178 lines
26 KiB
Plaintext
178 lines
26 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 37,
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"metadata": {},
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"outputs": [],
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"source": [
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"import random\n",
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"import numpy as np\n",
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"import matplotlib.pylab as plt\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 38,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"473.53100883248396"
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]
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},
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"execution_count": 38,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"Radius = 36\n",
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"random.seed(23)\n",
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"random.uniform(0,512)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 203,
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"metadata": {},
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"outputs": [],
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"source": [
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"cx = [312, 70, 173, 250, 100, 30, 70, 210, 200, 112, 332, 346, 452, 431, 500, 480]\n",
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"cy = [327, 64, 112, 20, 350, 450, 210, 438, 261, 500, 172, 455, 349, 60, 210, 460]\n",
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"radius = [46, 42, 49, 48, 43, 48, 64, 56, 46, 30, 86, 62, 52, 38, 59, 41]\n",
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"#for i in range(1,30):\n",
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"# cx.append(random.uniform(0,512))\n",
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"# cy.append(random.uniform(0,512))\n",
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" "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 244,
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"metadata": {},
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"outputs": [],
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"source": [
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"Lid = np.ones((512,512),dtype=np.uint8)\n",
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"ID = np.ones((512,512),dtype=np.uint8)\n",
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"for i in range(len(radius)):\n",
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" Cx = cx[i]\n",
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" Cy = cy[i]\n",
