Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

BUG: Fixes gh-12218, TypeError converting int to float inside stats.ks_2samp #12280

Merged
merged 2 commits into from
Jun 28, 2020
Merged

BUG: Fixes gh-12218, TypeError converting int to float inside stats.ks_2samp #12280

Show file tree
Hide file tree
Changes from 1 commit
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
3fc7845
BUG: Fixes gh-12218, TypeError converting int to float.
pvanmulbregt May 30, 2020
2a15c0d
Use a Python list to hold the two sizes to be sorted inside ks_2samp.
pvanmulbregt Jun 27, 2020
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Jump to
Jump to file
Failed to load files.
Diff view
Diff view
15 changes: 9 additions & 6 deletions scipy/stats/stats.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -6702,7 +6702,7 @@ def ks_2samp(data1, data2, alternative='two-sided', mode='auto'):
cdf1 = np.searchsorted(data1, data_all, side='right') / n1
cdf2 = np.searchsorted(data2, data_all, side='right') / n2
cddiffs = cdf1 - cdf2
minS = -np.min(cddiffs)
minS = np.clip(-np.min(cddiffs), 0, 1) # Ensure sign of minS is not negative.
maxS = np.max(cddiffs)
alt2Dvalue = {'less': minS, 'greater': maxS, 'two-sided': max(minS, maxS)}
d = alt2Dvalue[alternative]
Expand All @@ -6718,8 +6718,8 @@ def ks_2samp(data1, data2, alternative='two-sided', mode='auto'):
if n1g >= np.iinfo(np.int).max / n2g:
mode = 'asymp'
warnings.warn(
"Exact ks_2samp calculation not possible with samples sizes "
"%d and %d. Switching to 'asymp' " % (n1, n2), RuntimeWarning)
f"Exact ks_2samp calculation not possible with samples sizes "
f"{n1} and {n2}. Switching to 'asymp'.", RuntimeWarning)

if mode == 'exact':
success, d, prob = _attempt_exact_2kssamp(n1, n2, g, d, alternative)
Expand All @@ -6731,13 +6731,16 @@ def ks_2samp(data1, data2, alternative='two-sided', mode='auto'):

if mode == 'asymp':
# The product n1*n2 is large. Use Smirnov's asymptoptic formula.
# Ensure float to avoid overflow in multiplication
# sorted because the one-sided formula is not symmetric in n1, n2
m, n = sorted(np.array([n1, n2], float), reverse=True)
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

No need to create a numpy array here. This is quite a bit faster:

Suggested change
m, n = sorted(np.array([n1, n2], float), reverse=True)
m, n = sorted([float(n1), float(n2)], reverse=True)

Copy link
Contributor Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Done.

en = m * n / (m + n)
if alternative == 'two-sided':
en = n1 * n2 / (n1 + n2)
prob = distributions.kstwo.sf(d, np.round(en))
else:
m, n = max(n1, n2), min(n1, n2)
z = np.sqrt(m*n/(m+n)) * d
z = np.sqrt(en) * d
# Use Hodges' suggested approximation Eqn 5.3
# Requires m to be the larger of (n1, n2)
expt = -2 * z**2 - 2 * z * (m + 2*n)/np.sqrt(m*n*(m+n))/3.0
prob = np.exp(expt)

Expand Down
12 changes: 12 additions & 0 deletions scipy/stats/tests/test_stats.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -3265,6 +3265,18 @@ def test_argument_checking(self):
assert_raises(ValueError, stats.ks_2samp, [1], [])
assert_raises(ValueError, stats.ks_2samp, [], [])

def test_gh12218(self):
"""Ensure gh-12218 is fixed."""
# gh-1228 triggered a TypeError calculating sqrt(n1*n2*(n1+n2)).
# n1, n2 both large integers, the product exceeded 2^64
np.random.seed(12345678)
n1 = 2097152 # 2*^21
rvs1 = stats.uniform.rvs(size=n1, loc=0., scale=1)
rvs2 = rvs1 + 1 # Exact value of rvs2 doesn't matter.
stats.ks_2samp(rvs1, rvs2, alternative='greater', mode='asymp')
stats.ks_2samp(rvs1, rvs2, alternative='less', mode='asymp')
stats.ks_2samp(rvs1, rvs2, alternative='two-sided', mode='asymp')


def test_ttest_rel():
# regression test
Expand Down