import numpy
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import pylab
import os
import multiprocessing as MP
from P2P_CONSTANTS import *
def plotGraph(x, y, z, filename):
v = [0,5000,0,200]
plt.axis(v)
plt.scatter(x, y, alpha = 0.10, cmap=plt.cm.cool, edgecolors='None')
# plt.colorbar()
pylab.savefig(filename, bbox_inches = 0)
plt.clf()
#scale input data and plot graphs
def processFile(filename):
sem.acquire()
x1 = []
# x2 = []
y = []
z = []
inputfile = open(filename)
for line in inputfile:
fields = line.strip().split(',')
x1.append(float(fields[3]) / 1000)
# x2.append(float(fields[3]) / (1000 * int(fields[2])))
y.append(float(fields[-1]) / 1000)
z.append(float(fields[4]) / 1000)
inputfile.close()
filename = filename.split('/')
outputdir = NEWDIR + filename[-2] + '/'
if not os.path.exists(outputdir):
os.makedirs(outputdir)
plotGraph(x1, y, z, outputdir + filename[-1] + '.png')
# plotGraph(x2, y, z, filename + 'modified.png')
print 'Completed plotting ' + '/'.join(filename)
sem.release()
NEWDIR = SUPERFLOWDATADIR + 'alphachanged/'
if not os.path.exists(NEWDIR):
os.makedirs(NEWDIR)
folders = os.listdir(SUPERFLOWDATADIR)
csvfiles = []
for eachname in folders:
name = SUPERFLOWDATADIR + eachname +'/'
if os.path.isdir(name):
csvfiles += getCSVFiles(name)
print csvfiles
sem = MP.Semaphore(THREADLIMIT)
for eachfile in csvfiles:
task = MP.Process(target = processFile, args = (eachfile,))
task.start()
