{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "--- This is a regression problem ---\n",
      "\n",
      "1. Loading dataset from file...\n",
      "\n",
      "2. Calculating gram matrices. This could take a while...\n",
      "\n",
      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 0.3643152713775635 seconds ---\n",
      "\n",
      "gram matrix with parameters {'height': 0.0} is: \n",
      "[[  5.   6.   4. ...  20.  20.  20.]\n",
      " [  6.   8.   4. ...  20.  20.  20.]\n",
      " [  4.   4.   5. ...  21.  21.  21.]\n",
      " ...\n",
      " [ 20.  20.  21. ... 101. 101. 101.]\n",
      " [ 20.  20.  21. ... 101. 101. 101.]\n",
      " [ 20.  20.  21. ... 101. 101. 101.]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9d47a3b0f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 0.8394806385040283 seconds ---\n",
      "\n",
      "gram matrix with parameters {'height': 1.0} is: \n",
      "[[ 10.  10.   4. ...  20.  20.  20.]\n",
      " [ 10.  16.   4. ...  20.  20.  20.]\n",
      " [  4.   4.  10. ...  22.  22.  24.]\n",
      " ...\n",
      " [ 20.  20.  22. ... 130. 130. 122.]\n",
      " [ 20.  20.  22. ... 130. 130. 122.]\n",
      " [ 20.  20.  24. ... 122. 122. 154.]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9d47a2efd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 1.3557612895965576 seconds ---\n",
      "\n",
      "gram matrix with parameters {'height': 2.0} is: \n",
      "[[ 15.   4.   0. ...   0.   0.   0.]\n",
      " [  4.  24.   0. ...   0.   0.   0.]\n",
      " [  0.   0.  15. ...   1.   1.   5.]\n",
      " ...\n",
      " [  0.   0.   1. ...  87.  58.  23.]\n",
      " [  0.   0.   1. ...  58.  67.  23.]\n",
      " [  0.   0.   5. ...  23.  23. 101.]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9d459b9320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 2.07392954826355 seconds ---\n",
      "\n",
      "gram matrix with parameters {'height': 3.0} is: \n",
      "[[ 20.   0.   0. ...   0.   0.   0.]\n",
      " [  0.  32.   0. ...   0.   0.   0.]\n",
      " [  0.   0.  20. ...   0.   0.   0.]\n",
      " ...\n",
      " [  0.   0.   0. ... 116.   8.   0.]\n",
      " [  0.   0.   0. ...   8.  60.   0.]\n",
      " [  0.   0.   0. ...   0.   0.  50.]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9d45945fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 2.4412496089935303 seconds ---\n",
      "\n",
      "gram matrix with parameters {'height': 4.0} is: \n",
      "[[ 25.   0.   0. ...   0.   0.   0.]\n",
      " [  0.  40.   0. ...   0.   0.   0.]\n",
      " [  0.   0.  25. ...   0.   0.   0.]\n",
      " ...\n",
      " [  0.   0.   0. ... 145.   0.   0.]\n",
      " [  0.   0.   0. ...   0.  75.   0.]\n",
      " [  0.   0.   0. ...   0.   0.  55.]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9d4595b780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 2.8024017810821533 seconds ---\n",
      "\n",
      "gram matrix with parameters {'height': 5.0} is: \n",
      "[[ 30.   0.   0. ...   0.   0.   0.]\n",
      " [  0.  48.   0. ...   0.   0.   0.]\n",
      " [  0.   0.  30. ...   0.   0.   0.]\n",
      " ...\n",
      " [  0.   0.   0. ... 174.   0.   0.]\n",
      " [  0.   0.   0. ...   0.  90.   0.]\n",
      " [  0.   0.   0. ...   0.   0.  66.]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9d45921cc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 3.4581663608551025 seconds ---\n",
      "\n",
      "gram matrix with parameters {'height': 6.0} is: \n",
      "[[ 35.   0.   0. ...   0.   0.   0.]\n",
      " [  0.  56.   0. ...   0.   0.   0.]\n",
      " [  0.   0.  35. ...   0.   0.   0.]\n",
      " ...\n",
      " [  0.   0.   0. ... 203.   0.   0.]\n",
      " [  0.   0.   0. ...   0. 105.   0.]\n",
      " [  0.   0.   0. ...   0.   0.  77.]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9d440d3710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 3.761540174484253 seconds ---\n",
      "\n",
      "gram matrix with parameters {'height': 7.0} is: \n",
      "[[ 40.   0.   0. ...   0.   0.   0.]\n",
      " [  0.  64.   0. ...   0.   0.   0.]\n",
      " [  0.   0.  40. ...   0.   0.   0.]\n",
      " ...\n",
      " [  0.   0.   0. ... 232.   0.   0.]\n",
      " [  0.   0.   0. ...   0. 120.   0.]\n",
      " [  0.   0.   0. ...   0.   0.  88.]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9d45901f28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 4.494075775146484 seconds ---\n",
      "\n",
      "gram matrix with parameters {'height': 8.0} is: \n",
      "[[ 45.   0.   0. ...   0.   0.   0.]\n",
      " [  0.  72.   0. ...   0.   0.   0.]\n",
      " [  0.   0.  45. ...   0.   0.   0.]\n",
      " ...\n",
      " [  0.   0.   0. ... 261.   0.   0.]\n",
      " [  0.   0.   0. ...   0. 135.   0.]\n",
      " [  0.   0.   0. ...   0.   0.  99.]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9d4595ba20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 4.6411638259887695 seconds ---\n",
      "\n",
      "gram matrix with parameters {'height': 9.0} is: \n",
      "[[ 50.   0.   0. ...   0.   0.   0.]\n",
      " [  0.  80.   0. ...   0.   0.   0.]\n",
      " [  0.   0.  50. ...   0.   0.   0.]\n",
      " ...\n",
      " [  0.   0.   0. ... 290.   0.   0.]\n",
      " [  0.   0.   0. ...   0. 150.   0.]\n",
      " [  0.   0.   0. ...   0.   0. 110.]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9d440d3278>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman subtree kernel matrix of size 183 built in 5.17179536819458 seconds ---\n",
      "\n",
      "gram matrix with parameters {'height': 10.0} is: \n",
      "[[ 55.   0.   0. ...   0.   0.   0.]\n",
      " [  0.  88.   0. ...   0.   0.   0.]\n",
      " [  0.   0.  55. ...   0.   0.   0.]\n",
      " ...\n",
      " [  0.   0.   0. ... 319.   0.   0.]\n",
      " [  0.   0.   0. ...   0. 165.   0.]\n",
      " [  0.   0.   0. ...   0.   0. 121.]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9d4591efd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "3. Fitting and predicting using nested cross validation. This could really take a while...\n",
      "calculate performance:   0%|          | 3/13530 [00:00<09:39, 23.34it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ljia/.local/lib/python3.5/site-packages/sklearn/linear_model/ridge.py:154: UserWarning: Singular matrix in solving dual problem. Using least-squares solution instead.\n",
      "  warnings.warn(\"Singular matrix in solving dual problem. Using \"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                                                            \n",
      "4. Getting final performances...\n",
      "\n",
      "best_params_out:  [{'height': 1.0}]\n",
      "best_params_in:  [{'alpha': 0.12589254117941676}]\n",
      "best_val_perf:  7.593412392539851\n",
      "best_val_std:  0.7111794979520709\n",
      "final_performance:  7.923917693852004\n",
      "final_confidence:  2.919445947208125\n",
      "train_performance:  5.9954331001158705\n",
      "train_std:  0.26528917359193244\n",
      "time to calculate gram matrix:  0.8394806385040283 s\n",
      "\n",
      "params                                 train_perf         valid_perf               test_perf                gram_matrix_time\n",
      "-------------------------------------  -----------------  -----------------------  ---------------------  ------------------\n",
      "{'alpha': '1.00e-02', 'height': 0.0}   16.78±0.34         16.85±0.38               17.37±2.96                           0.36\n",
      "{'alpha': '1.00e-02', 'height': 1.0}   5.93±0.30          7.91±0.84                8.40±3.39                            0.84\n",
      "{'alpha': '1.00e-02', 'height': 2.0}   451.39±1422.80     2033.21±3426.97          13378.54±63943.34                    1.36\n",
      "{'alpha': '1.00e-02', 'height': 3.0}   13217.28±19076.04  261279.62±289350.01      437442.31±862782.28                  2.07\n",
      "{'alpha': '1.00e-02', 'height': 4.0}   10671.89±29293.73  21335653.32±64894754.82  4989479.40±9290521.80                2.44\n",
      "{'alpha': '1.00e-02', 'height': 5.0}   94.09±3.28         407296.40±47673.76       444502.94±272049.80                  2.8\n",
      "{'alpha': '1.00e-02', 'height': 6.0}   93.91±3.15         486340.54±58427.24       459992.03±280235.03                  3.46\n",
      "{'alpha': '1.00e-02', 'height': 7.0}   93.94±2.67         520804.91±75722.08       657807.23±404298.33                  3.76\n",
      "{'alpha': '1.00e-02', 'height': 8.0}   94.22±2.73         625727.59±61899.85       569481.82±335243.00                  4.49\n",
      "{'alpha': '1.00e-02', 'height': 9.0}   94.30±3.66         687051.15±78936.05       667719.96±446436.72                  4.64\n",
      "{'alpha': '1.00e-02', 'height': 10.0}  94.41±2.97         762435.00±95172.47       714393.46±458341.02                  5.17\n",
      "{'alpha': '1.26e-02', 'height': 0.0}   16.78±0.34         16.85±0.38               17.37±2.96                           0.36\n",
      "{'alpha': '1.26e-02', 'height': 1.0}   5.93±0.30          7.87±0.82                8.36±3.36                            0.84\n",
      "{'alpha': '1.26e-02', 'height': 2.0}   277.93±758.85      1552.65±2280.09          1514.81±2473.29                      1.36\n",
      "{'alpha': '1.26e-02', 'height': 3.0}   9437.19±13421.12   174782.35±151622.74      274881.23±586531.17                  2.07\n",
      "{'alpha': '1.26e-02', 'height': 4.0}   7398.32±18414.83   11840780.80±34685999.57  2942677.48±5100993.34                2.44\n",
      "{'alpha': '1.26e-02', 'height': 5.0}   94.09±3.28         323521.90±37866.99       353073.83±216091.39                  2.8\n",
      "{'alpha': '1.26e-02', 'height': 6.0}   93.90±3.15         386307.54±46409.46       365379.51±222589.05                  3.46\n",
      "{'alpha': '1.26e-02', 'height': 7.0}   93.94±2.67         413684.62±60146.49       522504.97±321142.58                  3.76\n",
      "{'alpha': '1.26e-02', 'height': 8.0}   94.22±2.73         497027.10±49166.67       452349.10±266285.35                  4.49\n",
      "{'alpha': '1.26e-02', 'height': 9.0}   94.30±3.66         545738.18±62699.49       530383.11±354608.84                  4.64\n",
      "{'alpha': '1.26e-02', 'height': 10.0}  94.41±2.97         605616.74±75596.99       567457.60±364065.72                  5.17\n",
      "{'alpha': '1.58e-02', 'height': 0.0}   16.78±0.34         16.85±0.38               17.37±2.96                           0.36\n",
      "{'alpha': '1.58e-02', 'height': 1.0}   5.92±0.30          7.85±0.81                8.33±3.33                            0.84\n",
      "{'alpha': '1.58e-02', 'height': 2.0}   176.25±161.40      1390.68±1857.71          1715.33±2996.09                      1.36\n",
      "{'alpha': '1.58e-02', 'height': 3.0}   6396.84±8263.38    131706.82±101947.90      251319.34±643023.46                  2.07\n",
      "{'alpha': '1.58e-02', 'height': 4.0}   5360.98±12332.55   6631038.07±18579708.95   1835063.49±3032523.77                2.44\n",
      "{'alpha': '1.58e-02', 'height': 5.0}   94.08±3.28         256977.44±30077.20       280449.12±171642.05                  2.8\n",
      "{'alpha': '1.58e-02', 'height': 6.0}   93.90±3.15         306848.51±36863.40       290226.11±176799.23                  3.46\n",
      "{'alpha': '1.58e-02', 'height': 7.0}   93.94±2.67         328595.95±47774.36       415030.57±255089.63                  3.76\n",
      "{'alpha': '1.58e-02', 'height': 8.0}   94.21±2.73         394796.67±39052.35       359307.28±211510.34                  4.49\n",
      "{'alpha': '1.58e-02', 'height': 9.0}   94.30±3.66         433489.29±49802.32       421292.58±281667.36                  4.64\n",
      "{'alpha': '1.58e-02', 'height': 10.0}  94.40±2.97         481051.56±60047.64       450742.30±289180.18                  5.17\n",
      "{'alpha': '2.00e-02', 'height': 0.0}   16.78±0.34         16.85±0.38               17.37±2.96                           0.36\n",
      "{'alpha': '2.00e-02', 'height': 1.0}   5.91±0.30          7.82±0.81                8.29±3.30                            0.84\n",
      "{'alpha': '2.00e-02', 'height': 2.0}   125.97±137.21      1048.44±1112.78          1021.78±1307.63                      1.36\n",
      "{'alpha': '2.00e-02', 'height': 3.0}   20302.49±82971.88  313670.36±1065466.94     589536.67±1943611.12                 2.07\n",
      "{'alpha': '2.00e-02', 'height': 4.0}   3955.13±8402.38    3769262.95±9990447.47    1172757.06±1852365.49                2.44\n",
      "{'alpha': '2.00e-02', 'height': 5.0}   94.08±3.28         204119.31±23889.56       222761.26±136334.68                  2.8\n",
      "{'alpha': '2.00e-02', 'height': 6.0}   93.90±3.15         243731.97±29280.69       230529.65±140427.07                  3.46\n",
      "{'alpha': '2.00e-02', 'height': 7.0}   93.93±2.67         261007.62±37946.83       329660.62±202621.89                  3.76\n",
      "{'alpha': '2.00e-02', 'height': 8.0}   94.21±2.73         313592.16±31018.26       285401.54±168001.01                  4.49\n",
      "{'alpha': '2.00e-02', 'height': 9.0}   94.30±3.66         344326.84±39557.74       334638.89±223727.89                  4.64\n",
      "{'alpha': '2.00e-02', 'height': 10.0}  94.40±2.97         382105.92±47696.35       358032.04±229696.49                  5.17\n",
      "{'alpha': '2.51e-02', 'height': 0.0}   16.78±0.34         16.85±0.38               17.37±2.96                           0.36\n",
      "{'alpha': '2.51e-02', 'height': 1.0}   5.91±0.30          7.78±0.80                8.25±3.27                            0.84\n",
      "{'alpha': '2.51e-02', 'height': 2.0}   188.37±542.93      1013.54±1474.00          1332.40±3017.49                      1.36\n",
      "{'alpha': '2.51e-02', 'height': 3.0}   9955.28±26477.71   253161.66±677515.09      1180633.15±5705131.18                2.07\n",
      "{'alpha': '2.51e-02', 'height': 4.0}   2955.62±5794.80    2156680.75±5406547.12    761733.10±1152104.32                 2.44\n",
      "{'alpha': '2.51e-02', 'height': 5.0}   94.07±3.28         162132.60±18974.53       176938.16±108289.04                  2.8\n",
      "{'alpha': '2.51e-02', 'height': 6.0}   93.89±3.15         193596.71±23257.53       183111.07±111535.65                  3.46\n",
      "{'alpha': '2.51e-02', 'height': 7.0}   93.93±2.67         207320.31±30140.54       261848.86±160945.29                  3.76\n",
      "{'alpha': '2.51e-02', 'height': 8.0}   94.20±2.73         249089.12±24636.56       226696.12±133440.31                  4.49\n",
      "{'alpha': '2.51e-02', 'height': 9.0}   94.29±3.66         273502.58±31420.18       265807.42±177704.93                  4.64\n",
      "{'alpha': '2.51e-02', 'height': 10.0}  94.40±2.97         303510.61±37885.37       284389.67±182446.91                  5.17\n",
      "{'alpha': '3.16e-02', 'height': 0.0}   16.78±0.34         16.85±0.38               17.37±2.96                           0.36\n",
      "{'alpha': '3.16e-02', 'height': 1.0}   5.90±0.29          7.75±0.80                8.20±3.24                            0.84\n",
      "{'alpha': '3.16e-02', 'height': 2.0}   142.63±251.72      906.42±815.89            1333.06±1973.95                      1.36\n",
      "{'alpha': '3.16e-02', 'height': 3.0}   6891.55±8840.69    166321.90±228973.64      279768.30±671954.98                  2.07\n",
      "{'alpha': '3.16e-02', 'height': 4.0}   2243.88±4055.42    1260772.00±2958901.20    499416.02±727770.64                  2.44\n",
      "{'alpha': '3.16e-02', 'height': 5.0}   94.06±3.28         128781.38±15070.39       140539.59±86011.60                   2.8\n",
      "{'alpha': '3.16e-02', 'height': 6.0}   93.88±3.15         153772.87±18473.17       145445.15±88586.37                   3.46\n",
      "{'alpha': '3.16e-02', 'height': 7.0}   93.92±2.67         164674.96±23939.79       207984.07±127840.39                  3.76\n",
      "{'alpha': '3.16e-02', 'height': 8.0}   94.20±2.73         197852.54±19567.39       180064.75±105987.78                  4.49\n",
      "{'alpha': '3.16e-02', 'height': 9.0}   94.29±3.66         217244.88±24956.29       211132.65±141147.59                  4.64\n",
      "{'alpha': '3.16e-02', 'height': 10.0}  94.39±2.97         241080.14±30092.23       225893.45±144915.23                  5.17\n",
      "{'alpha': '3.98e-02', 'height': 0.0}   16.78±0.34         16.85±0.38               17.37±2.96                           0.36\n",
      "{'alpha': '3.98e-02', 'height': 1.0}   5.89±0.29          7.72±0.79                8.16±3.20                            0.84\n",
      "{'alpha': '3.98e-02', 'height': 2.0}   138.31±196.80      1267.62±2668.98          1652.36±2796.92                      1.36\n",
      "{'alpha': '3.98e-02', 'height': 3.0}   6478.02±11055.70   123471.52±147910.88      298331.38±771669.13                  2.07\n",
      "{'alpha': '3.98e-02', 'height': 4.0}   1736.58±2903.69    754766.87±1650052.08     334691.85±467002.49                  2.44\n",
      "{'alpha': '3.98e-02', 'height': 5.0}   94.05±3.28         102289.57±11969.22       111627.19±68316.00                   2.8\n",
      "{'alpha': '3.98e-02', 'height': 6.0}   93.87±3.15         122139.68±14672.81       115526.06±70357.12                   3.46\n",
      "{'alpha': '3.98e-02', 'height': 7.0}   93.91±2.67         130800.57±19014.36       165197.76±101544.22                  3.76\n",
      "{'alpha': '3.98e-02', 'height': 8.0}   94.19±2.73         157153.89±15540.81       143024.15±84181.46                   4.49\n",
      "{'alpha': '3.98e-02', 'height': 9.0}   94.28±3.66         172557.81±19821.84       167702.93±112109.06                  4.64\n",
      "{'alpha': '3.98e-02', 'height': 10.0}  94.38±2.97         191489.86±23901.92       179428.26±115102.76                  5.17\n",
      "{'alpha': '5.01e-02', 'height': 0.0}   16.78±0.34         16.85±0.38               17.37±2.96                           0.36\n",
      "{'alpha': '5.01e-02', 'height': 1.0}   5.89±0.29          7.68±0.78                8.10±3.16                            0.84\n",
      "{'alpha': '5.01e-02', 'height': 2.0}   113.20±192.15      717.38±715.29            692.81±705.13                        1.36\n",
      "{'alpha': '5.01e-02', 'height': 3.0}   3320.31±3710.73    55827.61±48994.23        91365.16±124507.92                   2.07\n",
      "{'alpha': '5.01e-02', 'height': 4.0}   1379.39±2158.81    465219.45±944427.71      229421.22±306945.02                  2.44\n",
      "{'alpha': '5.01e-02', 'height': 5.0}   94.03±3.28         81246.39±9505.87         88661.26±54259.88                    2.8\n",
      "{'alpha': '5.01e-02', 'height': 6.0}   93.86±3.15         97012.54±11654.08        91760.49±55877.10                    3.46\n",
      "{'alpha': '5.01e-02', 'height': 7.0}   93.90±2.67         103893.18±15101.95       131211.38±80656.43                   3.76\n",
      "{'alpha': '5.01e-02', 'height': 8.0}   94.18±2.73         124825.80±12342.38       113601.75±66860.08                   4.49\n",
      "{'alpha': '5.01e-02', 'height': 9.0}   94.27±3.66         137061.61±15743.40       133205.49±89042.94                   4.64\n",
      "{'alpha': '5.01e-02', 'height': 10.0}  94.37±2.97         152098.91±18984.79       142519.65±91421.88                   5.17\n",
      "{'alpha': '6.31e-02', 'height': 0.0}   16.78±0.34         16.85±0.38               17.37±2.96                           0.36\n",
      "{'alpha': '6.31e-02', 'height': 1.0}   5.90±0.28          7.65±0.77                8.05±3.11                            0.84\n",
      "{'alpha': '6.31e-02', 'height': 2.0}   495.01±2368.19     701.09±907.85            1074.88±3332.14                      1.36\n",
      "{'alpha': '6.31e-02', 'height': 3.0}   10680.06±36678.01  84683.10±120163.09       218752.56±487822.52                  2.07\n",
      "{'alpha': '6.31e-02', 'height': 4.0}   1142.88±1719.11    298125.16±562161.90      162416.05±211678.35                  2.44\n",
      "{'alpha': '6.31e-02', 'height': 5.0}   94.01±3.28         64531.20±7549.16         70418.78±43094.71                    2.8\n",
      "{'alpha': '6.31e-02', 'height': 6.0}   93.84±3.15         77053.36±9256.22         72882.83±44375.22                    3.46\n",
      "{'alpha': '6.31e-02', 'height': 7.0}   93.88±2.67         82519.90±11994.21        104215.06±64064.67                   3.76\n",
      "{'alpha': '6.31e-02', 'height': 8.0}   94.17±2.73         99146.69±9801.78         90230.72±53101.22                    4.49\n",
      "{'alpha': '6.31e-02', 'height': 9.0}   94.26±3.66         108865.98±12503.78       105803.20±70720.87                   4.64\n",
      "{'alpha': '6.31e-02', 'height': 10.0}  94.36±2.97         120809.57±15078.97       113202.11±72611.48                   5.17\n",
      "{'alpha': '7.94e-02', 'height': 0.0}   16.78±0.34         16.85±0.38               17.37±2.96                           0.36\n",
      "{'alpha': '7.94e-02', 'height': 1.0}   5.91±0.28          7.62±0.76                8.00±3.06                            0.84\n",
      "{'alpha': '7.94e-02', 'height': 2.0}   306.95±857.73      1151.28±2004.26          1935.36±6798.23                      1.36\n",
      "{'alpha': '7.94e-02', 'height': 3.0}   4564.02±6486.95    54324.41±56928.97        104940.22±130143.03                  2.07\n",
      "{'alpha': '7.94e-02', 'height': 4.0}   1041.89±1605.14    203639.32±357797.85      122517.59±167291.18                  2.44\n",
      "{'alpha': '7.94e-02', 'height': 5.0}   93.99±3.28         51253.87±5994.90         55928.28±34225.89                    2.8\n",
      "{'alpha': '7.94e-02', 'height': 6.0}   93.82±3.15         61199.23±7351.53         57887.78±35238.96                    3.46\n",
      "{'alpha': '7.94e-02', 'height': 7.0}   93.87±2.67         65542.51±9525.65         82771.13±50885.35                    3.76\n",
      "{'alpha': '7.94e-02', 'height': 8.0}   94.15±2.73         78749.07±7783.72         71666.46±42172.18                    4.49\n",
      "{'alpha': '7.94e-02', 'height': 9.0}   94.24±3.65         86469.40±9930.46         84036.80±56167.13                    4.64\n",
      "{'alpha': '7.94e-02', 'height': 10.0}  94.35±2.97         95955.57±11976.46        89914.37±57669.85                    5.17\n",
      "{'alpha': '1.00e-01', 'height': 0.0}   16.78±0.34         16.85±0.38               17.37±2.96                           0.36\n",
      "{'alpha': '1.00e-01', 'height': 1.0}   5.94±0.27          7.60±0.74                7.95±2.99                            0.84\n",
      "{'alpha': '1.00e-01', 'height': 2.0}   89.35±130.88       702.29±1001.96           491.37±465.29                        1.36\n",
      "{'alpha': '1.00e-01', 'height': 3.0}   5890.66±16470.70   62994.31±97190.58        129042.83±260862.31                  2.07\n",
      "{'alpha': '1.00e-01', 'height': 4.0}   1590.22±3690.33    182193.69±313149.59      143780.91±375020.40                  2.44\n",
      "{'alpha': '1.00e-01', 'height': 5.0}   93.96±3.28         40707.33±4760.30         44418.08±27181.14                    2.8\n",
      "{'alpha': '1.00e-01', 'height': 6.0}   93.79±3.15         48605.86±5838.58         45976.81±27981.76                    3.46\n",
      "{'alpha': '1.00e-01', 'height': 7.0}   93.84±2.67         52056.90±7564.80         65737.62±40416.64                    3.76\n",
      "{'alpha': '1.00e-01', 'height': 8.0}   94.13±2.73         62546.67±6180.71         56920.35±33490.92                    4.49\n",
      "{'alpha': '1.00e-01', 'height': 9.0}   94.22±3.65         68679.18±7886.40         66747.14±44606.68                    4.64\n",
      "{'alpha': '1.00e-01', 'height': 10.0}  94.33±2.97         76213.34±9512.06         71416.26±45801.29                    5.17\n",
      "{'alpha': '1.26e-01', 'height': 0.0}   16.78±0.34         16.85±0.38               17.37±2.96                           0.36\n",
      "{'alpha': '1.26e-01', 'height': 1.0}   6.00±0.27          7.59±0.71                7.92±2.92                            0.84\n",
      "{'alpha': '1.26e-01', 'height': 2.0}   48.25±40.76        393.24±411.22            336.33±324.83                        1.36\n",
      "{'alpha': '1.26e-01', 'height': 3.0}   2530.54±3320.80    51756.89±85299.59        67083.99±85132.00                    2.07\n",
      "{'alpha': '1.26e-01', 'height': 4.0}   2161.16±4321.83    250431.27±513859.25      127397.71±211480.04                  2.44\n",
      "{'alpha': '1.26e-01', 'height': 5.0}   93.92±3.27         32329.94±3779.63         35275.22±21585.29                    2.8\n",
      "{'alpha': '1.26e-01', 'height': 6.0}   93.76±3.15         38602.62±4636.80         36515.60±22217.17                    3.46\n",
      "{'alpha': '1.26e-01', 'height': 7.0}   93.82±2.67         41344.91±6007.24         52207.45±32101.04                    3.76\n",
      "{'alpha': '1.26e-01', 'height': 8.0}   94.10±2.73         49676.66±4907.40         45207.11±26595.16                    4.49\n",
      "{'alpha': '1.26e-01', 'height': 9.0}   94.20±3.65         54547.92±6262.74         53013.49±35423.89                    4.64\n",
      "{'alpha': '1.26e-01', 'height': 10.0}  94.31±2.97         60531.55±7554.51         56722.71±36373.76                    5.17\n",
      "{'alpha': '1.58e-01', 'height': 0.0}   16.78±0.34         16.85±0.38               17.36±2.96                           0.36\n",
      "{'alpha': '1.58e-01', 'height': 1.0}   6.08±0.26          7.61±0.68                7.92±2.84                            0.84\n",
      "{'alpha': '1.58e-01', 'height': 2.0}   45.58±36.64        379.59±394.67            395.44±512.31                        1.36\n",
      "{'alpha': '1.58e-01', 'height': 3.0}   1514.06±2243.98    28601.81±56482.31        49247.17±86087.19                    2.07\n",
      "{'alpha': '1.58e-01', 'height': 4.0}   1070.69±1396.30    145407.22±381518.31      118222.29±291447.85                  2.44\n",
      "{'alpha': '1.58e-01', 'height': 5.0}   93.87±3.27         25675.56±3000.65         28012.82±17140.35                    2.8\n",
      "{'alpha': '1.58e-01', 'height': 6.0}   93.72±3.14         30656.78±3682.19         29000.32±17638.20                    3.46\n",
      "{'alpha': '1.58e-01', 'height': 7.0}   93.78±2.67         32836.10±4770.03         41460.07±25495.71                    3.76\n",
      "{'alpha': '1.58e-01', 'height': 8.0}   94.07±2.73         39453.66±3895.97         35902.98±21117.67                    4.49\n",
      "{'alpha': '1.58e-01', 'height': 9.0}   94.17±3.65         43323.07±4973.03         42104.49±28129.74                    4.64\n",
      "{'alpha': '1.58e-01', 'height': 10.0}  94.29±2.97         48075.07±5999.58         45051.22±28885.21                    5.17\n",
      "{'alpha': '2.00e-01', 'height': 0.0}   16.78±0.34         16.85±0.38               17.36±2.96                           0.36\n",
      "{'alpha': '2.00e-01', 'height': 1.0}   6.21±0.24          7.67±0.64                7.95±2.74                            0.84\n",
      "{'alpha': '2.00e-01', 'height': 2.0}   89.06±164.72       957.29±2783.62           870.02±2562.11                       1.36\n",
      "{'alpha': '2.00e-01', 'height': 3.0}   3623.18±13460.71   28255.58±55476.75        138758.54±431759.63                  2.07\n",
      "{'alpha': '2.00e-01', 'height': 4.0}   805.96±2638.59     106734.00±393681.69      55498.96±145636.61                   2.44\n",
      "{'alpha': '2.00e-01', 'height': 5.0}   93.81±3.27         20389.83±2381.89         22244.13±13609.61                    2.8\n",
      "{'alpha': '2.00e-01', 'height': 6.0}   93.67±3.14         24345.20±2923.92         23030.75±14000.99                    3.46\n",
      "{'alpha': '2.00e-01', 'height': 7.0}   93.74±2.66         26077.34±3787.28         32923.15±20248.89                    3.76\n",
      "{'alpha': '2.00e-01', 'height': 8.0}   94.03±2.73         31333.27±3092.57         28512.46±16766.74                    4.49\n",
      "{'alpha': '2.00e-01', 'height': 9.0}   94.14±3.65         34406.88±3948.58         33439.17±22335.79                    4.64\n",
      "{'alpha': '2.00e-01', 'height': 10.0}  94.25±2.97         38180.56±4764.45         35780.25±22936.84                    5.17\n",
      "{'alpha': '2.51e-01', 'height': 0.0}   16.78±0.34         16.85±0.38               17.36±2.96                           0.36\n",
      "{'alpha': '2.51e-01', 'height': 1.0}   6.39±0.23          7.77±0.60                8.02±2.65                            0.84\n",
      "{'alpha': '2.51e-01', 'height': 2.0}   54.61±89.25        274.39±293.91            239.06±230.21                        1.36\n",
      "{'alpha': '2.51e-01', 'height': 3.0}   1091.97±1284.58    15415.44±22101.51        55468.31±140524.95                   2.07\n",
      "{'alpha': '2.51e-01', 'height': 4.0}   294.90±426.58      26446.23±32961.94        22945.61±24803.83                    2.44\n",
      "{'alpha': '2.51e-01', 'height': 5.0}   93.74±3.26         16191.28±1890.39         17661.93±10805.03                    2.8\n",
      "{'alpha': '2.51e-01', 'height': 6.0}   93.61±3.14         19331.78±2321.60         18288.98±11111.86                    3.46\n",
      "{'alpha': '2.51e-01', 'height': 7.0}   93.68±2.66         20708.70±3006.66         26142.08±16081.17                    3.76\n",
      "{'alpha': '2.51e-01', 'height': 8.0}   93.98±2.73         24883.05±2454.41         22641.99±13310.68                    4.49\n",
      "{'alpha': '2.51e-01', 'height': 9.0}   94.09±3.64         27324.53±3134.83         26556.10±17733.49                    4.64\n",
      "{'alpha': '2.51e-01', 'height': 10.0}  94.21±2.97         30321.10±3783.36         28416.08±18211.88                    5.17\n",
      "{'alpha': '3.16e-01', 'height': 0.0}   16.78±0.34         16.85±0.38               17.36±2.96                           0.36\n",
      "{'alpha': '3.16e-01', 'height': 1.0}   6.62±0.22          7.92±0.56                8.16±2.56                            0.84\n",
      "{'alpha': '3.16e-01', 'height': 2.0}   54.05±109.97       238.59±298.74            188.49±227.69                        1.36\n",
      "{'alpha': '3.16e-01', 'height': 3.0}   1666.43±3413.96    20243.44±52284.88        32350.13±50420.16                    2.07\n",
      "{'alpha': '3.16e-01', 'height': 4.0}   192.44±134.92      15596.94±9967.47         14669.65±9654.92                     2.44\n",
      "{'alpha': '3.16e-01', 'height': 5.0}   93.65±3.26         12856.29±1499.98         14022.21±8577.27                     2.8\n",
      "{'alpha': '3.16e-01', 'height': 6.0}   93.53±3.14         15349.52±1843.17         14522.51±8816.95                     3.46\n",
      "{'alpha': '3.16e-01', 'height': 7.0}   93.61±2.66         16444.28±2386.59         20755.73±12770.61                    3.76\n",
      "{'alpha': '3.16e-01', 'height': 8.0}   93.92±2.73         19759.49±1947.51         17978.94±10565.44                    4.49\n",
      "{'alpha': '3.16e-01', 'height': 9.0}   94.03±3.64         21698.84±2488.45         21088.71±14077.75                    4.64\n",
      "{'alpha': '3.16e-01', 'height': 10.0}  94.16±2.96         24078.13±3004.05         22566.54±14458.70                    5.17\n",
      "{'alpha': '3.98e-01', 'height': 0.0}   16.78±0.34         16.85±0.38               17.36±2.96                           0.36\n",
      "{'alpha': '3.98e-01', 'height': 1.0}   6.91±0.22          8.12±0.51                8.35±2.47                            0.84\n",
      "{'alpha': '3.98e-01', 'height': 2.0}   49.86±74.92        423.62±1025.43           217.13±354.00                        1.36\n",
      "{'alpha': '3.98e-01', 'height': 3.0}   526.15±484.70      5601.31±3973.72          13993.28±18153.44                    2.07\n",
      "{'alpha': '3.98e-01', 'height': 4.0}   152.41±74.56       10732.48±4799.03         10551.26±5993.01                     2.44\n",
      "{'alpha': '3.98e-01', 'height': 5.0}   93.53±3.25         10207.29±1189.87         11131.15±6807.69                     2.8\n",
      "{'alpha': '3.98e-01', 'height': 6.0}   93.42±3.13         12186.37±1463.13         11530.74±6994.05                     3.46\n",
      "{'alpha': '3.98e-01', 'height': 7.0}   93.52±2.65         13056.99±1894.06         16477.25±10140.90                    3.76\n",
      "{'alpha': '3.98e-01', 'height': 8.0}   93.84±2.72         15689.75±1544.87         14275.00±8384.82                     4.49\n",
      "{'alpha': '3.98e-01', 'height': 9.0}   93.96±3.63         17230.25±1975.01         16745.85±11173.89                    4.64\n",
      "{'alpha': '3.98e-01', 'height': 10.0}  94.09±2.96         19119.21±2385.02         17920.12±11477.45                    5.17\n",
      "{'alpha': '5.01e-01', 'height': 0.0}   16.79±0.34         16.85±0.38               17.36±2.96                           0.36\n",
      "{'alpha': '5.01e-01', 'height': 1.0}   7.25±0.21          8.38±0.47                8.60±2.40                            0.84\n",
      "{'alpha': '5.01e-01', 'height': 2.0}   26.87±20.60        116.90±75.77             121.44±128.40                        1.36\n",
      "{'alpha': '5.01e-01', 'height': 3.0}   785.86±1508.78     8718.36±16998.65         47199.93±187043.98                   2.07\n",
      "{'alpha': '5.01e-01', 'height': 4.0}   129.42±49.88       7794.74±2735.41          7879.20±4255.73                      2.44\n",
      "{'alpha': '5.01e-01', 'height': 5.0}   93.38±3.25         8103.20±943.54           8834.78±5402.05                      2.8\n",
      "{'alpha': '5.01e-01', 'height': 6.0}   93.30±3.12         9673.86±1161.25          9154.37±5546.07                      3.46\n",
      "{'alpha': '5.01e-01', 'height': 7.0}   93.41±2.65         10366.44±1502.83         13078.82±8052.01                     3.76\n",
      "{'alpha': '5.01e-01', 'height': 8.0}   93.74±2.72         12457.10±1225.05         11332.90±6652.70                     4.49\n",
      "{'alpha': '5.01e-01', 'height': 9.0}   93.87±3.63         13680.77±1567.18         13296.25±8867.27                     4.64\n",
      "{'alpha': '5.01e-01', 'height': 10.0}  94.01±2.96         15180.25±1893.31         14229.39±9109.36                     5.17\n",
      "{'alpha': '6.31e-01', 'height': 0.0}   16.79±0.34         16.86±0.38               17.36±2.96                           0.36\n",
      "{'alpha': '6.31e-01', 'height': 1.0}   7.63±0.21          8.69±0.43                8.90±2.34                            0.84\n",
      "{'alpha': '6.31e-01', 'height': 2.0}   35.58±63.12        123.47±146.83            176.46±344.92                        1.36\n",
      "{'alpha': '6.31e-01', 'height': 3.0}   428.18±500.44      4257.16±4435.22          7930.43±12367.72                     2.07\n",
      "{'alpha': '6.31e-01', 'height': 4.0}   114.75±35.74       5820.70±1661.76          6004.25±3194.91                      2.44\n",
      "{'alpha': '6.31e-01', 'height': 5.0}   93.20±3.24         6431.96±747.88           7010.82±4285.50                      2.8\n",
      "{'alpha': '6.31e-01', 'height': 6.0}   93.14±3.12         7678.20±921.47           7266.83±4395.92                      3.46\n",
      "{'alpha': '6.31e-01', 'height': 7.0}   93.27±2.64         8229.34±1192.06          10379.44±6392.69                     3.76\n",
      "{'alpha': '6.31e-01', 'height': 8.0}   93.62±2.72         9889.39±971.02           8995.98±5276.84                      4.49\n",
      "{'alpha': '6.31e-01', 'height': 9.0}   93.76±3.62         10861.38±1243.23         10556.20±7035.04                     4.64\n",
      "{'alpha': '6.31e-01', 'height': 10.0}  93.90±2.95         12051.48±1502.73         11297.81±7228.31                     5.17\n",
      "{'alpha': '7.94e-01', 'height': 0.0}   16.79±0.34         16.86±0.38               17.35±2.96                           0.36\n",
      "{'alpha': '7.94e-01', 'height': 1.0}   8.04±0.22          9.03±0.40                9.24±2.31                            0.84\n",
      "{'alpha': '7.94e-01', 'height': 2.0}   22.69±28.56        142.73±379.10            386.12±1610.23                       1.36\n",
      "{'alpha': '7.94e-01', 'height': 3.0}   227.28±170.11      2519.01±1835.87          5056.97±8342.04                      2.07\n",
      "{'alpha': '7.94e-01', 'height': 4.0}   104.96±26.07       4421.51±1040.23          4634.21±2461.66                      2.44\n",
      "{'alpha': '7.94e-01', 'height': 5.0}   92.97±3.22         5104.59±592.46           5562.13±3398.57                      2.8\n",
      "{'alpha': '7.94e-01', 'height': 6.0}   92.94±3.11         6093.11±730.99           5767.62±3482.33                      3.46\n",
      "{'alpha': '7.94e-01', 'height': 7.0}   93.10±2.64         6531.89±945.22           8235.37±5074.57                      3.76\n",
      "{'alpha': '7.94e-01', 'height': 8.0}   93.46±2.71         7849.88±769.24           7139.78±4183.96                      4.49\n",
      "{'alpha': '7.94e-01', 'height': 9.0}   93.61±3.61         8621.95±985.92           8379.79±5579.65                      4.64\n",
      "{'alpha': '7.94e-01', 'height': 10.0}  93.77±2.94         9566.29±1192.49          8969.24±5734.14                      5.17\n",
      "{'alpha': '1.00e+00', 'height': 0.0}   16.80±0.34         16.86±0.38               17.35±2.96                           0.36\n",
      "{'alpha': '1.00e+00', 'height': 1.0}   8.45±0.22          9.39±0.38                9.61±2.31                            0.84\n",
      "{'alpha': '1.00e+00', 'height': 2.0}   13.42±5.66         48.59±20.64              53.77±66.09                          1.36\n",
      "{'alpha': '1.00e+00', 'height': 3.0}   197.96±199.80      2051.49±2168.73          3204.98±5011.18                      2.07\n",
      "{'alpha': '1.00e+00', 'height': 4.0}   98.24±18.96        3398.37±665.20           3607.25±1921.04                      2.44\n",
      "{'alpha': '1.00e+00', 'height': 5.0}   92.69±3.21         4050.38±469.01           4411.56±2694.04                      2.8\n",
      "{'alpha': '1.00e+00', 'height': 6.0}   92.70±3.10         4834.19±579.69           4576.90±2756.66                      3.46\n",
      "{'alpha': '1.00e+00', 'height': 7.0}   92.89±2.63         5183.70±749.16           6532.43±4027.47                      3.76\n",
      "{'alpha': '1.00e+00', 'height': 8.0}   93.27±2.71         6229.96±608.99           5665.46±3315.87                      4.49\n",
      "{'alpha': '1.00e+00', 'height': 9.0}   93.44±3.60         6843.20±781.54           6651.11±4423.58                      4.64\n",
      "{'alpha': '1.00e+00', 'height': 10.0}  93.61±2.94         7592.33±946.06           7119.70±4547.27                      5.17\n",
      "{'alpha': '1.26e+00', 'height': 0.0}   16.81±0.34         16.87±0.38               17.35±2.97                           0.36\n",
      "{'alpha': '1.26e+00', 'height': 1.0}   8.87±0.23          9.76±0.37                9.98±2.32                            0.84\n",
      "{'alpha': '1.26e+00', 'height': 2.0}   13.51±10.10        53.70±85.83              45.77±55.26                          1.36\n",
      "{'alpha': '1.26e+00', 'height': 3.0}   136.50±104.44      1287.66±1011.68          1825.89±1787.81                      2.07\n",
      "{'alpha': '1.26e+00', 'height': 4.0}   93.52±13.65        2634.90±433.90           2823.99±1508.58                      2.44\n",
      "{'alpha': '1.26e+00', 'height': 5.0}   92.34±3.19         3213.22±370.96           3497.85±2134.38                      2.8\n",
      "{'alpha': '1.26e+00', 'height': 6.0}   92.39±3.08         3834.38±459.50           3631.25±2180.26                      3.46\n",
      "{'alpha': '1.26e+00', 'height': 7.0}   92.62±2.62         4112.97±593.43           5179.92±3195.62                      3.76\n",
      "{'alpha': '1.26e+00', 'height': 8.0}   93.02±2.70         4943.36±481.71           4494.50±2626.34                      4.49\n",
      "{'alpha': '1.26e+00', 'height': 9.0}   93.22±3.58         5430.43±619.21           5278.11±3505.27                      4.64\n",
      "{'alpha': '1.26e+00', 'height': 10.0}  93.41±2.93         6024.49±750.32           5650.68±3604.50                      5.17\n",
      "{'alpha': '1.58e+00', 'height': 0.0}   16.82±0.34         16.88±0.38               17.34±2.97                           0.36\n",
      "{'alpha': '1.58e+00', 'height': 1.0}   9.28±0.24          10.12±0.36               10.35±2.34                           0.84\n",
      "{'alpha': '1.58e+00', 'height': 2.0}   11.00±3.60         32.59±10.44              33.85±32.34                          1.36\n",
      "{'alpha': '1.58e+00', 'height': 3.0}   157.26±355.85      1076.17±1289.59          1522.62±2631.35                      2.07\n",
      "{'alpha': '1.58e+00', 'height': 4.0}   90.10±9.74         2055.20±290.82           2219.31±1188.12                      2.44\n",
      "{'alpha': '1.58e+00', 'height': 5.0}   91.91±3.17         2548.51±293.07           2772.34±1689.80                      2.8\n",
      "{'alpha': '1.58e+00', 'height': 6.0}   92.02±3.06         3040.46±364.03           2880.31±1722.43                      3.46\n",
      "{'alpha': '1.58e+00', 'height': 7.0}   92.29±2.60         3262.68±469.74           4105.83±2534.72                      3.76\n",
      "{'alpha': '1.58e+00', 'height': 8.0}   92.72±2.69         3921.57±380.64           3564.55±2078.64                      4.49\n",
      "{'alpha': '1.58e+00', 'height': 9.0}   92.94±3.56         4308.40±490.27           4187.67±2775.82                      4.64\n",
      "{'alpha': '1.58e+00', 'height': 10.0}  93.16±2.92         4779.27±594.84           4483.95±2855.62                      5.17\n",
      "{'alpha': '2.00e+00', 'height': 0.0}   16.83±0.34         16.89±0.38               17.34±2.97                           0.36\n",
      "{'alpha': '2.00e+00', 'height': 1.0}   9.67±0.25          10.47±0.36               10.70±2.38                           0.84\n",
      "{'alpha': '2.00e+00', 'height': 2.0}   9.85±2.19          27.30±7.33               26.68±19.32                          1.36\n",
      "{'alpha': '2.00e+00', 'height': 3.0}   76.49±42.38        673.19±559.47            821.58±723.10                        2.07\n",
      "{'alpha': '2.00e+00', 'height': 4.0}   87.55±6.98         1610.11±201.24           1748.52±936.74                       2.44\n",
      "{'alpha': '2.00e+00', 'height': 5.0}   91.39±3.14         2020.85±231.21           2196.40±1336.59                      2.8\n",
      "{'alpha': '2.00e+00', 'height': 6.0}   91.56±3.04         2410.14±288.18           2284.11±1358.80                      3.46\n",
      "{'alpha': '2.00e+00', 'height': 7.0}   91.88±2.59         2587.56±371.50           3252.97±2009.57                      3.76\n",
      "{'alpha': '2.00e+00', 'height': 8.0}   92.35±2.68         3110.18±300.38           2826.08±1643.61                      4.49\n",
      "{'alpha': '2.00e+00', 'height': 9.0}   92.61±3.54         3417.35±387.88           3321.72±2196.37                      4.64\n",
      "{'alpha': '2.00e+00', 'height': 10.0}  92.84±2.90         3790.35±471.35           3557.39±2260.75                      5.17\n",
      "{'alpha': '2.51e+00', 'height': 0.0}   16.86±0.34         16.91±0.38               17.34±2.98                           0.36\n",
      "{'alpha': '2.51e+00', 'height': 1.0}   10.04±0.26         10.81±0.36               11.04±2.42                           0.84\n",
      "{'alpha': '2.51e+00', 'height': 2.0}   9.53±1.66          24.26±5.57               23.59±14.70                          1.36\n",
      "{'alpha': '2.51e+00', 'height': 3.0}   64.65±30.33        496.46±371.46            610.18±530.04                        2.07\n",
      "{'alpha': '2.51e+00', 'height': 4.0}   85.58±5.13         1265.71±143.92           1379.90±738.49                       2.44\n",
      "{'alpha': '2.51e+00', 'height': 5.0}   90.75±3.10         1602.17±182.08           1739.35±1055.97                      2.8\n",
      "{'alpha': '2.51e+00', 'height': 6.0}   90.99±3.01         1909.87±227.92           1810.89±1069.99                      3.46\n",
      "{'alpha': '2.51e+00', 'height': 7.0}   91.39±2.57         2051.64±293.48           2575.90±1592.21                      3.76\n",
      "{'alpha': '2.51e+00', 'height': 8.0}   91.90±2.67         2465.98±236.67           2239.78±1298.08                      4.49\n",
      "{'alpha': '2.51e+00', 'height': 9.0}   92.19±3.51         2709.83±306.56           2634.14±1736.07                      4.64\n",
      "{'alpha': '2.51e+00', 'height': 10.0}  92.46±2.88         3005.09±373.26           2821.66±1788.21                      5.17\n",
      "{'alpha': '3.16e+00', 'height': 0.0}   16.89±0.34         16.94±0.38               17.35±2.98                           0.36\n",
      "{'alpha': '3.16e+00', 'height': 1.0}   10.38±0.27         11.12±0.37               11.34±2.46                           0.84\n",
      "{'alpha': '3.16e+00', 'height': 2.0}   10.36±5.23         23.74±9.36               26.10±33.18                          1.36\n",
      "{'alpha': '3.16e+00', 'height': 3.0}   56.88±21.97        383.48±263.02            449.98±372.91                        2.07\n",
      "{'alpha': '3.16e+00', 'height': 4.0}   83.97±3.96         997.84±105.95            1090.21±581.67                       2.44\n",
      "{'alpha': '3.16e+00', 'height': 5.0}   89.98±3.06         1270.16±143.05           1376.88±832.97                       2.8\n",
      "{'alpha': '3.16e+00', 'height': 6.0}   90.31±2.98         1512.99±180.04           1435.46±840.63                       3.46\n",
      "{'alpha': '3.16e+00', 'height': 7.0}   90.78±2.54         1626.41±231.52           2038.59±1260.41                      3.76\n",
      "{'alpha': '3.16e+00', 'height': 8.0}   91.34±2.65         1954.66±186.11           1774.42±1023.66                      4.49\n",
      "{'alpha': '3.16e+00', 'height': 9.0}   91.68±3.47         2148.18±241.99           2088.34±1370.41                      4.64\n",
      "{'alpha': '3.16e+00', 'height': 10.0}  91.98±2.86         2381.65±295.35           2237.57±1412.83                      5.17\n",
      "{'alpha': '3.98e+00', 'height': 0.0}   16.93±0.34         16.98±0.38               17.36±2.99                           0.36\n",
      "{'alpha': '3.98e+00', 'height': 1.0}   10.70±0.28         11.41±0.37               11.63±2.50                           0.84\n",
      "{'alpha': '3.98e+00', 'height': 2.0}   9.48±0.93          20.50±3.00               20.32±8.64                           1.36\n",
      "{'alpha': '3.98e+00', 'height': 3.0}   51.49±15.77        299.15±180.84            336.42±259.88                        2.07\n",
      "{'alpha': '3.98e+00', 'height': 4.0}   82.57±3.27         788.88±79.69             862.12±457.37                        2.44\n",
      "{'alpha': '3.98e+00', 'height': 5.0}   89.07±3.00         1007.14±112.06           1089.69±655.72                       2.8\n",
      "{'alpha': '3.98e+00', 'height': 6.0}   89.49±2.94         1198.40±141.97           1137.84±658.48                       3.46\n",
      "{'alpha': '3.98e+00', 'height': 7.0}   90.05±2.51         1289.21±182.33           1612.42±996.51                       3.76\n",
      "{'alpha': '3.98e+00', 'height': 8.0}   90.67±2.63         1549.00±146.01           1405.22±805.71                       4.49\n",
      "{'alpha': '3.98e+00', 'height': 9.0}   91.05±3.42         1702.48±190.73           1655.23±1079.91                      4.64\n",
      "{'alpha': '3.98e+00', 'height': 10.0}  91.40±2.83         1886.86±233.47           1774.02±1114.62                      5.17\n",
      "{'alpha': '5.01e+00', 'height': 0.0}   16.99±0.34         17.04±0.38               17.38±2.99                           0.36\n",
      "{'alpha': '5.01e+00', 'height': 1.0}   10.99±0.29         11.69±0.38               11.90±2.53                           0.84\n",
      "{'alpha': '5.01e+00', 'height': 2.0}   9.70±0.73          19.43±2.10               19.50±6.56                           1.36\n",
      "{'alpha': '5.01e+00', 'height': 3.0}   47.51±11.06        234.40±120.08            254.16±177.40                        2.07\n",
      "{'alpha': '5.01e+00', 'height': 4.0}   81.24±2.87         625.67±60.77             682.53±358.65                        2.44\n",
      "{'alpha': '5.01e+00', 'height': 5.0}   88.01±2.93         799.12±87.44             862.50±514.76                        2.8\n",
      "{'alpha': '5.01e+00', 'height': 6.0}   88.53±2.89         949.33±111.70            902.18±513.85                        3.46\n",
      "{'alpha': '5.01e+00', 'height': 7.0}   89.18±2.47         1022.10±143.27           1274.68±786.48                       3.76\n",
      "{'alpha': '5.01e+00', 'height': 8.0}   89.86±2.60         1227.41±114.22           1112.54±632.63                       4.49\n",
      "{'alpha': '5.01e+00', 'height': 9.0}   90.30±3.37         1349.01±150.05           1311.77±849.09                       4.64\n",
      "{'alpha': '5.01e+00', 'height': 10.0}  90.70±2.80         1494.36±184.32           1406.34±877.69                       5.17\n",
      "{'alpha': '6.31e+00', 'height': 0.0}   17.07±0.34         17.12±0.38               17.41±3.00                           0.36\n",
