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I was happy to discover that read_stars supports reading any file as stars_proxy object, significantly easing my memory constraints (quite the contrary occured to my surprise, see #708)! However, st_bbox() when applied via st_set_bbox() to a stars_proxy does not outlast the conversion into a stars object, e.g.
library(stars)
fl = system.file("tif/L7_ETMs.tif", package = "stars")
rs = read_stars(fl, proxy = TRUE)
rs2 = rs |>
st_set_bbox(value = st_bbox(rs)*2) |>
st_as_stars()
# The two bboxes should be different, i.e. TRUE TRUE TRUE TRUE
st_bbox(rs) != st_bbox(rs2)
This entails problems for intermediate down-sampled output such as plots as well as repetitive statements after each obtained stars objects if the st_bbox of the raw data is not set correctly.
The text was updated successfully, but these errors were encountered:
Thank you, @edzer, for your reply. My raster in ASCII Grid form has wrong cellsize or dx/dy values so I wanted to correct these before further processing, by manually setting the bounding box.
I could work around this problem by modifying the data in place, but preferred an in memory replacement.
I was happy to discover that
read_stars
supports reading any file asstars_proxy
object,significantly easing my memory constraints(quite the contrary occured to my surprise, see #708)! However,st_bbox()
when applied viast_set_bbox()
to astars_proxy
does not outlast the conversion into astars
object, e.g.This entails problems for intermediate down-sampled output such as plots as well as repetitive statements after each obtained
stars
objects if thest_bbox
of the raw data is not set correctly.The text was updated successfully, but these errors were encountered: