{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Illustrative example\n", "\n", "This example explains the usage of the Python 3 library package `crispyn` that provides methods for multi-criteria decision analysis using objective and subjective weighting methods. This library contains module `weighting_methods` with the following weighting methods:\n", "\n", "## Objective weighting methods:\n", "\n", "1. Equal `equal_weighting`\n", "\n", "2. Entropy `entropy_weighting`\n", "\n", "3. Standard deviation `std_weighting`\n", "\n", "4. CRITIC `critic_weighting`\n", "\n", "5. Gini coefficient-based `gini_weighting`\n", "\n", "6. MEREC `merec_weighting`\n", "\n", "7. Statistical variance `stat_var_weighting`\n", "\n", "8. CILOS `cilos_weighting`\n", "\n", "9. IDOCRIW `idocriw_weighting`\n", "\n", "10. Angle `angle_weighting`\n", "\n", "11. Coefficient of variance `coeff_var_weighting`\n", "\n", "## Subjective weighting methods:\n", "\n", "12. AHP weighting `AHP_WEIGHTING`\n", "\n", "13. SWARA weighting `swara_weighting`\n", "\n", "14. LBWA weighting `lbwa_weighting`\n", "\n", "15. SAPEVO weighting `sapevo_weighting`\n", "\n", "In addition to the weighting methods, the library also provides other methods necessary for multi-criteria decision analysis, which are as follows:\n", "\n", "The VIKOR method for multi-criteria decision analysis `VIKOR` in module `mcda_methods`,\n", "\n", "The Stochastic Multi-criteria Acceptability Analysis method (SMAA) for determining criteria weights interacting with the VIKOR method `VIKOR_SMAA`\n", "\n", "Normalization techniques in module `normalizations`:\n", "\n", "1. Linear `linear_normalization`\n", "\n", "2. Minimum-Maximum `minmax_normalization`\n", "\n", "3. Maximum `max_normalization`\n", "\n", "4. Sum `sum_normalization`\n", "\n", "5. Vector `vector_normalization`\n", "\n", "Correlation coefficients in module `correlations`:\n", "\n", "1. Spearman rank correlation coefficient rs `spearman`\n", "\n", "2. Weighted Spearman rank correlation coefficient rw `weighted_spearman`\n", "\n", "3. Pearson coefficent `pearson_coeff`\n", "\n", "`rank_preferences` function in module `additions`" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Import other necessary Python modules." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "import copy\n", "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import matplotlib\n", "import seaborn as sns" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Import the necessary modules and methods from package `crispyn`." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "from crispyn.mcda_methods import VIKOR\n", "from crispyn.mcda_methods import VIKOR_SMAA\n", "from crispyn.additions import rank_preferences\n", "from crispyn import correlations as corrs\n", "from crispyn import normalizations as norm_methods\n", "from crispyn import weighting_methods as mcda_weights" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Functions for results visualization." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# Functions for visualizations\n", "\n", "def plot_barplot(df_plot, x_name, y_name, title):\n", " \"\"\"\n", " Display stacked column chart of weights for criteria for `x_name == Weighting methods`\n", " and column chart of ranks for alternatives `x_name == Alternatives`\n", "\n", " Parameters\n", " ----------\n", " df_plot : dataframe\n", " dataframe with criteria weights calculated different weighting methods\n", " or with alternaives rankings for different weighting methods\n", " x_name : str\n", " name of x axis, Alternatives or Weighting methods\n", " y_name : str\n", " name of y axis, Ranks or Weight values\n", " title : str\n", " name of chart title, Weighting methods or Criteria\n", "\n", " Examples\n", " ----------\n", " >>> plot_barplot(df_plot, x_name, y_name, title)\n", " \"\"\"\n", " \n", " list_rank = np.arange(1, len(df_plot) + 1, 1)\n", " stacked = True\n", " width = 0.5\n", " if x_name == 'Alternatives':\n", " stacked = False\n", " width = 0.8\n", " elif x_name == 'Alternative':\n", " pass\n", " else:\n", " df_plot = df_plot.T\n", " ax = df_plot.plot(kind='bar', width = width, stacked=stacked, edgecolor = 'black', figsize = (9,4))\n", " ax.set_xlabel(x_name, fontsize = 12)\n", " ax.set_ylabel(y_name, fontsize = 12)\n", "\n", " if x_name == 'Alternatives':\n", " ax.set_yticks(list_rank)\n", "\n", " ax.set_xticklabels(df_plot.index, rotation = 'horizontal')\n", " ax.tick_params(axis = 'both', labelsize = 12)\n", "\n", " plt.legend(bbox_to_anchor=(0., 1.02, 1., .102), loc='lower left',\n", " ncol=4, mode=\"expand\", borderaxespad=0., edgecolor = 'black', title = title, fontsize = 11)\n", "\n", " ax.grid(True, linestyle = '--')\n", " ax.set_axisbelow(True)\n", " plt.tight_layout()\n", " plt.savefig('results/bar_chart_weights_' + x_name + '.pdf')\n", " plt.savefig('results/bar_chart_weights_' + x_name + '.eps')\n", " plt.show()\n", "\n", "\n", "def draw_heatmap(data, title):\n", " \"\"\"\n", " Display heatmap with correlations of compared rankings generated using different methods\n", "\n", " Parameters\n", " ----------\n", " data : dataframe\n", " dataframe with correlation values between compared rankings\n", " title : str\n", " title of chart containing name of used correlation coefficient\n", "\n", " Examples\n", " ----------\n", " >>> draw_heatmap(data, title)\n", " \"\"\"\n", "\n", " plt.figure(figsize = (6, 4))\n", " sns.set(font_scale=1.0)\n", " heatmap = sns.heatmap(data, annot=True, fmt=\".2f\", cmap=\"RdYlBu\",\n", " linewidth=0.5, linecolor='w')\n", " plt.yticks(va=\"center\")\n", " plt.xlabel('Weighting methods')\n", " plt.title('Correlation coefficient: ' + title)\n", " plt.tight_layout()\n", " plt.savefig('results/heatmap_weights.pdf')\n", " plt.savefig('results/heatmap_weights.eps')\n", " plt.show()\n", "\n", " \n", "def draw_heatmap_smaa(data, title):\n", " \"\"\"\n", " Display heatmap with correlations of compared rankings generated using different methods\n", "\n", " Parameters\n", " ----------\n", " data : dataframe\n", " dataframe with correlation values between compared rankings\n", " title : str\n", " title of chart containing name of used correlation coefficient\n", "\n", " Examples\n", " ----------\n", " >>> draw_heatmap(data, title)\n", " \"\"\"\n", "\n", " sns.set(font_scale=1.0)\n", " heatmap = sns.heatmap(data, annot=True, fmt=\".2f\", cmap=\"RdYlBu_r\",\n", " linewidth=0.05, linecolor='w')\n", " plt.yticks(rotation=0)\n", " plt.ylabel('Alternatives')\n", " plt.tick_params(labelbottom=False,labeltop=True)\n", " \n", " plt.title(title)\n", " plt.tight_layout()\n", " plt.savefig('results/heatmap_smaa.pdf')\n", " plt.savefig('results/heatmap_smaa.eps')\n", " plt.show()\n", "\n", "\n", "def plot_boxplot(data):\n", " \"\"\"\n", " Display boxplot showing distribution of criteria weights determined with different methods.\n", "\n", " Parameters\n", " ----------\n", " data : dataframe\n", " dataframe with correlation values between compared rankings\n", "\n", " Examples\n", " ---------\n", " >>> plot_boxplot(data)\n", " \"\"\"\n", " \n", " df_melted = pd.melt(data)\n", " plt.figure(figsize = (7, 4))\n", " ax = sns.boxplot(x = 'variable', y = 'value', data = df_melted, width = 0.6)\n", " ax.grid(True, linestyle = '--')\n", " ax.set_axisbelow(True)\n", " ax.set_xlabel('Criterion', fontsize = 12)\n", " ax.set_ylabel('Different weights distribution', fontsize = 12)\n", " plt.tight_layout()\n", " plt.savefig('results/boxplot_weights.pdf')\n", " plt.savefig('results/boxplot_weights.eps')\n", " plt.show()\n", "\n", "\n", "# plot radar chart\n", "def plot_radar(data):\n", " \"\"\"\n", " Visualization method to display rankings of alternatives obtained with different methods\n", " on the radar chart.\n", "\n", " Parameters\n", " -----------\n", " data : DataFrame\n", " DataFrame containing containing rankings of alternatives obtained with different \n", " methods. The particular rankings are contained in subsequent columns of DataFrame.\n", " \n", " Examples\n", " ----------\n", " >>> plot_radar(data)\n", " \"\"\"\n", "\n", " fig=plt.figure()\n", " ax = fig.add_subplot(111, polar = True)\n", "\n", " for col in list(data.columns):\n", " labels=np.array(list(data.index))\n", " stats = data.loc[labels, col].values\n", "\n", " angles=np.linspace(0, 2*np.pi, len(labels), endpoint=False)\n", " # close the plot\n", " stats=np.concatenate((stats,[stats[0]]))\n", " angles=np.concatenate((angles,[angles[0]]))\n", " \n", " lista = list(data.index)\n", " lista.append(data.index[0])\n", " labels=np.array(lista)\n", "\n", " ax.plot(angles, stats, '-o', linewidth=2)\n", " # ax.fill(angles, stats, label='_nolegend_', alpha=0.5)\n", " \n", " ax.set_thetagrids(angles * 180/np.pi, labels)\n", " ax.set_rgrids(np.arange(1, data.shape[0] + 1, 1))\n", " ax.grid(True)\n", " ax.set_axisbelow(True)\n", " if data.shape[1] % 2 == 0:\n", " ncol = data.shape[1] // 2\n", " else:\n", " ncol = data.shape[1] // 2 + 1\n", " plt.legend(data.columns, bbox_to_anchor=(-0.1, 1.1, 1.2, .102), loc='lower left',\n", " ncol = ncol, mode=\"expand\", borderaxespad=0., edgecolor = 'black', title = 'Weighting methods', fontsize = 12)\n", " plt.tight_layout()\n", " plt.show()\n", "\n", "\n", "# bar (column) chart\n", "def plot_barplot_stacked(df_plot, stacked = False):\n", " \"\"\"\n", " Visualization method to display column chart of alternatives rankings obtained with \n", " different methods.\n", "\n", " Parameters\n", " ----------\n", " df_plot : DataFrame\n", " DataFrame containing rankings of alternatives obtained with different methods.\n", " The particular rankings are included in subsequent columns of DataFrame.\n", "\n", " stacked : Boolean\n", " Variable denoting if the chart is to be stacked or not.\n", "\n", " Examples\n", " ----------\n", " >>> plot_barplot(df_plot)\n", " \"\"\"\n", "\n", " ax = df_plot.plot(kind='bar', width = 0.6, stacked=stacked, edgecolor = 'black', figsize = (9,4))\n", " if stacked == False:\n", " list_rank = np.arange(0, 0.30, 0.05)\n", " ax.set_yticks(list_rank)\n", " ax.set_ylim(0, 0.25)\n", "\n", " ax.set_xticklabels(df_plot.index, rotation = 'horizontal')\n", " ax.tick_params(axis = 'both', labelsize = 12)\n", " y_ticks = ax.yaxis.get_major_ticks()\n", " \n", " ncol = df_plot.shape[1]\n", " plt.legend(bbox_to_anchor=(0., 1.02, 1., .102), loc='lower left',\n", " ncol = ncol, mode=\"expand\", borderaxespad=0., edgecolor = 'black', title = 'Criteria', fontsize = 12)\n", "\n", " ax.set_xlabel('Weighting methods', fontsize = 12)\n", " ax.set_ylabel('Weight value', fontsize = 12)\n", "\n", " ax.grid(True)\n", " ax.set_axisbelow(True)\n", " plt.tight_layout()\n", " plt.show()\n", "\n", "\n", "def plot_radar_weights(data):\n", " \"\"\"\n", " Visualization method to display weights values obtained with different weighing methods\n", " on the radar chart.\n", "\n", " Parameters\n", " -----------\n", " data : DataFrame\n", " DataFrame containing weights obtained with different weighting\n", " methods. The particular weights are contained in subsequent columns of DataFrame.\n", " \n", " Examples\n", " ----------\n", " >>> plot_radar_weights(data)\n", " \"\"\"\n", "\n", " fig=plt.figure()\n", " ax = fig.add_subplot(111, polar = True)\n", "\n", " for col in list(data.columns):\n", " labels=np.array(list(data.index))\n", " stats = data.loc[labels, col].values\n", "\n", " angles=np.linspace(0, 2*np.pi, len(labels), endpoint=False)\n", " # close the plot\n", " stats=np.concatenate((stats,[stats[0]]))\n", " angles=np.concatenate((angles,[angles[0]]))\n", " \n", " lista = list(data.index)\n", " lista.append(data.index[0])\n", " labels=np.array(lista)\n", "\n", " ax.plot(angles, stats, linewidth=2)\n", " ax.fill(angles, stats, label='_nolegend_', alpha=0.3)\n", " \n", " ax.set_thetagrids(angles * 180/np.pi, labels)\n", " ax.set_rgrids(np.round(np.linspace(0, np.max(stats) + 0.05, 5), 2))\n", " ax.grid(True)\n", " ax.set_axisbelow(True)\n", " if data.shape[1] % 2 == 0:\n", " ncol = data.shape[1] // 2\n", " else:\n", " ncol = data.shape[1] // 2 + 1\n", " plt.legend(data.columns, bbox_to_anchor=(-0.1, 1.1, 1.2, .102), loc='lower left',\n", " ncol = ncol, mode=\"expand\", borderaxespad=0., edgecolor = 'black', title = 'Weighting methods', fontsize = 12)\n", " plt.tight_layout()\n", " plt.show()\n", "\n", "\n", "# Create dictionary class\n", "class Create_dictionary(dict):\n", " \n", " # __init__ function\n", " def __init__(self):\n", " self = dict()\n", " \n", " # Function to add key:value\n", " def add(self, key, value):\n", " self[key] = value" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As an illustrative example, a dataset will be used containing performances of the twelve best-selling electric cars in 2021 according to a ranking available at https://www.caranddriver.com/features/g36278968/best-selling-evs-of-2021/ The dataset is displayed below. $A_1$-$A_{12}$ are the individual alternatives in rows, columns $C_1$-$C_{11}$ denote the criteria, and the Type row contains the criteria type, where 1 indicates a profit criterion (stimulant) and -1 a cost criterion (destimulant). The following are the evaluation criteria for the electric cars evaluated in this research." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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NameUnitType
Cj
C1Max speedmph1
C2Battery capacitykWh1
C3Electric motorkW1
C4Maximum torqueNm1
C5Horsepowerhp1
C6EPA Fuel Economy CombinedMPGe1
C7EPA Fuel Economy CityMPGe1
C8EPA Fuel Economy HighwayMPGe1
C9EPA rangemiles1
C10Turning Diameter / Radius, curb to curbfeet-1
C11Base priceUSD-1
