feat: added evaluate_model method for test data evaluation

CHANGELOG.md

@@ -105,4 +105,5 @@ activation function type
 
 - chore!: changed from temp library keras_core to keras > 3.0.0
 - removed python 3.8 support to accomodate tensorflow and keras dependiencies
-- increased major to 3.0.0 to align with keras major
+- increased major to 3.0.0 to align with keras major
+- added evaluate_model method to test model performance on test data

imbrium/predictors/multivarhybrid.py

@@ -707,6 +707,7 @@ def fit_model(
                     epochs=epochs,
                     verbose=show_progress,
                     callbacks=[callback_board],
+                    shuffle=False,
                 )
             else:
                 self.details = self.model.fit(
@@ -715,6 +716,7 @@ def fit_model(
                     validation_split=validation_split,
                     epochs=epochs,
                     verbose=show_progress,
+                    shuffle=False,
                 )
 
         else:
@@ -733,6 +735,7 @@ def fit_model(
                     epochs=epochs,
                     verbose=show_progress,
                     callbacks=[callback, callback_board],
+                    shuffle=False,
                 )
             else:
                 callback = EarlyStopping(**callback_setting)
@@ -743,6 +746,7 @@ def fit_model(
                     epochs=epochs,
                     verbose=show_progress,
                     callbacks=[callback],
+                    shuffle=False,
                 )
         return self.details
 

imbrium/predictors/multivarpure.py

@@ -667,6 +667,7 @@ def fit_model(
                     epochs=epochs,
                     verbose=show_progress,
                     callbacks=[callback_board],
+                    shuffle=False,
                 )
             else:
                 self.details = self.model.fit(
@@ -675,6 +676,7 @@ def fit_model(
                     validation_split=validation_split,
                     epochs=epochs,
                     verbose=show_progress,
+                    shuffle=False,
                 )
 
         else:
@@ -693,6 +695,7 @@ def fit_model(
                     epochs=epochs,
                     verbose=show_progress,
                     callbacks=[callback, callback_board],
+                    shuffle=False,
                 )
             else:
                 callback = EarlyStopping(**callback_setting)
@@ -703,6 +706,7 @@ def fit_model(
                     epochs=epochs,
                     verbose=show_progress,
                     callbacks=[callback],
+                    shuffle=False,
                 )
         return self.details
 

imbrium/predictors/univarhybrid.py

@@ -679,6 +679,7 @@ def fit_model(
                     epochs=epochs,
                     verbose=show_progress,
                     callbacks=[callback_board],
+                    shuffle=False,
                 )
             else:
                 self.details = self.model.fit(
@@ -687,6 +688,7 @@ def fit_model(
                     validation_split=validation_split,
                     epochs=epochs,
                     verbose=show_progress,
+                    shuffle=False,
                 )
 
         else:
@@ -705,6 +707,7 @@ def fit_model(
                     epochs=epochs,
                     verbose=show_progress,
                     callbacks=[callback, callback_board],
+                    shuffle=False,
                 )
             else:
                 callback = EarlyStopping(**callback_setting)
@@ -715,6 +718,7 @@ def fit_model(
                     epochs=epochs,
                     verbose=show_progress,
                     callbacks=[callback],
+                    shuffle=False,
                 )
         return self.details
 

imbrium/predictors/univarpure.py

@@ -1,5 +1,6 @@
 import datetime
 import os
+from typing import Tuple
 
 from keras.callbacks import EarlyStopping, TensorBoard
 from keras.saving import load_model
@@ -38,9 +39,21 @@ def _model_intake_prep(self, steps_past: int, steps_future: int) -> None:
             self.input_x, self.input_y = sequence_prep_standard_uni(
                 temp_data, steps_past, steps_future
             )
+            self.input_x, self.input_x_test = self._train_test_split(self.input_x)
+            self.input_y, self.input_y_test = self._train_test_split(self.input_y)
         else:
             pass
 
+    def _train_test_split(self, data: array, test_size=0.2) -> Tuple[array, array]:
+        """Splits the time series data into training and testing sets."""
+        n_samples = len(data)
+        n_test = int(test_size * n_samples)
+
+        train_data = data[:-n_test]
+        test_data = data[-n_test:]
+
+        return train_data, test_data
+
     def set_model_id(self, name: str):
         """Setter method to change model id field.
         Parameters:
@@ -155,6 +168,10 @@ def create_mlp(
             (self.input_x.shape[0], self.input_x.shape[1])
         )
 
+        self.input_x_test = self.input_x_test.reshape(
+            (self.input_x_test.shape[0], self.input_x_test.shape[1])
+        )
+
         optimizer_obj = get_optimizer(optimizer, optimizer_args)
 
         self.model = mlp(
@@ -663,6 +680,7 @@ def fit_model(
                     epochs=epochs,
                     verbose=show_progress,
                     callbacks=[callback_board],
+                    shuffle=False,
                 )
             else:
                 self.details = self.model.fit(
@@ -671,6 +689,7 @@ def fit_model(
                     validation_split=validation_split,
                     epochs=epochs,
                     verbose=show_progress,
+                    shuffle=False,
                 )
 
         else:
@@ -689,6 +708,7 @@ def fit_model(
                     epochs=epochs,
                     verbose=show_progress,
                     callbacks=[callback, callback_board],
+                    shuffle=False,
                 )
             else:
                 callback = EarlyStopping(**callback_setting)
@@ -699,9 +719,17 @@ def fit_model(
                     epochs=epochs,
                     verbose=show_progress,
                     callbacks=[callback],
+                    shuffle=False,
                 )
         return self.details
 
+    def evaluate_model(self):
+        self.evaluation_details = self.model.evaluate(
+            x=self.input_x_test, y=self.input_y_test
+        )
+
+        return self.evaluation_details
+
     def model_blueprint(self):
         """Prints a summary of the models layer structure."""
         self.model.summary()
@@ -710,6 +738,10 @@ def show_performance(self):
         """Returns performance details."""
         return self.details
 
+    def show_evaluation(self):
+        """Returns performance details on test data."""
+        return self.evaluation_details
+
     def predict(self, data: array) -> array:
         """Takes in a sequence of values and outputs a forecast.
         Parameters:

setup.py

@@ -17,9 +17,7 @@
     packages=find_packages(include=["imbrium", "imbrium.*"]),
     install_requires=[
         "setuptools >= 41.0.0",
-        #"tensorflow >=2.16.0, < 3.0.0",
-        "tf-nightly-cpu==2.16.0.dev20231130", # temporary solution for testing, waiting for release
-        "keras >=3.0.0, < 4.0.0",
+        "tensorflow>=2.16.0",
     ],
     classifiers=[
         "Programming Language :: Python :: 3.9",

tests/test_predictors/test_univarpure.py

@@ -44,8 +44,8 @@
 
 y = np.array([[3.422], [2.697], [2.992]])
 
-shape_x = (494, 2, 1)
-shape_y = (494, 3, 1)
+shape_x = (396, 2, 1)
+shape_y = (396, 3, 1)
 
 model_id = "LSTM"
 optimizer = "adam"