      "{'alpha': '6.31e+00', 'height': 1.0}   11.27±0.29         11.95±0.39               12.15±2.55                           0.84\n",
      "{'alpha': '6.31e+00', 'height': 2.0}   10.05±0.60         18.79±1.46               19.06±5.06                           1.36\n",
      "{'alpha': '6.31e+00', 'height': 3.0}   44.55±7.52         185.52±76.68             195.09±118.98                        2.07\n",
      "{'alpha': '6.31e+00', 'height': 4.0}   79.94±2.61         498.27±46.68             541.38±280.04                        2.44\n",
      "{'alpha': '6.31e+00', 'height': 5.0}   86.79±2.85         635.01±67.88             683.22±402.58                        2.8\n",
      "{'alpha': '6.31e+00', 'height': 6.0}   87.41±2.82         752.53±87.60             715.94±399.03                        3.46\n",
      "{'alpha': '6.31e+00', 'height': 7.0}   88.15±2.43         810.85±112.27            1007.40±619.15                       3.76\n",
      "{'alpha': '6.31e+00', 'height': 8.0}   88.90±2.57         972.76±89.06             880.80±495.21                        4.49\n",
      "{'alpha': '6.31e+00', 'height': 9.0}   89.41±3.30         1068.94±117.76           1039.67±665.68                       4.64\n",
      "{'alpha': '6.31e+00', 'height': 10.0}  89.86±2.75         1183.25±145.28           1114.96±689.42                       5.17\n",
      "{'alpha': '7.94e+00', 'height': 0.0}   17.18±0.33         17.23±0.38               17.47±3.01                           0.36\n",
      "{'alpha': '7.94e+00', 'height': 1.0}   11.55±0.30         12.21±0.39               12.40±2.57                           0.84\n",
      "{'alpha': '7.94e+00', 'height': 2.0}   10.53±0.51         18.48±1.04               18.93±4.12                           1.36\n",
      "{'alpha': '7.94e+00', 'height': 3.0}   42.39±4.96         149.46±47.10             153.16±78.74                         2.07\n",
      "{'alpha': '7.94e+00', 'height': 4.0}   78.64±2.42         399.16±35.95             430.91±217.30                        2.44\n",
      "{'alpha': '7.94e+00', 'height': 5.0}   85.43±2.75         506.05±52.35             542.31±313.21                        2.8\n",
      "{'alpha': '7.94e+00', 'height': 6.0}   86.13±2.75         597.50±68.40             569.22±307.89                        3.46\n",
      "{'alpha': '7.94e+00', 'height': 7.0}   86.98±2.37         644.20±87.66             796.32±485.66                        3.76\n",
      "{'alpha': '7.94e+00', 'height': 8.0}   87.79±2.52         771.49±69.17             697.67±386.13                        4.49\n",
      "{'alpha': '7.94e+00', 'height': 9.0}   88.36±3.21         847.37±92.16             824.42±519.91                        4.64\n",
      "{'alpha': '7.94e+00', 'height': 10.0}  88.86±2.70         936.99±114.27            884.36±539.77                        5.17\n",
      "{'alpha': '1.00e+01', 'height': 0.0}   17.33±0.33         17.38±0.38               17.56±3.02                           0.36\n",
      "{'alpha': '1.00e+01', 'height': 1.0}   11.82±0.31         12.47±0.40               12.66±2.57                           0.84\n",
      "{'alpha': '1.00e+01', 'height': 2.0}   11.11±0.45         18.44±0.78               19.03±3.63                           1.36\n",
      "{'alpha': '1.00e+01', 'height': 3.0}   40.93±3.23         123.40±27.88             123.83±51.72                         2.07\n",
      "{'alpha': '1.00e+01', 'height': 4.0}   77.36±2.25         322.54±27.66             345.07±167.13                        2.44\n",
      "{'alpha': '1.00e+01', 'height': 5.0}   83.97±2.63         405.32±40.04             432.25±241.90                        2.8\n",
      "{'alpha': '1.00e+01', 'height': 6.0}   84.73±2.66         475.97±53.08             454.19±235.59                        3.46\n",
      "{'alpha': '1.00e+01', 'height': 7.0}   85.66±2.31         513.25±68.14             630.15±379.00                        3.76\n",
      "{'alpha': '1.00e+01', 'height': 8.0}   86.52±2.47         612.86±53.49             553.40±299.57                        4.49\n",
      "{'alpha': '1.00e+01', 'height': 9.0}   87.15±3.11         672.50±71.85             654.57±404.04                        4.64\n",
      "{'alpha': '1.00e+01', 'height': 10.0}  87.71±2.64         742.44±89.61             702.26±420.77                        5.17\n",
      "{'alpha': '1.26e+01', 'height': 0.0}   17.54±0.33         17.58±0.37               17.68±3.03                           0.36\n",
      "{'alpha': '1.26e+01', 'height': 1.0}   12.11±0.31         12.74±0.41               12.93±2.57                           0.84\n",
      "{'alpha': '1.26e+01', 'height': 2.0}   11.79±0.41         18.61±0.65               19.33±3.46                           1.36\n",
      "{'alpha': '1.26e+01', 'height': 3.0}   40.12±2.21         104.95±15.95             103.80±34.12                         2.07\n",
      "{'alpha': '1.26e+01', 'height': 4.0}   76.19±2.08         263.95±21.20             279.11±126.97                        2.44\n",
      "{'alpha': '1.26e+01', 'height': 5.0}   82.49±2.50         327.33±30.30             347.09±184.90                        2.8\n",
      "{'alpha': '1.26e+01', 'height': 6.0}   83.25±2.55         381.38±40.85             364.69±178.29                        3.46\n",
      "{'alpha': '1.26e+01', 'height': 7.0}   84.23±2.24         410.95±52.65             499.97±293.62                        3.76\n",
      "{'alpha': '1.26e+01', 'height': 8.0}   85.12±2.41         488.41±41.17             440.33±230.94                        4.49\n",
      "{'alpha': '1.26e+01', 'height': 9.0}   85.79±2.99         534.99±55.75             521.05±311.93                        4.64\n",
      "{'alpha': '1.26e+01', 'height': 10.0}  86.40±2.57         589.26±69.99             558.96±326.09                        5.17\n",
      "{'alpha': '1.58e+01', 'height': 0.0}   17.80±0.33         17.84±0.37               17.85±3.05                           0.36\n",
      "{'alpha': '1.58e+01', 'height': 1.0}   12.43±0.31         13.05±0.41               13.24±2.56                           0.84\n",
      "{'alpha': '1.58e+01', 'height': 2.0}   12.55±0.38         18.94±0.58               19.79±3.51                           1.36\n",
      "{'alpha': '1.58e+01', 'height': 3.0}   39.96±1.74         92.26±8.91               90.66±23.13                          2.07\n",
      "{'alpha': '1.58e+01', 'height': 4.0}   75.23±1.92         219.83±16.15             229.30±94.91                         2.44\n",
      "{'alpha': '1.58e+01', 'height': 5.0}   81.10±2.33         267.76±22.63             282.13±139.31                        2.8\n",
      "{'alpha': '1.58e+01', 'height': 6.0}   81.79±2.43         308.54±31.08             295.85±132.99                        3.46\n",
      "{'alpha': '1.58e+01', 'height': 7.0}   82.75±2.15         331.73±40.37             398.69±225.15                        3.76\n",
      "{'alpha': '1.58e+01', 'height': 8.0}   83.63±2.33         391.42±31.52             352.40±176.60                        4.49\n",
      "{'alpha': '1.58e+01', 'height': 9.0}   84.32±2.84         427.47±42.98             416.70±238.73                        4.64\n",
      "{'alpha': '1.58e+01', 'height': 10.0}  84.95±2.49         469.25±54.35             446.79±250.71                        5.17\n",
      "{'alpha': '2.00e+01', 'height': 0.0}   18.14±0.32         18.18±0.36               18.08±3.06                           0.36\n",
      "{'alpha': '2.00e+01', 'height': 1.0}   12.79±0.31         13.41±0.41               13.59±2.55                           0.84\n",
      "{'alpha': '2.00e+01', 'height': 2.0}   13.40±0.36         19.40±0.54               20.37±3.67                           1.36\n",
      "{'alpha': '2.00e+01', 'height': 3.0}   40.46±1.54         83.97±5.08               82.57±16.64                          2.07\n",
      "{'alpha': '2.00e+01', 'height': 4.0}   74.68±1.74         187.34±12.21             192.64±69.47                         2.44\n",
      "{'alpha': '2.00e+01', 'height': 5.0}   79.96±2.15         223.11±16.63             233.53±102.90                        2.8\n",
      "{'alpha': '2.00e+01', 'height': 6.0}   80.46±2.28         253.32±23.30             243.80±97.37                         3.46\n",
      "{'alpha': '2.00e+01', 'height': 7.0}   81.34±2.05         271.18±30.63             320.72±170.22                        3.76\n",
      "{'alpha': '2.00e+01', 'height': 8.0}   82.14±2.23         316.59±23.99             284.87±133.67                        4.49\n",
      "{'alpha': '2.00e+01', 'height': 9.0}   82.80±2.67         344.11±32.84             335.87±180.58                        4.64\n",
      "{'alpha': '2.00e+01', 'height': 10.0}  83.43±2.39         375.94±41.86             359.68±190.69                        5.17\n",
      "{'alpha': '2.51e+01', 'height': 0.0}   18.57±0.32         18.60±0.36               18.38±3.07                           0.36\n",
      "{'alpha': '2.51e+01', 'height': 1.0}   13.22±0.31         13.83±0.40               14.02±2.55                           0.84\n",
      "{'alpha': '2.51e+01', 'height': 2.0}   14.34±0.33         19.98±0.52               21.06±3.90                           1.36\n",
      "{'alpha': '2.51e+01', 'height': 3.0}   41.66±1.40         79.04±3.28               78.13±13.05                          2.07\n",
      "{'alpha': '2.51e+01', 'height': 4.0}   74.71±1.56         164.15±9.12              166.63±49.53                         2.44\n",
      "{'alpha': '2.51e+01', 'height': 5.0}   79.26±1.94         190.52±11.99             198.13±74.03                         2.8\n",
      "{'alpha': '2.51e+01', 'height': 6.0}   79.45±2.12         212.35±17.12             205.39±69.66                         3.46\n",
      "{'alpha': '2.51e+01', 'height': 7.0}   80.13±1.94         225.73±22.93             261.54±126.25                        3.76\n",
      "{'alpha': '2.51e+01', 'height': 8.0}   80.78±2.12         259.70±18.11             233.98±99.89                         4.49\n",
      "{'alpha': '2.51e+01', 'height': 9.0}   81.35±2.48         280.29±24.78             274.11±134.48                        4.64\n",
      "{'alpha': '2.51e+01', 'height': 10.0}  81.92±2.28         304.20±31.87             292.80±142.98                        5.17\n",
      "{'alpha': '3.16e+01', 'height': 0.0}   19.09±0.32         19.12±0.35               18.76±3.09                           0.36\n",
      "{'alpha': '3.16e+01', 'height': 1.0}   13.73±0.30         14.34±0.40               14.53±2.58                           0.84\n",
      "{'alpha': '3.16e+01', 'height': 2.0}   15.38±0.31         20.68±0.50               21.86±4.19                           1.36\n",
      "{'alpha': '3.16e+01', 'height': 3.0}   43.61±1.24         76.67±2.49               76.31±11.21                          2.07\n",
      "{'alpha': '3.16e+01', 'height': 4.0}   80.30±14.24        148.43±6.91              149.33±34.31                         2.44\n",
      "{'alpha': '3.16e+01', 'height': 5.0}   79.23±1.72         167.56±8.45              173.20±51.51                         2.8\n",
      "{'alpha': '3.16e+01', 'height': 6.0}   78.97±1.94         182.82±12.24             178.00±48.52                         3.46\n",
      "{'alpha': '3.16e+01', 'height': 7.0}   79.33±1.82         192.49±16.84             217.50±91.31                         3.76\n",
      "{'alpha': '3.16e+01', 'height': 8.0}   79.71±1.98         217.32±13.52             196.67±73.47                         4.49\n",
      "{'alpha': '3.16e+01', 'height': 9.0}   80.10±2.27         232.29±18.38             227.84±98.06                         4.64\n",
      "{'alpha': '3.16e+01', 'height': 10.0}  80.54±2.15         249.95±23.87             242.27±105.24                        5.17\n",
      "{'alpha': '3.98e+01', 'height': 0.0}   19.72±0.31         19.73±0.34               19.22±3.13                           0.36\n",
      "{'alpha': '3.98e+01', 'height': 1.0}   14.35±0.29         14.95±0.38               15.15±2.64                           0.84\n",
      "{'alpha': '3.98e+01', 'height': 2.0}   16.53±0.30         21.49±0.50               22.77±4.51                           1.36\n",
      "{'alpha': '3.98e+01', 'height': 3.0}   46.33±1.07         76.23±2.02               76.33±10.32                          2.07\n",
      "{'alpha': '3.98e+01', 'height': 4.0}   80.48±8.03         138.29±5.15              137.97±23.05                         2.44\n",
      "{'alpha': '3.98e+01', 'height': 5.0}   80.82±2.98         152.15±5.80              156.40±34.49                         2.8\n",
      "{'alpha': '3.98e+01', 'height': 6.0}   79.61±2.59         162.33±8.45              159.32±32.94                         3.46\n",
      "{'alpha': '3.98e+01', 'height': 7.0}   79.14±1.69         169.01±12.06             185.60±63.98                         3.76\n",
      "{'alpha': '3.98e+01', 'height': 8.0}   79.15±1.82         186.61±9.93              170.37±53.04                         4.49\n",
      "{'alpha': '3.98e+01', 'height': 9.0}   79.26±2.04         197.08±13.33             194.09±69.52                         4.64\n",
      "{'alpha': '3.98e+01', 'height': 10.0}  79.50±2.02         209.85±17.51             204.94±75.70                         5.17\n",
      "{'alpha': '5.01e+01', 'height': 0.0}   20.46±0.31         20.46±0.33               19.79±3.18                           0.36\n",
      "{'alpha': '5.01e+01', 'height': 1.0}   15.09±0.27         15.68±0.36               15.88±2.76                           0.84\n",
      "{'alpha': '5.01e+01', 'height': 2.0}   17.81±0.28         22.43±0.50               23.80±4.85                           1.36\n",
      "{'alpha': '5.01e+01', 'height': 3.0}   50.44±1.59         78.25±4.26               78.30±10.37                          2.07\n",
      "{'alpha': '5.01e+01', 'height': 4.0}   91.96±38.47        135.38±18.53             131.56±15.55                         2.44\n",
      "{'alpha': '5.01e+01', 'height': 5.0}   90.40±17.17        142.42±3.88              145.68±22.34                         2.8\n",
      "{'alpha': '5.01e+01', 'height': 6.0}   81.84±4.22         148.80±5.58              147.34±22.09                         3.46\n",
      "{'alpha': '5.01e+01', 'height': 7.0}   91.10±35.41        153.18±8.34              163.31±43.24                         3.76\n",
      "{'alpha': '5.01e+01', 'height': 8.0}   79.30±1.63         165.15±7.13              152.74±37.56                         4.49\n",
      "{'alpha': '5.01e+01', 'height': 9.0}   79.04±1.80         172.09±9.40              170.36±47.55                         4.64\n",
      "{'alpha': '5.01e+01', 'height': 10.0}  78.98±1.87         181.10±12.50             178.19±53.04                         5.17\n",
      "{'alpha': '6.31e+01', 'height': 0.0}   21.33±0.30         21.30±0.33               20.46±3.26                           0.36\n",
      "{'alpha': '6.31e+01', 'height': 1.0}   15.96±0.25         16.52±0.34               16.73±2.94                           0.84\n",
      "{'alpha': '6.31e+01', 'height': 2.0}   19.24±0.27         23.51±0.50               24.96±5.20                           1.36\n",
      "{'alpha': '6.31e+01', 'height': 3.0}   78.43±40.71        91.95±17.39              116.54±148.94                        2.07\n",
      "{'alpha': '6.31e+01', 'height': 4.0}   106.61±35.60       129.17±3.43              130.85±16.10                         2.44\n",
      "{'alpha': '6.31e+01', 'height': 5.0}   88.50±5.62         136.82±2.60              139.36±14.58                         2.8\n",
      "{'alpha': '6.31e+01', 'height': 6.0}   220.59±206.13      140.44±3.49              140.26±15.23                         3.46\n",
      "{'alpha': '6.31e+01', 'height': 7.0}   84.18±7.15         143.15±5.52              148.50±28.28                         3.76\n",
      "{'alpha': '6.31e+01', 'height': 8.0}   97.51±64.45        150.87±4.97              141.67±26.21                         4.49\n",
      "{'alpha': '6.31e+01', 'height': 9.0}   81.80±5.96         155.12±6.42              154.41±31.25                         4.64\n",
      "{'alpha': '6.31e+01', 'height': 10.0}  79.21±1.71         161.29±8.63              159.79±36.26                         5.17\n",
      "{'alpha': '7.94e+01', 'height': 0.0}   22.30±0.29         22.25±0.32               21.23±3.38                           0.36\n",
      "{'alpha': '7.94e+01', 'height': 1.0}   16.96±0.23         17.49±0.33               17.70±3.18                           0.84\n",
      "{'alpha': '7.94e+01', 'height': 2.0}   20.82±0.27         24.75±0.52               26.27±5.56                           1.36\n",
      "{'alpha': '7.94e+01', 'height': 3.0}   99.59±176.99       95.37±58.38              91.73±43.12                          2.07\n",
      "{'alpha': '7.94e+01', 'height': 4.0}   90.49±2.54         127.88±1.90              127.56±9.96                          2.44\n",
      "{'alpha': '7.94e+01', 'height': 5.0}   94.09±5.71         134.04±1.85              136.05±10.60                         2.8\n",
      "{'alpha': '7.94e+01', 'height': 6.0}   94.02±15.17        135.76±2.11              136.56±11.47                         3.46\n",
      "{'alpha': '7.94e+01', 'height': 7.0}   87.74±6.40         137.33±3.49              139.36±18.45                         3.76\n",
      "{'alpha': '7.94e+01', 'height': 8.0}   82.97±1.51         141.96±3.36              135.29±18.38                         4.49\n",
      "{'alpha': '7.94e+01', 'height': 9.0}   82.47±2.75         144.25±4.26              144.31±20.09                         4.64\n",
      "{'alpha': '7.94e+01', 'height': 10.0}  84.55±15.38        148.31±5.72              147.78±24.62                         5.17\n",
      "{'alpha': '1.00e+02', 'height': 0.0}   23.39±0.28         23.30±0.32               22.11±3.53                           0.36\n",
      "{'alpha': '1.00e+02', 'height': 1.0}   18.09±0.22         18.57±0.31               18.77±3.49                           0.84\n",
      "{'alpha': '1.00e+02', 'height': 2.0}   22.59±0.29         26.17±0.53               27.75±5.90                           1.36\n",
      "{'alpha': '1.00e+02', 'height': 3.0}   79.09±42.07        90.37±17.21              95.78±43.47                          2.07\n",
      "{'alpha': '1.00e+02', 'height': 4.0}   94.07±1.21         128.24±1.51              128.04±9.68                          2.44\n",
      "{'alpha': '1.00e+02', 'height': 5.0}   94.28±2.04         133.06±1.48              134.71±9.20                          2.8\n",
      "{'alpha': '1.00e+02', 'height': 6.0}   92.69±3.44         133.56±1.35              135.04±9.73                          3.46\n",
      "{'alpha': '1.00e+02', 'height': 7.0}   123.03±45.60       134.39±2.15              134.30±13.01                         3.76\n",
      "{'alpha': '1.00e+02', 'height': 8.0}   86.03±1.21         136.90±2.24              132.06±13.47                         4.49\n",
      "{'alpha': '1.00e+02', 'height': 9.0}   88.14±6.91         137.84±2.80              138.45±13.68                         4.64\n",
      "{'alpha': '1.00e+02', 'height': 10.0}  96.95±37.44        140.36±3.63              140.49±17.49                         5.17\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "calculate performance: 100%|██████████| 13530/13530 [14:10<00:00, 15.71it/s]"
     ]
    }
   ],
   "source": [
    "%load_ext line_profiler\n",
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import sys\n",
    "sys.path.insert(0, \"../\")\n",
    "from pygraph.utils.model_selection_precomputed import model_selection_for_precomputed_kernel\n",
    "from pygraph.kernels.weisfeilerLehmanKernel import weisfeilerlehmankernel\n",
    "\n",
    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
    "estimator = weisfeilerlehmankernel\n",
    "param_grid_precomputed = {'height': np.linspace(0, 10, 11)}\n",
    "param_grid = {'alpha': np.logspace(-2, 2, num = 41, base = 10)}\n",
    "\n",
    "model_selection_for_precomputed_kernel(datafile, estimator, param_grid_precomputed, param_grid, \n",
    "                                       'regression', NUM_TRIALS=30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "--- This is a regression problem ---\n",
      "\n",
      "1. Loading dataset from file...\n",
      "\n",
      "2. Calculating gram matrices. This could take a while...\n",
      "\n",
      " --- Weisfeiler-Lehman edge kernel matrix of size 183 built in 0.8382418155670166 seconds ---\n",
      "\n",
      "gram matrix with parameters {'base_kernel': 'edge', 'height': 0.0} is: \n",
      "[[ 2.  1.  2. ...  0.  0.  1.]\n",
      " [ 1.  3.  1. ...  0.  0.  2.]\n",
      " [ 2.  1.  2. ...  0.  0.  1.]\n",
      " ...\n",
      " [ 0.  0.  0. ... 10.  7.  0.]\n",
      " [ 0.  0.  0. ...  7. 10.  1.]\n",
      " [ 1.  2.  1. ...  0.  1. 10.]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fddfaa7bb70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman edge kernel matrix of size 183 built in 1.797783374786377 seconds ---\n",
      "\n",
      "gram matrix with parameters {'base_kernel': 'edge', 'height': 1.0} is: \n",
      "[[ 4.  2.  4. ...  0.  0.  2.]\n",
      " [ 2.  6.  2. ...  0.  0.  4.]\n",
      " [ 4.  2.  4. ...  0.  0.  2.]\n",
      " ...\n",
      " [ 0.  0.  0. ... 20. 14.  0.]\n",
      " [ 0.  0.  0. ... 14. 20.  2.]\n",
      " [ 2.  4.  2. ...  0.  2. 20.]]\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fde3ecd9da0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman edge kernel matrix of size 183 built in 2.571061372756958 seconds ---\n",
      "\n",
      "gram matrix with parameters {'base_kernel': 'edge', 'height': 2.0} is: \n",
      "[[ 6.  3.  6. ...  0.  0.  3.]\n",
      " [ 3.  9.  3. ...  0.  0.  6.]\n",
      " [ 6.  3.  6. ...  0.  0.  3.]\n",
      " ...\n",
      " [ 0.  0.  0. ... 30. 21.  0.]\n",
      " [ 0.  0.  0. ... 21. 30.  3.]\n",
      " [ 3.  6.  3. ...  0.  3. 30.]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fddf89a64e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman edge kernel matrix of size 183 built in 3.4686691761016846 seconds ---\n",
      "\n",
      "gram matrix with parameters {'base_kernel': 'edge', 'height': 3.0} is: \n",
      "[[ 8.  4.  8. ...  0.  0.  4.]\n",
      " [ 4. 12.  4. ...  0.  0.  8.]\n",
      " [ 8.  4.  8. ...  0.  0.  4.]\n",
      " ...\n",
      " [ 0.  0.  0. ... 40. 28.  0.]\n",
      " [ 0.  0.  0. ... 28. 40.  4.]\n",
      " [ 4.  8.  4. ...  0.  4. 40.]]\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fde3c0bb518>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman edge kernel matrix of size 183 built in 4.349034786224365 seconds ---\n",
      "\n",
      "gram matrix with parameters {'base_kernel': 'edge', 'height': 4.0} is: \n",
      "[[10.  5. 10. ...  0.  0.  5.]\n",
      " [ 5. 15.  5. ...  0.  0. 10.]\n",
      " [10.  5. 10. ...  0.  0.  5.]\n",
      " ...\n",
      " [ 0.  0.  0. ... 50. 35.  0.]\n",
      " [ 0.  0.  0. ... 35. 50.  5.]\n",
      " [ 5. 10.  5. ...  0.  5. 50.]]\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fddf89436a0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman edge kernel matrix of size 183 built in 5.181172132492065 seconds ---\n",
      "\n",
      "gram matrix with parameters {'base_kernel': 'edge', 'height': 5.0} is: \n",
      "[[12.  6. 12. ...  0.  0.  6.]\n",
      " [ 6. 18.  6. ...  0.  0. 12.]\n",
      " [12.  6. 12. ...  0.  0.  6.]\n",
      " ...\n",
      " [ 0.  0.  0. ... 60. 42.  0.]\n",
      " [ 0.  0.  0. ... 42. 60.  6.]\n",
      " [ 6. 12.  6. ...  0.  6. 60.]]\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fddf89a6160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman edge kernel matrix of size 183 built in 6.3245463371276855 seconds ---\n",
      "\n",
      "gram matrix with parameters {'base_kernel': 'edge', 'height': 6.0} is: \n",
      "[[14.  7. 14. ...  0.  0.  7.]\n",
      " [ 7. 21.  7. ...  0.  0. 14.]\n",
      " [14.  7. 14. ...  0.  0.  7.]\n",
      " ...\n",
      " [ 0.  0.  0. ... 70. 49.  0.]\n",
      " [ 0.  0.  0. ... 49. 70.  7.]\n",
      " [ 7. 14.  7. ...  0.  7. 70.]]\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fddf8986e48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman edge kernel matrix of size 183 built in 7.080430507659912 seconds ---\n",
      "\n",
      "gram matrix with parameters {'base_kernel': 'edge', 'height': 7.0} is: \n",
      "[[16.  8. 16. ...  0.  0.  8.]\n",
      " [ 8. 24.  8. ...  0.  0. 16.]\n",
      " [16.  8. 16. ...  0.  0.  8.]\n",
      " ...\n",
      " [ 0.  0.  0. ... 80. 56.  0.]\n",
      " [ 0.  0.  0. ... 56. 80.  8.]\n",
      " [ 8. 16.  8. ...  0.  8. 80.]]\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fddf88cd4a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman edge kernel matrix of size 183 built in 7.857206344604492 seconds ---\n",
      "\n",
      "gram matrix with parameters {'base_kernel': 'edge', 'height': 8.0} is: \n",
      "[[18.  9. 18. ...  0.  0.  9.]\n",
      " [ 9. 27.  9. ...  0.  0. 18.]\n",
      " [18.  9. 18. ...  0.  0.  9.]\n",
      " ...\n",
      " [ 0.  0.  0. ... 90. 63.  0.]\n",
      " [ 0.  0.  0. ... 63. 90.  9.]\n",
      " [ 9. 18.  9. ...  0.  9. 90.]]\n"
     ]
    },
    {
     "data": {
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Ahgwg9k3Lktux1h7Orw1LYK1QSe4qYYngO7PWJ0t2zrStYZW6akmzlhLbryvSRV2T/pAitk1k12LC40hY7e4qxk/PhWdVXODHNX56BGf2nAt1kyaWzmJjbqyGPozrqpSieo9/ezJiW67bvu6arwBc64LKswveLqoIqCV90ChifGaXUy/7pxsF76sugGV1k7Jk+8rxU95X/UgxzmoercmPrL8VAQjGg3NQpPQHlvQdaF/Zlm5C1GH0TFneJ1kEpupn+H5aRpTy+mFJ76tOKzo4B1hDVD/Sku/H69dlTwWwXWJaQLuD6kKnjL/ZmXJNe5udqcAxFDiLehm9b3EWMwtb28JZkCuw173gNN4pqmNQ5Wh4+X1wFl4sDA8LoLE3lBOz4QpZbw+o1e2ZG8PvbhWjoofKxm/xED04OAvE79ealXVhhD7IYtVNJNVfnRv7bbXkmq1fsRJ8PsTkMDqvGgfRR5+jc5tSK0acjtGzcL5CgBxu5F7IPUf349FVr+D0cA66WDqPfLe2SEibnSl0HvluEFk6j3y3auOWgxX7f8tBtLqrESaD9SnoSxe+npZLpQhgxRgSFX8AXFgux7R5y0H0gFq/iCMJ5RJtTJf/azAfLuCejJe/lwyGpYLNx/UGBaxeR/wedNHZAEOt/Z1YAWesM5aj1GthnhPAI0vP3j6H+XvjMipuRJsbKlHCclVL97wt9NcuMWs1UssH7y8dGquU3RisnLWiGBWXei225sgmXH43usFyTOx7a38HZzeeTLZvqVFwNtRQQ0PRjuAsUrQ+P4p2t/5bT3tgqjSdxmaiqowqPqu6KIbQ9Dl99FTNdNru1nUOK4dn0Xmkkitj02mloCQoDIfmwmkSycb7OxVbbmRLEk9uazptd6V+ILRRw2+Q5ZbTuTidygaOHItOv/X50Vq9NJ2mUJT2ZCxO8Wq8vcVuzcuWNLOwFRTF8/c+HnnXqtjAeV8+RKVyyYL3QabadrTfrJf6Bb6z5UMFBxI4DKMbiPvbjeqrTKrdMA/6Pba7q5jB1LaQp8pRUVmt80sztfcOUqZTy2W1Nq5AUFbryLGKPSoHP21kdf5m3EygFAOOZ9iYQ83qQNZ3+nih7PXEl+njs1g5kGNiqVjowZZfWjm0LACsHMiDl2vxfBYwFpZNZJxQ6ydCb0yLPdjsTFVyczkPAXxUluO4+fGRFLzEj399fraGyZhZ2ApWl2l5ByqSaL1svw44q3ty9m45GC3MlcOzmCjFNPs8f9s56pVilpbjuBmWQK0hw8SkJFuuOgB+C/QQBRDVr0pAjtPOuRLHrRuLUqycj71KlTRgb+jv/k4QabV924Ze3+xMhf9JLadfV5zOoh9Zl2D74RWKzwJAxV1/YikGPpE7efb2OWzMjUUTNn30FCaWpkoOIY4RoCZN/iZXUXErp4ASSm4/JM/cSx2HurMzuLB1VFNXfM90qspUNfNq/hWaSVUP8eztcyHWgbVQtPZ3XCVtS7gQLghaUABj4jVoUXJI0Ydb1md1HCHdgi4aRz9SULzRsI5hSK0hihxWi4yiXlXpDtR1FrqwWS4Clkm7w/Y18g0p9U6RLsR5TxHy03CE1trUW+xuy0V9x28W1lxkFXkeFkKVVvZE23UyR+vIsSjS9Pr8KKaPF1wDxRPV0vNFt7sIog25FUB8DzpTUT8oQqyXp4me9EDFCVnLCutUZa4u4IAGLJ9hG7Z+oDqRWW/rSDeIS3oyrxyerfKqSL0BfdmZqrTvjva/XdYRxZcgB+MsdirgNGGOcjCqdF4ruaAUrmQYBKeXL4McgxUNeF2tJB7+QsmaX+1C9XAwnhjn5SWJ6vZwIaYOvrdpxL4gk6bsdhGcVyQoy2OHAUQmTmVP+923ACUFdnlmR4oakUNPucnYdrXvHI9eV/MlE8hEi9exsngmUp0fe53jJbEdbkCD6uUJ6QG0bKYxPmsBc/ZvW97rf7+ynoWM5G0cnp5AgW12MaoJ1xsH+6vkZSQbZryev43tq+UctS9ePhO2befRbnit/R08/sKDTa7Thhpq6OLSjhBDsrFR9N5+sLZ7WzY1/HZs78oBtI50I8Qnibvt5INPBDEEqMBam52pgJ/41icmMfZ0Fikz291V7OvG2IqVw7OBC5k+egrf+kTBQO69/5oifeLJHBOCvbBQc/adp78q9KxuBqg03aq0ZBv96rdcDOeUxPosPJz6Hsut8ITSebQ6F94nN+ZhZZTt1vFabAv1LNonezq39nfc09oiIQFESlTqunadzN1UllS+9245WEtTGFt84vSFijJmPwZlUNO+Lt3zNgCIvKrVQkjRSrmg1v4ibWG7W7cm8hkNT3juO1cggtOzhgCivDGsfNhEgKDVV2AMy3j31R2b5lG1IADA2NMZtm56CXg4DQwDKhMtF/fY02NlmZMhI5oHmNIXyUVfQNHjftiXrYpKzcqWagMo3fhRbUJceLpYWbcqhFP1qWJxTZ7fmMsw+aDog1DkgrWBikjaFt893wWtUhNLcd+U+sHTbTsrh2cjPYCWTfWv9j31mRtrlbG6o1D/ANOpbp5WEV/UER8oVMTqt8mynqXIXtuONWTH6CwuZlg969DV774nh2vZb31iEnvvvyZqz5PvPQcwfqRWf2Kh4YMUZz05ZWg/18WjbXiKNDt266vCvlgshZ0nz/RJUr2GF3JOEae2PzpvVjGY4jZSugWtW5/36rW6JFUm27nQOWEfvI2JY/CianlWGzsGRb16VinPWdErY50CSRZ2vx2dxY7gLLKxUlNvXlDEtsmHqKyvsun8WNShy344ZJXtS+cJ1TKb0t77r8Fzd70MADi33I4Un9oH4ia8E17bWjmQB/Mt4d40zaX8MNbee3MUCdwLAR8iKZX1AxX7OqhfQHGSeRB57zkAEVsMoIbZAGKsiIK9irD2cd32FPfuKXmL2TMZ8t161jTOuVXoaj5ZoO4BrG1ZJaPFaGhb3kFX809x+kFi+/bbpoiu11QssW0pbceRrFFwNtRQQ0PRjuAs8q16jEQANfivgmaicua3NWHqKaCmQ71HHYIFUAEFRwEAIzObAGKFJGVTL4Bvb7EbYRxSFNzpUe3+HmekbSvop18bhexfjdeOn7qBSQhQSepV8k74oFsQfIQ1VXMuLUdUjK1epwWL9Ss7KE4Gr/WTzKtn4vo5NkZMS/UBkFNbuNt0O8ORFVXaZR8VMwPEpvF2NwbDWQ7sQsLq7RidRQpnoXBv/rb6CCrE+DFabITFGQCxzKw4iUFwb3qcqq4iBfdO6Vu8YDiekpI4CL3XDw9h6weqzUzh3uy3nUeryPXqBqqPWIPfAHWsAQFdns1fcQPeHHlu4h5+pJbMxyGrS9G+1UQICcCjZW0AnxTOIoVBse8mpVOwc6j9DyLVAF2X58HMOi8EZ7EjOIt+plN1zebvuo9HlXWMz8fyd51beOZDewAAnUfOyrNVPSnF2us/e9rkJamemT/SDfqU5YSLOrkQGzuDruCRwmp/p5aRjH+nXNSVy6GZuXXkWBQPsrfYLUyV8kGrmdOr17NE1HKYcOGV1zRLl62LY6i5XLPPYuLc7EzVNqveLQdDBrVBZJ3b2DdF+bJfes62zDi0v+rmnYqh0a8fKeqXpyW0T2WoU45w75SuyY7x7N+4tm9/lHY8Z0FKIeqUvBSEqft212fgXpI1iQIVjqDdXQ2bjWIs+lkI2B/PSsKF7yUx8hRiXlg9PXnsJpfyDVFxyloY+s2/7Qfn0PbXWloi5aJjcfAsG57VQ+tPKQyVPM7CziHLKXai3/eW4mZsHXrdjssj6xOjbXnzZa9by4p3T/u1nbB6jYKzoYYaGop2BGeRykimcjV1D4onABD8OTQQr57e1t/DsmfkKGy9QB1Yo3Wyr898aE/kpq4ntQ0PP4gzAnz7u+I/+qUCGIQ3ABDpVewp1C8VQD+MgNLSPW+rxbO4kFQAioFQfZI3Zynql0qQ/QPKVADSDy3Ld1BL7yDj1usaVYtkRamUCKP9BipukHoxbcMTa9h2LZ5FidfR9/ON7zyEv/rLF64cnUW/eBbKtgWvSEGpAUVMCiCPNhkGyanu+5sQA9dAcApA2pFsY66AgAcbfPBWPVtTGqZiH7AuC5TSGBMrh2cj7EIYayKeRaoNjjf0qcxtwlgOim/w4ll49YWAPJ2pmtv4zMJWvCmiDl0neWOwqEwdd8o6E4X2S+kPzMLU/th4FtoXHUerz5zbOBFerIkIBNdHjOE4UvEsWEZjaJB6i1XMCq8PV3w8i5SCc005C7oqO5wFLSHWBMZFEUxgR+sRlskRUH7t4GB4lnoLQq8nls6GyVZ9Q+eRs3jurpcx9nSx6bDs8qExbN30EvaWdWrAV4vbL5R+1W/ddBRWrUFzeMqxDRtQ1rMCdW+7NsTkaJUKVBLnS+HnN35Y/A7k47XPkookNsVAuKnw5NZ55MIJXF+34io0dgakDm7knUdK/YNnYZFn9Ho/hGxI93cgD/3wyOuvjhtAUCSfuO3aEJnN6q7YrqfTsJ6xQPHdLJdJhrpSLxMGWd8Qtq3vgve7t12L14uy+4qM7n0hkbLI/qciZSn60cZAmFmYCi+C8Rf0Wa0PqF4AXyTbpi/JvofXQtkZTGEZ12F9nqJetVEwOhdQbFi05dt4FlZs0lOap1zVRsxJrBzIg4hEVOf08bwy98opqQrXGaknMheaRVRk3UJURypSlkW9Bg5RuL7WYrcWfUu5E2A29Gt6f6dwnIu75FK7W4+UxXcec6lF/XYhc5zaX0s2RaYqy/V6yDeT6PegSFnafipS1vTxLHz3Fllq+3XVcBY9VGYrQlppLlO53IoLvcWuk2ekWmgax2F9fjTSdfDDKbxO696S+7qxyTEsssOz2Pfwmu91KpxA0dYUJpYq2X0GU7WNTi0bvcVu8BRMep2WHAHrL+pC+N+KPLxHmlg6G1lllGyIf3Iw8/c+HkHvQ3ljntQ+6ztTgBPbmD56KnCROh/qdcp3xJSNXNgeVwHUId4AIr0N9Q0ejJ7t0OvUG2vkdUrcx2HJ02vmDEBwAKvBvaWvntepkhfQh8Q5JrfqAdM2O9vzOm2sIQ011NBQtCM4i34UZDn5bVla6/xky3jhzJYMotHS3vuvQbt7siYGADH7bdugh+pzd72M3Y/GWb94mlkcRHFS+kjG4rSvQtoxCCvr17Zt/UochyIerdWBMvH0cYSyK4dng/JX6wo4AA33d8TBFxw5hhnUT+Tpo6eiZFArxhtSOUqKNxaUFeJ6Cifa7q7W0JMnbrsWN374yVrfGHrO4nIo+lgcS6EviHVJKVyHdQUnUlj1BfYZANF8qiVjfX42tB/aFMud9kPD6amObHKxG73/NoCzk0MZQoo+DV3yMtCwqQCWD41h1/xslHdTUwFomHayqvxAKLu2jhyLgsqqTEviRzqzsBUmfLkMtsvybGv3ozlevPUMNp6+LhJzFGyjC9DGimB5CyBjfs/d8zfjxVvPAEBow9bvkeoErBJQY5EW5Lv6c471fy4wteJQ8cZgLHaxTx/PaiJirf5S8auKZkbaJtl3pAsdKCxeniu4hlks/p8NGd88L9Dp47ORDo397C12w5xNPth13RKKtgZHx/VMutNHTwX9k76/lQM5Jh+s16GQAUUn857qhFovDexSVXb4ojufBuEYLJoSAFDmoginRHmf1hXFXUzos2ZBbt30EpZxXeSfsvH0ddi66SVsLgiCs9S9pOJtpkj70bvlYKifbW8uTEX1A741pFCs1v0t2t3KzZ7K0JUD58LHD1TWEG+e+f/GXBY+xjCnh2dr80gYPq0L00djtKa1hqA8mYuxHATEb4bkmVw5dqsb8GJkFmke6hgPjlMxOyzHsuOnR6Jnirqq/tMJLIKWO1yJXtPDZPz0CCaWtsoNoBO1qe1WbRe5f5WL6MkYSSNnh8dZ7QhQ1nbh3kp6mtr4A3ofqDs2ATEUWbNyKyCmH1BLnXosXJvtMB7G2NPVZkJzLoBog1FFmcK1BzmoFabb6yIlHdtQJSv7RIuMhbjbjZZlbYRxK56FCE/GX8T6tViyimK+L431oeVsPZ6zFpAwQRqnsVTeEasE13nz4Pz6bXobfwqYNggOnoK32w3HOwQ9V4WaLw+wLVBWo+BsqKGGhqJw5DF0AAAgAElEQVQdLYYM4wjDTNoWbBWZ00RH4HlPcsden58N7S0FkA1qyj1ATjSRrVU/Qh1Cu7uKsacLUWfrppcws1CZVEkVEKou01ozp3dSsw2tH4g5Fo8KNrbqR0p8CzgJMZ3yVFaua2MuC4F32a8Qq6O7GtVtociKxejdclA4ryrSl4cABcy7hq9vYAxO5UoonnjpEOzzlSgRE/ELts7otEf927PfMv9njhnbVzt/g8i+c+8b2OxMYeSFVwhnkWVZF8BfAXgZQC/P8+/Lsmw3gN8E0AHQBfCjeZ7/xfnUn8Loe+KIsmcp2ZX3Us8q+8gPeUVkZaDyL/FEAX0OQHD75qKdWbimFBdikYPPRR+5aNQtJoELjWIB29D6gXob2k+rcFOXbZXr+Yz92DfmsggePX30VKHYFGTnZmcqigNhx6v9ISn2xF73xI/U9xCBkbqroR+K3yD2wFqgqJNi2Xa3Lia0u6uhvmn9TvUblD5636MnxqgY7MUy1Tlgm3YOFZ9js9x7eqZh6WJwFu/M83xFfn8EwFfzPP/nWZZ9pPx9z/lUbLXXKddflav1Wb1Psh+dyq7eRqIKP6Aep7IOr44/Jt23lw+NYezpgsNYPzkeRbC2G5yVT7UN6xPANrR+AFg/OR61DcTBb5TUaqH1cl4DyrUc266TubsRWcuN+vfo+0kpde14Ky4sMc+1GmJif6wFinWof0xqHCmOi/VF36kzFs20pmhYj7NQK5Buut44+zmi8ZlIv+aB1V5wH3fpUugs3g3g18u/fx3Aj1xIZXqK87c9SaipXj40huVDY2Gh6v12ia8vUG2rAU6rCiH78fP3zMJW+AcUHMNKqeHn81QYWiK0mv4rMwtb2P3oOF689Uyokxr2lcOzePb2uQAJ9haZt8A0UhjrZxsbc1mon7R8aKzW12dvn+sbOn5mYSuCIE8fPVU61Z2qecFqOZ0jJY8tnnzwiQJiLrDsmYUtTB895Yog6h0LiHJwf2Wp4GJaOTwbnLNaR46Fjbq1v1Nj8QNqthybbYcUOXsJ8dtjvRY6vnxozD30qKQPfS2veWOPcEXld+zNcz/xZbucxQVZQ7Is+3MAf4FC8P2VPM8/n2XZWp7nk+X9DMBf8HeKLtQakmJR9b7929r3KdemNNmk4B2aOBUtrJrAKgCRJWRmYStYSV73sbUa0ExP9MKh68miP6XJz0YLUzg0F4INeAPE7vJeSgTl0FpHjkVQaLvAPeuP6gD0Xdj3Z61PS/e8zQ2LSNd0FdM8YJ62b7+TVOoHz4UbqMLle1ydhhEk1+pZTmw/NOCQnRfWZclyx9aioW3b+pbueVsE3af7vVJrfwdfW/siNlaef0Vc1N+e5/lSlmV/E8BXsix7Rm/meZ5nWebuRlmW3Q3gbgBo47oL7EZDDTV0qemi4SyyLPs4gHUA7wfwjjzPT2VZNgvg9/M8/+/6PZviLIAY0eb91ms2F4h9xiap4T2y0F7wGpvhnM9q0p9U+Dptk3WSCuhulSpx96PjUdBhknciWhnaCwDMNoAiKvnuR8dDGQYLsrk8LLeUQoQqJ2ZRkKnkTilFpsUMKOfE+lwX7xKLYbkxm9gHiDkAkk22o+OyCl4Np5gCVaXmiH2x36ANNDwMzkLvax8szsLDmwTRzIDRthOw97w3iyzLdgEYyfP8r8q/vwLgfwfw/QBWRcG5O8/zn+1XV7/NYhjyXlS/wKeeyOKxnBo5iWU8kccTb1RcseAqZflJL956BueW2xFIilHHAdQ041HezbINWz9QKQhVtNCI4doHD3AWIQPNxqeLmn21gYi9WJdADJTiuDQIkBcVK3VA6IbhZSfXtuzf1pxp5xgwQWucqN62Xs9qVzO5O21qOZvh3rue+q1j1u/bixb2SkXKmgHw24VaAi0AX8jz/D9lWbYA4LeyLLsTwLMAfvQC2hiKsyBFL8TRFKdemF00pCL3aGzH11O1qKuec8RS9TGPBnOWfuTLh8ZwbrmNkZlNbMxVItl4ueHTxNePaApVcxmzlzF3CFDY7xX7QKvC8qExNzJXivgBcwwbc2PBZTpsTGJhGYbU1JtyF1dKzbdH7JviYwbNaeogsWWGRyqkv0HtJ4Ck67nXr2jD20ZftkvnvVnkeb4I4Cbn+ioK7uKikJqa+DvSBMsurslX1NFJAS/qJxCoMxVxAlW78QZC35HeYjdgDHqL3bDI6smL6hwEaWMuC2CrXSdz7DqZYWPuOsy/6zkAwNoDN2DlQGGeXD40h30PV8+29ncCCIyUaqMQi0ajZwEE5zv2d/5dzwEPt+KP2IhourlNyHVS8K3g7xKjMn20zt2FqGfldcbSePHWM9h7/zVhPBbXwGuMHmU5qcCSG+7vubsmMbF00I3pYM2rQMkxlNc1rQMMt8AUjWEBl745nqlTDxnAj961MZfhzJ5zmD5a4TxaRwQvYax8PcRijppwPfHPGg1GRoffXhq4d0MNNTQU7WhHMmB7Ck5L/cxSSnVgVaUHsKYqoO6t6eUN6cduejoLAJGCc/KO57H2wA3hnsb8tKepJ1YpWR2AmnW1LzZCudW3KNmIWlYnon3zQE12fmz8Tw0hQJ2LVRgqtgOIzbte37wsbEraV40mTkWwhgtQMJ+n37DfiCfKpEy9rN9z3LN1WUVvP9HJU5pecdG9+1FNMeboKjwlUZRQxrkffXiiJaZ8nZJTvWCyFENSH4j1WrXyPgFd46ezCiz1wA2YvON59D45E+kTNMCN9lG17PrBcLHZsPR8hgvizJ5zIbCLDRy8cng2svpQPNLF/eKtL2P3o+MhNib72s/93m4gqq+o0jfU+x1Ey85UbdOyc8trFHM0HoXqoLRsJWZW9cYBoSsxk/EhUoCo1Fg3S3EWiMUI3YRWRFGsYk0Uwg+xrkfD6FmyAsd2xZAdzVmcLyjLuiJbUFbqJBgmrsQgjoHX+XGqnGpPc+t0BtRPxNZHl7H02N7Il8KevmrGTAHUrPu+fpS8z49OTylmXhs/PRIpHVPu7J4VyrpL6zjZPlNC2n4+e/tcIcNLbhfdBDlPnE/Pec4CzQCEHCAWKMUNVLmIKFWDmS+bbS1lZrWgLH03KfJAWanwC3ZtaJ4Rklr2SK8kKGtHEC0ACve19wEEpZf6bKj1wFV+AhGC0370KfFoZqFaSOoDohsHrS2kdncVy4cqtOfyoTHgsb1B+Ujy0jNSYWrNm54IED1TjoXPW4ex8dMj2LrpJew6Ph4tSpSLatd83B5NoHrN24AtJmRkZjMoRDuPfDfMcbH4RzB9NOYwyFGoqKS5Ze2mG35L9CkqeHW8zE+yPj8aInMBdbRqaLdMmtwO5apntF4PAZsSpcMmI+UYPCe6TwWnBDxim+SE9P1Y6i12MTJxBQa/OfyaO10dgz3Jh5V/U+Age98DBWlZTUBMsqcp4IOS+vUFiE+51AlB6t1XfA69T87UThhvPJZ0PKlgO3aeFA7tcREp+7+HCSEQDEDgFFSMsZnPPCxLCkCmICrrFJjifDjnKu+T0/Ay0bFvCt1XzkLb0Lo4tx7uoh8GQknxIDYhNseveiJmLbOcObkpfX47oKzGGtJQQw0NRTtCDMnGRoudtvztnb6bemoZ7TBZRJ4wk4vdKG+IxV9MPvhEqE812hV+odrBVbGnsij7tV6e6uvzxf+aqT0VSyKcfsrFODJnZPX4ZDkfH13GxCdnXCBZPy5H51TZ4Qj9+NFl9D45E8YAmOCvx2N0KgFpQAwistxRkQXtu+LF+12/7yVuQVl+tlsogBGNK5yoDjelQXj53ugyD6B4z/s7Ico4gFA/n6f4yKRSVhXI+tTZMIg1h+aishZybkWMmvLR5CjxHOdorUvlM4mcDYEicviht4Uym53t5Q3ZMWJISsE5bPAbYDA6bljlpJKy7YDvq5H67ZkRPTZyGEWV+qxwUXvQXk9s0rZUn6CkCkv1vlTy/DCsGKLPt8xCUvOrVf6yD5wPbccjLzanbtS2n6zXiqK2LfXvUbLzp0pQfX/0OdGFmvLz8Hw1VKTygt/YesNz8p2lTLp8Fzp3r4hvyMWkVBZ1wF+M1j3bW+iedUDL6ofl6UM8K0s/Wd6WL/J6jEcLzOsj4OsLtJ+2j1o/4C8cS1Y3A8SbMU8+ZpVnv1JOatYHQz9ozw/EvgegsoBwLnRRe4GQrYzu4Re87+GZD+1J5w3pM/fe3LC/YWxmY01Z00LekMTzKTyR97y2qS7zJFUyq3memCFt48jZL2LruavAGtLkDWnyhjR5Q3ZO3pBGwdlQQw0NRTuas9gueUAse7+mt2iSDIW/myRDTZKhfrQjdBZNkqEmyVCTZKjql+2rHZ/dcLxD8FIkGdrRnIXdIDwFWpM3BKGNJm8Iot9arskbcpnzhlxq2o7pVHfcFDvKe6lnm7whxaJRVp3P2I+9yRvS5A3ZUWS11x5noR+ix1nYCbYfnbKj3kaiMjzQ5A3h2Jq8IQj1Rd+pM5Ymb0hDDTX0qqIdv1koy8/flu2kprpJMtQkGQLEgU2sFU2SoTpdVWIIgNrLaB05FrF6nNR2dzWwycTM632gYsEVOARUyrWUKKKJWvY9fLJmNg31HB+sVGZdY09fB2ArXCe7rVBjL8bksPWzja2bXgKW2zUIM/vKTaPziK8EjeReI7drMBmFSVPX0c8c7CorqafZHwfQsXoJsv4zC1M1MTAVHJiBYvRbSC0W3WBYtp85PlK4D1iYHpTc9hOo+4ooWatf75aDQb/Ca57y90KD+e78zSIBg/Vktch/wpHn9L7VaVBhp2U0xkNBo8GstlGe/tOINxO1XJA8q8TKgWvDCx2ZmcSu49RhjNae83QXXhs1R6MD1wJl1PD1+QoaXsTRKPKGUB/Tb6F5RAuDzg3r8Kw1w5DCuIeJ7m31VP2IVgu1Ogwar+o3Uu2kdAYpshGtvH4Cdf2C1y8SMSuXmnb8ZmEnz+7wnqbdu08Kykk5JW2CIdZBuLeKA8uHxrCv2wknhN7bmBurLRTvI1s+NIbx05Xj0+5HudCr9snFeBGu7OZh2yDbPH6a3q/jARo+/bE1dB6ZKhf2KvYV04qVw7OuZWLFpG5UIvinKOsrJ71APTo/KgaGiOGYCpzhyntvBkquT+eW5lXdnCPvYYP1AHx/C+V+KDJww6qie89VSmjHCtMTJalnaVAHMIo/0+ivoPT8drSPQGEF47oIeB8gTjVRPrc2Pxpg8lrvudHht4Adr7NoqKGGdgbtCARnyuvUuhdbiDRQnfYaPYkngI0YrfI/21KvTgXoeKCjlFs0lZQWDel5GqbQn4MiZWmMCY5VA+iyjZS4Ek7E+3pYemxvqEejftu4jfPveg69T864GAeNS5kaL9+D9p3tBjfrjy4X/7+/OuGUU9QoVjQJ773/mqGRmtoPLW+jTwGFyVnrtqd575aDAY3LcuQwrBfztz4xib33XxP1J6X38LBEOh7OIZNps15GxNKyQOGR/LqPrbmJnxe/8MbwfLu7euUhOPOts5HikqzVJFAhJI8ci36ra+6+bnHNuuWyjHefL2Tfw8VHUbyM+CO1sSE0yI7Nddp5JA5221vsYnKxi4mlg+4CXj40hvkjxd/d265FBwdr1higEj8sJJz1F9fSbQBFGLvOI6U37WNjmH/Xc1hcngZwXViAKydnw4dO0eRZ7MUM4vEXVG3mAWnpxM9kHEsvEBBQLoJy49qHCqSlliWKGTMLW4IbORvKKv5gLaFb4OamIofqaAL25OR4qNuOt40C+7D7UR4ecTsWZFaED6jrFgbpcSiOqaVO69/96CzW56trVNoq2Kxoe82N6G77NXL2Kkoy5JlOlRRZRxOllRdJ/LDti1qfHw0gowJeXUymVbLpSVpkEYsVlza3htbPf/x9Zs+5IFuPnx4J5l+Ogf2w40+RrZ9t7DqZY/z0SHR/cXka+2dWcGbPOZxbbuPccrtv3xX0poA0mmvJKYzMbIb5bXdXw1hS9SrpBjOxdBbjp0dq/fb6pCbSfspO24+NuSw5r6pv0s15GEoF64k30LSr+sZc1ve+9ovEsXtuCfx+tmNRS9GO4CxS1NrfCUqmnvkdwXnLWBQ2kjFZP7L4u05W2vvAth05hmlUJ5qKBlwYNUey8h5QKrpKVlQhymQn291VdG+rwulTiamxHNQ0xzFou170JmVX2YbWzzZYf9ggD88CuA4n9lyPG9/wAk588/pybvIwnyxr86QqsU8VBmEU55ZztLunI9OqcmreBsF2iajkvDLyeZHW0VqlJBpUrWd10nbUdGotQGr90JCBbIewdyUrNm7MZZhGXRnM8Q3yLvasWjoOnUf23XIWLKNjABDloSVtR8G5ozeLWsQlZ3fnQgXEDVtwFqn74aWV92xcTF5TkxQ/BF3IhDN7CVyA4gVXuoyYU9HcGIQ0s4/klPY9fLJm0rVzUbVR1z+tHMixMTcWRIuNuSxgL058s9gwAKD3yAyAmOuyoeO8AD1VOoMRjJ/OavoGG2CGxI2YqQ/U8W7l8CxGZs6U5a4JoojWy7nTxdpPDPFMi3bhkqvhdWu5aHVXa6KuJYXTDwLTeaQ+K944NDEUsUL8VornY11fFAXd6ddVJYY01FBDO4N2hDWkX65Tm4siFRRW41lorEFl1xlTwKJCrQUEqMQSG+OQlgtP856KDapiDPumylMFddks6tPHs1o8C5Iqy+zYgXqwX6CyWlDfoFYJtUhoGzZbOn/r9eVDY2UKxNORfO7FneRc6alntf2Wk/Icu1J5Xz28iFonLHnKRhXHbBxULQPU42R4ddpvwX6H+s44j947tWTBirY9a32zIR+eGv361ROw10awtuni1IxnJ9++IN1E7AZhIcWD0g960ZxTqQBs1Grr5ep9rN5CABAie7Mekg10ou1q23bhk9rdVfTu64XcqiRuKGoapkys5lt1cdfx9Ba7OPGZt0apAPi8mrU9qxOA0G6RCqBghLlx6nvUZz2Tt2cRIdkUjbqhAkXaP7ZjY4Xw27GpADQqvBeIWAFdHjjLG1fw/pVDxksFQDcBe3jRiqdz/YdPfW5o0+mO3yw8m/crGd3btg0MF92bH7nKh14fgf7Rvb18Ee1ukYNUF69Xv1JqTu2JzdyqnBt+pJ7Zz5sv7114pyoQb3zaN1uHDQsAVO/AbgDe4lv8whux/8f/uDYnduHogiJ+AagW9rc+MYnXfWwttBPaLDN9AbHuReecOBE+rxYmO19eWD99nvdtP7W/Ni0CNxBb/5FzX8DW4tKVg7NIkdVW8/crEd1b21ZAz6Do3uFUPy7KRQOMsQrXfmP3Fsn8kW5IvAMgaiMVDIZUwNXjcem9kFsVwBL2RgrOYUjrt2PR5ECt/Z0CY3GoKJNymFMLQIju/eATmFmom9Pb3dWKo5Q6xspYpXYTsXFW1+cLB8OZhS2XrR97egwrhwush0Ywb3dXsXVXkWapd2+3inIum1hh5boOwFroKyOIeWS55627JjH29HVYOTwe8DXEyNhxrRyexa6TRXT59sNroX1yQBrde+TM8GrLRsHZUEMNDUU7mrPYLinb5u3YXmDTVHRv0rDRvc/sOVfTIQCzWDkQZ0rXNHgaFi/oW8p6rauxQqapJwEI967a8NLsaT3zH+3hWfhwb6A4VZfK+/Pveg69hRmntko0UFFq5fBslBme72FjLgteukW7xbMzC1sB7o2HWzXRA4gBbzxJJ5YqqLYqoG2KS5LHKfRuOVgzkW7d9BImlnzxs3XkGGZQwb21HFBxL71bDqLVXcWLt57BxFKlAJ0GojCErBeow73DNSk/9vR1QQHM6OxjT4+Fsqq3ePHWM3jdx9awMTcHcjLEihT9Kuepu4rWxqssunc/ra8nV9sgrSpTDxPqjc8p2f6xrn5KOG4AmvHaKkGf+VABttKYoKRazk+pn/fVEgTEwCML9rIWCKDQKxC4Fdp14nZ4MUFUUWnfkW1LFaiEjfP6jW94IfiokKzeSMlaoNiOWru0DqvToq+R7Xs/XyX73vSaKjyt0lkte0Bl7bPKUNsen08llbJ+PgBqmdUB4GtrX8TGylWQkWxYYoCWlFxtg6kC8a5O+VZ9RkheVC6vbosWRfmxKrqOC4kwbq8N1bYXH3xenKgPV320AKcQOFbqB/zYjVX/pwCM1syDdozPlMCtpcf2Bu0+F7Nq5j10Y2rOOA69d+Mbeug9MhM2DV4fPz2HE7ger+/GzngMvKORrLjA1ZIBVIpaDTLc7hYxMzwulIuMYDDWZ61IrI/6LqDQe7BOrZd9s4da4DIl9mbYGITLYN4RO68pSBX1MRbVrNRb7GJkYnhmYUdvFva09jTdmgogbACIIwRpuH5vMwiLvDNVO+Hty7CngcfeAn6mcvWCnVnYcgO8WO31xtwcdh0fx2anwAgUi8kP9W69bD0TqTWvKjSbuTztprtUKj1pJZk+XgUOZj2TDz6BtffejJYokanA8yw6NgrY8mNjmMFWwJVwUc+/6zmc+Ob1bh3cHHUeObcaZJnKRBtvxML5rWlSLRwowwOqCZp122/EIl6nj55yrR5wsECM+rZeKiSBSrSx3JlnPSR530etbGcKI9/4eu3ZFO3ozQIYDPnWsHoWqKX39VmXWyjhvJZV9thGW0dgB404oNcBYKJkMWl9mZCyHoyYWm390KaPz9ZePNvQ+nldc6bouCwMe2LpLKaP+85Vu07mYcMAgBPfvL7MkKV5UW8O86JmO12UUZ3zcbCdXSfzwP7Pv+u5oDfBY3uBPeeiOih2eTomWm/0RGU75CQ4N3Zj17nTDai32AUOz0bvn5Yvcm+sN9Y1xX3zRAubV5VtTCydrXEbrJd/b3amahG1dAPxuD37HprgNw011NBFpx3PWQxDg9yHvfueOBIFpwXgOR95sUCtqAP4odx4j5yM5oUgqUKKcG/FLnh6gZZpO5weJqRgdU/l9BjZaU8e4jmmjyMoOm98wwtYO34D1udHMV4ihTfm0sFoUzoLvd69bU/Apqx883pMy8m+66QTdkA4A3I3gdsxOovpo+qAVYpNSAP6WkeOYeOetwXuonfLwSiEIIn1xaJXxR1ovfpOWGaQzgLCIXp5Q/rpLLw595wdR0avkoxkl5KsaFL7X7JxWTdfqzdRUScSDRwLB30ybOxHLmA1rwUxSOJjqo7AikJaP1A3vwKIAEieElBBcCxLqDbh1mvHb8DkHc+j98kZvHhrYUrc/ei4C8jS8SuxraqNClK+MZcFczAtJFZW54YBAK8vgxuxzOSDTwQRL/aArTZjKg89wFlrfyeyJEw+eKzWBuds+dAYJkqdAu/3s85ZXVqkFIeKulO1DYb3rYu6jlOTXHkUzSMAvDC8zmJHm06B4RzJgHgSLVKQpLBhfd5TnnmLHajj8a3Si/Bb71lVfOmiZp9ptgPiuAYK1fXIyrPqmMZNoAr5/13XbJpKO5AysU4snU36qZBevPUMxp6+zjXZ2bmhvoKWFpW9OefWYY8KWcV6eKZq7bP+1meA6hCwPi6E1nt6E513fYZlWK8X4lHL6dgA9G0rUnxq5vmStD3WwbANtuyTE09cWb4h/TaL8yGNaZm6bwEx6qUKxHZ0DUJjP3y7IQ3iLEg2R4n3MWuEb1VI0mnO4yyUNNmwfjTcqDbmsgCi4iaiHI9+uLrhjJ8eCfEqCaqipWTfwyeDYxaxEh7ZueVC4obBqFtFGLhY/NJ3p0A7nRsvA7q+A8/JzpZncqYbP/xkhH/wxqF1DcNZ2G8o/C3fpkd6oDCnytp7bw5cYiqaOtux8/L4Cw8O7XXaKDgbaqihoeiq0lmE3fs87nsAJqDYjek0pPqEwEEklKvqIl+HgddFGzqdkWYWtgp9QAnGIqc0aeoHELVhTzkq4SjfUgdSnNSj4HlBEUojhWlfC1h1YR7dmCtO/PV5YOOxChq+9sANtZNXRTMlRhjz5qNwSS/ehsc6U4YntF31EuQq9GRVLpHOaDxlCeWOqDTFM8hx7xYGU471C639nVCfcpTY33HDJQBIJnLmt7lWOsyl3P8JO2ebrcVu0MeE9mGg7+UYWovdqF89AOcmrpKwesBwOothg99o3Iue04bCvSkGTAu72O6uFi+hBHBZUoix1ZADVVg+spKUW9fnZ4MYoDlIdz9agLEmls7W5XBHQ671A5WFg3gAjmvlQI4Xb30Z55bzYM04s+dcbZGpiLAmyYao2FOdy9oDhdKz9f5WWGTr86OhXktLEnOBbbj1EqYu863vLkR9R7l5UAQ176172x5MH602wJUyEBKfU+qhzsbzm9LNtNVdrSmRV0q/najO8ntJ6TaAShRZKeH9k4vdMGaG9AMQtU9riIpdNfHLjs3cH7nSFJw7MW8IgKTsa30UbNQolqV+wIuNANT1JXpfNzo9mbTvVpdi6/fomQ/tCboE+/FadCIjNml/lHRz5by86Uvfxu889HfD8wwoo6TxMagXIHI05XPDnCQAojpV92MDIw0iO4+M6uXpedSHBaj0GECcEoF6hBOfeWstf4qn7LZ9YXnWCxQbFWNvKKfGeBb2m2LbNm8IULz/Gz/8ZDFf+zvbyhuyIzaLnajgBMQWLh+FNVl6cF173bOMaL39INHz9z5exCCQWB2ptmomQIclZz+s5cSFI0uf210/WZByQvQX+ZH3FKfVQ793GADcsHp2Y+DGQdMpSYPJkCza1VoYrLLXJmRK9cnWr0pDa5GiYpFYGC8AT2qsep1krT86PqsgtZaRJcGE9AvBp/0Diu+nUXA21FBDF52uCp0F4OAsHE5hIM6iMxXFmiBwhtcou0c4C1TKUU1BANRPmOg0F5mZCkTVu0wsnS1OMiL7FAlKPICZA8stoJSf1dxGHcbyoUJ8UpOszewdn9BTNYTmc3e9jI4EwaWOghzFe955FL/5p5UyzqNI5Dwepx/QPmjiZcbjXDlQ4Cx2idIydaoGMFwJ8vKC8JIDYFmOt+B4qrwqQKXYtu76VDp6nJNyZyncjGJwAqI5tHIAACAASURBVPcr9xWMxm9Dx8H8JoAv6nj+JMPSjt8shiFCrtcTH03QpB+ejX+Xf090HB3JLQeLzNMPPhFN7oRVGJVtsx4bWFjZRoox0+WmoAuiV7ZHNpkQZXosepB1y5pq/UCscFX7O+dJsR0rB3JMPljf3BQRaBd8EfClqJfRvcdPjwTsxm/+6UH8o+89hj/Ca2pseDH+2GVeRYc4e3ysZxo/PVf+XzDGHgTeXtu66SXMLFRRwz2PX+2jimXjp+cwsRTjF3rwwwV4dSl57SoVGJMzmFm4plLYm+91UFveu9J7wwO8Yxqos8iy7NcA/AMA38nz/O+U13YD+E0AHQBdAD+a5/lfZFmWAfjXAH4QwEsA7sjz/PigTuz06N5WKaoQ3e1G9075I1jSvqsSTwMBeyCvfhp3HZeldnc1KD8tAtTqVMIJZVIicMOyAYTe9KVv4yufenvQARAQppBqPWk9sNrNn34qcCw2yji5OcruFvCmZDnUZ2+fCxG4zi23a3Xzb46PCk6+g9aRY5GlSBWh3My0T1ZpaoP2WoAW54B1W2uRF12cyFYbYZx6IQXLbSe69zCcxQMAPgfgN+TaRwB8Nc/zf55l2UfK3/cAuBXAa8t/bwHwy+X/fSnfikWDyCnHQG83xbefFBRBcqJOHz0Vytj7VVg6AJgKYoRuIvx4dXFFi1BcvwN7fHg2+ujV94HPsaxuOF4Wdfad/eRHysXc7q4GsYFt2BMlpW23IfnZV8KsWe/G7XPRHNrNpyUimkdcHF/51NvxAz/zjWAlidjsQ5XSVMMNsO9s9yufejtwoA6P1xSGfE+e63qKNOHyyoEqHMAgi4pyLhb1mool4dVrcSbKxfKbmFAl9aG5WuAgpeJ95ugtdkPSb0AcHrEnev/byUg2cLPI8/xrWZZ1zOV3A3hH+fevA/h9FJvFuwH8Rl6wK09mWTaZZdlsnud9c7dlY0XnrbypC0qdbqytmf9zYlI5OdT86slyzJTNsu3uanT6pU4tsvY2EpLllAiespvXoAUHVCy3RnzyZGILG+9HloVmBO1+UOjzoY25DL/z0N8NVpKF1X2lB2u1kfaTpStwGaOZZwFYdiEyOFDhTpS8Bd+PlGOoPFvzII5ZnUtcLj2/CtTS5z1HMrXcrBy4NjwbuNugD4vDBb4S8SxmZAM4DYBRXecBPC/lXiivNdRQQ1c4XbCCM8/zPMuybYM1siy7G8DdANDGdb7iBtWpGxSJ8BU6tWflmp7w/Vi41PNWKeXpBbx6VXl6ocRTambhuyE8HOdsO230U7AFRGNZ766Ts8myg+qwbW7MZVhY3QcAODT1LE7geoGcD6ai34PPNsau1KziaiWaNOU35rKAYuXz+r9Su7salKsBMFXeq77fSvmqkc75vMeppbhBVczz+9cIYBSbLWdFLpQRvlJjBbaXGPl8N4tlihdZls0C+E55fQnADVLu+vJajfI8/zyAzwMFKMsrY0PieTE41XTqKYmsdr+32C0gsg74alNkQ9XGK7vHdmzofn4Ikbu08VTULFoqsigsVz9yQDJ7l4o3xr4EEIFzNjtTUf2sw4pCXjg9Ha+Gc1MFHBM56fV2N2Zzlxw3d/VyZfCcE7ge73nnUTzxyJujRUKLkJJ6yHKj25gr43SWGcN1A6DlyG6gRNiq6LfZmYqAZVRaKkzeEvugoqT9nlhu66bNsr/X1cRGjmNiCbU5AGIglrodqJ6JMHC73EMgYlTiyURnqnZQbHamCt5/SBoKwVnqLP6jWEP+JYBVUXDuzvP8Z7Ms+yEAH0RhDXkLgH+T5/mbB9XfpC9s0hdq3zzEplWwNukLX/n0hcOYTh9CocycBrAM4BcA/A6A3wKwF8CzKEynL5am088B+PsoTKfvy/P8Dwd1Yif6hth4C2xLn9XnNe8FUEGMbRbxlFnYWkMsKdRak/cCiNroZ18HgN59vbAZ2CRDNtfE/LueC/k67Gajpr/UeO3GrP3XDQNAlMHdgzxzsQDA3vuv6Wtq9GJ92PIKg2f/GKPDOyT4bTDJEMtxc7KHj2ZtV3O/t6FbTthGa+McapZ5zgk3C/Vheu6ul/G6j63VfEN6i10sfuGN4fl2d3VbviHDWEPek7hVc+YorSA/NUzDDTXU0JVFO9qRrF9EKhL1DQrUslGqPKi4dcKyZbUPKbwCn9dyFqwF+OIGUHeAAqpTThP6jMxs1thX1key4C3b3xgRWefUkkmGPrRnqCRD2p5yhp7exOtf774eep+skgxpv9T7Veth/3XOyO2kkgzpGD3xhnXr2PRZHUvQg8j35tWp15UsiFD7oO9GHQW9789bF/welDP2nCBfdWH1vJBlnpLTLmygHqKNNBBfb8QGj3XUjQxA7cURdce/7cekohBRiso+283RpuzzEKvewkiR1ZlE2dJKb0u7KAFEKEcgjnNJsv2hvmTtgRsiZSYXv42V6emUbE4OzqHOq3Ux90Le2fgW+g1EwWNKRKciIr0NwBM9tZ1UCEYPzOUdhJ4XtTu/zkF4Vbmobyf4jZ1Qq+yyz2obnmLNLnbvmg22Oigeo5rxSGqhePHWMwCqRLtcmFYPwL+1Tvu3AtCs3sae+pSxvRORG0O4Vv621zVmKH+zTUt2rqiwnbzjeaw9cEPNauPNa8r6Y+eXOWO1r/0Uz+yfbpI2IjvLAPGJ7YEBtc+R1cnZWLxUial8pkB/jtt+e7ae3mIXT41+fWgX9R2/WQxD58NZpEgnNxWM1XvG+rCEts1JohyHjWcBoPaB8pqKEyl21ppq+0Uo90yonr1fY0zYjGRU7AIxF2E18Ryjkh2HeltO3vF8UMICBcZEI34HfIH4o5A4V55iOkLPyomc2mhJyvnpRt3PUqRz7nEmyh15AXu9g8vWpeOw8+xxjd6mc1EVnFcCeaYmBap491PacV2UNkzd+nyRUMZyMZpkiDiBcNqIeLAxl4X0eMo6KhaBH6nNPWpxEtGLL9vQ+tnGUrnpUIxhwJaNucJLdGSm4GTw6HhN1l45PIvOI8W1ic5USCk4fTLHyoFzaHdXMTJToBwYM3P6aPVeVIxJ6SsiXUpZVlMlqmk1LBgg4AuKd1b1l+90GjFZnY6GqqvVX9bJTW8SdR8O9jllTtZylV9GDO33Dh6N9al+UVZXApRRucrnQggCpJ0I1X2dZbYDymqC3zTUUEND0Y4XQ4YVMTxuQe+TPFHEUxT1U/5ZnYnWY8vpdUVDei7sWpYgGroZq+uzTXjD57R+IAacWTHH4hhYt82iTldrzaJulY9Axapb+T0FLKtlUZc5UZm99dFlnPjm9TWAG+fX6ies6ztQ6WkUmKQcgZdF3T5vORObu8PqrazVqh/GwguVOEipzb7buLF2fqyOxJY9/o1/NbTOYkeLIXah83cKcBNYTGMOjVhEFC/Iso+t0p+ALG0/qwHrUVJWE6iCu6i7ND92umcvl+7Zk46Siguy8C8YCXk2p48XL18jW7ENrZ9jsIF/lAg3Jk0fz2oL+8Y3vIATuL6Aape+DrtOVtBzkr6bWO6fqsn17KO2dWbPuVCf+lSc+Ob1uPENL6D3yEwdwdmNA/QAwMRScU19KNiOwp2DgrRbz6JOfZHOw8TS2Ugpyyzqdsxav/aLcPmaDgzx4cbv1SpgrTmVZVuLXXcTevb2OcxgKiiZN+bGMH/EMf1PXFt7NkU7grNogt/USfveBL9pgt+w7p0e/OayET0IAYRkMvytsSEZG2BauIlWdzWcbPxImdgG8tKWD80VTj6Ig9/w9I+xC7IIxclnojNVOiPNRqf6+nxpdiyVfrqQrQVlUPAbLqrx0wCQh/oBhDbs6W1ZVqCANDPYiw1+M356JKp366aX0H54LZS1m48X/EbHy8Xx0O8dLgPX8CMfCfO7dVfpBvZw/+A3D/3eYbznnUXFXzn+9ig1I+dMuQFrIeGitDEiZha20N1T8IR0buN7rzAkxbfVQ8FpAUDvkZkwB3pIkLO58Q09rB2/IXqHQD2XKblDVd5a0z7rn1iqwgMCxTdhFbkIfWzVuCP2i30fdGBZahScDTXU0FC0I8SQi6XgJPVTQFp2r5+Dj603tOnYq61MmUIDAnWgkYfTsOKWddiKooibNjzAl9cHT2Fo+57CCAA+CE3ZZEbhVtdyJevOruKNpyQl/cDPfCMSSSxew46booKnzLVJp9lvZdXJuqvIoXWpQ5eKpUqeuMA2CWYjWci4/T5S3zDnkO/FInftN7rZmcKxr/4L/GX+4pUPyhrWN6QfUq2m4DQaZNUh2I/fazelD/DKedpq2x6QTgxDd2kvZL32wRsP/+4H//X0C9ZHxNNxpLwoPcsEUPeS1XuedcK+M4ugfOZDe/Cedx4NehBP32HxIh6GhNgWq4u5+dNP4Y/+4WuisqqXsqRZ3jzPaI7XigXW4mL7b9+d6md43UNl0gvWWnXUu5rPP/XHv4SNleev/M0CGA7uDfgOVnYBD8wbIpSC2PJU9xannjApjofXrKOSl9+D9+yYvMS/tn72R82RQAz31g//2dvnaqnwdMzqm8GP9MRn3hpS4ekHbZV8nkJV+6ttsB8k7/0SZs4gwFbhp4o9oFL6WW5BUafaB2tmvvnTT+Ern3q7a6FIjclueJwX6+JuOUcdB8keBp77gnLgqmjW+vlbDQGNI9lFgHsrS2zr8Z6xnMYwHIjV+gPVR8KTIQU59zYhW79tA4j9ZuyYLGfg+TzYevRZz1IF+B6xis/w+mEXnRUXuPn9yHu+HqKGA37SZqAei4RjtX4YQAW1t2KTjZnC+qyDIBexFUVSpI5zapnTTUHny8N0kNSp0Ipn3kH5tbUvDs1Z7GhryLDkxe8cdN9e48tpy32FcQOx7KgbkOIrQr3OBpISpYDqY/bMhpGOIrFJDKp/ELFd+/FZPQRQBtvpdmoLeFLKA0W8yImls8UCAiII/iRia4pujsXYqjkApoyoNhWSMGnU8N956O9ifX4UWze9hDN7qrdCjmL50FhIPcBsbNNH61zmvodP4pkP7QnxKnedzPEDP/MNPPHTb47eL+tT3Qth5L3FbkgOlMJhsK5a4qpbDuLEbdfi9Z8tLxw5VisDxH5EIQoWEMIK2jZaR47VrFcjZ4dnFhprSEMNNTQUXRWcxaUgj53uR2onByqHoUhcMOUtQEeJJzn1DqoktUpH27Zer1leyqC4DGhrAwTreDcFc6I0fnoEm52pmnxPXca+bqeYg/JUs7EuSa3uaoRraZUn6Pr8aI2F10zhdq4ohlAkGXv6OjeKuYW/TyydLeeymgs6DxaetnEbM6jeA9+Lh21Zl/nlOC2tHJ7FpOifrCjx+m4shpDoHMjxbHamYjd90xf9Hi2H4/WrH12Vm8WFiCXKknq6gZ4pz7/tQiULaK/b+0AR3LSuQyg3k8Ozrvyrz/drI4KEAxEsHIhl+ZXDs8GrVkl9JorfVZ38OIlw1GcVLKVE8cqDwnsw6YklD3BVbFYTsiFSJCnMqhV6knI84d2hf0eOYdd8jL78gZ95Ck8svLmmR8Dh2QixOv+u57CEvaE+RfTazay32A0iWAW6Q0i6/cyH9lSKYlTiEAFXrW6s1Ax+M45+IoDPTPT51pFj4W8FNGbffgnD0lWh4LyUZJWl/coBdYyCUj8HN5KVbb0I0P2Up16f+pUJ1wdE4LIxNajIsyhUD1eiGxv7ZZV4a5Lx3dP4K9lAzIRrjz19Hc7sOYf3vPNowGGoNcbqXixcvLW/E8ygaj1hsOC9918Txrt0z9sAwEVJ2nnup7NQMyevU++j0bitVZBzE9owUbCs1dAL/NTav71IWVclZ3GxydqxPbLX7YuxdVlzVyAxdU0snRVIdnx9UP22Xs8JL+o/qk0gcCr7qzgZG3NV3pCNuSwo3CL8RnlSWlAYIfakIAaZ3BjkEtbnq1N1qXTAsr4a7W7lLEZlJhMRKTR8YXUfWg+3CpPsu57D2gMxBHt9fjaMYW1+FOOnM7S7q3jPO7+Nh0DgV44ze9pod09HqTNZnyemRqIDUNuIVUTwklhpDthwrXwnpJZwvh5uyMXfGGDiyGgTz6Khhhq6yNRsFgMo5b34StdX6B+KE8HLlHWh9W+X+vVhEPWDoF8o7TpZQMwXVvdhYXUfDk09G+4tLk+HbGapvvCUZ6rFfu2wvguZ881Sh1RwVNX4berDFG3HGWy7jmOWdoTOoslINjgjmb1+qTKSPXfXyyFY8MXMSKbE+5qIR+/ZOqy1SH09rI+LDWIEFC7yf/QPX1PDoTDDmLVEaBoH7b/CwK1C+pkP7QGAKFao0rc+MYn9MyshTKAVF9RnxEs4xZQMrfe3QtsnPvPW4LMS+i/9UX1N97ZrceOHn6yB3449/xn85X9dvjoQnNuJ7u3FrbBKNBv3QtvwMqApFp9lbRwHGyMjdZ31BW23QQNqdO+9918TwbX7+awoxHcQwo8bkPVVYBYrTzFnFyR/28C/dMDSeBhUDFoiNF77qrBszyHM6kIshJvjU2AYUEDcGVNDyXIVFnZv86TYDdPmYgF8hK32zTuk+BxQpSqgkxuQ9h0ipXyDrOOb3Yh7i6/C6N6XklJh+YZ57nwUnJ6Phff3+So4U6Sbo/WnUYcwAC5E2sKoSZ7IoeY9tmURnAp7txYHtqc+MAAixykG/F1cnsb+H/9jrL33Ztz78V/BPR//gFs/+0orhKZ5ZL3z9z4erCBn9pzDr/7w53HPxz9Q4/zYJy86u+eroWZpjks3Qm9T0bI2CBIV1Z43qo4dAB5/4cGrI6ze+dIgc+cw1o2Uf0XLcCup55SrUf+KNS6UxSq0X0vAOdRNR67o7705cEPTic2GH8aabCxeX/ttINNHTwW4cLgGBOhwNQ+jtTii6xIyTrOSe9yZQr3Z1szCVCm6