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adapt tests to new implementation
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@aleeciu
aleeciu committed Nov 8, 2023
1 parent 157414b commit 8200a54
Showing 1 changed file with 43 additions and 71 deletions.
114 changes: 43 additions & 71 deletions climada/hazard/test/test_trop_cyclone.py
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Original file line number Diff line number Diff line change
Expand Up @@ -36,6 +36,7 @@
_stat_er_2011, tctrack_to_si, MBAR_TO_PA, KM_TO_M, H_TO_S,
)
from climada.hazard.centroids.centr import Centroids
from climada.hazard.tc_clim_change import get_knutson_scaling_factor
import climada.hazard.test as hazard_test

DATA_DIR = Path(hazard_test.__file__).parent.joinpath('data')
Expand Down Expand Up @@ -413,7 +414,7 @@ def test_apply_climate_scenario_track(self):
intensity[3, 3] = 3
tc = TropCyclone(
intensity=sparse.csr_matrix(intensity),
basin=['NA', 'NA', 'NA', 'NO'],
basin=['NA', 'NA', 'NA', 'WP'],
category=np.array([2, 0, 4, 1]),
event_id=np.arange(4),
frequency=np.ones(4) * 0.5,
Expand All @@ -435,14 +436,9 @@ def test_apply_climate_scenario_track(self):

def test_apply_criterion_track(self):
"""Test _apply_criterion function."""
criterion = [
{'basin': 'NA', 'category': [1, 2, 3, 4, 5],
'year': 2100, 'change': 1.045}
]
scale = 0.75

# artificially increase the size of
# the hazard by repeating (tiling) the data:
# the hazard by repeating (tiling) the
# data:
ntiles = 8

intensity = np.zeros((4, 10))
Expand All @@ -451,6 +447,7 @@ def test_apply_criterion_track(self):
intensity[2, :] = np.arange(10, 20)
intensity[3, 3] = 3
intensity = np.tile(intensity, (ntiles, 1))

tc = TropCyclone(
intensity=sparse.csr_matrix(intensity),
basin=ntiles * ['NA', 'NA', 'NA', 'WP'],
Expand All @@ -459,79 +456,54 @@ def test_apply_criterion_track(self):
event_id=np.arange(intensity.shape[0]),
)

NA_scaling_05, NA_scaling_45 = [
get_knutson_scaling_factor(variable=variable,
basin='NA').loc[2035, '8.5']
for variable in ['cat05', 'cat45']
]
WP_scaling_05, WP_scaling_45 = [
get_knutson_scaling_factor(variable=variable,
basin='WP').loc[2035, '8.5']
for variable in ['cat05', 'cat45']
]

NA_bas_sel = np.array([True, True, True, False]*ntiles)
WP_bas_sel = ~NA_bas_sel

cat05_sel = np.repeat(True, ntiles*4)
cat45_sel = np.array([False, False, True, False]*ntiles)
cat03_sel = ~cat45_sel

NA_scaling_03 = (NA_scaling_05 * np.sum(tc.frequency[cat05_sel & NA_bas_sel])
- NA_scaling_45 * np.sum(tc.frequency[cat45_sel & NA_bas_sel])
) / np.sum(tc.frequency[cat03_sel & NA_bas_sel])

WP_scaling_03 = (WP_scaling_05 * np.sum(tc.frequency[cat05_sel & WP_bas_sel])
- WP_scaling_45 * np.sum(tc.frequency[cat45_sel & WP_bas_sel])
) / np.sum(tc.frequency[cat03_sel & WP_bas_sel])

tc_cc = tc.apply_climate_scenario_knu()

for i_tile in range(ntiles):
offset = i_tile * 4
# no factor applied because of category 0
# factors to events in basin NA
np.testing.assert_array_equal(
tc.frequency[offset + 1], tc_cc.frequency[offset + 1]
tc.frequency[offset + 1] * (1 + NA_scaling_03/100),
tc_cc.frequency[offset + 1]
)
# no factor applied because of basin "WP"
np.testing.assert_array_equal(
tc.frequency[offset + 3], tc_cc.frequency[offset + 3]
)
# factor is applied to the remaining events
np.testing.assert_array_almost_equal(
tc.frequency[offset + 0] * 1.03375,
tc.frequency[offset + 0] * (1 + NA_scaling_03/100),
tc_cc.frequency[offset + 0]
)
np.testing.assert_array_almost_equal(
tc.frequency[offset + 2] * 1.03375,
np.testing.assert_array_equal(
tc.frequency[offset + 2] * (1 + NA_scaling_45/100),
tc_cc.frequency[offset + 2]
)

def test_two_criterion_track(self):
"""Test apply_climate_scenario_knu function with two criteria"""
criterion = [
{'basin': 'WP', 'category': [1, 2, 3, 4, 5],
'year': 2100, 'change': 1.025},
{'basin': 'NA', 'category': [0, 1, 2, 3, 4, 5],
'year': 2100, 'change': 0.7},
{'basin': 'NA', 'category': [1, 2, 3, 4, 5],
'year': 2100, 'change': 1},
{'basin': 'NA', 'category': [3, 4, 5],
'year': 2100, 'change': 1},
{'basin': 'NA', 'category': [4, 5],
'year': 2100, 'change': 2}
]
scale = 0.75

intensity = np.zeros((4, 10))
intensity[0, :] = np.arange(10)
intensity[1, 5] = 10
intensity[2, :] = np.arange(10, 20)
intensity[3, 3] = 3
tc = TropCyclone(
intensity=sparse.csr_matrix(intensity),
frequency=np.ones(4) * 0.5,
basin=['NA', 'NA', 'NA', 'WP'],
category=np.array([2, 0, 4, 1]),
event_id=np.arange(4),
)

tc_cc = tc.apply_climate_scenario_knu(criterion, scale)

res_frequency = np.ones(4) * 0.5
res_frequency[1] = 0.5 * (1 + (0.7 - 1) * scale)
res_frequency[2] = 0.5 * (1 + (2 - 1) * scale)
res_frequency[3] = 0.5 * (1 + (1.025 - 1) * scale)
self.assertTrue(np.allclose(tc_cc.frequency, res_frequency))

def test_no_negative_freq(self):
"""Test apply_climate_scenario_knu with too high changes and check
that no negative frequencies are returned."""
criterion = [{'basin': 'SP', 'category': [0, 1],
'year': 2100, 'change': 0.5}
]

tc = TropCyclone(
frequency=np.ones(2),
basin=['SP', 'SP'],
category=np.array([0, 1]),
)

tc_cc = tc.apply_climate_scenario_knu(criterion, 3)
self.assertTrue(tc_cc.frequency.min() >= 0.)
# factors to events in basin WP
np.testing.assert_array_equal(
tc.frequency[offset + 3] * (1 + WP_scaling_03/100),
tc_cc.frequency[offset + 3]
)

class TestDumpReloadCycle(unittest.TestCase):
def setUp(self):
Expand Down

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