From 62a6ec4ea81fa5dc272b72e70b5832ef8e0a5750 Mon Sep 17 00:00:00 2001
From: Holger Kohr <h.kohr@cwi.nl>
Date: Sun, 22 Oct 2017 00:34:07 +0200
Subject: [PATCH] TST: add ADMM tests optimized vs. simple

---
 odl/test/solvers/nonsmooth/admm_test.py | 34 +++++++++++++++++++++++++
 1 file changed, 34 insertions(+)

diff --git a/odl/test/solvers/nonsmooth/admm_test.py b/odl/test/solvers/nonsmooth/admm_test.py
index 5dc29e2ce55..dbab6f71921 100644
--- a/odl/test/solvers/nonsmooth/admm_test.py
+++ b/odl/test/solvers/nonsmooth/admm_test.py
@@ -11,6 +11,8 @@
 from __future__ import division
 import odl
 from odl.solvers import admm_linearized, admm_precon_nonlinear, Callback
+from odl.solvers.nonsmooth.admm import (
+    admm_linearized_simple, admm_precon_nonlinear_simple)
 
 from odl.util.testutils import all_almost_equal, noise_element
 
@@ -72,6 +74,22 @@ def test_admm_lin_l1():
     assert all_almost_equal(x, data_1, places=2)
 
 
+def test_admm_lin_vs_simple():
+    """Check ``admm_linearized`` against the simple implementation."""
+    space = odl.rn(5)
+    L = odl.ScalingOperator(space, 2)
+    y = L(odl.util.testutils.noise_element(space))
+    f = odl.solvers.L2NormSquared(space).translated(y)
+    g = 0.5 * odl.solvers.L1Norm(space)
+
+    x_simple = space.zero()
+    admm_linearized_simple(x_simple, f, g, L, tau=1.0, sigma=2.0, niter=10)
+    x_optim = space.zero()
+    admm_linearized(x_optim, f, g, L, tau=1.0, sigma=2.0, niter=10)
+
+    assert all_almost_equal(x_optim, x_simple)
+
+
 def test_admm_nonlin_affine_l1():
     """Verify that the correct value is returned for l1 dist optimization.
 
@@ -100,5 +118,21 @@ def test_admm_nonlin_affine_l1():
     assert all_almost_equal(x, x, places=2)
 
 
+def test_admm_nonlin_vs_simple():
+    """Check ``admm_precon_nonlinear`` against the simple implementation."""
+    space = odl.rn(5)
+    L = odl.ufunc_ops.sin(space) * odl.ScalingOperator(space, 2)
+    y = L(odl.util.testutils.noise_element(space))
+    f = odl.solvers.L2NormSquared(space).translated(y)
+    g = 0.5 * odl.solvers.L1Norm(space)
+
+    x_simple = space.zero()
+    admm_precon_nonlinear_simple(x_simple, f, g, L, delta=1.0, niter=2)
+    x_optim = space.zero()
+    admm_precon_nonlinear(x_optim, f, g, L, delta=1.0, niter=2)
+
+    assert all_almost_equal(x_optim, x_simple)
+
+
 if __name__ == '__main__':
     odl.util.test_file(__file__)