matplotlib:改变线的颜色以捕获数据中的自然时间参数化

Question

我试图改变从两个数组中的数据绘制的线的颜色(例如ax.plot(x,y)).颜色应作为索引变化x和y增加.我基本上是试图捕捉自然的"时间"的数据在阵列参数x和y.

在一个完美的世界里,我想要一样的东西:

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)

生产一条颜色从黑色到深红色变为亮红色的线.

我已经看到了一些适用于绘制由某个'time'数组显式参数化的函数的例子,但我无法使用原始数据...

Answer 1

第二个例子是你想要的那个...我编辑它以适合你的例子,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())