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Sale price spatial lag configuration #296

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Sale price spatial lag configuration #296

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4 changes: 2 additions & 2 deletions openavmkit/data.py
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Original file line number Diff line number Diff line change
Expand Up @@ -842,7 +842,7 @@ def _enrich_sup_spatial_lag_for_model_group(
df_sub = df_sub[~pd.isna(df_sub["latitude"]) & ~pd.isna(df_sub["longitude"])]

# Choose the number of nearest neighbors to use
k = 5 # adjust this number as needed
k = s_sl.get("sale_price", 5) # adjust this number as needed

df_sub_train = df_sub.loc[df_sub["key_sale"].isin(train_keys)].copy()

Expand Down Expand Up @@ -878,7 +878,7 @@ def _enrich_sup_spatial_lag_for_model_group(

# Query the tree: for each parcel in df_universe, find the k nearest sales
# distances: shape (n_universe, k); indices: corresponding indices in df_sales
distances, indices = sales_tree.query(universe_coords, k=k)
distances, indices = sales_tree.query(universe_coords, k=min(len(sales_coords_train), k))

# Ensure that distances and indices are 2D arrays (if k==1, reshape them)
if k == 1:
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