Further improvements to broadcast_techs

src/muse/__main__.py

@@ -114,8 +114,8 @@ def patched_broadcast_compat_data(self, other):
             "(e.g. a capacity dataset with an 'asset' dimension) with a fully explicit "
             "technology dataset (e.g. a technology dataset with 'region' and "
             "'technology' dimensions). "
-            "Please use `broadcast_techs` on the latter object before performing this "
-            "operation."
+            "Please use `broadcast_over_assets` on the latter object before performing "
+            "this operation."
         )
 
     return self_data, other_data, dims

src/muse/agents/agent.py

@@ -257,7 +257,6 @@ def asset_housekeeping(self):
 
         - remove empty assets
         - remove years prior to current
-        - interpolate current year and forecasted year
         """
         # TODO: move this into search and make sure filters, demand_share and
         #  what not use assets from search. That would remove another bit of

src/muse/demand_share.py

@@ -246,11 +246,11 @@ def new_and_retro(
 
     from muse.commodities import is_enduse
     from muse.quantities import maximum_production
-    from muse.utilities import agent_concatenation, reduce_assets
+    from muse.utilities import agent_concatenation, broadcast_over_assets, reduce_assets
 
     current_year, investment_year = map(int, market.year.values)
 
-    def decommissioning(capacity):
+    def decommissioning(capacity, technologies):
         return decommissioning_demand(
             technologies=technologies,
             capacity=capacity.interp(
@@ -263,10 +263,13 @@ def decommissioning(capacity):
         year=[current_year, investment_year], kwargs={"fill_value": 0.0}
     )
 
+    # Select technodata for assets
+    technodata = broadcast_over_assets(technologies, capacity, installed_as_year=True)
+
     demands = new_and_retro_demands(
         capacity,
         market,
-        technologies,
+        technodata,
         timeslice_level=timeslice_level,
     )
 
@@ -284,19 +287,20 @@ def decommissioning(capacity):
 
     id_to_share: MutableMapping[Hashable, xr.DataArray] = {}
     for region in demands.region.values:
-        regional_techs = technologies.sel(region=region)
         retro_capacity: MutableMapping[Hashable, xr.DataArray] = {
             agent.uuid: agent.assets.capacity
             for agent in agents
             if agent.category == "retrofit" and agent.region == region
         }
-
+        retro_technodata: MutableMapping[Hashable, xr.Dataset] = {
+            agent_uuid: technodata.sel(asset=retro_capacity[agent_uuid].asset)
+            for agent_uuid in retro_capacity.keys()
+        }
         name_to_id = {
             (agent.name, agent.region): agent.uuid
             for agent in agents
             if agent.category == "retrofit" and agent.region == region
         }
-
         id_to_rquantity = {
             agent.uuid: (agent.name, agent.region, agent.quantity)
             for agent in agents
@@ -305,6 +309,7 @@ def decommissioning(capacity):
 
         retro_demands: MutableMapping[Hashable, xr.DataArray] = _inner_split(
             retro_capacity,
+            retro_technodata,
             demands.retrofit.sel(region=region),
             decommissioning,
             id_to_rquantity,
@@ -319,18 +324,21 @@ def decommissioning(capacity):
             for agent in agents
             if agent.category != "retrofit" and agent.region == region
         }
-
+        new_technodata: MutableMapping[Hashable, xr.Dataset] = {
+            agent_uuid: technodata.sel(asset=new_capacity[agent_uuid].asset)
+            for agent_uuid in new_capacity.keys()
+        }
         id_to_nquantity = {
             agent.uuid: (agent.name, agent.region, agent.quantity)
             for agent in agents
             if agent.category != "retrofit" and agent.region == region
         }
         new_demands = _inner_split(
             new_capacity,
+            new_technodata,
             demands.new.sel(region=region),
             partial(
                 maximum_production,
-                technologies=regional_techs,
                 year=current_year,
                 timeslice_level=timeslice_level,
             ),
@@ -372,11 +380,11 @@ def standard_demand(
 
     from muse.commodities import is_enduse
     from muse.quantities import maximum_production
-    from muse.utilities import agent_concatenation, reduce_assets
+    from muse.utilities import agent_concatenation, broadcast_over_assets, reduce_assets
 
     current_year, investment_year = map(int, market.year.values)
 
-    def decommissioning(capacity):
+    def decommissioning(capacity, technologies):
         return decommissioning_demand(
             technologies=technologies,
             capacity=capacity.interp(
@@ -395,11 +403,14 @@ def decommissioning(capacity):
         year=[current_year, investment_year], kwargs={"fill_value": 0.0}
     )
 
+    # Select technodata for assets
+    technodata = broadcast_over_assets(technologies, capacity, installed_as_year=True)
+
     # Calculate new and retrofit demands
     demands = new_and_retro_demands(
         capacity=capacity,
         market=market,
-        technologies=technologies,
+        technologies=technodata,
         timeslice_level=timeslice_level,
     )
 
