ENH: reimplement may_share_memory in C to improve its performance

numpy/add_newdocs.py

@@ -3826,6 +3826,45 @@ def luf(lamdaexpr, *args, **kwargs):
     """)
 
 
+add_newdoc('numpy.core.multiarray', 'may_share_memory',
+    """
+    may_share_memory(a, b, max_work=None)
+
+    Determine if two arrays might share memory
+
+    A return of True does not necessarily mean that the two arrays
+    share any element.  It just means that they *might*.
+
+    Only the memory bounds of a and b are checked by default.
+
+    Parameters
+    ----------
+    a, b : ndarray
+        Input arrays
+    max_work : int, optional
+        Effort to spend on solving the overlap problem.  See
+        `shares_memory` for details.  Default for ``may_share_memory``
+        is to do a bounds check.
+
+    Returns
+    -------
+    out : bool
+
+    See Also
+    --------
+    shares_memory
+
+    Examples
+    --------
+    >>> np.may_share_memory(np.array([1,2]), np.array([5,8,9]))
+    False
+    >>> x = np.zeros([3, 4])
+    >>> np.may_share_memory(x[:,0], x[:,1])
+    True
+
+    """)
+
+
 add_newdoc('numpy.core.multiarray', 'ndarray', ('newbyteorder',
     """
     arr.newbyteorder(new_order='S')

numpy/core/function_base.py

@@ -1,6 +1,6 @@
 from __future__ import division, absolute_import, print_function
 
-__all__ = ['logspace', 'linspace', 'may_share_memory']
+__all__ = ['logspace', 'linspace']
 
 from . import numeric as _nx
 from .numeric import result_type, NaN, shares_memory, MAY_SHARE_BOUNDS, TooHardError
@@ -201,46 +201,3 @@ def logspace(start, stop, num=50, endpoint=True, base=10.0, dtype=None):
     if dtype is None:
         return _nx.power(base, y)
     return _nx.power(base, y).astype(dtype)
-
-
-def may_share_memory(a, b, max_work=None):
-    """Determine if two arrays can share memory
-
-    A return of True does not necessarily mean that the two arrays
-    share any element.  It just means that they *might*.
-
-    Only the memory bounds of a and b are checked by default.
-
-    Parameters
-    ----------
-    a, b : ndarray
-        Input arrays
-    max_work : int, optional
-        Effort to spend on solving the overlap problem.  See
-        `shares_memory` for details.  Default for ``may_share_memory``
-        is to do a bounds check.
-
-    Returns
-    -------
-    out : bool
-
-    See Also
-    --------
-    shares_memory
-
-    Examples
-    --------
-    >>> np.may_share_memory(np.array([1,2]), np.array([5,8,9]))
-    False
-    >>> x = np.zeros([3, 4])
-    >>> np.may_share_memory(x[:,0], x[:,1])
-    True
-
-    """
-    if max_work is None:
-        max_work = MAY_SHARE_BOUNDS
-    try:
-        return shares_memory(a, b, max_work=max_work)
-    except (TooHardError, OverflowError):
-        # Unable to determine, assume yes
-        return True

numpy/core/numeric.py

@@ -41,7 +41,8 @@
     'Inf', 'inf', 'infty', 'Infinity', 'nan', 'NaN', 'False_', 'True_',
     'bitwise_not', 'CLIP', 'RAISE', 'WRAP', 'MAXDIMS', 'BUFSIZE',
     'ALLOW_THREADS', 'ComplexWarning', 'full', 'full_like', 'matmul',
-    'shares_memory', 'MAY_SHARE_BOUNDS', 'MAY_SHARE_EXACT', 'TooHardError',
+    'shares_memory', 'may_share_memory', 'MAY_SHARE_BOUNDS', 'MAY_SHARE_EXACT',
+    'TooHardError',
     ]
 
 if sys.version_info[0] < 3:
@@ -384,6 +385,7 @@ def extend_all(module):
 fromfile = multiarray.fromfile
 frombuffer = multiarray.frombuffer
 shares_memory = multiarray.shares_memory
+may_share_memory = multiarray.may_share_memory
 if sys.version_info[0] < 3:
     newbuffer = multiarray.newbuffer
     getbuffer = multiarray.getbuffer

