def test_1d_coords(self):
cube = simple_2d()
defn = iplt._get_plot_defn_custom_coords_picked(
cube, ("foo", "bar"), POINT_MODE)
self.assertEqual([coord.name() for coord in defn.coords],
["bar", "foo"])
self.assertFalse(defn.transpose)
def setUp(self):
# Load a source cube, then generate an interpolator instance, calculate
# the interpolation weights and set up a target grid.
self.cube = stock.simple_2d()
x_points = self.cube.coord('bar').points
y_points = self.cube.coord('foo').points
self.interpolator = _RegularGridInterpolator([x_points, y_points],
self.cube.data,
method='linear',
bounds_error=False,
fill_value=None)
newx = x_points + 0.7
newy = y_points + 0.7
d_0 = self.cube.data[0, 0]
d_1 = self.cube.data[0, 1]
d_2 = self.cube.data[1, 0]
d_3 = self.cube.data[1, 1]
px_0, px_1 = x_points[0], x_points[1]
py_0, py_1 = y_points[0], y_points[1]
px_t = px_0 + 0.7
py_t = py_0 + 0.7
dyt_0 = self._interpolate_point(py_t, py_0, py_1, d_0, d_1)
dyt_1 = self._interpolate_point(py_t, py_0, py_1, d_2, d_3)
self.test_increment = self._interpolate_point(px_t, px_0, px_1,
dyt_0, dyt_1)
xv, yv = np.meshgrid(newy, newx)
self.tgrid = np.dstack((yv, xv))
self.weights = self.interpolator.compute_interp_weights(self.tgrid)
def test_1d_coords_as_integers(self):
cube = simple_2d()
defn = iplt._get_plot_defn_custom_coords_picked(
cube, (1, 0), POINT_MODE
)
self.assertEqual([coord for coord in defn.coords], [0, 1])
self.assertFalse(defn.transpose)
def test_time_coord_only_in_some_cubes(self):
list_of_cubes = self.simple_1d_time_cubes()
cube = stock.simple_2d()
list_of_cubes.append(cube)
expected = 'hours since 1970-01-01 00:00:00'
unify_time_units(list_of_cubes)
self._common(expected, list_of_cubes)
def test_1d_coords_swapped(self):
cube = simple_2d()
defn = iplt._get_plot_defn_custom_coords_picked(cube, ('bar', 'foo'),
POINT_MODE)
self.assertEqual([coord.name() for coord in defn.coords],
['foo', 'bar'])
self.assertTrue(defn.transpose)
def test_1d_coords_as_integers_swapped(self):
cube = simple_2d()
defn = iplt._get_plot_defn_custom_coords_picked(
cube, (0, 1), POINT_MODE
)
self.assertEqual([coord for coord in defn.coords], [1, 0])
self.assertTrue(defn.transpose)
def test_1d_coords_swapped(self):
cube = simple_2d()
defn = iplt._get_plot_defn_custom_coords_picked(cube, ('bar', 'foo'),
POINT_MODE)
self.assertEqual([coord.name() for coord in defn.coords],
['foo', 'bar'])
self.assertTrue(defn.transpose)
def setUp(self):
