Python 将背景图像添加到三维打印

本主题已涉及，但没有说明如何在指定的

z

高度创建三维绘图并在

（x，y）

平面中插入图像

为了得到一个简单且可重复的例子，假设我用

mplot3d

创建了一个这样的3D图：

from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
from matplotlib.ticker import LinearLocator, FormatStrFormatter
import matplotlib.pyplot as plt
import numpy as np

fig = plt.figure()
ax = fig.gca(projection='3d')
X = np.arange(-5, 5, 0.25)
Y = np.arange(-5, 5, 0.25)
X, Y = np.meshgrid(X, Y)
R = np.sqrt(X**2 + Y**2)
Z = np.sin(R)
surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.winter,
                       linewidth=0, antialiased=True)
ax.set_zlim(-1.01, 1.01)

ax.zaxis.set_major_locator(LinearLocator(10))
ax.zaxis.set_major_formatter(FormatStrFormatter('%.02f'))

plt.show()

我们有：

在级别

z=min（z）-1

，其中

-1

是一个视觉偏移，以避免重叠，我想插入一个图像，表示曲线显示特定值的元素怎么做？

在这个例子中，我不关心元素和它的值之间的完美匹配，所以请随意上传任何你喜欢的图片。还有，有没有办法让图像旋转，以防人们对匹配不满意

编辑

这是一个为3D柱状图制作的类似东西的视觉示例。级别

z=0

的灰色形状是条形图显示特定

z

值的元素。

---

使用

plot\u surface

通过

facecolors

参数绘制图像

from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
from matplotlib.ticker import LinearLocator, FormatStrFormatter
import matplotlib.pyplot as plt
import numpy as np
from matplotlib._png import read_png
from matplotlib.cbook import get_sample_data

fig = plt.figure()
ax = fig.gca(projection='3d')
X = np.arange(-5, 5, .25)
Y = np.arange(-5, 5, .25)
X, Y = np.meshgrid(X, Y)
R = np.sqrt(X**2 + Y**2)
Z = np.sin(R)
surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.winter,
                       linewidth=0, antialiased=True)

ax.set_zlim(-2.01, 1.01)
ax.zaxis.set_major_locator(LinearLocator(10))
ax.zaxis.set_major_formatter(FormatStrFormatter('%.02f'))

fn = get_sample_data("./lena.png", asfileobj=False)
arr = read_png(fn)
# 10 is equal length of x and y axises of your surface
stepX, stepY = 10. / arr.shape[0], 10. / arr.shape[1]

X1 = np.arange(-5, 5, stepX)
Y1 = np.arange(-5, 5, stepY)
X1, Y1 = np.meshgrid(X1, Y1)
# stride args allows to determine image quality 
# stride = 1 work slow
ax.plot_surface(X1, Y1, -2.01, rstride=1, cstride=1, facecolors=arr)

plt.show()

如果需要添加值，请使用

PathPatch

：

from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
from matplotlib.ticker import LinearLocator, FormatStrFormatter
import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
import mpl_toolkits.mplot3d.art3d as art3d
from matplotlib.text import TextPath
from matplotlib.transforms import Affine2D
from matplotlib.patches import PathPatch

def text3d(ax, xyz, s, zdir="z", size=None, angle=0, usetex=False, **kwargs):
    x, y, z = xyz
    if zdir == "y":
        xy1, z1 = (x, z), y
    elif zdir == "y":
        xy1, z1 = (y, z), x
    else:
        xy1, z1 = (x, y), z

    text_path = TextPath((0, 0), s, size=size, usetex=usetex)
    trans = Affine2D().rotate(angle).translate(xy1[0], xy1[1])

    p1 = PathPatch(trans.transform_path(text_path), **kwargs)
    ax.add_patch(p1)
    art3d.pathpatch_2d_to_3d(p1, z=z1, zdir=zdir)

# main
fig = plt.figure()
ax = fig.gca(projection='3d')
X = np.arange(-5, 5, .25)
Y = np.arange(-5, 5, .25)

Xg, Yg = np.meshgrid(X, Y)
R = np.sqrt(Xg**2 + Yg**2)
Z = np.sin(R)
surf = ax.plot_surface(Xg, Yg, Z, rstride=1, cstride=1, cmap=cm.winter,
                       linewidth=0, antialiased=True)

ax.set_zlim(-2.01, 1.01)
ax.zaxis.set_major_locator(LinearLocator(10))
ax.zaxis.set_major_formatter(FormatStrFormatter('%.02f'))

# add pathces with values
for i,x in enumerate(X[::4]):
    for j,y in enumerate(Y[::4]):
        text3d(ax, (x, y, -2.01), "{0:.1f}".format(Z[i][j]), zdir="z", size=.5, ec="none", fc="k")

plt.show()

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相关：添加到3d绘图中的图像似乎失去了一些亮度。有没有办法保持原来的亮度水平？