我最近以类似的要求回答了一个问题（使用matplotlib创建了20多种独特的图例颜色）。我在那里展示了您可以映射将线条绘制到颜色图所需的颜色循环。您可以使用相同的过程为每对点获取特定的颜色。
您应该仔细选择颜色图，因为如果颜色图是彩色的，则沿线的颜色过渡可能会显得很剧烈。
或者，您可以更改每个线段的Alpha，范围从0到1。
下面的代码示例中包含一个例程（
highResPoints），用于扩展您的随机游走的点数，因为如果您的点数太少，则过渡可能看起来很困难。我最近提供的另一个答案启发了这段代码：https
:
//stackoverflow.com/a/8253729/717357
import numpy as npimport matplotlib.pyplot as pltdef highResPoints(x,y,factor=10): ''' Take points listed in two vectors and return them at a higher resultion. Create at least factor*len(x) new points that include the original points and those spaced in between. Returns new x and y arrays as a tuple (x,y). ''' # r is the distance spanned between pairs of points r = [0] for i in range(1,len(x)): dx = x[i]-x[i-1] dy = y[i]-y[i-1] r.append(np.sqrt(dx*dx+dy*dy)) r = np.array(r) # rtot is a cumulative sum of r, it's used to save time rtot = [] for i in range(len(r)): rtot.append(r[0:i].sum()) rtot.append(r.sum()) dr = rtot[-1]/(NPOINTS*RESFACT-1) xmod=[x[0]] ymod=[y[0]] rPos = 0 # current point on walk along data rcount = 1 while rPos < r.sum(): x1,x2 = x[rcount-1],x[rcount] y1,y2 = y[rcount-1],y[rcount] dpos = rPos-rtot[rcount] theta = np.arctan2((x2-x1),(y2-y1)) rx = np.sin(theta)*dpos+x1 ry = np.cos(theta)*dpos+y1 xmod.append(rx) ymod.append(ry) rPos+=dr while rPos > rtot[rcount+1]: rPos = rtot[rcount+1] rcount+=1 if rcount>rtot[-1]: break return xmod,ymod#ConSTANTSNPOINTS = 10COLOR='blue'RESFACT=10MAP='winter' # choose carefully, or color transitions will not appear smoooth# create random datanp.random.seed(101)x = np.random.rand(NPOINTS)y = np.random.rand(NPOINTS)fig = plt.figure()ax1 = fig.add_subplot(221) # regular resolution color mapax2 = fig.add_subplot(222) # regular resolution alphaax3 = fig.add_subplot(223) # high resolution color mapax4 = fig.add_subplot(224) # high resolution alpha# Choose a color map, loop through the colors, and assign them to the color # cycle. You need NPOINTS-1 colors, because you'll plot that many lines # between pairs. In other words, your line is not cyclic, so there's # no line from end to beginningcm = plt.get_cmap(MAP)ax1.set_color_cycle([cm(1.*i/(NPOINTS-1)) for i in range(NPOINTS-1)])for i in range(NPOINTS-1): ax1.plot(x[i:i+2],y[i:i+2])ax1.text(.05,1.05,'Reg. Res - Color Map')ax1.set_ylim(0,1.2)# same approach, but fixed color and # alpha is scale from 0 to 1 in NPOINTS stepsfor i in range(NPOINTS-1): ax2.plot(x[i:i+2],y[i:i+2],alpha=float(i)/(NPOINTS-1),color=COLOR)ax2.text(.05,1.05,'Reg. Res - alpha')ax2.set_ylim(0,1.2)# get higher resolution dataxHiRes,yHiRes = highResPoints(x,y,RESFACT)npointsHiRes = len(xHiRes)cm = plt.get_cmap(MAP)ax3.set_color_cycle([cm(1.*i/(npointsHiRes-1))for i in range(npointsHiRes-1)])for i in range(npointsHiRes-1): ax3.plot(xHiRes[i:i+2],yHiRes[i:i+2])ax3.text(.05,1.05,'Hi Res - Color Map')ax3.set_ylim(0,1.2)for i in range(npointsHiRes-1): ax4.plot(xHiRes[i:i+2],yHiRes[i:i+2], alpha=float(i)/(npointsHiRes-1), color=COLOR)ax4.text(.05,1.05,'High Res - alpha')ax4.set_ylim(0,1.2)fig.savefig('gradColorLine.png')plt.show()此图显示了四种情况：
