Skip to content

Commit b1488dd

Browse files
Release 0.5.5 (#436)
* Update changelog and version number * Improve speed of multivariate_normality (#437)
1 parent aaae740 commit b1488dd

File tree

3 files changed

+12
-3
lines changed

3 files changed

+12
-3
lines changed

docs/changelog.rst

Lines changed: 9 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -3,10 +3,18 @@
33
What's new
44
##########
55

6+
v0.5.5 (September 2024)
7+
-----------------------
8+
9+
This is a minor release with several bugfixes, and major updates to the internal structure and sphinx documentation.
10+
11+
See the full `changelog for 0.5.5 <https://github.com/raphaelvallat/pingouin/releases/tag/v0.5.5>`_.
12+
13+
614
v0.5.4 (January 2024)
715
---------------------
816

9-
This is a minor release with several bugfixes and no new features. The new version is tested for Python 3.8-3.11 (but should also work with Python 3.12). See `GitHub <https://github.com/raphaelvallat/pingouin/releases>`_ for the full changelog.
17+
This is a minor release with several bugfixes and no new features. The new version is tested for Python 3.8-3.11 (but should also work with Python 3.12). See the full `changelog for 0.5.4 <https://github.com/raphaelvallat/pingouin/releases/tag/v0.5.4>`_.
1018

1119
This release requires pandas≥1.5. We recommend scipy≥1.11.0.
1220

src/pingouin/__init__.py

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -20,7 +20,7 @@
2020
from .config import *
2121

2222
# Current version
23-
__version__ = "0.5.4"
23+
__version__ = "0.5.5"
2424

2525
# load default options
2626
set_default_options()

src/pingouin/multivariate.py

Lines changed: 2 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -78,7 +78,8 @@ def multivariate_normality(X, alpha=0.05):
7878
# Squared-Mahalanobis distances
7979
Dj = np.diag(np.linalg.multi_dot([difT, S_inv, difT.T]))
8080
Y = np.linalg.multi_dot([X, S_inv, X.T])
81-
Djk = -2 * Y.T + np.repeat(np.diag(Y.T), n).reshape(n, -1) + np.tile(np.diag(Y.T), (n, 1))
81+
Y_diag = np.diag(Y)
82+
Djk = -2 * Y.T + Y_diag + Y_diag[..., None]
8283

8384
# Smoothing parameter
8485
b = 1 / (np.sqrt(2)) * ((2 * p + 1) / 4) ** (1 / (p + 4)) * (n ** (1 / (p + 4)))

0 commit comments

Comments
 (0)