histogram¶
-
astropy.stats.
histogram
(a, bins=10, range=None, weights=None, **kwargs)[source]¶ Enhanced histogram function, providing adaptive binnings
This is a histogram function that enables the use of more sophisticated algorithms for determining bins. Aside from the
bins
argument allowing a string specified how bins are computed, the parameters are the same asnumpy.histogram()
.Parameters: a : array_like
array of data to be histogrammed
bins : int or list or str (optional)
If bins is a string, then it must be one of:
- ‘blocks’ : use bayesian blocks for dynamic bin widths
- ‘knuth’ : use Knuth’s rule to determine bins
- ‘scott’ : use Scott’s rule to determine bins
- ‘freedman’ : use the Freedman-Diaconis rule to determine bins
range : tuple or None (optional)
the minimum and maximum range for the histogram. If not specified, it will be (x.min(), x.max())
weights : array_like, optional
An array the same shape as
a
. If given, the histogram accumulates the value of the weight corresponding toa
instead of returning the count of values. This argument does not affect determination of bin edges.other keyword arguments are described in numpy.histogram().
Returns: hist : array
The values of the histogram. See
density
andweights
for a description of the possible semantics.bin_edges : array of dtype float
Return the bin edges
(length(hist)+1)
.See also
numpy.histogram