iQUFiMyHSee80nLQ7q5iX7fY4Gj1GJvLwnP3fPwDuPfjvwIA+ODnfxIzC1u1nCbETaw9cAN2IT5IW/s7UX/uOV7U94vvf18ow01gXzc2o1siBL6NOEQfQK6oCjNIrAzHaLkWdanvLZaRzQOeo9po3PAJ28ii3ig4G2qooaFox4shl8tFPSV38qRMuajbtPap4DcahyHFNqo7umUnhwl+Q3HBCzGXEiWsSKTss1Wkqd6FSjpluVMiRKjDJFrieL14JJ6Lug1SY9lxJRsj9XN3/7sgQqSeVz0CdRY2LJ7GagUKxSL1DZ4ug4pQIjY9BKaXV9VzDdB5sUhcq5TWe+qS/63f/BdXh87iSgp+Y9vSF+al1wPicPL9FGKaJMgqBFmu3wfC8kA6MbJaiRTm7C14rdNz2R52rnRztRu2vjMtR7K6BpJnDdHUjKozsCIEv42le97mRq6iEhiIRT9VXAJ+usY3fenbAVUKIKRc0I0VqNzgrdi1fKhICsVNBogDFOu8trurkc4FKFCumlwbKL6/b/+fn8bWc1dJ8JsrhYaJmXEhcO9hc1B4fRqGBpk+7SawHZu9VV6qJcZyLh68W+sAYg5AOTQb9AaIN2gvb8jP3/fvg9JT55m/2V4q+hXd2TUXrRdPwz7/4q1ngsXrzJ5zbhJpa9Ui6SZs871qRC97oHzrE5PY/ej4la3gzMZG0Xu7n0jlSksFQG25p9mPcp0mFlud9az+B6oQbp4WvBYzc8Cis+2y7ijd4kVIBcCI4lR8jp8uRIiJpepE3ffwSaCMBaHvn5vl1k0vhSjcnUeqfkx0piIlqfaFxPo8T1RVet755btD3Ww7zG35zahpGyjuM+w+aWZhK0TEAoDdj46HfgQu6NFxLB/KogRIAEIMDADRe9iQMHkcx/r8bHiX7BcwixdvPYPpowxdWClJdz86Xpar6j33S8NvAY2Cs6GGGhqKdgRnkaImbwikn1XeEJ7eV0rekHPL7cBVkKaPFw5bw+YNObe8Z2DekGCW3t8JcTp0nFaZWXBAU7jzy3cD6JM3pHQX7wHYP7MCAOhhxlXckhPbP9OrOa2xXfaJWeba3dWQ0FhN3ax/+milE6nlDSkjfe1+tAJfTc6sAE7ekOmjpzB5Rw+9pZlQ7/O1EaSp0VkkyFOQAsPhMrTsIOQdn/WsO6p09WTlfvqRVFuD8mKm4m4qcIjkiSGeviEVD9KKC1bE1HZTwDQVxzbmshDPQrOBcUwK0+dYbfyJmz/9FJ746TdH7L5iXsJ4P7qMpcf2BjGiXzyLfnFcCcBSxaW1NAH++xsmnoWHxdENq0kF0KQCCH/bj8wiLZtUAE0qgKsmFcDlpgbuvXPg3jaeBRejIkY35rIQAAco41m8Px3PwsM40JdEExmtHMijDPPLh8ZCfd4GYq1anvI+hZ3guD306jDt9DsUtY3t+obsaJ3F+ZLqAFL3dcKA2CGNRN2HaqXn7+0OxfFovfpCKUtPQ160vERaMIoM67Fugn2YWKpvBKxLZfVpVB9iyyxmBWcBxcm2fGgOkzIGau8nluJTcNfJPJghK2/LagzMDq+WFEsaDZxlgUq/oNYF21eG9aMvB6Nwb8wVfZtZ+G4IXAMAr8dp7DqZY+mxvQHCzQWlm5CG0tMAOk888mZszI2FfnMOtD6ds3bQl5XvwdlMlLwwfDMLU66YqZaTfQ+fDNwfXdo7jxTvVyHipOpdlO8KAF74et++KTXWkIYaamgo2vFiSJORrMlIxjFZuHeTkazJSHbBNIzXqYd29Dw5lXSiU+X6BZpNKUs9olLPBpVV4NWg+r02UhnJrIKRZXu3HPSTDDlJhbmJhiRDZf9TIqH2g4pcuzkq4M6zFNECAiBsHC/eegbnlhNJhkpSJa49OKaPngrBYzgOJhnSQ8uD61vxlvV6ugXPwsH5Z+Jm1mVBiToPVr/BOm0b9j209m8vYO+O2CyaSFlNpCy9Z+toImU1kbICpTYLL3KVNUtRyWXzUOpC63cCKKzbg4Grcs5blHxe2Vqgss3zFCaloOzeB6KkCj9ritQ2UtyKLlDCj63PifUzePHWM5Hzkd1YPC5ET0Td2JTGT4+EMXzrE4VKlVG6UuIbFwuAYIHQxcZ51L7o8xTxFGfBOSRUmovZ4jeUs/mnX/kygAImTsuJio/kpn7+vn+PD37+JwHEZtGUZ6t9T+wj26dI2frocrDoWL8YoNjgb/70U1h44zVRcic1Cz/x028ObfzhU58bmrNoFJwNNdTQULQjOIudiLNoEJznh+D09BMW1XihCE721+vj/Luei1yzFcEZZf4q+2r71vrocsBlKIKT+iqKC/d+/Fdw55fvxo0ffrIW96OfspKkSmgANcV4ymVfvwOPMwkciMOp2jb3PXzyyvM63YnExZVKDZgqT/IAV/a6VybWjhc4B6tItIs2Bb7yrqe8XVOafQVl2aA60UKnx2ipiScVOA0/+A3bAEpxDgcrHAoX2KG52kZh+6wWpCUUG4XG4Jx8sFhkv/rDv4J7jksMzv2dyDNzYulsAeHGyWjTmSjFjPkjFfL0zi/fXcTgPP6BWt9UNGY/UyL2DIq6w6Zbigv0ytU5Yt2WdL4pRjJ0oYrdLOfF2xiGrsrNYhhrCKmJwVlRE4OzicHZjxoxZAAN2ngudX2eSbcfQnU7G6XSIJOvPuthPUgeWhPwWWag7t+S8nVQvwwiFpkywEbr0nq9U13LaOAallEl7aA6gCKADjcMVax7sHfWQ2vW5B3PY+mxvRGuxjOXa5/7KUXtpmqxPVZ8vWpMp9u1hqRCz6lcaE8nlfGUbfOcrKy9G6jwAfakBYodf/z0SHR6eSdkP7OkZ0akt2QVTGZkoB+BjjfFhlLk0ETD1rTs9VH/VrOy1mtBRnR2ItGq4I2Z754iwPy9j7sgMMA3ndoNgcS+aj9Ytwd6I8iM/dX7P3/fvwcA/LPXvKGGTSFuY2RmMzIVq+6GuhCWt/P9T7/yZbz/D34CY09fF9pOmYT1PdKaRX2NmoU3O1N4fPGz2FpcaqwhDTXU0MWjHcFZXKiLuuUKLMrNg4p7ikYPocnrpH4sumc5IQsNpHN8elgBq/32ArcMgqx7/VXOaVCE755RVvbLvNUPzKTtKSnuRRGgHgzai8LtBbb1OELbD6Di+tSN2yJIPU7K9se+i5/79jdDTE8SxQovO5zCs9muBeKplUoVzvP3Ph44EusZrNHHOTYdP59Z+sy9V0d07yuJrGWjnydq6j7QHwIO9Edppiwvw9AgBKYHyBqmD0DsN6K0nYC9qTb1uhe3YlAdNn5Hv7GxDo5FXeV186DSk6kIAdTSLDJ4DoBow/ZEUhusmOKnrVPr0L6S7IbVOnJsW74hA60hWZb9GoB/AOA7eZ7/nfLaxwG8H8D/Vxb73/I8/93y3s8BuBPAywD+lzzP//PANhIBe68kBOcJIjhNlGVFVyr304OP4EyZaoNcfWguieC0GAUNeXchCE67iDx4e0BwmkjX7e4qToRFU+lYGLawQnAWliDvQ293Vwu48huKEaUQnBOcW3mP2t/lQ2PB2kE9yq6TeXDu2j/TAz6J0L6H4KRu4p6PfyDUp9/YrpM5fvH97xuM4HzgBuw7mk4BwT4CiHRik3c8D5SWHtU/KQfxpi99GwtvvAbLZiMEpvCmL30bT/x0OU+3HASeii1V/WggZ5Fl2d8DsA7gN8xmsZ7n+f9hyn4vgIcAvBnAHID/B8Dr8jx/GX3oQjmLFKah330vqM0wEbG0vFdPv+f6nd6DytpNa1D9/frgkW6unkJz2OjeXpv8kBlzAUBN2ecpFIHqBE+F19eES4Pg3mphUCU44d67Hx2P/E08cUfzewAIymYlijifu/vfAWDU8DhvKTdJbZNtkdQHhH5GKs7pIXfiM28tnnc8aYF6mgPSM7/96YsH987z/GsAXhymMgDvBvDFPM+38jz/cwAnUGwcDTXU0BVOFwLK+mCWZT8B4A8B/Eye538BYB7Ak1LmhfLaFUdq/1cahFOwYoQ+zwji/L+fO7yy/IBz4jjAMq3fth0QnKkIYvs7NQWcKoqt0jDcU4XwkWPYdABINiwe72YmXQAAFnpJREFUAGzMXQeggiVDFMQqWhCEtmt+tnZaBhFI0KkBDOcMcWLpbISUJFEsC4rKklOIxNqyrDWZsj4tu3LgWux7+CTu3FNEDf/VH/48/uVnfzjqy7nlNkZmNkPkM3JtkQhVjm9kZhPTRwsTaLuLIOoGdwBgqIzr3dvqJuSRs95M+XS+m8UvA/hFFELoLwL4FID/aTsVZFl2N4C7AaCN6/zODWsNIeudsoZw4Ys1xGIc2qjjAbx+hOecMtpWYOkRs4Jt1tGZwlLQpaTh1l76Qmv9aJv2Ql1G+QcUiEyOw+qE2t3Vgt2fr8qm0hcGoJTOi6MIBaqFpEhEQqj3dTvRfNn5VTARqcpZOhq1AyAgY7UfhSt8fSEVLue1acfGXBbC9AMV9F7TF3IeCpoKnrXTx7OQqIgL+F9+9ocjnERxbwvANeCGGawaEqCZG+brup2A03jdx9aiwMWdR84Wa6Msu0n911evx/oDlcgyeV8PN37/kwVqVvRym1+PQwT0o/PaLPI8X+bfWZbdB+A/lj+XANwgRa8vr3l1fB7A54EClOUpOFXh1bvlYPg9MJ6FLCYrw3Nj4EKdQfWsLgjWafH1AXjUjctZfUGhsa78O/i8/s9FqWTnIASQsQ5moX6ENmz9SuyDnt6MxahzUwCyig96ojMVpRm0G5o11XqKUDtHOo9bd01is8wiZt+n1rlrfrbG8ew6WUdJpmj/zApa3fhTb3dX8dDvHcbrcbq22XgpEFnPZqeKR6E0MrMJAJg+WsTHsHP1/j/4Cdz3lt/AL97/PnhUzeVoqFsPqZGZzeL5zvvC/ZGZTbS7axEXxYPyW8uTGJOYouG+cIPT+zvYPf6S2x+PhjKdZlnWAfAfRcE5m+f5qfLvDwN4S57nP5Zl2d8G8AVUCs6vAnjthSg4X21h9WwEa6us7BcNy2402wmrZz1Obf12znqLRZoCHa9naaLlpp/Wn23whFVfEvv+SAxRRwWh1um1Zb1madbUAEUeFgIAnrvr5aCMTeEwUmZKEq1mtKZYfxLFSViPXPsdDPIgVgyNhZxbxOt24lkMYzp9CMA7AExnWfYCgF8A8I4sy96IQgzpAvgAAOR5/l+yLPstAH+KgjH4qUEbRUMNNXRlUAPKukjUgLLSpKkUlKzfyXaympEs9iblVGZNp0AxPxZ3kuJMrO5Hnb0Y3i7UW0azokn23HK7BqBSHIZyACpO2vikJIs4VfOt4k/sOBi0WOu/qKCsK4EuBc5Cr/era9AmYdv0XNf1b4Wbe2W9vlrxYJjxWmodOQbs7wRlHhDjKSBiBn975C00lcdJG3NZlN9Cg+dsOo5cFv9Bpef6/GwY52RpJVKLEMsXepIYqLbZmcLe+4HlQ8QmFPV7zna0UuhmRJd+uuIXdZzCs4/txb6jJ/HirQWWotBnxIrED37+J/G5u/8d7vzy3ZGo4IkZZ/aci5zOqBTmvFhRLSX2MZdt2PA6U9sCZV0Vm8Ugl28XgjzktX7xIIb5be9pfdupV6/3bjkYlFT96vfq67dp9Ba7IXYFqd1dDXEngkkW2+MuqtO/+oAnXLV31ab2idYebixcXHZBBCW4XNN+qgkUKMyn1kvWW2SbnSm0Frs1/dQMivom73g+BOIt5nkOm50p7H60ChYEbNXqZQCdD57+ycA5sI/aD9WrWJRuKON4qtqxk0JdR44BE7WqknRVbBaXki5mLIvt1GcXvZoUW91VF0cwTP2DYl20zEJN9ad15Jjfh76cRUGpFIxBie20OyH1qjizMZdhQhSBRVTrucihipsoFzj7MH30FM7sORctsMINvS72hA1a+sH6lh8bw/yRx0M5za5W/F+NjeICRYgPnv5J/Mk/+bf4/v/xztCHCBZu5gb7O9FmunJ4Fs/dNRlMsnS5r0Sbamxbd03iWUhk+lsOYuQbX8ew1OgsBtCwwWqG1Vl4YsUwNIxIYTmLYcQqrXOQeOO1nxKBLKX0AF5fUxyetbZ4HrkW6u15ifI3IeQKn/bigCr8W09leoumAt1oWwpbB2LvUAD46n/4VQDAD739R8J8KVfgpWQAKpFJYegp72bb1425DM//0qea6N4NNdTQxaUdz1kMg7OwcSOIF7AnLSM5W8iz9TQFqt3cxo+kEs5miLKejt511mfDxPGk8PAQKdg5x857POUUK+Epu6jgYhJgnkLEiHgYDs+xTE879t1mGuc1RtS28+hZXTwnLipZLZI2Fc3MGwND5WnfWL/9lmzfdB5TfSZ5CGBiUmxKRc/69H9/43fw2t+/A3vvv6YW44LPkZTbsONXt3agwplY0e/x3U9iY+X5V4815Goi9cyktYAKtotBlfwff2hnbtsT7itR2VahPqvf6/Oz4dr6/CzGT49Ei2djLsPIzJm+fQl/lxtqBbU2QWKkvIbv181YRQhdQK0jx4Db3hqsKCSNR8m61K8k3Ds8G1mFSAquU9GotoBLPYYHrtL5BYDX/v4d+LN3PIDX4g6MPV1aaVBtQjYUYW+xixUJOsSNku15mfciV4hGZ3HxyJ4y56ugtPUNMnHaE105KwC1E8Lrr1dvP52FPcGVYwFiWdyL7WHL85mk85qQpu8DYoWgrcOLsQkg5F9VBeiZPedC2j7NjGbT/mk/6HuisSAYw1K5No1i7lkjSB6HqFyMRVU+d9fL+LN3PBApPUneZnHiM291Y4yyn0A6d8nxb/yrKytSVr9cp3aRWAWUx8pxIXo+CXZBeAsEqIAw3j3LDitGYOmetwGo8jd40aBYh9Zn2WMCbVSk4jywT5GDmmIiOHeO0nAQ6Mkq0FSc8jYy+7zdSLzExrYufTf2b/v+eX8QXiU1Pi9uhJ3HfopiKw5oOED2jeU0zoYX+tETf7nZzSxsBaXn3/nX/3PgDKz46m3kTEJlEyavvffmIH7yme1sFo2Cs6GGGhqKdgRn0UTK8uvVE86erB55nNSwpG3Y56zSr9+p7r0DzXhO4unZr04dk6cQtikTrfKblKoXqCuVeS/FUaYcA5Wj4NjorEbXciXmPmFkq1TIRgD4k3/ybyOTqoaJLNzUv+uaZNV5rt1djaDtfAfbCdi7IxScFxqDc4l5Q8wCJutJd/T5e+vsb8gbUj7rtU2KlGllecq2XoYumzdElVraVrTA5V5b/tc4Ga0jXTdviK1fScfr5Q1p7e9grVw4W3cVMOWQN6Rs3/axd8vBKFZIq7uKpXve5tZPuDXncbrU2DObGGN6WIWfzg0XD3N7BHlfNlLPmlHkDan3h2z6Rlnvs7fPFV60nalYhCvrP5HIGwIgZFf/Z695AybKvCHTx5k3ZK2WN0Tzt2o8C83sxoX+Q2//EYmHUb2/N33p28A/LMZMCDhQfCPLh8awddNLaD8seUN+PM4bMtGZwrfnYhh6P9oRm0WKLLiEv208ixCTwsiWlEGJ2lM9hjrj8Nn4xK9OEIueLOJZdKLnq7gYRdluGcB3Ymkr2hT0I/TS01kiCo/9oi/AyoFcTqWt0PdBYC81p1kOZ2LpLF689eWABlQU4LBcik0twHrZHlBtNls3vRQWTz8HOi4qhYhbpWA/uvENL8D71Gl5sn1WnxVbT++RGbeN9//BTwAAXre/iC9h6wzxKCSehfbfArmAmMvw4mH85p8exOtQbAbKTU0DePETBapz5fB42ffni3tiKm4DFz+exaWmi5WR7HJG9+bmQPKie+vYgFh55+UrUVIteCq6t61fiX0+n+jeOqc6DquIZCYujXFBjIGSBtSponuvuYpP9v3Z2+dCprS9918TKV5JVgluyYoLVB5zbrl5eUr0ICbdV0UYV+V1LZDvHc+HfKv2u+TfXj9VzPBEiq/+h1/Fa3//DgAF50cuSzeZyTueD5ngSUHReV8v9Gti6ey24lnsiM3iYptO++UC5f2UKcuTl3XzsgFiUhr4lJxLsgvv/2/v6kLjOq7wt7Vsr+otbK0tslfEWhRT3BLstK4SEjdQLIop2I8mEPxQsAtNoBTShz6kj/JDH1oIggbqBNTYFIyhGNxg2uI8xTGpU5NAqVvXXlaq5UiNHESQXCndZvsw98z95tyZu9eObW2k+V6k3Z07f/femTPnfOcc33ehYCwAMlaPUBtsjZCxM/FJk8BCJkpdv8yFLASyk2rCGuDXWQDwWhGkLS35aWnSpzOShTuUL1WPgSnbgGu25UVEyGpiURDooDvSB9FFcEAbnZRYjmv6GQPgbG5Sp/x/bbyKf35nEoA5nshcyULK8US1fkPnoY3WkIiIiAeCnpAsYmLkmBh5NRMjc3Cee02M/NQv/wwAuPz4Bnsc06QunStFoKVXH8HrG7+7gdN/2+skRn7jrbMYO3I0wzGa+enThoy2+yb6fmB0NdfGq/jqzxZSJS7Me3Jxw+v4+B9z6/cYshbRzTzcywj5m9zNWEKerr56tb7D9z2QzffKR9OQ70roWJZH9/YR3rRfjfZ8BVJWK+uktBn9wqnXMHbkaNDr1SGGvTSH9vFBp+zdJBnqaWvIveJ+6Cx8HIc8nUW3OBECH4OPH2if0xsHuwmNzacY9O2yms/g4yzkMS0ZoksA3BR/2h8hw3totjKxMHyMW24nRF2XXRxwWbMCy7AFsOihaNeQQnQSNQBtuKZaG5xYWbPkRWY/Eq4PMNaJtow5GRs/R9PHqg4PYz6RGmtXzOfGuf86DFwe79iRo7hw6jU8etqE6BPKu/WdoWdsfvIRYMhVuD6MvCFrHvbhBYKBZnR5RjcFZ99Iw3IUnBc8qUcUgrXEsYl3E71g5LWxkJg+WcG5MLQJlcaA5VUAwHAr60DFPAqNxaFN6HuzZTkKlZm0vGjxZZHSmb4FfJzoa912FjVWcHIdMjdiJm4jPRKwMldHvpbPOhamm77wKWehEdNq30jD+GHAzSnK9cl9k6RBRtG5zZbRjoAcM3Pz+1/E1OE0eE3t4geoXVRHx5ZZ4BeHNtljIs6Y+/Do6R/ixrMmVeKTV57HR9/7DyoqGnm5ZSQUE+LPVXQWRVRwRkREFMKalCy6eTn6QsLZ3ZQkAmYRmr9wXKX52jwyVDdqt6QdbCPdoZjx6BPNi7ZhTXb0XRruzSU6dYPbhumPNpm2my3LpJU2K4mC0kfYYsg8MpFO91n6Ye8THWmknaruayLFlVtZic/MT3qUEompDKBxbsD2S66RMYiiWN83kapY2V1u3U4zhSUQnsxyY8BRsvKzJNfrREFiHm033wP2bceuiVk8eeV5AMA7P3/FKj2F6Sv17pow0sqFU68AAA5cPYjO68WIbUCPLBafle79IEhZCyFSltLUy/XXNSkL6E7KIop5t3gVHIdhy60OauR1WoiUlfxtJol5ZDwspoq465Kywn3i2A8CdpeW+3D90EYAHcx/0/hK9M9+wY6hecyklclrBzCWCMPEBOYnH0ENfkWpZouasaXBekRHIRYaPoZUB+dROT5oFxLLv6AXXawel158wknfyM+JWC/+9Itvp3OV6HMWrHJxwD6v7A7Pmw7zNKQtJnuJJY7HIDqMsSNHMT1exdbzsPVOHa478T4BoPMlf+pQH3raGlKE/ORTimkXdG3e005TPmelULtFHMUAVwPucyUH4F3EGGKKzDMLS7mQizn3B0Bw8WXTp+xkwur05TqVOrvFcZDvfPPIZlytmOR75jP3cj+LmE4lfoUTmuClOWtaFIjpkduTvrUObcxE/ZL6fEpd5/k90UZzruYE1g0RsthczXOwsueOowiVcTGkPlF6SlrFZ7/+F1x68YnM3L7dnMBKc+bzYw0JSRYL9DCLYs4nWXR7oVirjZGGsyPKqt5utuxuBaRSTcZk13BFU82z4B3G2OXrGZ6F7PJa1AayKQjZd0XGVD15Cdi33Xo1chshRzJ5oYRbwMccaZclCgBYqte9PAtdJ9fBPAuW3obPpOVsH0fr9t6EXh45kvDiUD15CYOXs5wMvTgJ+mfrGVZnuXUbU3/cgS37Os4OXm227PMgqFE9wljVnB1ROpbPmFynczQPy40BLE5uwmYy00pfZdGWueT5Zh7Kyp47VhEqdezcfRMLVzi1MND3ZgvT41Wr9BQp4uzoM8CoqWfkuWRsjQGgXVxtGSWL+yRZhKjiPvdybg9wzWg+nwh9xOLfpe2ieTF5LnwEID023w7uk6p83ATNKchzUdfxQvl7HS8UcHOXar8aPefcBy2x+LKB6fiV0kboPjL4Wj1eHYOT62HkHavZomR1Jso3BDAL/o5XN2QC6Ohyd8OziNaQiIiIQuiJY8haAJOKAHItB6xSS5OFZJeoBXgSDLacAHIMS12+Fzwu28ITAfUhzx3eSjJDrn5D913Aklgoo7fUIzEsbH2ii6D++OagMvMJluqbszEkR+uOAhIw1pewzuKTjBQg8R54Tsw817MMzP17bYRwAUspciRsnGM2aColVclblaElY18U7nIyhp27/4Ua6ViujVex49W9zpFSJNzv/uQGzo4+g8defgFAGkBHW4RK212dRx56+hgSkUL7pDwodGOjFrleQx+7RCTn2Ard4POAlZfM597vU676jpnssp+nrNXHOSDVa7G/hS/xEKdDkOvZz2Rlz51McmYAjg5p5Ln37BhZWS0u58JM3TUxmwnIJGN5462zeOzlFxwd2ts3T66vSFnrIZ6FRPvC6NMPPJ6F2ObvJZ7Fddp9pYzZdbcBEMe3dJ6av30cQPd4FtcPbcTO3WZ3XpxMXffLrTSVI/dFFNEiXel5kYVj6/n+1HT6/TbaxwftuBwqe9K3UTKdCobP3MI8MUxrFz9wTKe7JmYtF0MkPJZ0plBHZYYlEgORPLee77cRrton2sCk+X3qcB2Dx1eAIVirx3JjwJpHV/bcweKt/qReo7f4649/hbHLqen0038XXwKiZBFA6KXtFudTl8sja2m/lLzy+mEPRfHu1lbouKB3aSmrlcPcHx27IuS34gt3z9dI+3mLhf7suw++REuheeBjIy8KfL2z+NA1gEvKkt8A1wTsS5Tk+Gp4zOs6SZRApDCmvYv3MW8cTMri8jwmUXoeuHoQ7+z/DT7ufBQVnBEREfcPPXEM+azo5r7t+90nCRQxkeq6fG7SAIJBc9nkxtf66mUP0bKqA56dUx8NuO9Sf8gxTDgkTp/INMvZw6U/bWrD/u/pVxvuWVz6ys502hvWx+1wvmtkw9L1JUpFrXdhb1pm6C7VSxhupeK+ZEITL18bmBhZZz3La0mkL/ltqV5C9WTWkY2dAmW8lWQMy/v32j5UacycWrKSHKccAppHCjtw9aAzR7osl/nD136PL292Tal56IljSF6SIZ9SS7MXffZuH6ORy/rSuvk4GbptwA1zphcAKZsG7M2yErmPALz8Aq130d///UfbcsPIa4TmVL/A08eyAXt98xiaL9+9CC1iRpu/wSnrq0OzOyUatk5qJL9l3PJPtDNMTSANiqP1SBwBm+dO4kHwGHjeAKN70UfGcsvEGmUWpW/MgD/oksyVXG8X6BOpjsWONdG7TR/7Hz6dK6desQlbVSuEP9wygXffX/78BL8plUofAlgCML/afXnIqCGOeT2gl8c83Ol0vlKkYE8sFgBQKpXe7XQ631rtfjxMxDGvD6yVMUcFZ0RERCHExSIiIqIQemmx+PVqd2AVEMe8PrAmxtwzOouIiIjeRi9JFhERET2MuFhEREQUQlwsIiIiCiEuFhEREYUQF4uIiIhC+D/6uMRPO7llogAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fddf88e8b00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman edge kernel matrix of size 183 built in 8.728142738342285 seconds ---\n",
      "\n",
      "gram matrix with parameters {'base_kernel': 'edge', 'height': 9.0} is: \n",
      "[[ 20.  10.  20. ...   0.   0.  10.]\n",
      " [ 10.  30.  10. ...   0.   0.  20.]\n",
      " [ 20.  10.  20. ...   0.   0.  10.]\n",
      " ...\n",
      " [  0.   0.   0. ... 100.  70.   0.]\n",
      " [  0.   0.   0. ...  70. 100.  10.]\n",
      " [ 10.  20.  10. ...   0.  10. 100.]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fddf89a0048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman edge kernel matrix of size 183 built in 9.403308153152466 seconds ---\n",
      "\n",
      "gram matrix with parameters {'base_kernel': 'edge', 'height': 10.0} is: \n",
      "[[ 22.  11.  22. ...   0.   0.  11.]\n",
      " [ 11.  33.  11. ...   0.   0.  22.]\n",
      " [ 22.  11.  22. ...   0.   0.  11.]\n",
      " ...\n",
      " [  0.   0.   0. ... 110.  77.   0.]\n",
      " [  0.   0.   0. ...  77. 110.  11.]\n",
      " [ 11.  22.  11. ...   0.  11. 110.]]\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fddf88e0ef0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "3. Fitting and predicting using nested cross validation. This could really take a while...\n",
      "calculate performance:   0%|          | 2/13530 [00:00<14:18, 15.75it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ljia/.local/lib/python3.5/site-packages/sklearn/linear_model/ridge.py:154: UserWarning: Singular matrix in solving dual problem. Using least-squares solution instead.\n",
      "  warnings.warn(\"Singular matrix in solving dual problem. Using \"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                                                            \n",
      "4. Getting final performances...\n",
      "\n",
      "best_params_out:  [{'base_kernel': 'edge', 'height': 4.0}]\n",
      "best_params_in:  [{'alpha': 39.810717055349734}]\n",
      "best_val_perf:  35.13329422064896\n",
      "best_val_std:  0.7832828899376076\n",
      "final_performance:  37.697602888271526\n",
      "final_confidence:  6.917076511859134\n",
      "train_performance:  30.10471658333036\n",
      "train_std:  0.5666874899231609\n",
      "time to calculate gram matrix:  4.349034786224365 s\n",
      "\n",
      "params                                                        train_perf        valid_perf          test_perf             gram_matrix_time\n",
      "------------------------------------------------------------  ----------------  ------------------  ------------------  ------------------\n",
      "{'alpha': '1.00e-02', 'base_kernel': 'edge', 'height': 0.0}   49.55±29.71       84.81±62.30         83.10±69.42                       0.84\n",
      "{'alpha': '1.00e-02', 'base_kernel': 'edge', 'height': 1.0}   57.14±115.85      101.64±220.27       115.57±320.98                     1.8\n",
      "{'alpha': '1.00e-02', 'base_kernel': 'edge', 'height': 2.0}   41.17±15.40       69.60±33.17         69.69±38.03                       2.57\n",
      "{'alpha': '1.00e-02', 'base_kernel': 'edge', 'height': 3.0}   42.49±13.37       71.04±30.47         65.16±28.23                       3.47\n",
      "{'alpha': '1.00e-02', 'base_kernel': 'edge', 'height': 4.0}   70.30±107.52      137.29±269.14       119.54±173.83                     4.35\n",
      "{'alpha': '1.00e-02', 'base_kernel': 'edge', 'height': 5.0}   40.83±12.73       70.09±37.93         65.95±34.58                       5.18\n",
      "{'alpha': '1.00e-02', 'base_kernel': 'edge', 'height': 6.0}   53.81±67.21       93.79±126.55        105.99±195.09                     6.32\n",
      "{'alpha': '1.00e-02', 'base_kernel': 'edge', 'height': 7.0}   41.18±11.58       65.63±20.34         68.25±31.41                       7.08\n",
      "{'alpha': '1.00e-02', 'base_kernel': 'edge', 'height': 8.0}   808.40±4147.37    1438.75±7364.03     2314.42±12184.30                  7.86\n",
      "{'alpha': '1.00e-02', 'base_kernel': 'edge', 'height': 9.0}   62.14±96.18       98.99±147.17        109.28±213.74                     8.73\n",
      "{'alpha': '1.00e-02', 'base_kernel': 'edge', 'height': 10.0}  40.00±10.65       67.47±25.95         64.36±27.30                       9.4\n",
      "{'alpha': '1.26e-02', 'base_kernel': 'edge', 'height': 0.0}   58.16±73.04       101.23±140.79       86.85±74.37                       0.84\n",
      "{'alpha': '1.26e-02', 'base_kernel': 'edge', 'height': 1.0}   41.53±32.22       71.26±67.01         72.57±90.24                       1.8\n",
      "{'alpha': '1.26e-02', 'base_kernel': 'edge', 'height': 2.0}   41.44±16.81       70.03±35.29         70.07±39.51                       2.57\n",
      "{'alpha': '1.26e-02', 'base_kernel': 'edge', 'height': 3.0}   42.28±12.90       70.45±29.62         64.36±26.89                       3.47\n",
      "{'alpha': '1.26e-02', 'base_kernel': 'edge', 'height': 4.0}   57.66±66.16       104.73±147.17       100.94±129.40                     4.35\n",
      "{'alpha': '1.26e-02', 'base_kernel': 'edge', 'height': 5.0}   40.57±12.36       69.61±37.82         65.47±34.41                       5.18\n",
      "{'alpha': '1.26e-02', 'base_kernel': 'edge', 'height': 6.0}   55.93±77.91       99.94±160.71        110.97±222.84                     6.32\n",
      "{'alpha': '1.26e-02', 'base_kernel': 'edge', 'height': 7.0}   40.97±10.94       65.36±19.91         67.73±29.94                       7.08\n",
      "{'alpha': '1.26e-02', 'base_kernel': 'edge', 'height': 8.0}   657.80±3301.60    1169.35±5860.66     1863.72±9701.59                   7.86\n",
      "{'alpha': '1.26e-02', 'base_kernel': 'edge', 'height': 9.0}   388.32±1873.02    591.13±2826.58      844.72±4225.81                    8.73\n",
      "{'alpha': '1.26e-02', 'base_kernel': 'edge', 'height': 10.0}  39.83±10.31       67.10±25.07         64.05±26.55                       9.4\n",
      "{'alpha': '1.58e-02', 'base_kernel': 'edge', 'height': 0.0}   43.76±14.02       73.03±27.84         70.54±34.05                       0.84\n",
      "{'alpha': '1.58e-02', 'base_kernel': 'edge', 'height': 1.0}   38.74±18.63       65.57±45.38         64.93±52.75                       1.8\n",
      "{'alpha': '1.58e-02', 'base_kernel': 'edge', 'height': 2.0}   42.17±20.25       71.35±40.84         71.31±44.34                       2.57\n",
      "{'alpha': '1.58e-02', 'base_kernel': 'edge', 'height': 3.0}   42.63±13.79       70.95±31.35         64.08±26.01                       3.47\n",
      "{'alpha': '1.58e-02', 'base_kernel': 'edge', 'height': 4.0}   53.94±59.50       95.70±128.41        94.58±119.64                      4.35\n",
      "{'alpha': '1.58e-02', 'base_kernel': 'edge', 'height': 5.0}   40.32±12.05       69.19±37.95         65.02±34.38                       5.18\n",
      "{'alpha': '1.58e-02', 'base_kernel': 'edge', 'height': 6.0}   79.48±201.98      161.26±489.69       173.14±553.86                     6.32\n",
      "{'alpha': '1.58e-02', 'base_kernel': 'edge', 'height': 7.0}   40.78±10.43       65.15±19.79         67.25±28.57                       7.08\n",
      "{'alpha': '1.58e-02', 'base_kernel': 'edge', 'height': 8.0}   552.09±2629.44    977.82±4664.82      1520.27±7724.95                   7.86\n",
      "{'alpha': '1.58e-02', 'base_kernel': 'edge', 'height': 9.0}   57.81±76.95       92.24±118.53        99.28±167.28                      8.73\n",
      "{'alpha': '1.58e-02', 'base_kernel': 'edge', 'height': 10.0}  39.64±9.92        66.66±24.05         63.68±25.67                       9.4\n",
      "{'alpha': '2.00e-02', 'base_kernel': 'edge', 'height': 0.0}   41.47±10.17       68.45±21.01         66.46±27.88                       0.84\n",
      "{'alpha': '2.00e-02', 'base_kernel': 'edge', 'height': 1.0}   37.47±13.17       62.95±38.16         61.46±37.66                       1.8\n",
      "{'alpha': '2.00e-02', 'base_kernel': 'edge', 'height': 2.0}   44.47±31.02       75.62±58.32         75.56±62.41                       2.57\n",
      "{'alpha': '2.00e-02', 'base_kernel': 'edge', 'height': 3.0}   62.15±115.95      107.78±222.64       76.03±75.68                       3.47\n",
      "{'alpha': '2.00e-02', 'base_kernel': 'edge', 'height': 4.0}   51.70±55.50       90.49±118.82        90.40±112.40                      4.35\n",
      "{'alpha': '2.00e-02', 'base_kernel': 'edge', 'height': 5.0}   40.09±11.80       68.85±38.34         64.62±34.52                       5.18\n",
      "{'alpha': '2.00e-02', 'base_kernel': 'edge', 'height': 6.0}   74.80±127.92      136.16±255.16       160.62±354.93                     6.32\n",
      "{'alpha': '2.00e-02', 'base_kernel': 'edge', 'height': 7.0}   40.64±10.15       65.07±20.28         66.84±27.42                       7.08\n",
      "{'alpha': '2.00e-02', 'base_kernel': 'edge', 'height': 8.0}   432.06±2094.85    766.41±3713.96      1207.84±6156.20                   7.86\n",
      "{'alpha': '2.00e-02', 'base_kernel': 'edge', 'height': 9.0}   51.33±52.76       82.27±82.32         84.60±107.49                      8.73\n",
      "{'alpha': '2.00e-02', 'base_kernel': 'edge', 'height': 10.0}  39.42±9.49        66.15±22.89         63.26±24.67                       9.4\n",
      "{'alpha': '2.51e-02', 'base_kernel': 'edge', 'height': 0.0}   40.80±10.13       67.20±22.96         66.15±34.63                       0.84\n",
      "{'alpha': '2.51e-02', 'base_kernel': 'edge', 'height': 1.0}   36.75±10.47       61.75±37.19         59.49±30.06                       1.8\n",
      "{'alpha': '2.51e-02', 'base_kernel': 'edge', 'height': 2.0}   68.53±155.42      116.62±255.01       121.30±295.46                     2.57\n",
      "{'alpha': '2.51e-02', 'base_kernel': 'edge', 'height': 3.0}   42.18±13.29       69.91±29.50         63.34±25.54                       3.47\n",
      "{'alpha': '2.51e-02', 'base_kernel': 'edge', 'height': 4.0}   49.97±51.77       86.59±110.54        87.10±105.75                      4.35\n",
      "{'alpha': '2.51e-02', 'base_kernel': 'edge', 'height': 5.0}   39.89±11.64       68.60±39.11         64.28±34.91                       5.18\n",
      "{'alpha': '2.51e-02', 'base_kernel': 'edge', 'height': 6.0}   52.83±54.18       92.64±114.49        100.24±155.03                     6.32\n",
      "{'alpha': '2.51e-02', 'base_kernel': 'edge', 'height': 7.0}   40.63±10.38       65.29±22.10         66.64±26.78                       7.08\n",
      "{'alpha': '2.51e-02', 'base_kernel': 'edge', 'height': 8.0}   351.48±1668.81    622.36±2954.96      974.97±4903.80                    7.86\n",
      "{'alpha': '2.51e-02', 'base_kernel': 'edge', 'height': 9.0}   49.43±49.84       79.23±77.33         80.18±97.69                       8.73\n",
      "{'alpha': '2.51e-02', 'base_kernel': 'edge', 'height': 10.0}  39.17±9.01        65.57±21.61         62.77±23.54                       9.4\n",
      "{'alpha': '3.16e-02', 'base_kernel': 'edge', 'height': 0.0}   48.67±40.85       88.00±110.23        95.36±177.25                      0.84\n",
      "{'alpha': '3.16e-02', 'base_kernel': 'edge', 'height': 1.0}   36.57±10.21       63.00±48.53         58.92±28.47                       1.8\n",
      "{'alpha': '3.16e-02', 'base_kernel': 'edge', 'height': 2.0}   141.74±535.13     421.03±1916.16      281.89±1139.95                    2.57\n",
      "{'alpha': '3.16e-02', 'base_kernel': 'edge', 'height': 3.0}   42.60±17.73       71.25±39.40         66.20±40.82                       3.47\n",
      "{'alpha': '3.16e-02', 'base_kernel': 'edge', 'height': 4.0}   48.51±47.97       83.36±102.30        84.38±99.85                       4.35\n",
      "{'alpha': '3.16e-02', 'base_kernel': 'edge', 'height': 5.0}   39.73±11.62       68.50±40.42         64.06±35.71                       5.18\n",
      "{'alpha': '3.16e-02', 'base_kernel': 'edge', 'height': 6.0}   54.50±60.43       94.65±118.10        99.93±144.77                      6.32\n",
      "{'alpha': '3.16e-02', 'base_kernel': 'edge', 'height': 7.0}   40.96±11.99       66.31±27.46         67.00±27.60                       7.08\n",
      "{'alpha': '3.16e-02', 'base_kernel': 'edge', 'height': 8.0}   287.98±1328.70    508.43±2348.07      789.78±3903.78                    7.86\n",
      "{'alpha': '3.16e-02', 'base_kernel': 'edge', 'height': 9.0}   49.23±53.65       78.76±82.14         79.38±102.92                      8.73\n",
      "{'alpha': '3.16e-02', 'base_kernel': 'edge', 'height': 10.0}  38.89±8.49        64.92±20.21         62.23±22.32                       9.4\n",
      "{'alpha': '3.98e-02', 'base_kernel': 'edge', 'height': 0.0}   49.44±63.25       79.52±98.29         77.88±102.50                      0.84\n",
      "{'alpha': '3.98e-02', 'base_kernel': 'edge', 'height': 1.0}   45.07±56.68       114.52±334.41       79.62±139.83                      1.8\n",
      "{'alpha': '3.98e-02', 'base_kernel': 'edge', 'height': 2.0}   42.30±20.21       72.60±52.91         70.57±43.33                       2.57\n",
      "{'alpha': '3.98e-02', 'base_kernel': 'edge', 'height': 3.0}   41.02±12.95       68.19±30.95         63.27±30.39                       3.47\n",
      "{'alpha': '3.98e-02', 'base_kernel': 'edge', 'height': 4.0}   47.34±44.40       80.78±94.54         82.40±96.02                       4.35\n",
      "{'alpha': '3.98e-02', 'base_kernel': 'edge', 'height': 5.0}   39.65±11.86       68.65±42.63         64.03±37.19                       5.18\n",
      "{'alpha': '3.98e-02', 'base_kernel': 'edge', 'height': 6.0}   56.74±74.29       98.67±139.65        102.25±155.29                     6.32\n",
      "{'alpha': '3.98e-02', 'base_kernel': 'edge', 'height': 7.0}   42.65±19.55       70.65±47.62         69.63±36.09                       7.08\n",
      "{'alpha': '3.98e-02', 'base_kernel': 'edge', 'height': 8.0}   237.31±1056.74    417.19±1861.62      641.62±3103.70                    7.86\n",
      "{'alpha': '3.98e-02', 'base_kernel': 'edge', 'height': 9.0}   51.11±67.03       81.51±100.96        82.68±126.69                      8.73\n",
      "{'alpha': '3.98e-02', 'base_kernel': 'edge', 'height': 10.0}  38.59±7.95        64.22±18.74         61.63±21.02                       9.4\n",
      "{'alpha': '5.01e-02', 'base_kernel': 'edge', 'height': 0.0}   37.62±7.05        60.25±15.43         57.95±18.94                       0.84\n",
      "{'alpha': '5.01e-02', 'base_kernel': 'edge', 'height': 1.0}   34.90±5.62        55.49±18.04         54.58±17.16                       1.8\n",
      "{'alpha': '5.01e-02', 'base_kernel': 'edge', 'height': 2.0}   42.39±22.91       68.96±35.54         69.44±42.92                       2.57\n",
      "{'alpha': '5.01e-02', 'base_kernel': 'edge', 'height': 3.0}   39.92±11.32       66.10±30.42         60.90±25.06                       3.47\n",
      "{'alpha': '5.01e-02', 'base_kernel': 'edge', 'height': 4.0}   47.00±42.40       80.36±89.93         82.68±98.50                       4.35\n",
      "{'alpha': '5.01e-02', 'base_kernel': 'edge', 'height': 5.0}   39.76±12.60       69.33±46.49         64.43±39.94                       5.18\n",
      "{'alpha': '5.01e-02', 'base_kernel': 'edge', 'height': 6.0}   46.95±37.09       82.85±90.89         85.94±114.36                      6.32\n",
      "{'alpha': '5.01e-02', 'base_kernel': 'edge', 'height': 7.0}   87.95±246.72      181.50±605.37       140.96±376.77                     7.08\n",
      "{'alpha': '5.01e-02', 'base_kernel': 'edge', 'height': 8.0}   196.68±838.86     343.67±1470.51      522.64±2462.15                    7.86\n",
      "{'alpha': '5.01e-02', 'base_kernel': 'edge', 'height': 9.0}   61.55±123.59      97.78±183.18        102.23±230.34                     8.73\n",
      "{'alpha': '5.01e-02', 'base_kernel': 'edge', 'height': 10.0}  38.26±7.41        63.47±17.24         61.01±19.72                       9.4\n",
      "{'alpha': '6.31e-02', 'base_kernel': 'edge', 'height': 0.0}   36.53±5.41        58.47±14.84         55.98±17.17                       0.84\n",
      "{'alpha': '6.31e-02', 'base_kernel': 'edge', 'height': 1.0}   34.24±4.26        52.78±9.87          52.80±13.71                       1.8\n",
      "{'alpha': '6.31e-02', 'base_kernel': 'edge', 'height': 2.0}   41.71±17.28       69.36±35.58         69.82±41.67                       2.57\n",
      "{'alpha': '6.31e-02', 'base_kernel': 'edge', 'height': 3.0}   41.65±23.26       71.56±66.99         64.53±47.71                       3.47\n",
      "{'alpha': '6.31e-02', 'base_kernel': 'edge', 'height': 4.0}   47.56±48.46       81.23±101.74        85.92±126.16                      4.35\n",
      "{'alpha': '6.31e-02', 'base_kernel': 'edge', 'height': 5.0}   40.49±14.97       71.52±54.18         66.05±45.65                       5.18\n",
      "{'alpha': '6.31e-02', 'base_kernel': 'edge', 'height': 6.0}   45.51±35.45       82.69±102.60        84.75±121.47                      6.32\n",
      "{'alpha': '6.31e-02', 'base_kernel': 'edge', 'height': 7.0}   41.31±15.17       67.49±35.37         67.26±31.21                       7.08\n",
      "{'alpha': '6.31e-02', 'base_kernel': 'edge', 'height': 8.0}   164.00±664.11     284.16±1155.23      426.85±1946.93                    7.86\n",
      "{'alpha': '6.31e-02', 'base_kernel': 'edge', 'height': 9.0}   93.79±301.93      145.03±442.81       161.85±559.00                     8.73\n",
      "{'alpha': '6.31e-02', 'base_kernel': 'edge', 'height': 10.0}  37.95±6.91        62.72±15.77         60.41±18.54                       9.4\n",
      "{'alpha': '7.94e-02', 'base_kernel': 'edge', 'height': 0.0}   36.70±8.18        61.08±35.01         58.21±32.69                       0.84\n",
      "{'alpha': '7.94e-02', 'base_kernel': 'edge', 'height': 1.0}   33.85±3.65        51.64±8.74          51.71±11.96                       1.8\n",
      "{'alpha': '7.94e-02', 'base_kernel': 'edge', 'height': 2.0}   38.22±10.21       61.12±17.69         61.28±23.58                       2.57\n",
      "{'alpha': '7.94e-02', 'base_kernel': 'edge', 'height': 3.0}   42.88±33.18       75.39±95.49         67.07±67.25                       3.47\n",
      "{'alpha': '7.94e-02', 'base_kernel': 'edge', 'height': 4.0}   75.31±200.80      138.80±418.48       166.02±571.13                     4.35\n",
      "{'alpha': '7.94e-02', 'base_kernel': 'edge', 'height': 5.0}   201.63±885.83     377.62±1672.37      310.80±1337.66                    5.18\n",
      "{'alpha': '7.94e-02', 'base_kernel': 'edge', 'height': 6.0}   46.24±40.84       89.38±141.83        89.62±151.18                      6.32\n",
      "{'alpha': '7.94e-02', 'base_kernel': 'edge', 'height': 7.0}   38.68±7.93        61.23±15.47         62.25±21.59                       7.08\n",
      "{'alpha': '7.94e-02', 'base_kernel': 'edge', 'height': 8.0}   137.71±524.18     235.89±901.05       349.75±1533.66                    7.86\n",
      "{'alpha': '7.94e-02', 'base_kernel': 'edge', 'height': 9.0}   46.06±48.95       73.21±74.09         73.22±93.28                       8.73\n",
      "{'alpha': '7.94e-02', 'base_kernel': 'edge', 'height': 10.0}  37.88±6.82        62.38±14.75         60.38±18.67                       9.4\n",
      "{'alpha': '1.00e-01', 'base_kernel': 'edge', 'height': 0.0}   35.12±4.45        54.48±11.96         52.47±13.58                       0.84\n",
      "{'alpha': '1.00e-01', 'base_kernel': 'edge', 'height': 1.0}   33.55±3.26        50.96±8.78          50.87±10.80                       1.8\n",
      "{'alpha': '1.00e-01', 'base_kernel': 'edge', 'height': 2.0}   38.29±13.48       60.41±23.15         60.82±28.07                       2.57\n",
      "{'alpha': '1.00e-01', 'base_kernel': 'edge', 'height': 3.0}   37.71±9.20        60.93±25.37         56.58±20.37                       3.47\n",
      "{'alpha': '1.00e-01', 'base_kernel': 'edge', 'height': 4.0}   44.35±40.73       74.18±86.18         78.75±109.24                      4.35\n",
      "{'alpha': '1.00e-01', 'base_kernel': 'edge', 'height': 5.0}   44.15±28.67       86.29±114.63        78.18±93.59                       5.18\n",
      "{'alpha': '1.00e-01', 'base_kernel': 'edge', 'height': 6.0}   52.82±61.72       115.65±248.22       110.26±231.82                     6.32\n",
      "{'alpha': '1.00e-01', 'base_kernel': 'edge', 'height': 7.0}   37.80±6.91        59.09±10.99         60.49±20.97                       7.08\n",
      "{'alpha': '1.00e-01', 'base_kernel': 'edge', 'height': 8.0}   116.71±413.08     196.91±697.39       288.11±1204.79                    7.86\n",
      "{'alpha': '1.00e-01', 'base_kernel': 'edge', 'height': 9.0}   40.48±22.25       64.38±35.33         62.74±43.74                       8.73\n",
      "{'alpha': '1.00e-01', 'base_kernel': 'edge', 'height': 10.0}  37.40±6.26        61.58±13.69         59.27±16.87                       9.4\n",
      "{'alpha': '1.26e-01', 'base_kernel': 'edge', 'height': 0.0}   34.91±4.94        53.69±13.55         51.62±13.93                       0.84\n",
      "{'alpha': '1.26e-01', 'base_kernel': 'edge', 'height': 1.0}   33.33±3.00        50.51±9.21          50.24±10.15                       1.8\n",
      "{'alpha': '1.26e-01', 'base_kernel': 'edge', 'height': 2.0}   35.94±8.31        55.55±14.44         55.86±20.51                       2.57\n",
      "{'alpha': '1.26e-01', 'base_kernel': 'edge', 'height': 3.0}   36.45±5.88        57.56±14.97         54.03±14.90                       3.47\n",
      "{'alpha': '1.26e-01', 'base_kernel': 'edge', 'height': 4.0}   38.81±18.25       62.38±39.52         64.02±43.13                       4.35\n",
      "{'alpha': '1.26e-01', 'base_kernel': 'edge', 'height': 5.0}   86.97±270.81      269.55±1139.50      220.58±889.06                     5.18\n",
      "{'alpha': '1.26e-01', 'base_kernel': 'edge', 'height': 6.0}   52.17±70.64       125.69±334.51       113.39±276.09                     6.32\n",
      "{'alpha': '1.26e-01', 'base_kernel': 'edge', 'height': 7.0}   37.58±8.38        58.35±11.85         60.08±24.18                       7.08\n",
      "{'alpha': '1.26e-01', 'base_kernel': 'edge', 'height': 8.0}   100.28±326.85     165.91±537.15       239.78±948.57                     7.86\n",
      "{'alpha': '1.26e-01', 'base_kernel': 'edge', 'height': 9.0}   38.16±12.72       60.48±21.59         58.35±25.85                       8.73\n",
      "{'alpha': '1.26e-01', 'base_kernel': 'edge', 'height': 10.0}  36.92±5.91        60.62±12.85         58.30±15.80                       9.4\n",
      "{'alpha': '1.58e-01', 'base_kernel': 'edge', 'height': 0.0}   35.87±9.20        56.43±28.46         53.47±22.76                       0.84\n",
      "{'alpha': '1.58e-01', 'base_kernel': 'edge', 'height': 1.0}   33.93±4.87        52.11±14.29         51.28±12.85                       1.8\n",
      "{'alpha': '1.58e-01', 'base_kernel': 'edge', 'height': 2.0}   44.44±59.20       68.53±95.90         72.31±120.31                      2.57\n",
      "{'alpha': '1.58e-01', 'base_kernel': 'edge', 'height': 3.0}   35.67±4.70        55.56±11.13         52.46±13.11                       3.47\n",
      "{'alpha': '1.58e-01', 'base_kernel': 'edge', 'height': 4.0}   36.71±11.70       57.75±25.74         58.86±25.82                       4.35\n",
      "{'alpha': '1.58e-01', 'base_kernel': 'edge', 'height': 5.0}   43.26±29.52       82.85±106.43        77.68±97.43                       5.18\n",
      "{'alpha': '1.58e-01', 'base_kernel': 'edge', 'height': 6.0}   43.43±35.65       86.35±147.26        79.64±117.98                      6.32\n",
      "{'alpha': '1.58e-01', 'base_kernel': 'edge', 'height': 7.0}   42.23±35.51       65.44±53.34         70.85±85.04                       7.08\n",
      "{'alpha': '1.58e-01', 'base_kernel': 'edge', 'height': 8.0}   88.01±263.31      142.12±416.01       203.57±758.39                     7.86\n",
      "{'alpha': '1.58e-01', 'base_kernel': 'edge', 'height': 9.0}   36.81±8.22        58.03±15.08         55.78±17.30                       8.73\n",
      "{'alpha': '1.58e-01', 'base_kernel': 'edge', 'height': 10.0}  36.73±6.22        60.26±13.51         57.99±16.57                       9.4\n",
      "{'alpha': '2.00e-01', 'base_kernel': 'edge', 'height': 0.0}   43.41±49.80       69.89±94.80         66.89±93.62                       0.84\n",
      "{'alpha': '2.00e-01', 'base_kernel': 'edge', 'height': 1.0}   33.34±3.50        51.86±19.46         51.29±19.34                       1.8\n",
      "{'alpha': '2.00e-01', 'base_kernel': 'edge', 'height': 2.0}   34.24±7.30        51.46±12.19         51.60±18.54                       2.57\n",
      "{'alpha': '2.00e-01', 'base_kernel': 'edge', 'height': 3.0}   35.11±4.20        54.06±9.40          51.29±12.29                       3.47\n",
      "{'alpha': '2.00e-01', 'base_kernel': 'edge', 'height': 4.0}   35.44±8.16        54.83±18.09         55.87±17.87                       4.35\n",
      "{'alpha': '2.00e-01', 'base_kernel': 'edge', 'height': 5.0}   37.13±9.89        63.31±39.17         58.92±34.73                       5.18\n",
      "{'alpha': '2.00e-01', 'base_kernel': 'edge', 'height': 6.0}   40.76±21.36       70.95±62.82         68.60±57.27                       6.32\n",
      "{'alpha': '2.00e-01', 'base_kernel': 'edge', 'height': 7.0}   37.10±9.10        57.44±13.80         58.75±24.86                       7.08\n",
      "{'alpha': '2.00e-01', 'base_kernel': 'edge', 'height': 8.0}   80.02±222.76      125.35±332.42       179.55±634.08                     7.86\n",
      "{'alpha': '2.00e-01', 'base_kernel': 'edge', 'height': 9.0}   35.89±5.83        56.22±11.49         54.01±12.74                       8.73\n",
      "{'alpha': '2.00e-01', 'base_kernel': 'edge', 'height': 10.0}  37.06±8.52        61.16±19.00         58.91±22.17                       9.4\n",
      "{'alpha': '2.51e-01', 'base_kernel': 'edge', 'height': 0.0}   33.68±4.53        49.77±11.66         48.05±12.21                       0.84\n",
      "{'alpha': '2.51e-01', 'base_kernel': 'edge', 'height': 1.0}   33.57±4.82        51.45±17.36         50.96±17.63                       1.8\n",
      "{'alpha': '2.51e-01', 'base_kernel': 'edge', 'height': 2.0}   33.33±4.35        49.56±7.62          49.30±12.65                       2.57\n",
      "{'alpha': '2.51e-01', 'base_kernel': 'edge', 'height': 3.0}   34.74±4.34        52.96±9.18          50.47±12.28                       3.47\n",
      "{'alpha': '2.51e-01', 'base_kernel': 'edge', 'height': 4.0}   34.53±5.87        52.66±13.00         53.77±13.33                       4.35\n",
      "{'alpha': '2.51e-01', 'base_kernel': 'edge', 'height': 5.0}   35.66±5.90        58.32±21.69         54.54±21.11                       5.18\n",
      "{'alpha': '2.51e-01', 'base_kernel': 'edge', 'height': 6.0}   39.19±15.89       65.00±38.52         64.32±40.41                       6.32\n",
      "{'alpha': '2.51e-01', 'base_kernel': 'edge', 'height': 7.0}   41.82±29.54       74.79±102.03        68.44±61.96                       7.08\n",
      "{'alpha': '2.51e-01', 'base_kernel': 'edge', 'height': 8.0}   78.28±214.42      117.57±293.19       172.52±597.80                     7.86\n",
      "{'alpha': '2.51e-01', 'base_kernel': 'edge', 'height': 9.0}   35.21±4.48        54.74±9.27          52.69±10.25                       8.73\n",
      "{'alpha': '2.51e-01', 'base_kernel': 'edge', 'height': 10.0}  48.66±65.94       88.48±149.62        86.19±156.54                      9.4\n",
      "{'alpha': '3.16e-01', 'base_kernel': 'edge', 'height': 0.0}   32.84±3.45        47.45±8.98          45.97±9.93                        0.84\n",
      "{'alpha': '3.16e-01', 'base_kernel': 'edge', 'height': 1.0}   32.85±3.81        48.33±10.35         47.78±9.63                        1.8\n",
      "{'alpha': '3.16e-01', 'base_kernel': 'edge', 'height': 2.0}   32.74±3.37        48.09±5.93          47.63±10.58                       2.57\n",
      "{'alpha': '3.16e-01', 'base_kernel': 'edge', 'height': 3.0}   34.88±6.90        52.80±13.51         50.67±16.14                       3.47\n",
      "{'alpha': '3.16e-01', 'base_kernel': 'edge', 'height': 4.0}   33.83±4.33        50.92±9.46          52.14±10.52                       4.35\n",
      "{'alpha': '3.16e-01', 'base_kernel': 'edge', 'height': 5.0}   34.85±4.39        55.61±14.03         52.19±15.48                       5.18\n",
      "{'alpha': '3.16e-01', 'base_kernel': 'edge', 'height': 6.0}   38.76±17.61       63.99±44.78         63.42±42.30                       6.32\n",
      "{'alpha': '3.16e-01', 'base_kernel': 'edge', 'height': 7.0}   35.84±6.10        54.68±10.32         55.48±18.34                       7.08\n",
      "{'alpha': '3.16e-01', 'base_kernel': 'edge', 'height': 8.0}   118.44±434.85     150.35±475.03       269.92±1131.99                    7.86\n",
      "{'alpha': '3.16e-01', 'base_kernel': 'edge', 'height': 9.0}   34.73±3.81        53.55±7.77          51.73±9.11                        8.73\n",
      "{'alpha': '3.16e-01', 'base_kernel': 'edge', 'height': 10.0}  37.85±12.29       64.25±35.11         61.33±32.87                       9.4\n",
      "{'alpha': '3.98e-01', 'base_kernel': 'edge', 'height': 0.0}   32.46±3.85        46.22±9.82          44.84±10.43                       0.84\n",
      "{'alpha': '3.98e-01', 'base_kernel': 'edge', 'height': 1.0}   32.13±2.43        46.15±7.62          45.69±6.90                        1.8\n",
      "{'alpha': '3.98e-01', 'base_kernel': 'edge', 'height': 2.0}   32.22±2.78        46.63±4.57          46.13±9.46                        2.57\n",
      "{'alpha': '3.98e-01', 'base_kernel': 'edge', 'height': 3.0}   38.27±27.22       58.52±50.15         57.35±55.15                       3.47\n",
      "{'alpha': '3.98e-01', 'base_kernel': 'edge', 'height': 4.0}   33.27±3.31        49.45±6.97          50.80±8.73                        4.35\n",
      "{'alpha': '3.98e-01', 'base_kernel': 'edge', 'height': 5.0}   34.28±3.77        53.72±10.22         50.55±12.80                       5.18\n",
      "{'alpha': '3.98e-01', 'base_kernel': 'edge', 'height': 6.0}   35.46±8.81        55.30±18.13         55.98±25.44                       6.32\n",
      "{'alpha': '3.98e-01', 'base_kernel': 'edge', 'height': 7.0}   36.41±11.35       54.13±11.66         56.72±29.76                       7.08\n",
      "{'alpha': '3.98e-01', 'base_kernel': 'edge', 'height': 8.0}   85.02±258.70      122.18±337.54       196.44±747.08                     7.86\n",
      "{'alpha': '3.98e-01', 'base_kernel': 'edge', 'height': 9.0}   34.66±4.83        52.93±7.83          51.51±10.82                       8.73\n",
      "{'alpha': '3.98e-01', 'base_kernel': 'edge', 'height': 10.0}  35.23±5.65        56.99±15.26         54.86±14.99                       9.4\n",
      "{'alpha': '5.01e-01', 'base_kernel': 'edge', 'height': 0.0}   32.58±6.55        46.26±16.67         44.88±16.20                       0.84\n",
      "{'alpha': '5.01e-01', 'base_kernel': 'edge', 'height': 1.0}   31.79±2.15        44.89±6.48          44.52±6.27                        1.8\n",
      "{'alpha': '5.01e-01', 'base_kernel': 'edge', 'height': 2.0}   31.89±2.42        45.58±3.88          45.02±8.59                        2.57\n",
      "{'alpha': '5.01e-01', 'base_kernel': 'edge', 'height': 3.0}   33.69±4.52        49.78±9.01          47.79±11.38                       3.47\n",
      "{'alpha': '5.01e-01', 'base_kernel': 'edge', 'height': 4.0}   32.80±2.64        48.16±5.23          49.64±7.58                        4.35\n",
      "{'alpha': '5.01e-01', 'base_kernel': 'edge', 'height': 5.0}   33.81±3.41        52.18±8.13          49.22±11.34                       5.18\n",
      "{'alpha': '5.01e-01', 'base_kernel': 'edge', 'height': 6.0}   34.72±7.93        53.32±15.83         53.91±22.54                       6.32\n",
      "{'alpha': '5.01e-01', 'base_kernel': 'edge', 'height': 7.0}   36.73±14.06       54.36±15.57         57.42±36.23                       7.08\n",
      "{'alpha': '5.01e-01', 'base_kernel': 'edge', 'height': 8.0}   376.05±1858.91    479.48±2310.42      786.84±3996.13                    7.86\n",
      "{'alpha': '5.01e-01', 'base_kernel': 'edge', 'height': 9.0}   36.42±16.11       55.03±22.96         54.49±30.03                       8.73\n",
      "{'alpha': '5.01e-01', 'base_kernel': 'edge', 'height': 10.0}  34.01±3.60        53.52±7.92          51.89±9.13                        9.4\n",
      "{'alpha': '6.31e-01', 'base_kernel': 'edge', 'height': 0.0}   37.15±33.43       57.40±83.93         55.26±78.26                       0.84\n",
      "{'alpha': '6.31e-01', 'base_kernel': 'edge', 'height': 1.0}   31.52±1.89        43.80±5.39          43.52±5.85                        1.8\n",
      "{'alpha': '6.31e-01', 'base_kernel': 'edge', 'height': 2.0}   31.62±2.13        44.66±3.36          44.02±7.89                        2.57\n",
      "{'alpha': '6.31e-01', 'base_kernel': 'edge', 'height': 3.0}   33.01±2.80        48.09±5.73          46.19±9.06                        3.47\n",
      "{'alpha': '6.31e-01', 'base_kernel': 'edge', 'height': 4.0}   32.42±2.23        47.01±4.04          48.62±6.80                        4.35\n",
      "{'alpha': '6.31e-01', 'base_kernel': 'edge', 'height': 5.0}   33.40±3.05        50.79±6.75          48.01±10.32                       5.18\n",
      "{'alpha': '6.31e-01', 'base_kernel': 'edge', 'height': 6.0}   33.75±5.94        51.17±12.09         51.74±18.74                       6.32\n",
      "{'alpha': '6.31e-01', 'base_kernel': 'edge', 'height': 7.0}   36.13±11.20       57.72±40.70         56.79±37.15                       7.08\n",
      "{'alpha': '6.31e-01', 'base_kernel': 'edge', 'height': 8.0}   69.54±183.74      101.10±248.10       151.51±525.85                     7.86\n",
      "{'alpha': '6.31e-01', 'base_kernel': 'edge', 'height': 9.0}   33.38±2.77        50.13±5.38          48.92±7.32                        8.73\n",
      "{'alpha': '6.31e-01', 'base_kernel': 'edge', 'height': 10.0}  33.37±3.12        51.70±6.40          50.38±7.73                        9.4\n",
      "{'alpha': '7.94e-01', 'base_kernel': 'edge', 'height': 0.0}   31.23±3.10        42.36±7.91          41.22±8.51                        0.84\n",
      "{'alpha': '7.94e-01', 'base_kernel': 'edge', 'height': 1.0}   31.27±1.64        42.78±4.38          42.60±5.56                        1.8\n",
      "{'alpha': '7.94e-01', 'base_kernel': 'edge', 'height': 2.0}   31.37±1.88        43.81±2.94          43.10±7.30                        2.57\n",
      "{'alpha': '7.94e-01', 'base_kernel': 'edge', 'height': 3.0}   32.58±2.19        46.86±4.45          45.08±8.29                        3.47\n",
      "{'alpha': '7.94e-01', 'base_kernel': 'edge', 'height': 4.0}   32.08±1.97        45.97±3.24          47.70±6.26                        4.35\n",
      "{'alpha': '7.94e-01', 'base_kernel': 'edge', 'height': 5.0}   33.01±2.63        49.48±5.63          46.86±9.47                        5.18\n",
      "{'alpha': '7.94e-01', 'base_kernel': 'edge', 'height': 6.0}   9372.38±51155.15  31477.18±172141.77  19469.68±106369.85                6.32\n",
      "{'alpha': '7.94e-01', 'base_kernel': 'edge', 'height': 7.0}   34.52±5.69        52.16±15.67         51.49±18.34                       7.08\n",
      "{'alpha': '7.94e-01', 'base_kernel': 'edge', 'height': 8.0}   56.76±116.80      86.41±176.62        119.21±357.28                     7.86\n",
      "{'alpha': '7.94e-01', 'base_kernel': 'edge', 'height': 9.0}   32.80±2.16        48.72±4.59          47.72±6.28                        8.73\n",
      "{'alpha': '7.94e-01', 'base_kernel': 'edge', 'height': 10.0}  32.88±2.86        50.28±5.72          49.24±7.09                        9.4\n",
      "{'alpha': '1.00e+00', 'base_kernel': 'edge', 'height': 0.0}   30.58±1.42        40.47±3.34          39.50±5.48                        0.84\n",
      "{'alpha': '1.00e+00', 'base_kernel': 'edge', 'height': 1.0}   31.03±1.41        41.82±3.50          41.73±5.35                        1.8\n",
      "{'alpha': '1.00e+00', 'base_kernel': 'edge', 'height': 2.0}   31.14±1.67        43.00±2.60          42.21±6.80                        2.57\n",
      "{'alpha': '1.00e+00', 'base_kernel': 'edge', 'height': 3.0}   32.24±1.87        45.77±3.69          44.13±7.81                        3.47\n",
      "{'alpha': '1.00e+00', 'base_kernel': 'edge', 'height': 4.0}   31.79±1.80        45.00±2.73          46.83±5.86                        4.35\n",
      "{'alpha': '1.00e+00', 'base_kernel': 'edge', 'height': 5.0}   32.66±2.23        48.23±4.68          45.78±8.76                        5.18\n",
      "{'alpha': '1.00e+00', 'base_kernel': 'edge', 'height': 6.0}   32.54±3.86        48.04±8.20          48.43±13.78                       6.32\n",
      "{'alpha': '1.00e+00', 'base_kernel': 'edge', 'height': 7.0}   35.43±13.34       54.21±34.41         52.49±30.47                       7.08\n",
      "{'alpha': '1.00e+00', 'base_kernel': 'edge', 'height': 8.0}   42.34±40.70       63.07±57.42         74.50±120.54                      7.86\n",
      "{'alpha': '1.00e+00', 'base_kernel': 'edge', 'height': 9.0}   32.41±2.01        47.59±4.24          46.84±5.96                        8.73\n",
      "{'alpha': '1.00e+00', 'base_kernel': 'edge', 'height': 10.0}  32.48±2.65        49.03±5.22          48.29±6.73                        9.4\n",
      "{'alpha': '1.26e+00', 'base_kernel': 'edge', 'height': 0.0}   30.20±0.96        39.26±1.91          38.44±4.94                        0.84\n",
      "{'alpha': '1.26e+00', 'base_kernel': 'edge', 'height': 1.0}   30.78±1.21        40.89±2.79          40.88±5.22                        1.8\n",
