diff --git a/doc/pub/week34/ipynb/Results/FigureFiles/Masses2016.png b/doc/pub/week34/ipynb/Results/FigureFiles/Masses2016.png
index 043b9723f..f923e900b 100644
Binary files a/doc/pub/week34/ipynb/Results/FigureFiles/Masses2016.png and b/doc/pub/week34/ipynb/Results/FigureFiles/Masses2016.png differ
diff --git a/doc/pub/week34/ipynb/week34.ipynb b/doc/pub/week34/ipynb/week34.ipynb
index f9f842586..1ea08fa22 100644
--- a/doc/pub/week34/ipynb/week34.ipynb
+++ b/doc/pub/week34/ipynb/week34.ipynb
@@ -2156,7 +2156,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": 2,
    "id": "ca868b5c",
    "metadata": {},
    "outputs": [
@@ -2166,7 +2166,7 @@
        "'\"\\nfrom pylab import plt, mpl\\nplt.style.use(\\'seaborn\\')\\nmpl.rcParams[\\'font.family\\'] = \\'serif\\'\\n\\ndef MakePlot(x,y, styles, labels, axlabels):\\n    plt.figure(figsize=(10,6))\\n    for i in range(len(x)):\\n        plt.plot(x[i], y[i], styles[i], label = labels[i])\\n        plt.xlabel(axlabels[0])\\n        plt.ylabel(axlabels[1])\\n    plt.legend(loc=0)\\n'"
       ]
      },
-     "execution_count": 64,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2203,7 +2203,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 3,
    "id": "edef3728",
    "metadata": {},
    "outputs": [
@@ -2213,7 +2213,7 @@
        "'                                                                                                                         \\nThis is taken from the data file of the mass 2016 evaluation.                                                               \\nAll files are 3436 lines long with 124 character per line.                                                                  \\n       Headers are 39 lines long.                                                                                           \\n   col 1     :  Fortran character control: 1 = page feed  0 = line feed                                                     \\n   format    :  a1,i3,i5,i5,i5,1x,a3,a4,1x,f13.5,f11.5,f11.3,f9.3,1x,a2,f11.3,f9.3,1x,i3,1x,f12.5,f11.5                     \\n   These formats are reflected in the pandas widths variable below, see the statement                                       \\n   widths=(1,3,5,5,5,1,3,4,1,13,11,11,9,1,2,11,9,1,3,1,12,11,1),                                                            \\n   Pandas has also a variable header, with length 39 in this case.                                                          \\n'"
       ]
      },
-     "execution_count": 51,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2244,7 +2244,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 4,
    "id": "0a2099c5",
    "metadata": {},
    "outputs": [],
@@ -2288,7 +2288,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 5,
    "id": "c36ad284",
    "metadata": {},
    "outputs": [
@@ -2334,7 +2334,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 6,
    "id": "1ad1fff9",
    "metadata": {},
    "outputs": [],
@@ -2358,7 +2358,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 7,
    "id": "1ea1c99f",
    "metadata": {},
    "outputs": [],
