bipolaroidbipolaroid/colour_lut.ipynb
2024-04-12 20:11:56 +01:00

58 lines
33 KiB
Text

{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAA1IAAAINCAYAAAA0iU6RAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy81sbWrAAAACXBIWXMAAA9hAAAPYQGoP6dpAABeKElEQVR4nO3deXhU5d3/8c9JSAKJEBICJJGQRAUXCMj2KNAKqGyCgvgTLG0Ft6cW0VJBDFoqKBKlD4hCXVotuCFoAXeRKIKyaYiAQZSiJgRwKLJNgAxJSM7vD5wxQyaZmWyzvV/XlV6Zc87MfCfcpny47/O9DdM0TQEAAAAAPBbm6wIAAAAAINAQpAAAAADASwQpAAAAAPASQQoAAAAAvESQAgAAAAAvEaQAAAAAwEsEKQAAAADwEkEKAAAAALzUxNcF+IOKigr9+OOPat68uQzD8HU5AAAAAHzENE0dP35cycnJCgurft6JICXpxx9/VEpKiq/LAAAAAOAn9u7dq3bt2lV7niAlqXnz5pLO/LBatGjh01rKysq0evVqDRo0SBERET6tBf6LcQJ3GCPwBOMEnmCcwJ1gGyNFRUVKSUlxZITqEKQkx3K+Fi1a+EWQio6OVosWLYJiIKJhME7gDmMEnmCcwBOME7gTrGPE3S0/NJsAAAAAAC8RpAAAAADASwQpAAAAAPAS90h5yDRNnT59WuXl5Q36PmVlZWrSpIlOnTrV4O+FwOXrcRIREaHw8PBGf18AAAB/QZDyQGlpqSwWi4qLixv8vUzTVGJiovbu3cueVqiWr8eJYRhq166dzjnnnEZ/bwAAAH9AkHKjoqJC+fn5Cg8PV3JysiIjIxv0L64VFRU6ceKEzjnnnBo3AENo8+U4MU1TP/30k/bt26cOHTowMwUAAEISQcqN0tJSVVRUKCUlRdHR0Q3+fhUVFSotLVXTpk0JUqiWr8dJ69atVVBQoLKyMoIUAAAISfxN3UOEGuAXLDsFAAChjnQAAAAAAF4iSMGvpaWlaf78+T5578WLF6tly5Y+ee+6WLt2rQzD0LFjx3xdCgAAQNAiSAWp8ePHa+TIkV49xzAMvfnmmw1ST2Np7PBjGEaVr1/96leN9v5XXnmlJk2a5HSsT58+slgsio2NbbQ6AAAAQg3NJlDvysrKFBER4esyGs2iRYs0ZMgQx+PIyEgfVnPm/RMTE31aAwAAQLBjRqoRWaw2bfz+kCxWW6O/d//+/XXPPfdo6tSpio+PV2JiombMmOE4n5aWJkm6/vrrZRiG47EkvfPOO+rRo4eaNm2q8847TzNnztTp06cd5w3D0LPPPqsRI0YoJiZGs2bNciwve++999S1a1c1bdpUl112mfLy8pzqWr58uTp16qSoqCilpaVp7ty5NX6OefPmKSMjQzExMUpJSdGECRN04sQJSWeWtN1yyy2yWq2O2SH7ZywtLdXUqVN17rnnKiYmRpdddpnWrl3r9NqLFy9W+/btFR0dreuvv16HDx/26GfbsmVLJSYmOr7i4+MdP5ezZ/hatmypxYsXS5IKCgpkGIZWrFihAQMGKDo6Wl27dtWmTZucnrNhwwb169dP0dHRiouL0+DBg3X06FFNmDBB69at05NPPun4vAUFBS6X9rn7OaelpWn27Nm69dZb1bx5c7Vv317/+Mc/PPr8AAAAoYgg5SXTNFVcetrrr5c3FajvY2s09p+fq+9ja/TypoJqr7WVlrs8bppmnWp/8cUXFRMTo88//1xz5szRww8/rOzsbElSTk6OpDOzKxaLxfH4ww8/1O9+9zvdc8892rlzp5577jktXrxYjz76qNNrP/TQQxoxYoTy8vJ06623Oo7fd999+r//+z/l5OSoTZs2uu6661RWViZJys3N1ejRo3XTTTcpLy9PM2bM0PTp0x1Bw5WwsDA99dRT2rFjh1588UWtWbNGU6dOlXRmSdv8+fPVokULWSwWWSwWTZkyRZJ0yy23aMOGDVq6dKm++uor3XjjjRoyZIh2794tSfr888916623asKECdq2bZsGDBigWbNm1enn7akHH3xQU6ZM0bZt29SxY0f95je/cQTVbdu26aqrrlKnTp20adMmrV+/Xtdee63Ky8uVlZWl3r1764477nB83pSUlCqv7+nPee7cuerZs6e2bt2qCRMm6I9//KO+/fbbxvgRAAAABByW9nnJVlauS/76YZ1eo8KUpr/1taa/9bVXz9v58GBFR9b+j6xLly566KGHJEkdOnTQwoUL9fHHH2vgwIFq3bq1pF9mV+weffRRZWZmaty4cZKk8847T4888oimTp3qeC1JGjt2rFOAys/Pl3QmYA0cOFDSmSDXrl07rVy5UqNHj9a8efN01VVXafr06ZKkjh07aufOnfrb3/6m8ePHu/wMle8HSk9P1yOPPKI//vGPevrppxUZGanY2FgZhuH0Gb7//nu99tpr2rdvn5KTkyVJU6ZM0apVq7Ro0SLNnj1bTz75pAYPHqzMzExHLRs3btSqVavc/lx/85vfOO2l9Morr3h1f9qUKVM0bNgwSdLMmTPVqVMnfffdd7rooos0Z84c9ezZU08//bTj+k6dOqmiokJFRUWKjIxUdHR0jUv5PP05X3PNNZowYYIk6f7779cTTzyhtWvX6qKLLvL4swAAAIQKZqRCSJcuXZweJyUl6eDBgzU+Jzc3Vw8//LDOOeccx5d9BqS4uNhxXc+ePV0+v3fv3o7v4+PjdeGFF+qbb76RJH3zzTfq27ev0/V9+/bV7t27VV5e7vL1PvnkEw0cOFDnnnuumjdvrptvvlmHDx/WyZMnq/0MX375pUzTVMeOHZ0+x7p16/T99987aqlc69m11+SJJ57Qtm3bHF/24Oipyn8uSUlJkuT4c7HPSNWFpz/nynXYw6i78QEAAFAffHkLTG0xI+WlZhHh2vnwYK+ec8B6SlfPW6eKSivzwgzpo3v7KTG2qdO1FRUVOl50XM1bNK+yCXCziHDVxdkNIAzDUEVFRY3Pqaio0MyZMzVq1Kgq55o2/aX2mJgYj+uwb+ZqmmaVjV1rWr64Z88eXXPNNbrzzjv1yCOPKD4+XuvXr9dtt93mWC5Y3WcIDw9Xbm6u08yRJJ1zzjlu39edxMREXXDBBVWOG4ZR5XVd1Vn5z8X+87D/uTRr1qzWddl5+nOuzfgAAACoq9e+KNQDK/Jk6szfkbNGZWhMr/a+LsstgpSXDMPwenndea3PUdaoDD2wYofKTVPhhqHZozrrvNbnVLm2oqJCpyPDFR3ZpEqQamgRERFVZoK6d++uXbt2uQwKnti8ebPatz/zH8LRo0f1n//8x7FU7JJLLtH69eudrt+4caM6duxYJfBI0pYtW3T69GnNnTvX8bN5/fXXna6JjIys8hm6deum8vJyHTx4UL/+9a9d1nnJJZdo8+bNVWqvi9atW8tisTge796922kWzxNdunTRxx9/rJkzZ7o87+rP7Gze/pwBAAAai8Vqc4Qo6cwtMA+s2KErOrZWUmzd/0G5IRGkGsmYXu11RcfWKjhUrLSEaL8cGGlpafr444/Vt29fRUVFKS4uTn/96181fPhwpaSk6MYbb1RYWJi++uor5eXledSM4eGHH1arVq3Utm1bPfjgg0pISHDcPzR58mT16tVLjzzyiMaMGaNNmzZp4cKFTvcDVXb++efr9OnTWrBgga699lpt2LBBzz77bJXPcOLECX388cfq2rWroqOj1bFjR/32t7/VzTffrLlz56pbt246dOiQ1qxZo4yMDF1zzTW655571KdPH82ZM0cjR47U6tWrPbo/qiZXXnmlFi5cqMsvv1wVFRW6//77vW4LP23aNGVkZGjChAm68847FRkZqU8++UQ33HCDIiMjlZaWps8//1wFBQU655xzHB0DK/P25wwAANBYduyz6ux1MuWmqYJDxX759+XKuEeqESXFNlPv81v57aCYO3eusrOzlZKSom7dukmSBg8erHfffVfZ2dnq1auXLr/8cs2bN0+pqakeveZjjz2mP/3pT+rRo4csFovefvttxz5L3bt31+uvv66lS5eqc+fO+utf/6qHH3642kYTl156qebNm6fHH39cnTt31quvvqqsrCyna/r06aM777xTY8aMUevWrTVnzhxJZ7oR3nzzzZo8ebIuvPBCXXfddfr8888dXe4uv/xyPf/881qwYIEuvfRSrV69Wn/5y19q82N0mDt3rlJSUnTFFVdo7NixmjJliqKjo716jY4dO2r16tXavn27/ud//ke9e/fWW2+9pSZNzvwbyOTJkxUeHq5LLrlErVu3VmFhYZXX8PbnDAAA0BgsVpte3rynyvFww1Bagnd/Z/IFw6xrT+0gUFRUpNjYWFmtVrVo0cLp3KlTp5Sfn6/09HSne4Iair0bW4sWLRp9aV99Wrt2rQYMGKCjR4+qZcuWvi4n6Ph6nDT2fxfwXllZmd5//31dc801IbVBNrzDOIEnGCdwpzZjZFlOoTJX5MmeRAxJpuS4BcaX90jVlA0qY2kfAAAAgEZjsdo0rVKIks4EqYVju6l7apzfrt46W+BOeQAAAAAIOPmHTjp1s5akCknxMVEBE6IkZqTQQPr371+nluIAAAAIPharTctz91U5Hij3RVVGkAIAAADQ4JblFCpzeV6VLn32+6ICaTZKIkgBAAAAaGAWq+1Mc4lKx8IkLQiw+6Iq4x4pD7FMDfgF/z0AAABPWaw2vbixQGf/9SEQ74uqjBkpN+wtHIuLi9WsWWD+IQP1rbS0VJIUHh7u40oAAIA/W5ZTqGkr8qo0l5AC876oyghSboSHh6tly5Y6ePCgJCk6OlqGYTTY+1VUVKi0tFSnTp0K6H2k0LB8OU4qKir0008/KTo62rExMAAAwNnsbc6rC1GBeF9UZfwtyAOJiYmS5AhTDck0TdlsNjVr1qxBAxsCm6/HSVhYmNq3b88YBQAA1frih8MuQ9T0YRfrmi5JAR2iJIKURwzDUFJSktq0aaOysrIGfa+ysjJ9+umnuuKKK9g9HNXy9TiJjIxkxhQAAFRr6ReFylyRV+V4uGEERYiSCFJeCQ8Pb/B7QsLDw3X69Gk1bdqUIIVqMU4AAIC/si/pO1uYoYBfzleZT/9JOSsrS7169VLz5s3Vpk0bjRw5Urt27XK6Zvz48TIMw+nr8ssvd7qmpKREd999txISEhQTE6PrrrtO+/ZV3egLAAAAQMOxWG3Keu/bKntFSdJTN3XTmF7tG72mhuLTILVu3Trddddd2rx5s7Kzs3X69GkNGjRIJ0+edLpuyJAhslgsjq/333/f6fykSZO0cuVKLV26VOvXr9eJEyc0fPhwlZeXN+bHAQAAAELWG7n71OexNXr7qx+rnAs3DPVIi/NBVQ3Hp0v7Vq1a5fR40aJFatOmjXJzc3XFFVc4jkdFRTkaPpzNarXqhRde0Msvv6yrr75akvTKK68oJSVFH330kQYPHtxwHwAAAACAjpVIM97aWWWvKCk4OvS54ld3i1utVklSfHy80/G1a9eqTZs26tixo+644w6n7nm5ubkqKyvToEGDHMeSk5PVuXNnbdy4sXEKBwAAAEKUxXpKG/5ruAxR04ddrPWZA4JqSZ+d3zSbME1T9957r371q1+pc+fOjuNDhw7VjTfeqNTUVOXn52v69Om68sorlZubq6ioKB04cECRkZGKi3OeKmzbtq0OHDjg8r1KSkpUUlLieFxUVCTpTCe0hu7K5479/X1dB/wb4wTuMEbgCcYJPME4QU3eyN2nv7y1UxVm1YZsYYY08OLWSohuElDjx9Na/SZITZw4UV999ZXWr1/vdHzMmDGO7zt37qyePXsqNTVV7733nkaNGlXt65mmWe0eN1lZWZo5c2aV46tXr1Z0tH/srpydne3rEhAAGCdwhzECTzBO4AnGCc52rESa8WW4TFX+O7cpyZAhU6PTK7R1wxpt9VWBtVRcXOzRdX4RpO6++269/fbb+vTTT9WuXbsar01KSlJqaqp2794t6cxmuaWlpTp69KjTrNTBgwfVp08fl68xbdo03XvvvY7HRUVFSklJ0aBBg9SiRYt6+ES1V1ZWpuzsbA0cOJC21qgW4wTuMEbgCcYJPME4gSsW6ym9n3dApv5z1hlDDwztqCGdEpUU29QntdWVfbWaOz4NUqZp6u6779bKlSu1du1apaenu33O4cOHtXfvXiUlJUmSevTooYiICGVnZ2v06NGSJIvFoh07dmjOnDkuXyMqKkpRUVFVjkdERPjNLwh/qgX+i3ECdxgj8ATjBJ5gnMBuWU6hpq3IU0U1jSWuvbRdQDeW8HSc+zRI3XXXXVqyZIneeustNW/e3HFPU2xsrJo1a6YTJ05oxowZuuGGG5SUlKSCggI98MADSkhI0PXXX++49rbbbtPkyZPVqlUrxcfHa8qUKcrIyHB08QMAAABQd/bNdl2FqGDbcNcdnwapZ555RpLUv39/p+OLFi3S+PHjFR4erry8PL300ks6duyYkpKSNGDAAC1btkzNmzd3XP/EE0+oSZMmGj16tGw2m6666iotXrxY4eFVb3oDAAAAUDu5e466DFEjU8t1740D1D6hedWTQcrnS/tq0qxZM3344YduX6dp06ZasGCBFixYUF+lAQAAAKhkWU6h7l+eV+V4mCF1a2UG7D1RteVX+0gBAAAA8D/2JX1nCzOkWSMuUcuq7QeCHkEKAAAAQLUsVptez9nrcknfUzd10409au66Haz8ov05AAAAAP/jrkNfj7S4qidCBDNSAAAAAKqoqUNfuGGEVIc+V5iRAgAAAFBF/k8nXYao6cMu1jVdkkI6REnMSAEAAAA4i8Vq09KcwirHww2DEPUzZqQAAAAAOCzLKVTm8jzZJ6MMSaZYznc2ghQAAAAASWdmojJX/BKipDNBauHYbuqeGkeIqoSlfQAAAABksdq0aH2+zLPui6qQFB8TRYg6CzNSAAAAQIhz1+Y8LSG68Yvyc8xIAQAAACGMNue1w4wUAAAAEMI+/+Ewbc5rgRkpAAAAIEQt/aJQk5Ztr3KcNufuEaQAAACAEGRf0ne2MEMs5/MAS/sAAACAEGOx2vTwO1/LxYo+PXVTNw3vmtzoNQUaghQAAAAQQpblFJ7ZK6qa5hI90uIav6gAxNI+AAAAIEQ4NtylQ1+dMSMFAAAAhACL1aaXN+1xGaLo0Oc9ghQAAAAQ5NxtuEuI8h5BCgAAAAhSFqtNWwqOsJyvARCkAAAAgCBU0yyUxHK+uqLZBAAAABBk7HtEVReiWM5XdwQpAAAAIIhYrDat/HJfjSGK5Xx1x9I+AAAAIEjUtJwvTNKCsd3UPTWOEFUPCFIAAABAEKhpOZ99FmpYl+TGLyxIEaQAAACAIJC756jLEEVTiYbBPVIAAABAgFuWU6iJS7ZWOU5TiYbDjBQAAAAQoCxWmzZ8d0iZy/OqnAszRFOJBkSQAgAAAALQspxCZS7PUzXN+fTUTd00vCv3RDUUlvYBAAAAAcZitdUYosINQz3S4hq1plBDkAIAAAACiMVq0/yPdtcYoljS1/BY2gcAAAD4OYvVpvxDJ5W336rHPvhWJvtE+RxBCgAAAPBjNW2ya8c+UY2PIAUAAAD4qZo22bVjnyjf4B4pAAAAwE9Vt8muHftE+Q5BCgAAAPBDy3IKdbeLTXbtaCrhWyztAwAAAPyIxWrTloIjylxRtb15mCHdP+QidWnXUmkJ0YQoHyJIAQAAAH7CXWMJNtn1HyztAwAAAPyAu8YSbLLrXwhSAAAAgI9ZrDYt/aKwxhDF/VD+haV9AAAAgA/VtJyPTXb9F0EKAAAA8AGnphIuQhSb7Po3ghQAAADQyNw1lWCTXf/HPVIAAABAI/KkqQQhyv8RpAAAAIBG9PkPh2kqEQRY2gcAAAA0MIvVpvxDJ5W375iyPthV5TxNJQIPQQoAAABoQO7uhwozpKxRGTSVCDAEKQAAAKABuOvKZ/fUTd00vCshKtAQpAAAAIB65m4Wyi7cMNQjLa5xikK9otkEAAAAUI/cdeWzo7FEYGNGCgAAAKgnFqtNb27dX2NXvqlDLlSXdi2VlhBNiApgBCkAAACgHtS0nI+ufMGHIAUAAADU0fa9R5W5PE+uJqLsS/joyhdcCFIAAABALdj3hsotOKq52f9xec30YRfrmi5JzEIFIYIUAAAA4CVPuvKFGwYhKogRpAAAAAAPOfaGqmYZn12YITryBTmCFAAAAOABT/eGCpO0ckIfdU1hf6hgRpACAAAA3LBYbcpckSfTw72hCFHBjyAFAAAA1MBitem1LwqrDVHsDRWaCFIAAADAWewd+fL2W/X4B9+yNxSqIEgBAAAAlXjakY+9oUIbQQoAAAD42fa9R93eC8XeUJDOzEgCAAAAIW9ZTqFG/n1jjSGKvaFgx4wUAAAAQprFatPnP7jfG8q+nI8QBYkgBQAAgBDkaCax75ge+2BXtQEqzJDuH3IRHflQBUEKAAAAIYWNdVEfCFIAAAAICRarTVsKjrCxLuoFQQoAAABBzWK16V/r8/XC+nyPZqHYGwqe8GnXvqysLPXq1UvNmzdXmzZtNHLkSO3atcvpGtM0NWPGDCUnJ6tZs2bq37+/vv76a6drSkpKdPfddyshIUExMTG67rrrtG/fvsb8KAAAAPBDy3IK1Sdrjf75mfsQFW4YyrohQ8O6JBOi4JZPg9S6det01113afPmzcrOztbp06c1aNAgnTx50nHNnDlzNG/ePC1cuFA5OTlKTEzUwIEDdfz4ccc1kyZN0sqVK7V06VKtX79eJ06c0PDhw1VeXu6LjwUAAAAfs1htemf7/jPL+Gq4LtwwNG3oRXrtjsu1PnOAxvRq32g1IrD5dGnfqlWrnB4vWrRIbdq0UW5urq644gqZpqn58+frwQcf1KhRoyRJL774otq2baslS5boD3/4g6xWq1544QW9/PLLuvrqqyVJr7zyilJSUvTRRx9p8ODBjf65AAAA0Pgcnfj2W/X4B9/WOAPFEj7UlV/dI2W1WiVJ8fHxkqT8/HwdOHBAgwYNclwTFRWlfv36aePGjfrDH/6g3NxclZWVOV2TnJyszp07a+PGjS6DVElJiUpKShyPi4qKJEllZWUqKytrkM/mKfv7+7oO+DfGCdxhjMATjBN4IlDGyRu5+/SXt3a6Xb4nnWlpPmvEJRp0cWtJ/v/Z/F2gjBFPefo5/CZImaape++9V7/61a/UuXNnSdKBAwckSW3btnW6tm3bttqzZ4/jmsjISMXFxVW5xv78s2VlZWnmzJlVjq9evVrR0dF1/iz1ITs729clIAAwTuAOYwSeYJzAE/46To6VSPnHDb24O0ymDDdXmxqQVKH+SaZi/vuV3n//q0apMVT46xjxVnFxsUfX+U2Qmjhxor766iutX7++yjnDcP6PwjTNKsfOVtM106ZN07333ut4XFRUpJSUFA0aNEgtWrSoRfX1p6ysTNnZ2Ro4cKAiIiJ8Wgv8F+ME7jBG4AnGCTzhz+Pkjdx9munBLJQhaf7oLurWvqWSYps2Sm2hxJ/HSG3YV6u54xdB6u6779bbb7+tTz/9VO3atXMcT0xMlHRm1ikpKclx/ODBg45ZqsTERJWWluro0aNOs1IHDx5Unz59XL5fVFSUoqKiqhyPiIjwmz98f6oF/otxAncYI/AE4wSe8Ldxsn3vUT345s4aG0lIv+wHNaJ7SqPUFcr8bYzUlqefwadd+0zT1MSJE7VixQqtWbNG6enpTufT09OVmJjoNE1YWlqqdevWOUJSjx49FBER4XSNxWLRjh07qg1SAAAACDwWq00bvz+kJz/+j0b8fWO1IYpOfGgMPp2Ruuuuu7RkyRK99dZbat68ueOeptjYWDVr1kyGYWjSpEmaPXu2OnTooA4dOmj27NmKjo7W2LFjHdfedtttmjx5slq1aqX4+HhNmTJFGRkZji5+AAAACGzLcgo1bUUenfjgN3wapJ555hlJUv/+/Z2OL1q0SOPHj5ckTZ06VTabTRMmTNDRo0d12WWXafXq1WrevLnj+ieeeEJNmjTR6NGjZbPZdNVVV2nx4sUKDw9vrI8CAACABmCx2rSl4Igyl9e8H1SYIWWNOrOZLtAYfBqkTNN9f0rDMDRjxgzNmDGj2muaNm2qBQsWaMGCBfVYHQAAAHzBm/2gpDMzUSsn9FHXlLiaLwTqkV80mwAAAAAkz5bwVWZvJkGIQmMjSAEAAMBn7LNP6QkxOlh0Spkr8uRu0VK4YWjqkAvVpV1LpSVEcz8UfIIgBQAAgEbl7dI9O5pJwJ8QpAAAANBovF26Z2dfwkczCfgLghQAAAAanL37njchKsyQ7h9yEUv44JcIUgAAAGhQtZmFohMf/B1BCgAAAA1m+96jbveAkiTj5/8xTTrxITAQpAAAAFBnlbvvSVL+oZPa+N1hLfzku2qfc3b3PUkqOFTMMj4EBIIUAAAA6qTy0j3j52M1zUDV1H2PAIVAQZACAABArdgbSFReuuduCV+YIWWNyqD7HgIeQQoAAAAeq+0eUBINJBBcCFIAAADwSG33gJJoIIHgQ5ACAACASxarTd8dKNKxEmn7PqsyV+TJdBOizu6+V7mZBPc/IZgQpAAAAODgeuleuPTl5zU+r3IDCYnuewh+BCkAAABIqmnpnuHqcgf7sr3KDSQIUAh2BCkAAIAQZZ99iokMV+GRYq/ufwozpPuHXMSyPYQsghQAAEAIqkvjCLrvAQQpAACAoGefeUpPiJEkrdv1kzJX5HnxCqYMw3A0kKD7HkCQAgAACEqOphH7jumxVbvcdts7m73jXqekc/T9ts0acOWV2m8tZRkf8DOCFAAAQJCp67I9e/e9pNhmKisr0+FvpKTYpmqf0LzeawUCFUEKAAAgwFVeunew6JQyl+epFhnKZfc9AK4RpAAAAALE2fc61WXpnvTL7FO7uGYqLq1g2R7gBYIUAABAAKi8XM++q5O32cn4+X8qN41g9gmoHYIUAACAH6qyXG9FnmPWyZsAdfZ+T5JUcKiY2SegjghSAAAAfsLRaW+/VY9/8G2tmkVUVt1+TwQooO4IUgAAAH6gLp327Fwt3WO/J6BhEKQAAAB8wD77FBMZrsIjxV6FqLMD09QhF7J0D2hkBCkAAIAG5LLTXh2W7oVJWnlXH7Vp0bTawESAAhoeQQoAAKCBNFSnPftyPQIT4DsEKQAAgHpw9szTloIjTsv1vAlQLNcD/B9BCgAAoI7qY+ZJ+mWD3O6pcSzXA/wcQQoAAMBLVfZ4Wp7nCE61bbrHBrlAYCFIAQAAVMNlo4h9x/TYql2OzXE9VV2nvejIMBWXVrBsDwgwBCkAAAAXGmK5nsS9TkCwIEgBAADIxXK9FXmOWSdvApSrLnuVl+sRoIDgQJACAAAhpb73darMkz2eAAQHghQAAAgZ9bVcz449noDQRZACAABBq6GW67HHEwCCFAAACHjulusZqv3MkyfL9QhQQOghSAEAgIDmyXK9ujaLYLkegLMRpAAAQEBhuR4Af0CQAgAAAePs2SeW6wHwFYIUAADwS2ff9/T5D0eUuTzPEZ5YrgfAlwhSAADA5+yhKSYyXCdLy5W336rHPvjWsWTPUyzXA9BYahWkXn75ZT377LPKz8/Xpk2blJqaqvnz5ys9PV0jRoyo7xoBAEAQq7xcry5YrgegMYV5+4RnnnlG9957r6655hodO3ZM5eXlkqSWLVtq/vz59V0fAAAIIharTRu/PySL1SaL1aZ3tu9X5vLahShDkvFzm75ww1DWDRnqmhKnpNhm6n1+K0ITgAbl9YzUggUL9M9//lMjR47UY4895jjes2dPTZkypV6LAwAAgcvVcj37vk51ESZpwdhu6p565h4nlusB8AWvg1R+fr66detW5XhUVJROnjxZL0UBAIDAVl/L9STXjSKGdUl2nCdAAfAFr4NUenq6tm3bptTUVKfjH3zwgS655JJ6KwwAAASGs7vrbSlw7q5XGzSKAODvvA5S9913n+666y6dOnVKpmnqiy++0GuvvaasrCw9//zzDVEjAADwEzUt1/v5dqVaBSj7cr12cc1UXFpBowgAfs/rIHXLLbfo9OnTmjp1qoqLizV27Fide+65evLJJ3XTTTc1RI0AAMAPuFuuV9d9nSov1wMAf1er9ud33HGH7rjjDh06dEgVFRVq06ZNfdcFAAD8hMVqO7Ncb0We1/s6VcZyPQDBpE4b8iYkJNRXHQAAwA/VpWkEy/UABLNaNZsw7Js2uPDDDz/UqSAAAOAbZzeN+CLfu6YRLNcDEEq8DlKTJk1yelxWVqatW7dq1apVuu++++qrLgAA0Egs1lN6+fPden59vtdL91iuByBUeR2k/vSnP7k8/ve//11btmypc0EAAKDxbPqvoUn/96nHs04s1wOAM8Lq64WGDh2q5cuX19fLAQCAemax2rTx+0OyWG2yWG16a9uPWvpDmMchKtwwlHVDhoZ1SVbXlDj1Pr8VoQlAyKpTs4nK/v3vfys+Pr6+Xg4AANQD+31Plfd7clb9fc929lmo7qlxBCcA+JnXQapbt25OzSZM09SBAwf0008/6emnn67X4gAAQO3VtuMeTSMAwD2vg9TIkSOdHoeFhal169bq37+/LrroovqqCwAAeKly172DRae83vcpTNLtV6Trlr7pkmgaAQA18TpIPfTQQw1RBwAAqAX3S/fcMyQtdLF0jwAFANXzKEgVFRV5/IItWrSodTEAAMBz9bF0z5CpR0d2YukeAHjJoyDVsmXLGjfhlc7cK2UYhsrLy+ulMAAA8IuzN8vdUnDEqxAVZkj3D7nIab+n7/9bpO+3bdaNPdo1VNkAELQ8ClKffPJJQ9cBAACqUXnmyf7Pmt5MQoVJWjmhj7qmxDkdT4huosPf1FeVABBaPApS/fr1a+g6AACAC9v3HlXm8jxHcPIkQLnqund2iAIA1E2t95EqLi5WYWGhSktLnY536dKlzkUBABDK7Mv4cgqO6Ins3R49J9wwNHXIhU5L9+i6BwANx+sg9dNPP+mWW27RBx984PI890gBAFB73jaQqGmzXAIUADScMG+fMGnSJB09elSbN29Ws2bNtGrVKr344ovq0KGD3n77ba9e69NPP9W1116r5ORkGYahN9980+n8+PHjZRiG09fll1/udE1JSYnuvvtuJSQkKCYmRtddd5327dvn7ccCAMCnLFab3tm+X5nLaw5RhiR7/6dww1DWDRka1iWZ0AQAjczrGak1a9borbfeUq9evRQWFqbU1FQNHDhQLVq0UFZWloYNG+bxa508eVJdu3bVLbfcohtuuMHlNUOGDNGiRYscjyMjI53OT5o0Se+8846WLl2qVq1aafLkyRo+fLhyc3MVHh7u7ccDAKDB2ZfuxUSG62Rpucd7QIVJWnlXH7Vp0ZRlewDgY14HqZMnT6pNmzaSpPj4eP3000/q2LGjMjIy9OWXX3r1WkOHDtXQoUNrvCYqKkqJiYkuz1mtVr3wwgt6+eWXdfXVV0uSXnnlFaWkpOijjz7S4MGDvaoHAICGVtu9n85uGkGAAgDf8jpIXXjhhdq1a5fS0tJ06aWX6rnnnlNaWpqeffZZJSUl1XuBa9euVZs2bdSyZUv169dPjz76qCPI5ebmqqysTIMGDXJcn5ycrM6dO2vjxo3VBqmSkhKVlJQ4Hts3HC4rK1NZWVm9fwZv2N/f13XAvzFO4A5jxP9YrKf05R7nDnzuhBnSfYM6KOPcWLWPj1ZSbNN6/TNlnMATjBO4E2xjxNPP4XWQmjRpkiwWiyTpoYce0uDBg/Xqq68qMjJSixcv9vblajR06FDdeOONSk1NVX5+vqZPn64rr7xSubm5ioqK0oEDBxQZGam4OOeWrm3bttWBAweqfd2srCzNnDmzyvHVq1crOjq6Xj9DbWVnZ/u6BAQAxgncYYz41rES6adThgpPSO8UhslUzZvb/8LU+A4VSm9uqmXRNzpcJB2WtLWB6mScwBOME7gTLGOkuLjYo+u8DlK//e1vHd9369ZNBQUF+vbbb9W+fXslJCR4+3I1GjNmjOP7zp07q2fPnkpNTdV7772nUaNGVfs80zRlGNX/n9W0adN07733Oh4XFRUpJSVFgwYNUosWLeqn+FoqKytTdna2Bg4cqIiICJ/WAv/FOIE7jBHfeyN3n2a+tdPrJXxhhjRrRCfd2KNdwxRWCeMEnmCcwJ1gGyP21WrueB2k1q1b57RBb3R0tLp37+7ty9RKUlKSUlNTtXv3mT01EhMTVVpaqqNHjzrNSh08eFB9+vSp9nWioqIUFRVV5XhERITf/OH7Uy3wX4wTuMMYaXwWq01bCo7oL16EqLP3gGrs+58YJ/AE4wTuBMsY8fQzeB2kBg4cqMTERI0dO1a/+93v1LlzZ6+Lq63Dhw9r7969jnuxevTooYiICGVnZ2v06NGSJIvFoh07dmjOnDmNVhcAAJLnjSTsez+1i2um4tIKuu8BQADyOkj9+OOPWrp0qV577TXNmTNHnTt31u9+9zuNHTtW7dp5twzhxIkT+u677xyP8/PztW3bNsXHxys+Pl4zZszQDTfcoKSkJBUUFOiBBx5QQkKCrr/+eklSbGysbrvtNk2ePFmtWrVSfHy8pkyZooyMDEcXPwAAGsP2vZ41krB33xvWJblR6gIANAyvg1RCQoImTpyoiRMnKj8/X0uWLNFLL72kBx54QFdccYXWrFnj8Wtt2bJFAwYMcDy237c0btw4PfPMM8rLy9NLL72kY8eOKSkpSQMGDNCyZcvUvHlzx3OeeOIJNWnSRKNHj5bNZtNVV12lxYsXs4cUAKDB2feD2vjdIS385Ptqr/P10j0AQP3zOkhVlp6erszMTHXt2lXTp0/XunXrvHp+//79ZZrV/9vdhx9+6PY1mjZtqgULFmjBggVevTcAAHXhyTI++xK+7qlxhCcACDJhtX3ihg0bNGHCBCUlJWns2LHq1KmT3n333fqsDQAAv2Ox2vT2tv3KXO4mRBlS1g0ZGtYlmRAFAEHI6xmpBx54QK+99pp+/PFHXX311Zo/f75GjhzpN/svAQBQ3+xL+PL2W/XYB9+qhsUUks78K+XKCX3UNSWu5gsBAAHL6yC1du1aTZkyRWPGjKn3faMAAPA3nnbis7M3kyBEAUBw8zpIbdy4sSHqAADA72zfe1SZK/LczkDRTAIAQk+dmk0AABBs7Mv4vtp7TI+t2lXjtTSTAIDQRZACAOBn3izjYz8oAAhtBCkAQMizWG3aUnDE7TK+MEO6f8hFLOEDABCkAAChqXInvsc/+NbtLBSd+AAAlRGkAAAhh058AIC68ihIxcXFyTAMj17wyJEjdSoIAICGYl/C50mIohMfAKAmHgWp+fPnO74/fPiwZs2apcGDB6t3796SpE2bNunDDz/U9OnTG6RIAADqytNZKDrxAQA84VGQGjdunOP7G264QQ8//LAmTpzoOHbPPfdo4cKF+uijj/TnP/+5/qsEAKAOtu89qszleXK3ko9OfAAAT3l9j9SHH36oxx9/vMrxwYMHKzMzs16KAgCgruzNJLYVHtOcD6vfD4olfACA2vA6SLVq1UorV67Ufffd53T8zTffVKtWreqtMAAAasuTZXws4QMA1IXXQWrmzJm67bbbtHbtWsc9Ups3b9aqVav0/PPP13uBAAB4w2K1uQ9RhpQ1KoMlfACAWvM6SI0fP14XX3yxnnrqKa1YsUKmaeqSSy7Rhg0bdNlllzVEjQAAeMRitemdbT+6nYliPygAQF3Vah+pyy67TK+++mp91wIAQK15spyP/aAAAPWlVkHq+++/16JFi/TDDz9o/vz5atOmjVatWqWUlBR16tSpvmsEAKBa7vaGopkEAKAheB2k1q1bp6FDh6pv37769NNPNWvWLLVp00ZfffWVnn/+ef373/9uiDoBAHBisdr0r/X5emF9frWzUNOHXaxruiQRngAA9S7M2ydkZmZq1qxZys7OVmRkpOP4gAEDtGnTpnotDgAAV5blFKpP1hr987PqQ1S4YRCiAAANxusZqby8PC1ZsqTK8datW+vw4cP1UhQAAK7Yl/Flrqh5c137vVCEKABAQ/E6SLVs2VIWi0Xp6elOx7du3apzzz233goDAKAy9oYCAPgTr5f2jR07Vvfff78OHDggwzBUUVGhDRs2aMqUKbr55psbokYAQAizWG16e9t+ZS73YG+oG87sDUWIAgA0NK9npB599FGNHz9e5557rmMPqfLyco0dO1Z/+ctfGqJGAECIWpZTeGYZn5tZqNuvSNctfdMJUACARuN1kIqIiNCrr76qRx55RF9++aUqKirUrVs3dejQoSHqAwCEKIvVVmOIYhkfAMCXvF7a9/DDD6u4uFjnnXee/t//+38aPXq0OnToIJvNpocffrghagQAhBiL1aZXNu2pNkSFGwbL+AAAPuV1kJo5c6ZOnDhR5XhxcbFmzpxZL0UBAEKTxWrTo+/tVJ/H1ujva7+vcj5M0