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 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 main_chart(fiscal_year):
good_cnt = len(best_programs(fiscal_year, 0, 50))
all_cnt = len(ProgramObligation.objects.filter(fiscal_year=fiscal_year,
obligation__gt='0',
usaspending_obligation__gt='0',
type=1))
poor_cnt = all_cnt - good_cnt
print "%d: %d good (%.2f%%), %d poor (%.2f%%)" % (fiscal_year,
good_cnt,
good_cnt * 100 / all_cnt,
poor_cnt,
poor_cnt * 100 / all_cnt)
series = [[('',good_cnt),('',poor_cnt)]]
chart = Pie(240, 240, series,
show_labels=False,
stylesheet=MEDIA_ROOT + '/styles/bestprograms.css',
x_padding=0, y_padding=0)
chart.output(MEDIA_ROOT + '/images/charts/best-programs-pie.svg')
def main_chart(fiscal_year):
good_cnt = len(best_programs(fiscal_year, 0, 50))
all_cnt = len(
ProgramObligation.objects.filter(fiscal_year=fiscal_year,
obligation__gt='0',
usaspending_obligation__gt='0',
type=1))
poor_cnt = all_cnt - good_cnt
print "%d: %d good (%.2f%%), %d poor (%.2f%%)" % (
fiscal_year, good_cnt, good_cnt * 100 / all_cnt, poor_cnt,
poor_cnt * 100 / all_cnt)
series = [[('', good_cnt), ('', poor_cnt)]]
chart = Pie(240,
240,
series,
show_labels=False,
stylesheet=MEDIA_ROOT + '/styles/bestprograms.css',
x_padding=0,
y_padding=0)
chart.output(MEDIA_ROOT + '/images/charts/best-programs-pie.svg')
