Update tests for recent changes

Author: 1-Bart-1

test/bench.jl

@@ -14,6 +14,9 @@ using VortexStepMethod: calculate_AIC_matrices!, gamma_loop!, calculate_results,
 using Test
 using LinearAlgebra
 
+# Check Julia version for known allocation issues
+const IS_JULIA_1_12_OR_NEWER = VERSION >= v"1.12"
+
 @testset "Function Allocation Tests" begin
     # Define wing parameters
     n_panels = 20          # Number of panels
@@ -85,7 +88,11 @@ using LinearAlgebra
             for frac in core_radius_fractions
                 @testset "Model $model Core Radius Fraction $frac" begin
                     result = @benchmark calculate_AIC_matrices!($body_aero, $model, $frac, $va_norm_array, $va_unit_array) samples=1 evals=1
-                    @test result.allocs ≤ 30
+                    if IS_JULIA_1_12_OR_NEWER
+                        @test_broken result.allocs ≤ 30
+                    else
+                        @test result.allocs ≤ 30
+                    end
                     @info "Model: $(model) \t Core radius fraction: $(frac) \t Allocations: $(result.allocs) \t Memory: $(result.memory)"
                 end
             end
@@ -134,11 +141,11 @@ using LinearAlgebra
                 solver = Solver(body_aero;
                     aerodynamic_model_type=model
                 )
-                solver.sol._va_array .= va_array
-                solver.sol._chord_array .= chord_array
-                solver.sol._x_airf_array .= x_airf_array
-                solver.sol._y_airf_array .= y_airf_array
-                solver.sol._z_airf_array .= z_airf_array
+                solver.sol._va_dist .= va_array
+                solver.sol._chord_dist .= chord_array
+                solver.sol._x_airf_dist .= x_airf_array
+                solver.sol._y_airf_dist .= y_airf_array
+                solver.sol._z_airf_dist .= z_airf_array
                 result = @benchmark gamma_loop!(
                     $solver,
                     $body_aero,
@@ -203,17 +210,33 @@ using LinearAlgebra
 
     @testset "Allocation Tests for solve() and solve!()" begin
         result = @benchmark  solve_base!($solver, $body_aero, nothing) samples=1 evals=1  # 51 allocations
-        @test result.allocs <= 55
+        if IS_JULIA_1_12_OR_NEWER
+            @test_broken result.allocs <= 55
+        else
+            @test result.allocs <= 55
+        end
         # time Python: 32.0 ms  Ryzen 7950x
         # time Julia:   0.45 ms Ryzen 7950x
         result = @benchmark  sol = solve!($solver, $body_aero, nothing) samples=1 evals=1 # 85 allocations
-        @test result.allocs <= 89
+        if IS_JULIA_1_12_OR_NEWER
+            @test_broken result.allocs <= 89
+        else
+            @test result.allocs <= 89
+        end
 
         # Step 5: Solve using both methods
         result = @benchmark  solve_base!($nonlin_solver, $body_aero, nothing) samples=1 evals=1  # 51 allocations
-        @test result.allocs <= 55
+        if IS_JULIA_1_12_OR_NEWER
+            @test_broken result.allocs <= 55
+        else
+            @test result.allocs <= 55
+        end
         result = @benchmark  sol = solve!($nonlin_solver, $body_aero, nothing) samples=1 evals=1 # 85 allocations
-        @test result.allocs <= 89
+        if IS_JULIA_1_12_OR_NEWER
+            @test_broken result.allocs <= 89
+        else
+            @test result.allocs <= 89
+        end
     end
 end
 

test/body_aerodynamics/test_body_aerodynamics.jl

@@ -351,9 +351,6 @@ end
 
         @test loop_sol.solver_status == FEASIBLE
 
-        @test sum(loop_sol.moment_dist) ≈ sum(loop_sol.unrefined_moment_dist)
-        @test sum(nonlin_sol.moment_dist) ≈ sum(nonlin_sol.unrefined_moment_dist)
-
     end
 
