Matplotlib 3D plot - 输入数据的 2D 格式？

Question

我正在使用 matplotlib 绘制两个参数的函数。我在 matplotlib 教程中复制了一个示例，并用我自己的输入数据进行了转换：向量 X 和 Y（在 -3:3 中相等的空间数字）和 Z=peaks(X,Y)，其中峰值是我事先定义的函数。怎么了？

def peaks(x,y):
   xsq=x**2
   ysq=y**2
   xsq_one=(x+1)**2
   ysq_one=(y+1)**2
   m1=3*(1-x)**2
   m2=10*(x/5-x**3-y**5)
   m3=1/3
   return m1*numpy.exp(-xsq-ysq_one)-m2*numpy.exp(-xsq-ysq)-m3*numpy.exp(-xsq_one-ysq)


from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.gca(projection='3d')
X=Y=numpy.arange(-3,3,0.01).tolist()
Z=[]
for i in range(len(X)):
Z.append(peaks(X[i],Y[i]))

ax.plot_surface(X, Y, Z, rstride=8, cstride=8, alpha=0.3)
cset = ax.contour(X, Y, Z, zdir='z', offset=-100)
cset = ax.contour(X, Y, Z, zdir='x', offset=-40)
cset = ax.contour(X, Y, Z, zdir='y', offset=40)

ax.set_xlabel('X')
ax.set_xlim(-40, 40)
ax.set_ylabel('Y')
ax.set_ylim(-40, 40)
ax.set_zlabel('Z')
ax.set_zlim(-100, 100)

plt.show()

感谢您的建议！

Answer 1

您需要生成网格网格。 X,Y 和 Z 必须是二维数组

import numpy
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import axes3d

def peaks(x,y):
    return x * numpy.sin(y)

fig = plt.figure()
ax = fig.gca(projection='3d')
X = Y= numpy.arange(-3, 3, 0.1).tolist()
X, Y = numpy.meshgrid(X, Y)

Z = []
for i in range(len(X)):
    Z.append(peaks(X[i],Y[i]))

# Z must be an array
Z = numpy.array(Z)

ax.plot_surface(X, Y, Z, rstride=8, cstride=8, alpha=0.3)
cset = ax.contour(X, Y, Z, zdir='z', offset=-8)
cset = ax.contour(X, Y, Z, zdir='x', offset=-8)
cset = ax.contour(X, Y, Z, zdir='y', offset=8)

ax.set_xlabel('X')
ax.set_xlim(-8, 8)
ax.set_ylabel('Y')
ax.set_ylim(-8, 8)
ax.set_zlabel('Z')
ax.set_zlim(-8, 8)

plt.show()

Answer 2

接受的答案不再有效。可悲的是，审阅者拒绝了我建议的编辑，这将使它成为一个可行的答案。所以这里再次给出相同的答案，但需要进行一些小改动以使其在当前版本的 matplotlib 中工作。

    import numpy
    import matplotlib.pyplot as plt
    from mpl_toolkits.mplot3d import axes3d

    def peaks(x,y):
        return x * numpy.sin(y)

    fig = plt.figure()
    ax = fig.gca(projection='3d')
    X = Y= numpy.arange(-3, 3, 0.1).tolist()
    X, Y = numpy.meshgrid(X, Y)

    Z = numpy.zeros(X.shape)
    for i in range(len(X)):
        for j in range(len(Y)):
            Z[i,j] = peaks(X[i,j],Y[i,j])

    ax.plot_surface(X, Y, Z, rstride=8, cstride=8, alpha=0.3)
    cset = ax.contour(X, Y, Z, zdir='z', offset=-8)
    cset = ax.contour(X, Y, Z, zdir='x', offset=-8)
    cset = ax.contour(X, Y, Z, zdir='y', offset=8)

    ax.set_xlabel('X')
    ax.set_xlim(-8, 8)
    ax.set_ylabel('Y')
    ax.set_ylim(-8, 8)
    ax.set_zlabel('Z')
    ax.set_zlim(-8, 8)

    plt.show()