wassname/rl_2d_walker.js
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rl_2d_walker.js/scripts/view_log.ipynb
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{
"cells": [
{
"cell_type": "code",
"execution_count": 76,
"metadata": {
"ExecuteTime": {
"end_time": "2018-12-02T07:34:39.461661Z",
"start_time": "2018-12-02T07:34:39.452302Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Populating the interactive namespace from numpy and matplotlib\n"
]
}
],
"source": [
"%pylab inline\n",
"import pandas as pd\n",
"import os\n",
"import glob"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2018-12-02T03:01:10.959063Z",
"start_time": "2018-12-02T03:01:10.950282Z"
}
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 77,
"metadata": {
"ExecuteTime": {
"end_time": "2018-12-02T07:34:39.807097Z",
"start_time": "2018-12-02T07:34:39.801794Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"'../outputs/train_2018-12-02_11-57-52.log'"
]
},
"execution_count": 77,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"latest_log = sorted(glob.glob('../outputs/*.log'))[-1]\n",
"latest_log"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"ExecuteTime": {
"end_time": "2018-12-02T03:01:17.499589Z",
"start_time": "2018-12-02T03:01:17.493491Z"
}
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 78,
"metadata": {
"ExecuteTime": {
"end_time": "2018-12-02T07:34:40.116573Z",
"start_time": "2018-12-02T07:34:40.102114Z"
}
},
"outputs": [],
"source": [
"datas = []\n",
"data = {}\n",
"for line in open(latest_log).readlines():\n",
" if line.startswith('metric'):\n",
" _, name, val = line.strip('\\n').split(' ', 2)\n",
" val = float(val)\n",
" if name=='episodeSteps':\n",
" steps=val\n",
" if len(data): datas.append(data)\n",
" data = {}\n",
" data[name] = val\n",
" \n",
"# print(steps, name,val)"
]
},
{
"cell_type": "code",
"execution_count": 79,
"metadata": {
"ExecuteTime": {
"end_time": "2018-12-02T07:34:40.386932Z",
"start_time": "2018-12-02T07:34:40.303934Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>ActorLoss</th>\n",
" <th>CriticLoss</th>\n",
" <th>EpisodeDuration</th>\n",
" <th>NoiseDistance</th>\n",
" <th>Reward</th>\n",
" <th>bonus_happiness</th>\n",
" <th>episodeSteps</th>\n",
" <th>head_height_reward</th>\n",
" <th>leg_switch_reward</th>\n",
" <th>lin_vel_reward</th>\n",
" <th>position</th>\n",
" <th>quad_contact_cost</th>\n",
" <th>quad_joint_angle_cost</th>\n",
" <th>quad_power_cost</th>\n",
" <th>reward</th>\n",
" </tr>\n",
" <tr>\n",
" <th>steps</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>4000.5</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>800.0</td>\n",
" <td>1.001085</td>\n",
" <td>15.428472</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>9.125332</td>\n",
" <td>0.285500</td>\n",
" <td>0.070601</td>\n",
" <td>1.548446</td>\n",
" <td>-2.472562</td>\n",
" <td>-0.601705</td>\n",
" <td>-0.121749</td>\n",
" <td>15.428472</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8000.5</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>800.0</td>\n",
" <td>0.994691</td>\n",
" <td>-24.003403</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-50.378863</td>\n",
" <td>0.232750</td>\n",
" <td>0.077041</td>\n",
" <td>1.705007</td>\n",
" <td>-2.120969</td>\n",
" <td>-0.548225</td>\n",
" <td>-0.124130</td>\n",
" <td>-4.287465</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12000.5</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>800.0</td>\n",
" <td>1.019849</td>\n",
" <td>-27.004394</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-72.992035</td>\n",
" <td>0.186500</td>\n",
" <td>0.020328</td>\n",
" <td>1.828903</td>\n",
" <td>-2.127979</td>\n",
" <td>-0.520995</td>\n",
" <td>-0.145143</td>\n",
" <td>-11.859775</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16000.5</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>800.0</td>\n",
" <td>1.013509</td>\n",
" <td>-18.811241</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-78.189635</td>\n",
" <td>0.186500</td>\n",
" <td>0.022882</td>\n",
" <td>2.054154</td>\n",
" <td>-2.119297</td>\n",
" <td>-0.542288</td>\n",
" <td>-0.151087</td>\n",
" <td>-13.597642</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20000.5</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>800.0</td>\n",
" <td>0.966068</td>\n",
" <td>-29.553983</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-87.854409</td>\n",
" <td>0.209900</td>\n",
" <td>0.009446</td>\n",
" <td>2.018187</td>\n",
" <td>-2.046362</td>\n",
" <td>-0.523966</td>\n",
" <td>-0.161338</td>\n",
" <td>-16.788910</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24000.5</th>\n",
" <td>191.363654</td>\n",
" <td>2787.138015</td>\n",
" <td>800.0</td>\n",
" <td>0.986174</td>\n",
" <td>-20.272949</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-89.615552</td>\n",
" <td>0.193083</td>\n",
" <td>-0.015976</td>\n",
" <td>1.956940</td>\n",
" <td>-1.997354</td>\n",
" <td>-0.509704</td>\n",
" <td>-0.163246</td>\n",
" <td>-17.369583</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28000.5</th>\n",
" <td>208.339470</td>\n",
" <td>2542.897098</td>\n",
" <td>800.0</td>\n",
" <td>0.952842</td>\n",
" <td>-31.488694</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-95.714551</td>\n",
" <td>0.214857</td>\n",
" <td>0.035294</td>\n",
" <td>1.921250</td>\n",
" <td>-2.007009</td>\n",
" <td>-0.513981</td>\n",
" <td>-0.174407</td>\n",
" <td>-19.386599</td>\n",
" </tr>\n",
" <tr>\n",
" <th>32000.5</th>\n",
" <td>214.446994</td>\n",
" <td>3204.433846</td>\n",
" <td>800.0</td>\n",
" <td>1.064732</td>\n",
" <td>-19.854985</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-95.809296</td>\n",
" <td>0.194812</td>\n",
" <td>-0.008265</td>\n",
" <td>1.903555</td>\n",
" <td>-2.033891</td>\n",
" <td>-0.508228</td>\n",
" <td>-0.170573</td>\n",
" <td>-19.445147</td>\n",
" </tr>\n",
" <tr>\n",
" <th>36000.5</th>\n",
" <td>219.025467</td>\n",
" <td>3763.665469</td>\n",
" <td>800.0</td>\n",
" <td>1.011534</td>\n",
" <td>-31.246213</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-99.759212</td>\n",
" <td>0.194111</td>\n",
" <td>0.008420</td>\n",
" <td>1.836762</td>\n",
" <td>-2.032618</td>\n",
" <td>-0.506536</td>\n",
" <td>-0.173296</td>\n",
" <td>-20.756377</td>\n",
" </tr>\n",
" <tr>\n",
" <th>40000.5</th>\n",
" <td>222.761831</td>\n",
" <td>4402.325286</td>\n",
" <td>800.0</td>\n",
" <td>0.901060</td>\n",
" <td>-19.233865</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-99.335485</td>\n",
" <td>0.195500</td>\n",
" <td>0.005288</td>\n",
" <td>1.849608</td>\n",
" <td>-2.000762</td>\n",
