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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import math\n",
"\n",
"import pandas as pd\n",
"import numpy as np\n",
"\n",
"%matplotlib inline\n",
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"r004 = {4 : {\"ca_ijk\":0.00042104721069336,\"na_ijk\":0.0004429817199707,\"cv_ijk\":0.00049710273742676,\"nv_ijk\":0.00060391426086426,\"ca_ikj\":0.00030279159545898,\"na_ikj\":0.00032591819763184,\"cv_ikj\":0.00038003921508789,\"nv_ikj\":0.00046491622924805}}\n",
"r008 = {8 : {\"ca_ijk\":0.002924919128418,\"na_ijk\":0.003281831741333,\"cv_ijk\":0.0034310817718506,\"nv_ijk\":0.0043010711669922,\"ca_ikj\":0.0017859935760498,\"na_ikj\":0.0020260810852051,\"cv_ikj\":0.0023138523101807,\"nv_ikj\":0.0028958320617676}}\n",
"r016 = {16 : {\"ca_ijk\":0.019437074661255,\"na_ijk\":0.020691156387329,\"cv_ijk\":0.020630836486816,\"nv_ijk\":0.025195837020874,\"ca_ikj\":0.0088889598846436,\"na_ikj\":0.010462045669556,\"cv_ikj\":0.011255979537964,\"nv_ikj\":0.014892101287842}}\n",
"r032 = {32 : {\"ca_ijk\":0.094998121261597,\"na_ijk\":0.1055748462677,\"cv_ijk\":0.11357617378235,\"nv_ijk\":0.15099906921387,\"ca_ikj\":0.052932024002075,\"na_ikj\":0.064934968948364,\"cv_ikj\":0.0711350440979,\"nv_ikj\":0.10097599029541}}\n",
"r064 = {64 : {\"ca_ijk\":0.72782516479492,\"na_ijk\":0.83726596832275,\"cv_ijk\":0.9531569480896,\"nv_ijk\":1.1677219867706,\"ca_ikj\":0.39643001556396,\"na_ikj\":0.49447298049927,\"cv_ikj\":0.53884315490723,\"nv_ikj\":0.7768931388855}}\n",
"r128 = {128 : {\"ca_ijk\":2.8404879570007,\"na_ijk\":3.2943258285522,\"cv_ijk\":3.5353372097015,\"nv_ijk\":4.66787981987,\"ca_ikj\":1.5506911277771,\"na_ikj\":1.9599390029907,\"cv_ikj\":2.1567468643188,\"nv_ikj\":3.1205151081085}}\n",
"r256 = {256 : {\"ca_ijk\":22.941949129105,\"na_ijk\":26.903174877167,\"cv_ijk\":28.000234127045,\"nv_ijk\":38.06840801239,\"ca_ikj\":12.362766981125,\"na_ikj\":15.758536100388,\"cv_ikj\":17.036547899246,\"nv_ikj\":24.780100107193}}\n",
"r512 = {512 : {\"ca_ijk\":281.45276784897,\"na_ijk\":298.90023684502,\"cv_ijk\":236.78369307518,\"nv_ijk\":324.35555291176,\"ca_ikj\":99.469950199127,\"na_ikj\":126.31004500389,\"cv_ikj\":135.40308403969,\"nv_ikj\":198.58974289894}}\n",
"\n",
"r = dict(\n",
" list(r004.items()) +\n",
" list(r008.items()) +\n",
" list(r016.items()) +\n",
" list(r032.items()) +\n",
" list(r064.items()) +\n",
" list(r128.items()) +\n",
" list(r256.items()) +\n",
" list(r512.items())\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>ca_ijk</th>\n",
" <th>ca_ikj</th>\n",
" <th>cv_ijk</th>\n",
" <th>cv_ikj</th>\n",
" <th>na_ijk</th>\n",
" <th>na_ikj</th>\n",
" <th>nv_ijk</th>\n",
" <th>nv_ikj</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>0.000421</td>\n",
" <td>0.000303</td>\n",
" <td>0.000497</td>\n",
" <td>0.000380</td>\n",
" <td>0.000443</td>\n",
" <td>0.000326</td>\n",
" <td>0.000604</td>\n",
" <td>0.000465</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>0.002925</td>\n",
" <td>0.001786</td>\n",
" <td>0.003431</td>\n",
" <td>0.002314</td>\n",
" <td>0.003282</td>\n",
" <td>0.002026</td>\n",
" <td>0.004301</td>\n",
" <td>0.002896</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>0.019437</td>\n",
" <td>0.008889</td>\n",
" <td>0.020631</td>\n",
" <td>0.011256</td>\n",
" <td>0.020691</td>\n",
" <td>0.010462</td>\n",
" <td>0.025196</td>\n",
" <td>0.014892</td>\n",
" </tr>\n",
