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@leouieda
Last active August 29, 2015 14:20
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Updated derivative calculations using Matteo's data (reflects PR 196 https://github.com/fatiando/fatiando/pull/196)
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{
"cells": [
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"%matplotlib inline\n",
"from fatiando.gravmag import transform\n",
"from fatiando import gridder\n",
"from fatiando.vis import mpl\n",
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"data = np.loadtxt('continued.txt')\n",
"X = np.loadtxt('X.txt')\n",
"Y = np.loadtxt('Y.txt')"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"shape = data.shape"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# convert data, X, and Y arrays to 1D\n",
"d = data.ravel()\n",
"# x, y are switched because x in Fatiando is North-South. \n",
"# So when plotting you pass contourf(y, x, ...)\n",
"y = X.ravel()\n",
"x = Y.ravel()\n",
"\n",
"# calculate derivatives using Fatiando a Terra and reshape output arrays back\n",
"# to 2D\n",
"xderiv = transform.derivx(x, y, d, data.shape)\n",
"yderiv = transform.derivy(x, y, d, data.shape)\n",
"zderiv = transform.derivz(x, y, d, data.shape)\n",
"tga = transform.tga(x, y, data, data.shape)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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],
"text/plain": [
"<matplotlib.figure.Figure at 0x7fa0cffb8550>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"mpl.figure(figsize=(15, 4))\n",
"ax = mpl.subplot(141)\n",
"mpl.axis('scaled')\n",
"mpl.title('dz')\n",
"mpl.pcolor(y, x, zderiv, shape, cmap='cubehelix')\n",
"ax.xaxis.set_ticks([])\n",
"ax.yaxis.set_ticks([])\n",
"ax = mpl.subplot(142)\n",
"mpl.axis('scaled')\n",
"mpl.title('dy')\n",
"mpl.pcolor(y, x, yderiv, shape, cmap='cubehelix')\n",
"ax.xaxis.set_ticks([])\n",
"ax.yaxis.set_ticks([])\n",
"ax = mpl.subplot(143)\n",
"mpl.axis('scaled')\n",
"mpl.title('dx')\n",
"mpl.pcolor(y, x, xderiv, shape, cmap='cubehelix')\n",
"ax.xaxis.set_ticks([])\n",
"ax.yaxis.set_ticks([])\n",
"ax = mpl.subplot(144)\n",
"mpl.axis('scaled')\n",
"mpl.title('Total gradient amplitude')\n",
"mpl.pcolor(y, x, tga, shape, cmap='cubehelix')\n",
"ax.xaxis.set_ticks([])\n",
"ax.yaxis.set_ticks([])\n",
"mpl.tight_layout()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 2",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.9"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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