deleted metrixc test as it was not doing what it said

nifty5/extra.py

@@ -134,24 +134,20 @@ def _get_acceptable_location(op, loc, lin):
     return loc2, lin2
 
 
-def _check_consistency(op, loc, tol, ntries, do_metric):
+def _check_consistency(op, loc, tol, ntries):
     for _ in range(ntries):
-        lin = op(Linearization.make_var(loc, do_metric))
+        lin = op(Linearization.make_var(loc))
         loc2, lin2 = _get_acceptable_location(op, loc, lin)
         dir = loc2-loc
         locnext = loc2
         dirnorm = dir.norm()
         for i in range(50):
             locmid = loc + 0.5*dir
-            linmid = op(Linearization.make_var(locmid, do_metric))
+            linmid = op(Linearization.make_var(locmid))
             dirder = linmid.jac(dir)
             numgrad = (lin2.val-lin.val)
             xtol = tol * dirder.norm() / np.sqrt(dirder.size)
             cond = (abs(numgrad-dirder) <= xtol).all()
-            if do_metric:
-                dgrad = linmid.metric(dir)
-                dgrad2 = (lin2.gradient-lin.gradient)
-                cond = cond and (abs(dgrad-dgrad2) <= xtol).all()
             if cond:
                 break
             dir = dir*0.5
@@ -185,9 +181,5 @@ def check_value_gradient_consistency(op, loc, tol=1e-8, ntries=100):
         then satisfying any tolerance will let the check pass. 
         Default: 0
     """
-    _check_consistency(op, loc, tol, ntries, False)
+    _check_consistency(op, loc, tol, ntries)
 
-
-def check_value_gradient_metric_consistency(op, loc, tol=1e-8, ntries=100):
-    """FIXME"""
-    _check_consistency(op, loc, tol, ntries, True)

test/test_gaussian_energy.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 numpy as np
+import pytest
+
+import nifty5 as ift
+
+
+def _flat_PS(k):
+    return np.ones_like(k)
+
+
+pmp = pytest.mark.parametrize
+
+
+@pmp('space', [
+    ift.GLSpace(15),
+    ift.RGSpace(64, distances=.789),
+    ift.RGSpace([32, 32], distances=.789)
+])
+@pmp('nonlinearity', ["tanh", "exp", ""])
+@pmp('noise', [1, 1e-2, 1e2])
+@pmp('seed', [4, 78, 23])
+def test_gaussian_energy(space, nonlinearity, noise, seed):
+    np.random.seed(seed)
+    dim = len(space.shape)
+    hspace = space.get_default_codomain()
+    ht = ift.HarmonicTransformOperator(hspace, target=space)
+    binbounds = ift.PowerSpace.useful_binbounds(hspace, logarithmic=False)
+    pspace = ift.PowerSpace(hspace, binbounds=binbounds)
+    Dist = ift.PowerDistributor(target=hspace, power_space=pspace)
+    xi0 = ift.Field.from_random(domain=hspace, random_type='normal')
+
+    def pspec(k):
+        return 1/(1 + k**2)**dim
+
+    pspec = ift.PS_field(pspace, pspec)
+    A = Dist(ift.sqrt(pspec))
+    N = ift.ScalingOperator(noise, space)
+    n = N.draw_sample()
+    R = ift.ScalingOperator(10., space)
+
+    def d_model():
+        if nonlinearity == "":
+            return R(ht(ift.makeOp(A)))
+        else:
+            tmp = ht(ift.makeOp(A))
+            nonlin = getattr(tmp, nonlinearity)()
+            return R(nonlin)
+
+    d = d_model()(xi0) + n
+
+    if noise == 1:
+        N = None
+
+    energy = ift.GaussianEnergy(d, N)(d_model())
+    ift.extra.check_value_gradient_consistency(
+        energy, xi0, ntries=10, tol=5e-8)