Utils

Created on Wed Jul 20 08:51 2022

@author: MCR

Miscellaneous pipeline tools.

exotedrf.utils.do_replacement(frame, badpix_map, dq=None, box_size=5)

Replace flagged pixels with the median of a surrounding box.

Parameters:

  • frame (array-like[float]) – Data frame.

  • badpix_map (array-like[bool]) – Map of pixels to be replaced.

  • dq (array-like[int]) – Data quality flags.

  • box_size (int) – Size of box to consider.

Returns:

  • frame_out (array-like[float]) – Input frame wth pixels interpolated.

  • dq_out (array-like[int]) – Input dq map with interpolated pixels set to zero.

exotedrf.utils.download_stellar_spectra(st_teff, st_logg, st_met, outdir)

Download a grid of PHOENIX model stellar spectra.

Parameters:

  • st_teff (float) – Stellar effective temperature.

  • st_logg (float) – Stellar log surface gravity.

  • st_met (float) – Stellar metallicity as [Fe/H].

  • outdir (str) – Output directory.

Returns:

  • wfile (str) – Path to wavelength file.

  • ffiles (list[str]) – Path to model stellar spectrum files.

exotedrf.utils.fancyprint(message, msg_type='INFO')

Fancy printing statement mimicking logging. Basically a hack to get around complications with the STScI pipeline logging.

Parameters:

  • message (str) – Message to print.

  • msg_type (str) – Type of message. Mirrors the jwst pipeline logging.

exotedrf.utils.format_out_frames(out_frames)

Create a mask of baseline flux frames for lightcurve normalization.

Parameters:

out_frames (int, array-like[int]) – Integration numbers of ingress and/or egress.

Returns:

baseline_ints – Array of baseline frames.

Return type:

array-like[int]

exotedrf.utils.get_default_header()

Format the default header for the lightcurve file.

Returns:

  • header_dict (dict) – Header keyword dictionary.

  • header_commets (dict) – Header comment dictionary.

exotedrf.utils.get_dq_flag_metrics(dq_map, flags)

Take a data quality map and extract a map of pixels which are flagged for a specific reason. A list of data quality flags can be found here: https://jwst-reffiles.stsci.edu/source/data_quality.html.

Parameters:

  • dq_map (array-like(float)) – Map of data quality flags.

  • flags (list[str], str) – Flag types to find.

Returns:

flagged – Boolean map where True values have the applicable flag.

Return type:

np.array(bool)

exotedrf.utils.get_filename_root(datafiles)

Get the file name roots for each segment. Assumes that file names follow the default jwst pipeline structure and are in correct segment order.

Parameters:

datafiles (array-like[str], array-like[jwst.datamodel]) – Datamodels, or paths to datamodels for each segment.

Returns:

fileroots – List of file name roots.

Return type:

array-like[str]

exotedrf.utils.get_filename_root_noseg(fileroots)

Get the file name root for a SOSS TSO with no segment information.

Parameters:

fileroots (array-like[str]) – File root names for each segment.

Returns:

fileroot_noseg – File name root with no segment information.

Return type:

str

exotedrf.utils.get_interp_box(data, box_size, i, j, dimx)

Get median and standard deviation of a box centered on a specified pixel.

Parameters:

  • data (array-like[float]) – Data frame.

  • box_size (int) – Size of box to consider.

  • i (int) – X pixel.

  • j (int) – Y pixel.

  • dimx (int) – Size of x dimension.

Returns:

box_properties – Median and standard deviation of pixels in the box.

Return type:

array-like

exotedrf.utils.get_stellar_param_grid(st_teff, st_logg, st_met)

Given a set of stellar parameters, determine the neighbouring grid points based on the PHOENIX grid steps.

Parameters:

  • st_teff (float) – Stellar effective temperature.

  • st_logg (float) – Stellar log surface gravity.

  • st_met (float) – Stellar metallicity as [Fe/H].

Returns:

  • teffs (list[float]) – Effective temperature grid bounds.

  • loggs (list[float]) – Surface gravity grid bounds.

  • mets (list[float]) – Metallicity grid bounds.

exotedrf.utils.get_trace_centroids(deepframe, tracetable, subarray, save_results=True, save_filename='')

Get the trace centroids for all three orders via the edgetrigger method.

Parameters:

  • deepframe (array-like[float]) – Median stack.

  • tracetable (str) – Path to SpecTrace reference file.

  • subarray (str) – Subarray identifier.

  • save_results (bool) – If True, save results to file.

  • save_filename (str) – Filename of save file.

Returns:

  • cen_o1 (array-like[float]) – Order 1 X and Y centroids.

  • cen_o2 (array-like[float]) – Order 2 X and Y centroids.

  • cen_o3 (array-like[float]) – Order 3 X and Y centroids.

exotedrf.utils.get_wavebin_limits(wave)

Determine the upper and lower limits of wavelength bins centered on a given wavelength axis.

Parameters:

wave (array-like[float]) – Wavelengh array.

Returns:

  • bin_low (array-like[float]) – Lower edge of wavelength bin.

  • bin_up (array-like[float]) – Upper edge of wavelength bin.

exotedrf.utils.interpolate_stellar_model_grid(model_files, st_teff, st_logg, st_met)

Given a grid of stellar spectrum files, interpolate the model spectra to a set of stellar parameters.

Parameters:

  • model_files (list[str]) – List of paths to stellar spectra at grid points.

  • st_teff (float) – Stellar effective temperature.