@@ -416,6 +427,10 @@ def decommissioning(capacity):
             for agent in agents
             if agent.region == region
         }
+        current_technodata: MutableMapping[Hashable, xr.Dataset] = {
+            agent_uuid: technodata.sel(asset=current_capacity[agent_uuid].asset)
+            for agent_uuid in current_capacity.keys()
+        }
 
         # Split demands between agents
         id_to_quantity = {
@@ -425,16 +440,17 @@ def decommissioning(capacity):
         }
         retro_demands: MutableMapping[Hashable, xr.DataArray] = _inner_split(
             current_capacity,
+            current_technodata,
             demands.retrofit.sel(region=region),
             decommissioning,
             id_to_quantity,
         )
         new_demands = _inner_split(
             current_capacity,
+            current_technodata,
             demands.new.sel(region=region),
             partial(
                 maximum_production,
-                technologies=technologies.sel(region=region),
                 year=current_year,
                 timeslice_level=timeslice_level,
             ),
@@ -461,7 +477,7 @@ def unmet_forecasted_demand(
 ) -> xr.DataArray:
     """Forecast demand that cannot be serviced by non-decommissioned current assets."""
     from muse.commodities import is_enduse
-    from muse.utilities import reduce_assets
+    from muse.utilities import broadcast_over_assets, reduce_assets
 
     current_year, investment_year = map(int, market.year.values)
 
@@ -477,11 +493,14 @@ def unmet_forecasted_demand(
     future_market = smarket.sel(year=investment_year, drop=True)
     future_capacity = capacity.sel(year=investment_year)
 
+    # Select technology data for assets
+    techs = broadcast_over_assets(technologies, capacity, installed_as_year=True)
+
     # Calculate unmet demand
     result = unmet_demand(
         market=future_market,
         capacity=future_capacity,
-        technologies=technologies,
+        technologies=techs,
         timeslice_level=timeslice_level,
     )
     assert "year" not in result.dims
@@ -490,6 +509,7 @@ def unmet_forecasted_demand(
 
 def _inner_split(
     assets: Mapping[Hashable, xr.DataArray],
+    technologies: Mapping[Hashable, xr.DataSet],
     demand: xr.DataArray,
     method: Callable,
     quantity: Mapping,
@@ -503,7 +523,7 @@ def _inner_split(
 
     # Find decrease in capacity production by each asset over time
     shares: Mapping[Hashable, xr.DataArray] = {
-        key: method(capacity=capacity)
+        key: method(capacity=capacity, technologies=technologies[key])
         .groupby("technology")
         .sum("asset")
         .rename(technology="asset")

src/muse/examples.py

@@ -264,21 +264,19 @@ def matching_market(sector: str, model: str = "default") -> xr.Dataset:
     from muse.examples import sector as load_sector
     from muse.quantities import consumption, maximum_production
     from muse.sectors import Sector
-    from muse.utilities import agent_concatenation
+    from muse.utilities import agent_concatenation, broadcast_over_assets
 
     loaded_sector = cast(Sector, load_sector(sector, model))
     assets = agent_concatenation({u.uuid: u.assets for u in list(loaded_sector.agents)})
 
     market = xr.Dataset()
-    production = cast(
-        xr.DataArray,
-        maximum_production(loaded_sector.technologies, assets.capacity),
-    )
+    techs = broadcast_over_assets(loaded_sector.technologies, assets.capacity)
+    production = maximum_production(techs, assets.capacity)
     market["supply"] = production.sum("asset")
     if "dst_region" in market.dims:
         market = market.rename(dst_region="region")
     if market.region.dims:
-        consump = consumption(loaded_sector.technologies, production)
+        consump = consumption(techs, production)
         market["consumption"] = drop_timeslice(
             consump.groupby("region").sum(
                 {"asset", "dst_region"}.intersection(consump.dims)
@@ -287,7 +285,7 @@ def matching_market(sector: str, model: str = "default") -> xr.Dataset:
         )
     else:
         market["consumption"] = (
-            consumption(loaded_sector.technologies, production).sum(
+            consumption(techs, production).sum(
                 {"asset", "dst_region"}.intersection(market.dims)
             )
             + market.supply

src/muse/investments.py

@@ -225,14 +225,15 @@ def adhoc_match_demand(
 ) -> xr.DataArray:
     from muse.demand_matching import demand_matching
     from muse.quantities import capacity_in_use, maximum_production
+    from muse.utilities import broadcast_over_assets
 
     assert "year" not in technologies.dims
 
     demand = next(c for c in constraints if c.name == "demand").b
 
     max_capacity = next(c for c in constraints if c.name == "max capacity expansion").b
     max_prod = maximum_production(
-        technologies,
+        broadcast_over_assets(technologies, max_capacity),
         max_capacity,
         technology=costs.replacement,
         commodity=demand.commodity,
@@ -254,7 +255,7 @@ def adhoc_match_demand(
 
     capacity = capacity_in_use(
         production,
-        technologies,
+        broadcast_over_assets(technologies, production),
         technology=production.replacement,
         timeslice_level=timeslice_level,
     ).drop_vars("technology")