Fixed merge conflict with diabetes examples

.github/workflows/tests.yml

@@ -9,7 +9,6 @@ jobs:
       matrix:
         julia-version: ['1.9']
         os: [ubuntu-latest, macOS-latest]
-
     steps:
       - uses: actions/checkout@v2
       - uses: julia-actions/setup-julia@latest

.github/workflows/validate-notebooks.yml

@@ -0,0 +1,50 @@
+name: Check notebook examples for regressions
+
+on: [push, pull_request]
+
+env:
+  JULIA_NUM_THREADS: 'auto'
+jobs:
+  notebooks-examples-regression-test:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v3
+      - name: Setup Julia
+        uses: julia-actions/setup-julia@v1
+        with:
+          version: 1.9
+      - name: Cache Julia dependencies
+        uses: julia-actions/cache@v1
+      - name: Add IJulia Jupyter kernel
+        run: julia --color=yes --project=. -e 'ENV["JULIA_PKG_PRECOMPILE_AUTO"]=0; using Pkg; pkg"add IJulia"'
+      - name: Install Julia dependencies
+        run: julia --color=yes --project=. -e 'import Pkg; Pkg.instantiate(); Pkg.resolve(); Pkg.precompile()'
+      - uses: yaananth/run-notebook@v2
+        env:
+          RUNNER: ${{ toJson(runner) }}
+          SECRETS: ${{ toJson(secrets) }}
+          GITHUB: ${{ toJson(github) }}
+        with:
+          notebook: "examples/full_fledged_schema_examples_new/stratification/diabetes_diagnose.ipynb"
+      - uses: yaananth/run-notebook@v2
+        env:
+          RUNNER: ${{ toJson(runner) }}
+          SECRETS: ${{ toJson(secrets) }}
+          GITHUB: ${{ toJson(github) }}
+        with:
+          notebook: "examples/full_fledged_schema_examples_new/composition/diabetes_model.ipynb"
+      - uses: yaananth/run-notebook@v2
+        env:
+          RUNNER: ${{ toJson(runner) }}
+          SECRETS: ${{ toJson(secrets) }}
+          GITHUB: ${{ toJson(github) }}
+        with:
+          notebook: "examples/full_fledged_schema_examples_new/CausalLoopDiagrams/convert_from_SEIR_stockFlowDiagram.ipynb"
+      - uses: actions/upload-artifact@v3
+        if: always()
+        with:
+          name: output
+          path: ${{ RUNNER.temp }}/nb-runner
+        env:
+          RUNNER: ${{ toJson(runner) }}

docs/.gitignore

@@ -0,0 +1,2 @@
+build/
+src/generated/

docs/make.jl

@@ -0,0 +1,59 @@
+using Documenter
+using Literate
+
+const literate_dir = joinpath(@__DIR__, "literate")
+const generated_dir = joinpath(@__DIR__, "src", "generated")
+
+@info "Loading StockFlow.jl"
+using StockFlow
+
+const no_literate = "--no-literate" in ARGS
+if !no_literate
+  @info "Building Literate.jl docs"
+
+  # XXX: Work around old LaTeX distribution in GitHub CI.
+  if haskey(ENV, "GITHUB_ACTIONS")
+    import TikzPictures
+    TikzPictures.standaloneWorkaround(true)
+  end
+
+  # Set Literate.jl config if not being compiled on recognized service.
+  config = Dict{String,String}()
+  if !(haskey(ENV, "GITHUB_ACTIONS") || haskey(ENV, "GITLAB_CI"))
+    config["nbviewer_root_url"] = "https://nbviewer.jupyter.org/github/AlgebraicJulia/StockFlow.jl/blob/gh-pages/dev"
+    config["repo_root_url"] = "https://github.com/AlgebraicJulia/StockFlow.jl/blob/main/docs"
+  end
+
+  for (root, dirs, files) in walkdir(literate_dir)
+    out_dir = joinpath(generated_dir, relpath(root, literate_dir))
+    for file in files
+      if last(splitext(file)) == ".jl"
+        Literate.markdown(joinpath(root, file), out_dir;
+                          config=config, documenter=true, credit=false)
+        Literate.notebook(joinpath(root, file), out_dir;
+                          execute=true, documenter=true, credit=false)
+      end
+    end
+  end
+end
+
+@info "Building Documenter.jl docs"
+makedocs(
+  modules     = [StockFlow],
+  format      = Documenter.HTML(
+                                assets = ["assets/analytics.js"],
+                               ),
+  sitename    = "StockFlow.jl",
+  doctest     = false,
+  checkdocs   = :none,
+  pages       = Any[
+    "StockFlow.jl" => "index.md",
+  ]
+)
+
+@info "Deploying docs"
+deploydocs(
+  target = "build",
+  repo   = "github.com/AlgebraicJulia/StockFlow.jl.git",
+  branch = "gh-pages"
+)

docs/src/index.md

@@ -0,0 +1,10 @@
+# [StockFlow](@id StockFlow)
+
+```@autodocs
+Modules = [
+    StockFlow,
+    StockFlow.Syntax,
+    StockFlow.PremadeModels
+]
+Private = false
+```

src/CausalLoop.jl

@@ -2,7 +2,6 @@ export TheoryCausalLoop, AbstractCausalLoop, CausalLoopUntyped, CausalLoop, nn,
 sedge, tedge, convertToCausalLoop, nnames
 
 
-
 @present TheoryCausalLoop(FreeSchema) begin
   E::Ob
   N::Ob
@@ -26,6 +25,10 @@ add_nodes!(c::AbstractCausalLoop,n;kw...) = add_parts!(c,:N,n;kw...)
 add_edge!(c::AbstractCausalLoop,s,t;kw...) = add_part!(c,:E,s=s,t=t;kw...) 
 add_edges!(c::AbstractCausalLoop,n,s,t;kw...) = add_parts!(c,:E,n,s=s,t=t;kw...)
 
+"""
+    CausalLoop(ns,es)
+Create causal loop diagram from collection of nodes and collection of edges.
+"""
 CausalLoop(ns,es) = begin
     c = CausalLoop()
     ns = vectorify(ns)
@@ -42,15 +45,22 @@ CausalLoop(ns,es) = begin
 end
 
 # return the count of each components
+""" return count of nodes of CLD """
 nn(c::AbstractCausalLoop) = nparts(c,:N) #nodes
+""" return count of edges of CLD """
 ne(c::AbstractCausalLoop) = nparts(c,:E) #edges
 
+""" return node's name with index n """
 nname(c::AbstractCausalLoop,n) = subpart(c,n,:nname) # return the node's name with index of s
+""" return edge's name with target number t """
 sedge(c::AbstractCausalLoop,e) = subpart(c,e,:s)
+""" return edge's name with edge number e """
 tedge(c::AbstractCausalLoop,e) = subpart(c,e,:t)
 
+""" return node names of CLD """
 nnames(c::AbstractCausalLoop) = [nname(c, n) for n in 1:nn(c)]
 
+
 function convertToCausalLoop(p::AbstractStockAndFlowStructure)
 
     sns=snames(p)
@@ -73,6 +83,11 @@ function convertToCausalLoop(p::AbstractStockAndFlowStructure)
     return CausalLoop(ns,es)
 end
 
+"""
+Convert StockFlow to CLD.
+Nodes: stocks, flows, sum variables, parameters, nonflow dynamic variables
+Edges: morphisms in stock flow
+"""
 function convertToCausalLoop(p::AbstractStockAndFlowStructureF)
 
     sns=snames(p)

src/PremadeModels.jl

@@ -4,18 +4,30 @@ using ..StockFlow.Syntax
 
 export seir, sis, sir, svi
 
+"""
+Return a new SEIR model
+"""
 function seir()
     return deepcopy(seir_model)
 end
 
+"""
+Return a new SIS model
+"""
 function sis()
     return deepcopy(sis_model)
 end
 
+"""
+Return a new SIR model
+"""
 function sir()
     return deepcopy(sir_model)
 end
 
+"""
+Return a new SVI model
+"""
 function svi()
     return deepcopy(svi_model)
 end
@@ -36,8 +48,8 @@ seir_model = @stock_and_flow begin
         tlatent
         trecovery
         δ
-        c 
-        
+        c
+
 
         :dynamic_variables
         v_prevalence = NI / NS
@@ -49,14 +61,14 @@ seir_model = @stock_and_flow begin
 
         v_inf = E / tlatent
 
-        v_rec = I / trecovery 
+        v_rec = I / trecovery
 
 
-        v_deathS = δ * S       
+        v_deathS = δ * S
         v_deathE = δ * E
         v_deathI = δ * I
         v_deathR = δ * R
-        
+
 
         :flows
         CLOUD => f_birth(v_birth) => S
@@ -80,15 +92,15 @@ sis_model = @stock_and_flow begin
     S
     I
 
-    
+
     :parameters
     μ
     β
     trec # 1 / trecovery.  This corresponds to σ.
     δ
     c
 
-      
+
     :dynamic_variables
     v_deathsX = δ * S
     v_births = μ * N
@@ -114,7 +126,7 @@ sis_model = @stock_and_flow begin
     N = [S, I]
     NI = [I]
     NS = [S, I]
-  
+
 end
 
 
@@ -123,35 +135,35 @@ sir_model = @stock_and_flow begin
     S
     I
     R
-    
+
     :parameters
     c
     β
     rRec
-    
+
     :dynamic_variables
     v_prevalence = NI / NS
     v_meanInfectiousContactsPerS = c * v_prevalence
     v_perSIncidenceRate = β * v_meanInfectiousContactsPerS
     v_newInfections = S * v_perSIncidenceRate
     v_newRecovery = I * rRec
-    
+
     :flows
     S => f_inf(v_newInfections) => I
     I => f_rec(v_newRecovery) => R
-    
+
     :sums
     N = [S, I, R]
     NI = [I]
     NS = [S,I,R]
-    
-    
+
+
 end
 
 
 
 svi_model = @stock_and_flow begin
-    
+
     :stocks
     S
     V
@@ -165,9 +177,9 @@ svi_model = @stock_and_flow begin
     β
 
     :dynamic_variables
-    v_vacc = S * rvaccine 
+    v_vacc = S * rvaccine
     v_deathV = δ * V
-    
+
     v_prevalence = NI / NS
     v_meanInfectiousContactsPerS = c * v_prevalence
     v_perSIncidenceRate = β * v_meanInfectiousContactsPerS
@@ -178,9 +190,9 @@ svi_model = @stock_and_flow begin
     :flows
     S => f_vacc(v_vacc) => V
     V => f_deathV(v_deathV) => CLOUD
-    V => f_infV(v_perSIncidenceVaccinated) => I 
+    V => f_infV(v_perSIncidenceVaccinated) => I
+
 
-
     :sums
     N = [S, V, I]
     NI = [I]