Simplify the agents module, and additional changes #507
There are no files selected for viewing
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
|
|
@@ -80,14 +80,9 @@ def next( | |
| technologies: xr.Dataset, | ||
| market: xr.Dataset, | ||
| demand: xr.DataArray, | ||
| time_period: int, | ||
| ) -> None: | ||
| """Increments agent to the next time point (e.g. performing investments).""" | ||
|
|
||
| def __repr__(self): | ||
| return ( | ||
|
|
@@ -98,10 +93,7 @@ def __repr__(self): | |
|
|
||
|
|
||
| class Agent(AbstractAgent): | ||
| """Standard agent that does not perform investments.""" | ||
|
|
||
| def __init__( | ||
| self, | ||
|
|
@@ -124,7 +116,7 @@ def __init__( | |
| spend_limit: int = 0, | ||
| **kwargs, | ||
| ): | ||
| """Creates a standard agent. | ||
|
|
||
| Arguments: | ||
| name: Name of the agent, used for cross-refencing external tables | ||
|
|
@@ -166,10 +158,7 @@ def __init__( | |
| ) | ||
|
|
||
| self.year = year | ||
| """ Current year. Incremented by one every time next is called.""" | ||
| self.forecast = forecast | ||
| """Number of years to look into the future for forecating purposed.""" | ||
| if search_rules is None: | ||
|
|
@@ -250,8 +239,46 @@ def next( | |
| technologies: xr.Dataset, | ||
| market: xr.Dataset, | ||
| demand: xr.DataArray, | ||
| time_period: int, | ||
| ) -> None: | ||
| self.year += time_period | ||
|
|
||
|
|
||
| class InvestingAgent(Agent): | ||
| """Agent that performs investment for itself.""" | ||
|
|
||
| def __init__( | ||
| self, | ||
| *args, | ||
| constraints: Optional[Callable] = None, | ||
| investment: Optional[Callable] = None, | ||
| **kwargs, | ||
| ): | ||
| """Creates an investing agent. | ||
|
|
||
| Arguments: | ||
| *args: See :py:class:`~muse.agents.agent.Agent` | ||
| constraints: Set of constraints limiting investment | ||
| investment: A function to perform investments | ||
| **kwargs: See :py:class:`~muse.agents.agent.Agent` | ||
| """ | ||
| from muse.constraints import factory as csfactory | ||
| from muse.investments import factory as ifactory | ||
|
|
||
| super().__init__(*args, **kwargs) | ||
|
|
||
| self.invest = investment or ifactory() | ||
| """Method to use when fulfilling demand from rated set of techs.""" | ||
| self.constraints = constraints or csfactory() | ||
| """Creates a set of constraints limiting investment.""" | ||
|
|
||
| def next( | ||
| self, | ||
| technologies: xr.Dataset, | ||
| market: xr.Dataset, | ||
| demand: xr.DataArray, | ||
| time_period: int, | ||
| ) -> None: | ||
| """Iterates agent one turn. | ||
|
|
||
| The goal is to figure out from market variables which technologies to | ||
|
|
@@ -263,22 +290,75 @@ def next( | |
| """ | ||
| from logging import getLogger | ||
|
|
||
| current_year = self.year | ||
|
|
||
| # Skip forward if demand is zero | ||
| if demand.size == 0 or demand.sum() < 1e-12: | ||
| self.year += time_period | ||
| return None | ||
|
|
||
| # Calculate the search space | ||
| search_space = ( | ||
| self.search_rules(self, demand, technologies, market).fillna(0).astype(int) | ||
| ) | ||
|
|
||
| # Skip forward if the search space is empty | ||
| if any(u == 0 for u in search_space.shape): | ||
| getLogger(__name__).critical("Search space is empty") | ||
|
Collaborator
There was a problem hiding this comment. Should the simulation continue after this sort of
Collaborator
Author
There was a problem hiding this comment. In theory it can continue, the agent just won't perform any investments for that year. If this happens, then it probably means there's a mistake with the way the model is defined, so this is something the user should definitely pay attention to. In any case, I'm a bit concerned that a lot a important messages are getting ignored, so have suggested these get outputted to a file (#498) |
||
| self.year += time_period | ||
| return None | ||
|
|
||
| # Calculate the decision metric | ||
| decision = self.compute_decision(technologies, market, demand, search_space) | ||
| search = xr.Dataset(dict(search_space=search_space, decision=decision)) | ||
| if "timeslice" in search.dims: | ||
| search["demand"] = drop_timeslice(demand) | ||
| else: | ||
| search["demand"] = demand | ||
|
|
||
| # Filter assets with demand | ||
| not_assets = [u for u in search.demand.dims if u != "asset"] | ||
