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41 lines
1.6 KiB
Python
41 lines
1.6 KiB
Python
def prepare_input_measures(property_recommendations, goal, housing_type):
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"""
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Basic function to convert recommendations_to_upload to a format that is
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suitable for the optimiser - large
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:param property_recommendations: object containing the recommendations, created in the plan trigger api
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:param goal: goal to be optimised for, should be one of the keys in gain_map. E.g. if the gain is SAP points,
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the goal should reflect that desired gain
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:param housing_type: type of housing the recommendations are for - should be one of "Social" or "Private"
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:return: Nested list of input measures
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"""
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if housing_type not in ["Social", "Private"]:
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raise ValueError("Invalid housing type - investigate me")
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goal_map = {
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"Increase EPC": "sap_points"
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}
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goal_key = goal_map[goal]
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if not goal_key:
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raise NotImplementedError("Not implemented this gain type - investigate me")
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# We don't include suspended and solid floor insulation as possible measures in private housing, because
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# of the need to decant the tenant
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ignored_measures = ["suspended_floor_insulation", "solid_floor_insulation"] if housing_type == "Private" else []
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input_measures = []
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for recs in property_recommendations:
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input_measures.append(
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[
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{
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"id": rec["recommendation_id"],
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"cost": rec["total"],
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"gain": rec[goal_key],
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"type": rec["type"]
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}
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for rec in recs if rec["type"] not in ignored_measures
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]
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)
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return input_measures
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