{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# scona\n",
"\n",
"scona is a tool to perform network analysis over correlation networks of brain regions. \n",
"This tutorial will go through the basic functionality of scona, taking us from our inputs (a matrix of structural regional measures over subjects) to a report of local network measures for each brain region, and network level comparisons to a cohort of random graphs of the same degree. "
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import networkx as nx\n",
"import scona as scn\n",
"import scona.datasets as datasets"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Importing data\n",
"\n",
"A scona analysis starts with four inputs.\n",
"* __regional_measures__\n",
" A pandas DataFrame with subjects as rows. The columns should include structural measures for each brain region, as well as any subject-wise covariates. \n",
"* __names__\n",
" A list of names of the brain regions. This will be used to specify which columns of the __regional_measures__ matrix to want to correlate over.\n",
"* __covars__ _(optional)_ \n",
" A list of your covariates. This will be used to specify which columns of __regional_measure__ you wish to correct for. \n",
"* __centroids__\n",
" A list of tuples representing the cartesian coordinates of brain regions. This list should be in the same order as the list of brain regions to accurately assign coordinates to regions. The coordinates are expected to obey the convention the the x=0 plane is the same plane that separates the left and right hemispheres of the brain. "
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# Read in sample data from the NSPN WhitakerVertes PNAS 2016 paper.\n",
"df, names, covars, centroids = datasets.NSPN_WhitakerVertes_PNAS2016.import_data()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/html": [
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" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Unnamed: 0</th>\n",
" <th>nspn_id</th>\n",
" <th>occ</th>\n",
" <th>centre</th>\n",
" <th>study_primary</th>\n",
" <th>age_scan</th>\n",
" <th>sex</th>\n",
" <th>male</th>\n",
" <th>age_bin</th>\n",
" <th>mri_centre</th>\n",
" <th>...</th>\n",
" <th>rh_supramarginal_part5</th>\n",
" <th>rh_supramarginal_part6</th>\n",
" <th>rh_supramarginal_part7</th>\n",
" <th>rh_frontalpole_part1</th>\n",
" <th>rh_temporalpole_part1</th>\n",
" <th>rh_transversetemporal_part1</th>\n",
" <th>rh_insula_part1</th>\n",
" <th>rh_insula_part2</th>\n",
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" <th>rh_insula_part4</th>\n",
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" <td>10356</td>\n",
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" <td>Cambridge</td>\n",
" <td>2K_Cohort</td>\n",
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" <td>Female</td>\n",
" <td>0.0</td>\n",
" <td>4</td>\n",
" <td>WBIC</td>\n",
" <td>...</td>\n",
" <td>2.592</td>\n",
" <td>2.841</td>\n",
" <td>2.318</td>\n",
" <td>2.486</td>\n",
" <td>3.526</td>\n",
" <td>2.638</td>\n",
" <td>3.308</td>\n",
" <td>2.583</td>\n",
" <td>3.188</td>\n",
" <td>3.089</td>\n",
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" <tr>\n",
" <th>1</th>\n",
" <td>1</td>\n",
" <td>10702</td>\n",
" <td>0</td>\n",
" <td>Cambridge</td>\n",
" <td>2K_Cohort</td>\n",
" <td>16.055</td>\n",
" <td>Male</td>\n",
" <td>1.0</td>\n",
" <td>2</td>\n",
" <td>WBIC</td>\n",
" <td>...</td>\n",
" <td>3.448</td>\n",
" <td>3.283</td>\n",
" <td>2.740</td>\n",
" <td>3.225</td>\n",
" <td>4.044</td>\n",
" <td>3.040</td>\n",
" <td>3.867</td>\n",
" <td>2.943</td>\n",
" <td>3.478</td>\n",
" <td>3.609</td>\n",
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" <tr>\n",
" <th>2</th>\n",
" <td>2</td>\n",
" <td>10736</td>\n",
" <td>0</td>\n",
" <td>Cambridge</td>\n",
" <td>2K_Cohort</td>\n",
" <td>14.897</td>\n",
" <td>Female</td>\n",
" <td>0.0</td>\n",
" <td>1</td>\n",
" <td>WBIC</td>\n",
" <td>...</td>\n",
" <td>3.526</td>\n",
" <td>3.269</td>\n",
" <td>3.076</td>\n",
" <td>3.133</td>\n",
" <td>3.900</td>\n",
" <td>2.914</td>\n",
" <td>3.894</td>\n",
" <td>2.898</td>\n",
" <td>3.720</td>\n",
" <td>3.580</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>3</td>\n",
" <td>10778</td>\n",
" <td>0</td>\n",
" <td>Cambridge</td>\n",
" <td>2K_Cohort</td>\n",
" <td>20.022</td>\n",
" <td>Female</td>\n",
" <td>0.0</td>\n",
" <td>4</td>\n",
" <td>WBIC</td>\n",
" <td>...</td>\n",
" <td>2.830</td>\n",
" <td>2.917</td>\n",
" <td>2.647</td>\n",
" <td>2.796</td>\n",
" <td>3.401</td>\n",
" <td>3.045</td>\n",
" <td>3.138</td>\n",
" <td>2.739</td>\n",
" <td>2.833</td>\n",
" <td>3.349</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>4</td>\n",
" <td>10794</td>\n",
" <td>0</td>\n",
" <td>Cambridge</td>\n",
" <td>2K_Cohort</td>\n",
" <td>14.656</td>\n",
" <td>Female</td>\n",
" <td>0.0</td>\n",
" <td>1</td>\n",
" <td>WBIC</td>\n",
" <td>...</td>\n",
" <td>2.689</td>\n",
" <td>3.294</td>\n",
" <td>2.820</td>\n",
" <td>2.539</td>\n",
" <td>2.151</td>\n",
" <td>2.734</td>\n",
" <td>2.791</td>\n",
" <td>2.935</td>\n",
" <td>3.538</td>\n",
" <td>3.403</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 324 columns</p>\n",
"</div>"
],
"text/plain": [
" Unnamed: 0 nspn_id occ centre study_primary age_scan sex male \\\n",
"0 0 10356 0 Cambridge 2K_Cohort 20.761 Female 0.0 \n",
"1 1 10702 0 Cambridge 2K_Cohort 16.055 Male 1.0 \n",
"2 2 10736 0 Cambridge 2K_Cohort 14.897 Female 0.0 \n",
"3 3 10778 0 Cambridge 2K_Cohort 20.022 Female 0.0 \n",
"4 4 10794 0 Cambridge 2K_Cohort 14.656 Female 0.0 \n",
"\n",
" age_bin mri_centre ... rh_supramarginal_part5 \\\n",
"0 4 WBIC ... 2.592 \n",
"1 2 WBIC ... 3.448 \n",
"2 1 WBIC ... 3.526 \n",
"3 4 WBIC ... 2.830 \n",
"4 1 WBIC ... 2.689 \n",
"\n",
" rh_supramarginal_part6 rh_supramarginal_part7 rh_frontalpole_part1 \\\n",
"0 2.841 2.318 2.486 \n",
"1 3.283 2.740 3.225 \n",
"2 3.269 3.076 3.133 \n",
"3 2.917 2.647 2.796 \n",
"4 3.294 2.820 2.539 \n",
"\n",
" rh_temporalpole_part1 rh_transversetemporal_part1 rh_insula_part1 \\\n",
"0 3.526 2.638 3.308 \n",
"1 4.044 3.040 3.867 \n",
"2 3.900 2.914 3.894 \n",
"3 3.401 3.045 3.138 \n",
"4 2.151 2.734 2.791 \n",
"\n",
" rh_insula_part2 rh_insula_part3 rh_insula_part4 \n",
"0 2.583 3.188 3.089 \n",
"1 2.943 3.478 3.609 \n",
"2 2.898 3.720 3.580 \n",
"3 2.739 2.833 3.349 \n",
"4 2.935 3.538 3.403 \n",
"\n",
"[5 rows x 324 columns]"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Create a correlation matrix\n",
"We calculate residuals of the matrix df for the columns of names, correcting for the columns in covars."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"df_res = scn.create_residuals_df(df, names, covars)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
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" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
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" <th>lh_caudalanteriorcingulate_part1</th>\n",
" <th>lh_caudalmiddlefrontal_part1</th>\n",
" <th>lh_caudalmiddlefrontal_part2</th>\n",
" <th>lh_caudalmiddlefrontal_part3</th>\n",
" <th>lh_caudalmiddlefrontal_part4</th>\n",
" <th>lh_cuneus_part1</th>\n",
" <th>lh_cuneus_part2</th>\n",
" <th>lh_entorhinal_part1</th>\n",
" <th>...</th>\n",
" <th>rh_supramarginal_part5</th>\n",
" <th>rh_supramarginal_part6</th>\n",
" <th>rh_supramarginal_part7</th>\n",
" <th>rh_frontalpole_part1</th>\n",
" <th>rh_temporalpole_part1</th>\n",
" <th>rh_transversetemporal_part1</th>\n",
" <th>rh_insula_part1</th>\n",
" <th>rh_insula_part2</th>\n",
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" <td>-0.005168</td>\n",
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" <td>-0.170037</td>\n",
" <td>-0.192492</td>\n",
" <td>-0.119414</td>\n",
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" <td>-0.123926</td>\n",
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" <td>-0.103404</td>\n",
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" <td>0.406114</td>\n",
" <td>0.445832</td>\n",
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" <td>0.326963</td>\n",
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" <td>0.318074</td>\n",
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" <td>0.237293</td>\n",
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" <td>0.187832</td>\n",
" <td>0.576306</td>\n",
" <td>-0.061037</td>\n",
" <td>-0.062492</td>\n",
" <td>0.374586</td>\n",
" <td>...</td>\n",
" <td>0.512875</td>\n",
" <td>0.304074</td>\n",
" <td>0.37897</td>\n",
" <td>0.210391</td>\n",
" <td>0.230589</td>\n",
" <td>0.172596</td>\n",
" <td>0.264293</td>\n",
" <td>0.155781</td>\n",
" <td>0.34168</td>\n",
" <td>0.097859</td>\n",
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" <tr>\n",
" <th>3</th>\n",
" <td>-0.086677</td>\n",
" <td>-0.249253</td>\n",
" <td>-0.404108</td>\n",
" <td>-0.362586</td>\n",
" <td>-0.046886</td>\n",
" <td>-0.154168</td>\n",
" <td>-0.156694</td>\n",
" <td>0.029963</td>\n",
" <td>-0.246492</td>\n",
" <td>-0.009414</td>\n",
" <td>...</td>\n",
" <td>-0.183125</td>\n",
" <td>-0.047926</td>\n",
" <td>-0.05003</td>\n",
" <td>-0.126609</td>\n",
" <td>-0.268411</td>\n",
" <td>0.303596</td>\n",
" <td>-0.491707</td>\n",
" <td>-0.003219</td>\n",
" <td>-0.54532</td>\n",
" <td>-0.133141</td>\n",
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" <tr>\n",
" <th>4</th>\n",
" <td>0.400323</td>\n",
" <td>0.136747</td>\n",
" <td>0.125892</td>\n",
" <td>-0.218586</td>\n",
" <td>-1.003886</td>\n",
" <td>-0.142168</td>\n",
" <td>-0.752694</td>\n",
" <td>-0.091037</td>\n",
" <td>-0.550492</td>\n",
" <td>-1.223414</td>\n",
" <td>...</td>\n",
" <td>-0.324125</td>\n",
" <td>0.329074</td>\n",
" <td>0.12297</td>\n",
" <td>-0.383609</td>\n",
" <td>-1.518411</td>\n",
" <td>-0.007404</td>\n",
" <td>-0.838707</td>\n",
" <td>0.192781</td>\n",
" <td>0.15968</td>\n",
" <td>-0.079141</td>\n",
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" <td>0.010323</td>\n",
" <td>-0.090253</td>\n",
" <td>-0.248108</td>\n",
" <td>-0.131586</td>\n",
" <td>-0.080886</td>\n",
" <td>-0.110168</td>\n",
" <td>-0.142694</td>\n",
" <td>0.146963</td>\n",
" <td>-0.047492</td>\n",
" <td>0.155586</td>\n",
" <td>...</td>\n",
" <td>-0.097125</td>\n",
" <td>-0.074926</td>\n",
" <td>-0.12803</td>\n",
" <td>-0.114609</td>\n",
" <td>-0.241411</td>\n",
" <td>0.209596</td>\n",
" <td>0.326293</td>\n",
" <td>0.082781</td>\n",
" <td>0.26868</td>\n",
" <td>0.099859</td>\n",
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" <td>-0.118677</td>\n",
" <td>0.133747</td>\n",
" <td>0.089892</td>\n",
" <td>0.047414</td>\n",
" <td>0.268114</td>\n",
" <td>0.017832</td>\n",
" <td>-0.037694</td>\n",
" <td>0.061963</td>\n",
" <td>0.028508</td>\n",
" <td>-0.214414</td>\n",
" <td>...</td>\n",
" <td>0.080875</td>\n",
" <td>0.027074</td>\n",
" <td>0.00797</td>\n",
" <td>-0.067609</td>\n",
" <td>0.310589</td>\n",
" <td>-0.107404</td>\n",
" <td>-0.033707</td>\n",
" <td>-0.015219</td>\n",
" <td>-0.09132</td>\n",
" <td>0.048859</td>\n",
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" <tr>\n",
" <th>7</th>\n",
" <td>0.106323</td>\n",
" <td>0.043747</td>\n",
" <td>0.355892</td>\n",
" <td>0.174414</td>\n",
" <td>0.249114</td>\n",
" <td>0.068832</td>\n",
" <td>-0.017694</td>\n",
" <td>0.120963</td>\n",
" <td>0.095508</td>\n",
" <td>0.333586</td>\n",
" <td>...</td>\n",
" <td>0.427875</td>\n",
" <td>0.134074</td>\n",
" <td>0.25697</td>\n",
" <td>-0.229609</td>\n",
" <td>-0.214411</td>\n",
" <td>0.329596</td>\n",
" <td>-0.355707</td>\n",
" <td>0.015781</td>\n",
" <td>-0.02732</td>\n",
" <td>-0.118141</td>\n",
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" <tr>\n",
" <th>8</th>\n",
" <td>0.433323</td>\n",
" <td>0.037747</td>\n",
" <td>0.191892</td>\n",
" <td>0.103414</td>\n",
" <td>0.206114</td>\n",
" <td>-0.091168</td>\n",
" <td>0.210306</td>\n",
" <td>-0.105037</td>\n",
" <td>0.009508</td>\n",
" <td>0.388586</td>\n",
" <td>...</td>\n",
" <td>0.103875</td>\n",
" <td>0.182074</td>\n",
" <td>0.31697</td>\n",
" <td>-0.083609</td>\n",
" <td>0.176589</td>\n",
" <td>0.062596</td>\n",
" <td>0.404293</td>\n",
" <td>0.024781</td>\n",
" <td>-0.05932</td>\n",
" <td>0.041859</td>\n",
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" <tr>\n",
" <th>9</th>\n",
" <td>0.191323</td>\n",
" <td>0.081747</td>\n",
" <td>0.093892</td>\n",
" <td>0.100414</td>\n",
" <td>0.012114</td>\n",
" <td>0.180832</td>\n",
" <td>0.123306</td>\n",
" <td>-0.062037</td>\n",
" <td>-0.180492</td>\n",
" <td>-0.323414</td>\n",
" <td>...</td>\n",
" <td>-0.197125</td>\n",
" <td>-0.022926</td>\n",
" <td>-0.17103</td>\n",
" <td>0.527391</td>\n",
" <td>0.004589</td>\n",
" <td>0.123596</td>\n",
" <td>0.413293</td>\n",
" <td>-0.185219</td>\n",
" <td>-0.21632</td>\n",
" <td>0.065859</td>\n",
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" <tr>\n",
" <th>10</th>\n",
" <td>-1.036677</td>\n",
" <td>-0.759253</td>\n",
" <td>-0.621108</td>\n",
" <td>0.058414</td>\n",
" <td>-0.298886</td>\n",
" <td>0.005832</td>\n",
" <td>-0.419694</td>\n",
" <td>0.348963</td>\n",
" <td>0.232508</td>\n",
" <td>-0.997414</td>\n",
" <td>...</td>\n",
" <td>-0.463125</td>\n",
" <td>0.153074</td>\n",
" <td>0.01097</td>\n",
" <td>-0.540609</td>\n",
" <td>-0.149411</td>\n",
" <td>0.290596</td>\n",
" <td>-0.078707</td>\n",
" <td>0.073781</td>\n",
" <td>0.30068</td>\n",
" <td>0.333859</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>0.183323</td>\n",
" <td>0.155747</td>\n",
" <td>-0.100108</td>\n",
" <td>0.186414</td>\n",
" <td>-0.036886</td>\n",
" <td>0.206832</td>\n",
" <td>0.154306</td>\n",
" <td>0.020963</td>\n",
" <td>-0.053492</td>\n",
" <td>0.004586</td>\n",
" <td>...</td>\n",
" <td>0.149875</td>\n",
" <td>-0.113926</td>\n",
" <td>-0.11203</td>\n",
" <td>0.015391</td>\n",
" <td>0.233589</td>\n",
" <td>0.134596</td>\n",
" <td>-0.206707</td>\n",
" <td>-0.039219</td>\n",
" <td>-0.35132</td>\n",
" <td>0.220859</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>-0.058677</td>\n",
" <td>-0.222253</td>\n",
" <td>-0.230108</td>\n",
" <td>0.373414</td>\n",
" <td>0.219114</td>\n",
" <td>0.234832</td>\n",
" <td>0.018306</td>\n",
" <td>0.026963</td>\n",
" <td>0.090508</td>\n",
" <td>0.301586</td>\n",
" <td>...</td>\n",
" <td>0.102875</td>\n",
" <td>0.059074</td>\n",
" <td>-0.05203</td>\n",
" <td>0.061391</td>\n",
" <td>-0.193411</td>\n",
" <td>0.127596</td>\n",
" <td>0.292293</td>\n",
" <td>-0.027219</td>\n",
" <td>0.22968</td>\n",
" <td>0.481859</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>0.200323</td>\n",
" <td>-0.048253</td>\n",
" <td>0.032892</td>\n",
" <td>-0.106586</td>\n",
" <td>0.048114</td>\n",
" <td>-0.502168</td>\n",
" <td>-0.108694</td>\n",
" <td>0.127963</td>\n",
" <td>-0.104492</td>\n",
" <td>-0.043414</td>\n",
" <td>...</td>\n",
" <td>0.634875</td>\n",
" <td>0.150074</td>\n",
" <td>0.30797</td>\n",
" <td>0.413391</td>\n",
" <td>-0.463411</td>\n",
" <td>0.388596</td>\n",
" <td>0.216293</td>\n",
" <td>0.074781</td>\n",
" <td>0.23568</td>\n",
" <td>0.192859</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>0.221323</td>\n",
" <td>0.374747</td>\n",
" <td>0.107892</td>\n",
" <td>-0.115586</td>\n",
" <td>0.152114</td>\n",
" <td>-0.089168</td>\n",
" <td>0.032306</td>\n",
" <td>0.180963</td>\n",
" <td>0.287508</td>\n",
" <td>-0.422414</td>\n",
" <td>...</td>\n",
" <td>-0.086125</td>\n",
" <td>-0.217926</td>\n",
" <td>-0.06003</td>\n",
" <td>0.198391</td>\n",
" <td>0.171589</td>\n",
" <td>0.026596</td>\n",
" <td>0.124293</td>\n",
" <td>0.050781</td>\n",
" <td>-0.02332</td>\n",
" <td>-0.113141</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>0.075323</td>\n",
" <td>-0.141253</td>\n",
" <td>-0.161108</td>\n",
" <td>0.162414</td>\n",
" <td>-0.100886</td>\n",
" <td>-0.026168</td>\n",
" <td>-0.145694</td>\n",
" <td>0.209963</td>\n",
" <td>-0.070492</td>\n",
" <td>-0.518414</td>\n",
" <td>...</td>\n",
" <td>0.266875</td>\n",
" <td>0.019074</td>\n",
" <td>-0.21203</td>\n",
" <td>0.296391</td>\n",
" <td>-0.047411</td>\n",
" <td>-0.364404</td>\n",
" <td>-0.380707</td>\n",
" <td>0.210781</td>\n",
" <td>0.23068</td>\n",
" <td>0.030859</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>-0.047677</td>\n",
" <td>0.226747</td>\n",
" <td>-0.067108</td>\n",
" <td>0.019414</td>\n",
" <td>0.165114</td>\n",
" <td>-0.168168</td>\n",
" <td>-0.124694</td>\n",
" <td>-0.312037</td>\n",
" <td>-0.035492</td>\n",
" <td>0.112586</td>\n",
" <td>...</td>\n",
" <td>0.056875</td>\n",
" <td>-0.091926</td>\n",
" <td>-0.03103</td>\n",
" <td>0.301391</td>\n",
" <td>0.392589</td>\n",
" <td>0.115596</td>\n",
" <td>0.027293</td>\n",
" <td>0.234781</td>\n",
" <td>0.11168</td>\n",
" <td>0.111859</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>0.055323</td>\n",
" <td>-0.055253</td>\n",
" <td>0.164892</td>\n",
" <td>-0.322586</td>\n",
" <td>-0.029886</td>\n",
" <td>-0.139168</td>\n",
" <td>-0.103694</td>\n",
" <td>-0.004037</td>\n",
" <td>0.076508</td>\n",
" <td>0.069586</td>\n",
" <td>...</td>\n",
" <td>-0.157125</td>\n",
" <td>-0.117926</td>\n",
" <td>0.03697</td>\n",
" <td>-0.286609</td>\n",
" <td>0.243589</td>\n",
" <td>0.162596</td>\n",
" <td>0.045293</td>\n",
" <td>0.148781</td>\n",
" <td>0.22168</td>\n",
" <td>0.050859</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>-0.327677</td>\n",
" <td>0.128747</td>\n",
" <td>-0.260108</td>\n",
" <td>0.251414</td>\n",
" <td>-0.100886</td>\n",
" <td>0.145832</td>\n",
" <td>-0.091694</td>\n",
" <td>0.002963</td>\n",
" <td>0.038508</td>\n",
" <td>0.231586</td>\n",
" <td>...</td>\n",
" <td>0.261875</td>\n",
" <td>0.341074</td>\n",
" <td>0.20797</td>\n",
" <td>0.031391</td>\n",
" <td>0.052589</td>\n",
" <td>-0.204404</td>\n",
" <td>0.224293</td>\n",
" <td>-0.111219</td>\n",
" <td>-0.08532</td>\n",
" <td>0.079859</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>-0.012677</td>\n",
" <td>-0.090253</td>\n",
" <td>0.499892</td>\n",
" <td>-0.071586</td>\n",
" <td>0.111114</td>\n",
" <td>0.023832</td>\n",
" <td>0.103306</td>\n",
" <td>-0.278037</td>\n",
" <td>0.053508</td>\n",
" <td>0.236586</td>\n",
" <td>...</td>\n",
" <td>-0.003125</td>\n",
" <td>0.033074</td>\n",
" <td>-0.08003</td>\n",
" <td>-0.083609</td>\n",
" <td>0.069589</td>\n",
" <td>0.085596</td>\n",
" <td>0.416293</td>\n",
" <td>-0.049219</td>\n",
" <td>0.27268</td>\n",
" <td>0.344859</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>0.052323</td>\n",
" <td>-0.096253</td>\n",
" <td>0.879892</td>\n",
" <td>-0.218586</td>\n",
" <td>-0.087886</td>\n",
" <td>-0.296168</td>\n",
" <td>-0.231694</td>\n",
" <td>-0.080037</td>\n",
" <td>-0.212492</td>\n",
" <td>-0.596414</td>\n",
" <td>...</td>\n",
" <td>0.255875</td>\n",
" <td>-0.167926</td>\n",
" <td>-0.18103</td>\n",
" <td>0.095391</td>\n",
" <td>-0.579411</td>\n",
" <td>-0.360404</td>\n",
" <td>0.013293</td>\n",
" <td>-0.129219</td>\n",
" <td>-0.25632</td>\n",
" <td>0.101859</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>-0.028677</td>\n",
" <td>-0.236253</td>\n",
" <td>-0.091108</td>\n",
" <td>-0.280586</td>\n",
" <td>-0.182886</td>\n",
" <td>-0.320168</td>\n",
" <td>0.036306</td>\n",
