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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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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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"source": [
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"%pylab inline\n",
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"from network.network import (is_valid_network,\n",
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" get_number_of_activated_antenna,\n",
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" can_antenna_be_turned_on,\n",
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" pp_network,\n",
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" turn_off_antenna,\n",
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" turn_on_antenna)\n",
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"from numpy import mean\n",
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"from random import Random\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"random = Random(666)\n",
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"\n",
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"def create_new_network(network, box_size):\n",
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" number_of_square = box_size * box_size\n",
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" for antenna in range(number_of_square):\n",
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" if can_antenna_be_turned_on(antenna, network, box_size) and random.choice([True, False]):\n",
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" network = turn_on_antenna(antenna, network)\n",
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" else:\n",
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" network = turn_off_antenna(antenna, network)\n",
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" return network\n",
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"\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"box_size = 8\n",
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"n = 15000\n",
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"\n",
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"valid_networks = [0]\n",
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"\n",
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"for random_antenna in range(n):\n",
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" network = valid_networks[-1]\n",
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" new_network = create_new_network(network, box_size)\n",
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" valid_networks.append(new_network)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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truncated
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"text/plain": [
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"<matplotlib.figure.Figure at 0x7f6ffacf3f60>"
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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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}
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],
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"source": [
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"hist(list(map(get_number_of_activated_antenna, valid_networks)), bins=100)\n",
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"None"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"15.072261849210053"
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]
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},
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"execution_count": 14,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"mean(list(map(get_number_of_activated_antenna, valid_networks)))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"□-■-□-□-■\n",
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"□-□-■-□-□\n",
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"□-□-□-□-□\n",
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"□-■-□-■-□\n",
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"■-□-□-□-■\n",
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"\n",
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"□-□-□-□-■\n",
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"□-□-□-■-□\n",
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"■-□-■-□-■\n",
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"\n",
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"□-□-■-□-□\n",
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"□-■-□-□-□\n",
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"\n",
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"□-□-□-□-□\n",
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"□-□-□-□-□\n",
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"■-□-■-□-■\n",
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"□-□-□-■-□\n",
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"\n",
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"\n",
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"\n",
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"□-□-□-□-■\n",
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"□-□-□-□-□\n",
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"\n",
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"□-□-□-□-□\n",
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"\n"
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]
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}
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],
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"source": [
|
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"for network in valid_networks[-10:]:\n",
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" print(pp_network(network, box_size))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"ename": "ValueError",
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"evalue": "Cannot take a larger sample than population when 'replace=False'",
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"output_type": "error",
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"traceback": [
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"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[1;31mValueError\u001b[0m Traceback (most recent call last)",
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"\u001b[1;32m<ipython-input-14-e2f587eeb987>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mrandom\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mchoice\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m3\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m4\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m111\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mreplace\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
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"\u001b[1;32mmtrand.pyx\u001b[0m in \u001b[0;36mmtrand.RandomState.choice (numpy/random/mtrand/mtrand.c:11010)\u001b[1;34m()\u001b[0m\n",
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"\u001b[1;31mValueError\u001b[0m: Cannot take a larger sample than population when 'replace=False'"
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]
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}
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||||
],
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||||
"source": [
|
||||
"random.choice([1,2,3,4], 111, replace=False)"
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||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"collapsed": true
|
||||
},
|
||||
"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": "3.4.3+"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 0
|
||||
}
|
||||
Reference in new issue
Block a user