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adv-2.ipynb
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "adv-2.ipynb",
"provenance": [],
"collapsed_sections": [],
"include_colab_link": true
},
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
"name": "python"
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/likask/be00986ecb80db8cbf0bf9aacd0889fe/adv-2.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "84E4cEiyNqWu"
},
"source": [
"\n",
"#ADV-2 tutorial \n",
"\n",
"This code supplements [ADV-2](http://mofem.eng.gla.ac.uk/mofem/html/tutorial_thermo_plastic.html) tutorial. Follow the link to see implementation.\n",
"\n",
"*Note*: Installation is the most time-consuming party for this example. It is expected to take between 16 minutes."
]
},
{
"cell_type": "code",
"metadata": {
"id": "V3H5gle_UHia"
},
"source": [
"%%bash\n",
"apt-get update -qq && \\\n",
"apt-get install -qq -y \\\n",
"curl \\\n",
"git \\\n",
"g++ \\\n",
"gfortran \\\n",
"python \\\n",
"python3 \\\n",
"automake \\\n",
"build-essential \\\n",
"libtool \\\n",
"cmake \\\n",
"ca-certificates \\\n",
"gpg \\\n",
"gpg-agent \\\n",
"libgl1-mesa-glx \\\n",
"libglu1-mesa \\\n",
"xvfb "
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "VUPzq-3BUOxb",
"outputId": "5ebd8ea5-5612-4b32-fe80-333aae9a461e"
},
"source": [
"%%bash\n",
"rm /usr/bin/python3\n",
"ln -s /usr/bin/python3.7 /usr/bin/python3\n",
"#apt-get install python3-pip\n",
"#python3 -m pip install --upgrade pip\n",
"pip -q install pip --upgrade && \\\n",
" pip -q install \\\n",
" pandas \\\n",
" scipy \\\n",
" gmsh \\\n",
" piglet \\\n",
" pyvirtualdisplay \\\n",
" pyvista \\\n",
" itkwidgets \\\n",
" ipywidgets \\\n",
" ipyvtklink \\\n",
" ipyvtk-simple==0.1.2"
],
"execution_count": 2,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\n"
]
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "BkpSqO9adbMt"
},
"source": [
"%%bash\n",
"#rm -rf spack\n",
"#apt-get install python3\n",
"rm /usr/bin/python3\n",
"ln -s /usr/bin/python3.6 /usr/bin/python3\n",
"git clone --single-branch -b develop https://github.com/likask/spack.git\n",
"source spack/share/spack/setup-env.sh\n",
"spack mirror add colab http://userweb.eng.gla.ac.uk/lukasz.kaczmarczyk/Download/colab_mirror\n",
"#spack compiler find\n",
"#spack external find\n",
"curl http://userweb.eng.gla.ac.uk/lukasz.kaczmarczyk/Download/colab_mirror/build_cache/_pgp/47BF84D43F1C1F7F63153D58EC7CD9C7ABFE39B0.pub > key.pub\n",
"spack gpg trust key.pub \n",
"spack mirror list\n",
"spack buildcache list -a"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "l5DrpgbFeMqh"
},
"source": [
"# Install MoFEM packages is buildcaceh (this takes time)\n",
"%%bash\n",
"source spack/share/spack/setup-env.sh\n",
"spack buildcache install -ao mofem-users-modules@lukasz 2>&1 | tee log"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "bN1qPJ8ceSnp"
},
"source": [
"# Careate view to installed packages\n",
"%%bash\n",
"source spack/share/spack/setup-env.sh\n",
"spack view --verbose symlink -i um_view mofem-users-modules"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "MdkN0PMgeTMU",
"outputId": "506bd456-1847-4a00-c1e0-46776702aab1"
},
"source": [
"!cat /proc/cpuinfo\n",
"!free -h"
],
"execution_count": 6,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"processor\t: 0\n",
"vendor_id\t: GenuineIntel\n",
"cpu family\t: 6\n",
"model\t\t: 79\n",
"model name\t: Intel(R) Xeon(R) CPU @ 2.20GHz\n",
"stepping\t: 0\n",
"microcode\t: 0x1\n",
"cpu MHz\t\t: 2200.156\n",
"cache size\t: 56320 KB\n",
"physical id\t: 0\n",
"siblings\t: 2\n",
"core id\t\t: 0\n",
"cpu cores\t: 1\n",
"apicid\t\t: 0\n",
"initial apicid\t: 0\n",
"fpu\t\t: yes\n",
"fpu_exception\t: yes\n",
"cpuid level\t: 13\n",
"wp\t\t: yes\n",
"flags\t\t: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology nonstop_tsc cpuid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch invpcid_single ssbd ibrs ibpb stibp fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm rdseed adx smap xsaveopt arat md_clear arch_capabilities\n",
"bugs\t\t: cpu_meltdown spectre_v1 spectre_v2 spec_store_bypass l1tf mds swapgs taa\n",
"bogomips\t: 4400.31\n",
"clflush size\t: 64\n",
"cache_alignment\t: 64\n",
"address sizes\t: 46 bits physical, 48 bits virtual\n",
"power management:\n",
"\n",
"processor\t: 1\n",
"vendor_id\t: GenuineIntel\n",
"cpu family\t: 6\n",
"model\t\t: 79\n",
"model name\t: Intel(R) Xeon(R) CPU @ 2.20GHz\n",
"stepping\t: 0\n",
"microcode\t: 0x1\n",
"cpu MHz\t\t: 2200.156\n",
"cache size\t: 56320 KB\n",
"physical id\t: 0\n",
"siblings\t: 2\n",
"core id\t\t: 0\n",
"cpu cores\t: 1\n",
"apicid\t\t: 1\n",
"initial apicid\t: 1\n",
"fpu\t\t: yes\n",
"fpu_exception\t: yes\n",
"cpuid level\t: 13\n",
"wp\t\t: yes\n",
"flags\t\t: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology nonstop_tsc cpuid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch invpcid_single ssbd ibrs ibpb stibp fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm rdseed adx smap xsaveopt arat md_clear arch_capabilities\n",
"bugs\t\t: cpu_meltdown spectre_v1 spectre_v2 spec_store_bypass l1tf mds swapgs taa\n",
"bogomips\t: 4400.31\n",
"clflush size\t: 64\n",
"cache_alignment\t: 64\n",
"address sizes\t: 46 bits physical, 48 bits virtual\n",
"power management:\n",
"\n",
" total used free shared buff/cache available\n",
"Mem: 12G 486M 3.3G 1.1M 8.9G 11G\n",
"Swap: 0B 0B 0B\n"
]
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "MOpkSDWpeaPn"
},
"source": [
"Thermo Plasticity problem\n",
"\n",
"Effect of localised heating due to plastic deformation on a plate."
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "Li845THoFSgc",
"outputId": "4b6d1805-d15d-4723-ddce-aee132a191a7"
},
"source": [
"dir='/content/um_view/tutorials/adv-2'\n",
"bin_dir='/content/um_view/bin'\n",
"nb_proc=1\n",
"import os\n",
"os.chdir(dir)\n",
"!rm -f out_*\n",
"!{bin_dir}/mofem_part -my_file adv2_thermo_plast_2D.cub \\\n",
"-output_file ab.h5m -my_nparts {nb_proc} -dim 2 -adj_dim 1\n",
"!{bin_dir}/mpirun --allow-run-as-root -np {nb_proc} \\\n",
"./thermo_plastic_2d \\\n",
"-file_name ab.h5m \\\n",
"-ts_dt 0.001 \\\n",
"-ts_max_time 0.085 \\\n",
"-ts_type theta \\\n",
"-snes_linesearch_type l2 \\\n",
"-snes_stol 1e-6 \\\n",
"-snes_atol 1e-6 \\\n",
"-snes_rtol 1e-6 \\\n",
"-order 2 \\\n",
"-ts_max_snes_failres -1 \\\n",
"-ts_theta_initial_guess_extrapolate 1 \\\n",
"-ts_theta_theta 1 \\\n",
"-ts_exact_final_time matchstep 1 \\\n",
"-fix_skin_flux 0 \\\n",
"-snes_linesearch_type l2 \\\n",
"-number_of_cycles_in_total_time 0 \\\n",
"-fraction_of_dissipation 0.9 \\\n",
"-young_modulus 206913 \\\n",
"-poisson_ration 0.29 \\\n",
"-yield_stress 450 \\\n",
"-hardening 130 \\\n",
"-Qinf 265 \\\n",
"-b_iso 17 \\\n",
"-hardening_viscous 100 \\\n",
"-omega_0 0 \\\n",
"-omega_h 0 \\\n",
"-omega_inf 0 \\\n",
"-ts_max_steps 1000 \\\n",
"-cn 1 \\\n",
"-capacity 3.6 2>&1 | tee log_no_thermo_plasticity"
],
"execution_count": 7,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0mMoFEM version 0.12.1 (MOAB 5.3.0 Petsc Release Version 3.11.4, Sep, 28, 2019 )\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0mgit commit id dd3b8fb472b0ba2f863ca4b1faf2452065f5e5f0\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0mLocal time: 2021-10-14 9:57:6\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0mUTC time: 2021-10-14 9:57:6\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[MeshsetMng] \u001b[0mmeshset 12682136550675316752 type BLOCKSET UNKNOWNNAME msId 1 name FIX_Y block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[MeshsetMng] \u001b[0mmeshset 12682136550675316753 type BLOCKSET UNKNOWNNAME msId 2 name FIX_X block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[MeshsetMng] \u001b[0mmeshset 12682136550675316754 type BLOCKSET UNKNOWNNAME msId 3 name FIX_Y1 block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[MeshsetMng] \u001b[0mmeshset 12682136550675316755 type BLOCKSET UNKNOWNNAME msId 4 name TEMPERATURE_1 block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[MeshsetMng] \u001b[0mmeshset 12682136550675316756 type BLOCKSET UNKNOWNNAME msId 5 name REACTION block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[MeshsetMng] \u001b[0mmeshset 12682136550675316757 type BLOCKSET UNKNOWNNAME msId 6 name ZERO_FLUX block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[mofem_part] \u001b[0mmeshset 12682136550675316752 type BLOCKSET UNKNOWNNAME msId 1 name FIX_Y block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[mofem_part] \u001b[0mmeshset 12682136550675316753 type BLOCKSET UNKNOWNNAME msId 2 name FIX_X block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[mofem_part] \u001b[0mmeshset 12682136550675316754 type BLOCKSET UNKNOWNNAME msId 3 name FIX_Y1 block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[mofem_part] \u001b[0mmeshset 12682136550675316755 type BLOCKSET UNKNOWNNAME msId 4 name TEMPERATURE_1 block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[mofem_part] \u001b[0mmeshset 12682136550675316756 type BLOCKSET UNKNOWNNAME msId 5 name REACTION block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[mofem_part] \u001b[0mmeshset 12682136550675316757 type BLOCKSET UNKNOWNNAME msId 6 name ZERO_FLUX block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[ProblemsManager] \u001b[0mFinite elements in problem: row lower 0 row upper 129 nb. elems 129 ( 129 )\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0mMoFEM version 0.12.1 (MOAB 5.3.0 Petsc Release Version 3.11.4, Sep, 28, 2019 )\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0mgit commit id dd3b8fb472b0ba2f863ca4b1faf2452065f5e5f0\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0mLocal time: 2021-10-14 9:57:6\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0mUTC time: 2021-10-14 9:57:6\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[MeshsetMng] \u001b[0mmeshset 12682136550675316752 type BLOCKSET UNKNOWNNAME msId 1 name FIX_Y block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[MeshsetMng] \u001b[0mmeshset 12682136550675316753 type BLOCKSET UNKNOWNNAME msId 2 name FIX_X block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[MeshsetMng] \u001b[0mmeshset 12682136550675316754 type BLOCKSET UNKNOWNNAME msId 3 name FIX_Y1 block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[MeshsetMng] \u001b[0mmeshset 12682136550675316755 type BLOCKSET UNKNOWNNAME msId 4 name TEMPERATURE_1 block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[MeshsetMng] \u001b[0mmeshset 12682136550675316756 type BLOCKSET UNKNOWNNAME msId 5 name REACTION block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[MeshsetMng] \u001b[0mmeshset 12682136550675316757 type BLOCKSET UNKNOWNNAME msId 6 name ZERO_FLUX block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[FieldCore] \u001b[0mAdd field U field_id 1 space H1 approximation base AINSWORTH_LEGENDRE_BASE rank 2 meshset 12682136550675316759\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[FieldCore] \u001b[0mAdd field TAU field_id 2 space L2 approximation base AINSWORTH_LEGENDRE_BASE rank 1 meshset 12682136550675316760\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[FieldCore] \u001b[0mAdd field EP field_id 4 space L2 approximation base AINSWORTH_LEGENDRE_BASE rank 3 meshset 12682136550675316761\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[FieldCore] \u001b[0mAdd field T field_id 8 space L2 approximation base AINSWORTH_LEGENDRE_BASE rank 1 meshset 12682136550675316762\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[FieldCore] \u001b[0mAdd field FLUX field_id 16 space HCURL approximation base DEMKOWICZ_JACOBI_BASE rank 1 meshset 12682136550675316763\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[FECore] \u001b[0mAdd finite element dFE\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[FECore] \u001b[0mAdd finite element bFE\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[ProblemCore] \u001b[0mAdd problem SimpleProblem\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[FieldCore] \u001b[0mNumber of dofs 3215\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[FECore] \u001b[0mFinite element dFE added. Nb. of elements added 129\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[FECore] \u001b[0mFinite element bFE added. Nb. of elements added 39\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[FECore] \u001b[0mNumber of adjacencies 1833\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[ProblemsManager] \u001b[0mSimpleProblem Nb. local dof 3215 by 3215 nb global dofs 3215 by 3215\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[ProblemsManager] \u001b[0m FEs ghost dofs on problem SimpleProblem Nb. ghost dof 0 by 0 Nb. local dof 3215 by 3215\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mYoung modulus 206913\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mPoisson ratio 0.29\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mYield stress 450\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mHardening 130\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mViscous hardening 100\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mSaturation yield stress 265\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mSaturation exponent 17\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mcn 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mfraction_of_dissipation 0.9\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mScaled Young modulus 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mScaled Poisson ratio 0.29\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mScaled Yield stress 0.00217483\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mScaled Hardening 0.000628283\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mScaled Viscous hardening 0.000483295\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mScaled Saturation yield stress 0.00128073\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mScaled heat capacity 1.73986e-05\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mSet temerature 0 on ents:\n",
"\tEdge 80 - 82\n",
"\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 0.0000e+00 0.0000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 0.0000e+00 min 0.0000e+00 max 0.0000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 0.0000e+00 min 0.0000e+00 max 0.0000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m0 TS dt 0.001 time 0.\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 4.122982155350e-01 [ 4.122982155350e-01 , 3.407171532345e-18 , 0.000000000000e+00 , 0.000000000000e+00 , 0.000000000000e+00 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.226803061815e-15 [ 1.020523295542e-16 , 3.784169273450e-18 , 1.222545195309e-15 , 0.000000000000e+00 , 0.000000000000e+00 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 0 accepted t=0 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 1.0000e-03 -1.4429e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 1.0000e-03 min -4.1844e-03 max 9.1451e-17\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 1.0000e-03 min -3.2716e-16 max 6.0000e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m1 TS dt 0.001 time 0.001\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.245857282698e-15 [ 2.398582103703e-16 , 3.413677733843e-18 , 1.222545195310e-15 , 0.000000000000e+00 , 0.000000000000e+00 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 1 accepted t=0.001 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 2.0000e-03 -2.8858e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 2.0000e-03 min -8.3689e-03 max 1.8290e-16\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 2.0000e-03 min -6.5432e-16 max 1.2000e-01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m2 TS dt 0.001 time 0.002\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 6.509588707205e-02 [ 5.332175192462e-16 , 6.509588707205e-02 , 1.222545195310e-15 , 0.000000000000e+00 , 0.000000000000e+00 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 9.843759786713e-01 [ 4.783850215960e-16 , 5.334633616886e-02 , 2.222173736877e-14 , 9.829294154732e-01 , 0.000000000000e+00 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.286255723479e+00 [ 5.177261697693e-16 , 4.540707568275e-02 , 6.699865269281e-09 , 1.285453999045e+00 , 9.555220937798e-15 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 3 SNES Function norm 1.371743356425e+00 [ 5.284245071225e-16 , 3.942043259177e-02 , 1.992623015347e-08 , 1.371176817697e+00 , 1.025899482551e-14 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 4 SNES Function norm 1.370864707684e+00 [ 6.105223182966e-16 , 3.455728022307e-02 , 3.481313623088e-08 , 1.370429071918e+00 , 1.236768983855e-14 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 5 SNES Function norm 1.329838310312e+00 [ 5.925293349601e-16 , 3.035695611842e-02 , 4.986907442353e-08 , 1.329491777631e+00 , 1.332697818836e-14 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 6 SNES Function norm 1.266574534030e+00 [ 6.500300274408e-16 , 2.651942107974e-02 , 6.520638473379e-08 , 1.266296872996e+00 , 1.605957135676e-14 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 7 SNES Function norm 1.187346384968e+00 [ 6.181964215887e-16 , 2.281666978954e-02 , 8.176055622096e-08 , 1.187127136189e+00 , 1.806578056641e-14 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 8 SNES Function norm 1.092362221086e+00 [ 5.387460630353e-16 , 1.904583700644e-02 , 1.012054094097e-07 , 1.092196172008e+00 , 1.837346986155e-14 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 9 SNES Function norm 9.768728908334e-01 [ 4.480967968133e-16 , 1.499917665467e-02 , 1.262054842754e-07 , 9.767577332916e-01 , 2.165976159910e-14 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 10 SNES Function norm 8.279597532973e-01 [ 4.208227779763e-16 , 1.042600705472e-02 , 1.607384131698e-07 , 8.278941064273e-01 , 2.811772064395e-14 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 11 SNES Function norm 6.065780907921e-01 [ 3.690134476088e-16 , 4.850713507091e-03 , 2.110141784854e-07 , 6.065586952698e-01 , 3.173915790008e-14 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 12 SNES Function norm 7.294864021238e-02 [ 4.181898385173e-16 , 2.466729834133e-03 , 2.106574249071e-07 , 7.290692252946e-02 , 5.185722061845e-14 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 13 SNES Function norm 4.224702415268e-02 [ 2.100091275163e-16 , 3.912658313369e-04 , 5.765395259279e-08 , 4.224521228261e-02 , 3.776217765948e-14 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 14 SNES Function norm 1.065707763902e-05 [ 1.536112482111e-16 , 1.065442157889e-05 , 8.645291486393e-10 , 2.379156908823e-07 , 3.389273464982e-14 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 15 SNES Function norm 8.018012132965e-07 [ 1.506338283996e-16 , 1.025841951843e-07 , 7.712769790106e-12 , 7.952117129938e-07 , 3.490794938370e-14 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 2 accepted t=0.002 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 3.0000e-03 -3.5266e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 3.0000e-03 min -1.5762e-02 max 2.1398e-08\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 3.0000e-03 min -1.7907e-10 max 1.8000e-01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m3 TS dt 0.001 time 0.003\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.877447038983e+01 [ 7.876972813218e-16 , 3.210210798705e-02 , 4.460948244136e-06 , 1.877444294442e+01 , 7.729299424476e-14 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.325807751861e+00 [ 5.955125546799e-16 , 7.367232582756e-03 , 1.044653390400e-05 , 1.325787282587e+00 , 8.797119832617e-14 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 3.624826615411e-01 [ 2.884719879889e-16 , 6.710303136477e-04 , 2.156188106899e-06 , 3.624820404262e-01 , 1.249818763911e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 3 SNES Function norm 1.066773389781e-03 [ 1.713176216820e-16 , 5.697368966883e-06 , 1.683208296626e-09 , 1.066758175562e-03 , 1.088793122728e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 4 SNES Function norm 2.181849529692e-07 [ 1.328845414560e-16 , 4.106231321333e-10 , 9.932514247215e-13 , 2.181845665711e-07 , 1.105953304069e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 3 accepted t=0.003 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 4.0000e-03 -3.7717e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 4.0000e-03 min -2.4737e-02 max 1.6531e-07\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 4.0000e-03 min -1.5347e-09 max 2.4000e-01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m4 TS dt 0.001 time 0.004\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.822359097734e+01 [ 7.709150455489e-16 , 1.116673236480e-02 , 4.663717360537e-05 , 2.822358876823e+01 , 2.551974283225e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.394298527920e-01 [ 3.900178701023e-16 , 3.273078177719e-04 , 1.010284888953e-05 , 1.394294682523e-01 , 1.962748710595e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 7.554952286639e-04 [ 3.368498505357e-16 , 2.641594658831e-07 , 2.968228497832e-09 , 7.554951824763e-04 , 1.941819312679e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 3 SNES Function norm 7.265128498389e-11 [ 2.727711940295e-16 , 1.721572314163e-13 , 1.217009534157e-13 , 7.265075043158e-11 , 1.822696648850e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 4 accepted t=0.004 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 5.0000e-03 -3.8790e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 5.0000e-03 min -3.4264e-02 max 5.2247e-07\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 5.0000e-03 min -5.2645e-09 max 3.0000e-01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m5 TS dt 0.001 time 0.005\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.982482916881e+01 [ 8.977974317433e-16 , 3.907572512326e-03 , 1.142341897556e-04 , 1.982482878338e+01 , 3.790265356809e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 6.541331987936e-03 [ 5.486439501427e-16 , 2.116540499943e-05 , 3.245349926646e-06 , 6.541296940954e-03 , 2.271284513925e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 3.188523762723e-06 [ 4.039133305389e-16 , 6.164455438125e-10 , 1.231666454352e-10 , 3.188523700755e-06 , 2.169016070639e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 5 accepted t=0.005 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 6.0000e-03 -3.9382e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 6.0000e-03 min -4.3985e-02 max 1.1294e-06\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 6.0000e-03 min -1.2037e-08 max 3.6000e-01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m6 TS dt 0.001 time 0.006\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.228889394606e+01 [ 1.268090364088e-15 , 1.388459438758e-03 , 1.699784897478e-04 , 1.228889386644e+01 , 4.924075866326e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 2.894424795621e-03 [ 5.400659766758e-16 , 1.506361810909e-06 , 7.544838095192e-07 , 2.894424305304e-03 , 2.695896976669e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.579077320035e-08 [ 3.225285051899e-16 , 1.816784304513e-12 , 2.252267636340e-12 , 1.579077293333e-08 , 2.439255279037e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 6 accepted t=0.006 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 7.0000e-03 -3.9803e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 7.0000e-03 min -5.3776e-02 max 