" <td>-0.501912</td>\n",
" <td>-0.175004</td>\n",
" <td>-20.604125</td>\n",
" </tr>\n",
" <tr>\n",
" <th>44000.5</th>\n",
" <td>192.925095</td>\n",
" <td>6175.267422</td>\n",
" <td>800.0</td>\n",
" <td>0.907664</td>\n",
" <td>-12.129763</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-97.021365</td>\n",
" <td>0.185091</td>\n",
" <td>0.003564</td>\n",
" <td>1.776524</td>\n",
" <td>-1.996920</td>\n",
" <td>-0.496669</td>\n",
" <td>-0.174887</td>\n",
" <td>-19.833729</td>\n",
" </tr>\n",
" <tr>\n",
" <th>48000.5</th>\n",
" <td>186.271498</td>\n",
" <td>7918.174082</td>\n",
" <td>800.0</td>\n",
" <td>0.749639</td>\n",
" <td>10.577317</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-89.403447</td>\n",
" <td>0.182167</td>\n",
" <td>-0.002658</td>\n",
" <td>1.644775</td>\n",
" <td>-2.001734</td>\n",
" <td>-0.496787</td>\n",
" <td>-0.175965</td>\n",
" <td>-17.299475</td>\n",
" </tr>\n",
" <tr>\n",
" <th>52000.5</th>\n",
" <td>182.367172</td>\n",
" <td>9496.571895</td>\n",
" <td>800.0</td>\n",
" <td>0.706705</td>\n",
" <td>-9.020571</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-87.510926</td>\n",
" <td>0.178231</td>\n",
" <td>0.002521</td>\n",
" <td>1.660926</td>\n",
" <td>-1.990582</td>\n",
" <td>-0.490189</td>\n",
" <td>-0.176964</td>\n",
" <td>-16.662636</td>\n",
" </tr>\n",
" <tr>\n",
" <th>56000.5</th>\n",
" <td>209.881061</td>\n",
" <td>11588.859424</td>\n",
" <td>800.0</td>\n",
" <td>0.686202</td>\n",
" <td>-9.436242</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-85.972747</td>\n",
" <td>0.199179</td>\n",
" <td>0.005499</td>\n",
" <td>1.680981</td>\n",
" <td>-1.995598</td>\n",
" <td>-0.499409</td>\n",
" <td>-0.176319</td>\n",
" <td>-16.146465</td>\n",
" </tr>\n",
" <tr>\n",
" <th>60000.5</th>\n",
" <td>203.770711</td>\n",
" <td>13639.273037</td>\n",
" <td>800.0</td>\n",
" <td>0.612119</td>\n",
" <td>-31.330872</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-88.983683</td>\n",
" <td>0.191333</td>\n",
" <td>0.008175</td>\n",
" <td>1.692749</td>\n",
" <td>-2.012542</td>\n",
" <td>-0.503418</td>\n",
" <td>-0.176143</td>\n",
" <td>-17.158759</td>\n",
" </tr>\n",
" <tr>\n",
" <th>64000.5</th>\n",
" <td>220.845039</td>\n",
" <td>16973.926318</td>\n",
" <td>800.0</td>\n",
" <td>0.600943</td>\n",
" <td>-5.644547</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-86.825863</td>\n",
" <td>0.202906</td>\n",
" <td>0.000194</td>\n",
" <td>1.673126</td>\n",
" <td>-2.014898</td>\n",
" <td>-0.503954</td>\n",
" <td>-0.175746</td>\n",
" <td>-16.439121</td>\n",
" </tr>\n",
" <tr>\n",
" <th>68000.5</th>\n",
" <td>237.482885</td>\n",
" <td>19318.055244</td>\n",
" <td>800.0</td>\n",
" <td>0.577887</td>\n",
" <td>-28.311395</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-88.945980</td>\n",
" <td>0.205118</td>\n",
" <td>0.021373</td>\n",
" <td>1.684573</td>\n",
" <td>-2.020250</td>\n",
" <td>-0.496782</td>\n",
" <td>-0.175948</td>\n",
" <td>-17.137490</td>\n",
" </tr>\n",
" <tr>\n",
" <th>72000.5</th>\n",
" <td>233.844463</td>\n",
" <td>23049.072451</td>\n",
" <td>800.0</td>\n",
" <td>0.437918</td>\n",
" <td>-19.292133</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-89.266078</td>\n",
" <td>0.196333</td>\n",
" <td>0.004747</td>\n",
" <td>1.724214</td>\n",
" <td>-2.034951</td>\n",
" <td>-0.492618</td>\n",
" <td>-0.179009</td>\n",
" <td>-17.257192</td>\n",
" </tr>\n",
" <tr>\n",
" <th>76000.5</th>\n",
" <td>258.211864</td>\n",
" <td>25861.567061</td>\n",
" <td>800.0</td>\n",
" <td>0.343572</td>\n",
" <td>-4.006912</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-87.196266</td>\n",
" <td>0.207684</td>\n",
" <td>0.010595</td>\n",
" <td>1.741209</td>\n",
" <td>-2.030655</td>\n",
" <td>-0.491321</td>\n",
" <td>-0.179465</td>\n",
" <td>-16.559809</td>\n",
" </tr>\n",
" <tr>\n",
" <th>80000.5</th>\n",
" <td>259.855144</td>\n",
" <td>29057.213398</td>\n",
" <td>800.0</td>\n",
" <td>0.305389</td>\n",
" <td>-30.271102</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-89.240322</td>\n",
" <td>0.202325</td>\n",
" <td>0.002668</td>\n",
" <td>1.764335</td>\n",
" <td>-2.028444</td>\n",
" <td>-0.492691</td>\n",
" <td>-0.179657</td>\n",
" <td>-17.245374</td>\n",
" </tr>\n",
" <tr>\n",
" <th>84000.5</th>\n",
" <td>302.923168</td>\n",
" <td>34809.407969</td>\n",
" <td>800.0</td>\n",
" <td>0.198288</td>\n",
" <td>-14.004152</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-88.774951</td>\n",
" <td>0.202262</td>\n",
" <td>0.000983</td>\n",
" <td>1.760559</td>\n",
" <td>-2.030735</td>\n",
" <td>-0.492974</td>\n",
" <td>-0.177674</td>\n",
" <td>-17.091030</td>\n",
" </tr>\n",
" <tr>\n",
" <th>88000.5</th>\n",
" <td>292.210404</td>\n",
" <td>36090.210684</td>\n",
" <td>800.0</td>\n",
" <td>0.283443</td>\n",
" <td>-42.098855</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-92.166832</td>\n",
" <td>0.200818</td>\n",
" <td>-0.005441</td>\n",
" <td>1.798274</td>\n",
" <td>-2.036281</td>\n",
" <td>-0.495948</td>\n",
" <td>-0.179564</td>\n",
" <td>-18.227749</td>\n",
" </tr>\n",
" <tr>\n",
" <th>92000.5</th>\n",
" <td>348.208931</td>\n",
" <td>41075.092363</td>\n",
" <td>800.0</td>\n",
" <td>0.270578</td>\n",
" <td>-9.238977</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-91.002878</td>\n",
" <td>0.206109</td>\n",
" <td>0.006316</td>\n",
" <td>1.792339</td>\n",
" <td>-2.038217</td>\n",
" <td>-0.503308</td>\n",
" <td>-0.178819</td>\n",
" <td>-17.836933</td>\n",
" </tr>\n",
" <tr>\n",
" <th>96000.5</th>\n",
" <td>391.587693</td>\n",
" <td>42182.473066</td>\n",
" <td>800.0</td>\n",
" <td>0.365521</td>\n",
" <td>-43.590564</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-94.232951</td>\n",
" <td>0.208187</td>\n",
" <td>0.000129</td>\n",
" <td>1.777263</td>\n",
" <td>-2.026099</td>\n",
" <td>-0.500903</td>\n",
" <td>-0.178367</td>\n",
" <td>-18.910001</td>\n",
" </tr>\n",
" <tr>\n",
" <th>100000.5</th>\n",
" <td>363.875681</td>\n",
" <td>46710.245020</td>\n",
" <td>800.0</td>\n",
" <td>0.380616</td>\n",
" <td>-43.440455</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-97.170620</td>\n",
" <td>0.202540</td>\n",
" <td>-0.004936</td>\n",
" <td>1.748328</td>\n",
" <td>-2.017295</td>\n",
" <td>-0.501833</td>\n",
" <td>-0.181513</td>\n",
" <td>-19.891219</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104000.5</th>\n",
" <td>339.817678</td>\n",
" <td>50106.874199</td>\n",
" <td>800.0</td>\n",
" <td>0.342616</td>\n",
" <td>-3.568891</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-95.303719</td>\n",
" <td>0.208385</td>\n",
" <td>0.004970</td>\n",
" <td>1.811393</td>\n",
" <td>-2.015716</td>\n",
" <td>-0.500457</td>\n",
" <td>-0.183773</td>\n",
" <td>-19.263437</td>\n",
" </tr>\n",
" <tr>\n",
" <th>108000.5</th>\n",
" <td>313.327876</td>\n",
" <td>51655.751445</td>\n",
" <td>800.0</td>\n",
" <td>0.393287</td>\n",
" <td>-24.874761</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-95.933077</td>\n",
" <td>0.212852</td>\n",
" <td>-0.002024</td>\n",
" <td>1.807105</td>\n",
" <td>-2.014319</td>\n",
" <td>-0.496048</td>\n",
" <td>-0.181175</td>\n",
" <td>-19.471264</td>\n",
" </tr>\n",
" <tr>\n",
" <th>112000.5</th>\n",
" <td>270.483027</td>\n",
" <td>57878.171953</td>\n",
" <td>800.0</td>\n",
" <td>0.357968</td>\n",
" <td>-3.441934</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-94.227149</td>\n",
" <td>0.206036</td>\n",
" <td>0.007996</td>\n",
" <td>1.810939</td>\n",
" <td>-2.010103</td>\n",
" <td>-0.492748</td>\n",
" <td>-0.180397</td>\n",
" <td>-18.898788</td>\n",
" </tr>\n",
" <tr>\n",
" <th>116000.5</th>\n",
" <td>226.045801</td>\n",
" <td>59847.391836</td>\n",
" <td>800.0</td>\n",
" <td>0.402686</td>\n",
" <td>-9.032035</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-93.198698</td>\n",
" <td>0.201259</td>\n",
" <td>-0.004129</td>\n",
" <td>1.782489</td>\n",
" <td>-2.000569</td>\n",
" <td>-0.492186</td>\n",
" <td>-0.181342</td>\n",
" <td>-18.558555</td>\n",
" </tr>\n",
" <tr>\n",
" <th>120000.5</th>\n",
" <td>255.274086</td>\n",
" <td>60727.864102</td>\n",
" <td>800.0</td>\n",
" <td>0.379667</td>\n",
" <td>1.487278</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-91.195735</td>\n",
" <td>0.196033</td>\n",
" <td>-0.004114</td>\n",
" <td>1.788853</td>\n",
" <td>-1.995646</td>\n",
" <td>-0.490633</td>\n",
" <td>-0.180987</td>\n",
" <td>-17.890361</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>308000.5</th>\n",
" <td>358.649947</td>\n",
" <td>138975.352969</td>\n",
" <td>800.0</td>\n",
" <td>0.144606</td>\n",
" <td>-28.710064</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-95.784777</td>\n",
" <td>0.174526</td>\n",
" <td>0.001890</td>\n",
" <td>1.840785</td>\n",
" <td>-2.014213</td>\n",
" <td>-0.489832</td>\n",
" <td>-0.181992</td>\n",
" <td>-19.431466</td>\n",
" </tr>\n",
" <tr>\n",
" <th>312000.5</th>\n",
" <td>337.754779</td>\n",
" <td>140220.738906</td>\n",
" <td>800.0</td>\n",
" <td>0.119360</td>\n",
" <td>-23.076090</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-95.927744</td>\n",
" <td>0.177077</td>\n",
" <td>0.002362</td>\n",
" <td>1.832647</td>\n",
" <td>-2.014661</td>\n",
" <td>-0.489650</td>\n",
" <td>-0.181962</td>\n",
" <td>-19.478192</td>\n",
" </tr>\n",
" <tr>\n",
" <th>316000.5</th>\n",
" <td>259.325153</td>\n",
" <td>140588.052891</td>\n",
" <td>800.0</td>\n",
" <td>0.129157</td>\n",
" <td>-24.336979</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-96.117792</td>\n",
" <td>0.182222</td>\n",
" <td>0.001274</td>\n",
" <td>1.835341</td>\n",
" <td>-2.012020</td>\n",
" <td>-0.490779</td>\n",
" <td>-0.181994</td>\n",
" <td>-19.539696</td>\n",
" </tr>\n",
" <tr>\n",
" <th>320000.5</th>\n",
" <td>252.825544</td>\n",
" <td>146814.529766</td>\n",
" <td>800.0</td>\n",
" <td>0.126677</td>\n",
" <td>2.020660</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-95.309802</td>\n",
" <td>0.182613</td>\n",
" <td>-0.000708</td>\n",
" <td>1.829982</td>\n",
" <td>-2.011155</td>\n",
" <td>-0.488976</td>\n",
" <td>-0.182546</td>\n",
" <td>-19.270191</td>\n",
" </tr>\n",
" <tr>\n",
" <th>324000.5</th>\n",
" <td>311.681400</td>\n",
" <td>148886.869453</td>\n",
" <td>800.0</td>\n",
" <td>0.104543</td>\n",
" <td>-15.302837</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-95.163531</td>\n",
" <td>0.182605</td>\n",
" <td>0.001098</td>\n",
" <td>1.820914</td>\n",
" <td>-2.012655</td>\n",
" <td>-0.488455</td>\n",
" <td>-0.182696</td>\n",
" <td>-19.221212</td>\n",
" </tr>\n",
" <tr>\n",
" <th>328000.5</th>\n",
" <td>312.720243</td>\n",
" <td>152494.040937</td>\n",
" <td>800.0</td>\n",
" <td>0.097410</td>\n",
" <td>-21.306948</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-95.239122</td>\n",
" <td>0.181305</td>\n",
" <td>0.000272</td>\n",
" <td>1.819064</td>\n",
" <td>-2.012011</td>\n",
" <td>-0.487911</td>\n",
" <td>-0.182476</td>\n",
" <td>-19.246648</td>\n",
" </tr>\n",
" <tr>\n",
" <th>332000.5</th>\n",
" <td>312.151625</td>\n",
" <td>151137.147109</td>\n",
" <td>800.0</td>\n",
" <td>0.156087</td>\n",
" <td>-26.898011</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-95.512951</td>\n",
" <td>0.182747</td>\n",
" <td>0.000838</td>\n",
" <td>1.816929</td>\n",
" <td>-2.015391</td>\n",
" <td>-0.488862</td>\n",
" <td>-0.182880</td>\n",
" <td>-19.338833</td>\n",
" </tr>\n",
" <tr>\n",
" <th>336000.5</th>\n",
" <td>297.019186</td>\n",
" <td>154205.585469</td>\n",
" <td>800.0</td>\n",
" <td>0.150449</td>\n",
" <td>-15.047147</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-95.359666</td>\n",
" <td>0.183810</td>\n",
" <td>0.001657</td>\n",
" <td>1.822713</td>\n",
" <td>-2.017940</td>\n",
" <td>-0.488056</td>\n",
" <td>-0.183028</td>\n",
" <td>-19.287741</td>\n",
" </tr>\n",
" <tr>\n",
" <th>340000.5</th>\n",
" <td>347.804802</td>\n",
" <td>150311.306328</td>\n",
" <td>800.0</td>\n",
" <td>0.112766</td>\n",
" <td>-14.734657</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-95.205255</td>\n",
" <td>0.186147</td>\n",
" <td>0.001543</td>\n",
" <td>1.822670</td>\n",
" <td>-2.014554</td>\n",
" <td>-0.487522</td>\n",
" <td>-0.182885</td>\n",
" <td>-19.234176</td>\n",
" </tr>\n",
" <tr>\n",
" <th>344000.5</th>\n",
" <td>298.215561</td>\n",
" <td>165119.265234</td>\n",
" <td>800.0</td>\n",
" <td>0.120098</td>\n",
" <td>-25.377967</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-95.419098</td>\n",
" <td>0.186250</td>\n",
" <td>-0.001282</td>\n",
" <td>1.820896</td>\n",
" <td>-2.012657</td>\n",
" <td>-0.486891</td>\n",
" <td>-0.183168</td>\n",
" <td>-19.305615</td>\n",
" </tr>\n",
" <tr>\n",
" <th>348000.5</th>\n",
" <td>367.198066</td>\n",
" <td>164362.320156</td>\n",
" <td>800.0</td>\n",
" <td>0.143425</td>\n",
" <td>-9.835368</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-95.096557</td>\n",
" <td>0.185724</td>\n",
" <td>-0.001203</td>\n",
" <td>1.815989</td>\n",
" <td>-2.007950</td>\n",
" <td>-0.487463</td>\n",
" <td>-0.182836</td>\n",
" <td>-19.196762</td>\n",
" </tr>\n",
" <tr>\n",
" <th>352000.5</th>\n",
" <td>421.867589</td>\n",
" <td>172558.451094</td>\n",
" <td>800.0</td>\n",
" <td>0.161740</td>\n",
" <td>-45.918617</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-96.016492</td>\n",
" <td>0.185682</td>\n",
" <td>0.000611</td>\n",
" <td>1.827056</td>\n",
" <td>-2.000303</td>\n",
" <td>-0.487114</td>\n",
