Test normalize function in data.py

yenchenlin · yenchenlin · commit 16829dcc0d6e · 2016-03-23T10:58:28.000+08:00
diff --git a/sklearn/preprocessing/tests/test_data.py b/sklearn/preprocessing/tests/test_data.py
@@ -1270,6 +1270,39 @@ def test_normalize():
     assert_raises(ValueError, normalize, [[0]], norm='l3')
 
 
+def test_normalize_l1():
+    rs = np.random.RandomState(0)
+    X_dense = rs.rand(10, 5)
+    X_sparse = sparse.csr_matrix(X_dense)
+    ones = np.ones((10))
+    for X in (X_dense, X_sparse):
+        for dtype in (np.float32, np.float64):
+            X = X.astype(dtype)
+            X_norm = normalize(X, norm='l1')
+            assert_equal(X_norm.dtype, dtype)
+
+            X_norm = toarray(X_norm)
+            row_sums = np.abs(X_norm).sum(axis=1)
+            assert_array_almost_equal(row_sums, ones)
+
+
+def test_normalize_l2():
+    rs = np.random.RandomState(0)
+    X_dense = rs.rand(10, 5)
+    X_sparse = sparse.csr_matrix(X_dense)
+    ones = np.ones((10))
+    for X in (X_dense, X_sparse):
+        for dtype in (np.float32, np.float64):
+            X = X.astype(dtype)
+            X_norm = normalize(X, norm='l2')
+            assert_equal(X_norm.dtype, dtype)
+
+            X_norm = toarray(X_norm)
+            X_norm_squared = X_norm**2
+            row_sums = X_norm_squared.sum(axis=1)
+            assert_array_almost_equal(row_sums, ones)
+
+
 def test_binarizer():
     X_ = np.array([[1, 0, 5], [2, 3, -1]])
 
