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Module « scipy.signal »

Fonction argrelmin - module scipy.signal

Signature de la fonction argrelmin

def argrelmin(data, axis=0, order=1, mode='clip') 

Description

help(scipy.signal.argrelmin)

Calculate the relative minima of `data`.

Parameters
----------
data : ndarray
    Array in which to find the relative minima.
axis : int, optional
    Axis over which to select from `data`. Default is 0.
order : int, optional
    How many points on each side to use for the comparison
    to consider ``comparator(n, n+x)`` to be True.
mode : str, optional
    How the edges of the vector are treated.
    Available options are 'wrap' (wrap around) or 'clip' (treat overflow
    as the same as the last (or first) element).
    Default 'clip'. See numpy.take.

Returns
-------
extrema : tuple of ndarrays
    Indices of the minima in arrays of integers. ``extrema[k]`` is
    the array of indices of axis `k` of `data`. Note that the
    return value is a tuple even when `data` is 1-D.

See Also
--------
argrelextrema, argrelmax, find_peaks

Notes
-----
This function uses `argrelextrema` with np.less as comparator. Therefore, it
requires a strict inequality on both sides of a value to consider it a
minimum. This means flat minima (more than one sample wide) are not detected.
In case of 1-D `data` `find_peaks` can be used to detect all
local minima, including flat ones, by calling it with negated `data`.

.. versionadded:: 0.11.0

Examples
--------
>>> import numpy as np
>>> from scipy.signal import argrelmin
>>> x = np.array([2, 1, 2, 3, 2, 0, 1, 0])
>>> argrelmin(x)
(array([1, 5]),)
>>> y = np.array([[1, 2, 1, 2],
...               [2, 2, 0, 0],
...               [5, 3, 4, 4]])
...
>>> argrelmin(y, axis=1)
(array([0, 2]), array([2, 1]))

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