library(reproj)
x <- reproj_xy(do.call(cbind, maps::map(plot = F)[1:2], "EPSG:3976")
y <- reproj_xy(cbind(-180:180, -58), "EPSG:3976")
with these settings (region unset for good measure)
export AWS_ACCESS_KEY_ID=
export AWS_SECRET_ACCESS_KEY=
export AWS_S3_ENDPOINT=data.source.coop
export AWS_VIRTUAL_HOSTING=FALSE
export CPL_VSIL_USE_TEMP_FILE_FOR_RANDOM_WRITE=YES
export CPL_VSIS3_CREATE_DIR_OBJECT=TRUE
a
code golf for https://fosstodon.org/@coolbutuseless/113668013712145841
x <- c("apple", "app", "aptitude")
mx <- max(nchar(x))
pool <- c(letters, LETTERS)
flat <- function(x) {
running the quickstart
air_temp.to_zarr(repo.store, group='air_temperature')
/workenv/lib/python3.11/site-packages/xarray/core/dataset.py:2621: SerializationWarning: saving variable None with floating point data as an integer dtype without any _FillValue to use for NaNs
return to_zarr( # type: ignore[call-overload,misc]
Traceback (most recent call last):
From here https://planetarycomputer.microsoft.com/dataset/sentinel-5p-l2-netcdf#Example-Notebook
we get
import cartopy.crs as ccrs
import fsspec
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
A docker image for R folks wanting python too on GADI.
This update script will get the latest version of the image (it's big). Set your project/s for scratch and storage, I don't really understand the temp file stuff yet but this worked for me. Takes about 25min to get the image (you don't need to update often, this is very latest GDAL/PROJ/GEOS.
#!/bin/bash
#PBS -l ncpus=1
Get rema in longlat for a given extent, and resolution.
2m resolution is some thing like 1/50000 of a degree, so 3e-5 gives cells with 4m^2 area at 70S
#' Get REMA v2 data in longlat
#'
#' This is crafted VRT hosted on github that references the source 2m GeoTIFFs and some pre-rendered lower resolutions,
#' so we can make data from large areas quickly as well as small areas.
#'
for social co-working session, rOpensci 2024-12-03: https://ropensci.org/events/coworking-2024-12/
```R | |
prj <- "+proj=stere +lat_0=-90 +lon_0=100 +lat_ts=-70" | |
library(raadtools) | |
files <- read_amsr2_3k_ice(returnfiles = TRUE) | |
files <- files[nrow(files):1, ] | |
im <- vapour::gdal_raster_data(files$fullname[1], target_ext = e, target_crs = prj) | |
p <- reproj::reproj(cbind(99.3, -64.5), prj, source = "EPSG:4326") |