| condtechs = ( | ||
| search.demand.sum(not_assets) > getattr(self, "tolerance", 1e-8) | ||
| ).values | ||
| search = search.sel(asset=condtechs) | ||
|
|
||
| # Calculate constraints | ||
| constraints = self.constraints( | ||
| search.demand, | ||
| self.assets, | ||
| search.search_space, | ||
| market, | ||
| technologies, | ||
| year=current_year, | ||
| ) | ||
|
|
||
| # Calculate investments | ||
| investments = self.invest( | ||
| search[["search_space", "decision"]], | ||
| technologies, | ||
| constraints, | ||
| year=current_year, | ||
| ) | ||
|
|
||
| # Add investments | ||
| self.add_investments( | ||
| technologies, | ||
| investments, | ||
| current_year=current_year, | ||
| time_period=time_period, | ||
| ) | ||
|
|
||
| # Increment the year | ||
| self.year += time_period | ||
|
|
||
| def compute_decision( | ||
| self, | ||
| technologies: xr.Dataset, | ||
| market: xr.Dataset, | ||
| demand: xr.DataArray, | ||
| search_space: xr.DataArray, | ||
| ) -> xr.DataArray: | ||
| # Filter technologies according to the search space, forecast year and region | ||
| techs = self.filter_input( | ||
| technologies, | ||
|
|
@@ -297,23 +377,12 @@ def next( | |
| # Filter prices according to the region | ||
| prices = self.filter_input(market.prices) | ||
|
|
||
| # Compute the objectives | ||
| objectives = self.objectives( | ||
| technologies=techs, demand=reduced_demand, prices=prices | ||
| ) | ||
|
|
||
| # Compute the decision metric | ||
| decision = self.decision(objectives) | ||
| return decision | ||
|
|
||
|
|
@@ -323,19 +392,20 @@ def add_investments( | |
| investments: xr.DataArray, | ||
| current_year: int, | ||
| time_period: int, | ||
| ) -> None: | ||
| """Add new assets to the agent.""" | ||
| # Calculate retirement profile of new assets | ||
| new_capacity = self.retirement_profile( | ||
| technologies, investments, current_year, time_period | ||
| ) | ||
| if new_capacity is None: | ||
| return | ||
| new_capacity = new_capacity.drop_vars( | ||
| set(new_capacity.coords) - set(self.assets.coords) | ||
| ) | ||
| new_assets = xr.Dataset(dict(capacity=new_capacity)) | ||
|
|
||
| # Merge new assets with existing assets | ||
| self.assets = self.merge_transform(self.assets, new_assets) | ||
|
|
||
| def retirement_profile( | ||
|
|
@@ -347,10 +417,13 @@ def retirement_profile( | |
| ) -> Optional[xr.DataArray]: | ||
| from muse.investments import cliff_retirement_profile | ||
|
|
||
| # Sum investments | ||
| if "asset" in investments.dims: | ||
| investments = investments.sum("asset") | ||
| if "agent" in investments.dims: | ||
| investments = investments.squeeze("agent", drop=True) | ||
|
|
||
| # Filter out investments below the threshold | ||
| investments = investments.sel( | ||
| replacement=(investments > self.asset_threshold).any( | ||
| [d for d in investments.dims if d != "replacement"] | ||
|
|
@@ -359,22 +432,22 @@ def retirement_profile( | |
| if investments.size == 0: | ||
| return None | ||
|
|
||
| # Calculate the retirement profile for new investments | ||
| # Note: technical life must be at least the length of the time period | ||
| lifetime = self.filter_input( | ||
| technologies.technical_life, | ||
| year=current_year, | ||
| technology=investments.replacement, | ||
| ).clip(min=time_period) | ||
| profile = cliff_retirement_profile( | ||
| lifetime, | ||
| investment_year=current_year + time_period, | ||
| ) | ||
| if "dst_region" in investments.coords: | ||
| investments = investments.reindex_like(profile, method="ffill") | ||
|
|
||
| # Apply the retirement profile to the investments | ||
| new_assets = (investments * profile).rename(replacement="asset") | ||
| new_assets["installed"] = "asset", [current_year] * len(new_assets.asset) | ||
|
|
||
| # The new assets have picked up quite a few coordinates along the way. | ||
|
|
@@ -383,89 +456,3 @@ def retirement_profile( | |
| new, old = new_assets.dims, self.assets.dims | ||
| raise RuntimeError(f"Asset dimensions do not match: {new} vs {old}") | ||
| return new_assets | ||
Oops, something went wrong.
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
I'm pretty sure this is some sort of legacy feature not really used except, as you mention, by
trade. But that's a very obscure sector that I've no idea how it works or what it does.