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analysis in python done
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{
"cells": [
{
"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"from pandas import DataFrame, Series\n",
"import matplotlib.pyplot as plt\n",
"plt.rcParams[\"figure.figsize\"] = (30,5)"
]
},
{
"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
"outputs": [
{
"data": {
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"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>TEST</th>\n",
" <th>MAP</th>\n",
" <th>50000</th>\n",
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" <tr>\n",
" <th>0</th>\n",
" <td>int_insert</td>\n",
results update
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" <td>\"std::map&lt;int&gt;\"</td>\n",
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" <td>73</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>int_succ_lookup</td>\n",
results update
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" <td>\"std::map&lt;int&gt;\"</td>\n",
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" <td>17</td>\n",
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" <td>82</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>int_nosucc_lookup</td>\n",
results update
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" <td>\"std::map&lt;int&gt;\"</td>\n",
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" <td>165</td>\n",
" <td>262</td>\n",
" <td>388</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>int_delete</td>\n",
results update
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" <td>\"std::map&lt;int&gt;\"</td>\n",
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" <td>43</td>\n",
" <td>46</td>\n",
" <td>59</td>\n",
" <td>56</td>\n",
" <td>59</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>int_insert</td>\n",
results update
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" <td>\"std::map&lt;int&gt;\"</td>\n",
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" <td>52</td>\n",
" <td>51</td>\n",
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" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 33 columns</p>\n",
"</div>"
],
"text/plain": [
" TEST MAP 50000 100000 150000 200000 250000 \\\n",
results update
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"0 int_insert \"std::map<int>\" 73 51 52 55 57 \n",
"1 int_succ_lookup \"std::map<int>\" 17 17 17 17 18 \n",
"2 int_nosucc_lookup \"std::map<int>\" 165 262 388 437 601 \n",
"3 int_delete \"std::map<int>\" 43 46 59 56 59 \n",
"4 int_insert \"std::map<int>\" 52 51 52 55 57 \n",
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"\n",
" 300000 350000 400000 ... 9000000 10000000 15000000 20000000 \\\n",
"0 60 64 75 ... 242 270 250 252 \n",
"1 20 20 25 ... 70 73 73 72 \n",
"2 64 779 77 ... 246 279 256 251 \n",
"3 56 77 62 ... 127 130 136 133 \n",
"4 57 64 71 ... 242 254 253 253 \n",
"\n",
" 25000000 30000000 35000000 40000000 45000000 50000000 \n",
"0 253 298 293 307 313 322 \n",
"1 73 75 77 79 84 82 \n",
"2 252 278 283 282 298 289 \n",
"3 134 149 155 165 170 165 \n",
"4 250 274 284 282 291 287 \n",
"\n",
"[5 rows x 33 columns]"
]
},
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"execution_count": 4,
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"metadata": {},
"output_type": "execute_result"
}
],
"source": [
results update
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"data = pd.read_csv(\"results.csv\")\n",
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"data.head()"
]
},
{
"cell_type": "code",
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"execution_count": 5,
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"metadata": {
"scrolled": true
},
"outputs": [
{
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" </tr>\n",
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" <th>TEST</th>\n",
" <th>MAP</th>\n",
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results update
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" <th rowspan=\"6\" valign=\"top\">int_delete</th>\n",
" <th>\"robin_hood::unordered_flat&lt;int&gt;\"</th>\n",
analysis in python done
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" <td>9.066667</td>\n",
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" <td>24.233333</td>\n",
" <td>32.900000</td>\n",
" <td>48.266667</td>\n",
" </tr>\n",
" <tr>\n",
results update
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" <th>\"robin_hood::unordered_node&lt;int&gt;\"</th>\n",
analysis in python done
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" <td>10.700000</td>\n",
" <td>11.200000</td>\n",
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" <td>11.100000</td>\n",
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" <td>23.100000</td>\n",
" <td>26.166667</td>\n",
" <td>31.200000</td>\n",
" <td>41.900000</td>\n",
" <td>61.500000</td>\n",
" </tr>\n",
" <tr>\n",
results update
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" <th>\"robinhoodflat\"</th>\n",
" <td>34.000000</td>\n",
" <td>34.500000</td>\n",
" <td>47.250000</td>\n",
" <td>35.000000</td>\n",
" <td>40.750000</td>\n",
" <td>47.500000</td>\n",
" <td>59.750000</td>\n",
" <td>82.250000</td>\n",
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" <td>49.000000</td>\n",
" <td>...</td>\n",
" <td>55.250000</td>\n",
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" <td>57.750000</td>\n",
" <td>63.250000</td>\n",
" <td>122.750000</td>\n",
" <td>54.500000</td>\n",
" <td>67.500000</td>\n",
" <td>67.000000</td>\n",
" <td>98.750000</td>\n",
" <td>119.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>\"robinhoodnode</th>\n",
" <td>43.500000</td>\n",
" <td>41.000000</td>\n",
" <td>54.250000</td>\n",
" <td>43.500000</td>\n",
" <td>48.000000</td>\n",
" <td>56.000000</td>\n",
" <td>67.750000</td>\n",
" <td>98.500000</td>\n",
" <td>52.000000</td>\n",
" <td>59.000000</td>\n",
" <td>...</td>\n",
" <td>75.250000</td>\n",
" <td>90.750000</td>\n",
" <td>73.250000</td>\n",
" <td>87.000000</td>\n",
" <td>154.250000</td>\n",
" <td>75.750000</td>\n",
" <td>83.250000</td>\n",
" <td>95.000000</td>\n",
" <td>118.750000</td>\n",
" <td>152.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>\"std::map&lt;int&gt;\"</th>\n",
analysis in python done
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" <td>44.233333</td>\n",
" <td>47.766667</td>\n",
" <td>50.766667</td>\n",
" <td>54.200000</td>\n",
" <td>58.533333</td>\n",
" <td>55.000000</td>\n",
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" <td>139.566667</td>\n",
" <td>154.800000</td>\n",
" <td>164.200000</td>\n",
" <td>161.700000</td>\n",
" <td>166.400000</td>\n",
" <td>172.333333</td>\n",
" </tr>\n",
" <tr>\n",
results update
2020-03-19 22:11:00 +00:00
" <th>\"std::unordered_map\"</th>\n",
" <td>141.500000</td>\n",
" <td>136.250000</td>\n",
" <td>143.250000</td>\n",
" <td>147.000000</td>\n",
" <td>148.500000</td>\n",
" <td>164.750000</td>\n",
" <td>176.000000</td>\n",
" <td>178.500000</td>\n",
" <td>188.000000</td>\n",
" <td>312.500000</td>\n",
" <td>...</td>\n",
" <td>327.500000</td>\n",
" <td>336.750000</td>\n",
" <td>298.750000</td>\n",
" <td>306.750000</td>\n",
" <td>340.250000</td>\n",
" <td>351.000000</td>\n",
" <td>333.250000</td>\n",
" <td>410.500000</td>\n",
" <td>348.750000</td>\n",
" <td>365.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"6\" valign=\"top\">int_insert</th>\n",
" <th>\"robin_hood::unordered_flat&lt;int&gt;\"</th>\n",
analysis in python done
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" <td>24.333333</td>\n",
" <td>29.466667</td>\n",
" <td>16.866667</td>\n",
" <td>31.466667</td>\n",
" <td>13.100000</td>\n",
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" <td>13.733333</td>\n",
" <td>18.033333</td>\n",
" <td>...</td>\n",
" <td>47.666667</td>\n",
" <td>47.266667</td>\n",
" <td>33.366667</td>\n",
" <td>49.066667</td>\n",
" <td>103.266667</td>\n",
" <td>39.666667</td>\n",
" <td>46.866667</td>\n",
" <td>59.833333</td>\n",
" <td>85.566667</td>\n",
" <td>128.100000</td>\n",
" </tr>\n",
" <tr>\n",
results update
2020-03-19 22:11:00 +00:00
" <th>\"robin_hood::unordered_node&lt;int&gt;\"</th>\n",
analysis in python done
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" <td>28.500000</td>\n",
" <td>32.933333</td>\n",
" <td>21.800000</td>\n",
" <td>36.200000</td>\n",
" <td>18.100000</td>\n",
" <td>22.866667</td>\n",
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" <td>23.633333</td>\n",
" <td>...</td>\n",
" <td>57.666667</td>\n",
" <td>66.500000</td>\n",
" <td>52.633333</td>\n",
" <td>71.033333</td>\n",
" <td>129.100000</td>\n",
" <td>74.533333</td>\n",
" <td>83.533333</td>\n",
" <td>99.566667</td>\n",
" <td>126.200000</td>\n",
" <td>169.233333</td>\n",
" </tr>\n",
" <tr>\n",
results update
2020-03-19 22:11:00 +00:00
" <th>\"robinhoodflat\"</th>\n",
" <td>107.000000</td>\n",
" <td>103.750000</td>\n",
" <td>68.750000</td>\n",
" <td>110.750000</td>\n",
" <td>67.500000</td>\n",
" <td>74.250000</td>\n",
" <td>94.000000</td>\n",
" <td>116.250000</td>\n",
" <td>64.250000</td>\n",
" <td>73.750000</td>\n",
" <td>...</td>\n",
" <td>153.500000</td>\n",
" <td>166.750000</td>\n",
" <td>152.000000</td>\n",
" <td>177.250000</td>\n",
" <td>261.750000</td>\n",
" <td>170.250000</td>\n",
" <td>188.750000</td>\n",
" <td>215.000000</td>\n",
" <td>259.250000</td>\n",
" <td>312.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>\"robinhoodnode</th>\n",
" <td>120.250000</td>\n",
" <td>116.000000</td>\n",
" <td>80.250000</td>\n",
" <td>120.000000</td>\n",
" <td>72.500000</td>\n",
" <td>81.500000</td>\n",
" <td>98.000000</td>\n",
" <td>126.250000</td>\n",
" <td>74.750000</td>\n",
" <td>82.000000</td>\n",
" <td>...</td>\n",
" <td>173.750000</td>\n",
" <td>182.500000</td>\n",
" <td>161.250000</td>\n",
" <td>197.000000</td>\n",
" <td>286.500000</td>\n",
" <td>187.000000</td>\n",
" <td>223.000000</td>\n",
" <td>246.000000</td>\n",
" <td>291.000000</td>\n",
" <td>352.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>\"std::map&lt;int&gt;\"</th>\n",
analysis in python done
2020-03-04 13:53:42 +00:00
" <td>52.733333</td>\n",
" <td>52.066667</td>\n",
" <td>53.100000</td>\n",
" <td>55.433333</td>\n",
" <td>58.533333</td>\n",
" <td>58.166667</td>\n",
" <td>63.066667</td>\n",
" <td>71.133333</td>\n",
" <td>95.233333</td>\n",
" <td>121.100000</td>\n",
" <td>...</td>\n",
" <td>242.400000</td>\n",
" <td>256.333333</td>\n",
" <td>253.066667</td>\n",
" <td>251.300000</td>\n",
" <td>251.100000</td>\n",
" <td>292.166667</td>\n",
" <td>303.200000</td>\n",
" <td>306.166667</td>\n",
" <td>317.300000</td>\n",
" <td>310.600000</td>\n",
" </tr>\n",
" <tr>\n",
results update
2020-03-19 22:11:00 +00:00
" <th>\"std::unordered_map\"</th>\n",
" <td>222.500000</td>\n",
" <td>221.500000</td>\n",
" <td>222.250000</td>\n",
" <td>221.000000</td>\n",
" <td>227.000000</td>\n",
" <td>230.750000</td>\n",
" <td>228.000000</td>\n",
" <td>241.750000</td>\n",
" <td>267.000000</td>\n",
" <td>290.750000</td>\n",
" <td>...</td>\n",
" <td>392.000000</td>\n",
" <td>413.500000</td>\n",
" <td>406.000000</td>\n",
" <td>398.500000</td>\n",
" <td>403.000000</td>\n",
" <td>433.750000</td>\n",
" <td>482.500000</td>\n",
" <td>503.000000</td>\n",
" <td>504.250000</td>\n",
" <td>505.250000</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"6\" valign=\"top\">int_nosucc_lookup</th>\n",
" <th>\"robin_hood::unordered_flat&lt;int&gt;\"</th>\n",
analysis in python done
2020-03-04 13:53:42 +00:00
" <td>58.366667</td>\n",
" <td>105.200000</td>\n",
" <td>19.300000</td>\n",
" <td>199.733333</td>\n",
" <td>14.700000</td>\n",
" <td>19.633333</td>\n",
" <td>26.700000</td>\n",
" <td>36.900000</td>\n",
" <td>15.000000</td>\n",
" <td>19.200000</td>\n",
" <td>...</td>\n",
" <td>43.300000</td>\n",
" <td>51.933333</td>\n",
" <td>37.600000</td>\n",
" <td>53.966667</td>\n",
" <td>111.266667</td>\n",
" <td>41.600000</td>\n",
" <td>47.366667</td>\n",
" <td>58.800000</td>\n",
" <td>82.400000</td>\n",
" <td>119.600000</td>\n",
" </tr>\n",
" <tr>\n",
results update
2020-03-19 22:11:00 +00:00
" <th>\"robin_hood::unordered_node&lt;int&gt;\"</th>\n",
analysis in python done
2020-03-04 13:53:42 +00:00
" <td>71.600000</td>\n",
" <td>135.733333</td>\n",
" <td>23.500000</td>\n",
" <td>265.833333</td>\n",
" <td>18.333333</td>\n",
" <td>23.133333</td>\n",
" <td>31.066667</td>\n",
" <td>41.900000</td>\n",
" <td>19.866667</td>\n",
" <td>24.833333</td>\n",
" <td>...</td>\n",
" <td>57.033333</td>\n",
" <td>68.366667</td>\n",
" <td>50.966667</td>\n",
" <td>68.733333</td>\n",
" <td>130.166667</td>\n",
" <td>57.433333</td>\n",
" <td>63.000000</td>\n",
" <td>75.966667</td>\n",
" <td>102.166667</td>\n",
" <td>140.166667</td>\n",
" </tr>\n",
" <tr>\n",
results update
2020-03-19 22:11:00 +00:00
" <th>\"robinhoodflat\"</th>\n",
" <td>239.750000</td>\n",
" <td>411.500000</td>\n",
" <td>91.250000</td>\n",
" <td>750.250000</td>\n",
" <td>79.750000</td>\n",
" <td>96.750000</td>\n",
" <td>110.250000</td>\n",
" <td>140.000000</td>\n",
" <td>77.250000</td>\n",
" <td>88.250000</td>\n",
" <td>...</td>\n",
" <td>213.250000</td>\n",
" <td>222.250000</td>\n",
" <td>224.500000</td>\n",
" <td>239.250000</td>\n",
" <td>293.500000</td>\n",
" <td>241.750000</td>\n",
" <td>255.500000</td>\n",
" <td>266.250000</td>\n",
" <td>285.000000</td>\n",
" <td>305.250000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>\"robinhoodnode</th>\n",
" <td>285.750000</td>\n",
" <td>501.500000</td>\n",
" <td>95.500000</td>\n",
" <td>949.500000</td>\n",
" <td>83.500000</td>\n",
" <td>102.250000</td>\n",
" <td>113.750000</td>\n",
" <td>155.750000</td>\n",
" <td>90.250000</td>\n",
" <td>102.250000</td>\n",
" <td>...</td>\n",
" <td>230.250000</td>\n",
" <td>245.500000</td>\n",
" <td>236.750000</td>\n",
" <td>253.000000</td>\n",
" <td>307.000000</td>\n",
" <td>251.750000</td>\n",
" <td>268.250000</td>\n",
" <td>280.250000</td>\n",
" <td>297.500000</td>\n",
" <td>321.750000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>\"std::map&lt;int&gt;\"</th>\n",
analysis in python done
2020-03-04 13:53:42 +00:00
" <td>97.333333</td>\n",
" <td>154.100000</td>\n",
" <td>212.000000</td>\n",
" <td>251.966667</td>\n",
" <td>331.233333</td>\n",
" <td>61.200000</td>\n",
" <td>490.266667</td>\n",
" <td>74.766667</td>\n",
" <td>99.633333</td>\n",
" <td>1628.166667</td>\n",
" <td>...</td>\n",
" <td>245.033333</td>\n",
" <td>257.566667</td>\n",
" <td>254.733333</td>\n",
" <td>253.566667</td>\n",
" <td>253.400000</td>\n",
" <td>273.366667</td>\n",
" <td>278.166667</td>\n",
" <td>278.733333</td>\n",
" <td>288.666667</td>\n",
" <td>287.000000</td>\n",
" </tr>\n",
" <tr>\n",
results update
2020-03-19 22:11:00 +00:00
" <th>\"std::unordered_map\"</th>\n",
" <td>409.250000</td>\n",
" <td>619.000000</td>\n",
" <td>838.000000</td>\n",
" <td>991.250000</td>\n",
" <td>1211.750000</td>\n",
" <td>232.500000</td>\n",
" <td>1723.000000</td>\n",
" <td>248.750000</td>\n",
" <td>267.250000</td>\n",
" <td>4897.000000</td>\n",
" <td>...</td>\n",
" <td>402.500000</td>\n",
" <td>419.250000</td>\n",
" <td>414.000000</td>\n",
" <td>406.000000</td>\n",
" <td>409.000000</td>\n",
" <td>424.250000</td>\n",
" <td>446.750000</td>\n",
" <td>459.000000</td>\n",
" <td>458.000000</td>\n",
" <td>454.750000</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"6\" valign=\"top\">int_succ_lookup</th>\n",
" <th>\"robin_hood::unordered_flat&lt;int&gt;\"</th>\n",
analysis in python done
2020-03-04 13:53:42 +00:00
" <td>10.566667</td>\n",
" <td>11.933333</td>\n",
" <td>8.000000</td>\n",
" <td>12.100000</td>\n",
" <td>6.533333</td>\n",
" <td>8.033333</td>\n",
" <td>10.500000</td>\n",
" <td>13.000000</td>\n",
" <td>6.966667</td>\n",
" <td>8.000000</td>\n",
" <td>...</td>\n",
" <td>25.466667</td>\n",
" <td>27.200000</td>\n",
" <td>25.133333</td>\n",
" <td>28.133333</td>\n",
" <td>36.766667</td>\n",
" <td>31.400000</td>\n",
" <td>33.066667</td>\n",
" <td>35.700000</td>\n",
" <td>38.766667</td>\n",
" <td>43.466667</td>\n",
" </tr>\n",
" <tr>\n",
results update
2020-03-19 22:11:00 +00:00
" <th>\"robin_hood::unordered_node&lt;int&gt;\"</th>\n",
analysis in python done
2020-03-04 13:53:42 +00:00
" <td>14.300000</td>\n",
" <td>15.666667</td>\n",
" <td>11.266667</td>\n",
" <td>17.033333</td>\n",
" <td>10.033333</td>\n",
" <td>12.000000</td>\n",
" <td>14.866667</td>\n",
" <td>17.833333</td>\n",
" <td>13.100000</td>\n",
" <td>16.266667</td>\n",
" <td>...</td>\n",
" <td>57.200000</td>\n",
" <td>58.533333</td>\n",
" <td>59.466667</td>\n",
" <td>61.533333</td>\n",
" <td>72.600000</td>\n",
" <td>75.133333</td>\n",
" <td>77.466667</td>\n",
" <td>80.000000</td>\n",
" <td>82.933333</td>\n",
" <td>89.566667</td>\n",
" </tr>\n",
" <tr>\n",
results update
2020-03-19 22:11:00 +00:00
" <th>\"robinhoodflat\"</th>\n",
" <td>37.500000</td>\n",
" <td>38.250000</td>\n",
" <td>32.000000</td>\n",
" <td>40.250000</td>\n",
" <td>34.750000</td>\n",
" <td>36.500000</td>\n",
" <td>37.750000</td>\n",
" <td>43.000000</td>\n",
" <td>32.250000</td>\n",
" <td>35.500000</td>\n",
" <td>...</td>\n",
" <td>113.500000</td>\n",
" <td>116.000000</td>\n",
" <td>121.250000</td>\n",
" <td>120.750000</td>\n",
" <td>152.500000</td>\n",
" <td>131.750000</td>\n",
" <td>137.000000</td>\n",
" <td>143.500000</td>\n",
" <td>148.500000</td>\n",
" <td>168.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>\"robinhoodnode</th>\n",
" <td>37.750000</td>\n",
" <td>39.750000</td>\n",
" <td>35.250000</td>\n",
" <td>43.250000</td>\n",
" <td>35.250000</td>\n",
" <td>38.500000</td>\n",
" <td>41.750000</td>\n",
" <td>47.250000</td>\n",
" <td>45.750000</td>\n",
" <td>58.750000</td>\n",
" <td>...</td>\n",
" <td>206.000000</td>\n",
" <td>209.500000</td>\n",
" <td>213.750000</td>\n",
" <td>218.750000</td>\n",
" <td>250.250000</td>\n",
" <td>232.250000</td>\n",
" <td>246.000000</td>\n",
" <td>250.000000</td>\n",
" <td>259.000000</td>\n",
" <td>282.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>\"std::map&lt;int&gt;\"</th>\n",
analysis in python done
2020-03-04 13:53:42 +00:00
" <td>16.733333</td>\n",
" <td>17.266667</td>\n",
" <td>17.200000</td>\n",
" <td>17.600000</td>\n",
" <td>18.633333</td>\n",
" <td>18.433333</td>\n",
" <td>20.166667</td>\n",
" <td>23.833333</td>\n",
" <td>32.766667</td>\n",
" <td>41.100000</td>\n",
" <td>...</td>\n",
" <td>70.766667</td>\n",
" <td>73.966667</td>\n",
" <td>72.166667</td>\n",
" <td>72.166667</td>\n",
" <td>72.466667</td>\n",
" <td>84.733333</td>\n",
" <td>89.033333</td>\n",
" <td>91.266667</td>\n",
" <td>94.566667</td>\n",
" <td>93.933333</td>\n",
" </tr>\n",
" <tr>\n",
results update
2020-03-19 22:11:00 +00:00
" <th>\"std::unordered_map\"</th>\n",
" <td>88.750000</td>\n",
" <td>92.750000</td>\n",
" <td>102.250000</td>\n",
" <td>92.750000</td>\n",
" <td>107.000000</td>\n",
" <td>107.750000</td>\n",
" <td>101.750000</td>\n",
" <td>131.750000</td>\n",
" <td>158.000000</td>\n",
" <td>179.250000</td>\n",
" <td>...</td>\n",
" <td>324.000000</td>\n",
" <td>332.750000</td>\n",
" <td>334.250000</td>\n",
" <td>334.000000</td>\n",
" <td>337.000000</td>\n",
" <td>356.250000</td>\n",
" <td>369.750000</td>\n",
" <td>395.250000</td>\n",
" <td>388.250000</td>\n",
" <td>390.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"6\" valign=\"top\">string_delete</th>\n",
" <th>\"robin_hood::unordered_flat&lt;string&gt;\"</th>\n",
analysis in python done
2020-03-04 13:53:42 +00:00
" <td>25.233333</td>\n",
" <td>51.466667</td>\n",
" <td>46.800000</td>\n",
" <td>70.966667</td>\n",
" <td>41.933333</td>\n",
" <td>56.766667</td>\n",
" <td>83.300000</td>\n",
" <td>139.500000</td>\n",
" <td>48.066667</td>\n",
" <td>63.400000</td>\n",
" <td>...</td>\n",
" <td>96.733333</td>\n",
" <td>114.300000</td>\n",
" <td>76.666667</td>\n",
" <td>122.866667</td>\n",
" <td>232.700000</td>\n",
" <td>82.133333</td>\n",
" <td>100.233333</td>\n",
" <td>128.500000</td>\n",
" <td>172.533333</td>\n",
" <td>240.166667</td>\n",
" </tr>\n",
" <tr>\n",
results update
2020-03-19 22:11:00 +00:00
" <th>\"robin_hood::unordered_node&lt;string&gt;\"</th>\n",
analysis in python done
2020-03-04 13:53:42 +00:00
" <td>18.100000</td>\n",
" <td>18.866667</td>\n",
" <td>27.500000</td>\n",
" <td>57.633333</td>\n",
" <td>23.966667</td>\n",
" <td>29.166667</td>\n",
" <td>34.700000</td>\n",
" <td>43.466667</td>\n",
" <td>26.300000</td>\n",
" <td>30.800000</td>\n",
" <td>...</td>\n",
" <td>47.900000</td>\n",
" <td>58.033333</td>\n",
" <td>52.633333</td>\n",
" <td>73.033333</td>\n",
" <td>135.300000</td>\n",
" <td>62.900000</td>\n",
" <td>59.100000</td>\n",
" <td>85.266667</td>\n",
" <td>111.966667</td>\n",
" <td>167.733333</td>\n",
" </tr>\n",
" <tr>\n",
results update
2020-03-19 22:11:00 +00:00
" <th>\"robinhoodflat\"</th>\n",
" <td>146.250000</td>\n",
" <td>169.250000</td>\n",
" <td>263.500000</td>\n",
" <td>190.750000</td>\n",
" <td>186.500000</td>\n",
" <td>267.000000</td>\n",
" <td>420.250000</td>\n",
" <td>905.500000</td>\n",
" <td>187.250000</td>\n",
" <td>263.500000</td>\n",
" <td>...</td>\n",
" <td>267.500000</td>\n",
" <td>350.250000</td>\n",
" <td>210.750000</td>\n",
" <td>378.500000</td>\n",
" <td>815.000000</td>\n",
" <td>228.750000</td>\n",
" <td>302.250000</td>\n",
" <td>390.250000</td>\n",
" <td>545.750000</td>\n",
" <td>834.250000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>\"robinhoodnode\"</th>\n",
" <td>78.750000</td>\n",
" <td>86.500000</td>\n",
" <td>100.250000</td>\n",
" <td>140.250000</td>\n",
" <td>91.500000</td>\n",
" <td>101.750000</td>\n",
" <td>127.000000</td>\n",
" <td>157.250000</td>\n",
" <td>100.000000</td>\n",
" <td>106.250000</td>\n",
" <td>...</td>\n",
" <td>199.750000</td>\n",
" <td>208.500000</td>\n",
" <td>144.750000</td>\n",
" <td>198.500000</td>\n",
" <td>278.500000</td>\n",
" <td>188.500000</td>\n",
" <td>178.500000</td>\n",
" <td>254.000000</td>\n",
" <td>227.250000</td>\n",
" <td>358.750000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>\"std::map&lt;string&gt;\"</th>\n",
analysis in python done
2020-03-04 13:53:42 +00:00
" <td>63.300000</td>\n",
" <td>70.700000</td>\n",
" <td>108.900000</td>\n",
" <td>171.633333</td>\n",
" <td>207.366667</td>\n",
" <td>138.600000</td>\n",
" <td>261.000000</td>\n",
" <td>173.533333</td>\n",
" <td>182.000000</td>\n",
" <td>314.366667</td>\n",
" <td>...</td>\n",
" <td>330.566667</td>\n",
" <td>345.366667</td>\n",
" <td>377.800000</td>\n",
" <td>391.266667</td>\n",
" <td>409.000000</td>\n",
" <td>426.833333</td>\n",
" <td>437.366667</td>\n",
" <td>448.166667</td>\n",
" <td>471.900000</td>\n",
" <td>481.933333</td>\n",
" </tr>\n",
" <tr>\n",
results update
2020-03-19 22:11:00 +00:00
" <th>\"std::unordered_map\"</th>\n",
" <td>200.250000</td>\n",
" <td>195.250000</td>\n",
" <td>233.750000</td>\n",
" <td>304.000000</td>\n",
" <td>364.750000</td>\n",
" <td>302.000000</td>\n",
" <td>425.500000</td>\n",
" <td>344.000000</td>\n",
" <td>341.000000</td>\n",
" <td>481.750000</td>\n",
" <td>...</td>\n",
" <td>517.000000</td>\n",
" <td>539.750000</td>\n",
" <td>570.250000</td>\n",
" <td>586.250000</td>\n",
" <td>605.000000</td>\n",
" <td>639.750000</td>\n",
" <td>680.250000</td>\n",
" <td>644.250000</td>\n",
" <td>661.000000</td>\n",
" <td>648.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"6\" valign=\"top\">string_insert</th>\n",
" <th>\"robin_hood::unordered_flat&lt;string&gt;\"</th>\n",
analysis in python done
2020-03-04 13:53:42 +00:00
" <td>82.833333</td>\n",
" <td>97.466667</td>\n",
" <td>91.266667</td>\n",
" <td>163.566667</td>\n",
" <td>116.633333</td>\n",
" <td>131.833333</td>\n",
" <td>162.300000</td>\n",
" <td>224.466667</td>\n",
" <td>135.933333</td>\n",
" <td>154.100000</td>\n",
" <td>...</td>\n",
" <td>221.700000</td>\n",
" <td>234.566667</td>\n",
" <td>208.900000</td>\n",
" <td>238.900000</td>\n",
" <td>394.100000</td>\n",
" <td>216.866667</td>\n",
" <td>226.166667</td>\n",
" <td>245.700000</td>\n",
" <td>294.333333</td>\n",
" <td>378.300000</td>\n",
" </tr>\n",
" <tr>\n",
results update
2020-03-19 22:11:00 +00:00
" <th>\"robin_hood::unordered_node&lt;string&gt;\"</th>\n",
analysis in python done
2020-03-04 13:53:42 +00:00
" <td>57.500000</td>\n",
" <td>58.333333</td>\n",
" <td>47.800000</td>\n",
" <td>66.366667</td>\n",
" <td>58.966667</td>\n",
" <td>68.700000</td>\n",
" <td>83.033333</td>\n",
" <td>101.600000</td>\n",
" <td>109.500000</td>\n",
" <td>115.266667</td>\n",
" <td>...</td>\n",
" <td>156.033333</td>\n",
" <td>168.933333</td>\n",
" <td>172.733333</td>\n",
" <td>184.100000</td>\n",
" <td>250.333333</td>\n",
" <td>179.966667</td>\n",
" <td>196.600000</td>\n",
" <td>207.166667</td>\n",
" <td>228.566667</td>\n",
" <td>281.533333</td>\n",
" </tr>\n",
" <tr>\n",
results update
2020-03-19 22:11:00 +00:00
" <th>\"robinhoodflat\"</th>\n",
" <td>705.500000</td>\n",
" <td>841.000000</td>\n",
" <td>487.250000</td>\n",
" <td>993.500000</td>\n",
" <td>444.250000</td>\n",
" <td>541.500000</td>\n",
" <td>702.000000</td>\n",
" <td>1070.500000</td>\n",
" <td>508.250000</td>\n",
" <td>590.500000</td>\n",
" <td>...</td>\n",
" <td>671.500000</td>\n",
" <td>738.750000</td>\n",
" <td>610.750000</td>\n",
" <td>761.750000</td>\n",
" <td>1197.250000</td>\n",
" <td>622.000000</td>\n",
" <td>681.000000</td>\n",
" <td>788.750000</td>\n",
" <td>911.000000</td>\n",
" <td>1194.750000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>\"robinhoodnode\"</th>\n",
" <td>318.750000</td>\n",
" <td>333.000000</td>\n",
" <td>294.750000</td>\n",
" <td>352.250000</td>\n",
" <td>309.500000</td>\n",
" <td>325.000000</td>\n",
" <td>357.250000</td>\n",
" <td>403.750000</td>\n",
" <td>359.250000</td>\n",
" <td>377.000000</td>\n",
" <td>...</td>\n",
" <td>415.500000</td>\n",
" <td>441.000000</td>\n",
" <td>463.250000</td>\n",
" <td>451.500000</td>\n",
" <td>553.000000</td>\n",
" <td>424.000000</td>\n",
" <td>501.500000</td>\n",
" <td>528.500000</td>\n",
" <td>514.000000</td>\n",
" <td>633.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>\"std::map&lt;string&gt;\"</th>\n",
analysis in python done
2020-03-04 13:53:42 +00:00
" <td>92.000000</td>\n",
" <td>87.266667</td>\n",
" <td>123.700000</td>\n",
" <td>168.633333</td>\n",
" <td>195.966667</td>\n",
" <td>210.666667</td>\n",
" <td>235.933333</td>\n",
" <td>246.700000</td>\n",
" <td>259.700000</td>\n",
" <td>274.300000</td>\n",
" <td>...</td>\n",
" <td>371.733333</td>\n",
" <td>380.833333</td>\n",
" <td>398.800000</td>\n",
" <td>407.800000</td>\n",
" <td>419.900000</td>\n",
" <td>438.633333</td>\n",
" <td>448.633333</td>\n",
" <td>463.500000</td>\n",
" <td>470.933333</td>\n",
" <td>468.766667</td>\n",
" </tr>\n",
" <tr>\n",
results update
2020-03-19 22:11:00 +00:00
" <th>\"std::unordered_map\"</th>\n",
" <td>423.750000</td>\n",
" <td>435.750000</td>\n",
" <td>471.500000</td>\n",
" <td>511.750000</td>\n",
" <td>538.750000</td>\n",
" <td>560.000000</td>\n",
" <td>566.000000</td>\n",
" <td>577.500000</td>\n",
" <td>595.500000</td>\n",
" <td>604.250000</td>\n",
" <td>...</td>\n",
" <td>716.250000</td>\n",
" <td>725.250000</td>\n",
" <td>736.500000</td>\n",
" <td>810.000000</td>\n",
" <td>812.000000</td>\n",
" <td>818.500000</td>\n",
" <td>843.500000</td>\n",
" <td>838.750000</td>\n",
" <td>864.250000</td>\n",
" <td>850.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"6\" valign=\"top\">string_nosucc_lookup</th>\n",
" <th>\"robin_hood::unordered_flat&lt;string&gt;\"</th>\n",
analysis in python done
2020-03-04 13:53:42 +00:00
" <td>188.700000</td>\n",
" <td>413.366667</td>\n",
" <td>87.933333</td>\n",
" <td>858.400000</td>\n",
" <td>103.733333</td>\n",
" <td>117.266667</td>\n",
" <td>144.066667</td>\n",
" <td>202.766667</td>\n",
" <td>116.433333</td>\n",
" <td>127.266667</td>\n",
" <td>...</td>\n",
" <td>184.966667</td>\n",
" <td>192.800000</td>\n",
" <td>176.266667</td>\n",
" <td>210.400000</td>\n",
" <td>342.733333</td>\n",
" <td>191.433333</td>\n",
" <td>201.600000</td>\n",
" <td>223.566667</td>\n",
" <td>271.666667</td>\n",
" <td>355.566667</td>\n",
" </tr>\n",
" <tr>\n",
results update
2020-03-19 22:11:00 +00:00
" <th>\"robin_hood::unordered_node&lt;string&gt;\"</th>\n",
analysis in python done
2020-03-04 13:53:42 +00:00
" <td>120.033333</td>\n",
" <td>218.333333</td>\n",
" <td>36.900000</td>\n",
" <td>910.000000</td>\n",
" <td>46.933333</td>\n",
" <td>53.966667</td>\n",
" <td>62.700000</td>\n",
" <td>77.733333</td>\n",
" <td>79.233333</td>\n",
" <td>84.000000</td>\n",
" <td>...</td>\n",
" <td>133.166667</td>\n",
" <td>144.300000</td>\n",
" <td>130.733333</td>\n",
" <td>153.233333</td>\n",
" <td>203.833333</td>\n",
" <td>139.900000</td>\n",
" <td>136.466667</td>\n",
" <td>159.500000</td>\n",
" <td>183.266667</td>\n",
" <td>215.466667</td>\n",
" </tr>\n",
" <tr>\n",
results update
2020-03-19 22:11:00 +00:00
" <th>\"robinhoodflat\"</th>\n",
" <td>1251.750000</td>\n",
" <td>2316.000000</td>\n",
" <td>450.750000</td>\n",
" <td>4445.500000</td>\n",
" <td>370.500000</td>\n",
" <td>461.750000</td>\n",
" <td>649.750000</td>\n",
" <td>1103.250000</td>\n",
" <td>387.750000</td>\n",
" <td>478.500000</td>\n",
" <td>...</td>\n",
" <td>538.000000</td>\n",
" <td>622.750000</td>\n",
" <td>487.750000</td>\n",
" <td>650.750000</td>\n",
" <td>1090.250000</td>\n",
" <td>507.500000</td>\n",
" <td>570.750000</td>\n",
" <td>681.500000</td>\n",
" <td>823.750000</td>\n",
" <td>1098.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>\"robinhoodnode\"</th>\n",
" <td>397.500000</td>\n",
" <td>678.250000</td>\n",
" <td>203.000000</td>\n",
" <td>1873.000000</td>\n",
" <td>203.250000</td>\n",
" <td>227.250000</td>\n",
" <td>242.750000</td>\n",
" <td>282.250000</td>\n",
" <td>239.500000</td>\n",
" <td>252.750000</td>\n",
" <td>...</td>\n",
" <td>400.500000</td>\n",
" <td>417.000000</td>\n",
" <td>377.500000</td>\n",
" <td>414.250000</td>\n",
" <td>466.500000</td>\n",
" <td>402.500000</td>\n",
" <td>362.750000</td>\n",
" <td>431.500000</td>\n",
" <td>454.250000</td>\n",
" <td>492.250000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>\"std::map&lt;string&gt;\"</th>\n",
analysis in python done
2020-03-04 13:53:42 +00:00
" <td>141.133333</td>\n",
" <td>221.266667</td>\n",
" <td>368.500000</td>\n",
" <td>530.066667</td>\n",
" <td>806.966667</td>\n",
" <td>181.933333</td>\n",
" <td>1294.066667</td>\n",
" <td>208.200000</td>\n",
" <td>219.833333</td>\n",
" <td>2729.800000</td>\n",
" <td>...</td>\n",
" <td>306.866667</td>\n",
" <td>314.700000</td>\n",
" <td>335.333333</td>\n",
" <td>343.333333</td>\n",
" <td>348.466667</td>\n",
" <td>362.233333</td>\n",
" <td>371.300000</td>\n",
" <td>376.066667</td>\n",
" <td>394.466667</td>\n",
" <td>392.066667</td>\n",
" </tr>\n",
" <tr>\n",
results update
2020-03-19 22:11:00 +00:00
" <th>\"std::unordered_map\"</th>\n",
" <td>410.000000</td>\n",
" <td>532.250000</td>\n",
" <td>781.000000</td>\n",
" <td>1064.500000</td>\n",
" <td>1560.000000</td>\n",
" <td>417.500000</td>\n",
" <td>2483.000000</td>\n",
" <td>438.000000</td>\n",
" <td>442.500000</td>\n",
" <td>4799.000000</td>\n",
" <td>...</td>\n",
" <td>523.750000</td>\n",
" <td>542.750000</td>\n",
" <td>564.000000</td>\n",
" <td>613.250000</td>\n",
" <td>616.000000</td>\n",
" <td>639.750000</td>\n",
" <td>647.250000</td>\n",
" <td>647.500000</td>\n",
" <td>657.000000</td>\n",
" <td>653.250000</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"6\" valign=\"top\">string_succ_lookup</th>\n",
" <th>\"robin_hood::unordered_flat&lt;string&gt;\"</th>\n",
analysis in python done
2020-03-04 13:53:42 +00:00
" <td>25.933333</td>\n",
" <td>27.733333</td>\n",
" <td>45.700000</td>\n",
" <td>56.000000</td>\n",
" <td>78.700000</td>\n",
" <td>82.333333</td>\n",
" <td>84.500000</td>\n",
" <td>83.400000</td>\n",
" <td>96.566667</td>\n",
" <td>95.266667</td>\n",
" <td>...</td>\n",
" <td>152.966667</td>\n",
" <td>155.266667</td>\n",
" <td>163.900000</td>\n",
" <td>171.333333</td>\n",
" <td>182.533333</td>\n",
" <td>176.500000</td>\n",
" <td>178.400000</td>\n",
" <td>182.133333</td>\n",
" <td>185.866667</td>\n",
" <td>191.366667</td>\n",
" </tr>\n",
" <tr>\n",
results update
2020-03-19 22:11:00 +00:00
" <th>\"robin_hood::unordered_node&lt;string&gt;\"</th>\n",
analysis in python done
2020-03-04 13:53:42 +00:00
" <td>30.933333</td>\n",
" <td>35.600000</td>\n",
" <td>48.566667</td>\n",
" <td>79.666667</td>\n",
" <td>102.300000</td>\n",
" <td>113.000000</td>\n",
" <td>121.600000</td>\n",
" <td>126.266667</td>\n",
" <td>160.433333</td>\n",
" <td>163.900000</td>\n",
" <td>...</td>\n",
" <td>233.300000</td>\n",
" <td>240.866667</td>\n",
" <td>258.266667</td>\n",
" <td>272.933333</td>\n",
" <td>285.733333</td>\n",
" <td>288.500000</td>\n",
" <td>292.266667</td>\n",
" <td>296.700000</td>\n",
" <td>302.766667</td>\n",
" <td>309.800000</td>\n",
" </tr>\n",
" <tr>\n",
results update
2020-03-19 22:11:00 +00:00
" <th>\"robinhoodflat\"</th>\n",
" <td>77.500000</td>\n",
" <td>81.500000</td>\n",
" <td>104.750000</td>\n",
" <td>110.000000</td>\n",
" <td>128.250000</td>\n",
" <td>127.500000</td>\n",
" <td>131.750000</td>\n",
" <td>136.500000</td>\n",
" <td>139.250000</td>\n",
" <td>141.500000</td>\n",
" <td>...</td>\n",
" <td>193.250000</td>\n",
" <td>198.500000</td>\n",
" <td>204.750000</td>\n",
" <td>215.500000</td>\n",
" <td>265.750000</td>\n",
" <td>216.250000</td>\n",
" <td>218.750000</td>\n",
" <td>232.250000</td>\n",
" <td>240.250000</td>\n",
" <td>273.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>\"robinhoodnode\"</th>\n",
" <td>73.000000</td>\n",
" <td>90.750000</td>\n",
" <td>108.000000</td>\n",
" <td>128.000000</td>\n",
" <td>150.750000</td>\n",
" <td>165.250000</td>\n",
" <td>175.500000</td>\n",
" <td>181.000000</td>\n",
" <td>199.750000</td>\n",
" <td>204.500000</td>\n",
" <td>...</td>\n",
" <td>267.250000</td>\n",
" <td>278.250000</td>\n",
" <td>287.000000</td>\n",
" <td>307.250000</td>\n",
" <td>353.750000</td>\n",
" <td>321.000000</td>\n",
" <td>332.000000</td>\n",
" <td>338.500000</td>\n",
" <td>342.250000</td>\n",
" <td>381.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>\"std::map&lt;string&gt;\"</th>\n",
analysis in python done
2020-03-04 13:53:42 +00:00
" <td>48.866667</td>\n",
" <td>56.433333</td>\n",
" <td>113.566667</td>\n",
" <td>161.800000</td>\n",
" <td>191.100000</td>\n",
" <td>209.766667</td>\n",
" <td>225.066667</td>\n",
" <td>236.400000</td>\n",
" <td>248.933333</td>\n",
" <td>257.866667</td>\n",
" <td>...</td>\n",
" <td>352.433333</td>\n",
" <td>359.533333</td>\n",
" <td>385.633333</td>\n",
" <td>399.200000</td>\n",
" <td>409.733333</td>\n",
" <td>426.500000</td>\n",
" <td>441.966667</td>\n",
" <td>463.000000</td>\n",
" <td>468.466667</td>\n",
" <td>471.433333</td>\n",
" </tr>\n",
results update
2020-03-19 22:11:00 +00:00
" <tr>\n",
" <th>\"std::unordered_map\"</th>\n",
" <td>136.500000</td>\n",
" <td>141.500000</td>\n",
" <td>205.000000</td>\n",
" <td>246.500000</td>\n",
