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annotate read_ms5_xsf
This commit is contained in:
Justus Kuhlmann
parent
f44b19c9d1
commit
96cdec46e2
1 changed files with 79 additions and 92 deletions
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@ -10,10 +10,19 @@ from ..correlators import Corr
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from .misc import fit_t0
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from .utils import sort_names
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from io import BufferedReader
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from typing import Optional, Union
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from typing import Optional, Union, TypedDict, Unpack
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def read_rwms(path: str, prefix: str, version: str='2.0', names: Optional[list[str]]=None, **kwargs) -> list[Obs]:
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class rwms_kwargs(TypedDict):
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files: list[str]
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postfix: str
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r_start: list[Union[int]]
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r_stop: list[Union[int]]
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r_step: int
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def read_rwms(path: str, prefix: str, version: str='2.0', names: Optional[list[str]]=None, **kwargs: Unpack[rwms_kwargs]) -> list[Obs]:
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"""Read rwms format from given folder structure. Returns a list of length nrw
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Parameters
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@ -27,7 +36,7 @@ def read_rwms(path: str, prefix: str, version: str='2.0', names: Optional[list[s
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version : str
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version of openQCD, default 2.0
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names : list
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list of names that is assigned to the data according according
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list of names that is assigned to the data according
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to the order in the file list. Use careful, if you do not provide file names!
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r_start : list
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list which contains the first config to be read for each replicum
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@ -53,39 +62,24 @@ def read_rwms(path: str, prefix: str, version: str='2.0', names: Optional[list[s
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if version not in known_oqcd_versions:
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raise Exception('Unknown openQCD version defined!')
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print("Working with openQCD version " + version)
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if 'postfix' in kwargs:
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postfix = kwargs.get('postfix')
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else:
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postfix = ''
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postfix: str = kwargs.get('postfix', '')
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if 'files' in kwargs:
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known_files = kwargs.get('files')
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else:
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known_files = []
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known_files: list[str] = kwargs.get('files', [])
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ls = _find_files(path, prefix, postfix, 'dat', known_files=known_files)
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replica = len(ls)
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if 'r_start' in kwargs:
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r_start = kwargs.get('r_start')
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if len(r_start) != replica:
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raise Exception('r_start does not match number of replicas')
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r_start = [o if o else None for o in r_start]
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else:
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r_start = [None] * replica
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r_start: list[Union[int, None]] = kwargs.get('r_start', [None] * replica)
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if len(r_start) != replica:
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raise Exception('r_start does not match number of replicas')
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if 'r_stop' in kwargs:
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r_stop = kwargs.get('r_stop')
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if len(r_stop) != replica:
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raise Exception('r_stop does not match number of replicas')
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else:
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r_stop = [None] * replica
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r_stop: list[Union[int, None]] = kwargs.get('r_stop', [None] * replica)
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if len(r_stop) != replica:
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raise Exception('r_stop does not match number of replicas')
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if 'r_step' in kwargs:
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r_step = kwargs.get('r_step')
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else:
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r_step = 1
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r_step: int = kwargs.get('r_step', 1)
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print('Read reweighting factors from', prefix[:-1], ',',
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replica, 'replica', end='')
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@ -110,14 +104,14 @@ def read_rwms(path: str, prefix: str, version: str='2.0', names: Optional[list[s
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print_err = 1
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print()
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deltas = []
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deltas: list[list[float]] = []
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configlist = []
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configlist: list[list[int]] = []
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r_start_index = []
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r_stop_index = []
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for rep in range(replica):
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tmp_array = []
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tmp_array: list[list] = []
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with open(path + '/' + ls[rep], 'rb') as fp:
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t = fp.read(4) # number of reweighting factors
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@ -144,7 +138,7 @@ def read_rwms(path: str, prefix: str, version: str='2.0', names: Optional[list[s
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for i in range(nrw):
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nfct.append(1)
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nsrc = []
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nsrc: list[int] = []
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for i in range(nrw):
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t = fp.read(4)
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nsrc.append(struct.unpack('i', t)[0])
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@ -161,11 +155,12 @@ def read_rwms(path: str, prefix: str, version: str='2.0', names: Optional[list[s
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configlist[-1].append(config_no)
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for i in range(nrw):
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if (version == '2.0'):
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tmpd: dict = _read_array_openQCD2(fp)
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tmpd = _read_array_openQCD2(fp)
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tmpd = _read_array_openQCD2(fp)
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tmp_rw = tmpd['arr']
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tmp_rw: list[float] = tmpd['arr']
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tmp_n: list[int] = tmpd['n']
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tmp_nfct = 1.0
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for j in range(tmpd['n'][0]):
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for j in range(tmp_n[0]):
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tmp_nfct *= np.mean(np.exp(-np.asarray(tmp_rw[j])))
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if print_err:
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print(config_no, i, j,
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@ -179,7 +174,7 @@ def read_rwms(path: str, prefix: str, version: str='2.0', names: Optional[list[s
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for j in range(nfct[i]):
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t = fp.read(8 * nsrc[i])
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t = fp.read(8 * nsrc[i])
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tmp_rw = struct.unpack('d' * nsrc[i], t)
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tmp_rw: list[float] = struct.unpack('d' * nsrc[i], t)
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tmp_nfct *= np.mean(np.exp(-np.asarray(tmp_rw)))
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if print_err:
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print(config_no, i, j,
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@ -232,7 +227,7 @@ def read_rwms(path: str, prefix: str, version: str='2.0', names: Optional[list[s
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return result
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def _extract_flowed_energy_density(path: str, prefix: str, dtr_read: int, xmin: int, spatial_extent: int, postfix: str='ms', **kwargs) -> dict[float, Obs]:
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def _extract_flowed_energy_density(path: str, prefix: str, dtr_read: int, xmin: int, spatial_extent: int, postfix: str='ms', **kwargs: Unpack[rwms_kwargs]) -> dict[float, Obs]:
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"""Extract a dictionary with the flowed Yang-Mills action density from given .ms.dat files.
