Fix softening bug (#154)

* improve softening testing * fix bug and improve args handling
JuliaGeodynamics · Jan 24, 2024 · 7bca8f7 · 7bca8f7
1 parent b7d2750
commit 7bca8f7
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Showing 2 changed files with 24 additions and 12 deletions.
diff --git a/src/Softening/Softening.jl b/src/Softening/Softening.jl
@@ -10,20 +10,22 @@ struct LinearSoftening{T} <: AbstractSoftening
     lo::T
     max_value::T
     min_value::T
-    damage::T
+    slope::T
 
     function LinearSoftening(min_value::T, max_value::T, lo::T, hi::T) where T
-        damage = max_value + (max_value - min_value) / (hi - lo)
-        new{T}(hi, lo, max_value, min_value, damage)
+        slope = (max_value - min_value) / (hi - lo)
+        new{T}(hi, lo, max_value, min_value, slope)
     end
 end
 
 LinearSoftening(min_max_values::NTuple{2, T}, lo_hi::NTuple{2, T}) where T = LinearSoftening(min_max_values..., lo_hi...)
 
-function (softening::LinearSoftening)(max_value, softening_var::T) where T
+@inline (softening::LinearSoftening)(args::Vararg{Any, N}) where N = softening(promote(args...)...)
+
+@inline function (softening::LinearSoftening)(max_value::T, softening_var::T) where T
 
     softening_var ≥ softening.hi && return softening.min_value
-    softening_var ≤ softening.lo && return T(max_value)
+    softening_var ≤ softening.lo && return max_value
 
-    return softening_var * softening.damage
+    return softening.min_value + (one(T) - softening_var) * softening.slope
 end
diff --git a/test/test_Softening.jl b/test/test_Softening.jl
@@ -8,18 +8,29 @@ using GeoParams, Test
     @test x === soft(x, rand())
 
     # Test LinearSoftening
-    min_v, max_v = 15e0, 30e0
+    min_v, max_v = rand()*15, (rand()+1)*15
     lo, hi = 0.0, 1.0
 
     @test LinearSoftening(min_v, max_v, lo, hi) === LinearSoftening((min_v, max_v), (lo, hi))
 
     soft_ϕ = LinearSoftening(min_v, max_v, lo, hi)
 
-    @test soft_ϕ(30, 1) == min_v
-    @test soft_ϕ(30, 0) == max_v
-    @test soft_ϕ(30, 0.5) == 0.5 * (min_v + max_v)
+    @test soft_ϕ(max_v, 1) == min_v
+    @test soft_ϕ(max_v, 0) == max_v
+    @test soft_ϕ(max_v, 0.5) ≈ 0.5 * (min_v + max_v)
+
+    min_v, max_v = 20e0, 20e0
+    soft_ϕ = LinearSoftening(min_v, max_v, lo, hi)
+
+    @test soft_ϕ(max_v, 1) == 20e0
+    @test soft_ϕ(max_v, 0) == 20e0
+    @test soft_ϕ(max_v, 0.5) == 20e0
 
     # test Drucker-Prager with softening
+    min_v, max_v = 15e0, 30e0
+    lo, hi = 0.0, 1.0
+    soft_ϕ = LinearSoftening(min_v, max_v, lo, hi)
+
     τII = 20e6
     P = 1e6
     args = (P=P, τII=τII)
@@ -51,5 +62,4 @@ using GeoParams, Test
     @test compute_yieldfunction(p2, args) ≈ 1.95e7
     @test compute_yieldfunction(p3, args) ≈ 1.974118095489748e7
 
-end
-
+end