From ec5fae4cd6175326005a381d207eb9b4ef7e601c Mon Sep 17 00:00:00 2001 From: caes Date: Thu, 22 Jun 2017 09:28:44 -0400 Subject: [PATCH] more scripts --- scripts/psdlag_5bin.py | 112 +++++++++++++++++++++++++++++++++++++++++ scripts/psdlag_6bin.py | 112 +++++++++++++++++++++++++++++++++++++++++ 2 files changed, 224 insertions(+) create mode 100644 scripts/psdlag_5bin.py create mode 100644 scripts/psdlag_6bin.py diff --git a/scripts/psdlag_5bin.py b/scripts/psdlag_5bin.py new file mode 100644 index 0000000..45cde88 --- /dev/null +++ b/scripts/psdlag_5bin.py @@ -0,0 +1,112 @@ +#!/usr/bin/env python +import numpy as np +from scipy.stats import norm +from scipy.stats import lognorm +import sys +import getopt +sys.path.insert(1,"/usr/local/science/clag-agn/data/") +import clag +import matplotlib +# %pylab inline + + +#ref_file="data/lc/1367A.lc" +#echo_file="data/lc/2246A.lc" + +ref_file = str(sys.argv[1]) +echo_file = str(sys.argv[2]) + + +dt = 0.01 +t1, l1, l1e = np.loadtxt(ref_file).T +# errorbar(t1, l1, yerr=l1e, fmt='o') + +#A +fqL = np.logspace(np.log10(0.0049999999),np.log10(0.340002000),6) + +# not done for this bin number +#B +#fqL = np.array([0.0049999999, 0.018619375, 0.044733049, +# 0.069336227, 0.10747115, 0.16658029, +# 0.25819945, 0.40020915]) + + +#C +#fqL = np.array([0.0049999999, 0.018619375, 0.044733049, +# 0.069336227, 0.10747115, 0.16658029, +# 0.25819945, 0.40020915]) + +nfq = len(fqL) - 1 +fqd = 10**(np.log10( (fqL[:-1]*fqL[1:]) )/2.) + + + + + +P1 = clag.clag('psd10r', [t1], [l1], [l1e], dt, fqL) +p1 = np.ones(nfq) +p1, p1e = clag.optimize(P1, p1) + +p1, p1e = clag.errors(P1, p1, p1e) + +# xscale('log'); ylim(-4,2) +# errorbar(fqd, p1, yerr=p1e, fmt='o', ms=10, color="black") + +ref_psd = p1 +ref_psd_err = p1e + + + +t2, l2, l2e = np.loadtxt(echo_file).T +# errorbar(t1, l1, yerr=l1e, fmt='o', color="green") +# errorbar(t2, l2, yerr=l2e, fmt='o', color="black") + + +P2 = clag.clag('psd10r', [t2], [l2], [l2e], dt, fqL) +p2 = np.ones(nfq) +p2, p2e = clag.optimize(P2, p2) + +p2, p2e = clag.errors(P2, p2, p2e) + +# xscale('log'); ylim(-6,2) +# errorbar(fqd, p1, yerr=p1e, fmt='o', ms=10, color="green") +# errorbar(fqd, p2, yerr=p2e, fmt='o', ms=10, color="black") +echo_psd = p2 +echo_psd_err = p2e + + + + +Cx = clag.clag('cxd10r', [[t1,t2]], [[l1,l2]], [[l1e,l2e]], dt, fqL, p1, p2) +p = np.concatenate( ((p1+p2)*0.5-0.3,p1*0+0.1) ) # a good starting point generally +p, pe = clag.optimize(Cx, p) + +phi, phie = p[nfq:], pe[nfq:] +lag, lage = phi/(2*np.pi*fqd), phie/(2*np.pi*fqd) +cx, cxe = p[:nfq], pe[:nfq] + +cross_spectrm = cx +cross_spectrm_err = cxe + +# xscale('log'); ylim(-2,1) +# errorbar(fqd, lag, yerr=lage, fmt='o', ms=10,color="black") + + + + +s, loc, scale = lognorm.fit(lag,loc=.01) +# xscale('log'); ylim(-4,1.5) +# errorbar(fqd, lag, yerr=lage, fmt='o', ms=10,color="black") +##plot(fqd,norm.pdf(fqd,mu,sigma)) +#plot(fqd,lognorm.pdf(fqd,s,loc,scale)) +# mu,sigma + + + +#plot(ifft(lag)) + +np.savetxt("freq.out",fqL.reshape((-1,len(fqL)))) +np.savetxt("ref_psd.out",[ref_psd,ref_psd_err]) +np.savetxt("echo_psd.out",[echo_psd,echo_psd_err]) +np.savetxt("crsspctrm.out",[cross_spectrm,cross_spectrm_err]) +np.savetxt("lag.out",[lag,lage]) diff --git a/scripts/psdlag_6bin.py b/scripts/psdlag_6bin.py new file mode 100644 index 0000000..364eb00 --- /dev/null +++ b/scripts/psdlag_6bin.py @@ -0,0 +1,112 @@ +#!