Skip to content

Instantly share code, notes, and snippets.

@sgkang
Last active February 1, 2018 02:15
Show Gist options
  • Save sgkang/37f466dce1450d4c2fed129b468d978b to your computer and use it in GitHub Desktop.
Save sgkang/37f466dce1450d4c2fed129b468d978b to your computer and use it in GitHub Desktop.
Display the source blob
Display the rendered blob
Raw
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/sgkang/Projects/simpeg/SimPEG/EM/Static/DC/IODC.py:13: UserWarning: code under construction - API might change in the future\n",
" warnings.warn(\"code under construction - API might change in the future\")\n"
]
}
],
"source": [
"import matplotlib.pyplot as plt\n",
"from SimPEG import (\n",
" Mesh, Problem, Survey, Maps, Utils,\n",
" EM, DataMisfit, Regularization, Optimization,\n",
" InvProblem, Directives, Inversion\n",
")\n",
"from SimPEG.EM.Static import DC, Utils as DCUtils\n",
"try:\n",
" from pymatsolver import Pardiso as Solver\n",
"except ImportError:\n",
" from SimPEG import SolverLU as Solver\n",
"\n",
"import numpy as np\n",
"# import JDataObject as Jdata\n",
"\n",
"################################################################\n",
"# define the file required for import\n",
"# fileName = \"/Users/juan/Documents/testData/FieldSchool_2017new.DAT\"\n",
"# fileName2 = \"/Users/juan/Documents/testData/FieldSchool_Mesh.txt\"\n",
"# fileName3 = \"/Users/juan/Documents/testData/FS2017.obs\"\n",
"\n",
"fileName = \"FieldSchool_2017new.DAT\"\n",
"fileName2 = \"FieldSchool_Mesh.txt\"\n",
"fileName3 = \"FS2017.obs\"\n",
"\n",
"\n",
"# survey = Jdata.loadDiasToDcSurvey(fileName)\n",
"# plt.plot(np.asarray(xpp), np.asarray(ypp), 'o')\n",
"# plt.show()\n",
"survey = DCUtils.StaticUtils.readUBC_DC3Dobs(fileName3)\n",
"# print len(xpp)\n",
"# 3D Mesh\n",
"#############################################################\n",
"\n",
"# Create mesh and center it\n",
"mesh = Mesh.TensorMesh._readUBC_3DMesh(fileName2) # Read in/create the mesgh\n",
"survey = survey['dc_survey']\n",
"survey.getABMN_locations()\n",
"uniq = Utils.uniqueRows(np.vstack((survey.a_locations, survey.b_locations, survey.m_locations, survey.n_locations)))\n",
"electrode_locations = uniq[0]\n",
"actinds = Utils.surface2ind_topo(mesh, electrode_locations, method='cubic')\n",
"survey.drapeTopo(mesh, actinds)\n",
"\n",
"# Begin Formulating Problem\n",
"############################################################\n",
"# print minE, maxE, minN, maxN\n",
"\n",
"# Setup Problem with exponential mapping and Active cells only in the core mesh\n",
"expmap = Maps.ExpMap(mesh)\n",
"mapactive = Maps.InjectActiveCells(mesh=mesh, indActive=actinds,\n",
" valInactive=np.log(1e-8))\n",
"mapping = expmap * mapactive\n",
"problem = DC.Problem3D_N(mesh, sigmaMap=mapping)\n",
"problem.pair(survey)\n",
"problem.Solver = Solver"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Populating the interactive namespace from numpy and matplotlib\n"
]
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x113e2afd0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%pylab inline\n",
"# Assign Uncertainty\n",
"out = hist(np.log10(abs(survey.dobs)+1e-5), bins=100)\n",
"survey.std = 0.05\n",
"survey.eps = 1e-2"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# sig_half = 1./90\n",
"# m0 = np.log(sig_half) * np.ones(mapping.nP)\n",
"# pred = survey.dpred(m0)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x2293110f0>]"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x229311e10>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.semilogy(abs(survey.dobs))\n",
"plt.semilogy(abs(pred)*0.9, '.')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Tikhonov Inversion#\n",
"############################################################\n",
"\n",
"# Initial Model\n",
"sig_half = 1./90\n",
"m0 = np.log(sig_half) * np.ones(mapping.nP)\n",
"dmis = DataMisfit.l2_DataMisfit(survey) # Data Misfit\n",
"\n",
"# Regularization\n",
"regT = Regularization.Simple(mesh, indActive=actind, alpha_s=1e-6,\n",
" alpha_x=1., alpha_y=1., alpha_z=1.)\n",
"\n",
"# Optimization Scheme\n",
"opt = Optimization.InexactGaussNewton(maxIter=10)\n",
"\n",
"# Form the problem\n",
"opt.remember('xc')\n",
"invProb = InvProblem.BaseInvProblem(dmis, regT, opt)\n",
"\n",
"# Directives for Inversions\n",
"beta = Directives.BetaEstimate_ByEig(beta0_ratio=1e+1)\n",
"Target = Directives.TargetMisfit()\n",
"betaSched = Directives.BetaSchedule(coolingFactor=5., coolingRate=2)\n",
"\n",
"inv = Inversion.BaseInversion(invProb, directiveList=[beta, Target,\n",
" betaSched])\n",
"\n",
"# Run Inversion\n",
"minv = inv.run(m0)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment