def jobs_tables_by_algo_rows_sample_groups(context, samples_groups, tables):
source_descs = comp_store(Stats.all_descriptions())
# Crate a new store, add the key "group"
allstats = StoreResults()
for id_group, samples in samples_groups.items():
for key, value in samples.items():
nkey = dict(id_group=id_group, **key)
allstats[nkey] = value
for id_statstable, stats in tables.items():
for id_algo, samples in allstats.groups_by_field_value('id_algo'):
job_id = 'byalgo-%s-%s' % (id_algo, id_statstable)
r = context.comp(table_by_rows,
"byalgo-rows-sample-groups-%s-%s" % (id_algo, id_statstable),
samples=samples,
rows_field='id_group', # rows = tc
cols_fields=stats, # which statistics for each col
source_descs=source_descs,
job_id=job_id)
report_attrs = dict(id_statstable=id_statstable)
report_attrs.update(samples.fields_with_unique_values())
assert report_attrs['id_algo'] == id_algo
context.add_report(r, 'byalgo-rows-sample-groups', **report_attrs)
def jobs_tables_by_sample_groups(context, samples_groups, tables):
source_descs = comp_store(Stats.all_descriptions())
print tables
# Tables grouping by algorithm
for g, s in product(samples_groups.items(), tables.items()):
id_sample_group, samples = g
id_statstable, stats = s
r = context.comp(
table_by_rows,
"bysamplegroups-%s-%s" %
(sanitize(id_sample_group), id_statstable),
samples=samples,
rows_field='id_algo', # group by algorithm
cols_fields=stats, # which statistics for each col
source_descs=source_descs)
report_attrs = dict(id_sample_group=id_sample_group,
id_stats_table=id_statstable)
# print len(samples)
warnings.warn('not sure what to do')
# report_attrs.update(samples.fields_with_unique_values())
# print report_attrs
context.add_report(r, 'bysamplegroups-%s' % id_statstable,
**report_attrs)
def jobs_tables_by_algo_rows_sample_groups(context, samples_groups, tables):
source_descs = comp_store(Stats.all_descriptions())
# Crate a new store, add the key "group"
allstats = StoreResults()
for id_group, samples in samples_groups.items():
for key, value in samples.items():
nkey = dict(id_group=id_group, **key)
allstats[nkey] = value
for id_statstable, stats in tables.items():
for id_algo, samples in allstats.groups_by_field_value('id_algo'):
job_id = 'byalgo-%s-%s' % (id_algo, id_statstable)
r = context.comp(
table_by_rows,
"byalgo-rows-sample-groups-%s-%s" % (id_algo, id_statstable),
samples=samples,
rows_field='id_group', # rows = tc
cols_fields=stats, # which statistics for each col
source_descs=source_descs,
job_id=job_id)
report_attrs = dict(id_statstable=id_statstable)
report_attrs.update(samples.fields_with_unique_values())
assert report_attrs['id_algo'] == id_algo
context.add_report(r, 'byalgo-rows-sample-groups', **report_attrs)
def jobs_tables_by_sample_rows_algo(context, allstats, tables):
source_descs = comp_store(Stats.all_descriptions())
for id_statstable, stats in tables.items():
for id_tc, tcruns in allstats.groups_by_field_value('id_tc'):
job_id = 'bysample-%s-%s' % (id_tc, id_statstable)
r = context.comp(table_by_rows,
"bysample-%s-%s" % (id_tc, id_statstable),
samples=tcruns,
rows_field='id_algo', # group by algorithm
cols_fields=stats, # which statistics for each col
source_descs=source_descs,
job_id=job_id)
report_attrs = dict(id_statstable=id_statstable) # id_tc=id_tc,
report_attrs.update(tcruns.fields_with_unique_values())
context.add_report(r, 'bysample', **report_attrs)
def jobs_tables_by_sample_rows_algo(allstats, rm, tables):
source_descs = comp_store(Stats.all_descriptions())
for id_statstable, stats in tables.items():
for id_tc, tcruns in allstats.groups_by_field_value('id_tc'):
job_id = 'bysample-%s-%s' % (id_tc, id_statstable)
r = comp(table_by_rows,
"bysample-%s-%s" % (id_tc, id_statstable),
samples=tcruns,
rows_field='id_algo', # group by algorithm
cols_fields=stats, # which statistics for each col
source_descs=source_descs,
job_id=job_id)
report_attrs = dict(id_statstable=id_statstable) # id_tc=id_tc,
report_attrs.update(tcruns.fields_with_unique_values())
rm.add(r, 'bysample', **report_attrs)
def jobs_tables_by_algo_rows_samples(context, allstats, tables):
""" One table for each algo, where rows are test cases. """
source_descs = comp_store(Stats.all_descriptions())
for id_statstable, stats in tables.items():
for id_algo, samples in allstats.groups_by_field_value('id_algo'):
job_id = 'byalgo-%s-%s' % (id_algo, id_statstable)
r = context.comp(table_by_rows,
"byalgo-rows-sample-%s-%s" % (id_algo, id_statstable),
samples=samples,
