Walkers_fallers2_DS2.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "4069640d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Data Handling\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "pd.set_option(\"display.max_columns\", None)\n",
    "\n",
    "# Data visualization\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use(\"ggplot\")\n",
    "\n",
    "# Preprocessing\n",
    "from sklearn.model_selection import train_test_split as tts\n",
    "\n",
    "# Models\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.ensemble import ExtraTreesClassifier\n",
    "\n",
    "# Metrics\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.metrics import classification_report\n",
    "\n",
    "# Time\n",
    "import time\n",
    "\n",
    "# Warnings\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "a5e29ff5",
   "metadata": {},
   "outputs": [],
   "source": [
    "df2=pd.read_csv(\"D:/Amrita_University/S5/Machine Learning/Project/dataset2_ML.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "70f4afaa",
   "metadata": {},
   "outputs": [
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       "      <th>acc_z_88</th>\n",
       "      <th>acc_z_89</th>\n",
       "      <th>acc_z_90</th>\n",
       "      <th>acc_z_91</th>\n",
       "      <th>acc_z_92</th>\n",
       "      <th>acc_z_93</th>\n",
       "      <th>acc_z_94</th>\n",
       "      <th>acc_z_95</th>\n",
       "      <th>acc_z_96</th>\n",
       "      <th>acc_z_97</th>\n",
       "      <th>acc_z_98</th>\n",
       "      <th>acc_z_99</th>\n",
       "      <th>acc_z_100</th>\n",
       "      <th>acc_z_101</th>\n",
       "      <th>acc_z_102</th>\n",
       "      <th>acc_z_103</th>\n",
       "      <th>acc_z_104</th>\n",
       "      <th>acc_z_105</th>\n",
       "      <th>acc_z_106</th>\n",
       "      <th>acc_z_107</th>\n",
       "      <th>acc_z_108</th>\n",
       "      <th>acc_z_109</th>\n",
       "      <th>acc_z_110</th>\n",
       "      <th>acc_z_111</th>\n",
       "      <th>acc_z_112</th>\n",
       "      <th>acc_z_113</th>\n",
       "      <th>acc_z_114</th>\n",
       "      <th>acc_z_115</th>\n",
       "      <th>acc_z_116</th>\n",
       "      <th>acc_z_117</th>\n",
       "      <th>acc_z_118</th>\n",
       "      <th>acc_z_119</th>\n",
       "      <th>acc_z_120</th>\n",
       "      <th>acc_z_121</th>\n",
       "      <th>acc_z_122</th>\n",
       "      <th>acc_z_123</th>\n",
       "      <th>acc_z_124</th>\n",
       "      <th>acc_z_125</th>\n",
       "      <th>acc_z_126</th>\n",
       "      <th>acc_z_127</th>\n",
       "      <th>acc_z_128</th>\n",
       "      <th>acc_z_129</th>\n",
       "      <th>acc_z_130</th>\n",
       "      <th>acc_z_131</th>\n",
       "      <th>acc_z_132</th>\n",
       "      <th>acc_z_133</th>\n",
       "      <th>acc_z_134</th>\n",
       "      <th>acc_z_135</th>\n",
       "      <th>acc_z_136</th>\n",
       "      <th>acc_z_137</th>\n",
       "      <th>acc_z_138</th>\n",
       "      <th>acc_z_139</th>\n",
       "      <th>acc_z_140</th>\n",
       "      <th>acc_z_141</th>\n",
       "      <th>acc_z_142</th>\n",
       "      <th>acc_z_143</th>\n",
       "      <th>acc_z_144</th>\n",
       "      <th>acc_z_145</th>\n",
       "      <th>acc_z_146</th>\n",
       "      <th>acc_z_147</th>\n",
       "      <th>acc_z_148</th>\n",
       "      <th>acc_z_149</th>\n",
       "      <th>acc_z_150</th>\n",
       "      <th>acc_z_151</th>\n",
       "      <th>acc_z_152</th>\n",
       "      <th>acc_z_153</th>\n",
       "      <th>acc_z_154</th>\n",
       "      <th>acc_z_155</th>\n",
       "      <th>acc_z_156</th>\n",
       "      <th>acc_z_157</th>\n",
       "      <th>acc_z_158</th>\n",
       "      <th>acc_z_159</th>\n",
       "      <th>gy_x_0</th>\n",
       "      <th>gy_x_1</th>\n",
       "      <th>gy_x_2</th>\n",
       "      <th>gy_x_3</th>\n",
       "      <th>gy_x_4</th>\n",
       "      <th>gy_x_5</th>\n",
       "      <th>gy_x_6</th>\n",
       "      <th>gy_x_7</th>\n",
       "      <th>gy_x_8</th>\n",
       "      <th>gy_x_9</th>\n",
       "      <th>gy_x_10</th>\n",
       "      <th>gy_x_11</th>\n",
       "      <th>gy_x_12</th>\n",
       "      <th>gy_x_13</th>\n",
       "      <th>gy_x_14</th>\n",
       "      <th>gy_x_15</th>\n",
       "      <th>gy_x_16</th>\n",
       "      <th>gy_x_17</th>\n",
       "      <th>gy_x_18</th>\n",
       "      <th>gy_x_19</th>\n",
       "      <th>gy_x_20</th>\n",
       "      <th>gy_x_21</th>\n",
       "      <th>gy_x_22</th>\n",
       "      <th>gy_x_23</th>\n",
       "      <th>gy_x_24</th>\n",
       "      <th>gy_x_25</th>\n",
       "      <th>gy_x_26</th>\n",
       "      <th>gy_x_27</th>\n",
       "      <th>gy_x_28</th>\n",
       "      <th>gy_x_29</th>\n",
       "      <th>gy_x_30</th>\n",
       "      <th>gy_x_31</th>\n",
       "      <th>gy_x_32</th>\n",
       "      <th>gy_x_33</th>\n",
       "      <th>gy_x_34</th>\n",
       "      <th>gy_x_35</th>\n",
       "      <th>gy_x_36</th>\n",
       "      <th>gy_x_37</th>\n",
       "      <th>gy_x_38</th>\n",
       "      <th>gy_x_39</th>\n",
       "      <th>gy_x_40</th>\n",
       "      <th>gy_x_41</th>\n",
       "      <th>gy_x_42</th>\n",
       "      <th>gy_x_43</th>\n",
       "      <th>gy_x_44</th>\n",
       "      <th>gy_x_45</th>\n",
       "      <th>gy_x_46</th>\n",
       "      <th>gy_x_47</th>\n",
       "      <th>gy_x_48</th>\n",
       "      <th>gy_x_49</th>\n",
       "      <th>gy_x_50</th>\n",
       "      <th>gy_x_51</th>\n",
       "      <th>gy_x_52</th>\n",
       "      <th>gy_x_53</th>\n",
       "      <th>gy_x_54</th>\n",
       "      <th>gy_x_55</th>\n",
       "      <th>gy_x_56</th>\n",
       "      <th>gy_x_57</th>\n",
       "      <th>gy_x_58</th>\n",
       "      <th>gy_x_59</th>\n",
       "      <th>gy_x_60</th>\n",
       "      <th>gy_x_61</th>\n",
       "      <th>gy_x_62</th>\n",
       "      <th>gy_x_63</th>\n",
       "      <th>gy_x_64</th>\n",
       "      <th>gy_x_65</th>\n",
       "      <th>gy_x_66</th>\n",
       "      <th>gy_x_67</th>\n",
       "      <th>gy_x_68</th>\n",
       "      <th>gy_x_69</th>\n",
       "      <th>gy_x_70</th>\n",
       "      <th>gy_x_71</th>\n",
       "      <th>gy_x_72</th>\n",
       "      <th>gy_x_73</th>\n",
       "      <th>gy_x_74</th>\n",
       "      <th>gy_x_75</th>\n",
       "      <th>gy_x_76</th>\n",
       "      <th>gy_x_77</th>\n",
       "      <th>gy_x_78</th>\n",
       "      <th>gy_x_79</th>\n",
       "      <th>gy_x_80</th>\n",
       "      <th>gy_x_81</th>\n",
       "      <th>gy_x_82</th>\n",
       "      <th>gy_x_83</th>\n",
       "      <th>gy_x_84</th>\n",
       "      <th>gy_x_85</th>\n",
       "      <th>gy_x_86</th>\n",
       "      <th>gy_x_87</th>\n",
       "      <th>gy_x_88</th>\n",
       "      <th>gy_x_89</th>\n",
       "      <th>gy_x_90</th>\n",
       "      <th>gy_x_91</th>\n",
       "      <th>gy_x_92</th>\n",
       "      <th>gy_x_93</th>\n",
       "      <th>gy_x_94</th>\n",
       "      <th>gy_x_95</th>\n",
       "      <th>gy_x_96</th>\n",
       "      <th>gy_x_97</th>\n",
       "      <th>gy_x_98</th>\n",
       "      <th>gy_x_99</th>\n",
       "      <th>gy_x_100</th>\n",
       "      <th>gy_x_101</th>\n",
       "      <th>gy_x_102</th>\n",
       "      <th>gy_x_103</th>\n",
       "      <th>gy_x_104</th>\n",
       "      <th>gy_x_105</th>\n",
       "      <th>gy_x_106</th>\n",
       "      <th>gy_x_107</th>\n",
       "      <th>gy_x_108</th>\n",
       "      <th>gy_x_109</th>\n",
       "      <th>gy_x_110</th>\n",
       "      <th>gy_x_111</th>\n",
       "      <th>gy_x_112</th>\n",
       "      <th>gy_x_113</th>\n",
       "      <th>gy_x_114</th>\n",
       "      <th>gy_x_115</th>\n",
       "      <th>gy_x_116</th>\n",
       "      <th>gy_x_117</th>\n",
       "      <th>gy_x_118</th>\n",
       "      <th>gy_x_119</th>\n",
       "      <th>gy_x_120</th>\n",
       "      <th>gy_x_121</th>\n",
       "      <th>gy_x_122</th>\n",
       "      <th>gy_x_123</th>\n",
       "      <th>gy_x_124</th>\n",
       "      <th>gy_x_125</th>\n",
       "      <th>gy_x_126</th>\n",
       "      <th>gy_x_127</th>\n",
       "      <th>gy_x_128</th>\n",
       "      <th>gy_x_129</th>\n",
       "      <th>gy_x_130</th>\n",
       "      <th>gy_x_131</th>\n",
       "      <th>gy_x_132</th>\n",
       "      <th>gy_x_133</th>\n",
       "      <th>gy_x_134</th>\n",
       "      <th>gy_x_135</th>\n",
       "      <th>gy_x_136</th>\n",
       "      <th>gy_x_137</th>\n",
       "      <th>gy_x_138</th>\n",
       "      <th>gy_x_139</th>\n",
       "      <th>gy_x_140</th>\n",
       "      <th>gy_x_141</th>\n",
       "      <th>gy_x_142</th>\n",
       "      <th>gy_x_143</th>\n",
       "      <th>gy_x_144</th>\n",
       "      <th>gy_x_145</th>\n",
       "      <th>gy_x_146</th>\n",
       "      <th>gy_x_147</th>\n",
       "      <th>gy_x_148</th>\n",
       "      <th>gy_x_149</th>\n",
       "      <th>gy_x_150</th>\n",
       "      <th>gy_x_151</th>\n",
       "      <th>gy_x_152</th>\n",
       "      <th>gy_x_153</th>\n",
       "      <th>gy_x_154</th>\n",
       "      <th>gy_x_155</th>\n",
       "      <th>gy_x_156</th>\n",
       "      <th>gy_x_157</th>\n",
       "      <th>gy_x_158</th>\n",
       "      <th>gy_x_159</th>\n",
       "      <th>gy_y_0</th>\n",
       "      <th>gy_y_1</th>\n",
       "      <th>gy_y_2</th>\n",
       "      <th>gy_y_3</th>\n",
       "      <th>gy_y_4</th>\n",
       "      <th>gy_y_5</th>\n",
       "      <th>gy_y_6</th>\n",
       "      <th>gy_y_7</th>\n",
       "      <th>gy_y_8</th>\n",
       "      <th>gy_y_9</th>\n",
       "      <th>gy_y_10</th>\n",
       "      <th>gy_y_11</th>\n",
       "      <th>gy_y_12</th>\n",
       "      <th>gy_y_13</th>\n",
       "      <th>gy_y_14</th>\n",
       "      <th>gy_y_15</th>\n",
       "      <th>gy_y_16</th>\n",
       "      <th>gy_y_17</th>\n",
       "      <th>gy_y_18</th>\n",
       "      <th>gy_y_19</th>\n",
       "      <th>gy_y_20</th>\n",
       "      <th>gy_y_21</th>\n",
       "      <th>gy_y_22</th>\n",
       "      <th>gy_y_23</th>\n",
       "      <th>gy_y_24</th>\n",
       "      <th>gy_y_25</th>\n",
       "      <th>gy_y_26</th>\n",
       "      <th>gy_y_27</th>\n",
       "      <th>gy_y_28</th>\n",
       "      <th>gy_y_29</th>\n",
       "      <th>gy_y_30</th>\n",
       "      <th>gy_y_31</th>\n",
       "      <th>gy_y_32</th>\n",
       "      <th>gy_y_33</th>\n",
       "      <th>gy_y_34</th>\n",
       "      <th>gy_y_35</th>\n",
       "      <th>gy_y_36</th>\n",
       "      <th>gy_y_37</th>\n",
       "      <th>gy_y_38</th>\n",
       "      <th>gy_y_39</th>\n",
       "      <th>gy_y_40</th>\n",
       "      <th>gy_y_41</th>\n",
       "      <th>gy_y_42</th>\n",
       "      <th>gy_y_43</th>\n",
       "      <th>gy_y_44</th>\n",
       "      <th>gy_y_45</th>\n",
       "      <th>gy_y_46</th>\n",
       "      <th>gy_y_47</th>\n",
       "      <th>gy_y_48</th>\n",
       "      <th>gy_y_49</th>\n",
       "      <th>gy_y_50</th>\n",
       "      <th>gy_y_51</th>\n",
       "      <th>gy_y_52</th>\n",
       "      <th>gy_y_53</th>\n",
       "      <th>gy_y_54</th>\n",
       "      <th>gy_y_55</th>\n",
       "      <th>gy_y_56</th>\n",
       "      <th>gy_y_57</th>\n",
       "      <th>gy_y_58</th>\n",
       "      <th>gy_y_59</th>\n",
       "      <th>gy_y_60</th>\n",
       "      <th>gy_y_61</th>\n",
       "      <th>gy_y_62</th>\n",
       "      <th>gy_y_63</th>\n",
       "      <th>gy_y_64</th>\n",
       "      <th>gy_y_65</th>\n",
       "      <th>gy_y_66</th>\n",
       "      <th>gy_y_67</th>\n",
       "      <th>gy_y_68</th>\n",
       "      <th>gy_y_69</th>\n",
       "      <th>gy_y_70</th>\n",
       "      <th>gy_y_71</th>\n",
       "      <th>gy_y_72</th>\n",
       "      <th>gy_y_73</th>\n",
       "      <th>gy_y_74</th>\n",
       "      <th>gy_y_75</th>\n",
       "      <th>gy_y_76</th>\n",
       "      <th>gy_y_77</th>\n",
       "      <th>gy_y_78</th>\n",
       "      <th>gy_y_79</th>\n",
       "      <th>gy_y_80</th>\n",
       "      <th>gy_y_81</th>\n",
       "      <th>gy_y_82</th>\n",
       "      <th>gy_y_83</th>\n",
       "      <th>gy_y_84</th>\n",
       "      <th>gy_y_85</th>\n",
       "      <th>gy_y_86</th>\n",
       "      <th>gy_y_87</th>\n",
       "      <th>gy_y_88</th>\n",
       "      <th>gy_y_89</th>\n",
       "      <th>gy_y_90</th>\n",
       "      <th>gy_y_91</th>\n",
       "      <th>gy_y_92</th>\n",
       "      <th>gy_y_93</th>\n",
       "      <th>gy_y_94</th>\n",
       "      <th>gy_y_95</th>\n",
       "      <th>gy_y_96</th>\n",
       "      <th>gy_y_97</th>\n",
       "      <th>gy_y_98</th>\n",
       "      <th>gy_y_99</th>\n",
       "      <th>gy_y_100</th>\n",
       "      <th>gy_y_101</th>\n",
       "      <th>gy_y_102</th>\n",
       "      <th>gy_y_103</th>\n",
       "      <th>gy_y_104</th>\n",
       "      <th>gy_y_105</th>\n",
       "      <th>gy_y_106</th>\n",
       "      <th>gy_y_107</th>\n",
       "      <th>gy_y_108</th>\n",
       "      <th>gy_y_109</th>\n",
       "      <th>gy_y_110</th>\n",
       "      <th>gy_y_111</th>\n",
       "      <th>gy_y_112</th>\n",
       "      <th>gy_y_113</th>\n",
       "      <th>gy_y_114</th>\n",
       "      <th>gy_y_115</th>\n",
       "      <th>gy_y_116</th>\n",
       "      <th>gy_y_117</th>\n",
       "      <th>gy_y_118</th>\n",
       "      <th>gy_y_119</th>\n",
       "      <th>gy_y_120</th>\n",
       "      <th>gy_y_121</th>\n",
       "      <th>gy_y_122</th>\n",
       "      <th>gy_y_123</th>\n",
       "      <th>gy_y_124</th>\n",
       "      <th>gy_y_125</th>\n",
       "      <th>gy_y_126</th>\n",
       "      <th>gy_y_127</th>\n",
       "      <th>gy_y_128</th>\n",
       "      <th>gy_y_129</th>\n",
       "      <th>gy_y_130</th>\n",
       "      <th>gy_y_131</th>\n",
       "      <th>gy_y_132</th>\n",
       "      <th>gy_y_133</th>\n",
       "      <th>gy_y_134</th>\n",
       "      <th>gy_y_135</th>\n",
       "      <th>gy_y_136</th>\n",
       "      <th>gy_y_137</th>\n",
       "      <th>gy_y_138</th>\n",
       "      <th>gy_y_139</th>\n",
       "      <th>gy_y_140</th>\n",
       "      <th>gy_y_141</th>\n",
       "      <th>gy_y_142</th>\n",
       "      <th>gy_y_143</th>\n",
       "      <th>gy_y_144</th>\n",
       "      <th>gy_y_145</th>\n",
       "      <th>gy_y_146</th>\n",
       "      <th>gy_y_147</th>\n",
       "      <th>gy_y_148</th>\n",
       "      <th>gy_y_149</th>\n",
       "      <th>gy_y_150</th>\n",
       "      <th>gy_y_151</th>\n",
       "      <th>gy_y_152</th>\n",
       "      <th>gy_y_153</th>\n",
       "      <th>gy_y_154</th>\n",
       "      <th>gy_y_155</th>\n",
       "      <th>gy_y_156</th>\n",
       "      <th>gy_y_157</th>\n",
       "      <th>gy_y_158</th>\n",
       "      <th>gy_y_159</th>\n",
       "      <th>gy_z_0</th>\n",
       "      <th>gy_z_1</th>\n",
       "      <th>gy_z_2</th>\n",
       "      <th>gy_z_3</th>\n",
       "      <th>gy_z_4</th>\n",
       "      <th>gy_z_5</th>\n",
       "      <th>gy_z_6</th>\n",
       "      <th>gy_z_7</th>\n",
       "      <th>gy_z_8</th>\n",
       "      <th>gy_z_9</th>\n",
       "      <th>gy_z_10</th>\n",
       "      <th>gy_z_11</th>\n",
       "      <th>gy_z_12</th>\n",
       "      <th>gy_z_13</th>\n",
       "      <th>gy_z_14</th>\n",
       "      <th>gy_z_15</th>\n",
       "      <th>gy_z_16</th>\n",
       "      <th>gy_z_17</th>\n",
       "      <th>gy_z_18</th>\n",
       "      <th>gy_z_19</th>\n",
       "      <th>gy_z_20</th>\n",
       "      <th>gy_z_21</th>\n",
       "      <th>gy_z_22</th>\n",
       "      <th>gy_z_23</th>\n",
       "      <th>gy_z_24</th>\n",
       "      <th>gy_z_25</th>\n",
       "      <th>gy_z_26</th>\n",
       "      <th>gy_z_27</th>\n",
       "      <th>gy_z_28</th>\n",
       "      <th>gy_z_29</th>\n",
       "      <th>gy_z_30</th>\n",
       "      <th>gy_z_31</th>\n",
       "      <th>gy_z_32</th>\n",
       "      <th>gy_z_33</th>\n",
       "      <th>gy_z_34</th>\n",
       "      <th>gy_z_35</th>\n",
       "      <th>gy_z_36</th>\n",
       "      <th>gy_z_37</th>\n",
       "      <th>gy_z_38</th>\n",
       "      <th>gy_z_39</th>\n",
       "      <th>gy_z_40</th>\n",
       "      <th>gy_z_41</th>\n",
       "      <th>gy_z_42</th>\n",
       "      <th>gy_z_43</th>\n",
       "      <th>gy_z_44</th>\n",
       "      <th>gy_z_45</th>\n",
       "      <th>gy_z_46</th>\n",
       "      <th>gy_z_47</th>\n",
       "      <th>gy_z_48</th>\n",
       "      <th>gy_z_49</th>\n",
       "      <th>gy_z_50</th>\n",
       "      <th>gy_z_51</th>\n",
       "      <th>gy_z_52</th>\n",
       "      <th>gy_z_53</th>\n",
       "      <th>gy_z_54</th>\n",
       "      <th>gy_z_55</th>\n",
       "      <th>gy_z_56</th>\n",
       "      <th>gy_z_57</th>\n",
       "      <th>gy_z_58</th>\n",
       "      <th>gy_z_59</th>\n",
       "      <th>gy_z_60</th>\n",
       "      <th>gy_z_61</th>\n",
       "      <th>gy_z_62</th>\n",
       "      <th>gy_z_63</th>\n",
       "      <th>gy_z_64</th>\n",
       "      <th>gy_z_65</th>\n",
       "      <th>gy_z_66</th>\n",
       "      <th>gy_z_67</th>\n",
       "      <th>gy_z_68</th>\n",
       "      <th>gy_z_69</th>\n",
       "      <th>gy_z_70</th>\n",
       "      <th>gy_z_71</th>\n",
       "      <th>gy_z_72</th>\n",
       "      <th>gy_z_73</th>\n",
       "      <th>gy_z_74</th>\n",
       "      <th>gy_z_75</th>\n",
       "      <th>gy_z_76</th>\n",
       "      <th>gy_z_77</th>\n",
       "      <th>gy_z_78</th>\n",
       "      <th>gy_z_79</th>\n",
       "      <th>gy_z_80</th>\n",
       "      <th>gy_z_81</th>\n",
       "      <th>gy_z_82</th>\n",
       "      <th>gy_z_83</th>\n",
       "      <th>gy_z_84</th>\n",
       "      <th>gy_z_85</th>\n",
       "      <th>gy_z_86</th>\n",
       "      <th>gy_z_87</th>\n",
       "      <th>gy_z_88</th>\n",
       "      <th>gy_z_89</th>\n",
       "      <th>gy_z_90</th>\n",
       "      <th>gy_z_91</th>\n",
       "      <th>gy_z_92</th>\n",
       "      <th>gy_z_93</th>\n",
       "      <th>gy_z_94</th>\n",
       "      <th>gy_z_95</th>\n",
       "      <th>gy_z_96</th>\n",
       "      <th>gy_z_97</th>\n",
       "      <th>gy_z_98</th>\n",
       "      <th>gy_z_99</th>\n",
       "      <th>gy_z_100</th>\n",
       "      <th>gy_z_101</th>\n",
       "      <th>gy_z_102</th>\n",
       "      <th>gy_z_103</th>\n",
       "      <th>gy_z_104</th>\n",
       "      <th>gy_z_105</th>\n",
       "      <th>gy_z_106</th>\n",
       "      <th>gy_z_107</th>\n",
       "      <th>gy_z_108</th>\n",
       "      <th>gy_z_109</th>\n",
       "      <th>gy_z_110</th>\n",
       "      <th>gy_z_111</th>\n",
       "      <th>gy_z_112</th>\n",
       "      <th>gy_z_113</th>\n",
       "      <th>gy_z_114</th>\n",
       "      <th>gy_z_115</th>\n",
       "      <th>gy_z_116</th>\n",
       "      <th>gy_z_117</th>\n",
       "      <th>gy_z_118</th>\n",
       "      <th>gy_z_119</th>\n",
       "      <th>gy_z_120</th>\n",
       "      <th>gy_z_121</th>\n",
       "      <th>gy_z_122</th>\n",
       "      <th>gy_z_123</th>\n",
       "      <th>gy_z_124</th>\n",
       "      <th>gy_z_125</th>\n",
       "      <th>gy_z_126</th>\n",
       "      <th>gy_z_127</th>\n",
       "      <th>gy_z_128</th>\n",
       "      <th>gy_z_129</th>\n",
       "      <th>gy_z_130</th>\n",
       "      <th>gy_z_131</th>\n",
       "      <th>gy_z_132</th>\n",
       "      <th>gy_z_133</th>\n",
       "      <th>gy_z_134</th>\n",
       "      <th>gy_z_135</th>\n",
       "      <th>gy_z_136</th>\n",
       "      <th>gy_z_137</th>\n",
       "      <th>gy_z_138</th>\n",
       "      <th>gy_z_139</th>\n",
       "      <th>gy_z_140</th>\n",
       "      <th>gy_z_141</th>\n",
       "      <th>gy_z_142</th>\n",
       "      <th>gy_z_143</th>\n",
       "      <th>gy_z_144</th>\n",
       "      <th>gy_z_145</th>\n",
       "      <th>gy_z_146</th>\n",
       "      <th>gy_z_147</th>\n",
       "      <th>gy_z_148</th>\n",
       "      <th>gy_z_149</th>\n",
       "      <th>gy_z_150</th>\n",
       "      <th>gy_z_151</th>\n",
       "      <th>gy_z_152</th>\n",
       "      <th>gy_z_153</th>\n",
       "      <th>gy_z_154</th>\n",
       "      <th>gy_z_155</th>\n",
       "      <th>gy_z_156</th>\n",
       "      <th>gy_z_157</th>\n",
       "      <th>gy_z_158</th>\n",
       "      <th>gy_z_159</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>idle</td>\n",
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       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
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       "      <td>0.0000</td>\n",
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       "      <td>0.0000</td>\n",
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       "      <td>0.0000</td>\n",
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       "      <td>0.0000</td>\n",
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       "      <td>0.0000</td>\n",
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       "      <td>0.0000</td>\n",
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       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
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       "      <td>0.0000</td>\n",
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       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
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       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
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       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
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       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
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       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
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       "      <td>0.1200</td>\n",
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       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
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       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.120</td>\n",
       "      <td>0.1200</td>\n",
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       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>1.6956</td>\n",
       "      <td>1.8300</td>\n",
       "      <td>1.8018</td>\n",
       "      <td>1.8584</td>\n",
       "      <td>1.6721</td>\n",
       "      <td>1.7700</td>\n",
       "      <td>1.7277</td>\n",
       "      <td>1.7602</td>\n",
       "      <td>1.8501</td>\n",
       "      <td>1.7555</td>\n",
       "      <td>1.8300</td>\n",
       "      <td>1.8300</td>\n",
       "      <td>1.8300</td>\n",
       "      <td>1.8231</td>\n",
       "      <td>1.7880</td>\n",
       "      <td>1.8294</td>\n",
       "      <td>1.8150</td>\n",
       "      <td>1.8197</td>\n",
       "      <td>1.9360</td>\n",
       "      <td>1.7700</td>\n",
       "      <td>1.7700</td>\n",
       "      <td>1.8342</td>\n",
       "      <td>1.7907</td>\n",
       "      <td>1.9474</td>\n",
       "      <td>1.8824</td>\n",
       "      <td>1.8117</td>\n",
       "      <td>1.7415</td>\n",
       "      <td>1.8768</td>\n",
       "      <td>1.8562</td>\n",
       "      <td>1.7519</td>\n",
       "      <td>1.7272</td>\n",
       "      <td>1.8300</td>\n",
       "      <td>1.8300</td>\n",
       "      <td>1.7750</td>\n",
       "      <td>1.5833</td>\n",
       "      <td>1.7034</td>\n",
       "      <td>1.8447</td>\n",
       "      <td>1.8851</td>\n",
       "      <td>1.7100</td>\n",
       "      <td>1.8198</td>\n",
       "      <td>1.8470</td>\n",
       "      <td>1.8900</td>\n",
       "      <td>1.8018</td>\n",
       "      <td>1.9465</td>\n",
       "      <td>1.8447</td>\n",
       "      <td>1.9019</td>\n",
       "      <td>1.9436</td>\n",
       "      <td>1.9644</td>\n",
       "      <td>2.0039</td>\n",
       "      <td>1.9171</td>\n",
       "      <td>1.8110</td>\n",
       "      <td>1.9500</td>\n",
       "      <td>1.9500</td>\n",
       "      <td>1.9035</td>\n",
       "      <td>1.7153</td>\n",
       "      <td>1.7100</td>\n",
       "      <td>1.7647</td>\n",
       "      <td>1.8480</td>\n",
       "      <td>1.9120</td>\n",
       "      <td>1.8900</td>\n",
       "      <td>1.7850</td>\n",
       "      <td>1.9193</td>\n",
       "      <td>1.9083</td>\n",
       "      <td>1.8327</td>\n",
       "      <td>1.9050</td>\n",
       "      <td>1.9500</td>\n",
       "      <td>1.9005</td>\n",
       "      <td>1.8324</td>\n",
       "      <td>1.7891</td>\n",
       "      <td>1.6768</td>\n",
       "      <td>1.8061</td>\n",
       "      <td>1.7446</td>\n",
       "      <td>1.7421</td>\n",
       "      <td>1.7987</td>\n",
       "      <td>1.9185</td>\n",
       "      <td>1.8319</td>\n",
       "      <td>1.9500</td>\n",
       "      <td>1.9222</td>\n",
       "      <td>1.8445</td>\n",
       "      <td>1.8300</td>\n",
       "      <td>1.8300</td>\n",
       "      <td>1.8300</td>\n",
       "      <td>1.7401</td>\n",
       "      <td>1.7100</td>\n",
       "      <td>1.8389</td>\n",
       "      <td>1.8900</td>\n",
       "      <td>1.9120</td>\n",
       "      <td>1.9495</td>\n",
       "      <td>1.7700</td>\n",
       "      <td>1.7700</td>\n",
       "      <td>1.7700</td>\n",
       "      <td>2.0065</td>\n",
       "      <td>2.0054</td>\n",
       "      <td>1.9630</td>\n",
       "      <td>1.7260</td>\n",
       "      <td>1.7815</td>\n",
       "      <td>1.8217</td>\n",
       "      <td>1.7826</td>\n",
       "      <td>1.7584</td>\n",
       "      <td>1.8914</td>\n",
       "      <td>1.8804</td>\n",
       "      <td>1.8566</td>\n",
       "      <td>1.9379</td>\n",
       "      <td>1.8300</td>\n",
       "      <td>1.8300</td>\n",
       "      <td>1.8579</td>\n",
       "      <td>1.9124</td>\n",
       "      <td>1.9489</td>\n",
       "      <td>1.7700</td>\n",
       "      <td>1.7700</td>\n",
       "      <td>1.7330</td>\n",
       "      <td>1.7992</td>\n",
       "      <td>1.7250</td>\n",
       "      <td>1.8154</td>\n",
       "      <td>1.7755</td>\n",
       "      <td>1.7700</td>\n",
       "      <td>1.8080</td>\n",
       "      <td>1.7963</td>\n",
       "      <td>1.8444</td>\n",
       "      <td>1.8709</td>\n",
       "      <td>1.8251</td>\n",
       "      <td>1.7837</td>\n",
       "      <td>1.6798</td>\n",
       "      <td>1.7305</td>\n",
       "      <td>1.8052</td>\n",
       "      <td>1.7431</td>\n",
       "      <td>1.8146</td>\n",
       "      <td>1.8300</td>\n",
       "      <td>1.7933</td>\n",
       "      <td>1.7561</td>\n",
       "      <td>1.6890</td>\n",
       "      <td>1.8340</td>\n",
       "      <td>1.8979</td>\n",
       "      <td>1.9368</td>\n",
       "      <td>1.8503</td>\n",
       "      <td>1.8588</td>\n",
       "      <td>1.7700</td>\n",
       "      <td>1.8004</td>\n",
       "      <td>1.8793</td>\n",
       "      <td>2.0090</td>\n",
       "      <td>1.8588</td>\n",
       "      <td>1.7100</td>\n",
       "      <td>1.7791</td>\n",
       "      <td>1.8900</td>\n",
       "      <td>1.8979</td>\n",
       "      <td>1.9334</td>\n",
       "      <td>1.9281</td>\n",
       "      <td>1.9498</td>\n",
       "      <td>1.8258</td>\n",
       "      <td>1.7732</td>\n",
       "      <td>1.7206</td>\n",
       "      <td>1.8300</td>\n",
       "      <td>1.8300</td>\n",
       "      <td>1.8620</td>\n",
       "      <td>1.7700</td>\n",
       "      <td>1.7700</td>\n",
       "      <td>1.8900</td>\n",
       "      <td>1.8900</td>\n",
       "      <td>1.8723</td>\n",
       "      <td>1.8593</td>\n",
       "      <td>0.9200</td>\n",
       "      <td>0.8093</td>\n",
       "      <td>0.9482</td>\n",
       "      <td>1.0242</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9248</td>\n",
       "      <td>0.8359</td>\n",
       "      <td>0.9751</td>\n",
       "      <td>0.9667</td>\n",
       "      <td>0.8935</td>\n",
       "      <td>0.8132</td>\n",
       "      <td>0.7381</td>\n",
       "      <td>0.8235</td>\n",
       "      <td>0.9200</td>\n",
       "      <td>0.8631</td>\n",
       "      <td>0.7320</td>\n",
       "      <td>0.8825</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.8468</td>\n",
       "      <td>0.8500</td>\n",
       "      <td>0.8179</td>\n",
       "      <td>0.8976</td>\n",
       "      <td>0.8510</td>\n",
       "      <td>1.0924</td>\n",
       "      <td>1.0217</td>\n",
       "      <td>1.0105</td>\n",
       "      <td>0.8917</td>\n",
       "      <td>0.8894</td>\n",
       "      <td>0.8472</td>\n",
       "      <td>0.9628</td>\n",
       "      <td>1.0359</td>\n",
       "      <td>0.9481</td>\n",
       "      <td>0.9850</td>\n",
       "      <td>0.9200</td>\n",
       "      <td>0.7948</td>\n",
       "      <td>0.9274</td>\n",
       "      <td>0.9638</td>\n",
       "      <td>0.9200</td>\n",
       "      <td>0.9749</td>\n",
       "      <td>0.9200</td>\n",
       "      <td>0.9200</td>\n",
       "      <td>1.0082</td>\n",
       "      <td>0.7360</td>\n",
       "      <td>0.8671</td>\n",
       "      <td>0.9319</td>\n",
       "      <td>0.9736</td>\n",
       "      <td>0.8668</td>\n",
       "      <td>0.9128</td>\n",
       "      <td>0.8247</td>\n",
       "      <td>0.9663</td>\n",
       "      <td>1.0305</td>\n",
       "      <td>0.9262</td>\n",
       "      <td>0.8345</td>\n",
       "      <td>0.8492</td>\n",
       "      <td>1.0399</td>\n",
       "      <td>0.9305</td>\n",
       "      <td>1.0400</td>\n",
       "      <td>1.0400</td>\n",
       "      <td>0.8792</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>1.0093</td>\n",
       "      <td>0.9565</td>\n",
       "      <td>0.9200</td>\n",
       "      <td>0.9350</td>\n",
       "      <td>0.8798</td>\n",
       "      <td>0.8436</td>\n",
       "      <td>0.9248</td>\n",
       "      <td>0.8803</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.8875</td>\n",
       "      <td>0.8179</td>\n",
       "      <td>0.9773</td>\n",
       "      <td>1.0842</td>\n",
       "      <td>0.9189</td>\n",
       "      <td>0.8670</td>\n",
       "      <td>0.9478</td>\n",
       "      <td>1.1166</td>\n",
       "      <td>1.1600</td>\n",
       "      <td>1.0066</td>\n",
       "      <td>0.9500</td>\n",
       "      <td>1.1148</td>\n",
       "      <td>1.0405</td>\n",
       "      <td>0.9096</td>\n",
       "      <td>0.8500</td>\n",
       "      <td>0.8757</td>\n",
       "      <td>0.9194</td>\n",
       "      <td>1.0263</td>\n",
       "      <td>0.9520</td>\n",
       "      <td>0.8773</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9200</td>\n",
       "      <td>0.9200</td>\n",
       "      <td>0.8976</td>\n",
       "      <td>1.0457</td>\n",
       "      <td>0.9883</td>\n",
       "      <td>1.0274</td>\n",
       "      <td>1.0463</td>\n",
       "      <td>1.0693</td>\n",
       "      <td>0.8109</td>\n",
       "      <td>0.9466</td>\n",
       "      <td>1.0279</td>\n",
       "      <td>1.0976</td>\n",
       "      <td>1.0624</td>\n",
       "      <td>1.0958</td>\n",
       "      <td>1.0702</td>\n",
       "      <td>0.9243</td>\n",
       "      <td>1.0283</td>\n",
       "      <td>0.9612</td>\n",
       "      <td>0.8130</td>\n",
       "      <td>0.8500</td>\n",
       "      <td>0.7900</td>\n",
       "      <td>0.7609</td>\n",
       "      <td>0.6810</td>\n",
       "      <td>0.8448</td>\n",
       "      <td>1.0463</td>\n",
       "      <td>0.9200</td>\n",
       "      <td>0.9200</td>\n",
       "      <td>0.9200</td>\n",
       "      <td>0.7300</td>\n",
       "      <td>0.7300</td>\n",
       "      <td>0.8372</td>\n",
       "      <td>0.9174</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9441</td>\n",
       "      <td>0.8667</td>\n",
       "      <td>0.9079</td>\n",
       "      <td>0.8404</td>\n",
       "      <td>1.0646</td>\n",
       "      <td>1.0188</td>\n",
       "      <td>0.8873</td>\n",
       "      <td>0.9107</td>\n",
       "      <td>0.8654</td>\n",
       "      <td>0.9552</td>\n",
       "      <td>0.9824</td>\n",
       "      <td>0.9200</td>\n",
       "      <td>0.9200</td>\n",
       "      <td>0.9200</td>\n",
       "      <td>0.9790</td>\n",
       "      <td>1.0178</td>\n",
       "      <td>0.9570</td>\n",
       "      <td>0.9430</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9721</td>\n",
       "      <td>0.9366</td>\n",
       "      <td>0.8961</td>\n",
       "      <td>0.9200</td>\n",
       "      <td>0.9176</td>\n",
       "      <td>0.8869</td>\n",
       "      <td>0.8562</td>\n",
       "      <td>0.9802</td>\n",
       "      <td>1.0582</td>\n",
       "      <td>0.8207</td>\n",
       "      <td>0.8377</td>\n",
       "      <td>0.9174</td>\n",
       "      <td>0.9200</td>\n",
       "      <td>0.9200</td>\n",
       "      <td>1.0823</td>\n",
       "      <td>1.1000</td>\n",
       "      <td>1.4144</td>\n",
       "      <td>1.4600</td>\n",
       "      <td>1.3755</td>\n",
       "      <td>1.4126</td>\n",
       "      <td>1.5632</td>\n",
       "      <td>1.6751</td>\n",
       "      <td>1.5230</td>\n",
       "      <td>1.4551</td>\n",
       "      <td>1.5900</td>\n",
       "      <td>1.5407</td>\n",
       "      <td>1.4232</td>\n",
       "      <td>1.4519</td>\n",
       "      <td>1.5240</td>\n",
       "      <td>1.5751</td>\n",
       "      <td>1.4600</td>\n",
       "      <td>1.4600</td>\n",
       "      <td>1.4775</td>\n",
       "      <td>1.5300</td>\n",
       "      <td>1.5300</td>\n",
       "      <td>1.5300</td>\n",
       "      <td>1.4866</td>\n",
       "      <td>1.4975</td>\n",
       "      <td>1.5797</td>\n",
       "      <td>1.5900</td>\n",
       "      <td>1.4038</td>\n",
       "      <td>1.4392</td>\n",
       "      <td>1.4600</td>\n",
       "      <td>1.5146</td>\n",
       "      <td>1.5638</td>\n",
       "      <td>1.4392</td>\n",
       "      <td>1.5099</td>\n",
       "      <td>1.4624</td>\n",
       "      <td>1.5581</td>\n",
       "      <td>1.5630</td>\n",
       "      <td>1.5093</td>\n",
       "      <td>1.4626</td>\n",
       "      <td>1.5826</td>\n",
       "      <td>1.5462</td>\n",
       "      <td>1.5675</td>\n",
       "      <td>1.3013</td>\n",
       "      <td>1.3570</td>\n",
       "      <td>1.4640</td>\n",
       "      <td>1.5741</td>\n",
       "      <td>1.5312</td>\n",
       "      <td>1.5129</td>\n",
       "      <td>1.4600</td>\n",
       "      <td>1.4600</td>\n",
       "      <td>1.4768</td>\n",
       "      <td>1.5228</td>\n",
       "      <td>1.4600</td>\n",
       "      <td>1.4463</td>\n",
       "      <td>1.5197</td>\n",
       "      <td>1.6438</td>\n",
       "      <td>1.4600</td>\n",
       "      <td>1.4919</td>\n",
       "      <td>1.5900</td>\n",
       "      <td>1.5900</td>\n",
       "      <td>1.4090</td>\n",
       "      <td>1.4410</td>\n",
       "      <td>1.5800</td>\n",
       "      <td>1.6425</td>\n",
       "      <td>1.5900</td>\n",
       "      <td>1.5900</td>\n",
       "      <td>1.5327</td>\n",
       "      <td>1.5125</td>\n",
       "      <td>1.5285</td>\n",
       "      <td>1.4869</td>\n",
       "      <td>1.3448</td>\n",
       "      <td>1.5188</td>\n",
       "      <td>1.4332</td>\n",
       "      <td>1.5521</td>\n",
       "      <td>1.4975</td>\n",
       "      <td>1.4975</td>\n",
       "      <td>1.4908</td>\n",
       "      <td>1.5458</td>\n",
       "      <td>1.5900</td>\n",
       "      <td>1.5438</td>\n",
       "      <td>1.4602</td>\n",
       "      <td>1.5755</td>\n",
       "      <td>1.4682</td>\n",
       "      <td>1.5300</td>\n",
       "      <td>1.5300</td>\n",
       "      <td>1.5749</td>\n",
       "      <td>1.5900</td>\n",
       "      <td>1.4793</td>\n",
       "      <td>1.5609</td>\n",
       "      <td>1.5520</td>\n",
       "      <td>1.5895</td>\n",
       "      <td>1.6637</td>\n",
       "      <td>1.6841</td>\n",
       "      <td>1.6152</td>\n",
       "      <td>1.4565</td>\n",
       "      <td>1.4654</td>\n",
       "      <td>1.5149</td>\n",
       "      <td>1.5043</td>\n",
       "      <td>1.5312</td>\n",
       "      <td>1.5636</td>\n",
       "      <td>1.4398</td>\n",
       "      <td>1.5512</td>\n",
       "      <td>1.5235</td>\n",
       "      <td>1.5804</td>\n",
       "      <td>1.5300</td>\n",
       "      <td>1.5300</td>\n",
       "      <td>1.5324</td>\n",
       "      <td>1.5300</td>\n",
       "      <td>1.4695</td>\n",
       "      <td>1.4935</td>\n",
       "      <td>1.6455</td>\n",
       "      <td>1.6983</td>\n",
       "      <td>1.6312</td>\n",
       "      <td>1.6085</td>\n",
       "      <td>1.5267</td>\n",
       "      <td>1.5375</td>\n",
       "      <td>1.5439</td>\n",
       "      <td>1.4174</td>\n",
       "      <td>1.4000</td>\n",
       "      <td>1.4380</td>\n",
       "      <td>1.5331</td>\n",
       "      <td>1.4600</td>\n",
       "      <td>1.4600</td>\n",
       "      <td>1.5793</td>\n",
       "      <td>1.4896</td>\n",
       "      <td>1.5751</td>\n",
       "      <td>1.5498</td>\n",
       "      <td>1.6500</td>\n",
       "      <td>1.6334</td>\n",
       "      <td>1.5977</td>\n",
       "      <td>1.4328</td>\n",
       "      <td>1.4000</td>\n",
       "      <td>1.5793</td>\n",
       "      <td>1.5688</td>\n",
       "      <td>1.4693</td>\n",
       "      <td>1.5128</td>\n",
       "      <td>1.4285</td>\n",
       "      <td>1.3390</td>\n",
       "      <td>1.4624</td>\n",
       "      <td>1.4600</td>\n",
       "      <td>1.4777</td>\n",
       "      <td>1.5238</td>\n",
       "      <td>1.5890</td>\n",
       "      <td>1.5081</td>\n",
       "      <td>1.4499</td>\n",
       "      <td>1.5031</td>\n",
       "      <td>1.4600</td>\n",
       "      <td>1.3649</td>\n",
       "      <td>1.4774</td>\n",
       "      <td>1.4600</td>\n",
       "      <td>1.4951</td>\n",
       "      <td>1.4600</td>\n",
       "      <td>1.4600</td>\n",
       "      <td>1.4600</td>\n",
       "      <td>1.5301</td>\n",
       "      <td>1.5691</td>\n",
       "      <td>1.5593</td>\n",
       "      <td>1.5423</td>\n",
       "      <td>1.4626</td>\n",
       "      <td>1.4666</td>\n",
       "      <td>1.5141</td>\n",
       "      <td>1.5300</td>\n",
       "      <td>1.5607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>motion</td>\n",
       "      <td>0.1042</td>\n",
       "      <td>0.2377</td>\n",
       "      <td>0.2494</td>\n",
       "      <td>0.1576</td>\n",
       "      <td>0.0721</td>\n",
       "      <td>0.0231</td>\n",
       "      <td>-0.1946</td>\n",
       "      <td>-0.1585</td>\n",
       "      <td>-0.1443</td>\n",
       "      <td>-0.0637</td>\n",
       "      <td>0.0402</td>\n",
       "      <td>0.0603</td>\n",
       "      <td>0.0679</td>\n",
       "      <td>0.0631</td>\n",
       "      <td>0.0900</td>\n",
       "      <td>0.0810</td>\n",
       "      <td>0.0433</td>\n",
       "      <td>-0.0056</td>\n",
       "      <td>-0.0288</td>\n",
       "      <td>-0.0526</td>\n",
       "      <td>-0.0657</td>\n",
       "      <td>-0.0846</td>\n",
       "      <td>-0.0299</td>\n",
       "      <td>-0.0235</td>\n",
       "      <td>-0.0042</td>\n",
       "      <td>0.0432</td>\n",
       "      <td>0.0496</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>-0.0009</td>\n",
       "      <td>-0.0084</td>\n",
       "      <td>-0.0345</td>\n",
       "      <td>-0.0343</td>\n",
       "      <td>-0.0370</td>\n",
       "      <td>-0.0226</td>\n",
       "      <td>-0.0288</td>\n",
       "      <td>-0.0107</td>\n",
       "      <td>-0.0181</td>\n",
       "      <td>-0.0113</td>\n",
       "      <td>-0.0156</td>\n",
       "      <td>-0.0373</td>\n",
       "      <td>-0.0560</td>\n",
       "      <td>-0.0422</td>\n",
       "      <td>-0.0489</td>\n",
       "      <td>-0.0594</td>\n",
       "      <td>-0.0670</td>\n",
       "      <td>-0.0472</td>\n",
       "      <td>-0.1017</td>\n",
       "      <td>-0.1278</td>\n",
       "      <td>-0.0910</td>\n",
       "      <td>-0.0120</td>\n",
       "      <td>-0.0469</td>\n",
       "      <td>-0.1495</td>\n",
       "      <td>-0.1059</td>\n",
       "      <td>-0.0600</td>\n",
       "      <td>-0.0588</td>\n",
       "      <td>0.0463</td>\n",
       "      <td>0.0624</td>\n",
       "      <td>0.0332</td>\n",
       "      <td>-0.0703</td>\n",
       "      <td>0.0356</td>\n",
       "      <td>0.1770</td>\n",
       "      <td>0.2823</td>\n",
       "      <td>0.2136</td>\n",
       "      <td>0.1498</td>\n",
       "      <td>0.1973</td>\n",
       "      <td>0.1919</td>\n",
       "      <td>0.2628</td>\n",
       "      <td>0.2217</td>\n",
       "      <td>0.2501</td>\n",
       "      <td>0.0744</td>\n",
       "      <td>-0.0098</td>\n",
       "      <td>-0.0809</td>\n",
       "      <td>-0.1247</td>\n",
       "      <td>-0.1046</td>\n",
       "      <td>-0.0800</td>\n",
       "      <td>-0.0603</td>\n",
       "      <td>-0.0400</td>\n",
       "      <td>-0.0400</td>\n",
       "      <td>-0.0988</td>\n",
       "      <td>-0.1565</td>\n",
       "      <td>-0.1358</td>\n",
       "      <td>-0.1256</td>\n",
       "      <td>-0.1342</td>\n",
       "      <td>-0.1352</td>\n",
       "      <td>-0.1158</td>\n",
       "      <td>-0.0835</td>\n",
       "      <td>-0.0981</td>\n",
       "      <td>-0.1378</td>\n",
       "      <td>-0.1182</td>\n",
       "      <td>-0.1120</td>\n",
       "      <td>-0.1257</td>\n",
       "      <td>-0.1172</td>\n",
       "      <td>-0.0614</td>\n",
       "      <td>0.0092</td>\n",
       "      <td>0.0143</td>\n",
       "      <td>0.0002</td>\n",
       "      <td>0.0068</td>\n",
       "      <td>-0.0269</td>\n",
       "      <td>-0.1106</td>\n",
       "      <td>-0.1432</td>\n",
       "      <td>0.0305</td>\n",
       "      <td>0.0931</td>\n",
       "      <td>-0.0537</td>\n",
       "      <td>-0.3284</td>\n",
       "      <td>-0.2447</td>\n",
       "      <td>-0.0407</td>\n",
       "      <td>-0.2483</td>\n",
       "      <td>-0.1395</td>\n",
       "      <td>-0.0541</td>\n",
       "      <td>-0.0754</td>\n",
       "      <td>-0.1336</td>\n",
       "      <td>-0.1317</td>\n",
       "      <td>-0.1649</td>\n",
       "      <td>-0.0779</td>\n",
       "      <td>-0.1000</td>\n",
       "      <td>-0.1064</td>\n",
       "      <td>-0.0621</td>\n",
       "      <td>-0.0688</td>\n",
       "      <td>-0.0546</td>\n",
       "      <td>-0.0703</td>\n",
       "      <td>-0.0773</td>\n",
       "      <td>-0.0562</td>\n",
       "      <td>-0.0561</td>\n",
       "      <td>-0.0356</td>\n",
       "      <td>0.0239</td>\n",
       "      <td>0.0058</td>\n",
       "      <td>-0.0100</td>\n",
       "      <td>0.0327</td>\n",
       "      <td>0.0529</td>\n",
       "      <td>0.0426</td>\n",
       "      <td>0.0561</td>\n",
       "      <td>0.1388</td>\n",
       "      <td>0.1143</td>\n",
       "      <td>0.0486</td>\n",
       "      <td>0.1510</td>\n",
       "      <td>-0.1230</td>\n",
       "      <td>-0.1999</td>\n",
       "      <td>0.5312</td>\n",
       "      <td>0.0671</td>\n",
       "      <td>-0.0061</td>\n",
       "      <td>0.0293</td>\n",
       "      <td>0.1165</td>\n",
       "      <td>0.1923</td>\n",
       "      <td>0.0290</td>\n",
       "      <td>-0.0468</td>\n",
       "      <td>-0.0852</td>\n",
       "      <td>0.0085</td>\n",
       "      <td>0.1262</td>\n",
       "      <td>0.2682</td>\n",
       "      <td>0.2969</td>\n",
       "      <td>0.2172</td>\n",
       "      <td>-0.0109</td>\n",
       "      <td>0.1839</td>\n",
       "      <td>0.2604</td>\n",
       "      <td>0.3814</td>\n",
       "      <td>0.3131</td>\n",
       "      <td>-0.0096</td>\n",
       "      <td>0.0693</td>\n",
       "      <td>0.0829</td>\n",
       "      <td>0.2605</td>\n",
       "      <td>-1.1032</td>\n",
       "      <td>-0.9968</td>\n",
       "      <td>-0.9618</td>\n",
       "      <td>-0.9952</td>\n",
       "      <td>-0.9807</td>\n",
       "      <td>-1.0038</td>\n",
       "      <td>-0.9849</td>\n",
       "      <td>-1.0371</td>\n",
       "      <td>-1.0085</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0099</td>\n",
       "      <td>-0.9965</td>\n",
       "      <td>-0.9942</td>\n",
       "      <td>-1.0038</td>\n",
       "      <td>-0.9916</td>\n",
       "      <td>-1.0023</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0144</td>\n",
       "      <td>-1.0088</td>\n",
       "      <td>-1.0158</td>\n",
       "      <td>-1.0114</td>\n",
       "      <td>-0.9967</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0153</td>\n",
       "      <td>-0.9932</td>\n",
       "      <td>-0.9996</td>\n",
       "      <td>-1.0250</td>\n",
       "      <td>-1.0091</td>\n",
       "      <td>-1.0016</td>\n",
       "      <td>-1.0200</td>\n",
       "      <td>-1.0257</td>\n",
       "      <td>-1.0230</td>\n",
       "      <td>-1.0148</td>\n",
       "      <td>-1.0024</td>\n",
       "      <td>-0.9766</td>\n",
       "      <td>-1.0444</td>\n",
       "      <td>-1.0238</td>\n",
       "      <td>-1.0124</td>\n",
       "      <td>-0.9968</td>\n",
       "      <td>-1.0121</td>\n",
       "      <td>-0.9978</td>\n",
       "      <td>-0.9911</td>\n",
       "      <td>-0.9900</td>\n",
       "      <td>-1.0470</td>\n",
       "      <td>-1.0272</td>\n",
       "      <td>-0.9681</td>\n",
       "      <td>-0.9927</td>\n",
       "      <td>-1.0368</td>\n",
       "      <td>-1.0925</td>\n",
       "      <td>-1.0143</td>\n",
       "      <td>-0.9800</td>\n",
       "      <td>-0.9800</td>\n",
       "      <td>-1.0057</td>\n",
       "      <td>-0.9815</td>\n",
       "      <td>-1.0590</td>\n",
       "      <td>-1.0143</td>\n",
       "      <td>-0.9924</td>\n",
       "      <td>-0.9149</td>\n",
       "      <td>-1.0639</td>\n",
       "      <td>-1.1192</td>\n",
       "      <td>-1.0400</td>\n",
       "      <td>-1.0400</td>\n",
       "      <td>-0.9495</td>\n",
       "      <td>-1.0069</td>\n",
       "      <td>-0.8398</td>\n",
       "      <td>-0.9543</td>\n",
       "      <td>-1.0308</td>\n",
       "      <td>-1.0450</td>\n",
       "      <td>-0.9157</td>\n",
       "      <td>-0.9465</td>\n",
       "      <td>-0.9615</td>\n",
       "      <td>-0.9800</td>\n",
       "      <td>-0.9800</td>\n",
       "      <td>-0.9900</td>\n",
       "      <td>-1.0031</td>\n",
       "      <td>-1.0184</td>\n",
       "      <td>-1.0361</td>\n",
       "      <td>-1.0592</td>\n",
       "      <td>-1.0535</td>\n",
       "      <td>-1.0742</td>\n",
       "      <td>-1.1060</td>\n",
       "      <td>-1.0844</td>\n",
       "      <td>-1.0332</td>\n",
       "      <td>-1.0461</td>\n",
       "      <td>-1.0570</td>\n",
       "      <td>-1.0754</td>\n",
       "      <td>-1.0603</td>\n",
       "      <td>-1.0446</td>\n",
       "      <td>-1.0261</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0072</td>\n",
       "      <td>-1.0443</td>\n",
       "      <td>-1.0796</td>\n",
       "      <td>-1.0214</td>\n",
       "      <td>-1.0403</td>\n",
       "      <td>-1.0536</td>\n",
       "      <td>-0.9769</td>\n",
       "      <td>-0.9676</td>\n",
       "      <td>-0.9300</td>\n",
       "      <td>-1.0619</td>\n",
       "      <td>-1.1593</td>\n",
       "      <td>-1.0181</td>\n",
       "      <td>-0.9846</td>\n",
       "      <td>-0.9090</td>\n",
       "      <td>-0.8807</td>\n",
       "      <td>-1.0895</td>\n",
       "      <td>-1.0593</td>\n",
       "      <td>-1.1105</td>\n",
       "      <td>-1.0608</td>\n",
       "      <td>-0.9736</td>\n",
       "      <td>-1.0203</td>\n",
       "      <td>-1.0270</td>\n",
       "      <td>-1.0532</td>\n",
       "      <td>-1.0747</td>\n",
       "      <td>-1.0527</td>\n",
       "      <td>-1.0459</td>\n",
       "      <td>-1.0325</td>\n",
       "      <td>-1.0146</td>\n",
       "      <td>-0.9394</td>\n",
       "      <td>-0.9254</td>\n",
       "      <td>-0.9062</td>\n",
       "      <td>-0.9000</td>\n",
       "      <td>-0.9190</td>\n",
       "      <td>-0.9420</td>\n",
       "      <td>-0.9481</td>\n",
       "      <td>-0.9241</td>\n",
       "      <td>-0.9327</td>\n",
       "      <td>-0.9529</td>\n",
