def set_aspect_equal(ax: plt.Axes) -> None:
"""
kudos to https://stackoverflow.com/a/35126679
:param ax: matplotlib 3D axes object
"""
if not isinstance(ax, Axes3D):
ax.set_aspect("equal")
return
xlim = ax.get_xlim3d()
ylim = ax.get_ylim3d()
zlim = ax.get_zlim3d()
from numpy import mean
xmean = mean(xlim)
ymean = mean(ylim)
zmean = mean(zlim)
plot_radius = max([
abs(lim - mean_)
for lims, mean_ in ((xlim, xmean), (ylim, ymean), (zlim, zmean))
for lim in lims
])
ax.set_xlim3d([xmean - plot_radius, xmean + plot_radius])
ax.set_ylim3d([ymean - plot_radius, ymean + plot_radius])
ax.set_zlim3d([zmean - plot_radius, zmean + plot_radius])
def _set_axes_equal(ax: plt.Axes):
ax.set_box_aspect([1,1,1])
limits = np.array([
ax.get_xlim3d(),
ax.get_ylim3d(),
ax.get_zlim3d(),
])
origin = np.mean(limits, axis=1)
radius = 0.5 * np.max(np.abs(limits[:, 1] - limits[:, 0]))
_set_axes_radius(ax, origin, radius)
def set_axes_equal(ax: plt.Axes):
"""Set 3D plot axes to equal scale.
Make axes of 3D plot have equal scale so that spheres appear as
spheres and cubes as cubes. Required since `ax.axis('equal')`
and `ax.set_aspect('equal')` don't work on 3D.
"""
limits = np.array([
ax.get_xlim3d(),
ax.get_ylim3d(),
ax.get_zlim3d(),
])
origin = np.mean(limits, axis=1)
radius = 0.5 * np.max(np.abs(limits[:, 1] - limits[:, 0]))
_set_axes_radius(ax, origin, radius)
def _set_axes_equal(ax: plt.Axes):
"""
Set 3D plot axes to equal scale.
Make axes of 3D plot have equal scale so that spheres appear as
spheres and cubes as cubes. Required since `ax.axis('equal')`
and `ax.set_aspect('equal')` don't work on 3D.
# Credit for code:
https://stackoverflow.com/questions/13685386/matplotlib-equal-unit-length-with-equal-aspect-ratio-z-axis-is-not-equal-to/63625222#63625222
"""
limits = np.array([
ax.get_xlim3d(),
ax.get_ylim3d(),
ax.get_zlim3d(),
])
origin = np.mean(limits, axis=1)
# IMPORTANT, this scaling factor (0.3) might needed to be changed
# Orginally it was 0.5, and should be checked that all templates
# Fit this. A template specific scaling factor is possible, if problems
# arise.
radius = 0.3 * np.max(np.abs(limits[:, 1] - limits[:, 0]))
_set_axes_radius(ax, origin, radius)