refactor(Project): move out load_data to utils, rename fetch_data to run_fetch_data, got classifiers to work (#38)

archive/forecasting.py

@@ -9,7 +9,7 @@ from pytorch_forecasting.metrics import QuantileLoss
 import sys
 sys.path.insert(0, '..')
 
-from load_data import load_files
+from utils.load_data import load_files
 
 print("success")
 

archive/lightning/create_dataset.py

@@ -8,7 +8,7 @@ from pytorch_forecasting.metrics import QuantileLoss
 import sys
 sys.path.insert(0, '..')
 
-from load_data import load_files
+from utils.load_data import load_files
 
 print("success")
 

archive/lightning/train_predict.py

@@ -10,7 +10,7 @@ warnings.filterwarnings("ignore")
 import sys
 sys.path.insert(0, '..')
 
-from load_data import load_files
+from utils.load_data import load_files
 
 
 

archive/model_classification_keras.py

@@ -1,6 +1,6 @@
 #%% Import all the stuff, load data, define constants
 from sklearn.utils import shuffle
-from load_data import load_files, create_target_classes
+from utils.load_data import load_files, create_target_classes
 import pandas as pd
 from tensorflow import keras
 from utils.normalize import normalize

archive/model_classification_sklearn.py

@@ -2,7 +2,7 @@
 from sklearnex import patch_sklearn
 patch_sklearn()
 
-from load_data import create_target_cum_forward_returns, create_target_classes, load_files
+from utils.load_data import create_target_cum_forward_returns, create_target_classes, load_files
 from sktime.forecasting.model_selection import temporal_train_test_split
 from sklearn.metrics import accuracy_score
 from sklearn.metrics import confusion_matrix

archive/model_classification_sklearn_walk_forward.py

@@ -2,7 +2,7 @@
 from sklearnex import patch_sklearn
 patch_sklearn()
 
-from load_data import create_target_classes, load_files
+from utils.load_data import create_target_classes, load_files
 from sktime.forecasting.model_selection import temporal_train_test_split
 from sklearn.metrics import accuracy_score
 from sklearn.metrics import confusion_matrix
@@ -122,7 +122,7 @@ for model_name, create_model in models_to_try:
         retrain_every = retrain_every
     )
 
-    evaluate_predictions(model_name, y_train, preds, sliding_window_size)
+    evaluate_predictions(model_name, y_train, preds)
 
 
 #%%

archive/model_classification_sktime.py

@@ -1,5 +1,5 @@
 #%% Import all the stuff, load data, define constants
-from load_data import load_files, create_target_classes
+from utils.load_data import load_files, create_target_classes
 import pandas as pd
 import numpy as np
 from utils.sktime import from_df_to_sktime_data

archive/model_regression_keras.py

@@ -1,6 +1,6 @@
 #%% Import all the stuff, load data, define constants
 from sklearn.utils import shuffle
-from load_data import load_files, create_target_cum_forward_returns
+from utils.load_data import load_files, create_target_cum_forward_returns
 import pandas as pd
 from tensorflow import keras
 from utils.normalize import normalize

archive/run_lightning.py

@@ -1,4 +1,4 @@
-from load_data import load_files
+from utils.load_data import load_files
 import pandas as pd
 # from tensorflow import keras
 from utils.normalize import normalize