| <!doctype html> | |
| <html lang="en-gb" class="no-js"> | |
| <head> | |
| <meta charset="utf-8"> | |
| <meta name="viewport" content="width=device-width, initial-scale=1, maximum-scale=1"> | |
| <title>|7y|4r|</title> | |
| <meta name="description" content="web portfolio"> | |
| <meta name="author" content="7yl4r"> | |
| <link rel="stylesheet" href="css/bootstrap.min.css" /> |
| language | package manager | configuration file(s) | Package index | environment manager |
|---|---|---|---|---|
| R | . | DESCRIPTION | cran | packrat |
| python | pip | Pipfile, requirements.txt | pypi | pipenv |
| python | conda | environment.yml | conda-forge | . |
hdf -> geospatial raster moonbooks.org
hdf -> histograms moonbooks
tif -> raster, histograms earthdatascience.org
tif --(gdal)--> time series jgomezdans
nc VIIRS -> raster ARSET github
earth engine joaootavionf007
| # for each column in data table | |
| richness.partial.deviance.list = for(j in names(gam_data[,3])) { | |
| # ??? why are we looping here? | |
| # ??? Is this code not the same as setting j="abundance_sum" and not looping? | |
| # ??? Maybe there are multiple columns with name "abundance_sum"? Seems odd. | |
| if(j=="abundance_sum") { # only this one abundance column | |
| # fit a GAM with the following model: | |
| # $y_i = \alpha + f_1(X_1i) + f_2(X_2i) + g_1( X_3i ) + g_2(X_4i ) + \epsilon_i$ | |
| # $y_i = \alpha + f_1(YEAR) + f_2(PROT) + g_1(LONG, LAT)* YEAR + g_2(STRAT) + \epsilon_i$ | |
| # ??? why are some of these f_* and others g_*? |
| # Creates an OBJECTID and Sample_ID for "child" rows that don't have them using "parent" rows as lookup by lat+lon+date. | |
| # """ | |
| # Child rows are identified by OBJECTID == 0. | |
| # Pseudocode: | |
| # read in OJBECT != 0 lat/lon/date & IDs map & + increment starting @ 1 | |
| # for row OJBECT == 0: | |
| # OJBECT_ID = lookup lat / lon / date in our map | |
| # """ | |
| # | |
| # NOTE: this doesn't work. We gave up after finding that the subsample rows were not actually subsamples. |
| # === config details: | |
| [airflow@imars-airflow01 imars_dags]$ echo $AIRFLOW_HOME | |
| /home/airflow | |
| # === relevant excerpt from `tree` | |
| [airflow@imars-airflow01 ~]$ tree $AIRFLOW_HOME/dags | |
| /home/airflow/dags | |
| └── imars_dags | |
| ├── imars_dags |
| import matplotlib.pyplot as plt | |
| import numpy as np | |
| fig, ax = plt.subplots() | |
| size = 0.3 | |
| vals = [ | |
| 25, | |
| 50, | |
| 75 |
# set up gdal
# NOTE: could maybe use https://github.com/PolarGeospatialCenter/gdal-full ?
sudo apt install -y gdal-bin libgdal-dev python3-pip
pip3 install "pygdal==$(gdal-config --version).*"
# TODO: more here probably...
# install code from github
git clone https://github.com/7yl4r/imagery_utils
Use rsync, then move files out of folders and delete empty folders:
# starting in /tpa_pgs/
mkdir fl_se
rsync -avzh --recursive --files-from=./files_to_move/files_to_move_sefl.txt ./pgc_batches/imagery/ ./fl_se/.
# cd to region and cleanup if needed:
find ./ -mindepth 2 -type f -exec mv {} . \;
find ./ -type d -empty -delete