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Returns a dictionary with Obs as values and flow times as keys.
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@ -319,18 +314,18 @@ def _extract_flowed_energy_density(path: str, prefix: str, dtr_read: int, xmin:
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print('Extract flowed Yang-Mills action density from', prefix, ',', replica, 'replica')
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if 'names' in kwargs:
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rep_names = kwargs.get('names')
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else:
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rep_names: list[str] = kwargs.get('names', [])
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if len(rep_names) == 0:
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rep_names = []
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for entry in ls:
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truncated_entry = entry.split('.')[0]
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idx = truncated_entry.index('r')
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rep_names.append(truncated_entry[:idx] + '|' + truncated_entry[idx:])
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Ysum = []
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Ysum: list = []
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configlist = []
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configlist: list[list[int]] = []
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r_start_index = []
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r_stop_index = []
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@ -413,7 +408,7 @@ def _extract_flowed_energy_density(path: str, prefix: str, dtr_read: int, xmin:
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idl = [range(configlist[rep][r_start_index[rep]], configlist[rep][r_stop_index[rep]] + 1, r_step) for rep in range(replica)]
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E_dict = {}
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for n in range(nn + 1):
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samples = []
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samples: list[list[float]] = []
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for nrep, rep in enumerate(Ysum):
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samples.append([])
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for cnfg in rep:
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@ -599,7 +594,7 @@ def _parse_array_openQCD2(d: int, n: tuple[int, int], size: int, wa: Union[tuple
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return arr
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def _find_files(path: str, prefix: str, postfix: str, ext: str, known_files: Union[str, list[str]]=[]) -> list[str]:
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def _find_files(path: str, prefix: str, postfix: str, ext: str, known_files: list[str]=[]) -> list[str]:
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found = []
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files = []
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@ -1146,7 +1141,7 @@ def read_qtop_sector(path: str, prefix: str, c: float, target: int=0, **kwargs)
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return qtop_projection(qtop, target=target)
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def read_ms5_xsf(path: str, prefix: str, qc: str, corr: str, sep: str="r", **kwargs) -> Corr:
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def read_ms5_xsf(path: str, prefix: str, qc: str, corr: str, sep: str="r", **kwargs) -> Union[Corr, CObs]:
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"""
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Read data from files in the specified directory with the specified prefix and quark combination extension, and return a `Corr` object containing the data.
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@ -1188,9 +1183,7 @@ def read_ms5_xsf(path: str, prefix: str, qc: str, corr: str, sep: str="r", **kwa
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If there is an error unpacking binary data.
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"""
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# found = []
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files = []
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names = []
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# test if the input is correct
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if qc not in ['dd', 'ud', 'du', 'uu']:
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@ -1199,15 +1192,13 @@ def read_ms5_xsf(path: str, prefix: str, qc: str, corr: str, sep: str="r", **kwa
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if corr not in ["gS", "gP", "gA", "gV", "gVt", "lA", "lV", "lVt", "lT", "lTt", "g1", "l1"]:
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raise Exception("Unknown correlator!")
