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原文链接：https://blog.csdn.net/a1920993165/article/details/122277716
python画带方差的折线图
画好后效果图（直接一个图的）
实现代码如下
点击查看代码
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import pyplot
plt.style.use('seaborn-whitegrid')
palette = pyplot.get_cmap('Set1')
font1 = {'family' : 'Times New Roman',
'weight' : 'normal',
'size' : 32,
}
fig=plt.figure(figsize=(20,10))
iters=list(range(7))
#这里随机给了alldata1和alldata2数据用于测试
alldata1=[]#算法1所有纵坐标数据
data=np.array([2,4,5,8,11,13,15])#单个数据
alldata1.append(data)
data=np.array([2,3,6,12,13,13,15])
alldata1.append(data)
data=np.array([2,2,7,9,13,14,16])
alldata1.append(data)
alldata1=np.array(alldata1)
alldata2=[]#算法2所有纵坐标数据
data=np.array([2,4,5,8,10,10,11])#单个数据
alldata2.append(data)
data=np.array([3,3,3,6,7,8,10])
alldata2.append(data)
data=np.array([3,3,5,5,6,7,9])
alldata2.append(data)
alldata2=np.array(alldata2)
def draw_line(name_of_alg,color_index,datas):
color=palette(color_index)
avg=np.mean(datas,axis=0)
std=np.std(datas,axis=0)
r1 = list(map(lambda x: x[0]-x[1], zip(avg, std)))#上方差
r2 = list(map(lambda x: x[0]+x[1], zip(avg, std)))#下方差
plt.plot(iters, avg, color=color,label=name_of_alg,linewidth=3.5)
plt.fill_between(iters, r1, r2, color=color, alpha=0.2)
draw_line("alg1",1,alldata1)
draw_line("alg2",2,alldata2)
plt.xticks(fontsize=22)
plt.yticks(fontsize=22)
plt.xlabel('Time(s)',fontsize=32)
plt.ylabel('metric',fontsize=32)
plt.legend(loc='upper left',prop=font1)
plt.title("instance",fontsize=34)
画好后效果图（在ax子图里面的）
点击查看代码
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import pyplot
plt.style.use('seaborn-whitegrid')
palette = pyplot.get_cmap('Set1')
font1 = {'family' : 'Times New Roman',
'weight' : 'normal',
'size' : 18,
}
fig=plt.figure(figsize=(20,10))
iters=list(range(7))
#这里随机给了alldata1和alldata2数据用于测试
alldata1=[]#算法1所有纵坐标数据
data=np.array([2,4,5,8,11,13,15])#单个数据
alldata1.append(data)
data=np.array([2,3,6,12,13,13,15])
alldata1.append(data)
data=np.array([2,2,7,9,13,14,16])
alldata1.append(data)
alldata1=np.array(alldata1)
alldata2=[]#算法2所有纵坐标数据
data=np.array([2,4,5,8,10,10,11])#单个数据
alldata2.append(data)
data=np.array([3,3,3,6,7,8,10])
alldata2.append(data)
data=np.array([3,3,5,5,6,7,9])
alldata2.append(data)
alldata2=np.array(alldata2)
for i in range(2):
color=palette(0)#算法1颜色
ax=fig.add_subplot(1,2,i+1)
avg=np.mean(alldata1,axis=0)
std=np.std(alldata1,axis=0)
r1 = list(map(lambda x: x[0]-x[1], zip(avg, std)))#上方差
r2 = list(map(lambda x: x[0]+x[1], zip(avg, std)))#下方差
ax.plot(iters, avg, color=color,label="algo1",linewidth=3.0)
ax.fill_between(iters, r1, r2, color=color, alpha=0.2)
color=palette(1)
avg=np.mean(alldata2,axis=0)
std=np.std(alldata2,axis=0)
r1 = list(map(lambda x: x[0]-x[1], zip(avg, std)))
r2 = list(map(lambda x: x[0]+x[1], zip(avg, std)))
ax.plot(iters, avg, color=color,label="algo2",linewidth=3.0)
ax.fill_between(iters, r1, r2, color=color, alpha=0.2)
ax.legend(loc='lower right',prop=font1)
ax.set_xlabel('Outer loop iterations',fontsize=22)
ax.set_ylabel('Objectives',fontsize=22)
标签：alldata2,python,color,alldata1,csdn,画带,np,array,data From： https://www.cnblogs.com/devilmaycry812839668/p/18230265