ds = xr.open_zarr(
session.store,
group="goes19_goes18/10m/C08/2026-03-10",
zarr_format=3,
)
ds
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| code for https://rstats.me/@mdsumner/117059558926596079 | |
| run on Pawsey, packages are on CRAN or gh:hypertidy | |
| ```R | |
| #!/usr/bin/env Rscript | |
| ## Pacific mean SST from GHRSST COGs, one value per date. | |
| ## File-per-date cache: rerun any time, only missing dates are computed, | |
| ## failures write nothing and are picked up on the next run. |
https://github.com/hypertidy/bigcurve
{bigcurve} provides D3-level adaptive densifications at shape-segment level with bisecting line segments if required by the coordinate transformation, on a solid C++ basis, with {wk} for format wrangling and CRS transform, {wkpool} provides segments (with topology, future proof)
p <- geos::as_geos_geometry(terra::as.polygons(terra::rast(terra::ext(-150, 150, -85, 85), res = 15)))
tgt <- "+proj=laea"
tr <- PROJ::proj_trans_create(wk::wk_crs(p)$wkt, tgt)# dsn <- sds::nsidc_seaice()
# library(terra)
# plot(rast(dsn))
#e <- draw()
#dput(round(as.vector(e)))
## pole inside extent, south polar steregraphic
e <- c(xmin = -1094338, xmax = 1230070, ymin = -699223, ymax = 997424)
xyedge <- vaster::vaster_boundary(c(64, 64), e)
## reproj_extent infills the source extent to not miss the polexarray.open_dataset("https://www.ncei.noaa.gov/data/sea-surface-temperature-optimum-interpolation/v2.1/access/avhrr/198109/oisst-avhrr-v02r01.19810901.nc")
syntax error, unexpected WORD_WORD, expecting SCAN_ATTR or SCAN_DATASET or SCAN_ERROR
context: <!DOCTYPE^ HTML PUBLIC "-//IETF//DTD HTML 2.0//EN"><html><head><title>404 Not Found</title></head><body><h1>Not Found</h1><p>The requested URL was not found on this server.</p></body></html>
Traceback (most recent call last):
File "/opt/gdal-py/lib/python3.12/site-packages/xarray/backends/file_manager.py", line 219, in _acquire_with_cache_info
file = self._cache[self._key]
~~~~~~~~~~~^^^^^^^^^^^
File "/opt/gdal-py/lib/python3.12/site-packages/xarray/backends/lru_cache.py", line 56, in __getitem__small example using a docker image from https://github.com/hypertidy/gdal-r-ci, I'm using dev because the mdim print output is human readable (by default, json by option)
docker pull ghcr.io/hypertidy/gdal-system:dev
docker run --rm -ti ghcr.io/hypertidy/gdal-system:dev
#── ghcr.io/hypertidy/gdal-system ──
#GDAL 3.14.0dev PROJ 9.8.1 GEOS 3.15.0beta1
#Py 3.12.3 numpy 2.5.1
xy <- do.call(cbind, maps::map(plot = F)[1:2])
mm <- matrix(c(8L, -95L, -50L, 59L, -47L, -62L), ncol = 2)
mm <- rbind(mm, mm[1, ])
n <- nrow(mm)
x <- 1:n
idx <- seq(1, n, length.out = 200 )
par(mfrow = c(2, 1))
maps::map()Following the storage guide's Redirect Storage section: a 302 whose Location uses the documented http+icechunk://
scheme causes a Rust panic that escapes to Python as pyo3_runtime.PanicException rather than an IcechunkError.
Reprex:
import http.server, threading, icechunk as ic- List all of OISST netcdf files from object storage and derive date from path
- Remove duplicates that are 'preliminary' files replaced by final, and sort by date
- Stack into MDIM VRT with xml and templating from the first few files
### 1.
Sys.setenv("AWS_NO_SIGN_REQUEST" = "YES")
root <- "/vsis3/noaa-cdr-sea-surface-temp-optimum-interpolation-pds/data/v2.1/avhrr"#run --rm -ti -v $HOME/Git/gdalxarray:/gdalxarray ghcr.io/hypertidy/gdal-r-python:dev
import os
os.environ["AWS_NO_SIGN_REQUEST"] = "YES"
os.environ["AWS_REGION"] = "us-west-2"
# 1. confirm register() is active and chunk manager is happy
from dask_array.xarray import register; register()NewerOlder