matplotlib(等于单位长度):具有“相等”纵横比z轴不等于x-和y-

当我为三维图设置相等的宽高比时,z轴不会变为“相等”。 所以这:

fig = pylab.figure() mesFig = fig.gca(projection='3d', adjustable='box') mesFig.axis('equal') mesFig.plot(xC, yC, zC, 'r.') mesFig.plot(xO, yO, zO, 'b.') pyplot.show() 

给我以下几点: 在这里输入图像描述

显然z轴的单位长度不等于x和y单位。

我怎样才能使所有三个轴的单位长度相等? 我能find的所有解决scheme都不起作用。 谢谢。

我相信matplotlib还没有在3D中设置正确的平等轴…但是我发现前段时间(我不记得在哪里),我已经适应使用它。 这个概念是在你的数据周围创build一个假立方体边界框。 你可以用下面的代码来testing它:

 from mpl_toolkits.mplot3d import Axes3D from matplotlib import cm import matplotlib.pyplot as plt import numpy as np fig = plt.figure() ax = fig.gca(projection='3d') ax.set_aspect('equal') X = np.random.rand(100)*10+5 Y = np.random.rand(100)*5+2.5 Z = np.random.rand(100)*50+25 scat = ax.scatter(X, Y, Z) # Create cubic bounding box to simulate equal aspect ratio max_range = np.array([X.max()-X.min(), Y.max()-Y.min(), Z.max()-Z.min()]).max() Xb = 0.5*max_range*np.mgrid[-1:2:2,-1:2:2,-1:2:2][0].flatten() + 0.5*(X.max()+X.min()) Yb = 0.5*max_range*np.mgrid[-1:2:2,-1:2:2,-1:2:2][1].flatten() + 0.5*(Y.max()+Y.min()) Zb = 0.5*max_range*np.mgrid[-1:2:2,-1:2:2,-1:2:2][2].flatten() + 0.5*(Z.max()+Z.min()) # Comment or uncomment following both lines to test the fake bounding box: for xb, yb, zb in zip(Xb, Yb, Zb): ax.plot([xb], [yb], [zb], 'w') plt.grid() plt.show() 

z数据大约比x和y大一个数量级,但即使使用相同的轴选项,matplotlib自动缩放z轴:

坏

但是,如果添加边界框,则会获得正确的缩放比例:

在这里输入图像描述

我使用set_x/y/zlim 函数简化了Remy F的解决scheme。

 from mpl_toolkits.mplot3d import Axes3D from matplotlib import cm import matplotlib.pyplot as plt import numpy as np fig = plt.figure() ax = fig.gca(projection='3d') ax.set_aspect('equal') X = np.random.rand(100)*10+5 Y = np.random.rand(100)*5+2.5 Z = np.random.rand(100)*50+25 scat = ax.scatter(X, Y, Z) max_range = np.array([X.max()-X.min(), Y.max()-Y.min(), Z.max()-Z.min()]).max() / 2.0 mid_x = (X.max()+X.min()) * 0.5 mid_y = (Y.max()+Y.min()) * 0.5 mid_z = (Z.max()+Z.min()) * 0.5 ax.set_xlim(mid_x - max_range, mid_x + max_range) ax.set_ylim(mid_y - max_range, mid_y + max_range) ax.set_zlim(mid_z - max_range, mid_z + max_range) plt.show() 

在这里输入图像描述

我喜欢上面的解决scheme,但是他们有一个缺点,就是你需要跟踪所有数据的范围和手段。 如果您将多个数据集一起绘制,这可能会很麻烦。 为了解决这个问题,我使用了ax.get_ [xyz] lim3d()方法,把所有的东西放到一个独立的函数中,在你调用plt.show()之前只能调用一次。 这是新版本:

 from mpl_toolkits.mplot3d import Axes3D from matplotlib import cm import matplotlib.pyplot as plt import numpy as np def set_axes_equal(ax): '''Make axes of 3D plot have equal scale so that spheres appear as spheres, cubes as cubes, etc.. This is one possible solution to Matplotlib's ax.set_aspect('equal') and ax.axis('equal') not working for 3D. Input ax: a matplotlib axis, eg, as output from plt.gca(). ''' x_limits = ax.get_xlim3d() y_limits = ax.get_ylim3d() z_limits = ax.get_zlim3d() x_range = abs(x_limits[1] - x_limits[0]) x_middle = np.mean(x_limits) y_range = abs(y_limits[1] - y_limits[0]) y_middle = np.mean(y_limits) z_range = abs(z_limits[1] - z_limits[0]) z_middle = np.mean(z_limits) # The plot bounding box is a sphere in the sense of the infinity # norm, hence I call half the max range the plot radius. plot_radius = 0.5*max([x_range, y_range, z_range]) ax.set_xlim3d([x_middle - plot_radius, x_middle + plot_radius]) ax.set_ylim3d([y_middle - plot_radius, y_middle + plot_radius]) ax.set_zlim3d([z_middle - plot_radius, z_middle + plot_radius]) fig = plt.figure() ax = fig.gca(projection='3d') ax.set_aspect('equal') X = np.random.rand(100)*10+5 Y = np.random.rand(100)*5+2.5 Z = np.random.rand(100)*50+25 scat = ax.scatter(X, Y, Z) set_axes_equal(ax) plt.show() 

编辑: user2525140的代码应该工作得很好,虽然这个答案据称试图解决一个不存在的错误。 下面的答案只是一个重复(替代)的实现:

 def set_aspect_equal_3d(ax): """Fix equal aspect bug for 3D plots.""" 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])