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gmxFrequency.py
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# -*- coding: utf-8 -*-
"""
Created on Tue Apr 14 14:53:46 2020
@author: 郝蛤蛤
"""
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import random
import colorsys
import sys
import csv
#区分度高的随机RPG颜色
def get_n_hls_colors(num):
hls_colors = []
i = 0
step = 360.0 / num
while i < 360:
h = i
s = 90 + random.random() * 10
l = 50 + random.random() * 10
_hlsc = [h / 360.0, l / 100.0, s / 100.0]
hls_colors.append(_hlsc)
i += step
return hls_colors
print(hls_colors)
def ncolors(num):
rgb_colors = []
if num < 1:
return rgb_colors
hls_colors = get_n_hls_colors(num)
for hlsc in hls_colors:
_r, _g, _b = colorsys.hls_to_rgb(hlsc[0], hlsc[1], hlsc[2])
r, g, b = [int(x * 255.0) for x in (_r, _g, _b)]
rgb_colors.append([r, g, b])
return rgb_colors
def color(value):
digit = list(map(str, range(10))) + list("ABCDEF")
if isinstance(value, tuple):
string = '#'
for i in value:
a1 = i // 16
a2 = i % 16
string += digit[a1] + digit[a2]
return string
elif isinstance(value, str):
a1 = digit.index(value[1]) * 16 + digit.index(value[2])
a2 = digit.index(value[3]) * 16 + digit.index(value[4])
a3 = digit.index(value[5]) * 16 + digit.index(value[6])
return (a1, a2, a3)
def frequencyList(bins, data_choiced): # 此函数用于计算频数并输出频数列表
# 频数列表
max_data_choiced = max(data_choiced)
min_data_choiced = min(data_choiced)
differentNum = (max_data_choiced - min_data_choiced) / bins
divideList = []
for i in range(0, bins):
area = [min_data_choiced + (differentNum * i), min_data_choiced + (differentNum * (i + 1))]
divideList.append(area)
# print(divideList)
frequencyList = []
frequencyList_x = []
for j in range(0, bins):
frequencyNum = 0
for single_data in data_choiced:
if divideList[j][0] < single_data < divideList[j][1]:
frequencyNum += 1
frequencyList.append(frequencyNum)
frequencyList_x.append(divideList[j][0])
frequencyList = [((x/len(data_choiced))*100) for x in frequencyList] # 计算频率
# print(sum(frequencyList))
return frequencyList, frequencyList_x
def reductionList(old_list): # 降维
# 把列表转为字符串
b = str(old_list)
# 替换掉'['和']'
b = b.replace('[', '')
b = b.replace(']', '')
# 最后转化成列表
new_list = list(eval(b))
return new_list
if __name__ == '__main__':
#定义字体类型
plt.rc('font', family='Times New Roman')
#定义分割份数, 默认50
# bins = 50
filename = sys.argv[1]
unitsx = sys.argv[2]
unitsy = sys.argv[3]
bins_list = [20, 50, 100, 1000]
# showfig = sys.argv[4] #0表示不显示, 1表示显示
# 读取x轴的数据，也就是第一列数据
datax = pd.read_csv(filename, usecols=[0])
data_x_list = datax.values.tolist()
# data_choiced = list(data.iloc[:, 1])
# # 频数列表
# max_data_choiced = max(data_choiced)
# min_data_choiced = min(data_choiced)
# differentNum = (max_data_choiced - min_data_choiced) / bins
#
# divideList = []
# for i in range(0, bins):
# area = [min_data_choiced + (differentNum * i), min_data_choiced + (differentNum * (i + 1))]
# divideList.append(area)
#
# print(divideList)
# frequencyList = []
# for j in range(0, bins):
# frequencyNum = 0
# for single_data in data_choiced:
# if divideList[j][0] < single_data < divideList[j][1]:
# frequencyNum += 1
# frequencyList.append(frequencyNum)
# plt.plot(frequencyList(bins, data_choiced))
# plt.show()
for bins in bins_list:
