Science/psdlag-agn
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changed freq bins

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caes 2017-01-31 21:09:09 -05:00
parent 9fe84e07b3
commit 2eef59ea30
1 changed files with 19 additions and 10 deletions
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29
scripts/analyze_lightcurve.py
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@ -3,15 +3,15 @@ from __future__ import unicode_literals
import numpy as np import numpy as np
import sys import sys
import getopt import getopt
sys.path.insert(1,"/usr/local/science/clag/")
import clag import clag
sys.path.insert(1, "/usr/local/science/clag/")
# For jupyter notebook # For jupyter notebook
# %pylab inline # %pylab inline
try: try:
opts,args = getopt.getopt(sys.argv[1:], "") opts, args = getopt.getopt(sys.argv[1:], "")
except getopt.GetoptError: except getopt.GetoptError:
print 'analyze_lightcure.py <reference curve> <compared curve>' print 'analyze_lightcure.py <reference curve> <compared curve>'
sys.exit(2) sys.exit(2)
@ -20,10 +20,14 @@ except getopt.GetoptError:
# does not expect evenly spaced data in time. # does not expect evenly spaced data in time.
dt = 0.1 dt = 0.1
#### Get the psd for the first light curve #### ### Get the psd for the #fqL = np.hstack((np.array(0.5*f1),np.logspace(np.log10(0.9*f1),
first light curve ###
# These bin values determined summer 2016 for STORM III optical/UV lightcurves # These bin values determined summer 2016 for STORM III optical/UV lightcurves
fqL = np.array([0.0049999999, 0.018619375, 0.044733049, 0.069336227, 0.10747115, 0.16658029, 0.25819945, 0.40020915, 0.62032418]) fqL = np.array([0.0049999999, 0.018619375, 0.044733049, 0.069336227,
0.10747115, 0.16658029, 0.25819945, 0.40020915,
0.62032418])
#A general rules for fqL is as follows: #A general rules for fqL is as follows:
# #
@ -54,15 +58,18 @@ fqL = np.array([0.0049999999, 0.018619375, 0.044733049, 0.069336227, 0.10747115,
# fqL = np.concatenate(([0.5/seg_length], fqL)) # fqL = np.concatenate(([0.5/seg_length], fqL))
# #
f1 = 1/175. #f1 = 1/175.
f2 = 0.5/dt #f2 = 0.5/dt
fqL = np.hstack((np.array(0.5*f1),np.logspace(np.log10(0.9*f1),np.log10(0.3*f2),9),np.array(2*f2))) #fqL = np.hstack((np.array(0.5*f1),np.logspace(np.log10(0.9*f1),
# np.log10(0.3*f2),9),np.array(2*f2)))
fqL = np.logspace(np.log10(0.0049999999),np.log10(0.62032418),9)
nfq = len(fqL) - 1 nfq = len(fqL) - 1
fqd = 10**(np.log10( (fqL[:-1]*fqL[1:]) )/2.) fqd = 10**(np.log10( (fqL[:-1]*fqL[1:]) )/2.)
## load the first light curve ## load the first light curve
lc1_time, lc1_strength, lc1_strength_err = np.loadtxt(args[0],skiprows=1).T lc1_time, lc1_strength, lc1_strength_err =
np.loadtxt(args[0],skiprows=1).T
# for pylab: errorbar(t1,l1,yerr=l1e,fmt='o') # for pylab: errorbar(t1,l1,yerr=l1e,fmt='o')
@ -71,7 +78,9 @@ initial_args = np.ones(nfq)
## initialize the psd class for multiple light curves ## ## initialize the psd class for multiple light curves ##
P1 = clag.clag('psd10r', [lc1_time], [lc1_strength], [lc1_strength_err], dt, fqL) P1 = clag.clag('psd10r',
[lc1_time], [lc1_strength], [lc1_strength_err],
dt, fqL)
ref_psd, ref_psd_err = clag.optimize(P1, initial_args) ref_psd, ref_psd_err = clag.optimize(P1, initial_args)
ref_psd, ref_psd_err = clag.errors(P1, ref_psd, ref_psd_err) ref_psd, ref_psd_err = clag.errors(P1, ref_psd, ref_psd_err)