adjust a few demos

demos/bernoulli_demo.py

@@ -53,7 +53,7 @@ if __name__ == '__main__':
     A = pd(a)
 
     # Set up a sky model
-    sky = lambda inp: HT(A*inp).positive_tanh()
+    sky = HT.chain(ift.makeOp(A)).positive_tanh()
 
     GR = ift.GeometryRemover(position_space)
     # Set up instrumental response

demos/getting_started_2.py

@@ -70,7 +70,7 @@ if __name__ == '__main__':
     A = pd(a)
 
     # Set up a sky model
-    sky = lambda inp: (HT(inp*A)).exp()
+    sky = HT.chain(ift.makeOp(A)).exp()
 
     M = ift.DiagonalOperator(exposure)
     GR = ift.GeometryRemover(position_space)

nifty5/operators/operator.py

@@ -25,10 +25,7 @@ class Operator(NiftyMetaBase()):
     def __matmul__(self, x):
         if not isinstance(x, Operator):
             return NotImplemented
-        return OpChain.make((self, x))
-        ops1 = self._ops if isinstance(self, OpChain) else (self,)
-        ops2 = x._ops if isinstance(x, OpChain) else (x,)
-        return OpChain(ops1+ops2)
+        return _OpChain.make((self, x))
 
     def chain(self, x):
         res = self.__matmul__(x)
@@ -52,6 +49,25 @@ class Operator(NiftyMetaBase()):
         raise NotImplementedError
 
 
+for f in ["sqrt", "exp", "log", "tanh", "positive_tanh"]:
+    def func(f):
+        def func2(self):
+            fa = _FunctionApplier(self._target, f)
+            return _OpChain.make((fa, self))
+        return func2
+    setattr(Operator, f, func(f))
+
+
+class _FunctionApplier(Operator):
+    def __init__(self, domain, funcname):
+        from ..sugar import makeDomain
+        self._domain = self._target = makeDomain(domain)
+        self._funcname = funcname
+
+    def __call__(self, x):
+        return getattr(x, self._funcname)()
+
+
 class _CombinedOperator(Operator):
     def __init__(self, ops, _callingfrommake=False):
         if not _callingfrommake:
@@ -62,7 +78,7 @@ class _CombinedOperator(Operator):
     def unpack(cls, ops, res):
         for op in ops:
             if isinstance(op, cls):
-                res = cls.unpack(op, res)
+                res = cls.unpack(op._ops, res)
             else:
                 res = res + [op]
         return res