mirror of
https://github.com/fjosw/pyerrors.git
synced 2025-03-15 06:40:24 +01:00
input submodule refactored
This commit is contained in:
parent
cc3a734e15
commit
d8437fe122
5 changed files with 744 additions and 734 deletions
|
@ -1,3 +1,5 @@
|
|||
from .input import *
|
||||
from . import bdio
|
||||
from . import hadrons
|
||||
from . import sfcf
|
||||
from . import openQCD
|
||||
from . import misc
|
||||
|
|
|
@ -1,733 +0,0 @@
|
|||
#!/usr/bin/env python
|
||||
# coding: utf-8
|
||||
|
||||
import sys
|
||||
import os
|
||||
import fnmatch
|
||||
import re
|
||||
import struct
|
||||
import autograd.numpy as np # Thinly-wrapped numpy
|
||||
from ..pyerrors import Obs
|
||||
from ..fits import fit_lin
|
||||
|
||||
|
||||
def read_sfcf(path, prefix, name, **kwargs):
|
||||
"""Read sfcf C format from given folder structure.
|
||||
|
||||
Keyword arguments
|
||||
-----------------
|
||||
im -- if True, read imaginary instead of real part of the correlation function.
|
||||
single -- if True, read a boundary-to-boundary correlation function with a single value
|
||||
b2b -- if True, read a time-dependent boundary-to-boundary correlation function
|
||||
names -- Alternative labeling for replicas/ensembles. Has to have the appropriate length
|
||||
"""
|
||||
if kwargs.get('im'):
|
||||
im = 1
|
||||
part = 'imaginary'
|
||||
else:
|
||||
im = 0
|
||||
part = 'real'
|
||||
|
||||
if kwargs.get('single'):
|
||||
b2b = 1
|
||||
single = 1
|
||||
else:
|
||||
b2b = 0
|
||||
single = 0
|
||||
|
||||
if kwargs.get('b2b'):
|
||||
b2b = 1
|
||||
|
||||
read = 0
|
||||
T = 0
|
||||
start = 0
|
||||
ls = []
|
||||
for (dirpath, dirnames, filenames) in os.walk(path):
|
||||
ls.extend(dirnames)
|
||||
break
|
||||
if not ls:
|
||||
print('Error, directory not found')
|
||||
sys.exit()
|
||||
for exc in ls:
|
||||
if fnmatch.fnmatch(exc, prefix + '*'):
|
||||
ls = list(set(ls) - set(exc))
|
||||
if len(ls) > 1:
|
||||
ls.sort(key=lambda x: int(re.findall(r'\d+', x[len(prefix):])[0]))
|
||||
replica = len(ls)
|
||||
print('Read', part, 'part of', name, 'from', prefix, ',', replica, 'replica')
|
||||
if 'names' in kwargs:
|
||||
new_names = kwargs.get('names')
|
||||
if len(new_names) != replica:
|
||||
raise Exception('Names does not have the required length', replica)
|
||||
else:
|
||||
new_names = ls
|
||||
print(replica, 'replica')
|
||||
for i, item in enumerate(ls):
|
||||
print(item)
|
||||
sub_ls = []
|
||||
for (dirpath, dirnames, filenames) in os.walk(path+'/'+item):
|
||||
sub_ls.extend(dirnames)
|
||||
break
|
||||
for exc in sub_ls:
|
||||
if fnmatch.fnmatch(exc, 'cfg*'):
|
||||
sub_ls = list(set(sub_ls) - set(exc))
|
||||
sub_ls.sort(key=lambda x: int(x[3:]))
|
||||
no_cfg = len(sub_ls)
|
||||
print(no_cfg, 'configurations')
|
||||
|
||||
if i == 0:
|
||||
with open(path + '/' + item + '/' + sub_ls[0] + '/' + name) as fp:
|
||||
for k, line in enumerate(fp):
|
||||
if read == 1 and not line.strip() and k > start + 1:
|
||||
break
|
||||
if read == 1 and k >= start:
|
||||
T += 1
|
||||
if '[correlator]' in line:
|
||||
read = 1
|
||||
start = k + 7 + b2b
|
||||
T -= b2b
|
||||
|
||||
deltas = []
|
||||
for j in range(T):
|
||||
deltas.append([])
|
||||
|
||||
sublength = len(sub_ls)
|
||||
for j in range(T):
|
||||
deltas[j].append(np.zeros(sublength))
|
||||
|
||||
for cnfg, subitem in enumerate(sub_ls):
|
||||
with open(path + '/' + item + '/' + subitem + '/'+name) as fp:
|
||||
for k, line in enumerate(fp):
|
||||
if(k >= start and k < start + T):
|
||||
floats = list(map(float, line.split()))
|
||||
deltas[k-start][i][cnfg] = floats[1 + im - single]
|
||||
|
||||
result = []
|
||||
for t in range(T):
|
||||
result.append(Obs(deltas[t], new_names))
|
||||
|
||||
return result
|
||||
|
||||
|
||||
def read_sfcf_c(path, prefix, name, quarks='.*', noffset=0, wf=0, wf2=0, **kwargs):
|
||||
"""Read sfcf c format from given folder structure.
|
||||
|
||||
Arguments
|
||||
-----------------
|
||||
quarks -- Label of the quarks used in the sfcf input file
|
||||
noffset -- Offset of the source (only relevant when wavefunctions are used)
|
||||
wf -- ID of wave function
|
||||
wf2 -- ID of the second wavefunction (only relevant for boundary-to-boundary correlation functions)
|
||||
|
||||
Keyword arguments
|
||||
-----------------
|
||||
im -- if True, read imaginary instead of real part of the correlation function.
|
||||
b2b -- if True, read a time-dependent boundary-to-boundary correlation function
|
||||
names -- Alternative labeling for replicas/ensembles. Has to have the appropriate length
|
||||
"""
|
||||
|
||||
if kwargs.get('im'):
|
||||
im = 1
|
||||
part = 'imaginary'
|
||||
else:
|
||||
im = 0
|
||||
part = 'real'
|
||||
|
||||
if kwargs.get('b2b'):
|
||||
b2b = 1
|
||||
else:
|
||||
b2b = 0
|
||||
|
||||
read = 0
|
||||
T = 0
|
||||
start = 0
|
||||
ls = []
|
||||
for (dirpath, dirnames, filenames) in os.walk(path):
|
||||
ls.extend(dirnames)
|
||||
break
|
||||
if not ls:
|
||||
print('Error, directory not found')
|
||||
sys.exit()
|
||||
# Exclude folders with different names
|
||||
for exc in ls:
|
||||
if not fnmatch.fnmatch(exc, prefix+'*'):
|
||||
ls = list(set(ls) - set([exc]))
|
||||
if len(ls) > 1:
|
||||
ls.sort(key=lambda x: int(re.findall(r'\d+', x[len(prefix):])[0])) # New version, to cope with ids, etc.
|
||||
replica = len(ls)
|
||||
if 'names' in kwargs:
|
||||
new_names = kwargs.get('names')
|
||||
if len(new_names) != replica:
|
||||
raise Exception('Names does not have the required length', replica)
|
||||
else:
|
||||
new_names = ls
|
||||
print('Read', part, 'part of', name, 'from', prefix[:-1], ',', replica, 'replica')
|
||||
for i, item in enumerate(ls):
|
||||
sub_ls = []
|
||||
for (dirpath, dirnames, filenames) in os.walk(path+'/'+item):
|
||||
sub_ls.extend(filenames)
|
||||
break
|
||||
for exc in sub_ls:
|
||||
if not fnmatch.fnmatch(exc, prefix+'*'):
|
||||
sub_ls = list(set(sub_ls) - set([exc]))
|
||||
sub_ls.sort(key=lambda x: int(re.findall(r'\d+', x)[-1]))
|
||||
|
||||
first_cfg = int(re.findall(r'\d+', sub_ls[0])[-1])
|
||||
|
||||
last_cfg = len(sub_ls) + first_cfg - 1
|
||||
|
||||
for cfg in range(1, len(sub_ls)):
|
||||
if int(re.findall(r'\d+', sub_ls[cfg])[-1]) != first_cfg + cfg:
|
||||
last_cfg = cfg + first_cfg - 1
|
||||
break
|
||||
|
||||
no_cfg = last_cfg - first_cfg + 1
|
||||
print(item, ':', no_cfg, 'evenly spaced configurations (', first_cfg, '-', last_cfg, ') ,', len(sub_ls) - no_cfg, 'configs omitted\n')
|
||||
|
||||
if i == 0:
|
||||
pattern = 'name ' + name + '\nquarks ' + quarks + '\noffset ' + str(noffset) + '\nwf ' + str(wf)
|
||||
if b2b:
|
||||
pattern += '\nwf_2 ' + str(wf2)
|
||||
|
||||
with open(path+'/'+item+'/'+sub_ls[0], 'r') as file:
|
||||
content = file.read()
|
||||
match = re.search(pattern, content)
|
||||
if match:
|
||||
start_read = content.count('\n', 0, match.start()) + 5 + b2b
|
||||
end_match = re.search('\n\s*\n', content[match.start():])
|
||||
T = content[match.start():].count('\n', 0, end_match.start()) - 4 - b2b
|
||||
assert T > 0
|
||||
print(T, 'entries, starting to read in line', start_read)
|
||||
else:
|
||||
raise Exception('Correlator with pattern\n' + pattern + '\nnot found.')
|
||||
|
||||
deltas = []
|
||||
for j in range(T):
|
||||
deltas.append([])
|
||||
|
||||
sublength = no_cfg
|
||||
for j in range(T):
|
||||
deltas[j].append(np.zeros(sublength))
|
||||
|
||||
for cfg in range(no_cfg):
|
||||
with open(path+'/'+item+'/'+sub_ls[cfg]) as fp:
|
||||
for k, line in enumerate(fp):
|
||||
if k == start_read - 5 - b2b:
|
||||
if line.strip() != 'name ' + name:
|
||||
raise Exception('Wrong format', sub_ls[cfg])
|
||||
if(k >= start_read and k < start_read + T):
|
||||
floats = list(map(float, line.split()))
|
||||
deltas[k-start_read][i][cfg] = floats[-2:][im]
|
||||
|
||||
result = []
|
||||
for t in range(T):
|
||||
result.append(Obs(deltas[t], new_names))
|
||||
return result
|
||||
|
||||
|
||||
def read_qtop(path, prefix, **kwargs):
|
||||
"""Read qtop format from given folder structure.
|
||||
|
||||
Keyword arguments
|
||||
-----------------
|
||||
target -- specifies the topological sector to be reweighted to (default 0)
|
||||
full -- if true read the charge instead of the reweighting factor.
|
||||
"""
|
||||
|
||||
if 'target' in kwargs:
|
||||
target = kwargs.get('target')
|
||||
else:
|
||||
target = 0
|
||||
|
||||
if kwargs.get('full'):
|
||||
full = 1
|
||||
else:
|
||||
full = 0
|
||||
|
||||
ls = []
|
||||
for (dirpath, dirnames, filenames) in os.walk(path):
|
||||
ls.extend(filenames)
|
||||
break
|
||||
|
||||
if not ls:
|
||||
print('Error, directory not found')
|
||||
sys.exit()
|
||||
|
||||
# Exclude files with different names
|
||||
for exc in ls:
|
||||
if not fnmatch.fnmatch(exc, prefix+'*'):
|
||||
ls = list(set(ls) - set([exc]))
|
||||
if len(ls) > 1:
|
||||
ls.sort(key=lambda x: int(re.findall(r'\d+', x[len(prefix):])[0])) # New version, to cope with ids, etc.
|
||||
replica = len(ls)
|
||||
print('Read Q_top from', prefix[:-1], ',', replica, 'replica')
|
||||
|
||||
deltas = []
|
||||
|
||||
for rep in range(replica):
|
||||
tmp = []
|
||||
with open(path+'/'+ls[rep]) as fp:
|
||||
for k, line in enumerate(fp):
|
||||
floats = list(map(float, line.split()))
|
||||
if full == 1:
|
||||
tmp.append(floats[1])
|
||||
else:
|
||||
if int(floats[1]) == target:
|
||||
tmp.append(1.0)
|
||||
else:
|
||||
tmp.append(0.0)
|
||||
|
||||
deltas.append(np.array(tmp))
|
||||
|
||||
result = Obs(deltas, [(w.split('.'))[0] for w in ls])
|
||||
|
||||
return result
|
||||
|
||||
def parse_array_openQCD2(d, n, size, wa, quadrupel=False):
|
||||
arr = []
|
||||
if d == 2:
|
||||
tot = 0
|
||||
for i in range(n[d-1]-1):
|
||||
if quadrupel:
|
||||
tmp = wa[tot:n[d-1]]
|
||||
tmp2 = []
|
||||
for i in range(len(tmp)):
|
||||
if i % 2 == 0:
|
||||
tmp2.append(tmp[i])
|
||||
arr.append(tmp2)
|
||||
else:
|
||||
arr.append(np.asarray(wa[tot:n[d-1]]))
|
||||
return arr
|
||||
|
||||
|
||||
# mimic the read_array routine of openQCD-2.0.
|
||||
# fp is the opened file handle
|
||||
# returns the dict array
|
||||
# at this point we only parse a 2d array
|
||||
# d = 2
|
||||
# n = [nfct[irw], 2*nsrc[irw]]
|
||||
def read_array_openQCD2(fp):
|
||||
t = fp.read(4)
|
||||
d = struct.unpack('i', t)[0]
|
||||
t = fp.read(4*d)
|
||||
n = struct.unpack('%di' % (d), t)
|
||||
t = fp.read(4)
|
||||
size = struct.unpack('i', t)[0]
|
||||
if size == 4:
|
||||
types = 'i'
|
||||
elif size == 8:
|
||||
types = 'd'
|
||||
elif size == 16:
|
||||
types = 'dd'
|
||||
else:
|
||||
print('Type not known!')
|
||||
m = n[0]
|
||||
for i in range(1,d):
|
||||
m *= n[i]
|
||||
|
||||
t = fp.read(m*size)
|
||||
tmp = struct.unpack('%d%s' % (m, types), t)
|
||||
|
||||
arr = parse_array_openQCD2(d, n, size, tmp, quadrupel=True)
|
||||
return {'d': d, 'n': n, 'size': size, 'arr': arr}
|
||||
|
||||
def read_rwms(path, prefix, names=None, **kwargs):
|
||||
"""Read rwms format from given folder structure. Returns a list of length nrw
|
||||
|
||||
Keyword arguments
|
||||
-----------------
|
||||
new_format -- if True, the array of the associated numbers of Hasenbusch factors is extracted (v>=openQCD1.6)
|
||||
r_start -- list which contains the first config to be read for each replicum
|
||||
r_stop -- list which contains the last config to be read for each replicum
|
||||
oqcd_ver_string -- openQCD version
|
||||
postfix -- postfix of the file to read, e.g. '.ms1' for openQCD-files
|
||||
"""
|
||||
#oqcd versions implemented in this method
|
||||
known_oqcd_versions = ['1.4','1.6','2.0']
|
||||
if 'oqcd_ver_string' in kwargs:
|
||||
ver_str = kwargs.get('oqcd_ver_string')
|
||||
if not (ver_str in known_oqcd_versions):
|
||||
raise Exception('Unknown openQCD version defined!')
