TST Manually scramble the indices in svm tests (scikit-learn#12890)

qinhanmin2014 · jnothman · commit f9687ca1bf1e · 2019-07-23T16:16:44.000+10:00
* [scipy-dev] manually scramble the indices

* [scipy-dev] review comment
diff --git a/sklearn/svm/tests/test_sparse.py b/sklearn/svm/tests/test_sparse.py
@@ -111,8 +111,19 @@ def test_unsorted_indices():
     # make sure dense and sparse SVM give the same result
     assert_array_almost_equal(coef_dense, coef_sorted.toarray())
 
-    X_sparse_unsorted = X_sparse[np.arange(X.shape[0])]
-    X_test_unsorted = X_test[np.arange(X_test.shape[0])]
+    # reverse each row's indices
+    def scramble_indices(X):
+        new_data = []
+        new_indices = []
+        for i in range(1, len(X.indptr)):
+            row_slice = slice(*X.indptr[i - 1: i + 1])
+            new_data.extend(X.data[row_slice][::-1])
+            new_indices.extend(X.indices[row_slice][::-1])
+        return sparse.csr_matrix((new_data, new_indices, X.indptr),
+                                 shape=X.shape)
+
+    X_sparse_unsorted = scramble_indices(X_sparse)
+    X_test_unsorted = scramble_indices(X_test)
 
     # make sure we scramble the indices
     assert_false(X_sparse_unsorted.has_sorted_indices)
