Merge pull request #3 from Jimmy-INL/cleaningGQR

Cleaning gqr

Author: niharika2999

examples/basis_comparison-Copy1.ipynb

@@ -43,9 +43,9 @@ def matrix_representation(self, n_basis_modes=None, copy=False):
         n_basis_modes = self._validate_input(n_basis_modes)
 
         if copy:
-            return self.basis_matrix_[:, :n_basis_modes].copy()#self.original_data @
+            return self.basis_matrix_[:, :n_basis_modes].copy()
         else:
-            return self.basis_matrix_[:, :n_basis_modes]#self.original_data @
+            return self.basis_matrix_[:, :n_basis_modes]
 
     def _validate_input(self, n_basis_modes):
         """

examples/cost_constrained_qr.ipynb

@@ -6,7 +6,6 @@
 from warnings import warn
 
 from numpy import identity
-import numpy as np
 from sklearn.base import BaseEstimator
 from sklearn.utils import check_array
 
@@ -53,6 +52,7 @@ def fit(self, X):
         -------
         self : instance
         """
+
         # Note that we take a transpose here, so columns correspond to examples
         if self.n_basis_modes is None:
             self.basis_matrix_ = check_array(X).T.copy()
@@ -65,7 +65,7 @@ def fit(self, X):
                     )
                 )
 
-            self.basis_matrix_ = check_array(X)[: self.n_basis_modes, :].T.copy() # np.eye(X.shape[1])[:,:self.n_basis_modes]
+            self.basis_matrix_ = check_array(X)[: self.n_basis_modes, :].T.copy()
 
             if self.n_basis_modes < X.shape[0]:
                 warn(f"Only the first {self.n_basis_modes} examples were retained.")

examples/region_optimal.ipynb

@@ -259,7 +259,7 @@ def fit(
 
         if self.threshold is None:
             # Chosen as in Brunton et al. (2016)
-            threshold = np.sqrt(np.sum(s**2)) / (
+            threshold = np.sqrt(np.sum(s ** 2)) / (
                 2 * self.basis_matrix_inverse_.shape[0] * n_classes
             )
         else: