Merge pull request #371 from borglab/feature/quiet-python-tests

Capture stdout in python test

cython/gtsam/tests/test_logging_optimizer.py

@@ -4,6 +4,12 @@ Author: Jing Wu and Frank Dellaert
 """
 # pylint: disable=invalid-name
 
+import sys
+if sys.version_info.major >= 3:
+    from io import StringIO
+else:
+    from cStringIO import StringIO
+
 import unittest
 from datetime import datetime
 
@@ -37,11 +43,19 @@ class TestOptimizeComet(GtsamTestCase):
         self.optimizer = gtsam.GaussNewtonOptimizer(
             graph, initial, self.params)
 
+        # setup output capture
+        self.capturedOutput = StringIO()
+        sys.stdout = self.capturedOutput
+
+    def tearDown(self):
+        """Reset print capture."""
+        sys.stdout = sys.__stdout__
+
     def test_simple_printing(self):
         """Test with a simple hook."""
 
         # Provide a hook that just prints
-        def hook(_, error: float):
+        def hook(_, error):
             print(error)
 
         # Only thing we require from optimizer is an iterate method
@@ -65,7 +79,7 @@ class TestOptimizeComet(GtsamTestCase):
                        + str(time.hour)+":"+str(time.minute)+":"+str(time.second))
 
         # I want to do some comet thing here
-        def hook(optimizer, error: float):
+        def hook(optimizer, error):
             comet.log_metric("Karcher error",
                              error, optimizer.iterations())
 

cython/gtsam/utils/logging_optimizer.py

@@ -4,15 +4,11 @@ Author: Jing Wu and Frank Dellaert
 """
 # pylint: disable=invalid-name
 
-from typing import TypeVar
-
 from gtsam import NonlinearOptimizer, NonlinearOptimizerParams
 import gtsam
 
-T = TypeVar('T')
 
-
+def optimize(optimizer, check_convergence, hook):
-def optimize(optimizer: T, check_convergence, hook):
     """ Given an optimizer and a convergence check, iterate until convergence.
         After each iteration, hook(optimizer, error) is called.
         After the function, use values and errors to get the result.
@@ -36,8 +32,8 @@ def optimize(optimizer: T, check_convergence, hook):
         current_error = new_error
 
 
-def gtsam_optimize(optimizer: NonlinearOptimizer,
+def gtsam_optimize(optimizer,
-                   params: NonlinearOptimizerParams,
+                   params,
                    hook):
     """ Given an optimizer and params, iterate until convergence.
         After each iteration, hook(optimizer) is called.