Metadata-Version: 2.4
Name: zizou
Version: 0.1.8
Summary: Python package to detect anomalies in geoscience time series data
Project-URL: Homepage, https://tsc-tools.github.io/zizou/
Project-URL: Issues, https://github.com/tsc-tools/zizou/issues
Author-email: Yannik Behr <y.behr@gns.cri.nz>, Christof Mueller <c.mueller@gns.cri.nz>
License: GPL v3
License-File: LICENSE
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Python: <3.14,>=3.10
Requires-Dist: boto3
Requires-Dist: numpy
Requires-Dist: obspy
Requires-Dist: pandas
Requires-Dist: pyyaml
Requires-Dist: scipy
Requires-Dist: tonik
Requires-Dist: tqdm
Requires-Dist: xarray[io]
Provides-Extra: dev
Requires-Dist: build; extra == 'dev'
Requires-Dist: mkdocs; extra == 'dev'
Requires-Dist: mkdocs-jupyter; extra == 'dev'
Requires-Dist: mkdocstrings[python]; extra == 'dev'
Requires-Dist: pytest; extra == 'dev'
Requires-Dist: twine; extra == 'dev'
Provides-Extra: ml
Requires-Dist: scikit-fuzzy; extra == 'ml'
Requires-Dist: scikit-learn; extra == 'ml'
Requires-Dist: torch; extra == 'ml'
Requires-Dist: torchaudio; extra == 'ml'
Requires-Dist: torchvision; extra == 'ml'
Description-Content-Type: text/markdown

# Zizou: time-series classification tools for Geoscience

Zizou is a package to provide common tools for time-series classification in Geoscience. For example,
it allows you to download seismic data from an S3 bucket or an FDSN server, compute spectrograms, and then
use an Autoencoder to detect anomalies in the spectrograms.

## Requirements
* xarray
* boto3
* pandas
* numpy
* scipy
* obspy
* tqdm
* xarray
* pyyaml
* tonik

Using the machine learning modules requires the following additional packages:
* scikit-learn
* pytorch 

## Installation
To only compute features run:

```
pip install -U zizou
```

To also use the machine learning modules run:

```
pip install -U "zizou[ML]"
```

### Installation from source
#### Setup conda environment

```
cd zizou 
conda env create -f environment.yml
```

#### Install package in new environment
```
conda activate zizou 
cd zizou 
pip install -e .
```

## Run tests

To run only the quick tests:
```
cd zizou 
pytest
```
To run the whole test suite:
```
cd zizou 
pytest --runslow
```

## Setup Jupyter notebook kernel:

```
conda activate zizou 
python -m ipykernel install --user --name zizou 
kernda -o -y /path/to/jupyter/kernels/zizou/kernel.json
```

To find the path of your kernel.json file you can run:
```
jupyter --paths
```