# -*- coding: gbk -*-
from mpl_toolkits.mplot3d import Axes3D
from Matplotlib import cbook
from Matplotlib import cm
from Matplotlib.colors import LightSource
import Matplotlib.pyplot as plt
import numpy as np
from osgeo import gdal
gdal.AllRegister()

filePath = u"E:桌面dem实验/Himalaya.tif" #输入你的dem数据
dataset = gdal.Open(filePath)
adfGeoTransform = dataset.GetGeoTransform()
band = dataset.GetRasterBand(1)  #用gdal去读写你的数据，当然dem只有一个波段
nrows = dataset.RasterXSize 
ncols  = dataset.RasterYSize  #这两个行就是读取数据的行列数
Xmin = adfGeoTransform[0] #你的数据的平面四至
Ymin = adfGeoTransform[3]
Xmax = adfGeoTransform[0] + nrows * adfGeoTransform[1] + ncols * adfGeoTransform[2]
Ymax = adfGeoTransform[3] + nrows * adfGeoTransform[4] + ncols * adfGeoTransform[5]
x = np.linspace(Xmin,Xmax, ncols)
y = np.linspace(Ymin,Ymax, nrows)
X,Y = np.meshgrid(x, y)
Z = band.ReadAsArray(0, 0,nrows, ncols) #这一段就是讲数据的x，y，z化作numpy矩阵
region = np.s_[10:400,10:400]
X, Y, Z = X[region], Y[region],Z[region]
fig, ax = plt.subplots(subplot_kw=dict(projection='3d'), figsize=(12,10))
ls = LightSource(270, 20)  #设置你可视化数据的色带
rgb = ls.shade(Z, cmap=cm.gist_earth, vert_exag=0.1, blend_mode='soft')
surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, facecolors=rgb,
            linewidth=0, antialiased=False, shade=False)
plt.show() #最后渲染出你好看的三维图吧