Merge branch 'spectra_partial_merge' into 'NIFTy_5'

uncontroversial changes from operator_spectra

See merge request !345

.gitignore

@@ -2,6 +2,7 @@
 git_version.py
 
 # custom
+*.txt
 setup.cfg
 .idea
 .DS_Store

demos/plot_test.py

-# This program is free software: you can redistribute it and/or modify
-# it under the terms of the GNU General Public License as published by
-# the Free Software Foundation, either version 3 of the License, or
-# (at your option) any later version.
-#
-# This program is distributed in the hope that it will be useful,
-# but WITHOUT ANY WARRANTY; without even the implied warranty of
-# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
-# GNU General Public License for more details.
-#
-# You should have received a copy of the GNU General Public License
-# along with this program.  If not, see <http://www.gnu.org/licenses/>.
-#
-# Copyright(C) 2013-2019 Max-Planck-Society
-#
-# NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik.
-
-import nifty5 as ift
-import numpy as np
-
-
-def plot_test():
-    rg_space1 = ift.makeDomain(ift.RGSpace((100,)))
-    rg_space2 = ift.makeDomain(ift.RGSpace((80, 60), distances=1))
-    hp_space = ift.makeDomain(ift.HPSpace(64))
-    gl_space = ift.makeDomain(ift.GLSpace(128))
-
-    fft = ift.FFTOperator(rg_space2)
-
-    field_rg1_1 = ift.Field.from_global_data(rg_space1, np.random.randn(100))
-    field_rg1_2 = ift.Field.from_global_data(rg_space1, np.random.randn(100))
-    field_rg2 = ift.Field.from_global_data(
-        rg_space2, np.random.randn(80*60).reshape((80, 60)))
-    field_hp = ift.Field.from_global_data(hp_space, np.random.randn(12*64**2))
-    field_gl = ift.Field.from_global_data(gl_space, np.random.randn(32640))
-    field_ps = ift.power_analyze(fft.times(field_rg2))
-
-    # Start various plotting tests
-
-    plot = ift.Plot()
-    plot.add(field_rg1_1, title='Single plot')
-    plot.output()
-
-    plot = ift.Plot()
-    plot.add(field_rg2, title='2d rg')
-    plot.add([field_rg1_1, field_rg1_2], title='list 1d rg', label=['1', '2'])
-    plot.add(field_rg1_2, title='1d rg, xmin, ymin', xmin=0.5, ymin=0.,
-             xlabel='xmin=0.5', ylabel='ymin=0')
-    plot.output(title='Three plots')
-
-    plot = ift.Plot()
-    plot.add(field_hp, title='HP planck-color', colormap='Planck-like')
-    plot.add(field_rg1_2, title='1d rg')
-    plot.add(field_ps)
-    plot.add(field_gl, title='GL')
-    plot.add(field_rg2, title='2d rg')
-    plot.output(nx=2, ny=3, title='Five plots')
-
-
-if __name__ == '__main__':
-    plot_test()

docs/source/citations.rst

@@ -17,7 +17,7 @@ NIFTy-related publications
       date = {2018-04-05},
     }
 
-    @ARTICLE{2013A&A...554A..26S,
+    @article{2013A&A...554A..26S,
       author = {{Selig}, M. and {Bell}, M.~R. and {Junklewitz}, H. and {Oppermann}, N. and {Reinecke}, M. and {Greiner}, M. and {Pachajoa}, C. and {En{\ss}lin}, T.~A.},
       title = "{NIFTY - Numerical Information Field Theory. A versatile PYTHON library for signal inference}",
       journal = {\aap},
@@ -35,7 +35,7 @@ NIFTy-related publications
       adsnote = {Provided by the SAO/NASA Astrophysics Data System}
     }
 
