10000 Linted code · scikit-learn/scikit-learn@bb40fd2 · GitHub
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rithvikraorithvikrao
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3 files changed

+12
-6
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‎sklearn/linear_model/_base.py

Lines changed: 7 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -543,16 +543,17 @@ def rmatvec(b):
543543
for j in range(y.shape[1]))
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self.coef_ = np.vstack([out[0] for out in outs])
545545
self._residues = np.vstack([out[3] for out in outs])
546-
elif X.shape[1] <= 2 and np.all(np.linalg.eigvals(np.dot(X, np.transpose(X))) > 0):
546+
elif (X.shape[1] <= 2
547+
and np.all(np.linalg.eigvals(np.dot(X, np.transpose(X))) > 0)):
547548
n_samples, n_features = X.shape
548549
if y.ndim == 1:
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y = y.reshape(-1, 1)
550551
n_samples_, n_targets = y.shape
551552
alpha = np.asarray(0, dtype=X.dtype).ravel()
552553
if alpha.size not in [1, n_targets]:
553-
raise ValueError("Number of targets and number of penalties "
554-
"do not correspond: %d != %d"
555-
% (alpha.size, n_targets))
554+
raise ValueError("Number of targets and number of penalties"
555+
"do not correspond: %d != %d"
556+
% (alpha.size, n_targets))
556557

557558
if alpha.size == 1 and n_targets > 1:
558559
alpha = np.repeat(alpha, n_targets)
@@ -562,7 +563,8 @@ def rmatvec(b):
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try:
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dual_coef = _solve_cholesky_kernel(K, y, alpha)
564565

565-
self.coef_ = safe_sparse_dot(X.T, dual_coef, dense_output=True).T
566+
self.coef_ = safe_sparse_dot(X.T, dual_coef,
567+
dense_output=True).T
566568
except linalg.LinAlgError:
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# use SVD solver if matrix is singular
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self.coef_ = _solve_svd(X, y, alpha)

‎sklearn/linear_model/_ridge.py

Lines changed: 4 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -17,7 +17,10 @@
1717
from scipy import sparse
1818

1919
from ._base import LinearClassifierMixin, LinearModel, _rescale_data
20-
from ._ridge_solvers import _solve_sparse_cg, _solve_lsqr, _solve_cholesky, _solve_cholesky_kernel, _solve_svd
20+
from ._ridge_solvers import (
21+
_solve_sparse_cg, _solve_lsqr, _solve_cholesky,
22+
_solve_cholesky_kernel, _solve_svd
23+
)
2124
from ._sag import sag_solver
2225
from ..base import RegressorMixin, MultiOutputMixin, is_classifier
2326
from ..utils.extmath import safe_sparse_dot

‎sklearn/linear_model/_ridge_solvers.py

Lines changed: 1 addition & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -8,6 +8,7 @@
88
from ..exceptions import ConvergenceWarning
99
from scipy.sparse import linalg as sp_linalg
1010

11+
1112
def _solve_sparse_cg(X, y, alpha, max_iter=None, tol=1e-3, verbose=0,
1213
X_offset=None, X_scale=None):
1314

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