tart-cargo 0.3.9
Curated cargo of TART radio astronomy packages for stimela 2.0
License: MIT
Requires Python: <4.0,>=3.9

# tart_cargo

Curated cargo of TART radio astronomy packages for stimela 2.0. This allows the use of TART telescope tools as part of the [stimela 2.0](https://github.com/caracal-pipeline/stimela/) radio astronomy pipeline.

Author: Tim Molteno

Based on the [tart_tools](https://github.com/tart-telescope/tools) package which does most of the heavy lifting.

## Installation and Use

### GitHub Codespaces (Easiest)

The easiest way to get started is using GitHub Codespaces, which provides a pre-configured development environment in your browser:

1. Click the green "Code" button on the GitHub repository page
2. Select the "Codespaces" tab
3. Click "Create codespace on main" (or your desired branch)

The codespace will automatically set up Ubuntu with Python 3.12, Apptainer, and all required dependencies. Once ready, you can run tart-cargo directly in the terminal.

### Local Installation

You will need a Linux or Windows computer with [apptainer](https://apptainer.org/), and python installed.

#### Linux

Most linux has python preinstalled.. Packages are available for download from apptainer.org. On recent debian

    apt install apptainer squashfuse fuse2fs gocryptfs

#### Windows

install the Windows Subsystem for Linux (WSL), open PowerShell as an administrator and run the command ```wsl --install```. This will enable the necessary features and install the default Linux distribution, which is usually Ubuntu. 

To install pip on WSL, first ensure that Python is installed by running ```sudo apt install python3```. Then, install pip using the command ```sudo apt install python3-pip``.


## Use of tart_cargo

then create a python virtual environment

    python3 -m venv myvenv
    source myvenv/bin/activate
    pip install tart_cargo

This should install all the necessary dependencies (including stimela).

Then create a stimela recipe. An example is shown below...

```
#!/usr/bin/env -S stimela run -l
# This basic TART Stimela 2.0 processing pipeline
opts:
    log:
        dir: logs/log-{config.run.datetime}
        name: log-{info.fqname}
        nest: 2
        symlink: log

_include:
    - (tartcargo):
        - tart2ms.yml
        - tart-download-data.yml
        - disko.yml
        - disko-draw.yml

tart-image:
    info: TART imaging using stimela

    inputs:
        tart:
            dtype: str
            required: true
            info: "TART name (e.g. mu-udm)"

    outputs:
        ms:
            dtype: MS
            default:  '{current.tart}.ms'
        hdf:
            dtype: File
            default: =STRIPEXT(current.ms) + '-vis.hdf'
        svg:
            dtype: File
            default: =STRIPEXT(current.ms) + '.svg'

    assign:
        api: 'https://api.elec.ac.nz/tart/{recipe.tart}'


    steps:

        download-hdf:
            cab: tart-download-data
            params:
                api: =recipe.api
                vis: true
                file: =recipe.hdf

        create-ms:
            cab: tart2ms
            params:
                hdf: =steps.download-hdf.file
                ms: =recipe.ms
                clobber: true
                single-field: true
                rephase: obs-midpoint

        disko-image:
            cab: disko
            params:
                ms: =recipe.ms
                HDF: '{recipe.tart}.h5'
                healpix: true
                fov: 170deg
                res: 0.5deg
                lasso: true
                alpha: 0.006
                l1-ratio: 0.02

        project-image:
            cab: disko-draw
            params:
                hdf: '{recipe.tart}.h5'
                show-sources: true
                SVG: =recipe.svg
```

You can run this recipe as follows:

    stimela run example_recipe.yml tart=mu-udm
    
This will download data, and form an image from the specified TART telescope.