diff options
Diffstat (limited to 'numpy')
| -rw-r--r-- | numpy/core/fromnumeric.py | 87 | ||||
| -rw-r--r-- | numpy/core/src/multiarray/methods.c | 172 | ||||
| -rw-r--r-- | numpy/core/src/multiarray/reduction.c | 29 | ||||
| -rw-r--r-- | numpy/core/src/umath/ufunc_object.c | 26 | ||||
| -rw-r--r-- | numpy/core/src/umath/ufunc_type_resolution.c | 51 | ||||
| -rw-r--r-- | numpy/core/tests/test_regression.py | 6 |
6 files changed, 146 insertions, 225 deletions
diff --git a/numpy/core/fromnumeric.py b/numpy/core/fromnumeric.py index f3930eaa9..f374951c9 100644 --- a/numpy/core/fromnumeric.py +++ b/numpy/core/fromnumeric.py @@ -16,6 +16,7 @@ import multiarray as mu import umath as um import numerictypes as nt from numeric import asarray, array, asanyarray, concatenate +import _methods _dt_ = nt.sctype2char import types @@ -1482,12 +1483,12 @@ def sum(a, axis=None, dtype=None, out=None, skipna=False, keepdims=False): try: sum = a.sum except AttributeError: - return um.add.reduce(a, axis=axis, dtype=dtype, + return _methods._sum(a, axis=axis, dtype=dtype, out=out, skipna=skipna, keepdims=keepdims) # NOTE: Dropping the skipna and keepdims parameters here... return sum(axis=axis, dtype=dtype, out=out) else: - return um.add.reduce(a, axis=axis, dtype=dtype, + return _methods._sum(a, axis=axis, dtype=dtype, out=out, skipna=skipna, keepdims=keepdims) def product (a, axis=None, dtype=None, out=None, skipna=False, keepdims=False): @@ -1603,7 +1604,8 @@ def any(a, axis=None, out=None, skipna=False, keepdims=False): (191614240, 191614240) """ - return um.logical_or.reduce(a, axis=axis, out=out, skipna=skipna, keepdims=keepdims) + return _methods._any(a, axis=axis, out=out, + skipna=skipna, keepdims=keepdims) def all(a, axis=None, out=None, skipna=False, keepdims=False): """ @@ -1674,7 +1676,8 @@ def all(a, axis=None, out=None, skipna=False, keepdims=False): (28293632, 28293632, array([ True], dtype=bool)) """ - return um.logical_and.reduce(a, axis=axis, out=out, skipna=skipna, keepdims=keepdims) + return _methods._all(a, axis=axis, out=out, + skipna=skipna, keepdims=keepdims) def cumsum (a, axis=None, dtype=None, out=None): """ @@ -1873,12 +1876,12 @@ def amax(a, axis=None, out=None, skipna=False, keepdims=False): try: amax = a.max except AttributeError: - return um.maximum.reduce(a, axis=axis, + return _methods._amax(a, axis=axis, out=out, skipna=skipna, keepdims=keepdims) # NOTE: Dropping the skipna and keepdims parameters return amax(axis=axis, out=out) else: - return um.maximum.reduce(a, axis=axis, + return _methods._amax(a, axis=axis, out=out, skipna=skipna, keepdims=keepdims) def amin(a, axis=None, out=None, skipna=False, keepdims=False): @@ -1947,12 +1950,12 @@ def amin(a, axis=None, out=None, skipna=False, keepdims=False): try: amin = a.min except AttributeError: - return um.minimum.reduce(a, axis=axis, + return _methods._amin(a, axis=axis, out=out, skipna=skipna, keepdims=keepdims) # NOTE: Dropping the skipna and keepdims parameters return amin(axis=axis, out=out) else: - return um.minimum.reduce(a, axis=axis, + return _methods._amin(a, axis=axis, out=out, skipna=skipna, keepdims=keepdims) def alen(a): @@ -2080,11 +2083,11 @@ def prod(a, axis=None, dtype=None, out=None, skipna=False, keepdims=False): try: prod = a.prod except AttributeError: - return um.multiply.reduce(a, axis=axis, dtype=dtype, + return _methods._prod(a, axis=axis, dtype=dtype, out=out, skipna=skipna, keepdims=keepdims) return prod(axis=axis, dtype=dtype, out=out) else: - return um.multiply.reduce(a, axis=axis, dtype=dtype, + return _methods._prod(a, axis=axis, dtype=dtype, out=out, skipna=skipna, keepdims=keepdims) def cumprod(a, axis=None, dtype=None, out=None): @@ -2459,22 +2462,8 @@ def mean(a, axis=None, dtype=None, out=None, skipna=False, keepdims=False): except AttributeError: pass - arr = asarray(a) - - # Upgrade bool, unsigned int, and int to float64 - if dtype is None and arr.dtype.kind in ['b','u','i']: - ret = um.add.reduce(arr, axis=axis, dtype='f8', + return _methods._mean(a, axis=axis, dtype=dtype, out=out, skipna=skipna, keepdims=keepdims) - else: - ret = um.add.reduce(arr, axis=axis, dtype=dtype, - out=out, skipna=skipna, keepdims=keepdims) - rcount = mu.count_reduce_items(arr, axis=axis, - skipna=skipna, keepdims=keepdims) - if isinstance(ret, mu.ndarray): - um.true_divide(ret, rcount, out=ret, casting='unsafe') - else: - ret = ret / float(rcount) - return ret def std(a, axis=None, dtype=None, out=None, ddof=0, @@ -2579,16 +2568,9 @@ def std(a, axis=None, dtype=None, out=None, ddof=0, except AttributeError: pass - ret = var(a, axis=axis, dtype=dtype, out=out, ddof=ddof, + return _methods._std(a, axis=axis, dtype=dtype, out=out, ddof=ddof, skipna=skipna, keepdims=keepdims) - if isinstance(ret, mu.ndarray): - um.sqrt(ret, out=ret) - else: - ret = um.sqrt(ret) - - return ret - def var(a, axis=None, dtype=None, out=None, ddof=0, skipna=False, keepdims=False): """ @@ -2692,43 +2674,6 @@ def var(a, axis=None, dtype=None, out=None, ddof=0, except AttributeError: pass - arr = asarray(a) - - # First compute the mean, saving 'rcount' for reuse later - if dtype is None and arr.dtype.kind in ['b','u','i']: - arrmean = um.add.reduce(arr, axis=axis, dtype='f8', - skipna=skipna, keepdims=True) - else: - arrmean = um.add.reduce(arr, axis=axis, dtype=dtype, - skipna=skipna, keepdims=True) - rcount = mu.count_reduce_items(arr, axis=axis, - skipna=skipna, keepdims=True) - if isinstance(arrmean, mu.ndarray): - um.true_divide(arrmean, rcount, out=arrmean, casting='unsafe') - else: - arrmean = arrmean / float(rcount) - - # arr - arrmean - x = arr - arrmean - - # (arr - arrmean) ** 2 - if arr.dtype.kind == 'c': - um.multiply(x, um.conjugate(x), out=x) - x = x.real - else: - um.multiply(x, x, out=x) - - # add.reduce((arr - arrmean) ** 2, axis) - ret = um.add.reduce(x, axis=axis, dtype=dtype, out=out, + return _methods._var(a, axis=axis, dtype=dtype, out=out, ddof=ddof, skipna=skipna, keepdims=keepdims) - # add.reduce((arr - arrmean) ** 2, axis) / (n - ddof) - if not keepdims and isinstance(rcount, mu.ndarray): - rcount = rcount.squeeze(axis=axis) - rcount -= ddof - if isinstance(ret, mu.ndarray): - um.true_divide(ret, rcount, out=ret, casting='unsafe') - else: - ret = ret / float(rcount) - - return ret diff --git a/numpy/core/src/multiarray/methods.c b/numpy/core/src/multiarray/methods.c index 5cff8f767..afeae9a30 100644 --- a/numpy/core/src/multiarray/methods.c +++ b/numpy/core/src/multiarray/methods.c @@ -49,6 +49,54 @@ NpyArg_ParseKeywords(PyObject *keys, const char *format, char **kwlist, ...) return ret; } +/* + * Forwards an ndarray method to a the Python function + * numpy.core._methods.