def test_init(self): name = 'percentile' call_func = _percentile units_func = mock.sentinel.units_func lazy_func = mock.sentinel.lazy_func aggregator = PercentileAggregator(units_func=units_func, lazy_func=lazy_func) self.assertEqual(aggregator.name(), name) self.assertIs(aggregator.call_func, call_func) self.assertIs(aggregator.units_func, units_func) self.assertIs(aggregator.lazy_func, lazy_func) self.assertIsNone(aggregator.cell_method)
def test_simple_single_point(self): aggregator = PercentileAggregator() percent = 50 kwargs = dict(percent=percent) data = np.empty(self.cube_simple.shape) coords = [self.coord_simple] actual = aggregator.post_process(self.cube_simple, data, coords, **kwargs) self.assertEqual(actual.shape, self.cube_simple.shape) self.assertIs(actual.data, data) name = 'percentile_over_time' coord = actual.coord(name) expected = AuxCoord(percent, long_name=name) self.assertEqual(coord, expected)
def test_multi_single_point(self): aggregator = PercentileAggregator() percent = 70 kwargs = dict(percent=percent) data = np.empty(self.cube_multi.shape) coords = [self.coord_multi_0] actual = aggregator.post_process(self.cube_multi, data, coords, **kwargs) self.assertEqual(actual.shape, self.cube_multi.shape) self.assertIs(actual.data, data) name = "percentile_over_time" coord = actual.coord(name) expected = AuxCoord(percent, long_name=name, units="percent") self.assertEqual(coord, expected)
def test_simple_multiple_points(self): aggregator = PercentileAggregator() percent = np.array([10, 20, 50, 90]) kwargs = dict(percent=percent) shape = self.cube_simple.shape + percent.shape data = np.empty(shape) coords = [self.coord_simple] actual = aggregator.post_process(self.cube_simple, data, coords, **kwargs) self.assertEqual(actual.shape, percent.shape + self.cube_simple.shape) expected = np.rollaxis(data, -1) self.assertArrayEqual(actual.data, expected) name = 'percentile_over_time' coord = actual.coord(name) expected = AuxCoord(percent, long_name=name) self.assertEqual(coord, expected)
def test_multi_multiple_points(self): aggregator = PercentileAggregator() percent = np.array([17, 29, 81]) kwargs = dict(percent=percent) shape = self.cube_multi.shape + percent.shape data = np.empty(shape) coords = [self.coord_multi_0] actual = aggregator.post_process(self.cube_multi, data, coords, **kwargs) self.assertEqual(actual.shape, percent.shape + self.cube_multi.shape) expected = np.rollaxis(data, -1) self.assertArrayEqual(actual.data, expected) name = "percentile_over_time" coord = actual.coord(name) expected = AuxCoord(percent, long_name=name, units="percent") self.assertEqual(coord, expected)
def test_missing_mandatory_kwarg(self): aggregator = PercentileAggregator() emsg = "percentile aggregator requires .* keyword argument 'percent'" with self.assertRaisesRegex(ValueError, emsg): aggregator.aggregate("dummy", axis=0)
def test_missing_mandatory_kwarg(self): aggregator = PercentileAggregator() emsg = "percentile aggregator requires .* keyword argument 'percent'" with self.assertRaisesRegexp(ValueError, emsg): aggregator.aggregate('dummy', axis=0)