This example comes from Matplotlib's documentation. I'm running it inside Jupyter Lab. Here I attach the output figure:
import matplotlib.pyplot as pltimport numpy as npfrom matplotlib.projections import PolarAxesfrom matplotlib.transforms import Affine2Dfrom mpl_toolkits.axisartist import Axes, HostAxes, angle_helperfrom mpl_toolkits.axisartist.grid_helper_curvelinear import \ GridHelperCurveLineardef curvelinear_test1(fig):""" Grid for custom transform.""" def tr(x, y): return x, y - x def inv_tr(x, y): return x, y + x grid_helper = GridHelperCurveLinear((tr, inv_tr)) ax1 = fig.add_subplot(1, 2, 1, axes_class=Axes, grid_helper=grid_helper) # ax1 will have ticks and gridlines defined by the given transform (+ # transData of the Axes). Note that the transform of the Axes itself # (i.e., transData) is not affected by the given transform. xx, yy = tr(np.array([3, 6]), np.array([5, 10])) ax1.plot(xx, yy) ax1.set_aspect(1) ax1.set_xlim(0, 10) ax1.set_ylim(0, 10) ax1.axis["t"] = ax1.new_floating_axis(0, 3) ax1.axis["t2"] = ax1.new_floating_axis(1, 7) ax1.grid(True, zorder=0)fig = plt.figure()curvelinear_test1(fig)plt.show()
Note the weird top/bottom margins. Left/Right margins seems ok. If I execute this code inside a standard python interpreter, the picture looks like this:
Here, maybe there is too much top/bottom margin, and definitely too much right margin.
I've tried plt.tight_layout() just before plt.show(), but it does nothing in this case. I've looked at the source code of Axes/HostAxes but I couln't find anything obvious that would help fix these margins.
What can I try?