<name>(...) + */ +static PyObject * +forward_ndarray_method(PyArrayObject *self, PyObject *args, PyObject *kwds, + const char *name) +{ + PyObject *sargs, *ret; + PyObject *module_methods, *callable; + int i, n; + + /* Get a reference to the function we're calling */ + module_methods = PyImport_ImportModule("numpy.core._methods"); + if (module_methods == NULL) { + return NULL; + } + callable = PyDict_GetItemString(PyModule_GetDict(module_methods), name); + if (callable == NULL) { + Py_DECREF(module_methods); + PyErr_Format(PyExc_RuntimeError, + "NumPy internal error: could not find function " + "numpy.core._methods.%s", name); + return NULL; + } + + /* Combine 'self' and 'args' together into one tuple */ + n = PyTuple_GET_SIZE(args); + sargs = PyTuple_New(n + 1); + if (sargs == NULL) { + Py_DECREF(module_methods); + return NULL; + } + Py_INCREF(self); + PyTuple_SET_ITEM(sargs, 0, (PyObject *)self); + for (i = 0; i < n; ++i) { + PyObject *item = PyTuple_GET_ITEM(args, i); + Py_INCREF(item); + PyTuple_SET_ITEM(sargs, i+1, item); + } + + /* Call the function and return */ + ret = PyObject_Call(callable, sargs, kwds); + Py_DECREF(sargs); + Py_DECREF(module_methods); + return ret; +} + static PyObject * array_take(PyArrayObject *self, PyObject *args, PyObject *kwds) { @@ -292,36 +340,17 @@ array_argmin(PyArrayObject *self, PyObject *args, PyObject *kwds) static PyObject * array_max(PyArrayObject *self, PyObject *args, PyObject *kwds) { - int axis = MAX_DIMS; - PyArrayObject *out = NULL; - static char *kwlist[] = {"axis", "out", NULL}; - - if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O&O&", kwlist, - PyArray_AxisConverter, &axis, - PyArray_OutputConverter, &out)) - return NULL; - - return PyArray_Max(self, axis, out); + return forward_ndarray_method(self, args, kwds, "_amax"); } static PyObject * -array_ptp(PyArrayObject *self, PyObject *args, PyObject *kwds) +array_min(PyArrayObject *self, PyObject *args, PyObject *kwds) { - int axis = MAX_DIMS; - PyArrayObject *out = NULL; - static char *kwlist[] = {"axis", "out", NULL}; - - if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O&O&", kwlist, - PyArray_AxisConverter, &axis, - PyArray_OutputConverter, &out)) - return NULL; - - return PyArray_Ptp(self, axis, out); + return forward_ndarray_method(self, args, kwds, "_amin"); } - static PyObject * -array_min(PyArrayObject *self, PyObject *args, PyObject *kwds) +array_ptp(PyArrayObject *self, PyObject *args, PyObject *kwds) { int axis = MAX_DIMS; PyArrayObject *out = NULL; @@ -332,9 +361,10 @@ array_min(PyArrayObject *self, PyObject *args, PyObject *kwds) PyArray_OutputConverter, &out)) return NULL; - return PyArray_Min(self, axis, out); + return PyArray_Ptp(self, axis, out); } + static PyObject * array_swapaxes(PyArrayObject *self, PyObject *args) { @@ -1855,45 +1885,13 @@ _get_type_num_double(PyArray_Descr *dtype1, PyArray_Descr *dtype2) static PyObject * array_mean(PyArrayObject *self, PyObject *args, PyObject *kwds) { - int axis = MAX_DIMS; - PyArray_Descr *dtype = NULL; - PyArrayObject *out = NULL; - int num; - static char *kwlist[] = {"axis", "dtype", "out", NULL}; - - if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O&O&O&", kwlist, - PyArray_AxisConverter, &axis, - PyArray_DescrConverter2, &dtype, - PyArray_OutputConverter, &out)) { - Py_XDECREF(dtype); - return NULL; - } - - num = _get_type_num_double(PyArray_DESCR(self), dtype); - Py_XDECREF(dtype); - return PyArray_Mean(self, axis, num, out); + return forward_ndarray_method(self, args, kwds, "_mean"); } static PyObject * array_sum(PyArrayObject *self, PyObject *args, PyObject *kwds) { - int axis = MAX_DIMS; - PyArray_Descr *dtype = NULL; - PyArrayObject *out = NULL; - int rtype; - static char *kwlist[] = {"axis", "dtype", "out", NULL}; - - if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O&O&O&", kwlist, - PyArray_AxisConverter, &axis, - PyArray_DescrConverter2, &dtype, - PyArray_OutputConverter, &out)) { - Py_XDECREF(dtype); - return NULL; - } - - rtype = _CHKTYPENUM(dtype); - Py_XDECREF(dtype); - return PyArray_Sum(self, axis, rtype, out); + return forward_ndarray_method(self, args, kwds, "_sum"); } @@ -1922,23 +1920,7 @@ array_cumsum(PyArrayObject *self, PyObject *args, PyObject *kwds) static PyObject * array_prod(PyArrayObject *self, PyObject *args, PyObject *kwds) { - int axis = MAX_DIMS; - PyArray_Descr *dtype = NULL; - PyArrayObject *out = NULL; - int rtype; - static char *kwlist[] = {"axis", "dtype", "out", NULL}; - - if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O&O&O&", kwlist, - PyArray_AxisConverter, &axis, - PyArray_DescrConverter2, &dtype, - PyArray_OutputConverter, &out)) { - Py_XDECREF(dtype); - return NULL; - } - - rtype = _CHKTYPENUM(dtype); - Py_XDECREF(dtype); - return PyArray_Prod(self, axis, rtype, out); + return forward_ndarray_method(self, args, kwds, "_prod"); } static PyObject * @@ -2022,50 +2004,14 @@ array_all(PyArrayObject *self, PyObject *args, PyObject *kwds) static PyObject * array_stddev(PyArrayObject *self, PyObject *args, PyObject *kwds) { - int axis = MAX_DIMS; - PyArray_Descr *dtype = NULL; - PyArrayObject *out = NULL; - int num; - int ddof = 0; - static char *kwlist[] = {"axis", "dtype", "out", "ddof", NULL}; - - if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O&O&O&i", kwlist, - PyArray_AxisConverter, &axis, - PyArray_DescrConverter2, &dtype, - PyArray_OutputConverter, &out, - &ddof)) { - Py_XDECREF(dtype); - return NULL; - } - - num = _get_type_num_double(PyArray_DESCR(self), dtype); - Py_XDECREF(dtype); - return __New_PyArray_Std(self, axis, num, out, 0, ddof); + return forward_ndarray_method(self, args, kwds, "_std"); } static PyObject * array_variance(PyArrayObject *self, PyObject *args, PyObject *kwds) { - int axis = MAX_DIMS; - PyArray_Descr *dtype = NULL; - PyArrayObject *out = NULL; - int num; - int ddof = 0; - static char *kwlist[] = {"axis", "dtype", "out", "ddof", NULL}; - - if (!PyArg_ParseTupleAndKeywords(args, kwds, "|O&O&O&i", kwlist, - PyArray_AxisConverter, &axis, - PyArray_DescrConverter2, &dtype, - PyArray_OutputConverter, &out, - &ddof)) { - Py_XDECREF(dtype); - return NULL; - } - - num = _get_type_num_double(PyArray_DESCR(self), dtype); - Py_XDECREF(dtype); - return __New_PyArray_Std(self, axis, num, out, 1, ddof); + return