" <td>0.103963</td>\n",
" <td>0.198508</td>\n",
" <td>-0.637414</td>\n",
" <td>...</td>\n",
" <td>-0.242125</td>\n",
" <td>-0.060926</td>\n",
" <td>-0.35703</td>\n",
" <td>-0.273609</td>\n",
" <td>-0.645411</td>\n",
" <td>-0.026404</td>\n",
" <td>-0.240707</td>\n",
" <td>0.046781</td>\n",
" <td>0.16268</td>\n",
" <td>0.029859</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>0.235323</td>\n",
" <td>0.102747</td>\n",
" <td>0.235892</td>\n",
" <td>0.103414</td>\n",
" <td>0.131114</td>\n",
" <td>-0.083168</td>\n",
" <td>0.164306</td>\n",
" <td>0.311963</td>\n",
" <td>0.240508</td>\n",
" <td>-0.716414</td>\n",
" <td>...</td>\n",
" <td>0.374875</td>\n",
" <td>0.073074</td>\n",
" <td>-0.16303</td>\n",
" <td>0.303391</td>\n",
" <td>0.011589</td>\n",
" <td>0.207596</td>\n",
" <td>0.238293</td>\n",
" <td>0.056781</td>\n",
" <td>-0.27732</td>\n",
" <td>0.288859</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>0.120323</td>\n",
" <td>0.066747</td>\n",
" <td>-0.144108</td>\n",
" <td>0.195414</td>\n",
" <td>0.097114</td>\n",
" <td>0.122832</td>\n",
" <td>0.139306</td>\n",
" <td>0.166963</td>\n",
" <td>0.033508</td>\n",
" <td>0.176586</td>\n",
" <td>...</td>\n",
" <td>0.321875</td>\n",
" <td>0.009074</td>\n",
" <td>-0.23003</td>\n",
" <td>0.320391</td>\n",
" <td>0.749589</td>\n",
" <td>0.300596</td>\n",
" <td>0.069293</td>\n",
" <td>0.103781</td>\n",
" <td>0.02568</td>\n",
" <td>-0.048141</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>0.084323</td>\n",
" <td>0.094747</td>\n",
" <td>-0.203108</td>\n",
" <td>-0.025586</td>\n",
" <td>-0.042886</td>\n",
" <td>0.127832</td>\n",
" <td>0.332306</td>\n",
" <td>0.005963</td>\n",
" <td>0.178508</td>\n",
" <td>-0.394414</td>\n",
" <td>...</td>\n",
" <td>0.356875</td>\n",
" <td>0.079074</td>\n",
" <td>0.10597</td>\n",
" <td>0.071391</td>\n",
" <td>-1.264411</td>\n",
" <td>0.001596</td>\n",
" <td>-0.204707</td>\n",
" <td>-0.084219</td>\n",
" <td>-0.05932</td>\n",
" <td>-0.320141</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>0.098323</td>\n",
" <td>0.030747</td>\n",
" <td>0.304892</td>\n",
" <td>0.160414</td>\n",
" <td>0.197114</td>\n",
" <td>0.275832</td>\n",
" <td>0.115306</td>\n",
" <td>0.185963</td>\n",
" <td>0.222508</td>\n",
" <td>0.053586</td>\n",
" <td>...</td>\n",
" <td>-0.141125</td>\n",
" <td>0.200074</td>\n",
" <td>-0.05003</td>\n",
" <td>0.162391</td>\n",
" <td>0.155589</td>\n",
" <td>-0.153404</td>\n",
" <td>0.403293</td>\n",
" <td>0.026781</td>\n",
" <td>0.33068</td>\n",
" <td>0.282859</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>0.024323</td>\n",
" <td>-0.112253</td>\n",
" <td>0.335892</td>\n",
" <td>0.332414</td>\n",
" <td>0.285114</td>\n",
" <td>0.348832</td>\n",
" <td>0.333306</td>\n",
" <td>0.214963</td>\n",
" <td>0.120508</td>\n",
" <td>0.118586</td>\n",
" <td>...</td>\n",
" <td>0.263875</td>\n",
" <td>0.127074</td>\n",
" <td>0.17397</td>\n",
" <td>0.191391</td>\n",
" <td>0.249589</td>\n",
" <td>0.214596</td>\n",
" <td>0.029293</td>\n",
" <td>0.233781</td>\n",
" <td>0.14168</td>\n",
" <td>0.342859</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>0.215323</td>\n",
" <td>-0.008253</td>\n",
" <td>-0.041108</td>\n",
" <td>0.083414</td>\n",
" <td>0.159114</td>\n",
" <td>-0.089168</td>\n",
" <td>0.300306</td>\n",
" <td>0.156963</td>\n",
" <td>0.088508</td>\n",
" <td>0.425586</td>\n",
" <td>...</td>\n",
" <td>-0.098125</td>\n",
" <td>0.280074</td>\n",
" <td>0.28197</td>\n",
" <td>0.000391</td>\n",
" <td>0.808589</td>\n",
" <td>0.006596</td>\n",
" <td>-0.036707</td>\n",
" <td>0.331781</td>\n",
" <td>0.16468</td>\n",
" <td>-0.137141</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>-0.170677</td>\n",
" <td>-0.324253</td>\n",
" <td>-0.035108</td>\n",
" <td>-0.098586</td>\n",
" <td>-0.178886</td>\n",
" <td>0.071832</td>\n",
" <td>-0.251694</td>\n",
" <td>-0.172037</td>\n",
" <td>-0.109492</td>\n",
" <td>0.553586</td>\n",
" <td>...</td>\n",
" <td>-0.119125</td>\n",
" <td>0.094074</td>\n",
" <td>0.13297</td>\n",
" <td>-0.610609</td>\n",
" <td>-0.063411</td>\n",
" <td>0.001596</td>\n",
" <td>0.141293</td>\n",
" <td>0.106781</td>\n",
" <td>0.47968</td>\n",
" <td>0.154859</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>-0.102677</td>\n",
" <td>-0.035253</td>\n",
" <td>-0.117108</td>\n",
" <td>0.318414</td>\n",
" <td>0.114114</td>\n",
" <td>0.035832</td>\n",
" <td>0.131306</td>\n",
" <td>-0.108037</td>\n",
" <td>0.029508</td>\n",
" <td>0.241586</td>\n",
" <td>...</td>\n",
" <td>0.008875</td>\n",
" <td>-0.023926</td>\n",
" <td>-0.34803</td>\n",
" <td>-0.158609</td>\n",
" <td>0.240589</td>\n",
" <td>-0.392404</td>\n",
" <td>0.222293</td>\n",
" <td>-0.063219</td>\n",
" <td>-0.24132</td>\n",
" <td>-0.042141</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>267</th>\n",
" <td>-0.604677</td>\n",
" <td>-0.283253</td>\n",
" <td>-0.478108</td>\n",
" <td>-0.215586</td>\n",
" <td>-0.244886</td>\n",
" <td>-0.302168</td>\n",
" <td>-0.239694</td>\n",
" <td>-0.234037</td>\n",
" <td>-0.143492</td>\n",
" <td>-0.014414</td>\n",
" <td>...</td>\n",
" <td>-0.118125</td>\n",
" <td>-0.104926</td>\n",
" <td>-0.22403</td>\n",
" <td>-0.305609</td>\n",
" <td>-0.048411</td>\n",
" <td>-0.260404</td>\n",
" <td>-0.130707</td>\n",
" <td>-0.320219</td>\n",
" <td>-0.17832</td>\n",
" <td>-0.153141</td>\n",
" </tr>\n",
" <tr>\n",
" <th>268</th>\n",
" <td>-0.090677</td>\n",
" <td>-0.174253</td>\n",
" <td>-0.005108</td>\n",
" <td>-0.201586</td>\n",
" <td>-0.215886</td>\n",
" <td>-0.309168</td>\n",
" <td>-0.170694</td>\n",
" <td>-0.136037</td>\n",
" <td>-0.316492</td>\n",
" <td>-0.344414</td>\n",
" <td>...</td>\n",
" <td>0.110875</td>\n",
" <td>-0.069926</td>\n",
" <td>-0.21103</td>\n",
" <td>-0.029609</td>\n",
" <td>-0.027411</td>\n",
" <td>-0.401404</td>\n",
" <td>-0.151707</td>\n",
" <td>0.014781</td>\n",
" <td>0.04168</td>\n",
" <td>-0.192141</td>\n",
" </tr>\n",
" <tr>\n",
" <th>269</th>\n",
" <td>-0.357677</td>\n",
" <td>-0.119253</td>\n",
" <td>0.010892</td>\n",
" <td>-0.054586</td>\n",
" <td>0.006114</td>\n",
" <td>0.097832</td>\n",
" <td>-0.164694</td>\n",
" <td>-0.214037</td>\n",
" <td>-0.363492</td>\n",
" <td>0.059586</td>\n",
" <td>...</td>\n",
" <td>-0.299125</td>\n",
" <td>-0.240926</td>\n",
" <td>-0.48403</td>\n",
" <td>-0.392609</td>\n",
" <td>-0.081411</td>\n",
" <td>-0.217404</td>\n",
" <td>-0.334707</td>\n",
" <td>-0.190219</td>\n",
" <td>0.18768</td>\n",
" <td>0.153859</td>\n",
" </tr>\n",
" <tr>\n",
" <th>270</th>\n",
" <td>0.166323</td>\n",
" <td>0.225747</td>\n",
" <td>0.357892</td>\n",
" <td>0.109414</td>\n",
" <td>-0.017886</td>\n",
" <td>0.109832</td>\n",
" <td>0.233306</td>\n",
" <td>-0.187037</td>\n",
" <td>-0.090492</td>\n",
" <td>-0.414414</td>\n",
" <td>...</td>\n",
" <td>0.089875</td>\n",
" <td>-0.149926</td>\n",
" <td>0.09397</td>\n",
" <td>0.096391</td>\n",
" <td>-0.332411</td>\n",
" <td>-0.022404</td>\n",
" <td>0.040293</td>\n",
" <td>0.066781</td>\n",
" <td>0.14768</td>\n",
" <td>0.005859</td>\n",
" </tr>\n",
" <tr>\n",
" <th>271</th>\n",
" <td>-0.056677</td>\n",
" <td>0.032747</td>\n",
" <td>0.074892</td>\n",
" <td>-0.072586</td>\n",
" <td>0.140114</td>\n",
" <td>0.023832</td>\n",
" <td>0.040306</td>\n",
" <td>-0.314037</td>\n",
" <td>-0.106492</td>\n",
" <td>-0.014414</td>\n",
" <td>...</td>\n",
" <td>-0.155125</td>\n",
" <td>-0.173926</td>\n",
" <td>-0.16003</td>\n",
" <td>0.053391</td>\n",
" <td>0.091589</td>\n",
" <td>0.107596</td>\n",
" <td>0.312293</td>\n",
" <td>0.226781</td>\n",
" <td>-0.02432</td>\n",
" <td>-0.068141</td>\n",
" </tr>\n",
" <tr>\n",
" <th>272</th>\n",
" <td>-0.159677</td>\n",
" <td>-0.130253</td>\n",
" <td>-0.410108</td>\n",
" <td>-0.154586</td>\n",
" <td>-0.204886</td>\n",
" <td>-0.074168</td>\n",
" <td>-0.299694</td>\n",
" <td>-0.113037</td>\n",
" <td>-0.417492</td>\n",
" <td>0.117586</td>\n",
" <td>...</td>\n",
" <td>-0.390125</td>\n",
" <td>-0.220926</td>\n",
" <td>-0.15603</td>\n",
" <td>-0.479609</td>\n",
" <td>-0.070411</td>\n",
" <td>-0.258404</td>\n",
" <td>-0.035707</td>\n",
" <td>-0.082219</td>\n",
" <td>-0.24732</td>\n",
" <td>-0.106141</td>\n",
" </tr>\n",
" <tr>\n",
" <th>273</th>\n",
" <td>-0.044677</td>\n",
" <td>-0.066253</td>\n",
" <td>-0.054108</td>\n",
" <td>0.289414</td>\n",
" <td>0.055114</td>\n",
" <td>0.143832</td>\n",
" <td>0.033306</td>\n",
" <td>-0.118037</td>\n",
" <td>-0.057492</td>\n",
" <td>-0.447414</td>\n",
" <td>...</td>\n",
" <td>-0.160125</td>\n",
" <td>-0.059926</td>\n",
" <td>-0.21903</td>\n",
" <td>-0.042609</td>\n",
" <td>-0.973411</td>\n",
" <td>-0.063404</td>\n",
" <td>-0.117707</td>\n",
" <td>0.005781</td>\n",
" <td>0.16668</td>\n",
" <td>-0.132141</td>\n",
" </tr>\n",
" <tr>\n",
" <th>274</th>\n",
" <td>0.591323</td>\n",
" <td>0.204747</td>\n",
" <td>0.964892</td>\n",
" <td>0.083414</td>\n",
" <td>0.247114</td>\n",
" <td>0.060832</td>\n",
" <td>0.243306</td>\n",
" <td>0.269963</td>\n",
" <td>0.017508</td>\n",
" <td>-0.211414</td>\n",
" <td>...</td>\n",
" <td>0.078875</td>\n",
" <td>-0.030926</td>\n",
" <td>-0.10203</td>\n",
" <td>-0.002609</td>\n",
" <td>0.377589</td>\n",
" <td>0.035596</td>\n",
" <td>-0.297707</td>\n",
" <td>0.018781</td>\n",
" <td>-0.00032</td>\n",
" <td>0.275859</td>\n",
" </tr>\n",
" <tr>\n",
" <th>275</th>\n",
" <td>0.290323</td>\n",
" <td>0.104747</td>\n",
" <td>0.129892</td>\n",
" <td>-0.112586</td>\n",
" <td>0.008114</td>\n",
" <td>0.015832</td>\n",
" <td>0.017306</td>\n",
" <td>0.164963</td>\n",
" <td>0.092508</td>\n",
" <td>0.136586</td>\n",
" <td>...</td>\n",
" <td>0.151875</td>\n",
" <td>-0.044926</td>\n",
