Fix MatrixProductOperator

nifty5/operators/simple_linear_operators.py

@@ -364,20 +364,19 @@ class MatrixProductOperator(EndomorphicOperator):
         `dot()` and `transpose()` in the style of numpy arrays.
     """
     def __init__(self, domain, matrix):
-        self._domain = domain
+        self._domain = DomainTuple.make(domain)
+        shp = self._domain.shape
+        if len(shp) > 1:
+            raise TypeError('Only 1D-domain supported yet.')
+        if matrix.shape != (*shp, *shp):
+            raise ValueError
         self._capability = self.TIMES | self.ADJOINT_TIMES
-
         self._mat = matrix
-        self._mat_tr = matrix.transpose()
+        self._mat_tr = matrix.transpose().conjugate()
 
     def apply(self, x, mode):
         self._check_input(x, mode)
         res = x.to_global_data()
-        if mode == self.TIMES:
-            res = self._mat.dot(res)
-        if mode == self.ADJOINT_TIMES:
-            res = self._mat_tr.dot(res)
+        f = self._mat.dot if mode == self.TIMES else self._mat_tr.dot
+        res = f(res)
         return Field.from_global_data(self._domain, res)
-
-    def __repr__(self):
-        return "MatrixProductOperator"

test/test_operators/test_adjoint.py

@@ -297,6 +297,18 @@ def testValueInserter(sp, seed):
     ift.extra.consistency_check(op)
 
 
+@pmp('sp', [ift.RGSpace(10)])
+@pmp('seed', [12, 3])
+def testMatrixProductOperator(sp, seed):
+    np.random.seed(seed)
+    mat = np.random.randn(*sp.shape, *sp.shape)
+    op = ift.MatrixProductOperator(sp, mat)
+    ift.extra.consistency_check(op)
+    mat = mat + 1j*np.random.randn(*sp.shape, *sp.shape)
+    op = ift.MatrixProductOperator(sp, mat)
+    ift.extra.consistency_check(op)
+
+
 @pmp('seed', [12, 3])
 def testPartialExtractor(seed):
     np.random.seed(seed)