  • st_logg (float) – Stellar log surface gravity.

  • st_met (float) – Stellar metallicity as [Fe/H].

Returns:

model_interp – Model stellar spectrum interpolated to the input paramaters.

Return type:

array-like(float)

exotedrf.utils.line_mle(x, y, e)

Analytical solution for Chi^2 of fitting a straight line to data. All inputs are assumed to be 3D (ints, dimy, dimx).

Parameters:

  • x (array-like[float]) – X-data. Median stack for 1/f correction.

  • y (array-like[float]) – Y-data. Data frames for 1/f correction.

  • e (array-like[float]) – Errors.

Returns:

  • m_e (np.array(float)) – “Slope” values for even numbered columns.

  • b_e (np.array(float)) – “Intercept” values for even numbered columns.

  • m_o (np.array(float)) – “Slope” values for odd numbered columns.

  • b_o (np.array(float)) – “Intercept” values for odd numbered columns.

exotedrf.utils.make_deepstack(cube)

Make deep stack of a TSO.

Parameters:

cube (array-like[float]) – Stack of all integrations in a TSO

Returns:

deepstack – Median of the input cube along the integration axis.

Return type:

array-like[float]

exotedrf.utils.open_filetype(datafile)

Open a datamodel whether it is a path, or the datamodel itself.

Parameters:

datafile (str, jwst.datamodel) – Datamodel or path to datamodel.

Returns:

data – Opened datamodel.

Return type:

jwst.datamodel

Raises:

ValueError – If the filetype passed is not str or jwst.datamodel.

exotedrf.utils.outlier_resistant_variance(data)

Calculate the varaince of some data along the 0th axis in an outlier resistant manner.

exotedrf.utils.parse_config(config_file)

Parse a yaml config file.

Parameters:

config_file (str) – Path to config file.

Returns:

config – Dictionary of config parameters.

Return type:

dict

exotedrf.utils.save_extracted_spectra(filename, wl1, wu1, f1, e1, wl2, wu2, f2, e2, t, header_dict=None, header_comments=None, save_results=True)

Pack stellar spectra into a fits file.

Parameters:

  • filename (str) – File to which to save results.

  • wl1 (array-like[float]) – Order 1 wavelength bin lower limits.

  • wu1 (array-like[float]) – Order 1 wavelength bin upper limits.

  • f1 (array-like[float]) – Order 1 flux.

  • e1 (array-like[float]) – Order 1 flux error.

  • wl2 (array-like[float]) – Order 2 wavelength bin lower limits.

  • wu2 (array-like[float]) – Order 2 wavelength bin upper limits.

  • f2 (array-like[float]) – Order 2 flux.

  • e2 (array-like[float]) – Order 2 flux error.

  • t (array-like[float]) – Time axis.

  • header_dict (dict) – Header keywords and values.

  • header_comments (dict) – Header comments.

  • save_results (bool) – If True, save results to file.

Returns:

param_dict – Lightcurve parameters packed into a dictionary.

Return type:

dict

exotedrf.utils.save_ld_priors(wave, c1, c2, order, target, m_h, teff, logg, outdir)

Write model limb darkening parameters to a file to be used as priors for light curve fitting.

Parameters:

  • wave (array-like[float]) – Wavelength axis.

  • c1 (array-like[float]) – c1 parameter for two-parameter limb darkening law.

  • c2 (array-like[float]) – c2 parameter for two-parameter limb darkening law.

  • order (int) – SOSS order.

  • target (str) – Name of the target.

  • m_h (float) – Host star metallicity.

  • teff (float) – Host star effective temperature.

  • logg (float) – Host star gravity.

  • outdir (str) – Directory to which to save file.

exotedrf.utils.sigma_clip_lightcurves(flux, thresh=5, window=5)

Sigma clip outliers in time from final lightcurves.

Parameters:

  • flux (array-like[float]) – Flux array.

  • thresh (int) – Sigma level to be clipped.

  • window (int) – Window function to calculate median. Must be odd.

Returns:

flux_clipped – Flux array with outliers

Return type:

array-like[float]

exotedrf.utils.sort_datamodels(datafiles)

Sort a list of jwst datamodels or filenames in chronological order by segment.

Parameters:

datafiles (array-like(str), array-like(datamodel)) – List of jwst datamodels or filenames.

Returns:

files_sorted – Inputs sorted in chronological order.

Return type:

np.array

exotedrf.utils.unpack_atoca_spectra(datafile, quantities=('WAVELENGTH', 'FLUX', 'FLUX_ERROR'))

Unpack useful quantities from extract1d outputs.

Parameters:

  • datafile (str, MultiSpecModel) – Extract1d output, or path to the file.

  • quantities (tuple(str)) – Quantities to unpack.

Returns:

all_spec – Dictionary containing unpacked quantities for each order.

Return type:

dict

exotedrf.utils.unpack_input_dir(indir, filetag='', exposure_type='CLEAR')
Get all segment files of a specified exposure type from an input data

directory.

Parameters:

  • indir (str) – Path to input directory.

  • filetag (str) – File name extension of files to unpack.

  • exposure_type (str) – Either ‘CLEAR’ or ‘F277W’; unpacks the corresponding exposure type.

Returns:

segments – File names of the requested exposure and file tag in chronological order.

Return type:

array-like[str]

exotedrf.utils.verify_path(path)

Verify that a given directory exists. If not, create it.

Parameters:

path (str) – Path to directory.