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#! /usr/bin/env python
import os
import numpy as np
a_fr = (1, 2, 0)
b_fr = (1, 0, 0)
c_fr = (0, 1, 0)
d_fr = (0, 0, 1)
e_fr = (1, 1, 1)
f_fr = (2, 1, 0)
g_fr = (1, 1, 0)
full_scan_mfr = [
(1, 1, 1), (1, 1, 0)
]
fix_sfr_mfr = [
# (1, 1, 1, 1, 0, 0),
# (1, 1, 1, 0, 1, 0),
# (1, 1, 1, 0, 0, 1),
(1, 1, 1, 1, 2, 0),
# (1, 1, 0, 0, 1, 0),
# (1, 1, 0, 1, 2, 0),
# (1, 1, 0, 1, 0, 0),
# (1, 0, 0, 1, 0, 0),
# (0, 1, 0, 0, 1, 0),
# (1, 2, 0, 0, 1, 0),
# (1, 2, 0, 1, 2, 0)
]
sigmas = ['0.01']
dimensions = [3]
energy = [1e6]
flat = False
burnin = 20
nwalkers = 200
nsteps = 100
scales = "1E-20 1E-30"
no_bsm = False
outfile = 'dagman_FR.submit'
golemfitsourcepath = os.environ['GOLEMSOURCEPATH'] + '/GolemFit'
condor_script = golemfitsourcepath + '/scripts/flavour_ratio/submitter/submit.sub'
with open(outfile, 'w') as f:
job_number = 1
for dim in dimensions:
print 'dimension', dim
for en in energy:
print 'energy {0:.0E}'.format(en)
outchain_head = '/data/user/smandalia/flavour_ratio/data/DIM{0}/{1:.0E}'.format(dim, en)
for sig in sigmas:
print 'sigma', sig
for frs in fix_sfr_mfr:
print frs
outchains = outchain_head + '/fix_ifr/{0}/mcmc_chain'.format(str(sig).replace('.', '_'))
f.write('JOB\tjob{0}\t{1}\n'.format(job_number, condor_script))
f.write('VARS\tjob{0}\tmr0="{1}"\n'.format(job_number, frs[0]))
f.write('VARS\tjob{0}\tmr1="{1}"\n'.format(job_number, frs[1]))
f.write('VARS\tjob{0}\tmr2="{1}"\n'.format(job_number, frs[2]))
f.write('VARS\tjob{0}\tsigma="{1}"\n'.format(job_number, sig))
f.write('VARS\tjob{0}\tfix_source_ratio="{1}"\n'.format(job_number, 'True'))
f.write('VARS\tjob{0}\tsr0="{1}"\n'.format(job_number, frs[3]))
f.write('VARS\tjob{0}\tsr1="{1}"\n'.format(job_number, frs[4]))
f.write('VARS\tjob{0}\tsr2="{1}"\n'.format(job_number, frs[5]))
f.write('VARS\tjob{0}\tfix_scale="{1}"\n'.format(job_number, 'False'))
f.write('VARS\tjob{0}\tscale="{1}"\n'.format(job_number, 0))
f.write('VARS\tjob{0}\tdimension="{1}"\n'.format(job_number, dim))
f.write('VARS\tjob{0}\tenergy="{1}"\n'.format(job_number, en))
f.write('VARS\tjob{0}\tflat_llh="{1}"\n'.format(job_number, flat))
f.write('VARS\tjob{0}\tburnin="{1}"\n'.format(job_number, burnin))
f.write('VARS\tjob{0}\tnwalkers="{1}"\n'.format(job_number, nwalkers))
f.write('VARS\tjob{0}\tnsteps="{1}"\n'.format(job_number, nsteps))
f.write('VARS\tjob{0}\toutfile="{1}"\n'.format(job_number, outchains))
f.write('VARS\tjob{0}\tfix_mixing="{1}"\n'.format(job_number, 'False'))
f.write('VARS\tjob{0}\tno_bsm="{1}"\n'.format(job_number, no_bsm))
job_number += 1
# for frs in full_scan_mfr:
# print frs
# outchains = outchain_head + '/full_scan/{0}/mcmc_chain'.format(str(sig).replace('.', '_'))
# f.write('JOB\tjob{0}\t{1}\n'.format(job_number, condor_script))
# f.write('VARS\tjob{0}\tmr0="{1}"\n'.format(job_number, frs[0]))
# f.write('VARS\tjob{0}\tmr1="{1}"\n'.format(job_number, frs[1]))
# f.write('VARS\tjob{0}\tmr2="{1}"\n'.format(job_number, frs[2]))
# f.write('VARS\tjob{0}\tsigma="{1}"\n'.format(job_number, sig))
# f.write('VARS\tjob{0}\tfix_source_ratio="{1}"\n'.format(job_number, 'False'))
# f.write('VARS\tjob{0}\tsr0="{1}"\n'.format(job_number, 0))
# f.write('VARS\tjob{0}\tsr1="{1}"\n'.format(job_number, 0))
# f.write('VARS\tjob{0}\tsr2="{1}"\n'.format(job_number, 0))
# f.write('VARS\tjob{0}\tfix_scale="{1}"\n'.format(job_number, 'False'))
# f.write('VARS\tjob{0}\tscale="{1}"\n'.format(job_number, 0))
# f.write('VARS\tjob{0}\tdimension="{1}"\n'.format(job_number, dim))
# f.write('VARS\tjob{0}\tenergy="{1}"\n'.format(job_number, en))
# f.write('VARS\tjob{0}\tflat_llh="{1}"\n'.format(job_number, flat))
# f.write('VARS\tjob{0}\tburnin="{1}"\n'.format(job_number, burnin))
# f.write('VARS\tjob{0}\tnwalkers="{1}"\n'.format(job_number, nwalkers))
# f.write('VARS\tjob{0}\tnsteps="{1}"\n'.format(job_number, nsteps))
# f.write('VARS\tjob{0}\toutfile="{1}"\n'.format(job_number, outchains))
# f.write('VARS\tjob{0}\tfix_mixing="{1}"\n'.format(job_number, 'False'))
# f.write('VARS\tjob{0}\tno_bsm="{1}"\n'.format(job_number, no_bsm))
# job_number += 1
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