Add Cloudy example to test

Author: charleskawczynski

.appveyor.yml

@@ -8,6 +8,7 @@ branches:
     # - master
 
 environment:
+  PYTHON: conda
   matrix:
   - julia_version: 1.3
   - julia_version: nightly
@@ -30,6 +31,8 @@ notifications:
 
 install:
   - ps: iex ((new-object net.webclient).DownloadString("https://raw.githubusercontent.com/JuliaCI/Appveyor.jl/version-1/bin/install.ps1"))
+  - pip install --user -U numpy scipy scikit-learn
+  - C:\julia\bin\julia -e "using Pkg; Pkg.build(\"PyCall\"); Pkg.update()"
 
 build_script:
   - echo "%JL_BUILD_SCRIPT%"

Manifest.toml

@@ -10,12 +10,19 @@ DifferentialEquations = "0c46a032-eb83-5123-abaf-570d42b7fbaa"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae"
 EllipsisNotation = "da5c29d0-fa7d-589e-88eb-ea29b0a81949"
+GaussianProcesses = "891a1506-143c-57d2-908e-e1f8e92e6de9"
+JLD2 = "033835bb-8acc-5ee8-8aae-3f567f8a3819"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 NPZ = "15e1cf62-19b3-5cfa-8e77-841668bca605"
+Optim = "429524aa-4258-5aef-a3af-852621145aeb"
 Parameters = "d96e819e-fc66-5662-9728-84c9c7592b0a"
+Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
 PyCall = "438e738f-606a-5dbb-bf0a-cddfbfd45ab0"
 PyPlot = "d330b81b-6aea-500a-939a-2ce795aea3ee"
+Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 ScikitLearn = "3646fa90-6ef7-5e7e-9f22-8aca16db6324"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
+StatsPlots = "f3b207a7-027a-5e70-b257-86293d7955fd"
+Sundials = "c3572dad-4567-51f8-b174-8c6c989267f4"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"