# coding: utf-8

import sys

sys.path.extend(['/Users/jstemm/anaconda/lib/python2.7/site-packages'])

import pandas as pd

import itertools

import datetime

import calendar

import numpy

# import sys

import os

start_day = datetime.datetime(2014, 10, 8, 0, 0)

def wk2num(dt):

return tme

def sid_check(sid):

return 'Other'

topdir = os.path.join(os.getenv('HOME'), '.logstats')

dbdir = os.path.join(os.getenv('HOME'), 'Dropbox', 'workshare', 'batlog')

log = os.path.join(topdir, 'batlog.dat')

#log = os.path.join(topdir, 'example.data')

#D = pd.read_table(wake, names = ['dow', 'month', 'day', 'time', 'tz', 'year', 'user', 'SSID', 'runmode'],

# parse_dates = {'dtime': ['dow', 'month', 'day', 'time', 'year']},

# sep = ' ',

# index_col='dtime',

# header=None)

#D = D.fillna("WiFi Disconnected")

#H = D.groupby('SSID')

DATA = pd.DataFrame(columns=['Capacity', 'CycleCount', 'BatLife',

'CurrentPowerState', 'SSID', 'PCT',

'WiFi', 'Eth'])

with open(log) as f:

for a, b, c, d, e in itertools.izip_longest(*[f]*5):

# parse the date and time

A = a.split()

dt = A[1]+A[2].zfill(2)+A[3]+A[5]

dt = datetime.datetime.strptime(dt, '%b%d%H:%M:%S%Y')

# parse the nework info

sid = sid_check(b.split(' SSID ')[-1].split("\n")[0])

wifistat = b.split()[3]

C = c.split()

if len(C) < 2:

ethstat = "inactive"

elif len(C) >= 3:

ethstat = "active"

# parse the battery info

D = eval(d.split(" = ")[1].replace("=", ":"))

# parse the power state

if len(e) < 7:

E = {'CurrentPowerState': 0}

else:

E = eval(e.split(" = ")[1].replace("=", ":"))

# Create the single-row DataFrame

G = pd.DataFrame({'Capacity': D['Capacity'],

'Current': D['Current'],

'PCT' : (1.*D['Current']/D['Capacity'])*100.,

'BatLife' : D['Capacity']/8440.*100.,

'CycleCount': D['Cycle Count'],

'CurrentPowerState': E['CurrentPowerState'],

'SSID': sid,

'WiFi': wifistat,

'Eth': ethstat}, index=[dt,])

DATA = DATA.append(G)

nDays = (DATA.index[-1].date() - DATA.index[0].date()).days + 1

nTimeOfDay = (60./5)*24 # number of 5 minute samples per day

startDate = DATA.index[0].date()

SSID_namelist = DATA.SSID.unique()

SSID_namelist.sort()

nSSID = len(SSID_namelist)

netnames = SSID_namelist.tolist()

ssids = [netnames.index(i) for i in DATA.SSID]

DATA['ssids'] = ssids

AWAKE = DATA[DATA.CurrentPowerState != 0]

batgrid = numpy.zeros((nTimeOfDay, nDays))*numpy.nan

ssidgrid = numpy.zeros_like(batgrid)*numpy.nan

#awakegrid = numpy.zeros_like(batgrid)

for i in AWAKE.iterrows():

dS = (i[0].date() - startDate).days

tOD = numpy.int(numpy.floor(

(i[0].to_pydatetime() -

datetime.datetime(i[0].year, i[0].month, i[0].day)).seconds/300.))

batgrid[tOD, dS] = i[1].PCT

ssidgrid[tOD, dS] = i[1].ssids

#if i[1].CurrentPowerState !=0:

# awakegrid[tOD, dS] = 1

import matplotlib.pyplot as plt

from matplotlib import cm

# batfig

#################################################

batfig = plt.figure(figsize=(9,6), dpi=300)

ax = batfig.add_subplot(211)

ax.plot_date(DATA.index, DATA['CycleCount'], '-')

ax.set_ylabel('Cycle Count')

ax.set_xticklabels([])

ax.grid('on')

ax.set_title('Battery Statistics')

ax = batfig.add_subplot(212)

ax.plot_date(DATA.index, DATA['BatLife'], 'k.')

ax.set_ylabel('Battery Capacity (%)')

#ax.set_xticklabels([])

ax.grid('on')

#ax = batfig.add_subplot(313)

#ax.plot_date(DATA.index, DATA['Capacity'], 'k.')

