def _set_cumulative_points(self, point, previous):
"""
In place modification of point cumulative-to-present
based on previous sorted points.
"""
mode = getattr(self, 'cumulative', '')
if not mode:
return # not cumulative, no more work to do
opkey = getattr(self, 'cumulative_fn', 'SUM')
cfn = AGGREGATE_FUNCTIONS.get(opkey)
to_date = list(previous) + [point]
_div = lambda a, b: float(a) / float(b) if b else NOVALUE
divide = lambda a, b: NOVALUE if a is None or b is None else _div(a, b)
if mode == 'numerator':
key = 'raw_numerator'
values = filter(
lambda v: not math.isnan(v),
[p.get(key) for p in to_date],
)
cnum = point['cumulative_numerator'] = cfn(values)
val = point['value'] = self._normalize(
divide(cnum, point.get('raw_denominator')))
point['display_value'] = self.display_format(val)
point['user_notes'] = '%s%s' % (
point.get('user_notes', '') or '',
' (cumulative numerator)',
)
return # TODO: denominator, both, final modes
def _summarized_field_value(self, context, fieldpath, fn):
"""Return summarized value, for field, across all records in context"""
fn = AGGREGATE_FUNCTIONS.get(fn)
values = filter(
lambda v: v is not None,
[getattr(record, fieldpath, None) for record in context.values()])
return fn([float(v) for v in values])
def _set_cumulative_points(self, point, previous):
"""
In place modification of point cumulative-to-present
based on previous sorted points.
"""
mode = getattr(self, 'cumulative', '')
if not mode:
return # not cumulative, no more work to do
opkey = getattr(self, 'cumulative_fn', 'SUM')
cfn = AGGREGATE_FUNCTIONS.get(opkey)
to_date = list(previous) + [point]
_div = lambda a, b: float(a) / float(b) if b else NOVALUE
divide = lambda a, b: NOVALUE if a is None or b is None else _div(a, b)
if mode == 'numerator':
key = 'raw_numerator'
values = filter(
lambda v: not math.isnan(v),
[p.get(key) for p in to_date],
)
cnum = point['cumulative_numerator'] = cfn(values)
val = point['value'] = self._normalize(
divide(cnum, point.get('raw_denominator'))
)
point['display_value'] = self.display_format(val)
point['user_notes'] = '%s%s' % (
point.get('user_notes', '') or '',
' (cumulative numerator)',
)
return # TODO: denominator, both, final modes
def _summarized_field_value(self, context, fieldpath, fn):
"""Return summarized value, for field, across all records in context"""
fn = AGGREGATE_FUNCTIONS.get(fn)
values = filter(
lambda v: v is not None,
[getattr(record, fieldpath, None) for record in context.values()]
)
return fn([float(v) for v in values])
def _aggregate_dataset_points(self, aggregated, fn_name):
"""
given a list of other aggregated datasets, get data for
each, and calculate aggregate values for points, given
a value aggregation function (fn).
"""
consider = lambda o: o is not None
fn = AGGREGATE_FUNCTIONS.get(fn_name)
label = dict(AGGREGATE_LABELS).get(fn_name, '')
result = []
raw = []
for ds in filter(consider, aggregated):
points = self._dataset_points(ds)
raw.append(points)
all_points = list(chain(*raw))
_date = lambda info: info.get('start', None)
dates = sorted(set(map(_date, all_points))) # de-duped ordered dates
for d in dates:
_hasvalue = lambda info: not math.isnan(info.get('value', NOVALUE))
_match = lambda info: info.get('start') == d and _hasvalue(info)
matches = filter(_match, all_points)
if not matches:
continue # skip columns/dates for which no match found
values = [info.get('value') for info in matches]
calculated_value = fn(values)
if math.isnan(calculated_value):
continue
includes = ', '.join([info.get('title') for info in matches])
result.append({
'title':
'%s: %s' % (label, d.isoformat()),
'url':
self.absolute_url(),
'path':
'--',
'start':
d,
'value':
calculated_value,
'user_notes':
'Aggregate value (%s) includes: %s' % (
label,
includes,
),
'display_value':
self.display_format(calculated_value),
})
return result
def _aggregate_dataset_points(self, aggregated, fn_name):
"""
given a list of other aggregated datasets, get data for
each, and calculate aggregate values for points, given
a value aggregation function (fn).
"""
consider = lambda o: o is not None
fn = AGGREGATE_FUNCTIONS.get(fn_name)
label = dict(AGGREGATE_LABELS).get(fn_name, '')
result = []
raw = []
for ds in filter(consider, aggregated):
points = self._dataset_points(ds)
raw.append(points)
all_points = list(chain(*raw))
_date = lambda info: info.get('start', None)
dates = sorted(set(map(_date, all_points))) # de-duped ordered dates
for d in dates:
_hasvalue = lambda info: not math.isnan(info.get('value', NOVALUE))
_match = lambda info: info.get('start') == d and _hasvalue(info)
matches = filter(_match, all_points)
if not matches:
continue # skip columns/dates for which no match found
values = [info.get('value') for info in matches]
calculated_value = fn(values)
if math.isnan(calculated_value):
continue
includes = ', '.join([info.get('title') for info in matches])
result.append({
'title': '%s: %s' % (label, d.isoformat()),
'url': self.absolute_url(),
'path': '--',
'start': d,
'value': calculated_value,
'user_notes': 'Aggregate value (%s) includes: %s' % (
label,
includes,
),
'display_value': self.display_format(calculated_value),
})
return result
