def print_program_list(fiscal_year, best_program_ids):
best_program_consistencies = list(
ProgramConsistency.objects.filter(fiscal_year=fiscal_year,
type=1,
program__in=best_program_ids))
best_program_consistencies.sort(compare_consistencies)
fmtstr = "{program:<8} {consistency:>14} {completeness:>12} {timeliness:>11} {cfda:>21}"
print fmtstr.format(program='PROGRAM',
consistency='INCONSISTENT',
completeness='INCOMPLETE',
timeliness='LATE',
cfda='CFDA OBLIGATION')
for prog_consistency in best_program_consistencies:
program = Program.objects.get(pk=prog_consistency.program_id)
program_obligation = ProgramObligation.objects.get(
fiscal_year=fiscal_year,
type=1,
program=prog_consistency.program_id)
prog_completeness = ProgramCompleteness.objects.get(
fiscal_year=fiscal_year, program=prog_consistency.program_id)
try:
prog_timeliness = ProgramTimeliness.objects.get(
fiscal_year=fiscal_year, program=prog_consistency.program_id)
except:
prog_timeliness = None
if prog_consistency.over_reported_pct not in (None, ''):
over_or_under = "-" + str(prog_consistency.over_reported_pct)
elif prog_consistency.under_reported_pct not in (None, ''):
over_or_under = "-" + str(prog_consistency.under_reported_pct)
else:
over_or_under = None
values = {
'program':
str(program.program_number),
'consistency':
(str(over_or_under) + '%' if over_or_under else '---'),
'completeness':
str(round(prog_completeness.failed_pct)) +
'%' if prog_completeness.failed_pct is not None else '---',
'timeliness':
str(round(prog_timeliness.late_pct)) + '%' if prog_timeliness
and prog_timeliness.late_pct is not None else '---',
'cfda':
pretty_money(program_obligation.obligation)
}
print fmtstr.format(**values)
def print_program_list(fiscal_year, best_program_ids):
best_program_consistencies = list(ProgramConsistency.objects.filter(fiscal_year=fiscal_year,
type=1,
program__in=best_program_ids))
best_program_consistencies.sort(compare_consistencies)
fmtstr = "{program:<8} {consistency:>14} {completeness:>12} {timeliness:>11} {cfda:>21}"
print fmtstr.format(
program='PROGRAM',
consistency='INCONSISTENT',
completeness='INCOMPLETE',
timeliness='LATE',
cfda='CFDA OBLIGATION'
)
for prog_consistency in best_program_consistencies:
program = Program.objects.get(pk=prog_consistency.program_id)
program_obligation = ProgramObligation.objects.get(fiscal_year=fiscal_year,
type=1,
program=prog_consistency.program_id)
prog_completeness = ProgramCompleteness.objects.get(fiscal_year=fiscal_year,
program=prog_consistency.program_id)
try:
prog_timeliness = ProgramTimeliness.objects.get(fiscal_year=fiscal_year,
program=prog_consistency.program_id)
except:
prog_timeliness = None
if prog_consistency.over_reported_pct not in (None, ''):
over_or_under = "-" + str(prog_consistency.over_reported_pct)
elif prog_consistency.under_reported_pct not in (None, ''):
over_or_under = "-" + str(prog_consistency.under_reported_pct)
else:
over_or_under = None
values = {
'program': str(program.program_number),
'consistency': (str(over_or_under) + '%'
if over_or_under else '---'),
'completeness': str(round(prog_completeness.failed_pct)) + '%' if prog_completeness.failed_pct is not None else '---',
'timeliness': str(round(prog_timeliness.late_pct)) + '%' if prog_timeliness and prog_timeliness.late_pct is not None else '---',
'cfda': pretty_money(program_obligation.obligation)
}
print fmtstr.format(**values)
def __unicode__(self):
return "<USASpendingAggregate(%d, %s)>" % (self.fiscal_year, unicode(pretty_money(self.total_federal_funding)))
from django.db.models import Sum
from numpy import mean, std
from metrics.models import ProgramTimeliness, AgencyTimeliness, USASpendingAggregate
from utils import pretty_money
from settings import FISCAL_YEARS
print "----- Sample Size -----"
for fy in FISCAL_YEARS:
timeliness_sum = ProgramTimeliness.objects.filter(fiscal_year=fy).aggregate(Sum('total_dollars'))['total_dollars__sum']
usaspending_sum = USASpendingAggregate.objects.get(fiscal_year=fy).total_federal_funding
sample_pct = timeliness_sum * 100 / usaspending_sum
print "%d: %.2f%% (%s / %s)" % (fy, round(sample_pct, 2),
pretty_money(timeliness_sum),
pretty_money(usaspending_sum))
print "----- Average Lag (program) -----"
for fy in FISCAL_YEARS:
lag_values = [pt.avg_lag_rows for pt in ProgramTimeliness.objects.filter(fiscal_year=fy)]
print "%d: %d mean (days), %.1f stdev" % (fy, mean(lag_values), std(lag_values))
print "----- Average Lag (agency) -----"
for fy in FISCAL_YEARS:
lag_values = [at.avg_lag_rows for at in AgencyTimeliness.objects.filter(fiscal_year=fy)]
print "%d: %d mean (days), %.1f stdev" % (fy, mean(lag_values), std(lag_values))
# fail completeness?
if metric == 'all' or metric == 'completeness':
comp = ProgramCompleteness.objects.filter(program=program, fiscal_year=fy)
if len(comp) > 0:
comp = comp[0]
if comp.completeness_total_dollars and (float(comp.completeness_failed_dollars / comp.completeness_total_dollars) > .5):
total += ob.obligation
agency_totals = add_to_agency(agency_totals, program.agency.name, fy, ob.obligation)
writer.writerow((program.program_number, "%s" % program.program_title.encode('ascii', 'ignore'), 'completeness', ob.obligation))
continue
count += 1
all_obs = ProgramObligation.objects.filter(program__in=fins, fiscal_year=fy, type=TYPE).aggregate(summ=Sum('obligation'))['summ']
if all_obs:
print "%s - Total failed obligations: %s out of total obligations: %s (%s%%)" % (fy, pretty_money(total),
pretty_money(all_obs),
round(total * 100 / all_obs, 2))
else:
print "No obligations for %s " % fy
data = []
agency_names = []
for k in agency_totals.keys():
points = []
for fy in FISCAL_YEARS:
if agency_totals[k].has_key(fy):
points.append((fy, float(agency_totals[k][fy])))
else:
points.append((fy, 0))
data.append(points)
from django.db.models import Sum
from numpy import mean, std
from metrics.models import ProgramTimeliness, AgencyTimeliness, USASpendingAggregate
from utils import pretty_money
from settings import FISCAL_YEARS
print "----- Sample Size -----"
for fy in FISCAL_YEARS:
timeliness_sum = ProgramTimeliness.objects.filter(
fiscal_year=fy).aggregate(Sum('total_dollars'))['total_dollars__sum']
usaspending_sum = USASpendingAggregate.objects.get(
fiscal_year=fy).total_federal_funding
sample_pct = timeliness_sum * 100 / usaspending_sum
print "%d: %.2f%% (%s / %s)" % (fy, round(
sample_pct,
2), pretty_money(timeliness_sum), pretty_money(usaspending_sum))
print "----- Average Lag (program) -----"
for fy in FISCAL_YEARS:
lag_values = [
pt.avg_lag_rows
for pt in ProgramTimeliness.objects.filter(fiscal_year=fy)
]
print "%d: %d mean (days), %.1f stdev" % (fy, mean(lag_values),
std(lag_values))
print "----- Average Lag (agency) -----"
for fy in FISCAL_YEARS:
lag_values = [
at.avg_lag_rows
for at in AgencyTimeliness.objects.filter(fiscal_year=fy)
agency_totals = add_to_agency(agency_totals,
program.agency.name, fy,
ob.obligation)
writer.writerow(
(program.program_number, "%s" %
program.program_title.encode('ascii', 'ignore'),
'completeness', ob.obligation))
continue
count += 1
all_obs = ProgramObligation.objects.filter(
program__in=fins, fiscal_year=fy,
type=TYPE).aggregate(summ=Sum('obligation'))['summ']
if all_obs:
print "%s - Total failed obligations: %s out of total obligations: %s (%s%%)" % (
fy, pretty_money(total), pretty_money(all_obs),
round(total * 100 / all_obs, 2))
else:
print "No obligations for %s " % fy
data = []
agency_names = []
for k in agency_totals.keys():
points = []
for fy in FISCAL_YEARS:
if agency_totals[k].has_key(fy):
points.append((fy, float(agency_totals[k][fy])))
else:
points.append((fy, 0))
data.append(points)
agency_names.append(k)
