Question

我有以下代码，它们基本上加载了一些我在不同文件夹中的数据文件，取每个温度下每个重复的平均值，然后绘制结果。该代码工作正常，当我只有几组数据时还可以。但是现在我有9组不同的温度，每组5次重复，我认为代码变得太长了。有没有办法巩固它？谢谢！

import numpy as np 
import matplotlib.pyplot as plt

steps    = np.loadtxt('/home/aperego/data/HexaPaper/nvt/303K/1st/Average_MSD.txt',usecols=[0])


# T = 303 K

msd303_1 = np.loadtxt('/home/aperego/data/HexaPaper/nvt/303K/1st/Average_MSD.txt',usecols=[1])
msd303_2 = np.loadtxt('/home/aperego/data/HexaPaper/nvt/303K/2nd/Average_MSD.txt',usecols=[1])
msd303_3 = np.loadtxt('/home/aperego/data/HexaPaper/nvt/303K/3rd/Average_MSD.txt',usecols=[1])
msd303_4 = np.loadtxt('/home/aperego/data/HexaPaper/nvt/303K/4th/Average_MSD.txt',usecols=[1])
msd303_5 = np.loadtxt('/home/aperego/data/HexaPaper/nvt/303K/5th/Average_MSD.txt',usecols=[1])

msd303 = np.vstack((msd303_1,msd303_2,msd303_3,msd303_4,msd303_5)).T
msd303_mean = np.mean(msd303,axis=1)
msd303_std = np.std(msd303,axis=1)

# T = 313 K

msd313_1 = np.loadtxt('/home/aperego/data/HexaPaper/nvt/313K/1st/Average_MSD.txt',usecols=[1])
msd313_2 = np.loadtxt('/home/aperego/data/HexaPaper/nvt/313K/2nd/Average_MSD.txt',usecols=[1])
msd313_3 = np.loadtxt('/home/aperego/data/HexaPaper/nvt/313K/3rd/Average_MSD.txt',usecols=[1])
msd313_4 = np.loadtxt('/home/aperego/data/HexaPaper/nvt/313K/4th/Average_MSD.txt',usecols=[1])
msd313_5 = np.loadtxt('/home/aperego/data/HexaPaper/nvt/313K/5th/Average_MSD.txt',usecols=[1])

msd313 = np.vstack((msd313_1,msd313_2,msd313_3,msd313_4,msd313_5)).T
msd313_mean = np.mean(msd313,axis=1)
msd313_std = np.std(msd313,axis=1)


plt.yscale("log")
plt.xscale("log")
plt.plot(steps,msd303_mean)
plt.plot(steps,msd313_mean)

Answer 1

np.loadtxt('/home/aperego/data/HexaPaper/nvt/303K/1st/Average_MSD.txt',usecols=[1])

由于您经常执行此操作，请尝试替换为

def load(pos):
    return np.loadtxt('/home/aperego/data/HexaPaper/nvt/303K/'+pos+'/Average_MSD.txt',usecols=[1])

然后使用msd303_1 = load('1st')。不是很大的改进，但是可读性更高。

使Python代码更加紧凑和高效

1 个答案: