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# Licensed under a 3-clause BSD style license - see LICENSE.rst
from __future__ import absolute_import, division, unicode_literals
import numpy as np
from ..stats import histogram
from ..utils.compat.funcsigs import signature
__all__ = ['hist']
def hist(x, bins=10, ax=None, **kwargs):
"""Enhanced histogram function
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
as pylab.hist().
This function was ported from astroML: http://astroML.org/
Parameters
----------
x : 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
ax : Axes instance (optional)
specify the Axes on which to draw the histogram. If not specified,
then the current active axes will be used.
**kwargs :
other keyword arguments are described in ``plt.hist()``.
Notes
-----
Return values are the same as for ``plt.hist()``
See Also
--------
astropy.stats.histogram
"""
# arguments of np.histogram should be passed to astropy.stats.histogram
arglist = list(signature(np.histogram).parameters.keys())[1:]
np_hist_kwds = dict((key, kwargs[key]) for key in arglist if key in kwargs)
hist, bins = histogram(x, bins, **np_hist_kwds)
if ax is None:
# optional dependency; only import if strictly needed.
import matplotlib.pyplot as plt
ax = plt.gca()
return ax.hist(x, bins, **kwargs)
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