nt = observable1.shape[0]
ntWindow = int(cfg.stat.chunkWidth * sampFreq)
time = np.arange(0, nt, cfg.simulation.printStep)
# Get ccf averaged over seeds (should add weights based on length)
print 'Calculating correlation function...'
ccf = ergoStat.ccf(observable1, observable2, lagMax=cfg.stat.lagMax,
sampFreq=sampFreq)
# Get perio averaged over seeds (should add weights based on length)
print 'Calculating periodogram function...'
(freq, perio, perioSTD) \
= ergoStat.getPerio(observable1, observable2,
sampFreq=sampFreq, chunkWidth=cfg.stat.chunkWidth,
norm=False)
# Save results
np.savetxt('%s/correlation/%s_lag%d%s.txt'\
% (cfg.general.resDir, corrName, int(cfg.stat.lagMax),
srcPostfix), ccf)
np.savetxt('%s/correlation/lags_lag%d%s.txt'\
% (cfg.general.resDir, int(cfg.stat.lagMax),
srcPostfix), lags)
np.savetxt('%s/power/%s_chunk%d%s.txt'\
% (cfg.general.resDir, powerName, int(cfg.stat.chunkWidth),
srcPostfix), perio)
np.savetxt('%s/power/%sSTD_chunk%d%s.txt' \
% (cfg.general.resDir, powerName, int(cfg.stat.chunkWidth),
sampFreq=sampFreq,
norm=False)
# Get common frequencies
if s == 0:
nChunks = int(nt / (cfg.stat.chunkWidth * sampFreq))
freq = ergoStat.getFreqPow2(cfg.stat.chunkWidth, sampFreq=sampFreq)
nfft = freq.shape[0]
powerSample = np.zeros((nfft, ))
powerSampleSTD = np.zeros((nfft, ))
# Get powerSample averaged over seeds
# (should add weights based on length)
(freq, powerSampleSeed, powerSampleSTDSeed) \
= ergoStat.getPerio(observable1, observable2,
freq=freq, sampFreq=sampFreq,
chunkWidth=cfg.stat.chunkWidth, norm=False)
powerSample += powerSampleSeed
powerSampleSTD += powerSampleSTDSeed**2 * nChunks
corrSample /= nSeeds
powerSample /= nSeeds
powerSampleSTD = np.sqrt(powerSampleSTD / (nSeeds * nChunks))
if cfg.stat.norm:
cov = corrSample[(lags.shape[0] - 1) / 2]
corrSample /= cov
powerSample /= cov
powerSampleSTD /= cov
# Save results
np.savetxt('%s/correlation/corrSample%s_lagMax%dyr.txt'\
observable2 = observable2[:nt]
# Get corrSample averaged over seeds (should add weights based on length)
corrSample += ergoStat.ccf(observable1, observable2, lagMax=cfg.stat.lagMax, sampFreq=sampFreq)
# Get common frequencies
if s == 0:
nChunks = int(nt / (cfg.stat.chunkWidth * sampFreq))
freq = ergoStat.getFreqPow2(cfg.stat.chunkWidth, sampFreq=sampFreq)
nfft = freq.shape[0]
powerSample = np.zeros((nfft,))
powerSampleSTD = np.zeros((nfft,))
# Get powerSample averaged over seeds (should add weights based on length)
(freq, powerSampleSeed, powerSampleSTDSeed) = ergoStat.getPerio(
observable1, observable2, freq=freq, sampFreq=sampFreq, chunkWidth=cfg.stat.chunkWidth, norm=False
)
powerSample += powerSampleSeed
powerSampleSTD += powerSampleSTDSeed ** 2 * nChunks
corrSample /= nSeeds
powerSample /= nSeeds
powerSampleSTD = np.sqrt(powerSampleSTD / (nSeeds * nChunks))
# Save results
np.savetxt(
"%s/%s/corrSample%s_nSeeds%d_lagMax%dyr.txt"
% (cfg.general.resDir, outDir, postfix, nSeeds, cfg.stat.lagMax),
corrSample,
)
np.savetxt(