Fabry

Package for analyzing Fabry-Perot interference patterns

Usage

• Read in a Fabry-Perot image, locate the center of the ring pattern, and ring sum

from fabry.core import ringsum
from fabry.tools import images, plotting

filename = "<image_name>"
image_data = images.get_data(filename, color='b')  # r g b or None
xguess, yguess = plotting.center_plot(image_data)  # Prompt the user to click an initial guess for the center of the ring pattern
x0, y0 = ringsum.locate_center(image_data, xguess=xguess, yguess=yguess, binsize=0.1)  # Find the center from initial guess
r, signal, signal_uncertainty = ringsum.ringsum(image_data, x0, y0, binsize=0.1)

This is accomplished by the process_image.py script located in python_FabryPerot/bin. If the user not does provide --no_click flag, the user will be prompted to click an initial guess on the ring pattern as seen in the screenshot below.

After the user provides a guess of the center of the rings, the locate_center function will iteratively search for the center. An example of a found center is shown below.

After the center is found, a 'ringsum' is calculated where the image is split into annuli of equal area where means and standard deviations are calculated. An example figure plotted in pixel squared space is shown below.

Installation

Prerequisites

Preparing Python Distribution

Install the requirements listed in the requirements.txt file. I recommend using anaconda to do so to pick up on any not listed dependencies. However, PyMultiNest and RawPy require external non python libraries to be installed first.

• Anaconda has its own version of mpich that mpi4py is built with. I highly recommend that you uninstall mpi4py and install your own version of mpich or open-mpi. Afterwards, you will want to load them using module load mpich (or open-mpi). Then you can install mpi4py using pip. If you want to use MPI with PyMultiNest, it is critical you run module load before installation of MultiNest.

If you have Anaconda installed already, but would like to start with a clean working environment, you can run this

conda create -n test_env python=2.7
source activate test_env
conda install numpy h5py futures matplotlib scipy numba ipython
pip install exifread

If you have libraw install already you can install rawpy via pip

pip install rawpy # (if you already have libraw, see below if this fails)

If that step fails, see below for installing rawpy. If you have a version of MPI installed you can install mpi4py by running

module load path_to_mpi_you_want
pip install mpi4py

Installing PyMultiNest and MultiNest

• PyMultiNest can be installed via pip or via the github repository.

git clone https://github.com/JohannesBuchner/PyMultiNest/
cd PyMultiNest
python setup.py install

Use the "--user" switch if you want to install locally.

• PyMultiNest requires MultiNest to run. The simple instructions for building and installing are

git clone https://github.com/JohannesBuchner/MultiNest
cd MultiNest/build
cmake ..
make

More detailed instructions are located here. You will need to set the LD_LIBRARY_PATH environment variable to point to the install location of libmultinest.so.

Installing Rawpy if Pip Failed

• Rawpy requires libraw. If you looking for a specific version, it can be installed from the source repository.

git clone https://github.com/LibRaw/LibRaw.git libraw
git clone https://github.com/LibRaw/LibRaw-cmake.git libraw-cmake
cd libraw
git checkout 0.19.0
cp -R ../libraw-cmake/* .
cmake .
sudo make install

Afterwards rawpy can be installed using pip install rawpy --no-binary rawpy.

Install Fabry Package

• After the requirements have been satisfied, I recommend installing fabry as a developer because it is under active development still. This can be done by using

cd python_FabryPerot/
python setup.py develop

This will create a symlink for the fabry modules. Any change made will take immediate effect.