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adding impenetrable surfaces

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lucasmbrown-usds 2021-12-05 20:58:45 -05:00
parent f0295d21e2
commit 5e19dac35b
1 changed files with 16 additions and 0 deletions
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16
data/data-pipeline/data_pipeline/score/score_l.py
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@ -180,6 +180,7 @@ class ScoreL(Score):
field_names.EXPECTED_AGRICULTURE_LOSS_RATE_LOW_INCOME_FIELD, field_names.EXPECTED_AGRICULTURE_LOSS_RATE_LOW_INCOME_FIELD,
field_names.EXPECTED_BUILDING_LOSS_RATE_LOW_INCOME_FIELD, field_names.EXPECTED_BUILDING_LOSS_RATE_LOW_INCOME_FIELD,
field_names.EXTREME_HEAT_MEDIAN_HOUSE_VALUE_LOW_INCOME_FIELD, field_names.EXTREME_HEAT_MEDIAN_HOUSE_VALUE_LOW_INCOME_FIELD,
field_names.IMPENETRABLE_SURFACES_LOW_INCOME_FIELD,
] ]
expected_population_loss_threshold = ( expected_population_loss_threshold = (
@ -220,6 +221,14 @@ class ScoreL(Score):
<= self.MEDIAN_HOUSE_VALUE_THRESHOLD <= self.MEDIAN_HOUSE_VALUE_THRESHOLD
) )
impenetrable_surfaces_threshold = (
self.df[
field_names.IMPENETRABLE_SURFACES_FIELD
+ field_names.PERCENTILE_FIELD_SUFFIX
]
>= self.ENVIRONMENTAL_BURDEN_THRESHOLD
)
self.df[field_names.EXPECTED_POPULATION_LOSS_RATE_LOW_INCOME_FIELD] = ( self.df[field_names.EXPECTED_POPULATION_LOSS_RATE_LOW_INCOME_FIELD] = (
expected_population_loss_threshold expected_population_loss_threshold
& self.df[field_names.FPL_200_SERIES] & self.df[field_names.FPL_200_SERIES]
@ -242,6 +251,13 @@ class ScoreL(Score):
& self.df[field_names.FPL_200_SERIES] & self.df[field_names.FPL_200_SERIES]
) )
self.df[
field_names.IMPENETRABLE_SURFACES_LOW_INCOME_FIELD
] = (
impenetrable_surfaces_threshold
& self.df[field_names.FPL_200_SERIES]
)
self._increment_total_eligibility_exceeded(climate_eligibility_columns) self._increment_total_eligibility_exceeded(climate_eligibility_columns)
return self.df[climate_eligibility_columns].any(axis="columns") return self.df[climate_eligibility_columns].any(axis="columns")