def analysis_estimation(
self, worker: Worker,
options: gui.estimation.Options) -> EstimationResult:
CHUNK_SIZE = 64
with Core() as core:
worker.interrupt = lambda: core.shutdown(
) # register interrupt hook
rows: List[estimation_result.PackedResponse] = []
worker.set_work_size(len(self.subjects))
for i in range(0, len(self.subjects), CHUNK_SIZE):
request = estimation_result.Request(
subjects=self.subjects[i:i + CHUNK_SIZE],
models=options.models,
disable_parallelism=options.disable_parallelism,
)
responses = core.call('estimation', estimation_result.RequestC,
estimation_result.PackedResponsesC,
request)
rows.extend(responses)
worker.set_progress(len(rows))
ds = EstimationResult(
self.name + ' (model est.)',
self.alternatives,
)
ds.subjects = rows
return ds
def load_from_file(self, worker: Worker, fname: str) -> None:
with bz2.open(fname, 'rb') as f:
f = cast(FileIn, f) # assert we're doing input
sig = f.read(len(PREST_SIGNATURE))
if sig != PREST_SIGNATURE:
raise PersistenceError('not a Prest workspace file')
version = intC.decode(f)
if version >= 3:
prest_version = strC.decode(f)
else:
prest_version = None # too old
if version != FILE_FORMAT_VERSION:
message = 'incompatible PWF version: expected {0}, received {1}'.format(
FILE_FORMAT_VERSION,
version,
)
if prest_version:
message += ' (saved by {0})'.format(prest_version)
raise PersistenceError(message)
work_size = intC.decode(f)
worker.set_work_size(work_size)
datasets = listCP(DatasetCP).decode(worker, f)
# assign to self only once everything's gone all right
self.datasets = datasets
def analysis_integrity_check(self, worker: Worker,
_config: None) -> dataset.AnalysisResult:
worker.set_work_size(len(self.subjects))
subjects: List[dataset.integrity_check.Subject] = []
with Core() as core:
worker.interrupt = lambda: core.shutdown()
for i, subject in enumerate(self.subjects):
subj_issues = core.call('integrity-check', PackedSubjectC,
dataset.integrity_check.SubjectC,
subject)
if subj_issues.issues:
subjects.append(subj_issues)
worker.set_progress(i + 1)
if subjects:
ds = dataset.integrity_check.IntegrityCheck(
self.name + ' (integrity check)', self.alternatives)
ds.subjects = subjects
return ds
else:
return dataset.ShowMessageBox(
type=dataset.MessageBoxType.INFORMATION,
title='Integrity check',
message='No integrity issues found.',
)
def analysis_merge_choices(self, worker: Worker,
_config: None) -> 'ExperimentalData':
subjects: List[PackedSubject] = []
observ_count: int = 0
# we group by pairs (menu, default)
MenuDef = Tuple[FrozenSet[int], Optional[int]]
worker.set_work_size(len(self.subjects))
for i, subject_packed in enumerate(self.subjects):
subject = Subject.unpack(subject_packed)
choices: List[ChoiceRow] = []
menu_idx: Dict[MenuDef, int] = {}
deferrals_seen: Set[MenuDef] = set()
for cr in subject.choices:
# deferrals are kept separately
if not cr.choice:
if (cr.menu, cr.default) in deferrals_seen:
# this deferral has already been seen, just skip it
continue
else:
# this is the first time we've seen deferral at this menu
# add that deferral to the output
# but don't add it to the index
choices.append(cr)
deferrals_seen.add((cr.menu, cr.default))
observ_count += 1
continue
idx = menu_idx.get((cr.menu, cr.default))
if idx is None:
# not there yet
menu_idx[cr.menu, cr.default] = len(choices)
choices.append(cr)
observ_count += 1
else:
# already there, expand the choice
choices[idx] = ChoiceRow(
menu=cr.menu,
default=cr.default,
choice=cr.choice | choices[idx].choice,
)
subjects.append(
Subject(
name=subject.name,
alternatives=subject.alternatives,
choices=choices,
).pack())
worker.set_progress(i + 1)
ds = ExperimentalData(name=self.name + ' (merged)',
alternatives=self.alternatives)
ds.subjects = subjects
ds.observ_count = observ_count
return ds
def save_to_file(self, worker: Worker, fname: str) -> None:
with bz2.open(fname, 'wb') as f:
f = cast(FileOut, f) # assert we're doing output
f.write(PREST_SIGNATURE)
intC.encode(f, FILE_FORMAT_VERSION) # version
strC.encode(f, branding.VERSION)
work_size = listCP(DatasetCP).get_size(self.datasets)
intC.encode(f, work_size)
worker.set_work_size(work_size)
listCP(DatasetCP).encode(worker, f, self.datasets)
def analysis_summary_stats(self, worker: Worker,
_config: None) -> ExperimentStats:
subjects = []
worker.set_work_size(len(self.subjects))
with Core() as core:
worker.interrupt = lambda: core.shutdown()
for i, subject in enumerate(self.subjects):
subjects.append(