1.9864e-06\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 7.0000e-03 min -2.2008e-08 max 4.2000e-01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m7 TS dt 0.001 time 0.007\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 7.301727518226e+00 [ 1.080621897167e-15 , 5.133047742135e-04 , 2.025031185323e-04 , 7.301727497375e+00 , 5.847620375061e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 5.374710172218e-04 [ 4.024751505788e-16 , 1.242841523109e-07 , 1.497587376108e-07 , 5.374709819881e-04 , 2.360547319285e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.046962292414e-10 [ 4.044049526923e-16 , 7.734876266974e-15 , 2.100197468738e-13 , 1.046956455823e-10 , 2.793656974120e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 7 accepted t=0.007 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 8.0000e-03 -4.0160e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 8.0000e-03 min -6.3592e-02 max 3.0791e-06\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 8.0000e-03 min -3.5065e-08 max 4.8000e-01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m8 TS dt 0.001 time 0.008\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 4.246839917996e+00 [ 1.424807997196e-15 , 2.087303178483e-04 , 2.161974410272e-04 , 4.246839907363e+00 , 5.809270247596e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 9.202720223815e-05 [ 8.925550428244e-16 , 1.404168764413e-08 , 2.831598074622e-08 , 9.202719681060e-05 , 2.372474368621e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.402760903158e-12 [ 5.079365225819e-16 , 5.069530934438e-16 , 3.235940652819e-13 , 1.340779939377e-12 , 2.556045216846e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 8 accepted t=0.008 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 9.0000e-03 -4.0492e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 9.0000e-03 min -7.3420e-02 max 4.3903e-06\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 9.0000e-03 min -5.1006e-08 max 5.4000e-01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m9 TS dt 0.001 time 0.009\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.445229824728e+00 [ 1.843643505549e-15 , 1.023429547966e-04 , 2.184150318345e-04 , 2.445229812831e+00 , 5.920630913615e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.921587632154e-05 [ 4.449427011405e-16 , 2.870101392790e-09 , 6.343023924752e-09 , 1.921587506031e-05 , 3.135361469845e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 4.283594993036e-13 [ 4.578601909371e-16 , 7.870187794641e-16 , 2.712825911435e-13 , 2.059259866806e-13 , 2.597908300175e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 9 accepted t=0.009 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 1.0000e-02 -4.0811e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 1.0000e-02 min -8.3254e-02 max 5.9045e-06\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 1.0000e-02 min -6.9631e-08 max 6.0000e-01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m10 TS dt 0.001 time 0.01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.407007115971e+00 [ 2.259505431278e-15 , 6.483925834752e-05 , 2.148925610671e-04 , 1.407007098067e+00 , 5.696746891854e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 6.159991406276e-06 [ 4.405093209161e-16 , 1.299434202837e-09 , 2.774276872563e-09 , 6.159990644494e-06 , 2.723039997849e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 4.479729706375e-13 [ 7.956964657322e-16 , 6.786494792098e-16 , 2.754520952765e-13 , 2.366296947218e-13 , 2.623189270858e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 10 accepted t=0.01 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 1.1000e-02 -4.1122e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 1.1000e-02 min -9.3092e-02 max 7.6097e-06\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 1.1000e-02 min -9.0771e-08 max 6.6000e-01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m11 TS dt 0.001 time 0.011\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 8.173355544599e-01 [ 3.464424150344e-15 , 5.128803617460e-05 , 2.091593809929e-04 , 8.173355260884e-01 , 5.557512925161e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 3.176694255135e-06 [ 7.023601996795e-16 , 1.138912192980e-09 , 3.105242600531e-09 , 3.176692533274e-06 , 2.628265919088e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 4.856121449437e-13 [ 6.185033319626e-16 , 6.725567102766e-16 , 3.613332066977e-13 , 2.052162132585e-13 , 2.512825899089e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 11 accepted t=0.011 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 1.2000e-02 -4.1426e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 1.2000e-02 min -1.0293e-01 max 9.4966e-06\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 1.2000e-02 min -1.1429e-07 max 7.2000e-01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m12 TS dt 0.001 time 0.012\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 4.854356207936e-01 [ 2.607143148490e-15 , 4.607143224436e-05 , 2.030807481508e-04 , 4.854355761282e-01 , 4.970558186417e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 2.189890138661e-06 [ 5.878644441640e-16 , 1.415327088904e-09 , 4.993705746189e-09 , 2.189883987602e-06 , 2.627175089754e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 4.801746529173e-13 [ 5.689635777941e-16 , 6.454655188146e-16 , 3.728705079504e-13 , 1.853153543802e-13 , 2.391500798469e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 12 accepted t=0.012 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 1.3000e-02 -4.1725e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 1.3000e-02 min -1.1278e-01 max 1.1558e-05\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 1.3000e-02 min -1.4009e-07 max 7.8000e-01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m13 TS dt 0.001 time 0.013\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.996416644186e-01 [ 3.355322051955e-15 , 4.375909785568e-05 , 1.974947208129e-04 , 2.996415961387e-01 , 5.858470304116e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.610604395927e-06 [ 5.795363267841e-16 , 1.985357652695e-09 , 8.042638424607e-09 , 1.610583091462e-06 , 2.531701320792e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 4.915507849084e-13 [ 5.965564674183e-16 , 8.481712669688e-16 , 3.381865952285e-13 , 2.264897451181e-13 , 2.755963008353e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 13 accepted t=0.013 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 1.4000e-02 -4.2018e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 1.4000e-02 min -1.2262e-01 max 1.3790e-05\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 1.4000e-02 min -1.6810e-07 max 8.4000e-01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m14 TS dt 0.001 time 0.014\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.959512846505e-01 [ 3.053684308813e-15 , 4.246180044562e-05 , 1.926805106874e-04 , 1.959511853177e-01 , 5.452379691444e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.061740697436e-06 [ 8.672792875664e-16 , 2.793077345960e-09 , 1.205352018186e-08 , 1.061668601760e-06 , 2.393121755896e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 5.096045220167e-13 [ 7.468068846293e-16 , 9.818086356206e-16 , 4.232960801084e-13 , 1.535400045469e-13 , 2.386234329644e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 14 accepted t=0.014 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 1.5000e-02 -4.2306e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 1.5000e-02 min -1.3247e-01 max 1.6187e-05\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 1.5000e-02 min -1.9825e-07 max 9.0000e-01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m15 TS dt 0.001 time 0.015\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.381248321019e-01 [ 2.913154656468e-15 , 4.152238227651e-05 , 1.886484412212e-04 , 1.381246970343e-01 , 5.945410223595e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 5.140765792395e-07 [ 9.990279682062e-16 , 3.721621903152e-09 , 1.653272627163e-08 , 5.137971854876e-07 , 2.747888386787e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 15 accepted t=0.015 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 1.6000e-02 -4.2589e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 1.6000e-02 min -1.4233e-01 max 1.8747e-05\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 1.6000e-02 min -2.3049e-07 max 9.6000e-01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m16 TS dt 0.001 time 0.016\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.057730595195e-01 [ 4.008088076791e-15 , 4.071889891925e-05 , 1.853173347288e-04 , 1.057728893411e-01 , 5.563478590582e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 3.207115712585e-07 [ 1.530964145221e-15 , 4.591729179368e-09 , 2.071208189179e-08 , 3.200091211605e-07 , 2.483196940401e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 16 accepted t=0.016 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 1.7000e-02 -4.2866e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 1.7000e-02 min -1.5218e-01 max 2.1467e-05\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 1.7000e-02 min -2.6480e-07 max 1.0200e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m17 TS dt 0.001 time 0.017\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 8.749478046766e-02 [ 3.803654120300e-15 , 3.996006978465e-05 , 1.825336250610e-04 , 8.749458093935e-02 , 5.184323187500e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 6.659875001522e-07 [ 1.126702784444e-15 , 5.245631272388e-09 , 2.391717437344e-08 , 6.655372284714e-07 , 2.500292453344e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 17 accepted t=0.017 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 1.8000e-02 -4.3139e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 1.8000e-02 min -1.6204e-01 max 2.4346e-05\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 1.8000e-02 min -3.0114e-07 max 1.0800e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m18 TS dt 0.001 time 0.018\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 7.694164952017e-02 [ 4.474839828283e-15 , 3.922564648576e-05 , 1.801919075206e-04 , 7.694142852267e-02 , 5.106038556039e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 9.635774657781e-07 [ 1.057594380688e-15 , 5.636776348404e-09 , 2.595144765956e-08 , 9.632114418300e-07 , 2.355677895126e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 18 accepted t=0.018 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 1.9000e-02 -4.3406e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 1.9000e-02 min -1.7190e-01 max 2.7381e-05\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 1.9000e-02 min -3.3949e-07 max 1.1400e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m19 TS dt 0.001 time 0.019\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 7.062712148203e-02 [ 3.658239265962e-15 , 3.850622167807e-05 , 1.781959039894e-04 , 7.062688618598e-02 , 5.033585748501e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.150049710009e-06 [ 7.951975801299e-16 , 5.804123334645e-09 , 2.699003467888e-08 , 1.149718307097e-06 , 2.460567592566e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 7.052369869444e-13 [ 8.896428907129e-16 , 1.101445630901e-15 , 5.369879065080e-13 , 3.863994983143e-13 , 2.443289157551e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 19 accepted t=0.019 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 2.0000e-02 -4.3669e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 2.0000e-02 min -1.8176e-01 max 3.0572e-05\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 2.0000e-02 min -3.7983e-07 max 1.2000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m20 TS dt 0.001 time 0.02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 6.664740737171e-02 [ 3.711025592384e-15 , 3.778923742975e-05 , 1.764447066054e-04 , 6.664716309499e-02 , 4.957724503087e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.250094278751e-06 [ 9.809547835159e-16 , 5.811549388311e-09 , 2.731657835855e-08 , 1.249782275521e-06 , 2.599843941292e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 7.126886487935e-13 [ 1.304033830867e-15 , 1.195994295017e-15 , 5.036474789209e-13 , 4.366633567193e-13 , 2.521632587983e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 20 accepted t=0.02 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 2.1000e-02 -4.3927e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 2.1000e-02 min -1.9163e-01 max 3.3917e-05\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 2.1000e-02 min -4.2215e-07 max 1.2600e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m21 TS dt 0.001 time 0.021\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 6.394449056373e-02 [ 4.424732228293e-15 , 3.709562620031e-05 , 1.749364124321e-04 , 6.394424051172e-02 , 6.014521910719e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.294620149635e-06 [ 8.209161814498e-16 , 5.730859199839e-09 , 2.724325462508e-08 , 1.294320784880e-06 , 2.714260224110e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 6.908674779568e-13 [ 8.049932067191e-16 , 1.342959261581e-15 , 4.959462641177e-13 , 3.971470575533e-13 , 2.713059865339e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 21 accepted t=0.021 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 2.2000e-02 -4.4180e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 2.2000e-02 min -2.0150e-01 max 3.7414e-05\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 2.2000e-02 min -4.6643e-07 max 1.3200e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m22 TS dt 0.001 time 0.022\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 6.196365608689e-02 [ 5.169340364822e-15 , 3.641162677868e-05 , 1.736049069278e-04 , 6.196340219181e-02 , 5.859653276113e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.307231786118e-06 [ 1.486496486666e-15 , 5.596308681235e-09 , 2.692516228327e-08 , 1.306942485193e-06 , 2.466041735637e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 7.601646775783e-13 [ 1.194055013913e-15 , 1.493279821688e-15 , 6.071679898174e-13 , 3.890752906307e-13 , 2.404456939672e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 22 accepted t=0.022 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 2.3000e-02 -4.4429e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 2.3000e-02 min -2.1137e-01 max 4.1065e-05\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 2.3000e-02 min -5.1267e-07 max 1.3800e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m23 TS dt 0.001 time 0.023\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 6.038589266801e-02 [ 5.292635097427e-15 , 3.573813150052e-05 , 1.724206068391e-04 , 6.038563593465e-02 , 5.567176416280e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.301631580131e-06 [ 2.184329872408e-15 , 5.434734993209e-09 , 2.648085051874e-08 , 1.301350836095e-06 , 2.704456023171e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 8.241883109187e-13 [ 1.219668653942e-15 , 1.639530889860e-15 , 6.815138482716e-13 , 3.844931570312e-13 , 2.588166977072e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 23 accepted t=0.023 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 2.4000e-02 -4.4673e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 2.4000e-02 min -2.2124e-01 max 4.4867e-05\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 2.4000e-02 min -5.6085e-07 max 1.4400e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m24 TS dt 0.001 time 0.024\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 5.903790065121e-02 [ 3.041347763843e-15 , 3.507542495852e-05 , 1.713618047686e-04 , 5.903764153613e-02 , 5.527911603784e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.286462779261e-06 [ 1.305349155722e-15 , 5.261349612772e-09 , 2.597747373442e-08 , 1.286189710534e-06 , 2.607855491741e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 7.576191514899e-13 [ 1.295333655244e-15 , 1.385808830544e-15 , 6.095030180569e-13 , 3.740555859251e-13 , 2.501432988642e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 24 accepted t=0.024 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 2.5000e-02 -4.4913e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 2.5000e-02 min -2.3111e-01 max 4.8820e-05\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 2.5000e-02 min -6.1098e-07 max 1.5000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m25 TS dt 0.001 time 0.025\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 5.782433607146e-02 [ 3.969946485689e-15 , 3.442355730206e-05 , 1.704123311172e-04 , 5.782407471600e-02 , 5.374073456487e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.266582840232e-06 [ 1.459355518358e-15 , 5.084588841611e-09 , 2.545290765409e-08 , 1.266316859091e-06 , 2.809777286862e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 8.948616845744e-13 [ 1.441393859222e-15 , 1.308570254830e-15 , 7.771651880120e-13 , 3.608695661664e-13 , 2.579943241705e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 25 accepted t=0.025 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 2.6000e-02 -4.5149e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 2.6000e-02 min -2.4099e-01 max 5.2925e-05\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 2.6000e-02 min -6.6305e-07 max 1.5600e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m26 TS dt 0.001 time 0.026\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 5.669257684598e-02 [ 4.012077826689e-15 , 3.378248263047e-05 , 1.695598667953e-04 , 5.669231321469e-02 , 5.236709345079e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.244626487845e-06 [ 1.111287895610e-15 , 4.909019686839e-09 , 2.492644114795e-08 , 1.244367175838e-06 , 2.789355251118e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 8.505573943368e-13 [ 1.583352873148e-15 , 1.517928887401e-15 , 7.191461406741e-13 , 3.709680122842e-13 , 2.620202896000e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 26 accepted t=0.026 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 2.7000e-02 -4.5380e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 2.7000e-02 min -2.5087e-01 max 5.7180e-05\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 2.7000e-02 min -7.1706e-07 max 1.6200e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m27 TS dt 0.001 time 0.027\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 5.561352879170e-02 [ 4.742188162339e-15 , 3.315211249224e-05 , 1.687947535235e-04 , 5.561326275210e-02 , 5.848741195712e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.221982776796e-06 [ 1.434857233729e-15 , 4.737045788224e-09 , 2.440945432178e-08 , 1.221729776064e-06 , 2.455822979640e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 7.492626074355e-13 [ 1.471799256091e-15 , 1.551605801139e-15 , 6.327392552182e-13 , 3.206145423359e-13 , 2.413239138089e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 27 accepted t=0.027 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 2.8000e-02 -4.5607e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 2.8000e-02 min -2.6075e-01 max 6.1586e-05\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 2.8000e-02 min -7.7301e-07 max 1.6800e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m28 TS dt 0.001 time 0.028\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 5.457107857955e-02 [ 6.108059881834e-15 , 3.253233789856e-05 , 1.681091848068e-04 , 5.457080994712e-02 , 5.636774145410e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.199358322391e-06 [ 1.430742943078e-15 , 4.569880546601e-09 , 2.390703193734e-08 , 1.199111319063e-06 , 2.597554744570e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 9.888399220838e-13 [ 1.213055839957e-15 , 1.604362711122e-15 , 8.851461322931e-13 , 3.577001257950e-13 , 2.576184980070e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 28 accepted t=0.028 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 2.9000e-02 -4.5830e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 2.9000e-02 min -2.7064e-01 max 6.6142e-05\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 2.9000e-02 min -8.3091e-07 max 1.7400e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m29 TS dt 0.001 time 0.029\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 5.355628021922e-02 [ 4.680506197833e-15 , 3.192303910511e-05 , 1.674966568596e-04 , 5.355600878248e-02 , 5.061705687549e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.177091263043e-06 [ 1.532158673004e-15 , 4.408087780344e-09 , 2.342120397673e-08 , 1.176849972383e-06 , 2.332385523629e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 9.908240394188e-13 [ 1.504438561706e-15 , 1.434826796530e-15 , 8.733313037589e-13 , 3.888278243777e-13 , 2.604482902448e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 29 accepted t=0.029 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 3.0000e-02 -4.6049e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 3.0000e-02 min -2.8052e-01 max 7.0849e-05\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 3.0000e-02 min -8.9075e-07 max 1.8000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m30 TS dt 0.001 time 0.03\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 5.256414624207e-02 [ 4.215708764422e-15 , 3.132409039669e-05 , 1.669515992120e-04 , 5.256387177637e-02 , 5.157355636950e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.155323656071e-06 [ 1.545661757090e-15 , 4.251880014237e-09 , 2.295343583861e-08 , 1.155087793882e-06 , 2.630858981037e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 8.961883861611e-13 [ 1.731070339525e-15 , 2.067118056214e-15 , 7.693832624060e-13 , 3.951543366552e-13 , 2.346248061489e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 30 accepted t=0.03 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 3.1000e-02 -4.6264e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 3.1000e-02 min -2.9041e-01 max 7.5707e-05\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 3.1000e-02 min -9.5255e-07 max 1.8600e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m31 TS dt 0.001 time 0.031\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 5.159187537078e-02 [ 4.338888906702e-15 , 3.073536259933e-05 , 1.664691282338e-04 , 5.159159764575e-02 , 5.107354456266e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.134095728174e-06 [ 2.246478778960e-15 , 4.101281007968e-09 , 2.250304963935e-08 , 1.133865032935e-06 , 2.417051815166e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.011210069814e-12 [ 2.386360708862e-15 , 2.087676269306e-15 , 8.128501265191e-13 , 5.467009811428e-13 , 2.508554588167e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 31 accepted t=0.031 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 3.2000e-02 -4.6475e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 3.2000e-02 min -3.0030e-01 max 8.0715e-05\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 3.2000e-02 min -1.0163e-06 max 1.9200e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m32 TS dt 0.001 time 0.032\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 5.063787329432e-02 [ 5.731908491193e-15 , 3.015672454509e-05 , 1.660448820377e-04 , 5.063759207783e-02 , 5.108537051501e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.113396208824e-06 [ 1.771487981078e-15 , 3.956214697739e-09 , 2.207027982067e-08 , 1.113170413251e-06 , 2.531587303919e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.036304769380e-12 [ 1.683858601103e-15 , 1.767565808297e-15 , 9.307914964006e-13 , 3.812697988887e-13 , 2.493634817972e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 