rows_field='id_tc', # rows = tc
cols_fields=stats, # which statistics for each col
source_descs=source_descs,
job_id=job_id)
report_attrs = dict(id_statstable=id_statstable)
report_attrs.update(samples.fields_with_unique_values())
assert report_attrs['id_algo'] == id_algo
context.add_report(r, 'byalgo-rows-sample', **report_attrs)
def jobs_tables_by_sample_groups(samples_groups, rm, tables):
source_descs = comp_store(Stats.all_descriptions())
# Tables grouping by algorithm
for g, s in product(samples_groups.items(), tables.items()):
id_sample_group, samples = g
id_statstable, stats = s
r = comp(table_by_rows,
"bysamplegroups-%s-%s" % (sanitize(id_sample_group), id_statstable),
samples=samples,
rows_field='id_algo', # group by algorithm
cols_fields=stats, # which statistics for each col
source_descs=source_descs)
report_attrs = dict(id_sample_group=id_sample_group,
id_stats_table=id_statstable)
report_attrs.update(samples.fields_with_unique_values())
rm.add(r, 'bysamplegroups', **report_attrs)
def jobs_tables_by_algo_rows_samples(allstats, rm, tables):
""" One table for each algo, where rows are test cases. """
source_descs = comp_store(Stats.all_descriptions())
for id_statstable, stats in tables.items():
for id_algo, samples in allstats.groups_by_field_value('id_algo'):
job_id = 'byalgo-%s-%s' % (id_algo, id_statstable)
r = comp(table_by_rows,
"byalgo-rows-sample-%s-%s" % (id_algo, id_statstable),
samples=samples,
rows_field='id_tc', # rows = tc
cols_fields=stats, # which statistics for each col
source_descs=source_descs,
job_id=job_id)
report_attrs = dict(id_statstable=id_statstable)
report_attrs.update(samples.fields_with_unique_values())
assert report_attrs['id_algo'] == id_algo
rm.add(r, 'byalgo-rows-sample', **report_attrs)
def jobs_tables_by_sample_groups(context, samples_groups, tables):
source_descs = comp_store(Stats.all_descriptions())
print tables
# Tables grouping by algorithm
for g, s in product(samples_groups.items(), tables.items()):
id_sample_group, samples = g
id_statstable, stats = s
r = context.comp(table_by_rows,
"bysamplegroups-%s-%s" % (sanitize(id_sample_group), id_statstable),
samples=samples,
rows_field='id_algo', # group by algorithm
cols_fields=stats, # which statistics for each col
source_descs=source_descs)
report_attrs = dict(id_sample_group=id_sample_group,
id_stats_table=id_statstable)
# print len(samples)
warnings.warn('not sure what to do')
# report_attrs.update(samples.fields_with_unique_values())
# print report_attrs
context.add_report(r, 'bysamplegroups-%s' % id_statstable, **report_attrs)
def create_index_job(self):
if self.index_job_created:
msg = 'create_index_job() was already called once'
raise ValueError(msg)
self.index_job_created = True
if not self.allreports:
# no reports necessary
return
from compmake import comp
# Do not pass as argument, it will take lots of memory!
# XXX FIXME: there should be a way to make this update or not
# otherwise new reports do not appear
optimize_space = False
if optimize_space and len(self.allreports_filename) > 100:
allreports_filename = comp_store(self.allreports_filename, 'allfilenames')
else:
allreports_filename = self.allreports_filename
type2reports = {}
for report_type, xs in self.allreports_filename.groups_by_field_value('report'):
type2reports[report_type] = StoreResults(**xs.remove_field('report'))
for key in self.allreports:
job_report = self.allreports[key]
filename = self.allreports_filename[key]
write_job_id = job_report.job_id + '-write'
# Create the links to reports of the same type
report_type = key['report']
other_reports_same_type = type2reports[report_type]
key = dict(**key)
del key['report']
# find the closest report for different type
others = []
for other_type, other_type_reports in type2reports.items():
if other_type == report_type:
continue
best = get_most_similar(other_type_reports, key)
if best is not None:
# print('Best match:\n-%s %s\n- %s %s' % (report_type, key,
# other_type, best))
others.append((other_type, best, other_type_reports[best]))
report_type_sane = report_type.replace('_', '')
report_nid = self.html_resources_prefix + report_type_sane
if key:
report_nid += '-' + basename_from_key(key)
comp(write_report_and_update,
report=job_report, report_nid=report_nid,
report_html=filename, all_reports=allreports_filename,
index_filename=self.index_filename,
write_pickle=False,
this_report=key,
other_reports_same_type=other_reports_same_type,
most_similar_other_type=others,
job_id=write_job_id)
