Fix masked array checks in test_hdfeos.py

Also install nose in build env
briandobbins · Jan 18, 2019 · 4138237 · 4138237
1 parent e5e36ee
commit 4138237
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Showing 2 changed files with 13 additions and 7 deletions.
diff --git a/.circleci/config.yml b/.circleci/config.yml
@@ -35,7 +35,7 @@ jobs:
             curl -L -O "${MINICONDA_URL}/${MINICONDA_FILE}"
             bash $MINICONDA_FILE -b
             source ~/miniconda3/bin/activate root
-            conda create -c conda-forge/label/cf201901 -n pynio gcc setuptools python=3.6 numpy=1.14 g2clib=1.6 hdf4 hdf5 hdfeos2 hdfeos5 jasper libgdal libnetcdf proj4 pytest
+            conda create -c conda-forge/label/cf201901 -n pynio gcc setuptools python=3.6 numpy=1.14 g2clib=1.6 hdf4 hdf5 hdfeos2 hdfeos5 jasper libgdal libnetcdf proj4 pytest nose
 
       - save_cache:
           paths:

diff --git a/test/test_hdfeos.py b/test/test_hdfeos.py
@@ -43,12 +43,18 @@ def test_hdfeos_var_values(self):
         for var in var_values.keys():
             v = self.f.variables[var]
             val = v.get_value()
-            nt.assert_equal(np.ma.is_masked(val.min()), np.ma.is_masked(var_values[var][0]))
-            nt.assert_almost_equal(val.min(), var_values[var][0])
-            nt.assert_equal(np.ma.is_masked(val.max()), np.ma.is_masked(var_values[var][1]))
-            nt.assert_almost_equal(val.max(), var_values[var][1])
-            nt.assert_equal(np.ma.is_masked(val.mean()), np.ma.is_masked(var_values[var][2]))
-            nt.assert_almost_equal(val.mean(), var_values[var][2])
+            if np.ma.is_masked(val.min()) or np.ma.is_masked(var_values[var][0]):
+                nt.assert_equal(np.ma.is_masked(val.min()), np.ma.is_masked(var_values[var][0]))
+            else:
+                nt.assert_almost_equal(val.min(), var_values[var][0])
+            if np.ma.is_masked(val.max()) or np.ma.is_masked(var_values[var][1]):
+                nt.assert_equal(np.ma.is_masked(val.max()), np.ma.is_masked(var_values[var][1]))
+            else:
+                nt.assert_almost_equal(val.max(), var_values[var][1])
+            if np.ma.is_masked(val.mean()) or np.ma.is_masked(var_values[var][2]):
+                nt.assert_equal(np.ma.is_masked(val.mean()), np.ma.is_masked(var_values[var][2]))
+            else:
+                nt.assert_almost_equal(val.mean(), var_values[var][2])
             nt.assert_almost_equal(np.ma.count_masked(val), var_values[var][3])