test: added additional tests for non-overlapping configurations.

tests/obs_test.py

@@ -1038,6 +1038,7 @@ def test_hash():
     assert hash(obs) != hash(o1)
     assert hash(o1) != hash(o2)
 
+
 def test_gm_alias():
     samples = np.random.rand(500)
 
@@ -1049,3 +1050,55 @@ def test_gm_alias():
 
     assert np.isclose(tt1.dvalue, tt2.dvalue)
 
+
+def test_overlapping_missing_cnfgs():
+    length = 200000
+
+    l_samp = np.random.normal(2.87, 0.5, length)
+    s_samp = np.random.normal(7.87, 0.7, length // 2)
+
+    o1 = pe.Obs([l_samp], ["test"])
+    o2 = pe.Obs([s_samp], ["test"], idl=[range(1, length, 2)])
+
+    a2 = pe.Obs([s_samp], ["alt"])
+    t1 = o1 + o2
+    t1.gm(S=0)
+
+    t2 = o1 + a2
+    t2.gm(S=0)
+    assert np.isclose(t1.dvalue, t2.dvalue, rtol=0.01)
+
+
+def test_non_overlapping_missing_cnfgs():
+    length = 100000
+
+    xsamp = np.random.normal(1.0, 1.0, length)
+
+
+    full = pe.Obs([xsamp], ["ensemble"], idl=[range(0, length)])
+    full.gm()
+
+    even = pe.Obs([xsamp[0:length:2]], ["ensemble"], idl=[range(0, length, 2)])
+    odd = pe.Obs([xsamp[1:length:2]], ["ensemble"], idl=[range(1, length, 2)])
+
+    average = (even + odd) / 2
+    average.gm(S=0)
+    assert np.isclose(full.dvalue, average.dvalue, rtol=0.01)
+
+
+def test_non_overlapping_product():
+    length = 100000
+
+    samples = np.random.normal(0.93, 0.5, length)
+
+    e = pe.Obs([samples[0:length:2]], ["ensemble"], idl=[range(0, length, 2)])
+    o = pe.Obs([samples[1:length:2]], ["ensemble"], idl=[range(1, length, 2)])
+    prod1 = e * o
+    prod1.gm(S=0)
+
+    e2 = pe.Obs([samples[0:length:2]], ["even"])
+    o2 = pe.Obs([samples[1:length:2]], ["odd"])
+    prod2 = e2 * o2
+    prod2.gm(S=0)
+
+    assert np.isclose(prod1.dvalue, prod2.dvalue, rtol=0.01)