def _PassesThresholds(
values, split_index, min_segment_size, min_absolute_change,
min_relative_change, min_steppiness, multiple_of_std_dev):
"""Checks whether a point in a series appears to be an change point.
Args:
values: A list of numbers.
split_index: An index in the list of numbers.
min_segment_size: Threshold for size of segments before or after a point.
min_absolute_change: Minimum absolute median change threshold.
min_relative_change: Minimum relative median change threshold.
min_steppiness: Threshold for how similar to a step a change point must be.
multiple_of_std_dev: Threshold for change as multiple of std. deviation.
Returns:
True if it passes all of the thresholds, False otherwise.
"""
left, right = values[:split_index], values[split_index:]
left_median, right_median = math_utils.Median(left), math_utils.Median(right)
# 1. Segment size filter.
if len(left) < min_segment_size or len(right) < min_segment_size:
return False
# 2. Absolute change filter.
absolute_change = abs(left_median - right_median)
if absolute_change < min_absolute_change:
return False
# 3. Relative change filter.
relative_change = _RelativeChange(left_median, right_median)
if relative_change < min_relative_change:
return False
# 4. Multiple of standard deviation filter.
# The left and right sides are independently normalized so that their medians
# are zero, then the two sides are concatenated together. This, in effect,
# removes the step so that the step itself doesn't affect the std. dev.
min_std_dev = min(
math_utils.StandardDeviation(left),
math_utils.StandardDeviation(right))
if absolute_change < multiple_of_std_dev * min_std_dev:
return False
# 5. Steppiness filter.
steppiness = find_step.Steppiness(values, split_index)
if steppiness < min_steppiness:
return False
# Passed all filters!
return True
def _PassesThresholds(values, split_index, min_segment_size,
min_absolute_change, min_relative_change, min_steppiness,
multiple_of_std_dev):
"""Checks whether a point in a series appears to be an change point.
Args:
values: A list of numbers.
split_index: An index in the list of numbers.
min_segment_size: Threshold for size of segments before or after a point.
min_absolute_change: Minimum absolute median change threshold.
min_relative_change: Minimum relative median change threshold.
min_steppiness: Threshold for how similar to a step a change point must be.
multiple_of_std_dev: Threshold for change as multiple of std. deviation.
Returns:
A tuple of (bool, string) where the bool indicates whether the split index
passes the thresholds and the string being the reason it did not.
"""
left, right = values[:split_index], values[split_index:]
left_median, right_median = math_utils.Median(left), math_utils.Median(
right)
# 1. Segment size filter.
if len(left) < min_segment_size or len(right) < min_segment_size:
return (False, 'min_segment_size')
# 2. Absolute change filter.
absolute_change = abs(left_median - right_median)
if absolute_change < min_absolute_change:
return (False, 'min_absolute_change')
# 3. Relative change filter.
relative_change = math_utils.RelativeChange(left_median, right_median)
if relative_change < min_relative_change:
return (False, 'min_relative_change')
# 4. Multiple of standard deviation filter.
min_std_dev = min(math_utils.StandardDeviation(left),
math_utils.StandardDeviation(right))
if absolute_change < multiple_of_std_dev * min_std_dev:
return (False, 'min_std_dev')
# 5. Steppiness filter.
steppiness = find_step.Steppiness(values, split_index)
if steppiness < min_steppiness:
return (False, 'min_steppiness')
# Passed all filters!
return (True, 'passed')
def testSteppiness_UpDownPattern_ReturnsZero(self): step = [1, 0, 1, 0, 1, 0, 1, 0] self.assertAlmostEqual(0.0, find_step.Steppiness(step, 4))
def testSteppiness_LengthOfSeriesDoesntAffectScore(self):
step = [1, 2, 1, 2, 4, 3, 5, 4]
step_long = [1, 2, 1, 2, 2, 1, 2, 1, 4, 3, 5, 4, 5, 3, 4, 4]
self.assertAlmostEqual(
find_step.Steppiness(step, 4),
find_step.Steppiness(step_long, 8))
def testSteppiness_ImperfectStep_ReturnsValueBetweenZeroAndOne(self): step = [1, 2, 1, 2, 4, 3, 5, 4] self.assertAlmostEqual(0.56005865, find_step.Steppiness(step, 4))
def testSteppiness_PerfectStep_ReturnsOne(self): step = [3, 3, 3, 3, 10, 10, 10] self.assertEqual(1.0, find_step.Steppiness(step, 4))
