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Module « numpy »

Fonction piecewise - module numpy

Signature de la fonction piecewise

def piecewise(x, condlist, funclist, *args, **kw) 

Description

help(numpy.piecewise)

Evaluate a piecewise-defined function.

Given a set of conditions and corresponding functions, evaluate each
function on the input data wherever its condition is true.

Parameters
----------
x : ndarray or scalar
    The input domain.
condlist : list of bool arrays or bool scalars
    Each boolean array corresponds to a function in `funclist`.  Wherever
    `condlist[i]` is True, `funclist[i](x)` is used as the output value.

    Each boolean array in `condlist` selects a piece of `x`,
    and should therefore be of the same shape as `x`.

    The length of `condlist` must correspond to that of `funclist`.
    If one extra function is given, i.e. if
    ``len(funclist) == len(condlist) + 1``, then that extra function
    is the default value, used wherever all conditions are false.
funclist : list of callables, f(x,*args,**kw), or scalars
    Each function is evaluated over `x` wherever its corresponding
    condition is True.  It should take a 1d array as input and give an 1d
    array or a scalar value as output.  If, instead of a callable,
    a scalar is provided then a constant function (``lambda x: scalar``) is
    assumed.
args : tuple, optional
    Any further arguments given to `piecewise` are passed to the functions
    upon execution, i.e., if called ``piecewise(..., ..., 1, 'a')``, then
    each function is called as ``f(x, 1, 'a')``.
kw : dict, optional
    Keyword arguments used in calling `piecewise` are passed to the
    functions upon execution, i.e., if called
    ``piecewise(..., ..., alpha=1)``, then each function is called as
    ``f(x, alpha=1)``.

Returns
-------
out : ndarray
    The output is the same shape and type as x and is found by
    calling the functions in `funclist` on the appropriate portions of `x`,
    as defined by the boolean arrays in `condlist`.  Portions not covered
    by any condition have a default value of 0.


See Also
--------
choose, select, where

Notes
-----
This is similar to choose or select, except that functions are
evaluated on elements of `x` that satisfy the corresponding condition from
`condlist`.

The result is::

        |--
        |funclist[0](x[condlist[0]])
  out = |funclist[1](x[condlist[1]])
        |...
        |funclist[n2](x[condlist[n2]])
        |--

Examples
--------
>>> import numpy as np

Define the signum function, which is -1 for ``x < 0`` and +1 for ``x >= 0``.

>>> x = np.linspace(-2.5, 2.5, 6)
>>> np.piecewise(x, [x < 0, x >= 0], [-1, 1])
array([-1., -1., -1.,  1.,  1.,  1.])

Define the absolute value, which is ``-x`` for ``x <0`` and ``x`` for
``x >= 0``.

>>> np.piecewise(x, [x < 0, x >= 0], [lambda x: -x, lambda x: x])
array([2.5,  1.5,  0.5,  0.5,  1.5,  2.5])

Apply the same function to a scalar value.

>>> y = -2
>>> np.piecewise(y, [y < 0, y >= 0], [lambda x: -x, lambda x: x])
array(2)

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