" <td>-0.183640</td>\n",
" <td>-19.500419</td>\n",
" </tr>\n",
" <tr>\n",
" <th>356000.5</th>\n",
" <td>399.980753</td>\n",
" <td>170143.568750</td>\n",
" <td>800.0</td>\n",
" <td>0.134694</td>\n",
" <td>-28.956869</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-96.334658</td>\n",
" <td>0.185433</td>\n",
" <td>0.001569</td>\n",
" <td>1.827713</td>\n",
" <td>-2.001134</td>\n",
" <td>-0.486855</td>\n",
" <td>-0.184369</td>\n",
" <td>-19.606671</td>\n",
" </tr>\n",
" <tr>\n",
" <th>360000.5</th>\n",
" <td>323.039328</td>\n",
" <td>177826.681328</td>\n",
" <td>800.0</td>\n",
" <td>0.119141</td>\n",
" <td>-18.324828</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-96.291717</td>\n",
" <td>0.186406</td>\n",
" <td>0.000798</td>\n",
" <td>1.827721</td>\n",
" <td>-2.000875</td>\n",
" <td>-0.487775</td>\n",
" <td>-0.184123</td>\n",
" <td>-19.592429</td>\n",
" </tr>\n",
" <tr>\n",
" <th>364000.5</th>\n",
" <td>350.858816</td>\n",
" <td>182020.647344</td>\n",
" <td>800.0</td>\n",
" <td>0.122827</td>\n",
" <td>10.592855</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-95.296701</td>\n",
" <td>0.188764</td>\n",
" <td>-0.001131</td>\n",
" <td>1.815978</td>\n",
" <td>-2.000109</td>\n",
" <td>-0.488048</td>\n",
" <td>-0.184941</td>\n",
" <td>-19.260722</td>\n",
" </tr>\n",
" <tr>\n",
" <th>368000.5</th>\n",
" <td>158.930903</td>\n",
" <td>177610.984453</td>\n",
" <td>800.0</td>\n",
" <td>0.118055</td>\n",
" <td>-9.164740</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-94.969708</td>\n",
" <td>0.191533</td>\n",
" <td>0.001028</td>\n",
" <td>1.816592</td>\n",
" <td>-2.003416</td>\n",
" <td>-0.487366</td>\n",
" <td>-0.185021</td>\n",
" <td>-19.150983</td>\n",
" </tr>\n",
" <tr>\n",
" <th>372000.5</th>\n",
" <td>190.317296</td>\n",
" <td>180786.817500</td>\n",
" <td>800.0</td>\n",
" <td>0.135613</td>\n",
" <td>9.583231</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-94.042892</td>\n",
" <td>0.191065</td>\n",
" <td>0.001168</td>\n",
" <td>1.816862</td>\n",
" <td>-2.002914</td>\n",
" <td>-0.486753</td>\n",
" <td>-0.185713</td>\n",
" <td>-18.842013</td>\n",
" </tr>\n",
" <tr>\n",
" <th>376000.5</th>\n",
" <td>223.448859</td>\n",
" <td>191507.754922</td>\n",
" <td>800.0</td>\n",
" <td>0.130242</td>\n",
" <td>-13.130436</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-93.857549</td>\n",
" <td>0.191415</td>\n",
" <td>0.000406</td>\n",
" <td>1.818154</td>\n",
" <td>-2.007324</td>\n",
" <td>-0.485283</td>\n",
" <td>-0.185419</td>\n",
" <td>-18.781252</td>\n",
" </tr>\n",
" <tr>\n",
" <th>380000.5</th>\n",
" <td>193.026997</td>\n",
" <td>187127.255469</td>\n",
" <td>800.0</td>\n",
" <td>0.142632</td>\n",
" <td>-20.573801</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-93.914095</td>\n",
" <td>0.189837</td>\n",
" <td>0.001001</td>\n",
" <td>1.821333</td>\n",
" <td>-2.007509</td>\n",
" <td>-0.484451</td>\n",
" <td>-0.185144</td>\n",
" <td>-18.800121</td>\n",
" </tr>\n",
" <tr>\n",
" <th>384000.5</th>\n",
" <td>355.778719</td>\n",
" <td>188473.558984</td>\n",
" <td>800.0</td>\n",
" <td>0.120989</td>\n",
" <td>-31.464281</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-94.306487</td>\n",
" <td>0.188474</td>\n",
" <td>-0.001194</td>\n",
" <td>1.822966</td>\n",
" <td>-2.007951</td>\n",
" <td>-0.483834</td>\n",
" <td>-0.185125</td>\n",
" <td>-18.932039</td>\n",
" </tr>\n",
" <tr>\n",
" <th>388000.5</th>\n",
" <td>307.473244</td>\n",
" <td>198413.550000</td>\n",
" <td>800.0</td>\n",
" <td>0.108410</td>\n",
" <td>-23.395215</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-94.448342</td>\n",
" <td>0.187325</td>\n",
" <td>0.000665</td>\n",
" <td>1.822733</td>\n",
" <td>-2.005641</td>\n",
" <td>-0.483057</td>\n",
" <td>-0.185104</td>\n",
" <td>-18.978051</td>\n",
" </tr>\n",
" <tr>\n",
" <th>392000.5</th>\n",
" <td>209.888784</td>\n",
" <td>204072.744688</td>\n",
" <td>800.0</td>\n",
" <td>0.131776</td>\n",
" <td>-17.679262</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-94.404683</td>\n",
" <td>0.187393</td>\n",
" <td>0.000139</td>\n",
" <td>1.820639</td>\n",
" <td>-2.009751</td>\n",
" <td>-0.482796</td>\n",
" <td>-0.184697</td>\n",
" <td>-18.964798</td>\n",
" </tr>\n",
" <tr>\n",
" <th>396000.5</th>\n",
" <td>238.403602</td>\n",
" <td>204286.347188</td>\n",
" <td>800.0</td>\n",
" <td>0.140075</td>\n",
" <td>0.952222</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-93.801894</td>\n",
" <td>0.187505</td>\n",
" <td>0.001058</td>\n",
" <td>1.830544</td>\n",
" <td>-2.009674</td>\n",
" <td>-0.482872</td>\n",
" <td>-0.184972</td>\n",
" <td>-18.763616</td>\n",
" </tr>\n",
" <tr>\n",
" <th>400000.5</th>\n",
" <td>321.055877</td>\n",
" <td>214521.868750</td>\n",
" <td>800.0</td>\n",
" <td>0.136083</td>\n",
" <td>-23.540295</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-93.942884</td>\n",
" <td>0.189320</td>\n",
" <td>0.000971</td>\n",
" <td>1.829790</td>\n",
" <td>-2.011245</td>\n",
" <td>-0.485025</td>\n",
" <td>-0.185287</td>\n",
" <td>-18.811383</td>\n",
" </tr>\n",
" <tr>\n",
" <th>404000.5</th>\n",
" <td>202.083949</td>\n",
" <td>211019.176875</td>\n",
" <td>800.0</td>\n",
" <td>0.120063</td>\n",
" <td>-41.328331</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-94.607919</td>\n",
" <td>0.187738</td>\n",
" <td>0.001006</td>\n",
" <td>1.824316</td>\n",
" <td>-2.013222</td>\n",
" <td>-0.485388</td>\n",
" <td>-0.185184</td>\n",
" <td>-19.034323</td>\n",
" </tr>\n",
" <tr>\n",
" <th>408000.5</th>\n",
" <td>138.512097</td>\n",
" <td>216563.620625</td>\n",
" <td>800.0</td>\n",
" <td>0.152197</td>\n",
" <td>-18.446270</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-94.593475</td>\n",
" <td>0.188554</td>\n",
" <td>0.000253</td>\n",
" <td>1.821491</td>\n",
" <td>-2.011557</td>\n",
" <td>-0.484752</td>\n",
" <td>-0.184696</td>\n",
" <td>-19.028558</td>\n",
" </tr>\n",
" <tr>\n",
" <th>412000.5</th>\n",
" <td>34.515037</td>\n",
" <td>208167.654219</td>\n",
" <td>800.0</td>\n",
" <td>0.144590</td>\n",
" <td>-9.956440</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-94.327922</td>\n",
" <td>0.188238</td>\n",
" <td>0.000589</td>\n",
" <td>1.823128</td>\n",
" <td>-2.011543</td>\n",
" <td>-0.485977</td>\n",
" <td>-0.184822</td>\n",
" <td>-18.940479</td>\n",
" </tr>\n",
" <tr>\n",
" <th>416000.5</th>\n",
" <td>8.198625</td>\n",
" <td>220994.370625</td>\n",
" <td>800.0</td>\n",
" <td>0.122899</td>\n",
" <td>-8.377054</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-94.020780</td>\n",
" <td>0.188495</td>\n",
" <td>-0.000557</td>\n",
" <td>1.817646</td>\n",
" <td>-2.013103</td>\n",
" <td>-0.486009</td>\n",
