more __repr__ work

nifty5/operators/diagonal_operator.py

@@ -157,17 +157,21 @@ class DiagonalOperator(EndomorphicOperator):
             xdiag = 1./xdiag
         return self._from_ldiag((), xdiag)
 
-    def draw_sample(self, from_inverse=False, dtype=np.float64):
-        if self._complex:
-            raise ValueError("operator not positive definite")
-        if self._diagmin < 0.:
-            raise ValueError("operator not positive definite")
-        if self._diagmin == 0. and from_inverse:
-            raise ValueError("operator not positive definite")
-        res = Field.from_random(random_type="normal", domain=self._domain,
-                                dtype=dtype)
+    def process_sample(self, samp, from_inverse):
+        if (self._complex or (self._diagmin < 0.) or
+            (self._diagmin == 0. and from_inverse)):
+                raise ValueError("operator not positive definite")
         if from_inverse:
-            res = res.local_data/np.sqrt(self._ldiag)
+            res = samp.local_data/np.sqrt(self._ldiag)
         else:
-            res = res.local_data*np.sqrt(self._ldiag)
+            res = samp.local_data*np.sqrt(self._ldiag)
         return Field.from_local_data(self._domain, res)
+
+    def draw_sample(self, from_inverse=False, dtype=np.float64):
+        res = Field.from_random(random_type="normal", domain=self._domain,
+                                dtype=dtype)
+        return self.process_sample(res, from_inverse)
+
+    def __repr__(self):
+        subs = utilities.indent(self._domain.__repr__())
+        return "DiagonalOperator:\n  Spaces={}\n".format(self._spaces) + subs

nifty5/operators/operator_adapter.py

@@ -66,3 +66,9 @@ class OperatorAdapter(LinearOperator):
         if self._trafo & self.INVERSE_BIT:
             return self._op.draw_sample(not from_inverse, dtype)
         return self._op.draw_sample(from_inverse, dtype)
+
+    def __repr__(self):
+        from ..utilities import indent
+        mode = ["adjoint", "inverse", "adjoint inverse"][self._trafo]
+        res = "OperatorAdapter: {}\n".format(mode)
+        return res + indent(self._op.__repr__())

nifty5/operators/sampling_enabler.py

@@ -79,3 +79,11 @@ class SamplingEnabler(EndomorphicOperator):
 
     def apply(self, x, mode):
         return self._op.apply(x, mode)
+
+    def __repr__(self):
+        from ..utilities import indent
+        return "\n".join((
+            "SamplingEnabler:",
+            indent("\n".join((
+                "Likelihood:", self._likelihood.__repr__(),
+                "Prior:", self._prior.__repr__())))))

nifty5/operators/sandwich_operator.py

@@ -72,7 +72,7 @@ class SandwichOperator(EndomorphicOperator):
     def draw_sample(self, from_inverse=False, dtype=np.float64):
         # Inverse samples from general sandwiches are not possible
         if from_inverse:
-            if self._bun.capabilities & self._bun.INVERSE_TIMES:
+            if self._bun.capability & self._bun.INVERSE_TIMES:
                 try:
                     s = self._cheese.draw_sample(from_inverse, dtype)
                     return self._bun.inverse_times(s)
@@ -84,3 +84,11 @@ class SandwichOperator(EndomorphicOperator):
         # Samples from general sandwiches
         return self._bun.adjoint_times(
             self._cheese.draw_sample(from_inverse, dtype))
+
+    def __repr__(self):
+        from ..utilities import indent
+        return "\n".join((
+            "SandwichOperator:",
+            indent("\n".join((
+                "Cheese:", self._cheese.__repr__(),
+                "Bun:", self._bun.__repr__())))))