big progress

nifty4/library/nonlinear_power_energy.py

@@ -70,7 +70,7 @@ class NonlinearPowerEnergy(Energy):
             if samples is None or samples == 0:
                 xi_sample_list = [xi]
             else:
-                xi_sample_list = [D.draw_inverse_sample() + xi
+                xi_sample_list = [D.inverse_draw_sample() + xi
                                   for _ in range(samples)]
         self.xi_sample_list = xi_sample_list
         self.inverter = inverter

nifty4/library/wiener_filter_curvature.py

@@ -16,12 +16,12 @@
 # NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik
 # and financially supported by the Studienstiftung des deutschen Volkes.
 
-from ..operators.endomorphic_operator import EndomorphicOperator
+from ..operators.sandwich_operator import SandwichOperator
 from ..operators.inversion_enabler import InversionEnabler
 import numpy as np
 
 
-class WienerFilterCurvature(EndomorphicOperator):
+def WienerFilterCurvature(R, N, S, inverter):
     """The curvature of the WienerFilterEnergy.
 
     This operator implements the second derivative of the
@@ -40,28 +40,5 @@ class WienerFilterCurvature(EndomorphicOperator):
     inverter : Minimizer
         The minimizer to use during numerical inversion
     """
-
-    def __init__(self, R, N, S, inverter):
-        super(WienerFilterCurvature, self).__init__()
-        self.R = R
-        self.N = N
-        self.S = S
-        op = R.adjoint*N.inverse*R + S.inverse
-        self._op = InversionEnabler(op, inverter, S.times)
-
-    @property
-    def domain(self):
-        return self._op.domain
-
-    @property
-    def capability(self):
-        return self._op.capability
-
-    def apply(self, x, mode):
-        return self._op.apply(x, mode)
-
-    def draw_sample(self, dtype=np.float64):
-        n = self.N.inverse_draw_sample(dtype)
-        s = self.S.inverse_draw_sample(dtype)
-
-        return s - self.R.adjoint_times(n)
+    op = SandwichOperator(R, N.inverse) + S.inverse
+    return InversionEnabler(op, inverter, S.times)

nifty4/operators/diagonal_operator.py

@@ -147,7 +147,8 @@ class DiagonalOperator(EndomorphicOperator):
         return res
 
     def draw_sample(self, dtype=np.float64):
-        if np.issubdtype(self._ldiag.dtype, np.complexfloating) or (self._ldiag <= 0.).any():
+        if (np.issubdtype(self._ldiag.dtype, np.complexfloating) or
+                (self._ldiag <= 0.).any()):
             raise ValueError("operator not positive definite")
         res = Field.from_random(random_type="normal", domain=self._domain,
                                 dtype=dtype)
@@ -155,7 +156,8 @@ class DiagonalOperator(EndomorphicOperator):
         return res
 
     def inverse_draw_sample(self, dtype=np.float64):
-        if np.issubdtype(self._ldiag.dtype, np.complexfloating) or (self._ldiag <= 0.).any():
+        if (np.issubdtype(self._ldiag.dtype, np.complexfloating) or
+                (self._ldiag <= 0.).any()):
             raise ValueError("operator not positive definite")
 
         res = Field.from_random(random_type="normal", domain=self._domain,

nifty4/operators/endomorphic_operator.py

@@ -60,7 +60,7 @@ class EndomorphicOperator(LinearOperator):
             A sample from the Gaussian of given covariance
         """
         if self.capability & self.INVERSE_TIMES:
-            x = self.draw_sample(dtype=dtype)
+            x = self.draw_sample(dtype)
             return self.inverse_times(x)
         else:
             raise NotImplementedError

nifty4/operators/inverse_operator.py

@@ -17,6 +17,7 @@
 # and financially supported by the Studienstiftung des deutschen Volkes.
 
 from .linear_operator import LinearOperator
+import numpy as np
 
 
 class InverseOperator(LinearOperator):
@@ -44,3 +45,9 @@ class InverseOperator(LinearOperator):
 
     def apply(self, x, mode):
         return self._op.apply(x, self._inverseMode[mode])
+
+    def draw_sample(self, dtype=np.float64):
+        return self._op.inverse_draw_sample(dtype)
+
+    def inverse_draw_sample(self, dtype=np.float64):
+        return self._op.draw_sample(dtype)

nifty4/operators/inversion_enabler.py

@@ -21,6 +21,7 @@ from ..minimization.iteration_controller import IterationController
 from ..field import Field
 from ..logger import logger
 from .linear_operator import LinearOperator
+import numpy as np
 
 
 class InversionEnabler(LinearOperator):
@@ -74,3 +75,15 @@ class InversionEnabler(LinearOperator):
         if stat != IterationController.CONVERGED:
             logger.warning("Error detected during operator inversion")
         return r.position
+
+    def draw_sample(self, dtype=np.float64):
+        try:
+            return self._op.draw_sample(dtype)
+        except:
+            return self(self._op.inverse_draw_sample(dtype))
+
+    def inverse_draw_sample(self, dtype=np.float64):
+        try:
+            return self._op.inverse_draw_sample(dtype)
+        except:
+            return self.inverse_times(self._op.draw_sample(dtype))

nifty4/operators/sandwich_operator.py

@@ -17,6 +17,7 @@
 # and financially supported by the Studienstiftung des deutschen Volkes.
 
 from .endomorphic_operator import EndomorphicOperator
+import numpy as np
 
 
 class SandwichOperator(EndomorphicOperator):
@@ -47,5 +48,5 @@ class SandwichOperator(EndomorphicOperator):
     def apply(self, x, mode):
         return self._op.apply(x, mode)
 
-    def draw_sample(self):
-        return self._bun.adjoint_times(self._cheese.draw_sample())
+    def draw_sample(self, dtype=np.float64):
+        return self._bun.adjoint_times(self._cheese.draw_sample(dtype))

nifty4/operators/sum_operator.py

@@ -17,6 +17,7 @@
 # and financially supported by the Studienstiftung des deutschen Volkes.
 
 from .linear_operator import LinearOperator
+import numpy as np
 
 
 class SumOperator(LinearOperator):
@@ -143,3 +144,9 @@ class SumOperator(LinearOperator):
                 else:
                     res += op.apply(x, mode)
         return res
+
+    def draw_sample(self, dtype=np.float64):
+        res = self._ops[0].draw_sample(dtype)
+        for op in self._ops[1:]:
+            res += op.draw_sample(dtype)
+        return res

nifty4/probing/utils.py

@@ -51,7 +51,7 @@ class StatCalculator(object):
 def probe_with_posterior_samples(op, post_op, nprobes):
     sc = StatCalculator()
     for i in range(nprobes):
-        sample = post_op(op.draw_inverse_sample())
+        sample = post_op(op.inverse_draw_sample())
         sc.add(sample)
 
     if nprobes == 1:

test/test_energies/test_noise.py

@@ -84,7 +84,7 @@ class Noise_Energy_Tests(unittest.TestCase):
             S=S,
             inverter=inverter).curvature
 
-        res_sample_list = [d - R(f(ht(C.draw_inverse_sample() + xi)))
+        res_sample_list = [d - R(f(ht(C.inverse_draw_sample() + xi)))
                            for _ in range(10)]
 
         energy0 = ift.library.NoiseEnergy(eta0, alpha, q, res_sample_list)