radarqc

Python package for loading and processing HF radar spectra in Cross-Spectrum file format. See file specification here.

Python Package

This repository provides a python package with utilities for:

• Loading Cross-Spectrum files as Python objects containing headers and antenna spectra.
• Serializing Python object representation as Cross-Spectrum files.
• Preprocessing antenna spectra to calculate gain and deal with outliers.
• Filter spectra to reduce the effects of background noise on wave velocity calculation.

Installation

From within the repository:

pip3 install radarqc

Example Usage

The radar used to generate cross-spectrum data can sometimes detect outliers. This is indicated by negative signal values in the data. This example loads a file using the Abs method to ignore the outliers, computes the relative gain, then writes the result back into a file.

from radarqc import csfile
from radarqc.processing import Abs, CompositeProcessor, GainCalculator

def example():
    reference_dbm = 34.2
    path = "example.cs"
    preprocess = CompositeProcessor(
        Abs(), GainCalculator(reference=reference_dbm)
    )
    
    # Read binary file into 'CSFile' object.
    # Spectrum data will be processed to compute gain.
    with open(path, "rb") as f:
        cs = csfile.load(f, preprocess)
    
    # Write processed file back into original format on disk.
    with open(path, "wb") as f:
        csfile.dump(cs, f)

The loaded CSFile object can be used to access file metadata via the header attribute, as well as various attributes for accessing data from individual antenna and cross-antenna spectra with a numpy.ndarray data type.