numpy/core/src/multiarray/multiarraymodule.c

@@ -3989,7 +3989,8 @@ test_interrupt(PyObject *NPY_UNUSED(self), PyObject *args)
 
 
 static PyObject *
-array_shares_memory(PyObject *NPY_UNUSED(ignored), PyObject *args, PyObject *kwds)
+array_shares_memory_impl(PyObject *args, PyObject *kwds, Py_ssize_t default_max_work,
+                         int raise_exceptions)
 {
     PyArrayObject * self = NULL;
     PyArrayObject * other = NULL;
@@ -3998,9 +3999,11 @@ array_shares_memory(PyObject *NPY_UNUSED(ignored), PyObject *args, PyObject *kwd
 
     mem_overlap_t result;
     static PyObject *too_hard_cls = NULL;
-    Py_ssize_t max_work = NPY_MAY_SHARE_EXACT;
+    Py_ssize_t max_work;
     NPY_BEGIN_THREADS_DEF;
 
+    max_work = default_max_work;
+
     if (!PyArg_ParseTupleAndKeywords(args, kwds, "O&O&|O", kwlist,
                                      PyArray_Converter, &self,
                                      PyArray_Converter, &other,
@@ -4043,17 +4046,29 @@ array_shares_memory(PyObject *NPY_UNUSED(ignored), PyObject *args, PyObject *kwd
         Py_RETURN_TRUE;
     }
     else if (result == MEM_OVERLAP_OVERFLOW) {
-        PyErr_SetString(PyExc_OverflowError,
-                        "Integer overflow in computing overlap");
-        return NULL;
+        if (raise_exceptions) {
+            PyErr_SetString(PyExc_OverflowError,
+                            "Integer overflow in computing overlap");
+            return NULL;
+        }
+        else {
+            /* Don't know, so say yes */
+            Py_RETURN_TRUE;
+        }
     }
     else if (result == MEM_OVERLAP_TOO_HARD) {
-        npy_cache_import("numpy.core._internal", "TooHardError",
-                         &too_hard_cls);
-        if (too_hard_cls) {
-            PyErr_SetString(too_hard_cls, "Exceeded max_work");
+        if (raise_exceptions) {
+            npy_cache_import("numpy.core._internal", "TooHardError",
+                             &too_hard_cls);
+            if (too_hard_cls) {
+                PyErr_SetString(too_hard_cls, "Exceeded max_work");
+            }
+            return NULL;
+        }
+        else {
+            /* Don't know, so say yes */
+            Py_RETURN_TRUE;
         }
-        return NULL;
     }
     else {
         /* Doesn't happen usually */
@@ -4069,6 +4084,20 @@ array_shares_memory(PyObject *NPY_UNUSED(ignored), PyObject *args, PyObject *kwd
 }
 
 
+static PyObject *
+array_shares_memory(PyObject *NPY_UNUSED(ignored), PyObject *args, PyObject *kwds)
+{
+    return array_shares_memory_impl(args, kwds, NPY_MAY_SHARE_EXACT, 1);
+}
+
+
+static PyObject *
+array_may_share_memory(PyObject *NPY_UNUSED(ignored), PyObject *args, PyObject *kwds)
+{
+    return array_shares_memory_impl(args, kwds, NPY_MAY_SHARE_BOUNDS, 0);
+}
+
+
 static struct PyMethodDef array_module_methods[] = {
     {"_get_ndarray_c_version",
         (PyCFunction)array__get_ndarray_c_version,
@@ -4178,6 +4207,9 @@ static struct PyMethodDef array_module_methods[] = {
     {"shares_memory",
         (PyCFunction)array_shares_memory,
         METH_VARARGS | METH_KEYWORDS, NULL},
+    {"may_share_memory",
+        (PyCFunction)array_may_share_memory,
+        METH_VARARGS | METH_KEYWORDS, NULL},
     /* Datetime-related functions */
     {"datetime_data",
         (PyCFunction)array_datetime_data,