StepFluxjump

class sofia_redux.instruments.hawc.steps.stepfluxjump.StepFluxjump[source]

Bases: StepParent

Correct for flux jumps in raw data.

This pipeline step corrects for a detector effect that introduces discontinuous changes in flux values (flux jumps). Jumps are detected in the data, then a jump map is used to shift all data following the jump to correct values.

Input to this step is raw HAWC data files. This step should be called before sofia_redux.instruments.hawc.steps.StepPrepare. It uses the ‘SQ1Feedback’ and ‘FluxJumps’ columns in the data table. Output from this step has the same format as the input; only flux values in the SQ1FeedbackColumn are modified.

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. Read the jump map from the parameters.

  2. Identify pixel samples with flux jumps (FluxJump data at that pixel is < -32 or > 32).

  3. Fix flux jump data for any pixels that wrap around from 64 to -64, or from -64 to 64 (compared to the previous sample).

  4. Multiply flux jump data by the jump map.

  5. Add the jump data * map to the raw data array.

  6. Store the result in the SQ1Feedback column.

setup()[source]

Set parameters and metadata for the pipeline step.

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

Parameters defined for this step are:

jumpmapstr or float

Path to a file name, specifying the jump gap map in FITS format. Alternatively, a single value can be specified to apply to all pixels. If all jump map values are zero, no jump correction will be performed.