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1.5.0-DEV-dfcba8768f.log
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Julia Version 1.5.0-DEV.13
Commit dfcba8768f (2020-01-06 06:02 UTC)
Platform Info:
OS: Linux (x86_64-linux-gnu)
CPU: Intel(R) Xeon(R) Silver 4114 CPU @ 2.20GHz
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-8.0.1 (ORCJIT, skylake)
Environment:
JULIA_DEPOT_PATH = ::/usr/local/share/julia
Resolving package versions...
Installed SortingAlgorithms ─────────── v0.3.1
Installed Parsers ───────────────────── v0.3.10
Installed Roots ─────────────────────── v0.8.4
Installed ConstructionBase ──────────── v1.0.0
Installed StaticArrays ──────────────── v0.12.1
Installed Sundials ──────────────────── v3.8.1
Installed IterativeSolvers ──────────── v0.8.1
Installed Modia ─────────────────────── v0.3.0
Installed Tables ────────────────────── v0.2.11
Installed RecursiveFactorization ────── v0.1.0
Installed DataStructures ────────────── v0.17.7
Installed ModiaMath ─────────────────── v0.5.2
Installed FunctionWrappers ──────────── v1.0.0
Installed RecipesBase ───────────────── v0.7.0
Installed RecursiveArrayTools ───────── v1.2.1
Installed ChainRulesCore ────────────── v0.4.0
Installed ZygoteRules ───────────────── v0.2.0
Installed DataFrames ────────────────── v0.20.0
Installed Missings ──────────────────── v0.4.3
Installed BinaryProvider ────────────── v0.5.8
Installed Requires ──────────────────── v1.0.0
Installed MacroTools ────────────────── v0.5.3
Installed TreeViews ─────────────────── v0.3.0
Installed TableTraits ───────────────── v1.0.0
Installed Compat ────────────────────── v2.2.0
Installed Parameters ────────────────── v0.12.0
Installed DataValueInterfaces ───────── v1.0.0
Installed DiffEqDiffTools ───────────── v1.7.0
Installed Reexport ──────────────────── v0.2.0
Installed ArrayInterface ────────────── v2.3.1
Installed DocStringExtensions ───────── v0.8.1
Installed Unitful ───────────────────── v0.18.0
Installed JSON ──────────────────────── v0.21.0
Installed DataAPI ───────────────────── v1.1.0
Installed OrderedCollections ────────── v1.1.0
Installed MuladdMacro ───────────────── v0.2.1
Installed InvertedIndices ───────────── v1.0.0
Installed DiffEqBase ────────────────── v6.10.2
Installed CategoricalArrays ─────────── v0.7.6
Installed PooledArrays ──────────────── v0.5.3
Installed IteratorInterfaceExtensions ─ v1.0.0
Updating `~/.julia/environments/v1.5/Project.toml`
[cb905087] + Modia v0.3.0
Updating `~/.julia/environments/v1.5/Manifest.toml`
[4fba245c] + ArrayInterface v2.3.1
[b99e7846] + BinaryProvider v0.5.8
[324d7699] + CategoricalArrays v0.7.6
[d360d2e6] + ChainRulesCore v0.4.0
[34da2185] + Compat v2.2.0
[187b0558] + ConstructionBase v1.0.0
[9a962f9c] + DataAPI v1.1.0
[a93c6f00] + DataFrames v0.20.0
[864edb3b] + DataStructures v0.17.7
[e2d170a0] + DataValueInterfaces v1.0.0
[2b5f629d] + DiffEqBase v6.10.2
[01453d9d] + DiffEqDiffTools v1.7.0
[ffbed154] + DocStringExtensions v0.8.1
[069b7b12] + FunctionWrappers v1.0.0
[41ab1584] + InvertedIndices v1.0.0
[42fd0dbc] + IterativeSolvers v0.8.1
[82899510] + IteratorInterfaceExtensions v1.0.0
[682c06a0] + JSON v0.21.0
[1914dd2f] + MacroTools v0.5.3
[e1d29d7a] + Missings v0.4.3
[cb905087] + Modia v0.3.0
[67ccffd1] + ModiaMath v0.5.2
[46d2c3a1] + MuladdMacro v0.2.1
[bac558e1] + OrderedCollections v1.1.0
[d96e819e] + Parameters v0.12.0
[69de0a69] + Parsers v0.3.10
[2dfb63ee] + PooledArrays v0.5.3
[3cdcf5f2] + RecipesBase v0.7.0
[731186ca] + RecursiveArrayTools v1.2.1
[f2c3362d] + RecursiveFactorization v0.1.0
[189a3867] + Reexport v0.2.0
[ae029012] + Requires v1.0.0
[f2b01f46] + Roots v0.8.4
[a2af1166] + SortingAlgorithms v0.3.1
[90137ffa] + StaticArrays v0.12.1
[c3572dad] + Sundials v3.8.1
[3783bdb8] + TableTraits v1.0.0
[bd369af6] + Tables v0.2.11
[a2a6695c] + TreeViews v0.3.0
[1986cc42] + Unitful v0.18.0
[700de1a5] + ZygoteRules v0.2.0
[2a0f44e3] + Base64
[ade2ca70] + Dates
[8bb1440f] + DelimitedFiles
[8ba89e20] + Distributed
[9fa8497b] + Future
[b77e0a4c] + InteractiveUtils
[76f85450] + LibGit2
[8f399da3] + Libdl
[37e2e46d] + LinearAlgebra
[56ddb016] + Logging
[d6f4376e] + Markdown
[a63ad114] + Mmap
[44cfe95a] + Pkg
[de0858da] + Printf
[3fa0cd96] + REPL
[9a3f8284] + Random
[ea8e919c] + SHA
[9e88b42a] + Serialization
[1a1011a3] + SharedArrays
[6462fe0b] + Sockets
[2f01184e] + SparseArrays
[10745b16] + Statistics
[4607b0f0] + SuiteSparse
[8dfed614] + Test
[cf7118a7] + UUIDs
[4ec0a83e] + Unicode
Building Sundials → `~/.julia/packages/Sundials/MllUG/deps/build.log`
Updating `/tmp/jl_xRUj9G/Project.toml`
[no changes]
Updating `/tmp/jl_xRUj9G/Manifest.toml`
[no changes]
Testing Modia
Updating `/tmp/jl_FObxk9/Project.toml`
[no changes]
Updating `/tmp/jl_FObxk9/Manifest.toml`
[no changes]
Running sandbox
Status `/tmp/jl_FObxk9/Project.toml`
[864edb3b] DataStructures v0.17.7
[682c06a0] JSON v0.21.0
[cb905087] Modia v0.3.0
[67ccffd1] ModiaMath v0.5.2
[90137ffa] StaticArrays v0.12.1
[1986cc42] Unitful v0.18.0
[ade2ca70] Dates
[37e2e46d] LinearAlgebra
[d6f4376e] Markdown
[de0858da] Printf
[2f01184e] SparseArrays
[8dfed614] Test
Welcome to Modia - Dynamic Modeling and Simulation with Julia
Version 0.3.0 (2019-04-07)
Type "?Modia" for help.
Importing ModiaMath Version 0.5.2 (2019-07-10)
PyPlot not available (plot commands will be ignored).
Try to install PyPlot. See hints here:
https://github.com/ModiaSim/ModiaMath.jl/wiki/Installing-PyPlot-in-a-robust-way.
Test match
assign = [8, 1, 2, 7, 4, 5, 3, 0]
Singular system
assign = [0, 3, 1, 0]
(invAssign, unAssignedVariables) = ([3, 0, 2], [1, 4])
(ass, unAssignedEquations) = ([0, 3, 1, 0], [2])
Test Tarjans strong connect
components = Any[Any[6], Any[7, 5, 4, 3], Any[8, 2, 1]]
Fixed-length pendulum
assign = [5, 4, 1, 2, 0, 0, 3, 0, 0]
Assigned original equations:
Test diagnostics for too many equations
Gbig = Any[[3, 5], [4, 6], [1, 7, 9], [2, 8, 9], [1, 2], [1, 10], [2, 10]]
EGbig = Any[[3, 5, 11], [4, 6, 11], [1, 7, 9, 11], [2, 8, 9, 11], [1, 2, 11], [1, 10, 11], [2, 10, 11], [1, 5, 11], [2, 6, 11], [3, 7, 11], [4, 8, 11]]
componentsBig = Any[Any[5, 10, 3, 4, 11, 2, 9, 7, 6, 8, 1]]
Test diagnostics for too many variables
Gbig = Any[[3, 5], [4, 6], [1, 7, 9], [10, 8, 9], [1, 10]]
EGbig = Any[[3, 5], [4, 6], [1, 7, 9], [10, 8, 9], [1, 10], [1, 5], [2, 6], [3, 7], [4, 8], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]]
componentsBig = Any[Any[5, 4, 9, 2, 7, 10, 6, 3, 8, 1]]
Test diagnostics for too few equations
Gbig = Any[[3, 5], [4, 6], [1, 7, 9], [2, 8, 9]]
EGbig = Any[[3, 5], [4, 6], [1, 7, 9], [2, 8, 9], [1, 5], [2, 6], [3, 7], [4, 8], [1, 2, 3, 4, 5, 6, 7, 8, 9]]
componentsBig = Any[Any[6, 2, 8, 4, 9, 7, 3, 5, 1]]
Check consistency of equations by matching extended equation set
EG = Any[[3, 5], [4, 6], [1, 7, 9], [2, 8, 9], [1, 2], [1, 5], [2, 6], [3, 7], [4, 8]]
assign = [5, 7, 1, 9, 6, 2, 8, 4, 3]
Perform index reduction
G = Any[[3, 5], [4, 6], [1, 7, 9], [2, 8, 9], [1, 2], [1, 2, 5, 6], [3, 5, 7, 10], [4, 6, 8, 11], [1, 2, 5, 6, 10, 11]]
assign = [0, 0, 0, 0, 1, 2, 7, 4, 3, 9, 8]
A = [5, 6, 7, 8, 10, 11, 0, 0, 0, 0, 0]
B = [7, 8, 0, 0, 6, 9, 0, 0, 0]
------------------------------------------------------
vActive = Bool[0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1]
assign = [0, 5, 0, 2, 1, 6, 7, 4, 3, 9, 8]
components = Any[Any[1], Any[5], Any[6], Any[2], Any[4, 8, 9, 7, 3]]
------------------------------------------------------
All unknowns:
All equations:
Assigned equations:
Sorted equations:
Build augmented system.
