matplotlib（相等的單位長度）：'等於'長寬比z軸不等於x-和y-

Question

當我爲三維圖形設置等縱橫比時，z軸不會變爲'等於'。所以，這樣的：

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() 

給我以下：

其中明顯z軸的單位長度不等於X方向和Y單元。

如何讓所有三個軸的單位長度相等？我能找到的所有解決方案都無效。謝謝。

Answer 1

我相信matplotlib還沒有在3D中設置正確的等軸......但是我發現了一些前段時間（我不記得是在哪裏）使用它的技巧。這個概念是在你的數據周圍創建一個假立方體邊界框。 可以用下面的代碼測試：

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() 

ž數據是大約比x和y大一個數量級，但即使有等於軸線選項，matplotlib自動定標Z軸：

但如果添加邊框，您獲得正確的縮放：

Answer 2

我通過使用set_x/y/zlimfunctions簡化了Remy F的解決方案。

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() 

Answer 3

我喜歡上面的解決方案，但他們確實有，你需要跟蹤的範圍和手段上所有數據的缺點。如果您有多個數據集將被繪製在一起，這可能會很麻煩。爲了解決這個問題，我使用了ax.get_ [xyz] lim3d（）方法，並將整個事件放到一個獨立的函數中，在調用plt.show（）之前只能調用一次。這是新版本：

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, e.g., 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() 

Answer 4

編輯： user2525140的代碼應該工作完全正常，雖然這個答案據稱試圖修復一個非 - existant錯誤。下面的答案只是一個重複（替代）實現：

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])