import matplotlib.pyplot as plt
import numpy as np
from scipy.interpolate import make_interp_spline
def readLoss(path, x, y):
i = 0
y.append(float(0))
x.append(float(0))
with open(path, "r", encoding='utf-8') as file:
datas = file.readlines()
for data in datas:
i = i + 1
x.append(i)
y.append(float(data))
#x = np.array(x)
#y = np.array(y)
file.close()
#return x, y
if __name__=="__main__":
print("asd")
y1 = []
x1 = []
#x1, y1 = readLoss("DPF.txt", x1, y1)
i = 0
y1.append(float(0))
x1.append(float(0))
with open("DPF.txt", "r", encoding='utf-8') as file:
datas = file.readlines()
for data in datas:
i = i + 1
x1.append(i)
y1.append(float(data))
file.close()
y2 = []
x2 = []
x2, y2 = readLoss("DPF-DWT-50.txt", x2, y2)
y3 = []
x3 = []
x3, y3 = readLoss("DPF-perc-L1.txt", x3, y3)
y4 = []
x4 = []
x4, y4 = readLoss("DPF-perc-ssim-L1.txt", x4, y4)
plt.figure()
plt.plot(x1, y1, label='DPF')
plt.plot(x2, y2, label='DPF-DWT-50')
plt.plot(x3, y3, label='DPF-perc-L1')
plt.plot(x4, y4, label='DPF-perc-ssim-L1')
plt.xlabel('Epochs')
plt.ylabel('PSNR')
plt.title('Loss Function Comparison')
plt.legend()
plt.savefig("Loss.png")
#x = np.array(x)
#y = np.array(y)
#X_Y_Spline = make_interp_spline(x, y)
#X_ = np.linspace(x.min(), x.max(), 100)
#Y_ = X_Y_Spline(X_)
#plt.xlim(0, 50)
#plt.ylim(17, 22)
标签:plt,曲线图,Python,float,DPF,file,y1,CV,append
From: https://www.cnblogs.com/starcos/p/17814445.html