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rework FittingData #26

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166 changes: 101 additions & 65 deletions casm/project/fit/_FittingData.py
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Original file line number Diff line number Diff line change
Expand Up @@ -55,8 +55,8 @@ def __init__(self, proj: "Project", id: str):
"""dict: A description of the fit, read from `meta.json`."""

self.names = None
"""Optional[list[str]]: Names of the configurations, a length `n_configs` list,
if given."""
"""Optional[np.ndarray]: Names of the configurations, a shape=(n_configs,)
array of strings, if given."""

self.parametric_compositions = None
"""Optional[np.ndarray]: Parametric compositions of all the configurations, a
Expand All @@ -77,8 +77,27 @@ def __init__(self, proj: "Project", id: str):
# load data
self.load()

def from_dict(self, data):
"""Set fitting data attributes from a dictionary.

Parameters
----------
data : dict
A dictionary containing `names`, `parametric_compositions`,
`mol_compositions`, `correlations_per_unitcell`, and optionally
`formation_energies`.
"""
self.names = np.array(data["names"])
self.parametric_compositions = np.array(data["parametric_compositions"])
self.mol_compositions = np.array(data["mol_compositions"])
self.correlations_per_unitcell = np.array(data["correlations_per_unitcell"])
if data.get("formation_energies") is not None:
self.formation_energies = np.array(data["formation_energies"])
else:
self.formation_energies = None

def load(self):
"""Read meta.json
"""Read meta.json and fitting_data.json

This will replace the current contents of this FittingData object with
the contents of the associated files, or set the current contents to None if the
Expand All @@ -89,8 +108,14 @@ def load(self):
path = self.fit_dir / "meta.json"
self.meta = read_optional(path, default=dict())

# read fitting_data.json if it exists
path = self.fit_dir / "fitting_data.json"
data = read_optional(path, default=None)
if data is not None:
self.from_dict(data)

def commit(self, verbose: bool = True):
"""Write meta.json
"""Write meta.json and fitting_data.json

If the data does not exist in this object, this will erase the associated
files if they do exist.
Expand All @@ -114,6 +139,14 @@ def commit(self, verbose: bool = True):
elif path.exists():
path.unlink()

# write fitting_data.json
path = self.fit_dir / "fitting_data.json"
if self.names is not None:
data = self.to_dict()
safe_dump(data=data, path=path, quiet=quiet, force=True)
elif path.exists():
path.unlink()

def clear(self):
"""Clear fitting data"""
# TODO
Expand All @@ -132,39 +165,6 @@ def __repr__(self):

return s.strip()

@staticmethod
def from_dict(data):
"""Construct FittingData from a dictionary

Parameters
----------
data : dict
A dictionary containing `names`, `parametric_compositions`
`mol_compositions`, `correlations_per_unitcell` and `formation_energies`
of the configurations
Note that `formation_energies` can be None

Returns
-------
fitting_data : FittingData
:class:`FittingData` with `names`, `parametric_compositions`,
`mol_compositions`, `correlations_per_unitcell` and `formation_energies`
filled in for all the configurations


"""
fitting_data = FittingData()

fitting_data.names = data["names"]
fitting_data.parametric_compositions = np.array(data["parametric_compositions"])
fitting_data.mol_compositions = np.array(data["mol_compositions"])
fitting_data.correlations_per_unitcell = np.array(
data["correlations_per_unitcell"]
)
fitting_data.formation_energies = np.array(data["formation_energies"])

return fitting_data

def to_dict(self):
"""Turn `FittingData` into a dictionary with `names`,
`parametric_compositions`, `mol_compositions`, `correlations_per_unitcell`
Expand All @@ -175,13 +175,19 @@ def to_dict(self):
data : dict

"""

return dict(
names=self.names,
names=(
self.names if isinstance(self.names, list)
else self.names.tolist()
),
parametric_compositions=self.parametric_compositions.tolist(),
mol_compositions=self.mol_compositions.tolist(),
correlations_per_unitcell=self.correlations_per_unitcell.tolist(),
formation_energies=self.formation_energies.tolist(),
formation_energies=(
self.formation_energies.tolist()
if self.formation_energies is not None
else None
),
)


Expand Down Expand Up @@ -271,6 +277,9 @@ def make_calculated_fitting_data(
composition_converter: comp.CompositionConverter,
clexulator: clex.Clexulator,
prim_neighbor_list: clex.PrimNeighborList,
proj: "Project",
id: str,
names: list[str] = None,
) -> FittingData:
"""For a given `config_props` list, constructs FittingData which
which holds compositions, correlations per unitcell, formation energies
Expand All @@ -295,14 +304,22 @@ def make_calculated_fitting_data(
A :class:`~libcasm.clexulator.PrimNeighborList` which will be
used to construct the :class:`~libcasm.clexulator.SuperNeighborList`
for every configuration and will be used while obtaining correlations
proj: casm.project.Project
The CASM project
id: str
The fit identifier. Fitting data is stored in the
fits directory at `<project>/fits/fit.<id>/`.
names: Optional[list[str]]
Names of the configurations. If None (default), names are
auto-generated as ``"config.0"``, ``"config.1"``, etc.