-    @ARTICLE{2017arXiv170801073S,
+    @article{2017arXiv170801073S,
       author = {{Steininger}, T. and {Dixit}, J. and {Frank}, P. and {Greiner}, M. and {Hutschenreuter}, S. and {Knollm{\"u}ller}, J. and {Leike}, R. and {Porqueres}, N. and {Pumpe}, D. and {Reinecke}, M. and {{\v S}raml}, M. and {Varady}, C. and {En{\ss}lin}, T.},
       title = "{NIFTy 3 - Numerical Information Field Theory - A Python framework for multicomponent signal inference on HPC clusters}",
       journal = {ArXiv e-prints},

nifty5/extra.py

@@ -70,6 +70,9 @@ def _full_implementation(op, domain_dtype, target_dtype, atol, rtol,
 
 
 def _check_linearity(op, domain_dtype, atol, rtol):
+    needed_cap = op.TIMES
+    if (op.capability & needed_cap) != needed_cap:
+        return
     fld1 = from_random("normal", op.domain, dtype=domain_dtype)
     fld2 = from_random("normal", op.domain, dtype=domain_dtype)
     alpha = np.random.random()  # FIXME: this can break badly with MPI!
@@ -121,6 +124,9 @@ def consistency_check(op, domain_dtype=np.float64, target_dtype=np.float64,
         raise TypeError('This test tests only linear operators.')
     _domain_check(op)
     _check_linearity(op, domain_dtype, atol, rtol)
+    _check_linearity(op.adjoint, target_dtype, atol, rtol)
+    _check_linearity(op.inverse, target_dtype, atol, rtol)
+    _check_linearity(op.adjoint.inverse, domain_dtype, atol, rtol)
     _full_implementation(op, domain_dtype, target_dtype, atol, rtol,
                          only_r_linear)
     _full_implementation(op.adjoint, target_dtype, domain_dtype, atol, rtol,

nifty5/fft.py

@@ -26,7 +26,7 @@ def nthreads():
 
 def set_nthreads(nthr):
     global _nthreads
-    _nthreads = nthr
+    _nthreads = int(nthr)
 
 
 def fftn(a, axes=None):

nifty5/library/gridder.py

@@ -15,12 +15,13 @@
 #
 # NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik.
 
+import numpy as np
+
 from ..domain_tuple import DomainTuple
 from ..domains.rg_space import RGSpace
 from ..domains.unstructured_domain import UnstructuredDomain
 from ..operators.linear_operator import LinearOperator
 from ..sugar import from_global_data, makeDomain
-import numpy as np
 
 
 class GridderMaker(object):

nifty5/minimization/conjugate_gradient.py

@@ -74,27 +74,27 @@ class ConjugateGradient(Minimizer):
         if previous_gamma == 0:
             return energy, controller.CONVERGED
 
-        iter = 0
+        ii = 0
         while True:
             q = energy.apply_metric(d)
-            ddotq = d.vdot(q).real
-            if ddotq == 0.:
-                logger.error("Error: ConjugateGradient: ddotq==0.")
+            curv = d.vdot(q).real
+            if curv == 0.:
+                logger.error("Error: ConjugateGradient: curv==0.")
                 return energy, controller.ERROR
-            alpha = previous_gamma/ddotq
+            alpha = previous_gamma/curv
 
             if alpha < 0:
                 logger.error("Error: ConjugateGradient: alpha<0.")
                 return energy, controller.ERROR
 
-            iter += 1
-            if iter < self._nreset:
+            ii += 1
+            if ii < self._nreset:
                 r = r - q*alpha
                 energy = energy.at_with_grad(energy.position - alpha*d, r)
             else:
                 energy = energy.at(energy.position - alpha*d)
                 r = energy.gradient
-                iter = 0
+                ii = 0
 
             s = r if preconditioner is None else preconditioner(r)
 

nifty5/operators/block_diagonal_operator.py

@@ -15,6 +15,8 @@
 #
 # NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik.
 
+import numpy as np
+
 from ..multi_domain import MultiDomain
 from ..multi_field import MultiField
 from .endomorphic_operator import EndomorphicOperator
@@ -46,11 +48,10 @@ class BlockDiagonalOperator(EndomorphicOperator):
                     for op, v in zip(self._ops, x.values()))
         return MultiField(self._domain, val)
 
-#    def draw_sample(self, from_inverse=False, dtype=np.float64):
-#        dtype = MultiField.build_dtype(dtype, self._domain)
-#        val = tuple(op.draw_sample(from_inverse, dtype)
-#                    for op in self._op)
-#        return MultiField(self._domain, val)
+    def draw_sample(self, from_inverse=False, dtype=np.float64):
+        val = tuple(op.draw_sample(from_inverse, dtype)
+                    if op is not None else None for op in self._ops)
+        return MultiField(self._domain, val)
 
     def _combine_chain(self, op):
         if self._domain != op._domain: