Project.toml

name = "TimeSeriesClustering"
uuid = "61e8395a-c5b7-11e9-0bf6-872d3bc7175c"
keywords = ["clustering", "data mining", "optimization", "motifs", "data segmentation"]
license = "MIT"
desc = "julia implementation of unsupervised learning methods for time series datasets. It provides functionality for clustering and aggregating, detecting motifs, and quantifying similarity between time series datasets."
author = ["Holger Teichgraeber"]
version = "0.5.3"

[deps]
CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
Clustering = "aaaa29a8-35af-508c-8bc3-b662a17a0fe5"
DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
Distances = "b4f34e82-e78d-54a5-968a-f98e89d6e8f7"
FileIO = "5789e2e9-d7fb-5bc7-8068-2c6fae9b9549"
JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"

[compat]
julia = "^1.0"

[extras]
Cbc = "9961bab8-2fa3-5c5a-9d89-47fab24efd76"
JLD2 = "033835bb-8acc-5ee8-8aae-3f567f8a3819"
Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"

[targets]
test = ["Pkg", "Test", "StatsBase", "Cbc", "Random", "JLD2"]