forward_ndarray_method(self, args, kwds, "_var"); } diff --git a/numpy/core/src/multiarray/reduction.c b/numpy/core/src/multiarray/reduction.c index d60b07fce..94ca111a9 100644 --- a/numpy/core/src/multiarray/reduction.c +++ b/numpy/core/src/multiarray/reduction.c @@ -366,6 +366,13 @@ initialize_reduce_result_noidentity_skipna( goto fail; } + /* + * Track how many initializations we've done, both to + * short circuit completion and to raise an error if + * any remained uninitialized. + */ + initialized_countdown = PyArray_SIZE(result); + if (NpyIter_GetIterSize(iter) != 0) { NpyIter_IterNextFunc *iternext; char **dataptr; @@ -381,13 +388,6 @@ initialize_reduce_result_noidentity_skipna( strideptr = NpyIter_GetInnerStrideArray(iter); countptr = NpyIter_GetInnerLoopSizePtr(iter); - /* - * Track how many initializations we've done, both to - * short circuit completion and to raise an error if - * any remained uninitialized. - */ - initialized_countdown = PyArray_SIZE(result); - if (!needs_api) { NPY_BEGIN_THREADS; } @@ -870,7 +870,7 @@ PyArray_ReduceWrapper(PyArrayObject *operand, PyArrayObject *out, */ if (!reorderable && check_nonreorderable_axes(PyArray_NDIM(operand), axis_flags, funcname) < 0) { - return NULL; + goto fail; } if (assign_identity(result, !skipna, data) < 0) { @@ -884,8 +884,7 @@ PyArray_ReduceWrapper(PyArrayObject *operand, PyArrayObject *out, axis_flags, reorderable, skipna, &skip_first_count, funcname); if (op_view == NULL) { - Py_DECREF(result); - return NULL; + goto fail; } if (PyArray_SIZE(op_view) == 0) { Py_DECREF(op_view); @@ -943,9 +942,7 @@ PyArray_ReduceWrapper(PyArrayObject *operand, PyArrayObject *out, op_dtypes, 0, NULL, NULL, buffersize); if (iter == NULL) { - Py_DECREF(result); - Py_DECREF(op_dtypes[0]); - return NULL; + goto fail; } if (NpyIter_GetIterSize(iter) != 0) { @@ -957,10 +954,7 @@ PyArray_ReduceWrapper(PyArrayObject *operand, PyArrayObject *out, iternext = NpyIter_GetIterNext(iter, NULL); if (iternext == NULL) { - Py_DECREF(result); - Py_DECREF(op_dtypes[0]); - NpyIter_Deallocate(iter); - return NULL; + goto fail; } dataptr = NpyIter_GetDataPtrArray(iter); strideptr = NpyIter_GetInnerStrideArray(iter); @@ -1000,6 +994,7 @@ PyArray_ReduceWrapper(PyArrayObject *operand, PyArrayObject *out, } NpyIter_Deallocate(iter); + Py_DECREF(op_view); finish: /* Strip out the extra 'one' dimensions in the result */ diff --git a/numpy/core/src/umath/ufunc_object.c b/numpy/core/src/umath/ufunc_object.c index 9de0e7ef5..46513cda1 100644 --- a/numpy/core/src/umath/ufunc_object.c +++ b/numpy/core/src/umath/ufunc_object.c @@ -2536,6 +2536,7 @@ reduce_type_resolver(PyUFuncObject *ufunc, PyArrayObject *arr, retcode = ufunc->type_resolver( ufunc, NPY_UNSAFE_CASTING, op, type_tup, dtypes); + Py_DECREF(type_tup); if (retcode == -1) { return -1; } @@ -2806,6 +2807,8 @@ PyUFunc_Reduce(PyUFuncObject *ufunc, PyArrayObject *arr, PyArrayObject *out, int buffersize = 0, errormask = 0; PyObject *errobj = NULL; + NPY_UF_DBG_PRINT1("\nEvaluating ufunc %s.reduce\n", ufunc_name); + ndim = PyArray_NDIM(arr); /* Create an array of flags for reduction */ @@ -3628,7 +3631,7 @@ static PyObject * PyUFunc_GenericReduction(PyUFuncObject *ufunc, PyObject *args, PyObject *kwds, int operation) { - int i, naxes=0; + int i, naxes=0, ndim; int axes[NPY_MAXDIMS]; PyObject *axes_in = NULL; PyArrayObject *mp, *ret = NULL; @@ -3712,6 +3715,9 @@ PyUFunc_GenericReduction(PyUFuncObject *ufunc, PyObject *args, if (mp == NULL) { return NULL; } + + ndim = PyArray_NDIM(mp); + /* Check to see that type (and otype) is not FLEXIBLE */ if (PyArray_ISFLEXIBLE(mp) || (otype && PyTypeNum_ISFLEXIBLE(otype->type_num))) { @@ -3730,7 +3736,7 @@ PyUFunc_GenericReduction(PyUFuncObject *ufunc, PyObject *args, } /* Convert 'None' into all the axes */ else if (axes_in == Py_None) { - naxes = PyArray_NDIM(mp); + naxes = ndim; for (i = 0; i < naxes; ++i) { axes[i] = i; } @@ -3753,9 +3759,9 @@ PyUFunc_GenericReduction(PyUFuncObject *ufunc, PyObject *args, return NULL; } if (axis < 0) { - axis += PyArray_NDIM(mp); + axis += ndim; } - if (axis < 0 || axis >= PyArray_NDIM(mp)) { + if (axis < 0 || axis >= ndim) { PyErr_SetString(PyExc_ValueError, "'axis' entry is out of bounds"); Py_XDECREF(otype); @@ -3775,11 +3781,13 @@ PyUFunc_GenericReduction(PyUFuncObject *ufunc, PyObject *args, return NULL; } if (axis < 0) { - axis += PyArray_NDIM(mp); + axis += ndim; + } + /* Special case letting axis={0 or -1} slip through for scalars */ + if (ndim == 0 && (axis == 0 || axis == -1)) { + axis = 0; } - /* Special case letting axis=0 slip through for scalars */ - if ((axis < 0 || axis >= PyArray_NDIM(mp)) && - !(axis == 0 && PyArray_NDIM(mp) == 0)) { + else if (axis < 0 || axis >= ndim) { PyErr_SetString(PyExc_ValueError, "'axis' entry is out of bounds"); Py_XDECREF(otype); @@ -3791,7 +3799,7 @@ PyUFunc_GenericReduction(PyUFuncObject *ufunc, PyObject *args, } /* Check to see if input is zero-dimensional. */ - if (PyArray_NDIM(mp) == 0) { + if (ndim == 0) { /* * A reduction with no axes is still valid but trivial. * As a special case for backwards compatibility in 'sum', diff --git a/numpy/core/src/umath/ufunc_type_resolution.c b/numpy/core/src/umath/ufunc_type_resolution.c index de1da5c69..0d6cf19f1 100644 --- a/numpy/core/src/umath/ufunc_type_resolution.c +++ b/numpy/core/src/umath/ufunc_type_resolution.c @@ -217,6 +217,9 @@ PyUFunc_SimpleBinaryComparisonTypeResolver(PyUFuncObject *ufunc, Py_INCREF(out_dtypes[1]); } else { + PyObject *item; + PyArray_Descr *dtype = NULL; + /* * If the type tuple isn't a single-element tuple, let the * default type resolution handle this one. @@ -226,14 +229,18 @@ PyUFunc_SimpleBinaryComparisonTypeResolver(PyUFuncObject *ufunc, operands, type_tup, out_dtypes); } - if (!PyArray_DescrCheck(PyTuple_GET_ITEM(type_tup, 0))) { + item = PyTuple_GET_ITEM(type_tup, 0); + + if (item == Py_None) { PyErr_SetString(PyExc_ValueError, "require data type in the type tuple"); return -1; } + else if (!PyArray_DescrConverter(item, &dtype)) { + return -1; + } - out_dtypes[0] = ensure_dtype_nbo( - (PyArray_Descr *)PyTuple_GET_ITEM(type_tup, 0)); + out_dtypes[0] = ensure_dtype_nbo(dtype); if (out_dtypes[0] == NULL) { return -1; } @@ -314,6 +321,9 @@ PyUFunc_SimpleUnaryOperationTypeResolver(PyUFuncObject *ufunc, Py_INCREF(out_dtypes[1]); } else { + PyObject *item; + PyArray_Descr *dtype = NULL; + /* * If the type tuple isn't a single-element tuple, let the * default type resolution handle this one. @@ -323,14 +333,18 @@ PyUFunc_SimpleUnaryOperationTypeResolver(PyUFuncObject *ufunc, operands, type_tup, out_dtypes); } - if (!PyArray_DescrCheck(PyTuple_GET_ITEM(type_tup, 0))) { + item = PyTuple_GET_ITEM(type_tup, 0); + + if (item == Py_None) { PyErr_SetString(PyExc_ValueError, "require data type in the type tuple"); return -1; } + else if (!PyArray_DescrConverter(item, &dtype)) { + return -1; + } - out_dtypes[0] = ensure_dtype_nbo( - (PyArray_Descr *)PyTuple_GET_ITEM(type_tup, 0)); + out_dtypes[0] = ensure_dtype_nbo(dtype); if (out_dtypes[0] == NULL) { return -1; } @@ -424,6 +438,9 @@ PyUFunc_SimpleBinaryOperationTypeResolver(PyUFuncObject *ufunc, Py_INCREF(out_dtypes[2]); } else { + PyObject *item; + PyArray_Descr *dtype = NULL; + /* * If the type tuple isn't a single-element tuple, let the * default type resolution handle this one. @@ -433,14 +450,18 @@ PyUFunc_SimpleBinaryOperationTypeResolver(PyUFuncObject *ufunc, operands, type_tup, out_dtypes); } - if (!PyArray_DescrCheck(PyTuple_GET_ITEM(type_tup, 0))) { + item = PyTuple_GET_ITEM(type_tup, 0); + + if (item == Py_None) { PyErr_SetString(PyExc_ValueError, "require data type in the type tuple"); return -1; } + else if (!PyArray_DescrConverter(item, &dtype)) { + return -1; + } - out_dtypes[0] = ensure_dtype_nbo( - (PyArray_Descr *)PyTuple_GET_ITEM(type_tup, 0)); + out_dtypes[0] = ensure_dtype_nbo(dtype); if (out_dtypes[0] == NULL) { return -1; } @@ -591,8 +612,8 @@ PyUFunc_AdditionTypeResolver(PyUFuncObject *ufunc, /* Use the default when datetime and timedelta are not involved */ if (!PyTypeNum_ISDATETIME(type_num1) && !PyTypeNum_ISDATETIME(type_num2)) { - return PyUFunc_DefaultTypeResolver(ufunc, casting, operands, - type_tup, out_dtypes); + return PyUFunc_SimpleBinaryOperationTypeResolver(ufunc, casting, + operands, type_tup, out_dtypes); } if (type_num1 == NPY_TIMEDELTA) { @@ -780,8 +801,8 @@ PyUFunc_SubtractionTypeResolver(PyUFuncObject *ufunc, /* Use the default when datetime and timedelta are not involved */ if (!PyTypeNum_ISDATETIME(type_num1) && !PyTypeNum_ISDATETIME(type_num2)) { - return PyUFunc_DefaultTypeResolver(ufunc, casting, operands, - type_tup, out_dtypes); + return PyUFunc_SimpleBinaryOperationTypeResolver(ufunc, casting, + operands, type_tup, out_dtypes); } if (type_num1 == NPY_TIMEDELTA) { @@ -947,8 +968,8 @@ PyUFunc_MultiplicationTypeResolver(PyUFuncObject *ufunc, /* Use the default when datetime and timedelta are not involved */ if (!PyTypeNum_ISDATETIME(type_num1) && !PyTypeNum_ISDATETIME(type_num2)) { - return PyUFunc_DefaultTypeResolver(ufunc, casting, operands, - type_tup, out_dtypes); + return PyUFunc_SimpleBinaryOperationTypeResolver(ufunc, casting, + operands, type_tup, out_dtypes); } if (type_num1 == NPY_TIMEDELTA) { diff --git a/numpy/core/tests/test_regression.py b/numpy/core/tests/test_regression.py index 2bad0e90c..03c5f026b 100644 --- a/numpy/core/tests/test_regression.py +++ b/numpy/core/tests/test_regression.py @@ -1626,5 +1626,11 @@ class TestRegression(TestCase): a = np.empty((100000000,), dtype='i1') del a + def test_ufunc_reduce_memoryleak(self): + a = np.arange(6) + acnt = sys.getrefcount(a) + res = np.add.reduce(a) + assert_equal(sys.getrefcount(a), acnt) + if __name__ == "__main__": run_module_suite() |