Using crspy‐lite

Installation

You can install crspy-lite on your local machine directly from PyPI using pip. Simply open terminal and type:

pip install crspy_lite  

Or to upgrade to the latest version of the tool:

pip install --upgrade crspy_lite

Running crspy-lite

To run the code you need only 2 things: (i) Input time-series data from the CRNS, and (ii) a list of metadata variables. For information on the format and requirements of these please go to the wiki pages Input Timeseries Data and Metadata Input respectively. To then process and visualise your data simply open terminal and type:

crspy_lite

Or to specify the directory where outputs are stored (as opposed to the working directory that is the default), navigate to your chosen folder and Press Ctrl + Shift + C to copy the full path. Then paste this into the terminal after "crspy_lite" as exemplified below:

crspy_lite "C:\Users\YourName\Documents\your-folder"

If this is the first time the directory has been used, you will be prompted to input all requirements into the terminal. Optional requirements are highlighted and can be left empty. Once this is completed crspy-lite will generate folders and then convert your inputs into a config.json file. This can then be accessed by going to "\your-folder\inputs\config.json". To change the inputs simply open, edit and then save the config.json file. The code can then be re-run (exactly the same as above) to incorporate the changes. The config.json file also contains variables that can be edited to personalise the processing such as different research methodologies, limits and visualisation features. For more information on this please go to the wiki page Metadata Input.

Once crspy-lite is run, all time-series outputs are saved to "\your-folder\outputs\data", with all graphical outputs saved to "\your-folder\outputs\figures".

Examples

Please use the links below to see examples of using crspy-lite:

• No examples at present.