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jkuhl-uni 2022-12-21 17:47:01 +01:00
parent f9fe5c7ec9
commit 3fdbc371b2
1 changed files with 48 additions and 40 deletions
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88
pyerrors/input/openQCD.py
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@ -990,10 +990,10 @@ def read_qtop_sector(path, prefix, c, target=0, **kwargs):
return qtop_projection(qtop, target=target)
def read_ms5_xsf(path, prefix, qc, corr, sep = "r", **kwargs):
def read_ms5_xsf(path, prefix, qc, corr, sep="r", **kwargs):
"""
Read data from files in the specified directory with the specified prefix and quark combination extension, and return a `Corr` object containing the data.
Parameters
----------
path : str
@ -1008,14 +1008,14 @@ def read_ms5_xsf(path, prefix, qc, corr, sep = "r", **kwargs):
The separator to use when parsing the replika names.
**kwargs
Additional keyword arguments. The following keyword arguments are recognized:
- names (List[str]): A list of names to use for the replicas.
Returns
-------
Corr
A complex valued `Corr` object containing the data read from the files.
Raises
------
FileNotFoundError
@ -1025,17 +1025,19 @@ def read_ms5_xsf(path, prefix, qc, corr, sep = "r", **kwargs):
struct.error
If there is an error unpacking binary data.
"""
found = []
files = []
names = []
for (dirpath, dirnames, filenames) in os.walk(path + "/"):
found.extend(filenames)
break
for f in found:
if fnmatch.fnmatch(f, prefix + "*.ms5_xsf_"+qc+".dat"):
if fnmatch.fnmatch(f, prefix + "*.ms5_xsf_" + qc + ".dat"):
files.append(f)
if not sep == "":
names.append(prefix+"|r"+f.split(".")[0].split(sep)[1])
names.append(prefix + "|r" + f.split(".")[0].split(sep)[1])
else:
names.append(prefix)
files = sorted(files)
@ -1044,14 +1046,14 @@ def read_ms5_xsf(path, prefix, qc, corr, sep = "r", **kwargs):
names = kwargs.get("names")
else:
names = sorted(names)
cnfgs = []
realsamples = []
imagsamples = []
repnum = 0
for file in files:
with open(path+"/"+file, "rb") as fp:
with open(path + "/" + file, "rb") as fp:
t = fp.read(8)
kappa = struct.unpack('d', t)[0]
t = fp.read(8)
@ -1060,16 +1062,15 @@ def read_ms5_xsf(path, prefix, qc, corr, sep = "r", **kwargs):
dF = struct.unpack('d', t)[0]
t = fp.read(8)
zF = struct.unpack('d', t)[0]
t = fp.read(4)
tmax = struct.unpack('i', t)[0]
t = fp.read(4)
bnd = struct.unpack('i', t)[0]
placesBI = ["gS", "gP",
"gA", "gV",
"gVt", "lA",
# bnd = struct.unpack('i', t)[0]
placesBI = ["gS", "gP",
"gA", "gV",
"gVt", "lA",
"lV", "lVt",
"lT", "lTt"]
placesBB = ["g1", "l1"]
@ -1078,47 +1079,54 @@ def read_ms5_xsf(path, prefix, qc, corr, sep = "r", **kwargs):
# the chunks have the following structure:
# confignumber, 10x timedependent complex correlators as doubles, 2x timeindependent complex correlators as doubles
chunksize = 4 +( 8 *2*tmax*10)+( 8 *2*2)
packstr ='=i'+('d'*2*tmax*10)+('d'*2*2)
chunksize = 4 + (8 * 2 * tmax * 10) + (8 * 2 * 2)
packstr = '=i' + ('d' * 2 * tmax * 10) + ('d' * 2 * 2)
cnfgs.append([])
realsamples.append([])
imagsamples.append([])
for t in range(tmax):
realsamples[repnum].append([])
imagsamples[repnum].append([])
while True:
cnfgt = fp.read(chunksize)
if not cnfgt:
break
asascii=struct.unpack(packstr, cnfgt)
asascii = struct.unpack(packstr, cnfgt)
cnfg = asascii[0]
cnfgs[repnum].append(cnfg)
if not corr in placesBB:
tmpcorr = asascii[1+2*tmax*placesBI.index(corr):1+2*tmax*placesBI.index(corr)+2*tmax]
if corr not in placesBB:
tmpcorr = asascii[1 + 2 * tmax * placesBI.index(corr):1 + 2 * tmax * placesBI.index(corr) + 2 * tmax]
else:
tmpcorr = asascii[1+2*tmax*len(placesBI)+2*placesBB.index(corr):1+2*tmax*len(placesBI)+2*placesBB.index(corr)+2]
corrres = [[],[]]
for i in range(len(tmpcorr)): corrres[i%2].append(tmpcorr[i])
for t in range(int(len(tmpcorr)/2)): realsamples[repnum][t].append(corrres[0][t])
for t in range(int(len(tmpcorr)/2)): imagsamples[repnum][t].append(corrres[1][t])
tmpcorr = asascii[1 + 2 * tmax * len(placesBI) + 2 * placesBB.index(corr):1 + 2 * tmax * len(placesBI) + 2 * placesBB.index(corr) + 2]
corrres = [[], []]
for i in range(len(tmpcorr)):
corrres[i % 2].append(tmpcorr[i])
for t in range(int(len(tmpcorr) / 2)):
realsamples[repnum][t].append(corrres[0][t])
for t in range(int(len(tmpcorr) / 2)):
imagsamples[repnum][t].append(corrres[1][t])
repnum += 1
s = "Read correlator "+ corr+ " from "+ str(repnum)+ " replika with "+str(len(realsamples[0][t]))
for rep in range(1,repnum):
s+=", "+str(len(realsamples[rep][t]))
s+=" samples"
s = "Read correlator " + corr + " from " + str(repnum) + " replika with " + str(len(realsamples[0][t]))
for rep in range(1, repnum):
s += ", " + str(len(realsamples[rep][t]))
s += " samples"
print(s)
print("Asserted run parameters:\n T:", tmax, "kappa:", kappa, "csw:", csw, "dF:", dF, "zF:", zF)
# we have the data now... but we need to re format the whole thing and put it into Corr objects.
realObs = []
imagObs = []
compObs = []
for t in range(int(len(tmpcorr)/2)): realObs.append(Obs([realsamples[rep][t] for rep in range(repnum)], names = names, idl = cnfgs))
for t in range(int(len(tmpcorr)/2)): imagObs.append(Obs([imagsamples[rep][t] for rep in range(repnum)], names = names, idl = cnfgs))
for t in range(int(len(tmpcorr)/2)): compObs.append(CObs(realObs[t], imagObs[t]))
return Corr(compObs)
for t in range(int(len(tmpcorr) / 2)):
realObs.append(Obs([realsamples[rep][t] for rep in range(repnum)], names=names, idl=cnfgs))
for t in range(int(len(tmpcorr) / 2)):
imagObs.append(Obs([imagsamples[rep][t] for rep in range(repnum)], names=names, idl=cnfgs))
for t in range(int(len(tmpcorr) / 2)):
compObs.append(CObs(realObs[t], imagObs[t]))
return Corr(compObs)