|
||||
else: #Set defaults for openQCD Version to be version 1.4, emulate the old behaviour of this method
|
||||
# Deprecate this kwarg in version 2.0.
|
||||
if 'new_format':
|
||||
ver_str = '1.6'
|
||||
else:
|
||||
ver_str = '1.4'
|
||||
print("Working with openQCD version " + ver_str)
|
||||
if 'postfix' in kwargs:
|
||||
postfix = kwargs.get('postfix')
|
||||
else:
|
||||
postfix = ''
|
||||
ls = []
|
||||
for (dirpath, dirnames, filenames) in os.walk(path):
|
||||
ls.extend(filenames)
|
||||
break
|
||||
|
||||
if not ls:
|
||||
print('Error, directory not found')
|
||||
sys.exit()
|
||||
|
||||
# Exclude files with different names
|
||||
for exc in ls:
|
||||
if not fnmatch.fnmatch(exc, prefix + '*'+postfix+'.dat'):
|
||||
ls = list(set(ls) - set([exc]))
|
||||
if len(ls) > 1:
|
||||
ls.sort(key=lambda x: int(re.findall(r'\d+', x[len(prefix):])[0]))
|
||||
#ls = fnames
|
||||
#print(ls)
|
||||
replica = len(ls)
|
||||
|
||||
if 'r_start' in kwargs:
|
||||
r_start = kwargs.get('r_start')
|
||||
if len(r_start) != replica:
|
||||
raise Exception('r_start does not match number of replicas')
|
||||
# Adjust Configuration numbering to python index
|
||||
r_start = [o - 1 if o else None for o in r_start]
|
||||
else:
|
||||
r_start = [None] * replica
|
||||
|
||||
if 'r_stop' in kwargs:
|
||||
r_stop = kwargs.get('r_stop')
|
||||
if len(r_stop) != replica:
|
||||
raise Exception('r_stop does not match number of replicas')
|
||||
else:
|
||||
r_stop = [None] * replica
|
||||
|
||||
print('Read reweighting factors from', prefix[:-1], ',', replica, 'replica', end='')
|
||||
|
||||
print_err = 0
|
||||
if 'print_err' in kwargs:
|
||||
print_err = 1
|
||||
print()
|
||||
|
||||
deltas = []
|
||||
|
||||
for rep in range(replica):
|
||||
tmp_array = []
|
||||
with open(path+ '/' + ls[rep], 'rb') as fp:
|
||||
|
||||
#header
|
||||
t = fp.read(4) # number of reweighting factors
|
||||
if rep == 0:
|
||||
nrw = struct.unpack('i', t)[0]
|
||||
if ver_str == '2.0':
|
||||
nrw = int(nrw/2)
|
||||
for k in range(nrw):
|
||||
deltas.append([])
|
||||
else:
|
||||
if ((nrw != struct.unpack('i', t)[0] and (not ver_str == '2.0')) or (nrw != struct.unpack('i', t)[0]/2 and ver_str == '2.0')):# little weird if-clause due to the /2 operation needed.
|
||||
print('Error: different number of reweighting factors for replicum', rep)
|
||||
sys.exit()
|
||||
|
||||
for k in range(nrw):
|
||||
tmp_array.append([])
|
||||
|
||||
# This block is necessary for openQCD1.6 and openQCD2.0 ms1 files
|
||||
nfct = []
|
||||
if ver_str in ['1.6','2.0']:
|
||||
for i in range(nrw):
|
||||
t = fp.read(4)
|
||||
nfct.append(struct.unpack('i', t)[0])
|
||||
#print('nfct: ', nfct) # Hasenbusch factor, 1 for rat reweighting
|
||||
else:
|
||||
for i in range(nrw):
|
||||
nfct.append(1)
|
||||
|
||||
nsrc = []
|
||||
for i in range(nrw):
|
||||
t = fp.read(4)
|
||||
nsrc.append(struct.unpack('i', t)[0])
|
||||
if (ver_str == '2.0'):
|
||||
if not struct.unpack('i', fp.read(4))[0] == 0:
|
||||
print('something is wrong!')
|
||||
|
||||
#body
|
||||
while 0 < 1:
|
||||
t = fp.read(4)
|
||||
if len(t) < 4:
|
||||
break
|
||||
if print_err:
|
||||
config_no = struct.unpack('i', t)
|
||||
for i in range(nrw):
|
||||
if(ver_str == '2.0'):
|
||||
tmpd = read_array_openQCD2(fp)
|
||||
tmpd = read_array_openQCD2(fp)
|
||||
tmp_rw = tmpd['arr']
|
||||
tmp_nfct = 1.0
|
||||
for j in range(tmpd['n'][0]):
|
||||
tmp_nfct *= np.mean(np.exp(-np.asarray(tmp_rw[j])))
|
||||
if print_err:
|
||||
print(config_no, i, j, np.mean(np.exp(-np.asarray(tmp_rw[j]))), np.std(np.exp(-np.asarray(tmp_rw[j]))))
|
||||
print('Sources:', np.exp(-np.asarray(tmp_rw[j])))
|
||||
print('Partial factor:', tmp_nfct)
|
||||
elif(ver_str=='1.6' or ver_str=='1.4'):
|
||||
tmp_nfct = 1.0
|
||||
for j in range(nfct[i]):
|
||||
t = fp.read(8 * nsrc[i])
|
||||
t = fp.read(8 * nsrc[i])
|
||||
tmp_rw = struct.unpack('d' * nsrc[i], t)
|
||||
tmp_nfct *= np.mean(np.exp(-np.asarray(tmp_rw)))
|
||||
if print_err:
|
||||
print(config_no, i, j, np.mean(np.exp(-np.asarray(tmp_rw))), np.std(np.exp(-np.asarray(tmp_rw))))
|
||||
print('Sources:', np.exp(-np.asarray(tmp_rw)))
|
||||
print('Partial factor:', tmp_nfct)
|
||||
tmp_array[i].append(tmp_nfct)
|
||||
|
||||
for k in range(nrw):
|
||||
deltas[k].append(tmp_array[k][r_start[rep]:r_stop[rep]])
|
||||
|
||||
print(',', nrw, 'reweighting factors with', nsrc, 'sources')
|
||||
result = []
|
||||
for t in range(nrw):
|
||||
if names == None:
|
||||
result.append(Obs(deltas[t], [w.split(".")[0] for w in ls]))
|
||||
else:
|
||||
print(names)
|
||||
result.append(Obs(deltas[t], names))
|
||||
return result
|
||||
|
||||
|
||||
def read_pbp(path, prefix, **kwargs):
|
||||
"""Read pbp format from given folder structure. Returns a list of length nrw
|
||||
|
||||
Keyword arguments
|
||||
-----------------
|
||||
r_start -- list which contains the first config to be read for each replicum
|
||||
r_stop -- list which contains the last config to be read for each replicum
|
||||
|
||||
"""
|
||||
|
||||
extract_nfct = 1
|
||||
|
||||
ls = []
|
||||
for (dirpath, dirnames, filenames) in os.walk(path):
|
||||
ls.extend(filenames)
|
||||
break
|
||||
|
||||
if not ls:
|
||||
print('Error, directory not found')
|
||||
sys.exit()
|
||||
|
||||
# Exclude files with different names
|
||||
for exc in ls:
|
||||
if not fnmatch.fnmatch(exc, prefix + '*.dat'):
|
||||
ls = list(set(ls) - set([exc]))
|
||||
if len(ls) > 1:
|
||||
ls.sort(key=lambda x: int(re.findall(r'\d+', x[len(prefix):])[0]))
|
||||
replica = len(ls)
|
||||
|
||||
if 'r_start' in kwargs:
|
||||
r_start = kwargs.get('r_start')
|
||||
if len(r_start) != replica:
|
||||
raise Exception('r_start does not match number of replicas')
|
||||
# Adjust Configuration numbering to python index
|
||||
r_start = [o - 1 if o else None for o in r_start]
|
||||
else:
|
||||
r_start = [None] * replica
|
||||
|
||||
if 'r_stop' in kwargs:
|
||||
r_stop = kwargs.get('r_stop')
|
||||
if len(r_stop) != replica:
|
||||
raise Exception('r_stop does not match number of replicas')
|
||||
else:
|
||||
r_stop = [None] * replica
|
||||
|
||||
print('Read <bar{psi}\psi> from', prefix[:-1], ',', replica, 'replica', end='')
|
||||
|
||||
print_err = 0
|
||||
if 'print_err' in kwargs:
|
||||
print_err = 1
|
||||
print()
|
||||
|
||||
deltas = []
|
||||
|
||||
for rep in range(replica):
|
||||
tmp_array = []
|
||||
with open(path+ '/' + ls[rep], 'rb') as fp:
|
||||
|
||||
#header
|
||||
t = fp.read(4) # number of reweighting factors
|
||||
if rep == 0:
|
||||
nrw = struct.unpack('i', t)[0]
|
||||
for k in range(nrw):
|
||||
deltas.append([])
|
||||
else:
|
||||
if nrw != struct.unpack('i', t)[0]:
|
||||
print('Error: different number of reweighting factors for replicum', rep)
|
||||
sys.exit()
|
||||
|
||||
for k in range(nrw):
|
||||
tmp_array.append([])
|
||||
|
||||
# This block is necessary for openQCD1.6 ms1 files
|
||||
nfct = []
|
||||
if extract_nfct == 1:
|
||||
for i in range(nrw):
|
||||
t = fp.read(4)
|
||||
nfct.append(struct.unpack('i', t)[0])
|
||||
print('nfct: ', nfct) # Hasenbusch factor, 1 for rat reweighting
|
||||
else:
|
||||
for i in range(nrw):
|
||||
nfct.append(1)
|
||||
|
||||
nsrc = []
|
||||
for i in range(nrw):
|
||||
t = fp.read(4)
|
||||
nsrc.append(struct.unpack('i', t)[0])
|
||||
|
||||
#body
|
||||
while 0 < 1:
|
||||
t = fp.read(4)
|
||||
if len(t) < 4:
|
||||
break
|
||||
if print_err:
|
||||
config_no = struct.unpack('i', t)
|
||||
for i in range(nrw):
|
||||
tmp_nfct = 1.0
|
||||
for j in range(nfct[i]):
|
||||
t = fp.read(8 * nsrc[i])
|
||||
t = fp.read(8 * nsrc[i])
|
||||
tmp_rw = struct.unpack('d' * nsrc[i], t)
|
||||
tmp_nfct *= np.mean(np.asarray(tmp_rw))
|
||||
if print_err:
|
||||
print(config_no, i, j, np.mean(np.asarray(tmp_rw)), np.std(np.asarray(tmp_rw)))
|
||||
print('Sources:', np.asarray(tmp_rw))
|
||||
print('Partial factor:', tmp_nfct)
|
||||
tmp_array[i].append(tmp_nfct)
|
||||
|
||||
for k in range(nrw):
|
||||
deltas[k].append(tmp_array[k][r_start[rep]:r_stop[rep]])
|
||||
|
||||
print(',', nrw, '<bar{psi}\psi> with', nsrc, 'sources')
|
||||
result = []
|
||||
for t in range(nrw):
|
||||
result.append(Obs(deltas[t], [(w.split('.'))[0] for w in ls]))
|
||||
|
||||
return result
|
||||
|
||||
|
||||
def extract_t0(path, prefix, dtr_read, xmin, spatial_extent, fit_range=5, **kwargs):
|
||||
"""Extract t0 from given .ms.dat files. Returns t0 as Obs.
|
||||
|
||||
It is assumed that all boundary effects have sufficiently decayed at x0=xmin.
|
||||
The data around the zero crossing of t^2<E> - 0.3 is fitted with a linear function
|
||||
from which the exact root is extracted.
|
||||
Only works with openQCD v 1.2.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
path -- Path to .ms.dat files
|
||||
prefix -- Ensemble prefix
|
||||
dtr_read -- Determines how many trajectories should be skipped when reading the ms.dat files.
|
||||
Corresponds to dtr_cnfg / dtr_ms in the openQCD input file.
|
||||
xmin -- First timeslice where the boundary effects have sufficiently decayed.
|
||||
spatial_extent -- spatial extent of the lattice, required for normalization.
|
||||
fit_range -- Number of data points left and right of the zero crossing to be included in the linear fit. (Default: 5)
|
||||
|
||||
Keyword arguments
|
||||
-----------------
|
||||
r_start -- list which contains the first config to be read for each replicum.
|
||||
r_stop -- list which contains the last config to be read for each replicum.
|
||||
plaquette -- If true extract the plaquette estimate of t0 instead.
|
||||
"""
|
||||
|
||||
ls = []
|
||||
for (dirpath, dirnames, filenames) in os.walk(path):
|
||||
ls.extend(filenames)
|
||||
break
|
||||
|
||||
if not ls:
|
||||
print('Error, directory not found')
|
||||
sys.exit()
|
||||
|
||||
# Exclude files with different names
|
||||
for exc in ls:
|
||||
if not fnmatch.fnmatch(exc, prefix + '*.ms.dat'):
|
||||
ls = list(set(ls) - set([exc]))
|
||||
if len(ls) > 1:
|
||||
ls.sort(key=lambda x: int(re.findall(r'\d+', x[len(prefix):])[0]))
|
||||
replica = len(ls)
|
||||
|
||||
if 'r_start' in kwargs:
|
||||
r_start = kwargs.get('r_start')
|
||||
if len(r_start) != replica:
|
||||
raise Exception('r_start does not match number of replicas')
|
||||
# Adjust Configuration numbering to python index
|
||||
r_start = [o - 1 if o else None for o in r_start]
|
||||
else:
|
||||
r_start = [None] * replica
|
||||
|
||||
if 'r_stop' in kwargs:
|
||||
r_stop = kwargs.get('r_stop')
|
||||
if len(r_stop) != replica:
|
||||
raise Exception('r_stop does not match number of replicas')
|
||||
else:
|
||||
r_stop = [None] * replica
|
||||
|
||||
print('Extract t0 from', prefix, ',', replica, 'replica')
|
||||
|
||||
Ysum = []
|
||||
|
||||
for rep in range(replica):
|
||||
|
||||
with open(path + '/' + ls[rep], 'rb') as fp:
|
||||
# Read header
|
||||
t = fp.read(12)
|
||||
header = struct.unpack('iii', t)
|
||||
if rep == 0:
|
||||
dn = header[0]
|
||||
nn = header[1]
|
||||
tmax = header[2]
|
||||
elif dn != header[0] or nn != header[1] or tmax != header[2]:
|
||||
raise Exception('Replica parameters do not match.')
|
||||
|
||||
t = fp.read(8)
|
||||
if rep == 0:
|
||||
eps = struct.unpack('d', t)[0]
|
||||
print('Step size:', eps, ', Maximal t value:', dn * (nn) * eps)
|
||||
elif eps != struct.unpack('d', t)[0]:
|
||||
raise Exception('Values for eps do not match among replica.')
|
||||
|
||||
Ysl = []
|
||||
|
||||
# Read body
|
||||
while 0 < 1:
|
||||
t = fp.read(4)
|
||||
if(len(t) < 4):
|
||||
break
|
||||
nc = struct.unpack('i', t)[0]
|
||||
|
||||
t = fp.read(8 * tmax * (nn + 1))
|
||||
if kwargs.get('plaquette'):
|
||||
if nc % dtr_read == 0:
|
||||
Ysl.append(struct.unpack('d' * tmax * (nn + 1), t))
|
||||
t = fp.read(8 * tmax * (nn + 1))
|
||||
if not kwargs.get('plaquette'):
|
||||
if nc % dtr_read == 0:
|
||||
Ysl.append(struct.unpack('d' * tmax * (nn + 1), t))
|
||||
t = fp.read(8 * tmax * (nn + 1))
|
||||
|
||||
Ysum.append([])
|
||||
for i, item in enumerate(Ysl):
|
||||
Ysum[-1].append([np.mean(item[current + xmin:current + tmax - xmin]) for current in range(0, len(item), tmax)])
|
||||
|
||||
t2E_dict = {}
|
||||
for n in range(nn + 1):
|
||||
samples = []
|
||||
for nrep, rep in enumerate(Ysum):
|
||||
samples.append([])
|
||||
for cnfg in rep:
|
||||
samples[-1].append(cnfg[n])
|
||||
samples[-1] = samples[-1][r_start[nrep]:r_stop[nrep]]
|
||||
new_obs = Obs(samples, [(w.split('.'))[0] for w in ls])
|
||||
t2E_dict[n * dn * eps] = (n * dn * eps) ** 2 * new_obs / (spatial_extent ** 3) - 0.3
|
||||
|
||||
zero_crossing = np.argmax(np.array([o.value for o in t2E_dict.values()]) > 0.0)
|
||||
|
||||
x = list(t2E_dict.keys())[zero_crossing - fit_range: zero_crossing + fit_range]
|
||||
y = list(t2E_dict.values())[zero_crossing - fit_range: zero_crossing + fit_range]
|
||||
[o.gamma_method() for o in y]
|
||||
|
||||
fit_result = fit_lin(x, y)
|
||||
return -fit_result[0] / fit_result[1]
|
126
pyerrors/input/misc.py
Normal file
126
pyerrors/input/misc.py
Normal file
|
@ -0,0 +1,126 @@
|
|||
#!/usr/bin/env python
|
||||
# coding: utf-8
|
||||
|
||||
import os
|
||||
import fnmatch
|
||||
import re
|
||||
import struct
|
||||
import numpy as np # Thinly-wrapped numpy
|
||||
from ..pyerrors import Obs
|
||||
|
||||
|
||||
def read_pbp(path, prefix, **kwargs):
|
||||
"""Read pbp format from given folder structure. Returns a list of length nrw
|
||||
|
||||
Keyword arguments
|
||||
-----------------
|
||||
r_start -- list which contains the first config to be read for each replicum
|
||||
r_stop -- list which contains the last config to be read for each replicum
|
||||
|
||||
"""
|
||||
|
||||
extract_nfct = 1
|
||||
|
||||
ls = []
|
||||
for (dirpath, dirnames, filenames) in os.walk(path):
|
||||
ls.extend(filenames)
|
||||
break
|
||||
|
||||
if not ls:
|
||||
raise Exception('Error, directory not found')
|
||||
|
||||
# Exclude files with different names
|
||||
for exc in ls:
|
||||
if not fnmatch.fnmatch(exc, prefix + '*.dat'):
|
||||
ls = list(set(ls) - set([exc]))
|
||||
if len(ls) > 1:
|
||||
ls.sort(key=lambda x: int(re.findall(r'\d+', x[len(prefix):])[0]))
|
||||
replica = len(ls)
|
||||
|
||||
if 'r_start' in kwargs:
|
||||
r_start = kwargs.get('r_start')
|
||||
if len(r_start) != replica:
|
||||
raise Exception('r_start does not match number of replicas')
|
||||
# Adjust Configuration numbering to python index
|
||||
r_start = [o - 1 if o else None for o in r_start]
|
||||
else:
|
||||
r_start = [None] * replica
|
||||
|
||||
if 'r_stop' in kwargs:
|
||||
r_stop = kwargs.get('r_stop')
|
||||
if len(r_stop) != replica:
|
||||
raise Exception('r_stop does not match number of replicas')
|
||||
else:
|
||||
r_stop = [None] * replica
|
||||
|
||||
print('Read <bar{psi}\psi> from', prefix[:-1], ',', replica, 'replica', end='')
|
||||
|
||||
print_err = 0
|
||||
if 'print_err' in kwargs:
|
||||
print_err = 1
|
||||
print()
|
||||
|
||||
deltas = []
|
||||
|
||||
for rep in range(replica):
|
||||
tmp_array = []
|
||||
with open(path+ '/' + ls[rep], 'rb') as fp:
|
||||
|
||||
#header
|
||||
t = fp.read(4) # number of reweighting factors
|
||||
if rep == 0:
|
||||
nrw = struct.unpack('i', t)[0]
|
||||
for k in range(nrw):
|
||||
deltas.append([])
|
||||
else:
|
||||
if nrw != struct.unpack('i', t)[0]:
|
||||
raise Exception('Error: different number of reweighting factors for replicum', rep)
|
||||
|
||||
for k in range(nrw):
|
||||
tmp_array.append([])
|
||||
|
||||
# This block is necessary for openQCD1.6 ms1 files
|
||||
nfct = []
|
||||
if extract_nfct == 1:
|
||||
for i in range(nrw):
|
||||
t = fp.read(4)
|
||||
nfct.append(struct.unpack('i', t)[0])
|
||||
print('nfct: ', nfct) # Hasenbusch factor, 1 for rat reweighting
|
||||
else:
|
||||
for i in range(nrw):
|
||||
nfct.append(1)
|
||||
|
||||
nsrc = []
|
||||
for i in range(nrw):
|
||||
t = fp.read(4)
|
||||
nsrc.append(struct.unpack('i', t)[0])
|
||||
|
||||
#body
|
||||
while 0 < 1:
|
||||
t = fp.read(4)
|
||||
if len(t) < 4:
|
||||
break
|
||||
if print_err:
|
||||
config_no = struct.unpack('i', t)
|
||||
for i in range(nrw):
|
||||
tmp_nfct = 1.0
|
||||
for j in range(nfct[i]):
|
||||
t = fp.read(8 * nsrc[i])
|
||||
t = fp.read(8 * nsrc[i])
|
||||
tmp_rw = struct.unpack('d' * nsrc[i], t)
|
||||
tmp_nfct *= np.mean(np.asarray(tmp_rw))
|
||||
if print_err:
|
||||
print(config_no, i, j, np.mean(np.asarray(tmp_rw)), np.std(np.asarray(tmp_rw)))
|
||||
print('Sources:', np.asarray(tmp_rw))
|
||||
print('Partial factor:', tmp_nfct)
|
||||
tmp_array[i].append(tmp_nfct)
|
||||
|
||||
for k in range(nrw):
|
||||
deltas[k].append(tmp_array[k][r_start[rep]:r_stop[rep]])
|
||||
|
||||
print(',', nrw, '<bar{psi}\psi> with', nsrc, 'sources')
|
||||
result = []
|
||||
for t in range(nrw):
|
||||
result.append(Obs(deltas[t], [(w.split('.'))[0] for w in ls]))
|
||||
|
||||
return result
|
337
pyerrors/input/openQCD.py
Normal file
337
pyerrors/input/openQCD.py
Normal file
|
@ -0,0 +1,337 @@
|
|||
#!/usr/bin/env python
|
||||
# coding: utf-8
|
||||
|
||||
import os
|
||||
import fnmatch
|
||||
import re
|
||||
import struct
|
||||
import numpy as np # Thinly-wrapped numpy
|
||||
from ..pyerrors import Obs
|
||||
from ..fits import fit_lin
|
||||
|
||||
|
||||
def read_rwms(path, prefix, version='2.0', names=None, **kwargs):
|
||||
"""Read rwms format from given folder structure. Returns a list of length nrw
|
||||
|
||||
Attributes
|
||||
-----------------
|
||||
version -- version of openQCD, default 2.0
|
||||
|
||||
Keyword arguments
|
||||
-----------------
|
||||
r_start -- list which contains the first config to be read for each replicum
|
||||
r_stop -- list which contains the last config to be read for each replicum
|
||||
postfix -- postfix of the file to read, e.g. '.ms1' for openQCD-files
|
||||
"""
|
||||
#oqcd versions implemented in this method
|
||||
known_oqcd_versions = ['1.4','1.6','2.0']
|
||||
if not (version in known_oqcd_versions):
|
||||
raise Exception('Unknown openQCD version defined!')
|
||||
else: #Set defaults for openQCD Version to be version 1.4, emulate the old behaviour of this method
|
||||
# Deprecate this kwarg in version 2.0.
|
||||
print("Working with openQCD version " + version)
|
||||
if 'postfix' in kwargs:
|
||||
postfix = kwargs.get('postfix')
|
||||
else:
|
||||
postfix = ''
|
||||
ls = []
|
||||
for (dirpath, dirnames, filenames) in os.walk(path):
|
||||
ls.extend(filenames)
|
||||
break
|
||||
|
||||
if not ls:
|
||||
raise Exception('Error, directory not found')
|
||||
|
||||
# Exclude files with different names
|
||||
for exc in ls:
|
||||
if not fnmatch.fnmatch(exc, prefix + '*'+postfix+'.dat'):
|
||||
ls = list(set(ls) - set([exc]))
|
||||
if len(ls) > 1:
|
||||
ls.sort(key=lambda x: int(re.findall(r'\d+', x[len(prefix):])[0]))
|
||||
#ls = fnames
|
||||
#print(ls)
|
||||
replica = len(ls)
|
||||
|
||||
if 'r_start' in kwargs:
|
||||
r_start = kwargs.get('r_start')
|
||||
if len(r_start) != replica:
|
||||
raise Exception('r_start does not match number of replicas')
|
||||
# Adjust Configuration numbering to python index
|
||||
r_start = [o - 1 if o else None for o in r_start]
|
||||
else:
|
||||
r_start = [None] * replica
|
||||
|
||||
if 'r_stop' in kwargs:
|
||||
r_stop = kwargs.get('r_stop')
|
||||
if len(r_stop) != replica:
|
||||
raise Exception('r_stop does not match number of replicas')
|
||||
else:
|
||||
r_stop = [None] * replica
|
||||
|
||||
print('Read reweighting factors from', prefix[:-1], ',', replica, 'replica', end='')
|
||||
|
||||
print_err = 0
|
||||
if 'print_err' in kwargs:
|
||||
print_err = 1
|
||||
print()
|
||||
|
||||
deltas = []
|
||||
|
||||
for rep in range(replica):
|
||||
tmp_array = []
|
||||
with open(path+ '/' + ls[rep], 'rb') as fp:
|
||||
|
||||
#header
|
||||
t = fp.read(4) # number of reweighting factors
|
||||
if rep == 0:
|
||||
nrw = struct.unpack('i', t)[0]
|
||||
if version == '2.0':
|
||||
nrw = int(nrw/2)
|
||||
for k in range(nrw):
|
||||
deltas.append([])
|
||||
else:
|
||||
if ((nrw != struct.unpack('i', t)[0] and (not verion == '2.0')) or (nrw != struct.unpack('i', t)[0]/2 and version == '2.0')):# little weird if-clause due to the /2 operation needed.
