diff options
Diffstat (limited to 'numpy')
29 files changed, 299 insertions, 140 deletions
diff --git a/numpy/core/_add_newdocs.py b/numpy/core/_add_newdocs.py index dbe3d226f..b60edd1df 100644 --- a/numpy/core/_add_newdocs.py +++ b/numpy/core/_add_newdocs.py @@ -1326,9 +1326,9 @@ add_newdoc('numpy.core.multiarray', 'arange', See Also -------- - linspace : Evenly spaced numbers with careful handling of endpoints. - ogrid: Arrays of evenly spaced numbers in N-dimensions. - mgrid: Grid-shaped arrays of evenly spaced numbers in N-dimensions. + numpy.linspace : Evenly spaced numbers with careful handling of endpoints. + numpy.ogrid: Arrays of evenly spaced numbers in N-dimensions. + numpy.mgrid: Grid-shaped arrays of evenly spaced numbers in N-dimensions. Examples -------- @@ -3706,10 +3706,10 @@ add_newdoc('numpy.core.multiarray', 'ndarray', ('sort', See Also -------- numpy.sort : Return a sorted copy of an array. - argsort : Indirect sort. - lexsort : Indirect stable sort on multiple keys. - searchsorted : Find elements in sorted array. - partition: Partial sort. + numpy.argsort : Indirect sort. + numpy.lexsort : Indirect stable sort on multiple keys. + numpy.searchsorted : Find elements in sorted array. + numpy.partition: Partial sort. Notes ----- @@ -4497,7 +4497,7 @@ add_newdoc('numpy.core', 'ufunc', Alternate array object(s) in which to put the result; if provided, it must have a shape that the inputs broadcast to. A tuple of arrays (possible only as a keyword argument) must have length equal to the - number of outputs; use `None` for uninitialized outputs to be + number of outputs; use None for uninitialized outputs to be allocated by the ufunc. where : array_like, optional This condition is broadcast over the input. At locations where the @@ -4691,7 +4691,7 @@ add_newdoc('numpy.core', 'ufunc', ('signature', ----- Generalized ufuncs are used internally in many linalg functions, and in the testing suite; the examples below are taken from these. - For ufuncs that operate on scalars, the signature is `None`, which is + For ufuncs that operate on scalars, the signature is None, which is equivalent to '()' for every argument. Examples @@ -4742,7 +4742,7 @@ add_newdoc('numpy.core', 'ufunc', ('reduce', .. versionadded:: 1.7.0 - If this is `None`, a reduction is performed over all the axes. + If this is None, a reduction is performed over all the axes. If this is a tuple of ints, a reduction is performed on multiple axes, instead of a single axis or all the axes as before. @@ -4755,7 +4755,7 @@ add_newdoc('numpy.core', 'ufunc', ('reduce', to the data-type of the output array if this is provided, or the data-type of the input array if no output array is provided. out : ndarray, None, or tuple of ndarray and None, optional - A location into which the result is stored. If not provided or `None`, + A location into which the result is stored. If not provided or None, a freshly-allocated array is returned. For consistency with ``ufunc.__call__``, if given as a keyword, this may be wrapped in a 1-element tuple. @@ -4872,7 +4872,7 @@ add_newdoc('numpy.core', 'ufunc', ('accumulate', to the data-type of the output array if such is provided, or the the data-type of the input array if no output array is provided. out : ndarray, None, or tuple of ndarray and None, optional - A location into which the result is stored. If not provided or `None`, + A location into which the result is stored. If not provided or None, a freshly-allocated array is returned. For consistency with ``ufunc.__call__``, if given as a keyword, this may be wrapped in a 1-element tuple. @@ -4954,7 +4954,7 @@ add_newdoc('numpy.core', 'ufunc', ('reduceat', to the data type of the output array if this is provided, or the data type of the input array if no output array is provided. out : ndarray, None, or tuple of ndarray and None, optional - A location into which the result is stored. If not provided or `None`, + A location into which the result is stored. If not provided or None, a freshly-allocated array is returned. For consistency with ``ufunc.__call__``, if given as a keyword, this may be wrapped in a 1-element tuple. diff --git a/numpy/core/_internal.py b/numpy/core/_internal.py index 5fd643505..05e401e0b 100644 --- a/numpy/core/_internal.py +++ b/numpy/core/_internal.py @@ -313,7 +313,7 @@ class _ctypes(object): crashing. User Beware! The value of this attribute is exactly the same as ``self._array_interface_['data'][0]``. - Note that unlike `data_as`, a reference will not be kept to the array: + Note that unlike ``data_as``, a reference will not be kept to the array: code like ``ctypes.c_void_p((a + b).ctypes.data)`` will result in a pointer to a deallocated array, and should be spelt ``(a + b).ctypes.data_as(ctypes.c_void_p)`` diff --git a/numpy/core/arrayprint.py b/numpy/core/arrayprint.py index 8a7626d9d..401018015 100644 --- a/numpy/core/arrayprint.py +++ b/numpy/core/arrayprint.py @@ -111,7 +111,7 @@ def set_printoptions(precision=None, threshold=None, edgeitems=None, ---------- precision : int or None, optional Number of digits of precision for floating point output (default 8). - May be `None` if `floatmode` is not `fixed`, to print as many digits as + May be None if `floatmode` is not `fixed`, to print as many digits as necessary to uniquely specify the value. threshold : int, optional Total number of array elements which trigger summarization diff --git a/numpy/core/code_generators/ufunc_docstrings.py b/numpy/core/code_generators/ufunc_docstrings.py index 1ac477b54..4dec73505 100644 --- a/numpy/core/code_generators/ufunc_docstrings.py +++ b/numpy/core/code_generators/ufunc_docstrings.py @@ -22,7 +22,7 @@ subst = { 'PARAMS': textwrap.dedent(""" out : ndarray, None, or tuple of ndarray and None, optional A location into which the result is stored. If provided, it must have - a shape that the inputs broadcast to. If not provided or `None`, + a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs. where : array_like, optional @@ -2596,7 +2596,7 @@ add_newdoc('numpy.core.umath', 'matmul', out : ndarray, optional A location into which the result is stored. If provided, it must have a shape that matches the signature `(n,k),(k,m)->(n,m)`. If not - provided or `None`, a freshly-allocated array is returned. + provided or None, a freshly-allocated array is returned. **kwargs For other keyword-only arguments, see the :ref:`ufunc docs <ufuncs.kwargs>`. diff --git a/numpy/core/defchararray.py b/numpy/core/defchararray.py index a941c5b81..2d89d6fe0 100644 --- a/numpy/core/defchararray.py +++ b/numpy/core/defchararray.py @@ -82,7 +82,7 @@ def _clean_args(*args): Many of the Python string operations that have optional arguments do not use 'None' to indicate a default value. In these cases, - we need to remove all `None` arguments, and those following them. + we need to remove all None arguments, and those following