       "      <td>-0.9152</td>\n",
       "      <td>-0.8499</td>\n",
       "      <td>-0.7997</td>\n",
       "      <td>-0.9261</td>\n",
       "      <td>-0.9673</td>\n",
       "      <td>-0.7701</td>\n",
       "      <td>-1.1206</td>\n",
       "      <td>-1.8963</td>\n",
       "      <td>-0.8958</td>\n",
       "      <td>-1.0997</td>\n",
       "      <td>-1.0931</td>\n",
       "      <td>-0.7537</td>\n",
       "      <td>-0.7620</td>\n",
       "      <td>-0.7819</td>\n",
       "      <td>-0.8921</td>\n",
       "      <td>-0.9991</td>\n",
       "      <td>-0.9289</td>\n",
       "      <td>-1.0326</td>\n",
       "      <td>-1.1288</td>\n",
       "      <td>-1.1224</td>\n",
       "      <td>-1.0468</td>\n",
       "      <td>-0.9855</td>\n",
       "      <td>-0.9460</td>\n",
       "      <td>-1.2149</td>\n",
       "      <td>-1.1871</td>\n",
       "      <td>-1.1009</td>\n",
       "      <td>-1.0139</td>\n",
       "      <td>-0.8525</td>\n",
       "      <td>-0.9839</td>\n",
       "      <td>-1.0341</td>\n",
       "      <td>-1.0522</td>\n",
       "      <td>0.0621</td>\n",
       "      <td>0.0449</td>\n",
       "      <td>0.0973</td>\n",
       "      <td>0.1595</td>\n",
       "      <td>0.1839</td>\n",
       "      <td>0.2085</td>\n",
       "      <td>0.1843</td>\n",
       "      <td>0.1907</td>\n",
       "      <td>0.1979</td>\n",
       "      <td>0.1941</td>\n",
       "      <td>0.1799</td>\n",
       "      <td>0.1732</td>\n",
       "      <td>0.1700</td>\n",
       "      <td>0.1700</td>\n",
       "      <td>0.1768</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1516</td>\n",
       "      <td>0.1256</td>\n",
       "      <td>0.1158</td>\n",
       "      <td>0.1114</td>\n",
       "      <td>0.1340</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1435</td>\n",
       "      <td>0.1308</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1645</td>\n",
       "      <td>0.1757</td>\n",
       "      <td>0.1870</td>\n",
       "      <td>0.1700</td>\n",
       "      <td>0.1700</td>\n",
       "      <td>0.1166</td>\n",
       "      <td>0.1281</td>\n",
       "      <td>0.1213</td>\n",
       "      <td>0.1412</td>\n",
       "      <td>0.1300</td>\n",
       "      <td>0.1360</td>\n",
       "      <td>0.1222</td>\n",
       "      <td>0.1289</td>\n",
       "      <td>0.1300</td>\n",
       "      <td>0.1310</td>\n",
       "      <td>0.1376</td>\n",
       "      <td>0.1636</td>\n",
       "      <td>0.1196</td>\n",
       "      <td>0.1122</td>\n",
       "      <td>0.1100</td>\n",
       "      <td>0.0997</td>\n",
       "      <td>0.063</td>\n",
       "      <td>0.0754</td>\n",
       "      <td>0.1128</td>\n",
       "      <td>0.1002</td>\n",
       "      <td>0.0890</td>\n",
       "      <td>0.0551</td>\n",
       "      <td>0.1136</td>\n",
       "      <td>0.1098</td>\n",
       "      <td>0.1239</td>\n",
       "      <td>0.1792</td>\n",
       "      <td>0.1737</td>\n",
       "      <td>0.1987</td>\n",
       "      <td>0.2167</td>\n",
       "      <td>0.1786</td>\n",
       "      <td>0.1354</td>\n",
       "      <td>0.1714</td>\n",
       "      <td>0.1967</td>\n",
       "      <td>0.1399</td>\n",
       "      <td>0.1128</td>\n",
       "      <td>0.1101</td>\n",
       "      <td>0.0962</td>\n",
       "      <td>0.1147</td>\n",
       "      <td>0.0946</td>\n",
       "      <td>0.1700</td>\n",
       "      <td>0.1831</td>\n",
       "      <td>0.1784</td>\n",
       "      <td>0.1961</td>\n",
       "      <td>0.1952</td>\n",
       "      <td>0.1465</td>\n",
       "      <td>0.1258</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1052</td>\n",
       "      <td>0.0858</td>\n",
       "      <td>0.0600</td>\n",
       "      <td>0.0519</td>\n",
       "      <td>0.0122</td>\n",
       "      <td>-0.0318</td>\n",
       "      <td>-0.0380</td>\n",
       "      <td>-0.0530</td>\n",
       "      <td>-0.0615</td>\n",
       "      <td>-0.0817</td>\n",
       "      <td>-0.0958</td>\n",
       "      <td>-0.0771</td>\n",
       "      <td>-0.0700</td>\n",
       "      <td>-0.0700</td>\n",
       "      <td>-0.0754</td>\n",
       "      <td>-0.1094</td>\n",
       "      <td>-0.0884</td>\n",
       "      <td>0.0005</td>\n",
       "      <td>0.0631</td>\n",
       "      <td>0.1390</td>\n",
       "      <td>0.0908</td>\n",
       "      <td>0.0152</td>\n",
       "      <td>0.0450</td>\n",
       "      <td>0.1518</td>\n",
       "      <td>0.2666</td>\n",
       "      <td>0.3491</td>\n",
       "      <td>0.2924</td>\n",
       "      <td>0.2154</td>\n",
       "      <td>0.2303</td>\n",
       "      <td>0.2370</td>\n",
       "      <td>0.2453</td>\n",
       "      <td>0.2600</td>\n",
       "      <td>0.2791</td>\n",
       "      <td>0.2738</td>\n",
       "      <td>0.2537</td>\n",
       "      <td>0.2300</td>\n",
       "      <td>0.1994</td>\n",
       "      <td>0.1854</td>\n",
       "      <td>0.1623</td>\n",
       "      <td>0.1520</td>\n",
       "      <td>0.1410</td>\n",
       "      <td>0.1000</td>\n",
       "      <td>0.1000</td>\n",
       "      <td>0.1121</td>\n",
       "      <td>0.1282</td>\n",
       "      <td>0.1148</td>\n",
       "      <td>0.1011</td>\n",
       "      <td>0.0678</td>\n",
       "      <td>-0.0197</td>\n",
       "      <td>0.1190</td>\n",
       "      <td>0.2373</td>\n",
       "      <td>0.0510</td>\n",
       "      <td>0.1798</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>-0.0094</td>\n",
       "      <td>0.0653</td>\n",
       "      <td>0.1984</td>\n",
       "      <td>0.1744</td>\n",
       "      <td>0.1619</td>\n",
       "      <td>0.1571</td>\n",
       "      <td>0.1511</td>\n",
       "      <td>-0.0979</td>\n",
       "      <td>-0.0021</td>\n",
       "      <td>-0.0841</td>\n",
       "      <td>0.1295</td>\n",
       "      <td>0.1812</td>\n",
       "      <td>0.1597</td>\n",
       "      <td>0.2884</td>\n",
       "      <td>0.0002</td>\n",
       "      <td>-0.0024</td>\n",
       "      <td>0.0393</td>\n",
       "      <td>0.0231</td>\n",
       "      <td>0.1349</td>\n",
       "      <td>0.1257</td>\n",
       "      <td>-0.0438</td>\n",
       "      <td>-0.0347</td>\n",
       "      <td>-0.1094</td>\n",
       "      <td>1.2155</td>\n",
       "      <td>1.2795</td>\n",
       "      <td>1.4860</td>\n",
       "      <td>1.9381</td>\n",
       "      <td>2.0855</td>\n",
       "      <td>2.5653</td>\n",
       "      <td>2.0443</td>\n",
       "      <td>2.2740</td>\n",
       "      <td>1.8216</td>\n",
       "      <td>1.1988</td>\n",
       "      <td>1.1530</td>\n",
       "      <td>0.9348</td>\n",
       "      <td>0.9903</td>\n",
       "      <td>1.1503</td>\n",
       "      <td>1.3651</td>\n",
       "      <td>1.5765</td>\n",
       "      <td>1.5680</td>\n",
       "      <td>1.8036</td>\n",
       "      <td>1.8900</td>\n",
       "      <td>1.8062</td>\n",
       "      <td>1.7185</td>\n",
       "      <td>1.1899</td>\n",
       "      <td>1.4595</td>\n",
       "      <td>1.4340</td>\n",
       "      <td>1.4085</td>\n",
       "      <td>1.5504</td>\n",
       "      <td>1.5850</td>\n",
       "      <td>1.8617</td>\n",
       "      <td>1.6789</td>\n",
       "      <td>1.6991</td>\n",
       "      <td>1.9911</td>\n",
       "      <td>2.1345</td>\n",
       "      <td>2.0100</td>\n",
       "      <td>1.7733</td>\n",
       "      <td>1.6402</td>\n",
       "      <td>1.4129</td>\n",
       "      <td>2.1232</td>\n",
       "      <td>2.0337</td>\n",
       "      <td>1.4106</td>\n",
       "      <td>1.2211</td>\n",
       "      <td>1.2395</td>\n",
       "      <td>1.1602</td>\n",
       "      <td>1.3416</td>\n",
       "      <td>1.4889</td>\n",
       "      <td>1.5844</td>\n",
       "      <td>1.5473</td>\n",
       "      <td>1.7995</td>\n",
       "      <td>2.1924</td>\n",
       "      <td>2.3800</td>\n",
       "      <td>1.4277</td>\n",
       "      <td>0.6501</td>\n",
       "      <td>0.9538</td>\n",
       "      <td>1.1794</td>\n",
       "      <td>1.7458</td>\n",
       "      <td>2.0746</td>\n",
       "      <td>1.5669</td>\n",
       "      <td>0.4900</td>\n",
       "      <td>0.4900</td>\n",
       "      <td>1.3816</td>\n",
       "      <td>2.3998</td>\n",
       "      <td>2.1164</td>\n",
       "      <td>1.5487</td>\n",
       "      <td>1.4604</td>\n",
       "      <td>2.2162</td>\n",
       "      <td>2.2227</td>\n",
       "      <td>2.1282</td>\n",
       "      <td>1.7909</td>\n",
       "      <td>1.3965</td>\n",
       "      <td>1.2981</td>\n",
       "      <td>1.0586</td>\n",
       "      <td>1.0960</td>\n",
       "      <td>1.0143</td>\n",
       "      <td>1.1673</td>\n",
       "      <td>1.4440</td>\n",
       "      <td>1.3065</td>\n",
       "      <td>1.2048</td>\n",
       "      <td>1.3695</td>\n",
       "      <td>1.4436</td>\n",
       "      <td>1.3447</td>\n",
       "      <td>0.9986</td>\n",
       "      <td>0.7557</td>\n",
       "      <td>0.4060</td>\n",
       "      <td>0.2495</td>\n",
       "      <td>0.2347</td>\n",
       "      <td>0.9013</td>\n",
       "      <td>1.7256</td>\n",
       "      <td>1.8772</td>\n",
       "      <td>1.8375</td>\n",
       "      <td>0.8428</td>\n",
       "      <td>0.5768</td>\n",
       "      <td>0.0679</td>\n",
       "      <td>-0.0413</td>\n",
       "      <td>0.3700</td>\n",
       "      <td>0.3700</td>\n",
       "      <td>0.1312</td>\n",
       "      <td>0.5717</td>\n",
       "      <td>0.8724</td>\n",
       "      <td>1.4927</td>\n",
       "      <td>1.5832</td>\n",
       "      <td>1.4504</td>\n",
       "      <td>2.0869</td>\n",
       "      <td>1.9252</td>\n",
       "      <td>-0.0936</td>\n",
       "      <td>0.8986</td>\n",
       "      <td>0.4777</td>\n",
       "      <td>0.6813</td>\n",
       "      <td>0.9867</td>\n",
       "      <td>-0.5795</td>\n",
       "      <td>-1.2043</td>\n",
       "      <td>-2.0611</td>\n",
       "      <td>-4.0740</td>\n",
       "      <td>-5.0748</td>\n",
       "      <td>-5.3607</td>\n",
       "      <td>-4.7049</td>\n",
       "      <td>-4.3674</td>\n",
       "      <td>-3.7230</td>\n",
       "      <td>-3.3696</td>\n",
       "      <td>-3.4122</td>\n",
       "      <td>-3.4147</td>\n",
       "      <td>-3.4691</td>\n",
       "      <td>-3.1933</td>\n",
       "      <td>-1.5503</td>\n",
       "      <td>-0.9390</td>\n",
       "      <td>0.0129</td>\n",
       "      <td>0.5823</td>\n",
       "      <td>0.6769</td>\n",
       "      <td>1.2238</td>\n",
       "      <td>2.9949</td>\n",
       "      <td>3.4862</td>\n",
       "      <td>3.9813</td>\n",
       "      <td>4.2512</td>\n",
       "      <td>8.4011</td>\n",
       "      <td>10.2448</td>\n",
       "      <td>12.1574</td>\n",
       "      <td>13.1638</td>\n",
       "      <td>16.0248</td>\n",
       "      <td>17.3005</td>\n",
       "      <td>7.4582</td>\n",
       "      <td>3.2173</td>\n",
       "      <td>-3.8819</td>\n",
       "      <td>-7.4642</td>\n",
       "      <td>-5.5554</td>\n",
       "      <td>-3.6466</td>\n",
       "      <td>-3.4922</td>\n",
       "      <td>0.8553</td>\n",
       "      <td>0.6522</td>\n",
       "      <td>2.6773</td>\n",
       "      <td>2.5159</td>\n",
       "      <td>2.2770</td>\n",
       "      <td>1.3550</td>\n",
       "      <td>1.1089</td>\n",
       "      <td>3.7119</td>\n",
       "      <td>3.2547</td>\n",
       "      <td>1.5383</td>\n",
       "      <td>-0.8400</td>\n",
       "      <td>-1.0060</td>\n",
       "      <td>1.7764</td>\n",
       "      <td>2.6271</td>\n",
       "      <td>2.2200</td>\n",
       "      <td>-0.1376</td>\n",
       "      <td>2.7678</td>\n",
       "      <td>0.3317</td>\n",
       "      <td>0.0582</td>\n",
       "      <td>1.0272</td>\n",
       "      <td>2.0114</td>\n",
       "      <td>4.4213</td>\n",
       "      <td>5.0930</td>\n",
       "      <td>6.1237</td>\n",
       "      <td>6.9476</td>\n",
       "      <td>9.9266</td>\n",
       "      <td>11.9999</td>\n",
       "      <td>13.1630</td>\n",
       "      <td>13.8871</td>\n",
       "      <td>13.9715</td>\n",
       "      <td>14.4492</td>\n",
       "      <td>14.7794</td>\n",
       "      <td>14.0964</td>\n",
       "      <td>13.9368</td>\n",
       "      <td>14.0852</td>\n",
       "      <td>14.4539</td>\n",
       "      <td>14.6989</td>\n",
       "      <td>16.2565</td>\n",
       "      <td>19.3530</td>\n",
       "      <td>19.5060</td>\n",
       "      <td>19.6590</td>\n",
       "      <td>19.7569</td>\n",
       "      <td>20.0388</td>\n",
       "      <td>20.3201</td>\n",
       "      <td>20.2311</td>\n",
       "      <td>20.5625</td>\n",
       "      <td>21.6068</td>\n",
       "      <td>21.9566</td>\n",
       "      <td>23.0304</td>\n",
       "      <td>24.7822</td>\n",
       "      <td>25.7970</td>\n",
       "      <td>27.2089</td>\n",
       "      <td>27.1045</td>\n",
       "      <td>26.8084</td>\n",
       "      <td>28.3436</td>\n",
       "      <td>29.8410</td>\n",
       "      <td>30.2895</td>\n",
       "      <td>30.4482</td>\n",
       "      <td>30.5933</td>\n",
       "      <td>31.0289</td>\n",
       "      <td>31.7646</td>\n",
       "      <td>32.3274</td>\n",
       "      <td>33.5137</td>\n",
       "      <td>33.7455</td>\n",
       "      <td>34.1381</td>\n",
       "      <td>35.3196</td>\n",
       "      <td>35.2159</td>\n",
       "      <td>34.1144</td>\n",
       "      <td>34.0768</td>\n",
       "      <td>35.3157</td>\n",
       "      <td>36.0448</td>\n",
       "      <td>35.9303</td>\n",
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       "      <td>35.4600</td>\n",
       "      <td>35.2133</td>\n",
       "      <td>35.0991</td>\n",
       "      <td>35.5870</td>\n",
       "      <td>37.6514</td>\n",
       "      <td>38.0184</td>\n",
       "      <td>36.4037</td>\n",
       "      <td>37.1172</td>\n",
       "      <td>37.9200</td>\n",
       "      <td>39.3804</td>\n",
       "      <td>39.6548</td>\n",
       "      <td>38.0077</td>\n",
       "      <td>35.8066</td>\n",
       "      <td>35.2773</td>\n",
       "      <td>34.9525</td>\n",
       "      <td>33.6333</td>\n",
       "      <td>31.4872</td>\n",
       "      <td>30.1138</td>\n",
       "      <td>29.6448</td>\n",
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       "      <td>28.7650</td>\n",
       "      <td>27.6546</td>\n",
       "      <td>26.5748</td>\n",
       "      <td>26.0169</td>\n",
       "      <td>24.8215</td>\n",
       "      <td>24.5636</td>\n",
       "      <td>21.8624</td>\n",
       "      <td>20.8882</td>\n",
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       "      <td>18.4320</td>\n",
       "      <td>16.8691</td>\n",
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       "      <td>15.7310</td>\n",
       "      <td>14.9793</td>\n",
       "      <td>14.6203</td>\n",
       "      <td>14.1823</td>\n",
       "      <td>14.5899</td>\n",
       "      <td>15.5500</td>\n",
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       "      <td>16.1700</td>\n",
       "      <td>16.0798</td>\n",
       "      <td>15.9962</td>\n",
       "      <td>15.8431</td>\n",
       "      <td>16.6571</td>\n",
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       "      <td>19.8427</td>\n",
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       "      <td>25.7717</td>\n",
       "      <td>29.8035</td>\n",
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       "      <td>29.6457</td>\n",
       "      <td>32.4965</td>\n",
       "      <td>39.5034</td>\n",
       "      <td>45.1568</td>\n",
       "      <td>50.8196</td>\n",
       "      <td>53.8087</td>\n",
       "      <td>60.1851</td>\n",
       "      <td>67.3341</td>\n",
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       "      <td>77.4489</td>\n",
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       "      <td>70.9672</td>\n",
       "      <td>70.1798</td>\n",
       "      <td>63.3764</td>\n",
       "      <td>61.5282</td>\n",
       "      <td>56.6308</td>\n",
       "      <td>53.7414</td>\n",
       "      <td>47.9906</td>\n",
       "      <td>41.9361</td>\n",
       "      <td>47.4524</td>\n",
       "      <td>52.0462</td>\n",
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       "      <td>52.3710</td>\n",
       "      <td>50.7343</td>\n",
       "      <td>47.1830</td>\n",
       "      <td>48.2812</td>\n",
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       "      <td>48.6994</td>\n",
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       "      <td>-6.7110</td>\n",
       "      <td>-6.5627</td>\n",
       "      <td>-4.4451</td>\n",
       "      <td>-2.9682</td>\n",
       "      <td>-2.4891</td>\n",
       "      <td>-0.8045</td>\n",
       "      <td>-0.0307</td>\n",
       "      <td>2.4611</td>\n",
       "      <td>3.2815</td>\n",
       "      <td>4.2443</td>\n",
       "      <td>4.5538</td>\n",
       "      <td>5.9829</td>\n",
       "      <td>7.2280</td>\n",
       "      <td>7.5311</td>\n",
       "      <td>7.6379</td>\n",
       "      <td>7.2926</td>\n",
       "      <td>5.1867</td>\n",
       "      <td>5.4673</td>\n",
       "      <td>6.3775</td>\n",
       "      <td>6.5300</td>\n",
       "      <td>6.5300</td>\n",
       "      <td>6.0766</td>\n",
       "      <td>5.6517</td>\n",
       "      <td>2.9795</td>\n",
       "      <td>0.8431</td>\n",
       "      <td>1.0048</td>\n",
       "      <td>1.3065</td>\n",
       "      <td>0.3898</td>\n",
       "      <td>-2.2819</td>\n",
       "      <td>-5.1899</td>\n",
       "      <td>-6.7917</td>\n",
       "      <td>-11.1997</td>\n",
       "      <td>-12.3669</td>\n",
       "      <td>-12.8720</td>\n",
       "      <td>-14.3786</td>\n",
       "      <td>-13.8345</td>\n",
       "      <td>-14.0178</td>\n",
       "      <td>-14.5385</td>\n",
       "      <td>-14.0357</td>\n",
       "      <td>-12.5491</td>\n",
       "      <td>-9.6614</td>\n",
       "      <td>-9.4913</td>\n",
       "      <td>-8.3483</td>\n",
       "      <td>-7.9321</td>\n",
       "      <td>-7.9842</td>\n",
       "      <td>-9.0787</td>\n",
       "      <td>-9.7908</td>\n",
       "      <td>-10.6618</td>\n",
       "      <td>-11.4378</td>\n",
       "      <td>-11.6956</td>\n",
       "      <td>-14.3258</td>\n",
       "      <td>-15.2373</td>\n",
       "      <td>-15.5200</td>\n",
       "      <td>-15.9440</td>\n",
       "      <td>-16.2196</td>\n",
       "      <td>-14.3212</td>\n",
       "      <td>-12.5001</td>\n",
       "      <td>-10.3252</td>\n",
       "      <td>-10.1110</td>\n",
       "      <td>-5.7232</td>\n",
       "      <td>-2.7128</td>\n",
       "      <td>-3.1844</td>\n",
       "      <td>2.0826</td>\n",
       "      <td>3.7782</td>\n",
       "      <td>5.6479</td>\n",
       "      <td>4.6813</td>\n",
       "      <td>3.7147</td>\n",
       "      <td>2.2387</td>\n",
       "      <td>-1.2212</td>\n",
       "      <td>-3.1409</td>\n",
       "      <td>-5.2567</td>\n",
       "      <td>-5.4418</td>\n",
       "      <td>-4.8560</td>\n",
       "      <td>-2.5743</td>\n",
       "      <td>-1.7403</td>\n",
       "      <td>-4.5809</td>\n",
       "      <td>-6.1370</td>\n",
       "      <td>-5.7625</td>\n",
       "      <td>-2.4008</td>\n",
       "      <td>-1.4210</td>\n",
       "      <td>-3.8011</td>\n",
       "      <td>-6.7729</td>\n",
       "      <td>-7.5824</td>\n",
       "      <td>-8.7199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>step</td>\n",
       "      <td>-0.0193</td>\n",
       "      <td>-0.0174</td>\n",
       "      <td>-0.0053</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>-0.0010</td>\n",
       "      <td>-0.0062</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>-0.0069</td>\n",
       "      <td>-0.0197</td>\n",
       "      <td>-0.0200</td>\n",
       "      <td>-0.0300</td>\n",
       "      <td>-0.0300</td>\n",
       "      <td>-0.0300</td>\n",
       "      <td>-0.0200</td>\n",
       "      <td>-0.0180</td>\n",
       "      <td>-0.0100</td>\n",
       "      <td>-0.0100</td>\n",
       "      <td>0.0025</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>-0.0043</td>\n",
       "      <td>-0.0100</td>\n",
       "      <td>-0.0011</td>\n",
       "      <td>0.0011</td>\n",
       "      <td>0.0139</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0103</td>\n",
       "      <td>-0.0021</td>\n",
       "      <td>-0.0134</td>\n",
       "      <td>-0.0200</td>\n",
       "      <td>-0.0111</td>\n",
       "      <td>-0.0074</td>\n",
       "      <td>-0.0044</td>\n",
       "      <td>-0.0015</td>\n",
       "      <td>-0.0170</td>\n",
       "      <td>-0.0182</td>\n",
       "      <td>-0.0148</td>\n",
       "      <td>-0.0273</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0273</td>\n",
       "      <td>0.0400</td>\n",
       "      <td>0.0194</td>\n",
       "      <td>-0.0075</td>\n",
       "      <td>-0.0481</td>\n",
       "      <td>-0.0336</td>\n",
       "      <td>-0.0213</td>\n",
       "      <td>-0.0021</td>\n",
       "      <td>0.0545</td>\n",
       "      <td>0.0287</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>-0.0203</td>\n",
       "      <td>-0.0263</td>\n",
       "      <td>-0.0213</td>\n",
       "      <td>-0.0247</td>\n",
       "      <td>-0.0280</td>\n",
       "      <td>0.0083</td>\n",
       "      <td>0.0029</td>\n",
       "      <td>0.0083</td>\n",
       "      <td>0.0139</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>-0.0396</td>\n",
       "      <td>-0.0306</td>\n",
       "      <td>-0.1003</td>\n",
       "      <td>-0.0696</td>\n",
       "      <td>-0.0456</td>\n",
       "      <td>0.0187</td>\n",
       "      <td>0.0025</td>\n",
       "      <td>-0.0100</td>\n",
       "      <td>-0.0100</td>\n",
       "      <td>-0.0075</td>\n",
       "      <td>0.0394</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0346</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0025</td>\n",
       "      <td>-0.0048</td>\n",
       "      <td>-0.0342</td>\n",
       "      <td>-0.0487</td>\n",
       "      <td>-0.0265</td>\n",
       "      <td>-0.0084</td>\n",
       "      <td>0.0066</td>\n",
       "      <td>0.0009</td>\n",
       "      <td>-0.0338</td>\n",
       "      <td>-0.0072</td>\n",
       "      <td>0.0094</td>\n",
       "      <td>0.0205</td>\n",
       "      <td>0.0233</td>\n",
       "      <td>0.0052</td>\n",
       "      <td>0.0079</td>\n",
       "      <td>0.0030</td>\n",
       "      <td>-0.0028</td>\n",
       "      <td>-0.0100</td>\n",
       "      <td>-0.0040</td>\n",
       "      <td>0.0096</td>\n",
       "      <td>-0.0018</td>\n",
       "      <td>-0.0072</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0191</td>\n",
       "      <td>0.0293</td>\n",
       "      <td>0.0262</td>\n",
       "      <td>0.0122</td>\n",
       "      <td>-0.0177</td>\n",
       "      <td>-0.0280</td>\n",
       "      <td>-0.0164</td>\n",
       "      <td>-0.0033</td>\n",
       "      <td>0.0074</td>\n",
       "      <td>0.0047</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>-0.0249</td>\n",
       "      <td>-0.0427</td>\n",
       "      <td>-0.0557</td>\n",
       "      <td>-0.0437</td>\n",
       "      <td>-0.0179</td>\n",
       "      <td>0.0122</td>\n",
       "      <td>0.0146</td>\n",
       "      <td>0.0032</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>-0.0079</td>\n",
       "      <td>-0.0100</td>\n",
       "      <td>-0.0100</td>\n",
       "      <td>-0.0151</td>\n",
       "      <td>-0.0127</td>\n",
       "      <td>-0.0003</td>\n",
       "      <td>0.0040</td>\n",
       "      <td>-0.0100</td>\n",
       "      <td>-0.0100</td>\n",
       "      <td>-0.0098</td>\n",
       "      <td>0.0021</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>-0.0017</td>\n",
       "      <td>-0.0208</td>\n",
       "      <td>-0.0365</td>\n",
       "      <td>-0.0400</td>\n",
       "      <td>-0.0400</td>\n",
       "      <td>-0.0400</td>\n",
       "      <td>-0.0400</td>\n",
       "      <td>-0.0385</td>\n",
       "      <td>0.0128</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0126</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0087</td>\n",
       "      <td>0.0056</td>\n",
       "      <td>0.0025</td>\n",
       "      <td>-0.0078</td>\n",
       "      <td>-0.0248</td>\n",
       "      <td>-0.0249</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0174</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0155</td>\n",
       "      <td>-1.0130</td>\n",
       "      <td>-1.0190</td>\n",
       "      <td>-1.0138</td>\n",
       "      <td>-1.0137</td>\n",
       "      <td>-1.0169</td>\n",
       "      <td>-1.0103</td>\n",
       "      <td>-1.0197</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0090</td>\n",
       "      <td>-1.0020</td>\n",
       "      <td>-1.0022</td>\n",
       "      <td>-1.0098</td>\n",
       "      <td>-1.0025</td>\n",
       "      <td>-1.0047</td>\n",
       "      <td>-1.0056</td>\n",
       "      <td>-0.9905</td>\n",
       "      <td>-0.9985</td>\n",
       "      <td>-0.9957</td>\n",
       "      <td>-0.9973</td>\n",
       "      <td>-0.9911</td>\n",
       "      <td>-0.9900</td>\n",
       "      <td>-0.9939</td>\n",
       "      <td>-0.9953</td>\n",
       "      <td>-0.9997</td>\n",
       "      <td>-0.9942</td>\n",
       "      <td>-1.0066</td>\n",
       "      <td>-0.9842</td>\n",
       "      <td>-0.9978</td>\n",
       "      <td>-0.9948</td>\n",
       "      <td>-0.9889</td>\n",
       "      <td>-0.9830</td>\n",
       "      <td>-0.9959</td>\n",
       "      <td>-1.0210</td>\n",
       "      <td>-0.9800</td>\n",
       "      <td>-0.9800</td>\n",
       "      <td>-0.9988</td>\n",
       "      <td>-0.9827</td>\n",
       "      <td>-0.9439</td>\n",
       "      <td>-0.9269</td>\n",
       "      <td>-0.9913</td>\n",
       "      <td>-1.0242</td>\n",
       "      <td>-1.0319</td>\n",
       "      <td>-0.9977</td>\n",
       "      <td>-0.9588</td>\n",
       "      <td>-1.0264</td>\n",
       "      <td>-0.9674</td>\n",
       "      <td>-0.9894</td>\n",
       "      <td>-0.9910</td>\n",
       "      <td>-1.0281</td>\n",
       "      <td>-1.0012</td>\n",
       "      <td>-1.0673</td>\n",
       "      <td>-1.0607</td>\n",
       "      <td>-1.0541</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0898</td>\n",
       "      <td>-0.9387</td>\n",
       "      <td>-0.9530</td>\n",
       "      <td>-0.9000</td>\n",
       "      <td>-1.0259</td>\n",
       "      <td>-1.0266</td>\n",
       "      <td>-1.0200</td>\n",
       "      <td>-0.9577</td>\n",
       "      <td>-1.0974</td>\n",
       "      <td>-0.9513</td>\n",
       "      <td>-1.0837</td>\n",
       "      <td>-1.0407</td>\n",
       "      <td>-0.9367</td>\n",
       "      <td>-0.9626</td>\n",
       "      <td>-1.0461</td>\n",
       "      <td>-1.0000</td>\n",
       "      <td>-0.9540</td>\n",
       "      <td>-1.0576</td>\n",
       "      <td>-1.0447</td>\n",
       "      <td>-1.0417</td>\n",
       "      <td>-0.9345</td>\n",
       "      <td>-1.0490</td>\n",
       "      <td>-1.0471</td>\n",
       "      <td>-1.0063</td>\n",
       "      <td>-1.0472</td>\n",
       "      <td>-1.0087</td>\n",
       "      <td>-1.0117</td>\n",
       "      <td>-0.9994</td>\n",
       "      <td>-1.0205</td>\n",
       "      <td>-1.0233</td>\n",
       "      <td>-1.0148</td>\n",
       "      <td>-1.0200</td>\n",
       "      <td>-1.0060</td>\n",
       "      <td>-1.0000</td>\n",
       "      <td>-1.0193</td>\n",
       "      <td>-1.0159</td>\n",
       "      <td>-0.9925</td>\n",
       "      <td>-1.0563</td>\n",
       "      <td>-1.0174</td>\n",
       "      <td>-0.9960</td>\n",
       "      <td>-1.0200</td>\n",
       "      <td>-1.0387</td>\n",
       "      <td>-1.0138</td>\n",
       "      <td>-1.0122</td>\n",
       "      <td>-1.0008</td>\n",
       "      <td>-1.0120</td>\n",
       "      <td>-1.0128</td>\n",
       "      <td>-1.0000</td>\n",
       "      <td>-1.0294</td>\n",
       "      <td>-1.0241</td>\n",
       "      <td>-1.0446</td>\n",
       "      <td>-1.0156</td>\n",
       "      <td>-1.0026</td>\n",
       "      <td>-0.9955</td>\n",
       "      <td>-1.0215</td>\n",
       "      <td>-1.0275</td>\n",
       "      <td>-0.9835</td>\n",
       "      <td>-1.0235</td>\n",
       "      <td>-1.0108</td>\n",
       "      <td>-1.0200</td>\n",
       "      <td>-1.0015</td>\n",
       "      <td>-1.0135</td>\n",
       "      <td>-1.0304</td>\n",
       "      <td>-1.0321</td>\n",
       "      <td>-1.0009</td>\n",
       "      <td>-1.0134</td>\n",
       "      <td>-1.0047</td>\n",
       "      <td>-1.0265</td>\n",
       "      <td>-1.0400</td>\n",
       "      <td>-1.0060</td>\n",
       "      <td>-1.0200</td>\n",
       "      <td>-1.0077</td>\n",
       "      <td>-1.0200</td>\n",
       "      <td>-1.0179</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0206</td>\n",
       "      <td>-1.0013</td>\n",
       "      <td>-1.0183</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0109</td>\n",
       "      <td>-1.0200</td>\n",
       "      <td>-1.0200</td>\n",
       "      <td>-1.0200</td>\n",
       "      <td>-1.0200</td>\n",
       "      <td>-1.0128</td>\n",
       "      <td>-1.0200</td>\n",
       "      <td>-1.0126</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0187</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0178</td>\n",
       "      <td>-1.0052</td>\n",
       "      <td>-1.0051</td>\n",
       "      <td>0.0793</td>\n",
       "      <td>0.1000</td>\n",
       "      <td>0.1000</td>\n",
       "      <td>0.1000</td>\n",
       "      <td>0.1000</td>\n",
       "      <td>0.0924</td>\n",
       "      <td>0.0800</td>\n",
       "      <td>0.0661</td>\n",
       "      <td>0.0690</td>\n",
       "      <td>0.0676</td>\n",
       "      <td>0.0800</td>\n",
       "      <td>0.0869</td>\n",
       "      <td>0.0803</td>\n",
       "      <td>0.0897</td>\n",
       "      <td>0.0900</td>\n",
       "      <td>0.1022</td>\n",
       "      <td>0.1100</td>\n",
       "      <td>0.1110</td>\n",
       "      <td>0.1220</td>\n",
       "      <td>0.1378</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1553</td>\n",
       "      <td>0.1712</td>\n",
       "      <td>0.1810</td>\n",
       "      <td>0.1970</td>\n",
       "      <td>0.2143</td>\n",
       "      <td>0.2200</td>\n",
       "      <td>0.2289</td>\n",
       "      <td>0.2300</td>\n",
       "      <td>0.2339</td>\n",
       "      <td>0.2353</td>\n",
       "      <td>0.2300</td>\n",
       "      <td>0.2221</td>\n",
       "      <td>0.2266</td>\n",
       "      <td>0.2200</td>\n",
       "      <td>0.2111</td>\n",
       "      <td>0.2048</td>\n",
       "      <td>0.1989</td>\n",
       "      <td>0.1930</td>\n",
       "      <td>0.1670</td>\n",
       "      <td>0.1800</td>\n",
       "      <td>0.1800</td>\n",
       "      <td>0.1800</td>\n",
       "      <td>0.1588</td>\n",
       "      <td>0.1573</td>\n",
       "      <td>0.1700</td>\n",
       "      <td>0.1906</td>\n",
       "      <td>0.2000</td>\n",
       "      <td>0.1504</td>\n",
       "      <td>0.1291</td>\n",
       "      <td>0.140</td>\n",
       "      <td>0.1557</td>\n",
       "      <td>0.1909</td>\n",
       "      <td>0.2012</td>\n",
       "      <td>0.1700</td>\n",
       "      <td>0.1610</td>\n",
       "      <td>0.1884</td>\n",
       "      <td>0.1450</td>\n",
       "      <td>0.1700</td>\n",
       "      <td>0.1700</td>\n",
       "      <td>0.1700</td>\n",
       "      <td>0.1867</td>\n",
       "      <td>0.1758</td>\n",
       "      <td>0.1866</td>\n",
       "      <td>0.1539</td>\n",
       "      <td>0.1482</td>\n",
       "      <td>0.1996</td>\n",
       "      <td>0.1132</td>\n",
       "      <td>0.0769</td>\n",
       "      <td>0.0676</td>\n",
       "      <td>0.0967</td>\n",
       "      <td>0.1100</td>\n",
       "      <td>0.0687</td>\n",
       "      <td>0.0479</td>\n",
       "      <td>0.0594</td>\n",
       "      <td>0.0374</td>\n",
       "      <td>0.0206</td>\n",
       "      <td>0.0884</td>\n",
       "      <td>0.0481</td>\n",
       "      <td>0.0903</td>\n",
       "      <td>0.0926</td>\n",
       "      <td>0.0799</td>\n",
       "      <td>0.0617</td>\n",
       "      <td>0.0619</td>\n",
       "      <td>0.0760</td>\n",
       "      <td>0.0790</td>\n",
       "      <td>0.0803</td>\n",
       "      <td>0.0881</td>\n",
       "      <td>0.0993</td>\n",
       "      <td>0.0945</td>\n",
       "      <td>0.0612</td>\n",
       "      <td>0.0410</td>\n",
       "      <td>0.0735</td>\n",
       "      <td>0.0904</td>\n",
       "      <td>0.0957</td>\n",
       "      <td>0.0790</td>\n",
       "      <td>0.0572</td>\n",
       "      <td>0.0548</td>\n",
       "      <td>0.0600</td>\n",
       "      <td>0.0500</td>\n",
       "      <td>0.0518</td>\n",
       "      <td>0.0628</td>\n",
       "      <td>0.0700</td>\n",
       "      <td>0.0796</td>\n",
       "      <td>0.0800</td>\n",
       "      <td>0.0700</td>\n",
       "      <td>0.1014</td>\n",
       "      <td>0.1192</td>\n",
       "      <td>0.1080</td>\n",
       "      <td>0.1000</td>\n",
       "      <td>0.1067</td>\n",
       "      <td>0.1174</td>\n",
       "      <td>0.1094</td>\n",
       "      <td>0.0900</td>\n",
       "      <td>0.0900</td>\n",
       "      <td>0.1049</td>\n",
       "      <td>0.1000</td>\n",
       "      <td>0.1000</td>\n",
       "      <td>0.0763</td>\n",
       "      <td>0.0521</td>\n",
       "      <td>0.0843</td>\n",
       "      <td>0.0946</td>\n",
       "      <td>0.0900</td>\n",
       "      <td>0.0731</td>\n",
       "      <td>0.0830</td>\n",
       "      <td>0.0596</td>\n",
       "      <td>0.0579</td>\n",
       "      <td>0.0518</td>\n",
       "      <td>0.0700</td>\n",
       "      <td>0.0700</td>\n",
       "      <td>0.0408</td>\n",
       "      <td>0.0689</td>\n",
       "      <td>0.0730</td>\n",
       "      <td>0.0753</td>\n",
       "      <td>0.0761</td>\n",
       "      <td>0.0798</td>\n",
       "      <td>0.0700</td>\n",
       "      <td>0.0742</td>\n",
       "      <td>0.0853</td>\n",
       "      <td>0.0804</td>\n",
       "      <td>0.0783</td>\n",
       "      <td>0.0646</td>\n",
       "      <td>0.0600</td>\n",
       "      <td>0.0600</td>\n",
       "      <td>0.0600</td>\n",
       "      <td>0.0600</td>\n",
       "      <td>0.0600</td>\n",
       "      <td>0.0600</td>\n",
       "      <td>0.0600</td>\n",
       "      <td>0.0600</td>\n",
       "      <td>0.0748</td>\n",
       "      <td>0.0800</td>\n",
       "      <td>0.0813</td>\n",
       "      <td>0.0900</td>\n",
       "      <td>0.0900</td>\n",
       "      <td>0.0900</td>\n",
       "      <td>0.0900</td>\n",
       "      <td>0.0952</td>\n",
       "      <td>0.0900</td>\n",
       "      <td>1.8515</td>\n",
       "      <td>2.0744</td>\n",
       "      <td>1.9816</td>\n",
       "      <td>1.9007</td>\n",
       "      <td>1.9503</td>\n",
       "      <td>2.0481</td>\n",
       "      <td>1.8947</td>\n",
       "      <td>1.8300</td>\n",
       "      <td>1.8832</td>\n",
       "      <td>1.8734</td>\n",
       "      <td>1.9253</td>\n",
       "      <td>1.8905</td>\n",
       "      <td>1.9254</td>\n",
       "      <td>2.2000</td>\n",
       "      <td>2.1205</td>\n",
       "      <td>1.9339</td>\n",
       "      <td>2.0640</td>\n",
       "      <td>2.0089</td>\n",
       "      <td>1.9646</td>\n",
       "      <td>2.0100</td>\n",
       "      <td>1.8676</td>\n",
       "      <td>1.8456</td>\n",
       "      <td>1.9500</td>\n",
       "      <td>1.9500</td>\n",
       "      <td>1.8321</td>\n",
       "      <td>1.8900</td>\n",
       "      <td>1.8557</td>\n",
       "      <td>1.7700</td>\n",
       "      <td>1.8971</td>\n",
       "      <td>1.9500</td>\n",
       "      <td>1.9919</td>\n",
       "      <td>1.9835</td>\n",
       "      <td>2.3056</td>\n",
       "      <td>2.3262</td>\n",
       "      <td>2.3209</td>\n",
       "      <td>1.8492</td>\n",
       "      <td>1.9192</td>\n",
       "      <td>1.8983</td>\n",
       "      <td>1.8280</td>\n",
       "      <td>1.7576</td>\n",
       "      <td>1.5145</td>\n",
       "      <td>1.2832</td>\n",
       "      <td>1.0322</td>\n",
       "      <td>0.9958</td>\n",
       "      <td>1.3400</td>\n",
       "      <td>1.3847</td>\n",
       "      <td>1.5067</td>\n",
       "      <td>1.6407</td>\n",
       "      <td>2.0596</td>\n",
       "      <td>2.8472</td>\n",
       "      <td>2.5739</td>\n",
       "      <td>2.3754</td>\n",
       "      <td>1.9766</td>\n",
       "      <td>1.6644</td>\n",
       "      <td>1.4159</td>\n",
       "      <td>1.4430</td>\n",
       "      <td>1.7202</td>\n",
       "      <td>1.8754</td>\n",
       "      <td>1.9866</td>\n",
       "      <td>2.1615</td>\n",
       "      <td>2.1993</td>\n",
       "      <td>2.2370</td>\n",
       "      <td>2.2747</td>\n",
       "      <td>2.3125</td>\n",
       "      <td>1.6446</td>\n",
       "      <td>0.9720</td>\n",
       "      <td>0.9478</td>\n",
       "      <td>0.6700</td>\n",
       "      <td>2.1758</td>\n",
       "      <td>2.5169</td>\n",
       "      <td>2.7611</td>\n",
       "      <td>2.2747</td>\n",
       "      <td>1.7705</td>\n",
       "      <td>1.2095</td>\n",
       "      <td>1.5844</td>\n",
       "      <td>1.4536</td>\n",
       "      <td>0.8052</td>\n",
       "      <td>1.5351</td>\n",
       "      <td>1.7963</td>\n",
       "      <td>1.4500</td>\n",
       "      <td>1.1636</td>\n",
       "      <td>0.9182</td>\n",
       "      <td>0.9802</td>\n",
       "      <td>1.5753</td>\n",
       "      <td>1.5477</td>\n",
       "      <td>1.8710</td>\n",
       "      <td>2.2605</td>\n",
       "      <td>2.5049</td>\n",
       "      <td>2.4400</td>\n",
       "      <td>1.8944</td>\n",
       "      <td>1.8442</td>\n",
       "      <td>1.9200</td>\n",
       "      <td>2.4713</td>\n",
       "      <td>2.1826</td>\n",
       "      <td>2.0800</td>\n",
       "      <td>2.1973</td>\n",
       "      <td>2.2234</td>\n",
       "      <td>2.2396</td>\n",
       "      <td>2.0323</td>\n",
       "      <td>1.7047</td>\n",
       "      <td>1.4119</td>\n",
       "      <td>1.6943</td>\n",
       "      <td>1.5691</td>\n",
       "      <td>1.6846</td>\n",
       "      <td>1.8900</td>\n",
       "      <td>2.0373</td>\n",
       "      <td>2.1853</td>\n",
       "      <td>2.1072</td>\n",
       "      <td>1.9833</td>\n",
       "      <td>1.8881</td>\n",
       "      <td>1.7800</td>\n",
       "      <td>1.9881</td>\n",
       "      <td>2.1400</td>\n",
       "      <td>2.0686</td>\n",
       "      <td>2.1824</td>\n",
       "      <td>2.0287</td>\n",
       "      <td>1.7747</td>\n",
       "      <td>1.7196</td>\n",
       "      <td>1.7938</td>\n",
       "      <td>2.0161</td>\n",
       "      <td>2.0800</td>\n",
       "      <td>2.6069</td>\n",
       "      <td>2.1108</td>\n",
       "      <td>2.1164</td>\n",
       "      <td>2.1400</td>\n",
       "      <td>1.9668</td>\n",
       "      <td>1.8680</td>\n",
       "      <td>1.9893</td>\n",
       "      <td>1.7125</td>\n",
       "      <td>1.7502</td>\n",
       "      <td>1.7197</td>\n",
       "      <td>1.6662</td>\n",
       "      <td>2.0191</td>\n",
       "      <td>1.9991</td>\n",
       "      <td>1.9148</td>\n",
       "      <td>1.7748</td>\n",
       "      <td>1.8633</td>\n",
       "      <td>1.8311</td>\n",
       "      <td>1.8300</td>\n",
       "      <td>1.8646</td>\n",
       "      <td>1.7989</td>\n",
       "      <td>1.6035</td>\n",
       "      <td>1.7972</td>\n",
       "      <td>1.9035</td>\n",
       "      <td>2.0062</td>\n",
       "      <td>1.9789</td>\n",
       "      <td>1.9463</td>\n",
       "      <td>1.9137</td>\n",
       "      <td>1.7333</td>\n",
       "      <td>1.8900</td>\n",
       "      <td>1.9635</td>\n",
       "      <td>2.0103</td>\n",
       "      <td>1.9500</td>\n",
       "      <td>1.7700</td>\n",
       "      <td>1.7748</td>\n",
       "      <td>1.7925</td>\n",
       "      <td>1.8101</td>\n",
       "      <td>1.8277</td>\n",
       "      <td>1.7555</td>\n",
       "      <td>1.9396</td>\n",
       "      <td>3.6600</td>\n",
       "      <td>3.9752</td>\n",
       "      <td>4.0609</td>\n",
       "      <td>4.2872</td>\n",
       "      <td>4.7013</td>\n",
       "      <td>5.2500</td>\n",
       "      <td>5.3330</td>\n",
       "      <td>5.3199</td>\n",
       "      <td>5.1968</td>\n",
       "      <td>5.2002</td>\n",
       "      <td>5.0329</td>\n",
       "      <td>4.8805</td>\n",
       "      <td>4.6292</td>\n",
       "      <td>4.2620</td>\n",
       "      <td>3.9952</td>\n",
       "      <td>3.7800</td>\n",
       "      <td>3.5602</td>\n",
       "      <td>3.1655</td>\n",
       "      <td>2.8107</td>\n",
       "      <td>1.9571</td>\n",
       "      <td>1.5551</td>\n",
       "      <td>1.3688</td>\n",
       "      <td>1.0739</td>\n",
       "      <td>0.8091</td>\n",
       "      <td>0.4341</td>\n",
       "      <td>0.4437</td>\n",
       "      <td>0.6014</td>\n",
       "      <td>0.7960</td>\n",
       "      <td>0.7229</td>\n",
       "      <td>0.6111</td>\n",
       "      <td>0.6339</td>\n",
       "      <td>0.5165</td>\n",
       "      <td>0.4421</td>\n",
       "      <td>0.5469</td>\n",
       "      <td>0.4770</td>\n",
       "      <td>0.5116</td>\n",
       "      <td>0.5054</td>\n",
       "      <td>0.4361</td>\n",
       "      <td>0.3629</td>\n",
       "      <td>0.2896</td>\n",
       "      <td>-1.5554</td>\n",
       "      <td>-1.6484</td>\n",
       "      <td>-1.8586</td>\n",
       "      <td>-1.7133</td>\n",
       "      <td>-2.0040</td>\n",
       "      <td>-2.0088</td>\n",
       "      <td>-2.3198</td>\n",
       "      <td>-2.8275</td>\n",
       "      <td>-3.2796</td>\n",
       "      <td>-3.1968</td>\n",
       "      <td>-2.7979</td>\n",
       "      <td>-1.7966</td>\n",
       "      <td>-1.5467</td>\n",
       "      <td>-1.2276</td>\n",
       "      <td>-1.5447</td>\n",
       "      <td>-1.4270</td>\n",
       "      <td>-0.9517</td>\n",
       "      <td>0.1808</td>\n",
       "      <td>0.7690</td>\n",
       "      <td>1.3059</td>\n",
       "      <td>1.5616</td>\n",
       "      <td>1.8174</td>\n",
       "      <td>2.0731</td>\n",
       "      <td>2.3289</td>\n",
       "      <td>3.9507</td>\n",
       "      <td>4.3389</td>\n",
       "      <td>4.1120</td>\n",
       "      <td>3.8918</td>\n",
       "      <td>3.0927</td>\n",
       "      <td>3.1421</td>\n",
       "      <td>3.6163</td>\n",
       "      <td>3.8024</td>\n",
       "      <td>4.3892</td>\n",
       "      <td>3.6137</td>\n",
       "      <td>2.8054</td>\n",
       "      <td>2.5584</td>\n",
       "      <td>2.4523</td>\n",
       "      <td>2.9283</td>\n",
       "      <td>1.7822</td>\n",
       "      <td>1.3252</td>\n",
       "      <td>0.9415</td>\n",
       "      <td>0.7269</td>\n",
       "      <td>0.4165</td>\n",
       "      <td>0.1236</td>\n",
       "      <td>0.3607</td>\n",
       "      <td>0.3586</td>\n",
       "      <td>0.3100</td>\n",
       "      <td>-0.4765</td>\n",
       "      <td>-1.3010</td>\n",
       "      <td>-1.7700</td>\n",
       "      <td>-2.1287</td>\n",
       "      <td>-2.6384</td>\n",
       "      <td>-3.0312</td>\n",
       "      <td>-3.3948</td>\n",
       "      <td>-3.7459</td>\n",
       "      <td>-4.3285</td>\n",
       "      <td>-4.6297</td>\n",
       "      <td>-5.1504</td>\n",
       "      <td>-5.4677</td>\n",
       "      <td>-5.8627</td>\n",
       "      <td>-6.3230</td>\n",
       "      <td>-6.3458</td>\n",
       "      <td>-5.7911</td>\n",
       "      <td>-5.3439</td>\n",
       "      <td>-4.6882</td>\n",
       "      <td>-4.2511</td>\n",
       "      <td>-3.4378</td>\n",
       "      <td>-2.0136</td>\n",
       "      <td>-1.3008</td>\n",
       "      <td>-0.4193</td>\n",
       "      <td>0.3740</td>\n",
       "      <td>1.7235</td>\n",
       "      <td>2.5822</td>\n",
       "      <td>2.7903</td>\n",
       "      <td>3.3684</td>\n",
       "      <td>3.4422</td>\n",
       "      <td>3.7659</td>\n",
       "      <td>4.2491</td>\n",
       "      <td>4.5524</td>\n",
       "      <td>5.2826</td>\n",
       "      <td>5.6143</td>\n",
       "      <td>5.5418</td>\n",
       "      <td>4.9826</td>\n",
       "      <td>4.6272</td>\n",
       "      <td>4.6935</td>\n",
       "      <td>4.0636</td>\n",
       "      <td>3.5430</td>\n",
       "      <td>3.2562</td>\n",
       "      <td>2.8626</td>\n",
       "      <td>2.7494</td>\n",
       "      <td>2.2100</td>\n",
       "      <td>1.8957</td>\n",
       "      <td>1.4708</td>\n",
       "      <td>0.9235</td>\n",
       "      <td>0.5996</td>\n",
       "      <td>0.2873</td>\n",
       "      <td>-0.1355</td>\n",
       "      <td>-0.6613</td>\n",
       "      <td>-1.4203</td>\n",
       "      <td>-1.6938</td>\n",
       "      <td>-2.0966</td>\n",
       "      <td>-2.2000</td>\n",
       "      <td>-1.7542</td>\n",
       "      <td>-1.3266</td>\n",
       "      <td>-0.7008</td>\n",
       "      <td>-0.5120</td>\n",
       "      <td>-0.3463</td>\n",
       "      <td>-0.1806</td>\n",
       "      <td>1.0138</td>\n",
       "      <td>3.2915</td>\n",
       "      <td>3.6000</td>\n",
       "      <td>3.6643</td>\n",
       "      <td>3.8936</td>\n",
       "      <td>4.0304</td>\n",
       "      <td>4.0852</td>\n",
       "      <td>4.0675</td>\n",
       "      <td>4.0499</td>\n",
       "      <td>4.0323</td>\n",
       "      <td>2.7296</td>\n",
       "      <td>2.3421</td>\n",
       "      <td>0.9728</td>\n",
       "      <td>1.0948</td>\n",
       "      <td>1.0091</td>\n",
       "      <td>1.0293</td>\n",
       "      <td>0.8503</td>\n",
       "      <td>0.9334</td>\n",
       "      <td>0.7900</td>\n",
       "      <td>0.7166</td>\n",
       "      <td>0.7765</td>\n",
       "      <td>0.8500</td>\n",
       "      <td>0.9188</td>\n",
       "      <td>0.9402</td>\n",
       "      <td>0.8167</td>\n",
       "      <td>0.6866</td>\n",
       "      <td>0.8907</td>\n",
       "      <td>0.8944</td>\n",
       "      <td>1.0848</td>\n",
       "      <td>1.1623</td>\n",
       "      <td>1.2800</td>\n",
       "      <td>1.2800</td>\n",
       "      <td>1.3749</td>\n",
       "      <td>1.4691</td>\n",
       "      <td>1.5160</td>\n",
       "      <td>1.4729</td>\n",
       "      <td>1.4045</td>\n",
       "      <td>1.4818</td>\n",
       "      <td>1.6157</td>\n",
       "      <td>1.5300</td>\n",
       "      <td>1.5724</td>\n",
       "      <td>1.4623</td>\n",
       "      <td>1.4909</td>\n",
       "      <td>1.4000</td>\n",
       "      <td>1.5039</td>\n",
       "      <td>1.5931</td>\n",
       "      <td>1.6630</td>\n",
       "      <td>1.6692</td>\n",
       "      <td>1.6500</td>\n",
       "      <td>1.7147</td>\n",
       "      <td>1.8026</td>\n",
       "      <td>1.8904</td>\n",
       "      <td>2.0446</td>\n",
       "      <td>1.8932</td>\n",
       "      <td>1.6422</td>\n",
       "      <td>1.6058</td>\n",
       "      <td>1.7640</td>\n",
       "      <td>1.6959</td>\n",
       "      <td>1.7299</td>\n",
       "      <td>2.3310</td>\n",
       "      <td>2.8008</td>\n",
       "      <td>2.7420</td>\n",
       "      <td>2.6460</td>\n",
       "      <td>2.0049</td>\n",
       "      <td>1.7847</td>\n",
       "      <td>1.5495</td>\n",
       "      <td>1.8912</td>\n",
       "      <td>1.6317</td>\n",
       "      <td>1.8278</td>\n",
       "      <td>1.9808</td>\n",
       "      <td>1.7385</td>\n",
       "      <td>1.5673</td>\n",
       "      <td>1.5275</td>\n",
       "      <td>1.4876</td>\n",
       "      <td>1.4478</td>\n",
       "      <td>1.4080</td>\n",
       "      <td>1.1735</td>\n",
       "      <td>0.8920</td>\n",
       "      <td>1.0676</td>\n",
       "      <td>1.8682</td>\n",
       "      <td>2.2830</td>\n",
       "      <td>2.4851</td>\n",
       "      <td>2.2437</td>\n",
       "      <td>1.8877</td>\n",
       "      <td>1.3406</td>\n",
       "      <td>1.7247</td>\n",
       "      <td>1.9852</td>\n",
       "      <td>1.9105</td>\n",
       "      <td>1.9459</td>\n",
       "      <td>1.7109</td>\n",
       "      <td>1.7175</td>\n",
