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https://github.com/fjosw/pyerrors.git
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681 lines
26 KiB
Python
681 lines
26 KiB
Python
import os
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import fnmatch
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import re
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import numpy as np # Thinly-wrapped numpy
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from ..obs import Obs
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from .utils import sort_names, check_idl
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import itertools
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sep = "/"
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def read_sfcf(path, prefix, name, quarks='.*', corr_type="bi", noffset=0, wf=0, wf2=0, version="1.0c", cfg_separator="n", silent=False, **kwargs):
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"""Read sfcf files from given folder structure.
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Parameters
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----------
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path : str
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Path to the sfcf files.
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prefix : str
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Prefix of the sfcf files.
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name : str
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Name of the correlation function to read.
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quarks : str
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Label of the quarks used in the sfcf input file. e.g. "quark quark"
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for version 0.0 this does NOT need to be given with the typical " - "
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that is present in the output file,
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this is done automatically for this version
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corr_type : str
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Type of correlation function to read. Can be
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- 'bi' for boundary-inner
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- 'bb' for boundary-boundary
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- 'bib' for boundary-inner-boundary
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noffset : int
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Offset of the source (only relevant when wavefunctions are used)
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wf : int
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ID of wave function
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wf2 : int
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ID of the second wavefunction
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(only relevant for boundary-to-boundary correlation functions)
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im : bool
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if True, read imaginary instead of real part
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of the correlation function.
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names : list
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Alternative labeling for replicas/ensembles.
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Has to have the appropriate length
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ens_name : str
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replaces the name of the ensemble
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version: str
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version of SFCF, with which the measurement was done.
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if the compact output option (-c) was specified,
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append a "c" to the version (e.g. "1.0c")
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if the append output option (-a) was specified,
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append an "a" to the version
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cfg_separator : str
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String that separates the ensemble identifier from the configuration number (default 'n').
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replica: list
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list of replica to be read, default is all
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files: list
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list of files to be read per replica, default is all.
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for non-compact output format, hand the folders to be read here.
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check_configs: list[list[int]]
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list of list of supposed configs, eg. [range(1,1000)]
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for one replicum with 1000 configs
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Returns
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-------
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result: list[Obs]
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list of Observables with length T, observable per timeslice.
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bb-type correlators have length 1.
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"""
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ret = read_sfcf_multi(path, prefix, [name], quarks_list=[quarks], corr_type_list=[corr_type],
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noffset_list=[noffset], wf_list=[wf], wf2_list=[wf2], version=version,
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cfg_separator=cfg_separator, silent=silent, **kwargs)
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return ret[name][quarks][str(noffset)][str(wf)][str(wf2)]
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def read_sfcf_multi(path, prefix, name_list, quarks_list=['.*'], corr_type_list=['bi'], noffset_list=[0], wf_list=[0], wf2_list=[0], version="1.0c", cfg_separator="n", silent=False, keyed_out=False, **kwargs):
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"""Read sfcf files from given folder structure.
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Parameters
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----------
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path : str
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Path to the sfcf files.
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prefix : str
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Prefix of the sfcf files.
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name : str
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Name of the correlation function to read.
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quarks_list : list[str]
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Label of the quarks used in the sfcf input file. e.g. "quark quark"
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for version 0.0 this does NOT need to be given with the typical " - "
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that is present in the output file,
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this is done automatically for this version
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corr_type_list : list[str]
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Type of correlation function to read. Can be
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- 'bi' for boundary-inner
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- 'bb' for boundary-boundary
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- 'bib' for boundary-inner-boundary
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noffset_list : list[int]
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Offset of the source (only relevant when wavefunctions are used)
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wf_list : int
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ID of wave function
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wf2_list : list[int]
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ID of the second wavefunction
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(only relevant for boundary-to-boundary correlation functions)
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im : bool
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if True, read imaginary instead of real part
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of the correlation function.
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names : list
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Alternative labeling for replicas/ensembles.
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Has to have the appropriate length
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ens_name : str
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replaces the name of the ensemble
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version: str
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version of SFCF, with which the measurement was done.
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if the compact output option (-c) was specified,
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append a "c" to the version (e.g. "1.0c")
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if the append output option (-a) was specified,
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append an "a" to the version
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cfg_separator : str
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String that separates the ensemble identifier from the configuration number (default 'n').
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replica: list
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list of replica to be read, default is all
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files: list[list[int]]
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list of files to be read per replica, default is all.
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for non-compact output format, hand the folders to be read here.
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check_configs: list[list[int]]
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list of list of supposed configs, eg. [range(1,1000)]
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for one replicum with 1000 configs
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Returns
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-------
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result: dict[list[Obs]]
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dict with one of the following properties:
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if keyed_out:
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dict[key] = list[Obs]
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where key has the form name/quarks/offset/wf/wf2
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if not keyed_out:
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dict[name][quarks][offset][wf][wf2] = list[Obs]
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"""
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if kwargs.get('im'):
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im = 1
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part = 'imaginary'
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else:
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im = 0
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part = 'real'
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known_versions = ["0.0", "1.0", "2.0", "1.0c", "2.0c", "1.0a", "2.0a"]
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if version not in known_versions:
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raise Exception("This version is not known!")
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if (version[-1] == "c"):
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appended = False
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compact = True
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version = version[:-1]
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elif (version[-1] == "a"):
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appended = True
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compact = False
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version = version[:-1]
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else:
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compact = False
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appended = False
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ls = []
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if "replica" in kwargs:
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ls = kwargs.get("replica")
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else:
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for (dirpath, dirnames, filenames) in os.walk(path):
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if not appended:
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ls.extend(dirnames)
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else:
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ls.extend(filenames)
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break
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if not ls:
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raise Exception('Error, directory not found')
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# Exclude folders with different names
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for exc in ls:
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if not fnmatch.fnmatch(exc, prefix + '*'):
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ls = list(set(ls) - set([exc]))
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if not appended:
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ls = sort_names(ls)
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replica = len(ls)
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else:
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replica = len([file.split(".")[-1] for file in ls]) // len(set([file.split(".")[-1] for file in ls]))
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if replica == 0:
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raise Exception('No replica found in directory')
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if not silent:
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print('Read', part, 'part of', name_list, 'from', prefix[:-1], ',', replica, 'replica')
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if 'names' in kwargs:
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new_names = kwargs.get('names')
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if len(new_names) != len(set(new_names)):
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raise Exception("names are not unique!")
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if len(new_names) != replica:
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raise Exception('names should have the length', replica)
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else:
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ens_name = kwargs.get("ens_name")
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if not appended:
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new_names = _get_rep_names(ls, ens_name, rep_sep=(kwargs.get('rep_string', 'r')))
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else:
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new_names = _get_appended_rep_names(ls, prefix, name_list[0], ens_name, rep_sep=(kwargs.get('rep_string', 'r')))
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new_names = sort_names(new_names)
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idl = []
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noffset_list = [str(x) for x in noffset_list]
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wf_list = [str(x) for x in wf_list]
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wf2_list = [str(x) for x in wf2_list]
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# setup dict structures
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intern = {}
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for name, corr_type in zip(name_list, corr_type_list):
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intern[name] = {}
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b2b, single = _extract_corr_type(corr_type)
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intern[name]["b2b"] = b2b
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intern[name]["single"] = single
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intern[name]["spec"] = {}
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for quarks in quarks_list:
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intern[name]["spec"][quarks] = {}
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for off in noffset_list:
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intern[name]["spec"][quarks][off] = {}
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for w in wf_list:
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intern[name]["spec"][quarks][off][w] = {}
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if b2b:
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for w2 in wf2_list:
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intern[name]["spec"][quarks][off][w][w2] = {}
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intern[name]["spec"][quarks][off][w][w2]["pattern"] = _make_pattern(version, name, off, w, w2, intern[name]['b2b'], quarks)
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else:
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intern[name]["spec"][quarks][off][w]["0"] = {}
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intern[name]["spec"][quarks][off][w]["0"]["pattern"] = _make_pattern(version, name, off, w, 0, intern[name]['b2b'], quarks)
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internal_ret_dict = {}
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needed_keys = []
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for name, corr_type in zip(name_list, corr_type_list):
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b2b, single = _extract_corr_type(corr_type)
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if b2b:
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needed_keys.extend(_lists2key([name], quarks_list, noffset_list, wf_list, wf2_list))
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else:
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needed_keys.extend(_lists2key([name], quarks_list, noffset_list, wf_list, ["0"]))
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for key in needed_keys:
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internal_ret_dict[key] = []
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if not appended:
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for i, item in enumerate(ls):
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rep_path = path + '/' + item
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if "files" in kwargs:
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files = kwargs.get("files")
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if isinstance(files, list):
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if all(isinstance(f, list) for f in files):
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files = files[i]
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elif all(isinstance(f, str) for f in files):
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files = files
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else:
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raise TypeError("files has to be of type list[list[str]] or list[str]!")