      "{'alpha': '1.26e+00', 'base_kernel': 'edge', 'height': 2.0}   30.92±1.47        42.20±2.31          41.35±6.39                        2.57\n",
      "{'alpha': '1.26e+00', 'base_kernel': 'edge', 'height': 3.0}   31.93±1.65        44.74±3.15          43.25±7.40                        3.47\n",
      "{'alpha': '1.26e+00', 'base_kernel': 'edge', 'height': 4.0}   31.52±1.67        44.08±2.39          46.01±5.55                        4.35\n",
      "{'alpha': '1.26e+00', 'base_kernel': 'edge', 'height': 5.0}   32.34±1.88        47.06±3.92          44.75±8.21                        5.18\n",
      "{'alpha': '1.26e+00', 'base_kernel': 'edge', 'height': 6.0}   32.13±3.08        46.79±6.49          47.06±11.89                       6.32\n",
      "{'alpha': '1.26e+00', 'base_kernel': 'edge', 'height': 7.0}   34.24±9.14        50.83±22.84         49.45±21.89                       7.08\n",
      "{'alpha': '1.26e+00', 'base_kernel': 'edge', 'height': 8.0}   41.68±38.43       61.27±53.30         71.75±109.62                      7.86\n",
      "{'alpha': '1.26e+00', 'base_kernel': 'edge', 'height': 9.0}   32.11±1.92        46.62±3.92          46.08±5.77                        8.73\n",
      "{'alpha': '1.26e+00', 'base_kernel': 'edge', 'height': 10.0}  32.13±2.45        47.88±4.77          47.43±6.49                        9.4\n",
      "{'alpha': '1.58e+00', 'base_kernel': 'edge', 'height': 0.0}   29.93±0.77        38.31±1.32          37.64±4.83                        0.84\n",
      "{'alpha': '1.58e+00', 'base_kernel': 'edge', 'height': 1.0}   30.54±1.04        40.01±2.22          40.07±5.15                        1.8\n",
      "{'alpha': '1.58e+00', 'base_kernel': 'edge', 'height': 2.0}   30.70±1.29        41.43±2.07          40.51±6.07                        2.57\n",
      "{'alpha': '1.58e+00', 'base_kernel': 'edge', 'height': 3.0}   31.64±1.48        43.75±2.72          42.40±7.03                        3.47\n",
      "{'alpha': '1.58e+00', 'base_kernel': 'edge', 'height': 4.0}   31.26±1.57        43.19±2.16          45.22±5.31                        4.35\n",
      "{'alpha': '1.58e+00', 'base_kernel': 'edge', 'height': 5.0}   32.05±1.61        45.95±3.32          43.78±7.78                        5.18\n",
      "{'alpha': '1.58e+00', 'base_kernel': 'edge', 'height': 6.0}   31.79±2.34        46.11±6.75          45.99±11.08                       6.32\n",
      "{'alpha': '1.58e+00', 'base_kernel': 'edge', 'height': 7.0}   32.86±3.58        47.02±7.89          46.09±11.64                       7.08\n",
      "{'alpha': '1.58e+00', 'base_kernel': 'edge', 'height': 8.0}   39.81±25.84       59.29±43.25         67.33±79.38                       7.86\n",
      "{'alpha': '1.58e+00', 'base_kernel': 'edge', 'height': 9.0}   31.87±1.81        45.76±3.55          45.37±5.59                        8.73\n",
      "{'alpha': '1.58e+00', 'base_kernel': 'edge', 'height': 10.0}  31.81±2.25        46.79±4.32          46.66±6.32                        9.4\n",
      "{'alpha': '2.00e+00', 'base_kernel': 'edge', 'height': 0.0}   29.73±0.66        37.51±1.05          37.02±4.81                        0.84\n",
      "{'alpha': '2.00e+00', 'base_kernel': 'edge', 'height': 1.0}   30.30±0.90        39.17±1.80          39.30±5.13                        1.8\n",
      "{'alpha': '2.00e+00', 'base_kernel': 'edge', 'height': 2.0}   30.48±1.13        40.66±1.86          39.69±5.82                        2.57\n",
      "{'alpha': '2.00e+00', 'base_kernel': 'edge', 'height': 3.0}   31.36±1.34        42.79±2.36          41.58±6.68                        3.47\n",
      "{'alpha': '2.00e+00', 'base_kernel': 'edge', 'height': 4.0}   31.01±1.46        42.32±1.98          44.45±5.12                        4.35\n",
      "{'alpha': '2.00e+00', 'base_kernel': 'edge', 'height': 5.0}   31.79±1.41        44.88±2.86          42.85±7.45                        5.18\n",
      "{'alpha': '2.00e+00', 'base_kernel': 'edge', 'height': 6.0}   31.21±1.95        43.65±3.49          43.94±8.38                        6.32\n",
      "{'alpha': '2.00e+00', 'base_kernel': 'edge', 'height': 7.0}   32.33±2.38        45.48±4.68          44.55±9.49                        7.08\n",
      "{'alpha': '2.00e+00', 'base_kernel': 'edge', 'height': 8.0}   35.69±11.60       51.66±18.31         55.02±36.75                       7.86\n",
      "{'alpha': '2.00e+00', 'base_kernel': 'edge', 'height': 9.0}   31.65±1.70        44.92±3.21          44.69±5.42                        8.73\n",
      "{'alpha': '2.00e+00', 'base_kernel': 'edge', 'height': 10.0}  31.53±2.07        45.76±3.90          45.92±6.19                        9.4\n",
      "{'alpha': '2.51e+00', 'base_kernel': 'edge', 'height': 0.0}   29.59±0.59        36.84±0.91          36.53±4.82                        0.84\n",
      "{'alpha': '2.51e+00', 'base_kernel': 'edge', 'height': 1.0}   30.08±0.79        38.38±1.49          38.57±5.15                        1.8\n",
      "{'alpha': '2.51e+00', 'base_kernel': 'edge', 'height': 2.0}   30.26±0.99        39.91±1.70          38.89±5.66                        2.57\n",
      "{'alpha': '2.51e+00', 'base_kernel': 'edge', 'height': 3.0}   31.07±1.21        41.84±2.05          40.77±6.35                        3.47\n",
      "{'alpha': '2.51e+00', 'base_kernel': 'edge', 'height': 4.0}   30.77±1.34        41.47±1.81          43.68±5.00                        4.35\n",
      "{'alpha': '2.51e+00', 'base_kernel': 'edge', 'height': 5.0}   31.53±1.25        43.86±2.49          41.94±7.16                        5.18\n",
      "{'alpha': '2.51e+00', 'base_kernel': 'edge', 'height': 6.0}   30.93±1.65        42.56±2.94          42.81±7.34                        6.32\n",
      "{'alpha': '2.51e+00', 'base_kernel': 'edge', 'height': 7.0}   31.96±1.83        44.34±3.30          43.35±8.41                        7.08\n",
      "{'alpha': '2.51e+00', 'base_kernel': 'edge', 'height': 8.0}   34.01±6.61        48.24±9.99          49.84±21.37                       7.86\n",
      "{'alpha': '2.51e+00', 'base_kernel': 'edge', 'height': 9.0}   31.44±1.59        44.09±2.91          44.00±5.27                        8.73\n",
      "{'alpha': '2.51e+00', 'base_kernel': 'edge', 'height': 10.0}  31.27±1.88        44.76±3.46          45.25±6.06                        9.4\n",
      "{'alpha': '3.16e+00', 'base_kernel': 'edge', 'height': 0.0}   29.53±0.56        36.30±0.84          36.15±4.86                        0.84\n",
      "{'alpha': '3.16e+00', 'base_kernel': 'edge', 'height': 1.0}   29.88±0.70        37.66±1.27          37.91±5.19                        1.8\n",
      "{'alpha': '3.16e+00', 'base_kernel': 'edge', 'height': 2.0}   30.05±0.87        39.19±1.56          38.13±5.57                        2.57\n",
      "{'alpha': '3.16e+00', 'base_kernel': 'edge', 'height': 3.0}   30.79±1.09        40.92±1.78          39.98±6.06                        3.47\n",
      "{'alpha': '3.16e+00', 'base_kernel': 'edge', 'height': 4.0}   30.52±1.22        40.63±1.65          42.94±4.94                        4.35\n",
      "{'alpha': '3.16e+00', 'base_kernel': 'edge', 'height': 5.0}   31.27±1.11        42.86±2.17          41.04±6.90                        5.18\n",
      "{'alpha': '3.16e+00', 'base_kernel': 'edge', 'height': 6.0}   30.69±1.41        41.64±2.48          41.76±6.59                        6.32\n",
      "{'alpha': '3.16e+00', 'base_kernel': 'edge', 'height': 7.0}   31.64±1.48        43.34±2.52          42.28±7.65                        7.08\n",
      "{'alpha': '3.16e+00', 'base_kernel': 'edge', 'height': 8.0}   33.30±5.16        46.63±8.43          47.41±15.32                       7.86\n",
      "{'alpha': '3.16e+00', 'base_kernel': 'edge', 'height': 9.0}   31.23±1.48        43.26±2.63          43.29±5.13                        8.73\n",
      "{'alpha': '3.16e+00', 'base_kernel': 'edge', 'height': 10.0}  31.02±1.70        43.80±3.07          44.58±5.98                        9.4\n",
      "{'alpha': '3.98e+00', 'base_kernel': 'edge', 'height': 0.0}   29.56±0.54        35.87±0.79          35.88±4.91                        0.84\n",
      "{'alpha': '3.98e+00', 'base_kernel': 'edge', 'height': 1.0}   29.72±0.64        37.02±1.13          37.31±5.25                        1.8\n",
      "{'alpha': '3.98e+00', 'base_kernel': 'edge', 'height': 2.0}   29.87±0.78        38.49±1.44          37.41±5.55                        2.57\n",
      "{'alpha': '3.98e+00', 'base_kernel': 'edge', 'height': 3.0}   30.51±0.98        40.03±1.55          39.22±5.81                        3.47\n",
      "{'alpha': '3.98e+00', 'base_kernel': 'edge', 'height': 4.0}   30.27±1.11        39.81±1.50          42.20±4.93                        4.35\n",
      "{'alpha': '3.98e+00', 'base_kernel': 'edge', 'height': 5.0}   31.01±0.99        41.89±1.90          40.15±6.65                        5.18\n",
      "{'alpha': '3.98e+00', 'base_kernel': 'edge', 'height': 6.0}   30.47±1.23        40.79±2.13          40.78±6.09                        6.32\n",
      "{'alpha': '3.98e+00', 'base_kernel': 'edge', 'height': 7.0}   31.34±1.21        42.40±2.00          41.28±7.02                        7.08\n",
      "{'alpha': '3.98e+00', 'base_kernel': 'edge', 'height': 8.0}   73.50±226.84      132.22±483.48       127.18±453.61                     7.86\n",
      "{'alpha': '3.98e+00', 'base_kernel': 'edge', 'height': 9.0}   31.02±1.37        42.43±2.38          42.56±5.00                        8.73\n",
      "{'alpha': '3.98e+00', 'base_kernel': 'edge', 'height': 10.0}  30.79±1.53        42.88±2.73          43.92±5.91                        9.4\n",
      "{'alpha': '5.01e+00', 'base_kernel': 'edge', 'height': 0.0}   29.67±0.53        35.57±0.77          35.72±4.98                        0.84\n",
      "{'alpha': '5.01e+00', 'base_kernel': 'edge', 'height': 1.0}   29.60±0.59        36.46±1.03          36.78±5.33                        1.8\n",
      "{'alpha': '5.01e+00', 'base_kernel': 'edge', 'height': 2.0}   29.71±0.71        37.85±1.34          36.74±5.58                        2.57\n",
      "{'alpha': '5.01e+00', 'base_kernel': 'edge', 'height': 3.0}   30.25±0.88        39.18±1.36          38.49±5.62                        3.47\n",
      "{'alpha': '5.01e+00', 'base_kernel': 'edge', 'height': 4.0}   30.03±1.00        39.02±1.36          41.49±4.98                        4.35\n",
      "{'alpha': '5.01e+00', 'base_kernel': 'edge', 'height': 5.0}   30.75±0.88        40.94±1.66          39.27±6.42                        5.18\n",
      "{'alpha': '5.01e+00', 'base_kernel': 'edge', 'height': 6.0}   30.26±1.09        40.00±1.87          39.86±5.78                        6.32\n",
      "{'alpha': '5.01e+00', 'base_kernel': 'edge', 'height': 7.0}   31.04±0.99        41.50±1.61          40.34±6.48                        7.08\n",
      "{'alpha': '5.01e+00', 'base_kernel': 'edge', 'height': 8.0}   32.01±2.98        43.41±4.78          43.49±9.02                        7.86\n",
      "{'alpha': '5.01e+00', 'base_kernel': 'edge', 'height': 9.0}   30.81±1.26        41.61±2.14          41.82±4.87                        8.73\n",
      "{'alpha': '5.01e+00', 'base_kernel': 'edge', 'height': 10.0}  30.56±1.38        41.99±2.42          43.27±5.85                        9.4\n",
      "{'alpha': '6.31e+00', 'base_kernel': 'edge', 'height': 0.0}   29.90±0.52        35.39±0.76          35.65±5.07                        0.84\n",
      "{'alpha': '6.31e+00', 'base_kernel': 'edge', 'height': 1.0}   29.55±0.56        35.99±0.96          36.32±5.43                        1.8\n",
      "{'alpha': '6.31e+00', 'base_kernel': 'edge', 'height': 2.0}   29.59±0.66        37.25±1.26          36.13±5.65                        2.57\n",
      "{'alpha': '6.31e+00', 'base_kernel': 'edge', 'height': 3.0}   30.02±0.79        38.39±1.22          37.81±5.48                        3.47\n",
      "{'alpha': '6.31e+00', 'base_kernel': 'edge', 'height': 4.0}   29.81±0.90        38.26±1.24          40.81±5.08                        4.35\n",
      "{'alpha': '6.31e+00', 'base_kernel': 'edge', 'height': 5.0}   30.49±0.78        40.04±1.45          38.41±6.19                        5.18\n",
      "{'alpha': '6.31e+00', 'base_kernel': 'edge', 'height': 6.0}   30.07±0.97        39.25±1.66          39.01±5.62                        6.32\n",
      "{'alpha': '6.31e+00', 'base_kernel': 'edge', 'height': 7.0}   30.76±0.80        40.62±1.30          39.43±6.01                        7.08\n",
      "{'alpha': '6.31e+00', 'base_kernel': 'edge', 'height': 8.0}   31.40±1.90        41.88±2.61          41.71±6.84                        7.86\n",
      "{'alpha': '6.31e+00', 'base_kernel': 'edge', 'height': 9.0}   30.59±1.15        40.81±1.92          41.07±4.75                        8.73\n",
      "{'alpha': '6.31e+00', 'base_kernel': 'edge', 'height': 10.0}  30.34±1.24        41.12±2.15          42.62±5.81                        9.4\n",
      "{'alpha': '7.94e+00', 'base_kernel': 'edge', 'height': 0.0}   30.26±0.52        35.36±0.75          35.70±5.19                        0.84\n",
      "{'alpha': '7.94e+00', 'base_kernel': 'edge', 'height': 1.0}   29.57±0.54        35.63±0.91          35.94±5.57                        1.8\n",
      "{'alpha': '7.94e+00', 'base_kernel': 'edge', 'height': 2.0}   29.52±0.63        36.72±1.19          35.59±5.76                        2.57\n",
      "{'alpha': '7.94e+00', 'base_kernel': 'edge', 'height': 3.0}   29.82±0.72        37.67±1.11          37.17±5.41                        3.47\n",
      "{'alpha': '7.94e+00', 'base_kernel': 'edge', 'height': 4.0}   29.61±0.81        37.57±1.13          40.17±5.23                        4.35\n",
      "{'alpha': '7.94e+00', 'base_kernel': 'edge', 'height': 5.0}   30.24±0.68        39.19±1.28          37.58±5.99                        5.18\n",
      "{'alpha': '7.94e+00', 'base_kernel': 'edge', 'height': 6.0}   29.89±0.88        38.55±1.50          38.22±5.57                        6.32\n",
      "{'alpha': '7.94e+00', 'base_kernel': 'edge', 'height': 7.0}   30.48±0.64        39.78±1.07          38.58±5.61                        7.08\n",
      "{'alpha': '7.94e+00', 'base_kernel': 'edge', 'height': 8.0}   30.97±1.42        40.74±1.84          40.38±5.79                        7.86\n",
      "{'alpha': '7.94e+00', 'base_kernel': 'edge', 'height': 9.0}   30.36±1.03        40.02±1.72          40.32±4.63                        8.73\n",
      "{'alpha': '7.94e+00', 'base_kernel': 'edge', 'height': 10.0}  30.12±1.12        40.28±1.92          41.97±5.79                        9.4\n",
      "{'alpha': '1.00e+01', 'base_kernel': 'edge', 'height': 0.0}   30.77±0.52        35.49±0.75          35.87±5.34                        0.84\n",
      "{'alpha': '1.00e+01', 'base_kernel': 'edge', 'height': 1.0}   29.69±0.53        35.37±0.88          35.65±5.74                        1.8\n",
      "{'alpha': '1.00e+01', 'base_kernel': 'edge', 'height': 2.0}   29.52±0.61        36.27±1.13          35.13±5.89                        2.57\n",
      "{'alpha': '1.00e+01', 'base_kernel': 'edge', 'height': 3.0}   29.68±0.67        37.04±1.02          36.60±5.38                        3.47\n",
      "{'alpha': '1.00e+01', 'base_kernel': 'edge', 'height': 4.0}   29.46±0.74        36.93±1.04          39.58±5.40                        4.35\n",
      "{'alpha': '1.00e+01', 'base_kernel': 'edge', 'height': 5.0}   30.03±0.61        38.40±1.14          36.80±5.79                        5.18\n",
      "{'alpha': '1.00e+01', 'base_kernel': 'edge', 'height': 6.0}   29.73±0.80        37.90±1.38          37.51±5.58                        6.32\n",
      "{'alpha': '1.00e+01', 'base_kernel': 'edge', 'height': 7.0}   30.22±0.51        38.98±0.91          37.78±5.28                        7.08\n",
      "{'alpha': '1.00e+01', 'base_kernel': 'edge', 'height': 8.0}   30.60±1.12        39.76±1.42          39.25±5.21                        7.86\n",
      "{'alpha': '1.00e+01', 'base_kernel': 'edge', 'height': 9.0}   30.14±0.93        39.27±1.54          39.57±4.52                        8.73\n",
      "{'alpha': '1.00e+01', 'base_kernel': 'edge', 'height': 10.0}  29.91±1.01        39.48±1.72          41.32±5.78                        9.4\n",
      "{'alpha': '1.26e+01', 'base_kernel': 'edge', 'height': 0.0}   31.45±0.51        35.81±0.75          36.19±5.53                        0.84\n",
      "{'alpha': '1.26e+01', 'base_kernel': 'edge', 'height': 1.0}   29.91±0.53        35.24±0.85          35.45±5.94                        1.8\n",
      "{'alpha': '1.26e+01', 'base_kernel': 'edge', 'height': 2.0}   29.60±0.60        35.91±1.08          34.75±6.05                        2.57\n",
      "{'alpha': '1.26e+01', 'base_kernel': 'edge', 'height': 3.0}   29.61±0.62        36.50±0.95          36.10±5.39                        3.47\n",
      "{'alpha': '1.26e+01', 'base_kernel': 'edge', 'height': 4.0}   29.35±0.69        36.38±0.97          39.06±5.61                        4.35\n",
      "{'alpha': '1.26e+01', 'base_kernel': 'edge', 'height': 5.0}   29.85±0.56        37.69±1.05          36.08±5.61                        5.18\n",
      "{'alpha': '1.26e+01', 'base_kernel': 'edge', 'height': 6.0}   29.61±0.73        37.30±1.28          36.88±5.63                        6.32\n",
      "{'alpha': '1.26e+01', 'base_kernel': 'edge', 'height': 7.0}   30.00±0.41        38.24±0.80          37.05±5.03                        7.08\n",
      "{'alpha': '1.26e+01', 'base_kernel': 'edge', 'height': 8.0}   30.28±0.90        38.90±1.16          38.28±4.90                        7.86\n",
      "{'alpha': '1.26e+01', 'base_kernel': 'edge', 'height': 9.0}   29.94±0.83        38.54±1.38          38.85±4.44                        8.73\n",
      "{'alpha': '1.26e+01', 'base_kernel': 'edge', 'height': 10.0}  29.71±0.92        38.71±1.55          40.68±5.79                        9.4\n",
      "{'alpha': '1.58e+01', 'base_kernel': 'edge', 'height': 0.0}   32.35±0.51        36.34±0.74          36.67±5.75                        0.84\n",
      "{'alpha': '1.58e+01', 'base_kernel': 'edge', 'height': 1.0}   30.26±0.52        35.25±0.82          35.36±6.17                        1.8\n",
      "{'alpha': '1.58e+01', 'base_kernel': 'edge', 'height': 2.0}   29.77±0.59        35.65±1.04          34.48±6.23                        2.57\n",
      "{'alpha': '1.58e+01', 'base_kernel': 'edge', 'height': 3.0}   29.61±0.59        36.06±0.89          35.67±5.43                        3.47\n",
      "{'alpha': '1.58e+01', 'base_kernel': 'edge', 'height': 4.0}   29.32±0.65        35.91±0.92          38.60±5.84                        4.35\n",
      "{'alpha': '1.58e+01', 'base_kernel': 'edge', 'height': 5.0}   29.73±0.52        37.07±0.98          35.44±5.44                        5.18\n",
      "{'alpha': '1.58e+01', 'base_kernel': 'edge', 'height': 6.0}   29.53±0.67        36.77±1.19          36.34±5.70                        6.32\n",
      "{'alpha': '1.58e+01', 'base_kernel': 'edge', 'height': 7.0}   29.82±0.36        37.56±0.74          36.39±4.84                        7.08\n",
      "{'alpha': '1.58e+01', 'base_kernel': 'edge', 'height': 8.0}   30.02±0.74        38.13±1.00          37.45±4.76                        7.86\n",
      "{'alpha': '1.58e+01', 'base_kernel': 'edge', 'height': 9.0}   29.75±0.74        37.86±1.24          38.17±4.37                        8.73\n",
      "{'alpha': '1.58e+01', 'base_kernel': 'edge', 'height': 10.0}  29.53±0.85        37.99±1.41          40.05±5.81                        9.4\n",
      "{'alpha': '2.00e+01', 'base_kernel': 'edge', 'height': 0.0}   33.51±0.50        37.13±0.74          37.36±6.01                        0.84\n",
      "{'alpha': '2.00e+01', 'base_kernel': 'edge', 'height': 1.0}   30.77±0.52        35.42±0.80          35.40±6.43                        1.8\n",
      "{'alpha': '2.00e+01', 'base_kernel': 'edge', 'height': 2.0}   30.06±0.59        35.51±1.01          34.33±6.42                        2.57\n",
      "{'alpha': '2.00e+01', 'base_kernel': 'edge', 'height': 3.0}   29.71±0.57        35.75±0.84          35.33±5.49                        3.47\n",
      "{'alpha': '2.00e+01', 'base_kernel': 'edge', 'height': 4.0}   29.35±0.62        35.54±0.87          38.22±6.09                        4.35\n",
      "{'alpha': '2.00e+01', 'base_kernel': 'edge', 'height': 5.0}   29.68±0.50        36.55±0.93          34.89±5.27                        5.18\n",
      "{'alpha': '2.00e+01', 'base_kernel': 'edge', 'height': 6.0}   29.50±0.63        36.31±1.12          35.89±5.79                        6.32\n",
      "{'alpha': '2.00e+01', 'base_kernel': 'edge', 'height': 7.0}   29.69±0.34        36.96±0.71          35.82±4.71                        7.08\n",
      "{'alpha': '2.00e+01', 'base_kernel': 'edge', 'height': 8.0}   29.82±0.63        37.46±0.89          36.74±4.72                        7.86\n",
      "{'alpha': '2.00e+01', 'base_kernel': 'edge', 'height': 9.0}   29.60±0.67        37.24±1.12          37.54±4.34                        8.73\n",
      "{'alpha': '2.00e+01', 'base_kernel': 'edge', 'height': 10.0}  29.38±0.79        37.34±1.29          39.45±5.83                        9.4\n",
      "{'alpha': '2.51e+01', 'base_kernel': 'edge', 'height': 0.0}   54.26±26.40       54.52±22.51         56.61±28.88                       0.84\n",
      "{'alpha': '2.51e+01', 'base_kernel': 'edge', 'height': 1.0}   31.46±0.52        35.77±0.79          35.60±6.73                        1.8\n",
      "{'alpha': '2.51e+01', 'base_kernel': 'edge', 'height': 2.0}   30.47±0.59        35.51±0.99          34.32±6.63                        2.57\n",
      "{'alpha': '2.51e+01', 'base_kernel': 'edge', 'height': 3.0}   29.93±0.55        35.56±0.79          35.09±5.56                        3.47\n",
      "{'alpha': '2.51e+01', 'base_kernel': 'edge', 'height': 4.0}   29.49±0.60        35.27±0.84          37.93±6.35                        4.35\n",
      "{'alpha': '2.51e+01', 'base_kernel': 'edge', 'height': 5.0}   29.72±0.49        36.15±0.89          34.44±5.10                        5.18\n",
      "{'alpha': '2.51e+01', 'base_kernel': 'edge', 'height': 6.0}   29.54±0.59        35.93±1.06          35.54±5.90                        6.32\n",
      "{'alpha': '2.51e+01', 'base_kernel': 'edge', 'height': 7.0}   29.64±0.34        36.46±0.69          35.33±4.64                        7.08\n",
      "{'alpha': '2.51e+01', 'base_kernel': 'edge', 'height': 8.0}   29.69±0.55        36.89±0.82          36.17±4.73                        7.86\n",
      "{'alpha': '2.51e+01', 'base_kernel': 'edge', 'height': 9.0}   29.50±0.62        36.68±1.01          36.98±4.33                        8.73\n",
      "{'alpha': '2.51e+01', 'base_kernel': 'edge', 'height': 10.0}  29.28±0.74        36.75±1.19          38.89±5.85                        9.4\n",
      "{'alpha': '3.16e+01', 'base_kernel': 'edge', 'height': 0.0}   38.48±1.99        40.61±2.06          40.03±6.61                        0.84\n",
      "{'alpha': '3.16e+01', 'base_kernel': 'edge', 'height': 1.0}   32.36±0.52        36.32±0.78          35.99±7.05                        1.8\n",
      "{'alpha': '3.16e+01', 'base_kernel': 'edge', 'height': 2.0}   31.04±0.59        35.67±0.97          34.47±6.86                        2.57\n",
      "{'alpha': '3.16e+01', 'base_kernel': 'edge', 'height': 3.0}   30.28±0.53        35.52±0.75          34.97±5.64                        3.47\n",
      "{'alpha': '3.16e+01', 'base_kernel': 'edge', 'height': 4.0}   29.73±0.58        35.13±0.81          37.75±6.63                        4.35\n",
      "{'alpha': '3.16e+01', 'base_kernel': 'edge', 'height': 5.0}   29.86±0.49        35.87±0.85          34.10±4.94                        5.18\n",
      "{'alpha': '3.16e+01', 'base_kernel': 'edge', 'height': 6.0}   29.66±0.56        35.65±1.00          35.30±6.02                        6.32\n",
      "{'alpha': '3.16e+01', 'base_kernel': 'edge', 'height': 7.0}   29.67±0.36        36.05±0.68          34.94±4.61                        7.08\n",
      "{'alpha': '3.16e+01', 'base_kernel': 'edge', 'height': 8.0}   29.65±0.50        36.43±0.77          35.73±4.79                        7.86\n",
      "{'alpha': '3.16e+01', 'base_kernel': 'edge', 'height': 9.0}   29.46±0.58        36.21±0.92          36.50±4.37                        8.73\n",
      "{'alpha': '3.16e+01', 'base_kernel': 'edge', 'height': 10.0}  29.24±0.70        36.24±1.12          38.37±5.87                        9.4\n",
      "{'alpha': '3.98e+01', 'base_kernel': 'edge', 'height': 0.0}   39.37±0.82        41.50±1.16          40.87±6.85                        0.84\n",
      "{'alpha': '3.98e+01', 'base_kernel': 'edge', 'height': 1.0}   34.71±6.61        38.17±5.82          38.07±9.75                        1.8\n",
      "{'alpha': '3.98e+01', 'base_kernel': 'edge', 'height': 2.0}   31.79±0.59        36.02±0.96          34.83±7.11                        2.57\n",
      "{'alpha': '3.98e+01', 'base_kernel': 'edge', 'height': 3.0}   30.79±0.52        35.65±0.71          34.97±5.74                        3.47\n",
      "{'alpha': '3.98e+01', 'base_kernel': 'edge', 'height': 4.0}   30.10±0.57        35.13±0.78          37.70±6.92                        4.35\n",
      "{'alpha': '3.98e+01', 'base_kernel': 'edge', 'height': 5.0}   30.12±0.48        35.72±0.81          33.90±4.79                        5.18\n",
      "{'alpha': '3.98e+01', 'base_kernel': 'edge', 'height': 6.0}   29.87±0.53        35.48±0.94          35.18±6.17                        6.32\n",
      "{'alpha': '3.98e+01', 'base_kernel': 'edge', 'height': 7.0}   29.79±0.37        35.76±0.67          34.65±4.63                        7.08\n",
      "{'alpha': '3.98e+01', 'base_kernel': 'edge', 'height': 8.0}   29.70±0.47        36.07±0.74          35.43±4.88                        7.86\n",
      "{'alpha': '3.98e+01', 'base_kernel': 'edge', 'height': 9.0}   29.50±0.55        35.83±0.84          36.11±4.43                        8.73\n",
      "{'alpha': '3.98e+01', 'base_kernel': 'edge', 'height': 10.0}  29.26±0.67        35.82±1.06          37.93±5.87                        9.4\n",
      "{'alpha': '5.01e+01', 'base_kernel': 'edge', 'height': 0.0}   41.78±0.74        43.71±1.10          42.98±7.21                        0.84\n",
      "{'alpha': '5.01e+01', 'base_kernel': 'edge', 'height': 1.0}   53.47±24.05       56.16±26.70         54.78±25.25                       1.8\n",
      "{'alpha': '5.01e+01', 'base_kernel': 'edge', 'height': 2.0}   32.76±0.59        36.59±0.95          35.41±7.37                        2.57\n",
      "{'alpha': '5.01e+01', 'base_kernel': 'edge', 'height': 3.0}   31.47±0.51        35.96±0.67          35.13±5.84                        3.47\n",
      "{'alpha': '5.01e+01', 'base_kernel': 'edge', 'height': 4.0}   30.63±0.56        35.29±0.76          37.79±7.20                        4.35\n",
      "{'alpha': '5.01e+01', 'base_kernel': 'edge', 'height': 5.0}   30.52±0.47        35.73±0.77          33.83±4.67                        5.18\n",
      "{'alpha': '5.01e+01', 'base_kernel': 'edge', 'height': 6.0}   30.20±0.50        35.44±0.89          35.19±6.34                        6.32\n",
      "{'alpha': '5.01e+01', 'base_kernel': 'edge', 'height': 7.0}   30.03±0.39        35.59±0.66          34.47±4.69                        7.08\n",
      "{'alpha': '5.01e+01', 'base_kernel': 'edge', 'height': 8.0}   29.86±0.46        35.83±0.71          35.29±4.98                        7.86\n",
      "{'alpha': '5.01e+01', 'base_kernel': 'edge', 'height': 9.0}   29.63±0.54        35.56±0.76          35.84±4.54                        8.73\n",
      "{'alpha': '5.01e+01', 'base_kernel': 'edge', 'height': 10.0}  29.37±0.65        35.52±1.02          37.58±5.87                        9.4\n",
      "{'alpha': '6.31e+01', 'base_kernel': 'edge', 'height': 0.0}   44.96±0.73        46.69±1.07          45.86±7.54                        0.84\n",
      "{'alpha': '6.31e+01', 'base_kernel': 'edge', 'height': 1.0}   38.68±2.24        40.88±2.18          39.95±8.19                        1.8\n",
      "{'alpha': '6.31e+01', 'base_kernel': 'edge', 'height': 2.0}   36.00±7.12        39.78±8.77          38.26±9.07                        2.57\n",
      "{'alpha': '6.31e+01', 'base_kernel': 'edge', 'height': 3.0}   32.37±0.49        36.49±0.63          35.46±5.97                        3.47\n",
      "{'alpha': '6.31e+01', 'base_kernel': 'edge', 'height': 4.0}   31.33±0.55        35.63±0.74          38.05±7.49                        4.35\n",
      "{'alpha': '6.31e+01', 'base_kernel': 'edge', 'height': 5.0}   31.08±0.47        35.90±0.73          33.93±4.59                        5.18\n",
      "{'alpha': '6.31e+01', 'base_kernel': 'edge', 'height': 6.0}   30.66±0.48        35.54±0.84          35.34±6.54                        6.32\n",
      "{'alpha': '6.31e+01', 'base_kernel': 'edge', 'height': 7.0}   30.40±0.40        35.57±0.65          34.42±4.80                        7.08\n",
      "{'alpha': '6.31e+01', 'base_kernel': 'edge', 'height': 8.0}   30.15±0.45        35.73±0.69          35.30±5.11                        7.86\n",
      "{'alpha': '6.31e+01', 'base_kernel': 'edge', 'height': 9.0}   29.87±0.53        35.41±0.70          35.68±4.67                        8.73\n",
      "{'alpha': '6.31e+01', 'base_kernel': 'edge', 'height': 10.0}  29.59±0.64        35.32±0.98          37.33±5.87                        9.4\n",
      "{'alpha': '7.94e+01', 'base_kernel': 'edge', 'height': 0.0}   48.89±0.71        50.43±1.05          49.52±7.79                        0.84\n",
      "{'alpha': '7.94e+01', 'base_kernel': 'edge', 'height': 1.0}   39.52±0.76        41.71±0.90          40.53±8.79                        1.8\n",
      "{'alpha': '7.94e+01', 'base_kernel': 'edge', 'height': 2.0}   70.21±65.19       69.38±59.73         68.55±60.59                       2.57\n",
      "{'alpha': '7.94e+01', 'base_kernel': 'edge', 'height': 3.0}   33.52±0.48        37.27±0.60          36.00±6.12                        3.47\n",
      "{'alpha': '7.94e+01', 'base_kernel': 'edge', 'height': 4.0}   32.25±0.54        36.18±0.72          38.53±7.77                        4.35\n",
      "{'alpha': '7.94e+01', 'base_kernel': 'edge', 'height': 5.0}   31.82±0.46        36.27±0.69          34.22±4.59                        5.18\n",
      "{'alpha': '7.94e+01', 'base_kernel': 'edge', 'height': 6.0}   31.28±0.47        35.80±0.79          35.66±6.78                        6.32\n",
      "{'alpha': '7.94e+01', 'base_kernel': 'edge', 'height': 7.0}   30.92±0.40        35.71±0.63          34.51±4.95                        7.08\n",
      "{'alpha': '7.94e+01', 'base_kernel': 'edge', 'height': 8.0}   30.58±0.46        35.77±0.67          35.49±5.25                        7.86\n",
      "{'alpha': '7.94e+01', 'base_kernel': 'edge', 'height': 9.0}   30.24±0.52        35.41±0.65          35.67±4.82                        8.73\n",
      "{'alpha': '7.94e+01', 'base_kernel': 'edge', 'height': 10.0}  29.92±0.62        35.27±0.94          37.22±5.86                        9.4\n",
      "{'alpha': '1.00e+02', 'base_kernel': 'edge', 'height': 0.0}   53.55±0.70        54.91±1.02          53.96±7.97                        0.84\n",
      "{'alpha': '1.00e+02', 'base_kernel': 'edge', 'height': 1.0}   41.96±0.66        43.95±0.83          42.75±9.13                        1.8\n",
      "{'alpha': '1.00e+02', 'base_kernel': 'edge', 'height': 2.0}   38.44±1.04        40.51±1.29          40.16±8.00                        2.57\n",
      "{'alpha': '1.00e+02', 'base_kernel': 'edge', 'height': 3.0}   99.24±99.72       92.78±86.06         95.93±95.47                       3.47\n",
      "{'alpha': '1.00e+02', 'base_kernel': 'edge', 'height': 4.0}   33.61±1.13        37.24±1.34          39.38±8.20                        4.35\n",
      "{'alpha': '1.00e+02', 'base_kernel': 'edge', 'height': 5.0}   32.79±0.44        36.86±0.66          34.71±4.71                        5.18\n",
      "{'alpha': '1.00e+02', 'base_kernel': 'edge', 'height': 6.0}   32.08±0.45        36.25±0.74          36.17±7.04                        6.32\n",
      "{'alpha': '1.00e+02', 'base_kernel': 'edge', 'height': 7.0}   31.62±0.40        36.04±0.61          34.77±5.17                        7.08\n",
      "{'alpha': '1.00e+02', 'base_kernel': 'edge', 'height': 8.0}   31.18±0.46        35.98±0.65          35.87±5.40                        7.86\n",
      "{'alpha': '1.00e+02', 'base_kernel': 'edge', 'height': 9.0}   30.77±0.52        35.57±0.60          35.81±4.99                        8.73\n",
      "{'alpha': '1.00e+02', 'base_kernel': 'edge', 'height': 10.0}  30.39±0.61        35.36±0.91          37.26±5.87                        9.4\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "calculate performance: 100%|██████████| 13530/13530 [12:40<00:00, 17.72it/s]"
     ]
    }
   ],
   "source": [
    "%load_ext line_profiler\n",
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import sys\n",
    "sys.path.insert(0, \"../\")\n",
    "from pygraph.utils.model_selection_precomputed import model_selection_for_precomputed_kernel\n",
    "from pygraph.kernels.weisfeilerLehmanKernel import weisfeilerlehmankernel\n",
    "\n",
    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
    "estimator = weisfeilerlehmankernel\n",
    "param_grid_precomputed = {'height': np.linspace(0, 10, 11), 'base_kernel': ['edge']}\n",
    "param_grid = {'alpha': np.logspace(-2, 2, num = 41, base = 10)}\n",
    "\n",
    "model_selection_for_precomputed_kernel(datafile, estimator, param_grid_precomputed, param_grid, \n",
    "                                       'regression', NUM_TRIALS=30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "--- This is a regression problem ---\n",
      "\n",
      "1. Loading dataset from file...\n",
      "\n",
      "2. Calculating gram matrices. This could take a while...\n",
      "\n",
      " --- Weisfeiler-Lehman sp kernel matrix of size 183 built in 13.253133296966553 seconds ---\n",
      "\n",
      "gram matrix with parameters {'base_kernel': 'sp', 'height': 0.0} is: \n",
      "[[ 3.  1.  3. ...  1.  1.  1.]\n",
      " [ 1.  6.  1. ...  0.  0.  3.]\n",
      " [ 3.  1.  3. ...  1.  1.  1.]\n",
      " ...\n",
      " [ 1.  0.  1. ... 55. 21.  7.]\n",
      " [ 1.  0.  1. ... 21. 55.  7.]\n",
      " [ 1.  3.  1. ...  7.  7. 55.]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9497f6e828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman sp kernel matrix of size 183 built in 26.24978256225586 seconds ---\n",
      "\n",
      "gram matrix with parameters {'base_kernel': 'sp', 'height': 1.0} is: \n",
      "[[  6.   2.   6. ...   2.   2.   2.]\n",
      " [  2.  12.   2. ...   0.   0.   6.]\n",
      " [  6.   2.   6. ...   2.   2.   2.]\n",
      " ...\n",
      " [  2.   0.   2. ... 110.  42.  14.]\n",
      " [  2.   0.   2. ...  42. 110.  14.]\n",
      " [  2.   6.   2. ...  14.  14. 110.]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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8ac1zhpaumkx6nQ6hhPMSMDvX1KVbyNKhw3nYtjVgVn3acWjnSGIOx2bNTeMkisvYu3ASU5dMX+PlBZSaW04bgXg4hiMgSQCKvtzvsmNLagW0Y1D7ALB34SQqN9sY16uo3DQvhHzRS8K80Y1ZZG9eh5qqeA5Q59Abes69rNuDqk9PmDPS0azr04jS1JhOa3eg6Pz6NPDWGh8PCKeqjTRJzEroPDYmizMZKBxqnHtxrrM3On8G2ZvX+TObBlttb3PywtnCjBjdaULFCTLRpuyD5iw6UnfPrHAuUpueg/Rey4si0fl0TXKxoPYzuPdjfK81EZKW90CG0WkevdB+c3N/cqMcKRychRRSyIHkcIROVUP/YPKTE5qFdO7RKhmGPnU6NH6CQcqr5v2ffAqzL7zp/w6zi0T1GrZ/9DTmvnzDNGD9FxQyU9a2z9687vwCbOP5uA/A+haEWeGBtQLEqHM+Jf4OLFTFPLBOtDDv7HVrU0snq2xXOrBk+CwMK3Oo0vpC9KsXJ9CiZKoQzqB8fHliztiX0u0Dre0JqDhrA6snWB3PGxMAD4A2Xl7gceUhUQnABcAD0vGcBeFfCZmmviSwSs551umgfHzZ12pFuoGU8B6GIDM+bh9YeYitkT6LgziU8+D5EuAWhozDcPnL6i8KUFYByipAWfR3Acpyi1cByipAWQUoi+akAGW9b6Csw+HgRIGzoO8KnEWBs6DPBc5iHylwFgXOosBZHG6cRRENKaSQQg4kh8Nn8YBoSGgWSBMAcDuwSnycBe+y9nfAaAEhzoLUX/JvuJV46PkjALBGknV7nDpP2gwAD2fBO0cS826krbmk69MYnJqfxFkAPs7CgoZIAwFsbD0HZ0F9U/sAMDg1j8rNNrJ6lUFdfIzVkEgkzkJqHdKnIO11nQ7dDgZnHnn3pzFnNAb7G2s89emJyAJrKYSzCLAeE9cLp6FJnAXdu7fDWYQ+Buorj5aA/A9hREP6e/KeWRLZJmt6NnL2IJyF1C724yAJneKhSRuCwEKw2kud53A/23qEfBZUbSv0ngt/gfzsOeBsOFSnKabuCaRk8DsATN0bYu9ojCnxOyDURIvCnJCKQ4aS+i3HxG1YsNDE5dlKamxSdXcBzIsbt+ActKEjU4R1gUn1Wvbhtw8A8/uPodc3CwCZTenQOVPFw+g9XHYe6MliwBjIrg5eEvs7R6HsIqaGI2R7PtsXg7O6u0DFL9VAQDzeOOxiwCabIKfhvsVLo9Mhz6vzO6W8sEkTTLKrsZ8izaH7lwuqeGHJRyRFtun5dHL8Pnyf42TCX5R3/ERRJRq7GA8JL1RycXwHZsih1ywKnEWBsyhwFvs7lAuchYRz54lVbwFnLsjdl1Vx+/DmqdJkssx9+Yb3Mkv4sVwQAPALsvOJ87wYyRdP9pWeW2YThbWPxixUrw9dq0Kv3XYw8BvrhslKvGzSjKJ+ARinVTrE8NgRzwRSSeK1DwB67bZzAgqmLUDE/sXDrlZPYDhfdVSGMmQn8Bt0neN7LWbgUsPRBH5kP3WcZHhhFaX/+LfmN5GvMoFxsRtBaC6EYda8MLNKYq8fKWReyBClHLsM1QLA+GNPeuMNncTUhhxPOI7oK6+Zz5ZWcXRjLTd0modRGX3onHcdeeFjiasJTXaK/MhxvZQ9j/udWwWfRSGFFPLeyaHRLPJAWWHiC32mHQ8A7/QydKpm6hjfajLXpgydElIzL3RKJgVgbHpynHo+iweETtHa9rWQIHRKEpoLdB2eyRKETkktp9ApgInQqWxfthkeK1GTeaFTJcKsUoOT9yEP4Jbd7yI6veKTL+8TOqUwJ2lXoQnjz1ds5sOaYoS6nUD8PgBHI1VvAAwgk+MnJzFpJyGnJzt1YUweyWsZnT9j2mhu8nGcoSr5XnM0D4kV4TkOgWzWjFPLixhfuQYAKD31OMYXL3vmBiFFw9ApMHl/VBLjpdb/+4iBsrTOnbAMMGS6APCtK/w5WrvjLSKzF9sYHBPgpUHqZf/NXrSx95wU9dmLbew8NY/Z5iZ0XBap3DvG3OnusvoNwBz7wuZE35XXr/PxoPZFZAUAq/K6Pg3VBS9CutPlRYZT1OMy1EzdYCy6PUTdaW6LIzzypbS+GWofgOnDjqV3xiwWtZfe4giDn9ErPOWBbT7hRCOTb3mRIwzRkbozpYTpkwH+okBt1KrAVltgUJJcE4Z9DFtt/ptecvqfF8RO11PB6XxtnbeAQDpa80pCsCNYm59MwACdqeXiSQ5LemZDv1ZrG7D3NBORHBmF4fm1TlJ53dQHH0P3RG48zU0Gt0kAnKJjgudDD1Pv/kSBo//t5NBoFj8Yf2ri+9Amo8+SRVs6+RgCbtPOQydamFYuZecT5zH76oaX8yEhtgA8Z2eorYRQ3DzYN9v4rW1kq8cRrd0BAPQ/ehZTL14255MGYUOdqrs7wRgesohTH7J9AMhWj0PHEdL5CqYvb5gx3GoiOr3C7ZLzdzw/A3zryoTDTb54YQgZlcTzY/D4BIhN3icPiRrAu9khLHwUJPTC5+3Ksg1aPPIcfnkOyrx2w3A99cWLQ46fIiymLI+neZvg17DPJTmOw99lmzJULtuVPha+Xhl5CTkxBKKX5GvdP3r0NAsgB5obho7ocyWBksQxdocmCDjtvop2HfG7soQg8sHXcRmzr25g58NLHCWJjtQNHuBeCyA+i14f2uIAZl81L5/EQUiujbyHvnS0YTSPmbpZKOxuO/2NdejlRYzrVUSpCXFyqLMxiwgitGg1JooAQfwm2wecyVK+CadtTFXMS5PE5iEm4pdaFbDRJm+Xa8xxOJOPpWsFcp3SlOsiHY7yIVVJzOMPXygVODPZhGlu+g++VfPDlyx80altbXdUDyHZmPN2Xwr/krYhxzbeG3h1OKgPNkNE8mPW7fmQ9DSFWj3BOUyAj7nYLxmShJ4rqgci65HkOnnt4qha2w4hm8RssnjyDqqoH3rNQkYM6LO8kYCx58a1hIlrSD2WYTsA5oGzUQMK46nVE4YpywKkKEoy+8KbGJ87ifLNTW93HHzoDJJX3vS0DWOavOkBwMK6IICfTRsms+n6NJDE3rhkOFbW/WAVWiymUoX3sB/28+iUmcfS1Vvcf6j25z2wdB0TxYeCCIm8pjCLlu+jMDkATJCzTGgwwISGEY7Lw2+QtiTOl+FsmXhFYyudXPYyjcMEQe7XZuOG0RLa8cPQNAPq4BPs5F3v2yUAhpGiB2UpywVaRoZk//Iav3rntw8MyiqiIYUUUsiB5NBoFnnRkP0kXDFJVZVQa1nximxocpJJFZDs73CXW//FJ7BwMUX169fYXJDwaE4TPrlsdtflRajWDm7+/FkAwMrzW8bxebfL6EGCX4/nayjflM4nC3O2WAUW8R077EjjaMyyM5b6kO0D4D7CyMt4eQHjWoxk3XFx8DUInAZpNuw8td+juemwLiIRrP/Rs8Y3IuDpuj7NJpXkMh2fO4nyxo5vwpGmsryILDEWcqndYQcwz401BWn3lnMWwtBpd6c5lFwaHK2gSJGNZEjoOV0btZXHFVI62mBTV0bh6LnRa7cnfDbyvudFgiRsX1kzkPA2krOVE+eEFsscpQvzXnRoQtM9fwYvXf48dtKNR8hnAd+h44WBhCMor/ZodKTODxNxPEIAquh3wKm3XsjM3rASzINNL9rCxRRbTyU49Y3EOcYofNfadh7yThfjcyeNCTRTx8JF5x2fovCrIM9BaxulJPZfosYsxrUEo3qCqUv2hbIAK85MJVh2r8+Rlqlen8fAfdj2AfGiNmbdw9jaho4jlHpD8/DRA5kkpu1OFyBTCsI7P0iZ2xOAMZnSIUbHjpiP5GMRxLoATF7K2h1/DhpzUMPMXxjFuTodYmgXwlJzC0TYy+rzcOTU/IFT98m3EbbpFoCh75i0C1RIrMzPhgTGAf6LF8DuZbaryX3pcfYtO1KD8LOaqQPdXYxzTMjxvRZKdLBYFOQx2VbbIVMpmiYg62EYOUwZQDoExhkOKodDs9in1mmejRpK6GEHrI8iB6L9oN/z8BsqSXDz589i5QtveMeGaFEA7Cjl0JaNccvdSO4IOi57TM0SBk7XLjWgvQsnAQDxl79p6q2mI3cNIpmO2gfA4/F8JLQrW4Rr3vXzGOwOTX4BWSeVcQSCQySEPksUarrSYHYziXMJ/Q3hdfM4hSOZEtHYNifNT4StvcXJao5SAyC0qfQ3eDB54UCWCW58voX4y+uXIv05NCchi1l0pG5Yz99a8+aONGPpa5Fj2i+y4j4nE0RMUrPxyG/0nz9imoVSE7Fikgm6MWtW0M0hJxUGLsFL25c022q732EdNJWEf+c2OzY5TTq1Vk9ANzex8oU3sP6LTwAApu9maPyZcWQqUrXtqq8IrJWHJ6AdeTjC1g+fQOO1tgfsMg+iuYkyj0U+JOSA1adXEO4F3IdoHzBmxOjcSZTaPaihnVua8u4udGMOsBpBRIudWMC8W9Td9aIZajhyYDW4hzG8Br03QAQgvtT15iabn+FMW26DXvp06JyzXavhyMVQmhidrgMZCdh/+PRHp1dMRESGcvl6JnN+ALdAT13bNDwX9ZpzYG+1jXYVMInRPSP6RcABuGRfZpFKzByIkDswGRGRv8n5Hd9q8rMvgV98bOg4tRsYHVM62gAm0132lcLBWUghhRxIDodmsQ/O4iCipirO8ROgIOXvAFj9VUniOeEA5yNg/EZrx+AVBimm75q9fPdYhAYwUd9DJbHxL9B5tq8sHRrGLdIsqM90aLAipNImsVdgyBuToO0D7E47X4Nq913xIupDtm/HMKonKPVS1iCks4zNERhcBzkNee646I6ZszC5jcYIwPk5rH8hV2hcSczFkyTKFJjmNP/QGSjnAJhUvQEyWewx0slq+5kouEMOvwmAXzzxfFA7Dwp3+scOEZFPisYqEwJFe1LL0XsDF/YMM1AHtn/pOxIpCNQv+Wa8rF9Lf+BpHmnK795B5ND4LPJS1NVUxYN70+do7Y530SFWAvBvLOEsZIUumcVJOAk05jA4ZVS8qUu3LCzbf4FkximdL+HeYT6A+duHe0/Yv9JBKexyNRyxjSpzEkJ7mPqQ7QO+Dd/7+AcAGLi3JPYhmcAVCAlxIdSfWj0BCfeWZDcAcv0fct4oSkB9yIhU6Pc4SEq+xI6EcG8S8osRatKDe1s/gYyk0XUAfgEl8nfIVPNwruiejm81PYAXteXP8SRdQR6ylHhDgXxQFt+LQCjXRZ5TOtrAi80vFSnqRYo6ihR122eRom7k3aaoH5rFosgNKXJDitwQJ4cxN6RwcBZSSCEHkkOjWRR8FgWfRcFn4aTgs3iA5GErMsCz6+mzvrE+wWcxrokXz77wIZ+F/F3bh4r4KKZaBnq886x5UWZf2HSJZAJSOzhWR7J2m1Vy5sPISyTLSazyxiEzZxtz0CKRDLUq1CBFtHbHIPxs1IIAS1m3x+3T9/mOLfNS0/yUmpv8kmT3uxNgIACOO4Guwx7jJ2iZzF6Ia4iO1H2+hCN1RhJKPguKRnncC0ImKq2lQ2gB+mI4c0AETBiRgyaSje+1/EQycW0+KbNlT7+x7o3XY1kP+D+14LPQ+2SVer6VnAigt3naxUm1tt2xOXwWAHjhVQJTwe9XsKm8E2Xh0GsWeZTwADzNQuYKAM6zzjtHiPEPEI15jkUPgRloG6Zfe7xdxdd/8QksvjYweRpWBsfq2HymguNfsR74m5suh2B+hn0WlFdC0RcA3t/0GYAJLQa5IdSHbJ/7sCnvFLYcz9c4J4M1HxBIy3eQjmsJyjc3J7QpCa/mVHqLSM3NBbHnE8gJMEAnABgtGY2n1Ev9MpNhdMhC4gGTORu+0J5IhKhtixZ8L/U90BxHS7OcZSwr3MnQO403unSD22MfDckgxejUosuCtkJOaMBU0kuuNhnUR76j0Q2rHQeOSEJvynalf0f67kanFhFdujGRGxItzPM1AmYh/lr/jx8xBOc+TFljYW6M77X48/hey1tEVGvbUNITYs4uCpw+TKtpY86g7sSKSzn/EcGNOcdih3NBZAKZrM9BfamZOhZfG2DzmQpOfckiLdMUlXSIRcxjb8m8fLWeexm3n5zBQtssInvH6qDHQi4KDCEHvIWt/bMlAAAgAElEQVQDlQRobqJir4H6kO0DwPaTM5i90sOonvAiVt7Y4X4IG8Kf6Trtglgm3IpdnBgnIfEDdlzZ/IxhmrJIR8C84FlSNvkd9WnE7T0AxnlLLyqNhx76aGEeqE8z0hQWVq1aOyj37MtrEbS0CMkIFvFs8Iten0Zm75fURkdLs4i22h7mpryx4y0UrFESM3m3xy/MWDgP984uci2aaGEeOk1R3nDV9ACBf2jQ4miwNsQYNp63dWa3XKqD3MBoLOWNxOWwCG1LQtXLGwm0PccL1Q5SvkaWRy43pMg6LbJOi6xT77fDmHVaREMKKaSQA8nhMENgtQVOtplEs3lgm4AODYPU0LFJzUQeQzua+J0wGcnVplmtpyqebbvy/JY5XyaGWVzB8MIqyqTKDVzikk5Tcx6A9U8u8N+0s05dM6TApAo6z3rPpF3Xqg4qbX0m6YVVxHfLE45A2T71IdsHApYpscNGa3cMJV4wvwCw/ewJphak3VEBRqUWmbpk6rF5lCRGCwuTslopkMMMVmr3sP3sCQdus4l7KrGJfqQ5rp4AalWgtePuPyV1UcKY0ABUEhu/jkgU3H72BI786UVv/jTd29a2cyqLeVAzdTa3MqutbH94iduZSHWn8ynCYaH+oLlbXsT2U/OYe9n2ZVPreR4F7kLFCcZ7A0A4YxVM5O7In150uBcxZq9QEWlX3V3ng8vRYFSvj3H9wVq8lEOzWPiYdQcC8rLx7GdtqeUAmAiCtV09oI49hn4HACUAQhRm1TK8NHAl6gfH6oaPQoaebGQgvrTG9ijlbwyO1VFJh2warDy/hfVPLmDxtYFhCqfjbbZiVK8hFVwQulY15go9+IAzf2yOBo+j2+P2AXh9UPs0XwA8h59UYZVEhtp+Z650XLblpVvQsI7duMzHjOtVqLfWfIj46gk2YaS5xg5iuxCwtLYxc6Xqvuv1MRbVzSIOOw6Nn8lykdL1o5IAtBiGjuvmpsuuTRLMvXzbPAfp0Hee16uIgurzOnVgs5CHZO7lEfOxcl6HdbzTnCWvvOkqwRFnab0GDZiFQppoNKci5K4ESE3ev72zi+Z8gSzeu3ASyStv+mFtihAlMfYunGRHshbPBP2dbbVR2ssPV+fJoVks3pWEEOkwCSnnd0d+I/IGhFe5crfrbGVrq0ciGhK2vflMBYuY96Ih5PQ83jUvffnmpoeYlAvWftGQhF48sYjQw7f42oD7Pt5d9NqnPjgaYh2lbxcNKbU7fM7o1GJuNKQ0HAG2pGJE+S3p0BHkyJqog9Q4KZNkIhpSanccN2gvdcWh05TDjtKv4HhEU+e8G/j+mBBHo9MUqpJMhhAX5h1mJYyGCMcgzTcJjUFGQ7Awzy8lvKiFSAJsbhoNKy8aIlLqpZOfXY/dHqbsXMpoyNS1TaZVkLkpFA2Z6gmfhY24yGiIToeAPriD83AsFg+oGyKBK/RZ7w18uHdrm1VFwEVD+OUX0RByGDJYKcgf4Th8Y845tKjOaFzmY+X52f0ujn+lg72lKkco1HCEqUs7ON5dxJ0fMR7uxddMVEL1+hgsVZHE7uUpwUYyRBbo6NQisqSEUa1sVHxYFXNhHqrXZ22C+pDtA8BgqYpoqFHupijb77zwbS1hNiZdnzaOuHqNuTrKVqnLkjKiwElKY6RozfDYEZTqVeBbV7xQ4nh5wYSIk4SjITqOWAOhB3e8vGDYymw/6YrRHAm6j+YmyjTnAKvZocMPg9TXCurT0K3tfSDXieeApbGo5UVAOJtlXZIyOWRFO6OlWV481OoJ6K02yjfBJpmX9GYX/xj2+WzMAlttnkdJ/CQXOHLOl286rYm+i+o1XoR0c9Nch3VuesRAg9ScL4Fo7yDAUTg4CymkkAPJ4dAs9hEJ6x7vDVwSFYLsPru6Zta/ENVrftIPOUytLStXYtiUbwp5kTrnUtUdFwQGKZQNIXqVuI7UoW5uotabdedZtbR8cxOLr5kdZvOZCk79wSZ2H1/C9OUND0OhG7MTVHtkAsR3HQ+BWj1hMCACfEV9yPYBcPIYJX0BbjdTANQwExXYbgHUthWyvUvNLejlRecHaO2wqrv3Q48DAKrrHfTOzGL6rYq7LgD9kzXUmzap7y2Lh7AZmInASJSaMGNMjXnU+b4pAECjvQi0dhhoBwD44GOWmzOAzMdlIOAAZWcn+WyCsLycbwqfU7U46RRWScJpBLIdNVVB1O45n5LFdDCNH40tpE1MjX9M9fpmjHYcSpg8ktHKaMkJo04B459i/Abhc8R1AHBJhRa+LtPpo3oN6B8oamrG9m5wFkqpGwA6AMYARlrrjyqlGgB+F8BpADcA/KzWOh+wb2W/rNP9REJ0w2xFwKH2iEcg9GVIhGBe7J4+E//k1k+c5r6JVo8JbcJ4viAmYe4JgQC9+TMruWjL/fgp6EWXzrK9CydRudlm5yv1IdsH3GIjwVe8cEhCIMAzzUKQ04Qv6AEcoiFVgFdXQzpvgYnzhxdWmaczjw9EjoNwGbImh3w5JVKWFhbvGgBvrNS+bJuAUqV2hzeTMBtWEuzSGKhd4mIh/pW8OiuyhgsAl2tyeoVzQIj8hugkPVq9oBxiXq0QwDo+KR9HREheuv5/f0cRnD+utb4nPn8OwAta619TSn3Ofv7nD2zhAUxZtArK/IrwxVJJ4nFdqq7/8vEiYZ2GfDxgIgKW+wIzdXY0jeZrhiW712dOS4pW6CTOJQTWtSpDkssbO44d2r6su48v4fhXOrjzIzM49Qc7Dup89RYvVjK6kK3dZnJhekB0reqcaSL9XvX6XvsAcOoPdtgxOT5n/CPs3LKLCL0QaqvNoCyZc8IvJJEQwTBuj5dmUQIYABZdusHANFoUds82MH05cSziMvzbmAsckUPEd++bXJAPrLKTNUvKKLU7Xtr68MKqcQ4PUh94JKHTxIqejphtm/qh+UU6tFEakR9DuTCDlGkCqHKark+7CExwPLN8E7hsq+2cy3Ds7KEzlhexHI2H3oOwEprUkkiDmWC9D85RSYLRjbXJimTqO1SRzGoWH5WLhVLqMoAf01rfUUodB/CXWuvHH9TOEdXQH1OfmGxf4ONJhQo5LqQXWIav8hJ3Bh86w79zH3Z3YEccf+9XugLADzc90AD4nGz1uIFw//sb5jPxWywvYGDh3oxurCS4+TMrOPUls3Ns/+hpzFzpQMfuxqlh5h5WOKwGMWFJyDn1IdsHgJs/s4LF1wbYOxqjfsM85OWbm1zygKHWME468rJLzYA0C6m5AeA2Sm378liVmvgyWOz3Oi4jq9uoUjryWMtMn47cx4PX5ywAfLw9NtzVQ8nudxGdPwOvSp1gLveyivM0GsEIFpYcZDa3b13xfp8Ygz2eslN5EQQ8bSFk/wbgmWBSu5Es4CErPfcnyHwoE1Ze44tb/8+BK5K928XiOoA2jIP6/9Baf14pta21nrO/KwBt+ryf7LdYlE+v8uSNt1re55DqPe/BC5ORABEhkdRzROIiMBcyBJeXQJWXlBbS1RObFe3qhmV7xOErgoaf+tI1Ew2wDw/gEqx2V6Yxvb7rQ7etGTS0OA3qQ7YPuIVBdXe9kF8eLTxHfgQITZNmI8KrALj8oySUoeM8H8DyghcO9cwY2xeXa1xe5MVnwhy0yXPeomCJiPLm3yMssgt+SHwT1WtIzy0judr0Xj5qm0LZALxoGqX3y5dW+sAoV0X62wCw6ZhHJSDHG5ZXpL+JIU2WUMTyIsYXL6P02FnveRzfa2H8sSe59i9gcEPlf//XnJpP/X5t8CfY2Wt+R8yQH9Fa31JKLQH4c6XUG/JHrbVWSuWuRkqpzwD4DABMYTrvkEIKKeQQyXuWSKaU+hcAugD+W7xTMyRa0B/DT7i6ITm+C3L8TPQrkG5EEKPeWvOg3Q/6nVTX/kfPYvobjhRGqrleJmhzE9n9LgY/8TQA8DmU2FV5/bo93yVfsR/DOjV1p4udT5xnWPXNnz+Llee3uCoZAETpGFE6dslWQbq0pMSjPmT7gCHmGceGlZyh4c1N1kJkItjglKlNkkfMC0xyknJSGTkIhRmCDz5m5ra55Rc8kvctSJrjBC7SGIRWmMcBKuuUTCTZCS1Gqv8S1r0fgU/oeKTvQrXem5t9Erakr4zIcthcIE2EgH6k0VkNiCrwyfap/9ARrZJ44vw8wuM8oufviBmilKoBiLTWHfv3nwP4VQCfALAlHJwNrfV//6C29qtIFnIIhjyIAHKjHXnkrvS7xzYNMNQ2JGgBjPOOqo4D8B58yTbEkRSJiLQQbk7vJrEZm2S/A8aGX//kAmbWM8y+usF9m3KGtyZChDQWLztUhIJpAcjqVVuqUNjh+2VAEpO5cEQyJT3Zu8MR9hPKKRnfa7Fdri1JUMiFauYt4ZeIvwuqnNFchzkNzDVBKFRRmc3z9sO9JHkMWnIBpGMBn4UdgJfhmteOzHKVzOlsCtH9C6JQFMGaSCVHABugkG7Qv+TUzLvmkDU+5K3V6RBf2/sT7AzefzPkGIA/NG4JlAH8ttb6z5RSrwD4PaXUPwbwdwB+9m1bUiq31imxAAFOswhLu/GDL28EnM0XvhgcWhI2HiByBawHW/X6GNUTlOUOA5h+LCKQRCexh7wEwLkekjfCw1UIB+NoaRYz6xk6KxFmL5obubsyjZnL234tDCuM/KMQme0j5L7Q1gdAEQsAKOX4KwAAyawbvxde9P0VsHMQahZT90wVMTVVcenlVlNQlEchF4xKYvsSdH5U5UxoUqq7yzk5bkwp16j1ZJDjO0qHJswbsH7zGMQ8MIEvhZEF9B6tlNuR80Jz5nFX0DWzzyNlpCh9l9GzZhnDNG9oNm+j08mNlHgkx4mrLTIR3qbrlz4+clbbY1SSAHs4sHzbi4XW+hqAD+V8vwWjXbyTxgCFCbg30dXT3/Q5u9/lY8lrrOBUu+xO0ywsw9SnmyMn0ZVrXghJwcKS05FTVZMYU5dST90HwFmmGSU9rd3hHVTXp52aJ+qDyKiKBu0eTosZ1RPMvrqB2Ysx3viM6ev8b3aw8fEG5t/oo2SLCwPmpivKNZA7H2kGcLsTsIisXvXIb8iEYNYpG8144zPzuPDrfW/BVTN19B9fQtIeQAntZHCsjsrNNlrPLqHxstGEKnctH0ZzE8ouuFKjkpyUlBg1demWq62xNAvV7mH9p5eNyUQvY62KvadXGO5O4wJMQpvkJCWHJeAcm8pqSmv/5Ams/vHWhOYHkfim05S1Fh2XeZFVwwyl7i6nBvA4yPkrNC5lnbEy34MyWKmINmCZwWyR6+hInZnnk/UWdK1qYPgE1SbTgoo822iTbm6i9NTj3rNgIPBDa0YJPtVe3/F4ys1itL+2GEoB9y6kkEIOJIeGKSvPwQlgX6enx9J8ctlLjSafBZkuso4F/S55C1h9p90GcFwWgoIPEPYp7eoyvVyAtdjhROq17T/r9kzcPikzriJLSojSMXZXplG7bjSAN39pBk983pABz1zpeAAfDmmSUB+ifdNuGVG3j+GxI0jnzLzVru/YxLCR57wltViaM+S0HC3Nen6P4XyVxy2TwyjsSXiXcjf1zmMk6UCo5YLvUw0NjEheK51H9r2cx2hhHulKA/Hd+3wNFH7uftDylWyniO/e97hCAbCPibQkupeAwT3s/r0LmNqwyXcbO5P0hsJ/RXMPgLlCyzc3PYc6aSGkrWRJCaXeEKXm1kTFubx6H5z0FhSuZh+RfUazetU5lgNcDNE20LhK7Q5evPXF74jP4r0Trc1kHBDBmd3veouG7nRNNe2gWTJFJtLKZdeUhk4PA6mkjTnj3ZeAFyK0Dc+XTitSB+1iIzEOlEKerd1GZHEFgIl8jOoJZi5vY+Pjpq8nPt/CG5+Zx2Nf7GFci33AGOFBREYhpZNT+wAQLS+i9/hRTG30UbtscXOtbUTWHJMkuFtP17H0h5dNRifhSVrbGK8eZ5WZMkE73zeFxmuGUZ2AY73Hj6LWM5gUWkAIeclzI3JGkMQmO9jem5K9lv7KDMq9keGotG1MQLZn6sa8GI44zdvM44hxMbXr5j6Oa8bHtPvRs6heawkfSQqkQ8TtPY+yXyUJ1PIiatd3PMZ4rrhGGwe94Els5oyu02bHZt0eotT6geo1wDoyywKromyOj0pTxsyULfs64GNEiBRIA26jaG46AJy9Llp8okrCET3APNeEDSk14eQdmCGHY7GAr03IgrASMy8/M4nJkbqp7tXtu92DeAmnKvw74B5eprGHyx0gAlh6eNXQrMxe9bPUsD4ZZ5GtXGYri6kk8diuU7JBWzvIEpMIziQ9dpfZXTEPw5G/uYPyTbPbzr9hXr6dp8xCceUXajj3+3u+f8ImYpFQH177AJAOUf/rNaCSOELYJGYtyKAIzbXNv1Hi3WtMSMtaFcP5KUTpGDHAIJ/KXGILQi/w9dYu3zMPbGOOgVjkBwKMdhDu7gS4Aoy2Erf7SNoDP3rDY5j1HcVJbPwAoihw74PLqKVDANPsZB3VE5Qac6iudzywV7Z6HIOlqlmYyJlKC1owNwDMomeJnQERPUpTU/lN+Deibh8RgLEdQ5SmGJ5bRlyrOi2VnNN2Llg72hsYYuqTyx4AbHRqEaWevVY7D+PV44aESKBbdX0aEYB0pYFSbwbjmnWYHqsjeeVNn9tzOPKLLL+NHJrFIk8k1Z78HIZDedehyAbl8lv1jR5ewDqxxOTSSgwYB86YNBjuM/EcnNlW21DSiWxJT/uwi0181yVajWr0QAyZmRuNOUyvW5WSUKKt1HBCAJi5MsS4FuPc7+/h6n85hQu/bmuU2hsd373vqaSjWtlvH/DyL3gO6IVIh9C1hEO4pd6QTQMunTgcIYtnsPnMNFae7zu8yO7YMFd1nbYRpWPzojQ3WbsqNbeYrEWLotGIy86ksAvI3U8uYOXf3Ue6MoME4AU2bveRxcpcEzOvmwI6BFGnhXlqo89oz6HN/jXjGplcn3Qaw2OOTnG6bRZRL2LAi9cUKnYeRkuzyJKScT5SBKmVQjfmMDzmnKqA3RCGI/OckVM6SRC3+xMwdp2mUENDfqNpgbYhUt3pekTT5Zu2fUvmA9hUg9UTGFuzEgA7TYkusiSQzoYtzPRJzx2yR43d+wFV1CUMVtYO8Sj0SLMQq352Y90V0CXNQtqHoh5o1HX0eWG1cvLaA1Z1DbgM9QdWc+uShtyH5nwXxwfgZ36KjFkADnpuCXsu/TOjLTzxq29OVJoKxxRGb6QJ0Pn+Rcx8c9PL2QAwkT0LAPc/chz1P//biTqhBJ7y8B0iyiD7JoxA61PnMfe3xp8wnJ9C5WYbajjC/Y+YezPzzU3Od5ERKMlezREoirZQsafQfwBMhpHFvSMh81NiXkrtDvug6Hu5e+8+bdT+aKgZvj3BPD4cYffxJWP22LmlY7y6sQJoFz43+xWNoueVro3wHFJbGM/PMO0hn0cV44VfB4MUL278DnaGmwW7dyGFFPLeyeHQLB5QNyT8TtYEkZ8BeP4MWSFb/s4aiXASyeNkTYUwi5JWcpmFSOdE589MojXpGihZStT8kJqBh6akXVKQ3EpU5Ru/ch4Xfu3GRD8UIZlAc9r2SWMZXlhlE4aKAAFmR730z07gzHMCKZmODaXftRZazy5h9orLXCXym/QHzgOw5L4iuQuwJlMSYzhfRfn1qw6eHpeZJChKxwCszW6jTOP5GkdGtp+cQfXeyHd6Chg5ozgBTrkvtTsevJx2U/oNcJmeVE9WCp3PJprVNmSmKAYpJ/9JuDabGsJPROPVtSo/C5SRrN5a4x2f+qLxkZAj1Wvf9hFqQdLc9CTkMbHHfPXul3C/d/v9zzp9r+RBZgiJDCeF1Zpyi7fAzyGY+D3IOg2zFek4+SDpOOIwWhjCAjBxM/LK4BHjslSZ80K6TOcewqRbO7j0udO48Gs3vKxH6ttjdBbjlGoqvQjeSyXStWUomYtBC5PFU2V5bsocOg4JZUg13ztr69bGyrF40fkiNOrNjZ0fRkPSNQR5IoChINg7GuPIn15kc3JwypDpTnCgBCn3NEc7H14y5QkkOlSaaMKRmFt8iJyOwjTguRUywYoekOJQO4Cfx5IXEpXs4LwgBmatTMWXpD4vrv/bA5PfHI7FIlrQP7TwjyYKCO9XN0Ta0CGGHrCahT0m/J0WnNGHzgFwdUPCHAIinZEp23RThxdWUX79qhkr5T4Ex3t1Q2SZQPsiyFwUj1FL4jSam6wJsK0tKp95dUNyXrSwziWAieQtOb9YXsTOU/MTdUNYcjSVkHkq/Bwez5/liymuNy85DIBXplDOe2RZxgH4cyTmXNYN8XKGqG5IDluW3JnpXu2IuiF8jXYTk7kdeX4XtXrCzK2oGyKT/kiobogUSh6juiHhHIR1Q+ja8pjfZFW20sllfHn799Bt3XyEcBbwH9yiboiVom4IirohODR1QwoHZyGFFHIgOTSaxbuSHELXt/u9KDJUFBkqigwVRYaKIkNFkaGiyND7UGTocCwW+0hRN6SoG1LUDfkuqRvyXklRNwQT5k1RN2SSwaqoG/Lo1w1591LUDSnqhqRF3RAph7FuSBENKaSQQg4kh8MMKYoMFUWGiiJDps9DXGTocJghABPV0N+Ar5rJhUN+TxOl09QxHgkVTE6k/J2jHgSyiaNJpKH1iI+sCs9s23sDfrHpnCgdce6ElCgdIRq6BZnCkIuvDXgxGsdgpil+obp99B4/ynwUHjdmANKSfUh+BwrdTt/N+KU2qfyzHlmwudbM/j4Uarl48eSLak0Yb7GZr3HEhQlmLJM4hUHl4idNA76uJGGuhomFOhgPkcFgpu5eCCLW9a7BvvACtAfAITfDDF6Ie0rPRnOTX0pvDLa9UruDjKJ2gpx4IoQPcF+RDIULv5YWqFvPn2I3SaZYAEVDjH9Dizk31xD66YacOh/6gA4qh2OxUMqrCxKGUPf7DhBe6SRh0hZlYd7ydwAu5Th4OHSaIp2voHzTd4KiMQs1SPlFK/XczpPOm3bpHA1LtCJfMLtjlbv2u0HKbNJ7R2NMXTIvwu6xCI3XUqb/B4CoFht+hpDtWg5cRkS6qdc+AOwdjTF9NzPtiwdjXEtQsgznJevnGZyax1Qz5+EGLSDCvrZITTMRQ54bnmfB7j2R0GRFMnt7fdSqJqIxzD+PjgXsvIu07wnmanGsbsx6/gY+rrXjLbwPqhvijT+PLRz+YsvfCV8HjyuJoUnr6nQB8qEJdm9+tmfq3iIyUWFPMmIFi2SepvVOFwk+77CbIaTSjq9cc58ttoEkOn/G41LkcJHIIAXAXJUezqIxi96ZWdS/1fQYnUldl1BcwHA78m4P59QstXtMvALAxfxFHJ+EdnMSetHGtYT/7p2ZRe3yPeZU9ErpWbyITGqSfcj2aVwEDV/5whserkQ6VL0sVzGPHl8DnIm28+ElziPhBDRLTEPXw4WPRJSIOBdCqjyZLzERARFjoJeXSyaKaw+jFtKEkvVkSkcbzpSy5hfgZybzeC2UHfDNBNrtQ2g2z4PVHigqRqAquudkiuVpQoAfzZBmxnjLaMXl48sY3Wn6TPWBRiEjW15I1R7z4ubvHjgaUjg4CymkkAPJ4dAs9uGzkIlkkiUL8FfaibCjzcJjh5dY4eXvADxNJcRkyHMBOM5FqdXY88fnTrpSg3COJoJMA34BXPpM42E7l/AalIFqw5nEKDW1MTD0bkI7oj7C9nl+hLzxK+cnOCsAU68iXWkgWW9xKvn1T8d44vPWzyOLGFnNIOr2PVMiS8oY12Lmk+QUd7uDS/bucS1BeWPHMYB9vu00P0p3p35tkl3/rLnn1XWbHi9YzQEwfD2sauaxiUt8jNXQaG7LvTGT+kqCYklhSExZBHiT6f5832CIh8mPNHXp1kT/XkFuYKL6maz5oQQITzJwUXtebRpi6fr6NT8RzgoBAklevPlbB2bKOjSLxbupdTqhCsJPV88D7chsVpnSLiMMOo74RQfAnnm9N2DziLJbQ66AMO8AwARnA6n543MnuUwiF0oiXsUcuxiAz5EgTKIwHR5JbFi4LRw5/YHzuP7pGNO3Ixx7xThAAXBhH/ny7V046YoT9fpMr1+9ZRjHS70h+ifNfCXbKTY/Mo0TL4gCQZb4JrnanKgST2Olhalyt4vBsTri9h76J2sYzBqld+Grt10mq7xOiqaIKE16bhml3hBROmK/CdEthjSAFI0ISW7IPCK6fO9eirkG4OXXyI3IW/ABD5NDEbvK3a5XukKSLIdAP48mr5LwfZj+q0vQH1h1tH92TBLE5/kncszXl679xoEXi8Ph4NynIhngtAxeQMJap0TiK1LRZQFcSfpLXvxsq+0tSFG9Zti6LaEpAH4ZvFoNA+MhH3U6k+hF2HCiZVOOgMkohm2Da0vYNkrtnkMCUqWwXupqkdD/MLvMeHkBUWt7oliybJ/aKm/soJQOPRjx9O0IuycyjKZLmL6buWOlv8UK1fOIUEVEmkG3Dx1Hhh171zJdtfso71btIjfkc4ndalyLUWoK4hgxbsC8vOVuapi8hxmq92x0hoo+u7Wd6QOYjZtIktt9XqgiafunqRlLM3Ws2rWE2a+kRF3jVJZak+cvCcOstMDmJDFS20qgN/eOmuOmrvWZF1Olae6mwAmM6YifTVVJuJ6JSkwZAr038H1KlcQnzAGASmIiVhsuIRDJLJA9grkh7yR0Gv4G2BApTYxgAff6sLkIKom94suhEwgwajk9EFqoiFm3Z0oSCO840+r1+uY8WO4LsTAAJjxZam6ZsKOEYLe2TUaiDMvZXTBLytD2pQfAmaHUPn1HLzW1D8D1YdsnOfbKAKPpEm7+pxGOf9UNg3ffmiOw3Xq6jtlrKaJ0jKRtzcThiKNBPAdJGbPXUt6dAedcHS8vGJIhWY0+EEfim0HHEbqnraO5V0X7iSqO2msDbEawMFXYVMxxYJv+EuwtVVFrO5OSwtQUsgbgoh9i8C4AACAASURBVEmk2tPmY9HBlIxlBpEAFPqen0HJfj9eXmBthjWpeo2TEKdvu+KiUb1mXmBb3gGAV9zKc5aTUzdg9xrXYpSnKh5KGWSGpakrKNTcMhvQQJjWQVTw7eTQLBZ5IjWI8DNrCzmV1bPV48C3rpgVN1g0CPMvAVj0fbbV9rzFRqsAJ5JRCEyqmoy1zw2jmR2DMjsHx+ooWfr5UtsVvkVjjuuQMB6iPs1RFvNQW0q7pIwoLbv2Ae5Dtm/a6hiwVVx2SXbpGHefncb03QzHvwrc+WHTxBOvmn5KAC82UVrFwje6XGTo7t83KvTstQRZHKF2fYeLIs3cVEhny6jcdQtNVq9isFRF9VrLo8WTc8UcnO2+qYrW7WPj7x3D3oLRjOdebmEhnfUwGkZLcIxipOXxiyrMOdjrqV2+50VqVK8/4XMBnHmolxedlmdNRE9THKRGo1leRNTtuw1nLZ3IE9K2fASSmGuv0P2jTYDTBGbqXFSIr9eaIWRS7BHI79IQWVLytGoukkV1UQk0mA5deQvSimfqwPbBE8mKaEghhRRyIDk0mkVeRTLA5fdnnQ5/ltwXKk4mc/pfvchmDf0OOG+5fvUitOANUInZjSPBvkypzlQKDjDqt7IQ6IwcmbSCk0eaKd7iiSrqU5duGTtyq43RhdM8+Xun5lG5CSCZ9aqobz1dx/wbpiYmtVtiNTv2Pej1aa99ABhdOG3S0E/No2LnIFlvYaXtCgY98aqtov7ZJVz4dcEPaY/dfXwJCYASgKWXjIk1OFZH7fI9tJ5dwtJf3TXnJDGq6zBJb4K3s7recZGHiSrqu2y2jZZmUcqpoq5rVaTzFVSv3mLwVHljB5ipOw2R/T2xY/6WPotO11ZRDzRA8jPI8oVdADOWPd7OUbZ63GBCBP4DgI/zkBqKxXRQ2jg7H63vBHY+FQRuIym584lj1s6juUYL1ur2uBSlBhzZUkDiZHwWQ9eGjSpxrRXq+x34LA5NNKQoBWClKAVQlALA4SwFcGg0Cxm18OjwA/p/NVUxO6p42RjtJ46Vx8jfqW2qBF5es95zS3TK47Ew3NLRBvsT+IWbryIOGMjJzqf/t589gZkrHZTaHReJsDeaiysLdu8wrKVgdg5GZ1o7+MxzpkQhVVcH4PoQ7YPOF9BoALyTA+bBE/sZzjw3xPVPx3jsi3ZR2NhBZNGgjdfart00ZTYmSpcfLy+YB9VDe05DtXaQ9PpMdAsYDS1u7+HNX5rBhV8XZQtsDdmyYKlqCEwGv0CSHq6SeOjKEmEqRLTq9k8vY+ULd4zGZccR1WtWu3F0frQjE26lJNpQAG5/cgUrX7jD91291QMsaxoTOIvKZxEtWJUEu48vYeupBKf+QPpeYsQ2oa0kCJZ0mvqbnK1wv/7JBZz4V9fd9yL5kVIYiBhq/LEnTZV2u/ik55aRrLc8hvuokmA4I5+AB8uhWSzeDbt3mH0IgI+h3wEge/M6OzyJyp9gzpTlx0lJNkchLyeg/PpVZJTVev6MyUWxx8PucnNfvoG9CydNhmUOll8L3kUAExELennG1uknIc06LnP7ALw+OFcAfp4CmUKDU/OGFcvuSozLsOdTMWYAOPNcwmUGIQFFFtuQrjSYrIaLIc/POKo+GwmJ0hH0VpvHRfVnH/tixDgLrqUirh0A0OujlA7NWClK0+ubPJ3GLIbzVdY4oloVI1pYBOCNuErDmjC94zEqd4UjtDGLkYXcSyp/0ioWXxtM8FHw7XvGHLvw1b5xiCcJbzKoJEhny1h5fssjQkrWW+azcHCjkkDBkdUAJpzbenYJK89vQYnM2u0nZ7BgFwPvWRqkGCYlU+3+z6yDM7Ewc4EJ0p0uku7Bq6gXDs5CCinkQHJoNIt3JTlmiBd2zfmd/RuBRqOEbcjEsFYYipvT9riWoDxTZ1NApymmLt0yKi0R3wo4tkoSZCKdmM0F2lGT2BDN1qoeJHlqY8CpxlSwmfoI4d5eyr31eVz/7BLOwBEFR6nZ6ZL1FqJ0jPLGDs48Z3YeA/d22ZFSxssLiO/e93wnBPeOulYD6fVRahmzILPOVtOnMy2u/ALBvau+U1LswARMc3BvN/fJet+De5faPWbQIjH+lDlPO0IrRePljX3h3tHCvAf3LrV2UGruD/de+Optb9z9x5c8uPfsqxs+3Jx8CGQq58C9ORO1tcPt7z69wnDvha/ezod7P72C6tevYepanc1XMhd3n17hsauZOrB9cM3icDg432H5wrCUIQAvk9KrTCap5wQpiJdbQmJJZajdvHRjaickSWEPsyBxAQKHFBztGlWpAsC8DzodMgHu9OUNjOdnMJyfQhYrTL14GQCw90OPY/ob6z6OICTZDSqQy3mSGaFbT9ex8A2zaBLIKmkPPEKbNz4zj6WXgVFVoXLfPCvTt/fYMUlS3thxMGwBviKHK3NbAFxeQWbZtp6ZR+PlDfQeP4rRdMRkPVtP19H6fm1yR4Sfqv/Rs0z2IzM5KTpBzkXALE79lRlzbT2XZj9amp3I50FjDv2zDVQ2+q5a+XBkojW91HNQjk4tutR8werOGIfAjPHIjOgFD/JQyq9fzX+WyKEvKBYxSI0vwlbVM/c5YXKmUnPLh5db9LLcUF7c+n3s7DUfLQfnuxX5UsuoRp5ER+p+CjOFSC3kG5h0DJrvfIZmd76risbnwToyZcShuWW0mhwgF51HKEl6OKN0jM1nprFyzbwQ1Wstz/sPgPuQ7cs50enQAYVo3MPMIC7tw57AAcKYlSuJsfQysPEscOa5lBeI3RNTpsqXQHqOlmYNglSe39qGbswZ4hlRZnA0XzN1QizCEzB9NF4zf0/f3mMtZPZainLfLjpiAa6umwiFAhzac7eK6q0eonSE3hlzveXeGNPfWEfZOrSJzbzy+ibK4mUDACwvIkvKqK530Hl8Dkf+xiWHdU/XMPflTSiZg2HbS155k1/A9Nwy4rtlRLKUwCBFSUa57D2DdWxjkDqwVrC5AXAgrUpi+heLW5SOHXgQMFD1SgJY0B/ztdoxS40LgxTIHrW6IftIiL4MtYuJ4+0LRxR8EwhQMhm2WiifNrR4cvdFJYEmJJ69KdKzzgxKgiSWnbF2B+WiO7COutYOInI4Whiv/sAqonaHX1wqoqu6u1CCREb1+ogBrDzvyii2//OnOLmKHY62D9k+AESW6JZIYgDnCItQRZSOecEpAWg9u2TIie3Lrnp9jKoNnHkutVESM7bZi22ORtDCRZGJ8b0W84eoQQoMRyYh7fXrfF0lm6Ur0aJnnqtD9fqo3ipbCLZ5Ud/8pRk0vqlMKT5rdun6NC+OqCSIRmYma9dtYlZSxsxlQQ5cSRC3++ivzGD6G9aGEdEhiX6M7MI7c3nbmUKtHUSjuYks0XS+YtoTLyDXzgVctEtkwsrQqldcSkSwSEZ3rPP4qceZQcxj54bNKwqKSHNiWqfroXmZolBmJkcHd1se6sUCeDDkmz7LlHb6n0yRid8pySZgCKfalKwC2nyA7Mb6pMnT6U4UwiVot5dp2Jjzknk0hKYySF1uR5rmMkOlKw3EFkBFt3T2Ss8sErQrwWk8Xvu2D/qd5ysuo/f4UUTDDEl7wBDupZdamL3S81LRAaByXyNKx3jsiylHSZZerqGyk6HWnuYowOyVxNAOAkjtLh5ZANLUtU1vbDpN+SHn4jrpGHtnF1Humn6WXjZ9PfbFHrqna5i6tukg1ZXEweXr0zjyN3f4nqleHxFcgti4FpuqbjXDUSpzJUJSHgLglXpwKfh2vEf+5o4NaxJN3zamhyOGmJNPiEzSrNvjhVnyp3rVzi2pkeruIj1nMkmTq+5lL8uNRzyvhAuJ1u5gcGreaDaB6Uk+N1nljVMUJOHRhm9OPkiKaEghhRRyIDn0msVBhFZyj6It+B0Ap5J75gZpBZXEXznJ0SkJcSzgSPoAODlnpm687aKi97hedWAbgDkZeLUPfA+oJGxTR+kYne+bQmUuQXl3jCnSmm5uGgBUd5c5R6mPsH3qQ/VcxADDkbHrLXZj9prZvQbH6g4uLuZv+vYedk9MYfZim3f7jWeBJ/61gRxTTRWmJux0Ed8VBC/2uuT/CtafIe7V7okpzFzpYPvJGSy9DMz9rYX3pyNM3y5599EM2GlTRCOYzldQ2TA8IMSz0T9awsLrPejlBSCZcUzrTbjarKKSHe34/ZM1VC3bXqm7yyUK5bMwnjftVbt9N2e1qnk+RKlCvvaAiIg1ykrChEEEmpIJg6rXZ7CbSmJkgiw6bu8ZBCg9rxY3RHgNnnOL3lQCd6RaO48m3PvdkN9IJyUwybDlOfoC1mUKU4W1MBliKzkerT0Ygns8z7dgYpLfAy7/gSj0tbjBkhEKMLVD43Z/AkJOIUeZp0B9yPYBZ8/KdrN61YQ30zHS+Qo/eLXL90x5AEH2wwRAG6YgEmU71i7fwxufXcJjX+xxQaPjX+lgVE9Qef067v20ieg0Xr9vWNOHmUfko7q7jPhks8BmyJY3dtD94DKT3xDEXIkUdbK95YvLYuHfTH6TjjzgmSxsHFmnawiV5kJHXZfiz33IFHXbXqmXevB/LmcgwE8kkhgnS4x/Jrp0A9mF02YMV2/xc8omz/IishvrDmVMREu3mojOn4Feu+38VDY9Xj7/gDPHyT9G8l1DfqOHqeOdGKb8OSyiTElklLhDuzsdwy+3KIxM0ZLS0YZZaXt9R1hj2+CQqMDZq9UTGL95netNKsCVM0xiL7wXWR4DWmyiSzeg6jWu5JUHtG09a+qU1u4MDUdF4vgRACBa67FDzZUxMH3I9gFRMR3AzodNu7Ovmhg77bDkFGw9u4T5P7oIBPiC8XwNulZF+eYmam33kBHS84nP2xcsKRu050wdM2tm3vsna6hd32HCnpLYaT2SGVh/wzBD94PLqF2+h7pYoEenFlFqbrl6GcsLiDpd4yTtpRgLVix0umZXFhQEenmRNR8OC6+eYN8KRUO4RkoSQ63d4Rd7dO4kL3jMsm1D1BTRkflDsLwpUlOlZLStHzbh8sZrbfZZaLhIFN/XSsI4C712G9HpFcenYo8rnVxm8huGfdtNk+uh2oWKF8bmJp+fdXuAetRqne7D7k0LAwBvoQB8DEaIiSA+i9Axaf5OnFMKYP5NTggjPovGHIbHjni5FFQQmXg3pRAEWta74FJ2Vtvon21g+hvr5uGXmsXyog/YAZjbQQ1H7OgErLlwbdMr50d9yPYBeE5Ezqy0bObEcLVz1iyES39110DBbdt0bIiFAMyDvv7JBaw8v8VZso99sYfdlWkceenvcP/j3wcAqF3vMp+FZD5nprANn2iHqARbz8yju2Ie6dU/3nLs6YJuzgsPS+Ac4TwkPoZC1ILPQq/ddvU6xO+SOZwyRKNLN1y5Q2FmUqEjpENkN0yURU1VOEFNMmxP1BERzlUtIlicmIbJtAfmlBXpC9H5M0Bz0ytPKXlipWZB50v2rBfX/23B7l1IIYW8t3I4zBAgl1Yv63S8mgj0Oet0PDOktNBgVizAqKNja7bQ74BLUY+6rs6GBjjlXWae6tY2kuHIj2t3jOahhiNkQWEbHZeRSQauJIFaPQGdDjE8dgSA4XbQaWrIc1dPuDR5ANsfXsLUvSHzE+g4Qu/xo6hdvmfAULY/ZooepA4Bavvw2geA1RMMgJKmVLJtQEBZUsbMTbupJDGmLt1y2aNWyF9RvrmJ2Sumjd6ZWRz/SgdZUuYM1Su/UMOZ54bQaYrEQohLzS2Ua8vO5idnW6+PMnGJ2uLB41qCLCkh6vYxe6WHyo7DOJR7iV/rpdN1u/dM3Zkh6YidhiPrt8mSEuK7TiNgRioyTSUrlcDRjCSVYRIzt2ioLYxrCbL5KpKuI4OmELwE/nFBbYH0JFq/qLnpiihT1nGScIhUr90xWgFVmyNszNEGax9c8NpqDmS2kOjlRWirOVEgILvXejRxFnnkNypOODcjs0WG1PIiSiK3A/DrQgIwKb8LDT7Gq8BuVUktzz29ItLZrb390bMAgOrXfT5HXZ9mn4jsW3WNmubOu8ZRiJJ1oPXOzKLe2mF6f0mtP/flHU/FLLV7qPVSo74PHcqOCX7S1HPclepVr30AHtenpOXb/Mg0yrtVzF5Lkc6a76vrNrdCLBRZUkYE40tAJeFqafVvNbF3dhGVm210vt/0RentF665Yk+6MYu9pQqSq4nnu9FxGYOzi7w4mTnIUBpmQBJjVE/QOVWyfdnsWEl8LBya2Vab+S9HpxZNfo5tDwBKw8xAq5cXodduu7KNpxbN38uLvNiUmlvctuECda+HnBfAmb5kSknnOm0u5Hge32oiglkAyEQs39w0G8vyIjQcuS8ERwZzZxDCmJ4BUepQ1afNM83lLgz5s24abAv768QzSwtM6eQycPPgOIvD4bN4j+uGAL6NFtYNod+BB9QNCapwmb6GXhKaPJ+LFQs4MDFzSXuWmbmsDQrk57J4dUuEN15W5eIoie1Dti/bBVyB6OGFVdYqiNQFgAsV25AgYAFN1vk3vteacJpJGn4KuTb/1RSO/GujSfWOx6jeG6N6q+cR+cqcC3KmUrkAj9YersLYeHkB20+a86v3RkjaA2RJyeNskGUevftm/RJ5leFK7R7vwFs/cRoLX73NURlaLMh3JdnAJW2ArlWZHyVKxx4ZMLBPaUci6AlIbUjbolA2AJPibv1Ww/kq+9HSlQbiS2s+CxnchiKP5cLXovC0bszipSv/14FzQw7HYvGA8oVS48gzVQDkJpUR5Hu/3+Xfem+A0slljG81uU1ZLVtWuGZNQhD20vkeCxGJrBsSlw3On3Z+STRra12QOko1NBjl94DwLUdwgvYBAKxC2/Ml/VrdORe9yuYB4SyFX+mFiO/ex70fPoaZtRTpnDkm2R6hcrON/tkG7n/WFhl6zmgNSy+1JhLquGo9ZVsOR4aM5tomLyCAoPcXma8U7ozSETqPz2Fqwyz8VHxpbKMXJBSWzZISO4pJs5NJZ7Sjk/pPZR3ClxQw9330oXPut6vu2eF7ErBSydBtlpQM3N5GWWSodzhf5bA5AN8pCbATXW5OHisXnIbs1YEVizuNqXBwFlJIIe+5HBqfRZ5InAU5NfMIewF4YBN9Y90j7GWxOIvslr8LlI42DLotSGkH4GVx0rFh/YboSJ3NDrkbAPAYjBQAVa9h92wD1WstL08h6/ZQEqTD5a6twRE4HKkcgVdjJKd9wGaort1GyaZTA6aWiCzmLLULM3/TXMOCgGK6tQ01SDnXQ3V30Xj9vsVRdPkadGMWveMxaxT601sY/sVRoxHInZa0LaIShNHa4rY1U9KxSyW3oDTp4yE+0HsfamBmLfWpAmfqDgQGok+cYa2C7s/ehZMYTZeMA9k6pXVjzmJmIpOObs2Iez/QwOJf3vJKSChL669aOyglZU+7M4Pc9pCSVHaQ/D6kVeg4QoYy9zWsVTGqlQFUTU4LiSy4DBuet05LKkcAOJAgF3MmQuDV46bejHXMAjB1T9Qj6OB8N6L3BhjvDTi7M6wjwr4QS10XZrKSwhrWQM3qVURrd/yaJPQ/AYRsFKZ0tGHUfa5A7krr0aLQP1lD9fnXMH3ZOO0kIjECPKQmFYSJ0hFGpxahXjV8FlFjdhK5aPuQ7QMW6JTEQCXxkJnDlYahoktiBmdV1zuMheBFrJXaQklznInK82brhvRXzAteri1jb6mC6r0xesvGOTn8i6OIf/we9L8re6UhMUgdEzcJ+ZVoQRA0dZyZacdQuzM0KfZv9RGlY+cLsWhNItcx343Nolvz70+5m6JyN0gPINj8MOOiTQAw+5YgAhZzQO31T9ZQJ3o7wrMAnulVvdaC6u4aFneAfRpZUkLcSzG2m9reUgX9RoSjf9334PHUtga8OrCwhEuUiFYm31Ng9pVsBjIg8BvdXSB7Dx2cSqnfAPAPAGxorT9ov2sA+F0ApwHcAPCzWuu2UkoB+F8A/BSAXQC/pLX+m7cbxIPYvWUJAPosq5ORv0CiMmX9U/YnwHqlBTM4AC/dXIoMzUlHpzxXnk/M2nms05Jlm/0NwU4bph6TIypkAg/ZuVlsCNDzZ+Q5+wRAKwSnDS+sOl5IwPkKWjsmRVxwI8isSTqfAW+pS3HXcRl3/2UZx355xIzecXsPw/kp5t0ExEtmfSb0/eDUPCp3u7j7axqN/8lS61teDXJCyigLtyMgzQRwA+BpMsQkvrtiSzVsDJBcbTJoLsxtkYQ6gHNyyu8lEzgtxAAYmMZjEn4kIocmIdAZRwLrroyh1LDIbyMzkL1iyQHsXYZtab5euvEF7AwO5uA8iA7ymwA+FXz3OQAvaK0fA/CC/QwAPwngMfvvMwD+zUEGAa3ZtNDD1MNMlBYajKOgzxOnx2Vkq8eZcFfiF+h3HZcZRyF/13HZICip5OHyonNAztQ9ZxsA9xuR3tD5kiEK1gyxJehUkjhkYBKb8GtctipjatqgXIDGnCsvR8zVjTm0PnUerU+dR/n1q0yrh+am14fXPvUR/BvPGwr69NzyxM5efv2qWeTWbkOv3TZQ77XbQMXkfOhOl/9FqUnPRhKbBWWmDl2fNkzjrR1njjU3ceyXR7j7L8uI23uI26Z8X7lrNKfxfM3kslTs+IPFufL6dei12zj2yyIhb5gxfZ7q7hpTqRaaU1aS2OyqgXmZrR43EbSkhJlvbmLmm24hlFXhdH3azEnNlBMYLFW9RYAkWrtjtFCbJj9YqiJpD5C0B6h+/ZoxH2QqADk10yEvXGjMmQX3VtM8X8MR1HCEUrtjzB8ihqZ5eGvN3J/GHLJ61Wgrtaq5b/b5iNKRW1CSmOH73I5+D8lvtNb/QSl1Ovj60wB+zP79BQB/CeCf2+9/Sxt15WtKqTml1HGt9R08SCw+PS9RLGS8krU/WFrbUM1NptzP1m77x0iIbn3ao3iTv6mpiotHEznK1SYzNBHcV4YnCXOx96EzHL3gy7JVs+kFUW/1OBSarR5nqnlmr0pibzejXVN1d10W5sK8wTi87vAf1IdsHzAvhKRyA+hF66DUTL2XSnV3mQWKWbiHGS+IdD08tnTo5XqgkvAuy3NgC0nvnZrH4q/sYfNXzc7WXpvHY1+wZDBW1ddx2ecUEaA5lcQYnJoX0HQTbaF6KlyXZXmRNTGCP3u0d0nMc032e9zuM7dn51SMpbYJd1MyHmCIgf7/9t48SrLrrBP8vTX2jIzItaqySrWoVJKFFmyjtvG4q2XswQjbcGQw9oHpA2O3AbfPAGfcA8yZgRmYPuDGc6AHj8EybmPAG5zx0LRRm8a2XKjlMlosWbJdqiqpqpSVWZVLZURmRkRGxnsR8eaPe7/vfvdFZCllayBl4v5TlREv3hbx7v2W35LMX4EzUYHf0jwfgZGgegMAJbBzts3bAUDnjiNG/Eev7p2DFRVhzYwhEBNZUswrbo+IPKNjswjOqOegM2NwLAR1d1ptVgYrPbWK5q0VlJ9VUbBLkzYUIK15uIDy47Zi/W7Ht9sNmRETwBKAGf3/AwAui+0W9GujMRqj8RIf33GBM0mSxHGcFwzWcBzn3VCpCrLIDzBOAY24lEQy/bc0YHFSszKgZsDetZpOO+z3yYLQEuqlc5IRA4G9ZGFviHiv+pwupjXblnAqH1evPK7UCY26Q2sKsuZBHhoIfMSVLB+jHzg2KUkfw02dH2MrYPJUeo3JVlSDkZEMXU/UhVMqKsh4bd3q8EgHd8DUJ6xIRq+OFFnV51XkUjlUR1QZg79izqen3cRZX4TqMbpuFNS34bfF9ZF8QBha+qKdmSIyS6tsB+jEPrxaZJSyBV7FLRbQLYSse+pP+urzy03LTtCDkVmkeolTKqqoJ+7qCEzfszixtgOgvi9Kr/R35DcjjanIMq6Czo90V+h+u1GPQXp+MzLRZxgqn5MohhuZR9Df6qt70mhaRdKtuTz8rd2nHenx7U4Wy5ReOI6zD8CKfn0RwEGx3Zx+bWAkSXIfgPsABcoatk1vrcY1it5ajf/ubzbRW9OoxyCEd2BWeY8+M6/2LT5P7wNAf2kVfV34TCtN9zULkUI/AvZ4S2vG17TZVu2wpVWL8YmOEkYlQBAAZklmL5g8k4qT0CK2lliP1ikg053M5bpV9abQs3OwgvzZFcvSkI4h9w/A6iJQES4J3KHUeDquTKV6hRAeVCjfO3bA5PI6jXKbxjPVr22goyHg1E1R+wjQDz34zUilHgCiyhg237uJzK+VLJSjnMBov9A09LiSZaEdLvgBbDSkzl3dp/6hffzw9UMfSTGP9lxJtZIF+jQJfHSLIVr71H2uPlFnK0ACWwEAwgDRzBiC5U2eRJJGEwh8Vb+RMoTLTW0u1cPCD6jF64a/0umaAMt1iyoFC+rbA27uNDFQCk4QdcxqtrLQDPVakf4dTKrXmlvshQoYYSCv3mKrA1ngfiHckF0hOHXN4nOiG/I7ANaSJPltx3F+BUA1SZL/yXGcHwbwXqhuyD8D8H8lSXLX8+1/zJ1Ivn/ixywOB2B3HtJiIATdTov60rYEv06/z/aFtyhKMDuTCRg2AO6wDBPK6d5xTMFsYSNAJdxY2hcOIDtJ+JV+PEPsC3mbVHRDKEfaP4DBYwjRlQHBHxG5pMf2LQcG7AsJEm0hKOm+iMiIaxUpUVsSqk1DsXuVkrYv1H4b1NXQ2/E+ZqcG7AvdlH0hfz/6vNL2hZffcRRzH3/asmyg62VINQbtC9Pf2eV75zD38afVsQR9HIDd+aK6kehQGPvCBd5lNFdlj1fZBqeJgm0KD+0T9oWP2q8TRkQqxQ+zL5yrKvvCxSVDp5io4Mtbf4720uUXB+7tOM6noIqZkwCWAfw6gL8E8OcADgF4Dqp1WtOt0w9CdU+2APxMkiSPPt9JvNjcEMJL7MQNSeMphnJDJDeD7oU2gBnGDekdOzDgQUHEIfrhpWHa8nz5oRZKStBO2k6rbZkMEayZJgA6xgAMq80WAQAAIABJREFUHBhIt57+tZsGzI8BBZWmHxRFGcpkSBfTUsQ3FrRNtQN7hYAl4ujhT4p5y+xYmgyd+SUyGaozf8PiTAgFMWMypLkgxPeQKZFQ0uZBKu2WydA6T8TDTIaklwe1qoGdTYbooWSTobmSZTKUPj6do5xY6XUJrAJgteQJ3EX3d6jJ0IlpRWRMyUvS5+ncAeArl//kxVPKSpLkHTu8NUDm0F2Qf72bA4/GaIzGS2vsGSLZd+pIpv5vipPpSIHeZyxCSo/CkvTHYJhJ+x1mMgSAQVRSZp1WRWkyxKuGTpUAmw1LWowAdK6ew/Jdecz9JwFRlwg+gI8h9y/PLe2OBagoIK5kWT+D1aggQDuFHGp3VrTJUHxdkyFCPFIqAhjgE6+ielXtkcaGbmcCwNPvruDm++poHSkjXI/Y7DiuZNHaF2DiS5esXF0WVtfvUiuwv9Vnk6HGCXVvyWQoOjYLN+ox3Drz9YtwwtAyGSIQE31eWgxs3FrB+IOXrDSue3AK3WI4xGRok+Ub1fdgUjZ5zzj9lAA7qa+hBxPJUilkEpla0oA4sr7/aX3SdMT1ldXP7JpItjcmix0Ee72JKhcy039T4VM+vCyrt9lEEkfwJqoD71ONQdZF6O80spNzflGYIuFUGnJSGWCoat1FHkQ11nmqJYWWClMZnQco4I5IoaiyTuxICRvn/QOMqpQjKebROVjR3BPDDSHvC4me5KHDclkEJSFeGr1CYD3gtB2d34DQcTotCAOeMKgjAZj0x6Jgk09KFNlMSoG0pHtHk2hP60RwanFmnnN+S4xX11eGoWPp2Op7CPl+hws1K71Jp7Ak0AyYiZjSOCclsCRTS+/ZRX5NImXZN0SngQPWkATyglmIWIBYyh0Ucjh99r5dTxZ7gxuyg2Bvf7Npwbzp72S7M1AMBWDqC5tNOEE4KIpTHYfb3EJPfN7JZphy7ghdy3RxE4ASZtVanaztIKDiNMEAqdYp1Q2iyDKR4e4CEdAyIRberPa7/4EN9ueM5krISxizaG9axxD7B1R0Ax3dUBTixF2GWztxn1udC2+exdx/AtDcsshvze9R55Nb9BXqEsD6y0qYeOiKEtfVgr/yh5sVehSEVJWwerdYUBGFOFbzxCRuvq+Op99dwfFPtPh8e5WSIqydfsZWM+9EPBnTg0SK6JIbQvfm2ivGMPmYuLDZKQXNro6zjD4AONUynE6EXiFkNfMc+ZTq2hagamYM8xaGUWRE3L9WYxCTT5NibR2RLqwH9TaLMLnFgkUqTIp5+JdX0aPFoN6w6mVEnXfnr6p7IH53SSGH/uISPJpM9ULn6onSu7QAVxbWey9B+8KdtCq46ElRR8qRTCI6afXxJqtcCB14PxOawidEFTmlE5FUy0oX41KNndZZAWnM1gXg9KWYN4KwS6uMu+BVqVoGahtqlpdM0ihSP7JOhLm/EZJ2rS68VoQQphja17wFNJoW05DFcPT+AZhjNJqGAFUdR/tAAa5mPK6cVHi6ub9ZU1iHlHBwN+8if0VFEsaRDKzCTWrk5fMt5UjWMurgzOHQIbll+BvFVmoSrkfozBRZNZw8SsrnW+jmXbVipqwm3fmriimqV+ug3ubUj6KeXiGAH4ZKU6PVBqAecFk0tAyqNUPWifumBUmrsSAhKle1BoCS1cZO9G/IyWZMt6vVZhIYMWR7lZJ6oIt5oLnFE4Cnfzs4tN8umjbM4kYRHKCiOCkYlEYvS85NuAD0sxmDeD20H1jfvbr3npksdhppb1Mnm7GEbZI4YsJYjyaS7zmO5OqSoanrfRBQS7acAJ2K6HQEBBkPfcQzRWT1jA7YNQ9ZtwAMSIfqE04UK1af4Jc0bsii+nmjtzhgipQJDUgqNGF9P/TgU3oT91kD1KXQXB8jvX+Awv3QUsPulF3krvXRPFzA9oT+sUQxnNC38tykkEPxUosh4vQAj39LmQEV4y6rcGc2cmgc9LDvgrknXitS7uh1DUOnFjCphmvlJrVtzA/79MMFrOiG+8RDGygCzJ+B/j/7soh8v1cI4dc2FFP2oBAA0tdnYSI4ZREpQhhw6zKZLtsm2VrazwL56f31KgW4Ik2kf1n9Sv/ukijmSIrqS73KFH+Wvi8XAASU3gEszVfyekmiWMH8w8CkV0RJT/0++5tNLe0nangv0GRoJH4zGqMxGrsae6PAuUM3BBgeWchUZIBUBgyV1Eu/L13UqfBp5dVDXNQBcFEtTWtnoyPRoaCeP9csCP2phUhkz52OIwtrjDEAOHSULurS4YvFfvX+gbSGgR3FkEwehcXU+ag+UTdCwACWX38A5QuRBdbyWiqnly7qFNaTS5Z8TRHfjIs6ADYIomMR2KxXKbELGgCc+aX9qD7loHwhsl3UiznuvBBOgpzTLRlBcR8tF3UamdByS5cdEf58bQObr74BY1+7auEiyKdlANMhv2/Axn5I0F0hN6DVYeFnhIs63acBKYM0mA8wLurp3wIw4KL+lbW/2LUG555OQwaQmTIXG6KryTmxmFiGtk4D86XJsFHm6twJiSIMTKfpcJSdtQ2EG4WcaXFSMbK2gX6kUHWkgQHoLzeK0I9ibAvQT69SQlzJoh84yCrAKHLX9A9D7J+PIfYPwJrQ+D7pB6NXCFG/OYeJyPiE5q6pwqAnUqHabQn8doDqUw6ah9X9zV9R+pFdEer7LS3oI+TpqXCbWTZIUkBNWDThEPS8tS9A5rKP9oECunkXVJauPuWgdluC6dNNc29rETpHq8jX1feYXzCTOaIYXqttaUy4yHGxWLZcSZjXUjeLYnTmSsistA3PJRMiv6Cp8LSYNLcQ1o2yGU/cAECWlmLhYO0QCcoKfF5gKI3wv17n34uUY5C/Tdm9iWbGFDM6xUnqhz68MDScImnj+G2OvRFZjMRvRuI3I/Ebfm+vit/s6cjCLRaslEP+zVEECdCk5PJ4e6nHkM2YVY/YrLpwlgZxcWTREd2MKLKg4vLzvULIZjhq2xguNBRbSPO7Y0X2gKCOjdXe1cNp6U6Klk5j9WYqegofCTqG3D+giVYpuHf7lUeRP2tMgPg69L77a3U4BFk+WkXu0QtIZpXHh/TGIOyEk1rRqK3K9ybuovr+McQzxirRbweoPlFHf62O7e9XJsq5hUBHZrHyw9DfAxWYq+8/hNovq4d36tcCJIGLrRPTVgTQPlpFZkWlJ1JblGwI3KZ50Ojh8uotZDU5rPbLW5j6NdXC7Bdz6GlzqG7BR+5CDV69YXmV0jVK/Ebj+H6UH1/Buk7p+PuMu0Dc5VY0oAym1QPvc7rQOlJE6ew6HDHxec0tJVZUb1hwbZYmLBVZd9VvdVWhWx+boszudBleFKN21zRKz2n8SyvGCxG/GRU4R2M0RmNXY2+kId9hgVMiMgGDykxvn05BaL+Ey7BqHOS4zorK+ng61LciHtLWEOFzkmqlAcZJW0KMAVhQ8zSakI8vlKIpbTHnFAzsHwDnslY9R6cuhJJkijmR4CRcWJPZmMmZEu0lEVvAQIsl0al21zQKV2OlwSAAYACYfGUVF4d4lqgdrVteIKu/ESP/sQrcKGErRgCcNkl9CCKsEXu2J2wN3aiH7ekc4ymkF0np7Drfm+3pnHKDFzk/IWWJIMeq36Ui10IkEY3SOSKiUUQUz4yhW/ANMa0wKNkHwHwPktyo28fJjYdMSkOpsCy0AvZ3KBzcHn7s93dNJNvTk8UL4YbIAhrpWAyT9pdQcDkI1k0POT28aZq83J5eG8YjAWBqEcJUyJJiF0g6qo1I8yJndmpAcIfyW8kVoG0H9g/wD4zPV9RW5ERIx+1Oly0HrfZcCbmFBjuYAWAAm3XtGgfSnS4LqTyX5e4JywCAjY9Icp/PlbAFgo3ZP7SP9SxpbM3lsfUzdXY+o/e8ZxeNpoe4B9L2QF7D2usOY+JLl6xCbT/0UPvlLcz8isM5fvto1To+AGOPWG8o6rrg7jhx17qPxEDNXK7zZEUTF+lj0OTWOlJGdqWNbjE08nkptqwlN9Cx5RHJZCrWhc/mK1TXL7fY4hoTL2SH9uP0Mx/FRvvqS2uy2MmRjCYFWdiUdQMZWaRNa6kOwWK/GrkpIw96PU0kAzDwAANQIrM6CgFgHVsWI3ckopWMx4gsfAKmJQiYXBNQDyCZHUvOCg2JjLQsBfUx0laHzAEhGjyMr4RVmCXKOLX4RH2CSEx0XlInhH74176vivIzbdWeTf2oaaXl18KAW33u/FX7/gl6NgD0Axdu3MfmezcRfLpqRHE0LFvqZ6p72ULjtiklyksLijZiBsBR3tbtc8hdqPHkEFXUd7z53k2ePGR0RVT6njRRphbt2RUrOoq1eA4hXjMbfVOzEOfcPFxAuNFFbqFhgbq8A7PsOMff95BoT0aksm3P3y9tAyhHssVPvPQKnC8E7j3MEySdXtBkYm07REqPXidUptVJ6OgVOeV5CoiIZrvDD7tT22BuAN99EQ46oYo03ImK2laSkwjDr8PZ6JZDKo2oKo9KEiOmc5J+oHQMuX95PkmjaVfCJVlMHldHK6QQFS60Wd4PmVDB2aGKoahFauUU7dD+Wh1eK2bGZ2leycslga+4E1I4uVpmkV8ACt1ZKmqzonGDThWrZ2aFUosA3YKP4NNVxG+vIX7OTEIUjtODDgCZuI/CxabVFfEARJUS/FaXJ6zMitHnkJ8PPl1FXNmG1/KNPSDhMZptdGeK8FomneofKavoK9U9AQCPutLrkY4YXDZNAoDy4yt8DlxQPjxnObATj8RtGnKf9EUlYSUFQydpvi6bJA1N9XYx9sxksdPYDdxbSu8BgHf8KLuup993AmVHn2izYooKqDPBSt569XVE2AaYVdxyZteAKtkdYENjbQNAI9nusD+qZL46qSgjWN5UD1NtQ00cAjzlaPsAS5k8DK390/+pTuMK7UkAagKUhrr6AXZabcM90DTs5uEC3G7ClO3udBl+3EUv9JmU1At95WZebyCreQ7hQg29Skk9FNWy4SSUigoQpl3mAWD9tYcx/uAlw0bV0U3jxDjyC1vwVzb4QVfy9iFyCw3Ez+W5SzL5mxnElRyuviaPfQ+p17oFn42GtycDFC9pGb96S32+kuN74EKbIGvTZRrVhQaWfztR0YUe/dBH43gJxUsu/GZkJtjaBorf0GAqsZJ7erUvP26EZ5JGE5gus5wfYOj76v5oiL9uawfLOtoiqkJ1XOuF+pb/KXfnrAUphquPIYGHib/7HseoGzIaozEauxp7pmaxUzck/dqwbUj/UjJJZfTBdPJUrg8I8NUwynfayp58KqSWY8otO12B5m0gQEMpTUqmkHci7mR4rRhu1OWCl9RDIPi0dc4iT7WAYVoEV8LQuVugxWkBFdqTXJ8UlgVU0Y2o6ADsnDxVSBzQxRSwdGvoGgUdq3WkjOI3llSXoW6EgKXvR1t4uJKuQ68QMEjr2v/aQfX9eRYIBlTBkoFWJLgDjSFZaPC1AKom4re6CM7Mo3fsAEcXXitWEHRxbayZoaHcnBpo8yBZc+LvXtd/ALDzuqTXA2CtE2toEyGiCNC2FAFKSr5Xb+0IUpOvA6r78/dPfeglpmfhOJaJ8TDxG0on6G9jBWAzKuWgFGPY+9xuFClBeiKBNi6SMGPSyOCJSQCV0gpaTE+XoX9o0JrsYSl0NLilqieUAqEohWjK9mSADGDVQtCJrP3zNdYiK81yD8/Ba/lcrOMcngRiOhG64ocHqEo6AJ5wMis+H08C1vxS0epkOKUiT4JAqm17ua4LpbF1DGKe+gTBFrqamRWjtk1dDyWnr16vvl+lJNX351kRy2+S/qbyL4W+NurwSG5HZqWN1d+IUX3/IWvCoRanLNCuv6yk6gyFEF4Y8H2MZ8a4TsO/hbjL+h1kSRCcmUf32AF0iyG6eY9Tl16lBBRzDM4CTOEWnQgIfIui3pnOqQlOF5Vrd01j4qErBoQmUL6JXjSoyDrx0BW8EGPkvRFZ7KCUlY4whjmWSXFf+bAOg47vNIa1PyWMeSeVcRoSvp2u7ku4uOXoJaKcAaNjuoaULB0N5pVQnYO6NulIZpi6N8wDONCGg1kBAZjKuoYvS3IVIH7EgFWVJ/l5cjPnrodYMclKgFe+FIGLOwFa4UpGbyRdRx2ExbtVIXHmkQ7cqMcTBg2vFaNXCNC4IcvObu0DBY5kJOaF9k34B0C1ZhfvLmHuv2xwvSC+5ZC1PxrOM/MK9zB/1Rbh1Q8twa870zm7Y0ILmZ7Et49OWUpjBKNP5q9YrXi6r3LSljAAS4Ba140kLuerZz+CzebiSyiyQAqINaR4KfERUmoP0EVPAZTyJqvoNhrW+4DBZwxMLBICTumFwB/IzkZaJwDiPWRC63OJfn1AZVn/8NNtVTnZtE5MonBxQ+lqHKxwzx2AwlS02obglj5GR6ZCRmMU0FyW0IerDXoGiFBCJd2dqKBXKfEqRz/09oGC0rrUFn4A0NXgJK/eGFDx9iJ1TSQj2A89FUGISVACoZy4z3oUXiviVZJSpqBudy2omEkamxRhAED9QhW3/G4NcUXtr3FcTSxUaPRaseVz0g89RaD75S0En1a/vbDewb6HtrRnamjO4YYsGsdLyF6LET5yznw3kVIyS2gCsHRK1D3MLTSYKJi5XLf8V5IoghtVLblE55l5A8yjKPNaDZ3b5xBWCsZbpJhXnaTmFvrbHTtd1ukzm3HNX2Vhp92MUYFzNEZjNHY19kZkoVOhAQRnKu0Y9rpUwhq2bfp9SUkHDPKTcRlC9yG5Dr7CAoVRTaOYt1Z4hueK1IRD7aVVq93F56JfC9cVhbtbDJV9nShUdQ5WkL2QEpHVhUwrXVhaZRUwWa9JmyXvdI00/JYqIJL0W3vSQ+FiOiXx4MU2KSmu5IyNXxhwsdKJfVUETB2DIhc6DgB4QwK5XiG0kJ+ULvhQNYp+6KF+QUUFlaNaXjFwFL2fzldjLtIQdKpT1C9UMRmY6Lxb8GH9GqOY99fNe8jIe0YtSlJ1J/vEdPoadZW1YdzlGounf0vReMjHUymmQA8LYmRY72iUrPF0AaCiEYmAFuklb5PWmH2esWdqFi+GI5mlY6G32Qkm3r3jGADjSAbYpkbegdkBoRDpSCY/RzR4CYhav2s/xh/W7EtR8KNUo39pQRkUQSmGE0KP83rhaiXx/JTDy/3TMeT+ab80qCOUNkGS9Y3+oX24cncZU0+o+5g9s2iJCdNnScU83emg3FyK7RLj0+oO6HNcePMsDn5K6PDJ86IhaiZpVCtBuGWdg4VxxLZLv5/FzE8r/odEyy68eVY5jFF4r+nfPR3Wp6n6y7+dYPbdm0PPdfsWlWJlLtctYR5APajz985ia3/fmDal5Ad2SlUBVc/pzBSV6dNvnONaCHV0pIQBgeM2f+hWlM43+N7U7qyg+vlzFqAvCXw80P4kOvMvkiPZP8TYCe4N2DoW9Hey3RnKIyExmd43zxr9TRGFuDcdUT6aGrBFgyYXqd4swVr0UFM+n2x3rAed9pH2HWEFriETjnNovyWcSoWn+XfdDAC44TMLipS10DB6lTARj4wWLKLYEB4IP/AAt1JJvZpIVPP3zuKGzyzY0ZRWg5LVdgD84JJoLwBDdotii6wFGCKV1Bdtz5WQe/QC//DjmTF4rRjXXjGG6dO1wW0v1LhmQVyTxm1TKFxsssALEdbIXxXQEcWjF7D8x5OY/E0RYWpim0R1SluEzsEKGod0l2Szj3C9a7erM6HxEW1Fhtei30MnMordBKOPIrRefSMA1f0hn1f/8ipPNm7UQzQeWq3qZP4K/7b6m01WIuufu4j4tbcpFTJJNNSje3UJ3q0n+PUBW8ZM+IIcyfbGZOFOJK8K3jjw+m4KnHKySKM85fty7CTNRwxUAJZ2Q1oJPB2tELdkN0N6lwxNn8iyTvhlDAi5CO7ETvtPnycNlgsk9iJFMrNT6Ie+UooWRTF6IKJKxugoDPM11ffHnTDq3kG9bXVMkArVk6VVi4Dmr2xwFEL7bb/yKMJ6xyaiwaQR/WLOFC2/qQqFG8fN5Jy71kXu0QvoHTuA1330q/jCz7+Gzw1QbVxKPYjc5cR9rL+sxLoPwfImNr53GuUvnmOP3Gg8xD2/9QC+8POvQTQecuuT7Ax7hcCaYCXPBjCmTARd91taY6QVo3G8hF4AhoBz8RIGJ0Pn1T5ahRsnnO4FZ+ZNxKgRuHRtjdumMHb6Oavl/kJMhvZGzQIYirNwgnBgYpDu6YA9MfB2VJfQxDM5cRARjTklcYQkjlTEEkechtC+kQkZSwHY+p70efkZ6zyGTEqELdixpUsPugY8JVGEeGaWjZi9uIsE10m/BHYhzdrl/cr0QehEeq226Qbpbb2WkujPP7nAK2VnOocw0JYEBPcWZCp6SJzaBlwJBqL7IKwBKNfuFkP0Q2ICl1iFO//kgoqMBPNSpglus80QbkQxUAgx/q0GTyCAST2+8POvwev/4CEAwOd+/XUoPbVqXMzF8OoNeHHJPOxhoFTOw5ANnNyowPujCQhQyl7RuG+R1iTwqzNT1PdIHTeuZNGe9FHSk0WvEKD8zTo7xgHA9vQsT0bqe9PpUW0d/ROTuPwGFzd9TKS6AKd6HElkQmRXOqqWId3RUv7P1xujbshojMZo7GrsjTTkRahZSIo6k8JSNQuiqEtZPHo9bYEoBUbkoDrGAEVdi56wyxhRidM6mEQBJ8VnPSS2gbeLhOuWSIVI93Oo1maKYp62MKR9Ut4vwVS0z6E0/VTlnBSkqe7iFgsqJxYh8/bRKWWT+OziIEV6iEALANYetXw9Kd0R9Y3rQbhbR8q2oA3VJoQH6pv+9y/hCz//GhU9UIGwOm5R5wlW7UY9/l6lHgXCgPEhlBoAYLh6OnWicwcMnJ+6V60j6jvLamat14os/cy4kmMP1XSaJyHvVD8hEBfhN6hGk9Zu/a7Rs6CJAYBJFVLITAIdycp0VxsMUcohf+j9ZktZAeybtV4jo2IqWNIEkhbaoWKizPukiYxEgFJ9YcDKUNcKKP+VeaallKT5EBTC8qCOChXkxDGGKSlJE2YAnDun6wnkZ9rapybM6sMrKuQXoSwdX/p8yiEnTAKW0cRo1YF0C5gFXjS/Is2poLxbPni9SgEbxwsoPbet9DEXzGfSXZMk8LU145JVZI1nxvD6P3gIp+69zTpcv5hjHVHJ4wjqbSz84AQOftZ0mKgbRJ8BwIhOqQLWmSni4lt97DvlIM6r53Lqy4uWSTVfrkZ2yg5Sr1LC+stK8GIwMxcAVk7OoHQ5RmalbW3rRl1c/LEJFBYTFJbUJLJ2q49Dn1uzjpcELk6f+wiatZdYN+TbVcrqNxrKAFl4eUjhG3ofgNVBsAyWq+NGIUus7EPl66rj6J2/wBEPGRXLVpc6lhCK0V9u+oFJby8RlZ2ZIoL6NhsOSxVuxm/weYUWTZ4Ge5noSjhgFLH7xdyAUlVaKIdaoAPmv3qQtyh9lrohacISKUJJqbtuMVQaDHoCiuaqqi4jzITpfIHBSaj42DyT7mh0Cz47pjPJijxKD+1DXMkyhJpIYCc/+xS+9M5XAYCl6N2bnWAEJR1Hnl88M6avaZtRmICqWfQDB7kLtYFrSBpNbPzATQCA9oSDff95Ed3pMrbm8gjX1T3LXK4PFLV57GBcTXwUOhaLGlGUpsfijx/F/i+uGVJh4OP0xY+9xAqcjjPUEwTY2QqAtw2MtBxFHZbJUEpIxwkD9NZqvD/AxiP0FlUhyb3pCJzahhWZ9JstJJcW7AgnDNBbXDLMV/2gMQZfCrzQOevX0wS3JDItuIxejT0dgpP6M3QP3wJapY4hX8fSqlLu1q3XzZPHUbiozX3Fau00t9BLub5vvnwfxk4/xyI8PLSilWRNOmGoNC10CAyAhVa25vIoPbXKrNGw3kFrX4DsGbBB0Njp54BSEf2lVds0Wqt0bc3lWYW7cPYaugen+Pj0gIcZFZ2Fzy5ZEG7MTsFttuEHrjXpojqOL73zVXjdR78KQBVAQy2J58R93gdxR5LZKVz6UfXakf9wAd2Dar+oZK1rc+I+Lr1tFvlltRBPn9b4lEoJpfPq91w6rztAl1dRiCe4jYraugJLCaZw83tm4cZ9ZPQEL93r40oWma9fROPkcQBANvTUpKmV0nmRuLyKiW900J4rwW9RROMBz430LEZjNEbjRR57I7LYYezWNwRaho3mW9bl1L4hzP7T0GcrMpidggsM+IZgaVWZD4t0QUUZtm8IquPKH0TjBCw0XRjy6gGkDHI7kRWdGBAXQaJ1HSYTDrJRi3mg2TI1Gn0MuX8ASsouNfxWb1CLESZt6jdbcHQU4bd6LPnn1Dau6xuCMIS3tKZEcMk3RJshZ1c6iGfG0Dio7q0/6SvfkGaLoeQWcEwwIynlyq50hG+IWhm3bp9TKtn6GpRvSNuKjgjNqWoAouAofEOo9al8Q0zESbDzjtbmdFptjF3q8/nS/rIXVrno2DxcQPnxFYxdKtm+Ia02vBYGfEPI6InqT42TxxU1PYr5+6GUK+0bEs1VVSpXKvJ9BID2pI8cfYeUxh2cQuZyXfmGtMh1fhvo7943ZG/ULHagqKcBWPJvqkNIRqVENHItI/V+mhZOAKmhehbAQHeA9CxoSGp7Ws+Czs9sG/H5DCu80n4A2JR3EZL2KiU0jpdQ/uI5caxwYP/pc5B6FtQhkNgFLjAurVlAHsBI5Fswbt2hsY5N2o6NwZ4/METPQuTm0hpgQANjiMAMdQdI+p8G0dMJwek3I4aFc6gP022QsOxepaT1LGwBHa/eYsFdPo7QzZQdGaofWCmeFD0WLnW9nfQsgKF6FnS/pIHSgJ7FnRVLz2KYOjwZJU08dOUFCfbujcliZAUwsgIARlYAGFkBPO/4TuHeaSSjN1llB+r0+8P0LPh4Au6ddh0HsKOehYwG5KqafqjlftKEKe6GDNOzENV2vm6NggQweIy0c3pKz4K93/cWAAAgAElEQVRWHavn/h3qWRB8mUJ+QOhZpDAKrGch8BSbL99n61noKIAiABmqEzmqVwgRVTIMlSY9CxLAAUjP4gq3hEldu/z4yoBPKaALhtpblfQsyudbSp5PWxoAKuKp3VmBF2NAz4KxGqKrJKXs6Brkd8udk8urCrWr1d0BWIuOhMj3FpfQed3tCOsd03GRXrbXavx7tuwBhLDT6Y3/9yXWDUkSjirSg6nj+v3+ZtOyDQAwwAMhp3T+jHifuyv6ASdMBgAW0QHMlw5tCkwjePApdjCT58UGyRQtxN2hYTnLnS21bOBXdRxobvGPJrtigD0Z8aAAhmIuJzKKSjj8BJAsDXqhRHNV1VYMAyTVMoN2QA97c4t/jOS6Nfa1BkOrASC3qE2BS0WW4KOWbBL4nOtTZDGsFRhXcghrxrVr7GtXkRRyhtyWotQ7zS32HqVIJZqzH3RKHaJKhh/0ycBBUsihcShE+Zk2r+DU9iUVKkDVKPymSimCT08jfrv6jqMPjinLgEKO60D90EfpuW3Df5E1NFLq1vfGnb+i1LOabZ7oaKII6ttqgqZr02mXlM5DJ1Lfo/6T/FOya3WO+ug+eq0YnlRWk4sIySuQN03cBRqjbshojMZovMhjb0QWOwwrhdDQ7WGOZAAGHMncsSJ3OGhIRzKKDJwgHO5IRgCYKEL2gmDbCF9UPs8wUNJ2QhezL+oYXARsNJXgSycCpIZmGAJ69ZW5MI1hjmR9UUuhY1j7B4BD+7UOY8jpAqlHkyMZ4S8kHJuQhQQvTjuSedrpqiscyUhCbpgjmZcJFWaEvgeAVzkqGhKQKBf6lu4pQ+YzIYvc9MdDuJWMcSTTCE5KV0LArjFEMTKbfauW4UY9VRjVKtuA7npoJmf5fAuRrolIRzJaqb16A25Tk/0C11rBFeq2a+o0s1PoFpSob+1OFbVJR7KkmGdQ1catFXYko0GOZDTyTypcUKLlFb0W4FGWKhzJvMmqVfvx6g0gE1pyfXgBVYi9UbN4gcbIuzEZ6j2PyVB/B5Mh0qmQaLm0yZBkmbpjRRbVtYqLwmRIDppoBkyGUt0TaWIbHZu1TIawtGrRy+UxhvFWLAczWc9IWx1o4RrK46kzMtRkSNPJZVhNnQUKiclkiLoczCPRNHZZAxgwGdITljQZkuK2pJYVV3KWyVA/9AZMhnILDWEypDsYmtsRi8mC+CBu1LNMhoJ6m02GpJCwMhnSHSNphZiyerBMruXQhs+ym2KZDNF33mhy4VaK8BKXRcL22WTo2AFLu2KYALU7UcFDy5/CZuvKS6vAOVLKGillWedFY6SUNVLKkmPMnUheXfqRAZKYfHipi8EPs+xaiJWdBnU2JLFKRggM7jo8xwpZ6VYr3Vh62NN6nfLzvWMH1A9MbMtMTAHKGnZtDNRKtWFlatR+5VEAUIAc3ZXhIq0+Rjo9Shc3ASUmw8Q08YPkCUAwTLdun0P2K2cHzJilYng6IpJksHT7U3Yt+qGH4My8dV1Jo7nj95DceIjJWhMPXTEgOAk8E+3gdEQHGJl/QGhiBD4uvU1NpGOX+oPkOb1fOs4//y9qkWARHZ228H0MXGRX2njdR7+K+3/1bgAKfEU4Eery9EMPwfKmUeqi4iNpqKZYyQRAq90xhvIzxEyNedvGbWrCK1xsYum1Zez/z0uIZ8YQjYd8DgBw5YdmMfsgdU5cPPzEh7CxvTucxajAORqjMRq7GnsmsngxEJxyDENwAnYqspvXpGbD8xkXDapiDRoSyTFMN5Pfk63Y2jo6dyjdxeyZRQbWSEDa9YaMhqx0JJ1a6GjGMj2itEWYBEngGBtFC5o/g36EmQ1gDH2ljmi6lkL3g4eOGkmfAVBtV68Vcy1EUrxJDo/ZsLRCZ0I0v2fW6EVoLQ9pMkTYifFvNRgHobZtMGqVGKiv/4OHcP+v3o3sSpvNlADTLqXIAVBoz+rDK5beJ6CwNP5WD9G4r4h0UOlMUN9mq0IAVtRBOBC+tpQhUWc6ZyDvok5CUn9eK0ZnWqVXmZU2/v5bH/6nBcoCDB+E/j/S4Bw+CY40OEcanCMNTjFGGpwjDc6RBueLr8G5NyaLJFE/8mGt0yFGQ2n0Zvo1OdJtVjZUTj2stJ0sQA4bO01A7kQF20enFAsQJqzHRIVXZ7feAppbKi2Q2hEExY27gNClSADWjYBAgzqlIhzJiNXHkPsHbOwEaWdIEplEe9IDbJHbdKchfOQcMFExCE4qyAm0Yr+Ss5SlAMALfYaGA+DinhP31WTQ3GI0YfjIORP1FPMG/iwMoelanLiPy/fOYd9/baArIgOnuQVPtxKz19R5dfPkhB5he7rMD3apvo5+MaceSP1QZi+swmtFuHzvHKae6FiKUjSomJlZaSOazvGE8Xf/requBfVtuFHADFgAcOOEv7ugbohi4XoWV16bwf4HO8aMCWrirb+siMlH1CKUJTauJuvJbcP1CDd9rG0WmUZTTeA6KqW0KXx2SRk2U+sdw1nJ1xt7Jg35jrohmkItt7W6IXr165+7aO0fAAOp0mxSqbxl0eR154K7KTcdYSKYbJ2iE2H7lgPIXli11LYoIki2O+z/ICnZfHyin+tOB+fxs1OsaEXtOnmMnVrFMrVgF/c0Q1XfJwIOTTx0xXANUryX3uKShVehVKx7xzHbCR5a6k3XK+S1yTYrTRKOBnxJLIAM7QGjWEVhPU9OWlGsX8wpb1B9XZ07jliqXICCsjduyKL68ApPAH6ra0BipKGqryOaq6Ifeuhrl7LcQsM6d+qSnHr7y+G02tg6Mc2TBQDM31NGfjnB9Kll9YJui8vWL6CIZMXH5q16Q+vEJO75rQfwF//+9Zh8bJO3f/o947jl/3jOutebL9+Hsa9dxXM/MYfiQh+Fq+o+Ln9fBoc+p1SySHAov7CF//rcR9C+urvW6agbMhqjMRq7GnsjsngRKOpySCj4MIq6HBLByZEIYEHF0ynJAIITJlckWT7+LIGXAI4IJEYCgFUctejrWr6OeukAuDNAK6d1DLF/Om9apRmII7brzU4MrPiWLoXWlqCOAUchOhpLHwuAhSthyTsNrGpr4pcbJ6qiT7qd0KK4Z+Y5QrPwG3rVXL9LFX/HH77CNR2pMZlUy4grOfhff9YQ+ujadKG4c1DdBzfqwWvFiCtZTmOahwvIX9k2uhWS6q8BX60TkwAU0c+rt9A5WNGph1rtT376a/j8+06iH7iMbSC9zsxy0xD35Llp5W0Alu6GpT+q6e7UCQJUbaU7XR7ovJSe27bUvgFb07Vxg0q7xr/VwN9/4w93rWexN2oWjjO0wClH+jWZGgCD4jPDtgEGi46yGCgfYm+yyi3KoaI2NHFR7UB3GJgSDD0JdCIkOkWgh5dyc5kCkFAu/fi7hRB+GHJ9wboG3bHg89LHsPZPrxPYS0CNaTIg5ihtC0B1SGTdpNFEsOyr/XKrN1YPeW2Dj0UP+DD5e5p08mdN2L59ywFkREcnWN7k9CSNmoVOJcuPqyIhdU62jlbRP1Lm4p8CNPWQ3HgIDoX2Wn3bi7voF3OIxtV9KJ1toh/62phY8XHKj6/obkjXQqe2j1aRb6n0JitSC9qfGwVcT/n8+07ijR84hS+981VYOTkDAMhsJly0pId34QcnMPc3a+rhj/v8HZN1YjfvodAihqsHf0XB8KPxEO0b1eIz+VAbfa25GejfZem5beb0yHZ0Rt+fYHkTVPr16g3A3dU8AWAXkYXjOP8BwJsArCRJ8j36tf8NwL+CqaX+z0mS3K/f+1UA7wTQA/A/JEnyN893EiME5wjBOUJw7n0E524mi38OoAngT1KTRTNJkg+ktn0ZgE8BuAvAfgBfAHBTkiQ9XGfsBMoCMLSdmv7bm6wiqZYZPCU7JPQ+YML9fqPB6t7EauSinwjByaSHNTz17C8LlvR5xhsInoEsJNIgcJFlpKvHAJ6CTGjmr/I5yG6GVAeXD6vkSqT33TlYQWa5yVwLGXHwvvWPlAq0XGGn7yTFFaF76+quDKchOlLaun1uQGlq/odKOPLJJU4LMl+/aHAfQsKeiqBkEg0YHw+OGlI+IQCsh49AVbKQSHyPXiHE2u3qO2dDZlJcKxDD1JgxkYam1NyQoDC32cbKyRkUlnq457ceAADc/6t3K71NTRIDwGZHJCokTZLVDTG/qfiWQ/BaMZLAtQhu4UKNUxQq8oYLNWYJA+B2txQTosLs1olpPPHl39s1KOt5C5xJkvwdgOFAgsHxIwA+nSRJJ0mSiwCegZo4RmM0RuMlPr6TmsV7Hcf5lwAeBfA/JklSB3AAwFfFNgv6tW9r7BbunUTRQPuR0J7SkGcY/DqJIvRFcZOjBlFk4/RFmBdZUG0RjjM0HLLAaFZgLihKST2CUtdMcdF5Zh5OsQCX5PY00pK0JKTyuDyGLFjSMaTuYlZ/3olioFgw9ZSJimFK6oIis06p9pGqZahjm9Skt7gETziqycjGe3aRIev9wMENf7UBJ+4yLgVhiG6loHAVrbZJ0Yp526UNJvTPXdC/DYpwyD9F0MO9mmrJEjSciqy5CzV0ZorIXlhlXw9ARY9b2gXO1d8lZqe4tUvhfO2uaVSfqLO+JsGt45kxZDYTFM5e4zTknt96AKfe/nIrQsmu5NAt+Gy4JGUTSfGbornGDVmMfytWLFutqAWAlcWyK7DQor1CiH5FGS1Ru9lrxVh51RimHmvC15FFbqEBvIAGx7c7WfwBgN+EeiZ+E8D/CeC/fyE7cBzn3QDeDQBZ5AFneGFzWNqxI/pRfOZ6/A0nCG1RW13cdA7tR6KxGFLtexjnw1IM1+ZFlvHP7JRCLJL4DAwHhHgf0fcpd6rwkXNs6UfFRefQfqDVRnxsVulVtsyPwZH7F8dIdz544tMpAqDD9FrE+AUrtMyE2Doxjaisfhblx1dUGK/Fa+R20J6pPDlpSwR+HyrMzV2o8UOd+brGuegJkd4H1EPq1VuM6+Auk871cxdqBglayMGNE+MbKqjgCAMboVrIYf5NE7jhTy4Agc/1miTwcfGtPm75HXNZTqvN+04CH8mNCtrdLQQI4y7m751V+4GydgTA+7v4k0puYN/pDsrfVMrlNLGcevvLcfLTX8Of/tkbMPFNdQ3Fx+YRaOV2KVq8fcsBNXEIwFvhaoz5e8pwu2Xc8JkFnjzn3zSBQ5/VmBa9mGyePI7SqfNYfNfNmHnE/G6ffUcGN//eMlBbx6Y2JMovbKFTHewm7jS+rckiSZJl+r/jOB8B8Dn95yKAg2LTOf3asH3cB+A+QNUsvInqUD0LqYRFf0s9C9nitFqmehv5vmy5EsZf6lLIlZBg09xZALiwGN9yiD9nVlYN49YTw/qtFaU3YUU2xgMk2e7watLf7gATFUuEF4GP/lodQUqlCrNTcDoRNmj/AB9D7p+OIc8d0BONVtVKRH5OHYe1W0PM/Y1Cljpx10ChZV2GFLOW1kz0Qh0dcazchdqAES9gUIZrt4Y4eNbu9KC2ruDsdF9LRVMAjE0tRnZS2M4g7irFMXm8KMbW/r66P7Fd9Nx3ylFFVRL7adn7pmt3m4qns7W/bzmdyUIuuY9RPQiimOnVW/jTP3sD/ruf+lu2SkQm5CKrjIQoQpG/RTcaQ345wY//whdw6rO38SSSX04GQGylp9TCkV1L4DcjU+PoBmrCD0MFRYeuURVS9/86Y1c4C8dxDgP4nChw7kuS5Kr+/y8B+GdJkrzdcZxbAXwSpsD5RQDHn7fA+SK7qJOh8U4u6uQrQp8f5qI+zN+DHsju1SU+L1a8osKmkLMnO0N6Te7PEj4R6QLBnAGt9LyDh6ksMNIxBs5XH8MJQ4tQ1DlYwfZkoDAFwn/UPXPJxoXQA0l4hpRK+dpr9mPiS5esc5fK3Bxe84Rk9gfAUr0mb5QBs2XhnUJO427cR1jvYON4AV4MbqkOKzgCYJfywsUN5ma4UQ8bN+YQbCVsKdg+UEDh4gaTvCzhmIdXuCBK9xFhwPgFmlioiElKXnSdxHglq8TPv+8k8mdXsHViGn6ry9iHwtXYLCIkrKsL0bKDQ+/LCYlv2cGKRY6j16JxH+F616Q8YfCCrACeN7JwHOdTAP4FgEnHcRYA/DqAf+E4zp1QacglAD8LAEmSfNNxnD8H8C0AXQD/+vkmitEYjdF4aYznnSySJHnHkJc/ep3t/y2Af/uCzsJRE9uw+oRklMq/h1HTGX2ZInkNe19GHLQi9zebVi2DsBAWkjSKrZoH7Zs1FmjDjkHc0R4dIcPWD029gNqD/WLOQuqRLDwyoVVb6Ddb1t90DLl/PkZ1HInIi53mFjLLAbIXUkxLAI4umErOA52fCpsNk9ONusqeT0cbTtxVbT+hwelGPcsng9qkfjNSLuoXTJs2qZbRqyimJ1PgAVW0FG5kgCJxuc02Mhs5hOsm3ycUaOeVRy3BW6e2gVyoiokU5gPA1JdruPpDB1A6L27E0io8oW0JKHFd2k+/Msv3i/bXOlJE6ZSu3VQKWPjBCcw8vIWtOdUeza7kmO/x+fedBAAGbvmtLrxWjPL5nv7OPK5X0D2gArivmbcb36usACiiIk0LQKVBfjNSQszaeAoAMpeBaHxKRRwy0uvtfi3fG3Dv6+Ashg3JMmXWZ0pIl/YzzGSINDMBDGAVLFSlNAqCXaBMdwPSeAsS+5UpxACEOWXrB2DAIpCOy3DySkkhOHWBEsCAWLDlWAVYfXc6blrNnDxHeoXASgNYF1RiH3RxkxyuAKOzgeo4p1LsRqaNgmgQfkQeK2k0LZFjizhHtRVRp+hVCtxdkGZL3YNTrItBxwKMfkRaW8NptZkVTHoWdO5EEc9crvM9oHNonZhURksacUmhPWMpBFDKb/WQu1AzNQooFOrrPvpVfOojb8DsgxvmWFrYRpoUkVWj/Lz8fmRdiCZM677R0LghqteFC7WXoGDvDtwQ0pkAwDUIt1Qa0K9I1zHSLVdZ93CCEO5Ykd8fVhMBwHaA5P8J2KCu9L4HBGyF2C7VAMjDkx9+0fIDYERpYCYUpq7r0V+rG8sBARaTHqHD3NSkSA05n8kfHxU8LctE4m5oNCFNDGzPJ/JkCTiS1G5yH0MUc/dCvabzfCFQzA++mHD8y6v8INB+ZTvQ8i/V9ZjM5TpHMf3AYfGbfugJu8BtdkxjhO3sBOJK1iBMRRSSBC68ZxdZ9Utud+W1GdzwVwYV2Q89g64EuH5B4DJAMVxXX57HO/7V3+L+X70b/lbPOi8GnsFWBlP32kyE9J4r4O1Ocwvdg1MMY5fXQHUwAMqRbPM/fnd4nQKwooJhf8tBXRTqgAzwR8T7ckhLQ4aBC9+RtPydVNSScHQAVhqjPnN9r1R6XRo00/tSNo/PgaTyUwpVOx17GFSb9p22T5SK4gDYDkHSxwEw4nXYIKUvwECXyZ/VIo1p/xJzD2yCnXSG45apjqTaR6tMJye8AwAgipXto25ZArB0OrZun0N7Uu2j+oTiarSOFFG4qLtwzTZaJyYRrkeKX0Epki6wygm6cdsU/FYP7UlfFSV1REATmrRbJCk8p7bB+hJEBmsfKODUfffhB37qnea+aRo8oV63p3MoXNzgaENGabU7xtB76xqKH1bnVbi4wWhOskGg87r41jEc+rxxZWvPlfDEA7+7a7j33iCSvcBhEcFkfUNMAlIJi0Z6kqD33bGiNVEA+kHTD66cEAhXQT9mSnXIFxRCR8EpFeEAVrpANRAikwEqDXFrG0jCgEPEYHmTnbuTYg59vd9EMEUZwAUTjlr8E4p2Cjk4BCyrjqtJJYqRiOo+rYaebj+q8xpHpG3+nFabf+jB8ib6txxmKX7ApBausANMAhe9IIQnHjJAA4gozdP3JgkDOFGE3uwERw6ACpWjuSqCM/O8qufPriAp5NCrFJT0XGQczIvfWFLv6etStRFg++gU/FaXFalaR8rILbYQrncNX6OYM5+vFBgARa7oTqnIZkpjp59DdGwWpVbXEqNhd/qC6VRw9yETctejfF75svpbPfzAT70TX/wzVQZ87Xt/Fn6rp6QEdaSW1c0eZEL2dwUUqKrvA2MfHEP9hLqPxcc2VI0sihHA+Mv6KxuY/lrReMwC6B+xW9rPN0Z6FqMxGqOxq7Fn0pDvBGfBqztFAtp5jF6XtQyJsUgfI22LmE5N6HVJRJOkNXptp9fdYoGNmCnNAWzWqVTOBmClJgA4LZCGznQMuf/0fmUhVuasQ81tRA1lKLP0Wm1AxwOdiCMKqcK9PZ1B6dR5rpMAhpCXVvS20qKUg5YTBmho5GHp7DpaR8ro5l2mlQMwpkOCDEf1ITKEpqjFjXqIKhmFINXpUOPkcRQuNtE+UEDxsXmulWzcWkHxUssqnJKpca8QwI162NaK2VT0ZKMhPUi1mwqZbtRjQeO4kmXq/IMf/DDu/O33oLDUZ9Bdr1IyzvW6zsK/B12Ipc8XLjbRKwTY2p9lAWMAltu8NF0+ff6P0Nhc+O5NQ/4hR7qOsNsxTFX8eq/z8XQxNFlcUm7t2x3uyvA2UfTt7z+KgJrpNDDvRftmJlEER2w7TKTHyWa4jiLPi/gXMmduV12MaRk+T+zX6njABqYlS6sm5A1DLvaWzpoaR3alrcJxCZeurQPFnEoDUtT8aDxEVz9AgCo6Et2fUKjEAM2utLWOhvq+w40uH4MmwqC+jcbxEj+QxcdUmtg9OMXMXhq92QlORTKpbowbddEPHPgtlcrc+dvvwRO/8iHc8uH3wN9SaV/xG0so6s5T68Qkll6l7uSxT9X4XruRWfSDehtlEvDRkwVZODLCFKpQ7G7vXodzz0wW6XYoMEhVp7/l66zMvd2xOhwUPciVnb1O9faAKUymuyHUirVWdSoOCryHjCYsqvgOal7u4TmuLaQjoX6jwQ8UfdY7MMs6DwDgaG0HfOP8oDmz2D9gai0yErL4K5K3srSK/tAiq1jFdPGSafOaI6KOr9rGnaNT4kHJYfIxRdV3x4oGkwHdfhVQfG57Xl5VptEpCn9/rQ5HoD27xdCirANAsKSFcCtZuJEqQEfj6kEuXNxA7c6K8QJpRUawWOAOWifGEa530de0cEA9aHElh7C2AQT0+TZ6QQn90Ef9ZUVMiZZmN+8pyLi+XjoGqW3RsSxBXV3MLCz5uOXD78GZn/0Q7v6Zd6nvoZCDA/D3WiACRRQjGi/DjfsoXFTH78wU2ULRjbrYmlPHKz3VUoXTKEasUayZy3XA2X0lYm+kITuI3wCDD3FahXsngyDaT/r9tHjNsK4JYD/UvN94cEVPH4Pk3PqXFob6icj2bTrlkeLCyfwVOLNTxgc1hesY5nEi9w8MJ8O5Nx1hwlRako6Yu5amB8HFry7BP6yKr2QWbRkw3XhItfbSitGy/St8VlkgWcDkGb8h9tO9uqQYxsLEmcBqhC9hkpzuuLBJsxhJtcwMTwCWkY9Mi+S+09dhpU269dwthmpypG7TENd52X6mVM1bWuM0Zxg03I37eOBjfwQAeM0v/hzKj6/AaW5h+5YDrFjeDx1kVzrcmgbAZs/B8qbVGeoXcyxAJA2YvrLwp7vGWYwKnKMxGqOxq7Fn0hC5Ig5zE0v7f9DYkYpOKc3z0NlppKMAEpr1JqtGW0GkL3JVl+kGrUgcdosCKX2G6gCySNhbXFKtWWH9lyytqvOSArYaLJaEgSlE6mOk98/XovcPqBWc1bQEhNudv6oiGWGx59Q2kOi6hnfrCWMS1FJaC8n8FYP/mL+qcv+US5kDoK89PyjkdqOecR+TKNUw5LoHLXXerSfUfQ59eGK1d+KuSuUOz7HWB6rjJqoQ7vB0rv5EBdvT6hwyy8Y3hdSvio/Na53MthVJcMooUKwIA/grG9ienkW2toHmK1TUlV1RuphhbYPb4I0bsihcjeFGYwaxWsxz+hSNh9wedUKf27ev+cWfAwA89Ht/iJPvfjfC9QiZ5Sa2b1WRVOl8A60jykekq1OLfuCotGlmTFkr0j0r5rBxNMDs3zVY0yMq+0iWdh8v7JnJQj6I6boBYEL13fqG0DZp35CBtOTQfjhLqwP1iWHAI8rnkyg2E0jKN0RiH7aPTiELYfCjH+o+7Uv7hvTnr9jHhsrhTR5veC3kUuaEIfMB6Bhy/3S+TjaDZK1uhIQzoVIGDwNVPCSVcG0a5EZd1O5SKMOJh66o8DkMAQJWAUCpiP6lBbiH59BL+4Ycm0X4bAqZCvXQBmcMLBsAT1h0vxj41WiiT90baJxK6Bucx5l5JNVxlZ4JbAr5hkj1c0czQ7M1NamRuK/xDWnD1UhH0uikNIvFmw/MGt8QEs/R9RLaH0nonXr7y+GvtFkzEwDGvxUb35Bl/cjV1hFApQcFIVzTOlJGcWkNDoDy4+oenHz3u4VvSMxFWukb4gvfEKfVxtU3TSjfEJ12Sd+QbkFhXoqXWujmdy/Yu2cmC2kpyI5aqVWb/nZmp9DXK3Cy3VFFv9T+3MNz6C+t8vt8HL2/7h3KQYp0Kcj6jycj+kEP0bPo3nHM6FnMX1GrOhUC9Wq0/trDqvXViezWo95fb3HJuEhtd+y8G6Yr4LUGgTNOGJr962NycVWcb29xydRjRLRB9RHZFqVBqtPWSFHTk4aqNzjNLTNpV8twYSs2sZBNZGsm0AS+8IMTOPjZBesY6S4Gn3PUNVqbWjcjCXwFPlo29QJ0IrjCMAkALv5IgJu/HrFtH6CAZd7+LFBbR0ZQwRmtKsWF9PZPv3caN/2xQUR6LXM9f/HvXw8AmEYNvUoJmZW2RR93u2X8+C98AV96UulZ+HFXKYOl9Cxyiz5PmuQYFq6r/f/4L3wBp+69jc9p8hGXj08Wm6WnfKATIbuWoHy+xfD2rf19joqknoVTfJH1LP7/Hnta3TtljPyPpe5N6EUKsaWD+Yum7q3Pie6tVPeWUdb11L2jY7PGlVxwVJJCjrUk/GakMBGXFtB53e0Adlb3ls5kxKvIPXrBeo/Pi4rD4qDq24QAABG7SURBVHum8+1vNlUkF9kTS9r8mXAXw9rkThjg2ptVWlSaj7iwSVaQgGpHRuMh2pMeq3ADWkhXFFOt/wvEqdeKWLeD+CLU7nSbbdx/6rO4/QPvAQCUL/W4nUypRWaljXPvKuLmD63za4BGe4Y+zr2riJv+yMDbT8//yUvMRX0HUFbaw3RYexXAwGsEnNpJGdyirev3qN1K28iahJSk652/YHVjZHdDcjiGrdoSwJR+0CiFcA8reTZiEhILVULGd7N/69w1iAsAvONH0Toxyf4XBCYiuXprctHkLiKn0YSVBC6viFTR5w6LFLQBBtii8tosMpzuFPQKgUUQ855dNAxe+aBRe1jA30kFW3qtSHEdqhHQIFsAKTIjHeJpcso/ucCLDpHhgnpbYBx6FolOyvXzsWTHAsDG905j/OErPMl09PcQ1ju49JYiCotA6bKaLLp5V6UeUYyFN8/iyfd9CADwxh/+Se5wrN2mPj/91U0kgcviPdxWrrex8uoqJp5sMsHshU4Wo27IaIzGaOxq7I3IYmSMPBh2i/TDnb9qa1ToyOE7NUaWxwPAZDhp5iMp73xvyO7xwCx3WaQxMteBNGOUNDie15CIWK/ivCjlkQQzsjm0IhiICGFpzfotbH//CWS+9CSnjACA2SmsvLqK6VPL/DmKarx6g7tTdB0AbGd0QmLq/T39GwqKfsvvXGUjZ742LRqcX05Q/fomf54wGWwsBIG5SBkHnXtXEZOPuMhs9pkl+/m//gTuOXmv2o++F/HMGLoFH/UTITZP9DjlOPdLGdz0ux3L7ClY3sSXm5/E9uLujJH3xmRxHYr6bobkftCwGKjifYIZ0/uSV5IGaxHyUU4Ass4AGPSl1PeUI13zkMhQiTglvgu3Cs9dVG3BFPjJObRfMUZFXm55mqZqIZTiUDvaO37UejioAMaoSz3xASqEj2fGmHVJGhHS25OH0PHgzzeaXK9I5q8wApQfCJGGkB4GcSVIS8JtthX7VrIlicqeUR0hSQ/vTOeQu1BjlzBib3ZmiugHDvo6vckttnhbuq7smUVs3T6H/JML2Lp9jjselGLJQdoU/cBFuB5xnaZ7cIo1PKgOsT2d4zRPaqEC6uHeuDGHvp73Jh/b5LoHqYBtT2cwdlp1PZJq2bIzuP/UZ/GGt/00f4/dvIfcYmuoIdEz7zqAI//PJtoH1MJRuLiB0+f/6KVHUU9DuIHBusSwSUTCvSUiMv0+gKHvy5ZterilkloNpaJVSo2Lj51CalKxUmo00ERC2A3vuLLuk7oOJOJLUYc7UUEv9OHJfdTWrWKoKYSa/QNgHIITmXvgNLfg6C6RnzaOFjRy2jbUojdO3EX4yDn1usZepEluLJ5DiEjth4pGU0UZuv7ikdMbTA3GgypMehMVOwopFRE+u6QmXJqEZieQiLoEa0hEXbVq1tYRCsUrLK0is7SKzh1HcPkNarI48pcBMitqIiKLApSK8FtdJMU8wnpHQMMFxF3fo+2jU3DjBJff4OKmjwn/U/IeXTYSi4ShsLgwuhbkFXPovXULYx9UtRAmmsV97iwRBZ4+T5GBE3fxhrf9NP72z/8Yr33vz6pL0PwWJ+4jms4ht6ilFAKfYeISGo6ztkDO9caemSyGjQEz5B3k9tKamulth4G8rvdZAJasHlf1h1gOMvycVLuFCzug0xYqAhbz6C+twgkDFYmIkNjRr/MDS5JonQhu1LXk67y4y+G/PIbcP6BxJtRGJFh2MQ9XA6dYZVwfr19UuhdMJNPaj44OOtiPZGkVyY2H4M5fRe+YSoX8y6vclWL2abPN2IV+MYfWEVLWTgBMIn/qjFXgRBiotuxEhXU8eaKojmNLRwtSXzN7ZpHvTa9SUBFIGBoFMEpVZqfgRj3c9DF1Mb2CBoAFZWaz+q0e79tf2eBz8Oom7ZCpQa8QqP0JHkiwvIkgDNC4bQrZFbUIBfU2d1gooqCIyI26KH54nPUoSgs9uFGiHmg9+XdnivAzIZJmC9tzJWwcVd/v7LKPfujhte/9WTz4wQ8DAH74+9+C+R+dw+G/XEO4HnGh2GluIdxMMH9PGUc+odvVSDGOn2eMCpyjMRqjsauxN2oWOwj27ta+MJ0CcP6vaxRp/AWQSlV2IKOxMpY0tBmyLWBwEeliaJqKLYcUApZ/A2DtT0oBeJBuxDfOG7j4dY5hsUwBI5Mn8ClyyFYxHU+K/AKmbiI/K2smA6+l9UmBARIYf4bqG0PEh2W0IesWLLo8O6Vk9j5/bsDM2tI+1cch02TaL6Cg2ZW/+iZD3wFVMKVzla3O3KMXOPqk6CTOOSg9t21pZgIKWUlgKHURhvDFviwwRsYkxQcoDEW34KH01CqfE2AwHYWLG5zi/fVX/gr3nLwX8cwYvFbM0Vx+YYs9R+4/9VkAwO0feA8u/9//7sXzDfmHGsPg3k4YWtgI629p/KP5ElJvgbah9wGVE6c1PN3Dc3CGgLKMVqXUqYwHCqFUYVeq0qEFyrJo13h+UBZ9DgC8JSP5nwZlefUG+vp+ANcHZaXH1olp5M+uKDSjeNi57rHd4RoNg7IyqQlZM1HTWBFKa4wKuL6mQMnwNzWnwd/qo3D2GpJrNYNlIFCW6ELQeQEqhSNJuomFEI62elTplD6HuIuJh64oH9gh12bR7WsbcKtlJAXlOQoA7UkfEw9dQaJ/T8xFyYRwtA/u0lsUDmb2wQ2zv9kpjH1NYT2iuSqC5U1c+aFZ7P+i6XCQABB1sPxmpLo6YahSNX1evUKAoN5G5nKdMR25hQaLMZ/7xSkc/7g6r27BR26xhX7oY/5H1Xndc/Je3H/qs3jjD/8krtxdRmlB1SS8VoStE9N44GN/hHtO3gsAmJnZwuUXECzsjchih27ITqu/RQkXLUD6P3Uo0ohMQNUSKOqQg4pzw1CeNIYhC2XkYf1fq2Qn81csKDetvtRmBBTkXGpyAuAcOJqr8koKgLdjEVmAjyH3DxjgliX4KyMAaV2gSWDEgQCUNylRxtN2Ar3FJat1Kjs3VKRN2wfwfdSrO2lr0msSbCWjGCKHce1HC9/SqkxdByKnSaUsZEKs37Uf4w9esslhsxN47i1lHPng02bh0WK4vUKguhvCQ7VXKaB5uGC8OjTRkL6L+XsVb+XAAw1ewekcomOzuPqaPLJrCSaeVPebfD16hVB1TzRAbON7p5XHrCD0xTNj/Pnp0zUuvC69toyZrzYs9zRS+/78X38Ct3/gPWge08XRXA9H/yxhdS9A1VK+vPZxbF/ZXet0b0QWjmNjH3aBs5A/fsxOwRU4C4pS0hoRhLNwSyXzUOsfd7LdgaO7DMBwnIU0QOZ0RhPRBnAWWnsg26oM4CyISEbV7gQY0KugiMJrlQYUqwCwtgEA6xhpItnArS4VkazVtRJUZEU0biaE14p5Bc9eKKqHNIqARtOwTgf2qlGZ0MrduvbK6FON1uR0Tl+r1ypZbVZUxwfTqaVVeLIQq+8LQ8qLefg0IRXzypd0aVX5x0L9bkrnS0qPY98sF0PdqIvCYqIYqRJr0mxbOA1AFYr95hZKcZ9X+5CQrZrHUVwQXYVOhHiuipA6Pa0YM4902FIQgNG4CH10KxmOLIgk5kZdtE5Mqu9hpY3iQh/l8y2050pchN080cPU1zxE08ZsyWvFuHJ3Gbd/4D148n0fwj1v+AkAShowGk+wemcZ+x8whfqgOYosXpTIQh6bzud6kQVFDPQ6M1GJ1JROd+h1PdlIuXySfY8rOUVrFh4j0sgIgDmG2D+fg3BXB8ARCAGd2AVdtDbl/rePTiF7YXXAJYyAXZbJknhPfjf9Q/uUJYCITLrT5QHDHLoOCTvvH9rHuAsJ4Gq9+kYUTj+jjyNSReHvar0GWB4h3YNT2J5WTmGEffBXNpAUcor5qR3E6HiUYhFvo3D2mvJdubyK6NishVdxNGWd2paEZ3GjHkcQBHknQJbU1QSArbk81zhoYXCjHroF39LSTMPjt+by6PsOrp5McPOH1nH/334GAPCqf/NzKJ9voXm4ALernvnS2XU8NP/HaGzsToNz1A0ZjdEYjV2NvZGGYDgoSxYT2d9joBA52AmQUcVO71vHFpJk6W6J1UkQBj3W53WkYxUBtcco1uomD9cFUioORpqFGc5fgdPRlXpa3Yt55a1JoiZUs6BrLubZw4KOIfdPnxlY+WlkQlXlp/d1AU2tklon48IqV+S9esN0bTIh0+r7umaR6Mimd3AKno5MqN7hRl2VhtB9hEIwph3TkxsPwdXHoe+dPw8wO9TvRKqwpyOWAfYp2UNC1Rtqd1Yw8aVL8KK88GbtY+1WH8XHYEUbXkvtW9Ly+4f2wW22jZs6NN6lrrYLn13Cc/9SAexmHgEyMJEHoCKAZ9+RAboBjvxHHYFcNufbD32OsrZOTCO30FCamdT5KOaw/H0ZbO3v4+b7TEr79C8XcMuvXbPqI3moa7jyxhI2bq3gVf9GCeh89Xf+EPe84SdQ/mZkRTFRefd6FnsmDRnGOk1bFcq/pVBuWomqd602YH047H3AMFmpLZvWr3SLBQu41Duv6NGUxvCP+sDscB6FsCkkHcvupXl4x4/yvvzDh0zoTqK45y4y30KCtZhNKdWohD0A7R9Q0G7anjkcB2a5YOe1IlOAFAzXgSHtAfTf/WaLUwZgeAGTtqViLP1It+by8Fs9Q5UX28UzSk0qnWqleSBUYGTRXX1vGJYtNTEbTfSOHcDWXN4ApXRx9MoPTGDiG+q1zOW6LaxLCxIxaYVbWzwzhu3pDLIrnQHWKaBqHzRZrL6iiNkvLMNpbmHz1TfwNZSeWkWvUsCltxQx/TVV88iudJTITmAeYqVwVWOVs2uvUHWTycc2cfGtYygsAuGmeo4nHrqCrRPTcOME0biP/ALVTSLc/7efwd0/8y7rvn/l6idfYhT1kZ7Fd42ehWydSgtC6iYApnX6QvQsCEMBqAeCKOsDkyZg3Rt5bQBsX1m9CBDXglunYqWmz1Cn6erPKPGZ2Qc3+Ltgn1mkW6eqxtMrhIpqn2qd0mvRsVnL1zTtDUuOcOhEOPO/3MCt06iSYWLb/D3qWg7/+dLQ1mn5m3W050pW6zSeGcOjD//+rrkhe2ayGIGyRqAsYATK2sugrFGBczRGYzR2NfZ0ZLEb1imHrNVxTjMkOWxYSCtNd2RIDQj8hvaPIP8P9floIFJJf55qDk6rPSD4m7YOTLdfZdrAtY6UX4VVeLve/vUxzHmaFVoJ4AY2HV3Tyen/1jnoIUFR7BwmNEW9A7NWSE7hvHVOdO5C7wGASQuWVm0VbTp2Mc+rahK4qt6iawlcl9Eq4r1KyZhH62IwK34JvIYik9nUewKgyXvD56BrPYAqkBJQzKltcPvVifvw6g10p8uWgXGvEFrgKZLjSxpNtF951KLO9woBt1gBBdQqXmqpzzdTdSUtSExj9c4MZh7esrRQaTitNqK5KpbvUt/Hk+/7ECpHmi+9msX3T/yYxdQEYIX/aXQkTQxp/AUAFvUlGvUwfEZasBfAQE3EynVhwmop8EL7TW8vBXsH0gyNgCQJPTISAswEQHWCYbgDb2ltQLDX8grVE4pkplo1HnFv5USa3HgIV+4uG8HeJcMkJQYqbSvd1wDDULVSG2K3piYd2n7hzbOY+/jT1r2RqFMAjFFJmxRJXAilBlRD6E6XuU4EAGd+5TBu/o1zA9iLjVsrGH/wkvFg1UVTNgkS3qy9SgnnfrqEmz+o6z0idQDA3ZAbPrNgUi7hdHbpbbPIveoaZn5FPZdUrCSjIxqdgxVkzyxaNg2d6RxW7wyR+W/M5wHg2XdUcezjy3Y6qBe5S2+bxb7THS6UPnePrzop8rwAXHM/gEe/vv3SmSwcx1kF0AJw7R/7XP6BxyRG1/xPYezla74hSZKp599sj0wWAOA4zqNJkrzyH/s8/iHH6Jr/aYzvlmseFThHYzRGY1djNFmMxmiMxq7GXpos7vvHPoF/hDG65n8a47vimvdMzWI0RmM09vbYS5HFaIzGaOzhMZosRmM0RmNXYzRZjMZojMauxmiyGI3RGI1djdFkMRqjMRq7Gv8flxrFb8aLomkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9497e5a860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman sp kernel matrix of size 183 built in 39.78876876831055 seconds ---\n",
      "\n",
      "gram matrix with parameters {'base_kernel': 'sp', 'height': 2.0} is: \n",
      "[[  9.   3.   9. ...   3.   3.   3.]\n",
      " [  3.  18.   3. ...   0.   0.   9.]\n",
      " [  9.   3.   9. ...   3.   3.   3.]\n",
      " ...\n",
      " [  3.   0.   3. ... 165.  63.  21.]\n",
      " [  3.   0.   3. ...  63. 165.  21.]\n",
      " [  3.   9.   3. ...  21.  21. 165.]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9495d37438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman sp kernel matrix of size 183 built in 52.122785806655884 seconds ---\n",
      "\n",
      "gram matrix with parameters {'base_kernel': 'sp', 'height': 3.0} is: \n",
      "[[ 12.   4.  12. ...   4.   4.   4.]\n",
      " [  4.  24.   4. ...   0.   0.  12.]\n",
      " [ 12.   4.  12. ...   4.   4.   4.]\n",
      " ...\n",
      " [  4.   0.   4. ... 220.  84.  28.]\n",
      " [  4.   0.   4. ...  84. 220.  28.]\n",
      " [  4.  12.   4. ...  28.  28. 220.]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9495c27b00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman sp kernel matrix of size 183 built in 64.37597727775574 seconds ---\n",
      "\n",
      "gram matrix with parameters {'base_kernel': 'sp', 'height': 4.0} is: \n",
      "[[ 15.   5.  15. ...   5.   5.   5.]\n",
      " [  5.  30.   5. ...   0.   0.  15.]\n",
      " [ 15.   5.  15. ...   5.   5.   5.]\n",
      " ...\n",
      " [  5.   0.   5. ... 275. 105.  35.]\n",
      " [  5.   0.   5. ... 105. 275.  35.]\n",
      " [  5.  15.   5. ...  35.  35. 275.]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9495b1f668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman sp kernel matrix of size 183 built in 79.43934679031372 seconds ---\n",
      "\n",
      "gram matrix with parameters {'base_kernel': 'sp', 'height': 5.0} is: \n",
      "[[ 18.   6.  18. ...   6.   6.   6.]\n",
      " [  6.  36.   6. ...   0.   0.  18.]\n",
      " [ 18.   6.  18. ...   6.   6.   6.]\n",
      " ...\n",
      " [  6.   0.   6. ... 330. 126.  42.]\n",
      " [  6.   0.   6. ... 126. 330.  42.]\n",
      " [  6.  18.   6. ...  42.  42. 330.]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9495ad96a0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman sp kernel matrix of size 183 built in 91.50003838539124 seconds ---\n",
      "\n",
      "gram matrix with parameters {'base_kernel': 'sp', 'height': 6.0} is: \n",
      "[[ 21.   7.  21. ...   7.   7.   7.]\n",
      " [  7.  42.   7. ...   0.   0.  21.]\n",
      " [ 21.   7.  21. ...   7.   7.   7.]\n",
      " ...\n",
      " [  7.   0.   7. ... 385. 147.  49.]\n",
      " [  7.   0.   7. ... 147. 385.  49.]\n",
      " [  7.  21.   7. ...  49.  49. 385.]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9495a172e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman sp kernel matrix of size 183 built in 103.36761713027954 seconds ---\n",
      "\n",
      "gram matrix with parameters {'base_kernel': 'sp', 'height': 7.0} is: \n",
      "[[ 24.   8.  24. ...   8.   8.   8.]\n",
      " [  8.  48.   8. ...   0.   0.  24.]\n",
      " [ 24.   8.  24. ...   8.   8.   8.]\n",
      " ...\n",
      " [  8.   0.   8. ... 440. 168.  56.]\n",
      " [  8.   0.   8. ... 168. 440.  56.]\n",
      " [  8.  24.   8. ...  56.  56. 440.]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f949596eeb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman sp kernel matrix of size 183 built in 116.12333679199219 seconds ---\n",
      "\n",
      "gram matrix with parameters {'base_kernel': 'sp', 'height': 8.0} is: \n",
      "[[ 27.   9.  27. ...   9.   9.   9.]\n",
      " [  9.  54.   9. ...   0.   0.  27.]\n",
      " [ 27.   9.  27. ...   9.   9.   9.]\n",
      " ...\n",
      " [  9.   0.   9. ... 495. 189.  63.]\n",
      " [  9.   0.   9. ... 189. 495.  63.]\n",
      " [  9.  27.   9. ...  63.  63. 495.]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9495ace780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman sp kernel matrix of size 183 built in 129.00585055351257 seconds ---\n",
      "\n",
      "gram matrix with parameters {'base_kernel': 'sp', 'height': 9.0} is: \n",
      "[[ 30.  10.  30. ...  10.  10.  10.]\n",
      " [ 10.  60.  10. ...   0.   0.  30.]\n",
      " [ 30.  10.  30. ...  10.  10.  10.]\n",
      " ...\n",
      " [ 10.   0.  10. ... 550. 210.  70.]\n",
      " [ 10.   0.  10. ... 210. 550.  70.]\n",
      " [ 10.  30.  10. ...  70.  70. 550.]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9497e5ac18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman sp kernel matrix of size 183 built in 142.7631003856659 seconds ---\n",
      "\n",
      "gram matrix with parameters {'base_kernel': 'sp', 'height': 10.0} is: \n",
      "[[ 33.  11.  33. ...  11.  11.  11.]\n",
      " [ 11.  66.  11. ...   0.   0.  33.]\n",
      " [ 33.  11.  33. ...  11.  11.  11.]\n",
      " ...\n",
      " [ 11.   0.  11. ... 605. 231.  77.]\n",
      " [ 11.   0.  11. ... 231. 605.  77.]\n",
      " [ 11.  33.  11. ...  77.  77. 605.]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9495b1ac88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "3. Fitting and predicting using nested cross validation. This could really take a while...\n",
      "calculate performance:   0%|          | 2/13530 [00:00<18:41, 12.07it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ljia/.local/lib/python3.5/site-packages/sklearn/linear_model/ridge.py:154: UserWarning: Singular matrix in solving dual problem. Using least-squares solution instead.\n",
      "  warnings.warn(\"Singular matrix in solving dual problem. Using \"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                                                            \n",
      "4. Getting final performances...\n",
      "\n",
      "best_params_out:  [{'base_kernel': 'sp', 'height': 2.0}]\n",
      "best_params_in:  [{'alpha': 100.0}]\n",
      "best_val_perf:  35.99396330118595\n",
      "best_val_std:  0.975168619010553\n",
      "final_performance:  37.92011979777975\n",
      "final_confidence:  5.599617973456408\n",
      "train_performance:  28.31827397760314\n",
      "train_std:  0.6337452324001842\n",
      "time to calculate gram matrix:  39.78876876831055 s\n",
      "\n",
      "params                                                      train_perf            valid_perf             test_perf               gram_matrix_time\n",
      "----------------------------------------------------------  --------------------  ---------------------  --------------------  ------------------\n",
      "{'alpha': '1.00e-02', 'base_kernel': 'sp', 'height': 0.0}   6303.33±17673.66      12355.82±26031.70      23725.39±87669.55                  13.25\n",
      "{'alpha': '1.00e-02', 'base_kernel': 'sp', 'height': 1.0}   11167.76±22193.97     41656.88±103467.38     32381.60±72912.93                  26.25\n",
      "{'alpha': '1.00e-02', 'base_kernel': 'sp', 'height': 2.0}   14795.24±25795.77     35568.25±55185.30      29590.89±50716.39                  39.79\n",
      "{'alpha': '1.00e-02', 'base_kernel': 'sp', 'height': 3.0}   17333.71±39530.48     47391.61±108495.33     44509.59±98871.73                  52.12\n",
      "{'alpha': '1.00e-02', 'base_kernel': 'sp', 'height': 4.0}   18278.98±33231.47     41847.75±72770.75      34135.41±55211.24                  64.38\n",
      "{'alpha': '1.00e-02', 'base_kernel': 'sp', 'height': 5.0}   29803.79±66494.69     78569.33±175795.65     82370.17±157243.38                 79.44\n",
      "{'alpha': '1.00e-02', 'base_kernel': 'sp', 'height': 6.0}   17632.65±22083.28     39884.05±38376.83      50945.19±82473.15                  91.5\n",
      "{'alpha': '1.00e-02', 'base_kernel': 'sp', 'height': 7.0}   47674.56±138824.33    103908.47±267675.59    149730.54±504033.41               103.37\n",
      "{'alpha': '1.00e-02', 'base_kernel': 'sp', 'height': 8.0}   38700.43±57742.33     100584.20±172213.12    125033.09±243352.04               116.12\n",
      "{'alpha': '1.00e-02', 'base_kernel': 'sp', 'height': 9.0}   51137.13±109807.16    158062.18±287987.15    111850.92±189317.22               129.01\n",
      "{'alpha': '1.00e-02', 'base_kernel': 'sp', 'height': 10.0}  91585.56±358714.20    204806.70±740337.04    171099.59±539990.26               142.76\n",
      "{'alpha': '1.26e-02', 'base_kernel': 'sp', 'height': 0.0}   3768.93±6563.97       8039.24±10612.57       12197.40±30860.60                  13.25\n",
      "{'alpha': '1.26e-02', 'base_kernel': 'sp', 'height': 1.0}   8534.90±16639.10      31484.39±77224.48      24146.92±51302.34                  26.25\n",
      "{'alpha': '1.26e-02', 'base_kernel': 'sp', 'height': 2.0}   9522.71±13808.72      23859.97±34172.83      20790.22±36158.94                  39.79\n",
      "{'alpha': '1.26e-02', 'base_kernel': 'sp', 'height': 3.0}   15137.34±34822.01     41325.26±96108.07      38166.76±85847.44                  52.12\n",
      "{'alpha': '1.26e-02', 'base_kernel': 'sp', 'height': 4.0}   14602.91±26904.97     33388.42±58724.36      27246.28±44445.54                  64.38\n",
      "{'alpha': '1.26e-02', 'base_kernel': 'sp', 'height': 5.0}   36376.37±92923.37     89270.52±213430.12     154091.39±564983.92                79.44\n",
      "{'alpha': '1.26e-02', 'base_kernel': 'sp', 'height': 6.0}   13950.65±17415.09     31638.00±30110.29      40270.40±65177.46                  91.5\n",
      "{'alpha': '1.26e-02', 'base_kernel': 'sp', 'height': 7.0}   38475.48±113598.06    83787.88±218535.51     121394.03±413538.68               103.37\n",
      "{'alpha': '1.26e-02', 'base_kernel': 'sp', 'height': 8.0}   31296.81±45734.25     80949.11±137088.59     101612.85±192522.79               116.12\n",
      "{'alpha': '1.26e-02', 'base_kernel': 'sp', 'height': 9.0}   40632.06±86164.37     125455.67±226493.68    89065.57±149368.33                129.01\n",
      "{'alpha': '1.26e-02', 'base_kernel': 'sp', 'height': 10.0}  588900.37±3110944.10  1208690.68±6314266.44  912325.54±4674254.12              142.76\n",
      "{'alpha': '1.58e-02', 'base_kernel': 'sp', 'height': 0.0}   3402.21±4861.55       6927.14±7628.84        9974.47±17914.08                   13.25\n",
      "{'alpha': '1.58e-02', 'base_kernel': 'sp', 'height': 1.0}   6617.26±12608.36      24122.00±58386.26      18238.60±36649.01                  26.25\n",
      "{'alpha': '1.58e-02', 'base_kernel': 'sp', 'height': 2.0}   7174.76±10260.62      18390.19±26551.90      16156.03±28603.75                  39.79\n",
      "{'alpha': '1.58e-02', 'base_kernel': 'sp', 'height': 3.0}   15445.15±35597.93     42187.40±100161.18     36849.70±81732.90                  52.12\n",
      "{'alpha': '1.58e-02', 'base_kernel': 'sp', 'height': 4.0}   11719.06±21952.36     26721.73±47654.14      21827.47±35996.70                  64.38\n",
      "{'alpha': '1.58e-02', 'base_kernel': 'sp', 'height': 5.0}   19558.92±45231.30     51820.00±121029.46     53575.36±104092.62                 79.44\n",
      "{'alpha': '1.58e-02', 'base_kernel': 'sp', 'height': 6.0}   11054.71±13722.93     25122.73±23593.67      31880.38±51465.74                  91.5\n",
      "{'alpha': '1.58e-02', 'base_kernel': 'sp', 'height': 7.0}   31243.81±93849.12     67929.02±179990.76     99115.10±342685.77                103.37\n",
      "{'alpha': '1.58e-02', 'base_kernel': 'sp', 'height': 8.0}   24475.48±36661.26     63742.72±109997.86     78962.46±153441.71                116.12\n",
      "{'alpha': '1.58e-02', 'base_kernel': 'sp', 'height': 9.0}   32338.18±67471.74     99667.67±177830.20     71074.49±117877.28                129.01\n",
      "{'alpha': '1.58e-02', 'base_kernel': 'sp', 'height': 10.0}  44661.93±154596.34    102722.00±322326.26    88277.53±235092.65                142.76\n",
      "{'alpha': '2.00e-02', 'base_kernel': 'sp', 'height': 0.0}   2323.26±3304.60       5144.94±5951.59        6681.02±11271.13                   13.25\n",
      "{'alpha': '2.00e-02', 'base_kernel': 'sp', 'height': 1.0}   5297.66±9767.34       19017.71±44815.21      14128.45±26709.36                  26.25\n",
      "{'alpha': '2.00e-02', 'base_kernel': 'sp', 'height': 2.0}   6100.66±8418.77       16665.03±24140.44      14252.41±24053.28                  39.79\n",
      "{'alpha': '2.00e-02', 'base_kernel': 'sp', 'height': 3.0}   36896.38±113586.18    80947.13±190128.91     84225.84±237100.17                 52.12\n",
      "{'alpha': '2.00e-02', 'base_kernel': 'sp', 'height': 4.0}   9473.74±18126.17      21491.97±38982.70      17590.16±29442.06                  64.38\n",
      "{'alpha': '2.00e-02', 'base_kernel': 'sp', 'height': 5.0}   15381.25±37822.87     41288.25±102502.73     38927.96±74614.60                  79.44\n",
      "{'alpha': '2.00e-02', 'base_kernel': 'sp', 'height': 6.0}   8768.30±10806.66      19968.19±18466.73      25256.94±40607.09                  91.5\n",
      "{'alpha': '2.00e-02', 'base_kernel': 'sp', 'height': 7.0}   25597.38±78568.16     55496.02±150071.14     81734.72±287878.47                103.37\n",
      "{'alpha': '2.00e-02', 'base_kernel': 'sp', 'height': 8.0}   19449.04±29299.35     50750.84±88218.43      62647.17±121963.73                116.12\n",
      "{'alpha': '2.00e-02', 'base_kernel': 'sp', 'height': 9.0}   25681.00±52825.34     79181.94±139558.55     56756.57±93381.45                 129.01\n",
      "{'alpha': '2.00e-02', 'base_kernel': 'sp', 'height': 10.0}  23431.11±57792.85     57201.81±124925.25     52031.72±94962.04                 142.76\n",
      "{'alpha': '2.51e-02', 'base_kernel': 'sp', 'height': 0.0}   1706.68±1997.53       4156.92±5066.65        4811.88±7065.20                    13.25\n",
      "{'alpha': '2.51e-02', 'base_kernel': 'sp', 'height': 1.0}   5737.08±12922.22      19314.99±45491.91      13605.41±26445.29                  26.25\n",
      "{'alpha': '2.51e-02', 'base_kernel': 'sp', 'height': 2.0}   5554.08±8376.77       13323.20±18835.42      11745.90±19671.83                  39.79\n",
      "{'alpha': '2.51e-02', 'base_kernel': 'sp', 'height': 3.0}   10999.47±34932.16     29963.67±97524.08      27407.75±85255.47                  52.12\n",
      "{'alpha': '2.51e-02', 'base_kernel': 'sp', 'height': 4.0}   7756.89±15272.71      17431.87±32281.45      14323.33±24509.35                  64.38\n",
      "{'alpha': '2.51e-02', 'base_kernel': 'sp', 'height': 5.0}   12646.03±32780.60     34234.15±89891.06      30903.80±61870.70                  79.44\n",
      "{'alpha': '2.51e-02', 'base_kernel': 'sp', 'height': 6.0}   6962.54±8506.63       15891.34±14442.07      20025.21±32016.11                  91.5\n",
      "{'alpha': '2.51e-02', 'base_kernel': 'sp', 'height': 7.0}   21249.12±67027.30     45854.18±127344.48     68392.68±246542.65                103.37\n",
      "{'alpha': '2.51e-02', 'base_kernel': 'sp', 'height': 8.0}   15482.19±23467.38     40480.24±70964.55      49789.15±96986.21                 116.12\n",
      "{'alpha': '2.51e-02', 'base_kernel': 'sp', 'height': 9.0}   20569.62±41430.11     63260.95±109672.08     45739.85±74687.08                 129.01\n",
      "{'alpha': '2.51e-02', 'base_kernel': 'sp', 'height': 10.0}  15344.15±28899.03     38829.90±65159.35      36443.09±54440.50                 142.76\n",
      "{'alpha': '3.16e-02', 'base_kernel': 'sp', 'height': 0.0}   1812.34±3328.07       4517.74±7699.99        5334.46±11850.11                   13.25\n",
      "{'alpha': '3.16e-02', 'base_kernel': 'sp', 'height': 1.0}   3324.62±5881.84       11714.75±26863.60      8516.88±14830.75                   26.25\n",
      "{'alpha': '3.16e-02', 'base_kernel': 'sp', 'height': 2.0}   3883.95±5846.81       9900.98±14890.77       8853.41±15625.79                   39.79\n",
      "{'alpha': '3.16e-02', 'base_kernel': 'sp', 'height': 3.0}   16572.68±72812.56     46109.58±204728.63     40841.93±176065.17                 52.12\n",
      "{'alpha': '3.16e-02', 'base_kernel': 'sp', 'height': 4.0}   6522.78±13415.44      14395.81±27297.15      11930.62±21194.20                  64.38\n",
      "{'alpha': '3.16e-02', 'base_kernel': 'sp', 'height': 5.0}   10752.24±29757.31     29386.75±82846.79      25518.23±54417.30                  79.44\n",
      "{'alpha': '3.16e-02', 'base_kernel': 'sp', 'height': 6.0}   5537.57±6695.23       12669.69±11289.46      15895.51±25225.36                  91.5\n",
      "{'alpha': '3.16e-02', 'base_kernel': 'sp', 'height': 7.0}   18006.72±58796.31     38560.98±110938.86     58539.30±217197.03                103.37\n",
      "{'alpha': '3.16e-02', 'base_kernel': 'sp', 'height': 8.0}   12345.72±18866.15     32353.91±57339.24      39626.99±77215.49                 116.12\n",
      "{'alpha': '3.16e-02', 'base_kernel': 'sp', 'height': 9.0}   16755.53±33025.17     51204.59±87297.18      37580.82±61861.63                 129.01\n",
      "{'alpha': '3.16e-02', 'base_kernel': 'sp', 'height': 10.0}  10917.07±16757.44     28282.57±39373.53      27063.87±36881.79                 142.76\n",
      "{'alpha': '3.98e-02', 'base_kernel': 'sp', 'height': 0.0}   1701.12±3189.69       6228.13±19072.20       3746.43±5345.81                    13.25\n",
      "{'alpha': '3.98e-02', 'base_kernel': 'sp', 'height': 1.0}   2481.43±4218.54       8721.55±20347.10       6492.29±11068.31                   26.25\n",
      "{'alpha': '3.98e-02', 'base_kernel': 'sp', 'height': 2.0}   3072.55±4791.99       7921.48±12602.09       6942.43±12747.11                   39.79\n",
      "{'alpha': '3.98e-02', 'base_kernel': 'sp', 'height': 3.0}   11604.23±49720.92     32322.99±140230.45     28780.68±120751.41                 52.12\n",
      "{'alpha': '3.98e-02', 'base_kernel': 'sp', 'height': 4.0}   5923.37±13488.67      12371.10±24456.66      10555.83±20831.26                  64.38\n",
      "{'alpha': '3.98e-02', 'base_kernel': 'sp', 'height': 5.0}   9684.83±29484.54      26833.56±83789.06      22147.64±52139.65                  79.44\n",
      "{'alpha': '3.98e-02', 'base_kernel': 'sp', 'height': 6.0}   4415.64±5270.17       10128.04±8823.85       12641.33±19861.62                  91.5\n",
      "{'alpha': '3.98e-02', 'base_kernel': 'sp', 'height': 7.0}   15852.07±53873.47     33478.64±100769.54     52268.31±199990.98                103.37\n",
      "{'alpha': '3.98e-02', 'base_kernel': 'sp', 'height': 8.0}   9869.84±15253.60      25935.78±46628.64      31608.74±61607.54                 116.12\n",
      "{'alpha': '3.98e-02', 'base_kernel': 'sp', 'height': 9.0}   14477.22±29009.68     43449.52±75315.39      32950.38±59664.94                 129.01\n",
      "{'alpha': '3.98e-02', 'base_kernel': 'sp', 'height': 10.0}  8096.84±10755.21      21315.51±26117.25      20661.11±27131.39                 142.76\n",
      "{'alpha': '5.01e-02', 'base_kernel': 'sp', 'height': 0.0}   834.25±897.42         2250.77±3160.40        2286.24±2994.25                    13.25\n",
      "{'alpha': '5.01e-02', 'base_kernel': 'sp', 'height': 1.0}   4772.85±15849.74      10935.54±26327.58      8064.85±16783.61                   26.25\n",
      "{'alpha': '5.01e-02', 'base_kernel': 'sp', 'height': 2.0}   2872.84±4670.43       7070.37±11673.13       6309.78±11443.46                   39.79\n",
      "{'alpha': '5.01e-02', 'base_kernel': 'sp', 'height': 3.0}   4308.50±12657.79      11767.04±35381.85      10993.55±31407.59                  52.12\n",
      "{'alpha': '5.01e-02', 'base_kernel': 'sp', 'height': 4.0}   151764.66±812957.25   151573.89±784519.35    213676.11±1136693.41               64.38\n",
      "{'alpha': '5.01e-02', 'base_kernel': 'sp', 'height': 5.0}   10207.91±36268.27     28896.04±106100.30     21814.45±61722.17                  79.44\n",
      "{'alpha': '5.01e-02', 'base_kernel': 'sp', 'height': 6.0}   3533.92±4150.86       8126.65±6897.43        10082.44±15628.75                  91.5\n",
      "{'alpha': '5.01e-02', 'base_kernel': 'sp', 'height': 7.0}   14814.28±53186.63     30605.36±98450.06      49368.78±198322.84                103.37\n",
      "{'alpha': '5.01e-02', 'base_kernel': 'sp', 'height': 8.0}   7923.49±12441.66      20888.65±38281.24      25315.06±49342.79                 116.12\n",
      "{'alpha': '5.01e-02', 'base_kernel': 'sp', 'height': 9.0}   23740.36±83454.02     64160.95±202799.90     56787.26±205644.99                129.01\n",
      "{'alpha': '5.01e-02', 'base_kernel': 'sp', 'height': 10.0}  6156.18±7429.06       16387.77±18431.68      16025.72±20754.54                 142.76\n",
      "{'alpha': '6.31e-02', 'base_kernel': 'sp', 'height': 0.0}   680.06±759.87         1755.31±2249.35        1800.37±2297.44                    13.25\n",
      "{'alpha': '6.31e-02', 'base_kernel': 'sp', 'height': 1.0}   1487.10±2403.34       5367.92±12309.78       4060.60±6641.01                    26.25\n",
      "{'alpha': '6.31e-02', 'base_kernel': 'sp', 'height': 2.0}   2569.92±4858.09       6501.50±12447.45       5400.45±10867.48                   39.79\n",
      "{'alpha': '6.31e-02', 'base_kernel': 'sp', 'height': 3.0}   2836.84±6408.56       7476.78±16804.80       7183.84±15696.99                   52.12\n",
      "{'alpha': '6.31e-02', 'base_kernel': 'sp', 'height': 4.0}   3969.37±9296.64       8512.05±18714.80       7020.04±13965.44                   64.38\n",
      "{'alpha': '6.31e-02', 'base_kernel': 'sp', 'height': 5.0}   33967.75±169622.50    102667.58±518103.72    60392.94±280631.92                 79.44\n",
      "{'alpha': '6.31e-02', 'base_kernel': 'sp', 'height': 6.0}   2857.77±3264.58       6573.93±5378.61        8100.03±12278.90                   91.5\n",
      "{'alpha': '6.31e-02', 'base_kernel': 'sp', 'height': 7.0}   15222.97±61120.27     30754.07±111848.55     52158.17±228814.06                103.37\n",
      "{'alpha': '6.31e-02', 'base_kernel': 'sp', 'height': 8.0}   6414.19±10295.29      16979.06±31893.97      20502.03±39814.65                 116.12\n",
      "{'alpha': '6.31e-02', 'base_kernel': 'sp', 'height': 9.0}   9237.24±18448.57      27528.23±47723.63      21308.15±40081.82                 129.01\n",
      "{'alpha': '6.31e-02', 'base_kernel': 'sp', 'height': 10.0}  4767.49±5394.43       12780.17±13539.03      12573.28±16164.22                 142.76\n",
      "{'alpha': '7.94e-02', 'base_kernel': 'sp', 'height': 0.0}   1151.05±3339.29       3238.73±10857.56       2721.97±7584.68                    13.25\n",
      "{'alpha': '7.94e-02', 'base_kernel': 'sp', 'height': 1.0}   1238.91±1878.00       4265.39±9676.41        3261.55±5025.86                    26.25\n",
      "{'alpha': '7.94e-02', 'base_kernel': 'sp', 'height': 2.0}   6623.55±20063.54      14202.25±41137.00      12097.70±38056.93                  39.79\n",
      "{'alpha': '7.94e-02', 'base_kernel': 'sp', 'height': 3.0}   3606.28±9332.05       9808.70±22314.74       8154.59±17904.99                   52.12\n",
      "{'alpha': '7.94e-02', 'base_kernel': 'sp', 'height': 4.0}   3283.98±7983.29       7416.05±18008.67       5838.94±11564.90                   64.38\n",
      "{'alpha': '7.94e-02', 'base_kernel': 'sp', 'height': 5.0}   7428.02±25896.16      21389.21±75522.01      16306.25±45559.21                  79.44\n",
      "{'alpha': '7.94e-02', 'base_kernel': 'sp', 'height': 6.0}   2332.59±2573.99       5362.62±4201.36        6556.87±9643.76                    91.5\n",
      "{'alpha': '7.94e-02', 'base_kernel': 'sp', 'height': 7.0}   23856.19±111470.61    45837.78±201957.39     85222.77±418320.71                103.37\n",
      "{'alpha': '7.94e-02', 'base_kernel': 'sp', 'height': 8.0}   5234.47±8701.12       13904.46±27197.46      16642.70±32501.96                 116.12\n",
      "{'alpha': '7.94e-02', 'base_kernel': 'sp', 'height': 9.0}   6127.60±10443.05      18842.57±28929.22      13959.59±20242.76                 129.01\n",
      "{'alpha': '7.94e-02', 'base_kernel': 'sp', 'height': 10.0}  4161.08±4421.73       10774.68±10392.46      10587.68±12776.94                 142.76\n",
      "{'alpha': '1.00e-01', 'base_kernel': 'sp', 'height': 0.0}   545.03±706.84         1214.04±1367.67        1305.35±1469.96                    13.25\n",
      "{'alpha': '1.00e-01', 'base_kernel': 'sp', 'height': 1.0}   1231.30±1751.27       3927.93±7932.28        3529.36±5777.73                    26.25\n",
      "{'alpha': '1.00e-01', 'base_kernel': 'sp', 'height': 2.0}   2363.84±4738.11       5844.33±12039.10       4756.98±9194.94                    39.79\n",
      "{'alpha': '1.00e-01', 'base_kernel': 'sp', 'height': 3.0}   1897.24±4527.19       4709.00±9718.09        4501.55±9545.93                    52.12\n",
      "{'alpha': '1.00e-01', 'base_kernel': 'sp', 'height': 4.0}   3976.80±10959.83      8485.22±23090.27       7164.33±18149.02                   64.38\n",
      "{'alpha': '1.00e-01', 'base_kernel': 'sp', 'height': 5.0}   4703.35±15005.54      12362.04±38906.71      10531.94±25834.10                  79.44\n",
      "{'alpha': '1.00e-01', 'base_kernel': 'sp', 'height': 6.0}   1975.71±2062.28       4485.73±3319.66        5433.45±7573.52                    91.5\n",
      "{'alpha': '1.00e-01', 'base_kernel': 'sp', 'height': 7.0}   29597.78±143503.80    55853.17±259376.30     106935.97±538451.64               103.37\n",
      "{'alpha': '1.00e-01', 'base_kernel': 'sp', 'height': 8.0}   4380.00±7645.98       11663.78±24161.98      13828.87±27217.05                 116.12\n",
      "{'alpha': '1.00e-01', 'base_kernel': 'sp', 'height': 9.0}   4549.23±7324.03       14097.75±20993.30      10400.14±14095.80                 129.01\n",
      "{'alpha': '1.00e-01', 'base_kernel': 'sp', 'height': 10.0}  3076.05±3196.16       8146.84±7932.14        8019.92±10035.56                  142.76\n",
      "{'alpha': '1.26e-01', 'base_kernel': 'sp', 'height': 0.0}   393.24±333.57         912.35±712.52          1039.25±1033.27                    13.25\n",
      "{'alpha': '1.26e-01', 'base_kernel': 'sp', 'height': 1.0}   1287.33±2882.76       3566.75±7560.31        4372.56±13718.50                   26.25\n",
      "{'alpha': '1.26e-01', 'base_kernel': 'sp', 'height': 2.0}   1897.63±3127.60       4730.92±8235.63        3948.78±7398.67                    39.79\n",
      "{'alpha': '1.26e-01', 'base_kernel': 'sp', 'height': 3.0}   1250.87±2129.08       3122.28±4959.93        3041.04±4903.40                    52.12\n",
      "{'alpha': '1.26e-01', 'base_kernel': 'sp', 'height': 4.0}   6176.06±24487.49      14997.30±61326.15      8789.78±27176.70                   64.38\n",
      "{'alpha': '1.26e-01', 'base_kernel': 'sp', 'height': 5.0}   3046.99±7195.74       7861.87±18150.06       7941.93±16088.13                   79.44\n",
      "{'alpha': '1.26e-01', 'base_kernel': 'sp', 'height': 6.0}   1651.97±1657.99       3809.79±2637.45        4790.57±6404.92                    91.5\n",
      "{'alpha': '1.26e-01', 'base_kernel': 'sp', 'height': 7.0}   8266.61±27577.07      16428.14±50783.59      26937.19±102360.43                103.37\n",
      "{'alpha': '1.26e-01', 'base_kernel': 'sp', 'height': 8.0}   3830.28±7315.81       10262.57±23368.85      11935.69±24393.92                 116.12\n",
      "{'alpha': '1.26e-01', 'base_kernel': 'sp', 'height': 9.0}   3333.40±5254.34       10501.99±15544.38      7724.93±10372.21                  129.01\n",
      "{'alpha': '1.26e-01', 'base_kernel': 'sp', 'height': 10.0}  2355.02±2432.24       6381.11±6132.07        6323.10±7947.14                   142.76\n",
      "{'alpha': '1.58e-01', 'base_kernel': 'sp', 'height': 0.0}   987.04±3430.40        1516.44±3537.79        2048.54±5011.98                    13.25\n",
      "{'alpha': '1.58e-01', 'base_kernel': 'sp', 'height': 1.0}   893.86±1553.46        3118.86±7272.18        1820.70±2573.37                    26.25\n",
      "{'alpha': '1.58e-01', 'base_kernel': 'sp', 'height': 2.0}   1051.49±1740.21       2783.26±4592.68        2411.64±5213.85                    39.79\n",
      "{'alpha': '1.58e-01', 'base_kernel': 'sp', 'height': 3.0}   1665.73±4449.33       3264.69±6892.97        3266.88±6275.25                    52.12\n",
      "{'alpha': '1.58e-01', 'base_kernel': 'sp', 'height': 4.0}   3070.96±8336.51       7162.22±20478.54       4896.61±10069.33                   64.38\n",
      "{'alpha': '1.58e-01', 'base_kernel': 'sp', 'height': 5.0}   3189.83±6524.09       7203.79±14451.87       8017.59±17308.73                   79.44\n",
      "{'alpha': '1.58e-01', 'base_kernel': 'sp', 'height': 6.0}   1460.34±1423.49       3369.50±2300.81        3920.74±4811.40                    91.5\n",
      "{'alpha': '1.58e-01', 'base_kernel': 'sp', 'height': 7.0}   11268.54±39883.22     20562.41±65502.43      38277.74±143351.07                103.37\n",
      "{'alpha': '1.58e-01', 'base_kernel': 'sp', 'height': 8.0}   3906.02±8899.77       10575.85±28554.60      11626.77±27381.16                 116.12\n",
      "{'alpha': '1.58e-01', 'base_kernel': 'sp', 'height': 9.0}   2497.03±3763.45       7962.29±11508.02       5841.11±7726.10                   129.01\n",
      "{'alpha': '1.58e-01', 'base_kernel': 'sp', 'height': 10.0}  1880.34±1909.89       5135.89±4830.74        5095.65±6298.92                   142.76\n",
      "{'alpha': '2.00e-01', 'base_kernel': 'sp', 'height': 0.0}   335.30±230.75         875.21±713.55          1085.66±1258.03                    13.25\n",
      "{'alpha': '2.00e-01', 'base_kernel': 'sp', 'height': 1.0}   682.01±1000.38        2539.20±6516.93        1521.32±2323.02                    26.25\n",
      "{'alpha': '2.00e-01', 'base_kernel': 'sp', 'height': 2.0}   2087.48±5001.27       5452.53±12389.15       4343.69±12599.47                   39.79\n",
      "{'alpha': '2.00e-01', 'base_kernel': 'sp', 'height': 3.0}   676.52±834.45         1698.59±1948.51        1783.36±2133.86                    52.12\n",
      "{'alpha': '2.00e-01', 'base_kernel': 'sp', 'height': 4.0}   2766.45±8367.13       6991.50±21983.27       5034.32±13513.49                   64.38\n",
      "{'alpha': '2.00e-01', 'base_kernel': 'sp', 'height': 5.0}   11392.47±40527.42     26808.27±96896.63      34824.45±150399.43                 79.44\n",
      "{'alpha': '2.00e-01', 'base_kernel': 'sp', 'height': 6.0}   1260.68±1247.14       3187.49±3321.68        3223.18±3846.98                    91.5\n",
      "{'alpha': '2.00e-01', 'base_kernel': 'sp', 'height': 7.0}   3285.77±8714.53       7824.52±21337.93       9355.77±26538.69                  103.37\n",
      "{'alpha': '2.00e-01', 'base_kernel': 'sp', 'height': 8.0}   71420.63±381144.56    228140.64±1225336.89   224226.44±1196214.95              116.12\n",
      "{'alpha': '2.00e-01', 'base_kernel': 'sp', 'height': 9.0}   1903.23±2699.02       6180.65±8548.05        4524.93±5802.60                   129.01\n",
      "{'alpha': '2.00e-01', 'base_kernel': 'sp', 'height': 10.0}  1580.34±1531.54       4301.87±3935.30        4276.73±5016.39                   142.76\n",
      "{'alpha': '2.51e-01', 'base_kernel': 'sp', 'height': 0.0}   401.28±551.55         1074.26±1357.91        1222.40±1836.76                    13.25\n",
      "{'alpha': '2.51e-01', 'base_kernel': 'sp', 'height': 1.0}   786.57±1749.17        4063.58±15466.70       1710.58±3986.79                    26.25\n",
      "{'alpha': '2.51e-01', 'base_kernel': 'sp', 'height': 2.0}   743.06±921.48         2122.22±2961.46        1735.42±2927.44                    39.79\n",
      "{'alpha': '2.51e-01', 'base_kernel': 'sp', 'height': 3.0}   455.09±459.54         1235.28±1321.72        1317.90±1498.39                    52.12\n",
      "{'alpha': '2.51e-01', 'base_kernel': 'sp', 'height': 4.0}   3692.45±13938.33      9522.33±35805.14       9930.95±41966.12                   64.38\n",
      "{'alpha': '2.51e-01', 'base_kernel': 'sp', 'height': 5.0}   1754.93±3148.56       4777.58±8581.38        5257.31±11185.79                   79.44\n",
      "{'alpha': '2.51e-01', 'base_kernel': 'sp', 'height': 6.0}   1214.51±1398.61       2778.92±2496.59        3000.85±3559.93                    91.5\n",
      "{'alpha': '2.51e-01', 'base_kernel': 'sp', 'height': 7.0}   5157.46±19346.98      13889.96±57369.88      10732.12±33959.35                 103.37\n",
      "{'alpha': '2.51e-01', 'base_kernel': 'sp', 'height': 8.0}   2609.55±5660.76       7020.31±17624.58       7594.56±15875.30                  116.12\n",
      "{'alpha': '2.51e-01', 'base_kernel': 'sp', 'height': 9.0}   2063.15±3955.45       7484.87±17049.49       4831.87±8613.82                   129.01\n",
      "{'alpha': '2.51e-01', 'base_kernel': 'sp', 'height': 10.0}  1280.19±1230.03       3533.78±3206.22        3480.61±4002.11                   142.76\n",
      "{'alpha': '3.16e-01', 'base_kernel': 'sp', 'height': 0.0}   378.76±555.83         1023.31±1600.95        1126.33±1701.85                    13.25\n",
      "{'alpha': '3.16e-01', 'base_kernel': 'sp', 'height': 1.0}   2475.25±10482.86      5477.28±15819.43       4944.52±20510.60                   26.25\n",
      "{'alpha': '3.16e-01', 'base_kernel': 'sp', 'height': 2.0}   751.11±771.76         2054.06±2419.31        1795.60±2507.90                    39.79\n",
      "{'alpha': '3.16e-01', 'base_kernel': 'sp', 'height': 3.0}   368.00±315.85         1003.89±968.71         1098.56±1132.48                    52.12\n",
      "{'alpha': '3.16e-01', 'base_kernel': 'sp', 'height': 4.0}   957.58±1151.50        2780.80±4252.06        2066.49±2722.42                    64.38\n",
      "{'alpha': '3.16e-01', 'base_kernel': 'sp', 'height': 5.0}   1061.65±1427.32       2947.49±4678.79        2782.41±3951.64                    79.44\n",
      "{'alpha': '3.16e-01', 'base_kernel': 'sp', 'height': 6.0}   1978.17±4768.70       3699.81±7455.57        4112.44±8217.01                    91.5\n",
      "{'alpha': '3.16e-01', 'base_kernel': 'sp', 'height': 7.0}   1973.55±5484.54       5234.82±15804.86       4708.13±11198.72                  103.37\n",
      "{'alpha': '3.16e-01', 'base_kernel': 'sp', 'height': 8.0}   3363.14±8745.17       8611.23±25070.58       7569.05±16587.39                  116.12\n",
      "{'alpha': '3.16e-01', 'base_kernel': 'sp', 'height': 9.0}   1153.35±1450.27       3658.42±4645.51        2783.43±3397.71                   129.01\n",
      "{'alpha': '3.16e-01', 'base_kernel': 'sp', 'height': 10.0}  1050.51±1010.76       2930.57±2704.96        2854.07±3214.79                   142.76\n",
      "{'alpha': '3.98e-01', 'base_kernel': 'sp', 'height': 0.0}   275.58±242.80         694.98±854.81          870.79±947.55                      13.25\n",
      "{'alpha': '3.98e-01', 'base_kernel': 'sp', 'height': 1.0}   804.89±2589.58        1578.37±3723.52        1510.52±3815.99                    26.25\n",
      "{'alpha': '3.98e-01', 'base_kernel': 'sp', 'height': 2.0}   995.86±2651.98        3059.54±7733.15        3278.93±11066.34                   39.79\n",
      "{'alpha': '3.98e-01', 'base_kernel': 'sp', 'height': 3.0}   1377.25±5551.01       2591.96±9189.62        4589.48±19134.09                   52.12\n",
      "{'alpha': '3.98e-01', 'base_kernel': 'sp', 'height': 4.0}   521.19±559.18         1340.78±1326.65        1151.23±1218.05                    64.38\n",
      "{'alpha': '3.98e-01', 'base_kernel': 'sp', 'height': 5.0}   975.87±1951.32        2346.85±3715.26        2590.07±5122.07                    79.44\n",
      "{'alpha': '3.98e-01', 'base_kernel': 'sp', 'height': 6.0}   1178.06±2068.18       2354.25±3263.94        2665.16±4075.85                    91.5\n",
      "{'alpha': '3.98e-01', 'base_kernel': 'sp', 'height': 7.0}   1107.44±1994.18       2943.63±5462.83        2835.50±5166.80                   103.37\n",
      "{'alpha': '3.98e-01', 'base_kernel': 'sp', 'height': 8.0}   1607.54±2843.13       4337.88±8910.01        4984.27±9024.38                   116.12\n",
      "{'alpha': '3.98e-01', 'base_kernel': 'sp', 'height': 9.0}   884.36±995.74         2821.99±3353.17        2237.22±2527.26                   129.01\n",
      "{'alpha': '3.98e-01', 'base_kernel': 'sp', 'height': 10.0}  923.09±886.50         2647.56±2560.28        2522.59±2691.83                   142.76\n",
      "{'alpha': '5.01e-01', 'base_kernel': 'sp', 'height': 0.0}   228.58±212.42         528.85±396.79          724.90±824.41                      13.25\n",
      "{'alpha': '5.01e-01', 'base_kernel': 'sp', 'height': 1.0}   278.11±313.42         852.43±1191.77         625.82±668.67                      26.25\n",
      "{'alpha': '5.01e-01', 'base_kernel': 'sp', 'height': 2.0}   825.79±1319.94        3366.72±7097.38        2779.87±6170.34                    39.79\n",
      "{'alpha': '5.01e-01', 'base_kernel': 'sp', 'height': 3.0}   837.27±2750.02        2212.01±7619.98        2647.12±9278.17                    52.12\n",
      "{'alpha': '5.01e-01', 'base_kernel': 'sp', 'height': 4.0}   508.25±475.56         1291.61±1184.71        1170.82±1130.50                    64.38\n",
      "{'alpha': '5.01e-01', 'base_kernel': 'sp', 'height': 5.0}   651.10±692.95         1822.69±2416.04        1619.55±1566.94                    79.44\n",
      "{'alpha': '5.01e-01', 'base_kernel': 'sp', 'height': 6.0}   1454.95±4411.46       2706.75±6804.71        2798.44±5952.56                    91.5\n",
      "{'alpha': '5.01e-01', 'base_kernel': 'sp', 'height': 7.0}   798.70±1493.42        2184.30±4594.16        2061.02±3558.94                   103.37\n",
      "{'alpha': '5.01e-01', 'base_kernel': 'sp', 'height': 8.0}   1210.21±2464.67       2909.98±6211.39        3104.43±5488.84                   116.12\n",
      "{'alpha': '5.01e-01', 'base_kernel': 'sp', 'height': 9.0}   738.96±747.92         2381.85±2555.59        1802.01±1942.08                   129.01\n",
      "{'alpha': '5.01e-01', 'base_kernel': 'sp', 'height': 10.0}  882.14±1209.41        2587.12±4144.76        2243.90±2851.77                   142.76\n",
      "{'alpha': '6.31e-01', 'base_kernel': 'sp', 'height': 0.0}   171.34±121.82         412.56±321.12          510.62±400.92                      13.25\n",
      "{'alpha': '6.31e-01', 'base_kernel': 'sp', 'height': 1.0}   344.76±479.07         959.71±1415.03         699.51±728.27                      26.25\n",
      "{'alpha': '6.31e-01', 'base_kernel': 'sp', 'height': 2.0}   436.60±554.63         1437.93±2353.49        1356.78±2652.49                    39.79\n",
      "{'alpha': '6.31e-01', 'base_kernel': 'sp', 'height': 3.0}   293.62±243.54         851.22±935.67          856.78±885.31                      52.12\n",
      "{'alpha': '6.31e-01', 'base_kernel': 'sp', 'height': 4.0}   568.28±1146.87        1382.18±2741.51        1167.30±1975.91                    64.38\n",
      "{'alpha': '6.31e-01', 'base_kernel': 'sp', 'height': 5.0}   608.96±816.93         1390.46±1236.51        1423.62±1484.30                    79.44\n",
      "{'alpha': '6.31e-01', 'base_kernel': 'sp', 'height': 6.0}   957.60±1096.55        1936.60±1861.27        2404.79±2913.43                    91.5\n",
      "{'alpha': '6.31e-01', 'base_kernel': 'sp', 'height': 7.0}   703.76±1319.68        1960.75±4325.08        1774.14±2866.72                   103.37\n",
      "{'alpha': '6.31e-01', 'base_kernel': 'sp', 'height': 8.0}   850.36±1364.27        2608.20±6411.59        2310.74±3752.09                   116.12\n",
      "{'alpha': '6.31e-01', 'base_kernel': 'sp', 'height': 9.0}   559.80±549.07         1769.53±1823.78        1405.03±1501.48                   129.01\n",
      "{'alpha': '6.31e-01', 'base_kernel': 'sp', 'height': 10.0}  653.89±729.10         1870.07±2360.89        1674.93±1935.89                   142.76\n",
      "{'alpha': '7.94e-01', 'base_kernel': 'sp', 'height': 0.0}   172.53±191.94         479.84±750.45          564.91±736.81                      13.25\n",
      "{'alpha': '7.94e-01', 'base_kernel': 'sp', 'height': 1.0}   4165.18±15118.91      10454.60±40480.81      9184.73±36041.84                   26.25\n",
      "{'alpha': '7.94e-01', 'base_kernel': 'sp', 'height': 2.0}   409.22±482.30         1211.77±1415.81        1008.60±1614.57                    39.79\n",
      "{'alpha': '7.94e-01', 'base_kernel': 'sp', 'height': 3.0}   263.50±239.66         719.59±684.34          718.15±697.62                      52.12\n",
      "{'alpha': '7.94e-01', 'base_kernel': 'sp', 'height': 4.0}   519.54±724.84         1176.37±1284.97        1217.81±1650.90                    64.38\n",
      "{'alpha': '7.94e-01', 'base_kernel': 'sp', 'height': 5.0}   526.88±792.23         1516.67±2700.48        1414.25±2274.82                    79.44\n",
      "{'alpha': '7.94e-01', 'base_kernel': 'sp', 'height': 6.0}   595.38±737.37         1388.87±1559.55        1571.58±2075.53                    91.5\n",
      "{'alpha': '7.94e-01', 'base_kernel': 'sp', 'height': 7.0}   550.27±814.84         1468.74±1991.86        1318.78±1654.08                   103.37\n",
      "{'alpha': '7.94e-01', 'base_kernel': 'sp', 'height': 8.0}   971.09±2000.96        2252.21±4162.18        2297.08±3565.60                   116.12\n",
      "{'alpha': '7.94e-01', 'base_kernel': 'sp', 'height': 9.0}   575.20±582.60         1776.09±1806.91        1348.24±1333.22                   129.01\n",
      "{'alpha': '7.94e-01', 'base_kernel': 'sp', 'height': 10.0}  514.05±400.30         1389.84±1081.17        1365.91±1305.43                   142.76\n",
      "{'alpha': '1.00e+00', 'base_kernel': 'sp', 'height': 0.0}   313.16±1027.13        1194.78±4732.55        1335.90±5057.96                    13.25\n",
      "{'alpha': '1.00e+00', 'base_kernel': 'sp', 'height': 1.0}   146.91±87.68          423.68±306.58          359.56±254.83                      26.25\n",
      "{'alpha': '1.00e+00', 'base_kernel': 'sp', 'height': 2.0}   397.32±579.51         1504.03±3202.65        853.80±1207.73                     39.79\n",
      "{'alpha': '1.00e+00', 'base_kernel': 'sp', 'height': 3.0}   233.27±337.69         611.06±824.46          694.81±1045.53                     52.12\n",
      "{'alpha': '1.00e+00', 'base_kernel': 'sp', 'height': 4.0}   413.31±724.29         904.27±1430.04         899.51±1278.97                     64.38\n",
      "{'alpha': '1.00e+00', 'base_kernel': 'sp', 'height': 5.0}   404.15±512.47         1173.24±1461.10        999.04±1214.87                     79.44\n",
      "{'alpha': '1.00e+00', 'base_kernel': 'sp', 'height': 6.0}   10178.23±49845.32     17050.42±82306.41      21545.71±104210.20                 91.5\n",
      "{'alpha': '1.00e+00', 'base_kernel': 'sp', 'height': 7.0}   439.31±481.84         1187.98±1456.07        1077.96±1102.43                   103.37\n",
      "{'alpha': '1.00e+00', 'base_kernel': 'sp', 'height': 8.0}   557.17±686.54         1360.44±1724.16        1764.80±2757.79                   116.12\n",
      "{'alpha': '1.00e+00', 'base_kernel': 'sp', 'height': 9.0}   487.38±587.53         1450.71±1733.51        1193.33±1366.25                   129.01\n",
      "{'alpha': '1.00e+00', 'base_kernel': 'sp', 'height': 10.0}  578.58±665.47         1430.03±1373.97        1652.52±2404.96                   142.76\n",
      "{'alpha': '1.26e+00', 'base_kernel': 'sp', 'height': 0.0}   115.80±142.08         316.05±426.36          312.55±291.13                      13.25\n",
      "{'alpha': '1.26e+00', 'base_kernel': 'sp', 'height': 1.0}   261.99±586.53         708.50±1360.62         642.57±1469.16                     26.25\n",
      "{'alpha': '1.26e+00', 'base_kernel': 'sp', 'height': 2.0}   410.80±1096.22        1252.51±3603.69        767.98±1615.51                     39.79\n",
      "{'alpha': '1.26e+00', 'base_kernel': 'sp', 'height': 3.0}   175.96±137.65         453.90±442.06          516.49±457.84                      52.12\n",
      "{'alpha': '1.26e+00', 'base_kernel': 'sp', 'height': 4.0}   286.79±492.92         679.84±889.89          681.03±1108.27                     64.38\n",
      "{'alpha': '1.26e+00', 'base_kernel': 'sp', 'height': 5.0}   4940.06±25374.82      29209.38±155949.19     29379.75±156911.70                 79.44\n",
      "{'alpha': '1.26e+00', 'base_kernel': 'sp', 'height': 6.0}   388.67±446.70         932.14±1156.17         984.49±1099.88                     91.5\n",
      "{'alpha': '1.26e+00', 'base_kernel': 'sp', 'height': 7.0}   330.59±285.59         855.55±766.79          866.81±738.97                     103.37\n",
      "{'alpha': '1.26e+00', 'base_kernel': 'sp', 'height': 8.0}   463.48±498.55         1062.10±1143.48        1491.70±2247.83                   116.12\n",
      "{'alpha': '1.26e+00', 'base_kernel': 'sp', 'height': 9.0}   527.66±963.72         1398.08±2065.03        1124.32±1356.33                   129.01\n",
      "{'alpha': '1.26e+00', 'base_kernel': 'sp', 'height': 10.0}  549.31±766.58         1483.15±2662.34        1414.78±2543.72                   142.76\n",
      "{'alpha': '1.58e+00', 'base_kernel': 'sp', 'height': 0.0}   101.29±105.17         222.84±136.67          304.77±327.87                      13.25\n",
      "{'alpha': '1.58e+00', 'base_kernel': 'sp', 'height': 1.0}   132.58±136.61         368.01±329.84          363.26±510.95                      26.25\n",
      "{'alpha': '1.58e+00', 'base_kernel': 'sp', 'height': 2.0}   263.15±356.73         728.88±849.57          650.41±1094.24                     39.79\n",
      "{'alpha': '1.58e+00', 'base_kernel': 'sp', 'height': 3.0}   189.44±179.49         565.26±751.93          666.38±883.03                      52.12\n",
      "{'alpha': '1.58e+00', 'base_kernel': 'sp', 'height': 4.0}   243.65±343.37         555.44±569.30          616.19±968.13                      64.38\n",
      "{'alpha': '1.58e+00', 'base_kernel': 'sp', 'height': 5.0}   280.58±411.24         740.05±887.62          742.31±923.07                      79.44\n",
      "{'alpha': '1.58e+00', 'base_kernel': 'sp', 'height': 6.0}   358.92±580.34         1192.99±3178.66        923.14±1274.35                     91.5\n",
      "{'alpha': '1.58e+00', 'base_kernel': 'sp', 'height': 7.0}   581.48±1685.57        1660.38±5064.65        1177.61±2276.05                   103.37\n",
      "{'alpha': '1.58e+00', 'base_kernel': 'sp', 'height': 8.0}   588.85±1516.93        1186.02±2056.83        2189.04±6045.15                   116.12\n",
      "{'alpha': '1.58e+00', 'base_kernel': 'sp', 'height': 9.0}   340.37±296.05         953.18±703.55          870.74±827.91                     129.01\n",
      "{'alpha': '1.58e+00', 'base_kernel': 'sp', 'height': 10.0}  393.93±508.78         1175.08±1840.76        949.81±1045.93                    142.76\n",
      "{'alpha': '2.00e+00', 'base_kernel': 'sp', 'height': 0.0}   82.18±85.16           192.93±148.82          268.46±443.72                      13.25\n",
      "{'alpha': '2.00e+00', 'base_kernel': 'sp', 'height': 1.0}   206.26±358.79         610.55±1026.92         525.28±1196.95                     26.25\n",
      "{'alpha': '2.00e+00', 'base_kernel': 'sp', 'height': 2.0}   252.28±659.67         856.23±2475.25         544.08±1399.20                     39.79\n",
      "{'alpha': '2.00e+00', 'base_kernel': 'sp', 'height': 3.0}   219.02±316.64         548.68±715.50          829.26±1867.39                     52.12\n",
      "{'alpha': '2.00e+00', 'base_kernel': 'sp', 'height': 4.0}   552.28±2174.31        1106.39±3821.30        1431.52±5848.64                    64.38\n",
      "{'alpha': '2.00e+00', 'base_kernel': 'sp', 'height': 5.0}   396.62±1220.71        1944.65±7950.58        1496.46±5415.17                    79.44\n",
      "{'alpha': '2.00e+00', 'base_kernel': 'sp', 'height': 6.0}   210.91±143.24         528.43±366.88          616.07±616.92                      91.5\n",
      "{'alpha': '2.00e+00', 'base_kernel': 'sp', 'height': 7.0}   255.69±158.81         637.67±437.23          748.84±681.84                     103.37\n",
      "{'alpha': '2.00e+00', 'base_kernel': 'sp', 'height': 8.0}   449.03±992.84         1298.26±3237.24        2287.11±8474.64                   116.12\n",
      "{'alpha': '2.00e+00', 'base_kernel': 'sp', 'height': 9.0}   370.83±512.01         942.76±877.80          957.55±1443.97                    129.01\n",
      "{'alpha': '2.00e+00', 'base_kernel': 'sp', 'height': 10.0}  276.02±190.90         730.36±504.35          685.34±565.17                     142.76\n",
      "{'alpha': '2.51e+00', 'base_kernel': 'sp', 'height': 0.0}   60.66±69.56           159.65±249.39          158.56±189.06                      13.25\n",
      "{'alpha': '2.51e+00', 'base_kernel': 'sp', 'height': 1.0}   89.37±66.89           248.67±245.08          209.53±190.11                      26.25\n",
      "{'alpha': '2.51e+00', 'base_kernel': 'sp', 'height': 2.0}   149.06±227.83         457.05±737.33          328.97±529.72                      39.79\n",
      "{'alpha': '2.51e+00', 'base_kernel': 'sp', 'height': 3.0}   198.54±281.62         592.82±942.47          677.67±1116.40                     52.12\n",
      "{'alpha': '2.51e+00', 'base_kernel': 'sp', 'height': 4.0}   144.68±107.98         400.86±326.76          345.16±263.09                      64.38\n",
      "{'alpha': '2.51e+00', 'base_kernel': 'sp', 'height': 5.0}   214.80±300.35         572.89±797.00          734.57±1347.83                     79.44\n",
      "{'alpha': '2.51e+00', 'base_kernel': 'sp', 'height': 6.0}   377.36±588.85         771.73±910.77          1074.25±1643.66                    91.5\n",
      "{'alpha': '2.51e+00', 'base_kernel': 'sp', 'height': 7.0}   540.84±1424.94        1593.60±4133.64        1602.14±4130.62                   103.37\n",
      "{'alpha': '2.51e+00', 'base_kernel': 'sp', 'height': 8.0}   431.32±899.82         1745.71±5617.21        1289.64±2184.99                   116.12\n",
      "{'alpha': '2.51e+00', 'base_kernel': 'sp', 'height': 9.0}   477.79±829.83         1348.11±2152.20        1189.19±1817.65                   129.01\n",
      "{'alpha': '2.51e+00', 'base_kernel': 'sp', 'height': 10.0}  1847.52±8802.93       3593.44±16241.98       2425.17±9855.65                   142.76\n",
      "{'alpha': '3.16e+00', 'base_kernel': 'sp', 'height': 0.0}   62.88±72.72           178.51±235.00          193.17±338.99                      13.25\n",
      "{'alpha': '3.16e+00', 'base_kernel': 'sp', 'height': 1.0}   67.62±60.19           180.59±164.36          175.16±232.81                      26.25\n",
      "{'alpha': '3.16e+00', 'base_kernel': 'sp', 'height': 2.0}   209.46±566.22         572.08±1394.43         617.18±2030.38                     39.79\n",
      "{'alpha': '3.16e+00', 'base_kernel': 'sp', 'height': 3.0}   290.00±952.86         1149.72±4715.08        949.83±2923.23                     52.12\n",
      "{'alpha': '3.16e+00', 'base_kernel': 'sp', 'height': 4.0}   355.90±1207.42        615.93±1287.54         860.16±2928.02                     64.38\n",
      "{'alpha': '3.16e+00', 'base_kernel': 'sp', 'height': 5.0}   502.74±1767.21        1719.42±6588.93        2185.76±9234.25                    79.44\n",
      "{'alpha': '3.16e+00', 'base_kernel': 'sp', 'height': 6.0}   454.85±848.72         1040.30±1325.28        1382.82±2697.86                    91.5\n",
      "{'alpha': '3.16e+00', 'base_kernel': 'sp', 'height': 7.0}   7351.65±38531.25      21237.36±111591.78     16151.87±83041.16                 103.37\n",
      "{'alpha': '3.16e+00', 'base_kernel': 'sp', 'height': 8.0}   1496.99±6927.86       3169.09±13850.64       3761.52±16615.76                  116.12\n",
      "{'alpha': '3.16e+00', 'base_kernel': 'sp', 'height': 9.0}   247.74±282.05         758.30±1009.60         601.89±565.05                     129.01\n",
      "{'alpha': '3.16e+00', 'base_kernel': 'sp', 'height': 10.0}  291.72±345.44         871.92±1248.06         827.45±1220.86                    142.76\n",
      "{'alpha': '3.98e+00', 'base_kernel': 'sp', 'height': 0.0}   37.14±17.31           77.65±36.91            80.58±64.66                        13.25\n",
      "{'alpha': '3.98e+00', 'base_kernel': 'sp', 'height': 1.0}   52.82±27.07           141.48±85.95           129.16±148.44                      26.25\n",
      "{'alpha': '3.98e+00', 'base_kernel': 'sp', 'height': 2.0}   95.57±176.82          350.39±863.65          193.30±298.35                      39.79\n",
      "{'alpha': '3.98e+00', 'base_kernel': 'sp', 'height': 3.0}   80.10±38.77           223.56±160.92          236.68±142.92                      52.12\n",
      "{'alpha': '3.98e+00', 'base_kernel': 'sp', 'height': 4.0}   235.63±566.69         567.39±1201.09         877.31±2704.85                     64.38\n",
      "{'alpha': '3.98e+00', 'base_kernel': 'sp', 'height': 5.0}   134.60±113.24         406.24±430.90          415.14±495.27                      79.44\n",
      "{'alpha': '3.98e+00', 'base_kernel': 'sp', 'height': 6.0}   341.09±561.21         926.04±1417.76         979.60±1522.69                     91.5\n",
      "{'alpha': '3.98e+00', 'base_kernel': 'sp', 'height': 7.0}   622.53±1947.73        1659.66±5242.71        1519.89±3512.40                   103.37\n",
      "{'alpha': '3.98e+00', 'base_kernel': 'sp', 'height': 8.0}   269.69±411.99         675.14±824.06          895.73±1945.44                    116.12\n",
      "{'alpha': '3.98e+00', 'base_kernel': 'sp', 'height': 9.0}   250.37±471.20         584.43±542.18          568.28±832.90                     129.01\n",
      "{'alpha': '3.98e+00', 'base_kernel': 'sp', 'height': 10.0}  240.65±253.58         663.29±725.49          575.20±547.90                     142.76\n",
      "{'alpha': '5.01e+00', 'base_kernel': 'sp', 'height': 0.0}   78.57±210.55          211.71±570.24          232.69±829.55                      13.25\n",
      "{'alpha': '5.01e+00', 'base_kernel': 'sp', 'height': 1.0}   44.53±19.56           117.12±84.14           107.52±88.38                       26.25\n",
      "{'alpha': '5.01e+00', 'base_kernel': 'sp', 'height': 2.0}   157.29±482.24         625.13±2269.89         328.50±1015.40                     39.79\n",
      "{'alpha': '5.01e+00', 'base_kernel': 'sp', 'height': 3.0}   88.24±118.30          198.03±151.46          306.13±600.72                      52.12\n",
      "{'alpha': '5.01e+00', 'base_kernel': 'sp', 'height': 4.0}   254.67±797.93         948.47±3560.27         547.50±1241.96                     64.38\n",
      "{'alpha': '5.01e+00', 'base_kernel': 'sp', 'height': 5.0}   235.43±684.26         541.52±1415.03         681.29±2160.21                     79.44\n",
      "{'alpha': '5.01e+00', 'base_kernel': 'sp', 'height': 6.0}   258.58±527.10         675.87±1120.47         800.92±1570.03                     91.5\n",
      "{'alpha': '5.01e+00', 'base_kernel': 'sp', 'height': 7.0}   155.16±120.26         407.88±298.25          456.22±383.52                     103.37\n",
      "{'alpha': '5.01e+00', 'base_kernel': 'sp', 'height': 8.0}   206.73±316.53         434.77±486.68          656.11±1142.99                    116.12\n",
      "{'alpha': '5.01e+00', 'base_kernel': 'sp', 'height': 9.0}   177.39±191.56         553.77±609.05          535.66±1037.54                    129.01\n",
      "{'alpha': '5.01e+00', 'base_kernel': 'sp', 'height': 10.0}  167.24±139.02         457.57±426.91          467.86±494.62                     142.76\n",
      "{'alpha': '6.31e+00', 'base_kernel': 'sp', 'height': 0.0}   53.64±129.99          323.52±1483.77         103.18±293.36                      13.25\n",
      "{'alpha': '6.31e+00', 'base_kernel': 'sp', 'height': 1.0}   63.23±82.89           236.27±460.73          114.63±97.62                       26.25\n",
      "{'alpha': '6.31e+00', 'base_kernel': 'sp', 'height': 2.0}   71.91±78.70           226.69±271.04          150.04±156.33                      39.79\n",
      "{'alpha': '6.31e+00', 'base_kernel': 'sp', 'height': 3.0}   299.28±1210.64        576.75±2079.23         1156.72±4974.04                    52.12\n",
      "{'alpha': '6.31e+00', 'base_kernel': 'sp', 'height': 4.0}   322.15±971.44         1081.00±3311.33        603.82±1431.22                     64.38\n",
      "{'alpha': '6.31e+00', 'base_kernel': 'sp', 'height': 5.0}   104.20±73.96          319.58±297.05          257.07±170.52                      79.44\n",
      "{'alpha': '6.31e+00', 'base_kernel': 'sp', 'height': 6.0}   311.99±623.55         979.18±2316.44         1146.52±2638.34                    91.5\n",
      "{'alpha': '6.31e+00', 'base_kernel': 'sp', 'height': 7.0}   126.50±102.07         335.88±232.42          366.88±364.94                     103.37\n",
      "{'alpha': '6.31e+00', 'base_kernel': 'sp', 'height': 8.0}   115.91±55.68          293.19±150.16          368.98±261.37                     116.12\n",
      "{'alpha': '6.31e+00', 'base_kernel': 'sp', 'height': 9.0}   200.61±271.02         593.92±867.03          526.98±864.58                     129.01\n",
      "{'alpha': '6.31e+00', 'base_kernel': 'sp', 'height': 10.0}  176.73±295.53         476.23±712.28          548.79±1296.83                    142.76\n",
      "{'alpha': '7.94e+00', 'base_kernel': 'sp', 'height': 0.0}   28.69±1.09            45.94±5.53             44.04±6.03                         13.25\n",
      "{'alpha': '7.94e+00', 'base_kernel': 'sp', 'height': 1.0}   33.45±7.70            71.38±31.07            66.23±49.90                        26.25\n",
      "{'alpha': '7.94e+00', 'base_kernel': 'sp', 'height': 2.0}   43.50±18.41           115.93±75.13           91.06±53.30                        39.79\n",
      "{'alpha': '7.94e+00', 'base_kernel': 'sp', 'height': 3.0}   54.25±29.02           136.95±70.85           160.70±147.80                      52.12\n",
      "{'alpha': '7.94e+00', 'base_kernel': 'sp', 'height': 4.0}   75.45±55.48           202.39±142.62          210.75±254.35                      64.38\n",
      "{'alpha': '7.94e+00', 'base_kernel': 'sp', 'height': 5.0}   100.23±91.63          316.37±450.58          276.45±267.15                      79.44\n",
      "{'alpha': '7.94e+00', 'base_kernel': 'sp', 'height': 6.0}   152.62±170.96         363.17±361.95          508.83±631.51                      91.5\n",
      "{'alpha': '7.94e+00', 'base_kernel': 'sp', 'height': 7.0}   148.42±227.02         501.18±1227.73         379.72±427.84                     103.37\n",
      "{'alpha': '7.94e+00', 'base_kernel': 'sp', 'height': 8.0}   364.11±1351.93        1071.36±4405.97        727.38±1868.73                    116.12\n",
      "{'alpha': '7.94e+00', 'base_kernel': 'sp', 'height': 9.0}   157.27±191.02         608.72±1359.55         397.54±482.89                     129.01\n",
      "{'alpha': '7.94e+00', 'base_kernel': 'sp', 'height': 10.0}  159.21±291.95         380.87±419.23          416.37±636.28                     142.76\n",
      "{'alpha': '1.00e+01', 'base_kernel': 'sp', 'height': 0.0}   28.20±0.71            42.43±2.31             41.26±5.17                         13.25\n",
      "{'alpha': '1.00e+01', 'base_kernel': 'sp', 'height': 1.0}   30.44±1.91            57.35±12.58            51.51±11.90                        26.25\n",
      "{'alpha': '1.00e+01', 'base_kernel': 'sp', 'height': 2.0}   60.93±102.00          181.18±420.19          181.20±456.02                      39.79\n",
      "{'alpha': '1.00e+01', 'base_kernel': 'sp', 'height': 3.0}   123.08±347.61         321.00±1044.12         285.66±624.22                      52.12\n",
      "{'alpha': '1.00e+01', 'base_kernel': 'sp', 'height': 4.0}   137.91±321.36         404.50±830.23          394.43±1232.55                     64.38\n",
      "{'alpha': '1.00e+01', 'base_kernel': 'sp', 'height': 5.0}   105.08±159.05         225.72±195.95          323.31±572.33                      79.44\n",
      "{'alpha': '1.00e+01', 'base_kernel': 'sp', 'height': 6.0}   86.52±41.99           236.26±166.44          267.77±162.53                      91.5\n",
      "{'alpha': '1.00e+01', 'base_kernel': 'sp', 'height': 7.0}   120.03±114.73         362.36±424.83          349.10±433.82                     103.37\n",
      "{'alpha': '1.00e+01', 'base_kernel': 'sp', 'height': 8.0}   152.92±234.95         391.20±620.26          509.08±976.63                     116.12\n",
      "{'alpha': '1.00e+01', 'base_kernel': 'sp', 'height': 9.0}   153.03±230.19         426.80±550.86          364.67±518.27                     129.01\n",
      "{'alpha': '1.00e+01', 'base_kernel': 'sp', 'height': 10.0}  107.77±95.05          342.81±422.94          304.25±329.30                     142.76\n",
      "{'alpha': '1.26e+01', 'base_kernel': 'sp', 'height': 0.0}   27.95±0.60            40.31±1.52             39.41±4.90                         13.25\n",
      "{'alpha': '1.26e+01', 'base_kernel': 'sp', 'height': 1.0}   29.43±1.84            51.28±10.24            46.44±6.93                         26.25\n",
      "{'alpha': '1.26e+01', 'base_kernel': 'sp', 'height': 2.0}   31.61±3.44            63.43±14.82            60.12±20.85                        39.79\n",
      "{'alpha': '1.26e+01', 'base_kernel': 'sp', 'height': 3.0}   60.94±113.69          167.50±378.67          170.70±411.22                      52.12\n",
      "{'alpha': '1.26e+01', 'base_kernel': 'sp', 'height': 4.0}   61.57±96.04           190.80±466.61          138.18±190.08                      64.38\n",
      "{'alpha': '1.26e+01', 'base_kernel': 'sp', 'height': 5.0}   74.13±93.13           176.84±183.20          198.88±311.89                      79.44\n",
      "{'alpha': '1.26e+01', 'base_kernel': 'sp', 'height': 6.0}   72.48±45.37           166.21±87.94           237.52±238.07                      91.5\n",
      "{'alpha': '1.26e+01', 'base_kernel': 'sp', 'height': 7.0}   206.45±562.39         913.51±3315.49         575.41±1282.68                    103.37\n",
      "{'alpha': '1.26e+01', 'base_kernel': 'sp', 'height': 8.0}   216.95±641.80         624.98±2016.20         711.21±2255.48                    116.12\n",
      "{'alpha': '1.26e+01', 'base_kernel': 'sp', 'height': 9.0}   87.27±56.06           290.68±293.16          204.39±124.69                     129.01\n",
      "{'alpha': '1.26e+01', 'base_kernel': 'sp', 'height': 10.0}  136.53±281.21         507.41±1508.84         328.13±628.50                     142.76\n",
      "{'alpha': '1.58e+01', 'base_kernel': 'sp', 'height': 0.0}   27.85±0.54            38.78±1.18             38.02±4.90                         13.25\n",
      "{'alpha': '1.58e+01', 'base_kernel': 'sp', 'height': 1.0}   28.50±1.09            45.14±2.88             43.01±4.86                         26.25\n",
      "{'alpha': '1.58e+01', 'base_kernel': 'sp', 'height': 2.0}   30.98±7.34            59.86±38.29            55.06±17.57                        39.79\n",
      "{'alpha': '1.58e+01', 'base_kernel': 'sp', 'height': 3.0}   41.08±25.77           93.44±94.36            104.43±131.55                      52.12\n",
      "{'alpha': '1.58e+01', 'base_kernel': 'sp', 'height': 4.0}   55.83±65.16           203.93±508.77          151.93±260.27                      64.38\n",
      "{'alpha': '1.58e+01', 'base_kernel': 'sp', 'height': 5.0}   43.16±19.01           105.97±75.54           100.59±75.24                       79.44\n",
      "{'alpha': '1.58e+01', 'base_kernel': 'sp', 'height': 6.0}   68.72±73.07           183.61±231.20          192.09±205.52                      91.5\n",
      "{'alpha': '1.58e+01', 'base_kernel': 'sp', 'height': 7.0}   93.36±146.60          231.62±422.95          327.68±662.23                     103.37\n",
      "{'alpha': '1.58e+01', 'base_kernel': 'sp', 'height': 8.0}   76.91±78.82           163.99±98.55           270.13±421.43                     116.12\n",
      "{'alpha': '1.58e+01', 'base_kernel': 'sp', 'height': 9.0}   85.42±85.15           294.52±498.28          212.57±198.81                     129.01\n",
      "{'alpha': '1.58e+01', 'base_kernel': 'sp', 'height': 10.0}  116.98±248.15         306.60±500.65          440.61±1412.19                    142.76\n",
      "{'alpha': '2.00e+01', 'base_kernel': 'sp', 'height': 0.0}   27.89±0.51            37.66±1.00             36.96±5.06                         13.25\n",
      "{'alpha': '2.00e+01', 'base_kernel': 'sp', 'height': 1.0}   28.09±0.94            42.25±1.73             40.95±4.27                         26.25\n",
      "{'alpha': '2.00e+01', 'base_kernel': 'sp', 'height': 2.0}   28.72±1.40            47.28±4.82             47.96±8.01                         39.79\n",
      "{'alpha': '2.00e+01', 'base_kernel': 'sp', 'height': 3.0}   34.17±9.39            67.25±34.37            74.33±62.51                        52.12\n",
      "{'alpha': '2.00e+01', 'base_kernel': 'sp', 'height': 4.0}   46.28±60.79           125.88±313.09          94.99±149.78                       64.38\n",
      "{'alpha': '2.00e+01', 'base_kernel': 'sp', 'height': 5.0}   44.46±32.72           116.55±152.75          100.50±122.67                      79.44\n",
      "{'alpha': '2.00e+01', 'base_kernel': 'sp', 'height': 6.0}   69.12±104.19          204.42±330.98          170.65±204.70                      91.5\n",
      "{'alpha': '2.00e+01', 'base_kernel': 'sp', 'height': 7.0}   58.27±60.50           128.02±87.38           173.15±284.61                     103.37\n",
      "{'alpha': '2.00e+01', 'base_kernel': 'sp', 'height': 8.0}   81.93±145.79          163.82±153.51          281.76±700.83                     116.12\n",
      "{'alpha': '2.00e+01', 'base_kernel': 'sp', 'height': 9.0}   94.06±166.74          284.39±675.16          236.87±400.97                     129.01\n",
      "{'alpha': '2.00e+01', 'base_kernel': 'sp', 'height': 10.0}  79.15±112.94          270.08±554.56          168.71±219.55                     142.76\n",
      "{'alpha': '2.51e+01', 'base_kernel': 'sp', 'height': 0.0}   28.09±0.49            36.87±0.89             36.18±5.34                         13.25\n",
      "{'alpha': '2.51e+01', 'base_kernel': 'sp', 'height': 1.0}   27.86±0.82            40.27±1.39             39.44±4.26                         26.25\n",
      "{'alpha': '2.51e+01', 'base_kernel': 'sp', 'height': 2.0}   28.14±1.12            43.53±2.58             45.09±6.53                         39.79\n",
      "{'alpha': '2.51e+01', 'base_kernel': 'sp', 'height': 3.0}   29.63±1.43            49.35±4.14             49.44±13.95                        52.12\n",
      "{'alpha': '2.51e+01', 'base_kernel': 'sp', 'height': 4.0}   33.73±10.75           66.34±33.31            68.97±69.06                        64.38\n",
      "{'alpha': '2.51e+01', 'base_kernel': 'sp', 'height': 5.0}   35.14±11.19           76.80±57.42            71.70±57.99                        79.44\n",
      "{'alpha': '2.51e+01', 'base_kernel': 'sp', 'height': 6.0}   39.26±16.89           87.93±44.23            93.39±73.35                        91.5\n",
      "{'alpha': '2.51e+01', 'base_kernel': 'sp', 'height': 7.0}   42.39±24.94           111.28±134.72          94.89±74.40                       103.37\n",
      "{'alpha': '2.51e+01', 'base_kernel': 'sp', 'height': 8.0}   76.19±130.05          239.15±566.75          225.14±439.25                     116.12\n",
      "{'alpha': '2.51e+01', 'base_kernel': 'sp', 'height': 9.0}   59.63±55.32           166.25±210.07          163.55±205.37                     129.01\n",
      "{'alpha': '2.51e+01', 'base_kernel': 'sp', 'height': 10.0}  85.71±198.31          350.56±1128.48         152.67±206.21                     142.76\n",
      "{'alpha': '3.16e+01', 'base_kernel': 'sp', 'height': 0.0}   28.45±0.49            36.37±0.82             35.66±5.67                         13.25\n",
      "{'alpha': '3.16e+01', 'base_kernel': 'sp', 'height': 1.0}   27.76±0.72            38.78±1.18             38.33±4.48                         26.25\n",
      "{'alpha': '3.16e+01', 'base_kernel': 'sp', 'height': 2.0}   27.80±0.95            41.18±1.98             42.98±5.62                         39.79\n",
      "{'alpha': '3.16e+01', 'base_kernel': 'sp', 'height': 3.0}   28.76±0.89            44.71±2.01             43.29±6.27                         52.12\n",
      "{'alpha': '3.16e+01', 'base_kernel': 'sp', 'height': 4.0}   33.66±24.09           73.14±131.32           55.03±43.51                        64.38\n",
      "{'alpha': '3.16e+01', 'base_kernel': 'sp', 'height': 5.0}   33.56±13.11           72.33±68.57            57.67±29.57                        79.44\n",
      "{'alpha': '3.16e+01', 'base_kernel': 'sp', 'height': 6.0}   31.89±4.21            65.68±23.23            65.57±25.15                        91.5\n",
      "{'alpha': '3.16e+01', 'base_kernel': 'sp', 'height': 7.0}   39.16±25.57           102.74±147.59          80.81±62.30                       103.37\n",
      "{'alpha': '3.16e+01', 'base_kernel': 'sp', 'height': 8.0}   40.46±18.01           92.18±62.45            97.37±92.33                       116.12\n",
      "{'alpha': '3.16e+01', 'base_kernel': 'sp', 'height': 9.0}   39.62±14.63           88.90±42.27            100.88±80.51                      129.01\n",
      "{'alpha': '3.16e+01', 'base_kernel': 'sp', 'height': 10.0}  53.41±46.02           184.77±286.81          102.14±71.44                      142.76\n",
      "{'alpha': '3.98e+01', 'base_kernel': 'sp', 'height': 0.0}   29.01±0.49            36.17±0.78             35.41±6.02                         13.25\n",
      "{'alpha': '3.98e+01', 'base_kernel': 'sp', 'height': 1.0}   27.79±0.65            37.65±1.02             37.52±4.74                         26.25\n",
      "{'alpha': '3.98e+01', 'base_kernel': 'sp', 'height': 2.0}   27.62±0.84            39.43±1.63             41.32±5.17                         39.79\n",
      "{'alpha': '3.98e+01', 'base_kernel': 'sp', 'height': 3.0}   28.35±0.77            42.17±1.48             40.36±5.19                         52.12\n",
      "{'alpha': '3.98e+01', 'base_kernel': 'sp', 'height': 4.0}   28.81±1.80            45.49±4.04             44.54±11.91                        64.38\n",
      "{'alpha': '3.98e+01', 'base_kernel': 'sp', 'height': 5.0}   29.25±1.20            48.79±4.98             46.20±9.34                         79.44\n",
      "{'alpha': '3.98e+01', 'base_kernel': 'sp', 'height': 6.0}   30.42±3.58            59.35±21.28            58.62±15.75                        91.5\n",
      "{'alpha': '3.98e+01', 'base_kernel': 'sp', 'height': 7.0}   33.55±16.90           76.02±102.68           61.01±49.14                       103.37\n",
      "{'alpha': '3.98e+01', 'base_kernel': 'sp', 'height': 8.0}   33.94±8.19            68.81±28.50            74.71±54.91                       116.12\n",
      "{'alpha': '3.98e+01', 'base_kernel': 'sp', 'height': 9.0}   37.29±17.26           76.10±28.16            94.40±120.63                      129.01\n",
      "{'alpha': '3.98e+01', 'base_kernel': 'sp', 'height': 10.0}  37.06±21.20           74.59±34.49            90.76±119.74                      142.76\n",
      "{'alpha': '5.01e+01', 'base_kernel': 'sp', 'height': 0.0}   29.89±0.71            36.41±0.99             35.55±6.45                         13.25\n",
      "{'alpha': '5.01e+01', 'base_kernel': 'sp', 'height': 1.0}   27.98±0.59            36.84±0.90             36.99±4.99                         26.25\n",
      "{'alpha': '5.01e+01', 'base_kernel': 'sp', 'height': 2.0}   27.57±0.76            38.10±1.39             40.01±5.06                         39.79\n",
      "{'alpha': '5.01e+01', 'base_kernel': 'sp', 'height': 3.0}   28.11±0.68            40.31±1.15             38.36±4.85                         52.12\n",
      "{'alpha': '5.01e+01', 'base_kernel': 'sp', 'height': 4.0}   28.16±0.95            42.18±1.66             40.60±6.32                         64.38\n",
      "{'alpha': '5.01e+01', 'base_kernel': 'sp', 'height': 5.0}   28.58±0.98            44.34±2.32             42.82±7.47                         79.44\n",
      "{'alpha': '5.01e+01', 'base_kernel': 'sp', 'height': 6.0}   28.41±1.16            46.42±3.22             49.37±8.40                         91.5\n",
      "{'alpha': '5.01e+01', 'base_kernel': 'sp', 'height': 7.0}   29.38±2.13            50.52±10.65            48.54±11.72                       103.37\n",
      "{'alpha': '5.01e+01', 'base_kernel': 'sp', 'height': 8.0}   34.48±21.28           58.91±31.31            74.47±102.29                      116.12\n",
      "{'alpha': '5.01e+01', 'base_kernel': 'sp', 'height': 9.0}   39.64±38.29           73.46±60.57            111.30±231.17                     129.01\n",
      "{'alpha': '5.01e+01', 'base_kernel': 'sp', 'height': 10.0}  35.64±21.81           73.50±84.30            86.57±127.56                      142.76\n",
      "{'alpha': '6.31e+01', 'base_kernel': 'sp', 'height': 0.0}   70.25±108.86          64.95±65.14            72.95±115.94                       13.25\n",
      "{'alpha': '6.31e+01', 'base_kernel': 'sp', 'height': 1.0}   28.33±0.55            36.33±0.81             36.73±5.21                         26.25\n",
      "{'alpha': '6.31e+01', 'base_kernel': 'sp', 'height': 2.0}   27.66±0.70            37.10±1.21             39.02±5.15                         39.79\n",
      "{'alpha': '6.31e+01', 'base_kernel': 'sp', 'height': 3.0}   28.01±0.62            38.87±0.92             36.88±4.80                         52.12\n",
      "{'alpha': '6.31e+01', 'base_kernel': 'sp', 'height': 4.0}   27.93±0.86            40.26±1.44             38.72±5.99                         64.38\n",
      "{'alpha': '6.31e+01', 'base_kernel': 'sp', 'height': 5.0}   28.20±0.90            41.77±1.63             40.50±6.40                         79.44\n",
      "{'alpha': '6.31e+01', 'base_kernel': 'sp', 'height': 6.0}   27.86±0.96            42.67±1.91             46.15±7.14                         91.5\n",
      "{'alpha': '6.31e+01', 'base_kernel': 'sp', 'height': 7.0}   28.43±1.04            44.61±2.47             44.44±8.88                        103.37\n",
      "{'alpha': '6.31e+01', 'base_kernel': 'sp', 'height': 8.0}   29.33±1.83            47.62±7.63             48.61±11.63                       116.12\n",
      "{'alpha': '6.31e+01', 'base_kernel': 'sp', 'height': 9.0}   29.63±2.24            51.83±11.27            53.31±17.72                       129.01\n",
      "{'alpha': '6.31e+01', 'base_kernel': 'sp', 'height': 10.0}  30.27±4.31            53.46±17.47            54.80±26.98                       142.76\n",
      "{'alpha': '7.94e+01', 'base_kernel': 'sp', 'height': 0.0}   35.95±2.71            39.97±1.51             38.80±8.91                         13.25\n",
      "{'alpha': '7.94e+01', 'base_kernel': 'sp', 'height': 1.0}   28.88±0.52            36.10±0.74             36.72±5.40                         26.25\n",
      "{'alpha': '7.94e+01', 'base_kernel': 'sp', 'height': 2.0}   27.90±0.66            36.41±1.08             38.33±5.35                         39.79\n",
      "{'alpha': '7.94e+01', 'base_kernel': 'sp', 'height': 3.0}   28.04±0.58            37.77±0.77             35.78±4.92                         52.12\n",
      "{'alpha': '7.94e+01', 'base_kernel': 'sp', 'height': 4.0}   27.83±0.78            38.83±1.29             37.33±5.89                         64.38\n",
      "{'alpha': '7.94e+01', 'base_kernel': 'sp', 'height': 5.0}   27.99±0.83            39.92±1.25             38.71±5.76                         79.44\n",
      "{'alpha': '7.94e+01', 'base_kernel': 'sp', 'height': 6.0}   27.54±0.84            40.38±1.55             43.93±6.38                         91.5\n",
      "{'alpha': '7.94e+01', 'base_kernel': 'sp', 'height': 7.0}   28.05±0.92            41.93±1.85             42.06±7.45                        103.37\n",
      "{'alpha': '7.94e+01', 'base_kernel': 'sp', 'height': 8.0}   28.46±1.04            43.06±1.90             43.56±6.35                        116.12\n",
      "{'alpha': '7.94e+01', 'base_kernel': 'sp', 'height': 9.0}   28.46±1.34            45.96±6.41             46.21±8.71                        129.01\n",
      "{'alpha': '7.94e+01', 'base_kernel': 'sp', 'height': 10.0}  31.13±14.51           49.17±16.30            62.83±88.58                       142.76\n",
      "{'alpha': '1.00e+02', 'base_kernel': 'sp', 'height': 0.0}   35.48±0.55            39.76±0.63             38.31±7.83                         13.25\n",
      "{'alpha': '1.00e+02', 'base_kernel': 'sp', 'height': 1.0}   29.72±0.64            36.30±0.97             37.07±5.53                         26.25\n",
      "{'alpha': '1.00e+02', 'base_kernel': 'sp', 'height': 2.0}   28.32±0.63            35.99±0.98             37.92±5.60                         39.79\n",
      "{'alpha': '1.00e+02', 'base_kernel': 'sp', 'height': 3.0}   28.22±0.54            36.97±0.69             34.99±5.14                         52.12\n",
      "{'alpha': '1.00e+02', 'base_kernel': 'sp', 'height': 4.0}   27.87±0.72            37.75±1.16             36.27±5.89                         64.38\n",
      "{'alpha': '1.00e+02', 'base_kernel': 'sp', 'height': 5.0}   27.91±0.77            38.52±1.00             37.30±5.45                         79.44\n",
      "{'alpha': '1.00e+02', 'base_kernel': 'sp', 'height': 6.0}   27.38±0.75            38.70±1.34             42.26±5.96                         91.5\n",
      "{'alpha': '1.00e+02', 'base_kernel': 'sp', 'height': 7.0}   27.83±0.83            40.09±1.52             40.30±6.60                        103.37\n",
      "{'alpha': '1.00e+02', 'base_kernel': 'sp', 'height': 8.0}   28.09±0.85            40.81±1.51             41.06±5.16                        116.12\n",
      "{'alpha': '1.00e+02', 'base_kernel': 'sp', 'height': 9.0}   27.93±1.10            42.01±2.33             42.72±6.70                        129.01\n",
      "{'alpha': '1.00e+02', 'base_kernel': 'sp', 'height': 10.0}  28.15±1.42            42.94±3.37             45.42±11.43                       142.76\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "calculate performance: 100%|██████████| 13530/13530 [16:20<00:00, 14.10it/s]"
     ]
    }
   ],
   "source": [
    "%load_ext line_profiler\n",
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import sys\n",
    "sys.path.insert(0, \"../\")\n",
    "from pygraph.utils.model_selection_precomputed import model_selection_for_precomputed_kernel\n",
    "from pygraph.kernels.weisfeilerLehmanKernel import weisfeilerlehmankernel\n",
    "\n",
    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
    "estimator = weisfeilerlehmankernel\n",
    "param_grid_precomputed = {'height': np.linspace(0, 10, 11), 'base_kernel': ['sp']}\n",
    "param_grid = {'alpha': np.logspace(-2, 2, num = 41, base = 10)}\n",
    "\n",
    "model_selection_for_precomputed_kernel(datafile, estimator, param_grid_precomputed, param_grid, \n",
    "                                       'regression', NUM_TRIALS=30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- This is a regression problem ---\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when height = 0.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 0.3646550178527832 seconds ---\n",
      "[[  5.   6.   4. ...  20.  20.  20.]\n",
      " [  6.   8.   4. ...  20.  20.  20.]\n",
      " [  4.   4.   5. ...  21.  21.  21.]\n",
      " ...\n",
      " [ 20.  20.  21. ... 101. 101. 101.]\n",
      " [ 20.  20.  21. ... 101. 101. 101.]\n",
      " [ 20.  20.  21. ... 101. 101. 101.]]\n",
      "\n",
      " Starting calculate accuracy/rmse...\n",
      "calculate performance:  98%|█████████▊| 985/1000 [00:01<00:00, 664.77it/s]\n",
      " Mean performance on train set: 17.681582\n",
      "With standard deviation: 0.713183\n",
      "\n",
      " Mean performance on test set: 15.685879\n",
      "With standard deviation: 4.139197\n",
      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 681.36it/s]\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when height = 1.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 0.7535510063171387 seconds ---\n",
      "[[ 10.  10.   4. ...  20.  20.  20.]\n",
      " [ 10.  16.   4. ...  20.  20.  20.]\n",
      " [  4.   4.  10. ...  22.  22.  24.]\n",
      " ...\n",
      " [ 20.  20.  22. ... 130. 130. 122.]\n",
      " [ 20.  20.  22. ... 130. 130. 122.]\n",
      " [ 20.  20.  24. ... 122. 122. 154.]]\n",
      "\n",
      " Starting calculate accuracy/rmse...\n",
      "calculate performance:  94%|█████████▍| 945/1000 [00:01<00:00, 713.00it/s]\n",
      " Mean performance on train set: 6.270014\n",
      "With standard deviation: 0.654734\n",
      "\n",
      " Mean performance on test set: 7.550458\n",
      "With standard deviation: 2.331786\n",
      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 719.46it/s]\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when height = 2.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 1.3278343677520752 seconds ---\n",
      "[[ 15.  10.   4. ...  20.  20.  20.]\n",
      " [ 10.  24.   4. ...  20.  20.  20.]\n",
      " [  4.   4.  15. ...  22.  22.  26.]\n",
      " ...\n",
      " [ 20.  20.  22. ... 159. 151. 124.]\n",
      " [ 20.  20.  22. ... 151. 153. 124.]\n",
      " [ 20.  20.  26. ... 124. 124. 185.]]\n",
      "\n",
      " Starting calculate accuracy/rmse...\n",
      "calculate performance:  95%|█████████▍| 949/1000 [00:01<00:00, 736.38it/s]\n",
      " Mean performance on train set: 4.450682\n",
      "With standard deviation: 0.882129\n",
      "\n",
      " Mean performance on test set: 9.728466\n",
      "With standard deviation: 2.057669\n",
      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 709.22it/s]\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when height = 3.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 1.7653727531433105 seconds ---\n",
      "[[ 20.  10.   4. ...  20.  20.  20.]\n",
      " [ 10.  32.   4. ...  20.  20.  20.]\n",
      " [  4.   4.  20. ...  22.  22.  26.]\n",
      " ...\n",
      " [ 20.  20.  22. ... 188. 159. 124.]\n",
      " [ 20.  20.  22. ... 159. 168. 124.]\n",
      " [ 20.  20.  26. ... 124. 124. 202.]]\n",
      "\n",
      " Starting calculate accuracy/rmse...\n",
      "calculate performance:  96%|█████████▌| 959/1000 [00:01<00:00, 724.60it/s]\n",
      " Mean performance on train set: 2.270586\n",
      "With standard deviation: 0.481516\n",
      "\n",
      " Mean performance on test set: 11.296110\n",
      "With standard deviation: 2.799944\n",
      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 670.29it/s]\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when height = 4.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 2.2821996212005615 seconds ---\n",
      "[[ 25.  10.   4. ...  20.  20.  20.]\n",
      " [ 10.  40.   4. ...  20.  20.  20.]\n",
      " [  4.   4.  25. ...  22.  22.  26.]\n",
      " ...\n",
      " [ 20.  20.  22. ... 217. 159. 124.]\n",
      " [ 20.  20.  22. ... 159. 183. 124.]\n",
      " [ 20.  20.  26. ... 124. 124. 213.]]\n",
      "\n",
      " Starting calculate accuracy/rmse...\n",
      "calculate performance:  98%|█████████▊| 983/1000 [00:01<00:00, 709.28it/s]\n",
      " Mean performance on train set: 1.074035\n",
      "With standard deviation: 0.637823\n",
      "\n",
      " Mean performance on test set: 12.808303\n",
      "With standard deviation: 3.446939\n",
      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 646.12it/s]\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when height = 5.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 2.706934928894043 seconds ---\n",
      "[[ 30.  10.   4. ...  20.  20.  20.]\n",
      " [ 10.  48.   4. ...  20.  20.  20.]\n",
      " [  4.   4.  30. ...  22.  22.  26.]\n",
      " ...\n",
      " [ 20.  20.  22. ... 246. 159. 124.]\n",
      " [ 20.  20.  22. ... 159. 198. 124.]\n",
      " [ 20.  20.  26. ... 124. 124. 224.]]\n",
      "\n",
      " Starting calculate accuracy/rmse...\n",
      "calculate performance:  95%|█████████▌| 953/1000 [00:01<00:00, 553.49it/s]\n",
      " Mean performance on train set: 0.700602\n",
      "With standard deviation: 0.572640\n",
      "\n",
      " Mean performance on test set: 14.017923\n",
      "With standard deviation: 3.675042\n",
      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 621.01it/s]\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when height = 6.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 3.1140964031219482 seconds ---\n",
      "[[ 35.  10.   4. ...  20.  20.  20.]\n",
      " [ 10.  56.   4. ...  20.  20.  20.]\n",
      " [  4.   4.  35. ...  22.  22.  26.]\n",
      " ...\n",
      " [ 20.  20.  22. ... 275. 159. 124.]\n",
      " [ 20.  20.  22. ... 159. 213. 124.]\n",
      " [ 20.  20.  26. ... 124. 124. 235.]]\n",
      "\n",
      " Starting calculate accuracy/rmse...\n",
      "calculate performance: 100%|█████████▉| 997/1000 [00:01<00:00, 595.50it/s]\n",
      " Mean performance on train set: 0.691515\n",
      "With standard deviation: 0.564620\n",
      "\n",
      " Mean performance on test set: 14.918434\n",
      "With standard deviation: 3.805352\n",
      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 586.05it/s]\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when height = 7.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 3.5894455909729004 seconds ---\n",
      "[[ 40.  10.   4. ...  20.  20.  20.]\n",
      " [ 10.  64.   4. ...  20.  20.  20.]\n",
      " [  4.   4.  40. ...  22.  22.  26.]\n",
      " ...\n",
      " [ 20.  20.  22. ... 304. 159. 124.]\n",
      " [ 20.  20.  22. ... 159. 228. 124.]\n",
      " [ 20.  20.  26. ... 124. 124. 246.]]\n",
      "\n",
      " Starting calculate accuracy/rmse...\n",
      "calculate performance:  99%|█████████▉| 991/1000 [00:01<00:00, 663.55it/s]\n",
      " Mean performance on train set: 0.691516\n",
      "With standard deviation: 0.564620\n",
      "\n",
      " Mean performance on test set: 15.629476\n",
      "With standard deviation: 3.865387\n",
      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 627.59it/s]\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when height = 8.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 4.081295967102051 seconds ---\n",
      "[[ 45.  10.   4. ...  20.  20.  20.]\n",
      " [ 10.  72.   4. ...  20.  20.  20.]\n",
      " [  4.   4.  45. ...  22.  22.  26.]\n",
      " ...\n",
      " [ 20.  20.  22. ... 333. 159. 124.]\n",
      " [ 20.  20.  22. ... 159. 243. 124.]\n",
      " [ 20.  20.  26. ... 124. 124. 257.]]\n",
      "\n",
      " Starting calculate accuracy/rmse...\n",
      "calculate performance:  96%|█████████▌| 961/1000 [00:01<00:00, 601.33it/s]\n",
      " Mean performance on train set: 0.691515\n",
      "With standard deviation: 0.564620\n",
      "\n",
      " Mean performance on test set: 16.214369\n",
      "With standard deviation: 3.928756\n",
      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 603.90it/s]\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when height = 9.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 4.497286796569824 seconds ---\n",
      "[[ 50.  10.   4. ...  20.  20.  20.]\n",
      " [ 10.  80.   4. ...  20.  20.  20.]\n",
      " [  4.   4.  50. ...  22.  22.  26.]\n",
      " ...\n",
      " [ 20.  20.  22. ... 362. 159. 124.]\n",
      " [ 20.  20.  22. ... 159. 258. 124.]\n",
      " [ 20.  20.  26. ... 124. 124. 268.]]\n",
      "\n",
      " Starting calculate accuracy/rmse...\n",
      "calculate performance:  93%|█████████▎| 931/1000 [00:01<00:00, 511.55it/s]\n",
      " Mean performance on train set: 0.691515\n",
      "With standard deviation: 0.564620\n",
      "\n",
      " Mean performance on test set: 16.725744\n",
      "With standard deviation: 3.993095\n",
      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 550.66it/s]\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when height = 10.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- Weisfeiler-Lehman subtree kernel matrix of size 185 built in 4.984841585159302 seconds ---\n",
      "[[ 55.  10.   4. ...  20.  20.  20.]\n",
      " [ 10.  88.   4. ...  20.  20.  20.]\n",
      " [  4.   4.  55. ...  22.  22.  26.]\n",
      " ...\n",
      " [ 20.  20.  22. ... 391. 159. 124.]\n",
      " [ 20.  20.  22. ... 159. 273. 124.]\n",
      " [ 20.  20.  26. ... 124. 124. 279.]]\n",
      "\n",
      " Starting calculate accuracy/rmse...\n",
      "calculate performance:  94%|█████████▍| 942/1000 [00:01<00:00, 708.78it/s]\n",
      " Mean performance on train set: 0.691516\n",
      "With standard deviation: 0.564621\n",
      "\n",
      " Mean performance on test set: 17.186401\n",
      "With standard deviation: 4.056724\n",
      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 711.43it/s]\n",
      "\n",
      "\n",
      "  height    rmse_test    std_test    rmse_train    std_train    k_time\n",
      "--------  -----------  ----------  ------------  -----------  --------\n",
      "       0     15.6859      4.1392      17.6816       0.713183  0.364655\n",
      "       1      7.55046     2.33179      6.27001      0.654734  0.753551\n",
      "       2      9.72847     2.05767      4.45068      0.882129  1.32783\n",
      "       3     11.2961      2.79994      2.27059      0.481516  1.76537\n",
      "       4     12.8083      3.44694      1.07403      0.637823  2.2822\n",
      "       5     14.0179      3.67504      0.700602     0.57264   2.70693\n",
      "       6     14.9184      3.80535      0.691515     0.56462   3.1141\n",
      "       7     15.6295      3.86539      0.691516     0.56462   3.58945\n",
      "       8     16.2144      3.92876      0.691515     0.56462   4.0813\n",
      "       9     16.7257      3.9931       0.691515     0.56462   4.49729\n",
      "      10     17.1864      4.05672      0.691516     0.564621  4.98484\n"
     ]
    }
   ],
   "source": [
    "# wl subtree kernel\n",
    "%load_ext line_profiler\n",
    "\n",
    "import numpy as np\n",
    "import sys\n",
    "sys.path.insert(0, \"../\")\n",
    "from pygraph.utils.utils import kernel_train_test\n",
    "from pygraph.kernels.weisfeilerLehmanKernel import weisfeilerlehmankernel, _wl_subtreekernel_do\n",
    "\n",
    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
    "kernel_file_path = 'kernelmatrices_weisfeilerlehman_subtree_acyclic/'\n",
    "\n",
    "kernel_para = dict(node_label = 'atom', edge_label = 'bond_type')\n",
    "\n",
    "kernel_train_test(datafile, kernel_file_path, weisfeilerlehmankernel, kernel_para, \\\n",
    "    hyper_name = 'height', hyper_range = np.linspace(0, 10, 11), normalize = False)\n",
    "\n",
    "# %lprun -f _wl_subtreekernel_do \\\n",
    "#     kernel_train_test(datafile, kernel_file_path, weisfeilerlehmankernel, kernel_para, \\\n",
    "#     hyper_name = 'height', hyper_range = np.linspace(0, 10, 11), normalize = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- This is a regression problem ---\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when height = 0.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- Weisfeiler-Lehman sp kernel matrix of size 185 built in 13.473959922790527 seconds ---\n",
      "\n",
      " Starting calculate accuracy/rmse...\n",
      "calculate performance:  99%|█████████▊| 986/1000 [00:01<00:00, 802.19it/s]\n",
      " Mean performance on train set: 28.360361\n",
      "With standard deviation: 1.357183\n",
      "\n",
      " Mean performance on test set: 35.191954\n",
      "With standard deviation: 4.495767\n",
      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 805.00it/s]\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when height = 1.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- Weisfeiler-Lehman sp kernel matrix of size 185 built in 27.61470603942871 seconds ---\n",
      "\n",
      " Starting calculate accuracy/rmse...\n",
      "calculate performance:  96%|█████████▌| 959/1000 [00:01<00:00, 734.53it/s]\n",
      " Mean performance on train set: 27.933534\n",
      "With standard deviation: 1.448359\n",
      "\n",
      " Mean performance on test set: 35.180815\n",
      "With standard deviation: 4.500453\n",
      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 724.44it/s]\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when height = 2.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- Weisfeiler-Lehman sp kernel matrix of size 185 built in 41.05776810646057 seconds ---\n",
      "\n",
      " Starting calculate accuracy/rmse...\n",
      "calculate performance:  94%|█████████▎| 935/1000 [00:01<00:00, 740.19it/s]\n",
      " Mean performance on train set: 28.111311\n",
      "With standard deviation: 1.508915\n",
      "\n",
      " Mean performance on test set: 35.163150\n",
      "With standard deviation: 4.502054\n",
      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 717.12it/s]\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when height = 3.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- Weisfeiler-Lehman sp kernel matrix of size 185 built in 54.166242837905884 seconds ---\n",
      "\n",
      " Starting calculate accuracy/rmse...\n",
      "calculate performance:  93%|█████████▎| 932/1000 [00:01<00:00, 781.12it/s]\n",
      " Mean performance on train set: 28.390274\n",
      "With standard deviation: 1.365711\n",
      "\n",
      " Mean performance on test set: 35.194634\n",
      "With standard deviation: 4.498007\n",
      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 773.40it/s]\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when height = 4.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- Weisfeiler-Lehman sp kernel matrix of size 185 built in 70.05019497871399 seconds ---\n",
      "\n",
      " Starting calculate accuracy/rmse...\n",
      "calculate performance:  97%|█████████▋| 970/1000 [00:01<00:00, 880.10it/s]\n",
      " Mean performance on train set: 27.974611\n",
      "With standard deviation: 1.462223\n",
      "\n",
      " Mean performance on test set: 35.175314\n",
      "With standard deviation: 4.501113\n",
      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 874.69it/s]\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when height = 5.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- Weisfeiler-Lehman sp kernel matrix of size 185 built in 79.92547488212585 seconds ---\n",
      "\n",
      " Starting calculate accuracy/rmse...\n",
      "calculate performance: 100%|█████████▉| 996/1000 [00:01<00:00, 884.85it/s]\n",
      " Mean performance on train set: 28.018415\n",
      "With standard deviation: 1.455644\n",
      "\n",
      " Mean performance on test set: 35.199713\n",
      "With standard deviation: 4.507104\n",
      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 897.03it/s]\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when height = 6.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-2-e7b9d5ef03e3>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     13\u001b[0m \u001b[0mkernel_para\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnode_label\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'atom'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0medge_label\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'bond_type'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbase_kernel\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'sp'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     14\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 15\u001b[0;31m \u001b[0mkernel_train_test\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdatafile\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkernel_file_path\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mweisfeilerlehmankernel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkernel_para\u001b[0m\u001b[0;34m,\u001b[0m     \u001b[0mhyper_name\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'height'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhyper_range\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlinspace\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m10\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m11\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnormalize\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     16\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     17\u001b[0m \u001b[0;31m# %lprun -f _wl_subtreekernel_do \\\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/media/ljia/DATA/research-repo/codes/Linlin/py-graph/pygraph/utils/utils.py\u001b[0m in \u001b[0;36mkernel_train_test\u001b[0;34m(datafile, kernel_file_path, kernel_func, kernel_para, trials, splits, alpha_grid, C_grid, hyper_name, hyper_range, normalize, datafile_y, model_type)\u001b[0m\n\u001b[1;32m    159\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mhyper_name\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;34m''\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    160\u001b[0m                 \u001b[0mkernel_para\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mhyper_name\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mhyper_para\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 161\u001b[0;31m             \u001b[0mKmatrix\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrun_time\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkernel_func\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdataset\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkernel_para\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    162\u001b[0m             \u001b[0mkernel_time_list\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrun_time\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    163\u001b[0m             \u001b[0;32mimport\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpyplot\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/media/ljia/DATA/research-repo/codes/Linlin/py-graph/pygraph/kernels/weisfeilerLehmanKernel.py\u001b[0m in \u001b[0;36mweisfeilerlehmankernel\u001b[0;34m(node_label, edge_label, height, base_kernel, *args)\u001b[0m\n\u001b[1;32m     56\u001b[0m     \u001b[0;31m# for WL shortest path kernel\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     57\u001b[0m     \u001b[0;32melif\u001b[0m \u001b[0mbase_kernel\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'sp'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 58\u001b[0;31m         \u001b[0mKmatrix\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_wl_spkernel_do\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnode_label\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0medge_label\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheight\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     59\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     60\u001b[0m     \u001b[0;31m# for WL edge kernel\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/media/ljia/DATA/research-repo/codes/Linlin/py-graph/pygraph/kernels/weisfeilerLehmanKernel.py\u001b[0m in \u001b[0;36m_wl_spkernel_do\u001b[0;34m(Gn, node_label, edge_label, height)\u001b[0m\n\u001b[1;32m    254\u001b[0m                 \u001b[0;32mfor\u001b[0m \u001b[0me1\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mGn\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0medges\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    255\u001b[0m                     \u001b[0;32mfor\u001b[0m \u001b[0me2\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mGn\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mj\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0medges\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 256\u001b[0;31m                         \u001b[0;32mif\u001b[0m \u001b[0me1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'cost'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;36m0\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0me1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'cost'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0me2\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'cost'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0me1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0me2\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0me1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0me2\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0me1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0me2\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0me1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0me2\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    257\u001b[0m                             \u001b[0mKmatrix\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mj\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    258\u001b[0m                 \u001b[0mKmatrix\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mj\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mKmatrix\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mj\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "# WL sp kernel\n",
    "%load_ext line_profiler\n",
    "\n",
    "import numpy as np\n",
    "import sys\n",
    "sys.path.insert(0, \"../\")\n",
    "from pygraph.utils.utils import kernel_train_test\n",
    "from pygraph.kernels.weisfeilerLehmanKernel import weisfeilerlehmankernel, _wl_subtreekernel_do\n",
    "\n",
    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
    "kernel_file_path = 'kernelmatrices_weisfeilerlehman_subtree_acyclic/'\n",
    "\n",
    "kernel_para = dict(node_label = 'atom', edge_label = 'bond_type', base_kernel = 'sp')\n",
    "\n",
    "kernel_train_test(datafile, kernel_file_path, weisfeilerlehmankernel, kernel_para, \\\n",
    "    hyper_name = 'height', hyper_range = np.linspace(0, 10, 11), normalize = False)\n",
    "\n",
    "# %lprun -f _wl_subtreekernel_do \\\n",
    "#     kernel_train_test(datafile, kernel_file_path, weisfeilerlehmankernel, kernel_para, \\\n",
    "#     hyper_name = 'height', hyper_range = np.linspace(0, 10, 11), normalize = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The line_profiler extension is already loaded. To reload it, use:\n",
      "  %reload_ext line_profiler\n",
      "\n",
      " --- This is a regression problem ---\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when height = 0.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- Weisfeiler-Lehman edge kernel matrix of size 185 built in 0.8530018329620361 seconds ---\n",
      "[[ 2.  1.  2. ...  0.  0.  1.]\n",
      " [ 1.  3.  1. ...  0.  0.  2.]\n",
      " [ 2.  1.  2. ...  0.  0.  1.]\n",
      " ...\n",
      " [ 0.  0.  0. ... 10.  7.  0.]\n",
      " [ 0.  0.  0. ...  7. 10.  1.]\n",
      " [ 1.  2.  1. ...  0.  1. 10.]]\n",
      "\n",
      " Starting calculate accuracy/rmse...\n",
      "calculate performance:  95%|█████████▍| 947/1000 [00:01<00:00, 719.29it/s]\n",
      " Mean performance on train set: 29.997498\n",
      "With standard deviation: 0.902340\n",
      "\n",
      " Mean performance on test set: 33.407740\n",
      "With standard deviation: 4.732717\n",
      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 653.54it/s]\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when height = 1.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- Weisfeiler-Lehman edge kernel matrix of size 185 built in 1.717505931854248 seconds ---\n",
      "[[ 4.  2.  4. ...  0.  0.  2.]\n",
      " [ 2.  6.  2. ...  0.  0.  4.]\n",
      " [ 4.  2.  4. ...  0.  0.  2.]\n",
      " ...\n",
      " [ 0.  0.  0. ... 20. 14.  0.]\n",
      " [ 0.  0.  0. ... 14. 20.  2.]\n",
      " [ 2.  4.  2. ...  0.  2. 20.]]\n",
      "\n",
      " Starting calculate accuracy/rmse...\n",
      "calculate performance:  96%|█████████▌| 956/1000 [00:01<00:00, 721.27it/s]\n",
      " Mean performance on train set: 30.160338\n",
      "With standard deviation: 1.094235\n",
      "\n",
      " Mean performance on test set: 33.423458\n",
      "With standard deviation: 4.721311\n",
      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 723.53it/s]\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when height = 2.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- Weisfeiler-Lehman edge kernel matrix of size 185 built in 2.6603214740753174 seconds ---\n",
      "[[ 6.  3.  6. ...  0.  0.  3.]\n",
      " [ 3.  9.  3. ...  0.  0.  6.]\n",
      " [ 6.  3.  6. ...  0.  0.  3.]\n",
      " ...\n",
      " [ 0.  0.  0. ... 30. 21.  0.]\n",
      " [ 0.  0.  0. ... 21. 30.  3.]\n",
      " [ 3.  6.  3. ...  0.  3. 30.]]\n",
      "\n",
      " Starting calculate accuracy/rmse...\n",
      "calculate performance:  94%|█████████▍| 944/1000 [00:01<00:00, 650.98it/s]\n",
      " Mean performance on train set: 29.928570\n",
      "With standard deviation: 0.787941\n",
      "\n",
      " Mean performance on test set: 33.433014\n",
      "With standard deviation: 4.724408\n",
      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 688.71it/s]\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when height = 3.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- Weisfeiler-Lehman edge kernel matrix of size 185 built in 3.477631092071533 seconds ---\n",
      "[[ 8.  4.  8. ...  0.  0.  4.]\n",
      " [ 4. 12.  4. ...  0.  0.  8.]\n",
      " [ 8.  4.  8. ...  0.  0.  4.]\n",
      " ...\n",
      " [ 0.  0.  0. ... 40. 28.  0.]\n",
      " [ 0.  0.  0. ... 28. 40.  4.]\n",
      " [ 4.  8.  4. ...  0.  4. 40.]]\n",
      "\n",
      " Starting calculate accuracy/rmse...\n",
      "calculate performance:  95%|█████████▌| 954/1000 [00:01<00:00, 725.15it/s]\n",
      " Mean performance on train set: 30.011409\n",
      "With standard deviation: 0.909674\n",
      "\n",
      " Mean performance on test set: 33.407319\n",
      "With standard deviation: 4.732434\n",
      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 720.71it/s]\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when height = 4.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- Weisfeiler-Lehman edge kernel matrix of size 185 built in 4.5436692237854 seconds ---\n",
      "[[10.  5. 10. ...  0.  0.  5.]\n",
      " [ 5. 15.  5. ...  0.  0. 10.]\n",
      " [10.  5. 10. ...  0.  0.  5.]\n",
      " ...\n",
      " [ 0.  0.  0. ... 50. 35.  0.]\n",
      " [ 0.  0.  0. ... 35. 50.  5.]\n",
      " [ 5. 10.  5. ...  0.  5. 50.]]\n",
      "\n",
      " Starting calculate accuracy/rmse...\n",
      "calculate performance:  94%|█████████▎| 936/1000 [00:01<00:00, 568.04it/s]\n",
      " Mean performance on train set: 30.184162\n",
      "With standard deviation: 1.108902\n",
      "\n",
      " Mean performance on test set: 33.425625\n",
      "With standard deviation: 4.721660\n",
      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 564.24it/s]\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when height = 5.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- Weisfeiler-Lehman edge kernel matrix of size 185 built in 5.6617820262908936 seconds ---\n",
      "[[12.  6. 12. ...  0.  0.  6.]\n",
      " [ 6. 18.  6. ...  0.  0. 12.]\n",