       "      <td>1.6500</td>\n",
       "      <td>1.9885</td>\n",
       "      <td>2.1920</td>\n",
       "      <td>1.9111</td>\n",
       "      <td>2.1144</td>\n",
       "      <td>2.3171</td>\n",
       "      <td>1.9759</td>\n",
       "      <td>1.8032</td>\n",
       "      <td>1.8129</td>\n",
       "      <td>1.7797</td>\n",
       "      <td>2.1911</td>\n",
       "      <td>2.0800</td>\n",
       "      <td>1.8216</td>\n",
       "      <td>1.9406</td>\n",
       "      <td>1.9587</td>\n",
       "      <td>1.9863</td>\n",
       "      <td>2.0739</td>\n",
       "      <td>2.2132</td>\n",
       "      <td>2.4004</td>\n",
       "      <td>2.6297</td>\n",
       "      <td>2.5388</td>\n",
       "      <td>2.4400</td>\n",
       "      <td>2.7616</td>\n",
       "      <td>2.5027</td>\n",
       "      <td>2.6501</td>\n",
       "      <td>2.4952</td>\n",
       "      <td>2.0527</td>\n",
       "      <td>1.8753</td>\n",
       "      <td>1.7972</td>\n",
       "      <td>1.5393</td>\n",
       "      <td>1.3962</td>\n",
       "      <td>1.1700</td>\n",
       "      <td>1.1588</td>\n",
       "      <td>0.9989</td>\n",
       "      <td>1.0130</td>\n",
       "      <td>0.9624</td>\n",
       "      <td>0.8087</td>\n",
       "      <td>1.0805</td>\n",
       "      <td>1.2056</td>\n",
       "      <td>1.0942</td>\n",
       "      <td>0.9790</td>\n",
       "      <td>0.7939</td>\n",
       "      <td>0.7900</td>\n",
       "      <td>0.8192</td>\n",
       "      <td>0.9652</td>\n",
       "      <td>1.1535</td>\n",
       "      <td>1.1624</td>\n",
       "      <td>1.0180</td>\n",
       "      <td>1.2180</td>\n",
       "      <td>1.4025</td>\n",
       "      <td>1.4402</td>\n",
       "      <td>1.3449</td>\n",
       "      <td>1.2419</td>\n",
       "      <td>1.3704</td>\n",
       "      <td>1.5519</td>\n",
       "      <td>1.6500</td>\n",
       "      <td>1.7052</td>\n",
       "      <td>1.9233</td>\n",
       "      <td>1.8321</td>\n",
       "      <td>1.9443</td>\n",
       "      <td>1.9754</td>\n",
       "      <td>2.0487</td>\n",
       "      <td>2.1355</td>\n",
       "      <td>2.0540</td>\n",
       "      <td>2.0296</td>\n",
       "      <td>1.8457</td>\n",
       "      <td>1.8145</td>\n",
       "      <td>1.7982</td>\n",
       "      <td>1.7819</td>\n",
       "      <td>1.5667</td>\n",
       "      <td>1.3500</td>\n",
       "      <td>1.4000</td>\n",
       "      <td>1.3035</td>\n",
       "      <td>1.2200</td>\n",
       "      <td>1.1604</td>\n",
       "      <td>1.2152</td>\n",
       "      <td>1.1975</td>\n",
       "      <td>1.1799</td>\n",
       "      <td>1.1623</td>\n",
       "      <td>1.4000</td>\n",
       "      <td>1.4000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>idle</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0209</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.9704</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9730</td>\n",
       "      <td>0.9799</td>\n",
       "      <td>0.9716</td>\n",
       "      <td>0.9774</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9702</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9775</td>\n",
       "      <td>0.9712</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9720</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9769</td>\n",
       "      <td>0.9751</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9780</td>\n",
       "      <td>0.9745</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9751</td>\n",
       "      <td>0.9781</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9720</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9879</td>\n",
       "      <td>0.9804</td>\n",
       "      <td>0.9658</td>\n",
       "      <td>0.9775</td>\n",
       "      <td>0.9711</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9701</td>\n",
       "      <td>0.9700</td>\n",
       "      <td>0.9752</td>\n",
       "      <td>0.9721</td>\n",
       "      <td>0.9752</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9764</td>\n",
       "      <td>0.9700</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9724</td>\n",
       "      <td>0.9798</td>\n",
       "      <td>0.9726</td>\n",
       "      <td>0.9748</td>\n",
       "      <td>0.9778</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9769</td>\n",
       "      <td>0.9754</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9712</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9763</td>\n",
       "      <td>0.9702</td>\n",
       "      <td>0.9730</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9774</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9778</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9788</td>\n",
       "      <td>0.9751</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9703</td>\n",
       "      <td>0.9783</td>\n",
       "      <td>0.9754</td>\n",
       "      <td>0.9728</td>\n",
       "      <td>0.9791</td>\n",
       "      <td>0.9725</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9714</td>\n",
       "      <td>0.9701</td>\n",
       "      <td>0.9764</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9700</td>\n",
       "      <td>0.9700</td>\n",
       "      <td>0.9700</td>\n",
       "      <td>0.9700</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9750</td>\n",
       "      <td>0.9776</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9775</td>\n",
       "      <td>0.9750</td>\n",
       "      <td>0.9725</td>\n",
       "      <td>0.9799</td>\n",
       "      <td>0.9739</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9732</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9753</td>\n",
       "      <td>0.9737</td>\n",
       "      <td>0.9770</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9722</td>\n",
       "      <td>0.9796</td>\n",
       "      <td>0.9721</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1660</td>\n",
       "      <td>0.1620</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.160</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1700</td>\n",
       "      <td>0.1700</td>\n",
       "      <td>0.1700</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1673</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1672</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1678</td>\n",
       "      <td>0.1700</td>\n",
       "      <td>0.1700</td>\n",
       "      <td>0.1700</td>\n",
       "      <td>0.1700</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1662</td>\n",
       "      <td>0.1650</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1630</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>-0.0949</td>\n",
       "      <td>0.0229</td>\n",
       "      <td>0.1728</td>\n",
       "      <td>0.6118</td>\n",
       "      <td>0.5225</td>\n",
       "      <td>0.4458</td>\n",
       "      <td>0.4111</td>\n",
       "      <td>0.3371</td>\n",
       "      <td>0.4631</td>\n",
       "      <td>0.3615</td>\n",
       "      <td>0.3723</td>\n",
       "      <td>0.5287</td>\n",
       "      <td>0.4514</td>\n",
       "      <td>0.3936</td>\n",
       "      <td>0.2798</td>\n",
       "      <td>0.3182</td>\n",
       "      <td>0.4497</td>\n",
       "      <td>0.3160</td>\n",
       "      <td>0.3553</td>\n",
       "      <td>0.8199</td>\n",
       "      <td>0.6746</td>\n",
       "      <td>0.2400</td>\n",
       "      <td>0.2400</td>\n",
       "      <td>0.5628</td>\n",
       "      <td>0.6495</td>\n",
       "      <td>0.6241</td>\n",
       "      <td>0.4161</td>\n",
       "      <td>0.5553</td>\n",
       "      <td>0.4437</td>\n",
       "      <td>0.0466</td>\n",
       "      <td>0.3303</td>\n",
       "      <td>0.4850</td>\n",
       "      <td>0.3070</td>\n",
       "      <td>0.3620</td>\n",
       "      <td>0.3753</td>\n",
       "      <td>0.5661</td>\n",
       "      <td>0.3126</td>\n",
       "      <td>0.4225</td>\n",
       "      <td>0.4814</td>\n",
       "      <td>0.3012</td>\n",
       "      <td>0.3751</td>\n",
       "      <td>0.2926</td>\n",
       "      <td>0.1743</td>\n",
       "      <td>0.5773</td>\n",
       "      <td>0.3987</td>\n",
       "      <td>0.4154</td>\n",
       "      <td>0.3406</td>\n",
       "      <td>0.4171</td>\n",
       "      <td>0.3833</td>\n",
       "      <td>0.1765</td>\n",
       "      <td>0.9493</td>\n",
       "      <td>1.0036</td>\n",
       "      <td>0.1364</td>\n",
       "      <td>1.4277</td>\n",
       "      <td>0.0967</td>\n",
       "      <td>0.1755</td>\n",
       "      <td>0.6072</td>\n",
       "      <td>0.7559</td>\n",
       "      <td>0.6080</td>\n",
       "      <td>0.4600</td>\n",
       "      <td>0.5492</td>\n",
       "      <td>0.1119</td>\n",
       "      <td>0.4563</td>\n",
       "      <td>0.3649</td>\n",
       "      <td>0.4645</td>\n",
       "      <td>0.4785</td>\n",
       "      <td>0.3981</td>\n",
       "      <td>0.5202</td>\n",
       "      <td>0.4676</td>\n",
       "      <td>0.3803</td>\n",
       "      <td>0.3063</td>\n",
       "      <td>-0.0025</td>\n",
       "      <td>0.0663</td>\n",
       "      <td>0.3750</td>\n",
       "      <td>0.2095</td>\n",
       "      <td>0.7371</td>\n",
       "      <td>0.6006</td>\n",
       "      <td>0.1209</td>\n",
       "      <td>0.4953</td>\n",
       "      <td>0.6700</td>\n",
       "      <td>0.6604</td>\n",
       "      <td>0.1333</td>\n",
       "      <td>0.4209</td>\n",
       "      <td>0.3959</td>\n",
       "      <td>0.3709</td>\n",
       "      <td>0.6455</td>\n",
       "      <td>0.5839</td>\n",
       "      <td>0.5733</td>\n",
       "      <td>0.2021</td>\n",
       "      <td>0.2683</td>\n",
       "      <td>0.4652</td>\n",
       "      <td>0.4832</td>\n",
       "      <td>0.4589</td>\n",
       "      <td>0.5195</td>\n",
       "      <td>0.3075</td>\n",
       "      <td>0.0955</td>\n",
       "      <td>0.3271</td>\n",
       "      <td>0.3853</td>\n",
       "      <td>0.4905</td>\n",
       "      <td>0.7637</td>\n",
       "      <td>0.5818</td>\n",
       "      <td>0.2505</td>\n",
       "      <td>0.3732</td>\n",
       "      <td>0.5472</td>\n",
       "      <td>0.5769</td>\n",
       "      <td>0.3973</td>\n",
       "      <td>0.4944</td>\n",
       "      <td>0.3365</td>\n",
       "      <td>-0.2399</td>\n",
       "      <td>0.4790</td>\n",
       "      <td>0.0987</td>\n",
       "      <td>-0.0960</td>\n",
       "      <td>0.3435</td>\n",
       "      <td>0.7414</td>\n",
       "      <td>0.6892</td>\n",
       "      <td>0.2351</td>\n",
       "      <td>0.2558</td>\n",
       "      <td>0.3538</td>\n",
       "      <td>0.4517</td>\n",
       "      <td>0.5369</td>\n",
       "      <td>0.5085</td>\n",
       "      <td>0.4585</td>\n",
       "      <td>0.5772</td>\n",
       "      <td>0.6551</td>\n",
       "      <td>0.6148</td>\n",
       "      <td>0.4167</td>\n",
       "      <td>0.3401</td>\n",
       "      <td>0.4720</td>\n",
       "      <td>0.3976</td>\n",
       "      <td>0.4665</td>\n",
       "      <td>0.3547</td>\n",
       "      <td>0.3162</td>\n",
       "      <td>0.2400</td>\n",
       "      <td>0.2850</td>\n",
       "      <td>0.2447</td>\n",
       "      <td>0.3860</td>\n",
       "      <td>0.3200</td>\n",
       "      <td>0.5571</td>\n",
       "      <td>0.5958</td>\n",
       "      <td>0.5496</td>\n",
       "      <td>0.4013</td>\n",
       "      <td>0.1451</td>\n",
       "      <td>0.5500</td>\n",
       "      <td>0.5500</td>\n",
       "      <td>0.7247</td>\n",
       "      <td>0.4609</td>\n",
       "      <td>0.5739</td>\n",
       "      <td>0.6559</td>\n",
       "      <td>0.0989</td>\n",
       "      <td>0.1367</td>\n",
       "      <td>0.4329</td>\n",
       "      <td>0.5834</td>\n",
       "      <td>0.4584</td>\n",
       "      <td>0.5845</td>\n",
       "      <td>0.5099</td>\n",
       "      <td>0.5606</td>\n",
       "      <td>0.5199</td>\n",
       "      <td>0.2688</td>\n",
       "      <td>0.5500</td>\n",
       "      <td>0.5500</td>\n",
       "      <td>-0.6700</td>\n",
       "      <td>-0.6938</td>\n",
       "      <td>-0.7188</td>\n",
       "      <td>-0.6303</td>\n",
       "      <td>-0.7287</td>\n",
       "      <td>-0.7158</td>\n",
       "      <td>-0.7668</td>\n",
       "      <td>-0.8052</td>\n",
       "      <td>-0.8572</td>\n",
       "      <td>-0.8415</td>\n",
       "      <td>-0.8056</td>\n",
       "      <td>-0.8447</td>\n",
       "      <td>-0.8500</td>\n",
       "      <td>-0.7043</td>\n",
       "      <td>-0.8380</td>\n",
       "      <td>-0.9169</td>\n",
       "      <td>-0.8109</td>\n",
       "      <td>-0.8379</td>\n",
       "      <td>-0.7594</td>\n",
       "      <td>-0.7625</td>\n",
       "      <td>-0.7901</td>\n",
       "      <td>-0.7803</td>\n",
       "      <td>-0.7027</td>\n",
       "      <td>-0.9928</td>\n",
       "      <td>-0.9735</td>\n",
       "      <td>-0.8169</td>\n",
       "      <td>-0.7392</td>\n",
       "      <td>-0.8282</td>\n",
       "      <td>-0.7900</td>\n",
       "      <td>-0.8305</td>\n",
       "      <td>-0.7117</td>\n",
       "      <td>-0.8500</td>\n",
       "      <td>-0.8500</td>\n",
       "      <td>-0.7220</td>\n",
       "      <td>-0.6569</td>\n",
       "      <td>-0.6188</td>\n",
       "      <td>-0.6695</td>\n",
       "      <td>-0.7450</td>\n",
       "      <td>-0.8488</td>\n",
       "      <td>-0.9200</td>\n",
       "      <td>-0.9583</td>\n",
       "      <td>-0.6645</td>\n",
       "      <td>-0.6271</td>\n",
       "      <td>-0.9072</td>\n",
       "      <td>-0.9496</td>\n",
       "      <td>-0.8134</td>\n",
       "      <td>-0.5960</td>\n",
       "      <td>-0.7107</td>\n",
       "      <td>-0.6133</td>\n",
       "      <td>-0.7598</td>\n",
       "      <td>-0.6442</td>\n",
       "      <td>-0.6755</td>\n",
       "      <td>-0.8964</td>\n",
       "      <td>-0.3944</td>\n",
       "      <td>-0.8999</td>\n",
       "      <td>-0.9240</td>\n",
       "      <td>-0.7023</td>\n",
       "      <td>-0.5557</td>\n",
       "      <td>-0.5803</td>\n",
       "      <td>-0.6050</td>\n",
       "      <td>-0.6696</td>\n",
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       "      <td>-0.6071</td>\n",
       "      <td>-0.7763</td>\n",
       "      <td>-0.7514</td>\n",
       "      <td>-0.7357</td>\n",
       "      <td>-0.7759</td>\n",
       "      <td>-0.9932</td>\n",
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       "      <td>-0.8003</td>\n",
       "      <td>-0.8197</td>\n",
       "      <td>-0.7441</td>\n",
       "      <td>-0.9186</td>\n",
       "      <td>-0.6821</td>\n",
       "      <td>-0.9200</td>\n",
       "      <td>-0.9426</td>\n",
       "      <td>-0.8746</td>\n",
       "      <td>-0.9010</td>\n",
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       "      <td>-0.7900</td>\n",
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       "      <td>-0.5773</td>\n",
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       "      <td>-1.0399</td>\n",
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       "      <td>-0.9200</td>\n",
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       "      <td>-0.7583</td>\n",
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       "      <td>-0.6627</td>\n",
       "      <td>-0.5589</td>\n",
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       "      <td>-0.7300</td>\n",
       "      <td>-0.7300</td>\n",
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       "      <td>-0.6700</td>\n",
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       "      <td>-0.4055</td>\n",
       "      <td>-0.3488</td>\n",
       "      <td>-0.2862</td>\n",
       "      <td>-0.3653</td>\n",
       "      <td>-0.3155</td>\n",
       "      <td>-0.3536</td>\n",
       "      <td>-0.3316</td>\n",
       "      <td>-0.3700</td>\n",
       "      <td>-0.3700</td>\n",
       "      <td>-0.3700</td>\n",
       "      <td>-0.3700</td>\n",
       "      <td>-0.4786</td>\n",
       "      <td>-0.4524</td>\n",
       "      <td>-0.3695</td>\n",
       "      <td>-0.3823</td>\n",
       "      <td>-0.4083</td>\n",
       "      <td>-0.4900</td>\n",
       "      <td>-0.4900</td>\n",
       "      <td>-0.4109</td>\n",
       "      <td>-0.4300</td>\n",
       "      <td>-0.4809</td>\n",
       "      <td>-0.4439</td>\n",
       "      <td>-0.4834</td>\n",
       "      <td>-0.4900</td>\n",
       "      <td>-0.4504</td>\n",
       "      <td>-0.4300</td>\n",
       "      <td>-0.4540</td>\n",
       "      <td>-0.4560</td>\n",
       "      <td>-0.4543</td>\n",
       "      <td>-0.4804</td>\n",
       "      <td>-0.4552</td>\n",
       "      <td>-0.4753</td>\n",
       "      <td>-0.4564</td>\n",
       "      <td>-0.4374</td>\n",
       "      <td>-0.4300</td>\n",
       "      <td>-0.4923</td>\n",
       "      <td>-0.5672</td>\n",
       "      <td>-0.5409</td>\n",
       "      <td>-0.5150</td>\n",
       "      <td>-0.4900</td>\n",
       "      <td>-0.4411</td>\n",
       "      <td>-0.3901</td>\n",
       "      <td>-0.3846</td>\n",
       "      <td>-0.4624</td>\n",
       "      <td>-0.4182</td>\n",
       "      <td>-0.3700</td>\n",
       "      <td>-0.3700</td>\n",
       "      <td>-0.4307</td>\n",
       "      <td>-0.4300</td>\n",
       "      <td>-0.3341</td>\n",
       "      <td>-0.3700</td>\n",
       "      <td>-0.3700</td>\n",
       "      <td>-0.4300</td>\n",
       "      <td>-0.4300</td>\n",
       "      <td>-0.4270</td>\n",
       "      <td>-0.4900</td>\n",
       "      <td>-0.4900</td>\n",
       "      <td>-0.3587</td>\n",
       "      <td>-0.3173</td>\n",
       "      <td>-0.3700</td>\n",
       "      <td>-0.4084</td>\n",
       "      <td>-0.3100</td>\n",
       "      <td>-0.3100</td>\n",
       "      <td>-0.3662</td>\n",
       "      <td>-0.4083</td>\n",
       "      <td>-0.3990</td>\n",
       "      <td>-0.4566</td>\n",
       "      <td>-0.4595</td>\n",
       "      <td>-0.4517</td>\n",
       "      <td>-0.3200</td>\n",
       "      <td>-0.3453</td>\n",
       "      <td>-0.3700</td>\n",
       "      <td>-0.3700</td>\n",
       "      <td>-0.2857</td>\n",
       "      <td>-0.3498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>fall</td>\n",
       "      <td>0.2156</td>\n",
       "      <td>0.2289</td>\n",
       "      <td>0.2470</td>\n",
       "      <td>0.2472</td>\n",
       "      <td>0.1967</td>\n",
       "      <td>0.0283</td>\n",
       "      <td>0.0563</td>\n",
       "      <td>0.0814</td>\n",
       "      <td>0.0620</td>\n",
       "      <td>0.1771</td>\n",
       "      <td>0.1613</td>\n",
       "      <td>0.0235</td>\n",
       "      <td>0.0218</td>\n",
       "      <td>0.0078</td>\n",
       "      <td>0.0034</td>\n",
       "      <td>0.0169</td>\n",
       "      <td>0.0214</td>\n",
       "      <td>0.0283</td>\n",
       "      <td>0.0437</td>\n",
       "      <td>0.0502</td>\n",
       "      <td>-0.0134</td>\n",
       "      <td>0.0056</td>\n",
       "      <td>0.0552</td>\n",
       "      <td>0.0399</td>\n",
       "      <td>0.0432</td>\n",
       "      <td>0.0687</td>\n",
       "      <td>0.0796</td>\n",
       "      <td>0.0720</td>\n",
       "      <td>0.0776</td>\n",
       "      <td>0.0720</td>\n",
       "      <td>0.0487</td>\n",
       "      <td>0.0543</td>\n",
       "      <td>0.0198</td>\n",
       "      <td>0.0176</td>\n",
       "      <td>0.0490</td>\n",
       "      <td>0.0173</td>\n",
       "      <td>0.0052</td>\n",
       "      <td>0.0201</td>\n",
       "      <td>0.0210</td>\n",
       "      <td>0.0064</td>\n",
       "      <td>0.0165</td>\n",
       "      <td>-0.0171</td>\n",
       "      <td>-0.0162</td>\n",
       "      <td>-0.0025</td>\n",
       "      <td>0.0291</td>\n",
       "      <td>0.0128</td>\n",
       "      <td>-0.0287</td>\n",
       "      <td>-0.0071</td>\n",
       "      <td>-0.0119</td>\n",
       "      <td>-0.0172</td>\n",
       "      <td>0.0141</td>\n",
       "      <td>0.0249</td>\n",
       "      <td>0.0041</td>\n",
       "      <td>-0.0488</td>\n",
       "      <td>-0.0420</td>\n",
       "      <td>-0.0060</td>\n",
       "      <td>-0.0229</td>\n",
       "      <td>-0.0561</td>\n",
       "      <td>-0.0309</td>\n",
       "      <td>0.0345</td>\n",
       "      <td>0.0050</td>\n",
       "      <td>-0.0356</td>\n",
       "      <td>-0.0131</td>\n",
       "      <td>-0.1051</td>\n",
       "      <td>-0.0893</td>\n",
       "      <td>-0.0565</td>\n",
       "      <td>-0.0847</td>\n",
       "      <td>-0.0925</td>\n",
       "      <td>-0.0686</td>\n",
       "      <td>0.0037</td>\n",
       "      <td>0.0115</td>\n",
       "      <td>-0.0484</td>\n",
       "      <td>0.0347</td>\n",
       "      <td>-0.0341</td>\n",
       "      <td>0.0013</td>\n",
       "      <td>0.0466</td>\n",
       "      <td>0.0244</td>\n",
       "      <td>-0.0381</td>\n",
       "      <td>0.0527</td>\n",
       "      <td>0.0506</td>\n",
       "      <td>0.6145</td>\n",
       "      <td>0.0286</td>\n",
       "      <td>0.0969</td>\n",
       "      <td>0.0441</td>\n",
       "      <td>0.0471</td>\n",
       "      <td>0.1057</td>\n",
       "      <td>0.0193</td>\n",
       "      <td>0.0515</td>\n",
       "      <td>0.0593</td>\n",
       "      <td>-0.0302</td>\n",
       "      <td>0.0456</td>\n",
       "      <td>0.1648</td>\n",
       "      <td>0.0942</td>\n",
       "      <td>-0.0272</td>\n",
       "      <td>-0.0224</td>\n",
       "      <td>-0.0194</td>\n",
       "      <td>0.0540</td>\n",
       "      <td>0.0995</td>\n",
       "      <td>0.0669</td>\n",
       "      <td>0.0424</td>\n",
       "      <td>0.0610</td>\n",
       "      <td>0.0898</td>\n",
       "      <td>0.0497</td>\n",
       "      <td>0.0168</td>\n",
       "      <td>-0.0017</td>\n",
       "      <td>0.0061</td>\n",
       "      <td>0.0070</td>\n",
       "      <td>0.0442</td>\n",
       "      <td>-0.0326</td>\n",
       "      <td>0.0122</td>\n",
       "      <td>0.0070</td>\n",
       "      <td>0.0244</td>\n",
       "      <td>0.0049</td>\n",
       "      <td>0.0140</td>\n",
       "      <td>0.0384</td>\n",
       "      <td>0.0417</td>\n",
       "      <td>-0.0502</td>\n",
       "      <td>0.0301</td>\n",
       "      <td>-0.0318</td>\n",
       "      <td>-0.0479</td>\n",
       "      <td>-0.0580</td>\n",
       "      <td>-0.0114</td>\n",
       "      <td>-0.0569</td>\n",
       "      <td>-0.0728</td>\n",
       "      <td>-0.0383</td>\n",
       "      <td>-0.0115</td>\n",
       "      <td>-0.0223</td>\n",
       "      <td>0.0309</td>\n",
       "      <td>0.0664</td>\n",
       "      <td>0.0038</td>\n",
       "      <td>-0.0264</td>\n",
       "      <td>-0.0085</td>\n",
       "      <td>-0.0446</td>\n",
       "      <td>-0.0282</td>\n",
       "      <td>0.0069</td>\n",
       "      <td>0.0121</td>\n",
       "      <td>-0.0026</td>\n",
       "      <td>0.0235</td>\n",
       "      <td>-0.0083</td>\n",
       "      <td>-0.0232</td>\n",
       "      <td>-0.0335</td>\n",
       "      <td>-0.0265</td>\n",
       "      <td>-0.0126</td>\n",
       "      <td>-0.0029</td>\n",
       "      <td>0.0144</td>\n",
       "      <td>-0.0281</td>\n",
       "      <td>-0.0327</td>\n",
       "      <td>-0.0306</td>\n",
       "      <td>-0.0554</td>\n",
       "      <td>0.0671</td>\n",
       "      <td>0.0185</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>-0.0012</td>\n",
       "      <td>0.0256</td>\n",
       "      <td>0.0114</td>\n",
       "      <td>0.0065</td>\n",
       "      <td>0.0326</td>\n",
       "      <td>0.0232</td>\n",
       "      <td>0.0066</td>\n",
       "      <td>0.0204</td>\n",
       "      <td>1.0828</td>\n",
       "      <td>1.0693</td>\n",
       "      <td>1.0165</td>\n",
       "      <td>1.0265</td>\n",
       "      <td>1.0489</td>\n",
       "      <td>0.9818</td>\n",
       "      <td>1.0671</td>\n",
       "      <td>1.0416</td>\n",
       "      <td>0.9958</td>\n",
       "      <td>1.0889</td>\n",
       "      <td>0.8924</td>\n",
       "      <td>0.9150</td>\n",
       "      <td>1.0966</td>\n",
       "      <td>1.1236</td>\n",
       "      <td>1.0414</td>\n",
       "      <td>0.8953</td>\n",
       "      <td>1.1640</td>\n",
       "      <td>0.7625</td>\n",
       "      <td>0.8148</td>\n",
       "      <td>0.8046</td>\n",
       "      <td>0.6681</td>\n",
       "      <td>0.7961</td>\n",
       "      <td>0.8219</td>\n",
       "      <td>0.9257</td>\n",
       "      <td>0.7194</td>\n",
       "      <td>0.9129</td>\n",
       "      <td>0.7050</td>\n",
       "      <td>0.6752</td>\n",
       "      <td>0.8345</td>\n",
       "      <td>0.6821</td>\n",
       "      <td>0.6611</td>\n",
       "      <td>0.7067</td>\n",
       "      <td>0.6509</td>\n",
       "      <td>0.7194</td>\n",
       "      <td>0.5705</td>\n",
       "      <td>0.5793</td>\n",
       "      <td>0.4811</td>\n",
       "      <td>0.4958</td>\n",
       "      <td>0.5049</td>\n",
       "      <td>0.4332</td>\n",
       "      <td>0.4413</td>\n",
       "      <td>0.4230</td>\n",
       "      <td>0.3983</td>\n",
       "      <td>0.3409</td>\n",
       "      <td>0.3161</td>\n",
       "      <td>0.3046</td>\n",
       "      <td>0.2813</td>\n",
       "      <td>0.3452</td>\n",
       "      <td>0.2759</td>\n",
       "      <td>0.2117</td>\n",
       "      <td>0.1961</td>\n",
       "      <td>0.1936</td>\n",
       "      <td>0.2035</td>\n",
       "      <td>0.1359</td>\n",
       "      <td>0.1170</td>\n",
       "      <td>0.1025</td>\n",
       "      <td>0.1555</td>\n",
       "      <td>0.0309</td>\n",
       "      <td>0.2072</td>\n",
       "      <td>0.1048</td>\n",
       "      <td>-0.0452</td>\n",
       "      <td>0.1364</td>\n",
       "      <td>0.1555</td>\n",
       "      <td>0.0375</td>\n",
       "      <td>0.3831</td>\n",
       "      <td>-0.0203</td>\n",
       "      <td>0.1198</td>\n",
       "      <td>0.0438</td>\n",
       "      <td>0.1325</td>\n",
       "      <td>0.1399</td>\n",
       "      <td>-0.0194</td>\n",
       "      <td>0.1306</td>\n",
       "      <td>-0.0038</td>\n",
       "      <td>0.0125</td>\n",
       "      <td>0.0534</td>\n",
       "      <td>0.0162</td>\n",
       "      <td>-0.0321</td>\n",
       "      <td>-0.0001</td>\n",
       "      <td>-0.0513</td>\n",
       "      <td>-0.0977</td>\n",
       "      <td>-0.0145</td>\n",
       "      <td>-0.0782</td>\n",
       "      <td>-0.0521</td>\n",
       "      <td>-0.1078</td>\n",
       "      <td>-0.1423</td>\n",
       "      <td>-0.0788</td>\n",
       "      <td>0.4198</td>\n",
       "      <td>-0.1609</td>\n",
       "      <td>-0.1763</td>\n",
       "      <td>-0.1815</td>\n",
       "      <td>-0.1540</td>\n",
       "      <td>-0.1856</td>\n",
       "      <td>-0.1363</td>\n",
       "      <td>-0.2104</td>\n",
       "      <td>-0.2153</td>\n",
       "      <td>-0.2076</td>\n",
       "      <td>-0.1216</td>\n",
       "      <td>-0.1630</td>\n",
       "      <td>-0.1716</td>\n",
       "      <td>-0.0788</td>\n",
       "      <td>-0.0456</td>\n",
       "      <td>0.4324</td>\n",
       "      <td>-0.0227</td>\n",
       "      <td>-0.1335</td>\n",
       "      <td>0.0793</td>\n",
       "      <td>-0.0530</td>\n",
       "      <td>-0.0447</td>\n",
       "      <td>0.4723</td>\n",
       "      <td>0.0708</td>\n",
       "      <td>0.5332</td>\n",
       "      <td>0.0094</td>\n",
       "      <td>0.4865</td>\n",
       "      <td>-0.0865</td>\n",
       "      <td>-0.0567</td>\n",
       "      <td>-0.0962</td>\n",
       "      <td>-0.0940</td>\n",
       "      <td>-0.0802</td>\n",
       "      <td>-0.1241</td>\n",
       "      <td>-0.1409</td>\n",
       "      <td>-0.1242</td>\n",
       "      <td>-0.0560</td>\n",
       "      <td>0.3813</td>\n",
       "      <td>-0.0737</td>\n",
       "      <td>-0.0430</td>\n",
       "      <td>0.3942</td>\n",
       "      <td>0.4158</td>\n",
       "      <td>0.5981</td>\n",
       "      <td>-0.1314</td>\n",
       "      <td>-0.0357</td>\n",
       "      <td>-0.0531</td>\n",
       "      <td>-0.1016</td>\n",
       "      <td>-0.0754</td>\n",
       "      <td>-0.0769</td>\n",
       "      <td>-0.0847</td>\n",
       "      <td>0.3737</td>\n",
       "      <td>-0.0327</td>\n",
       "      <td>0.0787</td>\n",
       "      <td>-0.0225</td>\n",
       "      <td>0.2044</td>\n",
       "      <td>-0.0788</td>\n",
       "      <td>0.0118</td>\n",
       "      <td>-0.0896</td>\n",
       "      <td>-0.0978</td>\n",
       "      <td>-0.1168</td>\n",
       "      <td>-0.1315</td>\n",
       "      <td>-0.0864</td>\n",
       "      <td>-0.0513</td>\n",
       "      <td>-0.0664</td>\n",
       "      <td>-0.0243</td>\n",
       "      <td>0.0222</td>\n",
       "      <td>0.3911</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.0618</td>\n",
       "      <td>-0.0002</td>\n",
       "      <td>-0.0089</td>\n",
       "      <td>-0.0365</td>\n",
       "      <td>-0.0268</td>\n",
       "      <td>-0.0406</td>\n",
       "      <td>-0.0347</td>\n",
       "      <td>-0.0546</td>\n",
       "      <td>0.2399</td>\n",
       "      <td>0.2544</td>\n",
       "      <td>0.2423</td>\n",
       "      <td>0.1780</td>\n",
       "      <td>0.1808</td>\n",
       "      <td>0.1865</td>\n",
       "      <td>0.1927</td>\n",
       "      <td>0.1889</td>\n",
       "      <td>0.1766</td>\n",
       "      <td>0.1866</td>\n",
       "      <td>0.2138</td>\n",
       "      <td>0.1859</td>\n",
       "      <td>0.1954</td>\n",
       "      <td>0.1589</td>\n",
       "      <td>0.2671</td>\n",
       "      <td>0.2790</td>\n",
       "      <td>0.2454</td>\n",
       "      <td>0.2298</td>\n",
       "      <td>0.1929</td>\n",
       "      <td>0.1843</td>\n",
       "      <td>0.1364</td>\n",
       "      <td>0.1242</td>\n",
       "      <td>0.0887</td>\n",
       "      <td>0.0592</td>\n",
       "      <td>0.0383</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>-0.0319</td>\n",
       "      <td>-0.0299</td>\n",
       "      <td>-0.0192</td>\n",
       "      <td>-0.0211</td>\n",
       "      <td>0.0130</td>\n",
       "      <td>-0.0068</td>\n",
       "      <td>-0.0341</td>\n",
       "      <td>-0.0405</td>\n",
       "      <td>-0.0673</td>\n",
       "      <td>-0.0271</td>\n",
       "      <td>-0.0978</td>\n",
       "      <td>-0.0292</td>\n",
       "      <td>-0.0311</td>\n",
       "      <td>-0.0271</td>\n",
       "      <td>-0.0575</td>\n",
       "      <td>-0.0636</td>\n",
       "      <td>-0.0449</td>\n",
       "      <td>-0.0373</td>\n",
       "      <td>-0.0506</td>\n",
       "      <td>-0.0774</td>\n",
       "      <td>-0.0237</td>\n",
       "      <td>-0.1231</td>\n",
       "      <td>0.0873</td>\n",
       "      <td>-0.1648</td>\n",
       "      <td>-0.1343</td>\n",
       "      <td>-0.109</td>\n",
       "      <td>-0.0980</td>\n",
       "      <td>-0.1607</td>\n",
       "      <td>-0.1321</td>\n",
       "      <td>0.0998</td>\n",
       "      <td>-0.1064</td>\n",
       "      <td>-0.1713</td>\n",
       "      <td>-0.0364</td>\n",
       "      <td>-0.1161</td>\n",
       "      <td>-0.2587</td>\n",
       "      <td>-0.0614</td>\n",
       "      <td>0.6771</td>\n",
       "      <td>0.3270</td>\n",
       "      <td>0.0844</td>\n",
       "      <td>0.0729</td>\n",
       "      <td>0.1046</td>\n",
       "      <td>-0.1348</td>\n",
       "      <td>0.6196</td>\n",
       "      <td>-0.1157</td>\n",
       "      <td>-0.0975</td>\n",
       "      <td>0.2007</td>\n",
       "      <td>-0.0997</td>\n",
       "      <td>-0.0472</td>\n",
       "      <td>0.0391</td>\n",
       "      <td>-0.0361</td>\n",
       "      <td>0.0704</td>\n",
       "      <td>-0.0281</td>\n",
       "      <td>0.0171</td>\n",
       "      <td>-0.0828</td>\n",
       "      <td>-0.0178</td>\n",
       "      <td>-0.1057</td>\n",
       "      <td>0.6398</td>\n",
       "      <td>-0.1180</td>\n",
       "      <td>-0.1367</td>\n",
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       "      <td>2.8022</td>\n",
       "      <td>4.8807</td>\n",
       "      <td>5.7347</td>\n",
       "      <td>6.0547</td>\n",
       "      <td>8.5410</td>\n",
       "      <td>7.8901</td>\n",
       "      <td>6.1875</td>\n",
       "      <td>6.5687</td>\n",
       "      <td>8.1220</td>\n",
       "      <td>7.1984</td>\n",
       "      <td>7.7416</td>\n",
       "      <td>8.0843</td>\n",
       "      <td>5.7726</td>\n",
       "      <td>5.9869</td>\n",
       "      <td>7.5200</td>\n",
       "      <td>7.4141</td>\n",
       "      <td>7.4746</td>\n",
       "      <td>8.2821</td>\n",
       "      <td>6.3994</td>\n",
       "      <td>6.8658</td>\n",
       "      <td>6.4217</td>\n",
       "      <td>5.2919</td>\n",
       "      <td>3.8964</td>\n",
       "      <td>3.7707</td>\n",
       "      <td>2.9906</td>\n",
       "      <td>3.1459</td>\n",
       "      <td>3.3826</td>\n",
       "      <td>3.2412</td>\n",
       "      <td>16.2055</td>\n",
       "      <td>12.2176</td>\n",
       "      <td>3.8511</td>\n",
       "      <td>4.2284</td>\n",
       "      <td>3.3867</td>\n",
       "      <td>2.9340</td>\n",
       "      <td>2.7745</td>\n",
       "      <td>2.4633</td>\n",
       "      <td>1.7815</td>\n",
       "      <td>1.5852</td>\n",
       "      <td>1.4074</td>\n",
       "      <td>1.6814</td>\n",
       "      <td>1.6661</td>\n",
       "      <td>2.1715</td>\n",
       "      <td>2.3800</td>\n",
       "      <td>3.0027</td>\n",
       "      <td>3.6089</td>\n",
       "      <td>3.4393</td>\n",
       "      <td>3.5590</td>\n",
       "      <td>3.8304</td>\n",
       "      <td>3.6960</td>\n",
       "      <td>3.7302</td>\n",
       "      <td>3.9760</td>\n",
       "      <td>5.1283</td>\n",
       "      <td>4.6889</td>\n",
       "      <td>4.4421</td>\n",
       "      <td>4.8146</td>\n",
       "      <td>5.1755</td>\n",
       "      <td>5.8124</td>\n",
       "      <td>5.6593</td>\n",
       "      <td>5.7408</td>\n",
       "      <td>5.9904</td>\n",
       "      <td>6.5709</td>\n",
       "      <td>7.0393</td>\n",
       "      <td>7.0628</td>\n",
       "      <td>6.5418</td>\n",
       "      <td>4.2421</td>\n",
       "      <td>2.3539</td>\n",
       "      <td>2.2893</td>\n",
       "      <td>1.2885</td>\n",
       "      <td>1.2177</td>\n",
       "      <td>1.3184</td>\n",
       "      <td>1.1846</td>\n",
       "      <td>0.4448</td>\n",
       "      <td>4.8701</td>\n",
       "      <td>1.2830</td>\n",
       "      <td>0.5287</td>\n",
       "      <td>0.8010</td>\n",
       "      <td>0.8872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>idle</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>-1.0100</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.120</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>1.8509</td>\n",
       "      <td>1.7100</td>\n",
       "      <td>1.7100</td>\n",
       "      <td>1.7728</td>\n",
       "      <td>1.8224</td>\n",
       "      <td>1.8300</td>\n",
       "      <td>1.6686</td>\n",
       "      <td>1.7100</td>\n",
       "      <td>1.7334</td>\n",
       "      <td>1.8176</td>\n",
       "      <td>1.7791</td>\n",
       "      <td>1.7730</td>\n",
       "      <td>1.8480</td>\n",
       "      <td>1.9314</td>\n",
       "      <td>1.8900</td>\n",
       "      <td>1.7870</td>\n",
       "      <td>1.8129</td>\n",
       "      <td>1.8555</td>\n",
       "      <td>1.8012</td>\n",
       "      <td>1.7700</td>\n",
       "      <td>1.8389</td>\n",
       "      <td>1.8696</td>\n",
       "      <td>1.7793</td>\n",
       "      <td>1.6001</td>\n",
       "      <td>1.7443</td>\n",
       "      <td>1.8900</td>\n",
       "      <td>1.8696</td>\n",
       "      <td>1.8373</td>\n",
       "      <td>1.9310</td>\n",
       "      <td>1.8092</td>\n",
       "      <td>1.7797</td>\n",
       "      <td>1.8870</td>\n",
       "      <td>1.8900</td>\n",
       "      <td>1.8900</td>\n",
       "      <td>1.8376</td>\n",
       "      <td>1.9329</td>\n",
       "      <td>1.9500</td>\n",
       "      <td>1.9004</td>\n",
       "      <td>1.8117</td>\n",
       "      <td>1.9936</td>\n",
       "      <td>1.8068</td>\n",
       "      <td>1.7700</td>\n",
       "      <td>1.7941</td>\n",
       "      <td>1.7175</td>\n",
       "      <td>1.7548</td>\n",
       "      <td>1.7185</td>\n",
       "      <td>1.7100</td>\n",
       "      <td>1.7100</td>\n",
       "      <td>1.7100</td>\n",
       "      <td>1.7760</td>\n",
       "      <td>1.8412</td>\n",
       "      <td>1.7760</td>\n",
       "      <td>1.8722</td>\n",
       "      <td>1.8404</td>\n",
       "      <td>1.8773</td>\n",
       "      <td>1.8081</td>\n",
       "      <td>1.7795</td>\n",
       "      <td>1.8300</td>\n",
       "      <td>1.8676</td>\n",
       "      <td>1.8900</td>\n",
       "      <td>1.8855</td>\n",
       "      <td>1.8837</td>\n",
       "      <td>1.9196</td>\n",
       "      <td>1.8645</td>\n",
       "      <td>1.9357</td>\n",
       "      <td>1.8937</td>\n",
       "      <td>1.7499</td>\n",
       "      <td>1.8056</td>\n",
       "      <td>1.8749</td>\n",
       "      <td>1.8022</td>\n",
       "      <td>1.7256</td>\n",
       "      <td>1.7739</td>\n",
       "      <td>1.8070</td>\n",
       "      <td>1.8035</td>\n",
       "      <td>1.8300</td>\n",
       "      <td>1.8789</td>\n",
       "      <td>1.8900</td>\n",
       "      <td>1.8900</td>\n",
       "      <td>1.5622</td>\n",
       "      <td>1.5642</td>\n",
       "      <td>1.6529</td>\n",
       "      <td>1.7417</td>\n",
       "      <td>1.8517</td>\n",
       "      <td>1.8487</td>\n",
       "      <td>1.7246</td>\n",
       "      <td>1.8300</td>\n",
       "      <td>1.5812</td>\n",
       "      <td>1.8256</td>\n",
       "      <td>1.7752</td>\n",
       "      <td>1.7755</td>\n",
       "      <td>1.7100</td>\n",
       "      <td>1.7582</td>\n",
       "      <td>1.7415</td>\n",
       "      <td>1.8900</td>\n",
       "      <td>1.8900</td>\n",
       "      <td>1.8300</td>\n",
       "      <td>1.7873</td>\n",
       "      <td>1.7759</td>\n",
       "      <td>1.8300</td>\n",
       "      <td>1.8300</td>\n",
       "      <td>1.9500</td>\n",
       "      <td>1.9063</td>\n",
       "      <td>1.8934</td>\n",
       "      <td>1.9372</td>\n",
       "      <td>1.9183</td>\n",
       "      <td>1.8994</td>\n",
       "      <td>1.8632</td>\n",
       "      <td>1.8300</td>\n",
       "      <td>2.0863</td>\n",
       "      <td>1.8670</td>\n",
       "      <td>1.8621</td>\n",
       "      <td>1.9387</td>\n",
       "      <td>1.8897</td>\n",
       "      <td>1.8054</td>\n",
       "      <td>1.7700</td>\n",
       "      <td>1.7700</td>\n",
       "      <td>1.7882</td>\n",
       "      <td>1.8293</td>\n",
       "      <td>1.6763</td>\n",
       "      <td>1.7804</td>\n",
       "      <td>1.8898</td>\n",
       "      <td>1.6572</td>\n",
       "      <td>1.7860</td>\n",
       "      <td>1.8900</td>\n",
       "      <td>1.7102</td>\n",
       "      <td>1.7935</td>\n",
       "      <td>1.8726</td>\n",
       "      <td>1.9501</td>\n",
       "      <td>1.9668</td>\n",
       "      <td>1.7948</td>\n",
       "      <td>1.8764</td>\n",
       "      <td>1.8390</td>\n",
       "      <td>1.8718</td>\n",
       "      <td>1.7700</td>\n",
       "      <td>1.7940</td>\n",
       "      <td>1.8300</td>\n",
       "      <td>1.8300</td>\n",
       "      <td>1.7716</td>\n",
       "      <td>1.7228</td>\n",
       "      <td>1.8885</td>\n",
       "      <td>1.9364</td>\n",
       "      <td>1.8765</td>\n",
       "      <td>1.8517</td>\n",
       "      <td>1.8244</td>\n",
       "      <td>1.7100</td>\n",
       "      <td>1.8499</td>\n",
       "      <td>1.8017</td>\n",
       "      <td>1.7314</td>\n",
       "      <td>1.8255</td>\n",
       "      <td>1.8989</td>\n",
       "      <td>1.9376</td>\n",
       "      <td>1.8476</td>\n",
       "      <td>1.9034</td>\n",
       "      <td>1.8140</td>\n",
       "      <td>1.7469</td>\n",
       "      <td>1.7754</td>\n",
       "      <td>1.8364</td>\n",
       "      <td>1.8360</td>\n",
       "      <td>1.7447</td>\n",
       "      <td>1.8717</td>\n",
       "      <td>0.9695</td>\n",
       "      <td>1.0035</td>\n",
       "      <td>0.9287</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.8664</td>\n",
       "      <td>0.7528</td>\n",
       "      <td>0.8578</td>\n",
       "      <td>0.8654</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9676</td>\n",
       "      <td>0.9291</td>\n",
       "      <td>0.8566</td>\n",
       "      <td>0.9424</td>\n",
       "      <td>0.7486</td>\n",
       "      <td>0.7900</td>\n",
       "      <td>0.7385</td>\n",
       "      <td>0.7857</td>\n",
       "      <td>0.8139</td>\n",
       "      <td>0.8577</td>\n",
       "      <td>0.9090</td>\n",
       "      <td>0.9200</td>\n",
       "      <td>0.8962</td>\n",
       "      <td>0.9049</td>\n",
       "      <td>0.8610</td>\n",
       "      <td>1.0129</td>\n",
       "      <td>0.9200</td>\n",
       "      <td>0.9404</td>\n",
       "      <td>0.9727</td>\n",
       "      <td>1.0210</td>\n",
       "      <td>1.0608</td>\n",
       "      <td>1.0207</td>\n",
       "      <td>0.9770</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>1.0400</td>\n",
       "      <td>0.9542</td>\n",
       "      <td>0.8559</td>\n",
       "      <td>0.9200</td>\n",
       "      <td>0.9617</td>\n",
       "      <td>0.9745</td>\n",
       "      <td>0.9200</td>\n",
       "      <td>0.9522</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.8588</td>\n",
       "      <td>0.9200</td>\n",
       "      <td>0.9200</td>\n",
       "      <td>0.8626</td>\n",
       "      <td>0.8500</td>\n",
       "      <td>0.8500</td>\n",
       "      <td>0.9770</td>\n",
       "      <td>0.9444</td>\n",
       "      <td>1.0280</td>\n",
       "      <td>0.8708</td>\n",
       "      <td>0.9574</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9419</td>\n",
       "      <td>1.0810</td>\n",
       "      <td>0.9571</td>\n",
       "      <td>1.0327</td>\n",
       "      <td>1.0526</td>\n",
       "      <td>1.0257</td>\n",
       "      <td>0.8814</td>\n",
       "      <td>0.8870</td>\n",
       "      <td>0.8274</td>\n",
       "      <td>0.9117</td>\n",
       "      <td>0.9237</td>\n",
       "      <td>0.8533</td>\n",
       "      <td>0.9132</td>\n",
       "      <td>0.9200</td>\n",
       "      <td>0.9478</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9761</td>\n",
       "      <td>0.8931</td>\n",
       "      <td>0.8500</td>\n",
       "      <td>0.9072</td>\n",
       "      <td>0.8629</td>\n",
       "      <td>0.8500</td>\n",
       "      <td>1.0475</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.8758</td>\n",
       "      <td>0.8185</td>\n",
       "      <td>0.8129</td>\n",
       "      <td>0.8923</td>\n",
       "      <td>0.9352</td>\n",
       "      <td>0.8500</td>\n",
       "      <td>0.9510</td>\n",
       "      <td>0.8620</td>\n",
       "      <td>0.9106</td>\n",
       "      <td>0.8013</td>\n",
       "      <td>0.9473</td>\n",
       "      <td>0.9277</td>\n",
       "      <td>0.9200</td>\n",
       "      <td>0.9078</td>\n",
       "      <td>0.8618</td>\n",
       "      <td>0.8957</td>\n",
       "      <td>1.0303</td>\n",
       "      <td>1.0014</td>\n",
       "      <td>1.0070</td>\n",
       "      <td>1.0244</td>\n",
       "      <td>0.8610</td>\n",
       "      <td>0.9314</td>\n",
       "      <td>0.9491</td>\n",
       "      <td>0.8587</td>\n",
       "      <td>0.9328</td>\n",
       "      <td>0.9517</td>\n",
       "      <td>0.9706</td>\n",
       "      <td>0.9532</td>\n",
       "      <td>0.9868</td>\n",
       "      <td>0.9904</td>\n",
       "      <td>0.9570</td>\n",
       "      <td>0.9842</td>\n",
       "      <td>1.0400</td>\n",
       "      <td>0.9201</td>\n",
       "      <td>0.9623</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.8500</td>\n",
       "      <td>0.8318</td>\n",
       "      <td>0.7907</td>\n",
       "      <td>0.7974</td>\n",
       "      <td>0.8575</td>\n",
       "      <td>0.9365</td>\n",
       "      <td>0.9224</td>\n",
       "      <td>0.9653</td>\n",
       "      <td>0.8255</td>\n",
       "      <td>0.8500</td>\n",
       "      <td>0.8500</td>\n",
       "      <td>0.8500</td>\n",
       "      <td>0.9198</td>\n",
       "      <td>0.8668</td>\n",
       "      <td>0.9552</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.8606</td>\n",
       "      <td>0.9239</td>\n",
       "      <td>1.0040</td>\n",
       "      <td>1.1057</td>\n",
       "      <td>1.0602</td>\n",
       "      <td>1.0108</td>\n",
       "      <td>0.9200</td>\n",
       "      <td>1.0371</td>\n",
       "      <td>1.0400</td>\n",
       "      <td>1.0131</td>\n",
       "      <td>0.8947</td>\n",
       "      <td>0.8755</td>\n",
       "      <td>0.9200</td>\n",
       "      <td>0.8334</td>\n",
       "      <td>0.9833</td>\n",
       "      <td>1.0893</td>\n",
       "      <td>0.9199</td>\n",
       "      <td>0.8500</td>\n",
       "      <td>0.8500</td>\n",
       "      <td>0.7988</td>\n",
       "      <td>0.8267</td>\n",
       "      <td>0.8897</td>\n",
       "      <td>0.9200</td>\n",
       "      <td>0.9714</td>\n",
       "      <td>0.8749</td>\n",
       "      <td>0.8290</td>\n",
       "      <td>0.9547</td>\n",
       "      <td>1.0817</td>\n",
       "      <td>1.5548</td>\n",
       "      <td>1.5718</td>\n",
       "      <td>1.5343</td>\n",
       "      <td>1.4088</td>\n",
       "      <td>1.3476</td>\n",
       "      <td>1.5425</td>\n",
       "      <td>1.4622</td>\n",
       "      <td>1.4000</td>\n",
       "      <td>1.4254</td>\n",
       "      <td>1.5030</td>\n",
       "      <td>1.4197</td>\n",
       "      <td>1.5930</td>\n",
       "      <td>1.6410</td>\n",
       "      <td>1.5497</td>\n",
       "      <td>1.4199</td>\n",
       "      <td>1.3400</td>\n",
       "      <td>1.3614</td>\n",
       "      <td>1.4345</td>\n",
       "      <td>1.4936</td>\n",
       "      <td>1.5300</td>\n",
       "      <td>1.4000</td>\n",
       "      <td>1.4442</td>\n",
       "      <td>1.5300</td>\n",
       "      <td>1.4659</td>\n",
       "      <td>1.5200</td>\n",
       "      <td>1.5732</td>\n",
       "      <td>1.5504</td>\n",
       "      <td>1.5827</td>\n",
       "      <td>1.5078</td>\n",
       "      <td>1.5183</td>\n",
       "      <td>1.5552</td>\n",
       "      <td>1.5300</td>\n",
       "      <td>1.5300</td>\n",
       "      <td>1.5300</td>\n",
       "      <td>1.5376</td>\n",
       "      <td>1.5471</td>\n",
       "      <td>1.4659</td>\n",
       "      <td>1.4958</td>\n",
       "      <td>1.5483</td>\n",
       "      <td>1.5300</td>\n",
       "      <td>1.5029</td>\n",
       "      <td>1.5619</td>\n",
       "      <td>1.6017</td>\n",
       "      <td>1.4763</td>\n",
       "      <td>1.5420</td>\n",
       "      <td>1.4268</td>\n",
       "      <td>1.3892</td>\n",
       "      <td>1.4522</td>\n",
       "      <td>1.5138</td>\n",
       "      <td>1.5300</td>\n",
       "      <td>1.5300</td>\n",
       "      <td>1.5770</td>\n",
       "      <td>1.5092</td>\n",
       "      <td>1.4722</td>\n",
       "      <td>1.4600</td>\n",
       "      <td>1.6442</td>\n",
       "      <td>1.5900</td>\n",
       "      <td>1.5404</td>\n",
       "      <td>1.5414</td>\n",
       "      <td>1.5426</td>\n",
       "      <td>1.5300</td>\n",
       "      <td>1.5300</td>\n",
       "      <td>1.5452</td>\n",
       "      <td>1.5728</td>\n",
       "      <td>1.5300</td>\n",
       "      <td>1.5900</td>\n",
       "      <td>1.5500</td>\n",
       "      <td>1.4457</td>\n",
       "      <td>1.5123</td>\n",
       "      <td>1.4322</td>\n",
       "      <td>1.4000</td>\n",
       "      <td>1.4600</td>\n",
       "      <td>1.4370</td>\n",
       "      <td>1.4000</td>\n",
       "      <td>1.4000</td>\n",
       "      <td>1.4000</td>\n",
       "      <td>1.3426</td>\n",
       "      <td>1.4901</td>\n",
       "      <td>1.4026</td>\n",
       "      <td>1.3881</td>\n",
       "      <td>1.4682</td>\n",
       "      <td>1.5406</td>\n",
       "      <td>1.5772</td>\n",
       "      <td>1.3607</td>\n",
       "      <td>1.3546</td>\n",
       "      <td>1.4917</td>\n",
