jstults

#
# do some simple time series analysis on smartphone os data
# data: http://www.catb.org/esr/comscore/
# commentary: http://esr.ibiblio.org/?p=4368
#

# this file has the market share percentages table 
osdata = t(read.csv("os_stats.csv",header=TRUE,row.names=1))
# this file has the raw userbase in millions 
osdata2 = t(read.csv("os_stats_2.csv",header=TRUE,row.names=1))

jstults

/*
Sampling with the Arduino
  based on examples from 
  http://sites.goggle.com/site/MeasuringStuff
*/
#define FASTADC 1
// defines for setting and clearing register bits
#ifndef cbi
#define cbi(sfr, bit) (_SFR_BYTE(sfr) &= ~_BV(bit))
#endif

jstults

import scipy as sp
from scipy.integrate import ode 
from scipy.optimize import fsolve 
from matplotlib import rc
rc('text', usetex=True)
tick_size = 'large'
label_size = 'xx-large'
rc('xtick', labelsize=8)
rc('ytick', labelsize=8)
rc('legend', fontsize=12)

jstults

import scipy as sp
from scipy.integrate import ode 
from scipy.optimize import fsolve 
from scipy.optimize import fmin 
from matplotlib import rc
rc('text', usetex=True)
tick_size = 'large'
label_size = 'xx-large'
rc('xtick', labelsize=8)
rc('ytick', labelsize=8)

jstults

import scipy as sp
from scipy.integrate import ode 
from scipy.optimize import fsolve 
from matplotlib import rc
rc('text', usetex=True)
tick_size = 'large'
label_size = 'xx-large'
rc('xtick', labelsize=8)
rc('ytick', labelsize=8)
rc('legend', fontsize=12)

jstults

import scipy as sp
from scipy.integrate import ode 
from scipy.optimize import fsolve 
from matplotlib import rc
rc('text', usetex=True)
tick_size = 'large'
label_size = 'xx-large'
rc('xtick', labelsize=8)
rc('ytick', labelsize=8)
rc('legend', fontsize=12)

jstults

import scipy as sp
from scipy.integrate import ode 
from scipy.optimize import fsolve 
from matplotlib import rc
rc('text', usetex=True)
tick_size = 'large'
label_size = 'xx-large'
rc('xtick', labelsize=8)
rc('ytick', labelsize=8)
rc('legend', fontsize=12)

jstults

ssq = function (x) {sum(x ^ 2)}

plotTrend = function (x, st = 1978, en = c(2012, 12), y.pos = NA, x.pos = NA, main.t = "Untitled") {

	### Get trend
	trend = lm(window(x, st, en) ~ I(time(window(x, st, en))))

	### Initialize variables
	N = length(window(x, st, en))
	I = seq(1:N) / frequency(x)

jstults

/* Falkner-Skan ODE

    Zhang, J., Chen, B., 'An iterative method for solving the
    Falkner-Skan equation'

    Nachtsheim, P., Swigert, P., 'Satisfaction of Asymptotic Boundary
    Conditions in Numerical Solution of Systems of Nonlinear Equations
    of Boundary-Layer Type,' NASA TN D-3004, Lewis Research Center,
    Cleveland, Oct, 1965.

jstults

import scipy as sp
from scipy.integrate import ode 
from scipy.optimize import fsolve 
from matplotlib import rc
#rc('text', usetex=True)
tick_size = 'large'
label_size = 'xx-large'
rc('xtick', labelsize=8)
rc('ytick', labelsize=8)
rc('legend', fontsize=12)