gstlal-inspiral/bin/gstlal_inspiral_flopulator: output ratio of svd templates to input templates

write all data out to h5

gstlal-inspiral/bin/gstlal_inspiral_flopulator

@@ -20,8 +20,10 @@
 
 
 import numpy
+import os
 import sys
 from gstlal import svd_bank
+import h5py
 
 #FIXME hack to deal with pre ER5 / post ER5 bank file formats, remove when not an issue
 try:
@@ -29,13 +31,24 @@ try:
 except AttributeError:
 	banks = [svd_bank.read_bank(sys.argv[1])]
 
+svdbin = sys.argv[1].split('_')[0].split('-')[1]
+print("SVD BIN: ", svdbin)
+
+outpath = sys.argv[2]
+
+hf = h5py.File(outpath, 'a')
+g1 = hf.create_group(f'{svdbin}')
+
 totalMFLOPS=0
 averageMFLOPS=0
 totalMT = 0
+totalUT = 0
 
 for i, bank in enumerate(banks):
 
-	print ""
+	g = hf.create_group(f'{svdbin}/subbank-{i}')
+
+	print("")
 	rT = [f.rate for f in bank.bank_fragments]
 	r = numpy.array(sorted(list(set(rT))))
 	rT = numpy.array(rT)
@@ -44,12 +57,16 @@ for i, bank in enumerate(banks):
 	MT = [f.mix_matrix.shape[1] for f in bank.bank_fragments][0]
 	NT = numpy.array([(f.end - f.start) * f.rate for f in bank.bank_fragments])
 
-	print "\nSUB BANK %d" % i
-	print "--->\tUnique sampling rates: ",r
-	print "--->\tSampling rate for a given time slice: ",rT
-	print "--->\tTotal SVD filters for a given time slice: ",UT
-	print "--->\tNumber of SVD filter samples: ",NT
-	print "--->\tTotal real templates (e.g. twice number of complex templates): ",MT
+	print("\nSUB BANK %d" % i)
+	print("--->\tUnique sampling rates: ",r)
+	print("--->\tSampling rate for a given time slice: ",rT)
+	print("--->\tTotal SVD filters for a given time slice: ",UT)
+	print("--->\tNumber of SVD filter samples: ",NT)
+	print("--->\tTotal real templates (e.g. twice number of complex templates): ",MT)
+
+	g.create_dataset('sample-rates', data=rT)
+	g.create_dataset('num-svd-filters', data=UT)
+	g.create_dataset('num-real-templates', data=MT)
 
 	# Convolution of a 16 sample filter requires a multiply-add per sample point of data for each sample of the filter for each physical template
 	resample = (r * 16 * 2 * MT).sum()
@@ -63,17 +80,23 @@ for i, bank in enumerate(banks):
 
 	# get FLOPs per *complex* template (note the divide by 2)
 	totalMT += MT / 2
-	print "--->\tMFLOPS from resampling: ", resample / 1000.**2
-	print "--->\tMFLOPS from filtering: ", filter / 1000.**2
-	print "--->\tMFLOPS from reconstruction: ", reconstruct / 1000.**2
-	print "--->\tMFLOPS from addition: ", add / 1000.**2
+	totalUT += UT.sum()
+	print("--->\tMFLOPS from resampling: ", resample / 1000.**2)
+	print("--->\tMFLOPS from filtering: ", filter / 1000.**2)
+	print("--->\tMFLOPS from reconstruction: ", reconstruct / 1000.**2)
+	print("--->\tMFLOPS from addition: ", add / 1000.**2)
 
 	MFLOPs = resample / 1000.**2  + filter / 1000.**2 + reconstruct / 1000.**2 + add / 1000.**2
 	totalMFLOPS += MFLOPs
 
-	print "--->\tTotal MFLOPS: ", MFLOPs
-	print "--->\tMFLOPS per complex template: ", MFLOPs / (MT / 2.)
+	print("--->\tTotal MFLOPS: ", MFLOPs)
+	print("--->\tMFLOPS per complex template: ", MFLOPs / (MT / 2.))
+	print("--->\tRatio number SVD filters to number real input templates: ", UT.sum() / MT)
+
+	g.create_dataset('total-mflops', data=MFLOPs)
 	
 averageMFLOPS = totalMFLOPS / totalMT
 print("--\nAverage MFLOPS per template:", averageMFLOPS)
+print("--\nAverage Ratio number SVD filters to number real input templates: ", totalUT / totalMT / 2)
 
+hf.close()