fiplcr 1.0

Relative FIP bias diagnostics using linear combinations of spectral lines

Relative FIP bias diagnostics using linear combinations of spectral lines

The fiplcr Python package allows to perform FIP bias maps measurements on the solar corona from UV intensity maps. It calculates an optimal linear combination of the spectral lines in order to obtain an accurate FIP bias map.
The proof of concept for this module is published in Zambrana Prado & Buchlin, 2019. In order to apply the Linear Combination Ratio (LCR) method one must follow 4 steps:

• Selection of the spectral lines
• Computation of the contribution functions
• Determination of the optimal linear combinations
• Determination of the relative FIP bias from the observations

The 1st step must be done on a case by case basis taking into account the lines available in your observation. We suggest you follow the criteria stated in Sec. 3.3.1 of Zambrana Prado & Buchlin, 2019.
The 2nd step is done by the specline module of the fiplcr module.
The 3rd step corresponds to the linear_combination module.
Finally the 4th step can be done using the fip_map function.

Do not forget to define all required variables in the config.py file in order to perform all calculations.

Installation

fiplcr uses ChiantiPy and the Chianti database. Before installing fiplcr, follow the ChiantiPy installation instructions. In particular, make sure to set the $XUVTOP environment variable in your .bashrc.

You can then install fiplcr by running the following commands in your terminal:

git clone https://git.ias.u-psud.fr/nzambran/fiplcr.git
pip install fiplcr/

(If you have limited permission, you can install it locally with pip install fiplcr/ --user.)

The fiplcr module is now installed on your system. You can safely remove the fiplcr/ repository that was created.

Quick start examples

Exploring linear combinations and comparing them to a simple 2-line ratio

In order to check if your linear combinations are suited for relative FIP bias determination, you can compare their performance to that of a simple two-line ratio.
This can be done following the same method presented in Sec. 4 of Zambrana Prado & Buchlin, 2019.

Using a DEM cube (stored in examples/em_example/em_example.npz) we will synthetize radiance maps for the selected spectral lines one wishes to test out. The test case consists in using uniform abundances to compute these radiance maps. The test is considered successful for a given FIP bias determination method if the output relative FIP bias mapis consistent with the input elemental abundance maps, both in uniformity and in value.

Putting yourself in the directory examples/em_example you can run the em_test.py file and you will retrieve two LinearComb objects:

• The variable ll, containing the lines you wish to test out with their corresponding synthetic radiance maps and the obtained relative FIP bias map.
• The variable ll_2_lines, containing the lines for the simple two-line ratio with their corresponding synthetic radiance maps and the obtained relative FIP bias map.

The test has four main steps, detailed below:

1. We derive a DEM cube from the AIA observation. This is for the sole purpose of producing synthetic radiances, for which we have control over all parameters,
   while the DEMs are representative of different real solar regions.
2. Using CHIANTI for the contribution functions and the derived DEMs, we calculate
   the synthetic radiances. We assume different uniform abundances for different elements.
3. We determine the optimal linear combination coefficients for the LCR method, and the coefficients for the two-line ratio method we are comparing it to.
4. We use these coefficients to retrieve the FIP bias in each pixel. If the selected lines are suitable for FIP bias determination, the retrieved FIP bias map should be uniform.

FULL DESCRIPTION OF EACH MODULE

Notes:

If you have trouble using matplotlib and ChiantiPy and you get this kind of error: "RuntimeError: LaTeX was not able to process the following string:" you will need to install an additional package by running

sudo apt install dvipng texlive-latex-extra texlive-fonts-recommended