Prerequisites and Conventions

This page is the entry point for the shared prerequisites and conventions used across the GWexpy guides and tutorials. Page-specific assumptions and mathematical details remain on their original pages; this guide is meant to show where to check first.

At a Glance

The table below follows the shared table styling used across the docs. On mobile, horizontal scrolling is preferred instead of page-specific table behavior.

Item

Details

Page Role

Guide

Audience

Users who want the shared assumptions before diving into tutorials or API pages

Prerequisites

Basic Python and NumPy familiarity, with GWpy/GWexpy differences still being learned

Use Cases

Review GPS-time assumptions, FFT conventions, and what is preserved from GWpy

Search Keywords

prerequisites, conventions, GPS time, FFT, GWpy compatibility, Field API

On This Page

  • Environment Prerequisites

  • Data and Time Assumptions

  • FFT and Spectral Conventions

  • GWpy Compatibility and GWexpy Extensions

  • Where to Go Next

1. Environment Prerequisites

  • The basic user-facing environment assumes Python 3.11+.

  • The minimum background is basic Python, NumPy array handling, and optionally Matplotlib.

  • Optional dependencies unlock additional features. See the Installation Guide for setup details.

If you want the shortest overall learning path first, start with Getting Started.

2. Data and Time Assumptions

  • GWexpy is designed to stay compatible with gwpy-style time-series and frequency-series containers.

  • Some APIs assume GPS time explicitly. In particular, forecast timestamps such as ARIMA outputs should not be confused with UTC-style time systems that include leap seconds.

  • Some file formats do not preserve absolute timestamps. Audio formats are a representative case where t0=0.0 may be used only as a convenience convention.

  • Formats that only store local wall-clock time may require an explicit timezone. A common example is GBD in the File I/O Supported Formats Guide.

For algorithm-specific assumptions, see Validated Algorithms.

3. FFT and Spectral Conventions

  • GWexpy treats FFT normalization, one-sided vs two-sided spectra, and sign conventions explicitly.

  • fft_time and fft_space follow different assumptions for target axes and normalization.

  • spectral_density distinguishes PSD-style density from per-bin spectrum values.

For the mathematical details, see FFT Specifications and Conventions.

4. GWpy Compatibility and GWexpy Extensions

  • GWexpy is built on top of GWpy and preserves the basic data model and workflow expectations where possible.

  • At the same time, it adds Matrix containers, the Field API, broader I/O support, and extra analysis utilities that do not exist in GWpy.

  • If you want a quick view of what is still β€œGWpy-like” and what is GWexpy-specific, the migration guide is the fastest entry point.

For migration-oriented guidance, see Migration from GWpy and the GWpy Difference API Index.

5. Where to Go Next

Next to Read