Remove more forecast features

Author: tsmbland

src/muse/agents/agent.py

@@ -113,7 +113,6 @@ def __init__(
         decision: Callable | None = None,
         year: int = 2010,
         maturity_threshold: float = 0,
-        forecast: int = 5,
         housekeeping: Callable | None = None,
         merge_transform: Callable | None = None,
         demand_threshold: float | None = None,
@@ -137,7 +136,6 @@ def __init__(
             year: year the agent is created / current year
             maturity_threshold: threshold when filtering replacement
                 technologies with respect to market share
-            forecast: Number of years the agent will forecast
             housekeeping: transform applied to the assets at the start of
                 iteration. Defaults to doing nothing.
             merge_transform: transform merging current and newly invested assets
@@ -170,9 +168,6 @@ def __init__(
         """ Current year. Incremented by one every time next is called."""
         self.year = year
 
-        """Number of years to look into the future for forecating purposed."""
-        self.forecast = forecast
-
         """Search rule(s) determining potential replacement technologies.
 
         This is a string referring to a filter, or a sequence of strings
@@ -234,11 +229,6 @@ def __init__(
         """Threshold below which assets are not added."""
         self.asset_threshold = asset_threshold
 
-    @property
-    def forecast_year(self):
-        """Year to consider when forecasting."""
-        return self.year + self.forecast
-
     def asset_housekeeping(self):
         """Reduces memory footprint of assets.
 

src/muse/sectors/sector.py

@@ -169,15 +169,6 @@ def __init__(
         """Full supply, consumption and costs data for the most recent year."""
         self.output_data: xr.Dataset
 
-    @property
-    def forecast(self):
-        """Maximum forecast horizon across agents.
-
-        It cannot be lower than 1 year.
-        """
-        forecasts = [getattr(agent, "forecast") for agent in self.agents]
-        return max(1, max(forecasts))
-
     def next(
         self,
         mca_market: xr.Dataset,

src/muse/sectors/subsector.py

@@ -24,7 +24,6 @@ def __init__(
         constraints: Callable | None = None,
         investment: Callable | None = None,
         name: str = "subsector",
-        forecast: int = 5,
         expand_market_prices: bool = False,
         timeslice_level: str | None = None,
     ):
@@ -37,7 +36,6 @@ def __init__(
         self.demand_share = demand_share or ds.factory()
         self.constraints = constraints or cs.factory()
         self.investment = investment or iv.factory()
-        self.forecast = forecast
         self.name = name
         self.expand_market_prices = expand_market_prices
         self.timeslice_level = timeslice_level
@@ -142,7 +140,6 @@ def factory(
             asset_threshold=getattr(settings, "asset_threshold", 1e-12),
             # only used by self-investing agents
             investment=getattr(settings, "lpsolver", "scipy"),
-            forecast=getattr(settings, "forecast", 5),
             constraints=getattr(settings, "constraints", ()),
             timeslice_level=timeslice_level,
         )
@@ -181,7 +178,6 @@ def factory(
         constraints = cs.factory(getattr(settings, "constraints", None))
         # only used by non-self-investing agents
         investment = iv.factory(getattr(settings, "lpsolver", "scipy"))
-        forecast = getattr(settings, "forecast", 5)
 
         expand_market_prices = getattr(settings, "expand_market_prices", None)
         if expand_market_prices is None:
@@ -195,7 +191,6 @@ def factory(
             demand_share=demand_share,
             constraints=constraints,
             investment=investment,
-            forecast=forecast,
             name=name,
             expand_market_prices=expand_market_prices,
             timeslice_level=timeslice_level,