Deep learning toolbox for seismic waveform processing.
Project description
.. image:: https://github.com/lijunzh/yews/blob/master/logo/logo.gif
:scale: 50 %
:alt: Yews Logo
:align: center
Yews | Your Earthquake Waveform Solution
========================================
.. image:: https://travis-ci.com/lijunzh/yews.svg?branch=master
:target: https://travis-ci.com/lijunzh/yews
.. image:: https://ci.appveyor.com/api/projects/status/32r7s2skrgm9ubva?svg=true
:target: https://ci.appveyor.com/project/lijunzh/yews
.. image:: https://codecov.io/gh/lijunzh/yews/branch/master/graph/badge.svg
:target: https://codecov.io/gh/lijunzh/yews
.. image:: https://anaconda.org/lijunzhu/yews/badges/version.svg
:target: https://anaconda.org/lijunzhu/yews
.. image:: https://badge.fury.io/py/yews.svg
:target: https://badge.fury.io/py/yews
.. image:: https://pepy.tech/badge/yews
:target: https://pepy.tech/project/yews
Yews is a deep learning toolbox for processing seismic waveform made with flexibility, speed, and usability in mind. It is built upon `PyTorch <https://github.com/pytorch/pytorch>`_ for researchers interested in applying deep learning techniques on seismic waveform data.
Installation
============
It is recommened to first install `PyTorch <https://github.com/pytorch/pytorch>`_ using the offical guide: https://pytorch.org/get-started/locally/ . Then, install `Yews <https://github.com/lijunzh/yews>`_ via one of the following approaches:
conda:
.. code:: bash
conda install -c lijunzhu -c pytorch yews
pip:
.. code:: bash
pip install yews
From source:
.. code:: bash
python setup.py install
Note:
1. These assume that you have PyTorch installed via the default method.
2. If, however, yews is installed without going through the official PyTorch installation, it will still be installed properly using the pip method
3. The lateset PyTorch 1.0.1 has been manually uploaded to lijunzhu channel on anaconda cloud, which makes it possible to install PyTorch automatically as a dependency using the conda method. However, it does not support older PyTorch versions for now. Future updates of PyTorch will be added ASAP.
4. Yews can be installed via *conda-forge* with all dependencies handled automatically; however, it only supports the **CPU** version as *PyTorch* does not have a **GPU** version for the conda-forge channel.
Documentation
=============
You can find the API documentation on the yews website: https://www.yews.info
Contributing
============
We appreciate all contributions. If you are planning to contribute back bug-fixes, please do so without any further discussion. If you plan to contribute new features, utility functions or extensions, please first open an issue and discuss the feature with us.
:scale: 50 %
:alt: Yews Logo
:align: center
Yews | Your Earthquake Waveform Solution
========================================
.. image:: https://travis-ci.com/lijunzh/yews.svg?branch=master
:target: https://travis-ci.com/lijunzh/yews
.. image:: https://ci.appveyor.com/api/projects/status/32r7s2skrgm9ubva?svg=true
:target: https://ci.appveyor.com/project/lijunzh/yews
.. image:: https://codecov.io/gh/lijunzh/yews/branch/master/graph/badge.svg
:target: https://codecov.io/gh/lijunzh/yews
.. image:: https://anaconda.org/lijunzhu/yews/badges/version.svg
:target: https://anaconda.org/lijunzhu/yews
.. image:: https://badge.fury.io/py/yews.svg
:target: https://badge.fury.io/py/yews
.. image:: https://pepy.tech/badge/yews
:target: https://pepy.tech/project/yews
Yews is a deep learning toolbox for processing seismic waveform made with flexibility, speed, and usability in mind. It is built upon `PyTorch <https://github.com/pytorch/pytorch>`_ for researchers interested in applying deep learning techniques on seismic waveform data.
Installation
============
It is recommened to first install `PyTorch <https://github.com/pytorch/pytorch>`_ using the offical guide: https://pytorch.org/get-started/locally/ . Then, install `Yews <https://github.com/lijunzh/yews>`_ via one of the following approaches:
conda:
.. code:: bash
conda install -c lijunzhu -c pytorch yews
pip:
.. code:: bash
pip install yews
From source:
.. code:: bash
python setup.py install
Note:
1. These assume that you have PyTorch installed via the default method.
2. If, however, yews is installed without going through the official PyTorch installation, it will still be installed properly using the pip method
3. The lateset PyTorch 1.0.1 has been manually uploaded to lijunzhu channel on anaconda cloud, which makes it possible to install PyTorch automatically as a dependency using the conda method. However, it does not support older PyTorch versions for now. Future updates of PyTorch will be added ASAP.
4. Yews can be installed via *conda-forge* with all dependencies handled automatically; however, it only supports the **CPU** version as *PyTorch* does not have a **GPU** version for the conda-forge channel.
Documentation
=============
You can find the API documentation on the yews website: https://www.yews.info
Contributing
============
We appreciate all contributions. If you are planning to contribute back bug-fixes, please do so without any further discussion. If you plan to contribute new features, utility functions or extensions, please first open an issue and discuss the feature with us.
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
yews-0.0.2.tar.gz
(14.8 kB
view details)
Built Distribution
yews-0.0.2-py2.py3-none-any.whl
(17.6 kB
view details)
File details
Details for the file yews-0.0.2.tar.gz
.
File metadata
- Download URL: yews-0.0.2.tar.gz
- Upload date:
- Size: 14.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/41.0.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.7.3
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 6aed5ea0ae8fff60a07a22b7e34909c0cbe90128a2e466d2ab1aa5c741425635 |
|
MD5 | d7e5bd997318e4a4149a1a90f8bd9a73 |
|
BLAKE2b-256 | 52586ee6fed171ae49159974cf4206d98209317960616a8f39bc0814d11f2cd3 |
File details
Details for the file yews-0.0.2-py2.py3-none-any.whl
.
File metadata
- Download URL: yews-0.0.2-py2.py3-none-any.whl
- Upload date:
- Size: 17.6 kB
- Tags: Python 2, Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/41.0.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.7.3
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | b71fc1e101972c58fd3e34cd8f0a0eb02977e33f2582f25a8334a70eb32ac180 |
|
MD5 | 9c13863d16311a7e11a7ec5df1a6566c |
|
BLAKE2b-256 | 65cc87aece5a4a8a8c93b0ae11dba26def7f88c5d43a97db64b2427374a841b7 |