Exemplo n.º 1
0
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
Exemplo n.º 2
0
 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)
Exemplo n.º 3
0
 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)
Exemplo n.º 4
0
 def test_toSeconds(self):
     self.assertEqual(to_seconds(self.dt2 - self.dt), 86400)
Exemplo n.º 5
0
 def test_toSeconds(self):
     self.assertEqual(to_seconds(self.dt2 - self.dt), 86400)
Exemplo n.º 6
0
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