them. """ newargs = [] for chk in args: @@ -1333,7 +1333,7 @@ def rsplit(a, sep=None, maxsplit=None): a : array_like of str or unicode sep : str or unicode, optional - If `sep` is not specified or `None`, any whitespace string + If `sep` is not specified or None, any whitespace string is a separator. maxsplit : int, optional If `maxsplit` is given, at most `maxsplit` splits are done, @@ -1417,7 +1417,7 @@ def split(a, sep=None, maxsplit=None): a : array_like of str or unicode sep : str or unicode, optional - If `sep` is not specified or `None`, any whitespace string is a + If `sep` is not specified or None, any whitespace string is a separator. maxsplit : int, optional @@ -2659,7 +2659,7 @@ def array(obj, itemsize=None, copy=True, unicode=None, order=None): unicode : bool, optional When true, the resulting `chararray` can contain Unicode characters, when false only 8-bit characters. If unicode is - `None` and `obj` is one of the following: + None and `obj` is one of the following: - a `chararray`, - an ndarray of type `str` or `unicode` @@ -2799,7 +2799,7 @@ def asarray(obj, itemsize=None, unicode=None, order=None): unicode : bool, optional When true, the resulting `chararray` can contain Unicode characters, when false only 8-bit characters. If unicode is - `None` and `obj` is one of the following: + None and `obj` is one of the following: - a `chararray`, - an ndarray of type `str` or 'unicode` diff --git a/numpy/core/fromnumeric.py b/numpy/core/fromnumeric.py index 6c0b9cde9..5f7716455 100644 --- a/numpy/core/fromnumeric.py +++ b/numpy/core/fromnumeric.py @@ -1409,7 +1409,7 @@ def squeeze(a, axis=None): Raises ------ ValueError - If `axis` is not `None`, and an axis being squeezed is not of length 1 + If `axis` is not None, and an axis being squeezed is not of length 1 See Also -------- @@ -1945,7 +1945,7 @@ def compress(condition, a, axis=None, out=None): take, choose, diag, diagonal, select ndarray.compress : Equivalent method in ndarray np.extract: Equivalent method when working on 1-D arrays - numpy.doc.ufuncs : Section "Output arguments" + ufuncs-output-type Examples -------- @@ -1995,14 +1995,14 @@ def clip(a, a_min, a_max, out=None, **kwargs): ---------- a : array_like Array containing elements to clip. - a_min : scalar or array_like or `None` - Minimum value. If `None`, clipping is not performed on lower + a_min : scalar or array_like or None + Minimum value. If None, clipping is not performed on lower interval edge. Not more than one of `a_min` and `a_max` may be - `None`. - a_max : scalar or array_like or `None` - Maximum value. If `None`, clipping is not performed on upper + None. + a_max : scalar or array_like or None + Maximum value. If None, clipping is not performed on upper interval edge. Not more than one of `a_min` and `a_max` may be - `None`. If `a_min` or `a_max` are array_like, then the three + None. If `a_min` or `a_max` are array_like, then the three arrays will be broadcasted to match their shapes. out : ndarray, optional The results will be placed in this array. It may be the input @@ -2023,7 +2023,7 @@ def clip(a, a_min, a_max, out=None, **kwargs): See Also -------- - numpy.doc.ufuncs : Section "Output arguments" + ufuncs-output-type Examples -------- @@ -2206,7 +2206,7 @@ def any(a, axis=None, out=None, keepdims=np._NoValue): Input array or object that can be converted to an array. axis : None or int or tuple of ints, optional Axis or axes along which a logical OR reduction is performed. - The default (`axis` = `None`) is to perform a logical OR over all + The default (``axis=None``) is to perform a logical OR over all the dimensions of the input array. `axis` may be negative, in which case it counts from the last to the first axis. @@ -2219,7 +2219,7 @@ def any(a, axis=None, out=None, keepdims=np._NoValue): the same shape as the expected output and its type is preserved (e.g., if it is of type float, then it will remain so, returning 1.0 for True and 0.0 for False, regardless of the type of `a`). - See `doc.ufuncs` (Section "Output arguments") for details. + See `ufuncs-output-type` for more details. keepdims : bool, optional If this is set to True, the axes which are reduced are left @@ -2292,7 +2292,7 @@ def all(a, axis=None, out=None, keepdims=np._NoValue): Input array or object that can be converted to an array. axis : None or int or tuple of ints, optional Axis or axes along which a logical AND reduction is performed. - The default (`axis` = `None`) is to perform a logical AND over all + The default (``axis=None``) is to perform a logical AND over all the dimensions of the input array. `axis` may be negative, in which case it counts from the last to the first axis. @@ -2304,8 +2304,8 @@ def all(a, axis=None, out=None, keepdims=np._NoValue): Alternate output array in which to place the result. It must have the same shape as the expected output and its type is preserved (e.g., if ``dtype(out)`` is float, the result - will consist of 0.0's and 1.0's). See `doc.ufuncs` (Section - "Output arguments") for more details. + will consist of 0.0's and 1.0's). See `ufuncs-output-type` for more + details. keepdims : bool, optional If this is set to True, the axes which are reduced are left @@ -2383,8 +2383,8 @@ def cumsum(a, axis=None, dtype=None, out=None): out : ndarray, optional Alternative output array in which to place the result. It must have the same shape and buffer length as the expected output - but the type will be cast if necessary. See `doc.ufuncs` - (Section "Output arguments") for more details. + but the type will be cast if necessary. See `ufuncs-output-type` for + more details. Returns ------- @@ -2529,7 +2529,7 @@ def amax(a, axis=None, out=None, keepdims=np._NoValue, initial=np._NoValue, out : ndarray, optional Alternative output array in which to place the result. Must be of the same shape and buffer length as the expected output. - See `doc.ufuncs` (Section "Output arguments") for more details. + See `ufuncs-output-type` for more details. keepdims : bool, optional If this is set to True, the axes which are reduced are left @@ -2654,7 +2654,7 @@ def amin(a, axis=None, out=None, keepdims=np._NoValue, initial=np._NoValue, out : ndarray, optional Alternative output array in which to place the result. Must be of the same shape and buffer length as the expected output. - See `doc.ufuncs` (Section "Output arguments") for more details. + See `ufuncs-output-type` for more details. keepdims : bool, optional If this is set to True, the axes which are reduced are left @@ -2861,7 +2861,7 @@ def prod(a, axis=None, dtype=None, out=None, keepdims=np._NoValue, See Also -------- ndarray.prod : equivalent method - numpy.doc.ufuncs : Section "Output arguments" + ufuncs-output-type Notes ----- @@ -2957,7 +2957,7 @@ def cumprod(a, axis=None, dtype=None, out=None): See Also -------- - numpy.doc.ufuncs : Section "Output arguments" + ufuncs-output-type Notes ----- @@ -3103,8 +3103,8 @@ def around(a, decimals=0, out=None): out : ndarray, optional Alternative output array in which to place the result. It must have the same shape as the expected output, but the type of the output - values will be cast if necessary. See `doc.ufuncs` (Section - "Output arguments") for details. + values will be cast if necessary. See `ufuncs-output-type` for more + details. Returns ------- @@ -3218,7 +3218,7 @@ def mean(a, axis=None, dtype=None, out=None, keepdims=np._NoValue): Alternate output array in which to place the result. The default is ``None``; if provided, it must have the same shape as the expected output, but the type will be cast if necessary. - See `doc.ufuncs` for details. + See `ufuncs-output-type` for more details. keepdims : bool, optional If this is set to True, the axes which are reduced are left @@ -3353,7 +3353,7 @@ def std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=np._NoValue): See Also -------- var, mean, nanmean, nanstd, nanvar - numpy.doc.ufuncs : Section "Output arguments" + ufuncs-output-type Notes ----- @@ -3478,7 +3478,7 @@ def var(a, axis=None, dtype=None, out=None, ddof=0, keepdims=np._NoValue): See Also -------- std, mean, nanmean, nanstd, nanvar - numpy.doc.ufuncs : Section "Output arguments" + ufuncs-output-type Notes ----- diff --git a/numpy/core/numeric.py b/numpy/core/numeric.py index 750f69db8..1e011e2e7 100644 --- a/numpy/core/numeric.py +++ b/numpy/core/numeric.py @@ -292,7 +292,7 @@ def full(shape, fill_value, dtype=None, order='C'): fill_value : scalar Fill value. dtype : data-type, optional - The desired data-type for the array The default, `None`, means + The desired data-type for the array The default, None, means `np.array(fill_value).dtype`. order : {'C', 'F'}, optional Whether to store multidimensional data in C- or Fortran-contiguous @@ -2098,9 +2098,9 @@ def allclose(a, b, rtol=1.e-5, atol=1.e-8, equal_nan=False): `atol` are added together to compare against the absolute difference between `a` and `b`. - If either array contains one or more NaNs, False is returned. - Infs are treated as equal if they are in the same place and of the same - sign in both arrays. + NaNs are treated as equal if they are in the same place and if + ``equal_nan=True``. Infs are treated as equal if they are in the same + place and of the same sign in both arrays. Parameters ---------- @@ -2112,7 +2112,7 @@ def allclose(a, b, rtol=1.e-5, atol=1.e-8, equal_nan=False): The absolute tolerance parameter (see Notes). equal_nan : bool Whether to compare NaN's as equal. If True, NaN's in `a` will be - considered equal to NaN's in `b`. + considered equal to NaN's in `b` in the output array. .. versionadded:: 1.10.0 diff --git a/numpy/core/shape_base.py b/numpy/core/shape_base.py index d7e769e62..369d956fb 100644 --- a/numpy/core/shape_base.py +++ b/numpy/core/shape_base.py @@ -472,7 +472,7 @@ def _block_check_depths_match(arrays, parent_index=[]): first_index : list of int The full index of an element from the bottom of the nesting in `arrays`. If any element at the bottom is an empty list, this will - refer to it, and the last index along the empty axis will be `None`. + refer to it, and the last index along the empty axis will be None. max_arr_ndim : int The maximum of the ndims of the arrays nested in `arrays`. final_size: int diff --git a/numpy/core/src/multiarray/arrayobject.c b/numpy/core/src/multiarray/arrayobject.c index 4e229e321..5ed5b7635 100644 --- a/numpy/core/src/multiarray/arrayobject.c +++ b/numpy/core/src/multiarray/arrayobject.c @@ -557,7 +557,7 @@ PyArray_DebugPrint(PyArrayObject *obj) printf(" ndim : %d\n", fobj->nd); printf(" shape :"); for (i = 0; i < fobj->nd; ++i) { - printf(" %d", (int)fobj->dimensions[i]); + printf(" %" NPY_INTP_FMT, fobj->dimensions[i]); } printf("\n"); @@ -567,7 +567,7 @@ PyArray_DebugPrint(PyArrayObject *obj) printf(" data : %p\n", fobj->data); printf(" strides:"); for (i = 0; i < fobj->nd; ++i) { - printf(" %d", (int)fobj->strides[i]); + printf(" %" NPY_INTP_FMT, fobj->strides[i]); } printf("\n"); diff --git a/numpy/core/src/multiarray/conversion_utils.c b/numpy/core/src/multiarray/conversion_utils.c index 4baa02052..5f0ad5817 100644 --- a/numpy/core/src/multiarray/conversion_utils.c +++ b/numpy/core/src/multiarray/conversion_utils.c @@ -667,8 +667,8 @@ PyArray_ConvertClipmodeSequence(PyObject *object, NPY_CLIPMODE *modes, int n) if (object && (PyTuple_Check(object) || PyList_Check(object))) { if (PySequence_Size(object) != n) { PyErr_Format(PyExc_ValueError, - "list of clipmodes has wrong length (%d instead of %d)", - (int)PySequence_Size(object), n); + "list of clipmodes has wrong length (%zd instead of %d)", + PySequence_Size(object), n); return NPY_FAIL; } diff --git a/numpy/core/src/multiarray/ctors.c b/numpy/core/src/multiarray/ctors.c index 5174bd889..9b6f59e3a 100644 --- a/numpy/core/src/multiarray/ctors.c +++ b/numpy/core/src/multiarray/ctors.c @@ -544,8 +544,8 @@ setArrayFromSequence(PyArrayObject *a, PyObject *s, */ if (slen != PyArray_DIMS(a)[dim] && slen != 1) { PyErr_Format(PyExc_ValueError, - "cannot copy sequence with size %d to array axis " - "with dimension %d", (int)slen, (int)PyArray_DIMS(a)[dim]); + "cannot copy sequence with size %zd to array axis " + "with dimension %" NPY_INTP_FMT, slen, PyArray_DIMS(a)[dim]); goto fail; } @@ -2894,8 +2894,8 @@ PyArray_CopyAsFlat(PyArrayObject *dst, PyArrayObject *src, NPY_ORDER order) src_size = PyArray_SIZE(src); if (dst_size != src_size) { PyErr_Format(PyExc_ValueError, - "cannot copy from array of size %d into an array " - "of size %d", (int)src_size, (int)dst_size); + "cannot copy from array of size %" NPY_INTP_FMT " into an array " + "of size %" NPY_INTP_FMT, src_size, dst_size); return -1; } diff --git a/numpy/core/src/multiarray/datetime.c b/numpy/core/src/multiarray/datetime.c index de81bcea1..72a3df89c 100644 --- a/numpy/core/src/multiarray/datetime.c +++ b/numpy/core/src/multiarray/datetime.c @@ -758,8 +758,8 @@ parse_datetime_extended_unit_from_string(char *str, Py_ssize_t len, bad_input: if (metastr != NULL) { PyErr_Format(PyExc_TypeError, - "Invalid datetime metadata string \"%s\" at position %d", - metastr, (int)(substr-metastr)); + "Invalid datetime metadata string \"%s\" at position %zd", + metastr, substr-metastr); } else { PyErr_Format(PyExc_TypeError, @@ -820,8 +820,8 @@ parse_datetime_metadata_from_metastr(char *metastr, Py_ssize_t len, bad_input: if (substr != metastr) { PyErr_Format(PyExc_TypeError, - "Invalid datetime metadata string \"%s\" at position %d", - metastr, (int)(substr-metastr)); + "Invalid datetime metadata string \"%s\" at position %zd", + metastr, substr - metastr); } else { PyErr_Format(PyExc_TypeError, @@ -2273,15 +2273,15 @@ convert_pydatetime_to_datetimestruct(PyObject *obj, npy_datetimestruct *out, invalid_date: PyErr_Format(PyExc_ValueError, - "Invalid