kth

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kth contains some packages we build at KTH, Royal Institute of Technology, Sweden for multiple purpose tasks. We will constantly update sub-packages contained in it.

1. canteraKTH: collections for flame calculations.

2. keyfi: collections for dimensional reduction task and combustion visualization - also see keyfi

3. NN: collections for building all kinds of neural network.

4. POD: snapshot POD including pre- and post-processing tools. (contact author if compilation fails because environment.yml is not updated yet.)

Author

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Kai Zhang, KTH, Royal Institute of Technology, Sweden - Google Scholar

Email: [email protected]; [email protected];

Installation

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These instructions will get you a copy of the project up and running on your local machine for usage, development and testing purposes. Please note that only Linux environments have been tested in the current implementation but the code should work independently of the OS.

Open a terminal window and clone this repository by writing:

git clone https://github.com/WWIIWWIIWW/kth

In order to use kth several Python 3 packages are required. Creating a brand new Conda environment for is recommended. This can be done easily with the provided environment.yml file as follows:

conda env create -f environment.yml
conda activate kth

After executing these commands a new Conda environment named kth will be created with all necessary packages. The environment is self-contained so as to not influence other local python installations and avoid conflicts with previously installed packages.

Now you can install the kth package into this newly created environment that contains all requirements by moving into the main folder and using the pip install command as follows:

pip install -e .

You can test out your installation by running the main.py in the tutorial directory. (to be added)

To deactivate this environment simply type:

conda deactivate

Usage

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import keyfi as kf

import canteraKTH as ckth

from NN import *

import POD as POD