Returns
-------
FittingData

"""

names = []
_names = []
parametric_compositions = []
mol_compositions = []
correlations_per_unitcell = []
Expand All @@ -327,7 +344,7 @@ def make_calculated_fitting_data(
composition_converter=composition_converter,
)

names.append("config." + str(config_id))
_names.append("config." + str(config_id))
correlations_per_unitcell.append(corr_per_unitcell.tolist())
mol_compositions.append(mol_comp.tolist())
parametric_compositions.append(param_comp.tolist())
Expand All @@ -336,12 +353,16 @@ def make_calculated_fitting_data(
# in config props. Should it be like this??
formation_energies.append(config_prop["formation_energy"])

fitting_data = FittingData()
fitting_data.names = names
fitting_data.correlations_per_unitcell = np.array(correlations_per_unitcell)
fitting_data.mol_compositions = np.array(mol_compositions)
fitting_data.parametric_compositions = np.array(parametric_compositions)
fitting_data.formation_energies = np.array(formation_energies)
fitting_data = FittingData(proj, id)
fitting_data.from_dict(
dict(
names=names if names is not None else _names,
parametric_compositions=parametric_compositions,
mol_compositions=mol_compositions,
correlations_per_unitcell=correlations_per_unitcell,
formation_energies=formation_energies,
)
)

return fitting_data

Expand All @@ -352,6 +373,9 @@ def make_uncalculated_fitting_data(
composition_converter: comp.CompositionConverter,
clexulator: clex.Clexulator,
prim_neighbor_list: clex.PrimNeighborList,
proj: "Project",
id: str,
names: list[str] = None,
) -> FittingData:
"""For a given `config_list` list, constructs FittingData which
which holds compositions, correlations per unitcell of all the configurations
Expand All @@ -363,10 +387,10 @@ def make_uncalculated_fitting_data(
----------
xtal_prim : xtal.Prim
Prim of the project
config_props : list[dict]
A list containing results of mapping/import
composition_converter : libcasm.composition.CompositionCalculator
A :class:`~libcasm.composition.CompositionCalculator` object with
config_list : list[dict]
A list containing results of enumeration
composition_converter : libcasm.composition.CompositionConverter
A :class:`~libcasm.composition.CompositionConverter` object with
the warranted composition axes set, which will be used to obtain
mol and parametric compostions
clexulator : libcasm.clexulator.Clexulator
Expand All @@ -376,46 +400,58 @@ def make_uncalculated_fitting_data(
A :class:`~libcasm.clexulator.PrimNeighborList` which will be
used to construct the :class:`~libcasm.clexulator.SuperNeighborList`
for every configuration and will be used while obtaining correlations
proj: casm.project.Project
The CASM project
id: str
The fit identifier. Fitting data is stored in the
fits directory at `<project>/fits/fit.<id>/`.
names: Optional[list[str]]
Names of the configurations. If None (default), names are
auto-generated as ``"config.0"``, ``"config.1"``, etc.

Returns
-------
FittingData

"""
names = []
_names = []
parametric_compositions = []
mol_compositions = []
correlations_per_unitcell = []

supercell_set = casmconfig.SupercellSet(casmconfig.Prim(xtal_prim))
for config_id, config in enumerate(config_list):
config_with_properties = casmconfig.Configuration.from_dict(
configuration = casmconfig.Configuration.from_dict(
config["configuration_with_properties"], supercell_set
)

# Extract correlations
corr_per_unitcell = _extract_correlations_for_configuration(
configuration=config_with_properties.configuration,
configuration=configuration,
clexulator=clexulator,
prim_neighbor_list=prim_neighbor_list,
)

# Extract mol and param compositions
mol_comp, param_comp = _extract_mol_and_param_comp_for_configuration(
configuration=config_with_properties.configuration,
configuration=configuration,
xtal_prim=xtal_prim,
composition_converter=composition_converter,
)

names.append("config." + str(config_id))
correlations_per_unitcell.append(corr_per_unitcell)
mol_compositions.append(mol_comp)
parametric_compositions.append(param_comp)
_names.append("config." + str(config_id))
correlations_per_unitcell.append(corr_per_unitcell.tolist())
mol_compositions.append(mol_comp.tolist())
parametric_compositions.append(param_comp.tolist())

fitting_data = FittingData()
fitting_data.names = names
fitting_data.correlations_per_unitcell = correlations_per_unitcell
fitting_data.mol_compositions = mol_compositions
fitting_data.parametric_compositions = parametric_compositions
fitting_data = FittingData(proj, id)
fitting_data.from_dict(
dict(
names=names if names is not None else _names,
parametric_compositions=parametric_compositions,
mol_compositions=mol_compositions,
correlations_per_unitcell=correlations_per_unitcell,
)
)

return fitting_data