Repository: jrenaud90/CyRK (language: python)

Issue:
Unable to import cyrk_ode
I'm excited to try out the cython compiled ODE solver but having difficulty with what appears to be binary compatibility with numpy.

Error:
```shell
ValueError                                Traceback (most recent call last)
Input In [111], in <cell line: 2>()
      1 from numba import njit
----> 2 from CyRK import cyrk_ode

File ~\miniconda3\envs\arc\lib\site-packages\CyRK\__init__.py:9, in <module>
      6 from .nb.nbrk import nbrk_ode
      8 # Import cython solver
----> 9 from CyRK.cy.cyrk import cyrk_ode

File ~\miniconda3\envs\arc\lib\site-packages\CyRK\cy\_cyrk.pyx:1, in init CyRK.cy.cyrk()

ValueError: numpy.ndarray size changed, may indicate binary incompatibility. Expected 96 from C header, got 88 from PyObject
```

Relevant installed package versions:
- python=3.9.12
- numba=0.55.1
- numpy=1.21.5
- cython=0.29.32
- cyrk=0.1.1

Everything but cyrk is installed from conda standard channel.


Discussion / hints:
Thanks for the detailed report (and apologies on the delay, I missed this notification)! I am able to reproduce this issue. Looking into it.

Fix patch:
diff --git a/.github/workflows/python-publish.yml b/.github/workflows/python-publish.yml
index 44515f5..e0b469e 100644
--- a/.github/workflows/python-publish.yml
+++ b/.github/workflows/python-publish.yml
@@ -18,7 +18,6 @@ jobs:
     strategy:
       matrix:
         python-version:
-          - "3.7"
           - "3.8"
           - "3.9"
           - "3.10"
@@ -47,7 +46,6 @@ jobs:
     strategy:
       matrix:
         python-version:
-          - "3.7"
           - "3.8"
           - "3.9"
           - "3.10"
diff --git a/Benchmarks/CyRK - SciPy Comparison.ipynb b/Benchmarks/CyRK - SciPy Comparison.ipynb
index 5a6f96c..10317ea 100644
--- a/Benchmarks/CyRK - SciPy Comparison.ipynb
+++ b/Benchmarks/CyRK - SciPy Comparison.ipynb
@@ -18,7 +18,8 @@
     "import numpy as np\n",
     "import matplotlib.pyplot as plt\n",
     "from scipy.integrate import solve_ivp\n",
-    "from numba import njit"
+    "from numba import njit\n",
+    "plt.style.use('dark_background')"
    ]
   },
   {
@@ -100,13 +101,13 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "C:\\ProgramData\\Anaconda3\\envs\\cyrk\\lib\\site-packages\\matplotlib\\cbook\\__init__.py:1298: ComplexWarning: Casting complex values to real discards the imaginary part\n",
+      "C:\\ProgramData\\Anaconda3\\envs\\cyrk310a\\lib\\site-packages\\matplotlib\\cbook\\__init__.py:1369: ComplexWarning: Casting complex values to real discards the imaginary part\n",
       "  return np.asarray(x, float)\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -124,10 +125,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 4,
    "id": "86846611",
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\ProgramData\\Anaconda3\\envs\\cyrk310a\\lib\\site-packages\\CyRK\\nb\\nbrk.py:330: NumbaPerformanceWarning: \u001B[1m\u001B[1m\u001B[1mnp.dot() is faster on contiguous arrays, called on (array(complex128, 2d, A), array(complex128, 1d, C))\u001B[0m\u001B[0m\u001B[0m\n",
+      "  err5 = np.dot(K.T, E5) / scale\n",
+      "C:\\ProgramData\\Anaconda3\\envs\\cyrk310a\\lib\\site-packages\\CyRK\\nb\\nbrk.py:330: NumbaPerformanceWarning: \u001B[1m\u001B[1mnp.dot() is faster on contiguous arrays, called on (array(complex128, 2d, A), array(complex128, 1d, C))\u001B[0m\u001B[0m\n",
+      "  err5 = np.dot(K.T, E5) / scale\n"
+     ]
+    },
     {
      "name": "stdout",
      "output_type": "stream",
@@ -139,13 +150,13 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "C:\\ProgramData\\Anaconda3\\envs\\cyrk\\lib\\site-packages\\matplotlib\\cbook\\__init__.py:1298: ComplexWarning: Casting complex values to real discards the imaginary part\n",
+      "C:\\ProgramData\\Anaconda3\\envs\\cyrk310a\\lib\\site-packages\\matplotlib\\cbook\\__init__.py:1369: ComplexWarning: Casting complex values to real discards the imaginary part\n",
       "  return np.asarray(x, float)\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -165,7 +176,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 5,
    "id": "7322927e",
    "metadata": {},
    "outputs": [
@@ -180,13 +191,13 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "C:\\ProgramData\\Anaconda3\\envs\\cyrk\\lib\\site-packages\\matplotlib\\cbook\\__init__.py:1298: ComplexWarning: Casting complex values to real discards the imaginary part\n",
+      "C:\\ProgramData\\Anaconda3\\envs\\cyrk310a\\lib\\site-packages\\matplotlib\\cbook\\__init__.py:1369: ComplexWarning: Casting complex values to real discards the imaginary part\n",
       "  return np.asarray(x, float)\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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r1q1Vr6nE9ddfT2dnZ9/R1tYW7Y/KBLbRqtTBgxhxKK8Rd9YN5XhfOng3Za0fMjhwI7bDUG9KK7sPEM2Ew/Paa69xwgkncOqpp/Jv//ZvPPDAAxx11FF9n/dft9/Q0FB3LX+9a2666SZaWlr6jmImOVfKS+jBjOjL1lDFiBvqRTRED43oYbC1GE75tnAT22HovyTdRhweT+zZs4c333yT5cuXc8MNN7BixQr+/u//nvXr1wMMiNSMHz++L+qzfv16hg4dypgxY6peU4menh62b9/uOopHpQgPyCheRmnSwfdH9HBTqa1IErc4PFB/SisTbkVFMlmyhoYGhg4dyttvv017eztz5szp+2zIkCHMmjWLpUuXArB8+XJ6enpc17S2tjJ9+vS+a8pLpQgPlHfuWVZpGWQKx001PaStGPZi9qEpkx5DHa+THyzZMxWNjVmJqlWb0qr8eImosH9/mJ2aU1fwm9/8Jo8//jhr166lubmZiy66iNmzZ/ftxbNgwQJuuOEG3njjDd544w1uuOEGurq6+OEPfwhAZ2cn9957L7feeiubNm1i8+bN3HLLLaxcuZKnnnoqzZ+WAWTU6qbWqLUF55boxada3ZAO3k1Z20qt+jGScukx3PE6+QjPpk2bADjyyCN58803Y/1b3khnSuvII48EYOPG4I+8Sd3hmTBhAt///veZOHEi27Zt4w9/+ANnn312n7Ny8803M3z4cO6++27Gjh3LCy+8wFlnndX3tFWAa665ht7eXh566CGGDx/OokWLuOyyy9i3r/9/SNmQUbyhATNSq5bEPQp32L7ISAfvRlZpuallO1opV/2w68ZeoNfxfjJ1Y+fOnSxevJgLLrgAgFdffZXe3t4634qTscAEtOPbXeH9EUQ5cGxsbOTII4/kggsuYPHixXR1BX+OWOoOz9/8zd/UvebGG2/kxhtvrPp5d3c38+bNY968eVEWrQBIp2ZwhqWdenSjE7mb0HqUxeGp5wxLB68pY1sBsR1O6qUGjEB3pfE5Iffddx8AF154YWx/wzvNwH7oXbg3ON4fCYxD15nq+bNBWbx4cZ8OQUnd4RHiRDo1gzMsXUmPcWgjXsTtCSohHZob0cON6GGotvijfxL3lthKoJTie9/7Hj/60Y8YN24cDQ0N9b8UG58DbgB+Afwvx/sfBO4BVgJXRvbXlFJs3LgxVGTHRhyeQiN5GgZbi17MXLON0+EpC9KhuRE93EjEy1CtbuxB6zMcrUd8Do9NV1cX7777bux/pzY9aE06gXcc779tvd/S7/3skMlVWkJUiNEyVNMCyh3xqrUqKc1RZNLIKi03ktNkqDalBeW2pfkbHIjDU2hk1GqopgWUs1OrVzdAJ3GXBWkrbiQ6bKjWwUM560c1BzD7WojDU2gkh8fgJcKT3YYaPdWM1m50qB7KqYdENGAIZmlx/jq16Kk1WCpj/ajXVkaS1d2WxeEpNDJKM3gxWmXSw8uotUxGXKZ/Dc4Hy0rES6a0+uM1iTt7iMNTaEZYZzHiEuHpjziAbmRKy+B0eLr7fVZGPWoNDso8eOxvS/c43hOHR0iUJsdrMeISlu5PLQewzEa82qi1mfIkccvgwI0MDtzkN6dJHJ7C4iUsLR28JtuNNB7EiLupN6U1CJ2bUAZkcOBGprTc5HcBiDg8hcW50V5Pv8/K3Ej7h+gh6400HsThcVNNj12YHXTLoofUDTf5jWjEQ34dQHF4Ckul50bZlLGDr6VHthtpPEin5kb0MEjOihupG27y6wCKw1NY7A6+UkTDrpRNuJ8xVWS86JHNRhoPMm3hRvQwyODAjdQNN/m1peLwFBY7ablSpdzheJ3Nihk9+W2k8WDr0X+6E0SP/pRND2krbqRuuMlv/RCHp7DUqpT7cK8+KQP5baTxUMshLtu0xRDHa9HDW1spUxK3tBU3tepHtvUQh6ew1KqUkPWKGT219LAjXmVx/sCb0SqLHs5pXdHDdPCVIhq7MA/fLYse0lbceNEjm4+lEYensHh1eMrSUGuFpcumBYgRdyIOj5t6tqNsAwRpK27ya0vF4Sks4vC48RKWHgY0JlOc1BEjbrC12AOoCp+XVY96tiObo/jokbbixostzaYe4vAUllpeOMgozYnzGTBlM+KV6kdZ64a0FY0MltxIW3GTXwdQHJ7CIqM0N7X06MUsOc1mQ40eL6M0qRuasupRzQHMdqcWPV7aShPu5PciIw6PkDlqNVLIesWMHhm1usmv0YoeaStuRA83XqPDZdCjAePY5S/iJQ5PYZEO3o0kYroRh8cgbcWNtBU3tfTYS9afEB4tzodS5y86LA5PYREj7kbC9G7yu7Q0eqRuuBHb4Ub0MOR7RaM4PIVFGqkbr2H6snTytfZasbUoy+Zy0lbcSE6TG3GIDU6HR5alC5lBjLgb0cMw2Dqgsh5d6N24oRx6yBSOm1rOMJSrrUD9wVKZ6ocfO9oQf3F8Ig5PYZGltm7E4THUC0tDueqHRP/cSFtxIxEvg1dnGLIYHRaHp7CIEXcjRtzgxeEpU/2QuuFG9HAjehjqabGbLD96RByewiKN1I1MWxhsLfZhjFN/ylQ/JEfDjdgON6KHoZ4WkOXBkjg8hUUaqRvp1Az1on9QLj28tpWhlGNzOZkOdyO2w+DH4cmeHuLwFBZxeNzIZmqGfBut6PEa/YNy6CHT4W7EdhjqOX+QZT3E4Sks4vC4kcRDgzg8burpUbZHj4jtcDPMOst0eN6jw+LwFBavYekydPAgRtyJF4enjEbcy6i1DO1F2orBOYUpeuR9sCQOT2HxarRkczlNdhtp9PgJS0sHrylj/ZC2Iisa+5PvwZI4PIWlXuhxJ2ZzuTI1VEnEzHtYOnrE4XHjZ+PB7G0uFy31dhaGctWNfA+WxOEpLPn2xKNlENBovZZRq3Tw/RE93PhJ4i56dNjWohczQOxPmepGvgdL4vAUFjHihnpP+IXyaAFSN/ojeripp8cuzP5N2RvFR0u+O/joyXdbEYensOS7YkaLzMO7kbrhxkvSclmioSD1w4lEyt3ku26Iw1NY8l0xo8Xp8Oypco2txTDM9FdRyfdeGtGT791jo0fqh0HsqJt86yEOT2HxYrTKMjKxtdhd45oybS7nJUxfpm0L8m3Eo0emcQziDLvJdzRUHJ7C4sdoFb2henH+yrS5nHTwbkQPN6KHwU+0qwl3vmARybcDKA5PYZFRmsGLFlAePaRDcyN6uJG8FYOfaCgUX498txVxeAqLn91js1cxo0UcHjdSN9yIHoZBwGDrdT73WokWLx38XqDLel30+pHv/K7UHZ7rrruOF198kc7OTjo6OnjkkUc4/PDDXdfcd999KKVcx3PPPee6pqmpiTvuuIMNGzawY8cOHn30USZPnpzkT8kYYsQNXrSA8unhdZRW9M3l/Iziy1I3IK+j+GjxOlgqW/3IZ91I3eGZNWsWd911F6eeeipz5syhsbGRhQsXMmLECNd1jz/+OK2trX3HOeec4/p8wYIFzJ07l4suuoiZM2cyatQoHnvsMQYNSv0npoQ4PAa/Dk/RR61+6gYUf3M5eZaWwenwiO2QwVJ/8t2vpL7+9qMf/ajr35dffjkbNmzgpJNO4tlnn+17v7u7m46Ojor3aGlp4YorruCzn/0sixYtAuAzn/kMa9eu5cwzz2ThwoUDvtPU1MTQoWa5cnNz9v5zwiGrtAxitNx40cPeXG4wupPfUePavJNvIx4tToen2hYOUD49ZLCk8bNKaxQ6OqxiLZEfMhf+GD16NACbN292vT979mw6Ojp47bXXuOeeezjggAP6PjvppJNoampyOTbt7e2sWrWK0047reLfuf766+ns7Ow72traYvg1aeF3Hl6MlkYcQDeih0HaihvRw43oYXBGh7PlAGbO4bntttt49tlnWb16dd97jz/+OJdccglnnHEGX/7yl5kxYwZPP/00TU1a/NbWVrq7u9m6davrXh0dHbS2tlb8OzfddBMtLS19R7HyffyGpbNVKaNHjJYb0cONODwGL5FhEGe4P2WpH1702I3e5gOy1rekPqXl5Dvf+Q7HHXccM2fOdL3/0EMP9b1evXo1y5Yt45133uFjH/sYjzzySNX7NTQ0oFTlcFpPTw89PfUqcV6ReXg3YrTciB5uxOExyBSOG2krbvzoMRatR3usJfJDZiI8d9xxB+eeey4f+tCH6k4vrV+/nnfeeYfDDjus799Dhw5lzJgxruvGjx9fNe+n2Mg8vBsxWm5EDzd+8hKKvrmc1A03Mv3rJt/1IxMOz5133sn555/PGWecwZo1a+pev99++3HggQfS3q49x+XLl9PT08OcOXP6rmltbWX69OksXbo0rmJnGLtS7qF2wlg2K2X0yKjVTb6NVvT4zUsosh5SN9yIHm7yrUfqU1p33XUXF198Meeddx7bt29nwoQJAGzbto3du3czcuRIvva1r/Gzn/2M9vZ2pk6dyre+9S02btzYN53V2dnJvffey6233sqmTZvYvHkzt9xyCytXruSpp55K8+elRL4rZfSIHm7EAXTjRY+96JVrw9F6bIq7UCkhbcWNtBU3+d6XKHWH5wtf+AIAS5Yscb1/2WWX8cADD7B3716OPfZYPve5zzFmzBja29t55plnuPDCC9mxwyyVveaaa+jt7eWhhx5i+PDhLFq0iMsuu4x9+/Yl+nuyQZAwbLaWD0aLhKXdSGKqGz+d2nCKrYc4PG5EDzf51iN1h6ehofYurrt37+bss8+ue5/u7m7mzZvHvHnzoipajvH7KAWAEcDOeIqTOvlupNEjerjxo8d4iq2HDA7cSFtxk++IVyZyeISo8Vopu9Cheih2QxWj5Ub0MAxxvBY9gnVoRX70iLQVN/nWQxyeQuK1UkI5Rmpep3Cy2UijJ99GK1q8buEA5WgrfusGFPvRI9JW3ORbD3F4CokfhyebFTNa8t1Io0f0MPhxeMqkR73pcOfmcmXQQ5xhTb5thzg8hUQcHjf5nneOHtHDYGuxDzO9W40y6SG2QyNtxU2+HUBxeAqJTGm58dtIh+LO7Sga+TZa0SIdvBvRw02+IxrRk289xOEpJGK03ATJSxA9pG70R/RwIw6xoQx1A/Ie8RKHp5AEMeLZqpjR4lUPe3M5KLbhEiNuEIfHjejhxm9bGYJZJFFE8m07xOEpJGK03Igebvzu01QGLSSioZHBkhu/079Q3PoxCLN1nzg8QmaQDt6N6OEm36O0aJG64Ub0cONVj33ofc2guHrkf88qcXgKiRgtNzJqdSObyxm87tEEUjf6I7bDTdHrR/73rBKHp5CI0XIj0xZuZHM5g9fpPZC20h/Rw03R9XA6PHvqXJtNLcThKSTSwbsRo2XwMw+/m+I/ekTqhhuxHW6kfhhsLfZQ/0HTthYjyZKbkZ2SCBEiYXo3YrQMfubhofh6SN1wI3q4ET0MQbSALEWHxeEpJNJI3YgeBj/z8FAePSSioZGcFTdiOwx+BtLdmGmv7OghDk8hkUbqRvQw+JmHh/LoIXVDI3q4EYfY4EcLyGL9EIenkIjRciN6GPzMw0PxR/FB6sYQ3I5jkZC24kYiXgZxeIRMIkbLTZBRmhgtTdHrR5C6AaIHFL9uQLB8yKLq4dd2ZC/iJQ5PIZEwrBsx4ob8G61o8aPHXoq/uZzYDjdiOwxBB0vZGTyKw1NIgoZhi7q5nBgtg0R43IgebqStuJEIjyH/bUUcnkKS/+WD0SKbyxnyb7SiRSJebmRLC0Oj47U4PEWwHeLwFBI/HfwuZHM5J9lrpNGSf6MVLaKHG4kOG/xu4VB0Zzj/bUUcnkKS/4oZLeLwGPI/Dx8tooeboNHhIuohe1a5yX+/Ig5PIcl/xYwWWaVlkLrhRvRw40ePbG4uFx1Oh6fXw/VlcYa9zBxAFiNe4vAUEjHihkZMNZdRmr8cDSi+HtJW3EhOk8FvBy91w032HEBxeAqJGC1D0LB0U7/vFgWpG27E4XEjehhECzf510McnkKS/4oZHUETD6HYekjd0IgD6Cb/o/jokLbiJv96iMNTSMRoGfzOwxd9c7n8G61oET3ciB6GoM5wIzAs+uKkTv7rhjg8hST/FTM6/M7DQzn0EGdYI3q4kbwVQ1CHB0QPyGLdEIenkOS/YkaHXy2g2NMWUjfciB5uRA+DXy32ATut10V0iPM//SsOTyERo2UI4vAUeRQfJqJR5M3lpK1o8t+pRUcY2yF6ZFELcXgKSf4rZnSI0XITtG6AOIBQ7LrRAAyxXoseMh3en/xP/4rDU0hklGYQh8eNXyPejUn2LrIe0laMswN57tSiQ2yHm6AOz0iy4mpkoxRCxOTfE48OMVpuRA83EuEx+N3CAcqhh+T/afIfHRaHp5DIbroG6eDdSE6TGxkcGJwOz56qV7mRtuJG9DD0OK7Nhh7i8BQOmYd3I6M0N2LE3cgybIOtRS96xZEXyqCHDA40+bel4vAUjjDz8NmolNEiRsuNODxugkZ4hmAiqUVB6oYb0cNN/vUQh6dwyDy8m/w30mgRPdzI5nKG/I/go0Xaipv8Dx7F4SkcQRweMVpuxGi5kfph2EdxHz2S/w4tWsR2uMm/HuLwFA67Uu7F/zx8dpYPRkf+G2m0iB5uRA+DaOFGBgdu8l8/ita7CaEqJWinp0jkv5FGi4zi3YgeBmkrbkQPN35X/0LW9Ejd4bnuuut48cUX6ezspKOjg0ceeYTDDz98wHXz58+nra2Nrq4unnnmGY4++mjX501NTdxxxx1s2LCBHTt28OijjzJ58uSkfkaGCLI76G6Ku7mcjNLchDHiLRGXJQuIHoYwWkh0WNNpncV2aMThcTFr1izuuusuTj31VObMmUNjYyMLFy5kxIgRfddce+21fOlLX+Lqq69mxowZrF+/nieffJJRo8wIa8GCBcydO5eLLrqImTNnMmrUKB577DEGDUr9JyZMkEoJYsSdbLPORdMCwhlx0UNT1PoRpm6A6AHSVvpj6zE64rIER2XpGDdunFJKqdNPP73vvXXr1qlrr722799NTU1qy5Yt6sorr1SAamlpUd3d3eqCCy7ou2bixImqt7dXnXXWWZ7+bnNzs1JKqebm5tQ1CHecoEApWOvze29b3zslA78hyuNa63d9z8d3DrO+sy0D5Y/6eMr6bRf6+M4XrO/8JAPlj/IYZP0upWCsj+89an3nbzPwG6I8zrZ+1+98fq/L+t7BGfgNUR63Wb/rmz6+M9P6zmsZKH/Ux2rrt83y8Z2vW9+5M9ayee2/Mxf+GD16NACbN28GYNq0aUycOJGFCxf2XdPT08OSJUs47bTTADjppJNoampyXdPe3s6qVav6rulPU1MTzc3NrqMYBI3w2KPW0RGWJQuEHcFnromEJIweRa0bIHqA2I7+SFtxk/9oaOas+W233cazzz7L6tWrAWhtbQWgo6PDdV1HR0ffZ62trXR3d7N169aq1/Tn+uuvp7Ozs+9oa2uL+JekhRgtN0ES7bY5XhfFEbbJv9GKDnF43ARpK1D8+pHvKZzoyL8DmCmH5zvf+Q7HHXccn/70pwd8ppRy/buhoWHAe/2pdc1NN91ES0tL31GcBGdxeNwE0aMbk/QtRrz4dQO8PzsKpIPvT9HrR5C2Mgx3/SoC+bcdmXF47rjjDs4991w+9KEPuaIt69evBxgQqRk/fnxf1Gf9+vUMHTqUMWPGVL2mPz09PWzfvt11FIOgRquoIxMx4m7yb7SiQ+qGG7EdbsImcYseWasbmXB47rzzTs4//3zOOOMM1qxZ4/rs7bffpr29nTlz5vS9N2TIEGbNmsXSpUsBWL58OT09Pa5rWltbmT59et815UGMuBvRw02QaYtsGa3okLrhRvRwE0SPfciKVyfZqhuNaRfgrrvu4uKLL+a8885j+/btTJgwAYBt27axe/duQC85v+GGG3jjjTd44403uOGGG+jq6uKHP/whAJ2dndx7773ceuutbNq0ic2bN3PLLbewcuVKnnrqqdR+WzqI0XIjergJY7RGoE1Gb41r84TUDTeih5swejRTXD387PGWrenf1B2eL3zhCwAsWbLE9f5ll13GAw88AMDNN9/M8OHDufvuuxk7diwvvPACZ511Fjt2mAf5XXPNNfT29vLQQw8xfPhwFi1axGWXXca+fV4fr1AUwhqtbFTM6JAwvZsowvSboitOqgRN0pW64UZshxupH4ZsOcOpOzwNDQ2errvxxhu58cYbq37e3d3NvHnzmDdvXlRFyykySnMjergJosde9O7To9CdWlEcHung3UhbcSN6GIY4XgdxeIYAw4FdkZUoCJnI4RGixB61+ll1AsVspCCdWn/EiBtECzeihxvRwxB0C4ed6AETZEEPcXgKR5B5VihmIwUxWv2RML1B6oYbqRtuZLBkCOrwQJbqhzg8hcOO8IjDoxE93EgnbwirRRN6v5WiIHXDjUTLDXbd2GcdfsiOHuLwFA4xWm4k4mVwjtJEj+DO8A6M0Rc9ilk3ILjtyE5EIzqC1g3IUsRLHJ7CEbRiFrGRgqzEcRImLJ0doxUdQQcHCrPXShHrh9QNjTiAhigcnvT1EIencIRtpEMd9ygCYfUokhF3/r+KES/KqDU6pIN3I3oYgjrDkKXBozg8hSNoxXQ+WqNIRlym+AzOnITaz6EbSHaMVnSEMeJFrh9Bo8NFshsgES8nEuERMknQirmPYnZqMkozSAfvphhGPDrCdvCD0Xs1FQWxHYZi2A5xeApHMSpmdEjSskE6eDeih5ugeuzCrGQSPWTg2J/sRLzE4SkcYsTdBE1azk4jjQ6pG25kcOCmGJ1adMh0uKEYtkMcnsIRNKIBWaqY0RE2LN0IjIyuOKkSRQdfpA4tjBEvYt6KOIAG2cLBjSQtC5kkaEQDpKE66cI8FbwonVoxRmnRIXq4icIBLIoeUWzhMAqd11QEitFWxOEpHMWomNEhRtxQjFFadEhEw43oYYhiCweA5gjKkgWK0a+Iw1M4pFMzDMKMsPLdUKOhGEYrOkQPN6KHIcwWDnswTwUvih7FmA4Xh6dwSOKhwTlKk1FrdHWjKGZDOng3YjsMYTp4KN7gsRhtpSiWS+hDwtKGMGFpKJ4eUdQNKM5eK9JW3IgehjAdPBRPjzCLYbLj/InDUziK4YlHgzPx0O8Tj6F4eoSpGz3Abuu16FHMVVqS72YQh8dNFIthhgNDoilOQMThKRzi8BjCGq2idWoSpncjEQ03YjsMYdtK0ab4onCGIe36IQ5P4RAjbpBRmhvRw4108G7EdhikrbgJUzf2YZ7VKA6PEClixA1RjdKKoocYcTdRtJUR6M0pi4DYDkNU0WHRQ5ONiJc4PIVDRmkG6eDdiAPoJootHKAYegwmmi0cijKFI23FTTEcQF8Oz5QpU+IqhxAZMkozhFlZAMXToxijtOgIo8deYIf1ugh6hNlZGLLSoUWHDJbcFMMB9OXwvPrqq3z9619nxIgRcZVHCE0Uz9IqSpg+zMoCkA6+P9KpuSmSHrKFgxsZHLgphgPoy+GZM2cOZ511Fm+88QaXXXZZTEUSwjHMOgfp5Lc7XhehoUqH5qYYo7ToED0MzghPb9WrqlMkLUDqRn9K6PA899xznHrqqVx33XV8/etf56WXXmLWrFlxlU3wjXOPgyAVsxfYab0uQkOVKS03xTBa0SF6GGwtdte8qjq2Fk2YQVeekcGSm2Is0w+UtPz973+fww8/nF/84hf88pe/5OGHH+bQQw+NumyCb8LOw0MxjbhooZFRqxtxeAxhtdiBXn4MaXdq0SB1w00x9Ai8SquhoYGFCxdyzz33cO6557Jq1SpuueUWRo0qyrbz+eKTwGdDz8NDVipmGIYA/wgcKREeAA4CbgaGF8RoheVM4J8AcQA1VwMfCa2FwkQ1xoQtUmq0AN8AJkndAOAY4NvA4IJsWuorM/Xv/u7vmDFjBjNmzOCoo45i7969/OEPf+Cuu+7i5Zdf5pJLLuGVV15h7ty5LF++PK4yC/04A/gp0E4T3wf0CpJ9tb5Sg/w31JuBLwKTGco8IHgj3Wqdh6LD9EHD/ekxCPgtMAV4hKE8BwR3eLZa5zFhi5UaBwFPWq//haFWzSivHp8G7gReYii/BoJrAVqPMeRZjweATwAbGcoCoMx1Yxjwe/QA8t8ZyltAcD22WOcxocsVBl8Ozz/90z/x/PPP88ADD/D888+zbNkyenpMZ3Lfffdx/fXXc//993PsscdGXlihMt+2zt2hR/BgKubYEPdIjwPQzg5AU2g9tqOdx8FoPdpDlS0N/hva2YEoRq35rhsA8x2vw49a869H9LZjKnnV42i0swMwJrQedt0YjR52BB2ApseVmKzQ/UM7PFutc7p1w5fDc9BBB9W95t577+Wf//mfAxdI8McI4P3W62iM1lbrnE+jdarjdU/oKS3QeuyPHpnkz+E53fE6fP3Yap3HBC1O6nzQ8XpvyfWYChxove4J7fxB3vVwtpXwemxxvB4DbA54n/RwLkdSkekxJnB5oiDynZb//Oc/c8YZZ0R9W6EKJ6LjDzswjbQhlNHKRsUMygzr3Imzg49Cj3w6gCdb561E4fDkW4sxwPus11uAnpLrEW3dgKLosYUo9OjFbEw5JkSp0sPWYxtRDpZyFOHxym9+85s4bitU4BTrvBAYYVXKRrrZE/iO+TZatsPzA6KK8ORXjyHACdbrHxPlqHWkdffgtSwNbAP+J+AN1xYO5ZzSstvKz9BTFqBtR5BdeDT51sOuHw8RZcRrFHnUYzw6320fOj+0KIMleZZWzrEb6e+AtVYjbZKIhquRNpZUj+nodOvNwNNEYbS2YXIR8qfHSdZ5GfBmJCsa81s3wLSVpcB6y3YMK2lbGYpuLxBVBw951sNuK68BfyAKB3CrdR4TvFARIA5PzjncOr8CrLUa6dCSNtKxwDjr9VJgm6VHS0n1OMI6rwLeJgqjpTCr+PKnx5HWeSXwlsvhybcRD4pTjzZLj5ElbSvvQ093bEGvarQdnuEl1eMo67wSWEOUEZ7BQHPwgoVEHJ6cY2/3+CdgndWhlbWR2vkZbegF5JssPUaXXI8/4TZajSVNarf1eBNYY9WNQfQSfAVNfuvGcGCS9fpPmAjPyEiSlvOnh21H3wR2AZ2WHvuVNOLl7FfeJgqHZzdmW48xwQsWEnF4coy9dgjgLaDdqpQjStpInR08wCZLj3BGa6t1zp8eTiO+Adht6TE+EgdwTIh7pIPTiL8baTS0BT1yzQ+HWOct1rHe0qO5pHXD6QwDbLH0GFdSPZy24x1MdHh4zm2pODw5xm6k76F952iM1lbrnO8OHmCr1Uj3L6nR6m/Euyw9JpXQIR4BTLRev4mZ/h1GNw2B77rV8XpM4LukgdP5A9hg6VHWaGh/27Et0sFBfvX4E+4Vr5Nzroc4PDmmv9HaFElYOv8dvK1Hp9VIx+S8kQalvxG3IzzROID50sOOaGxGuymbHQn+wfcU34vZMj9fevR3hrdZeowqoTMMA9tKV990eL4jGkEYDBxsvbb12NM3eMz3Pk3i8OSY/kbL7uBHRdKhDQdXYmf2GRjRsEet5TPi/SMaYMLS4YxWPvXo36H1Oqa0xlX8hle2Wucxoe6SNP312BHplFa+6gYMHDzusvQYW0I9DkJvOrEbWAc4H0p9QM71EIcnx9i7pK6xzjscS0uDP8LVfpwC5LGhgtFjt6VHGSM8U63zVswv2FPiCM9U6/x23zsmwhPO4cmnHtOs81vWeWckKxq3Wucx5KlrGYSJaNj1Y3df/l/5psPtuvE2el2mc+AbzuFZh07ASO8xG7FsPCgkg/2MpDbrvMcxat0fs8+nPxTmcQpjgfVhipgYgzARjfes8+6+UVr5wtK2M7zW8V5vJHkJW61zPvV4t++dqCI8+XR4+tePLseU1lCCrsVxPk6hBXeOU3aZgI5o7MWOaJhoaBlXaQ20HSbCMyGUHn8b4rvRkLobfvrpp/Pzn/+ctrY2lFKcd955rs/vu+8+lFKu47nnnnNd09TUxB133MGGDRvYsWMHjz76KJMnT07yZ6SC/Qvf63unvEZ8Atp73wt0WO919xmt8kU0bGfYGK1B7LPGNweUMMdroBEvb1uBgfWju99gKRh7gJ3W6/zoYdeNdZjY9p5IV2nlRwuoZDvs7Sz2cIAV88krqTs8I0eOZMWKFVx99dVVr3n88cdpbW3tO8455xzX5wsWLGDu3LlcdNFFzJw5k1GjRvHYY48xaFDqPy9W+kd4nGH64EYL8thQbeevHWO0ehxh6eA1of/jFPJBrVFaawmNeDU9wreVrdZ5TKi7JMkoTGnFAazUwRuHJ9wUzlbrnB8tIM7BQfqkPqX1xBNP8MQTT9S8pru7m46OjoqftbS0cMUVV/DZz36WRYsWAfCZz3yGtWvXcuaZZ7Jw4cKK32tqamLoUDM32dyc3u6PQRiBaUbRR3i2Wuf8NNSBzp+ZwhlGD2OBTYHuvM3xegx6R5vsU81oAUwUh4cyd/C2Flsw8Zhoc5qmkEc9nA7PXkuP6KKhDZCT6EitwUHeHZ5chEBmz55NR0cHr732Gvfccw8HHHBA32cnnXQSTU1NLsemvb2dVatWcdppp1W95/XXX09nZ2ff0dbWVvXaLGJHNHZgFsZKhMft8Nh6hOvU9mEcwP0C3yVpas/Dh3nop1038qPFYAbmd0Xn8Gy2zvnRo1IHTyRTWpDH+mHr8Z7jvb2OR20E37bArhvpPk7BLwP1KE6EJ/MOz+OPP84ll1zCGWecwZe//GVmzJjB008/TVOTNuCtra10d3ezdetW1/c6OjpobW2tet+bbrqJlpaWviNvOT8D83cgOqNlN9T8OTyV9AjvANqxofwZ8f4RjSa6OaDC9d7JnxYT0V1ODya/K7pRa/4cHjsa6m4rUemRv/pRzwEMrkc30GW9DmeBkqRaDk8RHJ7Up7Tq8dBDD/W9Xr16NcuWLeOdd97hYx/7GI888kjV7zU0NKBU9RBiT08PPT1hwpXpUjmiEVXFtI1W/hpp9BEe0J3aoeTRiJtOzXRoI9C7LO0KdGe7gx9l3TP7bcjWog3npEJ520p8HTzk0QGsrIfbAXyToGxCJyDsh3NThKwyEjPMrTSlFW6wlD6Zj/D0Z/369bzzzjscdthhff8eOnQoY8aMcV03fvz4qnk/RaBWBx/dqDU/RrxexKtMndpotOGCymFpCNMdbcOkheejU6sc0TDRv3C/In8dfC09htId8pfkq61AfdsRLs6dL1tq141tOLc1MVo0k4MoSQ1y5/Dst99+HHjggbS3twOwfPlyenp6mDNnTt81ra2tTJ8+naVLl6ZVzNip10iDzztDHsPSlR1A06mF0yNfnZr9FOwtOKM4WoshlsMTXA9F3vI07Pydda53TfQvmraSjw4NTP2oNliKpq3kQ48GTP0wegzGfhhs2WxpvboBeoelvJK6szZy5Eje97739f172rRpHH/88WzevJnNmzfzta99jZ/97Ge0t7czdepUvvWtb7Fx48a+6azOzk7uvfdebr31VjZt2sTmzZu55ZZbWLlyJU899VRaPyt26kV4ymbEKzuAplML10jzpYdtwNtd72otGi2jFb5+jCMvethG3O3wRDU4yFcHD9Xqh9Ej3ANl8tXBj0NvNrGPgfld+lW5HMBadcM5WNpMPknd4Tn55JNZvHhx379vv/12AO6//36uuuoqjj32WD73uc8xZswY2tvbeeaZZ7jwwgvZscME3K655hp6e3t56KGHGD58OIsWLeKyyy5j3770trCOm3gjPPlqpM4pnGo5TWWM8FTq4AeHjvBA3vSo5QA2WY9hGYyZqPOH3cEPI0xmVJLUcwCHhbp7vmyHXTc2AL197w51vCpnhCc+25EuqTs8S5YsoaGhoernZ599dt17dHd3M2/ePObNmxdl0TJNMhGefDRSW4vN6AfeGcoZ8ao1ShscWYQH8qJHvQ4edJh+C0HYgd5heAhaj/dqX54yjdCXeFrNASyT7ajVVgAa6S3V4LHW4KAhEtuRLrnL4RG00bIX3Mcb4RmLPZedZSpHuxqxq3fZIl6VO3httAZJhMdCt5Vo9MhPJz8B3Sr2ABtdn5QzOlyrrTSymwbKUzeg9uCgwTE4yCvi8OSQVozR+rPrE2O0RhHmP9c5Qzsm8F2SolbCMsioVeM2WhLh0Z3avkhGrfnp5O26sZ7++/5GleBfnLYS7eAg+3UDkrAd6SIOTw6xIxrr6G+0osqm34vZXTj7DbVWwjLIqFVj61GuDn4YZl+RSqPWfSWL8FSuGxDdqjW7bjSSh1hA7WholNO/2a8bUFsPJVNaQhpU3nQQTFSjXCOTWpswwl4a2RvRKq18GK3Ky7CjrBv50cPWogvnI1ggHocn+22l8gge+q/SCr5Sazdmd+H81I/4Ihr5saNQWw8lER4hDSpP4YDtie8p2cikVgJ3NIl2ttFqJg9PTLdHafEZrfwY8XoRjd6SRbzq6RHNXit516Ocg4Nm9P7pUNl2RDM4SBdxeHLIwI2ybHTF3FPSTq1yhCcKLbaid+qArBuuFvRG9lB5pcXeSDq0/BjxehGN3pJ1avX06BE9iHYKx7kAJNvdra3FNkyMTuO2HeLwCIlSeQQP/Y1WWTbbqz2FoxvpcMLEZpy7C2dbD7tubKX/jjBRjtLy5wxXi2hEEw0tgh66fnSXrH7Ush3RRkMHhb5T3NSrG9EMDtJFHJ4cUs+I7y7RlFYjMN56XXmU1t33Thn0qGzAIdopnHxoARLR6E9lPcxQYFeJ6sf+mFR+91MX3YODcAPHPcB2x1/MLtUH0lEODtJFHJ4cUs+Il2mUZu8r0oveLdVgprTsPbnLoEe96F80ozRbi+HWkV3qjVqjiYbmo25AvZyVctkOW4s/o90Sg3sKpxEzTRyMfETLqw+W3LYj+2vvqiMOTw6pF+HZFWmeRj4a6cB9RcwybHt1TnOov2Rv0xbuuetx49VojRrwuR+2Y08V5kWPaqPWHut3hNMjH3VjMNWiocbh2VUiPeoNHPfR3Ze5VwbbUW+wZOeGhtMiXcThyRnV9xWB/hGeMhiteiN4Z4QnXEO140cH1LwqbbyGpcMbrXzpUa+tlKFuVI+G2oODXrqsLr4MevixHeFsqa1Htm1pvcFBdLYjPcThyRl2pdyFzqY3mI32dkVSMfNhtOpFNKC7bwa9DA5gPT3sKZzhhH1oSL70qDf9G01b2Z8sP4ql3i7L0Q8O8lo3THTYth3RRHiybUu9Tv+Gs6PpIg5Pzqg/KoHd1iM0y+Dw1ItoRGe08qGH1yRdKL4ewzBps/US/MNp4XwUS3YTdetNhTvbSjSDg+zWDfAW4RHbAdEODtJFHJ6cUX0EP6zv1a5IR63jgOpPs0+b6kbLTqbdVSqjVa9T29eXtRJVmD67etgP2B0YDQXbiO+OZNS6F5Pzll096nVo0sHbmC0tyhTx8rr6dxg6kTuPiMOTM6pHNEwHH828sz1KayTLCxGrGy3bAdwdcVg620arukMctQOYfT2qG3Cw68euSKKhkIdOrboeUbeV7GsBXiI8u0sT8RpFtV2Wwa4f3VZbgfxGecThyRn1IzxRGa0ezNOHsttQvRjxaBMPs6tF9a3hIb5OLbt6VHeGwdajKzKHJ/udWvKDg6Gh7xQn1fUoX3TYtqOdwM4Bn+r6sbcvHprfPB5xeHJG9QiPbbSiaqSQp4YqU1rureF3Dfi0fKP46m2lAePwaKXCG/Ds14/kosO7MN1mdvVIzgHMflupPTiI2pamhzg8OaN+Bx9VI4WsG/FGTMmSG7WOJKub7VV+pphNXFOe2awbUP+ZcwA7rQjPYML+r+anUxuoR9RtBbKux36YWuDFASz6Ki0v07/R1o90EIcnZ3iZ0oqmQ4OsG63q+4pA9I20k6xvtpes0cq2MwxeBgew0xELK2+nFscIPtt6VN9lGSq1lWimw0cT5ol+cVLbdkTtAKaHODw5o/6UVpReeLaNVvV9RSD6iAZkvZOvXjcgvim+bDp/4CW/qxfYWwoHcDB6gABJ5P9B1vVIdnCwFV3XIKvtxa8eksMjxE7tXZYHdmjhN5cTo+Um2w5gsnrYWuxHVs2Il8EBUAoH0I6G7sH8zxlM/l9ZosNeIxrR1A1F1rctkCktIXNU32UZKlVKKPaoNflGWgwjHk2nZhvwQWT1eWtepnCAUuQ02VrUjobK4EAzMD1AbAdI0rKQKF4b6R6IeHO5bDbS5FcWiANocG62l736MZxa0dA4IzzFqBvRRYezVzfAfwdflunwgXo0YmpClA5gOojDkyOqJyxD/1FrGZ4BI1NabkQPg91WdmJ2kzLE0VaK1cFDORzAWns0laWtgJcNSyFaBzAdxOHJEV4bKZRj1FrbAYxz1Vo29Ug+LJ1dPbw6fxD14CCbm+0lHx3OdgcvbcXQgt5sA2rlu0F0jx5JD3F4coTXDh6iMuJ/ts7jQ90lLpJdlQTQYZ2zp8cYzC8eqMcQTFOP0gG09ZhQ86o08OPwRLfZnl3T8qZHHBGv7NYNSCOHJ7t62FpsodKGpXHUjfQQhydH+DFa0Rhxu5EOJ4tV3O8UTvjN5Ww9WmtelQa2FpvA8Tx0m8ph6TIY8eQ6eNApwZDl+pHcYCm7WjTgffAY3RROXttK5cFB9noDb4jDkyOSn9LahcmAyFZDrb3LMjj1cD4bJhojni0twKvR2gf0SAcfS1uBonRq0UZ4sjdYOgBtP/ZhSukmjuhw3m2Hu25IDo8QO8lPaUFWoxq1d1kGp9FSRB3xyq7Rqj29V74Ovt50J5RDDz8LHqIZxWd3is+uGx3otYYDKWd0ONloaDqIw5MjxIgbnFoM3FcE4h+1toS6U9T4cYYlhycuPbIZ8RqCyTpLdhSfzU6+dt0Apy3tcrxb1Jym5GcO0kMcnpxQe5dl+wqIvmJm04jX3oMHyjbFl84UTjbrBqQdDc1W3bD/d7qBzRWviDunKVt61G4rgzHPu9qNIioH0K4bI8iauyARHiFz2Aa8i0q7LEPZRvF+RmlQ/E4tiNEaQdjN5bKpBaRlxLOpR/22Ui4H0JszDNHq0UXWp/iSjYamgzg8OaF+RKNcK0/8RniKPm0RJMIDUa7iy84U3yhMaZIN02d7CsdvWym6Hsk6PJDPiJdEeIQUkFGaGz9haSi7Hm6j1UNUm8tlc4rPdoY7MZ23mzi2cIB8dmhQrVMrpx62He1Br+MSB1DjtqPhHz2SDuLw5IT0HJ48RzSgLBEvP0YL4jDi2enUZHDgRvRw42fxB8SRxJ0dPfZD7w0O/qKhkM8ojzg8OcHvlFbRc3hq6+HeDh2KbcT3B5qs1+srXuFelg7FdgDT7+CzNcWXfr5bduoG+B8cFHlKy9ZiIybq68ZdN5yPHhGHR4gNifC48RuWLnKY3tZiA9ogDcTWY+CotYgOYP2clbg6+GxO8fm1HdFF/7LXVgZjSuNl+heK7QDWTuCGWg5gHhOXxeHJCekswwbTSIein9iUPvV3WR5otIo8D++3Q4Ni77UStIMfjDs2GIzsOoD1Izxx7cOTHS3Go/+fq29YGmeEJ3t6+I3+Qb4Tl8XhyQnphaW7ga3W62w01Pq7LIvRchOnA5i9UbxfPZyJzeV2iOOa0srOFJ+txXrs2G9/4sx3y2NbidOWJo84PDkh6Kg1mrBjtoy4312WoRzz8OkYrWzVDfCvh/PRI0WbAh6GTkyFanoMdbyOOjrsnOLLhh5hIhrljIYOzP/L8wNEU3d4Tj/9dH7+85/T1taGUorzzjtvwDXz58+nra2Nrq4unnnmGY4++mjX501NTdxxxx1s2LCBHTt28OijjzJ58uSkfkLsDMPsslw/L8FttMJvLgdZM+LeE7jjmMKxtXD+r6RLumFp+39hUs2rkiSIEY9ej4k1r0qK+huWOp8QFeWztGyypUe6gwP7r2ZDC/CzR1McDmDypO7wjBw5khUrVnD11VdX/Pzaa6/lS1/6EldffTUzZsxg/fr1PPnkk4waZeResGABc+fO5aKLLmLmzJmMGjWKxx57jEGDUv95kTDFOu+gmtEahKmY+tng0W0uB6ahZsOJtPV4r+oVI6yzeRJOdEa8BzORlg097FKkk8PTZp2z4/BkQ49s1Y36Hdpe9CRx1B1a3vRIwhkeCowLfbcoCNNW8hjhaUy7AE888QRPPPFE1c+/+MUv8s1vfpNHHnkEgEsvvZSOjg4uvvhi7rnnHlpaWrjiiiv47Gc/y6JFiwD4zGc+w9q1aznzzDNZuHBhIr8jTg60zmurXuEcpelO3t5crgldMSs7Sl7JltGy9ajv8OzseyfaRroOnTY9GVgVyR3DUL9+xOkA2nVjAtqc9Ia+Yxj2x7SGtqpXDawf0euRjbZiDw781I3+0eHKTxT3Sv71iK5u9KKntSag9dgY+o5hCWI78uzwZDoEMm3aNCZOnOhyWnp6eliyZAmnnXYaACeddBJNTU2ua9rb21m1alXfNZVoamqiubnZdWSV+hGNkY7XxR+1hjHi0fwv500Pu37E4QBuQLvWg8jClKetxZ+xd2CqhK1HHPUjW3WjfodWXQsoXnTYewc/sK0ULeLViGmx9fuWOBzA5Mm0w9Paqv87Ojo6XO93dHT0fdba2kp3dzdbt26tek0lrr/+ejo7O/uOtrbq48G08ddITRpvUUet3o14XBGe7OgxFL3UFvxN8UWnh8KE6tPXo37dgHgjgNmpGxCsg+/B7OcUnR7ZmPIM4wAWzXZMQjsAPegBQmXidgCTJdMOj41S7rU4DQ0NA97rT71rbrrpJlpaWvqOLCc5e4/wdLneLboRD9LBF22UZteNLmBz1auqO4DR6JGdUbw3h6d6pxZdRKMlkruFxbvt2Ol6t6jR4TARnmgdnvQdQKcdrd5Txj14TJZMOzzr1+sVMf0jNePHj++L+qxfv56hQ4cyZsyYqtdUoqenh+3bt7uOrBKkkUIcDk/6jbQBYzr9RHjsaFcjUWwulx09/EU04gpLZ0eP+h18E2bdYhw5PDswS7HT1yNIjgYUc7A0FvNrq8fz457CyY4eYQcH4vBEzNtvv017eztz5szpe2/IkCHMmjWLpUuXArB8+XJ6enpc17S2tjJ9+vS+a/JOkIgGxDFqTX91wQFWKfZRa2VB9Q4eimXE63fwUKYpPu9TFlCGaYsg078Q12CpIfTdwmBrUTu/K+4pnOxEQ73ZjjgT/JMn9VVaI0eO5H3ve1/fv6dNm8bxxx/P5s2bWbt2LQsWLOCGG27gjTfe4I033uCGG26gq6uLH/7whwB0dnZy7733cuutt7Jp0yY2b97MLbfcwsqVK3nqqafS+lmREiQpFaKsmHvQZmI8aa8usLVYT631QANHJfbmcqPQelTeodkr2TFa2Ril5bGD78FZg6LX4yjS1qMJsz2m3whPtBsx7gOGoIcr1bNF4iZsW7Gjw7sJQ57aCsQ7/Zs8qTs8J598MosXL+779+233w7A/fffz+WXX87NN9/M8OHDufvuuxk7diwvvPACZ511Fjt2mDH7NddcQ29vLw899BDDhw9n0aJFXHbZZezbV3nz8DwxHL3UFtIMS4NuqLbDsyKSOwYhaFIqaD1GEWVewgS0Ia/8yM4kCJukW7ScprDTv0XSw/7ru/CX3wVR6tGLdnJa0VGe9ByeoBENpzLNlM3hiTunKVlSd3iWLFlCQ0PtUOeNN97IjTfeWPXz7u5u5s2bx7x586IuXurYlXI7JjNgIHEnLYNuqO8n7YZaP9oF1fSIbtS6ER0UH4reNfXd0HcMStAprWjD0tmJeAVN8C9inkbQ/C6Iw3a0ovV4OZI7BiFoRCPa6LBdN8ah7Uf1ybW4qa/HYMyjRySHR0gAbx18eUat9fOZIP4kbshKJx+0U7O1GEkURiAbScvO/C4/mw5CMaf4/HXwoocmblu6BfOYhnTbi7/93YqRwyMOT8bx18HLqFWTVMQLsq9HA7XC0hDlFF8zaZpBW4sOak0yJlE3suEMhxksie1IYrCUnsPThNl0sP70716ckag85/CIw5NxvDk85RmlBZ2Hh7hWW6RntLzldw187Aho82U7BeH16AK2Wq/Tqx/Zi4amO4L3ZzviWuEJWXMAw+hRFFvqzO+qvgSlthbRPJg6WcThyTgHW+c1Na9Kah4e0jZath7v1LwqCaNlm80pNa+KE2d+V/VnpTnD0rtcn0Q7ik9fj4Osc7r5XWC0mEiaXYI/PeIcLKVfNxoIN6UVT/04sOZVcRJFagDkL8ojDk/GmWqd19S8KolRmp2Ye1DNq+KkEWMy19S8MgmjZetxcM2r4mSqdV5T8yqnM+zeTzXaTi0veiTRwa9Hx9AaSXOAMNU6v13zqiQGS/bwJL26MQG9pLyXcNPh0djS9PWYap3X1LyqshbRPnokWcThyThTrfOamlclkYhpN9IxwOhI7uiXKejx8i50nkZ1kojwrLHOUyO5WxDsv7ym5lWVO3goqx5JTGkpTLeal04tzsGBXYL0tXiPek9/T9KWpq/HmppX1bcdEuERIqMBE08JMoUTrdHqwizITKehTrXOtbWAZDq1vBityiN4KKsetZ3hIZiFuOGw9Zha66LY2A/T7mtvmhD3Lu2g3Yx96Hyy8XWujYep1nlNzauGYqYgk4h4Ta11UazYf3lNzasq21HI79J0cXgyzER0Nn0vtZbZQjKjEki7U5tqndfUvTKJML1digm4E4OTY2q/klQmqQhPXhyeym2l/+Zy4bFLkW5bWUe9nV6SmOLbg0lczrLtGOF4Hefg0S5F1ttK5cEBiMMjxMBU67wWr2HYOEdpkPa0hf1Xa0d4Km+WBVEbra2YrSDTyWuaap3X1LyqeoQnHiM+NZK7+aUZs2ItSDR0H6bLL4IDONU6r6l7ZVKDJbskUyO7ox/sv7qmxjXVHjsCceVDjiat9ICp1nlNzauqR3jyuhePODwZZqp1XlP3ytph+mg2l3OWJMtG3DlKk4hX8hGeyaSxgbv9P7AJ9yqSgdQP00c7xTc1krv5xf6r9ad/k8h3c5Yky20lqSkcZ3rA1Eju6IfBmFVaa2peWT/CIzk8QmRMtc5r6l5Ze+NBKIYR97ZE326k++gfzC/SqHUYesrTWYrKJNXBd6D1Hkway4+nWuc1da9MKkxvlyTLHTwks6IR0rYd9l8NEv2DOG1H8vXDHpL0AO01r0xqsJQc4vBkGG97zoCpdu6xrXNzufIYcbv73jHgk+hHJemNWu1JtO3UejAkJGfEFWnqMdU6r6l7ZXUjHm0nb2txEHr5QbJMtc5r6l5Zf3O5vEeHG/A7WIp7+hey0Fbeof9GFf2pv+BBHB4hMqZa5zV1r2yxzgMfLxptJ2+XZGokd/ODM25Q2wG0tRg4sVGkUav9F9fUvbKyMwzFMuLeOjSopUf0G3XuReeTtda5NnqmWuc1Na8ajOnU3HpEv7lcenXD3oNnL/U22rN/adx2FLLg8NTenwmStR3JIA5PhplqndfUvTIpI2430nG4d/CNnynoMGw3elu36ti/tLrRKkJYemq/ElSnvjNchCk++y+uqXGNpn5biaZT68V0r1mtH85fGnd0OP3BwXv0T0XuT/XBUnw5TVMju6NX7L+4pu6V9W2p5PAIkeAMw9aOaDRZB8TviTsnUJI14lOtc/0wbFLOn10ayHtEo0ij1jV1r0zSAUxHD+978Nha7KbS41bjmeJrBsZGckevTLXOa+pemaTtsEuTh7aShB7JIA5PRpmMDobvod5W6M4qVz1vJe8jk0Otc5gwrP1OI1FtLrfGOk9Cb1mXHIf0K0F10nAAp0Z2R69EoUdRpvimWed2tCtTnepaON+NxiHejdkfPR091tS9srozXJS6AUaPoLmhznfE4REi4X3W+W3q7cFjN9KuilcWZWRi6/FG3SurG63oN5fbgNZ9EEk/CNDW4091r0zSiK+xzsnWjbHoqAbAm3WvLr4DGEXdgOJMeXrXI41o6AEknR5wmHXOlu1IBnF4Mor/RlrbaEW/+eC0WhdFThRGK/rN5cDocUitiyLHu9FKsoO3428Hk+RePHbdeI/+z4PvTwPJ5iXYeqRTN+oPDrxFeKKvH4fWvCpq/OtRvW5E9+iRbcAW63VytnQE5nG2YeqH5PAIkeI9opG00bLH0O+reVXUROHwON+NTg+7RIfVvCpKxqH3Z91HNBGN6IzWOrTL0UiSo3jvzl/1JF3nO9HVDbv1Hh7ZHb3gP8JTua1EP4q39UiurUA0ekQfHQZ43TonVz9sV3Mzxt2qTpL5bskgDk9GiWIED3EYreQbKUTv8ETXySevh1033qPec5IgWaOlSKNT8z/duYdK2S3xtZWDMAsL4se/7UgqOpx83RiF2aAzjB7xRIez3FZAcniExMhuRMNuKoeSVPUZjy7/XrwkLSedl5Ce0apfN8BLku4ootwaL3k9ohocRF83Oqy7DibJaS3/DmDStiO5umFHNDagJ5Fq402PPDuAUdsOcXiESIgqLB19I30XHVcYRlKJurY5eBe9HXptko54ZX2UVn9pKZTFiCcd/YOk9WhBDxAgughP9BGvA4Hhkd21FsE6+OIOlrznMw3DrDyVfXiEGJmITi7rxc/SwaQaqTNzJJmGGtWoxPlu9Eb8EJJK1PUe0YBa9WM3ZiO2PE/xRbGCD+IK0yerh63FeiptUtGfpHN4NmP28UomB9B7Bw/JR7zSayvenWGotd1JdA+mToY8lbU02JXyHSptB9afpCMakJYR99bBJx3xWodemp5coq53PYajp1OgqNMWY9BJ3BAugdv5brRtJVk94hgc5DniFWWEJ77ocGukd62F/yXpO6i01Ws80eH4EYcng0SVWOZ8Nx6HJ39GK55EXbtkyTiA3ketttFyply6ic+IH0wSibp23bDdztokHdGApDv4YBGNJCNeWdYjaQewE/iz9Tr+iNdwzPMIwyzRB53U0NvvyjwgDk8GyXZEA5JebisOoGF/dFQD4K26V9fWwvlJtIm6nWjTEv9+K8HqRlKrkiCttpLN6V8oQnQ4Hgcwfj3stPktmInF6qRhO+JHHJ4MYld9MVqaYDkrxRzFO5ek195kD/wYrbxOW0RZN+x3nU+nC4/dVqaQRKKuPz2KHfEaiX7oC3jRYwg6URfSyfFKrq1EEf2DfCYui8OTQY62zq94unqMda686DJeozWVuJ8hNQm9yV4vXo34aOuc5Cg+OQfwSOv8qqera3dozk/y2qkdZZ1fr3mVjbcOHvKbqGvr8Zqnq4udw3OEdf4zsLXu1c7/8WI6gLbt8NZWJMIjJMAQTNX35vDYTx6uHKSMp1K2o5t/I3Fvi247f2/gJYF7JMYBq7yPaN47+GOss7+6UX1P1bwntdv1Y7Wnq2vrsQ+TB5TH+jEe/UyxvXh1eGrrEW9biT9R11/dGGOdd1Dt6YV5tx3B2srWqlfkcS8ecXgyxvvQXXYn0ObpG96MVvTLB5OZe/YX7bK16KFakm68YemDiHvaIpge1R2eePU4ouZVYRns+AtRODwQdwTwyJpXhcV2ht+i3lPSbdJweDrRi+Yh7voRbHBQPbslz3UDoh8sSYRHCI2/Dg28Gi2I+pm8f7TOx9S8Kiz+Gqn9zOykIxobgI3o5nRUnWvD4W+UZutR34hHq4dduumR3rU/h6CzLnbiZb8q8GPEW6peEYRV1jlePfzZjkGY6d/KesQ3gk+mfvjTo77tiKduvIqesB+LyTiKHqdlitoBFIdHCEzUDk83ZnfiaBvqSut8bKR37U/UEQ0702l01SuCEr8eIzE7/WRbj1fR0wL7Y55kFD123fgjlXYKqUR9I77VOkerh+3wZKmtjMaY/8r1Y6t1HknUW2omazuiiv5ttc5jApanMj2YKE98ehyMjj3vxsvqTvDiAG61zmMClyp5xOHJGP6M1gjMepL6FXNs1SuCkE+HZ6t1HhOwPNWx9Yhv1GqP0DrwsqwUvOhhfxJt3diNmfKMTw//gwPvRjyetnIEcSb529FQfx38Tqo9sGVrhaujIf6I13DMMmx/EZ76zvCYYEWqQfx62HXjVXSuWn28244xAcuUBuLwZIxgHXwvtTaSj6dTs434kcT1SIUJmCRMbysL0urgIQkH0N+IFbwY8Tzr4W+6E9KrH2vRsbQhxJm3EvXgYB8mAjgmYJkqE3/dOALduW2wjvqUw3b4bytp2I74EIcnQziTMKMyWs5Po62Y76ITEJuIy4jbjTSqJEznJ8Mwu25EQ/zTFlFPdzo/id5oJaeHNwewAdNtp2HE49VjHHAA2knxtmVB/Q4N4tLD/h+biJ72jB5pK27yEw2NF3F4MsQhwFB0kPldT99I0+GBuBuq/4iGt0Q7e0v0eML0kzDGIlr8TVmAnym++Eat8YTpB2HWtUSVs+L8JG962HXjbbxsSAleOjSIq37sxGSSxKuH/w6+vjPsrEnRYNeNoyO/s00ctkMiPEIo7A7+VfwmYabl8MQbio1jlAZxGfEd6O4G4jLicYzS4puHt+vGMcRhZqah8zR2AWs8fcP+3+6iWs4KJJHjla+2En/9yNpgqf7gAKJOan8LXS+HEcfmlA34XaEFfqa0xgQoU1qIw5MhjrPOUUY0IIlRfDxGy75rlB2889M86TECvyu0IN15eNuIDyeOZ2rFkYTp/DS+aGhWIhppTmlB3NHh4BGe6vXDmSkZrR6KOJfqH4xeadcNvOnpG0Mwuw3JlJYQE++3zi95/kbaRjy+Dr4Bo8fvPX8rbT3iM+LHoxvrOvSOP/Vx5qzUj/A496iOhn2Y7iZ6I27XjRWev5GVDn4acTx9yNbjD56/keaUFsQ5xdeM2bfYux5p14/4bOkJ1vkVqu0h3R/nr6v8yCKQKS0hJCda5/w5PFOJepefw9DdQhdet8mH7OhxXM2rgmDXjeWev9GCToOHWno4nzgWnx7HR35n/3qkHf3bjNk7Pdr6MQjTqXnXIytt5Vii7oZOsM7vAJs8fysrekTfVk6yzsHqRvX4qTOnqSFAudJAHJ6MsD869AjwsudvHWCda4/542ukWzB73L6/1oW+cY7gvY1KwKz4qG3m4tPDNiknEPVSfdtoeXeG7Q6+Cx3Mrsw+4hzF23qcHPmd/Q8O0o5oQFx6HIGe8tyB1ydhg5ckXYgzT+M1dPJyM1Gv8vRfNyD9+pG/tmJ/Opj87LaceYdn/vz5KKVcR3t7+4Br2tra6Orq4plnnuHoo4+ucrfsYnfwb1Dr+bT9GW+d/1zzqnhDj7+zzqdEetdgRmuCde6oedVW6xy9Hn+y7j6cqEP1/vWwtahdNyDO+hFP3RgPTEE7a96ntOy2Urtu5LGt2M7w7/GazwTp2469mNo8I9I7+x8cjMBMM6alx0toTQ5EP1g1Ovzr4a1udGO2C8nLtFbmHR6AVatW0dra2ncce6yZ57z22mv50pe+xNVXX82MGTNYv349Tz75JKNGRT9PHidxdvD2GC6exdIvWue0HZ7hmHFG7YYanx4K06lFZ8SHYpIw/Rut2nUDTDwsej1WoFdEHYCJX4bHrht2jMAb3hxAW4tmzB7m0WG3lWg7+Dhth61HPLvlZEUPu63sot5wMz49dmJy3qLTYxL6f7oXP4MDb3UDzNxCPPUjenLh8PT29tLR0dF3bNxopnC++MUv8s1vfpNHHnmE1atXc+mllzJixAguvvjimvdsamqiubnZdaRJMKPlzRO31Rrn695eyZrR2o07M2Ug9s6r8egR/Sj+WPQE2QbgPc/f8h7hsevHATWvCkI3Jm00Oj385++An+ifvU9T9EZ8mXU+nCgnifyP4MFr/YivbkAcbWUEZn8m7/XDewefjO2IzpbadeOPeN28FbJhO+IhFw7PYYcdRltbG2+99RYPPvgg06ZNA2DatGlMnDiRhQsX9l3b09PDkiVLOO2002re8/rrr6ezs7PvaGtrq3l93PhfoQVeR/F2I92POP7Dl6MD6QdjGko4DkaXtQc/S/S9RzTibaTRO4DhOrS0jXhW9PBWPxRmFB99/diMWRgcTa6GczWj9w5+GGaRgTfbEW/dOJ6o4mnHo3NK1uGl5ttkpYOP3gGMc3AAcdeP6Mm8w/PCCy/wuc99jo985CP87d/+La2trSxdupT99tuP1lY919nR4f6P6ejo6PusGjfddBMtLS19x+TJk2P7DfVoRo/5wM8S7KGYUaK3KZxBxDFtsYOoQ7F2I10J7PH8Le9GK5lR2nT0eDM84aJ/aTuA8RnxuBzAPEVE34e2H7vw+kgJMHWjm1rLjsGtRfQrcd62/sJQolq5FnfdkMGBm3jbSvRk3uF54oknePjhh1m1ahWLFi3iYx/7GACXXnpp3zVKufclbmhoGPBef3p6eti+fbvrSIsTrPO7+FlGaXdPPbj3AB1IL8bpyUOnlu8Ofh16+fFgolq5lu9Rmm3ETyIKc7MfZgPGl319078eeWgrdofmbzWjf+evkah3F7axp/mi6eTz3cGvRDuh+xHVZp1JDQ5kSismurq6WLlyJYcddhjr168HGBDNGT9+/ICoT5b5gHVeVvOq/niPaEBSnVo0RvxU6xysg087wgOmU/uL0HcaitmKLI4cDYjbaL2KjgKOwmxwHxx7IuhP1ItNOHFGQ9Pu1KJtK7abEFeH1oPJiIt3CjgfesTbVvZgYvzh9ZgITEYnHLzs65tZGSxFT+4cnqamJo466ija29t5++23aW9vZ86cOX2fDxkyhFmzZrF06dIUS+mPv7TOz/r6lvdRCcTdUF+wzqdiNrsLRiPG4fkvX9/0P0obRhx73gI8Z51nhr7TDHR3vR7zpC5vZMVo7cPUj9ND381W9Le+vuU9GgpxOzwvWeWYhH5ccDhsPfxZO+91A+LWw24r4evGGMxmEM/VuG4gWRosRaeH3a/8AT+rGSE707/Rk3mH51/+5V/44Ac/yNSpUznllFP46U9/SktLCw888AAACxYs4IYbbuATn/gExxxzDPfffz9dXV388Ic/TLnk3mjAVEx/RjxYhCceh2cFuiMZTdhpnOPRTsgW/DwHB/zo0WUdEFdDXWydZxE288E2e/6cYcjOFB8YPWaHvpOthz9nOEttZRfGAZwd6k4jMFMWcQ6W4tXjt+hJ90PRe9AEx7ajr+H1f9rGfwc/Cj1gip7F1nl26DsFsx3BoqEypRURU6ZM4cEHH+S1117j4Ycfpqenh1NPPZV3330XgJtvvpkFCxZw9913s2zZMiZPnsxZZ53Fjh076tw5GxyJXv7ahZ+EZTCbU/kzWvGN4n9jvf5QqDs5R/Denhhv40+PeBvqS+j9PPYj7LNxbD38dfBDMOnpWRi1LrbOs0PdZQhmktCfEc9SRAOi0uMv0BHRtej8P+/4cwDj1WM7ZvJ6Vqg7BWsr4Kd+dKLjcxCXHr9B29OjCLvqNZjDYzvD3qKhMqUVMZ/+9KeZPHkyQ4cOZcqUKXzqU5/ij3/8o+uaG2+8kUmTJjF8+HBmz57N6tXeFzOnjd1In8fs/+GNg6yzN1MXvyf+jHWeHeouwY2WPz3ibai9mF8Q3AEcBNibK/gzWlOs8y68pMHbdWMsUT8Qw+ZFqywTCJPHcxJ6e8kN+Hm+GpjIgbddjOKNaEBUDk/w6J8/PZKzHeEGS8H1sNuLt61J4nUAt2IyboI7gC2YdW/+bKmtxTpPV8uUluCL8B38OzWvsonfiNtG63TCdJvB9GjAGPHiOIDT0cHl7fh56jOYXY29abEZs8InHj16MBO2swPfJWlneHzNq8LwHHo1zoGEWY2TlB52HCg+PRZb59mB7zAMk7Dsz+HZD5PJt9bTN+z6Ec2uY5VYbJ2DO4AfQGdTvgm017nWjW07vPUrdt0YR9jszWQQhydl7HnnuI3Weusc7VNanPwBHU1oxiwO9ceh6PJ1E2TFWhO62/Y2MrGNwERff8cPi63zBwmax+NMSPW+5Bj8Gi2FqR/x6zE78B2Cd/D+9LBrUHxahM/jGYxZ3ek/opE1Pew8nkMwds0fM9AWoB14y9c37b/Xgde9iOPXY7F1nh34DnZb8V83/A+ke9GORHwOYHSIw5MiE9Gd/F70lJY//I3i7UYa3/aKClhivQ42MrEb6e+o9XzvSthatOHVNbD1mOTr7/jhJfSM/37oVGz/JDWChyT0WGydZxPEAWwgjBEP1lb2R6dwxsNi6xysrZyASe73N4E/AhPH86dHfHVjB2aIMzvQHcLXDW8dPCShx7PoPJ4jCepWBUvuhyCDJXvwGJ8e0SEOT4p82Dq/jJ8npINeDWVvDe8tDGvPTsdbKZ+2zh8J9G1bj7hHJZCE0dqL6dQ+GugOs61zMYz4i+haPh6ztsg709EOyE78JveD3/qxFR2DgThH8Yus80cIYoZnW+el+E3ut6d+t+F1J6P46wbAU9b5nEDfnm2d4+7gIQk9tmIcQP+2YxhBk/vB7+AAkqof0SAOT4qcbZ2f8P1N24BvwJjm2theeDNx7T0D8EvrPBO/D7FowLhJv/b9d/03UtsBjPeBIr+wzuf6/ubx6M52B373FIFsOoB7MDXdvx52W1mM3+T+Rsz/cpaM+G/R2VPjMJNT3rG7wSd9fzOLHTyYtnI2ej2ed0Zg0nv965HFtgJGj4/7/uZstNOzFnjd97ezWj+iQRyelBiE6eCDOzzeDfhOzHguvoq5Bp3L04jfkcmJ6LH/dvxuogbZnMIBeMw6n4rfGW5bvacxy2C9k9VRWnAH0Nbjcd/fnIzOeOnGz+Mkk4kA/sp67U+PkZgpC/96+K8b9mBpJCauHD2/Q2eSjUbnvXlnNnrqcQ1+nidmk/W2chZ+d/wJ3lZAHB4hFk5Ej+22ESZ/x9t0lk0yUY2fW2d/RtwewT+FnweG2gQ3WhOJ46GINusxW+d/zNc3wxmtrI5af4Xu6E/AzyZzzZgcDf96OJ1h75M/yehhtxV/o/gz0Am6bxFkBO+/buxC5wpBnHoozADBn+0oZge/Al1nR6D/x71j21L/eoxBtzYI4hCLwyNUxdnB+wvRAxxhnd/w9a1kjfjZaLPsjeDTe2CeNf+m52+sR6cFNqFzQ+LDvwPYgtl/x78eU9Ajwj143WcFkqobmzDL07138h9GT3K8jt8VOKCfJw56/O+dZPT4NTp+dxRwmOdvhevgs6xHsGmccHrY2wJ4f3CLrUUrcQ6WIEhE9BC0NdyDyRLzjq3FeryuWAOJ8AgeCNfBH22d/1jzqv4kUzGXWX+pBa8rLsZgshj86zEEY8S9P4yiF7OHRDIO4Bz0tnn1ORM9KfgqfrslMHXjDfy40skZLVuP8zx/I1yHZuvhby1TMnp0YhLbvXdq0ejh78EtySUu7wKm4XWH8sPQ3XQ3ZsmEd1rRuYZ78RMr60APloYQ94Z7TgfQm2tl143/wu9CGIBjrHMW60Y0iMOTAvthHpAZzOGxd6v1VzHtKa0pNa8Ki8J0ahd6+sYcdJbFK/jdIh+0yWtEdx7edkq1sa8OtvOHV1ai4xIj8NrJp9Gh2VpMIK5nBNn8p3U+A695TeEGB8GMuK3HwTWvioL/tM4Xe7r6SGAquoN/pvalFRiMiQ77cwCT0aMLWGi99qaH3Vaexe8DMsG0lTfxsxHGXsw0Trx6PINesTUJr4PHNGyHHUeO145Ggzg8KXA+2vT8Hj+TDjYtmCwcfxEeO2gb/hnN9fh/1vkCdKpjbf6bdf5FzauqEayRgtFjWqC/64fvW+fL6l7ZCHzCev3LGtdVJ5gem9AuI8RtxN9Ep6U3ApfUvXoG2pDuxMRC/BFMD3vqLP668WP0tNaJmGd9V+eT1vlpzANwvXMoOr13J36HFsnp8R/W+bN46Z5sPZJsK5CUHj3o+gFwad2rR6OjwxBWD3/OsG1Hx2IeO5pVxOFJATvu8aNA37ajO22YLsobdiON3+H5LXpKZRTavavOKOCvrNc/rnVhVYJFuyBJPWwjfib1Ar8fRofJO0i2g4ck9XjAOtc34hdZ50fxk1VgMwrjvgVzeCbjJxMtCJsxrr53PYK1FedUuL/de5KrG4+hNZmM2ZmrMpMx67l+EuhvBYv+QRpt5ZPUGzx+Au3OriLIL4KgenRhdmqP3yEOhzg8CTMes7fqQ4HuYHfw/qI74G6k8SbbAdxvnS+redXH0ZktrxNkQzkI08HbKc7xG6230E9BHgx8puaVdof2E/w+TsImDw7Pj9Huy3HoFVuVaSCqwUE7Zp2RNzag90AaRBLTWnan9hlqPZHoGHQMqBszEeYPu0Pz/3Dl5OpGD/Cg9bq2A3iBdf4NfiezbYJFNCBJPZ5DW8dRmHhWZWzbEaytjEBPlkK2bUc4xOFJmE+hTdoLBElIBZPM579SvotOYx1GnDvI2nwfndp3BrW6jHAjVjBGPLgDGPzxjX6wO7XLql4xFJhrvQ5mtCaiA8v+kjBtkjNa29AxG6ilx0z0KH4rQTajhDAjeEhSj8fRKfSt6H1XKnOR42pveyT3J3xE40D8bgsYBLutzKXWzj+fts7B2grkI8IDJkJc3QEch5nOCqbHkWh34M+YRyt7RxweoSLhRqxg0p1/5/ubezG7TcRfMddiFkZ+vuIVozEJqcH0aMEYreW+v51sI/0JOnfiKKrtq3E2WpO1BNl8EUzdeAW/TyODpPW43zpfitn7w43dwT9MkM0XwWyw/3KgbyenRy/wA+v1/6h6VbgRPITRowM9dZFMxOt36Do8Arii4hWHovO79gI/DfQ3DkVvSNFNkMFScvmQ4B48Vs7z+iQ6K+53+Nmcw8kp1nlFoG8nFy0Phzg8CfI+9JzzPoLOOQ/FPIk8WJdoV8xkohp3WuerqDRS+zQ6PyL4nPNfoKvwm/jZRdfmXbTBHE4SEa/twL3W6+sqXvE56/wQfjMsbOzde35b86pqJFs3fo3uaMYAfzfg06GYKYvg0b9weiQbAbwTXRs/ip7qc/MBtP3YSdDk/lZ0d7SPIFudQtJ63G6dv0SlmJI9MbwIPf3on7+0zssJMzg4CO1oxMu7wM+s19dWvMK2HcGdYVuPPLSV4IjDkyB2nONXBJ1zPhHdFXQQZAs2gD9Z5yNqXhUVj6HdmdFop8fNf7fO/yfw/e0OLZjz14sZqR0ZuAx+uM36q3Po/wDNAzGL1r8X+P7hjJa9jeVh1MokiQoF3Gy9vob+qcEXosP072AeK+mP0ZjRcDA97EnBo2peFRVvY7L6/nHAp3Zb+TFBVmeBqRsr8bvYwcbWI5m28h/oHV6m0H+J+hCMi5xWW2lHD2Ea8bNlZBi+bZ0/Tf8F4CegLWEPJk7on3B6JNtWgiMOT0IMBy63Xt8d+C729nzBOnjQ7gd43dYrLArTUK/BucPL6ejuaCdmxt4/4UbwoM0/JKXHO5iETHen9ndoJ+Npgka7wkf/1qATdYdhtnKMlx+gN2aYhF6GbLA7+H9DxyT8cyravP0Js8WkP+y2Un+xeFTYDuCFmARSvdDB3rrhO4HvHa5Dg6RtRw+wwHp9Lc5lFnPREdn16OnOYESnRzL1Yzna9W9ER70Mdlv5KUHi3KDVnIaOMAaL/tlp31PI/tJ0JQequblZKaVUc3NzLPe/DJQC9SaoQYHv80ulb/M/A5djplWONYlp26jgbavc/73v/R9Z5fhu4PsOVbDduu9xgcv3dasc9ySmx3SrzHsVHKkA1QSqwyrH+YHvO8u6b3uo8j1vleNTienxJavcrysYogA1wyrDblDjAt/3m9Z97w9cttFWOZT1Ohk9Hrf+5Hf73vsnqwxLQ913mXXfiwPf41NWOZ5PTIsWBVutcn+y7/0lVjm+Fvi+4+z/VgUHBC7fPdZNvp6YHmdaZd6hYIIC1FhQXVY5Tgt834us+74UqnxrrHLMTEwPc/jov5MvXBaPuB2eZVZl+IfA9xitoFvp2xwZuBxjMEa8JTF9r7L+5AYF+6mJoHqsMhwX+J4ft+75roKGwGX7b1Y5nktMCxQ8YpX91wpQF1tlWAtqcOB73mHd875QZfs/hO1M/B6jFHRYZf+yAtQDVhkeCHXfV617fjpU+d4lbGfi95hplbtXwftVo1UvlFVPgt3zYMc9xwcu25FWObaDakhMj69bZX9bwXB1rFWGPaAmBb7n31r3XBaqbPOssjycmBYoeM4q+wMKUF+2yvBSqHs+ZN3zplBl+4VVls8nqoc+xOGJTzDfx0etirAT1P6B73OJ0rdZHbo8thH/y8T0HaxghVX+f1cLrL+/JNQ9H7Dud3uosqVjxA9RsEuBUg18Uq20yvBPge/XoKDN0uOcUGX7e9Iw4pdZZd+uDmRynzM8I/D9jrXut0tphyp42X5JGkb8h1b5l6rLaFAK1Hp0JDDY/b5s3W9RqHINRkfdFKhDE9NihIJ3rPLfqB60/v6PQ93z19b9/jFU2T5kleVPidaNk5WODivVxEzVZpXhilD67rT0ODFU2W6yynJ3onroQxye+ATzffyWQUqB+pdQ93lYgVJ6xBOuPI/qG6kvJqrxX1rlV2oJf6EUqDMC32uIgi3W/f4yVLkGo50dBeqYRPX4mgKlRvCu2s5ItZkw0yZ2VGCLgqZQ5bKnPNsS1aJBwW8VKHUKDyoF6olQ97OjAo+ELps95XlfonpMUtCpQKmbuUwpUF8Kdb/nLT0+H7psL1h6fDpRPc5XoFQDu9SfOCRkZHh/BXssPQ4JVa4xmGh58IFskOO7CpQaxwq1h8FqDWGc4U9ZP+HN0OWypzyXJ6qFPsThiU8wX8fJzFaH8Zp6iSPU+MD32V9BlwKl4PjQZfpHfSP1k8R1vk+BUsewUv2KESHuc56lxToVZjrLPp6y9PjbRLUYpuAtBUpdyXfV9aHudZelxwOhyzUMM914cKJ6nKD0lItSP+GTIaI7DQpes/QInq9iH2dbWryWqBYoO7dpLJvU8xyshgW+zyGWFnuVnfcR5rjN0uPOxPXQUZmZ/Eb9PxpD3OfvLD2WR1KuVZYef5WoFvsp2KhAqa/yNXV5qHv9zNLjf4cu12RLi15QIxOuH+LwxCeYr2MGTyhQajyrlU7CC3KfbygibKT2KH5dwhofzAGqlXUKlDqAH4a41wuWHuEbKaQ1ikd9hDNVQ194+tKA92lVxhk+I5Jy2YnLyY7iUefyvxUoNYxOBUcEvI89Yt2iIHxbHoMZxQdPoPZ/DKdRnWDV8wP4ndJJ+kHudY9V/McjKVdao/jjOES1WAnMY7k14H0aFfzJ0uOLkZTLznn7VsJ6nMfF1u9QahAfDXifo5U9PaYXU4Qv1xqrULMT1kMcnvgE83XszwQ1mrVK14PHFL5HJ2MUbLO+/4lIyjQMVDdJz8WjngT1G2aqwfRYv+fLAe7zEeu7O1WYFRbOwx7Fv5mgFgeA2gjq63zF+j1dCk4JcK/brO//V2Rls0fx/5agHmeD2sNgNYunrd+zWsFYn/dpULDS+v5XIyvbakuPuQnqcSuodzhQjWWD9XvuU/6jmVMVfW3tA5GUaxJmFJ/UoodGUL8H9UhfZFcpndPo916XWd9drwgVYTbH5VaB/ivBunEoemXWVX2R3c0q2ADhQev7P42sbD+09PhqgnqAODxxChbgOEmZUfjPlL88C7tS/0FFMX1jH8/om6r/kZC+l1p/rwvU/vwP6zf5HWkNUyb5+ZbIyjYKk4x5REJ62IZhGQ2qgZ9bv2mrglN93OdoZerVnMjKdo5VtncS0mKU9bcUqK8xXsF71m96SenpXK/3utL63halVzVGU74FVtn+T0J6zEA7FArUyZyp7Kk+Ha3xYwN+an3viUjL94pVtqS2LrjO+nsbQQ3nJus39Sp/U5ZjlUl+/lJkZTsQ4wDul5Aei6y/+RhNyqzaaldwlI/7/KUy0Z3g23r0P/7aKtsLCWlhH+LwxCdYwOMcZa/M0QZonIfvXGBdH22HBjoJUoFamIC240Ftsv7e/+x73zZcSsE/K72Sq969/q91/XoVZnltpeOJAeWL7/gYxkieCApGKlhs/bZOBed6uM8oBX+0vhNthzYMvaJQgTo2AT3+FRNhGwFKO3Lt1m9bpbyNXk9Upn1F16EB6kzMFHDcK/mGgPqD9fe+3/f+xco4PQ8qb1N1f29d363Crr7pf3zbKt/9CdSNw0Htsv7eZ0DBIGXswF6lB0z1nMAGpaPrSukprWiiO/bxslW+SxLQ4wrrb+0ANQ2U7kdetn5bh9L7cdW7zwRlVnXeH2n5WjFTwBMS0MM+xOGJT7AQx4eV3jTK9sjPV9Ub62XKGPBvRF6Ww/SNVTd686q4fnMjZkSynP77zHzV+n1KwVJVfR65SdkrE7ThjyZXxXlcbRXktzFqAXpEuN76W992fTZcwUKHHv+uqk/ZTVFm5c27ypvz7O+wV/LFHZo+1/xg9WHXZ4crE+nZqeBqVT0y+iFl9vL5TxVlJBS0E9JplfHUmPWwnb8/03/lzwXKrC56U+lN6Krd58uOa/974LJUO07HRFyCrw6qfwxH2wwF6nHXZw0K/k2ZqvO4gvdVuU+zgh9b13WpKBZ99D++YRXkpzHXjWMw9fAa12f7KbOx5F6lcxurRTiPUHoQYQ8mRkZezhetMv5dzHo4D3F44hMs5HG8MhXOzlW4XmkDNkvBpUrvl2F//lPlLfrh//i99Ufmxfh7F1h/oxPU0RWvuViZJeZKwa+U3qhwptIO4v9UZtXNXqU7vujLORG9mZkCdVRMWjgN+O+tf7uvaVLwbYcWXUqPZi9RcJqCs5Xed2iz9fkmFSzvp/5xiVWItwmzM3jtw2nA76h4zUTldgLfU3oH5Y9Z9eOTSndmdvTjJRXlVJbzuJ/4p7Xs0btCO4IDr/lLZXYtV0on7/9PBbOt40plpjiU0k5B9OUcjNkM8b/FqIe9G3sHqCkVr7lKmSndXqVt5d9YOp2p9IDKnsbqVnBhLOW0N0PsRufmxfE39kNHQBWop6nUJkcq+D+O//ttCu5UOon/NKXbzHeV2Z2+TelBRfRltTdDTHJaSxye+ASL4BiqdNRmq8LYuH5Hr4L/paIerTqPq6w/tjqm+1/p+EHn1bz2QAU/UqbjqnRsVDphOb7/l0esP3ZbDPcejN4sTaEN+EE1r5+tTASn2rFM6aTUeLQYBmqz9cfOjuH+49Ebtil0BLCx6rUNCr6gTLSn2vE9pXO84tHDXtm4g3iSdWdhFhLU3oCyRcG/KtPRVzp2K738Oh4twKxsfCqm+8/HOBG1N0g9SsEv6tSNdxX8Rax62Csbr43h3kMxUfI3qbfnz7nKJO5XOxapqFMCnMc4TF0+IUbNnYc4PPEJFuHRorQxf1DpKMYfld6Abb7STkC8f78Fs+le1CtQnM7OfM/fO8T67Y8rHbb/g9L7b1yhwu6Y6+WwV2vtQM9FR3XfRujbIbYHP8+amaX0KqznlM49+L1VVz6q4or6OQ97tVa4ZzgNPCaB+qN177fwumlbk9KRru8pHSF9VcGLSke8op+mqHTYe67Mj/i+H8bkTHnfQXicgmuUXgTxhtKR4t8oHfFpjV2LgzER0ah3bP8qxnb8jefvTVd6ELlI6bayQmlH6GKlp4vj1eMyq7zriXYPmuHoPEuFjoZ62xy1QWkbcaeC31n14yWlV/rNVnEOou3DXpTxs5j/jn2IwxOfYIU6bkRXzFeJbj7+eozBiiNaEuex1Cr3v0d0v2ZMPkw3qE9k4Dd6PVoxHfEnI7rnUZjIzhqS3RYh7PFJTMczMaJ7fgqTlPsrCLHBYPLHv1vl/i3RTHsORi/HV9ZxXQZ+o9ejEdQbVrm/FtE9DwD1G+ue20F9MAO/0+txFGalYRKPMBKHJz7BCnU0Y5Jobw95r7HoZzAp6/jfGfh9fg87IVOhl2eHudexaEdSoTu1j2Xg9/k97KmLPxM+6nURJqL4J+pN62XzeM4q/0LCrdhqAnULpq49QrwJwHEckx3/n/8Y8l6t6NwUW48vZuD3+T3sTRn3gDol5L1Ow+RJbQX1gQz8Pr+HvSnjm8S/Z5M4PPEJVrjD3ndFoR8e6ff7Degk1w7rHrvxE4rO3nG79Tu2gfqLAN8fid551X5Ew7uEN4BpHU3oJzErdKJ1kL1GpoH6OaaOPUV8yZ1xH4ejpzwVqHsI5vScgZnSU+jVeoMD3CcLh73x3l6CPc29EdQX0J26QkfPooompnHYU9fr0Q8m9vv9/dAP39xr3ecV4ltEEfcxGr3oQYFajL3lRDyHODzxCVbIYz7GAN+Dt6XqI9Fz16sc310F6uQM/J4wx1DMaLML1H/HW4c0GdT/Qi/XtfV4mGQfSRDHcSiodkzOzWyP3zsJ1PcwuR7d6HB/Xjt3+/gUJlz/a1BTPXxnCHrl1WJM3WinXjJ/Po5/w+28eclhGYN2dN5yfPcFktv4M66jBTNA2IreO8iLU3yopZ29alGh286oDPymMMeJGGd2Jaj3x/R3xOGJT7DCHv+EGVlsQzs+F6Iz7Q9BjzTmoMPNj2DC2QrUFvSc+5AM/I4ojhGgHnP8vrfQ+218FL28/lD0E5vPQ+dBPevQTqGnsiovLc7ncSQm90aht9K/Bp1XcJh1nIIe5d+JO4Kh0Bs7BhnxZvW4AJPf1I1+EO/laGf/EHTHPRu9F8n/A7XBocVu9DL80Rn4HVEcDZjtJ5T1W+8EdT66jUxDt5mPolcx/Qqzs7lCR0OuIr7tD5I+9ke3D/v3rUYPhM5Et4FD0Tb1fFA3YfatsY+X0Kv20v4dUR1/gRkw7SWe3CxxeOITrNDHbMzOoV6O19Dz90k9VyfJowEd3fmzDz0Wo53Eohhv59EC6juYqbp6Rxd6tUbwJ59n+zgKHeHxWjfaQd2MXqWWdtnjOM4F9boPPVagN/wcuB9V/o9G9OKNbR616EVvrpjsU9eTO8ajHX+Fzk+K+v5e++8G60XpaW5uprOzk5aWFrZv3552cVKlAZgFnA+cAhwEtADdwDrgT8BSYBHwUkplTJIRwCeAs4ETgVZgCLAbeAd4FVgCPAm8m04RE2UicBG6jhwDHGC9vx14C1gBLAaeAjpTKF/SnABcAJwGHAKMBfYAG4E3gRfQejwL7E2lhMkxGDgLOA84GZgCjES3lTbgdeC36LqxOqUyJkkL8Em0JicAE9Aa7QTWAK+gbcdCoCOVEibL+9D9R9R47b/F4bEQh0cQBEEQ8ofX/ntQgmUSBEEQBEFIhUI5PFdddRVvvfUWu3btYtmyZcycOTPtIgmCIAiCkAEK4/BccMEFLFiwgG9+85u8//3v59lnn+Xxxx/nwAMPTLtogiAIgiCkTGFyeJ5//nleeuklvvCFL/S998orr/Cf//mf3HDDDXW/Lzk8giAIgpA/SpXDM2TIEE466SQWLlzoen/hwoWcdtppFb/T1NREc3Oz6xAEQRAEoZgUwuEZN24cjY2NdHS4F/Z1dHTQ2tpa8TvXX389nZ2dfUdbW1sSRRUEQRAEIQUK4fDYKOWenWtoaBjwns1NN91ES0tL3zF58uQkiigIgiAIQgo0pl2AKNi4cSO9vb0Dojnjx48fEPWx6enpoaenJ4niCYIgCIKQMoWI8OzZs4fly5czZ84c1/tz5sxh6dKlKZVKEARBEISsUIgID8Btt93G97//fZYtW8Zzzz3HlVdeyUEHHcR3v/vdtIsmCIIgCELKFMbheeihh9h///356le/ysSJE1m1ahXnnHMO775bhqcbCYIgCIJQi8LswxMW2YdHEARBEPJHqfbhEQRBEARBqIU4PIIgCIIgFJ7C5PBEhey4LAiCIAj5wWu/LQ6PhS2Y7LgsCIIgCPmjubm5Zg6PJC07mDRpUuQJy83NzbS1tTF58mRJho4Z0ToZROdkEJ2TQXROhrh1bm5uZt26dTWvkQiPg3pihWH79u3SmBJCtE4G0TkZROdkEJ2TIS6dvdxTkpYFQRAEQSg84vAIgiAIglB4xOGJme7ubr72ta/R3d2ddlEKj2idDKJzMojOySA6J0MWdJakZUEQBEEQCo9EeARBEARBKDzi8AiCIAiCUHjE4REEQRAEofCIwyMIgiAIQuERhydmrrrqKt566y127drFsmXLmDlzZtpFyjWnn346P//5z2lra0MpxXnnnTfgmvnz59PW1kZXVxfPPPMMRx99dAolzTfXXXcdL774Ip2dnXR0dPDII49w+OGHD7hOtA7H5z//eVasWMG2bdvYtm0bS5cu5eyzz3ZdIxpHz3XXXYdSittvv931vmgdnvnz56OUch3t7e0DrklLZyVHPMcFF1yguru71RVXXKGOPPJIdfvtt6vt27erAw88MPWy5fU4++yz1T//8z+ruXPnKqWUOu+881yfX3vttWrbtm1q7ty56phjjlEPPvigamtrU6NGjUq97Hk6Hn/8cXXppZeqo48+Wh133HHqF7/4hVqzZo0aMWKEaB3h8Vd/9Vfqox/9qDrssMPUYYcdpr7xjW+o7u5udfTRR4vGMR0nn3yyeuutt9TLL7+sbr/99r73Retojvnz56uVK1eqCRMm9B3jxo3Lis7pC1TU4/nnn1d33323671XXnlFfetb30q9bEU4Kjk869atU9dee23fv5uamtSWLVvUlVdemXp583yMGzdOKaXU6aefLlrHfGzatEn99V//tWgcwzFy5Ej12muvqQ9/+MPqmWeecTk8onU0x/z589Xvf//7qp+nqbNMacXEkCFDOOmkk1i4cKHr/YULF3LaaaelVKpiM23aNCZOnOjSvKenhyVLlojmIRk9ejQAmzdvBkTrOBg0aBAXXnghI0eO5LnnnhONY+Cuu+7il7/8JYsWLXK9L1pHy2GHHUZbWxtvvfUWDz74INOmTQPS11keHhoT48aNo7GxkY6ODtf7HR0dtLa2plSqYmPrWknzgw8+OI0iFYbbbruNZ599ltWrVwOidZRMnz6d5557jmHDhrFjxw7mzp3LH//4Rz7wgQ8AonFUXHjhhZx44onMmDFjwGdSn6PjhRde4HOf+xyvv/46EyZM4Ctf+QpLly7lmGOOSV1ncXhiRinl+ndDQ8OA94RoEc2j5Tvf+Q7HHXdcxYR70To8r732GieccAJjxozhk5/8JA888ACzZs3q+1w0Ds+UKVP413/9V84666yajzYQrcPzxBNP9L1etWoVzz33HG+++SaXXnopzz//PJCezjKlFRMbN26kt7d3QDRn/PjxA7xbIRrWr18PIJpHyB133MG5557Lhz70Idra2vreF62jY8+ePbz55pssX76cG264gRUrVvD3f//3onGEnHTSSUyYMIHly5ezZ88e9uzZw+zZs5k3bx579uzp01O0jp6uri5WrlzJYYcdlnqdFocnJvbs2cPy5cuZM2eO6/05c+awdOnSlEpVbN5++23a29tdmg8ZMoRZs2aJ5gG48847Of/88znjjDNYs2aN6zPROj4aGhoYOnSoaBwhixYtYvr06Zxwwgl9x+9+9zt+8IMfcMIJJ/DWW2+J1jHR1NTEUUcdRXt7eybqdOpZ3UU97GXpl19+uTryyCPVbbfdprZv364OOuig1MuW12PkyJHq+OOPV8cff7xSSqkvfvGL6vjjj+9b6n/ttdeqLVu2qE984hPqmGOOUT/4wQ9kaWmA46677lJbtmxRH/zgB13LS4cNG9Z3jWgd/vjmN7+pZs6cqQ4++GA1ffp09Y1vfEP19vaqM888UzSO+ei/Sku0jub4l3/5F/XBD35QTZ06VZ1yyinq5z//udq2bVtfv5eyzukLVOTjqquuUm+//bbavXu3WrZsmWtZrxz+j1mzZqlK3HfffX3XzJ8/X61bt07t2rVLLV68WB1zzDGplztvRzUuvfRS13Widbjj//7f/9tnHzo6OtSTTz7Z5+yIxvEe/R0e0Tqaw95Xp7u7W7333nvqpz/9qTrqqKMyoXOD9UIQBEEQBKGwSA6PIAiCIAiFRxweQRAEQRAKjzg8giAIgiAUHnF4BEEQBEEoPOLwCIIgCIJQeMThEQRBEASh8IjDIwiCIAhC4RGHRxAEQRCEwiMOjyAIgiAIhUccHkEQCs/tt9/OI488knYxBEFIEXF4BEEoPDNmzODFF19MuxiCIKSIPEtLEITC0tjYyM6dO2lqaup774UXXuDUU09NsVSCIKRBY9oFEARBiIu9e/cyc+ZMXnzxRY4//ng6OjrYvXt32sUSBCEFxOERBKGwKKWYNGkSGzdu5A9/+EPaxREEIUUkh0cQhELz/ve/nxUrVqRdDEEQUkYcHkEQCs0JJ5wgDo8gCOLwCIJQbI499liZzhIEQRweQRCKzaBBgzjuuOOYOHEiLS0taRdHEISUEIdHEIRC85WvfIULL7yQdevW8dWvfjXt4giCkBKyD48gCIIgCIVHIjyCIAiCIBQecXgEQRAEQSg84vAIgiAIglB4xOERBEEQBKHwiMMjCIIgCELhEYdHEARBEITCIw6PIAiCIAiFRxweQRAEQRAKjzg8giAIgiAUHnF4BEEQBEEoPOLwCIIgCIJQeP4/cZ4Fv1Dm5tcAAAAASUVORK5CYII=\n",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -231,7 +242,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 7,
    "id": "5c43792b",
    "metadata": {
     "scrolled": false
@@ -267,14 +278,6 @@
       "\tFinished SciPy.\n",
       "\tFinished CyRK Numba.\n",
       "\tFinished CyRK Cython.\n",
-      "Working on end_time = 1.0e+04.\n",
-      "\tFinished SciPy.\n",
-      "\tFinished CyRK Numba.\n",
-      "\tFinished CyRK Cython.\n",
-      "Working on end_time = 1.0e+05.\n",
-      "\tFinished SciPy.\n",
-      "\tFinished CyRK Numba.\n",
-      "\tFinished CyRK Cython.\n",
       "Done!\n"
      ]
     }
@@ -283,7 +286,8 @@
     "print('This can take a while...\\n')\n",
     "# Run Results\n",
     "# rtols = np.logspace(-3, -13, 11)\n",
-    "end_times = np.logspace(-2, 4, 7)\n",
+    "# end_times = np.logspace(-2, 4, 7)\n",
+    "end_times = np.logspace(-2, 3, 6)\n",
     "\n",
     "sci_times = list()\n",
     "nb_times = list()\n",
@@ -309,13 +313,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 11,
