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""" Usage:
pr_plot --in=DIR_NAME --out=OUTPUT_FILENAME
Options:
--in=DIR_NAME Folder in which to search for *.dat files, all of which should be in a P/R column format (outputs from benchmark.py)
--out=OUTPUT_FILENAME Output filename, filetype will determine the format. Possible formats: pdf, pgf, png
"""
import os
import ntpath
import numpy as np
from glob import glob
from docopt import docopt
import matplotlib.pyplot as plt
import logging
import ipdb
logging.basicConfig(level = logging.INFO)
plt.rcParams.update({'font.size': 14})
def trend_name(path):
''' return a system trend name from dat file path '''
head, tail = ntpath.split(path)
ret = tail or ntpath.basename(head)
return ret.split('.')[0]
def get_pr(path):
''' get PR curve from file '''
with open(path) as fin:
# remove header line
fin.readline()
prc = list(zip(*[[float(x) for x in line.strip().split('\t')] for line in fin]))
p = prc[0]
r = prc[1]
return p, r
if __name__ == '__main__':
args = docopt(__doc__)
input_folder = args['--in']
output_file = args['--out']
# plot graphs for all *.dat files in input path
files = glob(os.path.join(input_folder, '*.dat'))
for _file in files:
p, r = get_pr(_file)
name = trend_name(_file)
plt.plot(r, p, label = name)
# Set figure properties and save
logging.info("Plotting P/R graph to {}".format(output_file))
plt.ylim([0.0, 1.05])
plt.xlim([0.0, 0.8])
plt.xlabel('Recall')
plt.ylabel('Precision')
plt.legend(loc="lower right")
plt.savefig(output_file) |