" <tr>\n",
" <th>32</th>\n",
" <td>0.094998</td>\n",
" <td>0.052932</td>\n",
" <td>0.113576</td>\n",
" <td>0.071135</td>\n",
" <td>0.105575</td>\n",
" <td>0.064935</td>\n",
" <td>0.150999</td>\n",
" <td>0.100976</td>\n",
" </tr>\n",
" <tr>\n",
" <th>64</th>\n",
" <td>0.727825</td>\n",
" <td>0.396430</td>\n",
" <td>0.953157</td>\n",
" <td>0.538843</td>\n",
" <td>0.837266</td>\n",
" <td>0.494473</td>\n",
" <td>1.167722</td>\n",
" <td>0.776893</td>\n",
" </tr>\n",
" <tr>\n",
" <th>128</th>\n",
" <td>5.680976</td>\n",
" <td>3.101382</td>\n",
" <td>7.070674</td>\n",
" <td>4.313494</td>\n",
" <td>6.588652</td>\n",
" <td>3.919878</td>\n",
" <td>9.335760</td>\n",
" <td>6.241030</td>\n",
" </tr>\n",
" <tr>\n",
" <th>256</th>\n",
" <td>45.883898</td>\n",
" <td>24.725534</td>\n",
" <td>56.000468</td>\n",
" <td>34.073096</td>\n",
" <td>53.806350</td>\n",
" <td>31.517072</td>\n",
" <td>76.136816</td>\n",
" <td>49.560200</td>\n",
" </tr>\n",
" <tr>\n",
" <th>512</th>\n",
" <td>562.905536</td>\n",
" <td>198.939900</td>\n",
" <td>473.567386</td>\n",
" <td>270.806168</td>\n",
" <td>597.800474</td>\n",
" <td>252.620090</td>\n",
" <td>648.711106</td>\n",
" <td>397.179486</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" ca_ijk ca_ikj cv_ijk cv_ikj na_ijk na_ikj \\\n",
"4 0.000421 0.000303 0.000497 0.000380 0.000443 0.000326 \n",
"8 0.002925 0.001786 0.003431 0.002314 0.003282 0.002026 \n",
"16 0.019437 0.008889 0.020631 0.011256 0.020691 0.010462 \n",
"32 0.094998 0.052932 0.113576 0.071135 0.105575 0.064935 \n",
"64 0.727825 0.396430 0.953157 0.538843 0.837266 0.494473 \n",
"128 5.680976 3.101382 7.070674 4.313494 6.588652 3.919878 \n",
"256 45.883898 24.725534 56.000468 34.073096 53.806350 31.517072 \n",
"512 562.905536 198.939900 473.567386 270.806168 597.800474 252.620090 \n",
"\n",
" nv_ijk nv_ikj \n",
"4 0.000604 0.000465 \n",
"8 0.004301 0.002896 \n",
"16 0.025196 0.014892 \n",
"32 0.150999 0.100976 \n",
"64 1.167722 0.776893 \n",
"128 9.335760 6.241030 \n",
"256 76.136816 49.560200 \n",
"512 648.711106 397.179486 "
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = pd.DataFrame(r).transpose()\n",
"\n",
"# While generating the data, we used a multiplier of 40 for the range 4 ... 64,\n",
"# and 20 for the range 128 ... 512.\n",
"df.loc[128] *= 2\n",
"df.loc[256] *= 2\n",
"df.loc[512] *= 2\n",
"\n",
"df.loc[:]"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>ca_ijk</th>\n",
" <th>ca_ikj</th>\n",
" <th>cv_ijk</th>\n",
" <th>cv_ikj</th>\n",
" <th>na_ijk</th>\n",
" <th>na_ikj</th>\n",
" <th>nv_ijk</th>\n",
" <th>nv_ikj</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>0.074951</td>\n",
" <td>0.067150</td>\n",
" <td>0.079216</td>\n",
" <td>0.072434</td>\n",
" <td>0.076230</td>\n",
" <td>0.068818</td>\n",
" <td>0.084526</td>\n",
" <td>0.077468</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>0.143012</td>\n",
" <td>0.121328</td>\n",
" <td>0.150826</td>\n",
" <td>0.132265</td>\n",
" <td>0.148607</td>\n",
" <td>0.126537</td>\n",
" <td>0.162627</td>\n",
" <td>0.142536</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>0.268871</td>\n",
" <td>0.207149</td>\n",
" <td>0.274266</td>\n",
" <td>0.224110</td>\n",
" <td>0.274533</td>\n",
" <td>0.218712</td>\n",
" <td>0.293163</td>\n",
" <td>0.246028</td>\n",
" </tr>\n",
" <tr>\n",
" <th>32</th>\n",
" <td>0.456287</td>\n",
" <td>0.375468</td>\n",
" <td>0.484279</td>\n",
" <td>0.414344</td>\n",
" <td>0.472629</td>\n",
" <td>0.401938</td>\n",
" <td>0.532506</td>\n",
" <td>0.465664</td>\n",
" </tr>\n",
" <tr>\n",
" <th>64</th>\n",
" <td>0.899516</td>\n",
" <td>0.734608</td>\n",
" <td>0.984135</td>\n",
" <td>0.813743</td>\n",
" <td>0.942514</td>\n",
" <td>0.790765</td>\n",
" <td>1.053044</td>\n",
" <td>0.919293</td>\n",
" </tr>\n",
" <tr>\n",
" <th>128</th>\n",
" <td>1.784326</td>\n",
" <td>1.458316</td>\n",
" <td>1.919348</td>\n",
" <td>1.627833</td>\n",
" <td>1.874702</td>\n",
" <td>1.576731</td>\n",
" <td>2.105636</td>\n",
" <td>1.841134</td>\n",
" </tr>\n",
" <tr>\n",
" <th>256</th>\n",
" <td>3.580031</td>\n",
" <td>2.913278</td>\n",
" <td>3.825873</td>\n",
" <td>3.241932</td>\n",
" <td>3.775240</td>\n",
" <td>3.158750</td>\n",
" <td>4.238364</td>\n",
" <td>3.673198</td>\n",
" </tr>\n",
" <tr>\n",
" <th>512</th>\n",
" <td>8.256801</td>\n",
" <td>5.837685</td>\n",
" <td>7.794602</td>\n",
" <td>6.469730</td>\n",
" <td>8.424008</td>\n",
" <td>6.321536</td>\n",
" <td>8.656662</td>\n",
" <td>7.350704</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" ca_ijk ca_ikj cv_ijk cv_ikj na_ijk na_ikj nv_ijk \\\n",
"4 0.074951 0.067150 0.079216 0.072434 0.076230 0.068818 0.084526 \n",
"8 0.143012 0.121328 0.150826 0.132265 0.148607 0.126537 0.162627 \n",
"16 0.268871 0.207149 0.274266 0.224110 0.274533 0.218712 0.293163 \n",
"32 0.456287 0.375468 0.484279 0.414344 0.472629 0.401938 0.532506 \n",
"64 0.899516 0.734608 0.984135 0.813743 0.942514 0.790765 1.053044 \n",
"128 1.784326 1.458316 1.919348 1.627833 1.874702 1.576731 2.105636 \n",
"256 3.580031 2.913278 3.825873 3.241932 3.775240 3.158750 4.238364 \n",
"512 8.256801 5.837685 7.794602 6.469730 8.424008 6.321536 8.656662 \n",
"\n",
" nv_ikj \n",
"4 0.077468 \n",
"8 0.142536 \n",
"16 0.246028 \n",
"32 0.465664 \n",
"64 0.919293 \n",
"128 1.841134 \n",
"256 3.673198 \n",
"512 7.350704 "
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# I apply a cubic root to see if the behavior is as expected (cubic time complexity)\n",
"df_cr = df.apply(lambda R: list(map(lambda x: x**(1./3), R)))\n",
"df_cr"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7fd032eb6e48>"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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90t6OI23tWJm1vePi4hy+8FJsbCx9+/bgzp3brF4dQZ48eWyav7ltXbBgXrMm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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fd032fae128>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df.plot(style = ['k-', 'g-', 'k--', 'g--', 'k-.', 'g-.', 'k:', 'g:'], linewidth=0.75)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7fd032d760b8>"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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VGNVGT89lbN26iV69+vL777uYNm022bJlp0mTH/D2PhGnrLf3cXLkyEnFipWM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\n1L8APZ62LixOaWsAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7fd032e63278>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df_cr.plot(style = ['k-', 'g-', 'k--', 'g--', 'k-.', 'g-.', 'k:', 'g:'], linewidth=0.75)"
]
}
],
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "Python [conda root]",
"language": "python",
"name": "conda-root-py"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.5.2"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
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