https://github.com/hpc-maths/GenEO
Revision 9f83d7f18f7346885b67494b3124b6cf2d0228e8 authored by gouarin on 29 May 2018, 07:41:15 UTC, committed by gouarin on 29 May 2018, 07:41:15 UTC
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Tip revision: 9f83d7f18f7346885b67494b3124b6cf2d0228e8 authored by gouarin on 29 May 2018, 07:41:15 UTC
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Tip revision: 9f83d7f
demo 3d.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Writing demo_3d.py\n"
]
}
],
"source": [
"%%file demo_3d.py\n",
"\n",
"from __future__ import print_function, division\n",
"import os\n",
"import sys, petsc4py\n",
"petsc4py.init(sys.argv)\n",
"import mpi4py.MPI as mpi\n",
"from petsc4py import PETSc\n",
"import numpy as np\n",
"from GenEO import *\n",
"\n",
"def rhs(coords, rhs):\n",
" rhs[..., 1] = -9.81# + rand\n",
"\n",
"OptDB = PETSc.Options()\n",
"Lx = OptDB.getInt('Lx', 10)\n",
"Ly = OptDB.getInt('Ly', 1)\n",
"Lz = OptDB.getInt('Lz', 1)\n",
"n = OptDB.getInt('n', 16)\n",
"nx = OptDB.getInt('nx', Lx*n)\n",
"ny = OptDB.getInt('ny', Ly*n)\n",
"nz = OptDB.getInt('nz', Lz*n)\n",
"E1 = OptDB.getReal('E1', 10**6)\n",
"E2 = OptDB.getReal('E2', 1)\n",
"nu1 = OptDB.getReal('nu1', 0.4)\n",
"nu2 = OptDB.getReal('nu2', 0.4)\n",
"\n",
"hx = Lx/(nx - 1)\n",
"hy = Ly/(ny - 1)\n",
"hz = Lz/(nz - 1)\n",
"h = [hx, hy, hz]\n",
"\n",
"da = PETSc.DMDA().create([nx, ny, nz], dof=3, stencil_width=1)\n",
"da.setUniformCoordinates(xmax=Lx, ymax=Ly, zmax=Lz)\n",
"da.setMatType(PETSc.Mat.Type.IS)\n",
"\n",
"path = './output_3d/'\n",
"if mpi.COMM_WORLD.rank == 0:\n",
" if not os.path.exists(path):\n",
" os.mkdir(path)\n",
" else:\n",
" os.system('rm {}/*.vts'.format(path))\n",
"\n",
"class callback:\n",
" def __init__(self, da):\n",
" self.da = da\n",
" ranges = da.getRanges()\n",
" ghost_ranges = da.getGhostRanges()\n",
" \n",
" self.slices = []\n",
" for r, gr in zip(ranges, ghost_ranges):\n",
" self.slices.append(slice(gr[0], r[1]))\n",
" self.slices = tuple(self.slices)\n",
"\n",
" self.it = 0\n",
"\n",
" def __call__(self, locals):\n",
" pyKSP = locals['self']\n",
" proj = pyKSP.mpc.proj\n",
"\n",
"\n",
" if self.it == 0:\n",
" work, _ = proj.A.getVecs()\n",
" for i, vec in enumerate(proj.coarse_vecs):\n",
" if vec:\n",
" proj.workl = vec.copy()\n",
" else:\n",
" proj.workl.set(0.)\n",
" work.set(0)\n",
" proj.scatter_l2g(proj.workl, work, PETSc.InsertMode.ADD_VALUES)\n",
"\n",
" viewer = PETSc.Viewer().createVTK(path + 'coarse_vec_{}.vts'.format(i), 'w', comm = PETSc.COMM_WORLD)\n",
" tmp = self.da.createGlobalVec()\n",
" tmpl_a = self.da.getVecArray(tmp)\n",
" work_a = self.da.getVecArray(work)\n",
" tmpl_a[:] = work_a[:]\n",
" tmp.view(viewer)\n",
" viewer.destroy()\n",
" self.it += 1\n",
"\n",
"def lame_coeff(x, y, z, v1, v2):\n",
" output = np.empty(x.shape)\n",
