Astrometry Go Client

Offline astrometric plate-solving for Go - Solve astronomical images locally without internet access using the astrometry-dockerised-solver Docker container. Complete privacy and control over your data with no dependency on external services.

Features

• 100% Offline Operation - No internet required after initial setup
• Complete Privacy - Your images never leave your machine
• No Rate Limits - Solve unlimited images without API quotas
• Fast Local Processing - No network latency or upload time
• Simple, type-safe API for plate-solving astronomical images
• Docker-based integration (no complex installation required)
• Support for scale hints, downsampling, and RA/Dec position hints
• WCS header parsing with structured results
• Context-aware with timeout support
• Comprehensive error handling
• CLI tool for quick command-line solving
• Full test coverage with integration tests validating both Docker implementations (diarmuidk/astrometry-dockerised-solver and dm90/astrometry)

Why Offline?

Unlike cloud-based plate-solving services, this library runs entirely on your local machine:

• Privacy First - Your astrophotography images and location data stay private
• No Internet Required - Work in remote locations, observatories, or anywhere offline
• Free & Unlimited - No API keys, rate limits, or subscription fees
• Faster Processing - No upload/download time, just local computation
• Full Control - Customize solve parameters without service restrictions
• Self-Hosted - Perfect for automated pipelines, observatories, and air-gapped systems

Prerequisites

Note: Internet is only required once during initial setup to download the Docker image and index files. After setup, the solver runs 100% offline.

Required

• Go 1.21+
• Docker with the diarmuidk/astrometry-dockerised-solver image pulled (one-time download)
• Astrometry.net index files downloaded to a local directory (one-time download)

Quick Setup

# Clone the repository (for development)
git clone https://github.com/DiarmuidKelly/astrometry-go-client.git
cd astrometry-go-client

# Download all index files (~350MB)
./scripts/download-indexes.sh

Index Files Guide

Astrometry.net requires index files that match your camera's field of view (FOV). Using an index that's too wide for your FOV guarantees failure - the star patterns physically won't fit in your image.

Choosing the Right Index Files

First, calculate your FOV:

FOV = 2 × arctan(sensor_width / (2 × focal_length))
FOV ≈ sensor_width / focal_length   (in radians)
FOV ≈ (sensor_width / focal_length) × 57.3   (in degrees)

FOV (degrees) = (sensor_width_mm / focal_length_mm) × 57.3

Then download 2-3 indexes that bracket your FOV:

Index File	Field Width	Size	Full Frame (36mm)	APS-C Canon (22.3mm, 1.6x)	Download
index-4119	0.1° - 0.2°	144 KB	10,000-20,000mm	6,400-12,800mm	Download
index-4118	0.2° - 0.28°	187 KB	7,300-10,000mm	4,500-6,400mm	Download
index-4117	0.28° - 0.4°	248 KB	5,100-7,300mm	3,200-4,500mm	Download
index-4116	0.4° - 0.56°	409 KB	3,600-5,100mm	2,300-3,200mm	Download
index-4115	0.56° - 0.8°	740 KB	2,500-3,600mm	1,600-2,300mm	Download
index-4114	0.8° - 1.1°	1.4 MB	1,800-2,500mm	1,200-1,600mm	Download
index-4113	1.1° - 1.6°	2.7 MB	1,300-1,800mm	800-1,200mm	Download
index-4112	1.6° - 2.2°	5.3 MB	900-1,300mm	600-800mm	Download
index-4111	2.2° - 3.0°	10 MB	700-900mm	400-600mm	Download
index-4110	3.0° - 4.2°	25 MB	500-700mm	300-400mm	Download
index-4109	4.2° - 5.6°	50 MB	350-500mm	220-300mm	Download
index-4108	5.6° - 8.0°	95 MB	250-350mm	160-220mm	Download
index-4107	8.0° - 11.0°	165 MB	180-250mm	110-160mm	Download

