Add some reprs

nifty5/minimization/kl_energy.py

@@ -73,3 +73,7 @@ class KL_Energy(Energy):
     @property
     def samples(self):
         return self._samples
+
+    def __repr__(self):
+        return 'KL ({} samples):\n'.format(len(
+            self._samples)) + utilities.indent(self._ham.__repr__())

nifty5/operators/energy_operators.py

@@ -168,6 +168,11 @@ class Hamiltonian(EnergyOperator):
                                   self._ic_samp, prx.metric.inverse)
             return (lhx+prx).add_metric(mtr)
 
+    def __repr__(self):
+        subs = 'Likelihood:\n{}'.format(utilities.indent(self._lh.__repr__()))
+        subs += '\nPrior: Quadratic{}'.format(self._lh.domain.keys())
+        return 'Hamiltonian:\n' + utilities.indent(subs)
+
 
 class SampledKullbachLeiblerDivergence(EnergyOperator):
     def __init__(self, h, res_samples):

nifty5/operators/operator.py

@@ -2,7 +2,7 @@ from __future__ import absolute_import, division, print_function
 
 import numpy as np
 from ..compat import *
-from ..utilities import NiftyMetaBase
+from ..utilities import NiftyMetaBase, indent
 
 
 class Operator(NiftyMetaBase()):
@@ -177,6 +177,11 @@ class _OpChain(_CombinedOperator):
         return x
 
 
+    def __repr__(self):
+        subs = "\n".join(sub.__repr__() for sub in self._ops)
+        return "_OpChain:\n" + indent(subs)
+
+
 class _OpProd(Operator):
     def __init__(self, op1, op2):
         from ..sugar import domain_union
@@ -205,6 +210,11 @@ class _OpProd(Operator):
         return lin1.new(lin1._val*lin2._val, op(x.jac))
 
 
+    def __repr__(self):
+        subs = "\n".join(sub.__repr__() for sub in (self._op1, self._op2))
+        return "_OpProd:\n"+indent(subs)
+
+
 class _OpSum(Operator):
     def __init__(self, op1, op2):
         from ..sugar import domain_union
@@ -231,3 +241,7 @@ class _OpSum(Operator):
         if lin1._metric is not None and lin2._metric is not None:
             res = res.add_metric(lin1._metric + lin2._metric)
         return res
+
+    def __repr__(self):
+        subs = "\n".join(sub.__repr__() for sub in (self._op1, self._op2))
+        return "_OpSum:\n"+indent(subs)