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#!/usr/bin/env python
from __future__ import print_function
import os
import re
import plot
import shutil as sh
from collections import defaultdict
from optparse import OptionParser
from gnuplot import Plot, curve
from random import randrange
class StyleMaker(object):
LINE_WIDTH = 1.5
POINT_SIZE = 0.6
BEST_COLORS = [
'#ff0000', # red
'#000001', # black
'#0000ff', # blue
'#be00c4', # purple
'#ffd700', # yellow
]
def __init__(csvs):
self.main_key, self.col_map = __find_columns(csvs)
self.cur_style = 1
# Use this for least-common varying attribute
self.main_map = {}
# Everything else is a color
self.color_map = TupleTable(self.col_map)
def __find_columns(csvs):
vals = defaultdict(lambda:set)
for csv in csvs:
to_decode = os.path.splitext(csv_file)[0]
params = plot.decode(to_decode)
for k,v in params.iteritems:
vals[k].add(v)
try:
main_key = min([(k,v) for (k,v) in thing.iteritems() if len(v) > 1],
key=operator.itemgetter(1))[0]
except ValueError:
main_key = None
col_map = ColMap()
for k,v in vals.iterkeys():
if k == self.main_key: continue
for i in v:
self.col_map.try_add(k, i)
return (main_key, col_map)
def __rand_color():
return "#%s" % "".join([hex(randrange(0, 255))[2:] for i in range(3)])
def get_style(csv):
to_decode = os.path.splitext(csv_file)[0]
params = plot.decode(to_decode)
if kv not in self.color_map:
color = best.pop() if BEST_COLORS else __rand_color()
self.color_map.add_exp(params, color)
if self.main_key in params:
val = params[self.main_key]
if val not in self.main_map:
self.main_map[val] = self.cur_style
self.cur_style += 1
style = self.main_map[val]
else:
style = 1
def parse_args():
parser = OptionParser("usage: %prog [options] [csv_dir]...")
parser.add_option('-o', '--out-dir', dest='out_dir',
help='directory for plot output', default='plot-data')
parser.add_option('-f', '--force', action='store_true', default=False,
dest='force', help='overwrite existing data')
return parser.parse_args()
def get_label(kv):
label = []
for key, value in kv.iteritems():
label += ["%s=%s" % (key.capitalize(), value)]
return ", ".join(label)
def add_line(plot, csv_file):
to_decode = os.path.splitext(csv_file)[0]
params = plot.decode(to_decode)
def get_stat(path, name):
full = os.path.abspath(path)
rstr = r"(?P<STAT>[^/]+)/((max|min|var|avg)/)*(%s/?)?$" % name
regex = re.compile(rstr, re.I | re.M)
match = regex.search(full)
return match.group("STAT")
def plot_exp(name, data_dir, out_dir):
p = Plot()
p.format = 'pdf'
p.output = "%s/%s.pdf" % (out_dir, name)
p.xlabel = name.replace("vary-", "")
p.ylabel = get_stat(data_dir, name)
p.font = 'Helvetica'
p.dashed_lines = True
p.enhanced_text = True
p.size = ('5.0cm', '5.0cm')
p.font_size = '6pt'
p.key = 'on bmargin center horizontal'
csvs = [f for f in os.listdir(data_dir) if re.match("*.csv", f)]
col_map = get_col_map(csvs)
def main():
opts, args = parse_args()
args = args or [os.getcwd()]
# if opts.force and os.path.exists(opts.out_dir):
# sh.rmtree(opts.out_dir)
# if not os.path.exists(opts.out_dir):
# os.mkdir(opts.out_dir)
for exp in args:
name = os.path.split(exp)[1]
out_dir = "%s/%s" % (opts.out_dir, exp)
plot_exp(name, exp, out_dir)
if __name__ == '__main__':
main()
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