I do not think fig.add_axes([0.1, 1, 1, 1]) makes any sense. The docstring says:
fig.add_axes(*args, **kwargs) Add an axes at position *rect* [*left*, *bottom*, *width*, *height*] where all quantities are in fractions of figure width and height. If bottom and height are both 1 you need the height of the figure to be 2 in fractions of figure height. This means 1 must equal 2 and then Bertrand Russel must be the Pope[1]. Goyo [1] http://ceadserv1.nku.edu/longa//classes/mat385_resources/docs/russellpope.html 2015-05-20 13:43 GMT+02:00 aradand <arada...@gmail.com>: > I'm trying to plot an image on top of a Figure, but imshow seems to always > distort the size of the axes. What I want is that the lower part of the top > image stay always in the same position, for any image height > > This minimal example shows my issue > > import matplotlib.pyplot as plt > import numpy as np > > fig = plt.figure() > ax = fig.add_axes([0.1, 0, 1, 1]) > > # Top figure aligned with the bottom figure > # keeping the same width (?) > ax2 = fig.add_axes([0.1, 1, 1, 1]) > ax2.set_xticks([]) > > # Depending on the number of rows or columns > # the top image will be moved further to the top > # or will be stretched if rows > columns > # I dont know how to control this to stay always > # with the same separation with respect > # to the bottom figure and keeping the same width > # (so the frame is the same width than the bottom figure) > im = np.random.rand(10, 30) > ax2.imshow(im) > plt.plot() > > If it is possible to > > I would prefer to avoid using subplots or grid, since I have already > specified a lot of things using the add_axes method. > > > > -- > View this message in context: > http://matplotlib.1069221.n5.nabble.com/Fixing-axes-for-imshow-plot-on-top-of-a-figure-tp45579.html > Sent from the matplotlib - users mailing list archive at Nabble.com. > > ------------------------------------------------------------------------------ > 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
