sausero 0.2.3

This software is designed to reduce Broad Band Imaging observations obtained with OSIRIS+.

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 AUomatize in a Simple Environment the Reduction of Osiris+ data (SAUSERO) processes raw science frames to address noise, cosmetic defects, and pixel heterogeneity, preparing them for photometric studies. These corrections are essential before any analysis can be performed. The operations applied to the images depend on the type of observation. This software has been specifically designed to reduce and prepare science frames 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>=2.4.1
astrometry_net_client>=0.3.0
astropy>=5.3.4
astroquery>=0.4.6
ccdproc>=2.4.1
lacosmic>=1.1.0
loguru>=0.7.2
matplotlib>=3.8.0
numpy>=1.25.2
PyYAML>=6.0.2
sep>=1.2.1`

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=3.9 -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.

sausero -pr <your_program> -bl <your_ob>

• -pr: Your GTC program indicator.
• -bl: The observed block number.

ATTENTION: The first time, the code will 'fail' because the configuration file does not know the root directory where the images are stored and your astrometry-api-key. To fix this, follow the instructions below.

You must edit the configuration file, which is located in your home directory inside a folder named sausero/.

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

1. PATH_DATA: Set this to the root directory containing your frames. Example:

   "PATH_DATA": "/path/to/your/frames/"
   
   

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. During execution, SAUSERO will create a new folder named reduced/, where the reduced frames will be saved.

2. No_Session: 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.

Running SAUSERO

After updating and saving the configuration file, you can run the command again. This time, the software will execute successfully.

sausero -pr <your_program> -bl <your_ob>

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.
    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: [e-mail]

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