" <td>-0.184768</td>\n",
" <td>-18.838908</td>\n",
" </tr>\n",
" <tr>\n",
" <th>420000.5</th>\n",
" <td>-102.993905</td>\n",
" <td>212710.776719</td>\n",
" <td>800.0</td>\n",
" <td>0.138414</td>\n",
" <td>-5.776745</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-93.650548</td>\n",
" <td>0.189757</td>\n",
" <td>0.003217</td>\n",
" <td>1.819190</td>\n",
" <td>-2.015410</td>\n",
" <td>-0.485668</td>\n",
" <td>-0.184866</td>\n",
" <td>-18.714506</td>\n",
" </tr>\n",
" <tr>\n",
" <th>424000.5</th>\n",
" <td>-7.671242</td>\n",
" <td>210117.102656</td>\n",
" <td>800.0</td>\n",
" <td>0.156452</td>\n",
" <td>9.150613</td>\n",
" <td>40.0</td>\n",
" <td>400.5</td>\n",
" <td>-92.861258</td>\n",
" <td>0.189651</td>\n",
" <td>0.000655</td>\n",
" <td>1.817318</td>\n",
" <td>-2.013035</td>\n",
" <td>-0.486136</td>\n",
" <td>-0.184759</td>\n",
" <td>-18.451628</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>106 rows × 15 columns</p>\n",
"</div>"
],
"text/plain": [
" ActorLoss CriticLoss EpisodeDuration NoiseDistance \\\n",
"steps \n",
"4000.5 NaN NaN 800.0 1.001085 \n",
"8000.5 NaN NaN 800.0 0.994691 \n",
"12000.5 NaN NaN 800.0 1.019849 \n",
"16000.5 NaN NaN 800.0 1.013509 \n",
"20000.5 NaN NaN 800.0 0.966068 \n",
"24000.5 191.363654 2787.138015 800.0 0.986174 \n",
"28000.5 208.339470 2542.897098 800.0 0.952842 \n",
"32000.5 214.446994 3204.433846 800.0 1.064732 \n",
"36000.5 219.025467 3763.665469 800.0 1.011534 \n",
"40000.5 222.761831 4402.325286 800.0 0.901060 \n",
"44000.5 192.925095 6175.267422 800.0 0.907664 \n",
"48000.5 186.271498 7918.174082 800.0 0.749639 \n",
"52000.5 182.367172 9496.571895 800.0 0.706705 \n",
"56000.5 209.881061 11588.859424 800.0 0.686202 \n",
"60000.5 203.770711 13639.273037 800.0 0.612119 \n",
"64000.5 220.845039 16973.926318 800.0 0.600943 \n",
"68000.5 237.482885 19318.055244 800.0 0.577887 \n",
"72000.5 233.844463 23049.072451 800.0 0.437918 \n",
"76000.5 258.211864 25861.567061 800.0 0.343572 \n",
"80000.5 259.855144 29057.213398 800.0 0.305389 \n",
"84000.5 302.923168 34809.407969 800.0 0.198288 \n",
"88000.5 292.210404 36090.210684 800.0 0.283443 \n",
"92000.5 348.208931 41075.092363 800.0 0.270578 \n",
"96000.5 391.587693 42182.473066 800.0 0.365521 \n",
"100000.5 363.875681 46710.245020 800.0 0.380616 \n",
"104000.5 339.817678 50106.874199 800.0 0.342616 \n",
"108000.5 313.327876 51655.751445 800.0 0.393287 \n",
"112000.5 270.483027 57878.171953 800.0 0.357968 \n",
"116000.5 226.045801 59847.391836 800.0 0.402686 \n",
"120000.5 255.274086 60727.864102 800.0 0.379667 \n",
"... ... ... ... ... \n",
"308000.5 358.649947 138975.352969 800.0 0.144606 \n",
"312000.5 337.754779 140220.738906 800.0 0.119360 \n",
"316000.5 259.325153 140588.052891 800.0 0.129157 \n",
"320000.5 252.825544 146814.529766 800.0 0.126677 \n",
"324000.5 311.681400 148886.869453 800.0 0.104543 \n",
"328000.5 312.720243 152494.040937 800.0 0.097410 \n",
"332000.5 312.151625 151137.147109 800.0 0.156087 \n",
"336000.5 297.019186 154205.585469 800.0 0.150449 \n",
"340000.5 347.804802 150311.306328 800.0 0.112766 \n",
"344000.5 298.215561 165119.265234 800.0 0.120098 \n",
"348000.5 367.198066 164362.320156 800.0 0.143425 \n",
"352000.5 421.867589 172558.451094 800.0 0.161740 \n",
"356000.5 399.980753 170143.568750 800.0 0.134694 \n",
"360000.5 323.039328 177826.681328 800.0 0.119141 \n",
"364000.5 350.858816 182020.647344 800.0 0.122827 \n",
"368000.5 158.930903 177610.984453 800.0 0.118055 \n",
"372000.5 190.317296 180786.817500 800.0 0.135613 \n",
"376000.5 223.448859 191507.754922 800.0 0.130242 \n",
"380000.5 193.026997 187127.255469 800.0 0.142632 \n",
"384000.5 355.778719 188473.558984 800.0 0.120989 \n",
"388000.5 307.473244 198413.550000 800.0 0.108410 \n",
"392000.5 209.888784 204072.744688 800.0 0.131776 \n",
"396000.5 238.403602 204286.347188 800.0 0.140075 \n",
"400000.5 321.055877 214521.868750 800.0 0.136083 \n",
"404000.5 202.083949 211019.176875 800.0 0.120063 \n",
"408000.5 138.512097 216563.620625 800.0 0.152197 \n",
"412000.5 34.515037 208167.654219 800.0 0.144590 \n",
"416000.5 8.198625 220994.370625 800.0 0.122899 \n",
"420000.5 -102.993905 212710.776719 800.0 0.138414 \n",
"424000.5 -7.671242 210117.102656 800.0 0.156452 \n",
"\n",
" Reward bonus_happiness episodeSteps head_height_reward \\\n",
"steps \n",
"4000.5 15.428472 40.0 400.5 9.125332 \n",
"8000.5 -24.003403 40.0 400.5 -50.378863 \n",
"12000.5 -27.004394 40.0 400.5 -72.992035 \n",
"16000.5 -18.811241 40.0 400.5 -78.189635 \n",
"20000.5 -29.553983 40.0 400.5 -87.854409 \n",
"24000.5 -20.272949 40.0 400.5 -89.615552 \n",
"28000.5 -31.488694 40.0 400.5 -95.714551 \n",
"32000.5 -19.854985 40.0 400.5 -95.809296 \n",
"36000.5 -31.246213 40.0 400.5 -99.759212 \n",
"40000.5 -19.233865 40.0 400.5 -99.335485 \n",
"44000.5 -12.129763 40.0 400.5 -97.021365 \n",
"48000.5 10.577317 40.0 400.5 -89.403447 \n",
"52000.5 -9.020571 40.0 400.5 -87.510926 \n",
"56000.5 -9.436242 40.0 400.5 -85.972747 \n",
"60000.5 -31.330872 40.0 400.5 -88.983683 \n",
"64000.5 -5.644547 40.0 400.5 -86.825863 \n",
"68000.5 -28.311395 40.0 400.5 -88.945980 \n",
"72000.5 -19.292133 40.0 400.5 -89.266078 \n",
"76000.5 -4.006912 40.0 400.5 -87.196266 \n",
"80000.5 -30.271102 40.0 400.5 -89.240322 \n",
"84000.5 -14.004152 40.0 400.5 -88.774951 \n",
"88000.5 -42.098855 40.0 400.5 -92.166832 \n",
"92000.5 -9.238977 40.0 400.5 -91.002878 \n",
"96000.5 -43.590564 40.0 400.5 -94.232951 \n",
"100000.5 -43.440455 40.0 400.5 -97.170620 \n",
"104000.5 -3.568891 40.0 400.5 -95.303719 \n",
"108000.5 -24.874761 40.0 400.5 -95.933077 \n",
"112000.5 -3.441934 40.0 400.5 -94.227149 \n",
"116000.5 -9.032035 40.0 400.5 -93.198698 \n",
"120000.5 1.487278 40.0 400.5 -91.195735 \n",
"... ... ... ... ... \n",
"308000.5 -28.710064 40.0 400.5 -95.784777 \n",
"312000.5 -23.076090 40.0 400.5 -95.927744 \n",
"316000.5 -24.336979 40.0 400.5 -96.117792 \n",
"320000.5 2.020660 40.0 400.5 -95.309802 \n",
"324000.5 -15.302837 40.0 400.5 -95.163531 \n",
"328000.5 -21.306948 40.0 400.5 -95.239122 \n",
"332000.5 -26.898011 40.0 400.5 -95.512951 \n",
"336000.5 -15.047147 40.0 400.5 -95.359666 \n",
"340000.5 -14.734657 40.0 400.5 -95.205255 \n",
"344000.5 -25.377967 40.0 400.5 -95.419098 \n",
"348000.5 -9.835368 40.0 400.5 -95.096557 \n",
"352000.5 -45.918617 40.0 400.5 -96.016492 \n",
"356000.5 -28.956869 40.0 400.5 -96.334658 \n",
"360000.5 -18.324828 40.0 400.5 -96.291717 \n",
"364000.5 10.592855 40.0 400.5 -95.296701 \n",
"368000.5 -9.164740 40.0 400.5 -94.969708 \n",
"372000.5 9.583231 40.0 400.5 -94.042892 \n",
"376000.5 -13.130436 40.0 400.5 -93.857549 \n",
"380000.5 -20.573801 40.0 400.5 -93.914095 \n",
"384000.5 -31.464281 40.0 400.5 -94.306487 \n",
"388000.5 -23.395215 40.0 400.5 -94.448342 \n",
"392000.5 -17.679262 40.0 400.5 -94.404683 \n",
"396000.5 0.952222 40.0 400.5 -93.801894 \n",
"400000.5 -23.540295 40.0 400.5 -93.942884 \n",
"404000.5 -41.328331 40.0 400.5 -94.607919 \n",
"408000.5 -18.446270 40.0 400.5 -94.593475 \n",
"412000.5 -9.956440 40.0 400.5 -94.327922 \n",
"416000.5 -8.377054 40.0 400.5 -94.020780 \n",
"420000.5 -5.776745 40.0 400.5 -93.650548 \n",
"424000.5 9.150613 40.0 400.5 -92.861258 \n",
"\n",
" leg_switch_reward lin_vel_reward position quad_contact_cost \\\n",
"steps \n",
"4000.5 0.285500 0.070601 1.548446 -2.472562 \n",
"8000.5 0.232750 0.077041 1.705007 -2.120969 \n",
"12000.5 0.186500 0.020328 1.828903 -2.127979 \n",
"16000.5 0.186500 0.022882 2.054154 -2.119297 \n",
"20000.5 0.209900 0.009446 2.018187 -2.046362 \n",
"24000.5 0.193083 -0.015976 1.956940 -1.997354 \n",
"28000.5 0.214857 0.035294 1.921250 -2.007009 \n",
"32000.5 0.194812 -0.008265 1.903555 -2.033891 \n",
"36000.5 0.194111 0.008420 1.836762 -2.032618 \n",
"40000.5 0.195500 0.005288 1.849608 -2.000762 \n",
"44000.5 0.185091 0.003564 1.776524 -1.996920 \n",
"48000.5 0.182167 -0.002658 1.644775 -2.001734 \n",
"52000.5 0.178231 0.002521 1.660926 -1.990582 \n",
"56000.5 0.199179 0.005499 1.680981 -1.995598 \n",
"60000.5 0.191333 0.008175 1.692749 -2.012542 \n",
"64000.5 0.202906 0.000194 1.673126 -2.014898 \n",
"68000.5 0.205118 0.021373 1.684573 -2.020250 \n",
"72000.5 0.196333 0.004747 1.724214 -2.034951 \n",
"76000.5 0.207684 0.010595 1.741209 -2.030655 \n",
"80000.5 0.202325 0.002668 1.764335 -2.028444 \n",
"84000.5 0.202262 0.000983 1.760559 -2.030735 \n",
"88000.5 0.200818 -0.005441 1.798274 -2.036281 \n",
"92000.5 0.206109 0.006316 1.792339 -2.038217 \n",
"96000.5 0.208187 0.000129 1.777263 -2.026099 \n",
"100000.5 0.202540 -0.004936 1.748328 -2.017295 \n",
"104000.5 0.208385 0.004970 1.811393 -2.015716 \n",
"108000.5 0.212852 -0.002024 1.807105 -2.014319 \n",
"112000.5 0.206036 0.007996 1.810939 -2.010103 \n",
"116000.5 0.201259 -0.004129 1.782489 -2.000569 \n",
"120000.5 0.196033 -0.004114 1.788853 -1.995646 \n",
"... ... ... ... ... \n",
"308000.5 0.174526 0.001890 1.840785 -2.014213 \n",
"312000.5 0.177077 0.002362 1.832647 -2.014661 \n",
"316000.5 0.182222 0.001274 1.835341 -2.012020 \n",
"320000.5 0.182613 -0.000708 1.829982 -2.011155 \n",
"324000.5 0.182605 0.001098 1.820914 -2.012655 \n",
"328000.5 0.181305 0.000272 1.819064 -2.012011 \n",
"332000.5 0.182747 0.000838 1.816929 -2.015391 \n",
"336000.5 0.183810 0.001657 1.822713 -2.017940 \n",
"340000.5 0.186147 0.001543 1.822670 -2.014554 \n",
"344000.5 0.186250 -0.001282 1.820896 -2.012657 \n",
"348000.5 0.185724 -0.001203 1.815989 -2.007950 \n",
"352000.5 0.185682 0.000611 1.827056 -2.000303 \n",
"356000.5 0.185433 0.001569 1.827713 -2.001134 \n",
"360000.5 0.186406 0.000798 1.827721 -2.000875 \n",
"364000.5 0.188764 -0.001131 1.815978 -2.000109 \n",
"368000.5 0.191533 0.001028 1.816592 -2.003416 \n",
"372000.5 0.191065 0.001168 1.816862 -2.002914 \n",
"376000.5 0.191415 0.000406 1.818154 -2.007324 \n",
"380000.5 0.189837 0.001001 1.821333 -2.007509 \n",
"384000.5 0.188474 -0.001194 1.822966 -2.007951 \n",
"388000.5 0.187325 0.000665 1.822733 -2.005641 \n",
"392000.5 0.187393 0.000139 1.820639 -2.009751 \n",
"396000.5 0.187505 0.001058 1.830544 -2.009674 \n",
"400000.5 0.189320 0.000971 1.829790 -2.011245 \n",
"404000.5 0.187738 0.001006 1.824316 -2.013222 \n",
"408000.5 0.188554 0.000253 1.821491 -2.011557 \n",
"412000.5 0.188238 0.000589 1.823128 -2.011543 \n",
"416000.5 0.188495 -0.000557 1.817646 -2.013103 \n",
"420000.5 0.189757 0.003217 1.819190 -2.015410 \n",
"424000.5 0.189651 0.000655 1.817318 -2.013035 \n",
"\n",
" quad_joint_angle_cost quad_power_cost reward \n",
"steps \n",
"4000.5 -0.601705 -0.121749 15.428472 \n",
"8000.5 -0.548225 -0.124130 -4.287465 \n",
"12000.5 -0.520995 -0.145143 -11.859775 \n",
"16000.5 -0.542288 -0.151087 -13.597642 \n",
"20000.5 -0.523966 -0.161338 -16.788910 \n",
"24000.5 -0.509704 -0.163246 -17.369583 \n",
"28000.5 -0.513981 -0.174407 -19.386599 \n",
"32000.5 -0.508228 -0.170573 -19.445147 \n",
"36000.5 -0.506536 -0.173296 -20.756377 \n",
"40000.5 -0.501912 -0.175004 -20.604125 \n",
"44000.5 -0.496669 -0.174887 -19.833729 \n",
"48000.5 -0.496787 -0.175965 -17.299475 \n",
"52000.5 -0.490189 -0.176964 -16.662636 \n",
"56000.5 -0.499409 -0.176319 -16.146465 \n",
"60000.5 -0.503418 -0.176143 -17.158759 \n",
"64000.5 -0.503954 -0.175746 -16.439121 \n",
"68000.5 -0.496782 -0.175948 -17.137490 \n",
"72000.5 -0.492618 -0.179009 -17.257192 \n",
"76000.5 -0.491321 -0.179465 -16.559809 \n",
"80000.5 -0.492691 -0.179657 -17.245374 \n",
"84000.5 -0.492974 -0.177674 -17.091030 \n",
"88000.5 -0.495948 -0.179564 -18.227749 \n",
"92000.5 -0.503308 -0.178819 -17.836933 \n",
"96000.5 -0.500903 -0.178367 -18.910001 \n",
"100000.5 -0.501833 -0.181513 -19.891219 \n",
"104000.5 -0.500457 -0.183773 -19.263437 \n",
"108000.5 -0.496048 -0.181175 -19.471264 \n",
"112000.5 -0.492748 -0.180397 -18.898788 \n",
"116000.5 -0.492186 -0.181342 -18.558555 \n",
"120000.5 -0.490633 -0.180987 -17.890361 \n",
"... ... ... ... \n",
"308000.5 -0.489832 -0.181992 -19.431466 \n",
"312000.5 -0.489650 -0.181962 -19.478192 \n",
"316000.5 -0.490779 -0.181994 -19.539696 \n",
"320000.5 -0.488976 -0.182546 -19.270191 \n",
"324000.5 -0.488455 -0.182696 -19.221212 \n",
"328000.5 -0.487911 -0.182476 -19.246648 \n",
"332000.5 -0.488862 -0.182880 -19.338833 \n",
"336000.5 -0.488056 -0.183028 -19.287741 \n",
"340000.5 -0.487522 -0.182885 -19.234176 \n",
"344000.5 -0.486891 -0.183168 -19.305615 \n",
"348000.5 -0.487463 -0.182836 -19.196762 \n",
"352000.5 -0.487114 -0.183640 -19.500419 \n",
"356000.5 -0.486855 -0.184369 -19.606671 \n",
"360000.5 -0.487775 -0.184123 -19.592429 \n",
"364000.5 -0.488048 -0.184941 -19.260722 \n",
"368000.5 -0.487366 -0.185021 -19.150983 \n",
"372000.5 -0.486753 -0.185713 -18.842013 \n",
"376000.5 -0.485283 -0.185419 -18.781252 \n",
"380000.5 -0.484451 -0.185144 -18.800121 \n",
"384000.5 -0.483834 -0.185125 -18.932039 \n",
"388000.5 -0.483057 -0.185104 -18.978051 \n",
"392000.5 -0.482796 -0.184697 -18.964798 \n",
"396000.5 -0.482872 -0.184972 -18.763616 \n",
"400000.5 -0.485025 -0.185287 -18.811383 \n",
"404000.5 -0.485388 -0.185184 -19.034323 \n",
"408000.5 -0.484752 -0.184696 -19.028558 \n",
"412000.5 -0.485977 -0.184822 -18.940479 \n",
"416000.5 -0.486009 -0.184768 -18.838908 \n",
"420000.5 -0.485668 -0.184866 -18.714506 \n",