" mask = np.logical_or(np.logical_and(.2<=z, z<=.4),np.logical_and(.6<=z, z<=.8))\n",
" output[mask] = v1\n",
" output[np.logical_not(mask)] = v2\n",
" return output\n",
"\n",
"# non constant Young's modulus and Poisson's ratio \n",
"E = buildCellArrayWithFunction(da, lame_coeff, (E1,E2))\n",
"nu = buildCellArrayWithFunction(da, lame_coeff, (nu1, nu2))\n",
"\n",
"lamb = (nu*E)/((1+nu)*(1-2*nu)) \n",
"mu = .5*E/(1+nu)\n",
"\n",
"x = da.createGlobalVec()\n",
"b = buildRHS(da, h, rhs)\n",
"A = buildElasticityMatrix(da, h, lamb, mu)\n",
"A.assemble()\n",
"\n",
"bcApplyWest(da, A, b)\n",
"bcopy = b.copy()\n",
"\n",
"pcbnn = PCBNN(A)\n",
"\n",
"# Set initial guess\n",
"x.setRandom()\n",
"xnorm = b.dot(x)/x.dot(A*x)\n",
"x *= xnorm\n",
"\n",
"ksp = PETSc.KSP().create()\n",
"ksp.setOperators(A)\n",
"ksp.setType(ksp.Type.PYTHON)\n",
"pyKSP = KSP_AMPCG(pcbnn)\n",
"pyKSP.callback = callback(da)\n",
"ksp.setPythonContext(pyKSP)\n",
"ksp.setInitialGuessNonzero(True)\n",
"ksp.setFromOptions()\n",
"\n",
"ksp.solve(b, x)\n",
"\n",
"viewer = PETSc.Viewer().createVTK(path + 'solution_3d.vts', 'w', comm = PETSc.COMM_WORLD)\n",
"x.view(viewer)\n",
"\n",
"lamb_petsc = da.createGlobalVec()\n",
"lamb_a = da.getVecArray(lamb_petsc)\n",
"coords = da.getCoordinates()\n",
"coords_a = da.getVecArray(coords)\n",
"E = lame_coeff(coords_a[:, :, :, 0], coords_a[:, :, :, 1], coords_a[:, :, :, 2], E1, E2)\n",
"nu = lame_coeff(coords_a[:, :, :, 0], coords_a[:, :, :, 1], coords_a[:, :, :, 2], nu1, nu2)\n",
"\n",
"lamb_a[:, :, :, 0] = (nu*E)/((1+nu)*(1-2*nu)) \n",
"lamb_a[:, :, :, 1] = mpi.COMM_WORLD.rank\n",
"lamb_petsc.view(viewer)\n",
"\n",
"viewer.destroy()"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Subdomain number 2 contributes 6 coarse vectors as zero energy modes of local solver\n",
"Subdomain number 3 contributes 6 coarse vectors as zero energy modes of local solver\n",
"Subdomain number 1 contributes 6 coarse vectors as zero energy modes of local solver\n",
"Subdomain number 0 contributes 0 coarse vectors as zero energy modes of local solver\n",
"WARNING: The largest eigenvalue computed for GenEO_eigmax in subdomain 0 is (0.08792103741103695+0j) < the threshold which is 0.2. Consider setting PCBNN_GenEO_nev to something larger than 12\n",
"WARNING: The largest eigenvalue computed for GenEO_eigmax in subdomain 1 is (0.04587996918296301+0j) < the threshold which is 0.2. Consider setting PCBNN_GenEO_nev to something larger than 14\n",
"WARNING: The largest eigenvalue computed for GenEO_eigmax in subdomain 2 is (0.04587996918296301+0j) < the threshold which is 0.2. Consider setting PCBNN_GenEO_nev to something larger than 14\n",
"GenEO eigenvalue number 0 for lambdamax in subdomain 0: (0.00027210717238778715+0j)\n",
"GenEO eigenvalue number 1 for lambdamax in subdomain 0: (0.00028968623656886334+0j)\n",
"GenEO eigenvalue number 2 for lambdamax in subdomain 0: (0.004659628069890074+0j)\n",
"GenEO eigenvalue number 3 for lambdamax in subdomain 0: (0.004662790570237592+0j)\n",
"GenEO eigenvalue number 4 for lambdamax in subdomain 0: (0.007427946211460551+0j)\n",
"GenEO eigenvalue number 5 for lambdamax in subdomain 0: (0.0074445559391044846+0j)\n",
"GenEO eigenvalue number 6 for lambdamax in subdomain 0: (0.023991319480995324+0j)\n",
"GenEO eigenvalue number 7 for lambdamax in subdomain 0: (0.023992114566999734+0j)\n",
"GenEO eigenvalue number 8 for lambdamax in subdomain 0: (0.07872691268417042+0j)\n",
"GenEO eigenvalue number 9 for lambdamax in subdomain 0: (0.07873063971848118+0j)\n",
"GenEO eigenvalue number 10 for lambdamax in subdomain 0: (0.08777882036336886+0j)\n",
"GenEO eigenvalue number 11 for lambdamax in subdomain 0: (0.08792103741103695+0j)\n",
"Subdomain number 0 contributes 12 coarse vectors after first GenEO\n",
"This is BNN so eigmin = 1, no eigenvalue problem will be solved for eigmin\n",
"Subdomain number 0 contributes 12 coarse vectors in total\n",
"WARNING: The largest eigenvalue computed for GenEO_eigmax in subdomain 3 is (0.1527582349059751+0j) < the threshold which is 0.2. Consider setting PCBNN_GenEO_nev to something larger than 12\n",
"GenEO eigenvalue number 0 for lambdamax in subdomain 1: (1.4943965693716365e-06+0j)\n",
"GenEO eigenvalue number 1 for lambdamax in subdomain 1: (2.2484309735267134e-06+0j)\n",
"GenEO eigenvalue number 2 for lambdamax in subdomain 1: (1.1159913381184637e-05+0j)\n",
"GenEO eigenvalue number 3 for lambdamax in subdomain 1: (1.2644454455657916e-05+0j)\n",
"GenEO eigenvalue number 4 for lambdamax in subdomain 1: (3.433953656439918e-05+0j)\n",
"GenEO eigenvalue number 5 for lambdamax in subdomain 1: (4.0521819218450205e-05+0j)\n",
"GenEO eigenvalue number 6 for lambdamax in subdomain 1: (0.012524136504701952+0j)\n",
"GenEO eigenvalue number 7 for lambdamax in subdomain 1: (0.01253287403167038+0j)\n",
"GenEO eigenvalue number 8 for lambdamax in subdomain 1: (0.045511195880540124+0j)\n",
"GenEO eigenvalue number 9 for lambdamax in subdomain 1: (0.04553672984302139+0j)\n",
"GenEO eigenvalue number 10 for lambdamax in subdomain 1: (0.04553720869837318+0j)\n",
"GenEO eigenvalue number 11 for lambdamax in subdomain 1: (0.04561874608322997+0j)\n",
"GenEO eigenvalue number 12 for lambdamax in subdomain 1: (0.045622261557106365+0j)\n",
"GenEO eigenvalue number 13 for lambdamax in subdomain 1: (0.04587996918296301+0j)\n",
"Subdomain number 1 contributes 20 coarse vectors after first GenEO\n",
"Subdomain number 1 contributes 20 coarse vectors in total\n",
"GenEO eigenvalue number 0 for lambdamax in subdomain 2: (1.4943965693716365e-06+0j)\n",
"GenEO eigenvalue number 1 for lambdamax in subdomain 2: (2.2484309735267134e-06+0j)\n",
"GenEO eigenvalue number 2 for lambdamax in subdomain 2: (1.1159913381184637e-05+0j)\n",
"GenEO eigenvalue number 3 for lambdamax in subdomain 2: (1.2644454455657916e-05+0j)\n",
"GenEO eigenvalue number 4 for lambdamax in subdomain 2: (3.433953656439918e-05+0j)\n",
"GenEO eigenvalue number 5 for lambdamax in subdomain 2: (4.0521819218450205e-05+0j)\n",
"GenEO eigenvalue number 6 for lambdamax in subdomain 2: (0.012524136504701952+0j)\n",
"GenEO eigenvalue number 7 for lambdamax in subdomain 2: (0.01253287403167038+0j)\n",
"GenEO eigenvalue number 8 for lambdamax in subdomain 2: (0.045511195880540124+0j)\n",
"GenEO eigenvalue number 9 for lambdamax in subdomain 2: (0.04553672984302139+0j)\n",
"GenEO eigenvalue number 10 for lambdamax in subdomain 2: (0.04553720869837318+0j)\n",
"GenEO eigenvalue number 11 for lambdamax in subdomain 2: (0.04561874608322997+0j)\n",
"GenEO eigenvalue number 12 for lambdamax in subdomain 2: (0.045622261557106365+0j)\n",
"GenEO eigenvalue number 13 for lambdamax in subdomain 2: (0.04587996918296301+0j)\n",
"Subdomain number 2 contributes 20 coarse vectors after first GenEO\n",
"Subdomain number 2 contributes 20 coarse vectors in total\n",
"GenEO eigenvalue number 0 for lambdamax in subdomain 3: (4.950913362612114e-06+0j)\n",
"GenEO eigenvalue number 1 for lambdamax in subdomain 3: (1.931926873350419e-05+0j)\n",
"GenEO eigenvalue number 2 for lambdamax in subdomain 3: (3.1851795098490415e-05+0j)\n",
"GenEO eigenvalue number 3 for lambdamax in subdomain 3: (6.849472393730482e-05+0j)\n",
"GenEO eigenvalue number 4 for lambdamax in subdomain 3: (8.416808782391296e-05+0j)\n",
"GenEO eigenvalue number 5 for lambdamax in subdomain 3: (0.007419519611383512+0j)\n",
"GenEO eigenvalue number 6 for lambdamax in subdomain 3: (0.116681045637096+0j)\n",
"GenEO eigenvalue number 7 for lambdamax in subdomain 3: (0.11690279679885499+0j)\n",
"GenEO eigenvalue number 8 for lambdamax in subdomain 3: (0.1340511856189999+0j)\n",
"GenEO eigenvalue number 9 for lambdamax in subdomain 3: (0.13405131567845738+0j)\n",
"GenEO eigenvalue number 10 for lambdamax in subdomain 3: (0.15263867458595137+0j)\n",
"GenEO eigenvalue number 11 for lambdamax in subdomain 3: (0.1527582349059751+0j)\n",
"Subdomain number 3 contributes 18 coarse vectors after first GenEO\n",
"Subdomain number 3 contributes 18 coarse vectors in total\n",
"There are 70 vectors in the coarse space.\n",
"multipreconditioning initial iteration\n",
" 0 KSP Residual norm 4.879715526063e+01 \n",
"\tnatural_norm -> 4.07518473e+00\n",
"\tti -> 0.00000000e+00\n",
" 1 KSP Residual norm 1.601856581102e+02 \n",
"\tnatural_norm -> 1.26818285e+00\n",
"\tti -> 1.01363018e+01\n",
" 2 KSP Residual norm 3.354429682724e+01 \n",
"\tnatural_norm -> 2.34243292e-01\n",
"\tti -> 4.23565872e+00\n",
" 3 KSP Residual norm 1.308368954849e+01 \n",
"\tnatural_norm -> 7.42688385e-02\n",
