Fix two instances of memcpy with overlapping source and destination.

numpy/core/src/multiarray/lowlevel_strided_loops.c.src

@@ -151,7 +151,7 @@ static void
 #else
 
         /* unaligned copy and swap */
-        memcpy(dst, src, @elsize@);
+        memmove(dst, src, @elsize@);
 #  if @is_swap@ == 1
         @swap@@elsize@(dst);
 #  elif @is_swap@ == 2
@@ -239,7 +239,7 @@ _strided_to_strided(char *dst, npy_intp dst_stride,
                         NpyAuxData *NPY_UNUSED(data))
 {
     while (N > 0) {
-        memcpy(dst, src, src_itemsize);
+        memmove(dst, src, src_itemsize);
         dst += dst_stride;
         src += src_stride;
         --N;
@@ -255,7 +255,7 @@ _swap_strided_to_strided(char *dst, npy_intp dst_stride,
     char *a, *b, c;
 
     while (N > 0) {
-        memcpy(dst, src, src_itemsize);
+        memmove(dst, src, src_itemsize);
         /* general in-place swap */
         a = dst;
         b = dst + src_itemsize - 1;
@@ -281,7 +281,7 @@ _swap_pair_strided_to_strided(char *dst, npy_intp dst_stride,
     npy_intp itemsize_half = src_itemsize / 2;
 
     while (N > 0) {
-        memcpy(dst, src, src_itemsize);
+        memmove(dst, src, src_itemsize);
         /* general in-place swap */
         a = dst;
         b = dst + itemsize_half - 1;
@@ -312,7 +312,7 @@ _contig_to_contig(char *dst, npy_intp NPY_UNUSED(dst_stride),
                         npy_intp N, npy_intp src_itemsize,
                         NpyAuxData *NPY_UNUSED(data))
 {
-    memcpy(dst, src, src_itemsize*N);
+    memmove(dst, src, src_itemsize*N);
 }
 
 
@@ -802,7 +802,7 @@ static void
         src_value = *((_TYPE1 *)src);
 #  endif
 #else
-        memcpy(&src_value, src, sizeof(src_value));
+        memmove(&src_value, src, sizeof(src_value));
 #endif
 
 /* Do the cast */
@@ -838,7 +838,7 @@ static void
         *((_TYPE2 *)dst) = dst_value;
 #  endif
 #else
-        memcpy(dst, &dst_value, sizeof(dst_value));
+        memmove(dst, &dst_value, sizeof(dst_value));
 #endif
 
 #if @contig@

numpy/core/tests/test_multiarray_assignment.py

@@ -0,0 +1,78 @@
+import numpy as np
+from numpy.testing import TestCase
+
+ndims = 2
+size = 10
+shape = tuple([size] * ndims)
+
+
+def _indices_for_nelems(nelems):
+    """Returns slices of length nelems, from start onwards, in direction sign."""
+
+    if nelems == 0:
+        return [size // 2]  # int index
+
+    res = []
+    for step in (1, 2):
+        for sign in (-1, 1):
+            start = size // 2 - nelems * step * sign // 2
+            stop = start + nelems * step * sign
+            res.append(slice(start, stop, step * sign))
+
+    return res
+
+
+def _indices_for_axis():
+    """Returns (src, dst) pairs of indices."""
+
+    res = []
+    for nelems in (0, 2, 3):
+        ind = _indices_for_nelems(nelems)
+
+        # no itertools.product available in Py2.4
+        res.extend([(a, b) for a in ind for b in ind])  # all assignments of size "nelems"
+
+    return res
+
+
+def _indices(ndims):
+    """Returns ((axis0_src, axis0_dst), (axis1_src, axis1_dst), ... ) index pairs."""
+
+    ind = _indices_for_axis()
+
+    # no itertools.product available in Py2.4
+
+    res = [[]]
+    for i in xrange(ndims):
+        newres = []
+        for elem in ind:
+            for others in res:
+                newres.append([elem] + others)
+        res = newres
+
+    return res
+
+
+def _check_assignment(srcidx, dstidx):
+    """Check assignment arr[dstidx] = arr[srcidx] works."""
+
+    arr = np.arange(np.product(shape)).reshape(shape)
+
+    cpy = arr.copy()
+
+    cpy[dstidx] = arr[srcidx]
+    arr[dstidx] = arr[srcidx]
+
+    assert np.all(arr == cpy), 'assigning arr[%s] = arr[%s]' % (dstidx, srcidx)
+
+
+def test_overlapping_assignments():
+    """Test automatically generated assignments which overlap in memory."""
+
+    inds = _indices(ndims)
+
+    for ind in inds:
+        srcidx = tuple([a[0] for a in ind])
+        dstidx = tuple([a[1] for a in ind])
+
+        yield _check_assignment, srcidx, dstidx