在我的文件系统中,有一些标题和注释以及图形标签。图表标签由@
启动
如何从日志文件中调用我的标题和x和y级别
由@
提及?
@ title "RMSD"
@ xaxis label "Time (ns)"
@ yaxis label "RMSD (nm)"
脚本是:
import numpy as np
import matplotlib.pyplot as plt
import csv
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("-n","--filename", help="filename on")
args = parser.parse_args()
# example data
filename=(args.filename)
x, y = [],[]
with open(filename) as f:
for line in f:
cols = line.split()
if line.split("#"):
pass
if line.split("@"):
pass
try:
if len(cols) == 2:
x.append(float(cols[0]))
y.append(float(cols[1]))
except ValueError:
pass
fig = plt.figure()
ax1 = fig.add_subplot(111)
ax1.set_title("Temperature")
ax1.set_xlabel("time in PS")
ax1.set_ylabel("temp in K")
ax1.plot (x,y, c='r', label='the data')
leg = ax1.legend ()
plt.savefig('data.png', dpi=500)
文件格式为:
# This file was created Wed May 25 12:05:43 2016
# Created by:
# :-) GROMACS - gmx rms, VERSION 5.1.2 (-:
#
# Executable: /usr/local/bin/gmx
# Data prefix: /usr/local
# Command line:
# gmx rms -s md_0_1.tpr -f md_0_1_noPBC.xtc -o rmsd.xvg -tu ns
# gmx rms is part of G R O M A C S:
#
# Great Red Oystrich Makes All Chemists Sane
#
@ title "RMSD"
@ xaxis label "Time (ns)"
@ yaxis label "RMSD (nm)"
@TYPE xy
@ subtitle "Backbone after lsq fit to Backbone"
0.0000000 0.0005027
0.0100000 0.0691386
答案 0 :(得分:0)
你所拥有的方法已经很有希望了。
您基本上需要检查行中的第一个字符是否为@
,如果是,请检查第二个单词。因此,您需要将标题,xlabel,ylabel设置为行中的联合剩余单词。
import numpy as np
import matplotlib.pyplot as plt
import csv
import argparse
filename = "SO_labelsfromcsv.txt"
x, y = [],[]
title = ""
xlabel = ""
ylabel = ""
with open(filename) as f:
for line in f:
cols = line.split()
if cols[0][0] == "#":
pass
elif cols[0][0] == "@":
if cols[1] == "title":
title = " ".join(cols[2:]).replace('"', '')
elif cols[1] == "xaxis":
xlabel = " ".join(cols[3:]).replace('"', '')
elif cols[1] == "yaxis":
ylabel = " ".join(cols[3:]).replace('"', '')
else:
try:
if len(cols) == 2:
x.append(float(cols[0]))
y.append(float(cols[1]))
except ValueError:
pass
fig = plt.figure()
ax1 = fig.add_subplot(111)
ax1.plot(x,y)
ax1.set_title(title)
ax1.set_xlabel(xlabel)
ax1.set_ylabel(ylabel)
plt.show()