LEPHARE photometric redshift estimator
Project description
lephare
IMPORTANT! This project is in an early development stage. If you wish to use and run LePHARE please download it from the official repository.
LePHARE (PHotometric Analysis for Redshift Estimation) is a Python package built on a complete rewrite in C++ of the Fortran code LePhare. LePHARE computes photometric redshifts and physical parameters by fitting spectral energy distributions (SED) to a dataset of photometric fluxes or apparent magnitudes.
Installation
The simplest way to install lephare is using pip:
pip install lephare
If you have any problems using pip install please consider creating an issue and informing us what system you are using in order to help us improve robustness.
Example usage
We provide a number of Jupyter notebooks demonstrating various aspects of the Python code.
Dev Guide - Getting Started
Before installing any dependencies or writing code, it's a great idea to create a
virtual environment. LINCC-Frameworks engineers primarily use conda
to manage virtual
environments. If you have conda installed locally, you can run the following to
create and activate a new environment.
>> conda create -n <env_name> python=3.10
>> conda activate <env_name>
Once you have created a new environment, you can install this project for local development using the following commands:
>> git submodule update --init --recursive
>> conda install -c conda-forge cxx-compiler
>> pip install -e .'[dev]'
>> pre-commit install
>> conda install pandoc
Notes:
- The single quotes around
'[dev]'
may not be required for your operating system. pre-commit install
will initialize pre-commit for this local repository, so that a set of tests will be run prior to completing a local commit. For more information, see the Python Project Template documentation on pre-commit- Install
pandoc
allows you to verify that automatic rendering of Jupyter notebooks into documentation for ReadTheDocs works as expected. For more information, see the Python Project Template documentation on Sphinx and Python Notebooks
This project was automatically generated using the LINCC-Frameworks python-project-template. For more information about the project template see the documentation.
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