Installation

To install the TimeSeAD library, first clone the code to your local machine:

git clone https://github.com/wagner-d/TimeSeAD.git

Setup an environment

We recommend to set up a virtual python environment before installing TimeSeAD. The following instructions assume that you are using conda for this.

Install Miniconda if you do not have any conda installation on your system.
Open a terminal, cd into the project folder and create a new environment with
```
conda env create --file setup/conda_env_cpu.yaml
```
This will also install basic dependencies such as PyTorch. If you want to use TimeSeAD with NVIDIA GPU support, replace setup/conda_env_cpu.yaml with setup/conda_env_cuda.yaml (CUDA 10.2) or setup/conda_env_cuda111.yaml (CUDA 11.1).
Activate the environment with
```
conda activate TimeSeAD
```

Install the TimeSeAD library

We recommend installing the library in development mode so that you can make changes as you need them. This is easily achieved using pip:

pip install -e .

If you want to use the experiments as well, install the library as follows to include optional dependencies:

pip install -e .[experiments]

Now you can use the TimeSeAD library in your own projects by simply importing it

import timesead
# Or just import certain parts
from timesead.models.prediction import TCNPrediction