GWpy Difference API Index

This page is a difference-oriented lookup for what GWexpy adds relative to GWpy.
It is not a full API inventory. For the complete API surface, use the API Reference.

If you want the migration entry point first, go back to the Migration Guide for GWpy Users.

Start with categories

Category	Check this when you want to…	Representative items	Entry point
Multi-channel	process many channels together	to_matrix(), TimeSeriesMatrix, FrequencySeriesMatrix	Matrix Tutorial
Added methods	pull external function calls back onto the data object	.find_peaks(), .fit(), .hht(), .arima()	Added Methods
Field API	work with spacetime-like or 4D data structures	ScalarField, FieldList, FieldDict, fft_space()	Field API
Sharing / compatibility	understand result-sharing behavior	Transparent Pickle	Sharing–Compatibility

Detailed Index

Multi-channel

API Kind	Representative API	Stability	What it adds relative to GWpy	Details
Conversion method	TimeSeriesDict.to_matrix() -> TimeSeriesMatrix	Stable	converts channel collections into a batch-analysis container for spectral or statistical workflows	Matrix Tutorial, TimeSeriesDict, TimeSeriesMatrix
Conversion method	FrequencySeriesDict.to_matrix() -> FrequencySeriesMatrix	Stable	turns collections of frequency-series objects into a container suited for pairwise and batch analysis	FrequencySeriesDict, FrequencySeriesMatrix
Conversion method	SpectrogramDict.to_matrix() / SpectrogramList.to_matrix() -> SpectrogramMatrix	Stable	lets time-frequency collections move into a matrix-style container for downstream processing	SpectrogramDict, SpectrogramList, SpectrogramMatrix

Family-specific to_matrix() contract (current stable behavior)

to_matrix() is intentionally family-specific today. Use this table as the public contract for what conversion checks and metadata guarantees are applied.

Family	Collection entry points	Axis policy	Resampling / tolerance	Unit policy	Label / round-trip notes
TimeSeries	TimeSeriesDict.to_matrix() and TimeSeriesList.to_matrix()	Aligns onto a common time grid through align_timeseries_collection(); exact axis equality is not required when alignment succeeds.	align="intersection" default; forwards alignment kwargs (including method and tolerance) to the alignment helper.	Source TimeSeries.unit is not carried into per-cell matrix metadata by this conversion path; reconstructed elements are dimensionless unless metadata is set separately.	Dict keys are written into element names; generated row keys (row0, row1, …) are used for round-trip dict keys.
FrequencySeries	FrequencySeriesDict.to_matrix()	Checks sample length equality only; frequency coordinate values are taken from the first element.	No resampling and no tolerance parameter.	Per-element unit / name / channel are preserved in matrix metadata and restored by round trip.	Dict keys are preserved as row keys; single output column is value.
Spectrogram	SpectrogramDict.to_matrix() and SpectrogramList.to_matrix()	Requires equal shape plus equal time/frequency axes after conversion to the first axis unit.	No resampling and no tolerance parameter; comparisons are exact after unit conversion.	Per-element unit / name / channel are preserved; global matrix unit is set only when all elements share the same unit.	Dict keys are preserved as row keys; list rows are generated (batch0, batch1, …).
Fields	No SeriesMatrix to_matrix() collection API	Uses FieldList / FieldDict validation rules instead of SeriesMatrix conversion.	Field validation has its own axis tolerance checks.	Units stay on field objects; to_array() returns raw arrays.	Not a SeriesMatrix round-trip path.

Added Methods

API Kind	Representative API	Stability	What it adds relative to GWpy	Details
Instance method	.find_peaks()	Stable	lets you run peak detection directly on the data object instead of dropping to arrays first	Frequency Series Tutorial, TimeSeries, FrequencySeries
Instance method	.fit()	Stable	starts fitting workflows directly from the data object	Fitting, Fitting Reference
Instance method	.hht()	Experimental	exposes Hilbert-Huang Transform analysis as an object method	HHT, TimeSeries
Instance method	.arima()	Experimental	exposes time-series modelling and forecasting as an object method	ARIMA, TimeSeries

Field API

API Kind	Representative API	Stability	What it adds relative to GWpy	Details
Class	ScalarField	Experimental	introduces a metadata-aware 4D field container with time and spatial axes	Field API Intro, ScalarField
Instance method	ScalarField.fft_space()	Experimental	performs spatial-domain transforms while staying inside the Field-object model	Field API Intro, ScalarField
Collection	FieldList / FieldDict	Experimental	groups multiple ScalarField objects for batch-style processing and shared validation	Field API Intro, FieldList, FieldDict

Sharing / Compatibility

API Kind	Representative API / behavior	Stability	What it adds relative to GWpy	Details
Behavior	Transparent Pickle	Stable	allows a GWexpy-produced object to be restored as a GWpy base object on the receiving side even without GWexpy	Migration Guide for GWpy Users, Installation Guide

What this page does not duplicate

• For direct I/O formats, use the File I/O Supported Formats Guide.

• For external-library conversion lists, use the Interop / Conversion Guide.

• For the full API surface, use the API Reference.