histogram#

scipy.ndimage.histogram(input,min,max,bins,labels=None,index=None)[source]#

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

Histogram calculates the frequency of values in an array within binsdetermined bymin,max, andbins. Thelabels andindexkeywords can limit the scope of the histogram to specified sub-regionswithin the array.

Parameters:

inputarray_like

Data for which to calculate histogram.

min, maxint

Minimum and maximum values of range of histogram bins.

binsint

Number of bins.

labelsarray_like, optional

Labels for objects ininput.If not None, must be same shape asinput.

indexint or sequence of ints, optional

Label or labels for which to calculate histogram. If None, all valueswhere label is greater than zero are used

Returns:

histndarray

Histogram counts.

Examples

Try it in your browser!

>>>importnumpyasnp>>>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]])>>>fromscipyimportndimage>>>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])

Go BackOpen In Tab