![]() It deals well with unit conversions and can read and write a variety of different file types. It can also do model-grid based fitting and has an NH3 inversion fitter written at the moment. It can fit gaussian, lorentzian, and voigt profiles (built in). It fits profiles interactively or via “clever” guessing. Jordan Mirocha and I have been developing a python-based spectrosopic analysis toolkit. PAN was written such that the amount of typing done by the user is minimized. The initial parameter guesses (amplitude, position and width) can be specified visually with the mouse. The spectrum+fit, the residuals and the numerical results are displayed on-screen for each spectrum, meaning you can view and review the fit for each spectrum in a very visual manner.ģ. This is ideal for IFS data with potentially hundreds of spectra.Ģ. It has the ability to read in multiple spectra at once in an array format, and fit one initial guess to these spectra automatically. PAN is particularly useful for IFU/MOS data since:ġ. There is no limit to the number of functions to which you can fit simultaneously but more functions result in more computation time. PAN can be used to fit any of its in-built functions (straight line, Gaussian, Lorentzian, etc.) or you can create custom functions to fit your data (e.g. This is an IDL-based general-purpose curve-fitting utility with a graphical user interface, based on Craig Markwardt’s MPFIT. Just to add another alternative to the already fairly extensive list discussed above, I’ve been using PAN (Peak ANalysis). It mostly becomes bad if the data are marginally sampled and there are strong spikes (both emission and absorption) which cause interpolators to ring. Normally interpolation errors are not really as bad as people worry about. However, there is a plan to complete this this year (but you know how plans are).īTW, as George notes you can also use RSPECTEXT (or SINTERP) to fit the wavelength points by a WCS function and then interpolate the points to produce the image format where the pixels are flux and wavelengths are described by the function in the header. This work never was finished due to resources requiring me to move on to other things. Many years ago I did work to have IRAF spectral tools understand spectra in tables, which were starting to be more common. You could also dig through the help on “specwcs” for an example and discussion. Store the wavelength values in the image header as a lookup One of the parameters in this task should be set as “dtype=nonlinear”. This takes a text file with wavelength and flux pairs and produces the image format you mention. Getting this format is best done with RSPECTEXT. SPLOT, and all IRAF spectroscopy tasks for that matter, do support a sampled WCS (provided the number of points is not extremely large). Frank Valdes of the IRAF group responds to the query from Yang … ![]()
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