extract integrated spectra
fit the sinc emission lines
recalibrate your data in wavelength, astrometry and flux
choose between a Bayesian or a classical fitting algorithm
and much more ...
warning ORCS is always in fast development. You might see bugs or strange behaviours ! You might also want desperatly to have new features. In all cases please send an email: email@example.com
You can find the up-to-date documentation here: https://orcs.readthedocs.io/
Examples in Jupyter notebook format can be found in the documentation:
First basic examples
These examples show the basic usage of ORCS
- Example of a single spectrum fit
- How precise must be the input velocity parameter ?
- Extract the deep frame and use the WCS
- Make a fit over an entire region of the field
- Differences between fitting a sincgauss model and two sinc lines
Bayesian fitting vs. classical fitting
Here are more advanced examples that show step-by-step the differences between a classical fit and a Bayesian fit on a model spectrum. You will thus first learn how to model a spectrum and then fit a model spectrum with one line, two resolved lines and two unresolved lines: this is when the bayesian fitting algorithm becomes intersting ;)
- Modelling and fitting a single line spectrum
- Modelling and fitting a spectrum with two resolved lines
- Modelling and fitting two unresolved emission lines with a bayesian approach
Calibrating your data
A data cube can be recalibrated using mode specific algorithm which depends on the type of data you have observed. You might want to give a try to these examples to see if you can get a better calibration for your data.
- Wavelength recalibration with the sky lines (Mendel OH bands)
- Image registration
- Flux Calibration Example Using HST image
- Use calibration outputs
These examples show advanced fitting procedures.
Martin, Drissen, Melchior (2017). A SITELLE view of M31's central region - I: Calibrations and radial velocity catalogue of nearly 800 emission-line point-like sources. MNRAS (accepted) http://adsabs.harvard.edu/abs/2017arXiv170701366M
Martin, Drissen (2017). SITELLE's level-1 calibration. MNRAS (submitted) http://adsabs.harvard.edu/abs/2017arXiv170603230M
Martin, Prunet, Drissen (2016). Optimal fitting of Gaussian-apodized or under-resolved emission lines in Fourier transform spectra providing new insights on the velocity structure of NGC 6720. MNRAS http://adsabs.harvard.edu/abs/2016MNRAS.463.4223M
Martin, Drissen, Joncas (2015). ORBS, ORCS, OACS, a Software Suite for Data Reduction and Analysis of the Hyperspectral Imagers SITELLE and SpIOMM. PASP http://adsabs.harvard.edu/abs/2015ASPC..495..327M
Follow the installation instructions here
2. add orcs module
mkdir orcs-stable # do it where you want to put orcs files cd orcs-stable git clone https://github.com/thomasorb/orcs.git
in the downloaded folder
conda activate orb # you don't need to do it if you are already in the orb environment cd path/to/orcs-stable/orcs python setup.py install
conda activate orb # you don't need to do it if you are already in the orb environment python -c 'import orcs.process'