# DeepST

**Repository Path**: liweiowl/DeepST

## Basic Information

- **Project Name**: DeepST
- **Description**: Deep Learning for Spatio-Temporal Data
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 1
- **Created**: 2021-03-23
- **Last Updated**: 2022-12-23

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

DeepST
======
[DeepST](https://github.com/lucktroy/DeepST): A **Deep Learning** Toolbox for Spatio-Temporal Data

*Tested on `Windows Server 2012 R2`.*

## Installation

DeepST uses the following dependencies: 

* [Keras](https://keras.io/#installation) and its dependencies are required to use DeepST. 
* [Theano](http://deeplearning.net/software/theano/install.html#install) or [TensorFlow](https://github.com/tensorflow/tensorflow#download-and-setup), but **Theano** is recommended. 
* numpy and scipy
* HDF5 and [h5py](http://www.h5py.org/)
* [pandas](http://pandas.pydata.org/)
* CUDA 7.5 or latest version. And **cuDNN** is highly recommended. 

To install DeepST, `cd` to the **DeepST** folder and run the install command:

```
python setup.py install
```

To install the development version:

```
python setup.py develop
```

## Data path

The default `DATAPATH` variable is `DATAPATH=[path_to_DeepST]/data`. You may set your `DATAPATH` variable using

```
# Windows
set DATAPATH=[path_to_your_data]

# Linux
export DATAPATH=[path_to_your_data]
```

## License

DeepST is released under the MIT License (refer to the LICENSE file for details).