* Helper function taking the size input and growing it (based on min_grow). * The current scheme is a minimum growth and a general growth by 25% * o

Return the imaginary part of the complex argument. Parameters ---------- val : array_like Input array. Returns ----

Test whether each element of an array is also present in a second array. The output is always a masked array. See `numpy.in1d` for more

Return an antiderivative (indefinite integral) of this polynomial. Refer to `polyint` for full documentation. See Also

Find the intersection of two arrays. Return the sorted, unique values that are in both of the input arrays. Parameters ----------

Assumes d_ > 0 */

Mask rows and/or columns of a 2D array that contain masked values. Mask whole rows and/or columns of a 2D array that contain masked valu

Mask an array where `not` equal to a given value. This function is a shortcut to ``masked_where``, with `condition` = (x != value).

Mask using floating point equality. Return a MaskedArray, masked where the data in array `x` are approximately equal to `value`, determi

* Return the datetime metadata as a Unicode object. * * Returns new reference, NULL on error. * * If 'skip_brackets' is true, skips the '[]'. *

Resolve `..` and '.' from path.

Return the character for the minimum-size type to which given types can be safely cast. The returned type character must represent the s

* Make a new empty array, of the passed size, of a type that takes the * priority of ap1 and ap2 into account. * * If `out` is non-NULL, memory ove

* Sorts the array of dates provided in place and removes * NaT, duplicates and any date which is already excluded on account * of the weekmask. *

* dimension/stride cache, uses a different allocator and is always a multiple * of npy_intp */

* When we get a Python int, float, or complex, we may have to use weak * promotion logic. * To implement this, we sometimes have to tag the converte

* Unlink coercion cache item. * * @param current * @return next coercion cache object (or NULL) */

* This gets called after the buffers have been exhausted, and * their data needs to be written back to the arrays. The multi-index * must be positi

* Removes the (additive) NPY_ITER_REDUCTION_AXIS indication and sets * is_forced_broadcast to 1 if it is set. Otherwise to 0. * * @param axis The o

* Undo the axis permutation of the iterator. When the operand has fewer * dimensions then the iterator, this can return negative values for * insert

* Non-contiguous Load ***************************/ / 32

check special cases

* The central entry-point for the promotion and dispatching machinery. * * It currently may work with the operands (although it would be possible to

Return a random matrix with data from the "standard normal" distribution. `randn` generates a matrix filled with random floats sampled from

Return library info for a package from its configuration file. Parameters ---------- pkgname : str Name of the package (shou

The real part of the masked array. This property is a view on the real part of this `MaskedArray`. See Also -------

* Promote and resolve a reduction like operation. * * @param ufunc * @param arr The operation array * @param out The output array or NULL if not p

* Fill in the actual descriptors used for the operation. This function * supports falling back to the legacy `ufunc->type_resolver`. * * We guaran

result_type(*arrays_and_dtypes) Returns the type that results from applying the NumPy type promotion rules to the arguments. Type p

Return an array drawn from elements in choicelist, depending on conditions. Parameters ---------- condlist : list of bool ndarrays

Find the set difference of two arrays. Return the unique values in `ar1` that are not in `ar2`. Parameters ---------- ar1 : arr

The shape of the array to be iterated over. For an example, see `Arrayterator`.

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

Subroutine */

Subroutine */

Subroutine */

Split an array into multiple sub-arrays as views into `ary`. Parameters ---------- ary : ndarray Array to be divided into su

Subroutine */

Subroutine */

This function is available in the datetime module only from Python >= 2.5.

Singular Value Decomposition. When `a` is a 2D array, and ``full_matrices=False``, then it is factorized as ``u @ np.diag(s) @ vh = (u *

Construct an array by repeating A the number of times given by reps. If `reps` has length ``d``, the result will have dimension of ``max

Long integer init */

Transpose each matrix in a stack of matrices. Unlike np.transpose, this only swaps the last two axes, rather than all of them Param

Permute the dimensions of an array. This function is exactly equivalent to `numpy.transpose`. See Also -------- numpy.transpose

r""" Integrate along the given axis using the composite trapezoidal rule. If `x` is provided, the integration happens in sequence along its

Remove small Poly series coefficients. Parameters ---------- seq : sequence Sequence of Poly series coefficients. This routine fa

Truncate series to length `size`. Reduce the series to length `size` by discarding the high degree terms. The value of `size` must be

Find the best converter for a given string, and return the result. The supplied string `value` is converted by testing different

* Check casting: It would be nice to just move this into the iterator * or pass in the full cast information. But this can special case * the logic

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