InspectAllen - Volume Mapping.ipynb

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   "source": [
    "%matplotlib inline\n",
    "import math\n",
    "import numpy\n",
    "from matplotlib import pyplot\n",
    "from allensdk.core.mouse_connectivity_cache import MouseConnectivityCache\n",
    "\n",
    "# The manifest file is a simple JSON file that keeps track of all of\n",
    "# the data that has already been downloaded onto the hard drives.\n",
    "# If you supply a relative path, it is assumed to be relative to your\n",
    "# current working directory.\n",
    "mcc = MouseConnectivityCache(manifest_file='data/manifest.json')\n",
    "# grab the Ontology instance\n",
    "ontology = mcc.get_ontology()"
   ]
  },
  {
   "cell_type": "code",
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       "      <td>1</td>\n",
       "      <td>985</td>\n",
       "      <td>Primary motor area Layer 6a</td>\n",
       "      <td>20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/8/567/688/695/315/500/985/844/</td>\n",
       "      <td>3473508879</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>882</th>\n",
       "      <td>MOp6b</td>\n",
       "      <td>1100</td>\n",
       "      <td>1F9D5A</td>\n",
       "      <td>8</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>3</td>\n",
       "      <td>882</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>985</td>\n",
       "      <td>Primary motor area Layer 6b</td>\n",
       "      <td>21</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/8/567/688/695/315/500/985/882/</td>\n",
       "      <td>1442896821</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>993</th>\n",
       "      <td>MOs</td>\n",
       "      <td>831</td>\n",
       "      <td>1F9D5A</td>\n",
       "      <td>7</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>3</td>\n",
       "      <td>993</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>500</td>\n",
       "      <td>Secondary motor area</td>\n",
       "      <td>22</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/8/567/688/695/315/500/993/</td>\n",
       "      <td>1043755260</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>656</th>\n",
       "      <td>MOs1</td>\n",
       "      <td>930</td>\n",
       "      <td>1F9D5A</td>\n",
       "      <td>8</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "      <td>3</td>\n",
       "      <td>656</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>993</td>\n",
       "      <td>Secondary motor area layer 1</td>\n",
       "      <td>23</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/8/567/688/695/315/500/993/656/</td>\n",
       "      <td>4032915713</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>962</th>\n",
       "      <td>MOs2/3</td>\n",
       "      <td>1110</td>\n",
       "      <td>1F9D5A</td>\n",
       "      <td>8</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>23</td>\n",
       "      <td>3</td>\n",
       "      <td>962</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>993</td>\n",
       "      <td>Secondary motor area layer 2/3</td>\n",
       "      <td>24</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/8/567/688/695/315/500/993/962/</td>\n",
       "      <td>3274108161</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>767</th>\n",
       "      <td>MOs5</td>\n",
       "      <td>944</td>\n",
       "      <td>1F9D5A</td>\n",
       "      <td>8</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>3</td>\n",
       "      <td>767</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>993</td>\n",
       "      <td>Secondary motor area layer 5</td>\n",
       "      <td>25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/8/567/688/695/315/500/993/767/</td>\n",
       "      <td>4144803096</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1021</th>\n",
       "      <td>MOs6a</td>\n",
       "      <td>1117</td>\n",
       "      <td>1F9D5A</td>\n",
       "      <td>8</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>1021</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>993</td>\n",
       "      <td>Secondary motor area layer 6a</td>\n",
       "      <td>26</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/8/567/688/695/315/500/993/1021/</td>\n",
       "      <td>3489757563</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1085</th>\n",
       "      <td>MOs6b</td>\n",
       "      <td>1125</td>\n",
       "      <td>1F9D5A</td>\n",
       "      <td>8</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>26</td>\n",
       "      <td>3</td>\n",
       "      <td>1085</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>993</td>\n",
       "      <td>Secondary motor area layer 6b</td>\n",
       "      <td>27</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/8/567/688/695/315/500/993/1085/</td>\n",
       "      <td>1225271489</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>453</th>\n",
       "      <td>SS</td>\n",
       "      <td>339</td>\n",
       "      <td>188064</td>\n",
       "      <td>6</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>27</td>\n",
       "      <td>3</td>\n",
       "      <td>453</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>315</td>\n",
       "      <td>Somatosensory areas</td>\n",
       "      <td>28</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/8/567/688/695/315/453/</td>\n",
       "      <td>3016301862</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12993</th>\n",
       "      <td>SS1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>188064</td>\n",
       "      <td>7</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>28</td>\n",
       "      <td>3</td>\n",
       "      <td>12993</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>453</td>\n",
       "      <td>Somatosensory areas layer 1</td>\n",
       "      <td>29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/8/567/688/695/315/453/12993/</td>\n",
       "      <td>544207135</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12994</th>\n",
       "      <td>SS2/3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>188064</td>\n",
       "      <td>7</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>29</td>\n",
       "      <td>3</td>\n",
       "      <td>12994</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>453</td>\n",
       "      <td>Somatosensory areas layer 2/3</td>\n",
       "      <td>30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/8/567/688/695/315/453/12994/</td>\n",
       "      <td>3920828838</td>\n",
       "      <td>8690</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>chfl</td>\n",
       "      <td>721</td>\n",
       "      <td>AAAAAA</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>1204</td>\n",
       "      <td>3</td>\n",
       "      <td>116</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>81</td>\n",
       "      <td>choroid fissure</td>\n",
       "      <td>1205</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/73/81/116/</td>\n",
       "      <td>3192898784</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>IVF</td>\n",
       "      <td>722</td>\n",
       "      <td>AAAAAA</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>1205</td>\n",
       "      <td>3</td>\n",
       "      <td>124</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>73</td>\n",
       "      <td>interventricular foramen</td>\n",
       "      <td>1206</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/73/124/</td>\n",
       "      <td>1644273448</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>V3</td>\n",
       "      <td>723</td>\n",
       "      <td>AAAAAA</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>1206</td>\n",
       "      <td>3</td>\n",
       "      <td>129</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>73</td>\n",
       "      <td>third ventricle</td>\n",
       "      <td>1207</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/73/129/</td>\n",
       "      <td>562407244</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>AQ</td>\n",
       "      <td>724</td>\n",
       "      <td>AAAAAA</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>1207</td>\n",
       "      <td>3</td>\n",
       "      <td>140</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>73</td>\n",
       "      <td>cerebral aqueduct</td>\n",
       "      <td>1208</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/73/140/</td>\n",
       "      <td>3509002335</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>V4</td>\n",
       "      <td>725</td>\n",
       "      <td>AAAAAA</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>1208</td>\n",
       "      <td>3</td>\n",
       "      <td>145</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>73</td>\n",
       "      <td>fourth ventricle</td>\n",
       "      <td>1209</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/73/145/</td>\n",
       "      <td>2366263365</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>V4r</td>\n",
       "      <td>726</td>\n",
       "      <td>AAAAAA</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>1209</td>\n",
       "      <td>3</td>\n",
       "      <td>153</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>145</td>\n",
       "      <td>lateral recess</td>\n",
       "      <td>1210</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/73/145/153/</td>\n",
       "      <td>4006455201</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>c</td>\n",
       "      <td>727</td>\n",
       "      <td>AAAAAA</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>1210</td>\n",
       "      <td>3</td>\n",
       "      <td>164</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>73</td>\n",
       "      <td>central canal spinal cord/medulla</td>\n",
       "      <td>1211</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/73/164/</td>\n",
       "      <td>3758121442</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1024</th>\n",
       "      <td>grv</td>\n",
       "      <td>693</td>\n",
       "      <td>AAAAAA</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>1211</td>\n",
       "      <td>3</td>\n",
       "      <td>1024</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>997</td>\n",
       "      <td>grooves</td>\n",
       "      <td>1212</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/1024/</td>\n",
       "      <td>1816833424</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1032</th>\n",
       "      <td>grv of CTX</td>\n",
       "      <td>694</td>\n",
       "      <td>AAAAAA</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>1212</td>\n",
       "      <td>3</td>\n",
       "      <td>1032</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1024</td>\n",
       "      <td>grooves of the cerebral cortex</td>\n",
       "      <td>1213</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/1024/1032/</td>\n",
       "      <td>4010583074</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1055</th>\n",
       "      <td>eg</td>\n",
       "      <td>697</td>\n",
       "      <td>AAAAAA</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>1213</td>\n",
       "      <td>3</td>\n",
       "      <td>1055</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1032</td>\n",
       "      <td>endorhinal groove</td>\n",
       "      <td>1214</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/1024/1032/1055/</td>\n",
       "      <td>2757546022</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1063</th>\n",
       "      <td>hf</td>\n",
       "      <td>698</td>\n",
       "      <td>AAAAAA</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>1214</td>\n",
       "      <td>3</td>\n",
       "      <td>1063</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1032</td>\n",
       "      <td>hippocampal fissure</td>\n",
       "      <td>1215</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/1024/1032/1063/</td>\n",
       "      <td>1845828307</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1071</th>\n",
       "      <td>rf</td>\n",
       "      <td>699</td>\n",
       "      <td>AAAAAA</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>1215</td>\n",
       "      <td>3</td>\n",
       "      <td>1071</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1032</td>\n",
       "      <td>rhinal fissure</td>\n",
       "      <td>1216</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/1024/1032/1071/</td>\n",
       "      <td>915997995</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1078</th>\n",
       "      <td>ri</td>\n",
       "      <td>700</td>\n",
       "      <td>AAAAAA</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>1216</td>\n",
       "      <td>3</td>\n",
       "      <td>1078</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1032</td>\n",
       "      <td>rhinal incisure</td>\n",
       "      <td>1217</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/1024/1032/1078/</td>\n",
       "      <td>1408661066</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1040</th>\n",
       "      <td>grv of CBX</td>\n",
       "      <td>695</td>\n",
       "      <td>AAAAAA</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>1217</td>\n",
       "      <td>3</td>\n",
       "      <td>1040</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1024</td>\n",
       "      <td>grooves of the cerebellar cortex</td>\n",
       "      <td>1218</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/1024/1040/</td>\n",
       "      <td>306524468</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1087</th>\n",
       "      <td>pce</td>\n",
       "      <td>701</td>\n",
       "      <td>AAAAAA</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>1218</td>\n",
       "      <td>3</td>\n",
       "      <td>1087</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1040</td>\n",
       "      <td>precentral fissure</td>\n",
       "      <td>1219</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/1024/1040/1087/</td>\n",
       "      <td>2084828473</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1095</th>\n",
       "      <td>pcf</td>\n",
       "      <td>702</td>\n",
       "      <td>AAAAAA</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>1219</td>\n",
       "      <td>3</td>\n",
       "      <td>1095</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1040</td>\n",
       "      <td>preculminate fissure</td>\n",
       "      <td>1220</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/1024/1040/1095/</td>\n",
       "      <td>3439430666</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1103</th>\n",
       "      <td>pri</td>\n",
       "      <td>703</td>\n",
       "      <td>AAAAAA</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>1220</td>\n",
       "      <td>3</td>\n",
       "      <td>1103</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1040</td>\n",
       "      <td>primary fissure</td>\n",
       "      <td>1221</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/1024/1040/1103/</td>\n",
       "      <td>1359711822</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1112</th>\n",
       "      <td>psf</td>\n",
       "      <td>704</td>\n",
       "      <td>AAAAAA</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>1221</td>\n",
       "      <td>3</td>\n",
       "      <td>1112</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1040</td>\n",
       "      <td>posterior superior fissure</td>\n",
       "      <td>1222</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/1024/1040/1112/</td>\n",
       "      <td>706594763</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1119</th>\n",
       "      <td>ppf</td>\n",
       "      <td>705</td>\n",
       "      <td>AAAAAA</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>1222</td>\n",
       "      <td>3</td>\n",
       "      <td>1119</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1040</td>\n",
       "      <td>prepyramidal fissure</td>\n",
       "      <td>1223</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/1024/1040/1119/</td>\n",
       "      <td>90069120</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>sec</td>\n",
       "      <td>707</td>\n",
       "      <td>AAAAAA</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>1223</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1040</td>\n",
       "      <td>secondary fissure</td>\n",
       "      <td>1224</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/1024/1040/3/</td>\n",
       "      <td>1603026106</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>plf</td>\n",
       "      <td>708</td>\n",
       "      <td>AAAAAA</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>1224</td>\n",
       "      <td>3</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1040</td>\n",
       "      <td>posterolateral fissure</td>\n",
       "      <td>1225</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/1024/1040/11/</td>\n",
       "      <td>3968698314</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>nf</td>\n",
       "      <td>709</td>\n",
       "      <td>AAAAAA</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>1225</td>\n",
       "      <td>3</td>\n",
       "      <td>18</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1040</td>\n",
       "      <td>nodular fissure</td>\n",
       "      <td>1226</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/1024/1040/18/</td>\n",
       "      <td>3778172686</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>sif</td>\n",
       "      <td>710</td>\n",
       "      <td>AAAAAA</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>1226</td>\n",
       "      <td>3</td>\n",
       "      <td>25</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1040</td>\n",
       "      <td>simple fissure</td>\n",
       "      <td>1227</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/1024/1040/25/</td>\n",
       "      <td>3504067713</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>icf</td>\n",
       "      <td>711</td>\n",
       "      <td>AAAAAA</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>1227</td>\n",
       "      <td>3</td>\n",
       "      <td>34</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1040</td>\n",
       "      <td>intercrural fissure</td>\n",
       "      <td>1228</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/1024/1040/34/</td>\n",
       "      <td>1415991612</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>apf</td>\n",
       "      <td>712</td>\n",
       "      <td>AAAAAA</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>1228</td>\n",
       "      <td>3</td>\n",
       "      <td>43</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1040</td>\n",
       "      <td>ansoparamedian fissure</td>\n",
       "      <td>1229</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/1024/1040/43/</td>\n",
       "      <td>2452402730</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>ipf</td>\n",
       "      <td>713</td>\n",
       "      <td>AAAAAA</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>1229</td>\n",
       "      <td>3</td>\n",
       "      <td>49</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1040</td>\n",
       "      <td>intraparafloccular fissure</td>\n",
       "      <td>1230</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/1024/1040/49/</td>\n",
       "      <td>2654107150</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>pms</td>\n",
       "      <td>714</td>\n",
       "      <td>AAAAAA</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>1230</td>\n",
       "      <td>3</td>\n",
       "      <td>57</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1040</td>\n",
       "      <td>paramedian sulcus</td>\n",
       "      <td>1231</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/1024/1040/57/</td>\n",
       "      <td>3972977495</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>pfs</td>\n",
       "      <td>715</td>\n",
       "      <td>AAAAAA</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>1231</td>\n",
       "      <td>3</td>\n",
       "      <td>65</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1040</td>\n",
       "      <td>parafloccular sulcus</td>\n",
       "      <td>1232</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/1024/1040/65/</td>\n",
       "      <td>771629690</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>624</th>\n",
       "      <td>IPF</td>\n",
       "      <td>926</td>\n",
       "      <td>AAAAAA</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>1232</td>\n",
       "      <td>3</td>\n",
       "      <td>624</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1024</td>\n",
       "      <td>Interpeduncular fossa</td>\n",
       "      <td>1233</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/1024/624/</td>\n",
       "      <td>1476705011</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>304325711</th>\n",
       "      <td>retina</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7F2E7E</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "      <td>734881840</td>\n",
       "      <td>1</td>\n",
       "      <td>1233</td>\n",
       "      <td>3</td>\n",
       "      <td>304325711</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>997</td>\n",
       "      <td>retina</td>\n",
       "      <td>1234</td>\n",
       "      <td>NaN</td>\n",
       "      <td>/997/304325711/</td>\n",