AG = Any[[3, 5], [4, 6], [1, 7, 9], [2, 8, 9], [1, 2], [1, 2, 5, 6], [3, 5, 7, 10], [4, 6, 8, 11], [1, 2, 5, 6, 10, 11], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]]
assignAG = [5, 4, 1, 2, 6, 8, 3, 10, 11, 7, 9]
componentsAG = Any[Any[11, 3, 7, 9, 8, 2, 10, 4, 5, 6, 1]]
Assigned augmented equations:
Sorted augmented equations:
Set initial conditions on x and y. Should fail.
IG1 = Any[[3, 5], [4, 6], [1, 7, 9], [2, 8, 9], [1, 2], [1, 2, 5, 6], [3, 5, 7, 10], [4, 6, 8, 11], [1, 2, 5, 6, 10, 11], [1], [2]]
assignIG1 = [10, 5, 1, 2, 6, 8, 3, 4, 0, 7, 9]
componentsIG1 = Any[Any[10], Any[5], Any[4], Any[3], Any[7, 9, 2, 8, 6, 1], Any[11]]
Set initial conditions on x and w.
IG2 = Any[[3, 5], [4, 6], [1, 7, 9], [2, 8, 9], [1, 2], [1, 2, 5, 6], [3, 5, 7, 10], [4, 6, 8, 11], [1, 2, 5, 6, 10, 11], [1], [3]]
assignIG2 = [10, 5, 11, 2, 1, 6, 3, 8, 4, 7, 9]
componentsIG2 = Any[Any[11], Any[1], Any[10], Any[5], Any[6], Any[2], Any[7, 9, 8, 4, 3]]
Sorted IG2 equations:
Set initial conditions on w and z.
IG3 = Any[[3, 5], [4, 6], [1, 7, 9], [2, 8, 9], [1, 2], [1, 2, 5, 6], [3, 5, 7, 10], [4, 6, 8, 11], [1, 2, 5, 6, 10, 11], [3], [4]]
assignIG3 = [6, 5, 10, 11, 1, 2, 3, 8, 4, 7, 9]
componentsIG3 = Any[Any[10], Any[1], Any[11], Any[2], Any[5, 6], Any[7, 9, 8, 4, 3]]
Sorted IG3 equations:
Fixed-length pendulum
Perform index reduction
Set initial conditions on x and w.
