WordFrequencyExtractor#

Defined in: voxatlas.features.lexical.frequency.word_frequency

class voxatlas.features.lexical.frequency.word_frequency.WordFrequencyExtractor[source]#

Bases: BaseExtractor

Extract the lexical.frequency.word feature within the VoxAtlas pipeline.

This public extractor defines the reusable API for computing lexical.frequency.word from VoxAtlas structured inputs. It consumes token units and produces values aligned to token units, making the extractor a stable pipeline node that can be cited independently of the surrounding execution machinery.

Algorithm#

The extractor follows the standard VoxAtlas feature-computation pattern.

  1. Input preparation Structured audio, unit tables, and dependency outputs are gathered from feature_input.

  2. Feature-specific computation The implementation applies the domain-specific transformation required by this extractor.

  3. Packaging Results are aligned to token units and returned as a FeatureOutput object.

Notes

This extractor declares the upstream dependencies [‘lexical.frequency.lookup’] and is executed only after those features are available in the pipeline feature store.

Examples

>>> import pandas as pd
>>> from voxatlas.features.feature_input import FeatureInput
>>> from voxatlas.features.feature_output import TableFeatureOutput
>>> from voxatlas.features.lexical.frequency.word_frequency import WordFrequencyExtractor
>>> from voxatlas.pipeline.feature_store import FeatureStore
>>> table = pd.DataFrame({"id": [1], "frequency": [10.0]})
>>> store = FeatureStore()
>>> store.add("lexical.frequency.lookup", TableFeatureOutput(feature="lexical.frequency.lookup", unit="token", values=table))
>>> out = WordFrequencyExtractor().compute(FeatureInput(audio=None, units=None, context={"feature_store": store}), {})
>>> float(out.values.loc[1])
10.0
name: str = 'lexical.frequency.word'#
input_units: str | None = 'token'#
output_units: str | None = 'token'#
dependencies: list[str] = ['lexical.frequency.lookup']#
default_config: dict = {}#
compute(feature_input, params)[source]#

Compute raw token-level frequency values from the lookup table.

Parameters:

  • feature_input (FeatureInput) – Prepared stream input containing the feature store.

  • params (dict) – Resolved extractor configuration. Present for API consistency.

Returns:

Token-aligned raw frequency values.

Return type:

ScalarFeatureOutput

Raises:

KeyError – Raised when the lexical lookup dependency is unavailable.

Notes

The output index matches the token ids from the lookup dependency.

Examples

>>> import pandas as pd
>>> from voxatlas.features.feature_input import FeatureInput
>>> from voxatlas.features.feature_output import TableFeatureOutput
>>> from voxatlas.features.lexical.frequency.word_frequency import WordFrequencyExtractor
>>> from voxatlas.pipeline.feature_store import FeatureStore
>>> table = pd.DataFrame({"id": [1], "frequency": [10.0]})
>>> store = FeatureStore()
>>> store.add("lexical.frequency.lookup", TableFeatureOutput(feature="lexical.frequency.lookup", unit="token", values=table))
>>> result = WordFrequencyExtractor().compute(FeatureInput(audio=None, units=None, context={"feature_store": store}), {})
>>> result.unit
'token'