nUFqX0D47d/R6ttEvZm3ZmQMg5E9+Z6zsvQY5k3N9qZYAy2Bwo/mzgMAvHxwKyyOZpjVOswvmIpFo4tworE2aFtS8LCmuRGZ+kRvm8FmQko1Ip+dMBenv/8EGpx2mNRa1NqbcKKxFja3y6/doWpdm9magat15yQmo7Z1RqXv64OR0ssVMjlMai2SNHpcsDdhgEYfchvBaBVKJGn0YWuvP+o/d5JERHHuYr1II+Tt1CbsKt/ah+esDph0Suw+XdelmwTfdJD+erMxPCUBf/+yEne8uafdFJh7pwzF7JGpse5qnyXNjKxutMPh8kCtbPsLdFdqpLV5LWucEVEf4/sdoM7mhFGrwgPTc7FkZl6n21K95K0VtdAEud5K7c8ZmYaHioajrtmFlAQ1ayVTn6WLg2BkT7/nOJwyPDJmBoCWlOdDdTW4bsOr+N2U7+KxscW40BqMDBYoDMYlPDhru5i2XXKwDIt3rsfHc+dBBhlWHyyDxdGMquYG7D7/DYoH5qHeYcOZpvqgadYu4UGtvckvYCotaFNyoAx3fPJm0IBpsH76BgvrHTYYVBr8cu9mlLT2ybeNM031sLocIad+axVKDDUk4fl9pWFpr79iMJKIKE7saa0XOSYzvKv6SjMYG+xOjHvhYzQ53Di/fA40ys5vFqwOF54rLcfyDUe8j0npHgCwqCi3z8+QlD6DpzceBQCs+f64lhSY1m2g5TN5euNRyGWyfvGZxEJKghoapRx2lweV9TYMTWo7e7grNdLavJY1zoioD5L+Hkk/tEg/5HS2nahR4JLnSnHKYsP2BVMxcfCANm0LIfDd13bC6Rb4z08nYaBJy1rJ1GddnBnpgRAiJgvf9fR7jkGjhFopx6LRRXh07EzU2psxQNMSfDzecB5uIVDV1NClIJpv2vbisTNhcTR7V+B+tHW7KwHOWnuTX3CzOwvaBAYL10z7PnaeO+3XRoYuEeNTBkEukyFRrUG2wRzyzMYkjR7P7yv19qGn7fVX/GtBRBQn9p5pKRAdjsVrgslLNUApl6HJ6UZZRfC0i0C+6SCBVpVVQCXv+39GgqXErN56Iui+/eUziQWZTHZxEZu64KnaXamRFog1zoiILjJoVJiWkwwA+L+9wesln7zQjDP1dlianbgkIzGa3SOKOp3PjF+bKzbfF8L1PSdBpYZCJsfXjbXYcfYkKpvqYXU5YXO7ujWbT0rbPmSpwTmbFQctNahoqPVuH7LUoLKpPqSgnG9ws/K/l2LOoHy8fHBr0H1LDpYhSaNvU6/RN1iolMkxMzPPrw1ptuXOc6eR9eZTGLhuGQauW4bfHdqGoYYkaBXtTypQyuRI0ui9q5L3tL3+LO7vmL755hvcdtttSE5Ohk6nw+jRo7Fz507v80IIPPHEE8jMzIROp0NxcTGOHj3aQYtERPFHCOGdGTluoCkix5DJZJid15JG/MHhsyG9xjcdpM1zrWmtfV1HKTFt9u0nn0msZJlaUrVPWYIvYiPVMHuseATMOhUWrz+IBVNz8Pis4NtAy0yBJ2bl4ZEZwzmjlYjIx88nD8E7P74CT8zOQ01riQzfhb62fX0BQMuiezqmZlMfp1NdDJ00OWKTqp2gVuKhotywfc+xuhxh/SHWJTx+Ac3A7VCFuqCNpfU5ZetEAKVMjgSlyi9YGLjCNwC/2ZbS49Jsy5cPliFNa2h3QRqtQtmmTx219/y+UiRper4WQF8U19+6L1y4gClTpqCoqAj/+c9/kJqaiqNHj2LAgItpAs899xxWrVqFP//5z8jJycHjjz+OOXPm4MCBA9BqtTHsPRFR6Koa7DhrdUAuA0ZlRm52weyRqXht12l8ePgsnvuvzvf3TQdp81w/SWvtKCWmzb795DOJlWxz68zIDhax0aoUmJKThIdnDEeD3dVpjTSTVsUaZ0REQUzIMuPZTUdxx5t7gtaMloKRVw7l4m3U9ykVcqgUMjjdIqZ1I9cfrMb4LDNOPz4LVkff/p7T3oI2EnPrcxfszRioNyJJo0eDw4Y6h827v+8K3xZHM1I0CZiZmYc7PnnTr63ARXLyzWmotTehztEMtxB+C+BIx+6oPckbx7/Ao2Nn4rytCXYP07V9xfXMyF/+8pfIzs7GmjVrMHHiROTk5GD27NnIzc0F0DKT6KWXXsJjjz2G66+/HmPGjMFrr72GyspK/OMf/4ht54mIumDPNy0p2iNTDRGdXTArLxUyGbD3TD3O1AefXebLNx0kUH9Ja+0oJSZQf/lMYmVQ6yI2p+raH7s2pxtz//gZcp7ZBJVcDrVSDqNWBbVSjlSDJug2Z0QSEfmzOlxYsfkYnt541Pvjm1QzeuXmY7A6XNjeGowsHNK2niRRXyTVjWyKYTDyP4fP4sa1O/DilvJ2v9f0le85vgvaBDO/YCrqHTZkJ5jxu0PbMHDdMlz6zvNIUKphVrd8Z/Rd4RsIPlPSN8168N+XI3Pdk7h6/Ss4Z7NiWGIy0nSJGGIY4D3GB98c6rA9qc13Zv4Yu69/ABcczRhhSsFAvZEp2z7iOhj5z3/+E5dffjm++93vIi0tDZdddhn+8Ic/eJ+vqKhAVVUViouLvY+ZTCZMmjQJ27Zta7ddu92O+vp6v39ERLF05JwVozISMTUnsrMLUg0aTBhkQkqCGp+ftHS6f2DaK9D/0lqlz+CJWXlM9Y2x7NY07W86mBl55KwVQgAuj0CSnrNUiYi6I5Sa0adar8UMRlJ/EQ8ram8/0fIjQLgXvIxX0oI2j4+d5Q0wmtU6LBlbjEWjr4aA8NaHtDia2wQfAWDxzvWYf8lULBlbjGaX0ztTUhKYZp1vSsM/Z/0P3jrxJTLXLcO2mgqs2LvJe4zO2gsMbgbWkDQoNdH7AONYXN8xHT9+HL/97W+xcOFCPProo9ixYwcWLFgAtVqN22+/HVVVVQCA9PR0v9elp6d7nwtmxYoVWLZsWUT7TkQUKqvDhZ9NGoLrLs1ARqIGVocrogGtP35vHHJT9KhtcsLh8sDp8XR4PI8QGJ9lxqnHi2F1uGHuxeke3aVVKbCoKBePzhzR51JgepOs1jTtUx0EIw/WNAAACtIMMVnpkoioL+isZnRtswMpCWoAwJABuqD7EfU1enXrzMgY1Yy80OTAwZpGAMCV/eRHgGCrdRtUGmz45jBeP7Ybt+dd7reYDNASfPxo7jwAwMsHt+JQXQ2u2/Aqfjflu3hsbDGsLgfmF0zF8i83BE2z9g1OBnv+UF0Nrl7/Cp6dMBcPj54Bh8ftbS/w9RLfFcBvH3FFxD6v3iSug5EejweXX345nn32WQDAZZddhv379+N///d/cfvtt3e73cWLF2PhwoXe7fr6emRnZ/e4v0REXWVzuvFcaTlKyiqC1mOKxPH+b18lSspOhHy8fWcacOPaHbgk3YD9i4oAAOr4nlgfEVLANtXQ8mumWin33+6Hn0m0ZbemaZ/uIE37UOuX9Px0Q1T6RETUF4VSM7qqwY5pOUn84Yf6DZ1SmhkZm5I8n7VmNQ1PSfB+/+wPpAVtapoboZTL8e7X+5GhT8Rtwyd4F7Hx5RssrPzvpbA4mmFW61Brb8LxhvNQyORYNLrlnmbjmaN+adaBwcf20rAP1dXgxs1rkaJJwOGbHsZDY1rae+P4F53WkFw8dgbONVvD+hn1RnF955SZmYlLLrnE77GCggKcPHkSAJCRkQEAqK6u9tunurra+1wwGo0GRqPR7x8RUbRJ9ZiWbzjSbj2myByv/fpPweypbKlnKQWCiGIly9QyM7K6dVXXYLzByFQGI4mIuqujmtGPFA3H4X42O4sI8JkZGaM07W39vE6rtCr3rbkTsPPcaYx791cwKDV+KdKSQ3U1+J+yloCgxd6MQ5YaVDbVw+pyot5p98623HTN3RioN3rbCAw++i6A016fdEo1TjZacFd+IfbfsAiNLnuHNSQtDhtSdAZYnY6wfTa9UVwHI6dMmYLDhw/7PXbkyBEMGTIEAJCTk4OMjAxs2rTJ+3x9fT0+++wzFBYWRrWvRERdFUo9png43peVLXV1+0ttGopfKQlqaJRyCAFUtrMA08HqlhvkgvTIrUpPRNTXBdZLBoCJg83Y88B03HfVMAzQq1CxZCZ+MH5QjHtKFD06Vct35VjVjNz+dS2A/v0jQJJGj+f3leKZLzeivOF8m/qQvuYXTEWtvQmNLoc3kCmRZlsestSgztHsXSQnMPgYrAZlsGNYXQ5UNtXjSN057yrfkvZqSD6/rxQ2V/ByGP1BXAcj77//fmzfvh3PPvssjh07hjfeeAO///3vcc899wAAZDIZ7rvvPjz99NP45z//iX379uFHP/oRBg4ciO985zux7TwRUSc6q8dUZwvvH6fuHk8KRo4bZAprf4i6SiaTeWdHBqsb6fYIHDnbGoxM48xIIqKekOolVy2djXPL5qD055Pxf3srkbHsQ+Q8swnZyzfiD9tPwhbDxTyIosm7mnYMakZ6PMKbpt1fZ0YqZXIkafR+NSJ9F5PxXeDm8bGzsGh0EWrtTR226RIenLVZvYvkuISnwwVwOjuG3eNqswJ44AI5wMUakiv3bu63MyTjumbkFVdcgXfeeQeLFy/GU089hZycHLz00ku49dZbvfs89NBDsFqtuPPOO2GxWDB16lS8//770Gq1Mew5EVHnQqnHFOvjeTwCe8+0BCPHcmYkxYFssw7l55uC1o38+kITbC4PNEo5hibpY9A7IqK+RaqXrPHIsbK11ItEKvUCAIuKciO6+B5RPIjlatoHqhtQb3MhQa3AqIz+mf2hlMtxwd7klwLtWx/y5Pceh9XlgEmtRa29CScaa2Fzd172KnCRnAanHbMGjoQcMpQcLGuzAM4FnxqUwY4hrQAOdF5DsuRgGR4dO7MHn0rvFfd/Mf7rv/4L//Vf/9Xu8zKZDE899RSeeuqpKPaKiKjnpHpM0hd5Xwum5sDp8YR1UZTuHK/8vBVWhxtapRx5qQlh6wtRd0kzI08HmRkppWjnpSZAIeeCCkRE4dJZqZdHZ46Ico+Ioi+WNSN3f1OHURmJGJ6sh1IR1wmuEePyeDBAo4dZrWsTkLxx81rkJiZj/w2LcKTuHOyertXeD1wkRyGT+63g7bsAjlsIVDU1tEn99m1LCm4+OnYmLgRZZEdicTSjzmlDqqL/ZfTEfTCSiKivSlAr8dCM4fAIgdVbQ1/duifHe2TGcAAtNw7S8e6dOrTd40kp2qMyEvvtFx+KL1mtCymdCjIzUlq8piCtf84YICKKlFBKvfSn1X2pf9LGaGak1eHCzWMHYuqwZGQkamB1uPrlTGSX8HhToJd/uaHN8z8YNh7n7U1dDkQGHsPlbgkyWl0Ob3Cyo+BjMFJw87ytCSNMKW0CqBKzWgeTqn9m9fa/EUxEFEe2VtRifJYZpx8vhtXhhkmrgtPjCXsgUiLVf3p05gjUNjmQqFXik+PnoVEGDzTuaQ1GjmW9SIoTWaaWYOQ3wWZGtgYjR7JeJBFRWEW7tAxRPPLWjIxiMNLmdOO50nKU+EwkiNTEhd7ANwW65GCZd9bi/IKpWDS6CCcaa8N6PN/gZHf41pAMFkCdXzC1JTut/51KBiOJiGLpw8Nn8euPy7HwqmH41XWXAkBYU7ODkX5JNWqVyFtZisp6Gw4+VBQ0gLO3kvUiKb5km9tfwOZQTQMALl5DRBRu0S4tQxSPLtaM7H5wqiusDheeKy3Hcp//7/p7rdbA+o6WTuo3xoOOAqiPjJ0BraJ//pjTv0YuEVGc2f51y693o2MQ7NOrlShIN6Cy3ob3D9cEDUbuqawDAIwbxGAkxQcpTTtwARshhLdmZEE6g5FEROHUXqmX/jxDi/qfaK+mzVqtwQXWd+xqCnW0BQZQa+1NSNLo4fJ4+m0gEmAwkogoZhwuD3aebgn2FQ4dEJM+zBmZhk1Hz+HDw2fxi2nD/J6rbXJ4Az5jODOS4oS0gE11ox0Olwfq1hIDZxsduNDshEwG5KUyGElEFG6+pV7qbM6Il5Yhijc6Vct3DluU0rRZq7VjPU2hjibfAOp5uxUjjCnINsTm/i9ecC49EVGM7Kmsg93lQbJehREpsVmpes7IVADAR+Xn2nyxkhavyUnSw8haUBQnUhLU0CjlEAKorL84O/Jga4r20AF6bxoVERGFV4JaCbVSjlSDBmqlvN+liFL/Fu3VtKVarUGfY63WXsklPKh32uGBiHVXYo7BSCKiGNn29QUAwJVDBkAmk8WkD6MyEjHQqEWz04OyCv+Cz94U7YGcFUnxQyaTeWdH+taNvLiSNmdFEhERUfjporyatlSrNRipVitRb8VgJBFRjGz3CUbGikwmw+y8ltmRgcHIivNNGJWRGNP+EQWTbdYhJUGNBvvFIuUnLc0YlZGI8Vlc+Z2IiIjCL9o1IxPUSiwqysVjxSO8MyTNOhWemJWHR2YM58xk6tU4eomIYmTbiZZgZOGQpJj24+axmbh+VAZm5aWgptEOs1YFm8uNld+6BNWNdmQmamB1uPiFh+LGym8V4NKMRFianXC4PLC53HisOA8/nTSE45WIiIgiwjsz0hW9GYnvHajG+CwzTj8+C1aHi7Vaqc/gN3UiohiorLPhpKUZchkwcbA5pn0pGp6CFZuO4o439yAjUYMt8yZj1dYKrC47wdUyKe7YnG78+2A1rvnDZxyvREREFDXempFRmhkJAO8fOou1O0/h6Wvzvatnq5ngSn0Ag5FERDGw67QFozISkZKghkETu0ux1eHCc6XleHrjUQDAmu+Pw6qyCu820LJa31MbjgAAFhXlcsYZxYx3vG7geCUiIqLoklbTjlbNSADYfrIlk2pMJmu4U9/CkDoRURdYHS44XB7UNNrhcHlgdbi6/Jp6mxPFeal4938m4r2fTgqpjUhRyeUoKasA0LJKcXFeClZvPRF031VlFVDJ+WeDYofjlYiIiGLFWzMySsHI2iaHd4G+K4eYo3JMomjhdAEiohDZnG48V1qOkrKKkNNBfV8TjymlFpsTlmYnACAjUYOaRod3u82+zU7U2ZxINWii2UUiL45XIiIiipVor6b9WetilyNSEpCSwO8z1LdwygARUQisDhdWbD6G5RuOeIMfUjroys3Hgs5uDHzNirkFLSmlG46G3EakmbUq7+p8VQ12pBnU3u02++pUMGmDP0cUDRyvREREFCvRXk1729fSYpcDonI8omhiMJKIKAS+6aGB2ksH7Q0ppU6PBwum5gAAzlkd2HjkHO6dMjTovgum5sDpid7qgUSBOF6JiIgoVqSZkTaXBx6PiPjxtrcGI69kMJL6IKZpExH5sDpcUMnlsNicMGtVcHo8SFAr/dJDA7WXDtobUkoT1Eo8MmM4gJaA6OL1B7Fl3mTIZEBJnKSSE0k4XomIiChWpNW0AcDmckMfwUXy3B6Bz05aAACFQxmMpL6HwUgiolYd1YSU0kODBRPbSwf1fY1vSmlX2ogGrUqBRUW5eHTmCNTZnDBqVXhgei6WzMxDnc0JU2tQloEdigccr0RERBQLOp/vFs1OD/TqyB3rQHUDGuwuGDQKjMrgStrU9zBNm4gIndeEtLnc3vTQQO2lg/amlNIEtRJqpRypBg3USjmMWpXfdkIEf/kl6iqOVyIiIoo2hVwGtaIlhBLpFbWlepETswdAIZdF9FhEscBgJBEROq8JqVUq8PCM4XiseIR3wQyzToXHZ+XhkRnDgwY/EtRKPDB9mPc1i9cfxIKpOXh8ln8bT3TQBhERERERxQedqiWEEukVtb86U49RGYmYMSIloschihXe+RJRv2Z1uKCWy3GhufOakLtOWzA+y4zTjxejtsmJAXoVDtU0dpgO+tj7h1A0PBXfPDELjXYXU0qJiIiIiHopvVqBOpsroitqWx0uPPutAtQ0OpCZqIHV4eKkBepzODOSiPotqUbkJc+XwqBReGcrBpLqOZZ8UoEb1+7Amh2ncKimETnPbMJtr3/RbvtOtwd/3nkaN67dgUPVjUwpJSIiIiLqxaS6kZGaGSndn2Qv34jcZzdh4FMb8HxpOWwRnolJFG0MRhJRv+RbI7L8fFOH9RwfKRqORocLO07XQS4DbhydiSuyzbjQ7MThs1acqG0K+rrPTl5Avc2FZL0KYway8DQRERERUW+mbw1GRqJmZGc17K0OV9iPSRQrDEYSUdhYHS44XB7UNNrhcHlQb3P6bcfTH9DAGpGL1x/E/Kk5fjUhJw42Y88D03HfVcPQ7HSjYslMfPTzycg0amHSqVA4ZAAA4IPDNUGP8cHhswCAWXmpLDxNRERERNTLXZwZGf6FJzurYa+SM3xDfQdzA4koLKSUgpKyCmQkarBl3mSs2lqB1WUnYGl2wqxTYcHUHDwyY3hc1Ee02PxrRB6qacT0Vz7Fs3MLcOrxYticHujVCqzcfBQlPu9h/tShuDzbDK1KgdkjU1FWUYsPD5/FXYVD2xzjw9Zg5OyRadF6W0REREREFCH6CKZpB96f+D3XWsM+1aAJ+3GJYoGhdSLqscCUghVzC7CqrAJPbzgatykGZq2qTY3IQzWNuHHtDoz79cfQKOVYufkYlge8h+Ubjnrfw5y8liDjpmPn4HT7/zp6zmrHztMWAMDsvNTIvyEiIiIiIoooaTXtSCxgE+z+xPtcaw17or6CwUgi6jHflIKUBDWK81KweuuJoPvGS4qB0+1pt0bkzyYNgVrReZrE+CwTkvUqqBVy7DtT77fPjpMWJOvVGJ2ZiIEmbbi7T0REREREUaZXR25mpNPjwYKpOUGfWzA1B05P+FPDiWIl9hGBTjz55JOQyWR+//Lz873P22w23HPPPUhOTobBYMBNN92E6urqGPaYqP/xTSnISNSgptHRaYpBuHRWp7K9bavDjcUzR+DxWXneXyDNOhWemJWHX0zLCSlNQiGX4d8/mYSKJTORZtD4tT8q04iKJTPx5/++LGzvlYiIiIiIYkcXwQVsEtRKLJw+zK+GvXR/8siM4UhQs8oe9R29YjRfeuml2Lhxo3dbqbzY7fvvvx/vvfce3nrrLZhMJtx777248cYbsXXr1lh0lahfklIKLM1OVDXYkWZQe7fb7BvGFIOO6lR2tm1pdmLiYDN+/90xWDJzBOpsTpi0Kjg9HmhUCphlsk7fg83pxvpD1bj2j5+1Wydz/tQc5KcZ4qJOJhERERERdZ8ugjUjAWDl5qOYODgJ3zwxC412l/f+hPcS1NfE/cxIoCX4mJGR4f2XkpICAKirq8Of/vQnvPDCC5gxYwYmTJiANWvW4NNPP8X27dtj3Gui/sM3peCc1YGNR861mwIdrhSDzupUdrYNAJ+ftGDcr7fgpS3HkaBRQK2Ue39x7CxNwuZytx6//fZbakzGT51MIiIiIiLqvkjOjASAt/dV4ca1O7C14jxSDRq/+xOivqRXBCOPHj2KgQMHYtiwYbj11ltx8uRJAMCuXbvgdDpRXFzs3Tc/Px+DBw/Gtm3b2m3Pbrejvr7e7x8RdV+CWolHZgz3phQsXn8QC6bm4PFZ/ikGjxWPwMNhSjHoqE5lZ9uBVpYeg1LmfzmU3tMTQdK4H5kxHFqlotfVySQiIiIiou67WDMy/PUbz1sdOHLWCgAYn2UOe/tE8STuQ+yTJk3C2rVrMXLkSJw5cwbLli3DtGnTsH//flRVVUGtVsNsNvu9Jj09HVVVVe22uWLFCixbtizCPadosjpcUMnlsNicMGtVsLnc0CoV3m2nx8NflCJMo5Rj4uABODVjOBrtbhi1KjwwPRdLZuahzuaEQa1AVaMDAFDTaO/2ebE6XFDL5bjQ3H6dys62A0k1IFMNGr/HtSoFFhXl4tGANG6tSoGaRnuP2yciIiIiot5Dp2ydGRmB1bS3f30BADAyNQFJenXY2yeKJ3Efnbn22mu9/z1mzBhMmjQJQ4YMwd///nfodLputbl48WIsXLjQu11fX4/s7Owe95Vio6O6gVLdvgVTc1pms7HWRsScvNCM6179HJlGDU48WgyVUg61smU2YKpBg0a7C2s+P4nVW7t/XqRz/cYXp7Hngent1qnsbDtQR3UspWCpFEhUt04oj1WdTCIiIiIiig1pZqQtAmna20+2BCMLhySFvW2ieNPr8gbNZjPy8vJw7NgxZGRkwOFwwGKx+O1TXV2NjIyMdtvQaDQwGo1+/6h36qxuINAyK+0p1u2LuC/PtJQ7SE3QQKX0v7RYHS48/1E5nt7Y/fPie67Lzzf51aUMrFPZ2Xag7tSxjEWdTCIiIiIiih2dquU+JxI1I6WZkVcOHRD2toniTa8LRjY2NqK8vByZmZmYMGECVCoVNm3a5H3+8OHDOHnyJAoLC2PYS4qWjuoGBmLdvsja801LMHLcwLbBfd/zFCjU8xLYxuL1BzF/ak67dSo72wb8a0B2NV08sKZkuNsnIiIiIqL4oo/Qatpuj8Bn3pmRDEZS3xf3d8cPPvggvv3tb2PIkCGorKzE0qVLoVAocMstt8BkMuEnP/kJFi5ciKSkJBiNRsyfPx+FhYW48sorY911igKLrf26gW32Zd2+iNp7pg4AMCZIMNL3PLV5LsTzEtjGoZpGTH/lUzw7twCnHi+G1dG2TmVn2741ILsjsKZkuNsnIiIiIqL44V1NO8w1I7+qakCj3Y1EjRKXpCeGtW2ieBT3wcjTp0/jlltuwfnz55GamoqpU6di+/btSE1NBQC8+OKLkMvluOmmm2C32zFnzhy88sorMe41RQvr9sWPPZXSzEhTm+d8z1Ob50I8L8HaOFTTiBvX7kBush4HFhW1qVMJoPPtHk4Qb1NTMsztExERERFRfPCupu0KbwmmbV/XAgAmDTZDIZeFte14ZXO7UNVUj6wEM5TMYOx34v6Mr1u3DpWVlbDb7Th9+jTWrVuH3Nxc7/NarRYvv/wyamtrYbVa8fbbb3dYL5L6FqfHE9G6gBSaepsTx883AQDGBpkZ6VtfMdAjRcPhEp2fF99zHejW8Vlw8NwSEREREVEE6VQKpCSoMdCoDWu7py3NSElQ48o4StG+YG9Cg9MWsfbrHM1IVKlhcTRH7BgUv+J+ZiRFl9Xhgkouh8XmhFmrgsvjgQD8HrO53NAqFe1uOz2eqNXHE0JgfmuQa/XWE1i8/iC2zJsMmQwo4WraUbPvTAMAIMukRXKCus3zUn1FoKVGpKXZiYmDzfj9d8ciP9UAi80JpUze4dhxuj1+55rnloiIiIiIoumSdAMqlszE2UYHHC5Pj++Npfvvn04agkdmjsA5qyOK76Z9buGB1eWAWq5Ak8uJNK0BMll4Z2za3S5kGAbg68YLABLC2jbFPwYjycvmdOO50nKU+ASLPrjzSrzw8XGUlFUgI1GDLfMmY9XWCqwuO9FmOxbBob9/eQa/+qgcv/nOKDxW3LYuYHWjHUl6FY6ctTJYFUF7KlvqRQabFSnxra/YaHdBp1Zg5eajIQeN/7a7EiVlFSjxOdesyUhERERERNFgc7rx++1foyTIvXB37o0D77/jaaJFo9OBRJUGBeZ0HKk7i1NWCzL1Rqjk4elXk8sBnVKFgXojztoaYXU5kKBsO6mF+i4GIwlAyy8yz5WWY/mGI97HFs8YgV9/VI6nNx4FAKz5/jisKqtodxtoWYzkqdY2FhXlRnyG5J93nMKhmkbsOm3BrLzUNnX7jp5txH//9QuoFDJ8vaQYSkXcVybolb5srRcZbPEaX9J40HjkWLn5GJZvCH3svLaz5Vx/eaYeM33PdfxXmyAiIiIiol7s4v1yeO6Ng91/R/teuiONTjuGGZOQqTfCqNLgUN1ZnLReQLImISxBwwanHanaBKTrEpGhS8TXjRYGI/sZ3sUTgJY07JKyCu92SoIaxXkpWL31REjbgV7/4jTUES5Ce8rShIM1jZDJgNvGZwXdZ2pOMoQQOFNvx8fHz0e0P/3Zlx0sXhNM4HjzFWzsVJxvQvn5JijkMtzazrkmIiIiIiKKBN/7l67eG68qq4Aq4P6mo/uhYPtHk0cIeCCQomlJnU5QaTA2KRMFpjSct1vh9PR8JXG7x4UMnREymQyZeiMAARfXAOhXODOSAAAWm9NvleKMRA1qGh3exzrbluSnGbBibgGK81JQ2+zEAF34a0hKdTVkkKFiyUx8cboOWWZd0H3VSjl+cdUwjM4wonBIEmoa7VGva9nXudwe7DvTEozsKE3bV+B4A4KPHanmikrRcq73fFOH9ERN2N8DERERERFRe3zvX0K9N/a+ttmJOpvTm9kV2F4o+0dTk8uBBKUKZvXFe2ylXIHhxhQ0uhw4ZbUgW2/udg3JJpcDeoUKSZqW9pM0epg1OlgczUjRsnZkf8FoDAEAzFoVzDqV94JY1WBHmkHtfayzbaAlmPTxvMkoKavAHW/uiUjdi2B1NeZPHYorss3ttn//VcPwy83HItan/u7oOStsLg8S1ArkJof2xyNwvAWOnfZqrsyfOhQTsto/10REREREROHme/8Syr2x32t1Kpi0qnbbC2X/aGpw2pGVYIJW6d8HpVyBfFMaGpx2nLNbkao1dKv9eocN6bpEJKg03nazE8zYc74SXMim/2CaNgEAnB4PFrSuVAwA56wObDxyDvdOGRrSNgCsmFuAktY6GdJFVap7seqTCjQ5XT3qo9XhworNx7B8wxG/9pdvOIqVm4/B6mjbvlSLI1if2nsNdc2hmkaMykjEtJwkKOSh/ToWON4Cx86KuQUtNVc2HA35XBMREREREUWC7/1LKPfGvhZMzYEzIAU58H6os/2jRQgBp3C3G2g0qDTIN6XB6XHD6ur6yt9CCDiEGxn6RL/HU7UG6JWqbrVJvRNnRvZzUsqzzenBwzOGQwDeWYcrNh/FB3deCblMhlVlFVi8/iC2zJsMmQwoKTvht/3GF9+gOC8Fd7y5x69939TbRrsbSpm82ynSndXVeHTmiLC8hkJndbhwTX4axg0yISNRA6vDFdK5TVAr8ciM4QBaakT6jh2p5krgWJLwvBERERERUTT53r90dm9c4pfZFTwjT2rPAxHy6tvR0Ox2Qq9QwazWtrtPhi4RI4wpOGipgUavhLIL9S2bWtsfoPYvs2ZQafwWsvEIAYfHDYfbBbVcAY1C2e20cIpPMiGEiHUnYq2+vh4mkwl1dXUwGkOredcX2JxurNh8zBt8nDjYjN/fPAb5aYmoszlh0qrg8ngg0BLUkx6T6vj5buuUCtQ2O5G57ENv+76pt6u39vwCW9NoR8aTH7b7fPWTs9vU1ejOayg0geOnO+fW6nBBLZf7jZ1RGYl4938mIvfZTe2+jueNiIiIiIiiTZrM09G9sVapQHWjHUl6FSpqmzAqI3iMQQiB9w/X4KphyWiwuZCkV0dtbQO3x4OPq8ohgwxGn8BjdXMDUrUJuCJ1cIevd3rc+OLcaXzTVAeTWgejSgt5CMHCqqZ6ZOiNmJDSdlHS6uYGfFbzNTwQkEMGlVwJjUIBu9sNu8cFAQGtvKXWpFLee8t2nbJacFnyQAwxJMW6KxERanyNMyP7KSl9efmGI97HPj9pwbgXtmDl3ALcO20o1Eo51D6Z/FLwR62UB90eoPOve+GbeiuRUqQBYFFRbpcutN2pqxHPtTh6s2DjpzvnVtrHd+x0p+YKERERERFRpEn3L53dG2+tqMWCf+zHqIxEbP755KBtfVXVgG/98XNkm7U48vCMNvffsWD3uJCuS+x0P5VcgdFJmRig0eG0tQ6nmyzQylXQK1VweNywu11wCTcEAI1ciQSlGjqlqiVFu532UzQJGJWUCZVMAZ1SBa1CCa1CCZvbBavLgUanHaetdbjgaO52vUqKH6wZ2U91lL68svQYlLKuDw3fuhdSqu3qrSeC7ruqrAKqLkznDmw/UHt1NTp6zSNFw+ESsanF0dt1lv7ek3PbnZorRERERERE8eKKbDPOWR0oq6hFgy14vfsPDp8FAFyanghNHCzQaXO7oJUr/VbR7oheqUaeKQ1T0nNwRUo2zGoNHB4XdAolBhvMGJs0EJclDUKqNgEOjwuVTfUwKNUYoAnevkIux7DEZGQbzEjRJsCg0kApV8Cg0iBdl4hcYwoG6Y2wu7l+QF/AmZH9lMXmDDrrDGiZ4VZnc3Y5Dda3jsaGo2dR0+gI6zGk9gWEXx2OjlKDA2t7eNPRvzsW+akGWGzOHtWx7K/CPX46q8ESLzVUiIiIiIiIOpObkoDcZD3KzzehtPwcrrs0o80+Hx6pAQDMHpkW7e4F1ei0w6TWIlHVtTiARqFEVoIZA/VGuDweqOQKv/qOQxOTYHM50eCyw+XxQK9Ud7uPiWotBFpS3FlDsndj9KWfilT6slalwKKiXDw6cwREa1vhPIZWpcCsEal4qGg46ppdSEloqavRUXDKt0+Ndhd0agVWbj7KIFcPRGL8+J6nOpsTRq0KD0zPxZKZed4aLJ2dayIiIiIiongwe2QafvvpCXxw+GybYGSTw4Utx2sBAHNGpsaie5DJZKi1NaHBaQdkgMPtQp4ppdtBPrlMDrUieIacVqmCVtnzUlsGpRpahRJ2tyss7VHsME27n+pOynOoEtRKqJVyuCJwDCEEvrN2B3Ke2YTaJgfUSnnItQnVSjk0KjlWbj6K5RuOegNpUq3DlZuPwerglO9QRGr8SOcp1aCBWimHUavy2+bsVSIiIiIi6g2kIOOHh2vaPPdx+XnYXR5km7XIT4t+/UOFXI4RxhSMSx6IfHMqhicmo8CcHve1GPVKNQxKNZrcwbP0qPfgnX0/JaXFeiCwOkIzBIOlSJt1Ktw7ZWi3j3HkrBW1TU5olXLkpXb9QtlS6/BE0OdWlVXg0Zkjutxmf5SgVmLh9GHwCBGWldKJiIiIiIj6kqLcFKgUMtTZXDh5oQmDB+i9z+09U4+UBDXmjEyLWbpxVoI5JsftCZlMhiSNHsfqzwNdyyanOMNgZD+mUcoxecgAPFw0HA02F5L0nac8d5Vv6q3F5oRBrUB1owMAUNNoh7k19TbUGW/bvr4AALg82+xdqawrIlErsz8SQuC213fjfyYNRuUTs9BgdzGNmoiIiIiIqFWiVokNdxViQpYJlmYXHC4PbC43tEoF/nvcINw7NQfVDfZYd7PXMal18KB7mXiNTjtsbhd0ShV0ChXkrDsZMwxG9mMHqhsx94+fI8ukxZFHZkCtlEMdgcx9KdCYZtCgwebCms9Pdns23bavW+pqXDlkQLf6Eqlamf3NF9/U4d8Hq7Hx6FlULZ3tDeBGYvwQERERERH1NjanG5uOnsV31uxARqIGW+ZNxqqtFRHLTOwvDCo11HIlHG4X1IrQQlpOjxvVzQ3QKJQwqjRodNpxwd4EAYEEpQZJGn3njVBYMRjZj33QWrvi0ozEqFz8rA4XfvVxOZ7eeNT7mFSvUa9S4N5pQ6FXdTwkt7fOjCzsZjBSqnX41IYjbZ6Tah0yoNa5D4+cRUqCGsUjUmDUMYBLREREREQksTpceK60HMs3tNz7rvn+OKwqqwh6LwwAi4pyWR8/RAalBjqlCk1uZ6fBSCEEztubYHM7MVBvxHBjCgZo9Gh2OdHgtKHBaceRunOoc9hgUmu71A+Xxw2Hxw238CBBqeEsyy7iaO/HPjx8FgAwO0qrd7XUa6zweyw/zYAVcwtQnJeCRrsbSpm83bTtepsT+6saAHQ/GNleHcv5feAXKavDBZVcDovNCbNW5U0BaG+7K+nxgce4ZdwgLJiag/NWR4TeDRERERERUe/ke++bkqBGcV4K7nhzT9B9uXZB1yjkciRr9DjZaIFZretw38qmeiSqNbh0QDoydUYo5C0Tj3RKFXRKFdJ0iZBDhj0XKqFVKKHpJLhpc7tQY2uAHDIo5XKoZHLIZDKcaarDQL0pZvU/eyMGI/upJocLHx8/DwCYk5cWlWMG1mvMTzPg43mTUVJWgTve3NPpVPXPT1ogBDB0gA4Zxq79auHLt45lTaMdA/QqHKxu7NWBSJvTjedKy1FSVtEmBSBcKQG+x2BaARERERERUXC+974ZiRrUNDq4dkEYmdU6lHvOd7hPncMGrUKBy5IGwaxpP2g5JHEA6p02HG+sRZbe3O4MR6fHjZrmBgw3JiNdlwiNQgmNXAmb24Uvzp9Gja0R6brEHr2v/oT5qP3UluO1sLs8yDJpUZDe9VWpu0Oq1yhZMbcAJa1T1aULszRVfeXmY7A6XH6vlxavKRya1OO+JKiVUCvlOHmhCTnPbMKc32+H3eXucbuxYHW4sGLzMSzfcASWZidWzC1oSQHYcDToNtDyB/GyQSYIADUNdjhcnjafd0fHADo+V0RERERERP2V771vVYMdaQa1372w375cu6DLDCoNlHIZXJ7gC9m4PB7UOZuQa0zpMBAJAHKZHHmmNCRr9Khpbmi3vTNNdRhqGIB8czrSdIkwqXXQKlUwa3QYNSADcpkMF+xNPX5v/QWDkf3U3so6pCSoMSc/LWpTiaV6jcDFqeqrt54Iuu/rX5yGWu4/PM/U25CSoO724jXBTBqSBI1SjgvNTm/aem8TLAVA+lyDfc7SjNRdpy0Y9NQGZCz7EBnLPsTzpeWwOYMHZIOl2EtWlVVAJeelhIiIiIiICPC/9z1ndWDjkXO4d8rQoPtKaxdQ6AxKNXRKNZrdwcuG1dgakKFNxGBDaLEDnVKFAnM65DIZGpw2v+fcwoPK5jpkJZhxyYAMqORtswLTdIm41JyBZrcTjc6WFdKdHjcu2JvwjbXO+xhdxDTtPq69OoLfHzcI90zNQXVD9P6n8K3XuOHo2aBT1X1rSNY2OzFAd7HPDxUNx/PfvgT1tvDNwlPIZbjvqmEYnpyAmSNSUdNo73Y9xVjpKAUgWEqA74xUbxvNTvz9y0rcNCYTI1MNbepKBqbY+x2faQVERERERERegWsVLF5/EFvmTYZMBpRwNe0eUyuUMKl0OGtrRKLKv4Sb1eWAQibHCFNa0MBhe1K1BuSZUnHAUg2LoxkyyKCWK2H3uJChNeDSARkd1pTMSjDB5nbiK0sVau1NUCnkSFRqkZ2gxwnrBWgVKig5icerd0RbqFs6qiMYq4ufb71GgZYp6VKQK7CGZLT6/PPCIVi5+VhIdSvjkZQCYGl2+qUABNtur3iy72e/emvbz9r3GG2Oz7QCIiIiIiIiP773vnU2J4xaFR6YnoslM/NQZ3PC1Dr5ozfcc8ajFK0e3zTV+T3mEQLnbVbkm1ORok3ocps5iUkwqXVodjnR5Laj3mGHRwhcMiAdeqW6w9fKZDIMS0yGXNayuI1JpUOiSgMBAYfHjRpbAwbqTV3uU1/FsGwf1VkdQSB2Nf+keo0un6nrQNsaktHos9Xhwi9Ly0OuWxmPnB4P5reTAhC43V7x5M7qd9pcbqYVEBERERERdYF075tq0ECtlMOoVflt95ZsvHhkUGkgQ0sAEgBcHjeqmuuRrNUjx5DcrTblMjlStAnINpgx0pSOK1IHY1LakDazL9ujkMuRa0zBEEMSzBodFHI5lHIFRphSoZQpmK7tg8HIPqqjOoKBYlXzT5q6/sSsPOQm6zutdegrXH3uC7UQ9SoFfjEtB48Vj4BZp8Li9QexYGoOHp/VdrvZ6W5TPDmU+p1apRy/mDbMewygZUbkE7Py8MiM4fwjSkRERERERFFjUGqgUyhRa2/CaasF1bYGDNDoUGBOh1YZX5l7SRo9co1JqLU3wSM4kQfoZcHIlStXQiaT4b777vM+ZrPZcM899yA5ORkGgwE33XQTqqurY9fJONFRHcE2+7bW/IsFaer6gUVFaLS7o97nUGohxiurwwWHy4Mz9XZolXL8z8TBOLN0Nj6eN9mbAlAVsP3VoiI43P4zUtv7rPPTDHjnx1dgzwPTcaHZBb1KjrsLh6Jq6WxUPzkbVUtnY1FRLtMKiIiIiIiIKKp0ShVMah3kMmBYYhIK04aiMHUoUrWGWHctqKGGJKTpDHB4gi8a29/0mulMO3bswO9+9zuMGTPG7/H7778f7733Ht566y2YTCbce++9uPHGG7F169YY9TQ+dFRHsM2+Ma75J82qG6CLfp97ay1E33qgUn3H+VOHYvGMEd6FZNTKlt8aArfVSrVfMeVgn3Vg/c7AGpLeNnvX7xlERERERETUR4wakAGZTNZpPcd4oFYokWdKRQNTtQH0kpmRjY2NuPXWW/GHP/wBAwZcXJq9rq4Of/rTn/DCCy9gxowZmDBhAtasWYNPP/0U27dvj2GPY8/pU48xsG5goHip+ReLPjsD6lZG4hjhFlgPFGiZxbl8w9GQ61xKM1Krls7GV4uuhkegw/qd0jF6Uy1NIiIiIiIi6rsSVJpeEYiUpGoNyE1MhlYRn5OeoqlXBCPvuecefOtb30JxcbHf47t27YLT6fR7PD8/H4MHD8a2bdvabc9ut6O+vt7vX1/jW48xWB1BIP5q/sWiz4HHlI7xeBx9LoHCVefSt5hyoqb9+p09OQYRERERERERtRhhSkW6LjHW3Yi5+Iu0BFi3bh2++OIL7Nixo81zVVVVUKvVMJvNfo+np6ejqqqq3TZXrFiBZcuWhburcUea/fbozBGoszm9dQOXzMxDnc0Jk1YFp8cTVzX/YtFn32Oetdph1qmwt7I+rj4XX6HUuZTSqLtC+hyWzByB2ubIHIOIiIiIiIiI+re4nt506tQp/OIXv8Drr78OrTa0pdRDsXjxYtTV1Xn/nTp1Kmxtxxvf2W9qpRxGrcpvOx5n/sWiz9Ix620u5DyzCUW/3YYLTY6wHyccpDqXQZ/rYZ3LBLUSKqXcW78zEscgIiIiIiIiov4rroORu3btQk1NDcaPHw+lUgmlUomPP/4Yq1atglKpRHp6OhwOBywWi9/rqqurkZGR0W67Go0GRqPR7x8R0LJwS6ZRA4fbg3f3tz+7NpaiUeeyN9bSJCIiIiIiIqL4F3/T4nzMnDkT+/bt83vsjjvuQH5+Ph5++GFkZ2dDpVJh06ZNuOmmmwAAhw8fxsmTJ1FYWBiLLlMvJ5PJcN+0YUjSqzErLxU1jXaYW1PD42UWaYJaiYXTh8EjBFZvPdFmpetwpJdLtTSBlhqRkTgGEREREREREfU/MiGEiHUnuuLqq6/GuHHj8NJLLwEAfv7zn2P9+vVYu3YtjEYj5s+fDwD49NNPQ26zvr4eJpMJdXV1nCVJaHa6sWLT0YgF+npKCIFv/+lz/PTKIbhmZCoa7C5vLc1wB0ytDhdUcrlfvc54CcoSERERERERUfwINb7W66MKL774IuRyOW666SbY7XbMmTMHr7zySqy7Rb2U1eHCc6XleHrjUe9jlmYnntpwBACwqCg35sG4HacsWH+oBqXl51C1dLZ3IRl1BKouSO81kscgIiIiIiIiov6j182MjATOjCSJw+VBxrIPg64knZusx4FFRVApYxuQe3bjEbz0SQVm56Xir7eOj2lfiIiIiIiIiIiAfjQzkiicLDZnm0BkfpoBK+YWoDgvBbXNTgzQRSddWUqRtticMGtVsLnc0CoV+MH4LPziqmE4b43P1b6JiIiIiIiIiNrDYCSRD7NWBbNO5Q1I5qcZ8PG8ySgpq8Adb+6JWg1Jm9ON50rLUVJWgYxEDbbMm4xVWyuwuiw+61gSEREREREREYWCBeCIfDg9HiyYmuPdXjG3ACVlFXh641FvgFKqIbly8zFYHa6w98HqcGHF5mNYvuEILM1OrJhbgFVlFXh6Q/T6QEREREREREQUCQxGEvlIUCvxyIzheGJWHnKT9SjOS8HqrSeC7vv6F6ehlof/fyGVXI6SsgoAQEqCusM+rCqrgCoCfSAiIiIiIiIiigSmaRMF0KoUWFSUiyUzR6C2Ofo1JH3rVmYkalDT6Ai6oA7QMkOyzub0rnZNRERERERERBTPOKWKKIgEtRIqpRwDdC01JCVSDcldpy3IXr4Rmcs+RMayD/F8aTlsTndYji3VrQSAqgY70gxqvz747atTwaQN/hwRERERERERUbxhMJKoA12pIbnqkwo0OXtev9Hh9uDeKUMBAOesDmw8cs67HWjB1Bw4PZ4eH5OIiIiIiIiIKBqYpk3UAamGJNBSI7I4LwV3vLnHbx/ftO1GuxtKmbxbadtWhwsquRxNDjcWzxwBmUyGkrIKLF5/EFvmTYZMBpRwNW0iIiIiIiIi6sVkQggR607EWn19PUwmE+rq6mA0GmPdHYpDVocLarkctc1OZC770Pu4lLZdUlaB1Vu7Hyi0Od1YsfkYSsoqYGl2YuJgM37/3THIT01Enc0Jk1YFm8sNrVLh3Q5nnUoiIiIiIiIiop4INb7GNG2iELRXQ7KjtO2Vm4/B6ug8bdvqcGHF5mNYvuGIt43PT1ow7tdb8NKW40jQKKBWymHUqqBWypFq0ECtlDMQSURERERERES9DoORRF3gW0MyJUGN4rwUrN56Iui+r39xGmp55/+LqeRylJRVBH1uZekxKGX835SIiIiIiIiI+gZOrSLqAt8akhuOnkVNo8M7m1HiW0OyttmJAbqOU6otNmebNrzPNTtRZ3Mi1aAJ7xshIiIiIiIiIooBBiOJukirUmBRUS4enTkCAoBZp/IGE31rSN7x5p6QakiatSq/Nvye06lg0qraPE5ERERERERE1Bsx/5OoGxLUSqiVcrh80raB7tWQdHo8mO/Thq8FU3Pg9Hgi8yaIiIiIiIiIiKKMwUiiHpDStp+YlYfcZH2HNSRXlVVAFaSGZIJaifuvGobHikd4F8cx61R4YlYeHpkxnAvVEBEREREREVGfwSgHUQ9JadtLZo5AbXPw+o9SHUkBoKbRDrP2Yh3JJocLs363DUuK83Bm6SzU21wwtT4fLK2biIiIiIiIiKi34sxIojBIUCuhUsoxQKfyzm6USHUkd522IHPZh8h48kNkLPsQz5eWw+Z0Y/Oxc9h1ug4L390PlVyOVIMGaqWcMyKJiIiIiIiIqM9hMJIojJwBNSSBjutIrvqkApmJWqQkqPHDy7Mhl8ti0W0iIiIiIiIioqjg1CuiMJJqSAItNSKVchmK81Jwx5t7/PaT0raL81JgtbtRsWQmmh3uGPSYiIiIiIiIiCh6GIwkCjOphuSjM0eg0eGC1eH2qyMppW2XlFXgjjf3wNLshFmnwoKpOXhkxnDWiSQiIiIiIiKiPovBSKIIkOo9JinVcLg8MOtU3oCkb9q2RErbBoBFRbmsF0lEREREREREfRJrRhJFmG8dyZQENYrzUrB664mg+64qq4BKzv8tiYiIiIiIiKhv4vQrogjzrSO54ehZ1DQ6/NK2fVmanaizOZFq0ESzi0REREREREREUcFgJFEU+NaRFIBf2rYvs04Fk1YV/Q4SEREREREREUUB80GJoiRBrYRaKYfLJ2070IKpOXB6PFHuGRERERERERFRdHBmJFGU+aZtryqr4GraRERERERERNRvxP3MyN/+9rcYM2YMjEYjjEYjCgsL8Z///Mf7vM1mwz333IPk5GQYDAbcdNNNqK6ujmGPiTonpW1XLZ2N6idno2rpbCwqymUgkoiIiIiIiIj6tLgPRmZlZWHlypXYtWsXdu7ciRkzZuD666/HV199BQC4//778a9//QtvvfUWPv74Y1RWVuLGG2+Mca+JOielbacaNFAr5UhQc6IyEREREREREfVtMiGEiHUnuiopKQnPP/88br75ZqSmpuKNN97AzTffDAA4dOgQCgoKsG3bNlx55ZUhtVdfXw+TyYS6ujoYjcZIdp2IiIiIiIiIiKjPCTW+FvczI3253W6sW7cOVqsVhYWF2LVrF5xOJ4qLi7375OfnY/Dgwdi2bVu77djtdtTX1/v9IyIiIiIiIiIiosjqFcHIffv2wWAwQKPR4O6778Y777yDSy65BFVVVVCr1TCbzX77p6eno6qqqt32VqxYAZPJ5P2XnZ0d4XdAREREREREREREvSIYOXLkSOzZswefffYZfv7zn+P222/HgQMHut3e4sWLUVdX5/136tSpMPaWiIiIiIiIiIiIgukVK2ao1WoMHz4cADBhwgTs2LEDv/nNb/D9738fDocDFovFb3ZkdXU1MjIy2m1Po9FAo9FEuttERERERERERETko1fMjAzk8Xhgt9sxYcIEqFQqbNq0yfvc4cOHcfLkSRQWFsawh0RERERERERERBQo7mdGLl68GNdeey0GDx6MhoYGvPHGG/joo4/wwQcfwGQy4Sc/+QkWLlyIpKQkGI1GzJ8/H4WFhSGvpE1ERERERERERETREffByJqaGvzoRz/CmTNnYDKZMGbMGHzwwQeYNWsWAODFF1+EXC7HTTfdBLvdjjlz5uCVV17p0jGEEADAVbWJiIiIiIiIiIi6QYqrSXG29shEZ3v0A6dPn+aK2kRERERERERERD106tQpZGVltfs8g5FoqUFZWVmJxMREyGSyWHcn7Orr65GdnY1Tp07BaDTGujvUz3E8UjzheKR4wvFI8YTjkeIJxyPFE45HiifxNh6FEGhoaMDAgQMhl7e/TE3cp2lHg1wu7zBi21cYjca4GJxEAMcjxReOR4onHI8UTzgeKZ5wPFI84XikeBJP49FkMnW6T69cTZuIiIiIiIiIiIh6HwYjiYiIiIiIiIiIKCoYjOwHNBoNli5dCo1GE+uuEHE8UlzheKR4wvFI8YTjkeIJxyPFE45Hiie9dTxyARsiIiIiIiIiIiKKCs6MJCIiIiIiIiIioqhgMJKIiIiIiIiIiIiigsFIIiIiIiIiIiIiigoGI4mIiIiIiIiIiCgqGIwkIiIiIiIiIiKiqOgzwcgVK1bgiiuuQGJiItLS0vCd73wHhw8f9tvHZrPhnnvuQXJyMgwGA2666SZUV1f77XPy5El861vfgl6vR1paGhYtWgSXy+W3z0cffYTx48dDo9Fg+PDhWLt2baf9E0LgiSeeQGZmJnQ6HYqLi3H06FG/fZ555hlMnjwZer0eZrM5pPd9+PBhFBUVIT09HVqtFsOGDcNjjz0Gp9Pp3eerr77CTTfdhKFDh0Imk+Gll14Kqe29e/di2rRp0Gq1yM7OxnPPPddmn7feegv5+fnQarUYPXo01q9f32m7kfqMa2trceutt8JoNMJsNuMnP/kJGhsbu/yewiFa47GsrAxTpkxBcnIydDod8vPz8eKLL3bav1DGozRefP+tXLmyw3ZD6c+WLVvw7W9/GwMHDoRMJsM//vGPTvsLhDYmXn75ZQwdOhRarRaTJk3C559/3mm7vW2cd0c0r492ux1LlizBkCFDoNFoMHToULz66qud9rGzc1deXo4bbrgBqampMBqN+N73vtemf4HOnz+Pa665BgMHDoRGo0F2djbuvfde1NfX++3XnfPQ28ZNX7w+LliwABMmTIBGo8G4ceOCHqu776mz8fj73/8eV199NYxGI2QyGSwWS6dthjIez5w5gx/84AfIy8uDXC7HfffdF1J/e9u4Cdf1JhyiNR5D+b7Wns7G49VXX93m7/Xdd9/dYZv8/nhRf70+CiHwq1/9Cnl5edBoNBg0aBCeeeaZTvvY2bmrrq7Gj3/8YwwcOBB6vR7XXHNNm++YwVx33XUYPHgwtFotMjMz8cMf/hCVlZV++3TnPPS2cdPXro9ffvklbrnlFmRnZ0On06GgoAC/+c1v2hyL99cX8fpI/YboI+bMmSPWrFkj9u/fL/bs2SPmzp0rBg8eLBobG7373H333SI7O1ts2rRJ7Ny5U1x55ZVi8uTJ3uddLpcYNWqUKC4uFrt37xbr168XKSkpYvHixd59jh8/LvR6vVi4cKE4cOCAKCkpEQqFQrz//vsd9m/lypXCZDKJf/zjH+LLL78U1113ncjJyRHNzc3efZ544gnxwgsviIULFwqTyRTS+y4vLxevvvqq2LNnjzhx4oR49913RVpaml+fP//8c/Hggw+Kv/3tbyIjI0O8+OKLnbZbV1cn0tPTxa233ir2798v/va3vwmdTid+97vfeffZunWrUCgU4rnnnhMHDhwQjz32mFCpVGLfvn3tthvJz/iaa64RY8eOFdu3bxeffPKJGD58uLjlllu69J7CJVrj8YsvvhBvvPGG2L9/v6ioqBB/+ctfhF6v7/Q9hTIehwwZIp566ilx5swZ7z/f/gcTSn/Wr18vlixZIt5++20BQLzzzjudfp6hjIl169YJtVotXn31VfHVV1+Jn/3sZ8JsNovq6up22+2N47w7ojUehRDiuuuuE5MmTRIbNmwQFRUV4tNPPxVlZWUd9q+zc9fY2CiGDRsmbrjhBrF3716xd+9ecf3114srrrhCuN3udtutra0Vr7zyitixY4c4ceKE2Lhxoxg5cqTfdaE756E3jpu+dn0UQoj58+eL1atXix/+8Idi7NixbY7T3fcUyrXkxRdfFCtWrBArVqwQAMSFCxc6fd+hjMeKigqxYMEC8ec//1mMGzdO/OIXv+i03d44bsJ1vQmHaI3HUL6vBRPKeJw+fbr42c9+5vf3uq6ursN2+f3xov54fZT2GTlypHj33XfF8ePHxc6dO8WHH37YYf86O3cej0dceeWVYtq0aeLzzz8Xhw4dEnfeeWeb9xDMCy+8ILZt2yZOnDghtm7dKgoLC0VhYaH3+e6ch944bvra9fFPf/qTWLBggfjoo49EeXm5+Mtf/iJ0Op0oKSnx7sP7a14fqX/qM8HIQDU1NQKA+Pjjj4UQQlgsFqFSqcRbb73l3efgwYMCgNi2bZsQoiVIIpfLRVVVlXef3/72t8JoNAq73S6EEOKhhx4Sl156qd+xvv/974s5c+a02xePxyMyMjLE888/733MYrEIjUYj/va3v7XZf82aNSFfLIO5//77xdSpU4M+N2TIkJAulq+88ooYMGCA930LIcTDDz8sRo4c6d3+3ve+J771rW/5vW7SpEnirrvuarfdSH3GBw4cEADEjh07vI/95z//ETKZTHzzzTchv6dIidR4DOaGG24Qt912W7vPhzoeQx0rnemoP6EGI0MZExMnThT33HOPd9vtdouBAweKFStWtNtubxvn4RKp8fif//xHmEwmcf78+S71p7Nz98EHHwi5XO53c22xWIRMJhMbNmzo0rF+85vfiKysLO92d85Dbxs3ffH66Gvp0qVBb7a7+566ci0pLS0NORgZTOB49DV9+vSQgpG9bdxE8u9fOERqPAbT0fc1SSjjMdSx0pP+8Ptj37o+HjhwQCiVSnHo0KEu9aezc3f48GEBQOzfv9/7vNvtFqmpqeIPf/hDl4717rvvCplMJhwOhxCie+eht42bvn59lMybN08UFRV5t3l/zesj9U99Jk07UF1dHQAgKSkJALBr1y44nU4UFxd798nPz8fgwYOxbds2AMC2bdswevRopKene/eZM2cO6uvr8dVXX3n38W1D2kdqI5iKigpUVVX5vc5kMmHSpEkdvq47jh07hvfffx/Tp0/vUTvbtm3DVVddBbVa7X1szpw5OHz4MC5cuODdp7PP4sknn8TQoUP92g3HZ7x27VrIZDK/ds1mMy6//HLvY8XFxZDL5fjss89Cfk+REqnxGGj37t349NNPOzz/XRmPK1euRHJyMi677DI8//zzXU4BCaU/oehsTDgcDuzatctvH7lcjuLiYr/39OMf/xhXX321X7vxPM4jJVLj8Z///Ccuv/xyPPfccxg0aBDy8vLw4IMPorm5ud2+hHLu7HY7ZDIZNBqNdx+tVgu5XI6ysrKQ33dlZSXefvttv/HYnfMQ7+OmP1wfQ9Gd9xTqtSQcgo3H7oj3cfPRRx9BJpPhxIkTACL39y9cIjUeA4Xyfa0r4/H1119HSkoKRo0ahcWLF6OpqSns/QkFr4/hFanx+K9//QvDhg3Dv//9b+Tk5GDo0KH46U9/itra2g5f19lnbLfbAbT8jZbI5XJoNJou/b2ura3F66+/jsmTJ0OlUnmP3dXzEO/jpr9eH+vq6rxtALy/5vWR+qs+GYz0eDy47777MGXKFIwaNQoAUFVVBbVa3aZWRHp6Oqqqqrz7+P5PLD0vPdfRPvX19e3ecEuvDfY66bmemjx5MrRaLUaMGIFp06bhqaee6lF7PfksfN9TSkoKcnNzw9Ku72dsMpkwcuRIv3bT0tL8XqNUKpGUlNSl8xsJkRyPkqysLGg0Glx++eW455578NOf/rTd/oQ6HhcsWIB169ahtLQUd911F5599lk89NBDIb3nrvQnFJ2NiXPnzsHtdnf6njIzMzF48OBO25We62ifaIzzSIjkeDx+/DjKysqwf/9+vPPOO3jppZfw//7f/8O8efPa7U8o5+7KK69EQkICHn74YTQ1NcFqteLBBx+E2+3GmTNnOn3Pt9xyC/R6PQYNGgSj0Yg//vGP3ue6e02P53HTH66PoejOewr1WtITHY3H7oj3caPX6zFy5EhvQCHcf//CKZLjUdKV72uhjscf/OAH+Otf/4rS0lIsXrwYf/nLX3DbbbeFvT+h4PUxfCI5Ho8fP46vv/4ab731Fl577TWsXbsWu3btws0339zh6zo7d1IgavHixbhw4QIcDgd++ctf4vTp0yH9vX744YeRkJCA5ORknDx5Eu+++26nx5ae60p/fV/D62NowjUeP/30U7z55pu48847vY/x/prXR+qf+mQw8p577sH+/fuxbt26qB/79ddfh8Fg8P775JNPwtb2pZde6m332muv9XvuzTffxBdffIE33ngD7733Hn71q1+F7bg9ce+992LTpk1hb/eGG27AoUOHwt5uJERjPH7yySfYuXMn/vd//xcvvfQS/va3vwHo2XhcuHAhrr76aowZMwZ33303fv3rX6OkpMT7q7dvu4GF8tvrT6ytWLECr732WtjbjdQ4j4RIjkePxwOZTIbXX38dEydOxNy5c/HCCy/gz3/+M5qbm/HJJ5/4jZvXX389pHZTU1Px1ltv4V//+hcMBgNMJhMsFgvGjx8Pubzlz9i1117rbffSSy/1e/2LL76IL774Au+++y7Ky8uxcOHCsL/37uD1MbZ/r7s7HkPRG8djpMbNxIkTcejQIQwaNCjsbYdbNMZje9/XejIe77zzTsyZMwejR4/Grbfeitdeew3vvPMOysvLAfD7oy9eH1t4PB7Y7Xa89tprmDZtGq6++mr86U9/QmlpKQ4fPoyTJ0/6jcdnn302pHZVKhXefvttHDlyBElJSdDr9SgtLcW1117r/Xt99913+7Xta9GiRdi9ezc+/PBDKBQK/OhHP4IQIuzvv6t4fQzPeNy/fz+uv/56LF26FLNnzw75dby/9sfrI/UVylh3INzuvfde/Pvf/8aWLVuQlZXlfTwjIwMOhwMWi8Xv15vq6mpkZGR49wlcoVBaDcx3n8AVzaqrq2E0GqHT6XDddddh0qRJ3ucGDRrk/SWwuroamZmZfq9rb4W7YNavX+9dxUun0/k9l52dDQC45JJL4Ha7ceedd+KBBx6AQqEIuX1f7b1P6bmO9pGeb6/dnn7G7bVbU1Pj95jL5UJtbW2n7foeO9wiPR4lOTk5AIDRo0ejuroaTz75JG655ZawjsdJkybB5XLhxIkTGDlyJPbs2eN9zmg0htSf7upsTCgUCigUim6Nx940znsq0uMxMzMTgwYNgslk8u5TUFAAIQROnz6Nyy+/3G/cpKenQ6PRhHTuZs+ejfLycpw7dw5KpRJmsxkZGRkYNmwYAOCPf/yj95ddaYaB7/vLyMhAfn4+kpKSMG3aNDz++OPIzMzs9vWmN42bvnh9DEVn72no0KHdHo+d6e547I7eNm7C/fcvXCI9HiXtfV/ryfUxkPR3/9ixY8jNzeX3R14f28jMzIRSqUReXp73sYKCAgAtq/IWFRX5jUcppTaUczdhwgTs2bMHdXV1cDgcSE1NxaRJk7ypnk899RQefPDBoP1KSUlBSkoK8vLyUFBQgOzsbGzfvh2FhYXdvt70pnHTl6+PBw4cwMyZM3HnnXfiscce83uO99e8PlL/1GdmRgohcO+99+Kdd97B5s2bvcEQyYQJE6BSqfx+RZB++SssLAQAFBYWYt++fX7/023YsAFGoxGXXHKJd5/AXyI2bNjgbSMxMRHDhw/3/tPpdMjJyUFGRobf6+rr6/HZZ595XxeKIUOGeNvt6Bc0j8cDp9MJj8cTctuBCgsLsWXLFu/FGWh5nyNHjsSAAQO8+3T0WbTXbk8/4/batVgs2LVrl/exzZs3w+PxeP94hfKewiVa4zEY6dduILzjcc+ePZDL5d7p+r7tBk7hb68/3dXZmFCr1ZgwYYLfPh6PB5s2bep03PSmcd5d0RqPU6ZMQWVlJRobG737HDlyBHK5HFlZWdDpdH7jJjExscvnLiUlBWazGZs3b0ZNTQ2uu+46AC1fTKV2hwwZ0u5nIV0XpTHZ3fPbm8ZNX7w+hqKz9xSO8die7o7H7uht4yaSf/+6I1rjMRjf72vhHI9SEEm6Qef3R14fA02ZMgUul8s7exZo+XsNtIwXpVLpNx6lYGRXPmOTyYTU1FQcPXoUO3fuxPXXXw8ASEtL82u7PcH+Xnf1PPS2cdNXr49fffUVioqKcPvtt+OZZ55pcxzeX/P6SP1UzJbOCbOf//znwmQyiY8++kicOXPG+6+pqcm7z9133y0GDx4sNm/eLHbu3CkKCwtFYWGh93mXyyVGjRolZs+eLfbs2SPef/99kZqaKhYvXuzd5/jx40Kv14tFixaJgwcPipdfflkoFArx/vvvd9i/lStXCrPZLN59912xd+9ecf3114ucnBzR3Nzs3efrr78Wu3fvFsuWLRMGg0Hs3r1b7N69WzQ0NLTb7l//+lfx5ptvigMHDojy8nLx5ptvioEDB4pbb73Vu4/dbve2lZmZKR588EGxe/ducfTo0XbbtVgsIj09Xfzwhz8U+/fvF+vWrRN6vV787ne/8+6zdetWoVQqxa9+9Stx8OBBsXTpUqFSqcS+ffu8+5SUlIgZM2aE/TN+++2326zSdc0114jLLrtMfPbZZ6KsrEyMGDFC3HLLLV16T+ESrfG4evVq8c9//lMcOXJEHDlyRPzxj38UiYmJYsmSJR32r7Px+Omnn4oXX3xR7NmzR5SXl4u//vWvIjU1VfzoRz/qsN1Q+tPQ0OAdjwDECy+8IHbv3i2+/vrrdtsNZUysW7dOaDQasXbtWnHgwAFx5513CrPZ7Ley3COPPCJ++MMferfjfZyHS7TGY0NDg8jKyhI333yz+Oqrr8THH38sRowYIX7605922L9Qzt2rr74qtm3bJo4dOyb+8pe/iKSkJLFw4cIO233vvffEq6++Kvbt2ycqKirEv//9b1FQUCCmTJni3ac75yHex01/uD4KIcTRo0fF7t27xV133SXy8vK81xVpRcfuvqdQxuOZM2fE7t27xR/+8AcBQGzZskXs3r27w5XkQxmPQgjv+5gwYYL4wQ9+IHbv3i2++uqrdtuN93Hz2WefiZEjR4rTp097HwvH9SZcojUeQ/m+Fkxn4/HYsWPiqaeeEjt37hQVFRXi3XffFcOGDRNXXXVVh+3y++NF/fH66Ha7xfjx48VVV10lvvjiC7Fz504xadIkMWvWrA77F8q5+/vf/y5KS0tFeXm5+Mc//iGGDBkibrzxxg7b3b59uygpKRG7d+8WJ06cEJs2bRKTJ08Wubm5wmazCSG6dx7ifdz0h+vjvn37RGpqqrjtttv82qipqfHuw/trXh+pf+ozwUgAQf+tWbPGu09zc7OYN2+eGDBggNDr9eKGG24QZ86c8WvnxIkT4tprrxU6nU6kpKSIBx54QDidTr99SktLxbhx44RarRbDhg3zO0Z7PB6PePzxx0V6errQaDRi5syZ4vDhw3773H777UHfQ2lpabvtrlu3TowfP14YDAaRkJAgLrnkEvHss8/6XYQrKiqCtjt9+vQO+/zll1+KqVOnCo1GIwYNGiRWrlzZZp+///3vIi8vT6jVanHppZeK9957z+/5pUuXiiFDhvg9Fo7PeM2aNSIwln7+/Hlxyy23CIPBIIxGo7jjjjva/KEJ5T2FQ7TG46pVq8Sll14q9Hq9MBqN4rLLLhOvvPKKcLvdHfavs/G4a9cuMWnSJGEymYRWqxUFBQXi2Wef9X4hbE8o/SktLQ362dx+++0dth3K/3clJSVi8ODBQq1Wi4kTJ4rt27f7PX/77be3GffxPM7DJZrXx4MHD4ri4mKh0+lEVlaWWLhwod+X1vZ0du4efvhhkZ6eLlQqlRgxYoT49a9/LTweT4dtbt68WRQWFnrH8YgRI8TDDz8sLly44Ldfd85DPI+b/nJ9nD59etB2KioqevyeOhuPS5cu7fQ9BAp1PAZrN3CcBIrncSNd833PS7iuN+EQrfEYyve19nQ0Hk+ePCmuuuoqkZSUJDQajRg+fLhYtGiRqKur67BNfn+8qL9eH7/55htx4403CoPBINLT08WPf/zjDn9QkXR27n7zm9+IrKwsoVKpxODBg8Vjjz3mDYK2Z+/evaKoqMg7jocOHSruvvtuvyCdEN07D/E8bvrD9bG9v5eB/3/z/voiXh+pv5AJEQdVgYmIiIiIiIiIiKjP6zM1I4mIiIiIiIiIiCi+MRhJREREREREREREUcFgJBEREREREREREUUFg5FEREREREREREQUFQxGEhERERERERERUVQwGElERERERERERERRwWAkERERERERERERRQWDkURERERERERERBQVDEYSERERERERERFRVDAYSURERERERERERFHBYCQRERERERERERFFxf8H041xz9FWSsAAAAAASUVORK5CYII=", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# [visualise result]\n", + "\n", + "from sktime.utils.plotting import plot_series\n", + "\n", + "plot_series(\n", + " train['y'], \n", + " test['y'], \n", + " y_pred['y'], \n", + " labels=['train', 'test', 'predict'],\n", + " pred_interval=pd.concat([y_pred_interval['y']],keys=['y'], axis=1))" + ] + }, + { + "cell_type": "code", + "execution_count": 122, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
RecursiveTabularRegressionForecaster(estimator=KNeighborsRegressor(n_neighbors=3),\n",
+       "                                     window_length=15)
Please rerun this cell to show the HTML repr or trust the notebook.
