def smooth(requestContext, seriesList, intervalString='5min'):
results = []
interval = int(to_seconds(parseTimeOffset(intervalString)))
for series in seriesList:
if series.step < interval:
values_per_point = interval // series.step
series.consolidate(values_per_point)
series.step = interval
results.append(series)
return results
def test_toSeconds_invalid_inputs(self):
with self.assertRaises(AttributeError):
to_seconds(None)
with self.assertRaises(AttributeError):
to_seconds('')
with self.assertRaises(AttributeError):
to_seconds(1)
def test_toSeconds_invalid_inputs(self):
with self.assertRaises(AttributeError):
to_seconds(None)
with self.assertRaises(AttributeError):
to_seconds('')
with self.assertRaises(AttributeError):
to_seconds(1)
def test_toSeconds(self):
self.assertEqual(to_seconds(self.dt2 - self.dt), 86400)
def test_toSeconds(self):
self.assertEqual(to_seconds(self.dt2 - self.dt), 86400)
def ASAP(requestContext, seriesList, resolution=1000):
'''
use the ASAP smoothing on a series
https://arxiv.org/pdf/1703.00983.pdf
https://raw.githubusercontent.com/stanford-futuredata/ASAP/master/ASAP.py
:param requestContext:
:param seriesList:
:param resolution: either number of points to keep or a time resolution
:return: smoothed(seriesList)
'''
if not seriesList:
return []
windowInterval = None
if isinstance(resolution, six.string_types):
delta = parseTimeOffset(resolution)
windowInterval = to_seconds(delta)
if windowInterval:
previewSeconds = windowInterval
else:
previewSeconds = max([s.step for s in seriesList]) * int(resolution)
# ignore original data and pull new, including our preview
# data from earlier is needed to calculate the early results
newContext = requestContext.copy()
newContext['startTime'] = (requestContext['startTime'] -
timedelta(seconds=previewSeconds))
previewList = evaluateTokens(newContext, requestContext['args'][0])
result = []
for series in previewList:
if windowInterval:
# the resolution here is really the number of points to maintain
# so we need to convert the "seconds" to num points
windowPoints = round((series.end - series.start) / windowInterval)
else:
use_res = int(resolution)
if len(series) < use_res:
use_res = len(series)
windowPoints = use_res
if isinstance(resolution, six.string_types):
newName = 'asap(%s,"%s")' % (series.name, resolution)
else:
newName = "asap(%s,%s)" % (series.name, resolution)
step_guess = (series.end - series.start) // windowPoints
newSeries = TimeSeries(newName, series.start, series.end, step_guess,
[])
newSeries.pathExpression = newName
# detect "none" lists
if len([v for v in series if v is not None]) <= 1:
newSeries.extend(series)
else:
# the "resolution" is a suggestion,
# the algo will alter it some inorder
# to get the best view for things
new_s = smooth(series, windowPoints)
# steps need to be ints, so we must force the issue
new_step = round((series.end - series.start) / len(new_s))
newSeries.step = new_step
newSeries.extend(new_s)
result.append(newSeries)
return result