Total size of all indexes: ~350 MB

Example Setups

DSLR Astrophotography (APS-C sensor, 24mm wide):

mkdir -p ~/astrometry-data && cd ~/astrometry-data
# 200mm lens: ~7° FOV
wget http://data.astrometry.net/4100/index-4108.fits
wget http://data.astrometry.net/4100/index-4109.fits

# 50mm lens: ~27° FOV
wget http://data.astrometry.net/4100/index-4110.fits
wget http://data.astrometry.net/4100/index-4111.fits

Telescope (1000mm focal length, APS-C sensor):

mkdir -p ~/astrometry-data && cd ~/astrometry-data
# ~1.4° FOV
wget http://data.astrometry.net/4100/index-4113.fits
wget http://data.astrometry.net/4100/index-4114.fits

Quick Solver (50mm-300mm lenses - recommended default):

mkdir -p ~/astrometry-data && cd ~/astrometry-data
# Download 1.1° - 4.2° range (~43 MB total)
# Covers DSLR + 50-300mm focal lengths
wget http://data.astrometry.net/4100/index-4110.fits  # 3.0° - 4.2° (50-70mm)
wget http://data.astrometry.net/4100/index-4111.fits  # 2.2° - 3.0° (70-110mm)
wget http://data.astrometry.net/4100/index-4112.fits  # 1.6° - 2.2° (110-150mm)
wget http://data.astrometry.net/4100/index-4113.fits  # 1.1° - 1.6° (150-220mm)

Note: The scripts/download-indexes.sh script downloads all indexes automatically.

Why Index Matching Matters

Index files contain pre-computed star patterns (called "quads") at specific angular scales. Using the wrong index causes failure, not just slowness.

What happens with mismatched indexes:

Scenario	Result	Why
Narrow image (0.5°) + Wide index (6-8°)	❌ Guaranteed failure	Star patterns in the index span 6-8°. Your 0.5° image physically cannot contain patterns that large - they don't fit in the frame.
Wide image (8°) + Narrow index (0.5°)	⚠️ Likely failure	Your wide image does contain small sub-regions with narrow patterns, but matching is unreliable, very slow, and usually fails.

The critical rule:

• Index scale larger than your FOV → guaranteed failure (patterns don't fit in your image)
• Index scale smaller than your FOV → likely failure (unreliable matching of sub-regions)

✅ Best practice: Download 2-3 indexes that bracket your expected FOV (one above, one below). This ensures reliable, fast solving regardless of minor FOV variations.

Docker Setup

This library uses the diarmuidk/astrometry-dockerised-solver Docker container to perform plate-solving. You have several options for running the dependency:

Docker Execution Modes

The library supports two Docker execution modes:

1. Docker Run Mode (Default)

How it works: The library spawns a new Docker container for each solve operation, then removes it.

Pros:

• Simple setup - no container management required
• Clean isolation per solve

Cons:

• Slower for multiple solves (~1-2s container startup overhead per solve)
• More Docker overhead

Setup: Pull the image, then use the library - that's it!

# Pull from DockerHub (recommended)
docker pull diarmuidk/astrometry-dockerised-solver:latest

# Or from GitHub Container Registry (GHCR)
docker pull ghcr.io/diarmuidkelly/astrometry-dockerised-solver:latest

Client configuration:

config := &client.ClientConfig{
    IndexPath: "/path/to/astrometry-data",  // Path to your index files
    // DockerImage defaults to ghcr.io/diarmuidkelly/astrometry-dockerised-solver:latest
    // To use dm90/astrometry instead: DockerImage: "dm90/astrometry"
}
c, err := client.NewClient(config)

2. Docker Exec Mode (Recommended for Development)

How it works: Uses a long-running Docker container and executes solve commands via docker exec.

