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new idea for reading ms5_xsf data

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jkuhl-uni 2022-12-19 18:29:51 +01:00
parent 6ef081acef
commit 3399b72bfb
1 changed files with 56 additions and 22 deletions
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78
pyerrors/input/openQCD.py
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@ -1001,6 +1001,7 @@ def read_ms5_xsf(path, prefix, qc, corr):
files = sorted(files)
for file in files:
with open(path+"/"+file, "rb") as fp:
t = fp.read(8)
kappa = struct.unpack('d', t)[0]
t = fp.read(8)
@ -1018,30 +1019,63 @@ def read_ms5_xsf(path, prefix, qc, corr):
bnd = struct.unpack('i', t)[0]
print("T:", tmax)
t = fp.read(4)
cnfg = struct.unpack('i', t)[0]
print(cnfg)
placesBI = ["gS", "gP", "gA", "gV", "gVt", "lA", "lV", "lVt",
"lT", "lTt"]
placesBB = ["g1", "l1"]
if not corr in placesBB:
for i in range(placesBI.index(corr)):
t = fp.read(8*2*tmax)
t = fp.read(8*2*tmax)
tmpcorr = struct.unpack('d'*2*tmax, t)
corrres = [[],[]]
for i in range(len(tmpcorr)):
corrres[i%2].append(tmpcorr[i])
else:
# boundary to boundary correlators
for i in range(len(placesBI)):
t = fp.read(8*2*tmax)
for i in range(placesBB.index(corr)):
t = fp.read(8*2)
t = fp.read(8*2)
corrres = list(struct.unpack('d'*2, t))
placesBI = ["gS", "gP",
"gA", "gV",
"gVt", "lA",
"lV", "lVt",
"lT", "lTt"]
placesBB = ["g1", "l1"]
# bytes per config
# the chunks have the following structure:
# confignumber, 10x timedependent complex correlators, 2x timeindependent complex correlators
chunksize = 4 +( 8 *2*tmax*10)+( 8 *2*2)
print(chunksize)
packstr ='i'+('d'*2*tmax*10)+('d'*2*2)
while True:
cnfgt = fp.read(chunksize)
if not cnfgt:
break
asascii=struct.unpack(packstr, cnfgt)
cnfg = asascii[0]
#cnfg = struct.unpack('i', t)[0]
print(cnfg)
if not corr in placesBB:
#for i in range(placesBI.index(corr)):
# t = fp.read(8*2*tmax)
tmpcorr = asascii[1+2*tmax*placesBI.index(corr):1+2*tmax*placesBI.index(corr)+2*tmax]
#t = fp.read(8*2*tmax)
#tmpcorr = struct.unpack('d'*2*tmax, t)
corrres = [[],[]]
for i in range(len(tmpcorr)):
corrres[i%2].append(tmpcorr[i])
# jump to next config
#t = fp.read(chunksize-(4+placesBI.index(corr)*8*2*tmax+2*8*2))
else:
#for i in range(placesBI.index(corr)):
# t = fp.read(8*2*tmax)
tmpcorr = asascii[1+2*tmax*len(placesBI):1+2*tmax*len(placesBI)+2]
#t = fp.read(8*2*tmax)
#tmpcorr = struct.unpack('d'*2*tmax, t)
corrres = [[],[]]
for i in range(len(tmpcorr)):
corrres[i%2].append(tmpcorr[i])
# jump to next config
#t = fp.read(chunksize-(4+placesBI.index(corr)*8*2*tmax+2*8*2))
# boundary to boundary correlators
#for i in range(len(placesBI)):
# t = fp.read(8*2*tmax)
#for i in range(placesBB.index(corr)):
# t = fp.read(8*2)
#t = fp.read(8*2)
#corrres = list(struct.unpack('d'*2, t))
# jump to next config
#t = fp.read(chunksize-(4+len(placesBI)*8*2*tmax+(2-placesBB.index(corr))*8*2))
print(corrres)