    "id": "b8ad4501",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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RkUG7du145ZVXWL58OZs2bWLTpk0sXryYl19+mcOHD9O0aVMMw2DNmjWl3u6sWbP417/+hc1m45NPPvHgHomIiPjSUvIucJyG84UUyeQVdf651QmosCuSb66KLaj4v8p/b72mD7xV8Z8/f54ffviBUaNGcccdd1CxYkWSkpL4xz/+wV//+lcAHn/8cSZNmsQXX3xBcHAwhw8f5k9/+tMNbXf9+vUcP36cuLg4jh/3z7kHIiIinrEUWA50A3oB0eTdssz/9241tBS92O12wzAMw263F+pr1KiRMX/+fKNRo0Y3uJ3+hsWSbIBx1ZJgQH+/77+nl6CgIOPMmTNG//7m3rdq1ar5PQbw5L+xsrnYbDajb9++hs1m83ssWpQPsy3Kh3kWX+SipHrk2kUzdn63FLs9hvT0e/Hlkyd8yWKxULduXUaPHs25c+dYsWKFv0MSEREJSCrsTMBiycUfNzH0ldDQUOLj40lKSuK5555z60bHIiIi4joVduJ1CQkJWCwWf4chIiIS8HS7ExEREZEAocKuCJGRkcTFxbFt2zZ/hyIiIiLiMhV2RfDNs2JFREREPEuFnYiIiEiAUGEnIiIiEiBU2ImIiIgECBV2Ih5w7NgxRowY4e8wRESknFNhV07deuutTJ8+nSNHjpCVlUViYiIrVqzgwQcfdHkdc+fOxTAMDMMgOzubhIQEoqKiuOWWW5zGFVX0TJo0ifT0dLp37w7Ahg0bCA8PL9W+hIeHYxgGq1evdmqvVq0ahmHQtWvXUq1XRESkrNENik3AsBhwG1AVOA8kkPfENy9p1KgRW7Zs4ezZs7zyyivs3r2bihUr0rNnT2bMmEGzZs1cXtfq1auJiIigQoUK3H333cyZM4dbbrmFp556qsjxVquVf/zjHzz88MM8+OCDxMbGemSfsrOz6dGjB926dSMmJsYj6xQRESlrNGNXBJ/ex64ZZPw2A54DBpD3OjKv3VuioqIwDIP27duzePFiDh06xL59+5gyZQodOnQAYPbs2axcudLp52w2G8ePHyciIsLRdunSJVJTU0lJSWHdunUsWLCAhx56qMjtVqpUiUWLFhEWFkaXLl1KLOrGjRtHQkICWVlZpKSkMG3atBL36cKFC8ydO5eJEycWO6Zr164YhkG1atUcbS1btsQwDBo1agTkzf4lJCTQp08fDhw4wIULF1i0aBFVqlTh2Wef5dixY6SlpTF9+nSsVuevj91u57PPPiMjI4OUlBReeOEFp/5Ro0axe/duzp8/T2JiIjNmzCA4OLjE/RIREXGHCrsi+Ow+ds2AgWBUvWZ67ua8dm8Ud9WrV6dXr17MmDGDixcvFuo/d+4cALNmzaJXr17UrVvX0de7d2+qVq3KwoULi1x348aN6dWrF9nZ2YX6qlatyr///W+aN2/OAw88wIEDB4qN8fHHH2fUqFH8/ve/584776Rfv37s2bPnuvv25ptv0qJFCx5//PHrji1JUFAQL730Ek888QS9evWiW7duLFmyhN69e9O7d28GDx7M0KFDGTBggNPPjRkzht27d9OmTRveeecdpkyZwq9//WtHf25uLi+99BL33HMP4eHhPPjgg7z33ns3FKuIiMjVdCjWXyxAr6veX9tn5PcfwKOHZZs0aYLVai2xsALYunUrP/30E4MHD+b9998HICIigkWLFnHhwgXHuL59+5KRkYHNZiMoKAjIm5m61uuvv05GRgZ33303J0+eLNRfcK4dQGhoKCdOnGD9+vVcuXKFpKQktm/fft19O378ONOmTWPChAksW7bsuuOLU6lSJYYNG8bRo0cB+Oqrrxg8eDC33norFy5cYP/+/WzYsIHu3bs7Fblbtmzh3XffBeDQoUM88MADjBo1ivXr1wM4zTrGx8fz+uuvM3PmTIYPH17qWEVERK6mGTt/aQRUo3BRV8CS39/Is5u1WPI2aBjXrxZnzZrlOOxau3Zt+vTpw5w5c5zGbNiwgVatWnHfffcxffp0oqOj+fDDDwuta+3atQQHBzN27NjrbnfRokUEBQVx9OhR/v73v9OvXz9sNpsru8e7775L7dq1GTJkiEvji3LhwgVHUQeQmppKfHy8U0GbmppKnTp1nH5u69athT5ffb5it27dWLt2LcnJyaSnpzN//nxq1apFlSpVSh2riIjI1VTY+UtVD49z0aFDh8jNzXXpAon58+dz++2306FDB5555hni4+P59ttvncZcuHCBI0eOsGfPHkaMGEHlypUZN25coXV9/fXXPPLIIwwdOpTp06eXuN3k5GTuuusuhg8fTmZmJlFRUWzatIkKFa4/wXzu3Dneeecdxo0bV6hgys3NBf5b3AJUrFix0DquXLni9Lngqt9r2649x64oBQV0aGgoq1atYu/evTz++OO0bdvWMVNXVAwiIiKlocLOX857eJyLzpw5w5o1axg+fHiRM0VXX1iQlpbGsmXLiIiIICIigrlz5153/ePHj+ePf/wj9erVK9S3fv16+vbty5AhQ/joo49KXE9WVhYrV65kxIgRdOvWjY4dO9KiRQsX9hA+/PBDcnNzC91ipeAQ8NWxtWrVyqV1uqLgwpOrPxcc8m7Xrh0VKlRg9OjR/PDDDxw6dIj69et7bNsiIiKgws5/EoBzFH/+nJHfn+D5TUdGRmKz2di2bRuPPfYYTZo0oWnTprz44ouFDifOmjWL8PBwmjVrxieffHLddW/cuJG4uLhiD7lu2LCBPn36EB4ezowZM4ocEx4ezpAhQ2jevDmNGzdm8ODBXLx4kYQE134Zly5dYty4cbz00ktO7YcPHyYxMZE333yTO++8k969ezN69GiX1umKBx54gDFjxnDnnXcSGRnJ//7v/zrOqzty5AgVK1bkxRdfpHHjxjzzzDP84Q9/8Ni2RUREQIWd/xhA9FXvr+0jv98L97OLj4+nTZs2bNiwgQ8++IC9e/eybt06evTowbBhw5zGrl+/nuPHj7NmzRqOHz/u0vonT57M888/T4MGDYrs37hxo+Pq0pkzZxbqP3v2LM8//zxbtmxh9+7d9OjRg4cffpi0tDSX9/GTTz5xOk8O8g6xPvnkkzRt2pRdu3bx6quv8uc//9nldV7PBx98QNu2bdm5cyevv/46o0ePZu3atQDs2rWLUaNG8eqrr7J3716efvppXnvtNY9tW0REpIChpejFbrcbhmEYdru9UF+jRo2M+fPnG40aNbqx7TTDsIy2GLzJf5dRee3+3n/ACAoKMs6cOWP079/f77H4aqlWrZrfYwAP/hsro4vNZjP69u1r2Gw2v8eiRfkw26J8mGfxRS5KqkeuXXS7E3/bD/bjdtJvSffZkydcYbFYqFu3LqNHj+bcuXOsWLHCvwGJiIjIdamwK0JkZCTDhw936apHT7AYFoj3yaZcFhoaSnx8PElJSTz33HPk5OT4OyQRERG5DhV2RYiKiiIqKgq73U56erq/w/GLhIQEp9uCiIiIiPnp4gkRERGRAKHCTkRERCRAqLATERERCRAq7EREREQChAo7ERERkQChwk5EREQkQKiwE7kOwzB49NFH/R2GiIjIdamwK6duvfVWpk+fzpEjR8jKyiIxMZEVK1bw4IMPuryOuXPnYhgGhmGQnZ1NQkICUVFR3HLLLU7jjh07xogRI5zaJk2aRHp6Ot27dwdgw4YNhIeHl3p/KlasyJgxY/jPf/7DhQsXOHnyJN9++y3PPfccFSq4drvGcePGsXPnzlLHICIi4m+6QbEJWC0GXZtBvVvg+FnYfAByvfhIsUaNGrFlyxbOnj3LK6+8wu7du6lYsSI9e/ZkxowZNGvWzOV1rV69moiICCpUqMDdd9/NnDlzuOWWW3jqqaeKHG+1WvnHP/7Bww8/zIMPPkhsbOwN70/FihVZs2YNLVu25PXXX2fLli2kp6fToUMH/vjHP7Jz50527dp1w9sRERExO83Y+Vn/drDnLxnE/Bm+eAFi/gzx0/LavSUqKgrDMGjfvj2LFy/m0KFD7Nu3jylTptChQwcAZs+ezcqVK51+zmazcfz4cSIiIhxtly5dIjU1lZSUFNatW8eCBQt46KGHitxupUqVWLRoEWFhYXTp0qXEom7cuHEkJCSQlZVFSkoK06ZNK3bsyJEj6dKlCz169CAqKopdu3Zx7NgxvvjiC+677z4OHTrE4MGDOXXqFJUqVXL62a+++opPPvmE8PBw3nzzTVq1asXZs2cxDMNpBrFWrVosWbKECxcucPDgQR5++GGn9XTp0oUffviBrKwsfv75Z9555x1sNpujf8OGDUybNo13332X06dPc/z4ccaNG1fsPomIiJSGCjs/6t8OvhoJ9W5xnp4LqZ7X7o3irnr16vTq1YsZM2Zw8eLFQv3nzp0DYNasWfTq1Yu6des6+nr37k3VqlVZuHBhketu3LgxvXr1Ijs7u1Bf1apV+fe//03z5s154IEHOHDgQLExPv7444waNYrf//733HnnnfTr1489e/YUO/7pp59m/fr1/Oc//ynUd+XKFS5evMiiRYuw2Ww88sgjjr6aNWvSt29f5s6dy4IFC5g0aRJ79+7lV7/6FXXr1mXBggWOsePGjWPhwoXce++9rFq1is8++4zq1asDUL9+fVatWsX27dtp2bIlw4YN47e//S1//vOfnWIJDw/nwoUL3Hfffbzyyiu88cYb/PrXvy52v0RERNylws5PrBaY9ux/3zv1WQEDpg4u3HejmjRpgtVqLbGwAti6dSs//fQTgwcPdrRFRESwaNEiLly44Gjr27cvGRkZXLx4kaNHj9K8eXPefffdQut7/fXXadWqFZ07dyYpKalQf/fu3fnkk08ACA0N5cSJE6xfv56kpCS2b9/OrFmzio31zjvvvO7+ZGVl8fnnnzvNNj799NMkJycTExNDVlYW58+f58qVK/zyyy+kpqaSlZXlGDtv3jy+/PJLjhw5wtixYwkODqZ9+/YAREZGkpSUxAsvvMBPP/3E8uXLGTduHKNHj3Z63u7u3bt56623OHz4MJ9++imxsbH06NGjxLhFRETcocKuCJGRkcTFxbFt2zavbaNzU2hYs/jCzWqF0Fp54zypoNAwjOufxDdr1ixHIVS7dm369OnDnDlznMZs2LCBVq1acd999zF9+nSio6P58MMPC61r7dq1BAcHM3bs2Otud9GiRQQFBXH06FH+/ve/069fP6fDmkXtkyv7849//IOHHnqI+vXrA3mF6rx58677c5BXlBW4ePEiGRkZ1KlTB4BmzZqxdetWp/FbtmzBbrfToEGDItcBcPz4ccc6REREPEGFXRGioqJo3ry5Y0bGG+rd4tlxrjp06BC5ubkuXSAxf/58br/9djp06MAzzzxDfHw83377rdOYCxcucOTIEfbs2cOIESOoXLlykeeOff311zzyyCMMHTqU6dOnl7jd5ORk7rrrLoYPH05mZiZRUVFs2rSp2KtbDx486NL+/Oc//2HXrl08++yztG7dmhYtWrhc2F17eNkwDKzWvK9PUYVlUQV0SesQERHxBP1V8ZPjZz07zlVnzpxhzZo1DB8+nCpVqhTqr1atmuN9Wloay5YtIyIigoiICObOnXvd9Y8fP54//vGP1KtXr1Df+vXr6du3L0OGDOGjjz4qcT1ZWVmsXLmSESNG0K1bNzp27EiLFi2KHPv555/z61//mlatWhXqs9lsTvtZMAs5ZMgQ1q9fT3JysqPv8uXLJc4MFmffvn107NjRqa1jx46kp6eTkpLi9vpERERKS4Wdn2w+AEmnITe36P7cXEg8lTfO0yIjI7HZbGzbto3HHnuMJk2a0LRpU1588cVChxRnzZpFeHg4zZo1c5wDV5KNGzcSFxdX7CHXDRs20KdPH8LDw5kxY0aRY8LDwxkyZAjNmzencePGDB48mIsXL5KQkFDk+KlTp7Jlyxa+/vprIiMjuffee2ncuDH/+7//yw8//MCdd97pGPvZZ58REhLC888/X+iwcnx8PI0bN6ZFixbUrFmz0BW0xYmKiqJhw4Z8+OGH3HXXXTzyyCOMHz+eyZMnu3SIWERExFNU2PlJrgEj5gOWwvesy83Nax/5qXfuZxcfH0+bNm3YsGEDH3zwAXv37mXdunX06NGDYcOGOY1dv349x48fZ82aNRw/ftyl9U+ePJnnn3/e6fyyq23cuJHevXszePBgZs6cWaj/7NmzPP/882zZsoXdu3fTo0cPHn74YdLS0opc3+XLlwkLC+O9997j97//Pd9//z3bt2/npZdeYvr06ezdu9cxNiMjg8WLF3P+/HmWLVvmtJ7FixcTHR3NypUrOXXqFE8++aRL+/vzzz/Tu3dv2rdvz65du/j444+ZPXs2f/nLX1z6eREREU8ytBS92O12wzAMw263F+pr1KiRMX/+fKNRo0Y3tI3+7TCSP7IYxmc4loRpee3+3n/ACAoKMs6cOWP079/f77F4alm7dq0xbdq0YvurVavm9xjBc//Gyupis9mMvn37Gjabze+xaFE+zLYoH+ZZfJGLkuqRaxc9ecLPlsZCzGE799ZL99mTJ1xhsVioW7cuo0eP5ty5c6xYscK/AXlA9erVeeihh3jwwQd54YUX/B2OiIiIx6mwM4Fcw8LG/f6OwlloaCjx8fEkJSXx3HPPkZOT4++QbtiPP/5I9erVefXVVzl48KC/wxEREfE4FXZSpISEBKeb6waCxo0b+zsEERERr9LFEyIiIiIBQoVdKRXcxqK4m+aK3KiCf1u6ZYqIiLhKhV0pnT59GoCmTT38zC+RfAX/tk6dOuXnSEREpKzQdFMpXbhwgZiYGAYOHAjAgQMHuHLlSqnWZbfbueWWWzwYndwIf+ejQoUKNG3alIEDBxITE8PFixf9FouIiJQtKuxuQMEjtgYNGnRD6wkKCiIzM9MTIYkHmCUfMTExLj3GTUREpIAKuxtgGAZz5szhyy+/pFatWqW6itRms9GlSxc2bdoUELcUKevMkA/DMDh16pRm6kRExG0q7Dzg4sWLJCYmlupnbTYbp06dIiEhQYWdCSgfIiJSluniCREREZEAEfCFXYMGDdiwYQNxcXHs2rWLAQMG+DskEREREa8I+EOxV65cYeTIkezatYvatWvz448/smrVKp2/JCIiIgEn4Au7EydOcOLECQBOnjxJWloaNWrUUGEnIiIiAcf0h2I7d+7MihUrSElJwTAMHn300UJjhg0bxtGjR8nMzCQ2NpZOnToVua62bdtitVpJTk72dtgiIiIiPmf6wi44OJhdu3bxwgsvFNk/cOBApk6dyoQJE2jdujWbN29m9erVNGzY0GlcjRo1mD9/PkOHDvVF2CIiIiI+Z/pDsdHR0URHRxfb//LLLzN79mxmz54NwKhRo+jZsyfDhg1j7NixAFSqVImlS5fyzjvvsHXrVp/ELSIiIuJrpi/sSlKxYkXatm3LxIkTndrXrl1Lx44dHZ/nzZvHN998wz//+c8S11epUiUqV67s+Gy324G8e5vZbDYPRv5fNpsNq9XqtfWLe5QP81AuzEX5MBflwzx8kQt31l2mC7tatWpRoUIFUlNTndpTU1OpW7cuAA888ACDBg1i9+7d9OvXD4DBgwezd+/eQut77bXXePPNNwu1h4WFee0RUzabjTZt2mCxWHRDXBNQPsxDuTAX5cNclA/z8EUugoKCXB5bpgu7AoZhOH22WCyOti1btrhc6b7zzjtMnjzZ8dlut5OSksK6devIyMjwXMBXsdlsGIZBdHS0vpwmoHyYh3JhLsqHuSgf5uGLXBQcQXRFmS7sTp06xZUrVxyzcwXq1KlTaBbPFZcvX+by5cuF2nNycrz6xcnNzfX6NsR1yod5KBfmonyYi/JhHt7OhTvrNf1VsSXJzs5mx44dhIWFObWHhYXx3XfflXq9kZGRxMXFsW3bthsNUURERMRnTD9jFxwcTJMmTRyfGzduTMuWLUlLSyMpKYnJkyfz6aefEhsby9atWxk6dCihoaF8/PHHpd5mVFQUUVFR2O120tPTPbEbIiIiIl5n+sKuXbt2xMTEOD5PmTIFyLvSNSIigoULF1KzZk3eeOMN6tWrx969e+nduzeJiYl+ilhERETEP0xf2G3cuBGLxVLimJkzZzJz5kwfRSQiIiJiTmX6HDtv0Tl2IiJiXlagK9Al/1V/yuW/9K+hCFFRUTRv3pz27dv7OxQREZGr9Afiga+BMfmv8fntIirsREREyoj+wFdAyDXtIfntKu5EhZ2IiEgZYAWmXfX+2j6AqUX0SXmjfwEiIiKm1xloSPF/tq1AaP44Kc9U2BVBF0+IiIi51PPwOAlUKuyKoIsnRETEXI57eJwEKhV2IiIiprcZSAJyi+nPBRLzx4nPWIDbgEb5ryXfdtcnTH+DYhEREckFRpB39WsuzvMyBcXeSIov/MTjmgG9gFuAO4E6wFkgGtjvt6g0YyciIlI2LAUGACnXtCfnty/1eUTlVjNgIHDzNe0357c383lEDirsiqCLJ0RExJyWknfMrwfwfv5rY1TU+ZCFvJm6gvfX9pHf76fDsirsiqCLJ0RExLxygY3ApvxXHX71qUZANYov3Cz5/Y18FpETFXYiIiIirqrq4XEepsJORERExFXnPTzOw1TYiYiIiLgqATgHGMX0G/n9CT6LyIkKOxERERFXGeTd0qTg/bV95PcXV/h5mQo7EREREXfsBxYC6de0p+e3+/E+drpBcREiIyMZPnw4VqvqXhERESnCfuAAcDt5tzeJBo7it5m6AqpciqDbnYiIiMh1GUA8eefTxeP3og5U2ImIiIgEDBV2IiIiIgFChZ2IiIhIgFBhJyIiIlIKVgt0bQZdmua9Wv30fNir6apYERERETf1bwfTnoWGtYD6MKYNJJ2CEfNhaaz/4tKMXREiIyOJi4tj27Zt/g5FRERETKZ/O/hqJITUcG4PqZ7X3r+dP6LKo8KuCLrdiYiIiBTFasmbqSt479RnBQyYOth/h2VV2ImIiIi4qHNTaFiz+MLNaoXQWnnj/EGFnYiIiIiL6t3i2XGepsJORERExEXHz3p2nKepsBMRERFx0eYDkHQacnOL7s/NhcRTeeP8QYWdiIiIiItyjbxbmmApXNzl5ua1j/w0b5w/qLATERERccPSWBgwFVLOOLcnp+W1+/M+drpBsYiIiIiblsbC8h3QrTn06gXR0RAT57+ZugIq7ERERERKIdeAjfuhym15r/4u6kCHYoukJ0+IiIhIWeTSjN2LL77o9ornzp3L+fPn3f45M4iKiiIqKgq73U56erq/wxERERFxiUuF3dSpU0lOTiYnJ8ellTZs2JB//etfZbawExERESmLXD7Hrl27dpw8edKlsZrlEhEREfE9l86xGz9+vFuzb3/9619JS0srdVAiIiIi4j6XZuzeeustt1Y6ceLEUgUjIiIiIqXn9lWxN910E0FBQY7PoaGhjBgxgrCwMI8GJiIiIiLucbuwW758Oc8++ywA1apV44cffmD06NEsX76cP/zhDx4PUERERERc43Zh16ZNGzZv3gzAgAEDSE1NpVGjRjz77LO89NJLHg9QRERERFzjdmFXpUoVMjIyAHjooYdYsmQJhmHw/fff06hRI48HKCIiIiKucbuwO3z4MP369aNBgwb07NmTtWvXAlCnTh3d5kRERETEj9wu7N566y0mTZpEfHw8P/zwA99//z2QN3u3c+dOjwcoIiIiIq5x+QbFBRYvXkxoaCj16tVj165djvavv/6apUuXejQ4EREREXGd24UdQGpqKqmpqU5t27dv90hAIiIiIlI6bhd2lStX5sUXX6R79+7UqVMHq9X5aG7btm09Fpy/REZGMnz48EL7JiIiImJmbhd2c+bMISwsjK+++opt27ZhGIY34vKrqKgooqKisNvtuiBEREREygy3C7s+ffrQu3dvvvvuO2/EIyIiIiKl5PaxxpSUFMd97ERERETEPNwu7EaPHs27775LaGioN+IRERERkVJy+1BsbGwsN910E0ePHuXixYtkZ2c79desWdNjwYmIiIiI69wu7L744gtCQkIYO3YsqampAXnxhIiIiEhZ5HZh17FjR+6//352797tjXhEREREpJTcPsfuwIEDBAUFeSMWEREREbkBbhd2f/rTn/jggw/o2rUrNWrUwG63Oy0iIiIi4h9uH4qNjo4G8p4NezWLxYJhGFSoUKqnlImIiIjIDXK7Cuvevbs34hARERGRG+R2Ybdp0yZvxCEiIiIiN8ilc+xatGiBxWJxeaV33303Nput1EGJiIiIiPtcKux27tzp1o2Ht27dqidTiIiIiPiYS4diLRYLb7/9NhcvXnRppZUqVbqhoERERETEfS4Vdps2beKuu+5yeaVbt24lMzOz1EGJiIiIiPtcKux0JayIiIiI+bl9g+KyaMmSJaSlpbFo0SJ/hyIiIiLiNeWisJs+fTrPPvusv8MQERER8apyUdjFxMSQkZHh7zBEREREvMr0hV3nzp1ZsWIFKSkpGIbBo48+WmjMsGHDOHr0KJmZmcTGxtKpUyc/RCoiIiLiX6Yv7IKDg9m1axcvvPBCkf0DBw5k6tSpTJgwgdatW7N582ZWr15Nw4YNfRypiIiIiH+5/UgxgGeeeYY//OEPNG7cmPvvv5/ExERGjBjBsWPHWLFihUcDjI6OJjo6utj+l19+mdmzZzN79mwARo0aRc+ePRk2bBhjx451a1uVKlWicuXKjs92ux0Am83mtSdp2Gw2rFarntRhEsqHeSgX5qJ8mIvyYR6+yIU763a7sPvDH/7AW2+9xdSpU/m///s/x8bOnj3LyJEjPV7YlaRixYq0bduWiRMnOrWvXbuWjh07ur2+1157jTfffLNQe1hYmNfuy2ez2WjTpg0Wi4WcnByvbENcp3yYh3JhLsqHuSgf5uGLXAQFBbk81u3C7sUXX+T5559n+fLl/OlPf3K0x8bGMmnSJHdXd0Nq1apFhQoVSE1NdWpPTU2lbt26js/R0dG0adOG4OBgkpKS6N+/P7GxsYXW98477zB58mTHZ7vdTkpKCuvWrfPaxRc2mw3DMIiOjtaX0wSUD/NQLsxF+TAX5cM8fJGLgiOIrnC7sGvcuDE7d+4s1H7p0iWCg4PdXZ1HGIbh9NlisTi19erVy6X1XL58mcuXLxdqz8nJ8eoXJzc31+vbENcpH+ahXJiL8mEuyod5eDsX7qzX7Ysnjh07RqtWrQq1/+Y3v2Hfvn3uru6GnDp1iitXrjjNzgHUqVOn0CyeiIiISKBze8bu/fffZ8aMGdx0001YLBbat2/Pk08+yWuvvcbvfvc7b8RYrOzsbHbs2EFYWBjLli1ztIeFhbF8+fJSrzcyMpLhw4djtZr+omERERERB7cLu3nz5lGhQgXee+89qlSpwueff05KSgojRoxgwYIFHg8wODiYJk2aOD43btyYli1bkpaWRlJSEpMnT+bTTz8lNjaWrVu3MnToUEJDQ/n4449Lvc2oqCiioqKw2+2kp6d7YjdEREREvK5UtzuZNWsWs2bNombNmlitVk6ePOnpuBzatWtHTEyM4/OUKVOAvAIzIiKChQsXUrNmTd544w3q1avH3r176d27N4mJiV6LSUSkfLECXYEuwEUgBsj1Z0AiUoxSFXYFTp8+7ak4irVx40YsFkuJY2bOnMnMmTO9HouISPnTH5gGFNz0fQyQBIwAlvorKBEphtsnkdWoUYOPPvqIuLg4Tp48yenTp52WQBAZGUlcXBzbtm3zdygiIn7UH/gKCLmmPSS/vb/PIxKRkrk9Y/fPf/6TO+64g9mzZ5OamlroViOBQOfYiYhYyZupK3h/bV8uMBVYjg7LipiH24Vdp06d6NSpE7t37/ZGPCIiYgqd+e/h16JYgdD8cRt9EpGIXJ/bh2IPHDjg1qMtRESkLKrn4XEi4gtuF3aRkZFMmDCBLl26UKNGDex2u9MiIiKB4LiHx4mIL7h9KPbs2bNUq1aNb775xqm94DFeFSrc0IW2pqAbFIuIbCbv6tcQip4DyAWS88eJiFm4XYV99tlnXL58maeeekoXT4iIBKxc8m5p8lX+e+s1fQAj0YUTIubidmF3zz330Lp1aw4ePOiNeERExDSWAgNwvo8d5M3UjUT3sRMxH7ePNcbGxtKwYUlXSomISOBYCtwG9ADez39tjIo6EXNye8buww8/ZNq0abz//vvs2bOH7Oxsp/49e/Z4LDgRETGDXPJuaVIl/1WHX0XMyu3CbsGCBQDMmTPH0WYYhi6eEBEREfEzt6uwxo0beyMOU9HFEyIiIlIWuV3YJSYmeiMOEREREblBLhV2Dz/8MKtXr+bKlSs8/PDDJY5duXKlRwITEREREfe4VNgtW7aMunXrcvLkSZYtW1bsuEA5x05ERESkLHKpCrPZbI5bnNhsNq8GJCIiIiKl4/Jln8eOHaN27drejMU0IiMjiYuLY9u2bf4ORURERMRlLhd2FovFm3GYSlRUFM2bN6d9+/b+DkVERETEZbpRm4iIiEiAcOtKh9/97necP3++xDEffvjhDQUkIiIiIqXjVmH3hz/8gZycnGL7DcNQYSciIiLiJ24Vdu3atePkyZPeikVEREREboDL59gZhuHNOERERETkBumqWBERkTLEaoGuzaBL07xXq/48y1VcPhQ7fvz46144ESgiIyMZPnw4VqsuGhYREfPo3w6mPQsNawH1YUwbSDoFI+bD0lh/Rydm4HLl8tZbb5GZmenNWExD97ETERGz6d8OvhoJITWc20Oq57X3b+ePqMRsNCUlIiJiclZL3kxdwXunPitgwNTBOiwrKuxERERMr3NTaFiz+MLNaoXQWnnjpHxTYSciImJy9W7x7DgJXKUq7Gw2Gz169GDo0KFUrVoVgHr16hEcHOzR4ERERASOn/XsOAlcbt2gGCA0NJTo6GhCQ0OpXLky69at4/z587zyyivcdNNNDBs2zBtxioiIlFubD0DS6bwLJYq6YUNuLiSn5Y2T8s3tGbtp06YRGxtL9erVna6SXbp0KT169PBocCIiIgK5Rt4tTbDkvb+2DwuM/LRwn5Q/bs/YderUiQceeIDs7Gyn9oSEBEJCQjwWmIiIiPzX0gsw4DhMqw0NK/23PfkKjDyZ1y/idmFntVqx2WyF2hs0aEBGRoZHghIREZGrWIBesPQ8LL8A3apAr5sgOhliLubP1PUCDgCatSvX3D4Uu27dOkaOHOn4bBgGwcHBjB8/nlWrVnkyNr+JjIwkLi6Obdu2+TsUERERaARUI+9QLLAxEzZl5b3mktdOtfxxUq65XdiNGjWKrl27EhcXx0033cTnn39OfHw8ISEhvPrqq96I0ef05AkRETGVqh4eJwHL7UOxx48fp1WrVjz55JO0adMGq9XK7Nmz+eyzz8jKyvJGjCIiIuWbq49qLx+PdJcSuF3YAWRlZTF37lzmzp3r6XhERETkWgnAOeBm8g67XssA0vPHSbnmdmH38MMPF9luGAZZWVkcPnyY+Pj4G41LREREChhANDAw/73lmj7y+3XhRLnndmG3bNkyDMPAYnH+X4aCNsMw+Pbbb+nXrx9nz571VJwiIiLl235gIXlXv95yVXs6eUXdfj/EJKbj9sUTYWFhbN++nbCwMKpVq0a1atUICwtj27Zt9O3bly5dulCzZk0mTZrkjXhFRETKr/3AVGA+sCX/dSoq6sTB7Rm7adOmMXToULZu3epo++abb/jjH//I3//+d+655x5GjhzJnDlzPBqoiIiIkHe4NZ688+ni0eFXceL2jN0dd9xBenp6ofb09HRuv/12AA4dOkStWrVuPDoRERERcZnbhd2OHTt4//33nQq3WrVq8d5777F9+3YA7rzzTpKTkz0XpYiIiIhcl9uHYn/729+yfPlykpOTSUpKwjAMQkNDOXr0KI8++igAVatW5e233/Z4sCIiIiJSPLcLu4MHD9KsWTN69uzJr371KywWCwcOHGDdunUYRt6B/uXLl3s8UBEREREpWaluUAywZs0a1qxZ48lYREREROQGlKqwq1KlCl27diU0NJRKlSo59X344YceCUxERERE3ON2YdeqVStWrVpFlSpVCA4OJi0tjVq1anHx4kV++eWXgCjsIiMjGT58OFar29eWiIiIiPiN25XLlClTWLlyJTVq1CAzM5MOHTrQqFEjduzYwR//+EdvxOhzUVFRNG/enPbt2/s7FBERERGXuV3YtWrVig8++IDc3FxycnKoXLkyycnJvPLKK/z1r3/1RowiIiIi4gK3C7vs7GzH1a+pqamEhoYCcO7cOcd7EREREfE9t8+x27lzJ+3atePQoUNs2LCBt956i1q1ajF48GD27NnjjRhFRERExAVuz9iNHTuW48ePA/D6669z+vRpZs6cSZ06dRg6dKjHAxQRERER17g9Y3fy5Eni4uIAOHXqFH369PF4UCIiIiLiPrdm7CwWC4cOHaJBgwbeikdERERESsmtws4wDA4dOkTNmjW9FY+IiIiIlJLb59i98sorvP/++zRv3twb8YiIiIhIKbl9jt0///lPqlSpwq5du7h8+TKZmZlO/ZrNExEREfEPtwu7kSNHeiEMEREREblRbhd28+fP90YcIiIiInKDSvWU+9tvv523336bzz//nNq1awPQs2dP7r77bo8GJyIiIiKuc7uw69KlC3v27OG+++7jscceo2rVqgDce++9jB8/3uMBioiIiIhr3C7sJk6cyJ///GceeughLl++7GjfsGED999/v0eDExERERHXuV3YtWjRgqVLlxZqP3nypK6IFREREfEjtwu7s2fPUq9evULtrVu3JiUlxSNBiYiIiIj73C7sPv/8c959911uvfVWDMPAarXSsWNHJk2aZMorZvv06cOBAwc4ePAgv/3tb/0djoiIiIjXuF3Y/d///R+JiYmkpKRQtWpV9u3bx6ZNm/juu+/4y1/+4o0YS81mszF58mQefPBB2rRpw6uvvkr16tX9HZaIiIiIV7h9H7srV67wzDPP8MYbb9C6dWusVis7d+7k8OHD3ojvhrRv3564uDh+/vlnAFatWkXPnj358ssv/RyZiIiIiOeV6nYnAEePHmXx4sUsWrTIa0Vd586dWbFiBSkpKRiGwaOPPlpozLBhwzh69CiZmZnExsbSqVMnR1/9+vWdzvtLTk4mJCTEK7GKiIiI+Jvbhd26detISEjgnXfeoXnz5t6IySE4OJhdu3bxwgsvFNk/cOBApk6dyoQJE2jdujWbN29m9erVNGzYEACLxVLoZwzD8GrMIiIiIv7i9qHY+vXr88QTT/Dkk0/yyiuvsHfvXv75z3/y+eefe/yq2OjoaKKjo4vtf/nll5k9ezazZ88GYNSoUfTs2ZNhw4YxduxYUlJSnGboGjRowA8//FDs+ipVqkTlypUdn+12O5B3rp7NZrvR3SmSzWbDarV6bf3iHuXDPJQLc1E+zEX5MA9f5MKddbtd2J0+fZoZM2YwY8YMbrvtNp566imeffZZ/vrXv7Jp0yZ69Ojh7ipLpWLFirRt25aJEyc6ta9du5aOHTsCsG3bNu655x7q169Peno6vXv35q233ip2na+99hpvvvlmofawsDAyMzM9Gn8Bm81GmzZtsFgs5OTkeGUb4jrlwzyUC3NRPsxF+TAPX+QiKCjI5bFuF3ZXi4+PZ+LEiezatYu3336brl273sjq3FKrVi0qVKhAamqqU3tqaip169YFICcnh9GjR7NhwwasVivvvfceaWlpxa7znXfeYfLkyY7PdrudlJQU1q1bR0ZGhlf2w2azYRgG0dHR+nKagPJhHsqFuSgf5qJ8mIcvclFwBNEVpS7sOnbsyNNPP82AAQO46aabWLFiBWPHji3t6krt2nPmLBaLU9vKlStZuXKlS+u6fPmy02PSCuTk5Hj1i5Obm+v1bYjrlA/zUC7MRfkwF+XDPLydC3fW63ZhN2HCBJ588knq16/P+vXrGTlyJMuWLfPaocrinDp1iitXrjhm5wrUqVOn0CyeuyIjIxk+fDhWq9vXloiIR1iBrkAX4CIQA+T6MyARkTLB7cqlW7duTJo0iZCQEPr27csXX3zhKOpatmzp8QCLk52dzY4dOwgLC3NqDwsL47vvvruhdUdFRdG8eXPat29/Q+sRkdLoD8QDXwNj8l/j89tFRKQkbs/YPfDAA06fb775Zp5++ml+97vf0bJlSypUuKHT9pwEBwfTpEkTx+fGjRvTsmVL0tLSSEpKYvLkyXz66afExsaydetWhg4dSmhoKB9//LHHYhARX+oPfFVEe0h++wBgqU8jEhEpS0pdhXXv3p0hQ4bw2GOPkZCQwOLFiz3+LNZ27doRExPj+DxlyhQA5s2bR0REBAsXLqRmzZq88cYb1KtXj71799K7d28SExM9GoeI+IIVmHbV+2v7coGpwHJ0WFZEpGhuFXYhISE899xzDBkyhODgYBYuXEjFihV5/PHH2b9/v8eD27hxY5E3Gb7azJkzmTlzpke3q3PsRPyhM9CwhH4rEJo/bqNPIhIRKWtcrlz+/e9/s2/fPu6++25efPFF6tevz0svveTN2PxG59iJ+EM9D48TESl/XJ6xe+ihh5g+fTozZ8702rNhRaQ8O+7hcSIi5Y/LM3adO3fGbrcTGxvL999/z/Dhw6lVq5Y3YxORcmUzkETx58/lAon540REpCguF3bff/89Q4cOpV69evztb3/jiSeeICUlBavVSlhYGFWrVvVmnCIS8HKBEVe9v7YPYGQRfSIiUsDtqwMyMzOZO3cunTt3pkWLFnzwwQf86U9/4pdffmH58uXeiNHnIiMjiYuLY9u2bf4ORaScWUreLU1SrmlPRrc6ERG5vhu67PPgwYO8+uqrNGjQgCeffNJTMfmdLp4Q8aelwG1AD+D9/NfGqKgTEbk+j9xNODc3l+XLlwfMjJ2I+Fsuebc0qZL/qsOvIiKu0I3aRERERAKECjsRERGRAKHCrgi6eEJERETKIhV2RdDFEyIiIlIWqbATERERCRAq7EREREQChAo7ERERkQChwk5EREQkQKiwExEREQkQKuyKoNudiIiISFmkwq4Iut2JiIiIlEUq7EREpERWC3RtBl2a5r1aLf6OSESKU8HfAYiYhxXoCnQBLgIx6OHzUt71bwfTnoWGtYD6MKYNJJ2CEfNhaay/oxORa2nGTgSA/kA88DUwJv81Pr9dpHzq3w6+GgkhNZzbQ6rntfdv54+oRKQkKuxE6A98BYRc0x6S367iTsofqyVvpq7gvVOfFTBg6mAdlhUxGxV2Us5ZgWlXvb+2D2BqEX0iga1zU2hYs/jCzWqF0Fp540TEPPTXqgi63Ul50hloSPFfBSsQmj9OpPyod4tnx4mIb6iwK4Jud1Ke1PPwOJHAcPysZ8eJiG+osJNy7riHx4kEhs0HIOk05BZzYXhuLiSeyhsnIuahwk7Kuc1AEsXf1iQXSMwfJ1J+5Bp5tzTBUri4y83Nax/5ad44ETEPFXZSzuUCI656f20fwMgi+kQC39JYGDAVUs44tyen5bXrPnYi5qMbFIuwFBhA3tWxDa9qTyavqFvqh5hEzGFpLCz/Ebp1h15hEL0OYjYUf4hWRPxLhZ0IkFe8LQe6Ab2AaPTkCRGgGeT2go23QJVQ2NgFcu8l7yuy38+xiUghOhQr4pALbAQ25b+qqJNyrhkwELj5mvab89ub+TwiEbkOFXYiIlKYhbzJ64L31/aR368nT4iYigo7EREprBFQjeILN0t+fyOfRSQiLlBhVwTfPXnCCnQFuuS/Kh0iYhJVPTxORHxClUQRfPPkif5APPA1MCb/NR49cF5ETOG8h8eJiE+osPOL/sBXQMg17SH57SruRMTPEoBzQHE3IDby+xN8FpGIuECFnc9ZybtfWsH7a/sAphbRJyLiQwZ5tzQpeH9tH/n9evKEiKmoevC5zuTdBLe4X70VCM0fJyLiR/uBhUD6Ne3p+e26j52I6egGxT5Xz8PjRES8aD9wALid/967+yiaqRMxKc3Y+dxxD48TEfEyg7xruxLyX1XUiZiWCjuf2wwkUfxTDXKBxPxxIiIiIq5TYedzucCIq95f2wd5D57X46xERETEPSrs/GIpMABIuaY9Ob99qc8jEhERkbJPF0/4zVJgOdCN/56RHINm6kRERKS0VNj5VS6wEaiS/6qiTkREREpPh2JFREREAoQKOxEREZEAocKuCJGRkcTFxbFt2zZ/hyIiIiLiMhV2RYiKiqJ58+a0b9/e36GIiIiIuEyFnYiIiEiAUGEnIiIiEiBU2ImIiIgECBV2IiIiIgFChZ2IiIhIgFBhJyIiIhIgVNiJiIiIBAgVdiIiIiIBQoWdiIiISIBQYSciIiISIFTYiYiIiAQIFXYiIiIiAUKFnYiIiEiAUGEnIiIiEiBU2ImIiIgECBV2IiIiIgGiXBR2S5YsIS0tjUWLFvk7FBERERGvKReF3fTp03n22Wf9HYaIiIiIV5WLwi4mJoaMjAx/hyEiIiLiVX4v7Dp37syKFStISUnBMAweffTRQmOGDRvG0aNHyczMJDY2lk6dOvkhUhERERFz83thFxwczK5du3jhhReK7B84cCBTp05lwoQJtG7dms2bN7N69WoaNmzoGBMbG8uePXsKLfXq1fPVboiIiIj4XQV/BxAdHU10dHSx/S+//DKzZ89m9uzZAIwaNYqePXsybNgwxo4dC0C7du08EkulSpWoXLmy47PdbgfAZrNhs9k8so1r2Ww2rFar19Yv7lE+zEO5MBflw1yUD/PwRS7cWbffC7uSVKxYkbZt2zJx4kSn9rVr19KxY0ePb++1117jzTffLNQeFhZGZmamx7cHeclq06YNFouFnJwcr2xDXKd8mIdyYS7Kh7koH+bhi1wEBQW5PNbUhV2tWrWoUKECqampTu2pqanUrVvX5fVER0fTpk0bgoODSUpKon///sTGxhYa98477zB58mTHZ7vdTkpKCuvWrfPaxRc2mw3DMIiOjtaX0wSUD/NQLsxF+TAX5cM8fJGLgiOIrjB1YVfAMAynzxaLpVBbSXr16uXSuMuXL3P58uVC7Tk5OV794uTm5np9G+I65cM8lAtzUT7MRfkwD2/nwp31+v3iiZKcOnWKK1euFJqdq1OnTqFZPBEREZHyztSFXXZ2Njt27CAsLMypPSwsjO+++85r242MjCQuLo5t27Z5bRsiIiIinub3Q7HBwcE0adLE8blx48a0bNmStLQ0kpKSmDx5Mp9++imxsbFs3bqVoUOHEhoayscff+y1mKKiooiKisJut5Oenu617YiIiIh4kt8Lu3bt2hETE+P4PGXKFADmzZtHREQECxcupGbNmrzxxhvUq1ePvXv30rt3bxITE/0UsYiIiIg5+b2w27hxIxaLpcQxM2fOZObMmT6KSERERKRsMvU5dv6ic+xERESkLFJhV4SoqCiaN29O+/bt/R2KSLlktUDXZtClad6rteRJfRERyef3Q7EiIlfr3w6mPQsNawH1YUwbSDoFI+bD0sL3FRcRkatoxk5ETKN/O/hqJITUcG4PqZ7X3t8zj4UWEQlYKuxExBSslryZuoL3Tn1WwICpg3VYVkSkJCrsiqCLJ0R8r3NTaFiz+MLNaoXQWnnjRESkaCrsiqCLJ0R8r94tnh0nIlIeqbATEVM4ftaz40REyiMVdiJiCpsPQNJpyM0tuj83FxJP5Y0TEZGiqbATEVPINfJuaYKlcHGXm5vXPvLTvHEiIlI0FXZF0MUTIv6xNBYGTIWUM87tyWl57bqPnYhIyXSD4iJERUURFRWF3W4nPT3d3+GIlCtLY2H5DujWHHr1guhoiInTTJ2IiCtU2Inku/oxVhfjVUz4Uy6wMROqZOa9FnPanYiIXEOFnQh6jJWpNAN6AbcAdwJ1gLNANLDfb1GJiJQJOsdOyj09xspEmgEDgZuvab85v72ZzyMSESlTVNhJuabHWJmIhbyZuoL31/aR369ciIgUS4VdEXRVbPmhx1iZSCOgGsUXbpb8/kY+i0hEpMxRYVcEXz1S7OqT9bs206yQP+gxViZS1cPjRETKIV084Sc6Wd8c9BgrEznv4XEiIuWQZuz8QCfrm4ceY2UiCcA5oLhbzBj5/Qk+i0hEpMxRYedjOlnfXPQYKxMxyLulScH7a/vI71cuRESKpcLOx3SyvvnoMVYmsh9YCFz7wJf0/Hbdx05EpEQ6x87HdLK+OekxViayHzgA3E7e7U2igaNopk5ExAUq7HxMJ+ubV64BG/dDldvyXlXU+ZEBxJN3Pl08KupERFykQ7FF8OZ97HSyvolZgNvIu0/abehGuCIiUuaosCuCN+9jp5P1TaoZMBJ4Fngg/3UkeoSViIiUKSrs/EAn65uMnk8qIiIBQufY+YlO1jeJ6z2f1MjvP4DO8xIREdNTYedHOlnfBAqeT1qcq59PGu+LgEREREpPh2L9SSfr+5+eTyoiIgFEM3b+0oy8Q3y3AHcCdYCz5N2zSzdh9R09n1RERAKIZuz8QSfrm4eeTyoiIgFEhZ2vXe9kffL7dVjWN/R8UhERCSAq7Hyt4GT94gq3q0/WF9/Q80lFRCRA6By7IkRGRjJ8+HCsVi/UvTpZ35z0fFIREQkAmrErgjefPKGT9U1MzycVEZEyToWdr+lkfREREfESFXa+ppP1RURExEtU2PmDTtYXERERL9DFE/6ik/VFRETEwzRj5086WV9EREQ8SIWdiIiISIBQYSciIiISIFTYiYiIiAQIFXYiIiIiAUKFnYiIiEiAUGEnIiIiEiBU2ImIiIgECBV2RYiMjCQuLo5t27b5OxQRERERl6mwK0JUVBTNmzenffv2/g5FRERExGV6pJgL7Ha719Zts9kICgrCbreTk5Pjte2Ia5QP81AuzEX5MBflwzx8kQt36hAVdiUo+EWmpKT4ORIREREp7+x2OxkZGSWOsaAnlJaofv36jl/itm3bij08W1xfUe1Xt9ntdlJSUggJCblusjytpP3x5npcHX+9ce78zotrv7atrOejNOtw5WdKm4uS+vTdKP14T+ejPHw3SrMeT+TDG98NKPv5KMvfjWvbfZULu93Ozz//fN1xmrG7jqt/ibm5ucUmrbi+otqLasvIyPD5l7Ok/fHmelwdf71x7vzOi2svbmxZzUdp1uHKz5Q2FyX16btR+vGezkd5+G6UZj2eyIc3vxtQdvNRlr8bxbV7OxeurlsXT7hhxowZbvcV1V7SenzJU3G4ux5Xx19vnDu/8+LazZIL8EwspVmHKz9T2lyU1GfmfATqd6O4PjPnAsp2PgLtuwH++W+Vmb4b7sTjDzoU62d2u5309HRuvvlmn/9flxSmfJiHcmEuyoe5KB/mYbZcaMbOzy5dusSbb77JpUuX/B2KoHyYiXJhLsqHuSgf5mG2XGjGTkRERCRAaMZOREREJECosBMREREJECrsRERERAKECjsRERGRAKHCrgxp0KABGzZsIC4ujl27djFgwAB/h1SuLVmyhLS0NBYtWuTvUMqlPn36cODAAQ4ePMhvf/tbf4dTrum7YB76O2EuVatWZdu2bezcuZPdu3fzu9/9zifbNbSUjaVu3bpGy5YtDcCoXbu2kZSUZFSpUsXvcZXXpVu3bkbfvn2NRYsW+T2W8rbYbDbjp59+MurXr29UrVrVOHjwoFG9enW/x1VeF30XzLPo74S5FqvVagQFBRmAERQUZBw5csSoUaOGd7eJlBknTpxg165dAJw8eZK0tDRq1Kjh56jKr5iYGFPcjLI8at++PXFxcfz888+cP3+eVatW0bNnT3+HVW7pu2Ae+jthLrm5uWRmZgJw0003YbPZsFgsXt2mCjsP6ty5MytWrCAlJQXDMHj00UcLjRk2bBhHjx4lMzOT2NhYOnXqVKpttW3bFqvVSnJy8o2GHZB8mQtx343mp379+qSkpDg+JycnExIS4pPYA42+K+biyXzo78SN80Q+qlWrxn/+8x+Sk5N57733OH36tFdjVmHnQcHBwezatYsXXnihyP6BAwcydepUJkyYQOvWrdm8eTOrV6+mYcOGjjGxsbHs2bOn0FKvXj3HmBo1ajB//nyGDh3q9X0qq3yVCymdG81PUf/HaxiGV2MOVJ74rojneCof+jvhGZ7Ix7lz52jVqhWNGzfmqaeeok6dOl6P2+/HoANxMQzDePTRR53avv/+eyMqKsqpbd++fcZf//pXl9dbqVIlY+PGjcYzzzzj930sK4u3cgEYXbt21XlFfsjP/fffbyxZssTRN3XqVOPJJ5/0+76U9eVGviv6LpgnH/o7Ya58XL1ERUUZAwYM8GqcmrHzkYoVK9K2bVvWrl3r1L527Vo6duzo8nrmzZvHN998wz//+U9Ph1hueCoX4h2u5Gfbtm3cc8891K9fn6pVq9K7d2/WrFnjj3ADmr4r5uJqPvR3wjdcyUedOnWw2+0A2O12unTpwk8//eTVuCp4de3iUKtWLSpUqEBqaqpTe2pqKnXr1nVpHQ888ACDBg1i9+7d9OvXD4DBgwezd+9eT4cb0DyRC4Do6GjatGlDcHAwSUlJ9O/fn9jYWE+HW+64kp+cnBxGjx7Nhg0bsFqtvPfee6Slpfkj3IDm6ndF3wXfcCUf+jvhO67ko0GDBsyePRuLxYLFYuGjjz5iz549Xo1LhZ2PXXsekMVicfncoC1btmCz2bwRVrl0I7kA6NWrl6dDkqtcLz8rV65k5cqVvg6rXLpeLvRd8K2S8qG/E75XUj5+/PFHWrdu7dN4dCjWR06dOsWVK1cKzQjVqVOnULUv3qVcmJvyYx7KhbkoH+Zi1nyosPOR7OxsduzYQVhYmFN7WFgY3333nZ+iKp+UC3NTfsxDuTAX5cNczJwPv19pEihLcHCw0bJlS6Nly5aGYRjGyJEjjZYtWxoNGzY0AGPgwIHGpUuXjIiICKNp06bG5MmTjYyMDCM0NNTvsQfaolyYe1F+zLMoF+ZalA9zLWU0H/7/xQXK0rVrV6Moc+fOdYwZNmyYcezYMSMrK8uIjY01Onfu7Pe4A3FRLsy9KD/mWZQLcy3Kh7mWspgPS/4bERERESnjdI6diIiISIBQYSciIiISIFTYiYiIiAQIFXYiIiIiAUKFnYiIiEiAUGEnIiIiEiBU2ImIiIgECBV2IiIiIgFChZ2IiIhIgFBhJyLlzrhx49i5c6e/wxAR8TgVdiISUAzDKHGZO3cukyZNokePHn6J77HHHuP777/n7NmzpKens3fvXiZNmuSXWEQk8FTwdwAiIp5Ut25dx/tBgwbx1ltvcddddznaMjMzuXDhAhcuXPB5bD169ODLL79k7NixrFixAsMwuPvuu/1WZIpIYDK0aNGiJRCX8PBw48yZM4Xax40bZ+zcudPxee7cucbSpUuN1157zThx4oRx5swZ44033jBsNpvx3nvvGadPnzaSkpKMiIgIp/XUr1/f+PLLL420tDTj1KlTxrJly4xGjRoVG8+UKVOMb775psSYC2IbOnSokZiYaFy4cMFYuHChUa1aNceYdu3aGWvXrjVOnjxpnD171oiJiTFat27ttB7DMIzf/va3xpIlS4wLFy4YBw8eNB5++GG/50SLFi3eXXQoVkQEePDBB6lfvz5dunTh5ZdfZvz48fzrX//izJkz3HfffXz88cd8/PHHNGjQAICgoCA2bNjA+fPn6dKlC506deL8+fNER0dTsWLFIrdx4sQJmjdvTvPmzUuMpUmTJgwcOJCHH36YXr160apVK2bMmOHot9vtfPLJJ3Tu3JkOHTpw6NAhVq1aRdWqVZ3WM27cOBYuXMi9997LqlWr+Oyzz6hevfoN/qZExOz8Xl1q0aJFizcWd2bsjh07ZlgsFkfb/v37jY0bNzo+W61WIyMjwxg0aJABGBEREcb+/fud1luxYkXjwoULRlhYWJHxVKlSxfjXv/5lGIZhHDt2zPjiiy+MiIgIo1KlSk6xZWdnGyEhIY62nj17GleuXDFuvfXWItdrtVqNc+fOGX369HG0GYZhvPXWW07bzsnJMXr27On3vGjRosV7i2bsRESAuLg4DMNwfE5NTWXPnj2Oz7m5uZw+fZo6deoA0LZtW5o0aUJGRoZjSUtL46abbuKOO+4ochsXL16kb9++3HHHHfzlL3/h/PnzfPDBB2zbto2goCDHuMTERFJSUhyft27dis1mc5wrWLt2bWbOnMlPP/3E2bNnOXfuHFWrViU0NNRpe7t373badkZGhiN+EQlMunhCRATIzs52+mwYRpFtVmve/w9brVZ27NjB008/XWhdJ0+eLHFbR48e5ejRo8yePZsJEyZw8OBBBg0axLx584ocX1BwFrzOmzeP2rVrM3LkSBISErh06RJbt26lUqVK192ngvhFJDCpsBMRKYUff/yRQYMG8csvv5CRkVHq9cTHx3Px4kWCg4MdbaGhodSrV4/jx48DcP/995OTk8PBgwcB6Ny5M5GRkaxevRqABg0aULt27RvYGxEJFPpfNxGRUvjss884deoUy5cvp1OnTtx222106dKFqVOnEhISUuTPjBs3jnfffZeuXbty22230apVK+bMmUPFihVZt26dY1xWVhaffPIJ9957L506dWL69OksXLiQ1NRUAA4fPszgwYNp2rQp7du357PPPuPixYs+2W8RMTcVdiIipZCZmUmXLl1ITExkyZIl7N+/nzlz5hAUFER6enqRP7Nx40Zuv/125s+fz4EDB1i9ejV169bloYcecszGQV7htmTJElatWsXatWvZu3cvkZGRjv4hQ4ZQvXp1du7cyaeffsr06dP55ZdfvL7PImJ+FvKuohARERMYN24c/fr1o3Xr1v4ORUTKIM3YiYiIiAQIFXYiIiIiAUKHYkVEREQChGbsRERERAKECjsRERGRAKHCTkRERCRAqLATERERCRAq7EREREQChAo7ERERkQChwk5EREQkQKiwExEREQkQKuxEREREAsT/Awue3OYlx7GVAAAAAElFTkSuQmCC\n",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -336,15 +340,17 @@