Pros:

• Faster: No container startup overhead (typically 1-2s faster per solve)
• Ideal for development, testing, or batch processing

Cons:

• Requires manual container management

Setup Option A: Using Docker Compose (Recommended)

# 1. Copy and configure environment
cp .env.example .env
# Edit .env and set ASTROMETRY_INDEX_PATH to your index files directory

# 2. Start the container
docker compose up -d

# 3. Verify it's running
docker ps | grep astrometry-solver

Setup Option B: Manual Docker Run

docker run -d \
  --name astrometry-solver \
  -v ~/astrometry-data:/usr/local/astrometry/data:ro \
  -v /tmp/astrometry-shared:/shared-data \
  diarmuidk/astrometry-dockerised-solver:latest \
  tail -f /dev/null

Alternative: You can also use the original dm90/astrometry image if you prefer:

docker pull dm90/astrometry:latest

Client configuration:

config := &client.ClientConfig{
    IndexPath:     "/path/to/astrometry-data",
    UseDockerExec: true,
    ContainerName: "astrometry-solver",
}
c, err := client.NewClient(config)

Performance Comparison

Operation	Docker Run Mode	Docker Exec Mode	Difference
First solve	~15s	~13s	~2s faster
Subsequent solves (each)	~15s	~13s	~2s faster
Setup overhead	None	Start container once	One-time

Recommendation: Use docker exec mode for development/testing. Either mode works well for production depending on your orchestration setup.

Full Stack Setup

For a complete REST API server with web interface, see the Astrometry API Server project. It includes:

• docker-compose orchestration for both the API server and solver
• RESTful HTTP API
• Swagger documentation
• Health monitoring

Installation

As a Library

go get github.com/DiarmuidKelly/astrometry-go-client

CLI Tool

go install github.com/DiarmuidKelly/astrometry-go-client/cmd/astro-cli@latest

Or build from source:

git clone https://github.com/DiarmuidKelly/astrometry-go-client.git
cd astrometry-go-client
make install

Quick Start

Library Usage

package main

import (
    "context"
    "fmt"
    "log"

    "github.com/DiarmuidKelly/astrometry-go-client"
)

func main() {
    // Create client
    config := &client.ClientConfig{
        IndexPath: "/path/to/astrometry-data",
    }
    c, err := client.NewClient(config)
    if err != nil {
        log.Fatal(err)
    }

    // Configure solve options
    opts := client.DefaultSolveOptions()
    opts.ScaleLow = 1.0   // 1 arcmin/width
    opts.ScaleHigh = 3.0  // 3 arcmin/width

    // Solve the image
    result, err := c.Solve(context.Background(), "image.jpg", opts)
    if err != nil {
        log.Fatal(err)
    }

    if result.Solved {
        fmt.Printf("RA: %.6f, Dec: %.6f\n", result.RA, result.Dec)
        fmt.Printf("Pixel Scale: %.2f arcsec/pixel\n", result.PixelScale)
    } else {
        fmt.Println("Image could not be solved")
    }
}

CLI Usage

astro-cli \
  --image photo.jpg \
  --index-path ~/astrometry-data \
  --scale-low 1 \
  --scale-high 3 \
  --downsample 2

Output (JSON):

{
  "solved": true,
  "ra": 120.123456,
  "dec": 45.987654,
  "pixel_scale": 1.23,
  "rotation": 15.5,
  "field_width": 2.5,
  "field_height": 1.8,
  "solve_time": 12.34
}

API Reference

Client Configuration

type ClientConfig struct {
    DockerImage   string        // Default: "ghcr.io/diarmuidkelly/astrometry-dockerised-solver:latest"
                                 // Also compatible with: "dm90/astrometry"
    IndexPath     string        // Required: path to index files
    TempDir       string        // Optional: temp directory for processing
    Timeout       time.Duration // Default: 5 minutes
    UseDockerExec bool          // Use docker exec mode (default: false)
    ContainerName string        // Container name for docker exec mode
}

