不幸的是，matplotlib没有一个简单的选项来更改一行的一部分颜色.我们将不得不自己编写逻辑.技巧是将线切成线段的集合，然后为每个线段分配颜色，然后绘制它们.

Unfortunately, matplotlib doesn't have an easy option to change the color of only part of a line. We will have to write the logic ourselves. The trick is to cut the line up into a collection of line segments, then assign a color to each of them, and then plot them.

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

# The x and y data to plot
y = np.array([1,2,17,20,16,3,5,4])
x = np.arange(len(y))

# Threshold above which the line should be red
threshold = 15

# Create line segments: 1--2, 2--17, 17--20, 20--16, 16--3, etc.
segments_x = np.r_[x[0], x[1:-1].repeat(2), x[-1]].reshape(-1, 2)
segments_y = np.r_[y[0], y[1:-1].repeat(2), y[-1]].reshape(-1, 2)

# Assign colors to the line segments
linecolors = ['red' if y_[0] > threshold and y_[1] > threshold else 'blue'
              for y_ in segments_y]

# Stamp x,y coordinates of the segments into the proper format for the
# LineCollection
segments = [zip(x_, y_) for x_, y_ in zip(segments_x, segments_y)]

# Create figure
plt.figure()
ax = plt.axes()

# Add a collection of lines
ax.add_collection(LineCollection(segments, colors=linecolors))

# Set x and y limits... sadly this is not done automatically for line
# collections
ax.set_xlim(0, 8)
ax.set_ylim(0, 21)

您的第二个选择要容易得多.我们首先绘制线条，然后将标记作为散点图添加到其上方:

Your second option is much easier. We first draw the line and then add the markers as a scatterplot on top of it:

from matplotlib import pyplot as plt
import numpy as np

# The x and y data to plot
y = np.array([1,2,17,20,16,3,5,4])
x = np.arange(len(y))

# Threshold above which the markers should be red
threshold = 15

# Create figure
plt.figure()

# Plot the line
plt.plot(x, y, color='blue')

# Add below threshold markers
below_threshold = y < threshold
plt.scatter(x[below_threshold], y[below_threshold], color='green') 

# Add above threshold markers
above_threshold = np.logical_not(below_threshold)
plt.scatter(x[above_threshold], y[above_threshold], color='red')