       "      <td>3295290839</td>\n",
       "      <td>8690</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1234 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              acronym  atlas_id color_hex_triplet  depth failed  failed_facet  \\\n",
       "id                                                                              \n",
       "997              root        -1            FFFFFF      0  False     734881840   \n",
       "8                grey         0            BFDAE3      1  False     734881840   \n",
       "567                CH        70            B0F0FF      2  False     734881840   \n",
       "688               CTX        85            B0FFB8      3  False     734881840   \n",
       "695             CTXpl        86            70FF70      4  False     734881840   \n",
       "315         Isocortex       746            70FF71      5  False     734881840   \n",
       "184               FRP       871            268F45      6  False     734881840   \n",
       "68               FRP1       998            268F45      7  False     734881840   \n",
       "667            FRP2/3      1073            268F45      7  False     734881840   \n",
       "500                MO       203            1F9D5A      6  False     734881840   \n",
       "107               MO1      1003            1F9D5A      7  False     734881840   \n",
       "219             MO2/3      1017            1F9D5A      7  False     734881840   \n",
       "299               MO5      1027            1F9D5A      7  False     734881840   \n",
       "644              MO6a       787            1F9D5A      7  False     734881840   \n",
       "947              MO6b       825            1F9D5A      7  False     734881840   \n",
       "985               MOp       830            1F9D5A      7  False     734881840   \n",
       "320              MOp1       888            1F9D5A      8  False     734881840   \n",
       "943            MOp2/3       966            1F9D5A      8  False     734881840   \n",
       "648              MOp5       929            1F9D5A      8  False     734881840   \n",
       "844             MOp6a      1095            1F9D5A      8  False     734881840   \n",
       "882             MOp6b      1100            1F9D5A      8  False     734881840   \n",
       "993               MOs       831            1F9D5A      7  False     734881840   \n",
       "656              MOs1       930            1F9D5A      8  False     734881840   \n",
       "962            MOs2/3      1110            1F9D5A      8  False     734881840   \n",
       "767              MOs5       944            1F9D5A      8  False     734881840   \n",
       "1021            MOs6a      1117            1F9D5A      8  False     734881840   \n",
       "1085            MOs6b      1125            1F9D5A      8  False     734881840   \n",
       "453                SS       339            188064      6  False     734881840   \n",
       "12993             SS1       NaN            188064      7  False     734881840   \n",
       "12994           SS2/3       NaN            188064      7  False     734881840   \n",
       "...               ...       ...               ...    ...    ...           ...   \n",
       "116              chfl       721            AAAAAA      3  False     734881840   \n",
       "124               IVF       722            AAAAAA      2  False     734881840   \n",
       "129                V3       723            AAAAAA      2  False     734881840   \n",
       "140                AQ       724            AAAAAA      2  False     734881840   \n",
       "145                V4       725            AAAAAA      2  False     734881840   \n",
       "153               V4r       726            AAAAAA      3  False     734881840   \n",
       "164                 c       727            AAAAAA      2  False     734881840   \n",
       "1024              grv       693            AAAAAA      1  False     734881840   \n",
       "1032       grv of CTX       694            AAAAAA      2  False     734881840   \n",
       "1055               eg       697            AAAAAA      3  False     734881840   \n",
       "1063               hf       698            AAAAAA      3  False     734881840   \n",
       "1071               rf       699            AAAAAA      3  False     734881840   \n",
       "1078               ri       700            AAAAAA      3  False     734881840   \n",
       "1040       grv of CBX       695            AAAAAA      2  False     734881840   \n",
       "1087              pce       701            AAAAAA      3  False     734881840   \n",
       "1095              pcf       702            AAAAAA      3  False     734881840   \n",
       "1103              pri       703            AAAAAA      3  False     734881840   \n",
       "1112              psf       704            AAAAAA      3  False     734881840   \n",
       "1119              ppf       705            AAAAAA      3  False     734881840   \n",
       "3                 sec       707            AAAAAA      3  False     734881840   \n",
       "11                plf       708            AAAAAA      3  False     734881840   \n",
       "18                 nf       709            AAAAAA      3  False     734881840   \n",
       "25                sif       710            AAAAAA      3  False     734881840   \n",
       "34                icf       711            AAAAAA      3  False     734881840   \n",
       "43                apf       712            AAAAAA      3  False     734881840   \n",
       "49                ipf       713            AAAAAA      3  False     734881840   \n",
       "57                pms       714            AAAAAA      3  False     734881840   \n",
       "65                pfs       715            AAAAAA      3  False     734881840   \n",
       "624               IPF       926            AAAAAA      2  False     734881840   \n",
       "304325711      retina       NaN            7F2E7E      1  False     734881840   \n",
       "\n",
       "           graph_id  graph_order  hemisphere_id         id   ...    \\\n",
       "id                                                           ...     \n",
       "997               1            0              3        997   ...     \n",
       "8                 1            1              3          8   ...     \n",
       "567               1            2              3        567   ...     \n",
       "688               1            3              3        688   ...     \n",
       "695               1            4              3        695   ...     \n",
       "315               1            5              3        315   ...     \n",
       "184               1            6              3        184   ...     \n",
       "68                1            7              3         68   ...     \n",
       "667               1            8              3        667   ...     \n",
       "500               1            9              3        500   ...     \n",
       "107               1           10              3        107   ...     \n",
       "219               1           11              3        219   ...     \n",
       "299               1           12              3        299   ...     \n",
       "644               1           13              3        644   ...     \n",
       "947               1           14              3        947   ...     \n",
       "985               1           15              3        985   ...     \n",
       "320               1           16              3        320   ...     \n",
       "943               1           17              3        943   ...     \n",
       "648               1           18              3        648   ...     \n",
       "844               1           19              3        844   ...     \n",
       "882               1           20              3        882   ...     \n",
       "993               1           21              3        993   ...     \n",
       "656               1           22              3        656   ...     \n",
       "962               1           23              3        962   ...     \n",
       "767               1           24              3        767   ...     \n",
       "1021              1           25              3       1021   ...     \n",
       "1085              1           26              3       1085   ...     \n",
       "453               1           27              3        453   ...     \n",
       "12993             1           28              3      12993   ...     \n",
       "12994             1           29              3      12994   ...     \n",
       "...             ...          ...            ...        ...   ...     \n",
       "116               1         1204              3        116   ...     \n",
       "124               1         1205              3        124   ...     \n",
       "129               1         1206              3        129   ...     \n",
       "140               1         1207              3        140   ...     \n",
       "145               1         1208              3        145   ...     \n",
       "153               1         1209              3        153   ...     \n",
       "164               1         1210              3        164   ...     \n",
       "1024              1         1211              3       1024   ...     \n",
       "1032              1         1212              3       1032   ...     \n",
       "1055              1         1213              3       1055   ...     \n",
       "1063              1         1214              3       1063   ...     \n",
       "1071              1         1215              3       1071   ...     \n",
       "1078              1         1216              3       1078   ...     \n",
       "1040              1         1217              3       1040   ...     \n",
       "1087              1         1218              3       1087   ...     \n",
       "1095              1         1219              3       1095   ...     \n",
       "1103              1         1220              3       1103   ...     \n",
       "1112              1         1221              3       1112   ...     \n",
       "1119              1         1222              3       1119   ...     \n",
       "3                 1         1223              3          3   ...     \n",
       "11                1         1224              3         11   ...     \n",
       "18                1         1225              3         18   ...     \n",
       "25                1         1226              3         25   ...     \n",
       "34                1         1227              3         34   ...     \n",
       "43                1         1228              3         43   ...     \n",
       "49                1         1229              3         49   ...     \n",