" <td>0.03697</td>\n",
" <td>-0.131609</td>\n",
" <td>0.205589</td>\n",
" <td>0.024596</td>\n",
" <td>0.012293</td>\n",
" <td>-0.011219</td>\n",
" <td>-0.04732</td>\n",
" <td>0.044859</td>\n",
" </tr>\n",
" <tr>\n",
" <th>276</th>\n",
" <td>-0.197677</td>\n",
" <td>-0.123253</td>\n",
" <td>-0.140108</td>\n",
" <td>-0.063586</td>\n",
" <td>-0.268886</td>\n",
" <td>-0.137168</td>\n",
" <td>-0.176694</td>\n",
" <td>-0.029037</td>\n",
" <td>-0.158492</td>\n",
" <td>-1.103414</td>\n",
" <td>...</td>\n",
" <td>-0.183125</td>\n",
" <td>-0.317926</td>\n",
" <td>-0.23103</td>\n",
" <td>-0.011609</td>\n",
" <td>-0.146411</td>\n",
" <td>-0.106404</td>\n",
" <td>-0.307707</td>\n",
" <td>-0.149219</td>\n",
" <td>-0.46132</td>\n",
" <td>-0.449141</td>\n",
" </tr>\n",
" <tr>\n",
" <th>277</th>\n",
" <td>-0.115677</td>\n",
" <td>-0.187253</td>\n",
" <td>-0.163108</td>\n",
" <td>0.037414</td>\n",
" <td>-0.177886</td>\n",
" <td>0.092832</td>\n",
" <td>-0.158694</td>\n",
" <td>0.042963</td>\n",
" <td>-0.052492</td>\n",
" <td>0.311586</td>\n",
" <td>...</td>\n",
" <td>-0.040125</td>\n",
" <td>-0.144926</td>\n",
" <td>0.04497</td>\n",
" <td>-0.074609</td>\n",
" <td>0.241589</td>\n",
" <td>-0.098404</td>\n",
" <td>0.155293</td>\n",
" <td>-0.269219</td>\n",
" <td>-0.11532</td>\n",
" <td>0.224859</td>\n",
" </tr>\n",
" <tr>\n",
" <th>278</th>\n",
" <td>-0.020677</td>\n",
" <td>0.037747</td>\n",
" <td>0.184892</td>\n",
" <td>-0.231586</td>\n",
" <td>0.115114</td>\n",
" <td>-0.216168</td>\n",
" <td>0.078306</td>\n",
" <td>-0.119037</td>\n",
" <td>0.026508</td>\n",
" <td>0.500586</td>\n",
" <td>...</td>\n",
" <td>0.208875</td>\n",
" <td>-0.269926</td>\n",
" <td>-0.07503</td>\n",
" <td>0.109391</td>\n",
" <td>0.752589</td>\n",
" <td>-0.303404</td>\n",
" <td>-0.075707</td>\n",
" <td>-0.149219</td>\n",
" <td>-0.27532</td>\n",
" <td>-0.155141</td>\n",
" </tr>\n",
" <tr>\n",
" <th>279</th>\n",
" <td>-0.197677</td>\n",
" <td>-0.128253</td>\n",
" <td>-0.123108</td>\n",
" <td>0.221414</td>\n",
" <td>0.141114</td>\n",
" <td>-0.052168</td>\n",
" <td>0.001306</td>\n",
" <td>-0.256037</td>\n",
" <td>-0.088492</td>\n",
" <td>-0.018414</td>\n",
" <td>...</td>\n",
" <td>-0.179125</td>\n",
" <td>0.056074</td>\n",
" <td>-0.25603</td>\n",
" <td>-0.312609</td>\n",
" <td>0.540589</td>\n",
" <td>-0.281404</td>\n",
" <td>0.288293</td>\n",
" <td>-0.092219</td>\n",
" <td>-0.17332</td>\n",
" <td>0.202859</td>\n",
" </tr>\n",
" <tr>\n",
" <th>280</th>\n",
" <td>0.040323</td>\n",
" <td>0.115747</td>\n",
" <td>-0.322108</td>\n",
" <td>-0.163586</td>\n",
" <td>0.034114</td>\n",
" <td>-0.075168</td>\n",
" <td>-0.051694</td>\n",
" <td>-0.072037</td>\n",
" <td>0.161508</td>\n",
" <td>-0.070414</td>\n",
" <td>...</td>\n",
" <td>0.193875</td>\n",
" <td>-0.043926</td>\n",
" <td>-0.00603</td>\n",
" <td>-0.025609</td>\n",
" <td>0.129589</td>\n",
" <td>0.148596</td>\n",
" <td>-0.181707</td>\n",
" <td>-0.166219</td>\n",
" <td>0.11968</td>\n",
" <td>0.239859</td>\n",
" </tr>\n",
" <tr>\n",
" <th>281</th>\n",
" <td>-0.081677</td>\n",
" <td>-0.254253</td>\n",
" <td>-0.144108</td>\n",
" <td>-0.035586</td>\n",
" <td>-0.221886</td>\n",
" <td>0.103832</td>\n",
" <td>-0.140694</td>\n",
" <td>-0.201037</td>\n",
" <td>-0.285492</td>\n",
" <td>-0.566414</td>\n",
" <td>...</td>\n",
" <td>0.021875</td>\n",
" <td>-0.259926</td>\n",
" <td>-0.06303</td>\n",
" <td>-0.563609</td>\n",
" <td>-0.486411</td>\n",
" <td>-0.403404</td>\n",
" <td>0.208293</td>\n",
" <td>-0.200219</td>\n",
" <td>-0.38132</td>\n",
" <td>-0.004141</td>\n",
" </tr>\n",
" <tr>\n",
" <th>282</th>\n",
" <td>0.304323</td>\n",
" <td>0.275747</td>\n",
" <td>0.050892</td>\n",
" <td>0.406414</td>\n",
" <td>-0.260886</td>\n",
" <td>0.197832</td>\n",
" <td>-0.060694</td>\n",
" <td>0.071963</td>\n",
" <td>0.272508</td>\n",
" <td>0.086586</td>\n",
" <td>...</td>\n",
" <td>-0.065125</td>\n",
" <td>-0.018926</td>\n",
" <td>-0.05403</td>\n",
" <td>-0.079609</td>\n",
" <td>-0.345411</td>\n",
" <td>0.003596</td>\n",
" <td>0.190293</td>\n",
" <td>0.157781</td>\n",
" <td>-0.07332</td>\n",
" <td>-0.016141</td>\n",
" </tr>\n",
" <tr>\n",
" <th>283</th>\n",
" <td>-0.305677</td>\n",
" <td>-0.238253</td>\n",
" <td>-0.178108</td>\n",
" <td>-0.360586</td>\n",
" <td>-0.077886</td>\n",
" <td>-0.201168</td>\n",
" <td>-0.061694</td>\n",
" <td>-0.185037</td>\n",
" <td>-0.128492</td>\n",
" <td>-0.393414</td>\n",
" <td>...</td>\n",
" <td>0.182875</td>\n",
" <td>0.455074</td>\n",
" <td>0.07497</td>\n",
" <td>-0.132609</td>\n",
" <td>-0.289411</td>\n",
" <td>-0.127404</td>\n",
" <td>0.108293</td>\n",
" <td>-0.408219</td>\n",
" <td>-0.02232</td>\n",
" <td>-0.117141</td>\n",
" </tr>\n",
" <tr>\n",
" <th>284</th>\n",
" <td>-0.027677</td>\n",
" <td>-0.158253</td>\n",
" <td>0.325892</td>\n",
" <td>-0.156586</td>\n",
" <td>-0.180886</td>\n",
" <td>-0.258168</td>\n",
" <td>-0.495694</td>\n",
" <td>-0.088037</td>\n",
" <td>-0.003492</td>\n",
" <td>-0.279414</td>\n",
" <td>...</td>\n",
" <td>-0.426125</td>\n",
" <td>-0.618926</td>\n",
" <td>-0.58403</td>\n",
" <td>-0.095609</td>\n",
" <td>0.234589</td>\n",
" <td>0.208596</td>\n",
" <td>-0.040707</td>\n",
" <td>-0.310219</td>\n",
" <td>0.08468</td>\n",
" <td>-0.363141</td>\n",
" </tr>\n",
" <tr>\n",
" <th>285</th>\n",
" <td>-0.216677</td>\n",
" <td>-0.194253</td>\n",
" <td>-0.189108</td>\n",
" <td>-0.320586</td>\n",
" <td>-0.349886</td>\n",
" <td>-0.364168</td>\n",
" <td>-0.040694</td>\n",
" <td>-0.165037</td>\n",
" <td>-0.418492</td>\n",
" <td>-0.879414</td>\n",
" <td>...</td>\n",
" <td>0.286875</td>\n",
" <td>0.135074</td>\n",
" <td>-0.15703</td>\n",
" <td>-0.095609</td>\n",
" <td>-0.683411</td>\n",
" <td>0.179596</td>\n",
" <td>-0.602707</td>\n",
" <td>-0.162219</td>\n",
" <td>-0.05432</td>\n",
" <td>-0.057141</td>\n",
" </tr>\n",
" <tr>\n",
" <th>286</th>\n",
" <td>-0.073677</td>\n",
" <td>-0.038253</td>\n",
" <td>0.199892</td>\n",
" <td>0.169414</td>\n",
" <td>0.149114</td>\n",
" <td>-0.143168</td>\n",
" <td>-0.025694</td>\n",
" <td>-0.127037</td>\n",
" <td>0.317508</td>\n",
" <td>-0.432414</td>\n",
" <td>...</td>\n",
" <td>0.125875</td>\n",
" <td>-0.206926</td>\n",
" <td>-0.10503</td>\n",
" <td>-0.109609</td>\n",
" <td>-0.489411</td>\n",
" <td>0.110596</td>\n",
" <td>0.186293</td>\n",
" <td>-0.040219</td>\n",
" <td>-0.09332</td>\n",
" <td>0.113859</td>\n",
" </tr>\n",
" <tr>\n",
" <th>287</th>\n",
" <td>0.136323</td>\n",
" <td>-0.043253</td>\n",
" <td>-0.317108</td>\n",
" <td>-0.010586</td>\n",
" <td>-0.026886</td>\n",
" <td>-0.001168</td>\n",
" <td>0.083306</td>\n",
" <td>-0.012037</td>\n",
" <td>-0.007492</td>\n",
" <td>-0.286414</td>\n",
" <td>...</td>\n",
" <td>0.049875</td>\n",
" <td>0.157074</td>\n",
" <td>-0.14303</td>\n",
" <td>0.171391</td>\n",
" <td>0.224589</td>\n",
" <td>-0.221404</td>\n",
" <td>0.475293</td>\n",
" <td>-0.159219</td>\n",
" <td>-0.05332</td>\n",
" <td>-0.012141</td>\n",
" </tr>\n",
" <tr>\n",
" <th>288</th>\n",
" <td>-0.147677</td>\n",
" <td>-0.059253</td>\n",
" <td>0.028892</td>\n",
" <td>-0.108586</td>\n",
" <td>-0.090886</td>\n",
" <td>0.235832</td>\n",
" <td>-0.101694</td>\n",
" <td>0.177963</td>\n",
" <td>0.338508</td>\n",
" <td>0.024586</td>\n",
" <td>...</td>\n",
" <td>-0.163125</td>\n",
" <td>0.239074</td>\n",
" <td>-0.00603</td>\n",
" <td>0.187391</td>\n",
" <td>0.066589</td>\n",
" <td>0.212596</td>\n",
" <td>-0.525707</td>\n",
" <td>0.003781</td>\n",
" <td>0.26568</td>\n",
" <td>-0.061141</td>\n",
" </tr>\n",
" <tr>\n",
" <th>289</th>\n",
" <td>-0.209677</td>\n",
" <td>0.044747</td>\n",
" <td>0.043892</td>\n",
" <td>-0.130586</td>\n",
" <td>-0.178886</td>\n",
" <td>-0.134168</td>\n",
" <td>-0.152694</td>\n",
" <td>-0.034037</td>\n",
" <td>-0.011492</td>\n",
" <td>0.174586</td>\n",
" <td>...</td>\n",
" <td>0.039875</td>\n",
" <td>-0.199926</td>\n",
" <td>-0.02903</td>\n",
" <td>-0.080609</td>\n",
" <td>0.426589</td>\n",
" <td>-0.293404</td>\n",
" <td>-0.201707</td>\n",
" <td>-0.118219</td>\n",
" <td>-0.17732</td>\n",
" <td>-0.079141</td>\n",
" </tr>\n",
" <tr>\n",
" <th>290</th>\n",
" <td>-0.403677</td>\n",
" <td>0.044747</td>\n",
" <td>-0.360108</td>\n",
" <td>-0.476586</td>\n",
" <td>-0.218886</td>\n",
" <td>-0.099168</td>\n",
" <td>0.142306</td>\n",
" <td>-0.432037</td>\n",
" <td>-0.274492</td>\n",
" <td>0.156586</td>\n",
" <td>...</td>\n",
" <td>-0.027125</td>\n",
" <td>-0.110926</td>\n",
" <td>-0.17803</td>\n",
" <td>0.067391</td>\n",
" <td>0.109589</td>\n",
" <td>-0.089404</td>\n",
" <td>-0.283707</td>\n",
" <td>-0.212219</td>\n",
" <td>-0.07232</td>\n",
" <td>0.050859</td>\n",
" </tr>\n",
" <tr>\n",
" <th>291</th>\n",
" <td>-0.053677</td>\n",
" <td>-0.079253</td>\n",
" <td>0.122892</td>\n",
" <td>0.079414</td>\n",
" <td>-0.123886</td>\n",
" <td>0.224832</td>\n",
" <td>0.018306</td>\n",
" <td>0.144963</td>\n",
" <td>0.000508</td>\n",
" <td>0.409586</td>\n",
" <td>...</td>\n",
" <td>-0.114125</td>\n",
" <td>0.290074</td>\n",
" <td>-0.06003</td>\n",
" <td>-0.331609</td>\n",
" <td>0.194589</td>\n",
" <td>0.309596</td>\n",
" <td>-0.296707</td>\n",
" <td>0.559781</td>\n",
" <td>0.36268</td>\n",
" <td>-0.069141</td>\n",
" </tr>\n",
" <tr>\n",
" <th>292</th>\n",
" <td>-0.065677</td>\n",
" <td>-0.112253</td>\n",
" <td>-0.013108</td>\n",
" <td>-0.233586</td>\n",
" <td>0.178114</td>\n",
" <td>-0.049168</td>\n",
" <td>-0.103694</td>\n",
" <td>0.024963</td>\n",
" <td>0.088508</td>\n",
" <td>-0.169414</td>\n",
" <td>...</td>\n",
" <td>-0.417125</td>\n",
" <td>-0.198926</td>\n",
" <td>0.01897</td>\n",
" <td>0.430391</td>\n",
" <td>0.005589</td>\n",
" <td>0.126596</td>\n",
