API

Public Step API

jwst.refpix.refpix_step Module

Reference pixel correction step.

Classes

RefPixStep([name, parent, config_file, ...])

Use reference pixels to correct bias drifts.

Complete Developer API

jwst.refpix.irs2_subtract_reference Module

Functions

correct_model(output_model, irs2_model[, ...])	Correct an input NIRSpec IRS2 datamodel using reference pixels.
float_to_complex(data)	Convert real and imaginary parts to complex.
make_irs2_mask(nx, ny, scipix_n, refpix_r)	Make IRS2 mask.
strip_ref_pixels(output_model, irs2_mask)	Copy out the normal pixels from PIXELDQ and GROUPDQ arrays.
clobber_ref(data, output, odd_even, mask, ...)	Set some interleaved reference pixel values to zero.
decode_mask(mask)	Interpret the MASK column of the DQ table.
replace_refpix(bad_pix, data, bad_mask, ...)	Replace a bad reference pixel with its nearest neighboring value.
flag_bad_refpix(datamodel[, n_sigma, ...])	Flag bad reference pixels and replace with nearest good values.
subtract_reference(data0, alpha, beta, ...)	Subtract reference output and pixels for the current integration.
fft_interp_norm(dd0, mask0, row, hnorm, ...)	Filter iteratively in FFT space of the normal pixels in each group.
ols_line(x, y)	Fit a straight line using ordinary least squares.
remove_slopes(data0, ngroups, ny, row)	Remove slopes.
replace_bad_pixels(data0, ngroups, ny, row)	Replace bad pixels.
fill_bad_regions(data0, ngroups, ny, nx, ...)	Fill the bad regions in the data.

jwst.refpix.optimized_convolution Module

Functions for Simple Improved Reference Subtraction (SIRS).

They are for using the SIRS algorithm to improve the 1/f noise, only for full frame non-IRS2 NIR data.

Functions

make_kernels(sirs_kernel_model, detector, ...)	Make convolution kernels from Fourier coefficients in the reference file.
get_conv_kernel_coeffs(sirs_kernel_model, ...)	Get the convolution kernels coefficients from the reference file.
apply_conv_kernel(data, kernels[, sigreject])	Apply the convolution kernel.

jwst.refpix.reference_pixels Module

Module for handling Reference Pixels.

Functions

create_dataset(input_model, ...)	Create a dataset object from an input model.
correct_model(input_model, odd_even_columns, ...)	Perform Reference Pixel Correction on a JWST Model.
reference_pixel_correction(input_dataset)	Do the Reference Pixel Correction.
process_zeroframe_correction(input_dataset)	Do the Reference Pixel Correction for the ZEROFRAME array.
restore_input_model(input_dataset, saved_values)	Restore the input model.
setup_dataset_for_zeroframe(input_dataset, ...)	Set up dataset for zero frame.
save_science_values(input_dataset)	Save corrected data for the SCI extension.

Classes

Dataset(input_model, odd_even_columns, ...)	Data container for passing data from routine to routine.
NIRDataset(input_model, odd_even_columns, ...)	Container for NIR detector datasets.
MIRIDataset(input_model, odd_even_rows, ...)	Container for MIRI data.