core.call("summary", PackedSubjectC,
dataset.experiment_stats.SubjectC, subject))
worker.set_progress(i + 1)
ds = ExperimentStats(
name=self.name + ' (info)',
alternatives=self.alternatives,
)
ds.subjects = subjects
return ds
def analysis_tuple_intrans_alts(self, worker: Worker,
_config: None) -> TupleIntransAlts:
subjects = []
worker.set_work_size(len(self.subjects))
with Core() as core:
worker.interrupt = lambda: core.shutdown()
for i, subject in enumerate(self.subjects):
subjects.append(
core.call(
'tuple-intrans-alts',
PackedSubjectC,
dataset.tuple_intrans_alts.SubjectC,
subject,
))
worker.set_progress(i + 1)
ds = TupleIntransAlts(self.name + ' (inconsistent alternative tuples)',
self.alternatives)
ds.subjects = subjects
return ds
def analysis_consistency(self, worker: Worker,
_config: None) -> ConsistencyResult:
with Core() as core:
worker.interrupt = lambda: core.shutdown() # interrupt hook
rows = []
worker.set_work_size(len(self.subjects))
for i, subject in enumerate(self.subjects):
response = core.call('consistency', PackedSubjectC,
dataset.consistency_result.SubjectRawC,
subject)
rows.append(response)
worker.set_progress(i + 1)
ds = ConsistencyResult(
self.name + ' (consistency)',
self.alternatives,
)
ds.load_from_core(rows)
return ds
def analysis_simulation(
self, worker: Worker,
options: 'gui.copycat_simulation.Options') -> 'ExperimentalData':
subjects: List[PackedSubject] = []
with Core() as core:
worker.interrupt = lambda: core.shutdown(
) # register interrupt hook
worker.set_work_size(len(self.subjects) * options.multiplicity)
position = 0
for subject_packed in self.subjects:
for j in range(options.multiplicity):
response = simulation.run(
core,
simulation.Request(
name='random%d' % (j + 1),
alternatives=self.
alternatives, # we don't use subject.alternatives here
gen_menus=simulation.GenMenus(
generator=simulation.Copycat(subject_packed),
defaults=False, # this will be ignored, anyway
),
gen_choices=options.gen_choices,
preserve_deferrals=options.preserve_deferrals,
))
subjects.append(response.subject_packed)
position += 1
if position % 1024 == 0:
worker.set_progress(position)
ds = ExperimentalData(name=options.name,
alternatives=self.alternatives)
ds.subjects = subjects
ds.observ_count = options.multiplicity * self.observ_count
return ds
def export(self, fname: str, fformat: str, variant: ExportVariant,
worker: Worker) -> None:
worker.set_work_size(variant.size)
position = 0
if '*.csv' in fformat:
with open(fname, 'w') as f:
# Python's CSV module and line endings is a mess.
#
# Opening the file in binary mode doesn't work (writerow() fails).
# In text mode, you get \r\r\n on Windows.
#
# Hence we force the line terminator here to be '\n', on all platforms
# and leave the line ending translation to the underlying /file/ layer.
#
w = csv.writer(f, quoting=csv.QUOTE_ALL, lineterminator='\n')
w.writerow(variant.column_names)
for row in variant.get_rows():
if row:
w.writerow(row)
else:
# progress
position += 1
worker.set_progress(position)
elif '*.xlsx' in fformat:
wb = openpyxl.Workbook()
wb.properties.creator = branding.PREST_VERSION
ws = wb.active
ws.append(variant.column_names)
for row in variant.get_rows():
if row:
ws.append(row)
else:
# progress
position += 1
worker.set_progress(position)
# autosize columns
# who knows what the units are but it approximately fits
# furthermore, we fudge the numbers by 1 unit because that looks better
for column_number, column_cells in enumerate(ws.columns, start=1):
length = max(
(len(str(cell.value or '')) for cell in column_cells),
default=5) + 1
if length < 4:
length = 4
ws.column_dimensions[openpyxl.utils.cell.get_column_letter(
column_number)].width = length
wb.save(fname)
else:
raise Exception('unknown file export format: %s' % fformat)
def analysis_consistency(self, worker : Worker, _config : None) -> BudgetaryConsistency:
with Core() as core:
worker.interrupt = lambda: core.shutdown() # interrupt hook
rows = []
worker.set_work_size(len(self.subjects))
for i, subject in enumerate(self.subjects):
response = core.call(
'budgetary-consistency',
SubjectC,
dataset.budgetary_consistency.SubjectC,
subject
)
rows.append(response)
worker.set_progress(i+1)
ds = BudgetaryConsistency(
self.name + ' (consistency)',
self.alternatives,
rows,
)
return ds
def decode(worker: Worker, f: FileIn) -> Any:
result = dec(f)
worker.step()
return result
def encode(worker: Worker, f: FileOut, x: Any) -> None:
enc(f, x)
worker.step()