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Fonction histogram - module scipy.ndimage

Signature de la fonction histogram

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

Description

histogram.__doc__

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