" + ], + "text/plain": [ + "RecursiveTabularRegressionForecaster(estimator=KNeighborsRegressor(n_neighbors=3),\n", + " window_length=15)" + ] + }, + "execution_count": 122, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from sklearn.neighbors import KNeighborsRegressor\n", + "\n", + "from sktime.forecasting.compose import make_reduction\n", + "\n", + "regressor = KNeighborsRegressor(n_neighbors=3)\n", + "forecaster = make_reduction(regressor, window_length=15, strategy=\"recursive\")\n", + "\n", + "forecaster.fit(train['y'])" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "datetime\n", + "2000-01-31 41.0\n", + "2000-02-29 41.0\n", + "2000-03-31 45.0\n", + "2000-04-30 47.0\n", + "2000-05-31 47.0\n", + " ... \n", + "2020-08-31 57.0\n", + "2020-09-30 62.0\n", + "2020-10-31 62.0\n", + "2020-11-30 62.0\n", + "2020-12-31 67.0\n", + "Freq: M, Name: y, Length: 252, dtype: float64" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "train['y']" + ] + }, + { + "cell_type": "code", + "execution_count": 121, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(
, )" + ] + }, + "execution_count": 121, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "y_pred = forecaster.predict(fh)\n", + "# y_pred_interval = forecaster.(fh=fh, coverage=0.9)\n", + "plot_series(train['y'], test['y'], y_pred['y'], labels=[\"y_train\", \"y_test\", \"y_pred\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 123, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(
, )" + ] + }, + "execution_count": 123, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "y_pred = forecaster.predict(fh)\n", + "# y_pred_interval = forecaster.(fh=fh, coverage=0.9)\n", + "plot_series(train['y'], test['y'], y_pred, labels=[\"y_train\", \"y_test\", \"y_pred\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/zq/.local/lib/python3.10/site-packages/statsmodels/tsa/statespace/sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.\n", + " warn('Non-stationary starting autoregressive parameters'\n", + "/home/zq/.local/lib/python3.10/site-packages/statsmodels/tsa/statespace/sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.\n", + " warn('Non-invertible starting MA parameters found.'\n", + "/home/zq/.local/lib/python3.10/site-packages/statsmodels/tsa/statespace/sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.\n", + " warn('Non-stationary starting autoregressive parameters'\n", + "/home/zq/.local/lib/python3.10/site-packages/statsmodels/tsa/statespace/sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.\n", + " warn('Non-invertible starting MA parameters found.'\n", + "/home/zq/.local/lib/python3.10/site-packages/statsmodels/tsa/statespace/sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.\n", + " warn('Non-invertible starting MA parameters found.'\n", + "/home/zq/.local/lib/python3.10/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n", + " warnings.warn(\"Maximum Likelihood optimization failed to \"\n", + "/home/zq/.local/lib/python3.10/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n", + " warnings.warn(\"Maximum Likelihood optimization failed to \"\n", + "/home/zq/.local/lib/python3.10/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n", + " warnings.warn(\"Maximum Likelihood optimization failed to \"\n", + "/home/zq/.local/lib/python3.10/site-packages/statsmodels/tsa/statespace/sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.\n", + " warn('Non-stationary starting autoregressive parameters'\n", + "/home/zq/.local/lib/python3.10/site-packages/statsmodels/tsa/statespace/sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.\n", + " warn('Non-invertible starting MA parameters found.'\n", + "/home/zq/.local/lib/python3.10/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n", + " warnings.warn(\"Maximum Likelihood optimization failed to \"\n", + "/home/zq/.local/lib/python3.10/site-packages/statsmodels/tsa/statespace/sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.\n", + " warn('Non-invertible starting MA parameters found.'\n", + "/home/zq/.local/lib/python3.10/site-packages/statsmodels/tsa/statespace/sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.\n", + " warn('Non-stationary starting autoregressive parameters'\n", + "/home/zq/.local/lib/python3.10/site-packages/statsmodels/tsa/statespace/sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.\n", + " warn('Non-invertible starting MA parameters found.'\n", + "/home/zq/.local/lib/python3.10/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n", + " warnings.warn(\"Maximum Likelihood optimization failed to \"\n", + "/home/zq/.local/lib/python3.10/site-packages/statsmodels/tsa/statespace/sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.\n", + " warn('Non-stationary starting autoregressive parameters'\n", + "/home/zq/.local/lib/python3.10/site-packages/statsmodels/tsa/statespace/sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.\n", + " warn('Non-invertible starting MA parameters found.'\n", + "/home/zq/.local/lib/python3.10/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n", + " warnings.warn(\"Maximum Likelihood optimization failed to \"\n", + "/home/zq/.local/lib/python3.10/site-packages/statsmodels/tsa/statespace/sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.\n", + " warn('Non-stationary starting autoregressive parameters'\n", + "/home/zq/.local/lib/python3.10/site-packages/statsmodels/tsa/statespace/sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.\n", + " warn('Non-invertible starting MA parameters found.'\n", + "/home/zq/.local/lib/python3.10/site-packages/statsmodels/tsa/statespace/sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.\n", + " warn('Non-stationary starting autoregressive parameters'\n", + "/home/zq/.local/lib/python3.10/site-packages/statsmodels/tsa/statespace/sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.\n", + " warn('Non-invertible starting MA parameters found.'\n", + "/home/zq/.local/lib/python3.10/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n", + " warnings.warn(\"Maximum Likelihood optimization failed to \"\n", + "/home/zq/.local/lib/python3.10/site-packages/statsmodels/tsa/statespace/sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.\n", + " warn('Non-stationary starting autoregressive parameters'\n", + "/home/zq/.local/lib/python3.10/site-packages/statsmodels/tsa/statespace/sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.\n", + " warn('Non-invertible starting MA parameters found.'\n", + "/home/zq/.local/lib/python3.10/site-packages/statsmodels/tsa/statespace/sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.\n", + " warn('Non-stationary starting autoregressive parameters'\n", + "/home/zq/.local/lib/python3.10/site-packages/statsmodels/tsa/statespace/sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.\n", + " warn('Non-invertible starting MA parameters found.'\n", + "/home/zq/.local/lib/python3.10/site-packages/statsmodels/tsa/statespace/sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.\n", + " warn('Non-stationary starting autoregressive parameters'\n", + "/home/zq/.local/lib/python3.10/site-packages/statsmodels/tsa/statespace/sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.\n", + " warn('Non-invertible starting MA parameters found.'\n" + ] + } + ], + "source": [ + "from sktime.forecasting.arima import AutoARIMA\n", + "\n", + "forecaster = AutoARIMA()\n", + "\n", + "forecaster.fit(train)\n", + "\n", + "pred = forecaster.predict(fh=fh)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(
, )" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from sktime.utils.plotting import plot_series\n", + "\n", + "plot_series(\n", + " train['y'], \n", + " test['y'], \n", + " pred['y'], \n", + " labels=['train', 'test', 'predict'],\n", + " # pred_interval=pd.concat([y_pred_interval['y']],keys=['y'], axis=1)\n", + " )" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "demand-forecasting", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.10" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/Preprocessor.ipynb b/notebooks/Preprocessor.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..d39c22f8a08709a08c853934f529aae5b2144428 --- /dev/null +++ b/notebooks/Preprocessor.ipynb @@ -0,0 +1,131 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "data_path = '../data/demand_forecasting_demo_data.csv'" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "data = pd.read_csv(data_path)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "data = data.set_index('datetime')" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "data.index = pd.to_datetime(data.index, format='mixed')" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "data.reset_index().sort_values(by=['sku', 'datetime']).to_csv(data_path,index=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "test = pd.DataFrame([4, 3, 1, 2])" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "x = [\n", + " {'RMSE':1},\n", + " {'RMSE':3},\n", + " {'RMSE':2}\n", + " ]" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "x.sort(key=lambda x:x['RMSE'], reverse=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'RMSE': 3}, {'RMSE': 2}, {'RMSE': 1}]" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "x" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "base", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.10" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/test.ipynb b/notebooks/test.ipynb index 05c13a522a30a5cf090b5fb8ad86f817ed93c1e6..dfe2ed8f2c07fb1b42d00c73780ff2da63c2158b 100644 --- a/notebooks/test.ipynb +++ b/notebooks/test.ipynb @@ -39,16 +39,852 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 74, "metadata": {}, "outputs": [], "source": [ - "ts = pd.read_csv('../data/demand_forecasting_demo_models_10.csv')" + "ts = pd.read_csv('../data/raw/energy_consmption/AEP_hourly.csv')" ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 107, + "metadata": {}, + "outputs": [], + "source": [ + "ts.to_csv('../data/energy_consumption.csv', index=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 111, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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datetimeysku
2019-01-202019-01-203302854.0engy_use
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" + ], + "text/plain": [ + " datetime y sku\n", + "2019-01-20 2019-01-20 3302854.0 engy_use\n", + "2020-01-05 2020-01-05 3235220.0 engy_use\n", + "2020-02-16 2020-02-16 3382229.0 engy_use\n", + "2023-01-01 2023-01-01 3442532.0 engy_use" + ] + }, + "execution_count": 111, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ts[ts.y > 3.2e+06]" + ] + }, + { + "cell_type": "code", + "execution_count": 114, + "metadata": {}, + "outputs": [], + "source": [ + "ts.loc[pd.to_datetime('2023-01-01'), 'y'] = 2842532.0" + ] + }, + { + "cell_type": "code", + "execution_count": 115, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 115, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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"ts.to_csv('../data/demand_forecasting_demo_models_10.csv')" + "ts.to_csv('../data/demand_forecasting_demo_data_new.csv', index=False)" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'itemf' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m/Users/qiaozhang/Desktop/sentient-dev/snr_demand-forecasting/notebooks/test.ipynb Cell 7\u001b[0m line \u001b[0;36m1\n\u001b[0;32m----> 1\u001b[0m itemf\n", + "\u001b[0;31mNameError\u001b[0m: name 'itemf' is not defined" + ] + } + ], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ + "n_predict is 0, force run_test to be true\n", + "characteristic not provided, running profiling\n", + "apikey still available, logged in\n", + "Start profiling, note, predictability been disabled\n", + "Change point detection\n", + "predictability temporarily using order_quantity predictability\n", + "apikey still available, logged in\n", "Start profiling, note, predictability been disabled\n", "Change point detection\n", + "profiling completed, data characteristic is fuzzy\n", "callindg model: prophet_plus\n", - "has_idsc_model\n" + "has_idsc_model\n", + "apikey still available, logged in\n", + "callindg model: ceif_plus\n", + "has_idsc_model\n", + "IDSC ceif\n", + "apikey still available, logged in\n", + "IDSC ceif completed\n" ] } ], "source": [ "# Step 1 - evaluate RMSE\n", - "# res = df.forecast(ts, 10, model='all', run_test=False, characteristic='fuzzy')\n", + "res = df.forecast(ts, 0, model='all', run_test=True)\n", "\n", "# Step 2 - forecast\n", - "res = df.forecast(ts, 26, model='prophet_plus', characteristic='fuzzy')" + "# res = df.forecast(ts, 26, model='prophet_plus', characteristic='fuzzy')" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "DatetimeIndex(['2022-05-01', '2022-05-08', '2022-05-15', '2022-05-22',\n", + " '2022-05-29', '2022-06-05', '2022-06-12', '2022-06-19',\n", + " '2022-06-26', '2022-07-03', '2022-07-10', '2022-07-17',\n", + " '2022-07-24', '2022-07-31', '2022-08-07', '2022-08-14',\n", + " '2022-08-21', '2022-08-28', '2022-09-04', '2022-09-11',\n", + " '2022-09-18', '2022-09-25', '2022-10-02', '2022-10-09',\n", + " '2022-10-16', '2022-10-23', '2022-10-30', '2022-11-06',\n", + " '2022-11-13', '2022-11-20', '2022-11-27', '2022-12-04',\n", + " '2022-12-11', '2022-12-18', '2022-12-25', '2023-01-01',\n", + " '2023-01-08', '2023-01-15', '2023-01-22', '2023-01-29',\n", + " '2023-02-05', '2023-02-12', '2023-02-19', '2023-02-26',\n", + " '2023-03-05', '2023-03-12', '2023-03-19', '2023-03-26',\n", + " '2023-04-02', 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0000000000000000000000000000000000000000..581f6920a6189445b3d04f43d1c52707e524e48c --- /dev/null +++ b/src/active_models.py @@ -0,0 +1,27 @@ +''' +'ceif_plus' : 2023 Sep. currently the model is under review, so not recommended to use this mode - by idsc +''' + +active_models = { + 'intermittent': + [ + 'prophet_i', + 'ceif' + ], + 'continuous': + [ + 'fft_i', + # 'holt_winters', + # 'auto_arima', + 'prophet', # Original prophet + 'prophet_i', + ] +} + +idsc_models = [ + 'prophet_i', + 'ceif', + 'fft_i', + 'holt_winters_i', + 'auto_arima_i' +] diff --git a/src/analyser/__init__.py b/src/analyser/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..f0e5b35dd735052f060e24afa7643d47134c059e --- /dev/null +++ b/src/analyser/__init__.py @@ -0,0 +1 @@ +from .analyser import Analyser \ No newline at end of file diff --git a/src/analyser/__pycache__/__init__.cpython-310.pyc b/src/analyser/__pycache__/__init__.cpython-310.pyc new file mode 100644 index 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b/src/analyser/analyser.py @@ -0,0 +1,78 @@ +import pandas as pd +from statsmodels.tsa.tsatools import freq_to_period +from statsmodels.tsa.stattools import acf, pacf +from ..idsc import IDSC + +import logging + +from .visualiser import Visualiser + + +class Analyser(): + def __init__(self) -> None: + logging.debug('Analyser init') + self.idsc = IDSC() + self.viz = Visualiser() + + def fit(self, data): + self.data = data + + def profiling(self): + # --------------------------------- # + # Profiling data with IDSC profiler # + # --------------------------------- # + self.quantity_change_point = [] + self.quantity_predictability = [] + self.characteristic = None + + self.profile = self.idsc.profiling( + self.data[['y']].rename(columns={'y': 'target'}).dropna().to_json()) + # Parse profile result + self.intermittent_change_points_idx = self.profile['change_point_res']['inter_order_cpi'] + self.quantity_change_points_idx = self.profile['change_point_res']['order_quantity_cpi'] + + # Set the change points to datetime index value + self.intermittent_change_points = self.data.iloc[self.intermittent_change_points_idx].index + self.quantity_change_points = self.data.iloc[self.quantity_change_points_idx].index + + self.characteristic = self.profile['classification_res']['time_series_class']['overall_characteristic'] + self.intermittent_predictability = [ + round(r['predictability'], 3) + for r in + self.profile['predictability_res']['predictability_result']['inter_order'] + ] + self.quantity_predictability = [ + round(r['predictability'], 3) + for r in + self.profile['predictability_res']['predictability_result']['order_quantity'] + ] + # ----- End of [Profiling data with IDSC profiler] ----- # + + def analyse(self, data: pd.DataFrame): + ''' + data: pd.DataFrame, required + Data must contains datetime index, and the index must be proper datetime index with freq value + data should complete, no missing value and contain at least "y" columns as the time-series data itself + ''' + logging.debug('Analysing ...') + self.data = data + self.freq: str = pd.infer_freq(data.index) + self.period = freq_to_period(self.freq) + + self.acf = pd.DataFrame( + [acf(data[col]) for col in data.columns], + index=data.columns).T + + self.pacf = pd.DataFrame( + [pacf(data[col]) for col in data.columns], + index=data.columns).T + + self.viz.fit(data) + + return { + 'freq': self.freq, + 'period': self.period, + 'change_points': self.quantity_change_point, + 'predictability': self.quantity_predictability, + 'characteristic': self.characteristic + } diff --git a/src/analyser/visualiser.py b/src/analyser/visualiser.py new file mode 100644 index 0000000000000000000000000000000000000000..eb70144a3f8df836a4b4fe7345f223d610729fbe --- /dev/null +++ b/src/analyser/visualiser.py @@ -0,0 +1,94 @@ +import logging +import math + +import matplotlib.pyplot as plt +from statsmodels.graphics.tsaplots import plot_acf, plot_pacf +import numpy as np +import pandas as pd +import seaborn as sns +from sklearn.preprocessing import MinMaxScaler + + +class Visualiser(): + def __init__(self) -> None: + logging.debug('Init Visualiser') + self.scaler = MinMaxScaler() + + def fit(self, data: pd.DataFrame): + self.data = data + self.norm_data = pd.DataFrame( + self.scaler.fit_transform(data.values), + columns=data.columns, + index=data.index) + + # ------------ # + # ACF and PACF # + # ------------ # + + def plot_auto_correlation(self, func): + n_rows = len(self.data.columns) + fig, axs = plt.subplots( + n_rows, + 1, + figsize=(8, 2*n_rows), + sharex=True, + sharey=True) + for i, col in enumerate(self.data.columns): + func(self.data[col], ax=axs[i], zero=False) + axs[i].set_title(f'Autocorrelation - {col}') + fig.tight_layout() + return fig + + def acf(self): + return self.plot_auto_correlation(plot_acf) + + def pacf(self): + return self.plot_auto_correlation(plot_pacf) + + # ----- Enf of [ACF and PACF] ----- # + + def corr(self): + # Generate a mask for the upper triangle + corr = self.data.corr(numeric_only=True) + mask = np.triu(np.ones_like(corr, dtype=bool)) + fig, ax = plt.subplots(figsize=(8, 8)) + + sns.heatmap( + corr, + mask=mask, + square=True, + annot=True, + cmap='coolwarm', + linewidths=.5, + cbar_kws={"shrink": .5}, + ax=ax) + + return fig + + def distributions(self, norm=True): + data: pd.DataFrame = self.norm_data if norm else self.data + + plot_col = min(math.ceil(math.sqrt(data.shape[1])), 5) + plot_row = math.ceil(data.shape[1] / plot_col) + + fig, axs = plt.subplots( + plot_row, + plot_col, + figsize=(4*plot_row, 1.5*plot_col), + sharex=norm, + sharey=norm) + + for idx, col in enumerate(data.columns): + + axs_x = math.floor(idx/plot_col) + axs_y = idx - axs_x * plot_col + ax = axs[axs_x, axs_y] + + # sns.distplot(self.ts_df[col], ax=axs[axs_x, axs_y]) + sns.histplot(data[col], ax=ax, kde=True) + ax.set(xlabel=None) + ax.set_title(col) + + fig.suptitle(f'Distributions - Normalised ({str(norm)})') + + return fig diff --git a/src/analytics/analytic_tools/__init__.py b/src/analytics/analytic_tools/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/src/analytics/analytic_tools/infer_freq.py b/src/analytics/analytic_tools/infer_freq.