From 5bf5266eb2c39767843d5ae40c4f6b6fa4a8ae83 Mon Sep 17 00:00:00 2001
From: Gael Varoquaux <gael.varoquaux@normalesup.org>
Date: Sun, 6 May 2012 19:04:19 +0200
Subject: [PATCH] ENH: make LinearSVC copyiable
Fixes #820
---
sklearn/svm/base.py | 5 +++++
sklearn/svm/tests/test_svm.py | 15 +++++++++++++--
2 files changed, 18 insertions(+), 2 deletions(-)
diff --git a/sklearn/svm/base.py b/sklearn/svm/base.py
index 2dfe119ef0..1c56302110 100644
--- a/sklearn/svm/base.py
+++ b/sklearn/svm/base.py
@@ -755,6 +755,11 @@ class BaseLibLinear(BaseEstimator):
raise ValueError(
"cannot use sparse input in %r trained on dense data"
% type(self).__name__)
+ if not self.raw_coef_.flags['F_CONTIGUOUS']:
+ warnings.warn('Coefficients are the fortran-contiguous. '
+ 'Copying them.', RuntimeWarning,
+ stacklevel=3)
+ self.raw_coef_ = np.asfortranarray(self.raw_coef_)
return X
def _get_intercept_(self):
diff --git a/sklearn/svm/tests/test_svm.py b/sklearn/svm/tests/test_svm.py
index e8af5fc5f1..b77eca63f9 100644
--- a/sklearn/svm/tests/test_svm.py
+++ b/sklearn/svm/tests/test_svm.py
@@ -3,11 +3,13 @@ Testing for Support Vector Machine module (sklearn.svm)
TODO: remove hard coded numerical results when possible
"""
+import copy
+import warnings
import numpy as np
from numpy.testing import assert_array_equal, assert_array_almost_equal, \
assert_almost_equal
-from nose.tools import assert_raises, assert_true
+from nose.tools import assert_raises, assert_true, assert_equal
from sklearn import svm, linear_model, datasets, metrics, base
from sklearn.datasets.samples_generator import make_classification
@@ -151,7 +153,7 @@ def test_precomputed():
assert_almost_equal(np.mean(pred == iris.target), .99, decimal=2)
-def test_SVR():
+def test_svr():
"""
Test Support Vector Regression
"""
@@ -598,6 +600,15 @@ def test_linearsvc_verbose():
os.dup2(stdout, 1) # restore original stdout
+def test_linearsvc_deepcopy():
+ rng = check_random_state(0)
+ clf = svm.LinearSVC()
+ clf.fit(rng.rand(10, 2), rng.randint(0, 2, size=10))
+ with warnings.catch_warnings(record=True) as warn_queue:
+ copy.deepcopy(clf).predict(rng.rand(2))
+ assert_equal(len(warn_queue), 1)
+
+
def test_svc_clone_with_callable_kernel():
a = svm.SVC(kernel=lambda x, y: np.dot(x, y.T), probability=True)
b = base.clone(a)
--
GitLab