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fix(heatconduction)!: name the volume target volfrac #281

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2 changes: 1 addition & 1 deletion docs/problems/heatconduction2d.md
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Original file line number Diff line number Diff line change
Expand Up @@ -25,7 +25,7 @@ The simulator is a docker container with the dolfin-adjoint software that comput
We convert use intermediary files to convert from and to the simulator that is run from a Docker image.

## Dataset
The dataset has been generated the dolfin-adjoint software. It is hosted on the [Hugging Face Datasets Hub](https://huggingface.co/datasets/IDEALLab/heat_conduction_2d_v0).
The dataset has been generated the dolfin-adjoint software. It is hosted on the [Hugging Face Datasets Hub](https://huggingface.co/datasets/IDEALLab/heat_conduction_2d_v1).

### v0

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2 changes: 1 addition & 1 deletion docs/problems/heatconduction3d.md
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Original file line number Diff line number Diff line change
Expand Up @@ -31,7 +31,7 @@ The simulator is a docker container with the dolfin-adjoint software that comput
We convert use intermediary files to convert from and to the simulator that is run from a Docker image.

## Dataset
The dataset has been generated the dolfin-adjoint software. It is hosted on the [Hugging Face Datasets Hub](https://huggingface.co/datasets/IDEALLab/heat_conduction_3d_v0).
The dataset has been generated the dolfin-adjoint software. It is hosted on the [Hugging Face Datasets Hub](https://huggingface.co/datasets/IDEALLab/heat_conduction_3d_v1).

### v0

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40 changes: 20 additions & 20 deletions engibench/problems/heatconduction2d/v0.py
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Original file line number Diff line number Diff line change
Expand Up @@ -29,12 +29,12 @@


@constraint(categories=THEORY, criticality=Criticality.Warning)
def volume_fraction_bound(design: npt.NDArray, volume: float) -> None:
def volume_fraction_bound(design: npt.NDArray, volfrac: float) -> None:
"""Constraint for volume fraction of the design."""
actual_volfrac = design.mean()
tolerance = 0.01
assert abs(actual_volfrac - volume) <= tolerance, (
f"Volume fraction of the design {actual_volfrac:.4f} does not match target {volume:.4f} specified in the conditions. While the optimizer might fix it, this is likely to affect objective values as the initial design is not feasible given the constraints."
assert abs(actual_volfrac - volfrac) <= tolerance, (
f"Volume fraction of the design {actual_volfrac:.4f} does not match target {volfrac:.4f} specified in the conditions. While the optimizer might fix it, this is likely to affect objective values as the initial design is not feasible given the constraints."
)


Expand All @@ -56,7 +56,7 @@ class HeatConduction2D(Problem[npt.NDArray]):
class Conditions:
"""Conditions."""

volume: Annotated[
volfrac: Annotated[
float,
bounded(lower=0.0, upper=1.0).category(THEORY),
bounded(lower=0.3, upper=0.6).warning().category(IMPL),
Expand All @@ -80,7 +80,7 @@ class Config(Conditions):

design_constraints = (volume_fraction_bound,)
design_space = spaces.Box(low=0.0, high=1.0, shape=(101, 101), dtype=np.float64)
dataset_id = "IDEALLab/heat_conduction_2d_v0"
dataset_id = "IDEALLab/heat_conduction_2d_v1"
container_id = "quay.io/dolfinadjoint/pyadjoint:master"

def __init__(self, seed: int = 0, **kwargs: Any) -> None:
Expand All @@ -93,31 +93,31 @@ def __init__(self, seed: int = 0, **kwargs: Any) -> None:
super().__init__(seed=seed)
self.config = self.Config(**kwargs)
resolution = self.config.resolution
self.conditions = self.Conditions(self.config.volume, self.config.length)
self.conditions = self.Conditions(self.config.volfrac, self.config.length)
self.design_space = spaces.Box(low=0.0, high=1.0, shape=(resolution, resolution), dtype=np.float64)

def simulate_verbose(self, design: npt.NDArray | None = None, config: dict[str, Any] | None = None) -> SimulationResult:
"""Simulate the design.

Args:
design (Optional[np.ndarray]): The design to simulate.
config (dict): A dictionary with configuration (e.g., volume (float): Volume constraint,length (float): Length constraint,resolution (int): Resolution of the design space) for the simulation.
config (dict): A dictionary with configuration (e.g., volfrac (float): Target volume fraction,length (float): Length constraint,resolution (int): Resolution of the design space) for the simulation.

Returns:
A `SimulationResult` instance containing the thermal compliance of the design.
"""
config = config or {}
volume = config.get("volume", self.config.volume)
volfrac = config.get("volfrac", self.config.volfrac)
length = config.get("length", self.config.length)
resolution = config.get("resolution", self.config.resolution)
if design is None:
design = self.initialize_design(volume, resolution)
design = self.initialize_design(volfrac, resolution)

perf = load_float(
run_container_script(
self.container_id,
Path(__file__).parent / "templates" / "simulate_heat_conduction_2d.py",
args=(resolution - 1, volume, length),
args=(resolution - 1, volfrac, length),
stdin=np_array_to_bytes(design),
output_path="RES_SIM/Performance.txt",
)
Expand All @@ -132,26 +132,26 @@ def optimize(

Args:
starting_point (npt.NDArray | None): The initial design for optimization.
config (dict): A dictionary with configuration (e.g., volume (float): Volume constraint,length (float): Length constraint,resolution (int): Resolution of the design space) for the simulation.
config (dict): A dictionary with configuration (e.g., volfrac (float): Target volume fraction,length (float): Length constraint,resolution (int): Resolution of the design space) for the simulation.

Returns:
Tuple[OptimalDesign, list[OptiStep]]: The optimized design and the optimization history.
"""
config = config or {}
volume = config.get("volume", self.config.volume)
volfrac = config.get("volfrac", self.config.volfrac)
length = config.get("length", self.config.length)
max_iter = config.get("max_iter", self.config.max_iter)
resolution = config.get("resolution", self.config.resolution)
if starting_point is None:
starting_point = self.initialize_design(volume, resolution)
starting_point = self.initialize_design(volfrac, resolution)

output = np.load(
run_container_script(
self.container_id,
Path(__file__).parent / "templates" / "optimize_heat_conduction_2d.py",
args=(resolution - 1, volume, length, max_iter),
args=(resolution - 1, volfrac, length, max_iter),
stdin=np_array_to_bytes(starting_point),
output_path=f"RES_OPT/OUTPUT={volume}_w={length}.npz",
output_path=f"RES_OPT/OUTPUT={volfrac}_w={length}.npz",
)
)

Expand All @@ -164,26 +164,26 @@ def reset(self, seed: int | None = None, **kwargs) -> None:
"""Reset the problem to a given seed."""
super().reset(seed, **kwargs)

def initialize_design(self, volume: float | None = None, resolution: int | None = None) -> npt.NDArray:
def initialize_design(self, volfrac: float | None = None, resolution: int | None = None) -> npt.NDArray:
"""Initialize the design based on SIMP method.

Args:
volume (Optional[float]): Volume constraint.
volfrac (Optional[float]): Target volume fraction.
resolution (Optional[int]): Resolution of the design space.

Returns:
HeatConduction2D: The initialized design.
"""
volume = volume if volume is not None else self.config.volume
volfrac = volfrac if volfrac is not None else self.config.volfrac
resolution = resolution if resolution is not None else self.config.resolution

# Run the Docker command
return np.load(
run_container_script(
self.container_id,
Path(__file__).parent / "templates" / "initialize_design_2d.py",
args=(resolution - 1, volume),
output_path=f"initialize_design/initial_v={volume}_resol={resolution}.npy",
args=(resolution - 1, volfrac),
output_path=f"initialize_design/initial_v={volfrac}_resol={resolution}.npy",
)
)

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40 changes: 20 additions & 20 deletions engibench/problems/heatconduction3d/v0.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -29,12 +29,12 @@


@constraint(categories=THEORY, criticality=Criticality.Warning)
def volume_fraction_bound(design: npt.NDArray, volume: float) -> None:
def volume_fraction_bound(design: npt.NDArray, volfrac: float) -> None:
"""Constraint for volume fraction of the design."""
actual_volfrac = design.mean()
tolerance = 0.01
assert abs(actual_volfrac - volume) <= tolerance, (
f"Volume fraction of the design {actual_volfrac:.4f} does not match target {volume:.4f} specified in the conditions. While the optimizer might fix it, this is likely to affect objective values as the initial design is not feasible given the constraints."
assert abs(actual_volfrac - volfrac) <= tolerance, (
f"Volume fraction of the design {actual_volfrac:.4f} does not match target {volfrac:.4f} specified in the conditions. While the optimizer might fix it, this is likely to affect objective values as the initial design is not feasible given the constraints."
)


Expand All @@ -52,7 +52,7 @@ class HeatConduction3D(Problem[npt.NDArray]):
class Conditions:
"""Structured representation of the conditions."""

volume: Annotated[
volfrac: Annotated[
float,
bounded(lower=0.0, upper=1.0).category(THEORY),
bounded(lower=0.3, upper=0.6).warning().category(IMPL),
Expand All @@ -76,7 +76,7 @@ class Config(Conditions):

design_constraints = (volume_fraction_bound,)
design_space = spaces.Box(low=0.0, high=1.0, shape=(51, 51, 51), dtype=np.float64)
dataset_id = "IDEALLab/heat_conduction_3d_v0"
dataset_id = "IDEALLab/heat_conduction_3d_v1"
container_id = "quay.io/dolfinadjoint/pyadjoint:master"

def __init__(self, seed: int = 0, **kwargs) -> None:
Expand All @@ -89,31 +89,31 @@ def __init__(self, seed: int = 0, **kwargs) -> None:
super().__init__(seed=seed)
self.config = self.Config(**kwargs)
resolution = self.config.resolution
self.conditions = self.Conditions(self.config.volume, self.config.area)
self.conditions = self.Conditions(self.config.volfrac, self.config.area)
self.design_space = spaces.Box(low=0.0, high=1.0, shape=(resolution, resolution, resolution), dtype=np.float64)

def simulate_verbose(self, design: npt.NDArray | None = None, config: dict[str, Any] | None = None) -> SimulationResult:
r"""Launch a simulation on the given design and return the performance.

Args:
design (Optional[np.ndarray]): The design to simulate.
config (dict): A dictionary with configuration (e.g., volume (float): Volume constraint,area (float): Area constraint,resolution (int): Resolution of the design space) for the simulation.
config (dict): A dictionary with configuration (e.g., volfrac (float): Target volume fraction,area (float): Area constraint,resolution (int): Resolution of the design space) for the simulation.

Returns:
A `SimulationResult` instance containing the thermal compliance of the design.
"""
config = config or {}
volume = config.get("volume", self.config.volume)
volfrac = config.get("volfrac", self.config.volfrac)
area = config.get("area", self.config.area)
resolution = config.get("resolution", self.config.resolution)
if design is None:
design = self.initialize_design(volume, resolution)
design = self.initialize_design(volfrac, resolution)

perf = load_float(
run_container_script(
self.container_id,
Path(__file__).parent / "templates" / "simulate_heat_conduction_3d.py",
args=(resolution - 1, volume, area),
args=(resolution - 1, volfrac, area),
stdin=cli.np_array_to_bytes(design),
output_path="RES_SIM/Performance.txt",
)
Expand All @@ -128,26 +128,26 @@ def optimize(

Args:
starting_point (npt.NDArray | None): The initial design for optimization.
config (dict): A dictionary with configuration (e.g., volume (float): Volume constraint,Area (float): Area constraint,resolution (int): Resolution of the design space) for the simulation.
config (dict): A dictionary with configuration (e.g., volfrac (float): Target volume fraction,Area (float): Area constraint,resolution (int): Resolution of the design space) for the simulation.

Returns:
Tuple[OptimalDesign, list[OptiStep]]: The optimized design and the optimization history.
"""
config = config or {}
volume = config.get("volume", self.config.volume)
volfrac = config.get("volfrac", self.config.volfrac)
area = config.get("area", self.config.area)
resolution = config.get("resolution", self.config.resolution)
max_iter = config.get("max_iter", self.config.max_iter)
if starting_point is None:
starting_point = self.initialize_design(volume, resolution)
starting_point = self.initialize_design(volfrac, resolution)

output = np.load(
run_container_script(
self.container_id,
Path(__file__).parent / "templates" / "optimize_heat_conduction_3d.py",
args=(resolution - 1, volume, area, max_iter),
args=(resolution - 1, volfrac, area, max_iter),
stdin=cli.np_array_to_bytes(starting_point),
output_path=f"RES_OPT/OUTPUT={volume}_w={area}.npz",
output_path=f"RES_OPT/OUTPUT={volfrac}_w={area}.npz",
)
)

Expand All @@ -160,25 +160,25 @@ def reset(self, seed: int | None = None, **kwargs) -> None:
"""Reset the problem to a given seed."""
super().reset(seed, **kwargs)

def initialize_design(self, volume: float | None = None, resolution: int | None = None) -> npt.NDArray:
def initialize_design(self, volfrac: float | None = None, resolution: int | None = None) -> npt.NDArray:
"""Initialize the design based on SIMP method.

Args:
volume (Optional[float]): Volume constraint.
volfrac (Optional[float]): Target volume fraction.
resolution (Optional[int]): Resolution of the design space.

Returns:
HeatConduction3D: The initialized design.
"""
volume = volume if volume is not None else self.config.volume
volfrac = volfrac if volfrac is not None else self.config.volfrac
resolution = resolution if resolution is not None else self.config.resolution

return np.load(
run_container_script(
self.container_id,
Path(__file__).parent / "templates" / "initialize_design_3d.py",
args=(resolution - 1, volume),
output_path=f"initialize_design/initial_v={volume}_resol={resolution}.npy",
args=(resolution - 1, volfrac),
output_path=f"initialize_design/initial_v={volfrac}_resol={resolution}.npy",
)
)

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