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else:
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raise TypeError("files has to be of type list[list[str]] or list[str]!")
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else:
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files = []
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sub_ls = _find_files(rep_path, prefix, compact, files)
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rep_idl = []
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no_cfg = len(sub_ls)
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for cfg in sub_ls:
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try:
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if compact:
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rep_idl.append(int(cfg.split(cfg_separator)[-1]))
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else:
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rep_idl.append(int(cfg[3:]))
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except Exception:
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raise Exception("Couldn't parse idl from directory, problem with file " + cfg)
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rep_idl.sort()
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# maybe there is a better way to print the idls
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if not silent:
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print(item, ':', no_cfg, ' configurations')
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idl.append(rep_idl)
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# here we have found all the files we need to look into.
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if i == 0:
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if version != "0.0" and compact:
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file = path + '/' + item + '/' + sub_ls[0]
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for name_index, name in enumerate(name_list):
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if version == "0.0" or not compact:
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file = path + '/' + item + '/' + sub_ls[0] + '/' + name
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if corr_type_list[name_index] == 'bi':
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name_keys = _lists2key(quarks_list, noffset_list, wf_list, ["0"])
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else:
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name_keys = _lists2key(quarks_list, noffset_list, wf_list, wf2_list)
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for key in name_keys:
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specs = _key2specs(key)
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quarks = specs[0]
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off = specs[1]
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w = specs[2]
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w2 = specs[3]
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# here, we want to find the place within the file,
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# where the correlator we need is stored.
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# to do so, the pattern needed is put together
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# from the input values
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start_read, T = _find_correlator(file, version, intern[name]["spec"][quarks][str(off)][str(w)][str(w2)]["pattern"], intern[name]['b2b'], silent=silent)
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intern[name]["spec"][quarks][str(off)][str(w)][str(w2)]["start"] = start_read
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intern[name]["T"] = T
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# preparing the datastructure
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# the correlators get parsed into...
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deltas = []
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for j in range(intern[name]["T"]):
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deltas.append([])
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internal_ret_dict[sep.join([name, key])] = deltas
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if compact:
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rep_deltas = _read_compact_rep(path, item, sub_ls, intern, needed_keys, im)
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for key in needed_keys:
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name = _key2specs(key)[0]
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for t in range(intern[name]["T"]):
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internal_ret_dict[key][t].append(rep_deltas[key][t])
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else:
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for key in needed_keys:
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rep_data = []
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name = _key2specs(key)[0]
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for subitem in sub_ls:
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cfg_path = path + '/' + item + '/' + subitem
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file_data = _read_o_file(cfg_path, name, needed_keys, intern, version, im)
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rep_data.append(file_data)
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for t in range(intern[name]["T"]):
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internal_ret_dict[key][t].append([])
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for cfg in range(no_cfg):
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internal_ret_dict[key][t][i].append(rep_data[cfg][key][t])
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else:
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for key in needed_keys:
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specs = _key2specs(key)
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name = specs[0]
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quarks = specs[1]
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off = specs[2]
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w = specs[3]
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w2 = specs[4]
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if "files" in kwargs:
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if isinstance(kwargs.get("files"), list) and all(isinstance(f, str) for f in kwargs.get("files")):
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name_ls = kwargs.get("files")
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else:
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raise TypeError("In append mode, files has to be of type list[str]!")