" <td>0.327293</td>\n",
" <td>0.250781</td>\n",
" <td>0.18468</td>\n",
" <td>0.247859</td>\n",
" </tr>\n",
" <tr>\n",
" <th>293</th>\n",
" <td>0.014323</td>\n",
" <td>0.237747</td>\n",
" <td>-0.093108</td>\n",
" <td>0.100414</td>\n",
" <td>0.068114</td>\n",
" <td>-0.174168</td>\n",
" <td>-0.113694</td>\n",
" <td>0.013963</td>\n",
" <td>0.121508</td>\n",
" <td>-0.030414</td>\n",
" <td>...</td>\n",
" <td>0.227875</td>\n",
" <td>-0.383926</td>\n",
" <td>-0.02703</td>\n",
" <td>0.099391</td>\n",
" <td>-0.410411</td>\n",
" <td>-0.010404</td>\n",
" <td>-0.075707</td>\n",
" <td>0.181781</td>\n",
" <td>0.29768</td>\n",
" <td>0.126859</td>\n",
" </tr>\n",
" <tr>\n",
" <th>294</th>\n",
" <td>0.066323</td>\n",
" <td>0.071747</td>\n",
" <td>-0.301108</td>\n",
" <td>-0.021586</td>\n",
" <td>0.082114</td>\n",
" <td>-0.131168</td>\n",
" <td>-0.339694</td>\n",
" <td>-0.174037</td>\n",
" <td>-0.332492</td>\n",
" <td>0.478586</td>\n",
" <td>...</td>\n",
" <td>0.329875</td>\n",
" <td>0.022074</td>\n",
" <td>0.23197</td>\n",
" <td>-0.335609</td>\n",
" <td>0.068589</td>\n",
" <td>-0.007404</td>\n",
" <td>0.165293</td>\n",
" <td>0.018781</td>\n",
" <td>-0.20932</td>\n",
" <td>0.309859</td>\n",
" </tr>\n",
" <tr>\n",
" <th>295</th>\n",
" <td>0.053323</td>\n",
" <td>-0.269253</td>\n",
" <td>0.174892</td>\n",
" <td>-0.041586</td>\n",
" <td>-0.318886</td>\n",
" <td>-0.093168</td>\n",
" <td>-0.199694</td>\n",
" <td>0.185963</td>\n",
" <td>-0.272492</td>\n",
" <td>0.304586</td>\n",
" <td>...</td>\n",
" <td>-0.215125</td>\n",
" <td>-0.466926</td>\n",
" <td>0.03697</td>\n",
" <td>0.109391</td>\n",
" <td>-0.486411</td>\n",
" <td>-0.272404</td>\n",
" <td>-0.329707</td>\n",
" <td>-0.204219</td>\n",
" <td>0.12468</td>\n",
" <td>-0.165141</td>\n",
" </tr>\n",
" <tr>\n",
" <th>296</th>\n",
" <td>-0.206677</td>\n",
" <td>0.044747</td>\n",
" <td>0.205892</td>\n",
" <td>-0.159586</td>\n",
" <td>0.087114</td>\n",
" <td>-0.107168</td>\n",
" <td>-0.191694</td>\n",
" <td>0.220963</td>\n",
" <td>-0.106492</td>\n",
" <td>-0.066414</td>\n",
" <td>...</td>\n",
" <td>-0.022125</td>\n",
" <td>0.280074</td>\n",
" <td>0.14397</td>\n",
" <td>0.225391</td>\n",
" <td>0.312589</td>\n",
" <td>0.366596</td>\n",
" <td>0.028293</td>\n",
" <td>0.178781</td>\n",
" <td>0.47468</td>\n",
" <td>-0.205141</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>297 rows × 308 columns</p>\n",
"</div>"
],
"text/plain": [
" lh_bankssts_part1 lh_bankssts_part2 lh_caudalanteriorcingulate_part1 \\\n",
"0 -0.016677 -0.036253 0.035892 \n",
"1 0.280323 0.354747 0.482892 \n",
"2 0.168323 0.081747 0.365892 \n",
"3 -0.086677 -0.249253 -0.404108 \n",
"4 0.400323 0.136747 0.125892 \n",
"5 0.010323 -0.090253 -0.248108 \n",
"6 -0.118677 0.133747 0.089892 \n",
"7 0.106323 0.043747 0.355892 \n",
"8 0.433323 0.037747 0.191892 \n",
"9 0.191323 0.081747 0.093892 \n",
"10 -1.036677 -0.759253 -0.621108 \n",
"11 0.183323 0.155747 -0.100108 \n",
"12 -0.058677 -0.222253 -0.230108 \n",
"13 0.200323 -0.048253 0.032892 \n",
"14 0.221323 0.374747 0.107892 \n",
"15 0.075323 -0.141253 -0.161108 \n",
"16 -0.047677 0.226747 -0.067108 \n",
"17 0.055323 -0.055253 0.164892 \n",
"18 -0.327677 0.128747 -0.260108 \n",
"19 -0.012677 -0.090253 0.499892 \n",
"20 0.052323 -0.096253 0.879892 \n",
"21 -0.028677 -0.236253 -0.091108 \n",
"22 0.235323 0.102747 0.235892 \n",
"23 0.120323 0.066747 -0.144108 \n",
"24 0.084323 0.094747 -0.203108 \n",
"25 0.098323 0.030747 0.304892 \n",
"26 0.024323 -0.112253 0.335892 \n",
"27 0.215323 -0.008253 -0.041108 \n",
"28 -0.170677 -0.324253 -0.035108 \n",
"29 -0.102677 -0.035253 -0.117108 \n",
".. ... ... ... \n",
"267 -0.604677 -0.283253 -0.478108 \n",
"268 -0.090677 -0.174253 -0.005108 \n",
"269 -0.357677 -0.119253 0.010892 \n",
"270 0.166323 0.225747 0.357892 \n",
"271 -0.056677 0.032747 0.074892 \n",
"272 -0.159677 -0.130253 -0.410108 \n",
"273 -0.044677 -0.066253 -0.054108 \n",
"274 0.591323 0.204747 0.964892 \n",
"275 0.290323 0.104747 0.129892 \n",
"276 -0.197677 -0.123253 -0.140108 \n",
"277 -0.115677 -0.187253 -0.163108 \n",
"278 -0.020677 0.037747 0.184892 \n",
"279 -0.197677 -0.128253 -0.123108 \n",
"280 0.040323 0.115747 -0.322108 \n",
"281 -0.081677 -0.254253 -0.144108 \n",
"282 0.304323 0.275747 0.050892 \n",
"283 -0.305677 -0.238253 -0.178108 \n",
"284 -0.027677 -0.158253 0.325892 \n",
"285 -0.216677 -0.194253 -0.189108 \n",
"286 -0.073677 -0.038253 0.199892 \n",
"287 0.136323 -0.043253 -0.317108 \n",
"288 -0.147677 -0.059253 0.028892 \n",
"289 -0.209677 0.044747 0.043892 \n",
"290 -0.403677 0.044747 -0.360108 \n",
"291 -0.053677 -0.079253 0.122892 \n",
"292 -0.065677 -0.112253 -0.013108 \n",
"293 0.014323 0.237747 -0.093108 \n",
"294 0.066323 0.071747 -0.301108 \n",
"295 0.053323 -0.269253 0.174892 \n",
"296 -0.206677 0.044747 0.205892 \n",
"\n",
" lh_caudalmiddlefrontal_part1 lh_caudalmiddlefrontal_part2 \\\n",
"0 -0.004586 0.040114 \n",
"1 0.697414 0.406114 \n",
"2 0.412414 0.283114 \n",
"3 -0.362586 -0.046886 \n",
"4 -0.218586 -1.003886 \n",
"5 -0.131586 -0.080886 \n",
"6 0.047414 0.268114 \n",
"7 0.174414 0.249114 \n",
"8 0.103414 0.206114 \n",
"9 0.100414 0.012114 \n",
"10 0.058414 -0.298886 \n",
"11 0.186414 -0.036886 \n",
"12 0.373414 0.219114 \n",
"13 -0.106586 0.048114 \n",
"14 -0.115586 0.152114 \n",
"15 0.162414 -0.100886 \n",
"16 0.019414 0.165114 \n",
"17 -0.322586 -0.029886 \n",
"18 0.251414 -0.100886 \n",
"19 -0.071586 0.111114 \n",
"20 -0.218586 -0.087886 \n",
"21 -0.280586 -0.182886 \n",
"22 0.103414 0.131114 \n",
"23 0.195414 0.097114 \n",
"24 -0.025586 -0.042886 \n",
"25 0.160414 0.197114 \n",
"26 0.332414 0.285114 \n",
"27 0.083414 0.159114 \n",
"28 -0.098586 -0.178886 \n",
"29 0.318414 0.114114 \n",
".. ... ... \n",
"267 -0.215586 -0.244886 \n",
"268 -0.201586 -0.215886 \n",
"269 -0.054586 0.006114 \n",
"270 0.109414 -0.017886 \n",
"271 -0.072586 0.140114 \n",
"272 -0.154586 -0.204886 \n",
"273 0.289414 0.055114 \n",
"274 0.083414 0.247114 \n",
"275 -0.112586 0.008114 \n",
"276 -0.063586 -0.268886 \n",
"277 0.037414 -0.177886 \n",
"278 -0.231586 0.115114 \n",
"279 0.221414 0.141114 \n",
"280 -0.163586 0.034114 \n",
"281 -0.035586 -0.221886 \n",
"282 0.406414 -0.260886 \n",
"283 -0.360586 -0.077886 \n",
"284 -0.156586 -0.180886 \n",
"285 -0.320586 -0.349886 \n",
"286 0.169414 0.149114 \n",
"287 -0.010586 -0.026886 \n",
"288 -0.108586 -0.090886 \n",
"289 -0.130586 -0.178886 \n",
"290 -0.476586 -0.218886 \n",
"291 0.079414 -0.123886 \n",
"292 -0.233586 0.178114 \n",
"293 0.100414 0.068114 \n",
"294 -0.021586 0.082114 \n",
"295 -0.041586 -0.318886 \n",
"296 -0.159586 0.087114 \n",
"\n",
" lh_caudalmiddlefrontal_part3 lh_caudalmiddlefrontal_part4 \\\n",
"0 -0.005168 -0.252694 \n",
"1 0.445832 0.390306 \n",
"2 0.187832 0.576306 \n",
"3 -0.154168 -0.156694 \n",
"4 -0.142168 -0.752694 \n",
"5 -0.110168 -0.142694 \n",
"6 0.017832 -0.037694 \n",
"7 0.068832 -0.017694 \n",
"8 -0.091168 0.210306 \n",
"9 0.180832 0.123306 \n",
"10 0.005832 -0.419694 \n",
"11 0.206832 0.154306 \n",
"12 0.234832 0.018306 \n",
"13 -0.502168 -0.108694 \n",
"14 -0.089168 0.032306 \n",
"15 -0.026168 -0.145694 \n",
"16 -0.168168 -0.124694 \n",
"17 -0.139168 -0.103694 \n",
"18 0.145832 -0.091694 \n",
"19 0.023832 0.103306 \n",
"20 -0.296168 -0.231694 \n",
"21 -0.320168 0.036306 \n",
"22 -0.083168 0.164306 \n",
"23 0.122832 0.139306 \n",
"24 0.127832 0.332306 \n",
"25 0.275832 0.115306 \n",
"26 0.348832 0.333306 \n",
"27 -0.089168 0.300306 \n",
"28 0.071832 -0.251694 \n",
"29 0.035832 0.131306 \n",
".. ... ... \n",
"267 -0.302168 -0.239694 \n",
"268 -0.309168 -0.170694 \n",
"269 0.097832 -0.164694 \n",
"270 0.109832 0.233306 \n",
"271 0.023832 0.040306 \n",
"272 -0.074168 -0.299694 \n",
"273 0.143832 0.033306 \n",
"274 0.060832 0.243306 \n",
"275 0.015832 0.017306 \n",
"276 -0.137168 -0.176694 \n",
"277 0.092832 -0.158694 \n",
"278 -0.216168 0.078306 \n",
"279 -0.052168 0.001306 \n",
"280 -0.075168 -0.051694 \n",
"281 0.103832 -0.140694 \n",
"282 0.197832 -0.060694 \n",
"283 -0.201168 -0.061694 \n",
"284 -0.258168 -0.495694 \n",
"285 -0.364168 -0.040694 \n",
"286 -0.143168 -0.025694 \n",
"287 -0.001168 0.083306 \n",
"288 0.235832 -0.101694 \n",
"289 -0.134168 -0.152694 \n",
"290 -0.099168 0.142306 \n",
"291 0.224832 0.018306 \n",
"292 -0.049168 -0.103694 \n",
"293 -0.174168 -0.113694 \n",
"294 -0.131168 -0.339694 \n",
"295 -0.093168 -0.199694 \n",
"296 -0.107168 -0.191694 \n",
"\n",
" lh_cuneus_part1 lh_cuneus_part2 lh_entorhinal_part1 ... \\\n",
"0 -0.170037 -0.192492 -0.119414 ... \n",
"1 0.326963 0.389508 0.340586 ... \n",
"2 -0.061037 -0.062492 0.374586 ... \n",
"3 0.029963 -0.246492 -0.009414 ... \n",
"4 -0.091037 -0.550492 -1.223414 ... \n",
"5 0.146963 -0.047492 0.155586 ... \n",
"6 0.061963 0.028508 -0.214414 ... \n",
"7 0.120963 0.095508 0.333586 ... \n",
"8 -0.105037 0.009508 0.388586 ... \n",
"9 -0.062037 -0.180492 -0.323414 ... \n",
"10 0.348963 0.232508 -0.997414 ... \n",
"11 0.020963 -0.053492 0.004586 ... \n",
"12 0.026963 0.090508 0.301586 ... \n",
"13 0.127963 -0.104492 -0.043414 ... \n",
"14 0.180963 0.287508 -0.422414 ... \n",
"15 0.209963 -0.070492 -0.518414 ... \n",
"16 -0.312037 -0.035492 0.112586 ... \n",
"17 -0.004037 0.076508 0.069586 ... \n",
"18 0.002963 0.038508 0.231586 ... \n",
"19 -0.278037 0.053508 0.236586 ... \n",
"20 -0.080037 -0.212492 -0.596414 ... \n",
"21 0.103963 0.198508 -0.637414 ... \n",
"22 0.311963 0.240508 -0.716414 ... \n",
"23 0.166963 0.033508 0.176586 ... \n",
"24 0.005963 0.178508 -0.394414 ... \n",
"25 0.185963 0.222508 0.053586 ... \n",
"26 0.214963 0.120508 0.118586 ... \n",
"27 0.156963 0.088508 0.425586 ... \n",
"28 -0.172037 -0.109492 0.553586 ... \n",
"29 -0.108037 0.029508 0.241586 ... \n",
".. ... ... ... ... \n",
"267 -0.234037 -0.143492 -0.014414 ... \n",
"268 -0.136037 -0.316492 -0.344414 ... \n",
"269 -0.214037 -0.363492 0.059586 ... \n",
"270 -0.187037 -0.090492 -0.414414 ... \n",
"271 -0.314037 -0.106492 -0.014414 ... \n",
"272 -0.113037 -0.417492 0.117586 ... \n",
"273 -0.118037 -0.057492 -0.447414 ... \n",
"274 0.269963 0.017508 -0.211414 ... \n",
"275 0.164963 0.092508 0.136586 ... \n",
"276 -0.029037 -0.158492 -1.103414 ... \n",
"277 0.042963 -0.052492 0.311586 ... \n",
"278 -0.119037 0.026508 0.500586 ... \n",
"279 -0.256037 -0.088492 -0.018414 ... \n",
"280 -0.072037 0.161508 -0.070414 ... \n",
"281 -0.201037 -0.285492 -0.566414 ... \n",
"282 0.071963 0.272508 0.086586 ... \n",
"283 -0.185037 -0.128492 -0.393414 ... \n",
"284 -0.088037 -0.003492 -0.279414 ... \n",
"285 -0.165037 -0.418492 -0.879414 ... \n",
"286 -0.127037 0.317508 -0.432414 ... \n",
"287 -0.012037 -0.007492 -0.286414 ... \n",
"288 0.177963 0.338508 0.024586 ... \n",
"289 -0.034037 -0.011492 0.174586 ... \n",
"290 -0.432037 -0.274492 0.156586 ... \n",
"291 0.144963 0.000508 0.409586 ... \n",
"292 0.024963 0.088508 -0.169414 ... \n",
"293 0.013963 0.121508 -0.030414 ... \n",
"294 -0.174037 -0.332492 0.478586 ... \n",
"295 0.185963 -0.272492 0.304586 ... \n",
"296 0.220963 -0.106492 -0.066414 ... \n",
"\n",
" rh_supramarginal_part5 rh_supramarginal_part6 rh_supramarginal_part7 \\\n",
"0 -0.421125 -0.123926 -0.37903 \n",
"1 0.434875 0.318074 0.04297 \n",
"2 0.512875 0.304074 0.37897 \n",
"3 -0.183125 -0.047926 -0.05003 \n",
"4 -0.324125 0.329074 0.12297 \n",
"5 -0.097125 -0.074926 -0.12803 \n",
"6 0.080875 0.027074 0.00797 \n",
"7 0.427875 0.134074 0.25697 \n",
"8 0.103875 0.182074 0.31697 \n",
"9 -0.197125 -0.022926 -0.17103 \n",
"10 -0.463125 0.153074 0.01097 \n",
"11 0.149875 -0.113926 -0.11203 \n",
"12 0.102875 0.059074 -0.05203 \n",
"13 0.634875 0.150074 0.30797 \n",
"14 -0.086125 -0.217926 -0.06003 \n",
"15 0.266875 0.019074 -0.21203 \n",
"16 0.056875 -0.091926 -0.03103 \n",
"17 -0.157125 -0.117926 0.03697 \n",
"18 0.261875 0.341074 0.20797 \n",
"19 -0.003125 0.033074 -0.08003 \n",
"20 0.255875 -0.167926 -0.18103 \n",
"21 -0.242125 -0.060926 -0.35703 \n",
"22 0.374875 0.073074 -0.16303 \n",
"23 0.321875 0.009074 -0.23003 \n",
"24 0.356875 0.079074 0.10597 \n",
"25 -0.141125 0.200074 -0.05003 \n",
"26 0.263875 0.127074 0.17397 \n",
"27 -0.098125 0.280074 0.28197 \n",
"28 -0.119125 0.094074 0.13297 \n",
"29 0.008875 -0.023926 -0.34803 \n",
".. ... ... ... \n",
"267 -0.118125 -0.104926 -0.22403 \n",
"268 0.110875 -0.069926 -0.21103 \n",
"269 -0.299125 -0.240926 -0.48403 \n",
"270 0.089875 -0.149926 0.09397 \n",
"271 -0.155125 -0.173926 -0.16003 \n",
"272 -0.390125 -0.220926 -0.15603 \n",
"273 -0.160125 -0.059926 -0.21903 \n",
"274 0.078875 -0.030926 -0.10203 \n",
"275 0.151875 -0.044926 0.03697 \n",
"276 -0.183125 -0.317926 -0.23103 \n",
"277 -0.040125 -0.144926 0.04497 \n",
"278 0.208875 -0.269926 -0.07503 \n",
"279 -0.179125 0.056074 -0.25603 \n",
"280 0.193875 -0.043926 -0.00603 \n",
"281 0.021875 -0.259926 -0.06303 \n",
"282 -0.065125 -0.018926 -0.05403 \n",
"283 0.182875 0.455074 0.07497 \n",
"284 -0.426125 -0.618926 -0.58403 \n",
"285 0.286875 0.135074 -0.15703 \n",
"286 0.125875 -0.206926 -0.10503 \n",
"287 0.049875 0.157074 -0.14303 \n",
"288 -0.163125 0.239074 -0.00603 \n",
"289 0.039875 -0.199926 -0.02903 \n",
"290 -0.027125 -0.110926 -0.17803 \n",
"291 -0.114125 0.290074 -0.06003 \n",
"292 -0.417125 -0.198926 0.01897 \n",
"293 0.227875 -0.383926 -0.02703 \n",
"294 0.329875 0.022074 0.23197 \n",
"295 -0.215125 -0.466926 0.03697 \n",
"296 -0.022125 0.280074 0.14397 \n",
"\n",
" rh_frontalpole_part1 rh_temporalpole_part1 rh_transversetemporal_part1 \\\n",
"0 -0.436609 -0.143411 -0.103404 \n",
"1 0.302391 0.374589 0.298596 \n",
"2 0.210391 0.230589 0.172596 \n",
"3 -0.126609 -0.268411 0.303596 \n",
"4 -0.383609 -1.518411 -0.007404 \n",
"5 -0.114609 -0.241411 0.209596 \n",
"6 -0.067609 0.310589 -0.107404 \n",
"7 -0.229609 -0.214411 0.329596 \n",
"8 -0.083609 0.176589 0.062596 \n",
"9 0.527391 0.004589 0.123596 \n",
"10 -0.540609 -0.149411 0.290596 \n",
"11 0.015391 0.233589 0.134596 \n",
"12 0.061391 -0.193411 0.127596 \n",
"13 0.413391 -0.463411 0.388596 \n",
"14 0.198391 0.171589 0.026596 \n",
"15 0.296391 -0.047411 -0.364404 \n",
"16 0.301391 0.392589 0.115596 \n",
"17 -0.286609 0.243589 0.162596 \n",
"18 0.031391 0.052589 -0.204404 \n",
"19 -0.083609 0.069589 0.085596 \n",
"20 0.095391 -0.579411 -0.360404 \n",
"21 -0.273609 -0.645411 -0.026404 \n",
"22 0.303391 0.011589 0.207596 \n",
"23 0.320391 0.749589 0.300596 \n",
"24 0.071391 -1.264411 0.001596 \n",
"25 0.162391 0.155589 -0.153404 \n",
"26 0.191391 0.249589 0.214596 \n",
"27 0.000391 0.808589 0.006596 \n",
"28 -0.610609 -0.063411 0.001596 \n",
"29 -0.158609 0.240589 -0.392404 \n",
".. ... ... ... \n",
"267 -0.305609 -0.048411 -0.260404 \n",
"268 -0.029609 -0.027411 -0.401404 \n",
"269 -0.392609 -0.081411 -0.217404 \n",
"270 0.096391 -0.332411 -0.022404 \n",
"271 0.053391 0.091589 0.107596 \n",
"272 -0.479609 -0.070411 -0.258404 \n",
"273 -0.042609 -0.973411 -0.063404 \n",
"274 -0.002609 0.377589 0.035596 \n",
"275 -0.131609 0.205589 0.024596 \n",
"276 -0.011609 -0.146411 -0.106404 \n",
"277 -0.074609 0.241589 -0.098404 \n",
"278 0.109391 0.752589 -0.303404 \n",
"279 -0.312609 0.540589 -0.281404 \n",
"280 -0.025609 0.129589 0.148596 \n",
"281 -0.563609 -0.486411 -0.403404 \n",
"282 -0.079609 -0.345411 0.003596 \n",
"283 -0.132609 -0.289411 -0.127404 \n",
"284 -0.095609 0.234589 0.208596 \n",
"285 -0.095609 -0.683411 0.179596 \n",
"286 -0.109609 -0.489411 0.110596 \n",
"287 0.171391 0.224589 -0.221404 \n",
"288 0.187391 0.066589 0.212596 \n",
"289 -0.080609 0.426589 -0.293404 \n",
"290 0.067391 0.109589 -0.089404 \n",
"291 -0.331609 0.194589 0.309596 \n",
"292 0.430391 0.005589 0.126596 \n",
"293 0.099391 -0.410411 -0.010404 \n",
"294 -0.335609 0.068589 -0.007404 \n",
"295 0.109391 -0.486411 -0.272404 \n",
"296 0.225391 0.312589 0.366596 \n",
"\n",
" rh_insula_part1 rh_insula_part2 rh_insula_part3 rh_insula_part4 \n",
"0 -0.321707 -0.159219 -0.19032 -0.393141 \n",
"1 0.237293 0.200781 0.09968 0.126859 \n",
"2 0.264293 0.155781 0.34168 0.097859 \n",
"3 -0.491707 -0.003219 -0.54532 -0.133141 \n",
"4 -0.838707 0.192781 0.15968 -0.079141 \n",
"5 0.326293 0.082781 0.26868 0.099859 \n",
"6 -0.033707 -0.015219 -0.09132 0.048859 \n",
"7 -0.355707 0.015781 -0.02732 -0.118141 \n",
"8 0.404293 0.024781 -0.05932 0.041859 \n",
"9 0.413293 -0.185219 -0.21632 0.065859 \n",
"10 -0.078707 0.073781 0.30068 0.333859 \n",
"11 -0.206707 -0.039219 -0.35132 0.220859 \n",
"12 0.292293 -0.027219 0.22968 0.481859 \n",
"13 0.216293 0.074781 0.23568 0.192859 \n",
"14 0.124293 0.050781 -0.02332 -0.113141 \n",
"15 -0.380707 0.210781 0.23068 0.030859 \n",
"16 0.027293 0.234781 0.11168 0.111859 \n",
"17 0.045293 0.148781 0.22168 0.050859 \n",
"18 0.224293 -0.111219 -0.08532 0.079859 \n",
"19 0.416293 -0.049219 0.27268 0.344859 \n",
"20 0.013293 -0.129219 -0.25632 0.101859 \n",
"21 -0.240707 0.046781 0.16268 0.029859 \n",
"22 0.238293 0.056781 -0.27732 0.288859 \n",
"23 0.069293 0.103781 0.02568 -0.048141 \n",
"24 -0.204707 -0.084219 -0.05932 -0.320141 \n",
"25 0.403293 0.026781 0.33068 0.282859 \n",
"26 0.029293 0.233781 0.14168 0.342859 \n",
"27 -0.036707 0.331781 0.16468 -0.137141 \n",
"28 0.141293 0.106781 0.47968 0.154859 \n",
"29 0.222293 -0.063219 -0.24132 -0.042141 \n",
".. ... ... ... ... \n",
"267 -0.130707 -0.320219 -0.17832 -0.153141 \n",
"268 -0.151707 0.014781 0.04168 -0.192141 \n",
"269 -0.334707 -0.190219 0.18768 0.153859 \n",
"270 0.040293 0.066781 0.14768 0.005859 \n",
"271 0.312293 0.226781 -0.02432 -0.068141 \n",
"272 -0.035707 -0.082219 -0.24732 -0.106141 \n",
"273 -0.117707 0.005781 0.16668 -0.132141 \n",
"274 -0.297707 0.018781 -0.00032 0.275859 \n",
"275 0.012293 -0.011219 -0.04732 0.044859 \n",
"276 -0.307707 -0.149219 -0.46132 -0.449141 \n",
"277 0.155293 -0.269219 -0.11532 0.224859 \n",
"278 -0.075707 -0.149219 -0.27532 -0.155141 \n",
"279 0.288293 -0.092219 -0.17332 0.202859 \n",
"280 -0.181707 -0.166219 0.11968 0.239859 \n",
"281 0.208293 -0.200219 -0.38132 -0.004141 \n",
"282 0.190293 0.157781 -0.07332 -0.016141 \n",
"283 0.108293 -0.408219 -0.02232 -0.117141 \n",
"284 -0.040707 -0.310219 0.08468 -0.363141 \n",
"285 -0.602707 -0.162219 -0.05432 -0.057141 \n",
"286 0.186293 -0.040219 -0.09332 0.113859 \n",
"287 0.475293 -0.159219 -0.05332 -0.012141 \n",
"288 -0.525707 0.003781 0.26568 -0.061141 \n",
"289 -0.201707 -0.118219 -0.17732 -0.079141 \n",
"290 -0.283707 -0.212219 -0.07232 0.050859 \n",
"291 -0.296707 0.559781 0.36268 -0.069141 \n",
"292 0.327293 0.250781 0.18468 0.247859 \n",
"293 -0.075707 0.181781 0.29768 0.126859 \n",
"294 0.165293 0.018781 -0.20932 0.309859 \n",
"295 -0.329707 -0.204219 0.12468 -0.165141 \n",
"296 0.028293 0.178781 0.47468 -0.205141 \n",
"\n",
"[297 rows x 308 columns]"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_res"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now we create a correlation matrix over the columns of df_res"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": true,
"scrolled": false
},
"outputs": [],
"source": [
"M = scn.create_corrmat(df_res, method='pearson')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Create a weighted graph\n",
