StepNoiseFFT

class sofia_redux.instruments.hawc.steps.stepnoisefft.StepNoiseFFT[source]

Bases: StepParent

Take the FFT of diagnostic noise data.

The input to this step is lab data taken with CALMODE = ‘NOISE’. The output is a FITS file containing the power spectrum image with pixels arrayed along the y-axis and frequencies arrayed along the x-axis. Frequency values are stored in WCS keywords in the header. The full FFT with linear frequencies is stored in the primary image. Subsequent extensions contain binned frequencies, in linear and log scales.

Methods Summary

run()

Run the data reduction algorithm.

setup()

Set parameters and metadata for the pipeline step.

Methods Documentation

run()[source]

Run the data reduction algorithm.

Because this step is single-in, single-out (SISO), self.datain must be a DataFits object. The output is also a DataFits object, stored in self.dataout.

The process is:

  1. Convert the flux data to Amps/rtHz.

  2. Take the FFT of the flux data for each pixel.

  3. Bin the frequencies and average flux values within each bin.

  4. Store the data.

setup()[source]

Set parameters and metadata for the pipeline step.

Output files have PRODTYPE = ‘noisefft’, and are named with the step abbreviation ‘FFT’.

Parameters defined for this step are:

truncatebool

If set, will truncate to an integer power of 2 number of samples before taking the FFT.