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kerberizer committed May 16, 2024
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# ramanchada2

[![build](https://github.com/h2020charisma/ramanchada2/workflows/build/badge.svg)](https://github.com/h2020charisma/ramanchada2/actions/workflows/build.yml)
[![CI](https://github.com/h2020charisma/ramanchada2/workflows/CI/badge.svg)](https://github.com/h2020charisma/ramanchada2/actions/workflows/ci.yml)
[![docs](https://github.com/h2020charisma/ramanchada2/workflows/docs/badge.svg)](https://h2020charisma.github.io/ramanchada2/index.html)

Harmonising Raman spectroscopy: meant to fill the gap between the theoretical Raman analysis and the experimental Raman spectroscopy by providing means to compare data of different origin.
ramanchada2 is a Python library for Raman spectroscopy harmonization. It is meant to fill the gap between the theoretical Raman analysis and the experimental Raman spectroscopy by providing means to compare data of different origin.

## Quick start

```sh
pip install ramanchada2
```

- 📖 [Documentation](https://h2020charisma.github.io/ramanchada2/ramanchada2.html)
- ⚗️ [Examples](https://github.com/h2020charisma/ramanchada2/tree/main/examples)

## Quick start with Jupyter notebook examples

## Quick start
[Install Poetry](https://python-poetry.org/docs/#installation).

Clone the repo using https
```bash
```sh
git clone https://github.com/h2020charisma/ramanchada2.git
```
or by using ssh
```
git clone [email protected]:h2020charisma/ramanchada2.git
cd ramanchada2
poetry install --with=jupyter
poetry run jupyter notebook examples
```

The browser should open Jupyter automatically.

and go inside
```bash
cd ramanchada2 # make sure you are in ramanchada2 directory
```
## Development

Make sure you have virtualenv module and create a virtual environment
```bash
virtualenv .venv # create virtual environment
This project uses [Poetry](https://python-poetry.org/) for dependency management. Make sure to [have it installed](https://python-poetry.org/docs/#installation). Also, using [pyenv](https://github.com/pyenv/pyenv) on UNIX/MacOS or [pyenv-win](https://github.com/pyenv-win/pyenv-win) for Windows is recommended for Python version management (the default Python version for this project is set in the `.python-version` file).

# activate the virtual environment
source .venv/bin/activate # on linux
.venv\Scripts\activate # on windows
```
For better Visual Studio Code integration it may be helpful to set `poetry config virtualenvs.in-project true`.

Ramanchada package and all dependencies can be installed by runing:
### Setting up

```bash
pip install -r requirements-dev.txt # install development environment
hash -r # make sure the newly created environment is in use
```sh
git clone https://github.com/h2020charisma/ramanchada2.git
cd ramanchada2
poetry install
```

In order to create a jupyter kernel, from the already activated virtual environment execute following command:
### Basic usage

```bash
ipython kernel install --name=ramanchada2 --user # set up a new jupyter kernel
```

The kernel can be removed by:
```bash
jupyter kernelspec remove ramanchada2
poetry shell
python
>>> import ramanchada2
```

A jupyter server can be started from anywhere -- no need to activate the virtual environment:
```bash
jupyter-notebook
### Running the linters & tests

Everything:
```
or
```bash
jupyter-lab
poetry run tox
```

A web browser with jupyter should start automaticaly.

Linter only:
```
poetry run tox -e flake8
```

## Quick start with Conda
### Playing with the Jupyter notebooks

[Install Miniconda](https://conda.io/projects/conda/en/latest/user-guide/install/index.html) and, optionally, Mamba:
```
conda install mamba -n base -c conda-forge
poetry install --with=jupyter
```

Run the following. If you haven't installed Mamba, replace `mamba` with `conda`.
then
```
poetry run jupyter notebook examples
```
or
```
poetry run jupyter lab examples
```
or
```
mamba env update -f environment.yml
conda activate ramanchada2
jupyter notebook
poetry shell
```
---
and running `jupyter notebook` or `jupyter lab` from there.

## Acknowledgements

🇪🇺 This project has received funding from the European Union’s Horizon 2020 research and innovation program under [grant agreement No. 952921](https://cordis.europa.eu/project/id/952921).
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# ramanchada2

ramanchada2 is meant to fill the gap between the theoretical Raman analysis and the experimental Raman spectroscopy by providing means to compare data of different origin.
ramanchada2 is a Python library for Raman spectroscopy harmonization. It is meant to fill the gap between the theoretical Raman analysis and the experimental Raman spectroscopy by providing means to compare data of different origin.

For more information, see:
* https://github.com/h2020charisma/ramanchada2
* https://h2020charisma.github.io/ramanchada2/ramanchada2.html
* https://github.com/h2020charisma/ramanchada2/tree/main/examples

---
🇪🇺 This project has received funding from the European Union’s Horizon 2020 research and innovation program under [grant agreement No. 952921](https://cordis.europa.eu/project/id/952921).
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