Sourcery Starbot ⭐ refactored curenosm/MeIA #3

SourceryAI · 2023-12-10T17:49:34Z

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SourceryAI

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SourceryAI · 2023-12-10T17:49:35Z

modulo_2/sesion_1/src/exercise-S1-3-01.py

    start_test = True
    with torch.no_grad():
-        for batch_idx, data in enumerate(test_loader):
+        for data in test_loader:


Function test refactored with the following changes:

Remove unnecessary calls to enumerate when the index is not used (remove-unused-enumerate)

SourceryAI · 2023-12-10T17:49:35Z

modulo_2/sesion_1/src/exercise-S1-3-01.py


-        for i, (train_index, test_index) in enumerate(skf.split(x, y)):
-
+        for train_index, test_index in skf.split(x, y):


Function kfcv refactored with the following changes:

Remove unnecessary calls to enumerate when the index is not used (remove-unused-enumerate)

Use f-string instead of string concatenation (use-fstring-for-concatenation)

Use with when opening file to ensure closure (ensure-file-closed)

Replace unused for index with underscore (for-index-underscore)

SourceryAI · 2023-12-10T17:49:36Z

modulo_2/sesion_1/src/exercise-S1-3-02.py

    start_test = True
    with torch.no_grad():
-        for batch_idx, data in enumerate(test_loader):
+        for data in test_loader:


Function test refactored with the following changes:

Remove unnecessary calls to enumerate when the index is not used (remove-unused-enumerate)

SourceryAI · 2023-12-10T17:49:36Z

modulo_2/sesion_1/src/exercise-S1-3-02.py

    # variable used to save accuracy results
    list_metrics_clsf = []
-        
+


Function losocv refactored with the following changes:

Simplify numeric comparison (simplify-numeric-comparison)

Replace unused for index with underscore (for-index-underscore)

Use f-string instead of string concatenation [×3] (use-fstring-for-concatenation)

Use with when opening file to ensure closure (ensure-file-closed)

SourceryAI · 2023-12-10T17:49:36Z

modulo_2/sesion_1/src/utils/modules_pbashivan.py

-    print("Loading data from %s" % (data_file))
+    print(f"Loading data from {data_file}")

    dataMat = scipy.io.loadmat(data_file, mat_dtype=True)
    all_data = np.array(dataMat['features'])
-    
+
    data = np.array(all_data[:,:len(all_data[0])-1])
    labels = np.array(all_data[:,len(all_data[0])-1])
-    
+
    print("Data loading complete. Shape is %r" % (dataMat['features'].shape,))
-    
+


Function load_data refactored with the following changes:

Replace interpolated string formatting with f-string (replace-interpolation-with-fstring)

SourceryAI · 2023-12-10T17:49:37Z

modulo_2/sesion_2/src/utils/modules_pbashivan.py

-    print("Loading data from %s" % (data_file))
+    print(f"Loading data from {data_file}")

    dataMat = scipy.io.loadmat(data_file, mat_dtype=True)
    all_data = np.array(dataMat['features'])
-    
+
    data = np.array(all_data[:,:len(all_data[0])-1])
    labels = np.array(all_data[:,len(all_data[0])-1])
-    
+
    print("Data loading complete. Shape is %r" % (dataMat['features'].shape,))
-    
+


Function load_data refactored with the following changes:

Replace interpolated string formatting with f-string (replace-interpolation-with-fstring)

SourceryAI · 2023-12-10T17:49:37Z

modulo_2/sesion_2/src/utils/modules_pbashivan.py

-    
+
    """
        Module used to load dataset of bashivan et al. 2014.
    """

    # load data pbashivan
-    data, labels = load_data(data_dir + "FeatureMat_timeWin.mat")
+    data, labels = load_data(f"{data_dir}FeatureMat_timeWin.mat")
    print("Original data:",data.shape, labels.shape)
-        
+
    if generate_images:

        # NOTE: Only a 3D projection is proporcionated, then it is not avaliable other
        # records with positions.
-        
+
        #Load locations in 3D
-        locs_orig = scipy.io.loadmat(data_dir+'Neuroscan_locs_orig.mat', mat_dtype=True)
+        locs_orig = scipy.io.loadmat(
+            f'{data_dir}Neuroscan_locs_orig.mat', mat_dtype=True
+        )
        locs3D = locs_orig['A']
-
-        #Convert to 2D
-        locs2D =[]
-        for e in locs3D:
-            locs2D.append(azim_proj(e))
-
+
+        locs2D = [azim_proj(e) for e in locs3D]
        #save in numpy array
        locs2D = np.array(locs2D)
-        
+
        # visualize projection
        if visualize:
            print("No. channels:",locs3D.shape)
-            
+


Function load_bashivan_data refactored with the following changes:

Use f-string instead of string concatenation [×5] (use-fstring-for-concatenation)

Convert for loop into list comprehension (list-comprehension)

This removes the following comments ( why? ):

#Convert to 2D

SourceryAI · 2023-12-10T17:49:37Z

modulo_2/sesion_3/src/exercise-S1-3-01.py

    start_test = True
    with torch.no_grad():
-        for batch_idx, data in enumerate(test_loader):
+        for data in test_loader:


Function test refactored with the following changes:

Remove unnecessary calls to enumerate when the index is not used (remove-unused-enumerate)

SourceryAI · 2023-12-10T17:49:37Z

modulo_2/sesion_3/src/exercise-S1-3-01.py


-        for i, (train_index, test_index) in enumerate(skf.split(x, y)):
-
+        for train_index, test_index in skf.split(x, y):


Function kfcv refactored with the following changes:

Remove unnecessary calls to enumerate when the index is not used (remove-unused-enumerate)

Use f-string instead of string concatenation (use-fstring-for-concatenation)

Use with when opening file to ensure closure (ensure-file-closed)

Replace unused for index with underscore (for-index-underscore)

SourceryAI · 2023-12-10T17:49:37Z

modulo_2/sesion_3/src/exercise-S1-3-02.py

    start_test = True
    with torch.no_grad():
-        for batch_idx, data in enumerate(test_loader):
+        for data in test_loader:


Function test refactored with the following changes:

Remove unnecessary calls to enumerate when the index is not used (remove-unused-enumerate)

SourceryAI · 2023-12-10T17:49:39Z

modulo_2/sesion_3/src/exercise-S1-3-02.py

    # variable used to save accuracy results
    list_metrics_clsf = []
-        
+


Function losocv refactored with the following changes:

Simplify numeric comparison (simplify-numeric-comparison)

Replace unused for index with underscore (for-index-underscore)

Use f-string instead of string concatenation [×3] (use-fstring-for-concatenation)

Use with when opening file to ensure closure (ensure-file-closed)

SourceryAI · 2023-12-10T17:49:40Z

modulo_2/sesion_3/src/exercise-S2-2-01.py

    start_test = True
    with torch.no_grad():
-        for batch_idx, data in enumerate(test_loader):
+        for data in test_loader:


Function test refactored with the following changes:

Remove unnecessary calls to enumerate when the index is not used (remove-unused-enumerate)

SourceryAI · 2023-12-10T17:49:40Z

modulo_2/sesion_3/src/exercise-S2-2-01.py

-        
+
    # Extract pairs between indexes and subjects
    fold_pairs = get_subject_indices(subjects)
-    
+
    # Iterate over fold_pairs
    for foldNum, fold in enumerate(fold_pairs):
        print('Beginning fold {0} out of {1}'.format(foldNum+1, len(fold_pairs)))

        # Only Subjects 1, 2 are executed
-        if foldNum + 1 >= 3:# and foldNum + 1 <= 11:
+        if foldNum >= 2:# and foldNum + 1 <= 11:


Function losocv refactored with the following changes:

Simplify numeric comparison (simplify-numeric-comparison)

Hoist statements out of for/while loops (hoist-statement-from-loop)

Use f-string instead of string concatenation (use-fstring-for-concatenation)

Use with when opening file to ensure closure (ensure-file-closed)

SourceryAI · 2023-12-10T17:49:40Z

modulo_2/sesion_3/src/exercise-S2-2-02.py

    start_test = True
    with torch.no_grad():
-        for batch_idx, data in enumerate(test_loader):
+        for data in test_loader:


Function test refactored with the following changes:

Remove unnecessary calls to enumerate when the index is not used (remove-unused-enumerate)

SourceryAI · 2023-12-10T17:49:40Z

modulo_2/sesion_3/src/exercise-S2-2-02.py

-        
+
    # Extract pairs between indexes and subjects
    fold_pairs = get_subject_indices(subjects)
-    
+
    # Iterate over fold_pairs
    for foldNum, fold in enumerate(fold_pairs):
        print('Beginning fold {0} out of {1}'.format(foldNum+1, len(fold_pairs)))

-	# Only Subjects 1, 2 are executed
-	if foldNum + 1 >= 3:# and foldNum + 1 <= 11:
-	    continue
-
+        if foldNum >= 2:# and foldNum + 1 <= 11:
+            continue
+


Function losocv refactored with the following changes:

Simplify numeric comparison (simplify-numeric-comparison)

Hoist statements out of for/while loops (hoist-statement-from-loop)

Use f-string instead of string concatenation (use-fstring-for-concatenation)

Use with when opening file to ensure closure (ensure-file-closed)

This removes the following comments ( why? ):

# Only Subjects 1, 2 are executed

SourceryAI · 2023-12-10T17:49:41Z

modulo_2/sesion_4/src/exercise-S2-2-01.py

-        
+
    # Extract pairs between indexes and subjects
    fold_pairs = get_subject_indices(subjects)
-    
+
    # Iterate over fold_pairs
    for foldNum, fold in enumerate(fold_pairs):
        print('Beginning fold {0} out of {1}'.format(foldNum+1, len(fold_pairs)))

        # Only Subjects 1, 2 are executed
-        if foldNum + 1 >= 3:# and foldNum + 1 <= 11:
+        if foldNum >= 2:# and foldNum + 1 <= 11:


Function losocv refactored with the following changes:

Simplify numeric comparison (simplify-numeric-comparison)

Hoist statements out of for/while loops (hoist-statement-from-loop)

Use f-string instead of string concatenation (use-fstring-for-concatenation)

Use with when opening file to ensure closure (ensure-file-closed)

SourceryAI · 2023-12-10T17:49:41Z

modulo_2/sesion_4/src/exercise-S2-2-02.py

    start_test = True
    with torch.no_grad():
-        for batch_idx, data in enumerate(test_loader):
+        for data in test_loader:


Function test refactored with the following changes:

Remove unnecessary calls to enumerate when the index is not used (remove-unused-enumerate)

SourceryAI · 2023-12-10T17:49:41Z

modulo_2/sesion_4/src/exercise-S2-2-02.py

-        
+
    # Extract pairs between indexes and subjects
    fold_pairs = get_subject_indices(subjects)
-    
+
    # Iterate over fold_pairs
    for foldNum, fold in enumerate(fold_pairs):
        print('Beginning fold {0} out of {1}'.format(foldNum+1, len(fold_pairs)))

-	# Only Subjects 1, 2 are executed
-	if foldNum + 1 >= 3:# and foldNum + 1 <= 11:
-	    continue
-
+        if foldNum >= 2:# and foldNum + 1 <= 11:
+            continue
+


Function losocv refactored with the following changes:

Simplify numeric comparison (simplify-numeric-comparison)

Hoist statements out of for/while loops (hoist-statement-from-loop)

Use f-string instead of string concatenation (use-fstring-for-concatenation)

Use with when opening file to ensure closure (ensure-file-closed)

This removes the following comments ( why? ):

# Only Subjects 1, 2 are executed

SourceryAI · 2023-12-10T17:49:41Z

modulo_2/sesion_4/src/exercise-S2-2-03.py

    start_test = True
    with torch.no_grad():
-        for batch_idx, data in enumerate(test_loader):
+        for data in test_loader:


Function test refactored with the following changes:

Remove unnecessary calls to enumerate when the index is not used (remove-unused-enumerate)

SourceryAI · 2023-12-10T17:49:41Z

modulo_2/sesion_4/src/exercise-S2-2-03.py

-        
+
    # Extract pairs between indexes and subjects
    fold_pairs = get_subject_indices(subjects)
-    
+
    # Iterate over fold_pairs
    for foldNum, fold in enumerate(fold_pairs):
        print('Beginning fold {0} out of {1}'.format(foldNum+1, len(fold_pairs)))

        # Only Subjects 1, 2 are executed
-        if foldNum + 1 >= 3:# and foldNum + 1 <= 11:
+        if foldNum >= 2:# and foldNum + 1 <= 11:


Function losocv refactored with the following changes:

Simplify numeric comparison (simplify-numeric-comparison)

Use f-string instead of string concatenation (use-fstring-for-concatenation)

Use with when opening file to ensure closure (ensure-file-closed)

SourceryAI · 2023-12-10T17:49:43Z

modulo_2/sesion_4/src/exercise-S3-1-01.py

    start_test = True
    with torch.no_grad():
-        for batch_idx, data in enumerate(test_loader):
+        for data in test_loader:


Function test refactored with the following changes:

Remove unnecessary calls to enumerate when the index is not used (remove-unused-enumerate)

SourceryAI · 2023-12-10T17:49:43Z

modulo_2/sesion_4/src/exercise-S3-1-01.py

-        
+
    # Extract pairs between indexes and subjects
    fold_pairs = get_subject_indices(subjects)
-    
+
    # Iterate over fold_pairs
    for foldNum, fold in enumerate(fold_pairs):
        print('Beginning fold {0} out of {1}'.format(foldNum+1, len(fold_pairs)))

        # Only Subjects 1 and 2 are executed
-        if foldNum+1 >= 2:# and foldNum+1 <= 11:
+        if foldNum >= 1:# and foldNum+1 <= 11:


Function losocv refactored with the following changes:

Simplify numeric comparison (simplify-numeric-comparison)

Hoist statements out of for/while loops (hoist-statement-from-loop)

Use f-string instead of string concatenation (use-fstring-for-concatenation)

Use with when opening file to ensure closure (ensure-file-closed)

SourceryAI · 2023-12-10T17:49:44Z

modulo_2/sesion_4/src/exercise-S3-1-02.py

    start_test = True
    with torch.no_grad():
-        for batch_idx, data in enumerate(test_loader):
+        for data in test_loader:


Function test refactored with the following changes:

Remove unnecessary calls to enumerate when the index is not used (remove-unused-enumerate)

SourceryAI · 2023-12-10T17:49:44Z

modulo_2/sesion_4/src/exercise-S3-1-02.py

-        
+
    # Extract pairs between indexes and subjects
    fold_pairs = get_subject_indices(subjects)
-    
+
    # Iterate over fold_pairs
    for foldNum, fold in enumerate(fold_pairs):
        print('Beginning fold {0} out of {1}'.format(foldNum+1, len(fold_pairs)))

-        if foldNum+1 >= 3:# and foldNum+1 <= 11:
+        if foldNum >= 2:# and foldNum+1 <= 11:


Function losocv refactored with the following changes:

Simplify numeric comparison (simplify-numeric-comparison)

Use f-string instead of string concatenation (use-fstring-for-concatenation)

Use with when opening file to ensure closure (ensure-file-closed)

SourceryAI · 2023-12-10T17:49:44Z

modulo_2/sesion_4/src/models/model_modules.py

-        out = self.fc_out(x)
-
-        return out
+        return self.fc_out(x)


Function Predictor.forward refactored with the following changes:

Inline variable that is immediately returned (inline-immediately-returned-variable)

SourceryAI · 2023-12-10T17:49:45Z

modulo_2/sesion_5/src/exercise-S2-2-03.py

    start_test = True
    with torch.no_grad():
-        for batch_idx, data in enumerate(test_loader):
+        for data in test_loader:


Function test refactored with the following changes:

Remove unnecessary calls to enumerate when the index is not used (remove-unused-enumerate)

SourceryAI · 2023-12-10T17:49:45Z

modulo_2/sesion_5/src/exercise-S2-2-03.py

-        
+
    # Extract pairs between indexes and subjects
    fold_pairs = get_subject_indices(subjects)
-    
+
    # Iterate over fold_pairs
    for foldNum, fold in enumerate(fold_pairs):
        print('Beginning fold {0} out of {1}'.format(foldNum+1, len(fold_pairs)))

        # Only Subjects 1, 2 are executed
-        if foldNum + 1 >= 3:# and foldNum + 1 <= 11:
+        if foldNum >= 2:# and foldNum + 1 <= 11:


Function losocv refactored with the following changes:

Simplify numeric comparison (simplify-numeric-comparison)

Use f-string instead of string concatenation (use-fstring-for-concatenation)

Use with when opening file to ensure closure (ensure-file-closed)

SourceryAI · 2023-12-10T17:49:45Z

modulo_2/sesion_5/src/exercise-S3-1-01.py

    start_test = True
    with torch.no_grad():
-        for batch_idx, data in enumerate(test_loader):
+        for data in test_loader:


Function test refactored with the following changes:

Remove unnecessary calls to enumerate when the index is not used (remove-unused-enumerate)

SourceryAI · 2023-12-10T17:49:45Z

modulo_2/sesion_5/src/exercise-S3-1-01.py

-        
+
    # Extract pairs between indexes and subjects
    fold_pairs = get_subject_indices(subjects)
-    
+
    # Iterate over fold_pairs
    for foldNum, fold in enumerate(fold_pairs):
        print('Beginning fold {0} out of {1}'.format(foldNum+1, len(fold_pairs)))

        # Only Subjects 1 and 2 are executed
-        if foldNum+1 >= 2:# and foldNum+1 <= 11:
+        if foldNum >= 1:# and foldNum+1 <= 11:


Function losocv refactored with the following changes:

Simplify numeric comparison (simplify-numeric-comparison)

Hoist statements out of for/while loops (hoist-statement-from-loop)

Use f-string instead of string concatenation (use-fstring-for-concatenation)

Use with when opening file to ensure closure (ensure-file-closed)

SourceryAI · 2023-12-10T17:49:46Z

modulo_2/sesion_5/src/exercise-S3-1-02.py

    start_test = True
    with torch.no_grad():
-        for batch_idx, data in enumerate(test_loader):
+        for data in test_loader:


Function test refactored with the following changes:

Remove unnecessary calls to enumerate when the index is not used (remove-unused-enumerate)

'Refactored by Sourcery'

6193c53

SourceryAI commented Dec 10, 2023

View reviewed changes


		for i, (train_index, test_index) in enumerate(skf.split(x, y)):

		for train_index, test_index in skf.split(x, y):

		# variable used to save accuracy results
		list_metrics_clsf = []

Sourcery Starbot ⭐ refactored curenosm/MeIA #3

Are you sure you want to change the base?

Sourcery Starbot ⭐ refactored curenosm/MeIA #3

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SourceryAI commented Dec 10, 2023

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