python - 根据 Matplotlib 中的 y 值使线图的某些部分具有不同的颜色

Question

我正在制作一个程序，它采用随机数据列表并将其绘制出来。如果它超过某个值，我希望图表的颜色发生变化。

https://matplotlib.org/gallery/lines_bars_and_markers/multicolored_line.html Matplotlib 有一个关于这样做的条目，但它似乎需要使用函数作为不使用列表的图形的输入。

有谁知道如何将其转换为适用于列表或其他方式？

到目前为止，这是我的代码（没有我可怕的失败尝试对它们进行颜色编码）

from matplotlib import pyplot as plt
import random
import sys
import numpy as np

#setting the max and min values where I want the colour to change
A_min = 2
B_max = 28

#makes lists for later
A_min_lin = []
B_max_lin = []

#simulating a corruption of the data where it returns all zeros
sim_crpt = random.randint(0,10)
print(sim_crpt)
randomy = []
if sim_crpt == 0:
    randomy = []
    #making the empty lists for corrupted data
    for i in range(0,20):
        randomy.append(0)
    print(randomy)
else:
    #making a random set of values for the y axis
    for i in range(0,20):
        n = random.randint(0,30)
        randomy.append(n)
    print(randomy)


#making an x axis for time
time = t = np.arange(0, 20, 1)

#Making a list to plot a straight line showing where the maximum and minimum values
for i in range(0, len(time)):
    A_min_lin.append(A_min)
    B_max_lin.append(B_max)


#Testing to see if more than 5 y values are zero to return if it's corrupted
tracker = 0
for i in (randomy):
    if i == 0:
        tracker += 1
    if tracker > 5:
        sys.exit("Error, no data")

#ploting and showing the different graphs
plt.plot(time,randomy)
plt.plot(time,A_min_lin)
plt.plot(time,B_max_lin)
plt.legend(['Data', 'Minimum for linear', "Maximum for linear"])
plt.show

标签： pythonmatplotlib

Answer 1

您可以使用np.interp生成细粒度数据来绘制：

# fine grain time
new_time = np.linspace(time.min(), time.max(), 1000)

# interpolate the y values
new_randomy = np.interp(new_time, time, randomy)

# this is copied from the link with few modification
points = np.array([new_time, new_randomy]).T.reshape(-1, 1, 2)
segments = np.concatenate([points[:-1], points[1:]], axis=1)

fig, axs = plt.subplots()
norm = plt.Normalize(new_randomy.min(), new_randomy.max())
lc = LineCollection(segments, cmap='viridis', norm=norm)
# Set the values used for colormapping
lc.set_array(new_randomy[1:])
lc.set_linewidth(2)
line = axs.add_collection(lc)
fig.colorbar(line, ax=axs)

# set the limits
axs.set_xlim(new_time.min(), new_time.max())
axs.set_ylim(new_randomy.min(), new_randomy.max())
plt.show()

输出：