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else:
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name_ls = ls
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for exc in name_ls:
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if not fnmatch.fnmatch(exc, prefix + '*.' + name):
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name_ls = list(set(name_ls) - set([exc]))
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name_ls = sort_names(name_ls)
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pattern = intern[name]['spec'][quarks][off][w][w2]['pattern']
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deltas = []
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for rep, file in enumerate(name_ls):
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rep_idl = []
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filename = path + '/' + file
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T, rep_idl, rep_data = _read_append_rep(filename, pattern, intern[name]['b2b'], cfg_separator, im, intern[name]['single'])
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if rep == 0:
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intern[name]['T'] = T
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for t in range(intern[name]['T']):
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deltas.append([])
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for t in range(intern[name]['T']):
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deltas[t].append(rep_data[t])
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internal_ret_dict[key] = deltas
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if name == name_list[0]:
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idl.append(rep_idl)
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if kwargs.get("check_configs") is True:
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if not silent:
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print("Checking for missing configs...")
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che = kwargs.get("check_configs")
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if not (len(che) == len(idl)):
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raise Exception("check_configs has to be the same length as replica!")
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for r in range(len(idl)):
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if not silent:
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print("checking " + new_names[r])
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check_idl(idl[r], che[r])
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if not silent:
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print("Done")
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result_dict = {}
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if keyed_out:
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for key in needed_keys:
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name = _key2specs(key)[0]
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result = []
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for t in range(intern[name]["T"]):
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result.append(Obs(internal_ret_dict[key][t], new_names, idl=idl))
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result_dict[key] = result
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else:
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for name, corr_type in zip(name_list, corr_type_list):
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result_dict[name] = {}
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for quarks in quarks_list:
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result_dict[name][quarks] = {}
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for off in noffset_list:
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result_dict[name][quarks][off] = {}
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for w in wf_list:
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result_dict[name][quarks][off][w] = {}
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if corr_type != 'bi':
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for w2 in wf2_list:
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key = _specs2key(name, quarks, off, w, w2)
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result = []
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for t in range(intern[name]["T"]):
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result.append(Obs(internal_ret_dict[key][t], new_names, idl=idl))
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result_dict[name][quarks][str(off)][str(w)][str(w2)] = result
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else:
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key = _specs2key(name, quarks, off, w, "0")
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result = []
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for t in range(intern[name]["T"]):
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result.append(Obs(internal_ret_dict[key][t], new_names, idl=idl))
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result_dict[name][quarks][str(off)][str(w)][str(0)] = result
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return result_dict
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def _lists2key(*lists):
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keys = []
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for tup in itertools.product(*lists):
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keys.append(sep.join(tup))
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return keys
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def _key2specs(key):
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return key.split(sep)
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def _specs2key(*specs):
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return sep.join(specs)
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def _read_o_file(cfg_path, name, needed_keys, intern, version, im):
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return_vals = {}
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for key in needed_keys:
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file = cfg_path + '/' + name
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specs = _key2specs(key)
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if specs[0] == name:
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with open(file) as fp:
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lines = fp.readlines()
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quarks = specs[1]
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off = specs[2]
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w = specs[3]
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w2 = specs[4]
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T = intern[name]["T"]
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start_read = intern[name]["spec"][quarks][off][w][w2]["start"]
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deltas = []
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for line in lines[start_read:start_read + T]:
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floats = list(map(float, line.split()))
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if version == "0.0":
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deltas.append(floats[im - intern[name]["single"]])
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else:
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deltas.append(floats[1 + im - intern[name]["single"]])
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return_vals[key] = deltas
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return return_vals
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def _extract_corr_type(corr_type):
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if corr_type == 'bb':
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b2b = True
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single = True
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elif corr_type == 'bib':
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b2b = True
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single = False
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else:
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b2b = False
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single = False
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return b2b, single
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def _find_files(rep_path, prefix, compact, files=[]):
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sub_ls = []
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if not files == []:
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files.sort(key=lambda x: int(re.findall(r'\d+', x)[-1]))
|
|
else:
|
|
for (dirpath, dirnames, filenames) in os.walk(rep_path):
|
|
if compact:
|
|
sub_ls.extend(filenames)
|
|
else:
|
|
sub_ls.extend(dirnames)
|
|
break
|
|
if compact:
|
|
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]))
|
|
else:
|
|
for exc in sub_ls:
|
|
if not fnmatch.fnmatch(exc, 'cfg*'):
|
|
sub_ls = list(set(sub_ls) - set([exc]))
|
|
sub_ls.sort(key=lambda x: int(x[3:]))
|
|
files = sub_ls
|
|
if len(files) == 0:
|
|
raise FileNotFoundError("Did not find files in", rep_path, "with prefix", prefix, "and the given structure.")
