reconnect moved files to git repo

venv/lib/python3.11/site-packages/sklearn/utils/tests/test_arrayfuncs.py

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+import numpy as np
+import pytest
+
+from sklearn.utils._testing import assert_allclose
+from sklearn.utils.arrayfuncs import _all_with_any_reduction_axis_1, min_pos
+
+
+def test_min_pos():
+    # Check that min_pos returns a positive value and that it's consistent
+    # between float and double
+    X = np.random.RandomState(0).randn(100)
+
+    min_double = min_pos(X)
+    min_float = min_pos(X.astype(np.float32))
+
+    assert_allclose(min_double, min_float)
+    assert min_double >= 0
+
+
+@pytest.mark.parametrize("dtype", [np.float32, np.float64])
+def test_min_pos_no_positive(dtype):
+    # Check that the return value of min_pos is the maximum representable
+    # value of the input dtype when all input elements are <= 0 (#19328)
+    X = np.full(100, -1.0).astype(dtype, copy=False)
+
+    assert min_pos(X) == np.finfo(dtype).max
+
+
+@pytest.mark.parametrize(
+    "dtype", [np.int16, np.int32, np.int64, np.float32, np.float64]
+)
+@pytest.mark.parametrize("value", [0, 1.5, -1])
+def test_all_with_any_reduction_axis_1(dtype, value):
+    # Check that return value is False when there is no row equal to `value`
+    X = np.arange(12, dtype=dtype).reshape(3, 4)
+    assert not _all_with_any_reduction_axis_1(X, value=value)
+
+    # Make a row equal to `value`
+    X[1, :] = value
+    assert _all_with_any_reduction_axis_1(X, value=value)