B îq\v ã@s ddlmZdgZddd„ZdS)é)Úcalculate_bin_edgesÚhisté Nçjø@cKst| dd¡}| dd¡}t||||d}t|ƒ|krHtdjt|ƒdƒ‚|dkrdddlm}| ¡}|j||f|ŽS)aÆEnhanced 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. max_bins : int (optional) Maximum number of bins allowed. With more than a few thousand bins the performance of matplotlib will not be great. If the number of bins is large *and* the number of input data points is large then the it will take a very long time to compute the histogram. **kwargs : other keyword arguments are described in ``plt.hist()``. Notes ----- Return values are the same as for ``plt.hist()`` See Also -------- astropy.stats.histogram ÚrangeNÚweights)rrz‚Histogram has too many bins: {nbin}. Use max_bins to increase the number of allowed bins or range to restrict the histogram range.)Znbinr) ÚgetrÚlenÚ ValueErrorÚformatZmatplotlib.pyplotZpyplotZgcar)ÚxZbinsZaxZmax_binsÚkwargsrrZplt©rú9lib/python3.7/site-packages/astropy/visualization/hist.pyrs1    )rNr)Zastropy.stats.histogramrÚ__all__rrrrrÚs