Spectra Comparator

The programs listed bellow aim to analyze and characterize the Photron Lamp spectrum and compare it with the Westinghouse Lamp, both are Thorium-Argon lamps. Lamps specifications can be found here.

The IRAF procedures used can be found here

This project was done under grant #2020/14944-4, São Paulo Research Foundation (FAPESP) and the monograph with all the results are available here.

plot_norms.py

File
Program to plot the spectra before and after the normalization. Search for two types of file names:

• tha_ for non-normalized spectrum and;
• norm_tha_ for normalized spectrum.

And the rest of the name needs to be the wavalength information.
Obs: part of the name string will be used to write the plot name.

Example:

specplot.py

File
Program to visually verify the calibration. For N spectra, N-1 plots will be generated, each with two spectra to compare the alignment of the emission lines.

Example:

calib.py

File
Comparison between a file named "thar.fits" (reference file) and any other .fits spectra with the string tha_ in part of the name of the file.

This program shows a interactive window created with Python3 that uses matplotlib to enable interact with the spectra while running the script. The plot created can also be saved.

It has options to divide the spectra from 1 to 10 on horizontal axis. If the x axis is the same unit on both spetras it can also share the same limits on the axis to enable a better comparison.

If the x axis is in Angstrons, the program has an option to show the wavelength of the peaks.

Interface example:

rms_compar.py

File
A simple program to plot the RMS values of the calibration obtained with IRAF. This program read a .csv file as the following example:

Wavelength(A),	RMS_Old,	RMS_New
3240,		0.09712,	0.01160
3330,		0.04782,	0.00935
3415,		0.01131,	0.00855

Where each line is a spectrum file calibrated in the Westinghouse (old) and the Photron (new) lamp.

The execution of the program generate a table saved in LaTeX (.tex) format and an example can be found here. It also create an image as follows:

divide_spectra.py

File
Plot the Westinghouse and Photron spectra, followed by the division of them (created in IRAF).

Disabled: The execution of the program accepts (optional) one argument to plot the figure sharing the y-axis for all the subplots. The execution is like the following one:

python3 divide_spectra.py sharey

Example:

analyse_spectra.py

File
This program create a database in .csv with the best matches of a provided linelist (known wavelengths of eletronic transitions for an element). It also implements an error check based on the difference of the emission line center wavelength and the wavalength of the transition, saving the result if it's more or less than the error.

This database are also saved in .tex form and two images are generated. One with the entire spectrum and another with the spectrum cutted in three parts. The image files are saved in .pdf for better visualization.

The programs also accept linelists created with the NIST website

Example of part of a spectrum analyzed:

resolution_degradation.py

File
Degradate a spectrum to the desired resolution using convolution. The program saves the original spectrum and the new one in .csv form to future read it with the R program.

The program fits a gaussian in each emission line of the spectrum to find the resolution. The figure bellow exemplifies the fit:

spectrum_analysis.r

File
This program analyze two files os the same spectrum but with different resolutions.
Te program results are listed bellow:

1. A superposed image of the two spectra;
2. A fit of a gaussian using the Levenberg-Marquardt algorithm for each emission line;
3. A correlation between the standard deviation and the wavelength for both spectra;
4. A histogram of the standard deviation of the peaks of both spectra;
5. An analyzes of the change of emission lines center position between the spectra;
6. The lines with blend in the new spectrum;
7. A fit of an exponential function of the blended lines and the intensity observed.