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numpy.piecewise(x, condlist, funclist, *args, **kw)
[source] -
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
The input domain.
condlist : list of bool arrays
Each boolean array corresponds to a function in
funclist
. Wherevercondlist[i]
is True,funclist[i](x)
is used as the output value.Each boolean array in
condlist
selects a piece ofx
, and should therefore be of the same shape asx
.The length of
condlist
must correspond to that offunclist
. If one extra function is given, i.e. iflen(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 an array as input and give an 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 calledpiecewise(..., ..., 1, 'a')
, then each function is called asf(x, 1, 'a')
.kw : dict, optional
Keyword arguments used in calling
piecewise
are passed to the functions upon execution, i.e., if calledpiecewise(..., ..., lambda=1)
, then each function is called asf(x, lambda=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 ofx
, as defined by the boolean arrays incondlist
. Portions not covered by any condition have a default value of 0.Notes
This is similar to choose or select, except that functions are evaluated on elements of
x
that satisfy the corresponding condition fromcondlist
.The result is:
|-- |funclist[0](x[condlist[0]]) out = |funclist[1](x[condlist[1]]) |... |funclist[n2](x[condlist[n2]]) |--
Examples
Define the sigma function, which is -1 for
x < 0
and +1 forx >= 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
forx <0
andx
forx >= 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])
numpy.piecewise()
2017-01-10 18:16:27
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