t/HdtP6zAEa06t94xcIAMDPvF7aZ5qmDMOocnz79u2Kj4+vl6IAAKFnWU6hMpdX39bc3tJ8WJfkRq0LAABXPA5ScXFxMgxDhmGoY8eOTmGqvLxcJ06c0J133tkgRQIAgpdjb6gaQtT0YRezuS4AwK94HKTmz58v0zR16623aubMmYqNjXWci4yMVFpamnr37t0gRQIAgpMne0OFGwYhCgDgdzwOUuPGjZMkpaenq0+fPoqIiGiwogAAwc9dVz7pzN5Qs0d1JkQBAPyO1/dI9evXz/G9zWZTWVmZ0/kWLVrUvSoAQFCzWG1avKGgxtbm7A0FAPBnXgep4uJiTZ06Va+//roOHz5c5Xx5eXm9FAYACE41LedjbygAQKDwuv35fffdpzVr1ujpp59WVFSUnn/+ec2cOVPJycl66aWXGqJGAEAQsFhtemf7fmUudx2i2BsKABBIvJ6Reuedd/TSSy+pf//+uvXWW/XrX/9aF1xwgVJTU/Xqq6/qt7/9bUPUCQAIUBarTf9an6/n1+dXu5SPrnwAgEDjdZA6cuSI0tPTJZ25H+rIkSOSpF/96lf64x//WL/VAQACmru9oSS68gEAApPXS/vOO+88FRQUSJIuueQSvf7665LOzFS1bNmyPmsDAAQwR1e+Gq6xb7JLiAIABBqvZ6RuueUWbd++Xf369dO0adM0bNgwLViwQKdPn9a8efMaokYAQICxWG16/rMfauzKR1MJAEAg8zpI/fnPf3Z8P2DAAH377bfasmWLzj//fHXt2rVeiwMABB53m+yGGVLWqDNNJQAACFReB6mztW/fXu3bt6+PWgAAAcxitWlLwZFqN9llbygAQDDxKEg99dRTHr/gPffcU+tiAACByd0sFF35AADBxqMg9cQTT3j0YoZhEKQAIMRYrLYaQxRd+QAAwcijIJWfn9/QdQAAApDFatPrOXtrDFF05QMABKM63SNl/rwI3jCMeikGABA4alrOR1c+AECw83ofKUl66aWXlJGRoWbNmqlZs2bq0qWLXn755fquDQDgp7bvParM5a5DVLhhKOuGM135CFEAgGDl9YzUvHnzNH36dE2cOFF9+/aVaZrasGGD7rzzTh06dMipPToAIHhYrDblHzqpz3b/pGfW/uDyGppKAABChddBasGCBXrmmWd08803O46NGDFCnTp10owZMwhSABCE3HXlk2gqAQAILV4v7bNYLOrTp0+V43369JHFYqmXogAA/sNdVz7pzCa7NJUAAIQSr4PUBRdcoNdff73K8WXLlqlDhw71UhQAwD9YrDYt/aKw5hAlaeWEPhrTi83ZAQChw+ulfTNnztSYMWP06aefqm/fvjIMQ+vXr9fHH3/sMmABAAKTp8v5Zo/qrK4pcY1XGAAAfsDrIHXDDTfo888/1xNPPKE333xTpmnqkksu0RdffKFu3bo1RI0AgEZksdq0peCIMlfkyaymK9/UIReqS7uWSkuIZjkfACAk1WofqR49euiVV16p71oAAD7mbhaKrnwAAJxRqyBVXl6ulStX6ptvvpFhGLr44os1YsQINWlSp/19AQA+5K6pBF35AAD4hdfJZ8eOHRoxYoQOHDigCy+8UJL0n//8R61bt9bbb7+tjIyMei8SANCwLFab3tq2v8YQRVc+AAB+4XWQuv3229WpUydt2bJFcXFnbi4+evSoxo8fr//93//Vpk2b6r1IAEDDsFht+tf6fL2wPt9liAqTtGBsN3VPjSNEAQBQiddBavv27U4hSpLi4uL06KOPqlevXvVaHACg4SzLKVTm8jxV15TPPgs1rEtyo9YFAEAg8DpIXXjhhfrvf/+rTp06OR0/ePCgLrjggnorDADQcOz3Q1UXomgqAQBAzbzekHf27Nm655579O9//1v79u3Tvn379O9//1uTJk3S448/rqKiIscXAMA/fX/wJE0lAACoA69npIYPHy5JGj16tAzDkCSZP280cu211zoeG4ah8vLy+qoTAFBPfjxWrH9+9r3Lc2GGaCoBAIAHvA5Sn3zySUPUAQBoQBarTfmHTipv3zE99sEux5I+Q5KpM8sTbr8iXbf0TSdEAQDgAa+C1OnTp7V27VrdeuutSklJaaiaAAD1qKZNdg1JC+nKBwCA17y6R6pJkyb6v//7P5bsAUCAsFhP1bjJboWk+JgoQhQAAF7yutnEVVddpbVr1zZAKQCA+nSsRPpgx4FqQ5R0prFEWkJ04xUFAECQ8PoeqaFDh2ratGnasWOHevTooZiYGKfz1113Xb0VBwConTdy92nGl+Ey9Z9qr7HvE8VsFAAA3vM6SP3xj3+UJM2bN6/KOTr1AYDvbd97VA++tVOmjCrnwg1DU4dcqC7tWiotIZoQBQBALXkdpCoqKhqiDgBAPViWU6j7l+e5PMcmuwAA1B+v75Gq7NSpU/VVBwCgjixWmzKrCVFssgsAQP3yOkiVl5frkUce0bnnnqtzzjlHP/zwgyRp+vTpeuGFF7x6rU8//VTXXnutkpOTZRiG3nzzTafzpmlqxowZSk5OVrNmzdS/f399/fXXTteUlJTo7rvvVkJCgmJiYnTddddp37593n4sAAhoFqtNT328W676SrDJLgAA9c/rIPXoo49q8eLFmjNnjiIjIx3HMzIy9Pzzz3v1WidPnlTXrl21cOFCl+fnzJmjefPmaeHChcrJyVFiYqIGDhyo48ePO66ZNGmSVq5cqaVLl2r9+vU6ceKEhg8fzr1aAELGspxC9XlsjV77Ym+Vc4aklRP6aEyv9o1fGAAAQczrIPXSSy/pH//4h377298qPDzccbxLly769ttvvXqtoUOHatasWRo1alSVc6Zpav78+XrwwQc1atQode7cWS+++KKKi4u1ZMkSSZLVatULL7yguXPn6uqrr1a3bt30yiuvKC8vTx999JG3Hw0AAo7FatO0FXkyXW62a+rRkZeoa0pc4xcGAECQ8zpI7d+/XxdccEGV4xUVFSorK6uXoiQpPz9fBw4c0KBBgxzHoqKi1K9fP23cuFGSlJubq7KyMqdrkpOT1blzZ8c1ABCsLFab/r1ln8t9oh4Y2lEzupfrxh7tGr8wAABCgNdd+zp16qTPPvtMqampTsffeOMNdevWrd4KO3DggCSpbdu2Tsfbtm2rPXv2OK6JjIxUXFxclWvsz3elpKREJSUljsdFRUWSpLKysnoNg7Vhf39f1wH/xjjBG7n79Je3droMUWGGdPWFrZR3jDGCmvG7BJ5gnMCdYBsjnn4Or4PUQw89pN///vfav3+/KioqtGLFCu3atUsvvfSS3n33Xa8LdccwnPdBMU2zyrGzubsmKytLM2fOrHJ89erVio6Orl2h9Sw7O9vXJSAAME5Cz7ESKf+4oRd3h521T5QpyZAhU6PTK5T3+WeSGCPwDOMEnmCcwJ1gGSPFxcUeXed1kLr22mu1bNkyzZ49W4Zh6K9//au6d++ud955RwMHDvS60OokJiZKOjPrlJSU5Dh+8OBBxyxVYmKiSktLdfToUadZqYMHD6pPnz7Vvva0adN07733Oh4XFRUpJSVFgwYNUosWLertM9RGWVmZsrOzNXDgQEVERPi0FvgvxkloeiN3n2ZWMwslGXpgaEcN6ZSopNimjBF4hHECTzBO4E6wjRH7ajV3vA5SkjR48GANHjy4Nk/1WHp6uhITE5Wdne1YMlhaWqp169bp8ccflyT16NFDERERys7O1ujRoyVJFotFO3bs0Jw5c6p97aioKEVFRVU5HhER4Td/+P5UC/wX4yR0WKy2apfySWf2ibr20nZVWpwzRuAJxgk8wTiBO8EyRjz9DF4HqfPOO085OTlq1aqV0/Fjx46pe/fujn2lPHHixAl99913jsf5+fnatm2b4uPj1b59e02aNEmzZ89Whw4d1KFDB82ePVvR0dEaO3asJCk2Nla33XabJk+erFatWik+Pl5TpkxRRkaGrr76am8/GgD4rZz8IzWGKPaJAgCgcXkdpAoKClzu0VRSUqL9+/d79VpbtmzRgAEDHI/ty+3GjRunxYsXa+rUqbLZbJowYYKOHj2qyy67TKtXr1bz5s0dz3niiSfUpEkTjR49WjabTVdddZUWL17s1JodAAKRxWpT/qGTytt3TFkf7KpyPkzSgrHd