" <td>277.500000</td>\n",
" <td>293.500000</td>\n",
" <td>303.250000</td>\n",
" <td>322.000000</td>\n",
" <td>324.750000</td>\n",
" <td>339.000000</td>\n",
" <td>...</td>\n",
" <td>427.250000</td>\n",
" <td>442.250000</td>\n",
" <td>466.250000</td>\n",
" <td>482.000000</td>\n",
" <td>494.250000</td>\n",
" <td>508.500000</td>\n",
" <td>528.750000</td>\n",
" <td>531.250000</td>\n",
" <td>530.250000</td>\n",
" <td>535.500000</td>\n",
" </tr>\n",
analysis in python done
2020-03-04 13:53:42 +00:00
" </tbody>\n",
"</table>\n",
results update
2020-03-19 22:11:00 +00:00
"<p>48 rows × 31 columns</p>\n",
analysis in python done
2020-03-04 13:53:42 +00:00
"</div>"
],
"text/plain": [
results update
2020-03-19 22:11:00 +00:00
" 50000 \\\n",
"TEST MAP \n",
"int_delete \"robin_hood::unordered_flat<int>\" 9.066667 \n",
" \"robin_hood::unordered_node<int>\" 10.700000 \n",
" \"robinhoodflat\" 34.000000 \n",
" \"robinhoodnode 43.500000 \n",
" \"std::map<int>\" 44.233333 \n",
" \"std::unordered_map\" 141.500000 \n",
"int_insert \"robin_hood::unordered_flat<int>\" 24.333333 \n",
" \"robin_hood::unordered_node<int>\" 28.500000 \n",
" \"robinhoodflat\" 107.000000 \n",
" \"robinhoodnode 120.250000 \n",
" \"std::map<int>\" 52.733333 \n",
" \"std::unordered_map\" 222.500000 \n",
"int_nosucc_lookup \"robin_hood::unordered_flat<int>\" 58.366667 \n",
" \"robin_hood::unordered_node<int>\" 71.600000 \n",
" \"robinhoodflat\" 239.750000 \n",
" \"robinhoodnode 285.750000 \n",
" \"std::map<int>\" 97.333333 \n",
" \"std::unordered_map\" 409.250000 \n",
"int_succ_lookup \"robin_hood::unordered_flat<int>\" 10.566667 \n",
" \"robin_hood::unordered_node<int>\" 14.300000 \n",
" \"robinhoodflat\" 37.500000 \n",
" \"robinhoodnode 37.750000 \n",
" \"std::map<int>\" 16.733333 \n",
" \"std::unordered_map\" 88.750000 \n",
"string_delete \"robin_hood::unordered_flat<string>\" 25.233333 \n",
" \"robin_hood::unordered_node<string>\" 18.100000 \n",
" \"robinhoodflat\" 146.250000 \n",
" \"robinhoodnode\" 78.750000 \n",
" \"std::map<string>\" 63.300000 \n",
" \"std::unordered_map\" 200.250000 \n",
"string_insert \"robin_hood::unordered_flat<string>\" 82.833333 \n",
" \"robin_hood::unordered_node<string>\" 57.500000 \n",
" \"robinhoodflat\" 705.500000 \n",
" \"robinhoodnode\" 318.750000 \n",
" \"std::map<string>\" 92.000000 \n",
" \"std::unordered_map\" 423.750000 \n",
"string_nosucc_lookup \"robin_hood::unordered_flat<string>\" 188.700000 \n",
" \"robin_hood::unordered_node<string>\" 120.033333 \n",
" \"robinhoodflat\" 1251.750000 \n",
" \"robinhoodnode\" 397.500000 \n",
" \"std::map<string>\" 141.133333 \n",
" \"std::unordered_map\" 410.000000 \n",
"string_succ_lookup \"robin_hood::unordered_flat<string>\" 25.933333 \n",
" \"robin_hood::unordered_node<string>\" 30.933333 \n",
" \"robinhoodflat\" 77.500000 \n",
" \"robinhoodnode\" 73.000000 \n",
" \"std::map<string>\" 48.866667 \n",
" \"std::unordered_map\" 136.500000 \n",
analysis in python done
2020-03-04 13:53:42 +00:00
"\n",
results update
2020-03-19 22:11:00 +00:00
" 100000 \\\n",
"TEST MAP \n",
"int_delete \"robin_hood::unordered_flat<int>\" 9.233333 \n",
" \"robin_hood::unordered_node<int>\" 11.200000 \n",
" \"robinhoodflat\" 34.500000 \n",
" \"robinhoodnode 41.000000 \n",
" \"std::map<int>\" 47.766667 \n",
" \"std::unordered_map\" 136.250000 \n",
"int_insert \"robin_hood::unordered_flat<int>\" 29.466667 \n",
" \"robin_hood::unordered_node<int>\" 32.933333 \n",
" \"robinhoodflat\" 103.750000 \n",
" \"robinhoodnode 116.000000 \n",
" \"std::map<int>\" 52.066667 \n",
" \"std::unordered_map\" 221.500000 \n",
"int_nosucc_lookup \"robin_hood::unordered_flat<int>\" 105.200000 \n",
" \"robin_hood::unordered_node<int>\" 135.733333 \n",
" \"robinhoodflat\" 411.500000 \n",
" \"robinhoodnode 501.500000 \n",
" \"std::map<int>\" 154.100000 \n",
" \"std::unordered_map\" 619.000000 \n",
"int_succ_lookup \"robin_hood::unordered_flat<int>\" 11.933333 \n",
" \"robin_hood::unordered_node<int>\" 15.666667 \n",
" \"robinhoodflat\" 38.250000 \n",
" \"robinhoodnode 39.750000 \n",
" \"std::map<int>\" 17.266667 \n",
" \"std::unordered_map\" 92.750000 \n",
"string_delete \"robin_hood::unordered_flat<string>\" 51.466667 \n",
" \"robin_hood::unordered_node<string>\" 18.866667 \n",
" \"robinhoodflat\" 169.250000 \n",
" \"robinhoodnode\" 86.500000 \n",
" \"std::map<string>\" 70.700000 \n",
" \"std::unordered_map\" 195.250000 \n",
"string_insert \"robin_hood::unordered_flat<string>\" 97.466667 \n",
" \"robin_hood::unordered_node<string>\" 58.333333 \n",
" \"robinhoodflat\" 841.000000 \n",
" \"robinhoodnode\" 333.000000 \n",
" \"std::map<string>\" 87.266667 \n",
" \"std::unordered_map\" 435.750000 \n",
"string_nosucc_lookup \"robin_hood::unordered_flat<string>\" 413.366667 \n",
" \"robin_hood::unordered_node<string>\" 218.333333 \n",
" \"robinhoodflat\" 2316.000000 \n",
" \"robinhoodnode\" 678.250000 \n",
" \"std::map<string>\" 221.266667 \n",
" \"std::unordered_map\" 532.250000 \n",
"string_succ_lookup \"robin_hood::unordered_flat<string>\" 27.733333 \n",
" \"robin_hood::unordered_node<string>\" 35.600000 \n",
" \"robinhoodflat\" 81.500000 \n",
" \"robinhoodnode\" 90.750000 \n",
" \"std::map<string>\" 56.433333 \n",
" \"std::unordered_map\" 141.500000 \n",
analysis in python done
2020-03-04 13:53:42 +00:00
"\n",
" 150000 \\\n",
"TEST MAP \n",
results update
2020-03-19 22:11:00 +00:00
"int_delete \"robin_hood::unordered_flat<int>\" 16.033333 \n",
" \"robin_hood::unordered_node<int>\" 17.700000 \n",
" \"robinhoodflat\" 47.250000 \n",
" \"robinhoodnode 54.250000 \n",
" \"std::map<int>\" 50.766667 \n",
" \"std::unordered_map\" 143.250000 \n",
"int_insert \"robin_hood::unordered_flat<int>\" 16.866667 \n",
" \"robin_hood::unordered_node<int>\" 21.800000 \n",
" \"robinhoodflat\" 68.750000 \n",
" \"robinhoodnode 80.250000 \n",
" \"std::map<int>\" 53.100000 \n",
" \"std::unordered_map\" 222.250000 \n",
"int_nosucc_lookup \"robin_hood::unordered_flat<int>\" 19.300000 \n",
" \"robin_hood::unordered_node<int>\" 23.500000 \n",
" \"robinhoodflat\" 91.250000 \n",
" \"robinhoodnode 95.500000 \n",
" \"std::map<int>\" 212.000000 \n",
" \"std::unordered_map\" 838.000000 \n",
"int_succ_lookup \"robin_hood::unordered_flat<int>\" 8.000000 \n",
" \"robin_hood::unordered_node<int>\" 11.266667 \n",
" \"robinhoodflat\" 32.000000 \n",
" \"robinhoodnode 35.250000 \n",
" \"std::map<int>\" 17.200000 \n",
" \"std::unordered_map\" 102.250000 \n",
"string_delete \"robin_hood::unordered_flat<string>\" 46.800000 \n",
" \"robin_hood::unordered_node<string>\" 27.500000 \n",
" \"robinhoodflat\" 263.500000 \n",
" \"robinhoodnode\" 100.250000 \n",
" \"std::map<string>\" 108.900000 \n",
" \"std::unordered_map\" 233.750000 \n",
"string_insert \"robin_hood::unordered_flat<string>\" 91.266667 \n",
" \"robin_hood::unordered_node<string>\" 47.800000 \n",
" \"robinhoodflat\" 487.250000 \n",
" \"robinhoodnode\" 294.750000 \n",
" \"std::map<string>\" 123.700000 \n",
" \"std::unordered_map\" 471.500000 \n",
"string_nosucc_lookup \"robin_hood::unordered_flat<string>\" 87.933333 \n",
" \"robin_hood::unordered_node<string>\" 36.900000 \n",
" \"robinhoodflat\" 450.750000 \n",
" \"robinhoodnode\" 203.000000 \n",
" \"std::map<string>\" 368.500000 \n",
" \"std::unordered_map\" 781.000000 \n",
"string_succ_lookup \"robin_hood::unordered_flat<string>\" 45.700000 \n",
" \"robin_hood::unordered_node<string>\" 48.566667 \n",
" \"robinhoodflat\" 104.750000 \n",
" \"robinhoodnode\" 108.000000 \n",
" \"std::map<string>\" 113.566667 \n",
" \"std::unordered_map\" 205.000000 \n",
analysis in python done
2020-03-04 13:53:42 +00:00
"\n",
results update
2020-03-19 22:11:00 +00:00
" 200000 \\\n",
"TEST MAP \n",
"int_delete \"robin_hood::unordered_flat<int>\" 9.000000 \n",
" \"robin_hood::unordered_node<int>\" 11.100000 \n",
" \"robinhoodflat\" 35.000000 \n",
" \"robinhoodnode 43.500000 \n",
" \"std::map<int>\" 54.200000 \n",
" \"std::unordered_map\" 147.000000 \n",
"int_insert \"robin_hood::unordered_flat<int>\" 31.466667 \n",
" \"robin_hood::unordered_node<int>\" 36.200000 \n",
" \"robinhoodflat\" 110.750000 \n",
" \"robinhoodnode 120.000000 \n",
" \"std::map<int>\" 55.433333 \n",
" \"std::unordered_map\" 221.000000 \n",
"int_nosucc_lookup \"robin_hood::unordered_flat<int>\" 199.733333 \n",
" \"robin_hood::unordered_node<int>\" 265.833333 \n",
" \"robinhoodflat\" 750.250000 \n",
" \"robinhoodnode 949.500000 \n",
" \"std::map<int>\" 251.966667 \n",
" \"std::unordered_map\" 991.250000 \n",
"int_succ_lookup \"robin_hood::unordered_flat<int>\" 12.100000 \n",
" \"robin_hood::unordered_node<int>\" 17.033333 \n",
" \"robinhoodflat\" 40.250000 \n",
" \"robinhoodnode 43.250000 \n",
" \"std::map<int>\" 17.600000 \n",
" \"std::unordered_map\" 92.750000 \n",
"string_delete \"robin_hood::unordered_flat<string>\" 70.966667 \n",
" \"robin_hood::unordered_node<string>\" 57.633333 \n",
" \"robinhoodflat\" 190.750000 \n",
" \"robinhoodnode\" 140.250000 \n",
" \"std::map<string>\" 171.633333 \n",
" \"std::unordered_map\" 304.000000 \n",
"string_insert \"robin_hood::unordered_flat<string>\" 163.566667 \n",
" \"robin_hood::unordered_node<string>\" 66.366667 \n",
" \"robinhoodflat\" 993.500000 \n",
" \"robinhoodnode\" 352.250000 \n",
" \"std::map<string>\" 168.633333 \n",
" \"std::unordered_map\" 511.750000 \n",
"string_nosucc_lookup \"robin_hood::unordered_flat<string>\" 858.400000 \n",
" \"robin_hood::unordered_node<string>\" 910.000000 \n",
" \"robinhoodflat\" 4445.500000 \n",
" \"robinhoodnode\" 1873.000000 \n",
" \"std::map<string>\" 530.066667 \n",
" \"std::unordered_map\" 1064.500000 \n",
"string_succ_lookup \"robin_hood::unordered_flat<string>\" 56.000000 \n",
" \"robin_hood::unordered_node<string>\" 79.666667 \n",
" \"robinhoodflat\" 110.000000 \n",
" \"robinhoodnode\" 128.000000 \n",
" \"std::map<string>\" 161.800000 \n",
" \"std::unordered_map\" 246.500000 \n",
analysis in python done
2020-03-04 13:53:42 +00:00
"\n",
results update
2020-03-19 22:11:00 +00:00
" 250000 \\\n",
"TEST MAP \n",
"int_delete \"robin_hood::unordered_flat<int>\" 12.066667 \n",
" \"robin_hood::unordered_node<int>\" 13.800000 \n",
" \"robinhoodflat\" 40.750000 \n",
" \"robinhoodnode 48.000000 \n",
" \"std::map<int>\" 58.533333 \n",
" \"std::unordered_map\" 148.500000 \n",
"int_insert \"robin_hood::unordered_flat<int>\" 13.100000 \n",
" \"robin_hood::unordered_node<int>\" 18.100000 \n",
" \"robinhoodflat\" 67.500000 \n",
" \"robinhoodnode 72.500000 \n",
" \"std::map<int>\" 58.533333 \n",
" \"std::unordered_map\" 227.000000 \n",
"int_nosucc_lookup \"robin_hood::unordered_flat<int>\" 14.700000 \n",
" \"robin_hood::unordered_node<int>\" 18.333333 \n",
" \"robinhoodflat\" 79.750000 \n",
" \"robinhoodnode 83.500000 \n",
" \"std::map<int>\" 331.233333 \n",
" \"std::unordered_map\" 1211.750000 \n",
"int_succ_lookup \"robin_hood::unordered_flat<int>\" 6.533333 \n",
" \"robin_hood::unordered_node<int>\" 10.033333 \n",
" \"robinhoodflat\" 34.750000 \n",
" \"robinhoodnode 35.250000 \n",
" \"std::map<int>\" 18.633333 \n",
" \"std::unordered_map\" 107.000000 \n",
"string_delete \"robin_hood::unordered_flat<string>\" 41.933333 \n",
" \"robin_hood::unordered_node<string>\" 23.966667 \n",
" \"robinhoodflat\" 186.500000 \n",
" \"robinhoodnode\" 91.500000 \n",
" \"std::map<string>\" 207.366667 \n",
" \"std::unordered_map\" 364.750000 \n",
"string_insert \"robin_hood::unordered_flat<string>\" 116.633333 \n",
" \"robin_hood::unordered_node<string>\" 58.966667 \n",
" \"robinhoodflat\" 444.250000 \n",
" \"robinhoodnode\" 309.500000 \n",
" \"std::map<string>\" 195.966667 \n",
" \"std::unordered_map\" 538.750000 \n",
"string_nosucc_lookup \"robin_hood::unordered_flat<string>\" 103.733333 \n",
" \"robin_hood::unordered_node<string>\" 46.933333 \n",
" \"robinhoodflat\" 370.500000 \n",
" \"robinhoodnode\" 203.250000 \n",
" \"std::map<string>\" 806.966667 \n",
" \"std::unordered_map\" 1560.000000 \n",
"string_succ_lookup \"robin_hood::unordered_flat<string>\" 78.700000 \n",
" \"robin_hood::unordered_node<string>\" 102.300000 \n",
" \"robinhoodflat\" 128.250000 \n",
" \"robinhoodnode\" 150.750000 \n",
" \"std::map<string>\" 191.100000 \n",
" \"std::unordered_map\" 277.500000 \n",
analysis in python done
2020-03-04 13:53:42 +00:00
"\n",
" 300000 \\\n",
"TEST MAP \n",
results update
2020-03-19 22:11:00 +00:00
"int_delete \"robin_hood::unordered_flat<int>\" 15.866667 \n",
" \"robin_hood::unordered_node<int>\" 17.233333 \n",
" \"robinhoodflat\" 47.500000 \n",
" \"robinhoodnode 56.000000 \n",
" \"std::map<int>\" 55.000000 \n",
" \"std::unordered_map\" 164.750000 \n",
"int_insert \"robin_hood::unordered_flat<int>\" 17.466667 \n",
" \"robin_hood::unordered_node<int>\" 22.866667 \n",
" \"robinhoodflat\" 74.250000 \n",
" \"robinhoodnode 81.500000 \n",
" \"std::map<int>\" 58.166667 \n",
" \"std::unordered_map\" 230.750000 \n",
"int_nosucc_lookup \"robin_hood::unordered_flat<int>\" 19.633333 \n",
" \"robin_hood::unordered_node<int>\" 23.133333 \n",
" \"robinhoodflat\" 96.750000 \n",
" \"robinhoodnode 102.250000 \n",
" \"std::map<int>\" 61.200000 \n",
" \"std::unordered_map\" 232.500000 \n",
"int_succ_lookup \"robin_hood::unordered_flat<int>\" 8.033333 \n",
" \"robin_hood::unordered_node<int>\" 12.000000 \n",
" \"robinhoodflat\" 36.500000 \n",
" \"robinhoodnode 38.500000 \n",
" \"std::map<int>\" 18.433333 \n",
" \"std::unordered_map\" 107.750000 \n",
"string_delete \"robin_hood::unordered_flat<string>\" 56.766667 \n",
" \"robin_hood::unordered_node<string>\" 29.166667 \n",
" \"robinhoodflat\" 267.000000 \n",
" \"robinhoodnode\" 101.750000 \n",
" \"std::map<string>\" 138.600000 \n",
" \"std::unordered_map\" 302.000000 \n",
"string_insert \"robin_hood::unordered_flat<string>\" 131.833333 \n",
" \"robin_hood::unordered_node<string>\" 68.700000 \n",
" \"robinhoodflat\" 541.500000 \n",
" \"robinhoodnode\" 325.000000 \n",
" \"std::map<string>\" 210.666667 \n",
" \"std::unordered_map\" 560.000000 \n",
"string_nosucc_lookup \"robin_hood::unordered_flat<string>\" 117.266667 \n",
" \"robin_hood::unordered_node<string>\" 53.966667 \n",
" \"robinhoodflat\" 461.750000 \n",
" \"robinhoodnode\" 227.250000 \n",
" \"std::map<string>\" 181.933333 \n",
" \"std::unordered_map\" 417.500000 \n",
"string_succ_lookup \"robin_hood::unordered_flat<string>\" 82.333333 \n",
" \"robin_hood::unordered_node<string>\" 113.000000 \n",
" \"robinhoodflat\" 127.500000 \n",
" \"robinhoodnode\" 165.250000 \n",
" \"std::map<string>\" 209.766667 \n",
" \"std::unordered_map\" 293.500000 \n",
analysis in python done
2020-03-04 13:53:42 +00:00
"\n",
" 350000 \\\n",
"TEST MAP \n",
results update
2020-03-19 22:11:00 +00:00
"int_delete \"robin_hood::unordered_flat<int>\" 21.533333 \n",
" \"robin_hood::unordered_node<int>\" 23.300000 \n",
" \"robinhoodflat\" 59.750000 \n",
" \"robinhoodnode 67.750000 \n",
" \"std::map<int>\" 77.666667 \n",
" \"std::unordered_map\" 176.000000 \n",
"int_insert \"robin_hood::unordered_flat<int>\" 25.400000 \n",
" \"robin_hood::unordered_node<int>\" 30.000000 \n",
" \"robinhoodflat\" 94.000000 \n",
" \"robinhoodnode 98.000000 \n",
" \"std::map<int>\" 63.066667 \n",
" \"std::unordered_map\" 228.000000 \n",
"int_nosucc_lookup \"robin_hood::unordered_flat<int>\" 26.700000 \n",
" \"robin_hood::unordered_node<int>\" 31.066667 \n",
" \"robinhoodflat\" 110.250000 \n",
" \"robinhoodnode 113.750000 \n",
" \"std::map<int>\" 490.266667 \n",
" \"std::unordered_map\" 1723.000000 \n",
"int_succ_lookup \"robin_hood::unordered_flat<int>\" 10.500000 \n",
" \"robin_hood::unordered_node<int>\" 14.866667 \n",
" \"robinhoodflat\" 37.750000 \n",
" \"robinhoodnode 41.750000 \n",
" \"std::map<int>\" 20.166667 \n",
" \"std::unordered_map\" 101.750000 \n",
"string_delete \"robin_hood::unordered_flat<string>\" 83.300000 \n",
" \"robin_hood::unordered_node<string>\" 34.700000 \n",
" \"robinhoodflat\" 420.250000 \n",
" \"robinhoodnode\" 127.000000 \n",
" \"std::map<string>\" 261.000000 \n",
" \"std::unordered_map\" 425.500000 \n",
"string_insert \"robin_hood::unordered_flat<string>\" 162.300000 \n",
" \"robin_hood::unordered_node<string>\" 83.033333 \n",
" \"robinhoodflat\" 702.000000 \n",
" \"robinhoodnode\" 357.250000 \n",
" \"std::map<string>\" 235.933333 \n",
" \"std::unordered_map\" 566.000000 \n",
"string_nosucc_lookup \"robin_hood::unordered_flat<string>\" 144.066667 \n",
" \"robin_hood::unordered_node<string>\" 62.700000 \n",
" \"robinhoodflat\" 649.750000 \n",
" \"robinhoodnode\" 242.750000 \n",
" \"std::map<string>\" 1294.066667 \n",
" \"std::unordered_map\" 2483.000000 \n",
"string_succ_lookup \"robin_hood::unordered_flat<string>\" 84.500000 \n",
" \"robin_hood::unordered_node<string>\" 121.600000 \n",
" \"robinhoodflat\" 131.750000 \n",
" \"robinhoodnode\" 175.500000 \n",
" \"std::map<string>\" 225.066667 \n",
" \"std::unordered_map\" 303.250000 \n",
analysis in python done
2020-03-04 13:53:42 +00:00
"\n",
results update
2020-03-19 22:11:00 +00:00
" 400000 \\\n",
"TEST MAP \n",
"int_delete \"robin_hood::unordered_flat<int>\" 29.833333 \n",
" \"robin_hood::unordered_node<int>\" 32.400000 \n",
" \"robinhoodflat\" 82.250000 \n",
" \"robinhoodnode 98.500000 \n",
" \"std::map<int>\" 60.866667 \n",
" \"std::unordered_map\" 178.500000 \n",
"int_insert \"robin_hood::unordered_flat<int>\" 33.833333 \n",
" \"robin_hood::unordered_node<int>\" 39.300000 \n",
" \"robinhoodflat\" 116.250000 \n",
" \"robinhoodnode 126.250000 \n",
" \"std::map<int>\" 71.133333 \n",
" \"std::unordered_map\" 241.750000 \n",
"int_nosucc_lookup \"robin_hood::unordered_flat<int>\" 36.900000 \n",
" \"robin_hood::unordered_node<int>\" 41.900000 \n",
" \"robinhoodflat\" 140.000000 \n",
" \"robinhoodnode 155.750000 \n",
" \"std::map<int>\" 74.766667 \n",
" \"std::unordered_map\" 248.750000 \n",
"int_succ_lookup \"robin_hood::unordered_flat<int>\" 13.000000 \n",
" \"robin_hood::unordered_node<int>\" 17.833333 \n",
" \"robinhoodflat\" 43.000000 \n",
" \"robinhoodnode 47.250000 \n",
" \"std::map<int>\" 23.833333 \n",
" \"std::unordered_map\" 131.750000 \n",
"string_delete \"robin_hood::unordered_flat<string>\" 139.500000 \n",
" \"robin_hood::unordered_node<string>\" 43.466667 \n",
" \"robinhoodflat\" 905.500000 \n",
" \"robinhoodnode\" 157.250000 \n",
" \"std::map<string>\" 173.533333 \n",
" \"std::unordered_map\" 344.000000 \n",
"string_insert \"robin_hood::unordered_flat<string>\" 224.466667 \n",
" \"robin_hood::unordered_node<string>\" 101.600000 \n",
" \"robinhoodflat\" 1070.500000 \n",
" \"robinhoodnode\" 403.750000 \n",
" \"std::map<string>\" 246.700000 \n",
" \"std::unordered_map\" 577.500000 \n",
"string_nosucc_lookup \"robin_hood::unordered_flat<string>\" 202.766667 \n",
" \"robin_hood::unordered_node<string>\" 77.733333 \n",
" \"robinhoodflat\" 1103.250000 \n",
" \"robinhoodnode\" 282.250000 \n",
" \"std::map<string>\" 208.200000 \n",
" \"std::unordered_map\" 438.000000 \n",
"string_succ_lookup \"robin_hood::unordered_flat<string>\" 83.400000 \n",
" \"robin_hood::unordered_node<string>\" 126.266667 \n",
" \"robinhoodflat\" 136.500000 \n",
" \"robinhoodnode\" 181.000000 \n",
" \"std::map<string>\" 236.400000 \n",
" \"std::unordered_map\" 322.000000 \n",
analysis in python done
2020-03-04 13:53:42 +00:00
"\n",
" 500000 \\\n",
"TEST MAP \n",
results update
2020-03-19 22:11:00 +00:00
"int_delete \"robin_hood::unordered_flat<int>\" 12.033333 \n",
" \"robin_hood::unordered_node<int>\" 14.533333 \n",
" \"robinhoodflat\" 41.000000 \n",
" \"robinhoodnode 52.000000 \n",
" \"std::map<int>\" 69.266667 \n",
" \"std::unordered_map\" 188.000000 \n",
"int_insert \"robin_hood::unordered_flat<int>\" 13.733333 \n",
" \"robin_hood::unordered_node<int>\" 19.700000 \n",
" \"robinhoodflat\" 64.250000 \n",
" \"robinhoodnode 74.750000 \n",
" \"std::map<int>\" 95.233333 \n",
" \"std::unordered_map\" 267.000000 \n",
"int_nosucc_lookup \"robin_hood::unordered_flat<int>\" 15.000000 \n",
" \"robin_hood::unordered_node<int>\" 19.866667 \n",
" \"robinhoodflat\" 77.250000 \n",
" \"robinhoodnode 90.250000 \n",
" \"std::map<int>\" 99.633333 \n",
" \"std::unordered_map\" 267.250000 \n",
"int_succ_lookup \"robin_hood::unordered_flat<int>\" 6.966667 \n",
" \"robin_hood::unordered_node<int>\" 13.100000 \n",
" \"robinhoodflat\" 32.250000 \n",
" \"robinhoodnode 45.750000 \n",
" \"std::map<int>\" 32.766667 \n",
" \"std::unordered_map\" 158.000000 \n",
"string_delete \"robin_hood::unordered_flat<string>\" 48.066667 \n",
" \"robin_hood::unordered_node<string>\" 26.300000 \n",
" \"robinhoodflat\" 187.250000 \n",
" \"robinhoodnode\" 100.000000 \n",
" \"std::map<string>\" 182.000000 \n",
" \"std::unordered_map\" 341.000000 \n",
"string_insert \"robin_hood::unordered_flat<string>\" 135.933333 \n",
" \"robin_hood::unordered_node<string>\" 109.500000 \n",
" \"robinhoodflat\" 508.250000 \n",
" \"robinhoodnode\" 359.250000 \n",
" \"std::map<string>\" 259.700000 \n",
" \"std::unordered_map\" 595.500000 \n",
"string_nosucc_lookup \"robin_hood::unordered_flat<string>\" 116.433333 \n",
" \"robin_hood::unordered_node<string>\" 79.233333 \n",
" \"robinhoodflat\" 387.750000 \n",
" \"robinhoodnode\" 239.500000 \n",
" \"std::map<string>\" 219.833333 \n",
" \"std::unordered_map\" 442.500000 \n",
"string_succ_lookup \"robin_hood::unordered_flat<string>\" 96.566667 \n",
" \"robin_hood::unordered_node<string>\" 160.433333 \n",
" \"robinhoodflat\" 139.250000 \n",
" \"robinhoodnode\" 199.750000 \n",
" \"std::map<string>\" 248.933333 \n",
" \"std::unordered_map\" 324.750000 \n",
analysis in python done
2020-03-04 13:53:42 +00:00
"\n",
" 600000 ... \\\n",
"TEST MAP ... \n",
results update
2020-03-19 22:11:00 +00:00
"int_delete \"robin_hood::unordered_flat<int>\" 15.833333 ... \n",
" \"robin_hood::unordered_node<int>\" 18.066667 ... \n",
" \"robinhoodflat\" 49.000000 ... \n",
" \"robinhoodnode 59.000000 ... \n",
" \"std::map<int>\" 189.700000 ... \n",
" \"std::unordered_map\" 312.500000 ... \n",
"int_insert \"robin_hood::unordered_flat<int>\" 18.033333 ... \n",
" \"robin_hood::unordered_node<int>\" 23.633333 ... \n",
" \"robinhoodflat\" 73.750000 ... \n",
" \"robinhoodnode 82.000000 ... \n",
" \"std::map<int>\" 121.100000 ... \n",
" \"std::unordered_map\" 290.750000 ... \n",
"int_nosucc_lookup \"robin_hood::unordered_flat<int>\" 19.200000 ... \n",
" \"robin_hood::unordered_node<int>\" 24.833333 ... \n",
" \"robinhoodflat\" 88.250000 ... \n",
" \"robinhoodnode 102.250000 ... \n",
" \"std::map<int>\" 1628.166667 ... \n",
" \"std::unordered_map\" 4897.000000 ... \n",
"int_succ_lookup \"robin_hood::unordered_flat<int>\" 8.000000 ... \n",
" \"robin_hood::unordered_node<int>\" 16.266667 ... \n",
" \"robinhoodflat\" 35.500000 ... \n",
" \"robinhoodnode 58.750000 ... \n",
" \"std::map<int>\" 41.100000 ... \n",
" \"std::unordered_map\" 179.250000 ... \n",
"string_delete \"robin_hood::unordered_flat<string>\" 63.400000 ... \n",
" \"robin_hood::unordered_node<string>\" 30.800000 ... \n",
" \"robinhoodflat\" 263.500000 ... \n",
" \"robinhoodnode\" 106.250000 ... \n",
" \"std::map<string>\" 314.366667 ... \n",
" \"std::unordered_map\" 481.750000 ... \n",
"string_insert \"robin_hood::unordered_flat<string>\" 154.100000 ... \n",
" \"robin_hood::unordered_node<string>\" 115.266667 ... \n",
