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A practical route through the Luna documentation for first-time users

If you are new to Luna, do not start by reading the full command reference from top to bottom. Luna has a lot of functionality, and the reference pages are best used once you already know the basic workflow and are looking up a specific command, parameter, or output.

Luna can be used in several different ways, but they all sit on top of the same core library and commands. The command-line interface is usually the best fit for users who want explicit scripts, batch processing, reproducibility, and direct access to the full Luna command language. lunapi is usually the best fit for users who prefer Python, notebooks, interactive analysis, and tighter integration with plotting or downstream data-science tools. LunaScope is the most approachable entry point for users who want visual review and point-and-click exploration before moving to scripts or notebooks. There is also an R interface (lunaR), but this page focuses on the main current paths: command-line Luna, lunapi, and LunaScope.

Path

Command Line

For users who want explicit scripts, batch processing, sample lists, and direct access to the full Luna command language.

  1. Downloads and installation Install the command-line Luna tools.
  2. Quick start Learn the basic mechanics on a small example.
  3. Take two Continue with projects, outputs, and parameterization.
  4. Deeper dive Add masks, hypnograms, artifacts, and more realistic workflows.
  5. Concepts and syntax Read the core command model once the tutorial gives it context.
  6. Walk-through Follow the more realistic end-to-end analysis path.
  7. Command reference overview Use the domain pages and command docs as needed.

Python

For users who prefer notebooks, interactive analysis, Python scripts, and integration with plotting or downstream data-science tools.

  1. lunapi overview and installation Install the Python interface and see what it provides.
  2. Quick start Learn the shared Luna concepts on the main tutorial data.
  3. Take two Continue with outputs, projects, and parameterization.
  4. Deeper dive Build the core Luna workflow before switching interfaces.
  5. lunapi getting started Move into the Python-specific workflow.
  6. Concepts and syntax Keep the core command model in view.
  7. Walk-through Use the main walk-through for the overall analysis logic.
  8. lunapi reference Look up Python details when needed.

LunaScope

For users who want point-and-click visual review and an easier first entry point before moving into scripts or notebooks.

  1. LunaScope Start with the GUI and overall orientation.
  2. Downloads and installation Install the relevant Luna components.
  3. Quick start Learn the shared Luna ideas on a small example.
  4. Take two Continue with projects, outputs, and annotations.
  5. lunapi overview Understand the Python layer that LunaScope builds on.
  6. Concepts and syntax Learn the underlying Luna model behind the GUI.
  7. Walk-through See the fuller end-to-end analysis workflow.
  8. scope viewer Explore the related interactive viewer documentation.

Tutorial and Walk-through

The tutorial and the walk-through are the main guided entry points into Luna. They introduce the basic workflow and the concepts that the reference pages assume:

  • sample lists and projects
  • signals, annotations, epochs, and masks
  • commands and parameters
  • output tables and stratification
  • the overall analysis loop of inspect, analyze, extract, iterate

In practice:

  • the tutorial is the best first-pass introduction
  • the walk-through is the best practical next step after that

Concepts

After the tutorial, read these pages before diving into individual commands:

These three pages explain how Luna thinks about:

  • sample lists and projects
  • commands and parameters
  • epochs, masks, annotations, and signals
  • output tables and stratification

Without that framing, the detailed command pages can feel much denser than they actually are.

Reference

The reference pages are excellent when you already know roughly what you want to do. They are less effective as a first read.

Use them when one of these is true:

  • you know the command name and need parameters or outputs
  • you want to compare related commands
  • you are debugging an analysis and need exact field definitions
  • you are working in one domain, such as artifacts, hypnograms, or spectra

Useful starting points: