{ "metadata": { "name": "" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "\n", "\n", "# Generate synthetic magnetic data\n", "\n", "This notebook generates synthetic total field magnetic anomaly data. We use the forward modeling capabilities of [Fatiando a Terra](http://fatiando.org) to create models of polygonal prisms and calculate their total field anomaly. The data can then be saved to a file and used in other applications." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "First, we must load (i.e., import) the required modules." ] }, { "cell_type": "code", "collapsed": false, "input": [ "import json\n", "import cPickle as pickle\n", "import numpy as np\n", "from IPython.display import Image\n", "from fatiando.mesher import PolygonalPrism\n", "from fatiando.gravmag import polyprism\n", "from fatiando import gridder, utils\n", "from fatiando.vis import myv, mpl\n", "import fatiando\n", "print(\"Using Fatiando a Terra version {0}\".format((fatiando.version)))" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "Using Fatiando a Terra version 0.2\n" ] } ], "prompt_number": 1 }, { "cell_type": "markdown", "metadata": {}, "source": [ "We will use function mpl.draw_polygons to interactively draw polygons on the x-y plane. These polygons will be used as the outline for the polygonal prisms. We'll draw 3 bodies in total: a dike, a sill, and an intrusive body (like a batholith).\n", "\n", "Note that we will calculate the data inside the area specified by area but the model is contained on the larger volume bounds. We do this to minimize the unrealistic effects of the edges of the dike." ] }, { "cell_type": "code", "collapsed": false, "input": [ "area = [5000, 25000, 5000, 25000]\n", "bounds = [0, 30000, 0, 30000, 0, 5000]" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 3 }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Vertical dike\n", "\n", "First, we'll draw a model of a vertical dike." ] }, { "cell_type": "code", "collapsed": false, "input": [ "mpl.figure()\n", "mpl.axis('scaled')\n", "mpl.square(area)\n", "dike_verts = mpl.draw_polygon(bounds[:4], mpl.gca(), xy2ne=True)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 53 }, { "cell_type": "code", "collapsed": false, "input": [ "dike_verts" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 4, "text": [ "[[78.12500000000136, 17968.750000000004],\n", " [15156.250000000002, 19843.750000000004],\n", " [29843.75, 20781.250000000004],\n", " [29843.75, 21015.625000000004],\n", " [15078.125000000002, 20156.250000000004],\n", " [156.25000000000136, 18281.250000000004]]" ] } ], "prompt_number": 4 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we use the polygon vertices drawn to create a polygonal prism model." ] }, { "cell_type": "code", "collapsed": false, "input": [ "dike = PolygonalPrism(dike_verts, 0, 5000, {'magnetization': 10})" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 5 }, { "cell_type": "code", "collapsed": false, "input": [ "myv.figure(size=(600, 400))\n", "myv.polyprisms([dike], linewidth=2)\n", "myv.axes(myv.outline(bounds), ranges=[b*0.001 for b in bounds], nlabels=3, fmt='%.1f')\n", "myv.wall_north(bounds)\n", "myv.wall_bottom(bounds)\n", "myv.savefig('tmp/model_dike.png')\n", "myv.show()\n", "Image(filename='tmp/model_dike.png')" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "png": 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WiPgdljqdjjBlVAEQhEk6evTo888/v3v37nA4PG3atHvuuWflypXbt2/fvn37xo0b16xZ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\nTkSuQmCC\n", "prompt_number": 15, "text": [ "" ] } ], "prompt_number": 15 }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Sill\n", "\n", "Now we can draw a structure corresponding to a sill." ] }, { "cell_type": "code", "collapsed": false, "input": [ "mpl.figure()\n", "mpl.axis('scaled')\n", "mpl.square(area)\n", "mpl.polygon(dike, xy2ne=True)\n", "sill_verts = mpl.draw_polygon(bounds[:4], mpl.gca(), xy2ne=True)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 79 }, { "cell_type": "code", "collapsed": false, "input": [ "sill_verts" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 6, "text": [ "[[10000.000000000002, 8828.125000000004],\n", " [10156.250000000002, 9062.500000000004],\n", " [11328.125000000002, 10703.125000000004],\n", " [11875.000000000002, 11796.875000000004],\n", " [11953.125000000002, 12890.625000000004],\n", " [11406.250000000002, 13593.750000000004],\n", " [10156.250000000002, 13984.375000000004],\n", " [9375.000000000002, 13984.375000000004],\n", " [9218.750000000002, 13984.375000000004],\n", " [8437.500000000002, 12812.500000000004],\n", " [7968.750000000002, 11796.875000000004],\n", " [7968.750000000002, 10078.125000000004],\n", " [7968.750000000002, 9765.625000000004],\n", " [8593.750000000002, 9218.750000000004]]" ] } ], "prompt_number": 6 }, { "cell_type": "code", "collapsed": false, "input": [ "sill = PolygonalPrism(sill_verts, 1000, 1500, {'magnetization': 10})" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 7 }, { "cell_type": "code", "collapsed": false, "input": [ "myv.figure(size=(600, 400))\n", "myv.polyprisms([dike, sill], linewidth=2)\n", "myv.axes(myv.outline(bounds), ranges=[b*0.001 for b in bounds], nlabels=3, fmt='%.1f')\n", "myv.wall_north(bounds)\n", "myv.wall_bottom(bounds)\n", "myv.savefig('tmp/model_sill.png')\n", "myv.show()\n", "Image(filename='tmp/model_sill.png')" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "png": 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3Bs7IyHA4HH6KSdgsMapNNIcRYYjWrl378MMPJycnu1yuuXPnPvnkk+Xl5e++++7BgwfP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\n/wek4sejWwxNrgAAAABJRU5ErkJggg==\n", "prompt_number": 24, "text": [ "" ] } ], "prompt_number": 24 }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Batholith\n", "\n", "Finally, we draw a model of a batholith-like structure." ] }, { "cell_type": "code", "collapsed": false, "input": [ "mpl.figure()\n", "mpl.axis('scaled')\n", "mpl.square(area)\n", "mpl.polygon(dike, xy2ne=True)\n", "mpl.polygon(sill, xy2ne=True)\n", "batholith_verts = mpl.draw_polygon(bounds[:4], mpl.gca(), xy2ne=True)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 61 }, { "cell_type": "code", "collapsed": false, "input": [ "batholith_verts" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 8, "text": [ "[[18046.875, 9921.875000000004],\n", " [19062.5, 10234.375000000004],\n", " [19765.625, 11093.750000000004],\n", " [20078.125, 12500.000000000004],\n", " [19843.75, 13515.625000000004],\n", " [18281.25, 14140.625000000004],\n", " [16640.625, 14140.625000000004],\n", " [15781.250000000002, 13671.875000000004],\n", " [15703.125000000002, 11718.750000000004],\n", " [15859.375000000002, 10390.625000000004],\n", " [16250.000000000002, 9843.750000000004]]" ] } ], "prompt_number": 8 }, { "cell_type": "code", "collapsed": false, "input": [ "batholith = PolygonalPrism(batholith_verts, 500, 4000, {'magnetization': 2})" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 9 }, { "cell_type": "code", "collapsed": false, "input": [ "myv.figure(size=(600, 400))\n", "myv.polyprisms([dike, sill, batholith], linewidth=2)\n", "myv.axes(myv.outline(bounds), ranges=[b*0.001 for b in bounds], nlabels=3, fmt='%.1f')\n", "myv.wall_north(bounds)\n", "myv.wall_bottom(bounds)\n", "myv.savefig('tmp/model_batholith.png')\n", "myv.show()\n", "Image(filename='tmp/model_batholith.png')" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "png": 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VFTU1NXa73fstZs6cWV9fz8otiReHEi6BCUk/TdHQ/5V8XMgiUNRKMV5Dq930PBHxtC/e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\nDtl/hxSHwW80ioOTwAOCEBL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"prompt_number": 27, "text": [ "" ] } ], "prompt_number": 27 }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can group the 3 structures into a model for convenience." ] }, { "cell_type": "code", "collapsed": false, "input": [ "model = [dike, sill, batholith]" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 10 }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Forward modeling\n", "\n", "Now that we have a polygonal prism model, we can calculate the total field magnetic anomaly caused by the model using function polyprism.tf. Before doing that, we must specify the points where the anomaly will be calculated and the inclination and declination of the local magnetic field." ] }, { "cell_type": "code", "collapsed": false, "input": [ "shape = (100, 100)\n", "x, y, z = gridder.regular(area, shape, z=-300)\n", "inc, dec = -15, 30" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 11 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we forward model the anomaly and contaminate it with pseudo-random Gaussian noise with zero mean and 5 nT standard deviation. " ] }, { "cell_type": "code", "collapsed": false, "input": [ "tf = utils.contaminate(polyprism.tf(x, y, z, model, inc, dec), 5)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 12 }, { "cell_type": "code", "collapsed": false, "input": [ "mpl.figure()\n", "mpl.axis('scaled')\n", "for b in model:\n", " mpl.polygon(b, xy2ne=True)\n", "mpl.contourf(y, x, tf, shape, 60, cmap=mpl.cm.RdBu_r)\n", "cb = mpl.colorbar().set_label('nT')\n", "mpl.m2km()\n", "mpl.xlabel('East (km)')\n", "mpl.ylabel('North (km)')\n", "mpl.savefig('tmp/synthetic_data.png')\n", "mpl.show()\n", "Image(filename='tmp/synthetic_data.png')" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "png": 