def rows(self):
def format_val(val):
return self.no_value if val is None else val
def avg(values, idx=None):
sum = 0
denom = 0
for v in values:
if idx == 10:
numbers = re.split(r'/|\s|%', v['html'])
sum += int(numbers[0])
if int(numbers[1]) > denom:
denom = int(numbers[1])
else:
sum += v['sort_key'] if v is not None else 0
mean = (float(sum) / float(len(values)))
if idx == 10:
try:
percent = mean * 100 / denom
except ZeroDivisionError:
percent = 0
html = "{0}/{1} ({2}%)".format(int(mean), int(denom), int(percent))
return format_datatables_data(html, percent)
mean = "%.0f" % mean
return format_datatables_data(mean, mean)
data = []
config = self.report_config
for i in range(0, 3):
config['enddate'] = (
config['startdate'] + relativedelta(months=1) - relativedelta(days=1)
).replace(hour=23, minute=59, second=59)
for index, row_data in ASHAFacilitatorsData(config).data.items():
data.append(row_data)
config['startdate'] += relativedelta(months=1)
rows = [[
column.header,
format_val(column.get_value(data[2])),
format_val(column.get_value(data[1])),
format_val(column.get_value(data[0])),
avg([column.get_value(data[2]), column.get_value(data[1]), column.get_value(data[0])], idx)
] for idx, column in enumerate(self.model.columns[2:])]
total = [self.model.columns[0].get_raw_value(d) for d in data]
reporting = [self.model.columns[1].get_raw_value(d) for d in data]
not_reporting = [format_datatables_data(i - (j or 0), i - (j or 0)) for i, j in zip(total, reporting)]
rows.append([_("<b>Total number of ASHAs who did not report/not known</b>")] + not_reporting +
[avg(not_reporting)])
return rows, sum(total) // len(total)
def model(self):
return ASHAFacilitatorsData(config=self.report_config)
