Merge branch 'SciML:master' into iss3707

Author: fchen121

.github/workflows/Downgrade.yml

@@ -0,0 +1,36 @@
+name: Downgrade
+on:
+  pull_request:
+    branches:
+      - master
+    paths-ignore:
+      - 'docs/**'
+      - 'benchmark/**'
+  push:
+    branches:
+      - master
+    paths-ignore:
+      - 'docs/**'
+      - 'benchmark/**'
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        downgrade_mode: ['alldeps']
+        julia-version: ['1.10']
+        group: ['InterfaceI']
+    steps:
+      - uses: actions/checkout@v4
+      - uses: julia-actions/setup-julia@v2
+        with:
+          version: ${{ matrix.julia-version }}
+      - uses: julia-actions/julia-downgrade-compat@v2
+        with:
+          skip: Pkg,TOML
+      - uses: julia-actions/julia-buildpkg@1
+      - uses: julia-actions/julia-runtest@1
+        with:
+          ALLOW_RERESOLVE: false
+        env:
+          GROUP: ${{ matrix.group }}

.github/workflows/Downstream.yml

@@ -45,7 +45,7 @@ jobs:
           - {user: Neuroblox, repo: Neuroblox.jl, group: All}
     steps:
       - uses: actions/checkout@v4
-      - uses: julia-actions/setup-julia@v1
+      - uses: julia-actions/setup-julia@v2
         with:
           version: ${{ matrix.julia-version }}
           arch: x64

.github/workflows/ReleaseTest.yml

@@ -29,7 +29,7 @@ jobs:
           - {package: Catalyst, group: All}
     steps:
       - uses: actions/checkout@v4
-      - uses: julia-actions/setup-julia@v1
+      - uses: julia-actions/setup-julia@v2
         with:
           version: ${{ matrix.julia-version }}
           arch: x64

Project.toml

@@ -1,7 +1,7 @@
 name = "ModelingToolkit"
 uuid = "961ee093-0014-501f-94e3-6117800e7a78"
 authors = ["Yingbo Ma <[email protected]>", "Chris Rackauckas <[email protected]> and contributors"]
-version = "10.13.0"
+version = "10.15.0"
 
 [deps]
 ADTypes = "47edcb42-4c32-4615-8424-f2b9edc5f35b"
@@ -41,7 +41,6 @@ LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 MLStyle = "d8e11817-5142-5d16-987a-aa16d5891078"
 Moshi = "2e0e35c7-a2e4-4343-998d-7ef72827ed2d"
 NaNMath = "77ba4419-2d1f-58cd-9bb1-8ffee604a2e3"
-NonlinearSolve = "8913a72c-1f9b-4ce2-8d82-65094dcecaec"
 OffsetArrays = "6fe1bfb0-de20-5000-8ca7-80f57d26f881"
 OrderedCollections = "bac558e1-5e72-5ebc-8fee-abe8a469f55d"
 OrdinaryDiffEqCore = "bbf590c4-e513-4bbe-9b18-05decba2e5d8"
@@ -117,7 +116,7 @@ EnumX = "1.0.4"
 ExprTools = "0.1.10"
 FMI = "0.14"
 FindFirstFunctions = "1"
-ForwardDiff = "0.10.3"
+ForwardDiff = "0.10.3, 1"
 FunctionWrappers = "1.1"
 FunctionWrappersWrappers = "0.1"
 Graphs = "1.5.2"
@@ -151,14 +150,14 @@ RecursiveArrayTools = "3.26"
 Reexport = "0.2, 1"
 RuntimeGeneratedFunctions = "0.5.9"
 SCCNonlinearSolve = "1.0.0"
-SciMLBase = "2.104.0"
+SciMLBase = "2.106.0"
 SciMLPublic = "1.0.0"
 SciMLStructures = "1.7"
 Serialization = "1"
 Setfield = "0.7, 0.8, 1"
 SimpleNonlinearSolve = "0.1.0, 1, 2"
 SparseArrays = "1"
-SpecialFunctions = "0.7, 0.8, 0.9, 0.10, 1.0, 2"
+SpecialFunctions = "1, 2"
 StaticArrays = "0.10, 0.11, 0.12, 1.0"
 StochasticDelayDiffEq = "1.10"
 StochasticDiffEq = "6.72.1"

README.md

@@ -46,7 +46,7 @@ eqs = [D(D(x)) ~ σ * (y - x),
     D(y) ~ x * (ρ - z) - y,
     D(z) ~ x * y - β * z]
 
-@mtkbuild sys = ODESystem(eqs, t)
+@mtkcompile sys = System(eqs, t)
 
 u0 = [D(x) => 2.0,
     x => 1.0,
@@ -83,13 +83,13 @@ eqs = [D(x) ~ σ * (y - x),
     D(y) ~ x * (ρ - z) - y,
     D(z) ~ x * y - β * z]
 
-@named lorenz1 = ODESystem(eqs, t)
-@named lorenz2 = ODESystem(eqs, t)
+@named lorenz1 = System(eqs, t)
+@named lorenz2 = System(eqs, t)
 
 @variables a(t)
 @parameters γ
 connections = [0 ~ lorenz1.x + lorenz2.y + a * γ]
-@mtkbuild connected = ODESystem(connections, t, systems = [lorenz1, lorenz2])
+@mtkcompile connected = System(connections, t, systems = [lorenz1, lorenz2])
 
 u0 = [lorenz1.x => 1.0,
     lorenz1.y => 0.0,

demo.jl

@@ -20,7 +20,7 @@ using ModelingToolkit: t_nounits as t, D_nounits as D
 eqs = [D(D(x)) ~ λ * x
        D(D(y)) ~ λ * y - g
        x^2 + y^2 ~ 1]
-@mtkbuild pend = System(eqs, t)
+@mtkcompile pend = System(eqs, t)
 prob = ODEProblem(pend, [x => -1, y => 0], (0.0, 10.0), [g => 1], guesses = [λ => 1])
 
 sol = solve(prob, FBDF())
@@ -37,7 +37,7 @@ eqs = [
     D(z) ~ x * y - β * z + 0.1z * a
 ]
 
-@mtkbuild sys1 = System(eqs, t)
+@mtkcompile sys1 = System(eqs, t)
 
 eqs = [
     D(x) ~ σ * (y - x),
@@ -49,7 +49,7 @@ noiseeqs = [0.1*x;
             0.1*y;
             0.1*z;;]
 
-@mtkbuild sys2 = SDESystem(eqs, noiseeqs, t)
+@mtkcompile sys2 = SDESystem(eqs, noiseeqs, t)
 
 u0 = [
     x => 1.0,
@@ -73,7 +73,7 @@ odeprob = ODEProblem(sys1, u0, (0.0, 10.0), p; check_compatibility = false)
 eqs = [0 ~ σ * (y - x),
     y ~ x * (ρ - z),
     β * z ~ x * y]
-@mtkbuild sys = System(eqs)
+@mtkcompile sys = System(eqs)
 
 ## ImplicitDiscrete Affects
 
@@ -83,7 +83,7 @@ eqs = [D(D(x)) ~ λ * x
        D(D(y)) ~ λ * y - g
        x^2 + y^2 ~ 1]
 c_evt = [t ~ 5.0] => [x ~ Pre(x) + 0.1]
-@mtkbuild pend = System(eqs, t, continuous_events = c_evt)
+@mtkcompile pend = System(eqs, t, continuous_events = c_evt)
 prob = ODEProblem(pend, [x => -1, y => 0], (0.0, 10.0), [g => 1], guesses = [λ => 1])
 
 sol = solve(prob, FBDF())
@@ -104,4 +104,4 @@ function SysC(; name)
     @named subsys = SysB(; var1 = x)
     return System([D(x) ~ x], t; systems = [subsys], name)
 end
-@mtkbuild sys = SysC()
+@mtkcompile sys = SysC()

docs/src/API/variables.md

@@ -337,6 +337,7 @@ ModelingToolkit also defines a plethora of custom operators.
 Pre
 Initial
 Shift
+EvalAt
 ```
 
 While not an operator, `ShiftIndex` is commonly used to use `Shift` operators in a more

docs/src/basics/Composition.md

@@ -126,8 +126,8 @@ sys = System(
 # ...
 # directly in the defaults argument
     defaults = Pair{Num, Any}[x => u,
-    y => σ,
-    z => u - 0.1])
+y => σ,
+z => u - 0.1])
 # by assigning to the parameter
 sys.y = u * 1.1
 ```

docs/src/basics/MTKLanguage.md

@@ -382,7 +382,7 @@ Refer the following example for different ways to define symbolic arrays.
         p1[1:4]
         p2[1:N]
         p3[1:N,
-            1:M] = 10,
+        1:M] = 10,
         [description = "A multi-dimensional array of arbitrary length with description"]
         (p4[1:N, 1:M] = 10),
         [description = "An alternate syntax for p3 to match the syntax of vanilla parameters macro"]

docs/src/examples/sparse_jacobians.md

@@ -27,16 +27,16 @@ function brusselator_2d_loop(du, u, p, t)
         jm1 = limit(i + 1, N), limit(i - 1, N), limit(j + 1, N),
         limit(j - 1, N)
         du[i,
-            j,
-            1] = alpha * (u[im1, j, 1] + u[ip1, j, 1] + u[i, jp1, 1] + u[i, jm1, 1] -
-                  4u[i, j, 1]) +
-                 B + u[i, j, 1]^2 * u[i, j, 2] - (A + 1) * u[i, j, 1] +
-                 brusselator_f(x, y, t)
+        j,
+        1] = alpha * (u[im1, j, 1] + u[ip1, j, 1] + u[i, jp1, 1] + u[i, jm1, 1] -
+                       4u[i, j, 1]) +
+                      B + u[i, j, 1]^2 * u[i, j, 2] - (A + 1) * u[i, j, 1] +
+                      brusselator_f(x, y, t)
         du[i,
-            j,
-            2] = alpha * (u[im1, j, 2] + u[ip1, j, 2] + u[i, jp1, 2] + u[i, jm1, 2] -
-                  4u[i, j, 2]) +
-                 A * u[i, j, 1] - u[i, j, 1]^2 * u[i, j, 2]
+        j,
+        2] = alpha * (u[im1, j, 2] + u[ip1, j, 2] + u[i, jp1, 2] + u[i, jm1, 2] -
+                       4u[i, j, 2]) +
+                      A * u[i, j, 1] - u[i, j, 1]^2 * u[i, j, 2]
     end
 end
 p = (3.4, 1.0, 10.0, step(xyd_brusselator))