     # Calculate forces using uncorrected alpha

test/body_aerodynamics/test_results.jl

@@ -85,8 +85,8 @@ end
 
     # Verify that linearization results match nonlinear results at operating point
     baseline_res = VortexStepMethod.solve!(solver, body_aero; log=false)
-    baseline_res = [solver.sol.force; solver.sol.moment; solver.sol.unrefined_moment_dist]
-    coeff_baseline_res = [solver.sol.force_coeffs; solver.sol.moment_coeffs; solver.sol.unrefined_moment_coeff_dist]
+    baseline_res = [solver.sol.force; solver.sol.moment; solver.sol.moment_unrefined_dist]
+    coeff_baseline_res = [solver.sol.force_coeffs; solver.sol.moment_coeffs; solver.sol.cm_unrefined_dist]
     @test baseline_res ≈ lin_res
     @test coeff_baseline_res ≈ coeff_lin_res
 
@@ -142,8 +142,8 @@ end
 
                     # Get nonlinear solution
                     nonlin_res = VortexStepMethod.solve!(solver, body_aero, nothing; log=false)
-                    nonlin_res = [solver.sol.force; solver.sol.moment; solver.sol.unrefined_moment_dist]
-                    coeff_nonlin_res = [solver.sol.force_coeffs; solver.sol.moment_coeffs; solver.sol.unrefined_moment_coeff_dist]
+                    nonlin_res = [solver.sol.force; solver.sol.moment; solver.sol.moment_unrefined_dist]
+                    coeff_nonlin_res = [solver.sol.force_coeffs; solver.sol.moment_coeffs; solver.sol.cm_unrefined_dist]
                     @test nonlin_res ≉ baseline_res
                     @test coeff_nonlin_res ≉ baseline_res
 
@@ -250,7 +250,7 @@ end
 
                 # Get baseline results
                 baseline_res = VortexStepMethod.solve!(solver, body_aero; log=false)
-                baseline_res = [solver.sol.force; solver.sol.moment; solver.sol.unrefined_moment_dist]
+                baseline_res = [solver.sol.force; solver.sol.moment; solver.sol.moment_unrefined_dist]
 
                 # Should match the linearization result
                 @test baseline_res ≈ lin_res_combo
@@ -277,7 +277,7 @@ end
 
                 # Get nonlinear solution with perturbation
                 nonlin_res = VortexStepMethod.solve!(solver, body_aero; log=false)
-                nonlin_res = [solver.sol.force; solver.sol.moment; solver.sol.unrefined_moment_dist]
+                nonlin_res = [solver.sol.force; solver.sol.moment; solver.sol.moment_unrefined_dist]
 
                 # Compute linearized prediction using our specialized Jacobian
                 lin_prediction = lin_res_combo + jac_combo * perturbation

test/ram_geometry/test_kite_geometry.jl

@@ -195,8 +195,8 @@ using Serialization
         original_te_point = copy(body_aero.panels[i].TE_point_1)
 
         # Apply deformation with non-zero angles
-        theta_dist = fill(deg2rad(30.0), wing.n_unrefined_sections)  # 30 degrees twist for all sections
-        delta_dist = fill(deg2rad(5.0), wing.n_unrefined_sections)   # 5 degrees trailing edge deflection for all sections
+        theta_dist = fill(deg2rad(30.0), wing.n_panels)  # 30 degrees twist for all panels
+        delta_dist = fill(deg2rad(5.0), wing.n_panels)   # 5 degrees TE deflection for all panels
 
         VortexStepMethod.deform!(wing, theta_dist, delta_dist)
         VortexStepMethod.reinit!(body_aero)

test/runtests.jl

@@ -16,7 +16,7 @@ end
 function should_run_test(test_path::String)
     isempty(test_patterns) && return true
     for pattern in test_patterns
-        # Match directory (e.g., "solver") or specific file (e.g., "test_group_coefficients")
+        # Match directory (e.g., "solver") or specific file (e.g., "test_unrefined_dist")
         if occursin(pattern, test_path)
             return true
         end
@@ -45,7 +45,7 @@ end::Bool
     should_run_test("ram_geometry/test_kite_geometry.jl") && include("ram_geometry/test_kite_geometry.jl")
     should_run_test("settings/test_settings.jl") && include("settings/test_settings.jl")
     should_run_test("solver/test_solver.jl") && include("solver/test_solver.jl")
-    should_run_test("solver/test_group_coefficients.jl") && include("solver/test_group_coefficients.jl")
+    should_run_test("solver/test_unrefined_dist.jl") && include("solver/test_unrefined_dist.jl")
     should_run_test("VortexStepMethod/test_VortexStepMethod.jl") && include("VortexStepMethod/test_VortexStepMethod.jl")
     should_run_test("wake/test_wake.jl") && include("wake/test_wake.jl")
     should_run_test("wing_geometry/test_wing_geometry.jl") && include("wing_geometry/test_wing_geometry.jl")

test/wing_geometry/test_wing_geometry.jl

@@ -341,7 +341,7 @@ end
             span = 10.0
 
             wing = Wing(n_panels; spanwise_distribution=LINEAR)
-            # 3 sections = 2 unrefined panels
+            # 3 sections
             add_section!(wing, [0.0, span/2, 0.0], [1.0, span/2, 0.0], INVISCID)
             add_section!(wing, [0.0, 0.0, 0.0], [1.0, 0.0, 0.0], INVISCID)
             add_section!(wing, [0.0, -span/2, 0.0], [1.0, -span/2, 0.0], INVISCID)
@@ -350,8 +350,8 @@ end
 
             @test length(wing.refined_panel_mapping) == n_panels
 
-            # Manually verify each refined panel is mapped to its closest unrefined panel
-            n_unrefined_panels = length(wing.unrefined_sections) - 1
+            # Manually verify each refined panel is mapped to its closest unrefined section
+            n_unrefined_sections = length(wing.unrefined_sections)
             for refined_panel_idx in 1:n_panels
                 # Calculate refined panel center
                 le_mid = (wing.refined_sections[refined_panel_idx].LE_point +
@@ -360,20 +360,18 @@ end
                          wing.refined_sections[refined_panel_idx+1].TE_point) / 2
                 refined_center = (le_mid + te_mid) / 2
 
-                # Find closest unrefined panel manually
+                # Find closest unrefined section manually
                 min_dist = Inf
                 closest_idx = 1
-                for unrefined_panel_idx in 1:n_unrefined_panels
-                    le_mid_unref = (wing.unrefined_sections[unrefined_panel_idx].LE_point +
-                                   wing.unrefined_sections[unrefined_panel_idx+1].LE_point) / 2
-                    te_mid_unref = (wing.unrefined_sections[unrefined_panel_idx].TE_point +
-                                   wing.unrefined_sections[unrefined_panel_idx+1].TE_point) / 2
-                    unrefined_center = (le_mid_unref + te_mid_unref) / 2
+                for unrefined_section_idx in 1:n_unrefined_sections
+                    le_point = wing.unrefined_sections[unrefined_section_idx].LE_point
+                    te_point = wing.unrefined_sections[unrefined_section_idx].TE_point
+                    unrefined_center = (le_point + te_point) / 2
 
                     dist = norm(refined_center - unrefined_center)
                     if dist < min_dist
                         min_dist = dist
-                        closest_idx = unrefined_panel_idx
+                        closest_idx = unrefined_section_idx
                     end
                 end
 
@@ -387,7 +385,7 @@ end
             span = 20.0
 
             wing = Wing(n_panels; spanwise_distribution=COSINE)
-            # 4 sections = 3 unrefined panels
+            # 4 sections
             add_section!(wing, [0.0, span/2, 0.0], [1.0, span/2, 0.0], INVISCID)
             add_section!(wing, [0.0, span/6, 0.0], [1.0, span/6, 0.0], INVISCID)
             add_section!(wing, [0.0, -span/6, 0.0], [1.0, -span/6, 0.0], INVISCID)
@@ -397,8 +395,8 @@ end
 
