mirror of
https://github.com/wassname/simpeg.git
synced 2026-07-08 02:41:28 +08:00
seogi
402 lines
20 KiB
Plaintext
402 lines
20 KiB
Plaintext
{
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"metadata": {
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"name": ""
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},
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"nbformat": 3,
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"nbformat_minor": 0,
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"worksheets": [
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{
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"cells": [
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"from SimPEG import Mesh, Problem, Utils, np, sp, Tests\n",
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"from simpegPF.Magnetics import BaseMag, MagneticsDiffSecondary\n",
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"from scipy.constants import mu_0\n",
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"from simpegPF.MagAnalytics import spheremodel, CongruousMagBC\n",
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"%pylab inline"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"output_type": "stream",
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"stream": "stdout",
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"text": [
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"Populating the interactive namespace from numpy and matplotlib\n"
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]
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}
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],
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"prompt_number": 15
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [],
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"language": "python",
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"metadata": {},
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"outputs": [],
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"prompt_number": 16
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"import matplotlib.pyplot as plt\n",
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"# hxind = ((5,25,1.3),(41, 12.5),(5,25,1.3))\n",
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"# hyind = ((5,25,1.3),(41, 12.5),(5,25,1.3))\n",
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"# hzind = ((5,25,1.3),(40, 12.5),(5,25,1.3))\n",
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"\n",
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"hxind = ((5,25,1.3),(21, 25.),(5,25,1.3))\n",
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"hyind = ((5,25,1.3),(21, 25.),(5,25,1.3))\n",
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"hzind = ((5,25,1.3),(20, 25.),(5,25,1.3))\n",
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"\n",
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"hx, hy, hz = Utils.meshTensors(hxind, hyind, hzind)\n",
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"mesh = Mesh.TensorMesh([hx, hy, hz], [-hx.sum()/2,-hy.sum()/2,-hz.sum()/2])\n",
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"\n",
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"chibkg = 0.001\n",
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"chiblk = 0.1\n",
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"chi = np.ones(mesh.nC)*chibkg\n",
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"sph_ind = spheremodel(mesh, 0., 0., 0., 100)\n",
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"chi[sph_ind] = chiblk\n",
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"model = BaseMag.BaseMagModel(mesh)\n",
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"mu = (1.+chi)*mu_0\n",
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"\n",
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"data = BaseMag.BaseMagData()\n",
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"data.setBackgroundField(x=1., y=1., z=0.)\n",
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"xr = np.linspace(-300, 300, 41)\n",
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"yr = np.linspace(-300, 300, 41)\n",
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"X, Y = np.meshgrid(xr, yr)\n",
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"Z = np.ones((xr.size, yr.size))*150\n",
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"rxLoc = np.c_[Utils.mkvc(X), Utils.mkvc(Y), Utils.mkvc(Z)]\n",
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"data.rxLoc = rxLoc\n",
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"\n",
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"prob = MagneticsDiffSecondary(mesh, model)\n",
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"\n",
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"prob.pair(data)\n"
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],
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"language": "python",
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"metadata": {},
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"outputs": [],
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"prompt_number": 50
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"fields = prob.fields(chi)\n",
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"u = fields['u']\n",
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"B = fields['B']\n",
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"# mesh.plotSlice(B, 'F', view='vec', showIt=True)\n",
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"dpred = data.dpred(chi, fields)"
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],
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"language": "python",
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"metadata": {},
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"outputs": [],
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"prompt_number": 51
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## ?? they are different ?"
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]
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"MfMui = mesh.getFaceInnerProduct(mu).diagonal()\n",
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"MfMui_test = mesh.getFaceMass(mu).diagonal()\n",
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"print np.linalg.norm(MfMui - MfMui_test)"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"output_type": "stream",
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"stream": "stdout",
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"text": [
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"9.55511263546\n"
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]
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}
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],
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"prompt_number": 52
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"plot(MfMui/MfMui_test)"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 53,
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"text": [
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"[<matplotlib.lines.Line2D at 0x3363350>]"
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]
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},
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{
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"metadata": {},
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"output_type": "display_data",
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"png": 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55ZexYsUK9wA8fEREdM18te+csRQuX76MtWvXYtWqVdiyZcuMDxgdHY1PPvkEarXabXlZ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\n",
|
|
"text": [
|
|
"<matplotlib.figure.Figure at 0x1fa10d0>"
|
|
]
|
|
}
|
|
],
|
|
"prompt_number": 53
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"collapsed": false,
|
|
"input": [
|
|
"def MfmuIfun(mu):\n",
|
|
" \n",
|
|
"# MfMui = mesh.getFaceMass(1./mu)\n",
|
|
" \n",
|
|
" MfMui = mesh.getFaceInnerProduct(1./mu)*1/3\n",
|
|
" # There are scaling issue for Face inner product!! and bit slower than getFaceMass\n",
|
|
" \n",
|
|
" MfMuI = 1/MfMui.diagonal()\n",
|
|
"# dMfMuI = Utils.sdiag(MfMuI**2)*mesh.aveF2CC.T*Utils.sdiag(mesh.vol*1./mu**2)\n",
|
|
" dMfMuI = Utils.sdiag(MfMuI**2)*mesh.aveF2CC.T*Utils.sdiag(mesh.vol*1./mu**2)\n",
|
|
" \n",
|
|
" return MfMuI, dMfMuI"
|
|
],
|
|
"language": "python",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"prompt_number": 54
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"collapsed": false,
|
|
"input": [
|
|
"d_mu = 0.8*mu\n",
|
|
"# I am not sure why it does not give us second order accuracy\n",
|
|
"Tests.checkDerivative(MfmuIfun, mu, dx=d_mu, num=5, plotIt=False)"
|
|
],
|
|
"language": "python",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"output_type": "stream",
|
|
"stream": "stdout",
|
|
"text": [
|
|
"==================== checkDerivative ====================\n",
|
|
"iter\th\t\t|J0-Jt|\t\t|J0+h*dJ'*dx-Jt|\tOrder\n",
|
|
"---------------------------------------------------------\n",
|
|
"0\t1.00e-01\t4.299e-09\t\t1.152e-23\t\tnan"
|
|
]
|
|
},
|
|
{
|
|
"output_type": "stream",
|
|
"stream": "stdout",
|
|
"text": [
|
|
"\n",
|
|
"1\t1.00e-02\t4.299e-10\t\t7.723e-24\t\t0.174"
|
|
]
|
|
},
|
|
{
|
|
"output_type": "stream",
|
|
"stream": "stdout",
|
|
"text": [
|
|
"\n",
|
|
"2\t1.00e-03\t4.299e-11\t\t1.170e-23\t\t-0.180"
|
|
]
|
|
},
|
|
{
|
|
"output_type": "stream",
|
|
"stream": "stdout",
|
|
"text": [
|
|
"\n",
|
|
"3\t1.00e-04\t4.299e-12\t\t8.749e-24\t\t0.126"
|
|
]
|
|
},
|
|
{
|
|
"output_type": "stream",
|
|
"stream": "stdout",
|
|
"text": [
|
|
"\n",
|
|
"4\t1.00e-05\t4.299e-13\t\t1.107e-23\t\t-0.102"
|
|
]
|
|
},
|
|
{
|
|
"output_type": "stream",
|
|
"stream": "stdout",
|
|
"text": [
|
|
"\n",
|
|
"========================= PASS! =========================\n",
|
|
"Once upon a time, a happy little test passed.\n",
|
|
"\n"
|
|
]
|
|
},
|
|
{
|
|
"metadata": {},
|
|
"output_type": "pyout",
|
|
"prompt_number": 55,
|
|
"text": [
|
|
"True"
|
|
]
|
|
}
|
|
],
|
|
"prompt_number": 55
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"collapsed": false,
|
|
"input": [
|
|
"def derBbc(chi):\n",
|
|
" Bbc, const = CongruousMagBC(mesh, np.array([1., 1., 0.]), chi)\n",
|
|
" bc = Utils.sdiag(prob.mesh.vol)*prob.mesh.faceDiv*prob._Pout.T*Bbc \n",
|
|
" print const, np.linalg.norm(Bbc)\n",
|
|
" dBbc = lambda x: (Utils.sdiag(prob.mesh.vol)*(prob.mesh.faceDiv*prob._Pout.T*const*Bbc))*(np.inner(prob.mesh.vol, x)) \n",
|
|
" return bc, dBbc"
|
|
],
|
|
"language": "python",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"prompt_number": 56
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"collapsed": false,
|
|
"input": [
|
|
"a, b = derBbc(chi)\n",
|
|
"print np.linalg.norm(a), np.linalg.norm(b(chi))\n",
|
|
"print np.linalg.norm(chi)\n",
|
|
"print np.array([1., 1., 0.])\n",
|
|
"print mesh"
|
|
],
|
|
"language": "python",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"output_type": "stream",
|
|
"stream": "stdout",
|
|
"text": [
|
|
"7.65830184557e-07 0.0659506783728\n",
|
|
"55.718105908 55.6914561973\n",
|
|
"1.6089045963\n",
|
|
"[ 1. 1. 0.]\n",
|
|
" ---- 3-D TensorMesh ---- \n",
|
|
" x0: -488.58\n",
|
|
" y0: -488.58\n",
|
|
" z0: -476.08\n",
|
|
" nCx: 31\n",
|
|
" nCy: 31\n",
|
|
" nCz: 30\n",
|
|
" hx: 71.40, 54.93, 42.25, 32.50, 23*25.00, 32.50, 42.25, 54.93, 71.40\n",
|
|
" hy: 71.40, 54.93, 42.25, 32.50, 23*25.00, 32.50, 42.25, 54.93, 71.40\n",
|
|
" hz: 71.40, 54.93, 42.25, 32.50, 22*25.00, 32.50, 42.25, 54.93, 71.40\n"
|
|
]
|
|
}
|
|
],
|
|
"prompt_number": 57
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"collapsed": false,
|
|
"input": [
|
|
"d_chi = 0.8*chi\n",
|
|
"# I am not sure why it does not give us second order accuracy\n",
|
|
"Tests.checkDerivative(derBbc, chi, dx=d_chi, num=5, plotIt=False)"
|
|
],
|
|
"language": "python",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"output_type": "stream",
|
|
"stream": "stdout",
|
|
"text": [
|
|
"==================== checkDerivative ====================\n",
|
|
"iter\th\t\t|J0-Jt|\t\t|J0+h*dJ'*dx-Jt|\tOrder\n",
|
|
"---------------------------------------------------------\n",
|
|
"7.65830184557e-07"
|
|
]
|
|
},
|
|
{
|
|
"output_type": "stream",
|
|
"stream": "stdout",
|
|
"text": [
|
|
" 0.0659506783728\n",
|
|
"7.0907489096e-07"
|
|
]
|
|
},
|
|
{
|
|
"output_type": "stream",
|
|
"stream": "stdout",
|
|
"text": [
|
|
" 0.0712240073538\n",
|
|
"0\t1.00e-01\t4.455e+00\t\t1.705e-04\t\tnan\n",
|
|
"7.59749260143e-07"
|
|
]
|
|
},
|
|
{
|
|
"output_type": "stream",
|
|
"stream": "stdout",
|
|
"text": [
|
|
" 0.0664780294308\n",
|
|
"1\t1.00e-02\t4.455e-01\t\t1.705e-06\t\t2.000\n",
|
|
"7.65217717349e-07"
|
|
]
|
|
},
|
|
{
|
|
"output_type": "stream",
|
|
"stream": "stdout",
|
|
"text": [
|
|
" 0.0660034136602\n",
|
|
"2\t1.00e-03\t4.455e-02\t\t1.706e-08\t\t2.000\n",
|
|
"7.65768893742e-07"
|
|
]
|
|
},
|
|
{
|
|
"output_type": "stream",
|
|
"stream": "stdout",
|
|
"text": [
|
|
" 0.0659559519034\n",
|
|
"3\t1.00e-04\t4.455e-03\t\t1.749e-10\t\t1.989\n",
|
|
"7.65824055034e-07"
|
|
]
|
|
},
|
|
{
|
|
"output_type": "stream",
|
|
"stream": "stdout",
|
|
"text": [
|
|
" 0.0659512057259\n",
|
|
"4\t1.00e-05\t4.455e-04\t\t2.506e-12\t\t1.844\n",
|
|
"========================= PASS! =========================\n",
|
|
"The test be workin!\n",
|
|
"\n"
|
|
]
|
|
},
|
|
{
|
|
"metadata": {},
|
|
"output_type": "pyout",
|
|
"prompt_number": 58,
|
|
"text": [
|
|
"True"
|
|
]
|
|
}
|
|
],
|
|
"prompt_number": 58
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"collapsed": false,
|
|
"input": [],
|
|
"language": "python",
|
|
"metadata": {},
|
|
"outputs": []
|
|
}
|
|
],
|
|
"metadata": {}
|
|
}
|
|
]
|
|
} |