mt_metadata.features.fc_coherence

Classes

`BandDefinitionTypeEnum`	str(object='') -> str
`QRadiusEnum`	str(object='') -> str
`FCCoherence`	Base class for all metadata objects with Pydantic validation.

Module Contents

class mt_metadata.features.fc_coherence.BandDefinitionTypeEnum

Bases: mt_metadata.common.enumerations.StrEnumerationBase

str(object=’’) -> str str(bytes_or_buffer[, encoding[, errors]]) -> str

Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.__str__() (if defined) or repr(object). encoding defaults to ‘utf-8’. errors defaults to ‘strict’.

Q = 'Q'

fractional_bandwidth = 'fractional bandwidth'

user_defined = 'user defined'

class mt_metadata.features.fc_coherence.QRadiusEnum

Bases: mt_metadata.common.enumerations.StrEnumerationBase

str(object=’’) -> str str(bytes_or_buffer[, encoding[, errors]]) -> str

Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.__str__() (if defined) or repr(object). encoding defaults to ‘utf-8’. errors defaults to ‘strict’.

constant_Q = 'constant Q'

user_defined = 'user defined'

class mt_metadata.features.fc_coherence.FCCoherence(**data)

Bases: mt_metadata.features.coherence.Coherence, mt_metadata.features.feature.Feature

Base class for all metadata objects with Pydantic validation.

MetadataBase extends DotNotationBaseModel (which inherits from Pydantic’s BaseModel) to provide automatic validation according to metadata standards. It adds functionality beyond dictionaries, supporting JSON, XML, pandas Series, and other formats for metadata interchange.

_skip_equals

Private attribute listing fields to skip in equality comparisons

Type:: list[str]

_fields

Private attribute caching field information

Type:: dict[str, Any]

Notes

All field assignments are validated automatically via Pydantic
None values are converted to appropriate defaults (empty string or 0.0)
Supports nested attribute access via dot notation
Thread-safe for read operations after initialization

minimum_fcs: Annotated[int, Field(default=2, description='The minimum number of Fourier coefficients needed to compute the feature.', alias=None, json_schema_extra={'units': None, 'required': True, 'examples': ['2']})]

band_definition_type: Annotated[BandDefinitionTypeEnum, Field(default='Q', description='How the feature frequency bands are defined.', alias=None, json_schema_extra={'units': None, 'required': True, 'examples': ['user defined']})]

q_radius: Annotated[QRadiusEnum, Field(default='constant Q', description='How the feature frequency bands are defined.', alias=None, json_schema_extra={'units': None, 'required': True, 'examples': ['user defined']})]

classmethod set_defaults(data)

property channel_pair_str: str

compute(fc1, fc2)

Compute magnitude-squared coherence from FCs.

Parameters:

fc1 (np.ndarray) – Fourier coefficients for channel 1, shape (n_windows, n_freqs)
fc2 (np.ndarray) – Fourier coefficients for channel 2, shape (n_windows, n_freqs)

Returns:

freqs (np.ndarray) – Frequency axis (if available, else None)
coherence (np.ndarray) – Magnitude-squared coherence, shape (n_freqs,)

Return type:

tuple[numpy.ndarray | None, numpy.ndarray]