A joint project to organize and calculate key remote sensing output metrics. Input data was collected during field-work and the next task involves filtering and calculating key optical coefficients.
In order to use this repository for testing and submitting pull requests, it is advised to enable a pre-commit hook which keeps python dependencies in requirements.txt
up-to-date.
$ ./init.sh
In order to aggregate raw flox data into a csv file, place the relevant flox data inside ./data/flox
and execute the following:
$ Rscript aggregate_flox.R
The corresponding output will be saved in the ./out
directory.
The script dat2json.py
parses a RAMSES text output file into a python dictionary and correspondingly writes it to the ./out
directory as a JSON file.
usage: dat2json.py [-h] [--out OUT] -i INPUT
optional arguments:
-h, --help show this help message and exit
--out OUT name of output json <default:'out'>
required named arguments:
-i INPUT, --input INPUT
name of input file, eg. 'ramses.dat'
figure_vis.R
contains a workflow to plot pond-based results after preprocessing a json file from dat2json.py
.
temporal_slice_vis.R
contains a workflow to plot pond-based results after preprocessing based on temporal slices.
Proposed changes to our workflow are highlighted in todos.md
.