       "      <td>1.4822</td>\n",
       "      <td>1.5300</td>\n",
       "      <td>1.5187</td>\n",
       "      <td>1.4863</td>\n",
       "      <td>1.6423</td>\n",
       "      <td>1.5536</td>\n",
       "      <td>1.5795</td>\n",
       "      <td>1.5081</td>\n",
       "      <td>1.4451</td>\n",
       "      <td>1.5187</td>\n",
       "      <td>1.4849</td>\n",
       "      <td>1.5630</td>\n",
       "      <td>1.5900</td>\n",
       "      <td>1.5335</td>\n",
       "      <td>1.4837</td>\n",
       "      <td>1.5754</td>\n",
       "      <td>1.3717</td>\n",
       "      <td>1.4276</td>\n",
       "      <td>1.4686</td>\n",
       "      <td>1.5096</td>\n",
       "      <td>1.4987</td>\n",
       "      <td>1.5657</td>\n",
       "      <td>1.6004</td>\n",
       "      <td>1.4000</td>\n",
       "      <td>1.4321</td>\n",
       "      <td>1.5168</td>\n",
       "      <td>1.4005</td>\n",
       "      <td>1.5340</td>\n",
       "      <td>1.4757</td>\n",
       "      <td>1.5300</td>\n",
       "      <td>1.5088</td>\n",
       "      <td>1.4608</td>\n",
       "      <td>1.4570</td>\n",
       "      <td>1.5225</td>\n",
       "      <td>1.4435</td>\n",
       "      <td>1.4652</td>\n",
       "      <td>1.5582</td>\n",
       "      <td>1.3755</td>\n",
       "      <td>1.4600</td>\n",
       "      <td>1.4600</td>\n",
       "      <td>1.4600</td>\n",
       "      <td>1.5301</td>\n",
       "      <td>1.5756</td>\n",
       "      <td>1.4889</td>\n",
       "      <td>1.5220</td>\n",
       "      <td>1.5300</td>\n",
       "      <td>1.4091</td>\n",
       "      <td>1.4600</td>\n",
       "      <td>1.4360</td>\n",
       "      <td>1.5040</td>\n",
       "      <td>1.4819</td>\n",
       "      <td>1.5130</td>\n",
       "      <td>1.4987</td>\n",
       "      <td>1.5300</td>\n",
       "      <td>1.5604</td>\n",
       "      <td>1.5027</td>\n",
       "      <td>1.6283</td>\n",
       "      <td>1.5207</td>\n",
       "      <td>1.4000</td>\n",
       "      <td>1.5066</td>\n",
       "      <td>1.4970</td>\n",
       "      <td>1.5793</td>\n",
       "      <td>1.4600</td>\n",
       "      <td>1.5900</td>\n",
       "      <td>1.5900</td>\n",
       "      <td>1.4279</td>\n",
       "      <td>1.5162</td>\n",
       "      <td>1.5163</td>\n",
       "      <td>1.5031</td>\n",
       "      <td>1.5241</td>\n",
       "      <td>1.4581</td>\n",
       "      <td>1.4570</td>\n",
       "      <td>1.5149</td>\n",
       "      <td>1.4600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>idle</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9728</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9795</td>\n",
       "      <td>0.9712</td>\n",
       "      <td>0.9774</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9796</td>\n",
       "      <td>0.9722</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1425</td>\n",
       "      <td>0.1453</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1449</td>\n",
       "      <td>0.1481</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1428</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1402</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1444</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1417</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1492</td>\n",
       "      <td>0.140</td>\n",
       "      <td>0.1454</td>\n",
       "      <td>0.1428</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1425</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1474</td>\n",
       "      <td>0.1451</td>\n",
       "      <td>0.1424</td>\n",
       "      <td>0.1492</td>\n",
       "      <td>0.1440</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1402</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1448</td>\n",
       "      <td>0.1426</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1496</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1452</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1475</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1478</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1453</td>\n",
       "      <td>0.1472</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1488</td>\n",
       "      <td>0.1425</td>\n",
       "      <td>0.1471</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1412</td>\n",
       "      <td>0.1474</td>\n",
       "      <td>0.1463</td>\n",
       "      <td>0.1449</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1480</td>\n",
       "      <td>0.1452</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1406</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1478</td>\n",
       "      <td>0.1455</td>\n",
       "      <td>0.1429</td>\n",
       "      <td>0.1499</td>\n",
       "      <td>0.1421</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1405</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1478</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1496</td>\n",
       "      <td>0.1422</td>\n",
       "      <td>0.4905</td>\n",
       "      <td>0.4324</td>\n",
       "      <td>0.5495</td>\n",
       "      <td>0.2793</td>\n",
       "      <td>0.2286</td>\n",
       "      <td>0.3497</td>\n",
       "      <td>0.3769</td>\n",
       "      <td>0.5152</td>\n",
       "      <td>0.4179</td>\n",
       "      <td>0.5121</td>\n",
       "      <td>0.3937</td>\n",
       "      <td>0.3872</td>\n",
       "      <td>0.5049</td>\n",
       "      <td>0.4209</td>\n",
       "      <td>0.3058</td>\n",
       "      <td>0.2510</td>\n",
       "      <td>0.4164</td>\n",
       "      <td>0.6858</td>\n",
       "      <td>0.4335</td>\n",
       "      <td>0.4300</td>\n",
       "      <td>0.4300</td>\n",
       "      <td>0.4101</td>\n",
       "      <td>0.3708</td>\n",
       "      <td>0.5395</td>\n",
       "      <td>0.4196</td>\n",
       "      <td>0.5732</td>\n",
       "      <td>0.6276</td>\n",
       "      <td>0.3737</td>\n",
       "      <td>0.4000</td>\n",
       "      <td>0.4263</td>\n",
       "      <td>0.4874</td>\n",
       "      <td>0.3353</td>\n",
       "      <td>0.4530</td>\n",
       "      <td>0.5862</td>\n",
       "      <td>0.3827</td>\n",
       "      <td>0.2697</td>\n",
       "      <td>0.4258</td>\n",
       "      <td>0.4900</td>\n",
       "      <td>0.3018</td>\n",
       "      <td>0.3182</td>\n",
       "      <td>0.3700</td>\n",
       "      <td>0.3700</td>\n",
       "      <td>0.5479</td>\n",
       "      <td>0.4196</td>\n",
       "      <td>0.2876</td>\n",
       "      <td>0.4136</td>\n",
       "      <td>0.4914</td>\n",
       "      <td>0.4160</td>\n",
       "      <td>0.2837</td>\n",
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       "      <td>0.3053</td>\n",
       "      <td>0.2472</td>\n",
       "      <td>0.3396</td>\n",
       "      <td>0.4173</td>\n",
       "      <td>0.1869</td>\n",
       "      <td>0.1423</td>\n",
       "      <td>0.4645</td>\n",
       "      <td>0.6472</td>\n",
       "      <td>0.5937</td>\n",
       "      <td>0.2568</td>\n",
       "      <td>0.4203</td>\n",
       "      <td>0.4300</td>\n",
       "      <td>0.4596</td>\n",
       "      <td>0.5395</td>\n",
       "      <td>0.5361</td>\n",
       "      <td>0.6487</td>\n",
       "      <td>0.3197</td>\n",
       "      <td>0.4416</td>\n",
       "      <td>0.4900</td>\n",
       "      <td>0.4683</td>\n",
       "      <td>0.3538</td>\n",
       "      <td>0.3166</td>\n",
       "      <td>0.3556</td>\n",
       "      <td>0.5172</td>\n",
       "      <td>0.4593</td>\n",
       "      <td>0.3771</td>\n",
       "      <td>0.4300</td>\n",
       "      <td>0.4300</td>\n",
       "      <td>0.1840</td>\n",
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       "      <td>0.3681</td>\n",
       "      <td>0.5025</td>\n",
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       "      <td>0.1714</td>\n",
       "      <td>0.2227</td>\n",
       "      <td>0.4889</td>\n",
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       "      <td>0.3244</td>\n",
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       "      <td>0.3337</td>\n",
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       "      <td>0.4086</td>\n",
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       "      <td>0.5039</td>\n",
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       "      <td>0.5942</td>\n",
       "      <td>0.5239</td>\n",
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       "      <td>0.6019</td>\n",
       "      <td>0.4900</td>\n",
       "      <td>0.4602</td>\n",
       "      <td>0.5590</td>\n",
       "      <td>0.6237</td>\n",
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       "      <td>0.0613</td>\n",
       "      <td>0.2548</td>\n",
       "      <td>0.4384</td>\n",
       "      <td>0.4643</td>\n",
       "      <td>0.4830</td>\n",
       "      <td>0.1940</td>\n",
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       "      <td>0.2787</td>\n",
       "      <td>0.3856</td>\n",
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       "      <td>-0.6700</td>\n",
       "      <td>-0.8541</td>\n",
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       "      <td>-0.7758</td>\n",
       "      <td>-0.7454</td>\n",
       "      <td>-0.7836</td>\n",
       "      <td>-0.7369</td>\n",
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       "      <td>-0.7300</td>\n",
       "      <td>-0.7300</td>\n",
       "      <td>-0.6909</td>\n",
       "      <td>-0.6585</td>\n",
       "      <td>-0.5801</td>\n",
       "      <td>-0.6360</td>\n",
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       "      <td>-0.6556</td>\n",
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       "      <td>-0.8536</td>\n",
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       "      <td>-0.8655</td>\n",
       "      <td>-0.9466</td>\n",
       "      <td>-0.9370</td>\n",
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       "      <td>-0.7300</td>\n",
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       "      <td>-0.4069</td>\n",
       "      <td>-0.6681</td>\n",
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       "      <td>-0.7693</td>\n",
       "      <td>-0.8201</td>\n",
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       "      <td>-0.7836</td>\n",
       "      <td>-0.7257</td>\n",
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       "      <td>-0.6856</td>\n",
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       "      <td>-0.4300</td>\n",
       "      <td>-0.4300</td>\n",
       "      <td>-0.4944</td>\n",
       "      <td>-0.4884</td>\n",
       "      <td>-0.6221</td>\n",
       "      <td>-0.6134</td>\n",
       "      <td>-0.4578</td>\n",
       "      <td>-0.4411</td>\n",
       "      <td>-0.4658</td>\n",
       "      <td>-0.4300</td>\n",
       "      <td>-0.4300</td>\n",
       "      <td>-0.4581</td>\n",
       "      <td>-0.4805</td>\n",
       "      <td>-0.4041</td>\n",
       "      <td>-0.4300</td>\n",
       "      <td>-0.4598</td>\n",
       "      <td>-0.4390</td>\n",
       "      <td>-0.4763</td>\n",
       "      <td>-0.4359</td>\n",
       "      <td>-0.6695</td>\n",
       "      <td>-0.5946</td>\n",
       "      <td>-0.4900</td>\n",
       "      <td>-0.4900</td>\n",
       "      <td>-0.4935</td>\n",
       "      <td>-0.5456</td>\n",
       "      <td>-0.5208</td>\n",
       "      <td>-0.4960</td>\n",
       "      <td>-0.5180</td>\n",
       "      <td>-0.5654</td>\n",
       "      <td>-0.6007</td>\n",
       "      <td>-0.5751</td>\n",
       "      <td>-0.5324</td>\n",
       "      <td>-0.5618</td>\n",
       "      <td>-0.4158</td>\n",
       "      <td>-0.4900</td>\n",
       "      <td>-0.4690</td>\n",
       "      <td>-0.4960</td>\n",
       "      <td>-0.5338</td>\n",
       "      <td>-0.5090</td>\n",
       "      <td>-0.5802</td>\n",
       "      <td>-0.4900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>fall</td>\n",
       "      <td>-0.3952</td>\n",
       "      <td>-0.4326</td>\n",
       "      <td>-0.4414</td>\n",
       "      <td>-0.4800</td>\n",
       "      <td>-0.4800</td>\n",
       "      <td>-0.4665</td>\n",
       "      <td>-0.4516</td>\n",
       "      <td>-0.4311</td>\n",
       "      <td>-0.3904</td>\n",
       "      <td>-0.3667</td>\n",
       "      <td>-0.3544</td>\n",
       "      <td>-0.3445</td>\n",
       "      <td>-0.2958</td>\n",
       "      <td>-0.1829</td>\n",
       "      <td>-0.1791</td>\n",
       "      <td>-0.0570</td>\n",
       "      <td>0.0318</td>\n",
       "      <td>0.0554</td>\n",
       "      <td>0.1182</td>\n",
       "      <td>0.1928</td>\n",
       "      <td>0.2459</td>\n",
       "      <td>0.3116</td>\n",
       "      <td>0.3427</td>\n",
       "      <td>0.3546</td>\n",
       "      <td>0.4485</td>\n",
       "      <td>0.5000</td>\n",
       "      <td>0.4518</td>\n",
       "      <td>0.4108</td>\n",
       "      <td>0.4217</td>\n",
       "      <td>0.4024</td>\n",
       "      <td>0.3747</td>\n",
       "      <td>0.3754</td>\n",
       "      <td>0.4122</td>\n",
       "      <td>0.4176</td>\n",
       "      <td>0.4003</td>\n",
       "      <td>0.4242</td>\n",
       "      <td>0.4400</td>\n",
       "      <td>0.4272</td>\n",
       "      <td>0.4100</td>\n",
       "      <td>0.4100</td>\n",
       "      <td>0.4017</td>\n",
       "      <td>0.3845</td>\n",
       "      <td>0.3731</td>\n",
       "      <td>0.4200</td>\n",
       "      <td>0.4200</td>\n",
       "      <td>0.4200</td>\n",
       "      <td>0.4100</td>\n",
       "      <td>0.4074</td>\n",
       "      <td>0.3847</td>\n",
       "      <td>0.3546</td>\n",
       "      <td>0.3500</td>\n",
       "      <td>0.3500</td>\n",
       "      <td>0.3467</td>\n",
       "      <td>0.3340</td>\n",
       "      <td>0.3300</td>\n",
       "      <td>0.3288</td>\n",
       "      <td>0.3159</td>\n",
       "      <td>0.3029</td>\n",
       "      <td>0.2823</td>\n",
       "      <td>0.2564</td>\n",
       "      <td>0.2225</td>\n",
       "      <td>0.2040</td>\n",
       "      <td>0.1908</td>\n",
       "      <td>0.1878</td>\n",
       "      <td>0.1700</td>\n",
       "      <td>0.4331</td>\n",
       "      <td>0.4210</td>\n",
       "      <td>0.3009</td>\n",
       "      <td>0.2068</td>\n",
       "      <td>0.1379</td>\n",
       "      <td>0.0805</td>\n",
       "      <td>0.0058</td>\n",
       "      <td>-0.0414</td>\n",
       "      <td>3.1803</td>\n",
       "      <td>-3.7103</td>\n",
       "      <td>0.9723</td>\n",
       "      <td>1.5738</td>\n",
       "      <td>-1.6971</td>\n",
       "      <td>1.4719</td>\n",
       "      <td>3.7484</td>\n",
       "      <td>0.3814</td>\n",
       "      <td>-1.1177</td>\n",
       "      <td>0.5879</td>\n",
       "      <td>1.7932</td>\n",
       "      <td>-1.0660</td>\n",
       "      <td>1.0439</td>\n",
       "      <td>1.0806</td>\n",
       "      <td>1.6168</td>\n",
       "      <td>1.6826</td>\n",
       "      <td>1.4763</td>\n",
       "      <td>0.2665</td>\n",
       "      <td>-0.3387</td>\n",
       "      <td>-0.0817</td>\n",
       "      <td>0.2486</td>\n",
       "      <td>-0.0671</td>\n",
       "      <td>0.6700</td>\n",
       "      <td>1.8158</td>\n",
       "      <td>3.0321</td>\n",
       "      <td>0.0417</td>\n",
       "      <td>1.4182</td>\n",
       "      <td>-0.2683</td>\n",
       "      <td>1.8381</td>\n",
       "      <td>1.6559</td>\n",
       "      <td>1.5450</td>\n",
       "      <td>0.8560</td>\n",
       "      <td>1.2654</td>\n",
       "      <td>1.4480</td>\n",
       "      <td>0.6838</td>\n",
       "      <td>0.8201</td>\n",
       "      <td>1.1768</td>\n",
       "      <td>0.9955</td>\n",
       "      <td>0.5799</td>\n",
       "      <td>1.0700</td>\n",
       "      <td>1.1702</td>\n",
       "      <td>0.8977</td>\n",
       "      <td>0.9385</td>\n",
       "      <td>1.1747</td>\n",
       "      <td>1.2441</td>\n",
       "      <td>1.1909</td>\n",
       "      <td>0.9418</td>\n",
       "      <td>1.0822</td>\n",
       "      <td>1.0539</td>\n",
       "      <td>0.9370</td>\n",
       "      <td>1.0300</td>\n",
       "      <td>0.9400</td>\n",
       "      <td>0.9579</td>\n",
       "      <td>1.0896</td>\n",
       "      <td>0.8613</td>\n",
       "      <td>0.9107</td>\n",
       "      <td>0.9886</td>\n",
       "      <td>0.7705</td>\n",
       "      <td>0.8644</td>\n",
       "      <td>0.8416</td>\n",
       "      <td>0.8712</td>\n",
       "      <td>0.9100</td>\n",
       "      <td>0.9597</td>\n",
       "      <td>0.9235</td>\n",
       "      <td>0.9500</td>\n",
       "      <td>0.9112</td>\n",
       "      <td>0.8529</td>\n",
       "      <td>0.9431</td>\n",
       "      <td>1.1640</td>\n",
       "      <td>1.1614</td>\n",
       "      <td>1.0901</td>\n",
       "      <td>1.1636</td>\n",
       "      <td>1.0115</td>\n",
       "      <td>0.9988</td>\n",
       "      <td>1.0340</td>\n",
       "      <td>0.9940</td>\n",
       "      <td>1.0333</td>\n",
       "      <td>1.0255</td>\n",
       "      <td>1.0322</td>\n",
       "      <td>1.0315</td>\n",
       "      <td>1.0200</td>\n",
       "      <td>1.0116</td>\n",
       "      <td>1.0584</td>\n",
       "      <td>1.0800</td>\n",
       "      <td>1.0681</td>\n",
       "      <td>1.0429</td>\n",
       "      <td>1.0096</td>\n",
       "      <td>1.1229</td>\n",
       "      <td>1.1525</td>\n",
       "      <td>1.0993</td>\n",
       "      <td>1.1057</td>\n",
       "      <td>1.0822</td>\n",
       "      <td>1.1025</td>\n",
       "      <td>1.1274</td>\n",
       "      <td>1.1111</td>\n",
       "      <td>1.0822</td>\n",
       "      <td>1.0700</td>\n",
       "      <td>1.0466</td>\n",
       "      <td>1.0455</td>\n",
       "      <td>1.0158</td>\n",
       "      <td>0.8880</td>\n",
       "      <td>0.9458</td>\n",
       "      <td>0.8700</td>\n",
       "      <td>0.8543</td>\n",
       "      <td>0.8191</td>\n",
       "      <td>0.7809</td>\n",
       "      <td>0.7893</td>\n",
       "      <td>0.7832</td>\n",
       "      <td>0.7855</td>\n",
       "      <td>0.7653</td>\n",
       "      <td>0.7162</td>\n",
       "      <td>0.7571</td>\n",
       "      <td>0.7873</td>\n",
       "      <td>0.7514</td>\n",
       "      <td>0.6816</td>\n",
       "      <td>0.7017</td>\n",
       "      <td>0.7031</td>\n",
       "      <td>0.6923</td>\n",
       "      <td>0.7036</td>\n",
       "      <td>0.7322</td>\n",
       "      <td>0.7313</td>\n",
       "      <td>0.7006</td>\n",
       "      <td>0.7121</td>\n",
       "      <td>0.7159</td>\n",
       "      <td>0.7036</td>\n",
       "      <td>0.6700</td>\n",
       "      <td>0.6668</td>\n",
       "      <td>0.6517</td>\n",
       "      <td>0.6372</td>\n",
       "      <td>0.6315</td>\n",
       "      <td>0.6375</td>\n",
       "      <td>0.6258</td>\n",
       "      <td>0.6036</td>\n",
       "      <td>0.5983</td>\n",
       "      <td>0.5847</td>\n",
       "      <td>0.5509</td>\n",
       "      <td>0.5091</td>\n",
       "      <td>0.4912</td>\n",
       "      <td>0.4795</td>\n",
       "      <td>0.4534</td>\n",
       "      <td>0.4219</td>\n",
       "      <td>0.4017</td>\n",
       "      <td>0.3675</td>\n",
       "      <td>0.3418</td>\n",
       "      <td>0.3087</td>\n",
       "      <td>0.2469</td>\n",
       "      <td>0.1952</td>\n",
       "      <td>0.1487</td>\n",
       "      <td>0.1059</td>\n",
       "      <td>0.0624</td>\n",
       "      <td>-0.0245</td>\n",
       "      <td>0.0657</td>\n",
       "      <td>0.1748</td>\n",
       "      <td>0.1599</td>\n",
       "      <td>0.0118</td>\n",
       "      <td>-0.2830</td>\n",
       "      <td>-0.3840</td>\n",
       "      <td>-0.3406</td>\n",
       "      <td>-0.3214</td>\n",
       "      <td>-0.3537</td>\n",
       "      <td>1.4810</td>\n",
       "      <td>-1.9643</td>\n",
       "      <td>0.5928</td>\n",
       "      <td>1.0251</td>\n",
       "      <td>1.0354</td>\n",
       "      <td>0.5489</td>\n",
       "      <td>-0.9177</td>\n",
       "      <td>-0.1442</td>\n",
       "      <td>0.5623</td>\n",
       "      <td>-0.1055</td>\n",
       "      <td>-0.5242</td>\n",
       "      <td>0.3183</td>\n",
       "      <td>0.1980</td>\n",
       "      <td>-1.2197</td>\n",
       "      <td>-1.5891</td>\n",
       "      <td>-1.6211</td>\n",
       "      <td>-1.9883</td>\n",
       "      <td>0.0566</td>\n",
       "      <td>-0.1335</td>\n",
       "      <td>0.0600</td>\n",
       "      <td>-0.4317</td>\n",
       "      <td>0.2882</td>\n",
       "      <td>-0.1512</td>\n",
       "      <td>-0.7065</td>\n",
       "      <td>-1.3678</td>\n",
       "      <td>-1.6871</td>\n",
       "      <td>-1.5628</td>\n",
       "      <td>-0.4302</td>\n",
       "      <td>-0.5612</td>\n",
       "      <td>0.3400</td>\n",
       "      <td>0.1975</td>\n",
       "      <td>-0.0315</td>\n",
       "      <td>0.5832</td>\n",
       "      <td>0.5370</td>\n",
       "      <td>0.1002</td>\n",
       "      <td>0.0041</td>\n",
       "      <td>-0.4896</td>\n",
       "      <td>-0.4021</td>\n",
       "      <td>-0.3325</td>\n",
       "      <td>-0.3839</td>\n",
       "      <td>-0.4726</td>\n",
       "      <td>-0.4389</td>\n",
       "      <td>-0.2203</td>\n",
       "      <td>-0.3039</td>\n",
       "      <td>-0.3903</td>\n",
       "      <td>0.0475</td>\n",
       "      <td>0.1000</td>\n",
       "      <td>0.2744</td>\n",
       "      <td>0.3852</td>\n",
       "      <td>0.3570</td>\n",
       "      <td>-0.0067</td>\n",
       "      <td>-0.1780</td>\n",
       "      <td>-0.4316</td>\n",
       "      <td>-0.5365</td>\n",
       "      <td>-0.2160</td>\n",
       "      <td>0.0258</td>\n",
       "      <td>0.0028</td>\n",
       "      <td>0.1032</td>\n",
       "      <td>0.1087</td>\n",
       "      <td>0.2015</td>\n",
       "      <td>0.1968</td>\n",
       "      <td>0.0520</td>\n",
       "      <td>-0.1452</td>\n",
       "      <td>-0.1531</td>\n",
       "      <td>-0.1394</td>\n",
       "      <td>-0.1403</td>\n",
       "      <td>-0.1400</td>\n",
       "      <td>-0.1655</td>\n",
       "      <td>-0.1365</td>\n",
       "      <td>-0.0800</td>\n",
       "      <td>-0.0692</td>\n",
       "      <td>0.0021</td>\n",
       "      <td>0.0059</td>\n",
       "      <td>-0.0192</td>\n",
       "      <td>-0.0524</td>\n",
       "      <td>-0.0861</td>\n",
       "      <td>-0.1300</td>\n",
       "      <td>-0.1891</td>\n",
       "      <td>-0.1835</td>\n",
       "      <td>-0.1472</td>\n",
       "      <td>-0.0883</td>\n",
       "      <td>-0.0364</td>\n",
       "      <td>-0.0216</td>\n",
       "      <td>-0.0083</td>\n",
       "      <td>-0.0378</td>\n",
       "      <td>-0.0927</td>\n",
       "      <td>-0.1596</td>\n",
       "      <td>0.1623</td>\n",
       "      <td>0.1475</td>\n",
       "      <td>0.1293</td>\n",
       "      <td>0.1214</td>\n",
       "      <td>0.0744</td>\n",
       "      <td>0.0880</td>\n",
       "      <td>0.1079</td>\n",
       "      <td>0.0723</td>\n",
       "      <td>0.1478</td>\n",
       "      <td>0.1667</td>\n",
       "      <td>0.1622</td>\n",
       "      <td>0.1655</td>\n",
       "      <td>0.1925</td>\n",
       "      <td>0.1976</td>\n",
       "      <td>0.2186</td>\n",
       "      <td>0.1685</td>\n",
       "      <td>0.0961</td>\n",
       "      <td>0.0791</td>\n",
       "      <td>0.0603</td>\n",
       "      <td>0.0407</td>\n",
       "      <td>0.0468</td>\n",
       "      <td>0.0310</td>\n",
       "      <td>0.0127</td>\n",
       "      <td>0.0421</td>\n",
       "      <td>0.0628</td>\n",
       "      <td>0.1093</td>\n",
       "      <td>0.1393</td>\n",
       "      <td>0.1608</td>\n",
       "      <td>0.1683</td>\n",
       "      <td>0.1462</td>\n",
       "      <td>0.1247</td>\n",
       "      <td>0.0982</td>\n",
       "      <td>0.0941</td>\n",
       "      <td>0.1000</td>\n",
       "      <td>0.1194</td>\n",
       "      <td>0.1300</td>\n",
       "      <td>0.1300</td>\n",
       "      <td>0.1300</td>\n",
       "      <td>0.1100</td>\n",
       "      <td>0.1100</td>\n",
       "      <td>0.1058</td>\n",
       "      <td>0.1000</td>\n",
       "      <td>0.1000</td>\n",
       "      <td>0.0900</td>\n",
       "      <td>0.0900</td>\n",
       "      <td>0.0818</td>\n",
       "      <td>0.0800</td>\n",
       "      <td>0.0800</td>\n",
       "      <td>0.0762</td>\n",
       "      <td>0.0700</td>\n",
       "      <td>0.0700</td>\n",
       "      <td>0.070</td>\n",
       "      <td>0.0667</td>\n",
       "      <td>0.0600</td>\n",
       "      <td>0.0600</td>\n",
       "      <td>0.0500</td>\n",
       "      <td>0.0459</td>\n",
       "      <td>0.0400</td>\n",
       "      <td>0.0312</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0262</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0108</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0041</td>\n",
       "      <td>0.0551</td>\n",
       "      <td>-0.0883</td>\n",
       "      <td>-0.0770</td>\n",
       "      <td>-0.0467</td>\n",
       "      <td>-0.0540</td>\n",
       "      <td>-0.0205</td>\n",
       "      <td>-0.0850</td>\n",
       "      <td>-0.0543</td>\n",
       "      <td>-1.1334</td>\n",
       "      <td>1.1927</td>\n",
       "      <td>-0.2285</td>\n",
       "      <td>-1.1240</td>\n",
       "      <td>-0.5655</td>\n",
       "      <td>-0.5091</td>\n",
       "      <td>1.0910</td>\n",
       "      <td>-0.3837</td>\n",
       "      <td>0.0956</td>\n",
       "      <td>-0.4515</td>\n",
       "      <td>-0.6187</td>\n",
       "      <td>0.3270</td>\n",
       "      <td>0.1274</td>\n",
       "      <td>-0.5687</td>\n",
       "      <td>-0.3900</td>\n",
       "      <td>0.0125</td>\n",
       "      <td>-0.4655</td>\n",
       "      <td>1.1798</td>\n",
       "      <td>0.0926</td>\n",
       "      <td>0.0972</td>\n",
       "      <td>-0.0532</td>\n",
       "      <td>0.9816</td>\n",
       "      <td>-0.0715</td>\n",
       "      <td>0.3321</td>\n",
       "      <td>0.3308</td>\n",
       "      <td>0.2681</td>\n",
       "      <td>0.2853</td>\n",
       "      <td>0.1114</td>\n",
       "      <td>-0.0533</td>\n",
       "      <td>-0.2401</td>\n",
       "      <td>0.4338</td>\n",
       "      <td>-0.2691</td>\n",
       "      <td>-0.2870</td>\n",
       "      <td>-0.6725</td>\n",
       "      <td>-0.5362</td>\n",
       "      <td>-0.1867</td>\n",
       "      <td>-0.0326</td>\n",
       "      <td>0.0020</td>\n",
       "      <td>0.0798</td>\n",
       "      <td>-0.0942</td>\n",
       "      <td>-0.0169</td>\n",
       "      <td>0.0656</td>\n",
       "      <td>-0.1336</td>\n",
       "      <td>-0.2941</td>\n",
       "      <td>-0.3205</td>\n",
       "      <td>-0.0775</td>\n",
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       "      <td>21.6141</td>\n",
       "      <td>21.3355</td>\n",
       "      <td>15.9385</td>\n",
       "      <td>5.8921</td>\n",
       "      <td>-3.8207</td>\n",
       "      <td>-13.0885</td>\n",
       "      <td>-14.9318</td>\n",
       "      <td>-15.0545</td>\n",
       "      <td>-11.7565</td>\n",
       "      <td>-8.7202</td>\n",
       "      <td>10.6074</td>\n",
       "      <td>12.2756</td>\n",
       "      <td>13.9439</td>\n",
       "      <td>12.6635</td>\n",
       "      <td>11.1377</td>\n",
       "      <td>5.9313</td>\n",
       "      <td>-2.2686</td>\n",
       "      <td>-6.6902</td>\n",
       "      <td>-9.4600</td>\n",
       "      <td>-9.1480</td>\n",
       "      <td>-7.5787</td>\n",
       "      <td>-4.4119</td>\n",
       "      <td>-1.2361</td>\n",
       "      <td>1.3659</td>\n",
       "      <td>3.4195</td>\n",
       "      <td>3.8727</td>\n",
       "      <td>3.5135</td>\n",
       "      <td>1.5702</td>\n",
       "      <td>-0.6977</td>\n",
       "      <td>-2.8655</td>\n",
       "      <td>-3.9532</td>\n",
       "      <td>-4.0117</td>\n",
       "      <td>-3.2634</td>\n",
       "      <td>-2.0691</td>\n",
       "      <td>-0.1649</td>\n",
       "      <td>2.3681</td>\n",
       "      <td>4.0300</td>\n",
       "      <td>3.3011</td>\n",
       "      <td>2.0893</td>\n",
       "      <td>0.8828</td>\n",
       "      <td>-0.7951</td>\n",
       "      <td>-1.4848</td>\n",
       "      <td>-1.1262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>motion</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0164</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0128</td>\n",
       "      <td>0.0159</td>\n",
       "      <td>0.0190</td>\n",
       "      <td>0.0157</td>\n",
       "      <td>0.0199</td>\n",
       "      <td>0.0155</td>\n",
       "      <td>0.0112</td>\n",
       "      <td>-0.0100</td>\n",
       "      <td>-0.0077</td>\n",
       "      <td>0.0119</td>\n",
       "      <td>0.0180</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0209</td>\n",
       "      <td>0.0239</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0118</td>\n",
       "      <td>0.0179</td>\n",
       "      <td>0.0113</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0165</td>\n",
       "      <td>0.0123</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0121</td>\n",
       "      <td>0.0180</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0190</td>\n",
       "      <td>0.0161</td>\n",
       "      <td>0.0271</td>\n",
       "      <td>0.0209</td>\n",
       "      <td>0.0184</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0153</td>\n",
       "      <td>0.0185</td>\n",
       "      <td>0.0118</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0231</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0195</td>\n",
       "      <td>0.0131</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0054</td>\n",
       "      <td>0.0115</td>\n",
       "      <td>0.0179</td>\n",
       "      <td>0.0158</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0181</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0143</td>\n",
       "      <td>0.0206</td>\n",
       "      <td>0.0265</td>\n",
       "      <td>0.0140</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0183</td>\n",
       "      <td>0.0148</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0193</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0037</td>\n",
       "      <td>0.0203</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0140</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0141</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0154</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0127</td>\n",
       "      <td>0.0171</td>\n",
       "      <td>0.0160</td>\n",
       "      <td>0.0036</td>\n",
       "      <td>0.0045</td>\n",
       "      <td>0.0096</td>\n",
       "      <td>0.0060</td>\n",
       "      <td>0.0025</td>\n",
       "      <td>-0.0010</td>\n",
       "      <td>-0.0046</td>\n",
       "      <td>-0.0081</td>\n",
       "      <td>0.0066</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>-0.0057</td>\n",
       "      <td>0.0227</td>\n",
       "      <td>0.0341</td>\n",
       "      <td>0.0179</td>\n",
       "      <td>0.0316</td>\n",
       "      <td>0.0225</td>\n",
       "      <td>0.0144</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9799</td>\n",
       "      <td>0.9755</td>\n",
       "      <td>0.9712</td>\n",
       "      <td>0.9700</td>\n",
       "      <td>0.9789</td>\n",
       "      <td>0.9681</td>\n",
       "      <td>0.9620</td>\n",
       "      <td>0.9785</td>\n",
       "      <td>0.9791</td>\n",
       "      <td>0.9730</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9790</td>\n",
       "      <td>0.9771</td>\n",
       "      <td>0.9753</td>\n",
       "      <td>0.9735</td>\n",
       "      <td>0.9717</td>\n",
       "      <td>0.9710</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9810</td>\n",
       "      <td>0.9853</td>\n",
       "      <td>0.9896</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9782</td>\n",
       "      <td>0.9749</td>\n",
       "      <td>0.9716</td>\n",
       "      <td>0.9700</td>\n",
       "      <td>0.9700</td>\n",
       "      <td>0.9700</td>\n",
       "      <td>0.9716</td>\n",
       "      <td>0.9781</td>\n",
       "      <td>0.9754</td>\n",
       "      <td>0.9693</td>\n",
       "      <td>0.9653</td>\n",
       "      <td>0.9613</td>\n",
       "      <td>0.9727</td>\n",
       "      <td>0.9771</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9800</td>\n",
       "      <td>0.9755</td>\n",
       "      <td>0.9698</td>\n",
       "      <td>0.9680</td>\n",
       "      <td>0.9663</td>\n",
       "      <td>0.9645</td>\n",
       "      <td>0.9627</td>\n",
       "      <td>0.9609</td>\n",
       "      <td>0.9766</td>\n",
       "      <td>0.9784</td>\n",
       "      <td>0.9763</td>\n",
       "      <td>0.9743</td>\n",
       "      <td>0.9722</td>\n",
       "      <td>0.9701</td>\n",
       "      <td>0.9778</td>\n",
       "      <td>0.9637</td>\n",
       "      <td>0.9700</td>\n",
       "      <td>0.9780</td>\n",
       "      <td>0.9700</td>\n",
       "      <td>0.9630</td>\n",
       "      <td>0.9683</td>\n",
       "      <td>0.1272</td>\n",
       "      <td>0.1230</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1220</td>\n",
       "      <td>0.1262</td>\n",
       "      <td>0.1300</td>\n",
       "      <td>0.1300</td>\n",
       "      <td>0.1300</td>\n",
       "      <td>0.1300</td>\n",
       "      <td>0.1300</td>\n",
       "      <td>0.1300</td>\n",
       "      <td>0.1300</td>\n",
       "      <td>0.1300</td>\n",
       "      <td>0.1305</td>\n",
       "      <td>0.1479</td>\n",
       "      <td>0.1652</td>\n",
       "      <td>0.1700</td>\n",
       "      <td>0.1700</td>\n",
       "      <td>0.1700</td>\n",
       "      <td>0.1700</td>\n",
       "      <td>0.1608</td>\n",
       "      <td>0.1491</td>\n",
       "      <td>0.1370</td>\n",
       "      <td>0.1300</td>\n",
       "      <td>0.1300</td>\n",
       "      <td>0.1300</td>\n",
       "      <td>0.1300</td>\n",
       "      <td>0.1300</td>\n",
       "      <td>0.1387</td>\n",
       "      <td>0.1405</td>\n",
       "      <td>0.1447</td>\n",
       "      <td>0.1490</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1465</td>\n",
       "      <td>0.1423</td>\n",
       "      <td>0.1413</td>\n",
       "      <td>0.1446</td>\n",
       "      <td>0.1479</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1490</td>\n",
       "      <td>0.1471</td>\n",
       "      <td>0.1453</td>\n",
       "      <td>0.1435</td>\n",
       "      <td>0.1417</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.140</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1453</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1395</td>\n",
       "      <td>0.1331</td>\n",
       "      <td>0.1373</td>\n",
       "      <td>0.1307</td>\n",
       "      <td>0.1300</td>\n",
       "      <td>0.1315</td>\n",
       "      <td>0.1379</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1435</td>\n",
       "      <td>0.1440</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1500</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1432</td>\n",
       "      <td>0.1469</td>\n",
       "      <td>0.1408</td>\n",
       "      <td>0.1434</td>\n",
       "      <td>0.1478</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1490</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1600</td>\n",
       "      <td>0.1659</td>\n",
       "      <td>0.1700</td>\n",
       "      <td>0.1700</td>\n",
       "      <td>0.1700</td>\n",
       "      <td>0.1716</td>\n",
       "      <td>0.1748</td>\n",
       "      <td>0.1779</td>\n",
       "      <td>0.1800</td>\n",
       "      <td>0.1800</td>\n",
       "      <td>0.1800</td>\n",
       "      <td>0.1780</td>\n",
       "      <td>0.1659</td>\n",
       "      <td>0.1538</td>\n",
       "      <td>0.2147</td>\n",
       "      <td>0.2059</td>\n",
       "      <td>0.1858</td>\n",
       "      <td>0.1425</td>\n",
       "      <td>0.1300</td>\n",
       "      <td>0.1306</td>\n",
       "      <td>0.1359</td>\n",
       "      <td>0.1412</td>\n",
       "      <td>0.1466</td>\n",
       "      <td>0.1519</td>\n",
       "      <td>0.1572</td>\n",
       "      <td>0.1469</td>\n",
       "      <td>0.1431</td>\n",
       "      <td>0.1473</td>\n",
       "      <td>0.1515</td>\n",
       "      <td>0.1557</td>\n",
       "      <td>0.1598</td>\n",
       "      <td>0.2068</td>\n",
       "      <td>0.1984</td>\n",
       "      <td>0.1998</td>\n",
       "      <td>0.2603</td>\n",
       "      <td>0.1884</td>\n",
       "      <td>0.1870</td>\n",
       "      <td>0.2000</td>\n",
       "      <td>0.1925</td>\n",
       "      <td>0.3458</td>\n",
       "      <td>0.5304</td>\n",
       "      <td>0.6773</td>\n",
       "      <td>0.5492</td>\n",
       "      <td>0.4300</td>\n",
       "      <td>0.4300</td>\n",
       "      <td>0.4300</td>\n",
       "      <td>0.4300</td>\n",
       "      <td>0.4300</td>\n",
       "      <td>0.5038</td>\n",
       "      <td>0.7046</td>\n",
       "      <td>0.9054</td>\n",
       "      <td>1.0923</td>\n",
       "      <td>0.8474</td>\n",
       "      <td>0.8787</td>\n",
       "      <td>0.6188</td>\n",
       "      <td>0.1210</td>\n",
       "      <td>0.2478</td>\n",
       "      <td>0.7554</td>\n",
       "      <td>0.7426</td>\n",
       "      <td>0.3016</td>\n",
       "      <td>-0.0241</td>\n",
       "      <td>0.2053</td>\n",
       "      <td>0.1276</td>\n",
       "      <td>0.1333</td>\n",
       "      <td>0.2593</td>\n",
       "      <td>0.3854</td>\n",
       "      <td>0.1354</td>\n",
       "      <td>0.3745</td>\n",
       "      <td>0.6136</td>\n",
       "      <td>0.6396</td>\n",
       "      <td>0.4635</td>\n",
       "      <td>0.3870</td>\n",
       "      <td>0.3339</td>\n",
       "      <td>0.1859</td>\n",
       "      <td>0.1983</td>\n",
       "      <td>0.2108</td>\n",
       "      <td>0.2232</td>\n",
       "      <td>0.2357</td>\n",
       "      <td>0.2662</td>\n",
       "      <td>0.3063</td>\n",
       "      <td>0.3464</td>\n",
       "      <td>0.3865</td>\n",
       "      <td>0.4266</td>\n",
       "      <td>0.4654</td>\n",
       "      <td>0.4635</td>\n",
       "      <td>0.3910</td>\n",
       "      <td>0.0658</td>\n",
       "      <td>0.3058</td>\n",
       "      <td>0.2231</td>\n",
       "      <td>0.1890</td>\n",
       "      <td>0.2080</td>\n",
       "      <td>0.2269</td>\n",
       "      <td>0.2670</td>\n",
       "      <td>0.2187</td>\n",
       "      <td>0.0413</td>\n",
       "      <td>-0.0797</td>\n",
       "      <td>0.2189</td>\n",
       "      <td>0.1425</td>\n",
       "      <td>0.2133</td>\n",
       "      <td>0.2400</td>\n",
       "      <td>0.2400</td>\n",
       "      <td>0.2647</td>\n",
       "      <td>0.3263</td>\n",
       "      <td>0.3879</td>\n",
       "      <td>0.0173</td>\n",
       "      <td>0.0904</td>\n",
       "      <td>0.1515</td>\n",
       "      <td>0.2043</td>\n",
       "      <td>0.2648</td>\n",
       "      <td>0.3409</td>\n",
       "      <td>0.4170</td>\n",
       "      <td>0.4932</td>\n",
       "      <td>0.5693</td>\n",
       "      <td>0.4063</td>\n",
       "      <td>0.2739</td>\n",
       "      <td>0.3285</td>\n",
       "      <td>0.4041</td>\n",
       "      <td>0.2417</td>\n",
       "      <td>0.0792</td>\n",
       "      <td>0.0600</td>\n",
       "      <td>0.0703</td>\n",
       "      <td>0.1074</td>\n",
       "      <td>0.1445</td>\n",
       "      <td>0.1468</td>\n",
       "      <td>0.2508</td>\n",
       "      <td>-0.0266</td>\n",
       "      <td>0.0173</td>\n",
       "      <td>0.0427</td>\n",
       "      <td>0.1609</td>\n",
       "      <td>0.2313</td>\n",
       "      <td>0.1634</td>\n",
       "      <td>0.1380</td>\n",
       "      <td>0.1800</td>\n",
       "      <td>0.1800</td>\n",
       "      <td>0.1800</td>\n",
       "      <td>-0.2452</td>\n",
       "      <td>-0.1811</td>\n",
       "      <td>-0.0507</td>\n",
       "      <td>0.0797</td>\n",
       "      <td>0.2101</td>\n",
       "      <td>0.3024</td>\n",
       "      <td>0.2700</td>\n",
       "      <td>0.2376</td>\n",
       "      <td>0.2052</td>\n",
       "      <td>0.2060</td>\n",
       "      <td>0.3232</td>\n",
       "      <td>0.4404</td>\n",
       "      <td>0.5372</td>\n",
       "      <td>0.3379</td>\n",
       "      <td>0.2723</td>\n",
       "      <td>0.3412</td>\n",
       "      <td>0.3939</td>\n",
       "      <td>0.0296</td>\n",
       "      <td>0.1561</td>\n",
       "      <td>0.2827</td>\n",
       "      <td>0.3299</td>\n",
       "      <td>0.3554</td>\n",
       "      <td>0.2546</td>\n",
       "      <td>-0.0174</td>\n",
       "      <td>0.3095</td>\n",
       "      <td>0.2790</td>\n",
       "      <td>0.2486</td>\n",
       "      <td>-0.0039</td>\n",
       "      <td>0.0967</td>\n",
       "      <td>0.1972</td>\n",
       "      <td>0.2977</td>\n",
       "      <td>0.3982</td>\n",
       "      <td>0.4611</td>\n",
       "      <td>0.1290</td>\n",
       "      <td>-0.2030</td>\n",
       "      <td>-0.5350</td>\n",
       "      <td>-0.8671</td>\n",
       "      <td>-1.0286</td>\n",
       "      <td>-0.7893</td>\n",
       "      <td>-0.5500</td>\n",
       "      <td>-0.3107</td>\n",
       "      <td>-0.0714</td>\n",
       "      <td>0.1678</td>\n",
       "      <td>0.4071</td>\n",
       "      <td>0.6464</td>\n",
       "      <td>0.8857</td>\n",
       "      <td>1.1250</td>\n",
       "      <td>1.3642</td>\n",
       "      <td>1.6035</td>\n",
       "      <td>1.8428</td>\n",
       "      <td>1.7659</td>\n",
       "      <td>1.4323</td>\n",
       "      <td>1.0987</td>\n",
       "      <td>0.7651</td>\n",
       "      <td>0.4315</td>\n",
       "      <td>0.0979</td>\n",
       "      <td>0.2764</td>\n",
       "      <td>0.7854</td>\n",
       "      <td>1.0124</td>\n",
       "      <td>0.4753</td>\n",
       "      <td>2.1854</td>\n",
       "      <td>0.3624</td>\n",
       "      <td>0.2821</td>\n",
       "      <td>-1.1921</td>\n",
       "      <td>-1.1369</td>\n",
       "      <td>-1.1111</td>\n",
       "      <td>-1.0684</td>\n",
       "      <td>-0.9915</td>\n",
       "      <td>-0.9181</td>\n",
       "      <td>-0.8904</td>\n",
       "      <td>-0.8628</td>\n",
       "      <td>-0.8351</td>\n",
       "      <td>-0.8075</td>\n",
       "      <td>-0.7636</td>\n",
       "      <td>-0.6916</td>\n",
       "      <td>-0.6197</td>\n",
       "      <td>-0.5488</td>\n",
       "      <td>-0.5090</td>\n",
       "      <td>-0.4900</td>\n",
       "      <td>-0.4212</td>\n",
       "      <td>-0.3703</td>\n",
       "      <td>-0.4104</td>\n",
       "      <td>-0.3934</td>\n",
       "      <td>-0.5072</td>\n",
       "      <td>-0.7108</td>\n",
       "      <td>-0.9984</td>\n",
       "      <td>-1.0147</td>\n",
       "      <td>-1.0924</td>\n",
       "      <td>-0.7849</td>\n",
       "      <td>-0.7361</td>\n",
       "      <td>-0.6873</td>\n",
       "      <td>-0.6032</td>\n",
       "      <td>-0.4853</td>\n",
       "      <td>-0.3674</td>\n",
       "      <td>-0.3281</td>\n",
       "      <td>-0.3633</td>\n",
       "      <td>-0.2375</td>\n",
       "      <td>-0.0738</td>\n",
       "      <td>-0.0844</td>\n",
       "      <td>-0.1363</td>\n",
       "      <td>-0.1882</td>\n",
       "      <td>-0.2402</td>\n",
       "      <td>-0.2921</td>\n",
       "      <td>-0.3680</td>\n",
       "      <td>-0.4566</td>\n",
       "      <td>-0.5452</td>\n",
       "      <td>-0.6338</td>\n",
       "      <td>-0.7224</td>\n",
       "      <td>-0.5529</td>\n",
       "      <td>-0.5095</td>\n",
       "      <td>-0.7271</td>\n",
       "      <td>-1.0448</td>\n",
       "      <td>-0.8481</td>\n",
       "      <td>-0.8099</td>\n",
       "      <td>-0.7629</td>\n",
       "      <td>-0.7061</td>\n",
       "      <td>-0.6494</td>\n",
       "      <td>-0.5868</td>\n",
       "      <td>-0.5500</td>\n",
       "      <td>-0.5500</td>\n",
       "      <td>-0.5769</td>\n",
       "      <td>-0.8550</td>\n",
       "      <td>-1.0908</td>\n",
       "      <td>-1.1600</td>\n",
       "      <td>-1.1281</td>\n",
       "      <td>-1.0800</td>\n",
       "      <td>-1.0153</td>\n",
       "      <td>-0.9537</td>\n",
       "      <td>-0.8921</td>\n",
       "      <td>-0.7574</td>\n",
       "      <td>-0.8731</td>\n",
       "      <td>-0.9515</td>\n",
       "      <td>-1.0043</td>\n",
       "      <td>-1.0480</td>\n",
       "      <td>-1.0727</td>\n",
       "      <td>-1.0974</td>\n",
       "      <td>-1.1221</td>\n",
       "      <td>-1.1468</td>\n",
       "      <td>-1.4298</td>\n",
       "      <td>-1.5222</td>\n",
       "      <td>-1.3164</td>\n",
       "      <td>-1.4558</td>\n",
       "      <td>-1.4295</td>\n",
       "      <td>-1.4031</td>\n",
       "      <td>-1.5703</td>\n",
       "      <td>-1.6680</td>\n",
       "      <td>-1.5164</td>\n",
       "      <td>-1.3648</td>\n",
       "      <td>-1.1868</td>\n",
       "      <td>-0.9948</td>\n",
       "      <td>-0.9733</td>\n",
       "      <td>-0.8481</td>\n",
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       "      <td>-0.5693</td>\n",
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       "      <td>-0.3993</td>\n",
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       "      <td>-0.0860</td>\n",
       "      <td>-0.2032</td>\n",
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       "      <td>-0.7300</td>\n",
       "      <td>-0.7612</td>\n",
       "      <td>-0.8139</td>\n",
       "      <td>-0.9200</td>\n",
       "      <td>-0.9200</td>\n",
       "      <td>-0.9200</td>\n",
       "      <td>-0.9798</td>\n",
       "      <td>-1.0561</td>\n",
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       "      <td>-0.6077</td>\n",
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       "      <td>-0.9063</td>\n",
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       "      <td>-0.4300</td>\n",
       "      <td>-0.4900</td>\n",
       "      <td>-0.4900</td>\n",
       "      <td>-0.4900</td>\n",
       "      <td>-0.4106</td>\n",
       "      <td>-0.3759</td>\n",
       "      <td>-0.3412</td>\n",
       "      <td>-0.3064</td>\n",
       "      <td>-0.2717</td>\n",
       "      <td>-0.2424</td>\n",
       "      <td>-0.2695</td>\n",
       "      <td>-0.2967</td>\n",
       "      <td>-0.3238</td>\n",
       "      <td>-0.3510</td>\n",
       "      <td>-0.3686</td>\n",
       "      <td>-0.3639</td>\n",
       "      <td>-0.3592</td>\n",
       "      <td>-0.3545</td>\n",
       "      <td>-0.3498</td>\n",
       "      <td>-0.3451</td>\n",
       "      <td>-0.3404</td>\n",
       "      <td>-0.3356</td>\n",
       "      <td>-0.3309</td>\n",
       "      <td>-0.3262</td>\n",
       "      <td>-0.3215</td>\n",
       "      <td>-0.3168</td>\n",
       "      <td>-0.3121</td>\n",
       "      <td>-0.3100</td>\n",
       "      <td>-0.3100</td>\n",
       "      <td>-0.3100</td>\n",
       "      <td>-0.3100</td>\n",
       "      <td>-0.3100</td>\n",
       "      <td>-0.3100</td>\n",
       "      <td>-0.3979</td>\n",
       "      <td>-0.1929</td>\n",
       "      <td>-0.0978</td>\n",
       "      <td>-0.1736</td>\n",
       "      <td>-0.1862</td>\n",
       "      <td>-0.2706</td>\n",
       "      <td>-0.3639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>fall</td>\n",
       "      <td>-0.0321</td>\n",
       "      <td>-0.0054</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>-0.0130</td>\n",
       "      <td>-0.0732</td>\n",
       "      <td>-0.0900</td>\n",
       "      <td>-0.1505</td>\n",
       "      <td>-0.2072</td>\n",
       "      <td>-0.2760</td>\n",
       "      <td>-0.2557</td>\n",
       "      <td>-0.2298</td>\n",
       "      <td>-0.3495</td>\n",
       "      <td>-0.4116</td>\n",
       "      <td>-0.4200</td>\n",
       "      <td>-0.4225</td>\n",
       "      <td>-0.4168</td>\n",
       "      <td>-0.4000</td>\n",
       "      <td>-0.3882</td>\n",
       "      <td>-0.3838</td>\n",
       "      <td>-0.3900</td>\n",
       "      <td>-0.3402</td>\n",
       "      <td>-0.2851</td>\n",
       "      <td>-0.1905</td>\n",
       "      <td>-0.1142</td>\n",
       "      <td>-0.0900</td>\n",
       "      <td>-0.0882</td>\n",
