Merge branch 'master' of https://github.com/SciTools/iris into fix-co…

…nvert-unit-test

* 'master' of https://github.com/SciTools/iris:
  Moveplottests (#2139)

lib/iris/tests/__init__.py

@@ -755,6 +755,18 @@ def patch(self, *args, **kwargs):
         # Return patch replacement object.
         return start_result
 
+    def assertArrayShapeStats(self, result, shape, mean, std_dev):
+        """
+        Assert that the result, a cube, has the provided shape and that the
+        mean and standard deviation of the data array are also as provided.
+        Thus build confidence that a cube processing operation, such as a
+        cube.regrid, has maintained its behaviour.
+ 
+        """
+        self.assertEqual(result.shape, shape)
+        self.assertAlmostEqual(result.data.mean(), mean, places=5)
+        self.assertAlmostEqual(result.data.std(), std_dev, places=5)
+
 
 get_result_path = IrisTest.get_result_path
 

lib/iris/tests/experimental/regrid/test_regrid_area_weighted_rectilinear_src_and_grid.py

@@ -1,4 +1,4 @@
-# (C) British Crown Copyright 2013 - 2015, Met Office
+# (C) British Crown Copyright 2013 - 2016, Met Office
 #
 # This file is part of Iris.
 #
@@ -37,12 +37,6 @@
 import iris.analysis._interpolation
 import iris.tests.stock
 
-# Run tests in no graphics mode if matplotlib is not available.
-if tests.MPL_AVAILABLE:
-    import matplotlib.pyplot as plt
-    import iris.quickplot as qplt
-
-
 RESULT_DIR = ('experimental', 'regrid',
               'regrid_area_weighted_rectilinear_src_and_grid')
 
@@ -161,7 +155,7 @@ def _resampled_grid(cube, x_samplefactor, y_samplefactor):
     return new_cube
 
 
-class TestAreaWeightedRegrid(tests.GraphicsTest):
+class TestAreaWeightedRegrid(tests.IrisTest):
     def setUp(self):
         # A cube with a hybrid height derived coordinate.
         self.realistic_cube = iris.tests.stock.realistic_4d()[:2, :5, :20, :30]
@@ -367,25 +361,11 @@ def test_regrid_to_higher_res(self):
         res = regrid_area_weighted(src, dest)
         self.assertCMLApproxData(res, RESULT_DIR + ('higher.cml',))
 
-    @tests.skip_plot
     def test_hybrid_height(self):
         src = self.realistic_cube
         dest = _resampled_grid(src, 0.7, 0.8)
         res = regrid_area_weighted(src, dest)
         self.assertCMLApproxData(res, RESULT_DIR + ('hybridheight.cml',))
-        # Consider a single slice to allow visual tests of altitudes.
-        src = src[1, 2]
-        res = res[1, 2]
-        qplt.pcolormesh(res)
-        self.check_graphic()
-        plt.contourf(res.coord('grid_longitude').points,
-                     res.coord('grid_latitude').points,
-                     res.coord('altitude').points)
-        self.check_graphic()
-        plt.contourf(res.coord('grid_longitude').points,
-                     res.coord('grid_latitude').points,
-                     res.coord('surface_altitude').points)
-        self.check_graphic()
 
     def test_missing_data(self):
         src = self.simple_cube.copy()
@@ -443,7 +423,6 @@ def test_ten_by_ten_subset(self):
             res = regrid_area_weighted(src, dest)
             self.assertTrue(res, src[indices])
 
-    @tests.skip_plot
     def test_cross_section(self):
         # Slice to get a cross section.
         # Constant latitude
@@ -458,10 +437,6 @@ def test_cross_section(self):
         res = regrid_area_weighted(src, dest)
         self.assertCMLApproxData(res, RESULT_DIR +
                                  ('const_lat_cross_section.cml',))
-        # Plot a single slice.
-        qplt.plot(res[0])
-        qplt.plot(src[0], 'r')
-        self.check_graphic()
 
