pyerrors.input.openQCD
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#!/usr/bin/env python # coding: utf-8 import os import fnmatch import re import struct import numpy as np # Thinly-wrapped numpy from ..obs 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 Parameters ---------- version : str version of openQCD, default 2.0 r_start : list list which contains the first config to be read for each replicum r_stop : list list which contains the last config to be read for each replicum postfix : str postfix of the file to read, e.g. '.ms1' for openQCD-files """ known_oqcd_versions = ['1.4', '1.6', '2.0'] if not (version in known_oqcd_versions): raise Exception('Unknown openQCD version defined!') 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])) 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='') # Adjust replica names to new bookmarking system if names is None: rep_names = [] for entry in ls: truncated_entry = entry.split('.')[0] idx = truncated_entry.index('r') rep_names.append(truncated_entry[:idx] + '|' + truncated_entry[idx:]) 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 version == '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 == '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 == '1.6' or version == '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 is None: result.append(Obs(deltas[t], rep_names)) 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 : str Path to .ms.dat files prefix : str Ensemble prefix dtr_read : int 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 : int First timeslice where the boundary effects have sufficiently decayed. spatial_extent : int spatial extent of the lattice, required for normalization. fit_range : int Number of data points left and right of the zero crossing to be included in the linear fit. (Default: 5) r_start : list list which contains the first config to be read for each replicum. r_stop: list list which contains the last config to be read for each replicum. plaquette : bool 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}
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def read_rwms(path, prefix, version='2.0', names=None, **kwargs): """Read rwms format from given folder structure. Returns a list of length nrw Parameters ---------- version : str version of openQCD, default 2.0 r_start : list list which contains the first config to be read for each replicum r_stop : list list which contains the last config to be read for each replicum postfix : str postfix of the file to read, e.g. '.ms1' for openQCD-files """ known_oqcd_versions = ['1.4', '1.6', '2.0'] if not (version in known_oqcd_versions): raise Exception('Unknown openQCD version defined!') 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])) 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='') # Adjust replica names to new bookmarking system if names is None: rep_names = [] for entry in ls: truncated_entry = entry.split('.')[0] idx = truncated_entry.index('r') rep_names.append(truncated_entry[:idx] + '|' + truncated_entry[idx:]) 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 version == '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 == '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 == '1.6' or version == '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 is None: result.append(Obs(deltas[t], rep_names)) else: print(names) result.append(Obs(deltas[t], names)) return result
Read rwms format from given folder structure. Returns a list of length nrw
Parameters
- version (str): version of openQCD, default 2.0
- r_start (list): list which contains the first config to be read for each replicum
- r_stop (list): list which contains the last config to be read for each replicum
- postfix (str): postfix of the file to read, e.g. '.ms1' for openQCD-files
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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 : str Path to .ms.dat files prefix : str Ensemble prefix dtr_read : int 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 : int First timeslice where the boundary effects have sufficiently decayed. spatial_extent : int spatial extent of the lattice, required for normalization. fit_range : int Number of data points left and right of the zero crossing to be included in the linear fit. (Default: 5) r_start : list list which contains the first config to be read for each replicum. r_stop: list list which contains the last config to be read for each replicum. plaquette : bool 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]
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
Parameters
- path (str): Path to .ms.dat files
- prefix (str): Ensemble prefix
- dtr_read (int): 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 (int): First timeslice where the boundary effects have sufficiently decayed.
- spatial_extent (int): spatial extent of the lattice, required for normalization.
- fit_range (int): Number of data points left and right of the zero crossing to be included in the linear fit. (Default: 5)
- r_start (list): list which contains the first config to be read for each replicum.
- r_stop (list): list which contains the last config to be read for each replicum.
- plaquette (bool): If true extract the plaquette estimate of t0 instead.