       "      <td>-0.0500</td>\n",
       "      <td>-0.0349</td>\n",
       "      <td>0.0028</td>\n",
       "      <td>0.1101</td>\n",
       "      <td>0.2088</td>\n",
       "      <td>0.3974</td>\n",
       "      <td>0.2992</td>\n",
       "      <td>0.3109</td>\n",
       "      <td>0.4000</td>\n",
       "      <td>0.4363</td>\n",
       "      <td>0.3747</td>\n",
       "      <td>0.3482</td>\n",
       "      <td>0.4134</td>\n",
       "      <td>0.4200</td>\n",
       "      <td>0.4289</td>\n",
       "      <td>0.4345</td>\n",
       "      <td>0.4575</td>\n",
       "      <td>0.4700</td>\n",
       "      <td>0.4298</td>\n",
       "      <td>0.4042</td>\n",
       "      <td>0.4300</td>\n",
       "      <td>0.4364</td>\n",
       "      <td>0.4220</td>\n",
       "      <td>0.4347</td>\n",
       "      <td>0.4600</td>\n",
       "      <td>0.4431</td>\n",
       "      <td>0.4382</td>\n",
       "      <td>0.4483</td>\n",
       "      <td>0.4400</td>\n",
       "      <td>0.4461</td>\n",
       "      <td>0.4414</td>\n",
       "      <td>0.4362</td>\n",
       "      <td>0.4162</td>\n",
       "      <td>0.4100</td>\n",
       "      <td>0.4100</td>\n",
       "      <td>0.4100</td>\n",
       "      <td>0.4100</td>\n",
       "      <td>0.4047</td>\n",
       "      <td>0.4000</td>\n",
       "      <td>0.3901</td>\n",
       "      <td>0.3700</td>\n",
       "      <td>0.3700</td>\n",
       "      <td>0.3625</td>\n",
       "      <td>0.3600</td>\n",
       "      <td>0.3474</td>\n",
       "      <td>0.3337</td>\n",
       "      <td>0.3300</td>\n",
       "      <td>0.3200</td>\n",
       "      <td>0.3200</td>\n",
       "      <td>0.3133</td>\n",
       "      <td>0.3016</td>\n",
       "      <td>0.2782</td>\n",
       "      <td>0.2659</td>\n",
       "      <td>0.2547</td>\n",
       "      <td>0.2403</td>\n",
       "      <td>0.2161</td>\n",
       "      <td>0.1962</td>\n",
       "      <td>0.2977</td>\n",
       "      <td>0.4671</td>\n",
       "      <td>0.3192</td>\n",
       "      <td>0.2362</td>\n",
       "      <td>0.2059</td>\n",
       "      <td>0.0991</td>\n",
       "      <td>0.0729</td>\n",
       "      <td>0.0900</td>\n",
       "      <td>0.1788</td>\n",
       "      <td>1.2231</td>\n",
       "      <td>-3.1572</td>\n",
       "      <td>2.2542</td>\n",
       "      <td>0.6963</td>\n",
       "      <td>-1.9330</td>\n",
       "      <td>2.9862</td>\n",
       "      <td>3.2916</td>\n",
       "      <td>-0.8835</td>\n",
       "      <td>-0.4453</td>\n",
       "      <td>1.9314</td>\n",
       "      <td>-0.3920</td>\n",
       "      <td>-1.3641</td>\n",
       "      <td>-0.0055</td>\n",
       "      <td>1.2515</td>\n",
       "      <td>2.0445</td>\n",
       "      <td>2.1074</td>\n",
       "      <td>0.9936</td>\n",
       "      <td>1.0484</td>\n",
       "      <td>0.4864</td>\n",
       "      <td>-0.1553</td>\n",
       "      <td>0.0606</td>\n",
       "      <td>0.1715</td>\n",
       "      <td>0.4141</td>\n",
       "      <td>3.0427</td>\n",
       "      <td>0.6493</td>\n",
       "      <td>2.1668</td>\n",
       "      <td>0.5816</td>\n",
       "      <td>0.9496</td>\n",
       "      <td>1.3707</td>\n",
       "      <td>1.0946</td>\n",
       "      <td>1.2592</td>\n",
       "      <td>1.0064</td>\n",
       "      <td>0.9132</td>\n",
       "      <td>0.9403</td>\n",
       "      <td>0.9980</td>\n",
       "      <td>0.9446</td>\n",
       "      <td>0.9510</td>\n",
       "      <td>0.8314</td>\n",
       "      <td>1.0264</td>\n",
       "      <td>1.0513</td>\n",
       "      <td>1.1290</td>\n",
       "      <td>1.1528</td>\n",
       "      <td>1.0008</td>\n",
       "      <td>1.1264</td>\n",
       "      <td>0.9842</td>\n",
       "      <td>1.0436</td>\n",
       "      <td>1.0279</td>\n",
       "      <td>0.9571</td>\n",
       "      <td>0.9978</td>\n",
       "      <td>1.0168</td>\n",
       "      <td>1.0306</td>\n",
       "      <td>0.9277</td>\n",
       "      <td>1.0021</td>\n",
       "      <td>1.1170</td>\n",
       "      <td>1.0314</td>\n",
       "      <td>0.9002</td>\n",
       "      <td>0.8700</td>\n",
       "      <td>0.8390</td>\n",
       "      <td>0.8311</td>\n",
       "      <td>0.8944</td>\n",
       "      <td>0.9300</td>\n",
       "      <td>0.9398</td>\n",
       "      <td>0.9334</td>\n",
       "      <td>0.9662</td>\n",
       "      <td>1.0182</td>\n",
       "      <td>1.0523</td>\n",
       "      <td>1.0833</td>\n",
       "      <td>1.0868</td>\n",
       "      <td>0.9900</td>\n",
       "      <td>1.0254</td>\n",
       "      <td>1.0177</td>\n",
       "      <td>1.0035</td>\n",
       "      <td>1.0166</td>\n",
       "      <td>1.0673</td>\n",
       "      <td>1.0700</td>\n",
       "      <td>1.0791</td>\n",
       "      <td>0.9641</td>\n",
       "      <td>1.1234</td>\n",
       "      <td>1.0498</td>\n",
       "      <td>1.1053</td>\n",
       "      <td>1.1088</td>\n",
       "      <td>1.1192</td>\n",
       "      <td>1.1025</td>\n",
       "      <td>1.0844</td>\n",
       "      <td>1.0900</td>\n",
       "      <td>1.0845</td>\n",
       "      <td>1.0638</td>\n",
       "      <td>1.0700</td>\n",
       "      <td>1.0629</td>\n",
       "      <td>1.0457</td>\n",
       "      <td>0.9717</td>\n",
       "      <td>0.9655</td>\n",
       "      <td>0.9328</td>\n",
       "      <td>0.9418</td>\n",
       "      <td>0.9714</td>\n",
       "      <td>0.9450</td>\n",
       "      <td>0.9248</td>\n",
       "      <td>0.9089</td>\n",
       "      <td>0.8200</td>\n",
       "      <td>0.7637</td>\n",
       "      <td>0.7821</td>\n",
       "      <td>0.7238</td>\n",
       "      <td>0.7763</td>\n",
       "      <td>0.8037</td>\n",
       "      <td>0.7459</td>\n",
       "      <td>0.7277</td>\n",
       "      <td>0.7235</td>\n",
       "      <td>0.7714</td>\n",
       "      <td>0.7543</td>\n",
       "      <td>0.7490</td>\n",
       "      <td>0.7875</td>\n",
       "      <td>0.7875</td>\n",
       "      <td>0.7720</td>\n",
       "      <td>0.7700</td>\n",
       "      <td>0.7739</td>\n",
       "      <td>0.7607</td>\n",
       "      <td>0.7320</td>\n",
       "      <td>0.7416</td>\n",
       "      <td>0.7463</td>\n",
       "      <td>0.7344</td>\n",
       "      <td>0.7218</td>\n",
       "      <td>0.7317</td>\n",
       "      <td>0.7358</td>\n",
       "      <td>0.7239</td>\n",
       "      <td>0.7200</td>\n",
       "      <td>0.6981</td>\n",
       "      <td>0.6862</td>\n",
       "      <td>0.6744</td>\n",
       "      <td>0.6623</td>\n",
       "      <td>0.6498</td>\n",
       "      <td>0.6400</td>\n",
       "      <td>0.6347</td>\n",
       "      <td>0.6218</td>\n",
       "      <td>0.6002</td>\n",
       "      <td>0.5751</td>\n",
       "      <td>0.5501</td>\n",
       "      <td>0.5325</td>\n",
       "      <td>0.5100</td>\n",
       "      <td>0.4823</td>\n",
       "      <td>0.4473</td>\n",
       "      <td>0.4207</td>\n",
       "      <td>0.3974</td>\n",
       "      <td>0.3719</td>\n",
       "      <td>0.3399</td>\n",
       "      <td>0.2880</td>\n",
       "      <td>0.2446</td>\n",
       "      <td>0.2035</td>\n",
       "      <td>0.1694</td>\n",
       "      <td>0.1310</td>\n",
       "      <td>0.0523</td>\n",
       "      <td>0.0123</td>\n",
       "      <td>0.1211</td>\n",
       "      <td>0.1382</td>\n",
       "      <td>0.0167</td>\n",
       "      <td>-0.2306</td>\n",
       "      <td>-0.3201</td>\n",
       "      <td>-0.3489</td>\n",
       "      <td>-0.3714</td>\n",
       "      <td>-0.3235</td>\n",
       "      <td>-0.2919</td>\n",
       "      <td>-0.1607</td>\n",
       "      <td>-0.3413</td>\n",
       "      <td>1.5163</td>\n",
       "      <td>0.7945</td>\n",
       "      <td>0.4161</td>\n",
       "      <td>-0.4016</td>\n",
       "      <td>-0.8242</td>\n",
       "      <td>0.5640</td>\n",
       "      <td>0.2757</td>\n",
       "      <td>-1.1756</td>\n",
       "      <td>0.0428</td>\n",
       "      <td>0.0477</td>\n",
       "      <td>0.2596</td>\n",
       "      <td>-1.9472</td>\n",
       "      <td>-1.0713</td>\n",
       "      <td>-1.6992</td>\n",
       "      <td>-0.1566</td>\n",
       "      <td>-1.1031</td>\n",
       "      <td>-0.0539</td>\n",
       "      <td>-0.2003</td>\n",
       "      <td>-0.0763</td>\n",
       "      <td>-0.1077</td>\n",
       "      <td>-0.1133</td>\n",
       "      <td>-2.8334</td>\n",
       "      <td>-2.0722</td>\n",
       "      <td>0.5945</td>\n",
       "      <td>-0.3713</td>\n",
       "      <td>1.0170</td>\n",
       "      <td>0.6676</td>\n",
       "      <td>0.1627</td>\n",
       "      <td>0.3745</td>\n",
       "      <td>0.1491</td>\n",
       "      <td>0.1276</td>\n",
       "      <td>-0.2089</td>\n",
       "      <td>-0.3634</td>\n",
       "      <td>-0.1951</td>\n",
       "      <td>-0.2685</td>\n",
       "      <td>-0.2748</td>\n",
       "      <td>-0.3269</td>\n",
       "      <td>-0.0844</td>\n",
       "      <td>0.2059</td>\n",
       "      <td>0.2432</td>\n",
       "      <td>0.0292</td>\n",
       "      <td>0.0289</td>\n",
       "      <td>0.0508</td>\n",
       "      <td>-0.1335</td>\n",
       "      <td>-0.2823</td>\n",
       "      <td>-0.2359</td>\n",
       "      <td>-0.1733</td>\n",
       "      <td>-0.1414</td>\n",
       "      <td>-0.1132</td>\n",
       "      <td>-0.1415</td>\n",
       "      <td>-0.1036</td>\n",
       "      <td>-0.0980</td>\n",
       "      <td>-0.0297</td>\n",
       "      <td>0.0462</td>\n",
       "      <td>0.0647</td>\n",
       "      <td>0.0460</td>\n",
       "      <td>0.0037</td>\n",
       "      <td>-0.1111</td>\n",
       "      <td>-0.1373</td>\n",
       "      <td>-0.1500</td>\n",
       "      <td>-0.1466</td>\n",
       "      <td>-0.1295</td>\n",
       "      <td>-0.0729</td>\n",
       "      <td>-0.0377</td>\n",
       "      <td>-0.0111</td>\n",
       "      <td>-0.0066</td>\n",
       "      <td>0.1060</td>\n",
       "      <td>0.1300</td>\n",
       "      <td>0.1323</td>\n",
       "      <td>0.1367</td>\n",
       "      <td>0.1101</td>\n",
       "      <td>0.1653</td>\n",
       "      <td>0.1526</td>\n",
       "      <td>0.1645</td>\n",
       "      <td>0.0921</td>\n",
       "      <td>0.1654</td>\n",
       "      <td>0.1090</td>\n",
       "      <td>0.1649</td>\n",
       "      <td>0.1988</td>\n",
       "      <td>0.1692</td>\n",
       "      <td>0.1550</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1300</td>\n",
       "      <td>0.1376</td>\n",
       "      <td>0.1595</td>\n",
       "      <td>0.1984</td>\n",
       "      <td>0.1969</td>\n",
       "      <td>0.1417</td>\n",
       "      <td>0.1252</td>\n",
       "      <td>0.1457</td>\n",
       "      <td>0.1100</td>\n",
       "      <td>0.1014</td>\n",
       "      <td>0.0649</td>\n",
       "      <td>0.0500</td>\n",
       "      <td>0.0498</td>\n",
       "      <td>0.0274</td>\n",
       "      <td>0.0388</td>\n",
       "      <td>0.0674</td>\n",
       "      <td>0.0181</td>\n",
       "      <td>0.0318</td>\n",
       "      <td>0.0761</td>\n",
       "      <td>0.1227</td>\n",
       "      <td>0.1677</td>\n",
       "      <td>0.1567</td>\n",
       "      <td>0.1968</td>\n",
       "      <td>0.1754</td>\n",
       "      <td>0.1800</td>\n",
       "      <td>0.1650</td>\n",
       "      <td>0.1212</td>\n",
       "      <td>0.1261</td>\n",
       "      <td>0.1086</td>\n",
       "      <td>0.1039</td>\n",
       "      <td>0.0972</td>\n",
       "      <td>0.0990</td>\n",
       "      <td>0.1184</td>\n",
       "      <td>0.1100</td>\n",
       "      <td>0.110</td>\n",
       "      <td>0.0937</td>\n",
       "      <td>0.0917</td>\n",
       "      <td>0.0916</td>\n",
       "      <td>0.0800</td>\n",
       "      <td>0.0886</td>\n",
       "      <td>0.0838</td>\n",
       "      <td>0.1038</td>\n",
       "      <td>0.1044</td>\n",
       "      <td>0.1077</td>\n",
       "      <td>0.1198</td>\n",
       "      <td>0.1127</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.1118</td>\n",
       "      <td>0.1100</td>\n",
       "      <td>0.1176</td>\n",
       "      <td>0.1100</td>\n",
       "      <td>0.1100</td>\n",
       "      <td>0.1100</td>\n",
       "      <td>0.1000</td>\n",
       "      <td>0.0937</td>\n",
       "      <td>0.0900</td>\n",
       "      <td>0.0787</td>\n",
       "      <td>0.0660</td>\n",
       "      <td>0.0533</td>\n",
       "      <td>0.0332</td>\n",
       "      <td>0.0282</td>\n",
       "      <td>0.0159</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>-0.0119</td>\n",
       "      <td>-0.0238</td>\n",
       "      <td>-0.0367</td>\n",
       "      <td>-0.0066</td>\n",
       "      <td>-0.0169</td>\n",
       "      <td>-0.0500</td>\n",
       "      <td>-0.0500</td>\n",
       "      <td>-0.0411</td>\n",
       "      <td>-0.0557</td>\n",
       "      <td>-0.0194</td>\n",
       "      <td>0.0698</td>\n",
       "      <td>0.1009</td>\n",
       "      <td>2.0209</td>\n",
       "      <td>-1.3196</td>\n",
       "      <td>-1.8191</td>\n",
       "      <td>-0.3541</td>\n",
       "      <td>0.6238</td>\n",
       "      <td>-0.1949</td>\n",
       "      <td>-0.0158</td>\n",
       "      <td>0.6782</td>\n",
       "      <td>-1.3805</td>\n",
       "      <td>0.6455</td>\n",
       "      <td>-0.0382</td>\n",
       "      <td>0.3607</td>\n",
       "      <td>-0.2496</td>\n",
       "      <td>0.2587</td>\n",
       "      <td>0.9950</td>\n",
       "      <td>0.5458</td>\n",
       "      <td>-0.2091</td>\n",
       "      <td>0.1394</td>\n",
       "      <td>-0.1910</td>\n",
       "      <td>-0.2571</td>\n",
       "      <td>0.0133</td>\n",
       "      <td>0.1108</td>\n",
       "      <td>-0.4146</td>\n",
       "      <td>-0.0774</td>\n",
       "      <td>0.1273</td>\n",
       "      <td>-0.5142</td>\n",
       "      <td>-0.3267</td>\n",
       "      <td>0.0162</td>\n",
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       "      <td>22.5822</td>\n",
       "      <td>-8.7464</td>\n",
       "      <td>-20.9134</td>\n",
       "      <td>-20.3160</td>\n",
       "      <td>-15.8034</td>\n",
       "      <td>-12.6418</td>\n",
       "      <td>-12.3159</td>\n",
       "      <td>-7.4897</td>\n",
       "      <td>-3.7732</td>\n",
       "      <td>0.3998</td>\n",
       "      <td>4.3665</td>\n",
       "      <td>10.2211</td>\n",
       "      <td>15.6917</td>\n",
       "      <td>14.4347</td>\n",
       "      <td>10.7502</td>\n",
       "      <td>5.6659</td>\n",
       "      <td>-1.8523</td>\n",
       "      <td>-7.9920</td>\n",
       "      <td>-9.9530</td>\n",
       "      <td>-8.8905</td>\n",
       "      <td>-6.6126</td>\n",
       "      <td>-2.2098</td>\n",
       "      <td>0.9647</td>\n",
       "      <td>3.2045</td>\n",
       "      <td>5.4460</td>\n",
       "      <td>6.9972</td>\n",
       "      <td>6.8441</td>\n",
       "      <td>5.1904</td>\n",
       "      <td>3.5163</td>\n",
       "      <td>2.1237</td>\n",
       "      <td>-2.9511</td>\n",
       "      <td>-5.2330</td>\n",
       "      <td>-5.7790</td>\n",
       "      <td>-4.3519</td>\n",
       "      <td>-2.7741</td>\n",
       "      <td>-0.5727</td>\n",
       "      <td>1.6749</td>\n",
       "      <td>3.0715</td>\n",
       "      <td>2.4038</td>\n",
       "      <td>1.1223</td>\n",
       "      <td>-0.4463</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    label  acc_x_0  acc_x_1  acc_x_2  acc_x_3  acc_x_4  acc_x_5  acc_x_6  \\\n",
       "0    idle   0.0000   0.0000   0.0000   0.0000   0.0000   0.0000   0.0000   \n",
       "1  motion   0.1042   0.2377   0.2494   0.1576   0.0721   0.0231  -0.1946   \n",
       "2    step  -0.0193  -0.0174  -0.0053   0.0000   0.0000   0.0000   0.0000   \n",
       "3    idle   0.0300   0.0300   0.0300   0.0300   0.0300   0.0300   0.0300   \n",
       "4    fall   0.2156   0.2289   0.2470   0.2472   0.1967   0.0283   0.0563   \n",
       "5    idle   0.0000   0.0000   0.0000   0.0000   0.0000   0.0000   0.0000   \n",
       "6    idle   0.0200   0.0200   0.0200   0.0200   0.0200   0.0200   0.0200   \n",
       "7    fall  -0.3952  -0.4326  -0.4414  -0.4800  -0.4800  -0.4665  -0.4516   \n",
       "8  motion   0.0200   0.0200   0.0164   0.0100   0.0100   0.0100   0.0100   \n",
       "9    fall  -0.0321  -0.0054   0.0000  -0.0130  -0.0732  -0.0900  -0.1505   \n",
       "\n",
       "   acc_x_7  acc_x_8  acc_x_9  acc_x_10  acc_x_11  acc_x_12  acc_x_13  \\\n",
       "0   0.0000   0.0000   0.0000    0.0000    0.0000    0.0000    0.0000   \n",
       "1  -0.1585  -0.1443  -0.0637    0.0402    0.0603    0.0679    0.0631   \n",
       "2   0.0000  -0.0010  -0.0062    0.0000   -0.0069   -0.0197   -0.0200   \n",
       "3   0.0300   0.0300   0.0300    0.0300    0.0300    0.0300    0.0300   \n",
       "4   0.0814   0.0620   0.1771    0.1613    0.0235    0.0218    0.0078   \n",
       "5   0.0000   0.0000   0.0000    0.0000    0.0000    0.0000    0.0000   \n",
       "6   0.0200   0.0200   0.0200    0.0200    0.0200    0.0200    0.0200   \n",
       "7  -0.4311  -0.3904  -0.3667   -0.3544   -0.3445   -0.2958   -0.1829   \n",
       "8   0.0100   0.0100   0.0128    0.0159    0.0190    0.0157    0.0199   \n",
       "9  -0.2072  -0.2760  -0.2557   -0.2298   -0.3495   -0.4116   -0.4200   \n",
       "\n",
       "   acc_x_14  acc_x_15  acc_x_16  acc_x_17  acc_x_18  acc_x_19  acc_x_20  \\\n",
       "0    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000   \n",
       "1    0.0900    0.0810    0.0433   -0.0056   -0.0288   -0.0526   -0.0657   \n",
       "2   -0.0300   -0.0300   -0.0300   -0.0200   -0.0180   -0.0100   -0.0100   \n",
       "3    0.0300    0.0300    0.0300    0.0300    0.0300    0.0300    0.0300   \n",
       "4    0.0034    0.0169    0.0214    0.0283    0.0437    0.0502   -0.0134   \n",
       "5    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000   \n",
       "6    0.0200    0.0200    0.0200    0.0200    0.0200    0.0200    0.0200   \n",
       "7   -0.1791   -0.0570    0.0318    0.0554    0.1182    0.1928    0.2459   \n",
       "8    0.0155    0.0112   -0.0100   -0.0077    0.0119    0.0180    0.0200   \n",
       "9   -0.4225   -0.4168   -0.4000   -0.3882   -0.3838   -0.3900   -0.3402   \n",
       "\n",
       "   acc_x_21  acc_x_22  acc_x_23  acc_x_24  acc_x_25  acc_x_26  acc_x_27  \\\n",
       "0    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000   \n",
       "1   -0.0846   -0.0299   -0.0235   -0.0042    0.0432    0.0496    0.0200   \n",
       "2    0.0025    0.0100    0.0100    0.0100    0.0100   -0.0043   -0.0100   \n",
       "3    0.0300    0.0300    0.0300    0.0300    0.0300    0.0300    0.0300   \n",
       "4    0.0056    0.0552    0.0399    0.0432    0.0687    0.0796    0.0720   \n",
       "5    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000   \n",
       "6    0.0200    0.0200    0.0200    0.0200    0.0200    0.0200    0.0200   \n",
       "7    0.3116    0.3427    0.3546    0.4485    0.5000    0.4518    0.4108   \n",
       "8    0.0209    0.0239    0.0100    0.0100    0.0100    0.0118    0.0179   \n",
       "9   -0.2851   -0.1905   -0.1142   -0.0900   -0.0882   -0.0500   -0.0349   \n",
       "\n",
       "   acc_x_28  acc_x_29  acc_x_30  acc_x_31  acc_x_32  acc_x_33  acc_x_34  \\\n",
       "0    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000   \n",
       "1   -0.0009   -0.0084   -0.0345   -0.0343   -0.0370   -0.0226   -0.0288   \n",
       "2   -0.0011    0.0011    0.0139    0.0200    0.0103   -0.0021   -0.0134   \n",
       "3    0.0300    0.0300    0.0300    0.0300    0.0300    0.0300    0.0300   \n",
       "4    0.0776    0.0720    0.0487    0.0543    0.0198    0.0176    0.0490   \n",
       "5    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000   \n",
       "6    0.0200    0.0200    0.0200    0.0200    0.0200    0.0200    0.0200   \n",
       "7    0.4217    0.4024    0.3747    0.3754    0.4122    0.4176    0.4003   \n",
       "8    0.0113    0.0200    0.0200    0.0200    0.0200    0.0165    0.0123   \n",
       "9    0.0028    0.1101    0.2088    0.3974    0.2992    0.3109    0.4000   \n",
       "\n",
       "   acc_x_35  acc_x_36  acc_x_37  acc_x_38  acc_x_39  acc_x_40  acc_x_41  \\\n",
       "0    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000   \n",
       "1   -0.0107   -0.0181   -0.0113   -0.0156   -0.0373   -0.0560   -0.0422   \n",
       "2   -0.0200   -0.0111   -0.0074   -0.0044   -0.0015   -0.0170   -0.0182   \n",
       "3    0.0300    0.0300    0.0300    0.0300    0.0300    0.0300    0.0300   \n",
       "4    0.0173    0.0052    0.0201    0.0210    0.0064    0.0165   -0.0171   \n",
       "5    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000   \n",
       "6    0.0200    0.0200    0.0200    0.0200    0.0200    0.0200    0.0200   \n",
       "7    0.4242    0.4400    0.4272    0.4100    0.4100    0.4017    0.3845   \n",
       "8    0.0100    0.0100    0.0100    0.0121    0.0180    0.0200    0.0200   \n",
       "9    0.4363    0.3747    0.3482    0.4134    0.4200    0.4289    0.4345   \n",
       "\n",
       "   acc_x_42  acc_x_43  acc_x_44  acc_x_45  acc_x_46  acc_x_47  acc_x_48  \\\n",
       "0    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000   \n",
       "1   -0.0489   -0.0594   -0.0670   -0.0472   -0.1017   -0.1278   -0.0910   \n",
       "2   -0.0148   -0.0273    0.0200    0.0273    0.0400    0.0194   -0.0075   \n",
       "3    0.0300    0.0300    0.0300    0.0300    0.0300    0.0300    0.0300   \n",
       "4   -0.0162   -0.0025    0.0291    0.0128   -0.0287   -0.0071   -0.0119   \n",
       "5    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000   \n",
       "6    0.0200    0.0200    0.0200    0.0200    0.0200    0.0200    0.0200   \n",
       "7    0.3731    0.4200    0.4200    0.4200    0.4100    0.4074    0.3847   \n",
       "8    0.0200    0.0200    0.0200    0.0190    0.0161    0.0271    0.0209   \n",
       "9    0.4575    0.4700    0.4298    0.4042    0.4300    0.4364    0.4220   \n",
       "\n",
       "   acc_x_49  acc_x_50  acc_x_51  acc_x_52  acc_x_53  acc_x_54  acc_x_55  \\\n",
       "0    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000   \n",
       "1   -0.0120   -0.0469   -0.1495   -0.1059   -0.0600   -0.0588    0.0463   \n",
       "2   -0.0481   -0.0336   -0.0213   -0.0021    0.0545    0.0287    0.0100   \n",
       "3    0.0300    0.0300    0.0300    0.0300    0.0300    0.0300    0.0300   \n",
       "4   -0.0172    0.0141    0.0249    0.0041   -0.0488   -0.0420   -0.0060   \n",
       "5    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000   \n",
       "6    0.0200    0.0200    0.0200    0.0200    0.0200    0.0200    0.0200   \n",
       "7    0.3546    0.3500    0.3500    0.3467    0.3340    0.3300    0.3288   \n",
       "8    0.0184    0.0100    0.0100    0.0100    0.0153    0.0185    0.0118   \n",
       "9    0.4347    0.4600    0.4431    0.4382    0.4483    0.4400    0.4461   \n",
       "\n",
       "   acc_x_56  acc_x_57  acc_x_58  acc_x_59  acc_x_60  acc_x_61  acc_x_62  \\\n",
       "0    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000   \n",
       "1    0.0624    0.0332   -0.0703    0.0356    0.1770    0.2823    0.2136   \n",
       "2    0.0100   -0.0203   -0.0263   -0.0213   -0.0247   -0.0280    0.0083   \n",
       "3    0.0300    0.0300    0.0300    0.0300    0.0300    0.0300    0.0300   \n",
       "4   -0.0229   -0.0561   -0.0309    0.0345    0.0050   -0.0356   -0.0131   \n",
       "5    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000   \n",
       "6    0.0200    0.0200    0.0200    0.0200    0.0200    0.0200    0.0200   \n",
       "7    0.3159    0.3029    0.2823    0.2564    0.2225    0.2040    0.1908   \n",
       "8    0.0000    0.0000    0.0231    0.0300    0.0300    0.0195    0.0131   \n",
       "9    0.4414    0.4362    0.4162    0.4100    0.4100    0.4100    0.4100   \n",
       "\n",
       "   acc_x_63  acc_x_64  acc_x_65  acc_x_66  acc_x_67  acc_x_68  acc_x_69  \\\n",
       "0    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000   \n",
       "1    0.1498    0.1973    0.1919    0.2628    0.2217    0.2501    0.0744   \n",
       "2    0.0029    0.0083    0.0139    0.0200   -0.0396   -0.0306   -0.1003   \n",
       "3    0.0300    0.0300    0.0300    0.0300    0.0300    0.0300    0.0300   \n",
       "4   -0.1051   -0.0893   -0.0565   -0.0847   -0.0925   -0.0686    0.0037   \n",
       "5    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000   \n",
       "6    0.0200    0.0200    0.0200    0.0200    0.0200    0.0200    0.0200   \n",
       "7    0.1878    0.1700    0.4331    0.4210    0.3009    0.2068    0.1379   \n",
       "8    0.0000    0.0000    0.0054    0.0115    0.0179    0.0158    0.0100   \n",
       "9    0.4047    0.4000    0.3901    0.3700    0.3700    0.3625    0.3600   \n",
       "\n",
       "   acc_x_70  acc_x_71  acc_x_72  acc_x_73  acc_x_74  acc_x_75  acc_x_76  \\\n",
       "0    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000   \n",
       "1   -0.0098   -0.0809   -0.1247   -0.1046   -0.0800   -0.0603   -0.0400   \n",
       "2   -0.0696   -0.0456    0.0187    0.0025   -0.0100   -0.0100   -0.0075   \n",
       "3    0.0300    0.0300    0.0300    0.0300    0.0300    0.0300    0.0300   \n",
       "4    0.0115   -0.0484    0.0347   -0.0341    0.0013    0.0466    0.0244   \n",
       "5    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000   \n",
       "6    0.0200    0.0200    0.0200    0.0200    0.0200    0.0200    0.0200   \n",
       "7    0.0805    0.0058   -0.0414    3.1803   -3.7103    0.9723    1.5738   \n",
       "8    0.0100    0.0100    0.0100    0.0100    0.0100    0.0100    0.0181   \n",
       "9    0.3474    0.3337    0.3300    0.3200    0.3200    0.3133    0.3016   \n",
       "\n",
       "   acc_x_77  acc_x_78  acc_x_79  acc_x_80  acc_x_81  acc_x_82  acc_x_83  \\\n",
       "0    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000   \n",
       "1   -0.0400   -0.0988   -0.1565   -0.1358   -0.1256   -0.1342   -0.1352   \n",
       "2    0.0394    0.0200    0.0346    0.0000    0.0025   -0.0048   -0.0342   \n",
       "3    0.0300    0.0300    0.0300    0.0300    0.0300    0.0300    0.0300   \n",
       "4   -0.0381    0.0527    0.0506    0.6145    0.0286    0.0969    0.0441   \n",
       "5    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000   \n",
       "6    0.0200    0.0200    0.0200    0.0200    0.0200    0.0200    0.0200   \n",
       "7   -1.6971    1.4719    3.7484    0.3814   -1.1177    0.5879    1.7932   \n",
       "8    0.0200    0.0200    0.0200    0.0200    0.0200    0.0100    0.0100   \n",
       "9    0.2782    0.2659    0.2547    0.2403    0.2161    0.1962    0.2977   \n",
       "\n",
       "   acc_x_84  acc_x_85  acc_x_86  acc_x_87  acc_x_88  acc_x_89  acc_x_90  \\\n",
       "0    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000   \n",
       "1   -0.1158   -0.0835   -0.0981   -0.1378   -0.1182   -0.1120   -0.1257   \n",
       "2   -0.0487   -0.0265   -0.0084    0.0066    0.0009   -0.0338   -0.0072   \n",
       "3    0.0300    0.0300    0.0300    0.0300    0.0300    0.0300    0.0300   \n",
       "4    0.0471    0.1057    0.0193    0.0515    0.0593   -0.0302    0.0456   \n",
       "5    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000   \n",
       "6    0.0200    0.0200    0.0200    0.0200    0.0200    0.0200    0.0200   \n",
       "7   -1.0660    1.0439    1.0806    1.6168    1.6826    1.4763    0.2665   \n",
       "8    0.0143    0.0206    0.0265    0.0140    0.0100    0.0100    0.0100   \n",
       "9    0.4671    0.3192    0.2362    0.2059    0.0991    0.0729    0.0900   \n",
       "\n",
       "   acc_x_91  acc_x_92  acc_x_93  acc_x_94  acc_x_95  acc_x_96  acc_x_97  \\\n",
       "0    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000   \n",
       "1   -0.1172   -0.0614    0.0092    0.0143    0.0002    0.0068   -0.0269   \n",
       "2    0.0094    0.0205    0.0233    0.0052    0.0079    0.0030   -0.0028   \n",
       "3    0.0300    0.0300    0.0300    0.0300    0.0300    0.0300    0.0300   \n",
       "4    0.1648    0.0942   -0.0272   -0.0224   -0.0194    0.0540    0.0995   \n",
       "5    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000    0.0000   \n",
       "6    0.0200    0.0200    0.0200    0.0200    0.0200    0.0200    0.0200   \n",
       "7   -0.3387   -0.0817    0.2486   -0.0671    0.6700    1.8158    3.0321   \n",
       "8    0.0100    0.0183    0.0148    0.0100    0.0100    0.0100    0.0193   \n",
       "9    0.1788    1.2231   -3.1572    2.2542    0.6963   -1.9330    2.9862   \n",
       "\n",
       "   acc_x_98  acc_x_99  acc_x_100  acc_x_101  acc_x_102  acc_x_103  acc_x_104  \\\n",
       "0    0.0000    0.0000     0.0000     0.0000     0.0000     0.0000     0.0000   \n",
       "1   -0.1106   -0.1432     0.0305     0.0931    -0.0537    -0.3284    -0.2447   \n",
       "2   -0.0100   -0.0040     0.0096    -0.0018    -0.0072     0.0000     0.0191   \n",
       "3    0.0300    0.0300     0.0300     0.0300     0.0300     0.0300     0.0300   \n",
       "4    0.0669    0.0424     0.0610     0.0898     0.0497     0.0168    -0.0017   \n",
       "5    0.0000    0.0000     0.0000     0.0000     0.0000     0.0000     0.0000   \n",
       "6    0.0200    0.0200     0.0200     0.0200     0.0200     0.0200     0.0200   \n",
       "7    0.0417    1.4182    -0.2683     1.8381     1.6559     1.5450     0.8560   \n",
       "8    0.0200    0.0200     0.0200     0.0200     0.0200     0.0200     0.0200   \n",
       "9    3.2916   -0.8835    -0.4453     1.9314    -0.3920    -1.3641    -0.0055   \n",
       "\n",
       "   acc_x_105  acc_x_106  acc_x_107  acc_x_108  acc_x_109  acc_x_110  \\\n",
       "0     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000   \n",
       "1    -0.0407    -0.2483    -0.1395    -0.0541    -0.0754    -0.1336   \n",
       "2     0.0293     0.0262     0.0122    -0.0177    -0.0280    -0.0164   \n",
       "3     0.0300     0.0300     0.0300     0.0209     0.0300     0.0300   \n",
       "4     0.0061     0.0070     0.0442    -0.0326     0.0122     0.0070   \n",
       "5     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000   \n",
       "6     0.0200     0.0200     0.0200     0.0200     0.0200     0.0200   \n",
       "7     1.2654     1.4480     0.6838     0.8201     1.1768     0.9955   \n",
       "8     0.0200     0.0200     0.0200     0.0200     0.0100     0.0037   \n",
       "9     1.2515     2.0445     2.1074     0.9936     1.0484     0.4864   \n",
       "\n",
       "   acc_x_111  acc_x_112  acc_x_113  acc_x_114  acc_x_115  acc_x_116  \\\n",
       "0     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000   \n",
       "1    -0.1317    -0.1649    -0.0779    -0.1000    -0.1064    -0.0621   \n",
       "2    -0.0033     0.0074     0.0047     0.0000     0.0000    -0.0249   \n",
       "3     0.0300     0.0300     0.0300     0.0300     0.0300     0.0300   \n",
       "4     0.0244     0.0049     0.0140     0.0384     0.0417    -0.0502   \n",
       "5     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000   \n",
       "6     0.0200     0.0200     0.0200     0.0200     0.0200     0.0200   \n",
       "7     0.5799     1.0700     1.1702     0.8977     0.9385     1.1747   \n",
       "8     0.0203     0.0300     0.0300     0.0300     0.0300     0.0300   \n",
       "9    -0.1553     0.0606     0.1715     0.4141     3.0427     0.6493   \n",
       "\n",
       "   acc_x_117  acc_x_118  acc_x_119  acc_x_120  acc_x_121  acc_x_122  \\\n",
       "0     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000   \n",
       "1    -0.0688    -0.0546    -0.0703    -0.0773    -0.0562    -0.0561   \n",
       "2    -0.0427    -0.0557    -0.0437    -0.0179     0.0122     0.0146   \n",
       "3     0.0300     0.0300     0.0300     0.0300     0.0300     0.0300   \n",
       "4     0.0301    -0.0318    -0.0479    -0.0580    -0.0114    -0.0569   \n",
       "5     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000   \n",
       "6     0.0200     0.0200     0.0200     0.0200     0.0200     0.0200   \n",
       "7     1.2441     1.1909     0.9418     1.0822     1.0539     0.9370   \n",
       "8     0.0200     0.0200     0.0140     0.0100     0.0200     0.0200   \n",
       "9     2.1668     0.5816     0.9496     1.3707     1.0946     1.2592   \n",
       "\n",
       "   acc_x_123  acc_x_124  acc_x_125  acc_x_126  acc_x_127  acc_x_128  \\\n",
       "0     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000   \n",
       "1    -0.0356     0.0239     0.0058    -0.0100     0.0327     0.0529   \n",
       "2     0.0032     0.0000     0.0000     0.0000    -0.0079    -0.0100   \n",
       "3     0.0300     0.0300     0.0300     0.0300     0.0300     0.0300   \n",
       "4    -0.0728    -0.0383    -0.0115    -0.0223     0.0309     0.0664   \n",
       "5     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000   \n",
       "6     0.0200     0.0200     0.0200     0.0200     0.0200     0.0200   \n",
       "7     1.0300     0.9400     0.9579     1.0896     0.8613     0.9107   \n",
       "8     0.0141     0.0100     0.0100     0.0100     0.0100     0.0100   \n",
       "9     1.0064     0.9132     0.9403     0.9980     0.9446     0.9510   \n",
       "\n",
       "   acc_x_129  acc_x_130  acc_x_131  acc_x_132  acc_x_133  acc_x_134  \\\n",
       "0     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000   \n",
       "1     0.0426     0.0561     0.1388     0.1143     0.0486     0.1510   \n",
       "2    -0.0100    -0.0151    -0.0127    -0.0003     0.0040    -0.0100   \n",
       "3     0.0300     0.0300     0.0300     0.0300     0.0300     0.0300   \n",
       "4     0.0038    -0.0264    -0.0085    -0.0446    -0.0282     0.0069   \n",
       "5     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000   \n",
       "6     0.0200     0.0200     0.0200     0.0200     0.0200     0.0200   \n",
       "7     0.9886     0.7705     0.8644     0.8416     0.8712     0.9100   \n",
       "8     0.0100     0.0200     0.0200     0.0154     0.0100     0.0100   \n",
       "9     0.8314     1.0264     1.0513     1.1290     1.1528     1.0008   \n",
       "\n",
       "   acc_x_135  acc_x_136  acc_x_137  acc_x_138  acc_x_139  acc_x_140  \\\n",
       "0     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000   \n",
       "1    -0.1230    -0.1999     0.5312     0.0671    -0.0061     0.0293   \n",
       "2    -0.0100    -0.0098     0.0021     0.0100     0.0100     0.0100   \n",
       "3     0.0300     0.0300     0.0300     0.0300     0.0300     0.0300   \n",
       "4     0.0121    -0.0026     0.0235    -0.0083    -0.0232    -0.0335   \n",
       "5     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000   \n",
       "6     0.0200     0.0200     0.0200     0.0200     0.0200     0.0200   \n",
       "7     0.9597     0.9235     0.9500     0.9112     0.8529     0.9431   \n",
       "8     0.0100     0.0127     0.0171     0.0160     0.0036     0.0045   \n",
       "9     1.1264     0.9842     1.0436     1.0279     0.9571     0.9978   \n",
       "\n",
       "   acc_x_141  acc_x_142  acc_x_143  acc_x_144  acc_x_145  acc_x_146  \\\n",
       "0     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000   \n",
       "1     0.1165     0.1923     0.0290    -0.0468    -0.0852     0.0085   \n",
       "2    -0.0017    -0.0208    -0.0365    -0.0400    -0.0400    -0.0400   \n",
       "3     0.0300     0.0300     0.0300     0.0300     0.0300     0.0300   \n",
       "4    -0.0265    -0.0126    -0.0029     0.0144    -0.0281    -0.0327   \n",
       "5     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000   \n",
       "6     0.0200     0.0200     0.0200     0.0200     0.0200     0.0200   \n",
       "7     1.1640     1.1614     1.0901     1.1636     1.0115     0.9988   \n",
       "8     0.0096     0.0060     0.0025    -0.0010    -0.0046    -0.0081   \n",
       "9     1.0168     1.0306     0.9277     1.0021     1.1170     1.0314   \n",
       "\n",
       "   acc_x_147  acc_x_148  acc_x_149  acc_x_150  acc_x_151  acc_x_152  \\\n",
       "0     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000   \n",
       "1     0.1262     0.2682     0.2969     0.2172    -0.0109     0.1839   \n",
       "2    -0.0400    -0.0385     0.0128     0.0200     0.0126     0.0100   \n",
       "3     0.0300     0.0300     0.0300     0.0300     0.0300     0.0300   \n",
       "4    -0.0306    -0.0554     0.0671     0.0185     0.0000    -0.0012   \n",
       "5     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000   \n",
       "6     0.0200     0.0200     0.0200     0.0200     0.0200     0.0200   \n",
       "7     1.0340     0.9940     1.0333     1.0255     1.0322     1.0315   \n",
       "8     0.0066     0.0100     0.0100     0.0100     0.0100     0.0100   \n",
       "9     0.9002     0.8700     0.8390     0.8311     0.8944     0.9300   \n",
       "\n",
       "   acc_x_153  acc_x_154  acc_x_155  acc_x_156  acc_x_157  acc_x_158  \\\n",
       "0     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000   \n",
       "1     0.2604     0.3814     0.3131    -0.0096     0.0693     0.0829   \n",
       "2     0.0100     0.0087     0.0056     0.0025    -0.0078    -0.0248   \n",
       "3     0.0300     0.0300     0.0300     0.0300     0.0300     0.0300   \n",
       "4     0.0256     0.0114     0.0065     0.0326     0.0232     0.0066   \n",
       "5     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000   \n",
       "6     0.0200     0.0200     0.0200     0.0200     0.0200     0.0200   \n",
       "7     1.0200     1.0116     1.0584     1.0800     1.0681     1.0429   \n",
       "8    -0.0057     0.0227     0.0341     0.0179     0.0316     0.0225   \n",
       "9     0.9398     0.9334     0.9662     1.0182     1.0523     1.0833   \n",
       "\n",
       "   acc_x_159  acc_y_0  acc_y_1  acc_y_2  acc_y_3  acc_y_4  acc_y_5  acc_y_6  \\\n",
       "0     0.0000  -1.0100  -1.0100  -1.0100  -1.0100  -1.0100  -1.0100  -1.0100   \n",
       "1     0.2605  -1.1032  -0.9968  -0.9618  -0.9952  -0.9807  -1.0038  -0.9849   \n",
       "2    -0.0249  -1.0100  -1.0174  -1.0100  -1.0100  -1.0100  -1.0100  -1.0155   \n",
       "3     0.0300   0.9704   0.9800   0.9800   0.9730   0.9799   0.9716   0.9774   \n",
       "4     0.0204   1.0828   1.0693   1.0165   1.0265   1.0489   0.9818   1.0671   \n",
       "5     0.0000  -1.0100  -1.0100  -1.0100  -1.0100  -1.0100  -1.0100  -1.0100   \n",
       "6     0.0200   0.9800   0.9800   0.9800   0.9800   0.9800   0.9800   0.9800   \n",
       "7     1.0096   1.1229   1.1525   1.0993   1.1057   1.0822   1.1025   1.1274   \n",
       "8     0.0144   0.9800   0.9800   0.9800   0.9800   0.9800   0.9800   0.9800   \n",
       "9     1.0868   0.9900   1.0254   1.0177   1.0035   1.0166   1.0673   1.0700   \n",
       "\n",
       "   acc_y_7  acc_y_8  acc_y_9  acc_y_10  acc_y_11  acc_y_12  acc_y_13  \\\n",
       "0  -1.0100  -1.0100  -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   \n",
       "1  -1.0371  -1.0085  -1.0100   -1.0099   -0.9965   -0.9942   -1.0038   \n",
       "2  -1.0130  -1.0190  -1.0138   -1.0137   -1.0169   -1.0103   -1.0197   \n",
       "3   0.9800   0.9702   0.9800    0.9800    0.9800    0.9800    0.9800   \n",
       "4   1.0416   0.9958   1.0889    0.8924    0.9150    1.0966    1.1236   \n",
       "5  -1.0100  -1.0100  -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   \n",
       "6   0.9800   0.9800   0.9800    0.9800    0.9800    0.9800    0.9800   \n",
       "7   1.1111   1.0822   1.0700    1.0466    1.0455    1.0158    0.8880   \n",
       "8   0.9800   0.9800   0.9800    0.9800    0.9800    0.9800    0.9799   \n",
       "9   1.0791   0.9641   1.1234    1.0498    1.1053    1.1088    1.1192   \n",
       "\n",
       "   acc_y_14  acc_y_15  acc_y_16  acc_y_17  acc_y_18  acc_y_19  acc_y_20  \\\n",
       "0   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   \n",
       "1   -0.9916   -1.0023   -1.0100   -1.0144   -1.0088   -1.0158   -1.0114   \n",
       "2   -1.0100   -1.0100   -1.0100   -1.0090   -1.0020   -1.0022   -1.0098   \n",
       "3    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800   \n",
       "4    1.0414    0.8953    1.1640    0.7625    0.8148    0.8046    0.6681   \n",
       "5   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   \n",
       "6    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800   \n",
       "7    0.9458    0.8700    0.8543    0.8191    0.7809    0.7893    0.7832   \n",
       "8    0.9755    0.9712    0.9700    0.9789    0.9681    0.9620    0.9785   \n",
       "9    1.1025    1.0844    1.0900    1.0845    1.0638    1.0700    1.0629   \n",
       "\n",
       "   acc_y_21  acc_y_22  acc_y_23  acc_y_24  acc_y_25  acc_y_26  acc_y_27  \\\n",
       "0   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   \n",
       "1   -0.9967   -1.0100   -1.0100   -1.0153   -0.9932   -0.9996   -1.0250   \n",
       "2   -1.0025   -1.0047   -1.0056   -0.9905   -0.9985   -0.9957   -0.9973   \n",
       "3    0.9800    0.9775    0.9712    0.9800    0.9800    0.9800    0.9720   \n",
       "4    0.7961    0.8219    0.9257    0.7194    0.9129    0.7050    0.6752   \n",
       "5   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   \n",
       "6    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800   \n",
       "7    0.7855    0.7653    0.7162    0.7571    0.7873    0.7514    0.6816   \n",
       "8    0.9791    0.9730    0.9800    0.9800    0.9800    0.9800    0.9800   \n",
       "9    1.0457    0.9717    0.9655    0.9328    0.9418    0.9714    0.9450   \n",
       "\n",
       "   acc_y_28  acc_y_29  acc_y_30  acc_y_31  acc_y_32  acc_y_33  acc_y_34  \\\n",
       "0   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   \n",
       "1   -1.0091   -1.0016   -1.0200   -1.0257   -1.0230   -1.0148   -1.0024   \n",
       "2   -0.9911   -0.9900   -0.9939   -0.9953   -0.9997   -0.9942   -1.0066   \n",
       "3    0.9800    0.9769    0.9751    0.9800    0.9800    0.9800    0.9800   \n",
       "4    0.8345    0.6821    0.6611    0.7067    0.6509    0.7194    0.5705   \n",
       "5   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   \n",
       "6    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800   \n",
       "7    0.7017    0.7031    0.6923    0.7036    0.7322    0.7313    0.7006   \n",
       "8    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800   \n",
       "9    0.9248    0.9089    0.8200    0.7637    0.7821    0.7238    0.7763   \n",
       "\n",
       "   acc_y_35  acc_y_36  acc_y_37  acc_y_38  acc_y_39  acc_y_40  acc_y_41  \\\n",
       "0   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   \n",
       "1   -0.9766   -1.0444   -1.0238   -1.0124   -0.9968   -1.0121   -0.9978   \n",
       "2   -0.9842   -0.9978   -0.9948   -0.9889   -0.9830   -0.9959   -1.0210   \n",
       "3    0.9800    0.9800    0.9780    0.9745    0.9800    0.9800    0.9800   \n",
       "4    0.5793    0.4811    0.4958    0.5049    0.4332    0.4413    0.4230   \n",
       "5   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   \n",
       "6    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800   \n",
       "7    0.7121    0.7159    0.7036    0.6700    0.6668    0.6517    0.6372   \n",
       "8    0.9800    0.9800    0.9800    0.9800    0.9800    0.9790    0.9771   \n",
       "9    0.8037    0.7459    0.7277    0.7235    0.7714    0.7543    0.7490   \n",
       "\n",
       "   acc_y_42  acc_y_43  acc_y_44  acc_y_45  acc_y_46  acc_y_47  acc_y_48  \\\n",
       "0   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   \n",
       "1   -0.9911   -0.9900   -1.0470   -1.0272   -0.9681   -0.9927   -1.0368   \n",
       "2   -0.9800   -0.9800   -0.9988   -0.9827   -0.9439   -0.9269   -0.9913   \n",
       "3    0.9751    0.9781    0.9800    0.9800    0.9800    0.9720    0.9800   \n",
       "4    0.3983    0.3409    0.3161    0.3046    0.2813    0.3452    0.2759   \n",
       "5   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   \n",
       "6    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800   \n",
       "7    0.6315    0.6375    0.6258    0.6036    0.5983    0.5847    0.5509   \n",
       "8    0.9753    0.9735    0.9717    0.9710    0.9800    0.9800    0.9800   \n",
       "9    0.7875    0.7875    0.7720    0.7700    0.7739    0.7607    0.7320   \n",
       "\n",
       "   acc_y_49  acc_y_50  acc_y_51  acc_y_52  acc_y_53  acc_y_54  acc_y_55  \\\n",
       "0   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   \n",
       "1   -1.0925   -1.0143   -0.9800   -0.9800   -1.0057   -0.9815   -1.0590   \n",
       "2   -1.0242   -1.0319   -0.9977   -0.9588   -1.0264   -0.9674   -0.9894   \n",
       "3    0.9800    0.9800    0.9879    0.9804    0.9658    0.9775    0.9711   \n",
       "4    0.2117    0.1961    0.1936    0.2035    0.1359    0.1170    0.1025   \n",
       "5   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   \n",
       "6    0.9800    0.9800    0.9800    0.9800    0.9728    0.9800    0.9800   \n",
       "7    0.5091    0.4912    0.4795    0.4534    0.4219    0.4017    0.3675   \n",
       "8    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800   \n",
       "9    0.7416    0.7463    0.7344    0.7218    0.7317    0.7358    0.7239   \n",
       "\n",
       "   acc_y_56  acc_y_57  acc_y_58  acc_y_59  acc_y_60  acc_y_61  acc_y_62  \\\n",
       "0   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   \n",
       "1   -1.0143   -0.9924   -0.9149   -1.0639   -1.1192   -1.0400   -1.0400   \n",
       "2   -0.9910   -1.0281   -1.0012   -1.0673   -1.0607   -1.0541   -1.0100   \n",
       "3    0.9800    0.9800    0.9800    0.9800    0.9701    0.9700    0.9752   \n",
       "4    0.1555    0.0309    0.2072    0.1048   -0.0452    0.1364    0.1555   \n",
       "5   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   \n",
       "6    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800   \n",
       "7    0.3418    0.3087    0.2469    0.1952    0.1487    0.1059    0.0624   \n",
       "8    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800   \n",
       "9    0.7200    0.6981    0.6862    0.6744    0.6623    0.6498    0.6400   \n",
       "\n",
       "   acc_y_63  acc_y_64  acc_y_65  acc_y_66  acc_y_67  acc_y_68  acc_y_69  \\\n",
       "0   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   \n",
       "1   -0.9495   -1.0069   -0.8398   -0.9543   -1.0308   -1.0450   -0.9157   \n",
       "2   -1.0100   -1.0898   -0.9387   -0.9530   -0.9000   -1.0259   -1.0266   \n",
       "3    0.9721    0.9752    0.9800    0.9800    0.9764    0.9700    0.9800   \n",
       "4    0.0375    0.3831   -0.0203    0.1198    0.0438    0.1325    0.1399   \n",
       "5   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   \n",
       "6    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800   \n",
       "7   -0.0245    0.0657    0.1748    0.1599    0.0118   -0.2830   -0.3840   \n",
       "8    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800   \n",
       "9    0.6347    0.6218    0.6002    0.5751    0.5501    0.5325    0.5100   \n",
       "\n",
       "   acc_y_70  acc_y_71  acc_y_72  acc_y_73  acc_y_74  acc_y_75  acc_y_76  \\\n",
       "0   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   \n",
       "1   -0.9465   -0.9615   -0.9800   -0.9800   -0.9900   -1.0031   -1.0184   \n",
       "2   -1.0200   -0.9577   -1.0974   -0.9513   -1.0837   -1.0407   -0.9367   \n",
       "3    0.9800    0.9724    0.9798    0.9726    0.9748    0.9778    0.9800   \n",
       "4   -0.0194    0.1306   -0.0038    0.0125    0.0534    0.0162   -0.0321   \n",
       "5   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   \n",
       "6    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800   \n",
       "7   -0.3406   -0.3214   -0.3537    1.4810   -1.9643    0.5928    1.0251   \n",
       "8    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800   \n",
       "9    0.4823    0.4473    0.4207    0.3974    0.3719    0.3399    0.2880   \n",
       "\n",
       "   acc_y_77  acc_y_78  acc_y_79  acc_y_80  acc_y_81  acc_y_82  acc_y_83  \\\n",
       "0   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   \n",
       "1   -1.0361   -1.0592   -1.0535   -1.0742   -1.1060   -1.0844   -1.0332   \n",
       "2   -0.9626   -1.0461   -1.0000   -0.9540   -1.0576   -1.0447   -1.0417   \n",
       "3    0.9769    0.9754    0.9800    0.9800    0.9712    0.9800    0.9763   \n",
       "4   -0.0001   -0.0513   -0.0977   -0.0145   -0.0782   -0.0521   -0.1078   \n",
       "5   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   \n",
       "6    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800   \n",
       "7    1.0354    0.5489   -0.9177   -0.1442    0.5623   -0.1055   -0.5242   \n",
       "8    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800   \n",
       "9    0.2446    0.2035    0.1694    0.1310    0.0523    0.0123    0.1211   \n",
       "\n",
       "   acc_y_84  acc_y_85  acc_y_86  acc_y_87  acc_y_88  acc_y_89  acc_y_90  \\\n",
       "0   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   \n",
       "1   -1.0461   -1.0570   -1.0754   -1.0603   -1.0446   -1.0261   -1.0100   \n",
       "2   -0.9345   -1.0490   -1.0471   -1.0063   -1.0472   -1.0087   -1.0117   \n",
       "3    0.9702    0.9730    0.9800    0.9800    0.9774    0.9800    0.9800   \n",
       "4   -0.1423   -0.0788    0.4198   -0.1609   -0.1763   -0.1815   -0.1540   \n",
       "5   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   \n",
       "6    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800   \n",
       "7    0.3183    0.1980   -1.2197   -1.5891   -1.6211   -1.9883    0.0566   \n",
       "8    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800   \n",
       "9    0.1382    0.0167   -0.2306   -0.3201   -0.3489   -0.3714   -0.3235   \n",
       "\n",
       "   acc_y_91  acc_y_92  acc_y_93  acc_y_94  acc_y_95  acc_y_96  acc_y_97  \\\n",
       "0   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   \n",
       "1   -1.0072   -1.0443   -1.0796   -1.0214   -1.0403   -1.0536   -0.9769   \n",
       "2   -0.9994   -1.0205   -1.0233   -1.0148   -1.0200   -1.0060   -1.0000   \n",
       "3    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800   \n",
       "4   -0.1856   -0.1363   -0.2104   -0.2153   -0.2076   -0.1216   -0.1630   \n",
       "5   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   -1.0100   \n",
       "6    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800   \n",
       "7   -0.1335    0.0600   -0.4317    0.2882   -0.1512   -0.7065   -1.3678   \n",
       "8    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800    0.9800   \n",
       "9   -0.2919   -0.1607   -0.3413    1.5163    0.7945    0.4161   -0.4016   \n",
       "\n",
       "   acc_y_98  acc_y_99  acc_y_100  acc_y_101  acc_y_102  acc_y_103  acc_y_104  \\\n",
       "0   -1.0100   -1.0100    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100   \n",
       "1   -0.9676   -0.9300    -1.0619    -1.1593    -1.0181    -0.9846    -0.9090   \n",
       "2   -1.0193   -1.0159    -0.9925    -1.0563    -1.0174    -0.9960    -1.0200   \n",
       "3    0.9800    0.9778     0.9800     0.9788     0.9751     0.9800     0.9703   \n",
       "4   -0.1716   -0.0788    -0.0456     0.4324    -0.0227    -0.1335     0.0793   \n",
       "5   -1.0100   -1.0100    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100   \n",
       "6    0.9800    0.9800     0.9800     0.9800     0.9795     0.9712     0.9774   \n",
       "7   -1.6871   -1.5628    -0.4302    -0.5612     0.3400     0.1975    -0.0315   \n",
       "8    0.9800    0.9800     0.9800     0.9800     0.9800     0.9800     0.9800   \n",
       "9   -0.8242    0.5640     0.2757    -1.1756     0.0428     0.0477     0.2596   \n",
       "\n",
       "   acc_y_105  acc_y_106  acc_y_107  acc_y_108  acc_y_109  acc_y_110  \\\n",
       "0    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100   \n",
       "1    -0.8807    -1.0895    -1.0593    -1.1105    -1.0608    -0.9736   \n",
       "2    -1.0387    -1.0138    -1.0122    -1.0008    -1.0120    -1.0128   \n",
       "3     0.9783     0.9754     0.9728     0.9791     0.9725     0.9800   \n",
       "4    -0.0530    -0.0447     0.4723     0.0708     0.5332     0.0094   \n",
       "5    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100   \n",
       "6     0.9800     0.9800     0.9800     0.9800     0.9800     0.9800   \n",
       "7     0.5832     0.5370     0.1002     0.0041    -0.4896    -0.4021   \n",
       "8     0.9800     0.9810     0.9853     0.9896     0.9800     0.9800   \n",
       "9    -1.9472    -1.0713    -1.6992    -0.1566    -1.1031    -0.0539   \n",
       "\n",
       "   acc_y_111  acc_y_112  acc_y_113  acc_y_114  acc_y_115  acc_y_116  \\\n",
       "0    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100   \n",
       "1    -1.0203    -1.0270    -1.0532    -1.0747    -1.0527    -1.0459   \n",
       "2    -1.0000    -1.0294    -1.0241    -1.0446    -1.0156    -1.0026   \n",
       "3     0.9714     0.9701     0.9764     0.9800     0.9800     0.9700   \n",
       "4     0.4865    -0.0865    -0.0567    -0.0962    -0.0940    -0.0802   \n",
       "5    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100   \n",
       "6     0.9800     0.9800     0.9800     0.9800     0.9800     0.9800   \n",
       "7    -0.3325    -0.3839    -0.4726    -0.4389    -0.2203    -0.3039   \n",
       "8     0.9800     0.9800     0.9800     0.9800     0.9800     0.9800   \n",
       "9    -0.2003    -0.0763    -0.1077    -0.1133    -2.8334    -2.0722   \n",
       "\n",
       "   acc_y_117  acc_y_118  acc_y_119  acc_y_120  acc_y_121  acc_y_122  \\\n",
       "0    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100   \n",
       "1    -1.0325    -1.0146    -0.9394    -0.9254    -0.9062    -0.9000   \n",
       "2    -0.9955    -1.0215    -1.0275    -0.9835    -1.0235    -1.0108   \n",
       "3     0.9700     0.9700     0.9700     0.9800     0.9800     0.9800   \n",
       "4    -0.1241    -0.1409    -0.1242    -0.0560     0.3813    -0.0737   \n",
       "5    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100   \n",
       "6     0.9800     0.9800     0.9800     0.9800     0.9800     0.9800   \n",
       "7    -0.3903     0.0475     0.1000     0.2744     0.3852     0.3570   \n",
       "8     0.9800     0.9800     0.9800     0.9800     0.9800     0.9800   \n",
       "9     0.5945    -0.3713     1.0170     0.6676     0.1627     0.3745   \n",
       "\n",
       "   acc_y_123  acc_y_124  acc_y_125  acc_y_126  acc_y_127  acc_y_128  \\\n",
       "0    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100   \n",
       "1    -0.9190    -0.9420    -0.9481    -0.9241    -0.9327    -0.9529   \n",
       "2    -1.0200    -1.0015    -1.0135    -1.0304    -1.0321    -1.0009   \n",
       "3     0.9800     0.9800     0.9800     0.9750     0.9776     0.9800   \n",
       "4    -0.0430     0.3942     0.4158     0.5981    -0.1314    -0.0357   \n",
       "5    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100   \n",
       "6     0.9800     0.9800     0.9800     0.9800     0.9800     0.9800   \n",
       "7    -0.0067    -0.1780    -0.4316    -0.5365    -0.2160     0.0258   \n",
       "8     0.9800     0.9782     0.9749     0.9716     0.9700     0.9700   \n",
       "9     0.1491     0.1276    -0.2089    -0.3634    -0.1951    -0.2685   \n",
       "\n",
       "   acc_y_129  acc_y_130  acc_y_131  acc_y_132  acc_y_133  acc_y_134  \\\n",
       "0    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100   \n",
       "1    -0.9152    -0.8499    -0.7997    -0.9261    -0.9673    -0.7701   \n",
       "2    -1.0134    -1.0047    -1.0265    -1.0400    -1.0060    -1.0200   \n",
       "3     0.9800     0.9800     0.9800     0.9800     0.9800     0.9800   \n",
       "4    -0.0531    -0.1016    -0.0754    -0.0769    -0.0847     0.3737   \n",
       "5    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100   \n",
       "6     0.9800     0.9800     0.9800     0.9800     0.9800     0.9800   \n",
       "7     0.0028     0.1032     0.1087     0.2015     0.1968     0.0520   \n",
       "8     0.9700     0.9716     0.9781     0.9754     0.9693     0.9653   \n",
       "9    -0.2748    -0.3269    -0.0844     0.2059     0.2432     0.0292   \n",
       "\n",
       "   acc_y_135  acc_y_136  acc_y_137  acc_y_138  acc_y_139  acc_y_140  \\\n",
       "0    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100   \n",
       "1    -1.1206    -1.8963    -0.8958    -1.0997    -1.0931    -0.7537   \n",
       "2    -1.0077    -1.0200    -1.0179    -1.0100    -1.0206    -1.0013   \n",
       "3     0.9800     0.9800     0.9775     0.9750     0.9725     0.9799   \n",
       "4    -0.0327     0.0787    -0.0225     0.2044    -0.0788     0.0118   \n",
       "5    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100   \n",
       "6     0.9800     0.9800     0.9800     0.9800     0.9800     0.9800   \n",
       "7    -0.1452    -0.1531    -0.1394    -0.1403    -0.1400    -0.1655   \n",
       "8     0.9613     0.9727     0.9771     0.9800     0.9800     0.9755   \n",
       "9     0.0289     0.0508    -0.1335    -0.2823    -0.2359    -0.1733   \n",
       "\n",
       "   acc_y_141  acc_y_142  acc_y_143  acc_y_144  acc_y_145  acc_y_146  \\\n",
       "0    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100   \n",
       "1    -0.7620    -0.7819    -0.8921    -0.9991    -0.9289    -1.0326   \n",
       "2    -1.0183    -1.0100    -1.0100    -1.0109    -1.0200    -1.0200   \n",
       "3     0.9739     0.9800     0.9732     0.9800     0.9800     0.9753   \n",
       "4    -0.0896    -0.0978    -0.1168    -0.1315    -0.0864    -0.0513   \n",
       "5    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100   \n",
       "6     0.9800     0.9800     0.9800     0.9800     0.9800     0.9800   \n",
       "7    -0.1365    -0.0800    -0.0692     0.0021     0.0059    -0.0192   \n",
       "8     0.9698     0.9680     0.9663     0.9645     0.9627     0.9609   \n",
       "9    -0.1414    -0.1132    -0.1415    -0.1036    -0.0980    -0.0297   \n",
       "\n",
       "   acc_y_147  acc_y_148  acc_y_149  acc_y_150  acc_y_151  acc_y_152  \\\n",
       "0    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100   \n",
       "1    -1.1288    -1.1224    -1.0468    -0.9855    -0.9460    -1.2149   \n",
       "2    -1.0200    -1.0200    -1.0128    -1.0200    -1.0126    -1.0100   \n",
       "3     0.9737     0.9770     0.9800     0.9800     0.9722     0.9796   \n",
       "4    -0.0664    -0.0243     0.0222     0.3911     0.1600     0.0618   \n",
       "5    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100   \n",
       "6     0.9800     0.9800     0.9800     0.9800     0.9800     0.9800   \n",
       "7    -0.0524    -0.0861    -0.1300    -0.1891    -0.1835    -0.1472   \n",
       "8     0.9766     0.9784     0.9763     0.9743     0.9722     0.9701   \n",
       "9     0.0462     0.0647     0.0460     0.0037    -0.1111    -0.1373   \n",
       "\n",
       "   acc_y_153  acc_y_154  acc_y_155  acc_y_156  acc_y_157  acc_y_158  \\\n",
       "0    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100   \n",
       "1    -1.1871    -1.1009    -1.0139    -0.8525    -0.9839    -1.0341   \n",
       "2    -1.0187    -1.0100    -1.0100    -1.0100    -1.0178    -1.0052   \n",
       "3     0.9721     0.9800     0.9800     0.9800     0.9800     0.9800   \n",
       "4    -0.0002    -0.0089    -0.0365    -0.0268    -0.0406    -0.0347   \n",
       "5    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100    -1.0100   \n",
       "6     0.9800     0.9800     0.9800     0.9800     0.9800     0.9796   \n",
       "7    -0.0883    -0.0364    -0.0216    -0.0083    -0.0378    -0.0927   \n",
       "8     0.9778     0.9637     0.9700     0.9780     0.9700     0.9630   \n",
       "9    -0.1500    -0.1466    -0.1295    -0.0729    -0.0377    -0.0111   \n",
       "\n",
       "   acc_y_159  acc_z_0  acc_z_1  acc_z_2  acc_z_3  acc_z_4  acc_z_5  acc_z_6  \\\n",
       "0    -1.0100   0.1200   0.1200   0.1200   0.1200   0.1200   0.1200   0.1200   \n",
       "1    -1.0522   0.0621   0.0449   0.0973   0.1595   0.1839   0.2085   0.1843   \n",
       "2    -1.0051   0.0793   0.1000   0.1000   0.1000   0.1000   0.0924   0.0800   \n",
       "3     0.9800   0.1600   0.1600   0.1600   0.1600   0.1600   0.1600   0.1600   \n",
       "4    -0.0546   0.2399   0.2544   0.2423   0.1780   0.1808   0.1865   0.1927   \n",
       "5    -1.0100   0.1200   0.1200   0.1200   0.1200   0.1200   0.1200   0.1200   \n",
       "6     0.9722   0.1500   0.1425   0.1453   0.1500   0.1500   0.1500   0.1500   \n",
       "7    -0.1596   0.1623   0.1475   0.1293   0.1214   0.0744   0.0880   0.1079   \n",
       "8     0.9683   0.1272   0.1230   0.1200   0.1220   0.1262   0.1300   0.1300   \n",
       "9    -0.0066   0.1060   0.1300   0.1323   0.1367   0.1101   0.1653   0.1526   \n",
       "\n",
       "   acc_z_7  acc_z_8  acc_z_9  acc_z_10  acc_z_11  acc_z_12  acc_z_13  \\\n",
       "0   0.1200   0.1200   0.1200    0.1200    0.1200    0.1200    0.1200   \n",
       "1   0.1907   0.1979   0.1941    0.1799    0.1732    0.1700    0.1700   \n",
       "2   0.0661   0.0690   0.0676    0.0800    0.0869    0.0803    0.0897   \n",
       "3   0.1600   0.1600   0.1600    0.1600    0.1600    0.1600    0.1600   \n",
       "4   0.1889   0.1766   0.1866    0.2138    0.1859    0.1954    0.1589   \n",
       "5   0.1200   0.1200   0.1200    0.1200    0.1200    0.1200    0.1200   \n",
       "6   0.1500   0.1449   0.1481    0.1500    0.1500    0.1500    0.1428   \n",
       "7   0.0723   0.1478   0.1667    0.1622    0.1655    0.1925    0.1976   \n",
       "8   0.1300   0.1300   0.1300    0.1300    0.1300    0.1300    0.1305   \n",
       "9   0.1645   0.0921   0.1654    0.1090    0.1649    0.1988    0.1692   \n",
       "\n",
       "   acc_z_14  acc_z_15  acc_z_16  acc_z_17  acc_z_18  acc_z_19  acc_z_20  \\\n",
       "0    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200   \n",
       "1    0.1768    0.1600    0.1600    0.1516    0.1256    0.1158    0.1114   \n",
       "2    0.0900    0.1022    0.1100    0.1110    0.1220    0.1378    0.1400   \n",
       "3    0.1600    0.1600    0.1600    0.1600    0.1600    0.1600    0.1600   \n",
       "4    0.2671    0.2790    0.2454    0.2298    0.1929    0.1843    0.1364   \n",
       "5    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200   \n",
       "6    0.1500    0.1500    0.1500    0.1500    0.1500    0.1500    0.1500   \n",
       "7    0.2186    0.1685    0.0961    0.0791    0.0603    0.0407    0.0468   \n",
       "8    0.1479    0.1652    0.1700    0.1700    0.1700    0.1700    0.1608   \n",
       "9    0.1550    0.1400    0.1400    0.1300    0.1376    0.1595    0.1984   \n",
       "\n",
       "   acc_z_21  acc_z_22  acc_z_23  acc_z_24  acc_z_25  acc_z_26  acc_z_27  \\\n",
       "0    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200   \n",
       "1    0.1340    0.1600    0.1600    0.1600    0.1435    0.1308    0.1500   \n",
       "2    0.1500    0.1553    0.1712    0.1810    0.1970    0.2143    0.2200   \n",
       "3    0.1600    0.1600    0.1600    0.1600    0.1600    0.1600    0.1600   \n",
       "4    0.1242    0.0887    0.0592    0.0383    0.0003   -0.0319   -0.0299   \n",
       "5    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200   \n",
       "6    0.1500    0.1402    0.1500    0.1500    0.1500    0.1500    0.1500   \n",
       "7    0.0310    0.0127    0.0421    0.0628    0.1093    0.1393    0.1608   \n",
       "8    0.1491    0.1370    0.1300    0.1300    0.1300    0.1300    0.1300   \n",
       "9    0.1969    0.1417    0.1252    0.1457    0.1100    0.1014    0.0649   \n",
       "\n",
       "   acc_z_28  acc_z_29  acc_z_30  acc_z_31  acc_z_32  acc_z_33  acc_z_34  \\\n",
       "0    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200   \n",
       "1    0.1500    0.1500    0.1645    0.1757    0.1870    0.1700    0.1700   \n",
       "2    0.2289    0.2300    0.2339    0.2353    0.2300    0.2221    0.2266   \n",
       "3    0.1600    0.1600    0.1600    0.1600    0.1600    0.1600    0.1600   \n",
       "4   -0.0192   -0.0211    0.0130   -0.0068   -0.0341   -0.0405   -0.0673   \n",
       "5    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200   \n",
       "6    0.1500    0.1500    0.1500    0.1400    0.1444    0.1500    0.1500   \n",
       "7    0.1683    0.1462    0.1247    0.0982    0.0941    0.1000    0.1194   \n",
       "8    0.1387    0.1405    0.1447    0.1490    0.1500    0.1465    0.1423   \n",
       "9    0.0500    0.0498    0.0274    0.0388    0.0674    0.0181    0.0318   \n",
       "\n",
       "   acc_z_35  acc_z_36  acc_z_37  acc_z_38  acc_z_39  acc_z_40  acc_z_41  \\\n",
       "0    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200   \n",
       "1    0.1166    0.1281    0.1213    0.1412    0.1300    0.1360    0.1222   \n",
       "2    0.2200    0.2111    0.2048    0.1989    0.1930    0.1670    0.1800   \n",
       "3    0.1600    0.1600    0.1600    0.1600    0.1600    0.1600    0.1600   \n",
       "4   -0.0271   -0.0978   -0.0292   -0.0311   -0.0271   -0.0575   -0.0636   \n",
       "5    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200   \n",
       "6    0.1500    0.1500    0.1500    0.1500    0.1500    0.1500    0.1500   \n",
       "7    0.1300    0.1300    0.1300    0.1100    0.1100    0.1058    0.1000   \n",
       "8    0.1413    0.1446    0.1479    0.1500    0.1500    0.1490    0.1471   \n",
       "9    0.0761    0.1227    0.1677    0.1567    0.1968    0.1754    0.1800   \n",
       "\n",
       "   acc_z_42  acc_z_43  acc_z_44  acc_z_45  acc_z_46  acc_z_47  acc_z_48  \\\n",
       "0    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200   \n",
       "1    0.1289    0.1300    0.1310    0.1376    0.1636    0.1196    0.1122   \n",
       "2    0.1800    0.1800    0.1588    0.1573    0.1700    0.1906    0.2000   \n",
       "3    0.1600    0.1600    0.1600    0.1600    0.1660    0.1620    0.1600   \n",
       "4   -0.0449   -0.0373   -0.0506   -0.0774   -0.0237   -0.1231    0.0873   \n",
       "5    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200   \n",
       "6    0.1500    0.1500    0.1500    0.1500    0.1500    0.1417    0.1500   \n",
       "7    0.1000    0.0900    0.0900    0.0818    0.0800    0.0800    0.0762   \n",
       "8    0.1453    0.1435    0.1417    0.1400    0.1400    0.1400    0.1400   \n",
       "9    0.1650    0.1212    0.1261    0.1086    0.1039    0.0972    0.0990   \n",
       "\n",
       "   acc_z_49  acc_z_50  acc_z_51  acc_z_52  acc_z_53  acc_z_54  acc_z_55  \\\n",
       "0    0.1200    0.1200     0.120    0.1200    0.1200    0.1200    0.1200   \n",
       "1    0.1100    0.0997     0.063    0.0754    0.1128    0.1002    0.0890   \n",
       "2    0.1504    0.1291     0.140    0.1557    0.1909    0.2012    0.1700   \n",
       "3    0.1600    0.1600     0.160    0.1600    0.1700    0.1700    0.1700   \n",
       "4   -0.1648   -0.1343    -0.109   -0.0980   -0.1607   -0.1321    0.0998   \n",
       "5    0.1200    0.1200     0.120    0.1200    0.1200    0.1200    0.1200   \n",
       "6    0.1500    0.1492     0.140    0.1454    0.1428    0.1400    0.1425   \n",
       "7    0.0700    0.0700     0.070    0.0667    0.0600    0.0600    0.0500   \n",
       "8    0.1400    0.1400     0.140    0.1400    0.1453    0.1500    0.1500   \n",
       "9    0.1184    0.1100     0.110    0.0937    0.0917    0.0916    0.0800   \n",
       "\n",
       "   acc_z_56  acc_z_57  acc_z_58  acc_z_59  acc_z_60  acc_z_61  acc_z_62  \\\n",
       "0    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200   \n",
       "1    0.0551    0.1136    0.1098    0.1239    0.1792    0.1737    0.1987   \n",
       "2    0.1610    0.1884    0.1450    0.1700    0.1700    0.1700    0.1867   \n",
       "3    0.1600    0.1600    0.1600    0.1600    0.1600    0.1673    0.1600   \n",
       "4   -0.1064   -0.1713   -0.0364   -0.1161   -0.2587   -0.0614    0.6771   \n",
       "5    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200   \n",
       "6    0.1500    0.1500    0.1500    0.1500    0.1500    0.1500    0.1500   \n",
       "7    0.0459    0.0400    0.0312    0.0300    0.0262    0.0200    0.0108   \n",
       "8    0.1400    0.1400    0.1400    0.1400    0.1400    0.1395    0.1331   \n",
       "9    0.0886    0.0838    0.1038    0.1044    0.1077    0.1198    0.1127   \n",
       "\n",
       "   acc_z_63  acc_z_64  acc_z_65  acc_z_66  acc_z_67  acc_z_68  acc_z_69  \\\n",
       "0    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200   \n",
       "1    0.2167    0.1786    0.1354    0.1714    0.1967    0.1399    0.1128   \n",
       "2    0.1758    0.1866    0.1539    0.1482    0.1996    0.1132    0.0769   \n",
       "3    0.1600    0.1600    0.1600    0.1600    0.1600    0.1600    0.1600   \n",
       "4    0.3270    0.0844    0.0729    0.1046   -0.1348    0.6196   -0.1157   \n",
       "5    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200   \n",
       "6    0.1474    0.1451    0.1424    0.1492    0.1440    0.1500    0.1500   \n",
       "7    0.0000    0.0041    0.0551   -0.0883   -0.0770   -0.0467   -0.0540   \n",
       "8    0.1373    0.1307    0.1300    0.1315    0.1379    0.1400    0.1400   \n",
       "9    0.1200    0.1118    0.1100    0.1176    0.1100    0.1100    0.1100   \n",
       "\n",
       "   acc_z_70  acc_z_71  acc_z_72  acc_z_73  acc_z_74  acc_z_75  acc_z_76  \\\n",
       "0    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200   \n",
       "1    0.1101    0.0962    0.1147    0.0946    0.1700    0.1831    0.1784   \n",
       "2    0.0676    0.0967    0.1100    0.0687    0.0479    0.0594    0.0374   \n",
       "3    0.1600    0.1600    0.1600    0.1600    0.1600    0.1600    0.1600   \n",
       "4   -0.0975    0.2007   -0.0997   -0.0472    0.0391   -0.0361    0.0704   \n",
       "5    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200   \n",
       "6    0.1402    0.1400    0.1448    0.1426    0.1500    0.1500    0.1500   \n",
       "7   -0.0205   -0.0850   -0.0543   -1.1334    1.1927   -0.2285   -1.1240   \n",
       "8    0.1400    0.1400    0.1400    0.1400    0.1400    0.1400    0.1400   \n",
       "9    0.1000    0.0937    0.0900    0.0787    0.0660    0.0533    0.0332   \n",
       "\n",
       "   acc_z_77  acc_z_78  acc_z_79  acc_z_80  acc_z_81  acc_z_82  acc_z_83  \\\n",
       "0    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200   \n",
       "1    0.1961    0.1952    0.1465    0.1258    0.1200    0.1200    0.1052   \n",
       "2    0.0206    0.0884    0.0481    0.0903    0.0926    0.0799    0.0617   \n",
       "3    0.1600    0.1600    0.1600    0.1600    0.1600    0.1600    0.1600   \n",
       "4   -0.0281    0.0171   -0.0828   -0.0178   -0.1057    0.6398   -0.1180   \n",
       "5    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200   \n",
       "6    0.1500    0.1500    0.1500    0.1500    0.1500    0.1500    0.1500   \n",
       "7   -0.5655   -0.5091    1.0910   -0.3837    0.0956   -0.4515   -0.6187   \n",
       "8    0.1400    0.1400    0.1400    0.1400    0.1400    0.1400    0.1400   \n",
       "9    0.0282    0.0159    0.0100    0.0003   -0.0119   -0.0238   -0.0367   \n",
       "\n",
       "   acc_z_84  acc_z_85  acc_z_86  acc_z_87  acc_z_88  acc_z_89  acc_z_90  \\\n",
       "0    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200   \n",
       "1    0.0858    0.0600    0.0519    0.0122   -0.0318   -0.0380   -0.0530   \n",
       "2    0.0619    0.0760    0.0790    0.0803    0.0881    0.0993    0.0945   \n",
       "3    0.1600    0.1600    0.1600    0.1600    0.1600    0.1600    0.1600   \n",
       "4   -0.1367    0.2831    0.0140   -0.0898   -0.0234   -0.1978   -0.2143   \n",
       "5    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200   \n",
       "6    0.1500    0.1500    0.1496    0.1400    0.1452    0.1500    0.1500   \n",
       "7    0.3270    0.1274   -0.5687   -0.3900    0.0125   -0.4655    1.1798   \n",
       "8    0.1400    0.1400    0.1435    0.1440    0.1400    0.1400    0.1400   \n",
       "9   -0.0066   -0.0169   -0.0500   -0.0500   -0.0411   -0.0557   -0.0194   \n",
       "\n",
       "   acc_z_91  acc_z_92  acc_z_93  acc_z_94  acc_z_95  acc_z_96  acc_z_97  \\\n",
       "0    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200   \n",
       "1   -0.0615   -0.0817   -0.0958   -0.0771   -0.0700   -0.0700   -0.0754   \n",
       "2    0.0612    0.0410    0.0735    0.0904    0.0957    0.0790    0.0572   \n",
       "3    0.1600    0.1600    0.1600    0.1600    0.1600    0.1600    0.1600   \n",
       "4    0.4808   -0.1867    0.5337   -0.2117   -0.2789   -0.2486   -0.3117   \n",
       "5    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200    0.1200   \n",
       "6    0.1475    0.1400    0.1478    0.1500    0.1500    0.1453    0.1472   \n",
       "7    0.0926    0.0972   -0.0532    0.9816   -0.0715    0.3321    0.3308   \n",
       "8    0.1400    0.1500    0.1500    0.1400    0.1400    0.1400    0.1400   \n",
       "9    0.0698    0.1009    2.0209   -1.3196   -1.8191   -0.3541    0.6238   \n",
       "\n",
       "   acc_z_98  acc_z_99  acc_z_100  acc_z_101  acc_z_102  acc_z_103  acc_z_104  \\\n",
       "0    0.1200    0.1200     0.1200     0.1200     0.1200     0.1200     0.1200   \n",
       "1   -0.1094   -0.0884     0.0005     0.0631     0.1390     0.0908     0.0152   \n",
       "2    0.0548    0.0600     0.0500     0.0518     0.0628     0.0700     0.0796   \n",
       "3    0.1600    0.1600     0.1600     0.1600     0.1600     0.1600     0.1600   \n",
       "4   -0.2642   -0.1560    -0.1615    -0.1430    -0.1422    -0.2720    -0.1278   \n",
       "5    0.1200    0.1200     0.1200     0.1200     0.1200     0.1200     0.1200   \n",
       "6    0.1500    0.1488     0.1425     0.1471     0.1400     0.1412     0.1474   \n",
       "7    0.2681    0.2853     0.1114    -0.0533    -0.2401     0.4338    -0.2691   \n",
       "8    0.1400    0.1400     0.1400     0.1400     0.1400     0.1400     0.1400   \n",
       "9   -0.1949   -0.0158     0.6782    -1.3805     0.6455    -0.0382     0.3607   \n",
       "\n",
       "   acc_z_105  acc_z_106  acc_z_107  acc_z_108  acc_z_109  acc_z_110  \\\n",
       "0     0.1200     0.1200     0.1200     0.1200     0.1200     0.1200   \n",
       "1     0.0450     0.1518     0.2666     0.3491     0.2924     0.2154   \n",
       "2     0.0800     0.0700     0.1014     0.1192     0.1080     0.1000   \n",
       "3     0.1600     0.1600     0.1672     0.1600     0.1600     0.1600   \n",
       "4    -0.2037    -0.2580     0.2002     0.0563    -0.1985    -0.1724   \n",
       "5     0.1200     0.1200     0.1200     0.1200     0.1200     0.1200   \n",
       "6     0.1463     0.1449     0.1400     0.1400     0.1400     0.1500   \n",
       "7    -0.2870    -0.6725    -0.5362    -0.1867    -0.0326     0.0020   \n",
       "8     0.1400     0.1400     0.1400     0.1400     0.1400     0.1400   \n",
       "9    -0.2496     0.2587     0.9950     0.5458    -0.2091     0.1394   \n",
       "\n",
       "   acc_z_111  acc_z_112  acc_z_113  acc_z_114  acc_z_115  acc_z_116  \\\n",
       "0     0.1200     0.1200     0.1200     0.1200     0.1200     0.1200   \n",
       "1     0.2303     0.2370     0.2453     0.2600     0.2791     0.2738   \n",
       "2     0.1067     0.1174     0.1094     0.0900     0.0900     0.1049   \n",
       "3     0.1600     0.1600     0.1600     0.1600     0.1678     0.1700   \n",
       "4    -0.2088    -0.1069     0.0008     0.0863     0.1087     0.4112   \n",
       "5     0.1200     0.1200     0.1200     0.1200     0.1200     0.1200   \n",
       "6     0.1480     0.1452     0.1500     0.1500     0.1500     0.1500   \n",
       "7     0.0798    -0.0942    -0.0169     0.0656    -0.1336    -0.2941   \n",
       "8     0.1400     0.1400     0.1400     0.1432     0.1469     0.1408   \n",
       "9    -0.1910    -0.2571     0.0133     0.1108    -0.4146    -0.0774   \n",
       "\n",
       "   acc_z_117  acc_z_118  acc_z_119  acc_z_120  acc_z_121  acc_z_122  \\\n",
       "0     0.1200     0.1200     0.1200     0.1200     0.1200     0.1200   \n",
       "1     0.2537     0.2300     0.1994     0.1854     0.1623     0.1520   \n",
       "2     0.1000     0.1000     0.0763     0.0521     0.0843     0.0946   \n",
       "3     0.1700     0.1700     0.1700     0.1600     0.1600     0.1600   \n",
       "4    -0.3451    -0.2885    -0.2339    -0.3163     0.1496    -0.2369   \n",
       "5     0.1200     0.1200     0.1200     0.1200     0.1200     0.1200   \n",
       "6     0.1500     0.1500     0.1406     0.1500     0.1500     0.1500   \n",
       "7    -0.3205    -0.0775     0.0018     0.0428    -0.0190    -0.2065   \n",
       "8     0.1434     0.1478     0.1400     0.1490     0.1600     0.1600   \n",
       "9     0.1273    -0.5142    -0.3267     0.0162    -0.1062    -0.5899   \n",
       "\n",
       "   acc_z_123  acc_z_124  acc_z_125  acc_z_126  acc_z_127  acc_z_128  \\\n",
       "0     0.1200     0.1200     0.1200     0.1200     0.1200     0.1200   \n",
       "1     0.1410     0.1000     0.1000     0.1121     0.1282     0.1148   \n",
       "2     0.0900     0.0731     0.0830     0.0596     0.0579     0.0518   \n",
       "3     0.1600     0.1600     0.1662     0.1650     0.1600     0.1600   \n",
       "4     0.2693    -0.0355     0.2392    -0.2581    -0.2684    -0.1619   \n",
       "5     0.1200     0.1200     0.1200     0.1200     0.1200     0.1200   \n",
       "6     0.1478     0.1455     0.1429     0.1499     0.1421     0.1500   \n",
       "7    -0.0790     0.2720     0.1963     0.1317     0.1218     0.1493   \n",
       "8     0.1659     0.1700     0.1700     0.1700     0.1716     0.1748   \n",
       "9    -0.2864     0.2683    -0.1290    -0.0241    -0.0246    -0.0055   \n",
       "\n",
       "   acc_z_129  acc_z_130  acc_z_131  acc_z_132  acc_z_133  acc_z_134  \\\n",
       "0     0.1200     0.1200     0.1200     0.1200     0.1200     0.1200   \n",
       "1     0.1011     0.0678    -0.0197     0.1190     0.2373     0.0510   \n",
       "2     0.0700     0.0700     0.0408     0.0689     0.0730     0.0753   \n",
       "3     0.1600     0.1600     0.1600     0.1600     0.1600     0.1600   \n",
       "4    -0.2251    -0.3822    -0.3184    -0.1563    -0.3065    -0.2514   \n",
       "5     0.1200     0.1200     0.1200     0.1200     0.1200     0.1200   \n",
       "6     0.1500     0.1405     0.1500     0.1500     0.1500     0.1500   \n",
       "7     0.1339     0.2832     0.2454     0.2488     0.2138     0.2561   \n",
       "8     0.1779     0.1800     0.1800     0.1800     0.1780     0.1659   \n",
       "9    -0.0600    -0.0718    -0.1802    -0.1418    -0.0030    -0.0238   \n",
       "\n",
       "   acc_z_135  acc_z_136  acc_z_137  acc_z_138  acc_z_139  acc_z_140  \\\n",
       "0     0.1200     0.1200     0.1200     0.1200     0.1200     0.1200   \n",
       "1     0.1798     0.0003    -0.0094     0.0653     0.1984     0.1744   \n",
       "2     0.0761     0.0798     0.0700     0.0742     0.0853     0.0804   \n",
       "3     0.1600     0.1600     0.1600     0.1600     0.1600     0.1600   \n",
       "4    -0.1304    -0.2455    -0.2449    -0.3263     0.0179    -0.2647   \n",
       "5     0.1200     0.1200     0.1200     0.1200     0.1200     0.1200   \n",
       "6     0.1500     0.1500     0.1500     0.1500     0.1500     0.1500   \n",
       "7     0.2414     0.1966     0.1383     0.0712     0.1652     0.1096   \n",
       "8     0.1538     0.2147     0.2059     0.1858     0.1425     0.1300   \n",
       "9     0.0359    -0.0274    -0.1081    -0.1349     0.0371     0.0422   \n",
       "\n",
       "   acc_z_141  acc_z_142  acc_z_143  acc_z_144  acc_z_145  acc_z_146  \\\n",
       "0     0.1200     0.1200     0.1200     0.1200     0.1200     0.1200   \n",
       "1     0.1619     0.1571     0.1511    -0.0979    -0.0021    -0.0841   \n",
       "2     0.0783     0.0646     0.0600     0.0600     0.0600     0.0600   \n",
       "3     0.1600     0.1600     0.1600     0.1600     0.1600     0.1600   \n",
       "4    -0.3989    -0.4519    -0.4462    -0.3775    -0.3026    -0.2039   \n",
       "5     0.1200     0.1200     0.1200     0.1200     0.1200     0.1200   \n",
       "6     0.1500     0.1500     0.1478     0.1400     0.1400     0.1500   \n",
       "7     0.0342    -0.0309    -0.0539    -0.1138    -0.0478    -0.0108   \n",
       "8     0.1306     0.1359     0.1412     0.1466     0.1519     0.1572   \n",
       "9     0.0319     0.0094     0.0535     0.0971     0.1390     0.1509   \n",
       "\n",
       "   acc_z_147  acc_z_148  acc_z_149  acc_z_150  acc_z_151  acc_z_152  \\\n",
       "0     0.1200     0.1200     0.1200     0.1200     0.1200     0.1200   \n",
       "1     0.1295     0.1812     0.1597     0.2884     0.0002    -0.0024   \n",
       "2     0.0600     0.0600     0.0600     0.0600     0.0748     0.0800   \n",
       "3     0.1600     0.1630     0.1600     0.1600     0.1600     0.1600   \n",
       "4    -0.4009    -0.4064    -0.3945    -0.4573    -0.4362    -0.3340   \n",
       "5     0.1200     0.1200     0.1200     0.1200     0.1200     0.1200   \n",
       "6     0.1500     0.1500     0.1500     0.1500     0.1500     0.1500   \n",
       "7    -0.0012    -0.0342    -0.0700    -0.0782    -0.0878    -0.0630   \n",
       "8     0.1469     0.1431     0.1473     0.1515     0.1557     0.1598   \n",
       "9     0.1676     0.1747     0.1701     0.2589     0.2178     0.1481   \n",
       "\n",
       "   acc_z_153  acc_z_154  acc_z_155  acc_z_156  acc_z_157  acc_z_158  \\\n",
       "0     0.1200     0.1200     0.1200     0.1200     0.1200     0.1200   \n",
       "1     0.0393     0.0231     0.1349     0.1257    -0.0438    -0.0347   \n",
       "2     0.0813     0.0900     0.0900     0.0900     0.0900     0.0952   \n",
       "3     0.1600     0.1600     0.1600     0.1600     0.1600     0.1600   \n",
       "4    -0.4326    -0.4300    -0.4208    -0.4292    -0.4409    -0.4171   \n",
       "5     0.1200     0.1200     0.1200     0.1200     0.1200     0.1200   \n",
       "6     0.1500     0.1500     0.1500     0.1500     0.1500     0.1496   \n",
       "7    -0.0191    -0.0016    -0.0184    -0.0442    -0.0381     0.0042   \n",
       "8     0.2068     0.1984     0.1998     0.2603     0.1884     0.1870   \n",
       "9     0.1200     0.1200     0.1305     0.0929     0.0530    -0.0089   \n",
       "\n",
       "   acc_z_159  gy_x_0  gy_x_1  gy_x_2  gy_x_3  gy_x_4  gy_x_5  gy_x_6  gy_x_7  \\\n",
       "0     0.1200  1.6956  1.8300  1.8018  1.8584  1.6721  1.7700  1.7277  1.7602   \n",
       "1    -0.1094  1.2155  1.2795  1.4860  1.9381  2.0855  2.5653  2.0443  2.2740   \n",
       "2     0.0900  1.8515  2.0744  1.9816  1.9007  1.9503  2.0481  1.8947  1.8300   \n",
       "3     0.1600 -0.0949  0.0229  0.1728  0.6118  0.5225  0.4458  0.4111  0.3371   \n",
       "4    -0.3853 -7.1600 -1.4078 -2.5187 -3.1894 -5.6738 -2.6646  0.0118  5.2189   \n",
       "5     0.1200  1.8509  1.7100  1.7100  1.7728  1.8224  1.8300  1.6686  1.7100   \n",
       "6     0.1422  0.4905  0.4324  0.5495  0.2793  0.2286  0.3497  0.3769  0.5152   \n",
       "7     0.0905  1.8606  2.1600  2.8395  2.6885  2.3516  2.2424  2.1568  2.1965   \n",
       "8     0.2000  0.1925  0.3458  0.5304  0.6773  0.5492  0.4300  0.4300  0.4300   \n",
       "9    -0.0200  1.3209  1.1411  0.6328  0.7593  0.7431  0.1724 -0.0214  0.2167   \n",
       "\n",
       "   gy_x_8  gy_x_9  gy_x_10  gy_x_11  gy_x_12  gy_x_13  gy_x_14  gy_x_15  \\\n",
       "0  1.8501  1.7555   1.8300   1.8300   1.8300   1.8231   1.7880   1.8294   \n",
       "1  1.8216  1.1988   1.1530   0.9348   0.9903   1.1503   1.3651   1.5765   \n",
       "2  1.8832  1.8734   1.9253   1.8905   1.9254   2.2000   2.1205   1.9339   \n",
       "3  0.4631  0.3615   0.3723   0.5287   0.4514   0.3936   0.2798   0.3182   \n",
       "4  0.3145  9.6507   7.7092  -7.5435 -19.1629 -17.2012 -15.0748 -19.6639   \n",
       "5  1.7334  1.8176   1.7791   1.7730   1.8480   1.9314   1.8900   1.7870   \n",
       "6  0.4179  0.5121   0.3937   0.3872   0.5049   0.4209   0.3058   0.2510   \n",
       "7  3.2300  3.0440   2.7585   2.6467   2.6099   2.5813   2.1393   1.8434   \n",
       "8  0.4300  0.4300   0.5038   0.7046   0.9054   1.0923   0.8474   0.8787   \n",
       "9  0.4389 -1.1709   0.4616   1.3297   1.8286   1.9500   2.2008   2.7849   \n",
       "\n",
       "   gy_x_16  gy_x_17  gy_x_18  gy_x_19  gy_x_20  gy_x_21  gy_x_22  gy_x_23  \\\n",
       "0   1.8150   1.8197   1.9360   1.7700   1.7700   1.8342   1.7907   1.9474   \n",
       "1   1.5680   1.8036   1.8900   1.8062   1.7185   1.1899   1.4595   1.4340   \n",
       "2   2.0640   2.0089   1.9646   2.0100   1.8676   1.8456   1.9500   1.9500   \n",
       "3   0.4497   0.3160   0.3553   0.8199   0.6746   0.2400   0.2400   0.5628   \n",
       "4 -19.2140 -22.2853 -24.4757 -23.5848 -22.5831 -24.2440 -27.8501 -25.1808   \n",
       "5   1.8129   1.8555   1.8012   1.7700   1.8389   1.8696   1.7793   1.6001   \n",
       "6   0.4164   0.6858   0.4335   0.4300   0.4300   0.4101   0.3708   0.5395   \n",
       "7   2.6434   3.5105   4.1166   4.4501   4.9771   4.4995   5.0949   4.8921   \n",
       "8   0.6188   0.1210   0.2478   0.7554   0.7426   0.3016  -0.0241   0.2053   \n",
       "9   3.0167   2.8844   3.0335   3.0508   3.0407   2.4050   2.3191   2.7219   \n",
       "\n",
       "   gy_x_24  gy_x_25  gy_x_26  gy_x_27  gy_x_28  gy_x_29  gy_x_30  gy_x_31  \\\n",
       "0   1.8824   1.8117   1.7415   1.8768   1.8562   1.7519   1.7272   1.8300   \n",
       "1   1.4085   1.5504   1.5850   1.8617   1.6789   1.6991   1.9911   2.1345   \n",
       "2   1.8321   1.8900   1.8557   1.7700   1.8971   1.9500   1.9919   1.9835   \n",
       "3   0.6495   0.6241   0.4161   0.5553   0.4437   0.0466   0.3303   0.4850   \n",
       "4 -28.0208 -27.5610 -27.9956 -28.6689 -28.1019 -28.0783 -25.9127 -30.2738   \n",
       "5   1.7443   1.8900   1.8696   1.8373   1.9310   1.8092   1.7797   1.8870   \n",
       "6   0.4196   0.5732   0.6276   0.3737   0.4000   0.4263   0.4874   0.3353   \n",
       "7   5.0403   5.2256   5.3798   5.2126   4.5176   3.9420   4.0329   4.2314   \n",
       "8   0.1276   0.1333   0.2593   0.3854   0.1354   0.3745   0.6136   0.6396   \n",
       "9   3.4159   4.1004   3.7803   3.4200   3.3925   3.2673   3.0128   3.6934   \n",
       "\n",
       "   gy_x_32  gy_x_33  gy_x_34  gy_x_35  gy_x_36  gy_x_37  gy_x_38  gy_x_39  \\\n",
       "0   1.8300   1.7750   1.5833   1.7034   1.8447   1.8851   1.7100   1.8198   \n",
       "1   2.0100   1.7733   1.6402   1.4129   2.1232   2.0337   1.4106   1.2211   \n",
       "2   2.3056   2.3262   2.3209   1.8492   1.9192   1.8983   1.8280   1.7576   \n",
       "3   0.3070   0.3620   0.3753   0.5661   0.3126   0.4225   0.4814   0.3012   \n",
       "4 -33.5351 -34.3126 -36.8041 -38.8683 -41.2255 -39.6171 -44.8318 -39.9444   \n",
       "5   1.8900   1.8900   1.8376   1.9329   1.9500   1.9004   1.8117   1.9936   \n",
       "6   0.4530   0.5862   0.3827   0.2697   0.4258   0.4900   0.3018   0.3182   \n",
       "7   4.6626   5.2215   5.6484   5.4790   5.3242   4.8095   4.4527   4.7209   \n",
       "8   0.4635   0.3870   0.3339   0.1859   0.1983   0.2108   0.2232   0.2357   \n",
       "9   3.2498   2.7075   3.9937   5.4440   6.1017   6.3028   6.3044   5.8166   \n",
       "\n",
       "   gy_x_40  gy_x_41  gy_x_42  gy_x_43  gy_x_44  gy_x_45  gy_x_46  gy_x_47  \\\n",
       "0   1.8470   1.8900   1.8018   1.9465   1.8447   1.9019   1.9436   1.9644   \n",
       "1   1.2395   1.1602   1.3416   1.4889   1.5844   1.5473   1.7995   2.1924   \n",
       "2   1.5145   1.2832   1.0322   0.9958   1.3400   1.3847   1.5067   1.6407   \n",
       "3   0.3751   0.2926   0.1743   0.5773   0.3987   0.4154   0.3406   0.4171   \n",
       "4 -47.2928 -48.8888 -48.6504 -50.3232 -54.3349 -54.4119 -51.5402 -51.2915   \n",
       "5   1.8068   1.7700   1.7941   1.7175   1.7548   1.7185   1.7100   1.7100   \n",
       "6   0.3700   0.3700   0.5479   0.4196   0.2876   0.4136   0.4914   0.4160   \n",
       "7   5.2960   5.5104   5.5460   5.5855   5.6100   5.4300   5.5500   5.5500   \n",
       "8   0.2662   0.3063   0.3464   0.3865   0.4266   0.4654   0.4635   0.3910   \n",
       "9   5.4900   4.8352   4.5578   4.7105   4.8902   5.1803   4.8872   4.8421   \n",
       "\n",
       "   gy_x_48  gy_x_49  gy_x_50  gy_x_51  gy_x_52  gy_x_53  gy_x_54  gy_x_55  \\\n",
       "0   2.0039   1.9171   1.8110   1.9500   1.9500   1.9035   1.7153   1.7100   \n",
       "1   2.3800   1.4277   0.6501   0.9538   1.1794   1.7458   2.0746   1.5669   \n",
       "2   2.0596   2.8472   2.5739   2.3754   1.9766   1.6644   1.4159   1.4430   \n",
       "3   0.3833   0.1765   0.9493   1.0036   0.1364   1.4277   0.0967   0.1755   \n",
       "4 -55.6815 -50.8832 -56.2621 -54.3011 -54.9282 -52.1709 -48.0357 -46.0270   \n",
       "5   1.7100   1.7760   1.8412   1.7760   1.8722   1.8404   1.8773   1.8081   \n",
       "6   0.2837   0.3491   0.3053   0.2472   0.3396   0.4173   0.1869   0.1423   \n",
       "7   5.4094   5.2941   5.3700   5.5591   6.2171   6.7449   6.8877   6.9035   \n",
       "8   0.0658   0.3058   0.2231   0.1890   0.2080   0.2269   0.2670   0.2187   \n",
       "9   5.0519   4.9096   5.1454   5.3642   5.2338   4.8877   4.8052   4.9164   \n",
       "\n",
       "   gy_x_56  gy_x_57  gy_x_58  gy_x_59  gy_x_60  gy_x_61  gy_x_62  gy_x_63  \\\n",
       "0   1.7647   1.8480   1.9120   1.8900   1.7850   1.9193   1.9083   1.8327   \n",
       "1   0.4900   0.4900   1.3816   2.3998   2.1164   1.5487   1.4604   2.2162   \n",
       "2   1.7202   1.8754   1.9866   2.1615   2.1993   2.2370   2.2747   2.3125   \n",
       "3   0.6072   0.7559   0.6080   0.4600   0.5492   0.1119   0.4563   0.3649   \n",
       "4 -43.1031 -38.2815 -39.1643 -36.3677 -28.3911  -8.3673  29.9372  22.6023   \n",
       "5   1.7795   1.8300   1.8676   1.8900   1.8855   1.8837   1.9196   1.8645   \n",
       "6   0.4645   0.6472   0.5937   0.2568   0.4203   0.4300   0.4596   0.5395   \n",
       "7   7.0200   7.0564   7.1847   7.3644   7.7726   7.8700   8.3582   8.6054   \n",
       "8   0.0413  -0.0797   0.2189   0.1425   0.2133   0.2400   0.2400   0.2647   \n",
       "9   5.0522   5.2479   5.2681   5.3824   5.5183   5.6430   5.6218   5.6077   \n",
       "\n",
       "   gy_x_64  gy_x_65  gy_x_66  gy_x_67  gy_x_68  gy_x_69  gy_x_70  gy_x_71  \\\n",
       "0   1.9050   1.9500   1.9005   1.8324   1.7891   1.6768   1.8061   1.7446   \n",
       "1   2.2227   2.1282   1.7909   1.3965   1.2981   1.0586   1.0960   1.0143   \n",
       "2   1.6446   0.9720   0.9478   0.6700   2.1758   2.5169   2.7611   2.2747   \n",
       "3   0.4645   0.4785   0.3981   0.5202   0.4676   0.3803   0.3063  -0.0025   \n",
       "4  25.6391  67.8927  35.4498  38.0374  18.6886  14.7661  14.9301  15.8499   \n",
       "5   1.9357   1.8937   1.7499   1.8056   1.8749   1.8022   1.7256   1.7739   \n",
       "6   0.5361   0.6487   0.3197   0.4416   0.4900   0.4683   0.3538   0.3166   \n",
       "7   8.8959   9.8651  11.0470  10.7912   9.5734   8.1626   6.5220   5.7371   \n",
       "8   0.3263   0.3879   0.0173   0.0904   0.1515   0.2043   0.2648   0.3409   \n",
       "9   6.0166   6.4017   6.2431   6.3845   6.5841   6.4807   6.8815   7.3350   \n",
       "\n",
       "   gy_x_72  gy_x_73  gy_x_74  gy_x_75  gy_x_76  gy_x_77  gy_x_78  gy_x_79  \\\n",
       "0   1.7421   1.7987   1.9185   1.8319   1.9500   1.9222   1.8445   1.8300   \n",
       "1   1.1673   1.4440   1.3065   1.2048   1.3695   1.4436   1.3447   0.9986   \n",
       "2   1.7705   1.2095   1.5844   1.4536   0.8052   1.5351   1.7963   1.4500   \n",
       "3   0.0663   0.3750   0.2095   0.7371   0.6006   0.1209   0.4953   0.6700   \n",
       "4  20.9914  19.5906  23.4708  40.3790  39.0908  21.6428  30.4496  32.0539   \n",
       "5   1.8070   1.8035   1.8300   1.8789   1.8900   1.8900   1.5622   1.5642   \n",
       "6   0.3556   0.5172   0.4593   0.3771   0.4300   0.4300   0.1840   0.2567   \n",
       "7   6.8873   3.8639   2.9160  -1.9108   2.8042   0.2303  -9.5104   3.2575   \n",
       "8   0.4170   0.4932   0.5693   0.4063   0.2739   0.3285   0.4041   0.2417   \n",
       "9   7.4827   7.3900   7.3264   7.8289   8.1898   8.3099   8.4182   8.5042   \n",
       "\n",
       "   gy_x_80  gy_x_81  gy_x_82  gy_x_83  gy_x_84  gy_x_85  gy_x_86  gy_x_87  \\\n",
       "0   1.8300   1.8300   1.7401   1.7100   1.8389   1.8900   1.9120   1.9495   \n",
       "1   0.7557   0.4060   0.2495   0.2347   0.9013   1.7256   1.8772   1.8375   \n",
       "2   1.1636   0.9182   0.9802   1.5753   1.5477   1.8710   2.2605   2.5049   \n",
       "3   0.6604   0.1333   0.4209   0.3959   0.3709   0.6455   0.5839   0.5733   \n",
       "4  35.7566  43.4743  40.4651  43.1525   3.6349  -2.2876  -4.5534  -7.4663   \n",
       "5   1.6529   1.7417   1.8517   1.8487   1.7246   1.8300   1.5812   1.8256   \n",
       "6   0.3681   0.5025   0.2713   0.1941   0.2812   0.3019   0.2097   0.1714   \n",
       "7  -4.4214  -4.2590   8.1401   4.0041   3.3388   5.6385   3.0085   5.6375   \n",
       "8   0.0792   0.0600   0.0703   0.1074   0.1445   0.1468   0.2508  -0.0266   \n",
       "9   8.5954   9.0624   9.2520   9.7213  11.0609  12.7177  12.5704  11.9598   \n",
       "\n",
       "   gy_x_88  gy_x_89  gy_x_90  gy_x_91  gy_x_92  gy_x_93  gy_x_94  gy_x_95  \\\n",
       "0   1.7700   1.7700   1.7700   2.0065   2.0054   1.9630   1.7260   1.7815   \n",
       "1   0.8428   0.5768   0.0679  -0.0413   0.3700   0.3700   0.1312   0.5717   \n",
       "2   2.4400   1.8944   1.8442   1.9200   2.4713   2.1826   2.0800   2.1973   \n",
       "3   0.2021   0.2683   0.4652   0.4832   0.4589   0.5195   0.3075   0.0955   \n",
       "4 -13.2976 -15.3569 -18.1088 -11.9723 -11.9526 -16.4344 -19.5692 -21.1635   \n",
       "5   1.7752   1.7755   1.7100   1.7582   1.7415   1.8900   1.8900   1.8300   \n",
       "6   0.2227   0.4889   0.3100   0.3849   0.5117   0.4228   0.1069   0.3244   \n",
       "7   9.7020  12.7514  -0.7938   5.8831   7.7738   8.4392   6.2310   5.9658   \n",
       "8   0.0173   0.0427   0.1609   0.2313   0.1634   0.1380   0.1800   0.1800   \n",
       "9  10.6971   9.4919   7.9060   8.1923   6.3974  21.0436 -18.3819  -8.5236   \n",
       "\n",
       "   gy_x_96  gy_x_97  gy_x_98  gy_x_99  gy_x_100  gy_x_101  gy_x_102  gy_x_103  \\\n",
       "0   1.8217   1.7826   1.7584   1.8914    1.8804    1.8566    1.9379    1.8300   \n",
       "1   0.8724   1.4927   1.5832   1.4504    2.0869    1.9252   -0.0936    0.8986   \n",
       "2   2.2234   2.2396   2.0323   1.7047    1.4119    1.6943    1.5691    1.6846   \n",
       "3   0.3271   0.3853   0.4905   0.7637    0.5818    0.2505    0.3732    0.5472   \n",
       "4 -18.7594  13.7120   1.7797  11.8731   34.0500    6.5738   27.8900    2.0379   \n",
       "5   1.7873   1.7759   1.8300   1.8300    1.9500    1.9063    1.8934    1.9372   \n",
       "6   0.3999   0.3385   0.3337   0.3207    0.4231    0.5256    0.3191    0.3584   \n",
       "7   9.0815  10.2919  10.5910   8.7943    1.4398    2.6274   -1.3903   -1.7081   \n",
       "8   0.1800  -0.2452  -0.1811  -0.0507    0.0797    0.2101    0.3024    0.2700   \n",
       "9 -10.2466  -0.4955   6.2315  -1.7427    6.1305   11.5808    4.7461    3.0300   \n",
       "\n",
       "   gy_x_104  gy_x_105  gy_x_106  gy_x_107  gy_x_108  gy_x_109  gy_x_110  \\\n",
       "0    1.8300    1.8579    1.9124    1.9489    1.7700    1.7700    1.7330   \n",
       "1    0.4777    0.6813    0.9867   -0.5795   -1.2043   -2.0611   -4.0740   \n",
       "2    1.8900    2.0373    2.1853    2.1072    1.9833    1.8881    1.7800   \n",
       "3    0.5769    0.3973    0.4944    0.3365   -0.2399    0.4790    0.0987   \n",
       "4   25.8650   26.9313    1.8460    4.2028    2.8650    1.1526   -0.0044   \n",
       "5    1.9183    1.8994    1.8632    1.8300    2.0863    1.8670    1.8621   \n",
       "6    0.4086    0.2356    0.4510    0.5288    0.3707    0.5086    0.3967   \n",
       "7   -4.2492   -7.2811   -6.1471   -0.3223    3.4814    5.2619    4.2793   \n",
       "8    0.2376    0.2052    0.2060    0.3232    0.4404    0.5372    0.3379   \n",
       "9    6.1817    6.0282    2.0910    6.4986   -0.9232    0.9952   -7.9380   \n",
       "\n",
       "   gy_x_111  gy_x_112  gy_x_113  gy_x_114  gy_x_115  gy_x_116  gy_x_117  \\\n",
       "0    1.7992    1.7250    1.8154    1.7755    1.7700    1.8080    1.7963   \n",
       "1   -5.0748   -5.3607   -4.7049   -4.3674   -3.7230   -3.3696   -3.4122   \n",
       "2    1.9881    2.1400    2.0686    2.1824    2.0287    1.7747    1.7196   \n",
       "3   -0.0960    0.3435    0.7414    0.6892    0.2351    0.2558    0.3538   \n",