32 accepted t=0.032 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 3.3000e-02 -4.6682e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 3.3000e-02 min -3.1020e-01 max 8.5875e-05\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 3.3000e-02 min -1.0820e-06 max 1.9800e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m33 TS dt 0.001 time 0.033\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 4.970121160164e-02 [ 5.297033443047e-15 , 2.958804394278e-05 , 1.656749123494e-04 , 4.970092666181e-02 , 5.476860074119e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.093188918961e-06 [ 1.577183887834e-15 , 3.816553132944e-09 , 2.165431852189e-08 , 1.092967765742e-06 , 2.908277310757e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.075025124060e-12 [ 1.728434887959e-15 , 1.867580407226e-15 , 9.208919947476e-13 , 5.026051087248e-13 , 2.345603988515e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 33 accepted t=0.033 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 3.4000e-02 -4.6886e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 3.4000e-02 min -3.2009e-01 max 9.1187e-05\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 3.4000e-02 min -1.1497e-06 max 2.0400e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m34 TS dt 0.001 time 0.034\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 4.878132885608e-02 [ 7.449501464838e-15 , 2.902918795986e-05 , 1.653556003420e-04 , 4.878103996223e-02 , 5.227411815352e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.073427575025e-06 [ 1.755961276874e-15 , 3.682143219371e-09 , 2.125412139224e-08 , 1.073210819442e-06 , 2.573096508059e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.100787265338e-12 [ 1.241812343888e-15 , 1.897746829407e-15 , 9.186347903400e-13 , 5.432690836046e-13 , 2.696224856456e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 34 accepted t=0.034 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 3.5000e-02 -4.7086e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 3.5000e-02 min -3.2999e-01 max 9.6651e-05\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 3.5000e-02 min -1.2194e-06 max 2.1000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m35 TS dt 0.001 time 0.035\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 4.787786547392e-02 [ 5.883599810181e-15 , 2.848002360806e-05 , 1.650836094636e-04 , 4.787757239698e-02 , 5.297393796446e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.054062627704e-06 [ 2.486485699778e-15 , 3.552821086601e-09 , 2.086906652549e-08 , 1.053850028537e-06 , 2.631435648856e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.145319120014e-12 [ 2.592994769604e-15 , 2.149623092836e-15 , 9.791700177662e-13 , 5.458189213258e-13 , 2.346323157618e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 35 accepted t=0.035 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 3.6000e-02 -4.7282e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 3.6000e-02 min -3.3989e-01 max 1.0227e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 3.6000e-02 min -1.2911e-06 max 2.1600e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m36 TS dt 0.001 time 0.036\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 4.699057260359e-02 [ 5.988433066880e-15 , 2.794041802346e-05 , 1.648558430763e-04 , 4.699027511621e-02 , 5.456996442930e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.035046293971e-06 [ 2.327360160535e-15 , 3.428417058480e-09 , 2.049898271074e-08 , 1.034837604809e-06 , 2.599846619832e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.208352863258e-12 [ 1.946733495816e-15 , 2.011491924520e-15 , 1.020328163695e-12 , 5.874709421037e-13 , 2.718770619762e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 36 accepted t=0.036 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 3.7000e-02 -4.7475e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 3.7000e-02 min -3.4979e-01 max 1.0804e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 3.7000e-02 min -1.3648e-06 max 2.2200e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m37 TS dt 0.001 time 0.037\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 4.611926188634e-02 [ 6.642359993841e-15 , 2.741023867742e-05 , 1.646694149897e-04 , 4.611895976281e-02 , 5.475737487408e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.016332625899e-06 [ 2.154127367582e-15 , 3.308764292352e-09 , 2.014269107002e-08 , 1.016127615283e-06 , 2.688368407563e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.108858685933e-12 [ 1.881256950445e-15 , 1.917671462790e-15 , 9.497944084238e-13 , 5.202229298445e-13 , 2.383674763206e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 37 accepted t=0.037 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 3.8000e-02 -4.7664e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 3.8000e-02 min -3.5969e-01 max 1.1396e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 3.8000e-02 min -1.4405e-06 max 2.2800e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m38 TS dt 0.001 time 0.038\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 4.526377778648e-02 [ 5.759341129965e-15 , 2.688935354851e-05 , 1.645216283072e-04 , 4.526347080262e-02 , 5.515052481406e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 9.978799688438e-07 [ 1.791564478554e-15 , 3.193694418147e-09 , 1.979971999715e-08 , 9.976784069146e-07 , 2.456224167565e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 38 accepted t=0.038 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 3.9000e-02 -4.7850e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 3.9000e-02 min -3.6960e-01 max 1.2004e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 3.9000e-02 min -1.5182e-06 max 2.3400e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m39 TS dt 0.001 time 0.039\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 4.442160098349e-02 [ 6.476224885192e-15 , 2.638293618395e-05 , 1.644295575635e-04 , 4.442128882414e-02 , 4.965790401799e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 9.800432153936e-07 [ 1.823122533257e-15 , 3.085036917380e-09 , 1.948030710948e-08 , 9.798447347519e-07 , 2.615576047105e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 39 accepted t=0.039 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 4.0000e-02 -4.8032e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 4.0000e-02 min -3.7951e-01 max 1.2627e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 4.0000e-02 min -1.5979e-06 max 2.4000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m40 TS dt 0.001 time 0.04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 4.360043152027e-02 [ 7.793066543202e-15 , 2.587869528955e-05 , 1.643514759582e-04 , 4.360011407828e-02 , 5.062786443030e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 9.621167586853e-07 [ 3.001202140269e-15 , 2.977877882941e-09 , 1.915899621660e-08 , 9.619213702015e-07 , 2.456295943336e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 40 accepted t=0.04 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 4.1000e-02 -4.8211e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 4.1000e-02 min -3.8941e-01 max 1.3266e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 4.1000e-02 min -1.6798e-06 max 2.4600e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m41 TS dt 0.001 time 0.041\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 4.279168766472e-02 [ 5.276827040644e-15 , 2.538429500393e-05 , 1.643048508341e-04 , 4.279136469836e-02 , 5.348589089289e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 9.441115949275e-07 [ 3.446467007045e-15 , 2.875390612566e-09 , 1.885197109344e-08 , 9.439189790396e-07 , 2.692146438570e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 41 accepted t=0.041 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 4.2000e-02 -4.8387e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 4.2000e-02 min -3.9933e-01 max 1.3920e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 4.2000e-02 min -1.7637e-06 max 2.5200e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m42 TS dt 0.001 time 0.042\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 4.199796900181e-02 [ 5.490477787680e-15 , 2.489900424205e-05 , 1.642876197824e-04 , 4.199764028960e-02 , 5.840298092419e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 9.263074985272e-07 [ 2.655859828503e-15 , 2.776990103596e-09 , 1.855689313782e-08 , 9.261174395673e-07 , 2.590451995617e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 42 accepted t=0.042 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 4.3000e-02 -4.8560e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 4.3000e-02 min -4.0924e-01 max 1.4590e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 4.3000e-02 min -1.8496e-06 max 2.5800e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m43 TS dt 0.001 time 0.043\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 4.121948416769e-02 [ 7.645471519710e-15 , 2.442247922394e-05 , 1.642978308079e-04 , 4.121914949166e-02 , 6.424887711920e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 9.086423412159e-07 [ 2.545184551592e-15 , 2.682438522298e-09 , 1.827299440428e-08 , 9.084546254213e-07 , 2.835367091673e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 43 accepted t=0.043 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 4.4000e-02 -4.8729e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 4.4000e-02 min -4.1915e-01 max 1.5276e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 4.4000e-02 min -1.9377e-06 max 2.6400e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m44 TS dt 0.001 time 0.044\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 4.045614353918e-02 [ 6.879648189839e-15 , 2.395451754248e-05 , 1.643336465080e-04 , 4.045580268263e-02 , 6.011806525979e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 8.910753261913e-07 [ 2.869770930129e-15 , 2.591568057296e-09 , 1.799930194549e-08 , 8.908897495489e-07 , 2.949403584479e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 44 accepted t=0.044 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 4.5000e-02 -4.8896e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 4.5000e-02 min -4.2907e-01 max 1.5978e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 4.5000e-02 min -2.0279e-06 max 2.7000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m45 TS dt 0.001 time 0.045\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 3.970781175550e-02 [ 7.639839945491e-15 , 2.349496698786e-05 , 1.643933228246e-04 , 3.970746450269e-02 , 5.666265086370e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 8.735827063106e-07 [ 3.442190768919e-15 , 2.504233596856e-09 , 1.773553481171e-08 , 8.733990636495e-07 , 2.490000624350e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 45 accepted t=0.045 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 4.6000e-02 -4.9060e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 4.6000e-02 min -4.3899e-01 max 1.6695e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 4.6000e-02 min -2.1202e-06 max 2.7600e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m46 TS dt 0.001 time 0.046\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 3.897435182395e-02 [ 1.105273115475e-14 , 2.304369375205e-05 , 1.644752184333e-04 , 3.897399796002e-02 , 5.034234852218e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 8.561479165528e-07 [ 2.098310931822e-15 , 2.420300064671e-09 , 1.748177891349e-08 , 8.559659949853e-07 , 2.636982690584e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 46 accepted t=0.046 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 4.7000e-02 -4.9220e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 4.7000e-02 min -4.4891e-01 max 1.7429e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 4.7000e-02 min -2.2146e-06 max 2.8200e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m47 TS dt 0.001 time 0.047\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 3.825563218185e-02 [ 8.144366289064e-15 , 2.260057129955e-05 , 1.645777789805e-04 , 3.825527149298e-02 , 5.465348661398e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 8.387593323608e-07 [ 3.668919709277e-15 , 2.339637770856e-09 , 1.723689955960e-08 , 8.385789366607e-07 , 2.506084398511e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 47 accepted t=0.047 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 4.8000e-02 -4.9378e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 4.8000e-02 min -4.5883e-01 max 1.8179e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 4.8000e-02 min -2.3113e-06 max 2.8800e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m48 TS dt 0.001 time 0.048\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 3.755152637672e-02 [ 8.532509959426e-15 , 2.216547648501e-05 , 1.646995346654e-04 , 3.755115865025e-02 , 5.619057385672e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 8.214083328833e-07 [ 2.816473371519e-15 , 2.262118918438e-09 , 1.700137122065e-08 , 8.212292527210e-07 , 2.271927611979e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 48 accepted t=0.048 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 4.9000e-02 -4.9533e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 4.9000e-02 min -4.6876e-01 max 1.8945e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 4.9000e-02 min -2.4101e-06 max 2.9400e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m49 TS dt 0.001 time 0.049\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 3.686191157898e-02 [ 6.931332183651e-15 , 2.173828822847e-05 , 1.648391061228e-04 , 3.686153660351e-02 , 5.928812896974e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 8.040885068661e-07 [ 2.316225609514e-15 , 2.187621032060e-09 , 1.677394302084e-08 , 8.039105522531e-07 , 2.456633971875e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 49 accepted t=0.049 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 5.0000e-02 -4.9685e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 5.0000e-02 min -4.7868e-01 max 1.9727e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 5.0000e-02 min -2.5111e-06 max 3.0000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m50 TS dt 0.001 time 0.05\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 3.618666738923e-02 [ 6.911211901406e-15 , 2.131888705995e-05 , 1.649951757987e-04 , 3.618628495488e-02 , 5.600059753495e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 7.867971826990e-07 [ 3.098324965426e-15 , 2.116027010900e-09 , 1.655563092721e-08 , 7.866201371801e-07 , 2.617553050762e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 50 accepted t=0.05 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 5.1000e-02 -4.9835e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 5.1000e-02 min -4.8861e-01 max 2.0526e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 5.1000e-02 min -2.6143e-06 max 3.0600e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m51 TS dt 0.001 time 0.051\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 3.552567499575e-02 [ 5.776561465352e-15 , 2.090715498556e-05 , 1.651665145868e-04 , 3.552528489424e-02 , 5.468446948591e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 7.695336147428e-07 [ 2.837558357991e-15 , 2.047216417165e-09 , 1.634521558932e-08 , 7.693572817953e-07 , 2.343130632259e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 51 accepted t=0.051 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 5.2000e-02 -4.9981e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 5.2000e-02 min -4.9854e-01 max 2.1341e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 5.2000e-02 min -2.7197e-06 max 3.1200e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m52 TS dt 0.001 time 0.052\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 3.487881668218e-02 [ 6.936401962789e-15 , 2.050297543966e-05 , 1.653519475771e-04 , 3.487841870714e-02 , 5.447077610546e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 7.522999338243e-07 [ 3.026008312830e-15 , 1.981079368419e-09 , 1.614224363403e-08 , 7.521241212240e-07 , 2.478224413040e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 52 accepted t=0.052 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 5.3000e-02 -5.0125e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 5.3000e-02 min -5.0847e-01 max 2.2173e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 5.3000e-02 min -2.8274e-06 max 3.1800e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m53 TS dt 0.001 time 0.053\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 3.424597552206e-02 [ 9.690730753172e-15 , 2.010623330890e-05 , 1.655503702735e-04 , 3.424556946923e-02 , 5.524120168347e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 7.351010366380e-07 [ 2.551663100403e-15 , 1.917504085742e-09 , 1.594675148265e-08 , 7.349255461348e-07 , 2.425256090126e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 53 accepted t=0.053 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 5.4000e-02 -5.0267e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 5.4000e-02 min -5.1840e-01 max 2.3022e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 5.4000e-02 min -2.9373e-06 max 3.2400e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m54 TS dt 0.001 time 0.054\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 3.362703519991e-02 [ 1.271471674518e-14 , 1.971681492000e-05 , 1.657607379230e-04 , 3.362662086741e-02 , 5.973919525266e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 7.179445579059e-07 [ 2.725748255868e-15 , 1.856385832249e-09 , 1.575831771161e-08 , 7.177691951325e-07 , 2.508819222158e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 54 accepted t=0.054 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 5.5000e-02 -5.0406e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 5.5000e-02 min -5.2834e-01 max 2.3887e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 5.5000e-02 min -3.0495e-06 max 3.3000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m55 TS dt 0.001 time 0.055\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 3.302187987463e-02 [ 1.091725381131e-14 , 1.933460807164e-05 , 1.659820569189e-04 , 3.302145706331e-02 , 5.656402674299e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 7.008409815194e-07 [ 3.279915811497e-15 , 1.797618869348e-09 , 1.557713951856e-08 , 7.006655426577e-07 , 2.313750617021e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 55 accepted t=0.055 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 5.6000e-02 -5.0543e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 5.6000e-02 min -5.3827e-01 max 2.4769e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 5.6000e-02 min -3.1641e-06 max 3.3600e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m56 TS dt 0.001 time 0.056\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 3.243039409697e-02 [ 1.112505001945e-14 , 1.895950202786e-05 , 1.662133966687e-04 , 3.242996261066e-02 , 5.620672300781e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 6.838040497603e-07 [ 3.492500199689e-15 , 1.741103046802e-09 , 1.540235786053e-08 , 6.836283452294e-07 , 2.544859302881e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 56 accepted t=0.056 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 5.7000e-02 -5.0677e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 5.7000e-02 min -5.4821e-01 max 2.5668e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 5.7000e-02 min -3.2809e-06 max 3.4200e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m57 TS dt 0.001 time 0.057\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 3.185246271105e-02 [ 1.063516130877e-14 , 1.859138754199e-05 , 1.664538650172e-04 , 3.185202235699e-02 , 5.652789780674e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 6.668502493861e-07 [ 3.446794469326e-15 , 1.686739616056e-09 , 1.523442334104e-08 , 6.666740750630e-07 , 2.584886002570e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 57 accepted t=0.057 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 5.8000e-02 -5.0808e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 5.8000e-02 min -5.5815e-01 max 2.6584e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 5.8000e-02 min -3.4001e-06 max 3.4800e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m58 TS dt 0.001 time 0.058\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 3.128797076727e-02 [ 1.285994590798e-14 , 1.823015685795e-05 , 1.667026261618e-04 , 3.128752135644e-02 , 5.638511801646e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 6.499997309098e-07 [ 2.668410998742e-15 , 1.634434140554e-09 , 1.507225045041e-08 , 6.498229036239e-07 , 2.787551418450e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 58 accepted t=0.058 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 5.9000e-02 -5.0938e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 5.9000e-02 min -5.6809e-01 max 2.7518e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 5.9000e-02 min -3.5216e-06 max 3.5400e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m59 TS dt 0.001 time 0.059\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 3.073680343111e-02 [ 9.327741334022e-15 , 1.787570371426e-05 , 1.669588828648e-04 , 3.073634477867e-02 , 5.734785442757e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 6.332763994492e-07 [ 2.754015344932e-15 , 1.584092978922e-09 , 1.491578991885e-08 , 6.330987347641e-07 , 2.278352739078e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 59 accepted t=0.059 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 6.0000e-02 -5.1065e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 6.0000e-02 min -5.7804e-01 max 2.8468e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 6.0000e-02 min -3.6455e-06 max 3.6000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m60 TS dt 0.001 time 0.06\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 3.019884587576e-02 [ 1.264637265172e-14 , 1.752792335055e-05 , 1.672218864405e-04 , 3.019837780147e-02 , 5.547746874075e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 6.167073385057e-07 [ 3.442411019005e-15 , 1.535627219605e-09 , 1.476454700031e-08 , 6.165286622434e-07 , 2.639928286920e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 60 accepted t=0.06 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 6.1000e-02 -5.1190e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 6.1000e-02 min -5.8798e-01 max 2.9436e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 6.1000e-02 min -3.7718e-06 max 3.6600e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m61 TS dt 0.001 time 0.061\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.967398315843e-02 [ 1.594902414784e-14 , 1.718671250963e-05 , 1.674909189283e-04 , 2.967350548715e-02 , 4.865261179509e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 6.003245662812e-07 [ 2.482345779608e-15 , 1.488949901834e-09 , 1.461872188157e-08 , 6.001446999511e-07 , 2.395523856061e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 61 accepted t=0.061 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 6.2000e-02 -5.1312e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 6.2000e-02 min -5.9793e-01 max 3.0422e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 6.2000e-02 min -3.9006e-06 max 3.7200e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m62 TS dt 0.001 time 0.062\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.916210008985e-02 [ 9.097969127479e-15 , 1.685196942793e-05 , 1.677653110350e-04 , 2.916161265194e-02 , 5.634598509713e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 