Resending after subscribing to the list since original reply was rejected, that's what I get for reading the mailing list from gmane instead of actually subscribing :)
Keith Sloan <ke...@sloan-home.co.uk> writes: > Okay I have some data which I have created a scatter plot > <http://numpy-discussion.10968.n7.nabble.com/file/t2643/A2D75C32-6DAF-4DA7-B7AE-9DE8C2B0D07A.jpeg> > > > I have also created a histogram of red Galaxy counts for redshift with > > RedEllipticalMasses.keep_columns(['uminusr','Z_1']) > RedEllipticalMasses.sort(['Z_1','uminusr']) > counts, bins = np.histogram(RedEllipticalMasses['Z_1'],bins=80) > fig, ax = plt.subplots(1, 1, figsize=(12,8)) # make the figure with the size > 10 x 8 inches > fig.suptitle("2 - Histogram Count of Red Galaxies versus Redshift") > plt.hist(bins[:-1], bins, weights=counts) > plt.show() > <http://numpy-discussion.10968.n7.nabble.com/file/t2643/05EA171B-3CA3-4834-83FE-31EEB60B744C.jpeg> > > > Is there a way to created the histogram data for a stacked histogram formed > from different ranges of redness 'uminusr'? if you have already calculated a few histograms (i.e. you have the arrays of bin heights/counts), you can create a stacked histogram by passing a sequence of centers as the "data", a sequence of counts as the weights, and use stacked=True; for example: counts = [redness1, redness2, redness3] centers = [centers for _ in counts] plt.hist(centers, bins=bins, weights=counts, stacked=True) > Also is there an easy way of extracting the point information for the > midpoints of each histogram column? NumPy doesn't have a function for this, but since np.histogram returns the bin edges you can get the centers pretty easily with: centers = 0.5 * (edges[1:] + edges[:-1]) There's a nice object oriented histogramming library for Python called boost-histogram: https://boost-histogram.readthedocs.io/en/latest/ It might be worth giving it a look. _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