# Load a source cube, then generate an interpolator instance, calculate
# the interpolation weights and set up a target grid.
self.cube = stock.simple_2d()
x_points = self.cube.coord("bar").points
y_points = self.cube.coord("foo").points
self.interpolator = _RegularGridInterpolator(
[x_points, y_points],
self.cube.data,
method="linear",
bounds_error=False,
fill_value=None,
)
newx = x_points + 0.7
newy = y_points + 0.7
d_0 = self.cube.data[0, 0]
d_1 = self.cube.data[0, 1]
d_2 = self.cube.data[1, 0]
d_3 = self.cube.data[1, 1]
px_0, px_1 = x_points[0], x_points[1]
py_0, py_1 = y_points[0], y_points[1]
px_t = px_0 + 0.7
py_t = py_0 + 0.7
dyt_0 = self._interpolate_point(py_t, py_0, py_1, d_0, d_1)
dyt_1 = self._interpolate_point(py_t, py_0, py_1, d_2, d_3)
self.test_increment = self._interpolate_point(
px_t, px_0, px_1, dyt_0, dyt_1
)
xv, yv = np.meshgrid(newy, newx)
self.tgrid = np.dstack((yv, xv))
self.weights = self.interpolator.compute_interp_weights(self.tgrid)
def test_time_coord_only_in_some_cubes(self):
list_of_cubes = self.simple_1d_time_cubes()
cube = stock.simple_2d()
list_of_cubes.append(cube)
expected = 'hours since 1970-01-01 00:00:00'
unify_time_units(list_of_cubes)
self._common(expected, list_of_cubes)
def setUp(self):
super().setUp()
self.cube = simple_2d(with_bounds=True)
self.cube.add_aux_coord(
AuxCoord(list("abcd"), long_name="str_coord"), 1
)
self.lat_lon_cube = lat_lon_cube()
def setUp(self):
self.cube = stock.simple_2d()
self.scheme = mock.Mock(name='interpolation scheme')
self.interpolator = mock.Mock(name='interpolator')
self.interpolator.return_value = mock.sentinel.RESULT
self.scheme.interpolator.return_value = self.interpolator
self.collapse_coord = True
def setUp(self):
self.cube = stock.simple_2d()
self.scheme = mock.Mock(name='interpolation scheme')
self.interpolator = mock.Mock(name='interpolator')
self.interpolator.return_value = mock.sentinel.RESULT
self.scheme.interpolator.return_value = self.interpolator
self.collapse_coord = True
def test_single_cube_with_transform(self):
transform = lambda cube: {'long_name': 'wibble'}
target = ConcreteReferenceTarget('foo', transform)
src = stock.simple_2d()
target.add_cube(src)
dest = target.as_cube()
self.assertEqual(dest.long_name, 'wibble')
self.assertNotEqual(dest, src)
dest.long_name = src.long_name
self.assertEqual(dest, src)
def test_single_cube_with_transform(self):
transform = lambda cube: {'long_name': 'wibble'}
target = ConcreteReferenceTarget('foo', transform)
src = stock.simple_2d()
target.add_cube(src)
dest = target.as_cube()
self.assertEqual(dest.long_name, 'wibble')
self.assertNotEqual(dest, src)
dest.long_name = src.long_name
self.assertEqual(dest, src)
def test_skip_contour(self):
# Contours should not be added if data is all below second level. See #4086.
cube = simple_2d()
levels = [5, 15, 20, 200]
colors = ["b", "r", "y"]
with mock.patch("matplotlib.pyplot.contour") as mocked_contour:
iplt.contourf(cube, levels=levels, colors=colors, antialiased=True)
mocked_contour.assert_not_called()
def setUp(self):
# We have a 2d cube with dimensionality (bar: 3; foo: 4)
self.cube = simple_2d(with_bounds=False)
self.foo = self.cube.coord('foo').points
self.foo_index = np.arange(self.foo.size)
self.bar = self.cube.coord('bar').points
self.bar_index = np.arange(self.bar.size)
self.data = self.cube.data
self.dataT = self.data.T
self.mpl_patch = self.patch('matplotlib.pyplot.contour')
self.draw_func = qplt.contour
def setUp(self):
# We have a 2d cube with dimensionality (bar: 3; foo: 4)
self.cube = simple_2d(with_bounds=False)
self.foo = self.cube.coord("foo").points
self.foo_index = np.arange(self.foo.size)
self.bar = self.cube.coord("bar").points
self.bar_index = np.arange(self.bar.size)
self.data = None
self.dataT = None
self.mpl_patch = self.patch("matplotlib.pyplot.scatter")
self.draw_func = qplt.points
def test_single_cube_with_transform(self):
def transform(cube):
return {"long_name": "wibble"}
target = ConcreteReferenceTarget("foo", transform)
src = stock.simple_2d()
target.add_cube(src)
dest = target.as_cube()
self.assertEqual(dest.long_name, "wibble")
self.assertNotEqual(dest, src)
dest.long_name = src.long_name
self.assertEqual(dest, src)
def test_apply_contour_nans(self):