IG = Any[[3, 5], [4, 6], [1, 7, 9], [2, 8, 9], [1, 2], [1, 2, 5, 6], [3, 5, 7, 10], [4, 6, 8, 11], [1, 2, 5, 6, 10, 11], [1], [3]]
assignIG = [10, 5, 11, 2, 1, 6, 3, 8, 4, 7, 9]
componentsIG = Any[Any[11], Any[1], Any[10], Any[5], Any[6], Any[2], Any[7, 9, 8, 4, 3]]
Exothermic Reactor Model
assign = [0, 0, 1, 7, 3, 2, 8, 6]
A = [3, 4, 7, 0, 8, 0, 0, 0]
B = [6, 0, 7, 5, 8, 0, 0, 0]
components = Any[Any[3], Any[1], Any[8], Any[6], Any[7], Any[2], Any[4], Any[5]]
----------------------
----------------------
Big tests, n = 5000
Big test: diagonal
0.044262 seconds (76.44 k allocations: 51.765 MiB, 20.66% gc time)
Big test: band
0.044734 seconds (108.39 k allocations: 52.149 MiB, 13.95% gc time)
Big test: full, n=1000
0.957783 seconds (4.80 M allocations: 105.997 MiB, 2.69% gc time)
Test solve
Solve: x from: y = x
x = y
Solve: x from: y = x + z
x = y - z
Solve: x from: y = x + z + v + w
x = y - (z + v + w)
Solve: z from: y = x + z + v + w
z = (y - x) - (v + w)
Solve: v from: y = x + z + v + w
v = ((y - x) - z) - w
Solve: w from: y = x + z + v + w
w = ((y - x) - z) - v
Solve: x from: y = x - z
x = y + z
Solve: x from: y = (x - z) - w
x = (y + w) + z
Solve: x from: y = -(x, z, v, w)
x = y + (z + v + w)
Solve: v from: y = -(x, z, v, w)
v = ((x - y) - z) - w
Solve: x from: y = z - x
x = z - y
Solve: x from: y = x * z
x = y / z
Solve: x from: y = x * z * z * z
x = y / (z * z * z)
Solve: x from: y = /(x, z, w)
x = y * (z * w)
Solve: z from: y = /(x, z, w)
z = (x / y) / w
Solve: x from: y = x / z
x = y * z
Solve: z from: y = x / z
z = x / y
Solve: x from: y = x \ z
NOT SOLVED
x \ z = y
----------------------
Test differentiate
Equation: x + 5 + z = w
Differentiated: der(x) + der(z) = der(w)
Equation: der(x) + der(z) = der(w)
Differentiated: der(der(x)) + der(der(z)) = der(der(w))
Equation: +x = w
Differentiated: der(x) = der(w)
Equation: 2 + 3 = w
Differentiated: 0.0 = der(w)
Equation: -x = w
Differentiated: -(der(x)) = der(w)
Equation: (x - 5) - z = w
Differentiated: der(x) - der(z) = der(w)
Equation: 5x = w
Differentiated: 5 * der(x) = der(w)
Equation: x * 5 * z = w
Differentiated: der(x) * 5 * z + x * 5 * der(z) = der(w)
Equation: 4 * 5 * 6 = w
Differentiated: 0.0 = der(w)
Equation: y = x / y
Differentiated: der(y) = der(x) / y + (x / y ^ 2) * der(y)
Equation: y = x / 5
Differentiated: der(y) = der(x) / 5
Equation: y = 5 / y
Differentiated: der(y) = (5 / y ^ 2) * der(y)
Equation: y = [1, x]
Differentiated: der(y) = [0.0, der(x)]
Equation: y = [2x 3x; 4x 5x]
Differentiated: der(y) = [2 * der(x) 3 * der(x); 4 * der(x) 5 * der(x)]
Equation: y = [2x 3x; 4x 5x] * [1, x]
Differentiated: der(y) = [2 * der(x) 3 * der(x); 4 * der(x) 5 * der(x)] * [1, x] + [2x 3x; 4x 5x] * [0.0, der(x)]
Equation: y = transpose(B) + B´
Differentiated: der(y) = transpose(der(B)) + der(B´)
Equation: y = x[5, 6]
Differentiated: der(y) = (der(x))[5, 6]
Equation: y = x[5:7]
Differentiated: der(y) = (der(x))[5:7]
Equation: y = sin(x)
Differentiated: der(y) = cos(x) * der(x)
Equation: y = cos(x)
Differentiated: der(y) = -(sin(x)) * der(x)
Equation: y = tan(x)
Differentiated: der(y) = (1 / cos(x) ^ 2) * der(x)
Equation: y = exp(x)
Differentiated: der(y) = exp(x) * der(x)
Equation: y = x ^ y
Differentiated: der(y) = y * x ^ (y - 1) * der(x) + x ^ y * log(x) * der(y)
Equation: y = log(x)
Differentiated: der(y) = (1 / x) * der(x)
Equation: y = asin(x)
Differentiated: der(y) = (1 / sqrt(1 - x ^ 2)) * der(x)
Equation: y = acos(x)
Differentiated: der(y) = (-1 / sqrt(1 - x ^ 2)) * der(x)
Equation: y = atan(x)
Differentiated: der(y) = (1 / (1 + x ^ 2)) * der(x)
Equation: y = f(x, 5, z)
Derivative function f_der_1 not found.
Derivative function f_der_3 not found.
Differentiated: der(y) = f_der_1(x, 5, z) * der(x) + f_der_3(x, 5, z) * der(z)
Equation: y = f(x, 5, g(z))
Derivative function f_der_1 not found.
Derivative function g_der_1 not found.
