sed-processor 0.1.1

Single Event Data Frame Processor: Backend to handle photoelectron resolved datastreams

sed

Single Event Data Frame Processor: Backend to handle photoelectron resolved datastreams

Installation

Conda approach

Clone this repository and cd to its root folder. Create a new environment by typing:

conda env create -f env.yml

This should install all the requirements to run sed in your environment. To activate your environment:

conda activate sed_conda

If you intend to work with jupyter notebooks, it is helpfull to install a jupyter kernel of your environment. This can be done, once activating your environment, by typing:

python -m ipykernel install --user --name=sed_conda

Poetry approach (better, but more complex)

• Prerequisites:

  • poetry: https://python-poetry.org/docs/
  • pyenv: https://github.com/pyenv/pyenv

• Clone this repository and check the python version within the [tool.poetry.dependencies] section of the pyproject.toml file

  • If your system is using a different Python version, use pyenv to create and activate a Python version compatible with the specifications from the pyproject.toml. See pyenv basic usage

• Create a virtual environment by typing:

poetry shell

• A new shell will be spawn with the new environment activated

• Install the dependencies from the pyproject.toml by typing:

poetry install

• If you wish to use the virtual environment created by poetry to work in a Jupyter notebook, you first need to install the optional notebook dependencies and then create a Jupyter kernel for that.
  • Install the optional dependencies ipykernel and jupyter

  poetry install -E notebook
  

  • Make sure to run the command below within your virtual environment ('poetry run' ensures this) by typing:

  poetry run ipython kernel install --user --name=sed_poetry
  

  • The new kernel will be eligible now from your kernels list in Jupyter