Adapt Hazard from_hdf5 and write_hdf5 to forecast attributes#1181
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ValentinGebhart merged 3 commits intoforecast-classfrom Dec 9, 2025
Merged
Adapt Hazard from_hdf5 and write_hdf5 to forecast attributes#1181ValentinGebhart merged 3 commits intoforecast-classfrom
ValentinGebhart merged 3 commits intoforecast-classfrom
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ValentinGebhart
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chahank,
emanuel-schmid and
peanutfun
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ValentinGebhart
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chahank
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chahank,
emanuel-schmid and
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chahank
reviewed
Dec 9, 2025
climada/hazard/test/test_forecast.py
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| for key in haz_fc.__dict__.keys(): | ||
| if key not in ["intensity", "fraction"]: | ||
| npt.assert_array_equal(haz_fc.__dict__[key], haz_fc_read.__dict__[key]) |
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A bit confused. What about non array values? I would expect this to fail for units, haz_type, pool, etc.
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I would thus also invert the if.
if key in [intensity, fraction]:
...
elif key in [...]. (arrays)
....
else. (non arrays)
....
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np.testing.assert_array_equal also works with the other types of our hazards, right? e.g. these all pass:
np.testing.assert_array_equal(2.,2.)
np.testing.assert_array_equal([1,2], [1,2])
I will adapt the order of the if statement
chahank
reviewed
Dec 9, 2025
climada/hazard/test/test_forecast.py
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| haz_fc_read = HazardForecast.from_hdf5(file_name) | ||
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| assert haz_fc_read.lead_time.dtype == np.dtype("timedelta64[ns]") | ||
| assert haz_fc_read.member.dtype == int |
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This test might lead to failure. The init of hazard forecast does not require integer. Just a numpy array of things.
chahank
approved these changes
Dec 9, 2025
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Changes proposed in this PR:
This PR fixes #1134
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