         # Constant longitude
         src = self.realistic_cube[0, :, :, 10]
@@ -475,10 +450,6 @@ def test_cross_section(self):
         res = regrid_area_weighted(src, dest)
         self.assertCMLApproxData(res, RESULT_DIR +
                                  ('const_lon_cross_section.cml',))
-        # Plot a single slice.
-        qplt.plot(res[0])
-        qplt.plot(src[0], 'r')
-        self.check_graphic()
 
     def test_scalar_source_cube(self):
         src = self.simple_cube[1, 2]
@@ -495,39 +466,32 @@ def test_scalar_source_cube(self):
         self.assertEqual(res.data, src.data)
 
     @tests.skip_data
-    @tests.skip_plot
     def test_global_data_reduce_res(self):
         src = iris.tests.stock.global_pp()
         src.coord('latitude').guess_bounds()
         src.coord('longitude').guess_bounds()
         dest = _resampled_grid(src, 0.4, 0.3)
         res = regrid_area_weighted(src, dest)
-        qplt.pcolormesh(res)
-        self.check_graphic()
+        self.assertArrayShapeStats(res, (21, 38), 280.137698, 15.998966)
 
     @tests.skip_data
-    @tests.skip_plot
     def test_global_data_increase_res(self):
         src = iris.tests.stock.global_pp()
         src.coord('latitude').guess_bounds()
         src.coord('longitude').guess_bounds()
         dest = _resampled_grid(src, 1.5, 1.5)
         res = regrid_area_weighted(src, dest)
-        qplt.pcolormesh(res)
-        self.check_graphic()
+        self.assertArrayShapeStats(res, (109, 144), 279.955722, 16.313940)
 
     @tests.skip_data
-    @tests.skip_plot
     def test_global_data_same_res(self):
         src = iris.tests.stock.global_pp()
         src.coord('latitude').guess_bounds()
         src.coord('longitude').guess_bounds()
         res = regrid_area_weighted(src, src)
-        qplt.pcolormesh(res)
-        self.check_graphic()
+        self.assertArrayShapeStats(res, (73, 96), 279.945167, 16.345842)
 
     @tests.skip_data
-    @tests.skip_plot
     def test_global_data_subset(self):
         src = iris.tests.stock.global_pp()
         src.coord('latitude').guess_bounds()
@@ -545,12 +509,9 @@ def test_global_data_subset(self):
         dest.add_dim_coord(dest_lon, 1)
 
         res = regrid_area_weighted(src, dest)
-        qplt.pcolormesh(res)
-        plt.gca().coastlines()
-        self.check_graphic()
+        self.assertArrayShapeStats(res, (40, 30), 280.979336, 16.640421)
 
     @tests.skip_data
-    @tests.skip_plot
     def test_circular_subset(self):
         src = iris.tests.stock.global_pp()
         src.coord('latitude').guess_bounds()
@@ -568,12 +529,9 @@ def test_circular_subset(self):
         dest.add_dim_coord(dest_lon, 1)
 
         res = regrid_area_weighted(src, dest)
-        qplt.pcolormesh(res)
-        plt.gca().coastlines()
-        self.check_graphic()
+        self.assertArrayShapeStats(res, (40, 7), 285.653967, 15.212710)
 
     @tests.skip_data
-    @tests.skip_plot
     def test_non_circular_subset(self):
         src = iris.tests.stock.global_pp()
         src.coord('latitude').guess_bounds()
@@ -592,9 +550,7 @@ def test_non_circular_subset(self):
         dest.add_dim_coord(dest_lon, 1)
 
         res = regrid_area_weighted(src, dest)
-        qplt.pcolormesh(res)
-        plt.gca().coastlines()
-        self.check_graphic()
+        self.assertArrayShapeStats(res, (40, 7), 285.550800, 15.190245)
 
 
 if __name__ == "__main__":

lib/iris/tests/integration/test_grib_load.py

@@ -42,13 +42,6 @@
 from unittest import skipIf
 
 
-# Run tests in no graphics mode if matplotlib is not available.
-if tests.MPL_AVAILABLE:
-    import matplotlib.pyplot as plt
-    from matplotlib.colors import LogNorm
-    import iris.plot as iplt
-    import iris.quickplot as qplt
-
 if tests.GRIB_AVAILABLE:
     try:
         import iris_grib
@@ -97,64 +90,32 @@ def test_load_masked(self):
         self.assertCML(cubes, ('grib_load', 'missing_values_grib2.cml'))
 
