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@thesamovar
Created August 27, 2016 21:33
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true,
"level": 7
},
"outputs": [],
"source": [
"%matplotlib inline\n",
"from brian2 import *\n",
"from matplotlib.collections import LineCollection"
]
},
{
"cell_type": "code",
"execution_count": 62,
"metadata": {
"collapsed": true,
"level": 7
},
"outputs": [],
"source": [
"def plot_swc(fname, showtype=(True,)*4):\n",
" # Load SWC file directly (Morphology is too slow)\n",
" # index, type, x, y, z, radius, parent\n",
" i, t, x, y, z, r, p = loadtxt(fname).T\n",
" i = array(i, dtype=int)-1 # indices start at 1\n",
" t = array(t, dtype=int)-1 # types start at 1\n",
" p = array(p, dtype=int)\n",
" p[p>0] -= 1 # parent indices too, but -1 is special (root node)\n",
" # Create and plot a LineCollection\n",
" segs = [((x[i], y[i]), (x[p[i]], y[p[i]])) for i in xrange(len(t)) if p[i]>=0 and showtype[t[i]]]\n",
" c = LineCollection(segs, linewidths=1, colors='k', linestyle='solid')\n",
" gca().add_collection(c)\n",
" gca().autoscale_view(True,True,True) \n",
" xticks([])\n",
" yticks([])\n",
" gca().set_frame_on(False)\n",
" gca().set_aspect('equal', 'datalim')\n",
" savefig(fname.replace('.swc', '.pdf'))"
]
},
{
"cell_type": "code",
"execution_count": 63,
"metadata": {
"collapsed": false,
"level": 7
},
"outputs": [
{
"data": {
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6z2JJNFY+/xn9gW7AXU24dxCURYhu0Bj2BvZH9a37ogqEF81sSzNby8z6pp3/crgD5YVX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\nSIhuEARBDfk/Tt9nLcKNUL4AAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xa58afd0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_swc('neuromorpho/c11563.CNG.swc', showtype=[1,0,1,1])"
]
},
{
"cell_type": "code",
"execution_count": 64,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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"text/plain": [
"<matplotlib.figure.Figure at 0x9f83278>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_swc('neuromorpho/04a_pyramidal4aACC.CNG.swc')"
]
},
{
"cell_type": "code",
"execution_count": 65,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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bAHeR2Qj7R8QH9Y3QzNrFsN1IkzQ3sCywBrAb8BJZxWsE8Dey5c3T9Y3QzNrR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\nbXKzAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xcdacd30>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_swc('neuromorpho/05b_pyramidal9aACC.CNG.swc')"
]
},
{
"cell_type": "code",
"execution_count": 67,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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tjpbyuyKO9nJ3fy/POS3Q8nsQylpbGbgBFQ9/IcYajLzomUjq9TviZB909z+z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\nTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xbf93c18>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_swc('neuromorpho/c31164.CNG.swc', showtype=[1,0,1,1])"
]
},
{
"cell_type": "code",
"execution_count": 68,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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"text/plain": [
"<matplotlib.figure.Figure at 0xa583828>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot_swc('neuromorpho/A9-4.CNG.swc')"
]
}
],
"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": "2.7.12"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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