# Process module¶

ORCS (Outils de Réduction de Cubes Spectraux) provides tools to extract data from ORBS spectral cubes.

This module contains the processing classes

class orcs.process.SpectralCube(cube_path, debug=False, **kwargs)

ORCS spectral cube fitting class.

Note

parent class HDFCube is the ORCS implementation of HDFCube.

_get_calibration_laser_map_path()

Return path to the calibration map computed when fitting sky lines. Can be used instead of the original calibration map.

_get_deep_frame_wcs_path()

Return path to the generated deep frame with the reocmputed WCS.

_get_detection_frame_path()

Return path to the detection frame

_get_detection_pos_frame_path()

Return path to the detection position frame

_get_dxmap_path()

Return path to the generated X micro-shifting map.

_get_dymap_path()

Return path to the generated Y micro-shifting map.

_get_skymap_file_path()

Return path to the sky map file containing the results of the fit.

_get_skymap_fits_path()

Return path to the sky map file containing the interpolated sky velocity map.

_get_temp_reg_path()

Return path to a temporary region file

_get_wavefront_map_path()

Return path to the wavefront map computed when fitting the calibration laser map with a different calibration laser wavelength. Can be used instead of the original wavefront map during a reduction

detect_sources(fast=True)

Detect emission line sources in the spectral cube

Parameters: fast – (Optional) Fast detection algorithm (with FFT convolution). Borders of the frame are wrong but process is much faster (default True).
integrate(filter_function, xmin=None, xmax=None, ymin=None, ymax=None)

Integrate a cube under a filter function and generate an image

I = \int F(\sigma)S(\sigma) ext{d}\sigma

with I, the image, S the spectral cube, F the filter function.

Parameters: filter_function – Must be an orcs.core.Filter instance xmin – (Optional) lower boundary of the ROI along x axis (default None, i.e. min) xmax – (Optional) lower boundary of the ROI along y axis (default None, i.e. min) ymin – (Optional) upper boundary of the ROI along x axis (default None, i.e. max) ymax – (Optional) upper boundary of the ROI along y axis (default None, i.e. max)
map_sky_velocity(mean_sky_vel, div_nb=20, plot=True, x_range=None, y_range=None, exclude_reg_file_path=None, no_fit=False, threshold=None, sky_lines=None)

Map the sky velocity on a rectangular grid and interpolate it to return a map of the velocity zero point that can be subtracted to the returned velocity map of the cube fit.

Parameters: mean_sky_vel – (Optional) Mean sky velocity (in km/s). div_nb – (Optional) Number of division on one axis of the rectangular grid. The total number of points is div_nb^2 (default 15). plot – (Optional) If True, output plots are shown (default True). x_range – (Optional) Range of pixels along the X axis where the velocity is measured (default None). y_range – (Optional) Range of pixels along the Y axis where the velocity is measured (default None). exclude_reg_file_path – (Optional) Region to exclude from the computation (must be a ds9 reg file) no_fit – (Optional) Do not repeat the fitting process. Only recompute the velocity map model. threshold – (Optional) If not None, this threshold on the velocity uncertainty is used in place of an automatic threshold.
register(distortion_map_path=None)

Make a new registration of the cube.

Parameters: distortion_map – A path to a FITS image containing an SIP distortion model. It can be a registered image of a calibration field containing a lot of stars and taken during the same run as the science cube.