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akaysh/SODE Tests.ipynb

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SODE Tests.ipynb
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"metadata": {
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"name": "stderr",
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"text": [
"\u001b[1m\u001b[34mINFO: Cloning cache of GR from https://github.com/jheinen/GR.jl.git\n",
"\u001b[0m\u001b[1m\u001b[34mINFO: Installing GR v0.22.0\n",
"\u001b[0m\u001b[1m\u001b[34mINFO: Building GR\n",
"\u001b[0m\u001b[1m\u001b[34mINFO: Downloading pre-compiled GR 0.25.0 Ubuntu binary\n",
"\u001b[0m % Total % Received % Xferd Average Speed Time Time Time Current\n",
" Dload Upload Total Spent Left Speed\n",
"100 8004k 100 8004k 0 0 103k 0 0:01:17 0:01:17 --:--:-- 128k\n",
"\u001b[1m\u001b[34mINFO: Package database updated\n",
"\u001b[0m\u001b[1m\u001b[34mINFO: METADATA is out-of-date — you may not have the latest version of GR\n",
"\u001b[0m\u001b[1m\u001b[34mINFO: Use `Pkg.update()` to get the latest versions of your packages\n",
"\u001b[0m"
]
}
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"source": [
"Pkg.add(\"GR\")"
]
},
{
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"text": [
"\u001b[1m\u001b[34mINFO: Updating METADATA...\n",
"\u001b[0m\u001b[1m\u001b[34mINFO: Updating cache of DiffEqBase...\n",
"\u001b[0m\u001b[1m\u001b[34mINFO: Updating cache of RecursiveArrayTools...\n",
"\u001b[0m\u001b[1m\u001b[34mINFO: Updating cache of DiffEqFinancial...\n",
"\u001b[0m\u001b[1m\u001b[34mINFO: Updating cache of StochasticDiffEq...\n",
"\u001b[0m\u001b[1m\u001b[34mINFO: Updating cache of DelayDiffEq...\n",
"\u001b[0m\u001b[1m\u001b[34mINFO: Updating cache of GenericSVD...\n",
"\u001b[0m\u001b[1m\u001b[34mINFO: Updating cache of MultiScaleArrays...\n",
"\u001b[0m\u001b[1m\u001b[34mINFO: Updating cache of FileIO...\n",
"\u001b[0m\u001b[1m\u001b[34mINFO: Updating cache of NLsolve...\n",
"\u001b[0m\u001b[1m\u001b[34mINFO: Updating cache of TensorFlow...\n",
"\u001b[0m\u001b[1m\u001b[34mINFO: Updating cache of OrdinaryDiffEq...\n",
"\u001b[0m\u001b[1m\u001b[34mINFO: Updating cache of LearnBase...\n",
"\u001b[0m\u001b[1m\u001b[34mINFO: Updating cache of DiffEqJump...\n",
"\u001b[0m\u001b[1m\u001b[34mINFO: Updating cache of DiffEqNoiseProcess...\n",
"\u001b[0m\u001b[1m\u001b[34mINFO: Updating cache of ParameterizedFunctions...\n",
"\u001b[0m\u001b[1m\u001b[34mINFO: Updating cache of DiffEqDevTools...\n",
"\u001b[0m\u001b[1m\u001b[34mINFO: Updating cache of PyCall...\n",
"\u001b[0m\u001b[1m\u001b[34mINFO: Computing changes...\n",
"\u001b[0m\u001b[1m\u001b[34mINFO: No packages to install, update or remove\n",
"\u001b[0m"
]
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"source": [
"Pkg.update(\"GR\")"
]
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"text": [
"\u001b[1m\u001b[34mINFO: Precompiling module GR.\n",
"\u001b[0mWARNING: using GR.plot in module Main conflicts with an existing identifier.\n"
]
}
],
"source": [
"using NeuralNetDiffEq\n",
"using Base.Test\n",
"#using Plots; plotly()\n",
"using GR; gr()\n",
"using DiffEqBase, ParameterizedFunctions\n",
"using DiffEqProblemLibrary, DiffEqDevTools\n",
"using Knet"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Test 1"
]
},
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"execution_count": 14,
"metadata": {
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},
"outputs": [
{
"name": "stderr",
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"text": [
