The twlviewer package can be used to open and view the results from TWL processing.
download option - navigate to the latest release (v1.0) on the RHS of the root project page and download and unzip the source code.
clone option - from your local machine clone the repository from its GitHub address https://github.com/NOC-EO/twlviewer
To run the code in the project you need to install the required Python packages in an environment. To do this we will use Anaconda, which can be downloaded here.
Open an Anaconda Prompt from the start menu for Windows users or a terminal window for Mac and Linux and use the cd command (change directory) to the directory where you have installed the SAR-TWL repository. If you are unfamiliar with command windows check out the resources below ...
Create a new environment named twlviewer with all the required packages and activate this environment by entering the following commands (one at a time):
conda env create --file env/environment.yml
conda activate twlviewer
If you have successfully activated twlviewer, your terminal command line prompt will now start with (twlviewer).
In the terminal window opened in the twlviewer directory with the twlviewer environment activated (only needs to be activated if it wasnt done from the previous step) enter the following commands one at a time to start an iPython session:
conda activate twlviewer
jupyter notebook
This will initiate a iPython session in your defult brower where you can open the twlviewer notebook and run the cells to view TWL data. Example datsets have beeen included in the data directory.
this tutorial is a bit dated but the content is still relevant but note that you are best opening an anaconda command window known as an Anaconda Prompt from the start menu for Windows users (once anaconda has been installed)
command window basics tutorial
have fun ...