figures-report.py
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from optparse import OptionParser
import re
from collections import defaultdict as df
import os
import random
from pandas import DataFrame as DF
import matplotlib.pyplot as plt
# Objective
# Drawn figures of grid reports
#
# Input parameters
# --inputPath=PATH Path of inputfiles
# --outputPath=PATH Path to place output figures
# --figureName single run specific name figure, multifigure first part of name
# --inputFile Use it for a single report
# --version CRF-script version of reports
#
# Output
# training and test data set
#
# Examples
# python figures-reports.py
# --inputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/reports/
# --outputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/figures/
# --figureName FiguresGrid
# --inputFile report_Run1_v11.txt
# -version v11
# python figures-reports.py --inputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/reports/ --outputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/figures/ --figureName FiguresGrid_v1 --inputFile report_Run1_v11.txt ..version v11
__author__ = 'egaytan'
####################################################################################
# FUNCTIONS #
####################################################################################
def Filter(rfile, options,v):
if options[0]=='all':
if rfile[0:6]=='report' and rfile[-7:-4]==v: return(True)
elif rfile in options:
return(True)
return(False)
####################################################################################
# MAIN PROGRAM #
####################################################################################
if __name__ == '__main__':
# Defining parameters
parser = OptionParser()
parser.add_option('--inputPath', dest='inputPath', help='Path of output from CoreNLP', metavar='PATH')
parser.add_option('--outputPath', dest='outputPath', help='Path to place output figures', metavar='PATH')
parser.add_option('--figureName', dest='figureName', help='Specific or first part of figurename', metavar='FILE')
parser.add_option('--version', dest='version', help='script version', metavar='FILE')
parser.add_option('--inputFile', dest='inputFile', help='Use it for a specific report files', metavar='FILE', default='all,')
(options, args) = parser.parse_args()
if len(args) > 0:
parser.error('Any parameter given.\nFor multi input files be sure to seprate the filenames by coma')
sys.exit(1)
print('-------------------------------- PARAMETERS --------------------------------')
print('Path of output from CoreNLP: ' + str(options.inputPath))
print('Path to place output figures: ' + str(options.outputPath))
print('Specific or first part of figurename: ' + str(options.figureName))
print('CRF-script version: ' + str(options.version))
print('-------------------------------- PROCESSING --------------------------------')
rawInputRepotsList = str(options.inputFile).split(',')
reportFileList = [ rfile for rfile in os.listdir(options.inputPath) if Filter(rfile, rawInputRepotsList, str(options.version)) ]
scores = df(dict)
#CV={}
print('Report files: ' + str(options.inputFile ))
print('\n'.join(reportFileList))
print('----------------------------------- NOTE -----------------------------------')
print('\n-------- All chosen report files should be in inputPath given---------------\n')
print('------------------------------- SAVING DATA --------------------------------\n')
for report in reportFileList:
with open(os.path.join(options.inputPath, report), 'r') as File:
string = File.read()
scores[report[7:11]]['CV']=re.findall('best\sCV\sscore\:(\d+\.\d+)', string)[0]
summaryScores = re.findall('avg\s\/\stotal\s+(\d+\.\d+)\s+(\d+\.\d+)\s+(\d+\.\d+)', string)[0]
scores[report[7:11]]['precision']=summaryScores[0]
scores[report[7:11]]['recall']=summaryScores[1]
scores[report[7:11]]['f1-score']=summaryScores[2]
print(DF(scores).T)
scoresTable = DF(scores).T
imageName=os.path.join(options.outputPath, options.figureName)
ylab = "score",
fig = plt.figure()
plt.grid(False)
plt.rcParams.update({'font.size': 15})
fig.set_figheight(13)
fig.set_figwidth(20)
plt.xlabel("Runs")
plt.ylabel("score")
plt.xticks(range(8),scoresTable["CV"].index)
plt.plot(scoresTable['CV'], "--", color="red", label="CV")
plt.plot(scoresTable['precision'], color="blue", label="precision")
plt.plot(scoresTable['f1-score'], color="orange", label="F1")
plt.plot(scoresTable['recall'], color="g", label="recall")
plt.legend(loc='lower right')
plt.tight_layout()
fig.savefig(imageName, pad_inches=0.5)