Getting Started

This page provides a structured learning path for GWexpy users. Whether you’re new to time series analysis or migrating from GWpy, you’ll find tailored recommendations for your background.

What you’ll learn:

  • Installation and setup

  • Core data structures (TimeSeries, FrequencySeries, Spectrogram)

  • Multi-channel analysis and matrix containers

  • Advanced signal processing techniques

  • Real-world application examples

Time estimate: 2-3 hours for beginners, 30-60 minutes for GWpy users

Tip

If you’re in a hurry, start with Quickstart for a 5-minute overview.

About This Page

This page provides a detailed learning roadmap. If you haven’t visited the documentation homepage yet, start there to understand GWexpy’s overall capabilities.

Quick Example

Here’s the most basic GWexpy workflow:

from gwexpy.timeseries import TimeSeries
import numpy as np

# Create a time series
ts = TimeSeries(np.random.randn(1000), sample_rate=100, t0=0)

# Plot it
plot = ts.plot()
plot.show()

For more examples, continue to Quickstart.

Prerequisites

  • Basic Python 3.9+ knowledge

  • NumPy fundamentals (array operations)

  • (Optional) GWpy experience

Learning Path

1. Installation

First, install GWexpy by following installation.

2. Quickstart

Learn the basics with quickstart.

4. Advanced Topics

Multi-channel & Matrix Containers

High-dimensional Fields (Field API)

Advanced Signal Processing

5. Practical Examples

Browse the Examples Gallery for real-world applications:

Next Steps