SAUSERO

SAUSERO is a reduction software for the Broad Band Imaging mode of OSIRIS+ at GTC.

Developed by Fabricio M. Pérez-Toledo

General Description

Software to AUtomatize in a Simple Environment the Reduction of Osiris+ data (SAUSERO) processes OSIRIS+ raw science frames to address noise, cosmetic defects, and pixel heterogeneity, preparing them for photometric analysis. Correcting these artifacts is a critical prerequisite for reliable scientific analysis. The software applies observation-specific reduction steps, ensuring optimized treatment for different data types. Developed with a focus on simplicity and efficiency, SAUSERO streamlines the reduction pipeline, enabling researchers to obtain calibrated data ready for photometric studies.

Key Reduction Steps:

1. Application of a Bad Pixel Mask (BPM) to all frames.
2. Creation of the Master Bias.
3. Creation of the Master Flat.
4. Application of master calibration frames to both standard star and science frames.
5. Removal of cosmic rays.
6. Sky subtraction.
7. Alignment of science frames.
8. Astrometric calibration.
9. Flux calibration.

Input Requirements:

The software requires the following frames as input:

• Bias frames
• Sky flat frames
• Photometric standard star frames
• Science frames

Outputs

The generated results consist of one image per observed band. For each image, the following corrections and calibrations will have been applied:

• Bias subtraction
• Flat-field correction (including fringing correction for the Sloan z band, if applicable)
• Image alignment and stacking
• Astrometric calibration
• Photometric calibration (estimation of the zero-point, ZP ± error)

To address cosmetic defects, a Bad Pixel Mask (BPM) is applied, and the LACosmic algorithm is used to handle cosmic ray removal.

Requirements

Operative System

• Any: The software is designed to run within a Conda environment, ensuring compatibility across platforms.

Dependencies

The following Python packages are required (minimum versions specified), however, they will be installed automatically together the :

astroalign>=2.6.1
astrometry_net_client>=0.6.0
astropy>=7.1.0
astroquery>=0.4.10
ccdproc>=2.5.1
lacosmic>=1.3.0
loguru>=0.7.3
matplotlib>=3.10.3
numpy>=2.3.1
PyYAML>=6.0.2
sep>=1.4.1`

Hardware Requirements

• RAM: Minimum 4GB (higher is recommended for large datasets).

Installation

Installing SAUSERO is straightforward. Follow these steps:

1. Activate your Conda environment (or create a new one if needed (see below)):

   conda activate <your_env>
   
   

2. Install SAUSERO using pip:

   pip install sausero
   
   

That's it! SAUSERO is now almost ready to use ;)

Optional: Creating a New Conda Environment

If you don’t have an existing Conda environment, you can create one specifically for SAUSERO with the following commands:

conda create -n sausero_env python=3.11 -y
conda activate sausero_env
pip install sausero

First-Time Setup

Once Conda is set up, you should run SAUSERO for the first time to create the file configuration.json that has to be configured after.

$ sausero -c

or

$ sausero --create_config

You must edit the configuration file, which is located in your frame directory.

You need to set the following parameters in the configuration file:

1. No_Session (Required): This is your Astrometry.net API key. Example:

   "No_Session":"astrometry-api-key"
   
   

To obtain this key, create an account on Astrometry.net. Copy your API key and paste it into the configuration file.

2. Optional Setup: You need to adjust the setup according to your observation. For example, if you are working with Sloan z and need to remove the fringing, you must enable the option in the Reduction section and set the save_fringing parameter to true. Regarding the alignment, astrometrization, or photometry parameters, they can be modified, but they generally work well as they are.

The directory structure must follow the format <Your_Program>_<Your_OB>/. Inside this directory, you should have a raw/ folder where the original frames are stored, and a reduced/ folder where the reduced frames will be saved.

Your_program/
    configuration.json
    raw/
    reduced/

Running SAUSERO

After saving and updating the configuration file, you can run the command using the following argument. The software will execute successfully.

$ sausero -e

or

$ sausero --execute

Outputs and Results

Once the process is complete, you will find a collection of reduced frames in the reduced/ folder inside your frame directory. The output includes:

A. Reduced science frames:

• One version with the sky included.
• One version with the sky subtracted.

B. Aligned frames:

• Both sky-included and sky-subtracted versions.

C. Astrometrized frames:

• Frames with astrometric calibration applied.

D. Visualization PNG files:

• A PNG showing the detected sources in the Field of View (FoV).
• A PNG showing the photometric standard star.

E. Final reduced science frames:

• Both sky-included and sky-subtracted versions.

Important Notes

• By default, SAUSERO ensures your data remains private when using Astrometry.net. The software's internal configuration avoids sharing any data with the Astrometry.net community, ensuring your data's security.

Project Structure

SAUSERO/
    BPM/
        BPM_OSIRIS_PLUS.fits -> BAD PIXEL MASK
    config/
        configuration.json   -> Configuration file.
    check_files.py           -> It determines which steps can be performed by the pipeline based on the available FITS files.
    aligning_osirisplus.py   -> Aligns the science frames. 
    astrometry_osirisplus.py -> Astrometrization of the science frames.
    Color_Codes.py           -> Gives color to the comments
    OsirisDRP.py             -> Handles all the sofware and manages the frames. 
    photometry_osirisplus.py -> Carries out the photometric calibration.
    reduction_osirisplus.py  -> Carries out the clean process.

Note about the frames

The code is designed to work with OSIRIS+ frames. They must be in FITS format.

LICENSE

This software is under GPL v3.0 license. More information is available in the repository.

CONTACT

• Email: fabricio.perez@gtc.iac.es

• Repository: https://github.com/Kennicutt/SAUSERO