             @test length(wing.refined_panel_mapping) == n_panels
 
-            # Verify each panel is mapped to its closest unrefined panel
-            n_unrefined_panels = length(wing.unrefined_sections) - 1
+            # Verify each panel is mapped to its closest unrefined section
+            n_unrefined_sections = length(wing.unrefined_sections)
             for refined_panel_idx in 1:n_panels
                 # Calculate refined panel center
                 le_mid = (wing.refined_sections[refined_panel_idx].LE_point +
@@ -407,20 +405,18 @@ end
                          wing.refined_sections[refined_panel_idx+1].TE_point) / 2
                 refined_center = (le_mid + te_mid) / 2
 
-                # Find closest unrefined panel manually
+                # Find closest unrefined section manually
                 min_dist = Inf
                 closest_idx = 1
-                for unrefined_panel_idx in 1:n_unrefined_panels
-                    le_mid_unref = (wing.unrefined_sections[unrefined_panel_idx].LE_point +
-                                   wing.unrefined_sections[unrefined_panel_idx+1].LE_point) / 2
-                    te_mid_unref = (wing.unrefined_sections[unrefined_panel_idx].TE_point +
-                                   wing.unrefined_sections[unrefined_panel_idx+1].TE_point) / 2
-                    unrefined_center = (le_mid_unref + te_mid_unref) / 2
+                for unrefined_section_idx in 1:n_unrefined_sections
+                    le_point = wing.unrefined_sections[unrefined_section_idx].LE_point
+                    te_point = wing.unrefined_sections[unrefined_section_idx].TE_point
+                    unrefined_center = (le_point + te_point) / 2
 
                     dist = norm(refined_center - unrefined_center)
                     if dist < min_dist
                         min_dist = dist
-                        closest_idx = unrefined_panel_idx
+                        closest_idx = unrefined_section_idx
                     end
                 end
 
@@ -433,7 +429,7 @@ end
             n_panels = 12
 
             wing = Wing(n_panels; spanwise_distribution=SPLIT_PROVIDED)
-            # 4 sections = 3 unrefined panels
+            # 4 sections
             add_section!(wing, [0.0, 6.0, 0.0], [1.0, 6.0, 0.0], INVISCID)
             add_section!(wing, [0.0, 2.0, 0.0], [1.0, 2.0, 0.0], INVISCID)
             add_section!(wing, [0.0, -2.0, 0.0], [1.0, -2.0, 0.0], INVISCID)
@@ -443,8 +439,8 @@ end
 
             @test length(wing.refined_panel_mapping) == n_panels
 
-            # Verify each panel is mapped to its closest unrefined panel
-            n_unrefined_panels = length(wing.unrefined_sections) - 1
+            # Verify each panel is mapped to its closest unrefined section
+            n_unrefined_sections = length(wing.unrefined_sections)
             for refined_panel_idx in 1:n_panels
                 # Calculate refined panel center
                 le_mid = (wing.refined_sections[refined_panel_idx].LE_point +
@@ -453,20 +449,18 @@ end
                          wing.refined_sections[refined_panel_idx+1].TE_point) / 2
                 refined_center = (le_mid + te_mid) / 2
 
-                # Find closest unrefined panel manually
+                # Find closest unrefined section manually
                 min_dist = Inf
                 closest_idx = 1
-                for unrefined_panel_idx in 1:n_unrefined_panels
-                    le_mid_unref = (wing.unrefined_sections[unrefined_panel_idx].LE_point +
-                                   wing.unrefined_sections[unrefined_panel_idx+1].LE_point) / 2
-                    te_mid_unref = (wing.unrefined_sections[unrefined_panel_idx].TE_point +
-                                   wing.unrefined_sections[unrefined_panel_idx+1].TE_point) / 2
-                    unrefined_center = (le_mid_unref + te_mid_unref) / 2
+                for unrefined_section_idx in 1:n_unrefined_sections
+                    le_point = wing.unrefined_sections[unrefined_section_idx].LE_point
+                    te_point = wing.unrefined_sections[unrefined_section_idx].TE_point
+                    unrefined_center = (le_point + te_point) / 2
 
                     dist = norm(refined_center - unrefined_center)
                     if dist < min_dist
                         min_dist = dist
-                        closest_idx = unrefined_panel_idx
+                        closest_idx = unrefined_section_idx
                     end
                 end