Repository for a code package that calculates dissolved gas concentrations from air and equilibrated water data, from NEON's Dissolved gases in surface water (DP1.20097.001) data product.
GNU Affero General Public License v3.0
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Adding Python translation scripts to SDG repo in a separate directory #17
Hi @kcawley - This is to add a new 'Python' directory in the SDG repo that contains the Python translation scripts, a detailed README for their use, and an example 'wrapper' script to help users work with them more easily.
2 notes about the Python script translations -
They currently only work on already stacked tables (.csv) that are output from neonUtilities::stackByTable() in R. While it is possible to install and run R packages like neonUtilities from within Python using the rpy2 package, it is difficult to get consistently working with different installations. Because of this, it seemed most robust to just ask users to run stackByTable() first and provide a link in the README to the neonUtilities online tutorial for more details/examples about how to do that.
The output returned by the Python scripts is slightly different from output of the R package (about ~ 0.1% different for the saturation concentrations). This appears to be due to less intermediate rounding happening in the Python scripts than the R package. I'm assuming this small amount of variation isn't too much of a concern, but I wanted to let you know it is there (I've pointed this out in the README file so users are aware of these slight differences).
I also made slight changes to the main repo README to introduce the Python implementation of the SDG calculations, and to make the R package installation instructions more easily findable.
Hi @kcawley - This is to add a new 'Python' directory in the SDG repo that contains the Python translation scripts, a detailed README for their use, and an example 'wrapper' script to help users work with them more easily.
2 notes about the Python script translations -
I also made slight changes to the main repo README to introduce the Python implementation of the SDG calculations, and to make the R package installation instructions more easily findable.