问题描述
当我绘制pcolormesh图时，请使用色图from matplotlib.cm(例如"jet"，"Set2"等)，我可以使用:
When I plot the pcolormesh plot use the colormap from matplotlib.cm (like "jet", "Set2", etc), I can use:
cMap = plt.cm.get_cmap("jet",lut=6)
颜色栏显示如下:
但是如果我想从Basemap包中调用颜色图(例如GMT_drywet，GMT_no_green等).我不能使用plt.cm,get_cmap来获取这些颜色图并对其进行划分.
But if I want to call the colormap from the Basemap package (like GMT_drywet, GMT_no_green, etc). I can't use plt.cm,get_cmap to get these colormap and divide them.
mpl_toolkits.basemap.cm是否具有与lut类似的功能?
Does mpl_toolkits.basemap.cm have a similiar function like lut?
推荐答案
只要您制作的绘图具有离散的颜色值(例如contour或contourf)，则colorbar应该会自动生成带有不连续的步骤.这是一个基于来自basemap文档的第一个示例的图:
As long as the plot you are making has discrete color values (e.g. contour or contourf), then colorbar should automatically generate a colorbar with discrete steps. Here's a plot based on the first example from the basemap documentation:
from mpl_toolkits.basemap import Basemap, cm
import matplotlib.pyplot as plt
import numpy as np
fig, ax = plt.subplots(1, 1)
ax.hold(True)
map = Basemap(projection='ortho',lat_0=45,lon_0=-100,resolution='l')
map.drawcoastlines(linewidth=0.25)
map.drawcountries(linewidth=0.25)
map.fillcontinents(color='coral',lake_color='aqua')
map.drawmapboundary(fill_color='aqua')
map.drawmeridians(np.arange(0,360,30))
map.drawparallels(np.arange(-90,90,30))
nlats = 73; nlons = 145; delta = 2.*np.pi/(nlons-1)
lats = (0.5*np.pi-delta*np.indices((nlats,nlons))[0,:,:])
lons = (delta*np.indices((nlats,nlons))[1,:,:])
wave = 0.75*(np.sin(2.*lats)**8*np.cos(4.*lons))
mean = 0.5*np.cos(2.*lats)*((np.sin(2.*lats))**2 + 2.)
x, y = map(lons*180./np.pi, lats*180./np.pi)
map.contourf(x,y,wave+mean,15, alpha=0.5, cmap=cm.GMT_drywet)
cb = map.colorbar()
plt.show()
这篇关于如何使用mpl_toolkits.basemap.cm中的色图创建离散色条?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！