date (%d,%d,%d) when converting to NumPy datetime", - (int)out->year, (int)out->month, (int)out->day); + "Invalid date (%" NPY_INT64_FMT ",%" NPY_INT32_FMT ",%" NPY_INT32_FMT ") when converting to NumPy datetime", + out->year, out->month, out->day); return -1; invalid_time: PyErr_Format(PyExc_ValueError, - "Invalid time (%d,%d,%d,%d) when converting " + "Invalid time (%" NPY_INT32_FMT ",%" NPY_INT32_FMT ",%" NPY_INT32_FMT ",%" NPY_INT32_FMT ") when converting " "to NumPy datetime", - (int)out->hour, (int)out->min, (int)out->sec, (int)out->us); + out->hour, out->min, out->sec, out->us); return -1; } diff --git a/numpy/core/src/multiarray/datetime_strings.c b/numpy/core/src/multiarray/datetime_strings.c index 95b7bb3dc..dfc01494f 100644 --- a/numpy/core/src/multiarray/datetime_strings.c +++ b/numpy/core/src/multiarray/datetime_strings.c @@ -743,8 +743,8 @@ finish: parse_error: PyErr_Format(PyExc_ValueError, - "Error parsing datetime string \"%s\" at position %d", - str, (int)(substr-str)); + "Error parsing datetime string \"%s\" at position %zd", + str, substr - str); return -1; error: diff --git a/numpy/core/src/multiarray/descriptor.c b/numpy/core/src/multiarray/descriptor.c index 23d140cf6..522b69307 100644 --- a/numpy/core/src/multiarray/descriptor.c +++ b/numpy/core/src/multiarray/descriptor.c @@ -1149,8 +1149,8 @@ _convert_from_dict(PyObject *obj, int align) } Py_DECREF(off); if (offset < 0) { - PyErr_Format(PyExc_ValueError, "offset %d cannot be negative", - (int)offset); + PyErr_Format(PyExc_ValueError, "offset %ld cannot be negative", + offset); Py_DECREF(tup); Py_DECREF(ind); goto fail; @@ -1164,10 +1164,10 @@ _convert_from_dict(PyObject *obj, int align) /* If align=True, enforce field alignment */ if (align && offset % newdescr->alignment != 0) { PyErr_Format(PyExc_ValueError, - "offset %d for NumPy dtype with fields is " + "offset %ld for NumPy dtype with fields is " "not divisible by the field alignment %d " "with align=True", - (int)offset, (int)newdescr->alignment); + offset, newdescr->alignment); ret = NPY_FAIL; } else if (offset + newdescr->elsize > totalsize) { @@ -1286,7 +1286,7 @@ _convert_from_dict(PyObject *obj, int align) PyErr_Format(PyExc_ValueError, "NumPy dtype descriptor requires %d bytes, " "cannot override to smaller itemsize of %d", - (int)new->elsize, (int)itemsize); + new->elsize, itemsize); Py_DECREF(new); goto fail; } @@ -1295,7 +1295,7 @@ _convert_from_dict(PyObject *obj, int align) PyErr_Format(PyExc_ValueError, "NumPy dtype descriptor requires alignment of %d bytes, " "which is not divisible into the specified itemsize %d", - (int)new->alignment, (int)itemsize); + new->alignment, itemsize); Py_DECREF(new); goto fail; } diff --git a/numpy/core/src/multiarray/einsum.c.src b/numpy/core/src/multiarray/einsum.c.src index e7bbc3d0b..58af44091 100644 --- a/numpy/core/src/multiarray/einsum.c.src +++ b/numpy/core/src/multiarray/einsum.c.src @@ -1876,7 +1876,7 @@ parse_operand_subscripts(char *subscripts, int length, * later where it matters the char is cast to a signed char. */ for (idim = 0; idim < ndim - 1; ++idim) { - int label = op_labels[idim]; + int label = (signed char)op_labels[idim]; /* If it is a proper label, find any duplicates of it. */ if (label > 0) { /* Search for the next matching label. */ diff --git a/numpy/core/src/multiarray/mapping.c b/numpy/core/src/multiarray/mapping.c index 247864775..8dcd28c84 100644 --- a/numpy/core/src/multiarray/mapping.c +++ b/numpy/core/src/multiarray/mapping.c @@ -1198,9 +1198,9 @@ array_assign_boolean_subscript(PyArrayObject *self, if (size != PyArray_DIMS(v)[0]) { PyErr_Format(PyExc_ValueError, "NumPy boolean array indexing assignment " - "cannot assign %d input values to " - "the %d output values where the mask is true", - (int)PyArray_DIMS(v)[0], (int)size); + "cannot assign %" NPY_INTP_FMT " input values to " + "the %" NPY_INTP_FMT " output values where the mask is true", + PyArray_DIMS(v)[0], size); return -1; } v_stride = PyArray_STRIDES(v)[0]; diff --git a/numpy/core/src/multiarray/nditer_api.c b/numpy/core/src/multiarray/nditer_api.c index db0bfcece..e7fe0fa50 100644 --- a/numpy/core/src/multiarray/nditer_api.c +++ b/numpy/core/src/multiarray/nditer_api.c @@ -371,8 +371,8 @@ NpyIter_ResetToIterIndexRange(NpyIter *iter, } if (errmsg == NULL) { PyErr_Format(PyExc_ValueError, - "Out-of-bounds range [%d, %d) passed to " - "ResetToIterIndexRange", (int)istart, (int)iend); + "Out-of-bounds range [%" NPY_INTP_FMT ", %" NPY_INTP_FMT ") passed to " + "ResetToIterIndexRange", istart, iend); } else { *errmsg = "Out-of-bounds range passed to ResetToIterIndexRange"; @@ -382,8 +382,8 @@ NpyIter_ResetToIterIndexRange(NpyIter *iter, else if (iend < istart) { if (errmsg == NULL) { PyErr_Format(PyExc_ValueError, - "Invalid range [%d, %d) passed to ResetToIterIndexRange", - (int)istart, (int)iend); + "Invalid range [%" NPY_INTP_FMT ", %" NPY_INTP_FMT ") passed to ResetToIterIndexRange", + istart, iend); } else { *errmsg = "Invalid range passed to ResetToIterIndexRange"; @@ -1429,8 +1429,8 @@ NpyIter_DebugPrint(NpyIter *iter) printf("REUSE_REDUCE_LOOPS "); printf("\n"); - printf("| NDim: %d\n", (int)ndim); - printf("| NOp: %d\n", (int)nop); + printf("| NDim: %d\n", ndim); + printf("| NOp: %d\n", nop); if (NIT_MASKOP(iter) >= 0) { printf("| MaskOp: %d\n", (int)NIT_MASKOP(iter)); } diff --git a/numpy/core/src/multiarray/nditer_constr.c b/numpy/core/src/multiarray/nditer_constr.c index d40836dc2..5e770338d 100644 --- a/numpy/core/src/multiarray/nditer_constr.c +++ b/numpy/core/src/multiarray/nditer_constr.c @@ -154,7 +154,7 @@ NpyIter_AdvancedNew(int nop, PyArrayObject **op_in, npy_uint32 flags, if (nop > NPY_MAXARGS) { PyErr_Format(PyExc_ValueError, "Cannot construct an iterator with more than %d operands " - "(%d were requested)", (int)NPY_MAXARGS, (int)nop); + "(%d were requested)", NPY_MAXARGS, nop); return NULL; } @@ -810,7 +810,7 @@ npyiter_check_op_axes(int nop, int oa_ndim, int **op_axes, PyErr_Format(PyExc_ValueError, "Cannot construct an iterator with more than %d dimensions " "(%d were requested for op_axes)", - (int)NPY_MAXDIMS, oa_ndim); + NPY_MAXDIMS, oa_ndim); return 0; } if (op_axes == NULL) { @@ -826,14 +826,14 @@ npyiter_check_op_axes(int nop, int oa_ndim, int **op_axes, if (axes != NULL) { memset(axes_dupcheck, 0, NPY_MAXDIMS); for (idim = 0; idim < oa_ndim; ++idim) { - npy_intp i = axes[idim]; + int i = axes[idim]; if (i >= 0) { if (i >= NPY_MAXDIMS) { PyErr_Format(PyExc_ValueError, "The 'op_axes' provided to the iterator " "constructor for operand %d " "contained invalid " - "values %d", (int)iop, (int)i); + "values %d", iop, i); return 0; } else if (axes_dupcheck[i] == 1) { @@ -841,7 +841,7 @@ npyiter_check_op_axes(int nop, int oa_ndim, int **op_axes, "The 'op_axes' provided to the iterator " "constructor for operand %d " "contained duplicate " - "value %d", (int)iop, (int)i); + "value %d", iop, i); return 0; } else { @@ -1311,7 +1311,7 @@ npyiter_check_casting(int nop, PyArrayObject **op, PyObject *errmsg; errmsg = PyUString_FromFormat( "Iterator operand %d dtype could not be cast from ", - (int)iop); + iop); PyUString_ConcatAndDel(&errmsg, PyObject_Repr((PyObject *)PyArray_DESCR(op[iop]))); PyUString_ConcatAndDel(&errmsg, @@ -1342,7 +1342,7 @@ npyiter_check_casting(int nop, PyArrayObject **op, PyUString_ConcatAndDel(&errmsg, PyUString_FromFormat(", the operand %d dtype, " "according to the rule %s", - (int)iop, + iop, npyiter_casting_to_string(casting))); PyErr_SetObject(PyExc_TypeError, errmsg); Py_DECREF(errmsg); @@ -1500,8 +1500,8 @@ npyiter_fill_axisdata(NpyIter *iter, npy_uint32 flags, npyiter_opitflags *op_itf "Iterator input op_axes[%d][%d] (==%d) " "is not a valid axis of op[%d], which " "has %d dimensions ", - (int)iop, (int)(ndim-idim-1), (int)i, - (int)iop, (int)ondim); + iop, (ndim-idim-1), i, + iop, ondim); return 0; } } diff --git a/numpy/core/src/multiarray/nditer_pywrap.c b/numpy/core/src/multiarray/nditer_pywrap.c index 4b9d41aa4..246f9d382 100644 --- a/numpy/core/src/multiarray/nditer_pywrap.c +++ b/numpy/core/src/multiarray/nditer_pywrap.c @@ -2016,7 +2016,7 @@ npyiter_seq_item(NewNpyArrayIterObject *self, Py_ssize_t i) if (i < 0 || i >= nop) { PyErr_Format(PyExc_IndexError, - "Iterator operand index %d is out of bounds", (int)i_orig); + "Iterator operand index %zd is out of bounds", i_orig); return NULL; } @@ -2030,7 +2030,7 @@ npyiter_seq_item(NewNpyArrayIterObject *self, Py_ssize_t i) */ if (!self->readflags[i]) { PyErr_Format(PyExc_RuntimeError, - "Iterator operand %d is write-only", (int)i); + "Iterator operand %zd is write-only", i); return NULL; } #endif @@ -2147,12 +2147,12 @@ npyiter_seq_ass_item(NewNpyArrayIterObject *self, Py_ssize_t i, PyObject *v) if (i < 0 || i >= nop) { PyErr_Format(PyExc_IndexError, - "Iterator operand index %d is out of bounds", (int)i_orig); + "Iterator operand index %zd is out of bounds", i_orig); return -1; } if (!self->writeflags[i]) { PyErr_Format(PyExc_RuntimeError, - "Iterator operand %d is not writeable", (int)i_orig); + "Iterator operand %zd is not writeable", i_orig); return -1; } diff --git a/numpy/core/src/umath/ufunc_object.c b/numpy/core/src/umath/ufunc_object.c index e4ad3dc84..1dc581977 100644 --- a/numpy/core/src/umath/ufunc_object.c +++ b/numpy/core/src/umath/ufunc_object.c @@ -4058,8 +4058,8 @@ PyUFunc_Reduceat(PyUFuncObject *ufunc, PyArrayObject *arr, PyArrayObject *ind, for (i = 0; i < ind_size; ++i) { if (reduceat_ind[i] < 0 || reduceat_ind[i] >= red_axis_size) { PyErr_Format(PyExc_IndexError, - "index %d out-of-bounds in %s.%s [0, %d)", - (int)reduceat_ind[i], ufunc_name, opname, (int)red_axis_size); + "index %" NPY_INTP_FMT " out-of-bounds in %s.%s [0, %" NPY_INTP_FMT ")", + reduceat_ind[i], ufunc_name, opname, red_axis_size); return NULL; } } diff --git a/numpy/core/tests/test_einsum.py b/numpy/core/tests/test_einsum.py index cfeeb8a90..1b5b4cb26 100644 --- a/numpy/core/tests/test_einsum.py +++ b/numpy/core/tests/test_einsum.py @@ -5,7 +5,7 @@ import itertools import numpy as np from numpy.testing import ( assert_, assert_equal, assert_array_equal, assert_almost_equal, - assert_raises, suppress_warnings, assert_raises_regex + assert_raises, suppress_warnings, assert_raises_regex, assert_allclose ) # Setup for optimize einsum @@ -700,6 +700,14 @@ class TestEinsum(object): y2 = x[idx[:, None], idx[:, None], idx, idx] assert_equal(y1, y2) + def test_einsum_failed_on_p9_and_s390x(self): + # Issues gh-14692 and gh-12689 + # Bug with signed vs unsigned char errored on power9 and s390x Linux + tensor = np.random.random_sample((10, 10, 10, 10)) + x = np.einsum('ijij->', tensor) + y = tensor.trace(axis1=0, axis2=2).trace() + assert_allclose(x, y) + def test_einsum_all_contig_non_contig_output(self): # Issue gh-5907, tests that the all contiguous special case # actually checks the contiguity of the output diff --git a/numpy/lib/financial.py b/numpy/lib/financial.py index d72384e99..3ac3a4c33 100644 --- a/numpy/lib/financial.py +++ b/numpy/lib/financial.py @@ -12,6 +12,7 @@ otherwise stated. """ from __future__ import division, absolute_import, print_function +import warnings from decimal import Decimal import functools @@ -19,6 +20,10 @@ import numpy as np from numpy.core import overrides +_depmsg = ("numpy.{name} is deprecated and will be removed from NumPy 1.20. " + "Use numpy_financial.{name} instead " + "(https://pypi.org/project/numpy-financial/).") + array_function_dispatch = functools.partial( overrides.array_function_dispatch, module='numpy') @@ -45,6 +50,8 @@ def _convert_when(when): def _fv_dispatcher(rate, nper, pmt, pv, when=None): + warnings.warn(_depmsg.format(name='fv'), + DeprecationWarning, stacklevel=3) return (rate, nper, pmt, pv) @@ -53,6 +60,15 @@ def fv(rate, nper, pmt, pv, when='end'): """ Compute the future value. + .. deprecated:: 1.18 + + `fv` is deprecated; see NEP 32:: + + https://numpy.org/neps/nep-0032-remove-financial-functions.html + + Use the corresponding function in the numpy-financial library, + https://pypi.org/project/numpy-financial + Given: * a present value, `pv` * an interest `rate` compounded once per period, of which @@ -139,6 +155,8 @@ def fv(rate, nper, pmt, pv, when='end'): def _pmt_dispatcher(rate, nper, pv, fv=None, when=None): + warnings.warn(_depmsg.format(name='pmt'), + DeprecationWarning, stacklevel=3) return (rate, nper, pv, fv) @@ -147,6 +165,15 @@ def pmt(rate, nper, pv, fv=0, when='end'): """ Compute the payment against loan principal plus interest. + .. deprecated:: 1.18 + + `pmt` is deprecated; see NEP 32:: + + https://numpy.org/neps/nep-0032-remove-financial-functions.html + + Use the corresponding function in the numpy-financial library, + https://pypi.org/project/numpy-financial + Given: * a present value, `pv` (e.g., an amount borrowed) * a future value, `fv` (e.g., 0) @@ -237,6 +264,8 @@ def pmt(rate, nper, pv, fv=0, when='end'): def _nper_dispatcher(rate, pmt, pv, fv=None, when=None): + warnings.warn(_depmsg.format(name='nper'), + DeprecationWarning, stacklevel=3) return (rate, pmt, pv, fv) @@ -245,6 +274,15 @@ def nper(rate, pmt, pv, fv=0, when='end'): """ Compute the number of periodic payments. + .. deprecated:: 1.18 + + `nper` is deprecated; see NEP 32:: + + https://numpy.org/neps/nep-0032-remove-financial-functions.html + + Use the corresponding function in the numpy-financial library, + https://pypi.org/project/numpy-financial + :class:`decimal.Decimal` type is not supported. Parameters @@ -311,6 +349,8 @@ def nper(rate, pmt, pv, fv=0, when='end'): def _ipmt_dispatcher(rate, per, nper, pv, fv=None, when=None): + warnings.warn(_depmsg.format(name='ipmt'), + DeprecationWarning, stacklevel=3) return (rate, per, nper, pv, fv) @@ -319,6 +359,15 @@ def ipmt(rate, per, nper, pv, fv=0, when='end'): """ Compute the interest portion of a payment. + .. deprecated:: 1.18 + + `ipmt` is deprecated; see NEP 32:: + + https://numpy.org/neps/nep-0032-remove-financial-functions.html + + Use the corresponding function in the numpy-financial library, + https://pypi.org/project/numpy-financial + Parameters ---------- rate : scalar or array_like of shape(M, ) @@ -422,6 +471,8 @@ def _rbl(rate, per, pmt, pv, when): def _ppmt_dispatcher(rate, per, nper, pv, fv=None, when=None): + warnings.warn(_depmsg.format(name='ppmt'), + DeprecationWarning, stacklevel=3) return (rate, per, nper, pv, fv) @@ -430,6 +481,15 @@ def ppmt(rate, per, nper, pv, fv=0, when='end'): """ Compute the payment against loan principal. + .. deprecated:: 1.18 + + `ppmt` is deprecated; see NEP 32:: + + https://numpy.org/neps/nep-0032-remove-financial-functions.html + + Use the corresponding function in the numpy-financial library, + https://pypi.org/project/numpy-financial + Parameters ---------- rate : array_like @@ -456,6 +516,8 @@ def ppmt(rate, per, nper, pv, fv=0, when='end'): def _pv_dispatcher(rate, nper, pmt, fv=None, when=None): + warnings.warn(_depmsg.format(name='pv'), + DeprecationWarning, stacklevel=3) return (rate, nper, nper, pv, fv) @@ -464,6 +526,15 @@ def pv(rate, nper, pmt, fv=0, when='end'): """ Compute the present value. + .. deprecated:: 1.18 + + `pv` is deprecated; see NEP 32:: + + https://numpy.org/neps/nep-0032-remove-financial-functions.html + + Use the corresponding function in the numpy-financial library, + https://pypi.org/project/numpy-financial + Given: * a future value, `fv` * an interest `rate` compounded once per period, of which @@ -567,6 +638,8 @@ def _g_div_gp(r, n, p, x, y, w): def _rate_dispatcher(nper, pmt, pv, fv, when=None, guess=None, tol=None, maxiter=None): + warnings.warn(_depmsg.format(name='rate'), + DeprecationWarning, stacklevel=3) return (nper, pmt, pv, fv) @@ -582,6 +655,15 @@ def rate(nper, pmt, pv, fv, when='end', guess=None, tol=None, maxiter=100): """ Compute the rate of interest per period. + .. deprecated:: 1.18 + + `rate` is deprecated; see NEP 32:: + + https://numpy.org/neps/nep-0032-remove-financial-functions.html + + Use the corresponding function in the numpy-financial library, + https://pypi.org/project/numpy-financial + Parameters ---------- nper : array_like @@ -651,6 +733,8 @@ def rate(nper, pmt, pv, fv, when='end', guess=None, tol=None, maxiter=100): def _irr_dispatcher(values): + warnings.warn(_depmsg.format(name='irr'), + DeprecationWarning, stacklevel=3) return (values,) @@ -659,6 +743,15 @@ def irr(values): """ Return the Internal Rate of Return (IRR). + .. deprecated:: 1.18 + + `irr` is deprecated; see NEP 32:: + + https://numpy.org/neps/nep-0032-remove-financial-functions.html + + Use the corresponding function in the numpy-financial library, + https://pypi.org/project/numpy-financial + This is the "average" periodically compounded rate of return that gives a net present value of 0.0; for a more complete explanation, see Notes below. @@ -734,6 +827,8 @@ def irr(values): def _npv_dispatcher(rate, values): + warnings.warn(_depmsg.format(name='npv'), + DeprecationWarning, stacklevel=3) return (values,) @@ -742,6 +837,15 @@ def npv(rate, values): """ Returns the NPV (Net Present Value) of a cash flow series. + .. deprecated:: 1.18 + + `npv` is deprecated; see NEP 32:: + + https://numpy.org/neps/nep-0032-remove-financial-functions.html + + Use the corresponding function in the numpy-financial library, + https://pypi.org/project/numpy-financial + Parameters ---------- rate : scalar @@ -808,6 +912,8 @@ def npv(rate, values): def _mirr_dispatcher(values, finance_rate, reinvest_rate): + warnings.warn(_depmsg.format(name='mirr'), + DeprecationWarning, stacklevel=3) return (values,) @@ -816,6 +922,15 @@ def mirr(values, finance_rate, reinvest_rate): """ Modified internal rate of return. + .. deprecated:: 1.18 + + `mirr` is deprecated; see NEP 32:: + + https://numpy.org/neps/nep-0032-remove-financial-functions.html + + Use the corresponding function in the numpy-financial library, + https://pypi.org/project/numpy-financial + Parameters ---------- values : array_like diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py index c39c2eea1..3ad630a7d 100644 --- a/numpy/lib/function_base.py +++ b/numpy/lib/function_base.py @@ -1893,7 +1893,7 @@ class vectorize(object): typecode characters or a list of data type specifiers. There should be one data type specifier for each output. doc : str, optional - The docstring for the function. If `None`, the docstring will be the + The docstring for the function. If None, the docstring will be the ``pyfunc.__doc__``. excluded : set, optional Set of strings or integers representing the positional or keyword diff --git a/numpy/lib/nanfunctions.py b/numpy/lib/nanfunctions.py index 6cffab6ac..18ccab3b8 100644 --- a/numpy/lib/nanfunctions.py +++ b/numpy/lib/nanfunctions.py @@ -244,8 +244,8 @@ def nanmin(a, axis=None, out=None, keepdims=np._NoValue): out : ndarray, optional Alternate output array in which to place the result. The default is ``None``; if provided, it must have the same shape as the - expected output, but the type will be cast if necessary. See - `doc.ufuncs` for details. + expected output, but the type will be cast if necessary. See + `ufuncs-output-type` for more details. .. versionadded:: 1.8.0 keepdims : bool, optional @@ -359,8 +359,8 @@ def nanmax(a, axis=None, out=None, keepdims=np._NoValue): out : ndarray, optional Alternate output array in which to place the result. The default is ``None``; if provided, it must have the same shape as the - expected output, but the type will be cast if necessary. See - `doc.ufuncs` for details. + expected output, but the type will be cast if necessary. See + `ufuncs-output-type` for more details. .. versionadded:: 1.8.0 keepdims : bool, optional @@ -585,8 +585,8 @@ def nansum(a, axis=None, dtype=None, out=None, keepdims=np._NoValue): Alternate output array in which to place the result. The default is ``None``. If provided, it must have the same shape as the expected output, but the type will be cast if necessary. See - `doc.ufuncs` for details. The casting of NaN to integer can yield - unexpected results. + `ufuncs-output-type` for more details. The casting of NaN to integer + can yield unexpected results. .. versionadded:: 1.8.0 keepdims : bool, optional @@ -681,9 +681,9 @@ def nanprod(a, axis=None, dtype=None, out=None, keepdims=np._NoValue): out : ndarray, optional Alternate output array in which to place the result. The default is ``None``. If provided, it must have the same shape as the - expected output, but the type will be cast if necessary. See - `doc.ufuncs` for details. The casting of NaN to integer can yield - unexpected results. + expected output, but the type will be cast if necessary. See + `ufuncs-output-type` for more details. The casting of NaN to integer + can yield unexpected results. keepdims : bool, optional If True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will @@ -750,8 +750,8 @@ def nancumsum(a, axis=None, dtype=None, out=None): out : ndarray, optional Alternative output array in which to place the result. It must have the same shape and buffer length as the expected output - but the type will be cast if necessary. See `doc.ufuncs` - (Section "Output arguments") for more details. + but the type will be cast if necessary. See `ufuncs-output-type` for + more details. Returns ------- @@ -888,8 +888,8 @@ def nanmean(a, axis=None, dtype=None, out=None, keepdims=np._NoValue): out : ndarray, optional Alternate output array in which to place the result. The default is ``None``; if provided, it must have the same shape as the - expected output, but the type will be cast if necessary. See - `doc.ufuncs` for details. + expected output, but the type will be cast if necessary. See + `ufuncs-output-type` for more details. keepdims : bool, optional If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, @@ -1473,7 +1473,7 @@ def nanvar(a, axis=None, dtype=None, out=None, ddof=0, keepdims=np._NoValue): mean : Average var : Variance while not ignoring NaNs nanstd, nanmean - numpy.doc.ufuncs : Section "Output arguments" + ufuncs-output-type Notes ----- @@ -1625,7 +1625,7 @@ def nanstd(a, axis=None, dtype=None, out=None, ddof=0, keepdims=np._NoValue): -------- var, mean, std nanvar, nanmean - numpy.doc.ufuncs : Section "Output arguments" + ufuncs-output-type Notes ----- diff --git a/numpy/lib/polynomial.py b/numpy/lib/polynomial.py index 2c72f623c..3d07a0de4 100644 --- a/numpy/lib/polynomial.py +++ b/numpy/lib/polynomial.py @@ -479,10 +479,10 @@ def polyfit(x, y, deg, rcond=None, full=False, w=None, cov=False): coefficients for `k`-th data set are in ``p[:,k]``. residuals, rank, singular_values, rcond - Present only if `full` = True. Residuals of the least-squares fit, - the effective rank of the scaled Vandermonde coefficient matrix, - its singular values, and the specified value of `rcond`. For more - details, see `linalg.lstsq`. + Present only if `full` = True. Residuals is sum of squared residuals + of the least-squares fit, the effective rank of the scaled Vandermonde + coefficient matrix, its singular values, and the specified value of + `rcond`. For more details, see `linalg.lstsq`. V : ndarray, shape (M,M) or (M,M,K) Present only if `full` = False and `cov`=True. The covariance diff --git a/numpy/lib/tests/test_financial.py b/numpy/lib/tests/test_financial.py index 21088765f..cb67f7c0f 100644 --- a/numpy/lib/tests/test_financial.py +++ b/numpy/lib/tests/test_financial.py @@ -1,5 +1,6 @@ from __future__ import division, absolute_import, print_function +import warnings from decimal import Decimal import numpy as np @@ -8,22 +9,35 @@ from numpy.testing import ( ) +def filter_deprecation(func): + def newfunc(*args, **kwargs): + with warnings.catch_warnings(record=True) as ws: + warnings.filterwarnings('always', category=DeprecationWarning) + func(*args, **kwargs) + assert_(all(w.category is DeprecationWarning for w in ws)) + return newfunc + + class TestFinancial(object): + @filter_deprecation def test_npv_irr_congruence(self): # IRR is defined as the rate required for the present value of a # a series of cashflows to be zero i.e. NPV(IRR(x), x) = 0 cashflows = np.array([-40000, 5000, 8000, 12000, 30000]) assert_allclose(np.npv(np.irr(cashflows), cashflows), 0, atol=1e-10, rtol=0) + @filter_deprecation def test_rate(self): assert_almost_equal( np.rate(10, 0, -3500, 10000), 0.1107, 4) + @filter_deprecation def test_rate_decimal(self): rate = np.rate(Decimal('10'), Decimal('0'), Decimal('-3500'), Decimal('10000')) assert_equal(Decimal('0.1106908537142689284704528100'), rate) + @filter_deprecation def test_irr(self): v = [-150000, 15000, 25000, 35000, 45000, 60000] assert_almost_equal(np.irr(v), 0.0524, 2) @@ -43,20 +57,25 @@ class TestFinancial(object): v = [-1, -2, -3] assert_equal(np.irr(v), np.nan) + @filter_deprecation def test_pv(self): assert_almost_equal(np.pv(0.07, 20, 12000, 0), -127128.17, 2) + @filter_deprecation def test_pv_decimal(self): assert_equal(np.pv(Decimal('0.07'), Decimal('20'), Decimal('12000'), Decimal('0')), Decimal('-127128.1709461939327295222005')) + @filter_deprecation def test_fv(self): assert_equal(np.fv(0.075, 20, -2000, 0, 0), 86609.362673042924) + @filter_deprecation def test_fv_decimal(self): assert_equal(np.fv(Decimal('0.075'), Decimal('20'), Decimal('-2000'), 0, 0), Decimal('86609.36267304300040536731624')) + @filter_deprecation def test_pmt(self): res = np.pmt(0.08 / 12, 5 * 12, 15000) tgt = -304.145914 @@ -71,6 +90,7 @@ class TestFinancial(object): tgt = np.array([[-166.66667, -19311.258], [-626.90814, -19311.258]]) assert_allclose(res, tgt) + @filter_deprecation def test_pmt_decimal(self): res = np.pmt(Decimal('0.08') / Decimal('12'), 5 * 12, 15000) tgt = Decimal('-304.1459143262052370338701494') @@ -94,18 +114,22 @@ class TestFinancial(object): assert_equal(res[1][0], tgt[1][0]) assert_equal(res[1][1], tgt[1][1]) + @filter_deprecation def test_ppmt(self): assert_equal(np.round(np.ppmt(0.1 / 12, 1, 60, 55000), 2), -710.25) + @filter_deprecation def test_ppmt_decimal(self): assert_equal(np.ppmt(Decimal('0.1') / Decimal('12'), Decimal('1'), Decimal('60'), Decimal('55000')), Decimal('-710.2541257864217612489830917')) # Two tests showing how Decimal is actually getting at a more exact result # .23 / 12 does not come out nicely as a float but does as a decimal + @filter_deprecation def test_ppmt_special_rate(self): assert_equal(np.round(np.ppmt(0.23 / 12, 1, 60, 10000000000), 8), -90238044.232277036) + @filter_deprecation def test_ppmt_special_rate_decimal(self): # When rounded out to 8 decimal places like the float based test, this should not equal the same value # as the float, substituted for the decimal @@ -118,31 +142,38 @@ class TestFinancial(object): assert_equal(np.ppmt(Decimal('0.23') / Decimal('12'), 1, 60, Decimal('10000000000')), Decimal('-90238044.2322778884413969909')) + @filter_deprecation def test_ipmt(self): assert_almost_equal(np.round(np.ipmt(0.1 / 12, 1, 24, 2000), 2), -16.67) + @filter_deprecation def test_ipmt_decimal(self): result = np.ipmt(Decimal('0.1') / Decimal('12'), 1, 24, 2000) assert_equal(result.flat[0], Decimal('-16.66666666666666666666666667')) + @filter_deprecation def test_nper(self): assert_almost_equal(np.nper(0.075, -2000, 0, 100000.), 21.54, 2) + @filter_deprecation def test_nper2(self): assert_almost_equal(np.nper(0.0, -2000, 0, 100000.), 50.0, 1) + @filter_deprecation def test_npv(self): assert_almost_equal( np.npv(0.05, [-15000, 1500, 2500, 3500, 4500, 6000]), 122.89, 2) + @filter_deprecation def test_npv_decimal(self): assert_equal( np.npv(Decimal('0.05'), [-15000, 1500, 2500, 3500, 4500, 