tna.classes.Parameters

class tna.classes.Parameters(**data)

Parameter set controlling preprocessing and analysis of transient nutation data.

This model defines all configurable options for loading, processing, windowing, and Fourier transformation of transient nutation datasets.

Parameters:

• current_time (float)

• current_field (float)

• prodel (bool)

• two_d (bool)

• path (Path | None)

• baseline_correction (bool)

• baseline_correction_deg (int)

• reconstruction (bool)

• mean_subtraction (bool)

• wdw_chebwin (bool)

• chebwin_attenuation (float)

• wdw_hamming (bool)

• hamming_window_coefficient (float)

• wdw_kaiser (bool)

• kaiser_window_shape_parameter (float)

• wdw_sinebell (bool)

• sinebell_phase_shift (float)

• wdw_lorentz_gauss (bool)

• tau (float)

• sigma (float)

• zero_filling (bool)

• zero_filling_factor (int)

• reference_freq (bool)

• reference_freq_value (float)

• save_location (str | None)

current_time

Time point at which the magnetic field spectrum is evaluated.

Type:

float

current_field

Magnetic field point at which the time spectrum is evaluated.

Type:

float

prodel

If True, swaps real and imaginary parts of the signal during loading.

Type:

bool

two_d

If True, treats the dataset as two-dimensional (field-resolved).

Type:

bool

path

Absolute path to experimental data.

Type:

Path or None

baseline_correction

Enables polynomial baseline correction.

Type:

bool

baseline_correction_deg

Degree of the polynomial used for baseline correction.

Type:

int

reconstruction

Enables signal reconstruction.

Type:

bool

mean_subtraction

Enables subtraction of the mean signal.

Type:

bool

wdw_chebwin

Applies a Dolph-Chebyshev window function.

Type:

bool

chebwin_attenuation

Attenuation parameter (dB) for the Chebyshev window.

Type:

float

wdw_hamming

Applies a Hamming window function.

Type:

bool

hamming_window_coefficient

Coefficient defining the Hamming window shape (default ~0.54).

Type:

float

wdw_kaiser

Applies a Kaiser window function.

Type:

bool

kaiser_window_shape_parameter

Shape parameter of the Kaiser window.

Type:

float

wdw_sinebell

Applies a sine-bell window function.

Type:

bool

sinebell_phase_shift

Phase shift applied to the sine-bell window.

Type:

float

wdw_lorentz_gauss

Applies a combined Lorentz-Gauss window function.

Type:

bool

tau

Lorentzian parameter (related to FWHH via 1/(pi*tau)).

Type:

float

sigma

Gaussian width parameter.

Type:

float

zero_filling

Enables zero-filling before Fourier transformation.

Type:

bool

zero_filling_factor

Factor by which the signal length is extended with zeros.

Type:

int

reference_freq

Enables correction to a reference frequency.

Type:

bool

reference_freq_value

Reference frequency used for frequency axis correction.

Type:

float

save_location

Path where processed results are stored.

Type:

str or None

Notes

This class is validates the type of the fields (validate_assignment=”True”) and disallows additional attributes (extra=”forbid”) to ensure reproducibility and prevent silent configuration errors in scientific processing pipelines.

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

data (Any)

Return type:

None

Methods

__init__(**data)	Create a new model by parsing and validating input data from keyword arguments.
construct([_fields_set])
copy(*[, include, exclude, update, deep])	Returns a copy of the model.
dict(*[, include, exclude, by_alias, ...])
from_orm(obj)
json(*[, include, exclude, by_alias, ...])
model_construct([_fields_set])	Creates a new instance of the Model class with validated data.
model_copy(*[, update, deep])	!!! abstract "Usage Documentation"
model_dump(*[, mode, include, exclude, ...])	!!! abstract "Usage Documentation"
model_dump_json(*[, indent, ensure_ascii, ...])	!!! abstract "Usage Documentation"
model_json_schema([by_alias, ref_template, ...])	Generates a JSON schema for a model class.
model_parametrized_name(params)	Compute the class name for parametrizations of generic classes.
model_post_init(context, /)	Override this method to perform additional initialization after __init__ and model_construct.
model_rebuild(*[, force, raise_errors, ...])	Try to rebuild the pydantic-core schema for the model.
model_validate(obj, *[, strict, extra, ...])	Validate a pydantic model instance.
model_validate_json(json_data, *[, strict, ...])	!!! abstract "Usage Documentation"
model_validate_strings(obj, *[, strict, ...])	Validate the given object with string data against the Pydantic model.
parse_file(path, *[, content_type, ...])
parse_obj(obj)
parse_raw(b, *[, content_type, encoding, ...])
schema([by_alias, ref_template])
schema_json(*[, by_alias, ref_template])
update_forward_refs(**localns)
validate(value)

Attributes

model_computed_fields
model_config	Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
model_extra	Get extra fields set during validation.
model_fields
model_fields_set	Returns the set of fields that have been explicitly set on this model instance.
current_time
current_field
prodel
two_d
path
baseline_correction
baseline_correction_deg
reconstruction
mean_subtraction
wdw_chebwin
chebwin_attenuation
wdw_hamming
hamming_window_coefficient
wdw_kaiser
kaiser_window_shape_parameter
wdw_sinebell
sinebell_phase_shift
wdw_lorentz_gauss
tau
sigma
zero_filling
zero_filling_factor
reference_freq
reference_freq_value
save_location