RASA36 Transient Tool

Purpose

To identify transient candidates in RASA36 science images using a GUI tool.

The tool provides a graphical interface for examining and classifying potential transient astronomical objects detected in RASA36 telescope images. It displays three views:

1. A subtracted image showing the difference between science and reference images to highlight changes
2. The new science image showing the current observation
3. A reference image from a previous epoch for comparison

Key features:

• Interactive zoom and pan controls for detailed inspection
• Side-by-side display of science, reference and difference images
• Quick classification using keyboard shortcuts
• Progress tracking across multiple image tiles
• Memo field for notes on individual candidates
• Flexible configuration via config.ini
• Automatic image scaling and normalization
• Image caching for smooth navigation
• CSV output for analysis and followup

The tool is designed to efficiently process large numbers of candidate detections while maintaining high accuracy through careful visual inspection and comparison.

Requirements

The image format is either PNG or FITS. Python 3.10 or later is required.

Required Python packages:

• numpy
• pandas
• astropy
• matplotlib
• tkinter

Usage

1. Install required dependencies:

   pip install numpy pandas astropy matplotlib tkinter

2. Configure settings in config.ini:

   • Set data directory path containing FITS/PNG images
   • Configure display preferences (zoom, scaling, etc.)
   • Set keyboard shortcuts
   • Choose operation mode (normal/view-only)
   • Adjust cache and preload settings

3. Run the tool:

   python3 Transient_Tool_RASA36.py

4. Interface Features:

   • Image display with zoom/pan controls
   • Toggle between science and reference images
   • Classification buttons for candidates:
     • Significant (Q)
     • Marginal (W)
     • Subtraction artifact (E)
     • Error (R)
     • You can change the name of the categories in config.ini
   • Navigation controls:
     • Next/Previous image (Arrow keys)
     • Jump to unclassified (U)
     • Reset zoom (T)
   • Results saved to CSV file
   • Short-cut keys can be changed in config.ini

5. Output:

   • Classifications stored in CSV with columns:
     • File index
     • Tile ID
     • Unique number
     • Display scale
     • Memo field
     • Classification (Significant, Marginal, Subtraction artifact, Error)

6. Modes:

   • Normal mode: Full classification capabilities
   • View mode: Display-only without classification
   • Specific view mode: Filter by classification type

7. Logging:

   • Operations logged to configured log file
   • Configurable log level (DEBUG/INFO/WARNING/ERROR)

For detailed configuration options, refer to comments in config.ini.

Now working on

• Making another tool to make visualization of transient candidates

Future Work

• Make the code more efficient
• Generalize the code for other telescopes
• Add more analysis tools