def main():
for fy in FISCAL_YEARS:
timely_programs = ProgramTimeliness.objects.filter(fiscal_year=fy, avg_lag_rows__lte='45')
programs_available = ProgramTimeliness.objects.filter(fiscal_year=fy)
pct = len(timely_programs) * 100 / len(programs_available)
avg_avg_lag_rows = mean([t.avg_lag_rows for t in programs_available])
print "%d: %d / %d (%.2f%%) programs with avg lag <=45 days, avg program lag: %.2f days" % (
fy,
len(timely_programs),
len(programs_available),
pct,
avg_avg_lag_rows
)
for fy in FISCAL_YEARS:
timely_agencies = AgencyTimeliness.objects.filter(fiscal_year=fy, avg_lag_rows__lte='45')
agencies_available = AgencyTimeliness.objects.filter(fiscal_year=fy)
pct = len(timely_agencies) * 100 / len(agencies_available)
avg_avg_lag_rows = mean([t.avg_lag_rows for t in agencies_available])
print "%d: %d / %d (%.2f%%) agencies with avg lag <=45 days, avg agency lag: %.2f days" % (
fy,
len(timely_agencies),
len(agencies_available),
pct,
avg_avg_lag_rows)
for fy in FISCAL_YEARS:
all_agencies = AgencyTimeliness.objects.filter(fiscal_year=fy)
timely_sum = sum([t.total_dollars - t.late_dollars for t in all_agencies])
tardy_sum = sum([t.late_dollars for t in all_agencies])
tardy_pct = tardy_sum * 100 / (timely_sum + tardy_sum)
pie = Pie(170, 170, [[('Timely', float(timely_sum))],
[('Tardy', float(tardy_sum))]],
show_labels=False,
stylesheet=MEDIA_ROOT + '/styles/timeliness-charts.css',
x_padding=0, y_padding=0)
pie.output(MEDIA_ROOT + '/images/charts/program-timeliness-%d.svg' % fy)
print "%d: timely %s vs %s tardy, %.2f%% tardy" % (fy,
short_money(timely_sum),
short_money(tardy_sum),
tardy_pct)
def __unicode__(self):
if self.completeness_total_dollars in (0, None):
failed_pct = None
else:
failed_pct = "%2.2f%%" % (self.completeness_failed_dollars * 100 / self.completeness_total_dollars)
return "%s %s (%d) / %s / $%.1fm" % (self.program.program_title,
self.program.program_number,
self.fiscal_year,
failed_pct,
short_money(self.completeness_failed_dollars))
def main():
for fy in FISCAL_YEARS:
timely_programs = ProgramTimeliness.objects.filter(
fiscal_year=fy, avg_lag_rows__lte='45')
programs_available = ProgramTimeliness.objects.filter(fiscal_year=fy)
pct = len(timely_programs) * 100 / len(programs_available)
avg_avg_lag_rows = mean([t.avg_lag_rows for t in programs_available])
print "%d: %d / %d (%.2f%%) programs with avg lag <=45 days, avg program lag: %.2f days" % (
fy, len(timely_programs), len(programs_available), pct,
avg_avg_lag_rows)
for fy in FISCAL_YEARS:
timely_agencies = AgencyTimeliness.objects.filter(
fiscal_year=fy, avg_lag_rows__lte='45')
agencies_available = AgencyTimeliness.objects.filter(fiscal_year=fy)
pct = len(timely_agencies) * 100 / len(agencies_available)
avg_avg_lag_rows = mean([t.avg_lag_rows for t in agencies_available])
print "%d: %d / %d (%.2f%%) agencies with avg lag <=45 days, avg agency lag: %.2f days" % (
fy, len(timely_agencies), len(agencies_available), pct,
avg_avg_lag_rows)
for fy in FISCAL_YEARS:
all_agencies = AgencyTimeliness.objects.filter(fiscal_year=fy)
timely_sum = sum(
[t.total_dollars - t.late_dollars for t in all_agencies])
tardy_sum = sum([t.late_dollars for t in all_agencies])
tardy_pct = tardy_sum * 100 / (timely_sum + tardy_sum)
pie = Pie(
170,
170,
[[('Timely', float(timely_sum))], [('Tardy', float(tardy_sum))]],
show_labels=False,
stylesheet=MEDIA_ROOT + '/styles/timeliness-charts.css',
x_padding=0,
y_padding=0)
pie.output(MEDIA_ROOT +
'/images/charts/program-timeliness-%d.svg' % fy)
print "%d: timely %s vs %s tardy, %.2f%% tardy" % (
fy, short_money(timely_sum), short_money(tardy_sum), tardy_pct)
consistent_allyears.append(consistency_set)
consistent_programs = ProgramObligation.objects.filter(fiscal_year=fy, type=1, program__in=consistency_set)
consistent_dollars = sum([o.obligation for o in consistent_programs])
consistent_mean = mean([float(o.obligation) for o in consistent_programs])
all_grant_dollars = sum([o.obligation for o in all_programs])
all_grant_mean = mean([float(o.obligation) for o in all_programs])
print "%d: %d consistent programs, %.2f%% of programs (%d acccurate, %d under, %d over) / %d programs, %.2f%% of grant spending (%s / %s), mean of obligations: %s consistent vs %s all grants" % (
fy,
len(consistent_programs),
len(consistent_programs) * 100 / len(all_programs),
len(accurate_set),
len(under_reporting_set),
len(over_reporting_set),
len(all_programs),
consistent_dollars * 100 / all_grant_dollars,
short_money(consistent_dollars),
short_money(all_grant_dollars),
short_money(consistent_mean),
short_money(all_grant_mean))
progs = consistent_allyears[0] & consistent_allyears[1] & consistent_allyears[2]
for p in progs:
program = Program.objects.get(id=p)
writer.writerow((program.id, program.program_number, program.program_title))
print "%s programs report consistent for all three years" % len(progs)
get_program_id = attrgetter('program_id')
accurate_set = set(map(get_program_id, null_reporting)) & set(
map(get_program_id, programs_with_obligations))
under_reporting_set = set(map(get_program_id, under_reporting))
over_reporting_set = set(map(get_program_id, over_reporting))
consistency_set = accurate_set | under_reporting_set | over_reporting_set
consistent_allyears.append(consistency_set)
consistent_programs = ProgramObligation.objects.filter(
fiscal_year=fy, type=1, program__in=consistency_set)
consistent_dollars = sum([o.obligation for o in consistent_programs])
consistent_mean = mean([float(o.obligation) for o in consistent_programs])
all_grant_dollars = sum([o.obligation for o in all_programs])
all_grant_mean = mean([float(o.obligation) for o in all_programs])
print "%d: %d consistent programs, %.2f%% of programs (%d acccurate, %d under, %d over) / %d programs, %.2f%% of grant spending (%s / %s), mean of obligations: %s consistent vs %s all grants" % (
fy, len(consistent_programs),
len(consistent_programs) * 100 / len(all_programs), len(accurate_set),
len(under_reporting_set), len(over_reporting_set), len(all_programs),
consistent_dollars * 100 / all_grant_dollars,
short_money(consistent_dollars), short_money(all_grant_dollars),
short_money(consistent_mean), short_money(all_grant_mean))
progs = consistent_allyears[0] & consistent_allyears[1] & consistent_allyears[2]
for p in progs:
program = Program.objects.get(id=p)
writer.writerow(
(program.id, program.program_number, program.program_title))
print "%s programs report consistent for all three years" % len(progs)
