Review examples

Project.toml

@@ -26,13 +26,20 @@ MathOptSetDistances = "0.1"
 julia = "1.6"
 
 [extras]
-Clp = "e2554f3b-3117-50c0-817c-e040a3ddf72d"
+CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
+DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
 DelimitedFiles = "8bb1440f-4735-579b-a4ab-409b98df4dab"
+Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c"
 GLPK = "60bf3e95-4087-53dc-ae20-288a0d20c6a6"
+HTTP = "cd3eb016-35fb-5094-929b-558a96fad6f3"
 Ipopt = "b6b21f68-93f8-5de0-b562-5493be1d77c9"
+MLDatasets = "eb30cadb-4394-5ae3-aed4-317e484a6458"
 OSQP = "ab2f91bb-94b4-55e3-9ba0-7f65df51de79"
+Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
+Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
 SCS = "c946c3f1-0d1f-5ce8-9dea-7daa1f7e2d13"
+Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["Test", "Clp", "DelimitedFiles", "SCS", "OSQP", "GLPK", "Ipopt"]
+test = ["Test", "DelimitedFiles", "SCS", "OSQP", "GLPK", "Ipopt", "CSV", "Statistics", "DataFrames", "Flux", "MLDatasets", "Plots", "Printf", "HTTP"]

README.md

@@ -20,22 +20,24 @@ DiffOpt can be installed via the Julia package manager:
 
 1. Create a model using the wrapper.
 ```julia
-using JuMP, DiffOpt, Clp
+using JuMP
+import DiffOpt
+import GLPK
 
-model = JuMP.Model(() -> diff_optimizer(Clp.Optimizer))
+model = JuMP.Model(() -> DiffOpt.diff_optimizer(GLPK.Optimizer))
 ```
 
 2. Define your model and solve it a single line.
 ```julia
 @variable(model, x)
 @constraint(
-  model, 
-  cons, 
+  model,
+  cons,
   x >= 3,
 )
 @objective(
-  model, 
-  Min, 
+  model,
+  Min,
   2x,
 )
 
@@ -46,8 +48,8 @@ optimize!(model) # solve
 ```julia
 MOI.set.(  # set pertubations / gradient inputs
     model, 
-    DiffOpt.BackwardInVariablePrimal(), 
-    x, 
+    DiffOpt.BackwardInVariablePrimal(),
+    x,
     1.0,
 )
 ```
@@ -57,8 +59,8 @@ MOI.set.(  # set pertubations / gradient inputs
 DiffOpt.backward(model) # differentiate
 
 grad_exp = MOI.get(   # -3x+1
-    model, 
-    DiffOpt.BackwardOutConstraint(), 
+    model,
+    DiffOpt.BackwardOutConstraint(),
     cons
 )
 JuMP.constant(grad_exp)  # 1

docs/Project.toml

@@ -1,12 +1,18 @@
 [deps]
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
-Clp = "e2554f3b-3117-50c0-817c-e040a3ddf72d"
+GLPK = "60bf3e95-4087-53dc-ae20-288a0d20c6a6"
+CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
+DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
+Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c"
+HTTP = "cd3eb016-35fb-5094-929b-558a96fad6f3"
+Ipopt = "b6b21f68-93f8-5de0-b562-5493be1d77c9"
 JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
+LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Literate = "98b081ad-f1c9-55d3-8b20-4c87d4299306"
 MathOptInterface = "b8f27783-ece8-5eb3-8dc8-9495eed66fee"
 OSQP = "ab2f91bb-94b4-55e3-9ba0-7f65df51de79"
 Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
 SCS = "c946c3f1-0d1f-5ce8-9dea-7daa1f7e2d13"
+Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
-Ipopt = "b6b21f68-93f8-5de0-b562-5493be1d77c9"

docs/make.jl

@@ -38,7 +38,6 @@ end
 
 literate_directory(_EXAMPLE_DIR)
 
-
 makedocs(;
     modules=[DiffOpt],
     doctest = false,
@@ -53,11 +52,6 @@ makedocs(;
         "Manual" => "manual.md",
         "Usage" => "usage.md",
         "Reference" => "reference.md",
-        "Examples" => [
-            "Differentiating a simple QP by hand" => "matrix-inversion-manual.md",
-            "ChainRules integration (Relaxed Unit Commitment)" => "chainrules_unit.md",
-            "Solving conic with PSD and SOC constraints" => "solve-conic-1.md",
-        ],
         "Tutorials" => [
             joinpath("examples", f) for f in readdir(_EXAMPLE_DIR) if endswith(f, ".md")
         ],