compat julia, CSV, DataFrames, Optim, Plots, PrettyTables

viraltux · Jul 4, 2022 · 083de40 · 083de40
1 parent db10ae1
commit 083de40
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Showing 6 changed files with 20 additions and 14 deletions.
diff --git a/Project.toml b/Project.toml
@@ -21,16 +21,16 @@ Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 
 [compat]
-CSV = "0.8, 0.9"
+CSV = "0.8 - 0.10"
 CodecZlib = "0.7"
 ColorSchemes = "3"
-DataFrames = "1.2"
-DataFramesMeta = "0.7, 0.8, 0.9"
+DataFrames = "1.2 - 1.3"
+DataFramesMeta = "0.7 - 0.11"
 Distributions = "0.23, 0.25"
 HypothesisTests = "0.10"
-Optim = "1.3"
-Plots = "1.15"
-PrettyTables = "1.1"
-RecipesBase = "1.1"
+Optim = "^1.3"
+Plots = "^1.15"
+PrettyTables = "^1.1"
+RecipesBase = "^1.1"
 StatsBase = "0.33"
-julia = "1.5"
+julia = "1.5 - 1.7"
diff --git a/src/datasets.jl b/src/datasets.jl
@@ -105,7 +105,7 @@ function seaborne(full::Bool = false)
     sb_df = open(joinpath(path, "seaborne.csv.gz")) do file
         CSV.read(GzipDecompressorStream(file),DataFrame,
                  dateformat = "mm/dd/yyyy HH:MM:SS pp",
-                 types = Dict(:year => Date))
+                 types = Dict(:date => Date))
     end
 
     if full

diff --git a/test/Project.toml b/test/Project.toml
@@ -1,5 +1,9 @@
 [deps]
+DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
+Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
+Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 Forecast = "6efb3b9f-b065-4dd1-b1a5-fac2350e161b"
 Logging = "56ddb016-857b-54e1-b83d-db4d58db5568"
+Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
diff --git a/test/loess.jl b/test/loess.jl
@@ -11,10 +11,10 @@ using Forecast
     @test length(x) == 20
 
     x = loess(sin.(collect(1:10.)), sin.(collect(1:10.)); d=2)
-    @test x == [0.8414709848078965, 0.9092974268256817, 0.14112000805986716, -0.7568024953079282, -0.9589242746631381, -0.2794154981989261, 0.6569865987187891, 0.9893582466233829, 0.4121184852417571, -0.5440211108893702]
+    @test x ≈ [0.8414709848078965, 0.9092974268256817, 0.14112000805986716, -0.7568024953079282, -0.9589242746631381, -0.2794154981989261, 0.6569865987187891, 0.9893582466233829, 0.4121184852417571, -0.5440211108893702]
 
     x = loess(sin.(collect(1:10.)), sin.(collect(1:10.)); d=1)
-    @test x == [0.8414709848078965, 0.9092974268256815, 0.14112000805986719, -0.7568024953079282, -0.9589242746631382, -0.2794154981989259, 0.6569865987187891, 0.9893582466233817, 0.41211848524175654, -0.5440211108893699]
+    @test x ≈ [0.8414709848078965, 0.9092974268256815, 0.14112000805986719, -0.7568024953079282, -0.9589242746631382, -0.2794154981989259, 0.6569865987187891, 0.9893582466233817, 0.41211848524175654, -0.5440211108893699]
 
     x = loess(Int64.(round.(100*rand(100))),
               Int64.(round.(100*rand(100))); predict = Int64.(round.(100*rand(20))))

diff --git a/test/plots.jl b/test/plots.jl
@@ -1,6 +1,6 @@
 using Test
 using Forecast
-using Plots, RecipesBase
+using Plots
 
 @testset "plots" begin
 

diff --git a/test/stl.jl b/test/stl.jl
@@ -11,8 +11,10 @@ using Forecast
     @test x.call isa String
 
     x = stl(co2(),365; robust=true, spm=true)
-    @test Array(x.decomposition[1:5,:]) == 
-    Any[Date("1974-05-17") 3.3336092113804625 330.03520225817715 0.011188530442382216; Date("1974-05-18") 3.2974595453530924 330.0378212346287 -0.22528077998180152; Date("1974-05-19") 3.2594500979279815 330.0404399841902 0.16010991788181173; Date("1974-05-20") 3.219714340570647 330.043058508077 0.3772271513523151; Date("1974-05-21") 3.178405197122059 330.0456768071629 0.1859179957150463]
+    @test x.decomposition[1:5,1] ==
+        [Date("1974-05-17"), Date("1974-05-18"), Date("1974-05-19"), Date("1974-05-20"), Date("1974-05-21")]
+    @test Matrix(x.decomposition[1:5,2:end]) ≈
+        [3.3336092113804625 330.03520225817715 0.011188530442382216; 3.2974595453530924 330.0378212346287 -0.22528077998180152; 3.2594500979279815 330.0404399841902 0.16010991788181173; 3.219714340570647 330.043058508077 0.3772271513523151; 3.178405197122059 330.0456768071629 0.1859179957150463]
 
 end