5.841640155995e-07 [ 5.121325212542e-15 , 1.443974342276e-09 , 1.447765032330e-08 , 5.839827991479e-07 , 2.128663901867e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 62 accepted t=0.062 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 6.3000e-02 -5.1433e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 6.3000e-02 min -6.0787e-01 max 3.1425e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 6.3000e-02 min -4.0317e-06 max 3.7800e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m63 TS dt 0.001 time 0.063\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.866308110216e-02 [ 1.031579300578e-14 , 1.652359384953e-05 , 1.680444177013e-04 , 2.866258373409e-02 , 5.431762348967e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 5.682657403537e-07 [ 3.552639181627e-15 , 1.400619646549e-09 , 1.434148846187e-08 , 5.680830147373e-07 , 2.356017247946e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 63 accepted t=0.063 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 6.4000e-02 -5.1551e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 6.4000e-02 min -6.1782e-01 max 3.2446e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 6.4000e-02 min -4.1653e-06 max 3.8400e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m64 TS dt 0.001 time 0.064\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.817681008286e-02 [ 8.335650777894e-15 , 1.620148700720e-05 , 1.683276373146e-04 , 2.817630262763e-02 , 4.900231028959e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 5.526754060460e-07 [ 4.584634954697e-15 , 1.358806633469e-09 , 1.420894636503e-08 , 5.524910532631e-07 , 2.699836749052e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 64 accepted t=0.064 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 6.5000e-02 -5.1667e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 6.5000e-02 min -6.2777e-01 max 3.3484e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 6.5000e-02 min -4.3013e-06 max 3.9000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m65 TS dt 0.001 time 0.065\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.770317020429e-02 [ 9.888438403077e-15 , 1.588555163167e-05 , 1.686143959472e-04 , 2.770265251203e-02 , 5.744092099078e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 5.374434712390e-07 [ 1.995377143301e-15 , 1.318456374023e-09 , 1.408133159959e-08 , 5.372573522536e-07 , 2.666610151157e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 65 accepted t=0.065 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 6.6000e-02 -5.1781e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 6.6000e-02 min -6.3773e-01 max 3.4541e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 6.6000e-02 min -4.4399e-06 max 3.9600e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m66 TS dt 0.001 time 0.066\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.724204376878e-02 [ 1.462079288336e-14 , 1.557569192729e-05 , 1.689041496997e-04 , 2.724151569730e-02 , 5.508945069051e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 5.226253759554e-07 [ 3.555260849997e-15 , 1.279497076456e-09 , 1.395607439199e-08 , 5.224374359359e-07 , 2.606102763361e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 66 accepted t=0.066 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 6.7000e-02 -5.1893e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 6.7000e-02 min -6.4768e-01 max 3.5615e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 6.7000e-02 min -4.5809e-06 max 4.0200e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m67 TS dt 0.001 time 0.067\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.679331199819e-02 [ 2.034234697936e-14 , 1.527181359454e-05 , 1.691963809957e-04 , 2.679277341352e-02 , 5.593938731335e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 5.082828265439e-07 [ 3.643716762724e-15 , 1.241854470034e-09 , 1.383481438415e-08 , 5.080929909651e-07 , 2.279255108199e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 67 accepted t=0.067 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 6.8000e-02 -5.2003e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 6.8000e-02 min -6.5764e-01 max 3.6707e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 6.8000e-02 min -4.7245e-06 max 4.0800e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m68 TS dt 0.001 time 0.068\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.635685485294e-02 [ 1.429118394773e-14 , 1.497382378142e-05 , 1.694906084141e-04 , 2.635630562991e-02 , 5.771678181683e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 4.944818479705e-07 [ 4.359770639930e-15 , 1.205458818641e-09 , 1.371615625856e-08 , 4.942901090441e-07 , 2.581061512467e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 68 accepted t=0.068 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 6.9000e-02 -5.2111e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 6.9000e-02 min -6.6759e-01 max 3.7818e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 6.9000e-02 min -4.8706e-06 max 4.1400e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m69 TS dt 0.001 time 0.069\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.593255084327e-02 [ 9.769965346368e-15 , 1.468163111560e-05 , 1.697863655576e-04 , 2.593199086608e-02 , 6.089671060814e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 4.812943258555e-07 [ 3.263603041414e-15 , 1.170243775633e-09 , 1.359981398269e-08 , 4.811007209408e-07 , 2.813621197281e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 69 accepted t=0.069 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 7.0000e-02 -5.2218e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 7.0000e-02 min -6.7755e-01 max 3.8947e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 7.0000e-02 min -5.0192e-06 max 4.2000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m70 TS dt 0.001 time 0.07\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.552027679421e-02 [ 1.852735567317e-14 , 1.439514566166e-05 , 1.700832187832e-04 , 2.551970595699e-02 , 6.034646397214e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 4.687974658479e-07 [ 2.894811473968e-15 , 1.136145723956e-09 , 1.348586970620e-08 , 4.686020747676e-07 , 2.726707139879e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 70 accepted t=0.07 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 7.1000e-02 -5.2322e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 7.1000e-02 min -6.8751e-01 max 4.0094e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 7.1000e-02 min -5.1705e-06 max 4.2600e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m71 TS dt 0.001 time 0.071\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.511990766746e-02 [ 2.806109186672e-14 , 1.411427893667e-05 , 1.703807518663e-04 , 2.511932587487e-02 , 5.312991294539e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 4.570712323088e-07 [ 4.674303723267e-15 , 1.103103092740e-09 , 1.337385407823e-08 , 4.568741999663e-07 , 2.652111285236e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 71 accepted t=0.071 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 7.2000e-02 -5.2425e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 7.2000e-02 min -6.9748e-01 max 4.1259e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 7.2000e-02 min -5.3243e-06 max 4.3200e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m72 TS dt 0.001 time 0.072\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.473131632994e-02 [ 2.276707906155e-14 , 1.383894385804e-05 , 1.706785779423e-04 , 2.473072349767e-02 , 5.802071589945e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 4.461997071932e-07 [ 7.024405187259e-15 , 1.071054748689e-09 , 1.326325378774e-08 , 4.460012529578e-07 , 2.801883832594e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 72 accepted t=0.072 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 7.3000e-02 -5.2526e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 7.3000e-02 min -7.0744e-01 max 4.2443e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 7.3000e-02 min -5.4807e-06 max 4.3800e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m73 TS dt 0.001 time 0.073\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.435437336120e-02 [ 1.346211939423e-14 , 1.356905479570e-05 , 1.709763219597e-04 , 2.435376941656e-02 , 5.769142268324e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 4.362677781676e-07 [ 6.442803677088e-15 , 1.039946766255e-09 , 1.315325647738e-08 , 4.360682109739e-07 , 2.037987747926e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 73 accepted t=0.073 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 7.4000e-02 -5.2625e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 7.4000e-02 min -7.1740e-01 max 4.3646e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 7.4000e-02 min -5.6398e-06 max 4.4400e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m74 TS dt 0.001 time 0.074\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.398894683046e-02 [ 1.559210801906e-14 , 1.330452748200e-05 , 1.712736364510e-04 , 2.398833171284e-02 , 5.512352496227e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 4.273611217468e-07 [ 3.663260214488e-15 , 1.009722010080e-09 , 1.304352558120e-08 , 4.271608306979e-07 , 2.621289035724e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 74 accepted t=0.074 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 7.5000e-02 -5.2722e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 7.5000e-02 min -7.2737e-01 max 4.4868e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 7.5000e-02 min -5.8015e-06 max 4.5000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m75 TS dt 0.001 time 0.075\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.363490210248e-02 [ 9.611759624560e-15 , 1.304527905927e-05 , 1.715701926266e-04 , 2.363427576389e-02 , 5.594572266542e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 4.195615480010e-07 [ 3.392788953604e-15 , 9.803312123593e-10 , 1.293450767796e-08 , 4.193609781832e-07 , 2.460603707173e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 75 accepted t=0.075 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 7.6000e-02 -5.2817e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 7.6000e-02 min -7.3734e-01 max 4.6108e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 7.6000e-02 min -5.9659e-06 max 4.5600e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m76 TS dt 0.001 time 0.076\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.329210164136e-02 [ 9.383386491099e-15 , 1.279122802728e-05 , 1.718656751876e-04 , 2.329146404685e-02 , 4.574875342385e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 4.129466883112e-07 [ 5.657822246763e-15 , 9.517267011516e-10 , 1.282504149310e-08 , 4.127463869183e-07 , 2.847594226386e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 76 accepted t=0.076 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 7.7000e-02 -5.2911e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 7.7000e-02 min -7.4731e-01 max 4.7367e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 7.7000e-02 min -6.1329e-06 max 4.6200e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m77 TS dt 0.001 time 0.077\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.296040482216e-02 [ 1.912477868282e-14 , 1.254229424044e-05 , 1.721597878156e-04 , 2.295975595027e-02 , 5.445612008832e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 4.075842800831e-07 [ 2.706865729274e-15 , 9.238601898922e-10 , 1.271527371179e-08 , 4.073848471257e-07 , 2.449508622595e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 77 accepted t=0.077 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 7.8000e-02 -5.3004e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 7.8000e-02 min -7.5728e-01 max 4.8646e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 7.8000e-02 min -6.3027e-06 max 4.6800e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m78 TS dt 0.001 time 0.078\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.263966775669e-02 [ 2.394974331236e-14 , 1.229839890649e-05 , 1.724522550590e-04 , 2.263900759977e-02 , 5.465764806354e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 4.035324258368e-07 [ 3.162964744700e-15 , 8.966904889204e-10 , 1.260459167438e-08 , 4.033345248259e-07 , 2.957274282287e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 78 accepted t=0.078 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 7.9000e-02 -5.3094e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 7.9000e-02 min -7.6725e-01 max 4.9943e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 7.9000e-02 min -6.4752e-06 max 4.7400e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m79 TS dt 0.001 time 0.079\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.232974312826e-02 [ 2.541069286704e-14 , 1.205946451920e-05 , 1.727428149780e-04 , 2.232907169282e-02 , 5.696882498964e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 4.008336906056e-07 [ 4.190288967289e-15 , 8.701776884775e-10 , 1.249200013610e-08 , 4.006380414387e-07 , 2.730286586025e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 79 accepted t=0.079 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 8.0000e-02 -5.3183e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 8.0000e-02 min -7.7722e-01 max 5.1260e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 8.0000e-02 min -6.6504e-06 max 4.8000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m80 TS dt 0.001 time 0.08\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.203048005791e-02 [ 2.459071092420e-14 , 1.182541491716e-05 , 1.730312150690e-04 , 2.202979736494e-02 , 5.493579396025e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 3.995144347580e-07 [ 4.136878904813e-15 , 8.442818167420e-10 , 1.237784637673e-08 , 3.993217495795e-07 , 2.688840165958e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 80 accepted t=0.08 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 8.1000e-02 -5.3271e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 8.1000e-02 min -7.8720e-01 max 5.2596e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 8.1000e-02 min -6.8284e-06 max 4.8600e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m81 TS dt 0.001 time 0.081\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.174172396771e-02 [ 2.117749026126e-14 , 1.159617517868e-05 , 1.733172265641e-04 , 2.174103005278e-02 , 6.244963852910e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 3.995834533407e-07 [ 4.625594725993e-15 , 8.189711287037e-10 , 1.226133461124e-08 , 3.993944480629e-07 , 2.508936188951e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 81 accepted t=0.081 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 8.2000e-02 -5.3357e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 8.2000e-02 min -7.9717e-01 max 5.3951e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 8.2000e-02 min -7.0091e-06 max 4.9200e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m82 TS dt 0.001 time 0.082\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.146331647985e-02 [ 1.780481008029e-14 , 1.137167168264e-05 , 1.736006251239e-04 , 2.146261139335e-02 , 6.246858531349e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 4.010294020238e-07 [ 3.547718092937e-15 , 7.942125428247e-10 , 1.214279299248e-08 , 4.008447368898e-07 , 2.960552634373e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 82 accepted t=0.082 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 8.3000e-02 -5.3442e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 8.3000e-02 min -8.0715e-01 max 5.5325e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 8.3000e-02 min -7.1927e-06 max 4.9800e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m83 TS dt 0.001 time 0.083\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.119509533627e-02 [ 1.568858437723e-14 , 1.115183202433e-05 , 1.738812101435e-04 , 2.119437914342e-02 , 5.997962551006e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 4.038232016313e-07 [ 3.735749478257e-15 , 7.699769495153e-10 , 1.202084301176e-08 , 4.036435118325e-07 , 2.496116008540e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 83 accepted t=0.083 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 8.4000e-02 -5.3525e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 8.4000e-02 min -8.1713e-01 max 5.6720e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 8.4000e-02 min -7.3790e-06 max 5.0400e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m84 TS dt 0.001 time 0.084\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.093689434231e-02 [ 2.428900086495e-14 , 1.093658503842e-05 , 1.741587823436e-04 , 2.093616712320e-02 , 5.377818387248e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 4.079176731596e-07 [ 5.126549430685e-15 , 7.462360222067e-10 , 1.189585283503e-08 , 4.077434976710e-07 , 3.006507346679e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 84 accepted t=0.084 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 8.5000e-02 -5.3606e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 8.5000e-02 min -8.2711e-01 max 5.8134e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 8.5000e-02 min -7.5682e-06 max 5.1000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m85 TS dt 0.001 time 0.085\n"
]
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "mGFbCh7jeWZA",
"outputId": "a216a51c-54dd-4963-bbac-e7c0b61a874a"
},
"source": [
"dir='/content/um_view/tutorials/adv-2'\n",
"bin_dir='/content/um_view/bin'\n",
"nb_proc=1\n",
"import os\n",
"os.chdir(dir)\n",
"!rm -f out_*\n",
"!{bin_dir}/mofem_part -my_file adv2_thermo_plast_2D.cub \\\n",
"-output_file ab.h5m -my_nparts {nb_proc} -dim 2 -adj_dim 1\n",
"!{bin_dir}/mpirun --allow-run-as-root -np {nb_proc} \\\n",
"./thermo_plastic_2d \\\n",
"-file_name ab.h5m \\\n",
"-ts_dt 0.001 \\\n",
"-ts_max_time 0.085 \\\n",
"-ts_type theta \\\n",
"-snes_linesearch_type l2 \\\n",
"-snes_stol 1e-6 \\\n",
"-snes_atol 1e-6 \\\n",
"-snes_rtol 1e-6 \\\n",
"-order 2 \\\n",
"-ts_max_snes_failres -1 \\\n",
"-ts_theta_initial_guess_extrapolate 1 \\\n",
"-ts_theta_theta 1 \\\n",
"-ts_exact_final_time matchstep 1 \\\n",
"-fix_skin_flux 0 \\\n",
"-snes_linesearch_type l2 \\\n",
"-number_of_cycles_in_total_time 0 \\\n",
"-fraction_of_dissipation 0.9 \\\n",
"-young_modulus 206913 \\\n",
"-poisson_ration 0.29 \\\n",
"-yield_stress 450 \\\n",
"-hardening 130 \\\n",
"-Qinf 265 \\\n",
"-b_iso 17 \\\n",
"-hardening_viscous 100 \\\n",
"-omega_0 2e-3 \\\n",
"-omega_h 2e-3 \\\n",
"-omega_inf 2e-3 \\\n",
"-ts_max_steps 1000 \\\n",
"-cn 1 \\\n",
"-capacity 3.6 2>&1 | tee log_thermo_plasticity"
],
"execution_count": 8,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0mMoFEM version 0.12.1 (MOAB 5.3.0 Petsc Release Version 3.11.4, Sep, 28, 2019 )\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0mgit commit id dd3b8fb472b0ba2f863ca4b1faf2452065f5e5f0\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0mLocal time: 2021-10-14 9:57:33\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0mUTC time: 2021-10-14 9:57:33\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[MeshsetMng] \u001b[0mmeshset 12682136550675316752 type BLOCKSET UNKNOWNNAME msId 1 name FIX_Y block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[MeshsetMng] \u001b[0mmeshset 12682136550675316753 type BLOCKSET UNKNOWNNAME msId 2 name FIX_X block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[MeshsetMng] \u001b[0mmeshset 12682136550675316754 type BLOCKSET UNKNOWNNAME msId 3 name FIX_Y1 block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[MeshsetMng] \u001b[0mmeshset 12682136550675316755 type BLOCKSET UNKNOWNNAME msId 4 name TEMPERATURE_1 block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[MeshsetMng] \u001b[0mmeshset 12682136550675316756 type BLOCKSET UNKNOWNNAME msId 5 name REACTION block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[MeshsetMng] \u001b[0mmeshset 12682136550675316757 type BLOCKSET UNKNOWNNAME msId 6 name ZERO_FLUX block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[mofem_part] \u001b[0mmeshset 12682136550675316752 type BLOCKSET UNKNOWNNAME msId 1 name FIX_Y block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[mofem_part] \u001b[0mmeshset 12682136550675316753 type BLOCKSET UNKNOWNNAME msId 2 name FIX_X block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[mofem_part] \u001b[0mmeshset 12682136550675316754 type BLOCKSET UNKNOWNNAME msId 3 name FIX_Y1 block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[mofem_part] \u001b[0mmeshset 12682136550675316755 type BLOCKSET UNKNOWNNAME msId 4 name TEMPERATURE_1 block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[mofem_part] \u001b[0mmeshset 12682136550675316756 type BLOCKSET UNKNOWNNAME msId 5 name REACTION block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[mofem_part] \u001b[0mmeshset 12682136550675316757 type BLOCKSET UNKNOWNNAME msId 6 name ZERO_FLUX block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[ProblemsManager] \u001b[0mFinite elements in problem: row lower 0 row upper 129 nb. elems 129 ( 129 )\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0mMoFEM version 0.12.1 (MOAB 5.3.0 Petsc Release Version 3.11.4, Sep, 28, 2019 )\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0mgit commit id dd3b8fb472b0ba2f863ca4b1faf2452065f5e5f0\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0mLocal time: 2021-10-14 9:57:33\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0mUTC time: 2021-10-14 9:57:33\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[MeshsetMng] \u001b[0mmeshset 12682136550675316752 type BLOCKSET UNKNOWNNAME msId 1 name FIX_Y block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[MeshsetMng] \u001b[0mmeshset 12682136550675316753 type BLOCKSET UNKNOWNNAME msId 2 name FIX_X block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[MeshsetMng] \u001b[0mmeshset 12682136550675316754 type BLOCKSET UNKNOWNNAME msId 3 name FIX_Y1 block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[MeshsetMng] \u001b[0mmeshset 12682136550675316755 type BLOCKSET UNKNOWNNAME msId 4 name TEMPERATURE_1 block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[MeshsetMng] \u001b[0mmeshset 12682136550675316756 type BLOCKSET UNKNOWNNAME msId 5 name REACTION block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[MeshsetMng] \u001b[0mmeshset 12682136550675316757 type BLOCKSET UNKNOWNNAME msId 6 name ZERO_FLUX block header: blockCol = 4294967295 blockMat = 0 blockDimension = 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[FieldCore] \u001b[0mAdd field U field_id 1 space H1 approximation base AINSWORTH_LEGENDRE_BASE rank 2 meshset 12682136550675316759\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[FieldCore] \u001b[0mAdd field TAU field_id 2 space L2 approximation base AINSWORTH_LEGENDRE_BASE rank 1 meshset 12682136550675316760\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[FieldCore] \u001b[0mAdd field EP field_id 4 space L2 approximation base AINSWORTH_LEGENDRE_BASE rank 3 meshset 12682136550675316761\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[FieldCore] \u001b[0mAdd field T field_id 8 space L2 approximation base AINSWORTH_LEGENDRE_BASE rank 1 meshset 12682136550675316762\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[FieldCore] \u001b[0mAdd field FLUX field_id 16 space HCURL approximation base DEMKOWICZ_JACOBI_BASE rank 1 meshset 12682136550675316763\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[FECore] \u001b[0mAdd finite element dFE\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[FECore] \u001b[0mAdd finite element bFE\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[ProblemCore] \u001b[0mAdd problem SimpleProblem\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[FieldCore] \u001b[0mNumber of dofs 3215\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[FECore] \u001b[0mFinite element dFE added. Nb. of elements added 129\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[FECore] \u001b[0mFinite element bFE added. Nb. of elements added 39\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[FECore] \u001b[0mNumber of adjacencies 1833\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[ProblemsManager] \u001b[0mSimpleProblem Nb. local dof 3215 by 3215 nb global dofs 3215 by 3215\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[ProblemsManager] \u001b[0m FEs ghost dofs on problem SimpleProblem Nb. ghost dof 0 by 0 Nb. local dof 3215 by 3215\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mYoung modulus 206913\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mPoisson ratio 0.29\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mYield stress 450\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mHardening 130\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mViscous hardening 100\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mSaturation yield stress 265\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mSaturation exponent 17\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mcn 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mfraction_of_dissipation 0.9\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mScaled Young modulus 1\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mScaled Poisson ratio 0.29\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mScaled Yield stress 0.00217483\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mScaled Hardening 0.000628283\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mScaled Viscous hardening 0.000483295\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mScaled Saturation yield stress 0.00128073\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mScaled heat capacity 1.73986e-05\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mSet temerature 0 on ents:\n",
"\tEdge 80 - 82\n",
"\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 0.0000e+00 0.0000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 0.0000e+00 min 0.0000e+00 max 0.0000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 0.0000e+00 min 0.0000e+00 max 0.0000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m0 TS dt 0.001 time 0.\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 4.122982155350e-01 [ 4.122982155350e-01 , 3.407171532345e-18 , 0.000000000000e+00 , 0.000000000000e+00 , 0.000000000000e+00 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.226803061815e-15 [ 1.020523295542e-16 , 3.784169273450e-18 , 1.222545195309e-15 , 0.000000000000e+00 , 0.000000000000e+00 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 0 accepted t=0 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 1.0000e-03 -1.4429e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 1.0000e-03 min -4.1844e-03 max 9.1451e-17\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 1.0000e-03 min -3.2716e-16 max 6.0000e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m1 TS dt 0.001 time 0.001\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.245857282698e-15 [ 2.398582103703e-16 , 3.413677733843e-18 , 1.222545195310e-15 , 0.000000000000e+00 , 0.000000000000e+00 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 1 accepted t=0.001 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 2.0000e-03 -2.8858e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 2.0000e-03 min -8.3689e-03 max 1.8290e-16\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 2.0000e-03 min -6.5432e-16 max 1.2000e-01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m2 TS dt 0.001 time 0.002\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 6.509588707205e-02 [ 5.332175192462e-16 , 6.509588707205e-02 , 1.222545195310e-15 , 0.000000000000e+00 , 0.000000000000e+00 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 9.843759786714e-01 [ 4.801413636468e-16 , 5.334633616886e-02 , 2.280587891093e-14 , 9.829294154732e-01 , 0.000000000000e+00 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.304534899507e+00 [ 5.344971778497e-16 , 4.536207720912e-02 , 2.038796820854e-04 , 1.303745966213e+00 , 1.040455801140e-14 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 3 SNES Function norm 1.404660484438e+00 [ 5.984482811484e-16 , 3.932390954102e-02 , 3.813297405041e-04 , 1.404109882191e+00 , 1.038385486774e-14 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 4 SNES Function norm 1.413246200469e+00 [ 6.043854849026e-16 , 3.442866134778e-02 , 5.160355047358e-04 , 1.412826678727e+00 , 1.262113065791e-14 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 5 SNES Function norm 1.378008784671e+00 [ 6.251718369233e-16 , 3.023503014022e-02 , 6.174970752579e-04 , 1.377676911427e+00 , 1.497870786514e-14 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 6 SNES Function norm 1.318586135883e+00 [ 6.269936062536e-16 , 2.646154929203e-02 , 6.962405699016e-04 , 1.318320408474e+00 , 1.808697921135e-14 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 7 SNES Function norm 1.242853329876e+00 [ 5.225157638008e-16 , 2.290264025019e-02 , 7.606812010580e-04 , 1.242642060297e+00 , 1.890540689626e-14 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 8 SNES Function norm 1.152717236200e+00 [ 4.928912719611e-16 , 1.938582574624e-02 , 8.174475173374e-04 , 1.152553924193e+00 , 2.174822004119e-14 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 9 SNES Function norm 1.045906810657e+00 [ 4.991051755457e-16 , 1.574615064391e-02 , 8.717559230142e-04 , 1.045787911271e+00 , 2.672598228657e-14 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 10 SNES Function norm 9.150352133347e-01 [ 4.094680955459e-16 , 1.180630619175e-02 , 9.259338887772e-04 , 9.149585757962e-01 , 2.906084176589e-14 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 11 SNES Function norm 7.409386445249e-01 [ 3.809119920344e-16 , 7.324145864194e-03 , 9.717111714472e-04 , 7.409018069995e-01 , 2.961675715770e-14 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 12 SNES Function norm 4.545309570002e-01 [ 3.403465128475e-16 , 1.694464356876e-03 , 9.468192099663e-04 , 4.545268124054e-01 , 3.854358239861e-14 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 13 SNES Function norm 4.028564410797e-03 [ 2.539669298676e-16 , 1.186100148200e-04 , 2.868659654768e-05 , 4.026715777840e-03 , 5.423263125432e-14 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 14 SNES Function norm 1.271089004980e-04 [ 1.515703787398e-16 , 6.801112985090e-08 , 3.387322194889e-07 , 1.271084309587e-04 , 5.432802113824e-14 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 15 SNES Function norm 2.757685337202e-11 [ 1.839732531710e-16 , 3.907815459293e-14 , 1.056604173339e-13 , 2.757658431687e-11 , 4.634713147966e-14 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 2 accepted t=0.002 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 3.0000e-03 -3.4744e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 3.0000e-03 min -1.6445e-02 max 1.3297e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 3.0000e-03 min -1.4439e-06 max 1.8000e-01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m3 TS dt 0.001 time 0.003\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.845764408401e+01 [ 7.029214505095e-16 , 3.314639411212e-02 , 2.692298207023e-02 , 1.845759468624e+01 , 1.058657148279e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 2.802383588681e+00 [ 8.109622668428e-16 , 8.938468581569e-03 , 1.904167318161e-02 , 2.802304640215e+00 , 1.112068354886e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.061894421721e+00 [ 5.365028914071e-16 , 9.205499810629e-04 , 4.460235122392e-03 , 1.061884655587e+00 , 1.219564388208e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 3 SNES Function norm 3.803145781228e-03 [ 2.253455246692e-16 , 1.789660633172e-05 , 4.696796331452e-05 , 3.802813636662e-03 , 1.214668364830e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 4 SNES Function norm 4.343188486159e-06 [ 2.669075214578e-16 , 3.778819184446e-09 , 2.335962066495e-08 , 4.343124022516e-06 , 1.186795555220e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 3 accepted t=0.003 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 4.0000e-03 -3.5868e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 4.0000e-03 min -2.7624e-02 max 5.2375e-04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 4.0000e-03 min -7.1138e-06 max 2.4000e-01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m4 TS dt 0.001 time 0.004\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.932114619353e+01 [ 5.495689146005e-16 , 1.295861259662e-02 , 1.083071766447e-01 , 2.932094329541e+01 , 2.553027677464e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.009026957582e+00 [ 3.823078775452e-16 , 7.723431214720e-04 , 6.788972898290e-03 , 1.009003822817e+00 , 2.248620522448e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 2.935237983961e-02 [ 3.010987413998e-16 , 1.134959227119e-05 , 1.471804636918e-04 , 2.935200864245e-02 , 2.171086651323e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 3 SNES Function norm 6.223969095772e-07 [ 2.411767378283e-16 , 5.207790213373e-10 , 7.105669410011e-09 , 6.223561289990e-07 , 2.387210018284e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 4 accepted t=0.004 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 5.0000e-03 -3.5284e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 5.0000e-03 min -4.0868e-02 max 1.1421e-03\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 5.0000e-03 min -1.8256e-05 max 3.0000e-01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m5 TS dt 0.001 time 0.005\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.737511798617e+01 [ 6.734313489011e-16 , 5.597087848232e-03 , 1.479715751817e-01 , 2.737471749338e+01 , 5.643500173558e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 6.431827686068e-01 [ 5.281861963560e-16 , 8.532859716342e-05 , 2.413971838920e-03 , 6.431782329119e-01 , 4.139398852036e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.290372408183e-03 [ 3.960028512290e-16 , 1.114935198142e-07 , 1.051571295484e-05 , 1.290329554474e-03 , 3.807834319155e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 3 SNES Function norm 1.913394280304e-10 [ 3.320565331844e-16 , 5.532077090506e-14 , 3.646762333484e-12 , 1.913042951781e-10 , 3.760710311536e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 5 accepted t=0.005 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 6.0000e-03 -3.4341e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 6.0000e-03 min -5.5391e-02 max 1.9103e-03\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 6.0000e-03 min -3.4277e-05 max 3.6000e-01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m6 TS dt 0.001 time 0.006\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.155665048896e+01 [ 7.220713790192e-16 , 3.359669880940e-03 , 1.358300964909e-01 , 2.155622228500e+01 , 7.240128574600e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 4.585183226231e-01 [ 5.880519484736e-16 , 2.859233817821e-06 , 3.188346160061e-03 , 4.585072372621e-01 , 3.985438036566e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 2.552065671706e-05 [ 4.385622074568e-16 , 2.966696113928e-10 , 2.108854454707e-07 , 2.551978539312e-05 , 4.479889742470e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 3 SNES Function norm 1.175643363468e-12 [ 4.237646325504e-16 , 4.794054872792e-16 , 2.016215595417e-13 , 1.067937125116e-12 , 4.483257210856e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 6 accepted t=0.006 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 7.0000e-03 -3.3581e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 7.0000e-03 min -7.0568e-02 max 2.7516e-03\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 7.0000e-03 min -5.3667e-05 max 4.2000e-01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m7 TS dt 0.001 time 0.007\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.380173276760e+01 [ 1.047310567990e-15 , 2.360572717578e-03 , 1.019883527699e-01 , 1.380135573745e+01 , 1.006656230689e-12 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.890235574084e-01 [ 5.693664366037e-16 , 5.419594231469e-06 , 3.115000880107e-03 , 1.889978888651e-01 , 4.924128115590e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 2.613622196270e-06 [ 4.934164730605e-16 , 6.742760790804e-11 , 5.038635438647e-08 , 2.613136467079e-06 , 4.209500520392e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 7 accepted t=0.007 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 8.0000e-03 -3.3160e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 8.0000e-03 min -8.5951e-02 max 3.6075e-03\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 8.0000e-03 min -7.4834e-05 max 4.8000e-01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m8 TS dt 0.001 time 0.008\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 6.972267023011e+00 [ 1.076274768974e-15 , 1.531480894416e-03 , 6.774080724979e-02 , 6.971937770646e+00 , 9.499317686617e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 5.260505298321e-02 [ 7.343029062651e-16 , 3.850561170591e-06 , 1.803428033011e-03 , 5.257413082372e-02 , 4.846991651811e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.573734596851e-06 [ 7.050182874672e-16 , 6.526900923290e-11 , 1.542447739944e-08 , 1.573659004538e-06 , 4.824751499137e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 8 accepted t=0.008 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 9.0000e-03 -3.3058e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 9.0000e-03 min -1.0126e-01 max 4.4412e-03\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 9.0000e-03 min -9.6529e-05 max 5.4000e-01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m9 TS dt 0.001 time 0.009\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.183823384168e+00 [ 1.576115342664e-15 , 9.194153848742e-04 , 4.037156280637e-02 , 2.183449991374e+00 , 1.021922449752e-12 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 9.195228439748e-03 [ 5.489756042825e-16 , 1.477671811532e-05 , 8.748838480966e-04 , 9.153501295138e-03 , 4.194989219113e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 2.068740379991e-06 [ 4.493283425960e-16 , 3.335097410419e-09 , 1.036473616645e-07 , 2.066139603548e-06 , 3.910738882099e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 9 accepted t=0.009 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 1.0000e-02 -3.3191e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 1.0000e-02 min -1.1636e-01 max 5.2347e-03\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 1.0000e-02 min -1.1795e-04 max 6.0000e-01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m10 TS dt 0.001 time 0.01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 8.865915916976e-01 [ 3.602694946650e-15 , 6.661138111615e-04 , 2.031336381807e-02 , 8.863586035074e-01 , 9.774255175509e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 3.491010772231e-02 [ 5.378903243141e-16 , 1.067092966083e-05 , 8.444765027623e-04 , 3.489989064096e-02 , 4.014817225106e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.081940513546e-05 [ 1.008907799515e-15 , 6.714915083955e-09 , 2.511580738718e-07 , 1.081648750829e-05 , 4.159852722748e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 3 SNES Function norm 3.223093457409e-12 [ 8.200873852408e-16 , 9.880605736858e-16 , 3.383550630499e-13 , 3.167142814445e-12 , 4.930030736242e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 10 accepted t=0.01 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 1.1000e-02 -3.3468e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 1.1000e-02 min -1.3119e-01 max 5.9831e-03\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 1.1000e-02 min -1.3866e-04 max 6.6000e-01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m11 TS dt 0.001 time 0.011\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.233097960066e+00 [ 5.248056665995e-15 , 6.758675117842e-04 , 7.641263228099e-03 , 2.233084784228e+00 , 9.994246058756e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 3.959067973439e-02 [ 7.130020820856e-16 , 2.717911347143e-06 , 5.763931115136e-04 , 3.958648362036e-02 , 4.033416245984e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 3.070466533543e-06 [ 6.409636745459e-16 , 2.431237473029e-10 , 1.417234897070e-08 , 3.070433816096e-06 , 4.902567108528e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 3 SNES Function norm 6.583486201959e-13 [ 7.212812973656e-16 , 7.335706936538e-16 , 3.469247844120e-13 , 3.191028579157e-13 , 4.596067964814e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 11 accepted t=0.011 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 1.2000e-02 -3.3815e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 1.2000e-02 min -1.4576e-01 max 6.6890e-03\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 1.2000e-02 min -1.5853e-04 max 7.2000e-01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m12 TS dt 0.001 time 0.012\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.719972215266e+00 [ 4.517660008798e-15 , 7.110868827401e-04 , 8.139441101604e-03 , 2.719959943763e+00 , 1.076523280515e-12 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 3.995781494095e-02 [ 1.056567773022e-15 , 2.775662610902e-07 , 3.485192915522e-04 , 3.995629498692e-02 , 4.227115009626e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 7.645774263294e-07 [ 9.084546188035e-16 , 8.777557773624e-12 , 5.100000415962e-09 , 7.645604166912e-07 , 4.451553161965e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 12 accepted t=0.012 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 1.3000e-02 -3.4183e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 1.3000e-02 min -1.6010e-01 max 7.3580e-03\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 1.3000e-02 min -1.7754e-04 max 7.8000e-01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m13 TS dt 0.001 time 0.013\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.693379590033e+00 [ 4.539519259211e-15 , 6.949201763345e-04 , 1.295444368973e-02 , 2.693348346479e+00 , 9.847822652546e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 3.379090871096e-02 [ 6.107933261708e-16 , 1.609765178330e-06 , 1.762195216816e-04 , 3.379044917726e-02 , 4.409893938843e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.673303211685e-07 [ 5.604047789090e-16 , 5.697172730277e-12 , 3.261054641279e-09 , 1.672985411542e-07 , 4.609018457429e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 13 accepted t=0.013 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 1.4000e-02 -3.4545e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 1.4000e-02 min -1.7426e-01 max 7.9967e-03\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 1.4000e-02 min -1.9580e-04 max 8.4000e-01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m14 TS dt 0.001 time 0.014\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.427044783773e+00 [ 3.676091473338e-15 , 6.364214951034e-04 , 1.561920356699e-02 , 2.426994441256e+00 , 1.022499805678e-12 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 2.569456115863e-02 [ 1.028233212806e-15 , 2.001961524178e-06 , 7.907549389016e-05 , 2.569443940219e-02 , 4.691316710548e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 6.290991516948e-08 [ 9.064884038471e-16 , 8.104453367542e-12 , 3.491583182142e-09 , 6.281294617881e-08 , 4.113855678730e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 14 accepted t=0.014 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 1.5000e-02 -3.4886e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 1.5000e-02 min -1.8825e-01 max 8.6107e-03\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 1.5000e-02 min -2.1341e-04 max 9.0000e-01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m15 TS dt 0.001 time 0.015\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.085928151399e+00 [ 2.484175811214e-15 , 5.582450355937e-04 , 1.635446019702e-02 , 2.085863963156e+00 , 1.092924058206e-12 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.847276361174e-02 [ 1.200829758012e-15 , 1.894697026944e-06 , 3.719396541369e-05 , 1.847272607046e-02 , 4.572047373706e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 7.694962887768e-08 [ 6.206937151640e-16 , 1.069990444869e-11 , 2.440130071233e-09 , 7.691092922986e-08 , 3.998865341971e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 15 accepted t=0.015 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 1.6000e-02 -3.5204e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 1.6000e-02 min -2.0212e-01 max 9.2044e-03\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 1.6000e-02 min -2.3049e-04 max 9.6000e-01\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m16 TS dt 0.001 time 0.016\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.755343636628e+00 [ 2.896416526267e-15 , 4.778851524231e-04 , 1.586951715126e-02 , 1.755271834419e+00 , 9.656601487062e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.300777028088e-02 [ 8.835258967533e-16 , 1.594429535977e-06 , 2.336173827847e-05 , 1.300774920450e-02 , 4.350995386429e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 6.314103000062e-08 [ 1.041219311173e-15 , 9.688561966969e-12 , 1.505174804492e-09 , 6.312308630190e-08 , 4.492866765375e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 16 accepted t=0.016 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 1.7000e-02 -3.5500e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 1.7000e-02 min -2.1588e-01 max 9.7815e-03\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 1.7000e-02 min -2.4713e-04 max 1.0200e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m17 TS dt 0.001 time 0.017\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.470189725033e+00 [ 4.614394920970e-15 , 4.050684729694e-04 , 1.475844388500e-02 , 1.470115591322e+00 , 9.025565339091e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 9.182831458892e-03 [ 1.003281853908e-15 , 1.269238655240e-06 , 1.835928827609e-05 , 9.182813018241e-03 , 4.229447610831e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 4.361618734518e-08 [ 9.357643164000e-16 , 7.153640934759e-12 , 8.999962073979e-10 , 4.360690030302e-08 , 3.795050898534e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 17 accepted t=0.017 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 1.8000e-02 -3.5776e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 1.8000e-02 min -2.2955e-01 max 1.0344e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 1.8000e-02 min -2.6342e-04 max 1.0800e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m18 TS dt 0.001 time 0.018\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.237351409877e+00 [ 2.972042082150e-15 , 3.434082917444e-04 , 1.341753773550e-02 , 1.237278611824e+00 , 8.417931216214e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 6.578409041860e-03 [ 1.328791615991e-15 , 9.877477135608e-07 , 1.547954545091e-05 , 6.578390755348e-03 , 4.123374709156e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 2.809842385889e-08 [ 8.305510733756e-16 , 4.801006327291e-12 , 5.383897211923e-10 , 2.809326496956e-08 , 4.034046377421e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 18 accepted t=0.018 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 1.9000e-02 -3.6038e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 1.9000e-02 min -2.4315e-01 max 1.0895e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 1.9000e-02 min -2.7942e-04 max 1.1400e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m19 TS dt 0.001 time 0.019\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.050679539796e+00 [ 3.860074450233e-15 , 2.928036902833e-04 , 1.207066408627e-02 , 1.050610160184e+00 , 7.914624142131e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 4.793661096105e-03 [ 1.063457233961e-15 , 7.651009572056e-07 , 1.338881111099e-05 , 4.793642337374e-03 , 4.026826867429e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.770881565417e-08 [ 1.381005619374e-15 , 3.117072521301e-12 , 3.256502660701e-10 , 1.770582090356e-08 , 4.387555676089e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 19 accepted t=0.019 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 2.0000e-02 -3.6286e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 2.0000e-02 min -2.5669e-01 max 1.1435e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 2.0000e-02 min -2.9518e-04 max 1.2000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m20 TS dt 0.001 time 0.02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 8.998352221583e-01 [ 2.895150808310e-15 , 2.514433429772e-04 , 1.082213202797e-02 , 8.997701069002e-01 , 1.122223116571e-12 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 3.537086713837e-03 [ 1.338481424006e-15 , 5.946606199494e-07 , 1.169248026782e-05 , 3.537067337991e-03 , 4.038909233713e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.116504878979e-08 [ 2.119239318648e-15 , 2.024309304762e-12 , 1.996442427252e-10 , 1.116326351760e-08 , 4.398830122675e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 20 accepted t=0.02 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 2.1000e-02 -3.6523e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 2.1000e-02 min -2.7017e-01 max 1.1965e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 2.1000e-02 min -3.1075e-04 max 1.2600e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m21 TS dt 0.001 time 0.021\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 7.747914261225e-01 [ 5.088320656587e-15 , 2.171184296357e-04 , 9.705699073745e-03 , 7.747306023761e-01 , 9.529382342517e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 2.621382887955e-03 [ 9.145196757938e-16 , 4.643824065367e-07 , 1.020367586462e-05 , 2.621362987953e-03 , 4.185093595898e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 7.090384473705e-09 [ 1.359385394815e-15 , 1.333813421033e-12 , 1.237870882054e-10 , 7.089303688618e-09 , 4.162236953589e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 21 accepted t=0.021 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 2.2000e-02 -3.6751e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 2.2000e-02 min -2.8361e-01 max 1.2487e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 2.2000e-02 min -3.2616e-04 max 1.3200e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m22 TS dt 0.001 time 0.022\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 6.676337507111e-01 [ 4.221698086453e-15 , 1.878974511352e-04 , 8.719798530157e-03 , 6.675767782785e-01 , 8.943651082219e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.933538689855e-03 [ 1.632190308110e-15 , 3.633503384767e-07 , 8.849514629920e-06 , 1.933518404162e-03 , 3.670247553060e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 4.522470527293e-09 [ 1.610814720675e-15 , 8.912781868431e-13 , 7.708261120425e-11 , 4.521813462733e-09 , 3.938904956059e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 22 accepted t=0.022 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 2.3000e-02 -3.6970e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 2.3000e-02 min -2.9701e-01 max 1.3001e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 2.3000e-02 min -3.4147e-04 max 1.3800e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m23 TS dt 0.001 time 0.023\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 5.728814415008e-01 [ 4.343155820760e-15 , 1.623528798594e-04 , 7.849087770103e-03 , 5.728276455259e-01 , 9.299763972064e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.406845850778e-03 [ 1.331462547870e-15 , 2.834613075948e-07 , 7.611767926655e-06 , 1.406825230258e-03 , 4.080482449269e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 2.872611440992e-09 [ 1.100170934490e-15 , 5.999900763624e-13 , 4.799777114763e-11 , 2.872210327592e-09 , 4.230512945892e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 23 accepted t=0.023 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 2.4000e-02 -3.7181e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 2.4000e-02 min -3.1038e-01 max 1.3509e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 2.4000e-02 min -3.5668e-04 max 1.4400e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m24 TS dt 0.001 time 0.024\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 4.871267942500e-01 [ 5.093233157367e-15 , 1.395434688338e-04 , 7.075778694759e-03 , 4.870753818042e-01 , 8.395021494972e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.001157085414e-03 [ 1.499993380721e-15 , 2.192122043504e-07 , 6.488173326564e-06 , 1.001136037323e-03 , 3.506972615807e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.796642336949e-09 [ 1.541219735674e-15 , 4.014825908962e-13 , 2.971164347654e-11 , 1.796396551435e-09 , 4.170839546480e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 24 accepted t=0.024 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 2.5000e-02 -3.7385e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 2.5000e-02 min -3.2373e-01 max 1.4010e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 2.5000e-02 min -3.7184e-04 max 1.5000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m25 TS dt 0.001 time 0.025\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 4.084685306690e-01 [ 4.585335001923e-15 , 1.189035434615e-04 , 6.384478580222e-03 , 4.084186147105e-01 , 8.781502575127e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 6.907397804939e-04 [ 1.574364323185e-15 , 1.669784018321e-07 , 5.474807912258e-06 , 6.907180632887e-04 , 4.137689251783e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.091177220691e-09 [ 1.221220243963e-15 , 2.637892519094e-13 , 1.823034473413e-11 , 1.091024816956e-09 , 4.008545838985e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 25 accepted t=0.025 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 2.6000e-02 -3.7582e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 2.6000e-02 min -3.3706e-01 max 1.4506e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 2.6000e-02 min -3.8698e-04 max 1.5600e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m26 TS dt 0.001 time 0.026\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 3.359933394635e-01 [ 5.581521991238e-15 , 1.001250848150e-04 , 5.763465652411e-03 , 3.359438890685e-01 , 9.068529204582e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 4.575050800125e-04 [ 1.294904548278e-15 , 1.243244236969e-07 , 4.559932816051e-06 , 4.574823382311e-04 , 4.095970356352e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 6.314586395872e-10 [ 1.463973249600e-15 , 1.655618808937e-13 , 1.104626217001e-11 , 6.313618432900e-10 , 4.347711883128e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 26 accepted t=0.026 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 2.7000e-02 -3.7771e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 2.7000e-02 min -3.5038e-01 max 1.4997e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 2.7000e-02 min -4.0211e-04 max 1.6200e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m27 TS dt 0.001 time 0.027\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.694244154060e-01 [ 3.957381333487e-15 , 8.307040300164e-05 , 5.204344043685e-03 , 2.693741329810e-01 , 8.960427240668e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 2.875512492100e-04 [ 1.554180150218e-15 , 8.950164617908e-08 , 3.721675376426e-06 , 2.875271500990e-04 , 4.166642088240e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 3.373484744032e-10 [ 1.948643761306e-15 , 9.578837823973e-14 , 6.332401356080e-12 , 3.372887960117e-10 , 3.908720960050e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 27 accepted t=0.027 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 2.8000e-02 -3.7954e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 2.8000e-02 min -3.6369e-01 max 1.5484e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 2.8000e-02 min -4.1726e-04 max 1.6800e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m28 TS dt 0.001 time 0.028\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.090053250867e-01 [ 5.816728505364e-15 , 6.772876530796e-05 , 4.701197175687e-03 , 2.089524349523e-01 , 9.259954000821e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.694797409138e-04 [ 1.591771813846e-15 , 6.113824979935e-08 , 2.925337828484e-06 , 1.694544813244e-04 , 4.217436331488e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.557775758021e-10 [ 1.391777786560e-15 , 4.763750456679e-14 , 3.413148177709e-12 , 1.557396277133e-10 , 4.118625214762e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 28 accepted t=0.028 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 2.9000e-02 -3.8131e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 2.9000e-02 min -3.7701e-01 max 1.5968e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 2.9000e-02 min -4.3245e-04 max 1.7400e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m29 TS dt 0.001 time 0.029\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.557558035117e-01 [ 4.777830808631e-15 , 5.422505651717e-05 , 4.249776953647e-03 , 1.556978059674e-01 , 8.948196369105e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 9.333091455714e-05 [ 1.617699496535e-15 , 3.813379293132e-08 , 2.122979088556e-06 , 9.330675815650e-05 , 4.037523759210e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 5.249144346628e-11 [ 1.836455853612e-15 , 1.807200518142e-14 , 1.417504862792e-12 , 5.247043293995e-11 , 4.423282291075e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 29 accepted t=0.029 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 3.0000e-02 -3.8302e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 3.0000e-02 min -3.9032e-01 max 1.6448e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 3.0000e-02 min -4.4771e-04 max 1.8000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m30 TS dt 0.001 time 0.03\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.125372918149e-01 [ 4.384983369977e-15 , 4.289512822218e-05 , 3.846913725140e-03 , 1.124715140106e-01 , 9.112383709619e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 4.976609589511e-05 [ 1.530517341394e-15 , 2.017992773975e-08 , 1.305155065374e-06 , 4.974897449865e-05 , 4.066184874035e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.060625177037e-11 [ 1.288220313947e-15 , 3.946996326596e-15 , 9.664066253348e-13 , 1.055369723725e-11 , 4.220097595124e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 30 accepted t=0.03 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 3.1000e-02 -3.8467e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 3.1000e-02 min -4.0364e-01 max 1.6926e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 3.1000e-02 min -4.6305e-04 max 1.8600e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m31 TS dt 0.001 time 0.031\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 8.644406872403e-02 [ 4.785851715492e-15 , 3.442707178654e-05 , 3.490151451743e-03 , 8.637357625562e-02 , 8.881074415555e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 3.621410283343e-05 [ 2.287996438705e-15 , 1.056175000475e-08 , 8.302522397352e-07 , 3.620458277205e-05 , 4.038198039956e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.373491793227e-11 [ 1.794781265088e-15 , 4.684165193368e-15 , 9.528700427960e-13 , 1.369596041577e-11 , 4.008146886313e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 31 accepted t=0.031 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 3.2000e-02 -3.8626e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 3.2000e-02 min -4.1697e-01 max 1.7402e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 3.2000e-02 min -4.7850e-04 max 1.9200e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m32 TS dt 0.001 time 0.032\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 8.645585393355e-02 [ 7.805683363132e-15 , 2.986429532886e-05 , 3.177540562174e-03 , 8.639743644044e-02 , 9.762226732867e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 4.814476057584e-05 [ 1.875224239102e-15 , 1.304248809673e-08 , 1.324571212011e-06 , 4.812653438492e-05 , 3.970217922224e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 4.607678118401e-11 [ 1.606501157926e-15 , 1.262781883468e-14 , 1.586341557569e-12 , 4.604753712677e-11 , 4.212448914935e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 32 accepted t=0.032 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 3.3000e-02 -3.8780e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 3.3000e-02 min -4.3032e-01 max 1.7876e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 3.3000e-02 min -4.9406e-04 max 1.9800e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m33 TS dt 0.001 time 0.033\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.079878193366e-01 [ 7.313851388803e-15 , 2.983919546346e-05 , 2.907506978687e-03 , 1.079486666794e-01 , 9.106811979386e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 6.520982231195e-05 [ 2.097100079430e-15 , 1.758440870420e-08 , 1.805207891367e-06 , 6.518482830547e-05 , 3.631270597026e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.311775797958e-10 [ 1.780433325260e-15 , 2.504451200321e-14 , 2.227079744259e-12 , 1.311580952304e-10 , 3.885640758269e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 33 accepted t=0.033 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 3.4000e-02 -3.8928e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 3.4000e-02 min -4.4369e-01 max 1.8349e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 3.4000e-02 min -5.0976e-04 max 2.0400e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m34 TS dt 0.001 time 0.034\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.385702794028e-01 [ 7.354127826097e-15 , 3.352270069651e-05 , 2.678728153487e-03 , 1.385443814287e-01 , 9.711554163121e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 9.484748225995e-05 [ 3.222500563420e-15 , 2.047142251396e-08 , 1.845295714616e-06 , 9.482952786816e-05 , 4.161641665965e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 2.249641081077e-10 [ 1.716653752790e-15 , 3.730160839751e-14 , 2.682547517103e-12 , 2.249477405728e-10 , 4.080347379259e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 34 accepted t=0.034 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 3.5000e-02 -3.9071e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 3.5000e-02 min -4.5708e-01 max 1.8821e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 3.5000e-02 min -5.2561e-04 max 2.1000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m35 TS dt 0.001 time 0.035\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.715179502025e-01 [ 6.788980108988e-15 , 3.931659694142e-05 , 2.489970920584e-03 , 1.714998709640e-01 , 9.553629364215e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.388974204656e-04 [ 2.092165808029e-15 , 2.257233481745e-08 , 1.723458756114e-06 , 1.388867257602e-04 , 4.237209291470e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 3.177920371919e-10 [ 2.144295216551e-15 , 4.582838002745e-14 , 2.474890708851e-12 , 3.177821076405e-10 , 4.286925351797e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 35 accepted t=0.035 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 3.6000e-02 -3.9210e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 3.6000e-02 min -4.7049e-01 max 1.9292e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 3.6000e-02 min -5.4163e-04 max 2.1600e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m36 TS dt 0.001 time 0.036\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.043612981840e-01 [ 7.192378759308e-15 , 4.603355397840e-05 , 2.339878324933e-03 , 2.043478970917e-01 , 9.322167348910e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.937982399509e-04 [ 2.265550384616e-15 , 2.398412664343e-08 , 1.571202415785e-06 , 1.937918691684e-04 , 3.930791394765e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 4.186964966139e-10 [ 2.506359355985e-15 , 5.113300416556e-14 , 1.961704682579e-12 , 4.186916870696e-10 , 4.201778885704e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 36 accepted t=0.036 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 3.7000e-02 -3.9343e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 3.7000e-02 min -4.8393e-01 max 1.9762e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 3.7000e-02 min -5.5782e-04 max 2.2200e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m37 TS dt 0.001 time 0.037\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.362122746189e-01 [ 6.914322451452e-15 , 5.304348150505e-05 , 2.226731685683e-03 , 2.362017729252e-01 , 1.052663827577e-12 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 2.566438310827e-04 [ 1.458532776711e-15 , 2.468892265037e-08 , 1.427113111280e-06 , 2.566398620079e-04 , 4.202157254819e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 5.347614150321e-10 [ 1.638406573822e-15 , 5.471482544648e-14 , 2.318760736579e-12 , 5.347562127531e-10 , 4.292799935083e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 37 accepted t=0.037 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 3.8000e-02 -3.9472e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 3.8000e-02 min -4.9739e-01 max 2.0232e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 3.8000e-02 min -5.7421e-04 max 2.2800e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m38 TS dt 0.001 time 0.038\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.667646265142e-01 [ 7.677008276382e-15 , 6.004412089301e-05 , 2.148250589021e-03 , 2.667559697052e-01 , 1.023795404520e-12 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 3.254908071946e-04 [ 1.817928670006e-15 , 2.474299307826e-08 , 1.301047402574e-06 , 3.254882059793e-04 , 3.771219291385e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 6.716608796808e-10 [ 1.980504255648e-15 , 5.659053147091e-14 , 2.974539072041e-12 , 6.716541599931e-10 , 4.190089291478e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 38 accepted t=0.038 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 3.9000e-02 -3.9596e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 3.9000e-02 min -5.1089e-01 max 2.0703e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 3.9000e-02 min -5.9080e-04 max 2.3400e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m39 TS dt 0.001 time 0.039\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.959452733768e-01 [ 1.058418475115e-14 , 6.689501217548e-05 , 2.101506051110e-03 , 2.959378043296e-01 , 8.186157661263e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 3.989823898617e-04 [ 2.283269083564e-15 , 2.424567755230e-08 , 1.194441592973e-06 , 3.989806012091e-04 , 4.111533320292e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 8.335905081159e-10 [ 2.842660327029e-15 , 5.777762585477e-14 , 4.285403929404e-12 , 8.335793894526e-10 , 4.106915586134e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 39 accepted t=0.039 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 4.0000e-02 -3.9716e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 4.0000e-02 min -5.2443e-01 max 2.1173e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 4.0000e-02 min -6.0761e-04 max 2.4000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m40 TS dt 0.001 time 0.04\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 3.237816842437e-01 [ 1.078865740786e-14 , 7.353445525776e-05 , 2.082992840684e-03 , 3.237749755388e-01 , 9.530270302006e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 4.761307076699e-04 [ 2.307061877582e-15 , 2.330741261985e-08 , 1.106335301012e-06 , 4.761294217596e-04 , 3.877003465076e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.024500374719e-09 [ 2.087589180848e-15 , 5.750032846115e-14 , 5.652822043353e-12 , 1.024484683575e-09 , 4.395581029939e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 40 accepted t=0.04 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 4.1000e-02 -3.9832e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 4.1000e-02 min -5.3800e-01 max 2.1644e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 4.1000e-02 min -6.2465e-04 max 2.4600e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m41 TS dt 0.001 time 0.041\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 3.503463181211e-01 [ 8.324405513090e-15 , 7.994019448147e-05 , 2.088845021426e-03 , 3.503400818591e-01 , 9.658747181903e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 5.562045088118e-04 [ 2.436114837173e-15 , 2.203438135208e-08 , 1.035204296359e-06 , 5.562035450166e-04 , 3.756834178936e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.248161581618e-09 [ 3.033589638633e-15 , 5.615476251439e-14 , 7.528247738641e-12 , 1.248138804422e-09 , 4.254937242418e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 41 accepted t=0.041 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 4.2000e-02 -3.9943e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 4.2000e-02 min -5.5162e-01 max 2.2116e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 4.2000e-02 min -6.4193e-04 max 2.5200e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m42 TS dt 0.001 time 0.042\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 3.757314683594e-01 [ 1.070680446925e-14 , 8.611036725241e-05 , 2.115122548535e-03 , 3.757255050660e-01 , 9.515403186491e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 6.386650795538e-04 [ 2.523139663035e-15 , 2.052265510519e-08 , 9.794948653060e-07 , 6.386643281178e-04 , 4.086478770340e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.508643657603e-09 [ 2.305443132064e-15 , 5.366810914019e-14 , 9.451413967073e-12 , 1.508613985608e-09 , 4.426521756479e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 42 accepted t=0.042 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 4.3000e-02 -4.0050e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 4.3000e-02 min -5.6527e-01 max 2.2589e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 4.3000e-02 min -6.5946e-04 max 2.5800e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m43 TS dt 0.001 time 0.043\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 4.000372178743e-01 [ 1.342215216907e-14 , 9.205388230337e-05 , 2.158081722961e-03 , 4.000313861361e-01 , 9.406059275006e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 7.231252522067e-04 [ 2.312574834051e-15 , 1.885671345758e-08 , 9.377253659128e-07 , 7.231246439547e-04 , 3.986357205131e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.810510552266e-09 [ 3.008338946414e-15 , 5.137449733943e-14 , 1.202991961072e-11 , 1.810470549578e-09 , 3.568766987049e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 43 accepted t=0.043 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 