Source: scipy, python-skbio
Control: found -1 scipy/1.7.1-1
Control: found -1 python-skbio/0.5.6-4
Severity: serious
Tags: sid bookworm
X-Debbugs-CC: debian...@lists.debian.org
User: debian...@lists.debian.org
Usertags: breaks needs-update
Dear maintainer(s),
With a recent upload of scipy the autopkgtest of python-skbio fails in
testing when that autopkgtest is run with the binary packages of scipy
from unstable. It passes when run with only packages from testing. In
tabular form:
passfail
scipy from testing1.7.1-1
python-skbio from testing0.5.6-4
all others from testingfrom testing
I copied some of the output at the bottom of this report.
Currently this regression is blocking the migration of scipy to testing
[1]. Due to the nature of this issue, I filed this bug report against
both packages. Can you please investigate the situation and reassign the
bug to the right package?
More information about this bug and the reason for filing it can be found on
https://wiki.debian.org/ContinuousIntegration/RegressionEmailInformation
Paul
[1] https://qa.debian.org/excuses.php?package=scipy
https://ci.debian.net/data/autopkgtest/testing/amd64/p/python-skbio/14750991/log.gz
=== FAILURES
===
testPERMDISP.test_centroids_eq_groups
_
self =
def test_centroids_eq_groups(self):
exp = [[1.2886811963240687, 1.890538910062923, 1.490527658097728],
[2.17349240061718, 2.3192679626679946, 2.028338553903792]]
exp_stat, _ = f_oneway(*exp)
dm = pcoa(self.eq_mat)
dm = dm.samples
> obs = _compute_groups(dm, 'centroid', self.grouping_eq)
skbio/stats/distance/tests/test_permdisp.py:121:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _
skbio/stats/distance/_permdisp.py:251: in _compute_groups
groups.append(cdist(df.values[:, :-1], [centroids.loc[label].values],
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _
XA = array([[-1.7249342172942905, 0.4245950661770306, -0.4421150498378117,
-0.8800986337268075, 0.0, 0.0],
[... [-1.813911896152713, 0.25012463135432966, 0.42415638246654996,
0.9643046100830307, 0.0, 0.0]], dtype=object)
XB = array([[-1.19938106, -0.22670737, -0.50629061, 0.0977458 , 0.
,
0.]])
metric = 'euclidean', out = None, kwargs = {}, s = (3, 6), sB = (1, 6),
mA = 3
mB = 1, n = 6, mstr = 'euclidean'
def cdist(XA, XB, metric='euclidean', *, out=None, **kwargs):
"""
Compute distance between each pair of the two collections of inputs.
See Notes for common calling conventions.
Parameters
--
XA : array_like
An :math:`m_A` by :math:`n` array of :math:`m_A`
original observations in an :math:`n`-dimensional space.
Inputs are converted to float type.
XB : array_like
An :math:`m_B` by :math:`n` array of :math:`m_B`
original observations in an :math:`n`-dimensional space.
Inputs are converted to float type.
metric : str or callable, optional
The distance metric to use. If a string, the distance
function can be
'braycurtis', 'canberra', 'chebyshev', 'cityblock',
'correlation',
'cosine', 'dice', 'euclidean', 'hamming', 'jaccard',
'jensenshannon',
'kulsinski', 'mahalanobis', 'matching', 'minkowski',
'rogerstanimoto',
'russellrao', 'seuclidean', 'sokalmichener', 'sokalsneath',
'sqeuclidean', 'wminkowski', 'yule'.
**kwargs : dict, optional
Extra arguments to `metric`: refer to each metric
documentation for a
list of all possible arguments.
Some possible arguments:
p : scalar
The p-norm to apply for Minkowski, weighted and unweighted.
Default: 2.
w : array_like
The weight vector for metrics that support weights (e.g.,
Minkowski).
V : array_like
The variance vector for standardized Euclidean.
Default: var(vstack([XA, XB]), axis=0, ddof=1)
VI : array_like
The inverse of the covariance matrix for Mahalanobis.
Default: inv(cov(vstack([XA, XB].T))).T
out : ndarray
The output array
If not None, the distance matrix Y is stored in this array.
Returns
---
Y : ndarray
A :math:`m_A` by :math:`m_B` distance matrix is returned.
For each :math:`i` and :math:`j`, the metric
``dist(u=XA[i], v=XB[j])`` is computed and stored in the
:math:`ij` th entry.
Raises
--
ValueError
An exception is thrown if `XA` and `XB` do not have
the sa