"\tti -> 2.47389012e+00\n",
" 4 KSP Residual norm 3.702213625230e+00 \n",
"\tnatural_norm -> 2.07286714e-02\n",
"\tti -> 4.03940295e+00\n",
" 5 KSP Residual norm 1.933887183411e+00 \n",
"\tnatural_norm -> 1.02089449e-02\n",
"\tti -> 8.08709217e-01\n",
" 6 KSP Residual norm 1.112954693983e+00 \n",
"\tnatural_norm -> 7.59854971e-03\n",
"\tti -> 3.66921342e-01\n",
" 7 KSP Residual norm 4.747052328566e-01 \n",
"\tnatural_norm -> 3.50322665e-03\n",
"\tti -> 7.71452698e-01\n",
" 8 KSP Residual norm 1.247042269859e-01 \n",
"\tnatural_norm -> 1.00863435e-03\n",
"\tti -> 2.48418852e+00\n",
" 9 KSP Residual norm 7.745240355564e-02 \n",
"\tnatural_norm -> 4.93174094e-04\n",
"\tti -> 1.05337979e+00\n",
" 10 KSP Residual norm 5.119202384199e-02 \n",
"\tnatural_norm -> 3.19858407e-04\n",
"\tti -> 4.07518636e-01\n",
" 11 KSP Residual norm 2.073565765415e-02 \n",
"\tnatural_norm -> 1.28931583e-04\n",
"\tti -> 1.68871490e+00\n",
" 12 KSP Residual norm 1.145224306262e-02 \n",
"\tnatural_norm -> 7.65039445e-05\n",
"\tti -> 6.80558453e-01\n",
" 13 KSP Residual norm 4.674147033805e-03 \n",
"\tnatural_norm -> 3.55034026e-05\n",
"\tti -> 1.01878796e+00\n",
" 14 KSP Residual norm 2.994668518381e-03 \n",
"\tnatural_norm -> 2.12431166e-05\n",
"\tti -> 3.79630670e-01\n",
" 15 KSP Residual norm 9.717597005509e-04 \n",
"\tnatural_norm -> 8.24665178e-06\n",
"\tti -> 1.69338624e+00\n",
" 16 KSP Residual norm 5.081117632336e-04 \n",
"\tnatural_norm -> 5.84052397e-06\n",
"\tti -> 5.99348271e-01\n",
" 17 KSP Residual norm 3.002734160302e-04 \n",
"\tnatural_norm -> 2.44561337e-06\n",
"\tti -> 8.66033500e-01\n",
" 18 KSP Residual norm 1.506771668797e-04 \n",
"\tnatural_norm -> 1.05997555e-06\n",
"\tti -> 1.45701266e+00\n",
" 19 KSP Residual norm 4.833059413331e-05 \n",
"\tnatural_norm -> 3.24905577e-07\n",
"\tti -> 3.96088408e+00\n",
" 20 KSP Residual norm 2.503537813954e-05 \n",
"\tnatural_norm -> 1.72057142e-07\n",
"\tti -> 1.31581414e+00\n",
" 21 KSP Residual norm 1.369025117864e-05 \n",
"\tnatural_norm -> 9.10359985e-08\n",
"\tti -> 7.75168292e-01\n",
" 22 KSP Residual norm 6.058998523987e-06 \n",
"\tnatural_norm -> 4.11096140e-08\n",
"\tti -> 1.52648452e+00\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
" 23 KSP Residual norm 3.321180687944e-06 \r\n",
"\tnatural_norm -> 2.14657371e-08\r\n",
"\tti -> 1.08733139e+00\r\n"
]
}
],
"source": [
"!mpiexec -np 4 python demo_3d.py -AMPCG_verbose -ksp_monitor -PCBNN_verbose"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"from plot import plot_solution"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
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]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_solution('output_3d', 'solution_3d.vts')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
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