@@ -2378,7 +2378,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 8,
    "id": "4bb96bf8",
    "metadata": {},
    "outputs": [
@@ -2391,14 +2391,12 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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",
       "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     }
    ],
@@ -2438,7 +2436,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": 9,
    "id": "c3072d47",
    "metadata": {},
    "outputs": [
@@ -2461,22 +2459,12 @@
       "/Users/mhjensen/miniforge3/envs/myenv/lib/python3.9/site-packages/sklearn/neural_network/_multilayer_perceptron.py:691: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n",
       "  warnings.warn(\n",
       "/Users/mhjensen/miniforge3/envs/myenv/lib/python3.9/site-packages/sklearn/neural_network/_multilayer_perceptron.py:691: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n",
-      "  warnings.warn(\n",
-      "/Users/mhjensen/miniforge3/envs/myenv/lib/python3.9/site-packages/sklearn/neural_network/_multilayer_perceptron.py:691: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n",
-      "  warnings.warn(\n",
-      "/Users/mhjensen/miniforge3/envs/myenv/lib/python3.9/site-packages/sklearn/neural_network/_multilayer_perceptron.py:691: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n",
-      "  warnings.warn(\n",
-      "/Users/mhjensen/miniforge3/envs/myenv/lib/python3.9/site-packages/sklearn/neural_network/_multilayer_perceptron.py:691: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n",
-      "  warnings.warn(\n",
-      "/Users/mhjensen/miniforge3/envs/myenv/lib/python3.9/site-packages/sklearn/neural_network/_multilayer_perceptron.py:691: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n",
-      "  warnings.warn(\n",
-      "/Users/mhjensen/miniforge3/envs/myenv/lib/python3.9/site-packages/sklearn/neural_network/_multilayer_perceptron.py:691: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (100) reached and the optimization hasn't converged yet.\n",
       "  warnings.warn(\n"
      ]
     },
     {
      "data": {
-      "image/png": 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",
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nTiZMmJBevXpV/DoCCQAAsIh+/fpl7ty5GTRoUCZNmpQ77rgjN9xwQ/r375/kg3NHDj744Fx00UV54IEH8txzz+Xkk09Op06dstdee1X8Os4hAQAAFtGhQ4dce+21ueCCC9K3b9+ss846GThwYPr27dv4MyeccELef//9/OAHP8i8efPSu3fvDBs2bJET3T9OTUND87lcwFc3GFB6BJqJui3WLz0CzcQqcxeUHoFmomHc+NIj0Ezct3B46RE+0oypnUuPsFgd1n+t9AhLRGULAAAoRiABAACKcQ4JAABUoJpXtGrObEgAAIBiBBIAAKAYlS0AAKjAwuZzcdplyoYEAAAoRiABAACKUdkCAIAK1JceYCVlQwIAABQjkAAAAMWobAEAQAUWujFiVdiQAAAAxQgkAABAMSpbAABQgYUaW1VhQwIAABQjkAAAAMWobAEAQAXcGLE6bEgAAIBiBBIAAKAYlS0AAKjAwtSUHmGlZEMCAAAUI5AAAADFqGwBAEAF6t0YsSpsSAAAgGIEEgAAoBiVLQAAqICrbFWHDQkAAFCMQAIAABSjsgUAABVQ2aoOGxIAAKAYgQQAAChGZQsAACpQ36CyVQ02JAAAQDECCQAAUIzKFgAAVMBVtqrDhgQAAChGIAEAAIpR2QIAgAos9Fl+VXhXAQCAYgQSAACgGJUtAACogBsjVocNCQAAUIxAAgAAFKOyBQAAFXBjxOqwIQEAAIoRSAAAgGJUtgAAoAILG3yWXw3eVQAAoBiBBAAAKEZlCwAAKlDvs/yq8K4CAADFCCQAAEAxKlsAAFABN0asDhsSAACgGIEEAAAoRmULAAAq4MaI1eFdBQAAihFIAACAYlS2AACgAvWuslUVNiQAAEAxAgkAAFCMyhYAAFRgoc/yq8K7CgAAFCOQAAAAxahsAQBABdwYsTq8qwAAQDE2JM1Yt+02zmFnfD1b9Nwo770zP+P+38Rce97IzJ4xd7E/v2ptyxx0yleze7/eab9W27z24vSMuOrB/OHOsct4clZke+/dM/vuu33WW3/NzJz5TsaMmZTrf/lw3n23LknS+bNr57jj9shWW3VO/cKGPPLIC7nyygfyzjvzC0/Oimqdddvn6puPzTmnDs8zT0xpPN5hndVz9IA902vHrllllVXy/IS/Zehl9+fFF6YVnJblVa8vb5PDz90/G3bvnNlvzsmoq+/PLT8Z+bHP+fzXts0hP9wvXbbeMHNmvJ3Rdzya6wbdknnvLvrvszarr5arn/ppfnXu7fn9DQ9V6a+A5ZNA0kxtuvVn8+NbB+SpR17IeUdem7U7rZHDT/96zrru6Hz/m5cs9jmnDzksn99zq4y46oE89cgL6bpl5wz4yQFpv3bb/GaYf3nyf9t//x1y5FG7ZvjwP+fJJ6Zk/Q3WyuGH75yNN/5MBp56S9q2bZWLLjowM2bMzY9//LustVbbHHPMblln3fY5beAtpcdnBbRupzVy4WUHpd3qrZscX61NbX5+9aF5f8HCDL7wrtTVvZ+Djtg5P/7Fwel/4FV56yM+mKF56r7j5jl35MA8dOuf8suzhmerL3bL4efvnxYtavLrC+9c7HP67LNdzrnj1Nz/q4cz7MxfZ6PPdc7hFxyQNdZpnwsPvrzJz66+VtucO3JgOm287rL4c1gC9cpFVSGQNFNH/nDfvDThbzn38GtSX9+QJHn37Xk59tx+6fjZDpn+6owmP991y875wle3yfU//l2GX/77JMlTf3w+896ry5GDvpn7b3ss78x5b5n/Haw4amqSA7+zY0b97skMu/aDAPvEEy9nzpz3cvbZfbP55p2y/fZd0q5d6/Q/5rrMnv3BP09/f/PtXPjj/bPVVp3zl7+8VvJPYAVSU5Pstfc2OebEvRb7+LcO7JM11myTI789pDF8vDBxaq644ej02H6j/L/fj1+W47KcO+Ss/fLiUy/nJ4dekSQZe+/TabnqKtn/tG/m9ktGpW7egkWec9zFh2b0HY/moiOvTJI89YfxabFKi+w74CtptVpt5r/3wVZ4x2/0yvcuPSyrtWu9yO+A5kLMa4ZWX6tNeuy4aUbd8MfGMJIkf7rn6Xy391mLhJEk+exmHZMkj973bJPjz475a1Zr2yrbfGGz6g7NCq9Nm1a5//7xeeCBpv+h99qrbyVJ1l9/rfTq3SXPPvtaYxhJkscffynvvDM/O+zQdZnOy4qty6Ydc8Jpe+e+u57JT84eucjjO+3eLX98cGKTTcjMGe/kO/tcKozQxKq1LdNjl+4ZfedjTY4/POLRtFl9tWz9pc8t8pyuPTfO+l07ZeQv/qfJ8TsvvyeHbn5iYxhpu0abnH379/P0QxNyxlf/q3p/BCznbEiaoS6f2yAtWrTIrL+/nYGXfzc7/NvWqampyZj/eSZX/vC2zJ296Kbjw/NKOn62Q15+7vXG4+tt9JkPjm/YYdkMzwrrnXfm5xeX37fI8S99aYskyeSX38xGG34mf/h/E5s83tCQTJs2K507r71M5mTl8Ob02Tms3+X5+xtvp8d2GzV5bJVVWmSjLuvkwXuezaH9d81Xvrlt1lizTSY881p+8bN78vKLbxSamuXRept0TG2rVfO3v77e5PjUSR+ca9R5s/Uy7r5nmjy2ac+NkyR179XlvN8OzLa7b526eXV54KbRuWbgjVkw/4ONyvx35+eorU7Jay+8no4brVP9P4YltrChpvQIK6XigeT999/P73//+4wdOzZTp05NXV1dVltttXTq1Cm9evXKXnvtlZYti4+5UlmjQ7skyck/Pyhj/zAh5x05NOt3WSeHnf6NrLfxZ/L9b16ShoaGJs959s+T8vrLb+bYc/fL/Pfq8sJTr6RL9w1yxKBvZuHC+rRuU1viT2EF133LDXLAgX0yevTzmfLy39O2Xau8u5iTPd99ty5t2rYqMCErqrfnzMvbc+Yt9rHV27dOy5ar5FsH9snrf5uZSy4YlVVXXSWH9t81F1313fT/ztWZ8ebby3hilldt12yTJIvUkt99+4Pv27RfbZHnrPGZ9kmSs0d8P3+4+ZHcfvFd2aJX13z3nG9nzXXb54IDBydJ3l+wMK+98Poiz4fmpuh/6b/yyis5+uijM3369HTv3j3rrrtu1lhjjcyfPz8TJ07MiBEjcvnll+faa6/N+uuvX3LUlUrLVVdJkkx69tUMPvXmJMlTo1/IO7Pfy+lXHp5td94iTzz0XJPnvL9gYQYdNCQn//ygXDh8QJJkxrTZueqs23P6lYdn3v9eIQkqtfXWnXP+Bd/O1Kkzc9HP7k6S1NTU5F+ycOPxf64XwpL48N+BSXLmiTdl3nsffFr9wsSp+eWI/8g3v9071w15sNR4LGdatPjfdvvi/uWULPbfTS1rP/jPq0dGPp5rz/h1kuTp/zc+NS1qctSF38kNZ98qiMA/KRpIfvSjH6Vz5865/fbbs/rqqy/y+Jw5c3LyySfn3HPPzVVXXVVgwpXTe3M/+AT6sfv/0uT42P+tynTdsvMigSRJXn/57xnYb3DW6NAu7ddqm79NfjPrrL9WVlmlRd6e9W71B2elsdtun8vA0/bJq6/OyGkDh+fttz/4JPudd+an7WK2bauttmrefHPOsh6TldS773zwAcrTT7zcGEaS5M3pc/Lqy39P1807lRqN5dDcWe8kWXQT0mb1D75/Z86i///33v9uTx6964kmx8fe+1SOuvA76dpzY4FkBbXQ6ddVUfRdHTduXAYOHLjYMJIk7du3z6mnnprHH398GU+2cps6+c0kH5yo989atvzgU8P5i7laSG3rVbPbt3ql42c7ZPaMuXl10vTUL6zPZj0+m+SDbQtU4t/33yFnDvpmJkz4W04+6abMnPlO42Ovvjoj62+wVpOfr6lJOnVaM1OmLHqxBfg03n1nfmbOmJtVV130M7lVWrbI/PmL/juQ5mvqi9Oz8P2FWb9r06C6/qYffP/KhEWv/ve3SR+EjVVbNf1nbJX//Weu7j2tAvhnRQNJ+/bt88YbH3/y4NSpU9O6tUvhLU2v/HVapr0yIzt/c/smx3f4t62SJOMffXGR57xf936OP//b+epBX2g81qJFTb5x+M752+Q3MuU5n/Twf9tnn57p33/3PPTQxJw28JZFbnY4buzkbLPNhlljjX98Etm79yZp27ZVxo2dvKzHZSX2+JhJ2e7zXdL+n/5Z67xhh3x2w8/kL0+9UnAyljcL5i/IMw9PzE59P9/k+M79dsjbM+fmuccmLfKcZx6emPfmzstuB3yxyfEdv7593l/wfiaMeaGqM8OKpmhla7/99ssZZ5yRE044ITvssEPWW2+91NbWpq6uLtOnT89jjz2Wiy66KPvtt1/JMVdKw84fmTOuOjynX3l47v31n/LZTTvm0NO/ntF3PZkXx7+WNu1aZ8PNO+X1l/+e2W/NTX19Q0b99+jse9SumTFtdl6dNC1fP2zndO+9SX50xNBFToKHf7XWWm1z3PF7Ztq0WRl557hstlnTTxunTp2Z3/zmiezbt1d++rMD89//PTprtF8tRx+zWx599MVMmPC3QpOzMrrx2ofzhV265cLLD85Nwx7OKi1b5Ijjds+bb8zOPb95svR4LGd+/V935Ce//0F+OPzk/M8v/5DuO26eb//n13Pt6b9O3bwFabP6atmoe+dMfXFaZv/97cx7Z35uOPvWHPvz72buzHcy+s7H0n3HzbP/wG/mzsvuyey/u2gC/LOigWTAgAFp0aJFfvKTn+TddxftYLZt2zYHHXRQTjzxxALTrdxG3/VUfnT4NfnOSV/NOdf3z9uz3s3dvxqd//7pXUmSrlt3zk9vPzE/P/nG3H/ro0mSGy+6Kw319dnv+D2y+ppt89L413LWIVfliYcXPd8E/tUOO3RN69arplOnNTP4skMWefynPxmVe+99Nt8/5aYc/709c+aZ38h779bl4Yeey1VXOcGYpWva1Fk56ajrctR/7JmB5+yb+vqGPPHYS7nqknvznot08C+e+sP4nPvti/Pds7+dc+74z8z421sZOvCm3H7JqCTJptt1yc8fPDs/O2JIfn/DBzd+HXHpXZk76530O3mffOXI3TNj6sz89zm3ZfhPf1PyT2EJ1Tc4h6QaahqWg4+2FyxYkIkTJ2b69Ol577330rp163Tq1CndunVLbe3Su5zsVzcYsNR+F3ycui1cFY5lY5W5zndg2WgY54aRLBv3LRxeeoSPNHxS79IjLNb+m67Y51svFzf4WHXVVdOjR4/SYwAAAMvYchFIAABgeeeyv9XhXQUAAIoRSAAAgGJUtgAAoAILG2pKj7BSsiEBAACKEUgAAIBiVLYAAKAC9T7LrwrvKgAAUIxAAgAAFKOyBQAAFVjY4LP8avCuAgAAxQgkAABAMSpbAABQgfq4MWI12JAAAADFCCQAAEAxKlsAAFABV9mqDu8qAABQjEACAAAUo7IFAAAVWOiz/KrwrgIAAMUIJAAAQDEqWwAAUIH6BjdGrAYbEgAAoBiBBAAAKEZlCwAAKuAqW9XhXQUAAIoRSAAAgGJUtgAAoAL1DT7LrwbvKgAAUIxAAgAAFKOyBQAAFVgYN0asBhsSAACgGIEEAAAoRmULAAAq4Cpb1eFdBQAAihFIAACAYlS2AACgAq6yVR02JAAAQDECCQAAUIzKFgAAVMBVtqrDuwoAABQjkAAAAMWobAEAQAUWqmxVhXcVAAAoRiABAACKUdkCAIAK1LsxYlXYkAAAAMUIJAAAQDEqWwAAUAFX2aoO7yoAAFCMQAIAABSjsgUAABWob3CVrWqwIQEAAIoRSAAAgGJUtgAAoAILfZZfFd5VAACgGIEEAAAoRmULAAAq4Cpb1WFDAgAAzdSCBQtyySWXZNddd822226b73znO3niiScaH584cWIOPvjg9OzZM7vuumuGDRu21GcQSAAAoJm68sorM2LEiJx//vkZOXJkNtlkkxx99NGZPn16Zs6cmcMPPzwbb7xxRowYkQEDBmTw4MEZMWLEUp1BZQsAACpQvxJ+lv/AAw9kn332yU477ZQkOf3003Pbbbflqaeeyssvv5za2tqcc845admyZbp27ZopU6Zk6NCh6dev31KbYeV7VwEAgIqsueaa+cMf/pDXXnstCxcuzPDhw1NbW5vPfe5zGTt2bHr37p2WLf+xw+jTp08mT56cGTNmLLUZbEgAAGAFtscee3zs4w888MBHPjZo0KCcfPLJ2WOPPbLKKqukRYsWGTx4cDbccMNMmzYtm2++eZOfX3fddZMkU6dOTYcOHZZ8+AgkAABQkYUr4VW2XnzxxbRv3z5XXHFFOnbsmNtuuy2nnXZabrzxxsybNy+1tbVNfr5Vq1ZJkvnz5y+1GQQSAABYgX3cBuTj/O1vf8upp56a66+/Pr169UqSbL311pk0aVIuv/zytG7dOnV1dU2e82EQadOmzZIN/U+cQwIAAM3QM888kwULFmTrrbducnybbbbJyy+/nE6dOuWNN95o8tiH33fs2HGpzSGQAABABeobapbLr09rvfXWS5I8//zzTY6/8MIL2WijjdK7d++MGzcuCxcubHxszJgx6dKly1I7fyQRSAAAoFnq0aNHevXqldNOOy1//vOf8/LLL+fSSy/NmDFjcswxx6Rfv36ZO3duBg0alEmTJuWOO+7IDTfckP79+y/VOZxDAgAAzVCLFi0yZMiQXHrppTnjjDMye/bsbL755rn++uvTs2fPJMm1116bCy64IH379s0666yTgQMHpm/fvkt1jpqGhoaGpfobl2Nf3WBA6RFoJuq2WL/0CDQTq8xdUHoEmomGceNLj0Azcd/C4aVH+EgDnjio9AiLdfl2N5UeYYmobAEAAMUIJAAAQDHOIQEAgAoszMp3Y8TlgQ0JAABQjEACAAAUo7IFAAAVWJKbEPLRbEgAAIBiBBIAAKAYlS0AAKhAfYPP8qvBuwoAABQjkAAAAMWobAEAQAXq3RixKmxIAACAYgQSAACgGJUtAACowEI3RqwKGxIAAKAYgQQAAChGZQsAACrgxojV4V0FAACKEUgAAIBimlVl6/3Xp5UegWaihX/WWEYaSg8A0IzUu8pWVdiQAAAAxQgkAABAMc2qsgUAAJ9WfVS2qsGGBAAAKEYgAQAAilHZAgCACrjKVnXYkAAAAMUIJAAAQDEqWwAAUIH6Bp/lV4N3FQAAKEYgAQAAilHZAgCACrjKVnXYkAAAAMUIJAAAQDEqWwAAUIH6qGxVgw0JAABQjEACAAAUo7IFAAAVcJWt6rAhAQAAihFIAACAYlS2AACgAipb1WFDAgAAFCOQAAAAxahsAQBABVS2qsOGBAAAKEYgAQAAilHZAgCACqhsVYcNCQAAUIxAAgAAFKOyBQAAFaiPylY12JAAAADFCCQAAEAxKlsAAFABV9mqDhsSAACgGIEEAAAoRmULAAAqoLJVHTYkAABAMQIJAABQjMoWAABUQGWrOmxIAACAYgQSAACgGJUtAACogMpWddiQAAAAxQgkAABAMSpbAABQgQaVraqwIQEAAIoRSAAAgGJUtgAAoAL1UdmqBhsSAACgGIEEAAAoRmULAAAq4MaI1WFDAgAAFCOQAAAAxahsAQBABdwYsTpsSAAAgGIEEgAAoBiVLQAAqICrbFWHDQkAAFCMQAIAABSjsgUAABVwla3qsCEBAACKEUgAAIBiVLYAAKACrrJVHTYkAABAMQIJAABQjMoWAABUoKGh9AQrJxsSAACgGIEEAAAoRmULAAAqUB9X2aoGGxIAAKAYgQQAAChGZQsAACrQ4MaIVWFDAgAAFCOQAAAAxahsAQBABepVtqrChgQAAChGIAEAAIpR2QIAgAo0NJSeYOVkQwIAABQjkAAAAMWobAEAQAXcGLE6bEgAAIBiBBIAAKAYlS0AAKiAylZ12JAAAADFCCQAAEAxKlsAAFCBepWtqrAhAQAAihFIAACAYlS2AACgAg0NpSdYOdmQAAAAxQgkAABAMSpbAABQATdGrA4bEgAAoBiBBAAAKKZ4ZeuQQw5JTU1l66///u//rvI0AACweCpb1VE8kOy44465/PLLs8kmm6RHjx6lxwEAAJah4oHk+OOPT5s2bXLZZZfl6quvTufOnUuPBAAALCPLxTkkhx12WLbbbrtceumlpUcBAIDFalhOv1Z0xTckH7rgggsyYcKE0mMAAADL0HITSDp27JiOHTuWHgMAAFiGlptAAgAAyzNX2aqO5eIcEgAAoHkSSAAAgGJUtgAAoBIrwyWtlkM2JAAAQDECCQAAUIzKFgAAVMBVtqrDhgQAAChGIAEAAIpR2QIAgAo0uMpWVdiQAAAAxQgkAABAMSpbAABQAVfZqg4bEgAAoBiBBAAAKEZlCwAAKqGyVRU2JAAAQDECCQAANGMjR47M1772tWy99dbZe++9c8899zQ+NnHixBx88MHp2bNndt111wwbNmypv75AAgAAFWhoWD6/lsRvfvObnHnmmdl///0zatSofO1rX8spp5ySJ598MjNnzszhhx+ejTfeOCNGjMiAAQMyePDgjBgxYum8of/LOSQAANAMNTQ0ZPDgwTn00ENz6KGHJkm+973v5Yknnshjjz2Wxx57LLW1tTnnnHPSsmXLdO3aNVOmTMnQoUPTr1+/pTaHDQkAADRDL730Uv72t7/l61//epPjw4YNS//+/TN27Nj07t07LVv+Y4fRp0+fTJ48OTNmzFhqc9iQAABAJZawHlUte+yxx8c+/sADDyz2+Msvv5wkeffdd3PkkUdmwoQJ6dy5c4477rjsvvvumTZtWjbffPMmz1l33XWTJFOnTk2HDh2WfPjYkAAAQLM0d+7cJMlpp52WffbZJ9ddd12++MUv5vjjj8+YMWMyb9681NbWNnlOq1atkiTz589fanPYkAAAwArsozYg/5dVV101SXLkkUemb9++SZLPfe5zmTBhQn75y1+mdevWqaura/KcD4NImzZtlmDipmxIAACgAg0NNcvl16fVqVOnJFmklrXpppvmtddeS6dOnfLGG280eezD7zt27PipX/dfCSQAANAMde/ePW3bts3TTz/d5PgLL7yQDTfcML179864ceOycOHCxsfGjBmTLl26LLXzRxKBBAAAmqXWrVvnqKOOyhVXXJFRo0bllVdeyZVXXplHHnkkhx9+ePr165e5c+dm0KBBmTRpUu64447ccMMN6d+//1KdwzkkAABQieX0KltL4vjjj89qq62WSy65JNOnT0/Xrl1z+eWXZ4cddkiSXHvttbngggvSt2/frLPOOhk4cGDj+SZLS01Dw5Le33HFsVeLb5ceAQCAj3Ff/W2lR/hIXW68sPQIizX54DNKj7BEVLYAAIBiVLYAAKACS3JFKz6aDQkAAFCMQAIAABSjsgUAAJVoNpeCWrZsSAAAgGIEEgAAoBiVLQAAqIirbFWDDQkAAFCMQAIAABSjsgUAAJVwla2qsCEBAACKEUgAAIBiVLYAAKASKltVYUMCAAAUI5AAAADFqGwBAEAlGtwYsRpsSAAAgGIEEgAAoBiVLQAAqECDq2xVhQ0JAABQjEACAAAUo7IFAACVUNmqChsSAACgGIEEAAAoRmULAAAq4caIVWFDAgAAFCOQAAAAxahsAQBABWpcZasqbEgAAIBiBBIAAKAYlS0AAKiEylZV2JAAAADFCCQAAEAxKlsAAFAJN0asChsSAACgGIEEAAAoRmULAAAq4SpbVWFDAgAAFCOQAAAAxahsAQBAJVS2qsKGBAAAKEYgAQAAilHZAgCASqhsVYUNCQAAUIxAAgAAFKOyBQAAlWioKT3BSsmGBAAAKEYgAQAAilHZAgCACtS4ylZV2JAAAADFCCQAAEAxKlsAAFAJla2qsCEBAACKEUgAAIBiBBIAAKAYgQQAACjmE53U/uabb+aKK67Iq6++ms985jP53Oc+l6222ipbbrllVltttWrNCAAArKQ+USA588wzM3r06Gy22WZ57bXX8rvf/S4NDQ1p0aJFNtlkk2y11VbZeuuts/XWW6dbt25ZddVVqzU3AAAsU26MWB2fKJA8+eSTOfXUU3PEEUckSd59992MHz8+zz77bJ599tk8/vjjufPOO5MktbW1eeaZZ5b+xAAAwErjEwWSVq1apXv37o3ft2nTJr17907v3r0bj82aNSvPPPNM/vKXvyy9KQEAgJXSJwoke+65ZyZMmJA+ffp85M+sueaa2XnnnbPzzjsv8XBL28Ldti89As3EKn8YV3oEAGBpa6gpPcFK6RNdZatfv3655557MmnSpGrNAwAANCOfaEPy7//+76mpqcm3v/3tfOUrX8mXvvSlbLnlltloo42qNR8AALAS+0SB5Pzzz8/EiRMzfvz43HPPPbnzzjtTU1OTtm3bpnv37tlqq60ycODAas0KAADluMpWVXyiQLLffvs1/u/6+vq8+OKLGT9+fP7yl79kwoQJueWWWwQSAACgYp8okPyzFi1aZLPNNstmm22WfffdN0nS0CA2AgAAlfvUgWRxampceQAAgJWUz96r4hNdZQsAAGBpEkgAAIBilmplCwAAVlY1KltVYUMCAAAUI5AAAADFqGwBAEAlVLaqwoYEAAAoRiABAACKUdkCAIBKqGxVhQ0JAABQjEACAAAUo7IFAAAVcGPE6rAhAQAAihFIAACAYlS2AACgEg01pSdYKdmQAAAAxQgkAABAMSpbAABQCVfZqgobEgAAoBiBBAAAKEZlCwAAKuDGiNVhQwIAABQjkAAAAMWobAEAQCVUtqrChgQAAChGIAEAAIpR2QIAgAq4ylZ12JAAAADFCCQAAEAxKlsAAFAJla2qsCEBAACKEUgAAIBiVLYAAKASKltVYUMCAAAUI5AAAADFqGwBAEAF3BixOmxIAACAYgQSAACgGIEEAAAoRiABAACKEUgAAIBiXGULAAAq4SpbVWFDAgAAFCOQAAAAxahsAQBABdwYsTpsSAAAgGIEEgAAoBiVLQAAqITKVlXYkAAAAMUIJAAAQDEqWwAAUAmVraqwIQEAAIoRSAAAgGJUtgAAoAJujFgdNiQAAEAxAgkAAFCMyhYAAFRCZasqbEgAAIBiBBIAAKAYlS0AAKiAq2xVhw0JAABQjEACAAAUo7IFAACVUNmqChsSAACgGIEEAAAoRmULAAAqobJVFTYkAABAMQIJAABQjMoWAABUwI0Rq8OGBAAAKEYgAQAAihFIAACgEg3L6ddSMHny5Gy77ba54447Go9NnDgxBx98cHr27Jldd901w4YNWzov9i8EEgAAaMYWLFiQ//zP/8y7777beGzmzJk5/PDDs/HGG2fEiBEZMGBABg8enBEjRiz113dSOwAANGOXX3552rZt2+TYrbfemtra2pxzzjlp2bJlunbtmilTpmTo0KHp16/fUn19GxIAAKhE6WpWFSpbjz/+eIYPH56f/OQnTY6PHTs2vXv3TsuW/9hf9OnTJ5MnT86MGTOW7EX/hQ0JAACswPbYY4+PffyBBx5Y7PE5c+Zk4MCB+cEPfpD11luvyWPTpk3L5ptv3uTYuuuumySZOnVqOnTosAQTN2VDAgAAzdA555yTnj175utf//oij82bNy+1tbVNjrVq1SpJMn/+/KU6hw0JAABUYHm9MeJHbUA+zsiRIzN27Nj87ne/W+zjrVu3Tl1dXZNjHwaRNm3afPIhP4ZAAgAAzcyIESMyY8aM7Lrrrk2On3322Rk2bFjWX3/9vPHGG00e+/D7jh07LtVZBBIAAGhmLrroosybN6/JsX/7t3/LCSeckK997Wu56667csstt2ThwoVZZZVVkiRjxoxJly5dlur5I4lzSAAAoDKlr6a1FK+y1bFjx2y00UZNvpKkQ4cO2WCDDdKvX7/MnTs3gwYNyqRJk3LHHXfkhhtuSP/+/T/dC34MgQQAAGiiQ4cOufbaazN58uT07ds3v/jFLzJw4MD07dt3qb+WyhYAAJDnn3++yfc9evTI8OHDq/66AgkAAFRgeb3K1opOZQsAAChGIAEAAIpR2QIAgEqobFVF8Q3J5MmTc/nll+f888/PQw89tMjjc+fOzRlnnFFgMgAAoNqKBpJx48alb9++GTVqVB5++OEce+yxGTBgQJPb1M+bNy8jR44sNyQAAFA1RQPJz3/+8+y3336599578/vf/z4XX3xxHnnkkRx77LFZsGBBydEAAKCp0jdAXIo3RlyeFA0kzz//fA4++ODG77/61a9m6NChefLJJzNw4MCCkwEAAMtC0UDSrl27zJw5s8mx7bffPj/72c9y77335sILLyw0GQAAsCwUDSS77LJLzj333Dz99NNNKlp77rlnzjzzzNxwww0599xzC04IAABUU9FA8v3vfz9rrbVWDjjggIwZM6bJYwcffHDOOuusPPjgg4WmAwCAf6hZTr9WdEXvQ7LGGmvkuuuuyyuvvJK11lprkce/853vZMcdd8zvf//7AtMBAADVtlzcGHHDDTf8yMe6dOmS/v37L8NpAACAZWW5CCQAALDcWwkusbs8Kn6ndgAAoPkSSAAAgGJUtgAAoAI1KltVYUMCAAAUI5AAAADFqGwBAEAlVLaqwoYEAAAoRiABAACKUdkCAIBKqGxVhQ0JAABQjEACAAAUo7IFAAAVcGPE6rAhAQAAihFIAACAYlS2AACgEipbVWFDAgAAFCOQAAAAxahsAQBABVxlqzpsSAAAgGIEEgAAoBiVLQAAqITKVlXYkAAAAMUIJAAAQDEqWwAAUAFX2aoOGxIAAKAYgQQAAChGZQsAACqhslUVNiQAAEAxAgkAAFCMyhYAAFRCZasqbEgAAIBiBBIAAKAYlS0AAKiAGyNWhw0JAABQjEACAAAUo7IFAACVUNmqChsSAACgGIEEAAAoRmULAAAqUNOgs1UNNiQAAEAxAgkAAFCMyhYAAFRCY6sqbEgAAIBiBBIAAKAYlS0AAKhAjcpWVdiQAAAAxQgkAABAMSpbAABQCZWtqrAhAQAAihFIAACAYlS2AACgAq6yVR02JAAAQDECCQAAUIzKFgAAVEJlqypsSAAAgGIEEgAAoBiVLQAAqICrbFWHDQkAAFCMQAIAABSjsgUAAJVQ2aoKGxIAAKAYgQQAAChGZQsAACrgKlvVYUMCAAAUI5AAAADFqGwBAEAlGnS2qsGGBAAAKEYgAQAAilHZAgCACrjKVnXYkAAAAMUIJAAAQDEqWwAAUAmVraqwIQEAAIoRSAAAgGJUtgAAoAI19aUnWDnZkAAAAMUIJAAAQDEqWwAAUAlX2aoKGxIAAKAYgQQAAChGZQsAACpQo7JVFTYkAABAMQIJAABQjMoWAABUokFnqxpsSAAAgGIEEgAAoBiVLQAAqICrbFWHDQkAAFCMQAIAABTTrCpbHS94qfQINBOTrtmx9Ag0E9eec0npEWgmtq5drfQIUJ7KVlXYkAAAAMUIJAAAQDHNqrIFAACflqtsVYcNCQAAUIxAAgAAFKOyBQAAlWjQ2aoGGxIAAKAYgQQAAChGZQsAACrgKlvVYUMCAAAUI5AAAADFqGwBAEAlVLaqwoYEAAAoRiABAACKUdkCAIAKuMpWddiQAAAAxQgkAABAMSpbAABQiXqdrWqwIQEAAIoRSAAAgGJUtgAAoBIaW1VhQwIAABQjkAAAAMWobAEAQAXcGLE6bEgAAIBiBBIAAKAYlS0AAKhEg85WNdiQAAAAxQgkAABAMSpbAABQAVfZqg4bEgAAoBiBBAAAKEZlCwAAKqGyVRU2JAAAQDECCQAAUIxAAgAAFahpaFguv5bErFmzctZZZ2XnnXfOdtttlwMPPDBjx45tfHzixIk5+OCD07Nnz+y6664ZNmzYkr6NixBIAACgmTrllFPy9NNP5+KLL87tt9+eLbfcMkceeWRefPHFzJw5M4cffng23njjjBgxIgMGDMjgwYMzYsSIpTqDk9oBAKAZmjJlSh555JHcfPPN2W677ZIkgwYNysMPP5xRo0aldevWqa2tzTnnnJOWLVuma9eumTJlSoYOHZp+/fottTlsSAAAoBL1y+nXp7TWWmvlmmuuyVZbbdV4rKamJg0NDZk9e3bGjh2b3r17p2XLf+ww+vTpk8mTJ2fGjBmf/oX/hUACAADNUPv27bPLLruktra28dg999yTV155JTvttFOmTZuWTp06NXnOuuuumySZOnXqUptDZQsAAFZge+yxx8c+/sADD1T0e8aNG5czzzwze+yxR3bfffdceOGFTcJKkrRq1SpJMn/+/E837GIIJAAAUIElvaJV1dQs+a+4//7785//+Z/ZZpttcvHFFydJWrdunbq6uiY/92EQadOmzZK/6P8SSAAAYAVW6Qbko9x444254IILstdee+Wiiy5q3Ip06tQpb7zxRpOf/fD7jh07LtFr/jPnkAAAQDP161//Ouedd14OOuigXHrppU0qWr179864ceOycOHCxmNjxoxJly5d0qFDh6U2g0ACAACVaFhOvz6lyZMn57/+67+y1157pX///pkxY0befPPNvPnmm3n77bfTr1+/zJ07N4MGDcqkSZNyxx135IYbbkj//v0//YsuhsoWAAA0Q/fee28WLFiQ++67L/fdd1+Tx/r27Zsf//jHufbaa3PBBRekb9++WWeddTJw4MD07dt3qc4hkAAAQDN07LHH5thjj/3Yn+nRo0eGDx9e1TkEEgAAqMTyepWtFZxzSAAAgGIEEgAAoBiVLQAAqECNxlZV2JAAAADFCCQAAEAxKlsAAFAJV9mqChsSAACgGIEEAAAoRmULAAAqUFNfeoKVkw0JAABQjEACAAAUo7IFAACVcJWtqrAhAQAAihFIAACAYlS2AACgEhpbVWFDAgAAFCOQAAAAxahsAQBABWpcZasqbEgAAIBiBBIAAKAYlS0AAKiEylZV2JAAAADFCCQAAEAxKlsAAFCJ+tIDrJxsSAAAgGIEEgAAoBiVLQAAqIAbI1aHDQkAAFCMQAIAABSjsgUAAJVQ2aoKGxIAAKAYgQQAAChGZQsAACqhslUVNiQAAEAxAgkAAFCMyhYAAFSivvQAKycbEgAAoBiBBAAAKEZlCwAAKlDjKltVYUMCAAAUI5AAAADFqGwBAEAlVLaqwoYEAAAoRiABAACKKV7Zmj9/fv76179m0003TevWrTNx4sTceOONmT59ejbbbLMceuih6dSpU+kxAQBo7lS2qqLohuTFF1/Mnnvumf322y9f+9rX8qc//SkHHnhgnn766bRt2zb3339/vvnNb+bFF18sOSYAAFAlRQPJT3/602y77bYZOXJktt9++xx33HH5+te/nt/97ncZPHhw7rnnnnzxi1/MhRdeWHJMAACgSooGksceeywnnXRSunXrltNOOy3z58/PgQcemJqamiRJy5Ytc+yxx2bcuHElxwQAgA8qW8vj1wquaCBp3bp15s2blyT5zGc+k3//939Pq1atmvzMnDlzsvrqq5cYDwAAqLKigWSnnXbKeeed13iOyLnnnpuuXbsmSRoaGvLoo4/mrLPOyp577llyTAAAoEqKBpIzzjgjCxcuzJAhQxZ57O67786hhx6aDTbYIKecckqB6QAA4J/UL6dfK7iil/1de+21c+utt2bWrFmLPLbjjjtm5MiR6dat27IfDAAAWCaK34ckSdZcc81Fjq299tpZe+21l/0wAADAMrNcBBIAAFje1awEV7RaHhU9hwQAAGjeBBIAAKAYlS0AAKiEylZV2JAAAADFCCQAAEAxKlsAAFCJepWtarAhAQAAihFIAACAYlS2AACgEq6yVRU2JAAAQDECCQAAUIzKFgAAVEJlqypsSAAAgGIEEgAAoBiVLQAAqITKVlXYkAAAAMUIJAAAQDEqWwAAUIl6la1qsCEBAACKEUgAAIBiVLYAAKASDfWlJ1gp2ZAAAADFCCQAAEAxKlsAAFAJN0asChsSAACgGIEEAAAoRmULAAAq4caIVWFDAgAAFCOQAAAAxahsAQBAJVxlqypsSAAAgGIEEgAAoBiVLQAAqITKVlXYkAAAAMUIJAAAQDEqWwAAUAmVraqwIQEAAIoRSAAAgGJUtgAAoBL19aUnWCnZkAAAAMUIJAAAQDEqWwAAUAlX2aoKGxIAAKAYgQQAAChGZQsAACqhslUVNiQAAEAxAgkAAFCMyhYAAFSiXmWrGmxIAACAYgQSAACgGJUtAACoQENDfekRVko2JAAAQDECCQAAUIzKFgAAVMJVtqrChgQAAChGIAEAAIpR2QIAgEo0qGxVgw0JAABQjEACAAAUo7IFAACVqHdjxGqwIQEAAIoRSAAAgGJUtgAAoBKuslUVNiQAAEAxAgkAAFCMyhYAAFSgwVW2qsKGBAAAKEYgAQAAilHZAgCASrjKVlXYkAAAAMUIJAAAQDEqWwAAUIl6la1qsCEBAACKEUgAAIBiVLYAAKASDW6MWA02JAAAQDECCQAAUIzKFgAAVKDBVbaqwoYEAAAoRiABAACKUdkCAIBKuMpWVdiQAAAAxQgkAABAMSpbAABQAVfZqg4bEgAAoBiBBAAAKEZlCwAAKuEqW1VhQwIAABQjkAAAAMXUNDQ0uFwAAABQhA0JAABQjEACAAAUI5AAAADFCCQAAEAxAgkAAFCMQAIAABQjkAAAAMUIJAAAQDECCQAAUIxAAgAAFCOQAAAAxQgkAABAMQIJAABQjEDCYtXX1+eyyy7Ll770pWyzzTY54ogjMmXKlNJjsZIbMmRIDjnkkNJjsBKaNWtWzjrrrOy8887ZbrvtcuCBB2bs2LGlx2IlNWPGjJx66qnp06dPtt122xxzzDGZNGlS6bFguSWQsFhDhgzJLbfckvPPPz/Dhw9PTU1Njj766NTV1ZUejZXU9ddfn8suu6z0GKykTjnllDz99NO5+OKLc/vtt2fLLbfMkUcemRdffLH0aKyEjjvuuLz66qsZOnRobr/99rRu3TqHHXZY3nvvvdKjwXJJIGERdXV1ue666zJgwIDssssu6datWy655JJMnz499913X+nxWMlMnz49Rx11VAYPHpwuXbqUHoeV0JQpU/LII4/k7LPPTq9evbLJJptk0KBB6dixY0aNGlV6PFYyM2fOTOfOnXPeeedl6623TteuXXP88cfnzTffzF//+tfS48FySSBhEc8991zeeeed9OnTp/FY+/bt07179zz++OMFJ2NlNH78+Kyxxhr57W9/m2222ab0OKyE1lprrVxzzTXZaqutGo/V1NSkoaEhs2fPLjgZK6O11lorF198cTbbbLMkyd///vcMGzYsnTp1yqabblp4Olg+tSw9AMufadOmJUnWW2+9JsfXXXfdvP766yVGYiW2++67Z/fddy89Biux9u3bZ5dddmly7J577skrr7ySnXbaqdBUNAc//OEPc+utt6a2tjZXXnll2rRpU3okWC7ZkLCIDzuutbW1TY63atUq8+fPLzESwFIzbty4nHnmmdljjz2EYarq0EMPzYgRI/KNb3wj3/ve9zJ+/PjSI8FySSBhEa1bt06SRU5gnz9/flZbbbUSIwEsFffff3+OPPLI9OjRIxdffHHpcVjJbbrpptlqq61y3nnnpXPnzrnxxhtLjwTLJYGERXxY1XrjjTeaHH/jjTfSqVOnEiMBLLEbb7wxAwYMyM4775yhQ4c2fvgCS9OMGTMyatSoLFy4sPFYixYt0rVr10X+fxX4gEDCIrp165Z27drl0UcfbTw2Z86cTJgwIb169So4GcCn8+tf/zrnnXdeDjrooFx66aWLVFJhaXnjjTfy/e9/P4899ljjsQULFmTChAnp2rVrwclg+eWkdhZRW1ubgw8+OBdddFHWXnvtbLDBBvnZz36WTp06Za+99io9HsAnMnny5PzXf/1X9tprr/Tv3z8zZsxofKx169ZZffXVC07HyqZbt27Zaaed8qMf/Sjnn39+2rdvn6uuuipz5szJYYcdVno8WC4JJCzWCSeckPfffz8/+MEPMm/evPTu3TvDhg3zqSKwwrn33nuzYMGC3HfffYvcS6lv37758Y9/XGgyVkY1NTW59NJL8/Of/zwnnXRS3n777fTq1Ss33XRT1l9//dLjwXKppqGhoaH0EAAAQPPkHBIAAKAYgQQAAChGIAEAAIoRSAAAgGIEEgAAoBiBBAAAKEYgAQAAihFIAACAYgQSgBXM/Pnz071792y77bY577zzSo8DAEtEIAFYwdTU1OSGG25Ijx49cuONN2by5MmlRwKAT00gAVjB1NbWpnfv3jnqqKOSJOPHjy88EQB8egIJwApqk002SZJMnDix8CQA8OkJJAArqKFDhyZJnnvuucKTAMCnJ5AArIBGjx6dm2++OWussUYmTJhQehwA+NQEEoAVzJw5c3LmmWdmjz32yIEHHpi33nor06dPLz0WAHwqAgnACuZHP/pR3n///Zx//vnp3r17ErUtAFZcAgnACuR//ud/MmrUqFxwwQVZe+21GwOJE9sBWFEJJAAriDfffDNnn3129t9//+y2225Jks9+9rNp376980gAWGEJJAAriB/+8IdZY401cvrppzc5/rnPfU5lC4AVlkACsAK47bbb8vDDD+enP/1p2rRp0+Sx7t2755VXXsncuXMLTQcAn15NQ0NDQ+khAACA5smGBAAAKEYgAQAAihFIAACAYgQSAACgGIEEAAAoRiABAACKEUgAAIBiBBIAAKAYgQQAAChGIAEAAIoRSAAAgGIEEgAAoJj/D8vJXNNZv2LAAAAAAElFTkSuQmCC",
       "text/plain": [
        "<Figure size 1000x1000 with 2 Axes>"
       ]
@@ -2488,10 +2476,10 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[15.97637626  0.59409338  5.21563039 10.48408912]\n",
-      " [ 0.11387677  0.12790715  0.07085955  0.0876202 ]\n",
-      " [ 0.21155534  6.53228442  4.27904283  0.51498308]\n",
-      " [17.80782971 42.40085725 10.56507707 15.74791571]]\n"
+      "[[6.90732417e+00 1.97094475e+01 1.57990613e+01 6.05984191e-01]\n",
+      " [2.08450110e-01 1.86438494e-01 7.06379681e-02 2.67760777e-01]\n",
+      " [2.03157147e+01 3.53757381e-01 1.66436883e-01 1.76975172e-01]\n",
+      " [7.53767420e+01 3.13860106e+01 9.45323854e+01 1.01940852e+02]]\n"
      ]
     }
    ],