Core SuperDARN Processing Tools

Installation

Rust

Add the crate to your dependencies in your Cargo.toml file, specifying as a git dependency.

Python

pip install procdarn

From source

If you want to build from source, you first need to have Rust installed on your machine. Then:

1. Clone the repository: git clone https://github.com/SuperDARNCanada/procdarn
2. Run cargo build in the repository directory
3. If wanting to install the Python API, create a virtual environment and source it, then install maturin
4. In the project directory, run maturin develop to build and install the Python bindings. This will make a wheel file based on your operating system and architecture that you can install directly on any compatible machine.

Python API

In-memory fitting

Use FITACF3 algorithm to fit a list of RAWACF records

fitacf3(recs: list[dict]) -> list[dict]

Example

import procdarn
import dmap
infile = "path/to/rawacf"
rawacf_records = dmap.read_rawacf(infile)
fitacf_records = procdarn.fitacf3(rawacf_records)
dmap.write_fitacf(fitacf_records, "path/to/fitacf")

File-to-file fitting

Fit a RAWACF file into a FITACF file

fitacf3_file(rawacf_file: str, fitacf_file: str)

Example

import procdarn
procdarn.fitacf3_file("path/to/rawacf", "path/to/fitacf")

Rust API

• procdarn::fitacf3_file(raw_file: PathBuf, fit_file: PathBuf) -> Result<(), Fitacf3Error>: Fits a RAWACF file into a FITACF file
• procdarn::fitacf3(Vec<RawacfRecord>) -> Result<Vec<FitacfRecord>, Fitacf3Error>: parallelized FITACFv3 on collection of RawacfRecords (from dmap crate)
• procdarn::fitacf3_single_threaded(Vec<RawacfRecord>) -> Result<Vec<FitacfRecord>, Fitacf3Error>: single-threaded FITACFv3 implementation

Binary

raw2fit: Command-line tool for fitting a RAWACF file using the FITACF3 algorithm.

Usage: raw2fit <INFILE> <OUTFILE>

Arguments:
  <INFILE>   Rawacf file to fit
  <OUTFILE>  Output fitacf file path

Options:
  -h, --help     Print help
  -V, --version  Print version