/usr/bin/env python +import numpy as np +from scipy.stats import norm +from scipy.stats import lognorm +import sys +import getopt +sys.path.insert(1,"/usr/local/science/clag-agn/data/") +import clag +import matplotlib +# %pylab inline + + +#ref_file="data/lc/1367A.lc" +#echo_file="data/lc/2246A.lc" + +ref_file = str(sys.argv[1]) +echo_file = str(sys.argv[2]) + + +dt = 0.01 +t1, l1, l1e = np.loadtxt(ref_file).T +# errorbar(t1, l1, yerr=l1e, fmt='o') + +#A +fqL = np.logspace(np.log10(0.0049999999),np.log10(0.340002000),7) + +# not done for this bin number +#B +#fqL = np.array([0.0049999999, 0.018619375, 0.044733049, +# 0.069336227, 0.10747115, 0.16658029, +# 0.25819945, 0.40020915]) + + +#C +#fqL = np.array([0.0049999999, 0.018619375, 0.044733049, +# 0.069336227, 0.10747115, 0.16658029, +# 0.25819945, 0.40020915]) + +nfq = len(fqL) - 1 +fqd = 10**(np.log10( (fqL[:-1]*fqL[1:]) )/2.) + + + + + +P1 = clag.clag('psd10r', [t1], [l1], [l1e], dt, fqL) +p1 = np.ones(nfq) +p1, p1e = clag.optimize(P1, p1) + +p1, p1e = clag.errors(P1, p1, p1e) + +# xscale('log'); ylim(-4,2) +# errorbar(fqd, p1, yerr=p1e, fmt='o', ms=10, color="black") + +ref_psd = p1 +ref_psd_err = p1e + + + +t2, l2, l2e = np.loadtxt(echo_file).T +# errorbar(t1, l1, yerr=l1e, fmt='o', color="green") +# errorbar(t2, l2, yerr=l2e, fmt='o', color="black") + + +P2 = clag.clag('psd10r', [t2], [l2], [l2e], dt, fqL) +p2 = np.ones(nfq) +p2, p2e = clag.optimize(P2, p2) + +p2, p2e = clag.errors(P2, p2, p2e) + +# xscale('log'); ylim(-6,2) +# errorbar(fqd, p1, yerr=p1e, fmt='o', ms=10, color="green") +# errorbar(fqd, p2, yerr=p2e, fmt='o', ms=10, color="black") +echo_psd = p2 +echo_psd_err = p2e + + + + +Cx = clag.clag('cxd10r', [[t1,t2]], [[l1,l2]], [[l1e,l2e]], dt, fqL, p1, p2) +p = np.concatenate( ((p1+p2)*0.5-0.3,p1*0+0.1) ) # a good starting point generally +p, pe = clag.optimize(Cx, p) + +phi, phie = p[nfq:], pe[nfq:] +lag, lage = phi/(2*np.pi*fqd), phie/(2*np.pi*fqd) +cx, cxe = p[:nfq], pe[:nfq] + +cross_spectrm = cx +cross_spectrm_err = cxe + +# xscale('log'); ylim(-2,1) +# errorbar(fqd, lag, yerr=lage, fmt='o', ms=10,color="black") + + + + +s, loc, scale = lognorm.fit(lag,loc=.01) +# xscale('log'); ylim(-4,1.5) +# errorbar(fqd, lag, yerr=lage, fmt='o', ms=10,color="black") +##plot(fqd,norm.pdf(fqd,mu,sigma)) +#plot(fqd,lognorm.pdf(fqd,s,loc,scale)) +# mu,sigma + + + +#plot(ifft(lag)) + +np.savetxt("freq.out",fqL.reshape((-1,len(fqL)))) +np.savetxt("ref_psd.out",[ref_psd,ref_psd_err]) +np.savetxt("echo_psd.out",[echo_psd,echo_psd_err]) +np.savetxt("crsspctrm.out",[cross_spectrm,cross_spectrm_err]) +np.savetxt("lag.out",[lag,lage])