clean up docs, add examples

francescoalemanno · Sep 7, 2020 · 9b71195 · 9b71195
1 parent 2e066bb
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Showing 5 changed files with 5 additions and 31 deletions.
diff --git a/README.md b/README.md
@@ -81,4 +81,5 @@ julia> smc(prior,cost)
 (P = Particles{Float64,79}[2.0 ± 0.0062, 0.0401 ± 0.00081], W = 0.0127, ϵ = 0.011113205245491245)
 ```
 
-to know how to tune the configuration defaults of `smc`, consult the docs :)
+to know how to tune the configuration defaults of `smc`, consult the docs :)
+for more example look at the `examples` folder.
diff --git a/docs/Project.toml b/docs/Project.toml
@@ -2,6 +2,3 @@
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 KissABC = "9c9dad79-530a-4643-a18b-2704674d4108"
-Literate = "98b081ad-f1c9-55d3-8b20-4c87d4299306"
-Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
-StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
diff --git a/docs/make.jl b/docs/make.jl
@@ -1,20 +1,6 @@
 using KissABC
 using Documenter
-#using Literate
-#using Plots
-#ENV["GKSwstype"] = "100"
-#@show joinpath(@__DIR__, "src")
-#=Literate.markdown(
-    joinpath(@__DIR__, "literate", "example_1.jl"),
-    joinpath(@__DIR__, "src"),
-    documenter = true,
-)=#
-#=Literate.markdown(
-    joinpath(@__DIR__, "literate", "index.jl"),
-    joinpath(@__DIR__, "src"),
-    documenter = true,
-)
-@info "Literate finished."=#
+
 makedocs(;
     modules = [KissABC],
     authors = "Francesco Alemanno <francescoalemanno710@gmail.com> and contributors",

diff --git a/docs/literate/index.jl → examples/example_n1.jl b/docs/literate/index.jl → examples/example_n1.jl
@@ -45,9 +45,9 @@ res = sample(
 
 # You can also use Sequential Monte Carlo (SMC) to infer posterior parameters:
 
-#ressmc = smc(prior, cost, nparticles=500, epstol=0.01)
+ressmc = smc(prior, cost, nparticles=500, epstol=0.01)
 
-#@show ressmc
+@show ressmc
 
 # the parameters we chose are: a tolerance on distances equal to `0.1`, a number of samples equal to `2000`, the simulated posterior results are in `res`.
 # We can now extract the inference results:

diff --git a/docs/literate/example_1.jl → examples/example_n2.jl b/docs/literate/example_1.jl → examples/example_n2.jl
@@ -18,15 +18,6 @@ end
 parameters = (1.0, 0.0, 0.2, 2.0, 0.4)
 data = model(parameters, 200)
 
-# let's look at the data
-
-using Plots
-histogram(data,bins=100)
-savefig("ex1_hist1.svg");
-nothing; # hide
-
-# ![ex1_hist1](ex1_hist1.svg)
-
 # we can now try to infer all parameters using `KissABC`, first of all we need to define a reasonable prior for our model
 
 prior = Factored(
@@ -67,4 +58,3 @@ approx_density = ApproxPosterior(prior, D, 0.032)
 # In this case, it is best to apply SMC, as it leads to tighter CI's and lower computational costs
 @time res = smc(prior, D, verbose=false, nparticles=100, alpha=0.95)
 @show res.P
-