import os

import sys

import pylab

import csv

import numpy as np

from collections import defaultdict

files_ = defaultdict(set)

#data_dir_ = '_plots'

#if not os.path.isdir(data_dir_):

# os.makedirs(data_dir_)

def partition_data(mat):

blinkVec, timeVec = mat[:,0], mat[:,1]

i = 0

result = []

xvec, yvec = [], []

for i, t in enumerate(timeVec):

if t == 11:

result.append((xvec, yvec))

xvec, yvec = [], []

xvec.append(timeVec[i])

yvec.append(blinkVec[i])

else:

xvec.append(timeVec[i])

yvec.append(blinkVec[i])

result.append((xvec, yvec))

return result[1:]

def plot_dir(d, files):

data = {}

print("In directory %s total csv files %s" % (d, len(files)))

for f in files:

filepath = os.path.join(d, f)

try:

x = np.genfromtxt(filepath, delimiter=',', skiprows=3)

data[filepath] = x

except:

print("[WARN] Failed to load %s" % filepath)

for i, k in enumerate(data):

print("Processing %s" % k)

pylab.figure()

d = data[k]

chunks = partition_data(d)

length = 0

i = 0

for xv, yv in chunks:

i += 1

new_xv = [ x + length for x in xv]

pylab.plot(new_xv, yv, label="%s" % i)

length += xv[-1]

pylab.legend(loc='best', framealpha=0.4)

# baseline

baseX, baseY = chunks[0]

baseline = np.mean(baseY)

std = np.std(baseY)

pylab.plot([0, length], [baseline, baseline])

pylab.plot([baseX[-1], length], [baseline+2*std]*2)

pylab.plot([baseX[-1], length], [baseline-2*std]*2)

outfile = os.path.join("%s.png" % k)

print("[INFO] Saving to %s" % outfile)

pylab.savefig(outfile)

def plot(**kwargs):

global files_

if not os.path.exists('_data'):

os.makedirs('_data')

for d in files_:

files = files_[d]

plot_dir(d, files)

def main():

for d, sd, fs in os.walk('.'):

for f in fs:

if ".csv" in f:

files_[d].add(f)

plot()

if __name__ == '__main__':

main()