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if "files" in kwargs:
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known_files = kwargs.get("files")
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else:
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known_files = []
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known_files: list[str] = kwargs.get("files", [])
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expected_idl = kwargs.get('idl', [])
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files = _find_files(path, prefix, "ms5_xsf_" + qc, "dat", known_files=known_files)
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if "names" in kwargs:
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names = kwargs.get("names")
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else:
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names: list[str] = kwargs.get("names", [])
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if len(names) == 0:
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for f in files:
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if not sep == "":
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se = f.split(".")[0]
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@ -1216,31 +1207,30 @@ def read_ms5_xsf(path: str, prefix: str, qc: str, corr: str, sep: str="r", **kwa
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names.append(se.split(sep)[0] + "|r" + se.split(sep)[1])
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else:
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names.append(prefix)
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if 'idl' in kwargs:
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expected_idl = kwargs.get('idl')
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names = sorted(names)
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files = sorted(files)
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cnfgs = []
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realsamples = []
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imagsamples = []
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cnfgs: list[list[int]] = []
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realsamples: list[list[list[float]]] = []
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imagsamples: list[list[list[float]]] = []
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repnum = 0
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for file in files:
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with open(path + "/" + file, "rb") as fp:
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t = fp.read(8)
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kappa = struct.unpack('d', t)[0]
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t = fp.read(8)
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csw = struct.unpack('d', t)[0]
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t = fp.read(8)
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dF = struct.unpack('d', t)[0]
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t = fp.read(8)
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zF = struct.unpack('d', t)[0]
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tmp_bytes = fp.read(8)
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kappa: float = struct.unpack('d', tmp_bytes)[0]
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tmp_bytes = fp.read(8)
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csw: float = struct.unpack('d', tmp_bytes)[0]
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tmp_bytes = fp.read(8)
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dF: float = struct.unpack('d', tmp_bytes)[0]
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tmp_bytes = fp.read(8)
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zF: float = struct.unpack('d', tmp_bytes)[0]
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t = fp.read(4)
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tmax = struct.unpack('i', t)[0]
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t = fp.read(4)
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bnd = struct.unpack('i', t)[0]
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tmp_bytes = fp.read(4)
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tmax: int = struct.unpack('i', tmp_bytes)[0]
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tmp_bytes = fp.read(4)
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bnd: int = struct.unpack('i', tmp_bytes)[0]
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placesBI = ["gS", "gP",
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"gA", "gV",
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@ -1252,22 +1242,22 @@ def read_ms5_xsf(path: str, prefix: str, qc: str, corr: str, sep: str="r", **kwa
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# the chunks have the following structure:
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# confignumber, 10x timedependent complex correlators as doubles, 2x timeindependent complex correlators as doubles
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chunksize = 4 + (8 * 2 * tmax * 10) + (8 * 2 * 2)
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packstr = '=i' + ('d' * 2 * tmax * 10) + ('d' * 2 * 2)
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chunksize = struct.calcsize(packstr)
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cnfgs.append([])
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realsamples.append([])
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imagsamples.append([])
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for t in range(tmax):
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for time in range(tmax):
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realsamples[repnum].append([])
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imagsamples[repnum].append([])
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if 'idl' in kwargs:
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left_idl = set(expected_idl[repnum])
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while True:
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cnfgt = fp.read(chunksize)
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if not cnfgt:
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cnfg_bytes = fp.read(chunksize)
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if not cnfg_bytes:
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break
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asascii = struct.unpack(packstr, cnfgt)
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cnfg = asascii[0]
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asascii = struct.unpack(packstr, cnfg_bytes)
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cnfg: int = asascii[0]
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idl_wanted = True
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if 'idl' in kwargs:
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idl_wanted = (cnfg in expected_idl[repnum])
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@ -1280,24 +1270,21 @@ def read_ms5_xsf(path: str, prefix: str, qc: str, corr: str, sep: str="r", **kwa
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else:
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tmpcorr = asascii[1 + 2 * tmax * len(placesBI) + 2 * placesBB.index(corr):1 + 2 * tmax * len(placesBI) + 2 * placesBB.index(corr) + 2]
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corrres = [[], []]
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corrres: list[list[float]] = [[], []]
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for i in range(len(tmpcorr)):
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corrres[i % 2].append(tmpcorr[i])
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for t in range(int(len(tmpcorr) / 2)):
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realsamples[repnum][t].append(corrres[0][t])
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for t in range(int(len(tmpcorr) / 2)):
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imagsamples[repnum][t].append(corrres[1][t])
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if 'idl' in kwargs:
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left_idl = list(left_idl)
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if expected_idl[repnum] == left_idl:
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raise ValueError("None of the idls searched for were found in replikum of file " + file)
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elif len(left_idl) > 0:
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warnings.warn('Could not find idls ' + str(left_idl) + ' in replikum of file ' + file, UserWarning)
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for time in range(int(len(tmpcorr) / 2)):
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realsamples[repnum][time].append(corrres[0][time])
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for time in range(int(len(tmpcorr) / 2)):
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imagsamples[repnum][time].append(corrres[1][time])
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if len(expected_idl) > 0:
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left_idl_list = list(left_idl)
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if expected_idl[repnum] == left_idl_list:
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raise ValueError("None of the idls searched for were found in replicum of file " + file)
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elif len(left_idl_list) > 0:
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warnings.warn('Could not find idls ' + str(left_idl) + ' in replicum of file ' + file, UserWarning)
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repnum += 1
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s = "Read correlator " + corr + " from " + str(repnum) + " replika with idls" + str(realsamples[0][t])
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for rep in range(1, repnum):
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s += ", " + str(realsamples[rep][t])
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print(s)
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print("Read correlator " + corr + " from " + str(repnum) + " replica with idls")
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print("Asserted run parameters:\n T:", tmax, "kappa:", kappa, "csw:", csw, "dF:", dF, "zF:", zF, "bnd:", bnd)
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# we have the data now... but we need to re format the whole thing and put it into Corr objects.
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