From ef3de357f9adb2e492098dcd9f1027b9635fc116 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Bertrand=20N=C3=A9ron?= <bneron@pasteur.fr>
Date: Thu, 17 Oct 2024 14:45:16 +0200
Subject: [PATCH] fix path in statsmodel_cours
---
notebooks/Courses/statsmodels_cours.ipynb | 4360 +----------------
.../{ => Courses}/statsmodels_material.py | 0
notebooks/data/patients.csv | 201 +
3 files changed, 389 insertions(+), 4172 deletions(-)
rename notebooks/{ => Courses}/statsmodels_material.py (100%)
create mode 100644 notebooks/data/patients.csv
diff --git a/notebooks/Courses/statsmodels_cours.ipynb b/notebooks/Courses/statsmodels_cours.ipynb
index 57c7c38..b7acbd3 100644
--- a/notebooks/Courses/statsmodels_cours.ipynb
+++ b/notebooks/Courses/statsmodels_cours.ipynb
@@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": null,
"id": "ce9d2cf1-9281-4a58-9dcd-3b0b1ab7cb0b",
"metadata": {
"tags": []
@@ -19,7 +19,7 @@
"id": "f0b66572-e886-4b73-9a82-2f26a1295280",
"metadata": {},
"source": [
- "<div style=\"text-align: center; margin-top: 50px; margin-bottom: 50px\"><img alt=\"StatsModels logo\" src=\"images/statsmodels-logo-v2-horizontal.svg\" width=\"60%\" /></div>\n",
+ "<div style=\"text-align: center; margin-top: 50px; margin-bottom: 50px\"><img alt=\"StatsModels logo\" src=\"../images/statsmodels-logo-v2-horizontal.svg\" width=\"60%\" /></div>\n",
"\n",
"The statsmodels library provides utilities for the design of linear models of one or more response (or dependent) variables as a function of explanatory (or independent) variables.\n",
"\n",
@@ -28,7 +28,7 @@
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": null,
"id": "d6590258-e1ac-4f62-8adf-3fa014376a22",
"metadata": {},
"outputs": [],
@@ -39,7 +39,7 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": null,
"id": "7b4f63c1-9995-4516-aeb5-1fb4fe1db896",
"metadata": {},
"outputs": [],
@@ -62,147 +62,10 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": null,
"id": "79b07451-6f60-43b3-980b-1e8ebd46baaa",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
- "\n",
- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>Sex</th>\n",
- " <th>Risk</th>\n",
- " <th>Drug</th>\n",
- " <th>Cholesterol</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>0</th>\n",
- " <td>M</td>\n",
- " <td>Low</td>\n",
- " <td>A</td>\n",
- " <td>4.868845</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>5</th>\n",
- " <td>M</td>\n",
- " <td>Low</td>\n",
- " <td>B</td>\n",
- " <td>5.573970</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>10</th>\n",
- " <td>M</td>\n",
- " <td>Low</td>\n",
- " <td>C</td>\n",
- " <td>6.507308</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>15</th>\n",
- " <td>M</td>\n",
- " <td>High</td>\n",
- " <td>A</td>\n",
- " <td>7.787113</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>20</th>\n",
- " <td>M</td>\n",
- " <td>High</td>\n",
- " <td>B</td>\n",
- " <td>6.877862</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>25</th>\n",
- " <td>M</td>\n",
- " <td>High</td>\n",
- " <td>C</td>\n",
- " <td>5.320824</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>30</th>\n",
- " <td>F</td>\n",
- " <td>Low</td>\n",
- " <td>A</td>\n",
- " <td>4.675374</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>35</th>\n",
- " <td>F</td>\n",
- " <td>Low</td>\n",
- " <td>B</td>\n",
- " <td>6.942870</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>40</th>\n",
- " <td>F</td>\n",
- " <td>Low</td>\n",
- " <td>C</td>\n",
- " <td>4.659411</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>45</th>\n",
- " <td>F</td>\n",
- " <td>High</td>\n",
- " <td>A</td>\n",
- " <td>5.429768</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>50</th>\n",
- " <td>F</td>\n",
- " <td>High</td>\n",
- " <td>B</td>\n",
- " <td>4.702679</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>55</th>\n",
- " <td>F</td>\n",
- " <td>High</td>\n",
- " <td>C</td>\n",
- " <td>5.151045</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " Sex Risk Drug Cholesterol\n",
- "0 M Low A 4.868845\n",
- "5 M Low B 5.573970\n",
- "10 M Low C 6.507308\n",
- "15 M High A 7.787113\n",
- "20 M High B 6.877862\n",
- "25 M High C 5.320824\n",
- "30 F Low A 4.675374\n",
- "35 F Low B 6.942870\n",
- "40 F Low C 4.659411\n",
- "45 F High A 5.429768\n",
- "50 F High B 4.702679\n",
- "55 F High C 5.151045"
- ]
- },
- "execution_count": 4,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"df = pg.read_dataset('anova3')\n",
"df.loc[range(0, df.shape[0], 5)]"
@@ -210,7 +73,7 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": null,
"id": "0b44ca4b-baa1-4210-85ce-5284e0f320db",
"metadata": {},
"outputs": [],
@@ -248,7 +111,7 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": null,
"id": "aec2f6b1-c4fc-465e-9434-b32333770e24",
"metadata": {},
"outputs": [],
@@ -268,25 +131,10 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": null,
"id": "696ff83f-d827-4513-9801-51488e5a1df0",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "(array([85, 86, 88, 75, 78, 94, 98, 79, 71, 80, 91, 92, 93, 85, 87, 84, 82,\n",
- " 88, 95, 96, 79, 78, 88, 94, 92, 85, 83, 85, 82, 81]),\n",
- " array(['A', 'A', 'A', 'A', 'A', 'A', 'A', 'A', 'A', 'A', 'B', 'B', 'B',\n",
- " 'B', 'B', 'B', 'B', 'B', 'B', 'B', 'C', 'C', 'C', 'C', 'C', 'C',\n",
- " 'C', 'C', 'C', 'C'], dtype='<U1'))"
- ]
- },
- "execution_count": 7,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"Y = np.concatenate((A, B, C))\n",
"Group = np.repeat(['A', 'B', 'C'], (len(A), len(B), len(C)))\n",
@@ -295,229 +143,10 @@
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": null,
"id": "c324bd0f-e769-4a0d-8e6b-d4d346e76f68",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
- "\n",
- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>Y</th>\n",
- " <th>Group</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>0</th>\n",
- " <td>85</td>\n",
- " <td>A</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1</th>\n",
- " <td>86</td>\n",
- " <td>A</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2</th>\n",
- " <td>88</td>\n",
- " <td>A</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>3</th>\n",
- " <td>75</td>\n",
- " <td>A</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>4</th>\n",
- " <td>78</td>\n",
- " <td>A</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>5</th>\n",
- " <td>94</td>\n",
- " <td>A</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>6</th>\n",
- " <td>98</td>\n",
- " <td>A</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>7</th>\n",
- " <td>79</td>\n",
- " <td>A</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>8</th>\n",
- " <td>71</td>\n",
- " <td>A</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>9</th>\n",
- " <td>80</td>\n",
- " <td>A</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>10</th>\n",
- " <td>91</td>\n",
- " <td>B</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>11</th>\n",
- " <td>92</td>\n",
- " <td>B</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>12</th>\n",
- " <td>93</td>\n",
- " <td>B</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>13</th>\n",
- " <td>85</td>\n",
- " <td>B</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>14</th>\n",
- " <td>87</td>\n",
- " <td>B</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>15</th>\n",
- " <td>84</td>\n",
- " <td>B</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>16</th>\n",
- " <td>82</td>\n",
- " <td>B</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>17</th>\n",
- " <td>88</td>\n",
- " <td>B</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>18</th>\n",
- " <td>95</td>\n",
- " <td>B</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>19</th>\n",
- " <td>96</td>\n",
- " <td>B</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>20</th>\n",
- " <td>79</td>\n",
- " <td>C</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>21</th>\n",
- " <td>78</td>\n",
- " <td>C</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>22</th>\n",
- " <td>88</td>\n",
- " <td>C</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>23</th>\n",
- " <td>94</td>\n",
- " <td>C</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>24</th>\n",
- " <td>92</td>\n",
- " <td>C</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>25</th>\n",
- " <td>85</td>\n",
- " <td>C</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>26</th>\n",
- " <td>83</td>\n",
- " <td>C</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>27</th>\n",
- " <td>85</td>\n",
- " <td>C</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>28</th>\n",
- " <td>82</td>\n",
- " <td>C</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>29</th>\n",
- " <td>81</td>\n",
- " <td>C</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " Y Group\n",
- "0 85 A\n",
- "1 86 A\n",
- "2 88 A\n",
- "3 75 A\n",
- "4 78 A\n",
- "5 94 A\n",
- "6 98 A\n",
- "7 79 A\n",
- "8 71 A\n",
- "9 80 A\n",
- "10 91 B\n",
- "11 92 B\n",
- "12 93 B\n",
- "13 85 B\n",
- "14 87 B\n",
- "15 84 B\n",
- "16 82 B\n",
- "17 88 B\n",
- "18 95 B\n",
- "19 96 B\n",
- "20 79 C\n",
- "21 78 C\n",
- "22 88 C\n",
- "23 94 C\n",
- "24 92 C\n",
- "25 85 C\n",
- "26 83 C\n",
- "27 85 C\n",
- "28 82 C\n",
- "29 81 C"
- ]
- },
- "execution_count": 8,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"dataframe = pd.DataFrame(dict(Y=Y, Group=Group))\n",
"dataframe"
@@ -544,84 +173,20 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": null,
"id": "a597c0ef-75e7-47e1-a959-e7a7324b02e2",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "F_onewayResult(statistic=2.3575322551335636, pvalue=0.11384795345837218)"
- ]
- },
- "execution_count": 9,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"stats.f_oneway(A, B, C)"
]
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": null,
"id": "90c687e7-e9b7-44f0-8148-d93bb8605505",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
- "\n",
- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>Source</th>\n",
- " <th>ddof1</th>\n",
- " <th>ddof2</th>\n",
- " <th>F</th>\n",
- " <th>p-unc</th>\n",
- " <th>np2</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>0</th>\n",
- " <td>Group</td>\n",
- " <td>2</td>\n",
- " <td>27</td>\n",
- " <td>2.357532</td>\n",
- " <td>0.113848</td>\n",
- " <td>0.14867</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " Source ddof1 ddof2 F p-unc np2\n",
- "0 Group 2 27 2.357532 0.113848 0.14867"
- ]
- },
- "execution_count": 10,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"pg.anova(dataframe, dv='Y', between='Group')"
]
@@ -636,7 +201,7 @@
},
{
"cell_type": "code",
- "execution_count": 11,
+ "execution_count": null,
"id": "4a2a00ec-43c6-4299-82e3-15b807110828",
"metadata": {
"hidden": true
@@ -648,72 +213,12 @@
},
{
"cell_type": "code",
- "execution_count": 12,
+ "execution_count": null,
"id": "21bf5c1d-caa3-4072-bc86-ce860b8f33c8",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
- "\n",
- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>df</th>\n",
- " <th>sum_sq</th>\n",
- " <th>mean_sq</th>\n",
- " <th>F</th>\n",
- " <th>PR(>F)</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>Group</th>\n",
- " <td>2.0</td>\n",
- " <td>192.2</td>\n",
- " <td>96.100000</td>\n",
- " <td>2.357532</td>\n",
- " <td>0.113848</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>Residual</th>\n",
- " <td>27.0</td>\n",
- " <td>1100.6</td>\n",
- " <td>40.762963</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " df sum_sq mean_sq F PR(>F)\n",
- "Group 2.0 192.2 96.100000 2.357532 0.113848\n",
- "Residual 27.0 1100.6 40.762963 NaN NaN"
- ]
- },
- "execution_count": 12,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"sm.stats.anova_lm(fitted_model)"
]
@@ -744,24 +249,13 @@
},
{
"cell_type": "code",
- "execution_count": 13,
+ "execution_count": null,
"id": "638bdd6b-6964-4209-b762-2991fd3fb7fc",
"metadata": {
"hidden": true,
"tags": []
},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "F_onewayResult(statistic=2.3575322551335636, pvalue=0.11384795345837218)"
- ]
- },
- "execution_count": 13,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"stats.f_oneway(A, B, C)"
]
@@ -778,148 +272,13 @@
},
{
"cell_type": "code",
- "execution_count": 14,
+ "execution_count": null,
"id": "0fe841a0-21b1-4c92-a767-c4ab3abd37f8",
"metadata": {
"hidden": true,
"tags": []
},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<table class=\"simpletable\">\n",
- "<caption>OLS Regression Results</caption>\n",
- "<tr>\n",
- " <th>Dep. Variable:</th> <td>Y</td> <th> R-squared: </th> <td> 0.149</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Model:</th> <td>OLS</td> <th> Adj. R-squared: </th> <td> 0.086</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Method:</th> <td>Least Squares</td> <th> F-statistic: </th> <td> 2.358</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Date:</th> <td>Mon, 21 Aug 2023</td> <th> Prob (F-statistic):</th> <td> 0.114</td> \n",
- "</tr>\n",
- "<tr>\n",
- " <th>Time:</th> <td>16:37:44</td> <th> Log-Likelihood: </th> <td> -96.604</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>No. Observations:</th> <td> 30</td> <th> AIC: </th> <td> 199.2</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Df Residuals:</th> <td> 27</td> <th> BIC: </th> <td> 203.4</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Df Model:</th> <td> 2</td> <th> </th> <td> </td> \n",
- "</tr>\n",
- "<tr>\n",
- " <th>Covariance Type:</th> <td>nonrobust</td> <th> </th> <td> </td> \n",
- "</tr>\n",
- "</table>\n",
- "<table class=\"simpletable\">\n",
- "<tr>\n",
- " <td></td> <th>coef</th> <th>std err</th> <th>t</th> <th>P>|t|</th> <th>[0.025</th> <th>0.975]</th> \n",
- "</tr>\n",
- "<tr>\n",
- " <th>Intercept</th> <td> 83.4000</td> <td> 2.019</td> <td> 41.308</td> <td> 0.000</td> <td> 79.257</td> <td> 87.543</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Group[T.B]</th> <td> 5.9000</td> <td> 2.855</td> <td> 2.066</td> <td> 0.049</td> <td> 0.041</td> <td> 11.759</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Group[T.C]</th> <td> 1.3000</td> <td> 2.855</td> <td> 0.455</td> <td> 0.653</td> <td> -4.559</td> <td> 7.159</td>\n",
- "</tr>\n",
- "</table>\n",
- "<table class=\"simpletable\">\n",
- "<tr>\n",
- " <th>Omnibus:</th> <td> 0.758</td> <th> Durbin-Watson: </th> <td> 1.379</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Prob(Omnibus):</th> <td> 0.684</td> <th> Jarque-Bera (JB): </th> <td> 0.665</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Skew:</th> <td> 0.336</td> <th> Prob(JB): </th> <td> 0.717</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Kurtosis:</th> <td> 2.715</td> <th> Cond. No. </th> <td> 3.73</td>\n",
- "</tr>\n",
- "</table><br/><br/>Notes:<br/>[1] Standard Errors assume that the covariance matrix of the errors is correctly specified."
- ],
- "text/latex": [
- "\\begin{center}\n",
- "\\begin{tabular}{lclc}\n",
- "\\toprule\n",
- "\\textbf{Dep. Variable:} & Y & \\textbf{ R-squared: } & 0.149 \\\\\n",
- "\\textbf{Model:} & OLS & \\textbf{ Adj. R-squared: } & 0.086 \\\\\n",
- "\\textbf{Method:} & Least Squares & \\textbf{ F-statistic: } & 2.358 \\\\\n",
- "\\textbf{Date:} & Mon, 21 Aug 2023 & \\textbf{ Prob (F-statistic):} & 0.114 \\\\\n",
- "\\textbf{Time:} & 16:37:44 & \\textbf{ Log-Likelihood: } & -96.604 \\\\\n",
- "\\textbf{No. Observations:} & 30 & \\textbf{ AIC: } & 199.2 \\\\\n",
- "\\textbf{Df Residuals:} & 27 & \\textbf{ BIC: } & 203.4 \\\\\n",
- "\\textbf{Df Model:} & 2 & \\textbf{ } & \\\\\n",
- "\\textbf{Covariance Type:} & nonrobust & \\textbf{ } & \\\\\n",
- "\\bottomrule\n",
- "\\end{tabular}\n",
- "\\begin{tabular}{lcccccc}\n",
- " & \\textbf{coef} & \\textbf{std err} & \\textbf{t} & \\textbf{P$> |$t$|$} & \\textbf{[0.025} & \\textbf{0.975]} \\\\\n",
- "\\midrule\n",
- "\\textbf{Intercept} & 83.4000 & 2.019 & 41.308 & 0.000 & 79.257 & 87.543 \\\\\n",
- "\\textbf{Group[T.B]} & 5.9000 & 2.855 & 2.066 & 0.049 & 0.041 & 11.759 \\\\\n",
- "\\textbf{Group[T.C]} & 1.3000 & 2.855 & 0.455 & 0.653 & -4.559 & 7.159 \\\\\n",
- "\\bottomrule\n",
- "\\end{tabular}\n",
- "\\begin{tabular}{lclc}\n",
- "\\textbf{Omnibus:} & 0.758 & \\textbf{ Durbin-Watson: } & 1.379 \\\\\n",
- "\\textbf{Prob(Omnibus):} & 0.684 & \\textbf{ Jarque-Bera (JB): } & 0.665 \\\\\n",
- "\\textbf{Skew:} & 0.336 & \\textbf{ Prob(JB): } & 0.717 \\\\\n",
- "\\textbf{Kurtosis:} & 2.715 & \\textbf{ Cond. No. } & 3.73 \\\\\n",
- "\\bottomrule\n",
- "\\end{tabular}\n",
- "%\\caption{OLS Regression Results}\n",
- "\\end{center}\n",
- "\n",
- "Notes: \\newline\n",
- " [1] Standard Errors assume that the covariance matrix of the errors is correctly specified."
- ],
- "text/plain": [
- "<class 'statsmodels.iolib.summary.Summary'>\n",
- "\"\"\"\n",
- " OLS Regression Results \n",
- "==============================================================================\n",
- "Dep. Variable: Y R-squared: 0.149\n",
- "Model: OLS Adj. R-squared: 0.086\n",
- "Method: Least Squares F-statistic: 2.358\n",
- "Date: Mon, 21 Aug 2023 Prob (F-statistic): 0.114\n",
- "Time: 16:37:44 Log-Likelihood: -96.604\n",
- "No. Observations: 30 AIC: 199.2\n",
- "Df Residuals: 27 BIC: 203.4\n",
- "Df Model: 2 \n",
- "Covariance Type: nonrobust \n",
- "==============================================================================\n",
- " coef std err t P>|t| [0.025 0.975]\n",
- "------------------------------------------------------------------------------\n",
- "Intercept 83.4000 2.019 41.308 0.000 79.257 87.543\n",
- "Group[T.B] 5.9000 2.855 2.066 0.049 0.041 11.759\n",
- "Group[T.C] 1.3000 2.855 0.455 0.653 -4.559 7.159\n",
- "==============================================================================\n",
- "Omnibus: 0.758 Durbin-Watson: 1.379\n",
- "Prob(Omnibus): 0.684 Jarque-Bera (JB): 0.665\n",
- "Skew: 0.336 Prob(JB): 0.717\n",
- "Kurtosis: 2.715 Cond. No. 3.73\n",
- "==============================================================================\n",
- "\n",
- "Notes:\n",
- "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
- "\"\"\""
- ]
- },
- "execution_count": 14,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"fitted_model.summary()"
]
@@ -938,50 +297,10 @@
},
{
"cell_type": "code",
- "execution_count": 15,
+ "execution_count": null,
"id": "fb1e8107-18e7-4627-83af-eada7e8dcfca",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<table class=\"simpletable\">\n",
- "<tr>\n",
- " <td></td> <th>coef</th> <th>std err</th> <th>t</th> <th>P>|t|</th> <th>[0.025</th> <th>0.975]</th> \n",
- "</tr>\n",
- "<tr>\n",
- " <th>Intercept</th> <td> 83.4000</td> <td> 2.019</td> <td> 41.308</td> <td> 0.000</td> <td> 79.257</td> <td> 87.543</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Group[T.B]</th> <td> 5.9000</td> <td> 2.855</td> <td> 2.066</td> <td> 0.049</td> <td> 0.041</td> <td> 11.759</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Group[T.C]</th> <td> 1.3000</td> <td> 2.855</td> <td> 0.455</td> <td> 0.653</td> <td> -4.559</td> <td> 7.159</td>\n",
- "</tr>\n",
- "</table>"
- ],
- "text/latex": [
- "\\begin{center}\n",
- "\\begin{tabular}{lcccccc}\n",
- "\\toprule\n",
- " & \\textbf{coef} & \\textbf{std err} & \\textbf{t} & \\textbf{P$> |$t$|$} & \\textbf{[0.025} & \\textbf{0.975]} \\\\\n",
- "\\midrule\n",
- "\\textbf{Intercept} & 83.4000 & 2.019 & 41.308 & 0.000 & 79.257 & 87.543 \\\\\n",
- "\\textbf{Group[T.B]} & 5.9000 & 2.855 & 2.066 & 0.049 & 0.041 & 11.759 \\\\\n",
- "\\textbf{Group[T.C]} & 1.3000 & 2.855 & 0.455 & 0.653 & -4.559 & 7.159 \\\\\n",
- "\\bottomrule\n",
- "\\end{tabular}\n",
- "\\end{center}"
- ],
- "text/plain": [
- "<class 'statsmodels.iolib.table.SimpleTable'>"
- ]
- },
- "execution_count": 15,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"fitted_model.summary().tables[1]"
]
@@ -996,24 +315,10 @@
},
{
"cell_type": "code",
- "execution_count": 16,
+ "execution_count": null,
"id": "b4aca144-0aa3-45f3-82ff-2b9d5922437d",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "Intercept 83.4\n",
- "Group[T.B] 5.9\n",
- "Group[T.C] 1.3\n",
- "dtype: float64"
- ]
- },
- "execution_count": 16,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"coefficients = fitted_model.params\n",
"coefficients"
@@ -1021,21 +326,10 @@
},
{
"cell_type": "code",
- "execution_count": 17,
+ "execution_count": null,
"id": "59a500b3-c264-42a2-ac09-faa0eb07aed6",
"metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjIAAAGwCAYAAACzXI8XAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8pXeV/AAAACXBIWXMAAA9hAAAPYQGoP6dpAAAj+0lEQVR4nO3de3BU5eHG8efkwu4SIEiAXDBKEoQgwlhxxIC1pQYDUoiCUm8jNystlIpYFCx44VIEL2UQxdFShos4oyOXAWdYJQqKIhcpt4oIVDA2BGeQZCGwC2zO7w9+rqQQLkr23Zf9fmZ2Zvfs2bPP7hzNw/uePcdxXdcVAACAhRJMBwAAAPipKDIAAMBaFBkAAGAtigwAALAWRQYAAFiLIgMAAKxFkQEAANZKMh2grlVXV6usrEwNGzaU4zim4wAAgPPguq4OHTqkrKwsJSTUPu5yyReZsrIyZWdnm44BAAB+gtLSUl1++eW1Pn/JF5mGDRtKOvlFNGrUyHAaAABwPgKBgLKzsyN/x2tzyReZH6aTGjVqRJEBAMAy5zoshIN9AQCAtSgyAADAWhQZAABgLYoMAACwFkUGAABYiyIDAACsRZEBAADWosgAAABrUWQAAIC1KDIAAMBaFBkAAGAtigwAALDWJX/RyEuB67oKBoPGM4RCIUmSx+M550W86prX6zWeAQBgHkXGAsFgUEVFRaZjxBS/3y+fz2c6BgDAMKaWAACAtRiRsYDX65Xf7zeaIRgMqri4WJK0ZMkSeb1eo3lMvz8AIDZQZCzgOE5MTaN4vd6YygMAiF9MLQEAAGtRZAAAgLUoMgAAwFoUGQAAYC2KDAAAsBZFBgAAWIsiAwAArEWRAQAA1qLIAAAAa1FkAACAtSgyAADAWhQZAABgLYoMAACwFkUGAABYiyIDAACsRZEBAADWosgAAABrUWQAAIC1KDIAAMBaFBkAAGCtJNMBANjHdV0Fg0HjGUKhkCTJ4/HIcRyjebxer/EMQDyiyAC4YMFgUEVFRaZjxBS/3y+fz2c6BhB3mFoCAADWYkQGwAXzer3y+/1GMwSDQRUXF0uSlixZIq/XazSP6fcH4hVFBsAFcxwnpqZRvF5vTOUBED1MLQEAAGtRZAAAgLUoMgAAwFoUGQAAYC2KDAAAsBZFBgAAWMtokTl06JBGjBihK6+8Uj6fT507d9b69esjzw8YMECO49S4de/e3WBiAAAQS4yeR+bBBx/Utm3bNG/ePGVlZWn+/PkqLCzUF198oRYtWkiSunfvrtmzZ0de4/F4TMUFAAAxxliROXr0qN555x0tWbJEN998syTp6aef1tKlSzVz5kxNnDhR0snikpGRcd7bDYVCkQvJSVIgELi4wQEAQMwwNrV04sQJhcPh007r7fP5tHr16sjjlStXqnnz5mrTpo3++Mc/6sCBA2fd7uTJk5Wamhq5ZWdn10l+AABgnrEi07BhQxUUFGjChAkqKytTOBzW/PnztWbNGu3bt0/SyWmluXPnqqSkRFOmTNGqVavUo0cPhcPhWrc7ZswYVVZWRm6lpaXR+kgAACDKjB4jM2/ePA0aNEgtWrRQYmKirrvuOt1zzz36/PPPJUl33313ZN327durQ4cOysvL08qVK3XLLbeccZsej4fjaAAAiBNGf7WUl5enVatW6fDhwyotLdW6det0/Phx5ebmnnH93NxcNW3aVLt27YpyUgAAEIti4jwyKSkpyszM1MGDB+X3+1VcXHzG9b799lsdOHBAmZmZUU4IAABikdGpJb/fL9d11aZNG+3atUujRo1Sfn6+Bg4cqMOHD+uZZ55R3759lZGRod27d+uxxx5Tq1atVFRUZDI2AACIEUZHZCorKzVs2DDl5+frgQce0E033SS/36/k5GQlJiZqy5Yt6t27t1q3bq3BgwerY8eO+vjjjzkGBgAASDI8ItOvXz/169fvjM/5fD75/f4oJwIAADaJiWNkAAAAfgqKDAAAsBZFBgAAWMvoMTIAAFwMrusqGAwaz/DDtf48Ho8cxzGax+v1Gs8QDRQZAID1gsEgp+b4H36/Xz6fz3SMOsfUEgAAsBYjMgAA63m9XuOn7AgGg5Ez0y9ZskRer9doHtPvHy0UGQCA9RzHialpFK/XG1N5LmVMLQEAAGtRZAAAgLUoMgAAwFoUGQAAYC2KDAAAsBZFBgAAWIsiAwAArEWRAQAA1qLIAAAAa1FkAACAtbhEAWAZ13UVDAZNxzDu1O+A7+Mkr9crx3FMxwCiiiIDWCYYDKqoqMh0jJjyw4X64p3f7+f6Pog7TC0BAABrMSIDWOzlmyvkSXRNxzDCdaVj1Sfv10uQ4nVGJRR2NOyjxqZjAMZQZACLeRJdeRNNpzCHSRRJis8iC/yAqSUAAGAtigwAALAWRQYAAFiLIgMAAKxFkQEAANaiyAAAAGtRZAAAgLUoMgAAwFoUGQAAYC2KDAAAsBZFBgAAWIsiAwAArEWRAQAA1qLIAAAAa1FkAACAtSgyAADAWhQZAABgLYoMAACwFkUGAABYiyIDAACsRZEBAADWosgAAABrUWQAAIC1KDIAAMBaFBkAAGAtigwAALAWRQYAAFiLIgMAAKxltMgcOnRII0aM0JVXXimfz6fOnTtr/fr1kedd19WTTz6pzMxM+Xw+FRYWaufOnQYTAwCAWGK0yDz44IN6//33NW/ePG3dulW33nqrCgsL9d///leSNHXqVE2fPl2vvvqq1q5dq5SUFBUVFSkYDJqMDQAAYoSxInP06FG98847mjp1qm6++Wa1atVKTz/9tFq1aqWZM2fKdV1NmzZNY8eOVXFxsTp06KC5c+eqrKxMixcvrnW7oVBIgUCgxg0AAFyajBWZEydOKBwOy+v11lju8/m0evVqff311yovL1dhYWHkudTUVHXq1Elr1qypdbuTJ09Wampq5JadnV1nnwEAAJhlrMg0bNhQBQUFmjBhgsrKyhQOhzV//nytWbNG+/btU3l5uSQpPT29xuvS09Mjz53JmDFjVFlZGbmVlpbW6ecAAADmGD1GZt68eXJdVy1atJDH49H06dN1zz33KCHhp8fyeDxq1KhRjRsAALg0GS0yeXl5WrVqlQ4fPqzS0lKtW7dOx48fV25urjIyMiRJ+/fvr/Ga/fv3R54DAADxLSbOI5OSkqLMzEwdPHhQfr9fxcXFysnJUUZGhkpKSiLrBQIBrV27VgUFBQbTAjApseKYksuO1npLrDhmOiKAKEoy+eZ+v1+u66pNmzbatWuXRo0apfz8fA0cOFCO42jEiBGaOHGirrrqKuXk5GjcuHHKysrS7bffbjI2YJTrupH7obDBIAYkVhxT01d3yznh1rqOm+Ro3x/yFG5cL4rJzDl1Hzh13wDihdEiU1lZqTFjxujbb79VkyZN1LdvX02aNEnJycmSpMcee0xVVVV66KGHVFFRoZtuuknLly8/7ZdOQDwJhUKR+8M+usxgEkM6pZ97nX/VfYxYFAqFVL9+fdMxgKgyWmT69eunfv361fq84zgaP368xo8fH8VUAADAFkaLDIAL5/F4IvdfvvmgPIkGw0RZ8r6gMmb955zrlQ/O1fHM+Bi5DYV/HJk7dd8A4gVFBrCM4ziR+55EyRtPRSbBla+6+pzreRNcJcbR9/KDU/cNIF7ExK+WAAAAfgqKDAAAsBZFBgAAWIsiA8Aa1fUT5Sad/TgQN8lRdf04PEAGiFMc7AvAGuHG9VQ2/ColHKn9TIDV9RPj5mR4ACgyACwTblxP4camUwCIFUwtAQAAa1FkAACAtSgyAADAWhQZAABgLYoMAACwFkUGAABYiyIDAACsRZEBAADWosgAAABrUWQAAIC1KDIAAMBaFBkAAGAtigwAALAWRQYAAFgryXSAWOa6roLBoOkYMeHU74Hv5CSv1yvHcUzHAIC4RpE5i2AwqKKiItMxYk5xcbHpCDHB7/fL5/OZjgEAcY2pJQAAYC1GZM5T1XX3SQlx/HW5rlR94uT9hCQpXqdUqk8oZeMbplMAMYVp+JOYgj9dNKbg4/gv8wVKSJISk02nMKye6QAAYhDT8KdjCv6kaEzBM7UEAACsxYgMAOCiCfcKx+9fFldS+P/vJ0qK0xl4nZASlyZG7e3idXcDANSFJMX3X5Z4PwLBAKaWAACAtSgyAADAWhQZAABgLYoMAACwFkUGAABYiyIDAACsRZEBAADWosgAAABrUWQAAIC1KDIAAMBaFBkAAGAtigwAALAWRQYAAFiLIgMAAKxFkQEAANaiyAAAAGslmQ4A4KcLhR1JrukYRriudKz65P16CZLjmM1jysl9AIhfFBnAYsM+amw6AgAYxdQSAACwFiMygGW8Xq/8fr/pGMYFg0EVFxdLkpYsWSKv12s4kXl8B4hHFBnAMo7jyOfzmY4RU7xeL98JEKeMTi2Fw2GNGzdOOTk58vl8ysvL04QJE+S6Px68OGDAADmOU+PWvXt3g6kBAECsMDoiM2XKFM2cOVNz5sxRu3bttGHDBg0cOFCpqan685//HFmve/fumj17duSxx+MxERcAAMQYo0Xm008/VXFxsXr27ClJatmypd58802tW7euxnoej0cZGRkmIgIAcFbp34eUWnW81ucrU5K1vwn/AK8rRotM586d9dprr+mrr75S69attXnzZq1evVovvvhijfVWrlyp5s2b67LLLtNvfvMbTZw4UWlpaWfcZigUUigUijwOBAJ1+hkAAPEr/fuQ3py4UZ4TtZ/PKZTk6J6x11Fm6ojRIjN69GgFAgHl5+crMTFR4XBYkyZN0n333RdZp3v37urTp49ycnK0e/duPfHEE+rRo4fWrFmjxMTE07Y5efJkPfPMM9H8GACAOJVadfysJUaSPCdcpVYdp8jUEaNF5q233tIbb7yhBQsWqF27dtq0aZNGjBihrKws9e/fX5J09913R9Zv3769OnTooLy8PK1cuVK33HLLadscM2aMRo4cGXkcCASUnZ1d9x8GAABE3XkXmbKyMmVlZV3UNx81apRGjx4dKSvt27fX3r17NXny5EiR+V+5ublq2rSpdu3adcYi4/F4OBgYAIA4cd4/v27Xrp0WLFhwUd/8yJEjSkioGSExMVHV1dW1vubbb7/VgQMHlJmZeVGzAAAA+5x3kZk0aZKGDBmiu+66S99///1FefNevXpp0qRJevfdd7Vnzx4tWrRIL774ou644w5J0uHDhzVq1Ch99tln2rNnj0pKSlRcXKxWrVqpqKjoomQAAAD2Ou8iM3ToUG3ZskUHDhzQ1VdfraVLl/7sN3/ppZd05513aujQoWrbtq3+8pe/aMiQIZowYYKkk6MzW7ZsUe/evdW6dWsNHjxYHTt21Mcff8z0EQAAuLCDfXNycvTBBx9oxowZ6tOnj9q2baukpJqb2Lhx43lvr2HDhpo2bZqmTZt2xud9Ph/XlAEAALW64F8t7d27VwsXLtRll12m4uLi04oMAADxojIlWaEk55znkalMSY5iqvhyQS3k9ddf16OPPqrCwkL9+9//VrNmzeoqFwAAMW9/E4/uGXsdZ/Y16LyLTPfu3bVu3TrNmDFDDzzwQF1mAgDAGvubeCgqBp13kQmHw9qyZYsuv/zyuswDALCM654yrXLCXA7EiFP2gRr7Rh057yLz/vvv12UOAIClTr2+XeLS0y8dg/gVCoVUv379On2P8/75NQAAQKzhJ0cAgJ/l1PN6hXuF+csS7078ODIXjXO+sbsBAH4Wx3F+fJAk/rIgosa+UUfY3XBWGYEDanz0UK3PV/gaqrxRWhQTAQDwI4oMapUROKCFsx6XJ1z7+RFCicnqM3gKZQYAYAQH+6JWjY8eOmuJkSRP+PhZR2wAAKhLFBkAAGAtigwAALAWRQYAAFiLIgMAAKxFkQEAANaiyAAAAGtRZFCrCl9DhRKTz7pOKDFZFb6GUUoEAEBNnBAPtSpvlKY+g6dwZl8AQMyiyOCsyhulUVQAADGLqSUAAGAtigwAALAWU0tn4brujw/Occ0hxIlT9oMa+wcAwAiKzFmEQqHI/ZR/LTCYBLEoFAqpfv36pmMAQFxjagkAAFiLEZmz8Hg8kftVv7hXOsc5VRAHwscjo3On7h8AADMoMmfhOM6PDxKTKTKoocb+AQAwgqklAABgLUZkAFww13UVDAaNZjj1/U1nkSSv18soHWAARQbABQsGgyoqKjIdI6K4uNh0BPn9fvl8PtMxgLjD1BIAALAWIzIALpjX65Xf7zeawXXdyLmePB6P8Wkdr9dr9P2BeEWRAXDBHMeJiWkUTkgIgKklAABgLYoMAACwFkUGAABYiyIDAACsxcG+AICL54TpAAa5ksL/fz9RUryeHzHK+wBFBgBw0SQuTTQdAXGGqSUAAGAtRmQAAD9LLJwgMRYEg8HI5TKWLFnCSRIVnRNFUmQAAD9LrJwgMZZ4vV6+kyhhagkAAFiLIgMAAKxFkQEAANaiyAAAAGtRZAAAgLUoMgAAwFoUGQAAYC2KDAAAsBZFBgAAWMtokQmHwxo3bpxycnLk8/mUl5enCRMmyHXdyDqu6+rJJ59UZmamfD6fCgsLtXPnToOpAQBArDBaZKZMmaKZM2dqxowZ2r59u6ZMmaKpU6fqpZdeiqwzdepUTZ8+Xa+++qrWrl2rlJQUFRUVKRgMGkwOAABigdFrLX366acqLi5Wz549JUktW7bUm2++qXXr1kk6ORozbdo0jR07NnIhrrlz5yo9PV2LFy/W3XffbSw7AAAwz+iITOfOnVVSUqKvvvpKkrR582atXr1aPXr0kCR9/fXXKi8vV2FhYeQ1qamp6tSpk9asWXPGbYZCIQUCgRo3AABwaTI6IjN69GgFAgHl5+crMTFR4XBYkyZN0n333SdJKi8vlySlp6fXeF16enrkuf81efJkPfPMM3UbHAAAxASjIzJvvfWW3njjDS1YsEAbN27UnDlz9Pzzz2vOnDk/eZtjxoxRZWVl5FZaWnoREwMAgFhidERm1KhRGj16dORYl/bt22vv3r2aPHmy+vfvr4yMDEnS/v37lZmZGXnd/v37de21155xmx6PRx6Pp86zAwAA84yOyBw5ckQJCTUjJCYmqrq6WpKUk5OjjIwMlZSURJ4PBAJau3atCgoKopoVAADEHqMjMr169dKkSZN0xRVXqF27dvrXv/6lF198UYMGDZIkOY6jESNGaOLEibrqqquUk5OjcePGKSsrS7fffrvJ6AAAIAYYLTIvvfSSxo0bp6FDh+q7775TVlaWhgwZoieffDKyzmOPPaaqqio99NBDqqio0E033aTly5fL6/UaTA4AAGKB0SLTsGFDTZs2TdOmTat1HcdxNH78eI0fPz56wQAAgBW41hIAALAWRQYAAFiLIgMAAKxFkQEAANaiyAAAAGtRZAAAgLUoMgAAwFoUGQAAYC2KDAAAsBZFBgAAWIsiAwAArEWRAQAA1qLIAAAAaxm9+rVVqk+YTmCW6/74HSQkSY5jNo8p8b4fAECMocicp5SNb5iOAAAA/gdTSwAAwFqMyJyF1+uV3+83HSMmBINBFRcXS5KWLFkir9drOJF5fAdA7HBdV8Fg0GiGU9/fdBbp5P+jnDg4DIAicxaO48jn85mOEXO8Xi/fC4CYEgwGVVRUZDpGxA//8DPJ7/fHxf+rmVoCAADWYkQGAGC9WDgUwHVdhUIhSZLH4zE+rRMv098UGQCA9WLlUID69eubjhB3mFoCAADWosgAAABrUWQAAIC1KDIAAMBaFBkAAGAtigwAALAWRQYAAFiLIgMAAKxFkQEAANaiyAAAAGtRZAAAgLUoMgAAwFoUGQAAYC2KDAAAsBZFBgAAWIsiAwAArEWRAQAA1qLIAAAAa1FkAACAtSgyAADAWhQZAABgLYoMAACwFkUGAABYiyIDAACsRZEBAADWosgAAABrUWQAAIC1KDIAAMBaFBkAAGAtigwAALAWRQYAAFjLaJFp2bKlHMc57TZs2DBJ0q9//evTnvvDH/5gMjIAAIghSSbffP369QqHw5HH27ZtU7du3XTXXXdFlv3+97/X+PHjI4/r168f1YwAACB2GS0yzZo1q/H42WefVV5enn71q19FltWvX18ZGRnnvc1QKKRQKBR5HAgEfn5QAAAQk2LmGJljx45p/vz5GjRokBzHiSx/44031LRpU11zzTUaM2aMjhw5ctbtTJ48WampqZFbdnZ2XUcHAACGGB2ROdXixYtVUVGhAQMGRJbde++9uvLKK5WVlaUtW7bo8ccf144dO7Rw4cJatzNmzBiNHDky8jgQCFBmAAC4RMVMkZk1a5Z69OihrKysyLKHHnoocr99+/bKzMzULbfcot27dysvL++M2/F4PPJ4PHWeFwAAmBcTU0t79+7VihUr9OCDD551vU6dOkmSdu3aFY1YAAAgxsVEkZk9e7aaN2+unj17nnW9TZs2SZIyMzOjkAoAAMQ641NL1dXVmj17tvr376+kpB/j7N69WwsWLNBtt92mtLQ0bdmyRY888ohuvvlmdejQwWBiAAAQK4wXmRUrVuibb77RoEGDaiyvV6+eVqxYoWnTpqmqqkrZ2dnq27evxo4daygpAACINcaLzK233irXdU9bnp2drVWrVhlIBAAAbBETx8gAAAD8FBQZAABgLYoMAACwFkUGAABYiyIDAACsRZEBAADWosgAAABrUWQAAIC1KDIAAMBaFBkAAGAtigwAALAWRQYAAFiLIgMAAKxFkQEAANaiyAAAAGtRZAAAgLUoMgAAwFoUGQAAYC2KDAAAsBZFBgAAWIsiAwAArEWRAQAA1qLIAAAAa1FkAACAtSgyAADAWhQZAABgLYoMAACwFkUGAABYiyIDAACsRZEBAADWosgAAABrUWQAAIC1KDIAAMBaFBkAAGAtigwAALAWRQYAAFiLIgMAAKxFkQEAANaiyAAAAGtRZAAAgLWSTAfAubmuq2AwaDTDqe9vOoskeb1eOY5jOgYAwDCKjAWCwaCKiopMx4goLi42HUF+v18+n890DACAYUwtAQAAazEiYwGv1yu/3280g+u6CoVCkiSPx2N8Wsfr9Rp9fwBAbKDIWMBxnJiYRqlfv77pCAAA1MDUEgAAsBZFBgAAWIsiAwAArEWRAQAA1qLIAAAAa1FkAACAtYwWmZYtW8pxnNNuw4YNk3TyjLbDhg1TWlqaGjRooL59+2r//v0mIwMAgBhitMisX79e+/bti9zef/99SdJdd90lSXrkkUe0dOlSvf3221q1apXKysrUp08fk5EBAEAMcVzXdU2H+MGIESO0bNky7dy5U4FAQM2aNdOCBQt05513SpK+/PJLtW3bVmvWrNGNN954xm2EQqHIGWglKRAIKDs7W5WVlWrUqFFUPgcAAPh5AoGAUlNTz/n3O2aOkTl27Jjmz5+vQYMGyXEcff755zp+/LgKCwsj6+Tn5+uKK67QmjVrat3O5MmTlZqaGrllZ2dHIz4AADAgZorM4sWLVVFRoQEDBkiSysvLVa9ePTVu3LjGeunp6SovL691O2PGjFFlZWXkVlpaWoepAQCASTFzraVZs2apR48eysrK+lnb8Xg88ng8FykVAACIZTFRZPbu3asVK1Zo4cKFkWUZGRk6duyYKioqaozK7N+/XxkZGQZSAgCAWBMTRWb27Nlq3ry5evbsGVnWsWNHJScnq6SkRH379pUk7dixQ998840KCgrOe9s/HMscCAQubmgAAFBnfvi7fa7fJBkvMtXV1Zo9e7b69++vpKQf46Smpmrw4MEaOXKkmjRpokaNGmn48OEqKCio9RdLZ3Lo0CFJ4qBfAAAsdOjQIaWmptb6vPEis2LFCn3zzTcaNGjQac/9/e9/V0JCgvr27atQKKSioiK98sorF7T9rKwslZaWqmHDhnIc52LFjks//JS9tLSUn7IjJrBPItawT148ruvq0KFD5zx2NqbOI4PYdr6/6QeihX0SsYZ9Mvpi5ufXAAAAF4oiAwAArEWRwXnzeDx66qmnOE8PYgb7JGIN+2T0cYwMAACwFiMyAADAWhQZAABgLYoMAACwFkUGAABYiyKD87JmzRolJibWuB4WYMKAAQPkOE7klpaWpu7du2vLli2moyHOlZeXa/jw4crNzZXH41F2drZ69eqlkpIS09EuaRQZnJdZs2Zp+PDh+uijj1RWVmY6DuJc9+7dtW/fPu3bt08lJSVKSkrSb3/7W9OxEMf27Nmjjh076oMPPtBzzz2nrVu3avny5eratauGDRtmOt4ljZ9f45wOHz6szMxMbdiwQU899ZQ6dOigJ554wnQsxKkBAwaooqJCixcvjixbvXq1fvnLX+q7775Ts2bNzIVD3Lrtttu0ZcsW7dixQykpKTWeq6ioUOPGjc0EiwOMyOCc3nrrLeXn56tNmza6//779c9//vOcl1UHouXw4cOaP3++WrVqpbS0NNNxEIe+//57LV++XMOGDTutxEiixNQx41e/RuybNWuW7r//fkknh/QrKyu1atUq/frXvzYbDHFr2bJlatCggSSpqqpKmZmZWrZsmRIS+LcZom/Xrl1yXVf5+fmmo8Ql/qvHWe3YsUPr1q3TPffcI0lKSkrS7373O82aNctwMsSzrl27atOmTdq0aZPWrVunoqIi9ejRQ3v37jUdDXGIEWqzGJHBWc2aNUsnTpxQVlZWZJnruvJ4PJoxY4ZSU1MNpkO8SklJUatWrSKP//GPfyg1NVWvv/66Jk6caDAZ4tFVV10lx3H05Zdfmo4SlxiRQa1OnDihuXPn6oUXXoj863fTpk3avHmzsrKy9Oabb5qOCEiSHMdRQkKCjh49ajoK4lCTJk1UVFSkl19+WVVVVac9X1FREf1QcYQig1otW7ZMBw8e1ODBg3XNNdfUuPXt25fpJRgTCoVUXl6u8vJybd++XcOHD9fhw4fVq1cv09EQp15++WWFw2HdcMMNeuedd7Rz505t375d06dPV0FBgel4lzSKDGo1a9YsFRYWnnH6qG/fvtqwYQMnIYMRy5cvV2ZmpjIzM9WpUyetX79eb7/9Ngegw5jc3Fxt3LhRXbt21aOPPqprrrlG3bp1U0lJiWbOnGk63iWN88gAAABrMSIDAACsRZEBAADWosgAAABrUWQAAIC1KDIAAMBaFBkAAGAtigwAALAWRQYAAFiLIgMAAKxFkQEQdeXl5Xr44YfVqlUreb1epaenq0uXLpo5c6aOHDliOh4AiySZDgAgvvznP/9Rly5d1LhxY/3tb39T+/bt5fF4tHXrVr322mtq0aKFevfufdrrjh8/ruTkZAOJAcQyRmQARNXQoUOVlJSkDRs2qF+/fmrbtq1yc3NVXFysd999N3IFa8dxNHPmTPXu3VspKSmaNGmSJGnmzJnKy8tTvXr11KZNG82bNy+y7T179shxHG3atCmyrKKiQo7jaOXKlZKklStXynEcvfvuu+rQoYO8Xq9uvPFGbdu2LWrfAYCLhyIDIGoOHDig9957T8OGDVNKSsoZ13EcJ3L/6aef1h133KGtW7dq0KBBWrRokR5++GE9+uij2rZtm4YMGaKBAwfqww8/vOAso0aN0gsvvKD169erWbNm6tWrl44fP/6TPxsAMygyAKJm165dcl1Xbdq0qbG8adOmatCggRo0aKDHH388svzee+/VwIEDlZubqyuuuELPP/+8BgwYoKFDh6p169YaOXKk+vTpo+eff/6Cszz11FPq1q2b2rdvrzlz5mj//v1atGjRz/6MAKKLIgPAuHXr1mnTpk1q166dQqFQZPn1119fY73t27erS5cuNZZ16dJF27dvv+D3LCgoiNxv0qSJ2rRp85O2A8AsDvYFEDWtWrWS4zjasWNHjeW5ubmSJJ/PV2N5bdNPtUlIOPlvM9d1I8uYLgIubYzIAIiatLQ0devWTTNmzFBVVdUFv75t27b65JNPaiz75JNPdPXVV0uSmjVrJknat29f5PlTD/w91WeffRa5f/DgQX311Vdq27btBWcCYBYjMgCi6pVXXlGXLl10/fXX6+mnn1aHDh2UkJCg9evX68svv1THjh1rfe2oUaPUr18//eIXv1BhYaGWLl2qhQsXasWKFZJOjujceOONevbZZ5WTk6PvvvtOY8eOPeO2xo8fr7S0NKWnp+uvf/2rmjZtqttvv70uPjKAuuQCQJSVlZW5f/rTn9ycnBw3OTnZbdCggXvDDTe4zz33nFtVVeW6rutKchctWnTaa1955RU3NzfXTU5Odlu3bu3OnTu3xvNffPGFW1BQ4Pp8Pvfaa69133vvPVeS++GHH7qu67offvihK8ldunSp265dO7devXruDTfc4G7evLmuPzaAOuC47imTyQBwiVu5cqW6du2qgwcPqnHjxqbjAPiZOEYGAABYiyIDAACsxdQSAACwFiMyAADAWhQZAABgLYoMAACwFkUGAABYiyIDAACsRZEBAADWosgAAABrUWQAAIC1/g+DgFfUyrpLlwAAAABJRU5ErkJggg==",
- "text/plain": [
- "<Figure size 640x480 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"intercept, B_term, C_term = coefficients\n",
"ax = sns.boxplot(x='Group', y='Y', data=dataframe)\n",
@@ -1060,71 +354,10 @@
},
{
"cell_type": "code",
- "execution_count": 18,
+ "execution_count": null,
"id": "37d47be2-6e62-4fe7-b56f-bb47e951aca9",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<table class=\"simpletable\">\n",
- "<caption>OLS Regression Results</caption>\n",
- "<tr>\n",
- " <th>Dep. Variable:</th> <td>Y</td> <th> R-squared: </th> <td> 0.149</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Model:</th> <td>OLS</td> <th> Adj. R-squared: </th> <td> 0.086</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Method:</th> <td>Least Squares</td> <th> F-statistic: </th> <td> 2.358</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Date:</th> <td>Mon, 21 Aug 2023</td> <th> Prob (F-statistic):</th> <td> 0.114</td> \n",
- "</tr>\n",
- "<tr>\n",
- " <th>Time:</th> <td>16:37:44</td> <th> Log-Likelihood: </th> <td> -96.604</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>No. Observations:</th> <td> 30</td> <th> AIC: </th> <td> 199.2</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Df Residuals:</th> <td> 27</td> <th> BIC: </th> <td> 203.4</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Df Model:</th> <td> 2</td> <th> </th> <td> </td> \n",
- "</tr>\n",
- "<tr>\n",
- " <th>Covariance Type:</th> <td>nonrobust</td> <th> </th> <td> </td> \n",
- "</tr>\n",
- "</table>"
- ],
- "text/latex": [
- "\\begin{center}\n",
- "\\begin{tabular}{lclc}\n",
- "\\toprule\n",
- "\\textbf{Dep. Variable:} & Y & \\textbf{ R-squared: } & 0.149 \\\\\n",
- "\\textbf{Model:} & OLS & \\textbf{ Adj. R-squared: } & 0.086 \\\\\n",
- "\\textbf{Method:} & Least Squares & \\textbf{ F-statistic: } & 2.358 \\\\\n",
- "\\textbf{Date:} & Mon, 21 Aug 2023 & \\textbf{ Prob (F-statistic):} & 0.114 \\\\\n",
- "\\textbf{Time:} & 16:37:44 & \\textbf{ Log-Likelihood: } & -96.604 \\\\\n",
- "\\textbf{No. Observations:} & 30 & \\textbf{ AIC: } & 199.2 \\\\\n",
- "\\textbf{Df Residuals:} & 27 & \\textbf{ BIC: } & 203.4 \\\\\n",
- "\\textbf{Df Model:} & 2 & \\textbf{ } & \\\\\n",
- "\\textbf{Covariance Type:} & nonrobust & \\textbf{ } & \\\\\n",
- "\\bottomrule\n",
- "\\end{tabular}\n",
- "%\\caption{OLS Regression Results}\n",
- "\\end{center}"
- ],
- "text/plain": [
- "<class 'statsmodels.iolib.table.SimpleTable'>"
- ]
- },
- "execution_count": 18,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"fitted_model.summary().tables[0]"
]
@@ -1141,75 +374,23 @@
},
{
"cell_type": "code",
- "execution_count": 19,
+ "execution_count": null,
"id": "a5b2750a-8965-4769-b053-cd95e3583320",
"metadata": {
"hidden": true,
"tags": []
},
- "outputs": [
- {
- "data": {
- "image/png": "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",
- "text/plain": [
- "<Figure size 640x480 with 2 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"statsmodels_material.illustration_residuals(dataframe, fitted_model)"
]
},
{
"cell_type": "code",
- "execution_count": 20,
+ "execution_count": null,
"id": "158674d4-7123-4f60-b1fa-887f81261816",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "0 1.6\n",
- "1 2.6\n",
- "2 4.6\n",
- "3 -8.4\n",
- "4 -5.4\n",
- "5 10.6\n",
- "6 14.6\n",
- "7 -4.4\n",
- "8 -12.4\n",
- "9 -3.4\n",
- "10 1.7\n",
- "11 2.7\n",
- "12 3.7\n",
- "13 -4.3\n",
- "14 -2.3\n",
- "15 -5.3\n",
- "16 -7.3\n",
- "17 -1.3\n",
- "18 5.7\n",
- "19 6.7\n",
- "20 -5.7\n",
- "21 -6.7\n",
- "22 3.3\n",
- "23 9.3\n",
- "24 7.3\n",
- "25 0.3\n",
- "26 -1.7\n",
- "27 0.3\n",
- "28 -2.7\n",
- "29 -3.7\n",
- "dtype: float64"
- ]
- },
- "execution_count": 20,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"fitted_model.resid"
]
@@ -1241,26 +422,13 @@
},
{
"cell_type": "code",
- "execution_count": 21,
+ "execution_count": null,
"id": "fc687c84-7ad2-4055-b00d-efbcb4545ea2",
"metadata": {
"hidden": true,
"tags": []
},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "==============================================================================\n",
- "Omnibus: 0.758 Durbin-Watson: 1.379\n",
- "Prob(Omnibus): 0.684 Jarque-Bera (JB): 0.665\n",
- "Skew: 0.336 Prob(JB): 0.717\n",
- "Kurtosis: 2.715 Cond. No. 3.73\n",
- "==============================================================================\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"print(fitted_model.summary().tables[-1])"
]
@@ -1278,23 +446,12 @@
},
{
"cell_type": "code",
- "execution_count": 22,
+ "execution_count": null,
"id": "1ecb4ddd-d9f4-42cb-8611-0f0d69da4972",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "NormaltestResult(statistic=0.7583012334839462, pvalue=0.6844425164005732)"
- ]
- },
- "execution_count": 22,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"stats.normaltest(fitted_model.resid)"
]
@@ -1336,26 +493,12 @@
},
{
"cell_type": "code",
- "execution_count": 23,
+ "execution_count": null,
"id": "02834d6d-cc6a-4746-9f2e-443c10a65fd3",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "==============================================================================\n",
- " coef std err t P>|t| [0.025 0.975]\n",
- "------------------------------------------------------------------------------\n",
- "Intercept 83.4000 2.019 41.308 0.000 79.257 87.543\n",
- "Group[T.B] 5.9000 2.855 2.066 0.049 0.041 11.759\n",
- "Group[T.C] 1.3000 2.855 0.455 0.653 -4.559 7.159\n",
- "==============================================================================\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"print(fitted_model.summary().tables[1])"
]
@@ -1383,7 +526,7 @@
},
{
"cell_type": "code",
- "execution_count": 24,
+ "execution_count": null,
"id": "86386730-0784-4304-bb82-c8909e7ffb01",
"metadata": {
"hidden": true
@@ -1396,54 +539,12 @@
},
{
"cell_type": "code",
- "execution_count": 25,
+ "execution_count": null,
"id": "c885739b-16dc-4269-b0cf-1f0379e6c4c8",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "DesignMatrix with shape (30, 1) | DesignMatrix with shape (30, 3) \n",
- " Y | Intercept Group[T.B] Group[T.C]\n",
- " 85 | 1 0 0\n",
- " 86 | 1 0 0\n",
- " 88 | 1 0 0\n",
- " 75 | 1 0 0\n",
- " 78 | 1 0 0\n",
- " 94 | 1 0 0\n",
- " 98 | 1 0 0\n",
- " 79 | 1 0 0\n",
- " 71 | 1 0 0\n",
- " 80 | 1 0 0\n",
- " 91 | 1 1 0\n",
- " 92 | 1 1 0\n",
- " 93 | 1 1 0\n",
- " 85 | 1 1 0\n",
- " 87 | 1 1 0\n",
- " 84 | 1 1 0\n",
- " 82 | 1 1 0\n",
- " 88 | 1 1 0\n",
- " 95 | 1 1 0\n",
- " 96 | 1 1 0\n",
- " 79 | 1 0 1\n",
- " 78 | 1 0 1\n",
- " 88 | 1 0 1\n",
- " 94 | 1 0 1\n",
- " 92 | 1 0 1\n",
- " 85 | 1 0 1\n",
- " 83 | 1 0 1\n",
- " 85 | 1 0 1\n",
- " 82 | 1 0 1\n",
- " 81 | 1 0 1\n",
- " Terms: | Terms: \n",
- " 'Y' (column 0) | 'Intercept' (column 0) \n",
- " | 'Group' (columns 1:3) \n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"print(statsmodels_material.side_by_side(endog, exog))"
]
@@ -1490,50 +591,10 @@
},
{
"cell_type": "code",
- "execution_count": 26,
+ "execution_count": null,
"id": "f7ab66b2-b6aa-4437-8427-e3e731fd58e8",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "array([[1., 1., 0., 0.],\n",
- " [1., 1., 0., 0.],\n",
- " [1., 1., 0., 0.],\n",
- " [1., 1., 0., 0.],\n",
- " [1., 1., 0., 0.],\n",
- " [1., 1., 0., 0.],\n",
- " [1., 1., 0., 0.],\n",
- " [1., 1., 0., 0.],\n",
- " [1., 1., 0., 0.],\n",
- " [1., 1., 0., 0.],\n",
- " [1., 0., 1., 0.],\n",
- " [1., 0., 1., 0.],\n",
- " [1., 0., 1., 0.],\n",
- " [1., 0., 1., 0.],\n",
- " [1., 0., 1., 0.],\n",
- " [1., 0., 1., 0.],\n",
- " [1., 0., 1., 0.],\n",
- " [1., 0., 1., 0.],\n",
- " [1., 0., 1., 0.],\n",
- " [1., 0., 1., 0.],\n",
- " [1., 0., 0., 1.],\n",
- " [1., 0., 0., 1.],\n",
- " [1., 0., 0., 1.],\n",
- " [1., 0., 0., 1.],\n",
- " [1., 0., 0., 1.],\n",
- " [1., 0., 0., 1.],\n",
- " [1., 0., 0., 1.],\n",
- " [1., 0., 0., 1.],\n",
- " [1., 0., 0., 1.],\n",
- " [1., 0., 0., 1.]])"
- ]
- },
- "execution_count": 26,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"intercept, dummyB, dummyC = exog.T\n",
"dummyA = intercept - dummyB - dummyC\n",
@@ -1543,156 +604,12 @@
},
{
"cell_type": "code",
- "execution_count": 27,
+ "execution_count": null,
"id": "b18356ea-7df2-4596-abe4-b6a320280809",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<table class=\"simpletable\">\n",
- "<caption>OLS Regression Results</caption>\n",
- "<tr>\n",
- " <th>Dep. Variable:</th> <td>y</td> <th> R-squared: </th> <td> 0.149</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Model:</th> <td>OLS</td> <th> Adj. R-squared: </th> <td> 0.086</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Method:</th> <td>Least Squares</td> <th> F-statistic: </th> <td> 2.358</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Date:</th> <td>Mon, 21 Aug 2023</td> <th> Prob (F-statistic):</th> <td> 0.114</td> \n",
- "</tr>\n",
- "<tr>\n",
- " <th>Time:</th> <td>16:37:44</td> <th> Log-Likelihood: </th> <td> -96.604</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>No. Observations:</th> <td> 30</td> <th> AIC: </th> <td> 199.2</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Df Residuals:</th> <td> 27</td> <th> BIC: </th> <td> 203.4</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Df Model:</th> <td> 2</td> <th> </th> <td> </td> \n",
- "</tr>\n",
- "<tr>\n",
- " <th>Covariance Type:</th> <td>nonrobust</td> <th> </th> <td> </td> \n",
- "</tr>\n",
- "</table>\n",
- "<table class=\"simpletable\">\n",
- "<tr>\n",
- " <td></td> <th>coef</th> <th>std err</th> <th>t</th> <th>P>|t|</th> <th>[0.025</th> <th>0.975]</th> \n",
- "</tr>\n",
- "<tr>\n",
- " <th>const</th> <td> 64.3500</td> <td> 0.874</td> <td> 73.606</td> <td> 0.000</td> <td> 62.556</td> <td> 66.144</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>x1</th> <td> 19.0500</td> <td> 1.674</td> <td> 11.380</td> <td> 0.000</td> <td> 15.615</td> <td> 22.485</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>x2</th> <td> 24.9500</td> <td> 1.674</td> <td> 14.904</td> <td> 0.000</td> <td> 21.515</td> <td> 28.385</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>x3</th> <td> 20.3500</td> <td> 1.674</td> <td> 12.156</td> <td> 0.000</td> <td> 16.915</td> <td> 23.785</td>\n",
- "</tr>\n",
- "</table>\n",
- "<table class=\"simpletable\">\n",
- "<tr>\n",
- " <th>Omnibus:</th> <td> 0.758</td> <th> Durbin-Watson: </th> <td> 1.379</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Prob(Omnibus):</th> <td> 0.684</td> <th> Jarque-Bera (JB): </th> <td> 0.665</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Skew:</th> <td> 0.336</td> <th> Prob(JB): </th> <td> 0.717</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Kurtosis:</th> <td> 2.715</td> <th> Cond. No. </th> <td>2.43e+16</td>\n",
- "</tr>\n",
- "</table><br/><br/>Notes:<br/>[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.<br/>[2] The smallest eigenvalue is 6.79e-32. This might indicate that there are<br/>strong multicollinearity problems or that the design matrix is singular."
- ],
- "text/latex": [
- "\\begin{center}\n",
- "\\begin{tabular}{lclc}\n",
- "\\toprule\n",
- "\\textbf{Dep. Variable:} & y & \\textbf{ R-squared: } & 0.149 \\\\\n",
- "\\textbf{Model:} & OLS & \\textbf{ Adj. R-squared: } & 0.086 \\\\\n",
- "\\textbf{Method:} & Least Squares & \\textbf{ F-statistic: } & 2.358 \\\\\n",
- "\\textbf{Date:} & Mon, 21 Aug 2023 & \\textbf{ Prob (F-statistic):} & 0.114 \\\\\n",
- "\\textbf{Time:} & 16:37:44 & \\textbf{ Log-Likelihood: } & -96.604 \\\\\n",
- "\\textbf{No. Observations:} & 30 & \\textbf{ AIC: } & 199.2 \\\\\n",
- "\\textbf{Df Residuals:} & 27 & \\textbf{ BIC: } & 203.4 \\\\\n",
- "\\textbf{Df Model:} & 2 & \\textbf{ } & \\\\\n",
- "\\textbf{Covariance Type:} & nonrobust & \\textbf{ } & \\\\\n",
- "\\bottomrule\n",
- "\\end{tabular}\n",
- "\\begin{tabular}{lcccccc}\n",
- " & \\textbf{coef} & \\textbf{std err} & \\textbf{t} & \\textbf{P$> |$t$|$} & \\textbf{[0.025} & \\textbf{0.975]} \\\\\n",
- "\\midrule\n",
- "\\textbf{const} & 64.3500 & 0.874 & 73.606 & 0.000 & 62.556 & 66.144 \\\\\n",
- "\\textbf{x1} & 19.0500 & 1.674 & 11.380 & 0.000 & 15.615 & 22.485 \\\\\n",
- "\\textbf{x2} & 24.9500 & 1.674 & 14.904 & 0.000 & 21.515 & 28.385 \\\\\n",
- "\\textbf{x3} & 20.3500 & 1.674 & 12.156 & 0.000 & 16.915 & 23.785 \\\\\n",
- "\\bottomrule\n",
- "\\end{tabular}\n",
- "\\begin{tabular}{lclc}\n",
- "\\textbf{Omnibus:} & 0.758 & \\textbf{ Durbin-Watson: } & 1.379 \\\\\n",
- "\\textbf{Prob(Omnibus):} & 0.684 & \\textbf{ Jarque-Bera (JB): } & 0.665 \\\\\n",
- "\\textbf{Skew:} & 0.336 & \\textbf{ Prob(JB): } & 0.717 \\\\\n",
- "\\textbf{Kurtosis:} & 2.715 & \\textbf{ Cond. No. } & 2.43e+16 \\\\\n",
- "\\bottomrule\n",
- "\\end{tabular}\n",
- "%\\caption{OLS Regression Results}\n",
- "\\end{center}\n",
- "\n",
- "Notes: \\newline\n",
- " [1] Standard Errors assume that the covariance matrix of the errors is correctly specified. \\newline\n",
- " [2] The smallest eigenvalue is 6.79e-32. This might indicate that there are \\newline\n",
- " strong multicollinearity problems or that the design matrix is singular."
- ],
- "text/plain": [
- "<class 'statsmodels.iolib.summary.Summary'>\n",
- "\"\"\"\n",
- " OLS Regression Results \n",
- "==============================================================================\n",
- "Dep. Variable: y R-squared: 0.149\n",
- "Model: OLS Adj. R-squared: 0.086\n",
- "Method: Least Squares F-statistic: 2.358\n",
- "Date: Mon, 21 Aug 2023 Prob (F-statistic): 0.114\n",
- "Time: 16:37:44 Log-Likelihood: -96.604\n",
- "No. Observations: 30 AIC: 199.2\n",
- "Df Residuals: 27 BIC: 203.4\n",
- "Df Model: 2 \n",
- "Covariance Type: nonrobust \n",
- "==============================================================================\n",
- " coef std err t P>|t| [0.025 0.975]\n",
- "------------------------------------------------------------------------------\n",
- "const 64.3500 0.874 73.606 0.000 62.556 66.144\n",
- "x1 19.0500 1.674 11.380 0.000 15.615 22.485\n",
- "x2 24.9500 1.674 14.904 0.000 21.515 28.385\n",
- "x3 20.3500 1.674 12.156 0.000 16.915 23.785\n",
- "==============================================================================\n",
- "Omnibus: 0.758 Durbin-Watson: 1.379\n",
- "Prob(Omnibus): 0.684 Jarque-Bera (JB): 0.665\n",
- "Skew: 0.336 Prob(JB): 0.717\n",
- "Kurtosis: 2.715 Cond. No. 2.43e+16\n",
- "==============================================================================\n",
- "\n",
- "Notes:\n",
- "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
- "[2] The smallest eigenvalue is 6.79e-32. This might indicate that there are\n",
- "strong multicollinearity problems or that the design matrix is singular.\n",
- "\"\"\""
- ]
- },
- "execution_count": 27,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"overdefined_model = sm.OLS(endog, overdefined_exog).fit()\n",
"overdefined_model.summary()"
@@ -1739,46 +656,13 @@
},
{
"cell_type": "code",
- "execution_count": 28,
+ "execution_count": null,
"id": "d3de4753-0da7-4fe9-8412-eff18d66accf",
"metadata": {
"hidden": true,
"tags": []
},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- " OLS Regression Results \n",
- "==============================================================================\n",
- "Dep. Variable: Y R-squared: 0.149\n",
- "Model: OLS Adj. R-squared: 0.086\n",
- "Method: Least Squares F-statistic: 2.358\n",
- "Date: Mon, 21 Aug 2023 Prob (F-statistic): 0.114\n",
- "Time: 16:37:44 Log-Likelihood: -96.604\n",
- "No. Observations: 30 AIC: 199.2\n",
- "Df Residuals: 27 BIC: 203.4\n",
- "Df Model: 2 \n",
- "Covariance Type: nonrobust \n",
- "===============================================================================\n",
- " coef std err t P>|t| [0.025 0.975]\n",
- "-------------------------------------------------------------------------------\n",
- "C(Group)[A] 83.4000 2.019 41.308 0.000 79.257 87.543\n",
- "C(Group)[B] 89.3000 2.019 44.230 0.000 85.157 93.443\n",
- "C(Group)[C] 84.7000 2.019 41.952 0.000 80.557 88.843\n",
- "==============================================================================\n",
- "Omnibus: 0.758 Durbin-Watson: 1.379\n",
- "Prob(Omnibus): 0.684 Jarque-Bera (JB): 0.665\n",
- "Skew: 0.336 Prob(JB): 0.717\n",
- "Kurtosis: 2.715 Cond. No. 1.00\n",
- "==============================================================================\n",
- "\n",
- "Notes:\n",
- "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"del C # more about this later...\n",
"fitted_model = smf.ols('Y ~ C(Group) - 1', data=dataframe).fit()\n",
@@ -1806,23 +690,12 @@
},
{
"cell_type": "code",
- "execution_count": 29,
+ "execution_count": null,
"id": "44932add-b649-4c6d-a88f-421549bc9481",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Y ~ A\n",
- "Y ~ 0 + A\n",
- "Y ~ A + B + A:B\n",
- "Y ~ A\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"from patsy import ModelDesc\n",
"print(ModelDesc.from_formula('Y ~ 1 + A').describe())\n",
@@ -1843,7 +716,7 @@
},
{
"cell_type": "code",
- "execution_count": 30,
+ "execution_count": null,
"id": "b3fdcfa3-fe7a-48f3-9a2f-b01723a6e440",
"metadata": {
"hidden": true,
@@ -1881,7 +754,7 @@
},
{
"cell_type": "code",
- "execution_count": 31,
+ "execution_count": null,
"id": "e3e4e71e-27a4-4c96-ab41-050f4f7597d6",
"metadata": {
"hidden": true,
@@ -1925,7 +798,7 @@
},
{
"cell_type": "code",
- "execution_count": 32,
+ "execution_count": null,
"id": "4d947388-de44-4f13-b2c0-e8b392856b79",
"metadata": {
"hidden": true
@@ -1943,24 +816,13 @@
},
{
"cell_type": "code",
- "execution_count": 33,
+ "execution_count": null,
"id": "9ea0c1f5-fb3f-4110-b824-9a7c6018c35e",
"metadata": {
"hidden": true,
"tags": []
},
- "outputs": [
- {
- "data": {
- "image/png": "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",
- "text/plain": [
- "<Figure size 640x480 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"statsmodels_material.illustration_2way_data(plant_data)"
]
@@ -1977,7 +839,7 @@
},
{
"cell_type": "code",
- "execution_count": 34,
+ "execution_count": null,
"id": "215e908f-2c5f-4ec3-9eb4-8cb67f75a2f6",
"metadata": {
"hidden": true
@@ -1999,85 +861,12 @@
},
{
"cell_type": "code",
- "execution_count": 35,
+ "execution_count": null,
"id": "cc06b3ed-a066-4de3-884c-a7c82729c359",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
- "\n",
- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>sum_sq</th>\n",
- " <th>df</th>\n",
- " <th>F</th>\n",
- " <th>PR(>F)</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>Intercept</th>\n",
- " <td>394.218750</td>\n",
- " <td>1.0</td>\n",
- " <td>406.443314</td>\n",
- " <td>2.139588e-17</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>water</th>\n",
- " <td>15.552000</td>\n",
- " <td>1.0</td>\n",
- " <td>16.034261</td>\n",
- " <td>4.623155e-04</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>sun</th>\n",
- " <td>21.424667</td>\n",
- " <td>2.0</td>\n",
- " <td>11.044518</td>\n",
- " <td>3.373296e-04</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>Residual</th>\n",
- " <td>25.218000</td>\n",
- " <td>26.0</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " sum_sq df F PR(>F)\n",
- "Intercept 394.218750 1.0 406.443314 2.139588e-17\n",
- "water 15.552000 1.0 16.034261 4.623155e-04\n",
- "sun 21.424667 2.0 11.044518 3.373296e-04\n",
- "Residual 25.218000 26.0 NaN NaN"
- ]
- },
- "execution_count": 35,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"sm.stats.anova_lm(plant_model, typ=3) # `typ` specifies the type of sum of squares"
]
@@ -2092,32 +881,13 @@
},
{
"cell_type": "code",
- "execution_count": 36,
+ "execution_count": null,
"id": "ff91aa79-fb03-4b42-9129-8d5abd2add43",
"metadata": {
"hidden": true,
"tags": []
},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- " OLS Regression Results \n",
- "==============================================================================\n",
- "Dep. Variable: height R-squared: 0.595\n",
- "Model: OLS Adj. R-squared: 0.548\n",
- "Method: Least Squares F-statistic: 12.71\n",
- "Date: Mon, 21 Aug 2023 Prob (F-statistic): 2.64e-05\n",
- "Time: 16:37:44 Log-Likelihood: -39.964\n",
- "No. Observations: 30 AIC: 87.93\n",
- "Df Residuals: 26 BIC: 93.53\n",
- "Df Model: 3 \n",
- "Covariance Type: nonrobust \n",
- "==============================================================================\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"print(plant_model.summary().tables[0])"
]
@@ -2134,27 +904,12 @@
},
{
"cell_type": "code",
- "execution_count": 37,
+ "execution_count": null,
"id": "36130c37-c833-4953-9983-7c92bfdbe2e6",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "Intercept 7.25\n",
- "water[T.weekly] -1.44\n",
- "sun[T.low] -1.92\n",
- "sun[T.med] -1.63\n",
- "dtype: float64"
- ]
- },
- "execution_count": 37,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"plant_model.params"
]
@@ -2173,24 +928,13 @@
},
{
"cell_type": "code",
- "execution_count": 38,
+ "execution_count": null,
"id": "4f4785b3-b798-416a-9a53-1d5b873117ce",
"metadata": {
"hidden": true,
"tags": []
},
- "outputs": [
- {
- "data": {
- "image/png": "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",
- "text/plain": [
- "<Figure size 640x480 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"ax = sns.swarmplot(data=plant_data, x='sun', y='height', hue='water', dodge=True)\n",
"\n",
@@ -2229,24 +973,12 @@
},
{
"cell_type": "code",
- "execution_count": 39,
+ "execution_count": null,
"id": "60de13e5-b798-4312-8d06-0ef79f480760",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- " df sum_sq mean_sq F PR(>F)\n",
- "water 1.0 15.552000 15.552000 19.117394 0.000205\n",
- "sun 2.0 21.424667 10.712333 13.168203 0.000138\n",
- "water:sun 2.0 5.694000 2.847000 3.499693 0.046376\n",
- "Residual 24.0 19.524000 0.813500 NaN NaN\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"model_with_interaction = smf.ols('height ~ water * sun', data=plant_data).fit()\n",
"# remember `water * sun` is equivalent to `water + sun + water:sun`\n",
@@ -2255,52 +987,24 @@
},
{
"cell_type": "code",
- "execution_count": 40,
+ "execution_count": null,
"id": "6141c9fa-aab9-45d5-91e3-a41e8fe8587d",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "Intercept 7.02\n",
- "water[T.weekly] -0.98\n",
- "sun[T.low] -1.08\n",
- "sun[T.med] -1.78\n",
- "water[T.weekly]:sun[T.low] -1.68\n",
- "water[T.weekly]:sun[T.med] 0.30\n",
- "dtype: float64"
- ]
- },
- "execution_count": 40,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"model_with_interaction.params"
]
},
{
"cell_type": "code",
- "execution_count": 41,
+ "execution_count": null,
"id": "b4de4c0a-ada5-4df1-98bc-43bc7f038cc4",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAAAioAAAGwCAYAAACHJU4LAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8pXeV/AAAACXBIWXMAAA9hAAAPYQGoP6dpAABUjUlEQVR4nO3dd1xV9ePH8ddlqiwVRXGiaCrulVvRTLM0J+bO1G9DtKw0s3JmqVmpldh2ZSZojpy5wBwpbiX3LgdOQFRAuL8/+EkSoIjAuVzez8fjPorPPZz7BpH79nM+5xyT2Ww2IyIiImKBbIwOICIiIpIWFRURERGxWCoqIiIiYrFUVERERMRiqaiIiIiIxVJREREREYuloiIiIiIWy87oAI8jISGB8+fP4+LigslkMjqOiIiIpIPZbCYqKopixYphY/PgOZMcXVTOnz9PyZIljY4hIiIiGXDu3DlKlCjxwG1ydFFxcXEBEr9QV1dXg9OIiIhIekRGRlKyZMmk9/EHydFF5d7hHldXVxUVERGRHCY9yza0mFZEREQsloqKiIiIWCwVFREREbFYOXqNSnrFx8cTFxdndIxcyd7eHltbW6NjiIhIDmXVRcVsNnPx4kVu3LhhdJRcLX/+/BQtWlTXuhERkUdm1UXlXknx8PAgX758eqPMZmazmVu3bhEeHg6Ap6enwYlERCSnsdqiEh8fn1RS3N3djY6Ta+XNmxeA8PBwPDw8dBhIREQeidUupr23JiVfvnwGJ5F7fwZaJyQiIo/KaovKPTrcYzz9GYiISEZZfVERERGRnMtq16iIiIjc73ZsPL/tO8/JK9FU8nShTRVPHOz073VLp6IiIiJW7+/rt+j27Z/8ff120tj0Isf55eUGFHRyMDCZPIyqZA7g6+vLkCFDjI4hIpJjfbzyULKSAnD00k2mrTtqUCJJLxWVXCQ2NtboCCIihlj3V3iq42vCLmVzEnlUKipZYPny5eTPn5/4+HgA9u7di8lk4t13303aZsCAAfTq1YurV6/SvXt3ihcvTr58+ahatSrz589P2q5v376EhIQwbdo0TCYTJpOJ06dPA3Dw4EHatGmDs7MzRYoUoXfv3ly5ciXpc319fRk0aBBDhgyhUKFCtG7dOnu+ASIiFsbeNvWzDx3t9TZo6fQnlAWaNGlCVFQUe/bsASAkJIRChQoRHByctE1ISAi+vr7cuXOH2rVrs2LFCg4ePMjLL79M79692bFjBwDTpk2jQYMG/O9//+PChQtcuHCBkiVLcuPGDVq0aEHNmjXZuXMnq1ev5tKlS3Tt2jVZltmzZ+Pg4MCWLVv4+uuvs+17ICJiSdrXLJ76eI3Ux8VyaDFtFnBzc6NGjRoEBwdTp04dgoODefPNNxk7diw3b94kIiKC48eP06xZM4oXL87QoUOTPnfw4MGsWbOGwMBAnnzySdzc3HBwcCBfvnwULVo0abuvvvqKmjVr8vHHHyeN/fjjj5QsWZKjR4/yxBNPAFC+fHk++eST7PviRUQs0PBnKnL80k12nL6WNPZURQ8G+nobmErSQ0UlizRr1ozg4GDefvtt/vjjDyZMmEBgYCCbN2/m2rVrFCtWjPLlyxMfH8/HH39MYGAg//zzD7GxscTExDz0irr79u1j48aNODs7p3juxIkTSUWldu3aWfL1iYjkJG557Ql8tQG7zlzn5OWbVPJ0pUpxN6NjSTqoqGQRX19ffvzxR/bt24e9vT0VK1bE19eX4OBgrl+/TrNmzQCYPHky06ZNY+rUqVStWhUnJyeGDBny0IWvN2/epF27dkyaNCnFc/ff/M/JySlzvzARkRysdukC1C5dwOgY8ghUVLLIvXUqU6ZMSSolvr6+TJw4kevXr/P2228DsGXLFtq3b0+vXr0ASEhI4OjRo/j4+CTty8HBIWlh7j21atVi0aJFeHl5YWenP0YREbFOWkybRQoUKEC1atWYN28evr6+ADRt2pTdu3dz9OjRpPJSvnx51q5dy9atWzl06BCvvPIKly4lP13Oy8uL7du3c/r0aa5cuUJCQgL+/v5cu3aN7t27ExoayokTJ1izZg0vvfRSilIjIiKSU6moZKFmzZoRHx+fVFQKFiyIj48PRYsWpUKFCgB88MEH1KpVi9atW+Pr60vRokXp0KFDsv0MHToUW1tbfHx8KFy4MGfPnqVYsWJs2bKF+Ph4WrVqRdWqVRkyZAj58+fHxkZ/rCIiYh1MZrPZbHSIjIqMjMTNzY2IiAhcXV2TPXfnzh1OnTpFmTJlyJMnj0EJBfRnISIiyT3o/fu/9E9vERERsVgqKiIiImKxVFRERETEYqmoiIiIiMUytKjEx8czcuRIypQpQ968efH29ubDDz8kB6/vFRERkUxk6JXCJk2axIwZM5g9ezaVK1dm586dvPTSS7i5ufH6668bGU1EREQsgKFFZevWrbRv357nnnsOSLyw2fz585PuHCwiIiK5m6GHfho2bMj69es5evQokHijvc2bN9OmTZtUt4+JiSEyMjLZQ0RERKyXoUXl3XffpVu3blSsWBF7e3tq1qzJkCFD6NmzZ6rbT5gwATc3t6RHyZIlszmxcXx9fRkyZEi6tg0ODsZkMnHjxg0AZs2aRf78+bMsm4iISFYxtKgEBgYyb948fv75Z3bv3s3s2bP59NNPmT17dqrbjxgxgoiIiKTHuXPnsjlxztCwYUMuXLiAm5tuYS4iIjmboWtUhg0bljSrAlC1alXOnDnDhAkTePHFF1Ns7+joiKOjY3bHJD7BzI5T1wiPuoOHSx6eLFMQWxtTtudILwcHB4oWLWp0DBERkcdm6IzKrVu3UtxAz9bWloSEBIMSpbT64AUaT9pA9+/+5I1f9tL9uz9pPGkDqw9eyLLXjI6Opk+fPjg7O+Pp6clnn32W7Pm5c+dSp04dXFxcKFq0KD169CA8PDzp+f8e+rnf6dOnsbGxYefOncnGp06dSunSpS3qey8iImJoUWnXrh0fffQRK1as4PTp0yxevJjPP/+cjh07GhkryeqDF3jtp91ciLiTbPxixB1e+2l3lpWVYcOGERISwtKlS/n9998JDg5m9+7dSc/HxcXx4Ycfsm/fPpYsWcLp06fp27dvuvbt5eVFy5YtmTlzZrLxmTNn0rdvX915WURELIqhh36+/PJLRo4cycCBAwkPD6dYsWK88sorjBo1yshYQOLhnrG//UVql54zAyZg7G9/8bRP0Uw9DHTz5k1++OEHfvrpJ5566ikAZs+eTYkSJZK26devX9L/ly1bli+++IK6dety8+ZNnJ2dH/oaAwYM4NVXX+Xzzz/H0dGR3bt3c+DAAZYuXZppX4eIiEhmMPSfzy4uLkydOpUzZ85w+/ZtTpw4wfjx43FwcDAyFgA7Tl1LMZNyPzNwIeIOO05dy9TXPXHiBLGxsdSrVy9prGDBglSoUCHp4127dtGuXTtKlSqFi4sLzZo1A+Ds2bPpeo0OHTpga2vL4sWLgcSzgpo3b46Xl1fmfSEiIiKZQPP8aQiPSrukZGS7zBIdHU3r1q1xdXVl3rx5hIaGJhWO2NjYdO3DwcGBPn36MHPmTGJjY/n555+TzdKIiIhYChWVNHi45MnU7dLL29sbe3t7tm/fnjR2/fr1pIviHT58mKtXrzJx4kSaNGlCxYoVky2kTa8BAwawbt06AgICuHv3Lp06dcq0r0FERCSzqKik4ckyBfF0y0Naq09MgKdb4qnKmcnZ2Zn+/fszbNgwNmzYwMGDB5Mtci1VqhQODg58+eWXnDx5kmXLlvHhhx8+8utUqlSJ+vXrM3z4cLp3707evHkz9esQERHJDCoqabC1MTG6nQ9AirJy7+PR7Xyy5HoqkydPpkmTJrRr146WLVvSuHFjateuDUDhwoWZNWsWQUFB+Pj4MHHiRD799NMMvU7//v2JjY3VYR8REbFYJrPZnNqJLTlCZGQkbm5uRERE4Orqmuy5O3fucOrUKcqUKUOePBk/PLP64AXG/vZXsoW1nm55GN3Oh2eqeGZ4v5bgww8/JCgoiP3792fp62TWn4WIiFiHB71//5ehpyfnBM9U8eRpn6I56sq0D3Pz5k1Onz7NV199xfjx442OIyIikiYVlXSwtTHRwNvd6BiZZtCgQcyfP58OHTrosI+I5BqrD17k65ATnLoSTcWiLgxqUY4m5QsbHUseQmtUcqFZs2YRExPDggULsLW1NTqOiEiW+23feV79aRd7z90g4nYc209do+/MULYcv2J0NHkIFRUREbF6X204nmIsPsFMQHDKcbEsKioiImL1joZHpTp+5GLq42I5VFRERMTqlS3klOq4d+GH3x9NjKWiIiIiVm+gb7kUYyYTvOrrbUAaeRQ660dERKxe59olsLGBr4NPcvLKTSp5ujK4RXmaV/AwOpo8hIqKiIjkCh1rlqBjzRJGx5BHpEM/udysWbPInz9/ms8HBwdjMpm4ceNGtmUSERG5R0VFRERELJYO/aRHQjyc2Qo3L4FzESjdEGx0oTQREZGsphmVh/lrGUytArPbwqL+if+dWiVxPAssX76c/PnzEx8fD8DevXsxmUy8++67SdsMGDCAXr16AbB582aaNGlC3rx5KVmyJK+//jrR0dFJ28bExDB06FCKFy+Ok5MT9erVIzg4OM3Xv3z5MnXq1KFjx47ExMQkey46OhpXV1cWLlyYbHzJkiU4OTkRFaXrEYiISOZSUXmQv5ZBYB+IPJ98PPJC4ngWlJUmTZoQFRXFnj17AAgJCaFQoULJykVISAi+vr6cOHGCZ555hs6dO7N//34WLFjA5s2bGTRoUNK2gwYNYtu2bfzyyy/s378fPz8/nnnmGY4dO5bitc+dO0eTJk2oUqUKCxcuxNHRMdnzTk5OdOvWjZkzZyYbnzlzJl26dMHFxSUTvxMiIiIqKmlLiIfVwwFzKk/+/9jqdxO3y0Rubm7UqFEjqZgEBwfz5ptvsmfPHm7evMk///zD8ePHadasGRMmTKBnz54MGTKE8uXL07BhQ7744gvmzJnDnTt3OHv2LDNnziQoKIgmTZrg7e3N0KFDady4cYqyceTIERo1akTr1q2ZOXNmmvcAGjBgAGvWrOHChQsAhIeHs3LlSt3cUEREsoSKSlrObE05k5KMGSL/SdwukzVr1ozg4GDMZjN//PEHnTp1olKlSmzevJmQkBCKFStG+fLl2bdvH7NmzcLZ2Tnp0bp1axISEjh16hQHDhwgPj6eJ554Itk2ISEhnDhxIun1bt++TZMmTejUqRPTpk3DZDKlme3JJ5+kcuXKzJ49G4CffvqJ0qVL07Rp00z/PoiIiGgxbVpuXsrc7R6Br68vP/74I/v27cPe3p6KFSvi6+tLcHAw169fp1mzZokvffMmr7zyCq+//nqKfZQqVYr9+/dja2vLrl27UsyQODv/e9loR0dHWrZsyfLlyxk2bBjFixd/YL4BAwYwffp03n33XWbOnMlLL730wHIjIiKSUSoqaXEukrnbPYJ761SmTJmSVEp8fX2ZOHEi169f5+233wagVq1a/PXXX5Qrl/LS0AA1a9YkPj6e8PBwmjRpkubr2djYMHfuXHr06EHz5s0JDg6mWLFiaW7fq1cv3nnnHb744gv++usvXnzxxcf4akVERNKmQz9pKd0QXIsBac0UmMC1eOJ2maxAgQJUq1aNefPm4evrC0DTpk3ZvXs3R48eTSovw4cPZ+vWrQwaNIi9e/dy7Ngxli5dmrSY9oknnqBnz5706dOHX3/9lVOnTrFjxw4mTJjAihUrkr2mra0t8+bNo3r16rRo0YKLFy8+MF+nTp0YNmwYrVq1okQJXelRRESyhopKWmxs4ZlJ///Bf8vK/3/8zMQsu55Ks2bNiI+PTyoqBQsWxMfHh6JFi1KhQgUAqlWrRkhICEePHqVJkybUrFmTUaNGJZsNmTlzJn369OHtt9+mQoUKdOjQgdDQUEqVKpXiNe3s7Jg/fz6VK1emRYsWhIeHp5mvf//+xMbGahGtiIhkKZPZbE7ttJYcITIyEjc3NyIiInB1dU323J07dzh16hRlypQhT548GX+Rv5Ylnv1z/8Ja1+KJJcXn+YzvN4ebO3cub775JufPn8fBweGB22ban4WIiFiFB71//5fWqDyMz/NQ8Tldmfb/3bp1iwsXLjBx4kReeeWVh5YUERGRx6FDP+lhYwtlmkDVLon/zaUlBeCTTz6hYsWKFC1alBEjRhgdR0RErJyKijySMWPGEBcXx/r165Od4iwiIpIVVFRERETEYll9UcnBa4Wthv4MREQko6y2qNjb2wOJiz/FWPf+DO79mYiIiKSX1Z71Y2trS/78+ZOuBZIvXz5d5j2bmc1mbt26RXh4OPnz50/zRociIiJpsdqiAlC0aFGAB164TLJe/vz5k/4sREREHoVVFxWTyYSnpyceHh7ExcUZHSdXsre310yKiIhkmFUXlXtsbW31ZikiIpIDWe1iWhEREcn5VFRERETEYqmoiIiIiMVSURERERGLpaIiIiIiFktFRURERCyWioqIiOQagYGBlCxZkqCgIKOjSDqZzDn4jnGRkZG4ubkRERGBq6ur0XFERMSChYeH4+Pjw61bt3ByciIsLAwPDw+jY+VKj/L+rRkVERGxemazmYEDB2IymQgNDQXA39/f4FSSHoYWFS8vL0wmU4qHfnhERCQzBQYGsnTjdlq++x0Ttt3kmRHfsfj3TQQGBhodzTJFXoB1Y2BOe1j2Olw8YFgUQw/9XL58mfj4+KSPDx48yNNPP83GjRvx9fV96Ofr0I+IiDxMeHg4VXzb4dx2BAk29knjtvExRC0ew8Gt63QI6H7Xz8D3LSH6vhv62jpAjwXg3SJTXiLHHPopXLgwRYsWTXosX74cb29vmjVrZmQsERGxEvcO+TjW7ZqspADE2zpiX7O9ZvH/a/PnyUsKQHwsrB1lSByLWaMSGxvLTz/9RL9+/TCZTKluExMTQ2RkZLKHiIhIWsLCwli0aBF2nhVSfd7FuxYLFy4kLCwsm5NZsNNbUh+/eADuRGRvFiyoqCxZsoQbN27Qt2/fNLeZMGECbm5uSY+SJUtmX0AREclxKleuTOfOnYm/lfobbPSVCxQpUgR3d/dsTmbBnNM4DObgAvb5sjcLFlRUfvjhB9q0aUOxYsXS3GbEiBFEREQkPc6dO5eNCUVEJKcxmUwEBAQQd2hDqs9H7lnBpUuXqFatGqtXr87mdBaqbv/Ux2v1AVv71J/LQhZRVM6cOcO6desYMGDAA7dzdHTE1dU12UNERORBPDw8+Lx/KyJDl2BvSjx/xNHGzI3N8xjd8ymqVavG5cuXadOmDcOGDSM2NtbgxAar0hlajYc8bokf2zpA7b7QcowhcSzigm9jxozhm2++4dy5c9jZ2aX783TWj4iIpIfZbMbPz4+QbaHMWrCEvn7t8G3cgKCgIO7cucOwYcP46quvAKhTpw7z58+nXLlyBqc2WNxtuHYSXDwhX8FM3fWjvH8bXlQSEhIoU6YM3bt3Z+LEiY/0uSoqIiKSXg+7Mu3SpUvp168f165dw8XFhRkzZtCzZ08DE1uvHHN6MsC6des4e/Ys/fr1MzqKiIhYMQ8PDwICAnB3dycgICDFtVPat2/P3r17adq0KVFRUfTq1Yu+ffty8+ZNgxILWMCMyuPQjIqIiGS2+Ph4xo8fz7hx40hISOCJJ57gl19+oWbNmkZHsxo5akbF0iQkmNlw+BKTVh9m5pZTXI/O5YuqRERyGVtbW0aPHs3GjRspUaIER48epX79+kybNo0c/G/7HEszKveJuRvPgNk7+ePYlaQx1zx2zO73JDVLFXjs/YuISM5y9epV+vfvz9KlSwFo27YtM2fOpFChQgYny9k0o5JB87efTVZSACLv3GXEr8bdjElERIzj7u7O4sWL+eqrr3B0dGT58uVUr16djRs3Gh0t11BRuc/aQ5dSHT98MYqzV29lcxoREbEEJpMJf39/tm/fTsWKFTl//jxPPfUUI0eO5O7du0bHs3oqKvdxsE372+Fgp2+ViEhuVr16dXbu3En//v0xm82MHz8eX19fzpw5Y3Q0q6Z33/t0qFk81fH6ZQtS1C1PNqcRERFL4+TkxPfff88vv/yCq6srW7ZsoUaNGixatMjoaFZLReU+z1cvRu/6pbn/5s1lCzsxuUt140KJiIjFeeGFF9i7dy/16tXjxo0bdOnShVdffZXbt28bHS1znNkGczrAxNLwTVPYH2hYFJ31k4rTV6LZeeY6RVwdaeRdCBsb08M/SUREcp24uDhGjhzJpEmTgMS7NS9YsIDKlSsbnOwx/L0LZj4D8f+5PEfbqVDnpUx5CZ3185i8CjnRpXYJmpQvrJIiIiJpsre3Z+LEifz+++8UKVKEsLAw6tSpwzfffJNzr7myZUrKkgKw6VNISMj2OCoqIiIij+npp59m3759tG7dmjt37vDqq6/StWtXrl+/bnS0Rxd+KPXxyL8hNip7s6CiIiIikimKFCnCypUr+fTTT7Gzs2PhwoXUqFGDrVu3Gh3t0RR6IvVxl2Lg4JK9WVBRERERyTQ2Nja8/fbbbN26FW9vb86ePUvTpk356KOPiI+PNzpe+jR6A2zs0hjP/tqgoiIiIpLJ6taty+7du+nZsyfx8fF88MEHPP3005w/f97oaA9Xqj70DIKS9cDGHtzLJS6krf+qIXF01o+IiEgWMZvNzJkzB39/f6KjoylUqBCzZs3iueeeMzqaoXTWj4iIiAUwmUy8+OKL7Nq1i5o1a3LlyhXatm3Lm2++SUxMjNHxcgQVFRERkSxWoUIFtm3bxhtvvAHA1KlTadCgAUePHjU4meVTUREREckGjo6OTJ06ld9++w13d3f27NlDrVq1mDNnjtHRLJqKioiISDZq27Yt+/btw9fXl+joaF588UV69+5NVFT2X6MkJ1BRERERyWbFixdn3bp1fPjhh9ja2vLTTz9Rq1Ytdu3aZXQ0i6OiIiIiYgBbW1s++OADQkJCKFWqFMePH6dBgwZ89tlnJBhwqXpLpaIiIiJioEaNGrF37146d+5MXFwcQ4cO5bnnniM8PNzoaBZBRUVERMRgBQoUICgoiK+//po8efKwevVqqlevzrp164yOZjgVFRERyTVux8Zz9uotYu5a3uXsTSYTr7zyCqGhofj4+HDx4kVatWrFiBEjiIuLMzqeYVRURETE6pnNZj5dc4S6H62j6eSN1P94Pd9uOmF0rFRVqVKF0NBQXnnlFcxmMxMnTqRp06acOnXK6GiGUFERERGr93XISb7aeJybMXcBuH4rjo9XHiZo5zmDk6UuX758fP311wQFBeHm5saff/5JjRo1CAwMNDpatlNRERERqzdn2+lUx2enMW4punTpwr59+2jYsCGRkZG88MIL/O9//+PWrVtGR8s2KioiImLVzGYzFyPvpPrcxQjLv99O6dKlCQkJ4f3338dkMvH9999Tp04d9u/fb3S0bKGiIiIiVs1kMlG7VIFUn6tTOvVxS2NnZ8f48eNZt24dnp6eHDp0iCeffJKAgADMZrPR8bKUisp/JCSY2XD4EpNWH2bmllNcj441OpKIiDymoa0r4GCX/C3P2dGON1qWNyhRxrRo0YJ9+/bx3HPPERMTg7+/P507d+batWtGR8syJnMOrmKRkZG4ubkRERGBq6vrY+8v5m48A2bv5I9jV5LGXPPYMbvfk9RMo42LiEjOEHY+gh83n+bUlZtU9HSlf+MyeBd2NjpWhpjNZqZNm8Y777xDXFwcJUuWZN68eTRp0sToaOnyKO/fKir3mbXlFGN++yvFeMWiLqwe0vSx9y8iIpKZdu/eTbdu3Th27Bg2NjaMHj2a999/H1tbW6OjPdCjvH/r0M991h66lOr44YtRnL2ae1ZYi4hIznDvRoZ9+vQhISGB0aNH89RTT/H3338bHS3TqKjcx8E27W/Hf49tioiIWAIXFxdmz57N3LlzcXZ2JiQkhOrVq7Ns2TKjo2UKvfvep0PN4qmO1y9bkKJuebI5jYiISPr16tWL3bt3U7t2ba5du0b79u0ZPHgwd+6kfmp2TqGicp/nqxejd/3SmEz/jpUt7MTkLtWNCyUiIpJO5cuXZ+vWrbz11lsAfPXVV9SvX5/Dhw8/2o7ObIM5HWBiafimKew37oq4WkybitNXotl55jpFXB1p5F0IGxvTwz9JRETEgqxatYoXX3yRy5cvky9fPr788kteeuklTKaHvKf9vQtmPgPx/7k8R9upUOelTMmmxbSPyauQE11ql6BJ+cIqKSIikiO1adOGffv28dRTT3Hr1i369+9Pjx49iIiIePAnbpmSsqQAbPoUEhKyJuwDqKiIiIhYKU9PT37//XcmTJiAra0tv/zyCzVr1mTHjh1pf1L4odTHI/+G2KisCfoAKioiIiJWzMbGhnfffZfNmzfj5eXFqVOnaNSoEZ988gkJqc2QFHoi9R25FAMHl6wNmwoVFRErZzabCT19jZUHLnAplRuznboSzYr9Fzj4z0Omg0UkR6tfvz579uyha9eu3L17l+HDh9OmTRsuXryYfMNGb4CNXcodNHoDbLK/NmgxrYgVO3/jNv1mhXL4YuJ0rZ2NiVealWVY64rcjU/gnUX7WbznH+79Fmjo7c7XvWvjmsfewNQikpXMZjM//PADr7/+Ordv38bDw4M5c+bQunXrfzc6sQGCJxJ/bienb5i5XqkndV75KtMy6BL6IgJA92//ZNvJqynGv+ldmzNXo/l4ZcpTFrvVLcnEztWyI56IGOivv/6iW7duHDhwAIBhw4Yxfvx4HBwcAAgPD8fHx4dbt27h5OREWFgYHh4emfLaOutHRDh/43aqJQXg191/8+vuf1J9bsnef4hPyLH/fhGRdPLx8WH79u0MHDgQgMmTJ9O4cWNOnDiB2Wxm4MCBmEwmQkNDAfD39zckp4qKiJW6HRef5nO3YuPTfD7mboKKikgukTdvXqZPn86vv/5KgQIFCA0NpWbNmrzxxhssWrSIgIAAKleuzPTp01m4cCGBgdl/4TcVFRErVbaQE2ULOaX6XMtKRWhRMfUp3KblC+veViK5TMeOHdm7dy+NGzcmKiqKgIAAOnfujJ+fHwB+fn507twZf39/wsPDszWb4b+N/vnnH3r16oW7uzt58+alatWq7Ny507A816NjmbbuGL1/2M5bgXvZdea6YVlEHofJZGJ8xyrktU9+u/d6ZQryQt2SDGpejnIezsmeK+TswMi2lbIzpohYiFKlSrFhwwYqVaqEi4sLAQEBSc+ZTCYCAgIwm83ZfggolfOPss/169dp1KgRzZs3Z9WqVRQuXJhjx45RoEABQ/Jci46lY8AWzly9lTS2ePffTOtei+erFzMkk8jjaOhdiI1DfVm0+28uR8XwZJmCtPIpgp2tDXnsbVk+uDHL9p0n7J8ISrs70alWcfLnczA6togY5MiRIxw6dIhRo0alWDjr4eGBv78/48aNIywsjMqVK2dLJkPP+nn33XfZsmULf/zxR4Y+P7PP+vn89yN8seF4ivEiLg5sHdESW11OX0RErJjZbMbPz4+QkJAUZ/ncOwuoefPmBAUFPdbr5JizfpYtW0adOnXw8/PDw8ODmjVr8t1336W5fUxMDJGRkckemWn7qWupjl+KiuXM1ehMfS0RERFLk9YhnvvPApo+fXq2ZjK0qJw8eZIZM2ZQvnx51qxZw2uvvcbrr7/O7NmzU91+woQJuLm5JT1KliyZqXkKuTimOm6Ov0vI2pWZ+loiIiKWyMPDI+ksn3szJ0FBQSxatIjp06dn2rVU0svQQz8ODg7UqVOHrVu3Jo29/vrrhIaGsm3bthTbx8TEEBMTk/RxZGQkJUuWzLRDPyt3Hue1oEOYTMn7W8GoE5wL/DBTL3YjIiJiqe4/BBQcHIyvry++vr6Pfcjnnhxz6MfT0xMfH59kY5UqVeLs2bOpbu/o6Iirq2uyR2Yxm838OPFdYv+YScF8iWuMbW1MtKtejF9H+Bmy0llERMQI9x8Cqlu3LkC2H/K5x9Ci0qhRI44cOZJs7OjRo5QuXTrbs4SFhbFo0SJefroqf773NGuGNGX7e0/xZfeaeJXwxN/fn4ULFxIWFpbt2URERLKbh4cHAQEBuLu7ExAQYNgRBUMP/YSGhtKwYUPGjh1L165d2bFjB//73//49ttv6dmz50M/PzPP+smulc4iIiK5XY459FO3bl0WL17M/PnzqVKlCh9++CFTp05NV0nJbJa40llERCS3092T/2PBggV069aNwMBA/Pz8CAwM5IUXXmDBggV07do1U15DREQkN3uU928Vlf/470rnxo0bExkZycmTJw1ZOyMiFsJshuPr4cxmcPKAal3BqZDRqURyJBWVx3RvTcqtW7cwm83cuXOHl19+mW+++SbTXkNEcpD4OPilJxxb8++Ygwv0DILSDYzLJZJD5Zg1Kpbq/pXO7733HgA//vgjp0+fNjaYiBhj77zkJQUgNgqWDU6caRGRLKOikoauXbty7tw5Ro4cydNPP83du3cZP3680bFExAiH07gy9dVjcOVo9mYRyWVUVNJh7NixAMyaNYuTJ08anEZEsp2t/QOe092mRbKSiko6NGjQgNatWxMfH69ZFZHcqFoaZ/yVqAsFy2RvFpFcRkUlne7NqsyZM4fjx48bnEZEspVPe6jvD/ffB6xAGeioBfY5yeqDF+kwfQvVx/7OC99s449jl42OJOmgs34ewbPPPsuqVat48cUXmTVrVpa/nohYmOun4czWxNOTvZuDja3RiSSdftt3nsHz9yQbs7UxMaffkzQqp9PMs5vO+skiY8aMAWDu3LkcO3bM2DAikv0KeEGNHlC+pUpKDvPVhpQz4fEJZgKCNUNu6VRUHsGTTz5J27ZtSUhIYNy4cUbHERGRdDoaHpXq+JGLqY+L5VBReUT3ZlV+/vnnFHd+FhERy1S2kFOq496FnbM5iTwqFZVHVLt2bZ5//nnNqoiI5CADfculGDOZ4FVfbwPSyKNQUcmAe7Mq8+fP59ChQ8aGERGRh+pcuwRTXqhOhSIu2NuaqFbCjW9716F5BQ+jo8lD6KyfDOrYsSNLliyhW7duzJ8/P1tfW0REJCfL8rN+ypYty9WrV1OM37hxg7Jly2ZklznOvVmVBQsWEBYWZmwYERERK5WhonL69Gni4+NTjMfExPDPP/88dqicoHr16nTu3Bmz2ay1KiIiIlnE7lE2XrZsWdL/r1mzBjc3t6SP4+PjWb9+PV5eXpkWztKNHj2aRYsWERgYyAcffEDVqlWNjiQiImJVHmmNio1N4gSMyWTiv59mb2+Pl5cXn332GW3bts3clGnIijUq16NjmbPtDDvPXKOwiyM965WmdukCaW7ftWtXgoKC6Ny5MwsXLsyUDCIiItbsUd6/M7SYtkyZMoSGhlKokLGXHc7sonItOpaOAVs4c/VW0piNCaZ2q8nz1Yul+jlhYWFUrVoVs9nM3r17qV69+mPnEBERsWZZvpj21KlThpeUrDBry6lkJQUgwQwTVx4iPiH1Ple5cmW6dk28s+q9GxeKiIhI5nikNSr3W79+PevXryc8PJyEhIRkz/3444+PHcwI209dS3X8fMQdzlyNpmwaVzAcNWoUgYGBLF68mL1791KjRo0sTCkiIpJ7ZGhGZezYsbRq1Yr169dz5coVrl+/nuyRUxVycUx13M7GRIF8Dml+no+PD926dQP+PW1ZREREHl+G1qh4enryySef0Lt376zIlG6ZvUZl64kr9Px+O//9jrSvUYxp3Wo+8HMPHz5M5cqVSUhIYOfOndSuXfux84hkh9i7CVyMuEMhFwfyOWR4klVEJN2yfI1KbGwsDRs2zFA4S9bQuxCTOlWjkHPi7ImtjYl21YvxcceHn3ZcsWJFevToAWhWRXKOmVtO0WDCeppO3kjd8euY8ID1WCIiRsjQjMrw4cNxdnZm5MiRWZEp3bLqEvqxdxM4dSUad2cHCjmnfjgoNUePHqVSpUokJCSwY8cO6tatm2mZRDLbsn3neX3+nhTjQ1qWZ0jLJwxIJCK5RZacnvzWW28l/X9CQgKzZ8+mWrVqVKtWDXt7+2Tbfv755xmI/eiMvNdPWl588UXmzJnDs88+y4oVK4yOI5KmLjO2svNMyjVlBZ0c2PVBS0wmkwGpRCQ3eJT373QfkN6zJ/m/vO6d2XLw4MFk47n9l9vIkSOZN28eK1euZPv27dSrV8/oSCKpuhBxJ9Xxa9GxxMYn4Ghnm82JRERSSndR2bhxY1bmsBrlypWjd+/ezJo1izFjxrBq1SqjI4mkqo5XAf7ZezvFeNXibiopImIxMrSYVh5s5MiR2Nrasnr1arZt22Z0HJFUDW5RDtc8yf+tYm9rYljrCgYlsnBmMxxbB+vGwLYAiL5idCKRXCFDi2k7duyY6iEek8lEnjx5KFeuHD169KBChaz9hWeJa1TuGTBgAD/88ANPP/00v//+u9FxRFJ15mo03/9xik0HTnLqYChD2tTgrb6djY5leeLj4JeecGzNv2MOLtAzCEo3MC6XSA6V5acnu7m5sWHDBnbv3o3JZMJkMrFnzx42bNjA3bt3WbBgAdWrV2fLli0Z+gKswQcffICdnR1r167N1d8HsWyl3Z0Y3NCDsGn9uPLbZ0wY9irh4eFGx7I8e+clLykAsVGwbDApLrwkIpkqQ0WlaNGi9OjRg5MnT7Jo0SIWLVrEiRMn6NWrF97e3hw6dIgXX3yR4cOHZ3beHMPLy4uXXnoJgNGjRxucRiR1ZrOZgQMHYjKZCA0NBcDf39/gVBbo8MrUx68egytHszeLSC6ToaLyww8/MGTIEGxs/v10GxsbBg8ezLfffovJZGLQoEEpzgjKbd5//33s7e1Zv349f/zxh9FxRFIIDAxk0aJFBAQEULlyZaZPn87ChQsJDAw0OpplsbV/wHNp315DRB5fhorK3bt3OXz4cIrxw4cPEx8fD0CePHly/anKpUuXpl+/foBmVcTyhIeH4+/vT5cuXfDz8wPAz8+Pzp074+/vr0NA96vWNfXxEnWhYJnszSKSy2SoqPTu3Zv+/fszZcoUNm/ezObNm5kyZQr9+/enT58+AISEhFC5cuVMDZsTvffee9jb27Nx40aCg4ONjiMCJD/kM3369KRxk8lEQEAAZrNZh4Du59Me6vuD6b5fmQXKQMdvjMskkpl2fAfT68MkL5jfAy4eMDpRkgyd9RMfH8/EiRP56quvuHTpEgBFihRh8ODBDB8+HFtbW86ePYuNjQ0lSpTI9ND3WPJZP/fz9/cnICCApk2bEhwcnOtnmsR4Bw8epGrVqowaNYqxY8emeH706NGMGzeOgwcP6h8c97t+Gs5sBScP8G4ONrrejFiB4IkQPCH5mKMrvBwM7t5Z8pJZcgn9B70YYEhRyClF5e+//8bb25vY2FjWr19PixYtjI4kuZzZbMbPz4+QkBDCwsLw8PBIei48PJwKFSrg7e3Ntm3bUtwiQ0SsSGw0fFoh8Sy2/3ryZXh2cpa8bJafnnw/V1dXiy4JlqBEiRK8/PLLQOK/VB+zG4o8trQO8ZjNZl599VWioqLYtWsXFSpUYObMmdy9e9fAtCKSZSL+Tr2kAIQfyt4saUh3UalVqxbXryfewKxmzZrUqlUrzYekNGLECBwdHdm8eTPr1683Oo4IHh4eSWf5BAUFARAUFMTixYvp2bMnHh4enDp1in79+lGpUiXmzp2rwiJibVyLg71T6s8VKp+9WdKQ7kM/Y8eOZdiwYeTLly/VY9r3y64zXLLq0M/FiDvsPnsdDxdH6ngVzLT9vvHGG3zxxRc0bNiQzZs3a62KGO7+Q0DBwcH4+vri6+tLUFAQ0dHRzJgxg0mTJnHlSuLl4p944glGjx7NCy+8gK2t1meIWIV1Y2DzlORj9vnghXkQEwH5S0PxzJ2EyNY1KkbKiqIyYdUhfvjjFHcTEr8tPp6u/Ni3LkXd8jz2vi9cuEDZsmW5c+cOa9asoVWrVo+9T5HHFR4ejo+PD7du3cLJySnFmpWbN28yffp0PvnkE65duwZApUqVGD16NH5+fsmupyQiOVBCAmz7EnZ8DzcvQqkGiUXl6Grg/ytC6Ubwwk+QL3P+8Z4ta1Ru3LjB999/z4gRI5J+ee3evZt//vkno7s03Ir9F/gm5GRSSQH460Ikwxbuy5T9e3p68tprrwFaqyKWw8PDg4CAANzd3QkICEhWUgCcnZ0ZPnw4p06dYvz48eTPn59Dhw7RrVs3qlevzqJFi0hISDAovYg8NhsbaPQGvHkARl6Gim3h6CqSSgrAmS2w+l1D4mVoRmX//v20bNkSNzc3Tp8+zZEjRyhbtiwffPABZ8+eZc6cOVmRNYXMnlEZMDuUdYdSXuTKZILtI57Cw/XxZ1UuXbpEmTJluH37NitXrqRNmzaPvU+R7BQREcG0adP4/PPPiYiIAKB69eqMGTOG9u3b65CmSE73bXM4vzvluK0DjPgb7Bwf+yWyfEblrbfeom/fvhw7dow8ef5983722WfZtGlTRnZpEW7Fxqc6bjbD7bjUn3tURYoUYeDAgYBmVSRncnNzY9SoUZw+fZpRo0bh4uLCvn376NixI3Xq1GH58uX6uRbJyeJupT4eH5t4J/FslqGiEhoayiuvvJJivHjx4ly8ePGxQxmlRUWPVMfLezhT2j2NVdEZ8M4775AvXz5CQ0NZuTKNm52JWLj8+fMzduxYTp8+zXvvvYeTkxO7d++mXbt21KtXj1WrVqmwiORET7ROfdyrCTg6Z28WMlhUHB0dky70dr+jR49SuHDhdO9nzJgxmEymZI+KFStmJFKm6FW/NHW9CiQbc3KwZXyHKpn6Oh4eHknXrhgzZox+mYthzt+4zYSVh+j1/XbeW3yAo5fSuJ7CAxQsWJCPPvqI06dPM3z48KQS/uyzz9KwYUN+//13/YyL5CSN3wSP/1yROm9BeGaiIXEytEZlwIABXL16lcDAQAoWLMj+/fuxtbWlQ4cONG3alKlTp6ZrP2PGjGHhwoWsW7cuaczOzo5ChQql6/Oz4qyfuPgEfg+7ROjpaxR2caRL7RIUyYS1Kf91+fJlypQpQ3R0NMuWLaNdu3aZ/hoiD3LqSjSdZ2zlWnRs0pijnQ2z+z1J/bLuGd5veHg4n3zyCQEBAdy+fRuARo0aMW7cOJo3b641LCI5QdwdCFucuFYlf2mo3h2cMv574b+y/PTkiIgIunTpws6dO4mKiqJYsWJcvHiR+vXrs2rVKpyc0neYZMyYMSxZsoS9e/c+agQg51xCPy3vvvsukyZNombNmuzatUu/wCVbvRW4l193pzxLr2ap/Cwe2Oix93/x4kUmTZrEjBkziImJAaBZs2aMHTuWZs2aPfb+RSTnyvLFtG5ubqxdu5bly5fzxRdfMGjQIFauXMmmTZvSXVLuOXbsGMWKFaNs2bL07NmTs2fPprltTEwMkZGRyR452dChQ3F2dmbPnj0sXbrU6DiSy+w4dS3V8T1nbxBz9/EXjxctWpQpU6Zw8uRJBg0ahIODAyEhIfj6+vLUU0+xefPmx34NEbF+Gb6Oyvr161mxYgW7d+/m8OHD/Pzzz/Tr149+/fqlex/16tVj1qxZrF69mhkzZnDq1CmaNGlCVFTqx8knTJiAm5tb0qNkyZIZjW8RChUqxOuvvw4kzi7pWhSSnQo5p36KYf589jjYZt5F3IoVK8aXX37J8ePHee2117C3t2fDhg00adKEVq1asW3btkx7LRGxPhk69DN27FjGjRtHnTp18PT0THHIYvHixRkKc+PGDUqXLs3nn39O//79UzwfExOTNIUMiVNHJUuWzLGHfgCuXbuGl5cXUVFRLFq0iE6dOhkdSXKJhbv+ZmhQyosZDvT15p1nsm5R+5kzZ/joo4+S3eywTZs2jB07lrp162bZ64qI5cjyNSqenp588skn9O7dO8Mh01K3bl1atmzJhAkTHrptTl+jcs/IkSMZP348VatWZe/evbokuWSb6RuP83XICaLu3MXBzoZudUsyqq0Pdpk4o5KWe1e6nT17NvHxiYea2rZty9ixY3VzUxErl+VFxd3dnR07duDt7Z3hkKm5efMmpUqVYsyYMUmHRB7EWorK9evX8fLyIjIykqCgILp06WJ0JMlFbsXe5ey1W3i65sUtn322v/7x48cZP348c+fOTTr82aFDB8aMGUP16tWzPY+IZL0sX0w7YMAAfv755wyFu9/QoUMJCQnh9OnTbN26lY4dO2Jra0v37t0fe985SYECBRgyZAiQeFhNa1UkO+VzsKNiUVdDSgpAuXLlmDVrFocOHaJnz56YTCaWLFlCjRo16NKlCwcPHjQkl4hYhnTPqLz11ltJ/5+QkMDs2bOpVq0a1apVw94++S+4zz//PF0v3q1bNzZt2sTVq1cpXLgwjRs35qOPPkr3TI21zKhA4vocLy8vIiIiWLBgAV27djU6koghDh06xLhx41iwYAFmsxmTyUTXrl0ZPXo0lSpVMjqeiGSCLDn007x583S9uMlkYsOGDena9nFZU1EBGDduXNIv4wMHDmBra2t0JBHDhIWFMXbsWIKCgoDE3y3du3dn1KhRVKhQweB0IvI4snyNiqWwtqISERGBl5cXN27c4Oeff851h8BEUrN//37GjBmTdDahjY0NPXv2ZNSoUZQrV87gdCKSEVm+RkWyhpubG2+//TaQOLty70wIkdysWrVq/Prrr+zatYt27dqRkJDA3LlzqVixIv369ePkyZNGRxSRLKSiYmFef/11ChYsyOHDh/nll1+MjiNiMWrVqsWyZcvYsWMHzz77LPHx8cycOZMKFSrwv//9jzNnzhgdUUSygIqKhXF1dU02q3Lvglgikqhu3bqsWLGCP//8k9atW3P37l2+//57ypcvz2uvvca5c+eMjigimUhFxQINHjwYd3d3jh49yvz5842OI2KR6tWrx+rVq9m8eTNPPfUUcXFxfP3115QrV45Bgwbxzz8pb7goIjmPiooFcnFxYdiwYYBmVUQeplGjRqxbty7phoexsbFMnz4db29v3njjDS5cuGB0RBF5DCoqFsrf359ChQpx/PhxfvrpJ6PjiFi8pk2bsnHjRjZs2EDjxo2JiYnhiy++oGzZsrz99ttcunTJ6IgikgEqKhbK2dmZd955B4APP/yQuLg4gxOJ5AzNmzdn06ZNrF27lgYNGnDnzh0+//xzypYtyzvvvMPly5eNjigij0BFxYINHDgQDw8PTp48ydy5c42OI5JjmEwmWrZsyZYtW1i1ahVPPvkkt27dYvLkyZQpU4b33nuPq1evGh1TRNJBRcWCOTk5Jc2qjB8/XrMqIo/IZDLxzDPP8Oeff7J8+XJq1apFdHQ0EyZMoEyZMowcOZLr168bHVNEHkBFxcK99tprFClShFOnTjF79myj44jkSCaTieeee46dO3eydOlSqlevTlRUFOPHj8fLy4uxY8cSERFhdEwRSYWKioXLly8f7777LpA4qxIbG2twIpGcy2Qy8fzzz7N7924WLVpElSpViIyMZMyYMXh5eTF+/HgiIyPT3kHURbZ+P5zOdTwJCgzMvuAiuZju9ZMD3L59G29vby5cuMDXX3/NK6+8YnQkEauQkJDAokWLGDNmDH/99RcABQsWZOjQoQwePBhnZ+d/N94wHvPmKZgSEi8X8NdVEx5DNlLIu6YR0UVyNN3rx8rkzZs3aVblo48+IiYmxuBEItbBxsYGPz8/9u/fz88//0yFChW4du0a7733HmXKlGHy5MlER0fDkVWwaXJSSQHwcTcT/nUH48KL5BIqKjnEyy+/TLFixTh37hw//vij0XFErIqtrS3du3cnLCyMuXPnUq5cOa5cucI777xD2bJlORo0LtXP83G6wfKfArI5rUjuoqKSQ+TJk4cRI0YA8PHHH2tWRSQL2Nra0qtXLw4dOsSsWbMoW7Ys4eHhHD+0L83PmTBuFOHh4dmYUiR3UVHJQQYMGEDx4sX5+++/+f77742OI2K17OzsePHFFzl8+DDfffcda8/YprrdXddSHLlmxt/fP5sTiuQeKio5SJ48eXjvvfeAxFmVO3fuGJxIxLrZ29tTv359Av68yUlzyeRP2uXFrv0X+PsPYuHChYSFhRkTUsTK6ayfHCYmJoby5ctz7tw5pk2bxuuvv250JBGrZjab8fPzY/OmYI4snYLb9QPgXBiq9yA8xh4fHx+aN29OUFCQ0VFFcgyd9WPFHB0def/99wGYMGECt2/fNjiRiHUzmUwEBARwNwEGfL4Mnv0Emg7D7FqMgQMHYjKZmD59utExRayWikoO9NJLL1G6dGkuXrzIN998Y3QcEavn4eHB9OnTWbhwYdLMSVBQEIsWLWL69Ol4eHgYnFDEeunQTw713Xff8fLLL1OkSBFOnjxJvnz5jI4kYtXuHQIKCQkhODgYX19ffH19dchHJAN06CcX6Nu3L15eXly6dImvv/7a6DgiVu/eISCz2UzdunUBdMhHJBuoqORQ9vb2fPDBBwBMmjQp8eqZIpKlPDw8CAgIwN3dnYCAAB3yEckGOvSTg8XFxVGxYkVOnjzJ5MmTGTp0qNGRREREHkqHfnIJe3t7Ro4cCSTOqty8edPgRCIiIplLRSWH69WrV9J9SXS8XERErI2KSg5nZ2eXNKsyefJkoqKiDE4kIiKSeVRUrECPHj0oX748V69e5auvvjI6joiISKZRUbECdnZ2jBo1CoBPP/2UyMhIgxOJiIhkDhUVK9G9e3cqVKjAtWvX+PLLL42OIyIikilUVKyEra0to0ePBhJnVSIiIgxOJCIi8vhUVKxI165dqVSpEjdu3GDatGlGxxEREXlsKipW5P5Zlc8//5wbN24YG0hEROQxqahYGT8/PypXrkxERARTp041Oo6IiMhjUVGxMjY2NkmzKlOmTOH69esGJxIREck4FRUr1LlzZ6pWrUpkZCRTpkwxOo6IiEiGqahYoftnVaZOncq1a9cMTiQiIpIxKipWqmPHjlSvXp2oqCg+++wzo+OIiIhkiIqKlbKxsWHMmDEAfPHFF1y5ciVrXuj2dfhrGZzYAAnxWfMaIiKSa6moWLH27dtTs2ZNbt68mTWzKqE/wGeVILA3zO0I06rDhf2Z/zoiIpJrqahYMZPJlDSr8uWXX3L58uXM2/mF/bDibbh7+9+xiHOwoBckJGTe64iISK6momLl2rVrR+3atYmOjubTTz/NvB3vXwCYU47fOANnt2be64iISK6momLl7p9V+eqrrwgPD8+cHcfdesBzt9N+TkRE5BGoqOQCzz33HHXr1uXWrVt88sknmbPTJ55JfdzRFUo3zJzXEBGRXM9iisrEiRMxmUwMGTLE6ChWx2QyMXbsWAACAgK4ePHi4++0fCuo2vU/L2QLz34KDk6Pv38REREspKiEhobyzTffUK1aNaOjWK1nnnmGevXqcfv27cyZVTGZoNO30Hsx1HsNmg4D/+1Q/YXH37eIiMj/M7yo3Lx5k549e/Ldd99RoEABo+NYrftnVWbMmMGFCxcyY6fg3QLaTIQWH0Ch8o+/TxERkfsYXlT8/f157rnnaNmy5UO3jYmJITIyMtlD0q9Vq1Y0aNCAO3fuMGnSJKPjiIiIPJShReWXX35h9+7dTJgwIV3bT5gwATc3t6RHyZIlszihdbl/VuXrr7/m/PnzBicSERF5MMOKyrlz53jjjTeYN28eefLkSdfnjBgxgoiIiKTHuXPnsjil9WnZsiWNGjUiJiaGiRMnZs5Ob5yD6KuZsy8REZH7mMxmcypX7cp6S5YsoWPHjtja2iaNxcfHYzKZsLGxISYmJtlzqYmMjMTNzY2IiAhcXV2zOrLV2LBhA0899RQODg6cOHGCEiVKZGxHpzfDiqFw+RCYbKB8a3j+S3AunLmBRUTEqjzK+7dhMypPPfUUBw4cYO/evUmPOnXq0LNnT/bu3fvQkiIZ17x5c5o2bUpsbGy6D7ulcOMczOuaWFIAzAlwdBUs6Jl5QUVEJNczrKi4uLhQpUqVZA8nJyfc3d2pUqWKUbFyhfvXqnz//fcZO4S2dx7ERaccP7cdzu99vIAiIiL/z/CzfsQYvr6++Pr6Ehsby8cff/zoO4h8wELcqEw49VlERAQLKyrBwcFMnTrV6Bi5xr1ZlR9++IEzZ8482ieXqp/6uI09FKv1mMlEREQSWVRRkezVtGlTWrRoQVxc3KPPqlTuBMVqphxvOBhcimROQBERyfUMO+snM+isn8e3efNmmjRpgp2dHUePHqVMmTLp/+SYKNjxLRxbCw7OUKMHVOmUdWFFRMQqPMr7t4qK0KpVK9auXUv//v35/vvvjY4jIiJWLkecniyW495alVmzZnHy5EmD04iIiPxLRUVo0KABrVu3Jj4+nvHjxxsdR0REJImKigD/zqrMmTOH48ePG5xGREQkkYqKAFCvXj3atGmjWRUREbEoKiqSZMyYMQDMnTuXY8eOGRtGREQEFRW5z5NPPknbtm1JSEhg3LhxRscRERFRUZHk7s2q/Pzzzxw5csTYMCIikuupqEgytWvX5vnnn9esioiIWAQVFUnh3qzK/PnzOXTokLFhJMuduhLNiv0XOPhPhNFRLM/5vRC2GK6eMDqJSK5lZ3QAsTw1a9akQ4cOLFmyhHHjxjF//nyjI0kWuBufwDuL9rN4zz/cuz51Q293vu5dG9c89saGM9qdCFjQC05t+v8BE1TvDu2/AhtbQ6OJ5DaaUZFU3ZtVWbBgAWFhYcaGkSzx45ZT/Lr735ICsPXEVT5eoVk01rx3X0kBMMO+n+HPGYZFEsmtVFQkVdWrV6dz586YzWatVbFSv+7+J9XxJXv/IT4hx94C7PHF34UDC1N/bt8v2ZtFRFRUJG2jR48GIDAwkAMHDhicRjLb7bj4VMdj7ibk7qJijoe7Mak/FxedvVlEREVF0la1alX8/PyAfy+xL9ajRUWPVMebli+Mg10u/tVg5whlfVN/7ok22RpFRFRU5CFGjx6NyWRi0aJF7Nu3z+g4kokGNS9HOQ/nZGOFnB0Y2baSQYksyDMTwKlw8jH38oklZk4H+PVlOLPNkGgiuY3JbDbn2DneyMhI3NzciIiIwNXV1eg4Vqtbt24sWLCAjh078uuvvxodRzLRnbh4lu07T9g/EZR2d6JTreLkz+dgdCzLcOta4pqU66fAvRxs/wau3X+asgk6BECNHoZFFMmpHuX9W0VFHuqvv/6iSpUqmM1m9uzZQ40aNYyOJJK9Nn0KGz5MOe7kAW+GgZ3KncijeJT3bx36kYfy8fGhW7duwL+nLYvkKme2pD4eHQ5XjmZvFpFcRkVF0mXUqFHY2NiwdOlSdu3aZXQckezllPrCY0w2KdeyiEimUlGRdKlYsSI9eiQei9esiuQ6dfollpL/qvgcuBTJ/jwiuYiKiqTbyJEjsbGxYfny5YSGhhodRyT7lKoHHb4G5/8vJSYb8GkP7acbm0skF9BiWnkkL774InPmzOHZZ59lxYoVRscRyV7xcXDlGDgVAuc0DgeJyENpMa1kmZEjR2Jra8vKlSvZvn270XFEspetPRTxUUkRyUYqKvJIypUrR+/evQGtVRERkaynoiKP7N6syurVq9m2bRuBgYGULFmSoKAgo6OJiIiVUVGRR1a2bFn69u0LwIgRIxg4cCBXr15l4MCBhIeHGxtORESsioqKZMgHH3yAra0tmzZtAkg6C8jf39/IWCIiYmVUVCRDvLy8aNasGWazmRkzZlC5cmWmT5/OwoULCQwMNDqeiIhYCRUVyZDw8HD27NlDp06d8PPzA8DPz4/OnTvj7++vQ0AiIpIpVFTkkZnNZgYOHIitrS0zZsxIGjeZTAQEBGA2m3UISEREMoWKijyysLAwFi1axMCBA/HwSH49CQ8PD/z9/Vm4cCFhYWEGJRQREWthZ3QAyXkqV65M586dWTZ3Ou9WPEPec5vAwRlq9CC8Qm+mT59Oly5dqFy5stFRRUQkh9Ml9CVDLp87zp0ptSn5n2/7phtF6TzvGmFhYSlmW0RERODR3r81oyIZUviftZDKz1ZjtwvMmvKxSoqIiGQKrVGRjAn/K9VhG5OJ5+p6Z3MYERGxVioqkjGFnkj7Offy2ZdDRESsmoqKZEyNnuBcNOV4peehULnszyMiIlZJRUUyJl9BeGllYjGxywNOhaHRG9DpO6OTiYiIFdFiWsk4d294Ya7RKURExIppRkVEREQsloqKiIiIWCwVFREREbFYhhaVGTNmUK1aNVxdXXF1daVBgwasWrXKyEgiIiJiQQwtKiVKlGDixIns2rWLnTt30qJFC9q3b6+b2YmIiAhggff6KViwIJMnT6Z///4P3Vb3+hEREcl5cuS9fuLj4wkKCiI6OpoGDRqkuk1MTAwxMTFJH0dGRmZXPBERETGA4YtpDxw4gLOzM46Ojrz66qssXrwYHx+fVLedMGECbm5uSY+SJUtmc1oRERHJToYf+omNjeXs2bNERESwcOFCvv/+e0JCQlItK6nNqJQsWVKHfox24xzY5wMnd6OTiIhIDvAoh34MLyr/1bJlS7y9vfnmm28euq3WqBjs9GZYMRQuHwKTDZRvDc9/Cc6FjU4mIiIW7FHevw0/9PNfCQkJyWZNxELdOAfzuiaWFABzAhxdBQt6GptLRESsiqGLaUeMGEGbNm0oVaoUUVFR/PzzzwQHB7NmzRojY0l67J0HcdEpx89th/N7oViN7E4kIiJWyNCiEh4eTp8+fbhw4QJubm5Uq1aNNWvW8PTTTxsZS9Ij8nzaz0VdAGpkVxIREbFihhaVH374wciXl8dRqj7snp1y3MYeitXK/jwiImKVLG6NiuQQlTtBsZopxxsOBpci2Z9HRESsksVc8E1yGPs88OJvsONbOLYWHJyhRg+o0snoZCIiYkUs7vTkR6HTk0VERHKeHH16soiIiMg9KioiIiJisVRURERExGKpqIiIiIjFUlERERERi6WiIiIiIhZLRUVEREQsloqKiIiIWCwVFREREbFYKioiIiJisVRURERExGKpqIiIiIjFUlERERERi6WiIiIiIhZLRUVEREQsloqKiIiIWCwVFREREbFYKioiIiJisVRURERExGKpqIiIiIjFUlERERERi6WiIiIiIhZLRUVEREQsloqKiIiIWCwVFREREbFYdkYHkBzu7J9w7HdwcIaqfpC/pNGJRETEiqioSMYtex12z/73440fQ5cfwKe9cZlERMSq6NCPZMzx9clLCkBCXGJ5ibttTCYREbE6KiqSMUdWpj5+5wac3pKtUURExHqpqEjG2Dqk/ZzdA54TERF5BCoqkjFV/VIfdy0BpRtlbxYREbFaKiqSMcVrQavxYGP/75hTYeg6G2xsjcslIiJWRWf9SMY1HAxVu8LJjeDoAuVagp2j0alERMSKqKjI43EpAtW7GZ1CRESslA79iIiIiMVSURERERGLpaIiIiIiFktFRURERCyWioqIiIhYLBUVERERsVgqKiIiImKxVFRERETEYhlaVCZMmEDdunVxcXHBw8ODDh06cOTIESMjiYiIiAUxtKiEhITg7+/Pn3/+ydq1a4mLi6NVq1ZER0cbGUtEREQshMlsNpuNDnHP5cuX8fDwICQkhKZNmz50+8jISNzc3IiIiMDV1TUbEoqIiMjjepT3b4u6109ERAQABQsWTPX5mJgYYmJiUmwfGRmZ9eFEREQkU9x7307PXInFzKgkJCTw/PPPc+PGDTZv3pzqNmPGjGHs2LHZnExERESywrlz5yhRosQDt7GYovLaa6+xatUqNm/enGbo/86oJCQkcO3aNdzd3TGZTNkV1TCRkZGULFmSc+fO6VCXWD39vEtuktt+3s1mM1FRURQrVgwbmwcvl7WIQz+DBg1i+fLlbNq06YHNytHREUdHx2Rj+fPnz+J0lsfV1TVX/CCLgH7eJXfJTT/vbm5u6drO0KJiNpsZPHgwixcvJjg4mDJlyhgZR0RERCyMoUXF39+fn3/+maVLl+Li4sLFixeBxJaVN29eI6OJiIiIBTD0OiozZswgIiICX19fPD09kx4LFiwwMpbFcnR0ZPTo0SkOf4lYI/28S26in/e0WcxiWhEREZH/0r1+RERExGKpqIiIiIjFUlERERERi6WiYiF8fX0ZMmSI0TFEcjT9PRJL8LCfQ5PJxJIlS9K9v+DgYEwmEzdu3HjsbDmRRVzwTUREJLe4cOECBQoUMDpGjqGiIiIiko2KFi1qdIQcRYd+LND169fp06cPBQoUIF++fLRp04Zjx44BiVfzLVy4MAsXLkzavkaNGnh6eiZ9vHnzZhwdHbl161a2ZxdJja+vL4MHD2bIkCEUKFCAIkWK8N133xEdHc1LL72Ei4sL5cqVY9WqVUmfc/DgQdq0aYOzszNFihShd+/eXLlyJen56Oho+vTpg7OzM56ennz22WdGfGkiqUpISOCdd96hYMGCFC1alDFjxiQ9999DP1u3bqVGjRrkyZOHOnXqsGTJEkwmE3v37k22z127dlGnTh3y5ctHw4YNOXLkSPZ8MQZTUbFAffv2ZefOnSxbtoxt27ZhNpt59tlniYuLw2Qy0bRpU4KDg4HEUnPo0CFu377N4cOHAQgJCaFu3brky5fPwK9CJLnZs2dTqFAhduzYweDBg3nttdfw8/OjYcOG7N69m1atWtG7d29u3brFjRs3aNGiBTVr1mTnzp2sXr2aS5cu0bVr16T9DRs2jJCQEJYuXcrvv/9OcHAwu3fvNvArFPnX7NmzcXJyYvv27XzyySeMGzeOtWvXptguMjKSdu3aUbVqVXbv3s2HH37I8OHDU93n+++/z2effcbOnTuxs7OjX79+Wf1lWAazWIRmzZqZ33jjDfPRo0fNgHnLli1Jz125csWcN29ec2BgoNlsNpu/+OILc+XKlc1ms9m8ZMkSc7169czt27c3z5gxw2w2m80tW7Y0v/fee9n/RYikoVmzZubGjRsnfXz37l2zk5OTuXfv3kljFy5cMAPmbdu2mT/88ENzq1atku3j3LlzZsB85MgRc1RUlNnBwSHp74TZbDZfvXrVnDdvXvMbb7yR5V+PyIP89+fdbDab69atax4+fLjZbDabAfPixYvNZrPZPGPGDLO7u7v59u3bSdt+9913ZsC8Z88es9lsNm/cuNEMmNetW5e0zYoVK8xAss+zVppRsTCHDh3Czs6OevXqJY25u7tToUIFDh06BECzZs3466+/uHz5MiEhIfj6+uLr60twcDBxcXFs3boVX19fg74CkdRVq1Yt6f9tbW1xd3enatWqSWNFihQBIDw8nH379rFx40acnZ2THhUrVgTgxIkTnDhxgtjY2GR/TwoWLEiFChWy6asRebD7f94BPD09CQ8PT7HdkSNHqFatGnny5Ekae/LJJx+6z3uH+1Pbp7XRYtocqGrVqhQsWJCQkBBCQkL46KOPKFq0KJMmTSI0NJS4uDgaNmxodEyRZOzt7ZN9bDKZko2ZTCYg8dj+zZs3adeuHZMmTUqxH09PT44fP561YUUeU2o/7wkJCZm2z/v/vlg7zahYmEqVKnH37l22b9+eNHb16lWOHDmCj48PkPgD2qRJE5YuXUpYWBiNGzemWrVqxMTE8M0331CnTh2cnJyM+hJEHlutWrUICwvDy8uLcuXKJXs4OTnh7e2Nvb19sr8n169f5+jRowamFnl0FSpU4MCBA8TExCSNhYaGGpjI8qioWJjy5cvTvn17/ve//7F582b27dtHr169KF68OO3bt0/aztfXl/nz51OjRg2cnZ2xsbGhadOmzJs3j2bNmhn4FYg8Pn9/f65du0b37t0JDQ3lxIkTrFmzhpdeeon4+HicnZ3p378/w4YNY8OGDRw8eJC+fftiY6NfaZKz9OjRg4SEBF5++WUOHTrEmjVr+PTTT4F/Z01yO/2ttkAzZ86kdu3atG3blgYNGmA2m1m5cmWyab9mzZoRHx+fbC2Kr69vijGRnKhYsWJs2bKF+Ph4WrVqRdWqVRkyZAj58+dPKiOTJ0+mSZMmtGvXjpYtW9K4cWNq165tcHKRR+Pq6spvv/3G3r17qVGjBu+//z6jRo0CSLZuJTczmc1ms9EhREREJNG8efN46aWXiIiIIG/evEbHMZwW04qIiBhozpw5lC1bluLFi7Nv3z6GDx9O165dVVL+n4qKiIiIgS5evMioUaO4ePEinp6e+Pn58dFHHxkdy2Lo0I+IiIhYLC2mFREREYuloiIiIiIWS0VFRERELJaKioiIiFgsFRURERGxWCoqIiIiYrFUVERERMRiqaiIiIiIxVJREZFst3DhQqpWrUrevHlxd3enZcuWREdH4+vry5AhQ5Jt26FDB/r27Zv0sZeXFx9//DH9+vXDxcWFUqVK8e2332bvFyAi2UZFRUSy1YULF+jevTv9+vXj0KFDBAcH06lTJx7lItmfffYZderUYc+ePQwcOJDXXnuNI0eOZGFqETGK7vUjItnqwoUL3L17l06dOlG6dGkAqlat+kj7ePbZZxk4cCAAw4cPZ8qUKWzcuJEKFSpkel4RMZZmVEQkW1WvXp2nnnqKqlWr4ufnx3fffcf169cfaR/VqlVL+n+TyUTRokUJDw/P7KgiYgFUVEQkW9na2rJ27VpWrVqFj48PX375JRUqVODUqVPY2NikOAQUFxeXYh/29vbJPjaZTCQkJGRpbhExhoqKiGQ7k8lEo0aNGDt2LHv27MHBwYHFixdTuHBhLly4kLRdfHw8Bw8eNDCpiBhNa1REJFtt376d9evX06pVKzw8PNi+fTuXL1+mUqVKODk58dZbb7FixQq8vb35/PPPuXHjhtGRRcRAKioikq1cXV3ZtGkTU6dOJTIyktKlS/PZZ5/Rpk0b4uLi2LdvH3369MHOzo4333yT5s2bGx1ZRAxkMj/KOYEiIiIi2UhrVERERMRiqaiIiIiIxVJREREREYuloiIiIiIWS0VFRERELJaKioiIiFgsFRURERGxWCoqIiIiYrFUVERERMRiqaiIiIiIxVJREREREYv1f8AywmmpFnNeAAAAAElFTkSuQmCC",
