""" Laser_plots.py data_dir fig_dir

Read the following data files:

    LaserLP5       Simulated laser data for figure LaserLP5
    LaserLogLike   Dependence of LL on s and b for figure LaserLogLike
    LaserStates    Sequence of 250 states from EKF for figure LaserStates
    LaserForecast  Sequence of 400 scalar values for figure LaserForecast
    LaserHist      Histogram 600 values for figure LaserHist in Chap 3

and make the following figures:

    In Chapter 1:
        LaserLP5.pdf       Figure 1.1
        LaserLogLike.pdf   Figure 1.2
        LaserStates.pdf    Figure 1.3
        LaserForecast.pdf  Figure 1.4
    In Chapter 3:
        LaserHist.pdf      Figure 3.1

"""
import matplotlib, sys, os, os.path, numpy
matplotlib.use('PDF')
import pylab
params = {'axes.labelsize': 12,
               'text.fontsize': 10,
               'legend.fontsize': 10,
               'text.usetex': True,
               'xtick.labelsize': 11,
               'ytick.labelsize': 11}
pylab.rcParams.update(params)

data_dir, fig_dir = sys.argv[1:3]

GP = os.popen("gnuplot","w")
GP.write("""
set terminal postscript eps color
set output "%s"
set hidden
set contour
set xtics .02
set ytics 0.001
set xlabel 's'
set ylabel 'b'
set ztics 5
splot "data/LaserLogLike" with lines t "LogLikelihood"
"""%(fig_dir+'/LaserLogLike.eps'))

def read_data(name):
    # Read in "data_file" as an array
    f = file(data_dir+'/'+name, 'r')
    data = [[float(x) for x in line.split()] for line in f.xreadlines()]
    f.close()
    return numpy.array(data).T

LP5 = read_data('LaserLP5')
States = read_data('LaserStates')
Forecast = read_data('LaserForecast')
Hist = read_data('LaserHist')

pylab.plot(LP5[0],LP5[1],'r-')
pylab.plot(LP5[0],LP5[2],'b-')
pylab.ylabel(r'$y(t)$')
pylab.xlabel(r'$t$')
pylab.axis(xmin=0,xmax=250)
pylab.legend(('Laser','Simulation'))
pylab.savefig(fig_dir+'/LaserLP5.pdf')
pylab.clf() # Clear figure window

pylab.plot(States[0],States[1],'r-')
pylab.xlabel(r'$x_1$')
pylab.ylabel(r'$x_3$')
pylab.savefig(fig_dir+'/LaserStates.pdf')
pylab.clf() # Clear figure window

pylab.plot(Forecast[0],Forecast[1],'r-')
pylab.plot(Forecast[0],Forecast[2],'b-')
pylab.ylabel(r'$y(t)$')
pylab.xlabel(r'$t$')
pylab.savefig(fig_dir+'/LaserForecast.pdf')
pylab.clf() # Clear figure window

pylab.bar(Hist[0],Hist[1])
pylab.ylabel(r'Counts')
pylab.xlabel(r'$x$')
pylab.savefig(fig_dir+'/LaserHist.pdf')
pylab.clf() # Clear figure window