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" ], "text/plain": [ " Name Unit Type\n", "Cj \n", "C1 Max speed mph 1\n", "C2 Battery capacity kWh 1\n", "C3 Electric motor kW 1\n", "C4 Maximum torque Nm 1\n", "C5 Horsepower hp 1\n", "C6 EPA Fuel Economy Combined MPGe 1\n", "C7 EPA Fuel Economy City MPGe 1\n", "C8 EPA Fuel Economy Highway MPGe 1\n", "C9 EPA range miles 1\n", "C10 Turning Diameter / Radius, curb to curb feet -1\n", "C11 Base price USD -1" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "criteria_presentation = pd.read_csv('criteria_electric_cars.csv', index_col = 'Cj')\n", "criteria_presentation" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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NameC1 Max speed [mph]C2 Battery [kWh]C3 Electric motor [kW] FrontC4 Torque [Nm] FrontC5 Mechanical horsepower [hp]C6 EPA Fuel Economy Combined [MPGe]C7 EPA Fuel Economy City [MPGe]C8 EPA Fuel Economy Highway [MPGe]C9 EPA range [miles]C10 Turning Diameter / Radius, curb to curb [feet]C11 Base price [$]
Ai
A1Tesla Model Y155.374.0340673456.011111510624439.865440
A2Tesla Model 3162.279.5247639283.011311810726338.860440
A3Ford Mustang Mach-E112.568.0198430266.0981059123038.156575
A4Chevrolet Bolt EV and EUV90.166.0150360201.212013110925934.832495
A5Volkswagen ID.499.477.0150310201.2971029026036.445635
A6Nissan Leaf89.540.0110320147.51111239922634.828425
A7Audi e-tron and e-tron Sportback124.395.0125247187.778787722240.084595
A8Porsche Taycan155.379.2160300214.679798022738.4105150
A9Tesla Model S162.2100.0205420502.912012411540240.396440
A10Hyundai Kona Electric96.339.2100395134.112013210825834.835245
A11Tesla Model X162.2100.0205420502.9981039337140.8127940
A12Hyundai Ioniq Electric102.538.3101295136.113314512117034.834250
TypeNaN1.01.0111.01111-1.0-1
\n", "
" ], "text/plain": [ " Name C1 Max speed [mph] C2 Battery [kWh] \\\n", "Ai \n", "A1 Tesla Model Y 155.3 74.0 \n", "A2 Tesla Model 3 162.2 79.5 \n", "A3 Ford Mustang Mach-E 112.5 68.0 \n", "A4 Chevrolet Bolt EV and EUV 90.1 66.0 \n", "A5 Volkswagen ID.4 99.4 77.0 \n", "A6 Nissan Leaf 89.5 40.0 \n", "A7 Audi e-tron and e-tron Sportback 124.3 95.0 \n", "A8 Porsche Taycan 155.3 79.2 \n", "A9 Tesla Model S 162.2 100.0 \n", "A10 Hyundai Kona Electric 96.3 39.2 \n", "A11 Tesla Model X 162.2 100.0 \n", "A12 Hyundai Ioniq Electric 102.5 38.3 \n", "Type NaN 1.0 1.0 \n", "\n", " C3 Electric motor [kW] Front C4 Torque [Nm] Front \\\n", "Ai \n", "A1 340 673 \n", "A2 247 639 \n", "A3 198 430 \n", "A4 150 360 \n", "A5 150 310 \n", "A6 110 320 \n", "A7 125 247 \n", "A8 160 300 \n", "A9 205 420 \n", "A10 100 395 \n", "A11 205 420 \n", "A12 101 295 \n", "Type 1 1 \n", "\n", " C5 Mechanical horsepower [hp] C6 EPA Fuel Economy Combined [MPGe] \\\n", "Ai \n", "A1 456.0 111 \n", "A2 283.0 113 \n", "A3 266.0 98 \n", "A4 201.2 120 \n", "A5 201.2 97 \n", "A6 147.5 111 \n", "A7 187.7 78 \n", "A8 214.6 79 \n", "A9 502.9 120 \n", "A10 134.1 120 \n", "A11 502.9 98 \n", "A12 136.1 133 \n", "Type 1.0 1 \n", "\n", " C7 EPA Fuel Economy City [MPGe] C8 EPA Fuel Economy Highway [MPGe] \\\n", "Ai \n", "A1 115 106 \n", "A2 118 107 \n", "A3 105 91 \n", "A4 131 109 \n", "A5 102 90 \n", "A6 123 99 \n", "A7 78 77 \n", "A8 79 80 \n", "A9 124 115 \n", "A10 132 108 \n", "A11 103 93 \n", "A12 145 121 \n", "Type 1 1 \n", "\n", " C9 EPA range [miles] \\\n", "Ai \n", "A1 244 \n", "A2 263 \n", "A3 230 \n", "A4 259 \n", "A5 260 \n", "A6 226 \n", "A7 222 \n", "A8 227 \n", "A9 402 \n", "A10 258 \n", "A11 371 \n", "A12 170 \n", "Type 1 \n", "\n", " C10 Turning Diameter / Radius, curb to curb [feet] C11 Base price [$] \n", "Ai \n", "A1 39.8 65440 \n", "A2 38.8 60440 \n", "A3 38.1 56575 \n", "A4 34.8 32495 \n", "A5 36.4 45635 \n", "A6 34.8 28425 \n", "A7 40.0 84595 \n", "A8 38.4 105150 \n", "A9 40.3 96440 \n", "A10 34.8 35245 \n", "A11 40.8 127940 \n", "A12 34.8 34250 \n", "Type -1.0 -1 " ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data_presentation = pd.read_csv('electric_cars_2021.csv', index_col = 'Ai')\n", "data_presentation" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Load a decision matrix containing only the performance values of the alternatives against the criteria and the criteria type in the last row, as shown below. Transform the decision matrix and criteria type from dataframe to NumPy array." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Decision matrix\n" ] }, { "data": { "text/html": [ "
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C1C2C3C4C5C6C7C8C9C10C11
Ai
A1155.374.0340673456.011111510624439.865440
A2162.279.5247639283.011311810726338.860440
A3112.568.0198430266.0981059123038.156575
A490.166.0150360201.212013110925934.832495
A599.477.0150310201.2971029026036.445635
A689.540.0110320147.51111239922634.828425
A7124.395.0125247187.778787722240.084595
A8155.379.2160300214.679798022738.4105150
A9162.2100.0205420502.912012411540240.396440
A1096.339.2100395134.112013210825834.835245
A11162.2100.0205420502.9981039337140.8127940
A12102.538.3101295136.113314512117034.834250
\n", "
" ], "text/plain": [ " C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11\n", "Ai \n", "A1 155.3 74.0 340 673 456.0 111 115 106 244 39.8 65440\n", "A2 162.2 79.5 247 639 283.0 113 118 107 263 38.8 60440\n", "A3 112.5 68.0 198 430 266.0 98 105 91 230 38.1 56575\n", "A4 90.1 66.0 150 360 201.2 120 131 109 259 34.8 32495\n", "A5 99.4 77.0 150 310 201.2 97 102 90 260 36.4 45635\n", "A6 89.5 40.0 110 320 147.5 111 123 99 226 34.8 28425\n", "A7 124.3 95.0 125 247 187.7 78 78 77 222 40.0 84595\n", "A8 155.3 79.2 160 300 214.6 79 79 80 227 38.4 105150\n", "A9 162.2 100.0 205 420 502.9 120 124 115 402 40.3 96440\n", "A10 96.3 39.2 100 395 134.1 120 132 108 258 34.8 35245\n", "A11 162.2 100.0 205 420 502.9 98 103 93 371 40.8 127940\n", "A12 102.5 38.3 101 295 136.1 133 145 121 170 34.8 34250" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Load data from CSV\n", "filename = 'dataset_cars.csv'\n", "data = pd.read_csv(filename, index_col = 'Ai')\n", "# Load decision matrix from CSV\n", "df_data = data.iloc[:len(data) - 1, :]\n", "# Criteria types are in the last row of CSV\n", "types = data.iloc[len(data) - 1, :].to_numpy()\n", "\n", "# Convert decision matrix from dataframe to numpy ndarray type for faster calculations.\n", "matrix = df_data.to_numpy()\n", "\n", "# Symbols for alternatives Ai\n", "list_alt_names = [r'$A_{' + str(i) + '}$' for i in range(1, df_data.shape[0] + 1)]\n", "# Symbols for columns Cj\n", "cols = [r'$C_{' + str(j) + '}$' for j in range(1, data.shape[1] + 1)]\n", "print('Decision matrix')\n", "df_data" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Criteria types\n" ] }, { "data": { "text/plain": [ "array([ 1., 1., 1., 1., 1., 1., 1., 1., 1., -1., -1.])" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "print('Criteria types')\n", "types" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Objective weighting methods" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Calculate the weights with the selected weighing method. In this case, the Entropy weighting method (entropy_weighting) is selected." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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$C_{1}$$C_{2}$$C_{3}$$C_{4}$$C_{5}$$C_{6}$$C_{7}$$C_{8}$$C_{9}$$C_{10}$$C_{11}$
Weights0.0577410.0998430.1426730.0964880.2360870.0245440.0324320.0181260.0539580.0038630.234244
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" ], "text/plain": [ " $C_{1}$ $C_{2}$ $C_{3}$ $C_{4}$ $C_{5}$ $C_{6}$ $C_{7}$ \\\n", "Weights 0.057741 0.099843 0.142673 0.096488 0.236087 0.024544 0.032432 \n", "\n", " $C_{8}$ $C_{9}$ $C_{10}$ $C_{11}$ \n", "Weights 0.018126 0.053958 0.003863 0.234244 " ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "weights = mcda_weights.entropy_weighting(matrix)\n", "df_weights = pd.DataFrame(weights.reshape(1, -1), index = ['Weights'], columns = cols)\n", "df_weights" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Use the VIKOR method to determine the value of the preference function (pref) and the ranking of alternatives (rank). The VIKOR method ranks alternatives ascendingly according to preference function values, so the reverse parameter in the `rank_preferences` method is set to False." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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PrefRank
$A_{1}$0.0000001
$A_{2}$0.3251542
$A_{3}$0.5310504
$A_{4}$0.6822585
$A_{5}$0.7341627
$A_{6}$0.92209110
$A_{7}$0.8848289
$A_{8}$0.8217738
$A_{9}$0.3326003
$A_{10}$0.94046011
$A_{11}$0.6964346
$A_{12}$0.95483212
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" ], "text/plain": [ " Pref Rank\n", "$A_{1}$ 0.000000 1\n", "$A_{2}$ 0.325154 2\n", "$A_{3}$ 0.531050 4\n", "$A_{4}$ 0.682258 5\n", "$A_{5}$ 0.734162 7\n", "$A_{6}$ 0.922091 10\n", "$A_{7}$ 0.884828 9\n", "$A_{8}$ 0.821773 8\n", "$A_{9}$ 0.332600 3\n", "$A_{10}$ 0.940460 11\n", "$A_{11}$ 0.696434 6\n", "$A_{12}$ 0.954832 12" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Create the VIKOR method object\n", "vikor = VIKOR(normalization_method=norm_methods.minmax_normalization)\n", "\n", "# Calculate alternatives preference function values with VIKOR method\n", "pref = vikor(matrix, weights, types)\n", "\n", "# rank alternatives according to preference values\n", "rank = rank_preferences(pref, reverse = False)\n", "df_results = pd.DataFrame(index = list_alt_names)\n", "df_results['Pref'] = pref\n", "df_results['Rank'] = rank\n", "df_results" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The second part of the manual contains codes for benchmarking against several different criteria weighting methods. List the weighting methods you wish to explore." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "# Create a list with weighting methods that you want to explore\n", "weighting_methods_set = [\n", " mcda_weights.entropy_weighting,\n", " #mcda_weights.std_weighting,\n", " mcda_weights.critic_weighting,\n", " mcda_weights.gini_weighting,\n", " mcda_weights.merec_weighting,\n", " mcda_weights.stat_var_weighting,\n", " #mcda_weights.cilos_weighting,\n", " mcda_weights.idocriw_weighting,\n", " mcda_weights.angle_weighting,\n", " mcda_weights.coeff_var_weighting\n", "]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Below is a loop with code to collect results for each weighting technique. Then display the results, namely weights, preference function values and rankings." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "df_weights = pd.DataFrame(index = cols)\n", "df_preferences = pd.DataFrame(index = list_alt_names)\n", "df_rankings = pd.DataFrame(index = list_alt_names)\n", "\n", "# Create dataframes for weights, preference function values and rankings determined using different weighting methods\n", "df_weights = pd.DataFrame(index = cols)\n", "df_preferences = pd.DataFrame(index = list_alt_names)\n", "df_rankings = pd.DataFrame(index = list_alt_names)\n", "\n", "# Create the VIKOR method object\n", "vikor = VIKOR()\n", "for weight_type in weighting_methods_set:\n", " \n", " if weight_type.__name__ in [\"cilos_weighting\", \"idocriw_weighting\", \"angle_weighting\", \"merec_weighting\"]:\n", " weights = weight_type(matrix, types)\n", " else:\n", " weights = weight_type(matrix)\n", " \n", " df_weights[weight_type.__name__[:-10].upper().replace('_', ' ')] = weights\n", " pref = vikor(matrix, weights, types)\n", " rank = rank_preferences(pref, reverse = False)\n", " df_preferences[weight_type.__name__[:-10].upper().replace('_', ' ')] = pref\n", " df_rankings[weight_type.__name__[:-10].upper().replace('_', ' ')] = rank" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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ENTROPYCRITICGINIMERECSTAT VARIDOCRIWANGLECOEFF VAR
$C_{1}$0.0577410.0939600.0808820.0673630.1438550.0893620.0817320.079378
$C_{2}$0.0998430.0992770.1038000.1251950.1039760.0764050.1030020.101129
$C_{3}$0.1426730.0661320.1282020.1034890.0673080.0942710.1297020.129595
$C_{4}$0.0964880.0758740.1032000.0930500.0766650.0795720.1083790.106746
$C_{5}$0.2360870.0711950.1635130.1245810.1128800.1542350.1623540.166788
$C_{6}$0.0245440.1128650.0523080.0648860.0743610.0718760.0531450.051074
$C_{7}$0.0324320.1206020.0603880.0771070.0739250.0768220.0607390.058510
$C_{8}$0.0181260.1035360.0461880.0537080.0761500.0694180.0460610.044183
$C_{9}$0.0539580.0655140.0730990.0871090.0605650.0397020.0816910.079337
$C_{10}$0.0038630.0984320.0211510.0185660.1260250.0170620.0217110.020518
$C_{11}$0.2342440.0926120.1672700.1849470.0842890.2312760.1514840.162742
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" ], "text/plain": [ " ENTROPY CRITIC GINI MEREC STAT VAR IDOCRIW \\\n", "$C_{1}$ 0.057741 0.093960 0.080882 0.067363 0.143855 0.089362 \n", "$C_{2}$ 0.099843 0.099277 0.103800 0.125195 0.103976 0.076405 \n", "$C_{3}$ 0.142673 0.066132 0.128202 0.103489 0.067308 0.094271 \n", "$C_{4}$ 0.096488 0.075874 0.103200 0.093050 0.076665 0.079572 \n", "$C_{5}$ 0.236087 0.071195 0.163513 0.124581 0.112880 0.154235 \n", "$C_{6}$ 0.024544 0.112865 0.052308 0.064886 0.074361 0.071876 \n", "$C_{7}$ 0.032432 0.120602 0.060388 0.077107 0.073925 0.076822 \n", "$C_{8}$ 0.018126 0.103536 0.046188 0.053708 0.076150 0.069418 \n", "$C_{9}$ 0.053958 0.065514 0.073099 0.087109 0.060565 0.039702 \n", "$C_{10}$ 0.003863 0.098432 0.021151 0.018566 0.126025 0.017062 \n", "$C_{11}$ 0.234244 0.092612 0.167270 0.184947 0.084289 0.231276 \n", "\n", " ANGLE COEFF VAR \n", "$C_{1}$ 0.081732 0.079378 \n", "$C_{2}$ 0.103002 0.101129 \n", "$C_{3}$ 0.129702 0.129595 \n", "$C_{4}$ 0.108379 0.106746 \n", "$C_{5}$ 0.162354 0.166788 \n", "$C_{6}$ 0.053145 0.051074 \n", "$C_{7}$ 0.060739 0.058510 \n", "$C_{8}$ 0.046061 0.044183 \n", "$C_{9}$ 0.081691 0.079337 \n", "$C_{10}$ 0.021711 0.020518 \n", "$C_{11}$ 0.151484 0.162742 " ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_weights" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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ENTROPYCRITICGINIMERECSTAT VARIDOCRIWANGLECOEFF VAR
