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added upgrade eligibility check for optimisation

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This commit is contained in:
Khalim Conn-Kowlessar 2025-08-13 11:42:42 +01:00
parent b73525e571
commit 06e8204404
1 changed files with 23 additions and 2 deletions
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25
recommendations/tests/test_optimisers.py
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@ -779,12 +779,24 @@ def _filter_measures_by_types(input_measures, allowed_types):
return filtered
def optimise_with_funding_paths(input_measures, budget=None, target_gain=None, social=False):
def _is_eligible_funding_package(scheme, starting_sap, total_gain):
if scheme == "eco4":
# We check if we meet the upgrade requirements
# If the property is an E or above, we need to upgrade to a C or above
if starting_sap >= 39: # ie. EPC C or above
return starting_sap + total_gain >= 69
if scheme == "gbis":
# GBIS is a fixed measure only, so we don't check the gain
return True
def optimise_with_funding_paths(p, input_measures, housing_type, budget=None, target_gain=None):
"""
run_optimizer(sub_measures, budget, target_gain) -> (picked_options, sub_cost, sub_gain)
"""
funding_paths = make_funding_paths(p, input_measures, body.housing_type)
funding_paths = make_funding_paths(p, input_measures, housing_type)
# We now produce a fabric only path for ECO4
# We add in generic insulation funding paths (where there is no fixed measure)
@ -811,6 +823,8 @@ def optimise_with_funding_paths(input_measures, budget=None, target_gain=None, s
if picked is None:
continue
scheme = _path_scheme([path_spec])
solutions.append(
{
"fixed_ids": [],
@ -818,8 +832,11 @@ def optimise_with_funding_paths(input_measures, budget=None, target_gain=None, s
"total_cost": sub_cost,
"total_gain": sub_gain,
"path": path_spec,
"scheme": scheme,
"is_eligible": _is_eligible_funding_package(scheme, p.data["current-energy-efficiency"], sub_gain)
}
)
continue
# 1) expand fixed selections for this path
@ -872,12 +889,16 @@ def optimise_with_funding_paths(input_measures, budget=None, target_gain=None, s
total_gain = fixed_gain + sub_gain
total_picks = fixed_items + picked
scheme = _path_scheme(path_spec)
solutions.append({
"fixed_ids": fixed_ids,
"items": total_picks,
"total_cost": total_cost,
"total_gain": total_gain,
"path": path_spec,
"scheme": scheme,
"is_eligible": _is_eligible_funding_package(scheme, p.data["current-energy-efficiency"], sub_gain)
})
solutions = pd.DataFrame(solutions)