Merge branch 'main' of https://github.com/tslearn-team/tslearn

docs/requirements_rtd.txt

@@ -12,5 +12,5 @@ tensorflow>=2
 Pygments
 numba
 sphinx_bootstrap_theme
-git+git://github.com/numpy/numpydoc@master
+git+git://github.com/numpy/numpydoc@main
 matplotlib

pyproject.toml

@@ -1,2 +1,2 @@
 [build-system]
-requires = ["setuptools", "wheel", "numpy", "Cython"]
+requires = ["setuptools", "wheel", "numpy<=1.19", "Cython"]

tslearn/metrics/dtw_variants.py

@@ -189,6 +189,9 @@ def dtw_path(s1, s2, global_constraint=None, sakoe_chiba_radius=None,
     s1 = to_time_series(s1, remove_nans=True)
     s2 = to_time_series(s2, remove_nans=True)
 
+    if len(s1) == 0 or len(s2) == 0:
+        raise ValueError("One of the input time series contains only nans or has zero length.")
+
     mask = compute_mask(
         s1, s2, GLOBAL_CONSTRAINT_CODE[global_constraint],
         sakoe_chiba_radius, itakura_max_slope

tslearn/tests/test_metrics.py

@@ -1,8 +1,10 @@
+import pytest
 import numpy as np
 from scipy.spatial.distance import cdist
 import tslearn.metrics
 import tslearn.clustering
 from tslearn.utils import to_time_series
+from tslearn.metrics.dtw_variants import dtw_path
 
 __author__ = 'Romain Tavenard romain.tavenard[at]univ-rennes2.fr'
 
@@ -426,3 +428,16 @@ def test_softdtw():
 
     np.testing.assert_equal(dist, dist_ref ** 2)
     np.testing.assert_allclose(matrix_path, mat_path_ref)
+
+
+def test_dtw_path_with_empty_or_nan_inputs():
+    s1 = np.zeros((3, 10))
+    s2_empty = np.zeros((0, 10))
+    with pytest.raises(ValueError) as excinfo:
+        dtw_path(s1, s2_empty)
+    assert str(excinfo.value) == "One of the input time series contains only nans or has zero length."
+
+    s2_nan = np.full((3, 10), np.nan)
+    with pytest.raises(ValueError) as excinfo:
+        dtw_path(s1, s2_nan)
+    assert str(excinfo.value) == "One of the input time series contains only nans or has zero length."