I had the same problem some time ago and what I did is to use bar() to plot the histogram, which can be done in one line:
hist, bin_edges = np.histogram(data) plt.bar(bin_edges[:-1], hist) Perhaps this trick can be added in the documentation? I am willing to code Virgil's request if many will find this useful. On Fri, Apr 24, 2015 at 11:33 AM, Virgil Stokes <v...@it.uu.se> wrote: > I have some Python (2.7.9) code that processes some rather large data sets > to determine the curvatures along 2D curves. One feature of these data that > I like to look at is the distribution of the curvatures. I use NumPy to to > determine histograms for each set, and save the histogram parameters > returned from numpy.histogram in a file. > > I would like to use Matplotlib to plot histograms from the parameters > returned in NumPy and stored in a file --- why? Because the size of my data > sets does not allow for the use of the histogram plot function in Matplotlib > (1.4.3); i.e., it needs the data sets to calculate the histogram, before > doing the plot. I would like to have a histogram plot function in Matplotlib > that could bypass the actual calculation of the bin counts and edges from > the data, and use values of these found a priori. Of course, an obvious > question is -- Why not write code to plot the rectangles yourself? Yes, I > could do this; but, why not extend the Matplotlib histogram class to allow > for this option? If I better understood Matplotlib, I would try this myself. > Maybe it is possible to get this into the next planned release (1.5). :-) > > If this request is inappropriate for this list, then please accept my > apology and direct me to where I should send this request. > > Best regards. > > ------------------------------------------------------------------------------ > One dashboard for servers and applications across Physical-Virtual-Cloud > Widest out-of-the-box monitoring support with 50+ applications > Performance metrics, stats and reports that give you Actionable Insights > Deep dive visibility with transaction tracing using APM Insight. > http://ad.doubleclick.net/ddm/clk/290420510;117567292;y > _______________________________________________ > Matplotlib-users mailing list > Matplotlib-users@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > ------------------------------------------------------------------------------ One dashboard for servers and applications across Physical-Virtual-Cloud Widest out-of-the-box monitoring support with 50+ applications Performance metrics, stats and reports that give you Actionable Insights Deep dive visibility with transaction tracing using APM Insight. http://ad.doubleclick.net/ddm/clk/290420510;117567292;y _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