"424000.5 -0.486136 -0.184759 -18.451628 \n",
"\n",
"[106 rows x 15 columns]"
]
},
"execution_count": 79,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = pd.DataFrame(datas)\n",
"df = df.set_index('steps')\n",
"df"
]
},
{
"cell_type": "code",
"execution_count": 83,
"metadata": {
"ExecuteTime": {
"end_time": "2018-12-02T07:35:02.882221Z",
"start_time": "2018-12-02T07:35:02.671787Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7ffa1e391c18>"
]
},
"execution_count": 83,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7ffa1da84ac8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df['reward'].plot(style='.', title='reward')\n",
"df['Reward'].plot(style='.', title='Reward')"
]
},
{
"cell_type": "code",
"execution_count": 84,
"metadata": {
"ExecuteTime": {
"end_time": "2018-12-02T07:35:19.882538Z",
"start_time": "2018-12-02T07:35:19.683529Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7ffa1db2f588>"
]
},
"execution_count": 84,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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gZmb9qfMYweuAD0kaBf6L1N4PfBl4ITAB3Ae8psYazMysg9qCICL+HTihon8AZ9Y1XzMzm555c4sJMzPrjYPAzCxzDgIzs8w5CGaI735qZsNqXtx9dNDa3f1087bdvvWFmc1pDoIZUHX30xNWLprW7bEdGGY2KPMyCGZrpdqYz6KDFrJwdIQH9k5Ouftpq4Como5/T8HMBmXeBcFsrVSb53POqcex+749U8KncXvs5oBo1m1gmJnVYd4FwWytVJvns/u+PZx54lHA1D2S8u2xAc6/euIheyrtAsNNRv3x8jPrbN4FQbdb4b3q1BxUtUdy5olHVfYH2gbGooMW8pdfvNlNRj1yk5tZd+ZdEDT/SA1Ub4X3opvmoFZ7JM39L79uB5+7bkfbwBiRmIxwk1Ey3a17N7mZdWfeBQHs/5Gamd4ibNcc1NBqj6S5v6BjYBDByIgQMSd+grPfZpZ+xu/lvWxe5osOWjhjGwVm88m8DIKGmd4i7KbZqdXPZlbtqVx+3Y6OgVG119FQV/t31XS72RvqNM1eQrlRy233/Lrr97LqGE1zM9t06zebz+Z1EMz08YJufxu51c9mNvfvJjDarezqaP9utcIvr4j3PDDJOV+4icmIrufdSyiXaxkdEaMLRti3r/3WfatjNOdfPdFX/Wbz2bwOgjp+1H4mfxu528BoKG/p1tX+XZ5ueYVZXhGrh2MXnZppyq+tUUc5fPZNBi9bu4Jlhz288iB61Tjl2srzr6q/Mb73ECxH8zoIYP78qH3VlnodZ0e1WmFWrYjL8+7UTFUO5apmmsbj0RGBxN59D90LOH3Nck5YuWjK1n3zgffmcRrLpWr+5VCaT2cX+ZRZg+JzsOCQxVW/Kf8Q8z4I5ouqA9UzubfTrl29scJsrIgBnvDYQ6dswbc6ftCovVFj1Yr8Kzfdvv/xvgCCYGr4tLtQr3zgvdU4MHWjoFx/u72rYVipNu9Ndfte2PzV2HBccPCiZd0M7yAYElXHO2Zqb6dVuzpMXWG2Wqm2an8vb92Xt7SbX8spT1zKd3/8Mx7YO8mCNE7zXkBZpwPvVeM0a152Vc1W7Q4ww+yvVLs5iH/6muXTei+sf1XNmtP5XNQxfqOJFHX3GhwEQ6LT8Y5etly7OSOnm7Bp2f5e2rovT7fqtTTvYUz3gHw/e0etmq3K13G0W6nWeQZS+QLGqlBqfu8CunovLr9uh/cO+lD1vnT6XFStsNuN381NKluN32gipfhp4I7U5XADNTY2FuPj44MuY87q5Qyi5jNyylvhvWwtNn8wq7buh2Er9PyrJ3j/V29hMoof6xgZERExZaXa2MgK9g9TPgMJqAy1cvd0T7kth1J5nlXvXWM+rd6LBbMYZHPJTF0H02pjod3notVxsFbjLxC8bO3jHmzihKmfo6rPRdX4573yxJ17f3HX8k6vzXsE80Avbdzlcdq1q3erVft7Y17DspJpdR1Hq5Vq8xlIzQeuy1torVa+UL2MWl1c2OogfvNpyFD9Xtx2z6+5+NqfVJ5KO9OhMN2Vb/PwrZpNeunuZWOp08q3/L60+1y0Og7WavwFI+Kzm3dUfnbKzX+txm80kb7nl3f/tJv3Kbsg6Lc9bi5qdb1Eu4vAmsfppl29W83NNsO0bNs1wVWtVJsPqE+5YrzcHFPq7tR2X552p1Dq9N5VvRebt+1+8JiKWjR/ddq7ab52o5uVb6vwa16W3ZxNNp3u5pVnN01j7Y69NF/xX/W6mt+jdsfBqsYvh3Vzs165+a/V+NNdp2XVNFTVHDJfDp5VbXlVNXO0+pIP82sftKotx1bNMc1bi1W78+V7ULXaQp/pZo7mUGiupdUeTbs27tPXLH9wZVbVnNW8wh5pmv9vHbWEb07c9ZDlNN3u8mspvy/t9s7KK+Lm8Ttd8d/qPZrORmhjXdWqibXT+A2SNkfEWKfPQ1Z7BFOaUFocyGw2DKcPwtQtv6o7pFZdRHXmiUfN6dc0LNoduIbWW75VX/Lme1BV3c+qap791NzY0+l276a85zDlxohttlxbHrhu0UzSbit6ut2NvabT1yxv2zTW6RqWxvjdrguq9sa63VOuOjOu6i4EMyWrICg3hzR/UKouyBrG2xi3ag6qugjM6tHuC9/pOApU34Nqtuptruvypq3o5j2aTm3UjZVnpwPXVc0k7c4mm253eeXZqmmsm2tYZvP7P5tNrFk1DcH0jhGUm1YWCN7y/CdUbp3NJe1qHpa9m9zNpfep3SmP022j7ubA72xfkzHsZ7l10m3TUHZBMB3ldrph+WAMY802fOZSWPVrPp5A0jArQSDpD4B3Ar8JrI2I8dJzZwF/AuwD/iwirkz9TwY+BCwAPhER7+00n9kOgmH/YMynL6mZ9W62DhbfBLwEuKBp5scC64HjgCOAqyQdk54+H3gesAP4rqQrIuJ7fdbRt1ZXcJZvtzAsZurWE2aWh76CICL+E0B6yA0tTgMuiYj7gVslTQBr03MTEbE1jXdJGnagQeCfhzSznI3UNN1lwPbS4x2pX6v+DyFpg6RxSeO7du2qqcxC+bTSycnilLgFwmfXmFkWOu4RSLoKqLqn9dkR8YWZL6kQERuBjVAcI6hrPjC9n4c0M5tvOgZBRJzUw3R3AitKj5enfrTpPzCd7uxpZjaf1XVB2RXAP0r6W4qDxUcD11Jc+X20pCMpAmA98Ic11TAtPsBqZrnqKwgk/R7wv4HDgS9Juj4iXhARN0u6lOIg8F7gzIjYl8Z5A3AlxemjF0bEzX29AjMz64svKDMzm6e6vY6grrOGzMxsSDgIzMwy5yAwM8ucg8DMLHNDcbBY0i5g26DraLIEuGvQRbTh+vrj+no3l2uDvOpbGRGHdxpoKIJgLpI03s3R+EFxff1xfb2by7WB66vipiEzs8w5CMzMMucg6N3GQRfQgevrj+vr3VyuDVzfQ/gYgZlZ5rxHYGaWOQeBmVnuIiLrP+DHwI3A9cB46vco4GvAD9P/Ram/gA8DE8AWYE1pOq9Kw/8QeFWp/wlp+hNpXHWo50LgTuCmUr/a62k1jy7reyfFbcWvT38vLD13VprXLcALSv1PTv0mgHeU+h8JfCf1/wywMPU/MD2eSM+valHfCuBqijvf3gy8ca4swza1zYnlBzyM4nbxN6T63tXrNGeq7i7r+yRwa2n5HT+o70cadgHwH8AX59Lya7vemakV6rD+UQTBkqZ+5zUWMvAO4K9T9wuBr6QP2DrgO6UPydb0f1Hqbqxork3DKo17Sod6ng2sYeqKtvZ6Ws2jy/reCfyPimGPpfjSHpg+qD9KX5IFqXs1sDANc2wa51Jgfer+GHBG6v5T4GOpez3wmRb1LSV94YFDgR+kOga+DNvUNieWX3o9h6TuAyhWLOumO82ZrLvL+j4J/H7F8LP+/UjPvwX4R/YHwZxYfm3XOzO5Uh3GP6qD4BZgaenLe0vqvgB4efNwwMuBC0r9L0j9lgLfL/WfMlybmlYxdUVbez2t5tFlfe+kekV2FnBW6fGVwDPS35XNw6Uv313AaOr/4HCNcVP3aBqu7d5VGvYLwPPm2jJsqm3OLT/gIOA64OnTneZM1t1lfZ+kOghm/b2l+NXFrwO/C3yxl/dkNpZf85+PEUAAX5W0WdKG1O8xEXF76v4p8JjUvQzYXhp3R+rXrv+Oiv7TNRv1tJpHt94gaYukCyU1fuptuvUtBu6JiL0V9T04Tnr+3jR8S5JWAU+l2HKcU8uwqTaYI8tP0gJJ11M0/32NYgt0utOcybrb1hcRjeV3blp+H5B0YHN9XdYxE+/tB4G3AZPpcS/vSW3LrxUHAfx2RKwBTgHOlPTs8pNRRGwMpLIKs1FPD/P4KPB44HjgduD9ddQ1HZIOAS4H3hQRPy8/N+hlWFHbnFl+EbEvIo6n2LJdC/zGoGqp0lyfpCdSbBX/BvA0iuaet9dcQ+V7K+lU4M6I2Fzn/OuQfRBExM70/07g8xQf/jskLQVI/+9Mg++kOODXsDz1a9d/eUX/6ZqNelrNo6OIuCN9QSeBj1Msw17quxs4TNJoU/8p00rPPzIN/xCSDqBY0V4UEZ/r8PpmdRlW1TbXll+q6R6KA9vP6GGaM1l3p/pOjojbo3A/8H/pffn1+/14JvBiST8GLqFoHvpQm9c2sOX3ENNpR5pvf8DBwKGl7m9RHJV/H1MPDJ2Xul/E1INP16b+j6I4a2FR+rsVeFR6rvng0wu7qGsVU9vga6+n1Ty6rG9pqfvNwCWp+zimHvTaSnHAazR1H8n+g17HpXEuY+pBrz9N3Wcy9cDapS1qE/Ap4INN/Qe+DNvUNieWH8Vvjx+Wuh8O/Btw6nSnOZN1d1nf0tLy/SDw3kF+P9Iwz2H/weI5sfza1jtTK9Vh/KM4+n4D+09HOzv1X0xxwOeHwFWlD4mA8ynaTW8ExkrT+mOKU7cmgNeU+o8BN6VxPkLn00cvpmgeeICire9PZqOeVvPosr5/SPPfAlzB1BXb2Wlet1A6Y4rijI4fpOfObnpPrk11XwYcmPo/LD2eSM+vblHfb1Pstm+hdDrmXFiGbWqbE8sPeDLFaY9b0us7p9dpzlTdXdb3L2n53QR8mv1nFs3696M0neewPwjmxPJr9+dbTJiZZS77YwRmZrlzEJiZZc5BYGaWOQeBmVnmHARmZplzEJh1IOlNkg4adB1mdfHpo2YdpCtFxyLirkHXYlYH7xGYlUg6WNKXJN0g6SZJfwEcAVwt6eo0zPMlfVvSdZIuS/cOQtKPJZ0n6UZJ10o6KvX/gzStGyR9Y3Cvzqyag8BsqpOB2yLiKRHxRIpbFtwGnBgRJ0paAvw5cFIUNyscp7j/fMO9EfEkiqtSP5j6nUPx4yJPAV48Wy/ErFsOArOpbgSeJ+mvJT0rIu5ten4dxQ+HfDPdDvlVwMrS8xeX/j8jdX8T+KSk11HcM8ZsThntPIhZPiLiB5LWUNzT5a8kfb1pEFHcB//lrSbR3B0Rr5f0dIqboG2WdEJEtLzzp9ls8x6BWYmkI4D7IuLTFHecXAP8guKnJQE2Ac8stf8fLOmY0iReVvr/7TTM4yPiOxFxDrCLqbcSNhs47xGYTfUk4H2SJinusHoGRRPPP0u6LR0neDVwcemXsP6c4o6QAIskbQHup/ipQ9L0jqbYm/g6xd1uzeYMnz5qNkN8mqkNKzcNmZllznsEZmaZ8x6BmVnmHARmZplzEJiZZc5BYGaWOQeBmVnm/j833oxlzwl6QwAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7ffa1d993c88>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df['head_height_reward'].plot(style='.', title='head height reward')"
]
},
{
"cell_type": "code",
"execution_count": 81,
"metadata": {
"ExecuteTime": {