4.4000e-02 -4.0152e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 4.4000e-02 min -5.7897e-01 max 2.3063e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 4.4000e-02 min -6.7725e-04 max 2.6400e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m44 TS dt 0.001 time 0.044\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 4.233654764507e-01 [ 1.014451742700e-14 , 9.778535842902e-05 , 2.214369574437e-03 , 4.233596741020e-01 , 9.541388830455e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 8.093208808216e-04 [ 2.464009426233e-15 , 1.710985055312e-08 , 9.084677660273e-07 , 8.093203707602e-04 , 4.220664616893e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 2.158619296979e-09 [ 2.487138248324e-15 , 4.813994214592e-14 , 1.459542054562e-11 , 2.158569900012e-09 , 4.768924877699e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 44 accepted t=0.044 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 4.5000e-02 -4.0251e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 4.5000e-02 min -5.9271e-01 max 2.3538e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 4.5000e-02 min -6.9531e-04 max 2.7000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m45 TS dt 0.001 time 0.045\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 4.458170160870e-01 [ 1.028273315933e-14 , 1.033223727216e-04 , 2.281124674699e-03 , 4.458111681277e-01 , 9.326504346895e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 8.970899600021e-04 [ 2.667671611840e-15 , 1.534533076034e-08 , 8.903055314539e-07 , 8.970895180846e-04 , 5.012183792364e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 2.559102308814e-09 [ 2.484779074056e-15 , 4.592943116556e-14 , 1.750852768631e-11 , 2.559042375550e-09 , 4.432348042562e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 45 accepted t=0.045 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 4.6000e-02 -4.0346e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 4.6000e-02 min -6.0650e-01 max 2.4014e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 4.6000e-02 min -7.1365e-04 max 2.7600e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m46 TS dt 0.001 time 0.046\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 4.674900649490e-01 [ 1.037665679186e-14 , 1.086839325617e-04 , 2.355998636202e-03 , 4.674841155422e-01 , 9.134126891477e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 9.863569654485e-04 [ 3.726516095398e-15 , 1.361778698984e-08 , 8.818224088474e-07 , 9.863565711712e-04 , 4.094837975325e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 3.018632975308e-09 [ 2.927218397408e-15 , 4.228784681924e-14 , 2.112694108912e-11 , 3.018559014427e-09 , 4.081690093416e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 46 accepted t=0.046 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 4.7000e-02 -4.0437e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 4.7000e-02 min -6.2034e-01 max 2.4492e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 4.7000e-02 min -7.3228e-04 max 2.8200e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m47 TS dt 0.001 time 0.047\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 4.884797533500e-01 [ 7.624441873215e-15 , 1.138896243518e-04 , 2.437125229053e-03 , 4.884736603775e-01 , 9.751397372668e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.077121086968e-03 [ 2.531818772449e-15 , 1.197463614145e-08 , 8.816224953716e-07 , 1.077120726097e-03 , 4.389481360703e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 3.545011319112e-09 [ 2.171069565125e-15 , 3.804993353118e-14 , 2.486823188383e-11 , 3.544924064243e-09 , 4.482953605091e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 47 accepted t=0.047 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 4.8000e-02 -4.0524e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 4.8000e-02 min -6.3423e-01 max 2.4972e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 4.8000e-02 min -7.5122e-04 max 2.8800e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m48 TS dt 0.001 time 0.048\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 5.088780496840e-01 [ 1.214888270383e-14 , 1.189591516928e-04 , 2.523062703295e-03 , 5.088717809561e-01 , 1.047900359238e-12 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.169447554697e-03 [ 2.997732206108e-15 , 1.045746032088e-08 , 8.883700895477e-07 , 1.169447217226e-03 , 4.071054777879e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 4.147385689373e-09 [ 2.279324246838e-15 , 3.495242061193e-14 , 2.920471854996e-11 , 4.147282840939e-09 , 4.205477157610e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 48 accepted t=0.048 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 4.9000e-02 -4.0607e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 4.9000e-02 min -6.4818e-01 max 2.5454e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 4.9000e-02 min -7.7047e-04 max 2.9400e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m49 TS dt 0.001 time 0.049\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 5.287739940546e-01 [ 9.806970331220e-15 , 1.239121064695e-04 , 2.612727725418e-03 , 5.287675246156e-01 , 9.025073139716e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.263461554155e-03 [ 2.794606506920e-15 , 9.103214873347e-09 , 9.008421349762e-07 , 1.263461232974e-03 , 4.676254862063e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 4.836708133575e-09 [ 3.248555596244e-15 , 3.183101210985e-14 , 3.438655499007e-11 , 4.836585874864e-09 , 4.563599448279e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 49 accepted t=0.049 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 5.0000e-02 -4.0686e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 5.0000e-02 min -6.6218e-01 max 2.5937e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 5.0000e-02 min -7.9004e-04 max 3.0000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m50 TS dt 0.001 time 0.05\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 5.482541248786e-01 [ 1.030578883036e-14 , 1.287678849500e-04 , 2.705331821426e-03 , 5.482474350555e-01 , 1.044094100153e-12 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.359344404722e-03 [ 2.246516632335e-15 , 7.945446385948e-09 , 9.179681909405e-07 , 1.359344094746e-03 , 4.937779456583e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 5.626016491488e-09 [ 3.372252401493e-15 , 2.962170599800e-14 , 3.983523967747e-11 , 5.625875441835e-09 , 4.777502063439e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 50 accepted t=0.05 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 5.1000e-02 -4.0761e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 5.1000e-02 min -6.7623e-01 max 2.6422e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 5.1000e-02 min -8.0993e-04 max 3.0600e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m51 TS dt 0.001 time 0.051\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 5.674030414113e-01 [ 1.060499343597e-14 , 1.335456980991e-04 , 2.800325560847e-03 , 5.673961153772e-01 , 1.148942350200e-12 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.457331800125e-03 [ 2.804482265424e-15 , 7.015292352728e-09 , 9.388619843773e-07 , 1.457331497685e-03 , 4.176310334890e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 6.530111544463e-09 [ 4.172951620381e-15 , 2.712577221339e-14 , 4.648783064373e-11 , 6.529946055063e-09 , 4.265466918980e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 51 accepted t=0.051 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 5.2000e-02 -4.0833e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 5.2000e-02 min -6.9035e-01 max 2.6910e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 5.2000e-02 min -8.3017e-04 max 3.1200e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m52 TS dt 0.001 time 0.052\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 5.863040728310e-01 [ 8.847065253521e-15 , 1.382646470089e-04 , 2.897352214882e-03 , 5.862968975283e-01 , 9.260653994436e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.557714016483e-03 [ 3.299892380143e-15 , 6.342545218634e-09 , 9.628412154331e-07 , 1.557713718898e-03 , 4.342969414945e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 7.567432421751e-09 [ 2.737482117626e-15 , 2.616031925806e-14 , 5.373728543378e-11 , 7.567241606182e-09 , 4.846634263741e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 52 accepted t=0.052 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 5.3000e-02 -4.0901e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 5.3000e-02 min -7.0452e-01 max 2.7400e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 5.3000e-02 min -8.5076e-04 max 3.1800e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m53 TS dt 0.001 time 0.053\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 6.050400423330e-01 [ 1.034531291366e-14 , 1.429438466996e-04 , 2.996210774569e-03 , 6.050326066539e-01 , 1.050061571619e-12 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.660838083549e-03 [ 2.789237481851e-15 , 5.956562154448e-09 , 9.894374842682e-07 , 1.660837788812e-03 , 4.075460883025e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 8.759891538848e-09 [ 3.080250809799e-15 , 2.613257394974e-14 , 6.226329648196e-11 , 8.759670247772e-09 , 4.515574094856e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 53 accepted t=0.053 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 5.4000e-02 -4.0966e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 5.4000e-02 min -7.1876e-01 max 2.7893e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 5.4000e-02 min -8.7170e-04 max 3.2400e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m54 TS dt 0.001 time 0.054\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 6.236941273314e-01 [ 1.005538938232e-14 , 1.476025899665e-04 , 3.096827334348e-03 , 6.236864214825e-01 , 9.616086533170e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.767112014859e-03 [ 3.125943694908e-15 , 5.887267768539e-09 , 1.018406758456e-06 , 1.767111721390e-03 , 4.021241222080e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.013370871519e-08 [ 2.791457244473e-15 , 2.729400520671e-14 , 7.208812858182e-11 , 1.013345229593e-08 , 4.373104977407e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 54 accepted t=0.054 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 5.5000e-02 -4.1027e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 5.5000e-02 min -7.3306e-01 max 2.8387e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 5.5000e-02 min -8.9302e-04 max 3.3000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m55 TS dt 0.001 time 0.055\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 6.423508273275e-01 [ 1.420371289219e-14 , 1.522605482553e-04 , 3.199233662484e-03 , 6.423428423272e-01 , 1.066147127291e-12 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.877011304035e-03 [ 2.448567722502e-15 , 6.166215906803e-09 , 1.049736409181e-06 , 1.877011010487e-03 , 4.780988159095e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.172024932692e-08 [ 2.815736193175e-15 , 3.134720572614e-14 , 8.339502114928e-11 , 1.171995261925e-08 , 3.965312526254e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 55 accepted t=0.055 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 5.6000e-02 -4.1084e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 5.6000e-02 min -7.4742e-01 max 2.8885e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 5.6000e-02 min -9.1471e-04 max 3.3600e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m56 TS dt 0.001 time 0.056\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 6.610970607869e-01 [ 1.207250966651e-14 , 1.569380109731e-04 , 3.303551809499e-03 , 6.610887880588e-01 , 9.892686194767e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.991088016098e-03 [ 2.781077634947e-15 , 6.827611273124e-09 , 1.083662679401e-06 , 1.991087721191e-03 , 4.247371378472e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.355856024499e-08 [ 2.135868870960e-15 , 3.807604254254e-14 , 9.631961875717e-11 , 1.355821810728e-08 , 4.495385670675e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 56 accepted t=0.056 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 5.7000e-02 -4.1137e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 5.7000e-02 min -7.6186e-01 max 2.9385e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 5.7000e-02 min -9.3679e-04 max 3.4200e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m57 TS dt 0.001 time 0.057\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 6.800234227711e-01 [ 1.013759520461e-14 , 1.616561681977e-04 , 3.409983784863e-03 , 6.800148538048e-01 , 9.703139453216e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 2.109982975046e-03 [ 3.414423620565e-15 , 7.909575872969e-09 , 1.120692533811e-06 , 2.109982677410e-03 , 4.497092267598e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.569648653832e-08 [ 3.210428442042e-15 , 4.925492010617e-14 , 1.112678778214e-10 , 1.569609215459e-08 , 4.231743656678e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 57 accepted t=0.057 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 5.8000e-02 -4.1187e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 5.8000e-02 min -7.7636e-01 max 2.9888e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 5.8000e-02 min -9.5927e-04 max 3.4800e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m58 TS dt 0.001 time 0.058\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 6.992256472421e-01 [ 1.127454489999e-14 , 1.664374454326e-04 , 3.518805580298e-03 , 6.992167733021e-01 , 1.078081523289e-12 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 2.234441749377e-03 [ 2.923286223759e-15 , 9.455515455512e-09 , 1.161637450052e-06 , 2.234441447402e-03 , 4.810646021634e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.819239940767e-08 [ 3.665708778227e-15 , 6.483340483885e-14 , 1.285246802229e-10 , 1.819194539783e-08 , 5.027418231486e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 58 accepted t=0.058 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 5.9000e-02 -4.1233e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 5.9000e-02 min -7.9093e-01 max 3.0394e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 5.9000e-02 min -9.8216e-04 max 3.5400e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m59 TS dt 0.001 time 0.059\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 7.188063331013e-01 [ 1.055088948963e-14 , 1.713059032501e-04 , 3.630365064062e-03 , 7.187971449653e-01 , 1.000981300378e-12 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 2.365335423950e-03 [ 2.739231303943e-15 , 1.151576395795e-08 , 1.207659670405e-06 , 2.365335115627e-03 , 4.024615820716e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 2.112022088336e-08 [ 3.759417458339e-15 , 8.560041341106e-14 , 1.490293746210e-10 , 2.111969507712e-08 , 4.995978220565e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 59 accepted t=0.059 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 6.0000e-02 -4.1275e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 6.0000e-02 min -8.0558e-01 max 3.0903e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 6.0000e-02 min -1.0055e-03 max 3.6000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m60 TS dt 0.001 time 0.06\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 7.388770128797e-01 [ 1.350743556500e-14 , 1.762877193883e-04 , 3.745083476467e-03 , 7.388675005942e-01 , 9.639418211453e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 2.503687532821e-03 [ 4.000330197424e-15 , 1.414977935882e-08 , 1.260330633485e-06 , 2.503687215562e-03 , 4.065885355998e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 2.457278015481e-08 [ 3.194796797347e-15 , 1.199104760347e-13 , 1.730568382869e-10 , 2.457217075571e-08 , 4.526171350852e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 60 accepted t=0.06 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 6.1000e-02 -4.1313e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 6.1000e-02 min -8.2030e-01 max 3.1415e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 6.1000e-02 min -1.0292e-03 max 3.6600e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m61 TS dt 0.001 time 0.061\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 7.595606696427e-01 [ 1.331445941448e-14 , 1.814117777304e-04 , 3.863460528194e-03 , 7.595508222829e-01 , 8.932529195263e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 2.650709061065e-03 [ 3.025587735804e-15 , 1.742869393875e-08 , 1.321704561647e-06 , 2.650708731491e-03 , 4.253661307336e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 2.866724319308e-08 [ 2.311771707096e-15 , 1.664870860879e-13 , 2.009405472071e-10 , 2.866653894325e-08 , 4.180463048828e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 61 accepted t=0.061 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 6.2000e-02 -4.1348e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 6.2000e-02 min -8.3509e-01 max 3.1930e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 6.2000e-02 min -1.0534e-03 max 3.7200e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m62 TS dt 0.001 time 0.062\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 7.809948445520e-01 [ 9.854122848679e-15 , 1.867103970877e-04 , 3.986083350078e-03 , 7.809846499744e-01 , 8.847690264078e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 2.807844203831e-03 [ 3.966046738589e-15 , 2.143881435648e-08 , 1.394409714090e-06 , 2.807843857509e-03 , 5.223909311392e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 3.355498365373e-08 [ 3.421390268067e-15 , 2.274146132437e-13 , 2.350077619609e-10 , 3.355416068259e-08 , 4.349872986850e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 62 accepted t=0.062 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 6.3000e-02 -4.1379e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 6.3000e-02 min -8.4997e-01 max 3.2448e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 6.3000e-02 min -1.0780e-03 max 3.7800e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m63 TS dt 0.001 time 0.063\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 8.033355289443e-01 [ 1.395243760804e-14 , 1.922202449872e-04 , 4.113639816344e-03 , 8.033249735213e-01 , 1.085957654939e-12 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 2.976830683159e-03 [ 2.895538855422e-15 , 2.628620796802e-08 , 1.481762700571e-06 , 2.976830314258e-03 , 4.379880571597e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 3.943264719119e-08 [ 3.545352707795e-15 , 3.138095546767e-13 , 2.750994307650e-10 , 3.943168756895e-08 , 4.172196568224e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 63 accepted t=0.063 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 6.4000e-02 -4.1405e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 6.4000e-02 min -8.6493e-01 max 3.2970e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 6.4000e-02 min -1.1031e-03 max 3.8400e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m64 TS dt 0.001 time 0.064\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 8.267621083421e-01 [ 1.371247751529e-14 , 1.979834990090e-04 , 4.246937141921e-03 , 8.267511766654e-01 , 1.075026212459e-12 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 3.159780077324e-03 [ 4.254099324539e-15 , 3.210282814486e-08 , 1.587912890071e-06 , 3.159779678166e-03 , 4.563587560971e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 4.655951903769e-08 [ 3.134375895042e-15 , 4.297726036826e-13 , 3.240317366412e-10 , 4.655839146761e-08 , 4.679806461674e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 64 accepted t=0.064 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 6.5000e-02 -4.1428e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 6.5000e-02 min -8.7997e-01 max 3.3496e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 6.5000e-02 min -1.1287e-03 max 3.9000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m65 TS dt 0.001 time 0.065\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 8.514837317556e-01 [ 1.445777499346e-14 , 2.040493429432e-04 , 4.386927144258e-03 , 8.514724062931e-01 , 8.698329156325e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 3.359286106299e-03 [ 5.417600923958e-15 , 3.905493974605e-08 , 1.718038115597e-06 , 3.359285666744e-03 , 4.124068533664e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 5.528188936188e-08 [ 3.753136543892e-15 , 5.873899914818e-13 , 3.832421529995e-10 , 5.528056092657e-08 , 4.121682492982e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 65 accepted t=0.065 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 6.6000e-02 -4.1447e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 6.6000e-02 min -8.9510e-01 max 3.4025e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 6.6000e-02 min -1.1548e-03 max 3.9600e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m66 TS dt 0.001 time 0.066\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 8.777476356226e-01 [ 1.684964447039e-14 , 2.104759215989e-04 , 4.534740192150e-03 , 8.777358963107e-01 , 1.028410032964e-12 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 3.578572625623e-03 [ 3.835059001244e-15 , 4.735489979004e-08 , 1.878626007974e-06 , 3.578572132203e-03 , 4.401335436801e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 6.607026613063e-08 [ 3.940947379400e-15 , 8.020451359993e-13 , 4.566930140714e-10 , 6.606868772154e-08 , 4.163068749100e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 66 accepted t=0.066 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 6.7000e-02 -4.1461e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 6.7000e-02 min -9.1032e-01 max 3.4558e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 6.7000e-02 min -1.1814e-03 max 4.0200e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m67 TS dt 0.001 time 0.067\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 9.058501842670e-01 [ 1.487538143623e-14 , 2.173329323935e-04 , 4.691730833875e-03 , 9.058380080151e-01 , 8.628637314508e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 3.821699037217e-03 [ 4.439233421830e-15 , 5.727790631606e-08 , 2.077895397918e-06 , 3.821698471902e-03 , 4.566495795148e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 7.957562673280e-08 [ 3.411092667431e-15 , 1.095750494316e-12 , 5.478086062521e-10 , 7.957374111021e-08 , 4.153418548994e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 67 accepted t=0.067 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 6.8000e-02 -4.1470e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 6.8000e-02 min -9.2563e-01 max 3.5094e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 6.8000e-02 min -1.2085e-03 max 4.0800e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m68 TS dt 0.001 time 0.068\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 9.361517424525e-01 [ 1.125321060470e-14 , 2.247051145701e-04 , 4.859539522824e-03 , 9.361391025271e-01 , 1.019042810695e-12 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 4.093850356352e-03 [ 5.047775710987e-15 , 6.918624769889e-08 , 2.326442963092e-06 , 4.093849694735e-03 , 4.481057787518e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 9.671678836460e-08 [ 4.872679614723e-15 , 1.500690861129e-12 , 6.626052168613e-10 , 9.671451857628e-08 , 4.411110523650e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 68 accepted t=0.068 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 6.9000e-02 -4.1475e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 6.9000e-02 