|
||||
raise Exception('Error: different number of reweighting factors for replicum', rep)
|
||||
|
||||
for k in range(nrw):
|
||||
tmp_array.append([])
|
||||
|
||||
# This block is necessary for openQCD1.6 and openQCD2.0 ms1 files
|
||||
nfct = []
|
||||
if version in ['1.6','2.0']:
|
||||
for i in range(nrw):
|
||||
t = fp.read(4)
|
||||
nfct.append(struct.unpack('i', t)[0])
|
||||
#print('nfct: ', nfct) # Hasenbusch factor, 1 for rat reweighting
|
||||
else:
|
||||
for i in range(nrw):
|
||||
nfct.append(1)
|
||||
|
||||
nsrc = []
|
||||
for i in range(nrw):
|
||||
t = fp.read(4)
|
||||
nsrc.append(struct.unpack('i', t)[0])
|
||||
if version is '2.0':
|
||||
if not struct.unpack('i', fp.read(4))[0] == 0:
|
||||
print('something is wrong!')
|
||||
|
||||
#body
|
||||
while 0 < 1:
|
||||
t = fp.read(4)
|
||||
if len(t) < 4:
|
||||
break
|
||||
if print_err:
|
||||
config_no = struct.unpack('i', t)
|
||||
for i in range(nrw):
|
||||
if(version == '2.0'):
|
||||
tmpd = _read_array_openQCD2(fp)
|
||||
tmpd = _read_array_openQCD2(fp)
|
||||
tmp_rw = tmpd['arr']
|
||||
tmp_nfct = 1.0
|
||||
for j in range(tmpd['n'][0]):
|
||||
tmp_nfct *= np.mean(np.exp(-np.asarray(tmp_rw[j])))
|
||||
if print_err:
|
||||
print(config_no, i, j, np.mean(np.exp(-np.asarray(tmp_rw[j]))), np.std(np.exp(-np.asarray(tmp_rw[j]))))
|
||||
print('Sources:', np.exp(-np.asarray(tmp_rw[j])))
|
||||
print('Partial factor:', tmp_nfct)
|
||||
elif version is '1.6' or version is '1.4':
|
||||
tmp_nfct = 1.0
|
||||
for j in range(nfct[i]):
|
||||
t = fp.read(8 * nsrc[i])
|
||||
t = fp.read(8 * nsrc[i])
|
||||
tmp_rw = struct.unpack('d' * nsrc[i], t)
|
||||
tmp_nfct *= np.mean(np.exp(-np.asarray(tmp_rw)))
|
||||
if print_err:
|
||||
print(config_no, i, j, np.mean(np.exp(-np.asarray(tmp_rw))), np.std(np.exp(-np.asarray(tmp_rw))))
|
||||
print('Sources:', np.exp(-np.asarray(tmp_rw)))
|
||||
print('Partial factor:', tmp_nfct)
|
||||
tmp_array[i].append(tmp_nfct)
|
||||
|
||||
for k in range(nrw):
|
||||
deltas[k].append(tmp_array[k][r_start[rep]:r_stop[rep]])
|
||||
|
||||
print(',', nrw, 'reweighting factors with', nsrc, 'sources')
|
||||
result = []
|
||||
for t in range(nrw):
|
||||
if names == None:
|
||||
result.append(Obs(deltas[t], [w.split(".")[0] for w in ls]))
|
||||
else:
|
||||
print(names)
|
||||
result.append(Obs(deltas[t], names))
|
||||
return result
|
||||
|
||||
|
||||
|
||||
|
||||
def extract_t0(path, prefix, dtr_read, xmin, spatial_extent, fit_range=5, **kwargs):
|
||||
"""Extract t0 from given .ms.dat files. Returns t0 as Obs.
|
||||
|
||||
It is assumed that all boundary effects have sufficiently decayed at x0=xmin.
|
||||
The data around the zero crossing of t^2<E> - 0.3 is fitted with a linear function
|
||||
from which the exact root is extracted.
|
||||
Only works with openQCD v 1.2.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
path -- Path to .ms.dat files
|
||||
prefix -- Ensemble prefix
|
||||
dtr_read -- Determines how many trajectories should be skipped when reading the ms.dat files.
|
||||
Corresponds to dtr_cnfg / dtr_ms in the openQCD input file.
|
||||
xmin -- First timeslice where the boundary effects have sufficiently decayed.
|
||||
spatial_extent -- spatial extent of the lattice, required for normalization.
|
||||
fit_range -- Number of data points left and right of the zero crossing to be included in the linear fit. (Default: 5)
|
||||
|
||||
Keyword arguments
|
||||
-----------------
|
||||
r_start -- list which contains the first config to be read for each replicum.
|
||||
r_stop -- list which contains the last config to be read for each replicum.
|
||||
plaquette -- If true extract the plaquette estimate of t0 instead.
|
||||
"""
|
||||
|
||||
ls = []
|
||||
for (dirpath, dirnames, filenames) in os.walk(path):
|
||||
ls.extend(filenames)
|
||||
break
|
||||
|
||||
if not ls:
|
||||
raise Exception('Error, directory not found')
|
||||
|
||||
# Exclude files with different names
|
||||
for exc in ls:
|
||||
if not fnmatch.fnmatch(exc, prefix + '*.ms.dat'):
|
||||
ls = list(set(ls) - set([exc]))
|
||||
if len(ls) > 1:
|
||||
ls.sort(key=lambda x: int(re.findall(r'\d+', x[len(prefix):])[0]))
|
||||
replica = len(ls)
|
||||
|
||||
if 'r_start' in kwargs:
|
||||
r_start = kwargs.get('r_start')
|
||||
if len(r_start) != replica:
|
||||
raise Exception('r_start does not match number of replicas')
|
||||
# Adjust Configuration numbering to python index
|
||||
r_start = [o - 1 if o else None for o in r_start]
|
||||
else:
|
||||
r_start = [None] * replica
|
||||
|
||||
if 'r_stop' in kwargs:
|
||||
r_stop = kwargs.get('r_stop')
|
||||
if len(r_stop) != replica:
|
||||
raise Exception('r_stop does not match number of replicas')
|
||||
else:
|
||||
r_stop = [None] * replica
|
||||
|
||||
print('Extract t0 from', prefix, ',', replica, 'replica')
|
||||
|
||||
Ysum = []
|
||||
|
||||
for rep in range(replica):
|
||||
|
||||
with open(path + '/' + ls[rep], 'rb') as fp:
|
||||
# Read header
|
||||
t = fp.read(12)
|
||||
header = struct.unpack('iii', t)
|
||||
if rep == 0:
|
||||
dn = header[0]
|
||||
nn = header[1]
|
||||
tmax = header[2]
|
||||
elif dn != header[0] or nn != header[1] or tmax != header[2]:
|
||||
raise Exception('Replica parameters do not match.')
|
||||
|
||||
t = fp.read(8)
|
||||
if rep == 0:
|
||||
eps = struct.unpack('d', t)[0]
|
||||
print('Step size:', eps, ', Maximal t value:', dn * (nn) * eps)
|
||||
elif eps != struct.unpack('d', t)[0]:
|
||||
raise Exception('Values for eps do not match among replica.')
|
||||
|
||||
Ysl = []
|
||||
|
||||
# Read body
|
||||
while 0 < 1:
|
||||
t = fp.read(4)
|
||||
if(len(t) < 4):
|
||||
break
|
||||
nc = struct.unpack('i', t)[0]
|
||||
|
||||
t = fp.read(8 * tmax * (nn + 1))
|
||||
if kwargs.get('plaquette'):
|
||||
if nc % dtr_read == 0:
|
||||
Ysl.append(struct.unpack('d' * tmax * (nn + 1), t))
|
||||
t = fp.read(8 * tmax * (nn + 1))
|
||||
if not kwargs.get('plaquette'):
|
||||
if nc % dtr_read == 0:
|
||||
Ysl.append(struct.unpack('d' * tmax * (nn + 1), t))
|
||||
t = fp.read(8 * tmax * (nn + 1))
|
||||
|
||||
Ysum.append([])
|
||||
for i, item in enumerate(Ysl):
|
||||
Ysum[-1].append([np.mean(item[current + xmin:current + tmax - xmin]) for current in range(0, len(item), tmax)])
|
||||
|
||||
t2E_dict = {}
|
||||
for n in range(nn + 1):
|
||||
samples = []
|
||||
for nrep, rep in enumerate(Ysum):
|
||||
samples.append([])
|
||||
for cnfg in rep:
|
||||
samples[-1].append(cnfg[n])
|
||||
samples[-1] = samples[-1][r_start[nrep]:r_stop[nrep]]
|
||||
new_obs = Obs(samples, [(w.split('.'))[0] for w in ls])
|
||||
t2E_dict[n * dn * eps] = (n * dn * eps) ** 2 * new_obs / (spatial_extent ** 3) - 0.3
|
||||
|
||||
zero_crossing = np.argmax(np.array([o.value for o in t2E_dict.values()]) > 0.0)
|
||||
|
||||
x = list(t2E_dict.keys())[zero_crossing - fit_range: zero_crossing + fit_range]
|
||||
y = list(t2E_dict.values())[zero_crossing - fit_range: zero_crossing + fit_range]
|
||||
[o.gamma_method() for o in y]
|
||||
|
||||
fit_result = fit_lin(x, y)
|
||||
return -fit_result[0] / fit_result[1]
|
||||
|
||||
|
||||
def _parse_array_openQCD2(d, n, size, wa, quadrupel=False):
|
||||
arr = []
|
||||
if d == 2:
|
||||
tot = 0
|
||||
for i in range(n[d-1]-1):
|
||||
if quadrupel:
|
||||
tmp = wa[tot:n[d-1]]
|
||||
tmp2 = []
|
||||
for i in range(len(tmp)):
|
||||
if i % 2 == 0:
|
||||
tmp2.append(tmp[i])
|
||||
arr.append(tmp2)
|
||||
else:
|
||||
arr.append(np.asarray(wa[tot:n[d-1]]))
|
||||
return arr
|
||||
|
||||
|
||||
# mimic the read_array routine of openQCD-2.0.
|
||||
# fp is the opened file handle
|
||||
# returns the dict array
|
||||
# at this point we only parse a 2d array
|
||||
# d = 2
|
||||
# n = [nfct[irw], 2*nsrc[irw]]
|
||||
def _read_array_openQCD2(fp):
|
||||
t = fp.read(4)
|
||||
d = struct.unpack('i', t)[0]
|
||||
t = fp.read(4*d)
|
||||
n = struct.unpack('%di' % (d), t)
|
||||
t = fp.read(4)
|
||||
size = struct.unpack('i', t)[0]
|
||||
if size == 4:
|
||||
types = 'i'
|
||||
elif size == 8:
|
||||
types = 'd'
|
||||
elif size == 16:
|
||||
types = 'dd'
|
||||
else:
|
||||
print('Type not known!')
|
||||
m = n[0]
|
||||
for i in range(1,d):
|
||||
m *= n[i]
|
||||
|
||||
t = fp.read(m*size)
|
||||
tmp = struct.unpack('%d%s' % (m, types), t)
|
||||
|
||||
arr = _parse_array_openQCD2(d, n, size, tmp, quadrupel=True)
|
||||
return {'d': d, 'n': n, 'size': size, 'arr': arr}
|
278
pyerrors/input/sfcf.py
Normal file
278
pyerrors/input/sfcf.py
Normal file
|
@ -0,0 +1,278 @@
|
|||
#!/usr/bin/env python
|
||||
# coding: utf-8
|
||||
|
||||
import os
|
||||
import fnmatch
|
||||
import re
|
||||
import numpy as np # Thinly-wrapped numpy
|
||||
from ..pyerrors import Obs
|
||||
|
||||
|
||||
def read_sfcf(path, prefix, name, **kwargs):
|
||||
"""Read sfcf C format from given folder structure.
|
||||
|
||||
Keyword arguments
|
||||
-----------------
|
||||
im -- if True, read imaginary instead of real part of the correlation function.
|
||||
single -- if True, read a boundary-to-boundary correlation function with a single value
|
||||
b2b -- if True, read a time-dependent boundary-to-boundary correlation function
|
||||
names -- Alternative labeling for replicas/ensembles. Has to have the appropriate length
|
||||
"""
|
||||
if kwargs.get('im'):
|
||||
im = 1
|
||||
part = 'imaginary'
|
||||
else:
|
||||
im = 0
|
||||
part = 'real'
|
||||
|
||||
if kwargs.get('single'):
|
||||
b2b = 1
|
||||
single = 1
|
||||
else:
|
||||
b2b = 0
|
||||
single = 0
|
||||
|
||||
if kwargs.get('b2b'):
|
||||
b2b = 1
|
||||
|
||||
read = 0
|
||||
T = 0
|
||||
start = 0
|
||||
ls = []
|
||||
for (dirpath, dirnames, filenames) in os.walk(path):
|
||||
ls.extend(dirnames)
|
||||
break
|
||||
if not ls:
|
||||
raise Exception('Error, directory not found')
|
||||
for exc in ls:
|
||||
if fnmatch.fnmatch(exc, prefix + '*'):
|
||||
ls = list(set(ls) - set(exc))
|
||||
if len(ls) > 1:
|
||||
ls.sort(key=lambda x: int(re.findall(r'\d+', x[len(prefix):])[0]))
|
||||
replica = len(ls)
|
||||
print('Read', part, 'part of', name, 'from', prefix, ',', replica, 'replica')
|
||||
if 'names' in kwargs:
|
||||
new_names = kwargs.get('names')
|
||||
if len(new_names) != replica:
|
||||
raise Exception('Names does not have the required length', replica)
|
||||
else:
|
||||
new_names = ls
|
||||
print(replica, 'replica')
|
||||
for i, item in enumerate(ls):
|
||||
print(item)
|
||||
sub_ls = []
|
||||
for (dirpath, dirnames, filenames) in os.walk(path+'/'+item):
|
||||
sub_ls.extend(dirnames)
|
||||
break
|
||||
for exc in sub_ls:
|
||||
if fnmatch.fnmatch(exc, 'cfg*'):
|
||||
sub_ls = list(set(sub_ls) - set(exc))
|
||||
sub_ls.sort(key=lambda x: int(x[3:]))
|
||||
no_cfg = len(sub_ls)
|
||||
print(no_cfg, 'configurations')
|
||||
|
||||
if i == 0:
|
||||
with open(path + '/' + item + '/' + sub_ls[0] + '/' + name) as fp:
|
||||
for k, line in enumerate(fp):
|
||||
if read == 1 and not line.strip() and k > start + 1:
|
||||
break
|
||||
if read == 1 and k >= start:
|
||||
T += 1
|
||||
if '[correlator]' in line:
|
||||
read = 1
|
||||
start = k + 7 + b2b
|
||||
T -= b2b
|
||||
|
||||
deltas = []
|
||||
for j in range(T):
|
||||
deltas.append([])
|
||||
|
||||
sublength = len(sub_ls)
|
||||
for j in range(T):
|
||||
deltas[j].append(np.zeros(sublength))
|
||||
|
||||
for cnfg, subitem in enumerate(sub_ls):
|
||||
with open(path + '/' + item + '/' + subitem + '/'+name) as fp:
|
||||
for k, line in enumerate(fp):
|
||||
if(k >= start and k < start + T):
|
||||
floats = list(map(float, line.split()))
|
||||
deltas[k-start][i][cnfg] = floats[1 + im - single]
|
||||
|
||||
result = []
|
||||
for t in range(T):
|
||||
result.append(Obs(deltas[t], new_names))
|
||||
|
||||
return result
|
||||
|
||||
|
||||
def read_sfcf_c(path, prefix, name, quarks='.*', noffset=0, wf=0, wf2=0, **kwargs):
|
||||
"""Read sfcf c format from given folder structure.
|
||||
|
||||
Arguments
|
||||
-----------------
|
||||
quarks -- Label of the quarks used in the sfcf input file
|
||||
noffset -- Offset of the source (only relevant when wavefunctions are used)
|
||||
wf -- ID of wave function
|
||||
wf2 -- ID of the second wavefunction (only relevant for boundary-to-boundary correlation functions)
|
||||
|
||||
Keyword arguments
|
||||
-----------------
|
||||
im -- if True, read imaginary instead of real part of the correlation function.
|
||||
b2b -- if True, read a time-dependent boundary-to-boundary correlation function
|
||||
names -- Alternative labeling for replicas/ensembles. Has to have the appropriate length
|
||||
"""
|
||||
|
||||
if kwargs.get('im'):
|
||||
im = 1
|
||||
part = 'imaginary'
|
||||
else:
|
||||
im = 0
|
||||
part = 'real'
|
||||
|
||||
if kwargs.get('b2b'):
|
||||
b2b = 1
|
||||
else:
|
||||
b2b = 0
|
||||
|
||||
read = 0
|
||||
T = 0
|
||||
start = 0
|
||||
ls = []
|
||||
for (dirpath, dirnames, filenames) in os.walk(path):
|
||||
ls.extend(dirnames)
|
||||
break
|
||||
if not ls:
|
||||
raise Exception('Error, directory not found')
|
||||
# Exclude folders with different names
|
||||
for exc in ls:
|
||||
if not fnmatch.fnmatch(exc, prefix+'*'):
|
||||
ls = list(set(ls) - set([exc]))
|
||||
if len(ls) > 1:
|
||||
ls.sort(key=lambda x: int(re.findall(r'\d+', x[len(prefix):])[0])) # New version, to cope with ids, etc.
|
||||
replica = len(ls)
|
||||
if 'names' in kwargs:
|
||||
new_names = kwargs.get('names')
|
||||
if len(new_names) != replica:
|
||||
raise Exception('Names does not have the required length', replica)
|
||||
else:
|
||||
new_names = ls
|
||||
print('Read', part, 'part of', name, 'from', prefix[:-1], ',', replica, 'replica')
|
||||
for i, item in enumerate(ls):
|
||||
sub_ls = []
|
||||
for (dirpath, dirnames, filenames) in os.walk(path+'/'+item):
|
||||
sub_ls.extend(filenames)
|
||||
break
|
||||
for exc in sub_ls:
|
||||
if not fnmatch.fnmatch(exc, prefix+'*'):
|
||||
sub_ls = list(set(sub_ls) - set([exc]))
|
||||
sub_ls.sort(key=lambda x: int(re.findall(r'\d+', x)[-1]))
|
||||
|
||||
first_cfg = int(re.findall(r'\d+', sub_ls[0])[-1])
|
||||
|
||||
last_cfg = len(sub_ls) + first_cfg - 1
|
||||
|
||||
for cfg in range(1, len(sub_ls)):
|
||||
if int(re.findall(r'\d+', sub_ls[cfg])[-1]) != first_cfg + cfg:
|
||||
last_cfg = cfg + first_cfg - 1
|
||||
break
|
||||
|
||||
no_cfg = last_cfg - first_cfg + 1
|
||||
print(item, ':', no_cfg, 'evenly spaced configurations (', first_cfg, '-', last_cfg, ') ,', len(sub_ls) - no_cfg, 'configs omitted\n')
|
||||
|
||||
if i == 0:
|
||||
pattern = 'name ' + name + '\nquarks ' + quarks + '\noffset ' + str(noffset) + '\nwf ' + str(wf)
|
||||
if b2b:
|
||||
pattern += '\nwf_2 ' + str(wf2)
|
||||
|
||||
with open(path+'/'+item+'/'+sub_ls[0], 'r') as file:
|
||||
content = file.read()
|
||||
match = re.search(pattern, content)
|
||||
if match:
|
||||
start_read = content.count('\n', 0, match.start()) + 5 + b2b
|
||||
end_match = re.search('\n\s*\n', content[match.start():])
|
||||
T = content[match.start():].count('\n', 0, end_match.start()) - 4 - b2b
|
||||
assert T > 0
|
||||
print(T, 'entries, starting to read in line', start_read)
|
||||
else:
|
||||
raise Exception('Correlator with pattern\n' + pattern + '\nnot found.')
|
||||
|
||||
deltas = []
|
||||
for j in range(T):
|
||||
deltas.append([])
|
||||
|
||||
sublength = no_cfg
|
||||
for j in range(T):
|
||||
deltas[j].append(np.zeros(sublength))
|
||||
|
||||
for cfg in range(no_cfg):
|
||||
with open(path+'/'+item+'/'+sub_ls[cfg]) as fp:
|
||||
for k, line in enumerate(fp):
|
||||
if k == start_read - 5 - b2b:
|
||||
if line.strip() != 'name ' + name:
|
||||
raise Exception('Wrong format', sub_ls[cfg])
|
||||
if(k >= start_read and k < start_read + T):
|
||||
floats = list(map(float, line.split()))
|
||||
deltas[k-start_read][i][cfg] = floats[-2:][im]
|
||||
|
||||
result = []
|
||||
for t in range(T):
|
||||
result.append(Obs(deltas[t], new_names))
|
||||
return result
|
||||
|
||||
|
||||
def read_qtop(path, prefix, **kwargs):
|
||||
"""Read qtop format from given folder structure.
|
||||
|
||||
Keyword arguments
|
||||
-----------------
|
||||
target -- specifies the topological sector to be reweighted to (default 0)
|
||||
full -- if true read the charge instead of the reweighting factor.
|
||||
"""
|
||||
|
||||
if 'target' in kwargs:
|
||||
target = kwargs.get('target')
|
||||
else:
|
||||
target = 0
|
||||
|
||||
if kwargs.get('full'):
|
||||
full = 1
|
||||
else:
|
||||
full = 0
|
||||
|
||||
ls = []
|
||||
for (dirpath, dirnames, filenames) in os.walk(path):
|
||||
ls.extend(filenames)
|
||||
break
|
||||
|
||||
if not ls:
|
||||
raise Exception('Error, directory not found')
|
||||
|
||||
# Exclude files with different names
|
||||
for exc in ls:
|
||||
if not fnmatch.fnmatch(exc, prefix+'*'):
|
||||
ls = list(set(ls) - set([exc]))
|
||||
if len(ls) > 1:
|
||||
ls.sort(key=lambda x: int(re.findall(r'\d+', x[len(prefix):])[0])) # New version, to cope with ids, etc.
|
||||
replica = len(ls)
|
||||
print('Read Q_top from', prefix[:-1], ',', replica, 'replica')
|
||||
|
||||
deltas = []
|
||||
|
||||
for rep in range(replica):
|
||||
tmp = []
|
||||
with open(path+'/'+ls[rep]) as fp:
|
||||
for k, line in enumerate(fp):
|
||||
floats = list(map(float, line.split()))
|
||||
if full == 1:
|
||||
tmp.append(floats[1])
|
||||
else:
|
||||
if int(floats[1]) == target:
|
||||
tmp.append(1.0)
|
||||
else:
|
||||
tmp.append(0.0)
|
||||
|
||||
deltas.append(np.array(tmp))
|
||||
|
||||
result = Obs(deltas, [(w.split('.'))[0] for w in ls])
|
||||
|
||||
return result
|
Loading…
Add table
Reference in a new issue