histogram¶
-
astropy.stats.
histogram
(a, bins=10, range=None, weights=None, **kwargs)[source] [edit on github]¶ 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