python - 如何在 Python 中制作 3D 图？

Question

这是 3D 绘图代码的 MATLAB 版本: 编辑: 这是当前代码:

        plt.figure(2)
        fig_b = Axes3D(fig2)
        xx2 = np.arange(0, L+h_grid*L, h_grid*L)
        yy2 = np.arange(-b, b+h_grid*b, h_grid*b)
        X, Y = np.meshgrid(xx2, yy2)
        W = np.zeros((41,21), float)
        mx = len(xx2)*len(yy2)
        X = np.reshape(X, (1, mx))
        Y = np.reshape(Y, (1, mx))
        W = np.reshape(W, (1, mx))
        for j in range(0, mx):
            W[0][j] = np.sin(np.pi*X[0][j]/L)
        surf = fig_b.plot_surface(X, Y, W, rstride=1, cstride=1, cmap=cm.jet, linewidth=0, antialiased=False) # This is the line number 168
        plt.xlabel('x')
        plt.ylabel('y')

这是我收到的错误信息:

Traceback (most recent call last):
  File "nonhomog.py", line 247, in <module>
    main()
  File "nonhomog.py", line 245, in main
    nonhomog(nu)
  File "nonhomog.py", line 168, in nonhomog
    surf = fig_b.plot_surface(X, Y, W, rstride=1, cstride=1, cmap=cm.jet, linewidth=0, antialiased=False)
  File "/usr/lib/pymodules/python2.6/mpl_toolkits/mplot3d/axes3d.py", line 618, in plot_surface
    polyc = art3d.Poly3DCollection(polys, *args, **kwargs)
  File "/usr/lib/pymodules/python2.6/mpl_toolkits/mplot3d/art3d.py", line 290, in __init__
    PolyCollection.__init__(self, verts, *args, **kwargs)
  File "/usr/lib/pymodules/python2.6/matplotlib/collections.py", line 668, in __init__
    self.set_verts(verts, closed)
  File "/usr/lib/pymodules/python2.6/mpl_toolkits/mplot3d/art3d.py", line 312, in set_verts
    self.get_vector(verts)
  File "/usr/lib/pymodules/python2.6/mpl_toolkits/mplot3d/art3d.py", line 305, in get_vector
    xs, ys, zs = zip(*points)
ValueError: need more than 0 values to unpack

Answer 1

为 X 和 Y 设置网格后，您需要为 Z 值设置网格。

我目前在我的代码中这样做的方式是:

# [ (x1, y1, z1), (x2, y2, z2), ... (xN, yN, zN) ]
all_vals = ...
# (x1, x2, ... xN) , (y1, y2, ... yN) , (z1, z2, ... zN)
all_xvals, all_yvals, all_zvals = zip(*all_vals)
fig = plt.figure()
ax = Axes3D(fig)
X, Y = np.meshgrid(xvals, yvals)
# This is the part you want:
Z1 = np.zeros(X.shape, float)
for (x, y, z) in all_vals:
    x = find_in_sorted_list(x, xvals)
    y = find_in_sorted_list(y, yvals)
    Z1[y,x] = z    
surf = ax.plot_surface(X, Y, Z1, rstride=1, cstride=1, cmap=cm.jet,
        linewidth=0, antialiased=False)
plt.xlabel('Blur standard deviation')  
plt.ylabel('JPEG quality')
ax.w_zaxis.set_major_locator(LinearLocator(10))
ax.w_zaxis.set_major_formatter(FormatStrFormatter('%.03f'))    
fig.colorbar(surf, shrink=0.5, aspect=5)    
plt.show()

这给了我一个看起来像这样的情节:

我已将它保存为一个文件，但是当您调用 plt.show() 时，您会看到一个交互式窗口，您可以在其中将视点更改为任何您想要的。