File fix-scipy-version-compatibility.patch of Package python-pot
From 22ab1ff2e66657a3e447e773651f59a99247be38 Mon Sep 17 00:00:00 2001
From: nathanneike <nathanneike@outlook.de>
Date: Tue, 20 Jan 2026 10:24:03 +0100
Subject: [PATCH 2/8] Add emd2_lazy function and fix SciPy sparse matrix
compatibility
---
ot/__init__.py | 2 +
ot/gromov/_estimators.py | 25 ++--
ot/lp/__init__.py | 3 +-
ot/lp/_network_simplex.py | 255 +++++++++++++++++++++++++++++---------
ot/solvers.py | 10 +-
test/test_solvers.py | 54 ++++----
6 files changed, 246 insertions(+), 103 deletions(-)
diff --git a/ot/gromov/_estimators.py b/ot/gromov/_estimators.py
index 14871bfe3..18359afe5 100644
--- a/ot/gromov/_estimators.py
+++ b/ot/gromov/_estimators.py
@@ -122,8 +122,8 @@ def GW_distance_estimation(
for i in range(nb_samples_p):
if nx.issparse(T):
- T_indexi = nx.reshape(nx.todense(T[index_i[i], :]), (-1,))
- T_indexj = nx.reshape(nx.todense(T[index_j[i], :]), (-1,))
+ T_indexi = nx.reshape(nx.todense(T[[index_i[i]], :]), (-1,))
+ T_indexj = nx.reshape(nx.todense(T[[index_j[i]], :]), (-1,))
else:
T_indexi = T[index_i[i], :]
T_indexj = T[index_j[i], :]
@@ -243,16 +243,18 @@ def pointwise_gromov_wasserstein(
index = np.zeros(2, dtype=int)
# Initialize with default marginal
- index[0] = generator.choice(len_p, size=1, p=nx.to_numpy(p))
- index[1] = generator.choice(len_q, size=1, p=nx.to_numpy(q))
+ index[0] = int(generator.choice(len_p, size=1, p=nx.to_numpy(p)).item())
+ index[1] = int(generator.choice(len_q, size=1, p=nx.to_numpy(q)).item())
T = nx.tocsr(emd_1d(C1[index[0]], C2[index[1]], a=p, b=q, dense=False))
best_gw_dist_estimated = np.inf
for cpt in range(max_iter):
- index[0] = generator.choice(len_p, size=1, p=nx.to_numpy(p))
- T_index0 = nx.reshape(nx.todense(T[index[0], :]), (-1,))
- index[1] = generator.choice(
- len_q, size=1, p=nx.to_numpy(T_index0 / nx.sum(T_index0))
+ index[0] = int(generator.choice(len_p, size=1, p=nx.to_numpy(p)).item())
+ T_index0 = nx.reshape(nx.todense(T[[index[0]], :]), (-1,))
+ index[1] = int(
+ generator.choice(
+ len_q, size=1, p=nx.to_numpy(T_index0 / nx.sum(T_index0))
+ ).item()
)
if alpha == 1:
@@ -404,10 +406,15 @@ def sampled_gromov_wasserstein(
)
Lik = 0
for i, index0_i in enumerate(index0):
+ T_row = (
+ nx.reshape(nx.todense(T[[index0_i], :]), (-1,))
+ if nx.issparse(T)
+ else T[index0_i, :]
+ )
index1 = generator.choice(
len_q,
size=nb_samples_grad_q,
- p=nx.to_numpy(T[index0_i, :] / nx.sum(T[index0_i, :])),
+ p=nx.to_numpy(T_row / nx.sum(T_row)),
replace=False,
)
# If the matrices C are not symmetric, the gradient has 2 terms, thus the term is chosen randomly.
From 3a67a4f08ecc62cedae1be37da1ca6c0c135c5d5 Mon Sep 17 00:00:00 2001
From: nathanneike <nathanneike@outlook.de>
Date: Tue, 20 Jan 2026 10:47:42 +0100
Subject: [PATCH 3/8] small fix errors not appearing locally
---
ot/regpath.py | 3 +++
1 file changed, 3 insertions(+)
diff --git a/ot/regpath.py b/ot/regpath.py
index e64ca7c77..aedc35b88 100644
--- a/ot/regpath.py
+++ b/ot/regpath.py
@@ -486,6 +486,9 @@ def complement_schur(M_current, b, d, id_pop):
else:
X = M_current.dot(b)
s = d - b.T.dot(X)
+ # Ensure s is a scalar (extract from array if needed)
+ if np.ndim(s) > 0:
+ s = s.item()
M = np.zeros((n, n))
M[:-1, :-1] = M_current + X.dot(X.T) / s
X_ravel = X.ravel()
From cd610707dda74be3e0d8be883bac19cdfef84435 Mon Sep 17 00:00:00 2001
From: nathanneike <nathanneike@outlook.de>
Date: Tue, 20 Jan 2026 10:58:50 +0100
Subject: [PATCH 4/8] Fix SciPy version compatibility for distance metrics
---
ot/utils.py | 4 +++-
test/test_utils.py | 25 ++++++++++++++++++++++++-
2 files changed, 27 insertions(+), 2 deletions(-)
diff --git a/ot/utils.py b/ot/utils.py
index cc9de4f02..64bf1ace9 100644
--- a/ot/utils.py
+++ b/ot/utils.py
@@ -429,7 +429,9 @@ def dist(
else:
if isinstance(metric, str) and metric.endswith("minkowski"):
return cdist(x1, x2, metric=metric, p=p, w=w)
- if w is not None:
+ # Only pass w parameter for metrics that support it
+ # According to SciPy docs, only 'minkowski' and 'wminkowski' support w
+ if w is not None and metric in ["minkowski", "wminkowski"]:
return cdist(x1, x2, metric=metric, w=w)
return cdist(x1, x2, metric=metric)
diff --git a/test/test_utils.py b/test/test_utils.py
index 0b2769109..8c5e65b93 100644
--- a/test/test_utils.py
+++ b/test/test_utils.py
@@ -19,7 +19,7 @@
"correlation",
]
-lst_all_metrics = lst_metrics + [
+lst_all_metrics_candidates = lst_metrics + [
"braycurtis",
"canberra",
"chebyshev",
@@ -34,6 +34,18 @@
"yule",
]
+# Filter to only include metrics available in current SciPy version
+# (some metrics like sokalmichener were removed in newer SciPy versions)
+lst_all_metrics = []
+for metric in lst_all_metrics_candidates:
+ try:
+ scipy.spatial.distance.cdist(
+ np.array([[0, 0]]), np.array([[1, 1]]), metric=metric
+ )
+ lst_all_metrics.append(metric)
+ except ValueError:
+ pass
+
def get_LazyTensor(nx):
n1 = 100
@@ -240,7 +252,18 @@ def test_dist():
"seuclidean",
] # do not support weights depending on scipy's version
+ # Filter out metrics not available in current scipy version
+ from scipy.spatial.distance import cdist
+
+ available_metrics_w = []
for metric in metrics_w:
+ try:
+ cdist(x[:2], x[:2], metric=metric)
+ available_metrics_w.append(metric)
+ except ValueError:
+ pass
+
+ for metric in available_metrics_w:
print(metric)
ot.dist(x, x, metric=metric, p=3, w=rng.random((2,)))
ot.dist(
