Merge branch 'develop' into documentation

pyerrors/linalg.py

@@ -86,7 +86,7 @@ def derived_array(func, data, **kwargs):
     for name in new_names:
         d_extracted[name] = []
         for i_dat, dat in enumerate(data):
-            ens_length = new_idl_d[name][-1] - new_idl_d[name][0] + 1
+            ens_length = len(new_idl_d[name])
             d_extracted[name].append(np.array([_expand_deltas_for_merge(o.deltas[name], o.idl[name], o.shape[name], new_idl_d[name]) for o in dat.reshape(np.prod(dat.shape))]).reshape(dat.shape + (ens_length, )))
 
     for i_val, new_val in np.ndenumerate(new_values):

pyerrors/obs.py

@@ -248,7 +248,7 @@ class Obs:
 
             r_length = []
             for r_name in e_content[e_name]:
-                if self.idl[r_name] is range:
+                if isinstance(self.idl[r_name], range):
                     r_length.append(len(self.idl[r_name]))
                 else:
                     r_length.append((self.idl[r_name][-1] - self.idl[r_name][0] + 1))
@@ -339,7 +339,7 @@ class Obs:
         idx     -- List or range of configs on which the deltas are defined.
         shape   -- Number of configs in idx.
         """
-        if type(idx) is range:
+        if isinstance(idx, range):
             return deltas
         else:
             ret = np.zeros(idx[-1] - idx[0] + 1)

tests/linalg_test.py

@@ -51,6 +51,29 @@ def test_multi_dot():
             assert e.is_zero(), t
 
 
+def test_matmul_irregular_histories():
+    dim = 2
+    length = 500
+
+    standard_array = []
+    for i in range(dim ** 2):
+        standard_array.append(pe.Obs([np.random.normal(1.1, 0.2, length)], ['ens1']))
+    standard_matrix = np.array(standard_array).reshape((dim, dim))
+
+    for idl in [range(1, 501, 2), range(250, 273), [2, 8, 19, 20, 78]]:
+        irregular_array = []
+        for i in range(dim ** 2):
+            irregular_array.append(pe.Obs([np.random.normal(1.1, 0.2, len(idl))], ['ens1'], idl=[idl]))
+        irregular_matrix = np.array(irregular_array).reshape((dim, dim))
+
+        t1 = standard_matrix @ irregular_matrix
+        t2 = pe.linalg.matmul(standard_matrix, irregular_matrix)
+
+        assert np.all([o.is_zero() for o in (t1 - t2).ravel()])
+        assert np.all([o.is_merged for o in t1.ravel()])
+        assert np.all([o.is_merged for o in t2.ravel()])
+
+
 def test_matrix_inverse():
     content = []
     for t in range(9):