input_csv = csv.reader(open(filename, 'r')) # 读取并判断有多少列数
row_num = ""
for row in input_csv:
row_num = row
# print(len(row_num))
fig = plt.figure()
colorlist = list(map(lambda x: color(tuple(x)), ncolors(len(row_num))))
# 颜色初始化
colorlist.insert(1, 'black')
colorlist.insert(3, 'red')
colorlist.insert(5, 'blue')
colorlist.insert(7, '#046804')
colorlist.insert(9, '#040484')
colorlist.insert(11, '#FF00FF')
print("colorlist:" + str(colorlist))
ranNum_list = []
datax_whole = []# 记录所有的csv的x坐标
datay_whole = [] # 记录所有的csv的y坐标
for num in range(1, len(row_num)):
# exec('listy' + str(i) + ' = ' + datay.values.tolist())
while (len(ranNum_list) < len(colorlist)):
ranNum = random.randint(0, len(colorlist) - 1)
if ranNum not in ranNum_list:
ranNum_list.append(ranNum)
print("本次迭代数字" + str(ranNum_list[num - 2]))
# rancolor = colorlist[ranNum_list[num - 3]]
rancolor = colorlist[num]
if num % 2 != 0:
# print(num)
# datay = pd.read_csv(filename, usecols=[num])
data_choiced = pd.read_csv(filename, usecols=[num])
outfit = str(data_choiced.columns)
outfit = outfit.replace("Index([\'", "") # 正则表达式总是学不会，那我只能暴力替换了
outfit = outfit.replace("Index([u\'", "")
outfit = outfit.replace("\'], dtype=\'object\')", "")
outfit = outfit.replace(".2", "")
outfit = outfit.replace(".1", "")
outfit = outfit.replace(".xvg", "")
# 随机颜色
# colorArr = ['1', '2', '3', '4', '5', '6', '7', '8', '9', 'A', 'B', 'C', 'D', 'E', 'F']
# rancolor = ""
# for i in range(6):
# rancolor += colorArr[random.randint(0, 14)]
# print(rancolor)
# print(outfit)
# 批量定义
# listy = str(datay.values.tolist())
data_choiced = reductionList(data_choiced.values.tolist())
# listy = str(frequencyList(bins, data_choiced))
list_whole = frequencyList(bins, data_choiced)
listy = str(list_whole[0])
listx = list_whole[1]
# listx = [round(x, 1) for x in listx] # 四舍五入生成式
# print(listx)
exec('listx' + str(num) + ' = ' + str(listx))
exec('listy' + str(num) + ' = ' + listy) # 批量定义列到变量
exec('outfit' + str(num) + ' = ' + ' \" ' + outfit + ' \" ') # 批量定义表头到变量
# exec('data_y' + str(num) + ' = ' + str('data_y' + str(num)))
exec('data_y' + str(num) + ' = ' + str("list(" + "listy" + str(num) + ")"))
exec('data_x' + str(num) + ' = ' + str("list(" + "listx" + str(num) + ")"))
exec('datax_whole.append(data_x' + str(num) + ')')
exec('datay_whole.append(data_y' + str(num) + ')')
exec('DM' + str(num) + '=' + str("fig.add_subplot(1, 1, 1)"))
exec('DM' + str(num) + '.plot(data_x' + str(num) + ',data_y' + str(num) + ", 'm-', label=outfit"
+ str(num) + ", color='" + rancolor + "'" + ', linewidth=1, alpha=0.8)')
datax_whole = reductionList(datax_whole) # 给大列表降维
datay_whole = reductionList(datay_whole) # 给大列表降维
DM1.legend(frameon=False) # 图例，去掉框框
# print(datay_whole)
plt.xlim(min(datax_whole), round(max(datax_whole), 1)) # 坐标轴范围
plt.ylim(min(datay_whole), max(datay_whole)*1.1)
DM1.set_xlabel(unitsx) # 例如Time(ns)
DM1.set_ylabel(unitsy + " (%)") # 例如RMSD(ns)
# plt.yticks([])
jpgName = filename.replace('.csv', str(bins))
jpgName = jpgName + '.jpg'
plt.savefig(jpgName)