def test_calc_decay_no_landfall_pass(self):
"""Test _calc_land_decay with no historical tracks with landfall"""
tc_track = tc.TCTracks()
tc_track.read_processed_ibtracs_csv(TEST_TRACK_SHORT)
extent = tc_track.get_extent()
land_geom = climada.util.coordinates.get_land_geometry(
extent=extent, resolution=10
)
tc.track_land_params(tc_track.data[0], land_geom)
with self.assertLogs('climada.hazard.tc_tracks_synth', level='INFO') as cm:
tc_synth._calc_land_decay(tc_track.data, land_geom)
self.assertIn('No historical track with landfall.', cm.output[0])
def test_decay_values_andrew_pass(self):
"""Test _decay_values with central pressure function."""
tc_track = tc.TCTracks()
tc_track.read_processed_ibtracs_csv(TC_ANDREW_FL)
s_rel = False
extent = tc_track.get_extent()
land_geom = climada.util.coordinates.get_land_geometry(extent=extent,
resolution=10)
tc.track_land_params(tc_track.data[0], land_geom)
v_lf, p_lf, x_val = tc_synth._decay_values(tc_track.data[0], land_geom,
s_rel)
ss_category = 6
s_cell_1 = 1 * [1.0149413347244263]
s_cell_2 = 8 * [1.047120451927185]
s_cell = s_cell_1 + s_cell_2
p_vs_lf_time_relative = [
1.0149413020277482, 1.018848167539267, 1.037696335078534,
1.0418848167539267, 1.043979057591623, 1.0450261780104713,
1.0460732984293193, 1.0471204188481675, 1.0471204188481675
]
self.assertEqual(list(p_lf.keys()), [ss_category])
self.assertEqual(p_lf[ss_category][0], array.array('f', s_cell))
self.assertEqual(p_lf[ss_category][1],
array.array('f', p_vs_lf_time_relative))
v_vs_lf_time_relative = [
0.8846153846153846, 0.6666666666666666, 0.4166666666666667,
0.2916666666666667, 0.250000000000000, 0.250000000000000,
0.20833333333333334, 0.16666666666666666, 0.16666666666666666
]
self.assertEqual(list(v_lf.keys()), [ss_category])
self.assertEqual(v_lf[ss_category],
array.array('f', v_vs_lf_time_relative))
x_val_ref = np.array([
95.9512939453125, 53.624916076660156, 143.09530639648438,
225.0262908935547, 312.5832824707031, 427.43109130859375,
570.1857299804688, 750.3827514648438, 1020.5431518554688
])
self.assertEqual(list(x_val.keys()), [ss_category])
self.assertTrue(np.allclose(x_val[ss_category], x_val_ref))
def test_calc_land_decay_pass(self):
"""Test _calc_land_decay with environmental pressure function."""
tc_track = tc.TCTracks.from_processed_ibtracs_csv(TC_ANDREW_FL)
extent = tc_track.get_extent()
land_geom = climada.util.coordinates.get_land_geometry(extent=extent,
resolution=10)
tc.track_land_params(tc_track.data[0], land_geom)
v_rel, p_rel = tc_synth._calc_land_decay(tc_track.data, land_geom)
self.assertEqual(7, len(v_rel))
for i, val in enumerate(v_rel.values()):
self.assertAlmostEqual(val, 0.0038894834)
self.assertTrue(i - 1 in v_rel.keys())
self.assertEqual(7, len(p_rel))
for i, val in enumerate(p_rel.values()):
self.assertAlmostEqual(val[0], 1.0598491)
self.assertAlmostEqual(val[1], 0.0041949237)
self.assertTrue(i - 1 in p_rel.keys())
def test_apply_decay_no_landfall_pass(self):
"""Test _apply_land_decay with no historical tracks with landfall"""
tc_track = tc.TCTracks()
tc_track.read_processed_ibtracs_csv(TEST_TRACK_SHORT)
extent = tc_track.get_extent()
land_geom = climada.util.coordinates.get_land_geometry(
extent=extent, resolution=10
)
tc.track_land_params(tc_track.data[0], land_geom)
tc_track.data[0]['orig_event_flag'] = False
tc_ref = tc_track.data[0].copy()
tc_synth._apply_land_decay(tc_track.data, dict(), dict(), land_geom)
self.assertTrue(np.allclose(tc_track.data[0].max_sustained_wind.values,
tc_ref.max_sustained_wind.values))
self.assertTrue(np.allclose(tc_track.data[0].central_pressure.values,
tc_ref.central_pressure.values))
self.assertTrue(np.allclose(tc_track.data[0].environmental_pressure.values,
tc_ref.environmental_pressure.values))
self.assertTrue(np.all(np.isnan(tc_track.data[0].dist_since_lf.values)))
def test_apply_decay_pass(self):
"""Test _apply_land_decay against MATLAB reference."""
