my_cmap_rgb = plt.get_cmap('winter')(np.arange(256)) alpha = 0.5 for i in range(3): # Do not include the last column! my_cmap_rgb[:,i] = (1 - alpha) + alpha*my_cmap_rgb[:,i] my_cmap = mpl.colors.ListedColormap(my_cmap_rgb, name='my_cmap') 1. 2. 3. 4. 5. ...
在mpl.cm.get_cmap函数中有两个参数,第一个是颜色名,第二个是颜色分段数。颜色名有很多种,比如jet,viridis,spring等等,可根据实际需要选择,本程序中颜色名采用了rainbow。程序中需要的颜色种类是根据城市个数决定的,所以是cityN。 import matplotlib.pyplot as plt import numpy as np import matplotlib as mpl ...
cm import get_cmap from matplotlib.colors import from_levels_and_colors import cartopy.crs as ccrs import cartopy.feature as cfeature import cartopy.io.shapereader as shpreader from cartopy.feature import NaturalEarthFeature from cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatter from ...
(h2))) # y值重复20次 z2 = np.outer(np.ones(len(u2)),h2) # x,y 对应的高度 pole = ax.pot_surface(x2, y2, z2, cmap=cm.get_cmap('summer') ) #cmap=cm.get_cmap('Greens'),cmap=cm.get_cmap('summer'),color='g' plt.axis('off') fig.savefig('redRose.png', transparent=...
from 示例.mpl_squares import RandomWalk # 创建RandomWalk实例,并且将包含的点都绘制出来 rw = RandomWalk() rw.fill_walk() # 给点着色 point_numbers = list(range(rw.num_points)) plt.scatter(rw.x_values, rw.y_values, c=point_numbers,cmap=plt.cm.Greens,s=15) ...
plt.contourf(xx, yy, zMat, 100, cmap=plt.cm.get_cmap('jet'), origin='lower', levels = levels) plt.annotate(showText, xy=(x[xMax],y[yMax]), xytext=(x[xMax],y[yMax]),fontsize=10) plt.colorbar() plt.xlabel('Xupt')
cmap=plt.cm.YlOrRd 然后我们把每个省的数据映射到colormap上: 代码语言:javascript 代码运行次数:0 运行 AI代码解释 colors[s]=cmap(np.sqrt((pop-vmin)/(vmax-vmin)))[:3] 最后,我们把各个省的颜色描在地图上: 代码语言:javascript 代码运行次数:0 ...
cm.get_cmap('hsv')) m.scatter(x, y, c=val, s=1.0, marker="s", zorder=1, vmin=vmin,vmax=vmax, cmap=plt.cm.get_cmap('hsv'), alpha=1.0) m.colorbar(location='bottom', label='Brightness Temperature [K]') m.drawcoastlines() m.drawcountries() m.drawmapboundary(fill_color='...
y = np.linspace(-3,3, n)# 生成网格数据X, Y = np.meshgrid(x, y)# 填充等高线的颜色, 8是等高线分为几部分plt.contourf(X, Y, f(X, Y),8, alpha =0.75, cmap = plt.cm.hot)# 绘制等高线C = plt.contour(X, Y, f(X, Y),8, colors ='black', linewidth =0.5)# 绘制等高线数据plt...