       "57                1         1230              3         57   ...     \n",
       "65                1         1231              3         65   ...     \n",
       "624               1         1232              3        624   ...     \n",
       "304325711         1         1233              3  304325711   ...     \n",
       "\n",
       "          neuro_name_structure_id  neuro_name_structure_id_path  ontology_id  \\\n",
       "id                                                                             \n",
       "997                           NaN                           NaN            1   \n",
       "8                             NaN                           NaN            1   \n",
       "567                           NaN                           NaN            1   \n",
       "688                           NaN                           NaN            1   \n",
       "695                           NaN                           NaN            1   \n",
       "315                           NaN                           NaN            1   \n",
       "184                           NaN                           NaN            1   \n",
       "68                            NaN                           NaN            1   \n",
       "667                           NaN                           NaN            1   \n",
       "500                           NaN                           NaN            1   \n",
       "107                           NaN                           NaN            1   \n",
       "219                           NaN                           NaN            1   \n",
       "299                           NaN                           NaN            1   \n",
       "644                           NaN                           NaN            1   \n",
       "947                           NaN                           NaN            1   \n",
       "985                           NaN                           NaN            1   \n",
       "320                           NaN                           NaN            1   \n",
       "943                           NaN                           NaN            1   \n",
       "648                           NaN                           NaN            1   \n",
       "844                           NaN                           NaN            1   \n",
       "882                           NaN                           NaN            1   \n",
       "993                           NaN                           NaN            1   \n",
       "656                           NaN                           NaN            1   \n",
       "962                           NaN                           NaN            1   \n",
       "767                           NaN                           NaN            1   \n",
       "1021                          NaN                           NaN            1   \n",
       "1085                          NaN                           NaN            1   \n",
       "453                           NaN                           NaN            1   \n",
       "12993                         NaN                           NaN            1   \n",
       "12994                         NaN                           NaN            1   \n",
       "...                           ...                           ...          ...   \n",
       "116                           NaN                           NaN            1   \n",
       "124                           NaN                           NaN            1   \n",
       "129                           NaN                           NaN            1   \n",
       "140                           NaN                           NaN            1   \n",
       "145                           NaN                           NaN            1   \n",
       "153                           NaN                           NaN            1   \n",
       "164                           NaN                           NaN            1   \n",
       "1024                          NaN                           NaN            1   \n",
       "1032                          NaN                           NaN            1   \n",
       "1055                          NaN                           NaN            1   \n",
       "1063                          NaN                           NaN            1   \n",
       "1071                          NaN                           NaN            1   \n",
       "1078                          NaN                           NaN            1   \n",
       "1040                          NaN                           NaN            1   \n",
       "1087                          NaN                           NaN            1   \n",
       "1095                          NaN                           NaN            1   \n",
       "1103                          NaN                           NaN            1   \n",
       "1112                          NaN                           NaN            1   \n",
       "1119                          NaN                           NaN            1   \n",
       "3                             NaN                           NaN            1   \n",
       "11                            NaN                           NaN            1   \n",
       "18                            NaN                           NaN            1   \n",
       "25                            NaN                           NaN            1   \n",
       "34                            NaN                           NaN            1   \n",
       "43                            NaN                           NaN            1   \n",
       "49                            NaN                           NaN            1   \n",
       "57                            NaN                           NaN            1   \n",
       "65                            NaN                           NaN            1   \n",
       "624                           NaN                           NaN            1   \n",
       "304325711                     NaN                           NaN            1   \n",
       "\n",
       "           parent_structure_id                          safe_name sphinx_id  \\\n",
       "id                                                                            \n",
       "997                        NaN                               root         1   \n",
       "8                          997      Basic cell groups and regions         2   \n",
       "567                          8                           Cerebrum         3   \n",
       "688                        567                    Cerebral cortex         4   \n",
       "695                        688                     Cortical plate         5   \n",
       "315                        695                          Isocortex         6   \n",
       "184                        315       Frontal pole cerebral cortex         7   \n",
       "68                         184               Frontal pole layer 1         8   \n",
       "667                        184             Frontal pole layer 2/3         9   \n",
       "500                        315                  Somatomotor areas        10   \n",
       "107                        500          Somatomotor areas Layer 1        11   \n",
       "219                        500        Somatomotor areas Layer 2/3        12   \n",
       "299                        500          Somatomotor areas Layer 5        13   \n",
       "644                        500         Somatomotor areas Layer 6a        14   \n",
       "947                        500         Somatomotor areas Layer 6b        15   \n",
       "985                        500                 Primary motor area        16   \n",
       "320                        985         Primary motor area Layer 1        17   \n",
       "943                        985       Primary motor area Layer 2/3        18   \n",
       "648                        985         Primary motor area Layer 5        19   \n",
       "844                        985        Primary motor area Layer 6a        20   \n",
       "882                        985        Primary motor area Layer 6b        21   \n",
       "993                        500               Secondary motor area        22   \n",
       "656                        993       Secondary motor area layer 1        23   \n",
       "962                        993     Secondary motor area layer 2/3        24   \n",
       "767                        993       Secondary motor area layer 5        25   \n",
       "1021                       993      Secondary motor area layer 6a        26   \n",
       "1085                       993      Secondary motor area layer 6b        27   \n",
       "453                        315                Somatosensory areas        28   \n",
       "12993                      453        Somatosensory areas layer 1        29   \n",
       "12994                      453      Somatosensory areas layer 2/3        30   \n",
       "...                        ...                                ...       ...   \n",
       "116                         81                    choroid fissure      1205   \n",
       "124                         73           interventricular foramen      1206   \n",
       "129                         73                    third ventricle      1207   \n",
       "140                         73                  cerebral aqueduct      1208   \n",
       "145                         73                   fourth ventricle      1209   \n",
       "153                        145                     lateral recess      1210   \n",
       "164                         73  central canal spinal cord/medulla      1211   \n",
       "1024                       997                            grooves      1212   \n",
       "1032                      1024     grooves of the cerebral cortex      1213   \n",
       "1055                      1032                  endorhinal groove      1214   \n",
       "1063                      1032                hippocampal fissure      1215   \n",
       "1071                      1032                     rhinal fissure      1216   \n",
       "1078                      1032                    rhinal incisure      1217   \n",
       "1040                      1024   grooves of the cerebellar cortex      1218   \n",
       "1087                      1040                 precentral fissure      1219   \n",
       "1095                      1040               preculminate fissure      1220   \n",
       "1103                      1040                    primary fissure      1221   \n",
       "1112                      1040         posterior superior fissure      1222   \n",
