Remove old implementation of region allocation/reduction endpoints

Author: sverhoeven

ws.py

@@ -756,49 +756,9 @@ def ndc_projections(region):
     return {"ndc_inventory": ndc_range_inventory(region), "ndc_jones": ndc_range_jones(region)}
 
 
-def get_ds(region):
-    if region not in available_region_files:
-        raise ValueError(f"Region {region} not found")
-    fn = available_region_files[region]
-    return xr.open_dataset(fn)
-
-
-def emission_allocation_per_method_old(region, allocation_method):
-    selection = global_pathway_choices()
-    ds = get_ds(region)[allocation_method].sel(**selection).rename(Time="time")
-    # set time as the first dimension
-    dim_order = ["time"] + [dim for dim in ds.dims if dim != "time"]
-    ds = ds.transpose(*dim_order)
-
-    # extract the 'most reasonable' (mr) df which will be the main trajectory line
-    mr_selection = dict()
-    if allocation_method in ["PC", "PCC", "AP", "GDR", "ECPC"]:
-        mr_selection.update(Scenario="SSP2")
-    if allocation_method in ["PCC", "ECPC"]:
-        mr_selection.update(Convergence_year=DEFAULT_CONVERGENCE_YEAR)
-    if allocation_method in ["ECPC", "GDR"]:
-        mr_selection.update(Historical_startyear=DEFAULT_HISTORICAL_STARTYEAR)
-    if allocation_method == "ECPC":
-        mr_selection.update(
-            Discount_factor=DEFAULT_DISCOUNT_FACTOR,
-        )
-    if allocation_method == "GDR":
-        mr_selection.update(RCI_weight=DEFAULT_RCI_WEIGHT, Capability_threshold=DEFAULT_CAPABILITY_THRESHOLD)
-
-    mr_df = ds.sel(**mr_selection).to_pandas().rename("mean")
-
-    if mr_df.isna().all():
-        return None
-
-    agg_dims = [dim for dim in ds.dims if dim != "time"]
-    min_df = ds.min(agg_dims, skipna=True).to_pandas().rename("min")
-    max_df = ds.max(agg_dims, skipna=True).to_pandas().rename("max")
-
-    return pd.concat([mr_df, min_df, max_df], axis=1).reset_index().dropna().to_dict(orient="records")
-
-
 allocation_methods = {"PC", "PCC", "AP", "GDR", "ECPC", "GF"}
 
+
 def emission_allocation_per_method(allocator_ds, allocation_method):
     ds = allocator_ds.rename(Time="time")
     dim_order = ["time"] + [dim for dim in ds.dims if dim != "time"]
@@ -830,14 +790,15 @@ def emission_allocation_per_method(allocator_ds, allocation_method):
 
     return pd.concat([mr_df, min_df, max_df], axis=1).reset_index().dropna().to_dict(orient="records")
 
+
 @app.get("/timeseries/<region>/emissions/allocations")
 def emission_allocations(region):
     allocator = create_allocator(region)
     allocations = {}
     selection = global_pathway_choices()
     for allocation_method in allocation_methods:
         allocation_data = emission_allocation_per_method(
-            allocator.xr_total[allocation_method].sel(**selection), 
+            allocator.xr_total[allocation_method].sel(**selection),
             allocation_method,
         )
         if allocation_data is None:
@@ -848,11 +809,13 @@ def emission_allocations(region):
 
 @lru_cache(maxsize=20)
 def create_allocator(region):
-    lulucf="incl"
-    gas="GHG"
-    input_file = '../effort-sharing/notebooks/input.yml'
+    lulucf = "incl"
+    gas = "GHG"
+    input_file = "../effort-sharing/notebooks/input.yml"
     allocator = allocation(
-        region, lulucf=lulucf, gas=gas,
+        region,
+        lulucf=lulucf,
+        gas=gas,
         input_file=input_file,
     )
     allocator.gf()
@@ -867,18 +830,6 @@ def create_allocator(region):
     allocator.gdr()
     return allocator
 
-def emission_allocations_old(region):
-    """
-    http://127.0.0.1:5000/timeseries/USA/emissions/allocations?exceedanceRisk=0.67&negativeEmissions=0.4&temperature=1.8: 36.94ms
-    """
-    allocations = {}
-    for allocation_method in allocation_methods:
-        allocation = emission_allocation_per_method_old(region, allocation_method)
-        if allocation is None:
-            continue
-        allocations[allocation_method] = allocation
-    return allocations
-
 
 @app.get("/statistics/reductions/<region>")
 def allocation_reduction(region):
@@ -909,34 +860,6 @@ def allocation_reduction(region):
 
     return reductions
 
-def allocation_reduction_old(region):
-    periods = (2030, 2040)
-    selection = dict(
-        **global_pathway_choices(),
-        Time=periods,
-    )
-
-    hist = ds_global.GHG_hist.sel(Region=region, Time=1990).values + 0
-    ds = get_ds(region)
-
-    reductions = {}
-    for allocation_method in allocation_methods:
-        pselection = selection.copy()
-        if allocation_method in ["PC", "PCC", "AP", "GDR", "ECPC"]:
-            pselection.update(Scenario="SSP2")
-        if allocation_method in ["PCC", "ECPC"]:
-            pselection.update(Convergence_year=DEFAULT_CONVERGENCE_YEAR)
-        reductions[allocation_method] = {}
-        for period in periods:
-            pselection.update(Time=period)
-            es = ds[allocation_method].sel(**pselection).mean().values + 0
-            if np.isnan(es) or np.isnan(hist) or hist == 0:
-                reductions[allocation_method][period] = None
-            else:
-                reductions[allocation_method][period] = -(es - hist) / hist * 100
-
-    return reductions
-
 
 if __name__ == "__main__":
     print(create_allocator("BRA"))