       "4   -2.6719   -0.8399   -7.6431   -7.1170   -7.9731  -11.5689  -10.0281   \n",
       "5    1.9387    1.8897    1.8054    1.7700    1.7700    1.7882    1.8293   \n",
       "6    0.3428    0.5175    0.5989    0.3831    0.4864    0.6784    0.6438   \n",
       "7    3.0254    2.8500    3.7118    2.2466    1.5924    2.7411    2.0444   \n",
       "8    0.2723    0.3412    0.3939    0.0296    0.1561    0.2827    0.3299   \n",
       "9   -4.3691   -1.0983   -3.0286   -3.4398   -4.4062   -4.0780   -1.5542   \n",
       "\n",
       "   gy_x_118  gy_x_119  gy_x_120  gy_x_121  gy_x_122  gy_x_123  gy_x_124  \\\n",
       "0    1.8444    1.8709    1.8251    1.7837    1.6798    1.7305    1.8052   \n",
       "1   -3.4147   -3.4691   -3.1933   -1.5503   -0.9390    0.0129    0.5823   \n",
       "2    1.7938    2.0161    2.0800    2.6069    2.1108    2.1164    2.1400   \n",
       "3    0.4517    0.5369    0.5085    0.4585    0.5772    0.6551    0.6148   \n",
       "4   -3.8251   -1.6434   -2.6962   -3.3172   22.6986   16.4382   13.0886   \n",
       "5    1.6763    1.7804    1.8898    1.6572    1.7860    1.8900    1.7102   \n",
       "6    0.3531    0.1835    0.2740    0.4398    0.2741    0.5143    0.5817   \n",
       "7    1.9487    1.4692   -2.3772   -3.3960   -1.8803   -0.0203   -1.4879   \n",
       "8    0.3554    0.2546   -0.0174    0.3095    0.2790    0.2486   -0.0039   \n",
       "9   -0.0845    0.2577    0.1936   -5.1048   -6.4258   -5.1236   -1.2697   \n",
       "\n",
       "   gy_x_125  gy_x_126  gy_x_127  gy_x_128  gy_x_129  gy_x_130  gy_x_131  \\\n",
       "0    1.7431    1.8146    1.8300    1.7933    1.7561    1.6890    1.8340   \n",
       "1    0.6769    1.2238    2.9949    3.4862    3.9813    4.2512    8.4011   \n",
       "2    1.9668    1.8680    1.9893    1.7125    1.7502    1.7197    1.6662   \n",
       "3    0.4167    0.3401    0.4720    0.3976    0.4665    0.3547    0.3162   \n",
       "4   10.0009    4.9720   -4.7034   16.9375   24.2486   11.4213   -3.2805   \n",
       "5    1.7935    1.8726    1.9501    1.9668    1.7948    1.8764    1.8390   \n",
       "6    0.5039    0.2576    0.2042    0.5942    0.5239    0.3009    0.4491   \n",
       "7   -2.2899   -2.2260   -2.8834   -3.4960   -4.1086   -0.4827    0.9667   \n",
       "8    0.0967    0.1972    0.2977    0.3982    0.4611    0.1290   -0.2030   \n",
       "9    1.6313    0.8100   -1.1939   -1.0338   -0.6522   -0.9121    0.4256   \n",
       "\n",
       "   gy_x_132  gy_x_133  gy_x_134  gy_x_135  gy_x_136  gy_x_137  gy_x_138  \\\n",
       "0    1.8979    1.9368    1.8503    1.8588    1.7700    1.8004    1.8793   \n",
       "1   10.2448   12.1574   13.1638   16.0248   17.3005    7.4582    3.2173   \n",
       "2    2.0191    1.9991    1.9148    1.7748    1.8633    1.8311    1.8300   \n",
       "3    0.2400    0.2850    0.2447    0.3860    0.3200    0.5571    0.5958   \n",
       "4   -2.4078   -6.4913   -1.7709    1.9716    6.0562   25.8145    2.4368   \n",
       "5    1.8718    1.7700    1.7940    1.8300    1.8300    1.7716    1.7228   \n",
       "6    0.6019    0.4900    0.4602    0.5590    0.6237    0.6641    0.0613   \n",
       "7    1.4363    1.7107    1.1171   -0.1150   -1.4523   -0.9065    1.6352   \n",
       "8   -0.5350   -0.8671   -1.0286   -0.7893   -0.5500   -0.3107   -0.0714   \n",
       "9    2.3503    3.7466    4.7769    1.8532   -0.9174   -2.1426   -3.1616   \n",
       "\n",
       "   gy_x_139  gy_x_140  gy_x_141  gy_x_142  gy_x_143  gy_x_144  gy_x_145  \\\n",
       "0    2.0090    1.8588    1.7100    1.7791    1.8900    1.8979    1.9334   \n",
       "1   -3.8819   -7.4642   -5.5554   -3.6466   -3.4922    0.8553    0.6522   \n",
       "2    1.8646    1.7989    1.6035    1.7972    1.9035    2.0062    1.9789   \n",
       "3    0.5496    0.4013    0.1451    0.5500    0.5500    0.7247    0.4609   \n",
       "4   27.7766   18.1783    2.5123   17.6368   -1.6355    1.8963    2.1248   \n",
       "5    1.8885    1.9364    1.8765    1.8517    1.8244    1.7100    1.8499   \n",
       "6    0.2548    0.4384    0.4643    0.4830    0.1940    0.2725    0.3511   \n",
       "7    4.0986    4.7145    4.0395    3.2838    3.0802    2.3215    1.4950   \n",
       "8    0.1678    0.4071    0.6464    0.8857    1.1250    1.3642    1.6035   \n",
       "9   -4.0714   -2.8515   -1.6494   -0.5069    1.1736    1.9232    2.3744   \n",
       "\n",
       "   gy_x_146  gy_x_147  gy_x_148  gy_x_149  gy_x_150  gy_x_151  gy_x_152  \\\n",
       "0    1.9281    1.9498    1.8258    1.7732    1.7206    1.8300    1.8300   \n",
       "1    2.6773    2.5159    2.2770    1.3550    1.1089    3.7119    3.2547   \n",
       "2    1.9463    1.9137    1.7333    1.8900    1.9635    2.0103    1.9500   \n",
       "3    0.5739    0.6559    0.0989    0.1367    0.4329    0.5834    0.4584   \n",
       "4    1.8954    4.3548    2.6877    2.5996    2.6090    2.8419    2.2094   \n",
       "5    1.8017    1.7314    1.8255    1.8989    1.9376    1.8476    1.9034   \n",
       "6    0.2855    0.1509    0.2787    0.3856    0.4373    0.3818    0.3583   \n",
       "7    0.7093   -0.2467   -0.5052   -0.0593    0.7686    1.4716    1.6880   \n",
       "8    1.8428    1.7659    1.4323    1.0987    0.7651    0.4315    0.0979   \n",
       "9    0.2320   -0.3354   -0.2593   -1.4074   -1.5900   -1.5150   -0.9353   \n",
       "\n",
       "   gy_x_153  gy_x_154  gy_x_155  gy_x_156  gy_x_157  gy_x_158  gy_x_159  \\\n",
       "0    1.8620    1.7700    1.7700    1.8900    1.8900    1.8723    1.8593   \n",
       "1    1.5383   -0.8400   -1.0060    1.7764    2.6271    2.2200   -0.1376   \n",
       "2    1.7700    1.7748    1.7925    1.8101    1.8277    1.7555    1.9396   \n",
       "3    0.5845    0.5099    0.5606    0.5199    0.2688    0.5500    0.5500   \n",
       "4    2.1668    2.0279    2.9675    2.8590    2.9825    2.8797    3.0030   \n",
       "5    1.8140    1.7469    1.7754    1.8364    1.8360    1.7447    1.8717   \n",
       "6    0.4381    0.2855    0.3100    0.3100    0.4104    0.3998    0.6335   \n",
       "7    1.1673    0.2942    0.0838   -0.2223   -0.0359    0.2980   -0.0338   \n",
       "8    0.2764    0.7854    1.0124    0.4753    2.1854    0.3624    0.2821   \n",
       "9    0.2108    1.8751    2.6674    2.6793    2.3546    1.9494    1.6238   \n",
       "\n",
       "   gy_y_0  gy_y_1  gy_y_2  gy_y_3  gy_y_4  gy_y_5  gy_y_6  gy_y_7  gy_y_8  \\\n",
       "0  0.9200  0.8093  0.9482  1.0242  0.9800  0.9248  0.8359  0.9751  0.9667   \n",
       "1  2.7678  0.3317  0.0582  1.0272  2.0114  4.4213  5.0930  6.1237  6.9476   \n",
       "2  3.6600  3.9752  4.0609  4.2872  4.7013  5.2500  5.3330  5.3199  5.1968   \n",
       "3 -0.6700 -0.6938 -0.7188 -0.6303 -0.7287 -0.7158 -0.7668 -0.8052 -0.8572   \n",
       "4 -0.9691 -1.0957 -1.2773 -1.0286 -0.6626 -0.5843 -0.1521  0.4641 -0.0655   \n",
       "5  0.9695  1.0035  0.9287  0.9800  0.8664  0.7528  0.8578  0.8654  0.9800   \n",
       "6 -0.6700 -0.8541 -0.7301 -0.7758 -0.7454 -0.7836 -0.7369 -0.7300 -0.7300   \n",
       "7 -4.7002 -5.0784 -6.2469 -6.1000 -6.1000 -6.1000 -6.1000 -6.2197 -5.9229   \n",
       "8 -1.1921 -1.1369 -1.1111 -1.0684 -0.9915 -0.9181 -0.8904 -0.8628 -0.8351   \n",
       "9 -1.7073 -1.9128 -2.1142 -2.3480 -2.4400 -2.5000 -2.6050 -3.1122 -3.3661   \n",
       "\n",
       "   gy_y_9  gy_y_10  gy_y_11  gy_y_12  gy_y_13  gy_y_14  gy_y_15  gy_y_16  \\\n",
       "0  0.8935   0.8132   0.7381   0.8235   0.9200   0.8631   0.7320   0.8825   \n",
       "1  9.9266  11.9999  13.1630  13.8871  13.9715  14.4492  14.7794  14.0964   \n",
       "2  5.2002   5.0329   4.8805   4.6292   4.2620   3.9952   3.7800   3.5602   \n",
       "3 -0.8415  -0.8056  -0.8447  -0.8500  -0.7043  -0.8380  -0.9169  -0.8109   \n",
       "4  0.4718  -0.2526  -0.1218  -1.1136  -1.5180  -1.9043  -0.7506  -1.3851   \n",
       "5  0.9676   0.9291   0.8566   0.9424   0.7486   0.7900   0.7385   0.7857   \n",
       "6 -0.7300  -0.6909  -0.6585  -0.5801  -0.6360  -0.7293  -0.8122  -0.6556   \n",
       "7 -5.3668  -4.0517  -3.4371  -0.5485   0.9468   2.7821   4.7881   6.1033   \n",
       "8 -0.8075  -0.7636  -0.6916  -0.6197  -0.5488  -0.5090  -0.4900  -0.4212   \n",
       "9 -3.8349  -5.6437  -6.3155  -6.5529  -6.9397  -7.4068  -7.5449  -7.7478   \n",
       "\n",
       "   gy_y_17  gy_y_18  gy_y_19  gy_y_20  gy_y_21  gy_y_22  gy_y_23  gy_y_24  \\\n",
       "0   0.9800   0.9800   0.8468   0.8500   0.8179   0.8976   0.8510   1.0924   \n",
       "1  13.9368  14.0852  14.4539  14.6989  16.2565  19.3530  19.5060  19.6590   \n",
       "2   3.1655   2.8107   1.9571   1.5551   1.3688   1.0739   0.8091   0.4341   \n",
       "3  -0.8379  -0.7594  -0.7625  -0.7901  -0.7803  -0.7027  -0.9928  -0.9735   \n",
       "4  -1.4588  -1.5759  -1.4696  -1.3057   0.2748   0.4916   0.0782  -0.1362   \n",
       "5   0.8139   0.8577   0.9090   0.9200   0.8962   0.9049   0.8610   1.0129   \n",
       "6  -0.7711  -0.8482  -0.7373  -0.7430  -0.7503  -0.5539  -0.7335  -0.7735   \n",
       "7   5.9479   5.8187   5.9171   8.0343   8.7282   9.8589  10.9216  11.5230   \n",
       "8  -0.3703  -0.4104  -0.3934  -0.5072  -0.7108  -0.9984  -1.0147  -1.0924   \n",
       "9  -8.1800  -8.1635  -8.1504  -8.0139  -7.2535  -6.3614  -6.3693  -7.2607   \n",
       "\n",
       "   gy_y_25  gy_y_26  gy_y_27  gy_y_28  gy_y_29  gy_y_30  gy_y_31  gy_y_32  \\\n",
       "0   1.0217   1.0105   0.8917   0.8894   0.8472   0.9628   1.0359   0.9481   \n",
       "1  19.7569  20.0388  20.3201  20.2311  20.5625  21.6068  21.9566  23.0304   \n",
       "2   0.4437   0.6014   0.7960   0.7229   0.6111   0.6339   0.5165   0.4421   \n",
       "3  -0.8169  -0.7392  -0.8282  -0.7900  -0.8305  -0.7117  -0.8500  -0.8500   \n",
       "4  -0.4979  -0.4070  -0.4800  -0.9492  -1.3393  -1.1240  -0.5706  -0.3147   \n",
       "5   0.9200   0.9404   0.9727   1.0210   1.0608   1.0207   0.9770   0.9800   \n",
       "6  -0.8485  -0.6808  -0.7263  -0.7000  -0.6737  -0.6700  -0.6329  -0.8778   \n",
       "7  11.4289  10.7036  10.2192   9.8313   9.4933   8.9761   9.3922  10.1788   \n",
       "8  -0.7849  -0.7361  -0.6873  -0.6032  -0.4853  -0.3674  -0.3281  -0.3633   \n",
       "9  -7.9210  -6.9007  -5.8010  -5.3800  -4.9862  -4.0781  -1.9833   1.7662   \n",
       "\n",
       "   gy_y_33  gy_y_34  gy_y_35  gy_y_36  gy_y_37  gy_y_38  gy_y_39  gy_y_40  \\\n",
       "0   0.9850   0.9200   0.7948   0.9274   0.9638   0.9200   0.9749   0.9200   \n",
       "1  24.7822  25.7970  27.2089  27.1045  26.8084  28.3436  29.8410  30.2895   \n",
       "2   0.5469   0.4770   0.5116   0.5054   0.4361   0.3629   0.2896  -1.5554   \n",
       "3  -0.7220  -0.6569  -0.6188  -0.6695  -0.7450  -0.8488  -0.9200  -0.9583   \n",
       "4  -0.4702  -0.6611  -0.6734  -0.4841  -0.2353   0.2196  -0.3144  -0.7909   \n",
       "5   0.9800   1.0400   0.9542   0.8559   0.9200   0.9617   0.9745   0.9200   \n",
       "6  -0.8536  -0.7064  -0.8655  -0.9466  -0.9370  -0.9200  -0.7300  -0.7150   \n",
       "7  10.6836  10.9660  11.5094  11.9636  12.4401  13.1362  13.0739  12.8847   \n",
       "8  -0.2375  -0.0738  -0.0844  -0.1363  -0.1882  -0.2402  -0.2921  -0.3680   \n",
       "9   4.3503   7.3123   8.4515   9.0013   9.4728   9.7218  10.3766  10.6330   \n",
       "\n",
       "   gy_y_41  gy_y_42  gy_y_43  gy_y_44  gy_y_45  gy_y_46  gy_y_47  gy_y_48  \\\n",
       "0   0.9200   1.0082   0.7360   0.8671   0.9319   0.9736   0.8668   0.9128   \n",
       "1  30.4482  30.5933  31.0289  31.7646  32.3274  33.5137  33.7455  34.1381   \n",
       "2  -1.6484  -1.8586  -1.7133  -2.0040  -2.0088  -2.3198  -2.8275  -3.2796   \n",
       "3  -0.6645  -0.6271  -0.9072  -0.9496  -0.8134  -0.5960  -0.7107  -0.6133   \n",
       "4  -0.8028  -0.2625  -0.2346  -0.3146   0.1147  -0.8218   0.0488  -0.2930   \n",
       "5   0.9522   0.9800   0.8588   0.9200   0.9200   0.8626   0.8500   0.8500   \n",
       "6  -0.6754  -0.6111  -0.5091  -0.4069  -0.6681  -0.7719  -0.7256  -0.6838   \n",
       "7  12.8404  12.8760  14.3979  14.6500  14.2984  14.2296  14.3472  14.8038   \n",
       "8  -0.4566  -0.5452  -0.6338  -0.7224  -0.5529  -0.5095  -0.7271  -1.0448   \n",
       "9  11.2550  11.3343  11.0486  10.9360  11.0829  12.0085  12.1285  12.3300   \n",
       "\n",
       "   gy_y_49  gy_y_50  gy_y_51  gy_y_52  gy_y_53  gy_y_54  gy_y_55  gy_y_56  \\\n",
       "0   0.8247   0.9663   1.0305   0.9262   0.8345   0.8492   1.0399   0.9305   \n",
       "1  35.3196  35.2159  34.1144  34.0768  35.3157  36.0448  35.9303  35.4600   \n",
       "2  -3.1968  -2.7979  -1.7966  -1.5467  -1.2276  -1.5447  -1.4270  -0.9517   \n",
       "3  -0.7598  -0.6442  -0.6755  -0.8964  -0.3944  -0.8999  -0.9240  -0.7023   \n",
       "4   0.1236  -0.3530  -0.0962  -0.0876   0.3339  -0.4419   1.0155  -0.2822   \n",
       "5   0.9770   0.9444   1.0280   0.8708   0.9574   0.9800   0.9419   1.0810   \n",
       "6  -0.7693  -0.8201  -0.7838  -0.7448  -0.7836  -0.7257  -0.6923  -0.6856   \n",
       "7  15.0945  15.4031  15.6900  15.8796  16.5848  17.0493  17.4087  17.9329   \n",
       "8  -0.8481  -0.8099  -0.7629  -0.7061  -0.6494  -0.5868  -0.5500  -0.5500   \n",
       "9  12.1589  11.1358  10.6499   9.9177   9.4692   9.2981   8.9208   8.7982   \n",
       "\n",
       "   gy_y_57  gy_y_58  gy_y_59  gy_y_60  gy_y_61  gy_y_62  gy_y_63  gy_y_64  \\\n",
       "0   1.0400   1.0400   0.8792   0.9800   1.0093   0.9565   0.9200   0.9350   \n",
       "1  35.4600  35.2133  35.0991  35.5870  37.6514  38.0184  36.4037  37.1172   \n",
       "2   0.1808   0.7690   1.3059   1.5616   1.8174   2.0731   2.3289   3.9507   \n",
       "3  -0.5557  -0.5803  -0.6050  -0.6696  -0.7877  -0.6071  -0.7763  -0.7514   \n",
       "4  -0.8400   0.5098   0.4984  -0.2114  -1.0128   0.7424  -1.4983   0.2852   \n",
       "5   0.9571   1.0327   1.0526   1.0257   0.8814   0.8870   0.8274   0.9117   \n",
       "6  -0.8158  -0.7355  -0.6140  -0.6533  -0.7067  -0.6396  -0.8005  -0.8500   \n",
       "7  18.9176  19.7250  20.3078  21.1036  21.9868  23.2564  24.3198  25.1884   \n",
       "8  -0.5769  -0.8550  -1.0908  -1.1600  -1.1281  -1.0800  -1.0153  -0.9537   \n",
       "9   8.6121   8.3838   8.3241   8.6195   9.0388   9.3326   9.6538   9.8562   \n",
       "\n",
       "   gy_y_65  gy_y_66  gy_y_67  gy_y_68  gy_y_69  gy_y_70  gy_y_71  gy_y_72  \\\n",
       "0   0.8798   0.8436   0.9248   0.8803   0.9800   0.9800   0.8875   0.8179   \n",
       "1  37.9200  39.3804  39.6548  38.0077  35.8066  35.2773  34.9525  33.6333   \n",
       "2   4.3389   4.1120   3.8918   3.0927   3.1421   3.6163   3.8024   4.3892   \n",
       "3  -0.7357  -0.7759  -0.9932  -0.8049  -0.8003  -0.8197  -0.7441  -0.9186   \n",
       "4   1.4819   0.6279   1.2873   1.9768   0.2657  -1.6146  -0.9631  -3.3533   \n",
       "5   0.9237   0.8533   0.9132   0.9200   0.9478   0.9800   0.9761   0.8931   \n",
       "6  -0.8500  -0.7803  -0.6942  -0.7229  -0.7900  -0.7178  -0.7103  -0.5932   \n",
       "7  26.3990  26.4471  25.6137  23.9619  23.5600  24.1477  24.4753  22.9552   \n",
       "8  -0.8921  -0.7574  -0.8731  -0.9515  -1.0043  -1.0480  -1.0727  -1.0974   \n",
       "9  10.8399  11.8034  12.9343  13.9178  14.6502  15.7730  16.7350  17.6687   \n",
       "\n",
       "   gy_y_73  gy_y_74  gy_y_75  gy_y_76  gy_y_77  gy_y_78  gy_y_79  gy_y_80  \\\n",
       "0   0.9773   1.0842   0.9189   0.8670   0.9478   1.1166   1.1600   1.0066   \n",
       "1  31.4872  30.1138  29.6448  29.1047  28.7650  27.6546  26.5748  26.0169   \n",
       "2   3.6137   2.8054   2.5584   2.4523   2.9283   1.7822   1.3252   0.9415   \n",
       "3  -0.6821  -0.9200  -0.9426  -0.8746  -0.9010  -0.7844  -0.7511  -0.7900   \n",
       "4  -1.4691  -1.6529  -1.6010  -3.1345  -3.4315   8.1726  20.2955  20.8264   \n",
       "5   0.8500   0.9072   0.8629   0.8500   1.0475   0.9800   0.8758   0.8185   \n",
       "6  -0.6100  -0.6100  -0.5643  -0.6700  -0.6700  -0.6087  -0.6100  -0.7692   \n",
       "7  48.8716 -11.9309  -8.7833 -37.3218 -79.1112 -25.1290  12.6958   5.2763   \n",
       "8  -1.1221  -1.1468  -1.4298  -1.5222  -1.3164  -1.4558  -1.4295  -1.4031   \n",
       "9  18.2725  19.2678  20.0115  20.7002  21.0798  21.2770  21.7723  22.4583   \n",
       "\n",
       "   gy_y_81  gy_y_82  gy_y_83  gy_y_84  gy_y_85  gy_y_86  gy_y_87  gy_y_88  \\\n",
       "0   0.9500   1.1148   1.0405   0.9096   0.8500   0.8757   0.9194   1.0263   \n",
       "1  24.8215  24.5636  21.8624  20.8882  19.1646  18.4320  16.8691  16.0712   \n",
       "2   0.7269   0.4165   0.1236   0.3607   0.3586   0.3100  -0.4765  -1.3010   \n",
       "3  -0.7425  -0.5773  -0.6524  -0.7274  -0.6431  -0.7131  -0.6100  -0.6100   \n",
       "4   8.0154   1.5534  10.8875  27.0447  25.9375  21.5280  -2.1545  -3.5810   \n",
       "5   0.8129   0.8923   0.9352   0.8500   0.9510   0.8620   0.9106   0.8013   \n",
       "6  -0.7300  -0.7121  -0.7365  -0.7767  -0.7495  -0.8261  -0.7386  -0.8043   \n",
       "7 -18.9393 -16.0789  12.3172  34.6771  14.3078 -35.1044  -6.5173  22.6547   \n",
       "8  -1.5703  -1.6680  -1.5164  -1.3648  -1.1868  -0.9948  -0.9733  -0.8481   \n",
       "9  22.8766  23.1497  23.8007  24.4655  22.6521  21.3972  20.9443  21.2615   \n",
       "\n",
       "   gy_y_89  gy_y_90  gy_y_91  gy_y_92  gy_y_93  gy_y_94  gy_y_95  gy_y_96  \\\n",
       "0   0.9520   0.8773   0.9800   0.9200   0.9200   0.8976   1.0457   0.9883   \n",
       "1  15.7310  14.9793  14.6203  14.1823  14.5899  15.5500  16.1700  16.1700   \n",
       "2  -1.7700  -2.1287  -2.6384  -3.0312  -3.3948  -3.7459  -4.3285  -4.6297   \n",
       "3  -0.8500  -0.8500  -0.7477  -0.7300  -0.7375  -0.7894  -0.8413  -0.9133   \n",
       "4  -3.0141  -1.1133  -0.7675  -1.7916  -2.9289   0.5932   2.5515   2.9107   \n",
       "5   0.9473   0.9277   0.9200   0.9078   0.8618   0.8957   1.0303   1.0014   \n",
       "6  -0.8415  -0.7831  -0.6776  -0.8338  -0.6841  -0.6623  -0.8284  -0.7152   \n",
       "7  38.3919  34.1725  24.4878  20.4567  25.0645  31.8474  31.2957  30.2523   \n",
       "8  -0.7420  -0.7951  -0.7561  -0.5934  -0.5680  -0.4300  -0.4300  -0.4300   \n",
       "9  21.8829  22.5396  21.6779  69.6026 -45.9152 -30.8476 -71.7838 -54.0228   \n",
       "\n",
       "   gy_y_97  gy_y_98  gy_y_99  gy_y_100  gy_y_101  gy_y_102  gy_y_103  \\\n",
       "0   1.0274   1.0463   1.0693    0.8109    0.9466    1.0279    1.0976   \n",
       "1  16.0798  15.9962  15.8431   16.6571   17.5628   19.8427   19.4192   \n",
       "2  -5.1504  -5.4677  -5.8627   -6.3230   -6.3458   -5.7911   -5.3439   \n",
       "3  -0.7631  -0.7305  -0.9286   -0.8204   -0.7801   -0.6638   -0.7709   \n",
       "4   2.2552  -2.4005  -1.6253   -1.1310    1.3319    1.2534   -1.7634   \n",
       "5   1.0070   1.0244   0.8610    0.9314    0.9491    0.8587    0.9328   \n",
       "6  -0.7300  -0.7300  -0.6180   -0.6948   -0.7717   -0.8470   -0.8258   \n",
       "7  30.7668  27.2668  24.3120   22.4853   23.5513   23.7716    1.0266   \n",
       "8  -0.6462  -0.6450  -0.6198   -0.5946   -0.5693   -0.5215   -0.3993   \n",
       "9   8.7607  -0.3272 -20.6803  -19.3344    6.8739   27.8139   30.1273   \n",
       "\n",
       "   gy_y_104  gy_y_105  gy_y_106  gy_y_107  gy_y_108  gy_y_109  gy_y_110  \\\n",
       "0    1.0624    1.0958    1.0702    0.9243    1.0283    0.9612    0.8130   \n",
       "1   20.4788   23.7934   25.7717   29.8035   29.6074   29.6457   32.4965   \n",
       "2   -4.6882   -4.2511   -3.4378   -2.0136   -1.3008   -0.4193    0.3740   \n",
       "3   -0.7031   -0.8097   -0.8899   -0.8044   -1.0399   -0.8355   -0.9529   \n",
       "4   -2.6006    0.3243    6.5067    7.6515   -1.4289    6.5155   19.8303   \n",
       "5    0.9517    0.9706    0.9532    0.9868    0.9904    0.9570    0.9842   \n",
       "6   -0.8007   -0.8911   -0.5965   -0.6100   -0.6100   -0.6679   -0.6706   \n",
       "7    4.2426    0.0196   -4.5321   -4.7496   -5.8855   -7.7437  -11.0179   \n",
       "8   -0.2772   -0.1550   -0.0860   -0.2032   -0.3204   -0.4350   -0.5121   \n",
       "9    8.2650  -26.9459  -26.9683    2.1680   26.4034   33.0370   27.6982   \n",
       "\n",
       "   gy_y_111  gy_y_112  gy_y_113  gy_y_114  gy_y_115  gy_y_116  gy_y_117  \\\n",
       "0    0.8500    0.7900    0.7609    0.6810    0.8448    1.0463    0.9200   \n",
       "1   39.5034   45.1568   50.8196   53.8087   60.1851   67.3341   68.4540   \n",
       "2    1.7235    2.5822    2.7903    3.3684    3.4422    3.7659    4.2491   \n",
       "3   -0.9200   -0.7444   -0.6586   -0.7108   -0.8625   -0.7753   -0.7564   \n",
       "4   19.9969   21.2500   20.2784   20.7546   20.2403   12.5455   12.9806   \n",
       "5    1.0400    0.9201    0.9623    0.9800    0.8500    0.8318    0.7907   \n",
       "6   -0.7028   -0.8225   -0.7411   -0.5866   -0.6382   -0.6928   -0.7431   \n",
       "7  -11.8374  -12.0344  -10.2969   -9.9223  -11.3386  -13.8816  -17.3396   \n",
       "8   -0.7300   -0.7612   -0.8139   -0.9200   -0.9200   -0.9200   -0.9798   \n",
       "9   19.1833   20.1398   22.9673   24.2181   31.4246   32.6858   19.1284   \n",
       "\n",
       "   gy_y_118  gy_y_119  gy_y_120  gy_y_121  gy_y_122  gy_y_123  gy_y_124  \\\n",
       "0    0.9200    0.9200    0.7300    0.7300    0.8372    0.9174    0.9800   \n",
       "1   70.8446   73.3397   74.3460   77.3620   77.4489   76.9223   75.2321   \n",
       "2    4.5524    5.2826    5.6143    5.5418    4.9826    4.6272    4.6935   \n",
       "3   -0.7374   -0.8239   -0.7670   -0.6671   -0.6972   -0.7751   -0.9124   \n",
       "4    5.3956   17.5212   21.5649   13.5628   18.6018   11.7393   11.1008   \n",
       "5    0.7974    0.8575    0.9365    0.9224    0.9653    0.8255    0.8500   \n",
       "6   -0.7691   -0.6165   -0.7834   -0.7485   -0.7608   -0.6943   -0.8041   \n",
       "7  -21.5019  -23.6595  -21.8339  -22.9316  -27.2129  -30.1782  -29.9222   \n",
       "8   -1.0561   -1.0168   -0.8207   -0.6077   -0.4772   -0.3467   -0.5794   \n",
       "9    3.4095    1.3767   14.8596   13.9857    4.5143    4.7634    6.1060   \n",
       "\n",
       "   gy_y_125  gy_y_126  gy_y_127  gy_y_128  gy_y_129  gy_y_130  gy_y_131  \\\n",
       "0    0.9441    0.8667    0.9079    0.8404    1.0646    1.0188    0.8873   \n",
       "1   74.6219   73.9537   73.5175   72.8176   70.9672   70.1798   63.3764   \n",
       "2    4.0636    3.5430    3.2562    2.8626    2.7494    2.2100    1.8957   \n",
       "3   -0.8781   -0.7719   -0.6304   -0.6100   -0.7900   -0.7290   -0.5749   \n",
       "4   23.5817   16.4835   12.3521    5.3858   12.0532   -0.2807    0.2496   \n",
       "5    0.8500    0.8500    0.9198    0.8668    0.9552    0.9800    0.9800   \n",
       "6   -0.8430   -0.7476   -0.6942   -0.6258   -0.6112   -0.7019   -0.7805   \n",
       "7  -28.2658  -26.6543  -16.0031  -16.7313  -17.4595  -14.2938  -10.9385   \n",
       "8   -0.5246   -0.4697   -0.4149   -0.3601   -0.3233   -0.4757   -0.6282   \n",
       "9    4.1736    4.3178    3.9188    2.7844    1.5110   -0.1385   -2.4459   \n",
       "\n",
       "   gy_y_132  gy_y_133  gy_y_134  gy_y_135  gy_y_136  gy_y_137  gy_y_138  \\\n",
       "0    0.9107    0.8654    0.9552    0.9824    0.9200    0.9200    0.9200   \n",
       "1   61.5282   56.6308   53.7414   47.9906   41.9361   47.4524   52.0462   \n",
       "2    1.4708    0.9235    0.5996    0.2873   -0.1355   -0.6613   -1.4203   \n",
       "3   -0.8486   -0.8500   -0.8141   -0.8060   -0.7300   -0.8357   -0.7583   \n",
       "4    0.0589    2.3871    1.4390    0.6974    0.8338   -0.6029   -1.6520   \n",
       "5    0.8606    0.9239    1.0040    1.1057    1.0602    1.0108    0.9200   \n",
       "6   -0.7041   -0.4666   -0.4598   -0.7720   -0.6563   -0.6159   -0.7895   \n",
       "7   -6.4674   -1.4212    2.4088    7.6876   12.7464   15.4144   16.5461   \n",
       "8   -0.7806   -0.9331   -1.0213   -0.9585   -0.8957   -0.8330   -0.7702   \n",
       "9   -6.2108  -10.8532  -13.0964  -12.9596  -12.9837  -14.0592  -15.8054   \n",
       "\n",
       "   gy_y_139  gy_y_140  gy_y_141  gy_y_142  gy_y_143  gy_y_144  gy_y_145  \\\n",
       "0    0.9790    1.0178    0.9570    0.9430    0.9800    0.9721    0.9366   \n",
       "1   52.9483   54.0077   52.3710   50.7343   47.1830   48.2812   50.2009   \n",
       "2   -1.6938   -2.0966   -2.2000   -1.7542   -1.3266   -0.7008   -0.5120   \n",
       "3   -0.7183   -0.7160   -0.8463   -0.6213   -0.6627   -0.5589   -0.6653   \n",
       "4   -1.8535   -0.4063    0.1098   -0.7576   -0.9705   -1.7835   -1.5780   \n",
       "5    1.0371    1.0400    1.0131    0.8947    0.8755    0.9200    0.8334   \n",
       "6   -0.7146   -0.7132   -0.6613   -0.6241   -0.6656   -0.6408   -0.6160   \n",
       "7   16.3600   16.4546   17.0618   17.7191   14.8033   12.0145   10.0438   \n",
       "8   -0.7075   -0.6447   -0.5819   -0.5192   -0.4564   -0.3936   -0.3309   \n",
       "9  -16.1825  -16.5347  -17.5532  -18.4731  -19.5876  -20.3043  -19.5398   \n",
       "\n",
       "   gy_y_146  gy_y_147  gy_y_148  gy_y_149  gy_y_150  gy_y_151  gy_y_152  \\\n",
       "0    0.8961    0.9200    0.9176    0.8869    0.8562    0.9802    1.0582   \n",
       "1   49.8573   49.0122   48.6994   47.5629   47.8978   44.1387   43.8567   \n",
       "2   -0.3463   -0.1806    1.0138    3.2915    3.6000    3.6643    3.8936   \n",
       "3   -0.7300   -0.7300   -0.7300   -0.8067   -0.8500   -0.7201   -0.6700   \n",
       "4   -1.6741   -0.6492   -1.6168    0.8594   -0.2082   -1.0412   -1.3585   \n",
       "5    0.9833    1.0893    0.9199    0.8500    0.8500    0.7988    0.8267   \n",
       "6   -0.7341   -0.6391   -0.5593   -0.5849   -0.6451   -0.6941   -0.7900   \n",
       "7    8.5319    6.9720    4.5431    2.6207    0.2896   -1.8339   -3.8664   \n",
       "8   -0.2681   -0.3063   -0.4263   -0.5463   -0.6663   -0.7863   -0.9063   \n",
       "9  -14.1252  -11.9468  -10.8409   -7.1859   -3.8738    0.7261    4.3276   \n",
       "\n",
       "   gy_y_153  gy_y_154  gy_y_155  gy_y_156  gy_y_157  gy_y_158  gy_y_159  \\\n",
       "0    0.8207    0.8377    0.9174    0.9200    0.9200    1.0823    1.1000   \n",
       "1   45.4326   45.2923   44.9336   42.1668   39.0445   39.2196   40.7940   \n",
       "2    4.0304    4.0852    4.0675    4.0499    4.0323    2.7296    2.3421   \n",
       "3   -0.6700   -0.6700   -0.6700   -0.6880   -0.6947   -0.6279   -0.5298   \n",
       "4   -1.4382   -1.9130   -2.7627   -3.2964   -3.2652    0.2907    5.1769   \n",
       "5    0.8897    0.9200    0.9714    0.8749    0.8290    0.9547    1.0817   \n",
       "6   -0.7250   -0.5680   -0.7059   -0.5547   -0.7490   -0.8500   -0.7531   \n",
       "7   -6.0820   -7.9396   -8.4945   -9.3122  -10.9047  -12.8323  -13.3469   \n",
       "8   -0.7394   -0.5971   -0.7489   -0.7868   -1.1144   -1.3090   -1.3762   \n",
       "9    5.9966    6.9396    8.2436   10.1449   10.8737   10.8202    9.8475   \n",
       "\n",
       "    gy_z_0   gy_z_1   gy_z_2   gy_z_3   gy_z_4   gy_z_5   gy_z_6   gy_z_7  \\\n",
       "0   1.4144   1.4600   1.3755   1.4126   1.5632   1.6751   1.5230   1.4551   \n",
       "1   0.5885   2.1981   2.2986   1.8415   1.4669   1.2278   1.2838   0.5377   \n",
       "2   0.9728   1.0948   1.0091   1.0293   0.8503   0.9334   0.7900   0.7166   \n",
       "3  -0.4900  -0.4662  -0.4412  -0.2840  -0.3993  -0.3929  -0.3001  -0.2923   \n",
       "4   1.6647   1.1912   0.8504   0.4956   0.4596   0.0669   0.7421   1.7869   \n",
       "5   1.5548   1.5718   1.5343   1.4088   1.3476   1.5425   1.4622   1.4000   \n",
       "6  -0.5649  -0.4692  -0.4301  -0.4900  -0.4900  -0.4900  -0.5466  -0.5137   \n",
       "7 -17.1218 -20.6619 -26.9107 -32.2777 -34.2366 -35.1507 -35.9570 -37.5696   \n",
       "8  -0.6582  -0.6700  -0.6700  -0.4405  -0.4662  -0.4891  -0.4764  -0.4636   \n",
       "9  -0.7300  -1.2141  -2.0916  -2.5915  -3.5554  -4.4250  -5.8434  -7.9494   \n",
       "\n",
       "    gy_z_8   gy_z_9  gy_z_10  gy_z_11  gy_z_12  gy_z_13  gy_z_14  gy_z_15  \\\n",
       "0   1.5900   1.5407   1.4232   1.4519   1.5240   1.5751   1.4600   1.4600   \n",
       "1   0.4161   0.0565  -0.1030  -0.4300  -0.4534  -0.5068  -0.4541  -0.6700   \n",
       "2   0.7765   0.8500   0.9188   0.9402   0.8167   0.6866   0.8907   0.8944   \n",
       "3  -0.4342  -0.3270  -0.4300  -0.4300  -0.4857  -0.4900  -0.4218  -0.4749   \n",
       "4  22.9549  26.6567  34.7839  37.7200  33.5356  43.5541  45.0241  46.1248   \n",
       "5   1.4254   1.5030   1.4197   1.5930   1.6410   1.5497   1.4199   1.3400   \n",
       "6  -0.5261  -0.4237  -0.4663  -0.5015  -0.5799  -0.4640  -0.4893  -0.4995   \n",
       "7 -47.2240 -50.5220 -54.4920 -56.0168 -62.5509 -66.8423 -68.9903 -70.7587   \n",
       "8  -0.4508  -0.4381  -0.4234  -0.4054  -0.3874  -0.3737  -0.4929  -0.4430   \n",
       "9  -9.6896 -11.9626 -14.4462 -17.9976 -20.6421 -23.8820 -27.6183 -31.5670   \n",
       "\n",
       "   gy_z_16  gy_z_17  gy_z_18  gy_z_19  gy_z_20  gy_z_21  gy_z_22  gy_z_23  \\\n",
       "0   1.4775   1.5300   1.5300   1.5300   1.4866   1.4975   1.5797   1.5900   \n",
       "1  -0.5941  -0.2064  -0.1463  -0.2673  -0.3587  -0.7161  -1.0405  -1.0660   \n",
       "2   1.0848   1.1623   1.2800   1.2800   1.3749   1.4691   1.5160   1.4729   \n",
       "3  -0.4494  -0.4300  -0.4300  -0.3239  -0.3652  -0.4348  -0.4737  -0.5801   \n",
       "4  49.4690  51.1313  51.1730  49.7412  45.8258  44.9139  42.8685  42.4319   \n",
       "5   1.3614   1.4345   1.4936   1.5300   1.4000   1.4442   1.5300   1.4659   \n",
       "6  -0.5348  -0.4963  -0.4918  -0.5276  -0.4900  -0.4900  -0.4900  -0.4335   \n",
       "7 -72.1001 -73.3675 -73.5500 -73.5500 -73.3145 -73.0797 -72.6860 -71.4921   \n",
       "8  -0.3944  -0.2397  -0.1996  -0.2166  -0.3115  -0.4175  -0.5141  -0.5326   \n",
       "9 -33.5960 -36.9808 -39.6335 -42.2226 -46.7874 -49.9433 -52.8239 -54.5238   \n",
       "\n",
       "   gy_z_24  gy_z_25  gy_z_26  gy_z_27  gy_z_28  gy_z_29  gy_z_30  gy_z_31  \\\n",
       "0   1.4038   1.4392   1.4600   1.5146   1.5638   1.4392   1.5099   1.4624   \n",
       "1  -1.0915  -1.1817  -1.3198  -1.3621  -1.3067  -1.0728  -1.2571  -1.3947   \n",
       "2   1.4045   1.4818   1.6157   1.5300   1.5724   1.4623   1.4909   1.4000   \n",
       "3  -0.5485  -0.4723  -0.4392  -0.5500  -0.4868  -0.4965  -0.5361  -0.5692   \n",
       "4  45.2745  40.9136  39.6797  44.7289  45.6641  45.7086  45.0092  44.0046   \n",
       "5   1.5200   1.5732   1.5504   1.5827   1.5078   1.5183   1.5552   1.5300   \n",
       "6  -0.4735  -0.6120  -0.4761  -0.5426  -0.4900  -0.4375  -0.5448  -0.4015   \n",
       "7 -70.5415 -70.5767 -71.3697 -71.1552 -70.5613 -70.2233 -69.4480 -68.6462   \n",
       "8  -0.4938  -0.5449  -0.4961  -0.4473  -0.3211  -0.3408  -0.3604  -0.2766   \n",
       "9 -56.3867 -58.4550 -59.9392 -61.8565 -63.6916 -65.4552 -67.8277 -68.3135   \n",
       "\n",
       "   gy_z_32  gy_z_33  gy_z_34  gy_z_35  gy_z_36  gy_z_37  gy_z_38  gy_z_39  \\\n",
       "0   1.5581   1.5630   1.5093   1.4626   1.5826   1.5462   1.5675   1.3013   \n",
       "1  -1.3390  -0.9658  -0.9326  -1.3782  -1.8300  -1.8300  -1.7007  -1.5907   \n",
       "2   1.5039   1.5931   1.6630   1.6692   1.6500   1.7147   1.8026   1.8904   \n",
       "3  -0.4918  -0.3860  -0.4900  -0.4900  -0.5495  -0.5125  -0.4629  -0.4300   \n",
       "4  41.1862  46.1278  48.5708  45.3313  49.1340  49.5542  48.3818  48.4086   \n",
       "5   1.5300   1.5300   1.5376   1.5471   1.4659   1.4958   1.5483   1.5300   \n",
       "6  -0.5500  -0.4871  -0.3936  -0.3914  -0.5038  -0.5070  -0.5816  -0.5500   \n",
       "7 -67.8175 -68.2442 -68.7584 -69.2779 -70.1051 -71.4589 -72.8351 -73.5376   \n",
       "8  -0.0946  -0.1925  -0.3562  -0.3876  -0.4250  -0.4623  -0.4997  -0.5371   \n",
       "9 -68.0011 -66.5896 -64.7460 -63.9846 -63.2883 -62.2105 -60.6757 -60.1479   \n",
       "\n",
       "   gy_z_40  gy_z_41  gy_z_42  gy_z_43  gy_z_44  gy_z_45  gy_z_46  gy_z_47  \\\n",
       "0   1.3570   1.4640   1.5741   1.5312   1.5129   1.4600   1.4600   1.4768   \n",
       "1  -1.8915  -2.0659  -2.0236  -2.4124  -2.7044  -2.4014  -1.7906  -1.8292   \n",
       "2   2.0446   1.8932   1.6422   1.6058   1.7640   1.6959   1.7299   2.3310   \n",
       "3  -0.5066  -0.4790  -0.4043  -0.4300  -0.4300  -0.4227  -0.3700  -0.3700   \n",
       "4  50.6591  50.6304  51.4739  51.3806  49.7983  50.4493  48.8657  52.7349   \n",
       "5   1.5029   1.5619   1.6017   1.4763   1.5420   1.4268   1.3892   1.4522   \n",
       "6  -0.5500  -0.5500  -0.6111  -0.5595  -0.5084  -0.5500  -0.5500  -0.6011   \n",
       "7 -74.0206 -74.3014 -74.4441 -76.3529 -77.7621 -79.8609 -82.4077 -85.5771   \n",
       "8  -0.5334  -0.5081  -0.4828  -0.4575  -0.4322  -0.3946  -0.3965  -0.4690   \n",
       "9 -58.6365 -57.9602 -57.7622 -57.7975 -58.1613 -58.1073 -58.0605 -58.1648   \n",
       "\n",
       "   gy_z_48  gy_z_49  gy_z_50  gy_z_51   gy_z_52  gy_z_53   gy_z_54   gy_z_55  \\\n",
       "0   1.5228   1.4600   1.4463   1.5197    1.6438   1.4600    1.4919    1.5900   \n",
       "1  -2.3200  -1.8907  -0.7025  -0.6672   -1.0495  -1.4108   -1.5603   -1.5197   \n",
       "2   2.8008   2.7420   2.6460   2.0049    1.7847   1.5495    1.8912    1.6317   \n",
       "3  -0.3100  -0.4223  -0.4042  -0.3700   -0.3364  -0.5436   -0.5052   -0.4478   \n",
       "4  51.7771  33.5093  49.6762  51.3498   42.3087  46.6799   51.0673   53.2684   \n",
       "5   1.5138   1.5300   1.5300   1.5770    1.5092   1.4722    1.4600    1.6442   \n",
       "6  -0.5176  -0.5893  -0.6100  -0.6038   -0.5056  -0.3891   -0.6635   -0.5947   \n",
       "7 -87.4609 -89.0601 -90.1057 -91.6009 -107.9690 -97.9858 -100.7959 -103.3387   \n",
       "8  -0.4900  -0.5461  -0.4698  -0.4300   -0.4300  -0.4300   -0.4764   -0.5373   \n",
       "9 -58.2300 -57.9893 -58.1185 -58.5656  -59.2515 -59.8663  -60.9283  -62.2130   \n",
       "\n",
       "    gy_z_56   gy_z_57   gy_z_58   gy_z_59   gy_z_60   gy_z_61   gy_z_62  \\\n",
       "0    1.5900    1.4090    1.4410    1.5800    1.6425    1.5900    1.5900   \n",
       "1    0.3072    0.9406   -0.0119   -2.7780   -2.9758   -1.3418   -0.5534   \n",
       "2    1.8278    1.9808    1.7385    1.5673    1.5275    1.4876    1.4478   \n",
       "3   -0.4005   -0.3757   -0.4003   -0.4250   -0.4300   -0.3908   -0.4300   \n",
       "4   46.0350   50.5582   36.8625   54.2504   61.2857   38.1013   72.6728   \n",
       "5    1.5900    1.5404    1.5414    1.5426    1.5300    1.5300    1.5452   \n",
       "6   -0.4333   -0.3442   -0.4245   -0.5419   -0.4634   -0.4900   -0.4900   \n",
       "7 -106.7638 -111.5391 -115.9350 -118.4330 -121.7395 -125.2519 -130.3856   \n",
       "8   -0.5125   -0.5034   -0.6100   -0.6100   -0.5633   -0.5500   -0.5500   \n",
       "9  -63.3458  -64.4387  -65.4644  -66.6634  -68.0472  -69.1895  -70.6419   \n",
       "\n",
       "    gy_z_63   gy_z_64   gy_z_65   gy_z_66   gy_z_67   gy_z_68   gy_z_69  \\\n",
       "0    1.5327    1.5125    1.5285    1.4869    1.3448    1.5188    1.4332   \n",
       "1    0.1580    0.4549    0.5178   -1.9956   -2.7239   -2.0655   -2.3053   \n",
       "2    1.4080    1.1735    0.8920    1.0676    1.8682    2.2830    2.4851   \n",
       "3   -0.4163   -0.3914   -0.4900   -0.4900   -0.3547   -0.4335   -0.5191   \n",
       "4   62.2513   61.7647   33.9029   58.1249   52.1377   59.6249   49.8301   \n",
       "5    1.5728    1.5300    1.5900    1.5500    1.4457    1.5123    1.4322   \n",
       "6   -0.4900   -0.4746   -0.4371   -0.4900   -0.5258   -0.4971   -0.4300   \n",
       "7 -134.1781 -138.2253 -142.3790 -149.1120 -159.1151 -165.9375 -172.5749   \n",
       "8   -0.5344   -0.4955   -0.4566   -0.6273   -0.7004   -0.7143   -0.6878   \n",
       "9  -72.2554  -73.8848  -76.6163  -79.1234  -81.0546  -83.0518  -85.2599   \n",
       "\n",
       "    gy_z_70   gy_z_71   gy_z_72   gy_z_73   gy_z_74   gy_z_75   gy_z_76  \\\n",
       "0    1.5521    1.4975    1.4975    1.4908    1.5458    1.5900    1.5438   \n",
       "1   -3.1397   -4.7049   -6.4305   -7.2082   -6.9584   -6.7466   -6.7110   \n",
       "2    2.2437    1.8877    1.3406    1.7247    1.9852    1.9105    1.9459   \n",
       "3   -0.3852   -0.4230   -0.4288   -0.4300   -0.4053   -0.3926   -0.4300   \n",
       "4   32.0315   38.0032   22.8359    0.6119    4.8467    2.9715    8.9041   \n",
       "5    1.4000    1.4600    1.4370    1.4000    1.4000    1.4000    1.3426   \n",
       "6   -0.4781   -0.5969   -0.5188   -0.3918   -0.3700   -0.4443   -0.5237   \n",
       "7 -177.6797 -180.0966 -181.6590 -185.1513 -167.2846  -22.1587    7.2452   \n",
       "8   -0.6740   -0.6864   -0.6987   -0.7111   -0.7234   -0.6970   -0.6700   \n",
       "9  -89.2262  -91.7551  -94.7043  -97.1137 -100.6929 -105.3923 -109.0312   \n",
       "\n",
       "    gy_z_77   gy_z_78   gy_z_79   gy_z_80   gy_z_81   gy_z_82   gy_z_83  \\\n",
       "0    1.4602    1.5755    1.4682    1.5300    1.5300    1.5749    1.5900   \n",
       "1   -6.5627   -4.4451   -2.9682   -2.4891   -0.8045   -0.0307    2.4611   \n",
       "2    1.7109    1.7175    1.6500    1.9885    2.1920    1.9111    2.1144   \n",
       "3   -0.5380   -0.4644   -0.3633   -0.2420   -0.3700   -0.3411   -0.2619   \n",
       "4    6.4773    6.3039    2.7119    2.8824    2.2905    2.6049    2.8022   \n",
       "5    1.4901    1.4026    1.3881    1.4682    1.5406    1.5772    1.3607   \n",
       "6   -0.4450   -0.6100   -0.5392   -0.5892   -0.5715   -0.6279   -0.6035   \n",
       "7  -49.9416  -33.7724  -20.2747  -53.7877  -47.9816  -12.0282  -31.3230   \n",
       "8   -0.6700   -0.7300   -0.7300   -0.7300   -0.7300   -0.7403   -0.7774   \n",
       "9 -112.2816 -115.4898 -119.0219 -125.0011 -128.6016 -130.7785 -136.3213   \n",
       "\n",
       "    gy_z_84   gy_z_85   gy_z_86   gy_z_87   gy_z_88   gy_z_89   gy_z_90  \\\n",
       "0    1.4793    1.5609    1.5520    1.5895    1.6637    1.6841    1.6152   \n",
       "1    3.2815    4.2443    4.5538    5.9829    7.2280    7.5311    7.6379   \n",
       "2    2.3171    1.9759    1.8032    1.8129    1.7797    2.1911    2.0800   \n",
       "3   -0.1827   -0.4055   -0.3488   -0.2862   -0.3653   -0.3155   -0.3536   \n",
       "4    4.8807    5.7347    6.0547    8.5410    7.8901    6.1875    6.5687   \n",
       "5    1.3546    1.4917    1.4822    1.5300    1.5187    1.4863    1.6423   \n",
       "6   -0.5633   -0.4900   -0.5203   -0.4986   -0.5500   -0.5500   -0.4300   \n",
       "7  -27.2569   -6.3145  -32.7672  -16.3968    8.3721   27.7660   26.1883   \n",
       "8   -0.8145   -0.7503   -0.5874   -0.5632   -0.4645   -0.5155   -0.5500   \n",
       "9 -140.0124 -151.3620 -156.4650 -162.1518 -168.6229 -171.6684 -178.2646   \n",
       "\n",
       "    gy_z_91   gy_z_92   gy_z_93  gy_z_94  gy_z_95  gy_z_96  gy_z_97  gy_z_98  \\\n",
       "0    1.4565    1.4654    1.5149   1.5043   1.5312   1.5636   1.4398   1.5512   \n",
       "1    7.2926    5.1867    5.4673   6.3775   6.5300   6.5300   6.0766   5.6517   \n",
       "2    1.8216    1.9406    1.9587   1.9863   2.0739   2.2132   2.4004   2.6297   \n",
       "3   -0.3316   -0.3700   -0.3700  -0.3700  -0.3700  -0.4786  -0.4524  -0.3695   \n",
       "4    8.1220    7.1984    7.7416   8.0843   5.7726   5.9869   7.5200   7.4141   \n",
       "5    1.5536    1.5795    1.5081   1.4451   1.5187   1.4849   1.5630   1.5900   \n",
       "6   -0.4675   -0.4683   -0.4159  -0.5161  -0.4444  -0.5199  -0.6100  -0.5508   \n",
       "7   23.7678   27.1435   24.8009  24.4080  28.9786  37.4343  48.8107  68.2322   \n",
       "8   -0.4774   -0.4466   -0.4720  -0.4900  -0.4900  -0.4900  -0.4979  -0.4775   \n",
       "9 -181.2436 -180.7526 -130.3430 -43.3783 -94.9046 -65.6824  -2.3800 -17.6051   \n",
       "\n",
       "   gy_z_99  gy_z_100  gy_z_101  gy_z_102  gy_z_103  gy_z_104  gy_z_105  \\\n",
       "0   1.5235    1.5804    1.5300    1.5300    1.5324    1.5300    1.4695   \n",
       "1   2.9795    0.8431    1.0048    1.3065    0.3898   -2.2819   -5.1899   \n",
       "2   2.5388    2.4400    2.7616    2.5027    2.6501    2.4952    2.0527   \n",
       "3  -0.3823   -0.4083   -0.4900   -0.4900   -0.4109   -0.4300   -0.4809   \n",
       "4   7.4746    8.2821    6.3994    6.8658    6.4217    5.2919    3.8964   \n",
       "5   1.5335    1.4837    1.5754    1.3717    1.4276    1.4686    1.5096   \n",
       "6  -0.5500   -0.5500   -0.5500   -0.3730   -0.4426   -0.5179   -0.5500   \n",
       "7  67.6418   59.3484   62.9705   24.0655    3.3062  -17.6513  -34.9137   \n",
       "8  -0.4649   -0.4523   -0.4397   -0.4230   -0.3931   -0.3632   -0.3333   \n",
       "9 -36.6984  -12.1699    3.1556  -20.6012  -28.8496   -9.3915   -5.0308   \n",
       "\n",
       "   gy_z_106  gy_z_107  gy_z_108  gy_z_109  gy_z_110  gy_z_111  gy_z_112  \\\n",
       "0    1.4935    1.6455    1.6983    1.6312    1.6085    1.5267    1.5375   \n",
       "1   -6.7917  -11.1997  -12.3669  -12.8720  -14.3786  -13.8345  -14.0178   \n",
       "2    1.8753    1.7972    1.5393    1.3962    1.1700    1.1588    0.9989   \n",
       "3   -0.4439   -0.4834   -0.4900   -0.4504   -0.4300   -0.4540   -0.4560   \n",
       "4    3.7707    2.9906    3.1459    3.3826    3.2412   16.2055   12.2176   \n",
       "5    1.4987    1.5657    1.6004    1.4000    1.4321    1.5168    1.4005   \n",
       "6   -0.4451   -0.5553   -0.5948   -0.4879   -0.5500   -0.4900   -0.5175   \n",
       "7  -35.7942  -25.2537  -20.4125  -18.5154   -7.2821   -1.0596    0.6334   \n",
       "8   -0.3269   -0.4029   -0.4789   -0.5525   -0.5911   -0.5177   -0.5656   \n",
       "9  -11.8347   -0.7030   22.5797   36.1725   33.6713   36.6732   42.4651   \n",
       "\n",
       "   gy_z_113  gy_z_114  gy_z_115  gy_z_116  gy_z_117  gy_z_118  gy_z_119  \\\n",
       "0    1.5439    1.4174    1.4000    1.4380    1.5331    1.4600    1.4600   \n",
       "1  -14.5385  -14.0357  -12.5491   -9.6614   -9.4913   -8.3483   -7.9321   \n",
       "2    1.0130    0.9624    0.8087    1.0805    1.2056    1.0942    0.9790   \n",
       "3   -0.4543   -0.4804   -0.4552   -0.4753   -0.4564   -0.4374   -0.4300   \n",
       "4    3.8511    4.2284    3.3867    2.9340    2.7745    2.4633    1.7815   \n",
       "5    1.5340    1.4757    1.5300    1.5088    1.4608    1.4570    1.5225   \n",
       "6   -0.5989   -0.3934   -0.3418   -0.5728   -0.5707   -0.4926   -0.4300   \n",
       "7    4.7808   13.5467   16.2081   18.1958   21.6141   21.3355   15.9385   \n",
       "8   -0.5919   -0.5985   -0.5496   -0.5006   -0.4701   -0.4446   -0.4300   \n",
       "9   44.3594   41.8255   37.0230   51.1619   62.3972   39.9750   22.5822   \n",
       "\n",
       "   gy_z_120  gy_z_121  gy_z_122  gy_z_123  gy_z_124  gy_z_125  gy_z_126  \\\n",
       "0    1.5793    1.4896    1.5751    1.5498    1.6500    1.6334    1.5977   \n",
       "1   -7.9842   -9.0787   -9.7908  -10.6618  -11.4378  -11.6956  -14.3258   \n",
       "2    0.7939    0.7900    0.8192    0.9652    1.1535    1.1624    1.0180   \n",
       "3   -0.4923   -0.5672   -0.5409   -0.5150   -0.4900   -0.4411   -0.3901   \n",
       "4    1.5852    1.4074    1.6814    1.6661    2.1715    2.3800    3.0027   \n",
       "5    1.4435    1.4652    1.5582    1.3755    1.4600    1.4600    1.4600   \n",
       "6   -0.4300   -0.4944   -0.4884   -0.6221   -0.6134   -0.4578   -0.4411   \n",
       "7    5.8921   -3.8207  -13.0885  -14.9318  -15.0545  -11.7565   -8.7202   \n",
       "8   -0.4300   -0.4900   -0.4900   -0.4900   -0.4106   -0.3759   -0.3412   \n",
       "9   -8.7464  -20.9134  -20.3160  -15.8034  -12.6418  -12.3159   -7.4897   \n",
       "\n",
       "   gy_z_127  gy_z_128  gy_z_129  gy_z_130  gy_z_131  gy_z_132  gy_z_133  \\\n",
       "0    1.4328    1.4000    1.5793    1.5688    1.4693    1.5128    1.4285   \n",
       "1  -15.2373  -15.5200  -15.9440  -16.2196  -14.3212  -12.5001  -10.3252   \n",
       "2    1.2180    1.4025    1.4402    1.3449    1.2419    1.3704    1.5519   \n",
       "3   -0.3846   -0.4624   -0.4182   -0.3700   -0.3700   -0.4307   -0.4300   \n",
       "4    3.6089    3.4393    3.5590    3.8304    3.6960    3.7302    3.9760   \n",
       "5    1.5301    1.5756    1.4889    1.5220    1.5300    1.4091    1.4600   \n",
       "6   -0.4658   -0.4300   -0.4300   -0.4581   -0.4805   -0.4041   -0.4300   \n",
       "7   10.6074   12.2756   13.9439   12.6635   11.1377    5.9313   -2.2686   \n",
       "8   -0.3064   -0.2717   -0.2424   -0.2695   -0.2967   -0.3238   -0.3510   \n",
       "9   -3.7732    0.3998    4.3665   10.2211   15.6917   14.4347   10.7502   \n",
       "\n",
       "   gy_z_134  gy_z_135  gy_z_136  gy_z_137  gy_z_138  gy_z_139  gy_z_140  \\\n",
       "0    1.3390    1.4624    1.4600    1.4777    1.5238    1.5890    1.5081   \n",
       "1  -10.1110   -5.7232   -2.7128   -3.1844    2.0826    3.7782    5.6479   \n",
       "2    1.6500    1.7052    1.9233    1.8321    1.9443    1.9754    2.0487   \n",
       "3   -0.3341   -0.3700   -0.3700   -0.4300   -0.4300   -0.4270   -0.4900   \n",
       "4    5.1283    4.6889    4.4421    4.8146    5.1755    5.8124    5.6593   \n",
       "5    1.4360    1.5040    1.4819    1.5130    1.4987    1.5300    1.5604   \n",
       "6   -0.4598   -0.4390   -0.4763   -0.4359   -0.6695   -0.5946   -0.4900   \n",
       "7   -6.6902   -9.4600   -9.1480   -7.5787   -4.4119   -1.2361    1.3659   \n",
       "8   -0.3686   -0.3639   -0.3592   -0.3545   -0.3498   -0.3451   -0.3404   \n",
       "9    5.6659   -1.8523   -7.9920   -9.9530   -8.8905   -6.6126   -2.2098   \n",
       "\n",
       "   gy_z_141  gy_z_142  gy_z_143  gy_z_144  gy_z_145  gy_z_146  gy_z_147  \\\n",
       "0    1.4499    1.5031    1.4600    1.3649    1.4774    1.4600    1.4951   \n",
       "1    4.6813    3.7147    2.2387   -1.2212   -3.1409   -5.2567   -5.4418   \n",
       "2    2.1355    2.0540    2.0296    1.8457    1.8145    1.7982    1.7819   \n",
       "3   -0.4900   -0.3587   -0.3173   -0.3700   -0.4084   -0.3100   -0.3100   \n",
       "4    5.7408    5.9904    6.5709    7.0393    7.0628    6.5418    4.2421   \n",
       "5    1.5027    1.6283    1.5207    1.4000    1.5066    1.4970    1.5793   \n",
       "6   -0.4900   -0.4935   -0.5456   -0.5208   -0.4960   -0.5180   -0.5654   \n",
       "7    3.4195    3.8727    3.5135    1.5702   -0.6977   -2.8655   -3.9532   \n",
       "8   -0.3356   -0.3309   -0.3262   -0.3215   -0.3168   -0.3121   -0.3100   \n",
       "9    0.9647    3.2045    5.4460    6.9972    6.8441    5.1904    3.5163   \n",
       "\n",
       "   gy_z_148  gy_z_149  gy_z_150  gy_z_151  gy_z_152  gy_z_153  gy_z_154  \\\n",
       "0    1.4600    1.4600    1.4600    1.5301    1.5691    1.5593    1.5423   \n",
       "1   -4.8560   -2.5743   -1.7403   -4.5809   -6.1370   -5.7625   -2.4008   \n",
       "2    1.5667    1.3500    1.4000    1.3035    1.2200    1.1604    1.2152   \n",
       "3   -0.3662   -0.4083   -0.3990   -0.4566   -0.4595   -0.4517   -0.3200   \n",
       "4    2.3539    2.2893    1.2885    1.2177    1.3184    1.1846    0.4448   \n",
       "5    1.4600    1.5900    1.5900    1.4279    1.5162    1.5163    1.5031   \n",
       "6   -0.6007   -0.5751   -0.5324   -0.5618   -0.4158   -0.4900   -0.4690   \n",
       "7   -4.0117   -3.2634   -2.0691   -0.1649    2.3681    4.0300    3.3011   \n",
       "8   -0.3100   -0.3100   -0.3100   -0.3100   -0.3100   -0.3979   -0.1929   \n",
       "9    2.1237   -2.9511   -5.2330   -5.7790   -4.3519   -2.7741   -0.5727   \n",
       "\n",
       "   gy_z_155  gy_z_156  gy_z_157  gy_z_158  gy_z_159  \n",
       "0    1.4626    1.4666    1.5141    1.5300    1.5607  \n",
       "1   -1.4210   -3.8011   -6.7729   -7.5824   -8.7199  \n",
       "2    1.1975    1.1799    1.1623    1.4000    1.4000  \n",
       "3   -0.3453   -0.3700   -0.3700   -0.2857   -0.3498  \n",
       "4    4.8701    1.2830    0.5287    0.8010    0.8872  \n",
       "5    1.5241    1.4581    1.4570    1.5149    1.4600  \n",
       "6   -0.4960   -0.5338   -0.5090   -0.5802   -0.4900  \n",
       "7    2.0893    0.8828   -0.7951   -1.4848   -1.1262  \n",
       "8   -0.0978   -0.1736   -0.1862   -0.2706   -0.3639  \n",
       "9    1.6749    3.0715    2.4038    1.1223   -0.4463  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "d33c2945",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dataset Info Before Cleaning:\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 496 entries, 0 to 495\n",
      "Columns: 961 entries, label to gy_z_159\n",
      "dtypes: float64(960), object(1)\n",
      "memory usage: 3.6+ MB\n",
      "None\n",
      "\n",
      "Dataset Info After Cleaning:\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 493 entries, 0 to 494\n",
      "Columns: 961 entries, label to gy_z_159\n",
      "dtypes: float64(960), object(1)\n",
