Merge branch 'develop' into documentation

pyerrors/linalg.py

@@ -203,7 +203,12 @@ def cholesky(x):
     return _mat_mat_op(anp.linalg.cholesky, x)
 
 
-def scalar_mat_op(op, obs, **kwargs):
+def det(x):
+    """Determinant of Obs valued matrices."""
+    return _scalar_mat_op(anp.linalg.det, x)
+
+
+def _scalar_mat_op(op, obs, **kwargs):
     """Computes the matrix to scalar operation op to a given matrix of Obs."""
     def _mat(x, **kwargs):
         dim = int(np.sqrt(len(x)))

pyerrors/obs.py

@@ -1052,11 +1052,10 @@ def derived_observable(func, data, array_mode=False, **kwargs):
     raveled_data = data.ravel()
 
     # Workaround for matrix operations containing non Obs data
-    if array_mode is True:
-        if not all(isinstance(x, Obs) for x in raveled_data):
-            for i in range(len(raveled_data)):
-                if isinstance(raveled_data[i], (int, float)):
-                    raveled_data[i] = cov_Obs(raveled_data[i], 0.0, "###dummy_covobs###")
+    if not all(isinstance(x, Obs) for x in raveled_data):
+        for i in range(len(raveled_data)):
+            if isinstance(raveled_data[i], (int, float)):
+                raveled_data[i] = cov_Obs(raveled_data[i], 0.0, "###dummy_covobs###")
 
     allcov = {}
     for o in raveled_data:

tests/linalg_test.py

@@ -311,6 +311,9 @@ def test_matrix_functions():
     for (i, j), entry in np.ndenumerate(diff):
         assert entry.is_zero()
 
+    # Check determinant
+    assert pe.linalg.det(np.diag(np.diag(matrix))) == np.prod(np.diag(matrix))
+
 
 def test_complex_matrix_operations():
     dimension = 4