Parameters

jtow takes parameters from a parameter file as a dictionary. The default parameters can be found at the default parameters

Here are some descriptions of what the parameters do.

custBias

custBias controls the bias subtraction.

  • None in Python or null in the YAML parameter file to use the default bias from the pipeline.

  • Path If you give it a path to a custom fits file (e.g. bias/jwst_nircam_superbias_0027.fits), it will use that superbias.

  • selfBias : it will use the first frame available

  • cycleBias: it will cycle through biases in a pattern defined by biasCycle

  • lineIntercept: it will fit a line to the integration and use the intercept as the bias frame

biasCycle

Controls how the bias is subtracted in the case that custBias is equal to cycleBias For example, ['A','B','B','B'] will do bias A, B, B, B, A, B, B, B.

biasCycleSearch

Controls where to find the bias cycle files. For example data_path/superbias_nrca3_?.fits will search for superbias_nrca3_A.fits and superbias_nrca3_B.fits if the biasCycle contains A and B.

ROEBACorrection

If ROEBACorrection is True, it row-by-row, odd/even by amplifier (ROEBA) correction on each group after bias subtraction instead of the reference pixel correction. If it is False, no ROEBA is done. The reference pixel step is run, which only takes effect if reference pixels are available. If ROEBCorrection is GROEBA, then it uses a Gaussian Process train-1/f noise model

ROEBAK

If ROEBAK is True, it adds a step to ROEBA that attempts to remove the kTC noise. Only has an effect if ROEBACorrection is True. If False, no extra kTC correction will be done. This does a slow-read correction of all groups in a frame, calculates the median pixel for all groups for integration-specific kTC correction. This kTC correction is subtracted from all groups in that integration to find the underlying 1/f noise better. However, the kTC correction is undone after the 1/f correction to be sure it doesn’t not introduce any new noise, especially on the source pixels. This is a similar idea to using the custBias="lineIntercept" but with undoing the bias.

colByCol

If colByCol is True, ROEBA will use the median of each column to estimate the slow-read correction. If False, it will subtract the median of all odd columns from all odd columns within an amplifier and the median of all even columns from all even columns within an amplifier.

saveROEBAdiagnostics

saveROEBAdiagnostics saves diagnostics from row-by-row, odd/even by amplifier (ROEBA) correction. If just using regular reference pixel correction, then the regular reference pixel correction is saved.

  • True saves the step immediately following ROEBA correction (full ramp with all integrations). If growing the mask with a kernel, it also saves the growth kernel and before/after growth. If doing regular reference pixel correction instead of ROEBA, save the output of the reference pixel step.

  • False does not save these images.

jumpRejectionThreshold

jumpRejectionThreshold sets the sigma rejection threshold for the JWST jump step to detect cosmic rays

ROEBAmaskGrowthSize

ROEBAmaskGrowthSize sets the size (in pixels) of how large a smoothing kernel should be used to grow the ROEBA mask. This allows the mask to go into faint wings of the image

ROEBAbadRowsAllowed

The number of bad rows allowed befor giving up on ROEBA. This prevents ROEBA from cutting out extended sources.

ROEBApreserveBackg

Preserve the background? When there is a rate file, you can restore the background level from the rate

saveBiasStep

Save the result of the bias subtraction step of the pipeline?

saveJumpStep

Save the jump step result before ramp fitting?

doLincor

Do the linearity correction? It should be True for correct results, but sometimes can be helpful to turn off for troubleshooting

simpleSlopes

Do a simple line fit rather than the most-optimal (right now ordinary least squares) fit?

  • None (‘null’ in .yaml file), no simple slopes are done. Regular jwst pipeline ramp fits.

  • 'Both' Both the jwst fits and simple slopes are performed.

  • 'Only' Only simple slopes are calculated and the (slow) most-optimal fit is skipped.

  • 'Last Group' Save the last group of every integration divided by the estimated int time?

rampFitWeighting

Pass the weighting scheme along to the ramp fit step. If rampFitWeighting is ‘optimal’ it will use optimal weights. If rampFitWeighting is ‘unweighted’, not weighting of groups up the ramp is performed - this approaches last minus first for bright targets. More info is available at the JWST pipelin ramp fitting description page

side_smoothing_length

Set the side smoothing length for reference pixels. This is passed to the jwst reference pixel step. This does not affect ROEBA so if ROEBACorrection is set to True, this will not matter (in the current version of jtow at least). For ROEBA, use smoothSlowDir

smoothSlowDir

If None (‘null’ in .yaml file), no smoothing is done with ROEBA. If set to an int or float, a Savgol filter is applied along the slow-read direction to smooth the ROEBA model.

useGrismRefpx

Use the reference pixels for ROEBA corrections? If True, the left refpix will be used for F322W2 data and right refpix will be used for F444W data. If False, only the background pixels will be used from the rightmost amplifier (F322W2 data) or leftmost amplifier (F444W data).

recenteredNIRCamGrism

Are the grism spectra re-centered in the middle (enabling 1/f corrections from amplifier 1 and 4)?

custGroupDQfile

Set a custom data quality array for after the saturation step to manually set some pixels as saturated. Could be useful if you want to treat all the pixels in a column the same or enforce that the data quality flags are not as variable. Should be the path to a FITS file with the same number of groups as the data and the same dimensions as the data. Will be combined with all integrations’ group data quality flags with a bitwise or. If None (“Null” in YAML file), this is not done.

skipJumpDet

Skip the jump detection step? Passed to the jump detection skip parameter. If True, it is skipped.