TST Extend tests for scipy.sparse.*array in sklearn/linear_model/tests/test_perceptron.py (scikit-learn#27160)

Author: IsaacTrost

sklearn/linear_model/tests/test_perceptron.py

@@ -1,20 +1,18 @@
 import numpy as np
 import pytest
-import scipy.sparse as sp
 
 from sklearn.datasets import load_iris
 from sklearn.linear_model import Perceptron
 from sklearn.utils import check_random_state
 from sklearn.utils._testing import assert_allclose, assert_array_almost_equal
+from sklearn.utils.fixes import CSR_CONTAINERS
 
 iris = load_iris()
 random_state = check_random_state(12)
 indices = np.arange(iris.data.shape[0])
 random_state.shuffle(indices)
 X = iris.data[indices]
 y = iris.target[indices]
-X_csr = sp.csr_matrix(X)
-X_csr.sort_indices()
 
 
 class MyPerceptron:
@@ -40,12 +38,13 @@ def predict(self, X):
         return np.sign(self.project(X))
 
 
-def test_perceptron_accuracy():
-    for data in (X, X_csr):
-        clf = Perceptron(max_iter=100, tol=None, shuffle=False)
-        clf.fit(data, y)
-        score = clf.score(data, y)
-        assert score > 0.7
+@pytest.mark.parametrize("container", CSR_CONTAINERS + [np.array])
+def test_perceptron_accuracy(container):
+    data = container(X)
+    clf = Perceptron(max_iter=100, tol=None, shuffle=False)
+    clf.fit(data, y)
+    score = clf.score(data, y)
+    assert score > 0.7
 
 
 def test_perceptron_correctness():