ENH: Allow 0-d indexes in np.take

The TakeFrom already supported this. This removes the check which
made it not possible and adds some tests for take.

Also add documentation and information to the release notes.

3 files changed, 53 insertions, 3 deletions

diff --git a/numpy/core/fromnumeric.py b/numpy/core/fromnumeric.py
index d73f1313c..7596e3707 100644
--- a/numpy/core/fromnumeric.py
+++ b/numpy/core/fromnumeric.py
@@ -57,6 +57,10 @@ def take(a, indices, axis=None, out=None, mode='raise'):
         The source array.
     indices : array_like
         The indices of the values to extract.
+        
+        .. versionadded:: 1.8.0
+        
+        Also allow scalars for indices.
     axis : int, optional
         The axis over which to select values. By default, the flattened
         input array is used.
@@ -96,6 +100,11 @@ def take(a, indices, axis=None, out=None, mode='raise'):
     >>> a[indices]
     array([4, 3, 6])
 
+    If `indices` is not one dimensional, the output also has these dimensions.
+    
+    >>> np.take(a, [[0, 1], [2, 3]])
+    array([[4, 3],
+           [5, 7]])
     """
     try:
         take = a.take
diff --git a/numpy/core/src/multiarray/item_selection.c b/numpy/core/src/multiarray/item_selection.c
index ab8480857..0da921b62 100644
--- a/numpy/core/src/multiarray/item_selection.c
+++ b/numpy/core/src/multiarray/item_selection.c
@@ -44,13 +44,11 @@ PyArray_TakeFrom(PyArrayObject *self0, PyObject *indices0, int axis,
     }
     indices = (PyArrayObject *)PyArray_ContiguousFromAny(indices0,
                                                          NPY_INTP,
-                                                         1, 0);
+                                                         0, 0);
     if (indices == NULL) {
         goto fail;
     }
 
-
-
     n = m = chunk = 1;
     nd = PyArray_NDIM(self) + PyArray_NDIM(indices) - 1;
     for (i = 0; i < nd; i++) {
diff --git a/numpy/core/tests/test_item_selection.py b/numpy/core/tests/test_item_selection.py
new file mode 100644
index 000000000..f35e04c4f
--- /dev/null
+++ b/numpy/core/tests/test_item_selection.py
@@ -0,0 +1,43 @@
+import numpy as np
+from numpy.testing import *
+import sys, warnings
+
+def test_take():
+    a = [[1, 2], [3, 4]]
+    a_str = [['1','2'],['3','4']]
+    modes = ['raise', 'wrap', 'clip']
+    indices = [-1, 4]
+    index_arrays = [np.empty(0, dtype=np.intp),
+                    np.empty(tuple(), dtype=np.intp),
+                    np.empty((1,1), dtype=np.intp)]
+    real_indices = {}
+    real_indices['raise'] = {-1:1, 4:IndexError}
+    real_indices['wrap'] = {-1:1, 4:0}
+    real_indices['clip'] = {-1:0, 4:1}
+    # Currently all types but object, use the same function generation.
+    # So it should not be necessary to test all, but the code does support it.
+    types = np.int, np.object
+    for t in types:
+        ta = np.array(a if issubclass(t, np.number) else a_str, dtype=t)
+        tresult = list(ta.T.copy())
+        for index_array in index_arrays:
+            if index_array.size != 0:
+                tresult[0].shape = (2,) + index_array.shape
+                tresult[1].shape = (2,) + index_array.shape
+            for mode in modes:
+                for index in indices:
+                    real_index = real_indices[mode][index]
+                    if real_index is IndexError and index_array.size != 0:
+                        index_array.put(0, index)
+                        assert_raises(IndexError, ta.take, index_array,
+                                      mode=mode, axis=1)
+                    elif index_array.size != 0:
+                        index_array.put(0, index)
+                        res = ta.take(index_array, mode=mode, axis=1)
+                        assert_array_equal(res, tresult[real_index])
+                    else:
+                        res = ta.take(index_array, mode=mode, axis=1)
+                        assert_(res.shape == (2,) + index_array.shape)
+
+if __name__ == "__main__":
+    run_module_suite()