ENH: Allow 0-d indexes in np.take

doc/release/1.8.0-notes.rst

@@ -37,6 +37,7 @@ Changes
 General
 -------
 
+The function np.take now allows 0-d arrays as indices.
 
 Deprecations
 ============

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

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++) {

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()