Merge pull request #753 from CCI-Tools/jg-746-pearsonr

Make sure pearson_correlation_scalar input is validated
CCI-Tools · Sep 21, 2018 · 6540e61 · 6540e61
2 parents 49aaf3f + a044555
commit 6540e61
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diff --git a/cate/ops/correlation.py b/cate/ops/correlation.py
@@ -90,7 +90,7 @@ def pearson_correlation_scalar(ds_x: DatasetLike.TYPE,
     array_y = ds_y[var_y]
     array_x = ds_x[var_x]
 
-    if ((len(array_x.dims) != len(array_y.dims)) and
+    if ((len(array_x.dims) != len(array_y.dims)) or
        (len(array_x.dims) != 1)):
         raise ValidationError('To calculate simple correlation, both provided'
                               ' datasets should be simple 1d timeseries. To'

diff --git a/test/ops/test_correlation.py b/test/ops/test_correlation.py
@@ -68,6 +68,37 @@ def test_error(self):
             pearson_correlation_scalar(ds1, ds2, 'first', 'first')
         self.assertIn('dimension should not be less', str(err.exception))
 
+    def test_3D(self):
+        """
+        Test nominal run
+        """
+        # Test general functionality 3D dataset variables
+        ds1 = xr.Dataset({
+            'first': (['time', 'lat', 'lon'], np.array([np.ones([4, 8]),
+                                                        np.ones([4, 8]) * 2,
+                                                        np.ones([4, 8]) * 3])),
+            'second': (['time', 'lat', 'lon'], np.array([np.ones([4, 8]) * 2,
+                                                         np.ones([4, 8]) * 3,
+                                                         np.ones([4, 8])])),
+            'lat': np.linspace(-67.5, 67.5, 4),
+            'lon': np.linspace(-157.5, 157.5, 8),
+            'time': np.array([1, 2, 3])}).chunk(chunks={'lat': 2, 'lon': 4})
+
+        ds2 = xr.Dataset({
+            'second': (['time', 'lat', 'lon'], np.array([np.ones([4, 8]),
+                                                         np.ones([4, 8]) * 2,
+                                                         np.ones([4, 8]) * 3])),
+            'first': (['time', 'lat', 'lon'], np.array([np.ones([4, 8]) * 2,
+                                                        np.ones([4, 8]) * 3,
+                                                        np.ones([4, 8])])),
+            'lat': np.linspace(-67.5, 67.5, 4),
+            'lon': np.linspace(-157.5, 157.5, 8),
+            'time': np.array([1, 2, 3])}).chunk(chunks={'lat': 2, 'lon': 4})
+
+        with self.assertRaises(ValueError) as err:
+            pearson_correlation_scalar(ds1, ds2, 'first', 'first')
+        self.assertIn('should be simple 1d', str(err.exception))
+
 
 class TestPearson(TestCase):
     def test_nominal(self):