Matplotlib 3D绘图 - 输入数据的2D格式?

时间:2012-02-05 20:57:39

标签: python 3d matplotlib mplot3d

我正在使用matplotlib绘制两个参数的函数。我在matplotlib教程中复制了一个例子并用我自己的输入数据进行了转换:向量X和Y(在-3:3中等间隔数字)和Z =峰值(X,Y),峰值是我定义为befohand的函数。有什么问题?

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!

2 个答案:

答案 0 :(得分:6)

您需要生成meshgrid。 X,Y和Z必须是2D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]))

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()

enter image description here

答案 1 :(得分:1)

接受的答案不再适用。可悲的是,审稿人拒绝了我的建议编辑,这将使其成为一个工作asnwer。所以这里再次给出相同的答案,但需要做一些小改动才能使它在matplotlib的当前版本中运行。

    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()