Metadata-Version: 2.1
Name: nais
Version: 1.2.1
Summary: NORSAR AI System.
Home-page: https://github.com/NorwegianSeismicArray/nais
Download-URL: https://github.com/NorwegianSeismicArray/nais/archive/refs/tags/1.0.tar.gz
Author: Erik B. Myklebust & Tord S. Stangeland
Author-email: tord@norsar.no
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: tensorflow
Requires-Dist: keras-tuner
Requires-Dist: scikit-learn
Requires-Dist: pandas
Requires-Dist: tqdm
Requires-Dist: pillow

### [Documentation](https://norwegianseismicarray.github.io/nais/nais)

### NORSAR Artificial Inteligence System (NAIS, yes, the acronym was chosen first)

This repository will eventually contain tools specific to aiding in AI research at NORSAR.

This repository is based on Tensorflow and Keras. 

This repository will contain: 
* Baseline models, for waveforms and spectrograms. Possibly pretrained for certain tasks.
* Standard datasets to test models. Development of new models can be difficult. Standard datasets eliminates errors in the data and lets you focus on developing the model. 
  * Classification
  * Regression
  * Masking (eg. arrival picking)
* Augmentation methods.

## Installation
``pip install nais``

If an error occurs when importing `nais`, likely ``sndfile`` library is not installed (check the error), and needs to be:

``apt-get install libsndfile1-dev``

# Quick example

```python
import numpy as np
from nais.Models import AlexNet1D

X = np.random.normal(size=(16,256,3)) #16 examples of three channel data.
y = np.random.randint(0,1,size=(16,)) #Labels

model = AlexNet1D(num_outputs=1) #binary 
model.compile('adam','binary_crossentropy')
model.fit(X,y)
```