       "1119                      1040               prepyramidal fissure      1223   \n",
       "3                         1040                  secondary fissure      1224   \n",
       "11                        1040             posterolateral fissure      1225   \n",
       "18                        1040                    nodular fissure      1226   \n",
       "25                        1040                     simple fissure      1227   \n",
       "34                        1040                intercrural fissure      1228   \n",
       "43                        1040             ansoparamedian fissure      1229   \n",
       "49                        1040         intraparafloccular fissure      1230   \n",
       "57                        1040                  paramedian sulcus      1231   \n",
       "65                        1040               parafloccular sulcus      1232   \n",
       "624                       1024              Interpeduncular fossa      1233   \n",
       "304325711                  997                             retina      1234   \n",
       "\n",
       "           st_level                     structure_id_path  \\\n",
       "id                                                          \n",
       "997             NaN                                 /997/   \n",
       "8               NaN                               /997/8/   \n",
       "567             NaN                           /997/8/567/   \n",
       "688             NaN                       /997/8/567/688/   \n",
       "695             NaN                   /997/8/567/688/695/   \n",
       "315             NaN               /997/8/567/688/695/315/   \n",
       "184             NaN           /997/8/567/688/695/315/184/   \n",
       "68              NaN        /997/8/567/688/695/315/184/68/   \n",
       "667             NaN       /997/8/567/688/695/315/184/667/   \n",
       "500             NaN           /997/8/567/688/695/315/500/   \n",
       "107             NaN       /997/8/567/688/695/315/500/107/   \n",
       "219             NaN       /997/8/567/688/695/315/500/219/   \n",
       "299             NaN       /997/8/567/688/695/315/500/299/   \n",
       "644             NaN       /997/8/567/688/695/315/500/644/   \n",
       "947             NaN       /997/8/567/688/695/315/500/947/   \n",
       "985             NaN       /997/8/567/688/695/315/500/985/   \n",
       "320             NaN   /997/8/567/688/695/315/500/985/320/   \n",
       "943             NaN   /997/8/567/688/695/315/500/985/943/   \n",
       "648             NaN   /997/8/567/688/695/315/500/985/648/   \n",
       "844             NaN   /997/8/567/688/695/315/500/985/844/   \n",
       "882             NaN   /997/8/567/688/695/315/500/985/882/   \n",
       "993             NaN       /997/8/567/688/695/315/500/993/   \n",
       "656             NaN   /997/8/567/688/695/315/500/993/656/   \n",
       "962             NaN   /997/8/567/688/695/315/500/993/962/   \n",
       "767             NaN   /997/8/567/688/695/315/500/993/767/   \n",
       "1021            NaN  /997/8/567/688/695/315/500/993/1021/   \n",
       "1085            NaN  /997/8/567/688/695/315/500/993/1085/   \n",
       "453             NaN           /997/8/567/688/695/315/453/   \n",
       "12993           NaN     /997/8/567/688/695/315/453/12993/   \n",
       "12994           NaN     /997/8/567/688/695/315/453/12994/   \n",
       "...             ...                                   ...   \n",
       "116             NaN                       /997/73/81/116/   \n",
       "124             NaN                          /997/73/124/   \n",
       "129             NaN                          /997/73/129/   \n",
       "140             NaN                          /997/73/140/   \n",
       "145             NaN                          /997/73/145/   \n",
       "153             NaN                      /997/73/145/153/   \n",
       "164             NaN                          /997/73/164/   \n",
       "1024            NaN                            /997/1024/   \n",
       "1032            NaN                       /997/1024/1032/   \n",
       "1055            NaN                  /997/1024/1032/1055/   \n",
       "1063            NaN                  /997/1024/1032/1063/   \n",
       "1071            NaN                  /997/1024/1032/1071/   \n",
       "1078            NaN                  /997/1024/1032/1078/   \n",
       "1040            NaN                       /997/1024/1040/   \n",
       "1087            NaN                  /997/1024/1040/1087/   \n",
       "1095            NaN                  /997/1024/1040/1095/   \n",
       "1103            NaN                  /997/1024/1040/1103/   \n",
       "1112            NaN                  /997/1024/1040/1112/   \n",
       "1119            NaN                  /997/1024/1040/1119/   \n",
       "3               NaN                     /997/1024/1040/3/   \n",
       "11              NaN                    /997/1024/1040/11/   \n",
       "18              NaN                    /997/1024/1040/18/   \n",
       "25              NaN                    /997/1024/1040/25/   \n",
       "34              NaN                    /997/1024/1040/34/   \n",
       "43              NaN                    /997/1024/1040/43/   \n",
       "49              NaN                    /997/1024/1040/49/   \n",
       "57              NaN                    /997/1024/1040/57/   \n",
       "65              NaN                    /997/1024/1040/65/   \n",
       "624             NaN                        /997/1024/624/   \n",
       "304325711       NaN                       /997/304325711/   \n",
       "\n",
       "          structure_name_facet  weight  \n",
       "id                                      \n",
       "997                  385153371    8690  \n",
       "8                   2244697386    8690  \n",
       "567                 2878815794    8690  \n",
       "688                 3591311804    8690  \n",
       "695                 3945900931    8690  \n",
       "315                 2323732626    8690  \n",
       "184                 2565719060    8690  \n",
       "68                  1397862467    8690  \n",
       "667                 4268100038    8690  \n",
       "500                  356591023    8690  \n",
       "107                  900612548    8690  \n",
       "219                 1075749695    8690  \n",
       "299                  851674589    8690  \n",
       "644                 1003126892    8690  \n",
       "947                 2730742230    8690  \n",
       "985                 1852742012    8690  \n",
       "320                  571569106    8690  \n",
       "943                 2488357079    8690  \n",
       "648                  628930507    8690  \n",
       "844                 3473508879    8690  \n",
       "882                 1442896821    8690  \n",
       "993                 1043755260    8690  \n",
       "656                 4032915713    8690  \n",
       "962                 3274108161    8690  \n",
       "767                 4144803096    8690  \n",
       "1021                3489757563    8690  \n",
       "1085                1225271489    8690  \n",
       "453                 3016301862    8690  \n",
       "12993                544207135    8690  \n",
       "12994               3920828838    8690  \n",
       "...                        ...     ...  \n",
       "116                 3192898784    8690  \n",
       "124                 1644273448    8690  \n",
       "129                  562407244    8690  \n",
       "140                 3509002335    8690  \n",
       "145                 2366263365    8690  \n",
       "153                 4006455201    8690  \n",
       "164                 3758121442    8690  \n",
       "1024                1816833424    8690  \n",
       "1032                4010583074    8690  \n",
       "1055                2757546022    8690  \n",
       "1063                1845828307    8690  \n",
       "1071                 915997995    8690  \n",
       "1078                1408661066    8690  \n",
       "1040                 306524468    8690  \n",
       "1087                2084828473    8690  \n",
       "1095                3439430666    8690  \n",
       "1103                1359711822    8690  \n",
       "1112                 706594763    8690  \n",
       "1119                  90069120    8690  \n",
       "3                   1603026106    8690  \n",
       "11                  3968698314    8690  \n",
       "18                  3778172686    8690  \n",
       "25                  3504067713    8690  \n",
       "34                  1415991612    8690  \n",
       "43                  2452402730    8690  \n",
       "49                  2654107150    8690  \n",
       "57                  3972977495    8690  \n",
       "65                   771629690    8690  \n",
       "624                 1476705011    8690  \n",
       "304325711           3295290839    8690  \n",
       "\n",
       "[1234 rows x 21 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ontology.df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PARENTS: 278\n",
      "LEAFS: 956  of  1234 MIN: 1 MAX: 312782652\n"
     ]
    }
   ],
   "source": [
    "tree_levels = [[] for i in range(0, 12)]\n",
    "childs_map = dict()\n",
    "\n",
    "for i in range(0, 12):\n",
    "    level_ids = []\n",
    "    for a in ontology.df.values:\n",
    "        if (i == 0 and math.isnan(a[14])) or (i > 0 and a[14] in tree_levels[i - 1]):\n",
    "            level_ids.append(a[9])\n",
    "            childs_map[a[9]] = []\n",
    "    tree_levels[i] = level_ids\n",
    "    \n",
    "for i in range(11, 0, -1):\n",
    "    for a in ontology.df.values:\n",
    "        if a[14] in tree_levels[i - 1]:\n",
    "            childs_map[a[14]].append(a[9])\n",
    "            childs_map[a[14]].extend(childs_map[a[9]])\n",
    "\n",
    "parents = set([a[14] for a in ontology.df.values if not math.isnan(a[14])])\n",
    "print \"PARENTS:\", len(parents)\n",
    "leafs = [(a[0], a[9]) for a in ontology.df.values if a[9] not in parents]\n",
    "leaf_ids = [l[1] for l in leafs]\n",
    "print \"LEAFS:\", len(leafs), \" of \", len(ontology.df.values), \"MIN:\", min(leaf_ids), \"MAX:\", max(leaf_ids)\n",
    "\n",
    "def find_matching_tree_level(node_id):\n",
    "    for i, arr_ids in enumerate(tree_levels):\n",
    "        if node_id in arr_ids:\n",
    "            return i+1\n",