$A_{1}$0.0000000.1933240.0000000.0000000.2104770.0000000.0000000.000000
$A_{2}$0.3251540.0538630.2677840.0966020.0627290.1000570.2901310.285029
$A_{3}$0.5310500.3519730.5192850.3538530.4421860.3328130.5444290.535374
$A_{4}$0.6822580.3844200.6296190.3761150.7059290.3532780.6561960.650874
$A_{5}$0.7341620.4491210.7130590.4854360.6807680.4733330.7378800.731601
$A_{6}$0.9220910.5583230.8799330.6198880.8568150.5495590.9057040.901084
$A_{7}$0.8848281.0000000.8690110.6622080.7106090.6576400.8887080.885934
$A_{8}$0.8217730.9207430.7868660.8093770.4353390.7981930.7971430.796411
$A_{9}$0.3326000.2237870.2895560.2554990.2632610.3015150.2568220.278596
$A_{10}$0.9404600.4902340.8680500.5807550.6770000.5285580.8901870.889102
$A_{11}$0.6964340.4934010.6767740.6829020.5067720.7322540.6132630.652189
$A_{12}$0.9548320.4536660.8699300.5855750.5448420.4950330.8966130.895689
\n", "
" ], "text/plain": [ " ENTROPY CRITIC GINI MEREC STAT VAR IDOCRIW \\\n", "$A_{1}$ 0.000000 0.193324 0.000000 0.000000 0.210477 0.000000 \n", "$A_{2}$ 0.325154 0.053863 0.267784 0.096602 0.062729 0.100057 \n", "$A_{3}$ 0.531050 0.351973 0.519285 0.353853 0.442186 0.332813 \n", "$A_{4}$ 0.682258 0.384420 0.629619 0.376115 0.705929 0.353278 \n", "$A_{5}$ 0.734162 0.449121 0.713059 0.485436 0.680768 0.473333 \n", "$A_{6}$ 0.922091 0.558323 0.879933 0.619888 0.856815 0.549559 \n", "$A_{7}$ 0.884828 1.000000 0.869011 0.662208 0.710609 0.657640 \n", "$A_{8}$ 0.821773 0.920743 0.786866 0.809377 0.435339 0.798193 \n", "$A_{9}$ 0.332600 0.223787 0.289556 0.255499 0.263261 0.301515 \n", "$A_{10}$ 0.940460 0.490234 0.868050 0.580755 0.677000 0.528558 \n", "$A_{11}$ 0.696434 0.493401 0.676774 0.682902 0.506772 0.732254 \n", "$A_{12}$ 0.954832 0.453666 0.869930 0.585575 0.544842 0.495033 \n", "\n", " ANGLE COEFF VAR \n", "$A_{1}$ 0.000000 0.000000 \n", "$A_{2}$ 0.290131 0.285029 \n", "$A_{3}$ 0.544429 0.535374 \n", "$A_{4}$ 0.656196 0.650874 \n", "$A_{5}$ 0.737880 0.731601 \n", "$A_{6}$ 0.905704 0.901084 \n", "$A_{7}$ 0.888708 0.885934 \n", "$A_{8}$ 0.797143 0.796411 \n", "$A_{9}$ 0.256822 0.278596 \n", "$A_{10}$ 0.890187 0.889102 \n", "$A_{11}$ 0.613263 0.652189 \n", "$A_{12}$ 0.896613 0.895689 " ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_preferences" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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ENTROPYCRITICGINIMERECSTAT VARIDOCRIWANGLECOEFF VAR
$A_{1}$12112111
$A_{2}$21221233
$A_{3}$44445444
$A_{4}$555510565
$A_{5}$76769677
$A_{6}$10101291291212
$A_{7}$9121010111099
$A_{8}$81181241288
$A_{9}$33333322
$A_{10}$11897881010
$A_{11}$6961161156
$A_{12}$127118771111
\n", "
" ], "text/plain": [ " ENTROPY CRITIC GINI MEREC STAT VAR IDOCRIW ANGLE COEFF VAR\n", "$A_{1}$ 1 2 1 1 2 1 1 1\n", "$A_{2}$ 2 1 2 2 1 2 3 3\n", "$A_{3}$ 4 4 4 4 5 4 4 4\n", "$A_{4}$ 5 5 5 5 10 5 6 5\n", "$A_{5}$ 7 6 7 6 9 6 7 7\n", "$A_{6}$ 10 10 12 9 12 9 12 12\n", "$A_{7}$ 9 12 10 10 11 10 9 9\n", "$A_{8}$ 8 11 8 12 4 12 8 8\n", "$A_{9}$ 3 3 3 3 3 3 2 2\n", "$A_{10}$ 11 8 9 7 8 8 10 10\n", "$A_{11}$ 6 9 6 11 6 11 5 6\n", "$A_{12}$ 12 7 11 8 7 7 11 11" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_rankings" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Visualize the results as column graphs of weights, rankings, and correlations." ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "The PostScript backend does not support transparency; partially transparent artists will be rendered opaque.\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plot_barplot(df_weights, 'Weighting methods', 'Weight value', 'Criteria')" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plot_boxplot(df_weights.T)" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "The PostScript backend does not support transparency; partially transparent artists will be rendered opaque.\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plot_barplot(df_rankings, 'Alternatives', 'Rank', 'Weighting methods')" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "results = copy.deepcopy(df_rankings)\n", "method_types = list(results.columns)\n", "dict_new_heatmap_rw = Create_dictionary()\n", "\n", "for el in method_types:\n", " dict_new_heatmap_rw.add(el, [])\n", "\n", "# heatmaps for correlations coefficients\n", "for i, j in [(i, j) for i in method_types[::-1] for j in method_types]:\n", " dict_new_heatmap_rw[j].append(corrs.weighted_spearman(results[i], results[j]))\n", "\n", "df_new_heatmap_rw = pd.DataFrame(dict_new_heatmap_rw, index = method_types[::-1])\n", "df_new_heatmap_rw.columns = method_types\n", "\n", "# correlation matrix with rw coefficient\n", "draw_heatmap(df_new_heatmap_rw, r'$r_w$')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Stochastic Multicriteria Acceptability Analysis Method (SMAA)" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": [ "cols_ai = [str(el) for el in range(1, matrix.shape[0] + 1)]" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": [ "# criteria number\n", "n = matrix.shape[1]\n", "# number of SMAA iterations\n", "iterations = 10000" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": [ "# create the VIKOR_SMAA method object\n", "vikor_smaa = VIKOR_SMAA()\n", "# generate multiple weight vectors in matrix\n", "weight_vectors = vikor_smaa._generate_weights(n, iterations)" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [], "source": [ "# Calculate the rank acceptability index, central weight vector and final ranking\n", "rank_acceptability_index, central_weight_vector, rank_scores = vikor_smaa(matrix, weight_vectors, types)" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [], "source": [ "acc_in_df = pd.DataFrame(rank_acceptability_index, index = list_alt_names, columns = cols_ai)\n", "acc_in_df.to_csv('results_smaa/ai.csv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Rank acceptability indexes\n", "This is dataframe with rank acceptability indexes for each alternative in relation to ranks. Rank acceptability index shows the share of different scores placing an alternative in a given rank." ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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$A_{1}$0.23950.24990.18470.13410.05400.05320.02400.04410.01280.00370.00000.0000
$A_{2}$0.22070.35760.22520.11550.04050.03510.00540.00000.00000.00000.00000.0000
$A_{3}$0.00020.01020.02490.07230.29240.14290.15160.13590.15890.01070.00000.0000
$A_{4}$0.10630.06600.07490.13860.16660.22960.07970.03750.03030.03480.03570.0000
$A_{5}$0.00050.01170.01420.02180.07430.10690.25640.14030.13110.22300.01980.0000
$A_{6}$0.00000.00090.00740.04190.02420.03640.13180.11580.15240.16300.14180.1844
$A_{7}$0.00000.00000.00070.00130.00610.03140.03440.03420.08880.07660.09000.6365
$A_{8}$0.00000.00240.00250.00550.06430.04380.05740.14690.07710.11910.44160.0394
$A_{9}$0.38590.10730.28180.04160.03120.02840.02240.01680.06440.02020.00000.0000
$A_{10}$0.00950.03570.06810.07070.08580.15970.09980.06980.14910.15120.08890.0117
$A_{11}$0.00000.10770.07990.30250.06880.05380.05530.09420.02140.07730.10010.0390
$A_{12}$0.03740.05060.03570.05420.09180.07880.08180.16450.11370.12040.08210.0890
\n", "
" ], "text/plain": [ " 1 2 3 4 5 6 7 8 \\\n", "$A_{1}$ 0.2395 0.2499 0.1847 0.1341 0.0540 0.0532 0.0240 0.0441 \n", "$A_{2}$ 0.2207 0.3576 0.2252 0.1155 0.0405 0.0351 0.0054 0.0000 \n", "$A_{3}$ 0.0002 0.0102 0.0249 0.0723 0.2924 0.1429 0.1516 0.1359 \n", "$A_{4}$ 0.1063 0.0660 0.0749 0.1386 0.1666 0.2296 0.0797 0.0375 \n", "$A_{5}$ 0.0005 0.0117 0.0142 0.0218 0.0743 0.1069 0.2564 0.1403 \n", "$A_{6}$ 0.0000 0.0009 0.0074 0.0419 0.0242 0.0364 0.1318 0.1158 \n", "$A_{7}$ 0.0000 0.0000 0.0007 0.0013 0.0061 0.0314 0.0344 0.0342 \n", "$A_{8}$ 0.0000 0.0024 0.0025 0.0055 0.0643 0.0438 0.0574 0.1469 \n", "$A_{9}$ 0.3859 0.1073 0.2818 0.0416 0.0312 0.0284 0.0224 0.0168 \n", "$A_{10}$ 0.0095 0.0357 0.0681 0.0707 0.0858 0.1597 0.0998 0.0698 \n", "$A_{11}$ 0.0000 0.1077 0.0799 0.3025 0.0688 0.0538 0.0553 0.0942 \n", "$A_{12}$ 0.0374 0.0506 0.0357 0.0542 0.0918 0.0788 0.0818 0.1645 \n", "\n", " 9 10 11 12 \n", "$A_{1}$ 0.0128 0.0037 0.0000 0.0000 \n", "$A_{2}$ 0.0000 0.0000 0.0000 0.0000 \n", "$A_{3}$ 0.1589 0.0107 0.0000 0.0000 \n", "$A_{4}$ 0.0303 0.0348 0.0357 0.0000 \n", "$A_{5}$ 0.1311 0.2230 0.0198 0.0000 \n", "$A_{6}$ 0.1524 0.1630 0.1418 0.1844 \n", "$A_{7}$ 0.0888 0.0766 0.0900 0.6365 \n", "$A_{8}$ 0.0771 0.1191 0.4416 0.0394 \n", "$A_{9}$ 0.0644 0.0202 0.0000 0.0000 \n", "$A_{10}$ 0.1491 0.1512 0.0889 0.0117 \n", "$A_{11}$ 0.0214 0.0773 0.1001 0.0390 \n", "$A_{12}$ 0.1137 0.1204 0.0821 0.0890 " ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "acc_in_df" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Rank acceptability indexes displayed in the form of stacked bar chart." ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "The PostScript backend does not support transparency; partially transparent artists will be rendered opaque.\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "matplotlib.rcdefaults()\n", "plot_barplot(acc_in_df, 'Alternative', 'Rank acceptability index', 'Rank')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Rank acceptability indexes displayed in the form of heatmap" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "draw_heatmap_smaa(acc_in_df, 'Rank acceptability indexes')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Central weight vector\n", "The central weight vector describes the preferences of a typical decision-maker, supporting this alternative with the assumed preference model. It allows the decision-maker to see what criteria preferences result in the best evaluation of given alternatives. Rows containing only zeroes mean that a given alternative never becomes a leader." ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [], "source": [ "central_weights_df = pd.DataFrame(central_weight_vector, index = list_alt_names, columns = cols)\n", "central_weights_df.to_csv('results_smaa/cw.csv')" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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$C_{1}$$C_{2}$$C_{3}$$C_{4}$$C_{5}$$C_{6}$$C_{7}$$C_{8}$$C_{9}$$C_{10}$$C_{11}$
$A_{1}$0.0855570.0688520.1635670.1277210.1209780.0743110.0730520.0798220.0556290.0533720.097139
$A_{2}$0.1195050.0911970.0767900.1238500.0561690.0804980.0806110.0790160.0718700.1097970.110698
$A_{3}$0.0254810.0240650.1937220.1168420.1529550.0394040.0320340.0208950.0053100.2683070.120985
$A_{4}$0.0438950.0857920.0666430.0564970.0658950.0847700.0922580.0843030.0815210.2063660.132060
$A_{5}$0.0417010.2832980.0350200.0577310.0510690.0467570.0373620.0320760.1002420.2431140.071629
$A_{6}$0.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.000000
$A_{7}$0.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.000000
$A_{8}$0.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.000000
$A_{9}$0.0969950.1159520.0661200.0619430.1050550.1015780.0999290.1042950.1325370.0558600.059736
$A_{10}$0.0562990.0308170.0415810.1502710.0452650.0872090.1076150.0808660.0734990.2270220.099554
$A_{11}$0.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.0000000.000000
$A_{12}$0.0741290.0384180.0443760.0448030.0440550.1476040.1698260.1321900.0383410.1445660.121692
\n", "
" ], "text/plain": [ " $C_{1}$ $C_{2}$ $C_{3}$ $C_{4}$ $C_{5}$ $C_{6}$ \\\n", "$A_{1}$ 0.085557 0.068852 0.163567 0.127721 0.120978 0.074311 \n", "$A_{2}$ 0.119505 0.091197 0.076790 0.123850 0.056169 0.080498 \n", "$A_{3}$ 0.025481 0.024065 0.193722 0.116842 0.152955 0.039404 \n", "$A_{4}$ 0.043895 0.085792 0.066643 0.056497 0.065895 0.084770 \n", "$A_{5}$ 0.041701 0.283298 0.035020 0.057731 0.051069 0.046757 \n", "$A_{6}$ 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", "$A_{7}$ 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", "$A_{8}$ 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", "$A_{9}$ 0.096995 0.115952 0.066120 0.061943 0.105055 0.101578 \n", "$A_{10}$ 0.056299 0.030817 0.041581 0.150271 0.045265 0.087209 \n", "$A_{11}$ 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n", "$A_{12}$ 0.074129 0.038418 0.044376 0.044803 0.044055 0.147604 \n", "\n", " $C_{7}$ $C_{8}$ $C_{9}$ $C_{10}$ $C_{11}$ \n", "$A_{1}$ 0.073052 0.079822 0.055629 0.053372 0.097139 \n", "$A_{2}$ 0.080611 0.079016 0.071870 0.109797 0.110698 \n", "$A_{3}$ 0.032034 0.020895 0.005310 0.268307 0.120985 \n", "$A_{4}$ 0.092258 0.084303 0.081521 0.206366 0.132060 \n", "$A_{5}$ 0.037362 0.032076 0.100242 0.243114 0.071629 \n", "$A_{6}$ 0.000000 0.000000 0.000000 0.000000 0.000000 \n", "$A_{7}$ 0.000000 0.000000 0.000000 0.000000 0.000000 \n", "$A_{8}$ 0.000000 0.000000 0.000000 0.000000 0.000000 \n", "$A_{9}$ 0.099929 0.104295 0.132537 0.055860 0.059736 \n", "$A_{10}$ 0.107615 0.080866 0.073499 0.227022 0.099554 \n", "$A_{11}$ 0.000000 0.000000 0.000000 0.000000 0.000000 \n", "$A_{12}$ 0.169826 0.132190 0.038341 0.144566 0.121692 " ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "central_weights_df" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Rank scores" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [], "source": [ "rank_scores_df = pd.DataFrame(rank_scores, index = list_alt_names, columns = ['Rank'])\n", "rank_scores_df.to_csv('results_smaa/fr.csv')" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Rank
$A_{1}$3
$A_{2}$1
$A_{3}$6
$A_{4}$4
$A_{5}$9
$A_{6}$10
$A_{7}$12
$A_{8}$11
$A_{9}$2
$A_{10}$7
$A_{11}$5
$A_{12}$8
\n", "
" ], "text/plain": [ " Rank\n", "$A_{1}$ 3\n", "$A_{2}$ 1\n", "$A_{3}$ 6\n", "$A_{4}$ 4\n", "$A_{5}$ 9\n", "$A_{6}$ 10\n", "$A_{7}$ 12\n", "$A_{8}$ 11\n", "$A_{9}$ 2\n", "$A_{10}$ 7\n", "$A_{11}$ 5\n", "$A_{12}$ 8" ] }, "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ "rank_scores_df" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Subjective weighting methods" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The illustrative example concerns the multi-criteria problem involving a selection of four alternative sites in Poland for wind farm location regarding ten criteria assessment. The data for this problem used in the procedure for determining the criteria weights in this example and the data on the performance of the alternatives against the evaluation criteria were acquired from the research paper https://doi.org/10.3390/su8080702" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "# Load data from csv file\n", "data = pd.read_csv('./dataset_localisations.csv', index_col='Symbol')\n", "\n", "# decision matrix with alternatives' performance values\n", "df_data = data.iloc[:len(data) - 1, :]\n", "\n", "# Criteria types\n", "types = data.iloc[len(data) - 1, :].to_numpy()\n", "\n", "# Decision matrix in numpy.ndarray data type required by methods implemented in crispyn package\n", "matrix = df_data.to_numpy()\n", "\n", "# Column names\n", "cols = [r'$C_{' + str(j) + '}$' for j in range(1, matrix.shape[1] + 1)]\n", "\n", "# Dataframe for weight values determined by different weighting methods\n", "df_weights = pd.DataFrame(index = cols)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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C1C2C3C4C5C6C7C8C9C10
Symbol
A11067806.7522206152455.58.936.8
A2863707.12340010020336.57.229.8
A31048506.95602207160416.08.736.2
A4466006.0412203050277.03.916.0
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" ], "text/plain": [ " C1 C2 C3 C4 C5 C6 C7 C8 C9 C10\n", "Symbol \n", "A1 106780 6.75 2 220 6 1 52 455.5 8.9 36.8\n", "A2 86370 7.12 3 400 10 0 20 336.5 7.2 29.8\n", "A3 104850 6.95 60 220 7 1 60 416.0 8.7 36.2\n", "A4 46600 6.04 1 220 3 0 50 277.0 3.9 16.0" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### AHP weighting method" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Construct matrix with criteria pairwise comparison as `numpy.ndarray` type" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "PCcriteria_ahp = np.array([\n", " [1, 2, 2, 2, 6, 2, 1, 1, 1/2, 1/2],\n", " [1/2, 1, 1, 1, 4, 1, 1, 1, 1/2, 1/2],\n", " [1/2, 1, 1, 1, 3, 1, 1/2, 1/2, 1/3, 1/3],\n", " [1/2, 1, 1, 1, 3, 1, 1/2, 1/2, 1/3, 1/3],\n", " [1/6, 1/4, 1/3, 1/3, 1, 1/3, 1/5, 1/5, 1/9, 1/9],\n", " [1/2, 1, 1, 1, 3, 1, 1/2, 1/2, 1/3, 1/3],\n", " [1, 1, 2, 2, 5, 2, 1, 1, 1/2, 1/2],\n", " [1, 1, 2, 2, 5, 2, 1, 1, 1/2, 1/2],\n", " [2, 2, 3, 3, 9, 3, 2, 2, 1, 1],\n", " [2, 2, 3, 3, 9, 3, 2, 2, 1, 1]\n", "])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Calculate AHP weights" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Inconsistency index: 0.006188266444440638\n" ] } ], "source": [ "# Initialize the `AHP_WEIGHTING` method object\n", "ahp_weighting = mcda_weights.AHP_WEIGHTING()\n", "\n", "# Calculate AHP weights passing matrix with criteria pairwise comparison and method of priority vector calculation\n", "weights_ahp = ahp_weighting(X = PCcriteria_ahp, compute_priority_vector_method=ahp_weighting._eigenvector)\n", "\n", "# save calculated AHP weights in dataframe for weights\n", "df_weights['AHP'] = weights_ahp" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([0.11649504, 0.08039711, 0.0614321 , 0.0614321 , 0.02051697,\n", " 0.0614321 , 0.10648668, 0.10648668, 0.1926606 , 0.1926606 ])" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "weights_ahp" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### SWARA weighting method" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Provide vector `criteria_indexes` (numpy.ndarray type) with indexes of criteria in accordance with given decision problem from $C_1$ to $C_n$ ordered in descending order beginning from the most important criterion and vector `s` including values representing how much criterion (j-1) is more significant than criterion j in percentage in range from 0 to 1" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "# criteria ordered in descending order from the most significant\n", "criteria_indexes = np.array([8, 9, 0, 6, 7, 1, 2, 3, 5, 4])\n", "# vector s\n", "s = np.array([0, 0.4, 0.17, 0, 0.2, 0.25, 0, 0, 0.67])\n", "\n", "# Calculate SWARA weights\n", "weights_swara = mcda_weights.swara_weighting(criteria_indexes, s)\n", "\n", "# save calculated AHP weights in dataframe for weights\n", "df_weights['SWARA'] = weights_swara" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### LBWA weighting method" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Construct list with lists (subsets) `criteria_indexes` of grouped and ordered index of criteria according to their significance beginning from the most important within each subset and list with lists containing influence values of criteria within each subset provided in order beginning from the most significant `criteria_values_I`. Then calculate LBWA weights using `lbwa_weighting` function." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "criteria_indexes = [\n", " [8, 9, 0],\n", " [6, 7, 1],\n", " [2, 3, 5],\n", " [],\n", " [],\n", " [],\n", " [],\n", " [],\n", " [],\n", " [4]\n", "]\n", "\n", "criteria_values_I = [\n", " [0, 0, 2],\n", " [1, 1, 2],\n", " [1, 1, 1],\n", " [],\n", " [],\n", " [],\n", " [],\n", " [],\n", " [],\n", " [3]\n", "]\n", "\n", "weights_lbwa = mcda_weights.lbwa_weighting(criteria_indexes, criteria_values_I)\n", "\n", "df_weights['LBWA'] = weights_lbwa" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### SAPEVO weighting method" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Construct matrix with degrees of pairwise criteria comparison in scale from -3 to 3, then calculate criteria weights using `sapevo_weighting` function." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "PCcriteria_sapevo = np.array([\n", " [ 0, 1, 1, 1, 2, 1, 0, 0, -1, -1],\n", " [-1, 0, 0, 0, 1, 0, 0, 0, -1, -1],\n", " [-1, 0, 0, 0, 1, 0, -1, -1, -1, -1],\n", " [-1, 0, 0, 0, 1, 0, -1, -1, -1, -1],\n", " [-2, -1, -1, -1, 0, -1, -2, -2, -3, -3],\n", " [-1, 0, 0, 0, 1, 0, -1, -1, -1, -1],\n", " [ 0, 0, 1, 1, 2, 1, 0, 0, -1, -1],\n", " [ 0, 0, 1, 1, 2, 1, 0, 0, -1, -1],\n", " [ 1, 1, 1, 1, 3, 1, 1, 1, 0, 0],\n", " [ 1, 1, 1, 1, 3, 1, 1, 1, 0, 0]\n", "])\n", "\n", "weights_sapevo = mcda_weights.sapevo_weighting(PCcriteria_sapevo)\n", "\n", "df_weights['SAPEVO'] = weights_sapevo" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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AHPSWARALBWASAPEVO
$C_{1}$0.1164950.1208860.1340930.12500
$C_{2}$0.0803970.0861010.0804560.08750
$C_{3}$0.0614320.0688810.0618890.07500
$C_{4}$0.0614320.0688810.0618890.07500
$C_{5}$0.0205170.0412460.0187110.00000
$C_{6}$0.0614320.0688810.0618890.07500
$C_{7}$0.1064870.1033210.0893960.11875
$C_{8}$0.1064870.1033210.0893960.11875
$C_{9}$0.1926610.1692400.2011400.16250
$C_{10}$0.1926610.1692400.2011400.16250
\n", "
" ], "text/plain": [ " AHP SWARA LBWA SAPEVO\n", "$C_{1}$ 0.116495 0.120886 0.134093 0.12500\n", "$C_{2}$ 0.080397 0.086101 0.080456 0.08750\n", "$C_{3}$ 0.061432 0.068881 0.061889 0.07500\n", "$C_{4}$ 0.061432 0.068881 0.061889 0.07500\n", "$C_{5}$ 0.020517 0.041246 0.018711 0.00000\n", "$C_{6}$ 0.061432 0.068881 0.061889 0.07500\n", "$C_{7}$ 0.106487 0.103321 0.089396 0.11875\n", "$C_{8}$ 0.106487 0.103321 0.089396 0.11875\n", "$C_{9}$ 0.192661 0.169240 0.201140 0.16250\n", "$C_{10}$ 0.192661 0.169240 0.201140 0.16250" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_weights" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Visualize criteria weights calculated with each subjective weighting method in column charts and radar chart." ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "image/png": 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flClT9N5772nt2rXauXOnbDZbbk9BB656rv7cceyc1OHw4cM1YMAAt96NP3H+sNv25Ynj56T+3nrrLdWuXVu+vr567733dP/992v37t0qWrRormI4Ge+5btu5PXZ26+/YsWO6cOGC9u7dq4MHD2rfvn3661//qpo1a+quu+7KVQz7zxzK1faePrYr15GffvpJe/fuVbdu3XJ9/FOnTuV6H548fk7q7/7771d0dLTGjh0rSZoxY4ZbHgR/+PDVXO/DU8fObv3dfvvtKl68uN5++231799fq1ev1rp163I8JjwzKYd/z/U+PHlsd/2WvnTpkoKDg53KgoOD3dMl1iCDXbt2mUaNGpldu3Y5lR86dMgEBAYZSR5/BQQGmUOHDrl8jvv37zdPPPGEqVChgvH39zdly5Y1TZs2NaNGjTL79+/PsP4zzzxjRo4c6fLx0h06dMgEBQZ4vP6CAgNuWf1dvXrVPPDAA+bRRx81aWlpua6/gHxQfwG3sP6u1759e/P555+7fNxDhw6ZoADP119QQO7qz5js1eG2bdtMw4YNTUpKijHGmF69epnXXnstV/UXmE/+DQy8xf8Gprv99tvNqlWrXD7utTr0/Hcw8Ba04W3bthlJ5uDBg47t+vXrZ/7xj3/kqv6C8sF3MCiX37/s1uH1hgwZYrp165arY177/gV6vP6ufQcD8/w7eObMGVO0aFHz8ccfm5SUFPPjjz+a0NBQ85///CdXdRgU5Pk2HBR0a67DP/74o2nRooUpWbKkadu2rXnsscfM6NGjc1V/AUGeb8MBQbe+DWf2W3rbtm2mRIkSTmX9+vUzgwcPzvK4WeUpf8advBwIDw/Xnt27dPr0aU+HotKlSys8PNzl7atWraqZM2e6MaLsCQ8P167dezxeh7eq/tLS0vT444/LZrNpzpw5ub4Lde076D3192cpKSnav3+/y8cNDw/Xrj0Fv/6k7NXhunXrtGfPHlWoUEGSdOHCBfn5+enAgQOaNWtWjo8ZHh6u3V7+b6CPj0+G7ks5ca0OC/53MDv1V6NGDRUqVMjp3z13/Bu4Kx98B29VG06XlpamhQsX6t///neujnnt+7fb4/Un3Zrv4IEDB1S4cGF17dpVklSvXj1FRkZq3bp1atiwoUvHDQ8P165d3tGGpWt1tm7dOsf7yMhI9ezZ0+XjhoeHa88u72vDWalevbouXbqkY8eOOa7VO3fudEu3bJK8HAoPD8/1l6IgSUlJUUpKilJTU5WSkqIrV67I399fvr6+Lu/Tm+rwmWeeUVxcnL7++mv5+bmnuXlL/V24cEGff/65OnTooICAAC1fvlwxMTEaN25crvbrLfUnXXsERY8ePRzv//73v6ty5cr6xz/+4fI+van+zp8/r61bt6pFixay2WyaPHmyzp49q4iIiFzt11vqMP3H9dixY/Xuu+/qt99+0+LFi7VkyZJc7ddb6u96q1evVnJyslse4eFN9VejRg0lJCTok08+UYcOHbRr1y59//33+tvf/par/XpTHf7000+qUaOG0tLSNHnyZKWlpem+++7L1T69qf6kG/+WLlKkiB566CGNHDlS7733nlavXq2ffvpJDz30UK6Py8QruKExY8YoMDBQ06dP19ixYxUYGKh58+Z5OqwC4dChQ5o+fbq2bNmi0qVLO55x9P3333s6tALBZrNp2rRpqlixokqVKqU33nhDCxcuVP369T0dWoERFBSkcuXKOV6BgYEqUqQIs+VmU3JysoYNG6bSpUurXLly+uyzz/TFF1+4ZVytt5g8ebJOnz6t0qVLq127dnrttddyPR7PG82bN089evRw2x8LvUWxYsX00UcfaeTIkQoODtb999+vQYMG6Z577vF0aAXGrFmzHNeQTZs2acWKFZ4OqcC52W/pKVOm6Pjx4ypVqpQGDRqkxYsXq2TJkrk+rs3kpt+JRe3evVs9e/bU/PnzVbNmTU+HAwAAAADZzlO4kwcAAAAAFkKSBwAAAAAWQpIHAAAAABZCkpcJH59r1ZKamurhSAAAAADgmpSUFEn/y1eyQpKXiVKlSkmSe542DwAAAABukJ6flC5d+obrkeRlokSJEipRooS++eYbT4cCAAAAAJKkb775RiVKlLjp45B44EomfHx81LdvX40ZM0ZVqlRRkyZNcvXwbwAAAABwVWpqqrZs2aKvvvpKI0aMuGl3TZ6Tl4W0tDSNGzdOK1euVHJysqfDAQAAAODF/P391b59ew0bNowkL7fi4+N14sQJpaWleToUAAAAAF7Ix8dH5cqVU3BwcLbWJ8kDAAAAAAth4hUAAAAAsBAmXslEWlqajh8/rqJFi8pms3k6HAAAAACQMUYXL15U+fLlbzgujyQvE8ePH1dYWJinwwAAAACADI4cOaKKFStmuZwkLxNFixaVdK3ysju4EZ6TnJysVatWqW3btvL39/d0OEC+QLsAMqJdAM5oEwVPfHy8wsLCHPlKVkjyMpHeRTM4OJgkrwBITk5WUFCQgoOD+QcK+C/aBZAR7QJwRpsouG42pIyJVwAAAADAQkjyAAAAAMBCSPIAAAAAwEJI8gAAAADAQvJVknfp0iWNHDlS9913n0qWLCmbzabZs2dne/vz58+rT58+CgkJUeHChdW6dWtt27Yt7wIGAAAAgHwmXyV5p0+f1quvvqpdu3bpzjvvzNG2aWlpeuCBB7Rw4UL169dPb731lk6ePKlWrVpp3759eRQxAAAAAOQv+eoRCqGhoYqLi1O5cuX0ww8/qHHjxtnedsmSJdqwYYM+/vhjde3aVZL08MMPq0aNGho5cqQWLlyYV2EDAAAAQL6Rr+7k2e12lStXzqVtlyxZorJly6pz586OspCQED388MP65JNPlJSU5K4wAQAAACDfyld38nJj+/btatiwoXx8nPPWJk2aaOrUqdq7d6/q1q2b6bZJSUlOSWB8fLykaw+ITE5Ozrug89jhw4d15swZT4eR55KTk3XgwAFt2bLFax7kWapUKYWHh3s6jAKJdmFNtAnXeUubkGgXyD5vaRfe1iakgt8uspubWCbJi4uLU4sWLTKUh4aGSpKOHz+eZZI3btw4jR49OkP5qlWrFBQU5N5Ab5FTp07puX79lMwdTEvyt9s1ZdIkhYSEeDqUAoV2YV20CdfQJqyNduEa2oW1FfR2kZCQkK31LJPkJSYmym63ZygPCAhwLM/KsGHDNGjQIMf7+Ph4hYWFqW3btgoODnZ/sLfA9u3blZyUpOCXxsovvLKnw4EbpRz+XfGvD1e9evXUoEEDT4dToNAurIk24TrahHXRLlxHu7AuK7SL9B6HN2OZJC8wMDDTcXdXrlxxLM+K3W7PNEH09/cvsLeu/fyufbR+4ZXlX6OWh6NBXvDz8yuw309PoV1YG20i52gT1ke7yDnahfUV5HaR3bjz1cQruZE+M+efpZeVL1/+VocEAAAAALecZZK8+vXra9u2bUpLS3Mq37x5s4KCglSjRg0PRQYAAAAAt06BTPLi4uK0e/dup9llunbtqj/++EPLli1zlJ0+fVoff/yxHnzwwUy7YwIAAACA1eS7MXmTJk3S+fPndfz4cUnSZ599pqNHj0qS+vfvr2LFimnYsGGaM2eOfv/9d1WqVEnStSSvadOmeuKJJ/Trr7+qdOnSmjJlilJTUzOdORMAAAAArCjfJXn//Oc/dejQIcf7ZcuWOe7O9ezZU8WKFct0O19fX33xxRd64YUX9O677yoxMVGNGzfW7Nmzdfvtt9+S2AEAAADA0/Jdknfw4MGbrjN79mzNnj07Q3mJEiU0ffp0TZ8+3f2BAQAAAEABUCDH5AEAAAAAMkeSBwAAAAAWQpIHAAAAABZCkgcAAAAAFkKSBwAAAAAWQpIHAAAAABZCkgcAAAAAFkKSBwAAAAAWQpIHAAAAABZCkgcAAAAAFkKSBwAAAAAWQpIHAAAAABZCkgcAAAAAFkKSBwAAAAAWQpIHAAAAABZCkgcAAAAAFkKSBwAAAAAWQpIHAAAAABZCkgcAAAAAFkKSBwAAAAAWQpIHAAAAABZCkgcAAAAAFkKSBwAAAAAWQpIHAAAAABZCkgcAAAAAFkKSBwAAAAAWQpIHAAAAABZCkgcAAAAAFkKSBwAAAAAWQpIHAAAAABbi5+kAAAAAgPwm5fDvng4BbuZNnylJHgCv403/yHsDPk8A7pSUlCT5+Cj+9eGeDgV5wcfn2mdscSR5ALwGF24L85KLNoC8Z7fbpbQ0PfFEcZUr5+/pcOBGJ04ka9as89c+Y4sjyQPgNbhwW5M3XbQB3DpNmhRW9Rr8u2Il+/Ymadas854O45YgyQPgdbhwW4s3XbQBAMiOfDe7ZlJSkl588UWVL19egYGBioiI0DfffJOtbb/99lu1bt1apUuXVvHixdWkSRPNmzcvjyMGAAAAgPwj3yV5vXv31ttvv63HHntMEydOlK+vr9q1a6f169ffcLtPP/1Ubdu21dWrVzVq1CiNHTtWgYGBio6O1r/+9a9bFD0AAAAAeFa+6q65ZcsWLVq0SOPHj9eQIUMkSdHR0apTp46GDh2qDRs2ZLntpEmTFBoaqjVr1jjGZTzzzDOqWbOmZs+erYEDB96Sc8hvmHXOevhMAQAAcCP5KslbsmSJfH191adPH0dZQECAnnrqKb300ks6cuSIwsLCMt02Pj5eJUqUcBp47+fnp9KlS+d53PkRswhaHDMJAgAAIAv5Ksnbvn27atSooeDgYKfyJk2aSJJ27NiRZZLXqlUrvfnmmxoxYoR69eolm82mhQsX6ocfftBHH310w+MmJSU5/WCOj4+XJCUnJys5OTk3p+Qxvr6+zCJoUekzCfr6+hbY76enpKSkeDoE5KGUlBTaRA6ltwl6CFhP+mdKu8g5rhXWV5DbRXbjzldJXlxcnEJDQzOUp5cdP348y21HjBih33//XWPHjtWYMWMkSUFBQVq6dKkeeuihGx533LhxGj16dIbyVatWKSgoKCenkG8cOHBAErMIWlH6TILr169XXFycp8MpUNLbBayJNpFzu3fvpteHlfn4KCYmhnaRQ1wrrK8gXy8SEhKytV6+SvISExMzfc5RQECAY3lW7Ha7atSooa5du6pz585KTU3V1KlT1bNnT33zzTdq2rRpltsOGzZMgwYNcryPj49XWFiY2rZtm+GuYkGxfft2T4eAPBYVFaUGDRp4OowChXZhbbSJnAsNDaXXh0Wl9/po3bo17SKHuFZYX0G+XqT3OLyZfJXkBQYGZjrO6MqVK47lWenXr582bdqkbdu2ycfn2qShDz/8sO644w79/e9/1+bNm7Pc1m63Z5pc+vv7y9+/YF70/Pzy1UeLPODn51dgv5+eQruwNtpEzqW3CXp9WE96rw/aRc5xrbC+gtwusht3vnqEQmhoaKa3TtPLypcvn+l2V69e1YwZM/TAAw84EjzpWiXcf//9+uGHH3T16tW8CRoAAAAA8pF8leTVr19fe/fuzXAbMv0uXP369TPd7syZM0pJSVFqamqGZcnJyUpLS8t0GQAAAABYTb5K8rp27eoYS5cuKSlJs2bNUkREhGNmzcOHD18bLP5fZcqUUfHixbV8+XKnO3aXLl3SZ599ppo1a96wqycAAAAAWEW+6nQcERGhbt26adiwYTp58qSqVaumOXPm6ODBg5oxY4ZjvejoaK1bt07GGEnXHhcwZMgQvfzyy2ratKmio6OVmpqqGTNm6OjRo5o/f76nTgkAAAAAbql8leRJ0ty5czVixAjNmzdP586dU7169bRy5Uq1aNHihtsNHz5clStX1sSJEzV69GglJSWpXr16WrJkibp06XKLogcAAAAAz8p3SV5AQIDGjx+v8ePHZ7nO2rVrMy1/9NFH9eijj+ZRZAAAAACQ/+WrMXkAAAAAgNwhyQMAAAAACyHJAwAAAAALIckDAAAAAAshyQMAAAAACyHJAwAAAAALIckDAAAAAAvJ1XPyNm3apJiYGJ08eVLPPfecqlevroSEBO3evVs1atRQkSJF3BUnAAAAACAbXLqTd/XqVXXu3FnNmzfX8OHD9e677+rIkSPXdujjo7Zt22rixIluDRQAAAAAcHMuJXkjRozQypUr9f7772vPnj0yxjiWBQQEqFu3bvrkk0/cFiQAAAAAIHtcSvI+/PBDPfvss+rTp49KliyZYXmtWrX022+/5To4AAAAAEDOuJTknTx5UnXr1s1yua+vrxISElwOCgAAAADgGpeSvLCwMO3evTvL5bGxsapWrZrLQQEAAAAAXONSkvfoo4/qgw8+0MaNGx1lNptNkjRt2jR99NFHio6Odk+EAAAAAIBsc+kRCsOHD9emTZvUokUL1apVSzabTQMHDtTZs2d19OhRtWvXTgMHDnR3rAAAAACAm3DpTl6hQoX01VdfadasWapSpYpq1qyppKQk1atXT7Nnz9Znn30mX19fd8cKAAAAALgJlx+GbrPZ1LNnT/Xs2dOd8QAAAAAAcsGlO3kAAAAAgPzJpTt5d999903XsdlsWr16tSu7BwAAAAC4yKUkLy0tzTGbZrrU1FQdOnRIR44cUbVq1VShQgW3BAgAAAAAyD6Xkry1a9dmuWzlypXq06eP3n77bVdjAgAAAAC4yOWJV7LSvn179ezZUwMGDNC6devcvXsAAAAgzx0+fNXTIcDNvOkzdXuSJ0lVq1bVpEmT8mLXAAAAQJ5JSkqSj480btwpT4eCPODjc+0ztjq3J3kpKSn66KOPVLp0aXfvGgAAAMhTdrtdaWlS69atVaJECU+HAzc6d+6cYmJiZLfbPR1KnnMpyXvyySczLT9//rw2bdqkEydOMCYPQL7lTd01vAGfJ4C8UL16dYWGhno6DLhRXFycYmJiPB3GLeFSkrdmzZoMs2vabDaVKFFCUVFR+r//+z+1bdvWLQECgLvQBce6vKX7DQAA2eFSknfw4EE3hwEAeY8uONbkTd1vAADIjjyZeAUA8jO64FiLN3W/AQAgO7KV5H333Xcu7bxFixYubQcAAAAAcE22krxWrVplGIN3I8YY2Ww2paamuhwYAAAAACDnspXk0Q0GAAAAAAqGbCV5LVu2zOs4AAAAAABu4OPpAAAAAAAA7uPy7JpXrlzR0qVLtW3bNl24cEFpaWlOy202m2bMmJHrAAEAAAAA2edSknfo0CG1bt1aBw8eVPHixXXhwgWVLFlS58+fV2pqqkqXLq0iRYq4O1YAAAAAwE24lOS98MILunDhgjZt2qQqVaqoTJkyWrx4sZo3b653331XkyZN0tdff+1SQElJSXrllVc0b948nTt3TvXq1dOYMWPUpk2bbG2/ePFivfPOO/rpp5/k7++v2rVra8yYMbr77rtdiqegO3z4qqdDgJvxmQIAAOBGXEry1qxZo+eee05NmjTR2bNnJV17bILdbtcLL7ygXbt2acCAAfr8889zvO/evXtryZIlGjBggKpXr67Zs2erXbt2iomJUVRU1A23HTVqlF599VV17dpVvXv3VnJysnbu3Kljx465cpoFWlJSknx8pHHjTnk6FOQBH59rnzEAAADwZy4leQkJCapUqZIkKTg4WDabTRcuXHAsb9asmYYMGZLj/W7ZskWLFi3S+PHjHdtHR0erTp06Gjp0qDZs2JDltps2bdKrr76qCRMmaODAgTk+ttXY7XalpUmtW7dWiRIlPB0O3OjcuXOKiYmR3W73dCgAAADIh1xK8sLDw3X06NFrO/DzU4UKFbRp0yZ17txZkvTrr78qICAgx/tdsmSJfH191adPH0dZQECAnnrqKb300ks6cuSIwsLCMt32nXfeUbly5fT3v/9dxhhdvnyZcYGSqlevrtDQUE+HATeKi4vj2ZUAAADIkktJ3t13361PPvlEI0eOlHSti+W4ceN07tw5paWlad68eYqOjs7xfrdv364aNWooODjYqbxJkyaSpB07dmSZ5K1evVqRkZF69913NWbMGJ05c0blypXT8OHD1a9fvxseNykpyanrW3x8vCQpOTlZycnJOT6P/CAlJcXTISCPpaSkFNjvp6fQLqyNNpFz6W2Csb7Wk/6Z0i5yjmuF9RXkdpHduF1K8v7xj39o69atSkpKkt1u10svvaTjx4877sQ9+uijevvtt3O837i4uEzvOqWXHT9+PNPtzp07p9OnTys2NlZr1qzRyJEjFR4erlmzZql///7y9/fXM888k+Vxx40bp9GjR2coX7VqlYKCgnJ8HvnBgQMHPB0C8tj69esVFxfn6TAKFNqFtdEmcm737t2M37YwHx8pJiaGdpFDXCusryBfLxISErK1nsvdNcPDwx3vAwICNH36dE2fPt2V3TkkJiZmOs4ovetnYmJipttdunRJknTmzBktWrRI3bt3lyR17dpVdevW1ZgxY26Y5A0bNkyDBg1yvI+Pj1dYWJjatm2b4a5iQbF9+3ZPh4A8FhUVpQYNGng6jAKFdmFttImcCw0NZfy2RaWP327dujXtIoe4VlhfQb5epPc4vBmXkrwvvvhC9957r3x9fV3ZPEuBgYGZzhh45coVx/KstpMkf39/de3a1VHu4+Oj7t27a+TIkTp8+LBTYno9u92eaXLp7+8vf3//HJ9HfuDn5/Jz7lFA+Pn5Fdjvp6fQLqyNNpFz6W2C8dvWkz5+m3aRc1wrrK8gt4vsxu3jys7bt2+vsmXLqk+fPlq9erXS0tJc2U0GoaGhmd46TS8rX758ptuVLFlSAQEBKlWqVIbEs0yZMpKu/UULAAAAAKzOpSTvyy+/VIcOHbRkyRK1bdtWoaGh6tu3r77//vtcBVO/fn3t3bs3w23IzZs3O5ZnxsfHR/Xr19epU6d09arz4PH0cXwhISG5ig0AAAAACgKXkrx7771XM2fO1B9//KFPPvlEbdu21YIFC9SqVStVrFhRAwYM0MaNG3O8365duyo1NVVTp051lCUlJWnWrFmKiIhwzKx5+PBh7d6922nb7t27KzU1VXPmzHGUXblyRQsWLFDt2rWzvAsIAAAAAFaSq07H/v7+at++vdq3b6+rV6/qyy+/1OLFizV9+nRNmjQpx1PQRkREqFu3bho2bJhOnjypatWqac6cOTp48KBmzJjhWC86Olrr1q2TMcZR9swzz2j69Onq27ev9u7dq/DwcM2bN0+HDh3SZ599lpvTBAAAAIACw20jSy9duqSTJ0/qjz/+0JUrV5wSsJyYO3euRowYoXnz5uncuXOqV6+eVq5cqRYtWtxwu8DAQK1Zs0ZDhw7VzJkzdfnyZdWvX1+ff/657r33XpdiAQAAAICCJldJ3oULF7Rs2TItXrxYMTExSk5OVt26dfXqq686HmOQUwEBARo/frzGjx+f5Tpr167NtLxMmTKaPXu2S8cFAAAAACtwKcmbN2+ePvroI33zzTe6evWqatasqZdeekndu3dXzZo13R0jALjVqVM8+NlK+DwBAHDmUpLXq1cvValSRYMHD1b37t1Vr149d8cFAG6XlJQkm82m5cuXezoUuJnNZsv0OasA4Cr+gGQ93vSZupTkbd26VY0aNXJ3LACQp+x2u4wxeuGupxRWjAc/W8WRC3Ea//0M2e12T4cCwAL4g6C1ecsfBV1K8kjwABRkras0Vd1yt3s6DLjJzyf2aPz3M26+IgBkA38QtC5v+qOg22bXBAAAAKyCPwhajzf9UdClh6EDAAAAAPInkjwAAAAAsBCSPAAAAACwEJeSvFdffVU7d+7Mcvkvv/yiV1991eWgAAAAAACucSnJGzVqlH766acsl+/cuVOjR492OSgAAAAAgGvypLvm2bNnVahQobzYNQAAAADgBrL9CIXvvvtOa9eudbxftmyZ9u/fn2G98+fPa/Hixapbt65bAgQAAAAAZF+2k7yYmBhHF0ybzaZly5Zp2bJlma5bu3Ztvffee+6JELly6tQpT4cAN+MzBeBu/LtiPXymgHfLdpI3dOhQ9evXT8YYlSlTRv/+97/VpUsXp3VsNpuCgoIUEBDg9kCRM0lJSbLZbFq+fLmnQ0EesNlsSkpK8nQYAAo4rhXWxrUC8F7ZTvICAwMVGBgoSfr9998VEhKioKCgPAsMuWO322WM0Qt3PaWwYqGeDgdudORCnMZ/P0N2u93ToQAo4LhWWBfXCsC7ZTvJu95tt93m7jiQR1pXaaq65W73dBhwo59P7NH472d4OgwAFsK1wnq4VgDezaXZNY0x+uCDD9SkSROVLl1avr6+GV5+fi7ljwAAAACAXHApExs6dKjefvtt1a9fXz179lSJEiXcHRcAAAAAwAUuJXlz5sxRly5d9NFHH7k7HgAAAABALrjUXTMxMVH33HOPu2MBAAAAAOSSS0neX//6V23dutXdsQAAAAAAcsmlJG/KlCnatGmTXn/9dZ05c8bdMQEAAAAAXJStMXlFixaVzWZzKktJSdGIESM0YsQIBQQEyNfX12m5zWbThQsX3BcpAAAAAOCmspXkdenSJUOSBwAAAADIf7KV5M2ePTuPwwAAAAAAuANPLAfgdfafOeTpEOBGfJ4AADhzKcmbO3fuDZfbbDYFBASoYsWKatiwoex2u0vBAYA7JSUlycfmo+dXjvF0KHAzH5uPkpKSPB0GAAD5gktJXu/evR1j9IwxTsuuL7fZbAoODtawYcM0dOjQXIYKALljt9uVZtJ0X50aKlk4yNPhwE3OXk7QVzv38gdFAAD+y6Ukb8eOHerVq5dKlSqlvn37qlq1apKkffv2afLkyTp//rwmTZqkP/74Q++9956GDRumokWL6tlnn3Vr8ADgipqhZVSxRDFPhwE3OXrugr7audfTYQAAkG+49Jy8f/3rXypbtqy+/fZbderUSXXr1lXdunXVuXNnffvttwoJCdGMGTPUsWNHffPNN2ratKmmTJni7tgBAAAAAH/i0p28FStW6PXXX890mc1mU4cOHfTyyy9r+vTp8vHxUZcuXTR8+PBcBQoAAADcKkzqZD3e9Jm6lOSlpaVpz549WS7fvXu30tLSHO/tdrsCAgJcORQAAABwyzBJl7V5y0RdLiV5HTp00JQpU1StWjX93//9nyOBu3LliqZNm6Z///vf6t69u2P9jRs3OsbtAQAAAPkVk3RZlzdN1OVSkjdx4kQdOHBAzz//vIYMGaLQ0FBJUlxcnK5evaomTZpo4sSJkq4lfoGBgRo0aJD7ogYAAADyEJN0WY83TdTlUpJXsmRJxcbGavny5fr666916NC1/q1t27bVvffeq44dO8rH59qcLgEBAZo2bZr7IgYAAG7lTeNUvAWfKeDdXErypGsTrHTu3FmdO3d2ZzxKSkrSK6+8onnz5uncuXOqV6+exowZozZt2uRoP23atNG3336rvn37atKkSW6NEQAAK2DskbV5y9gjABm5nOTlld69e2vJkiUaMGCAqlevrtmzZ6tdu3aKiYlRVFRUtvaxbNkybdy4MY8jBQCgYGPskXV509gjABllK8mrXLmyfHx8tHv3bvn7+6ty5cqy2Ww33MZms+nAgQM5CmbLli1atGiRxo8fryFDhkiSoqOjVadOHQ0dOlQbNmy46T6uXLmiwYMH68UXX9Qrr7ySo+MDAOCNGHtkPd409ghARtlK8lq2bCmbzeYYZ5f+3t2WLFkiX19f9enTx1EWEBCgp556Si+99JKOHDmisLCwG+7jrbfeUlpamoYMGUKSJ/rkWxGfKQAAAG4kW0ne7Nmzb/jeXbZv364aNWooODjYqbxJkyaSpB07dtwwyTt8+LDeeOMNzZw5U4GBgdk+blJSklOf9fj4eElScnKykpOTc3IK+cbly5cZZ2FhPjYfXb58ucB+Pz0lJSXF0yEgD6WkpNAmcog2YX20i5yjXVhfQW4X2Y07X43Ji4uLczyO4XrpZcePH7/h9oMHD1aDBg3Uo0ePHB133LhxGj16dIbyVatWKSioYI5ROHDgAOMsLCp9nMXWrVt19uxZT4dToOS0CzkKlvXr1ysuLs7TYRQotAnro13kHO3C+gpyu0hISMjWei4nefHx8ZoyZYpiYmJ08uRJffDBB2rSpInOnj2r2bNnq0OHDjl+AHpiYmKmA4TTH7aemJiY5bYxMTFaunSpNm/enLMTkTRs2DCn5/jFx8crLCxMbdu2zXBXsaDYvn27JMZZWFH6OIuoqCg1aNDA0+EUKOntAtZEm8g52oT10S5yjnZhfQW5XaT3OLwZl5K8o0ePqmXLljpy5IiqV6+u3bt369KlS5KuPUPvgw8+0KFDhxwPRM+uwMDATKf6vXLlimN5ZlJSUvT888/r8ccfV+PGjXN4NtdmF8ssufT395e/v3+O95cf+Pnlq5u0yAN+fn4F9vvpKent4mT8JQ9HAndK/zxpEznHtcL6aBc5R7uwvoLcLrIbt0vf4hdeeEEXL17Ujh07VKZMGZUpU8ZpeceOHbVy5coc7zc0NFTHjh3LUJ5+O7V8+fKZbjd37lzt2bNHH3zwgQ4ePOi07OLFizp48KDKlClTYLteAnCPpKQk2Ww2Ldy8w9OhwM1sNhvPAwMA4L9cSvJWrVqlgQMHqnbt2jpz5kyG5VWqVNGRI0dyvN/69esrJiZG8fHxTt0k07tg1q9fP9PtDh8+rOTkZDVv3jzDsrlz52ru3Llavny5OnbsmOOYAFiH3W6XMUbtGz+hUkXKeTocuMmZSye0cussngcGAMB/uZTkJSYmKiQkJMvlFy9edCmYrl276p///KemTp3qeE5eUlKSZs2apYiICMfMmocPH1ZCQoJq1qwpSerRo0emCWCnTp3Url07Pf3004qIiHApJgDWc0dYE4WF1PB0GHCTI6f2auXWWZ4OAwCAfMOlJK927dr67rvv9Mwzz2S6fMWKFS4NZoyIiFC3bt00bNgwnTx5UtWqVdOcOXN08OBBzZgxw7FedHS01q1bJ2OMJKlmzZqOhO/PKleuzB08AAAAAF7DpSRvwIAB6tWrl+rVq6du3bpJktLS0rR//36NHj1aGzdu1NKlS10KaO7cuRoxYoTmzZunc+fOqV69elq5cqVatGjh0v4AAAAAwJu4lOT17NlThw4d0ssvv6zhw4dLku677z4ZY+Tj46PXX3/d5btnAQEBGj9+vMaPH5/lOmvXrs3WvtLv9AEAAAA5wUzM1uNNn6nLc8QOHz5cPXv21LJly7R//36lpaWpatWq6ty5s6pUqeLOGAEAQB7yph8+3oLP1HXMxGxt3jIbc7aTvKioKN11111q3ry5mjdvrhIlSui2227TwIED8zI+AACQR/gxa23e8mPW3dJnYn6+dGlV9CuYz1JD5o6mJOvd06e9YjbmbCd5hw8f1ptvvimbzSabzaaaNWs6JX6VKlXKwzABAIC78VgR6+LRIrnXonAR1Q4I8HQYcKNfr1zRu6dPezqMWyJHSd7Ro0e1fv16rV+/Xhs2bNCMGTM0depU2Ww2lS9fXs2bN1dUVJSioqJ05513ymaz5WXsAOCSE+cPezoEuBGfZ+7xWBHr4dEigHfL0Zi8ihUrqkePHurRo4ck6dKlS9qwYYNiY2MVGxurzz//XB9//LEkKTg4WOfOnXN/xMgR+uRbD5+p6651TfPRnDXjPB0K3Mxm86FbGgAA/+XyxCuSVKRIEbVt21Zt27ZVXFycYmJiNHnyZG3cuFHx8fHuihEuYJyFtTHOwjXXuqalMc7CYrxpjEVe4W6o9fCZAt7N5SRv586dWr9+veMu3qFDh2S329WgQQMNHjxYzZs3d2ecyCHGWVgX4yxyj3EW1uJNYyzcjbvb1sYdbsB7ZTvJW7dunWJjY7V+/Xpt2rRJ58+fV9myZRUZGam+ffsqMjJSjRo1UqFChfIyXuQQ4yysh3EWANyFu9vWxR1uwLtlO8lr3bq1/P391a1bN7333ntq1qwZz8MDAMACuLttPdzhBrxbtpO8unXr6pdfftGHH36on3/+WZGRkYqKilJkZKQqV66clzEiF+iTbz18pgAAALiRbCd5P/74oy5evKiNGzc6xuHNnz9fCQkJKlOmjCIjI9W8eXNHt01/f7p9eBLjLKyNcRYAAADISo4mXilatKhjNk1JSk1N1Y4dOxQbG6sNGzboX//6l1544QXZ7Xb95S9/0XfffZcnQePmGGdhXYyzAAAAwI3k6hEKvr6+atSokRo1aqTWrVvr+++/14IFCxx3++B5jLOwHsZZAAAA4EZcSvKSkpK0efNmrV+/3jHb5oULFyRdu4N01113KSoqyq2BAgAAAABuLttJ3ieffOJI6rZv367k5GQZY1SqVClHUhcVFaW//OUvjMcDAAAAAA/JdpLXqVMnSVLlypXVvXt3R1JXq1atPAsOAAAAAJAz2U7yFi9erKioKIWGhuZlPAAAAACAXMh2ktetW7e8jAMAAADINw5c5VFFVuNNn2muZtcEAAAArCQpKUk+kl6Mi/N0KMgDPpJXPGuYJA8AAAD4L7vdrjRJZTqXUaHShTwdDtzo6umrOrnspFc8a5gkD4DX8abuGt6AzzP3qEPr4TPNvaL1iiqwUqCnw4AbJR5M1MllJz0dxi1BkgfAa9AFx7q8pfuNu9EmrI12AXgvkjwAXoMuONbkTd1v3I02YV20C8C7keQB8Dp0wbEWb+p+k1doE9ZDuwC8m4+nAwAAAAAAuA938iyOgdfWw2cKAACAGyHJsygG01sbg+kBAACQFZI8i2IwvXUxmB4AAAA3QpJncQymtx4G0wMAAOBGmHgFAAAAACyEJA8AAAAALIQkDwAAAAAshCQPAAAAACyEJA8AAAAALIQkDwAAAAAsJN89QiEpKUmvvPKK5s2bp3PnzqlevXoaM2aM2rRpc8Ptli1bpsWLF2vr1q06ceKEwsLC1L59e40YMULFixe/NcEDAFAAJR1P8nQIcDM+U8C75bskr3fv3lqyZIkGDBig6tWra/bs2WrXrp1iYmIUFRWV5XZ9+vRR+fLl1bNnT4WHh+vnn3/WpEmT9MUXX2jbtm0KDORZcQAAXC8pKUmySUenHvV0KMgLtv9+xnAJibL1eNNnmq+SvC1btmjRokUaP368hgwZIkmKjo5WnTp1NHToUG3YsCHLbZcsWaJWrVo5lTVq1Ei9evXSggUL9H//9395GTqAAsSb/pH3BnyerrPb7ZKRXmttV+USNk+HAzf6/ZzRiJika58xcoQ/flicl/zxI18leUuWLJGvr6/69OnjKAsICNBTTz2ll156SUeOHFFYWFim2/45wZOkTp06qVevXtq1a1dehQygAOHCbWFectHOK+2q+6lhqK+nw4AbbYtL1YgY2oQr+OOHdXnTHz/yVZK3fft21ahRQ8HBwU7lTZo0kSTt2LEjyyQvMydOnJAklS5d+obrJSUlOf04iI+PlyQlJycrOTk528fLT1JSUjwdAvJYSkpKgf1+eoqvry8XbgtKv2j7+vrSJnKIa4X1ca3IufR2wR8/rCf9jx8FuV1kN+58leTFxcUpNDQ0Q3l62fHjx3O0vzfffFO+vr7q2rXrDdcbN26cRo8enaF81apVCgoKytEx84sDBw5IohuTFaV/puvXr1dcXJyHoylY0tsFF25rSb9o0yZyLr1NwLpoFzlHu7C+gtwuEhISsrVevkryEhMTM719GhAQ4FieXQsXLtSMGTM0dOhQVa9e/YbrDhs2TIMGDXK8j4+PV1hYmNq2bZvhrmJBsWnTJrqlWZlNaty4sZo2berpSAqU7du3ezoE5KGoqCg1aNDA02EUKLQJ66Nd5BztwvoKcrtI73F4M/kqyQsMDMx0TMWVK1ccy7Pj+++/11NPPaV7771XY8eOven6drs90+TS399f/v7+2TpmflO4cGG6pVlUete0woULF9jvp6f4+eWrf/LgZn5+frSJHKJNWB/tIudoF9ZXkNtFduPOV9/i0NBQHTt2LEN5+u3U8uXL33QfP/74ozp06KA6depoyZIlXt9Q6ZZmPQymBwAAwI34eDqA69WvX1979+7NcBty8+bNjuU3cuDAAd13330qU6aMvvjiCxUpUiSvQgUAAACAfClfJXldu3ZVamqqpk6d6ihLSkrSrFmzFBER4ZhZ8/Dhw9q9e7fTtidOnFDbtm3l4+Ojr7/+WiEhIbc0dgAAAADID/JVX8aIiAh169ZNw4YN08mTJ1WtWjXNmTNHBw8e1IwZMxzrRUdHa926dTLGOMruu+8+/fbbbxo6dKjWr1+v9evXO5aVLVtWbdq0uaXnAgAAAACekK+SPEmaO3euRowYoXnz5uncuXOqV6+eVq5cqRYtWtxwux9//FGS9NZbb2VY1rJlS5I8AAAAAF4h3yV5AQEBGj9+vMaPH5/lOmvXrs1Qdv1dPQAAAADwVvlqTB4AAAAAIHdI8gAAAADAQkjyAAAAAMBCSPIAAAAAwEJI8gAAAADAQkjyAAAAAMBC8t0jFAAAwK2161Sap0OAm/GZAt6NJA8AAC+VlJQkH5vUc3mip0NBHvCxXfuMAXgfkjwAALyU3W5XmpGK3dVTfsXKejocuFHKhT904fv5stvtng6lwOJuqPV402dKkgfA63jTP/LegM8z9wKr/EX2ctU8HQbcKOnEfl34fr6nwyiQuMNtbd5yh5skz+L48WM9fKau48JtXd5y0QaQ97jDbV3edIebJM+i+DFrbfygdQ0Xbmvypos2gFuHO9zW4013uEnyLIofs9bFD9rc48JtLd500QYAIDtI8iyOH7PWww9aAAAA3AgPQwcAAAAACyHJAwAAAAALIckDAAAAAAshyQMAAAAACyHJAwAAAAALIckDAAAAAAshyQMAAAAACyHJAwAAAAALIckDAAAAAAshyQMAAAAACyHJAwAAAAALIckDAAAAAAshyQMAAAAACyHJAwAAAAALIckDAAAAAAshyQMAAAAACyHJAwAAAAALIckDAAAAAAshyQMAAAAACyHJAwAAAAALIckDAAAAAAvJd0leUlKSXnzxRZUvX16BgYGKiIjQN998k61tjx07pocffljFixdXcHCwHnroIf322295HDEAAAAA5B/5Lsnr3bu33n77bT322GOaOHGifH191a5dO61fv/6G2126dEmtW7fWunXr9NJLL2n06NHavn27WrZsqTNnztyi6AEAAADAs/w8HcD1tmzZokWLFmn8+PEaMmSIJCk6Olp16tTR0KFDtWHDhiy3nTJlivbt26ctW7aocePGkqT7779fderU0YQJE/T666/fknMAAAAAAE/KV3fylixZIl9fX/Xp08dRFhAQoKeeekobN27UkSNHbrht48aNHQmeJNWsWVN//etf9dFHH+Vp3AAAAACQX+SrO3nbt29XjRo1FBwc7FTepEkTSdKOHTsUFhaWYbu0tDT99NNPevLJJzMsa9KkiVatWqWLFy+qaNGimR43KSlJSUlJjvcXLlyQJJ09e1bJyckun48nnT9/XpKUdGK/0q5e8WwwcKvks0clXfuM6YqcM7QLa6JNuI42YV20C9elt4uEvRuUdGK/Z4OBW6XGn5RUsNvFxYsXJUnGmBuvaPKRO+64w9x9990Zyn/55Rcjyfz73//OdLtTp04ZSebVV1/NsGzy5MlGktm9e3eWxx05cqSRxIsXL168ePHixYsXL175/nXkyJEb5lX56k5eYmKi7HZ7hvKAgADH8qy2k+TStpI0bNgwDRo0yPE+LS1NZ8+eValSpWSz2bJ/AvCI+Ph4hYWF6ciRIxnuAgPeinYBZES7AJzRJgoeY4wuXryo8uXL33C9fJXkBQYGOnWbTHflyhXH8qy2k+TSttK15PDPCWLx4sWzFTPyj+DgYP6BAv6EdgFkRLsAnNEmCpZixYrddJ18NfFKaGio4uLiMpSnl2WVsZYsWVJ2u92lbQEAAADASvJVkle/fn3t3btX8fHxTuWbN292LM+Mj4+P6tatqx9++CHDss2bN6tKlSpZTroCAAAAAFaSr5K8rl27KjU1VVOnTnWUJSUladasWYqIiHDMrHn48GHt3r07w7Zbt251SvT27NmjNWvWqFu3brfmBOARdrtdI0eOzHRMJuCtaBdARrQLwBltwrpsxtxs/s1b6+GHH9by5cs1cOBAVatWTXPmzNGWLVu0evVqtWjRQpLUqlUrrVu3zmnq0IsXL6pBgwa6ePGihgwZIn9/f7399ttKTU3Vjh07FBIS4qlTAgAAAIBbJl9NvCJJc+fO1YgRIzRv3jydO3dO9erV08qVKx0JXlaKFi2qtWvXauDAgRozZozS0tLUqlUr/etf/yLBAwAAAOA18t2dPAAAAACA6/LVmDwAAAAAQO6Q5AEAAACAhZDkId+ZMmWKbDabIiIiMl1us9nUr1+/TJfNnj1bNpvNaZbVUaNGyWazOV5BQUGqXbu2Xn755QyP6wDy0s8//6yuXbvqtttuU0BAgCpUqKA2bdrovffekyTVrl1bd955Z4btli9fLpvNppYtW2ZYNnPmTNlsNq1atcqp/IsvvpDNZlP58uWVlpaWaTyVKlVyahuFCxdWkyZNNHfu3CzPITU1VeXLl5fNZtOXX36Zk9MHciSzf8+vd/DgQafvr81mU3BwsOrXr69JkyYpNTVVkvTRRx/JZrNp+fLlGfZx5513ymazKSYmJsOy8PBwRUZGZihv0qSJbDab3n///VyeIfA/N7s+/NnDDz8sm82mF198MdPla9eudWob/v7+qlKliqKjo/Xbb7851susHV3/euONN3Ty5En5+fmpZ8+eWcZ/8eJFBQYGqnPnzk7lK1eu1H333adSpUopICBANWrU0JAhQ3TmzBkXagk5ke8mXgEWLFigSpUqacuWLdq/f7+qVavmlv2+//77KlKkiC5duqRVq1Zp7NixWrNmjWJjY2Wz2dxyDCArGzZsUOvWrRUeHq6nn35a5cqV05EjR7Rp0yZNnDhR/fv3V1RUlGbMmKELFy6oWLFijm1jY2Pl5+enrVu3Kjk5Wf7+/k7LfH191axZM6fjpbejgwcPas2aNbrnnnsyjat+/foaPHiwJCkuLk7Tp09Xr169lJSUpKeffjrD+mvWrFFcXJwqVaqkBQsW6P7773dH9QAue+SRR9SuXTtJ0oULF/TFF1+of//+OnTokMaPH6+oqChJ0vr169WpUyfHdvHx8dq5c6f8/PwUGxur1q1bO5YdOXJER44cUY8ePZyOtW/fPm3dutXx/X/22WdvwRnC6rJzfbhefHy8PvvsM1WqVEkffvih3njjjSx/xzz//PNq3LixkpOTtW3bNk2dOlWff/65fv75Z5UvX96x3vXt6HoNGjRQmTJl1KZNG33yySdKSEhQUFBQhvWWLVumK1euOCWCQ4YM0YQJE3TnnXfqxRdfVMmSJbVt2zZNmjRJixYt0urVq3X77be7Wm24GQPkI7/99puRZJYtW2ZCQkLMqFGjMqwjyfTt2zfT7WfNmmUkma1btzrKRo4caSSZU6dOOa3buXNnI8ls2LDBvScBZKJdu3YmJCTEnDt3LsOyP/74wxhjzJw5c4wk88UXXzgtb9q0qXn00UeNJLNx40anZTVq1DANGjRwKrt06ZIpXLiweffdd02DBg1M7969M43ptttuMw888IBT2cmTJ02RIkVMrVq1Mt0mOjraNGzY0EycONEULlzYXLp06YbnDbgqs3/Pr/f7778bSWb8+PFO5WlpaaZx48amfPnyjrLKlSubJk2aOK331VdfGZvNZh555BFz7733Oi1buHChkWQ++eQTp/JXXnnFlClTxixdutTYbDbz+++/5+IMgWuyc3243syZM42/v79Zs2aNkWTWrl2bYZ2YmBgjyXz88cdO5e+++66RZF5//XVjTNbt6M/mzZtnJJkPP/ww0+Vt27Y1xYoVM1euXDHG/K8Nde/e3aSkpDitu3nzZhMUFGTq1q1rkpOTb3hcuI7umshXFixYoBIlSuiBBx5Q165dtWDBgjw71t133y1J+v333/PsGEC6AwcO6I477lDx4sUzLCtTpowkOe44xMbGOpZduXJF27ZtU+fOnVWlShWnZadOndLevXsd26Vbvny5EhMT1a1bN/Xo0cPxF9bsCAkJUc2aNXXgwIEMyxITE7V8+XL16NFDDz/8sBITE/XJJ59ka7/ArWKz2VS2bFn5+f2vs1JUVJS2b9+uxMRER1lsbKzuuOMO3X///dq0aZNTt+b0Hh7Nmzd32vfChQvVtWtXtW/fXsWKFdPChQvz/oRgedm5PlxvwYIFatOmjVq3bq1atWrl6LeSq799OnXqpMKFC2f6nT958qRWr16trl27Oh6qPnr0aJUoUUJTp06Vr6+v0/pNmjTRiy++qJ9//llLlizJURzIPpI85CsLFixQ586dVahQIT3yyCOOrjF/duXKFZ0+fTrD69KlS9k+VvqP2FKlSrktfiArt912m/7zn/9o586dWa5TpUoVlS9fXuvXr3eUbd26VVevXlVkZKQiIyOdkrwNGzZIUoYkb8GCBWrdurXKlSunHj166OLFi/rss8+yFWdKSoqOHj2qEiVKZFj26aef6tKlS+rRo4fKlSunVq1a5ekfYoDsSEhIcFwDfvvtN02ePFlfffWVevXq5VgnKipKycnJ2rx5s6MsNjbW0a4uXLjg1DZjY2NVs2ZNp+vD5s2btX//fj3yyCMqVKiQOnfuzPcfbpGd60O648ePKyYmRo888oika90slyxZoqtXr2brWFn99rm+HV3/SklJkSQVLlxYDz30kL7++mudPXvWadvFixcrNTVVjz32mKRr3Zr37Nmjhx56SMHBwZnGER0dLenamD3kEU/fSgTS/fDDD0aS+eabb4wx17rcVKxY0fz97393Wk/STV+Zddfcs2ePOXXqlPn999/NBx98YOx2uylbtqy5fPnyrTxNeKlVq1YZX19f4+vra5o1a2aGDh1qvv76a3P16lWn9bp162YCAwMd5ePGjTOVK1c2xhgzZcoUU6ZMGce6Q4YMMZLMsWPHHGV//PGH8fPzM9OmTXOURUZGmoceeihDTLfddptp27atOXXqlDl16pT5+eefzeOPP55ll+j27dub5s2bO95PnTrV+Pn5mZMnT7pWKcANZLe7ZmavZ5991qSlpTnW/eWXX4wk89prrxljjElOTjaFCxc2c+bMMcYYU7ZsWTN58mRjjDHx8fHG19fXPP30007H69evnwkLC3Psd9WqVUaS2b59u7tPHV4mu9cHY4z55z//aQIDA018fLwxxpi9e/caSWb58uVO66V315w5c6Y5deqUOX78uPn8889NpUqVjM1mc7SrG7Uj/WmIwOeff24kmQ8++MDpWE2bNjUVKlQwqampxhhjVqxYYSSZf/3rXzc87+DgYNOwYcOcVheyiSQP+cbAgQNN2bJlnfpuDx48OEOZJPPQQw+Zb775JsPrhRdeyDLJ+/PrjjvuMD/88MMtPUd4ty1btphOnTqZoKAgx/cwJCTEadzPxIkTnS6s7du3N4899pgxxpgff/zRSDJ79+41xhjTrFkzRwJ4/faFChUyZ8+edZS99957GcqMuZbkZdY2nnjiCZOQkOC07unTp42/v7+ZNGmSo+zMmTMZygB3yW6S16dPH8c1YOnSpaZv377Gx8fHDBgwwLFuWlqaKVWqlGPsXfofFfft22eMMaZTp07m0UcfNcYY8/XXXxtJjgTQmGtJYUhIiBkyZIijLCUlxZQpU8apDHBVdq4PxhjToEED07VrV6eyRo0aZShLT/L+/AoJCTFz5851rJdZO7r+deHCBce66e2gZcuWjrL0uRSubwfp4/emT59+w3OuUKGCqVatWrbrCDnD7JrIF1JTU7Vo0SK1bt3aqZ94RESEJkyYoNWrV6tt27aO8ooVK2Y6W+DRo0ezPMbSpUsVHBwsf39/VaxYUVWrVnXvSQA30bhxYy1btkxXr17Vjz/+qOXLl+tf//qXunbtqh07dqh27dpO4/IiIiK0YcMGjRkzRpJUp04dBQcHKzY2VmFhYfrPf/6j7t27Ox1j/vz5atKkic6cOeOYorpBgwa6evWqPv74Y/Xp08dp/YiICI0ZM0apqanauXOnxowZo3PnzqlQoUJO6y1evFjJyclq0KCB9u/f77T9ggUL1LdvX7fXF5Ad1atXd7oedO7cWTabTe+8846efPJJ1a1bVzabTZGRkfruu++Ulpam2NhYlSlTxjF7c2RkpCZNmiTpf2Nir+8GvWrVKp06dUpNmjRx+v63bt1aH374od588035+DACBq7LzvVh165d2r59u6Kjo52+h61atdLkyZMVHx+foXvkK6+8orvuuku+vr4qXbq0atWq5TReNd2f21Fm/Pz81L17d02ZMkXHjh1ThQoVHGP00rtqSlLRokUlXXuswo1cvHgx0zGHcBNPZ5mAMf/r9pLVKzo62rGu3DS7JpAfpH9n02eSTUlJMUWLFjUdO3Y0v/76q5FkduzY4Vi/TZs25qmnnjLfffddhm4z6d12snq1aNHC6diZza65cuVKI8lMmDDBqTwyMvKG+z5w4IC7qwZeztXZNY0xZvny5UaS013mN99809GeHn74YdOxY0fHstjYWCPJHD161Nx9991OM3MaYxyz22b1WrNmjZvOGvifP18fXnrppRt+D2fOnOnYNqvZNf8su7Nrptu0aZPT+nfccYepXbu20zp79uxx9ArJysGDB40kR08VuB938pAvLFiwQGXKlNHkyZMzLFu2bJmWL1+uf//73woMDPRAdEDe+ctf/iLp2jPqJMnX11dNmzZVbGys1q9fr+DgYNWtW9exfmRkpBYvXuy4A3H93YYFCxbI399f8+bNyzCb2fr16/Xuu+/q8OHDCg8PzzKeBx54QC1bttTrr7+uZ555RoULF9bvv/+uDRs2qF+/fhkeyJ6WlqbHH39cCxcu1Msvv5y7ygDcJH2yiOsn47r+eXmxsbEaMGCAY1mjRo1kt9u1du1abd682el5YZcvX9Ynn3yi7t27q2vXrhmO9fzzzzsmOwLc6frrgzFGCxcuVOvWrfXcc89lWPe1117TggUL9MQTT+RpTBEREapataoWLlyoNm3a6JdfftHYsWOd1qlRo4Zq1KihFStWaOLEiY47e9ebO3euJKl9+/Z5Gq9X83SWCSQkJJiiRYuaJ598MtPl6X9hXbRokTGGO3komNasWeM0EUS69LsLb7/9tqNs9OjRRpJp1qyZadOmjdP6X3/9tbHZbKZp06amVKlSTvusVq2aufvuuzM9/tGjR43NZjNvvPGGoyyzO3nGGPPFF184DZp/7bXXjCRz+PDhTPfdpk0bU7NmzaxPHnBBbu7kRUdHG0nmyy+/dJQlJSWZgIAA06xZMyPJxMbGOm3TrFkzx7KJEyc6ytPHF3333XeZxvH000+b4sWLO54PBuRUdq4P33//vZHkNJ7uemPHjjU+Pj6Oibjy6k6eMdeeF6n/zo+Q1fMi58+fbySZRx99NMNz8n744QdTuHBhU6dOnUwnl4F7cCcPHvfpp5/q4sWL6tChQ6bLmzZtqpCQEC1YsCDD+COgoOjfv78SEhLUqVMn1axZU1evXtWGDRu0ePFiVapUyemvr+l3HDZu3KhRo0Y57adp06ay2WzatGmTHnzwQdlsNkn/m969X79+mR6/QoUKatiwoRYsWKAXX3zxhrHef//9qlOnjt5++2317dtXCxYsUP369RUWFpbp+h06dFD//v21bds2NWzYMLtVAmTLzJkz9dVXX2Uof+ihhyRJ27Zt0/z58yVdG+OzevVqLV26VJGRkU5juQsVKqTGjRvr+++/l91uV6NGjZz2FxkZqQkTJkjKeIe8VKlSioyMzDS+Dh06aNq0afr888/VuXPn3J0svFJ2rg/Dhg2Tr6+vHnjggUz30aFDBw0fPlyLFi3SoEGDchzD9e3oelWrVlWzZs2cynr27KlXX31Vn3zyiZo3b65KlSpl2O6xxx7T1q1bNXHiRP3666967LHHVKJECW3btk0zZ85UqVKltGTJEvn7++c4VmSTp7NM4MEHHzQBAQE3fJRB7969jb+/vzl9+jR38lAgffnll+bJJ580NWvWNEWKFDGFChUy1apVM/379zd//PGH07qXL182fn5+RpJZtWpVhn3Vq1fPSDJvvvmmo6x///43HRs3atQoI8n8+OOPxpis7+QZY8zs2bMdY/MkmREjRmS53/SxFQMHDrxhHQA5kf7veVav9Dsb17/8/PxMlSpVzAsvvGAuXryYYZ/Dhg0zkkxkZGSGZcuWLTOSTNGiRR13HtIfSfL4449nGWdCQoIJCgoynTp1ct/Jw6vc7Ppw9epVU6pUKXPXXXfdcD+VK1c2DRo0MMbk/E5eVq9evXplul3jxo2NJDNlypQb7n/FihWmTZs2pkSJEsZut5tq1aqZwYMH85vsFrAZY0zep5IAAAAAgFuB+X4BAAAAwEJI8gAAAADAQkjyAAAAAMBCSPIAAAAAwEJI8gAAAADAQkjyAAAAAMBCSPIAAAAAwEJI8gAAAADAQkjyAAAAAMBCSPIAAPlG7969ValSJZe3LVKkSK6OP2rUKNlstlztoyBr1aqV6tSpk+fHOXjwoGw2m2bPnp3nxwIAb0SSBwC4oY8++kg2m03Lly/PsOzOO++UzWZTTExMhmXh4eGKjIy8FSHmSEJCgkaNGqW1a9d6OhSPOH78uEaNGqUdO3Z4OhQAQB4hyQMA3FBUVJQkaf369U7l8fHx2rlzp/z8/BQbG+u07MiRIzpy5Ihj2+yaNm2a9uzZk7uAbyIhIUGjR4/ONMl7+eWXlZiYmKfH97Tjx49r9OjRJHkAYGF+ng4AAJC/lS9fXpUrV86Q5G3cuFHGGHXr1i3DsvT3OU3y/P39cxdsLvn5+cnPj0sjAKBg404eAOCmoqKitH37dqe7XLGxsbrjjjt0//33a9OmTUpLS3NaZrPZ1Lx5c0fZ/Pnz1ahRIwUGBqpkyZLq0aOHjhw54nSczMbknTlzRo8//riCg4NVvHhx9erVSz/++GOWY7qOHTumjh07qkiRIgoJCdGQIUOUmpoq6dpYsJCQEEnS6NGjZbPZZLPZNGrUKEmZj8mz2Wzq16+fVqxYoTp16shut+uOO+7QV199leHYa9eu1V/+8hcFBASoatWq+uCDD7I9zi99PNxPP/2kli1bKigoSNWqVdOSJUskSevWrVNERIQCAwN1++2369tvv8303J988kmVLVvWEefMmTOd4mvcuLEk6YknnnCc/5/r8ddff1Xr1q0VFBSkChUq6K233spwrJMnT+qpp55S2bJlFRAQoDvvvFNz5szJsN758+fVu3dvFStWzPH5nT9/PsN6J06c0BNPPKGKFSvKbrcrNDRUDz30kA4ePHjTugMAOCPJAwDcVFRUlJKTk7V582ZHWWxsrCIjIxUZGakLFy5o586dTstq1qypUqVKSZLGjh2r6OhoVa9eXW+//bYGDBig1atXq0WLFpn+4E+XlpamBx98UB9++KF69eqlsWPHKi4uTr169cp0/dTUVN17770qVaqU/vnPf6ply5aaMGGCpk6dKkkKCQnR+++/L0nq1KmT5s2bp3nz5qlz5843PP/169frueeeU48ePfTWW2/pypUr6tKli86cOeNYZ/v27brvvvt05swZjR49Wk899ZReffVVrVix4ob7vt65c+fUvn17RURE6K233pLdblePHj20ePFi9ejRQ+3atdMbb7yhy5cvq2vXrrp48aJj2z/++ENNmzbVt99+q379+mnixImqVq2annrqKb3zzjuSpFq1aunVV1+VJPXp08dx/i1atHCK4b777tOdd96pCRMmqGbNmnrxxRf15ZdfOtZJTExUq1atNG/ePD322GMaP368ihUrpt69e2vixImO9YwxeuihhzRv3jz17NlTY8aM0dGjRzP9/Lp06aLly5friSee0JQpU/T888/r4sWLOnz4cLbrDwDwXwYAgJv45ZdfjCTz2muvGWOMSU5ONoULFzZz5swxxhhTtmxZM3nyZGOMMfHx8cbX19c8/fTTxhhjDh48aHx9fc3YsWOd9vnzzz8bPz8/p/JevXqZ2267zfF+6dKlRpJ55513HGWpqanm7rvvNpLMrFmznLaVZF599VWn4zRo0MA0atTI8f7UqVNGkhk5cmSG8xw5cqT586VRkilUqJDZv3+/o+zHH380ksx7773nKHvwwQdNUFCQOXbsmKNs3759xs/PL8M+M9OyZUsjySxcuNBRtnv3biPJ+Pj4mE2bNjnKv/766wzn/9RTT5nQ0FBz+vRpp/326NHDFCtWzCQkJBhjjNm6dWuGbf8cw9y5cx1lSUlJply5cqZLly6OsnfeecdIMvPnz3eUXb161TRr1swUKVLExMfHG2OMWbFihZFk3nrrLcd6KSkp5q677nKK4dy5c0aSGT9+/E3rCQBwc9zJAwDcVK1atVSqVCnHWLsff/xRly9fdsyeGRkZ6Zh8ZePGjUpNTXWMx1u2bJnS0tL08MMP6/Tp045XuXLlVL169Uxn5kz31Vdfyd/fX08//bSjzMfHR3379s1ym7/97W9O7++66y799ttvrp34f91zzz2qWrWq4329evUUHBzs2G9qaqq+/fZbdezYUeXLl3esV61aNd1///3ZPk6RIkXUo0cPx/vbb79dxYsXV61atRQREeEoT///9OMbY7R06VI9+OCDMsY41fO9996rCxcuaNu2bdmOoWfPno73hQoVUpMmTZzq8IsvvlC5cuX0yCOPOMr8/f31/PPP69KlS1q3bp1jPT8/Pz377LOO9Xx9fdW/f3+nYwYGBqpQoUJau3atzp07l604AQBZY3Q5AOCmbDabIiMj9d133yktLU2xsbEqU6aMqlWrJulakjdp0iRJciR76Unevn37ZIxR9erVM933jSZbOXTokEJDQxUUFORUnn7cPwsICHCMuUtXokSJXCcO4eHhGcqu3+/JkyeVmJiYaVxZxZqZihUrZhi/V6xYMYWFhWUok+Q4/qlTp3T+/HlNnTrV0TX1z06ePOlyDCVKlNBPP/3keH/o0CFVr15dPj7OfyuuVauWY3n6f0NDQzM8v/D22293em+32/Xmm29q8ODBKlu2rJo2bar27dsrOjpa5cqVy1bcAID/IckDAGRLVFSUPvvsM/3888+O8XjpIiMj9cILL+jYsWNav369ypcvrypVqki6Nq7OZrPpyy+/lK+vb4b95vYB5tfLbP95uV9jzC05zs2Onz7pTc+ePbMcr1ivXr1cxeDuc/2zAQMG6MEHH9SKFSv09ddfa8SIERo3bpzWrFmjBg0a5OmxAcBqSPIAANly/fPyYmNjNWDAAMeyRo0ayW63a+3atdq8ebPatWvnWFa1alUZY1S5cmXVqFEjR8e87bbbFBMTo4SEBKe7efv373f5PLIz02VOlSlTRgEBAZnGlZtYsyskJERFixZVamqq7rnnnhuu647zv+222/TTTz8pLS3N6W7e7t27HcvT/7t69WpdunTJKZnP6lmIVatW1eDBgzV48GDt27dP9evX14QJEzR//vxcxwwA3oQxeQCAbEl/NMCCBQt07Ngxpzt5drtdDRs21OTJk3X58mWn5+N17txZvr6+Gj16dIa7QcYYpxkq/+zee+9VcnKypk2b5ihLS0vT5MmTXT6P9GTxRrN65pSvr6/uuecerVixQsePH3eU79+/32lWyrzi6+urLl26aOnSpU6znKY7deqU4/8LFy4sKXfn365dO504cUKLFy92lKWkpOi9995TkSJF1LJlS8d6KSkpjhlNpWvjF9977z2n/SUkJOjKlStOZVWrVlXRokWVlJTkcpwA4K24kwcAyJZChQqpcePG+v7772W329WoUSOn5ZGRkZowYYIk54egV61aVWPGjNGwYcN08OBBdezYUUWLFtXvv/+u5cuXq0+fPhoyZEimx+zYsaOaNGmiwYMHa//+/apZs6Y+/fRTnT17VpJrd6UCAwNVu3ZtLV68WDVq1FDJkiVVp04d1alTJ8f7ut6oUaO0atUqNW/eXM8++6xSU1M1adIk1alTRzt27MjVvrPjjTfeUExMjCIiIvT000+rdu3aOnv2rLZt26Zvv/3WUWdVq1ZV8eLF9e9//1tFixZV4cKFFRERocqVK2f7WH369NEHH3yg3r176z//+Y8qVaqkJUuWKDY2Vu+8846KFi0qSXrwwQfVvHlz/eMf/9DBgwdVu3ZtLVu2TBcuXHDa3969e/XXv/5VDz/8sGrXri0/Pz8tX75cf/zxh9NENACA7OFOHgAg29KTt/TumddLf/B50aJFdeeddzot+8c//qGlS5fKx8dHo0eP1pAhQ/Tpp5+qbdu26tChQ5bH8/X11eeff67u3btrzpw5Gj58uMqXL++4kxcQEODSeUyfPl0VKlTQwIED9cgjjzgeOJ4bjRo10pdffqkSJUpoxIgRmjFjhl599VX99a9/dTnOnChbtqy2bNmiJ554QsuWLXM8K+/s2bN68803Hev5+/trzpw58vX11d/+9jc98sgjjtkwsyswMFBr167VY489pjlz5mjw4ME6e/asZs2apb///e+O9Xx8fPTpp5/qscce0/z58zV8+HBVqFAhw0PTw8LC9Mgjj2jt2rUaNmyYhg0bpvj4eH300Ufq0qVL7ioGALyQzeT1SGoAANxsxYoV6tSpk9avX+9ILvOrjh076pdfftG+ffs8HQoAwEtwJw8AkK8lJiY6vU8f0xUcHKyGDRt6KKrM/TnWffv26YsvvlCrVq08ExAAwCsxJg8AkK/1799fiYmJatasmZKSkrRs2TJt2LBBr7/+ugIDAz0dnpMqVaqod+/eqlKlig4dOqT3339fhQoV0tChQz0dGgDAi9BdEwCQry1cuFATJkzQ/v37deXKFVWrVk3PPvus+vXr5+nQMnjiiScUExOjEydOyG63q1mzZnr99dfz3R1HAIC1keQBAAAAgIUwJg8AAAAALIQkDwAAAAAshCQPAAAAACyEJA8AAAAALIQkDwAAAAAshCQPAAAAACyEJA8AAAAALIQkDwAAAAAs5P8B/O3Ge+sr8ukAAAAASUVORK5CYII=", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_barplot_stacked(df_weights.T, stacked = True)" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "image/png": 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seyorbfh661vTcVuzZg1WrlyJiIgI3LhxAxKJpFT938vW39jpom9Nxm/OnDmYNm2azs7AP3sZq5N29NW/JmP37bffonnz5jA1NcXKlSvRu3dvxMTEwMbGRqu+E1L1e3l2aftXd+yePHmClJQU3L59Gw8fPsSdO3fw9ttvw83NDW+99ZZWfd9NelSq2EurtP1r813x119/4fbt2xg2bFip+gby7wfSl9L2rcnY9e7dGwEBAVi4cCEAYOPGjaV+CHxsbHap9tdn3+qOXbNmzVC9enUsW7YMU6ZMwcmTJ3H69GmN7/1+XW7sg1Ltr+++dfU3cnp6OmxtbZXKbG1tdXM5rCCtRUdHi7Zt24ro6GiVbY8ePRJSK2sBQK8vqZW1ePTokdbHePfuXTF27FhRr149YW5uLurUqSPat28v5s+fL+7evatS/6OPPhLz5s3Tuj8h8sfO2kqq97GztpKWauyE0Gz8srOzRd++fcV7770n5HK51mMnNYCxk5Zy7DT93BXo16+f+PXXX7Xq89GjR8Jaqv+xs5aWz+fu8uXLok2bNiI3N1cIIcTo0aPF119/rfXYWRnA7zsAwqqcf+cVaNasmTh+/LiWY6f/z13+2JX9vL18+bIAIB4+fKjYb/LkyeI///mPVmNnbSCfO+ty/twFBgaKYcOGad2fEAWfPSu9j52VlVWZj11SUpKwsbERP//8s8jNzRXXrl0TDg4O4s8//9R67Kyt9T9vra3L57v22rVrolOnTqJmzZqiR48eYtSoUSI4OFjrsZNa63/eSq1LN2c1Gb8Chf2NfPnyZVGjRg2lssmTJ4uZM2cW2W9x+cereCavjDg7O+NWTDQSExP1GketWrXg7Oys9f5NmjTBpk2bdBhRyZydnREdc6vCjx2g/vjJ5XK8//77kEgk2Lp1q9Zno/I/dxV/7LT93OXm5uLu3bta9ens7IzoWxV/7AD1xu/06dO4desW6tWrBwBISUmBmZkZ7t27h82bN2vUn7OzM2IM4PcdoL/PnomJicolTerIHzv9f+6A8hk7V1dXWFhYKP2OK83vu+hK+LmTy+XYtWsXfvjhB637Awo+ezF6H7/yGLt79+6hSpUq8PPzAwB4enrCx8cHp0+fRps2bTTu09nZGdHR+p+35fW58/T0xOnTpxXvfXx84O/vr1Wfzs7OuBWt/3lbnn/jFadp06ZIT0/HkydPFN/HN27c0Mml2EzyypCzs3OpP0AVRW5uLnJzc5GXl4fc3FxkZWXB3NwcpqamWrVXmcYOAD766CPEx8fj2LFjMDMr3bSsLGOXkpKCX3/9FQMGDIBUKsX+/fsRHh6OxYsXa91mZRk7IP/xEyNGjFC8//TTT9GoUSP85z//0aq9yjR2L1++xKVLl9CpUydIJBKsXr0aycnJ8Pb21qq9yjR2BX9oL1y4ECtWrMD9+/exZ88ehIaGatVeZRq7AidPnkROTo5OHttRWcbP1dUVGRkZOHjwIAYMGIDo6GicOXMGH3/8sdZtVpaxA/IvD3Z1dYVcLsfq1ashl8vRq1cvrdurTGMHFP83ctWqVTFw4EDMmzcPK1euxMmTJ/HXX39h4MCBpe6XC6+QTixYsABWVlbYsGEDFi5cCCsrK2zfvl3fYVUIjx49woYNG3Dx4kXUqlVL8fyjM2fO6Ds0gyaRSLB+/XrUr18fdnZ2+Oabb7Br1y60atVK36FVCNbW1qhbt67iZWVlhapVq3KFXDXk5OQgKCgItWrVQt26dfHLL7/gyJEjpbqPtjJZvXo1EhMTUatWLfTp0wdff/211vfjVUbbt2/HiBEjSv0PgpVJtWrVsHfvXsybNw+2trbo3bs3ZsyYgXfeeUffoVUImzdvVnxXnD9/HgcOHNB3SBVKSX8jr1mzBk+fPoWdnR1mzJiBPXv2oGbNmqXuVyK0ub6EAAAxMTHw9/fHjh074Obmpu9wiIiIiIjIiKmbf/BMHhERERERkRFhkkdERERERGREmOQREREREREZESZ5pWBikj98eXl5eo6EiIiIiIiMXW5uLoD/y0OKwiSvFOzs7ABAN0+lJyIiIiIiKkZB3lGrVq1i6zHJK4UaNWqgRo0aOHHihL5DISIiIiIiI3fixAnUqFGjxEce8SErpWBiYoJJkyZhwYIFaNy4Mby8vLR++DcREREREVFh8vLycPHiRRw9ehRz584t8XJNg3tOnkwmw5dffont27fjxYsX8PT0xIIFC9C9e/di9wsLC8OePXtw6dIlPHv2DE5OTujXrx/mzp2rkuk2bNgQjx49Umnjo48+wg8//KBRvHK5HIsXL8bhw4eRk5Oj0b5ERERERETqMDc3R79+/RAUFFTxkryRI0ciNDQU06ZNQ9OmTbFlyxZcunQJ4eHh8PX1LXK/WrVqwdHREYMGDYKzszOuX7+OH374AY0bN8bly5dhZWWlqNuwYUPUqFEDM2fOVGrD1dUVXl5eWsWdmpqKZ8+eQS6Xa7U/ERERERFRYUxMTFC3bl3Y2tqqVd+gkryLFy/C29sbISEhCAwMBABkZWXBw8MDtWvXxtmzZ4vcNyIiAl26dFEq27ZtG0aPHo3169fjgw8+UJQ3bNgQHh4eOHz4cJkcBxERERERkb4Y1MIroaGhMDU1xYQJExRlUqkU48ePx7lz5xAXF1fkvq8neAAwePBgAEB0dHSh+2RnZ+Pff/8tXdBEREREREQGxKAWXrly5QpcXV1VTkMWXEJ59epVODk5qd3es2fPABS+xOipU6dgbW2NvLw8NGjQANOnT8enn35abHsymQwymUzxXi6XIzk5GXZ2dpBIJGrHRUREREREpCkhBNLS0uDo6FjsfXkGleTFx8fDwcFBpbyg7OnTpxq1t2TJEpiamsLPz0+p3NPTE76+vmjWrBmSkpKwZcsWTJs2DU+fPsWSJUuKbG/x4sUIDg7WKAYiIiIiIiJdiouLQ/369YvcblD35DVp0gTNmjXDkSNHlMrv37+PJk2a4LvvvsO0adPUamvXrl0YNWoUZs2aVWziBuRnxL1798bJkyfx4MGDIgfs9TN5KSkpcHZ2xoMHD2BjY6NWXKQfOTk5CA8PR9euXWFubq7vcIj0ivOBKB/nAlE+zoWKIy0tDY0aNcLLly9RrVq1IusZ1Jk8KysrpSSqQFZWlmK7Os6cOYPx48ejZ8+eWLhwYYn1JRIJpk+fjmPHjiEiIgL+/v6F1rO0tISlpaVKec2aNdVe6Yb0IycnB9bW1rCzs+MvL6r0OB+I8nEuEOXjXKg4Cn4+Jd0qZlALrzg4OCA+Pl6lvKDM0dGxxDauXbuGAQMGwMPDA6GhoTAzUy+PLbjXLzk5WYOIiYiIiIiIDItBJXmtWrXC7du3kZqaqlR+4cIFxfbi3Lt3D7169ULt2rVx5MgRVK1aVe2+79+/DwCwt7fXLGgiIiIiIiIDYlBJnp+fH/Ly8rBu3TpFmUwmw+bNm+Ht7a042xYbG4uYmBilfZ89e4YePXrAxMQEx44dKzJZS05ORl5enlJZTk4OvvnmG1hYWKBr1646PioiIiIiIqLyY1D35Hl7e2PYsGEICgpCQkICXFxcsHXrVjx8+BAbN25U1AsICMDp06fx6poxvXr1wv379zFr1ixERkYiMjJSsa1OnTro3r07AODQoUNYsGAB/Pz80KhRIyQnJ2PXrl24ceMGFi1ahLp165bfARMREREREemYQSV5ALBt2zbMnTsX27dvx4sXL+Dp6YnDhw+jU6dOxe537do1AMC3336rsq1z586KJK9ly5Zo3rw5duzYgefPn8PCwgKtWrXC3r17MWzYMN0fEBERERERUTkyuCRPKpUiJCQEISEhRdaJiIhQKVP3SRBt27bFoUOHtA2PiIiIiIjIoBnUPXlERERERERUOkzyiIiIiIiIjAiTPCIiIiIiIiPCJI+IiIiIiMiIMMkjIiIiIiIyIkzyiIiIiIiIjAiTPCIiIiIiIiPCJI+IiIiIiMiIMMkjIiIiIiIyIkzyiIiIiIiIjAiTPCIiIiIiIiPCJI+IiIiIiMiIMMkjIiIiIiIyIkzyiIiIiIiIjAiTPCIiIiIiIiPCJI+IiIiIiMiIMMkjIiIiIiIyIkzyiIiIiIiIjAiTPCIiIiIiIiPCJI+IiIiIiMiIMMkjIiIiIiIyIkzyiIiIiIiIjAiTPCIiIiIiIiPCJI+IiIiIiMiIMMkjIiIiIiIyIkzyiIiIiIiIjAiTPCIiIiIiIiPCJI+IiIiIiMiIMMkjIiIiIiIyIkzyiIiIiIiIjAiTPCIiIiIiIiPCJI+IiIiIiMiIMMkjIiIiIiIyIkzyiIiIiIiIjAiTPCIiIiIiIiPCJI+IiIiIiMiIMMkjIiIiIiIyIgaX5MlkMnz++edwdHSElZUVvL29ceLEiRL3CwsLw/Dhw9G4cWNYW1ujWbNmmDlzJl6+fFlo/UOHDqFNmzaQSqVwdnbGvHnzkJubq+OjISIiIiIiKl8Gl+SNGTMGy5Ytw6hRo7B8+XKYmpqiT58+iIyMLHa/CRMmIDo6Gv7+/lixYgV69eqFVatWoUOHDsjMzFSq+9tvv2HQoEGoXr06Vq5ciUGDBmHBggWYMmVKWR4aERERERFRmTPTdwCvunjxInbv3o2QkBAEBgYCAAICAuDh4YFZs2bh7NmzRe4bGhqKLl26KJW1bdsWo0ePxs6dO/HBBx8oygMDA+Hp6Ynjx4/DzCx/CGxtbbFo0SJ8+umncHNz0/3BERERERERlQODSvJCQ0NhamqKCRMmKMqkUinGjx+P2bNnIy4uDk5OToXu+3qCBwCDBw/G6NGjER0drSj7+++/8ffff2P16tWKBA8AJk6ciIULFyI0NBRffPGF7g6KiIiISA2xsbFITExUq65MJoOlpaXabdeqVQvOzs7ahkZEFYxBJXlXrlyBq6srbG1tlcq9vLwAAFevXi0yySvMs2fPAOT/Ynu1DwB48803leo6Ojqifv36iu2FkclkkMlkivepqakAgJycHOTk5KgdF5W/gp8Pf05EnA9EBQxpLsTGxsLT0wMZGVnq7WBiAsjlarcvtbbGjb/+YqJHhTKkuUDFU/dnZFBJXnx8PBwcHFTKC8qePn2qUXtLliyBqakp/Pz8lPp4tc3X+ymuj8WLFyM4OFil/Pjx47C2ttYoNtIPdRbxIaosOB+I8hnCXLh37x4yMrIQFGQPZ2eLYutevPgvNm9+CdvZC2Hm3KjEtnNjHyB10RwcPHgQTZo00VXIZIQMYS5Q8TIyMtSqZ1BJXmZmZqGXHkilUsV2de3atQsbN27ErFmz0LRpU6U+ABTZT8HZucIEBQVhxowZivepqalwcnJCjx49VM4+kmHJycnBiRMn0L17d5ibm+s7HCK94nwgymdIc6HgSiJnZws0dS3+MszY2GwAgJlzI5i7uqvdh6+vL1q3bq19kGS0DGkuUPGKy1VeZVBJnpWVldLlkAWysrIU29Vx5swZjB8/Hj179sTChQtV+gBQZD/F9WFpaVlocmhubs4JUUHwZ0X0fzgfiPIZwlx4dZ2AsuxD38dJhs0Q5gIVT92fj0E9QsHBwUFxOeWrCsocHR1LbOPatWsYMGAAPDw8EBoaqvJLs+AyzaL6UacPIiIiIiIiQ2VQSV6rVq1w+/ZtldOQFy5cUGwvzr1799CrVy/Url0bR44cQdWqVQvtAwD++OMPpfKnT5/i8ePHJfZBRERERERkyAwqyfPz80NeXh7WrVunKJPJZNi8eTO8vb0VK2vGxsYiJiZGad9nz56hR48eMDExwbFjx2Bvb19oHy1atICbmxvWrVuHvLw8RfnatWshkUiUFmkhIiIiIiKqaAzqnjxvb28MGzYMQUFBSEhIgIuLC7Zu3YqHDx9i48aNinoBAQE4ffo0hBCKsl69euH+/fuYNWsWIiMjERkZqdhWp04ddO/eXfE+JCQEAwYMQI8ePTBixAjcuHEDq1atwgcffAB3d/VvYCYiIiIiIjI0BpXkAcC2bdswd+5cbN++HS9evICnpycOHz6MTp06FbvftWvXAADffvutyrbOnTsrJXn9+vVDWFgYgoODMWXKFNjb22P27Nn48ssvdXswRMXgQ2+JiIiIqCwYXJInlUoREhKCkJCQIutERESolL16Vk8dgwYNwqBBgzSMjkg3YmNj4e7erEwfensrOpqJHhEREVElZHBJHlFlkJiYWOYPvU1MTGSSR0RERFQJMckj0qOyfOgtEREREVVOBrW6JhEREREREZUOkzwiIiIiIiIjwiSPiIiIiIjIiDDJIyIiIiIiMiJM8oiIiIiIiIwIkzwiIiIiIiIjwiSPiIiIiIjIiDDJIyIiIiIiMiJM8oiIiIiIiIwIkzwiIiIiIiIjwiSPiIiIiIjIiDDJIyIiIiIiMiJM8oiIiIiIiIwIkzwiIiIiIiIjwiSPiIiIiIjIiJiVZufz588jPDwcCQkJmDhxIpo2bYqMjAzExMTA1dUVVatW1VWcREREREREpAatzuRlZ2djyJAh6NixI+bMmYMVK1YgLi4uv0ETE/To0QPLly/XaaBERERERERUMq2SvLlz5+Lw4cNYu3Ytbt26BSGEYptUKsWwYcNw8OBBnQVJRERERERE6tEqyfvpp5/wySefYMKECahZs6bKdnd3d9y/f7/UwREREREREZFmtEryEhIS0LJlyyK3m5qaIiMjQ+ugiIiIiIiISDtaLbzi5OSEmJiYIrdHRUXBxcVF66CIiKjyiI2NRWJiolp1ZTIZLC0t1W67Vq1acHZ21jY0IiKiCkmrJO+9997DsmXLMHToULi6ugIAJBIJAGD9+vXYu3cvvvnmG91FSURERik2Nhbu7s2QkZGl3g4mJoBcrnb7Umtr3IqOZqJHRESVilZJ3pw5c3D+/Hl06tQJ7u7ukEgkmD59OpKTk/H48WP06dMH06dP13WsRERkZBITE5GRkYWgIHs4O1sUW/fixX+xefNL2M5eCDPnRiW2nRv7AKmL5iAxMZFJHhERVSpaJXkWFhY4evQodu7cidDQUOTl5UEmk8HT0xMLFizA+++/rzizR0REVBJnZws0dS3+MszY2GwAgJlzI5i7updHWERERBWS1g9Dl0gk8Pf3h7+/vy7jISIiIiIiolLQanVNIiIiIiIiMkxancnr1q1biXUkEglOnjypTfNERERERESkJa2SPLlcrnLPXV5eHh49eoS4uDi4uLigXr16OgmQiIiIiIgqD00erQNo9nidyvJoHa2SvIiIiCK3HT58GBMmTMCyZcu0jYmIiIiIiCohjR+tA2j0eJ3K8mgdrRdeKUq/fv3g7++PadOm4fTp07punoiIiIiIjJQmj9YBNHu8TmV6tI7OkzwAaNKkCVatWlUWTRMRERERkZFT59E6AB+vUxSdr66Zm5uLvXv3olatWrpumoiIiIiIiEqg1Zm8cePGFVr+8uVLnD9/Hs+ePeM9eURERERERHqgVZJ36tQpldU1JRIJatSoAV9fX3zwwQfo0aOHTgIkIiIiIiIi9WmV5D18+FDHYRAREREREZEu6PyePCIiIiIiItIftc7k/f7771o13qlTJ433kclk+PLLL7F9+3a8ePECnp6eWLBgAbp3717sfrdu3cIPP/yACxcu4PLly5DJZHjw4AEaNmyoUrdhw4Z49OiRSvlHH32EH374QeOYiYiIiIiIDIVaSV6XLl1U7sErjhACEokEeXl5Ggc0ZswYhIaGYtq0aWjatCm2bNmCPn36IDw8HL6+vkXud+7cOaxYsQLNmzeHu7s7rl69Wmw/rVq1wsyZM5XKXF1dNY6XiIiIiIjIkKiV5IWHh5d1HACAixcvYvfu3QgJCUFgYCAAICAgAB4eHpg1axbOnj1b5L4DBgzAy5cvYWNjg//+978lJnn16tWDv7+/LsMnIiIiIiLSO7WSvM6dO5d1HACA0NBQmJqaYsKECYoyqVSK8ePHY/bs2YiLi4OTk1Oh+9asWVPj/rKzs5GTk4MqVapoHTMREREREZEh0Wp1zbJy5coVuLq6wtbWVqncy8sLAHD16tUikzxNnTp1CtbW1sjLy0ODBg0wffp0fPrpp8XuI5PJIJPJFO9TU1MBADk5OcjJydFJXFQ2Cn4+hvJzys3NLZc+DOV4ybAY0nzgXCB94lwgyse5UHGoG7fWSV5WVhb27duHy5cvIyUlBXK5XGm7RCLBxo0bNWozPj4eDg4OKuUFZU+fPtU2XCWenp7w9fVFs2bNkJSUhC1btmDatGl4+vQplixZUuR+ixcvRnBwsEr58ePHYW1trZPYqGydOHFC3yEAAO7du1fmfURGRiI+Pr7M+6GKyxDmA+cCGQLOBaJ8nAuGLyMjQ616WiV5jx49QteuXfHw4UNUr14dKSkpqFmzJl6+fIm8vDzUqlULVatW1bjdzMxMWFpaqpRLpVLFdl04dOiQ0vuxY8eid+/eWLZsGaZMmYL69esXul9QUBBmzJiheJ+amgonJyf06NFD5ewjGZacnBycOHEC3bt3h7m5ub7DwZUrV8q8D19fX7Ru3brM+6GKx5DmA+cC6RPnAlE+zoWKo+BKwpJoleR99tlnSElJwfnz59G4cWPUrl0be/bsQceOHbFixQqsWrUKx44d07hdKysrpcshC2RlZSm2lwWJRILp06fj2LFjiIiIKHJBFktLy0KTUHNzc71PCFKPofyszMzK/kppMzMzgzhWMlyGMB84F8gQcC4Q5eNcMHzqxq3Vw9BPnTqFiRMnwsvLCyYm+U0IIWBpaYnPPvsMb7/9NqZNm6Zxuw4ODoWeOi0oc3R01CZctRTc65ecnFxmfRAREREREZU1rZK8jIwMxUPGbW1tIZFIkJKSotjeoUMHREZGatxuq1atcPv2bZXTkBcuXFBsLyv3798HANjb25dZH0RERERERGVNqyTP2dkZjx8/BpB/urNevXo4f/68Yvvff/+tuI9OE35+fsjLy8O6desUZTKZDJs3b4a3t7fibFtsbCxiYmK0CR3JyckqD2nPycnBN998AwsLC3Tt2lWrdomIiIiIiAyBVhe9duvWDQcPHsS8efMAAGPGjMHixYvx4sULyOVybN++HQEBARq36+3tjWHDhiEoKAgJCQlwcXHB1q1b8fDhQ6WVOgMCAnD69GkIIRRlKSkpWLlyJQAgKioKALBq1SpUr14d1atXx+TJkwHkL7qyYMEC+Pn5oVGjRkhOTsauXbtw48YNLFq0CHXr1tVmSIiIiIiIiAyCVknef/7zH1y6dAkymQyWlpaYPXs2nj59qniY+XvvvYdly5ZpFdC2bdswd+5cbN++HS9evICnpycOHz6MTp06FbvfixcvMHfuXKWypUuXAgAaNGigSPJatmyJ5s2bY8eOHXj+/DksLCzQqlUr7N27F8OGDdMqZiIiIiIiIkOhVZLn7OwMZ2dnxXupVIoNGzZgw4YNpQ5IKpUiJCQEISEhRdaJiIhQKWvYsKHSmb2itG3bVuURCkRERERERMZCq3vyjhw5onJfGxEREREREemfVklev379UKdOHUyYMAEnT56EXC7XdVxERERERESkBa2SvN9++w0DBgxAaGgoevToAQcHB0yaNAlnzpzRdXxERERERESkAa2SvJ49e2LTpk34559/cPDgQfTo0QM7d+5Ely5dUL9+fUybNg3nzp3TdaxERERERERUAq2SvALm5ubo168ftm/fjoSEBISFhaFTp07YsGED3nrrLV3FSERERERERGoqVZL3qvT0dCQkJOCff/5BVlaWWitdEhERERERkW5p9QiFAikpKQgLC8OePXsQHh6OnJwctGzZEl999RWGDx+uqxiJiIioHMXGxiIxMVHt+rVq1VJ6tBIREemXVkne9u3bsXfvXpw4cQLZ2dlwc3PD7NmzMXz4cLi5uek6RiIiIionsbGxaObmjqzMDLX3kVpZ41ZMNBM9IiIDoVWSN3r0aDRu3BgzZ87E8OHD4enpqeu4iIiISA8SExORlZkBu34zYW7nVGL9nKQ4JB1eisTERCZ5REQGQqsk79KlS2jbtq2uYyEiIiIDYW7nBMu6LvoOg4iItKDVwitM8IiIiIiIiAyTzlbXJCIiIiIiIv1jkkdERERERGREmOQREREREREZESZ5RERERERERkSr1TW/+uorDBkyBB4eHoVuv3nzJvbt24cvv/yyVMEREREREelLbGwsEhMT1a5fq1YtPkqEDIJWSd78+fPh4uJSZJJ348YNBAcHM8kjIiIiogopNjYWzdzckZWZofY+Uitr3IqJZqJHeqdVkleS5ORkWFhYlEXTRERERERlLjExEVmZGbDrNxPmdk4l1s9JikPS4aVITExkkkd6p3aS9/vvvyMiIkLxPiwsDHfv3lWp9/LlS+zZswctW7bUSYBERERERPpibucEy7ou+g6DSCNqJ3nh4eEIDg4GAEgkEoSFhSEsLKzQus2bN8fKlSt1EyERERERERGpTe0kb9asWZg8eTKEEKhduzZ++OEHDB06VKmORCKBtbU1pFKpzgMlIiprvMGeiIiIjIHaSZ6VlRWsrKwAAA8ePIC9vT2sra3LLDAiovLEG+yJiIjIWGi18EqDBg10HQcRkV7xBnsiIiL1aHrli0wmg6WlpVp1o6OjtQ2LXqFVkieEwLp167Bx40bcv38fL168UKkjkUiQm5tb6gCJiMoTb7AnIiIqWmxsLNzd3JGhwZUvEokEQogyjIpep1WSN2vWLCxbtgytWrWCv78/atSooeu4qBzxPiQiIiIiUkdiYiIyMjOwot8XcLEr+eq+8PvnEXJmIwYPHgx7e/sS69+5cwfh4eG6CLVS0yrJ27p1K4YOHYq9e/fqOh4qZ7wPiYiIiIg05WLXAC3rNiux3t2kRwAAe3t7ODg4lFhfkxMPVDStkrzMzEy88847uo6F9ID3IRERERERGRetkry3334bly5dwoQJE3QdD+kJ70MiIiIiIjIOJtrstGbNGpw/fx6LFi1CUlKSrmMiIiIiIiIiLal1Js/GxgYSiUSpLDc3F3PnzsXcuXMhlUphamqqtF0ikSAlJUV3kRIREREREVGJ1Eryhg4dqpLkERERERERkeFRK8nbsmVLGYdBREREREREuqDVPXlERERERERkmLRaXXPbtm3FbpdIJJBKpahfvz7atGkDS0tLrYIjIiIiIiIizWiV5I0ZM0Zxj54QQmnbq+USiQS2trYICgrCrFmzShkqUfmKjY3V6IGcMplM7X/QiI6O1jYsIiIiIqJiaZXkXb16FaNHj4adnR0mTZoEF5f856vduXMHq1evxsuXL7Fq1Sr8888/WLlyJYKCgmBjY4NPPvlEp8ETlZXY2Fi4u7kjIzND7X0kEonKP3oQEREREZU3rZK87777DnXq1MHRo0eVylu2bInBgwejd+/e2LhxIzZs2IABAwbgrbfewpo1a5jkUYWRmJiIjMwMrOj3BVzsGpRYP/z+eYSc2YjBgwfD3t6+xPp37txBeHi4LkIlIiIiIlKi1cIrBw4cwMCBAwvdJpFIMGDAAISFheV3YGKCoUOH4u7du2q1LZPJ8Pnnn8PR0RFWVlbw9vbGiRMnStzv1q1bmD59Onx8fCCVSiGRSPDw4cMi6x86dAht2rSBVCqFs7Mz5s2bh9zcXLVipMrDxa4BWtZtVuLLqZoDAMDe3h4ODg4lvmrUqKHnIyMiIiIiY6XVmTy5XI5bt24VuT0mJgZyuVzx3tLSElKpVK22x4wZg9DQUEybNg1NmzbFli1b0KdPH4SHh8PX17fI/c6dO4cVK1agefPmcHd3x9WrV4us+9tvv2HQoEHo0qULVq5cievXr2PBggVISEjA2rVr1YqTiKiy4P2pREREFYtWSd6AAQOwZs0auLi44IMPPlAkcFlZWVi/fj1++OEHDB8+XFH/3Llzivv2inPx4kXs3r0bISEhCAwMBAAEBATAw8MDs2bNwtmzZ4uN6eXLl7CxscF///vfYpO8wMBAeHp64vjx4zAzyx8CW1tbLFq0CJ9++inc3NzUGQYiIqPH+1OJiIgqHq2SvOXLl+PevXuYOnUqAgMD4eCQf6lafHw8srOz4eXlheXLlwPIT/ysrKwwY8aMEtsNDQ2FqakpJkyYoCiTSqUYP348Zs+ejbi4ODg5ORW6b82aNdWK/e+//8bff/+N1atXKxI8AJg4cSIWLlyI0NBQfPHFF2q1RURk7Hh/KhERUcWjVZJXs2ZNREVFYf/+/Th27BgePXoEAOjRowd69uyJQYMGwcQk/3Y/qVSK9evXq9XulStX4OrqCltbW6VyLy8vAPmrehaV5KnrypUrAIA333xTqdzR0RH169dXbC+MTCaDTCZTvE9NTQUA5OTkICcnp1Rx6Yu29yHm5uZWqGMuiFXdmI3h/syK9jPSt8oyFwDN5kPBuBTcn1qSu0n53wcF96eWRJPLQLVVEX9G+sS5oB/l8b1TEX9G+sS5UDj+jaRf6satVZIH5F+OM2TIEAwZMkTbJlTEx8cX+kdBQdnTp0910serbb7eT3F9LF68GMHBwSrlx48fh7W1dalj04d79+5ptV9kZKRiLCsSdRbxAbQfF0NSUX9G+lLZ5gKg3nzgXKh8OBf0ozzmWkX+GekD50Lh+L2gXxkZ6t0+oXWSVxYyMzMLvVm/4J6/zMxMnfQBoMh+Cs7OFSYoKEjpstPU1FQ4OTmhR48eKmcfK4rizlwWx9fXF61bt9ZxNGUnJycHJ06cQPfu3WFubl5ifW3HxZBUtJ+RvlWWuQBoNh84FyofzgX9KI+5VhF/RvrEuVA4fi/oV3G5yqvUSvIaNWoEExMTxMTEwNzcHI0aNYJEIil2H4lEonGmb2VlpXQ5ZIGsrCzF9tIqaKOoforrw9LSstDk0NzcXO9fDtp69b5ETferiMes7s9K23ExJBX1Z6QvlW0uAOrNB86FyodzQT/KY65V5J+RPnAuFI7fC/qlbtxq/ZQ6d+4MiUSiuM+u4L2uOTg44MmTJyrlBadTHR0dddJHQZuv398XHx+vuP+PiIiIiIioIlIryduyZUux73WlVatWCA8PR2pqqtLljxcuXFBs10UfAPDHH38oJXRPnz7F48ePlVb2JCIiIiIiqmhM9B3Aq/z8/JCXl4d169YpymQyGTZv3gxvb2/FmbfY2FjExMRo1UeLFi3g5uaGdevWIS8vT1G+du1aSCQS+Pn5le4giIiIiIiI9Ejri2pTU1OxZs0ahIeHIyEhAT/++CO8vLyQnJyMLVu2YMCAAWo9AP1V3t7eGDZsGIKCgpCQkAAXFxds3boVDx8+xMaNGxX1AgICcPr0aaWH7aakpGDlypUAgKioKADAqlWrUL16dVSvXh2TJ09W1A0JCcGAAQPQo0cPjBgxAjdu3MCqVavwwQcfwN3dXdshISIiIiIi0jutkrzHjx+jc+fOiIuLQ9OmTRETE4P09HQA+c/Q+/HHH/Ho0SPFA9E1sW3bNsydOxfbt2/Hixcv4OnpicOHD6NTp07F7vfixQvMnTtXqWzp0qUAgAYNGiglef369UNYWBiCg4MxZcoU2NvbY/bs2fjyyy81jpeIiIiIiMiQaJXkffbZZ0hLS8PVq1dRu3Zt1K5dW2n7oEGDcPjwYa0CkkqlCAkJQUhISJF1IiIiVMoaNmyodGavJIMGDcKgQYO0iJCIiIiIiMhwaXVP3vHjxzF16lQ0b9680FU2GzdujLi4uFIHR0RERERERJrR6kxeZmYm7O3ti9yelpamdUBEREREhig2NhaJiYlq15fJZIU+X7cw0dHR2oZFRKRCqySvefPm+P333/HRRx8Vuv3AgQMV9inyRERERK+LjY2Fu5s7MjIz1N5HIpFodCsJEZGuaJXkTZs2DaNHj4anpyeGDRsGAJDL5bh79y6Cg4Nx7tw57Nu3T6eBEhEREelLYmIiMjIzsKLfF3Cxa1Bi/fD75xFyZiMGDx5c7NVPBe7cuYPw8HBdhEp6pslZ2Vq1asHZ2bkMo6HKSqskz9/fH48ePcIXX3yBOXPmAAB69eoFIQRMTEywaNEiLmpCRJWCul/m/CInMg4udg3Qsm6zEuvdTXoEALC3t4eDg0OJ9TW5DJQMU176C5hI8v9OVpe1lRTRMbf4/UA6p/Vz8ubMmQN/f3+EhYXh7t27kMvlaNKkCYYMGYLGjRvrMkYiIoOj6Zc5v8iJiIybXJYOuQB2DLaCu33JaxtGP5fDf38mEhMT+d1AOqd2kufr64u33noLHTt2RMeOHVGjRg00aNAA06dPL8v4iIgMkiZf5vwiJyKqPNztTdDGwVTfYVAlp3aSFxsbiyVLlkAikUAikcDNzU0p8WvYsGEZhklEZJj4ZU5ERESGRqMk7/Hjx4iMjERkZCTOnj2LjRs3Yt26dZBIJHB0dETHjh3h6+sLX19fvPHGG4U+Q4+IiIiIiIjKjkb35NWvXx8jRozAiBEjAADp6ek4e/YsoqKiEBUVhV9//RU///wzAMDW1hYvXrzQfcRERERERERUJK0XXgGAqlWrokePHujRowfi4+MRHh6O1atX49y5c0hNTdVVjGSAuKIgERG9isvGExEZDq2TvBs3biAyMlJxFu/Ro0ewtLRE69atMXPmTHTs2FGXcZKB4IqCRET0Ki4bT0RkeNRO8k6fPo2oqChERkbi/PnzePnyJerUqQMfHx9MmjQJPj4+aNu2LSwsLMoyXtIzrihIRESv4rLxRESGR+0kr2vXrjA3N8ewYcOwcuVKdOjQgc/Dq8S4oiAREb2K3wtERIZD7SSvZcuWuHnzJn766Sdcv34dPj4+8PX1hY+PDxo1alSWMRIREREREZGa1E7yrl27hrS0NJw7d05xH96OHTuQkZGB2rVrw8fHBx07dlRctmlubl6WcRMREREREVEhNFp4xcbGRrGaJgDk5eXh6tWriIqKwtmzZ/Hdd9/hs88+g6WlJd588038/vvvZRI0EREREZExUHdlWplMBktLS7Xb1XQV2+fPn+PKlSswMys+PdBkJV3Sn1I9QsHU1BRt27ZF27Zt0bVrV5w5cwY7d+5UnO0jIiIiIiJV8elyQIOVaU0AyDVo31oqRfQt9VaxjY2NxeRJkyDLztagBzJkWiV5MpkMFy5cQGRkpGK1zZSUFACApaUl3nrrLfj6+uo0UCIiIiIiY/EySwACqD+hPiwdiz9Dl/ZXGhLCErDEwQFNLEo+m3cvW4bP4+PVXsU2KSkJsuxsvOfdCrVtqxZbNyY+AUdv3C6xTdIvtZO8gwcPKpK6K1euICcnB0II2NnZKZI6X19fvPnmm7wfj4iIiIhIDZaOlrBqaFVsHdlTGQCgiYUlmkulZRZLbduqqF+jWrF1ElLTy6x/0h21k7zBgwcDABo1aoThw4crkjp3d/cyC46IiIiIiIg0o3aSt2fPHvj6+sLBwaEs4yEiIiIiIqJSUDvJGzZsWFnGQURk9DRZkYyrqBEREZG2SrW6JhERlUzTFdQArqJGRERE2mOSR0RUxjRZQQ3gKmpERERUOkzyiIjKiTorqAFcRY2IiIhKx0TfARAREREREZHuMMkjIiIiIiIyIkzyiIiIiIiIjAjvySMiIqJyp+7jOfg4ESIizTHJozJnKM8GU/eLHOCXORFRWdH0kSJ8nAgRkeaY5FGZMaRng/GLnIjIMGjySBE+ToSISDtM8qjMGNKzwTT5Igf4ZU5EVNbUeaQIHydCRKQdJnlU5gzp2WDqfJED/DInIiIiooqLq2sSEREREREZESZ5RERERERERoRJHhERERERkRExuCRPJpPh888/h6OjI6ysrODt7Y0TJ06ote+TJ0/w7rvvonr16rC1tcXAgQNx//59lXoSiaTQ1zfffKPrwyEiIiIiIipXBrfwypgxYxAaGopp06ahadOm2LJlC/r06YPw8HD4+voWuV96ejq6du2KlJQUzJ49G+bm5vjuu+/QuXNnXL16FXZ2dkr1u3fvjoCAAKWy1q1bl8kxERERERERlReDSvIuXryI3bt3IyQkBIGBgQCAgIAAeHh4YNasWTh79myR+65ZswZ37tzBxYsX0a5dOwBA79694eHhgaVLl2LRokVK9V1dXTV6fhsREREREVFFYFCXa4aGhsLU1BQTJkxQlEmlUowfPx7nzp1DXFxcsfu2a9dOkeABgJubG95++23s3bu30H0yMzORlZWluwMgIiIiIiLSM4M6k3flyhW4urrC1tZWqdzLywsAcPXqVTg5OansJ5fL8ddff2HcuHEq27y8vHD8+HGkpaXBxsZGUb5lyxasWbMGQgi4u7vjiy++wHvvvVdsfDKZDDKZTPE+NTUVAJCTk4OcnBz1D9SA5Obm6juEUsvNzS1x/Cvqz6c01BkX+j+VZS4AlW8+cC5ohnPBeHEuaIZzwXhV5LmgbtwGleTFx8fDwcFBpbyg7OnTp4Xul5ycDJlMVuK+zZo1AwD4+Pjg3XffRaNGjfD06VOsXr0ao0aNQkpKCj755JMi41u8eDGCg4NVyo8fPw5ra+uSD9AA3bt3T98hlFpkZCTi4+OLrWMMx6kpdcaF/o8xfEbU/Zkbw7FqgnNBM8bw+eBcKBzngmaM4fPBuVC4ijwXMjIy1KpnUEleZmYmLC0tVcqlUqlie1H7AVB736ioKKU648aNQ9u2bTF79myMGTMGVlZWhfYTFBSEGTNmKN6npqbCyckJPXr0UDn7WFFcuXJF3yGUmq+vb4mL5ly8eLGcojEc6owL/Z/KMheAyjcfOBc0w7lgvDgXNMO5YLwq8lwouJKwJAaV5FlZWSldDlmg4L65opKvgnJt9gUACwsLTJ48GR9//DH+/PPPIlfxtLS0LDSRNDc3h7m5eZHtGzIzM4P6CGjFzMysxPGvqD+f0lBnXOj/VJa5AFS++cC5oBnOBePFuaAZzgXjVZHngrpxG9TCKw4ODoWeOi0oc3R0LHS/mjVrwtLSUqt9CxTc65ecnKxRzERERERERIbEoJK8Vq1a4fbt2yqnIS9cuKDYXhgTExO0bNkSf/zxh8q2CxcuoHHjxkqLrhSm4KHp9vb2WkRORERERERkGAwqyfPz80NeXh7WrVunKJPJZNi8eTO8vb0VZ9tiY2MRExOjsu+lS5eUEr1bt27h1KlTGDZsmKLs+fPnKv2mpaXh+++/R61atdC2bVtdHxYREREREVG5MaiLjb29vTFs2DAEBQUhISEBLi4u2Lp1Kx4+fIiNGzcq6gUEBOD06dMQQijKJk6ciPXr16Nv374IDAyEubk5li1bhjp16mDmzJmKeqtXr8aBAwfQv39/ODs7Iz4+Hps2bUJsbCy2b98OCwuLcj1mIiIiIiIiXTKoJA8Atm3bhrlz52L79u148eIFPD09cfjwYXTq1KnY/WxsbBAREYHp06djwYIFkMvl6NKlC7777julSzA7duyIs2fPYsOGDUhKSkKVKlXg5eWFTZs2oVu3bmV9eERERERERGXK4JI8qVSKkJAQhISEFFknIiKi0PL69evj559/Lrb97t27o3v37qUJkYjIIEVHR6tV7/XL3YmIiMi4GFySR0REmnmemwuJxAT+/v76DoWIiIgMAJM8IqIKLi0vD0LIMbpbEOpWdy6x/s24izh8aXM5REZERET6wCSPiMhI1K3uDCd71xLrPXsRWw7REBERkb4Y1CMUiIiIiIiIqHSY5BERERERERkRJnlERERERERGhEkeERERERGREWGSR0REREREZESY5BERERERERkRJnlERERERERGhEkeERERERGREWGSR0REREREZESY5BERERERERkRJnlERERERERGhEkeERERERGREWGSR0REREREZESY5BERERERERkRJnlERERERERGhEkeERERERGREWGSR0REREREZESY5BERERERERkRM30HQFRa0dHRJdaJiYkph0iIiIiIiPSPSR5VWM9zcyGRmMDf31/foRARkQFR5x//AP4DIBEZLyZ5VGGl5eVBCDlGdwtC3erOxda9GXcRhy9tLqfIiIhIH/iPf0RE+ZjkUYVXt7oznOxdi63z7EVsOUVDRET6osk//gH8B0AiMl5M8oiIiMioqPOPfwD/AZCIjBdX1yQiIiIiIjIiTPKIiIiIiIiMCJM8IiIiIiIiI8Ikj4iIiIiIyIgwySMiIiIiIjIiTPKIiIiIiIiMCJM8IiIiIiIiI8Ikj4iIiIiIyIgwySMiIiIiIjIiTPKIiIiIiIiMCJM8IiIiIiIiI8Ikj4iIiIiIyIgYXJInk8nw+eefw9HREVZWVvD29saJEyfU2vfJkyd49913Ub16ddja2mLgwIG4f/9+oXU3btwId3d3SKVSNG3aFCtXrtTlYRAREREREemFwSV5Y8aMwbJlyzBq1CgsX74cpqam6NOnDyIjI4vdLz09HV27dsXp06cxe/ZsBAcH48qVK+jcuTOSkpKU6v7444/44IMP0KJFC6xcuRIdOnTA1KlTsWTJkrI8NCIiIiIiojJnpu8AXnXx4kXs3r0bISEhCAwMBAAEBATAw8MDs2bNwtmzZ4vcd82aNbhz5w4uXryIdu3aAQB69+4NDw8PLF26FIsWLQIAZGZmYs6cOejbty9CQ0MBAB9++CHkcjm+/vprTJgwATVq1CjjIyUiIiIiIiobBnUmLzQ0FKamppgwYYKiTCqVYvz48Th37hzi4uKK3bddu3aKBA8A3Nzc8Pbbb2Pv3r2KsvDwcCQlJWHixIlK+0+aNAn//vsvfv31Vx0eERERERERUfkyqDN5V65cgaurK2xtbZXKvby8AABXr16Fk5OTyn5yuRx//fUXxo0bp7LNy8sLx48fR1paGmxsbHDlyhUAwJtvvqlUr23btjAxMcGVK1fg7+9faHwymQwymUzxPiUlBQCQnJyMnJwcDY7UcLx8+RIAIHt2F/LsrBLr5yTlJ9p/Ps1DerYotm70czkAIPNhJuRZ8hLbzorP7/9mViYy5CXXv5ed/7OITbwDWU5msXWfpcQCAJ4kp0CWm1ti2wmpaQCA689uIyO7+LYB4G7SIwDA06dPkZ2dXWL958+fAwDu3MlCZmbxxxobm99ezp1oiMyMEtvOfZwfy8uXL1UuVaaiVZa5AGg2HzgXKp+ynAuAZvOBc6FwnAvloyLPhQf/fy5cunRJcRzFxhIdDaDizQVAs/lgDHMhLS1//IUo4TMmDEiLFi1Et27dVMpv3rwpAIgffvih0P2eP38uAIivvvpKZdvq1asFABETEyOEEGLSpEnC1NS00Hbs7e3FiBEjioxv3rx5AgBffPHFF1988cUXX3zxxZfeXnFxccXmVQZ1Ji8zMxOWlpYq5VKpVLG9qP0AqLVvZmYmLCwsCm1HKpUW2QcABAUFYcaMGYr3crkcycnJsLOzg0QiKXI/0r/U1FQ4OTkhLi5O5UwxUWXD+UCUj3OBKB/nQsUhhEBaWhocHR2LrWdQSZ6VlZXS5ZAFsrKyFNuL2g+AWvtaWVkVeao4KyuryD6A/CTy9USyevXqRdYnw2Nra8tfXkT/H+cDUT7OBaJ8nAsVQ7Vq1UqsY1ALrzg4OCA+Pl6lvKCsqIy1Zs2asLS0VGtfBwcH5OXlISEhQalednY2kpKSSsyKiYiIiIiIDJlBJXmtWrXC7du3kZqaqlR+4cIFxfbCmJiYoGXLlvjjjz9Utl24cAGNGzeGjY2NUhuv1/3jjz8gl8uL7IOIiIiIiKgiMKgkz8/PD3l5eVi3bp2iTCaTYfPmzfD29lasrBkbG4uYmBiVfS9duqSUvN26dQunTp3CsGHDFGXdunVDzZo1sXbtWqX9165dC2tra/Tt27csDo30zNLSEvPmzSv0vk2iyobzgSgf5wJRPs4F4yMRoqT1N8vXu+++i/3792P69OlwcXHB1q1bcfHiRZw8eRKdOnUCAHTp0gWnT59WWjo0LS0NrVu3RlpaGgIDA2Fubo5ly5YhLy8PV69ehb29vaLumjVrMGnSJPj5+aFnz544c+YMtm3bhoULF2L27NnlfsxERERERES6YnBJXlZWFubOnYsdO3bgxYsX8PT0xNdff42ePXsq6hSW5AHA48ePMX36dBw/fhxyuRxdunTBd999BxcXF5V+1q9fj6VLl+LBgwdwcnLC5MmT8emnn3KVTCIiIiIiqtAMLskjIiIiIiIi7RnUPXlERERERERUOkzyiIiIiIiIjAiTPKqw1qxZA4lEAm9v70K3SyQSTJ48udBtW7ZsgUQiUVqNdf78+ZBIJIqXtbU1mjdvji+++ELlsR5Eunb9+nX4+fmhQYMGkEqlqFevHrp3746VK1cCAJo3b4433nhDZb/9+/dDIpGgc+fOKts2bdoEiUSC48ePK5UfOXIEEokEjo6OkMvlhcbTsGFDpflQpUoVeHl5Ydu2bUUeQ15eHhwdHSGRSPDbb79pcvhEJSrs9/arHj58qPSZlUgksLW1RatWrbBq1Srk5eUBAPbu3QuJRIL9+/ertPHGG29AIpEgPDxcZZuzszN8fHxUyr28vCCRSFRW7SbSVEnfA6979913IZFI8Pnnnxe6PSIiQmk+mJubo3HjxggICMD9+/cV9QqbO6++vvnmGyQkJMDMzAz+/v5Fxp+WlgYrKysMGTJEqfzw4cPo1asX7OzsIJVK4erqisDAQCQlJWkxSqQuM30HQKStnTt3omHDhrh48SLu3r1b6AI72li7di2qVq2K9PR0HD9+HAsXLsSpU6cQFRXFhXmoTJw9exZdu3aFs7MzPvzwQ9StWxdxcXE4f/48li9fjilTpsDX1xcbN25ESkoKqlWrptg3KioKZmZmuHTpEnJycmBubq60zdTUFB06dFDqr2DuPHz4EKdOncI777xTaFytWrXCzJkzAQDx8fHYsGEDRo8eDZlMhg8//FCl/qlTpxAfH4+GDRti586d6N27ty6Gh0gjI0eORJ8+fQAAKSkpOHLkCKZMmYJHjx4hJCQEvr6+AIDIyEgMHjxYsV9qaipu3LgBMzMzREVFoWvXroptcXFxiIuLw4gRI5T6unPnDi5duqT4zH/yySflcIRkjNT5HnhVamoqfvnlFzRs2BA//fQTvvnmmyL/Rpk6dSratWuHnJwcXL58GevWrcOvv/6K69evw9HRUVHv1bnzqtatW6N27dro3r07Dh48iIyMDFhbW6vUCwsLQ1ZWllIiGBgYiKVLl+KNN97A559/jpo1a+Ly5ctYtWoVdu/ejZMnT6JZs2baDhsVRxBVQPfv3xcARFhYmLC3txfz589XqQNATJo0qdD9N2/eLACIS5cuKcrmzZsnAIjnz58r1R0yZIgAIM6ePavbgyD6//r06SPs7e3FixcvVLb9888/Qgghtm7dKgCII0eOKG1v3769eO+99wQAce7cOaVtrq6uonXr1kpl6enpokqVKmLFihWidevWYsyYMYXG1KBBA9G3b1+lsoSEBFG1alXh7u5e6D4BAQGiTZs2Yvny5aJKlSoiPT292OMm0kRhv7df9eDBAwFAhISEKJXL5XLRrl074ejoqChr1KiR8PLyUqp39OhRIZFIxMiRI0XPnj2Vtu3atUsAEAcPHlQq//LLL0Xt2rXFvn37hEQiEQ8ePCjFEVJlps73wKs2bdokzM3NxalTpwQAERERoVInPDxcABA///yzUvmKFSsEALFo0SIhRNFz53Xbt28XAMRPP/1U6PYePXqIatWqiaysLCHE/82b4cOHi9zcXKW6Fy5cENbW1qJly5YiJyen2H5JO7xckyqknTt3okaNGujbty/8/Pywc+fOMuurW7duAIAHDx6UWR9Uud27dw8tWrRA9erVVbbVrl0bABRnH6KiohTbsrKycPnyZQwZMgSNGzdW2vb8+XPcvn1bsV+B/fv3IzMzE8OGDcOIESMU//KqDnt7e7i5ueHevXsq2zIzM7F//36MGDEC7777LjIzM3Hw4EG12iUqSxKJBHXq1IGZ2f9dvOTr64srV64gMzNTURYVFYUWLVqgd+/eOH/+vNKlzAVXcnTs2FGp7V27dsHPzw/9+vVDtWrVsGvXrrI/IDJK6nwPvGrnzp3o3r07unbtCnd3d43+DtL275rBgwejSpUqhX7OExIScPLkSfj5+SkeqB4cHIwaNWpg3bp1MDU1Varv5eWFzz//HNevX0doaKhGcZB6mORRhbRz504MGTIEFhYWGDlypOKSmddlZWUhMTFR5ZWenq52XwV/0NrZ2eksfqJXNWjQAH/++Sdu3LhRZJ3GjRvD0dERkZGRirJLly4hOzsbPj4+8PHxUUryzp49CwAqSd7OnTvRtWtX1K1bFyNGjEBaWhp++eUXteLMzc3F48ePUaNGDZVthw4dQnp6OkaMGIG6deuiS5cuZfqPL0RFycjIUPyuv3//PlavXo2jR49i9OjRijq+vr7IycnBhQsXFGVRUVGKuZSSkqI0H6OiouDm5qb0PXDhwgXcvXsXI0eOhIWFBYYMGcLPPGlNne+BAk+fPkV4eDhGjhwJIP8yy9DQUGRnZ6vVV1F/17w6d1595ebmAgCqVKmCgQMH4tixY0hOTlbad8+ePcjLy8OoUaMA5F/KfOvWLQwcOBC2traFxhEQEAAg/549KgP6PpVIpKk//vhDABAnTpwQQuRfilO/fn3x6aefKtUDUOKrsMs1b926JZ4/fy4ePHggfvzxR2FpaSnq1Kkj/v333/I8TKpEjh8/LkxNTYWpqano0KGDmDVrljh27JjIzs5Wqjds2DBhZWWlKF+8eLFo1KiREEKINWvWiNq1ayvqBgYGCgDiyZMnirJ//vlHmJmZifXr1yvKfHx8xMCBA1ViatCggejRo4d4/vy5eP78ubh+/bp4//33i7wMul+/fqJjx46K9+vWrRNmZmYiISFBu0Eheo26l2sW9vrkk0+EXC5X1L1586YAIL7++mshhBA5OTmiSpUqYuvWrUIIIerUqSNWr14thBAiNTVVmJqaig8//FCpv8mTJwsnJydFu8ePHxcAxJUrV3R96FQJqPs9IIQQ//3vf4WVlZVITU0VQghx+/ZtAUDs379fqV7B5ZqbNm0Sz58/F0+fPhW//vqraNiwoZBIJIq5VNzcwWu3Avz6668CgPjxxx+V+mrfvr2oV6+eyMvLE0IIceDAAQFAfPfdd8Uet62trWjTpo2mw0VqYJJHFc706dNFnTp1lK7vnjlzpkoZADFw4EBx4sQJlddnn31WZJL3+qtFixbijz/+KNdjpMrn4sWLYvDgwcLa2lrx2bO3t1e6B2j58uVKX7j9+vUTo0aNEkIIce3aNQFA3L59WwghRIcOHRQJ4Kv7W1hYiOTkZEXZypUrVcqEyE/yCpsPY8eOFRkZGUp1ExMThbm5uVi1apWiLCkpSaWMqDTUTfImTJig+F2/b98+MWnSJGFiYiKmTZumqCuXy4WdnZ3i3ruCfzy8c+eOEEKIwYMHi/fee08IIcSxY8cEAEUCKER+Umhvby8CAwMVZbm5uaJ27dpKZUSaUOd7QAghWrduLfz8/JTK2rZtq1JWkOS9/rK3txfbtm1T1Cts7rz6SklJUdQt+Ox37txZUVawTsKrn/2C+/c2bNhQ7DHXq1dPuLi4qD1GpD6urkkVSl5eHnbv3o2uXbsqXUvu7e2NpUuX4uTJk+jRo4eivH79+oWuHPj48eMi+9i3bx9sbW1hbm6O+vXro0mTJro9CKJCtGvXDmFhYcjOzsa1a9ewf/9+fPfdd/Dz88PVq1fRvHlzpfvyvL29cfbsWSxYsAAA4OHhAVtbW0RFRcHJyQl//vknhg8frtTHjh074OXlhaSkJMXS1a1bt0Z2djZ+/vlnTJgwQam+t7c3FixYgLy8PNy4cQMLFizAixcvYGFhoVRvz549yMnJQevWrXH37l2l/Xfu3IlJkybpfLyIitK0aVOl3/tDhgyBRCLB999/j3HjxqFly5aQSCTw8fHB77//DrlcjqioKNSuXVuxSrOPjw9WrVoF4P/ug3310ufjx4/j+fPn8PLyUvrMd+3aFT/99BOWLFkCExPeEUOaUed7IDo6GleuXEFAQIDSZ69Lly5YvXo1UlNTVS6P/PLLL/HWW2/B1NQUtWrVgru7u9I9qgVenzuFMTMzw/Dhw7FmzRo8efIE9erVU9yjV3CpJgDY2NgAyH+sQnHS0tIKveeQdEDfWSaRJgouhynqFRAQoKgLHa2uSaQvBZ/TgtVjc3NzhY2NjRg0aJD4+++/BQBx9epVRf3u3buL8ePHi99//13lcpqCy3mKenXq1Emp78JW1zx8+LAAIJYuXapU7uPjU2zb9+7d0/XQUCWk7eqaQgixf/9+AUDpzPKSJUsUc+jdd98VgwYNUmyLiooSAMTjx49Ft27dlFbmFEIoVrQt6nXq1CkdHTVVdq9/D8yePbvYz96mTZsU+xa1uubr1F1ds8D58+eV6rdo0UI0b95cqc6tW7cUV38U5eHDhwKA4ooU0i2eyaMKZefOnahduzZWr16tsi0sLAz79+/HDz/8ACsrKz1ER6Rbb775JoD8Z9QBgKmpKdq3b4+oqChERkbC1tYWLVu2VNT38fHBnj17FGcjXj3zsHPnTpibm2P79u0qq5xFRkZixYoViI2NhbOzc5Hx9O3bF507d8aiRYvw0UcfoUqVKnjw4AHOnj2LyZMnqzyQXS6X4/3338euXbvwxRdflG4wiEqhYOGIVxfdevV5eVFRUZg2bZpiW9u2bWFpaYmIiAhcuHBB6dlh//77Lw4ePIjhw4fDz89Ppa+pU6cqFjgiKq1XvweEENi1axe6du2KiRMnqtT9+uuvsXPnTowdO7ZMY/L29kaTJk2wa9cudO/eHTdv3sTChQuV6ri6usLV1RUHDhzA8uXLFWf2XrVt2zYAQL9+/co03kpL31kmkboyMjKEjY2NGDduXKHbC/7ldffu3UIInsmjiuPUqVNKi0IUKDjTsGzZMkVZcHCwACA6dOggunfvrlT/2LFjQiKRiPbt2ws7OzulNl1cXES3bt0K7f/x48dCIpGIb775RlFW2Jk8IYQ4cuSI0s30X3/9tQAgYmNjC227e/fuws3NreiDJ1JTac7kBQQECADit99+U5TJZDIhlUpFhw4dBAARFRWltE+HDh0U25YvX64oL7jX6Pfffy80jg8//FBUr15d8awwInWo8z1w5swZAUDpfrpXLVy4UJiYmCgW3CqrM3lC5D8jEv9/7YOinhG5Y8cOAUC89957Ks/J++OPP0SVKlWEh4dHoYvLUOnxTB5VGIcOHUJaWhoGDBhQ6Pb27dvD3t4eO3fuVLkXiciQTZkyBRkZGRg8eDDc3NyQnZ2Ns2fPYs+ePWjYsKHSv8oWnH04d+4c5s+fr9RO+/btIZFIcP78efTv3x8SiQTA/y31Pnny5EL7r1evHtq0aYOdO3fi888/LzbW3r17w8PDA8uWLcOkSZOwc+dOtGrVCk5OToXWHzBgAKZMmYLLly+jTZs26g4JUZE2bdqEo0ePqpQPHDgQAHD58mXs2LEDQP79PidPnsS+ffvg4+OjdM+2hYUF2rVrhzNnzsDS0hJt27ZVas/HxwdLly4FoHpW3M7ODj4+PoXGN2DAAKxfvx6//vorhgwZUrqDpUpDne+BoKAgmJqaom/fvoW2MWDAAMyZMwe7d+/GjBkzNI7h1bnzqiZNmqBDhw5KZf7+/vjqq69w8OBBdOzYEQ0bNlTZb9SoUbh06RKWL1+Ov//+G6NGjUKNGjVw+fJlbNq0CXZ2dggNDYW5ubnGsZIa9J1lEqmrf//+QiqVFvsogzFjxghzc3ORmJjIM3lUYfz2229i3Lhxws3NTVStWlVYWFgIFxcXMWXKFPHPP/8o1f3333+FmZmZACCOHz+u0panp6cAIJYsWaIomzJlSon3xs2fP18AENeuXRNCFH0mTwghtmzZorg3D4CYO3duke0W3HMxffr0YseAqCQFv7eLehWc5Xj1ZWZmJho3biw+++wzkZaWptJmUFCQACB8fHxUtoWFhQkAwsbGRnEWouAxJO+//36RcWZkZAhra2sxePBg3R08Gb2Svgeys7OFnZ2deOutt4ptp1GjRqJ169ZCCM3P5BX1Gj16dKH7tWvXTgAQa9asKbb9AwcOiO7du4saNWoIS0tL4eLiImbOnMm/t8qYRAghyj6VJCIiIiIiovLA9X2JiIiIiIiMCJM8IiIiIiIiI8Ikj4iIiIiIyIgwySMiIiIiIjIiTPKIiIiIiIiMCJM8IiIiIiIiI8Ikj4iIiIiIyIgwySMiIiIiIjIiTPKIiIiIiIiMCJM8IiIyaGPGjEHDhg213rdq1aql6n/+/PmQSCSlaqMi69KlCzw8PMq8n4cPH0IikWDLli1l3hcRkbFjkkdERBrbu3cvJBIJ9u/fr7LtjTfegEQiQXh4uMo2Z2dn+Pj4lEeIGsnIyMD8+fMRERGh71D04unTp5g/fz6uXr2q71CIiEgHmOQREZHGfH19AQCRkZFK5ampqbhx4wbMzMwQFRWltC0uLg5xcXGKfdW1fv163Lp1q3QBlyAjIwPBwcGFJnlffPEFMjMzy7R/fXv69CmCg4OZ5BERGQkzfQdAREQVj6OjIxo1aqSS5J07dw5CCAwbNkxlW8F7TZM8c3Pz0gVbSmZmZjAz49clERFVHDyTR0REWvH19cWVK1eUznJFRUWhRYsW6N27N86fPw+5XK60TSKRoGPHjoqyHTt2oG3btrCyskLNmjUxYsQIxMXFKfVT2D15SUlJeP/992Fra4vq1atj9OjRuHbtWpH3dD158gSDBg1C1apVYW9vj8DAQOTl5QHIvxfM3t4eABAcHAyJRAKJRIL58+cDKPyePIlEgsmTJ+PAgQPw8PCApaUlWrRogaNHj6r0HRERgTfffBNSqRRNmjTBjz/+qPZ9fgX3w/3111/o3LkzrK2t4eLigtDQUADA6dOn4e3tDSsrKzRr1gz/+9//Cj32cePGoU6dOoo4N23apBRfu3btAABjx45VHP/r4/j333+ja9eusLa2Rr169fDtt9+q9JWQkIDx48ejTp06kEqleOONN7B161aVei9fvsSYMWNQrVo1xc/v5cuXKvWePXuGsWPHon79+rC0tISDgwMGDhyIhw8fljh2RESVGZM8IiLSiq+vL3JycnDhwgVFWVRUFHx8fODj44OUlBTcuHFDaZubmxvs7OwAAAsXLkRAQACaNm2KZcuWYdq0aTh58iQ6depU6B/8BeRyOfr374+ffvoJo0ePxsKFCxEfH4/Ro0cXWj8vLw89e/aEnZ0d/vvf/6Jz585YunQp1q1bBwCwt7fH2rVrAQCDBw/G9u3bsX37dgwZMqTY44+MjMTEiRMxYsQIfPvtt8jKysLQoUORlJSkqHPlyhX06tULSUlJCA4Oxvjx4/HVV1/hwIEDxbb9qhcvXqBfv37w9vbGt99+C0tLS4wYMQJ79uzBiBEj0KdPH3zzzTf4999/4efnh7S0NMW+//zzD9q3b4///e9/mDx5MpYvXw4XFxeMHz8e33//PQDA3d0dX331FQBgwoQJiuPv1KmTUgy9evXCG2+8gaVLl8LNzQ2ff/45fvvtN0WdzMxMdOnSBdu3b8eoUaMQEhKCatWqYcyYMVi+fLminhACAwcOxPbt2+Hv748FCxbg8ePHhf78hg4div3792Ps2LFYs2YNpk6dirS0NMTGxqo9fkRElZIgIiLSws2bNwUA8fXXXwshhMjJyRFVqlQRW7duFUIIUadOHbF69WohhBCpqanC1NRUfPjhh0IIIR4+fChMTU3FwoULldq8fv26MDMzUyofPXq0aNCggeL9vn37BADx/fffK8ry8vJEt27dBACxefNmpX0BiK+++kqpn9atW4u2bdsq3j9//lwAEPPmzVM5znnz5onXvy4BCAsLC3H37l1F2bVr1wQAsXLlSkVZ//79hbW1tXjy5Imi7M6dO8LMzEylzcJ07txZABC7du1SlMXExAgAwsTERJw/f15RfuzYMZXjHz9+vHBwcBCJiYlK7Y4YMUJUq1ZNZGRkCCGEuHTpksq+r8ewbds2RZlMJhN169YVQ4cOVZR9//33AoDYsWOHoiw7O1t06NBBVK1aVaSmpgohhDhw4IAAIL799ltFvdzcXPHWW28pxfDixQsBQISEhJQ4TkREpIxn8oiISCvu7u6ws7NT3Gt37do1/Pvvv4rVM318fBSLr5w7dw55eXmK+/HCwsIgl8vx7rvvIjExUfGqW7cumjZtWujKnAWOHj0Kc3NzfPjhh4oyExMTTJo0qch9Pv74Y6X3b731Fu7fv6/dgf9/77zzDpo0aaJ47+npCVtbW0W7eXl5+N///odBgwbB0dFRUc/FxQW9e/dWu5+qVatixIgRivfNmjVD9erV4e7uDm9vb0V5wf8X9C+EwL59+9C/f38IIZTGuWfPnkhJScHly5fVjsHf31/x3sLCAl5eXkpjeOTIEdStWxcjR45UlJmbm2Pq1KlIT0/H6dOnFfXMzMzwySefKOqZmppiypQpSn1aWVnBwsICERERePHihVpxEhFRPt5JTkREWpFIJPDx8cHvv/8OuVyOqKgo1K5dGy4uLgDyk7xVq1YBgCLZK0jy7ty5AyEEmjZtWmjbxS228ujRIzg4OMDa2lqpvKDf10mlUsU9dwVq1KhR6sTB2dlZpezVdhMSEpCZmVloXEXFWpj69eur3L9XrVo1ODk5qZQBUPT//PlzvHz5EuvWrVNcmvq6hIQErWOoUaMG/vrrL8X7R48eoWnTpjAxUf73Y3d3d8X2gv86ODioPL+wWbNmSu8tLS2xZMkSzJw5E3Xq1EH79u3Rr18/BAQEoG7dumrFTURUWTHJIyIirfn6+uKXX37B9evXFffjFfDx8cFnn32GJ0+eIDIyEo6OjmjcuDGA/PvqJBIJfvvtN5iamqq0W9oHmL+qsPbLsl0hRLn0U1L/BYve+Pv7F3m/oqenZ6li0PWxvm7atGno378/Dhw4gGPHjmHu3LlYvHgxTp06hdatW5dp30REFRmTPCIi0tqrz8uLiorCtGnTFNvatm0LS0tLRERE4MKFC+jTp49iW5MmTSCEQKNGjeDq6qpRnw0aNEB4eDgyMjKUzubdvXtX6+NQZ6VLTdWuXRtSqbTQuEoTq7rs7e1hY2ODvLw8vPPOO8XW1cXxN2jQAH/99RfkcrnS2byYmBjF9oL/njx5Eunp6UrJfFHPQmzSpAlmzpyJmTNn4s6dO2jVqhWWLl2KHTt2lDpmIiJjxXvyiIhIawWPBti5cyeePHmidCbP0tISbdq0werVq/Hvv/8qPR9vyJAhMDU1RXBwsMrZICGE0gqVr+vZsydycnKwfv16RZlcLsfq1au1Po6CZLG4VT01ZWpqinfeeQcHDhzA06dPFeV3795VWpWyrJiammLo0KHYt2+f0iqnBZ4/f674/ypVqgAo3fH36dMHz549w549exRlubm5WLlyJapWrYrOnTsr6uXm5ipWNAXy719cuXKlUnsZGRnIyspSKmvSpAlsbGwgk8m0jpOIqDLgmTwiItKahYUF2rVrhzNnzsDS0hJt27ZV2u7j44OlS5cCUH4IepMmTbBgwQIEBQXh4cOHGDRoEGxsbPDgwQPs378fEyZMQGBgYKF9Dho0CF5eXpg5cybu3r0LNzc3HDp0CMnJyQC0OytlZWWF5s2bY8+ePXB1dUXNmjXh4eEBDw8Pjdt61fz583H8+HF07NgRn3zyCfLy8rBq1Sp4eHjg6tWrpWpbHd988w3Cw8Ph7e2NDz/8EM2bN0dycjIuX76M//3vf4oxa9KkCapXr44ffvgBNjY2qFKlCry9vdGoUSO1+5owYQJ+/PFHjBkzBn/++ScaNmyI0NBQREVF4fvvv4eNjQ0AoH///ujYsSP+85//4OHDh2jevDnCwsKQkpKi1N7t27fx9ttv491330Xz5s1hZmaG/fv3459//lFaiIaIiFTxTB4REZVKQfJWcHnmqwoefG5jY4M33nhDadt//vMf7Nu3DyYmJggODkZgYCAOHTqEHj16YMCAAUX2Z2pqil9//RXDhw/H1q1bMWfOHDg6OirO5EmlUq2OY8OGDahXrx6mT5+OkSNHKh44Xhpt27bFb7/9hho1amDu3LnYuHEjvvrqK7z99ttax6mJOnXq4OLFixg7dizCwsIUz8pLTk7GkiVLFPXMzc2xdetWmJqa4uOPP8bIkSMVq2Gqy8rKChERERg1ahS2bt2KmTNnIjk5GZs3b8ann36qqGdiYoJDhw5h1KhR2LFjB+bMmYN69eqpPDTdyckJI0eOREREBIKCghAUFITU1FTs3bsXQ4cOLd3AEBEZOYko67umiYiIysGBAwcwePBgREZGKpJLQzVo0CDcvHkTd+7c0XcoRERkhHgmj4iIKpzMzEyl9wX3dNna2qJNmzZ6iqpwr8d6584dHDlyBF26dNFPQEREZPR4Tx4REVU4U6ZMQWZmJjp06ACZTIawsDCcPXsWixYtgpWVlb7DU9K4cWOMGTMGjRs3xqNHj7B27VpYWFhg1qxZ+g6NiIiMFC/XJCKiCmfXrl1YunQp7t69i6ysLLi4uOCTTz7B5MmT9R2airFjxyI8PBzPnj2DpaUlOnTogEWLFhncGUciIjIeTPKIiIiIiIiMCO/JIyIiIiIiMiJM8oiIiIiIiIwIkzwiIiIiIiIjwiSPiIiIiIjIiDDJIyIiIiIiMiJM8oiIiIiIiIwIkzwiIiIiIiIjwiSPiIiIiIjIiPw/aNRI37jdtXUAAAAASUVORK5CYII=", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_barplot_stacked(df_weights.T, stacked = False)" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_radar_weights(df_weights)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Determine utility function values using the VIKOR method and rank alternatives to generate rankings for each weighting method." ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "weighting_methods_names = ['AHP', 'SWARA', 'LBWA', 'SAPEVO']\n", "weights_list = [weights_ahp, weights_swara, weights_lbwa, weights_sapevo]\n", "\n", "# MCDA assessment\n", "# dataframe for alternatives\n", "alts = [r'$A_{' + str(j) + '}$' for j in range(1, matrix.shape[0] + 1)]\n", "df_prefs = pd.DataFrame(index = alts)\n", "df_ranks = pd.DataFrame(index = alts)\n", "\n", "vikor = VIKOR()\n", "for el, weights in enumerate(weights_list):\n", " pref = vikor(matrix, weights, types)\n", " rank = rank_preferences(pref, reverse=False)\n", "\n", " df_prefs[weighting_methods_names[el]] = pref\n", " df_ranks[weighting_methods_names[el]] = rank" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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AHPSWARALBWASAPEVO
$A_{1}$0.9712620.9228280.8635880.962927
$A_{2}$0.0000000.0000000.0000000.000000
$A_{3}$0.9411760.9411760.8618220.925714
$A_{4}$0.9541060.8826631.0000000.937836
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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_radar(df_ranks)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.5" } }, "nbformat": 4, "nbformat_minor": 4 }