     @skip_irisgrib_fails
-    @tests.skip_plot
     def test_y_fastest(self):
         cubes = iris.load(tests.get_data_path(("GRIB", "y_fastest",
                                                "y_fast.grib2")))
         self.assertCML(cubes, ("grib_load", "y_fastest.cml"))
-        iplt.contourf(cubes[0])
-        plt.gca().coastlines()
-        plt.title("y changes fastest")
-        self.check_graphic()
 
-    @tests.skip_plot
     def test_polar_stereo_grib1(self):
         cube = iris.load_cube(tests.get_data_path(
             ("GRIB", "polar_stereo", "ST4.2013052210.01h")))
         self.assertCML(cube, ("grib_load", "polar_stereo_grib1.cml"))
-        qplt.contourf(cube, norm=LogNorm())
-        plt.gca().coastlines()
-        plt.gca().gridlines()
-        plt.title("polar stereo grib1")
-        self.check_graphic()
 
-    @tests.skip_plot
     def test_polar_stereo_grib2(self):
         cube = iris.load_cube(tests.get_data_path(
             ("GRIB", "polar_stereo",
              "CMC_glb_TMP_ISBL_1015_ps30km_2013052000_P006.grib2")))
         self.assertCML(cube, ("grib_load", "polar_stereo_grib2.cml"))
 
-        qplt.contourf(cube)
-        plt.gca().coastlines()
-        plt.gca().gridlines()
-        plt.title("polar stereo grib2")
-        self.check_graphic()
-
-    @tests.skip_plot
     def test_lambert_grib1(self):
         cube = iris.load_cube(tests.get_data_path(
             ("GRIB", "lambert", "lambert.grib1")))
         self.assertCML(cube, ("grib_load", "lambert_grib1.cml"))
 
-        qplt.contourf(cube)
-        plt.gca().coastlines()
-        plt.gca().gridlines()
-        plt.title("lambert grib1")
-        self.check_graphic()
-
-    @tests.skip_plot
     def test_lambert_grib2(self):
         cube = iris.load_cube(tests.get_data_path(
             ("GRIB", "lambert", "lambert.grib2")))
         self.assertCML(cube, ("grib_load", "lambert_grib2.cml"))
 
-        qplt.contourf(cube)
-        plt.gca().coastlines()
-        plt.gca().gridlines()
-        plt.title("lambert grib2")
-        self.check_graphic()
-
     def test_regular_gg_grib1(self):
         cube = iris.load_cube(tests.get_data_path(
             ('GRIB', 'gaussian', 'regular_gg.grib1')))
@@ -191,38 +152,21 @@ def _old_compat_load(name):
                                               name)))[0]
         return [cube]
 
-    @tests.skip_plot
     def test_ij_directions_ipos_jpos(self):
         cubes = self._old_compat_load("ipos_jpos.grib2")
         self.assertCML(cubes, ("grib_load", "ipos_jpos.cml"))
-        iplt.contourf(cubes[0])
-        plt.gca().coastlines()
-        plt.title("ipos_jpos cube")
-        self.check_graphic()
 
     def test_ij_directions_ipos_jneg(self):
         cubes = self._old_compat_load("ipos_jneg.grib2")
         self.assertCML(cubes, ("grib_load", "ipos_jneg.cml"))
-        iplt.contourf(cubes[0])
-        plt.gca().coastlines()
-        plt.title("ipos_jneg cube")
-        self.check_graphic()
 
     def test_ij_directions_ineg_jneg(self):
         cubes = self._old_compat_load("ineg_jneg.grib2")
         self.assertCML(cubes, ("grib_load", "ineg_jneg.cml"))
-        iplt.contourf(cubes[0])
-        plt.gca().coastlines()
-        plt.title("ineg_jneg cube")
-        self.check_graphic()
 
     def test_ij_directions_ineg_jpos(self):
         cubes = self._old_compat_load("ineg_jpos.grib2")
         self.assertCML(cubes, ("grib_load", "ineg_jpos.cml"))
-        iplt.contourf(cubes[0])
-        plt.gca().coastlines()
-        plt.title("ineg_jpos cube")
-        self.check_graphic()
 