# Presence of nans should not prevent contours being added.
cube = simple_2d()
cube.data = cube.data.astype(np.float_)
cube.data[0, 0] = np.nan
levels = [2, 4, 6, 8]
colors = ["b", "r", "y"]
with mock.patch("matplotlib.pyplot.contour") as mocked_contour:
iplt.contourf(cube, levels=levels, colors=colors, antialiased=True)
mocked_contour.assert_called_once()
def setUp(self):
# We have a 2d cube with dimensionality (bar: 3; foo: 4)
self.cube = simple_2d(with_bounds=True)
coord = self.cube.coord('foo')
self.foo = coord.contiguous_bounds()
self.foo_index = np.arange(coord.points.size + 1)
coord = self.cube.coord('bar')
self.bar = coord.contiguous_bounds()
self.bar_index = np.arange(coord.points.size + 1)
self.data = self.cube.data
self.dataT = self.data.T
self.mpl_patch = self.patch('matplotlib.pyplot.pcolormesh')
self.draw_func = qplt.outline
def setUp(self):
# We have a 2d cube with dimensionality (bar: 3; foo: 4)
self.cube = simple_2d(with_bounds=False)
self.foo = self.cube.coord('foo').points
self.foo_index = np.arange(self.foo.size)
self.bar = self.cube.coord('bar').points
self.bar_index = np.arange(self.bar.size)
self.data = self.cube.data
self.dataT = self.data.T
mocker = mock.Mock(alpha=0, antialiased=False)
self.mpl_patch = self.patch('matplotlib.pyplot.contourf',
return_value=mocker)
self.draw_func = iplt.contourf
def setUp(self):
# We have a 2d cube with dimensionality (bar: 3; foo: 4)
self.cube = simple_2d(with_bounds=False)
self.foo = self.cube.coord("foo").points
self.foo_index = np.arange(self.foo.size)
self.bar = self.cube.coord("bar").points
self.bar_index = np.arange(self.bar.size)
self.data = self.cube.data
self.dataT = self.data.T
mocker = mock.Mock(alpha=0, antialiased=False)
self.mpl_patch = self.patch("matplotlib.pyplot.contourf",
return_value=mocker)
self.draw_func = iplt.contourf
def blockplot_setup(self):
# We have a 2d cube with dimensionality (bar: 3; foo: 4)
self.cube = simple_2d(with_bounds=True)
coord = self.cube.coord('foo')
self.foo = coord.contiguous_bounds()
self.foo_index = np.arange(coord.points.size + 1)
coord = self.cube.coord('bar')
self.bar = coord.contiguous_bounds()
self.bar_index = np.arange(coord.points.size + 1)
self.data = self.cube.data
self.dataT = self.data.T
self.draw_func = self.blockplot_func()
patch_target_name = 'matplotlib.pyplot.' + self.draw_func.__name__
self.mpl_patch = self.patch(patch_target_name)
def blockplot_setup(self):
# We have a 2d cube with dimensionality (bar: 3; foo: 4)
self.cube = simple_2d(with_bounds=True)
coord = self.cube.coord('foo')
self.foo = coord.contiguous_bounds()
self.foo_index = np.arange(coord.points.size + 1)
coord = self.cube.coord('bar')
self.bar = coord.contiguous_bounds()
self.bar_index = np.arange(coord.points.size + 1)
self.data = self.cube.data
self.dataT = self.data.T
self.draw_func = self.blockplot_func()
patch_target_name = 'matplotlib.pyplot.' + self.draw_func.__name__
self.mpl_patch = self.patch(patch_target_name)
def setUp(self):
# We have a 2d cube with dimensionality (bar: 3; foo: 4)
self.cube = simple_2d(with_bounds=True)
coord = self.cube.coord("foo")
self.foo = coord.contiguous_bounds()
self.foo_index = np.arange(coord.points.size + 1)
coord = self.cube.coord("bar")
self.bar = coord.contiguous_bounds()
self.bar_index = np.arange(coord.points.size + 1)
self.data = self.cube.data
self.dataT = self.data.T
self.mpl_patch = self.patch("matplotlib.pyplot.pcolor",
return_value=None)
self.draw_func = qplt.pcolor
def setUp(self):
# We have a 2d cube with dimensionality (bar: 3; foo: 4)
self.cube = simple_2d(with_bounds=False)
self.foo = self.cube.coord('foo').points
self.foo_index = np.arange(self.foo.size)
self.bar = self.cube.coord('bar').points
self.bar_index = np.arange(self.bar.size)
self.data = self.cube.data
self.dataT = self.data.T
mocker = mock.Mock(alpha=0, antialiased=False)
self.mpl_patch = self.patch('matplotlib.pyplot.contourf',
return_value=mocker)
# Also need to mock the colorbar.
self.patch('matplotlib.pyplot.colorbar')
self.draw_func = qplt.contourf
def test_apply_contour_nans(self):
