Project.toml

name = "DINCAE"
uuid = "0d879ee6-e5ed-4b6f-b65c-f78122b59944"
keywords = ["satellite observations", "oceanography", "missing data", "inpainting", "auto-encoder", "neural network"]
license = "GPL3+"
desc = "DINCAE (Data-Interpolating Convolutional Auto-Encoder) is a neural network to reconstruct missing data in satellite observations"
authors = ["Alexander Barth <barth.alexander@gmail.com>"]
version = "2.0.4"

[deps]
CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c"
JLD2 = "033835bb-8acc-5ee8-8aae-3f567f8a3819"
NCDatasets = "85f8d34a-cbdd-5861-8df4-14fed0d494ab"
Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
Profile = "9abbd945-dff8-562f-b5e8-e1ebf5ef1b79"
Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
ThreadsX = "ac1d9e8a-700a-412c-b207-f0111f4b6c0d"

[compat]
CUDA = "3.8, 4, 5"
ChainRulesCore = "1"
Flux = "0.14"
NCDatasets = "0.11, 0.12, 0.13, 0.14"
ThreadsX = "0.1"
julia = "1"

[extras]
CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c"
LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
NCDatasets = "85f8d34a-cbdd-5861-8df4-14fed0d494ab"
Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"

[targets]
test = ["Test", "NCDatasets", "Random", "CUDA", "Flux", "LinearAlgebra"]