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 <keith@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.