Derivative function f_der_3 not found.
Differentiated: der(y) = f_der_1(x, 5, g(z)) * der(x) + f_der_3(x, 5, g(z)) * (g_der_1(z) * der(z))
Equation: y = if true
x
else
y
end
Differentiated: der(y) = if true
der(x)
else
der(y)
end
Equation: y = time
Differentiated: der(y) = 1.0
Equation: y = a * x
Differentiated: der(y) = a * der(x)
----------------------
... Test two coupled inertias (all unknowns can be solved for)
Variables of _x vector (length=2):
_x[1]: J1_phi
_x[2]: der(J1_phi) # = der(_x[1])
Variables of _der_x vector (length=2):
_der_x[1]: --- # = _x[2] = der(J1_phi)
_der_x[2]: der2(J1_phi)
Sorted equations (length(_r) = 2, nc = 0):
_r[1] = _der_x[1] - _x[2]
J2_phi = < solved from eq.5 >
der(J2_phi) = < solved from eq.7 = der(eq.5) >
J1_w = < solved from eq.1 >
J2_w = < solved from eq.3 >
der2(J2_phi) = < solved from eq.10 = der2(eq.5) >
der(J1_w) = < solved from eq.8 = der(eq.1) >
der(J2_w) = < solved from eq.9 = der(eq.3) >
J2_tau = < solved from eq.4 >
J1_tau = < solved from eq.6 >
_r[2] = < residue of eq.2 >
... Test two coupled inertias (only a subset of unknowns can be solved for)
Variables of _x vector (length=2):
_x[1]: J2_phi
_x[2]: der(J2_phi) # = der(_x[1])
Variables of _der_x vector (length=2):
_der_x[1]: --- # = _x[2] = der(J2_phi)
_der_x[2]: der2(J2_phi)
Sorted equations (length(_r) = 2, nc = 0):
_r[1] = _der_x[1] - _x[2]
J1_phi = < solved from eq.5 >
der(J1_phi) = < solved from eq.7 = der(eq.5) >
J1_w = < solved from eq.1 >
J2_w = < solved from eq.3 >
der2(J1_phi) = < solved from eq.10 = der2(eq.5) >
der(J1_w) = < solved from eq.8 = der(eq.1) >
der(J2_w) = < solved from eq.9 = der(eq.3) >
J2_tau = < solved from eq.4 >
J1_tau = < solved from eq.6 >
_r[2] = < residue of eq.2 >
... Test two coupled inertias (no unknowns can be solved for)
Variables of _x vector (length=9):
_x[1]: J1_phi
_x[2]: J2_phi
_x[3]: der(J1_phi) # = der(_x[1])
_x[4]: der(J2_phi) # = der(_x[2])
_x[5]: J2_w
_x[6]: J1_w
_x[7]: --- # integral of lambda variable
_x[8]: --- # integral of lambda variable
_x[9]: --- # integral of mue variable
Variables of _der_x vector (length=9):
_der_x[1]: --- # = _x[3] = der(J1_phi)
_der_x[2]: --- # = _x[4] = der(J2_phi)
_der_x[3]: der2(J1_phi)
_der_x[4]: der2(J2_phi)
_der_x[5]: der(J2_w)
_der_x[6]: der(J1_w)
_der_x[7]: J2_tau # lambda variable
_der_x[8]: J1_tau # lambda variable
_der_x[9]: --- # mue variable associated with equation eq.7 = der(eq.5)
Sorted equations (length(_r) = 9, nc = 4):
_r[1] = _der_x[1] - _x[3]
_r[2] = _der_x[2] - _x[4]
_r[6] = < residue of eq.5 >
_r[7] = < residue of eq.1 >
_r[9] = < residue of eq.7 = der(eq.5) >
_r[8] = < residue of eq.3 >
_r[3] = < residue of eq.4 >
_r[4] = < residue of eq.6 >
_r[5] = < residue of eq.2 >
... Test simple sliding mass model with Tearing
Variables of _x vector (length=3):
_x[1]: s
_x[2]: der(s) # = der(_x[1])
_x[3]: sf
Variables of _der_x vector (length=3):
_der_x[1]: --- # = _x[2] = der(s)
_der_x[2]: der2(s)
_der_x[3]: der(sf)
Sorted equations (length(_r) = 3, nc = 0):
_r[1] = _der_x[1] - _x[2]
r = < solved from eq.1 >
der(r) = < solved from eq.6 = der(eq.1) >
v = < solved from eq.2 >
der2(r) = < solved from eq.7 = der2(eq.1) >
der(v) = < solved from eq.8 = der(eq.2) >
u = < solved from eq.5 >
_r[2] = < residue of eq.9 >
f = < solved from eq.3 >
_r[3] = < residue of eq.4 >
... Test Multi-Index DAE without tearing
Variables of _x vector (length=21):
_x[1]: x7
_x[2]: x6
_x[3]: der(x7) # = der(_x[1])
_x[4]: der(x6) # = der(_x[2])
_x[5]: der2(x7) # = der(_x[3])
_x[6]: der2(x6) # = der(_x[4])
_x[7]: x1
_x[8]: x2
_x[9]: x3
_x[10]: der(x1) # = der(_x[7])
_x[11]: der(x2) # = der(_x[8])
_x[12]: der(x3) # = der(_x[9])
_x[13]: x4
_x[14]: x8 # algebraic variable
_x[15]: --- # integral of lambda variable
_x[16]: --- # integral of mue variable
_x[17]: --- # integral of mue variable
_x[18]: --- # integral of mue variable
_x[19]: --- # integral of mue variable
_x[20]: --- # integral of mue variable
_x[21]: --- # integral of mue variable
Variables of _der_x vector (length=21):
_der_x[1]: --- # = _x[3] = der(x7)
_der_x[2]: --- # = _x[4] = der(x6)
_der_x[3]: --- # = _x[5] = der2(x7)
_der_x[4]: --- # = _x[6] = der2(x6)
_der_x[5]: der3(x7)
_der_x[6]: der3(x6)
_der_x[7]: --- # = _x[10] = der(x1)
_der_x[8]: --- # = _x[11] = der(x2)
_der_x[9]: --- # = _x[12] = der(x3)
_der_x[10]: der2(x1)
_der_x[11]: der2(x2)
_der_x[12]: der2(x3)
_der_x[13]: der(x4)
_der_x[14]: --- # derivative of algebraic variable
_der_x[15]: x5 # lambda variable
_der_x[16]: --- # mue variable associated with equation eq.14 = der(eq.6)
_der_x[17]: --- # mue variable associated with equation eq.15 = der(eq.7)
_der_x[18]: --- # mue variable associated with equation eq.16 = der2(eq.6)
_der_x[19]: --- # mue variable associated with equation eq.17 = der2(eq.7)
_der_x[20]: --- # mue variable associated with equation eq.9 = der(eq.1)
_der_x[21]: --- # mue variable associated with equation eq.11 = der(eq.2)
Sorted equations (length(_r) = 21, nc = 12):
_r[1] = _der_x[1] - _x[3]
_r[2] = _der_x[2] - _x[4]
_r[3] = _der_x[3] - _x[5]
_r[4] = _der_x[4] - _x[6]
_r[5] = _der_x[7] - _x[10]
_r[6] = _der_x[8] - _x[11]
_r[7] = _der_x[9] - _x[12]
_r[11] = < residue of eq.6 >
_r[12] = < residue of eq.7 >
_r[16] = < residue of eq.14 = der(eq.6) >
_r[17] = < residue of eq.15 = der(eq.7) >
_r[18] = < residue of eq.16 = der2(eq.6) >
_r[19] = < residue of eq.17 = der2(eq.7) >
_r[13] = < residue of eq.1 >
_r[14] = < residue of eq.2 >
_r[20] = < residue of eq.9 = der(eq.1) >
_r[21] = < residue of eq.11 = der(eq.2) >
_r[15] = < residue of eq.3 >
_r[10] = < residue of eq.8 >
_r[8] = < residue of eq.4 >
_r[9] = < residue of eq.5 >
... Test Multi-Index DAE WITH tearing
Variables of _x vector (length=8):
_x[1]: x7
_x[2]: der(x7) # = der(_x[1])
_x[3]: der2(x7) # = der(_x[2])
_x[4]: x2
_x[5]: der(x2) # = der(_x[4])
_x[6]: x8 # algebraic variable
_x[7]: --- # integral of mue variable
_x[8]: --- # integral of mue variable
Variables of _der_x vector (length=8):
_der_x[1]: --- # = _x[2] = der(x7)
_der_x[2]: --- # = _x[3] = der2(x7)
_der_x[3]: der3(x7)
_der_x[4]: --- # = _x[5] = der(x2)
_der_x[5]: der2(x2)
_der_x[6]: --- # derivative of algebraic variable
_der_x[7]: --- # mue variable associated with equation eq.15 = der(eq.7)