- "text/plain": [
- "<Figure size 640x480 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"ax = sns.swarmplot(data=plant_data, x='sun', y='height', hue='water', dodge=True)\n",
"\n",
@@ -2333,24 +1037,13 @@
},
{
"cell_type": "code",
- "execution_count": 42,
+ "execution_count": null,
"id": "811df467-f3ec-4ae4-939c-a8917c2f9d04",
"metadata": {
"hidden": true,
"tags": []
},
- "outputs": [
- {
- "data": {
- "image/png": "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",
- "text/plain": [
- "<Figure size 640x480 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"statsmodels_material.interaction_plot(plant_data)"
]
@@ -2382,13 +1075,13 @@
"hidden": true
},
"source": [
- "<table><tr><td><img src=\"img/two-way-anova-interaction-significant-flowchart.png\" /></td></tr>\n",
+ "<table><tr><td><img src=\"../images/two-way-anova-interaction-significant-flowchart.png\" /></td></tr>\n",
"<tr><td><a href=\"https://www.spss-tutorials.com/spss-two-way-anova-interaction-significant/\">SPSS recommendation for two-way ANOVA interaction</a></td></tr></table>"
]
},
{
"cell_type": "code",
- "execution_count": 43,
+ "execution_count": null,
"id": "c380d42c",
"metadata": {
"hidden": true
@@ -2414,121 +1107,24 @@
},
{
"cell_type": "code",
- "execution_count": 44,
+ "execution_count": null,
"id": "93ccdd87",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "0.03098093333325329"
- ]
- },
- "execution_count": 44,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"daily_water_model.f_pvalue"
]
},
{
"cell_type": "code",
- "execution_count": 45,
+ "execution_count": null,
"id": "d1392464",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
- "\n",
- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>coef</th>\n",
- " <th>std err</th>\n",
- " <th>t</th>\n",
- " <th>P>|t|</th>\n",
- " <th>Conf. Int. Low</th>\n",
- " <th>Conf. Int. Upp.</th>\n",
- " <th>pvalue-hs</th>\n",
- " <th>reject-hs</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>low-high</th>\n",
- " <td>-1.08</td>\n",
- " <td>0.58458</td>\n",
- " <td>-1.847481</td>\n",
- " <td>0.089466</td>\n",
- " <td>-2.35369</td>\n",
- " <td>0.19369</td>\n",
- " <td>0.170928</td>\n",
- " <td>False</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>med-high</th>\n",
- " <td>-1.78</td>\n",
- " <td>0.58458</td>\n",
- " <td>-3.044923</td>\n",
- " <td>0.010180</td>\n",
- " <td>-3.05369</td>\n",
- " <td>-0.50631</td>\n",
- " <td>0.030231</td>\n",
- " <td>True</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>med-low</th>\n",
- " <td>-0.70</td>\n",
- " <td>0.58458</td>\n",
- " <td>-1.197442</td>\n",
- " <td>0.254253</td>\n",
- " <td>-1.97369</td>\n",
- " <td>0.57369</td>\n",
- " <td>0.254253</td>\n",
- " <td>False</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " coef std err t P>|t| Conf. Int. Low Conf. Int. Upp. \\\n",
- "low-high -1.08 0.58458 -1.847481 0.089466 -2.35369 0.19369 \n",
- "med-high -1.78 0.58458 -3.044923 0.010180 -3.05369 -0.50631 \n",
- "med-low -0.70 0.58458 -1.197442 0.254253 -1.97369 0.57369 \n",
- "\n",
- " pvalue-hs reject-hs \n",
- "low-high 0.170928 False \n",
- "med-high 0.030231 True \n",
- "med-low 0.254253 False "
- ]
- },
- "execution_count": 45,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"daily_water_posthoc = daily_water_model.t_test_pairwise('sun')\n",
"daily_water_posthoc.result_frame"
@@ -2536,30 +1132,19 @@
},
{
"cell_type": "code",
- "execution_count": 46,
+ "execution_count": null,
"id": "8724bf04",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "0.001224005685747233"
- ]
- },
- "execution_count": 46,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"weekly_water_model.f_pvalue"
]
},
{
"cell_type": "code",
- "execution_count": 47,
+ "execution_count": null,
"id": "6dc3a0ad",
"metadata": {
"hidden": true,
@@ -2612,7 +1197,7 @@
},
{
"cell_type": "code",
- "execution_count": 48,
+ "execution_count": null,
"id": "7f395588",
"metadata": {
"hidden": true
@@ -2635,24 +1220,13 @@
},
{
"cell_type": "code",
- "execution_count": 49,
+ "execution_count": null,
"id": "8642f0e6",
"metadata": {
"hidden": true,
"tags": []
},
- "outputs": [
- {
- "data": {
- "image/png": "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",
- "text/plain": [
- "<Figure size 1330x410 with 2 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"statsmodels_material.illustration_multiple_comparisons(power, type1_error_rate)"
]
@@ -2700,23 +1274,12 @@
},
{
"cell_type": "code",
- "execution_count": 50,
+ "execution_count": null,
"id": "1b9e153d",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "7"
- ]
- },
- "execution_count": 50,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"from statsmodels.stats.multitest import multipletests\n",
"\n",
@@ -2738,150 +1301,12 @@
},
{
"cell_type": "code",
- "execution_count": 51,
+ "execution_count": null,
"id": "2fe99f26",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
- "\n",
- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>coef</th>\n",
- " <th>std err</th>\n",
- " <th>t</th>\n",
- " <th>P>|t|</th>\n",
- " <th>Conf. Int. Low</th>\n",
- " <th>Conf. Int. Upp.</th>\n",
- " <th>pvalue-hs</th>\n",
- " <th>reject-hs</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>low-high[water=daily]</th>\n",
- " <td>-1.08</td>\n",
- " <td>0.584580</td>\n",
- " <td>-1.847481</td>\n",
- " <td>0.089466</td>\n",
- " <td>-2.353690</td>\n",
- " <td>0.193690</td>\n",
- " <td>0.170928</td>\n",
- " <td>False</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>med-high[water=daily]</th>\n",
- " <td>-1.78</td>\n",
- " <td>0.584580</td>\n",
- " <td>-3.044923</td>\n",
- " <td>0.010180</td>\n",
- " <td>-3.053690</td>\n",
- " <td>-0.506310</td>\n",
- " <td>0.049876</td>\n",
- " <td>True</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>med-low[water=daily]</th>\n",
- " <td>-0.70</td>\n",
- " <td>0.584580</td>\n",
- " <td>-1.197442</td>\n",
- " <td>0.254253</td>\n",
- " <td>-1.973690</td>\n",
- " <td>0.573690</td>\n",
- " <td>0.254253</td>\n",
- " <td>False</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>low-high[water=weekly]</th>\n",
- " <td>-2.76</td>\n",
- " <td>0.555938</td>\n",
- " <td>-4.964586</td>\n",
- " <td>0.000328</td>\n",
- " <td>-3.971284</td>\n",
- " <td>-1.548716</td>\n",
- " <td>0.002279</td>\n",
- " <td>True</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>med-high[water=weekly]</th>\n",
- " <td>-1.48</td>\n",
- " <td>0.555938</td>\n",
- " <td>-2.662169</td>\n",
- " <td>0.020708</td>\n",
- " <td>-2.691284</td>\n",
- " <td>-0.268716</td>\n",
- " <td>0.080295</td>\n",
- " <td>False</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>med-low[water=weekly]</th>\n",
- " <td>1.28</td>\n",
- " <td>0.555938</td>\n",
- " <td>2.302416</td>\n",
- " <td>0.040022</td>\n",
- " <td>0.068716</td>\n",
- " <td>2.491284</td>\n",
- " <td>0.115325</td>\n",
- " <td>False</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>weekly-daily[sun=low]</th>\n",
- " <td>-2.66</td>\n",
- " <td>0.443847</td>\n",
- " <td>-5.993059</td>\n",
- " <td>0.000326</td>\n",
- " <td>-3.683513</td>\n",
- " <td>-1.636487</td>\n",
- " <td>0.002279</td>\n",
- " <td>True</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " coef std err t P>|t| Conf. Int. Low \\\n",
- "low-high[water=daily] -1.08 0.584580 -1.847481 0.089466 -2.353690 \n",
- "med-high[water=daily] -1.78 0.584580 -3.044923 0.010180 -3.053690 \n",
- "med-low[water=daily] -0.70 0.584580 -1.197442 0.254253 -1.973690 \n",
- "low-high[water=weekly] -2.76 0.555938 -4.964586 0.000328 -3.971284 \n",
- "med-high[water=weekly] -1.48 0.555938 -2.662169 0.020708 -2.691284 \n",
- "med-low[water=weekly] 1.28 0.555938 2.302416 0.040022 0.068716 \n",
- "weekly-daily[sun=low] -2.66 0.443847 -5.993059 0.000326 -3.683513 \n",
- "\n",
- " Conf. Int. Upp. pvalue-hs reject-hs \n",
- "low-high[water=daily] 0.193690 0.170928 False \n",
- "med-high[water=daily] -0.506310 0.049876 True \n",
- "med-low[water=daily] 0.573690 0.254253 False \n",
- "low-high[water=weekly] -1.548716 0.002279 True \n",
- "med-high[water=weekly] -0.268716 0.080295 False \n",
- "med-low[water=weekly] 2.491284 0.115325 False \n",
- "weekly-daily[sun=low] -1.636487 0.002279 True "
- ]
- },
- "execution_count": 51,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"all_comparisons['reject-hs'], all_comparisons['pvalue-hs'], _, _ = multipletests(all_comparisons['P>|t|'], alpha=significance_level)\n",
"all_comparisons"
@@ -2889,24 +1314,13 @@
},
{
"cell_type": "code",
- "execution_count": 52,
+ "execution_count": null,
"id": "25b21f28-f70d-466e-bbb6-8a6fc86b3696",
"metadata": {
"hidden": true,
"tags": []
},
- "outputs": [
- {
- "data": {
- "image/png": "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",
- "text/plain": [
- "<Figure size 640x480 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"statsmodels_material.confidence_intervals(all_comparisons)"
]
@@ -3012,711 +1426,10 @@
},
{
"cell_type": "code",
- "execution_count": 53,
+ "execution_count": null,
"id": "4e203a8d-a9d5-43e0-a437-918d7e036aed",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
- "\n",
- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>0</th>\n",
- " <th>1</th>\n",
- " <th>2</th>\n",
- " <th>3</th>\n",
- " <th>4</th>\n",
- " <th>5</th>\n",
- " <th>6</th>\n",
- " <th>7</th>\n",
- " <th>8</th>\n",
- " <th>9</th>\n",
- " <th>...</th>\n",
- " <th>740</th>\n",
- " <th>741</th>\n",
- " <th>742</th>\n",
- " <th>743</th>\n",
- " <th>744</th>\n",
- " <th>745</th>\n",
- " <th>746</th>\n",
- " <th>747</th>\n",
- " <th>748</th>\n",
- " <th>749</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>subject</th>\n",
- " <td>15</td>\n",
- " <td>15</td>\n",
- " <td>15</td>\n",
- " <td>15</td>\n",
- " <td>15</td>\n",
- " <td>15</td>\n",
- " <td>15</td>\n",
- " <td>15</td>\n",
- " <td>15</td>\n",
- " <td>15</td>\n",
- " <td>...</td>\n",
- " <td>13</td>\n",
- " <td>13</td>\n",
- " <td>13</td>\n",
- " <td>13</td>\n",
- " <td>13</td>\n",
- " <td>13</td>\n",
- " <td>13</td>\n",
- " <td>13</td>\n",
- " <td>13</td>\n",
- " <td>13</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>subject_name</th>\n",
- " <td>Alex</td>\n",
- " <td>Alex</td>\n",
- " <td>Alex</td>\n",
- " <td>Alex</td>\n",
- " <td>Alex</td>\n",
- " <td>Alex</td>\n",
- " <td>Alex</td>\n",
- " <td>Alex</td>\n",
- " <td>Alex</td>\n",
- " <td>Alex</td>\n",
- " <td>...</td>\n",
- " <td>Timo</td>\n",
- " <td>Timo</td>\n",
- " <td>Timo</td>\n",
- " <td>Timo</td>\n",
- " <td>Timo</td>\n",
- " <td>Timo</td>\n",
- " <td>Timo</td>\n",
- " <td>Timo</td>\n",
- " <td>Timo</td>\n",
- " <td>Timo</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>gender</th>\n",
- " <td>male</td>\n",
- " <td>male</td>\n",
- " <td>male</td>\n",
- " <td>male</td>\n",
- " <td>male</td>\n",
- " <td>male</td>\n",
- " <td>male</td>\n",
- " <td>male</td>\n",
- " <td>male</td>\n",
- " <td>male</td>\n",
- " <td>...</td>\n",
- " <td>male</td>\n",
- " <td>male</td>\n",
- " <td>male</td>\n",
- " <td>male</td>\n",
- " <td>male</td>\n",
- " <td>male</td>\n",
- " <td>male</td>\n",
- " <td>male</td>\n",
- " <td>male</td>\n",
- " <td>male</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>item</th>\n",
- " <td>stauge</td>\n",
- " <td>roke</td>\n",
- " <td>schuke</td>\n",
- " <td>quade</td>\n",
- " <td>jiete</td>\n",
- " <td>gaude</td>\n",
- " <td>flape</td>\n",
- " <td>quope</td>\n",
- " <td>priege</td>\n",
- " <td>mube</td>\n",
- " <td>...</td>\n",
- " <td>blote</td>\n",
- " <td>wiebe</td>\n",
- " <td>drute</td>\n",
- " <td>frade</td>\n",
- " <td>gage</td>\n",
- " <td>griede</td>\n",
- " <td>nauge</td>\n",
- " <td>schrieke</td>\n",
- " <td>klape</td>\n",
- " <td>gobe</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>item_singular</th>\n",
- " <td>staug</td>\n",
- " <td>rok</td>\n",
- " <td>schuk</td>\n",
- " <td>quad</td>\n",
- " <td>jiet</td>\n",
- " <td>gaud</td>\n",
- " <td>flap</td>\n",
- " <td>quop</td>\n",
- " <td>prieg</td>\n",
- " <td>mub</td>\n",
- " <td>...</td>\n",
- " <td>blot</td>\n",
- " <td>wieb</td>\n",
- " <td>drut</td>\n",
- " <td>frad</td>\n",
- " <td>gag</td>\n",
- " <td>gried</td>\n",
- " <td>naug</td>\n",
- " <td>schriek</td>\n",
- " <td>klap</td>\n",
- " <td>gob</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>voicing</th>\n",
- " <td>voiced</td>\n",
- " <td>voiceless</td>\n",
- " <td>voiceless</td>\n",
- " <td>voiced</td>\n",
- " <td>voiceless</td>\n",
- " <td>voiced</td>\n",
- " <td>voiceless</td>\n",
- " <td>voiceless</td>\n",
- " <td>voiced</td>\n",
- " <td>voiced</td>\n",
- " <td>...</td>\n",
- " <td>voiceless</td>\n",
- " <td>voiced</td>\n",
- " <td>voiceless</td>\n",
- " <td>voiced</td>\n",
- " <td>voiced</td>\n",
- " <td>voiced</td>\n",
- " <td>voiced</td>\n",
- " <td>voiceless</td>\n",
- " <td>voiceless</td>\n",
- " <td>voiced</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>item_pair</th>\n",
- " <td>24</td>\n",
- " <td>22</td>\n",
- " <td>23</td>\n",
- " <td>20</td>\n",
- " <td>16</td>\n",
- " <td>15</td>\n",
- " <td>13</td>\n",
- " <td>21</td>\n",
- " <td>18</td>\n",
- " <td>17</td>\n",
- " <td>...</td>\n",
- " <td>1</td>\n",
- " <td>12</td>\n",
- " <td>2</td>\n",
- " <td>3</td>\n",
- " <td>5</td>\n",
- " <td>7</td>\n",
- " <td>9</td>\n",
- " <td>11</td>\n",
- " <td>8</td>\n",
- " <td>6</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>order</th>\n",
- " <td>1+0i</td>\n",
- " <td>8+0i</td>\n",
- " <td>9+0i</td>\n",
- " <td>10+0i</td>\n",
- " <td>12+0i</td>\n",
- " <td>13+0i</td>\n",
- " <td>19+0i</td>\n",
- " <td>20+0i</td>\n",
- " <td>23+0i</td>\n",
- " <td>25+0i</td>\n",
- " <td>...</td>\n",
- " <td>114+0i</td>\n",
- " <td>122+0i</td>\n",
- " <td>124+0i</td>\n",
- " <td>127+0i</td>\n",
- " <td>129+0i</td>\n",
- " <td>130+0i</td>\n",
- " <td>132+0i</td>\n",
- " <td>135+0i</td>\n",
- " <td>141+0i</td>\n",
- " <td>144+0i</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>vowel</th>\n",
- " <td>au</td>\n",
- " <td>o</td>\n",
- " <td>u</td>\n",
- " <td>a</td>\n",
- " <td>i</td>\n",
- " <td>au</td>\n",
- " <td>a</td>\n",
- " <td>o</td>\n",
- " <td>i</td>\n",
- " <td>u</td>\n",
- " <td>...</td>\n",
- " <td>o</td>\n",
- " <td>i</td>\n",
- " <td>u</td>\n",
- " <td>a</td>\n",
- " <td>a</td>\n",
- " <td>i</td>\n",
- " <td>au</td>\n",
- " <td>i</td>\n",
- " <td>a</td>\n",
- " <td>o</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>stop</th>\n",
- " <td>g</td>\n",
- " <td>k</td>\n",
- " <td>k</td>\n",
- " <td>d</td>\n",
- " <td>t</td>\n",
- " <td>d</td>\n",
- " <td>p</td>\n",
- " <td>p</td>\n",
- " <td>g</td>\n",
- " <td>b</td>\n",
- " <td>...</td>\n",
- " <td>t</td>\n",
- " <td>b</td>\n",
- " <td>t</td>\n",
- " <td>d</td>\n",
- " <td>g</td>\n",
- " <td>d</td>\n",
- " <td>g</td>\n",
- " <td>k</td>\n",
- " <td>p</td>\n",
- " <td>b</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>place</th>\n",
- " <td>velar</td>\n",
- " <td>velar</td>\n",
- " <td>velar</td>\n",
- " <td>alveolar</td>\n",
- " <td>alveolar</td>\n",
- " <td>alveolar</td>\n",
- " <td>labial</td>\n",
- " <td>labial</td>\n",
- " <td>velar</td>\n",
- " <td>labial</td>\n",
- " <td>...</td>\n",
- " <td>alveolar</td>\n",
- " <td>labial</td>\n",
- " <td>alveolar</td>\n",
- " <td>alveolar</td>\n",
- " <td>velar</td>\n",
- " <td>alveolar</td>\n",
- " <td>velar</td>\n",
- " <td>velar</td>\n",
- " <td>labial</td>\n",
- " <td>labial</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>utterancelength</th>\n",
- " <td>1.784</td>\n",
- " <td>1.408</td>\n",
- " <td>1.448</td>\n",
- " <td>1.472</td>\n",
- " <td>1.704</td>\n",
- " <td>1.528</td>\n",
- " <td>1.6</td>\n",
- " <td>1.608</td>\n",
- " <td>1.512</td>\n",
- " <td>1.568</td>\n",
- " <td>...</td>\n",
- " <td>1.472</td>\n",
- " <td>1.472</td>\n",
- " <td>1.512</td>\n",
- " <td>1.512</td>\n",
- " <td>1.616</td>\n",
- " <td>1.456</td>\n",
- " <td>1.544</td>\n",
- " <td>1.568</td>\n",
- " <td>1.728</td>\n",
- " <td>1.672</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>accent_type</th>\n",
- " <td>nuclear</td>\n",
- " <td>nuclear</td>\n",
- " <td>prenuclear</td>\n",
- " <td>nuclear</td>\n",
- " <td>nuclear</td>\n",
- " <td>nuclear</td>\n",
- " <td>nuclear</td>\n",
- " <td>prenuclear</td>\n",
- " <td>prenuclear</td>\n",
- " <td>prenuclear</td>\n",
- " <td>...</td>\n",
- " <td>prenuclear</td>\n",
- " <td>prenuclear</td>\n",
- " <td>prenuclear</td>\n",
- " <td>prenuclear</td>\n",
- " <td>prenuclear</td>\n",
- " <td>prenuclear</td>\n",
- " <td>prenuclear</td>\n",
- " <td>prenuclear</td>\n",
- " <td>prenuclear</td>\n",
- " <td>prenuclear</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>prosodic_boundary</th>\n",
- " <td>yes</td>\n",
- " <td>yes</td>\n",
- " <td>no</td>\n",
- " <td>yes</td>\n",
- " <td>yes</td>\n",
- " <td>yes</td>\n",
- " <td>yes</td>\n",
- " <td>no</td>\n",
- " <td>no</td>\n",
- " <td>no</td>\n",
- " <td>...</td>\n",
- " <td>no</td>\n",
- " <td>no</td>\n",
- " <td>no</td>\n",
- " <td>no</td>\n",
- " <td>no</td>\n",
- " <td>no</td>\n",
- " <td>no</td>\n",
- " <td>no</td>\n",
- " <td>no</td>\n",
- " <td>no</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>norming_voiceless_count</th>\n",
- " <td>0</td>\n",
- " <td>1</td>\n",
- " <td>1</td>\n",
- " <td>1</td>\n",
- " <td>2</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>1</td>\n",
- " <td>0</td>\n",
- " <td>1</td>\n",
- " <td>...</td>\n",
- " <td>2</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>1</td>\n",
- " <td>1</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>1</td>\n",
- " <td>1</td>\n",
- " <td>1</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>norming_schwa_total</th>\n",
- " <td>3</td>\n",
- " <td>2</td>\n",
- " <td>3</td>\n",
- " <td>3</td>\n",
- " <td>3</td>\n",
- " <td>3</td>\n",
- " <td>5</td>\n",
- " <td>2</td>\n",
- " <td>5</td>\n",
- " <td>4</td>\n",
- " <td>...</td>\n",
- " <td>2</td>\n",
- " <td>4</td>\n",
- " <td>2</td>\n",
- " <td>3</td>\n",
- " <td>4</td>\n",
- " <td>5</td>\n",
- " <td>4</td>\n",
- " <td>3</td>\n",
- " <td>2</td>\n",
- " <td>3</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>norming_schwa_pure</th>\n",
- " <td>3</td>\n",
- " <td>2</td>\n",
- " <td>3</td>\n",
- " <td>3</td>\n",
- " <td>3</td>\n",
- " <td>3</td>\n",
- " <td>5</td>\n",
- " <td>2</td>\n",
- " <td>5</td>\n",
- " <td>4</td>\n",
- " <td>...</td>\n",
- " <td>2</td>\n",
- " <td>4</td>\n",
- " <td>2</td>\n",
- " <td>3</td>\n",
- " <td>4</td>\n",
- " <td>5</td>\n",
- " <td>4</td>\n",
- " <td>3</td>\n",
- " <td>2</td>\n",
- " <td>3</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>usable</th>\n",
- " <td>usable</td>\n",
- " <td>usable</td>\n",
- " <td>usable</td>\n",
- " <td>not_usable</td>\n",
- " <td>usable</td>\n",
- " <td>usable</td>\n",
- " <td>usable</td>\n",
- " <td>usable</td>\n",
- " <td>not_usable</td>\n",
- " <td>usable</td>\n",
- " <td>...</td>\n",
- " <td>not_usable</td>\n",
- " <td>usable</td>\n",
- " <td>usable</td>\n",
- " <td>usable</td>\n",
- " <td>usable</td>\n",
- " <td>usable</td>\n",
- " <td>usable</td>\n",
- " <td>usable</td>\n",
- " <td>usable</td>\n",
- " <td>not_usable</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>item_vowel_dur</th>\n",
- " <td>169.76</td>\n",
- " <td>155.85</td>\n",
- " <td>113.14</td>\n",
- " <td>190.37</td>\n",
- " <td>140.71</td>\n",
- " <td>213.2</td>\n",
- " <td>109.48</td>\n",
- " <td>146.96</td>\n",
- " <td>142.02</td>\n",
- " <td>190.24</td>\n",
- " <td>...</td>\n",
- " <td>153.82</td>\n",
- " <td>115.02</td>\n",
- " <td>111.7</td>\n",
- " <td>198.19</td>\n",
- " <td>220.77</td>\n",
- " <td>116.35</td>\n",
- " <td>206.35</td>\n",
- " <td>124.84</td>\n",
- " <td>152.21</td>\n",
- " <td>153.2</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>vowel_dur</th>\n",
- " <td>175.348118</td>\n",
- " <td>142.93876</td>\n",
- " <td>103.278765</td>\n",
- " <td>198.189655</td>\n",
- " <td>134.959224</td>\n",
- " <td>200.714031</td>\n",
- " <td>170.130933</td>\n",
- " <td>146.76317</td>\n",
- " <td>151.648318</td>\n",
- " <td>107.40031</td>\n",
- " <td>...</td>\n",
- " <td>184.023194</td>\n",
- " <td>113.494857</td>\n",
- " <td>110.395575</td>\n",
- " <td>210.267881</td>\n",
- " <td>254.574444</td>\n",
- " <td>136.924026</td>\n",
- " <td>225.882315</td>\n",
- " <td>146.512138</td>\n",
- " <td>228.258654</td>\n",
- " <td>175.189705</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>comment</th>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>[kw] nicht nativer kluster</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>VQ e; deaccented?</td>\n",
- " <td>NaN</td>\n",
- " <td>...</td>\n",
- " <td>sounds english ou</td>\n",
- " <td>NO RELEASE</td>\n",
- " <td>NaN</td>\n",
- " <td>flapped R</td>\n",
- " <td>NaN</td>\n",
- " <td>flapped R</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>NaN</td>\n",
- " <td>sounds english ou</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "<p>21 rows × 750 columns</p>\n",
- "</div>"
- ],
- "text/plain": [
- " 0 1 2 \\\n",
- "subject 15 15 15 \n",
- "subject_name Alex Alex Alex \n",
- "gender male male male \n",
- "item stauge roke schuke \n",
- "item_singular staug rok schuk \n",
- "voicing voiced voiceless voiceless \n",
- "item_pair 24 22 23 \n",
- "order 1+0i 8+0i 9+0i \n",
- "vowel au o u \n",
- "stop g k k \n",
- "place velar velar velar \n",
- "utterancelength 1.784 1.408 1.448 \n",
- "accent_type nuclear nuclear prenuclear \n",
- "prosodic_boundary yes yes no \n",
- "norming_voiceless_count 0 1 1 \n",
- "norming_schwa_total 3 2 3 \n",
- "norming_schwa_pure 3 2 3 \n",
- "usable usable usable usable \n",
- "item_vowel_dur 169.76 155.85 113.14 \n",
- "vowel_dur 175.348118 142.93876 103.278765 \n",
- "comment NaN NaN NaN \n",
- "\n",
- " 3 4 5 \\\n",
- "subject 15 15 15 \n",
- "subject_name Alex Alex Alex \n",
- "gender male male male \n",
- "item quade jiete gaude \n",
- "item_singular quad jiet gaud \n",
- "voicing voiced voiceless voiced \n",
- "item_pair 20 16 15 \n",
- "order 10+0i 12+0i 13+0i \n",
- "vowel a i au \n",
- "stop d t d \n",
- "place alveolar alveolar alveolar \n",
- "utterancelength 1.472 1.704 1.528 \n",
- "accent_type nuclear nuclear nuclear \n",
- "prosodic_boundary yes yes yes \n",
- "norming_voiceless_count 1 2 0 \n",
- "norming_schwa_total 3 3 3 \n",
- "norming_schwa_pure 3 3 3 \n",
- "usable not_usable usable usable \n",
- "item_vowel_dur 190.37 140.71 213.2 \n",
- "vowel_dur 198.189655 134.959224 200.714031 \n",
- "comment [kw] nicht nativer kluster NaN NaN \n",
- "\n",
- " 6 7 8 \\\n",
- "subject 15 15 15 \n",
- "subject_name Alex Alex Alex \n",
- "gender male male male \n",
- "item flape quope priege \n",
- "item_singular flap quop prieg \n",
- "voicing voiceless voiceless voiced \n",
- "item_pair 13 21 18 \n",
- "order 19+0i 20+0i 23+0i \n",
- "vowel a o i \n",
- "stop p p g \n",
- "place labial labial velar \n",
- "utterancelength 1.6 1.608 1.512 \n",
- "accent_type nuclear prenuclear prenuclear \n",
- "prosodic_boundary yes no no \n",
- "norming_voiceless_count 0 1 0 \n",
- "norming_schwa_total 5 2 5 \n",
- "norming_schwa_pure 5 2 5 \n",
- "usable usable usable not_usable \n",
- "item_vowel_dur 109.48 146.96 142.02 \n",
- "vowel_dur 170.130933 146.76317 151.648318 \n",
- "comment NaN NaN VQ e; deaccented? \n",
- "\n",
- " 9 ... 740 741 \\\n",
- "subject 15 ... 13 13 \n",
- "subject_name Alex ... Timo Timo \n",
- "gender male ... male male \n",
- "item mube ... blote wiebe \n",
- "item_singular mub ... blot wieb \n",
- "voicing voiced ... voiceless voiced \n",
- "item_pair 17 ... 1 12 \n",
- "order 25+0i ... 114+0i 122+0i \n",
- "vowel u ... o i \n",
- "stop b ... t b \n",
- "place labial ... alveolar labial \n",
- "utterancelength 1.568 ... 1.472 1.472 \n",
- "accent_type prenuclear ... prenuclear prenuclear \n",
- "prosodic_boundary no ... no no \n",
- "norming_voiceless_count 1 ... 2 0 \n",
- "norming_schwa_total 4 ... 2 4 \n",
- "norming_schwa_pure 4 ... 2 4 \n",
- "usable usable ... not_usable usable \n",
- "item_vowel_dur 190.24 ... 153.82 115.02 \n",
- "vowel_dur 107.40031 ... 184.023194 113.494857 \n",
- "comment NaN ... sounds english ou NO RELEASE \n",
- "\n",
- " 742 743 744 745 \\\n",
- "subject 13 13 13 13 \n",
- "subject_name Timo Timo Timo Timo \n",
- "gender male male male male \n",
- "item drute frade gage griede \n",
- "item_singular drut frad gag gried \n",
- "voicing voiceless voiced voiced voiced \n",
- "item_pair 2 3 5 7 \n",
- "order 124+0i 127+0i 129+0i 130+0i \n",
- "vowel u a a i \n",
- "stop t d g d \n",
- "place alveolar alveolar velar alveolar \n",
- "utterancelength 1.512 1.512 1.616 1.456 \n",
- "accent_type prenuclear prenuclear prenuclear prenuclear \n",
- "prosodic_boundary no no no no \n",
- "norming_voiceless_count 0 1 1 0 \n",
- "norming_schwa_total 2 3 4 5 \n",
- "norming_schwa_pure 2 3 4 5 \n",
- "usable usable usable usable usable \n",
- "item_vowel_dur 111.7 198.19 220.77 116.35 \n",
- "vowel_dur 110.395575 210.267881 254.574444 136.924026 \n",
- "comment NaN flapped R NaN flapped R \n",
- "\n",
- " 746 747 748 749 \n",
- "subject 13 13 13 13 \n",
- "subject_name Timo Timo Timo Timo \n",
- "gender male male male male \n",
- "item nauge schrieke klape gobe \n",
- "item_singular naug schriek klap gob \n",
- "voicing voiced voiceless voiceless voiced \n",
- "item_pair 9 11 8 6 \n",
- "order 132+0i 135+0i 141+0i 144+0i \n",
- "vowel au i a o \n",
- "stop g k p b \n",
- "place velar velar labial labial \n",
- "utterancelength 1.544 1.568 1.728 1.672 \n",
- "accent_type prenuclear prenuclear prenuclear prenuclear \n",
- "prosodic_boundary no no no no \n",
- "norming_voiceless_count 0 1 1 1 \n",
- "norming_schwa_total 4 3 2 3 \n",
- "norming_schwa_pure 4 3 2 3 \n",
- "usable usable usable usable not_usable \n",
- "item_vowel_dur 206.35 124.84 152.21 153.2 \n",
- "vowel_dur 225.882315 146.512138 228.258654 175.189705 \n",
- "comment NaN NaN NaN sounds english ou \n",
- "\n",
- "[21 rows x 750 columns]"
- ]
- },
- "execution_count": 53,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"rt_data = pd.read_csv('https://osf.io/download/asq8n/')\n",
"rt_data.T"
@@ -3724,126 +1437,10 @@
},
{
"cell_type": "code",
- "execution_count": 54,
+ "execution_count": null,
"id": "399ab879-04f4-440d-85c3-c3e6d773b33a",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<table class=\"simpletable\">\n",
- "<tr>\n",
- " <td>Model:</td> <td>MixedLM</td> <td>Dependent Variable:</td> <td>utterancelength</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <td>No. Observations:</td> <td>750</td> <td>Method:</td> <td>REML</td> \n",
- "</tr>\n",
- "<tr>\n",
- " <td>No. Groups:</td> <td>16</td> <td>Scale:</td> <td>0.0141</td> \n",
- "</tr>\n",
- "<tr>\n",
- " <td>Min. group size:</td> <td>44</td> <td>Log-Likelihood:</td> <td>482.5110</td> \n",
- "</tr>\n",
- "<tr>\n",
- " <td>Max. group size:</td> <td>48</td> <td>Converged:</td> <td>Yes</td> \n",
- "</tr>\n",
- "<tr>\n",
- " <td>Mean group size:</td> <td>46.9</td> <td></td> <td></td> \n",
- "</tr>\n",
- "</table>\n",
- "<table class=\"simpletable\">\n",
- "<tr>\n",
- " <td></td> <th>Coef.</th> <th>Std.Err.</th> <th>z</th> <th>P>|z|</th> <th>[0.025</th> <th>0.975]</th>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Intercept</th> <td>1.576</td> <td>0.061</td> <td>25.905</td> <td>0.000</td> <td>1.457</td> <td>1.695</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>place[T.labial]</th> <td>0.005</td> <td>0.015</td> <td>0.363</td> <td>0.716</td> <td>-0.023</td> <td>0.034</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>place[T.velar]</th> <td>0.029</td> <td>0.014</td> <td>1.996</td> <td>0.046</td> <td>0.001</td> <td>0.057</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>gender[T.male]</th> <td>-0.072</td> <td>0.092</td> <td>-0.783</td> <td>0.434</td> <td>-0.252</td> <td>0.108</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>place[T.labial]:gender[T.male]</th> <td>-0.006</td> <td>0.022</td> <td>-0.292</td> <td>0.770</td> <td>-0.050</td> <td>0.037</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>place[T.velar]:gender[T.male]</th> <td>-0.016</td> <td>0.022</td> <td>-0.735</td> <td>0.463</td> <td>-0.058</td> <td>0.026</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>subject Var</th> <td>0.032</td> <td>0.105</td> <td></td> <td></td> <td></td> <td></td> \n",
- "</tr>\n",
- "</table><br/>\n"
- ],
- "text/latex": [
- "\\begin{table}\n",
- "\\caption{Mixed Linear Model Regression Results}\n",
- "\\label{}\n",
- "\\begin{center}\n",
- "\\begin{tabular}{llll}\n",
- "\\hline\n",
- "Model: & MixedLM & Dependent Variable: & utterancelength \\\\\n",
- "No. Observations: & 750 & Method: & REML \\\\\n",
- "No. Groups: & 16 & Scale: & 0.0141 \\\\\n",
- "Min. group size: & 44 & Log-Likelihood: & 482.5110 \\\\\n",
- "Max. group size: & 48 & Converged: & Yes \\\\\n",
- "Mean group size: & 46.9 & & \\\\\n",
- "\\hline\n",
- "\\end{tabular}\n",
- "\\end{center}\n",
- "\n",
- "\\begin{center}\n",
- "\\begin{tabular}{lrrrrrr}\n",
- "\\hline\n",
- " & Coef. & Std.Err. & z & P$> |$z$|$ & [0.025 & 0.975] \\\\\n",
- "\\hline\n",
- "Intercept & 1.576 & 0.061 & 25.905 & 0.000 & 1.457 & 1.695 \\\\\n",
- "place[T.labial] & 0.005 & 0.015 & 0.363 & 0.716 & -0.023 & 0.034 \\\\\n",
- "place[T.velar] & 0.029 & 0.014 & 1.996 & 0.046 & 0.001 & 0.057 \\\\\n",
- "gender[T.male] & -0.072 & 0.092 & -0.783 & 0.434 & -0.252 & 0.108 \\\\\n",
- "place[T.labial]:gender[T.male] & -0.006 & 0.022 & -0.292 & 0.770 & -0.050 & 0.037 \\\\\n",
- "place[T.velar]:gender[T.male] & -0.016 & 0.022 & -0.735 & 0.463 & -0.058 & 0.026 \\\\\n",
- "subject Var & 0.032 & 0.105 & & & & \\\\\n",
- "\\hline\n",
- "\\end{tabular}\n",
- "\\end{center}\n",
- "\\end{table}\n",
- "\\bigskip\n"
- ],
- "text/plain": [
- "<class 'statsmodels.iolib.summary2.Summary'>\n",
- "\"\"\"\n",
- " Mixed Linear Model Regression Results\n",
- "=========================================================================\n",
- "Model: MixedLM Dependent Variable: utterancelength\n",
- "No. Observations: 750 Method: REML \n",
- "No. Groups: 16 Scale: 0.0141 \n",
- "Min. group size: 44 Log-Likelihood: 482.5110 \n",
- "Max. group size: 48 Converged: Yes \n",
- "Mean group size: 46.9 \n",
- "-------------------------------------------------------------------------\n",
- " Coef. Std.Err. z P>|z| [0.025 0.975]\n",
- "-------------------------------------------------------------------------\n",
- "Intercept 1.576 0.061 25.905 0.000 1.457 1.695\n",
- "place[T.labial] 0.005 0.015 0.363 0.716 -0.023 0.034\n",
- "place[T.velar] 0.029 0.014 1.996 0.046 0.001 0.057\n",
- "gender[T.male] -0.072 0.092 -0.783 0.434 -0.252 0.108\n",
- "place[T.labial]:gender[T.male] -0.006 0.022 -0.292 0.770 -0.050 0.037\n",
- "place[T.velar]:gender[T.male] -0.016 0.022 -0.735 0.463 -0.058 0.026\n",
- "subject Var 0.032 0.105 \n",
- "=========================================================================\n",
- "\n",
- "\"\"\""
- ]
- },
- "execution_count": 54,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"model = smf.mixedlm('utterancelength ~ place * gender', rt_data, groups='subject').fit()\n",
"model.summary()"
@@ -3851,139 +1448,10 @@
},
{
"cell_type": "code",
- "execution_count": 55,
+ "execution_count": null,
"id": "efbc0d33-5d7f-4942-817f-47faf5c5ca50",
"metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "/home/flaurent/Boxes/jammy-1/Projects/scientific_python/lib/python3.10/site-packages/statsmodels/regression/mixed_linear_model.py:2238: ConvergenceWarning: The MLE may be on the boundary of the parameter space.\n",
- " warnings.warn(msg, ConvergenceWarning)\n"
- ]
- },
- {
- "data": {
- "text/html": [
- "<table class=\"simpletable\">\n",
- "<tr>\n",
- " <td>Model:</td> <td>MixedLM</td> <td>Dependent Variable:</td> <td>utterancelength</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <td>No. Observations:</td> <td>750</td> <td>Method:</td> <td>REML</td> \n",
- "</tr>\n",
- "<tr>\n",
- " <td>No. Groups:</td> <td>16</td> <td>Scale:</td> <td>0.0105</td> \n",
- "</tr>\n",
- "<tr>\n",
- " <td>Min. group size:</td> <td>44</td> <td>Log-Likelihood:</td> <td>482.5110</td> \n",
- "</tr>\n",
- "<tr>\n",
- " <td>Max. group size:</td> <td>48</td> <td>Converged:</td> <td>Yes</td> \n",
- "</tr>\n",
- "<tr>\n",
- " <td>Mean group size:</td> <td>46.9</td> <td></td> <td></td> \n",
- "</tr>\n",
- "</table>\n",
- "<table class=\"simpletable\">\n",
- "<tr>\n",
- " <td></td> <th>Coef.</th> <th>Std.Err.</th> <th>z</th> <th>P>|z|</th> <th>[0.025</th> <th>0.975]</th>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Intercept</th> <td>1.576</td> <td>0.061</td> <td>25.902</td> <td>0.000</td> <td>1.457</td> <td>1.695</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>place[T.labial]</th> <td>0.005</td> <td>0.015</td> <td>0.363</td> <td>0.716</td> <td>-0.023</td> <td>0.034</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>place[T.velar]</th> <td>0.029</td> <td>0.014</td> <td>1.996</td> <td>0.046</td> <td>0.001</td> <td>0.057</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>gender[T.male]</th> <td>-0.072</td> <td>0.092</td> <td>-0.783</td> <td>0.434</td> <td>-0.252</td> <td>0.108</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>place[T.labial]:gender[T.male]</th> <td>-0.006</td> <td>0.022</td> <td>-0.292</td> <td>0.770</td> <td>-0.050</td> <td>0.037</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>place[T.velar]:gender[T.male]</th> <td>-0.016</td> <td>0.022</td> <td>-0.735</td> <td>0.463</td> <td>-0.058</td> <td>0.026</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>subject Var</th> <td>0.032</td> <td></td> <td></td> <td></td> <td></td> <td></td> \n",
- "</tr>\n",
- "<tr>\n",
- " <th>item Var</th> <td>0.004</td> <td></td> <td></td> <td></td> <td></td> <td></td> \n",
- "</tr>\n",
- "</table><br/>\n"
- ],
- "text/latex": [
- "\\begin{table}\n",
- "\\caption{Mixed Linear Model Regression Results}\n",
- "\\label{}\n",
- "\\begin{center}\n",
- "\\begin{tabular}{llll}\n",
- "\\hline\n",
- "Model: & MixedLM & Dependent Variable: & utterancelength \\\\\n",
- "No. Observations: & 750 & Method: & REML \\\\\n",
- "No. Groups: & 16 & Scale: & 0.0105 \\\\\n",
- "Min. group size: & 44 & Log-Likelihood: & 482.5110 \\\\\n",
- "Max. group size: & 48 & Converged: & Yes \\\\\n",
- "Mean group size: & 46.9 & & \\\\\n",
- "\\hline\n",
- "\\end{tabular}\n",
- "\\end{center}\n",
- "\n",
- "\\begin{center}\n",
- "\\begin{tabular}{lrrrrrr}\n",
- "\\hline\n",
- " & Coef. & Std.Err. & z & P$> |$z$|$ & [0.025 & 0.975] \\\\\n",
- "\\hline\n",
- "Intercept & 1.576 & 0.061 & 25.902 & 0.000 & 1.457 & 1.695 \\\\\n",
- "place[T.labial] & 0.005 & 0.015 & 0.363 & 0.716 & -0.023 & 0.034 \\\\\n",
- "place[T.velar] & 0.029 & 0.014 & 1.996 & 0.046 & 0.001 & 0.057 \\\\\n",
- "gender[T.male] & -0.072 & 0.092 & -0.783 & 0.434 & -0.252 & 0.108 \\\\\n",
- "place[T.labial]:gender[T.male] & -0.006 & 0.022 & -0.292 & 0.770 & -0.050 & 0.037 \\\\\n",
- "place[T.velar]:gender[T.male] & -0.016 & 0.022 & -0.735 & 0.463 & -0.058 & 0.026 \\\\\n",
- "subject Var & 0.032 & & & & & \\\\\n",
- "item Var & 0.004 & & & & & \\\\\n",
- "\\hline\n",
- "\\end{tabular}\n",
- "\\end{center}\n",
- "\\end{table}\n",
- "\\bigskip\n"
- ],
- "text/plain": [
- "<class 'statsmodels.iolib.summary2.Summary'>\n",
- "\"\"\"\n",
- " Mixed Linear Model Regression Results\n",
- "=========================================================================\n",
- "Model: MixedLM Dependent Variable: utterancelength\n",
- "No. Observations: 750 Method: REML \n",
- "No. Groups: 16 Scale: 0.0105 \n",
- "Min. group size: 44 Log-Likelihood: 482.5110 \n",
- "Max. group size: 48 Converged: Yes \n",
- "Mean group size: 46.9 \n",
- "-------------------------------------------------------------------------\n",
- " Coef. Std.Err. z P>|z| [0.025 0.975]\n",
- "-------------------------------------------------------------------------\n",
- "Intercept 1.576 0.061 25.902 0.000 1.457 1.695\n",
- "place[T.labial] 0.005 0.015 0.363 0.716 -0.023 0.034\n",
- "place[T.velar] 0.029 0.014 1.996 0.046 0.001 0.057\n",
- "gender[T.male] -0.072 0.092 -0.783 0.434 -0.252 0.108\n",
- "place[T.labial]:gender[T.male] -0.006 0.022 -0.292 0.770 -0.050 0.037\n",
- "place[T.velar]:gender[T.male] -0.016 0.022 -0.735 0.463 -0.058 0.026\n",
- "subject Var 0.032 \n",
- "item Var 0.004 \n",
- "=========================================================================\n",
- "\n",
- "\"\"\""
- ]
- },
- "execution_count": 55,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"model = smf.mixedlm('utterancelength ~ place * gender', rt_data, groups='subject', vc_formula={'item': '0 + item'}, re_formula='1').fit()\n",
"model.summary()"
@@ -3991,7 +1459,7 @@
},
{
"cell_type": "code",
- "execution_count": 56,
+ "execution_count": null,
"id": "31ea99ae-96a7-45cd-98fe-1ad67b131978",
"metadata": {},
"outputs": [],
@@ -4011,22 +1479,10 @@
},
{
"cell_type": "code",
- "execution_count": 57,
+ "execution_count": null,
"id": "4fac0c5c-93d6-4221-9be4-c601583ba295",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<class 'statsmodels.stats.contrast.ContrastResults'>\n",
- "<Wald test (chi2): statistic=0.6127919202597879, p-value=0.4337385352487245, df_denom=1>"
- ]
- },
- "execution_count": 57,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"model.wald_test('gender[T.male] = 0', scalar=True, use_f=False)"
]
@@ -4045,22 +1501,10 @@
},
{
"cell_type": "code",
- "execution_count": 58,
+ "execution_count": null,
"id": "b122d238-a7a3-4203-86c5-db96eb229fb4",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<class 'statsmodels.stats.contrast.ContrastResults'>\n",
- "<Wald test (chi2): statistic=4.750900500325523, p-value=0.09297261884853324, df_denom=2>"
- ]
- },
- "execution_count": 58,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"model.wald_test('place[T.velar] = place[T.labial] = 0', scalar=True, use_f=False)"
]
@@ -4075,22 +1519,10 @@
},
{
"cell_type": "code",
- "execution_count": 59,
+ "execution_count": null,
"id": "4afad7ba-e03b-47cf-8d60-4f2cd9dacfe6",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<class 'statsmodels.stats.contrast.ContrastResults'>\n",
- "<Wald test (chi2): statistic=0.557156630905794, p-value=0.7568589916741078, df_denom=2>"
- ]
- },
- "execution_count": 59,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"model.wald_test('place[T.labial]:gender[T.male] = place[T.velar]:gender[T.male] = 0', scalar=True, use_f=False)"
]
@@ -4105,22 +1537,10 @@
},
{
"cell_type": "code",
- "execution_count": 60,
+ "execution_count": null,
"id": "af9058d6-6110-49e3-a3af-8af9d4c7cdcd",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "<class 'statsmodels.stats.contrast.ContrastResults'>\n",
- "<Wald test (chi2): statistic=2.850158520213407, p-value=0.09136492767813915, df_denom=1>"
- ]
- },
- "execution_count": 60,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"model.wald_test('place[T.velar] = place[T.labial]', scalar=True, use_f=False)"
]
@@ -4160,212 +1580,12 @@
},
{
"cell_type": "code",
- "execution_count": 61,
+ "execution_count": null,
"id": "b350dec1",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
- "\n",
- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>Response</th>\n",
- " <th>MARCO</th>\n",
- " <th>TLR8</th>\n",
- " <th>PSMB5</th>\n",
- " <th>HAVCR2</th>\n",
- " <th>LILRA2</th>\n",
- " <th>MS4A1</th>\n",
- " <th>ITGAE</th>\n",
- " <th>FCGRT</th>\n",
- " <th>NFKB1</th>\n",
- " <th>...</th>\n",
- " <th>IL13RA1</th>\n",
- " <th>TMEM173</th>\n",
- " <th>TRAF6</th>\n",
- " <th>IKBKB</th>\n",
- " <th>IL12RB1</th>\n",
- " <th>B2M</th>\n",
- " <th>LEF1</th>\n",
- " <th>PRDM1</th>\n",
- " <th>HLA.C</th>\n",
- " <th>CCL20</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>0</th>\n",
- " <td>0.348895</td>\n",
- " <td>6.628041</td>\n",
- " <td>5.451410</td>\n",
- " <td>12.765834</td>\n",
- " <td>14.004527</td>\n",
- " <td>3.672567</td>\n",
- " <td>13.609538</td>\n",
- " <td>-1.291865</td>\n",
- " <td>7.737586</td>\n",
- " <td>14.977723</td>\n",
- " <td>...</td>\n",
- " <td>3.500934</td>\n",
- " <td>7.429266</td>\n",
- " <td>11.254056</td>\n",
- " <td>18.621722</td>\n",
- " <td>12.067877</td>\n",
- " <td>6.713297</td>\n",
- " <td>5.373240</td>\n",
- " <td>4.179533</td>\n",
- " <td>11.793683</td>\n",
- " <td>17.192958</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1</th>\n",
- " <td>0.062775</td>\n",
- " <td>7.434965</td>\n",
- " <td>15.983178</td>\n",
- " <td>0.293150</td>\n",
- " <td>5.041096</td>\n",
- " <td>14.223888</td>\n",
- " <td>15.333888</td>\n",
- " <td>0.732892</td>\n",
- " <td>9.179190</td>\n",
- " <td>14.577946</td>\n",
- " <td>...</td>\n",
- " <td>17.132192</td>\n",
- " <td>6.349028</td>\n",
- " <td>7.435596</td>\n",
- " <td>17.324485</td>\n",
- " <td>17.576044</td>\n",
- " <td>6.477195</td>\n",
- " <td>3.490226</td>\n",
- " <td>13.702533</td>\n",
- " <td>5.336035</td>\n",
- " <td>13.813157</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2</th>\n",
- " <td>-0.203249</td>\n",
- " <td>6.600255</td>\n",
- " <td>3.098568</td>\n",
- " <td>4.850231</td>\n",
- " <td>1.087381</td>\n",
- " <td>2.526257</td>\n",
- " <td>6.331897</td>\n",
- " <td>2.443893</td>\n",
- " <td>7.195147</td>\n",
- " <td>7.718794</td>\n",
- " <td>...</td>\n",
- " <td>12.630984</td>\n",
- " <td>6.335089</td>\n",
- " <td>13.074254</td>\n",
- " <td>9.196277</td>\n",
- " <td>11.556602</td>\n",
- " <td>5.124115</td>\n",
- " <td>7.739951</td>\n",
- " <td>11.442156</td>\n",
- " <td>11.219388</td>\n",
- " <td>-0.290347</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>3</th>\n",
- " <td>1.609151</td>\n",
- " <td>8.760969</td>\n",
- " <td>12.544481</td>\n",
- " <td>16.560668</td>\n",
- " <td>14.646189</td>\n",
- " <td>8.661329</td>\n",
- " <td>10.293389</td>\n",
- " <td>-3.245664</td>\n",
- " <td>6.490695</td>\n",
- " <td>-1.381632</td>\n",
- " <td>...</td>\n",
- " <td>8.081113</td>\n",
- " <td>6.423302</td>\n",
- " <td>-3.322394</td>\n",
- " <td>4.470948</td>\n",
- " <td>18.348316</td>\n",
- " <td>13.384904</td>\n",
- " <td>15.261042</td>\n",
- " <td>17.193111</td>\n",
- " <td>1.124725</td>\n",
- " <td>-1.044398</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>4</th>\n",
- " <td>0.508908</td>\n",
- " <td>7.379778</td>\n",
- " <td>10.360622</td>\n",
- " <td>11.389056</td>\n",
- " <td>6.076842</td>\n",
- " <td>7.255451</td>\n",
- " <td>17.260926</td>\n",
- " <td>14.943879</td>\n",
- " <td>0.158889</td>\n",
- " <td>7.968893</td>\n",
- " <td>...</td>\n",
- " <td>4.980194</td>\n",
- " <td>7.365077</td>\n",
- " <td>4.547918</td>\n",
- " <td>3.884870</td>\n",
- " <td>15.489645</td>\n",
- " <td>-0.660620</td>\n",
- " <td>5.110488</td>\n",
- " <td>18.508337</td>\n",
- " <td>7.551574</td>\n",
- " <td>8.716116</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "<p>5 rows × 31 columns</p>\n",
- "</div>"
- ],
- "text/plain": [
- " Response MARCO TLR8 PSMB5 HAVCR2 LILRA2 MS4A1 \\\n",
- "0 0.348895 6.628041 5.451410 12.765834 14.004527 3.672567 13.609538 \n",
- "1 0.062775 7.434965 15.983178 0.293150 5.041096 14.223888 15.333888 \n",
- "2 -0.203249 6.600255 3.098568 4.850231 1.087381 2.526257 6.331897 \n",
- "3 1.609151 8.760969 12.544481 16.560668 14.646189 8.661329 10.293389 \n",
- "4 0.508908 7.379778 10.360622 11.389056 6.076842 7.255451 17.260926 \n",
- "\n",
- " ITGAE FCGRT NFKB1 ... IL13RA1 TMEM173 TRAF6 \\\n",
- "0 -1.291865 7.737586 14.977723 ... 3.500934 7.429266 11.254056 \n",
- "1 0.732892 9.179190 14.577946 ... 17.132192 6.349028 7.435596 \n",
- "2 2.443893 7.195147 7.718794 ... 12.630984 6.335089 13.074254 \n",
- "3 -3.245664 6.490695 -1.381632 ... 8.081113 6.423302 -3.322394 \n",
- "4 14.943879 0.158889 7.968893 ... 4.980194 7.365077 4.547918 \n",
- "\n",
- " IKBKB IL12RB1 B2M LEF1 PRDM1 HLA.C CCL20 \n",
- "0 18.621722 12.067877 6.713297 5.373240 4.179533 11.793683 17.192958 \n",
- "1 17.324485 17.576044 6.477195 3.490226 13.702533 5.336035 13.813157 \n",
- "2 9.196277 11.556602 5.124115 7.739951 11.442156 11.219388 -0.290347 \n",
- "3 4.470948 18.348316 13.384904 15.261042 17.193111 1.124725 -1.044398 \n",
- "4 3.884870 15.489645 -0.660620 5.110488 18.508337 7.551574 8.716116 \n",
- "\n",
- "[5 rows x 31 columns]"
- ]
- },
- "execution_count": 61,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"patients = pd.read_csv('../data/patients.csv')\n",
"patients.head()"
@@ -4373,48 +1593,24 @@
},
{
"cell_type": "code",
- "execution_count": 62,
+ "execution_count": null,
"id": "67e86aec",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "image/png": "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",
- "text/plain": [
- "<Figure size 640x480 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"sns.scatterplot(data=patients, x='CHUK', y='Response', label='Patient');"
]
},
{
"cell_type": "code",
- "execution_count": 63,
+ "execution_count": null,
"id": "8bd68586",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "==============================================================================\n",
- " coef std err t P>|t| [0.025 0.975]\n",
- "------------------------------------------------------------------------------\n",
- "Intercept -11.2792 0.599 -18.838 0.000 -12.460 -10.098\n",
- "CHUK 0.9727 0.052 18.839 0.000 0.871 1.075\n",
- "==============================================================================\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"model = smf.ols('Response ~ CHUK', patients).fit()\n",
"#print(model.summary().tables[0])\n",
@@ -4433,48 +1629,24 @@
},
{
"cell_type": "code",
- "execution_count": 64,
+ "execution_count": null,
"id": "50155198",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "image/png": "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",
- "text/plain": [
- "<Figure size 640x480 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"statsmodels_material.illustration_regression(patients, model)"
]
},
{
"cell_type": "code",
- "execution_count": 65,
+ "execution_count": null,
"id": "215fb86c-3a14-45b7-ad65-9cfeafc410d4",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "Intercept -11.279184\n",
- "CHUK 0.972682\n",
- "dtype: float64"
- ]
- },
- "execution_count": 65,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"model.params"
]
@@ -4519,55 +1691,22 @@
},
{
"cell_type": "code",
- "execution_count": 66,
+ "execution_count": null,
"id": "95319ec8-320b-4fbb-a62e-a3665b40b043",
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "0 0.012319\n",
- "1 -0.041911\n",
- "2 -0.390476\n",
- "3 1.557927\n",
- "4 0.379972\n",
- " ... \n",
- "195 -0.342436\n",
- "196 -0.236740\n",
- "197 0.096321\n",
- "198 -0.123735\n",
- "199 0.584860\n",
- "Length: 200, dtype: float64"
- ]
- },
- "execution_count": 66,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"model.resid"
]
},
{
"cell_type": "code",
- "execution_count": 67,
+ "execution_count": null,
"id": "bc471543",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "image/png": "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",
- "text/plain": [
- "<Figure size 640x480 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"statsmodels_material.illustration_regression_residuals(patients, model)"
]
@@ -4610,23 +1749,12 @@
},
{
"cell_type": "code",
- "execution_count": 68,
+ "execution_count": null,
"id": "0d7780a9",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "image/png": "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",
- "text/plain": [
- "<Figure size 640x480 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"sm.graphics.qqplot(model.resid, fit=True, line='45', fmt='b', marker='+');"
]
@@ -4646,25 +1774,12 @@
},
{
"cell_type": "code",
- "execution_count": 69,
+ "execution_count": null,
"id": "5492f4e8-2ac8-4ba7-9a6c-241f33994998",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "==============================================================================\n",
- "Omnibus: 11.549 Durbin-Watson: 2.042\n",
- "Prob(Omnibus): 0.003 Jarque-Bera (JB): 11.949\n",
- "Skew: 0.586 Prob(JB): 0.00254\n",
- "Kurtosis: 3.245 Cond. No. 242.\n",
- "==============================================================================\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"print(model.summary().tables[-1])"
]
@@ -4702,7 +1817,7 @@
},
{
"cell_type": "code",
- "execution_count": 70,
+ "execution_count": null,
"id": "e79b930e",
"metadata": {
"hidden": true
@@ -4715,228 +1830,24 @@
},
{
"cell_type": "code",
- "execution_count": 71,
+ "execution_count": null,
"id": "3cab691b",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
- "\n",
- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>dfb_Intercept</th>\n",
- " <th>dfb_CHUK</th>\n",
- " <th>cooks_d</th>\n",
- " <th>standard_resid</th>\n",
- " <th>hat_diag</th>\n",
- " <th>dffits_internal</th>\n",
- " <th>student_resid</th>\n",
- " <th>dffits</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>0</th>\n",
- " <td>-0.001274</td>\n",
- " <td>0.001379</td>\n",
- " <td>0.000003</td>\n",
- " <td>0.030294</td>\n",
- " <td>0.007067</td>\n",
- " <td>0.002556</td>\n",
- " <td>0.030218</td>\n",
- " <td>0.002549</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1</th>\n",
- " <td>0.001223</td>\n",
- " <td>-0.001576</td>\n",
- " <td>0.000028</td>\n",
- " <td>-0.102972</td>\n",
- " <td>0.005234</td>\n",
- " <td>-0.007469</td>\n",
- " <td>-0.102714</td>\n",
- " <td>-0.007451</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2</th>\n",
- " <td>0.021748</td>\n",
- " <td>-0.025056</td>\n",
- " <td>0.002629</td>\n",
- " <td>-0.959589</td>\n",
- " <td>0.005678</td>\n",
- " <td>-0.072515</td>\n",
- " <td>-0.959396</td>\n",
- " <td>-0.072500</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>3</th>\n",
- " <td>-0.019622</td>\n",
- " <td>0.033215</td>\n",
- " <td>0.037323</td>\n",
- " <td>3.827412</td>\n",
- " <td>0.005070</td>\n",
- " <td>0.273213</td>\n",
- " <td>3.967316</td>\n",
- " <td>0.283200</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>4</th>\n",
- " <td>-0.014066</td>\n",
- " <td>0.017275</td>\n",
- " <td>0.002340</td>\n",
- " <td>0.933618</td>\n",
- " <td>0.005341</td>\n",
- " <td>0.068412</td>\n",
- " <td>0.933314</td>\n",
- " <td>0.068390</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>...</th>\n",
- " <td>...</td>\n",
- " <td>...</td>\n",
- " <td>...</td>\n",
- " <td>...</td>\n",
- " <td>...</td>\n",
- " <td>...</td>\n",
- " <td>...</td>\n",
- " <td>...</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>195</th>\n",
- " <td>0.049498</td>\n",
- " <td>-0.052442</td>\n",
- " <td>0.003169</td>\n",
- " <td>-0.842874</td>\n",
- " <td>0.008843</td>\n",
- " <td>-0.079612</td>\n",
- " <td>-0.842255</td>\n",
- " <td>-0.079554</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>196</th>\n",
- " <td>-0.002152</td>\n",
- " <td>0.000169</td>\n",
- " <td>0.000850</td>\n",
- " <td>-0.581587</td>\n",
- " <td>0.005000</td>\n",
- " <td>-0.041228</td>\n",
- " <td>-0.580613</td>\n",
- " <td>-0.041159</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>197</th>\n",
- " <td>0.002771</td>\n",
- " <td>-0.001967</td>\n",
- " <td>0.000143</td>\n",
- " <td>0.236635</td>\n",
- " <td>0.005069</td>\n",
- " <td>0.016891</td>\n",
- " <td>0.236070</td>\n",
- " <td>0.016850</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>198</th>\n",
- " <td>-0.043672</td>\n",
- " <td>0.042665</td>\n",
- " <td>0.001156</td>\n",
- " <td>-0.306910</td>\n",
- " <td>0.023949</td>\n",
- " <td>-0.048075</td>\n",
- " <td>-0.306207</td>\n",
- " <td>-0.047965</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>199</th>\n",
- " <td>-0.090400</td>\n",
- " <td>0.095454</td>\n",
- " <td>0.009763</td>\n",
- " <td>1.439930</td>\n",
- " <td>0.009330</td>\n",
- " <td>0.139737</td>\n",
- " <td>1.443869</td>\n",
- " <td>0.140119</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "<p>200 rows × 8 columns</p>\n",
- "</div>"
- ],
- "text/plain": [
- " dfb_Intercept dfb_CHUK cooks_d standard_resid hat_diag \\\n",
- "0 -0.001274 0.001379 0.000003 0.030294 0.007067 \n",
- "1 0.001223 -0.001576 0.000028 -0.102972 0.005234 \n",
- "2 0.021748 -0.025056 0.002629 -0.959589 0.005678 \n",
- "3 -0.019622 0.033215 0.037323 3.827412 0.005070 \n",
- "4 -0.014066 0.017275 0.002340 0.933618 0.005341 \n",
- ".. ... ... ... ... ... \n",
- "195 0.049498 -0.052442 0.003169 -0.842874 0.008843 \n",
- "196 -0.002152 0.000169 0.000850 -0.581587 0.005000 \n",
- "197 0.002771 -0.001967 0.000143 0.236635 0.005069 \n",
- "198 -0.043672 0.042665 0.001156 -0.306910 0.023949 \n",
- "199 -0.090400 0.095454 0.009763 1.439930 0.009330 \n",
- "\n",
- " dffits_internal student_resid dffits \n",
- "0 0.002556 0.030218 0.002549 \n",
- "1 -0.007469 -0.102714 -0.007451 \n",
- "2 -0.072515 -0.959396 -0.072500 \n",
- "3 0.273213 3.967316 0.283200 \n",
- "4 0.068412 0.933314 0.068390 \n",
- ".. ... ... ... \n",
- "195 -0.079612 -0.842255 -0.079554 \n",
- "196 -0.041228 -0.580613 -0.041159 \n",
- "197 0.016891 0.236070 0.016850 \n",
- "198 -0.048075 -0.306207 -0.047965 \n",
- "199 0.139737 1.443869 0.140119 \n",
- "\n",
- "[200 rows x 8 columns]"
- ]
- },
- "execution_count": 71,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"diagnostics.summary_frame()"
]
},
{
"cell_type": "code",
- "execution_count": 72,
+ "execution_count": null,
"id": "7f143230",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "image/png": "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",
- "text/plain": [
- "<Figure size 1330x410 with 2 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"_, axes = plt.subplots(1, 2, figsize=(13.3,4.1))\n",
"\n",
@@ -4970,7 +1881,7 @@
},
{
"cell_type": "code",
- "execution_count": 73,
+ "execution_count": null,
"id": "bc655fc0",
"metadata": {
"hidden": true
@@ -4984,23 +1895,12 @@
},
{
"cell_type": "code",
- "execution_count": 74,
+ "execution_count": null,
"id": "b5b46df6",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "image/png": "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",
- "text/plain": [
- "<Figure size 640x480 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"ax = sns.scatterplot(x=x, y=y)\n",
"ax.set_xlabel('x')\n",
@@ -5009,30 +1909,19 @@
},
{
"cell_type": "code",
- "execution_count": 75,
+ "execution_count": null,
"id": "a0b5ffc9",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "image/png": "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",
- "text/plain": [
- "<Figure size 640x480 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"sns.regplot(x=x, y=y);"
]
},
{
"cell_type": "code",
- "execution_count": 76,
+ "execution_count": null,
"id": "7bb8d264",
"metadata": {
"hidden": true
@@ -5046,23 +1935,12 @@
},
{
"cell_type": "code",
- "execution_count": 77,
+ "execution_count": null,
"id": "1ddf4e63",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "image/png": "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",
- "text/plain": [
- "<Figure size 1330x410 with 2 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"_, axes = plt.subplots(1, 2, figsize=(13.3,4.1))\n",
"\n",
@@ -5074,7 +1952,7 @@
},
{
"cell_type": "code",
- "execution_count": 78,
+ "execution_count": null,
"id": "7a441682",
"metadata": {
"hidden": true
@@ -5087,23 +1965,12 @@
},
{
"cell_type": "code",
- "execution_count": 79,
+ "execution_count": null,
"id": "0d8019bc",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "image/png": "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",
- "text/plain": [
- "<Figure size 1330x410 with 2 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"statsmodels_material.illustration_outlier(x, y, high_leverage_point, cooks_distant_point)"
]
@@ -5155,23 +2022,12 @@
},
{
"cell_type": "code",
- "execution_count": 80,
+ "execution_count": null,
"id": "b5b96410",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "image/png": "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",
- "text/plain": [
- "<Figure size 640x480 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"sns.regplot(x=np.log(x), y=y);"
]
@@ -5190,23 +2046,12 @@
},
{
"cell_type": "code",
- "execution_count": 81,
+ "execution_count": null,
"id": "709f2da0",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "image/png": "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",
- "text/plain": [
- "<Figure size 1500x800 with 6 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"statsmodels_material.illustration_monotonous_functions()"
]
@@ -5244,23 +2089,12 @@
},
{
"cell_type": "code",
- "execution_count": 82,
+ "execution_count": null,
"id": "02debff3",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "image/png": "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",
- "text/plain": [
- "<Figure size 640x480 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"def get_sample(n=100):\n",
" # we will use this code again later in the notebook\n",
@@ -5295,23 +2129,12 @@
},
{
"cell_type": "code",
- "execution_count": 83,
+ "execution_count": null,
"id": "32746edb",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "image/png": "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",
- "text/plain": [
- "<Figure size 1330x410 with 2 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"df = pd.DataFrame({'x': x, 'y': y})\n",
"linear_model = sm.OLS.from_formula('y ~ x', df).fit()\n",
@@ -5341,87 +2164,12 @@
},
{
"cell_type": "code",
- "execution_count": 84,
+ "execution_count": null,
"id": "9a3edfab",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
- "\n",
- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>y</th>\n",
- " <th>x</th>\n",
- " <th>x2</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>0</th>\n",
- " <td>1.010651</td>\n",
- " <td>0.030349</td>\n",
- " <td>0.000921</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1</th>\n",
- " <td>3.869300</td>\n",
- " <td>0.042248</td>\n",
- " <td>0.001785</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2</th>\n",
- " <td>2.815199</td>\n",
- " <td>0.044500</td>\n",
- " <td>0.001980</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>3</th>\n",
- " <td>4.360370</td>\n",
- " <td>0.069110</td>\n",
- " <td>0.004776</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>4</th>\n",
- " <td>2.486747</td>\n",
- " <td>0.075106</td>\n",
- " <td>0.005641</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " y x x2\n",
- "0 1.010651 0.030349 0.000921\n",
- "1 3.869300 0.042248 0.001785\n",
- "2 2.815199 0.044500 0.001980\n",
- "3 4.360370 0.069110 0.004776\n",
- "4 2.486747 0.075106 0.005641"
- ]
- },
- "execution_count": 84,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"augmented_df = df.assign(x2 = x**2)[['y', 'x', 'x2']]\n",
"augmented_df.head()"
@@ -5429,7 +2177,7 @@
},
{
"cell_type": "code",
- "execution_count": 85,
+ "execution_count": null,
"id": "24c100a8",
"metadata": {
"hidden": true
@@ -5453,7 +2201,7 @@
},
{
"cell_type": "code",
- "execution_count": 86,
+ "execution_count": null,
"id": "d6ac4ac8",
"metadata": {
"hidden": true
@@ -5466,23 +2214,12 @@
},
{
"cell_type": "code",
- "execution_count": 87,
+ "execution_count": null,
"id": "078047e2",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "image/png": "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",
- "text/plain": [
- "<Figure size 640x480 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"statsmodels_material.illustration_nonlinear_regression(df, y_th, poly2_model, 2)"
]
@@ -5522,7 +2259,7 @@
},
{
"cell_type": "code",
- "execution_count": 88,
+ "execution_count": null,
"id": "fba76906",
"metadata": {
"hidden": true
@@ -5535,23 +2272,12 @@
},
{
"cell_type": "code",
- "execution_count": 89,
+ "execution_count": null,
"id": "424e6080",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "image/png": "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",
- "text/plain": [
- "<Figure size 640x480 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"statsmodels_material.illustration_nonlinear_regression(df, y_th, poly6_model, 6)"
]
@@ -5568,81 +2294,12 @@
},
{
"cell_type": "code",
- "execution_count": 90,
+ "execution_count": null,
"id": "74c19b10",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
- "\n",
- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>R2</th>\n",
- " <th>R2_adjusted</th>\n",
- " <th>log-likelihood</th>\n",
- " <th>AIC</th>\n",
- " <th>BIC</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>1</th>\n",
- " <td>0.574957</td>\n",
- " <td>0.570619</td>\n",
- " <td>-218.166948</td>\n",
- " <td>440.333896</td>\n",
- " <td>445.544236</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2</th>\n",
- " <td>0.630454</td>\n",
- " <td>0.622834</td>\n",
- " <td>-211.171153</td>\n",
- " <td>428.342307</td>\n",
- " <td>436.157817</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>6</th>\n",
- " <td>0.663161</td>\n",
- " <td>0.641430</td>\n",
- " <td>-206.537608</td>\n",
- " <td>427.075215</td>\n",
- " <td>445.311406</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " R2 R2_adjusted log-likelihood AIC BIC\n",
- "1 0.574957 0.570619 -218.166948 440.333896 445.544236\n",
- "2 0.630454 0.622834 -211.171153 428.342307 436.157817\n",
- "6 0.663161 0.641430 -206.537608 427.075215 445.311406"
- ]
- },
- "execution_count": 90,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"scores = pd.DataFrame(np.array(\n",
" [[model.rsquared, model.rsquared_adj, model.llf, model.aic, model.bic] \\\n",
@@ -5664,7 +2321,7 @@
},
{
"cell_type": "code",
- "execution_count": 91,
+ "execution_count": null,
"id": "42c8cdf3",
"metadata": {
"hidden": true
@@ -5676,23 +2333,12 @@
},
{
"cell_type": "code",
- "execution_count": 92,
+ "execution_count": null,
"id": "3131de8c",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAAAkQAAAGwCAYAAABIC3rIAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8pXeV/AAAACXBIWXMAAA9hAAAPYQGoP6dpAABmOElEQVR4nO3deZyN5f/H8deZMytmxjoMxgxZGjuDMbTom9Km1PdXKmXJUhpZJsK3RSuViBBSlvJt+ypRRCVUdjPJkgyyM4MwYwaznfv3x53JZGmGM3Of5f18PM7jOufMfe55n5Ocj+u67uuyGYZhICIiIuLFfKwOICIiImI1FUQiIiLi9VQQiYiIiNdTQSQiIiJeTwWRiIiIeD0VRCIiIuL1VBCJiIiI1/O1OoC7cDgcHDx4kODgYGw2m9VxREREpBAMw+DkyZNUrVoVH5+L9wOpICqkgwcPEhERYXUMERERuQz79u2jevXqF/25CqJCCg4OBswPNCQkxOI0Ii5s40a49Vb4+mto3NjqNCLi5dLT04mIiMj/Hr8YFUSFdHaYLCQkRAWRyKXUqQMvvGC2+n9FRFzEP013UUEkIs5VuTIkJFidQkSkSHSVmYg4V3o6fPed2YqIuAkVRCLiXDt2wE03ma2IiJvQkJkTORwOsrOzrY7hlvz8/LDb7VbHEGdo0AB27YLwcKuTiIgUmgoiJ8nOzmbXrl04HA6ro7itsmXLUqVKFa3z5O4CAiAqyuoUIiJFooLICQzD4NChQ9jtdiIiIi658JOczzAMTp06xeHDhwEIV8+Ce9u7F157DYYOhRo1rE4jIlIoKoicIDc3l1OnTlG1alVKlSpldRy3FBQUBMDhw4cJCwvT8Jk7y8yEVavMVkTETaggcoK8vDwA/P39LU7i3s4Wkzk5OSqI3Fl0NCQlWZ1CRKRINLbjRJr7cmX0+YmIiFVUEImIc23caF5htnGj1UlERApNBZGIOFelShAfb7YiIm5CBZE4TVRUFOPGjbM6hlgtPByeeUbrEImIW9Gkai/Xrl07mjZt6pRCZt26dZQuXfrKQ4l7y8iATZugUSMoU8bqNCIeyTAu3hb2OWce76xzVa4MgYGF+wycTQWRXJJhGOTl5eHr+89/VCppiEQAkpOhTRtITITmza1O45Hy8mD2bNi+/a8vlXNvDkfRnneF17hChku9xpWKDE+2bBlcf701v1sFUTEwDDh1yprfXaoUFPZire7du7N8+XKWL1/O+PHjAZgxYwY9evRg4cKFPPPMM2zatIlvvvmGiIgIEhISWL16NZmZmURHRzNq1Cjat2+ff76oqCgGDhzIwIEDAfOqsWnTprFgwQIWL15MtWrVGDNmDHfeeaez37a4kuho2LwZatWyOolHysyEhx6CL76wOonIhZ39Djq3vdBzF/qZlRcbqyAqBqdOWTdSkJEBhR21Gj9+PMnJyTRs2JAXX3wRgC1btgAwbNgw3njjDWrVqkW5cuXYt28ft912G6+88goBAQG8//77dOzYkW3btlHjEqsRv/DCC7z++uuMHj2aCRMm0KVLF/bs2UP58uWv+L2KiwoKMvczE6c7eBDuvNPsfPP3h+7dzeGFs18kf7/5+BTv895yrnNvcHlf9Jd7vDPPVRJZ3ZkKIi8WGhqKv78/pUqVokqVKgD89ttvALz44ovcdNNN+ceWL1+eJk2a5D9+6aWXmDt3LvPnz6dfv34X/R3du3fngQceAGDkyJG89dZbrF27lltuuaU43pK4gv37Yfx4GDAAqle3Oo3H+OUXuOMO8+OtWNHsIWrb1upUIp5DBVExKFXK7Kmx6nc7Q4sWLQo8zsjI4Pnnn2fBggUcOnSI3NxcTp8+zd69ey95nsaNG+ffL126NCEhIfl7lomHSkuD+fPN7gsVRE6xcCF07mz+vVKvHixYAFddZXUqEc/ikpfdT5o0iaioKAIDA4mNjWXt2rWXPP7EiRPEx8cTHh5OQEAAdevWZeHChQWOOXDgAA899BAVKlQgKCiIRo0asX79+mLJb7OZw1ZW3JzVbfn3q8UGDx7M3LlzGTlyJD/++CMbNmygUaNGZGdnX/I8fn5+f/tsbDgcDueEFNfUoAFs26ZhMyeZOBE6djSLoRtuMLeJUzEk4nwu10P0ySefkJCQwJQpU4iNjWXcuHF06NCBbdu2ERYWdt7x2dnZ3HTTTYSFhTFnzhyqVavGnj17KFu2bP4xx48fp23bttxwww18/fXXVKpUie3bt1OuXLkSfGeuyd/fP38vtktZsWIF3bt35+677wbMHqPdu3cXczoR75WXBwkJ8NZb5uNHHoHJk825QyLifC5XEI0dO5bevXvTo0cPAKZMmcKCBQuYPn06w4YNO+/46dOnc+zYMVauXJnfGxEVFVXgmNdee42IiAhmzJiR/1zNmjWL7024kaioKNasWcPu3bspU6bMRXtv6tSpw+eff07Hjh2x2Ww8++yz6umRC9uyBe66C+bNUy/RZTp5Eh54wBwaAxg1CoYO9YyJqyKuyqWGzLKzs0lMTCxwKbePjw/t27dn1apVF3zN/PnziYuLIz4+nsqVK9OwYUNGjhxZoNdj/vz5tGjRgnvvvZewsDCaNWvGtGnTLpklKyuL9PT0AjdPNHjwYOx2O/Xr16dSpUoXnRM0duxYypUrR5s2bejYsSMdOnSgudaYkQspWxbuvddspcj274drrzWLocBA+PRTGDZMxZBIsTNcyIEDBwzAWLlyZYHnhwwZYrRq1eqCr6lXr54REBBgPPLII8b69euNjz/+2Chfvrzx/PPP5x8TEBBgBAQEGMOHDzeSkpKMqVOnGoGBgcbMmTMvmmXEiBEGcN4tLS3tvGNPnz5t/Prrr8bp06cv852LYehzFElMNIyqVc2l+MLCDGP1aqsTibi/tLS0i35/n8uleoguh8PhICwsjHfeeYeYmBg6d+7M008/zZQpUwoc07x5c0aOHEmzZs3o06cPvXv3LnDM3w0fPpy0tLT82759+0ri7Yi4v9OnzZ3uT5+2OolbmTfP7Bk6eNAcaVyzBmJjrU4l4j1cqiCqWLEidrud1NTUAs+npqbmr5Pzd+Hh4dStWxe73Z7/XHR0NCkpKflXQIWHh1O/fv0Cr4uOjr7kJeMBAQGEhIQUuIlIIWzdCk2amK38I8OAN9+Eu+82F3W9+WZYsQL+NhVSRIqZSxVE/v7+xMTEsGTJkvznHA4HS5YsIS4u7oKvadu2LTt27CgwwTc5OZnw8HD8/7wco23btmzbtq3A65KTk4mMjCyGdyHi5erVg7VrzVYuKTcX4uPNq8kMAx59FL76CkJDrU4m4n1cqiACSEhIYNq0acyaNYutW7fSt29fMjMz868669q1K8OHD88/vm/fvhw7dowBAwaQnJzMggULGDlyJPHx8fnHDBo0iNWrVzNy5Eh27NjBhx9+yDvvvFPgGBFxktKloWXLwu8h46XS082VpydPNidMjxlj3v/b0l0iUkJc7rL7zp07c+TIEZ577jlSUlJo2rQpixYtonLlygDs3bsXH5+/6riIiAgWL17MoEGDaNy4MdWqVWPAgAEMHTo0/5iWLVsyd+5chg8fzosvvkjNmjUZN24cXbp0KfH3J+LxDh2CqVPN7o7wcKvTuKQ9e8xiaPNmc3X5//4XOnWyOpWId7MZhmFYHcIdpKenExoaSlpa2nnzic6cOcOuXbuoWbMmgYGBFiV0f/ocPcSmTXDrrfD119CokdVpXM66debK06mpZr345ZcQE2N1KhHPdanv73O5XA+RiLi5Ro3MxXTkPJ99Bg8/bF6A17ixOV8oIsLqVCICLjiHSETE0xgGvP46/N//mcXQbbfBTz+pGBJxJSqIRMS5fv3V7P749Verk7iEnBzo08fcegOgXz9zzaHgYGtziUhBKoi8XLt27Rg4cKDTzte9e3c6aXaodwsOhnbt9I0PnDhhTqd6913w8TE3ap0wAXw1WUHE5eh/SxFxroiIv7Zo92K7dsHtt5vrU5YuDZ98Yj4WEdekHiIv1r17d5YvX8748eOx2WzYbDZ2797N5s2bufXWWylTpgyVK1fm4Ycf5ujRo/mvmzNnDo0aNSIoKIgKFSrQvn17MjMzef7555k1axbz5s3LP9+yZcuse4NijTNnYMcOs/VSq1aZ225s3QrVqpnzhVQMibg29RAVA8MwOJVzypLfXcqvFLZCbos9fvx4kpOTadiwIS+++CIAfn5+tGrVil69evHmm29y+vRphg4dyn333cf333/PoUOHeOCBB3j99de5++67OXnyJD/++COGYTB48GC2bt1Keno6M2bMAKB8+fLF9l7FRf36q3kdeWIiNG9udZoS98kn0K0bZGWZb//LL6FqVatTicg/UUFUDE7lnKLMqDKW/O6M4RmU9i/cCsGhoaH4+/tTqlSp/L3iXn75ZZo1a8bIkSPzj5s+fToREREkJyeTkZFBbm4u99xzT/7WJ43OWWsmKCiIrKysi+49J16gTh1YutRsvYhhwCuvwLPPmo/vvBM+/FALdou4CxVEUsAvv/zC0qVLKVPm/IJu586d3Hzzzdx44400atSIDh06cPPNN/N///d/lCtXzoK04pLOTqr2ItnZ5pVks2aZjxMSzMvsz9lzWkRcnAqiYlDKrxQZwzMs+91XIiMjg44dO/Laa6+d97Pw8HDsdjvffvstK1eu5JtvvmHChAk8/fTTrFmzhpo1a17R7xYPkZoK778PXbvCn1vueLJjx+Cee2D5crMAmjAB+va1OpWIFJUKomJgs9kKPWxlNX9/f/Ly8vIfN2/enM8++4yoqCh8L3JtsM1mo23btrRt25bnnnuOyMhI5s6dS0JCwnnnEy+UkgKjRsHNN3t8QbR9uzlZevt2s2Psf/+DDh2sTiUil0NXmXm5qKgo1qxZw+7duzl69Cjx8fEcO3aMBx54gHXr1rFz504WL15Mjx49yMvLY82aNYwcOZL169ezd+9ePv/8c44cOUJ0dHT++TZu3Mi2bds4evQoOTk5Fr9DKXFNmpjdJk2aWJ2kWP34I7RubRZDNWrAihUqhkTcmQoiLzd48GDsdjv169enUqVKZGdns2LFCvLy8rj55ptp1KgRAwcOpGzZsvj4+BASEsIPP/zAbbfdRt26dXnmmWcYM2YMt956KwC9e/emXr16tGjRgkqVKrFixQqL36GI882eDe3bm3Vfy5awZo32sRVxd9rtvpC0233x0+foIbZtg+7dYeZMqFfP6jROZRjw/PPw5yoV/Pvf5nSpUlc2dU9EipF2uxcRawQGQoMGZutBzpyBnj3NS+nB3Jts5EhzSw4RcX8qiETEuSIjzc27PMiRI3D33eY8IV9fmDwZevWyOpWIOJMKIhFxrpwcOHoUKlYEPz+r01yx334zryT7/XcIDYXPPoMbb7Q6lYg4mzp7RcS5Nm0y96rYtMnqJFds6VKIizOLoZo1zT3KVAyJeCYVRCLiXFddBV99ZbZubMYMcymlEyfMomj1avhzdQkR8UAqiETEuUJDzTGm0FCrk1wWhwP+8x945BHIzYXOneH77yEszOpkIlKcVBCJiHMdOQKTJpmtmzl9Gu6/31xoG+CZZ8yryjzsgjkRuQAVRCLiXPv3m7ub7t9vdZIiSU2FG24wt9/w8zOXUXrpJV1WL+ItdJWZiDhXs2aQlWV1iiLZsgXuuAN274Zy5WDuXLj+eqtTiUhJ0r99RMSrffsttGljFkO1a5uTp1UMiXgfFURerl27dgwcONDqGOJJtm83N/ravt3qJP9o2jS49VZIT4drrzUvq69b1+pUImIFFURySYZhkJuba3UMcSe+vlCpktm6KIcDhgyBPn0gLw8eesjsKapY0epkImIVFURerHv37ixfvpzx48djs9mw2WzMnDkTm83G119/TUxMDAEBAfz00090796dTp06FXj9wIEDadeuXf5jh8PBqFGjqFmzJkFBQTRp0oQ5c+aU7JsS69WsCR99ZLYuKDPT3JT1jTfMxy+8YG7QGhBgbS4RsZbr/hNOit348eNJTk6mYcOGvPjn9t1btmwBYNiwYbzxxhvUqlWLcuXKFep8o0aNYvbs2UyZMoU6derwww8/8NBDD1GpUiWu16QM75GXZ1YdpUuD3W51mgIOHYKOHSExEfz9zcUXH3zQ6lQi4grUQ1ScDh0quH3Br7/Cvn3m/TNnICkJTp40H6emwi+//HXstm2wZ495PyfHPDYtzXx85Aj8/PNfx27fDrt2FTleaGgo/v7+lCpViipVqlClShXsf36Bvfjii9x0001cddVVlC9f/h/PlZWVxciRI5k+fTodOnSgVq1adO/enYceeoipU6cWOZu4sV9+MRdlPPfPswvYuBFiY81iqGJFc7FFFUMicpYKouI0dao5Y/Os+++H0aPN+/v3Q0yM+bczmH32N9zw17Hdu5uLoIC5UWZMDPz0k/n400+hdeu/ju3b11xa14latGhRpON37NjBqVOnuOmmmyhTpkz+7f3332fnzp1OzSYurmZN88+oCw2ZLVwIbdua/x6pV8+8kqxtW6tTiYgr0ZBZcXr0UXOywlkffwzBweb96tXNYqhOHfNx167mxklnzZz51/K4FSuax57dG+q++8zrhM+aPNnpE1hLly5d4LGPjw+GYRR4LicnJ/9+RkYGAAsWLKBatWoFjgvQ5AzvUq4c3Huv1SnyTZoE/fubE6lvuMHcrb6Qo8Ai4kVUEBWn8HDzdlb9+n/dDwyE5s3/ely5snk7q169v+77+RU8tlIl83bW2aLqMvj7+5OXl/ePx1WqVInNmzcXeG7Dhg34+fkBUL9+fQICAti7d6/mC3m7P/6AL780J+tUqGBZjLw8ePJJGD/efNyjB0yZYs4dEhH5OxVEXi4qKoo1a9awe/duypQpg8PhuOBx//rXvxg9ejTvv/8+cXFxzJ49m82bN9OsWTMAgoODGTx4MIMGDcLhcHDNNdeQlpbGihUrCAkJoVu3biX5tsRKe/aY1UdiomUFUUYGPPAAfPWV+XjkSBg2DGw2S+KIiBvQHCIvN3jwYOx2O/Xr16dSpUrs3bv3gsd16NCBZ599lqeeeoqWLVty8uRJunbtWuCYl156iWeffZZRo0YRHR3NLbfcwoIFC6jpQnNJpAQ0a2ZeCPBnsVzS9u83F1n86iuzI/bTT2H4cBVDInJpNuPvE0PkgtLT0wkNDSUtLY2QkJACPztz5gy7du2iZs2aBGpb7Mumz1Gu1M8/m3uSHTwIYWEwb17B6w9ExPtc6vv7XOohEhHn2rkT7rzTbEvQ/PlwzTVmMVS/PqxZo2JIRApPBZGIuDXDgHHjoFMnOHUKbroJVqyAqCiLg4mIW9GkahFxrquuMrtrSkBuLgwYAG+/bT7u0wcmTjQvzBQRKQoVRCLiXIZhXvNutxfrTOb0dOjcGRYtMn/N6NGQkKDJ0yJyeVxyyGzSpElERUURGBhIbGwsa9euveTxJ06cID4+nvDwcAICAqhbty4LFy684LGvvvoqNpuNgQMHOj235qdfGX1+HuLnn80umnO3l3GyvXvN+UKLFkFQkLnY4pNPqhgSkcvncj1En3zyCQkJCUyZMoXY2FjGjRtHhw4d2LZtG2FhYecdn52dzU033URYWBhz5syhWrVq7Nmzh7Jly5537Lp165g6dSqNGzd2auaz+39lZ2cTFBTk1HN7k1OnTgHkL/Yobioy0tw1NTKyWE6/bp255mNqKlSpYq4BWcSdZkREzuNyBdHYsWPp3bs3PXr0AGDKlCksWLCA6dOnM2zYsPOOnz59OseOHWPlypX5X6RRF5hNmZGRQZcuXZg2bRovv/zyP+bIysoiKysr/3F6evpFj/X19aVUqVIcOXIEPz8/fHxcsuPNZRmGwalTpzh8+DBly5bNLzDFTVWoYO7FVww+/xweeghOn4ZGjcy1hmrUKJZfJSJexqUKouzsbBITExk+fHj+cz4+PrRv355Vq1Zd8DXz588nLi6O+Ph45s2bR6VKlXjwwQcZOnRogS/W+Ph4br/9dtq3b1+ogmjUqFG88MILhcpts9kIDw9n165d7Dm7Q70UWdmyZalSpYrVMeRKHT8O330H7ds7bdMww4A33oCnnjIf33qruTXgJZYUEREpEpcqiI4ePUpeXh6Vz93TC6hcuTK//fbbBV/z+++/8/3339OlSxcWLlzIjh07ePzxx8nJyWHEiBEAfPzxxyQlJbFu3bpCZxk+fDgJCQn5j9PT04mIiLjo8f7+/tSpU4fs7OxC/w75i5+fn3qGPMWuXeYGxImJTimIcnIgPh6mTTMfx8ebl9k7eT9jEfFybv9XisPhICwsjHfeeQe73U5MTAwHDhxg9OjRjBgxgn379jFgwAC+/fbbIq1+HBAQUORd2n18fLTCskiTJpCWBqVLX/GpTpyAe+81O5xsNrMQ6t//ik8rInIelyqIKlasiN1uJzU1tcDzqampFx1KCQ8PP693ITo6mpSUlPwhuMOHD9P8nN3i8/Ly+OGHH5g4cSJZWVnqmRBxJrvdKWNZu3bB7bfD1q1mbfXRR+ZkahGR4uBSs3/9/f2JiYlhyZIl+c85HA6WLFlCXFzcBV/Ttm1bduzYUWCX9uTkZMLDw/H39+fGG29k06ZNbNiwIf/WokULunTpwoYNG1QMiTjbrl3mVvO7dl32KVatgthYsxiqVg1+/FHFkIgUL5cqiAASEhKYNm0as2bNYuvWrfTt25fMzMz8q866du1aYNJ13759OXbsGAMGDCA5OZkFCxYwcuRI4uPjAQgODqZhw4YFbqVLl6ZChQo0bNjQkvco4tFyc+HIEbO9DJ98AjfcYJ6iWTNzT7JmzZycUUTkb1xqyAygc+fOHDlyhOeee46UlBSaNm3KokWL8ida7927t8Bl7RERESxevJhBgwbRuHFjqlWrxoABAxg6dKhVb0HEu9WpY076KSLDgJEj4ZlnzMcdO8KHH0KZMk7OJyJyATZDywMXSnp6OqGhoaSlpRGia31FnCo729yHbNYs8/GgQeZWHBrRFpErVdjvb5cbMhMRN/fzzxAQUOitO44dg5tvNoshHx9zo9axY1UMiUjJcrkhMxFxc9WrmxVN9er/eOiOHeaVZMnJEBwMn34Kt9xSAhlFRP5GBZGIOFelSubqif/gp5+gUyf44w9z+42vvjK34xARsYKGzETEudLSYMECs72I//4XbrzRLIZatjSvJFMxJCJWUkEkIs61cyfccYfZ/o1hwPPPmxu0ZmfDPffAsmXmrvUiIlbSkJmIOFejRnDwIFSsWODprCzo2dPsHQJzo9ZRo8yJ1CIiVlNBJCLO5ecH4eEFnjp6FO6+25w35OtrXknWu7dF+UTEKQzDIDsvm6y8LLPNzbrk/azcrPzjL3a/T0wfospGWfJ+VBCJiHPt2QMvvQTPPguRkWzbZl5JtnMnhIbCnDnQvr3VIUXch8Nw/GOxcUUFyWW+PseR4/T3evNVN6sgEhEPceYMbNkCZ86wbJk5T+j4cYiKMuda169vdUCR8xmGQY4jJ/9L/9zb2QLgiguSy3x9ruPytsEpab4+vgTYA/C3+xPgG3DJ+wG+fz62F/xZ1eCq1uW37DeLiGeqVw9WrWLmTHP16ZwcaN0a5s2DsDCrw4kVzg6tnFtgnFd0/K0Q+fsxFytUivKaS/3e4ujtKC5nC4nCFB4FipDLeE2hCpo/7/vY3HtCoAoiEXEqh8McLRs50nzcuTPMmAFBQdbm8lQOw0FOXs7lFRBFKBiyHZfxmj9v7lRsnOVj88kvAi6rcLhA0eCMIsTPxw+bzWb1x+ORVBCJyCU5HHD6NJw6VfB2oedOnYLf5/7Cc8tu4CuW0vHpJrz4oq4kc7bvfv+Ofgv7sfP4TrcZTjmX3WYvUGicvX9uz8fFfn7BYy7nNf/we+0+2jvG26ggEnFThmFO17lQUVKYwqWwx545U7RcYVQh0Gc4/3mzCp37F89791anck4x7LthTFg74aLH+Pr4XnExcNmvKURx4+fjp2JDXJIKIhEnMwxzzR1nFCP/dGxJCwyEUqUufQsOrsxdPYYQF1fy+TzZ2gNr6Tq3K9v+2AZAfMt4nmr7FKX8SuUXHCo2RC6fCiLxGoZhTvAtjl6Uv98Mo2TfW0DAXwVJUNA/Fy2Xc2xgYCGHvk6ehMREOBlj7tgqVyQnL4eXf3iZV358hTwjj6rBVZlx1wxuvupmq6OJeBQVROIVZs82r3g6fbpkf6+fn/MKkosdGxQEdlfqFNi+HW64wSyKmje3Oo1b23pkKw/PfZjEQ4kAPNDwASbdNolyQeUsTibieVQQicfbtw8ef7xgMWS3Q+nSxdebEhRk3vz8rHvflqlf3yyKqle3OonbchgOJqyZwLAlwziTe4ZygeWYfPtkOjfsbHU0EY+lgkg8mmHAo4+aozhxcbBwoVkIeWWhUlICA6F2batTuK29aXvp/kV3lu5eCsAttW/hvTvfs3TBOhFvoIthxaN98AF8/bU5x2b6dChbVsVQsdu3D/r3N1spNMMweP+X92k0uRFLdy+llF8pJt8+mYUPLlQxJFICVBCJx0pJgYEDzfsjRsDVV1sax3ucPAnLlpmtFMqRzCP83//+j25fdCM9K5246nH88tgvPNbiMS3CJ1JCNGQmHskwzHlDx4+b83oHD7Y6kRepXx82brQ6hdv4ctuX9PqyF4czD+Pn48cL7V5gSNsh+Pror2eRkqT/48QjzZkDc+eCr685VKZhMnE1J7NOMmjxIN77+T0AGlRqwOx7ZtO0SlNrg4l4KQ2Zicc5ehT69TPv/+c/0KSJtXm8zqZN5hVmmzZZncRl/bDnBxpPacx7P7+HDRuD4wazvs96FUMiFlIPkXicgQPh8GFo0ACeftrqNF6oYkXo1ctspYAzuWd49vtnGbNqDAYGUWWjmNVpFtdFXmd1NBGvp4JIPMqXX8J//2uuqDx9Ovj7W53IC4WHw/PPW53C5WxI2cDDcx9m8+HNAPRs1pOxHcYSEhBicTIRARVE4kFOnIDHHjPvP/kktGplaRzvlZkJv/5qTq4uXdrqNJbLdeQyesVoRiwbQY4jh7DSYUzrOI07691pdTQROYcKIvEYQ4bAwYNQpw688ILVabzYtm1mNaqtO9hxbAdd53Zl1f5VANx99d1MvWMqlUpXsjiZiPydCiLxCN9+C+++a95/7z1z2wyxSHQ0/PKLWZl6KcMwmJo4lSe/eZJTOacICQhhwq0TeLjxw1pXSMRFqSASt5eRAb17m/f79YNrr7U2j9cLCoLGja1OYZmDJw/Sc35PFu1YBMANUTcw464ZRJaNtDiZiFyKLrsXt/ef/8CePRAZCaNGWZ1GOHAAhg83Wy/z6ZZPaTS5EYt2LCLAHsCbHd7ku67fqRgScQMqiMSt/fgjTJhg3p82DcqUsTaPYM5u/9//zNZLHD99nAc/e5DOczpz7PQxYsJjSHo0iYGtB+Jj01+zIu5AQ2bitk6fhp49zfs9e8JNN1mbR/7UoAHs2GF1ihLzzc5veGTeIxw4eQC7zc5/rv0Pz173LH52LY8u4k5UEInbev552L4dqlaFN96wOo14m8zsTIZ+N5RJ6yYBULdCXd7v9D6x1WMtTiYil0N9ueKW1q37qwiaMgXKlrU0jpxryxaoV89sPdSa/WtoNrVZfjHUr2U/fn70ZxVDIm5MPUTidrKyoEcPcDjgwQehY0erE0kBoaFw551m62Gy87J5aflLjPxpJA7DQbXgasy4awY3XaXxWhF3p4JI3M7IkWbnQ6VKMH681WnkPNWrw+jRVqdwul+P/MrDcx8m6VASAA82epCJt06kXFA5i5OJiDOoIBK3snGjWRABTJyo/UNd0unT8PvvUKuWR6yQ6TAcjF89nuFLhpOVl0X5oPJMvn0y9zW4z+poIuJEKojEbeTmmkNlublw991w771WJ5IL2roVYmI8YuuOPSf20H1ed5btXgbArbVv5b073yM8ONzaYCLidC45qXrSpElERUURGBhIbGwsa9euveTxJ06cID4+nvDwcAICAqhbty4LFy7M//moUaNo2bIlwcHBhIWF0alTJ7Zt21bcb0Oc7I03ICkJypWDSZNAOyC4qLp1YeVKs3VThmEwc8NMGk1uxLLdyyjlV4opt09hwYMLVAyJeCiXK4g++eQTEhISGDFiBElJSTRp0oQOHTpw+PDhCx6fnZ3NTTfdxO7du5kzZw7btm1j2rRpVKtWLf+Y5cuXEx8fz+rVq/n222/Jycnh5ptvJjMzs6Tellyh334zL7MHePNNCNd3kusqUwbi4tx2lczDmYe559N76DGvByezT9Imog2/PPYLj7Z4VPuQiXgwm2EYhtUhzhUbG0vLli2ZOHEiAA6Hg4iICJ544gmGDRt23vFTpkxh9OjR/Pbbb/j5FW4htCNHjhAWFsby5cu57rrrCvWa9PR0QkNDSUtLIyQkpPBvSK5YXp65P9mqVXDLLbBwoXqHXNqhQ+YOuz17ul3lOn/bfHp/2ZvDmYfx8/HjxRteZEibIdh97FZHE5HLVNjvb5fqIcrOziYxMZH27dvnP+fj40P79u1ZtWrVBV8zf/584uLiiI+Pp3LlyjRs2JCRI0eSl5d30d+TlpYGQPny5S96TFZWFunp6QVuYo2JE81iKDgYpk5VMeTyjhwxxzSPHLE6SaGlZ6XTc15P7vr4Lg5nHqZhWEPW9l7LsGuGqRgS8RIuNan66NGj5OXlUbly5QLPV65cmd9+++2Cr/n999/5/vvv6dKlCwsXLmTHjh08/vjj5OTkMGLEiPOOdzgcDBw4kLZt29KwYcOLZhk1ahQvvPDClb0huWK//25u3grmldw1alibRwqhcWOzl8hNLN+9nG5fdGNP2h5s2BjSZggv3vAiAb4BVkcTkRLkUgXR5XA4HISFhfHOO+9gt9uJiYnhwIEDjB49+oIFUXx8PJs3b+ann3665HmHDx9OQkJC/uP09HQiIiKcnl8uzjCgVy84dQratYPeva1OJJ7kTO4Znvn+GcauGouBQc2yNZnVaRbXRl5rdTQRsYBLFUQVK1bEbreTmppa4PnU1FSqVKlywdeEh4fj5+eH3f5Xt3Z0dDQpKSlkZ2fj7++f/3y/fv346quv+OGHH6hevfolswQEBBAQoH8hWmnaNFi61FzK5t13wcelBnjlorZuhS5d4L//hehoq9Nc0M+HfubhuQ+z5Yi5vUivZr0Y22EswQHBFicTEau41FeMv78/MTExLFmyJP85h8PBkiVLiIuLu+Br2rZty44dO3A4HPnPJScnEx4enl8MGYZBv379mDt3Lt9//z01a9Ys3jciV2zfPhg82Lw/ciRcdZW1eaQISpc2rzIrXdrqJOfJdeTyyg+v0OrdVmw5soXKpSvz5QNfMu3OaSqGRLycSxVEAAkJCUybNo1Zs2axdetW+vbtS2ZmJj169ACga9euDB8+PP/4vn37cuzYMQYMGEBycjILFixg5MiRxMfH5x8THx/P7Nmz+fDDDwkODiYlJYWUlBROnz5d4u9P/plhwGOPwcmT5vfqE09YnUiKpEYNc1K1i0342v7Hdq6dcS3PLH2GXEcu90Tfw6a+m7ij7h1WRxMRF+BSQ2YAnTt35siRIzz33HOkpKTQtGlTFi1alD/Reu/evficM3YSERHB4sWLGTRoEI0bN6ZatWoMGDCAoUOH5h8zefJkANq1a1fgd82YMYPu3bsX+3uSopk927y03t/fvHrbrot83EtWljmpOjwcXGDY2TAMpqyfwuBvB3Mq5xQhASFMvHUiDzV+SOsKiUg+l1uHyFVpHaKSkZIC9evD8ePmUNk5nYHiLpKSXGbrjgPpB+g5vyeLdy4G4F81/8WMu2ZQI9S1eq9EpPgU9vvb5XqIxLv162cWQ82a/TWHSNxM7drw7bdma6GPN3/M4wse5/iZ4wT6BvJa+9fo16ofPjaXmykgIi5ABZG4jDlz4LPPwNcXpk+HQi48Lq4mJATOWVy1pB07fYz4hfF8vPljAGLCY/jg7g+IruSaV7yJiGvQP5XEJfzxB5ydBz98ODRtamkcuRKpqTB2rNmWsEU7FtHw7YZ8vPlj7DY7I64fwaqeq1QMicg/Ug+RuISBA+HwYWjQAJ5+2uo0ckUOHTJ34v3Xv+Bvq84Xl8zsTIZ8O4TJ680LKOpVqMcHd39Ay2otS+T3i4j7U0EklvvqK/PKMh8fc6jMBS5MkivRtCmU4N5/q/atousXXdlxbAcA/Vv1Z1T7UZTyK1ViGUTE/akgEkulpZlrDgEkJECrVtbmEfeRnZfNC8te4NUVr+IwHFQPqc6Mu2bQvpZ185dExH1pDpFYasgQOHAA6tSBF1+0Oo04xbZtcM01ZltMthzeQut3WzPyp5E4DAcPNX6ITX03qRgSkcumHiKxzHffmfuVgblXWVCQtXnESQICzEvui2HsM8+Rx7jV43j6+6fJysuiQlAFptwxhf+r/39O/10i4l1UEIklMjL+2r0+Ph6uu87aPOJEUVEwc6bTT7v7xG66fdGNH/b8AMBtdW7j3Y7vEh4c7vTfJSLeRwWRWOI//4HduyEyEkaNsjqNOFVODpw4AWXLOmUxKcMwmLlhJgMWDeBk9klK+5XmzQ5v0qt5L229ISJOo4JIStxPP8HEieb9d96BYG0y7lk2bXLa1h2pGan0+aoP87fNB6BtRFvev/t9apWr5YykIiL5VBBJiTp9Gnr2NHe0f+QRuPlmqxOJ09WqBfPmme0V+OK3L+jzZR+OnDqCn48fL93wEoPbDMbuo91+RcT5VBBJiXr+eUhONjdCHzPG6jRSLMqWhTvvvOyXp51JY8CiAcz6ZRYAjcIaMfue2TSu3NhJAUVEzqfL7qXErFsHb7xh3p8yxfzeFA905AhMnWq2RbR011IaT2nMrF9mYcPG0LZDWdd7nYohESl26iGSEpGdbQ6RORzwwANX1IEgrm7fPvPSwZYtoVKlQr3kdM5pnv7+ad5c/SYAtcrVYlanWVxT45riTCoikk8FkZSIkSNh82bz+/Gtt6xOI8WqeXPIzS304UmHknh47sP8euRXAHo3782Ym8cQHKDZ9iJSclQQSbHbuBFeecW8P3EiVKxobR5xDbmOXF796VVeWP4CuY5cKpeuzHt3vsftdW+3OpqIeCHNIZJilZtrDpXl5kKnTnDvvVYnkmK3fTt06GC2F5H8RzLXTL+GZ5c+S64jl/+r/39sfnyziiERsYx6iKRYjRljLkdTtiy8/TZoHT0vYLdDSIjZ/o1hGLy97m2GfDuE07mnCQ0IZeJtE+nSqIsWWRQRS6kgkmKzbRuMGGHeHzfOvNRevECtWvC//5339IH0A/SY14Nvf/8WgBtr3siMu2YQERpR0glFRM6jgkiKRV6eOVSWlQW33AJdu1qdSEpMXh6cOQOBgWC3YxgGH2/+mMcXPs6JMycI9A3k9favE98qHh+bRu1FxDWoIJJiMWkSrFwJZcqYS9JoNMSL/PJL/tYdf1wdyeMLH+fTLZ8C0LJqS96/+32urni1xSFFRApSQSRO9/vvMHy4eX/0aKhRw9o8UsKiouDDD/kubwddJ9/BoYxD2G12nrv+OYZfMxw/+5Vv+Coi4mwqiMSpDAN694ZTp+D666FPH6sTSUnLKOPPkOAfmLJwCgBXV7yaD+7+gBZVW1icTETk4lQQiVO9+y58/z0EBZn3fVxkikh2XjY/7PmBUzmncBgODMPAwMi/7zAcGBgF7l/ouMt5jSXn/ttzzspYmHOfPLSH5j+nUq4OdL1hAKNuHEWQX5DVfwRERC5JBZE4zf798OST5v1XXoHata3Nc65nv3+W11e+bnUMr9DsIMyeC2vnTabVLY9ZHUdEpFBUEIlTGAY8+iicPAmtW0P//lYn+svx08d5e/3bADSr0owA3wBs2PCx+WCz/dliK3D/7M+celwx/45iz1/I4/xsdk6ObkWrMuUt/i8vIlJ4KojEKf77X1i4EPz9Yfr0C67JZ5kp66eQkZ1B48qNSeyTqAUARUTkPC4yw0PcWWoqDBhg3h8xAqKjrc1zrjO5Zxi/ZjwAQ9oMUTFUEn7/He65x2xFRNyECiK5Yv36wbFj0KwZDBlidZqCZm+cTWpmKhEhEXRu0NnqON7B4TBX5HQ4rE4iIlJoGjKTKzJnjnnz9TWHyvxcaIkZh+Fg9MrRACTEJWj9m5JSuzYsWGB1ChGRIlEPkVy2P/6A+Hjz/rBh0LSppXHOM3/bfJL/SKZsYFl6Ne9ldRwREXFhKojksg0cCIcPQ/368MwzVqc53+srzMvsH2/xOGX8y1icxoskJZl7tSQlWZ1ERKTQVBDJZVmwAGbPNhdenD4dAgKsTlTQir0rWLV/FQH2AJ6IfcLqON6lRg2YNk17toiIW9EcIimytDRzzSGAQYMgNtbaPBdydhHGrk26UqVMFYvTeJmKFaGXhihFxL2oh0iKbMgQOHDAnDv74otWpznf1iNbmb9tPjZsPBn3pNVxvM/x4/D552YrIuImVBBJkSxZYo6GALz3HpQqZW2eCxmzagwAna7uRL2K9SxO44V27YJ//9tsRUTchIbMpNAyMsyd7AEefxyuu87aPBdy8ORBPtj4AWAuxCgWaNzYvAQxJMTqJCIihaaCSArt6afNf/TXqAGvvmp1mgt7a81bZOdlc02Na4iLiLM6jnfy9YXy2sdMRNyLSw6ZTZo0iaioKAIDA4mNjWXt2rWXPP7EiRPEx8cTHh5OQEAAdevWZeHChVd0TiloxQqYMMG8P20aBAdbm+dC0rPSmbJ+CgBPtXnK4jRebNcueOghDZmJiFtxuYLok08+ISEhgREjRpCUlESTJk3o0KEDhw8fvuDx2dnZ3HTTTezevZs5c+awbds2pk2bRrVq1S77nFLQ6dPwyCPmjvY9esDNN1ud6MKmJU4jLSuNqyteze11b7c6jvfKyYH9+81WRMRN2AzDMKwOca7Y2FhatmzJxIkTAXA4HERERPDEE08wbNiw846fMmUKo0eP5rfffsPvIvtGFPWcF5Kenk5oaChpaWmEeNnciGHD4LXXIDwctmyBcuWsTnS+7Lxsao2vxYGTB3jvzvd4pNkjVkcSEREXUNjvb5fqIcrOziYxMZH27dvnP+fj40P79u1ZtWrVBV8zf/584uLiiI+Pp3LlyjRs2JCRI0eSl5d32ecEyMrKIj09vcDNG61fD2+8Yd6fMsU1iyGAjzd/zIGTBwgvE06XRl2sjiMiIm7GpQqio0ePkpeXR+XKlQs8X7lyZVJSUi74mt9//505c+aQl5fHwoULefbZZxkzZgwvv/zyZZ8TYNSoUYSGhubfIiIirvDduZ/sbHOoLC8P7r8f7rzT6kQXZhhG/jYdA2IHEODrYstme5sNG6B0abMVEXETLlUQXQ6Hw0FYWBjvvPMOMTExdO7cmaeffpopU6Zc0XmHDx9OWlpa/m3fvn1OSuw+Ro2CTZvMhYffesvqNBf39Y6v2XJkC8H+wTza4lGr40jVquYfnqpVrU4iIlJoLnXZfcWKFbHb7aSmphZ4PjU1lSpVLrz9Qnh4OH5+ftjt9vznoqOjSUlJITs7+7LOCRAQEECAq23QVYI2bYI/O9mYOBEqVbI2z6WMXjkagEdjHqVsYFlrwwiEhUH//lanEBEpEpfqIfL39ycmJoYlS5bkP+dwOFiyZAlxcRdeU6Zt27bs2LEDh8OR/1xycjLh4eH4+/tf1jm9XW6uOVSWmwudOsF991md6OLWHljLst3L8PXxZUDrAVbHEYD0dFi82GxFRNyESxVEAAkJCUybNo1Zs2axdetW+vbtS2ZmJj169ACga9euDB8+PP/4vn37cuzYMQYMGEBycjILFixg5MiRxMfHF/qcUtDYseZk6rJl4e23wWazOtHFne0d6tKoC9VDqlucRgDYsQNuucVsRUTcRJGHzE6fPs2xY8cKrPMDsGXLFho0aHDFgTp37syRI0d47rnnSElJoWnTpixatCh/UvTevXvx8fmrjouIiGDx4sUMGjSIxo0bU61aNQYMGMDQoUMLfU75y7Zt8Nxz5v033zQvtXdVO47t4POtnwMwuM1gi9NIvoYNYd8+c+hMRMRNFGkdojlz5jBw4EAqVqyIw+Fg2rRpxMbGAtC8eXOSkpKKLajVvGEdIofD3J9sxQro0AG+/tq1e4ceX/A4k9dP5rY6t7HgwQVWxxERERdULOsQvfzyyyQmJrJhwwZmzJhBz549+fDDDwHz0mdxb5MmmcVQmTLwzjuuXQwdzjzMjA0zAG3T4XL27oVHHzVbERE3UaQhs5ycnPxhppiYGH744QfuvvtuduzYgc2Vvz3lH+3aZa5IDfD66+YGrq5s4tqJnMk9Q6tqrbgu8jqr48i5Tp2CpCSzFRFxE0XqIQoLC2Pjxo35j8uXL8+3337L1q1bCzwv7sUwoHdv8/vr+uvNf9y7sszsTCatmwSYvUMqxl3M1VfDunVmKyLiJopUEH3wwQeE/W2ipL+/Px999BHLly93ajApOe+9B0uWQFAQvPsu+LjctYcFTf95OsdOH6N2+dp0urqT1XFERMQDFOmrr3r16hddzLBt27ZOCSQla/9+ePJJ8/7LL0Pt2tbm+Se5jlzGrh4LwJNxT2L3sf/DK6TEbdxoruSpXmMRcSNX1BewZ88evvnmm4vuCXbw4MErOb0UM8OAvn3N9fNiY2GAG6xrOOfXOew+sZtKpSrRrUk3q+PIhYSFQUKCLrsXEbdy2QXRRx99RO3atbnllluoVasWH3zwAWCuE/Tqq68SGxtLDVefmevlPvwQvvoK/P1h+nSwu3hny7mbuD7R6gmC/IIsTiQXVKUKDB9utiIibuKyC6KXXnqJJ554gk2bNnHTTTfRt29fnn32Wa666ipmzpxJixYt+N///ufMrOJEqal/bTf13HNQv761eQpjya4l/JzyM6X8SvF4y8etjiMXk5EBP/1ktiIibuKyN3fduXMnAwYMIDIykkmTJlGjRg1WrFjBxo0biY6OdmZGKQb9+sGxY9C0KTzlJsv4nN2mo1ezXlQoVcHiNHJRyclw7bWQmAjNm1udRkSkUC67IMrJySEoyByyqF69OoGBgbzxxhsqhtzAZ5/BnDng6wszZoCfn9WJ/tmGlA18s/Mb7DY7g+IGWR1HLqV+ffjtN4iMtDqJiEihXdGk6g8//JDffvsNALvdTrly5ZwSSorPH3/A2X1vhw41e4jcwdneofsa3EdU2Shrw8ilBQZCvXpmKyLiJi67ILr22msZMWIEDRo0oGLFipw5c4bx48fz6aef8uuvv5Kbm+vMnOIkgwaZ84eio+HZZ61OUzh7Tuzhk82fADCkzRCL08g/2r/fvMps/36rk4iIFNplD5mdXYhx+/btJCYmkpSURFJSEu+//z4nTpzA39+funXragVrF7JwIXzwgbnw4owZEBBgdaLCeXP1m+QZebSv1Z5m4c2sjiP/JD0dFi+GXr2sTiIiUmiXXRCdVadOHerUqcP999+f/9yuXbtYv349P//885WeXpwkLe2vLTkGDjTXHXIHx04fY1rSNECbuLqN+vVhyxarU4iIFMkVF0QXUrNmTWrWrMm9995bHKeXy/DUU+YIxlVXwUsvWZ2m8Cavm8ypnFM0rdKU9rXaWx1HREQ8lIvvWiXO8P338M475v333oNSpazNU1inc07z1tq3AHPukDZxdRObN0NUlNmKiLgJFUQeLjPzr6kcffuau9m7i/d/eZ/DmYeJDI3k3vrqbXQb5cvDQw+ZrYiImyiWITNxHU8/Dbt2QY0a8NprVqcpvDxHHmNWjQEgIS4BP7sbLJYkpqpVzZ2CRUTciHqIPNiKFfCWOeLEO+9AcLC1eYpi3rZ5bD+2nXKB5Xik2SNWx5GiOHUKkpLMVkTETagg8lBnzkDPnuaO9j16QIcOVicqPMMweG2F2Z0V3zKeMv5lLE4kRfLbbxATY7YiIm5CBZGHeuEF2LbN3HB8zBir0xTNj3t/ZO2BtQTYA3gi9gmr40hRXX21uY/Z1VdbnUREpNA0h8gDJSbCaHOnC6ZMAXfbUeXsNh09mvYgrHSYxWmkyEqV0qauIuJ21EPkYbKz4ZFHIC8P7r8f7rrL6kRFs+XwFr5K/gobNhLiEqyOI5fj4EF45hmzFRFxEyqIPMyrr8LGjVCx4l8Tqt3JG6veAOCe6HuoU6GOxWnkshw7BrNnm62IiJvQkJkH2bz5r6udJ0yASpWszVNUB9IP8N+N/wW0iatba9gQdu+2OoWISJGoh8hD5OaaQ2U5OeYwWefOVicquvFrxpPjyOG6yOuIre4mm62JiIhHUEHkId58E9atg9BQePttcLddLtLOpDFl/RRAm7i6vV9/hQYNzFZExE2oIPIAycnw3HPm/TffNBcKdjfvJL7DyeyTNKjUgFvr3Gp1HLkSISHmwlchIVYnEREpNM0hcnMOh7kA45kzcPPN0L271YmKLis3i3FrxgEwuM1gfGyq091a9eowdqzVKUREikTfPG7u7bfhp5+gTBlzew53GyoD+HDThxw8eZCqwVV5sNGDVseRK3XmjLkq6JkzVicRESk0FURubNcuGDbMvP/aaxAZaW2ey+EwHPmX2g9qPQh/u7/FieSK/fqruUq15hCJiBtRQeSmDAP69IHMTLjuOnjsMasTXZ6F2xfy65FfCQkIoU9MH6vjiDPUrQs//mi2IiJuQnOI3NT06fDddxAUBO+9Bz5uWtq+vuJ1AB6LeYyQAE3C9QhlysA111idQkSkSNz0a9S7HTgACX/uavHSS1C7trV5Ltfq/av5ce+P+Pn4MaD1AKvjiLOkpMCoUWYrIuImVBC5GcMwh8fS06FVKxg40OpEl+/sJq4PNX6IqsFuuFaAXNjhw+ZVZocPW51ERKTQNGTmZj76CL76Cvz9zWEzu93qRJcn+Y9k5m6dC5iX2osHadwYjhyxOoWISJGoh8iNpKbCE0+Y95991lwM2F2NXTUWA4OOdTtSv1J9q+OIiIiXU0HkRp54wtxAvGlTGDrU6jSXLzUjlZkbZgLaxNUj/fYbtGxptiIibkIFkZv4/HP43//MIbLp08HPz+pEl2/C2glk5WXRunprrqmhq5E8TqlS0Ly52YqIuAmXLIgmTZpEVFQUgYGBxMbGsnbt2oseO3PmTGw2W4FbYGBggWMyMjLo168f1atXJygoiPr16zNlypTifhtOc+wYPP64eX/YMGjWzNo8VyIjO4O3170NmJu42txxaW25tBo1YOpUsxURcRMuN6n6k08+ISEhgSlTphAbG8u4cePo0KED27ZtIyws7IKvCQkJYdu2bfmP//4lm5CQwPfff8/s2bOJiorim2++4fHHH6dq1arceeedxfp+nGHQIHP+UHS0OXfInb2X9B7HzxynTvk63FnP9T97uQzZ2eYVZmFh5ux/ERE34HI9RGPHjqV379706NEjvyenVKlSTJ8+/aKvsdlsVKlSJf9WuXLlAj9fuXIl3bp1o127dkRFRdGnTx+aNGlyyZ6nrKws0tPTC9yssHAhvP++uUfZ9OkQEGBJDKfIycth7Gpz08/BbQZj93HTS+Tk0jZvhogIsxURcRMuVRBlZ2eTmJhI+/bt85/z8fGhffv2rFq16qKvy8jIIDIykoiICO666y62bNlS4Odt2rRh/vz5HDhwAMMwWLp0KcnJydx8880XPeeoUaMIDQ3Nv0VERFz5Gyyi9HR49FHz/qBB0Lp1iUdwqk+3fMretL2ElQ6ja5OuVseR4lK7Nixa5L4rhoqIV3Kpgujo0aPk5eWd18NTuXJlUi6y6m29evWYPn068+bNY/bs2TgcDtq0acP+/fvzj5kwYQL169enevXq+Pv7c8sttzBp0iSuu+66i2YZPnw4aWlp+bd9+/Y5500WwVNPwf79cNVV5orU7swwjPyFGAfEDiDQN/AfXiFuKyQEOnQwWxERN+Fyc4iKKi4ujri4uPzHbdq0ITo6mqlTp/LSn1XEhAkTWL16NfPnzycyMpIffviB+Ph4qlatWqA36lwBAQEEWDg+tXSpOS8V4N133f+CnW9//5ZfUn+htF9p+rboa3UcKU6HD8PHH8P995vziERE3IBLFUQVK1bEbreTmppa4PnU1FSqVKlSqHP4+fnRrFkzduzYAcDp06f5z3/+w9y5c7n99tsBaNy4MRs2bOCNN964aEFkpcxM6NXLvN+3L7RrZ2kcpzi7iWvv5r0pF1TO4jRSrA4ehOHD4brrVBCJiNtwqSEzf39/YmJiWLJkSf5zDoeDJUuWFOgFupS8vDw2bdpEeHg4ADk5OeTk5ODzt+3g7XY7DofDeeGd6Jln4PffzXmpr75qdZorl3QoiSW7lmC32RkUN8jqOFLcmjY1q/qmTa1OIiJSaC7VQwTmJfLdunWjRYsWtGrVinHjxpGZmUmPHj0A6Nq1K9WqVWPUqFEAvPjii7Ru3ZratWtz4sQJRo8ezZ49e+j1ZxdLSEgI119/PUOGDCEoKIjIyEiWL1/O+++/z9ixYy17nxezciWMH2/ef+cdz5iGcXbu0P0N76dGqNamERER1+NyBVHnzp05cuQIzz33HCkpKTRt2pRFixblT7Teu3dvgd6e48eP07t3b1JSUihXrhwxMTGsXLmS+vX/2h/r448/Zvjw4XTp0oVjx44RGRnJK6+8wmOPPVbi7+9SzpyBnj3NHe27d4dbbrE60ZXbdXwXn275FNA2HV4jORn69DEr+rp1rU4jIlIoNsMwDKtDuIP09HRCQ0NJS0sjpJi6bf7zHxg1CqpUgV9/hXIeMNWm/9f9mbB2Ah2u6sCihxZZHUdKwq5d5gqiL70ENWtanUZEvFxhv79drofIWyUlwevmvGMmT/aMYujoqaO8m/QuoN4hr1KzJsyebXUKEZEicalJ1d4qOxt69IC8POjcGTp1sjqRc7y97m1O556meXhz/lXzX1bHkZKSm2tuwJeba3USEZFCU0HkAl57DTZuhIoVYcIEq9M4x+mc00xYa74ZbeLqZTZuhAoVzFZExE2oILLY5s1/rUL91ltQqZK1eZxl5oaZHD11lKiyUfy7/r+tjiMlqWZN+OwzzR8SEbeiOUQWys2FRx6BnBy4805zYV9PkOfIY8yqMQA8Gfckvj76Y+ZVypWDe+6xOoWISJGoh8hCNhvcdx+Eh5sTqT1lVGnub3PZeXwnFYIq0KNpD6vjSEk7etTcb+boUauTiIgUmgoiC9ntMHgw7NwJVatancY5DMPI36YjvmU8pf1LW5xIStzevdC7t9mKiLgJjWW4gKAgqxM4z/I9y1l3cB2BvoH0a9XP6jhihebNzdVFRUTciHqIxKnObtPxSNNHqFTaQ2aIi4iIx1NBJE6zKXUTC7cvxMfmQ0JcgtVxxCo7dsDtt5utiIibUEEkTvPGqjcA+Hf0v7mq/FUWpxHL+PhAQIDZioi4Cc0hEqfYl7aPDzd9CGibDq9XqxZ8/rnVKUREikT/hBOnGL9mPLmOXG6IuoGW1VpaHUes5HBAVpbZioi4CRVEcsVOnDnB1MSpgHqHBNiwAQIDzVZExE2oIJIrNmX9FDKyM2gY1pBbat9idRyxWlQUfPCB2YqIuAnNIZIrkpWbxfg14wFt4ip/Kl8eHnrI6hQiIkWiHiK5IrM3ziYlI4XqIdW5v6GHbMYmV+bYMfjoI7MVEXETKojksjkMR/5CjINaD8LP7mdxInEJu3fDgw+arYiIm9CQmVy2r5K/Ytsf2wgNCKV3895WxxFX0aQJZGSYE6tFRNyECiK5bGc3ce3boi/BAcEWpxGXYbdDaW3qKyLuRUNmcllW7lvJin0r8Lf70z+2v9VxxJX8/jvce6/Zioi4CRVEclnOzh3q2rgr4cHhFqcRl5KXB+npZisi4iY0ZCZF9tvR35j32zwAnmzzpMVpxOXUqQOLF1udQkSkSNRDJEU2ZuUYDAzuqncXV1e82uo4IiIiV0wFkRRJSkYK7298H4Cn2j5lcRpxSUlJ4OtrtiIibkIFkRTJW2veIjsvmzYRbWgT0cbqOOKKIiJg0iSzFRFxE5pDJIV2Muskb697GzC36RC5oEqV4NFHrU4hIlIk6iGSQns36V3SstKoV6EeHet1tDqOuKoTJ2D+fLMVEXETKoikUHLychi7eiwAg9sMxsemPzpyEb//DnfdpXWIRMStaMhMCuXjzR+zP30/VcpU4aHG2slcLqFRIzh8GMqWtTqJiEihqSCSf2QYRv5CjANiBxDoqz2q5BL8/Mx5RCIibkTjHvKPFu9czKbDmyjjX4bHWjxmdRxxdbt3Q/fu2u1eRNyKCiL5R2c3ce3TvA9lA8taG0ZcX1YW7NhhtiIibkJDZnJJ6w+uZ+nupfj6+DKw9UCr44g7qFcPfvrJ6hQiIkWiHiK5pLNzhx5s9CARoVpoT0REPJMKIrmoncd2MufXOQAMjhtscRpxGxs2QEiI2YqIuAkVRHJRY1eNxWE4uLX2rTSq3MjqOOIuwsPh+efNVkTETWgOkVzQkcwjzNgwA9AmrlJElStDQoLVKUREisQle4gmTZpEVFQUgYGBxMbGsnbt2oseO3PmTGw2W4FbYOD56+Rs3bqVO++8k9DQUEqXLk3Lli3Zu3dvcb4NtzZp3SRO556mRdUWXB95vdVxxJ2kp8N335mtiIibcLmC6JNPPiEhIYERI0aQlJREkyZN6NChA4cPH77oa0JCQjh06FD+bc+ePQV+vnPnTq655hquvvpqli1bxsaNG3n22WcvWDgJnMo5xcS1EwFzE1ebzWZxInErO3bATTeZrYiIm7AZhmFYHeJcsbGxtGzZkokTzS9kh8NBREQETzzxBMOGDTvv+JkzZzJw4EBOXGIjyfvvvx8/Pz8++OCDy86Vnp5OaGgoaWlphISEXPZ53MGktZPo93U/apWrRXK/ZOw+dqsjiTvJyoJDh8w5RAEBVqcRES9X2O9vl+ohys7OJjExkfbt2+c/5+PjQ/v27Vm1atVFX5eRkUFkZCQRERHcddddbNmyJf9nDoeDBQsWULduXTp06EBYWBixsbF88cUXl8ySlZVFenp6gZs3yHXkMmbVGACejHtSxZAUXUAAREWpGBIRt+JSBdHRo0fJy8ujcuXKBZ6vXLkyKSkpF3xNvXr1mD59OvPmzWP27Nk4HA7atGnD/v37ATh8+DAZGRm8+uqr3HLLLXzzzTfcfffd3HPPPSxfvvyiWUaNGkVoaGj+LSLCO9bg+ezXz9h1YhcVS1Wke9PuVscRd7R3L8THm62IiJtw+6vM4uLiiIuLy3/cpk0boqOjmTp1Ki+99BIOhwOAu+66i0GDBgHQtGlTVq5cyZQpU7j++gtPGB4+fDgJ51wpk56e7vFF0bmbuD7R6glK+ZWyOJG4pcxMWLXKbEVE3IRLFUQVK1bEbreTmppa4PnU1FSqVKlSqHP4+fnRrFkzdvw5obNixYr4+vpSv379AsdFR0fz0yW2FwgICCDAy7r8l+5eSuKhRIJ8g3i85eNWxxF3FR0NSUlWpxARKRKXGjLz9/cnJiaGJUuW5D/ncDhYsmRJgV6gS8nLy2PTpk2E/7konL+/Py1btmTbtm0FjktOTiYyMtJ54T3A2U1cezbrScVSFS1OIyIiUnJcqocIICEhgW7dutGiRQtatWrFuHHjyMzMpEePHgB07dqVatWqMWrUKABefPFFWrduTe3atTlx4gSjR49mz5499OrVK/+cQ4YMoXPnzlx33XXccMMNLFq0iC+//JJly5ZZ8RZd0sbUjSzeuRgfmw8JcVpUT67Axo3QoQMsXgyNG1udRkSkUFyuIOrcuTNHjhzhueeeIyUlhaZNm7Jo0aL8idZ79+7Fx+evjq3jx4/Tu3dvUlJSKFeuHDExMaxcubLAENndd9/NlClTGDVqFP3796devXp89tlnXHPNNSX+/lzV2blD99a/l5rlalqcRtxapUrmpOpKlaxOIiJSaC63DpGr8uR1iPac2MNVb11FnpHH+t7riakaY3UkERERp3DLdYjEGuNWjyPPyOPGmjeqGJIrl5FhXmWWkWF1EhGRQlNB5OWOnz7OtKRpAAxpM8TiNOIRkpOhTRuzFRFxEy43h0hK1uT1k8nMyaRx5cbcfNXNVscRTxAdDZs3Q61aVicRESk0FURe7EzuGd5a8xagTVzFiYKCoEEDq1OIiBSJhsy82Ae/fEBqZio1QmtwX4P7rI4jnmL/fhgyxGxFRNyECiIvlefI441VbwAwqPUg/Ox+FicSj5GWBvPnm62IiJvQkJmXmr9tPsl/JFMusBy9mvf65xeIFFaDBvC3leFFRFydeoi8kGEYvL7S3Kbj8ZaPU8a/jMWJRERErKWCyAut2LeC1ftXE2AP4IlWT1gdRzzNli1Qu7bZioi4CRVEXujsJq7dmnSjcpnKFqcRj1O2LNx7r9mKiLgJzSHyMluPbOXL5C+xYePJNk9aHUc8UbVq8OfmyyIi7kI9RF7mjZXmlWWdru5E3Qp1LU4jHun0aXPH+9OnrU4iIlJoKoi8yMGTB/lg4wcAPNX2KYvTiMfauhWaNDFbERE3oYLIi7y15i1yHDlcW+NaWldvbXUc8VT16sHatWYrIuImNIfIS6RnpTN5/WRAm7hKMStdGlq2tDqFiEiRqIfIS7yT+A7pWelEV4zm9rq3Wx1HPNmhQ/D882YrIuImVBB5gey8bMatHgeYvUM+Nv1nl2J09Ci8+67Zioi4CQ2ZeYGPNn3EgZMHCC8TzoONHrQ6jni6Ro20sauIuB11FXg4h+Fg9MrRAAxsPZAA3wCLE4mIiLgeFUQe7uvtX7PlyBaC/YN5NOZRq+OIN/j1V2jc2GxFRNyECiIPd7Z36NGYRwkNDLU4jXiF4GBo185sRUTchOYQebA1+9ewfM9y/Hz8GNB6gNVxxFtERMBbb1mdQkSkSNRD5MHO9g51adyF6iHVLU4jXuPMGdixw2xFRNyECiIPtePYDj7f+jkAg+MGW5xGvMqvv0KdOppDJCJuRQWRhxqzcgwGBrfXuZ0GYQ2sjiPepE4dWLrUbEVE3ITmEHmgw5mHmbFhBqBNXMUCZydVi4i4EfUQeaCJayeSlZdFbLVYrq1xrdVxxNukpsLo0WYrIuImVBB5mIzsDCaunQiY23TYbDaLE4nXSUmBUaPMVkTETWjIzMNM/3k6x88cp3b52nS6upPVccQbNWkCx45ZnUJEpEjUQ+RBch25jF01FjCvLLP72C1OJCIi4h5UEHmQ/235H3vS9lCpVCW6NulqdRzxVtu2QVyc2YqIuAkVRB7CMAxeX/k6AP1j+xPkF2RxIvFagYHQoIHZioi4Cc0h8hBLdi1hQ8oGSvmV4vGWj1sdR7xZZCS8+67VKUREikQ9RB7i9RVm71CvZr0oH1Te4jTi1XJy4NAhsxURcRMqiDzAz4d+5tvfv8VuszMobpDVccTbbdoEVauarYiIm1BB5AHeWPUGAJ0bdiaqbJS1YUSuugq++spsRUTchOYQubndJ3bzyeZPAHMhRhHLhYbC7bdbnUJEpEjUQ+Tm3lz1JnlGHjfVuommVZpaHUcEjhyBSZPMVkTETaggcmN/nPqDd382r+bRJq7iMvbvh4QEsxURcRMuWRBNmjSJqKgoAgMDiY2NZe3atRc9dubMmdhstgK3wEusf/LYY49hs9kYN25cMSQvWZPXT+ZUzimaVmnKjTVvtDqOiKlZM8jKMlsRETfhcgXRJ598QkJCAiNGjCApKYkmTZrQoUMHDh8+fNHXhISEcOjQofzbnj17Lnjc3LlzWb16NVWrVi2u+CXmdM5p3lrzFgBPtXlKm7iKiIhcAZcriMaOHUvv3r3p0aMH9evXZ8qUKZQqVYrp06df9DU2m40qVark3ypXrnzeMQcOHOCJJ57gv//9L35+fv+YIysri/T09AI3VzLrl1kcOXWEyNBI7m1wr9VxRP6yfTu0b2+2IiJuwqUKouzsbBITE2nfvn3+cz4+PrRv355Vq1Zd9HUZGRlERkYSERHBXXfdxZYtWwr83OFw8PDDDzNkyBAaNGhQqCyjRo0iNDQ0/xYREXF5b6oY5DnyGLNqDAAJcQn4+uhiQXEhvr5QqZLZioi4CZcqiI4ePUpeXt55PTyVK1cmJSXlgq+pV68e06dPZ968ecyePRuHw0GbNm3Yf86Eztdeew1fX1/69+9f6CzDhw8nLS0t/7Zv377Le1PF4IvfvmDHsR2UDypPz2Y9rY4jUlDNmvDRR2YrIuIm3P6fcHFxccTFxeU/btOmDdHR0UydOpWXXnqJxMRExo8fT1JSUpHm2QQEBBAQEFAcka/IuZu4xreMp7R/aYsTifxNXh5kZkLp0mC3W51GRKRQXKqHqGLFitjtdlJTUws8n5qaSpUqVQp1Dj8/P5o1a8aOHTsA+PHHHzl8+DA1atTA19cXX19f9uzZw5NPPklUVJSz30Kx+3Hvj6w9sJZA30D6tepndRyR8/3yi7k44y+/WJ1ERKTQXKog8vf3JyYmhiVLluQ/53A4WLJkSYFeoEvJy8tj06ZNhIeHA/Dwww+zceNGNmzYkH+rWrUqQ4YMYfHixcXyPorT2U1cuzfpTljpMIvTiFxAzZrw6acaMhMRt+JyQ2YJCQl069aNFi1a0KpVK8aNG0dmZiY9evQAoGvXrlSrVo1Ro0YB8OKLL9K6dWtq167NiRMnGD16NHv27KFXr14AVKhQgQoVKhT4HX5+flSpUoV69eqV7Ju7QlsOb2HB9gXYsPFkmyetjiNyYeXKwb268lFE3IvLFUSdO3fmyJEjPPfcc6SkpNC0aVMWLVqUP9F67969+Pj81bF1/PhxevfuTUpKCuXKlSMmJoaVK1dSv359q95CsTm7ieu/6/+b2uVrW5xG5CL++AO+/BI6doS//WNERMRV2QzDMKwO4Q7S09MJDQ0lLS2NkJCQEv/9+9P3U2t8LXIcOazptYZW1VqVeAaRQklKgpgYSEyE5s2tTiMiXq6w398u10MkFzZ+9XhyHDlcH3m9iiFxbc2aQU6OrjATEbeigsgNpJ1JY2riVECbuIobsNm0KKOIuB2XuspMLmxq4lROZp+kQaUG3Fr7VqvjiFzazp1w551mKyLiJlQQubis3CzGrR4HwJA2Q7SJq4iISDFQv7aL+3DThxzKOES14Go80OgBq+OI/LOrroL5861OISJSJOohcmEOw8HolaMBGNh6IP52f4sTiRSCYUBurtmKiLgJFUQubEHyArYe3UpIQAh9YvpYHUekcH7+Gfz8zFZExE2oIHJhZzdx7duiLyEBJb/2kchliYyEGTPMVkTETWgOkYtatW8VP+39CT8fP/rH9rc6jkjhVagA3btbnUJEpEjUQ+Sizs4derjxw1QNrmpxGpEiOH4c/vc/sxURcRMqiFxQ8h/JfPHbFwAMbjPY2jAiRbVrF9x3n9mKiLgJDZm5oDErx2Bg0LFuR6IrRVsdR6RomjSBtDQoXdrqJCIihaaCyMWkZKQw65dZgLbpEDdlt4MFGyCLiFwJDZm5mAlrJpCVl0Vc9TjaRrS1Oo5I0e3aBQ88oCEzEXErKohcSEZ2Bm+vfxvQNh3ixnJz4cgRsxURcRMaMnMh7ya9y4kzJ6hboS531rvT6jgil6dOHfjuO6tTiIgUiXqIXEROXg5jV40FYHDcYOw+dosTiYiIeA8VRC7i0y2fsi99H5VLV+bhJg9bHUfk8v38MwQEaOsOEXErKohcgGEY+dt09I/tT6BvoMWJRK5A9eowdqzZioi4Cc0hcgHf7PyGjakbKe1Xmr4t+lodR+TKVKoE8fFWpxARKRL1ELmAs9t09InpQ7mgchanEblCaWmwYIHZioi4CRVEFks8mMiSXUuw2+wMbD3Q6jgiV27nTrjjDrMVEXETGjKz2NneoQcaPUCN0BoWpxFxgkaN4OBBqFjR6iQiIoWmgshCeY48zuSewYaNIW2GWB1HxDn8/CA83OoUIiJFoiEzC9l97Hxx/xf8PuB3GldubHUcEefYswd69TJbERE3oYLIBUSVjbI6gojznDkDW7aYrYiIm9CQmYg4V716sGqV1SlERIpEPUQiIiLi9VQQiYhz/fILlC9vtiIibkIFkYg4V5UqMHy42YqIuAnNIRIR56pcGYZoGQkRcS/qIRIR5zp5EpYtM1sRETehgkhEnGv7drjhBrMVEXETGjITEeeqX98shqpXtzqJiEihqSASEecKDITata1OISJSJBoyExHn2rcP+vc3WxERN6GCSEScS5OqRcQNachMRJyrfn3YuNHqFCIiRaIeIhEREfF66iEqJMMwAEhPT7c4iYiL27IF/v1v+OwzaNDA6jQi4uXOfm+f/R6/GBVEhXTyz/kQERERFicRcRNt2lidQEQk38mTJwkNDb3oz23GP5VMAoDD4eDgwYMEBwdjs9mcdt709HQiIiLYt28fISEhTjuvFKTPueTosy4Z+pxLhj7nklGcn7NhGJw8eZKqVavi43PxmULqISokHx8fqhfjQnMhISH6n60E6HMuOfqsS4Y+55Khz7lkFNfnfKmeobM0qVpERES8ngoiERER8XoqiCwWEBDAiBEjCAgIsDqKR9PnXHL0WZcMfc4lQ59zyXCFz1mTqkVERMTrqYdIREREvJ4KIhEREfF6KohERETE66kgEhEREa+ngsgiP/zwAx07dqRq1arYbDa++OILqyN5pFGjRtGyZUuCg4MJCwujU6dObNu2zepYHmfy5Mk0btw4f1G1uLg4vv76a6tjebxXX30Vm83GwIEDrY7icZ5//nlsNluB29VXX211LI904MABHnroISpUqEBQUBCNGjVi/fr1JZ5DBZFFMjMzadKkCZMmTbI6ikdbvnw58fHxrF69mm+//ZacnBxuvvlmMjMzrY7mUapXr86rr75KYmIi69ev51//+hd33XUXW7ZssTqax1q3bh1Tp06lcePGVkfxWA0aNODQoUP5t59++snqSB7n+PHjtG3bFj8/P77++mt+/fVXxowZQ7ly5Uo8i7busMitt97KrbfeanUMj7do0aICj2fOnElYWBiJiYlcd911FqXyPB07dizw+JVXXmHy5MmsXr2aBtrx3ukyMjLo0qUL06ZN4+WXX7Y6jsfy9fWlSpUqVsfwaK+99hoRERHMmDEj/7maNWtakkU9ROJV0tLSAChfvrzFSTxXXl4eH3/8MZmZmcTFxVkdxyPFx8dz++230759e6ujeLTt27dTtWpVatWqRZcuXdi7d6/VkTzO/PnzadGiBffeey9hYWE0a9aMadOmWZJFPUTiNRwOBwMHDqRt27Y0bNjQ6jgeZ9OmTcTFxXHmzBnKlCnD3LlzqV+/vtWxPM7HH39MUlIS69atszqKR4uNjWXmzJnUq1ePQ4cO8cILL3DttdeyefNmgoODrY7nMX7//XcmT55MQkIC//nPf1i3bh39+/fH39+fbt26lWgWFUTiNeLj49m8ebPmARSTevXqsWHDBtLS0pgzZw7dunVj+fLlKoqcaN++fQwYMIBvv/2WwMBAq+N4tHOnNDRu3JjY2FgiIyP59NNP6dmzp4XJPIvD4aBFixaMHDkSgGbNmrF582amTJlS4gWRhszEK/Tr14+vvvqKpUuXUr16davjeCR/f39q165NTEwMo0aNokmTJowfP97qWB4lMTGRw4cP07x5c3x9ffH19WX58uW89dZb+Pr6kpeXZ3VEj1W2bFnq1q3Ljh07rI7iUcLDw8/7R1N0dLQlw5PqIRKPZhgGTzzxBHPnzmXZsmWWTdbzRg6Hg6ysLKtjeJQbb7yRTZs2FXiuR48eXH311QwdOhS73W5RMs+XkZHBzp07efjhh62O4lHatm173lIoycnJREZGlngWFUQWycjIKPAvjV27drFhwwbKly9PjRo1LEzmWeLj4/nwww+ZN28ewcHBpKSkABAaGkpQUJDF6TzH8OHDufXWW6lRowYnT57kww8/ZNmyZSxevNjqaB4lODj4vPlvpUuXpkKFCpoX52SDBw+mY8eOREZGcvDgQUaMGIHdbueBBx6wOppHGTRoEG3atGHkyJHcd999rF27lnfeeYd33nmn5MMYYomlS5cawHm3bt26WR3No1zoMwaMGTNmWB3NozzyyCNGZGSk4e/vb1SqVMm48cYbjW+++cbqWF7h+uuvNwYMGGB1DI/TuXNnIzw83PD39zeqVatmdO7c2dixY4fVsTzSl19+aTRs2NAICAgwrr76auOdd96xJIfNMAyj5MswEREREdehSdUiIiLi9VQQiYiIiNdTQSQiIiJeTwWRiIiIeD0VRCIiIuL1VBCJiIiI11NBJCIiIl5PBZGIiIh4PRVEIlLsZs6cSdmyZa2OUSjPP/88TZs2LdJrbDYbX3zxRbHk+bt27doxcODAEvldIt5EBZGIyDkGDx7MkiVLrI4hIiVMm7uKiJyjTJkylClTxtIMhmGQl5eHr6/z/4rOy8vDZrPh46N/D4ucS/9HiMgltWvXjn79+tGvXz9CQ0OpWLEizz77LOdug3j8+HG6du1KuXLlKFWqFLfeeivbt2+/4Pl2796Nj48P69evL/D8uHHjiIyMxOFwsGzZMmw2G0uWLKFFixaUKlWKNm3asG3btgKvmTx5MldddRX+/v7Uq1ePDz74oMDPbTYbU6dO5Y477qBUqVJER0ezatUqduzYQbt27ShdujRt2rRh586d+a/5+5DZunXruOmmm6hYsSKhoaFcf/31JCUlFekzzMrKon///oSFhREYGMg111zDunXr8n9+9v1+/fXXxMTEEBAQwE8//URmZiZdu3alTJkyhIeHM2bMmAuee/DgwVSrVo3SpUsTGxvLsmXL8n9+drhy/vz51K9fn4CAAPbu3Vuk/CLeQAWRiPyjWbNm4evry9q1axk/fjxjx47l3Xffzf959+7dWb9+PfPnz2fVqlUYhsFtt91GTk7OeeeKioqiffv2zJgxo8DzM2bMoHv37gV6Lp5++mnGjBnD+vXr8fX15ZFHHsn/2dy5cxkwYABPPvkkmzdv5tFHH6VHjx4sXbq0wHlfeuklunbtyoYNG7j66qt58MEHefTRRxk+fDjr16/HMAz69et30fd+8uRJunXrxk8//cTq1aupU6cOt912GydPniz05/fUU0/x2WefMWvWLJKSkqhduzYdOnTg2LFjBY4bNmwYr776Klu3bqVx48YMGTKE5cuXM2/ePL755huWLVt2XjHWr18/Vq1axccff8zGjRu59957ueWWWwoUpKdOneK1117j3XffZcuWLYSFhRU6u4jXMERELuH66683oqOjDYfDkf/c0KFDjejoaMMwDCM5OdkAjBUrVuT//OjRo0ZQUJDx6aefGoZhGDNmzDBCQ0Pzf/7JJ58Y5cqVM86cOWMYhmEkJiYaNpvN2LVrl2EYhrF06VIDML777rv81yxYsMAAjNOnTxuGYRht2rQxevfuXSDrvffea9x22235jwHjmWeeyX+8atUqAzDee++9/Oc++ugjIzAwMP/xiBEjjCZNmlz088jLyzOCg4ONL7/8ssDvmTt37gWPz8jIMPz8/Iz//ve/+c9lZ2cbVatWNV5//fUC7/eLL77IP+bkyZOGv79//mdoGIbxxx9/GEFBQcaAAQMMwzCMPXv2GHa73Thw4ECB33njjTcaw4cPNwzD/OwBY8OGDRd9TyJiGOohEpF/1Lp1a2w2W/7juLg4tm/fTl5eHlu3bsXX15fY2Nj8n1eoUIF69eqxdevWC56vU6dO2O125s6dC5jDOjfccANRUVEFjmvcuHH+/fDwcAAOHz4MwNatW2nbtm2B49u2bXve7zz3HJUrVwagUaNGBZ47c+YM6enpF8yamppK7969qVOnDqGhoYSEhJCRkVHoYaedO3eSk5NTIKufnx+tWrU6L2uLFi0KvC47O7vA51q+fHnq1auX/3jTpk3k5eVRt27d/LlPZcqUYfny5QWGAf39/Qt8DiJyPk2qFpES5+/vT9euXZkxYwb33HMPH374IePHjz/vOD8/v/z7Zwsyh8NRpN91oXMU5bzdunXjjz/+YPz48URGRhIQEEBcXBzZ2dlFylEYpUuXLtLxGRkZ2O12EhMTsdvtBX527sTwoKCgAgWtiJxPPUQi8o/WrFlT4PHZuTR2u53o6Ghyc3MLHPPHH3+wbds26tevf9Fz9urVi++++463336b3Nxc7rnnniJlio6OZsWKFQWeW7FixSV/5+VYsWIF/fv357bbbqNBgwYEBARw9OjRQr/+7KTvc7Pm5OSwbt26S2a96qqr8PPzK/C5Hj9+nOTk5PzHzZo1Iy8vj8OHD1O7du0CtypVqhTxnYp4N/UQicg/2rt3LwkJCTz66KMkJSUxYcKE/Cue6tSpw1133UXv3r2ZOnUqwcHBDBs2jGrVqnHXXXdd9JzR0dG0bt2aoUOH8sgjjxAUFFSkTEOGDOG+++6jWbNmtG/fni+//JLPP/+c77777ore69/VqVOHDz74gBYtWpCens6QIUOKlLV06dL07duXIUOGUL58eWrUqMHrr7/OqVOn6Nmz50VfV6ZMGXr27MmQIUOoUKECYWFhPP300wUmndetW5cuXbrQtWtXxowZQ7NmzThy5AhLliyhcePG3H777Vf03kW8iQoiEflHXbt25fTp07Rq1Qq73c6AAQPo06dP/s9nzJjBgAEDuOOOO8jOzua6665j4cKFBYamLqRnz56sXLmywNVjhdWpUyfGjx/PG2+8wYABA6hZsyYzZsygXbt2RT7Xpbz33nv06dOH5s2bExERwciRIxk8eHCRzvHqq6/icDh4+OGHOXnyJC1atGDx4sWUK1fukq8bPXo0GRkZdOzYkeDgYJ588knS0tIKHDNjxgxefvllnnzySQ4cOEDFihVp3bo1d9xxR5Hfq4g3sxnGOYuJiIj8Tbt27WjatCnjxo1z+rlfeukl/ve//7Fx40ann1tEpCg0h0hESlxGRgabN29m4sSJPPHEE1bHERFRQSQiJa9fv37ExMTQrl27yxouExFxNg2ZiYiIiNdTD5GIiIh4PRVEIiIi4vVUEImIiIjXU0EkIiIiXk8FkYiIiHg9FUQiIiLi9VQQiYiIiNdTQSQiIiJe7/8BXOaye6EgvvsAAAAASUVORK5CYII=",
- "text/plain": [
- "<Figure size 640x480 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"statsmodels_material.illustration_R2_poly(x, y, x_test, y_test)"
]
@@ -5757,81 +2403,12 @@
},
{
"cell_type": "code",
- "execution_count": 93,
+ "execution_count": null,
"id": "43ac886e",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
- "\n",
- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>R2</th>\n",
- " <th>R2_adjusted</th>\n",
- " <th>log-likelihood</th>\n",
- " <th>AIC</th>\n",
- " <th>BIC</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>1</th>\n",
- " <td>0.574957</td>\n",
- " <td>0.570619</td>\n",
- " <td>-218.166948</td>\n",
- " <td>440.333896</td>\n",
- " <td>445.544236</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2</th>\n",
- " <td>0.630454</td>\n",
- " <td>0.622834</td>\n",
- " <td>-211.171153</td>\n",
- " <td>428.342307</td>\n",
- " <td>436.157817</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>6</th>\n",
- " <td>0.663161</td>\n",
- " <td>0.641430</td>\n",
- " <td>-206.537608</td>\n",
- " <td>427.075215</td>\n",
- " <td>445.311406</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " R2 R2_adjusted log-likelihood AIC BIC\n",
- "1 0.574957 0.570619 -218.166948 440.333896 445.544236\n",
- "2 0.630454 0.622834 -211.171153 428.342307 436.157817\n",
- "6 0.663161 0.641430 -206.537608 427.075215 445.311406"
- ]
- },
- "execution_count": 93,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"scores"
]
@@ -5864,23 +2441,12 @@
},
{
"cell_type": "code",
- "execution_count": 94,
+ "execution_count": null,
"id": "60322cd4",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "image/png": "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",
- "text/plain": [
- "<Figure size 640x480 with 1 Axes>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
+ "outputs": [],
"source": [
"statsmodels_material.illustration_AIC_BIC_poly(x, y)"
]
@@ -5979,7 +2545,7 @@
},
{
"cell_type": "code",
- "execution_count": 95,
+ "execution_count": null,
"id": "c906df73",
"metadata": {
"hidden": true
@@ -6018,7 +2584,7 @@
},
{
"cell_type": "code",
- "execution_count": 96,
+ "execution_count": null,
"id": "42165fc7",
"metadata": {
"hidden": true
@@ -6053,7 +2619,7 @@
},
{
"cell_type": "code",
- "execution_count": 97,
+ "execution_count": null,
"id": "fcf2d971",
"metadata": {
"hidden": true
@@ -6076,7 +2642,7 @@
},
{
"cell_type": "code",
- "execution_count": 98,
+ "execution_count": null,
"id": "9c495f24",
"metadata": {
"hidden": true
@@ -6111,281 +2677,25 @@
},
{
"cell_type": "code",
- "execution_count": 99,
+ "execution_count": null,
"id": "01e6b10d-fc3a-4fe8-9f94-b3ff3a1278ea",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
- "\n",
- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>PassengerId</th>\n",
- " <th>Survived</th>\n",
- " <th>Pclass</th>\n",
- " <th>Name</th>\n",
- " <th>Sex</th>\n",
- " <th>Age</th>\n",
- " <th>SibSp</th>\n",
- " <th>Parch</th>\n",
- " <th>Ticket</th>\n",
- " <th>Fare</th>\n",
- " <th>Cabin</th>\n",
- " <th>Embarked</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>0</th>\n",
- " <td>1</td>\n",
- " <td>0</td>\n",
- " <td>3</td>\n",
- " <td>Braund, Mr. Owen Harris</td>\n",
- " <td>male</td>\n",
- " <td>22.0</td>\n",
- " <td>1</td>\n",
- " <td>0</td>\n",
- " <td>A/5 21171</td>\n",
- " <td>7.2500</td>\n",
- " <td>NaN</td>\n",
- " <td>S</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1</th>\n",
- " <td>2</td>\n",
- " <td>1</td>\n",
- " <td>1</td>\n",
- " <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
- " <td>female</td>\n",
- " <td>38.0</td>\n",
- " <td>1</td>\n",
- " <td>0</td>\n",
- " <td>PC 17599</td>\n",
- " <td>71.2833</td>\n",
- " <td>C85</td>\n",
- " <td>C</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2</th>\n",
- " <td>3</td>\n",
- " <td>1</td>\n",
- " <td>3</td>\n",
- " <td>Heikkinen, Miss. Laina</td>\n",
- " <td>female</td>\n",
- " <td>26.0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>STON/O2. 3101282</td>\n",
- " <td>7.9250</td>\n",
- " <td>NaN</td>\n",
- " <td>S</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>3</th>\n",
- " <td>4</td>\n",
- " <td>1</td>\n",
- " <td>1</td>\n",
- " <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
- " <td>female</td>\n",
- " <td>35.0</td>\n",
- " <td>1</td>\n",
- " <td>0</td>\n",
- " <td>113803</td>\n",
- " <td>53.1000</td>\n",
- " <td>C123</td>\n",
- " <td>S</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>4</th>\n",
- " <td>5</td>\n",
- " <td>0</td>\n",
- " <td>3</td>\n",
- " <td>Allen, Mr. William Henry</td>\n",
- " <td>male</td>\n",
- " <td>35.0</td>\n",
- " <td>0</td>\n",
- " <td>0</td>\n",
- " <td>373450</td>\n",
- " <td>8.0500</td>\n",
- " <td>NaN</td>\n",
- " <td>S</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " PassengerId Survived Pclass \\\n",
- "0 1 0 3 \n",
- "1 2 1 1 \n",
- "2 3 1 3 \n",
- "3 4 1 1 \n",
- "4 5 0 3 \n",
- "\n",
- " Name Sex Age SibSp \\\n",
- "0 Braund, Mr. Owen Harris male 22.0 1 \n",
- "1 Cumings, Mrs. John Bradley (Florence Briggs Th... female 38.0 1 \n",
- "2 Heikkinen, Miss. Laina female 26.0 0 \n",
- "3 Futrelle, Mrs. Jacques Heath (Lily May Peel) female 35.0 1 \n",
- "4 Allen, Mr. William Henry male 35.0 0 \n",
- "\n",
- " Parch Ticket Fare Cabin Embarked \n",
- "0 0 A/5 21171 7.2500 NaN S \n",
- "1 0 PC 17599 71.2833 C85 C \n",
- "2 0 STON/O2. 3101282 7.9250 NaN S \n",
- "3 0 113803 53.1000 C123 S \n",
- "4 0 373450 8.0500 NaN S "
- ]
- },
- "execution_count": 99,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "df = pd.read_csv('data/titanic.csv')\n",
+ "outputs": [],
+ "source": [
+ "df = pd.read_csv('../data/titanic.csv')\n",
"df.head()"
]
},
{
"cell_type": "code",
- "execution_count": 100,
+ "execution_count": null,
"id": "e959c8a9",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<table class=\"simpletable\">\n",
- "<caption>Generalized Linear Model Regression Results</caption>\n",
- "<tr>\n",
- " <th>Dep. Variable:</th> <td>Survived</td> <th> No. Observations: </th> <td> 714</td> \n",
- "</tr>\n",
- "<tr>\n",
- " <th>Model:</th> <td>GLM</td> <th> Df Residuals: </th> <td> 709</td> \n",
- "</tr>\n",
- "<tr>\n",
- " <th>Model Family:</th> <td>Binomial</td> <th> Df Model: </th> <td> 4</td> \n",
- "</tr>\n",
- "<tr>\n",
- " <th>Link Function:</th> <td>Logit</td> <th> Scale: </th> <td> 1.0000</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Method:</th> <td>IRLS</td> <th> Log-Likelihood: </th> <td> -323.64</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Date:</th> <td>Mon, 21 Aug 2023</td> <th> Deviance: </th> <td> 647.28</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Time:</th> <td>16:37:53</td> <th> Pearson chi2: </th> <td> 767.</td> \n",
- "</tr>\n",
- "<tr>\n",
- " <th>No. Iterations:</th> <td>5</td> <th> Pseudo R-squ. (CS):</th> <td>0.3587</td> \n",
- "</tr>\n",
- "<tr>\n",
- " <th>Covariance Type:</th> <td>nonrobust</td> <th> </th> <td> </td> \n",
- "</tr>\n",
- "</table>\n",
- "<table class=\"simpletable\">\n",
- "<tr>\n",
- " <td></td> <th>coef</th> <th>std err</th> <th>z</th> <th>P>|z|</th> <th>[0.025</th> <th>0.975]</th> \n",
- "</tr>\n",
- "<tr>\n",
- " <th>Intercept</th> <td> 3.7770</td> <td> 0.401</td> <td> 9.416</td> <td> 0.000</td> <td> 2.991</td> <td> 4.563</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>C(Pclass)[T.2]</th> <td> -1.3098</td> <td> 0.278</td> <td> -4.710</td> <td> 0.000</td> <td> -1.855</td> <td> -0.765</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>C(Pclass)[T.3]</th> <td> -2.5806</td> <td> 0.281</td> <td> -9.169</td> <td> 0.000</td> <td> -3.132</td> <td> -2.029</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>C(Sex)[T.male]</th> <td> -2.5228</td> <td> 0.207</td> <td> -12.164</td> <td> 0.000</td> <td> -2.929</td> <td> -2.116</td>\n",
- "</tr>\n",
- "<tr>\n",
- " <th>Age</th> <td> -0.0370</td> <td> 0.008</td> <td> -4.831</td> <td> 0.000</td> <td> -0.052</td> <td> -0.022</td>\n",
- "</tr>\n",
- "</table>"
- ],
- "text/latex": [
- "\\begin{center}\n",
- "\\begin{tabular}{lclc}\n",
- "\\toprule\n",
- "\\textbf{Dep. Variable:} & Survived & \\textbf{ No. Observations: } & 714 \\\\\n",
- "\\textbf{Model:} & GLM & \\textbf{ Df Residuals: } & 709 \\\\\n",
- "\\textbf{Model Family:} & Binomial & \\textbf{ Df Model: } & 4 \\\\\n",
- "\\textbf{Link Function:} & Logit & \\textbf{ Scale: } & 1.0000 \\\\\n",
- "\\textbf{Method:} & IRLS & \\textbf{ Log-Likelihood: } & -323.64 \\\\\n",
- "\\textbf{Date:} & Mon, 21 Aug 2023 & \\textbf{ Deviance: } & 647.28 \\\\\n",
- "\\textbf{Time:} & 16:37:53 & \\textbf{ Pearson chi2: } & 767. \\\\\n",
- "\\textbf{No. Iterations:} & 5 & \\textbf{ Pseudo R-squ. (CS):} & 0.3587 \\\\\n",
- "\\textbf{Covariance Type:} & nonrobust & \\textbf{ } & \\\\\n",
- "\\bottomrule\n",
- "\\end{tabular}\n",
- "\\begin{tabular}{lcccccc}\n",
- " & \\textbf{coef} & \\textbf{std err} & \\textbf{z} & \\textbf{P$> |$z$|$} & \\textbf{[0.025} & \\textbf{0.975]} \\\\\n",
- "\\midrule\n",
- "\\textbf{Intercept} & 3.7770 & 0.401 & 9.416 & 0.000 & 2.991 & 4.563 \\\\\n",
- "\\textbf{C(Pclass)[T.2]} & -1.3098 & 0.278 & -4.710 & 0.000 & -1.855 & -0.765 \\\\\n",
- "\\textbf{C(Pclass)[T.3]} & -2.5806 & 0.281 & -9.169 & 0.000 & -3.132 & -2.029 \\\\\n",
- "\\textbf{C(Sex)[T.male]} & -2.5228 & 0.207 & -12.164 & 0.000 & -2.929 & -2.116 \\\\\n",
- "\\textbf{Age} & -0.0370 & 0.008 & -4.831 & 0.000 & -0.052 & -0.022 \\\\\n",
- "\\bottomrule\n",
- "\\end{tabular}\n",
- "%\\caption{Generalized Linear Model Regression Results}\n",
- "\\end{center}"
- ],
- "text/plain": [
- "<class 'statsmodels.iolib.summary.Summary'>\n",
- "\"\"\"\n",
- " Generalized Linear Model Regression Results \n",
- "==============================================================================\n",
- "Dep. Variable: Survived No. Observations: 714\n",
- "Model: GLM Df Residuals: 709\n",
- "Model Family: Binomial Df Model: 4\n",
- "Link Function: Logit Scale: 1.0000\n",
- "Method: IRLS Log-Likelihood: -323.64\n",
- "Date: Mon, 21 Aug 2023 Deviance: 647.28\n",
- "Time: 16:37:53 Pearson chi2: 767.\n",
- "No. Iterations: 5 Pseudo R-squ. (CS): 0.3587\n",
- "Covariance Type: nonrobust \n",
- "==================================================================================\n",
- " coef std err z P>|z| [0.025 0.975]\n",
- "----------------------------------------------------------------------------------\n",
- "Intercept 3.7770 0.401 9.416 0.000 2.991 4.563\n",
- "C(Pclass)[T.2] -1.3098 0.278 -4.710 0.000 -1.855 -0.765\n",
- "C(Pclass)[T.3] -2.5806 0.281 -9.169 0.000 -3.132 -2.029\n",
- "C(Sex)[T.male] -2.5228 0.207 -12.164 0.000 -2.929 -2.116\n",
- "Age -0.0370 0.008 -4.831 0.000 -0.052 -0.022\n",
- "==================================================================================\n",
- "\"\"\""
- ]
- },
- "execution_count": 100,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"model = smf.glm('Survived ~ Age + C(Pclass) + C(Sex)', df, family=sm.families.Binomial())\n",
"model = model.fit()\n",
@@ -6404,23 +2714,12 @@
},
{
"cell_type": "code",
- "execution_count": 101,
+ "execution_count": null,
"id": "797dabea",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "657.2831255018241"
- ]
- },
- "execution_count": 101,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"model.aic"
]
@@ -6469,117 +2768,12 @@
},
{
"cell_type": "code",
- "execution_count": 102,
+ "execution_count": null,
"id": "bea2319c",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
- "\n",
- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>Subject</th>\n",
- " <th>Time</th>\n",
- " <th>Metric</th>\n",
- " <th>Performance</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>0</th>\n",
- " <td>1</td>\n",
- " <td>Pre</td>\n",
- " <td>Product</td>\n",
- " <td>13</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1</th>\n",
- " <td>2</td>\n",
- " <td>Pre</td>\n",
- " <td>Product</td>\n",
- " <td>12</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>10</th>\n",
- " <td>1</td>\n",
- " <td>Pre</td>\n",
- " <td>Client</td>\n",
- " <td>12</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>11</th>\n",
- " <td>2</td>\n",
- " <td>Pre</td>\n",
- " <td>Client</td>\n",
- " <td>19</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>20</th>\n",
- " <td>1</td>\n",
- " <td>Pre</td>\n",
- " <td>Action</td>\n",
- " <td>17</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>21</th>\n",
- " <td>2</td>\n",
- " <td>Pre</td>\n",
- " <td>Action</td>\n",
- " <td>18</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>30</th>\n",
- " <td>1</td>\n",
- " <td>Post</td>\n",
- " <td>Product</td>\n",
- " <td>18</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>31</th>\n",
- " <td>2</td>\n",
- " <td>Post</td>\n",
- " <td>Product</td>\n",
- " <td>6</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " Subject Time Metric Performance\n",
- "0 1 Pre Product 13\n",
- "1 2 Pre Product 12\n",
- "10 1 Pre Client 12\n",
- "11 2 Pre Client 19\n",
- "20 1 Pre Action 17\n",
- "21 2 Pre Action 18\n",
- "30 1 Post Product 18\n",
- "31 2 Post Product 6"
- ]
- },
- "execution_count": 102,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"import pingouin as pg\n",
"\n",
@@ -6614,108 +2808,24 @@
},
{
"cell_type": "code",
- "execution_count": 103,
+ "execution_count": null,
"id": "a7df0d24",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "/tmp/ipykernel_2421/2299974535.py:1: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead.\n",
- " pg.sphericity(data, dv='Performance', subject='Subject', within=['Time', 'Metric'])\n"
- ]
- },
- {
- "data": {
- "text/plain": [
- "SpherResults(spher=True, W=0.6247989838343564, chi2=3.762602454747652, dof=2, pval=0.15239168046050933)"
- ]
- },
- "execution_count": 103,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"pg.sphericity(data, dv='Performance', subject='Subject', within=['Time', 'Metric'])"
]
},
{
"cell_type": "code",
- "execution_count": 104,
+ "execution_count": null,
"id": "6a8362eb",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
- "\n",
- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>F Value</th>\n",
- " <th>Num DF</th>\n",
- " <th>Den DF</th>\n",
- " <th>Pr > F</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>Time</th>\n",
- " <td>33.85228</td>\n",
- " <td>1.0</td>\n",
- " <td>9.0</td>\n",
- " <td>0.000254</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>Metric</th>\n",
- " <td>26.95919</td>\n",
- " <td>2.0</td>\n",
- " <td>18.0</td>\n",
- " <td>0.000004</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>Time:Metric</th>\n",
- " <td>12.63227</td>\n",
- " <td>2.0</td>\n",
- " <td>18.0</td>\n",
- " <td>0.000373</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " F Value Num DF Den DF Pr > F\n",
- "Time 33.85228 1.0 9.0 0.000254\n",
- "Metric 26.95919 2.0 18.0 0.000004\n",
- "Time:Metric 12.63227 2.0 18.0 0.000373"
- ]
- },
- "execution_count": 104,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"from statsmodels.stats import anova\n",
"result = anova.AnovaRM(data, depvar='Performance', subject='Subject', within=['Time', 'Metric']).fit()\n",
@@ -6734,106 +2844,12 @@
},
{
"cell_type": "code",
- "execution_count": 105,
+ "execution_count": null,
"id": "a66cb913",
"metadata": {
"hidden": true
},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
- "\n",
- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>Source</th>\n",
- " <th>SS</th>\n",
- " <th>ddof1</th>\n",
- " <th>ddof2</th>\n",
- " <th>MS</th>\n",
- " <th>F</th>\n",
- " <th>p-unc</th>\n",
- " <th>p-GG-corr</th>\n",
- " <th>ng2</th>\n",
- " <th>eps</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>0</th>\n",
- " <td>Time</td>\n",
- " <td>828.816667</td>\n",
- " <td>1</td>\n",
- " <td>9</td>\n",
- " <td>828.816667</td>\n",
- " <td>33.85228</td>\n",
- " <td>0.000254</td>\n",
- " <td>0.000254</td>\n",
- " <td>0.254011</td>\n",
- " <td>1.000000</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1</th>\n",
- " <td>Metric</td>\n",
- " <td>1365.233333</td>\n",
- " <td>2</td>\n",
- " <td>18</td>\n",
- " <td>682.616667</td>\n",
- " <td>26.95919</td>\n",
- " <td>0.000004</td>\n",
- " <td>0.000005</td>\n",
- " <td>0.359335</td>\n",
- " <td>0.969103</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2</th>\n",
- " <td>Time * Metric</td>\n",
- " <td>224.433333</td>\n",
- " <td>2</td>\n",
- " <td>18</td>\n",
- " <td>112.216667</td>\n",
- " <td>12.63227</td>\n",
- " <td>0.000373</td>\n",
- " <td>0.001708</td>\n",
- " <td>0.084420</td>\n",
- " <td>0.727166</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " Source SS ddof1 ddof2 MS F p-unc \\\n",
- "0 Time 828.816667 1 9 828.816667 33.85228 0.000254 \n",
- "1 Metric 1365.233333 2 18 682.616667 26.95919 0.000004 \n",
- "2 Time * Metric 224.433333 2 18 112.216667 12.63227 0.000373 \n",
- "\n",
- " p-GG-corr ng2 eps \n",
- "0 0.000254 0.254011 1.000000 \n",
- "1 0.000005 0.359335 0.969103 \n",
- "2 0.001708 0.084420 0.727166 "
- ]
- },
- "execution_count": 105,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"pg.rm_anova(data, dv='Performance', subject='Subject', within=['Time', 'Metric'])"
]
@@ -6865,7 +2881,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.10.12"
+ "version": "3.11.10"
},
"toc": {
"base_numbering": 1,
diff --git a/notebooks/statsmodels_material.py b/notebooks/Courses/statsmodels_material.py
similarity index 100%
rename from notebooks/statsmodels_material.py
rename to notebooks/Courses/statsmodels_material.py
diff --git a/notebooks/data/patients.csv b/notebooks/data/patients.csv
new file mode 100644
index 0000000..78b5260
--- /dev/null
+++ b/notebooks/data/patients.csv
@@ -0,0 +1,201 @@
+Response,MARCO,TLR8,PSMB5,HAVCR2,LILRA2,MS4A1,ITGAE,FCGRT,NFKB1,C1QB,CHUK,IL18RAP,IL17A,TAPBP,LILRB4,TNFSF10,LIF,IL32,IL10RA,IL15,IL13RA1,TMEM173,TRAF6,IKBKB,IL12RB1,B2M,LEF1,PRDM1,HLA.C,CCL20
+0.34889518788890583,6.628040856655359,5.451410249350932,12.76583425041736,14.004527425665552,3.672567199173818,13.609538436424243,-1.2918652450911834,7.737586429080416,14.977722985110681,5.575724892187889,11.941989823140991,10.89847854678198,12.962980648617336,20.84522686145162,19.436671691835958,11.400617875199066,19.953882501135276,16.822631691751127,10.491798033965306,2.7415189017660513,3.500934142758572,7.429266322526408,11.25405609934774,18.621721980763816,12.067877078587957,6.713296528770188,5.3732404017735265,4.1795333870827385,11.793682535980471,17.192958302678036
+0.06277494308987389,7.434965289291056,15.983178035425812,0.2931504593976061,5.041096037649776,14.223887992959828,15.3338881802685,0.7328916265585335,9.179190170106015,14.577945594169574,1.019203616745953,11.70358632970897,10.078197948690814,12.437069953317684,16.84227441542269,1.8173661138163464,9.069487970426165,5.554197827650523,1.770093161457031,12.469930349083473,18.55259389841825,17.132192181075933,6.34902758653156,7.435596389216839,17.32448495356723,17.57604372407555,6.477194569285183,3.49022603349011,13.702533338228863,5.336034703141786,13.81315650989863
+-0.2032489086932749,6.600255220032926,3.0985679404011215,4.850230797125031,1.0873807592458675,2.5262565008549576,6.331897136462766,2.443892672200475,7.195146927284581,7.718794364465697,10.217233787714711,11.788446025867149,20.8286561734525,6.9694766564894195,8.702388700536419,9.03951457838045,14.8153094482313,4.2177042233523565,10.24975780724536,3.0058439405705224,15.931461984872954,12.630983902372073,6.335088685038245,13.07425439638385,9.19627679202744,11.556602165874738,5.124114673181907,7.739950775351158,11.442155870160796,11.21938832720526,-0.2903473816243078
+1.609150978604691,8.760969132446924,12.54448133312924,16.560668425772185,14.64618931077733,8.661329003779922,10.293388820012837,-3.2456637142009157,6.490694915710644,-1.3816317225368815,11.184243593254175,11.64862278372278,15.885758252276535,5.586254631464314,10.6300909133502,15.513748885688988,9.851555664810624,9.39802623741573,1.5580726317210827,15.087967216912512,8.77210354799413,8.081112604282131,6.423301878348401,-3.3223941383930384,4.470948473854705,18.348315927929523,13.384903788249492,15.261042439651941,17.193111488403034,1.1247250721553232,-1.0443984525585233
+0.5089080013720545,7.379778409745117,10.360621674861166,11.38905611410871,6.076842190635428,7.2554507497495315,17.260925572423414,14.943879342073936,0.15888933231408764,7.968892888170764,7.685918089145808,11.72851730903462,19.760820162934625,6.40922234098022,13.282272652575188,12.113154182414288,0.9857817291506876,12.943983285294225,3.3071216445469327,0.8616845614403994,5.522228672890925,4.980194085295631,7.365077290068131,4.547917987530294,3.8848700391117816,15.489645133123696,-0.6606201816225923,5.110488300302812,18.50833697660584,7.551574199327651,8.716116070084475
+-0.8357713091274173,6.677115869228604,1.957842798804256,12.239458487616776,17.48475368973942,-1.003882619110513,10.168500875384849,3.0483531346676225,0.14310041654075603,-1.1538771079501702,13.941403280215326,11.065756242204028,10.5552503044065,11.080402405702596,9.466401233068819,2.74609812560505,2.425327046102856,7.105045958716293,8.092912472261638,8.743926440881193,14.300257422556962,9.72690953033991,5.578525944178488,3.1583925368808554,12.891333598527257,9.913766374748382,11.914501778123398,3.621414073396741,15.451845645112334,16.075473889147453,6.659973283240301
+0.10413271083311552,7.808556651927551,-1.1712660677288254,7.741126064655356,5.032813402016144,3.1705074861635367,5.769036796512761,10.242465013325198,-3.4929260735354433,11.928544933123998,-0.8312231017792263,11.218916249827114,16.029682769630796,3.313746577584947,11.419226173072882,6.4376405061609905,13.102791988362576,19.07180001508692,4.954264219494583,-1.354480817623612,13.35854488450587,17.013274963864898,5.684475048632632,-4.004581346326296,1.4764068805993862,14.59812009995031,-1.5986613248959571,15.481048453816424,16.201244189652265,-2.377507969670882,16.5603059697547
+-0.05137298783834075,7.309424738074933,-0.25222642222523733,17.4230611635819,13.526752955784229,15.320892884262953,20.461870435391678,12.389306761039485,-1.996180351157885,9.708126448589201,3.5899666434604,11.636321383609987,18.650727428042085,4.872582093281014,10.073907198689833,12.396993703431173,1.3762946137689127,9.599472942232113,1.7766694536763064,8.337903965771655,2.3394386140218923,7.0979682954205465,5.692616485553146,-2.6643537319045825,13.73960872467912,11.994579653728778,-1.336144646314211,6.397337281291508,15.028126693768533,9.54558042111072,4.88487255445342
+0.7606751616623827,6.994436354170701,-2.8061469075508407,1.1015448459085704,6.899177684869885,0.880933227666107,3.3153583397298156,15.743812166752878,7.12515065703219,-2.1854948702401487,4.535312755809178,12.47603202448399,22.539641741313233,17.955986293483477,15.445400451608021,2.2462474479503953,14.655826979977661,16.68578446215853,12.613247073008056,0.9201866087121049,9.52529474604039,16.90784719903619,6.273679481415555,14.76911144713258,4.185044240105732,1.2502713092905804,13.278685263089706,12.25550570827106,14.334387627925171,12.603897558214506,16.336449105687198
+-0.05199632819605356,6.908874945324497,9.9298306507607,0.6796020258454476,19.379623218612792,4.860079822891047,7.016842701922831,-1.3532930102415692,-4.814509770647248,6.918619590189192,5.119137266140123,11.730432790541006,15.292974319263088,13.786336537418082,13.274093676935053,4.475402567337554,3.0148191706384786,7.72699789081733,4.370104643397759,0.9989828689007466,11.611219086896744,19.797323139241115,6.386649617994965,15.842339766782139,5.736972924481551,19.326676002712375,14.335420726701773,11.373521276017112,3.7563242536525348,9.473358865800641,1.3008459921840725
+-0.12074086124264033,6.7936820190301255,-0.6301291731892275,13.307641224617518,6.96418060323793,-1.5522630435271854,18.51982466063069,7.1167698979398715,13.522154454732416,10.814596800728783,11.069049894222974,11.953645899579417,18.067768562068043,3.538359841158641,16.03929295536647,4.11392141835381,10.775015673696041,19.270263367726358,14.88328187574454,5.073734021641654,19.291829946231537,7.3572012452014395,6.2301537729664895,4.416977409825794,17.565935304333188,14.636749100774857,14.306544264394574,11.106300212902534,5.975187472237881,8.651085700478053,16.032254945975126
+0.5567117490492098,8.211044455736442,0.5071837655254585,16.339530280116428,2.3148512014683646,13.742983209367917,2.9125516262848326,12.191281405492555,2.077479452814085,14.009994931486897,-1.6185115310915883,11.570194351582794,27.41136042609899,10.925817378168098,6.885839161310528,4.19275047454898,11.429202160218702,2.657987250416941,9.706753082681782,10.537504819596219,5.014499450297308,7.016239222938205,5.810885374748008,5.218314657338445,13.956492005142552,-0.41954047738079586,14.782281611031827,10.955931579101136,15.978587666586654,4.670213995084169,18.669186374870186
+-0.6204465984715338,6.476911055276006,3.716884055926551,4.1858985509262805,6.362564230726935,16.190018320582347,6.156573095739299,-4.1770637224803435,7.82797773760665,5.576649767684987,12.113684163362489,11.619184288207972,13.037411746561968,2.5544488499988933,18.556548614464653,10.081879265382998,12.233320584130784,6.4241791055736375,11.83360083810917,-0.3292213310133763,11.504878382931585,4.808400333913601,5.7868613055161395,3.6672899269956245,10.74342766787547,0.21285880112690578,11.552584885921505,-1.080545580422024,13.85849924686924,9.651855577956068,12.362791782155204
+-0.25814889172808547,7.594939700045988,16.166565952822243,8.081218696595913,12.288621403021526,5.887703281714022,18.57633903356605,2.888636747593104,4.537029963938096,-0.8682981463984242,3.3772485096204017,11.502838420937705,9.242984845069945,15.538537519186328,2.998007115152088,12.551529235719745,4.357803128138977,15.345096331812444,10.836631056378991,3.688394773315724,11.152784856627045,17.924187555624755,5.824549019470668,-2.508170699427155,17.441562113539568,3.5104973144921807,5.594197019039265,5.530281170200967,14.615881878222364,-1.2810595064736443,9.904125691174427
+-0.11890702017807925,6.320331205807039,-3.662157755431571,13.75164616820905,7.98629193424995,12.288350823105691,9.923629596577594,8.819736582470767,9.357125750135836,-0.21508518110013514,9.870441618437974,11.887980738623796,28.07359612530886,4.610549730195141,8.80882559279331,11.786609242761642,1.5718526348632231,14.675619178503355,3.984625594693597,15.575929053494615,12.1542701869092,3.062890670201112,6.416442567339395,5.468300022160853,0.9494346686313655,3.6078982717465777,5.419405112194324,17.91292869623863,7.816239170112928,8.932827594759015,-0.23029578688455385
+0.22609615484985807,7.811820165714088,6.116119540674726,11.67310148636071,15.296615463730351,10.95633453510473,3.3430222152597224,1.1585570702654524,10.397500984811067,9.60258143019308,7.329357894968755,11.510335317809199,8.866302868099897,3.526418776105686,4.317582477804432,8.84744881829317,16.582904137471566,5.511845377900322,4.569123786068805,9.385056760334097,20.570560530715866,9.96885274981369,6.382733086560273,1.9944104989397058,17.009371483950474,15.716463516467748,13.967326309790803,2.1955558527610908,1.6125269154819097,7.7723090846791525,18.63727665574738
+2.141858685208561,7.133834388143472,7.12364451701741,14.414294118729554,14.062637996540026,12.848021372150285,16.922347902454824,4.752863940895163,6.971829265635437,13.658019491233357,2.0605264808323067,12.958622481211572,11.287325336913451,13.772255159577247,8.236219288268922,5.598300625441755,15.895705342518745,15.568048045806437,2.9274776193632013,11.502129154672364,13.14303996323805,17.463729661975243,7.3499270150572595,4.612415749706026,11.232074731444603,7.814641242359382,15.152946229332228,8.85827714251717,5.656180911059355,14.69682867863791,0.28926205824792983
+-0.37962653669451774,7.520768597952829,13.940986113016145,7.382030758605847,16.291718348058446,5.959513576245067,20.534093786044515,8.904423651677305,0.5403042528283928,10.226914650843282,15.007074909510319,11.048739765235986,13.131749422285004,18.116301231966325,6.127125867946866,12.186188998683564,12.192631302426657,13.249839031656895,17.07180091018618,10.036605883977288,15.065545252825853,11.80951753646034,5.578366149112688,0.31327348542620725,1.7909090520941486,5.891834673570793,10.359973912413064,-0.8710153159774235,10.200290286906377,13.861051115867934,1.3534942305287831
+0.6530836382325479,8.108947621223729,1.9850980557707238,13.826709140613131,11.589543029126986,1.3818473118594863,16.063367967769313,8.733113462173403,-0.21966983152199934,3.2953629943796283,13.13604663710731,11.760149121797411,18.794414106499612,2.3796794312410103,8.65974034656946,8.263674816206295,7.0155841747770005,3.208099023757409,8.31717032388325,13.53460776661939,9.96370895708656,4.5400083948752314,5.771897879452134,-3.534325988000001,9.428436819871784,4.479100158628562,-3.204805358852985,-0.3666948496884714,2.278612955559854,0.8448385799575703,15.879951834548724
+-0.41821264280050374,7.131350601429304,3.386659286097366,8.109716278038574,15.265176995201927,-0.44306818780727036,17.954267893528247,10.62146945746128,-2.034613289699352,3.0430112420128825,6.506772251821763,11.4003492897817,21.631606928066315,4.893856150025028,13.46125850060634,16.914518057842088,18.373343219725314,5.746501938844201,8.818405593743186,5.15072154431777,15.422073988605524,12.177142295014336,5.688826525494739,0.8510412407130258,1.5756956593176756,6.6710470148323715,14.928695434115381,9.844247875120471,11.852373701137525,4.52973974954014,9.206549734993667
+-0.6209735438502544,7.4493450887919135,13.176403504971493,15.700943302019553,16.15119392088757,17.17523989065388,19.323759919215902,7.543033014708447,0.266656608485309,-2.441228623081062,9.053141345894725,10.891076643589878,13.781350210042504,10.015915884085935,13.208057410606141,5.454079811880314,4.174557536429761,1.967347368486795,2.569591026901332,6.652284290454215,18.632871608059336,9.80206040651551,5.598140405808578,10.828342075998732,3.5588806825605896,16.85146006233594,3.923235378437977,13.465410658421424,13.457134576008778,16.437980586958993,3.016071340275568
+0.07221722872647263,7.957355312873525,16.36604115097051,3.151556396017618,0.36715392670338254,16.879340060114167,19.70975112408086,6.569666927176717,9.712830141102346,5.3129928801668465,2.1061068711962516,11.009928868751462,26.872258955966828,12.102178427332749,4.677344272494507,2.3772801291687564,16.062355530994896,2.168643328317822,16.854173195301787,4.302546609095697,17.103206431078682,3.4299372063679545,5.85860614998974,5.533540716813189,15.428806323884809,1.7866702401180525,-0.1881271275225255,11.284961928342936,17.876115768199455,13.77372940474693,4.532674712774924
+0.5197705117907545,7.863837041056145,15.539345280140731,4.308374907932912,11.44158091617646,-1.0457366294128594,5.762372951918881,10.364811366330157,-1.2394326536264533,14.175536073923224,8.774079029178644,11.82993100920442,16.394452462709175,10.480191937414695,16.660198082601426,5.338554150568516,6.350529548403225,18.710480037746244,3.7282651897650503,2.0842015064667025,16.711937206748857,14.390106777002606,6.148930663116492,13.124787797724911,2.3723793200631498,19.802272142073498,9.73493990055102,17.36451028529657,12.508287789020619,15.317188654473515,12.422674852391536
+-0.2575573621826635,6.922360394651449,13.042663787051964,4.334163373723685,3.260576806593525,13.377396359216297,8.756110726807751,-0.6596320571476894,13.895830940637257,2.6150502760413534,0.3894249001680467,11.75124144585923,23.65279965421391,17.16580571251737,6.820567327875128,12.239379257017026,9.188088916646443,1.1081966061879172,1.0006757629733354,15.974008200707498,13.4437438896537,2.081830618512509,5.555246998531485,-2.086515748432192,18.214316693030167,5.131831070847303,6.435561134518728,5.115563168726339,1.0819032282138856,6.366104040593799,13.585719846694893
+-0.6456372108200575,7.355364006562983,7.838121739667771,2.7148003361362427,6.693563976207175,4.885223322232461,7.738062231569044,-4.896809342774532,-0.21305992545753671,10.88669206962243,13.24215688862504,10.671034085993004,14.397788820257233,16.41941824035797,16.659457837158325,16.92046744735483,4.638346748868905,16.556447504104522,6.558023236025022,3.6334040477611103,16.044380290357108,10.233540720147667,5.1826856374078725,9.306904419366106,-1.801356113277488,17.748425663916787,0.4243627319483227,7.054080084019443,4.127319563369937,11.509638018668968,16.162519791611565
+-0.3514867153349633,7.445991141904092,-0.2172961413687356,15.483324583916952,8.641728685429472,14.733638978204171,20.598350827113023,13.935036184173779,-2.1266297638983405,8.635741000515154,17.50681535613557,11.111652860783524,23.20840427528728,9.045623094353433,8.946261585629466,12.198780419194868,-0.35738318230912647,17.192254064333103,12.646138645932746,-1.1067975969141708,17.625449626175055,4.738997411532333,5.564311240818629,4.0471422970181,9.405174177571425,8.781376349369202,-2.551758862720768,16.229115171148166,13.805756905286618,7.418306043323369,18.533813022748
+-0.3589646969503888,6.9949217275736055,-2.313916926017087,5.083464025083608,14.55544813483337,13.815496550341997,9.703970599232784,14.871614378413415,0.9415703991334086,4.492270963585866,11.194178029278355,11.574564623712245,27.39513229853859,4.856383622766799,8.413592163231256,8.570460900404392,15.53587704566352,3.2946938000537784,5.053764844739753,10.777800393348372,2.649332795510821,8.309959699441608,5.910427174751018,5.9766741615626255,9.735130509972016,7.309677860804591,7.780968469596744,8.911477372741588,19.18941813930703,5.382692363643125,3.055508601714603
+-0.2851828579189699,7.688550733001966,13.855482161839696,8.155818867383216,0.7235929937163252,3.7316333362325302,13.096733416283902,-1.5693035554603485,9.484317306364481,15.358123336052216,15.368479978708399,11.143007686357322,26.92313663344126,14.879734346446329,7.435918864977705,2.10658013838688,16.882999111797243,19.5457147096133,12.33999127350517,0.08072359014569136,6.195416104303542,9.994044913282991,5.77165826679656,16.365278444147563,-0.34707654103006463,4.19276812929877,17.14913121359823,9.906396615535773,9.605768237035194,5.394958576926818,-0.21252511451824677
+1.271124882881197,6.323964206069009,13.305276383788705,15.775036801685202,9.797702833091472,17.56755527638748,9.66582392727678,11.882212964211718,11.982379730357433,11.081841684515567,6.057467133816115,12.811217681880068,14.1602490822483,7.419400794940737,12.188825853114109,8.52909015483223,12.601526886365473,5.07855191114532,13.095094353854112,10.941847935273108,12.936173936620769,16.12202942329629,6.855545253484776,13.104752031828273,16.33357136276655,15.942742661694844,5.949385520080061,13.645498402716193,5.8716992030992685,16.350614752391998,12.087376566760025
+-0.6726346180306968,7.010632163209184,2.5011346056712336,2.1347639470156263,13.382030317484565,17.662203256973804,15.612920138835507,-0.32074583145698193,14.626178475397879,13.343957375565601,1.5160047788804958,11.20494182089585,19.688646142743963,6.7485241562069636,4.885742162415566,13.379309442897537,15.44285253272375,0.8305208307134002,12.100143730831265,14.920340069962402,2.628660645643576,14.542776011267048,5.3271341679292235,6.037038619698449,18.07519860397742,11.849756292292737,6.365112154863863,11.381649071744048,15.397619122106953,1.5271232262332637,13.304791797710235
+-0.6352970679697888,7.131746715513392,2.8912907055520645,-0.35149044270101104,10.24006199527498,15.563440812407888,12.168369466065101,8.34221474283611,0.3470395613867273,2.343785091413589,14.520183547823391,10.99362704235504,13.333187965703,4.996185056500746,5.5687869523529745,9.036235655038322,18.29323033749253,5.412169243033777,3.5968216040574426,9.091685006344743,11.384141647178236,12.259548015221787,5.883600445534777,4.79066790091957,3.3842422954180833,7.857743038642182,15.406105828349322,8.223734821647966,10.643129940866197,0.8707797229116299,-1.1831450796482859
+0.6832519362201672,7.35511008741801,13.462142000302196,11.527222521939306,2.1895088290386795,8.419595669792164,13.560102082226976,-2.018374123791947,10.879306375278713,14.248940303823328,17.858508926713174,12.171870066558705,26.815285037198286,12.70647407654428,15.800576182912454,7.003604158982101,12.529064602511847,11.805124168348328,9.522820565006388,12.104333207430656,3.2938819192977817,4.903018566468884,6.6982050652089145,-2.3337259019891565,11.632030978113168,4.948683385012572,-1.894317974305709,11.252583645739191,2.5752107560678716,2.218724010726273,10.836470809139247
+0.7162045802431953,6.595140526676722,-2.093074239053391,5.348262859706255,17.911856322595142,16.21997516671545,11.808356233870727,8.731834907041787,-5.090121068573455,8.172519894447372,12.125988587659299,12.453792582988143,28.328105883857223,0.49263344167838063,12.465846909957305,8.759579585281031,4.182115539588006,20.046048397667313,3.5602797643046564,2.551544585246794,5.247710233558907,15.942525585899057,6.543517349472734,-6.278976990136857,16.29480824198687,6.51148907665889,0.8075073579057852,6.8019904467991035,12.586245870195036,12.29001561528042,18.275954587526922
+-0.012090803774883623,7.806861782979105,4.108490278433457,17.40784339446902,10.430200793046888,13.82129912292704,5.837482240280918,7.738476406325676,-1.767942230127444,4.930906387006466,6.722586790780738,11.00228689316218,21.027378049657898,3.4931020449685874,10.069319117252844,12.497099980461655,11.355104818377422,5.272529081394135,6.222959740343522,14.4168884733934,11.195043120665055,18.6615415492578,6.386924783520523,8.338391475648574,11.864463670968513,11.217057605193252,-1.3054627564400603,8.441184690593886,9.677459173677855,9.934201404580488,8.986834810204726
+-0.8286027118446537,6.228860649452176,12.553227599126425,16.421714402269817,19.025510083686342,-1.137575571401582,13.25534318321033,8.68461355910717,0.965779124705123,12.247919918215961,6.859205043134002,11.402199286728608,16.564991738964686,11.085712083876619,12.374266483129162,18.014523774989115,-0.27589719864078427,19.955227825154445,6.367455458169012,1.532150035266314,10.249337935207011,10.872313048665703,5.79670647826683,9.280794829704842,16.780539188322535,9.00729314239083,6.907606993409223,6.497046316676217,3.2509896277197274,2.648250709802179,2.52627831816765
+0.16402999121784698,7.122054721173586,2.7716520298372256,-1.5666158014384308,15.402276201790126,7.657716645048849,8.550314696404651,-0.9118599578631877,8.515791477434304,1.7509099499236322,-0.03155739388804506,11.982398957345914,19.76648801226582,15.009290310186332,8.959503304650358,2.6667365406584853,19.20218938135556,0.927967447672243,11.7555625509682,-1.1948860447492589,2.2127033657555337,10.166676814982049,6.025827826125894,7.8500608623582675,1.326867259593243,0.8353508514400776,3.2946051017442795,-1.06534763978253,13.400551315716054,-3.3670869795596903,8.767943860325223
+0.5472756331653053,7.267454566814129,5.782253436038086,14.50790305395478,17.21025380369401,1.0212205302912845,4.613732400508024,12.903705781171105,10.777417625540934,9.583172765504589,6.6659230404424346,12.00208103686446,21.703805423276844,16.425397992791446,13.416553068078594,4.952346440527403,19.03328772783494,19.62980002892938,12.6624919866643,9.784546381953863,0.7213263972199223,1.0678448238305087,6.668010984438115,-1.3798437632929128,10.060772449076458,14.682593935656405,2.154179934140976,2.8817145736314203,3.9729323335823707,-1.2457731793421445,-0.939846254929428
+-0.2377679709786015,6.7589255292241575,-0.2521509215268685,9.08800023648308,10.841215421514905,-1.1217806519637854,15.857617414833344,1.7054374701829227,2.9070522735850934,3.9908825999646345,4.303564420070602,11.526321167771002,21.485247990663243,16.754888736411278,13.931791597744938,7.767477235935608,11.293654163145044,11.03571147696802,15.961130384252357,7.361327964356004,13.281150523824198,12.97875192432362,6.299406807116654,2.390152262658037,0.7250222542556202,11.924149820520292,2.0352737642517313,5.182337709486767,7.568482889258853,5.67877220990019,4.58254063802238
+0.04255258019034641,7.189898647777187,8.657778842209895,13.848174860654295,4.471050211883204,3.035463474672328,11.500400776189831,5.6477295474087414,-4.5624125714437715,16.038707223498104,-0.06463627538594176,11.74223240555761,10.718099177077171,17.534282105838905,6.161699523388762,12.746061148777978,4.902643196968347,19.87517960473601,1.206576530511004,15.148323086976916,13.877641375106965,6.224918233866211,6.454348268995021,-1.797220500262977,18.953160777995848,18.830895341683245,2.5586774573608544,11.578785826989307,8.087592036430088,14.149989758748802,8.00386790050787
+0.8315642951313377,7.635268428395869,4.409579268316976,16.01034246503702,4.762773394112024,4.9158077833585025,8.650885451052835,12.310832988293456,-2.5898586913175663,13.242369544200429,4.622710115148898,12.173919234672173,10.176791833827512,3.5929073849481092,15.813469136918716,9.719834682418389,19.195319229187923,12.74312872884011,7.661726860456487,10.719316043887247,7.232584728967037,15.196394435365454,6.646228176531327,7.63163862992646,4.346816922648193,2.2303244711876875,9.921450603246036,-0.39532896901506126,1.2307169525401953,-4.551199446741096,9.039281963439288
+-0.9655547088222942,6.585960272354071,11.338774620401374,12.473813323631326,5.994960838536896,5.0286944690200635,13.46274422181592,4.168603330894948,5.199602691624886,15.913020993289898,7.645485003604836,10.964326500424525,9.376820196183967,19.204463802980193,10.282594567259547,2.659345012486808,15.11569665771754,10.182951974069228,13.280377393115744,6.2783015608597275,5.50874216201985,17.619595084431467,4.666592787699193,2.099723613099272,2.09523626999653,-0.8323102103657654,2.0234901651092523,9.281351561499598,3.752382296721663,-2.337949509848012,4.79844293046931
+0.11348451437046796,7.340194680552103,10.15591290233828,10.247995725372842,16.66642300425395,18.016172470694222,14.262379198912507,10.265329274542317,5.229315167707543,11.18286643035354,6.01728915380145,11.833794075313014,23.602714150194473,19.440678023767326,5.609018737326268,18.327437997910643,7.969270637024694,16.837042583805648,-0.30952173517884685,7.796550840624296,18.58204770730235,9.760107445219386,6.047462681509127,-2.879383009783256,12.808590977287807,10.86418214572541,-2.945911698090117,-0.3122208023006934,19.928805594247727,7.967564524697511,15.991267282548302
+-0.954473414392237,7.269250329483377,2.378770648790571,10.709938795088553,13.001281129614343,13.519505237049339,12.945882934056744,16.12202292336079,5.000596531369937,5.402616071572958,7.743850433520714,10.308795266487882,7.854208769633189,9.114759917825607,14.322425134712583,9.055316756150777,8.953177260252627,6.564041142305662,11.157524037171703,14.83623976356039,9.098490896742472,14.873488837937831,4.703032659333978,5.856823316516043,-1.8638940679653375,12.485682070573864,10.553153782403644,17.926836994836233,2.345916069888645,9.375781817083038,2.0605753895822545
+0.37574489783757725,7.796643004935711,9.017864975093666,-0.5238984138640622,1.9179244008934884,2.6975147601009155,12.594364982851202,0.25561833207598833,-2.90508727193526,10.612395025586768,9.893698555101851,11.846156318398327,9.197713541394965,17.40532448315453,12.0921285571654,17.412551081498588,19.216458530099274,14.175801498560414,2.0326043676179104,-0.27741988592711125,11.478020117297177,12.731924868189381,5.243115636425619,2.270048068977739,13.014337573617956,1.2687308664003094,5.892570091728642,12.52340530491468,4.658697270603129,4.858140570665886,15.124938958562439
+-0.6279295544579003,6.760184240192379,0.23552691628777214,4.252460355877416,14.21970005127747,5.38721319548814,17.334990703266854,10.626404483449802,-1.2670880484951659,15.558531980696515,12.615673128015342,11.340244774785214,18.290146105197532,13.76958181204519,5.108480391909644,17.29520276226095,4.512634935771564,19.240644003806388,10.23786242360142,-0.6460711420563117,4.134416614716969,6.355059906431904,5.808031826347243,10.566618247703046,1.6017768850471095,3.160930202423014,2.385643223013174,4.881480666833813,4.206631427812235,3.4144482441584163,12.056769170731256
+-0.41324264517072645,6.520172021501176,1.6339487093256224,9.713248875168645,17.078105690484243,7.657312936742999,6.1558480416012955,11.806924859038462,6.14371873199644,2.692052002068114,2.419083296182814,11.69076661589617,27.36265434262812,4.714211201865872,12.708782483066356,5.325597259756437,6.252207235694788,15.681471085185816,14.172587459531343,0.4103361562578254,6.198384913761762,6.910137312426873,5.553412890503789,3.2510293951266345,15.132879783711937,18.293689881329783,8.794919006505793,12.150628125271552,6.5823227730080305,-3.8922152478552334,6.489777957702307
+-0.3905052221881571,6.395039305783107,8.322692060437046,8.21208538522466,7.504518082772071,2.3775434092181165,10.391673845509452,1.2478007434945848,-2.358871906763425,5.6811961866476395,17.325709182083052,11.789974236213117,8.59087275988539,12.614507682661854,7.4774889771505695,13.147230034729649,18.25339709158814,1.2129314562683575,11.088431652890684,5.687327767924017,18.04710506415458,10.275485132959021,5.417566349208181,5.898261964094948,16.655373782425176,13.534162992526351,0.7978375371914783,2.748662408457143,1.6905390939286633,5.57242730144803,16.0706060282496
+0.025728917476136492,7.134491107215175,6.532152426081289,2.0133963200515126,2.2248625594867892,13.347550513800964,9.621319812493574,15.367908728179696,11.073114800550137,12.974061873746702,11.347272949585133,11.920158328138774,8.12682127541256,10.611624321310765,1.2526956241723894,0.8519103116903272,7.63484609351951,11.536134566628807,-4.03567184540593,7.0782299515996545,19.616207833631066,20.5832211203591,5.5608560164116785,-3.506668114334304,18.088827664492282,18.1920463795471,-1.2046310273513345,5.416101109514978,19.362704043583605,5.67640505068482,3.33513196071406
+-0.4953824991790282,6.401554615415708,3.8784821837027934,13.70605588063616,3.647951865566437,2.022817697914409,21.091920488934285,13.91944893612996,11.372824366441048,16.24805574023839,-1.0240985538200071,11.579316424736314,9.543804726464792,15.089042344631586,16.551172819762034,3.3439173902681194,4.518219795659887,4.062738339294826,14.402351880537585,7.059821313298566,6.261689807809001,10.114513972197726,5.700836559076325,14.985497832923354,3.3435826238244513,4.772006155841803,9.089858485487778,6.819334827520599,0.6995484341071219,11.839728182312605,10.09360813941503
+-0.7913262699807981,7.141182572674969,2.8839143708735575,14.164006243489112,2.594786237282486,0.5747700424804689,15.888270842063484,-2.670054941445704,1.2588892112420798,0.3902707008608931,10.469902935403306,11.05764360377561,16.177223963506307,7.206645180370948,8.000026081799033,14.302918587826484,10.902471832834085,7.880485332381149,-3.6337175639904586,10.981411283983793,12.589195606639715,3.491908334140959,5.234855065144411,-2.714130008501378,11.552699585746668,12.93259963478386,14.014919258881164,-1.3072924429398718,8.129005806610328,-3.6109902903274538,-0.3014753703625335
+-0.70387877830435,7.14393728225741,6.6083525522902375,17.910331011758295,12.721740006936612,12.56392177774006,9.14623707517925,6.690596500412824,0.1852332138101306,3.609597315034029,15.364885260278477,11.169898472704094,24.485423490577038,16.473201340379894,18.754406141447646,4.353078967570131,4.7573860905653245,10.22680970307169,17.225948410044726,-1.4929868222811813,17.165021650917204,10.937575640741262,5.2806246222277595,2.9450350552919504,8.423281364722376,9.483084020665192,11.00113698097385,12.244886710401856,11.595186957476876,11.36555278806567,11.604556979017351
+-0.2970261510684559,6.725867144724276,-2.714571227892243,0.6520465962090096,10.717887421571302,1.962483211438995,10.031106130050775,13.583849994307705,10.45976324595906,-0.001536119575360939,15.980895277658352,11.566934434873803,8.253911928699338,2.156716973296751,12.953372020917298,1.2244766072413888,2.3292063415356825,11.180319126818508,10.879316478390272,12.813916496498564,2.8226695049851003,12.494307445186747,6.401844666252155,-0.4729730302031409,12.000184373756989,11.73177560515717,-0.6810754574884728,8.890626168316023,6.437941243385389,-0.2173889826675871,16.191746641562432
+-1.1928385937771333,7.041636415784928,-2.8318088988468775,5.501486450904148,12.061585499357387,16.91701141306171,10.117549923989433,10.833034541533578,8.855659104399997,5.444889701073678,5.245149953963215,9.801258007650405,17.905952116935666,16.50657739627464,16.706919637965097,4.946658598215745,6.173023270771704,14.288178012052215,6.508865230683366,13.864200977407368,8.318652347882068,4.545198807945939,4.362321074317787,3.065607142489675,2.086140807410514,16.77716471106321,5.330250936339296,11.497239962578217,15.166249898836076,7.867667147226754,9.385457144070607
+0.2010735074462788,6.57917498998797,-2.5247909368751085,13.454684733718809,6.34436680372804,16.23824914478242,8.058005627099828,14.208012684059725,1.8226629109516832,7.86537406821707,4.92135548940359,12.261291032982516,11.931965062896523,20.046680913902502,16.531210138260754,17.08682770304648,14.124676980471078,15.249394005628808,15.425660282093311,11.88384994503581,18.83092589162634,16.712098262490002,6.077548625962141,14.734222726376366,19.13926240277243,3.301977042779825,8.98530577824739,14.330897623431706,18.69955105459664,7.032289991233227,5.520098196851023
+-0.14847523257074918,7.629946208203473,15.714086925601919,-1.4022519474042179,10.968643284014325,4.669274030886578,12.96334085342949,11.42401938416403,-1.6842466104688159,3.3067378854286575,-0.3806946910482072,11.141991461039673,23.114198351894057,12.87369486986149,2.261314241814068,12.71551006299,8.991356112512795,4.435558588122321,16.797449273999245,13.93815003945341,12.856103664823923,7.153066705681873,5.924904433031759,12.924487583238225,16.16408495431392,4.137183543257162,6.048285827583437,7.524231746304094,5.72523073507482,12.801923388636718,11.604347995020625
+-0.29537038937748267,7.693360483807387,1.8826981339462847,7.200200650054718,1.3506289314836888,0.16415996167730826,4.4128626502813955,4.229334107064641,4.141675842398399,10.848582409793032,5.023263681175864,10.858453115112383,12.538196754463709,16.535973155607095,13.455061705386944,8.942777647080963,15.471575751298504,3.044918673348935,16.898752065963542,6.293398824250454,13.264028961278212,1.0571138923127685,5.814542280764403,13.245299242789217,3.8096790837347783,20.720358153617987,1.3611275002607552,1.559016417784468,11.436595549180453,14.309440537609348,16.73140215702522
+0.7606778879455036,6.961222210743319,10.988627608064247,18.419713254783538,12.904811994903742,12.331617355950474,10.58884923776258,7.422271867640571,-4.138070398591468,17.393091607811492,0.18754792341189316,12.405604364849163,15.116475924171596,12.593315908811942,1.3586587476564649,14.203119610984277,19.496540261819284,13.59831735819655,11.75445007845503,15.977118106238631,2.282171759792927,18.523977439583454,6.264546290669603,-2.431988284063581,16.301234692597877,18.004000827518162,12.47039864177291,10.779012080315182,14.627951543540751,2.442473459455381,6.984709333533429
+1.332503594190059,7.880532918989927,8.055548977794349,0.2547500462138555,15.212273561146896,16.404402945970748,8.272363078459724,-3.7490393129182893,0.24540254693706748,15.672115417891177,9.552519960673704,12.356789030926471,13.43726214780115,16.03852967331327,17.100190136687285,10.05723111517833,3.3529241354695003,13.442554162882844,-1.7131651732042323,-0.5713011625933486,12.684655303179767,3.5552622532536144,6.78064622188089,2.0807294767981004,5.85298598499149,15.483916151446273,7.762637075738064,4.4264000808547035,6.836395894267826,10.2184235160833,1.3118628961307497
+-0.46207941339143227,6.779399334111413,12.594997037474991,18.226849185358994,17.24358814159079,6.9494841123987126,4.053010193712531,11.81860328065434,-3.1577556876575845,4.048998514495098,15.900673560881557,11.456503172869297,14.306391431002158,1.4565327748819676,16.147911128899345,10.104466151905353,12.070929991362085,18.66020134410256,13.92299639775071,2.524583426667702,9.801026020630479,12.047729117562449,5.623153485752482,-2.0179930804762938,11.962333829397448,7.493269629261809,6.411684716805001,2.8314958845054434,12.354111235272901,15.292945533404662,4.88897411121653
+-0.45633717116708994,7.868072915614308,11.476100244065393,17.15158549609272,7.736779573558472,5.134633173812638,20.591709987135992,5.790783443728152,1.1612505129019857,9.384209348701752,11.11767643103064,10.741932116922278,24.463810679181996,7.422237342480782,10.657571163593643,7.598564965756006,11.526548584267998,3.31710439589987,14.264895384530984,-2.0253181602563037,7.168571854887302,10.477453791977904,4.6261153028185396,9.03310793027983,-0.6097116629317618,16.222607267393208,0.16524046398778755,2.10901323660619,2.1318922221797685,1.2566921627332945,8.232679763019352
+-0.9603529315296777,6.174356476796403,10.750609999203832,10.007944886418656,14.571140541640036,2.6389950891094696,9.90331746696188,-0.39214707800309245,-2.636435795683087,7.008894764831023,2.330618327567718,11.135021732734934,10.020845276857383,6.773495324080919,15.896311435167334,10.784747840915355,13.527567096012973,15.036366675689425,7.833171017799273,3.886543406157024,10.15537401351556,18.837260450457087,5.6391470468309635,6.579484105388152,4.913441057713094,11.034311405653979,10.523418993298407,0.13608706952187077,19.871897342513954,7.055071419781861,11.182305389587375
+0.7641787671639338,7.608541062370961,0.3831771159774692,17.139076533556164,4.737255608800009,3.888426636476469,13.189692723928562,3.3670654472239017,-3.199922231768392,-0.34507341170820366,9.808994435483744,12.110172873905174,11.892036224606226,1.079722062504091,18.795982424478666,2.362592243923654,13.285857435339517,7.8241771795315085,14.321735336447915,5.787832748648135,14.28952750205584,13.008142607736687,6.453236254126574,2.0706212577464074,5.957502972433609,0.7192246723552724,8.465911754720022,12.435390014191567,5.040135355858583,5.363178727144511,1.76936610480017
+0.38472520713073377,6.945462847131858,3.809683166386554,17.518315282941366,16.60293054215333,11.879344930375852,8.650560570422822,11.787195778789552,0.8086779408937996,6.753609977483581,0.24723532068327528,12.02506096774658,14.168163125881449,16.779369383631135,19.280055987530986,0.1236966840666618,15.595592190657854,11.351213129650162,10.278042333141029,13.899010379184505,15.38636778607534,0.983731593083462,6.8987180616199275,13.434538187338559,4.7209186643796315,18.462930362450678,7.6579025752433765,6.618216883940537,13.357724539408364,4.934905706461715,8.560076086838011
+1.786120707333787,7.738055060013591,3.5821219052138025,0.5679761116754136,15.087333214332114,13.903725880175209,17.211725769176184,6.514340907962503,12.144429749023908,-1.4396335325910492,2.133224141710963,12.527139245114359,14.584426079558291,1.399437507606164,10.050675482265676,18.66284931655476,3.048724551639827,12.911432154024231,6.514735916047282,2.2950093742110047,19.389824456096974,18.662772494456366,7.564795902410915,9.84997771624149,10.939775969679927,16.07181207503588,10.586549291277173,4.318976144546452,4.97654541022956,14.01582154669812,6.468612223121513
+1.292406412238103,7.089119539253444,2.00128890753658,17.939619081420183,6.933582203503068,18.297867976750773,3.347475735949221,5.634847882439231,-2.556464790615876,7.30213212999242,7.414269039755231,12.731985355700859,25.471713897289174,7.095787227862125,12.046066566125504,15.36067194160559,12.305923693509808,3.5793696946729163,12.84488412400584,3.1871715002329193,12.814518349147749,9.523774109921517,6.224704178153521,12.344382316535105,10.050175404310552,9.559736334523794,6.432981361743204,6.704902204558692,1.6078955183314108,0.750787765710633,16.465894828177156