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6W13PjWBV1PLjPMxwW4T4EXplfb/eiA5W8quRsFCPV//fbTHiRpUfvWpZgEHJ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VEuTqsLF44DoSI+AOC1p7+L+nQVx1/wN9LuhxWe+LCOXLaWX1nzYgy9BxHOjUrrAoF1DG9rHHfr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\n4Nxzz0V3d7dhu+HhYdx9991YuHAhWltbUVNTg9122w333Xcf0mnjxYj29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iiUGLmp/bAj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diB2shIg6YIkmoNsNIJTpgJUe2ggAqGhs5r5OOjq7MP/QfW2PQ8Or//By7odXjLf0K83Epby8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\nsWtkgOLiYp+TUwAYMmQIhg0bhv3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"prompt_number": 13, "text": [ "" ] } ], "prompt_number": 13 }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Output\n", "\n", "Now we can save the data and model to output files. \n", "\n", "Lets start with the data. We can use function [numpy.savetxt](http://docs.scipy.org/doc/numpy/reference/generated/numpy.savetxt.html) to output an xyz file." ] }, { "cell_type": "code", "collapsed": false, "input": [ "np.savetxt('data/synthetic_data.txt', np.transpose([x, y, z, tf]))" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 34 }, { "cell_type": "raw", "metadata": {}, "source": [ "This is what it looks like." ] }, { "cell_type": "code", "collapsed": false, "input": [ "# Can run bash commands inside the IPython notebook\n", "!head data/synthetic_data.txt" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "5.000000000000000000e+03 5.000000000000000000e+03 -3.000000000000000000e+02 2.472022980608290510e+01\r\n", "5.202020202020202305e+03 5.000000000000000000e+03 -3.000000000000000000e+02 2.136612504694526748e+01\r\n", "5.404040404040404610e+03 5.000000000000000000e+03 -3.000000000000000000e+02 2.919065176934347150e+01\r\n", "5.606060606060606915e+03 5.000000000000000000e+03 -3.000000000000000000e+02 2.367618454109635806e+01\r\n", "5.808080808080809220e+03 5.000000000000000000e+03 -3.000000000000000000e+02 1.911091399975841654e+01\r\n", "6.010101010101011525e+03 5.000000000000000000e+03 -3.000000000000000000e+02 2.005544989791811972e+01\r\n", "6.212121212121213830e+03 5.000000000000000000e+03 -3.000000000000000000e+02 8.401696415669032802e+00\r\n", "6.414141414141416135e+03 5.000000000000000000e+03 -3.000000000000000000e+02 2.473401968099981829e+01\r\n", "6.616161616161618440e+03 5.000000000000000000e+03 -3.000000000000000000e+02 1.283030388866875526e+01\r\n", "6.818181818181820745e+03 5.000000000000000000e+03 -3.000000000000000000e+02 1.549856793636272734e+01\r\n" ] } ], "prompt_number": 14 }, { "cell_type": "markdown", "metadata": {}, "source": [ "We also need to save other information about our data (i.e., metadata), like the area, model bounds, inclination, declination, and the shape of the grid. For this, we'll use a file format called [json](http://en.wikipedia.org/wiki/JSON)." ] }, { "cell_type": "code", "collapsed": false, "input": [ "with open('data/metadata.json', 'w') as f:\n", " json.dump(dict(area=area, bounds=bounds, inc=inc, dec=dec, shape=shape), f)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 87 }, { "cell_type": "markdown", "metadata": {}, "source": [ "A json file looks like this:" ] }, { "cell_type": "code", "collapsed": false, "input": [ "!cat data/metadata.json" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "{\"shape\": [100, 100], \"dec\": 30, \"inc\": -15, \"bounds\": [0, 30000, 0, 30000, 0, 5000], \"area\": [5000, 25000, 5000, 25000]}" ] } ], "prompt_number": 15 }, { "cell_type": "markdown", "metadata": {}, "source": [ "For the polygonal prism objects (PolygonalPrisms), we need to use a different format. The Python language provides the great [pickle](http://docs.python.org/2/library/pickle.html) module for object serialization. This allows us to load the same variable in another Python file from the .pickle file." ] }, { "cell_type": "code", "collapsed": false, "input": [ "with open('data/model.pickle', 'w') as f:\n", " pickle.dump(model, f)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 38 }, { "cell_type": "markdown", "metadata": {}, "source": [ "We'll also save the vertices that we used to create the model for later reference. We can use the json format for this." ] }, { "cell_type": "code", "collapsed": false, "input": [ "with open('data/dike.json', 'w') as f:\n", " json.dump(dike_verts.tolist(), f)\n", "with open('data/sill.json', 'w') as f:\n", " json.dump(sill_verts.tolist(), f)\n", "with open('data/batholith.json', 'w') as f:\n", " json.dump(batholith_verts.tolist(), f)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 88 } ], "metadata": {} } ] }