"\n",
"A short sidenote on the BrainNetwork class: This is a very lightweight subclass of the [`Networkx.Graph`](https://networkx.github.io/documentation/stable/reference/classes/graph.html) class. This means that any methods you can use on a `Networkx.Graph` object can also be used on a `BrainNetwork` object, although the reverse is not true. We have added various methods which allow us to keep track of measures that have already been calculated, which, especially later on when one is dealing with 10^3 random graphs, saves a lot of time. \n",
"All scona measures are implemented in such a way that they can be used on a regular `Networkx.Graph` object. For example, instead of `G.threshold(10)` you can use `scn.threshold_graph(G, 10)`. \n",
"Also you can create a `BrainNetwork` from a `Networkx.Graph` `G`, using `scn.BrainNetwork(network=G)`"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Initialise a weighted graph `G` from the correlation matrix `M`. The `parcellation` and `centroids` arguments are used to label nodes with names and coordinates respectively. "
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"G = scn.BrainNetwork(network=M, parcellation=names, centroids=centroids)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Threshold to create a binary graph\n",
"\n",
"We threshold G at cost 10 to create a binary graph with 10% as many edges as the complete graph G. Ordinarily when thresholding one takes the 10% of edges with the highest weight. In our case, because we want the resulting graph to be connected, we calculate a minimum spanning tree first. If you want to omit this step, you can pass the argument `mst=False` to `threshold`.\n",
"The threshold method does not edit objects inplace"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"H = G.threshold(10)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Calculate nodal summary. \n",
"\n",
"`calculate_nodal_measures` will compute and record the following nodal measures \n",
"\n",
"* average_dist (if centroids available)\n",
"* total_dist (if centroids available)\n",
"* betweenness\n",
"* closeness\n",
"* clustering coefficient\n",
"* degree\n",
"* interhem (if centroids are available)\n",
"* interhem_proportion (if centroids are available)\n",
"* nodal partition\n",
"* participation coefficient under partition calculated above\n",
"* shortest_path_length"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"`export_nodal_measure` returns nodal attributes in a DataFrame. Let's try it now."
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
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" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>centroids</th>\n",
" <th>name</th>\n",
" <th>x</th>\n",
" <th>y</th>\n",
" <th>z</th>\n",
" </tr>\n",
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" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>[-27.965157, -19.013702, 17.919528]</td>\n",
" <td>lh_bankssts_part1</td>\n",
" <td>-27.9652</td>\n",
" <td>-19.0137</td>\n",
" <td>17.9195</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>[-14.455663, -13.693461, 13.713674]</td>\n",
" <td>lh_bankssts_part2</td>\n",
" <td>-14.4557</td>\n",
" <td>-13.6935</td>\n",
" <td>13.7137</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>[-33.906934, -22.284672, -15.821168]</td>\n",
" <td>lh_caudalanteriorcingulate_part1</td>\n",
" <td>-33.9069</td>\n",
" <td>-22.2847</td>\n",
" <td>-15.8212</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>[-17.305373, -53.431573, -36.017154]</td>\n",
" <td>lh_caudalmiddlefrontal_part1</td>\n",
" <td>-17.3054</td>\n",
" <td>-53.4316</td>\n",
" <td>-36.0172</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>[-22.265823, -64.366296, -37.674831]</td>\n",
" <td>lh_caudalmiddlefrontal_part2</td>\n",
" <td>-22.2658</td>\n",
" <td>-64.3663</td>\n",
" <td>-37.6748</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" centroids name \\\n",
"0 [-27.965157, -19.013702, 17.919528] lh_bankssts_part1 \n",
"1 [-14.455663, -13.693461, 13.713674] lh_bankssts_part2 \n",
"2 [-33.906934, -22.284672, -15.821168] lh_caudalanteriorcingulate_part1 \n",
"3 [-17.305373, -53.431573, -36.017154] lh_caudalmiddlefrontal_part1 \n",
"4 [-22.265823, -64.366296, -37.674831] lh_caudalmiddlefrontal_part2 \n",
"\n",
" x y z \n",
"0 -27.9652 -19.0137 17.9195 \n",
"1 -14.4557 -13.6935 13.7137 \n",
"2 -33.9069 -22.2847 -15.8212 \n",
"3 -17.3054 -53.4316 -36.0172 \n",
"4 -22.2658 -64.3663 -37.6748 "
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"H.report_nodal_measures().head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Use `calculate_nodal_measures` to fill in a bunch of nodal measures"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" Calculating participation coefficient - may take a little while\n"
]
}
],
"source": [
"H.calculate_nodal_measures()"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"text/html": [
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"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>betweenness</th>\n",
" <th>centroids</th>\n",
" <th>closeness</th>\n",
" <th>clustering</th>\n",
" <th>degree</th>\n",
" <th>module</th>\n",
" <th>name</th>\n",
" <th>participation_coefficient</th>\n",
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" <th>y</th>\n",
" <th>z</th>\n",
" </tr>\n",
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" <tr>\n",
" <th>0</th>\n",
" <td>0.00824713</td>\n",
" <td>[-27.965157, -19.013702, 17.919528]</td>\n",
" <td>0.495961</td>\n",
" <td>0.3358</td>\n",
" <td>47</td>\n",
" <td>0</td>\n",
" <td>lh_bankssts_part1</td>\n",
" <td>0.717067</td>\n",
" <td>0.00824713</td>\n",
" <td>-27.9652</td>\n",
" <td>-19.0137</td>\n",
" <td>17.9195</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>0.0124798</td>\n",
" <td>[-14.455663, -13.693461, 13.713674]</td>\n",
" <td>0.507438</td>\n",
" <td>0.278788</td>\n",
" <td>55</td>\n",
" <td>0</td>\n",
" <td>lh_bankssts_part2</td>\n",
" <td>0.809587</td>\n",
" <td>0.0124798</td>\n",
" <td>-14.4557</td>\n",
" <td>-13.6935</td>\n",
" <td>13.7137</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>0</td>\n",
" <td>[-33.906934, -22.284672, -15.821168]</td>\n",
" <td>0.336254</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>lh_caudalanteriorcingulate_part1</td>\n",
" <td>0.75</td>\n",
" <td>0</td>\n",
" <td>-33.9069</td>\n",
" <td>-22.2847</td>\n",
" <td>-15.8212</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>0.0120765</td>\n",
" <td>[-17.305373, -53.431573, -36.017154]</td>\n",
" <td>0.525685</td>\n",
" <td>0.383485</td>\n",
" <td>83</td>\n",
" <td>2</td>\n",
" <td>lh_caudalmiddlefrontal_part1</td>\n",
" <td>0.459864</td>\n",
" <td>0.0120765</td>\n",
" <td>-17.3054</td>\n",
" <td>-53.4316</td>\n",
" <td>-36.0172</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>0.0292617</td>\n",
" <td>[-22.265823, -64.366296, -37.674831]</td>\n",
" <td>0.549195</td>\n",
" <td>0.293617</td>\n",
" <td>95</td>\n",
" <td>2</td>\n",
" <td>lh_caudalmiddlefrontal_part2</td>\n",
" <td>0.688753</td>\n",
" <td>0.0292617</td>\n",
" <td>-22.2658</td>\n",
" <td>-64.3663</td>\n",
" <td>-37.6748</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" betweenness centroids closeness clustering \\\n",
"0 0.00824713 [-27.965157, -19.013702, 17.919528] 0.495961 0.3358 \n",
"1 0.0124798 [-14.455663, -13.693461, 13.713674] 0.507438 0.278788 \n",
"2 0 [-33.906934, -22.284672, -15.821168] 0.336254 1 \n",
"3 0.0120765 [-17.305373, -53.431573, -36.017154] 0.525685 0.383485 \n",
"4 0.0292617 [-22.265823, -64.366296, -37.674831] 0.549195 0.293617 \n",
"\n",
" degree module name participation_coefficient \\\n",
"0 47 0 lh_bankssts_part1 0.717067 \n",
"1 55 0 lh_bankssts_part2 0.809587 \n",
"2 2 1 lh_caudalanteriorcingulate_part1 0.75 \n",
"3 83 2 lh_caudalmiddlefrontal_part1 0.459864 \n",
"4 95 2 lh_caudalmiddlefrontal_part2 0.688753 \n",
"\n",
" shortest_path_length x y z \n",
"0 0.00824713 -27.9652 -19.0137 17.9195 \n",
"1 0.0124798 -14.4557 -13.6935 13.7137 \n",
"2 0 -33.9069 -22.2847 -15.8212 \n",
"3 0.0120765 -17.3054 -53.4316 -36.0172 \n",
"4 0.0292617 -22.2658 -64.3663 -37.6748 "
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"H.report_nodal_measures().head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can also add measures as one might normally add nodal attributes to a networkx graph"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"nx.set_node_attributes(H, name=\"hat\", values={x: x**2 for x in H.nodes})"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"These show up in our DataFrame too"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
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"\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>degree</th>\n",
" <th>hat</th>\n",
" <th>name</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>47</td>\n",
" <td>0</td>\n",
" <td>lh_bankssts_part1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>55</td>\n",
" <td>1</td>\n",
" <td>lh_bankssts_part2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2</td>\n",
" <td>4</td>\n",
" <td>lh_caudalanteriorcingulate_part1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>83</td>\n",
" <td>9</td>\n",
" <td>lh_caudalmiddlefrontal_part1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>95</td>\n",
" <td>16</td>\n",
" <td>lh_caudalmiddlefrontal_part2</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" degree hat name\n",
"0 47 0 lh_bankssts_part1\n",
