def main():
if len(sys.argv) != 3:
helper.msg("Usage: sample Path SamplingFrequency")
exit(0)
pathname = sys.argv[1]
samplingfreq = int(sys.argv[2])
filelist = sorted(os.listdir(pathname))
filelist = [os.path.join(pathname, filename) for filename in filelist]
(_, startdate, _) = helper.readtwitterfile(filelist[0])
filesize, twfile = 0, []
for filename in filelist:
helper.printinline("Reading %s", filename)
(_filesize, _, _twfile) = helper.readtwitterfile(filename)
filesize += _filesize
twfile += _twfile
timeseries = helper.totimeseries(
twfile, startdate, samplingfreq, filesize)
# store metadata and time seires as a tuple
print json.dumps((str(startdate), samplingfreq, timeseries))
def main():
if len(sys.argv) < 4 or len(sys.argv) > 5:
helper.msg(
"Usage: timeanalysis TimeseriesFile Top ScalingFactor [plotname]\n"
)
exit(0)
filename = sys.argv[1]
top = int(sys.argv[2])
scalingfactor = int(sys.argv[3])
helper.msg("Reading the file...\n")
filedata = json.load(open(filename))
helper.msg("[DONE]\n")
helper.msg("Parsing the file...\n")
startdate_str, freq, timeseries = filedata
startdate = helper.strtodate(startdate_str)
helper.msg("[DONE]\n")
perminute, sorted_perminute = {}, {}
for category in timeseries:
helper.msg("Changing the time scale...\n")
perminute[category] = helper.scaletime(timeseries[category],
scalingfactor)
helper.msg("[DONE]\n")
tickcount = len(perminute[category])
sorted_perminute[category] = [(dict)] * tickcount
helper.msg("Calculating the top topics...\n")
for tick in range(tickcount):
sorted_perminute[category][tick] = dict(
sorted(perminute[category][tick].items(),
key=lambda l: l[1],
reverse=True)[:top])
#print helper.findtops(perminute[category], top)
print json.dumps((startdate_str, scalingfactor * freq, sorted_perminute))
if len(sys.argv) == 5:
plotname = sys.argv[4]
for category in sorted_perminute:
#print sorted_perminute
helper.plot(sorted_perminute[category], startdate,
scalingfactor * freq, plotname + " " + category)
def main():
if len(sys.argv) < 4 or len(sys.argv) > 5:
helper.msg("Usage: timeanalysis TimeseriesFile Top ScalingFactor [plotname]\n")
exit(0)
filename = sys.argv[1]
top = int(sys.argv[2])
scalingfactor = int(sys.argv[3])
helper.msg("Reading the file...\n")
filedata = json.load(open(filename))
helper.msg("[DONE]\n")
helper.msg("Parsing the file...\n")
startdate_str, freq, timeseries = filedata
startdate = helper.strtodate(startdate_str)
helper.msg("[DONE]\n")
perminute, sorted_perminute = {}, {}
for category in timeseries:
helper.msg("Changing the time scale...\n")
perminute[category] = helper.scaletime(
timeseries[category], scalingfactor)
helper.msg("[DONE]\n")
tickcount = len(perminute[category])
sorted_perminute[category] = [(dict)]*tickcount
helper.msg("Calculating the top topics...\n")
for tick in range(tickcount):
sorted_perminute[category][tick] = dict(
sorted(perminute[category][tick].items(),
key=lambda l: l[1], reverse=True) [:top]
)
#print helper.findtops(perminute[category], top)
print json.dumps((startdate_str, scalingfactor * freq, sorted_perminute))
if len(sys.argv) == 5:
plotname = sys.argv[4]
for category in sorted_perminute:
#print sorted_perminute
helper.plot(sorted_perminute[category],
startdate, scalingfactor * freq, plotname + " " + category)