_der_x[8]: --- # mue variable associated with equation eq.17 = der2(eq.7)
Sorted equations (length(_r) = 8, nc = 4):
_r[1] = _der_x[1] - _x[2]
_r[2] = _der_x[2] - _x[3]
_r[3] = _der_x[4] - _x[5]
x6 = < solved from eq.6 >
_r[6] = < residue of eq.7 >
der(x6) = < solved from eq.14 = der(eq.6) >
_r[7] = < residue of eq.15 = der(eq.7) >
der2(x6) = < solved from eq.16 = der2(eq.6) >
_r[8] = < residue of eq.17 = der2(eq.7) >
x1 = < solved from eq.1 >
x3 = < solved from eq.2 >
der(x1) = < solved from eq.9 = der(eq.1) >
der(x3) = < solved from eq.11 = der(eq.2) >
x4 = < solved from eq.3 >
der3(x6) = < solved from eq.18 = der3(eq.6) >
der2(x1) = < solved from eq.10 = der2(eq.1) >
der2(x3) = < solved from eq.12 = der2(eq.2) >
der(x4) = < solved from eq.13 = der(eq.3) >
x5 = < solved from eq.5 >
_r[5] = < residue of eq.8 >
_r[4] = < residue of eq.4 >
TestVariableTypes: Demonstrating the handling of various variable types
Simulating model: TestVariableTypes1
Number of equations: 9
Number of variables: 11
Number of continuous states: 2
final i = 1
Simulation OK
(result["f"])[end] = 1.0
(result["b"])[end] = true
(result["i"])[end] = 1
(result["s"])[end] = "asdf"
(result["c"])[end] = 2.0 + 3.0im
(result["re"])[end] = 2.0
(result["im"])[end] = 3.0
Simulating model: TestArrays1
Number of equations: 5
Number of variables: 7
Number of continuous states: 2
final i = [1, 2]
Simulation OK
keys(result) = AbstractString["f", "c1", "time", "der(f)", "der(c1)", "b", "s", "i"]
(result["f"])[end, :] = [2.999999999999999, 5.999999999999998, 8.999999999999996]
(result["der(f)"])[end, :] = [2.0, 4.0, 6.0]
(result["b"])[end] = Bool[0, 1]
(result["i"])[end] = [1, 2]
(result["s"])[end] = ["asdf", "qwerty"]
(result["c1"])[end, :] = [2.999999999999999, 5.999999999999998]
(result["der(c1)"])[end, :] = [2.0, 4.0]
storeEliminated = false
Simulating model: TestVariableTypes2
Number of equations: 10
Number of variables: 10
Number of continuous states: 0
Variable(T=Array{Float64,1}; args...) does not work with storeEliminated=true!
logTranslation = true
removeSingularities = false
storeEliminated = false
Log file: /home/pkgeval/ModiaResults/Test.txt
Simulating model: Test
Number of equations: 9
Number of variables: 10
Number of continuous states: 1
Time=0.0: size of u: (10, 10)
Time=0.0: size of u: (10, 10)
Time=0.0: size of u: (10, 10)
Time=0.0: size of u: (10, 10)
Time=0.0: size of u: (10, 10)
Time=0.0: size of u: (10, 10)
Time=5.005005005005005e-6: size of u: (10, 10)
Time=5.005005005005005e-6: size of u: (10, 10)
Time=1.991991991991992: size of u: ()
Time=1.996996996996997: size of u: ()
Time=2.002002002002002: size of u: ()
Time=2.007007007007007: size of u: ()
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
Simulating model: Resistor
Number of equations: 6
Number of variables: 6
Number of continuous states: 0
Simulating model: ParallelResistors
Number of equations: 12
Number of variables: 12
Number of continuous states: 0
Simulating model: ParallelCapacitors
Number of equations: 15
Number of variables: 16
Number of continuous states: 1
Number of non states: 2
TestFilter: Tests various features of the symbolic handling.
