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assign ml node in the 950,000 range #338

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merged 1 commit into from
Apr 9, 2024
Merged

assign ml node in the 950,000 range #338

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20 changes: 15 additions & 5 deletions network_wrangler/roadwaynetwork.py
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Original file line number Diff line number Diff line change
Expand Up @@ -158,6 +158,8 @@ class RoadwayNetwork(object):
SP_WEIGHT_FACTOR = 100
MANAGED_LANES_NODE_ID_SCALAR = 500000
MANAGED_LANES_LINK_ID_SCALAR = 1000000
MANAGED_LANES_NODE_ID_MIN= 950001
MANAGED_LANES_NODE_ID_MAX= 1000000

SELECTION_REQUIRES = ["link"]

Expand Down Expand Up @@ -2172,12 +2174,20 @@ def _update_location_reference(location_reference: list):
)
return out_location_reference

ml_links_df["A"] = (
ml_links_df["A"] + RoadwayNetwork.MANAGED_LANES_NODE_ID_SCALAR
)
ml_links_df["B"] = (
ml_links_df["B"] + RoadwayNetwork.MANAGED_LANES_NODE_ID_SCALAR
# ml_links_df["A"] = (
# ml_links_df["A"] + RoadwayNetwork.MANAGED_LANES_NODE_ID_SCALAR
# )
# ml_links_df["B"] = (
# ml_links_df["B"] + RoadwayNetwork.MANAGED_LANES_NODE_ID_SCALAR
# )
unique_ids = pd.concat([ml_links_df['A'], ml_links_df['B']]).unique()
available_ids = (iter(range(RoadwayNetwork.MANAGED_LANES_NODE_ID_MIN,
RoadwayNetwork.MANAGED_LANES_NODE_ID_MAX))
)
ml_node_mapping = {original_id: next(available_ids) for original_id in unique_ids}
ml_links_df["A"] = ml_links_df['A'].map(ml_node_mapping)
ml_links_df["B"] = ml_links_df['B'].map(ml_node_mapping)

ml_links_df[RoadwayNetwork.UNIQUE_LINK_KEY] = (
ml_links_df[RoadwayNetwork.UNIQUE_LINK_KEY]
+ RoadwayNetwork.MANAGED_LANES_LINK_ID_SCALAR
Expand Down