Feature helmholtz dataset

.gitignore

@@ -1,3 +1,7 @@
+# Project specific
+playground/
+out/
+
 # Byte-compiled / optimized / DLL files
 __pycache__/
 *.py[cod]

.pre-commit-config.yaml

@@ -16,6 +16,7 @@ repos:
     rev: 3.9.2
     hooks:
       - id: flake8
+        args: [ '--max-line-length=120' ]
   - repo: https://github.com/pycqa/isort
     rev: 5.12.0
     hooks:

README.md

@@ -9,6 +9,24 @@
 
 ## Setup
 
+### Sonic Crystal Data Set
+
+To create the dataset, I recommend using the docker-container provided by the developers
+of [Dolfinx](https://github.com/FEniCS/dolfinx):
+
+```shell
+docker create --name dolfinx dolfinx/dolfinx
+```
+
+With the [run_on_docker.py script](standalone/data/run_on_docker.py) datasets can be created.
+For help:
+
+```shell
+python3 standalone/data/run_on_docker.py --help
+```
+
+### Running PINNs and PINOs
+
 I recommend setting up a python venv.
 
 Install the required packages and libraries

pyproject.toml

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 [tool.black]
-line-length = 79
+line-length = 120
 
 [tool.isort]
 profile = "black"
@@ -8,5 +8,8 @@ include_trailing_comma = true
 force_grid_wrap = 0
 use_parentheses = true
 ensure_newline_before_comments = true
-line_length = 79
+line_length = 120
 skip_glob = [".github/*", ".idea/*", ".pytest_cache/*", "data/*", "docs/*", "models/*", "venv/*"]
+
+[tool.flake8]
+max-line-length = 120

requirements.txt

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+numpy
+matplotlib
+seaborn
+h5py

src/data/helmholtz/__init__.py

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+from .helmholtz import Helmholtz
+
+__all__ = ["Helmholtz"]

src/data/helmholtz/domain_properties/__init__.py

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+from .description import CShapeDescription, CylinderDescription, Description, NoneDescription
+from .file_input import read_config
+
+__all__ = [
+    "read_config",
+    "Description",
+    "CylinderDescription",
+    "CShapeDescription",
+    "NoneDescription",
+]

src/data/helmholtz/domain_properties/description.py

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+import dataclasses
+import json
+import pathlib
+from typing import Dict
+
+import numpy as np
+
+from src.utility import get_unique_id
+
+
+@dataclasses.dataclass
+class CrystalDescription:
+    """Holds information about a crystal."""
+
+    type_name: str
+    grid_size: float
+    n_x: int
+    n_y: int
+
+
+@dataclasses.dataclass
+class Description:
+    """Holds information of a domain on which only the frequency is varied.
+
+    The reason for only varying the frequency in a single sample is that it may be easier to generate multiple samples
+    on the same mesh. The frequency can but does not need to change the mesh of the domain. Compared to changing the
+    parametrization of the crystals, this may save storage space.
+    If the domain should be resampled for every simulation for every frequency, create one Description per frequency.
+
+    """
+
+    # physics
+    frequencies: np.array
+    rho: float
+    c: float
+
+    # domain
+    right_space: float  # in value of wavelengths
+    elements: float
+    # for marking cell_indices
+    domain_index: int
+    right_index: int
+    excitation_index: int
+
+    # absorber
+    depth: float
+    round_trip: float
+    directions: Dict[str, bool]
+    absorber_index: int  # for marking cell_indices
+
+    # crystals
+    crystal_index: int  # for marking cell_indices
+    crystal_description: CrystalDescription
+
+    # derived properties
+    height: float = dataclasses.field(init=False)  # height of the central stack
+    width: float = dataclasses.field(init=False)  # width of the crystal domain
+    absorber_depth: float = dataclasses.field(init=False)  # Description is used to create one mesh -> no array
+    ks: np.array = dataclasses.field(init=False)
+    wave_lengths: np.array = dataclasses.field(init=False)
+    unique_id: str = dataclasses.field(init=False)
+    right_width: float = dataclasses.field(init=False)
+
+    def __post_init__(self):
+        self.update_derived_properties()
+
+    def update_derived_properties(self):
+        self.height = self.crystal_description.n_y * self.crystal_description.grid_size
+        self.width = self.crystal_description.n_x * self.crystal_description.grid_size
+        self.wave_lengths = self.c / self.frequencies
+        self.ks = 2 * np.pi * self.frequencies / self.c
+        self.absorber_depth = max(self.wave_lengths) * self.depth
+        self.right_width = max(self.right_space, 0) * max(self.wave_lengths)
+
+        self.unique_id = get_unique_id()
+
+    def serialize(self) -> dict:
+        """Serializes this object to a dictionary.
+
+        Returns:
+
+        """
+        des_dict = dataclasses.asdict(self)
+
+        for key, value in des_dict.items():
+            if isinstance(value, np.ndarray):
+                des_dict[key] = value.tolist()
+
+        return des_dict
+
+    def save_to_json(self, out_dir: pathlib.Path) -> None:
+        """Saves this object to the provided dir.
+
+        Args:
+            out_dir:
+
+        Returns:
+
+        """
+        out_dir.mkdir(parents=True, exist_ok=True)
+        file_path = out_dir.joinpath(f"{self.unique_id}_description.json")
+        with open(file_path, "w") as file_handle:
+            json.dump(self.serialize(), file_handle)
+
+
+@dataclasses.dataclass
+class CylinderDescription(CrystalDescription):
+    """Holds information about a cylindrical crystal."""
+
+    radius: float
+
+
+@dataclasses.dataclass
+class CShapeDescription(CrystalDescription):
+    """Holds information about a C-shaped crystal."""
+
+    outer_radius: float
+    inner_radius: float
+    gap_width: float
+
+
+@dataclasses.dataclass
+class NoneDescription(CrystalDescription):
+    """A domain without crystals."""