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/src/analytics/ts_analytics.py b/src/analytics/ts_analytics.py new file mode 100644 index 0000000000000000000000000000000000000000..8bc19c800624a99cc85f871d8484094911284eb8 --- /dev/null +++ b/src/analytics/ts_analytics.py @@ -0,0 +1,186 @@ +import pandas as pd +import numpy as np +import math + +import matplotlib.pyplot as plt +import seaborn as sns + +from statsmodels.graphics.tsaplots import plot_pacf +from statsmodels.tsa.seasonal import MSTL, seasonal_decompose +from statsmodels.tsa.tsatools import freq_to_period + +import statsmodels.api as sm + +from scipy import stats +from sklearn.preprocessing import MinMaxScaler + + +class Ts_Analytics(): + def __init__(self): + self.log_transformed = False + self.scaler = MinMaxScaler() + pass + + def analyse( + self, + ts_df: pd.DataFrame, + auto_correlations={}): + ''' + ts_df: timeseries dataframe, will assume the datetime column is the index and time encoded + auto_correlations: dictionary to input customised auto correlations + ''' + self.ts_df = ts_df.copy() + + self.ts_df['datetime'] = pd.to_datetime(self.ts_df['datetime']) + self.ts_df.set_index('datetime', inplace=True) + + self.ar = auto_correlations + + self.__infer_frequency() + + # Annual maps to 1, quarterly maps to 4, monthly to 12, weekly to 52. + # Using statsmodel's freq_to_period function + self.period = freq_to_period(self.freq) + pass + + def set_ar(self, col, ar): + ''' + Set the auto correlation + ''' + self.ar[col] = ar + + def set_period(self, period): + self.period = period + + def create_target_lag_columns(self): + print('create_target_lag_columns') + + def create_lag_dfs(col, n): + print('create_lag_dfs', col, n) + for i in range(n): + self.ts_df[f'{col}_t-{i+1}'] = self.ts_df[col].shift(-(i+1)) + + for col, n in self.ar.items(): + create_lag_dfs(col, n) + + print('drop all null values') + self.ts_df.ffill(inplace=True) + + def log_transform(self): + self.log_transformed = True + self.ts_df = np.log2(self.ts_df) + + def exp_transform(self): + self.log_transformed = False + self.ts_df = np.exp(self.ts_df) + + def train_multiple_regression(self): + print('train_multiple_regression') + + x_cols = self.ts_df.columns.tolist() + x_cols.remove('y') + + _X = self.ts_df[x_cols] + y = self.ts_df['y'] + + X = sm.add_constant(_X) + + # ----------------------------------------------------------------------- # + # Train an additional model with standardized data, to get the Beta value # + # ----------------------------------------------------------------------- # + std_ts_df = pd.DataFrame(self.scaler.fit_transform( + self.ts_df), columns=self.ts_df.columns) + + std_X = sm.add_constant(std_ts_df[x_cols]) + std_y = std_ts_df['y'] + + self.multiple_regression = sm.OLS(y, X).fit() + + coef = self.multiple_regression.params + + self.multiple_regression_formula = f'{coef[0]} + {" + ".join([f"{c} * {round(n, 3)}" for c, n in zip(x_cols, coef[1:])]) }' + + self.std_multiple_regression = sm.OLS(std_y, std_X).fit() + beta = self.std_multiple_regression.params + + self.multiple_regression_beta = pd.DataFrame( + np.array(beta[1:]) ** 2, index=x_cols, columns=['Beta (influence on "y")']) + self.multiple_regression_beta['Beta (influence on "y")'] = self.multiple_regression_beta['Beta (influence on "y")'].round( + 3) + + return self.multiple_regression.summary() + + # ===== # + # Plots # + # ===== # + + def plot_correlation(self): + # Generate a mask for the upper triangle + corr = self.ts_df.corr(numeric_only=True) + mask = np.triu(np.ones_like(corr, dtype=bool)) + fig, ax = plt.subplots(figsize=(8, 8)) + + sns.heatmap( + corr, + mask=mask, + square=True, + annot=True, + cmap='coolwarm', + linewidths=.5, + cbar_kws={"shrink": .5}, + ax=ax) + + return fig + + def plot_target_pacf(self): + fig, ax = plt.subplots(figsize=(12, 4)) + plot_pacf(self.ts_df['y'], ax=ax) + fig.tight_layout() + return fig + + def plot_distributions(self): + plot_col = min(math.ceil(math.sqrt(self.ts_df.shape[1])), 5) + plot_row = math.ceil(self.ts_df.shape[1] / plot_col) + + fig, axs = plt.subplots(plot_row, plot_col) + + for idx, col in enumerate(self.ts_df.columns): + + axs_x = math.floor(idx/plot_col) + axs_y = idx - axs_x * plot_col + + # sns.distplot(self.ts_df[col], ax=axs[axs_x, axs_y]) + sns.histplot(self.ts_df[col], ax=axs[axs_x, axs_y], kde=True) + + fig.tight_layout() + + return fig + + def plot_target_seasonality(self): + + if isinstance(self.period, list): + seasonal = MSTL( + self.ts_df['y'], periods=self.period).fit() + else: + seasonal = seasonal_decompose(self.ts_df['y'], period=self.period) + return seasonal + + def plot_beta(self): + fig, ax = plt.subplots(figsize=(6, 4)) + + beta_plot = sns.barplot( + self.multiple_regression_beta['Beta (influence on "y")'], gap=2, ax=ax) + beta_plot.set_xticklabels(beta_plot.get_xticklabels(), rotation=45) + ax.bar_label(ax.containers[-1], fmt='%.2f', label_type='center') + return fig + + def __infer_frequency(self): + # Attempt to get the frequency from the provided datetime column + freq = pd.infer_freq(self.ts_df.index) + if freq is not None: + self.freq = freq + + # Always make sure the frequency is not None + if self.freq is None: + raise ValueError( + 'Unable inference freq from datetime column, please make timeseries interval consistent or provide customized frequency.') diff --git a/src/forecast/__pycache__/Prophet.cpython-310.pyc b/src/forecast/__pycache__/Prophet.cpython-310.pyc index 9b5949c14b4c58a4f60fdca9ced4d97297742b4d..edb977c0347dbbc11507bde2150491f638864aa8 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0000000000000000000000000000000000000000..f8c3f47f500082aebd8cab404028a30954e94087 --- /dev/null +++ b/src/forecast/multivariate.py @@ -0,0 +1,83 @@ +import pandas as pd +from xgboost import XGBRegressor +from sktime.forecasting.compose import make_reduction +from statsmodels.tsa.tsatools import freq_to_period +from sklearn.model_selection import train_test_split +from sktime.forecasting.base import ForecastingHorizon +from sktime.performance_metrics.forecasting import mean_absolute_percentage_error + + +class MultivariateForecasting(): + def __init__( + self, + n_predict: int, + data: pd.DataFrame, + window_length: 10 + ): + ''' + data: data must contains datetime column, and y column as target. Everything else will be considered as exogenous data + n_predict: how may future values are expected to produce + + window_length default to 10 following sktime's default setting + + test_size : test size is same size as n predict + ''' + self.data = data.copy() + self.n_predict = n_predict + + # Set datetime as the index + self.data.set_index('datetime', inplace=True) + self.data.index = pd.to_datetime(self.data.index) + + self.exog = self.data.drop(columns=['y']).reset_index(drop=True) + + self.window_length = window_length + + # Keep n_predict rows of latest exog data for prediction use + self.exog_train = self.exog[:- self.n_predict] + self.exog_pred = self.exog[-self.n_predict:] + + # If we need to use n_predict rows of exog data for prediction, we are going to remove n_predict rows of y historical data + # This will make sure the shape of 2 data consistent + self.y = self.data['y'][self.n_predict:] + + # test size is same size as the forecast window_length + # self.X_train = self.X[:-self.window_length] + # self.X_test = self.X[-self.window_length:] + + # self.y_train = self.y[:-self.window_length] + # self.y_test = self.y[-self.window_length:] + + # self.fh_test = ForecastingHorizon( + # self.y_test.index, + # is_relative=False) + + # self.fh = ForecastingHorizon( + # self.exog.index, + # is_relative=False) + + self.models = {} + + def train_xgboost(self): + regressor = XGBRegressor( + objective='reg:squarederror', + random_state=42) + + forecaster = make_reduction( + regressor, strategy='recursive', + window_length=self.window_length) + + forecaster.fit(y=self.y_train, X=self.X_train) + + y_pred = forecaster.predict(fh=self.fh_test, X=self.X_test) + + self.models['xgboost'] = {} + self.models['xgboost']['mape'] = mean_absolute_percentage_error( + self.y_test, y_pred, symmetric=False) + + self.models['xgboost']['test'] = y_pred + + forecaster.fit(y=self.y, X=self.X) + + self.models['xgboost']['forecast'] = forecaster.predict( + fh=self.fh, X=self.exog) diff --git a/src/forecaster/__init__.py b/src/forecaster/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..16f8c53cbeb73de02baabcf469dcfa2dcabc830d --- /dev/null +++ b/src/forecaster/__init__.py @@ -0,0 +1 @@ +from .forecaster import Forecaster diff --git a/src/forecaster/__pycache__/__init__.cpython-310.pyc b/src/forecaster/__pycache__/__init__.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..338aebb18be563dc4fd5b17a1f369dcce254f878 Binary files /dev/null and b/src/forecaster/__pycache__/__init__.cpython-310.pyc differ diff --git a/src/forecaster/__pycache__/__init__.cpython-39.pyc b/src/forecaster/__pycache__/__init__.cpython-39.pyc new file mode 100644 index 0000000000000000000000000000000000000000..ea17387f71a9ade842e21389c1ac1ad3022f9df6 Binary files /dev/null and b/src/forecaster/__pycache__/__init__.cpython-39.pyc differ diff --git a/src/forecaster/__pycache__/forecaster.cpython-310.pyc b/src/forecaster/__pycache__/forecaster.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..8663a57f34ae52c64a7193cea77391eda25b0992 Binary files /dev/null and b/src/forecaster/__pycache__/forecaster.cpython-310.pyc differ diff --git a/src/forecaster/__pycache__/forecaster.cpython-39.pyc b/src/forecaster/__pycache__/forecaster.cpython-39.pyc new file mode 100644 index 0000000000000000000000000000000000000000..8d292c6b5f8122425fef71811c7c8f93e8f143c9 Binary files /dev/null and b/src/forecaster/__pycache__/forecaster.cpython-39.pyc differ diff --git a/src/forecaster/forecaster.py b/src/forecaster/forecaster.py new file mode 100644 index 0000000000000000000000000000000000000000..3697bfb349b153f229e3bbbc61729844a08a48bd --- /dev/null +++ b/src/forecaster/forecaster.py @@ -0,0 +1,286 @@ + +import pandas as pd +from statsmodels.tsa.tsatools import freq_to_period +from sktime.forecasting.base import ForecastingHorizon +from sktime.forecasting.model_selection import SlidingWindowSplitter, SingleWindowSplitter +from sktime.forecasting.model_selection import temporal_train_test_split + +from typing import List +import logging + +from .utils import split_x_y, k_folds +from .models import AllModels + + +class Forecaster(): + def __init__( + self + ) -> None: + logging.debug('Forecaster init') + + def fit( + self, + data: pd.DataFrame, + exog: pd.DataFrame = None, + n_predict: int = 1, + window_length: int = None, + target_col: str = None + ) -> None: + ''' + data: pandas DataFrame, required + Data must contains datetime index and y column. Any additional column will be considered + as exogenous data and been used for multi variate forecasting + + window_length: int, optional + if not given, window_length will be inferred from the seasonality period, at most 20, at least 4 + recommend to use the amount of auto correlation(AR) as window length + + exog: pandas DataFrame, optionsal + Exogenous data, must contains datetime columns, must NOT contain y column, the datetime index must + covers full range of training and forecasting data length == (training + n_predict) + ''' + + print('[Forecaster - fit] ----- START -----') + self.freq: str = pd.infer_freq(data.index) + self.period = freq_to_period(self.freq) + self.window_length = window_length + self.target_col = target_col + + # Handle forecast window, this wil be used to build models + # Forecast window will be always smaller than 20, or 1 seasonality period + if window_length is None: + self.window_length = min(20, self.period, int(len(data)*0.2)) + # Forecast window will not be smaller than 4 + self.window_length = max(4, self.window_length) + print(f'Inferred window_length: {self.window_length}') + + self.data = data.copy() + + if data.index.freq is None: + self.data.index.freq = self.freq + # self.data.index = pd.to_timedelta(self.data.index, unit="MS") + + # if there is no columns other than 'y', self.X and self.X_future will be None + ( + self.fh, + self.y, + self.X, + self.X_future) = split_x_y( + self.data, + window_length, + n_predict, + self.freq) + + if exog is not None: + print('[Forecaster - fit] - exogenous data provided') + try: + self.exog = exog.loc[self.X.index] + self.exog_future = exog.loc[self.X_future.index] + except Exception: + raise ValueError( + 'Exogenous value not fit, exogenous data must contains a datetime index and covers the entire train and forecast time range.') + + print('[Forecaster - fit] - merge exogenous data with features') + self.X = pd.concat([self.exog, self.X], axis=1) + self.X_future = pd.concat( + [self.exog_future, self.X_future], axis=1) + + # ---------------- # + # Train Test Split # + # ---------------- # + print('[Forecaster - fit] Train test split') + test_size = len(self.fh) + + print('[Forecaster - fit] Test size: ', test_size) + if self.X is not None: + ( + self.y_train, + self.y_test, + self.X_train, + self.X_test + ) = temporal_train_test_split( + self.y, + self.X, + test_size=test_size) + else: + ( + self.y_train, + self.y_test, + ) = temporal_train_test_split( + self.y, + test_size=test_size) + self.fh_test = ForecastingHorizon(self.y_test.index, is_relative=False) + + # ---------------- # + # Cross Validation # + # ---------------- # + + print( + f'[Forecaster - fit] Single window splitter, with window_length {len(self.y) + test_size} and fh {test_size}') + self.cv = SingleWindowSplitter( + window_length=len(self.y) + test_size, + fh=test_size + ) + + # ----- END [Train Test Split] ----- # + + # Originally wanted to create my own k-fold validation, but realised this doesn't work well with sktime API + # self.k_folds = k_folds( + # data, + # self.period, + # window_length, + # n_predict, + # self.freq) + + print('[Forecaster - fit] ----- END -----') + + def forecast( + self, + models: str or List[str] = 'all', + test: bool = False, + ): + # ----------- # + # Init Models # + # ----------- # + logging.debug('Init models') + all_models = AllModels() + + self.models = all_models.init_models(models) + + results = [] + + for m in self.models: + + model_name = m['name'] + + m['model'].fit( + self.y_train if test else self.y, + self.cv, + self.window_length, + self.X_train if test else self.X) + + results.append({ + 'model': model_name, + 'results': m['model'].forecast( + self.fh_test if test else self.fh, + self.X_test if test else self.X_future + ) + }) + + self.results = results + + return results + + def forecast__old( + self, + data: pd.DataFrame, + n_predict: int, + models: str or List[str] = 'all', + window_length: int = None + ) -> None: + ''' + data: pandas DataFrame, required + Data must contains datetime index and y column. Any additional column will be considered + as exogenous data and been used for multi variate forecasting + + window_length: int, optional + if not given, window_length will be inferred from the seasonality period, at most 20, at least 4 + recommend to use the amount of auto correlation(AR) as window length + ''' + self.data = data + logging.debug('Fitting data') + + datetime_index = data.index + + y = data[[self.target_col]].reset_index(drop=True) + + freq: str = pd.infer_freq(datetime_index) + + period = freq_to_period(freq) + + self.window_length = window_length + + # Handle forecast window, this wil be used to build models + # Forecast window will be always smaller than 20, or 1 seasonality period + if window_length is None: + self.window_length = min(20, period, int(len(data)*0.2)) + # Forecast window will not be smaller than 4 + self.window_length = max(4, self.window_length) + + # ----------------------- # + # Handling exogenous data # + # ----------------------- # + exog, exog_columns, exog_train, exog_pred = None, None, None, None + if len(data.columns) > 1: + logging.debug('Exogenous found') + exog = data.drop(columns=self.target_col).reset_index(drop=True) + exog_columns = exog.columns + exog_train = exog.copy() + + # Build lags of the exog data + logging.debug('Building lags of exog data') + for n in range(1, self.window_length+1): + + shifted_columns = {} + for col in exog_columns: + shifted_columns[col] = f'{col}_-{n}' + + shifted = exog.shift(n).rename(columns=shifted_columns) + + exog_train = pd.concat( + [exog_train, shifted], + axis=1) + + logging.debug('Backward fill lags of exog data') + exog_train = exog_train.bfill() + + # Split last