" \"robinhoodflat\" 590.500000 ... \n",
" \"robinhoodnode\" 377.000000 ... \n",
" \"std::map<string>\" 274.300000 ... \n",
" \"std::unordered_map\" 604.250000 ... \n",
"string_nosucc_lookup \"robin_hood::unordered_flat<string>\" 127.266667 ... \n",
" \"robin_hood::unordered_node<string>\" 84.000000 ... \n",
" \"robinhoodflat\" 478.500000 ... \n",
" \"robinhoodnode\" 252.750000 ... \n",
" \"std::map<string>\" 2729.800000 ... \n",
" \"std::unordered_map\" 4799.000000 ... \n",
"string_succ_lookup \"robin_hood::unordered_flat<string>\" 95.266667 ... \n",
" \"robin_hood::unordered_node<string>\" 163.900000 ... \n",
" \"robinhoodflat\" 141.500000 ... \n",
" \"robinhoodnode\" 204.500000 ... \n",
" \"std::map<string>\" 257.866667 ... \n",
" \"std::unordered_map\" 339.000000 ... \n",
analysis in python done
2020-03-04 13:53:42 +00:00
"\n",
" 9000000 \\\n",
"TEST MAP \n",
results update
2020-03-19 22:11:00 +00:00
"int_delete \"robin_hood::unordered_flat<int>\" 19.033333 \n",
" \"robin_hood::unordered_node<int>\" 23.066667 \n",
" \"robinhoodflat\" 55.250000 \n",
" \"robinhoodnode 75.250000 \n",
" \"std::map<int>\" 128.866667 \n",
" \"std::unordered_map\" 327.500000 \n",
"int_insert \"robin_hood::unordered_flat<int>\" 47.666667 \n",
" \"robin_hood::unordered_node<int>\" 57.666667 \n",
" \"robinhoodflat\" 153.500000 \n",
" \"robinhoodnode 173.750000 \n",
" \"std::map<int>\" 242.400000 \n",
" \"std::unordered_map\" 392.000000 \n",
"int_nosucc_lookup \"robin_hood::unordered_flat<int>\" 43.300000 \n",
" \"robin_hood::unordered_node<int>\" 57.033333 \n",
" \"robinhoodflat\" 213.250000 \n",
" \"robinhoodnode 230.250000 \n",
" \"std::map<int>\" 245.033333 \n",
" \"std::unordered_map\" 402.500000 \n",
"int_succ_lookup \"robin_hood::unordered_flat<int>\" 25.466667 \n",
" \"robin_hood::unordered_node<int>\" 57.200000 \n",
" \"robinhoodflat\" 113.500000 \n",
" \"robinhoodnode 206.000000 \n",
" \"std::map<int>\" 70.766667 \n",
" \"std::unordered_map\" 324.000000 \n",
"string_delete \"robin_hood::unordered_flat<string>\" 96.733333 \n",
" \"robin_hood::unordered_node<string>\" 47.900000 \n",
" \"robinhoodflat\" 267.500000 \n",
" \"robinhoodnode\" 199.750000 \n",
" \"std::map<string>\" 330.566667 \n",
" \"std::unordered_map\" 517.000000 \n",
"string_insert \"robin_hood::unordered_flat<string>\" 221.700000 \n",
" \"robin_hood::unordered_node<string>\" 156.033333 \n",
" \"robinhoodflat\" 671.500000 \n",
" \"robinhoodnode\" 415.500000 \n",
" \"std::map<string>\" 371.733333 \n",
" \"std::unordered_map\" 716.250000 \n",
"string_nosucc_lookup \"robin_hood::unordered_flat<string>\" 184.966667 \n",
" \"robin_hood::unordered_node<string>\" 133.166667 \n",
" \"robinhoodflat\" 538.000000 \n",
" \"robinhoodnode\" 400.500000 \n",
" \"std::map<string>\" 306.866667 \n",
" \"std::unordered_map\" 523.750000 \n",
"string_succ_lookup \"robin_hood::unordered_flat<string>\" 152.966667 \n",
" \"robin_hood::unordered_node<string>\" 233.300000 \n",
" \"robinhoodflat\" 193.250000 \n",
" \"robinhoodnode\" 267.250000 \n",
" \"std::map<string>\" 352.433333 \n",
" \"std::unordered_map\" 427.250000 \n",
analysis in python done
2020-03-04 13:53:42 +00:00
"\n",
" 10000000 \\\n",
"TEST MAP \n",
results update
2020-03-19 22:11:00 +00:00
"int_delete \"robin_hood::unordered_flat<int>\" 23.000000 \n",
" \"robin_hood::unordered_node<int>\" 27.733333 \n",
" \"robinhoodflat\" 61.500000 \n",
" \"robinhoodnode 90.750000 \n",
" \"std::map<int>\" 134.066667 \n",
" \"std::unordered_map\" 336.750000 \n",
"int_insert \"robin_hood::unordered_flat<int>\" 47.266667 \n",
" \"robin_hood::unordered_node<int>\" 66.500000 \n",
" \"robinhoodflat\" 166.750000 \n",
" \"robinhoodnode 182.500000 \n",
" \"std::map<int>\" 256.333333 \n",
" \"std::unordered_map\" 413.500000 \n",
"int_nosucc_lookup \"robin_hood::unordered_flat<int>\" 51.933333 \n",
" \"robin_hood::unordered_node<int>\" 68.366667 \n",
" \"robinhoodflat\" 222.250000 \n",
" \"robinhoodnode 245.500000 \n",
" \"std::map<int>\" 257.566667 \n",
" \"std::unordered_map\" 419.250000 \n",
"int_succ_lookup \"robin_hood::unordered_flat<int>\" 27.200000 \n",
" \"robin_hood::unordered_node<int>\" 58.533333 \n",
" \"robinhoodflat\" 116.000000 \n",
" \"robinhoodnode 209.500000 \n",
" \"std::map<int>\" 73.966667 \n",
" \"std::unordered_map\" 332.750000 \n",
"string_delete \"robin_hood::unordered_flat<string>\" 114.300000 \n",
" \"robin_hood::unordered_node<string>\" 58.033333 \n",
" \"robinhoodflat\" 350.250000 \n",
" \"robinhoodnode\" 208.500000 \n",
" \"std::map<string>\" 345.366667 \n",
" \"std::unordered_map\" 539.750000 \n",
"string_insert \"robin_hood::unordered_flat<string>\" 234.566667 \n",
" \"robin_hood::unordered_node<string>\" 168.933333 \n",
" \"robinhoodflat\" 738.750000 \n",
" \"robinhoodnode\" 441.000000 \n",
" \"std::map<string>\" 380.833333 \n",
" \"std::unordered_map\" 725.250000 \n",
"string_nosucc_lookup \"robin_hood::unordered_flat<string>\" 192.800000 \n",
" \"robin_hood::unordered_node<string>\" 144.300000 \n",
" \"robinhoodflat\" 622.750000 \n",
" \"robinhoodnode\" 417.000000 \n",
" \"std::map<string>\" 314.700000 \n",
" \"std::unordered_map\" 542.750000 \n",
"string_succ_lookup \"robin_hood::unordered_flat<string>\" 155.266667 \n",
" \"robin_hood::unordered_node<string>\" 240.866667 \n",
" \"robinhoodflat\" 198.500000 \n",
" \"robinhoodnode\" 278.250000 \n",
" \"std::map<string>\" 359.533333 \n",
" \"std::unordered_map\" 442.250000 \n",
analysis in python done
2020-03-04 13:53:42 +00:00
"\n",
" 15000000 \\\n",
"TEST MAP \n",
results update
2020-03-19 22:11:00 +00:00
"int_delete \"robin_hood::unordered_flat<int>\" 15.633333 \n",
" \"robin_hood::unordered_node<int>\" 20.900000 \n",
" \"robinhoodflat\" 57.750000 \n",
" \"robinhoodnode 73.250000 \n",
" \"std::map<int>\" 131.566667 \n",
" \"std::unordered_map\" 298.750000 \n",
"int_insert \"robin_hood::unordered_flat<int>\" 33.366667 \n",
" \"robin_hood::unordered_node<int>\" 52.633333 \n",
" \"robinhoodflat\" 152.000000 \n",
" \"robinhoodnode 161.250000 \n",
" \"std::map<int>\" 253.066667 \n",
" \"std::unordered_map\" 406.000000 \n",
"int_nosucc_lookup \"robin_hood::unordered_flat<int>\" 37.600000 \n",
" \"robin_hood::unordered_node<int>\" 50.966667 \n",
" \"robinhoodflat\" 224.500000 \n",
" \"robinhoodnode 236.750000 \n",
" \"std::map<int>\" 254.733333 \n",
" \"std::unordered_map\" 414.000000 \n",
"int_succ_lookup \"robin_hood::unordered_flat<int>\" 25.133333 \n",
" \"robin_hood::unordered_node<int>\" 59.466667 \n",
" \"robinhoodflat\" 121.250000 \n",
" \"robinhoodnode 213.750000 \n",
" \"std::map<int>\" 72.166667 \n",
" \"std::unordered_map\" 334.250000 \n",
"string_delete \"robin_hood::unordered_flat<string>\" 76.666667 \n",
" \"robin_hood::unordered_node<string>\" 52.633333 \n",
" \"robinhoodflat\" 210.750000 \n",
" \"robinhoodnode\" 144.750000 \n",
" \"std::map<string>\" 377.800000 \n",
" \"std::unordered_map\" 570.250000 \n",
"string_insert \"robin_hood::unordered_flat<string>\" 208.900000 \n",
" \"robin_hood::unordered_node<string>\" 172.733333 \n",
" \"robinhoodflat\" 610.750000 \n",
" \"robinhoodnode\" 463.250000 \n",
" \"std::map<string>\" 398.800000 \n",
" \"std::unordered_map\" 736.500000 \n",
"string_nosucc_lookup \"robin_hood::unordered_flat<string>\" 176.266667 \n",
" \"robin_hood::unordered_node<string>\" 130.733333 \n",
" \"robinhoodflat\" 487.750000 \n",
" \"robinhoodnode\" 377.500000 \n",
" \"std::map<string>\" 335.333333 \n",
" \"std::unordered_map\" 564.000000 \n",
"string_succ_lookup \"robin_hood::unordered_flat<string>\" 163.900000 \n",
" \"robin_hood::unordered_node<string>\" 258.266667 \n",
" \"robinhoodflat\" 204.750000 \n",
" \"robinhoodnode\" 287.000000 \n",
" \"std::map<string>\" 385.633333 \n",
" \"std::unordered_map\" 466.250000 \n",
analysis in python done
2020-03-04 13:53:42 +00:00
"\n",
" 20000000 \\\n",
"TEST MAP \n",
results update
2020-03-19 22:11:00 +00:00
"int_delete \"robin_hood::unordered_flat<int>\" 23.466667 \n",
" \"robin_hood::unordered_node<int>\" 28.933333 \n",
" \"robinhoodflat\" 63.250000 \n",
" \"robinhoodnode 87.000000 \n",
" \"std::map<int>\" 135.300000 \n",
" \"std::unordered_map\" 306.750000 \n",
"int_insert \"robin_hood::unordered_flat<int>\" 49.066667 \n",
" \"robin_hood::unordered_node<int>\" 71.033333 \n",
" \"robinhoodflat\" 177.250000 \n",
" \"robinhoodnode 197.000000 \n",
" \"std::map<int>\" 251.300000 \n",
" \"std::unordered_map\" 398.500000 \n",
"int_nosucc_lookup \"robin_hood::unordered_flat<int>\" 53.966667 \n",
" \"robin_hood::unordered_node<int>\" 68.733333 \n",
" \"robinhoodflat\" 239.250000 \n",
" \"robinhoodnode 253.000000 \n",
" \"std::map<int>\" 253.566667 \n",
" \"std::unordered_map\" 406.000000 \n",
"int_succ_lookup \"robin_hood::unordered_flat<int>\" 28.133333 \n",
" \"robin_hood::unordered_node<int>\" 61.533333 \n",
" \"robinhoodflat\" 120.750000 \n",
" \"robinhoodnode 218.750000 \n",
" \"std::map<int>\" 72.166667 \n",
" \"std::unordered_map\" 334.000000 \n",
"string_delete \"robin_hood::unordered_flat<string>\" 122.866667 \n",
" \"robin_hood::unordered_node<string>\" 73.033333 \n",
" \"robinhoodflat\" 378.500000 \n",
" \"robinhoodnode\" 198.500000 \n",
" \"std::map<string>\" 391.266667 \n",
" \"std::unordered_map\" 586.250000 \n",
"string_insert \"robin_hood::unordered_flat<string>\" 238.900000 \n",
" \"robin_hood::unordered_node<string>\" 184.100000 \n",
" \"robinhoodflat\" 761.750000 \n",
" \"robinhoodnode\" 451.500000 \n",
" \"std::map<string>\" 407.800000 \n",
" \"std::unordered_map\" 810.000000 \n",
"string_nosucc_lookup \"robin_hood::unordered_flat<string>\" 210.400000 \n",
" \"robin_hood::unordered_node<string>\" 153.233333 \n",
" \"robinhoodflat\" 650.750000 \n",
" \"robinhoodnode\" 414.250000 \n",
" \"std::map<string>\" 343.333333 \n",
" \"std::unordered_map\" 613.250000 \n",
"string_succ_lookup \"robin_hood::unordered_flat<string>\" 171.333333 \n",
" \"robin_hood::unordered_node<string>\" 272.933333 \n",
" \"robinhoodflat\" 215.500000 \n",
" \"robinhoodnode\" 307.250000 \n",
" \"std::map<string>\" 399.200000 \n",
" \"std::unordered_map\" 482.000000 \n",
analysis in python done
2020-03-04 13:53:42 +00:00
"\n",
results update
2020-03-19 22:11:00 +00:00
" 25000000 \\\n",
"TEST MAP \n",
"int_delete \"robin_hood::unordered_flat<int>\" 45.933333 \n",
" \"robin_hood::unordered_node<int>\" 56.266667 \n",
" \"robinhoodflat\" 122.750000 \n",
" \"robinhoodnode 154.250000 \n",
" \"std::map<int>\" 139.566667 \n",
" \"std::unordered_map\" 340.250000 \n",
"int_insert \"robin_hood::unordered_flat<int>\" 103.266667 \n",
" \"robin_hood::unordered_node<int>\" 129.100000 \n",
" \"robinhoodflat\" 261.750000 \n",
" \"robinhoodnode 286.500000 \n",
" \"std::map<int>\" 251.100000 \n",
" \"std::unordered_map\" 403.000000 \n",
"int_nosucc_lookup \"robin_hood::unordered_flat<int>\" 111.266667 \n",
" \"robin_hood::unordered_node<int>\" 130.166667 \n",
" \"robinhoodflat\" 293.500000 \n",
" \"robinhoodnode 307.000000 \n",
" \"std::map<int>\" 253.400000 \n",
" \"std::unordered_map\" 409.000000 \n",
"int_succ_lookup \"robin_hood::unordered_flat<int>\" 36.766667 \n",
" \"robin_hood::unordered_node<int>\" 72.600000 \n",
" \"robinhoodflat\" 152.500000 \n",
" \"robinhoodnode 250.250000 \n",
" \"std::map<int>\" 72.466667 \n",
" \"std::unordered_map\" 337.000000 \n",
"string_delete \"robin_hood::unordered_flat<string>\" 232.700000 \n",
" \"robin_hood::unordered_node<string>\" 135.300000 \n",
" \"robinhoodflat\" 815.000000 \n",
" \"robinhoodnode\" 278.500000 \n",
" \"std::map<string>\" 409.000000 \n",