v_rel = {
6: 0.0038950967656296597,
1: 0.0038950967656296597,
2: 0.0038950967656296597,
3: 0.0038950967656296597,
4: 0.0038950967656296597,
5: 0.0038950967656296597,
7: 0.0038950967656296597
}
p_rel = {
6: (1.0499941, 0.007978940084158488),
1: (1.0499941, 0.007978940084158488),
2: (1.0499941, 0.007978940084158488),
3: (1.0499941, 0.007978940084158488),
4: (1.0499941, 0.007978940084158488),
5: (1.0499941, 0.007978940084158488),
7: (1.0499941, 0.007978940084158488)
}
tc_track = tc.TCTracks()
tc_track.read_processed_ibtracs_csv(TC_ANDREW_FL)
tc_track.data[0]['orig_event_flag'] = False
extent = tc_track.get_extent()
land_geom = climada.util.coordinates.get_land_geometry(
extent=extent, resolution=10
)
tc.track_land_params(tc_track.data[0], land_geom)
tc_synth._apply_land_decay(tc_track.data, v_rel, p_rel, land_geom,
s_rel=True, check_plot=False)
p_ref = np.array([
1.010000000000000, 1.009000000000000, 1.008000000000000,
1.006000000000000, 1.003000000000000, 1.002000000000000,
1.001000000000000, 1.000000000000000, 1.000000000000000,
1.001000000000000, 1.002000000000000, 1.005000000000000,
1.007000000000000, 1.010000000000000, 1.010000000000000,
1.010000000000000, 1.010000000000000, 1.010000000000000,
1.010000000000000, 1.007000000000000, 1.004000000000000,
1.000000000000000, 0.994000000000000, 0.981000000000000,
0.969000000000000, 0.961000000000000, 0.947000000000000,
0.933000000000000, 0.922000000000000, 0.930000000000000,
0.937000000000000, 0.951000000000000, 0.947000000000000,
0.943000000000000, 0.948000000000000, 0.946000000000000,
0.941000000000000, 0.937000000000000, 0.955000000000000,
0.9741457117, 0.99244068917, 1.00086729492, 1.00545853355,
1.00818354609, 1.00941850023, 1.00986192053, 1.00998400565
]) * 1e3
self.assertTrue(np.allclose(p_ref, tc_track.data[0].central_pressure.values))
v_ref = np.array([
0.250000000000000, 0.300000000000000, 0.300000000000000,
0.350000000000000, 0.350000000000000, 0.400000000000000,
0.450000000000000, 0.450000000000000, 0.450000000000000,
0.450000000000000, 0.450000000000000, 0.450000000000000,
0.450000000000000, 0.400000000000000, 0.400000000000000,
0.400000000000000, 0.400000000000000, 0.450000000000000,
0.450000000000000, 0.500000000000000, 0.500000000000000,
0.550000000000000, 0.650000000000000, 0.800000000000000,
0.950000000000000, 1.100000000000000, 1.300000000000000,
1.450000000000000, 1.500000000000000, 1.250000000000000,
1.300000000000000, 1.150000000000000, 1.150000000000000,
1.150000000000000, 1.150000000000000, 1.200000000000000,
1.250000000000000, 1.250000000000000, 1.200000000000000,
0.9737967353, 0.687255951, 0.4994850556, 0.3551480462, 0.2270548036,
0.1302099557, 0.0645385918, 0.0225325851
]) * 1e2
self.assertTrue(np.allclose(v_ref, tc_track.data[0].max_sustained_wind.values))
cat_ref = tc.set_category(tc_track.data[0].max_sustained_wind.values,
tc_track.data[0].max_sustained_wind_unit)
self.assertEqual(cat_ref, tc_track.data[0].category)