CASCADe-jitter: Calibration of trAnsit Spectroscopy using CAusal Data jitter detection module.
Project description
CASCADe-jitter
This package is a sub package of the CASCADe package, developed within the EC Horizons 2020 project Exoplanets A . This package contains all functionality to detect and correct pointing jitter in spectroscopic transit observations.
Installing CASCADe-jitter
The easiest way to install the CASCADe-jitter package is to create an Anaconda environment, download the distribution from PyPi, and install the package in the designated Anaconda environment with the following commands:
conda create --name CASCADe-jitter python=3.9 ipython
conda activate CASCADe-jitter
pip install CASCADe-jitter
This will install all code and scripts you need for the package to work. For updating an existing installation to the latest release, simply use the -U flag with pip:
conda activate CASCADe-jitter
pip install CASCADe-jitter -U
Installing the CASCADe-jitter examples
The CASCADe-jitter package comes with several examples, demonstrating how to find and deterine the position of sources in and to detect pointing jitter in spectroscopic image cubes. If the package is installed from PypPi, the example jupyter notebooks and simulated data need be downloaded from the GitLab repository. To initialize the data download one can use the following bash command in the Anaconda environment:
setup_cascade-jitter.py
or alternatively from within the python interpreter:
from cascade_jitter.initialize import setup_examples
setup_examples()
The additional downloaded data also includes examples and observational data to try out the CASCADe-jitter package, which are explained below.
NOTE: The data files will be downloaded by default to a
CASCADeSTORAGE/
directory in the users home directory. If a different location is preferred, please read the section on how to set the CASCADeCASCADE_STORAGE_PATH
environment variable first. For details in the environment variables we refer to the documentation of the CASCADe main package.
Installing alternatives for the CASCADe-jitter package
The CASCADe-jitter code can also be downloaded from GitLab directly by either using git or pip. To download and install with a single command using pip, type in a terminal the following command
pip install git+git://gitlab.com/jbouwman/CASCADe-jitter.git@main
which will download the latest version. For other releases replace the main
branch with one of the available releases on GitLab. Alternatively, one can first
clone the repository and then install, either using the HTTPS protocol:
git clone https://gitlab.com/jbouwman/CASCADe-jitter.git
or clone using SSH:
git clone git@gitlab.com:jbouwman/CASCADe-jitter.git
Both commands will download a copy of the files in a folder named after the project's name. You can then navigate to the directory and start working on it locally. After accessing the root folder in a terminal, type
pip install .
to install the package.
In case one is installing CASCADe-jitter directly from GitLab, and one is using Anaconda, make sure a cascade environment is created and activated before using our package. For convenience, in the CASCADe-jitter main package directory an environment.yml can be found. You can use this yml file to create or update the cascade Anaconda environment. If you not already had created an cascade environment execute the following command:
conda env create -f environment.yml
In case you already have an cascade environment, you can update the necessary packages with the following command (also use this after updating CASCADe-jitter itself):
conda env update -f environment.yml
Make sure the CASCADe-jitter - package is
in your path. You can either set a PYTHONPATH
environment variable pointing to
the location of the CASCADe -filtering package
on your system, or when using anaconda with the following command:
conda develop <path_to_the_CASCADe_package_on_your_system>/CASCADe-jitter
Using CASCADe-jitter
The CASCADe-jitter distribution comes with several working examples and test data sets which can be found in the examples directory of the CASCADe-jitter distribution on GitLab, or have been installed locally with the commands outlined above. The example jupyter notebooks explain and demonstrate the basic usage of the filtering modules, and use simulated JWST/MIRI low resolution spectroscopic data as an example how to identify and remove cosmic hits. To run the examples make sure that the conda CASCADe-jitter environment can be found by the jupyter server. This can be achieved with the following command:
python -m ipykernel install --user --name=CASCADe-jitter
after which the notebooks can be viewed and executed with jupyter which can be started with.
jupyter notebook
Documentation
The full documentation can be found online at:
https://jbouwman.gitlab.io/CASCADe-jitter/
Alternatively, the documentation can be found in the docs
directory of the
CASCADe-jitter GitLab repository.
After cloning the git repository, the full documentation can be generated
by executing in the in the docs
directory the following commands:
make html
make latexpdf
The generated HTML and PDF files will be located in the build/html
and
build/latex
sub-directories of the main documentation directory, respectively.
Documentation on the CASCADe main package can be found at:
https://jbouwman.gitlab.io/CASCADe/
Acknowledgments
The CASCADe-jitter code was developed by Jeroen Bouwman, with contributions from the following collaborators:
Juergen Schreiber (MPIA)
This work was supported by the European Unions Horizon 2020 Research and Innovation Programme, under Grant Agreement N 776403.
Publications
https://ui.adsabs.harvard.edu/abs/2021AJ....161..284M/abstract
https://ui.adsabs.harvard.edu/abs/2021A%26A...646A.168C/abstract
https://ui.adsabs.harvard.edu/abs/2020ASPC..527..179L/abstract
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