min -9.4104e-01 max 3.5635e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 6.9000e-02 min -1.2361e-03 max 4.1400e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m69 TS dt 0.001 time 0.069\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 9.690970440426e-01 [ 1.324475226540e-14 , 2.326970246150e-04 , 5.040176989253e-03 , 9.690839092876e-01 , 1.005274665349e-12 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 4.401754762826e-03 [ 4.063514435921e-15 , 8.356541911527e-08 , 2.638264971441e-06 , 4.401753971389e-03 , 4.439931783850e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.188205347218e-07 [ 3.709358166959e-15 , 2.066690004577e-12 , 8.099220729285e-10 , 1.188177743159e-07 , 4.108627552036e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 69 accepted t=0.069 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 7.0000e-02 -4.1475e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 7.0000e-02 min -9.5654e-01 max 3.6180e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 7.0000e-02 min -1.2644e-03 max 4.2000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m70 TS dt 0.001 time 0.07\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.005243588836e+00 [ 1.931093280008e-14 , 2.414396891411e-04 , 5.236141200789e-03 , 1.005229922668e+00 , 9.875049065928e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 4.754297687768e-03 [ 3.631260744029e-15 , 1.010789122121e-07 , 3.032372200206e-06 , 4.754296719644e-03 , 4.277031722596e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.478525201343e-07 [ 4.944537359965e-15 , 2.870863352849e-12 , 1.002082788913e-09 , 1.478491242170e-07 , 4.183453559432e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 70 accepted t=0.07 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 7.1000e-02 -4.1470e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 7.1000e-02 min -9.7215e-01 max 3.6730e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 7.1000e-02 min -1.2932e-03 max 4.2600e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m71 TS dt 0.001 time 0.071\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.045302007760e+00 [ 2.114933623621e-14 , 2.511000544432e-04 , 5.450582203338e-03 , 1.045287766851e+00 , 1.014900540862e-12 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 5.163446869078e-03 [ 6.368629380228e-15 , 1.226537414164e-07 , 3.535396026958e-06 , 5.163445657284e-03 , 4.239201756850e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.868145929136e-07 [ 6.754375028069e-15 , 4.031403031110e-12 , 1.257711872705e-09 , 1.868103591074e-07 , 5.030184814871e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 71 accepted t=0.071 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 7.2000e-02 -4.1459e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 7.2000e-02 min -9.8787e-01 max 3.7284e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 7.2000e-02 min -1.3226e-03 max 4.3200e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m72 TS dt 0.001 time 0.072\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.090194679905e+00 [ 2.328130712502e-14 , 2.618946981329e-04 , 5.687539027716e-03 , 1.090179812418e+00 , 9.459496255054e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 5.645683996482e-03 [ 6.661208660391e-15 , 1.496181376350e-07 , 4.185871908178e-06 , 5.645682442737e-03 , 4.658309193788e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 2.404481099525e-07 [ 6.017947375646e-15 , 5.753852006571e-12 , 1.606789890825e-09 , 2.404427411518e-07 , 5.290819095740e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 72 accepted t=0.072 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 7.3000e-02 -4.1442e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 7.3000e-02 min -1.0037e+00 max 3.7843e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 7.3000e-02 min -1.3526e-03 max 4.3800e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m73 TS dt 0.001 time 0.073\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.141142900303e+00 [ 2.527110561422e-14 , 2.741102030351e-04 , 5.952287781440e-03 , 1.141127343484e+00 , 1.099302541735e-12 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 6.224289201992e-03 [ 4.091176544861e-15 , 1.839304798612e-07 , 5.041496499053e-06 , 6.224287157540e-03 , 4.710520548882e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 3.165458363448e-07 [ 3.805646034684e-15 , 8.381159459808e-12 , 2.097188529412e-09 , 3.165388889804e-07 , 5.424597787028e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 73 accepted t=0.073 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 7.4000e-02 -4.1418e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 7.4000e-02 min -1.0196e+00 max 3.8407e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 7.4000e-02 min -1.3833e-03 max 4.4400e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m74 TS dt 0.001 time 0.074\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.199800007416e+00 [ 2.174464931121e-14 , 2.881342497550e-04 , 6.251866255425e-03 , 1.199783684229e+00 , 1.163610897309e-12 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 6.933116055100e-03 [ 4.058495168513e-15 , 2.285752969877e-07 , 6.191872345792e-06 , 6.933113286393e-03 , 4.260212349704e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 4.285305362957e-07 [ 4.821846426502e-15 , 1.254787347949e-11 , 2.809530793463e-09 , 4.285213260935e-07 , 4.826114091240e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 74 accepted t=0.074 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 7.5000e-02 -4.1386e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 7.5000e-02 min -1.0357e+00 max 3.8977e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 7.5000e-02 min -1.4147e-03 max 4.5000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m75 TS dt 0.001 time 0.075\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.268460945748e+00 [ 2.055182699711e-14 , 3.045045259278e-04 , 6.595887766957e-03 , 1.268443760057e+00 , 9.995780988019e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 7.823085886945e-03 [ 4.015163456230e-15 , 2.882790728396e-07 , 7.781885315652e-06 , 7.823082011181e-03 , 4.611926912310e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 6.008382767039e-07 [ 4.706599728533e-15 , 1.946794492302e-11 , 3.890855756236e-09 , 6.008256782252e-07 , 4.599470649836e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 75 accepted t=0.075 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 7.6000e-02 -4.1346e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 7.6000e-02 min -1.0519e+00 max 3.9553e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 7.6000e-02 min -1.4469e-03 max 4.5600e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m76 TS dt 0.001 time 0.076\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.350403796051e+00 [ 1.744351997389e-14 , 3.239883863933e-04 , 6.997846695395e-03 , 1.350385625502e+00 , 9.397354018243e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 8.973897259123e-03 [ 4.753060023973e-15 , 3.708727909571e-07 , 1.005685109361e-05 , 8.973891616210e-03 , 4.058336194119e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 8.810404151978e-07 [ 4.191399203065e-15 , 3.165069409166e-11 , 5.619116631391e-09 , 8.810224955915e-07 , 4.637871263925e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 76 accepted t=0.076 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 7.7000e-02 -4.1296e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 7.7000e-02 min -1.0683e+00 max 4.0136e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 7.7000e-02 min -1.4798e-03 max 4.6200e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m77 TS dt 0.001 time 0.077\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.450469296942e+00 [ 1.461507847878e-14 , 3.477179592525e-04 , 7.477296062566e-03 , 1.450449982077e+00 , 8.853933945610e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.051634212895e-02 [ 3.116455827864e-15 , 4.900490522898e-07 , 1.345509357615e-05 , 1.051633351000e-02 , 4.809843944471e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.369664828105e-06 [ 5.950920343331e-15 , 5.475685190696e-11 , 8.569165257205e-09 , 1.369638020704e-06 , 4.545738126861e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 77 accepted t=0.077 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 7.8000e-02 -4.1233e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 7.8000e-02 min -1.0848e+00 max 4.0726e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 7.8000e-02 min -1.5136e-03 max 4.6800e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m78 TS dt 0.001 time 0.078\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.576092239088e+00 [ 2.394195164276e-14 , 3.774305308538e-04 , 8.063651947516e-03 , 1.576071566007e+00 , 9.883395250905e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.267776328231e-02 [ 5.257362186148e-15 , 6.713648992711e-07 , 1.881208956231e-05 , 1.267774930722e-02 , 5.356888935939e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 2.302113593578e-06 [ 4.264989850054e-15 , 1.030133028185e-10 , 1.405347423500e-08 , 2.302070695480e-06 , 4.677804630853e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 3 SNES Function norm 2.345964485615e-12 [ 5.234113974791e-15 , 4.810273340533e-15 , 2.128528374365e-12 , 8.737684108820e-13 , 4.575964999412e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 78 accepted t=0.078 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 7.9000e-02 -4.1156e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 7.9000e-02 min -1.1015e+00 max 4.1325e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 7.9000e-02 min -1.5483e-03 max 4.7400e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m79 TS dt 0.001 time 0.079\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.739252982687e+00 [ 2.982008513525e-14 , 4.159226822669e-04 , 8.803238011467e-03 , 1.739230653995e+00 , 9.490153144118e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 1.588255861094e-02 [ 4.890252719231e-15 , 9.665361719895e-07 , 2.785235332357e-05 , 1.588253415995e-02 , 4.588837630563e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 4.307253435333e-06 [ 5.235767279096e-15 , 2.175261383474e-10 , 2.545465195977e-08 , 4.307178214279e-06 , 4.146176701919e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 3 SNES Function norm 2.333430198130e-12 [ 5.261385472062e-15 , 5.878380441144e-15 , 1.994503475804e-12 , 1.114719967273e-12 , 4.734865695879e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 79 accepted t=0.079 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 8.0000e-02 -4.1059e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 8.0000e-02 min -1.1184e+00 max 4.1933e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 8.0000e-02 min -1.5841e-03 max 4.8000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m80 TS dt 0.001 time 0.08\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 1.960392276603e+00 [ 2.740279339725e-14 , 4.679652343327e-04 , 9.773182850183e-03 , 1.960367859375e+00 , 1.104999871348e-12 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 2.099804688938e-02 [ 5.224633435828e-15 , 1.491560427226e-06 , 4.451439698610e-05 , 2.099799965264e-02 , 4.739931823776e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 9.385925123340e-06 [ 5.667101067648e-15 , 5.409924937798e-10 , 5.308037877968e-08 , 9.385775013373e-06 , 4.783073322621e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 3 SNES Function norm 2.173781007345e-12 [ 5.708368059721e-15 , 5.933426989885e-15 , 1.707109667859e-12 , 1.251772675847e-12 , 4.940625737472e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 80 accepted t=0.08 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 8.1000e-02 -4.0935e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 8.1000e-02 min -1.1355e+00 max 4.2554e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 8.1000e-02 min -1.6211e-03 max 4.8600e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m81 TS dt 0.001 time 0.081\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.277171955423e+00 [ 2.440992683297e-14 , 5.423425885777e-04 , 1.111168364719e-02 , 2.277144780403e+00 , 1.037719470781e-12 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 3.002256048272e-02 [ 4.803575035243e-15 , 2.544350767914e-06 , 7.907727199780e-05 , 3.002245623279e-02 , 4.915771372617e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 2.565438018836e-05 [ 5.981046373892e-15 , 1.711742080911e-09 , 1.364413061102e-07 , 2.565401730117e-05 , 4.847257943343e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 3 SNES Function norm 6.405278069876e-12 [ 5.678194232320e-15 , 5.747640744219e-15 , 2.077888631027e-12 , 6.035123602824e-12 , 5.358953357305e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 81 accepted t=0.081 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 8.2000e-02 -4.0772e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 8.2000e-02 min -1.1528e+00 max 4.3189e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 8.2000e-02 min -1.6595e-03 max 4.9200e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m82 TS dt 0.001 time 0.082\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 2.766362088577e+00 [ 1.483831121713e-14 , 6.569616389909e-04 , 1.309215424804e-02 , 2.766331030267e+00 , 1.041942581535e-12 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 4.839358496658e-02 [ 7.243333662497e-15 , 5.048537873664e-06 , 1.638343402058e-04 , 4.839330737549e-02 , 4.877951348580e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 1.003997043804e-04 [ 5.020890114297e-15 , 7.875890585182e-09 , 4.892855413730e-07 , 1.003985118281e-04 , 4.855359198732e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 3 SNES Function norm 8.870194748044e-11 [ 6.207277557359e-15 , 1.367216343825e-14 , 2.166631471664e-12 , 8.867405018896e-11 , 5.037782408094e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 82 accepted t=0.082 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 8.3000e-02 -4.0545e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 8.3000e-02 min -1.1706e+00 max 4.3847e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 8.3000e-02 min -1.6998e-03 max 4.9800e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m83 TS dt 0.001 time 0.083\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 3.609516588763e+00 [ 1.736233915633e-14 , 8.541768728033e-04 , 1.634137306109e-02 , 3.609479496335e+00 , 1.110795428545e-12 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 9.510989667797e-02 [ 3.964672079990e-15 , 1.280430926949e-05 , 4.328855122219e-04 , 9.510891068810e-02 , 5.162754923437e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 7.413812613300e-04 [ 5.273011877792e-15 , 6.858466627461e-08 , 3.212011493016e-06 , 7.413743001545e-04 , 5.159209961355e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 3 SNES Function norm 4.996979445774e-09 [ 5.034036882490e-15 , 9.366778255224e-13 , 2.950157378444e-11 , 4.996892245187e-09 , 5.012315615437e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 83 accepted t=0.083 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 8.4000e-02 -4.0194e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 8.4000e-02 min -1.1889e+00 max 4.4539e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 8.4000e-02 min -1.7428e-03 max 5.0400e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m84 TS dt 0.001 time 0.084\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 0 SNES Function norm 5.357510566042e+00 [ 1.708438122889e-14 , 1.262476000623e-03 , 2.271068429539e-02 , 5.357462281363e+00 , 1.195659328180e-12 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 1 SNES Function norm 2.724298498744e-01 [ 6.474975846661e-15 , 5.134961305678e-05 , 1.789144897886e-03 , 2.724239699923e-01 , 4.964504613594e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 2 SNES Function norm 2.423364775862e-02 [ 7.975598619096e-15 , 1.831897464228e-06 , 1.128378331010e-04 , 2.423338498758e-02 , 4.956965925763e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 3 SNES Function norm 1.703440345564e-05 [ 6.256734685521e-15 , 4.472480499923e-09 , 1.303579886981e-07 , 1.703390407045e-05 , 5.501135131304e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m 4 SNES Function norm 1.830985337816e-10 [ 7.472275304157e-15 , 1.717114160062e-14 , 2.254712406471e-12 , 1.830839551335e-10 , 5.043479990169e-13 ]\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m TSAdapt none theta 0: step 84 accepted t=0.084 + 1.000e-03 dt=1.000e-03 \n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mreaction time 8.5000e-02 -3.9475e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUx time 8.5000e-02 min -1.2085e+00 max 4.5310e-02\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[example] \u001b[0mUy time 8.5000e-02 min -1.7912e-03 max 5.1000e+00\n",
"[\u001b[32m0\u001b[0m] \u001b[34m<inform> \u001b[0m\u001b[1m[petsc] \u001b[0m85 TS dt 0.001 time 0.085\n"
]
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 863
},
"id": "K_C3MwC9FiR1",
"outputId": "aa51e9fb-ce2f-49f6-88e8-372fe2321566"
},
"source": [
"import os\n",
"import numpy as np\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib.image as mpimg\n",
"\n",
"\n",
"#global parameters\n",
"markersize=6\n",
"line_width=2\n",
"font_size=12\n",
"font_weight='normal'\n",
"plt.rcParams['figure.dpi'] = 100\n",
"plt.rcParams['font.family'] = \"DejaVu Serif\"\n",
"plt.rcParams['font.size'] = font_size\n",
"plt.rcParams['font.weight'] = font_weight\n",
"plt.rcParams['figure.figsize'] = [15, 10]\n",
"\n",
"u_pos = []\n",
"os.chdir(dir)\n",
"\n",
"!grep reaction 'log_thermo_plasticity' > reaction\n",
"!grep Uy 'log_thermo_plasticity' > uy\n",
"\n",
"final_u = []\n",
"final_f = []\n",
"\n",
"data_reaction=pd.read_csv('reaction',sep='\\s+',header=None)\n",
"data_reaction=data_reaction.rename(columns={ 6: \"force\"})\n",
"final_f = np.abs(np.array(206913*data_reaction['force']/1000))\n",
"\n",
"data_uy=pd.read_csv('uy',sep='\\s+',header=None)\n",
"data_uy=data_uy.rename(columns={5: \"time\", 7: \"min\", 9: \"max\"})\n",
"np_u_array_min = np.array(data_uy['min'])\n",
"np_u_array_max = np.array(data_uy['max'])\n",
"final_u = np.where(abs(np_u_array_min) > abs(np_u_array_max), np_u_array_min, np_u_array_max)\n",
"\n",
"!grep reaction 'log_no_thermo_plasticity' > reaction_nt\n",
"!grep Uy 'log_no_thermo_plasticity' > uy_nt\n",
"\n",
"final_u_nt = []\n",
"final_f_nt = []\n",
"\n",
"data_reaction_nt=pd.read_csv('reaction_nt',sep='\\s+',header=None)\n",
"data_reaction_nt=data_reaction_nt.rename(columns={ 6: \"force\"})\n",
"final_f_nt = np.abs(np.array(206913*data_reaction_nt['force']/1000))\n",
"\n",
"data_uy_nt=pd.read_csv('uy_nt',sep='\\s+',header=None)\n",
"data_uy_nt=data_uy_nt.rename(columns={5: \"time\", 7: \"min\", 9: \"max\"})\n",
"np_u_array_min_nt = np.array(data_uy_nt['min'])\n",
"np_u_array_max_nt = np.array(data_uy_nt['max'])\n",
"final_u_nt = np.where(abs(np_u_array_min_nt) > abs(np_u_array_max_nt), np_u_array_min_nt, np_u_array_max_nt)\n",
"\n",
"\n",
"fig, ax = plt.subplots()\n",
"\n",
"\n",
"ax.plot(final_u_nt, \n",
" final_f_nt, 'bo-', label='$\\omega_{0} = 0$,$\\omega_{H} = 0$,$\\omega_{Q_{/inf}} = 0$')\n",
"\n",
"ax.plot(final_u , \n",
" final_f , 'ro-', label='$\\omega_{0} = 2e^{-3}$,$\\omega_{H} = 2e^{-3}$,$\\omega_{Q_{/inf}} = 2e^{-3}$')\n",
"\n",
"\n",
"ax.set(xlabel='Axial Displacement [mm]', ylabel='Force [kN]',\n",
" title='Load displacement path')\n",
"ax.legend(loc='lower right')\n",
"ax.grid(True)\n",
"plt.savefig('Necking2RodThermalD.png')"
],
"execution_count": 9,
"outputs": [
{
"output_type": "display_data",
"data": {
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"text/plain": [
"<Figure size 1500x1000 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "mFT4ihVfMtZT"
},
"source": [
"**Visualisation of the results via PyVista**"
]
},
{
"cell_type": "code",
"metadata": {
"id": "uqWDPYyaMgBV"
},
"source": [
"dir='/content/um_view/tutorials/adv-2'\n",
"bin_dir='/content/um_view/bin'\n",
"import os\n",
"os.chdir(dir)\n",
"list_of_files=!ls -c1 out*h5m\n",
"for f in list_of_files:\n",
" !{bin_dir}/mbconvert {f} {f}.vtk 2>/dev/null"
],
"execution_count": 10,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"id": "oNMqPXVEOYh9",
"outputId": "985efeb0-84bb-48db-c327-17f27378fa2f"
},
"source": [
"#from pyvirtualdisplay import Display\n",
"#display = Display(visible=0, size=(1200, 800))\n",
"#display.start()\n",
"import os\n",
"os.system('/usr/bin/Xvfb :98 -screen 0 1024x768x24 &')\n",
"os.environ['DISPLAY'] = ':98'\n",
"os.environ['PYVISTA_USE_IPYVTK'] = 'true'\n",
"\n",
"import pyvista as pv\n",
"import matplotlib.pyplot as plt\n",
"from matplotlib.colors import ListedColormap\n",
"\n",
"import numpy as np\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib.image as mpimg\n",
"\n",
"from IPython.display import HTML, Image\n",
"\n",
"dir='/content/um_view/tutorials/adv-2'\n",
"bin_dir='/content/um_view/bin'\n",
"import os\n",
"os.chdir(dir)\n",
"\n",
"nb_steps=!ls -c1 out*h5m.vtk | wc -l\n",
"nb_steps=int(nb_steps[0])\n",
"print(nb_steps)\n",
"\n",
"file='out_plastic_%d.h5m.vtk' % (nb_steps-1)\n",
"mesh = pv.read(file)\n",
"\n",
"cpos=[(0.0, 0.0, 100),\n",
" (0.0, 0.0, 0.0),\n",
" (1.0, 0.0, 0.0)]\n",
"\n",
"# Scale displacements\n",
"scale_factor=1\n",
"\n",
"# Create a plotter object \n",
"plotter = pv.Plotter(notebook=True)\n",
"my_cmap = plt.cm.get_cmap(\"twilight\", 32)\n",
"\n",
"plotter.add_mesh(mesh, \n",
" scalars='PLASTIC_MULTIPLIER',\n",
" cmap=my_cmap,\n",
" show_edges=True, \n",
" smooth_shading=False)\n",
"#mesh=mesh.warp_by_vector('U',factor=scale_factor)\n",
"plotter.add_axes()\n",
"plotter.camera_position=cpos\n",
"\n",
"print(mesh.point_arrays)\n",
"\n",
"# setup camera and close\n",
"plotter.render()\n",
"\n",
"# # Open a gif\n",
"out_gif='thermo_plasticity_plastic_multiplier.gif'\n",
"plotter.open_gif(out_gif)\n",
"\n",
"list_of_files=!ls -c1 out*h5m.vtk\n",
"for f in list_of_files:\n",
" #print('Render file ',f)\n",
" n_mesh=pv.read(f)\n",
" n_mesh=n_mesh.warp_by_vector('U',factor=scale_factor)\n",
" plotter.update_coordinates(n_mesh.points, mesh, render=True)\n",
" plotter.update_scalars(n_mesh.point_arrays['PLASTIC_MULTIPLIER'], mesh, render=True)\n",
" plotter.write_frame() # this will trigger the render\n",
"\n",
"# Close movie and delete object\n",
"plotter.close()\n",
"from IPython.display import HTML, Image\n",
"dir='/content/um_view/tutorials/adv-2'\n",
"bin_dir='/content/um_view/bin'\n",
"import os\n",
"os.chdir(dir)\n",
"Image(open('thermo_plasticity_plastic_multiplier.gif','rb').read())"
],
"execution_count": 20,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"86\n",
"pyvista DataSetAttributes\n",
"Association : POINT\n",
"Active Scalars : PLASTIC_MULTIPLIER\n",
"Active Vectors : U\n",
"Active Texture : None\n",
"Active Normals : None\n",
"Contains arrays :\n",
" GLOBAL_ID int32 (774,)\n",
" HARDENING float64 (774,)\n",
" PLASTIC_FLOW float64 (774, 9) TENSORS\n",
" PLASTIC_MULTIPLIER float64 (774,) SCALARS\n",
" PLASTIC_SURFACE float64 (774,)\n",
" TEMPERATURE float64 (774,)\n",
" U float64 (774, 3) VECTORS\n"
]
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.7/dist-packages/pyvista/core/dataset.py:1195: PyvistaDeprecationWarning: Use of `point_arrays` is deprecated. Use `point_data` instead.\n",
" PyvistaDeprecationWarning\n"
]
},
{
"output_type": "execute_result",
"data": {
"image/png": 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