      " [12.  6. 12. ...  0.  0.  6.]\n",
      " ...\n",
      " [ 0.  0.  0. ... 60. 42.  0.]\n",
      " [ 0.  0.  0. ... 42. 60.  6.]\n",
      " [ 6. 12.  6. ...  0.  6. 60.]]\n",
      "\n",
      " Starting calculate accuracy/rmse...\n",
      "calculate performance:  99%|█████████▉| 993/1000 [00:01<00:00, 519.25it/s]\n",
      " Mean performance on train set: 30.041068\n",
      "With standard deviation: 1.018451\n",
      "\n",
      " Mean performance on test set: 33.406717\n",
      "With standard deviation: 4.726409\n",
      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 548.91it/s]\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when height = 6.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- Weisfeiler-Lehman edge kernel matrix of size 185 built in 6.148027420043945 seconds ---\n",
      "[[14.  7. 14. ...  0.  0.  7.]\n",
      " [ 7. 21.  7. ...  0.  0. 14.]\n",
      " [14.  7. 14. ...  0.  0.  7.]\n",
      " ...\n",
      " [ 0.  0.  0. ... 70. 49.  0.]\n",
      " [ 0.  0.  0. ... 49. 70.  7.]\n",
      " [ 7. 14.  7. ...  0.  7. 70.]]\n",
      "\n",
      " Starting calculate accuracy/rmse...\n",
      "calculate performance:  98%|█████████▊| 985/1000 [00:01<00:00, 498.31it/s]\n",
      " Mean performance on train set: 29.905596\n",
      "With standard deviation: 0.782179\n",
      "\n",
      " Mean performance on test set: 33.418992\n",
      "With standard deviation: 4.730753\n",
      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 534.86it/s]\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when height = 7.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- Weisfeiler-Lehman edge kernel matrix of size 185 built in 7.603543519973755 seconds ---\n",
      "[[16.  8. 16. ...  0.  0.  8.]\n",
      " [ 8. 24.  8. ...  0.  0. 16.]\n",
      " [16.  8. 16. ...  0.  0.  8.]\n",
      " ...\n",
      " [ 0.  0.  0. ... 80. 56.  0.]\n",
      " [ 0.  0.  0. ... 56. 80.  8.]\n",
      " [ 8. 16.  8. ...  0.  8. 80.]]\n",
      "\n",
      " Starting calculate accuracy/rmse...\n",
      "calculate performance:  95%|█████████▌| 953/1000 [00:01<00:00, 586.15it/s]\n",
      " Mean performance on train set: 30.175921\n",
      "With standard deviation: 1.103820\n",
      "\n",
      " Mean performance on test set: 33.424820\n",
      "With standard deviation: 4.721550\n",
      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 546.00it/s]\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when height = 8.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- Weisfeiler-Lehman edge kernel matrix of size 185 built in 7.972221612930298 seconds ---\n",
      "[[18.  9. 18. ...  0.  0.  9.]\n",
      " [ 9. 27.  9. ...  0.  0. 18.]\n",
      " [18.  9. 18. ...  0.  0.  9.]\n",
      " ...\n",
      " [ 0.  0.  0. ... 90. 63.  0.]\n",
      " [ 0.  0.  0. ... 63. 90.  9.]\n",
      " [ 9. 18.  9. ...  0.  9. 90.]]\n",
      "\n",
      " Starting calculate accuracy/rmse...\n",
      "calculate performance:  98%|█████████▊| 980/1000 [00:01<00:00, 490.30it/s]\n",
      " Mean performance on train set: 30.136537\n",
      "With standard deviation: 1.074854\n",
      "\n",
      " Mean performance on test set: 33.412196\n",
      "With standard deviation: 4.715539\n",
      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 536.66it/s]\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when height = 9.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- Weisfeiler-Lehman edge kernel matrix of size 185 built in 9.070842504501343 seconds ---\n",
      "[[ 20.  10.  20. ...   0.   0.  10.]\n",
      " [ 10.  30.  10. ...   0.   0.  20.]\n",
      " [ 20.  10.  20. ...   0.   0.  10.]\n",
      " ...\n",
      " [  0.   0.   0. ... 100.  70.   0.]\n",
      " [  0.   0.   0. ...  70. 100.  10.]\n",
      " [ 10.  20.  10. ...   0.  10. 100.]]\n",
      "\n",
      " Starting calculate accuracy/rmse...\n",
      "calculate performance:  98%|█████████▊| 975/1000 [00:01<00:00, 527.13it/s]\n",
      " Mean performance on train set: 30.032887\n",
      "With standard deviation: 0.921065\n",
      "\n",
      " Mean performance on test set: 33.407050\n",
      "With standard deviation: 4.731928\n",
      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 600.62it/s]\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when height = 10.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- Weisfeiler-Lehman edge kernel matrix of size 185 built in 10.02536916732788 seconds ---\n",
      "[[ 22.  11.  22. ...   0.   0.  11.]\n",
      " [ 11.  33.  11. ...   0.   0.  22.]\n",
      " [ 22.  11.  22. ...   0.   0.  11.]\n",
      " ...\n",
      " [  0.   0.   0. ... 110.  77.   0.]\n",
      " [  0.   0.   0. ...  77. 110.  11.]\n",
      " [ 11.  22.  11. ...   0.  11. 110.]]\n",
      "\n",
      " Starting calculate accuracy/rmse...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "calculate performance:  97%|█████████▋| 970/1000 [00:01<00:00, 694.38it/s]\n",
      " Mean performance on train set: 29.924232\n",
      "With standard deviation: 0.790843\n",
      "\n",
      " Mean performance on test set: 33.416469\n",
      "With standard deviation: 4.731694\n",
      "calculate performance: 100%|██████████| 1000/1000 [00:01<00:00, 678.72it/s]\n",
      "\n",
      "\n",
      "  height    rmse_test    std_test    rmse_train    std_train     k_time\n",
      "--------  -----------  ----------  ------------  -----------  ---------\n",
      "       0      33.4077     4.73272       29.9975     0.90234    0.853002\n",
      "       1      33.4235     4.72131       30.1603     1.09423    1.71751\n",
      "       2      33.433      4.72441       29.9286     0.787941   2.66032\n",
      "       3      33.4073     4.73243       30.0114     0.909674   3.47763\n",
      "       4      33.4256     4.72166       30.1842     1.1089     4.54367\n",
      "       5      33.4067     4.72641       30.0411     1.01845    5.66178\n",
      "       6      33.419      4.73075       29.9056     0.782179   6.14803\n",
      "       7      33.4248     4.72155       30.1759     1.10382    7.60354\n",
      "       8      33.4122     4.71554       30.1365     1.07485    7.97222\n",
      "       9      33.4071     4.73193       30.0329     0.921065   9.07084\n",
      "      10      33.4165     4.73169       29.9242     0.790843  10.0254\n"
     ]
    }
   ],
   "source": [
    "# WL edge kernel\n",
    "%load_ext line_profiler\n",
    "\n",
    "import numpy as np\n",
    "import sys\n",
    "sys.path.insert(0, \"../\")\n",
    "from pygraph.utils.utils import kernel_train_test\n",
    "from pygraph.kernels.weisfeilerLehmanKernel import weisfeilerlehmankernel, _wl_subtreekernel_do\n",
    "\n",
    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
    "kernel_file_path = 'kernelmatrices_weisfeilerlehman_subtree_acyclic/'\n",
    "\n",
    "kernel_para = dict(node_label = 'atom', edge_label = 'bond_type', base_kernel = 'edge')\n",
    "\n",
    "kernel_train_test(datafile, kernel_file_path, weisfeilerlehmankernel, kernel_para, \\\n",
    "    hyper_name = 'height', hyper_range = np.linspace(0, 10, 11), normalize = False)\n",
    "\n",
    "# %lprun -f _wl_subtreekernel_do \\\n",
    "#     kernel_train_test(datafile, kernel_file_path, weisfeilerlehmankernel, kernel_para, \\\n",
    "#     hyper_name = 'height', hyper_range = np.linspace(0, 10, 11), normalize = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "ename": "IndentationError",
     "evalue": "unindent does not match any outer indentation level (<tokenize>, line 16)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;36m  File \u001b[0;32m\"<tokenize>\"\u001b[0;36m, line \u001b[0;32m16\u001b[0m\n\u001b[0;31m    10     34.0963      6.93115      11.4257     11.2624    4.94888\u001b[0m\n\u001b[0m    ^\u001b[0m\n\u001b[0;31mIndentationError\u001b[0m\u001b[0;31m:\u001b[0m unindent does not match any outer indentation level\n"
     ]
    }
   ],
   "source": [
    "# results\n",
    "\n",
    "# subtree with y normalization\n",
    "  height    RMSE_test    std_test    RMSE_train    std_train    k_time\n",
    "--------  -----------  ----------  ------------  -----------  --------\n",
    "       0     36.2108      7.33179      38.6059      1.57064   0.379475\n",
    "       1      9.00098     6.37145       6.76379     1.96568   0.844898\n",
    "       2     19.8113      4.04911       5.28757     1.81899   1.35308\n",
    "       3     25.0455      4.94276       2.3274      0.805733  1.81136\n",
    "       4     28.2255      6.5212        0.85156     0.423465  2.23098\n",
    "       5     30.6354      6.73647       3.35947     8.17561   2.71575\n",
    "       6     32.1027      6.85601       3.54105     8.71922   3.11459\n",
    "       7     32.9709      6.89606       6.94372     9.94045   3.55571\n",
    "       8     33.5112      6.90753       6.97339     9.76975   3.79657\n",
    "       9     33.8502      6.91427      11.8345     11.6213    4.41555\n",
    "      10     34.0963      6.93115      11.4257     11.2624    4.94888\n",
    "\n",
    "# subtree without y normalization\n",
    "  height    RMSE_test    std_test    RMSE_train    std_train    k_time\n",
    "--------  -----------  ----------  ------------  -----------  --------\n",
    "       0     15.6859      4.1392      17.6816       0.713183  0.360443\n",
    "       1      7.55046     2.33179      6.27001      0.654734  0.837389\n",
    "       2      9.72847     2.05767      4.45068      0.882129  1.25317\n",
    "       3     11.2961      2.79994      2.27059      0.481516  1.79971\n",
    "       4     12.8083      3.44694      1.07403      0.637823  2.35346\n",
    "       5     14.0179      3.67504      0.700602     0.57264   2.78285\n",
    "       6     14.9184      3.80535      0.691515     0.56462   3.20764\n",
    "       7     15.6295      3.86539      0.691516     0.56462   3.71648\n",
    "       8     16.2144      3.92876      0.691515     0.56462   3.99213\n",
    "       9     16.7257      3.9931       0.691515     0.56462   4.26315\n",
    "      10     17.1864      4.05672      0.691516     0.564621  5.00918\n",
    "    \n",
    "# sp\n",
    "  height    rmse_test    std_test    rmse_train    std_train    k_time\n",
    "--------  -----------  ----------  ------------  -----------  --------\n",
    "       0      35.192      4.49577       28.3604      1.35718   13.5041\n",
    "       1      35.1808     4.50045       27.9335      1.44836   26.8292\n",
    "       2      35.1632     4.50205       28.1113      1.50891   40.2356\n",
    "       3      35.1946     4.49801       28.3903      1.36571   54.6704\n",
    "       4      35.1753     4.50111       27.9746      1.46222   67.1522\n",
    "       5      35.1997     4.5071        28.0184      1.45564   80.0881\n",
    "       6      35.1645     4.49849       28.3731      1.60057   92.1925\n",
    "       7      35.1771     4.5009        27.9604      1.45742  105.812\n",
    "       8      35.1968     4.50526       28.1991      1.5149   119.022\n",
    "       9      35.1956     4.50197       28.2665      1.30769  131.228\n",
    "      10      35.1676     4.49723       28.4163      1.61596  144.964\n",
    "    \n",
    "# path\n",
    "  height    rmse_test    std_test    rmse_train    std_train     k_time\n",
    "--------  -----------  ----------  ------------  -----------  ---------\n",
    "       0      33.4077     4.73272       29.9975     0.90234    0.853002\n",
    "       1      33.4235     4.72131       30.1603     1.09423    1.71751\n",
    "       2      33.433      4.72441       29.9286     0.787941   2.66032\n",
    "       3      33.4073     4.73243       30.0114     0.909674   3.47763\n",
    "       4      33.4256     4.72166       30.1842     1.1089     4.54367\n",
    "       5      33.4067     4.72641       30.0411     1.01845    5.66178\n",
    "       6      33.419      4.73075       29.9056     0.782179   6.14803\n",
    "       7      33.4248     4.72155       30.1759     1.10382    7.60354\n",
    "       8      33.4122     4.71554       30.1365     1.07485    7.97222\n",
    "       9      33.4071     4.73193       30.0329     0.921065   9.07084\n",
    "      10      33.4165     4.73169       29.9242     0.790843  10.0254"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'O', 'C'}\n",
      "{'O', 'C'}\n"
     ]
    },
    {
     "ename": "TypeError",
     "evalue": "'int' object is not iterable",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-4-e54963002171>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     66\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabelset1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     67\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabelset2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 68\u001b[0;31m \u001b[0mkernel\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0mspkernel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mG2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     69\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkernel\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     70\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/media/ljia/DATA/research-repo/codes/Linlin/py-graph/pygraph/kernels/spKernel.py\u001b[0m in \u001b[0;36mspkernel\u001b[0;34m(edge_weight, *args)\u001b[0m\n\u001b[1;32m     39\u001b[0m     \u001b[0mstart_time\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     40\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 41\u001b[0;31m     \u001b[0mGn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m \u001b[0mgetSPGraph\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0medge_weight\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0medge_weight\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mG\u001b[0m \u001b[0;32min\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m]\u001b[0m \u001b[0;31m# get shortest path graphs of Gn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     42\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     43\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mGn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/media/ljia/DATA/research-repo/codes/Linlin/py-graph/pygraph/kernels/spKernel.py\u001b[0m in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m     39\u001b[0m     \u001b[0mstart_time\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     40\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 41\u001b[0;31m     \u001b[0mGn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m \u001b[0mgetSPGraph\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0medge_weight\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0medge_weight\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mG\u001b[0m \u001b[0;32min\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m]\u001b[0m \u001b[0;31m# get shortest path graphs of Gn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     42\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     43\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mGn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/media/ljia/DATA/research-repo/codes/Linlin/py-graph/pygraph/utils/utils.py\u001b[0m in \u001b[0;36mgetSPGraph\u001b[0;34m(G, edge_weight)\u001b[0m\n\u001b[1;32m     35\u001b[0m     \u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0mBorgwardt\u001b[0m \u001b[0mKM\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mKriegel\u001b[0m \u001b[0mHP\u001b[0m\u001b[0;34m.\u001b[0m \u001b[0mShortest\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0mpath\u001b[0m \u001b[0mkernels\u001b[0m \u001b[0mon\u001b[0m \u001b[0mgraphs\u001b[0m\u001b[0;34m.\u001b[0m \u001b[0mInData\u001b[0m \u001b[0mMining\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mFifth\u001b[0m \u001b[0mIEEE\u001b[0m \u001b[0mInternational\u001b[0m \u001b[0mConference\u001b[0m \u001b[0mon\u001b[0m \u001b[0;36m2005\u001b[0m \u001b[0mNov\u001b[0m \u001b[0;36m27\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mpp\u001b[0m\u001b[0;34m.\u001b[0m \u001b[0;36m8\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0mpp\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m \u001b[0mIEEE\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     36\u001b[0m     \"\"\"\n\u001b[0;32m---> 37\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mfloydTransformation\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0medge_weight\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0medge_weight\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     38\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     39\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mfloydTransformation\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0medge_weight\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'bond_type'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/media/ljia/DATA/research-repo/codes/Linlin/py-graph/pygraph/utils/utils.py\u001b[0m in \u001b[0;36mfloydTransformation\u001b[0;34m(G, edge_weight)\u001b[0m\n\u001b[1;32m     56\u001b[0m     \u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0mBorgwardt\u001b[0m \u001b[0mKM\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mKriegel\u001b[0m \u001b[0mHP\u001b[0m\u001b[0;34m.\u001b[0m \u001b[0mShortest\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0mpath\u001b[0m \u001b[0mkernels\u001b[0m \u001b[0mon\u001b[0m \u001b[0mgraphs\u001b[0m\u001b[0;34m.\u001b[0m \u001b[0mInData\u001b[0m \u001b[0mMining\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mFifth\u001b[0m \u001b[0mIEEE\u001b[0m \u001b[0mInternational\u001b[0m \u001b[0mConference\u001b[0m \u001b[0mon\u001b[0m \u001b[0;36m2005\u001b[0m \u001b[0mNov\u001b[0m \u001b[0;36m27\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mpp\u001b[0m\u001b[0;34m.\u001b[0m \u001b[0;36m8\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0mpp\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m \u001b[0mIEEE\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     57\u001b[0m     \"\"\"\n\u001b[0;32m---> 58\u001b[0;31m     \u001b[0mspMatrix\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfloyd_warshall_numpy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mweight\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0medge_weight\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     59\u001b[0m     \u001b[0mS\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mGraph\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     60\u001b[0m     \u001b[0mS\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd_nodes_from\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnodes\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/networkx/algorithms/shortest_paths/dense.py\u001b[0m in \u001b[0;36mfloyd_warshall_numpy\u001b[0;34m(G, nodelist, weight)\u001b[0m\n\u001b[1;32m     52\u001b[0m     \u001b[0;31m# nonedges are not given the value 0 as well.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     53\u001b[0m     A = nx.to_numpy_matrix(G, nodelist=nodelist, multigraph_weight=min,\n\u001b[0;32m---> 54\u001b[0;31m                            weight=weight, nonedge=np.inf)\n\u001b[0m\u001b[1;32m     55\u001b[0m     \u001b[0mn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mm\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mA\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     56\u001b[0m     \u001b[0mI\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0midentity\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/networkx/convert_matrix.py\u001b[0m in \u001b[0;36mto_numpy_matrix\u001b[0;34m(G, nodelist, dtype, order, multigraph_weight, weight, nonedge)\u001b[0m\n\u001b[1;32m    446\u001b[0m     A = to_numpy_array(G, nodelist=nodelist, dtype=dtype, order=order,\n\u001b[1;32m    447\u001b[0m                        \u001b[0mmultigraph_weight\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmultigraph_weight\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mweight\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mweight\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 448\u001b[0;31m                        nonedge=nonedge)\n\u001b[0m\u001b[1;32m    449\u001b[0m     \u001b[0mM\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0masmatrix\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mA\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    450\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mM\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.5/dist-packages/networkx/convert_matrix.py\u001b[0m in \u001b[0;36mto_numpy_array\u001b[0;34m(G, nodelist, dtype, order, multigraph_weight, weight, nonedge)\u001b[0m\n\u001b[1;32m   1061\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1062\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mnodelist\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1063\u001b[0;31m         \u001b[0mnodelist\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1064\u001b[0m     \u001b[0mnodeset\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnodelist\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1065\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnodelist\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnodeset\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mTypeError\u001b[0m: 'int' object is not iterable"
     ]
    }
   ],
   "source": [
    "import sys\n",
    "import networkx as nx\n",
    "sys.path.insert(0, \"../\")\n",
    "from pygraph.utils.graphfiles import loadDataset\n",
    "from pygraph.kernels.spkernel import spkernel\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "def weisfeilerlehman_test(G):\n",
    "    '''\n",
    "    Weisfeiler-Lehman test of graph isomorphism.\n",
    "    '''\n",
    "\n",
    "    nx.draw_networkx(G)\n",
    "    plt.show()\n",
    "    nx.draw_networkx_labels(G, nx.spring_layout(G), labels = nx.get_node_attributes(G,'label'))\n",
    "    print(G.nodes(data = True))\n",
    "    \n",
    "    set_multisets = []\n",
    "    for node in G.nodes(data = True):\n",
    "        # Multiset-label determination.\n",
    "        multiset = [ G.node[neighbors]['label'] for neighbors in G[node[0]] ]\n",
    "        # sorting each multiset\n",
    "        multiset.sort()\n",
    "        multiset = node[1]['label'] + ''.join(multiset) # concatenate to a string and add the prefix \n",
    "        set_multisets.append(multiset)\n",
    "        \n",
    "    # label compression\n",
    "#     set_multisets.sort() # this is unnecessary\n",
    "    set_unique = list(set(set_multisets)) # set of unique multiset labels\n",
    "    set_compressed = { value : str(set_unique.index(value)) for value in set_unique } # assign indices as the new labels\n",
    "#     print(set_compressed)\n",
    "#     print(set_multisets)\n",
    "    \n",
    "    # relabel nodes with multisets\n",
    "    for node in G.nodes(data = True):\n",
    "        node[1]['label'] = set_multisets[node[0]]\n",
    "    print(' -> ')\n",
    "    nx.draw_networkx(G)\n",
    "    plt.show()\n",
    "    print(G.nodes(data = True))\n",
    "\n",
    "    \n",
    "    # relabel nodes\n",
    "    for node in G.nodes(data = True):\n",
    "        node[1]['label'] = set_compressed[set_multisets[node[0]]]\n",
    "        \n",
    "    print(' -> ')\n",
    "    nx.draw_networkx(G)\n",
    "    plt.show()\n",
    "    print(G.nodes(data = True))\n",
    "\n",
    "dataset, y = loadDataset(\"../../../../datasets/acyclic/Acyclic/dataset_bps.ds\")\n",
    "G1 = dataset[12]\n",
    "G2 = dataset[55]\n",
    "\n",
    "# init.\n",
    "kernel = 0 # init kernel\n",
    "num_nodes1 = G1.number_of_nodes()\n",
    "num_nodes2 = G2.number_of_nodes()\n",
    "\n",
    "# the first iteration.\n",
    "labelset1 = { G1.nodes(data = True)[i]['label'] for i in range(num_nodes1) }\n",
    "labelset2 = { G2.nodes(data = True)[i]['label'] for i in range(num_nodes2) }\n",
    "print(labelset1)\n",
    "print(labelset2)\n",
    "kernel += spkernel(G1, G2)\n",
    "print(kernel)\n",
    "\n",
    "\n",
    "\n",
    "for height in range(0, min(num_nodes1, num_nodes2)): #Q how to determine the upper bound of the height?\n",
    "    if labelset1 != labelset2:\n",
    "        break\n",
    "        \n",
    "    # Weisfeiler-Lehman test of graph isomorphism.\n",
    "    weisfeilerlehman_test(G1)\n",
    "    weisfeilerlehman_test(G2)\n",
    "    \n",
    "    # calculate kernel\n",
    "    kernel += spkernel(G1, G2)\n",
    "    \n",
    "    # get label sets of both graphs\n",
    "    labelset1 = { G1.nodes(data = True)[i]['label'] for i in range(num_nodes1) }\n",
    "    labelset2 = { G2.nodes(data = True)[i]['label'] for i in range(num_nodes2) }\n",
    "#     print(labelset1)\n",
    "#     print(labelset2)\n",
    "\n",
    "print(kernel)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'O', 6: 'O'}\n",
      "{0: 'C', 1: 'C', 2: 'C', 3: 'C', 4: 'C', 5: 'C', 6: 'S', 7: 'S'}\n",
      "\n",
      " --- height = 0 --- \n",
      "\n",
      " --- for graph 0 --- \n",
      "\n",
      "labels_ori: ['C', 'C', 'C', 'C', 'C', 'O', 'O']\n",
      "all_labels_ori: {'C', 'O'}\n",
      "num_of_each_label: {'C': 5, 'O': 2}\n",
      "all_num_of_each_label: [{'C': 5, 'O': 2}]\n",
      "num_of_labels: 2\n",
      "all_labels_ori: {'C', 'O'}\n",
      "\n",
      " --- for graph 1 --- \n",
      "\n",
      "labels_ori: ['C', 'C', 'C', 'C', 'C', 'C', 'S', 'S']\n",
      "all_labels_ori: {'C', 'O', 'S'}\n",
      "num_of_each_label: {'C': 6, 'S': 2}\n",
      "all_num_of_each_label: [{'C': 5, 'O': 2}, {'C': 6, 'S': 2}]\n",
      "num_of_labels: 2\n",
      "all_labels_ori: {'C', 'O', 'S'}\n",
      "\n",
      " all_num_of_labels_occured: 3\n",
      "\n",
      " --- calculating kernel matrix ---\n",
      "\n",
      " labels: {'C', 'O'}\n",
      "vector1: [[5 2]]\n",
      "vector2: [[5 2]]\n",
      "Kmatrix: [[ 29.   0.]\n",
      " [  0.   0.]]\n",
      "\n",
      " labels: {'C', 'O', 'S'}\n",
      "vector1: [[5 2 0]]\n",
      "vector2: [[6 0 2]]\n",
      "Kmatrix: [[ 29.  30.]\n",
      " [ 30.   0.]]\n",
      "\n",
      " labels: {'C', 'S'}\n",
      "vector1: [[6 2]]\n",
      "vector2: [[6 2]]\n",
      "Kmatrix: [[ 29.  30.]\n",
      " [ 30.  40.]]\n",
      "\n",
      " --- height = 1 --- \n",
      "\n",
      " --- for graph 0 --- \n",
      "\n",
      "multiset: ['CC', 'CC', 'CCO', 'CCO', 'COO', 'OCC', 'OCC']\n",
      "set_unique: ['OCC', 'COO', 'CCO', 'CC']\n",
      "set_compressed: {'OCC': '4', 'COO': '5', 'CCO': '6', 'CC': '7'}\n",
      "all_set_compressed: {'OCC': '4', 'COO': '5', 'CCO': '6', 'CC': '7'}\n",
      "num_of_labels_occured: 7\n",
      "\n",
      " compressed labels: {0: '7', 1: '7', 2: '6', 3: '6', 4: '5', 5: '4', 6: '4'}\n",
      "labels_comp: ['7', '7', '6', '6', '5', '4', '4']\n",
      "all_labels_ori: {'5', '4', '6', '7'}\n",
      "num_of_each_label: {'5': 1, '4': 2, '6': 2, '7': 2}\n",
      "all_num_of_each_label: [{'5': 1, '4': 2, '6': 2, '7': 2}]\n",
      "\n",
      " --- for graph 1 --- \n",
      "\n",
      "multiset: ['CC', 'CC', 'CC', 'CCS', 'CCS', 'CCSS', 'SCC', 'SCC']\n",
      "set_unique: ['SCC', 'CC', 'CCS', 'CCSS']\n",
      "set_compressed: {'SCC': '8', 'CC': '7', 'CCS': '9', 'CCSS': '10'}\n",
      "all_set_compressed: {'SCC': '8', 'COO': '5', 'CCS': '9', 'OCC': '4', 'CCO': '6', 'CCSS': '10', 'CC': '7'}\n",
      "num_of_labels_occured: 10\n",
      "\n",
      " compressed labels: {0: '7', 1: '7', 2: '7', 3: '9', 4: '9', 5: '10', 6: '8', 7: '8'}\n",
      "labels_comp: ['7', '7', '7', '9', '9', '10', '8', '8']\n",
      "all_labels_ori: {'10', '4', '7', '9', '6', '5', '8'}\n",
      "num_of_each_label: {'10': 1, '9': 2, '7': 3, '8': 2}\n",
      "all_num_of_each_label: [{'5': 1, '4': 2, '6': 2, '7': 2}, {'10': 1, '9': 2, '7': 3, '8': 2}]\n",
      "\n",
      " all_num_of_labels_occured: 10\n",
      "\n",
      " --- calculating kernel matrix ---\n",
      "\n",
      " labels: {'5', '4', '6', '7'}\n",
      "vector1: [[1 2 2 2]]\n",
      "vector2: [[1 2 2 2]]\n",
      "\n",
      " labels: {'10', '4', '7', '9', '6', '5', '8'}\n",
      "vector1: [[0 2 2 0 2 1 0]]\n",
      "vector2: [[1 0 3 2 0 0 2]]\n",
      "\n",
      " labels: {'8', '10', '7', '9'}\n",
      "vector1: [[2 1 3 2]]\n",
      "vector2: [[2 1 3 2]]\n",
      "\n",
      " Kmatrix: [[ 42.  36.]\n",
      " [ 36.  58.]]\n",
      "\n",
      " --- height = 2 --- \n",
      "\n",
      " --- for graph 0 --- \n",
      "\n",
      "multiset: ['76', '76', '647', '647', '544', '456', '456']\n",
      "set_unique: ['647', '76', '456', '544']\n",
      "set_compressed: {'647': '11', '76': '12', '544': '14', '456': '13'}\n",
      "all_set_compressed: {'647': '11', '76': '12', '456': '13', '544': '14'}\n",
      "num_of_labels_occured: 14\n",
      "\n",
      " compressed labels: {0: '12', 1: '12', 2: '11', 3: '11', 4: '14', 5: '13', 6: '13'}\n",
      "labels_comp: ['12', '12', '11', '11', '14', '13', '13']\n",
      "all_labels_ori: {'14', '12', '11', '13'}\n",
      "num_of_each_label: {'14': 1, '13': 2, '12': 2, '11': 2}\n",
      "all_num_of_each_label: [{'14': 1, '13': 2, '12': 2, '11': 2}]\n",
      "\n",
      " --- for graph 1 --- \n",
      "\n",
      "multiset: ['79', '79', '710', '978', '978', '10788', '8109', '8109']\n",
      "set_unique: ['710', '8109', '79', '10788', '978']\n",
      "set_compressed: {'710': '15', '79': '17', '8109': '16', '978': '19', '10788': '18'}\n",
      "all_set_compressed: {'710': '15', '79': '17', '978': '19', '10788': '18', '8109': '16', '456': '13', '544': '14', '647': '11', '76': '12'}\n",
      "num_of_labels_occured: 19\n",
      "\n",
      " compressed labels: {0: '17', 1: '17', 2: '15', 3: '19', 4: '19', 5: '18', 6: '16', 7: '16'}\n",
      "labels_comp: ['17', '17', '15', '19', '19', '18', '16', '16']\n",
      "all_labels_ori: {'18', '19', '12', '13', '17', '11', '14', '16', '15'}\n",
      "num_of_each_label: {'15': 1, '17': 2, '19': 2, '16': 2, '18': 1}\n",
      "all_num_of_each_label: [{'14': 1, '13': 2, '12': 2, '11': 2}, {'15': 1, '17': 2, '19': 2, '16': 2, '18': 1}]\n",
      "\n",
      " all_num_of_labels_occured: 19\n",
      "\n",
      " --- calculating kernel matrix ---\n",
      "\n",
      " labels: {'14', '12', '11', '13'}\n",
      "vector1: [[1 2 2 2]]\n",
      "vector2: [[1 2 2 2]]\n",
      "\n",
      " labels: {'18', '19', '12', '13', '17', '11', '14', '16', '15'}\n",
      "vector1: [[0 0 2 2 0 2 1 0 0]]\n",
      "vector2: [[1 2 0 0 2 0 0 2 1]]\n",
      "\n",
      " labels: {'18', '17', '15', '16', '19'}\n",
      "vector1: [[1 2 1 2 2]]\n",
      "vector2: [[1 2 1 2 2]]\n",
      "\n",
      " Kmatrix: [[ 55.  36.]\n",
      " [ 36.  72.]]\n",
      "\n",
      " --- Weisfeiler-Lehman subtree kernel built in 0.0034377574920654297 seconds ---\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[ 55.,  36.],\n",
       "       [ 36.,  72.]])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# test of WL subtree kernel on many graphs\n",
    "\n",
    "import sys\n",
    "import pathlib\n",
    "from collections import Counter\n",
    "sys.path.insert(0, \"../\")\n",
    "\n",
    "import networkx as nx\n",
    "import numpy as np\n",
    "import time\n",
    "\n",
    "from pygraph.kernels.spkernel import spkernel\n",
    "from pygraph.kernels.pathKernel import pathkernel\n",
    "\n",
    "def weisfeilerlehmankernel(*args, height = 0, base_kernel = 'subtree'):\n",
    "    \"\"\"Calculate Weisfeiler-Lehman kernels between graphs.\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    Gn : List of NetworkX graph\n",
    "        List of graphs between which the kernels are calculated.\n",
    "    /\n",
    "    G1, G2 : NetworkX graphs\n",
    "        2 graphs between which the kernel is calculated.\n",
    "        \n",
    "    height : subtree height\n",
    "    \n",
    "    base_kernel : base kernel used in each iteration of WL kernel\n",
    "        the default base kernel is subtree kernel\n",
    "        \n",
    "    Return\n",
    "    ------\n",
    "    Kmatrix/Kernel : Numpy matrix/int\n",
    "        Kernel matrix, each element of which is the Weisfeiler-Lehman kernel between 2 praphs. / Weisfeiler-Lehman Kernel between 2 graphs.\n",
    "        \n",
    "    Notes\n",
    "    -----\n",
    "    This function now supports WL subtree kernel and WL shortest path kernel.\n",
    "    \n",
    "    References\n",
    "    ----------\n",
    "    [1] Shervashidze N, Schweitzer P, Leeuwen EJ, Mehlhorn K, Borgwardt KM. Weisfeiler-lehman graph kernels. Journal of Machine Learning Research. 2011;12(Sep):2539-61.\n",
    "    \"\"\"\n",
    "    if len(args) == 1: # for a list of graphs\n",
    "\n",
    "#         print(args)\n",
    "        start_time = time.time()\n",
    "        \n",
    "        # for WL subtree kernel\n",
    "        if base_kernel == 'subtree':           \n",
    "            Kmatrix = _wl_subtreekernel_do(args[0], height = height, base_kernel = 'subtree')\n",
    "            \n",
    "        # for WL edge kernel\n",
    "        elif base_kernel == 'edge':\n",
    "            print('edge')\n",
    "            \n",
    "        # for WL shortest path kernel\n",
    "        elif base_kernel == 'sp':\n",
    "            Gn = args[0]\n",
    "            Kmatrix = np.zeros((len(Gn), len(Gn)))\n",
    "            \n",
    "            for i in range(0, len(Gn)):\n",
    "                for j in range(i, len(Gn)):\n",
    "                    Kmatrix[i][j] = _weisfeilerlehmankernel_do(Gn[i], Gn[j])\n",
    "                    Kmatrix[j][i] = Kmatrix[i][j]\n",
    "\n",
    "        print(\"\\n --- Weisfeiler-Lehman %s kernel matrix of size %d built in %s seconds ---\" % (base_kernel, len(args[0]), (time.time() - start_time)))\n",
    "        \n",
    "        return Kmatrix\n",
    "        \n",
    "    else: # for only 2 graphs\n",
    "        \n",
    "        start_time = time.time()\n",
    "        \n",
    "        # for WL subtree kernel\n",
    "        if base_kernel == 'subtree':\n",
    "            \n",
    "            args = [args[0], args[1]]\n",
    "#             print(args)\n",
    "            kernel = _wl_subtreekernel_do(args, height = height, base_kernel = 'subtree')\n",
    "            \n",
    "        # for WL edge kernel\n",
    "        elif base_kernel == 'edge':\n",
    "            print('edge')\n",
    "            \n",
    "        # for WL shortest path kernel\n",
    "        elif base_kernel == 'sp':\n",
    "            \n",
    "\n",
    "            kernel = _pathkernel_do(args[0], args[1])\n",
    "\n",
    "        print(\"\\n --- Weisfeiler-Lehman %s kernel built in %s seconds ---\" % (base_kernel, time.time() - start_time))\n",
    "        \n",
    "        return kernel\n",
    "    \n",
    "    \n",
    "def _weisfeilerlehmankernel_do(G1, G2):\n",
    "    \"\"\"Calculate Weisfeiler-Lehman kernels between 2 graphs. This kernel use shortest path kernel to calculate kernel between two graphs in each iteration.\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    G1, G2 : NetworkX graphs\n",
    "        2 graphs between which the kernel is calculated.\n",
    "        \n",
    "    Return\n",
    "    ------\n",
    "    Kernel : int\n",
    "        Weisfeiler-Lehman Kernel between 2 graphs.\n",
    "    \"\"\"\n",
    "    \n",
    "    # init.\n",
    "    kernel = 0 # init kernel\n",
    "    num_nodes1 = G1.number_of_nodes()\n",
    "    num_nodes2 = G2.number_of_nodes()\n",
    "    height = 12 #min(num_nodes1, num_nodes2)) #Q how to determine the upper bound of the height?\n",
    "    \n",
    "    # the first iteration.\n",
    "    labelset1 = { G1.nodes(data = True)[i]['label'] for i in range(num_nodes1) }\n",
    "    labelset2 = { G2.nodes(data = True)[i]['label'] for i in range(num_nodes2) }\n",
    "    kernel += pathkernel(G1, G2) # change your base kernel here (and one more below)\n",
    "    \n",
    "    for h in range(0, height):\n",
    "#         if labelset1 != labelset2:\n",
    "#             break\n",
    "\n",
    "        # Weisfeiler-Lehman test of graph isomorphism.\n",
    "        relabel(G1)\n",
    "        relabel(G2)\n",
    "\n",
    "        # calculate kernel\n",
    "        kernel += pathkernel(G1, G2) # change your base kernel here (and one more before)\n",
    "\n",
    "        # get label sets of both graphs\n",
    "        labelset1 = { G1.nodes(data = True)[i]['label'] for i in range(num_nodes1) }\n",
    "        labelset2 = { G2.nodes(data = True)[i]['label'] for i in range(num_nodes2) }\n",
    "    \n",
    "    return kernel\n",
    "\n",
    "\n",
    "def relabel(G):\n",
    "    '''\n",
    "    Relabel nodes in graph G in one iteration of the 1-dim. WL test of graph isomorphism.\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    G : NetworkX graph\n",
    "        The graphs whose nodes are relabeled.\n",
    "    '''\n",
    "    \n",
    "    # get the set of original labels\n",
    "    labels_ori = list(nx.get_node_attributes(G, 'label').values())\n",
    "    print(labels_ori)\n",
    "    num_of_each_label = dict(Counter(labels_ori))\n",
    "    print(num_of_each_label)\n",
    "    num_of_labels = len(num_of_each_label)\n",
    "    print(num_of_labels)\n",
    "    \n",
    "    set_multisets = []\n",
    "    for node in G.nodes(data = True):\n",
    "        # Multiset-label determination.\n",
    "        multiset = [ G.node[neighbors]['label'] for neighbors in G[node[0]] ]\n",
    "        # sorting each multiset\n",
    "        multiset.sort()\n",
    "        multiset = node[1]['label'] + ''.join(multiset) # concatenate to a string and add the prefix \n",
    "        set_multisets.append(multiset)\n",
    "    print(set_multisets)\n",
    "        \n",
    "    # label compression\n",
    "#     set_multisets.sort() # this is unnecessary\n",
    "    set_unique = list(set(set_multisets)) # set of unique multiset labels\n",
    "    print(set_unique)\n",
    "    set_compressed = { value : str(set_unique.index(value) + num_of_labels + 1) for value in set_unique } # assign new labels\n",
    "    print(set_compressed)\n",
    "    \n",
    "    # relabel nodes\n",
    "#     nx.relabel_nodes(G, set_compressed, copy = False)\n",
    "    for node in G.nodes(data = True):\n",
    "        node[1]['label'] = set_compressed[set_multisets[node[0]]]\n",
    "    print(nx.get_node_attributes(G, 'label'))\n",
    "\n",
    "    # get the set of compressed labels\n",
    "    labels_comp = list(nx.get_node_attributes(G, 'label').values())\n",
    "    print(labels_comp)\n",
    "    num_of_each_label.update(dict(Counter(labels_comp)))\n",
    "    print(num_of_each_label)\n",
    "    \n",
    "    \n",
    "def _wl_subtreekernel_do(*args, height = 0, base_kernel = 'subtree'):\n",
    "    \"\"\"Calculate Weisfeiler-Lehman subtree kernels between graphs.\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    Gn : List of NetworkX graph\n",
    "        List of graphs between which the kernels are calculated.\n",
    "        \n",
    "    Return\n",
    "    ------\n",
    "    Kmatrix/Kernel : Numpy matrix/int\n",
    "        Kernel matrix, each element of which is the Weisfeiler-Lehman kernel between 2 praphs.\n",
    "    \"\"\"\n",
    "    \n",
    "#     print(args)\n",
    "    Gn = args[0]\n",
    "#     print(Gn)\n",
    "\n",
    "    Kmatrix = np.zeros((len(Gn), len(Gn)))\n",
    "    all_num_of_labels_occured = 0 # number of the set of letters that occur before as node labels at least once in all graphs\n",
    "    \n",
    "    # initial for height = 0\n",
    "    print('\\n --- height = 0 --- ')\n",
    "    all_labels_ori = set() # all unique orignal labels in all graphs in this iteration\n",
    "    all_num_of_each_label = [] # number of occurence of each label in each graph in this iteration\n",
    "    all_set_compressed = {} # a dictionary mapping original labels to new ones in all graphs in this iteration\n",
    "    num_of_labels_occured = all_num_of_labels_occured # number of the set of letters that occur before as node labels at least once in all graphs\n",
    "\n",
    "    # for each graph\n",
    "    for idx, G in enumerate(Gn):\n",
    "        # get the set of original labels\n",
    "        print('\\n --- for graph %d --- \\n' % (idx))\n",
    "        labels_ori = list(nx.get_node_attributes(G, 'label').values())\n",
    "        print('labels_ori: %s' % (labels_ori))\n",
    "        all_labels_ori.update(labels_ori)\n",
    "        print('all_labels_ori: %s' % (all_labels_ori))\n",
    "        num_of_each_label = dict(Counter(labels_ori)) # number of occurence of each label in graph\n",
    "        print('num_of_each_label: %s' % (num_of_each_label))\n",
    "        all_num_of_each_label.append(num_of_each_label)\n",
    "        print('all_num_of_each_label: %s' % (all_num_of_each_label))\n",
    "        num_of_labels = len(num_of_each_label) # number of all unique labels\n",
    "        print('num_of_labels: %s' % (num_of_labels))\n",
    "        \n",
    "\n",
    "        all_labels_ori.update(labels_ori)\n",
    "        print('all_labels_ori: %s' % (all_labels_ori))\n",
    "        \n",
    "    all_num_of_labels_occured += len(all_labels_ori)\n",
    "    print('\\n all_num_of_labels_occured: %s' % (all_num_of_labels_occured))\n",
    "        \n",
    "    # calculate subtree kernel with the 0th iteration and add it to the final kernel\n",
    "    print('\\n --- calculating kernel matrix ---')\n",
    "    for i in range(0, len(Gn)):\n",
    "        for j in range(i, len(Gn)):\n",
    "            labels = set(list(all_num_of_each_label[i].keys()) + list(all_num_of_each_label[j].keys()))\n",
    "            print('\\n labels: %s' % (labels))\n",
    "            vector1 = np.matrix([ (all_num_of_each_label[i][label] if (label in all_num_of_each_label[i].keys()) else 0) for label in labels ])\n",
    "            vector2 = np.matrix([ (all_num_of_each_label[j][label] if (label in all_num_of_each_label[j].keys()) else 0) for label in labels ])\n",
    "            print('vector1: %s' % (vector1))\n",
    "            print('vector2: %s' % (vector2))\n",
    "            Kmatrix[i][j] += np.dot(vector1, vector2.transpose())\n",
    "            Kmatrix[j][i] = Kmatrix[i][j]\n",
    "            print('Kmatrix: %s' % (Kmatrix))\n",
    "\n",
    "    \n",
    "    # iterate each height\n",
    "    for h in range(1, height + 1):\n",
    "        print('\\n --- height = %d --- ' % (h))\n",
    "        all_set_compressed = {} # a dictionary mapping original labels to new ones in all graphs in this iteration\n",
    "        num_of_labels_occured = all_num_of_labels_occured # number of the set of letters that occur before as node labels at least once in all graphs\n",
    "        all_labels_ori = set()\n",
    "        all_num_of_each_label = []\n",
    "        \n",
    "        # for each graph\n",
    "        for idx, G in enumerate(Gn):\n",
    "#             # get the set of original labels\n",
    "            print('\\n --- for graph %d --- \\n' % (idx))\n",
    "#             labels_ori = list(nx.get_node_attributes(G, 'label').values())\n",
    "#             print('labels_ori: %s' % (labels_ori))\n",
    "#             num_of_each_label = dict(Counter(labels_ori)) # number of occurence of each label in graph\n",
    "#             print('num_of_each_label: %s' % (num_of_each_label))\n",
    "#             num_of_labels = len(num_of_each_label) # number of all unique labels\n",
    "#             print('num_of_labels: %s' % (num_of_labels))\n",
    "            \n",
    "#             all_labels_ori.update(labels_ori)\n",
    "#             print('all_labels_ori: %s' % (all_labels_ori))\n",
    "#             #             num_of_labels_occured += num_of_labels #@todo not precise\n",
    "#             num_of_labels_occured = all_num_of_labels_occured + len(all_labels_ori) + len(all_set_compressed)\n",
    "#             print('num_of_labels_occured: %s' % (num_of_labels_occured))\n",
    "            \n",
    "            set_multisets = []\n",
    "            for node in G.nodes(data = True):\n",
    "                # Multiset-label determination.\n",
    "                multiset = [ G.node[neighbors]['label'] for neighbors in G[node[0]] ]\n",
    "                # sorting each multiset\n",
    "                multiset.sort()\n",
    "                multiset = node[1]['label'] + ''.join(multiset) # concatenate to a string and add the prefix \n",
    "                set_multisets.append(multiset)\n",
    "            print('multiset: %s' % (set_multisets))\n",
    "\n",
    "            # label compression\n",
    "        #     set_multisets.sort() # this is unnecessary\n",
    "            set_unique = list(set(set_multisets)) # set of unique multiset labels\n",
    "            print('set_unique: %s' % (set_unique))\n",
    "            # a dictionary mapping original labels to new ones. \n",
    "            set_compressed = {}\n",
    "            # if a label occured before, assign its former compressed label, else assign the number of labels occured + 1 as the compressed label \n",
    "            for value in set_unique:\n",
    "                if value in all_set_compressed.keys():\n",
    "                    set_compressed.update({ value : all_set_compressed[value] })\n",
    "                else:\n",
    "                    set_compressed.update({ value : str(num_of_labels_occured + 1) })\n",
    "                    num_of_labels_occured += 1\n",
    "#             set_compressed = { value : (all_set_compressed[value] if value in all_set_compressed.keys() else str(set_unique.index(value) + num_of_labels_occured + 1)) for value in set_unique }\n",
    "            print('set_compressed: %s' % (set_compressed))\n",
    "            \n",
    "            all_set_compressed.update(set_compressed)\n",
    "            print('all_set_compressed: %s' % (all_set_compressed))\n",
    "#             num_of_labels_occured += len(set_compressed) #@todo not precise\n",
    "            print('num_of_labels_occured: %s' % (num_of_labels_occured))\n",
    "            \n",
    "            # relabel nodes\n",
    "        #     nx.relabel_nodes(G, set_compressed, copy = False)\n",
    "            for node in G.nodes(data = True):\n",
    "                node[1]['label'] = set_compressed[set_multisets[node[0]]]\n",
    "            print('\\n compressed labels: %s' % (nx.get_node_attributes(G, 'label')))\n",
    "\n",
    "            # get the set of compressed labels\n",
    "            labels_comp = list(nx.get_node_attributes(G, 'label').values())\n",
    "            print('labels_comp: %s' % (labels_comp))\n",
    "            all_labels_ori.update(labels_comp)\n",
    "            print('all_labels_ori: %s' % (all_labels_ori))\n",
    "            num_of_each_label = dict(Counter(labels_comp))\n",
    "            print('num_of_each_label: %s' % (num_of_each_label))\n",
    "            all_num_of_each_label.append(num_of_each_label)\n",
    "            print('all_num_of_each_label: %s' % (all_num_of_each_label))\n",
    "                    \n",
    "        all_num_of_labels_occured += len(all_labels_ori)\n",
    "        print('\\n all_num_of_labels_occured: %s' % (all_num_of_labels_occured))\n",
    "        \n",
    "        # calculate subtree kernel with h iterations and add it to the final kernel\n",
    "        print('\\n --- calculating kernel matrix ---')\n",
    "        for i in range(0, len(Gn)):\n",
    "            for j in range(i, len(Gn)):\n",
    "                labels = set(list(all_num_of_each_label[i].keys()) + list(all_num_of_each_label[j].keys()))\n",
    "                print('\\n labels: %s' % (labels))\n",
    "                vector1 = np.matrix([ (all_num_of_each_label[i][label] if (label in all_num_of_each_label[i].keys()) else 0) for label in labels ])\n",
    "                vector2 = np.matrix([ (all_num_of_each_label[j][label] if (label in all_num_of_each_label[j].keys()) else 0) for label in labels ])\n",
    "                print('vector1: %s' % (vector1))\n",
    "                print('vector2: %s' % (vector2))\n",
    "                Kmatrix[i][j] += np.dot(vector1, vector2.transpose())\n",
    "                Kmatrix[j][i] = Kmatrix[i][j]\n",
    "                    \n",
    "        print('\\n Kmatrix: %s' % (Kmatrix))\n",
    "\n",
    "    return Kmatrix\n",
    "\n",
    "    \n",
    "# main\n",
    "import sys\n",
    "from collections import Counter\n",
    "import networkx as nx\n",
    "sys.path.insert(0, \"../\")\n",
    "from pygraph.utils.graphfiles import loadDataset\n",
    "from pygraph.kernels.spkernel import spkernel\n",
    "\n",
    "dataset, y = loadDataset(\"../../../../datasets/acyclic/Acyclic/dataset_bps.ds\")\n",
    "G1 = dataset[15]\n",
    "print(nx.get_node_attributes(G1, 'label'))\n",
    "G2 = dataset[80]\n",
    "print(nx.get_node_attributes(G2, 'label'))\n",
    "\n",
    "weisfeilerlehmankernel(G1, G2, height = 2)\n",
    "# Kmatrix = weisfeilerlehmankernel(G1, G2)"
   ]
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