15

我试图改变从两个数组（例如ax.plot(x,y)）中的数据绘制的线的颜色。颜色应该随着指数的变化而x变化y。我本质上是在尝试捕获数组中数据的自然“时间”参数化x和y.

在一个完美的世界里，我想要这样的东西：

fig = pyplot.figure()
ax  = fig.add_subplot(111)
x   = myXdata 
y   = myYdata

# length of x and y is 100
ax.plot(x,y,color=[i/100,0,0]) # where i is the index into x (and y)

产生一条颜色从黑色到深红色再到鲜红色的线条。

我已经看到了非常适合绘制由某个“时间”数组显式参数化的函数的示例，但我无法让它与原始数据一起使用......

4

1 回答 1

21

第二个示例是您想要的示例...我已经对其进行了编辑以适合您的示例，但更重要的是阅读我的评论以了解发生了什么：

import numpy as np
from matplotlib import pyplot as plt
from matplotlib.collections import LineCollection

x   = myXdata 
y   = myYdata
t = np.linspace(0,1,x.shape[0]) # your "time" variable

# set up a list of (x,y) points
points = np.array([x,y]).transpose().reshape(-1,1,2)
print points.shape  # Out: (len(x),1,2)

# set up a list of segments
segs = np.concatenate([points[:-1],points[1:]],axis=1)
print segs.shape  # Out: ( len(x)-1, 2, 2 )
                  # see what we've done here -- we've mapped our (x,y)
                  # points to an array of segment start/end coordinates.
                  # segs[i,0,:] == segs[i-1,1,:]

# make the collection of segments
lc = LineCollection(segs, cmap=plt.get_cmap('jet'))
lc.set_array(t) # color the segments by our parameter

# plot the collection
plt.gca().add_collection(lc) # add the collection to the plot
plt.xlim(x.min(), x.max()) # line collections don't auto-scale the plot
plt.ylim(y.min(), y.max())
于 2012-04-20T20:32:53.870 回答