jstults

# compare point distributions for I and D optimal designs 
# file: idopt.R
# 
rm(list=ls()) 
library(pwr) 
library(AlgDesign)
library(xtable)

dice = data.frame(var=c("x","y"), low=c(-1,-1), high=c(1,1), center=c(0,0), nLevels=111, round=4, factor=FALSE)
Ispace = gen.factorial(levels=c(111,111),nVars=2,center=TRUE,varNames=c("x","y"))/55 

jstults

# file: polywell_sym.R
#   example of a test design and mixed effect analysis for measuring
#   polywell performance and characterizing symmetry
# author: Josh Stults, www.variousconsequences.com 
# date: 28 July 2012
# see also:
#   http://prometheusfusionperfection.com/2012/07/27/symmetry-test/ 
#   http://cran.r-project.org/web/packages/AlgDesign/index.html
#   www.stat.wisc.edu/~bates/IMPS2008/lme4D.pdf

jstults

#
# experimental designs using different basis
#
library(AlgDesign)

# generate a full factorial combination of factor levels 
candidates = gen.factorial(levels=c(51,51), nVars=2, center=TRUE, varNames=c("X1","X2"))
cand.2 = gen.factorial(levels=c(7,7), nVars=2, center=TRUE, varNames=c("X1","X2"))
# add columns for the orthogonal basis 
candidates = transform(candidates, X1.p = poly(candidates$X1, degree=6), X2.p = poly(candidates$X2, degree=6))

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)