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From huiky...@apache.org
Subject [2/2] climate git commit: CLIMATE-659 - Remove SpatialMeanOfTemporalMeanBias
Date Wed, 19 Aug 2015 00:37:48 GMT
CLIMATE-659 - Remove SpatialMeanOfTemporalMeanBias

Conflicts:
	ocw/metrics.py
	ocw/tests/test_metrics.py


Project: http://git-wip-us.apache.org/repos/asf/climate/repo
Commit: http://git-wip-us.apache.org/repos/asf/climate/commit/45779fb9
Tree: http://git-wip-us.apache.org/repos/asf/climate/tree/45779fb9
Diff: http://git-wip-us.apache.org/repos/asf/climate/diff/45779fb9

Branch: refs/heads/master
Commit: 45779fb9890cb6d00e71fd2e47432f9687f39068
Parents: b08d379 ee1d860
Author: huikyole <huikyole@argo.jpl.nasa.gov>
Authored: Tue Aug 18 17:36:30 2015 -0700
Committer: huikyole <huikyole@argo.jpl.nasa.gov>
Committed: Tue Aug 18 17:36:30 2015 -0700

----------------------------------------------------------------------
 ocw/metrics.py            | 20 --------------------
 ocw/tests/test_metrics.py | 28 ----------------------------
 2 files changed, 48 deletions(-)
----------------------------------------------------------------------


http://git-wip-us.apache.org/repos/asf/climate/blob/45779fb9/ocw/metrics.py
----------------------------------------------------------------------
diff --cc ocw/metrics.py
index 76fc78b,3d7c536..62f4e3d
--- a/ocw/metrics.py
+++ b/ocw/metrics.py
@@@ -229,28 -211,14 +229,8 @@@ class TemporalMeanBias(BinaryMetric)
          :returns: The mean bias between a reference and target dataset over time.
          '''
  
 -        diff = target_dataset.values - ref_dataset.values 
 -        if absolute:
 -            diff = abs(diff)
 -        mean_bias = ma.mean(diff, axis=0)
 -
 -        return mean_bias
 -
 +        return calc_bias(target_dataset.values,ref_dataset.values, average_over_time=True)

  
- class SpatialMeanOfTemporalMeanBias(BinaryMetric):
-     '''Calculate the bias averaged over time and domain.'''
- 
-     def run(self, reference_dataset, target_dataset):
-         '''Calculate the bias averaged over time and domain.
-         .. note::
-            Overrides BinaryMetric.run()
-         :param reference_dataset: The reference dataset to use in this metric
-             run
-         :type reference_dataset: :class:`dataset.Dataset`
-         :param target_dataset: The target dataset to evaluate against the
-             reference dataset in this metric run
-         :type target_dataset: :class:`dataset.Dataset`
-         :returns: The bias averaged over time and domain
-         '''
- 
-         bias = target_dataset.values - reference_dataset.values 
-         return ma.mean(bias)
- 
- 
  class RMSError(BinaryMetric):
      '''Calculate the Root Mean Square Difference (RMS Error), with the mean
         calculated over time and space.'''

http://git-wip-us.apache.org/repos/asf/climate/blob/45779fb9/ocw/tests/test_metrics.py
----------------------------------------------------------------------
diff --cc ocw/tests/test_metrics.py
index 8d638be,9ee19e2..facf1d3
--- a/ocw/tests/test_metrics.py
+++ b/ocw/tests/test_metrics.py
@@@ -229,34 -208,13 +229,6 @@@ class TestTemporalMeanBias(unittest.Tes
          expected_result.fill(-300)
          np.testing.assert_array_equal(self.mean_bias.run(self.target_dataset,self.reference_dataset),
expected_result)
  
- class TestSpatialMeanOfTemporalMeanBias(unittest.TestCase):
-     '''Test the metrics.SpatialMeanOfTemporalMeanBias metric.'''
-     def setUp(self):
-         # Set metric.
-         self.metric = metrics.SpatialMeanOfTemporalMeanBias()
-         # Initialize reference dataset.
-         self.ref_lats = np.array([10, 20, 30, 40, 50])
-         self.ref_lons = np.array([5, 15, 25, 35, 45])
-         self.ref_times = np.array([dt.datetime(2000, x, 1)
-                                    for x in range(1, 13)])
-         self.ref_values = np.array(range(300)).reshape(12, 5, 5)
-         self.ref_variable = "ref"
-         self.ref_dataset = Dataset(self.ref_lats, self.ref_lons,
-             self.ref_times, self.ref_values, self.ref_variable)
-         # Initialize target dataset.
-         self.tgt_lats = np.array([10, 20, 30, 40, 50])
-         self.tgt_lons = np.array([5, 15, 25, 35, 45])
-         self.tgt_times = np.array([dt.datetime(2000, x, 1)
-                                    for x in range(1, 13)])
-         self.tgt_values = np.array(range(299, -1, -1)).reshape(12, 5, 5)
-         self.tgt_variable = "tgt"
-         self.tgt_dataset = Dataset(self.tgt_lats, self.tgt_lons,
-             self.tgt_times, self.tgt_values, self.tgt_variable)
 -    def test_function_run_abs(self):
 -        '''Test mean bias function between reference dataset and target dataset with abs
as True.'''
 -        expected_result = np.zeros((5, 5), dtype=np.int)
 -        expected_result.fill(300)
 -        np.testing.assert_array_equal(self.mean_bias.run(self.reference_dataset, self.target_dataset,
True), expected_result)
--
-     def test_function_run(self):
-         result = self.metric.run(self.ref_dataset, self.tgt_dataset)
-         self.assertEqual(result, 0.0)
--
  class TestRMSError(unittest.TestCase):
      '''Test the metrics.RMSError metric.'''
      def setUp(self):


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