spacing fixed

changing tab for spaces to build correctly
MachineLearningBCAM · Sep 21, 2021 · 65e4da8 · 65e4da8
1 parent c732892
commit 65e4da8
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Showing 5 changed files with 11 additions and 8 deletions.
diff --git a/MRCpy/base_mrc.py b/MRCpy/base_mrc.py
@@ -185,7 +185,7 @@ def fit(self, X, Y):
         elif self.phi == 'linear':
             self.phi = BasePhi(n_classes=n_classes,
                                fit_intercept=self.fit_intercept,
-							   **self.phi_kwargs)
+                               **self.phi_kwargs)
         elif self.phi == 'threshold':
             self.phi = ThresholdPhi(n_classes=n_classes,
                                     fit_intercept=self.fit_intercept,

diff --git a/MRCpy/phi/base_phi.py b/MRCpy/phi/base_phi.py
@@ -70,7 +70,7 @@ def __init__(self, n_classes, fit_intercept=True, one_hot=False):
 
         self.n_classes = n_classes
         self.fit_intercept = fit_intercept
-        self.one_hot=one_hot
+        self.one_hot = one_hot
 
     def fit(self, X, Y=None):
         '''

diff --git a/MRCpy/phi/random_fourier_phi.py b/MRCpy/phi/random_fourier_phi.py
@@ -41,7 +41,7 @@ class RandomFourierPhi(BasePhi):
             Whether to calculate the intercept.
             If set to false, no intercept will be used in calculations
             (i.e. data is expected to be already centered).
-            
+
     one_hot : bool, default=False
         Only applies in the binary case, namely, only when there are two
         classes. If set to true, one-hot-encoding will be used. If set to
@@ -86,7 +86,8 @@ def __init__(self, n_classes, fit_intercept=True, gamma='avg_ann_50',
                  n_components=300, random_state=None, one_hot=False):
 
         # Call the base class init function.
-        super().__init__(n_classes=n_classes, fit_intercept=fit_intercept, one_hot=one_hot)
+        super().__init__(n_classes=n_classes, fit_intercept=fit_intercept,
+                         one_hot=one_hot)
 
         self.gamma = gamma
         self.n_components = n_components

diff --git a/MRCpy/phi/random_relu_phi.py b/MRCpy/phi/random_relu_phi.py
@@ -37,7 +37,7 @@ class RandomReLUPhi(BasePhi):
             Whether to calculate the intercept.
             If set to false, no intercept will be used in calculations
             (i.e. data is expected to be already centered).
-            
+
     one_hot : bool, default=False
         Only applies in the binary case, namely, only when there are two
         classes. If set to true, one-hot-encoding will be used. If set to
@@ -82,7 +82,8 @@ def __init__(self, n_classes, fit_intercept=True, gamma='avg_ann_50',
                  n_components=300, random_state=None, one_hot=False):
 
         # Call the base class init function.
-        super().__init__(n_classes=n_classes, fit_intercept=fit_intercept, one_hot=one_hot)
+        super().__init__(n_classes=n_classes, fit_intercept=fit_intercept,
+                         one_hot=one_hot)
 
         self.gamma = gamma
         self.n_components = n_components

diff --git a/MRCpy/phi/threshold_phi.py b/MRCpy/phi/threshold_phi.py
@@ -30,7 +30,7 @@ class ThresholdPhi(BasePhi):
             Whether to calculate the intercept.
             If set to false, no intercept will be used in calculations
             (i.e. data is expected to be already centered).
-            
+
     one_hot : bool, default=False
         Only applies in the binary case, namely, only when there are two
         classes. If set to true, one-hot-encoding will be used. If set to
@@ -62,7 +62,8 @@ def __init__(self, n_classes, fit_intercept=True,
                  n_thresholds=200, one_hot=False):
 
         # Call the base class init function.
-        super().__init__(n_classes=n_classes, fit_intercept=fit_intercept, one_hot=one_hot)
+        super().__init__(n_classes=n_classes, fit_intercept=fit_intercept,
+                         one_hot=one_hot)
 
         self.n_thresholds = n_thresholds