chore: raise minimum Python version to 3.11

.github/workflows/ci.yml

@@ -26,7 +26,7 @@ jobs:
       fail-fast: false
       matrix:
         os: [ubuntu-latest, macos-latest, windows-latest]
-        python-version: ["3.10", "3.11", "3.12", "3.13", "3.14"]
+        python-version: ["3.11", "3.12", "3.13", "3.14"]
 
     steps:
       - name: Checkout

.pre-commit-config.yaml

@@ -22,7 +22,7 @@ repos:
 
       # Python syntax upgrades (should run before linting/formatting)
 -   repo: https://github.com/asottile/pyupgrade
-    rev: v3.21.2
+    rev: v3.22.0
     hooks:
     -   id: pyupgrade
         args: ["--py311-plus"]
@@ -36,7 +36,7 @@ repos:
 
       # Ruff for linting and formatting Python files
 -   repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.16.9
+    rev: v0.17.1
     hooks:
     -   id: ruff-check
         args: ["--fix"]
@@ -66,7 +66,7 @@ repos:
 
       # Keep pre-commit itself up to date (run last)
 -   repo: https://gitlab.com/vojko.pribudic.foss/pre-commit-update
-    rev: v0.9.0
+    rev: v0.10.0
     hooks:
     -   id: pre-commit-update
         args: ["--verbose", "--exclude", "cffconvert"]

README.md

@@ -3,7 +3,7 @@
 ![Buscar Logo](https://raw.githubusercontent.com/WayScience/buscar/main/logo/with-text-for-light-bg.svg)
 
 [![DOI](https://img.shields.io/badge/DOI-10.64898%2F2026.04.15.718737-blue)](https://doi.org/10.64898/2026.04.15.718737)
-[![Python](https://img.shields.io/badge/python-3.10%20%7C%203.11%20%7C%203.12%20%7C%203.13%20%7C%203.14-blue)](https://github.com/axiomcura/buscar/blob/main/pyproject.toml)
+[![Python](https://img.shields.io/badge/python-3.11%20%7C%203.12%20%7C%203.13%20%7C%203.14-blue)](https://github.com/axiomcura/buscar/blob/main/pyproject.toml)
 
 ## About
 

pyproject.toml

@@ -17,14 +17,13 @@ description = "A Python framework for prioritizing compounds in high-content ima
 authors = [{ name = "Erik Serrano", email = "erik.serrano@cuanschutz.edu" }]
 readme = "README.md"
 license = "BSD-3-Clause"
-requires-python = ">=3.10,<3.15"
+requires-python = ">=3.11,<3.15"
 dynamic = ["version"]
 keywords = ["single-cell", "drug-screening", "image-profiling", "phenotypic-screening"]
 classifiers = [
   "Development Status :: 3 - Alpha",
   "Intended Audience :: Science/Research",
   "Programming Language :: Python :: 3",
-  "Programming Language :: Python :: 3.10",
   "Programming Language :: Python :: 3.11",
   "Programming Language :: Python :: 3.12",
   "Programming Language :: Python :: 3.13",
@@ -62,7 +61,7 @@ addopts = "-ra"
 testpaths = ["tests"]
 
 [tool.ruff]
-target-version = "py310"
+target-version = "py311"
 line-length = 88
 
 [tool.ruff.lint]

tests/test_metrics.py

@@ -103,6 +103,58 @@ def test_emd_direct(synthetic_profiles):
     assert emd > 0.0
 
 
+@pytest.mark.parametrize(
+    ("target", "treated", "expected"),
+    [
+        pytest.param(
+            [[0], [1], [3]],
+            [[3], [0], [1]],
+            0.0,
+            id="1d-identical-reordered",
+        ),
+        pytest.param(
+            [[0], [0], [2]],
+            [[0], [2], [2], [2]],
+            # 5/12 of the mass must move between 0 and 2 at a squared cost of 4
+            5 / 3,
+            id="1d-unequal-sample-sizes",
+        ),
+        pytest.param(
+            [[0, 0], [0, 1], [0, 2]],
+            [[3, 4], [3, 5], [3, 6]],
+            # every sample moves by (3, 4): squared distance 9 + 16 = 25
+            25.0,
+            id="2d-translation",
+        ),
+        pytest.param(
+            [[0, 0], [2, 2], [0, 0], [2, 2]],
+            [[0, 2], [2, 0], [0, 2], [2, 0]],
+            # same marginals, but every pairing costs a squared distance of 4
+            4.0,
+            id="2d-same-marginals-different-joint",
+        ),
+    ],
+)
+def test_compute_earth_movers_distance_matches_analytic_solution(
+    target, treated, expected
+):
+    """Check EMD against analytical costs for empirical distributions.
+
+    The ground metric is squared Euclidean distance (the ``ot.dist`` default),
+    so expected values are minimal *squared*-distance transport costs. All
+    samples are used (no subsampling) so every case has an exact solution.
+    """
+    features = [f"Feature_{i}" for i in range(len(target[0]))]
+    schema = {feature: pl.Float64 for feature in features}
+
+    target_df = pl.DataFrame(target, schema=schema, orient="row")
+    treated_df = pl.DataFrame(treated, schema=schema, orient="row")
+
+    actual = compute_earth_movers_distance(target_df, treated_df)
+
+    assert actual == pytest.approx(expected, rel=1e-9, abs=1e-12)
+
+
 def test_calculate_score_small_group_returns_nan_not_zero():
     """A too-small treated group must not silently report a 0.0 off-score.