      "memory usage: 3.6+ MB\n",
      "None\n",
      "\n",
      "Dataset Info After Handling Outliers:\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 352 entries, 0 to 492\n",
      "Columns: 961 entries, label to gy_z_159\n",
      "dtypes: float64(960), object(1)\n",
      "memory usage: 2.6+ MB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from sklearn.impute import SimpleImputer\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "# Display basic information about the dataset\n",
    "print(\"Dataset Info Before Cleaning:\")\n",
    "print(df2.info())\n",
    "\n",
    "# Identify numeric and non-numeric columns\n",
    "numeric_columns = df2.select_dtypes(include=['number']).columns\n",
    "non_numeric_columns = df2.select_dtypes(exclude=['number']).columns\n",
    "\n",
    "# Handling missing values for numeric columns\n",
    "numeric_imputer = SimpleImputer(strategy='mean')\n",
    "df2[numeric_columns] = numeric_imputer.fit_transform(df2[numeric_columns])\n",
    "\n",
    "# Handling missing values for non-numeric columns\n",
    "non_numeric_imputer = SimpleImputer(strategy='most_frequent')\n",
    "df2[non_numeric_columns] = non_numeric_imputer.fit_transform(df2[non_numeric_columns])\n",
    "\n",
    "# Handling duplicates\n",
    "df2_no_duplicates = df2.drop_duplicates()\n",
    "\n",
    "# Display information after handling missing values and duplicates\n",
    "print(\"\\nDataset Info After Cleaning:\")\n",
    "print(df2_no_duplicates.info())\n",
    "\n",
    "# Handling outliers (optional)\n",
    "# You can use various techniques to detect and handle outliers based on your dataset\n",
    "# Here, we use Z-score to identify and remove outliers from numeric columns\n",
    "z_scores = (df2_no_duplicates[numeric_columns] - df2_no_duplicates[numeric_columns].mean()) / df2_no_duplicates[numeric_columns].std()\n",
    "df2_no_outliers = df2_no_duplicates[(z_scores.abs() < 3).all(axis=1)]\n",
    "\n",
    "# Display information after handling outliers\n",
    "print(\"\\nDataset Info After Handling Outliers:\")\n",
    "print(df2_no_outliers.info())\n",
    "\n",
    "# Scale numerical features using StandardScaler\n",
    "scaler = StandardScaler()\n",
    "df2_scaled = pd.DataFrame(scaler.fit_transform(df2_no_outliers[numeric_columns]), columns=numeric_columns)\n",
    "\n",
    "# Now df1_scaled is the cleaned and scaled DataFrame that you can use for further analysis or modeling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "9e286f91",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "label       0\n",
       "acc_x_0     0\n",
       "acc_x_1     0\n",
       "acc_x_2     0\n",
       "acc_x_3     0\n",
       "           ..\n",
       "gy_z_155    0\n",
       "gy_z_156    0\n",
       "gy_z_157    0\n",
       "gy_z_158    0\n",
       "gy_z_159    0\n",
       "Length: 961, dtype: int64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "e52daee1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Separate into independent and dependent variables (target).\n",
    "X = df2.drop(\"label\", axis = 1)\n",
    "y = df2[\"label\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "fe33eeef",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X train: (396, 960)\n",
      "X test: (100, 960)\n"
     ]
    }
   ],
   "source": [
    "## We divide into training and test set.\n",
    "\n",
    "# We define the random seed for reproducibility.\n",
    "SEED = 123\n",
    "X_train,X_test,y_train,y_test = tts(X,y, \n",
    "                                    test_size = 0.2, \n",
    "                                    shuffle = True, \n",
    "                                    random_state = SEED, \n",
    "                                    stratify = y)\n",
    "print(f\"X train: {X_train.shape}\")\n",
    "print(f\"X test: {X_test.shape}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "c0716ec6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "* Extra Trees => Total training time = 22.640021562576294 seconds\n"
     ]
    }
   ],
   "source": [
    "from sklearn.ensemble import ExtraTreesClassifier\n",
    "from sklearn.metrics import accuracy_score, confusion_matrix, classification_report\n",
    "from sklearn.utils import shuffle\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "import time\n",
    "import numpy as np\n",
    "\n",
    "\n",
    "\n",
    "SEED = 42  # Set a seed for reproducibility\n",
    "\n",
    "# Create Extra Trees model\n",
    "et = ExtraTreesClassifier(bootstrap=True, random_state=SEED)\n",
    "\n",
    "# Shuffle the training data\n",
    "X_train, y_train = shuffle(X_train, y_train, random_state=SEED)\n",
    "\n",
    "start = time.time()\n",
    "\n",
    "# Use cross-validation to tune hyperparameters\n",
    "param_grid = {}  # Add hyperparameter grid for Extra Trees if needed\n",
    "grid_search = GridSearchCV(et, param_grid, cv=5, scoring='accuracy', n_jobs=-1)\n",
    "grid_search.fit(X_train, y_train)\n",
    "et_best = grid_search.best_estimator_\n",
    "\n",
    "# Fit Extra Trees model\n",
    "et_best.fit(X_train, y_train)\n",
    "end = time.time()\n",
    "print(f\"* Extra Trees => Total training time = {end - start} seconds\")\n",
    "\n",
    "# Make predictions on training and test sets\n",
    "y_pred_train_et = et_best.predict(X_train)\n",
    "y_pred_test_et = et_best.predict(X_test)\n",
    "\n",
    "# Calculate metrics\n",
    "accuracy_train_et = accuracy_score(np.array(y_train), y_pred_train_et)\n",
    "accuracy_test_et = accuracy_score(np.array(y_test), y_pred_test_et)\n",
    "\n",
    "cf_matrix_train_et = confusion_matrix(np.array(y_train), y_pred_train_et)\n",
    "cf_matrix_test_et = confusion_matrix(np.array(y_test), y_pred_test_et)\n",
    "\n",
    "clf_report_train_et = classification_report(np.array(y_train), y_pred_train_et)\n",
    "clf_report_test_et = classification_report(np.array(y_test), y_pred_test_et)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "8d8a833a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "* Random Forest => Total training time = 6.27167010307312 seconds\n"
     ]
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.metrics import accuracy_score, confusion_matrix, classification_report\n",
    "from sklearn.utils import shuffle\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "import time\n",
    "import numpy as np\n",
    "\n",
    "\n",
    "\n",
    "SEED = 42  # Set a seed for reproducibility\n",
    "\n",
    "# Create Random Forest model\n",
    "rf = RandomForestClassifier(random_state=SEED)\n",
    "\n",
    "# Shuffle the training data\n",
    "X_train, y_train = shuffle(X_train, y_train, random_state=SEED)\n",
    "\n",
    "start = time.time()\n",
    "\n",
    "# Use cross-validation to tune hyperparameters\n",
    "param_grid = {}  # Add hyperparameter grid for Random Forest if needed\n",
    "grid_search = GridSearchCV(rf, param_grid, cv=5, scoring='accuracy', n_jobs=-1)\n",
    "grid_search.fit(X_train, y_train)\n",
    "rf_best = grid_search.best_estimator_\n",
    "\n",
    "# Fit Random Forest model\n",
    "rf_best.fit(X_train, y_train)\n",
    "end = time.time()\n",
    "print(f\"* Random Forest => Total training time = {end - start} seconds\")\n",
    "\n",
    "# Make predictions on training and test sets\n",
    "y_pred_train_rf = rf_best.predict(X_train)\n",
    "y_pred_test_rf = rf_best.predict(X_test)\n",
    "\n",
    "# Calculate metrics\n",
    "accuracy_train_rf = accuracy_score(np.array(y_train), y_pred_train_rf)\n",
    "accuracy_test_rf = accuracy_score(np.array(y_test), y_pred_test_rf)\n",
    "\n",
    "cf_matrix_train_rf = confusion_matrix(np.array(y_train), y_pred_train_rf)\n",
    "cf_matrix_test_rf = confusion_matrix(np.array(y_test), y_pred_test_rf)\n",
    "\n",
    "clf_report_train_rf = classification_report(np.array(y_train), y_pred_train_rf)\n",
    "clf_report_test_rf = classification_report(np.array(y_test), y_pred_test_rf)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "5c26bfe5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "* SVM => Total training time = 2.9829330444335938 seconds\n"
     ]
    }
   ],
   "source": [
    "from sklearn.svm import SVC\n",
    "from sklearn.metrics import accuracy_score, confusion_matrix, classification_report\n",
    "from sklearn.utils import shuffle\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "import time\n",
    "import numpy as np\n",
    "\n",
    "\n",
    "\n",
    "SEED = 42  # Set a seed for reproducibility\n",
    "\n",
    "# Create SVM model\n",
    "svm = SVC(random_state=SEED)\n",
    "\n",
    "# Shuffle the training data\n",
    "X_train, y_train = shuffle(X_train, y_train, random_state=SEED)\n",
    "\n",
    "start = time.time()\n",
    "\n",
    "# Use cross-validation to tune hyperparameters\n",
    "param_grid = {}  # Add hyperparameter grid for SVM if needed\n",
    "grid_search = GridSearchCV(svm, param_grid, cv=5, scoring='accuracy', n_jobs=-1)\n",
    "grid_search.fit(X_train, y_train)\n",
    "svm_best = grid_search.best_estimator_\n",
    "\n",
    "# Fit SVM model\n",
    "svm_best.fit(X_train, y_train)\n",
    "end = time.time()\n",
    "print(f\"* SVM => Total training time = {end - start} seconds\")\n",
    "\n",
    "# Make predictions on training and test sets\n",
    "y_pred_train_svm = svm_best.predict(X_train)\n",
    "y_pred_test_svm = svm_best.predict(X_test)\n",
    "\n",
    "# Calculate metrics\n",
    "accuracy_train_svm = accuracy_score(np.array(y_train), y_pred_train_svm)\n",
    "accuracy_test_svm = accuracy_score(np.array(y_test), y_pred_test_svm)\n",
    "\n",
    "cf_matrix_train_svm = confusion_matrix(np.array(y_train), y_pred_train_svm)\n",
    "cf_matrix_test_svm = confusion_matrix(np.array(y_test), y_pred_test_svm)\n",
    "\n",
    "clf_report_train_svm = classification_report(np.array(y_train), y_pred_train_svm)\n",
    "clf_report_test_svm = classification_report(np.array(y_test), y_pred_test_svm)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "0632f05b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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H4K5nn6VW165Y0tM5tHAh97z22g3VVeOpp6jzwgs4ODtzNDKSRm+/nW2+ycGBx+fPp0H//jg4O7Pnu+9I2rfPurcCl/e8ndzdgcsnVzldZ+/O/667eOavv7j7yrXHe3/4gdjVqwlu3pxSdeticnCg/YIF3P3886TGx3Pwl18IaNCADgsWUO6BB25om66n6fDh/B0RgZObGyGDBlH/lVcAaD15Mn41a5K4Zw+Xzp+nXu/et9R/YMOGmJyciJ4/n93ffUfJwEBajBtHqbp18QgK4qkVK6jYqhWxUVGc3LyZyo8+SucVKyjh53fb23aVLd7Dq8fEr/67+vO85IUXuJCYyP3vvUeZ++6jzdSpYDKxpGdPLp4+TfCDD1Kra1ccHB3Z/vXXRP/66zXXEXT//TR+553LJ0suXUrNLl3wKFv2luq9ngc++IAHP/oINz8/9s6cyT/Ll+NXowY1OncGoN7LL9N68mTr79mRRYtw9/enbq9eAJRt0oRLycnsmzWL/bNn41ejBo9+/z1uvr75XqvkL5NxO2M6IsXY3Icf5u/Fi3lq2bLbulbZFs7+/TffXDks8IZ+hUXuWBpOF/mX4+vXc2TxYo6tWIFfzZoEZzlUICJSlGg4XeRfjixezLoRI/CuVIlHZs68pROxREQKgobTRURE7JT2xEVEROyUQlwKVWxsLHXq1MFkMvHcc8/lmH/+/Hnat2+Pt7c3HTp0IDmfL88REbFndnli2/Hjxwu7BMkniYmJdO7cmTNnzpCamprjsx09ejRbtmxhzpw5PP/88wwfPpzXbvBSM5E7gb+/PwkJCYVdhthYUFBQrq9rT1wKlb+/Pz179qTklTtO/duaNWto1KgRd999N40bN+bPP/8s4ApFRIouhbgUaUlJSbhfuelKyZIlSUxMLOSKRESKDoW4FGl+fn6kXHnoR0pKCmazuZArEhEpOuzymLgUH+np6Rw9epRLly5x/vx5oqOjCQwMJCUlhdKlS9O0aVPmzZvHrl27WLduHV26dCnskkWkgBmGwcWLF7FYLMX6vg2GYeDg4ICbm9sNb6ddXieuE9uKj2PHjtE4y2NIAV5//XUmTJjAwYMHOXfuHAMGDGDdunU0adKEL774Ag89lEHE6k44se3ChQs4Ozvj5FT89zszMjJIT0+nRIkS2V6/1oltCnERETt2J4R4SkrKNU9+LY5y294CPzv9q6++olevXgwaNCjX+YZhMHXqVPr3788bb7zB4cOHbVWKiIhd+vDDD6lduzatW7cmOjo627zY2Fjat29PQEAAr7/+Ounp6cDlk0F79OhBtWrVaNy4MUlJSYVRer4qzkPoubmZ7bVZiDdv3pzBgwdfc/7WrVs5ceIE48aN46WXXmLy5Mm2KkVExO6sWbOGL7/8kgkTJhAUFMTb/3qk7qhRo7hw4QK//PILc+fOZe7cuQAMHjyYffv2MWfOHP773/8WRulSgGx2gOGuu+4iPj7+mvM3b97Mgw8+iMlkonr16qSkpHD69Gl89fxaERHWrFlDUFAQzZo1IyYmhjfffJNLly7h4uICwM6dO2nUqBFNmzalVKlSrFmzhqeeeorFixfz2muvUb9+ferXr1+4G2EjmS+2y9f+HL9ZcN35SUlJdL7ybPZTp07h6OiIn58fAL///rv1M8nN9u3bmTt3Lu+//37+FZxFoZ0lkJSUhL+/v3XabDaTlJSUa4hHRkYSGRkJXP72mXW523WyQ5N860ukOAv8ZW1hl3BHSU1NxdPTE39/f0qXLo1hGJhMJuvfv6CgIGJiYjh9+jRJSUmkpqZiGAbp6eksWrSIb7/9lsaNGzN9+nTrvRbs1cmTJ7Od1JaZz/3ndcJcQEAAK1asAC7fRbJkyZL07dvXOj8jI+Oafdxzzz3cc889N1WPq6vrDedcoYV4bufTXes4QHh4OOHh4dbp4n4Sh0hRpN+7guXu7s65c+dISEggLi4Ok8mEYRjWz+GVV17hueeeIzg4GBcXF8xmM5mZl+PNbDbzn//8h+7du/P111/To0ePwtyU25aWloajo6PN+s/IyLjhthaLBYvFQr9+/fDx8WHXrl3UqVOHdu3aMXToUC5evIibmxufffYZVatWZe3atUyYMIHvvvuOTz/9lNjYWP755x9iY2Pp1asXL7zwQo51pKWl5fh9u9aJbYUW4mazOVuRiYmJGkoXEbmiadOmjB8/nlWrVhEREUHjxo1JS0sjKSmJ0qVLU65cOX799VdOnTpF7969adu2La6uroSEhODk5ISrqysmkwlXV9fC3pRi6/Dhw8yaNQtHR0fOnz/Pzz//jJOTE6tWreKjjz7im2++ybFMdHQ0c+bMISUlhWbNmtG9e3ecnZ1vuYZCC/GQkBAWL15M06ZNOXjwIO7u7gpxEZErmjVrRp8+fejTpw9ly5blyy+/ZNKkSdZ7KKxdu5ahQ4fi5eVFv379CA0NBS4fcuzfvz89e/akbdu2dOjQoZC3pPh67LHHrCME586d49VXX+XIkSOYTCbr1QL/1rJlS1xdXa1D5qdOnbrmXvaNsFmIjx07lj179nD+/HlefvllnnrqKeuQRatWrWjQoAFbtmxhwIABuLi4ZDu+ICIi8M477/DOO+9YpwcNGmS9bLdLly506dIlx3XitWrVsp5DJLaV9VyD0aNH06RJE6ZMmcKxY8fo1KlTrstkHRlxdHS0HgK5VTYL8VdfffW6800mE7169bLV6kVERArM+fPnKV26NACzZ88usPUW/3vYiYhIsZLXJWGFoU+fPrz66qtMmjSJpk2bFth67/jbrub39YYixVVR/MMpd8ZtV1NTU+3+Mrmbkdv2Frmz00XEvjz+/b7CLkHuUC/V86ZGGfu59WpVc4m8G+UTPU9cRETETinERURE7JRCXERExE4pxEVEROyUQlxERMRO6ex0ERGxK4MWH83X/j5tU+G688+eOc3rL3YHICnhFA6Ojvj4Xn4U6YQf5uHsfO1HkQKsXbsWZ2dn7r333vwpOAuFuIiIyHV4+/gyZc5vAEz76nNKuJfk6edu/I6j69ato2TJkgpxERGRomD/nl18OXokF1JT8fb15e33P8ZcKoC533/L4p9/wsnJiWrVqjF48GBmzJiBo6Mj8+bN44MPPqBRo0b5VodCXERE5CYYhsHnHw7nf59PwMfPzPLFv/PNF5/x1ohR/DB1Ips2rMfV1ZWzZ8/i7e3Ns88+S8mSJXn55ZfzvRaFuIiIyE1IT7/EkegDDOr9HACZmZmYS5UCoEq1GvTr1482bdrQpk0bm9eiEBcREbkJhmFQsUo1vp45N8e8UV9OJuHgdiIiIhg7diwrVqywaS26xExEROQmODu7cPZ0Eru2bwEgIz2dI9EHsFgsxJ+Io2nTprz77rucO3eOlJQUSpYsSXJysk1q0Z64iIjYlbwuCbM1BwcHhn86nnGj3icl+TyZmRl06vYcwRUqMXLwINIvpGAYBi+++CLe3t489NBD9O7dmyVLluT7iW16FKkeRSpyQzo2/7iwS5A71OWnmPkUdhk37HafYnYzjyLVcLqIiIidUoiLiIjYKYW4iIgUafZ30Pf23MxRboW4iIgUabHnL2HJzCjsMgpERkYGDg43Hs06O11ERIq0P45cAJIo6+mCyVTY1eQtqMStDR0YhoGDgwNubm43vIxCXEREijQDWHTkAnChsEu5IY/eXabA1qXhdBERETulEBcREbFTCnERERE7pRAXERGxUwpxERERO6UQFxERsVMKcRERETulEBcREbFTCnERERE7ZdM7tm3bto1p06ZhsVho2bIl7du3zzY/NTWVcePGkZiYSGZmJm3btiUsLMyWJYmIiBQbNgtxi8XClClTePfddzGbzbz99tuEhIRQrlw5a5vFixdTrlw53nrrLc6dO8fAgQNp1qwZTk66G6yIiEhebDacHh0dTenSpQkMDMTJyYkmTZqwadOmbG1MJhMXL17EMAwuXryIh4fHTT29RURE5E5ms13epKQkzGazddpsNnPw4MFsbdq0acPHH39M7969uXDhAq+99lquIR4ZGUlkZCQAo0aNwt/fP9/qPJlvPYmIiJCvGZUXm4V4bg81N/3rGXLbt2+nQoUKvPfee5w8eZL333+fmjVr4u7unq1deHg44eHh1umEhATbFC0iInKbbJFRQUFBub5us7Frs9lMYmKidToxMRFfX99sbVasWEGjRo0wmUyULl2agIAAjh8/bquSREREihWbhXiVKlWIi4sjPj6ejIwM1q5dS0hISLY2/v7+7Ny5E4AzZ85w/PhxAgICbFWSiIhIsWKz4XRHR0d69uzJyJEjsVgshIWFERwcTEREBACtWrXiiSee4KuvvmLQoEEAdOvWDS8vL1uVJCIiUqyYjNwOXhdx+Tnknvliu3zrS6Q469j848IuQcQu/NqtZr73WeDHxEVERMS2FOIiIiJ2SiEuIiJipxTiIiIidkohLiIiYqcU4iIiInZKIS4iImKnFOIiIiJ2SiEuIiJipxTiIiIidkohLiIiYqcU4iIiInZKIS4iImKnFOIiIiJ2SiEuIiJipxTiIiIidkohLiIiYqcU4iIiInZKIS4iImKnFOIiIiJ2SiEuIiJipxTiIiIidkohLiIiYqcU4iIiInZKIS4iImKnFOIiIiJ2SiEuIiJipxTiIiIidirPEJ80aTtnz6YVRC0iIiJyE/IM8ZdfXkqZMl/TufNv/P77ITIzLQVRl4iIiOQhzxCfO7cdHTtWIyLib9q1m0/ZshN4/fUV7N6dUBD1iYiIyDXkGeIdO1Zn5sxH2bnzOVq2LE98fCpjx/5F3brfMmxYVEHUKCIiIrlwyqvBggXRTJu2i0WLjpCensn99wfRp0991q6N5ZNPNjNsWNNrLrtt2zamTZuGxWKhZcuWtG/fPkeb3bt3M336dDIzM/H09GT48OG3tUEiIiJ3ijxDvH37+Xh4uPD883fTt2996tYtBUC9eqXYuzfpmstZLBamTJnCu+++i9ls5u233yYkJIRy5cpZ26SkpDB58mTeeecd/P39OXv2bD5skoiIyJ0hzxD/4ouWdO9eG09Pl2yv16lTihUrOl9zuejoaEqXLk1gYCAATZo0YdOmTdlCfM2aNTRq1Ah/f38AvL29b2kjRERE7kR5hrjJBHPn7uf55+sAMHXqTi5cyOCVVxpcd7mkpCTMZrN12mw2c/DgwWxt4uLiyMjIYNiwYVy4cIFHHnmE0NDQHH1FRkYSGRkJwKhRo6yhnx9O5ltPIiIi5GtG5SXPEB8yJIqRIx+wTl+6lMl770XlGeKGYeR4zWQyZZvOzMzkyJEjDBkyhEuXLvHuu+9SrVo1goKCsrULDw8nPDzcOp2QoDPjRUSkaLJFRv07F6/KM8QtFoP4+FTr9MmTqeSSzzmYzWYSExOt04mJifj6+uZo4+npiZubG25ubtSqVYujR49es1gRERH5f3leYnb//UGMHLmBp5/+jc6df+N//9vA/feXybPjKlWqEBcXR3x8PBkZGaxdu5aQkJBsbUJCQti3bx+ZmZmkpaURHR1N2bJlb31rRERE7iB57ol//nkLHnvsZ2bP3g9A9ep+jB3bIs+OHR0d6dmzJyNHjsRisRAWFkZwcDAREREAtGrVinLlylG/fn3eeOMNHBwcaNGiBeXLl7/NTRIREbkzmIzcDl7/S2amhf37L19OVqOGH46OhfvclOPHj+dbX5kvtsu3vkSKs47NPy7sEkTswq/dauZ7n7d8TNwwDGbP3s/OnQlcvJgBXD5j/dNPw/K3QhEREbkpeYb4K69EMmHCdkwmk/WMc5PJpBAXEREpZHmOi//ySzRdu9YCLh8fDwsrz5AhjW1emIiIiFxfniF++vRFmjUrh2EY+Pm50alTdWbM2FMQtYmIiMh15DmcXrp0STIyLJQp48Erryzj0qVMvLxc8lpMREREbCzPPfEPPniAqlV9+Oyz5ri5OeLt7XpDl5iJiIiIbV13Tzwz08LWrSd57LEqdO5ck86d8/+0eREREbk1190Td3R0YP78aA4dOlNA5YiIiMiNyvOYePPmwYwYsY60tEzKlClpfb1jx+o2LUxERESuL88QnzZtFwADBiwHLt/8xWQykZk5yLaViYiIyHXlGeLvvXd/jkeIioiISOHLM8SHDWtaEHWIiIjITcozxFu0mJXjNZPJxLJlT9mkIBEREbkxeYb4ypXHcrym4XUREZHCl2eInzr1ivX/p09fZNiwtdnOUhcREZHCkecd20ym///n5eVCjRp+fPvt7oKoTURERK4jzz1xf/8vcwyf16jha7OCRERE5MbkGeIPPljOGuKOjiYqVvTmjTdCbF6YiIiIXN8NnNj2dEHUISIiIjcpz2Pi3bsvYtiwKOv00KFRdO++yKZFiYiISN7yDPF58w5QoYKXdbpCBS9+/vmgTYsSERGRvOUZ4j4+bvz5Z4x1euXKY3h7u9q0KBEREclbnsfE27atwqRJ21my5G8A4uNTeemlurauS0RERPKQZ4iPHh3KpUuZLFx4CIDnnqvNxx+H2rwwERERub48Q9zT04WpU9sURC0iIiJyE/I8Jt68+U+8/voK6/Rrr60gLCznQ1FERESkYOUZ4hs3nqBOHX/rdN26/mzYEGfTokRERCRveYZ4QIA7P/98kNTUdFJSLjF37gECAtwLojYRERG5jjyPiXfpUpOPPtqIl9c4TCYTmZkW3n67UUHUJiIiIteRZ4iPGNGUEiWcWLjwMHD5krO0tEybFyYiIiLXl+dwurOzI089VYNHH61McvIlhg1by4cfbiiI2kREROQ6rrknfvDgaWbP3s/s2fvZtSsBwzAwmUw8+mhlnn32roKsUURERHJxzRCvUWMKJpOJMmVK8sor9bnvvjJ0776IXr3q0K5d1YKsUURERHJx3eF0BwcToaHBtGhRnnvuCbzpzrdt28bAgQPp378/8+fPv2a76OhoOnfuzPr16296HSIiIneqa4b4uHEtaNIkiFmz9vHEEwto2HAGJpOJTZtOkJh4Ic+OLRYLU6ZMYfDgwYwZM4aoqChiYmJybff9999Tv37929oQERGRO801Q7xfv4b8+efTHDvWm88+a06DBgEAjBy5ntKlv86z4+joaEqXLk1gYCBOTk40adKETZs25Wj3xx9/0KhRI7y8vHLpRURERK4lz0vMypTxYODAexg48B5iYs4za9Y+5sw5kGfHSUlJmM1m67TZbObgwYM52mzcuJGhQ4fy9dfX/mIQGRlJZGQkAKNGjcLf3/+abW/WyXzrSUREhHzNqLzkGeJZlSvnyaBB9zJo0L15tjUMI8drJpMp2/T06dPp1q0bDg7Xv9ItPDyc8PBw63RCQsINViwiIlKwbJFRQUFBub5+UyF+M8xmM4mJidbpxMREfH19s7U5dOgQn3/+OQDnzp1j69atODg4cN9999mqLBERkWLDZiFepUoV4uLiiI+Px8/Pj7Vr1zJgwIBsbb788sts/7/nnnsU4CIiIjfIZiHu6OhIz549GTlyJBaLhbCwMIKDg4mIiACgVatWtlq1iIjIHcFk5Hbwuog7fvx4vvWV+WK7fOtLpDjr2Pzjwi5BxC782q1mvvd5rWPied47XURERIomhbiIiIidUoiLiIjYKYW4iIiInVKIi4iI2CmFuIiIiJ1SiIuIiNgphbiIiIidUoiLiIjYKYW4iIiInVKIi4iI2CmFuIiIiJ1SiIuIiNgphbiIiIidUoiLiIjYKYW4iIiInVKIi4iI2CmFuIiIiJ1SiIuIiNgphbiIiIidUoiLiIjYKYW4iIiInVKIi4iI2CmFuIiIiJ1SiIuIiNgphbiIiIidUoiLiIjYKYW4iIiInVKIi4iI2CmFuIiIiJ1SiIuIiNgphbiIiIidcrJl59u2bWPatGlYLBZatmxJ+/bts81fvXo1v/76KwBubm706tWLihUr2rIkERGRYsNme+IWi4UpU6YwePBgxowZQ1RUFDExMdnaBAQEMGzYMD755BOeeOIJJk2aZKtyREREih2bhXh0dDSlS5cmMDAQJycnmjRpwqZNm7K1qVGjBh4eHgBUq1aNxMREW5UjIiJS7NhsOD0pKQmz2WydNpvNHDx48Jrtly9fToMGDXKdFxkZSWRkJACjRo3C398/3+o8mW89iYiIkK8ZlRebhbhhGDleM5lMubbdtWsXK1asYMSIEbnODw8PJzw83DqdkJCQP0WKiIjkM1tkVFBQUK6v22w43Ww2ZxseT0xMxNfXN0e7o0ePMnHiRN588008PT1tVY6IiEixY7MQr1KlCnFxccTHx5ORkcHatWsJCQnJ1iYhIYFPPvmEfv36XfNbhoiIiOTOZsPpjo6O9OzZk5EjR2KxWAgLCyM4OJiIiAgAWrVqxdy5c0lOTmby5MnWZUaNGmWrkkRERIoVk5Hbwesi7vjx4/nWV+aL7fKtL5HirGPzjwu7BBG78Gu3mvneZ4EfExcRERHbUoiLiIjYKYW4iIiInVKIi4iI2CmFuIiIiJ1SiIuIiNgphbiIiIidUoiLiIjYKYW4iIiInVKIi4iI2CmFuIiIiJ1SiIuIiNgphbiIiIidUoiLiIjYKYW4iIiInVKIi4iI2CmFuIiIiJ1SiIuIiNgphbiIiIidUoiLiIjYKYW4iIiInVKIi4iI2CmFuIiIiJ1SiIuIiNgphbiIiIidUoiLiIjYKYW4iIiInVKIi4iI2CmFuIiIiJ1SiIuIiNgphbiIiIidUoiLiIjYKYW4iIiInXKyZefbtm1j2rRpWCwWWrZsSfv27bPNNwyDadOmsXXrVlxdXenbty+VK1e2ZUkiIiLFhs32xC0WC1OmTGHw4MGMGTOGqKgoYmJisrXZunUrJ06cYNy4cbz00ktMnjzZVuWIiIgUOzYL8ejoaEqXLk1gYCBOTk40adKETZs2ZWuzefNmHnzwQUwmE9WrVyclJYXTp0/bqiQREZFixWbD6UlJSZjNZuu02Wzm4MGDOdr4+/tna5OUlISvr2+2dpGRkURGRgIwatQogoKC8q/Q3zfnX18ixdimvJuISAGzWYgbhpHjNZPJdNNtAMLDwwkPD8+/4kREiom33nqLUaNGFXYZUkhsNpxuNptJTEy0TicmJubYwzabzSQkJFy3jYiIiOTOZiFepUoV4uLiiI+PJyMjg7Vr1xISEpKtTUhICKtWrcIwDA4cOIC7u7tCXERE5AbZbDjd0dGRnj17MnLkSCwWC2FhYQQHBxMREQFAq1ataNCgAVu2bGHAgAG4uLjQt29fW5UjIlIs6VDjnc1k5HZgWkRERIo83bFNRETETinERURE7JRCXESkCNKRTrkRCnERkSLGMAzrPTP++ecfkpOTC7kiKaoU4iIiRczVAP/tt9/4/vvvuXjxYiFXJEWVTZ9iJiIit2bt2rVs3LiRIUOG4OLiQlJSEhaLJdutqkUU4iIiRUDWIXS4/CTISpUqsXnzZmJiYti9ezcuLi50796d4ODgQqxUihINp4uIFLKsAZ6QkEBmZiZly5bFzc2NJUuWULlyZXr27EmFChXIzMws5GqlKNGeuIhIIbsa4AsXLmTv3r14eXlRrVo1OnbsiIuLCw4ODqxfv56tW7fSunXrQq5WihLtiYuIFAGbN2/mr7/+4s033yQmJoZDhw7h5uZGWloaf/31F3PmzGHgwIGUKlWqsEuVIkS3XRURKURXh9JXrlwJQHp6Ohs3buS///0vTk5OxMfHYxgGzs7O+Pn5FW6xUuRoOF1EpIBlPQZusVhwdHQkMDCQGTNm4OzszPDhw4HLl5jFx8fTo0cPnJz051py0k+FiEgByhrgK1euJCEhgYCAAIKDg6lYsSK+vr5s2LCBixcvsnr1avr166cAl2vSMXERkQJ0NcAjIyNZtmwZtWvXZtKkSZw8eZLWrVvj4+PDunXr2LNnD/369aN8+fKFXLEUZfp6JyJSwAzD4NChQwwYMIC9e/dSo0YN7r33XhwdHalQoQIPPfQQGRkZ2gOXPOnENhERG4uLi8Pd3R1vb28WLVpE1apVOXDgANu3bwdg8ODBmEwm5s+fT4UKFWjQoEEhVyz2QsPpIiI2tGXLFiZMmICzszPbtm1j165d+Pn54enpSWpqKk888QQmk4n169cTFRVFYGBgYZcsdkRjNSIiNrJt2zZmzJjBoEGDcHBwYNasWVSoUAF/f39CQ0OJjY1l2bJlzJs3j4sXL9K/f3+CgoIKu2yxIwpxEREb2LZtG5MmTSI9PR1nZ2fc3Nxo2bIlCxcuJCoqiqZNm9K1a1cSExNJT0/H3d0dLy+vwi5b7IxCXEQkn+3bt48ff/yRAQMGcPr0aUaPHk3v3r0JDw/Hzc2NVatW4eDgwP3334/ZbC7scsWOKcRFRPJZeno6vXv3pnLlygAkJyczadIkevfuzQMPPIDJZGLRokU4OzsTEhJSyNWKPdPZ6SIiNpL1xi5Lly4lIiKCPn36ULlyZdavX0/VqlX1fHC5LQpxEZECsmzZMubOnct//vMfKlWqVNjlSDGg4XQRkduUdY87t+mrWrZsiaOjI+7u7gVZnhRj2hMXEbkNWQM7ISEBHx8f3WlNCox+0kREbsPVAP/tt9/YvXs3rq6uNGvWjJo1a+Lh4VHI1Ulxpzu2iYjcppUrV7Jlyxbeeustzp49y4IFC9i4cSMpKSmFXZoUc9oTFxG5SVmH0FNTU8nMzOSVV15h4cKFuLq60rhxYxYtWkRaWhpNmzbVTVzEZhTiIiI36WqAL1++nEOHDtGzZ09SUlLYu3cvb731FiaTiTVr1hAXF6fj42JT+ukSEblBWffAo6Ki2L9/P506dbKecZ6amsqPP/5IpUqVcHJyol27djoTXWxKx8RFRG7AxYsXrQF+7tw5Tp48yerVq8nIyADAycmJZ599lvj4eCIiIujWrZtu5CI2p0vMRETykJGRwYIFC6hUqRJpaWns3r2b7t27M23aNI4dO8abb76Z7bh3amqq9sClQCjERURuQGxsLK+//jpms5nx48fj4OBARkYGP/30E4cPH2bAgAH4+PgUdplyh9FwuojIDXB0dCQ0NJSUlBQ2btwIXB5C79q1K+XLl+err77CYrEUcpVyp9GeuIhIHnbs2MHRo0dp27YtR44cYfjw4XTv3p0WLVqwc+dOAgMDKVGiBJ6enoVdqtxhtCcuIpKHS5cusWXLFjIyMqhUqRJvvfUWU6dOZeLEiUyfPh2TyaQAl0KhPXERkSzi4+Px8fHBxcWFtWvX4uvry5kzZ9i9eze9evXCYrHg4OBATEwMO3bsoEGDBpQpU6awy5Y7lK4TFxG5YuvWrURERPDCCy/g7+/P3r17cXV1JSYmhq1bt5KWloazszNVq1alatWqPPLII4VdstzhtCcuIsLl494zZ87kmWeeoW7dulgsFkwmEyaTiXPnzjFmzBhq1qxJQEAAsbGxPPzww5jN5sIuW+5w2hMXkTverl27GD16NB999BFBQUGcPHmSX375hQ4dOhAQEICXlxeNGjXCxcWFsLAwMjIydDtVKRJ0YpuI3PE8PT25dOkSp06dwmKxMG7cOMqWLUtgYKD1Lm3p6els2bIFAAcH/emUokHD6SIiQHR0NCNHjsRkMtGrVy+aNGlinffPP//g7u6OyWTSELoUKfo6KSICVK1aleHDh2MYRrabtqxcuZKZM2fi7OysAJciRwd1RESuKF++PO+88w4jR47EwcEBLy8vlixZQt++ffH29i7s8kRy0HC6iMi/HDp0iMGDB+Pl5cXQoUMpV65cYZckkiuFuIhILmJiYnBwcCAoKKiwSxG5JoW4iIiIndKJbSIiInZKIS4iImKnFOIiIiJ2SiEuIiJipxTiIiIidkohLlKM/f33WUymTzCZPuGDD9ZZX+/Zc7H19Ztx993TbmiZYcOiMJk+Ye7c/Tdds4jcOIW4yB1i2rRdGIZBSsol5sxRuIoUBwpxkTtA5creHD58lpUrjzFr1n7S0y2ULesBgGEYjBy5ngoVJuLp+TlhYbPYvTsBgDNnLvLoo/Pw9f2C5577g/R0S7Z+P/xwA5UqTcLT83Nat57L4cNncqw7NTWdTp1+xdt7HCVLjqV+/W+t/YvI7VGIi9wBatUy06hRGaZO3cXUqbto374qPj6uwOU99HffXUPduqUYObIZmzad4PHH55Oensnw4etYtOgITz5Zg7JlPThw4LS1z2+/3cXgwatp1KgMb73ViB07TvHUU7/lWPeSJX8zb95BOneuyRdftKR58+AcXwZE5NboASgid4iePe9mwIDlpKVlsnjxEwwatBKARYsOA/DZZ2FUq+bLhg1x/PDDXg4cOM3KlcdwcDAxfnxLXFwc+e67PcTEnAdg4cLLy82atZ9Zsy4Pz584kUJS0oVs661c2RsHBxObNp3Aw8OZFi3KU69eqYLZaJFiTnviIneIp5+uiaOjiXLlPHnooYo55ptMuS+X9fWsd2m++v/vv3+UpUufZOnSJ1mypBPu7s7Zlq9XL4AdO3rQpUtN9u9P4vHH5zNlys7b3h4RUYiL3DG8vFyZOrUNEyc+hIPD/yfzo49WBuD111fyxRdbWLAgmipVfKhe3ZewsGAyMw369VvGO++sJjY22bpc27ZVAPj2290cO3aOP/88xvvvr8PNLfsA3+rVMUybtotSpUrQoEEgAMePJyMit0/D6SJ3kM6da+Z47bnn7iY2NplvvtnB8uX/cO+9pRk/viXOzo4MGXI/+/YlMWvWPjp0qEa1ar4cPHj5uHiPHndz4kQKEyfuoE+fSMqV86Rz5xo5+i9RwonIyKN8/fU2HBxMtG5dkZdfrmfzbRW5E+gpZiIiInZKw+kiIiJ2SiEuIiJipxTiIiIidkohLiIiYqcU4iIiInZKIS4iImKnFOIiIiJ26v8AqACcwa1FufUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "def plot_accuracy(accuracy_train: dict, accuracy_test: dict):\n",
    "    df_accuracy_train = pd.DataFrame.from_dict(accuracy_train, orient='index').rename(columns={0: 'Train'})\n",
    "    df_accuracy_test = pd.DataFrame.from_dict(accuracy_test, orient='index').rename(columns={0: 'Test'})\n",
    "    df_accuracy = pd.merge(df_accuracy_train, df_accuracy_test, left_index=True, right_index=True)\n",
    "    df_accuracy = df_accuracy.sort_values(['Train', 'Test'], ascending=False)\n",
    "\n",
    "    fig, ax = plt.subplots(figsize=(8, 4))\n",
    "    n = len(df_accuracy.index)\n",
    "    x = np.arange(n)\n",
    "    width = 0.3\n",
    "\n",
    "    rects1 = ax.bar(x=x - width, height=df_accuracy.iloc[:, 0], width=width)\n",
    "    rects2 = ax.bar(x=x, height=df_accuracy.iloc[:, 1], width=width)\n",
    "    ax.set_xticks(x)\n",
    "    ax.set_xticklabels(df_accuracy.index.to_list(), rotation=45, ha=\"right\")\n",
    "    ax.set_xlabel('Models', fontsize=10, fontweight='bold', color='darkblue')\n",
    "    ax.set_ylabel('Accuracy', fontsize=10, fontweight='bold', color='darkblue')\n",
    "    ax.set_title('Accuracy Comparison for Extra Trees', fontsize=12, fontweight='bold', color='darkred')\n",
    "\n",
    "    def autolabel(rects):\n",
    "        for rect in rects:\n",
    "            height = rect.get_height()\n",
    "            ax.annotate(text=f'{round(height, 5)}',\n",
    "                        xy=(rect.get_x() + rect.get_width() / 2, height),\n",
    "                        xytext=(0, 3),\n",
    "                        textcoords='offset points',\n",
    "                        ha='center',\n",
    "                        va='bottom',\n",
    "                        size=8,\n",
    "                        weight='bold',\n",
    "                        color='black')\n",
    "\n",
    "    autolabel(rects1)\n",
    "    autolabel(rects2)\n",
    "    ax.legend([\"Train\", \"Test\"])\n",
    "    plt.show()\n",
    "\n",
    "# Call the function to plot accuracy metrics for Extra Trees\n",
    "plot_accuracy({'Extra Trees': accuracy_train_et}, {'Extra Trees': accuracy_test_et})\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "a566f69b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "def plot_accuracy(accuracy_train: dict, accuracy_test: dict):\n",
    "    df_accuracy_train = pd.DataFrame.from_dict(accuracy_train, orient='index').rename(columns={0: 'Train'})\n",
    "    df_accuracy_test = pd.DataFrame.from_dict(accuracy_test, orient='index').rename(columns={0: 'Test'})\n",
    "    df_accuracy = pd.merge(df_accuracy_train, df_accuracy_test, left_index=True, right_index=True)\n",
    "    df_accuracy = df_accuracy.sort_values(['Train', 'Test'], ascending=False)\n",
    "\n",
    "    fig, ax = plt.subplots(figsize=(8, 4))\n",
    "    n = len(df_accuracy.index)\n",
    "    x = np.arange(n)\n",
    "    width = 0.3\n",
    "\n",
    "    rects1 = ax.bar(x=x - width, height=df_accuracy.iloc[:, 0], width=width)\n",
    "    rects2 = ax.bar(x=x, height=df_accuracy.iloc[:, 1], width=width)\n",
    "    ax.set_xticks(x)\n",
    "    ax.set_xticklabels(df_accuracy.index.to_list(), rotation=45, ha=\"right\")\n",
    "    ax.set_xlabel('Models', fontsize=10, fontweight='bold', color='darkblue')\n",
    "    ax.set_ylabel('Accuracy', fontsize=10, fontweight='bold', color='darkblue')\n",
    "    ax.set_title('Accuracy Comparison for Random Forest', fontsize=12, fontweight='bold', color='darkred')\n",
    "\n",
    "    def autolabel(rects):\n",
    "        for rect in rects:\n",
    "            height = rect.get_height()\n",
    "            ax.annotate(text=f'{round(height, 5)}',\n",
    "                        xy=(rect.get_x() + rect.get_width() / 2, height),\n",
    "                        xytext=(0, 3),\n",
    "                        textcoords='offset points',\n",
    "                        ha='center',\n",
    "                        va='bottom',\n",
    "                        size=8,\n",
    "                        weight='bold',\n",
    "                        color='black')\n",
    "\n",
    "    autolabel(rects1)\n",
    "    autolabel(rects2)\n",
    "    ax.legend([\"Train\", \"Test\"])\n",
    "    plt.show()\n",
    "\n",
    "# Call the function to plot accuracy metrics for Random Forest\n",
    "plot_accuracy({'Random Forest': accuracy_train_rf}, {'Random Forest': accuracy_test_rf})\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "d47e9a0b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "def plot_accuracy(accuracy_train: dict, accuracy_test: dict):\n",
    "    df_accuracy_train = pd.DataFrame.from_dict(accuracy_train, orient='index').rename(columns={0: 'Train'})\n",
    "    df_accuracy_test = pd.DataFrame.from_dict(accuracy_test, orient='index').rename(columns={0: 'Test'})\n",
    "    df_accuracy = pd.merge(df_accuracy_train, df_accuracy_test, left_index=True, right_index=True)\n",
    "    df_accuracy = df_accuracy.sort_values(['Train', 'Test'], ascending=False)\n",
    "\n",
    "    fig, ax = plt.subplots(figsize=(8, 4))\n",
    "    n = len(df_accuracy.index)\n",
    "    x = np.arange(n)\n",
    "    width = 0.3\n",
    "\n",
    "    rects1 = ax.bar(x=x - width, height=df_accuracy.iloc[:, 0], width=width)\n",
    "    rects2 = ax.bar(x=x, height=df_accuracy.iloc[:, 1], width=width)\n",
    "    ax.set_xticks(x)\n",
    "    ax.set_xticklabels(df_accuracy.index.to_list(), rotation=45, ha=\"right\")\n",
    "    ax.set_xlabel('Models', fontsize=10, fontweight='bold', color='darkblue')\n",
    "    ax.set_ylabel('Accuracy', fontsize=10, fontweight='bold', color='darkblue')\n",
    "    ax.set_title('Accuracy Comparison for SVM', fontsize=12, fontweight='bold', color='darkred')\n",
    "\n",
    "    def autolabel(rects):\n",
    "        for rect in rects:\n",
    "            height = rect.get_height()\n",
    "            ax.annotate(text=f'{round(height, 5)}',\n",
    "                        xy=(rect.get_x() + rect.get_width() / 2, height),\n",
    "                        xytext=(0, 3),\n",
    "                        textcoords='offset points',\n",
    "                        ha='center',\n",
    "                        va='bottom',\n",
    "                        size=8,\n",
    "                        weight='bold',\n",
    "                        color='black')\n",
    "\n",
    "    autolabel(rects1)\n",
    "    autolabel(rects2)\n",
    "    ax.legend([\"Train\", \"Test\"])\n",
    "    plt.show()\n",
    "\n",
    "# Call the function to plot accuracy metrics for SVM\n",
    "plot_accuracy({'SVM': accuracy_train_svm}, {'SVM': accuracy_test_svm})\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "63ae168b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "* Extra_Trees => Total training time = 7.98416543006897\n",
      "* Random_Forest => Total training time = 10.959824323654175\n",
      "* SVM => Total training time = 1.131746530532837\n",
      "Final Results:\n",
      "Accuracy on Train Set: {'Extra_Trees': 1.0, 'Random_Forest': 1.0, 'SVM': 0.696969696969697}\n",
      "Accuracy on Test Set: {'Extra_Trees': 0.97, 'Random_Forest': 0.95, 'SVM': 0.62}\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import time\n",
    "from sklearn.ensemble import ExtraTreesClassifier, RandomForestClassifier\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.metrics import accuracy_score, confusion_matrix, classification_report\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "# Function for enhanced feature engineering\n",
    "def enhance_features(data):\n",
    "    # Add more sophisticated feature engineering\n",
    "    # Example: data['new_feature'] = np.log1p(data['feature1'] * data['feature2'])\n",
    "    return data\n",
    "\n",
    "# Load and preprocess your dataset\n",
    "# Assuming X_train, X_test, y_train, y_test are already defined\n",
    "\n",
    "# Enhance features\n",
    "X_train = enhance_features(X_train)\n",
    "X_test = enhance_features(X_test)\n",
    "\n",
    "SEED = 42  # Set a seed for reproducibility\n",
    "\n",
    "# Update ExtraTreesClassifier and RandomForestClassifier hyperparameter grids\n",
    "et_param_grid = {\n",
    "    'n_estimators': [100, 200, 300],\n",
    "    'max_depth': [None, 10, 20],\n",
    "    'min_samples_split': [2, 5, 10],\n",
    "    # Add more hyperparameters as needed\n",
    "}\n",
    "\n",
    "rf_param_grid = {\n",
    "    'n_estimators': [100, 200, 300],\n",
    "    'max_depth': [None, 10, 20],\n",
    "    'min_samples_split': [2, 5, 10],\n",
    "    # Add more hyperparameters as needed\n",
    "}\n",
    "\n",
    "svm_param_grid = {\n",
    "    'C': [0.1, 1, 10],\n",
    "    'kernel': ['linear', 'rbf', 'poly'],\n",
    "    # Add more hyperparameters as needed\n",
    "}\n",
    "\n",
    "et = ExtraTreesClassifier(bootstrap=True, random_state=SEED)\n",
    "rf = RandomForestClassifier(random_state=SEED)\n",
    "svm = SVC(random_state=SEED)\n",
    "\n",
    "MODELS = {'Extra_Trees': et, 'Random_Forest': rf, 'SVM': svm}\n",
    "\n",
    "# We store the accuracy metric\n",
    "accuracy_train = {}\n",
    "accuracy_test = {}\n",
    "\n",
    "# We store the confusion matrix\n",
    "cf_matrix_train = {}\n",
    "cf_matrix_test = {}\n",
    "\n",
    "# We store the classification report\n",
    "clf_report_train = {}\n",
    "clf_report_test = {}\n",
    "\n",
    "for model_name, model in MODELS.items():\n",
    "    start = time.time()\n",
    "\n",
    "    # Use cross-validation to tune hyperparameters\n",
    "    if model_name == 'Extra_Trees':\n",
    "        param_grid = et_param_grid\n",
    "    elif model_name == 'Random_Forest':\n",
    "        param_grid = rf_param_grid\n",
    "    else:  # SVM\n",
    "        param_grid = svm_param_grid\n",
    "\n",
    "    grid_search = GridSearchCV(model, param_grid, cv=5, scoring='accuracy', n_jobs=-1)\n",
    "    grid_search.fit(X_train, y_train)\n",
    "    model = grid_search.best_estimator_\n",
    "\n",
    "    # Fit model\n",
    "    model.fit(X_train, y_train)\n",
    "    end = time.time()\n",
    "    print(f\"* {model_name} => Total training time = {end - start}\")\n",
    "\n",
    "    y_pred_train = model.predict(X_train)\n",
    "    y_pred_test = model.predict(X_test)\n",
    "\n",
    "    # Accuracy score\n",
    "    accuracy_train[model_name] = accuracy_score(np.array(y_train), y_pred_train)\n",
    "    accuracy_test[model_name] = accuracy_score(np.array(y_test), y_pred_test)\n",
    "\n",
    "    # Confusion Matrix\n",
    "    cf_matrix_train[model_name] = confusion_matrix(np.array(y_train), y_pred_train)\n",
    "    cf_matrix_test[model_name] = confusion_matrix(np.array(y_test), y_pred_test)\n",
    "\n",
    "    # Classification Report\n",
    "    clf_report_train[model_name] = classification_report(np.array(y_train), y_pred_train)\n",
    "    clf_report_test[model_name] = classification_report(np.array(y_test), y_pred_test)\n",
    "\n",
    "# Print the results\n",
    "print(\"Final Results:\")\n",
    "print(f\"Accuracy on Train Set: {accuracy_train}\")\n",
    "print(f\"Accuracy on Test Set: {accuracy_test}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "84607604",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "* Extra_Trees => Total training time = 8.15294885635376\n",
      "* Random_Forest => Total training time = 12.320245027542114\n",
      "* SVM => Total training time = 1.1700098514556885\n"
     ]
    }
   ],
   "source": [
    "MODELS = {'Extra_Trees': et, 'Random_Forest': rf, 'SVM': svm}\n",
    "\n",
    "# We store the accuracy metric\n",
    "accuracy_train = {}\n",
    "accuracy_test = {}\n",
    "\n",
    "# We store the confusion matrix\n",
    "cf_matrix_train = {}\n",
    "cf_matrix_test = {}\n",
    "\n",
    "# We store the classification report\n",
    "clf_report_train = {}\n",
    "clf_report_test = {}\n",
    "\n",
    "for model_name, model in MODELS.items():\n",
    "    start = time.time()\n",
    "\n",
    "    # Use cross-validation to tune hyperparameters\n",
    "    if model_name == 'Extra_Trees':\n",
    "        param_grid = et_param_grid\n",
    "    elif model_name == 'Random_Forest':\n",
    "        param_grid = rf_param_grid\n",
    "    else:  # SVM\n",
    "        param_grid = svm_param_grid\n",
    "\n",
    "    grid_search = GridSearchCV(model, param_grid, cv=5, scoring='accuracy', n_jobs=-1)\n",
    "    grid_search.fit(X_train, y_train)\n",
    "    model = grid_search.best_estimator_\n",
    "\n",
    "    # Fit model\n",
    "    model.fit(X_train, y_train)\n",
    "    end = time.time()\n",
    "    print(f\"* {model_name} => Total training time = {end - start}\")\n",
    "\n",
    "    y_pred_train = model.predict(X_train)\n",
    "    y_pred_test = model.predict(X_test)\n",
    "\n",
    "    # Accuracy score\n",
    "    accuracy_train[model_name] = accuracy_score(np.array(y_train), y_pred_train)\n",
    "    accuracy_test[model_name] = accuracy_score(np.array(y_test), y_pred_test)\n",
    "\n",
    "    # Confusion Matrix\n",
    "    cf_matrix_train[model_name] = confusion_matrix(np.array(y_train), y_pred_train)\n",
    "    cf_matrix_test[model_name] = confusion_matrix(np.array(y_test), y_pred_test)\n",
    "\n",
    "    # Classification Report\n",
    "    clf_report_train[model_name] = classification_report(np.array(y_train), y_pred_train)\n",
    "    clf_report_test[model_name] = classification_report(np.array(y_test), y_pred_test)\n",
    "\n",
    "    # Store the trained model in a variable with a specific name\n",
    "    if model_name == 'Extra_Trees':\n",
    "        model_et = model\n",
    "    elif model_name == 'Random_Forest':\n",
    "        model_rf = model\n",
    "    else:  # SVM\n",
    "        model_svm = model\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "80c6732b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Recall for Extra Trees: 0.97\n",
      "Precision for Extra Trees: 0.9732142857142857\n",
      "F1 Score for Extra Trees: 0.9698490566037736\n",
      "MCC for Extra Trees: 0.9611078921196086\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import recall_score, precision_score, f1_score, matthews_corrcoef\n",
    "\n",
    "# Assuming y_true and y_pred are your true and predicted labels for Extra Trees\n",
    "# Modify as needed based on your actual variable names\n",
    "y_true_et = y_test  # Change this based on your actual variable names\n",
    "y_pred_et = model_et.predict(X_test)  # Change this based on your actual variable names\n",
    "\n",
    "# Calculate metrics for Extra Trees\n",
    "recall_et = recall_score(y_true_et, y_pred_et, average='weighted')\n",
    "precision_et = precision_score(y_true_et, y_pred_et, average='weighted')\n",
    "f1_et = f1_score(y_true_et, y_pred_et, average='weighted')\n",
    "mcc_et = matthews_corrcoef(y_true_et, y_pred_et)\n",
    "\n",
    "# Print the metrics for Extra Trees\n",
    "print(f\"Recall for Extra Trees: {recall_et}\")\n",
    "print(f\"Precision for Extra Trees: {precision_et}\")\n",
    "print(f\"F1 Score for Extra Trees: {f1_et}\")\n",
    "print(f\"MCC for Extra Trees: {mcc_et}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "03907c9f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Recall for Random Forest: 0.95\n",
      "Precision for Random Forest: 0.9517857142857143\n",
      "F1 Score for Random Forest: 0.949182389937107\n",
      "MCC for Random Forest: 0.934377037103071\n"
     ]
    }
   ],
   "source": [
    "y_true_rf = y_test  # Change this based on your actual variable names\n",
    "y_pred_rf = model_rf.predict(X_test)  # Change this based on your actual variable names\n",
    "\n",
    "# Calculate metrics for Random Forest\n",
    "recall_rf = recall_score(y_true_rf, y_pred_rf, average='weighted')\n",
    "precision_rf = precision_score(y_true_rf, y_pred_rf, average='weighted')\n",
    "f1_rf = f1_score(y_true_rf, y_pred_rf, average='weighted')\n",
    "mcc_rf = matthews_corrcoef(y_true_rf, y_pred_rf)\n",
    "\n",
    "# Print the metrics for Random Forest\n",
    "print(f\"Recall for Random Forest: {recall_rf}\")\n",
    "print(f\"Precision for Random Forest: {precision_rf}\")\n",
    "print(f\"F1 Score for Random Forest: {f1_rf}\")\n",
    "print(f\"MCC for Random Forest: {mcc_rf}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "49782efa",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Recall for SVM: 0.62\n",
      "Precision for SVM: 0.6848509316770186\n",
      "F1 Score for SVM: 0.6279999256616117\n",
      "MCC for SVM: 0.5018682652510785\n"
     ]
    }
   ],
   "source": [
    "y_true_svm = y_test  # Change this based on your actual variable names\n",
    "y_pred_svm = model_svm.predict(X_test)  # Change this based on your actual variable names\n",
    "\n",
    "# Calculate metrics for SVM\n",
    "recall_svm = recall_score(y_true_svm, y_pred_svm, average='weighted')\n",
    "precision_svm = precision_score(y_true_svm, y_pred_svm, average='weighted')\n",
    "f1_svm = f1_score(y_true_svm, y_pred_svm, average='weighted')\n",
    "mcc_svm = matthews_corrcoef(y_true_svm, y_pred_svm)\n",
    "\n",
    "# Print the metrics for SVM\n",
    "print(f\"Recall for SVM: {recall_svm}\")\n",
    "print(f\"Precision for SVM: {precision_svm}\")\n",
    "print(f\"F1 Score for SVM: {f1_svm}\")\n",
    "print(f\"MCC for SVM: {mcc_svm}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "1c60bcfe",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Random Forest Metrics:\n",
      "Accuracy: 0.98\n",
      "Confusion Matrix:\n",
      " [[26  0  1  0]\n",
      " [ 0 21  0  0]\n",
      " [ 0  0 23  1]\n",
      " [ 0  0  0 28]]\n",
      "Classification Report:\n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "        fall       1.00      0.96      0.98        27\n",
      "        idle       1.00      1.00      1.00        21\n",
      "      motion       0.96      0.96      0.96        24\n",
      "        step       0.97      1.00      0.98        28\n",
      "\n",
      "    accuracy                           0.98       100\n",
      "   macro avg       0.98      0.98      0.98       100\n",
      "weighted avg       0.98      0.98      0.98       100\n",
      "\n",
      "\n",
      "Extra Trees Metrics:\n",
      "Accuracy: 0.98\n",
      "Confusion Matrix:\n",
      " [[27  0  0  0]\n",
      " [ 0 21  0  0]\n",
      " [ 0  1 22  1]\n",
      " [ 0  0  0 28]]\n",
      "Classification Report:\n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "        fall       1.00      1.00      1.00        27\n",
      "        idle       0.95      1.00      0.98        21\n",
      "      motion       1.00      0.92      0.96        24\n",
      "        step       0.97      1.00      0.98        28\n",
      "\n",
      "    accuracy                           0.98       100\n",
      "   macro avg       0.98      0.98      0.98       100\n",
      "weighted avg       0.98      0.98      0.98       100\n",
      "\n",
      "\n",
      "SVM Metrics:\n",
      "Accuracy: 0.58\n",
      "Confusion Matrix:\n",
      " [[27  0  0  0]\n",
      " [ 0 21  0  0]\n",
      " [ 1 13 10  0]\n",
      " [ 0 28  0  0]]\n",
      "Classification Report:\n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "        fall       0.96      1.00      0.98        27\n",
      "        idle       0.34      1.00      0.51        21\n",
      "      motion       1.00      0.42      0.59        24\n",
      "        step       0.00      0.00      0.00        28\n",
      "\n",
      "    accuracy                           0.58       100\n",
      "   macro avg       0.58      0.60      0.52       100\n",
      "weighted avg       0.57      0.58      0.51       100\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.ensemble import RandomForestClassifier, ExtraTreesClassifier\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.metrics import accuracy_score, confusion_matrix, classification_report\n",
    "\n",
    "# Split your data into training and testing sets\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
    "\n",
    "# Random Forest\n",
    "rf_model = RandomForestClassifier()\n",
    "rf_model.fit(X_train, y_train)\n",
    "y_pred_rf = rf_model.predict(X_test)\n",
    "\n",
    "print(\"Random Forest Metrics:\")\n",
    "print(\"Accuracy:\", accuracy_score(y_test, y_pred_rf))\n",
    "print(\"Confusion Matrix:\\n\", confusion_matrix(y_test, y_pred_rf))\n",
    "print(\"Classification Report:\\n\", classification_report(y_test, y_pred_rf))\n",
    "\n",
    "# Extra Trees\n",
    "et_model = ExtraTreesClassifier()\n",
    "et_model.fit(X_train, y_train)\n",
    "y_pred_et = et_model.predict(X_test)\n",
    "\n",
    "print(\"\\nExtra Trees Metrics:\")\n",
    "print(\"Accuracy:\", accuracy_score(y_test, y_pred_et))\n",
    "print(\"Confusion Matrix:\\n\", confusion_matrix(y_test, y_pred_et))\n",
    "print(\"Classification Report:\\n\", classification_report(y_test, y_pred_et))\n",
    "\n",
    "# SVM\n",
    "svm_model = SVC()\n",
    "svm_model.fit(X_train, y_train)\n",
    "y_pred_svm = svm_model.predict(X_test)\n",
    "\n",
    "print(\"\\nSVM Metrics:\")\n",
    "print(\"Accuracy:\", accuracy_score(y_test, y_pred_svm))\n",
    "print(\"Confusion Matrix:\\n\", confusion_matrix(y_test, y_pred_svm))\n",
    "print(\"Classification Report:\\n\", classification_report(y_test, y_pred_svm))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "803c94e8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.multiclass import OneVsRestClassifier\n",
    "from sklearn.preprocessing import label_binarize\n",
    "from sklearn.metrics import roc_curve, auc\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# Split your data into training and testing sets\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
    "\n",
    "# Create a multiclass classifier using One-vs-Rest strategy\n",
    "rf_model = OneVsRestClassifier(RandomForestClassifier())\n",
    "y_score = rf_model.fit(X_train, y_train).predict_proba(X_test)\n",
    "\n",
    "# Binarize the labels\n",
    "y_test_bin = label_binarize(y_test, classes=np.unique(y))\n",
    "\n",
    "# Plot ROC curve for each class\n",
    "plt.figure(figsize=(8, 6))\n",
    "\n",
    "for i in range(len(np.unique(y))):\n",
    "    fpr, tpr, _ = roc_curve(y_test_bin[:, i], y_score[:, i])\n",
    "    roc_auc = auc(fpr, tpr)\n",
    "    plt.plot(fpr, tpr, label=f'Class {i+1} (AUC = {roc_auc:.2f})')\n",
    "\n",
    "plt.plot([0, 1], [0, 1], linestyle='--', color='gray', label='Random Guessing')\n",
    "plt.xlabel('False Positive Rate (FPR)')\n",
    "plt.ylabel('True Positive Rate (TPR)')\n",
    "plt.title('ROC Curve for Random Forest (Multiclass)')\n",
    "plt.legend(loc='lower right')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "ec4e3e38",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.ensemble import ExtraTreesClassifier\n",
    "from sklearn.multiclass import OneVsRestClassifier\n",
    "from sklearn.preprocessing import label_binarize\n",
    "from sklearn.metrics import roc_curve, auc\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# Split your data into training and testing sets\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
    "\n",
    "# Create a multiclass classifier using One-vs-Rest strategy\n",
    "et_model = OneVsRestClassifier(ExtraTreesClassifier())\n",
    "y_score_et = et_model.fit(X_train, y_train).predict_proba(X_test)\n",
    "\n",
    "# Binarize the labels\n",
    "y_test_bin_et = label_binarize(y_test, classes=np.unique(y))\n",
    "\n",
    "# Plot ROC curve for each class\n",
    "plt.figure(figsize=(8, 6))\n",
    "\n",
    "for i in range(len(np.unique(y))):\n",
    "    fpr, tpr, _ = roc_curve(y_test_bin_et[:, i], y_score_et[:, i])\n",
    "    roc_auc = auc(fpr, tpr)\n",
    "    plt.plot(fpr, tpr, label=f'Class {i+1} (AUC = {roc_auc:.2f})')\n",
    "\n",
    "plt.plot([0, 1], [0, 1], linestyle='--', color='gray', label='Random Guessing')\n",
    "plt.xlabel('False Positive Rate (FPR)')\n",
    "plt.ylabel('True Positive Rate (TPR)')\n",
    "plt.title('ROC Curve for Extra Trees (Multiclass)')\n",
    "plt.legend(loc='lower right')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "ef649e05",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.multiclass import OneVsRestClassifier\n",
    "from sklearn.preprocessing import label_binarize\n",
    "from sklearn.metrics import roc_curve, auc\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# Split your data into training and testing sets\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
    "\n",
    "# Create a multiclass classifier using One-vs-Rest strategy\n",
    "svm_model = OneVsRestClassifier(SVC(probability=True))\n",
    "y_score_svm = svm_model.fit(X_train, y_train).predict_proba(X_test)\n",
    "\n",
    "# Binarize the labels\n",
    "y_test_bin_svm = label_binarize(y_test, classes=np.unique(y))\n",
    "\n",
    "# Plot ROC curve for each class\n",
    "plt.figure(figsize=(8, 6))\n",
    "\n",
    "for i in range(len(np.unique(y))):\n",
    "    fpr, tpr, _ = roc_curve(y_test_bin_svm[:, i], y_score_svm[:, i])\n",
    "    roc_auc = auc(fpr, tpr)\n",
    "    plt.plot(fpr, tpr, label=f'Class {i+1} (AUC = {roc_auc:.2f})')\n",
    "\n",
    "plt.plot([0, 1], [0, 1], linestyle='--', color='gray', label='Random Guessing')\n",
    "plt.xlabel('False Positive Rate (FPR)')\n",
    "plt.ylabel('True Positive Rate (TPR)')\n",
    "plt.title('ROC Curve for SVM (Multiclass)')\n",
    "plt.legend(loc='lower right')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e2c5e458",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}