Refactor domain initialization and data loading

src/f3dasm/_src/design/domain.py

@@ -14,7 +14,7 @@
 from dataclasses import dataclass, field
 from pathlib import Path
 from typing import (Any, Dict, Iterable, Iterator, List, Literal, Optional,
- Sequence, Type)
+ Protocol, Sequence, Type)
 
 # Third-party core
 import numpy as np
@@ -36,6 +36,13 @@
 # =============================================================================
 
 
+class _Data(Protocol):
+ def to_dataframe(self) -> pd.DataFrame:
+ ...
+
+# =============================================================================
+
+
 @dataclass
 class Domain:
  """Main class for defining the domain of the design of experiments.
@@ -238,6 +245,26 @@ def from_dataframe(cls, df_input: pd.DataFrame,
 
  return cls(space=input_space, output_space=output_space)
 
+ @classmethod
+ def from_data(cls: Type[Domain],
+ input_data: _Data, output_data: _Data) -> Domain:
+ """Initializes a Domain from input and output data.
+
+ Parameters
+ ----------
+ input_data : _Data
+ Input data.
+ output_data : _Data
+ Output data.
+
+ Returns
+ -------
+ Domain
+ Domain object
+ """
+ return cls.from_dataframe(
+ input_data.to_dataframe(), output_data.to_dataframe())
+
 # Export
 # =============================================================================
 
@@ -645,9 +672,7 @@ def make_nd_continuous_domain(bounds: np.ndarray | List[List[float]],
  return Domain(space)
 
 
-def _domain_factory(domain: Domain | DictConfig | None,
- input_data: pd.DataFrame,
- output_data: pd.DataFrame) -> Domain:
+def _domain_factory(domain: Domain | DictConfig | str | Path) -> Domain:
  if isinstance(domain, Domain):
  return domain
 
@@ -657,14 +682,14 @@ def _domain_factory(domain: Domain | DictConfig | None,
  elif isinstance(domain, DictConfig):
  return Domain.from_yaml(domain)
 
- elif (input_data.empty and output_data.empty and domain is None):
- return Domain()
+ # elif (input_data.empty and output_data.empty and domain is None):
+ #  return Domain()
 
- elif domain is None:
- return Domain.from_dataframe(
- input_data, output_data)
+ # elif domain is None:
+ #  return Domain.from_dataframe(
+ #  input_data, output_data)
 
  else:
  raise TypeError(
- f"Domain must be of type Domain, DictConfig "
- f"or None, not {type(domain)}")
+ f"Domain must be of type Domain, DictConfig, str or Path, "
+ f"not {type(domain)}")

src/f3dasm/_src/experimentdata/_data.py

@@ -186,7 +186,8 @@ def from_file(cls, filename: Path | str) -> _Data:
  return cls(df, columns=_Columns(_columns))
 
  @classmethod
- def from_numpy(cls: Type[_Data], array: np.ndarray) -> _Data:
+ def from_numpy(cls: Type[_Data],
+ array: np.ndarray, keys: Iterable[str]) -> _Data:
  """Loads the data from a numpy array.
 
  Parameters
@@ -458,7 +459,8 @@ def _convert_dict_to_data(dictionary: Dict[str, Any]) -> _Data:
  return _Data(data=df, columns=_Columns(_columns))
 
 
-def _data_factory(data: DataTypes) -> _Data:
+def _data_factory(data: DataTypes,
+ keys: Optional[Iterable[str]] = None) -> _Data:
  if data is None:
  return _Data()
 
@@ -469,10 +471,10 @@ def _data_factory(data: DataTypes) -> _Data:
  return _Data.from_dataframe(data)
 
  elif isinstance(data, (Path, str)):
- return _Data.from_file(data)
+ return _Data.from_file(Path(data))
 
  elif isinstance(data, np.ndarray):
- return _Data.from_numpy(data)
+ return _Data.from_numpy(data, keys=keys)
 
  else:
  raise TypeError(