"1 55 1 lh_bankssts_part2\n",
"2 2 4 lh_caudalanteriorcingulate_part1\n",
"3 83 9 lh_caudalmiddlefrontal_part1\n",
"4 95 16 lh_caudalmiddlefrontal_part2"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"H.report_nodal_measures(columns=['name', 'degree', 'hat']).head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Calculate Global measures"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'assortativity': 0.09076922258276784,\n",
" 'average_clustering': 0.4498887255891581,\n",
" 'average_shortest_path_length': 2.376242649858285,\n",
" 'efficiency': 0.47983958611582617,\n",
" 'modularity': 0.3828553111606414}"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"H.calculate_global_measures()"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"scrolled": false
},
"outputs": [],
"source": [
"H.rich_club();"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Create a GraphBundle\n",
"\n",
"The `GraphBundle` object is the scona way to handle across network comparisons. What is it? Essentially it's a python dictionary with `BrainNetwork` objects as values. "
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"brain_bundle = scn.GraphBundle([H], ['NSPN_cost=10'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This creates a dictionary-like object with BrainNetwork `H` keyed by `'NSPN_cost=10'`"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"{'NSPN_cost=10': <scona.classes.BrainNetwork at 0x7f3f247f6fd0>}"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"brain_bundle"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now add a series of random_graphs created by edge swap randomisation of H (keyed by `'NSPN_cost=10'`)"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" Creating 10 random graphs - may take a little while\n"
]
}
],
"source": [
"# Note that 10 is not usually a sufficient number of random graphs to do meaningful analysis,\n",
"# it is used here for time considerations\n",
"brain_bundle.create_random_graphs('NSPN_cost=10', 10)"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'NSPN_cost=10': <scona.classes.BrainNetwork at 0x7f3f247f6fd0>,\n",
" 'NSPN_cost=10_R1': <scona.classes.BrainNetwork at 0x7f3f138b7f28>,\n",
" 'NSPN_cost=10_R10': <scona.classes.BrainNetwork at 0x7f3f134b8828>,\n",
" 'NSPN_cost=10_R2': <scona.classes.BrainNetwork at 0x7f3f138b7e80>,\n",
" 'NSPN_cost=10_R3': <scona.classes.BrainNetwork at 0x7f3f138b7780>,\n",
" 'NSPN_cost=10_R4': <scona.classes.BrainNetwork at 0x7f3f138b7da0>,\n",
" 'NSPN_cost=10_R5': <scona.classes.BrainNetwork at 0x7f3f1388ae10>,\n",
" 'NSPN_cost=10_R6': <scona.classes.BrainNetwork at 0x7f3f134b8a58>,\n",
" 'NSPN_cost=10_R7': <scona.classes.BrainNetwork at 0x7f3f134b84a8>,\n",
" 'NSPN_cost=10_R8': <scona.classes.BrainNetwork at 0x7f3f134b8390>,\n",
" 'NSPN_cost=10_R9': <scona.classes.BrainNetwork at 0x7f3f134b83c8>}"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"brain_bundle"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Report on a GraphBundle\n",
"\n",
"The following method will calculate global measures ( if they have not already been calculated) for all of the graphs in `graph_bundle` and report the results in a DataFrame. We can do the same for rich club coefficients below."
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: top;\n",
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"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>assortativity</th>\n",
" <th>average_clustering</th>\n",
" <th>average_shortest_path_length</th>\n",
" <th>efficiency</th>\n",
" <th>modularity</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>NSPN_cost=10</th>\n",
" <td>0.090769</td>\n",
" <td>0.449889</td>\n",
" <td>2.376243</td>\n",
" <td>0.479840</td>\n",
" <td>0.382855</td>\n",
" </tr>\n",
" <tr>\n",
" <th>NSPN_cost=10_R1</th>\n",
" <td>-0.083993</td>\n",
" <td>0.222571</td>\n",
" <td>2.086721</td>\n",
" <td>0.519147</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>NSPN_cost=10_R10</th>\n",
" <td>-0.087652</td>\n",
" <td>0.222462</td>\n",
" <td>2.087821</td>\n",
" <td>0.518918</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>NSPN_cost=10_R2</th>\n",
" <td>-0.080897</td>\n",
" <td>0.230384</td>\n",
" <td>2.090423</td>\n",
" <td>0.518615</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>NSPN_cost=10_R3</th>\n",
" <td>-0.102626</td>\n",
" <td>0.221894</td>\n",
" <td>2.082745</td>\n",
" <td>0.519803</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>NSPN_cost=10_R4</th>\n",
" <td>-0.072122</td>\n",
" <td>0.221924</td>\n",
" <td>2.087842</td>\n",
" <td>0.518902</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>NSPN_cost=10_R5</th>\n",
" <td>-0.086952</td>\n",
" <td>0.232706</td>\n",
" <td>2.084754</td>\n",
" <td>0.519357</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>NSPN_cost=10_R6</th>\n",
" <td>-0.084438</td>\n",
" <td>0.223727</td>\n",
" <td>2.085325</td>\n",
" <td>0.519440</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>NSPN_cost=10_R7</th>\n",
" <td>-0.080285</td>\n",
" <td>0.224930</td>\n",
" <td>2.087525</td>\n",
" <td>0.519003</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>NSPN_cost=10_R8</th>\n",
" <td>-0.070332</td>\n",
" <td>0.225730</td>\n",
" <td>2.085135</td>\n",
" <td>0.519281</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>NSPN_cost=10_R9</th>\n",
" <td>-0.086510</td>\n",
" <td>0.227159</td>\n",
" <td>2.090782</td>\n",
" <td>0.518527</td>\n",
" <td>0.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" assortativity average_clustering \\\n",
"NSPN_cost=10 0.090769 0.449889 \n",
"NSPN_cost=10_R1 -0.083993 0.222571 \n",
"NSPN_cost=10_R10 -0.087652 0.222462 \n",
"NSPN_cost=10_R2 -0.080897 0.230384 \n",
"NSPN_cost=10_R3 -0.102626 0.221894 \n",
"NSPN_cost=10_R4 -0.072122 0.221924 \n",
"NSPN_cost=10_R5 -0.086952 0.232706 \n",
"NSPN_cost=10_R6 -0.084438 0.223727 \n",
"NSPN_cost=10_R7 -0.080285 0.224930 \n",
"NSPN_cost=10_R8 -0.070332 0.225730 \n",
"NSPN_cost=10_R9 -0.086510 0.227159 \n",
"\n",
" average_shortest_path_length efficiency modularity \n",
"NSPN_cost=10 2.376243 0.479840 0.382855 \n",
"NSPN_cost=10_R1 2.086721 0.519147 0.000000 \n",
"NSPN_cost=10_R10 2.087821 0.518918 0.000000 \n",
"NSPN_cost=10_R2 2.090423 0.518615 0.000000 \n",
"NSPN_cost=10_R3 2.082745 0.519803 0.000000 \n",
"NSPN_cost=10_R4 2.087842 0.518902 0.000000 \n",
"NSPN_cost=10_R5 2.084754 0.519357 0.000000 \n",
"NSPN_cost=10_R6 2.085325 0.519440 0.000000 \n",
"NSPN_cost=10_R7 2.087525 0.519003 0.000000 \n",
"NSPN_cost=10_R8 2.085135 0.519281 0.000000 \n",
"NSPN_cost=10_R9 2.090782 0.518527 0.000000 "
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"brain_bundle.report_global_measures()"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [
{
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],
"text/plain": [
" 0 1 2 3 4 5 \\\n",
"NSPN_cost=10 0.100004 0.103228 0.107244 0.112039 0.117842 0.122398 \n",
"NSPN_cost=10_R1 0.100004 0.103228 0.107175 0.111920 0.117564 0.121950 \n",
"NSPN_cost=10_R10 0.100004 0.103228 0.107175 0.111920 0.117564 0.121950 \n",
"NSPN_cost=10_R2 0.100004 0.103228 0.107175 0.111920 0.117564 0.121950 \n",
"NSPN_cost=10_R3 0.100004 0.103228 0.107175 0.111920 0.117589 0.122003 \n",
"NSPN_cost=10_R4 0.100004 0.103228 0.107175 0.111920 0.117564 0.121976 \n",
"NSPN_cost=10_R5 0.100004 0.103228 0.107175 0.111920 0.117564 0.121950 \n",
"NSPN_cost=10_R6 0.100004 0.103228 0.107175 0.111920 0.117564 0.121950 \n",
"NSPN_cost=10_R7 0.100004 0.103228 0.107175 0.111920 0.117564 0.121976 \n",
"NSPN_cost=10_R8 0.100004 0.103228 0.107175 0.111920 0.117564 0.121950 \n",
"NSPN_cost=10_R9 0.100004 0.103228 0.107175 0.111920 0.117564 0.121976 \n",
"\n",
" 6 7 8 9 ... 96 97 98 \\\n",
"NSPN_cost=10 0.127975 0.131899 0.136820 0.141069 ... 1.0 1.0 1.0 \n",
"NSPN_cost=10_R1 0.127226 0.131092 0.135825 0.139877 ... 1.0 1.0 1.0 \n",
"NSPN_cost=10_R10 0.127226 0.131150 0.135885 0.139908 ... 0.0 0.0 0.0 \n",
"NSPN_cost=10_R2 0.127226 0.131092 0.135855 0.139971 ... 1.0 1.0 1.0 \n",
"NSPN_cost=10_R3 0.127282 0.131150 0.135885 0.139940 ... 1.0 1.0 1.0 \n",
"NSPN_cost=10_R4 0.127282 0.131150 0.135885 0.139940 ... 1.0 1.0 1.0 \n",
"NSPN_cost=10_R5 0.127254 0.131150 0.135915 0.139940 ... 1.0 1.0 1.0 \n",
"NSPN_cost=10_R6 0.127226 0.131092 0.135885 0.139908 ... 1.0 1.0 1.0 \n",
"NSPN_cost=10_R7 0.127254 0.131150 0.135915 0.139971 ... 1.0 1.0 1.0 \n",
"NSPN_cost=10_R8 0.127226 0.131121 0.135915 0.139940 ... 1.0 1.0 1.0 \n",
"NSPN_cost=10_R9 0.127254 0.131150 0.135915 0.140034 ... 0.0 0.0 0.0 \n",
"\n",
" 99 100 101 102 103 104 105 \n",
"NSPN_cost=10 1.0 1.0 1.0 1.0 1.0 1.0 1.0 \n",
"NSPN_cost=10_R1 1.0 1.0 1.0 1.0 1.0 1.0 1.0 \n",
"NSPN_cost=10_R10 0.0 0.0 0.0 0.0 0.0 0.0 0.0 \n",
"NSPN_cost=10_R2 1.0 1.0 1.0 1.0 1.0 1.0 1.0 \n",
"NSPN_cost=10_R3 1.0 1.0 1.0 1.0 1.0 1.0 1.0 \n",
"NSPN_cost=10_R4 1.0 1.0 1.0 1.0 1.0 1.0 1.0 \n",
"NSPN_cost=10_R5 1.0 1.0 1.0 1.0 1.0 1.0 1.0 \n",
"NSPN_cost=10_R6 1.0 1.0 1.0 1.0 1.0 1.0 1.0 \n",
"NSPN_cost=10_R7 1.0 1.0 1.0 1.0 1.0 1.0 1.0 \n",
"NSPN_cost=10_R8 1.0 1.0 1.0 1.0 1.0 1.0 1.0 \n",
"NSPN_cost=10_R9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 \n",
"\n",
"[11 rows x 106 columns]"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"brain_bundle.report_rich_club()"
]
}
],
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
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"file_extension": ".py",
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"name": "python",
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