Commit 72a05c28 authored by Karsten Wiesner's avatar Karsten Wiesner 💬
Browse files

finshed chunking of the workload for condor

parent 1289aa45
......@@ -5,7 +5,7 @@
###################################
Executable = /usr/bin/python
Arguments = GB_Benchmarking_3x3_fisher_analysis.py --proc=$(Process)
Arguments = GB_Benchmarking_3x3_fisher_analysis.py --proc=$(Process) --chunk_size=3
# get environment setting from my home and set it
# as environment on the copute nodes for each job
......@@ -22,4 +22,4 @@ Universe = vanilla
# lisa.(dev|sim|prod).galacticbinary
accounting_group = lisa.dev.galacticbinary`
Queue 5
Queue 3
......@@ -22,27 +22,9 @@ plt.rcParams['agg.path.chunksize'] = 10000
parser = argparse.ArgumentParser()
parser.add_argument('-p', '--proc', dest='proc', type=int)
#parser.add_argument('-d', '--dummy', dest='dummy')
parser.add_argument('-c', '--chunk_size', dest='chunk_size', type=int)
args = parser.parse_args()
print 3 * args.proc
import pprint
def chunks(l, n):
"""Yield successive n-sized chunks from l."""
for i in range(0, len(l), n):
pprint.pprint(i) ### das sind schon die richtige indexe !!!
#yield l[i:i + n]
l=xrange(12)
chunks(l,2)
#print (list(chunks(l,2)))
exit()
## Detector configuration
armL = 2.5e9
FastBinary.setL(armL)
......@@ -123,7 +105,19 @@ delon = 1e-3
df, de, dn = [], [], []
SNRs = []
for id_binary in range(tot_res_bins):
#len=12
#index= args.proc * args.chunk_size
#for i in xrange(index, index + args.chunk_size):
# if i >= len: break
# print(i)
#loop for single call
#for id_binary in range(tot_res_bins):
#loop for atlas condor chunked call
index= args.proc * args.chunk_size
for id_binary in xrange(index, index + args.chunk_size):
if id_binary >= tot_res_bins: break
## Load each binary parameter
f_bin, fdot, ampl = f_bins[id_binary], fdots[id_binary], ampls[id_binary]
df_bin = pre_f*f_bin
......@@ -155,10 +149,6 @@ for id_binary in range(tot_res_bins):
params = [f_bin, fdot, phi0, inc, ampl, elat, elon, psi]
dxs = [df_bin, delat, delon]
# Hint: Got rid of of the (...'time', 'A','E') - we just give it the signal-class that we want to use
# old: fisher = my_calc_fisher_3X3_symm(params, dxs, nspec, NYear, OneYear, stime, 'time', 'A','E')
# new:
# time domain 6-link investigation
fisher = my_calc_fisher_3X3_symm(params, dxs, nspec, NYear, OneYear, stime, td_aet_signal)
......@@ -167,22 +157,14 @@ for id_binary in range(tot_res_bins):
#print id_binary, SNR_tot_temp, cov[0]/f_bin,3, cov[3], cov[5]
print id_binary, round(SNR_tot_temp,2), round(cov[0]/f_bin,14), round(cov[3],5), round(cov[5],5)
if id_binary == 0:
break
print "Computed in ==> ", (time.time() - start_time)
# Computed in ==>
sys.exit()
savepath = "/Users/swshah/LISAGalacticBinaryDataAnalysis/fast_fisher_analysis/GBs_2pt5/results/"
np.save(savepath+"GB_fisher_analysis_freq_sky_4yr_6link", [SNRs, df, de, dn
])
sys.exit()
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