Use gradient evaluation for Evaluator test

leeping · Nov 24, 2019 · dc27aa1 · dc27aa1
1 parent b3b4dd1
commit dc27aa1
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Showing 6 changed files with 168 additions and 291 deletions.
diff --git a/devtools/conda-envs/test_env.yaml b/devtools/conda-envs/test_env.yaml
@@ -21,6 +21,7 @@ dependencies:
   - swig
   - future
   - pymbar=3.0.3
+  - mdtraj=1.9.1
   - openmm
   - ambertools
   # The following two are not compatible with python 2.7 and 3.5, so they are conditionally installed in .travis.yml

diff --git a/src/optimizer.py b/src/optimizer.py
@@ -640,7 +640,7 @@ def print_progress(itn, nx, nd, ng, clr, x, std, qual):
                 if ngd < self.convergence_gradient:
                     logger.info("Convergence criterion reached for gradient norm (%.2e)\n" % self.convergence_gradient)
                     ncrit += 1
-                if ndx < self.convergence_step and ITERATION > self.iterinit:
+                if ndx < self.convergence_step and ndx >= 0.0 and ITERATION > self.iterinit:
                     logger.info("Convergence criterion reached in step size (%.2e)\n" % self.convergence_step)
                     ncrit += 1
                 if stdfront < self.convergence_objective and len(X_hist) >= self.hist: