Merge pull request #19899 from arunppsg/issue16751_add_note_to_docs

DOC: replace return type in np.ma.* docstring

2 files changed, 83 insertions, 11 deletions

diff --git a/numpy/ma/core.py b/numpy/ma/core.py
index 7e2d744a3..2ff1667ba 100644
--- a/numpy/ma/core.py
+++ b/numpy/ma/core.py
@@ -68,13 +68,13 @@ __all__ = [
     'masked_singleton', 'masked_values', 'masked_where', 'max', 'maximum',
     'maximum_fill_value', 'mean', 'min', 'minimum', 'minimum_fill_value',
     'mod', 'multiply', 'mvoid', 'ndim', 'negative', 'nomask', 'nonzero',
-    'not_equal', 'ones', 'outer', 'outerproduct', 'power', 'prod',
+    'not_equal', 'ones', 'ones_like', 'outer', 'outerproduct', 'power', 'prod',
     'product', 'ptp', 'put', 'putmask', 'ravel', 'remainder',
     'repeat', 'reshape', 'resize', 'right_shift', 'round', 'round_',
     'set_fill_value', 'shape', 'sin', 'sinh', 'size', 'soften_mask',
     'sometrue', 'sort', 'sqrt', 'squeeze', 'std', 'subtract', 'sum',
     'swapaxes', 'take', 'tan', 'tanh', 'trace', 'transpose', 'true_divide',
-    'var', 'where', 'zeros',
+    'var', 'where', 'zeros', 'zeros_like',
     ]
 
 MaskType = np.bool_
@@ -8159,8 +8159,18 @@ arange = _convert2ma(
     np_ret='arange : ndarray',
     np_ma_ret='arange : MaskedArray',
 )
-clip = np.clip
-diff = np.diff
+clip = _convert2ma(
+    'clip',
+    params=dict(fill_value=None, hardmask=False),
+    np_ret='clipped_array : ndarray',
+    np_ma_ret='clipped_array : MaskedArray',
+)
+diff = _convert2ma(
+    'diff',
+    params=dict(fill_value=None, hardmask=False),
+    np_ret='diff : ndarray',
+    np_ma_ret='diff : MaskedArray',
+)
 empty = _convert2ma(
     'empty', 
     params=dict(fill_value=None, hardmask=False),
@@ -8188,22 +8198,40 @@ identity = _convert2ma(
     np_ret='out : ndarray',
     np_ma_ret='out : MaskedArray',
 )
-indices = np.indices
+indices = _convert2ma(
+    'indices',
+    params=dict(fill_value=None, hardmask=False),
+    np_ret='grid : one ndarray or tuple of ndarrays',
+    np_ma_ret='grid : one MaskedArray or tuple of MaskedArrays',
+)
 ones = _convert2ma(
     'ones',
     params=dict(fill_value=None, hardmask=False),
     np_ret='out : ndarray',
     np_ma_ret='out : MaskedArray',
 )
-ones_like = np.ones_like
-squeeze = np.squeeze
+ones_like = _convert2ma(
+    'ones_like',
+    np_ret='out : ndarray',
+    np_ma_ret='out : MaskedArray',
+)
+squeeze = _convert2ma(
+    'squeeze',
+    params=dict(fill_value=None, hardmask=False),
+    np_ret='squeezed : ndarray',
+    np_ma_ret='squeezed : MaskedArray',
+)
 zeros = _convert2ma(
     'zeros',
     params=dict(fill_value=None, hardmask=False),
     np_ret='out : ndarray',
     np_ma_ret='out : MaskedArray',
 )
-zeros_like = np.zeros_like
+zeros_like = _convert2ma(
+    'zeros_like',
+    np_ret='out : ndarray',
+    np_ma_ret='out : MaskedArray',
+)
 
 
 def append(a, b, axis=None):
diff --git a/numpy/ma/tests/test_core.py b/numpy/ma/tests/test_core.py
index 7e9522b3a..bf95c999a 100644
--- a/numpy/ma/tests/test_core.py
+++ b/numpy/ma/tests/test_core.py
@@ -43,9 +43,9 @@ from numpy.ma.core import (
     masked_less, masked_less_equal, masked_not_equal, masked_outside,
     masked_print_option, masked_values, masked_where, max, maximum,
     maximum_fill_value, min, minimum, minimum_fill_value, mod, multiply,
-    mvoid, nomask, not_equal, ones, outer, power, product, put, putmask,
-    ravel, repeat, reshape, resize, shape, sin, sinh, sometrue, sort, sqrt,
-    subtract, sum, take, tan, tanh, transpose, where, zeros,
+    mvoid, nomask, not_equal, ones, ones_like, outer, power, product, put,
+    putmask, ravel, repeat, reshape, resize, shape, sin, sinh, sometrue, sort,
+    sqrt, subtract, sum, take, tan, tanh, transpose, where, zeros, zeros_like,
     )
 from numpy.compat import pickle
 
@@ -3229,6 +3229,50 @@ class TestMaskedArrayMethods:
         b = a.view(masked_array)
         assert_(np.may_share_memory(a.mask, b.mask))
 
+    def test_zeros(self):
+        # Tests zeros/like
+        datatype = [('a', int), ('b', float), ('c', '|S8')]
+        a = masked_array([(1, 1.1, '1.1'), (2, 2.2, '2.2'), (3, 3.3, '3.3')],
+                         dtype=datatype)
+        assert_equal(len(a.fill_value.item()), len(datatype))
+
+        b = zeros(len(a), dtype=datatype)
+        assert_equal(b.shape, a.shape)
+        assert_equal(b.fill_value, a.fill_value)
+
+        b = zeros_like(a)
+        assert_equal(b.shape, a.shape)
+        assert_equal(b.fill_value, a.fill_value)
+
+        # check zeros_like mask handling
+        a = masked_array([1, 2, 3], mask=[False, True, False])
+        b = zeros_like(a)
+        assert_(not np.may_share_memory(a.mask, b.mask))
+        b = a.view()
+        assert_(np.may_share_memory(a.mask, b.mask))
+
+    def test_ones(self):
+        # Tests ones/like
+        datatype = [('a', int), ('b', float), ('c', '|S8')]
+        a = masked_array([(1, 1.1, '1.1'), (2, 2.2, '2.2'), (3, 3.3, '3.3')],
+                         dtype=datatype)
+        assert_equal(len(a.fill_value.item()), len(datatype))
+
+        b = ones(len(a), dtype=datatype)
+        assert_equal(b.shape, a.shape)
+        assert_equal(b.fill_value, a.fill_value)
+
+        b = ones_like(a)
+        assert_equal(b.shape, a.shape)
+        assert_equal(b.fill_value, a.fill_value)
+
+        # check ones_like mask handling
+        a = masked_array([1, 2, 3], mask=[False, True, False])
+        b = ones_like(a)
+        assert_(not np.may_share_memory(a.mask, b.mask))
+        b = a.view()
+        assert_(np.may_share_memory(a.mask, b.mask))
+
     @suppress_copy_mask_on_assignment
     def test_put(self):
         # Tests put.