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Module « scipy.ndimage »

Fonction histogram - module scipy.ndimage

Signature de la fonction histogram

def histogram(input, min, max, bins, labels=None, index=None) 

Description

help(scipy.ndimage.histogram)

Calculate the histogram of the values of an array, optionally at labels.

Histogram calculates the frequency of values in an array within bins
determined by `min`, `max`, and `bins`. The `labels` and `index`
keywords can limit the scope of the histogram to specified sub-regions
within the array.

Parameters
----------
input : array_like
    Data for which to calculate histogram.
min, max : int
    Minimum and maximum values of range of histogram bins.
bins : int
    Number of bins.
labels : array_like, optional
    Labels for objects in `input`.
    If not None, must be same shape as `input`.
index : int or sequence of ints, optional
    Label or labels for which to calculate histogram. If None, all values
    where label is greater than zero are used

Returns
-------
hist : ndarray
    Histogram counts.

Examples
--------
>>> import numpy as np
>>> a = np.array([[ 0.    ,  0.2146,  0.5962,  0.    ],
...               [ 0.    ,  0.7778,  0.    ,  0.    ],
...               [ 0.    ,  0.    ,  0.    ,  0.    ],
...               [ 0.    ,  0.    ,  0.7181,  0.2787],
...               [ 0.    ,  0.    ,  0.6573,  0.3094]])
>>> from scipy import ndimage
>>> ndimage.histogram(a, 0, 1, 10)
array([13,  0,  2,  1,  0,  1,  1,  2,  0,  0])

With labels and no indices, non-zero elements are counted:

>>> lbl, nlbl = ndimage.label(a)
>>> ndimage.histogram(a, 0, 1, 10, lbl)
array([0, 0, 2, 1, 0, 1, 1, 2, 0, 0])

Indices can be used to count only certain objects:

>>> ndimage.histogram(a, 0, 1, 10, lbl, 2)
array([0, 0, 1, 1, 0, 0, 1, 1, 0, 0])

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