tests

src/library/variational_models.py

@@ -179,7 +179,7 @@ class GaussianEntropy(EnergyOperator):
         self._check_input(x)
         res = -0.5*(2*np.pi*np.e*x**2).log().sum()
         if not isinstance(x, Linearization):
-            return Field.scalar(res)
+            return res
         if not x.want_metric:
             return res
         # FIXME not sure about metric

test/test_operators/test_diagonal_selector.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) 2013-2020 Max-Planck-Society
+#
+# NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik.
+
+import numpy as np
+from numpy.testing import assert_allclose
+
+import nifty7 as ift
+
+from ...nifty7.library.variational_models import DiagonalSelector
+
+
+def test_diagonal_selector():
+    N = 42
+    square_space = ift.RGSpace([N,N])
+    linear_space = ift.RGSpace(N)
+    myField = ift.from_random(square_space)
+    myDiagonalSelector = DiagonalSelector(square_space)
+    selected = myDiagonalSelector(myField).val
+    np_selected = np.diag(myField.val)
+    assert_allclose(np_selected, selected)
+    

test/test_operators/test_gaussian_entropy.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) 2013-2020 Max-Planck-Society
+#
+# NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik.
+
+import numpy as np
+from numpy.testing import assert_allclose
+
+import nifty7 as ift
+
+from ...nifty7.library.variational_models import GaussianEntropy
+
+
+def test_gaussian_entropy():
+    N = 42
+    linear_space = ift.RGSpace(N)
+    myField = ift.from_random(linear_space, 'uniform')
+    vals = myField.val
+    entropy = - 0.5 * np.sum(np.log(2 * vals**2 * np.pi * np.e)) # minus due to subtraction in KL
+    myEntropy = GaussianEntropy(myField.domain)
+    assert_allclose(entropy, myEntropy(myField).val)
+    

test/test_operators/test_lower_triangular_inserter.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) 2013-2020 Max-Planck-Society
+#
+# NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik.
+
+import numpy as np
+from numpy.testing import assert_allclose
+
+import nifty7 as ift
+
+from ...nifty7.library.variational_models import LowerTriangularInserter
+
+
+def test_lower_triangular_inserter():
+    N = 42
+    square_space = ift.RGSpace([N,N])
+    myInserter = LowerTriangularInserter(square_space)
+    flat_space = myInserter.domain
+    assert_allclose(flat_space.size, N*(N+1)//2)
+
+    myField = ift.from_random(flat_space)
+    myMatrix = myInserter(myField)
+
+    assert_allclose(np_selected, selected)
+
+    upper_i = []
+    upper_j = []
+    for i in range(0,N):
+        for j in range(i+1,N):
+            upper_i.append(i)
+            upper_j.append(j)
+    zeros = myMatrix.val[(upper_i,upper_j)]
+
+    assert_allclose(zeros, np.zeros((N-1)*N//2))
+    assert_allclose((myMatrix==0).val.sum(), (N-1)*N//2)
+
+
+
+    

test/test_operators/test_multifield2vector.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) 2013-2020 Max-Planck-Society
+#
+# NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik.
+
+import numpy as np
+from numpy.testing import assert_allclose
+
+import nifty7 as ift
+
+
+def test_multifield2vector():
+    myFirstSpace = ift.RGSpace([42,43])
+    mySecondSpace = ift.RGSpace([1,2,3])
+    myDict = {
+        'first': ift.from_random(myFirstSpace),
+        'second': ift.from_random(mySecondSpace)
+    }
+    myMultiField = ift.MultiField.from_dict(myDict)
+    myMultifield2Vector = ift.Multifield2Vector(myMultiField.domain)
+    myVector =  myMultifield2Vector(myMultiField)
+    assert_allclose(myVector.size, myMultiField.size)
+    
+    myNumpyVector = np.empty(myMultiField.size)
+    myNumpyVector[:myFirstSpace.size] = myDict['first'].val.flatten()
+    myNumpyVector[myFirstSpace.size:] = myDict['second'].val.flatten()
+    assert_allclose(myNumpyVector, myVector.val)
+
+    mySecondMultiField = myMultifield2Vector.adjoint(myVector)
+
+    assert_allclose(mySecondMultiField['first'].val, myMultiField['first'].val)
+    assert_allclose(mySecondMultiField['second'].val, myMultiField['second'].val)
+
+