6000]), Decimal('122.894854950942692161628715')) + @filter_deprecation def test_mirr(self): val = [-4500, -800, 800, 800, 600, 600, 800, 800, 700, 3000] assert_almost_equal(np.mirr(val, 0.08, 0.055), 0.0666, 4) @@ -156,6 +187,7 @@ class TestFinancial(object): val = [39000, 30000, 21000, 37000, 46000] assert_(np.isnan(np.mirr(val, 0.10, 0.12))) + @filter_deprecation def test_mirr_decimal(self): val = [Decimal('-4500'), Decimal('-800'), Decimal('800'), Decimal('800'), Decimal('600'), Decimal('600'), Decimal('800'), Decimal('800'), @@ -174,6 +206,7 @@ class TestFinancial(object): val = [Decimal('39000'), Decimal('30000'), Decimal('21000'), Decimal('37000'), Decimal('46000')] assert_(np.isnan(np.mirr(val, Decimal('0.10'), Decimal('0.12')))) + @filter_deprecation def test_when(self): # begin assert_equal(np.rate(10, 20, -3500, 10000, 1), @@ -238,6 +271,7 @@ class TestFinancial(object): assert_equal(np.nper(0.075, -2000, 0, 100000., 0), np.nper(0.075, -2000, 0, 100000., 'end')) + @filter_deprecation def test_decimal_with_when(self): """Test that decimals are still supported if the when argument is passed""" # begin @@ -312,6 +346,7 @@ class TestFinancial(object): np.ipmt(Decimal('0.1') / Decimal('12'), Decimal('1'), Decimal('24'), Decimal('2000'), Decimal('0'), 'end').flat[0]) + @filter_deprecation def test_broadcast(self): assert_almost_equal(np.nper(0.075, -2000, 0, 100000., [0, 1]), [21.5449442, 20.76156441], 4) @@ -329,6 +364,7 @@ class TestFinancial(object): [-74.998201, -75.62318601, -75.62318601, -76.88882405, -76.88882405], 4) + @filter_deprecation def test_broadcast_decimal(self): # Use almost equal because precision is tested in the explicit tests, this test is to ensure # broadcast with Decimal is not broken. diff --git a/numpy/ma/core.py b/numpy/ma/core.py index bb3788c9a..bb0d8d412 100644 --- a/numpy/ma/core.py +++ b/numpy/ma/core.py @@ -4394,7 +4394,7 @@ class MaskedArray(ndarray): ---------- axis : None or int or tuple of ints, optional Axis or axes along which the count is performed. - The default (`axis` = `None`) performs the count over all + The default, None, performs the count over all the dimensions of the input array. `axis` may be negative, in which case it counts from the last to the first axis. @@ -4774,7 +4774,7 @@ class MaskedArray(ndarray): See Also -------- - ndarray.all : corresponding function for ndarrays + numpy.ndarray.all : corresponding function for ndarrays numpy.all : equivalent function Examples @@ -4812,7 +4812,7 @@ class MaskedArray(ndarray): See Also -------- - ndarray.any : corresponding function for ndarrays + numpy.ndarray.any : corresponding function for ndarrays numpy.any : equivalent function """ @@ -4866,7 +4866,7 @@ class MaskedArray(ndarray): flatnonzero : Return indices that are non-zero in the flattened version of the input array. - ndarray.nonzero : + numpy.ndarray.nonzero : Equivalent ndarray method. count_nonzero : Counts the number of non-zero elements in the input array. @@ -4994,7 +4994,7 @@ class MaskedArray(ndarray): See Also -------- - ndarray.sum : corresponding function for ndarrays + numpy.ndarray.sum : corresponding function for ndarrays numpy.sum : equivalent function Examples @@ -5065,7 +5065,7 @@ class MaskedArray(ndarray): See Also -------- - ndarray.cumsum : corresponding function for ndarrays + numpy.ndarray.cumsum : corresponding function for ndarrays numpy.cumsum : equivalent function Examples @@ -5102,7 +5102,7 @@ class MaskedArray(ndarray): See Also -------- - ndarray.prod : corresponding function for ndarrays + numpy.ndarray.prod : corresponding function for ndarrays numpy.prod : equivalent function """ kwargs = {} if keepdims is np._NoValue else {'keepdims': keepdims} @@ -5148,7 +5148,7 @@ class MaskedArray(ndarray): See Also -------- - ndarray.cumprod : corresponding function for ndarrays + numpy.ndarray.cumprod : corresponding function for ndarrays numpy.cumprod : equivalent function """ result = self.filled(1).cumprod(axis=axis, dtype=dtype, out=out) @@ -5171,7 +5171,7 @@ class MaskedArray(ndarray): See Also -------- - ndarray.mean : corresponding function for ndarrays + numpy.ndarray.mean : corresponding function for ndarrays numpy.mean : Equivalent function numpy.ma.average: Weighted average. @@ -5260,7 +5260,7 @@ class MaskedArray(ndarray): See Also -------- - ndarray.var : corresponding function for ndarrays + numpy.ndarray.var : corresponding function for ndarrays numpy.var : Equivalent function """ kwargs = {} if keepdims is np._NoValue else {'keepdims': keepdims} @@ -5323,7 +5323,7 @@ class MaskedArray(ndarray): See Also -------- - ndarray.std : corresponding function for ndarrays + numpy.ndarray.std : corresponding function for ndarrays numpy.std : Equivalent function """ kwargs = {} if keepdims is np._NoValue else {'keepdims': keepdims} @@ -5344,7 +5344,7 @@ class MaskedArray(ndarray): See Also -------- - ndarray.around : corresponding function for ndarrays + numpy.ndarray.around : corresponding function for ndarrays numpy.around : equivalent function """ result = self._data.round(decimals=decimals, out=out).view(type(self)) @@ -5406,7 +5406,7 @@ class MaskedArray(ndarray): -------- MaskedArray.sort : Describes sorting algorithms used. lexsort : Indirect stable sort with multiple keys. - ndarray.sort : Inplace sort. + numpy.ndarray.sort : Inplace sort. Notes ----- @@ -5558,7 +5558,7 @@ class MaskedArray(ndarray): See Also -------- - ndarray.sort : Method to sort an array in-place. + numpy.ndarray.sort : Method to sort an array in-place. argsort : Indirect sort. lexsort : Indirect stable sort on multiple keys. searchsorted : Find elements in a sorted array. @@ -5978,7 +5978,7 @@ class MaskedArray(ndarray): See Also -------- - ndarray.tobytes + numpy.ndarray.tobytes tolist, tofile Notes diff --git a/numpy/ma/extras.py b/numpy/ma/extras.py index de1aa3af8..4a83ac781 100644 --- a/numpy/ma/extras.py +++ b/numpy/ma/extras.py @@ -542,7 +542,7 @@ def average(a, axis=None, weights=None, returned=False): Data to be averaged. Masked entries are not taken into account in the computation. axis : int, optional - Axis along which to average `a`. If `None`, averaging is done over + Axis along which to average `a`. If None, averaging is done over the flattened array. weights : array_like, optional The importance that each element has in the computation of the average. diff --git a/numpy/matrixlib/defmatrix.py b/numpy/matrixlib/defmatrix.py index 3c7e8ffc2..cabd41367 100644 --- a/numpy/matrixlib/defmatrix.py +++ b/numpy/matrixlib/defmatrix.py @@ -1046,7 +1046,7 @@ def bmat(obj, ldict=None, gdict=None): referenced by name. ldict : dict, optional A dictionary that replaces local operands in current frame. - Ignored if `obj` is not a string or `gdict` is `None`. + Ignored if `obj` is not a string or `gdict` is None. gdict : dict, optional A dictionary that replaces global operands in current frame. Ignored if `obj` is not a string. |