" \"std::unordered_map\" 605.000000 \n",
"string_insert \"robin_hood::unordered_flat<string>\" 394.100000 \n",
" \"robin_hood::unordered_node<string>\" 250.333333 \n",
" \"robinhoodflat\" 1197.250000 \n",
" \"robinhoodnode\" 553.000000 \n",
" \"std::map<string>\" 419.900000 \n",
" \"std::unordered_map\" 812.000000 \n",
"string_nosucc_lookup \"robin_hood::unordered_flat<string>\" 342.733333 \n",
" \"robin_hood::unordered_node<string>\" 203.833333 \n",
" \"robinhoodflat\" 1090.250000 \n",
" \"robinhoodnode\" 466.500000 \n",
" \"std::map<string>\" 348.466667 \n",
" \"std::unordered_map\" 616.000000 \n",
"string_succ_lookup \"robin_hood::unordered_flat<string>\" 182.533333 \n",
" \"robin_hood::unordered_node<string>\" 285.733333 \n",
" \"robinhoodflat\" 265.750000 \n",
" \"robinhoodnode\" 353.750000 \n",
" \"std::map<string>\" 409.733333 \n",
" \"std::unordered_map\" 494.250000 \n",
analysis in python done
2020-03-04 13:53:42 +00:00
"\n",
" 30000000 \\\n",
"TEST MAP \n",
results update
2020-03-19 22:11:00 +00:00
"int_delete \"robin_hood::unordered_flat<int>\" 16.566667 \n",
" \"robin_hood::unordered_node<int>\" 23.100000 \n",
" \"robinhoodflat\" 54.500000 \n",
" \"robinhoodnode 75.750000 \n",
" \"std::map<int>\" 154.800000 \n",
" \"std::unordered_map\" 351.000000 \n",
"int_insert \"robin_hood::unordered_flat<int>\" 39.666667 \n",
" \"robin_hood::unordered_node<int>\" 74.533333 \n",
" \"robinhoodflat\" 170.250000 \n",
" \"robinhoodnode 187.000000 \n",
" \"std::map<int>\" 292.166667 \n",
" \"std::unordered_map\" 433.750000 \n",
"int_nosucc_lookup \"robin_hood::unordered_flat<int>\" 41.600000 \n",
" \"robin_hood::unordered_node<int>\" 57.433333 \n",
" \"robinhoodflat\" 241.750000 \n",
" \"robinhoodnode 251.750000 \n",
" \"std::map<int>\" 273.366667 \n",
" \"std::unordered_map\" 424.250000 \n",
"int_succ_lookup \"robin_hood::unordered_flat<int>\" 31.400000 \n",
" \"robin_hood::unordered_node<int>\" 75.133333 \n",
" \"robinhoodflat\" 131.750000 \n",
" \"robinhoodnode 232.250000 \n",
" \"std::map<int>\" 84.733333 \n",
" \"std::unordered_map\" 356.250000 \n",
"string_delete \"robin_hood::unordered_flat<string>\" 82.133333 \n",
" \"robin_hood::unordered_node<string>\" 62.900000 \n",
" \"robinhoodflat\" 228.750000 \n",
" \"robinhoodnode\" 188.500000 \n",
" \"std::map<string>\" 426.833333 \n",
" \"std::unordered_map\" 639.750000 \n",
"string_insert \"robin_hood::unordered_flat<string>\" 216.866667 \n",
" \"robin_hood::unordered_node<string>\" 179.966667 \n",
" \"robinhoodflat\" 622.000000 \n",
" \"robinhoodnode\" 424.000000 \n",
" \"std::map<string>\" 438.633333 \n",
" \"std::unordered_map\" 818.500000 \n",
"string_nosucc_lookup \"robin_hood::unordered_flat<string>\" 191.433333 \n",
" \"robin_hood::unordered_node<string>\" 139.900000 \n",
" \"robinhoodflat\" 507.500000 \n",
" \"robinhoodnode\" 402.500000 \n",
" \"std::map<string>\" 362.233333 \n",
" \"std::unordered_map\" 639.750000 \n",
"string_succ_lookup \"robin_hood::unordered_flat<string>\" 176.500000 \n",
" \"robin_hood::unordered_node<string>\" 288.500000 \n",
" \"robinhoodflat\" 216.250000 \n",
" \"robinhoodnode\" 321.000000 \n",
" \"std::map<string>\" 426.500000 \n",
" \"std::unordered_map\" 508.500000 \n",
analysis in python done
2020-03-04 13:53:42 +00:00
"\n",
" 35000000 \\\n",
"TEST MAP \n",
results update
2020-03-19 22:11:00 +00:00
"int_delete \"robin_hood::unordered_flat<int>\" 19.566667 \n",
" \"robin_hood::unordered_node<int>\" 26.166667 \n",
" \"robinhoodflat\" 67.500000 \n",
" \"robinhoodnode 83.250000 \n",
" \"std::map<int>\" 164.200000 \n",
" \"std::unordered_map\" 333.250000 \n",
"int_insert \"robin_hood::unordered_flat<int>\" 46.866667 \n",
" \"robin_hood::unordered_node<int>\" 83.533333 \n",
" \"robinhoodflat\" 188.750000 \n",
" \"robinhoodnode 223.000000 \n",
" \"std::map<int>\" 303.200000 \n",
" \"std::unordered_map\" 482.500000 \n",
"int_nosucc_lookup \"robin_hood::unordered_flat<int>\" 47.366667 \n",
" \"robin_hood::unordered_node<int>\" 63.000000 \n",
" \"robinhoodflat\" 255.500000 \n",
" \"robinhoodnode 268.250000 \n",
" \"std::map<int>\" 278.166667 \n",
" \"std::unordered_map\" 446.750000 \n",
"int_succ_lookup \"robin_hood::unordered_flat<int>\" 33.066667 \n",
" \"robin_hood::unordered_node<int>\" 77.466667 \n",
" \"robinhoodflat\" 137.000000 \n",
" \"robinhoodnode 246.000000 \n",
" \"std::map<int>\" 89.033333 \n",
" \"std::unordered_map\" 369.750000 \n",
"string_delete \"robin_hood::unordered_flat<string>\" 100.233333 \n",
" \"robin_hood::unordered_node<string>\" 59.100000 \n",
" \"robinhoodflat\" 302.250000 \n",
" \"robinhoodnode\" 178.500000 \n",
" \"std::map<string>\" 437.366667 \n",
" \"std::unordered_map\" 680.250000 \n",
"string_insert \"robin_hood::unordered_flat<string>\" 226.166667 \n",
" \"robin_hood::unordered_node<string>\" 196.600000 \n",
" \"robinhoodflat\" 681.000000 \n",
" \"robinhoodnode\" 501.500000 \n",
" \"std::map<string>\" 448.633333 \n",
" \"std::unordered_map\" 843.500000 \n",
"string_nosucc_lookup \"robin_hood::unordered_flat<string>\" 201.600000 \n",
" \"robin_hood::unordered_node<string>\" 136.466667 \n",
" \"robinhoodflat\" 570.750000 \n",
" \"robinhoodnode\" 362.750000 \n",
" \"std::map<string>\" 371.300000 \n",
" \"std::unordered_map\" 647.250000 \n",
"string_succ_lookup \"robin_hood::unordered_flat<string>\" 178.400000 \n",
" \"robin_hood::unordered_node<string>\" 292.266667 \n",
" \"robinhoodflat\" 218.750000 \n",
" \"robinhoodnode\" 332.000000 \n",
" \"std::map<string>\" 441.966667 \n",
" \"std::unordered_map\" 528.750000 \n",
analysis in python done
2020-03-04 13:53:42 +00:00
"\n",
" 40000000 \\\n",
"TEST MAP \n",
results update
2020-03-19 22:11:00 +00:00
"int_delete \"robin_hood::unordered_flat<int>\" 24.233333 \n",
" \"robin_hood::unordered_node<int>\" 31.200000 \n",
" \"robinhoodflat\" 67.000000 \n",
" \"robinhoodnode 95.000000 \n",
" \"std::map<int>\" 161.700000 \n",
" \"std::unordered_map\" 410.500000 \n",
"int_insert \"robin_hood::unordered_flat<int>\" 59.833333 \n",
" \"robin_hood::unordered_node<int>\" 99.566667 \n",
" \"robinhoodflat\" 215.000000 \n",
" \"robinhoodnode 246.000000 \n",
" \"std::map<int>\" 306.166667 \n",
" \"std::unordered_map\" 503.000000 \n",
"int_nosucc_lookup \"robin_hood::unordered_flat<int>\" 58.800000 \n",
" \"robin_hood::unordered_node<int>\" 75.966667 \n",
" \"robinhoodflat\" 266.250000 \n",
" \"robinhoodnode 280.250000 \n",
" \"std::map<int>\" 278.733333 \n",
" \"std::unordered_map\" 459.000000 \n",
"int_succ_lookup \"robin_hood::unordered_flat<int>\" 35.700000 \n",
" \"robin_hood::unordered_node<int>\" 80.000000 \n",
" \"robinhoodflat\" 143.500000 \n",
" \"robinhoodnode 250.000000 \n",
" \"std::map<int>\" 91.266667 \n",
" \"std::unordered_map\" 395.250000 \n",
"string_delete \"robin_hood::unordered_flat<string>\" 128.500000 \n",
" \"robin_hood::unordered_node<string>\" 85.266667 \n",
" \"robinhoodflat\" 390.250000 \n",
" \"robinhoodnode\" 254.000000 \n",
" \"std::map<string>\" 448.166667 \n",
" \"std::unordered_map\" 644.250000 \n",
"string_insert \"robin_hood::unordered_flat<string>\" 245.700000 \n",
" \"robin_hood::unordered_node<string>\" 207.166667 \n",
" \"robinhoodflat\" 788.750000 \n",
" \"robinhoodnode\" 528.500000 \n",
" \"std::map<string>\" 463.500000 \n",
" \"std::unordered_map\" 838.750000 \n",
"string_nosucc_lookup \"robin_hood::unordered_flat<string>\" 223.566667 \n",
" \"robin_hood::unordered_node<string>\" 159.500000 \n",
" \"robinhoodflat\" 681.500000 \n",
" \"robinhoodnode\" 431.500000 \n",
" \"std::map<string>\" 376.066667 \n",
" \"std::unordered_map\" 647.500000 \n",
"string_succ_lookup \"robin_hood::unordered_flat<string>\" 182.133333 \n",
" \"robin_hood::unordered_node<string>\" 296.700000 \n",
" \"robinhoodflat\" 232.250000 \n",
" \"robinhoodnode\" 338.500000 \n",
" \"std::map<string>\" 463.000000 \n",
" \"std::unordered_map\" 531.250000 \n",
analysis in python done
2020-03-04 13:53:42 +00:00
"\n",
" 45000000 \\\n",
"TEST MAP \n",
results update
2020-03-19 22:11:00 +00:00
"int_delete \"robin_hood::unordered_flat<int>\" 32.900000 \n",
" \"robin_hood::unordered_node<int>\" 41.900000 \n",
" \"robinhoodflat\" 98.750000 \n",
" \"robinhoodnode 118.750000 \n",
" \"std::map<int>\" 166.400000 \n",
" \"std::unordered_map\" 348.750000 \n",
"int_insert \"robin_hood::unordered_flat<int>\" 85.566667 \n",
" \"robin_hood::unordered_node<int>\" 126.200000 \n",
" \"robinhoodflat\" 259.250000 \n",
" \"robinhoodnode 291.000000 \n",
" \"std::map<int>\" 317.300000 \n",
" \"std::unordered_map\" 504.250000 \n",
"int_nosucc_lookup \"robin_hood::unordered_flat<int>\" 82.400000 \n",
" \"robin_hood::unordered_node<int>\" 102.166667 \n",
" \"robinhoodflat\" 285.000000 \n",
" \"robinhoodnode 297.500000 \n",
" \"std::map<int>\" 288.666667 \n",
" \"std::unordered_map\" 458.000000 \n",
"int_succ_lookup \"robin_hood::unordered_flat<int>\" 38.766667 \n",
" \"robin_hood::unordered_node<int>\" 82.933333 \n",
" \"robinhoodflat\" 148.500000 \n",
" \"robinhoodnode 259.000000 \n",
" \"std::map<int>\" 94.566667 \n",
" \"std::unordered_map\" 388.250000 \n",
"string_delete \"robin_hood::unordered_flat<string>\" 172.533333 \n",
" \"robin_hood::unordered_node<string>\" 111.966667 \n",
" \"robinhoodflat\" 545.750000 \n",
" \"robinhoodnode\" 227.250000 \n",
" \"std::map<string>\" 471.900000 \n",
" \"std::unordered_map\" 661.000000 \n",
"string_insert \"robin_hood::unordered_flat<string>\" 294.333333 \n",
" \"robin_hood::unordered_node<string>\" 228.566667 \n",
" \"robinhoodflat\" 911.000000 \n",
" \"robinhoodnode\" 514.000000 \n",
" \"std::map<string>\" 470.933333 \n",
" \"std::unordered_map\" 864.250000 \n",
"string_nosucc_lookup \"robin_hood::unordered_flat<string>\" 271.666667 \n",
" \"robin_hood::unordered_node<string>\" 183.266667 \n",
" \"robinhoodflat\" 823.750000 \n",
" \"robinhoodnode\" 454.250000 \n",
" \"std::map<string>\" 394.466667 \n",
" \"std::unordered_map\" 657.000000 \n",
"string_succ_lookup \"robin_hood::unordered_flat<string>\" 185.866667 \n",
" \"robin_hood::unordered_node<string>\" 302.766667 \n",
" \"robinhoodflat\" 240.250000 \n",
" \"robinhoodnode\" 342.250000 \n",
" \"std::map<string>\" 468.466667 \n",
" \"std::unordered_map\" 530.250000 \n",
analysis in python done
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"\n",
results update
2020-03-19 22:11:00 +00:00
" 50000000 \n",
"TEST MAP \n",
"int_delete \"robin_hood::unordered_flat<int>\" 48.266667 \n",
" \"robin_hood::unordered_node<int>\" 61.500000 \n",
" \"robinhoodflat\" 119.000000 \n",
" \"robinhoodnode 152.000000 \n",
" \"std::map<int>\" 172.333333 \n",
" \"std::unordered_map\" 365.500000 \n",
"int_insert \"robin_hood::unordered_flat<int>\" 128.100000 \n",
" \"robin_hood::unordered_node<int>\" 169.233333 \n",
" \"robinhoodflat\" 312.500000 \n",
" \"robinhoodnode 352.000000 \n",
" \"std::map<int>\" 310.600000 \n",
" \"std::unordered_map\" 505.250000 \n",
"int_nosucc_lookup \"robin_hood::unordered_flat<int>\" 119.600000 \n",
" \"robin_hood::unordered_node<int>\" 140.166667 \n",
" \"robinhoodflat\" 305.250000 \n",
" \"robinhoodnode 321.750000 \n",
" \"std::map<int>\" 287.000000 \n",
" \"std::unordered_map\" 454.750000 \n",
"int_succ_lookup \"robin_hood::unordered_flat<int>\" 43.466667 \n",
" \"robin_hood::unordered_node<int>\" 89.566667 \n",
" \"robinhoodflat\" 168.000000 \n",
" \"robinhoodnode 282.000000 \n",
" \"std::map<int>\" 93.933333 \n",
" \"std::unordered_map\" 390.000000 \n",
"string_delete \"robin_hood::unordered_flat<string>\" 240.166667 \n",
" \"robin_hood::unordered_node<string>\" 167.733333 \n",
" \"robinhoodflat\" 834.250000 \n",
" \"robinhoodnode\" 358.750000 \n",
" \"std::map<string>\" 481.933333 \n",
" \"std::unordered_map\" 648.000000 \n",
"string_insert \"robin_hood::unordered_flat<string>\" 378.300000 \n",
" \"robin_hood::unordered_node<string>\" 281.533333 \n",
" \"robinhoodflat\" 1194.750000 \n",
" \"robinhoodnode\" 633.500000 \n",
" \"std::map<string>\" 468.766667 \n",
" \"std::unordered_map\" 850.500000 \n",
"string_nosucc_lookup \"robin_hood::unordered_flat<string>\" 355.566667 \n",
" \"robin_hood::unordered_node<string>\" 215.466667 \n",
" \"robinhoodflat\" 1098.000000 \n",
" \"robinhoodnode\" 492.250000 \n",
" \"std::map<string>\" 392.066667 \n",
" \"std::unordered_map\" 653.250000 \n",
"string_succ_lookup \"robin_hood::unordered_flat<string>\" 191.366667 \n",
" \"robin_hood::unordered_node<string>\" 309.800000 \n",
" \"robinhoodflat\" 273.500000 \n",
" \"robinhoodnode\" 381.500000 \n",
" \"std::map<string>\" 471.433333 \n",
" \"std::unordered_map\" 535.500000 \n",
analysis in python done
2020-03-04 13:53:42 +00:00
"\n",
results update
2020-03-19 22:11:00 +00:00
"[48 rows x 31 columns]"
analysis in python done
2020-03-04 13:53:42 +00:00
]
},
results update
2020-03-19 22:11:00 +00:00
"execution_count": 5,
analysis in python done
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"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"groups_mean = data.groupby([\"TEST\", \"MAP\"]).mean()\n",
"groups_mean"
]
},
{
"cell_type": "code",
results update
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"execution_count": 6,
analysis in python done
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"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"groups_std = data.groupby([\"TEST\", \"MAP\"]).std()"
]
},
{
"cell_type": "code",
results update
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"execution_count": 7,
analysis in python done
2020-03-04 13:53:42 +00:00
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
results update
2020-03-19 22:11:00 +00:00
"image/png": "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
analysis in python done
2020-03-04 13:53:42 +00:00
"text/plain": [
"<Figure size 2160x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
results update
2020-03-19 22:11:00 +00:00
"image/png": "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
analysis in python done
2020-03-04 13:53:42 +00:00
"text/plain": [
"<Figure size 2160x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
results update
2020-03-19 22:11:00 +00:00
"image/png": "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
analysis in python done
2020-03-04 13:53:42 +00:00
"text/plain": [
"<Figure size 2160x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
results update
2020-03-19 22:11:00 +00:00
"image/png": "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
analysis in python done
2020-03-04 13:53:42 +00:00
"text/plain": [
"<Figure size 2160x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"for i in groups_mean.loc[\"int_insert\"].index:\n",
"# plt.plot(groups_mean.loc[\"int_insert\", i], label=i)\n",
" plt.errorbar(groups_mean.columns,groups_mean.loc[\"int_insert\", i], yerr=groups_std.loc[\"int_insert\", i], label=i)\n",
"plt.ylabel('insert time(ns)')\n",
"plt.legend()\n",
"plt.title(\"int insert\")\n",
"# plt.xscale(\"log\")\n",
"plt.show()\n",
"for i in groups_mean.loc[\"int_insert\"].index:\n",
"# plt.plot(groups_mean.loc[\"int_succ_lookup\", i], label=i)\n",
" plt.errorbar(groups_mean.columns,groups_mean.loc[\"int_succ_lookup\", i], yerr=groups_std.loc[\"int_succ_lookup\", i], label=i)\n",
"plt.ylabel('succesful lookup time(ns)')\n",
"plt.legend()\n",
"plt.title(\"int succesful lookup\")\n",
"# plt.xscale(\"log\")\n",
"plt.show()\n",
"for i in groups_mean.loc[\"int_insert\"].index:\n",
"# plt.plot(groups_mean.loc[\"int_succ_lookup\", i], label=i)\n",
" plt.errorbar(groups_mean.columns,groups_mean.loc[\"int_nosucc_lookup\", i], yerr=groups_std.loc[\"int_nosucc_lookup\", i], label=i)\n",
"plt.ylabel('unscuccesful time(ns)')\n",
"plt.legend()\n",
"plt.title(\"int unsuccesful lookup\")\n",
"# plt.xscale(\"log\")\n",
"plt.show()\n",
"for i in groups_mean.loc[\"int_insert\"].index:\n",
"# plt.plot(groups_mean.loc[\"int_succ_lookup\", i], label=i)\n",
" plt.errorbar(groups_mean.columns,groups_mean.loc[\"int_delete\", i], yerr=groups_std.loc[\"int_delete\", i], label=i)\n",
"plt.ylabel('delete time(ns)')\n",
"plt.legend()\n",
"plt.title(\"int delete\")\n",
"# plt.xscale(\"log\")\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"scrolled": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
results update
2020-03-19 22:11:00 +00:00
"execution_count": 8,
analysis in python done
2020-03-04 13:53:42 +00:00
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
results update
2020-03-19 22:11:00 +00:00
"image/png": "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
analysis in python done
2020-03-04 13:53:42 +00:00
"text/plain": [
"<Figure size 2160x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
results update
2020-03-19 22:11:00 +00:00
"image/png": "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
analysis in python done
2020-03-04 13:53:42 +00:00
"text/plain": [
"<Figure size 2160x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
results update
2020-03-19 22:11:00 +00:00
"image/png": "iVBORw0KGgoAAAANSUhEUgAABsYAAAE/CAYAAAD1xHZ7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjMsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+AADFEAAAgAElEQVR4nOzdeVzWVd7/8dcBcUksNVGhVLAUWQREwBU0LW1Gb1Kz/JkbMrRY1mytt42SrVNOu93NqGlNWpSl4+RUUyohSgk42KRsLbgEuWuKWizn9wcXV1BsIovL+/l48Liu66yf77n0D/x4zjHWWkRERERERERERERERETOdy7NHYCIiIiIiIiIiIiIiIhIU1BiTERERERERERERERERC4ISoyJiIiIiIiIiIiIiIjIBUGJMREREREREREREREREbkgKDEmIiIiIiIiIiIiIiIiFwQlxkREREREREREREREROSCoMSYiIiIiIic94wx7xtjZjR3HOciY8wsY8xeY8xxY8yltbSNMcYkV1PnbYyxxpgWZxjPcGPMnjMZQ0RERERELlxn9AuJiIiIiIhIczLGxANXWmun1tTOWvurpono/GKMcQOeBgZaa7c1dzwiIiIiIiJnSjvGRERERETkvGXK6Pee+usCtAa2N3cgIiIiIiIiDUG/IIqIiIiIyFnPGHOfMeZbY8wxY0y2MWakMeZa4H+BSY5j/rY52iYaYx41xmwCTgA9HWVxjvoYY0yyMWaBMeawMeYbY8yvKszlY4xJcsz1sTFmoTHm9Wri+sXRgY7jAq90vF/m6L/WMd5nxpgrHHXGGPOMMWafMeZ7Y8x/jTGBFZ4hrrp5jDEBxpiPjDGHHMcc/q+j3NUY87/GmK8c86UbY7o56vpU6JNtjLmxwni/NsbscPT51hhztzGmN5DtaHLEGLO+quMQfx7raXynXsaYNY54vjTG3FyhrpUx5lljTL7j51ljTKtqxrnLEfvldfw+XnaswzFjzCfGmB6nG7uIiIiIiJy7lBgTEREREZGzmjHGF5gNhFtr2wGjgTxr7QfAY0CCtdbdWhtcods04BagHbCzimEHUJb06QQ8CSwxxhhH3QpgC3ApEO8Y60z8P+AhoAPwJfCoo3wUEAX0Bi4BbgQO1jaYMaYd8DHwAeAFXAmsc1T/AZgM/Bq4GIgFThhj2gIfOZ6tsyOml4wx/o5+S4BbHesbCKy31uYAAY769tbaEfV5+Bq8CexxPMNE4DFjTPkcc4CBQAgQDEQAD/58AGPMXCAGGGatreu9Y1OAhyn77jOA5fV/BBEREREROdcoMSYiIiIiIme7EqAV4G+McbPW5llrv6qlzzJr7XZrbbG1tqiK+p3W2kXW2hLgVcAT6GKM6Q6EA3OttT9aa5OBNWcY/ypr7RZrbTFlSZgQR3kRZYm7PoCx1mZaawvqMN5Y4Dtr7V+staestcestZ856uKAB6212bbMNmvtQUefPGvtUsea/Ad4B7ihQiz+xpiLrbWHrbVbz/CZa+TYxTYEuM/xDBnAYmC6o8kUYL61dp+1dj9licVplYcwT1OWXLzK0aau1lprk6y1P1CWgBtUvqtORERERETOf0qMiYiIiIjIWc1a+yXwO8p2b+0zxrxpjPGqpdvuWuq/qzD+Ccdbd8p2Lx2qUFaXsWrzXYX3JxzzYK1dD7wILKTsuf5mjLm4DuN1A6pLDFZX1wMYYIw5Uv5DWfKpq6P+esp2me10HC84qA5xnInydT5WoWwncFmF+p0/q6v4nbenbEfg49bao6c5t/P7tNYeBw79bGwRERERETmPKTEmIiIiIiJnPWvtCmvtUMoSPBb4c3lVdV3qOVUB0NEYc1GFspp2ExUCzrbGmK41tP0Fa+3z1tr+gD9lRyreU9W4/JTAgrLETs9qhtwNXFFN+SfW2vYVftyttbMccaRaa6+j7JjF1cBb1Yxf6HitLra6yqdsndtVKOsOfFuhvsfP6vIrfD5M2S64pcaYIT+Lr7bvo1uFeneg48/GFhERERGR85gSYyIiIiIiclYzxvgaY0YYY1oBp4CTQKmjei/gbYxpkN9trLU7gTQg3hjT0rFz6n9q6LINCDDGhBhjWlO2q61OjDHhxpgBxhg3yhI6p/jpuTKACcaYi4wxVwK/qdD1PcDTGPM7Y0wrY0w7Y8wAR91i4GFjTC9TJsgYc6mjT29jzDRjjJvjJ9wY4+d4zinGmEscx05+XyGOn6/PfsqSV1ONMa7GmFiqTsTVyFq7G9gMPG6MaW2MCXI84+uOJm8ADxpjPIwxnYC5FerKx0ikbNfbu8aYCEdxXb6PXxtjhhpjWlJ219injnhEREREROQCoMSYiIiIiIic7VoBTwAHKDuWsDPwgKPubcfrQWNMQ92LNQUYBBwEHgESgB+qamitzQHmAx8DuUDyacxzMbCIst1POx3zPeWoewb4kbLE36uU3U1WPucx4BrKEnbfOea9ylH9NGW7vf5NWYJrCdDG0WcU8P8o2x31HWW77lo5+k0D8owx3wO3OdagOjdTtrPtIBBAWYKrPiYD3o54VgHzrLUfO+oeoSxB+TnwX2Cro6wSa+1HQCzwT2NMaB2/jxXAPMqOUOwPTK1n/CIiIiIicg4y1tb3hBEREREREZHznzEmAciy1s5r7ljkzBhjlgF7rLUPNncsIiIiIiLSPLRjTEREREREpALHEYNXGGNcjDHXAtdRdu+WiIiIiIiInONaNHcAIiIiIiIiZ5muwLvApcAeYJa19j/NG5KIiIiIiIg0BB2lKCIiIiIiIiIiIiIiIhcEHaUoIiIiIiIiIiIiIiIiFwQlxkREREREREREREREROSCcF7eMdapUyfr7e3d3GGIiIiIiIiIiIiIiIhIE0tPTz9grfWoqu68TIx5e3uTlpbW3GGIiIiIiIiIiIiIiIhIEzPG7KyuTkcpioiIiIiIiIiIiIiIyAVBiTERERERERERERERERG5ICgxJiIiIiIiIiIiIiIiIheE8/KOMRERERERERERERGR+igqKmLPnj2cOnWquUMRkVq0bt2ayy+/HDc3tzr3UWJMRERERERERERERMRhz549tGvXDm9vb4wxzR2OiFTDWsvBgwfZs2cPPj4+de6noxRFRERERERERERERBxOnTrFpZdeqqSYyFnOGMOll1562rs7lRgTEREREREREREREalASTGRc0N9/q4qMSYiIiIiIiIiIiIicgYm/TWFSX9Nae4wRKQOlBgTERERERERERERETlLeXt7V3qtq7y8PAIDA6usi4uLY8eOHacdS0xMDCtXrjztfs01bn15e3tz4MCBBh+3pu+k3OTJkwkKCuKZZ56p07osW7aM/Pz8M4orIyODf/3rX9XWp6Wlcdddd53RHDVZtmwZ8fHxxMfHs2zZskabp5wSYyIiIiIiIiIiIiIi56Di4uJ69Vu8eDH+/v4NHM25qb5rWFFJSUkDRALfffcdqampfP755/z+97+vU5+6JsYOHz5cbV1NibHi4mLCwsJ4/vnn6xTP6c7dHJQYExERERFpYgkP3U/CQ/c3dxgiIiIiInIO8PDwqPSamJhIZGQk0dHRzuTW008/TWBgIIGBgTz77LPOvsXFxUyZMgU/Pz8mTpzIiRMnABg+fDhpaWkAuLu7M2fOHIKDgxk4cCB79+6tMZ6kpCQGDx5Mz549nbuZrLXcc889BAYG0rdvXxISEmotnz17Nr6+vlx99dXs27ev1nVYtmwZs2fPdn4eO3YsiYmJNT5DXl4eI0aMICgoiJEjR7Jr1y6gbIfabbfdxoABA7j33ns5ePAgo0aNIiAggLi4OKy1znlef/11IiIiCAkJ4dZbb3Umwdzd3fnjH/9IcHAwKSkppKenM2zYMPr378/o0aMpKCgAID09neDgYIKDg1m4cGGNzzhq1Ci+/fZbQkJC2LhxY6W6+fPnEx4eTmBgILfccgvWWlauXElaWhpTpkwhJCSEkydPVuqzb98+FixYQGBgoHPt3377bQIDAwkODiYqKooff/yRuXPnkpCQQEhICAkJCcTHxzNt2jSGDBnCtGn
analysis in python done
2020-03-04 13:53:42 +00:00
"text/plain": [
"<Figure size 2160x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
results update
2020-03-19 22:11:00 +00:00
"image/png": "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
analysis in python done
2020-03-04 13:53:42 +00:00
"text/plain": [
"<Figure size 2160x360 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"for i in groups_mean.loc[\"string_insert\"].index:\n",
"# plt.plot(groups_mean.loc[\"string_insert\", i], label=i)\n",
" plt.errorbar(groups_mean.columns,groups_mean.loc[\"string_insert\", i], yerr=groups_std.loc[\"string_insert\", i], label=i)\n",
"plt.ylabel('insert time(ns)')\n",
"plt.legend()\n",
"plt.title(\"string insert\")\n",
"# plt.xscale(\"log\")\n",
"plt.show()\n",
"\n",
"\n",
"for i in groups_mean.loc[\"string_insert\"].index:\n",
"# plt.plot(groups_mean.loc[\"string_succ_lookup\", i], label=i)\n",
" plt.errorbar(groups_mean.columns,groups_mean.loc[\"string_succ_lookup\", i], yerr=groups_std.loc[\"string_succ_lookup\", i], label=i)\n",
"plt.ylabel('succesful lookup time(ns)')\n",
"plt.legend()\n",
"plt.title(\"string succesful lookup\")\n",
"# plt.xscale(\"log\")\n",
"plt.show()\n",
"\n",
"for i in groups_mean.loc[\"string_insert\"].index:\n",
"# plt.plot(groups_mean.loc[\"string_succ_lookup\", i], label=i)\n",
" plt.errorbar(groups_mean.columns,groups_mean.loc[\"string_nosucc_lookup\", i], yerr=groups_std.loc[\"string_nosucc_lookup\", i], label=i)\n",
"plt.ylabel('unscuccesful time(ns)')\n",
"plt.legend()\n",
"plt.title(\"string unsuccesful lookup\")\n",
"# plt.xscale(\"log\")\n",
"plt.show()\n",
"for i in groups_mean.loc[\"string_insert\"].index:\n",
"# plt.plot(groups_mean.loc[\"string_succ_lookup\", i], label=i)\n",
" plt.errorbar(groups_mean.columns,groups_mean.loc[\"string_delete\", i], yerr=groups_std.loc[\"string_delete\", i], label=i)\n",
"plt.ylabel('delete time(ns)')\n",
"plt.legend()\n",
"plt.title(\"string delete\")\n",
"# plt.xscale(\"log\")\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"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": "3.8.1"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
Reference in New Issue Copy Permalink