NUMPY_API * Get intp chunk from sequence * * This function takes a Python sequence object and allocates and * fills in an intp array with the conv

* Simple helper to create a tuple from an array of items. The `make_null_none` * flag means that NULL entries are replaced with None, which is occasi

NUMPY_API * Update Several Flags at once. */

Create a view into the array with the given shape and strides. .. warning:: This function has to be used with extreme care, see notes.

View inputs as arrays with at least two dimensions. Parameters ---------- arys1, arys2, ... : array_like One or more array-l

* Creates a datetime or timedelta dtype using a copy of the provided metadata. */

Subroutine */

Customize Fortran compiler. This method gets Fortran compiler specific information from (i) class definition, (ii) environment, (iii)

Subroutine */

Return the distutils distribution object for self.

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

Returns True if the type of `element` is a scalar type. Parameters ---------- element : any Input argument, can be of any ty

Length accessor

Return (x1 <= x2) element-wise. Unlike `numpy.less_equal`, this comparison is performed by first stripping whitespace characters from th

Merge arrays field by field. Parameters ---------- seqarrays : sequence of ndarrays Sequence of arrays fill_value : {flo

Return the minimum of an array or minimum along an axis. Parameters ---------- a : array_like Input data. axis : None or

Parse a Fortran expression to a Expr.

Evaluate a piecewise-defined function. Given a set of conditions and corresponding functions, evaluate each function on the input data w

Subroutine */

Join a sequence of arrays along a new axis. The ``axis`` parameter specifies the index of the new axis in the dimensions of the result.

* try eliding a binary op, if commutative is true also try swapped arguments */

Subroutine */

NUMPY_API * Get an array of strides which are fixed. Any strides which may * change during iteration receive the value NPY_MAX_INTP. Once * the i

NUMPY_API * Whether the buffer allocation is being delayed */

NUMPY_API * Resets the iterator to its initial state * * The use of errmsg is discouraged, it cannot be guaranteed that the GIL * will not be grab

* Add a new casting implementation using a PyArrayMethod_Spec. * * @param spec * @param private If private, allow slots not publicly exposed. * @r

* An array assignment function for copying arrays, broadcasting 'src' into * 'dst'. This function makes a temporary copy of 'src' if 'src' and * 'ds

NUMPY_API * Returns 1 if the array object may be cast to the given data type using * the casting rule, 0 otherwise. This differs from PyArray_CanCa

NUMPY_API * New shape for an array */

NUMPY_API * Return Transpose. */

* Handler which uses the default `np.errstate` given that `fpe_errors` is * already set. `fpe_errors` is typically the (nonzero) result of * `npy_g

Private function validating the given `fill_value` for the given dtype. If fill_value is None, it is set to the default corresponding to the

* check the floating point status * - errmask: mask of status to check * - extobj: ufunc pyvals object * may be null, in which case th

A convenience function for operations that want to collapse to a scalar like _align, but are using keepdims=True

Return element-wise string concatenation for two arrays of str or unicode. Arrays `x1` and `x2` must have the same shape. Parameters

Apply a function to 1-D slices along the given axis. Execute `func1d(a, *args, **kwargs)` where `func1d` operates on 1-D arrays and `a`

Split an array into multiple sub-arrays. Please refer to the ``split`` documentation. The only difference between these functions is th

Return object as APPLY expression (function call, constructor, etc.)

Test that warnings are not raised. This is just a shorthand for: self.assert_deprecated(function, num=0, ignore_others=True,

Return the weighted average of array over the given axis. Parameters ---------- a : array_like Data to be averaged.

Broadcast any number of arrays against each other. Parameters ---------- `*args` : array_likes The arrays to broadcast.

Broadcast an array to a new shape. Parameters ---------- array : array_like The array to broadcast. shape : tuple or int

Subroutine */

Return the cumulative product of the array elements over the given axis. Masked values are set to 1 internally during the computatio

Return the indices of the bins to which each value in input array belongs. ========= ============= ============================ `right

Raise a distutils error

Subroutine */

Subroutine */

Return numbers spaced evenly on a log scale (a geometric progression). This is similar to `logspace`, but with endpoints specified directly.

Takes in a temporary file for testing and returns the expected output and input paths Here expected output is essentially one of any of the possi

Return the youngest subclass of MaskedArray from a list of (masked) arrays. In case of siblings, the first listed takes over.

Return (x1 > x2) element-wise. Unlike `numpy.greater`, this comparison is performed by first stripping whitespace characters from the en

Compute the dot product of two or more arrays in a single function call, while automatically selecting the fastest evaluation order. `mu

Apply glob to paths and prepend local_path if needed. Applies glob.glob(...) to each path in the sequence (if needed) and pre-pends t

Return (maximum - minimum) along the given dimension (i.e. peak-to-peak value). .. warning:: `ptp` preserves the

Evenly round to the given number of decimals. Parameters ---------- a : array_like Input data. decimals : int, optional

maskedarray version of the numpy function.

Subroutine */

Subroutine */

Trim the leading and/or trailing zeros from a 1-D array or sequence. Parameters ---------- filt : 1-D array or sequence Inpu

Returns a view of the mrecarray.

Stack arrays in sequence vertically (row wise). This is equivalent to concatenation along the first axis after 1-D arrays of shape `(N,)

Subroutine */

* Helper to set up a strided loop used for clearing. Clearing means * deallocating any references (e.g. via Py_DECREF) and resetting the data * bac