Merge branch 'main' into jg/moi

Author: joaquimg

.gitignore

@@ -25,3 +25,4 @@ Manifest.toml
 
 # other ignores
 .vscode/settings.json
+*.txt

docs/src/index.md

@@ -84,8 +84,17 @@ data = ModelAnalyzer.analyze(
     model,
     optimizer = HiGHS.Optimizer,
 )
-# print report
+
+# print report to the screen
 ModelAnalyzer.summarize(data)
+
+# or print ehte report to a file
+
+# open a file
+open("my_report.txt", "w") do io
+    # print report
+    ModelAnalyzer.summarize(io, data)
+end
 ```
 
 The `ModelAnalyzer.analyze(...)` function can always take the keyword arguments:
@@ -117,6 +126,6 @@ issues = ModelAnalyzer.list_of_issues(data, list[1])
 # the list of issues of the given type can be summarized with:
 ModelAnalyzer.summarize(data, issues)
 
-# infdividual issues can also be summarized
+# individual issues can also be summarized
 ModelAnalyzer.summarize(data, issues[1])
 ```

src/ModelAnalyzer.jl

@@ -27,7 +27,7 @@ See [`summarize`](@ref), [`list_of_issues`](@ref), and
 function analyze end
 
 """
-    summarize([io::IO,] AbstractData; model = nothing, verbose = true, max_issues = typemax(Int), kwargs...)
+    summarize([io::IO,] AbstractData; model = nothing, verbose = true, max_issues = 10, kwargs...)
 
 Print a summary of the analysis results contained in `AbstractData` to the
 specified IO stream. If no IO stream is provided, it defaults to `stdout`.
@@ -89,17 +89,27 @@ function summarize(
     end
 end
 
+const DEFAULT_MAX_ISSUES = 10
+
 function summarize(
     io::IO,
     issues::Vector{T};
     model = nothing,
     verbose = true,
-    max_issues = typemax(Int),
+    max_issues = DEFAULT_MAX_ISSUES,
 ) where {T<:AbstractIssue}
     summarize(io, T, verbose = verbose)
     print(io, "\n## Number of issues\n\n")
     print(io, "Found ", length(issues), " issues")
     print(io, "\n\n## List of issues\n\n")
+    if length(issues) > max_issues
+        print(
+            io,
+            "Showing first ",
+            max_issues,
+            " issues ($(length(issues) - max_issues) issues ommitted)\n\n",
+        )
+    end
     for issue in first(issues, max_issues)
         print(io, " * ")
         summarize(io, issue, verbose = verbose, model = model)

src/feasibility.jl

@@ -685,7 +685,7 @@ function ModelAnalyzer.summarize(
     io::IO,
     data::Data;
     verbose = true,
-    max_issues = typemax(Int),
+    max_issues = ModelAnalyzer.DEFAULT_MAX_ISSUES,
     configurations = true,
 )
     print(io, "## Feasibility Analysis\n\n")

src/infeasibility.jl

@@ -154,20 +154,18 @@ function ModelAnalyzer.analyze(
     for var in JuMP.all_variables(model)
         lb = if JuMP.has_lower_bound(var)
             JuMP.lower_bound(var)
+        elseif JuMP.is_fixed(var)
+            JuMP.fix_value(var)
         else
             -Inf
         end
         ub = if JuMP.has_upper_bound(var)
             JuMP.upper_bound(var)
+        elseif JuMP.is_fixed(var)
+            JuMP.fix_value(var)
         else
             Inf
         end
-        if lb > ub
-            push!(out.infeasible_bounds, InfeasibleBounds(var, lb, ub))
-            bounds_consistent = false
-        else
-            variables[var] = Interval(lb, ub)
-        end
         if JuMP.is_integer(var)
             if abs(ub - lb) < 1 && ceil(ub) == ceil(lb)
                 push!(
@@ -186,6 +184,12 @@ function ModelAnalyzer.analyze(
                 bounds_consistent = false
             end
         end
+        if lb > ub
+            push!(out.infeasible_bounds, InfeasibleBounds(var, lb, ub))
+            bounds_consistent = false
+        else
+            variables[var] = Interval(lb, ub)
+        end
     end
     # check PSD diagonal >= 0 ?
     # other cones?
@@ -371,10 +375,6 @@ function iis_elastic_filter(original_model::JuMP.GenericModel, optimizer)
         end
     end
 
-    # TODO: add deletion filter
-    # otherwise this is not an IIS (it does contain an IIS)
-
-    # pre_iis = Set(val[1] for val in de_elastisized)
     pre_iis = Set(cadidates)
     iis = JuMP.ConstraintRef[]
     for con in JuMP.all_constraints(
@@ -677,7 +677,7 @@ function ModelAnalyzer.summarize(
     io::IO,
     data::Data;
     verbose = true,
-    max_issues = typemax(Int),
+    max_issues = ModelAnalyzer.DEFAULT_MAX_ISSUES,
 )
     print(io, "## Infeasibility Analysis\n\n")
 

src/numerical.jl

@@ -2427,7 +2427,7 @@ function ModelAnalyzer.summarize(
     io::IO,
     data::Data;
     verbose = true,
-    max_issues = typemax(Int),
+    max_issues = ModelAnalyzer.DEFAULT_MAX_ISSUES,
     configurations = true,
     dimensions = true,
     ranges = true,

test/infeasibility.jl

@@ -219,7 +219,7 @@ function test_range_equalto()
     return
 end
 
-function test_range_equalto()
+function test_range_equalto_2()
     model = Model()
     @variable(model, x == 1)
     @variable(model, y == 2)
@@ -261,7 +261,7 @@ function test_range_greaterthan()
     return
 end
 
-function test_range_equalto()
+function test_range_equalto_3()
     model = Model()
     @variable(model, 10 <= x <= 11)
     @variable(model, 1 <= y <= 11)

test/numerical.jl

@@ -993,6 +993,34 @@ function test_qp_range()
     ModelAnalyzer.summarize(buf, data)
     ModelAnalyzer.summarize(buf, data, verbose = false)
 
+    open("my_report.txt", "w") do io
+        return ModelAnalyzer.summarize(io, data)
+    end
+
+    file_data = read("my_report.txt", String)
+    @test occursin("## Numerical Analysis", file_data)
+
+    return
+end
+
+function test_more_than_max_issues()
+    model = Model()
+    @variable(model, xg[1:20] <= 2e9)
+    data = ModelAnalyzer.analyze(ModelAnalyzer.Numerical.Analyzer(), model)
+    list = ModelAnalyzer.list_of_issue_types(data)
+    @test length(list) >= 1
+    ret = ModelAnalyzer.list_of_issues(
+        data,
+        ModelAnalyzer.Numerical.LargeBoundCoefficient,
+    )
+    @test length(ret) == 20
+
+    buf = IOBuffer()
+    ModelAnalyzer.summarize(buf, data)
+    str = String(take!(buf))
+    @test occursin("Showing first ", str)
+    @test occursin(" issues ommitted)\n\n", str)
+
     return
 end