    "    return -1\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x105de1c90>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Hbre7ZFkAeX5dNeWT61W2TvHzVbk6kiWtXD6Urp0bpmqOn6r+ZDHN183jL74v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Xt3wf1Ip9Mm82m1hou1FBpjadgsJVNTU3AcBy0tLeZ9Vs07ZXJycsl17ljTdynr0+zsbFFs4xve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\ntbe3FzCoM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iGcf/75VR/X0NCwCq0pLx6PB/l83tWwIA1eJ7twzRsZGUF/f/+Jbk5JSafT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\n7X45ToOMI9kv/F6p+OD3amHEt7EN+ex7Yd++fZ6h0jXwYFmRSOSmWSvih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jBv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\nfq3JIR9P0xjo+mzbtsp9x4ULHWHSaYi4sM79EU2ETpJ5mj9O8nT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psCpsQqGQFR9VyTb5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\nQRBaCBFpgiAIgiAIgiAILcT/A6/OrGX5II1eAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x109e3a5d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "template, template_info = mcc.get_template_volume()\n",
    "annot, annot_info = mcc.get_annotation_volume()\n",
    "\n",
    "# show that slice of all volumes side-by-side\n",
    "f, ((ax1, ax2)) = pyplot.subplots(1, 2, figsize=(15, 6))\n",
    "# pick a slice to show\n",
    "slice_idx = 264\n",
    "\n",
    "ax1.imshow(template[slice_idx,:,:], cmap='gray', aspect='equal', vmin=template.min(), vmax=template.max())\n",
    "ax1.set_title(\"registration template\")\n",
    "\n",
    "ax2.imshow(annot[slice_idx,:,:], cmap='gray', aspect='equal', vmin=0, vmax=2000)\n",
    "ax2.set_title(\"annotation volume\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 516 0 312782652\n"
     ]
    }
   ],
   "source": [
    "print template.min(), template.max(), annot.min(), annot.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{u'dimension': 3,\n",
       " u'encoding': 'gzip',\n",
       " u'endian': 'little',\n",
       " u'keyvaluepairs': {},\n",
       " u'kinds': ['domain', 'domain', 'domain'],\n",
       " u'sizes': [528, 320, 456],\n",
       " u'space': 'left-posterior-superior',\n",
       " u'space directions': [['25', '0', '0'], ['0', '25', '0'], ['0', '0', '25']],\n",
       " u'space origin': ['0', '0', '0'],\n",
       " u'type': 'unsigned int'}"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "annot_info"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "517 distinct annotations 589\n"
     ]
    }
   ],
   "source": [
    "found_ann = numpy.unique(annot)\n",
    "print len(numpy.unique(template)), \"distinct annotations\", len(found_ann)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Background Value(s) [0]\n"
     ]
    }
   ],
   "source": [
    "all_region_idx = [a[9] for a in ontology.df.values]\n",
    "background_idx = [ann for ann in found_ann if ann not in all_region_idx]\n",
    "print \"Background Value(s)\", background_idx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "conn2voxels = {a[9]: (find_matching_tree_level(a[9]), a[0], (annot == a[9]).sum())\n",
    "               for a in ontology.df.values}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "================================\n",
      "LEVEL 1\n",
      "Regions with no associated voxels: 0 set([])\n",
      "\n",
      "Regions with at least one voxel associated: 1\n",
      "[(997, 'root', 40)]\n",
      "================================\n",
      "LEVEL 2\n",
      "Regions with no associated voxels: 3 set(['grv', 'retina', 'grey'])\n",
      "\n",
      "Regions with at least one voxel associated: 2\n",
      "[(73, 'VS', 18385), (1009, 'fiber tracts', 236648)]\n",
      "================================\n",
      "LEVEL 3\n",
      "Regions with no associated voxels: 11 set(['IVF', 'CH', 'cbf', 'cm', 'eps', 'mfbs', 'BS', 'IPF', 'grv of CBX', 'lfbs', 'grv of CTX'])\n",
      "\n",
      "Regions with at least one voxel associated: 6\n",
      "[(81, 'VL', 159548), (129, 'V3', 82850), (140, 'AQ', 28584), (512, 'CB', 1), (145, 'V4', 50656), (164, 'c', 80)]\n",
      "================================\n",
      "LEVEL 4\n",
      "Regions with no associated voxels: 50 set(['vsp', 'cbc', 'ipf', 'ppf', 'pms', 'eg', 'CTX', 'SEZ', 'cbp', 'sec', 'epsc', 'IIIn', 'HB', 'Vn', 'apf', 'mfbc', 'vrt', 'icf', 'nf', 'tn', 'chpl', 'rf', 'XIIn', 'sif', 'RC', 'pcf', 'ri', 'pce', 'CNU', 'chfl', 'sst', 'pri', 'mfsbshy', 'VIn', 'plf', 'pfs', 'rst', 'Xn', 'IB', 'hf', 'psf', 'IXn', 'CBN', 'drt', 'XIn', 'lfbst', 'ctb', 'In', 'VIIIn', 'CBX'])\n",
      "\n",
      "Regions with at least one voxel associated: 11\n",
      "[(728, 'arb', 451669), (313, 'MB', 353356), (776, 'cc', 652685), (784, 'cst', 4959), (798, 'VIIn', 6612), (848, 'IIn', 3786), (877, 'tsp', 10009), (949, 'von', 17), (863, 'rust', 22757), (153, 'V4r', 53228), (911, 'IVn', 451)]\n",
      "================================\n",
      "LEVEL 5\n",
      "Regions with no associated voxels: 71 set(['cett', 'fp', 'mfb', 'MBsta', 'ee', 'ptf', 'MBmot', 'ttp', 'pmx', 'iVIIn', 'CBXmo', 'tspc', 'sop', 'CBXgr', 'tp', 'cbt', 'tspd', 'rrt', 'nst', 'poc', 'apd', 'pap', 'CBXpu', 'scrt', 'cte', 'pvbh', 'mfbse', 'csc', 'sup', 'rstm', 'rstl', 'cstu', 'lotg', 'tct', 'IVd', 'fxs', 'cstc', 'cVIIIn', 'ntt', 'lab', 'sV', 'mfbsma', 'MBsen', 'step', 'aot', 'snp', 'HEM', 'php', 'pyd', 'vlt', 'bsc', 'shp', 'mfbst', 'stf', 'crt', 'fa', 'cvb', 'sttv', 'VERM', 'ccs', 'ccr', 'gVIIn', 'sttl', 'srp', 'stp', 'CTXpl', 'mfbsm', 'mtc', 'ccg', 'cpt', 'svp'])\n",
      "\n",
      "Regions with at least one voxel associated: 34\n",
      "[(6, 'int', 155764), (62, 'mlf', 67923), (78, 'mcp', 59418), (91, 'IP', 55207), (93, 'moV', 3952), (117, 'och', 18309), (125, 'opt', 43331), (158, 'pc', 3399), (14, 'im', 106), (190, 'py', 34577), (237, 'ts', 652), (301, 'st', 45648), (326, 'scp', 28914), (341, 'smd', 1000), (354, 'MY', 575501), (397, 'vtd', 4164), (413, 'vVIIIn', 15391), (477, 'STR', 175862), (549, 'TH', 295591), (703, 'CTXsp', 105638), (771, 'P', 384669), (803, 'PAL', 111434), (846, 'DN', 21468), (884, 'amc', 4933), (900, 'aco', 56240), (908, 'act', 13189), (924, 'cpd', 55637), (940, 'cing', 66890), (989, 'FN', 32651), (1016, 'onl', 251153), (1060, 'dtd', 2632), (1092, 'em', 8312), (1097, 'HY', 232031), (1123, 'icp', 47841)]\n",
      "================================\n",
      "LEVEL 6\n",
      "Regions with no associated voxels: 64 set(['SCm', 'vc', 'jrb', 'hht', 'fxprg', 'DORpm', 'dl', 'ec', 'ab', 'per', 'P-sat', 'DT', 'PALv', 'SCs', 'PVR', 'dlf', 'aolt', 'sctv', 'PVZ', 'dtt', 'sctd', 'EP', 'P-sen', 'PRT', 'fpr', 'PIS', 'LZ', 'LSX', 'lotd', 'pvbt', 'phpl', '6b', 'dcm', 'fxpo', 'SNl', 'STRv', 'dscp', 'dc', 'DORsm', 'das', 'hc', 'BLA', 'PALc', 'STRd', 'ME', 'phpm', 'uf', 'phpd', 'cct', 'supv', 'PALd', 'MT', 'P-mot', 'PALm', 'ias', 'MY-mot', 'bct', 'supa', 'phpv', 'MY-sat', 'supd', 'MY-sen', 'RAmb', 'MEZ'])\n",
      "\n",
      "Regions with at least one voxel associated: 60\n",
      "[(4, 'IC', 357773), (35, 'III', 2303), (66, 'LT', 382), (115, 'IV', 466), (128, 'MRN', 311620), (131, 'LA', 41076), (214, 'RN', 41425), (231, 'AT', 998), (246, 'RR', 27478), (271, 'SAG', 5980), (278, 'sAMY', 15406), (315, 'Isocortex', 6), (319, 'BMA', 69327), (374, 'SNc', 13715), (381, 'SNr', 107010), (530, 'df', 4736), (580, 'NB', 8983), (583, 'CLA', 31625), (603, 'fi', 90210), (616, 'CUN', 18893), (633, 'cic', 1282), (658, 'll', 60621), (673, 'mp', 1377), (681, 'mtg', 5319), (690, 'mtt', 10515), (697, 'ml', 34820), (698, 'OLF', 275171), (460, 'MEV', 2226), (749, 'VTA', 51455), (753, 'pm', 59), (757, 'VTN', 2406), (780, 'PA', 20241), (794, 'sptV', 101999), (795, 'PAG', 283394), (802, 'sm', 17327), (841, 'tb', 17735), (874, 'PBG', 5430), (912, 'LING', 7942), (920, 'CENT', 250358), (928, 'CUL', 448510), (936, 'DEC', 239591), (944, 'FOTU', 58946), (951, 'PYR', 58832), (957, 'UVU', 140142), (968, 'NOD', 80661), (975, 'EW', 2053), (1007, 'SIM', 351345), (1017, 'AN', 733048), (1025, 'PRM', 315291), (1033, 'COPY', 155348), (1049, 'FL', 84339), (1052, 'PPN', 29476), (1089, 'HPF', 171733), (1041, 'PFL', 356892), (705, 'mtV', 840), (595, 'fr', 10990), (482, 'bic', 21795), (611, 'hbc', 3617), (466, 'alv', 36066), (665, 'lot', 81071)]\n",
      "================================\n",
      "LEVEL 7\n",
      "Regions with no associated voxels: 108 set(['SIMmo', 'PRNv', 'FLpu', 'EPI', 'sct', 'UVUpu', 'LINGpu', 'DCN', 'PYRgr', 'VNC', 'AOB', 'NODgr', 'PERI', 'LINGgr', 'CUL4', 'CUL5', 'MDRN', 'oct', 'SPF', 'GU', 'DECmo', 'db', 'NODpu', 'COPYgr', 'PFLpu', 'AHA', 'RHP', 'VIS', 'PHY', 'LAT', 'VENT', 'PRMgr', 'CUL4, 5', 'ACVI', 'PYRmo', 'AMB', 'NODmo', 'PGRN', 'PFLgr', 'AI', 'COPYpu', 'DECgr', 'PL', 'FOTUmo', 'CENT3', 'CENT2', 'SCzo', 'EV', 'INV', 'PRMmo', 'ECO', 'SSN', 'FLgr', 'ACA', 'SIMpu', 'ILA', 'ATN', 'TEa', 'ILM', 'ANcr2', 'ANcr1', 'COA', 'UVUmo', 'PMR', 'NLOT', 'rct', 'iaf', 'AUD', 'MRNp', 'FRP', 'DECpu', 'MRNm', 'mct', 'LTN', 'PFLmo', 'MED', 'VISC', 'SS', 'FOTUgr', 'UVUgr', 'PSCH', 'BMAp', 'z', 'ORB', 'MO', 'LINGmo', 'BMAa', 'FLmo', 'PYRpu', 'PTLp', 'MSC', 'CN', 'HIP', 'SOC', 'MBO', 'SIMgr', 'LS', 'GENv', 'PRMpu', 'MTN', 'GENd', 'FOTUpu', 'ICc', 'ICe', 'ICd', 'MRNmg', 'COPYmo', 'RSP'])\n",
      "\n",
      "Regions with at least one voxel associated: 143\n",
      "[(7, 'PSV', 70385), (10, 'SCig', 133547), (12, 'IF', 2156), (17, 'SCiw', 134245), (23, 'AAA', 37040), (26, 'SCdg', 78038), (30, 'PVa', 816), (38, 'PVH', 15889), (42, 'SCdw', 21888), (50, 'PRC', 5291), (56, 'ACB', 263008), (63, 'PVHd', 3051), (67, 'INC', 3513), (72, 'ADP', 2188), (83, 'IO', 33071), (88, 'AHN', 49955), (100, 'IPN', 22723), (106, 'ISN', 456), (118, 'PVi', 6785), (126, 'PVp', 8772), (133, 'PVpo', 5380), (136, 'IRN', 153949), (146, 'PRNr', 164040), (159, 'AON', 240263), (162, 'LDT', 7472), (173, 'RCH', 16634), (194, 'LHA', 218492), (197, 'RL', 710), (203, 'LIN', 1644), (206, 'RM', 8135), (207, 'AP', 2893), (215, 'APN', 73669), (689, 'VLPO', 1968), (222, 'RO', 969), (223, 'ARH', 15693), (226, 'LPO', 65423), (230, 'RPA', 2242), (235, 'LRN', 31634), (238, 'RPO', 2777), (262, 'RT', 87419), (263, 'AVP', 4181), (272, 'AVPV', 4375), (280, 'B', 2272), (286, 'SCH', 6273), (287, 'BAC', 478), (292, 'BA', 4769), (298, 'MA', 21620), (303, 'BLAa', 46578), (307, 'MARN', 41122), (310, 'SF', 16876), (311, 'BLAp', 40334), (318, 'SG', 1128), (332, 'ASO', 100), (333, 'SH', 2365), (338, 'SFO', 1485), (342, 'SI', 178368), (347, 'SBPV', 9556), (350, 'SLC', 1954), (351, 'BST', 95464), (356, 'PST', 912), (358, 'SLD', 4961), (364, 'PSTN', 3901), (372, 'ICB', 624), (380, 'cuf', 1592), (388, 'grf', 190), (390, 'SO', 3713), (403, 'MEA', 100225), (429, 'SPVC', 84534), (437, 'SPVI', 75635), (445, 'SPVO', 32813), (451, 'BLAv', 16609), (452, 'MEPO', 10218), (470, 'STN', 11971), (507, 'MOB', 1028777), (515, 'MPN', 13213), (523, 'MPO', 53336), (531, 'MPT', 7298), (534, 'SUT', 10567), (536, 'CEA', 78676), (566, 'TR', 66078), (574, 'TRN', 45575), (576, 'ACVII', 350), (581, 'TRS', 13836), (587, 'ND', 1935), (589, 'TT', 98588), (591, 'CLI', 5341), (604, 'NI', 8536), (609, 'SPA', 3375), (443, 'dhc', 60607), (612, 'NLL', 41788), (614, 'TU', 30356), (621, 'V', 24252), (628, 'NOT', 5492), (634, 'NPC', 15510), (642, 'NTB', 6415), (651, 'NTS', 31890), (653, 'VI', 1290), (661, 'VII', 51799), (672, 'CP', 1627409), (679, 'CS', 43388), (693, 'VMH', 29872), (706, 'OP', 5117), (754, 'OT', 242728), (763, 'OV', 755), (765, 'x', 3979), (773, 'XII', 22521), (781, 'y', 1672), (788, 'PAA', 45973), (797, 'ZI', 88068), (814, 'DP', 15028), (830, 'DMH', 31008), (839, 'DMX', 5665), (842, 'SCsg', 97230), (851, 'SCop', 41274), (852, 'PARN', 118338), (859, 'PAS', 860), (867, 'PB', 55843), (872, 'DR', 8056), (880, 'DTN', 5586), (895, 'ECT', 101), (898, 'PCG', 38868), (903, 'ECU', 5822), (914, 'PD', 188), (931, 'PG', 60851), (946, 'PH', 47189), (952, 'EPd', 116160), (961, 'PIR', 822843), (966, 'EPv', 29142), (980, 'PMd', 5281), (998, 'FS', 23171), (1004, 'PMv', 5630), (1022, 'GPe', 103116), (1031, 'GPi', 27122), (1044, 'PP', 2799), (1048, 'GRN', 121816), (1061, 'PPT', 4278), (1069, 'PPY', 2505), (1093, 'PRNc', 198025), (1105, 'IA', 12448), (1109, 'PS', 1720), (449, 'vhc', 7495), (147, 'LC', 1042), (436, 'fx', 17309)]\n",
      "================================\n",
      "LEVEL 8\n",
      "Regions with no associated voxels: 184 set(['DMHa', 'ACA2/3', 'ORB1', 'PVHlp', 'ORB5', 'LRNm', 'VMHdm', 'NTSm', 'NTSl', 'DMHp', 'VISpm', 'VISpl', 'PIR1-3', 'NLOT2', 'SPVOvl', 'NTSco', 'PVHmpv', 'BSTa', 'PIN', 'NTSce', 'MPNc', 'CUL4, 5gr', 'MOBopl', 'BSTp', 'ILA2', 'CUL4pu', 'DP6a', 'PVHm', 'ANcr2gr', 'ANcr2pu', 'PVHf', 'CUL4gr', 'CENT2pu', 'ORBv', 'ORBm', 'ORBl', 'SS2/3', 'PVHp', 'NLOT1-3', 'PAA1-3', 'ANcr1gr', 'CENT2gr', 'SPVOmdmv', 'DMHv', 'CUL4, 5mo', 'NIS', 'VIS2/3', 'PAA2', 'PAA3', 'PAA1', 'PTLp1', 'ORB6a', 'ORB6b', 'SS5', 'SS4', 'MO1', 'VISal', 'VISam', 'MO5', 'PTLp2/3', 'VIS4', 'AONl', 'AONm', 'MOs', 'AONd', 'AONe', 'DP2/3', 'ORBvl', 'TR1', 'TR3', 'TR2', 'CUL5gr', 'ACA1', 'AON2', 'AON1', 'SSp', 'SSs', 'SPVOmdmd', 'ENT', 'SPVOcdm', 'PTLp4', 'CNspg', 'RSPv', 'PIR3', 'PIR2', 'PIR1', 'OT1-3', 'CSm', 'CSl', 'SPVOrdm', 'MO2/3', 'isl', 'PBm', 'PBl', 'CUL5pu', 'PTLp5', 'PVHdp', 'PL2', 'ANcr1pu', 'VMHc', 'VMHa', 'PPYd', 'PPYs', 'CUL4mo', 'AUDv', 'ACAd', 'AUDp', 'CUL5mo', 'NC', 'MOBgr', 'AUDd', 'RSPd', 'ACAv', 'MOBgl', 'CENT2mo', 'NTSge', 'CENT3gr', 'CNlam', 'CENT3pu', 'MOBipl', 'CEAm', 'CEAl', 'CEAc', 'SS1', 'CA', 'MO6b', 'VMHvl', 'TTv', 'VISpor', 'AONpv', 'KF', 'AHNa', 'AHNc', 'AHNd', 'ACA5', 'PTLp6a', 'PTLp6b', 'AHNp', 'VISa', 'VISrl', 'DG', 'AUDpo', 'OT1', 'OT2', 'OT3', 'VISp', 'MOBmi', 'A13', 'AIv', 'AIp', 'MEApd', 'LRNp', 'TM', 'islm', 'CENT3mo', 'TTd', 'MEApv', 'VISl', 'VISli', 'VIS6a', 'VIS6b', 'NLLv', 'ANcr1mo', 'TR1-3', 'MEAav', 'VP', 'NLLh', 'NLLd', 'MO6a', 'MEAad', 'DP5', 'VIS1', 'DP2', 'DP1', 'VIS5', 'MPNm', 'MPNl', 'ORB2/3', 'ANcr2mo', 'ACA6b', 'CUL4, 5pu', 'ACA6a', 'SS6a', 'SS6b'])\n",
      "\n",
      "Regions with at least one voxel associated: 120\n",
      "[(15, 'PT', 17129), (19, 'IG', 1772), (27, 'IGL', 4556), (36, 'GU1', 28255), (59, 'IMD', 9498), (64, 'AD', 10074), (68, 'FRP1', 41158), (84, 'PL6a', 16388), (96, 'DCO', 37734), (97, 'TEa1', 28872), (101, 'VCO', 48367), (104, 'AId', 8), (105, 'SOCm', 9435), (114, 'SOCl', 12408), (122, 'POR', 8213), (127, 'AM', 21509), (132, 'PL6b', 1333), (143, 'AMBv', 1406), (148, 'GU4', 12954), (149, 'PVT', 25631), (155, 'LD', 68148), (169, 'PRP', 10012), (170, 'LGd', 46211), (171, 'PL1', 30765), (177, 'NR', 1389), (178, 'LGv', 25851), (180, 'GU2/3', 43435), (181, 'RE', 24576), (186, 'LH', 20631), (187, 'GU5', 52850), (188, 'AOBgl', 9454), (189, 'RH', 4099), (196, 'AOBgr', 13589), (202, 'MV', 86910), (204, 'AOBmi', 17753), (209, 'LAV', 9057), (210, 'LM', 2062), (218, 'LP', 69350), (225, 'SPIV', 39468), (234, 'TEa4', 14555), (250, 'LSc', 34325), (255, 'AV', 26109), (258, 'LSr', 138535), (260, 'NLOT1', 10457), (266, 'LSv', 7287), (289, 'TEa5', 58112), (304, 'PL2/3', 34208), (321, 'SubG', 1726), (325, 'SGN', 2009), (335, 'PERI6a', 16967), (362, 'MD', 86351), (363, 'PL5', 28852), (366, 'SMT', 11317), (368, 'PERI6b', 5078), (414, 'SPFm', 5070), (422, 'SPFp', 16827), (427, 'ECT2/3', 40003), (475, 'MG', 30179), (483, 'MH', 19039), (491, 'MM', 36227), (494, 'SCig-a', 8243), (502, 'SUB', 289037), (503, 'SCig-b', 26045), (511, 'SCig-c', 4918), (525, 'SUM', 12409), (540, 'PERI1', 29487), (556, 'ILA2/3', 33218), (564, 'MS', 39040), (575, 'CL', 15427), (596, 'NDB', 67827), (599, 'CM', 10754), (638, 'GU6a', 47156), (639, 'COAa', 36755), (647, 'COAp', 124500), (662, 'GU6b', 4219), (667, 'FRP2/3', 7768), (685, 'VM', 47254), (692, 'PERI5', 41974), (707, 'ILA1', 17329), (711, 'CU', 19078), (729, 'TEa6a', 30318), (786, 'TEa6b', 8572), (804, 'FF', 3662), (827, 'ILA5', 29789), (836, 'ECT1', 25197), (843, 'PAR', 59900), (849, 'VISC6b', 2660), (857, 'VISC6a', 30680), (888, 'PERI2/3', 46144), (894, 'RSPagl', 3439), (897, 'VISC1', 18373), (907, 'PCN', 16836), (930, 'PF', 26914), (939, 'AMBd', 1210), (970, 'PGRNd', 9881), (977, 'ECT6a', 19220), (978, 'PGRNl', 42251), (982, 'FC', 4025), (985, 'MOp', 34027), (988, 'ECT5', 40220), (1010, 'VISC4', 12560), (1020, 'PO', 75867), (1029, 'POL', 6759), (1037, 'POST', 53374), (1039, 'GR', 4320), (1045, 'ECT6b', 6388), (1054, 'ILA6a', 22853), (1058, 'VISC5', 30944), (1077, 'PR', 1164), (1081, 'ILA6b', 6116), (1084, 'PRE', 67752), (1098, 'MDRNd', 22557), (1106, 'VISC2/3', 26981), (1107, 'MDRNv', 48209), (1113, 'IAD', 5646), (1120, 'IAM', 2981), (1127, 'TEa2/3', 42070), (1139, 'NLOT3', 14544), (217, 'SUV', 22710), (629, 'VAL', 46277)]\n",
      "================================\n",
      "LEVEL 9\n",
      "Regions with no associated voxels: 89 set(['DGlb', 'BSTam', 'BSTal', 'RSPv2', 'SSp-tr', 'BSTif', 'BSTd', 'POST3', 'POST2', 'POST1', 'BSTv', 'PBlc', 'DGmb', 'BSTfu', 'SSp-un', 'PVHmpd', 'SSp-ul', 'TTv2', 'DG-sgz', 'PAR3', 'PAR2', 'PAR1', 'BSTov', 'SSp2/3', 'AMd', 'AMv', 'MEApd-c', 'MEApd-b', 'MEApd-a', 'BSTpr', 'PBlv', 'MGd', 'COApl', 'COApm', 'Mmme', 'TTv1', 'SSp-ll', 'PVHam', 'ORBm2', 'MGm', 'MGv', 'PVHap', 'SUBv', 'TTd1', 'TTd2', 'TTd3', 'TTd4', 'PVHpv', 'SSp6a', 'SUBd', 'SSp6b', 'COAa1', 'COAa3', 'COAa2', 'MDl', 'MDm', 'MDc', 'PBld', 'PBle', 'PBls', 'PRE1', 'TTv3', 'PRE3', 'PRE2', 'BSTju', 'SUMm', 'SUMl', 'LGvm', 'LGvl', 'BSTrh', 'AIp6b', 'BSTse', 'SSp-m', 'SSp-n', 'TTv1-3', 'BSTtr', 'PVHpm', 'PBmv', 'BSTdm', 'PBme', 'PBmm', 'SSp4', 'SSp5', 'SSp1', 'PVHmm', 'BSTmg', 'SSp-bfd', 'DGcr', 'TTd1-4'])\n",
      "\n",
      "Regions with at least one voxel associated: 169\n",
      "[(1, 'TMv', 1884), (33, 'VISp6a', 82014), (41, 'VISpm2/3', 19917), (74, 'VISl6a', 12778), (120, 'AIp1', 31189), (121, 'VISl6b', 1610), (156, 'AUDd6a', 52134), (163, 'AIp2/3', 33257), (211, 'ACAd2/3', 50656), (233, 'VISal5', 14082), (243, 'AUDd6b', 10217), (249, 'AUDpo6a', 1307), (251, 'AUDp2/3', 39182), (252, 'AUDd5', 75964), (257, 'VISpm6a', 11585), (269, 'VISpl2/3', 9689), (274, 'RSPd6a', 46322), (279, 'RSPagl6b', 158), (281, 'VISam1', 8083), (288, 'ORBvl2/3', 35411), (296, 'ACAv2/3', 46352), (305, 'VISp6b', 10335), (314, 'AIp6a', 13892), (320, 'MOp1', 149419), (328, 'AId2/3', 70598), (330, 'RSPd6b', 1223), (344, 'AIp5', 29191), (377, 'VISpl6a', 9301), (382, 'CA1', 555065), (393, 'VISpl6b', 126), (401, 'VISam4', 5000), (412, 'ORBl2/3', 44449), (421, 'VISl1', 9779), (423, 'CA2', 88966), (430, 'RSPv2/3', 88080), (433, 'VISam5', 13976), (434, 'RSPd2/3', 64270), (440, 'ORBl6a', 11953), (441, 'VISam6b', 1086), (442, 'RSPd1', 30893), (448, 'ORBl1', 17882), (456, 'AUDpo6b', 270), (463, 'CA3', 354791), (10704, 'DG-po', 51187), (469, 'VISpm6b', 2275), (484, 'ORBm1', 19533), (488, 'ORBl6b', 19), (501, 'VISpm4', 7169), (520, 'AUDv6a', 30840), (527, 'AUDd1', 29577), (542, 'RSPv1', 35900), (545, 'RSPd4', 976), (565, 'VISpm5', 16877), (573, 'VISl4', 7752), (582, 'ORBm2/3', 23368), (588, 'ACAv1', 33890), (590, 'RSPv6a', 59776), (593, 'VISp1', 56148), (598, 'AUDv6b', 4998), (600, 'AUDd2/3', 60142), (601, 'VISal6a', 7715), (608, 'ORBvl6a', 9998), (610, 'RSPd5', 76561), (613, 'VISl5', 21668), (620, 'ORBm5', 15388), (622, 'RSPv6b', 5614), (630, 'ORBl5', 30371), (632, 'DG-sg', 101404), (643, 'AUDpo2/3', 3137), (648, 'MOp5', 344358), (649, 'VISal6b', 1441), (656, 'MOs1', 121223), (671, 'RSPagl1', 19519), (675, 'AIv6a', 6165), (678, 'AUDd4', 25950), (680, 'ORBvl6b', 76), (687, 'RSPv5', 118143), (694, 'AIv2/3', 39670), (696, 'AUDpo1', 1728), (699, 'AIv6b', 8), (704, 'AIv1', 30945), (718, 'VPL', 40066), (721, 'VISp4', 61357), (725, 'VPLpc', 2273), (733, 'VPM', 102689), (735, 'AUDp1', 16294), (741, 'VPMpc', 8633), (750, 'VISpl1', 4462), (755, 'AUDv2/3', 33060), (759, 'AUDpo4', 1356), (767, 'MOs5', 191770), (772, 'ACAv5', 37081), (774, 'RSPagl5', 24606), (778, 'VISp5', 132000), (783, 'AId6a', 19039), (791, 'AUDpo5', 3728), (800, 'AIv5', 25696), (805, 'VISpm1', 11155), (806, 'SSs2/3', 105435), (810, 'ACAv6a', 18507), (816, 'AUDp4', 16563), (819, 'ACAv6b', 4443), (821, 'VISp2/3', 132154), (831, 'AId6b', 418), (844, 'MOp6a', 244017), (847, 'AUDp5', 46593), (862, 'SSs6a', 68575), (869, 'VISpl4', 3003), (873, 'SSs1', 49609), (882, 'MOp6b', 43771), (893, 'SSs6b', 8102), (902, 'VISpl5', 14368), (905, 'VISal2/3', 11661), (906, 'RSPagl6a', 14114), (910, 'ORBm6a', 6524), (918, 'ENTl', 526878), (919, 'ACAd6a', 22529), (926, 'ENTm', 191405), (927, 'ACAd6b', 3005), (934, 'ENTmv', 16552), (935, 'ACAd1', 34249), (943, 'MOp2/3', 330988), (954, 'AUDp6a', 21820), (959, 'AUDv1', 18862), (962, 'MOs2/3', 208905), (965, 'RSPagl2/3', 24510), (969, 'ORBvl1', 25156), (973, 'VISl23', 20753), (990, 'AUDv4', 16821), (996, 'AId1', 40001), (1005, 'AUDp6b', 6090), (1015, 'ACAd5', 43701), (1021, 'MOs6a', 79750), (1023, 'AUDv5', 47654), (1035, 'SSs4', 50294), (1046, 'VISam6a', 9415), (1066, 'VISam2/3', 13266), (1074, 'VISal1', 5504), (1085, 'MOs6b', 5942), (1090, 'SSs5', 93754), (1101, 'AId5', 41939), (1114, 'VISal4', 4975), (1125, 'ORBvl5', 15049), (1126, 'TMd', 936), (312782550, 'VISa1', 5549), (312782554, 'VISa2/3', 10105), (312782558, 'VISa4', 4552), (312782562, 'VISa5', 10867), (312782566, 'VISa6a', 6155), (312782570, 'VISa6b', 899), (312782578, 'VISli1', 4320), (312782582, 'VISli2/3', 7962), (312782586, 'VISli4', 2933), (312782590, 'VISli5', 9603), (312782594, 'VISli6a', 5424), (312782598, 'VISli6b', 892), (312782604, 'VISrl1', 7720), (312782608, 'VISrl2/3', 16931), (312782612, 'VISrl4', 7218), (312782616, 'VISrl5', 19519), (312782620, 'VISrl6a', 10905), (312782624, 'VISrl6b', 2699), (312782632, 'VISpor1', 9528), (312782636, 'VISpor2/3', 24180), (312782640, 'VISpor4', 2354), (312782644, 'VISpor5', 23387), (312782648, 'VISpor6a', 8268), (312782652, 'VISpor6b', 979), (10703, 'DG-mo', 257103)]\n",
      "================================\n",
      "LEVEL 10\n",
      "Regions with no associated voxels: 66 set(['ENTl6a', 'DGcr-po', 'ENTl6b', 'COApl1-3', 'COApl1-2', 'ENTl4', 'ENTl5', 'ENTl2', 'ENTl3', 'DGlb-mo', 'SUBd-sp', 'DGmb-mo', 'DGcr-mo', 'COApm1', 'COApm2', 'COApm3', 'ENTmv4', 'SUBd-sr', 'ENTmv1', 'ENTmv2', 'ENTmv3', 'CA3sr', 'CA3sp', 'SUBd-m', 'SUBv-m', 'ENTm5/6', 'CA2sp', 'CA1slm', 'ENTm2a', 'ENTm2b', 'CA3so', 'DGmb-sg', 'ENTl2b', 'DGcr-sg', 'CA3slm', 'COApm1-2', 'COApm1-3', 'ENTm5', 'ENTm4', 'CA2slm', 'ENTm6', 'ENTm1', 'CA2so', 'PVHpmm', 'ENTm2', 'COApl3', 'COApl2', 'COApl1', 'ENTm3', 'PVHpml', 'CA3slu', 'DGlb-sg', 'CA2sr', 'SUBv-sr', 'SUBv-sp', 'ENTl2/3', 'ENTl2a', 'DGlb-po', 'DGmb-po', 'CA1sp', 'CA1sr', 'ENTmv5/6', 'CA1so', 'ENTl4/5', 'ENTl1', 'ENTl5/6'])\n",
      "\n",
      "Regions with at least one voxel associated: 42\n",
      "[(2, 'SSp-m6b', 7487), (9, 'SSp-tr6a', 10674), (113, 'SSp-ll2/3', 33461), (201, 'SSp-bfd2/3', 112563), (450, 'SSp-ul1', 20915), (461, 'SSp-tr6b', 2045), (478, 'SSp-ll6a', 24511), (510, 'SSp-ll6b', 6193), (558, 'SSp-n1', 21892), (577, 'SSp-ul4', 30178), (625, 'SSp-ul5', 61493), (654, 'SSp-n4', 32103), (657, 'SSp-m2/3', 126863), (670, 'SSp-tr2/3', 22678), (702, 'SSp-n5', 55951), (838, 'SSp-n2/3', 63473), (854, 'SSp-ul2/3', 60653), (878, 'SSp-m1', 50816), (889, 'SSp-n6a', 52755), (182305693, 'SSp-un1', 8938), (929, 'SSp-n6b', 5198), (182305701, 'SSp-un4', 12962), (182305705, 'SSp-un5', 27361), (182305709, 'SSp-un6a', 21825), (182305713, 'SSp-un6b', 4331), (950, 'SSp-m4', 57011), (974, 'SSp-m5', 103521), (981, 'SSp-bfd1', 35823), (1006, 'SSp-tr1', 8145), (1026, 'SSp-ul6b', 10803), (1030, 'SSp-ll1', 13610), (1038, 'SSp-bfd6a', 78454), (1047, 'SSp-bfd4', 51691), (1062, 'SSp-bfd6b', 14293), (1070, 'SSp-bfd5', 103351), (1086, 'SSp-tr4', 6378), (1094, 'SSp-ll4', 14951), (1102, 'SSp-m6a', 79118), (1111, 'SSp-tr5', 25067), (1128, 'SSp-ll5', 33760), (182305697, 'SSp-un2/3', 29066), (945, 'SSp-ul6a', 46906)]\n",
      "Total no of regions with associated voxels: 588 total not associated 646\n"
     ]
    }
   ],
   "source": [
    "mapped_regions = []\n",
    "not_mapped_regions= []\n",
    "for l in range(1, 11):\n",
    "    ## ID, LABEL, VOXELS_NO\n",
    "    level_data = [(i, a[1], a[2]) for i, a in conn2voxels.iteritems() if a[0]==l and a[2] >0]\n",
    "    no_voxels = set([a[1] for i, a in conn2voxels.iteritems() if a[0]==l and a[2] ==0])\n",
    "    voxels = set([i for i, a in conn2voxels.iteritems() if a[0]==l and a[2] >0])\n",
    "    mapped_regions.extend(voxels)\n",
    "    not_mapped_regions.extend(no_voxels)\n",
    "    print \"================================\"\n",
    "    print \"LEVEL\", l \n",
    "    print \"Regions with no associated voxels:\", len(no_voxels), no_voxels\n",
    "    print \"\"\n",
    "    print \"Regions with at least one voxel associated:\", len(level_data)\n",
    "    print level_data\n",
    "    \n",
    "print \"Total no of regions with associated voxels:\", len(mapped_regions), \"total not associated\", len(not_mapped_regions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "================================\n",
      "Conflict between parent associations for node: 997 (1, 'root', 40)\n",
      "and  587 child nodes (all with associated voxels as well)\n",
      "================================\n",
      "Conflict between parent associations for node: 73 (2, 'VS', 18385)\n",
      "and children with voxels [(3, 'V3', 82850), (3, 'c', 80), (3, 'V4', 50656), (3, 'AQ', 28584), (3, 'VL', 159548), (4, 'V4r', 53228)]\n",
      "================================\n",
      "Conflict between parent associations for node: 1009 (2, 'fiber tracts', 236648)\n",
      "and  56 child nodes (all with associated voxels as well)\n",
      "================================\n",
      "Conflict between parent associations for node: 512 (3, 'CB', 1)\n",
      "and children with voxels [(6, 'CUL', 448510), (6, 'PRM', 315291), (6, 'FOTU', 58946), (6, 'SIM', 351345), (6, 'DEC', 239591), (6, 'COPY', 155348), (5, 'DN', 21468), (6, 'UVU', 140142), (6, 'LING', 7942), (6, 'PFL', 356892), (6, 'AN', 733048), (6, 'NOD', 80661), (6, 'PYR', 58832), (6, 'CENT', 250358), (6, 'FL', 84339), (5, 'IP', 55207), (5, 'FN', 32651)]\n",
      "================================\n",
      "Conflict between parent associations for node: 145 (3, 'V4', 50656)\n",
      "and children with voxels [(4, 'V4r', 53228)]\n",
      "================================\n",
      "Conflict between parent associations for node: 784 (4, 'cst', 4959)\n",
      "and children with voxels [(5, 'cpd', 55637), (5, 'py', 34577), (5, 'int', 155764)]\n",
      "================================\n",
      "Conflict between parent associations for node: 877 (4, 'tsp', 10009)\n",
      "and children with voxels [(5, 'dtd', 2632)]\n",
      "================================\n",
      "Conflict between parent associations for node: 848 (4, 'IIn', 3786)\n",
      "and children with voxels [(5, 'och', 18309), (5, 'opt', 43331)]\n",
      "================================\n",
      "Conflict between parent associations for node: 313 (4, 'MB', 353356)\n",
      "and  43 child nodes (all with associated voxels as well)\n",
      "================================\n",
      "Conflict between parent associations for node: 863 (4, 'rust', 22757)\n",
      "and children with voxels [(5, 'vtd', 4164)]\n",
      "================================\n",
      "Conflict between parent associations for node: 771 (5, 'P', 384669)\n",
      "and  23 child nodes (all with associated voxels as well)\n",
      "================================\n",
      "Conflict between parent associations for node: 803 (5, 'PAL', 111434)\n",
      "and children with voxels [(7, 'TRS', 13836), (7, 'GPi', 27122), (7, 'MA', 21620), (8, 'MS', 39040), (7, 'SI', 178368), (8, 'NDB', 67827), (7, 'BAC', 478), (7, 'GPe', 103116), (7, 'BST', 95464)]\n",
      "================================\n",
      "Conflict between parent associations for node: 549 (5, 'TH', 295591)\n",
      "and  40 child nodes (all with associated voxels as well)\n",
      "================================\n",
      "Conflict between parent associations for node: 703 (5, 'CTXsp', 105638)\n",
      "and children with voxels [(6, 'LA', 41076), (7, 'EPv', 29142), (6, 'CLA', 31625), (6, 'PA', 20241), (7, 'BLAa', 46578), (7, 'BLAv', 16609), (7, 'BLAp', 40334), (7, 'EPd', 116160), (6, 'BMA', 69327)]\n",
      "================================\n",
      "Conflict between parent associations for node: 1097 (5, 'HY', 232031)\n",
      "and  42 child nodes (all with associated voxels as well)\n",
      "================================\n",
      "Conflict between parent associations for node: 477 (5, 'STR', 175862)\n",
      "and children with voxels [(7, 'CP', 1627409), (8, 'LSr', 138535), (7, 'BA', 4769), (7, 'SF', 16876), (7, 'FS', 23171), (7, 'IA', 12448), (8, 'LSv', 7287), (7, 'SH', 2365), (7, 'ACB', 263008), (7, 'OT', 242728), (7, 'MEA', 100225), (6, 'sAMY', 15406), (7, 'AAA', 37040), (7, 'CEA', 78676), (8, 'LSc', 34325)]\n",
      "================================\n",
      "Conflict between parent associations for node: 354 (5, 'MY', 575501)\n",
      "and  44 child nodes (all with associated voxels as well)\n",
      "================================\n",
      "Conflict between parent associations for node: 278 (6, 'sAMY', 15406)\n",
      "and children with voxels [(7, 'CEA', 78676), (7, 'IA', 12448), (7, 'MEA', 100225), (7, 'BA', 4769), (7, 'AAA', 37040)]\n",
      "================================\n",
      "Conflict between parent associations for node: 795 (6, 'PAG', 283394)\n",
      "and children with voxels [(7, 'ND', 1935), (7, 'PRC', 5291), (7, 'INC', 3513)]\n",
      "================================\n",
      "Conflict between parent associations for node: 698 (6, 'OLF', 275171)\n",
      "and children with voxels [(7, 'PIR', 822843), (8, 'AOBgr', 13589), (8, 'COAp', 124500), (8, 'COAa', 36755), (8, 'AOBmi', 17753), (7, 'TT', 98588), (7, 'DP', 15028), (8, 'NLOT3', 14544), (7, 'PAA', 45973), (7, 'TR', 66078), (8, 'NLOT1', 10457), (7, 'MOB', 1028777), (8, 'AOBgl', 9454), (7, 'AON', 240263)]\n",
      "================================\n",
      "Conflict between parent associations for node: 315 (6, 'Isocortex', 6)\n",
      "and  240 child nodes (all with associated voxels as well)\n",
      "================================\n",
      "Conflict between parent associations for node: 1089 (6, 'HPF', 171733)\n",
      "and children with voxels [(8, 'FC', 4025), (9, 'ENTmv', 16552), (9, 'CA2', 88966), (8, 'PAR', 59900), (9, 'ENTl', 526878), (8, 'POST', 53374), (9, 'DG-mo', 257103), (9, 'DG-po', 51187), (8, 'IG', 1772), (9, 'ENTm', 191405), (8, 'SUB', 289037), (9, 'DG-sg', 101404), (9, 'CA3', 354791), (8, 'PRE', 67752), (9, 'CA1', 555065)]\n",
      "================================\n",
      "Conflict between parent associations for node: 10 (7, 'SCig', 133547)\n",
      "and children with voxels [(8, 'SCig-c', 4918), (8, 'SCig-a', 8243), (8, 'SCig-b', 26045)]\n",
      "================================\n",
      "Conflict between parent associations for node: 797 (7, 'ZI', 88068)\n",
      "and children with voxels [(8, 'FF', 3662)]\n",
      "================================\n",
      "Conflict between parent associations for node: 895 (7, 'ECT', 101)\n",
      "and children with voxels [(8, 'ECT6a', 19220), (8, 'ECT5', 40220), (8, 'ECT2/3', 40003), (8, 'ECT1', 25197), (8, 'ECT6b', 6388)]\n",
      "================================\n",
      "Conflict between parent associations for node: 104 (8, 'AId', 8)\n",
      "and children with voxels [(9, 'AId2/3', 70598), (9, 'AId6b', 418), (9, 'AId1', 40001), (9, 'AId5', 41939), (9, 'AId6a', 19039)]\n",
      "================================\n",
      "Conflict between parent associations for node: 894 (8, 'RSPagl', 3439)\n",
      "and children with voxels [(9, 'RSPagl6a', 14114), (9, 'RSPagl6b', 158), (9, 'RSPagl2/3', 24510), (9, 'RSPagl5', 24606), (9, 'RSPagl1', 19519)]\n",
      "================================\n",
      "Conflict between parent associations for node: 985 (8, 'MOp', 34027)\n",
      "and children with voxels [(9, 'MOp5', 344358), (9, 'MOp1', 149419), (9, 'MOp6b', 43771), (9, 'MOp6a', 244017), (9, 'MOp2/3', 330988)]\n"
     ]
    }
   ],
   "source": [
    "#Find conflicting mappings\n",
    "for m in mapped_regions:\n",
    "    my_children = childs_map[m]\n",
    "    children_mapped = set(my_children).intersection(mapped_regions)\n",
    "    children_mapped = [conn2voxels[c] for c in children_mapped]\n",
    "    if children_mapped:\n",
    "        print \"================================\"\n",
    "        print \"Conflict between parent associations for node:\", m, conn2voxels[m]\n",
    "        if len(children_mapped) > 20:\n",
    "            print \"and \", len(children_mapped), \"child nodes (all with associated voxels as well)\"\n",
    "        else:\n",
    "            print \"and children with voxels\", children_mapped\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
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