Returns the numpy.distutils config command instance.

Force the mask to hard, preventing unmasking by assignment. Whether the mask of a masked array is hard or soft is determined by

Test whether input is an instance of MaskedArray. This function returns True if `x` is an instance of MaskedArray and returns False othe

This docstring Has multiple lines And notes Notes ----- original note

Normalize a description adding the platform byteorder.

This is a copy of _PyErr_ChainExceptions */

This is a copy of _PyErr_ChainExceptions, with: * - a minimal implementation for python 2 * - __cause__ used instead of __context__ */

* The code below currently makes use of !NPY_ALIGNMENT_REQUIRED, which * should be OK but causes the clang sanitizer to warn. It may make *

Get equivalent "uint" alignment given an itemsize, for use in copy code */

* This sets the AXISDATA portion of the iterator to the specified * iterindex, updating the pointers as well. This function does * no error checkin

Context manager for setting print options. Set print options for the scope of the `with` block, and restore the old options at the end. See `

Return the product of array elements over a given axis. .. deprecated:: 1.25.0 ``product`` is deprecated as of NumPy 1.25.0, and wil

See array_assign.h for parameter documentation */

Return a new masked array with the specified size and shape. This is the masked equivalent of the `numpy.resize` function. The new array

Resize array

Subroutine */

Subroutine */

Array API compatible wrapper for :py:func:`np.subtract <numpy.subtract>`. See its docstring for more information.

Subroutine */

Subroutine */

NUMPY_API * Removes multi-index support from an iterator. * * Returns NPY_SUCCEED or NPY_FAIL. */

* NumPyOS_ascii_isspace: * * Same as isspace under C locale */

* Create a new ArrayMethod (internal version). * * @param name A name for the individual method, may be NULL. * @param spec A filled context object

* Given a descriptor (dtype instance), handles conversion of legacy flexible * "unsized" descriptors to their DType. It returns the DType and descri

NUMPY_API * Get Priority from object */

NUMPY_API * Return the typecode of the array a Python object would be converted to * * Returns the type number the result should have, or NPY_NOTYP

Private function: return a recarray, a ndarray, a MaskedArray or a MaskedRecords depending on the input parameters

Test if path is a net location. Tests the scheme and netloc.

* very simplistic small memory block cache to avoid more expensive libc * allocations * base function for data cache with 1 byte buckets and dimensi

Peak-to-peak value of x. This implementation avoids the problem of signed integer arrays having a peak-to-peak value that cannot be represent

Shrink a mask to nomask if possible

Returns True if two arrays are element-wise equal within a tolerance. This function is equivalent to `allclose` except that masked values

Return True if all entries of a and b are equal, using fill_value as a truth value where either or both are masked. Parameters -----

Function version of the eponymous method.

Returns 1 if the arrays have overlapping data, 0 otherwise */

Return object as REAL constant.

Asserts that comparison between two masked arrays is satisfied. The comparison is elementwise.

Compute the weighted average along the specified axis. Parameters ---------- a : array_like Array containing data to be aver

try elide unary temporary */

Subroutine */

Complex */

Subroutine */

concatenate((a1, a2, ...), axis=0, out=None, dtype=None, casting="same_kind") Join a sequence of arrays along an existing axis. Paramet

Returns an array with the number of non-overlapping occurrences of substring `sub` in the range [`start`, `end`]. See Also

Returns a list of final CPU baseline compiler flags

return a list of final CPU baseline feature names

Subroutine */

Subroutine */

Subroutine */

Extract a diagonal or construct a diagonal array. See the more detailed documentation for ``numpy.diagonal`` if you use this function to

Subroutine */

Subroutine */

dot(a, b, out=None) Dot product of two arrays. Specifically, - If both `a` and `b` are 1-D arrays, it is inner product of vectors

Stack arrays in sequence depth wise (along third axis). This is equivalent to concatenation along the third axis after 2-D arrays of sha

Subroutine */

Compute the differences between consecutive elements of an array. This function is the equivalent of `numpy.ediff1d` that takes masked v

Return a list of CPU features flags sorted from the lowest to highest interest.