Phoenix Command.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1172ce7f0>]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# FN Mk 1\n",
    "plt.plot([1,2,3,4,5,6],[-17,-11,-10,-9,-8,-7])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1174cdeb8>]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Type 51\n",
    "plt.plot([1,2,3,4,5,6],[-16,-11,-10,-9,-8,-7])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x117527d68>]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXkAAAD4CAYAAAAJmJb0AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjAsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+17YcXAAAcxElEQVR4nO3deXhcd33v8fdXu2VZspaRV9nyopFjO5utOIlNPFmxEygpcAOBAoEEEngIy720tCG9t33am0vbS1vaS0sJNDSUQG4IBHhILGchdnKzWs5mybbkPbKjkUaSJWtfZn73Dw2KE5R4GY2O5szn9Tx5Is0ZzfmMLX98/NM532POOURExJ8yvA4gIiLJo5IXEfExlbyIiI+p5EVEfEwlLyLiY1leBzhZWVmZq6ys9DqGiEhK2blzZ7tzLjDRtmlV8pWVldTV1XkdQ0QkpZjZkXfapuUaEREfU8mLiPiYSl5ExMdU8iIiPqaSFxHxsaSXvJltNrNGM9tvZn+W7P2JiMibklryZpYJ/AtwLbAS+JiZrUzmPkVE5E3JPpJfB+x3zh10zg0D9wPXJ3mfIiIp43B7H//xzCEefq0lKa+f7IuhFgDNJ31+FLj45CeY2a3ArQCLFi1KchwREW/1D4/y3IEOtjdF2N4U4UhHPwAfOH8+7ztv3qTvL9klbxM89pa7lDjn7gbuBqipqdEdTETEV5xz7G/rZVvjWKm/eKiT4WiMGdmZrF9Wyi3vWUIoGGBx6cyk7D/ZJX8UqDjp84XAG0nep4iIp3oGR3hmfwfbm9rY3hjhje5BAIJzCrhp/WJCwXJqKovJy85MepZkl/wOoMrMlgDHgBuBjyd5nyIiU8o5x+6WE+NH6y8dOc5ozDErN4sNy8v40lUBNgYDLJg9Y8qzJbXknXOjZnY7sBXIBO5xzjUkc58iIlOhq3+Yp/e1s60xwlP7IkR6hgBYOa+QWzcuJRQMsGZxMdmZ3l6OlPQplM65R4BHkr0fEZFkisYcu451s70xwramNl5t7iLmYHZ+NpdVBQgFA2ysKqO8MM/rqG8xrUYNi4hMJ5GeIZ7eN7YE81RThOP9I5jB+Qtn86UrqwhVBzh/4WwyMyY6x2R6UMmLiMSNRmO83Nw1frRef+wEAGUFOVyxopxQMMBlVQFKZuZ4nPT0qeRFJK21dA/wVPyc9af3tdMzOEpmhrF2UTF/sqmaUDDAynmFZEzjo/V3o5IXkbQyNBpl5+HjbG+KsK0xQmNrDwBzC/O4bvU8Lq8OsH55GUUzsj1OOjlU8iLie82d/WxrirC9McKzB9rpH46SnWmsW1LCh9euIBQsJzinALPUPFp/Nyp5EfGdwZEozx+Mjw5ojHCwvQ+AipIZfHjNQkLBAJcuK2Vmrv8r0P/vUER8zznHwfY+tscvRnr+YAdDozFyszK4ZGkpn7x0MaFggCVlM315tP5uVPIikpL6hkZ59kB8dEBThObOAQCWBmby8YsXcXl1ORcvKZmS0QHTmUpeRFKCc47G1p7xo/UdhzsZiTryczJZv6yM2zYuIxQMUFGS73XUaUUlLyLTVvfACM/sbx8v9vCJsUFfK+bO4uYNY9MbaypLyMnSnUzfiUpeRKaNWMzR8MaJ8SWYl17vIhpzzMrL4rKqsrHRAcEA84qmftBXqlLJi4inOvuGx0YHxAd9tfcOA3DugiK+EFpGqDrAhRWzyfJ40FeqUsmLyJSKxhyvNHeN3xnptaNdOAfF+dlsDAbGRwcEZuV6HdUXVPIiknRtJwbHS/3pfe10D4yQYXBBxWy+elWQUHWAcxcUTetBX6lKJS8ik24kGmPnkTdHB+xpGRv0FZiVyzUr5xAKBnjP8jKKU2jQV6pSyYvIpDjWNRA/C6aNZ/Z30Ds0SlaGsXZxMV/f/Oagr3S7GMlrKnkROSuDI1F2HO4cP71xX1svAPOL8viD8+cTCgbYsLyUWXn+GPSVqlTyInLaDrf3ja+tP3egg4GRKDmZGVy8tISPXlRBKBhgebk/B32lKpW8iLyj/uHRsUFfjRG2NUU40tEPQGVpPh+pWUioOsAlS0vJz1GVTFf6nRGRcc459rf1jh+tv3Cok+HRGHnZGaxfVjZ+lWll2Uyvo8ppUsmLpLmewRGe2d8xfh/TY11jg76WlxfwqUsWE6oOcFGlBn2lKpW8SJpxzrG75cT46Y0vHTnOaMxRkJvFhuWlfPGK5WwMlrGwWIO+/EAlL5IGuvqHeXpf+/gyTKRnCICV8wr53MalhIIB1i4uJlujA3xHJS/iQ9GYY9ex7vHz1l9p7iLmoGhG9vigr1AwQHlhntdRJclU8iI+EekZGhv0FV9bP94/ghmct3A2t19ZRSgY4IKK2RodkGZU8iIpajQa4+XmrvGLkXYd6wagrCCHK6rLCVWPDfoq0eiAtKaSF0khLd0DPHXSoK+ewVEyM4w1i2bzx+8NEgqWs2p+IRk6Wpc4lbzINDY8GqPucOf4mTCNrT0AzC3M47rV8whVB9iwvIyiGRodIBNTyYtMM82d/WxrirC9sY1nD3TQPxwlO9O4qLKEO9asIFQdoHrOLI0OkNOikhfx2OBIdGx0QNPY3ZEOtvcBsLB4Bh9as4BQsJz1y0qZmas/rnLm9F0jMsWccxxs7xv/genzBzsYGo2Rm5XBJUtL+UT8KtOlZTN1tC4JU8mLTIG+oVGePdAxfoPq5s6x0QFLAzP5+MWLCAXHBn1pdIBMNpW8SBI452hq7WVb41ip7zjcyUjUkZ+TyfplZdy6cRmXBwNUlGh0gCSXSl5kknQPjPDs/na2xZdhwicGAVgxd9b49Ma1lcXkZuloXaZO0krezP4S+BwQiT/0DefcI8nan8hUi8XGBn397mj9pde7iMYcs/KyxkcHbAwGmFc0w+uoksaSfST/j865byV5HyJTprNveGx0QGOEp/ZFaO8dBuDcBUV8IbSMUHWACytmk6VBXzJNaLlG5F1EY45Xj3aN3xnptaNdOAfF+dlsjA/5uqwqQGBWrtdRRSaU7JK/3cw+BdQBX3POHX/7E8zsVuBWgEWLFiU5jsiptfUM8lRTe3x0QISu/hEyDC6omM1XrwoSqg5w7oIiDfqSlGDOubP/YrPHgbkTbLoTeB5oBxzw18A859zN7/Z6NTU1rq6u7qzziJyNkWiMl44cHx8dsLvlBACBWbnjI3nfs7yMYg36kmnKzHY652om2pbQkbxz7urTDPB94DeJ7EtkMr3RNRAv9Tae2d9B79AoWRnG2sXFfH1zNaFggJXzCnUxkqS8ZJ5dM8851xL/9INAfbL2JXIqQ6NRdhw6zvamNrY1RtjX1gvA/KI8/uD8+YSCATYsL2VWngZ9ib8kc03+78zsAsaWaw4DtyVxXyK/50hH3/gSzHMHOhgYiZKTmcHFS0v46EUVhIIBlpcX6GhdfC1pJe+c+2SyXltkIgPDbw762tbYxuGOfgAqS/P5SM1CQtVjowPyc3RSmaQPfbdLynLOcSDSO36F6QuHOhkejZGXncH6ZWV8Jn6VaWXZTK+jinhGJS8ppWdwJD7oa+yCpGNdY4O+qsoL+FR8euNFlSUa9CUSp5KXac05x56WnrFSb2qj7vBxRmOOgtwsNiwv5YtXLGdjsIyFxRr0JTIRlbxMO939Izy9PzI+b72tZwiAlfMK+exlS7m8OsDaxcVka3SAyCmp5MVzsZhj17Hu+NF6hJdfP07MQdGM7PFBX6FggPLCPK+jiqQclbx4or136KRBX+109g1jBuctnM3tV1YRCga4oGK2RgeIJEglL1NiNBrjleau8fPWdx3rBqB0Zg6XBwOEqsdGB5QWaNCXyGRSyUvShLsHeSq+BPP0vggnBkfJzDDWLJrNH783SChYzqr5hWToaF0kaVTyMmmGR2PUHekcP71xb7gHgLmFeVy7eh6h6gAblpVRlK/RASJTRSUvCWnu7B//gemz+9vpG46SnWnULC7hjmtXEKoOUD1nlkYHiHhEJS9nbMfhTrbsCrOtqY2DkT4AFhbP4INrFhAKlnPpslIKcvWtJTId6E+inLYDkV7+18N7eGJvGzlZGVyytJRPXDx2lenSspk6WheZhlTyckrH+4b5pyf28ePnj5CXncmfbl7Bp9dXMiNHowNEpjuVvLyj4dEY//n8Ef75iX30DI5w47pF/LdrgpTpNEeRlKGSl9/jnOOx3a18c8teDrX3cVlVGXe+7xxWzC30OpqInCGVvLxFwxvd/M/f7OG5gx0sC8zkh5++iMurA1pvF0lRKnkBoO3EIN96tJGf7TzK7BnZ/NX1q/jYukUaAiaS4lTyaW5gOMoPnj7Id7cfYCQa47PvWcLtV1ZRNEMXLIn4gUo+TcVijl+/+gZ/W7uXlu5BNq+ayx3XrWBxqe6iJOInKvk0VHe4k79+eA+vNnexekEh3/7oBVy8tNTrWCKSBCr5NNLc2c/f1O7l4ddamFOYy7duOJ8PXbhAA8JEfEwlnwZ6Bkf4lycPcM8zh8gw+MpVVdwWWkp+jn77RfxOf8p9bDQa4//WNfMPjzbR0TfMh9Ys4OubVjC3SHdYEkkXKnmfeqopwl0P76GxtYd1lSX88DPncN7C2V7HEpEpppL3mf1tPdz18B6ebIywqCSf7/7RGjavnquLmUTSlEreJzr7hvn2403c98Lr5Gdn8o3rVnDT+kpyszRETCSdqeRT3NBolB89e4R//u0++oejfHzdIr56dZXulSoigEo+ZTnn2NoQ5ptb9nKko5/LqwPced05VM2Z5XU0EZlGVPIpaHg0xp//chcP1B0lOKeAe29eRygY8DqWiExDKvkUc7xvmM//eCcvHOrky1cu58tXVZGlIWIi8g5U8inkYKSXW+6t49jxAb790Qv4wwsXeB1JRKY5lXyKeO5AB5//8U4yM4yffO5iaipLvI4kIilAJZ8CHtjRzDce2kVl2UzuuekiFpXmex1JRFKESn4ai8Ucf7t1L9/bfpDLqsr4zsfXaM67iJyRhH5iZ2Y3mFmDmcXMrOZt2+4ws/1m1mhmmxKLmX76h0f5wn07+d72g3zikkX88NMXqeBF5IwleiRfD3wI+N7JD5rZSuBGYBUwH3jczILOuWiC+0sLrScGueXeHex+4wT/4/0r+cyGSo0lEJGzklDJO+f2ABMV0PXA/c65IeCQme0H1gHPJbK/dFB/rJvP3ltHz+AIP7iphitXzPE6koiksGSdYL0AaD7p86Pxx36Pmd1qZnVmVheJRJIUJzU8truVG/7tOTIMHvzCehW8iCTslEfyZvY4MHeCTXc65371Tl82wWNuoic65+4G7gaoqamZ8Dl+55zj+08f5Jtb9nLegiK+/6kaygs1811EEnfKknfOXX0Wr3sUqDjp84XAG2fxOr43Eo3x339Zz/07mrnu3Ln8/Q0XMCNHkyNFZHIka7nm18CNZpZrZkuAKuDFJO0rZXX3j3DTPS9y/45mbr9iOd/52BoVvIhMqoR+8GpmHwT+DxAAHjazV5xzm5xzDWb2ALAbGAW+qDNr3upwex8337uD5s5+/v6G8/nw2oVeRxIRH0r07JqHgIfeYdtdwF2JvL5fvXCwg9t+vBMD7vvsJaxbohEFIpIcuuJ1ij248yh3/OI1Kkryueemi6gsm+l1JBHxMZX8FInFHN96tJF/3XaA9ctK+e4fraUoX1ewikhyqeSnwMBwlK/97BUe2RXmY+sq+KvrV5OtGfAiMgVU8knWdmKQz/2ojteOdfPn7zuHW96zRCMKRGTKqOSTaPcbJ/jsvTvoGhjh7k/WcM1KXcEqIlNLJZ8kT+xp5cs/fZlZedk8cNulrF5Q5HUkEUlDKvlJ5pzj3//fIe56ZA+r5xfxg5tqmKMRBSLiEZX8JBqJxviLXzfwkxdeZ9OqOfzjRy8gP0e/xCLiHTXQJOkeGOH2n7zE0/va+XxoGV/fVE1Ghn7AKiLeUslPgtc7+rn53h0cbu/j7/7LeXykpuLUXyQiMgVU8gnaeeQ4n/tRHdGY4z9vuZhLl5V6HUlEZJxKPgHOOf7kZ68yMzeTez+zjqWBAq8jiYi8hS67TEBTay8H2/u4beMyFbyITEsq+QRsqW/BDN67Shc5icj0pJJPQG19mJrFxZTP0nnwIjI9qeTP0uH2PvaGe9i0aqLb34qITA8q+bNU2xAGYPNqlbyITF8q+bNUWx/m3AVFLCzO9zqKiMg7UsmfhZbuAV5p7tJRvIhMeyr5s7C1Xks1IpIaVPJnobYhTFV5Act0bryITHMq+TPU0TvEi4c6uVZH8SKSAlTyZ+ix3a3EHGxSyYtIClDJn6Et9WEWleSzcl6h11FERE5JJX8GugdGePZAO5tXz9XNuEUkJajkz8Bv97YyEnW6ylVEUoZK/gzU1oeZU5jLhRWzvY4iInJaVPKnqX94lO1NETatmqvb+olIylDJn6btjREGR2K6AEpEUopK/jTVNoQpzs9mXWWJ11FERE6bSv40DI1G+e2eNt67ci5ZmfolE5HUocY6Dc/u76BnaFRLNSKSclTyp2FLfQuzcrNYv7zU6ygiImdEJX8Ko9EYj+1u5cpzysnNyvQ6jojIGUmo5M3sBjNrMLOYmdWc9HilmQ2Y2Svx//4t8ajeePFwJ8f7R9isC6BEJAVlJfj19cCHgO9NsO2Ac+6CBF/fc7X1YfKyMwhVB7yOIiJyxhIqeefcHsC3c1xiMcfWhjChYID8nET/PhQRmXrJXJNfYmYvm9l2M7vsnZ5kZreaWZ2Z1UUikSTGOXMvN3fRemKIa1fP8zqKiMhZOeXhqZk9Dky0IH2nc+5X7/BlLcAi51yHma0Ffmlmq5xzJ97+ROfc3cDdADU1Ne70oyff1oYw2ZnGFSvKvY4iInJWTlnyzrmrz/RFnXNDwFD8451mdgAIAnVnnNAjzjlq68OsX1ZG0Yxsr+OIiJyVpCzXmFnAzDLjHy8FqoCDydhXsuxuOcHrnf26zZ+IpLRET6H8oJkdBS4FHjazrfFNG4HXzOxV4EHg8865zsSiTq2t9WEyDK5ZOcfrKCIiZy3Rs2seAh6a4PGfAz9P5LW9tqU+zLolJZQW5HodRUTkrOmK1wnsb+tlX1uvLoASkZSnkp/A1oYwAJu0Hi8iKU4lP4Ha+jAXVMxmXtEMr6OIiCREJf82R4/3s+tYt8YKi4gvqOTfprZ+bKlG6/Ei4gcq+bfZ2hBmxdxZVJbN9DqKiEjCVPInaesZpO7Icc2qERHfUMmf5NGGVpxD6/Ei4hsq+ZPU1odZUjaT4JwCr6OIiEwKlXxcV/8wzx3sYPPqub6djy8i6UclH/f4njaiMaezakTEV1TycbX1LcwvyuO8hUVeRxERmTQqeaB3aJSn9rWzSUs1IuIzKnngyb1tDI/GdOqkiPiOSh6obQhTVpDD2sXFXkcREZlUaV/ygyNRntzbxjUr55KZoaUaEfGXtC/5p/e10z8c1W3+RMSX0r7ka+vDFOZlccnSUq+jiIhMurQu+ZFojMf3tHL1yjnkZKX1L4WI+FRaN9vzBzvoHhjRBVAi4ltpXfJb6sPk52SyMRjwOoqISFKkbclHY45HG1q5orqcvOxMr+OIiCRF2pb8S68fp713SDfrFhFfS9uS37IrTE5mBleuKPc6iohI0qRlyTvn2NoQ5rKqMgpys7yOIyKSNGlZ8ruOdXOsa0B3gBIR30vLkq+tD5OZYVx9zhyvo4iIJFXalbxzjtr6MJcsLaF4Zo7XcUREkirtSn5fWy8H2/vYrLHCIpIG0q7ka+vDmMGmlVqqERH/S7uS31IfZu2iYsoL87yOIiKSdGlV8kc6+tjTckJn1YhI2kirkq+tDwOwSQPJRCRNpFfJN4RZvaCQipJ8r6OIiEyJhErezP63me01s9fM7CEzm33StjvMbL+ZNZrZpsSjJqale4CXX+/SWGERSSuJHsk/Bqx2zp0HNAF3AJjZSuBGYBWwGfhXM/N01OOjDa0AOnVSRNJKQiXvnHvUOTca//R5YGH84+uB+51zQ865Q8B+YF0i+0pUbX2Y5eUFLC8v8DKGiMiUmsw1+ZuBLfGPFwDNJ207Gn/s95jZrWZWZ2Z1kUhkEuO8qaN3iBcOdehm3SKSdk45gtHMHgcmasc7nXO/ij/nTmAUuO93XzbB891Er++cuxu4G6CmpmbC5yTq8T2txJzOqhGR9HPKknfOXf1u283sJuD9wFXOud+V9FGg4qSnLQTeONuQidpSH6aiZAar5hd6FUFExBOJnl2zGfhT4APOuf6TNv0auNHMcs1sCVAFvJjIvs7WicERntnfzuZVczGb6B8YIiL+legdM74D5AKPxQv0eefc551zDWb2ALCbsWWcLzrnognu66w8ubeNkajTVa4ikpYSKnnn3PJ32XYXcFcirz8ZtuwKUz4rlwsrir2OIiIy5Xx9xevAcJRtTW1sWjWXjAwt1YhI+vF1yW9vamNwJKZTJ0Ukbfm65Gvrw8zOz2bdkhKvo4iIeMK3JT80GuWJPW1cc84csjJ9+zZFRN6Vb9vv2QMd9AyNcu25WqoRkfTl25LfWh+mIDeLDcvLvI4iIuIZX5b8aDTGo7tbuXJFOblZng6/FBHxlC9Lfsfh43T2DesCKBFJe74s+dr6FnKzMri8OuB1FBERT/mu5GMxx9aGVkLBAPk5iU5tEBFJbb4r+VeOdhE+MailGhERfFjyW+vDZGUYV50zx+soIiKe81XJO+eobQizfnkZRTOyvY4jIuI5X5X8npYejnT0a1aNiEicr0q+tiFMhsE1K7VUIyICfiv5+hYuqiyhrCDX6ygiItOCb0r+QKSXptZenVUjInIS35T81oYwAJtWqeRFRH7HNyVfWx/m/IrZzJ89w+soIiLThi9K/ljXAK8d7WazjuJFRN7CFyXfPzTKNSvnaD1eRORtfDHcpWrOLL7/qRqvY4iITDu+OJIXEZGJqeRFRHxMJS8i4mMqeRERH1PJi4j4mEpeRMTHVPIiIj6mkhcR8TFzznmdYZyZRYAjXuc4C2VAu9chppjec3pIt/ecqu93sXMuMNGGaVXyqcrM6pxzaXXJrd5zeki39+zH96vlGhERH1PJi4j4mEp+ctztdQAP6D2nh3R7z757v1qTFxHxMR3Ji4j4mEpeRMTHVPIJMLMKM3vSzPaYWYOZfcXrTFPBzDLN7GUz+43XWaaCmc02swfNbG/89/pSrzMlm5n91/j3dL2Z/dTM8rzONNnM7B4zazOz+pMeKzGzx8xsX/z/xV5mnAwq+cSMAl9zzp0DXAJ80cxWepxpKnwF2ON1iCn0T0Ctc24FcD4+f+9mtgD4MlDjnFsNZAI3epsqKf4D2Py2x/4MeMI5VwU8Ef88pankE+Cca3HOvRT/uIexP/wLvE2VXGa2EHgf8AOvs0wFMysENgL/DuCcG3bOdXmbakpkATPMLAvIB97wOM+kc849BXS+7eHrgXvjH98L/OGUhkoClfwkMbNK4ELgBW+TJN23ga8DMa+DTJGlQAT4YXyJ6gdmNtPrUMnknDsGfAt4HWgBup1zj3qbasrMcc61wNhBHFDucZ6EqeQngZkVAD8HvuqcO+F1nmQxs/cDbc65nV5nmUJZwBrgu865C4E+fPBP+HcTX4e+HlgCzAdmmtknvE0lZ0slnyAzy2as4O9zzv3C6zxJtgH4gJkdBu4HrjSzH3sbKemOAkedc7/7F9qDjJW+n10NHHLORZxzI8AvgPUeZ5oqrWY2DyD+/zaP8yRMJZ8AMzPG1mr3OOf+wes8yeacu8M5t9A5V8nYD+J+65zz9RGecy4MNJtZdfyhq4DdHkaaCq8Dl5hZfvx7/Cp8/sPmk/wauCn+8U3ArzzMMimyvA6Q4jYAnwR2mdkr8ce+4Zx7xMNMMvm+BNxnZjnAQeAzHudJKufcC2b2IPASY2eQvYwfL/c3+ylwOVBmZkeBvwD+BnjAzG5h7C+7G7xLODk01kBExMe0XCMi4mMqeRERH1PJi4j4mEpeRMTHVPIiIj6mkhcR8TGVvIiIj/1/whNa23beZWoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Beretta SC 70\n",
    "plt.plot([1,2,3,4,5,6,7,8,9,10,11],[-23,-12,-9,-7,-6,-5,-4,-3,-2,-1,0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x117662208>]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# M16A2\n",
    "plt.plot([1,2,3,4,5,6,7,8,9,10,11],[-22,-12,-9,-7,-6,-5,-4,-3,-2,-1,0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Gun Accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-30"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# number of combat actions aiming\n",
    "x = 1\n",
    "\n",
    "# aiming modifier (tuned to the AK 47)\n",
    "y = round(6.606656 + (-35531390 - 6.606656) / (1 + ( x / 1.086559e-11) ** 0.5550615))\n",
    "\n",
    "# size modifier, -7 to 7\n",
    "z = 7 #heavy machinegun\n",
    "# z = -7 #light handgun\n",
    "\n",
    "m = y - z\n",
    "\n",
    "m"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x116e99b70>]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}