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Add timezone mask test on europe lat/lon domain
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@tjtg
tjtg committed Nov 24, 2021
1 parent 196c83e commit c2c7591
Showing 1 changed file with 113 additions and 28 deletions.
141 changes: 113 additions & 28 deletions improver_tests/generate_ancillaries/test_GenerateTimezoneMask.py
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Original file line number Diff line number Diff line change
Expand Up @@ -89,11 +89,24 @@ def global_grid_fixture_360() -> Cube:
return cube


@pytest.fixture(name="europe_grid")
def europe_grid_fixture() -> Cube:
data = np.zeros((10, 10), dtype=np.float32)
cube = set_up_variable_cube(
data,
name="template",
grid_spacing=1,
domain_corner=(45, -5),
attributes=GLOBAL_ATTRIBUTES,
)
return cube


@pytest.fixture(name="uk_grid")
def uk_grid_fixture() -> Cube:
"""UK grid template"""

data = np.zeros((21, 22), dtype=np.float32)
data = np.zeros((11, 11), dtype=np.float32)
cube = set_up_variable_cube(
data,
name="template",
Expand Down Expand Up @@ -160,7 +173,7 @@ def test__get_coordinate_pairs(request, grid_fixture):
expected_data = {
"global_grid": [[-90.0, -180.0], [-90.0, -80.0], [90.0, 180.0]],
"global_grid_360": [[-90.0, -180.0], [-90.0, -80.0], [90.0, 180.0]],
"uk_grid": [[44.517, -17.117], [45.548, -4.913], [62.026, 14.410]],
"uk_grid": [[44.517, -17.117], [45.548, -4.913], [54.263, -5.401]],
}

grid = request.getfixturevalue(grid_fixture)
Expand Down Expand Up @@ -245,7 +258,7 @@ def test__create_template_cube(request, grid_fixture, include_dst):

expected = {
"global_grid": {"shape": (19, 37), "attributes": GLOBAL_ATTRIBUTES},
"uk_grid": {"shape": (21, 22), "attributes": UK_ATTRIBUTES},
"uk_grid": {"shape": (11, 11), "attributes": UK_ATTRIBUTES},
}

# Set expected includes_daylight_savings attribute
Expand Down Expand Up @@ -309,52 +322,113 @@ def test__group_timezones_empty_group(timezone_mask):


# Expected data for process tests

# ungrouped
GLOBAL_GRID = {"shape": (27, 19, 37), "min": -12 * 3600, "max": 14 * 3600}
# grouped
GLOBAL_GRID_GR = {"shape": (2, 19, 37), "min": -6 * 3600, "max": 6 * 3600}
UK_GRID_GR = {"shape": (2, 21, 22), "min": -6 * 3600, "max": 6 * 3600}

EXPECTED_TIME = {None: 1510286400, "20200716T1500Z": 1594911600}
GROUPED_MIN_MAX = {"min": -6 * 3600, "max": 6 * 3600}
EXPECTED = {
"ungrouped": {
"global": {
None: GLOBAL_GRID,
"20200716T1500Z": GLOBAL_GRID,
"indices": (12, 2),
},
"uk": {
None: {"shape": (4, 21, 22), "min": -2 * 3600, "max": 1 * 3600},
None: {
"shape": (3, 11, 11),
"min": -1 * 3600,
"max": 1 * 3600,
"data": np.array(
[
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
]
),
},
"20200716T1500Z": {
"shape": (4, 11, 11),
"min": -1 * 3600,
"max": 2 * 3600,
"data": np.array(
[
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0],
[1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1],
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
],
),
},
},
"europe": {
None: {
"shape": (2, 10, 10),
"min": 0,
"max": 1 * 3600,
"data": np.array(
[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]
),
},
"20200716T1500Z": {
"shape": (5, 21, 22),
"min": -2 * 3600,
"shape": (3, 10, 10),
"min": 0,
"max": 2 * 3600,
"data": np.array(
[
[1, 0, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
]
),
},
"indices": (2, 10),
},
},
"grouped": {
"global": {
None: GLOBAL_GRID_GR,
"20200716T1500Z": GLOBAL_GRID_GR,
"indices": (0, 2),
"uk": {
None: {
"shape": (2, 11, 11),
**GROUPED_MIN_MAX,
"data": np.array(
[
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
]
),
},
"20200716T1500Z": {
"shape": (2, 11, 11),
**GROUPED_MIN_MAX,
"data": np.array(
[
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0],
[1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1],
],
),
},
},
"europe": {
None: {
"shape": (2, 10, 10),
**GROUPED_MIN_MAX,
"data": np.array(
[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]
),
},
"20200716T1500Z": {
"shape": (2, 10, 10),
**GROUPED_MIN_MAX,
"data": np.array(
[[1, 0, 1, 1, 1, 1, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 1, 1, 1, 1]]
),
},
},
"uk": {None: UK_GRID_GR, "20200716T1500Z": UK_GRID_GR, "indices": (0, 9)},
},
}


@pytest.mark.parametrize("grouping", ["ungrouped", "grouped"])
@pytest.mark.parametrize("time", [None, "20200716T1500Z"])
@pytest.mark.parametrize("grid_fixture", ["global_grid", "global_grid_360", "uk_grid"])
@pytest.mark.parametrize("grid_fixture", ["uk_grid", "europe_grid"])
def test_process(request, grid_fixture, time, grouping):
"""Test that the process method returns cubes that take the expected form
for different grids and different dates.
The output data is checked in the acceptance tests as a large number of
data points are required to reliably check it and the output is highly
subject to changes based on the version of the timezone database in use."""
The output data is primarily checked in the acceptance tests as a reasonably
large number of data points are required to reliably check it. Here we check
only a small sample."""

domain = grid_fixture.split("_")[0]
groupings = None
Expand All @@ -379,3 +453,14 @@ def test_process(request, grid_fixture, time, grouping):
assert (
result.coord("UTC_offset").bounds.dtype == TIME_COORDS["UTC_offset"].dtype
)
# slice the first spatial dimension to moderate size of expected arrays
assert_array_equal(result.data[:, 9, :], expected["data"])

# check each spatial location in the UTC_offset dimension
zone_count = np.count_nonzero(result.data, axis=0)
if grouping == "grouped":
# grouped outputs have a single UTC_offset with a non-zero entry
assert_array_equal(zone_count, 1)
else:
# ungrouped outputs have a single UTC_offset with a zero entry
assert_array_equal(zone_count, expected["shape"][0] - 1)

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