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https://github.com/fjosw/pyerrors.git
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use benedict to make loops easier
This commit is contained in:
Justus Kuhlmann
parent
eb58920e34
commit
fa3987479b
1 changed files with 181 additions and 173 deletions
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@ -4,6 +4,8 @@ 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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from benedict import benedict
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from copy import deepcopy
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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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@ -65,7 +67,9 @@ def read_sfcf(path, prefix, name, quarks='.*', corr_type="bi", noffset=0, wf=0,
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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], noffset_list=[noffset], wf_list=[wf], wf2_list=[wf2], version=version, cfg_separator=cfg_separator, silent=silent, nice_output=True, **kwargs)
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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, nice_output=True, **kwargs)
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return ret
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@ -195,32 +199,11 @@ def read_sfcf_multi(path, prefix, name_list, quarks_list=['.*'], corr_type_list=
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idl = []
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# setup dect 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][str(off)] = {}
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for w in wf_list:
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intern[name]["spec"][quarks][str(off)][str(w)] = {}
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for w2 in wf2_list:
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intern[name]["spec"][quarks][str(off)][str(w)][str(w2)] = {}
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# setup dict structures
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intern = _setup_intern_dict(name_list, corr_type_list, quarks_list, noffset_list, wf_list, wf2_list)
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internal_ret_dict = {}
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for name in name_list:
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internal_ret_dict[name] = {}
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for quarks in quarks_list:
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internal_ret_dict[name][quarks] = {}
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for off in noffset_list:
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internal_ret_dict[name][quarks][str(off)] = {}
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for w in wf_list:
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internal_ret_dict[name][quarks][str(off)][str(w)] = {}
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ret_key_paths, internal_ret_dict = _setup_ret_dict(name_list, quarks_list, noffset_list, wf_list, wf2_list)
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dict_template = deepcopy(internal_ret_dict)
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if not appended:
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for i, item in enumerate(ls):
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@ -249,60 +232,53 @@ def read_sfcf_multi(path, prefix, name_list, quarks_list=['.*'], corr_type_list=
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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 in name_list:
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for k in ret_key_paths:
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ori_keys = k.split("/")
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name = ori_keys[0]
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quarks = ori_keys[1]
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off = ori_keys[2]
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w = ori_keys[3]
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w2 = ori_keys[4]
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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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for quarks in quarks_list:
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for off in noffset_list:
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for w in wf_list:
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for w2 in wf2_list:
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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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intern[name]["spec"][quarks][str(off)][str(w)][str(w2)]["pattern"] = _make_pattern(version, name, off, w, w2, intern[name]['b2b'], quarks)
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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[name][quarks][str(off)][str(w)][str(w2)] = deltas
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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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intern[name]["spec"][quarks][str(off)][str(w)][str(w2)]["pattern"] = _make_pattern(version, name, off, w, w2, intern[name]['b2b'], quarks)
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start_read, T = _find_correlator(file, version, intern[name]["spec"][quarks][off][w][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[k] = deltas
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if compact:
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rep_deltas = _read_compact_rep(path, item, sub_ls, intern, im)
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for name in name_list:
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for quarks in quarks_list:
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for off in noffset_list:
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for w in wf_list:
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for w2 in wf2_list:
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for t in range(intern[name]["T"]):
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internal_ret_dict[name][quarks][str(off)][str(w)][str(w2)][t].append(rep_deltas[name][quarks][str(off)][str(w)][str(w2)][t])
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rep_deltas = _read_compact_rep(path, item, sub_ls, intern, ret_key_paths, im, dict_template)
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for k in ret_key_paths:
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name = k.split("/")[0]
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for t in range(intern[name]["T"]):
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internal_ret_dict[k][t].append(rep_deltas[k][t])
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else:
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for name in name_list:
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for name in internal_ret_dict:
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rep_data = []
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for cnfg, subitem in enumerate(sub_ls):
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for quarks in quarks_list:
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for off in noffset_list:
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for w in wf_list:
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for w2 in wf2_list:
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cfg_path = path + '/' + item + '/' + subitem
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file_data = _read_o_file(cfg_path, name, intern, version, im)
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rep_data.append(file_data)
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for k in _get_deep_paths(internal_ret_dict.subset(name)):
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cfg_path = path + '/' + item + '/' + subitem
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file_data = _read_o_file(cfg_path, name, intern, version, im, dict_template)
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rep_data.append(file_data)
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for quarks in quarks_list:
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for off in noffset_list:
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for w in wf_list:
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for w2 in wf2_list:
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for t in range(intern[name]["T"]):
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internal_ret_dict[name][quarks][str(off)][str(w)][str(w2)][t].append([])
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for cfg in range(no_cfg):
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internal_ret_dict[name][quarks][str(off)][str(w)][str(w2)][t][i].append(rep_data[cfg][quarks][str(off)][str(w)][str(w2)][t])
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for k in _get_deep_paths(internal_ret_dict.subset(name)[name]):
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for t in range(intern[name]["T"]):
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internal_ret_dict[name][k][t].append([])
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for cfg in range(no_cfg):
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internal_ret_dict[name][k][t][i].append(rep_data[cfg][k][t])
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else:
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for name in name_list:
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for name in internal_ret_dict:
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if "files" in kwargs:
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ls = kwargs.get("files")
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else:
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@ -310,26 +286,29 @@ def read_sfcf_multi(path, prefix, name_list, quarks_list=['.*'], corr_type_list=
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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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for quarks in quarks_list:
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for off in noffset_list:
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for w in wf_list:
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for w2 in wf2_list:
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pattern = _make_pattern(version, name, off, w, w2, intern[name]['b2b'], quarks)
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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[name][quarks][str(off)][str(w)][str(w2)] = deltas
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if name == name_list[0]:
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idl.append(rep_idl)
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for k in _get_deep_paths(internal_ret_dict.subset(name)[name]):
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ori_keys = k.split("/")
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quarks = ori_keys[0]
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off = ori_keys[1]
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w = ori_keys[2]
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w2 = ori_keys[3]
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pattern = _make_pattern(version, name, off, w, w2, intern[name]['b2b'], quarks)
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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[name][k] = 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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@ -344,47 +323,78 @@ def read_sfcf_multi(path, prefix, name_list, quarks_list=['.*'], corr_type_list=
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if not silent:
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print("Done")
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result_dict = {}
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for name in name_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][str(off)] = {}
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for w in wf_list:
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result_dict[name][quarks][str(off)][str(w)] = {}
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for w2 in wf2_list:
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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[name][quarks][str(off)][str(w)][str(w2)][t], new_names, idl=idl))
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result_dict[name][quarks][str(off)][str(w)][str(w2)] = result
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result_dict = deepcopy(dict_template)
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for k in ret_key_paths:
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name = k.split("/")[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[k][t], new_names, idl=idl))
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print(result)
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result_dict[k] = result
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if nice_output:
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result_dict = _reduce_dict(result_dict)
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return result_dict
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def _read_o_file(cfg_path, name, intern, version, im):
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def _setup_ret_dict(name_list, quarks_list, noffset_list, wf_list, wf2_list):
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internal_ret_dict = {}
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for name in name_list:
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internal_ret_dict[name] = {}
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for quarks in quarks_list:
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internal_ret_dict[name][quarks] = {}
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for off in noffset_list:
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internal_ret_dict[name][quarks][str(off)] = {}
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for w in wf_list:
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internal_ret_dict[name][quarks][str(off)][str(w)] = {}
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for w2 in wf2_list:
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internal_ret_dict[name][quarks][str(off)][str(w)][str(w2)] = []
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internal_ret_dict = benedict(internal_ret_dict, keypath_separator="/")
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ret_key_paths = _get_deep_paths(internal_ret_dict)
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return ret_key_paths, internal_ret_dict
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def _setup_intern_dict(name_list, corr_type_list, quarks_list, noffset_list, wf_list, wf2_list):
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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][str(off)] = {}
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for w in wf_list:
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intern[name]["spec"][quarks][str(off)][str(w)] = {}
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for w2 in wf2_list:
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intern[name]["spec"][quarks][str(off)][str(w)][str(w2)] = {}
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return intern
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def _read_o_file(cfg_path, name, intern, version, im, template):
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file = cfg_path + '/' + name
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return_vals = {}
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return_vals = deepcopy(template)
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return_vals = return_vals.subset(name)[name]
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print(return_vals)
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with open(file) as fp:
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lines = fp.readlines()
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for quarks in intern[name]["spec"].keys():
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return_vals[quarks] = {}
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for off in intern[name]["spec"][quarks].keys():
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return_vals[quarks][off] = {}
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for w in intern[name]["spec"][quarks][off].keys():
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return_vals[quarks][off][w] = {}
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for w2 in intern[name]["spec"][quarks][off][w].keys():
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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[quarks][off][w][w2] = deltas
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for k in _get_deep_paths(return_vals):
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ori_keys = k.split("/")
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quarks = ori_keys[0]
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off = ori_keys[1]
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w = ori_keys[2]
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w2 = ori_keys[3]
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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[quarks][off][w][w2] = deltas
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return return_vals
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@ -468,67 +478,55 @@ def _find_correlator(file_name, version, pattern, b2b, silent=False):
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return start_read, T
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def _read_compact_file(rep_path, cfg_file, intern, im):
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return_vals = {}
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def _read_compact_file(rep_path, cfg_file, intern, im, template):
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return_vals = deepcopy(template)
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with open(rep_path + cfg_file) as fp:
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lines = fp.readlines()
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for name in intern.keys():
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return_vals[name] = {}
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for quarks in intern[name]["spec"].keys():
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return_vals[name][quarks] = {}
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for off in intern[name]["spec"][quarks].keys():
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return_vals[name][quarks][off] = {}
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for w in intern[name]["spec"][quarks][off].keys():
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return_vals[name][quarks][off][w] = {}
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for w2 in intern[name]["spec"][quarks][off][w].keys():
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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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# check, if the correlator is in fact
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# printed completely
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if (start_read + T + 1 > len(lines)):
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raise Exception("EOF before end of correlator data! Maybe " + rep_path + cfg_file + " is corrupted?")
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corr_lines = lines[start_read - 6: start_read + T]
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t_vals = []
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for key in _get_deep_paths(return_vals):
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ori_keys = key.split("/")
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name = ori_keys[0]
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quarks = ori_keys[1]
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off = ori_keys[2]
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w = ori_keys[3]
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w2 = ori_keys[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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# check, if the correlator is in fact
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# printed completely
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if (start_read + T + 1 > len(lines)):
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raise Exception("EOF before end of correlator data! Maybe " + rep_path + cfg_file + " is corrupted?")
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corr_lines = lines[start_read - 6: start_read + T]
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t_vals = []
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if corr_lines[1 - intern[name]["b2b"]].strip() != 'name ' + name:
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raise Exception('Wrong format in file', cfg_file)
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if corr_lines[1 - intern[name]["b2b"]].strip() != 'name ' + name:
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raise Exception('Wrong format in file', cfg_file)
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for k in range(6, T + 6):
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floats = list(map(float, corr_lines[k].split()))
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t_vals.append(floats[-2:][im])
|
||||
return_vals[name][quarks][off][w][w2] = t_vals
|
||||
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, im_list):
|
||||
def _read_compact_rep(path, rep, sub_ls, intern, keys, im_list, template):
|
||||
rep_path = path + '/' + rep + '/'
|
||||
no_cfg = len(sub_ls)
|
||||
|
||||
return_vals = {}
|
||||
for name in intern.keys():
|
||||
return_vals[name] = {}
|
||||
for quarks in intern[name]["spec"].keys():
|
||||
return_vals[name][quarks] = {}
|
||||
for off in intern[name]["spec"][quarks].keys():
|
||||
return_vals[name][quarks][off] = {}
|
||||
for w in intern[name]["spec"][quarks][off].keys():
|
||||
return_vals[name][quarks][off][w] = {}
|
||||
for w2 in intern[name]["spec"][quarks][off][w].keys():
|
||||
deltas = []
|
||||
for t in range(intern[name]["T"]):
|
||||
deltas.append(np.zeros(no_cfg))
|
||||
return_vals[name][quarks][off][w][w2] = deltas
|
||||
|
||||
print(template)
|
||||
return_vals = deepcopy(template)
|
||||
for k in keys:
|
||||
name = k.split("/")[0]
|
||||
deltas = []
|
||||
for t in range(intern[name]["T"]):
|
||||
deltas.append(np.zeros(no_cfg))
|
||||
return_vals[k] = deltas
|
||||
for cfg in range(no_cfg):
|
||||
cfg_file = sub_ls[cfg]
|
||||
cfg_data = _read_compact_file(rep_path, cfg_file, intern, im_list)
|
||||
for name in intern.keys():
|
||||
for quarks in intern[name]["spec"].keys():
|
||||
for off in intern[name]["spec"][quarks].keys():
|
||||
for w in intern[name]["spec"][quarks][off].keys():
|
||||
for w2 in intern[name]["spec"][quarks][off][w].keys():
|
||||
for t in range(intern[name]["T"]):
|
||||
return_vals[name][quarks][off][w][w2][t][cfg] = cfg_data[name][quarks][off][w][w2][t]
|
||||
cfg_data = _read_compact_file(rep_path, cfg_file, intern, im_list, template)
|
||||
for k in keys:
|
||||
name = k.split("/")[0]
|
||||
for t in range(intern[name]["T"]):
|
||||
return_vals[k][t][cfg] = cfg_data[k][t]
|
||||
print(template)
|
||||
return return_vals
|
||||
|
||||
|
||||
|
|
@ -641,3 +639,13 @@ def _reduce_dict(d):
|
|||
if len(list(d.keys())) == 1:
|
||||
ret = d[list(d.keys())[0]]
|
||||
return ret
|
||||
|
||||
|
||||
def _get_deep_paths(f, sep='/'):
|
||||
max_count = max([k.count(sep) for k in f.keypaths()])
|
||||
|
||||
deep_paths = []
|
||||
for k in f.keypaths():
|
||||
if k.count(sep) == max_count:
|
||||
deep_paths.append(k)
|
||||
return deep_paths
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue