To counteract this you can use negative padding (and padding greater than 1) e.g. I haven't looked into the details of your code, but it appears as though the actual plot (the actual graphics) is well within the margins of your subplot (extending the boundaries of the subplot would still leave a lot of white space). Im = imshow(Z,cmap=cm.jet, extent=(-pi, pi, -pi, pi)) # make these smaller to increase the resolutionįigtext(.55. See pcolor_demo2 for a much faster way of generating pcolor plots Please see the snippet at the end of the email. Of course, one can always resort to pdfcrop, but I believe there must be a better solution to resize the margins from matplotlib. However, in the following snippet, nothing I tried has been able to reduce the amount of white space around the figure (including toying around with As mentioned above, the grid helps the plot serve as a lookup table for quantitative information, and the white-on grey helps to keep the grid from competing with lines that represent data.I am aware that this question has already been asked several times on the mailing list, see e.g. They are each suited to different applications and personal preferences. There are five preset seaborn themes: darkgrid, whitegrid, dark, white, and ticks. In both cases, the first function returns a dictionary of parameters and the second sets the matplotlib defaults. To scale the plot, use the plotting_context() and set_context() functions. To control the style, use the axes_style() and set_style() functions. The interface for manipulating these parameters are two pairs of functions. The first group sets the aesthetic style of the plot, and the second scales various elements of the figure so that it can be easily incorporated into different contexts. Seaborn splits matplotlib parameters into two independent groups. On later versions, it must be explicitly invoked). (Note that in versions of seaborn prior to 0.8, set_theme() was called on import.
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