|
|
return files
|
|
|
|
|
|
def _make_pattern(version, name, noffset, wf, wf2, b2b, quarks):
|
|
if version == "0.0":
|
|
pattern = "# " + name + " : offset " + str(noffset) + ", wf " + str(wf)
|
|
if b2b:
|
|
pattern += ", wf_2 " + str(wf2)
|
|
qs = quarks.split(" ")
|
|
pattern += " : " + qs[0] + " - " + qs[1]
|
|
else:
|
|
pattern = 'name ' + name + '\nquarks ' + quarks + '\noffset ' + str(noffset) + '\nwf ' + str(wf)
|
|
if b2b:
|
|
pattern += '\nwf_2 ' + str(wf2)
|
|
return pattern
|
|
|
|
|
|
def _find_correlator(file_name, version, pattern, b2b, silent=False):
|
|
T = 0
|
|
|
|
with open(file_name, "r") as my_file:
|
|
|
|
content = my_file.read()
|
|
match = re.search(pattern, content)
|
|
if match:
|
|
if version == "0.0":
|
|
start_read = content.count('\n', 0, match.start()) + 1
|
|
T = content.count('\n', start_read)
|
|
else:
|
|
start_read = content.count('\n', 0, match.start()) + 5 + b2b
|
|
end_match = re.search(r'\n\s*\n', content[match.start():])
|
|
T = content[match.start():].count('\n', 0, end_match.start()) - 4 - b2b
|
|
if not T > 0:
|
|
raise ValueError("Correlator with pattern\n" + pattern + "\nis empty!")
|
|
if not silent:
|
|
print(T, 'entries, starting to read in line', start_read)
|
|
|
|
else:
|
|
raise ValueError('Correlator with pattern\n' + pattern + '\nnot found.')
|
|
|
|
return start_read, T
|
|
|
|
|
|
def _read_compact_file(rep_path, cfg_file, intern, needed_keys, im):
|
|
return_vals = {}
|
|
with open(rep_path + cfg_file) as fp:
|
|
lines = fp.readlines()
|
|
for key in needed_keys:
|
|
keys = _key2specs(key)
|
|
name = keys[0]
|
|
quarks = keys[1]
|
|
off = keys[2]
|
|
w = keys[3]
|
|
w2 = keys[4]
|
|
|
|
T = intern[name]["T"]
|
|
start_read = intern[name]["spec"][quarks][off][w][w2]["start"]
|
|
# check, if the correlator is in fact
|
|
# printed completely
|
|
if (start_read + T + 1 > len(lines)):
|
|
raise Exception("EOF before end of correlator data! Maybe " + rep_path + cfg_file + " is corrupted?")
|
|
corr_lines = lines[start_read - 6: start_read + T]
|
|
t_vals = []
|
|
|
|
if corr_lines[1 - intern[name]["b2b"]].strip() != 'name ' + name:
|
|
raise Exception('Wrong format in file', cfg_file)
|
|
|
|
for k in range(6, T + 6):
|
|
floats = list(map(float, corr_lines[k].split()))
|
|
t_vals.append(floats[-2:][im])
|
|
return_vals[key] = t_vals
|
|
return return_vals
|
|
|
|
|
|
def _read_compact_rep(path, rep, sub_ls, intern, needed_keys, im):
|
|
rep_path = path + '/' + rep + '/'
|
|
no_cfg = len(sub_ls)
|
|
|
|
return_vals = {}
|
|
for key in needed_keys:
|
|
name = _key2specs(key)[0]
|
|
deltas = []
|
|
for t in range(intern[name]["T"]):
|
|
deltas.append(np.zeros(no_cfg))
|
|
return_vals[key] = deltas
|
|
|
|
for cfg in range(no_cfg):
|
|
cfg_file = sub_ls[cfg]
|
|
cfg_data = _read_compact_file(rep_path, cfg_file, intern, needed_keys, im)
|
|
for key in needed_keys:
|
|
name = _key2specs(key)[0]
|
|
for t in range(intern[name]["T"]):
|
|
return_vals[key][t][cfg] = cfg_data[key][t]
|
|
return return_vals
|
|
|
|
|
|
def _read_chunk(chunk, gauge_line, cfg_sep, start_read, T, corr_line, b2b, pattern, im, single):
|
|
try:
|
|
idl = int(chunk[gauge_line].split(cfg_sep)[-1])
|
|
except Exception:
|
|
raise Exception("Couldn't parse idl from directory, problem with chunk around line ", gauge_line)
|
|
|
|
found_pat = ""
|
|
data = []
|
|
for li in chunk[corr_line + 1:corr_line + 6 + b2b]:
|
|
found_pat += li
|
|
if re.search(pattern, found_pat):
|
|
for t, line in enumerate(chunk[start_read:start_read + T]):
|
|
floats = list(map(float, line.split()))
|
|
data.append(floats[im + 1 - single])
|
|
return idl, data
|
|
|
|
|
|
def _read_append_rep(filename, pattern, b2b, cfg_separator, im, single):
|
|
with open(filename, 'r') as fp:
|
|
content = fp.readlines()
|
|
data_starts = []
|
|
for linenumber, line in enumerate(content):
|
|
if "[run]" in line:
|
|
data_starts.append(linenumber)
|
|
if len(set([data_starts[i] - data_starts[i - 1] for i in range(1, len(data_starts))])) > 1:
|
|
raise Exception("Irregularities in file structure found, not all runs have the same output length")
|
|
chunk = content[:data_starts[1]]
|
|
for linenumber, line in enumerate(chunk):
|
|
if line.startswith("gauge_name"):
|
|
gauge_line = linenumber
|
|
elif line.startswith("[correlator]"):
|
|
corr_line = linenumber
|
|
found_pat = ""
|
|
for li in chunk[corr_line + 1: corr_line + 6 + b2b]:
|
|
found_pat += li
|
|
if re.search(pattern, found_pat):
|
|
start_read = corr_line + 7 + b2b
|
|
break
|
|
else:
|
|
raise ValueError("Did not find pattern\n", pattern, "\nin\n", filename)
|
|
endline = corr_line + 6 + b2b
|
|
while not chunk[endline] == "\n":
|
|
endline += 1
|
|
T = endline - start_read
|
|
|
|
# all other chunks should follow the same structure
|
|
rep_idl = []
|
|
rep_data = []
|
|
|
|
for cnfg in range(len(data_starts)):
|
|
start = data_starts[cnfg]
|
|
stop = start + data_starts[1]
|
|
chunk = content[start:stop]
|
|
idl, data = _read_chunk(chunk, gauge_line, cfg_separator, start_read, T, corr_line, b2b, pattern, im, single)
|
|
rep_idl.append(idl)
|
|
rep_data.append(data)
|
|
|
|
data = []
|
|
|
|
for t in range(T):
|
|
data.append([])
|
|
for c in range(len(rep_data)):
|
|
data[t].append(rep_data[c][t])
|
|
return T, rep_idl, data
|
|
|
|
|
|
def _get_rep_names(ls, ens_name=None, rep_sep='r'):
|
|
new_names = []
|
|
for entry in ls:
|
|
try:
|
|
idx = entry.index(rep_sep)
|
|
except Exception:
|
|
raise Exception("Automatic recognition of replicum failed, please enter the key word 'names'.")
|
|
|
|
if ens_name:
|
|
new_names.append(ens_name + '|' + entry[idx:])
|
|
else:
|
|
new_names.append(entry[:idx] + '|' + entry[idx:])
|
|
return new_names
|
|
|
|
|
|
def _get_appended_rep_names(ls, prefix, name, ens_name=None, rep_sep='r'):
|
|
new_names = []
|
|
for exc in ls:
|
|
if not fnmatch.fnmatch(exc, prefix + '*.' + name):
|
|
ls = list(set(ls) - set([exc]))
|
|
ls.sort(key=lambda x: int(re.findall(r'\d+', x)[-1]))
|
|
for entry in ls:
|
|
myentry = entry[:-len(name) - 1]
|
|
try:
|
|
idx = myentry.index(rep_sep)
|
|
except Exception:
|
|
raise Exception("Automatic recognition of replicum failed, please enter the key word 'names'.")
|
|
|
|
if ens_name:
|
|
new_names.append(ens_name + '|' + entry[idx:])
|
|
else:
|
|
new_names.append(myentry[:idx] + '|' + myentry[idx:])
|
|
return new_names
|