+0.13431711299798454,6.89476194963938,16.025877655797,0.4571603595781895,4.900249340156876,10.445031497977023,3.2441580812444712,5.795038107088838,-1.04479131927976,8.354812497530027,4.9966003125819025,11.916054105562244,12.597976702098865,14.228668591942194,8.851980808993202,12.990012796102883,5.9542646166498425,10.547560335550969,5.357296129209211,9.609421653795085,14.283840499376238,9.061783939524632,6.336509184933633,-2.397671280526966,10.587638143175184,6.815946169917607,0.2894704148622039,11.275486033799321,1.8093545654893646,11.303116298527803,0.8418517720348432
+-0.30984903685431114,7.476159678806718,5.9309315126140465,6.997917618580909,14.71924558033617,10.116188503898844,12.693916003770198,0.7413357253530587,8.29282812348,-0.2565956471235538,15.150435846705532,10.901250177184393,23.78135744493144,4.439631621253167,14.474419006857902,-0.055217808525968706,13.151772585923942,9.321044971006721,-2.976330792726573,2.292701435239292,15.756223156006879,16.84922135099474,6.116479080469473,13.797259304085934,2.809229114901136,13.613412252599426,6.6834917306445805,15.224230144572296,15.766674680018713,14.390471422717972,8.536539594898166
+-0.062295055988749334,5.948772136829561,-2.738037959448463,2.282823701224755,18.4257346882152,8.515611195756838,20.048108507125924,5.41774471587915,-0.6989481196220179,8.502250783707442,10.770819217649839,12.088019588425288,12.4268106350189,4.091230005229926,5.1287947115629695,16.986275790087902,12.221867708424465,6.34444920488373,12.11401566678221,12.239710681398464,17.73702800836539,20.074565182446232,6.48349288615791,3.180980591099445,4.1207828742783,13.092490473630992,2.4262155201652735,11.161905178335504,19.205332905343845,9.247882775479342,7.7272427415606
+-0.6273783517885855,6.45991213898006,15.491072885483222,2.2747610080791834,-0.36259377781773067,7.615062392390928,19.876973694741334,10.280301719848138,6.049915578627129,2.640265908876632,4.3508896682961185,11.61046807716626,24.33031286364503,11.550676686762372,5.005489494624875,9.407808236332167,7.75935474300786,11.32729613632337,-1.5309279796428585,11.625221746091928,17.896794142571615,10.48109049782003,5.481679425313409,4.181754514794464,4.1662774296543965,6.0155258560882015,-1.0684051636567622,5.48422169206046,11.466075264698281,15.629576653808108,0.9485834755193583
+0.3395342102157176,6.660934973545109,-3.141669348439925,13.836937704755906,5.00714483051258,16.789812119157773,12.779138489195343,7.401212319425677,9.623789366724646,4.453565735360194,6.915959820128565,12.150159842785444,15.513314543190521,1.3181858458435975,6.420073709900247,15.286463361439925,12.038675249206971,5.124172418149572,16.440655423846415,3.2280643820782275,15.111989137484887,4.633041202372963,5.919246801833674,12.583279213920358,7.357003593403901,15.44652580526727,-1.468871358411529,5.82659982985035,5.407530161571293,3.4077315676088373,17.775270336639046
+0.04190485883582162,6.228382142987662,-4.378352972297967,-0.9337845608531925,18.291401832504647,13.488179127467632,7.881610595315262,14.81907972668914,13.357039704240394,12.291501142654665,8.309176121942677,12.398934433332744,12.653042152851341,19.667366044878435,18.46889274442951,7.722166893750051,8.161395044722852,11.666899592666228,-2.264114623922712,13.8151159943945,8.81534395063749,16.70540451546969,5.269954744887832,10.243267375636615,1.2067510573554687,-0.3249834902914373,11.653896295841058,11.63255583207719,19.03634461672526,5.068841232006805,10.581936288242712
+1.4311252111396047,6.939736795316238,0.2384937258339975,8.293664849148481,5.227619983506459,18.22048871549734,3.3590810567378018,13.24162942888618,9.861956303194212,10.68262458026008,8.533784111921355,12.741751290788878,26.00461696225959,8.772933615772878,20.08147820802796,6.048300629910186,0.9239420014816471,7.231549278646707,8.19414881220021,11.151851584425716,5.695543766019808,16.034153678135546,6.7903980502754155,-0.8386634423722262,19.909474106531214,-0.09705005185369053,12.690239072445182,13.031694309212135,3.3852338503888273,0.8760918250863261,2.276145350376982
+-1.0194655201478877,6.221397307592628,12.258414423780438,5.725350371053489,7.78793169034943,12.731101335051866,16.051197499866753,9.555539552265547,13.642268245284038,14.60103968960452,3.051010240421572,11.06326973109126,14.1355075131159,14.661179911106606,11.100399117413652,4.623922451745564,8.363125094895887,19.16575420187766,2.7688333344420712,17.192742447682118,5.116354587582416,14.312107867793301,5.142367811303343,-2.0889477515161996,14.25597698257568,18.697357805954148,-0.51606235234709,5.324941958347148,0.30721952070239134,1.6289929636830127,15.043199703879354
+-0.9915836620234911,6.702032966401576,-1.1913237508574852,17.103761785798724,8.438691957813353,-0.13255408364456403,19.31104130754706,11.881286252453316,4.840593107491794,-2.2329848388827314,4.47485073709717,10.776876807727302,11.828629971373402,18.408483602590906,-0.15068979220826337,-0.7567067798844996,4.90412402359097,14.810569620690478,7.334885762964762,11.992496292990413,9.964739787010332,19.02486174953021,4.746222028274193,-2.365648218755042,11.236941171342819,5.085329084439797,3.6103023237364837,5.4396220614742745,4.868464518444766,8.462423487325257,2.260788494382682
+-0.32611754401401394,6.936405731927596,0.7241300364941409,0.20625943294413687,15.196151324674446,5.359809535517893,11.46953381434524,-0.1353881757584796,0.9411635171440653,-2.199448657034913,16.292304719088555,11.667990161562333,26.3235168837499,4.851336758602228,7.19396524870691,7.592408698584125,12.124413820207653,6.970463085484656,0.5209002088515229,15.38609776982057,9.92893874858072,1.9073378803536922,5.683168304912905,13.330386422910546,11.18503701836681,17.057039961279763,-2.095475314247536,12.900813440586504,18.52719685941767,8.714207624930513,-0.488071237896218
+-0.6256741809397757,7.2122030109105655,6.679747708436994,16.14146263733202,8.843754964051719,14.530523242189831,14.445938803166795,0.6128926224959015,0.309258393322878,0.1080436173566985,16.646146626281848,10.852242402278057,19.794420201055893,16.18601083695931,9.106875889249642,6.087189796587051,14.912642492398938,2.880652466343145,2.5437034289598257,2.387954925711621,1.7237903817982545,13.938655073541327,5.461331101038297,9.58614603839866,0.9259772137539493,8.905188560023799,14.541030541538115,4.580523350952603,12.86206839424254,4.835316015027923,5.581221080382452
+-0.28326995401132615,7.5800802442074735,16.095085128651192,5.539976212866858,5.261725229145952,2.9989637621280103,16.65332462511379,13.884237648164302,6.695707163723307,13.227686044790522,9.846930695136649,11.188342641784192,20.4953191274231,16.63630586348186,14.615125977433351,13.907053189843612,4.563344097498668,12.266643436820852,-0.7726385541675659,-0.7458099714987565,13.113824378893437,11.469479475525999,4.897975520087533,1.2797469363220806,1.5440544559492047,14.164876470917926,-3.1752748076849633,1.310605067655592,0.5120936227807782,2.5672983709948474,14.133270510261942
+1.1368818849128859,7.812490120814002,5.822652541745034,-0.8278906467330723,0.4699154820973809,9.335604993767557,8.433422680228587,11.733920659705927,-1.752929399370215,2.5743299766374204,8.117631554792979,12.397283051609545,23.489591255542553,10.1322932748978,0.6051577073933122,3.054292852121387,10.748376501105316,3.3253413979997895,1.1914892780098845,15.379600512972662,3.425442298870868,3.480633726169984,5.567998553673501,9.174270826736795,13.831690378853134,13.192179137653394,9.162434106527147,11.813986049520423,6.049122587423794,1.614694186745682,14.185883102474802
+-0.5826398964881528,5.77859304891225,2.617672889458084,11.823941003441906,12.497614658163533,5.715128022811706,16.67862049918404,-2.1381463479121097,-6.426742124235922,10.218423617959445,-1.2664447305269242,11.834399999400592,13.054850876840284,11.506409763150042,14.117625059305936,9.400347302371948,14.971870520011075,17.1796061030502,3.0922313083085715,5.04399393321529,2.8199226133638557,4.967665782256194,5.978603371817104,1.5278032653541302,3.3555514305872673,18.110262854654145,14.118086332661377,2.211175572009454,4.633358187121239,7.058442601254811,15.077063583712816
+0.47930655094427405,6.475226888209432,0.9286265216710596,12.894183632888154,9.490316240536426,7.730817374874913,7.6776521580405195,-1.1520996874139726,11.280178426238022,2.848027954429746,17.715100116526074,12.161932236517483,8.899168360824891,4.121977574173162,4.076639604609907,19.416741072176535,2.651698993088724,16.884953172246895,-1.0778900090752455,7.081820712869484,1.6372655449482885,19.248990451784373,7.136426769374699,-0.29433172330236523,16.020489975899856,6.18902016359908,2.20688097068487,5.390517186805178,16.432226493774664,-1.2648367522623172,7.377118822472813
+0.8013484257718843,7.994256166621998,0.9782986586840021,16.949994972387977,4.313513312426769,17.919551188665935,20.100214127059363,10.186146316597611,9.2604071767324,7.817300105907389,11.956507335487983,11.842361461755935,18.337256895258804,11.439267347644329,15.411368200109978,16.99433648809549,17.897407509299377,18.092478307346937,15.380783384970664,15.976436222765923,12.154707761767412,7.09310996821819,5.794726240217472,-0.27225925344723123,18.886661456901994,8.57464097230153,14.09786428351714,14.238839189257929,9.534787862161433,3.576538839818392,10.709007822670898
+0.5882147261150742,7.911395850491807,4.437606950784674,1.7076519841408135,5.309927091750453,14.673653411814156,0.8479455946950942,8.209645974970423,13.937619282923652,6.898803627011403,16.911973457583883,11.80386607376166,12.956563020083301,12.90209065155983,13.406929427813063,-0.500229394511857,7.348597162711869,0.6676513095336726,9.34696869131168,-2.069288464186357,7.53206104205961,18.460894210850626,6.003357495924881,-2.4000460542527575,-0.11558663284751701,18.814228002635225,9.140993298409228,0.18137402609869116,6.507642210654959,10.516357319611952,17.467882829410044
+0.34657205861688933,6.549320424316184,13.861065926214295,0.45480090942957035,12.263110872221581,9.580210228771517,12.059040796084282,9.22828782381193,-4.964717270156397,-0.3930884541749054,15.573730189949051,12.341928728939653,23.13966135749097,4.533145561400099,14.408552933579164,13.68486655306337,3.42711723692163,12.956074533684902,2.811310201436952,14.131858934679322,13.830550712072311,13.774387395116472,6.00338089034805,7.497564701417157,18.206531521991074,1.2199705515183688,14.506904826347302,0.10634101705759505,4.956384305212287,13.677273007924622,4.828266773067147
+-0.16807814507185534,7.839574404089414,10.991506488350918,15.192161003045914,4.56308994882883,6.884435292767115,18.93067509303225,2.8712302115596273,10.179941764637515,6.308407863788296,7.943649565120046,11.068583413281257,18.874039739261082,10.317589108425604,18.962234116553557,3.7542160892485494,1.1891001387626847,5.280594254963059,9.168785366892223,-0.7888180384622476,2.8176083614570118,19.024504484831752,5.853307402736468,-2.429521478396963,6.328595129813081,0.5532745438061291,9.919317314196983,16.26567746110635,0.11014879789552452,12.915203694332586,5.231201946841971
+0.821575067210037,7.074076252516799,1.1808677676339796,10.342569465506717,20.326463294266823,12.770950964525156,2.5142714962839445,3.955794915415443,-4.039879573956467,17.04277111768382,4.556086966051989,12.336246742288402,26.24549971927993,1.642243817462683,12.97548108834133,0.3427731809810873,18.010250347315775,1.3685375701380043,14.720694391636181,11.363986969590226,2.5577342621227714,19.652524865537032,6.9143282258792835,4.567486036042497,1.3909897785530987,4.8940084712055185,7.1110339540296135,10.396093851170795,13.129750860443034,1.0833570769190954,3.7908900323937136
+0.6692120227334545,8.366311715837202,7.054620143933429,6.771884036134061,11.599379430624456,-0.6662460670652345,12.230525343144562,3.7514635310061673,-1.2234797184681705,14.355768168732972,5.729346792973988,11.520078350807038,9.736692348372245,2.8536068686922302,8.663884108699127,7.233855983668141,18.235571171117634,14.893678500555854,-0.28373672867779476,9.323868943676484,13.219584355562683,16.04905868978745,5.3667142861822175,-2.7484590167252216,8.085443342365005,12.315928155051783,12.60661563368864,19.0242734906141,13.513065233383294,0.9167326468283826,11.017021544359359
+-0.07427324111569922,6.92809655306882,2.4573509255794166,17.25876435278694,11.388516244728281,9.013762238798083,20.91171953165653,3.741026527647887,14.264790905149773,10.72595035081391,8.907360786906732,11.609351886852897,21.17630395205234,5.996588115493839,15.014937175502055,12.419736387212003,6.891698082916896,7.7642305196518855,17.875890046780235,0.8613977130424191,12.070253825581695,15.552665258024561,6.751697846935351,2.618643349802973,-1.00813823974749,12.341127346083784,11.73164655926962,4.72586993679735,19.622151746955872,3.2446659791074257,-0.14715770093406275
+0.7822519211346348,7.469949746011849,10.338589231212012,5.068529645981773,17.097149623148486,1.614018165562058,4.415449099735177,12.353151556418238,12.462474401298943,0.46445089369569553,9.636914915721022,12.252016114566402,9.77266237496056,4.2129673620254735,14.777524471866013,9.31030597169271,2.271136951716443,17.256799165640835,-3.129307363222032,13.70853775950116,9.566170572241976,19.005478209374807,6.533417130961362,2.9640102883213864,16.9521910844231,6.157089799724558,-1.207874819246065,2.673772191070949,6.489074683414199,8.571646284710955,12.931692029619343
+-0.1280670378701286,8.027972815877046,10.274296842074818,16.375358534736307,7.88897377515155,9.956260833138245,13.531893680597307,9.284502127811209,0.7569786383687479,0.17669782206976517,13.647368351953808,10.616491892933734,27.644828231604208,18.98564568371322,5.566321491556355,14.093655409238783,15.226815286493345,4.562329267511155,12.191138645972277,14.698550334865189,0.6037552479037842,7.356045827222925,5.367649043870496,12.719941217108252,2.046048885821344,18.657350473451594,10.877280730056127,3.407311426585558,15.440709255117735,2.3384412360093947,17.628437397478724
+0.6680447387568307,6.516240720406808,-3.5874484239296907,2.40694904012894,9.001886779716854,2.172893980078131,6.437378913626672,-0.04259732762195241,8.009371573900964,-0.6672220751143945,14.347242126358104,12.284478615398163,14.609978138836041,2.766874003707601,8.918131637437893,3.7093248558469085,2.5592606334652306,11.551648959603957,-0.8233369562685926,7.780563668697197,4.544859611576129,8.746465666401214,7.130220251188192,2.825806345661185,16.85259488165667,4.7326910867450565,4.432501382324206,2.00460109235385,15.221656418823148,3.373620987543179,17.139420599055143
+1.5394145415379306,6.108923363420494,13.963726634398032,0.07081090091982221,8.302096745445711,3.59879371063346,20.501220986441783,6.530488623588093,14.589684835788571,15.889619514611173,8.545194704814614,12.878166746744988,13.557489422108098,4.270088524975488,1.2243311434498647,18.854580598749358,17.127352311949082,12.082709820703604,-1.846937448676779,0.0016940895149427481,1.8047350220301759,18.37300953836963,7.316969364091555,7.7181532512586175,11.062306283722695,11.473269484338434,15.029859976802229,11.20957473426961,0.9875969561118029,3.28510850186757,0.5526178389892191
+0.7974661044562963,7.713886671568338,3.042406817414623,0.19768690055436985,13.720517612455913,14.532510571060925,0.998617252347854,-0.5034327808818464,12.949063369845494,16.246481362701978,11.847962392103303,12.293910062055502,18.245655899414963,10.855774495210715,7.801992908910716,5.171848296656176,10.870037958050954,6.23169284054879,13.022796776672891,4.32766561826077,20.524102626357525,5.370858695894478,5.5856254315886655,-2.380557261405878,20.089060275791613,0.04917481051255019,-0.5113428829485871,15.071537548566738,3.614050553560123,0.18064964357348737,0.1334521059569927
+-0.2569557718891404,6.975999161115957,-0.5815272571387329,18.086596141787815,10.201556332390444,18.352334307215276,5.464915386283307,4.179363473273466,4.012899800614212,15.00969621653134,3.020815737351434,11.573227826482624,25.50253862445385,14.164373677747987,11.610346406836479,5.827692040670421,6.3287495081550595,11.911805928660526,9.35505000540274,14.470900199346438,18.30011851160586,12.656612680293518,6.4313268369914205,0.415870788311575,14.178817055786018,13.696492237681257,3.224659657377038,11.5385736946966,1.154813847345233,12.462320267360358,18.108063296888872
+0.052711640273630345,7.558715476424217,8.208706760903807,14.942708625755747,16.44292586544094,-0.8258693610581017,19.92635263515346,13.388990319232201,5.881572613407434,15.636129424831463,0.3242943610091196,11.795912535747101,20.993503248379252,10.530747247232323,12.245776581041431,3.310031486039099,-0.5401209596866927,2.2273964779681084,8.937058229857541,12.06662627765338,5.311457913706446,11.665204907974239,5.443132209240789,-3.4139354388541285,15.160828706383843,14.17034140564988,12.390130844184455,3.6901355719726077,2.175013930350257,0.5293263366644645,10.592045090207037
+-0.7710194105652469,7.107067445471707,3.2496535177347097,10.406459003936526,9.001319127751984,15.588045496432217,18.506140630130616,13.444619417375964,0.3093245416420487,0.06139023063133569,9.507002059447858,11.024242436832578,13.648947683247158,13.30890883416651,-0.04834019267562706,12.925571276746071,11.87608270664699,10.864156990626375,0.3550674800436465,3.2809713722576372,5.467106240827048,1.1457633354504928,5.156537921755898,10.626241789256866,0.4230723987324154,-0.028425921781268525,0.6162560471634437,6.298214397474528,2.633268856773583,-3.2437571293590324,11.4780590183394
+-0.4509190600928427,7.288137366906038,4.462143372015448,17.979754864941174,4.235978403716391,0.6914462264886668,13.380982787482774,9.471619386931714,7.9697134758014965,16.683113425254483,11.534235860664122,11.364372920636171,24.85673078578895,19.870738501808695,14.633849325874278,15.884238022910282,18.07733043578933,15.252831942723008,10.472671495688347,9.209712136084384,13.289880010176645,4.502437931413867,5.433461004654951,9.372959832418246,14.60187593892894,2.934686547177858,5.109135188682226,17.667877509048104,12.539671360127095,3.635442128127231,5.431538320378541
+-0.6457681043982271,7.039824036519436,4.851629285335124,2.115480481987486,13.538799571536861,11.271317240569239,17.81935775827852,13.487465354017788,1.9591938975100804,13.305160102085804,7.178894567312081,10.960402169059037,23.05918412305703,14.690658240855846,3.342053946368427,8.413640341959404,9.548452945681733,13.259292772453914,13.282010893786895,2.827610070151346,11.217302528034645,14.76306199322089,4.934077827887148,4.7829994216458465,7.307011721619196,10.134881641458746,15.581928960123529,0.30506426166157213,17.46619653120511,9.01105357230149,12.729250671824293
+-0.3134632547955199,7.319015282198299,13.591160938026452,4.864644005344072,17.628026519724287,2.3301268371760635,1.683220384219469,-0.2885294441768282,-5.162598534272949,7.8463138618844965,8.668268134572664,11.395276887232935,8.832173331032145,-0.6067545239581216,15.325808681967361,0.014324799287024341,15.887474752482207,18.965008377967763,13.402425653089113,2.988441489627582,12.864494040939135,8.850513987976909,5.842857105622555,3.2313397198848257,15.659372166273512,0.936409208872119,6.330570271154248,14.387642305857666,12.830824855018465,-0.784147846665042,11.294908487592686
+-0.05366568216681541,7.4799849752286285,5.725782564505942,13.082230167753497,1.6590584514961275,13.89540103316726,5.968978671205679,-0.3159077350138251,0.06947339586664555,14.074296546140658,-0.713834764216772,11.602728547928448,9.512582941197,5.576880346544694,14.123568054349233,1.4299743666930382,16.478835005526363,8.139200229874403,6.0528487918660865,12.997142457185317,8.931337170383978,20.339102790909934,5.923781857545209,1.6849244664920278,8.617560438508601,3.4061753721265084,7.780841819275271,6.346197253116129,19.59805981653814,8.250245600613273,1.7061796283936062
+-0.6556555554244845,6.9304320967816855,5.471027581452445,0.5057944326386768,12.74104277871506,9.72438127250791,12.237269989845654,11.040077886121225,12.094255484501781,3.2650380227245206,1.958500492215836,11.28145200316671,24.615671870302602,19.23271374521036,-0.1735611831080313,3.2516112327692817,0.7508852235680017,3.0919262312747335,15.205831348563557,9.080712743241612,1.109053498148892,14.23449003367852,4.764670044236276,12.488660675712396,8.132710516534571,12.548267596991028,-0.4250839391561528,-0.1925113768219404,4.983910523423583,-1.886553478026495,3.7391034613934355
+0.01877944514022585,6.8063169190060355,13.003554749260298,1.9503028261880964,9.83441652288346,0.05003458159552555,3.545745965421215,-0.2526712261802783,3.9861092142997654,8.080047362287715,3.2235132556519144,12.039675593505423,24.80651073255653,2.8149667367824183,-0.7553468943972047,-0.7437012496120214,14.905387656516066,8.093267231264026,15.303567999117778,-0.4759915175844087,9.28492056771431,5.621471801291296,5.962524555978032,-0.9681130709114925,9.065903268221406,7.648918388025152,13.932986698600288,10.773721466409164,17.955435901317557,6.388547256482438,9.632462085584004
+-1.0162228172325027,6.71904136261126,8.962674015125327,4.473150576096817,12.341630695307465,1.548987594592358,1.731816133313794,-3.4713162698435527,13.720476547707426,1.4215627372395767,11.522535741497316,10.830289126810332,16.590594509344665,11.150949067792084,6.083448403605985,17.25899723844165,6.915013038707437,12.777253452858451,13.549042356379797,1.8583177714830859,11.359945957092512,14.033635390256377,5.459707152048947,3.7900153433761563,-0.9706815839222518,17.23754257367168,7.284557988621862,13.489436044064448,16.06240451213266,-1.5065830518098058,10.670163294955353
+-0.43111822169154745,5.6541329216952985,15.113864946905803,-1.5908602802114213,8.355718762594876,8.781705193569366,18.451976145446444,10.5894227993994,0.23504663544957893,7.699607634524399,0.6282142710337162,11.785670952793032,27.66828782855023,12.578278258857678,0.29406334353650176,16.299023146171677,11.292799591482511,16.303006780524484,1.918333902865161,11.88025694233597,10.836440972811141,9.72778412622059,5.905839311600965,10.243725508358864,13.579386610834982,3.975083686537525,8.641091859051958,14.875280786611693,13.218688566751895,-3.5849197855532653,6.012887370889562
+-0.4367754325899154,5.9421461936279405,13.730878776214308,11.192608235719234,2.709263405612157,0.6155902364947775,16.267077265686527,-4.93747706287898,5.844284745699662,9.422661980264522,16.84640915499051,11.783293975315939,13.254616117572002,15.864735127809677,9.202904058481412,2.385509095931493,2.467488811148476,18.94256219569074,0.5082519825358061,16.22892966935178,12.731979888402762,15.248427729971521,5.817111108534682,10.516647535167563,1.1685604726708991,7.177722653839355,-2.742312861651559,17.025969304121027,2.3569781897793334,1.9620467999862559,0.03489815809730941
+0.8516262409392381,7.378454868607375,-1.86343481020193,8.177203977145618,10.665446623799713,11.533406592653028,12.459010526401613,5.8912420175590015,-1.6579693260266954,-0.20074453074384122,13.791281259292496,12.343741868135865,22.295617652351343,15.19965057203686,15.737648956777614,18.06938924069477,19.215196030347684,10.626141618869125,9.06695473121744,9.162210883495645,1.664603114927333,7.353627772808828,6.595189528313963,-1.4706154891824479,12.748144911833492,19.882334992409547,6.472980764705033,7.163246421937405,3.85476980811217,8.2730258428233,10.184155852378318
+1.2737374310925715,8.083176953083353,5.782625675237586,4.1824108688468105,16.257980815660652,4.154283328335394,16.957505613745674,1.4408580546493237,6.926930808885124,3.8330986034535615,11.242992344058138,12.211478659973718,22.374316951738805,18.53741688522074,6.386760219913278,12.722158496440406,2.2536468821980815,7.581013564443186,16.77010872520591,2.303867336069647,9.430672106828178,16.116300204239835,6.2589351897401455,1.4379850843689432,10.112044848837584,12.713396627957295,11.274308004997465,1.396852242875678,3.7227097995518506,14.445222506652588,11.828932239127287
+-0.275616959255341,7.352502878698068,-1.4118321743099997,7.448629010733505,15.626450689522759,16.042974339923465,1.4878409220241,7.8273729939445715,7.922896745403606,15.994843849513181,4.920873208159003,11.063128449093837,20.16792912695407,2.293956134328049,12.225543967782002,18.39638927386523,14.367541396323453,6.380542783915825,8.89322456886067,9.174345690150435,5.067611568653705,10.106691288271609,6.0341898248911265,5.516435354481941,1.0198004357641963,1.4359747872854456,6.998061400314655,4.701409250516466,18.450941897401954,17.047773262795562,10.507237095005607
+0.31306991599781747,6.603056745784343,3.4002287947370684,14.480058769851684,13.201467490836325,12.282151906752455,17.79010749652215,8.8068625991219,8.826814616462768,9.509138257387264,6.84303838369052,12.17795524411678,17.722772995124647,4.024535384320107,1.7836759948564236,2.8549282804522065,15.875413142194368,12.416625980934048,15.537299137542881,7.578091618588138,12.11247867618189,7.012485645119073,6.437961487907083,6.8109576893646455,15.17490452462505,-0.19750242680588145,-2.582933506187037,13.448263562764307,0.03567592516540495,3.368155867547384,7.45708551603218
+0.08404160404398342,6.551495097527088,1.6654051638783294,-1.0075227315609752,18.160465312735905,8.610672228534627,18.33347540694848,5.1150915783929385,10.675985273618668,11.901271598920431,12.87238158064572,12.039282406478351,26.215607575213657,18.47748679968887,8.274297970211352,17.78159759473033,3.5438905139890977,7.5346613381420475,4.124894228655947,7.274306579071108,1.4555895290512773,8.67941001099667,6.642113961617036,6.214782741007302,14.695389301005674,14.689825404720862,-1.757223446840908,16.763056623493565,7.1720351913305915,7.533601498046172,-1.2527520942808898
+0.3300058578295454,7.226405267338751,2.7500596770381946,16.639995335838606,15.809654566712783,0.8750293761901435,16.00261837857225,15.793549969175707,8.587609960204016,7.808908961687873,0.3990133110939844,11.72894743980095,25.024057716103,0.21398483715880265,4.838563789333815,8.547189794878342,14.868191172177983,3.611492738628659,12.391374423462686,15.458986442833424,9.060510278957262,15.780082104746299,6.837914684821075,0.6878773111160738,7.117500328748516,4.7571548619259865,11.044878354491798,15.603353921730122,2.1124139259221693,0.9798370845191302,-1.1639729239348533
+-0.14527672351017898,7.2806263023999955,13.409984458430099,-0.42329047489466737,11.415839130458934,16.762156382835784,20.01815690123231,7.723463237988307,1.2265091143731173,10.033700733311626,0.5619429408903011,11.472404394635204,22.088870406938366,14.11491692944309,13.434625415231377,2.0520214865719346,12.89407278902973,10.099051028921446,16.762503050233818,10.306887692481965,12.365265187352295,0.987990056693695,6.011395380124131,0.8675496511892238,2.666734858442755,6.111905106803473,15.185339114670136,2.6769537408460398,12.049018832216994,-0.7182221083790985,4.2335958939780305
+-0.7782890497838552,6.285162861474651,14.25437330944894,16.900962349781665,18.22383631531234,5.588404113357289,11.985097864163222,9.328187226452604,-5.017792567640585,-2.9218119531879028,4.026047601623201,11.324325604535026,14.165077229037735,18.732816341280362,7.248520524259302,18.455750817575414,5.256036922173031,19.050917457658898,15.943536568036212,5.880182677516656,0.7234813103981317,8.585295354011114,5.573109199047294,10.988826770526416,13.308652798176597,6.3115516766647115,13.039685057686203,10.954240950736494,8.130409933994633,7.299997085650274,1.0165682144630033
+0.08409802827489364,8.07839201747602,15.395967264276031,8.335737399557692,4.643562038257203,-1.277946185092369,10.41756821770753,11.14806442017077,-5.593105423841958,7.583037331006903,6.34827107857414,10.944966075460503,9.532562993244746,0.8435906794420109,19.011762160686253,13.04366109189139,18.173643293116175,6.684426104419407,-1.7630037601412143,9.101320547392403,8.489274794938542,12.829575293422852,5.525952515930285,13.006675006641915,10.319618346271188,3.1800318913898096,15.620006191266917,4.179472322989593,17.855000926160955,8.108318767668642,13.855745635380314
+-0.5113808032206579,7.51037494670251,11.166241941104865,15.356100038780149,6.49065537709563,7.102249834358608,4.458669405180011,2.8657629867537633,2.6333735339873767,1.5055886590694927,1.0370706512319856,10.992255381994378,14.897175988962093,13.753065149676408,12.49694581833134,9.043373132418976,13.472669459154945,15.985527453849288,12.035230122517053,0.5778442923627196,6.140903528800585,0.063883782033141,4.711832442839613,-1.1365597238503735,16.21207818322687,18.716907492823523,8.651065348764416,16.68303033796834,5.957406376832578,6.410307461146032,17.83775869420648
+1.869547183544404,6.955286444899354,7.863245244183259,8.760277615422943,15.363216947882778,13.668903507231022,7.929820834925511,12.841913560954852,6.316087531481457,0.5511392232858485,6.940067295062825,12.77761549893302,10.68378878400165,12.793542566837543,11.917816379481506,10.431983705888081,18.17700795349602,18.20489199679062,8.879137700900166,0.017404055563758764,10.254858573800504,3.9733550232866754,7.854565268483191,1.5289416456535556,8.2889630915529,3.219581673788479,9.296143618531042,16.227290894634844,15.075970988622016,12.908761219712439,1.6329558784974179
+-0.3638313039541473,7.328781055280752,16.042896883781964,-0.9000430878677257,5.823714450625225,16.653720566336084,16.250428447888897,0.9807227400225367,6.42018632243058,9.399738490292009,7.283756439187307,11.447076318267314,18.50110645501767,11.158748886242686,0.820991519480522,-0.4321648893185178,10.472478394008952,5.321359983095084,1.926802431402563,15.818510131440583,11.515902422992747,19.426483177501147,5.830657443360377,-1.6830074436150877,18.70512504344158,10.531904212686117,15.536648261213816,16.523768879791717,19.134324468105834,-2.3563431067732816,2.1639069990211386
+0.2699792890921989,7.544288484192881,15.054100117030178,5.983897987730682,6.280698045438257,17.230325639131465,16.55692466784854,1.0076262008933483,6.328589353577721,11.14120957135105,5.919729979002005,11.839819046065887,27.06600874959409,15.41483903131198,7.422220208388763,11.253284431612805,1.0294242780425247,17.628023890179648,5.561608509465316,9.01438839037575,4.707820927017234,1.2643710439922717,5.849524676596219,-2.981575398488271,19.211772084959126,5.828185601992251,-2.5915469474749964,4.186050542359549,3.5960325653449257,4.307763474189665,3.269927107865067
+-0.43321975549951725,7.170091302087153,3.299233336638305,8.297150967415034,5.590393782586293,5.298192129386463,11.159868947154266,6.837994636396125,0.3639099266697007,7.324186469369331,6.289268979936283,11.346540717741417,22.705586765999204,17.56494470105974,17.62438030762077,0.6663966149649453,13.743198395112763,5.861862961887413,-0.953750132818474,1.7425798414354885,9.42866852369916,20.494791965972656,5.67008843013869,-0.016049992664673725,3.473958096207964,11.003225787738693,14.983818850060285,17.425248128942307,11.576597534237568,11.96943733149753,13.17350074350675
+-0.6687074397994971,7.520542239096087,-1.539479750983972,8.352598283736354,2.121343200780263,7.993663322603988,9.295315107114622,-4.4692658812181545,-4.973721686483448,7.704177500051386,14.080060804781436,10.730103015589215,27.039089134986284,0.25617635341918904,3.22023505695757,2.015881422725144,6.196865975267867,10.933254831951707,10.371963643276871,12.300788965492838,9.17544230427421,7.861575845800909,5.30258085208073,-0.349765811152145,7.421235786040021,2.369758593352989,17.01388075906291,11.908422065855625,13.507290877334619,-0.2135847065845908,11.264641619851332
+-0.008467253055655908,7.570983149606923,5.455488936074548,14.22764359677394,15.921872638700458,5.174291588344818,17.874621033972844,3.409713011417156,8.064742594952733,4.752608312438945,9.727572360355275,11.456408107421884,25.71707871400363,18.817672798773017,11.394283924092361,1.114699083603714,14.618257865406276,18.071466307774465,7.722598989853475,-2.0700676961049105,15.17284848452935,6.46622081346764,5.832022878545004,13.198746348174685,3.9951762279514913,19.688109154062143,0.4197047082822944,16.841755769256153,8.676586220521767,12.14639627222379,6.110395027886987
+-0.7160160169310664,6.6204748135368385,-1.7807604423716494,0.6146965641470992,8.69237902706666,4.849485885736447,20.369402502026997,4.301429548256334,4.5960827455050115,1.2663158645672912,0.7184679147280892,11.47473639547086,18.517664637466854,14.58010994516532,5.293315140449195,10.543680736545856,14.275573651456389,17.041244285792875,15.873449471569327,6.5490763228037885,17.607607453768665,8.80745425153314,5.144545127972073,8.235366937888521,13.653124729852914,10.751788845861663,13.115709974374393,10.578579415215673,19.67538302757702,2.1615022255194773,8.782650869055917
+0.6151992053483177,7.83031371234769,7.343098610543727,3.6574464951943444,14.406141419002347,13.989880208633995,7.558249900867667,-0.9612144112464421,10.323008086111656,-0.9078262252550963,16.51952659613205,11.789278583448683,23.194796662077955,18.12562156814556,13.383217822117983,12.080346873141812,0.3708448451415619,9.468441183454255,7.763651020611479,15.722557530677228,16.21097406865286,17.615325707741178,6.459540011571668,10.895128779818155,2.4743605399732544,16.27093751254708,11.06447151510204,-1.4852636033455493,6.947848214643912,15.916199400279108,14.662142754572642
+0.032402862065045876,7.853494200203809,15.563629476630133,0.03694835621208444,9.68729952109884,17.007051375507952,4.847411508177599,0.02711463730269515,1.7985943958994914,10.315187899390189,17.631168963761922,11.354373272531738,18.267211935492455,0.6031928209765756,4.1431414702574525,8.570810975333695,19.233472032790452,5.692711216482721,-0.829444464177616,1.4380832196768605,9.469526234268473,14.848608535628793,5.688655175425842,5.467543418154457,13.88421009547707,0.42707477157706114,2.2873924069573945,14.033585720362842,17.592089696622004,-3.2033097061451103,3.3878958211777856
+0.08447123143105052,7.937847041056797,1.1595477018444473,3.7203365762803315,10.22594948490588,15.102028350606147,4.626831679372621,-0.06696012381431517,4.2585239413487805,14.264007536363195,-1.9363013286798856,11.111756264189856,27.668400886700557,12.512287383844301,5.274751846903682,-0.8483075981854588,12.362193362278216,19.403534349224497,13.075655418348362,10.193887350323244,14.690097024600188,17.138928895386968,5.969852187713857,-0.3365826894882717,3.41859934649589,16.631558879420304,10.906696796786266,9.375076888916096,10.351619518830608,14.316029806942522,8.9959737568769
+-0.8127041403329106,7.223941879422228,8.963830683605742,10.947344185329813,2.5634458186683915,14.987644771112025,11.308399072792616,5.992166657758517,11.10306301606342,11.269519481550216,8.34470474286629,10.986769340905111,26.52246388061602,12.822102286453106,11.136987763717654,3.825549368250252,11.524522809052028,10.333711264879863,13.937542257488396,-2.458359841155729,15.401257420112685,9.223520470360135,4.818499866015978,13.11717784077432,9.722529407499856,13.887536450310748,2.9845597093519265,17.97550315550288,6.154999486765236,-3.959547369314278,3.318164693190969
+0.17973467924578493,6.835786501770805,15.790265004755327,9.664514016034905,14.553805709561628,7.268952516518269,6.7350928348419234,9.901253581216597,8.502897588390086,2.6350526420749922,2.064540929062108,12.134869324366209,23.011066707180913,5.503796321601353,15.374424913462557,4.1083139951963155,3.7641649513532,20.004827547601387,3.117428595031641,-2.4603608188575317,2.69971194733348,13.588572751222198,6.414164427350357,13.636208163530105,10.797178917638648,0.621720463430325,5.8371391374939865,7.788272604912894,1.2804598177964301,-0.8059263965586214,6.462966316113247
+-0.7068223040638532,6.13233357414183,5.56851668215848,10.825446844962551,16.79083939755398,10.972633595386334,1.283203041251772,0.2461459438195011,7.817996073216843,13.175664237325208,-1.690222794618034,11.493529240584733,8.32133694266204,17.334593493665423,12.727650522970823,3.214809428604644,1.8326073693219556,4.390861372257925,15.438255911752815,0.5243188075580028,15.81468038681173,2.191343420542834,6.093037019081641,11.761878393231594,16.493588794527753,18.805310003898796,7.557840021003496,11.455782780075133,3.446829841290599,-0.6528222536600773,2.567527517572568
+1.1477689788768748,7.408699512223101,5.4275241717366995,16.6831273622265,2.342706530369144,4.987026979016463,13.302193665644259,-3.253677670893092,10.463341542751113,0.4445673471864246,16.95871974042705,12.459120306382228,24.155773960420106,19.207014874435842,16.365787256045675,19.211381009327404,8.899846411862418,18.535478989666796,1.3587722432750722,2.738604018967435,16.85987381811541,10.299258864578455,7.086159731947073,3.253672136983437,15.726319971797755,14.95829355937167,-0.2702232088193392,3.8368360172818914,13.992022455570122,-0.48237446613083534,15.935984069274562
+-0.10425802841723836,7.46334299976289,8.892422442871693,12.242972282193351,10.84217030797358,0.7401045242277178,7.407406773164244,7.877590135115771,3.345442128458288,-1.855728703543135,14.745406864342645,11.4560679218234,11.40973060711405,6.5355510182725,10.813648828326459,16.5426576650113,17.472062829034208,5.928191797967308,16.17272037279809,17.35648648782272,15.879426777754238,13.680773754075767,5.832440005798566,-1.483513690918155,0.8157504493874139,0.4553028065734655,3.069071164862123,17.165061067289862,17.88640580107269,2.6136673305525626,12.645364419909036
+-0.02581112032421716,7.051313131607666,-2.7856154029619518,14.977321615183033,12.29288769429116,14.48249339757177,3.7285202480990822,5.954265487907378,10.064817284425722,7.988815808789004,0.9162746035222717,11.840047610555349,9.554394768995106,18.972085543117856,10.930529567393524,4.652992380603894,8.947981268434704,0.8737566948711315,3.5837296031129124,12.894323687259437,8.537928674222293,16.759055944247173,5.873604314925005,5.3516262989204115,2.7252254552496744,10.535231063685421,15.477659680171307,3.6929255777494614,17.669030232769963,-1.4930472220043414,18.827033264611273
+-0.7143125230609382,6.833001917912055,4.318705196073737,16.034960437784235,5.0504184545229,15.137239264713328,20.604574169856257,-3.9120240179671875,-0.8723337168334675,-0.2940768781523832,2.45412292557849,11.003522212523503,17.63194888610334,9.69011949663154,5.317035058440025,12.202694588154591,18.986970177968107,14.438074294498552,12.797344504264437,0.9053179831851869,17.564614677023194,2.4792328262542487,5.9790521008243545,11.338199637291225,7.010207640180049,14.654024728831551,1.5926439130063823,5.48307389584329,8.262814501061515,6.761285179526316,12.148432062543785
+-0.49345927516819543,7.137765394876516,5.403288035185953,6.413590892345276,5.76549344093333,16.928093439214607,17.875228030849897,-2.16965762188035,0.572828991048401,8.932499724911711,2.4686387182176386,11.333453279939839,9.87150669078429,18.50844498579244,9.601811493594129,-0.06007430780609716,6.142170005408438,6.887159185358321,13.372058283368009,2.238209842448846,6.2841092123133695,11.300336993549596,5.830912586853927,1.8430507413563184,-0.12009063076815168,2.2932499901587793,1.5426965970743005,6.109968668655521,9.462063665510264,-2.8669078193726154,17.68094323727992