#ax.set_ylabel('Battery Current')

#ax.grid('on')

plt.savefig(os.path.join(dbdir, 'batstats.png'), dpi=300)

# batyear

#################################################

batyear = plt.figure(figsize=(10, 5), dpi=300)

ax = batyear.add_axes([0.12, 0.1, 0.9, 0.8])

#c = ax.scatter(DOY, TOD, c=DATA['PCT'], edgecolor='none', marker='s', s=1,

# cmap=cm.rainbow_r, vmax=100., vmin=0.)

c = ax.imshow(batgrid, vmin=0., vmax=100, aspect='auto', interpolation='none',

cmap=cm.jet_r)

ax.set_xlabel('Days')

ax.set_ylabel('Time of Day')

#ax.set_xlim((0, 366))

#ax.set_ylim((-288, 0))

ax.set_yticks(numpy.arange(0, 25, 3)*12)

ax.set_yticklabels(['Midnight', '3am', '6am', '9am', 'Noon', '3pm', '6pm', '9pm', 'Midnight'])

ax.grid('on')

cb = plt.colorbar(c, pad=0.02)

cb.set_label('Battery Percentage')

cb.ax.tick_params(labelsize=8)

plt.savefig(os.path.join(dbdir, 'batyear.png'), dpi=300)

# yearview

#################################################

from matplotlib.colors import ListedColormap as LC

fig = plt.figure(figsize=(10,5), dpi=300)

ax = fig.add_subplot(111)

#c=ax.scatter(DOY, TOD, c=numpy.array(ssids), edgecolor='none', marker='s',

# s=1, cmap=cm.rainbow)

mp = cm.jet_r(numpy.linspace(0, 1, nSSID))

ssidcols = LC(mp, 'ssidcols')

cm.register_cmap(cmap = ssidcols)

ssidtick = AWAKE.ssids.unique()

ssidtick.sort()

ssidtick = ssidtick * (ssidtick.max() / float(nSSID))

ssidtick = ssidtick + ssidtick[1]/2.

c = ax.imshow(ssidgrid, interpolation='none', aspect='auto', cmap=ssidcols)

ax.set_xlabel('Day of Year')

ax.set_ylabel('Time of Day')

#ax.set_xlim((0, 366))

#ax.set_ylim((-288, 0))

ax.set_yticks(numpy.arange(0, 25, 3)*12)

ax.set_yticklabels(['Midnight', '3am', '6am', '9am', 'Noon', '3pm', '6pm', '9pm', 'Midnight'])

ax.grid('on')

cb = plt.colorbar(c)

cb.set_ticks(ssidtick)

cb.set_ticklabels(netnames)

cb.ax.tick_params(labelsize=8)

plt.savefig(os.path.join(dbdir, 'yearview.png'), dpi=300)

# weekstats

#################################################

fig.clf()

#ax = fig.add_axes([0.05, 0.1, 0.7, 0.8])

ax = fig.add_subplot(111)

histbins = numpy.arange(0, 2016, 3)

counts = [wk2num(g) for g in DATA.index]

ax.hist(counts, bins=histbins, histtype='step', label='ALL')

#H = AWAKE.groupby('SSID')

##H = DATA.groupby('SSID')

#for g in H.groups.keys():

# counts = [wk2num(v) for v in H.get_group(g).index]

# ax.hist(counts, bins=histbins, histtype='step', label=g)

ax.set_xticks(numpy.arange(7)*288)

ax.set_xticks((numpy.arange(7)+.5)*288, minor=True)

ax.set_xticklabels([])

ax.set_xticklabels(calendar.day_name[0:7], minor=True)

ax.set_xlim((0, 2016))

ax.set_yticks([])

ax.set_ylim(0, ax.get_ylim()[1]*1.1)

#ax.legend(loc='upper left', bbox_to_anchor=(1, 1), fontsize=10,

# title="SSID", frameon=False)

ax.grid('on', which='major')

ax.set_xlabel('Day of Week')

ax.set_ylabel('Computer Useage')

#plt.suptitle('Computer Useage by Day of Week and SSID')

plt.savefig(os.path.join(dbdir, 'weekstats.png'), dpi=300)

plt.close('all')