package scipy

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val get_py : string -> Py.Object.t

Get an attribute of this module as a Py.Object.t. This is useful to pass a Python function to another function.

val isscalarlike : Py.Object.t -> Py.Object.t

Is x either a scalar, an array scalar, or a 0-dim array?

val matrix : ?kwargs:(string * Py.Object.t) list -> Py.Object.t list -> Py.Object.t

None

val npfunc : ?out: [ `Ndarray of [> `Ndarray ] Np.Obj.t | `Tuple_of_ndarray_and_None of Py.Object.t ] -> ?where:[> `Ndarray ] Np.Obj.t -> x:[> `Ndarray ] Np.Obj.t -> unit -> [ `ArrayLike | `Ndarray | `Object ] Np.Obj.t

sign(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True, signature, extobj)

Returns an element-wise indication of the sign of a number.

The `sign` function returns ``-1 if x < 0, 0 if x==0, 1 if x > 0``. nan is returned for nan inputs.

For complex inputs, the `sign` function returns ``sign(x.real) + 0j if x.real != 0 else sign(x.imag) + 0j``.

complex(nan, 0) is returned for complex nan inputs.

Parameters ---------- x : array_like Input values. 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 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 This condition is broadcast over the input. At locations where the condition is True, the `out` array will be set to the ufunc result. Elsewhere, the `out` array will retain its original value. Note that if an uninitialized `out` array is created via the default ``out=None``, locations within it where the condition is False will remain uninitialized. **kwargs For other keyword-only arguments, see the :ref:`ufunc docs <ufuncs.kwargs>`.

Returns ------- y : ndarray The sign of `x`. This is a scalar if `x` is a scalar.

Notes ----- There is more than one definition of sign in common use for complex numbers. The definition used here is equivalent to :math:`x/\sqrtx*x` which is different from a common alternative, :math:`x/|x|`.

Examples -------- >>> np.sign(-5., 4.5) array(-1., 1.) >>> np.sign(0) 0 >>> np.sign(5-2j) (1+0j)

val validateaxis : Py.Object.t -> Py.Object.t

None

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