     "\n",
     "fig, ax = plt.subplots()\n",
     "\n",
-    "ax.scatter(end_times, sci_times*1000, c='blue', label='SciPy', marker='.')\n",
-    "ax.scatter(end_times, nb_times*1000, c='green', label=\"CyRK's Numba\", marker='.')\n",
-    "ax.scatter(end_times, cy_times*1000, c='orange', label=\"CyRK's Cython\", marker='.')\n",
+    "ax.scatter(end_times, sci_times*1000, c='blue', label='SciPy', marker='o')\n",
+    "ax.scatter(end_times, nb_times*1000, c='green', label=\"CyRK's Numba\", marker='o')\n",
+    "ax.scatter(end_times, cy_times*1000, c='orange', label=\"CyRK's Cython\", marker='o')\n",
     "\n",
     "ax.set(ylabel='Average Time [ms]', xlabel='Time Span', xscale='log', yscale='log',\n",
     "       title=f'CyRK v{version} vs. SciPy')\n",
+    "ax.grid(alpha=0.3)\n",
     "# ax.set_xlim(ax.get_xlim()[::-1])\n",
     "\n",
     "ax.legend(loc='best')\n",
+    "ax.set(title=f'{version}')\n",
     "fig.tight_layout()\n",
     "fig.savefig(f'CyRK_SciPy_Compare_v{version_filesafe}.png')\n",
     "plt.show()"
@@ -352,7 +358,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 9,
    "id": "697a88bd",
    "metadata": {},
    "outputs": [
@@ -360,14 +366,12 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "end_time-1.0e-02: Numba=8.262x; Cython=5.062x\n",
-      "end_time-1.0e-01: Numba=11.398x; Cython=7.393x\n",
-      "end_time-1.0e+00: Numba=15.909x; Cython=10.720x\n",
-      "end_time-1.0e+01: Numba=23.608x; Cython=18.827x\n",
-      "end_time-1.0e+02: Numba=25.615x; Cython=19.222x\n",
-      "end_time-1.0e+03: Numba=15.880x; Cython=19.647x\n",
-      "end_time-1.0e+04: Numba=1.031x; Cython=18.956x\n",
-      "end_time-1.0e+05: Numba=0.061x; Cython=21.175x\n"
+      "end_time-1.0e-02: Numba=8.755x; Cython=6.213x\n",
+      "end_time-1.0e-01: Numba=11.159x; Cython=7.909x\n",
+      "end_time-1.0e+00: Numba=16.317x; Cython=11.754x\n",
+      "end_time-1.0e+01: Numba=24.450x; Cython=18.255x\n",
+      "end_time-1.0e+02: Numba=23.817x; Cython=19.601x\n",
+      "end_time-1.0e+03: Numba=12.227x; Cython=18.621x\n"
      ]
     }
    ],
@@ -390,64 +394,60 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 10,
    "id": "ec44f0de",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "ename": "ModuleNotFoundError",
+     "evalue": "No module named 'memory_profiler'",
+     "output_type": "error",
+     "traceback": [
+      "\u001B[1;31m---------------------------------------------------------------------------\u001B[0m",
+      "\u001B[1;31mModuleNotFoundError\u001B[0m                       Traceback (most recent call last)",
+      "Cell \u001B[1;32mIn[10], line 1\u001B[0m\n\u001B[1;32m----> 1\u001B[0m \u001B[43mget_ipython\u001B[49m\u001B[43m(\u001B[49m\u001B[43m)\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mrun_line_magic\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;124;43m'\u001B[39;49m\u001B[38;5;124;43mload_ext\u001B[39;49m\u001B[38;5;124;43m'\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;124;43m'\u001B[39;49m\u001B[38;5;124;43mmemory_profiler\u001B[39;49m\u001B[38;5;124;43m'\u001B[39;49m\u001B[43m)\u001B[49m\n",
+      "File \u001B[1;32mC:\\ProgramData\\Anaconda3\\envs\\cyrk310a\\lib\\site-packages\\IPython\\core\\interactiveshell.py:2364\u001B[0m, in \u001B[0;36mInteractiveShell.run_line_magic\u001B[1;34m(self, magic_name, line, _stack_depth)\u001B[0m\n\u001B[0;32m   2362\u001B[0m     kwargs[\u001B[38;5;124m'\u001B[39m\u001B[38;5;124mlocal_ns\u001B[39m\u001B[38;5;124m'\u001B[39m] \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mget_local_scope(stack_depth)\n\u001B[0;32m   2363\u001B[0m \u001B[38;5;28;01mwith\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mbuiltin_trap:\n\u001B[1;32m-> 2364\u001B[0m     result \u001B[38;5;241m=\u001B[39m fn(\u001B[38;5;241m*\u001B[39margs, \u001B[38;5;241m*\u001B[39m\u001B[38;5;241m*\u001B[39mkwargs)\n\u001B[0;32m   2365\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m result\n",
+      "File \u001B[1;32mC:\\ProgramData\\Anaconda3\\envs\\cyrk310a\\lib\\site-packages\\IPython\\core\\magics\\extension.py:33\u001B[0m, in \u001B[0;36mExtensionMagics.load_ext\u001B[1;34m(self, module_str)\u001B[0m\n\u001B[0;32m     31\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m module_str:\n\u001B[0;32m     32\u001B[0m     \u001B[38;5;28;01mraise\u001B[39;00m UsageError(\u001B[38;5;124m'\u001B[39m\u001B[38;5;124mMissing module name.\u001B[39m\u001B[38;5;124m'\u001B[39m)\n\u001B[1;32m---> 33\u001B[0m res \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mshell\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mextension_manager\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mload_extension\u001B[49m\u001B[43m(\u001B[49m\u001B[43mmodule_str\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m     35\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m res \u001B[38;5;241m==\u001B[39m \u001B[38;5;124m'\u001B[39m\u001B[38;5;124malready loaded\u001B[39m\u001B[38;5;124m'\u001B[39m:\n\u001B[0;32m     36\u001B[0m     \u001B[38;5;28mprint\u001B[39m(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mThe \u001B[39m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;124m extension is already loaded. To reload it, use:\u001B[39m\u001B[38;5;124m\"\u001B[39m \u001B[38;5;241m%\u001B[39m module_str)\n",
+      "File \u001B[1;32mC:\\ProgramData\\Anaconda3\\envs\\cyrk310a\\lib\\site-packages\\IPython\\core\\extensions.py:76\u001B[0m, in \u001B[0;36mExtensionManager.load_extension\u001B[1;34m(self, module_str)\u001B[0m\n\u001B[0;32m     69\u001B[0m \u001B[38;5;124;03m\"\"\"Load an IPython extension by its module name.\u001B[39;00m\n\u001B[0;32m     70\u001B[0m \n\u001B[0;32m     71\u001B[0m \u001B[38;5;124;03mReturns the string \"already loaded\" if the extension is already loaded,\u001B[39;00m\n\u001B[0;32m     72\u001B[0m \u001B[38;5;124;03m\"no load function\" if the module doesn't have a load_ipython_extension\u001B[39;00m\n\u001B[0;32m     73\u001B[0m \u001B[38;5;124;03mfunction, or None if it succeeded.\u001B[39;00m\n\u001B[0;32m     74\u001B[0m \u001B[38;5;124;03m\"\"\"\u001B[39;00m\n\u001B[0;32m     75\u001B[0m \u001B[38;5;28;01mtry\u001B[39;00m:\n\u001B[1;32m---> 76\u001B[0m     \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43m_load_extension\u001B[49m\u001B[43m(\u001B[49m\u001B[43mmodule_str\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m     77\u001B[0m \u001B[38;5;28;01mexcept\u001B[39;00m \u001B[38;5;167;01mModuleNotFoundError\u001B[39;00m:\n\u001B[0;32m     78\u001B[0m     \u001B[38;5;28;01mif\u001B[39;00m module_str \u001B[38;5;129;01min\u001B[39;00m BUILTINS_EXTS:\n",
+      "File \u001B[1;32mC:\\ProgramData\\Anaconda3\\envs\\cyrk310a\\lib\\site-packages\\IPython\\core\\extensions.py:91\u001B[0m, in \u001B[0;36mExtensionManager._load_extension\u001B[1;34m(self, module_str)\u001B[0m\n\u001B[0;32m     89\u001B[0m \u001B[38;5;28;01mwith\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mshell\u001B[38;5;241m.\u001B[39mbuiltin_trap:\n\u001B[0;32m     90\u001B[0m     \u001B[38;5;28;01mif\u001B[39;00m module_str \u001B[38;5;129;01mnot\u001B[39;00m \u001B[38;5;129;01min\u001B[39;00m sys\u001B[38;5;241m.\u001B[39mmodules:\n\u001B[1;32m---> 91\u001B[0m         mod \u001B[38;5;241m=\u001B[39m \u001B[43mimport_module\u001B[49m\u001B[43m(\u001B[49m\u001B[43mmodule_str\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m     92\u001B[0m     mod \u001B[38;5;241m=\u001B[39m sys\u001B[38;5;241m.\u001B[39mmodules[module_str]\n\u001B[0;32m     93\u001B[0m     \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_call_load_ipython_extension(mod):\n",
+      "File \u001B[1;32mC:\\ProgramData\\Anaconda3\\envs\\cyrk310a\\lib\\importlib\\__init__.py:126\u001B[0m, in \u001B[0;36mimport_module\u001B[1;34m(name, package)\u001B[0m\n\u001B[0;32m    124\u001B[0m             \u001B[38;5;28;01mbreak\u001B[39;00m\n\u001B[0;32m    125\u001B[0m         level \u001B[38;5;241m+\u001B[39m\u001B[38;5;241m=\u001B[39m \u001B[38;5;241m1\u001B[39m\n\u001B[1;32m--> 126\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[43m_bootstrap\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43m_gcd_import\u001B[49m\u001B[43m(\u001B[49m\u001B[43mname\u001B[49m\u001B[43m[\u001B[49m\u001B[43mlevel\u001B[49m\u001B[43m:\u001B[49m\u001B[43m]\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mpackage\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mlevel\u001B[49m\u001B[43m)\u001B[49m\n",
+      "File \u001B[1;32m<frozen importlib._bootstrap>:1050\u001B[0m, in \u001B[0;36m_gcd_import\u001B[1;34m(name, package, level)\u001B[0m\n",
+      "File \u001B[1;32m<frozen importlib._bootstrap>:1027\u001B[0m, in \u001B[0;36m_find_and_load\u001B[1;34m(name, import_)\u001B[0m\n",
+      "File \u001B[1;32m<frozen importlib._bootstrap>:1004\u001B[0m, in \u001B[0;36m_find_and_load_unlocked\u001B[1;34m(name, import_)\u001B[0m\n",
+      "\u001B[1;31mModuleNotFoundError\u001B[0m: No module named 'memory_profiler'"
+     ]
+    }
+   ],
    "source": [
     "%load_ext memory_profiler"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": null,
    "id": "4d12c3e5",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "peak memory: 297.47 MiB, increment: 0.00 MiB\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "%memit scipy_run(1.0e-6, 1.0e-8, (0., 10000.))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": null,
    "id": "0bda8d56",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "peak memory: 300.27 MiB, increment: 2.85 MiB\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "%memit nbrk_run(1.0e-6, 1.0e-8, (0., 10000.))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": null,
    "id": "3580f2a1",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "peak memory: 297.46 MiB, increment: 0.00 MiB\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "%memit cyrk_run(1.0e-6, 1.0e-8, (0., 10000.))"
    ]
@@ -469,7 +469,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.13"
+   "version": "3.10.8"
   }
  },
  "nbformat": 4,
diff --git a/Benchmarks/CyRK_SciPy_Compare_v0-1-2a4.png b/Benchmarks/CyRK_SciPy_Compare_v0-1-2a4.png
new file mode 100644
index 0000000..00b7630
Binary files /dev/null and b/Benchmarks/CyRK_SciPy_Compare_v0-1-2a4.png differ
diff --git a/Benchmarks/CyRK_SciPy_Compare_v0-1-2a4v.png b/Benchmarks/CyRK_SciPy_Compare_v0-1-2a4v.png
new file mode 100644
index 0000000..8c3df28
Binary files /dev/null and b/Benchmarks/CyRK_SciPy_Compare_v0-1-2a4v.png differ
diff --git a/Benchmarks/CyRK_SciPy_Compare_v0-1-3a0.png b/Benchmarks/CyRK_SciPy_Compare_v0-1-3a0.png
new file mode 100644
index 0000000..cd84705
Binary files /dev/null and b/Benchmarks/CyRK_SciPy_Compare_v0-1-3a0.png differ
diff --git a/Benchmarks/CyRK_SciPy_Compare_v0-1-3dev2.png b/Benchmarks/CyRK_SciPy_Compare_v0-1-3dev2.png
new file mode 100644
index 0000000..133243f
Binary files /dev/null and b/Benchmarks/CyRK_SciPy_Compare_v0-1-3dev2.png differ
diff --git a/CHANGES.md b/CHANGES.md
index 7315279..2f2a160 100644
--- a/CHANGES.md
+++ b/CHANGES.md
@@ -2,6 +2,17 @@
 
 ## 2022 - September
 
+### v0.1.3 - Alpha
+
+- Fixed a broken example in the readme documentation.
+- Added better quick tests for both the numba and cython versions.
+- Added `SciPy` dependency that was missing (required for numba integrator).
+- Increased the lower limit on `numpy` package version (to fix issue [7](https://github.com/jrenaud90/CyRK/issues/7)) and removed the upper limit version.
+- Removed python 3.7 as a supported version. 
+- Updated graphic in readme.
+- Converted over to using `pyproject.toml` instead of `setup.py`
+  - removed `version.py` from project folder.
+
 ### v0.1.2 - Alpha
 
 - Made the calling argument for the numba solver more consistent with the cython one by letting first_step==0 be
diff --git a/CyRK/__init__.py b/CyRK/__init__.py
index fe5d9a1..3d72917 100644
--- a/CyRK/__init__.py
+++ b/CyRK/__init__.py
@@ -1,9 +1,13 @@
 # Find Version Number
-from ._version import version
-__version__ = version
+import importlib.metadata
+__version__ = importlib.metadata.version("CyRK")
+version = __version__
 
 # Import numba solver
 from .nb.nbrk import nbrk_ode
 
 # Import cython solver
 from CyRK.cy.cyrk import cyrk_ode
+
+# Import test functions
+from ._test import test_cyrk, test_nbrk
diff --git a/CyRK/_version.py b/CyRK/_version.py
deleted file mode 100644
index c366422..0000000
--- a/CyRK/_version.py
+++ /dev/null
@@ -1,16 +0,0 @@
-# Version number should always be updated before pushing commits onto the main branch (or when merging branches onto the main).
-# Version number should have the following format:
-# A.B.C.<desc>
-#     A = Major Release: May break backwards compatibility
-#     B = Minor Release: New features but not critical, should be backwards compatible to previous minor releases
-#     C = Bug/Hot Fixes: Bug fixes or very minor features and improvements
-# 1.2.0.dev1   # Development Build (May be only a partial implementation of a feature / bug-fix)
-# 1.2.0.a1     # Alpha Build (All implementation should be done, but not all features for the release are in place; lots of bugs)
-# 1.2.0.b1     # Beta Release (All features are in place; minor changes might be needed based on user feedback; some bugs)
-# 1.2.0.rc1    # Release Candidate (All features are in place; no changes should be made unless essential; few bugs)
-# 1.2.X        # Final Release (X are bug fixes and patches that do not fall on the regular release cycle)
-
-# Note that a particular *version* of TidalPy may be in alpha, beta, dev, etc. that does not necessarily
-#   reflect the state of TidalPy as a whole project (which is currently still in Alpha).
-
-version = '0.1.2a4'
\ No newline at end of file
diff --git a/CyRK/nb/nbrk.py b/CyRK/nb/nbrk.py
index f8290cf..1e9d2ab 100644
--- a/CyRK/nb/nbrk.py
+++ b/CyRK/nb/nbrk.py
@@ -54,7 +54,7 @@
     [-71 / 57600, 0, 71 / 16695, -71 / 1920, 17253 / 339200, -22 / 525,
      1 / 40], order='C'
     )
-# Corresponds to the optimum value of c_6 from [2]_.
+
 RK45_P = np.array(
     [
         [1, -8048581381 / 2820520608, 8663915743 / 2820520608,
diff --git a/CyRK_SciPy_Compare_v0-0-1-dev4.png b/CyRK_SciPy_Compare_v0-0-1-dev4.png
deleted file mode 100644
index e9a1df2..0000000
Binary files a/CyRK_SciPy_Compare_v0-0-1-dev4.png and /dev/null differ
diff --git a/CyRK_SciPy_Compare_v0-1-3a0.png b/CyRK_SciPy_Compare_v0-1-3a0.png
new file mode 100644
index 0000000..cd84705
Binary files /dev/null and b/CyRK_SciPy_Compare_v0-1-3a0.png differ
diff --git a/README.md b/README.md
index 9073edf..c263fdd 100644
--- a/README.md
+++ b/README.md
@@ -1,33 +1,34 @@
 # CyRK
 <div style="text-align: center;">
 <a href="https://doi.org/10.5281/zenodo.7093266"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.7093266.svg" alt="DOI"></a>
-<a href="https://www.python.org/downloads/"><img src="https://img.shields.io/badge/Python-3.7|3.8|3.9|3.10-blue" alt="Python Version 3.7-3.10" /></a>
+<a href="https://www.python.org/downloads/"><img src="https://img.shields.io/badge/Python-3.8|3.9|3.10-blue" alt="Python Version 3.8-3.10" /></a>
 <a href="https://codecov.io/gh/jrenaud90/CyRK" ><img src="https://codecov.io/gh/jrenaud90/CyRK/branch/main/graph/badge.svg?token=MK2PqcNGET" alt="Code Coverage"/></a>
 <a href="https://github.com/jrenaud90/CyRK/actions/workflows/push_tests_win.yml"><img src="https://github.com/jrenaud90/CyRK/actions/workflows/push_tests_win.yml/badge.svg?branch=main" alt="Windows Tests" /></a>
 <a href="https://github.com/jrenaud90/CyRK/actions/workflows/push_tests_win.yml"><img src="https://github.com/jrenaud90/CyRK/actions/workflows/push_tests_mac.yml/badge.svg?branch=main" alt="MacOS Tests" /></a>
-<a href="https://github.com/jrenaud90/CyRK/actions/workflows/push_tests_win.yml"><img src="https://github.com/jrenaud90/CyRK/actions/workflows/push_tests_ubun.yml/badge.svg?branch=main" alt="Ubuntu Tests" /></a>
+
+[//]: # (<a href="https://github.com/jrenaud90/CyRK/actions/workflows/push_tests_win.yml"><img src="https://github.com/jrenaud90/CyRK/actions/workflows/push_tests_ubun.yml/badge.svg?branch=main" alt="Ubuntu Tests" /></a>)
 </div>
 
 ---
 
-<a href="https://github.com/jrenaud90/CyRK/releases"><img src="https://img.shields.io/badge/CyRK-0.1.1 Alpha-orange" alt="CyRK Version 0.0.1 Alpha" /></a>
+<a href="https://github.com/jrenaud90/CyRK/releases"><img src="https://img.shields.io/badge/CyRK-0.1.3 Alpha-orange" alt="CyRK Version 0.1.3 Alpha" /></a>
 
 
 **Runge-Kutta ODE Integrator Implemented in Cython and Numba**
 
 CyRK provides fast integration tools to solve systems of ODEs with adaptive time stepping. CyRK can accept differential equation functions 
-that are written in pure Python or njited numba, speeding up development time. The purpose of this package is to provide some of the 
+that are written in pure Python or njited numba, speeding up development time. The purpose of this package is to provide some 
 functionality of [scipy's solve_ivp](https://docs.scipy.org/doc/scipy/reference/generated/scipy.integrate.solve_ivp.html) with improved performance.
 
 CyRK's [numba](https://numba.discourse.group/) (njit-safe) implementation is 10-25x faster than scipy's solve_ivp function (except for very long integrations). 
 The [cython](https://cython.org/) implementation is about 20x faster. The cython function is also largely pre-compiled which avoids most of the 
 initial performance hit found with using the numba version.
 
-![CyRK Performance](CyRK_SciPy_Compare_v0-0-1-dev4.png)
+![CyRK Performance](CyRK_SciPy_Compare_v0-1-3a0.png)
 
 ## Installation
 
-It is recommended you use an [Anaconda](https://www.anaconda.com/products/distribution) environment.
+It is recommended you use an [Anaconda](https://www.anaconda.com/products/distribution) environment. CyRK has been tested on Python 3.8--3.10
 
 To install simply open a terminal (in administrator mode if using Windows) and call:
 
@@ -35,7 +36,18 @@ To install simply open a terminal (in administrator mode if using Windows) and c
 
 If not installing from a wheel, CyRK will attempt to install Cython and Numpy in order to compile the cython code. 
 After the files have been compiled, cython will be uninstalled and CyRK's runtime dependencies 
-(see setup.py for the latest list) will be installed instead.
+(see the pyproject.toml file for the latest list) will be installed instead.
+
+CyRK requires the `cython` and `numpy` packages during installation. The `numpy`, `numba`, and `scipy` packages are required for runtime.
+
+A new installation of CyRK can be tested quickly by running the following from a python console.
+```python
+from CyRK import test_cyrk, test_nbrk
+test_cyrk()
+# You will hopefully see the message "CyRK's cyrk_ode was tested successfully."
+test_nbrk()
+# You will hopefully see the message "CyRK's nbrk_ode was tested successfully."
+```
 
 ### Installation Troubleshooting
 
@@ -60,8 +72,8 @@ import numpy as np
 from numba import njit
 # For even more speed up you can use numba's njit to compile the diffeq
 @njit
-def diffeq(t, y):
-    dy = list()
+def diffeq_nb(t, y):
+    dy = np.empty_like(y)
     dy[0] = (1. - 0.01 * y[1]) * y[0]
     dy[1] = (0.02 * y[0] - 1.) * y[1]
     return dy
@@ -77,7 +89,7 @@ The ODE can then be solved using the numba function by calling CyRK's `nbrk_ode`
 ```python
 from CyRK import nbrk_ode
 time_domain, y_results, success, message = \
-    nbrk_ode(diffeq, time_span, initial_conds, rk_method=1, rtol=rtol, atol=atol)
+    nbrk_ode(diffeq_nb, time_span, initial_conds, rk_method=1, rtol=rtol, atol=atol)
 ```
 
 To call the cython version of the integrator you need to slightly edit the differential equation so that it does not
@@ -85,7 +97,7 @@ return the derivative. Instead, the output is passed as an input argument (a np.
 
 ```python
 @njit
-def diffeq(t, y, dy):
+def diffeq_cy(t, y, dy):
     dy[0] = (1. - 0.01 * y[1]) * y[0]
     dy[1] = (0.02 * y[0] - 1.) * y[1]
 ```
@@ -95,7 +107,7 @@ You can then call the ODE solver in a similar fashion as the numba version.
 ```python
 from CyRK import cyrk_ode
 time_domain, y_results, success, message = \
-    cyrk_ode(diffeq, time_span, initial_conds, rk_method=1, rtol=rtol, atol=atol)
+    cyrk_ode(diffeq_cy, time_span, initial_conds, rk_method=1, rtol=rtol, atol=atol)
 ```
 
 ### Optional Inputs
@@ -123,15 +135,13 @@ The solver will then interpolate the results to fit this array.
 (same for all y's).
 - [Issue 3](https://github.com/jrenaud90/CyRK/issues/3): Right now the cython version only allows for complex-valued
 y-values.
-- [Issue 5](https://github.com/jrenaud90/CyRK/issues/5): The numba solver is worse than the pure python scipy solver at
-large timespans (high integration times).
 
 ## Citing CyRK
 
 It is great to see CyRK used in other software or in scientific studies. We ask that you cite back to CyRK's 
 [GitHub](https://github.com/jrenaud90/CyRK) website so interested parties can learn about this package. 
 
-Renaud, Joe P. (2022). CyRK - ODE Integrator Implemented in Cython and Numba (0.1.2). Zenodo. https://doi.org/10.5281/zenodo.7093266
+Renaud, Joe P. (2022). CyRK - ODE Integrator Implemented in Cython and Numba. Zenodo. https://doi.org/10.5281/zenodo.7093266
 
 In addition to citing CyRK, please consider citing SciPy and its references for the specific Runge-Kutta model that
 was used in your work. CyRK is largely an adaptation of SciPy's functionality.
diff --git a/_build_cyrk.py b/_build_cyrk.py
new file mode 100644
index 0000000..13a92ba
--- /dev/null
+++ b/_build_cyrk.py
@@ -0,0 +1,38 @@
+""" Commands to build the cython extensions of CyRK (a hack to work with pyproject.toml) """
+import os
+
+from setuptools.extension import Extension
+
+from setuptools.command.build_py import build_py as _build_py
+
+
+class build_cyrk(_build_py):
+
+    def run(self):
+        self.run_command("build_ext")
+        return super().run()
+
+    def initialize_options(self):
+        super().initialize_options()
+        import numpy as np
+        from Cython.Build import cythonize
+        print('!-- Cythonizing CyRK')
+        if self.distribution.ext_modules == None:
+            self.distribution.ext_modules = []
+
+        # Add cyrk to ext_modules list
+        self.distribution.ext_modules.append(
+                Extension(
+                    'CyRK.cy.cyrk',
+                    sources=[os.path.join('CyRK', 'cy', '_cyrk.pyx')],
+                    include_dirs=[os.path.join('CyRK', 'cy'), np.get_include()]
+                    )
+                )
+
+        # Add cythonize ext_modules
+        self.distribution.ext_modules = cythonize(
+                self.distribution.ext_modules,
+                compiler_directives={'language_level': "3"},
+                include_path = ['.', np.get_include()]
+                )
+        print('!-- Finished Cythonizing CyRK')
diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..f4e0eb4
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,79 @@
+[project]
+
+name='CyRK'
+version = '0.1.3a1'
+description='Runge-Kutta ODE Integrator Implemented in Cython and Numba.'
+authors= [
+    {name = 'Joe P. Renaud', email = 'joe.p.renaud@gmail.com'}
+    ]
+
+requires-python = ">=3.8,<3.11"
+dependencies = [
+    'numba>=0.54.1',
+    'numpy>=1.22',
+    'scipy>=1.9.3'
+]
+license = {file = "LICENSE.txt"}
+readme = "README.md"
+# repository = "https://github.com/jrenaud90/CyRK/"
+keywords = [
+    'Scientific Computing',
+    'Runge-Kutta',
+    'Numerical Integration',
+    'ODEs',
+    'Ordinary Differential Equations',
+    'cython',
+    'numba',
+    'Integration'
+]
+
+classifiers = [
+    "Development Status :: 4 - Beta",
+    "Operating System :: Microsoft :: Windows",
+    "Operating System :: MacOS",
+    "Operating System :: POSIX :: Linux",
+    "Programming Language :: Cython",
+    "Programming Language :: Python :: 3.8",
+    "Programming Language :: Python :: 3.9",
+    "Programming Language :: Python :: 3.10",
+    "Programming Language :: Python :: Implementation :: CPython",
+    "Natural Language :: English",
+    "Intended Audience :: Science/Research",
+    "Intended Audience :: Education",
+    "Topic :: Scientific/Engineering",
+    "Topic :: Scientific/Engineering :: Mathematics",
+    "Topic :: Scientific/Engineering :: Physics"
+]
+
+[project.optional-dependencies]
+dev = [
+    "jupyter",
+    "matplotlib",
+    "pytest"
+]
+
+[build-system]
+requires = [
+    # Setuptools 18.0 properly handles Cython extensions.
+    'setuptools>=18.0',
+    'numpy>=1.22',
+    'cython>=0.29.30',
+    'wheel>=0.38'
+]
+
+[tool.setuptools]
+py-modules = ["_build_cyrk"]
+
+[tool.setuptools.packages]
+find = {}
+
+[tool.setuptools.cmdclass]
+build_py = "_build_cyrk.build_cyrk"
+
+[tool.pytest.ini_options]
+minversion = "6.0"
+addopts = "-ra -v"
+testpaths = [
+    "Tests"
+]
+timeout = 300
\ No newline at end of file
diff --git a/setup.py b/setup.py
deleted file mode 100644
index 5c89696..0000000
--- a/setup.py
+++ /dev/null
@@ -1,101 +0,0 @@
-import os
-
-from setuptools import setup, find_packages
-from setuptools.extension import Extension
-from setuptools.command.build_ext import build_ext
-
-# Find CyRK Directory
-dir_path = os.path.dirname(os.path.realpath(__file__))
-
-# Find long description
-long_description = ''
-with open(os.path.join(dir_path, "README.md"), 'r') as f:
-    long_description = f.read()
-
-# Find version number
-version = ''
-with open(os.path.join(dir_path, "CyRK", "_version.py"), 'r') as f:
-    for line in f:
-        if 'version =' in line:
-            version = line.split('=')[-1].strip().replace("'", '').replace('"', '')
-
-# Dependencies
-setup_requirements = [
-    # Setuptools 18.0 properly handles Cython extensions.
-    'setuptools>=18.0',
-    'numpy>=1.20.3,<1.23',
-    'cython>=0.29.30'
-    ]
-
-requirements = [
-    'numba>=0.54.1',
-    'numpy>=1.20.3,<1.23'
-    ]
-
-# Meta Data
-classifiers = [
-    "Development Status :: 4 - Beta",
-    "Operating System :: Microsoft :: Windows",
-    "Operating System :: MacOS",
-    "Operating System :: POSIX :: Linux",
-    "Programming Language :: Cython",
-    "Programming Language :: Python :: 3.7",
-    "Programming Language :: Python :: 3.8",
-    "Programming Language :: Python :: 3.9",
-    "Programming Language :: Python :: 3.10",
-    "Programming Language :: Python :: Implementation :: CPython",
-    "Natural Language :: English",
-    "Intended Audience :: Science/Research",
-    "Intended Audience :: Education",
-    "Topic :: Scientific/Engineering",
-    "Topic :: Scientific/Engineering :: Mathematics",
-    "Topic :: Scientific/Engineering :: Physics"
-    ]
-
-# Find Cython files and turn them into c code. Must have numpy installed in order to find its c headers.
-ext_modules = [
-    Extension('CyRK.cy.cyrk',
-              sources=[os.path.join('CyRK', 'cy', '_cyrk.pyx')],
-              include_dirs=[os.path.join('CyRK', 'cy')]
-              )
-    ]
-
-
-# Create a build ext class that waits until setup dependencies are installed before cythonizing and building c-code
-class BuildExtCmd(build_ext):
-
-    def run(self):
-        import numpy as np
-        self.include_dirs.append(np.get_include())
-        super().run()
-
-    def finalize_options(self):
-        from Cython.Build import cythonize
-        print('!-- Cythonizing CyRK')
-        self.distribution.ext_modules = cythonize(
-            self.distribution.ext_modules,
-            compiler_directives={'language_level': "3"}
-            )
-        print('!-- Finished Cythonizing CyRK')
-        super().finalize_options()
-
-
-setup(
-    name='CyRK',
-    version=version,
-    description='Runge-Kutta ODE Integrator Implemented in Cython and Numba.',
-    author='Joe P. Renaud',
-    author_email='joe.p.renaud@gmail.com',
-    long_description=long_description,
-    long_description_content_type='text/markdown',
-    classifiers=classifiers,
-    url='https://github.com/jrenaud90/CyRK',
-    repository="https://github.com/jrenaud90/CyRK/",
-    python_requires=">=3.7",
-    setup_requires=setup_requirements,
-    ext_modules=ext_modules,
-    install_requires=requirements,
-    cmdclass={"build_ext": BuildExtCmd},
-    packages=find_packages(),
-    package_data={"CyRK.cy": ["_cyrk.pyx"]},
-    )


Test patch:
diff --git a/.github/workflows/push_tests_mac.yml b/.github/workflows/push_tests_mac.yml
index da3f4e3..64d1ad1 100644
--- a/.github/workflows/push_tests_mac.yml
+++ b/.github/workflows/push_tests_mac.yml
@@ -13,7 +13,6 @@ jobs:
     strategy:
       matrix:
         python-version:
-          - "3.7"
           - "3.8"
           - "3.9"
           - "3.10"
diff --git a/.github/workflows/push_tests_ubun.yml b/.github/workflows/push_tests_ubun.yml.dev
similarity index 99%
rename from .github/workflows/push_tests_ubun.yml
rename to .github/workflows/push_tests_ubun.yml.dev
index b8ed087..0eb13f7 100644
--- a/.github/workflows/push_tests_ubun.yml
+++ b/.github/workflows/push_tests_ubun.yml.dev
@@ -35,7 +35,6 @@ jobs:
     strategy:
       matrix:
         python-version:
-          - "3.7"
           - "3.8"
           - "3.9"
           - "3.10"
diff --git a/.github/workflows/push_tests_win.yml b/.github/workflows/push_tests_win.yml
index afcbef6..e9e047a 100644
--- a/.github/workflows/push_tests_win.yml
+++ b/.github/workflows/push_tests_win.yml
@@ -12,7 +12,6 @@ jobs:
     strategy:
       matrix:
         python-version:
-          - "3.7"
           - "3.8"
           # Skip 3.9 since we will perform coverage on it later
           - "3.10"
@@ -51,12 +50,12 @@ jobs:
           python -m pip install . -v
 
       - name: Run pytest
-        run: pytest -v --cov=. --cov-report=xml --timeout=300 .\Tests\
+        run: pytest -v --cov=.\CyRK --cov-report=xml --timeout=300 .\Tests\
       - name: Upload coverage to Codecov
         uses: codecov/codecov-action@v3
         with:
           env_vars: OS,PYTHON
-          fail_ci_if_error: true
+          fail_ci_if_error: false
           flags: unittests
           verbose: true
           name: coverage
\ No newline at end of file
diff --git a/CyRK/_test.py b/CyRK/_test.py
index f4573c5..a7944f4 100644
--- a/CyRK/_test.py
+++ b/CyRK/_test.py
@@ -6,7 +6,44 @@
 rtol = 1.0e-7
 atol = 1.0e-8
 
+
 @njit
-def diffeq(t, y, dy):
+def cy_diffeq(t, y, dy):
     dy[0] = (1. - 0.01 * y[1]) * y[0]
     dy[1] = (0.02 * y[0] - 1.) * y[1]
+
+
+@njit
+def nb_diffeq(t, y):
+    dy = np.empty_like(y)
+    dy[0] = (1. - 0.01 * y[1]) * y[0]
+    dy[1] = (0.02 * y[0] - 1.) * y[1]
+    return dy
+
+
+def test_cyrk():
+
+    from CyRK import cyrk_ode
+
+    time_domain, y_results, success, message = cyrk_ode(cy_diffeq, time_span, initial_conds)
+
+    assert success
+    assert type(time_domain) == np.ndarray
+    assert type(y_results) == np.ndarray
+    assert y_results.shape[0] == 2
+
+    print("CyRK's cyrk_ode was tested successfully.")
+
+
+def test_nbrk():
+
+    from CyRK import nbrk_ode
+
+    time_domain, y_results, success, message = nbrk_ode(nb_diffeq, time_span, initial_conds)
+
+    assert success
+    assert type(time_domain) == np.ndarray
+    assert type(y_results) == np.ndarray
+    assert y_results.shape[0] == 2
+
+    print("CyRK's nbrk_ode was tested successfully.")
diff --git a/Tests/A_Package_Tests/package_test.py b/Tests/A_Package_Tests/package_test.py
index bb1119a..cd17a47 100644
--- a/Tests/A_Package_Tests/package_test.py
+++ b/Tests/A_Package_Tests/package_test.py
@@ -1,6 +1,7 @@
 def test_package():
     """Check if all the functions can be imported. """
 
-    from CyRK import cyrk_ode, nbrk_ode, version
+    from CyRK import cyrk_ode, nbrk_ode, version, __version__, test_cyrk, test_nbrk
 
     assert type(version) == str
+    assert version == __version__
diff --git a/Tests/B_Cython_Tests/cython_test.py b/Tests/B_Cython_Tests/cython_test.py
index aafa51e..ebb8618 100644
--- a/Tests/B_Cython_Tests/cython_test.py
+++ b/Tests/B_Cython_Tests/cython_test.py
@@ -30,6 +30,12 @@ def diffeq_scipy(t, y):
 atol = 1.0e-8
 
 
+def test_cyrk_test():
+    """Check that the builtin test function for the cyrk integrator is working"""
+
+    from CyRK import test_cyrk
+    test_cyrk()
+
 def test_basic_integration():
     """Check that the cython solver is able to run with its default arguments"""
 
diff --git a/Tests/C_Numba_Tests/numba_test.py b/Tests/C_Numba_Tests/numba_test.py
index 7c24e1a..9da460e 100644
--- a/Tests/C_Numba_Tests/numba_test.py
+++ b/Tests/C_Numba_Tests/numba_test.py
@@ -27,6 +27,13 @@ def diffeq(t, y):
 atol = 1.0e-8
 
 
+def test_nbrk_test():
+    """Check that the builtin test function for the nbrk integrator is working"""
+
+    from CyRK import test_nbrk
+    test_nbrk()
+
+
 def test_basic_integration():
     """Check that the numba solver is able to run with its default arguments"""
 
diff --git a/pytest.ini b/pytest.ini
deleted file mode 100644
index b19c31f..0000000
--- a/pytest.ini
+++ /dev/null
@@ -1,2 +0,0 @@
-[pytest]
-timeout = 300
\ No newline at end of file