bpo-36546: Clean-up comments (GH-14857)
This commit is contained in:
parent
8dbe563aa6
commit
eed5e9a956
|
@ -596,12 +596,9 @@ def multimode(data):
|
|||
# intervals, and exactly 100p% of the intervals lie to the left of
|
||||
# Q7(p) and 100(1 - p)% of the intervals lie to the right of Q7(p)."
|
||||
|
||||
# If the need arises, we could add method="median" for a median
|
||||
# unbiased, distribution-free alternative. Also if needed, the
|
||||
# distribution-free approaches could be augmented by adding
|
||||
# method='normal'. However, for now, the position is that fewer
|
||||
# options make for easier choices and that external packages can be
|
||||
# used for anything more advanced.
|
||||
# If needed, other methods could be added. However, for now, the
|
||||
# position is that fewer options make for easier choices and that
|
||||
# external packages can be used for anything more advanced.
|
||||
|
||||
def quantiles(dist, /, *, n=4, method='exclusive'):
|
||||
'''Divide *dist* into *n* continuous intervals with equal probability.
|
||||
|
@ -620,9 +617,6 @@ def quantiles(dist, /, *, n=4, method='exclusive'):
|
|||
data. The minimum value is treated as the 0th percentile and the
|
||||
maximum value is treated as the 100th percentile.
|
||||
'''
|
||||
# Possible future API extensions:
|
||||
# quantiles(data, already_sorted=True)
|
||||
# quantiles(data, cut_points=[0.02, 0.25, 0.50, 0.75, 0.98])
|
||||
if n < 1:
|
||||
raise StatisticsError('n must be at least 1')
|
||||
if hasattr(dist, 'inv_cdf'):
|
||||
|
|
Loading…
Reference in New Issue