Below are the instructions to install Polpy and threeML. Everything is to be done inside the Python environment.

The process of installing Prerequisites varies with different operating systems.

1. If you are using a MacOSX-arm64 system, please follow:

1.1 Install miniconda3

First, we need to install miniconda Do this through:

mkdir -p ~/miniconda3
curl https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-arm64.sh -o ~/miniconda3/miniconda.sh
bash ~/miniconda3/miniconda.sh -b -u -p ~/miniconda3
rm ~/miniconda3/miniconda.sh

1.2 Conda Environment

Set up a Python virtual environment using conda (install Anaconda if you don't have it already). Do this through

conda create -n polpyenv python=3.9

Activate your conda environment

conda activate polpyenv

When you finish your analysis, you can exit the environment by

conda deactivate polpyenv

You can deactivate it through “conda deactivate”. Install pip inside conda:

conda install conda-forge::pip

1.3 Installing Necessary Packages

Install the necessary packages through the following commands:

conda install -c conda-forge numpy pandas matplotlib scipy
pip install --upgrade pip setuptools wheel
conda install -c conda-forge hdf5
pip install cmake
conda install -c conda-forge gfortran
conda install conda-forge::pygmo
conda install conda-forge::numba
conda install -c conda-forge pytables

2. If you are using a Linux or MacOSX-Intel system, please follow:

2.1 Use pyenv for a Virtual Environment

Creating a virtual environment allows you to install packages safely without interfering with the system Python.

You can use pyenv for this purpose (or virtualenvwrapper, instructions in this https://virtualenvwrapper.readthedocs.io/en/latest/).

You can install pyenv by executing this line in your terminal:

curl https://pyenv.run | bash

After installing the package, append the auto-loading lines printed on the terminal to ‘~/.bashrc’ or ‘~/.zshrc’, and source the files.

2.2 Establishing a Virtual Environment

We suggest fixing Python 3.9 for this work (to avoid deprecation of dependencies).

With pyenv, you can install Python 3.9 by:

pyenv install 3.9 
pyenv virtualenv 3.9 polpyenv 
pyenv activate polpyenv

Once you are done with all your analysis, you can deactivate the virtual environment with (don't do it now but when you finish your analysis):

pyenv deactivate

2.3 Installing Necessary Packages

Install the necessary packages through the following commands:

pip install --upgrade pip setuptools wheel
pip install numpy pandas matplotlib scipy
pip install pygmo
pip install numba

Once the prerequisites are satisfied, you can thereafter follow the steps below commonly for different systems.

Create a dedicated directory for the whole project/environment. Navigate to the folder containing the whole project:

mkdir workshop
cd workshop/

Thereafter, cone the GitHub repos through:

git clone https://github.com/sujaymate/astromodels
git clone --branch polpy_dev --single-branch https://github.com/sujaymate/threeML/
git clone https://github.com/JohannesBuchner/MultiNest/
git clone https://github.com/JohannesBuchner/PyMultiNest
git clone --branch patch-1 --single-branch https://github.com/hellohancheng/polpy/

Assuming you are in the “workshop” directory. Install the astromodels through:

cd astromodels/
pip install .
cd ../

Assuming you are in the “workshop” directory. Install the threeML through:

cd threeML/
pip install .
cd ../

Assuming you are in the “workshop” directory. Install the MultiNest through:

cd ../MultiNest/build/
cmake ../
make
sudo make install
cd ../..

Assuming you are in the “workshop” directory. Install the __ pyMultiNest__ through:

cd PyMultiNest
pip install .
cd ../

Assuming you are in the “workshop” directory. Install the __ polpy__ through:

cd polpy
pip install .
cd ../

Assuming you are in the “workshop/polpy” directory. You can run the example script through:

cd examples
python polar_GRB170114A.py

Thereafter, if your script running complained about the incompatibilities among Numpy, Astropy and other packages, you can downgrade your Numpy by doing this:

pip install numpy==1.26.4 --force-reinstall --no-cache-dir

Add the following lines to your .bash_profile file (or similar).

vim ~/.bash_profile

Inside add the following lines.

export OMP_NUM_THREADS=1
export MKL_NUM_THREADS=1
export NUMEXPR_NUM_THREADS=1

Save and exit the file. Then do:

source ~/.bash_profile