 
 @tests.skip_data

lib/iris/tests/integration/test_regridding.py

@@ -1,4 +1,4 @@
-# (C) British Crown Copyright 2013 - 2015, Met Office
+# (C) British Crown Copyright 2013 - 2016, Met Office
 #
 # This file is part of Iris.
 #
@@ -32,20 +32,17 @@
 from iris.cube import Cube
 from iris.tests.stock import global_pp
 
-# Run tests in no graphics mode if matplotlib is not available.
-if tests.MPL_AVAILABLE:
-    import iris.quickplot as qplt
-
 
 @tests.skip_data
-@tests.skip_plot
-class TestOSGBToLatLon(tests.GraphicsTest):
+class TestOSGBToLatLon(tests.IrisTest):
     def setUp(self):
         path = tests.get_data_path(
             ('NIMROD', 'uk2km', 'WO0000000003452',
              '201007020900_u1096_ng_ey00_visibility0180_screen_2km'))
         self.src = iris.load_cube(path)[0]
-        self.src.data = self.src.data.astype(np.float32)
+        # Cast up to float64, to work around numpy<=1.8 bug with means of
+        # arrays of 32bit floats.
+        self.src.data = self.src.data.astype(np.float64)
         self.grid = Cube(np.empty((73, 96)))
         cs = GeogCS(6370000)
         lat = DimCoord(np.linspace(46, 65, 73), 'latitude', units='degrees',
@@ -58,23 +55,25 @@ def setUp(self):
     def _regrid(self, method):
         regridder = Regridder(self.src, self.grid, method, 'mask')
         result = regridder(self.src)
-        qplt.pcolor(result, antialiased=False)
-        qplt.plt.gca().coastlines()
+        return result
 
     def test_linear(self):
-        self._regrid('linear')
-        self.check_graphic()
+        res = self._regrid('linear')
+        self.assertArrayShapeStats(res, (73, 96), -16100.351951, 5603.850769)
 
     def test_nearest(self):
-        self._regrid('nearest')
-        self.check_graphic()
+        res = self._regrid('nearest')
+        self.assertArrayShapeStats(res, (73, 96), -16095.965585, 5612.657155)
 
 
 @tests.skip_data
-@tests.skip_plot
-class TestGlobalSubsample(tests.GraphicsTest):
+class TestGlobalSubsample(tests.IrisTest):
     def setUp(self):
         self.src = global_pp()
+        _ = self.src.data
+        # Cast up to float64, to work around numpy<=1.8 bug with means of
+        # arrays of 32bit floats.
+        self.src.data = self.src.data.astype(np.float64)
         # Subsample and shift the target grid so that we can see a visual
         # difference between regridding scheme methods.
         grid = self.src[1::2, 1::3]
@@ -85,16 +84,15 @@ def setUp(self):
     def _regrid(self, method):
         regridder = Regridder(self.src, self.grid, method, 'mask')
         result = regridder(self.src)
-        qplt.pcolormesh(result)
-        qplt.plt.gca().coastlines()
+        return result
 
     def test_linear(self):
-        self._regrid('linear')
-        self.check_graphic()
+        res = self._regrid('linear')
+        self.assertArrayShapeStats(res, (36, 32), 280.35907, 15.997223)
 
     def test_nearest(self):
-        self._regrid('nearest')
-        self.check_graphic()
+        res = self._regrid('nearest')
+        self.assertArrayShapeStats(res, (36, 32), 280.33726, 16.064001)
 
 
 if __name__ == "__main__":