Anshul Singhvi
Anshul Singhvi
That would make `DataFrame(fc)` work, which would be _incredibly_ convenient. We currently don't have that so it's very difficult to tell beginner users how to use a GI feature collection.
Fixes #151 What do people think of this? This enables: ```julia tab = Shapefile.Table(...) shapes = GI.geometry(tab) # or, and more importantly, tab = GeoJSON.read(...) shapes = GI.geometry(tab) ``` This...
Does this make sense? Currently you have to do `(GI.geometry(x) for x in GI.getfeature(fc))` which is a mouthful.
We also need release notes but that can come later
apparently it just keeps running if you pass `Makie.plot` a featurecollection - see https://github.com/MakieOrg/GeoMakie.jl/issues/260
Does what it says on the tin, and tests that `DataFrame(table)` retains these values. We currently use the `:note` style meaning that the value of the metadata is propagated through...
MWE: ``` julia> feature = Shapefile.Table("/Users/anshul/downloads/not_ocean.zip") ERROR: ArgumentError: Month: 22 out of range (1:12) Stacktrace: [1] Dates.Date(y::Int64, m::Int64, d::Int64) @ Dates ~/.julia/juliaup/julia-1.10.5+0.aarch64.apple.darwin14/share/julia/stdlib/v1.10/Dates/src/types.jl:257 [2] Date @ ~/.julia/juliaup/julia-1.10.5+0.aarch64.apple.darwin14/share/julia/stdlib/v1.10/Dates/src/types.jl:402 [inlined] [3] DBFTables.Header(io::IOBuffer) @...
Currently this has a runtime of ~80 microseconds on my test case. Built on top of #198. Feel free to ignore the first two commits.
```julia-repl julia> data = [i+j for i in 1:200, j in 1:100] 200×100 Matrix{Int64}: [...] julia> da = ChunkedDiskArray(data, chunksize=(10,10)) 200×100 ChunkedDiskArray{Int64, 2, Matrix{Int64}} Chunked: ( [10, 10, 10, 10,...
It would be nice to have a larger memory limit on CachedDiskArrays when doing computation, and to not occupy RAM that could be used for data or computation. In this...