Solve Options

type SolveOptions struct {
    ScaleLow         float64  // Lower bound of image scale
    ScaleHigh        float64  // Upper bound of image scale
    ScaleUnits       string   // "degwidth", "arcminwidth", "arcsecperpix"
    DownsampleFactor int      // Reduce resolution (default: 2)
    DepthLow         int      // Min quads to try (default: 10)
    DepthHigh        int      // Max quads to try (default: 20)
    NoPlots          bool     // Disable plot generation (default: true)
    RA               float64  // RA hint in degrees (optional)
    Dec              float64  // Dec hint in degrees (optional)
    Radius           float64  // Search radius in degrees (optional)
    Verbose          bool     // Enable verbose output
}

Result Structure

type Result struct {
    Solved      bool              // Whether the image was solved
    RA          float64           // Right ascension (J2000, degrees)
    Dec         float64           // Declination (J2000, degrees)
    PixelScale  float64           // arcsec/pixel
    Rotation    float64           // Field rotation (degrees)
    FieldWidth  float64           // Field of view width (degrees)
    FieldHeight float64           // Field of view height (degrees)
    WCSHeader   map[string]string // Raw WCS header fields
    OutputFiles []string          // Paths to generated files
    SolveTime   float64           // Solve duration (seconds)
}

Methods

NewClient(config *ClientConfig) (*Client, error)

Creates a new astrometry client with the given configuration.

Solve(ctx context.Context, imagePath string, opts *SolveOptions) (*Result, error)

Solves a single image file and returns the plate solution.

SolveBytes(ctx context.Context, data []byte, format string, opts *SolveOptions) (*Result, error)

Solves image data from a byte slice (useful for in-memory images).

Examples

See the examples/ directory for more usage examples:

• examples/basic/ - Basic plate-solving example
• examples/batch/ - Batch processing multiple images (coming soon)
• examples/with-hints/ - Using RA/Dec hints for faster solving (coming soon)

Error Handling

The library provides structured error types:

var (
    ErrNoSolution    = errors.New("no solution found")
    ErrTimeout       = errors.New("solve operation timed out")
    ErrDockerFailed  = errors.New("docker command failed")
    ErrInvalidInput  = errors.New("invalid input parameters")
    ErrWCSParseFailed = errors.New("failed to parse WCS output")
)

Example:

result, err := c.Solve(ctx, imagePath, opts)
if err != nil {
    if errors.Is(err, client.ErrTimeout) {
        log.Println("Solve timed out - try increasing timeout or downsample")
    } else if errors.Is(err, client.ErrDockerFailed) {
        log.Println("Docker error - check Docker is running")
    }
    return err
}

if !result.Solved {
    log.Println("No solution - try adjusting scale parameters")
}

Performance Tips

1. Use scale bounds: Providing ScaleLow and ScaleHigh dramatically speeds up solving
2. Downsample: Higher downsample factors (2-4) work well for most images
3. RA/Dec hints: If you know approximate coordinates, use them to reduce search space
4. Index files: Download only the indexes appropriate for your field of view

Development

Building

make build        # Build all binaries
make test         # Run tests
make lint         # Run linter
make clean        # Clean build artifacts

Running Tests

go test ./...

Integration tests requiring Docker can be run with:

go test -tags=integration ./...

Contributing

Contributions welcome! See CONTRIBUTING.md for workflow details.

Quick Start:

1. Fork the repository
2. Create a feature branch (git checkout -b feat/my-feature)
3. Make your changes with conventional commits
4. Push and create a PR with [MAJOR], [MINOR], or [PATCH] prefix

Auto-release workflow handles versioning, changelog, and releases on PR merge.

License

This project is licensed under the GNU General Public License v3.0 - see the LICENSE file for details.

Links

• Astrometry API Server - REST API server for this library
• Astrometry Dockerised Solver - Maintained solver-only Docker image
• Changelog
• Contributing Guide
• Issues
• Astrometry.net
• dam90/astrometry - Alternative Docker image with web UI

Acknowledgments

• Astrometry.net - The plate-solving engine
• dam90/astrometry - Original containerized version with web UI
• astrometry-dockerised-solver - Maintained solver-only image