"end_time": "2018-12-02T07:34:43.257152Z",
"start_time": "2018-12-02T07:34:40.657601Z"
},
"scrolled": false
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7ffa1d65a630>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7ffa1d646c18>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7ffa1d7a5470>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7ffa1d84b898>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7ffa1d934e80>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7ffa1d6ac198>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7ffa1da831d0>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7ffa1d5e2710>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7ffa1d8e9ef0>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7ffa1d867208>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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JJ9ew6+lWR7ljKQml323S3SM8mp646pi6ol89Vpo2dST31wPvyM6wmz0R8XXgdOCG7hUz8wrgCuiMlqlh31OtjprxUgx7V980JLkmjeeWmmCooZBFzf0TPUbLvAf4Vma+LSKeBNwIPDsz7+m3TYdCdqzUNw41aZiXpPHVNrdMRFwLnAMcHxH7gLcC6wEy83LgN4GrIuIWOkN/f31QYtej6qoZ99PUoYySls8wo2XOH/D8XcCLa4tolap7uuNhpoa1FS+1l9MPNESdNeOqqWEnOZOjpJVncm+Q7tEa49bJh50atkk3JEmq16pM7tPQubiUOvkoU8M25YYkSfVadcl9WjoXlzIGfpypYSW1y6pL7k2dJ6XbUjtYx5kaVlJ7rLrkPi1fwm0LW9JSrMr53Keh5i5JVab2C7JXwiTKEp5QJK2kVZncV1rVuPNeX+ElSXUwua+AcifuwjeYL3wdW1NH60iabmsmHcBqsNCJuzYe/Z7N8mgdSaqbLfcVUPWNQU0frSNpupncV0i5E9evY5O03EzuEzDOaB1H20gahcl9CkzLlAmSmsMO1SlQNWWCJPVjcl9Gs3OH2LFzD7Nzh5a0nfJoGzthJQ3DsswyqbOU4jwzkkZlcl8mdc8+6UyOkkZhWWaZWEqRNEm23JeJpRRJk2RyX0aWUiRNimWZGtU1OkaSlsqWe0280UhSk9hyr4k3GklqEpN7TRwdI6lJLMvUxNExkprE5F4jR8dIagrLMpLUQiZ3SWqhiSd3x4ZLUv0G1twj4krgPGB/Zp5R8fyvAa8tbe8ZwObMvHfQth0bLknLY5iW+1XAub2ezMxLM/PMzDwTuBj4q2ESOzg2XJKWy8DknpnXA0Mla+B84Nphd+7YcElaHrUNhYyIo+m08H+xzzoXAhcCnHzyyY4Nl6RlUuc491cAn+tXksnMK4ArAGZmZhKmZ2z47NwhT0KSpkadyf01jFCSmSZ2/EqaNrUMhYyIJwD/FPhYHdtrGjt+JU2bYYZCXgucAxwfEfuAtwLrATLz8mK1nwA+lZn3L1OcE7XQ8fvQ4fkjOn4t10hqosjMiex4ZmYmd+/ePZF9D6ucuIEjkrjlGkkrLSJmM3Nm0HpOHNZDVeK+6IVPW7ROVbnG5C6pCSY+/UBTDVNnd5y+pKay5d7DsHV2x+lLaiKTew+9brAaplwjSZNmcu+j6gYr6+ySpoE19xFZZ5c0DWy5j8j5cCRNA5N7ybA3JE3LfDiSVi+Te8EbkiS1iTX3gvPHSGoTk3vBjlJJbWJZpmBHqaQ2MbmX2FEqqS1WfVlmdu4QO3buYXbu0KRDkaTarOqWuyNkJLXVqm65O0JGUlut6uTuCBlJbbWqyzKOkJHUVqs6uYMjZCS106ouy0hSW5ncJamFTO6S1EImd0lqIZO7JLWQyV2SWsjkLkktZHKXpBYyuUtSC5ncJamFTO6S1EIDk3tEXBkR+yPi1j7rnBMRN0XEbRHxV/WGKEka1TAt96uAc3s9GRHHAf8deGVmPgv4yXpCkySNa2Byz8zrgXv7rPKvgI9m5t8X6++vKTZJ0pjqqLmfBmyMiL+MiNmI+OleK0bEhRGxOyJ2HzhwoIZdS5Kq1JHc1wFnAS8HXgK8JSJOq1oxM6/IzJnMnNm8eXMNu5YkVanjyzr2AQcz837g/oi4Hng28NUati1JGkMdLfePAc+PiHURcTRwNvDlGrYrSRrTwJZ7RFwLnAMcHxH7gLcC6wEy8/LM/HJE/BlwMzAPvC8zew6blCQtv4HJPTPPH2KdS4FLa4lIkrRk3qEqSS1kcpekFjK5S1ILmdwlqYVM7pLUQiZ3SWohk7sktZDJXZJayOQuSS1kcpekFjK5S1ILmdwlqYUmltz3f/f7zM4dmtTuJanVJpbcv3XfP/Da9+0ywUvSMphoWeahw/Ps2ntwkiFIUitNNLmvX7eG7adummQIktRKE0vuT3r8Y7jmgu2cdcrGSYUgSa01seT+j449ysQuScvEoZCS1EImd0lqIZO7JLWQyV2SWsjkLkktZHKXpBaKzJzMjiMOAHMT2XlvxwP3TDqIPoxvfE2ODYxvqVZTfKdk5uZBK00suTdRROzOzJlJx9GL8Y2vybGB8S2V8R3JsowktZDJXZJayOS+2BWTDmAA4xtfk2MD41sq4+tizV2SWsiWuyS1kMldktooM1v3A9wB3ALcBOwulj0R+DTwteLfjcXyAN4N7AFuBraVtvO6Yv2vAa8rLT+r2P6e4ndjQDxXAvuBW0vLlj2eXvsYMr63AXcWx/Am4GWl5y4u9nU78JLS8nOLZXuA3ygtfwrwhWL5h4ANxfKjiv/vKZ7fWhHbk4GdwJeA24BfatLx6xNfU47fY4AbgC8W8f3HcbdZV9xDxncV8PXS8TtzUn8fxbprgb8FPtGk49c379SVUJv0Qye5H9+17J0LBw74DeC3i8cvAz5ZfGi2A18ovfF7i383Fo8XEsgNxbpR/O5LB8TzAmAbi5PnssfTax9Dxvc24Fcr1n0mnT/Eo4oP398VH/y1xeNTgQ3FOs8sfufDwGuKx5cDP188/gXg8uLxa4APVezvBIo/YOBY4KtFDI04fn3ia8rxC+CY4vF6Osli+6jbrDPuIeO7CviXFeuv+N9H8fwvA3/Io8m9Ecevb96pM6k25Yfq5H47cELpD/L24vF7gfO71wPOB95bWv7eYtkJwFdKyxet1yemrSxOnsseT699DBnf26hOThcDF5f+/+fAc4ufP+9er/iDugdYVyx/ZL2F3y0eryvWG3QV9DHgx5t2/Cria9zxA44GbgTOHnWbdcY9ZHxXUZ3cV/z9BbYAnwFeBHxinPdkJY5f909ba+4JfCoiZiPiwmLZkzLz7uLxN4EnFY9PAr5R+t19xbJ+y/dVLB/VSsTTax/D+sWIuDkiroyIha/NGjW+TcC3M/NwRXyP/E7x/HeK9StFxFbgR+i07hp3/Lrig4Ycv4hYGxE30Sm9fZpOS3HUbdYZd9/4MnPh+P1Wcfx+LyKO6o5vyDjqeH/fBfwHYL74/zjvybIdv17amtyfn5nbgJcCF0XEC8pPZudUmBOJrMJKxDPGPt4DPBU4E7gb+N3liGtYEXEMcB3whsy8r/xcE45fRXyNOX6Z+XBmnkmnBfoc4PRJxVKlO76IOINO6/V04EfplFp+fZljqHx/I+I8YH9mzi7n/pdDK5N7Zt5Z/Lsf+CM6H+hvRcQJAMW/+4vV76TTKbZgS7Gs3/ItFctHtRLx9NrHQJn5reKPbh74AzrHcJz4DgLHRcS6ivge+Z3i+ScU6y8SEevpJM5rMvOjA17bih+/qviadPwWZOa36XT+PneMbdYZ96D4zs3Mu7Pj+8D7Gf/4LfX9fR7wyoi4A/ggndLM7/d5bRM7fkcYpYYzDT/A44BjS4//hk5v9KUs7jx5Z/H45SzuoLmhWP5EOr31G4ufrwNPLJ7r7qB52RBxbWVxTXvZ4+m1jyHjO6H0+N8DHyweP4vFHUN76XQKrSseP4VHO4aeVfzOR1jcMfQLxeOLWNz59OGKuAL4APCuruWNOH594mvK8dsMHFc8fizw18B5o26zzriHjO+E0vF9F/COSf59FOucw6Mdqo04fn3jrSupNuWHTq/zF3l0aNWbiuWb6HSKfA34i9IbH8AOOnXIW4CZ0rb+LZ1hSHuA15eWzwC3Fr9zGYM7Aa+lc2n+EJ3a2c+uRDy99jFkfP+r2P/NwMdZnKzeVOzrdkojheiMZPhq8dybut6TG4q4PwIcVSx/TPH/PcXzp1bE9nw6l8s3UxpW2JTj1ye+phy/H6YzhO/m4jVeMu4264p7yPg+Wxy/W4GreXREzYr/fZS2cw6PJvdGHL9+P04/IEkt1MqauyStdiZ3SWohk7sktZDJXZJayOQuSS1kcteqFBFviIijJx2HtFwcCqlVqbjjcCYz75l0LNJysOWu1ouIx0XEn0TEFyPi1oh4K3AisDMidhbrvDgiPh8RN0bER4q5YoiIOyLinRFxS0TcEBFPK5b/ZLGtL0bE9ZN7dVI1k7tWg3OBuzLz2Zl5Bp3b2e8CXpiZL4yI44E3A/8sOxPO7aYzf/eC72TmD9G5u/FdxbJL6HzhwrOBV67UC5GGZXLXanAL8OMR8dsR8U8y8ztdz2+n82UKnyumnn0dcErp+WtL/z63ePw54KqI+Dk6c4RIjbJu8CrSdMvMr0bENjpzeLw9Ij7TtUrQmUf8/F6b6H6cmf8uIs6mM5HVbESclZk9Z2SUVpotd7VeRJwIPJCZV9OZCXAb8F06X4sHsAt4Xqme/riIOK20iVeX/v18sc5TM/MLmXkJcIDF07ZKE2fLXavBDwGXRsQ8nZkvf55OeeXPIuKuou7+M8C1pW/8eTOdmfoANkbEzcD36XxNG8X2nk6n1f8ZOrOQSo3hUEipD4dMalpZlpGkFrLlLkktZMtdklrI5C5JLWRyl6QWMrlLUguZ3CWphf4/pfjd+Gu0UIsAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7ffa1d9eba58>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7ffa1e07b4a8>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7ffa1df4eb70>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7ffa1dfb44a8>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7ffa1d9e3d68>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"for col in df.columns:\n",
" df[col].plot(style='.', title=col)\n",
" plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "jupyter3.6",
"language": "python",
"name": "jupyter3.6"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.0"
},
"toc": {
"colors": {
"hover_highlight": "#DAA520",
"navigate_num": "#000000",
"navigate_text": "#333333",
"running_highlight": "#FF0000",
"selected_highlight": "#FFD700",
"sidebar_border": "#EEEEEE",
"wrapper_background": "#FFFFFF"
},
"moveMenuLeft": true,
"nav_menu": {
"height": "12px",
"width": "252px"
},
"navigate_menu": true,
"number_sections": true,
"sideBar": false,
"threshold": 4,
"toc_cell": false,
"toc_section_display": "block",
"toc_window_display": true,
"widenNotebook": false
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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