Simulating model: LPfilter
Number of equations: 20
Number of variables: 21
Number of continuous states: 1
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
logTranslation = true
storeEliminated = false
logSimulation = true
Log file: /home/pkgeval/ModiaResults/LPfilter.txt
Simulating model: LPfilter
Number of equations: 20
Number of variables: 21
Number of continuous states: 1
... ModiaMath.simulate! (version 0.5.2 2019-07-10) to simulate model: LPfilter
Initialization at time = 0.0 s
initial values:
│ x │ name │ start │ fixed │ nominal │
├───┼────────┼─────────┼───────┼─────────┤
│ 1 │ C.v │ 0.0 │ 1 │ 1.0 │
determine consistent DAE variables x,der(x) (with implicit Euler step; step size = 1.0e-8)
Simulation started
Simulation is terminated at time = 2.0 s
Statistics (get help with ?ModiaMath.SimulationStatistics):
structureOfDAE = DAE_NoSpecialStructure
cpuTime = 0.59 s (init: 0.59 s, integration: 0.0027 s)
startTime = 0.0 s
stopTime = 2.0 s
interval = 0.002002002002002002 s
tolerance = 0.0001
nEquations = 1
nResults = 1000
nSteps = 58
nResidues = 92 (includes residue calls for Jacobian)
nZeroCrossings = 0
nJac = 22
nTimeEvents = 0
nStateEvents = 0
nRestartEvents = 0
nErrTestFails = 1
h0 = 1.3e-07 s
hMin = 1.3e-07 s
hMax = 0.24 s
orderMax = 5
sparseSolver = false
final C.v = 9.996843043929996
Simulation OK
aliasElimination = true
Simulating model: LPfilter
Number of equations: 12
Number of variables: 13
Number of continuous states: 1
logName = "LPfilter aliasElimination"
aliasElimination = true
Simulating model: LPfilter
Number of equations: 12
Number of variables: 13
Number of continuous states: 1
final C.v = 9.996843043929996
Simulation OK
logName = "LPfilter aliasElimination removeSingularities"
aliasElimination = true
removeSingularities = true
Simulating model: LPfilter
Number of equations: 12
Number of variables: 13
Number of continuous states: 1
final C.v = 9.996843043929996
Simulation OK
logName = "LPfilter aliasElimination removeSingularities"
aliasElimination = true
removeSingularities = true
Simulating model: LPfilter
Number of equations: 12
Number of variables: 13
Number of continuous states: 1
removeSingularities = true
Simulating model: LPfilterWithoutGround
Number of equations: 18
Number of variables: 19
Number of continuous states: 1
final C.v = 9.996843043929996
Simulation OK
Simulating model: LPfilterAndSineSource
Number of equations: 20
Number of variables: 22
Number of continuous states: 2
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
removeSingularities = true
Simulating model: HPfilter
Number of equations: 20
Number of variables: 21
Number of continuous states: 1
final C.v = 7.16540372163548
Simulation OK
removeSingularities = true
Simulating model: NewFilter
Number of equations: 20
Number of variables: 21
Number of continuous states: 1
final C.v = 9.999596486913553
Simulation OK
removeSingularities = true
Simulating model: CondFilter
Number of equations: 20
Number of variables: 21
Number of continuous states: 1
final C.v = 3.6787780967777772
Simulation OK
removeSingularities = true
Simulating model: CondFilter2
Number of equations: 20
Number of variables: 21
Number of continuous states: 1
final C.v = 3.6787780967777772
Simulation OK
removeSingularities = true
Simulating model: FilterModels
Number of equations: 20
Number of variables: 21
Number of continuous states: 1
final C.v = 3.6787780967777772
Simulation OK
Simulating model: FilterComponents
Number of equations: 20
Number of variables: 21
Number of continuous states: 1
final C.v = 3.6787780967777772
Simulation OK
Simulating model: TenCoupledFilters
Number of equations: 188
Number of variables: 198
Number of continuous states: 10
final F10.C.v = 1.232726022885834e-5
Simulation OK
aliasElimination = true
Simulating model: TenCoupledFilters
Number of equations: 115
Number of variables: 125
Number of continuous states: 10
final F10.C.v = 1.232726022885834e-5
Simulation OK
TestArrayOfComponents: Demonstrating the handling of arrays of components
Simulating model: TwoFilters
Number of equations: 40
Number of variables: 42
Number of continuous states: 2
final F[2].C.v = 3.2967996078157973
Simulation OK
Simulating model: ManyFilters
Number of equations: 200
Number of variables: 210
Number of continuous states: 10
final F[1].C.v = 9.816758325302478
Simulation OK
Simulating model: ManyDifferentFilters
Number of equations: 200
Number of variables: 210
Number of continuous states: 10
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
Simulating model: AdvancedLPfilter
Number of equations: 20
Number of variables: 21
Number of continuous states: 1
Rectifier: Demonstrating conditional components
logTranslation = true
Log file: /home/pkgeval/ModiaResults/ConditionalLoad.txt
Simulating model: ConditionalLoad
Number of equations: 39
Number of variables: 41
Number of continuous states: 2
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
Simulating model: NoExtraLoad
Number of equations: 33
Number of variables: 35
Number of continuous states: 2
... ModiaMath.plot(..): Call is ignored, since PyPlot not available.
Demonstrating conditional equations
logTranslation = true
removeSingularities = false
Log file: /home/pkgeval/ModiaResults/Conditional.txt
Simulating model: Conditional
Conditional equation:
if !steadyState
var"der(x)" + 2x = u
else
0 + 2x = u
end
condition = true
Conditional equation:
if !cond
y = 1
else
y = 2
end
condition = true
Number of equations: 3
Number of variables: 4
Number of continuous states: 1