"WARNING: Method definition SODE_2(Any, Any) in module Main at In[2]:2 overwritten at In[14]:2.\n"
]
},
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"data": {
"text/plain": [
"SODE_2 (generic function with 1 method)"
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"metadata": {},
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"source": [
"function SODE_2(t,u)\n",
" du1 = -u[1]/5 + exp(-t/5)*cos(t)\n",
" du2 = -u[2]\n",
" [du1,du2]\n",
"end"
]
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"DiffEqBase.ODEProblem{Array{Float32,1},Float32,false,#SODE_2,Void,UniformScaling{Int64}}(SODE_2,Float32[0.0,1.0],(0.0f0,2.0f0),nothing,UniformScaling{Int64}\n",
"1*I)"
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"source": [
"prob1 = ODEProblem(SODE_2,Float32[0.0,1.0],(Float32(0.0),Float32(2.0)))"
]
},
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"execution_count": 16,
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"(:iteration,100,:loss,0.056779962f0)\n",
"(:iteration,200,:loss,0.025023488f0)\n",
"(:iteration,300,:loss,0.011247986f0)\n",
"(:iteration,400,:loss,0.010076475f0)\n",
"(:iteration,500,:loss,0.0047588036f0)\n",
"(:iteration,600,:loss,0.0035654646f0)\n",
"(:iteration,700,:loss,0.002517598f0)\n",
"(:iteration,800,:loss,0.0064811353f0)\n",
"(:iteration,900,:loss,0.0049035056f0)\n",
"(:iteration,1000,:loss,0.0032021091f0)\n",
" 82.887497 seconds (268.48 M allocations: 12.598 GB, 3.83% gc time)\n"
]
},
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"1*I),NeuralNetDiffEq.nnode(10),DiffEqBase.LinearInterpolation{LinSpace{Float32},Array{Array{Any,1},1}}(linspace(0.0f0,2.0f0,10),Array{Any,1}[Any[0.0,1.0],Any[0.212861,0.799015],Any[0.397781,0.638066],Any[0.54676,0.508428],Any[0.655869,0.404192],Any[0.724561,0.320949],Any[0.752817,0.25408],Any[0.740966,0.199549],Any[0.692261,0.154956],Any[0.614865,0.119459]]),false,0,:Success)"
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"source": [
"sol1 = solve(prob1,nnode(10),dt=0.2,iterations=1000)"
]
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"source": [
"plot(sol1)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Test 2"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false
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"outputs": [
{
"data": {
"text/plain": [
"SODE_3 (generic function with 1 method)"
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"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"function SODE_3(t,u)\n",
" du1 = -u[1]/5 + exp(-t/5)*cos(t)\n",
" du2 = -u[2]/5 + exp(-t/5)*cos(t)\n",
" [du1,du2]\n",
"end"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
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"outputs": [
{
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"DiffEqBase.ODEProblem{Array{Float32,1},Float32,false,#SODE_3,Void,UniformScaling{Int64}}(SODE_3,Float32[0.0,0.0],(0.0f0,2.0f0),nothing,UniformScaling{Int64}\n",
"1*I)"
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"(:iteration,300,:loss,0.0037576563f0)\n",
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"(:iteration,500,:loss,0.013106221f0)\n",
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"(:iteration,700,:loss,0.016314188f0)\n",
"(:iteration,800,:loss,0.006872811f0)\n",
"(:iteration,900,:loss,0.0098809f0)\n",
"(:iteration,1000,:loss,0.014690644f0)\n",
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],
"source": [
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]
},
{
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}
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