clophfit.fitting.data_structures#

Core data structures in clophfit.

Classes:#

  • DataArray: Represents matched x, y, and optional w arrays.

  • Dataset: Extends dict to store DataArray as key-value pairs, with optional support for pH-specific datasets.

Classes#

DataArray

Represent matched x, y, and optional w (weight) arrays.

Dataset

A dictionary-like container for storing DataArray.

MiniProtocol

A very small common interface for all minimizers / backends.

FitResult

Result container of a fitting procedure.

SpectraGlobResults

A dataclass representing the results of both svd and bands fits.

Module Contents#

class clophfit.fitting.data_structures.DataArray#

Represent matched x, y, and optional w (weight) arrays.

Parameters:

  • xc (ArrayF) – x at creation.

  • yc (ArrayF) – y at creation.

  • x_errc (ArrayF, optional) – x_err at creation.

  • y_errc (ArrayF, optional) – y_err at creation.

property mask: clophfit.clophfit_types.ArrayMask#

Mask.

Return type:

clophfit.clophfit_types.ArrayMask

property x: clophfit.clophfit_types.ArrayF#

Masked x.

Return type:

clophfit.clophfit_types.ArrayF

property y: clophfit.clophfit_types.ArrayF#

Masked y.

Return type:

clophfit.clophfit_types.ArrayF

property y_err: clophfit.clophfit_types.ArrayF#

Masked y_err.

Return type:

clophfit.clophfit_types.ArrayF

property x_err: clophfit.clophfit_types.ArrayF#

Masked x_err.

Return type:

clophfit.clophfit_types.ArrayF

class clophfit.fitting.data_structures.Dataset(data, *, is_ph=False)#

Bases: collections.UserDict[str, DataArray]

A dictionary-like container for storing DataArray.

Parameters:

  • data (dict[str, DataArray]) – Maps keys to DataArray instances.

  • is_ph (bool)

is_ph: bool = False#

Indicates whether x values represent pH. Default is False.

classmethod from_da(da, *, is_ph=False)#

Alternative constructor to create Dataset from a list of DataArray.

Parameters:

  • da (DataArray | list[DataArray]) – The DataArray objects to populate the dataset.

  • is_ph (bool, optional) – Indicate if x values represent pH (default is False).

Returns:

The constructed Dataset object.

Return type:

Dataset

apply_mask(combined_mask)#

Correctly distribute and apply the combined mask across all DataArrays.

Parameters:

combined_mask (ArrayMask) – Boolean array where True keeps the data point, and False masks it out.

Raises:

ValueError – If the length of the combined_mask does not match the total number of data points.

Return type:

None

copy(keys=None)#

Return a copy of the Dataset.

If keys are provided, only data associated with those keys are copied.

Parameters:

keys (list[str] | set[str] | None, optional) – List of keys to include in the copied dataset. If None (default), copies all data.

Returns:

A copy of the dataset.

Return type:

Dataset

Raises:

KeyError – If a provided key does not exist in the Dataset.

clean_data(n_params)#

Remove too small datasets.

Parameters:

n_params (int)

Return type:

None

concatenate_data()#

Concatenate x, y, x_err, and y_err across all datasets.

Optimized version with pre-allocation for better memory efficiency.

Return type:

tuple[clophfit.clophfit_types.ArrayF, clophfit.clophfit_types.ArrayF, clophfit.clophfit_types.ArrayF, clophfit.clophfit_types.ArrayF]

export(filep)#

Export this dataset into a csv file.

Parameters:

filep (str | pathlib.Path)

Return type:

None

plot(*, title=None, ax=None)#

Plot the dataset with error bars.

Parameters:

  • title (str | None) – Plot title.

  • ax (Axes | None) – Axes to plot on. If None, creates a new figure.

Returns:

The figure containing the plot.

Return type:

Figure

class clophfit.fitting.data_structures.MiniProtocol#

Bases: Protocol

A very small common interface for all minimizers / backends.

class clophfit.fitting.data_structures.FitResult[MiniType: MiniProtocol]#

Result container of a fitting procedure.

figure: matplotlib.figure.Figure | None = None#

Matplotlib figure visualizing the fit, if generated.

result: lmfit.minimizer.MinimizerResult | _Result | None = None#

Backend-agnostic fit result exposing a .params attribute along with residual, redchi, and success fields (as in lmfit). For lmfit this is a MinimizerResult.

mini: MiniType | None = None#

The primary backend object (e.g., lmfit.Minimizer, scipy.odr.Output, or az.InferenceData for PyMC).

dataset: Dataset | None = None#

Dataset used for the fit (typically a deep copy of the input dataset).

pprint()#

Provide a brief summary of the fit, focusing on the K value.

Return type:

str

is_valid()#

Whether figure, result, and minimizer exist.

Return type:

bool

class clophfit.fitting.data_structures.SpectraGlobResults#

A dataclass representing the results of both svd and bands fits.

svd: FitResult[lmfit.minimizer.Minimizer] | None = None#

The FitResult object representing the outcome of the concatenated svd fit, or None if the svd fit was not performed.

gsvd: FitResult[lmfit.minimizer.Minimizer] | None = None#

The FitResult object representing the outcome of the global svd fit, or None if the svd fit was not performed.

bands: FitResult[lmfit.minimizer.Minimizer] | None = None#

The FitResult object representing the outcome of the bands fit, or None if the bands fit was not performed.