Fixed #1006 RuntimeWarning divide by zero encountered in divide

stumpy/core.py

@@ -2254,6 +2254,7 @@ def preprocess_diagonal(
 
     M_T, Σ_T = compute_mean_std(T, m)
     Σ_T[T_subseq_isconstant] = 1.0  # Avoid divide by zero in next inversion step
+    Σ_T[~T_subseq_isfinite] = 1.0
     Σ_T_inverse = 1.0 / Σ_T
     M_T_m_1, _ = compute_mean_std(T, m - 1)
 

tests/test_core.py

@@ -1,6 +1,7 @@
 import functools
 import math
 import os
+import warnings
 from unittest.mock import patch
 
 import naive
@@ -880,9 +881,11 @@ def test_preprocess_non_normalized():
 def test_preprocess_diagonal():
     T = np.array([0, np.nan, 2, 3, 4, 5, 6, 7, np.inf, 9])
     m = 3
+    T_subseq_isfinite = core.rolling_isfinite(T, m)
 
     ref_T = np.array([0, 0, 2, 3, 4, 5, 6, 7, 0, 9], dtype=float)
     ref_M, ref_Σ = naive.compute_mean_std(ref_T, m)
+    ref_Σ[~T_subseq_isfinite] = 1.0
     ref_Σ_inverse = 1.0 / ref_Σ
     ref_M_m_1, _ = naive.compute_mean_std(ref_T, m - 1)
 
@@ -1753,3 +1756,16 @@ def test_process_isconstant_2d():
     T_subseq_isconstant_comp = core.process_isconstant(T, m, T_subseq_isconstant)
 
     npt.assert_array_equal(T_subseq_isconstant_ref, T_subseq_isconstant_comp)
+
+
+def test_preprocess_diagonal_std_inverse():
+    T = np.random.rand(64)
+    m = 3
+    T[:m] = np.nan
+
+    with warnings.catch_warnings(record=True) as w:
+        warnings.simplefilter("always")
+        core.preprocess_diagonal(T, m)
+        for item in w:
+            if issubclass(item.category, RuntimeWarning):
+                assert "divide by zero encountered in divide" not in str(item.message)