refactor(WalkForward): separate train / test functions to help with inference later (#158)

* refactor(WalkForward): separate train / test functions (draft) to potentially help with inference later

* fix(Training): use the new separate train / test functions

* feat(Training): return and pass in scalers that are necessary for inference

* fix(Project): runtime errors

* fix(WalkForward): use the correct `train_from` value

* fix(Tests): for new walk_forward functions()

* refactor(WalkForward): rename `walk_forward_test()` to `walk_forward_inference()`

tests/test_evaluation.py

@@ -1,9 +1,10 @@
 
 import numpy as np
 import pandas as pd
-from training.walk_forward import walk_forward_train_test
+from training.walk_forward import walk_forward_train, walk_forward_inference
 from models.base import Model
 from utils.evaluate import evaluate_predictions
+from sklearn.preprocessing import MinMaxScaler
 
 no_of_rows = 100
 
@@ -67,9 +68,9 @@ def test_evaluation():
     window_length = 10
 
     model = EvenOddStubModel(window_length = window_length)
-    scaler = None
+    scaler = MinMaxScaler()
     
-    models, predictions, probs = walk_forward_train_test(
+    models, scalers = walk_forward_train(
         model_name='test',
         model=model,
         X=X,
@@ -78,7 +79,14 @@ def test_evaluation():
         expanding_window=False,
         window_size=window_length,
         retrain_every=10,
-        scaler=scaler
+        scaler=scaler)
+    predictions, probs = walk_forward_inference(
+        model_name='test',
+        models=models,
+        scalers=scalers,
+        X=X,
+        expanding_window=False,
+        window_size=window_length
     )
     
     # verify if predictions are the same as y

tests/test_walk_forward.py

@@ -1,7 +1,8 @@
 import numpy as np
 import pandas as pd
-from training.walk_forward import walk_forward_train_test
+from training.walk_forward import walk_forward_train, walk_forward_inference
 from models.base import Model
+from sklearn.preprocessing import MinMaxScaler
 
 no_of_rows = 100
 
@@ -65,9 +66,9 @@ def test_walk_forward_train_test():
     window_length = 10
 
     model = IncrementingStubModel(window_length = window_length)
-    scaler = None
+    scaler = MinMaxScaler()
 
-    models, predictions, probs = walk_forward_train_test(
+    models, scalers = walk_forward_train(
         model_name='test',
         model=model,
         X=X,
@@ -77,6 +78,14 @@ def test_walk_forward_train_test():
         window_size=window_length,
         retrain_every=10,
         scaler=scaler)
+    predictions, probs = walk_forward_inference(
+        model_name='test',
+        models=models,
+        scalers=scalers,
+        X=X,
+        expanding_window=False,
+        window_size=window_length
+    )
     
     # verify if predictions are the same as y
     for i in range(window_length+2, no_of_rows):