Plot width settings in ipython notebook
ipython, jupyter-notebook, matplotlib, python
Solution
If you use `%pylab inline` you can (on a new line) insert the following command:
%pylab inline
pylab.rcParams['figure.figsize'] = (10, 6)
This will set all figures in your document (unless otherwise specified) to be of the size `(10, 6)`, where the first entry is the width and the second is the height.
See this SO post for more details. https://stackoverflow.com/a/17231361/1419668
Problem
I've got the following plots: It would look nicer if they have the same width. Do you have any idea how to do it in ipython notebook when I am using `%matplotlib inline`? UPDATE: To generate both figures I am using the following functions: ``` import numpy as np import matplotlib.pyplot as plt def show_plots2d(title, plots, points, xlabel = '', ylabel = ''): """ Shows 2D plot. Arguments: title : string Title of the plot. plots : array_like of pairs like array_like and array_like List of pairs, where first element is x axis and the second is the y axis. points : array_like of pairs like integer and integer List of pairs, where first element is x coordinate and the second is the y coordinate. xlabel : string Label of x axis ylabel : string Label of y axis """ xv, yv = zip(*plots) y_exclNone = [y[y != np.array(None)] for y in yv] y_mins, y_maxs = zip(* [(float(min(y)), float(max(y))) for y in y_exclNone] ) y_min = min(y_mins) y_max = max(y_maxs) y_amp = y_max - y_min plt.figure().suptitle(title) plt.axis( [xv[0][0], xv[0][-1], y_min - 0.3 * y_amp, y_max + 0.3 * y_amp] ) plt.xlabel(xlabel) plt.ylabel(ylabel) for x, y in plots: plt.plot(x, y) for x, y in points: plt.plot(x, y, 'bo') plt.show() def show_plot3d(title, x, y, z, xlabel = '', ylabel = '', zlabel = ''): """ Shows 3D plot. Arguments: title : string Title of the plot. x : array_like List of x coordinates y : array_like List of y coordinates z : array_like List of z coordinates xlabel : string Label of x axis ylabel : string Label of y axis zlabel : string Label of z axis """ plt.figure().suptitle(title) plt.pcolormesh(x, y, z) plt.axis([x[0], x[-1], y[0], y[-1]]) plt.xlabel(xlabel) plt.ylabel(ylabel) plt.colorbar().set_label(zlabel) plt.show() ```