use more array as underlying data structure to speed it up

.gitignore

@@ -1,3 +1,4 @@
 docs/build/
-
+.vscode/
 *.log
+Manifest.toml

.travis.yml

@@ -2,7 +2,7 @@ language: julia
 os: linux
 
 julia: 
-    - 1.0
+    - 1.3
     - nightly
 
 notifications: 
@@ -15,28 +15,19 @@ install:
 
 script:
     - julia -e 'import Pkg; Pkg.clone("https://github.com/seung-lab/BigArrays.jl.git")'
-    - julia -e 'import Pkg; Pkg.clone(pwd()); Pkg.test("RealNeuralNetworks", coverage=true)'
+    - julia --project -e 'import Pkg; Pkg.build(); Pkg.test(;coverage=true)'
     - julia -e 'using Pkg; Pkg.add("Documenter")'
     - julia -e 'using Pkg; cd(Pkg.dir("RealNeuralNetworks")); include(joinpath("docs", "make.jl"))'
-
-
-      #jobs:
-      #  include:
-      #    - stage: "Documentation"
-      #      julia: 1.0
-      #      os: linux
-      #      script:
-      #        - julia -e 'import Pkg; Pkg.clone("https://github.com/seung-lab/BigArrays.jl.git")'
-      #        - julia -e 'import Pkg; Pkg.clone(pwd()); Pkg.test("RealNeuralNetworks")'
-      #        - julia -e 'import Pkg; Pkg.add("Documenter")'
-      #        - julia --project=docs/ -e 'using Pkg; Pkg.instantiate(); Pkg.develop(PackageSpec(path=pwd()))'
-      #        - julia --project=docs/ docs/make.jl
-      #      after_success: skip 
-
+
 matrix:
     allow_failures:
         - julia: nightly
 
 after_success:
   # push coverage results to Coveralls
   - julia -e 'import Pkg; cd(Pkg.dir("RealNeuralNetworks")); Pkg.add("Coverage"); using Coverage; Coveralls.submit(Coveralls.process_folder())'
+  # make documentation
+  - julia -e 'import Pkg; Pkg.add("Documenter")'
+  - julia --project=docs/ -e 'using Pkg; Pkg.instantiate(); Pkg.develop(PackageSpec(path=pwd()))'
+  - julia --project=docs/ docs/make.jl
+

Project.toml

@@ -1,18 +1,21 @@
 name = "RealNeuralNetworks"
 uuid = "4491297b-8966-5840-8cb9-b189d60f3398"
-version = "1.0.0"
+authors = ["Jingpeng Wu <[email protected]>"]
+version = "1.3.1"
 
 [deps]
 BigArrays = "c2a8506f-1b35-5b08-8aa1-bb4a7b47a05e"
 CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
 DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
+DelimitedFiles = "8bb1440f-4735-579b-a4ab-409b98df4dab"
 Distributed = "8ba89e20-285c-5b6f-9357-94700520ee1b"
 ImageFiltering = "6a3955dd-da59-5b1f-98d4-e7296123deb5"
 JSON = "682c06a0-de6a-54ab-a142-c8b1cf79cde6"
 LightGraphs = "093fc24a-ae57-5d10-9952-331d41423f4d"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 LsqFit = "2fda8390-95c7-5789-9bda-21331edee243"
+Memoize = "c03570c3-d221-55d1-a50c-7939bbd78826"
 MetaGraphs = "626554b9-1ddb-594c-aa3c-2596fe9399a5"
 NearestNeighbors = "b8a86587-4115-5ab1-83bc-aa920d37bbce"
 OffsetArrays = "6fe1bfb0-de20-5000-8ca7-80f57d26f881"
@@ -23,7 +26,7 @@ SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 
 [compat]
-julia = "≥ 1.0.0"
+julia = "≥ 1.3.0"
 
 [extras]
 CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"