/
loaders.py
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/
loaders.py
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""" Functions for loading GST objects from text files."""
#***************************************************************************************************
# Copyright 2015, 2019 National Technology & Engineering Solutions of Sandia, LLC (NTESS).
# Under the terms of Contract DE-NA0003525 with NTESS, the U.S. Government retains certain rights
# in this software.
# Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except
# in compliance with the License. You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0 or in the LICENSE file in the root pyGSTi directory.
#***************************************************************************************************
import os as _os
import pathlib as _pathlib
from . import stdinput as _stdinput
from .. import objects as _objs
from . import metadir as _metadir
def load_dataset(filename, cache=False, collisionAction="aggregate",
recordZeroCnts=True, ignoreZeroCountLines=True,
withTimes="auto", verbosity=1):
"""
Load a DataSet from a file. First tries to load file as a
saved DataSet object, then as a standard text-formatted DataSet.
Parameters
----------
filename : string
The name of the file
cache : bool, optional
When set to True, a pickle file with the name filename + ".cache"
is searched for and loaded instead of filename if it exists
and is newer than filename. If no cache file exists or one
exists but it is older than filename, a cache file will be
written after loading from filename.
collisionAction : {"aggregate", "keepseparate"}
Specifies how duplicate operation sequences should be handled. "aggregate"
adds duplicate-sequence counts, whereas "keepseparate" tags duplicate-
sequence data with by appending a final "#<number>" operation label to the
duplicated gate sequence.
recordZeroCnts : bool, optional
Whether zero-counts are actually recorded (stored) in the returned
DataSet. If False, then zero counts are ignored, except for potentially
registering new outcome labels. When reading from a cache file
(using `cache==True`) this argument is ignored: the presence of zero-
counts is dictated by the value of `recordZeroCnts` when the cache file
was created.
ignoreZeroCountLines : bool, optional
Whether circuits for which there are no counts should be ignored
(i.e. omitted from the DataSet) or not.
withTimes : bool or "auto", optional
Whether to the time-stamped data format should be read in. If
"auto", then the time-stamped format is allowed but not required on a
per-circuit basis (so the dataset can contain both formats). Typically
you only need to set this to False when reading in a template file.
verbosity : int, optional
If zero, no output is shown. If greater than zero,
loading progress is shown.
Returns
-------
DataSet
"""
printer = _objs.VerbosityPrinter.build_printer(verbosity)
try:
# a saved Dataset object is ok
ds = _objs.DataSet(fileToLoadFrom=filename)
except:
#Parser functions don't take a VerbosityPrinter yet, and so
# always output to stdout (TODO)
bToStdout = (printer.verbosity > 0 and printer.filename is None)
if cache:
#bReadCache = False
cache_filename = filename + ".cache"
if _os.path.exists(cache_filename) and \
_os.path.getmtime(filename) < _os.path.getmtime(cache_filename):
try:
printer.log("Loading from cache file: %s" % cache_filename)
ds = _objs.DataSet(fileToLoadFrom=cache_filename)
return ds
except: print("WARNING: Failed to load from cache file") # pragma: no cover
else:
printer.log("Cache file not found or is tool old -- one will"
+ "be created after loading is completed")
# otherwise must use standard dataset file format
parser = _stdinput.StdInputParser()
ds = parser.parse_datafile(filename, bToStdout,
collisionAction=collisionAction,
recordZeroCnts=recordZeroCnts,
ignoreZeroCountLines=ignoreZeroCountLines,
withTimes=withTimes)
printer.log("Writing cache file (to speed future loads): %s"
% cache_filename)
ds.save(cache_filename)
else:
# otherwise must use standard dataset file format
parser = _stdinput.StdInputParser()
ds = parser.parse_datafile(filename, bToStdout,
collisionAction=collisionAction,
recordZeroCnts=recordZeroCnts,
ignoreZeroCountLines=ignoreZeroCountLines,
withTimes=withTimes)
return ds
def load_multidataset(filename, cache=False, collisionAction="aggregate",
recordZeroCnts=True, verbosity=1):
"""
Load a MultiDataSet from a file. First tries to load file as a
saved MultiDataSet object, then as a standard text-formatted MultiDataSet.
Parameters
----------
filename : string
The name of the file
cache : bool, optional
When set to True, a pickle file with the name filename + ".cache"
is searched for and loaded instead of filename if it exists
and is newer than filename. If no cache file exists or one
exists but it is older than filename, a cache file will be
written after loading from filename.
collisionAction : {"aggregate", "keepseparate"}
Specifies how duplicate operation sequences should be handled. "aggregate"
adds duplicate-sequence counts, whereas "keepseparate" tags duplicate-
sequence data with by appending a final "#<number>" operation label to the
duplicated gate sequence.
recordZeroCnts : bool, optional
Whether zero-counts are actually recorded (stored) in the returned
MultiDataSet. If False, then zero counts are ignored, except for
potentially registering new outcome labels. When reading from a cache
file (using `cache==True`) this argument is ignored: the presence of
zero-counts is dictated by the value of `recordZeroCnts` when the cache
file was created.
verbosity : int, optional
If zero, no output is shown. If greater than zero,
loading progress is shown.
Returns
-------
MultiDataSet
"""
printer = _objs.VerbosityPrinter.build_printer(verbosity)
try:
# a saved MultiDataset object is ok
mds = _objs.MultiDataSet(fileToLoadFrom=filename)
except:
#Parser functions don't take a VerbosityPrinter yet, and so
# always output to stdout (TODO)
bToStdout = (printer.verbosity > 0 and printer.filename is None)
if cache:
# bReadCache = False
cache_filename = filename + ".cache"
if _os.path.exists(cache_filename) and \
_os.path.getmtime(filename) < _os.path.getmtime(cache_filename):
try:
printer.log("Loading from cache file: %s" % cache_filename)
mds = _objs.MultiDataSet(fileToLoadFrom=cache_filename)
return mds
except: print("WARNING: Failed to load from cache file") # pragma: no cover
else:
printer.log("Cache file not found or is too old -- one will be"
+ "created after loading is completed")
# otherwise must use standard dataset file format
parser = _stdinput.StdInputParser()
mds = parser.parse_multidatafile(filename, bToStdout,
collisionAction=collisionAction,
recordZeroCnts=recordZeroCnts)
printer.log("Writing cache file (to speed future loads): %s"
% cache_filename)
mds.save(cache_filename)
else:
# otherwise must use standard dataset file format
parser = _stdinput.StdInputParser()
mds = parser.parse_multidatafile(filename, bToStdout,
collisionAction=collisionAction,
recordZeroCnts=recordZeroCnts)
return mds
def load_tddataset(filename, cache=False, recordZeroCnts=True):
"""
Load time-dependent (time-stamped) data as a DataSet.
Parameters
----------
filename : string
The name of the file
cache : bool, optional
Reserved to perform caching similar to `load_dataset`. Currently
this argument doesn't do anything.
recordZeroCnts : bool, optional
Whether zero-counts are actually recorded (stored) in the returned
DataSet. If False, then zero counts are ignored, except for
potentially registering new outcome labels.
Returns
-------
DataSet
"""
parser = _stdinput.StdInputParser()
tdds = parser.parse_tddatafile(filename, recordZeroCnts=recordZeroCnts)
return tdds
def load_model(filename):
"""
Load a Model from a file, formatted using the
standard text-format for models.
Parameters
----------
filename : string
The name of the file
Returns
-------
Model
"""
return _stdinput.read_model(filename)
def load_circuit_dict(filename):
"""
Load a operation sequence dictionary from a file, formatted
using the standard text-format.
Parameters
----------
filename : string
The name of the file.
Returns
-------
Dictionary with keys = operation sequence labels and
values = Circuit objects.
"""
std = _stdinput.StdInputParser()
return std.parse_dictfile(filename)
def load_circuit_list(filename, readRawStrings=False, line_labels='auto', num_lines=None):
"""
Load a operation sequence list from a file, formatted
using the standard text-format.
Parameters
----------
filename : string
The name of the file
readRawStrings : boolean
If True, operation sequences are not converted
to tuples of operation labels.
line_labels : iterable, optional
The (string valued) line labels used to initialize :class:`Circuit`
objects when line label information is absent from the one-line text
representation contained in `filename`. If `'auto'`, then line labels
are taken to be the list of all state-space labels present in the
circuit's layers. If there are no such labels then the special value
`'*'` is used as a single line label.
num_lines : int, optional
Specify this instead of `line_labels` to set the latter to the
integers between 0 and `num_lines-1`.
Returns
-------
list of Circuit objects
"""
if readRawStrings:
rawList = []
with open(str(filename), 'r') as circuitlist:
for line in circuitlist:
if len(line.strip()) == 0: continue
if len(line) == 0 or line[0] == '#': continue
rawList.append(line.strip())
return rawList
else:
std = _stdinput.StdInputParser()
return std.parse_stringfile(filename, line_labels, num_lines)
def load_protocol_from_dir(dirname, comm=None):
"""
Load a :class:`Protocol` from a directory on disk.
Parameters
----------
dirname : string
Directory name.
comm : mpi4py.MPI.Comm, optional
When not ``None``, an MPI communicator used to synchronize file access.
Returns
-------
Protocol
"""
dirname = _pathlib.Path(dirname)
return _metadir.cls_from_meta_json(dirname).from_dir(dirname)
def load_edesign_from_dir(dirname, comm=None):
"""
Load a :class:`ExperimentDesign` from a directory on disk.
Parameters
----------
dirname : string
Directory name.
comm : mpi4py.MPI.Comm, optional
When not ``None``, an MPI communicator used to synchronize file access.
Returns
-------
ExperimentDesign
"""
dirname = _pathlib.Path(dirname)
return _metadir.cls_from_meta_json(dirname / 'edesign').from_dir(dirname)
def load_data_from_dir(dirname, comm=None):
"""
Load a :class:`ProtocolData` from a directory on disk.
Parameters
----------
dirname : string
Directory name.
comm : mpi4py.MPI.Comm, optional
When not ``None``, an MPI communicator used to synchronize file access.
Returns
-------
ProtocolData
"""
dirname = _pathlib.Path(dirname)
return _metadir.cls_from_meta_json(dirname / 'data').from_dir(dirname)
def load_results_from_dir(dirname, name=None, preloaded_data=None, comm=None):
"""
Load a :class:`ProtocolResults` or :class:`ProtocolsResultsDir` from a
directory on disk (depending on whether `name` is given).
Parameters
----------
dirname : string
Directory name. This should be a "base" directory, containing
subdirectories like "edesign", "data", and "results"
name : string or None
The 'name' of a particular :class:`ProtocolResults` object, which
is a sub-directory beneath `dirname/results/`. If None, then *all*
the results (all names) at the given base-directory are loaded and
returned as a :class:`ProtocolResultsDir` object.
preloaded_data : ProtocolData, optional
The data object belonging to the to-be-loaded results, in cases
when this has been loaded already (only use this if you know what
you're doing).
comm : mpi4py.MPI.Comm, optional
When not ``None``, an MPI communicator used to synchronize file access.
Returns
-------
ProtocolResults or ProtocolResultsDir
"""
from ..protocols import ProtocolResultsDir as _ProtocolResultsDir
dirname = _pathlib.Path(dirname)
results_dir = dirname / 'results'
if name is None: # then it's a directory object
cls = _metadir.cls_from_meta_json(results_dir) if (results_dir / 'meta.json').exists() \
else _ProtocolResultsDir # default if no meta.json (if only a results obj has been written inside dir)
return cls.from_dir(dirname)
else: # it's a ProtocolResults object
return _metadir.cls_from_meta_json(results_dir / name).from_dir(dirname, name, preloaded_data)