from scipy import *
import Gnuplot
from scipy import fftpack
import Gnuplot
import math
import copy
y = [[], [], [], []]
power = copy.deepcopy(y)
period = copy.deepcopy(y)
p_data = [ [[],[]] , [[],[]] , [[],[]] , [[],[]] ]
nyquist=1./2
for i in xrange(32):
y[0].append(math.sin(i)/100.)
for i in xrange(1,4):
y[i] = copy.deepcopy(y[0])
# randomised y
for i in xrange(32):
y[1][i] += random.random()
# random inserts and doubled range
for i in xrange(1, 63, 2):
if ( random.random() >= 0.75 ) and ( i < len(y[2]) ):
y[2].insert(i-1, y[2][i-1])
y[3].insert(i-1, y[3][i-1])
for i in xrange(0, 4):
Y = fft(y[i])
ni = len(Y)/2
nf = len(Y)/2.0
freq = array(range(ni))/(nf)*nyquist
power[i] = abs( Y[1:ni] )**2
period[i] = 1./freq
data1 = zip(range(len(y[i])-1), y[i])
data2 = zip(period[i][1:len(period[i])], power[i])
p_data[i][0] = Gnuplot.PlotItems.Data(data1, with="lines", title="signal" )
p_data[i][1] = Gnuplot.PlotItems.Data(data2, with="lines", title="fft power" )
plt = Gnuplot.Gnuplot()
plt.plot(p_data[0][0], p_data[0][1], p_data[1][0], p_data[1][1], p_data[2][0], p_data[2][1], p_data[3][0], p_data[3][1])
#plt.xaxis((0,64))
#plt.ytitle('|FFT|**2')
#plt.grid("off")
#plt.output('sunspot_period.png','png medium transparent picsize 600 400')