n_predict rows from exog_train as exog_pred + exog_pred = exog_train[-n_predict:] + exog_train = exog_train[:-n_predict] + + # For both y and datetime index, need to cut off n_predict value to keep data consistent + logging.debug('Cutting off y and datetime index be n_predict') + y = y[n_predict:] + datetime_index = datetime_index[n_predict:] + + # ----------- # + # Init Models # + # ----------- # + logging.debug('Init models') + all_models = AllModels() + + self.models = all_models.init_models(models) + + # Handle forecasting horizon + fh = ForecastingHorizon( + list(range(1, n_predict+1)), is_relative=True, freq=freq) + # Cutoff is the last datetime value in the given data + # meaning we'll forecast right after this point of time + cutoff = datetime_index[-1] + fh = fh.to_absolute(cutoff=cutoff) + + results = [] + + # ----------------------- # + # Fitting and Forecasting # + # ----------------------- # + + for m in self.models: + m['model'].fit( + y, + datetime_index, + exog=exog_train, + window_length=self.window_length) + + model_name = m['name'] + + results.append({ + 'model': model_name, + 'forecast': m['model'].forecast(fh, exog=exog_pred) + }) + + self.results = results + + # For testing + self.exog_train = exog_train + self.exog_pred = exog_pred diff --git a/src/forecaster/forecaster_old.py b/src/forecaster/forecaster_old.py new file mode 100644 index 0000000000000000000000000000000000000000..1003f1a2420b9d4ffb044f20c4bbfd2e62f6e107 --- /dev/null +++ b/src/forecaster/forecaster_old.py @@ -0,0 +1,212 @@ +from typing import List + +import logging +import pandas as pd +from statsmodels.tsa.tsatools import freq_to_period +from sklearn.metrics import mean_squared_error +from math import sqrt + +from .models import AllModels + +logging.basicConfig(level=logging.DEBUG) + + +class Forecaster(): + + def __init__( + self, + ) -> None: + logging.debug('Forecaster init') + + self.models = {} # Init models dict + + def fit(self, data): + ''' + Fot data into the forecaster + ''' + self.data = data + pass + + def forecast( + self, + data: pd.DataFrame, + models: str or List[str] = 'all', + test: bool = False, + enable_exog: bool = True + ): + ''' + Main function, will perform the entire forecast operation + + data : pd.DataFrame, required + Data for training the model, must contain "datetime", "y" columns, any additional column + will be considered as exogenuous columns and be used for multivariate forecasting + data must be cleaned without any missing value + data's datetime column must be valid datetime strings, the frequency must be able to inference + + models : str or List[str], default='all' + Selected model(s) to use fore forecasting. Default is "all", + which will use all available models registered in models.AllModels + + test : bool, default=False + Decide if the forecasting purpose is for testing or actual prediction + Testing and prediction will not happen at the same time. 20% of the data + will be splitted for testing + + enable_exog : bool, default=True + If disabled, exog data will not be used in the model training, and the data will be considered as univariate data + If enabled, and the data does contains exog data, for multivariate forecasting purpose, the data must be shifted + by n_predict steps. This will cause a few things: + 1. y column will be remapped to exog data that is n_predict unit of time ago + 2. n_predict length of the oldest y will be trimmed off + 3. n_predict length of exog values will be used for the forecasting + ''' + logging.debug('Start forecasting ...') + + self.enable_exog = enable_exog + + # Below properties will be init by prep_data() + self.data: pd.DataFrame = None + self.y = None + self.exog = None + self.freq: str = None + self.period: int = None + + self.y_test = None + + self.n_predict: int = None # init by calculate_n_predict() + + self.kwargs = {} + + self.results = [] # Contains all result value + + # Prepare data, including set the datetime index, slit y and exog columns + self.prep_data(data) + + # Calculate n_predict value based on self.period + self.calculate_n_predict() + + # Init the basic kwargs for models to use + self.init_kwargs() + + # Shift exog value by n_predict unit of time + self.shift_exog() + + # Split test set for testing purpose + if test: + logging.debug('Testing ...') + self.train_test_split() + + # ================================ # + # Train models and make prediction # + # ================================ # + + self.init_models(models) + + for model_name, model in self.models.items(): + result = { + 'model': model_name, + 'result': None, + 'evaluate': None, + 'rmse': None, + } + + fcst = model.forecast() + + # Assign the models result to the result dict + if 'forecast' in fcst.keys(): + result['result'] = fcst['forecast'] + else: + result['result'] = fcst + + if 'evaluate' in fcst.keys(): + result['evaluate'] = fcst['evaluate'] + + if test: + mse = mean_squared_error(self.y_test, result['result']) + result['rmse'] = sqrt(mse) + + self.results.append(result) + + # - END of forecast - # + + def init_models(self, models): + ''' + Initialize models based on the provided parameter. + Get self.models ready for forecasting + ''' + logging.debug('Init models') + + all_models = AllModels(models) + + self.models = all_models.init_models( + self.y, + self.n_predict, + self.exog, + **self.kwargs) + + def prep_data( + self, + data: pd.DataFrame + ) -> None: + logging.debug('Prep data') + + self.data = data.copy() + self.data.set_index('datetime', inplace=True) + self.data.index = pd.to_datetime(self.data.index) + + logging.debug('Inferencing freq and period') + self.freq = pd.infer_freq(self.data.index) + self.period = freq_to_period(self.freq) + + self.y = self.data['y'] + + if len(self.data.columns) > 1 and self.enable_exog: + self.exog = self.data.drop(columns='y') + + def calculate_n_predict(self): + ''' + The n_predict will be the smaller number in 20, self.period value + + By default, try only predict 1 seasonal cycle + ''' + n_predict = min(20, self.period) + + # Set a max prediction size to be 20% of given data size + if n_predict > int(len(self.data)*0.2): + n_predict = int(len(self.data)*0.2) + + # Set a min prediction to be 4 + if n_predict < 4: + n_predict = 4 + + self.n_predict = n_predict + + def init_kwargs(self): + ''' + kwargs will be used for initializing models. + kwargs contains all necessary information about the data + ''' + self.kwargs['period'] = self.period + + def train_test_split(self): + ''' + n_predict length of y value will be splitted out for testing + although, each model will probably have it's own cross validator + ''' + logging.debug('Train test split') + self.y_test = self.y[-self.n_predict:] + self.y = self.y[:-self.n_predict] + + if self.exog is not None: + self.exog = self.exog[:-self.n_predict] + + def shift_exog(self): + + if self.exog is not None: + logging.debug('Shifted exog datetime index by n_predict period') + self.exog.index = self.exog.index.shift( + self.n_predict, freq=self.freq) + + logging.debug( + 'Trimmed y by n_predict, so it is aligned with shifted exog') + self.y = self.y[self.n_predict:] diff --git a/src/forecaster/models/__init__.py b/src/forecaster/models/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..518539b4d77df9b111868ab8f939dbc6e2558e59 --- /dev/null +++ b/src/forecaster/models/__init__.py @@ -0,0 +1,55 @@ +from typing import TypedDict + +import logging + +from .xgbregressor import XGBRegressor +from .multiple_linear_regressor import MultipleLinearRegressor + +from .xgboost import XGBoost +from .prophet import ProphetForecaster + +from typing import TypedDict, List + + +class Model(TypedDict): + name: str + model: any + + +class AllModels(): + def __init__(self) -> None: + + # Any available model must register here + self.all_models = { + 'xgbreg': XGBRegressor, + 'mlr': MultipleLinearRegressor + } + self.all_model_names = self.all_models.keys() + + def init_models( + self, + models + ) -> List[Model]: + logging.debug('Init models') + + if models == 'all': + self.model_names = self.all_model_names + elif isinstance(models, str): + self.model_names = [models] + else: + self.model_names = models + + logging.debug('Check model names') + unknown_models = set(self.model_names) - set(self.all_model_names) + if len(unknown_models) > 0: + raise ValueError( + f'Unknown model : {unknown_models}, please use active models: {self.all_model_names}') + else: + self.models = [ + { + 'name': name, + 'model': self.all_models[name]() + } + for name in self.model_names] + + return self.models diff --git a/src/forecaster/models/__pycache__/__init__.cpython-310.pyc b/src/forecaster/models/__pycache__/__init__.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..0559c106aebc2d4a5e81f1278c77533e1ab772bb Binary files /dev/null and b/src/forecaster/models/__pycache__/__init__.cpython-310.pyc differ diff --git a/src/forecaster/models/__pycache__/base.cpython-310.pyc b/src/forecaster/models/__pycache__/base.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..050dcccb4a867fc77c37d30b1f5661867a5727b5 Binary files /dev/null and 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0000000000000000000000000000000000000000..1b4abf2e4fc843974b0cbfe2bfcae0ab9b6bcb5a Binary files /dev/null and b/src/forecaster/models/__pycache__/xgboost.cpython-310.pyc differ diff --git a/src/forecaster/models/__pycache__/xgbregressor.cpython-310.pyc b/src/forecaster/models/__pycache__/xgbregressor.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..351f2e8cf150b028ccaf3dc85aa8c9c0493f5de9 Binary files /dev/null and b/src/forecaster/models/__pycache__/xgbregressor.cpython-310.pyc differ diff --git a/src/forecaster/models/base.py b/src/forecaster/models/base.py new file mode 100644 index 0000000000000000000000000000000000000000..2756c291aa1d349d57f0dcf9101619c662812711 --- /dev/null +++ b/src/forecaster/models/base.py @@ -0,0 +1,86 @@ +import logging + +from sktime.split import ExpandingWindowSplitter +from sktime.forecasting.compose import make_reduction +from sktime.forecasting.model_evaluation import evaluate +from sktime.forecasting.model_selection import ForecastingRandomizedSearchCV +from sktime.performance_metrics.forecasting import mean_absolute_percentage_error + +import pandas as pd + + +class ModelBase(): + def __init__( + self, + estimator, + param_grid + ) -> None: + + print('Init model ...') + self.estimator = estimator + self.param_grid = param_grid + + def fit( + self, + y: pd.DataFrame, + cv, + window_length, + X: pd.DataFrame = None, + **kwargs + ): + ''' + datetime: pd.DateTimeIndex, required + this is the datetime value of y, or the historical value of forecasting horizon + ''' + + forecaster = make_reduction( + self.estimator, + strategy='recursive', + window_length=window_length) + + self.gscv = ForecastingRandomizedSearchCV( + forecaster, + cv=cv, + param_distributions=self.param_grid, + n_iter=100, + random_state=42, + scoring=mean_absolute_percentage_error, + error_score='raise') + + self.gscv.fit(y=y, X=X) + + def forecast(self, fh, X): + y_pred = self.gscv.predict(fh=fh, X=X) + + return { + "forecast": y_pred, + "best_score": self.gscv.best_score_, + "best_params": self.gscv.best_params_} + + # def forecast( + # self, + # fh, + # exog=None + # ): + # predict_args = { + # 'fh': fh + # } + + # if exog is not None: + # predict_args['X'] = exog + + # return self.forecaster.predict(**predict_args) + + # def evaluate(self): + + # cv_args = { + # 'initial_window': self.n_predict * 2, + # 'step_length': self.n_predict, + # 'fh': list(range(1, self.n_predict+1))} + + # cv = ExpandingWindowSplitter(**cv_args) + + # return evaluate( + # forecaster=self.forecaster, + # y=self.y, + # cv=cv) diff --git a/src/forecaster/models/multiple_linear_regressor.py b/src/forecaster/models/multiple_linear_regressor.py new file mode 100644 index 0000000000000000000000000000000000000000..790cd77b05556b91e6a85efb7dfb2ed925e2f592 --- /dev/null +++ b/src/forecaster/models/multiple_linear_regressor.py @@ -0,0 +1,33 @@ +import logging + +from sklearn.linear_model import Ridge + +from .base import ModelBase + + +class MultipleLinearRegressor(ModelBase): + def __init__( + self, + **kwargs + ) -> None: + + logging.debug('Init MultipleLinearRegressor') + + regressor = Ridge() + + param_grid = { + 'estimator__alpha': [0, 1, 3, 5, 10], + 'estimator__fit_intercept': [True, False], + 'estimator__solver': ['auto', 'svd', 'cholesky', 'lsqr', 'sparse_cg', 'sag', 'saga'], + } + + super().__init__( + regressor, + param_grid, + **kwargs) + + # def forecast(self): + # logging.debug('MultipleLinearRegressor forecast') + + # return {'forecast': self.forecaster.predict(**self.predict_args), + # 'evaluate': self.evaluate()} diff --git a/src/forecaster/models/prophet.py b/src/forecaster/models/prophet.py new file mode 100644 index 0000000000000000000000000000000000000000..ac6a7124f06b45d23a86c4af6c6afcfb2599435d --- /dev/null +++ b/src/forecaster/models/prophet.py @@ -0,0 +1,55 @@ +from sktime.forecasting.fbprophet import Prophet + + +class ProphetForecaster(): + def __init__(self) -> None: + print('[Prophet] Init customized prophet model') + pass + + def fit_predict( + self, + y_train, + y_future, + fh, + fh_test, + sp, + freq, + round_val=False, + X=None, + seasonality_mode=None, + add_country_holidays=None, + yearly_seasonality=False, + weekly_seasonality=False, + daily_seasonality=False + ): + + print('[Prophet] Start forecasting') + + round_decimal = 0 if round else 0.4 + + forecaster = Prophet( + seasonality_mode=seasonality_mode, + n_changepoints=int(len(y_train) / sp), + add_country_holidays=add_country_holidays, + yearly_seasonality=yearly_seasonality, + weekly_seasonality=weekly_seasonality, + daily_seasonality=daily_seasonality + ) + + forecaster.fit(y_train) + + self.predict = forecaster.predict(fh_test) + self.predict_interval = forecaster.predict_interval( + fh_test, coverage=.9) + + forecaster.update(y_future, update_params=False) + + self.forecast = forecaster.predict(fh) + self.forecast_interval = forecaster.predict_interval(fh, coverage=.9) + + self.predict = round(self.predict, round_decimal) + self.predict_interval = round(self.predict_interval, round_decimal) + self.forecast = round(self.forecast, round_decimal) + self.forecast_interval = round(self.forecast_interval, round_decimal) + + print('[Prophet] Fit-predict completed') diff --git a/src/forecaster/models/xgboost.py b/src/forecaster/models/xgboost.py new file mode 100644 index 0000000000000000000000000000000000000000..5efd6c11224a3377639293cf43ac411a81df7e54 --- /dev/null +++ b/src/forecaster/models/xgboost.py @@ -0,0 +1,84 @@ + +import pandas as pd +from xgboost import XGBRegressor +from sktime.forecasting.compose import make_reduction +from sktime.forecasting.model_selection import SlidingWindowSplitter, SingleWindowSplitter +from sktime.forecasting.model_selection import ForecastingRandomizedSearchCV +from sktime.performance_metrics.forecasting import mean_absolute_percentage_error + + +class XGBoost(): + def __init__(self) -> None: + self.estimator = XGBRegressor( + objective='reg:squarederror', + random_state=42) + + # self.cv_params = { + # "max_depth": [3, 5, 6, 10, 15, 20], + # "learning_rate": [0.01, 0.1, 0.2, 0.3], + # "subsample": [0.5, 0.6, 0.7, 0.8, 0.9, 1.0], + # "colsample_bytree": [0.5, 0.6, 0.7, 0.8, 0.9, 1.0], + # "colsample_bylevel": [0.5, 0.6, 0.7, 0.8, 0.9, 1.0], + # "n_estimators": [100, 500, 1000] + # } + + self.cv_params = { + 'n_estimators': [100, 500], + "learning_rate": [0.01, 0.1, 0.2] + } + + self.round_result = True + + def fit_predict( + self, + y: pd.DataFrame, + y_train: pd.DataFrame, + window_length, + fh, + fh_test, + params, + X: pd.DataFrame = None, + X_train=None, + X_test=None, + X_future: pd.DataFrame = None + ): + + print('[XGboost fit predict]') + param_grid = {} + for k, v in params.items(): + param_grid[f"estimator__{k}"] = v + + forecaster = make_reduction( + self.estimator, + strategy='recursive', + window_length=window_length) + + cv = SingleWindowSplitter( + window_length=len(y_train) - len(fh), + fh=len(fh)) + + gscv = ForecastingRandomizedSearchCV( + forecaster, + cv=cv, + param_distributions=param_grid, + n_iter=100, + random_state=42, + scoring=mean_absolute_percentage_error, + update_behaviour='inner_only', + error_score='raise') + + gscv.fit(y=y_train, X=X_train) + + y_pred = gscv.predict(fh=fh_test, X=X_test) + + gscv.update(y=y, X=X, update_params=False) + + y_forecast = gscv.predict(fh=fh, X=X_future) + + best_params = gscv.best_params_ + + if self.round_result: + y_pred = round(y_pred) + y_forecast = round(y_forecast) + + return (y_pred, y_forecast, best_params) diff --git a/src/forecaster/models/xgbregressor.py b/src/forecaster/models/xgbregressor.py new file mode 100644 index 0000000000000000000000000000000000000000..2a81cf7afcf9e17ff8eb64c3330658ad7cf75a3c --- /dev/null +++ b/src/forecaster/models/xgbregressor.py @@ -0,0 +1,39 @@ +import logging + +from xgboost import XGBRegressor as xgbreg +import numpy as np + +from .base import ModelBase + + +class XGBRegressor(ModelBase): + def __init__( + self, + **kwargs + ) -> None: + + logging.debug('Init XGBRegressor') + + regressor = xgbreg( + objective='reg:squarederror', + random_state=42) + + param_grid = { + 'estimator__max_depth': [3, 5, 6, 10, 15, 20], + 'estimator__learning_rate': [0.01, 0.1, 0.2, 0.3], + 'estimator__subsample': np.arange(0.5, 1.0, 0.1), + 'estimator__colsample_bytree': np.arange(0.4, 1.0, 0.1), + 'estimator__colsample_bylevel': np.arange(0.4, 1.0, 0.1), + 'estimator__n_estimators': [100, 500, 1000] + } + + super().__init__( + regressor, + param_grid, + **kwargs) + + # def forecast(self): + # logging.debug('XGBRegressor forecast') + + # return {'forecast': self.forecaster.predict(**self.predict_args), + # 'evaluate': self.evaluate()} diff --git a/src/forecaster/utils/__init__.py b/src/forecaster/utils/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..9928cd211d87a1471021f2fd3a685277dff84299 --- /dev/null +++ b/src/forecaster/utils/__init__.py @@ -0,0 +1 @@ +from .prep_data import split_x_y, k_folds diff --git a/src/forecaster/utils/__pycache__/__init__.cpython-310.pyc b/src/forecaster/utils/__pycache__/__init__.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..68957d405de35b8f386ac09eb00551fec37dcc24 Binary files /dev/null and b/src/forecaster/utils/__pycache__/__init__.cpython-310.pyc differ diff --git a/src/forecaster/utils/__pycache__/prep_data.cpython-310.pyc b/src/forecaster/utils/__pycache__/prep_data.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..63f4004a8d8bde1293ec90c57587fcc7c71793f0 Binary files /dev/null and b/src/forecaster/utils/__pycache__/prep_data.cpython-310.pyc differ diff --git a/src/forecaster/utils/prep_data.py b/src/forecaster/utils/prep_data.py new file mode 100644 index 0000000000000000000000000000000000000000..197cb2c290b001b92529ec01627097661af57bcb --- /dev/null +++ b/src/forecaster/utils/prep_data.py @@ -0,0 +1,108 @@ +import math + +import pandas as pd +from sktime.forecasting.base import ForecastingHorizon + + +def split_x_y( + data: pd.DataFrame, + window_length: int, + n_predict: int, + freq: str, +): + # print('[prep_data] ----- Start -----') + datetime_index = data.index + y = data['y'] + X_train, X_forecast = None, None + + has_X = len(data.columns) > 1 + + if has_X: + # print('[prep_data] - additional feature columns found') + + X = data.drop(columns='y').reset_index(drop=True) + X_columns = X.columns + + X_train = pd.DataFrame() + + # ------------------------ # + # Build lags of the X data # + # ------------------------ # + + # print('[prep_data] - Building lags of features data') + for n in range(0, window_length): + # print('[prep_data],', n) + shifted_columns = {} + for col in X_columns: + shifted_columns[col] = f'{col}_-{n_predict + n}' + + shifted = X.shift(n).rename(columns=shifted_columns) + + X_train = pd.concat( + [X_train, shifted], + axis=1) + # print('[prep_data],', X_train) + + # print('[prep_data] - Backward fill lags of exog data') + X_train = X_train.bfill() + + # Split last n_predict rows from exog_train as exog_pred + X_forecast = X_train[-n_predict:] + X_train = X_train[:-n_predict] + + # For both y and datetime index, need to cut off n_predict value to keep data consistent + # print('[prep_data] - Cutting off y and datetime index be n_predict') + y = y[n_predict:] + datetime_index = datetime_index[n_predict:] + + X_train.set_index(datetime_index, inplace=True) + + fh = ForecastingHorizon( + list(range(1, n_predict+1)), is_relative=True, freq=freq) + # Cutoff is the last datetime value in the given data + # meaning we'll forecast right after this point of time + cutoff = datetime_index[-1] + fh = fh.to_absolute(cutoff=cutoff) + + if X_forecast is not None: + X_forecast.set_index(fh.to_pandas(), inplace=True) + + return (fh, y, X_train, X_forecast) + + +def k_folds( + data: pd.DataFrame, + period: int, + window_length: int, + n_predict: int, + freq: str +): + ''' + Amount of folds for testing is data size - window length and 2 seasonality period + This will make sure the smallest fold will still have 2 seasons and n_predict value, these will be sufficient to train a minimal model + ''' + print('[k_folds] ----- START -----') + k = math.floor((len(data) - n_predict - (2*period)) / period) + folds = [] + print('k', k) + + # Make sure k is not large than 10 + k = min(k, 10) + + if k == 0: + raise ValueError( + f'Data should at least have length of 2 seasons + n_predict rows, \ + currently length {len(data)}, expected length {2 * period + n_predict}') + + for i in reversed(range(1, k + 1)): + d = data[: (-i * period)] + folds.append( + split_x_y( + d, + window_length, + n_predict, + freq + )) + + print('[k_folds] ----- END -----') + return folds diff --git a/src/functions/__pycache__/__init__.cpython-310.pyc b/src/functions/__pycache__/__init__.cpython-310.pyc index 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--git a/src/idsc/IDSC.py b/src/idsc/IDSC.py index de0756cf9bcbf079fc781d30f4ccd9362937c7fc..a38d3bc7137ad3676e015294e1d0eef6b05d47ea 100644 --- a/src/idsc/IDSC.py +++ b/src/idsc/IDSC.py @@ -11,8 +11,9 @@ from .fft import fft from .holt_winters import holt_winters from .auto_arima import auto_arima + from dotenv import load_dotenv -load_dotenv() +# load_dotenv() class IDSC(): @@ -23,22 +24,26 @@ class IDSC(): self.config_path = os.path.join(__location__, 'config.yml') self.logged_in = False self.timeformat = '%m/%d/%Y, %H:%M:%S' + with open(self.config_path, 'r') as file: self.config = yaml.safe_load(file) + + self.expire = self.config['apikey_expire'] + self.apikey = self.config['apikey'] self.login() def login(self): - expire = self.config['apikey_expire'] + now = datetime.now() + expire_date = datetime.strptime(self.expire, self.timeformat) - expire_date = datetime.strptime(expire, self.timeformat) if now >= expire_date: print('apikey expired, requesting new one.') self.apikey = self.fetch_apikey() self.update_config() else: print('apikey still available, logged in') - self.apikey = self.config['apikey'] + self.logged_in = True def fetch_apikey(self): @@ -64,6 +69,9 @@ class IDSC(): expire = (now + timedelta(days=3)).strftime(self.timeformat) self.config['apikey'] = self.apikey self.config['apikey_expire'] = expire + + self.expire = expire + with open(self.config_path, 'w') as f: yaml.dump(self.config, f, default_flow_style=False) @@ -74,6 +82,7 @@ class IDSC(): ts_obj = json.loads(ts) ts_list = ts_obj['target'].values() + self.login() profiling = Profiling(apikey=self.apikey) return profiling.profile(ts_list) @@ -85,6 +94,7 @@ class IDSC(): ts: time series object string profile: refer to self.profiling response ''' + self.login() prophet = Prophet(apikey=self.apikey) characteristic = profile['classification_res']['time_series_class']['overall_characteristic'] @@ -107,6 +117,8 @@ class IDSC(): rate_score_weight=None, timing_score_weight=None): print('IDSC ceif') + + self.login() ceif = CEIF(apikey=self.apikey) ts_obj = json.loads(ts) @@ -130,6 +142,7 @@ class IDSC(): print('IDSC fft') + self.login() model = fft(apikey=self.apikey) ts_obj = json.loads(ts) @@ -146,6 +159,7 @@ class IDSC(): print('IDSC holt_winters') + self.login() model = holt_winters(apikey=self.apikey) ts_obj = json.loads(ts) @@ -161,6 +175,7 @@ class IDSC(): def auto_arima(self, ts, n_predict): print('IDSC auto_arima') + self.login() model = auto_arima(apikey=self.apikey) ts_obj = json.loads(ts) ts_list = list(ts_obj['target'].values()) diff --git a/src/idsc/Profiling.py b/src/idsc/Profiling.py index fe5753fa61f5c5c6b5545f18d019e04a79afa834..f6eac23ad7dc7f1ac9e4dc612ecf6e31facbd393 100644 --- a/src/idsc/Profiling.py +++ b/src/idsc/Profiling.py @@ -33,19 +33,27 @@ class Profiling(): self.change_point(list(ts)) inter_order_cpi = self.change_point_res['inter_order_cpi'] + order_quantity_cpi = self.change_point_res['order_quantity_cpi'] + self.classification(list(ts), inter_order_cpi=inter_order_cpi) ''' Predictability is disabled because not really required at this moment ''' - # self.predictability(list(ts)) + self.predictability( + list(ts), + inter_order_cpi=inter_order_cpi, + order_quantity_cpi=order_quantity_cpi) profile_res = { 'change_point_res': self.change_point_res, 'classification_res': self.classification_res, - # 'predictability_res': self.predictability_res + 'predictability_res': self.predictability_res } + print('Predictability') + print(self.predictability_res) + # self.__save_res(profile_res) # print('Profiling Completed\n', profile_res) diff --git a/src/idsc/Prophet.py b/src/idsc/Prophet.py index ce093625717905ed1c3893b76b5adc42adcfe323..07b55ff69dea67429bd58e3bebad878f76a5f961 100644 --- a/src/idsc/Prophet.py +++ b/src/idsc/Prophet.py @@ -22,6 +22,8 @@ class Prophet(): payloads = { 'time_series_table': ts, 'num_predict': n_predict} + + # print('[Prophet] - continuous', ts) if inter_order_cpi is not None: payloads['inter_order_cpi'] = inter_order_cpi diff --git a/src/idsc/__init__.py b/src/idsc/__init__.py index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..8a3adfb36ec60907297fc9eb24847e8b2f4050b4 100644 --- a/src/idsc/__init__.py +++ b/src/idsc/__init__.py @@ -0,0 +1 @@ +from .IDSC import IDSC \ No newline at end of file diff --git a/src/idsc/__pycache__/CEIF.cpython-310.pyc b/src/idsc/__pycache__/CEIF.cpython-310.pyc index dcb4c0c725b670599ff66ef883d3150a906f785a..022e90867b4760115daa5de210568e3e39261289 100644 Binary files a/src/idsc/__pycache__/CEIF.cpython-310.pyc and b/src/idsc/__pycache__/CEIF.cpython-310.pyc differ diff --git a/src/idsc/__pycache__/CEIF.cpython-311.pyc b/src/idsc/__pycache__/CEIF.cpython-311.pyc index 9c2cf5a93744a992c4702170e78dc2c0c77600ea..48617c2512f8e3ee6d44466dfd98588d8c0bd60f 100644 Binary files a/src/idsc/__pycache__/CEIF.cpython-311.pyc and b/src/idsc/__pycache__/CEIF.cpython-311.pyc differ diff --git a/src/idsc/__pycache__/CEIF.cpython-39.pyc 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b/src/idsc/__pycache__/holt_winters.cpython-39.pyc differ diff --git a/src/idsc/auto_arima.py b/src/idsc/auto_arima.py index 1fde38c948fd3be04b78d5513d9ba6072cb63096..44765dfec140d015668a99c98473cd794efe7a5a 100644 --- a/src/idsc/auto_arima.py +++ b/src/idsc/auto_arima.py @@ -10,7 +10,7 @@ class auto_arima(): def parse_res(self, res): if str(res.status_code)[0] != '2': - raise ValueError('auto_arima_plus API Call Failed!\n', res.text) + raise ValueError('auto_arima API Call Failed!\n', res.text) else: parsed_res = res.json() return parsed_res diff --git a/src/idsc/config.yml b/src/idsc/config.yml index f94d686fe47b32712da8fa902687c5e377b560b6..981c03612dd270c3fd3bcb0dcca4ddcdbad9df61 100644 --- a/src/idsc/config.yml +++ b/src/idsc/config.yml @@ -1,2 +1,2 @@ -apikey: 32ad72300f8d13d1356b9e7d6eb1cab41131f1da -apikey_expire: 10/25/2023, 19:53:41 +apikey: dff418c479f0c77b4e1162271831ebaabafce35b +apikey_expire: 12/14/2023, 20:57:06 diff --git a/src/idsc/fft.py b/src/idsc/fft.py index 3149eb4fadf23426fe5c26b45434bf18e57eb646..86c023a082a228b47e8d818b64fa1c10c779dfb7 100644 --- a/src/idsc/fft.py +++ b/src/idsc/fft.py @@ -10,7 +10,7 @@ class fft(): def parse_res(self, res): if str(res.status_code)[0] != '2': - raise ValueError('fft_plus API Call Failed!\n', res.text) + raise ValueError('fft API Call Failed!\n', res.text) else: parsed_res = res.json() return parsed_res diff --git a/src/idsc/holt_winters.py b/src/idsc/holt_winters.py index d4a241669748466b08aa19ddf3f6762d9650e650..5972355c3782530cb8b5fb66e19c19050f2c1c7e 100644 --- a/src/idsc/holt_winters.py +++ b/src/idsc/holt_winters.py @@ -10,7 +10,7 @@ class holt_winters(): def parse_res(self, res): if str(res.status_code)[0] != '2': - raise ValueError('holt_winters_plus API Call Failed!\n', res.text) + raise ValueError('holt_winters API Call Failed!\n', res.text) else: parsed_res = res.json() return parsed_res diff --git a/src/idsc/tests/auto_arima_success_res.dict b/src/idsc/tests/auto_arima_success_res.dict index 27d90495e2f67498dd4aabd3bf676ee08049aaed..3b7a8fa9924d7c13f8081f97ea50b815e037ffd3 100644 Binary files a/src/idsc/tests/auto_arima_success_res.dict and b/src/idsc/tests/auto_arima_success_res.dict differ diff --git a/src/main.py b/src/main.py index c85f0478c015a3b05cf5e45c1a689958cb98ba41..d195b1f615f1d195d09cf11cb9e7f5162344f721 100644 --- a/src/main.py +++ b/src/main.py @@ -1,4 +1,4 @@ -from .avtive_models import active_models +from .active_models import active_models, idsc_models from .forecast.Prophet import ProphetWrapper from .idsc.IDSC import IDSC @@ -33,20 +33,22 @@ class DemandForecasting(): self.idsc = IDSC() pass - def forecast(self, - ts, - n_predict: int, - model: str or list, - freq=None, - run_test: bool = False, - characteristic=None, - m=None): + def forecast( + self, + ts, + n_predict: int, + model: str or list, + freq=None, + run_test: bool = False, + characteristic=None, + m=None): ''' ts: timeseries object, use pd.DataFrame().to_json() to generate example: - {"datetime": + { + "datetime": {"0":"2018-05-06","1":"2018-05-13"}, - "y": + "y": {"0":2,"1":12}} n_predict: number of future values to predict freq: optional, timeseries data frequency, if not provided, will try to inference by pandas lib @@ -148,8 +150,12 @@ class DemandForecasting(): For idsc models, the profiling process will be required Also input data will be formated specifically for idsc ''' + temp_models = [list(filter(lambda x: x in self.model, sublist)) + for sublist in idsc_models] - self.has_idsc_model = any('plus' in m for m in self.model) + # self.has_idsc_model = any('plus' in m for m in self.model) + self.has_idsc_model = len(temp_models) > 0 + print('Has idsc model, ', self.has_idsc_model) if self.has_idsc_model and self.idsc_profile is None: ''' @@ -190,15 +196,18 @@ class DemandForecasting(): # ========================== # "For continuous data, use RMSE, for intermittent data, use average of interm scores" + # Sort forecast result by smallest RMSE if self.run_test and self.characteristic == 'continuous': self.fcst_res.sort(key=lambda x: x['RMSE']) + # Sort forecast result by highest avg_interm_scores if self.run_test and self.characteristic != 'continuous': self.fcst_res.sort( key=lambda x: x['avg_interm_scores'], reverse=True) # Return the result with lowest RMSE ranked as 1st item self.res = {'characteristic': self.characteristic, + 'predictability': self.predictability, 'forecast': self.fcst_res} return self.res @@ -237,6 +246,7 @@ class DemandForecasting(): def __prep_idsc_ts(self): # Time series configured for IDSC apis, all converted to json strings + print('[__prep_idsc_ts]') self.idsc_ts = self.ts_df.rename( columns={'datetime': 'date', 'y': 'target'}) self.idsc_ts['date'] = self.idsc_ts['date'].dt.strftime('%Y-%m-%d') @@ -250,14 +260,24 @@ class DemandForecasting(): def __profiling(self): self.idsc_profile = self.idsc.profiling(self.idsc_ts) + characteristic = self.idsc_profile['classification_res'][ 'time_series_class']['overall_characteristic'] + print('predictability temporarily using order_quantity predictability') + # print(self.idsc_profile) + + predictability = self.idsc_profile['predictability_res'][ + 'predictability_result']['order_quantity'][-1]['predictability'] + predictability = predictability if isinstance( + predictability, str) else round(predictability, 2) + if self.characteristic is not None and self.characteristic != characteristic: raise ValueError( f"Provided characteristics - {self.characteristic} is different from data's characteristics - {characteristic}. Please use the correct data characteristics.") self.characteristic = characteristic + self.predictability = predictability if self.run_test: self.idsc_profile_train = self.idsc.profiling( @@ -289,7 +309,8 @@ class DemandForecasting(): res = {'model': model_name} # IDSC is using different input configuration - if 'plus' in model_name: + # if 'plus' in model_name: + if model_name in idsc_models: print('has_idsc_model') ts = self.idsc_ts train = self.idsc_ts_train @@ -309,8 +330,9 @@ class DemandForecasting(): # # Same for below 'test' dataframe # index=self.forecast_horizon[:len(pred_val)], # columns=['y']) - res['forecast'] = {'datetime': self.forecast_horizon[:len(pred_val)+1], - 'y': pred_val} + res['forecast'] = { + 'datetime': self.forecast_horizon[:len(pred_val)+1], + 'y': pred_val} res['raw'] = pred # Run the test set and evaluate model performance @@ -362,9 +384,9 @@ class DemandForecasting(): # ---------- # # All Models # # ---------- # - def prophet_plus(self): + def prophet_i(self): model = self.idsc.prophet - model_name = 'prophet_plus' + model_name = 'prophet_i' args = {'profile': self.idsc_profile} @@ -384,29 +406,30 @@ class DemandForecasting(): args = {'freq': self.freq} - self.__use_model(model.forecast, - model_name, - lambda x: x['yhat'].to_list(), - args=args) + self.__use_model( + model.forecast, + model_name, + lambda x: x['yhat'].to_list(), + args=args) - def ceif_plus(self): - model_name = 'ceif_plus' + def ceif(self): + model_name = 'ceif' self.__use_model( self.idsc.ceif, model_name, lambda x: x['prediction_result']['predicted_value']) - def fft_plus(self): - model_name = 'fft_plus' + def fft_i(self): + model_name = 'fft_i' self.__use_model( self.idsc.fft, model_name, lambda x: x['prediction_result']['predicted_value']) - def holt_winters_plus(self): - model_name = 'holt_winters_plus' + def holt_winters_i(self): + model_name = 'holt_winters_i' def get_value(x): return x['prediction_result']['predicted_value'] @@ -423,8 +446,8 @@ class DemandForecasting(): model_name, get_value) - def auto_arima_plus(self): - model_name = 'auto_arima_plus' + def auto_arima_i(self): + model_name = 'auto_arima_i' model = self.idsc.auto_arima def get_value(x): return x['prediction_result']['predicted_value'] diff --git a/src/models/__pycache__/DemandForecastingRes.cpython-310.pyc b/src/models/__pycache__/DemandForecastingRes.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..f8aab6ae74a333183207eff4e5730f148be8ec41 Binary files /dev/null and b/src/models/__pycache__/DemandForecastingRes.cpython-310.pyc differ diff --git a/src/models/__pycache__/__init__.cpython-310.pyc b/src/models/__pycache__/__init__.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..246e84b121c4c46e849687fd0d8674bd9c1f7cfa Binary files /dev/null and b/src/models/__pycache__/__init__.cpython-310.pyc differ diff --git a/temp/20231211223454.csv b/temp/20231211223454.csv new file mode 100644 index 0000000000000000000000000000000000000000..2e479ad045056aa931bfe143362976061f9886b3 --- /dev/null +++ b/temp/20231211223454.csv @@ -0,0 +1,5 @@ +,y +2023-01-31,73.0 +2023-02-28,78.0 +2023-03-31,79.0 +2023-04-30,80.0 diff --git a/temp/20231211223529.csv b/temp/20231211223529.csv new file mode 100644 index 0000000000000000000000000000000000000000..2e479ad045056aa931bfe143362976061f9886b3 --- /dev/null +++ b/temp/20231211223529.csv @@ -0,0 +1,5 @@ +,y +2023-01-31,73.0 +2023-02-28,78.0 +2023-03-31,79.0 +2023-04-30,80.0 diff --git a/temp/20231211223803.csv b/temp/20231211223803.csv new file mode 100644 index 0000000000000000000000000000000000000000..2e479ad045056aa931bfe143362976061f9886b3 --- /dev/null +++ b/temp/20231211223803.csv @@ -0,0 +1,5 @@ +,y +2023-01-31,73.0 +2023-02-28,78.0 +2023-03-31,79.0 +2023-04-30,80.0