Merge remote-tracking branch 'origin/NIFTy_6' into NIFTy_7

README.md

@@ -142,3 +142,85 @@ and a citation to one of the [publications](http://ift.pages.mpcdf.de/nifty/cita
 The NIFTy package is licensed under the terms of the
 [GPLv3](https://www.gnu.org/licenses/gpl.html) and is distributed
 *without any warranty*.
+
+
+Contributors
+------------
+Find the list of all people who authored commits in this repository.
+
+### NIFTy6
+
+- Andrija Kostic
+- Gordian Edenhofer
+- Lukas Platz
+- Martin Reinecke
+- [Philipp Arras](https://wwwmpa.mpa-garching.mpg.de/~parras/)
+- Philipp Frank
+- Philipp Haim
+- [Reimar Heinrich Leike](https://wwwmpa.mpa-garching.mpg.de/~reimar/)
+- Rouven Lemmerz
+- [Torsten Enßlin](https://wwwmpa.mpa-garching.mpg.de/~ensslin/)
+- Vincent Eberle
+
+
+### NIFTy5
+
+- Christoph Lienhard
+- Gordian Edenhofer
+- Jakob Knollmüller
+- Julia Stadler
+- Julian Rüstig
+- Lukas Platz
+- Martin Reinecke
+- Max-Niklas Newrzella
+- Natalia
+- [Philipp Arras](https://wwwmpa.mpa-garching.mpg.de/~parras/)
+- Philipp Frank
+- Philipp Haim
+- Reimar Heinrich Leike
+- Sebastian Hutschenreuter
+- Silvan Streit
+- [Torsten Enßlin](https://wwwmpa.mpa-garching.mpg.de/~ensslin/)
+
+
+### NIFTy4
+
+- Christoph Lienhard
+- Jakob Knollmüller
+- Lukas Platz
+- Martin Reinecke
+- Mihai Baltac
+- [Philipp Arras](https://wwwmpa.mpa-garching.mpg.de/~parras/)
+- Philipp Frank
+- Reimar Heinrich Leike
+- Silvan Streit
+- [Torsten Enßlin](https://wwwmpa.mpa-garching.mpg.de/~ensslin/)
+
+
+### NIFTy3
+
+- Daniel Pumpe
+- Jait Dixit
+- Jakob Knollmüller
+- Martin Reinecke
+- Mihai Baltac
+- Natalia
+- [Philipp Arras](https://wwwmpa.mpa-garching.mpg.de/~parras/)
+- Philipp Frank
+- Reimar Heinrich Leike
+- Matevz Sraml
+- Theo Steininger
+- csongor
+
+### NIFTy2
+
+- Jait Dixit
+- Theo Steininger
+- csongor
+
+
+### NIFTy1
+
+- Johannes Buchner
+- Marco Selig
+- Theo Steininger

demos/getting_started_5_mf.py

@@ -116,7 +116,7 @@ if __name__ == '__main__':
                                              iteration_limit=35)
     ic_sampling.enable_logging()
     ic_newton.enable_logging()
-    minimizer = ift.NewtonCG(ic_newton, activate_logging=True)
+    minimizer = ift.NewtonCG(ic_newton, enable_logging=True)
 
     ## number of samples used to estimate the KL
     N_samples = 20

src/minimization/descent_minimizers.py

@@ -167,7 +167,7 @@ class NewtonCG(DescentMinimizer):
 
     def __init__(self, controller, napprox=0, line_searcher=None, name=None,
                  nreset=20, max_cg_iterations=200, energy_reduction_factor=0.1,
-                 activate_logging=False):
+                 enable_logging=False):
         if line_searcher is None:
             line_searcher = LineSearch(preferred_initial_step_size=1.)
         super(NewtonCG, self).__init__(controller=controller,
@@ -178,7 +178,7 @@ class NewtonCG(DescentMinimizer):
         self._max_cg_iterations = max_cg_iterations
         self._alpha = energy_reduction_factor
         from .iteration_controllers import EnergyHistory
-        self._history = EnergyHistory() if activate_logging else None
+        self._history = EnergyHistory() if enable_logging else None
 
     def get_descent_direction(self, energy, old_value=None):
         if old_value is None:

src/minimization/iteration_controllers.py

@@ -43,7 +43,7 @@ class IterationController(metaclass=NiftyMeta):
 
     For analyzing minimization procedures IterationControllers can log energy
     values together with the respective time stamps. In order to activate this
-    feature `activate_logging()` needs to be called.
+    feature `enable_logging()` needs to be called.
     """
 
     CONVERGED, CONTINUE, ERROR = list(range(3))
@@ -107,6 +107,9 @@ class EnergyHistory(object):
     def reset(self):
         self._lst = []
 
+    def __getitem__(self, i):
+        return self._lst[i]
+
     @property
     def time_stamps(self):
         return [x for x, _ in self._lst]

src/operators/einsum.py

@@ -262,8 +262,11 @@ class LinearEinsum(LinearOperator):
         iss, oss, *_ = subscripts.split("->")
         iss_spl = iss.split(",")
 
-        adj_iss = ",".join((",".join(iss_spl[:-1]), oss))
-        self._adj_sscr = "->".join((adj_iss, iss_spl[-1]))
+        if len(iss_spl) == 1:
+            self._adj_sscr = "->".join((oss, iss))
+        else:
+            adj_iss = ",".join((",".join(iss_spl[:-1]), oss))
+            self._adj_sscr = "->".join((adj_iss, iss_spl[-1]))
         self._capability = self.TIMES | self.ADJOINT_TIMES
 
     def apply(self, x, mode):

test/test_kl.py

@@ -94,7 +94,7 @@ def test_kl(constants, point_estimates, mirror_samples, mf):
 
     # Test constants (after some minimization)
     cg = ift.GradientNormController(iteration_limit=5)
-    minimizer = ift.NewtonCG(cg, activate_logging=True)
+    minimizer = ift.NewtonCG(cg, enable_logging=True)
     kl, _ = minimizer(kl)
     if len(constants) != 2:
         assert_(len(minimizer.inversion_history) > 0)

test/test_operators/test_einsum.py

@@ -111,6 +111,23 @@ class _SwitchSpacesOperator(ift.LinearOperator):
         return ift.Field(self._tgt(mode), np.moveaxis(x.val, *args))
 
 
+def test_linear_einsum_transpose(space1, space2, dtype, n_invocations=10):
+    dom = ift.DomainTuple.make((space1, space2))
+    mf = ift.MultiField.from_dict({})
+    ss = "ij->ji"
+    le = ift.LinearEinsum(dom, mf, ss)
+    assert_(consistency_check(le, domain_dtype=dtype, target_dtype=dtype) is None)
+
+    # SwitchSpacesOperator is equivalent to LinearEinsum with "ij->ji"
+    le_ift = _SwitchSpacesOperator(dom, 1)
+
+    for _ in range(n_invocations):
+        r = ift.from_random(le.domain, "normal", dtype=dtype)
+        assert_allclose(le(r).val, le_ift(r).val)
+        r_adj = ift.from_random(le.target, "normal", dtype=dtype)
+        assert_allclose(le.adjoint(r_adj).val, le_ift.adjoint(r_adj).val)
+
+
 def test_multi_linear_einsum_outer(space1, space2, dtype):
     ntries = 10
     n_invocations = 5