1D01jhAFAEAj8zhIvf32247vP/zwQ8XGxjoel5eX6+OPP1ZaWppXb96/f3+ZrjY/+ZlhGJoxY4ZmzJhR7TVNmzbVggULtGDBAq/eGwD82bKcQk1bkVftLFSYIWWNytCwLsmNWxgAAJDkRZAaOXKkpDPhZty4cU7nIiIilJaWprlz59ZrcQAQiuyb7FYXoiTpqZu6aXhXQhQAAL7icZCqqKiQdKYJRE5OjhISEhqsKAAIZfk/nawxRIUbhnqkxVV/AQAAaHBe3yOVn5/fEHUAAHRmNmrJF3uqPU9jCQAA/EOt2p9//PHH+vjjj3Xw4EHHTJXdv/71r3opDABCReWmEo99sEv2yShDZ7bZDTcMTR1yobq0a6m0hGhCFAAAfsDrIDVz5kw9/PDD6tmzp5KSkmQYRkPUBQAhoaamEoakhXTlAwDAL3kdpJ599lktXrxYv//97xuiHgAIGe6aSlRIio+JIkQBAOCHwrx9Qmlpqfr06dMQtQBASMndc9RtU4m0hOjGKwgAAHjM6yB1++23a8mSJQ1RCwCEjGU5hZq4ZGu152kqAQCAf/N6ad+pU6f0j3/8Qx999JG6dOmiiIgIp/Pz5s2rt+IAIBhZrDZlrsircjzMkO4fchFNJQAACABeB6mvvvpKl156qSRpx44dTudoPAEANbNYbXp10x6ZLpb0sckuAACBw+sg9cknnzREHQAQ9Grq0McmuwAABJZa7SMFAPCcxWrTloIjylyR53ImivuhAAAIPB4HqVGjRnl03YoVK2pdDAAEm5pmoSRp+rCLdU2XJEIUAAABxuMgFRsb25B1AEDQcbdPVLhhEKIAAAhQHgepRYsWNWQdABBULFab3vxyf40hiuV8AAAELu6RAoB6VtNyvjBJC8Z2U/fUOEIUAAABjCAFAPVo+96jylyeJ1cTUfZZqGFdaHEOAECgI0gBQD15ZfMe/eXNHS7P0VQCAIDgEubrAgAgGBQeOVltiKKpBAAAwYcgBQB19OOxYt295EuX58IM0VQCAIAgxNI+AKiDZTmF1d4TFSZp5YQ+6poS19hlAQCABkaQAoBaslhtbhtLEKIAAAhOBCkAqAWL1aanPt7tMkTRWAIAgOBHkAIALy3LKVTmijyZLlIUjSUAAAgNBCkA8JDFatMX+UfcLucjRAEAEPwIUgDggZpmoSSW8wEAEGpofw4AblisthpDFMv5AAAIPQQpAKiBxWrTy5v21BiiWM4HAEDoYWkfALhgsdr0r/X5en59vssQFSZpwdhu6p4aR4gCACAEEaQA4Cw1bbIr/TILNaxLcqPWBQAA/AdBCgAqsVhtmrai+hBFUwkAACBxjxQAOFisNi37Yq8qaCoBAADcYEYKAHRmOd+0FXnVhqgwQzSVAAAADgQpACHPvpzPVYgKk3T7Fem6pW86IQoAADgQpACENIvVpne3/+gyRHE/FAAAqA5BCkDIqmk5H/dDAQCAmhCkAIQci9WmLQVHagxR3A8FAABqQpACEFLcNZVgOR8AAPAE7c8BhIyamkpILOcDAACeI0gBCBm5e47WGKJYzgcAADzF0j4AIWFZTqHuX55X5XiYpAVju6l7ahwhCgAAeIwgBSDoWaw2Za5wEaIMKWtUhoZ1SfZBVQAAIJARpAAENYvVplc37ZHpYknfUzd10/CuhCgAAOA9ghSAoOVun6geaXGNXxQAAAgKBCkAQce+T1TmijyXM1E0lgAAAHVFkAIQVNgnCgAANAbanwMIGuwTBQAAGgtBCkBQsFhtevPL/ewTBQAAGgVL+wAEvJqW87FPFAAAaAgEKQABbfveo8pcnidXE1H2WSj2iQIAAPWNIAUgYL28qUDT3/ra5TmaSgAAgIbEPVIAAlLhkZPVhiiaSgAAgIZGkAIQcH48Vqy7l2x1eS7MEE0lAABAg2NpH4CAYLHalH/opPL2HdNjH+xyeU9UmKSVE/qoa0pcY5cHAABCDEEKgN9zt8mu9EtjCUIUAABoDAQpAH7N3Sa7Eo0lAABA4+MeKQB+y2K16d2vfnQ7E0WIAgAAjY0ZKQB+yZvlfIQoAADQ2AhSAPxOTcv5wg1DU4dcqC7tWiotIZoQBQAAfIIgBcDv5B866TJEcS8UAADwF9wjBcDvFNlKqxzjXigAAOBPmJEC4Bfs+0Rt/O6QFn7yvdM57oUCAAD+hiAFwOdqaiwRJmnFhN7sDwUAAPwKS/sA+JS7faIqJBWXVjRqTQAAAO4QpAD4jMVq0+s5e922OE9LiG68ogAAADzA0j4APsE+UQAAIJARpAA0KovVpi0FR5S5Ik8m+0QBAIAARZAC0GjczUKxTxQAAAgUfn2P1IwZM2QYhtNXYmKi47xpmpoxY4aSk5PVrFkz9e/fX19//bUPKwZQHXdNJdgnCgAABBK/DlKS1KlTJ1ksFsdXXl6e49ycOXM0b948LVy4UDk5OUpMTNTAgQN1/PhxH1YM4GwWq01vb/uxxhDFvVAAACCQ+P3SviZNmjjNQtmZpqn58+frwQcf1KhRoyRJL774otq2baslS5boD3/4Q2OXCsAFd3tELRjbTd1T4whRAAAgoPh9kNq9e7eSk5MVFRWlyy67TLNnz9Z5552n/Px8HThwQIMGDXJcGxUVpX79+mnjxo01BqmSkhKVlJQ4HhcVFUmSysrKVFZW1nAfxgP29/d1HfBvgTJOtu+zKnN5nlxNRIUZ0qwRl2jQxa0l+f9nCTSBMkbgW4wTeIJxAneCbYx4+jkM03TVN8s/fPDBByouLlbHjh313//+V7NmzdK3336rr7/+Wrt27VLfvn21f/9+JScnO57zv//7v9qzZ48+/PDDal93xowZmjlzZpXjS5YsUXQ0+9UA9WHDAUOv54dJMqqcG5larm6tTLWMavy6AAAAalJcXKyxY8fKarWqRYsW1V7n10HqbCdPntT555+vqVOn6vLLL1ffvn31448/KikpyXHNHXfcob1792rVqlXVvo6rGamUlBQdOnSoxh9WYygrK1N2drYGDhyoiIgIn9YC/+Xv4+THozb1m/eZy3NhhrR28hVKim3ayFWFFn8fI/APjBN4gnECd4JtjBQVFSkhIcFtkPL7pX2VxcTEKCMjQ7t379bIkSMlSQcOHHAKUgcPHlTbtm1rfJ2oqChFRVX9p/CIiAi/+cP3p1rgv/xxnFisNk17a6fLc2GGlDUqQ+0TmjdyVaHLH8cI/A/jBJ5gnMCdYBkjnn4Gv+/aV1lJSYm++eYbJSUlKT09XYmJicrOznacLy0t1bp169SnTx8fVgmEHovVpo3fH9Jzn36vPllrtPH7w1WuCZO0ckIfjenVvvELBAAAqGd+PSM1ZcoUXXvttWrfvr0OHjyoWbNmqaioSOPGjZNhGJo0aZJmz56tDh06qEOHDpo9e7aio6M1duxYX5cOhAx3m+xKv7Q375oS13iFAQAANCC/DlL79u3Tb37zGx06dEitW7fW5Zdfrs2bNys1NVWSNHXqVNlsNk2YMEFHjx7VZZddptWrV6t5c5YNAY3B3Sa7kjR92MVstAsAAIKOXweppUuX1njeMAzNmDFDM2bMaJyCADhYrDa9+1X1m+xKZ2aiCFEAACAY+XWQAuCfvFnOR4gCAADBiCAFwCvb9x5V5oo8udo4IdwwNHXIherSrqXSEqIJUQAAIGgRpAB4bFlOoe5fnufyHPdCAQCAUBJQ7c8B+I7FalNmNSGKe6EAAECoIUgBcMtitWnhmt1ydUtUmCHuhQIAACGHpX0AalRTYwn7JrvsDwUAAEINQQqASxarTVsKjihzeZ7LmSg22QUAAKGMIAWgimU5hdV25pNoLAEAAMA9UgCcWKy2GkMUjSUAAAAIUgAqsVhtevXzwhpDFI0lAAAAWNoHQGcC1L/W5+uF9fnVNpVYMLabuqfGEaIAAABEkAJC3rKcwmobSki/zEIN65LcqHUBAAD4M4IUEMIsVpumrag+RNFUAgAAwDXukQJClMVq0xtb9rlcyifRVAIAAKAmzEgBIaimTXYlKcwQTSUAAABqQJACQoh9k93qQlSYpNuvSNctfdMJUQAAADUgSAEhwt0sFPdDAQAAeI4gBQQ5+yyUu858hCgAAADPEaSAIOZuFkpik10AAIDaIEgBQcre2rzahhJik10AAIDaIkgBQWrD7kM1tjZnk10AAIDaI0gBQcRitSn/0EltKzymOR/uqnKeWSgAAID6QZACgoQne0NljcpgFgoAAKAeEKSAIODufihJeuqmbhrelRAFAABQH8J8XQCAurFYbXpr249uO/P1SItrvKIAAACCHDNSQAB7I3ef/vLWTtqbAwAANDKCFBCALNZT2nrI0EubXYeocMPQ1CEXqku7lkpLiCZEAQAA1DOCFBBgfmkqEe7y/PRhF+uaLkmEJwAAgAZEkAICyPa9R5W5PE/VreQLNwxCFAAAQCMgSAF+zr431MbvD2vhmu+qvY57oQAAABoPQQrwY+72hpLYZBcAAMAXCFKAn/Jkbyg22QUAAPANghTghyxWm5Z+UVhjiJJMvf6/l6tnekJjlQUAAICfEaQAP+PRcj5DGp1eoa7tYhuvMAAAADgQpAA/YbHatKXgiDJX5Ml0szfUubGR2rphTeMXCQAAAEkEKcCn7B358vZb9fgH31Y7C3X23lBlZWXa2oh1AgAAwBlBCvART5bwSewNBQAA4I8IUoAPbN97tNolfJWxNxQAAIB/IkgBjWxZTqEyl+eppgzF3lAAAAD+jSAFNCKL1XZmJqqGa+yzUOwNBQAA4L8IUkAjsVht+uenP7hczhdmSPcPuUhd2rVUWkI0s1AAAAB+jiAFNIKaGkuESVo5oY+6psQ1el0AAACoHYIU0IAce0NVc0+UfRkfIQoAACCwEKSAelbbvaEAAAAQOAhSQD1ibygAAIDQQJAC6gl7QwEAAIQOghRQB45lfPuOKeuDXTVey95QAAAAwYMgBdSSp8v4JPaGAgAACDYEKcBLjk58bpbxsTcUAABA8CJIAV7wdBaKvaEAAACCG0EK8IC7/aAqY28oAACA4EeQAmpgsdr0r/X5en59fo3L+MINQ1OHXMgyPgAAgBBBkAKqsSyn0O0MFJ34AAAAQhNBCjiLxWrTxu8OuQ1RdOIDAAAIXQQpQL/sB/XV3mN6fNUuZqEAAABQI4IUQp43+0GFGVLWqAxmoQAAAEIcQQohy9P9oKQzs1C3X5GuW/qmMwsFAAAAghRCj70T3wvr8z3aD4plfAAAADgbQQohxZNOfHY0kwAAAEB1CFIICZ5uqMt+UAAAAPAEQQpBy96JL2+/VY9/8G2Ny/hYwgcAAABvEKQQlOjEBwAAgIZEkEJQsS/h8yRE0YkPAAAAtUWQQtDwdBaKZXwAAACoK4IUApb9HqiYyHAVHin2aD8oOvEBAACgPhCkEFDs4Wlb4TH97cNdHrcxpxMfAAAA6hNBCgHDmwYSEkv4AAAA0HDCfF1AfXn66aeVnp6upk2bqkePHvrss898XRLqwGK1aeP3h2Sx2mSx2vTO9v3K9CJEhRuGsm4404mPEAUAAID6FhQzUsuWLdOkSZP09NNPq2/fvnruuec0dOhQ7dy5U+3bt/d1efCCxWrTv9bn64X1+Y7QZEgeLeGTmIUCAABA4wiKGal58+bptttu0+23366LL75Y8+fPV0pKip555hlflwYvLMspVJ+sNfrnZ/lOM0+ehihmoQAAANBYAn5GqrS0VLm5ucrMzHQ6PmjQIG3cuNHlc0pKSlRSUuJ4XFRUJEkqKytTWVlZwxXrAfv7+7qOhmaxntKew8VKbRUtSdpaeEyZy/M8n3kypPsGdVDGubFqGhGuU2Xlah8fraTYpkH/s5NCZ5yg9hgj8ATjBJ5gnMCdYBsjnn6OgA9Shw4dUnl5udq2bet0vG3btjpw4IDL52RlZWnmzJlVjq9evVrR0dENUqe3srOzfV1CvTlWIv10ylBkmKnSCkOFJ6R3CsNkOi3aMzx8NVPjO1QovbmplkXf6HDRL2cOS9pav6X7vWAaJ2gYjBF4gnECTzBO4E6wjJHi4mKPrgv4IGVnGM5/ETdNs8oxu2nTpunee+91PC4qKlJKSooGDRqkFi1aNGid7pSVlSk7O1sDBw5URESET2upD2/k7tPMt3bW0CSi5gBl/Pw/pnlmFmrWiE66sUe7eq4y8ATbOEH9Y4zAE4wTeIJxAneCbYzYV6u5E/BBKiEhQeHh4VVmnw4ePFhllsouKipKUVFRVY5HRET4zR++P9XiKfseT+kJMZKkLQVH9OBbO91ukutKmKTbr0jXLX3TJUkFh4rZA8qFQBwnaFyMEXiCcQJPME7gTrCMEU8/Q8AHqcjISPXo0UPZ2dm6/vrrHcezs7M1YsQIH1YWWirv8WSfY6pFfqq26x4BCgAAAP4k4IOUJN177736/e9/r549e6p37976xz/+ocLCQt15552+Li2onD3jlH/opGIiw1V4pNipUYQ3Aary0r1ww9DsUZ01rEtyPVcOAAAA1K+gCFJjxozR4cOH9fDDD8tisahz5856//33lZqa6uvSvGaxntJuqyGL9ZQiIk67DC4nS8udjqUnxLidsXEVgqr73tV7bNt7TH9btatWs0xnCzcMTR1yobq0a6m0hDPNPVi6BwAAgEASFEFKkiZMmKAJEyb4uow6+WV5XLj+vvNTSWdmd1wtlat8LMyQskZlaEwv15sPV7fsrrrvXb1HXdiX67WLa6bi0gqXgYkABQAAgEASNEEq0FmsNkfYkZzDi6sgU/lYhSlNW56nmKgm6pEaJ+msZXcr8hwNH6p7XXfv4Q2W6wEAACDYEaT8RP6hkzW0CHevQtLEJb7dRalyowiJ5XoAAAAIXgQpP5GeEKMwQ3UKU42l8oyTnauZJwIUAAAAghVByk8kxTZT1qgM53uZfg4rroKLq2OeqO513b1HdQ0ioiPDqr3vCQAAAAhWBCk/MqZXe/VOj9Pr73+i0dcMUEREE8fyOKlqcJGk3IKjumfpVrczWdUtu3P1/dnvUd0SPYITAAAAQhVBys8kxTZVh1hTSbFNFRER4XZT2uFdm+lk6Wk9sGKHyk2zVsvu3L0HgQkAAABwRpAKAmN6tdcVHVvXOLNEGAIAAADqD0EqSCTFNnM7swQAAACgfoT5ugAAAAAACDQEKQAAAADwEkEKAAAAALxEkAIAAAAALxGkAAAAAMBLBCkAAAAA8BJBCgAAAAC8RJACAAAAAC8RpAAAAADASwQpAAAAAPASQQoAAAAAvESQAgAAAAAvEaQAAAAAwEsEKQAAAADwEkEKAAAAALzUxNcF+APTNCVJRUVFPq5EKisrU3FxsYqKihQREeHrcuCnGCdwhzECTzBO4AnGCdwJtjFizwT2jFAdgpSk48ePS5JSUlJ8XAkAAAAAf3D8+HHFxsZWe94w3UWtEFBRUaEff/xRzZs3l2EYPq2lqKhIKSkp2rt3r1q0aOHTWuC/GCdwhzECTzBO4AnGCdwJtjFimqaOHz+u5ORkhYVVfycUM1KSwsLC1K5dO1+X4aRFixZBMRDRsBgncIcxAk8wTuAJxgncCaYxUtNMlB3NJgAAAADASwQpAAAAAPASQcrPREVF6aGHHlJUVJSvS4EfY5zAHcYIPME4gScYJ3AnVMcIzSYAAAAAwEvMSAEAAACAlwhSAAAAAOAlghQAAAAAeIkgBQAAAABeIkj5maefflrp6elq2rSpevTooc8++8zXJcFHZsyYIcMwnL4SExMd503T1IwZM5ScnKxmzZqpf//++vrrr31YMRrDp59+qmuvvVbJyckyDENvvvmm03lPxkVJSYnuvvtuJSQkKCYmRtddd5327dvXiJ8CDcndGBk/fnyV3y2XX3650zWMkeCWlZWlXr16qXnz5mrTpo1GjhypXbt2OV3D7xJ4Mk5C/fcJQcqPLFu2TJMmTdKDDz6orVu36te//rWGDh2qwsJCX5cGH+nUqZMsFovjKy8vz3Fuzpw5mjdvnhYuXKicnBwlJiZq4MCBOn78uA8rRkM7efKkunbtqoULF7o878m4mDRpklauXKmlS5dq/fr1OnHihIYPH67y8vLG+hhoQO7GiCQNGTLE6XfL+++/73SeMRLc1q1bp7vuukubN29Wdna2Tp8+rUGDBunkyZOOa/hdAk/GiRTiv09M+I3/+Z//Me+8806nYxdddJGZmZnpo4rgSw899JDZtWtXl+cqKirMxMRE87HHHnMcO3XqlBkbG2s+++yzjVQhfE2SuXLlSsdjT8bFsWPHzIiICHPp0qWOa/bv32+GhYWZq1atarTa0TjOHiOmaZrjxo0zR4wYUe1zGCOh5+DBg6Ykc926daZp8rsErp09TkyT3yfMSPmJ0tJS5ebmatCgQU7HBw0apI0bN/qoKvja7t27lZycrPT0dN1000364YcfJEn5+fk6cOCA03iJiopSv379GC8hzJNxkZubq7KyMqdrkpOT1blzZ8ZOCFm7dq3atGmjjh076o477tDBgwcd5xgjocdqtUqS4uPjJfG7BK6dPU7sQvn3CUHKTxw6dEjl5eVq27at0/G2bdvqwIEDPqoKvnTZZZfppZde0ocffqh//vOfOnDggPr06aPDhw87xgTjBZV5Mi4OHDigyMhIxcXFVXsNgtvQoUP16quvas2aNZo7d65ycnJ05ZVXqqSkRBJjJNSYpql7771Xv/rVr9S5c2dJ/C5BVa7GicTvkya+LgDODMNwemyaZpVjCA1Dhw51fJ+RkaHevXvr/PPP14svvui4kZPxAldqMy4YO6FjzJgxju87d+6snj17KjU1Ve+9955GjRpV7fMYI8Fp4sSJ+uqrr7R+/foq5/hdArvqxkmo/z5hRspPJCQkKDw8vEo6P3jwYJV/EUJoiomJUUZGhnbv3u3o3sd4QWWejIvExESVlpbq6NGj1V6D0JKUlKTU1FTt3r1bEmMklNx99916++239cknn6hdu3aO4/wuQWXVjRNXQu33CUHKT0RGRqpHjx7Kzs52Op6dna0+ffr4qCr4k5KSEn3zzTdKSkpSenq6EhMTncZLaWmp1q1bx3gJYZ6Mix49eigiIsLpGovFoh07djB2QtThw4e1d+9eJSUlSWKMhALTNDVx4kStWLFCa9asUXp6utN5fpdAcj9OXAm53ye+6XEBV5YuXWpGRESYL7zwgrlz505z0qRJZkxMjFlQUODr0uADkydPNteuXWv+8MMP5ubNm83hw4ebzZs3d4yHxx57zIyNjTVXrFhh5uXlmb/5zW/MpKQks6ioyMeVoyEdP37c3Lp1q7l161ZTkjlv3jxz69at5p49e0zT9Gxc3HnnnWa7du3Mjz76yPzyyy/NK6+80uzatat5+vRpX30s1KOaxsjx48fNyZMnmxs3bjTz8/PNTz75xOzdu7d57rnnMkZCyB//+EczNjbWXLt2rWmxWBxfxcXFjmv4XQJ344TfJ6ZJkPIzf//7383U1FQzMjLS7N69u1OLSYSWMWPGmElJSWZERISZnJxsjho1yvz6668d5ysqKsyHHnrITExMNKOioswrrrjCzMvL82HFaAyffPKJKanK17hx40zT9Gxc2Gw2c+LEiWZ8fLzZrFkzc/jw4WZhYaEPPg0aQk1jpLi42Bw0aJDZunVrMyIiwmzfvr05bty4Kn/+jJHg5mp8SDIXLVrkuIbfJXA3Tvh9YpqGaZpm481/AQAAAEDg4x4pAAAAAPASQQoAAAAAvESQAgAAAAAvEaQAAAAAwEsEKQAAAADwEkEKAAAAALxEkAIAAAAALxGkAAAAAMBLBCkAQKPp37+/Jk2a5OsyfMYwDL355pu+LgMAUA8IUgCAkFBeXq6Kigpfl1EvysrKfF0CAIQ8ghQAoFGMHz9e69at05NPPinDMGQYhgoKClxem5aWpkceeURjx47VOeeco+TkZC1YsMDpmnnz5ikjI0MxMTFKSUnRhAkTdOLECcf5xYsXq2XLlnr33Xd1ySWXKCoqSnv27FFOTo4GDhyohIQExcbGql+/fvryyy+dXtswDD333HMaPny4oqOjdfHFF2vTpk367rvv1L9/f8XExKh37976/vvvnZ73zjvvqEePHmratKnOO+88zZw5U6dPn3Z8Jkm6/vrrZRiG47G759nrefbZZzVixAjFxMRo1qxZ3v74AQD1jCAFAGgUTz75pHr37q077rhDFotFFotFKSkp1V7/t7/9TV26dNGXX36padOm6c9//rOys7Md58PCwvTUU09px44devHFF7VmzRpNnTrV6TWKi4uVlZWl559/Xl9//bXatGmj48ePa9y4cfrss8+0efNmdejQQddcc42OHz/u9NxHHnlEN998s7Zt26aLLrpIY8eO1R/+8AdNmzZNW7ZskSRNnDjRcf2HH36o3/3ud7rnnnu0c+dOPffcc1q8eLEeffRRSVJOTo4kadGiRbJYLI7H7p5n99BDD2nEiBHKy8vTrbfe6u2PHwBQ30wAABpJv379zD/96U9ur0tNTTWHDBnidGzMmDHm0KFDq33O66+/brZq1crxeNGiRaYkc9u2bTW+1+nTp83mzZub77zzjuOYJPMvf/mL4/GmTZtMSeYLL7zgOPbaa6+ZTZs2dTz+9a9/bc6ePdvptV9++WUzKSnJ6XVXrlzpdI2nz5s0aVKNnwMA0Lia+DTFAQBQjd69e1d5PH/+fMfjTz75RLNnz9bOnTtVVFSk06dP69SpUzp58qRiYmIkSZGRkerSpYvT6xw8eFB//etftWbNGv33v/9VeXm5iouLVVhY6HRd5ee1bdtWkpSRkeF07NSpUyoqKlKLFi2Um5urnJwcp5mk8vJynTp1SsXFxYqOjnb5OT19Xs+ePd3+zAAAjYcgBQAIGIZhSJL27Nmja665RnfeeaceeeQRxcfHa/369brtttucGjE0a9bM8Ry78ePH66efftL8+fOVmpqqqKgo9e7dW6WlpU7XRUREVHlfV8fsDSwqKio0c+ZMjRo1qkrdTZs2rfYzefo8ezgEAPgHghQAoNFERkaqvLzco2s3b95c5fFFF10kSdqyZYtOnz6tuXPnKizszO2+r7/+ukev+9lnn+npp5/WNddcI0nau3evDh065OlHqFb37t21a9cuXXDBBdVeExERUeXze/I8AID/IUgBABpNWlqaPv/8cxUUFOicc85RfHy8IwidbcOGDZozZ45Gjhyp7OxsvfHGG3rvvfckSeeff75Onz6tBQsW6Nprr9WGDRv07LPPelTDBRdcoJdfflk9e/ZUUVGR7rvvPjVr1qzOn+2vf/2rhg8frpSUFN14440KCwvTV199pby8PEeXvbS0NH388cfq27evoqKiFBcX59HzAAD+h659AIBGM2XKFIWHh+uSSy5R69atq9yXVNnkyZOVm5urbt266ZFHHtHcuXM1ePBgSdKll16qefPm6fHHH1fnzp316quvKisry6Ma/vWvf+no0aPq1q2bfv/73+uee+5RmzZt6vzZBg8erHfffVfZ2dnq1auXLr/8cs2bN0+pqamOa+bOnavs7GylpKSoW7duHj8PAOB/DNM0TV8XAQBAZWlpaZo0aZImTZrk61IAAHCJGSkAAAAA8BJBCgAAAAC8xNI+AAAAAPASM1IAAAAA4CWCFAAAAAB4iSAFAAAAAF4iSAEAAACAlwhSAAAAAOAlghQAAAAAeIkgBQAAAABeIkgBAAAAgJcIUgAAAADgpf8PpoVnPhQ8EhsAAAAASUVORK5CYII=",
"text/plain": [
"<Figure size 1000x600 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"from editor.utils import get_colour_lut\n",
"\n",
"t_values = np.linspace(0, 256, 256)\n",
"interpolated_values = get_colour_lut(variance=0.2, type='cubic')\n",
"\n",
"plt.figure(figsize=(10, 6))\n",
"plt.plot(t_values, interpolated_values, label='Interpolated Function', marker='o', markersize=3)\n",
"plt.xlabel('t parameter')\n",
"plt.ylabel('Interpolated value')\n",
"plt.grid(True)\n",
"plt.legend()\n",
"plt.show()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "bipolaroid",
"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": "3.12.2"
}
},
"nbformat": 4,
"nbformat_minor": 2
}