# Presence of nans should not prevent contours being added.
cube = simple_2d()
cube.data = cube.data.astype(np.float_)
cube.data[0, 0] = np.nan
levels = [2, 4, 6, 8]
colors = ["b", "r", "y"]
iplt.contourf(cube, levels=levels, colors=colors, antialiased=True)
ax = plt.gca()
# If contour has been called, last collection will be a LineCollection.
self.assertIsInstance(ax.collections[-1],
matplotlib.collections.LineCollection)
def test_skip_contour(self):
# Contours should not be added if data is all below second level. See #4086.
cube = simple_2d()
levels = [5, 15, 20, 200]
colors = ["b", "r", "y"]
iplt.contourf(cube, levels=levels, colors=colors, antialiased=True)
ax = plt.gca()
# Expect 3 PathCollection objects (one for each colour) and no LineCollection
# objects.
for collection in ax.collections:
self.assertIsInstance(collection,
matplotlib.collections.PathCollection)
self.assertEqual(len(ax.collections), 3)
def test_single(self):
cubes = [stock.simple_2d()]
self.assertEqual(concatenate(cubes), cubes)
def setUp(self):
self.cube = stock.simple_2d()
self.cm = CellMethod('mean', 'foo', '1 hour')
self.cube.cell_methods = (self.cm, )
def test_single_cube_no_transform(self):
target = ConcreteReferenceTarget("foo")
src = stock.simple_2d()
target.add_cube(src)
self.assertIs(target.as_cube(), src)
def setUp(self):
self.cube = stock.simple_2d()
self.cm = CellMethod("mean", "foo", "1 hour")
self.cube.cell_methods = (self.cm, )
def setUp(self):
super(TestGraphicStringCoord, self).setUp()
self.cube = simple_2d(with_bounds=True)
self.cube.add_aux_coord(AuxCoord(list("abcd"), long_name="str_coord"), 1)
def test_1d_coords_as_integers_swapped(self):
cube = simple_2d()
defn = iplt._get_plot_defn_custom_coords_picked(cube, (0, 1),
POINT_MODE)
self.assertEqual([coord for coord in defn.coords], [1, 0])
self.assertTrue(defn.transpose)
def test_compare_cubes_incompatible(self):
test_case_a = stock.simple_2d()
test_case_b = stock.simple_3d()
test_cubes = [test_case_a, test_case_b]
self.assertRaises(OSError, ch.compare_cubes, test_cubes)
def test_single_cube_no_transform(self):
target = ConcreteReferenceTarget('foo')
src = stock.simple_2d()
target.add_cube(src)
self.assertIs(target.as_cube(), src)
def setUp(self):
super(TestGraphicStringCoord, self).setUp()
self.cube = simple_2d(with_bounds=True)
self.cube.add_aux_coord(AuxCoord(list('abcd'),
long_name='str_coord'), 1)
self.lat_lon_cube = lat_lon_cube()
def setUp(self):
self.cube = stock.simple_2d()
self.extrapolation = 'extrapolation_mode'
self.scheme = mock.Mock(name='linear scheme')
def test_multi_equal(self):
cubes = [stock.simple_2d()] * 2
self.assertEqual(concatenate(cubes), cubes)
def test_1d_coords_as_integers(self):
cube = simple_2d()
defn = iplt._get_plot_defn_custom_coords_picked(cube, (1, 0),
POINT_MODE)
self.assertEqual([coord for coord in defn.coords], [0, 1])
self.assertFalse(defn.transpose)
def setUp(self):
self.cube = stock.simple_2d()
self.extrapolation = 'extrapolation_mode'
self.scheme = mock.Mock(name='linear scheme')
def setUp(self):
self.cube = stock.simple_2d()
self.cm = CellMethod('mean', 'foo', '1 hour')
self.cube.cell_methods = (self.cm, )
def test_single(self):
cubes = [stock.simple_2d()]
self.assertEqual(concatenate(cubes), cubes)
def test_axis_order_xy(self):
cube_xy = simple_2d()
defn = iplt._get_plot_defn(cube_xy, iris.coords.POINT_MODE)
self.assertEqual([coord.name() for coord in defn.coords],
['bar', 'foo'])
def test_axis_order_yx(self):
cube_yx = simple_2d()
cube_yx.transpose()
defn = iplt._get_plot_defn(cube_yx, iris.coords.POINT_MODE)
self.assertEqual([coord.name() for coord in defn.coords],
['foo', 'bar'])
def test_multi_equal(self):
cubes = [stock.simple_2d()] * 2
self.assertEqual(concatenate(cubes), cubes)