+1.2242418097545,7.431033348034429,-0.5359054115112674,1.2677732706070906,5.576945985143965,2.267906253794232,11.232291097322696,14.179694160103383,11.11293436397037,15.778330374674937,5.255579790532497,12.322937195044272,27.935040287579806,14.014436228823355,2.056724760367331,13.51629484665602,18.38994055551283,3.8555893439462796,12.406603449798466,8.049245805998249,1.6224701247789834,14.056594041194254,7.229002580131395,11.39670613301547,7.712902985568315,8.538449469912267,7.899595205119719,9.917298619546663,12.949074356419468,12.15742079615385,5.309836636269996
+0.40017651703341045,7.289530059657158,-4.032917992132656,2.0489761894682577,19.078693396691882,8.596437147469551,5.201823245941036,-3.6304852454960566,-0.14340029192881598,4.0531912432488495,16.364870106583872,11.903690713421598,14.337679048790115,19.46582245827178,16.897381749114025,3.096245398686623,13.418271069481612,17.98366786242218,1.4360721464671133,13.342607060757711,15.6035833439706,15.581912980858718,6.537421876086065,10.282562377770367,3.226983910641364,17.882412800261285,15.878166249858975,13.59532542599806,5.101372032455853,0.1790032428682032,14.668539662610414
+-0.8314631813269128,6.470462622798614,6.621386557363578,18.699367740907086,16.287782527439443,-0.9714642798140734,19.651411817656218,11.41272663885552,7.960552516167683,1.6982726242728114,5.22120173140601,11.002686294544182,9.469434383532398,4.5733850472048125,19.515294968943742,17.422553043843678,18.22500685606566,0.611101415237215,11.4028609609001,13.956351813138525,14.648816355065692,4.856465738291137,5.297474390086639,5.935114213051567,10.041993778286013,14.792957504057473,11.956310865254345,4.273318784445495,18.439011702266782,-1.20523022527152,13.517935067983746
+-0.8648958636428065,6.8400062566788575,2.4608600664191176,5.846187568211022,0.1786392235927535,13.36855632517432,3.112894999125599,2.18585846303131,-4.577652254218438,-0.629586311756622,8.591904001671576,10.981497728088021,9.72942053382074,4.37967849316084,12.361774935838675,10.64277588456657,10.254286653791107,13.158050712946098,6.573648077782684,14.778041221301933,15.179122186624443,18.792186999637998,5.905726841803569,3.3343039807238855,6.023237855241193,0.8663810925606423,13.628175357760899,4.581439037633698,2.8227998474497564,12.474395345329167,4.405340578682095
+-0.37868684389665686,7.495926286113379,9.521930255832368,5.963178285292601,2.285759052072274,16.001568976003508,12.925190982454275,-1.7342490417096759,-1.3906355474670202,0.26147689246298345,13.34890134306413,10.960984080183067,17.077163117034964,1.1893639085381176,12.788510885044605,10.191866531895084,10.603592718485224,12.696265959366448,5.88846522530446,-0.7819370353325253,17.827610343492815,15.102017438361761,5.379325510344623,8.019228752158696,2.417116103112207,8.130831893967335,7.820899885388712,9.585576722280038,14.462600957931318,13.263741207338601,3.689648281090566
+-0.310265763077921,7.158867310752335,9.866138407272224,12.995535133567886,9.956682368006996,8.97410207756491,15.226923908743206,9.211736527724414,5.1222279997295335,16.061948620357427,12.00913074773284,11.465385130798367,21.887534662325635,5.482076814577805,12.292903019531279,5.502673863270667,14.59244638946864,15.049895288095072,1.4155197874329257,-1.1205364085344094,5.333740442987487,14.752120471237976,5.735116372215987,8.398598910797677,10.398130022318709,1.748273152702847,10.131937608063618,16.17288617423825,16.63871058212247,8.350549312226796,1.729976176995418
+0.8825806044953269,8.127539257729582,9.90548640615592,3.7887920740534398,19.27640531808308,4.560776578867841,14.39629673226079,11.176469911524174,4.506651681272296,11.807100545202122,16.091695878054637,11.764752891111607,11.392391039307189,6.936512448225402,5.033990079245038,15.29535325844098,4.682785426206758,19.46176176562985,14.223177277797983,7.206090792024119,6.880214054611889,11.720418351269048,6.502104784015927,4.6803393976782175,0.9343105811666028,13.274266360369952,-1.1858771740477412,1.6122332708078364,5.9220731098921,-0.07995016447660237,15.473291958262385
+-0.09055617378128229,5.897764303258773,4.5867560463093735,0.3236309071860096,4.876384164250894,8.229065965608076,19.98386380835401,5.3003611040218095,9.400715538776883,-0.22430955452855975,9.377658949835423,12.13787615414542,8.769709327743993,4.0499443747012815,16.023869213990203,9.140913014982605,1.2849371459493248,13.937949676792192,0.642281047370882,4.636074494242558,14.414812266081153,7.5082116260312315,5.645200807529517,8.848785741282502,13.995228974243174,13.186536342620894,7.35067956913721,17.929976749914502,19.359516909629285,5.666253211039247,14.524531634333968
+0.5781993986432743,5.83110907355901,4.937414511694781,-0.0876573858057892,15.066037405022392,5.0917467594093875,20.949832327967275,0.7953353848030567,0.9189015406446019,0.7437266484964571,4.335569710556355,12.458944348738907,22.074756435635525,5.725604871265684,5.080884398787132,7.570000517880681,11.30578006580406,6.091880475697986,6.598736619880167,14.896832203326264,2.30244887487531,9.591074449278278,6.747692357797546,9.286340903814452,7.1370696939864775,8.067700684033055,11.945783158780916,8.929972868258785,19.32022186673958,7.279762161078509,5.147310795402644
+-0.2635420876623497,7.066192158736891,5.821943594604439,1.331444869573394,8.534770944732246,3.1472312862821443,19.672066739724443,15.146440302605848,3.72598376318244,10.256978121789945,2.441349703999519,11.615043743729599,25.26713036736222,15.18960360615634,16.179012000073417,14.75320271740786,11.867356660310454,13.661798006622572,2.5386210534617906,9.250691995412666,8.08008267411516,12.835623592500333,5.72382786867121,9.300231467322003,12.341817011971735,12.838409242680811,4.073288076278566,1.356090733478613,18.913706500330814,2.201765735866962,7.321069500787527
+1.0874058601497723,7.738008886644266,-3.356685612924437,6.688065858612507,1.5465080079058318,2.9917370854297562,13.613193663245363,-3.8933254512907167,3.10805604358191,12.67540760155177,-0.1240294510057218,12.29690548715732,25.385050142282267,16.83829815448297,15.734752931716992,6.222660778425341,12.985811846571204,9.772951651290615,16.740398467239856,6.834403319721592,2.114141951251689,10.729160083426718,6.515522647393091,9.054728636604704,16.115667024503093,5.483540214558175,16.200020013502854,-0.8762281310261208,1.9243915799226272,-0.03467735204932415,10.274258305149313
+1.2195236901293793,8.217694560746718,1.2126533304748897,11.403060193345283,9.75715584731293,14.251148902186506,20.12372069524352,-1.0458814151030102,-6.007633944047735,4.964396422435354,14.414916048584157,12.17318727731597,11.968316398007133,9.040387046080976,-1.2490017125961081,14.638781360626718,2.640653540374039,11.735896022883804,16.295384393343692,12.798855019759106,17.757856850996056,10.099023477710912,5.987210697656303,2.271193788977709,-0.5396880031387976,5.606432713260821,1.2024857328171645,5.135155550666958,9.95415881930839,3.350036368456834,6.653185509653261
+0.07495692028699452,7.294022364913257,5.638669745145126,17.133163549938118,13.39274985950121,7.569899843256037,3.3819567179658367,8.729783502074017,4.57164920794673,10.96181048724339,7.539853188727443,11.854824406563658,22.426175569538298,13.094900641110254,13.649893816128664,16.235392954693904,2.431564107632269,16.47470427289391,4.121673537207597,8.04270231521014,14.930369721692097,8.822527970628006,5.420523363219392,4.206905891493745,12.280573484102678,2.760365220064685,12.324414557089877,2.123447342651925,11.323440264259922,7.026954241437691,3.908286305954622
+1.4743740179057807,7.835905480612883,9.142707312969861,8.877806766548044,15.838002813208671,17.94671656200209,20.066710146528084,15.955530782458236,6.165056891732442,0.011183387657043374,-0.6128522287242273,12.366837615772386,22.67722834153199,15.254207571515353,11.20881635897311,10.710872319215449,2.305500142649702,8.082405618464458,4.936421713788503,8.121742969062346,17.250996757514994,7.509477813553481,6.95569954380681,16.23231770558504,3.8429441123489596,7.747789527819409,4.870776281023157,4.75774739969232,0.8156207300681242,4.248005514747345,-1.4991165900450998
+-1.5343921027338125,5.719864833883795,-2.511393501609021,9.616544524231681,12.06186642006075,0.28295757204644184,12.57429815701368,1.5609679815855433,4.3684387148574775,0.7532556440666783,9.747414782935452,10.383423881683681,21.839879568084243,0.0014575880950323998,9.28223045627209,18.06586211076448,12.366864776130717,16.993008979245992,4.843352997892954,1.3508336761968938,4.759163847470534,15.236620339680877,4.691843273366945,-3.127299184731455,15.745653460459792,14.646033768451108,16.47301688602327,0.690625110429913,17.729440613978184,8.231785090852561,0.12325906996323255
+0.26889751189882477,7.887930726341612,13.640456969040363,3.205074984556944,18.743390477535563,15.881076672852755,16.63445561801563,9.884159879519695,6.263304181811565,-1.3551689241038627,1.6246360034143343,11.525736791360504,13.762466831760221,6.6581554801697855,15.202158783779515,4.536048048991827,1.4962144381934692,8.049979019836314,13.23816018606317,12.113883934659192,12.530012015541871,1.4099606876769961,6.060406800760244,-1.7522860015066302,1.6866835365901345,17.570986623865053,11.87339147130852,18.958171055114605,8.701514905639419,8.612626451117322,8.987002984353529
+-0.867464407017949,6.409325864969906,1.0995275604903885,18.557699661598466,18.051360893821798,17.59358755698842,16.641292348276725,-5.0514892657487955,-4.4242560091693095,13.861737928690959,9.078004365213836,11.262456828966744,22.000376218209286,-1.1933825733209336,10.033676940574551,10.475508028330491,1.1488612005614929,8.92596718034423,13.537765237935504,15.22310779098839,14.8362864610195,12.725399032957982,4.810758685742963,7.40232905568393,-0.4314388068572655,8.168630632606437,15.401240299961724,18.142044005896324,11.293406765473158,7.403411393162235,16.207701760146264
+-0.5716027813959361,6.669658475639086,13.167317903129351,4.9569979550623025,12.390469976959933,8.67501617229435,6.662274439342058,-0.31087010136528287,-4.900945901095006,6.649432344448008,1.9207017426424198,11.325398069618673,27.53645131974621,3.309112701447301,7.679272175544524,18.66706709362572,13.584174057793128,19.084512405278353,12.047199437339263,5.289654572608775,12.082480261745292,17.160350892634483,6.517124475979922,0.44819043294267485,-0.3277011605443345,19.146645194662035,6.411046635150137,6.155890735475117,5.970224519485534,5.052646985185554,4.631595232137514
+-0.8375021941556215,7.168125585863986,8.672646956919515,9.571770036643773,4.808326476772903,2.549247247784983,6.76837556812489,14.810246331838208,-2.583971608982071,-2.9726305703268645,10.86225584727874,10.881566819236776,16.6857300428527,1.7427505243395274,14.588144010462916,14.252577069176825,12.064395205381956,4.30144730817619,13.06262196484328,14.537593067272812,6.313228165475623,7.38918847466222,4.91512361039786,13.941053519173472,12.08889103168034,4.396479608387276,0.10972273272965706,16.67567091059359,18.49097305053864,11.578417822283242,10.09635776261921
+-1.0511025770482387,6.600831824121944,11.04942160457432,16.63862388636955,6.047074148306569,0.4122829280822877,1.5176352013817294,6.369792342856411,0.4781629872092755,-0.43305196841083504,-0.01936474872793601,10.724682374038975,22.366131881226735,5.375446580039277,9.848298038885714,-0.527769995834916,7.01679467304931,0.6183848553543712,14.829466221121287,15.381624116670407,15.956368084638056,3.807232811371474,5.229887248642809,2.431939749271665,-0.0006124373201786483,18.513277331374027,15.933525606424723,17.40783280758892,17.814939949588794,-8.02134771067502,2.0385951385959924
+0.39079285272769215,7.194119771349748,-2.4797805613953647,4.9205081107742075,18.248923509075574,17.990540088278863,20.313816551272005,2.2562980873511833,15.33004513654828,6.406883064152339,9.706270676238177,12.043813687557552,19.18213828868357,0.05010466515562064,4.103327198091522,8.244884200855298,11.964061131706302,4.786191939073053,-1.4285716181426755,5.92992629045088,17.87934778361523,17.896386185778162,6.041075025843342,3.2345647039459724,11.640511680644545,9.691707116145801,12.25375784376714,14.4274167857993,4.04362692835862,1.05802405532177,5.991928570171229
+0.17385578899875268,7.134577429503016,15.07400658331344,9.217974851519843,11.355910934938205,8.861548641241704,17.815122395925762,8.693981576907106,-0.8923362892661891,3.137011321175427,3.005628432903471,12.002100436392315,9.569464058812944,2.659675278548111,5.547792884931376,12.597948217616699,10.798093599662142,14.534677150993598,0.46708478825788563,16.86250889566589,19.425403504198886,5.122139996283124,6.0368213816386005,-2.814001745554201,8.172248282131275,15.871660581603765,6.984790631112893,6.439937181853999,4.447035892694057,-1.6154025952708713,-0.6427537793391256
+0.8771962809146582,7.4744914787239365,0.8335629684634336,0.22523990100969535,3.041238373263896,15.33300550593999,16.618088357145822,5.680429998929302,4.3691834448774305,15.081201699487561,8.185629406948038,12.460851260541139,13.273052307271826,16.225848321650155,7.308847694764156,8.934603780684325,4.441095357041295,3.951624938393337,14.274352703384277,-2.5391209536176813,10.591009722453627,11.732155569265078,5.932412219225293,1.9725110111547037,10.782168147024185,6.417531128668948,4.118626886872906,0.866089513832419,6.409468417237857,-0.16948107120709918,14.912884201211543
+0.34531353988571656,7.912453074542967,4.726346394916813,3.730900350903278,16.22421800173005,4.678652606744652,12.353707691453687,14.778389860547657,-1.8049874937069523,10.232824646221571,10.105949751625374,11.293199940230735,25.51142365492978,15.485242817690436,17.223526190164577,11.588602382723,8.38326113287513,8.453952696226661,7.639621231494374,1.178031359328247,7.395126133562211,19.56765607923942,6.449996789925285,7.933104211990319,10.593973378150125,16.27629746567021,7.610691018492565,1.3111872132383198,0.4262273303622681,9.868861415594662,-0.14096592368155209
+-1.0276099446385925,6.354843785051573,7.4872292469272566,-1.4769698177302235,3.5321840605838375,7.803469094976263,7.965335253181729,10.393484977025533,8.590806808110356,10.565771851746007,8.776180366106093,11.06985124753489,17.684308396676336,17.94012226157208,1.6021955881596028,14.275280625501706,13.710211600593018,8.360482438489834,16.7217104696144,-3.26619763786951,19.889265176093218,14.936443278954012,5.484639033969489,14.863863675494141,-1.407383644016928,16.610451618057347,5.582501234413394,17.738256969757707,19.74660019711277,1.9383121257213807,14.712635275183247
+0.3091234394501067,7.727419348348629,11.556052241066983,4.781618455632756,18.222323297096754,1.218157517445235,15.671841679112596,-2.9474580586198798,9.77321828256103,0.10453438096692386,-0.9111178974717015,11.704113811323985,19.08835426325211,17.81663126605938,1.8818591399773226,9.90669725951775,9.079981401479204,19.05003263456299,1.9288405766608285,0.756265942862127,19.005806044189505,1.5175414010888293,5.713552363003069,15.37042457412165,10.906854878353927,15.660513761173764,15.803114073346254,5.124097755394427,11.872218048402829,5.826221976615088,1.4264127166375076
+0.2633274357562634,7.139070344196519,-1.981360677127249,8.194978958664537,7.989000541606718,15.091938821515615,10.837921229879486,1.206080967294799,13.788909916472761,10.366038063346624,11.690800833379386,12.009295852131633,23.86415260399308,8.353141528665825,8.25846446512512,17.075031271478274,19.18489757250621,17.107370089116763,1.1591722745106185,6.379672801215624,1.2485776778503723,4.300382416299689,6.504439473810605,10.049936548197524,9.092066192268618,10.869947394774917,7.442374725849395,18.350510604546553,8.648588043397107,1.934000878244344,13.328403101751647
+0.04427208064996429,7.746075006876999,3.314465993166009,8.436633434358798,16.556039493991847,9.874079850874688,18.501654410537938,5.718395675567787,-0.060101618840698166,15.777272448313024,10.767202226690745,11.354454948237686,20.059695466055565,11.987416494787023,15.195026275666095,5.96497813765942,8.022565169154824,7.84746992218825,6.300260182399803,8.45135078253493,7.202314564317108,4.4380420044932904,5.717619578503575,7.739850384562505,11.085459881613147,13.753463647008262,13.074011161038914,17.88647965796195,1.4423877241552638,5.532182288175892,16.8189308973572
+-0.09310439681239077,7.019267108746857,-0.6318960714599271,17.655752610806587,9.521991825986957,10.22281396106312,8.299027660445356,6.520934875489552,-1.0116194145693598,14.840929884626801,11.669201790917002,11.440941295684263,24.330194737455706,19.281462240208725,10.05874927175033,8.759564492798656,1.412118277544213,11.034615186661433,7.977700083776048,2.7532788959197694,11.752668580033783,7.315601576966172,7.0266447936416645,8.234228185184563,8.954914823977079,13.184021800669017,5.312235082431436,-0.7697544108608403,3.3870688971050225,3.0254275664541233,7.116358975036913
+0.33545198597566933,8.039149013197042,-1.7172889736568226,15.31722521113148,13.148046691601547,4.495697719779415,12.07207493394893,-2.355981879332064,13.942551320441241,5.02006441267151,6.906265823359009,11.451472849169482,8.944459847037198,15.610995692657367,9.129855574755222,5.662008801151668,1.6836351560834988,9.775573776025787,14.057535759986356,14.224356037271516,14.95008106021742,1.9975966595720553,5.954966873798405,8.244563029481352,5.8288939249959295,11.686692970449458,16.336139587494852,0.8404896715124935,3.515219180084161,2.5668423222515004,5.06149853523465
+-0.191190681273799,7.437086212530226,4.259868451542913,4.1206585629823405,13.299937722829787,9.742718822572629,10.888360197934286,3.950286938361854,3.390132104510289,7.911306642871572,-1.541111988583575,11.436186414708505,9.18187480094327,7.774201347078343,5.334455279860661,1.9640025668604189,14.040451914953008,1.699184550931001,16.445060952564628,13.422485338278523,2.6049740880739627,18.863441380546483,5.827803431436821,-6.1953496889319855,7.795360221471475,9.562019541847635,9.330829821715739,11.325501779204599,19.17506521430153,4.0978552210543375,5.005845144258176
+-0.4495269684143708,7.886858053858765,0.7972053426163415,7.863118235669448,17.19541606597997,7.360932077450961,8.845503170217087,-4.370309190075505,3.248589294084894,11.909589462010539,0.1812405028218862,10.451442116108955,8.843181588258648,1.295172491622127,-1.6393072482686026,14.10434015291412,9.359512555647957,3.3921898441250242,4.000023800572985,3.7226470176311066,4.743229609793186,1.7985339817737422,5.23813841942622,-1.1001846329995293,5.731895996249586,15.933450358194126,7.69167877958084,0.013865270426501687,10.070329045738838,1.0686980833255326,3.9899925602406157
+0.7550594766638156,8.207836169641833,10.109540148315872,17.796277177772765,1.070739776351802,6.001764910553382,5.408219702588177,13.88377543109054,13.294204831632204,9.304037671226828,8.00407054221852,11.65227112486087,16.253024427796205,17.150666769000914,6.673725486191364,11.993302460452192,9.364997441779238,12.418325264822158,5.80911766632079,15.044918380489435,14.583728233438096,12.118389249720124,6.248113763947333,13.687903267036639,6.485550081788016,9.434990191947909,-1.242124066770005,12.508310491756953,15.572077933191924,-4.151054887676072,0.044476488374714546
+0.7690531714206919,8.248937519881775,8.313829338702561,11.848487439383073,2.2040415056549545,13.820093592987655,17.784051821088294,1.8375477103140518,8.854203191916952,2.0578642605725044,7.538208686985445,11.560968680808193,21.79460046098328,0.15178972964455376,4.485228162023185,17.686450856900116,2.947066304396758,5.9038671778429315,10.497856281111979,2.226513249242849,0.5205865955338087,11.598121075964807,6.345204952040568,-4.151364153719322,3.1468172950058158,4.284319265486959,15.797563190234776,13.687506668511068,10.970191219803835,4.374954239308276,12.07719183081749
+-0.237244386228543,7.375978345403522,6.873798867899084,16.56780084428282,15.708239484386352,0.37436175858039816,4.569323707553748,3.717440265516477,-3.332639296649237,14.810854855812003,8.663015632464948,11.411962173763484,23.76296733798555,6.091727485916293,-0.6128579633801117,12.913787653197492,14.776078924553342,1.8961087173783007,2.8419619996189116,-0.15591016136872243,14.785527324357998,17.078207611199545,5.248009934974321,13.091204041421996,7.753802044114474,5.150940616566217,-1.7914120949978871,0.8315486552557605,17.124137064310254,7.335337347774484,12.15588102663627
+-0.7591464330224046,6.045690062416719,15.205010061732954,3.521376633007579,4.340843234187501,5.407598609368447,20.522903560369077,-1.2446323466073448,-5.333836386623416,16.02955523478643,14.688001300055808,11.58590736912744,20.855021989355848,13.036904622112388,4.350969378242096,7.538853741847783,3.612194345304685,14.352501381485983,14.21023894552823,5.782358672249419,15.487485211173807,12.477191741992216,5.414888800612315,3.9334352571077753,12.846840267672773,12.626424979334878,2.6422173572536174,11.023756062919983,5.518614690110063,10.90230158131831,17.131457069138094
+-0.578930682733342,7.4720041258950785,1.2790101322907645,9.305062328937579,5.774469080456472,0.6612766331012274,15.66691175788088,-2.253596834751984,1.8618599620782081,1.5424932268093858,10.119472891920728,10.841152235418074,26.117700836527117,0.8210998720171715,15.876381308977278,7.507850163483177,11.062857108022968,10.313871452627126,4.628245091917189,13.894136785100066,18.20727348837267,8.486016525062805,5.3150042593742945,9.993702021429563,8.183624633527184,3.741409899871499,5.420551377856691,6.052194058179349,8.420644242714246,14.738036244160487,16.349005358316436
+-0.4024111478938608,6.303630475863501,7.738921478440039,13.941438267164179,1.8588505271998947,18.126133823056094,11.794259437748794,8.998274412592883,12.9929185198191,5.4492834706409745,16.663713253262763,11.820961416009753,28.01287339885735,7.773249741419965,17.971212642363845,17.795983939440134,7.323501339715191,13.902668825533093,4.970137834212488,7.632565540041821,15.082102786056934,19.43454065782235,5.9898318212352795,0.02548040254369284,1.6898350976201808,14.066424750956227,16.504382794312363,14.784062323210545,15.355483560013793,-5.809658379017466,13.999934250481498
+-0.553084316228075,7.10793574988639,-1.0994726470934983,15.987450481010313,12.146235417991475,13.96842166457774,2.960700443680164,11.048182164639773,12.02968712186096,-0.6979336678791759,9.94399676802519,11.307767141696468,23.34166801795113,1.5762235987058588,13.588796379621623,17.336256924172623,16.240582779795716,13.88408631914349,15.616557073663923,-1.6261728872949357,4.253828587642557,11.547732505691851,5.168906404358401,-0.4459689194222003,7.068442531311755,9.085580143010988,13.997449268024063,13.732573781154962,1.4928834740502186,2.918706818218751,1.8824027498879197
+-0.3059710293059447,6.883471901995674,-0.4191008911929028,11.270152289553856,0.9646143487879524,16.2072765951003,19.45388503964483,7.029973584734446,-1.9118194292978168,-2.5760699262798337,1.200881820697334,11.60451223985181,15.835461908793018,3.6818891643963756,4.2394472337395115,15.817770295256116,4.397483840267546,8.441182888487848,10.798169630406676,12.905337367542849,14.86496305457582,18.54731001911194,6.01942316715983,6.3464438501678675,15.779781474631134,11.867203129356996,-1.5809988204842131,15.937963436808776,9.329145924005392,1.3672428082444852,11.25212627434295
+0.08061427146175001,7.0686168291105265,4.314163949859171,5.126527286491202,18.98022697878006,2.478392533458136,2.0566454203461113,6.10092994105579,9.398148133537065,12.830549098998233,-0.7489148290069744,11.855747374557525,20.332277600256777,11.130456718255884,3.0659286592822035,18.820189216425398,13.645666385177247,2.4693135550449874,-0.8245808522715361,14.280448818314731,10.261790093697542,16.125357427169632,6.499160586100143,-1.1069294930122036,15.290425742213548,19.47235085306845,11.237488678606777,6.156278781965385,2.7239312503052986,15.969526655458072,19.367102171731098
+0.01622621544646831,8.295434218910781,7.483160698264256,16.836776052976052,16.02675559118073,3.2575460673473913,14.806077590849076,15.373698088212343,3.4539851644034067,15.754206623722231,14.533790948903588,10.421576941899199,24.486322241932942,1.471325540188305,1.3343802303133359,7.691580242919745,11.293920753769338,14.168609209016617,12.101049227145982,3.5452597233400267,13.289734697071973,3.366680044888735,4.655263814769995,6.845803210113595,-1.1309429886124631,11.40602620592237,-0.6038116512352962,13.282303818253448,7.480582359203627,1.5598258057148922,12.175293907765612
+-0.41668588528489053,7.670081971066899,-2.022774660740949,-0.7575969578660242,1.9675505444217087,17.25889373859362,4.133712372783155,14.123017153038028,-2.935758006012544,13.800131307902042,0.5601191204562381,10.733633525208443,25.535139303558125,2.371631730604788,3.5785569644274737,16.68613052838463,10.604658800497509,8.00293320516971,10.879670286336165,5.649507631944878,16.461366772168418,4.182337599633611,5.313067397184504,10.637984410000826,16.76688177588951,17.451770320383822,8.2287735066316,18.177497325443642,12.921086361974755,-1.8139383756092613,0.10597516235725916
+-0.0903020242109723,6.977041604795339,0.6404096903147759,9.779193858973331,3.1515788375338385,7.935675040916665,10.846333313084575,2.9484712487421136,7.1527066191459365,12.782477521243507,7.975365981797088,11.626965495280539,15.40345941299859,5.507437792041731,16.039284674851412,15.866067041986145,5.36302588195643,6.199448929635773,1.530683676176638,6.009701978435983,16.921300495316,16.21726236409439,6.427129041264496,9.270652965557527,8.554393884767187,5.204902285397056,15.997254403151656,6.016799790484397,12.400489378097568,6.165446189720479,7.574499931907939
+-0.42531533377116604,6.916978719053687,-2.8689002033233066,14.370263981906248,19.356530814858775,-0.9414402699614134,17.297983623057068,9.98040694893677,5.623591513146695,1.0601276285644756,2.2862514717789715,11.584093911566056,13.168378787085643,14.679273903948907,6.919538842459778,5.631231265670408,17.95780760187567,18.276830790116897,11.001496514530766,7.0059969959715955,10.799056773251873,17.962394092871186,5.7129689037599185,11.753322855893487,15.024854485413627,4.0036829999212245,3.579210538649358,17.29069066284572,5.881303599336233,6.567070312657858,7.7238326633981504
+-0.42349988769209673,6.968502935327613,3.0291628821905183,-0.8104463106381861,15.701723534216024,9.54300483480408,21.14834626607469,-3.0464084874052535,2.380159243027806,-1.9402525148761942,14.796770968488381,11.39148499646355,21.54019624820295,1.6253085920639059,3.7730239896931845,14.794718650497096,10.20491262335367,10.708380154689834,15.850134866175443,16.006828164019286,6.9086090766290535,4.016887229117371,6.391136706819847,-4.361662610932437,12.372500023041859,17.572969990664305,4.5321568466872435,13.56072008045467,13.70777214123307,13.791017350395652,4.9886698169316634
+0.4030770480500616,7.821810078531023,-1.7486097774666438,11.8600542921146,19.321216773961964,17.554519553824548,17.9835444050955,-0.17809471970752003,0.9232353746500923,0.10143480351077899,3.8886086611589796,11.623539704184962,14.144251389509574,17.22830813564463,13.825401476072802,18.053781423038394,2.492583449195161,6.257499016496469,-0.02613849139925243,0.20980839122955505,3.821121618553118,8.383178286379994,6.465510283145204,1.1696759777490264,10.192324686169938,2.534336565772959,7.353535798383845,1.756174602079291,4.29703926149382,5.475936908969395,14.207300208523842
+0.2931542905468688,7.114729971501666,2.8672671081649757,18.215604550661766,19.44317018723892,18.603062587196632,3.28684901317356,6.556090416052916,14.126606558366483,12.504641383933288,10.572021392198122,11.898063223036463,23.17230595087575,13.928766164825461,5.85688379672548,15.153757867444693,14.883468294619991,10.76249766951763,9.44109880493657,0.5240711773856503,7.138984613789896,11.085988771039727,6.680454553744379,0.9943512560631742,11.024623946146448,5.774336706725997,2.140553160483255,1.513012905897682,9.234731822748765,0.8589205384345293,14.855557776863494
+-1.068293275502069,6.688431139135614,4.394859862258552,3.264441020124309,10.112924430459204,2.401832720979302,19.996232552633266,-2.4342087821777945,-0.002138651374970752,5.375342791407982,9.099910516129622,10.80228340017105,22.003948091786636,16.63923096895831,12.041527329160441,2.3884665476409204,6.818900036480699,12.017177507087172,-1.4436547242408784,13.64705410418305,13.04355734711472,12.886475198893509,5.33008029223365,1.191318959825609,3.1850489486603326,13.215888532878894,13.313807064916059,4.059530051339422,1.5339585261184663,9.259999609604241,7.847281215457528
+-0.42541003220054086,7.782423541777732,4.813785215889612,10.355336100344111,4.102404520958894,2.151741371673287,9.544142193911055,-5.553507754283357,4.709748615136537,5.160983908916758,0.7958476991880515,10.53625329586316,21.33605684398865,11.516030574008827,3.136755772098697,-0.19601282474544854,6.7932740277467065,4.786895176101435,-0.8852087587845503,10.82818083067376,0.5163437321566153,2.401249072954913,4.448866422069554,-0.9519542890558554,15.930534034678901,-0.30945732175092455,-0.1652760640214934,0.9562414598436888,5.9680813064140565,0.7031493891498997,14.11647367983301
+-0.6443918037549983,6.33772999678485,15.500045692057217,13.952905635471323,10.335069132173146,8.687859968570022,12.616425335430888,9.212657235242867,12.707543147446456,16.067662592115077,11.754656157784591,11.514073138250845,27.467361975369066,10.92652693579917,14.242420691312008,14.791332519128817,6.716531720841635,4.414172141666262,-2.116281656177871,15.152177171364471,18.862485225420563,3.2249920162584313,5.869361259355915,6.600021071042125,9.496413376713074,19.533263197561958,12.737424678825281,7.925206395466148,18.54839810711364,4.24431887519781,19.457245841224566
+0.30863442114050993,7.427487459487148,15.954024120036767,10.627037128180742,1.4059673390123741,14.231361408228786,6.1599775264261645,7.342537219350252,0.6414176307009809,13.406607773594747,15.56185387287033,11.516585233748293,16.3449574844747,6.657722971968752,19.31344303572324,4.274739735743955,8.914965467776453,6.208289556559654,4.31510842609954,12.046072790510921,3.2517518159761813,11.003546945430559,7.234175910796937,12.761808760237042,17.5987510332023,14.91881873186424,1.6142981315393525,3.989487681295069,19.095718996845676,2.352855593333233,4.15989627836289
+-0.32437729273814614,7.681908959769901,9.09688967307273,10.671708476280013,16.47153068657346,7.787147563930107,15.98846688983047,10.934699367575343,-6.214142502887111,10.005049110085078,15.514080038315443,11.151650074797919,8.53110938593515,15.89322547516351,11.647690785809154,16.04756572532715,8.323753689039536,12.387416259845837,12.169387872032647,-2.841081026788194,6.736126146881908,6.656531167482379,5.395456170007543,-3.831165624222739,0.7310685424256036,10.764998404312223,14.016247207191768,13.031496508839323,14.525103919099548,-3.4979138757695196,15.506400603458836
+0.004882969327554491,6.880051491983344,-2.0125461447264703,9.289985472279,18.44641808747798,0.81756746318878,11.75504928429594,8.79936132919623,1.022537571139809,9.676443896831447,10.991274754582491,11.904526959217524,20.13070550842738,16.102092242450986,11.095898490817493,14.535186516468176,1.6695752962565784,2.1928573875874164,8.96037143059307,15.558787742665604,14.457602185689368,14.440699298522967,5.977360243809625,8.630087664686432,0.34494760067632585,9.37033865277216,4.424397544077917,-1.1890300683725634,14.270160155900994,4.076739321620405,3.563819372488055
+1.854064758963438,7.359780514655561,11.92005595071335,12.233987883933215,0.8504078459087409,4.3140446249381625,2.8553525527354697,1.9240308422883183,2.587149770626911,0.6331020837151344,11.543369973422127,12.85653160898834,20.560130109369528,14.030905884707664,5.1179189034738855,14.629036741366546,10.00312023903248,14.882993609952178,7.868520034839083,-0.49097552572981135,15.750573631731438,12.036903018467882,7.072764343348746,8.323702760244581,10.816399946309327,4.606337237539002,15.184641399745612,5.034566265416064,2.4454910010733624,10.787750996506027,15.993843495600942
+-0.31577708639583185,7.522321876175821,0.1559709497448535,0.8483521127695699,-0.08400471363184721,5.961284320909762,10.014705787395911,12.539017761068724,12.319199269872556,6.092392935106715,-1.8850670025182081,11.237412297120901,12.898557558276977,0.8862996435769528,1.0075037895606158,7.202022784975998,10.879773360881632,4.982503684077786,12.260894479426657,7.963755019265221,11.047295225112064,13.54453731612153,5.562395884743102,7.371689285283488,11.537486529178636,17.24424020184242,-0.8211063650981014,12.1765453485614,8.036216733198652,9.608935724539378,8.30445952738376
+-0.751280327600173,6.863218011903719,-1.2158229614203586,18.50978672087966,5.998184067880217,17.82309211994999,9.109798039505359,11.407817030891422,12.274442898550102,2.452612473511423,17.06988313236063,11.010782591410589,11.56961121066671,16.48523241772797,6.689604114499446,-0.592033382800789,8.422447946282325,14.771603616527257,-0.8962212815209759,15.833882005467284,9.707152280944948,15.582792854912729,4.602757599780826,4.747322294214447,8.289627755639833,14.293877104273715,8.169385791637684,6.682875960503008,13.213330745260906,2.5290687883771428,0.5607554425171095
+-0.2245134738012466,7.105761065799777,-3.0916507986476773,14.20503920712776,11.217162920193253,5.338414287872144,6.705794547513063,2.519845222425354,12.666534334211144,9.267746035336845,9.971671100343375,11.615281567001356,15.067465820436961,5.777237271184271,9.620719116127788,12.698570461888142,0.5948441030822771,14.1338274066603,8.90447548282482,-0.33132386109984063,5.011047694817249,3.4101847779139494,5.790425380951137,5.942254144080581,8.319715273768205,12.324559847863544,7.280700664337567,7.5763286883403715,1.5137137864862567,-4.278300153207962,1.2826891285398627
+-0.7344377709331181,6.518965097980281,-0.38546276136833946,18.440984473367912,9.996785010644421,15.83729804327308,5.689905879194551,-3.484147704440735,-6.453877437143689,8.785999559038878,1.698716166600784,11.321416673910365,16.435398444346035,2.317713755538236,8.218911201083593,6.452760392467143,15.092689174880446,19.656522233303036,7.993520974312563,10.025217664435061,13.864827269825954,19.905200948419342,5.30713313945265,14.256376354414433,13.100586363563647,2.774150816955414,8.1918727350577,18.01668925838051,5.5709998439827135,-3.339825058371698,8.117553119965887
+-0.7940260630531353,7.014256009254609,10.04729147593637,3.517262509751255,15.20667752186182,4.584362983725727,5.76840001378517,10.731366762234806,-0.5870154050918988,-2.8621167689814433,2.6992064725937404,10.937420795916431,14.57939850481344,19.69598891563686,11.406079138924213,18.45594059874933,19.441103613981305,15.127564417626754,5.819041804700898,16.671570554303745,17.222408417007607,11.875875854695543,5.149706889521877,-0.1265857730481787,6.601282927268093,3.9407215274436833,6.53013682757545,14.176480054027193,17.174220738839054,9.857607436147942,16.554166967315
+-0.54320045112721,7.046675219415725,7.454119693229676,5.714902217567685,19.6193369145606,15.239657114409919,9.67051075265578,10.989121282058603,13.706247459652246,15.994599528201872,1.580295116234831,11.387306824726284,15.499932377948564,4.20863712441848,5.9424806612082754,12.50939413884742,12.623412885160162,6.410531197256885,3.0763712897230437,8.347829127448744,3.0069476608170014,16.855038932265128,4.944656998028655,0.8414640304472626,-0.1719727408482897,4.598979389736707,9.214023045768641,12.97822149962273,8.176926953533153,0.1976319502478434,10.586472372830976
+-0.18758784997207975,7.437003737160336,-2.1485897891108623,15.475520909810195,3.214566967447965,15.751100005805323,6.971039551929863,0.8952169915480876,6.747659901174144,16.776839252990627,0.5263528471347741,11.446616482511656,24.699217564686478,15.20201476897991,16.537074161766995,18.892429009640274,5.048319594454917,3.1933396956836404,0.2034341250924284,1.800039757605857,19.073685085298244,19.288921296665755,5.238062619638234,-0.7987342914676177,2.178222638827668,19.18081248576666,16.040544541625728,-1.228484752894996,6.441410646805025,-6.041583496441335,11.841835219801238
+0.23439996263529977,7.266504655288271,4.939019965336528,4.046466760543131,11.985221660743735,12.479846779736759,10.2543823213002,14.234072669365634,-0.0925389103932952,5.698067253580263,5.278810981530597,11.883909236581,20.514820818843493,-0.5867456227934458,0.21826318573748618,11.532310262928357,5.67015757797202,19.52812088948095,6.630343614826277,10.47157329465314,2.673230721804453,4.995420300941898,6.275967516408384,-1.0277402022040114,12.792003411220552,11.85858859596667,15.433295904203428,15.761372232667998,19.991080511969432,5.3573921837077405,14.529226218175586
+0.12113323692719355,6.796013449156901,9.662426282016753,15.106991778307776,3.2880551753831906,15.201063982759132,18.27016273056691,7.207132936199871,3.3589043306640685,3.4996493841487,11.1507577531887,12.072549274324288,9.889956267962372,16.265632014444847,13.262777724183806,10.422078482894076,6.096010023415989,14.582580624320402,17.2355559796185,2.899150622202362,8.669877625169578,17.336873835983635,6.488003858839667,-4.404464136703567,4.440923242739789,12.241880712659238,1.4450987575025822,14.969089823165463,14.898652161046513,14.992566286906122,2.143351391248771
+-0.2519457509587627,6.744609092861937,14.26502867850176,1.2143782896451913,3.356672567816368,12.356659671888487,14.798376397533268,2.204826036893997,11.171645602494582,-1.7310863479188485,11.499416738044566,11.580328088994996,21.641546463153947,1.7122909566792277,0.36049102455669585,7.47478398380923,1.5332767390202147,15.390862162911112,4.155886041306992,3.2028706370700046,12.156570521735095,17.849094187148605,6.365771339044445,1.2613727691471421,-0.4449279694041551,0.3545741299685811,14.263148369973976,17.81650151655361,3.1618862152216884,0.061637326172674034,15.549921003780979
+0.01946225975773412,7.5293969577025175,4.9564795959316275,1.737337687048881,12.943885413431891,10.615044526364017,18.95838598347561,0.9328406757074319,3.4931657180060514,5.3699917407578415,-0.767428593547029,11.516943127622927,12.856343729803957,7.158069938870364,8.373171984759711,13.875709815800219,12.167709966747646,12.806677896012127,14.767360954978844,3.8997798718950607,11.512749711737127,18.274925830495963,5.5781451547864185,16.23532751190548,15.57267440873616,11.346454729927505,12.157772793987858,4.365636654684462,18.502966850221313,11.538684490527746,7.792997532257997
+-1.194958554274966,6.887000327309883,-0.7069508696146194,6.385335828787747,13.718701486418922,2.1417125857480173,10.558709420131596,7.36317922417973,-2.066037574529336,1.3636863570976114,4.24258981984153,10.494651885407194,24.189468082753468,1.2998190471382909,5.243488993917133,12.36845805767685,19.239323775289755,15.963436546330907,13.65362643235952,14.8407045290566,2.1139126774768418,6.18321749487424,4.742700741322475,-3.691651217885312,13.291079267222976,5.901002195479464,0.4355949473189646,10.51438711908699,9.11175614971179,-2.835385854215115,16.37821713672139
+1.0777390793548756,7.839857835558427,8.857225533233215,-0.7513464933836164,10.42881100412093,14.1071835363317,12.634875376670138,-4.0154581588424465,13.323359944309837,8.802283470642658,18.17273752479866,12.102682478642011,14.59292002690874,16.12801669500845,16.04578785447222,1.2586292132938954,8.114250157936043,9.998486831098596,14.611531549950705,2.3903187863092272,11.552892196820094,12.351899024086988,6.418855487594698,4.540445637928105,1.577521661822212,10.695487640510992,-3.3161289150871465,12.649255489762627,6.63994791733105,3.6455607787658684,11.063992150773691
--
GitLab