3DCubeGen Documentation

3DCubeGen is a Python toolkit for reconstructing 3D astronomical data cubes from IFU (Integral Field Unit) spectrograph observations. It converts Row-Stacked Spectra (RSS) data into regular 3D cubes and 2D maps using weighted kernel interpolation. Three spectrographs are supported: LVM (SDSS Local Volume Mapping), MEGARA (GTC), and VirusP (HET).

Getting Started

• Installation & Getting Started
  • Prerequisites
  • Installing from Source
  • Core Dependencies
  • Optional Dependencies
  • Quick Verification

LVM Pipeline

• Commands Overview
  • Single vs. Pipeline Commands
  • Cube vs. Map Commands
  • pipecube-Specific Features
  • pipemap-Specific Features
  • Parameter Comparison
  • Quick-Start Examples
• Kernel Smoothing Parameters
  • sincube / sinmap: explicit parameters
  • pipecube / pipemap: type letter
  • Type-to-parameter mapping
  • Differences beyond the kernel
  • Small-exposure guard in pipecube
• YAML Configuration Reference
  • sincube Configuration
  • pipecube Configuration
  • Kernel Type Codes
  • SAS Directory Resolution
  • Output Path Construction
• Exposure List File Format
  • File Format
  • Example File
  • Tile Group Derivation
  • How the Exposure List Connects to Config Parameters
  • RSS File Path Resolution

Other Spectrographs

• MEGARA Pipeline
  • Overview
  • CLI Entry Point
  • rundrp
  • runfulldrp
  • Configuration File
  • Differences from LVM
• VirusP Pipeline
  • Overview
  • CLI Entry Point
  • Basic Usage
  • CLI Options
  • Configuration File
  • VirusP-Specific Features
  • Differences from LVM

Reference

• Reconstruction Algorithm
  • Kernel Interpolation
  • Radius Cutoff
  • Error Propagation
  • ADR-Aware Mode
  • Spaxel Size
  • Flux Scaling
  • Multi-Threading
  • Implementation Reference
• Output Data Products
  • LVM Cubes
  • LVM Maps
  • JPEG Composite Images
  • LVM RSS (from cube)
  • MEGARA Outputs
  • VirusP Outputs
  • Flux Units
• DAP Integration Tools
  • RSS Extraction from Cubes
  • DAP Emission Line Tools