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" Radius = radius[i]\n",
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" for i in range(np.int(Cx-Radius),np.int(Cx+Radius)):\n",
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" for j in range(np.int(Cy-Radius),np.int(Cy+Radius)):\n",
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" if i>1 and i<512 and j>1 and j<512:\n",
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" if ((i-Cx)*(i-Cx) + (j-Cy)*(j-Cy) < Radius*Radius):\n",
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" ID[i,j] = 0\n",
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" \n",
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"for i in range(512):\n",
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" ID[1,i] = 0\n",
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" ID[2,i] = 0\n",
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" ID[510,i] = 0\n",
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" ID[511,i] = 0"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 245,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": 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SpNolk2pdVfG3j4zDfcx5RbBebX5PtLn2sjnczcw6yOFutoRx3RLcMDnZdAkDG9dltRiHu5ktqE1h2aZa67JsuEt6rqQ7JN0l6R5JH8qHnyjpVkkP5tcrC6+5XNIeSQ9IOrfKGbDRecUw655+ttyfBH4jIl4OvAI4T9KrgcuA2yJiPXBbfh9JpwNbgDOA84CrJa2oonizKvlDrx1t0IYam7BsuEdmLr97ZH4J4ALg2nz4tcCF+e0LgKmIeDIiHgL2AGeWWrWVziuILSbl90Yb9w3URdHHgsu3vGeAXwSuioj3SDoYEScUnnMgIlZKuhK4PSKuy4fvAG6OiOt7xrkN2AawatWqyampqZFmZG5ujomJiZHGUYeU6yz+x+eatWt5bHa2wWr6V1WtwwTHUv+T2lSbDjMfC71Pq/oP2GFtmJxMen3qVUWtmzdvnomIjQs+GBF9X4ATgF3Ay4CDPY8dyK+vAi4qDN8BvHGp8U5OTsaodu3aNfI46pByncfCM5ePb99+2P2UL1XUWkYb1lFnVfOy2Pu06WXdO08pr0+9qqgVuDMWydUjBvmUiIiDkqbJ+tIfl7Q6IvZJWg3sz582C5xSeNlaYO8g0xkHgx41mPJXYxsfcxGNHvHq9aB//fxa5mRJJ+S3jwHOAe4HbgS25k/bCtyQ374R2CLpaEmnAuuBO8ouvK12z8wMtXJMSM9cquIVJzNKO6TWhlXUMxfRyHym1rap62fLfTVwbd7v/hxgZ0TcJOnrwE5JFwOPAG8CiIh7JO0E7gWeAi6JiKerKX88zQd8VSvuuJ2LxIYz//6r+v3iUB/OsuEeEX8PbFhg+A+Asxd5zRXAFSNXZ0uakPzGL1kZ7ZnKB2Rd742qQt7v7dH4CNWWq6KrxivV6MaxDee7a0bt1mqq26drBtqhatZlXQqUpuel6embt9w7o+yt93E7OKSq/RdNcLAaONw7pewumnEJiSrns+42HJdlZstzuNuSHBajq3vHphk43G3MdSV4HezWy+HeQVX8eqaL4VH3PG2YnCx9ml1dNjY6h3tHpfA765Q1GYhlBLJD3Zbjn0Ja3+o6IrFqqYRibx3LtWsqdVs7ONw7rKojWFM5AnNQqYdj6vUtpp/3Qlvnrc0c7jaUtga8lWPQZd/7fId99RzuNrS2dNM4SMpR5nIujsvLpxreoWojS3Xl9E7H8lT5AZ76xkFbOdytFKkFaUq1tFnV/yFQnI6Vy90yVqpiqNa9wjrQy1X38qvyfwrGkbfcrTJ1bc1XcXDQOJuQGv0zbG/Fl8PhbpWrIuR93u9uc8CPzt0yVhsHcfpSClX/09hoHO5mPQYJuC6FT0rBPs8BPzyHu1lumHDryk7AFIPdRuNwt7FWVqj5oJzqeOt9ON6hamOrqq3Vtm0Ft6HeNtSYGoe7jaWqw6Kug39G1YYabTgO9w7zV9lnqzt0HZ7lcVsOxuFuNqYclt3mcO8ob7U/W1Nh5hC1JjjcO8jB/mxNB2zT07fx43A3s9bwh2T/HO4dU9ZW++6ZmWd2Pi53SV0qNTZ5Mq5eqbSJVcfh3iGjBvuwgd2moG+a28jq4nDviFGCvcxgTi28UqvHrC4+/UAHDBvsVR+h6R27Zs3xlnvLpRbsdU/DzBbmcG+xlIO9OC3/vvxwqdZl3bJsuEs6RdIuSfdJukfSO/PhJ0q6VdKD+fXKwmsul7RH0gOSzq1yBsbNqP9A5KA1Gw/9bLk/Bbw7Il4KvBq4RNLpwGXAbRGxHrgtv0/+2BbgDOA84GpJK6oovo2G/b/PMv5SzgFrNj6W3aEaEfuAffntJyTdB6wBLgA25U+7FpgG3pMPn4qIJ4GHJO0BzgS+XnbxbTaOOxt9Xm6z+igGWNkkrQO+CrwMeCQiTig8diAiVkq6Erg9Iq7Lh+8Abo6I63vGtQ3YBrBq1arJqampkWZkbm6OiYmJkcZRh6bqHPQAmjVr1/LY7GwltWyYnCx1fIu1aUoHDcHhbVp2GwxjqfapcvmPqth2bVnvoZpaN2/ePBMRGxd8MCL6ugATwAzwb/P7B3seP5BfXwVcVBi+A3jjUuOenJyMUe3atWvkcdShiTqPhYEvH9++fajX9XMp22JtWlX9w16KbZqCppZ/me+ftqz3EdXUCtwZi+RqX7+WkXQk8AXgsxHxxXzw45JW54+vBvbnw2eBUwovXwvs7Wc6Vr4U+9lTrMnawd16/evn1zIi2/q+LyI+XnjoRmBrfnsrcENh+BZJR0s6FVgP3FFeydYFDnizavVzhOpZwFuAb0n6Zj7sj4CPADslXQw8ArwJICLukbQTuJfslzaXRMTTpVdutoy5iCQ/RLz1aXXo59cyXwMWW0POXuQ1VwBXjFCXmVUs1Q8/K4ePUO0wr7jWJf7GMxiHu3WaA2Fpbp/ucrhbY8bxm0WKYZpiTb3aUGNqHO5mljQH+3Ac7tZ5qYRDCkelLiaVNrLyONxtLDQdXk1Pvx8p1phiTW3hcDezZ6QUpinV0kYOdxsbTYWFQ2pwbrPROdxtrJRxXvxBp9c2cxGN7R+oe/l0mcPdrCJtD6m66297e6Wmn3PLmFWiyZV5ftpV/Na+SyFVZTv1TsPK5S33DvNKs7wyuwG63KVQ1bx1tb1S4C13M0bfQh2XkCprS35c2qtJDnezAodOf9xO6XO3jDXC4WBWLYd7xzlEzcaTw30MpBbwqdVj1kUOd6uVg92sHg73MeFQNRsvDvcx0nTANz39NpuQBr50Ue887p6ZGYv5HobDfcz45FntMkpgdSnsBpmXrszzqBzuVjkH++DKDOa2h13b62+Kw30M1XWYfB3TWeyreZu/qldRb1vboW01p8RHqI6xuYjKVp4qQ32YmouvSfmbRNVhNiElPf/zHOqjc7iPubLP+ldVcJS5ss+PK7WQqyvQ2hLwNhp3yxhwqAtlmK6UYV/Xjyq/mqfUbVN3DSnM82JSrq1NvOVuC9owOdno1l1TYdfEPDvMDnFblMdb7pacJlfwcdqCdpB2m8PdkpFSF0kKddRhXOZzHDncLQkOGbNyOdytcakGe9Vb8KnMdyp1WLkc7taoNgRLG2o06+Vfy3REvwHk3zebjYdlt9wlfVrSfkl3F4adKOlWSQ/m1ysLj10uaY+kBySdW1XhNtzvtMf5t92jKLvWNs27tVM/3TJ/BpzXM+wy4LaIWA/clt9H0unAFuCM/DVXS1pRWrUGlNcX3GTItzHc2lizja9lwz0ivgr8sGfwBcC1+e1rgQsLw6ci4smIeAjYA5xZUq1GdSeVMrNuUfTRBytpHXBTRLwsv38wIk4oPH4gIlZKuhK4PSKuy4fvAG6OiOsXGOc2YBvAqlWrJqempkaakbm5OSYmJkYaRx2GrXP3zEwF1Rxuw+TkM7erbM+y52XN2rU8Njtb6jiXUmynQRTbtI7lOYjeeWpqfRq0XRZb9sMuoypV0aabN2+eiYiNCz4YEctegHXA3YX7B3seP5BfXwVcVBi+A3jjcuOfnJyMUe3atWvkcdRh2DqPhVouo9bZxHx8fPv22tqn2EaDKrZpnfUOM09Nrk9lLPsUVdGmwJ2xSK4O+1PIxyWtBsiv9+fDZ4FTCs9bC+wdchqWq7PbxF00y3MbWRsMG+43Alvz21uBGwrDt0g6WtKpwHrgjtFKHG9NBInDy5rkn+uWY9nfuUv6PLAJOEnSLPAB4CPATkkXA48AbwKIiHsk7QTuBZ4CLomIpyuqvfO6FrJdmh+fE71aVf6RzLhYNtwj4s2LPHT2Is+/ArhilKKsebtnZti0aVPTZXSWw2t5bqPR+PQDZpasuv7vt4sc7olKYYulir+2s0NSCa1U6ljKICHfhvmpg88tYzYk97vXr7e9p6envQwW4S33BKW0lZtSLVY+B2N3ecvdrEFd3mm43Hz5g6VaDnezhjUV8GWH66Dz0Pt8h3253C1jloC6g63M6XXhLKVd5HA3GzNlB3vZHPDlcLeMWSLmQ7fKcCsr2KsO4Pnxu6tmeN5yN0tMVYHWlmBvalpd43A3S1CZAV/mUZ4O2/Zwt0yCUvp5nL8WN6fY9sO8H5r+NUzZ0/V7cTAOd7Mh1Rk2/fbHV1VTKhsb1j+Hu1mLjPPWq0/3MBj3uScqhTdx2f2+1k4pbbWnVEvqHO5mtiiHaXs53BPW5NZuiv8ebwb+wOmXw91q06WumS7Ni3WTwz1xTYSIg8us/RzuLdDET+5scePSRil3f6RcWyoc7i1RR6B0ZRpVanv9Nj4c7i1SZbD424FZtzjcW6bsf4Nv6t/l2xjwbazZxpfDvaVGDZqmQt3M6uHTD7TYMCeWSinQUzpB2nJSajezfjjcO6Kt4dOGgG9r29p4c7eMNS7l8Ey5NrOlONzNFuFgtzZzuFsSUtvBm1ItZsNwuFtSUgjVFGowG5XD3ZLTZLg62A9JuS1Sri0V/rWMJanfv5Urc1pmXeJwt6RVGfIOdesyh7u1Qm8QDxP2DvPBpXgcgpdjfyrrc5d0nqQHJO2RdFlV07HxNP/rmrkINkxOHnZ/sYu1n5dj/yoJd0krgKuA1wGnA2+WdHoV0zKzajlQ26mqbpkzgT0R8R0ASVPABcC9FU2vNXbPzHD+5s1Nl7GsD2/f3oo6oT21tqVOSLfW3i6ixer0BxIoKmgESb8NnBcRb8vvvwV4VUS8vfCcbcC2/O5pwAMjTvYk4PsjjqMOrrN8bam1LXVCe2ptS51QTa0vioiTF3qgqi33hfbAHPYpEhHXANeUNkHpzojYWNb4quI6y9eWWttSJ7Sn1rbUCfXXWtUO1VnglML9tcDeiqZlZmY9qgr3bwDrJZ0q6ShgC3BjRdMyM7MelXTLRMRTkt4O3AKsAD4dEfdUMa2C0rp4KuY6y9eWWttSJ7Sn1rbUCTXXWskOVTMza5ZPHGZm1kEOdzOzDmpduEt6k6R7JP1M0saexy7PT3fwgKRzC8MnJX0rf+xPpfpPlpHa6RgkfVrSfkl3F4adKOlWSQ/m1ysLjy3YtjXUeYqkXZLuy5f7OxOu9bmS7pB0V17rh1KtNZ/2Ckm7Jd2UeJ0P5+vvNyXdmWqtkk6QdL2k+/P36682WmdEtOoCvJTsoKdpYGNh+OnAXcDRwKnAt4EV+WN3AL9K9vv7m4HX1VzziryeFwNH5XWe3nA7/mvgV4C7C8P+BLgsv30Z8NHl2raGOlcDv5LfPg74h7yeFGsVMJHfPhL4O+DVKdaaT/8PgM8BN6W6/PPpPwyc1DMsuVqBa4G35bePAk5oss7WbblHxH0RsdDRrBcAUxHxZEQ8BOwBzpS0Gjg+Ir4eWav+d+DCGkuGwukYIuKnwPzpGBoTEV8Fftgz+AKyNyj59YWF4c9q25rq3BcR/ze//QRwH7Am0VojIubyu0fml0ixVklrgd8EPlUYnFydS0iqVknHk20w7QCIiJ9GxMEm62xduC9hDfBo4f5sPmxNfrt3eJ0Wqy01qyJiH2ShCjw/H55E/ZLWARvItoiTrDXv6vgmsB+4NSJSrfW/An8I/KwwLMU6IfuA/LKkmfy0JZBerS8Gvgd8Ju/q+pSkY5usM8nzuUv6G+AFCzz03oi4YbGXLTAslhhepxRqGEXj9UuaAL4AvCsifrTEbpNGa42Ip4FXSDoB+JKkly3x9EZqlXQ+sD8iZiRt6uclCwyrc/mfFRF7JT0fuFXS/Us8t6lajyDr5vz9iPg7SZ8g64ZZTOV1JhnuEXHOEC9b7JQHs/nt3uF1asvpGB6XtDoi9uXdWfvz4Y3WL+lIsmD/bER8MeVa50XEQUnTwHmkV+tZwG9Jej3wXOB4SdclWCcAEbE3v94v6Utk3Rep1ToLzObf1ACuJwv3xursUrfMjcAWSUdLOhVYD9yRfxV6QtKr81/JvBVYbOu/Km05HcONwNb89lYOtdOCbVtHQfky2wHcFxEfT7zWk/MtdiQdA5wD3J9arRFxeUSsjYh1ZO/Fr0TERanVCSDpWEnHzd8GXgvcnVqtEfFd4FFJp+WDziY7xXlzddaxF7nMC/BvyD71ngQeB24pPPZesr3OD1D4RQywkewN8W3gSvIjc2uu+/Vkv/T4Nln3UtPt+HlgH/DPeXteDDwPuA14ML8+cbm2raHOf0X2dfXvgW/ml9cnWuu/AHbnteNEedIAAABdSURBVN4NvD8fnlythelv4tCvZZKrk6wv+678cs/8upNora8A7syX//8AVjZZp08/YGbWQV3qljEzs5zD3cysgxzuZmYd5HA3M+sgh7uZWQc53M3MOsjhbmbWQf8fBEplud2yjAwAAAAASUVORK5CYII=\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.figure(1)\n",
|
|
"plt.title('segmented image')\n",
|
|
"plt.pcolormesh(ID[:,:],cmap='hot')\n",
|
|
"plt.grid(True)\n",
|
|
"plt.axis('equal')\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 246,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"Data = np.transpose(np.array([Lid,ID,ID,ID,ID,ID,ID,ID,ID,ID,ID,ID,ID,ID,ID,ID,ID,Lid]))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 248,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"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.figure(1)\n",
|
|
"plt.title('segmented image')\n",
|
|
"plt.pcolormesh(Data[:,:,9],cmap='hot')\n",
|
|
"plt.grid(True)\n",
|
|
"plt.axis('equal')\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 249,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"Data.tofile(\"discs512x512x18.raw\")"
|
|
]
|
|
},
|
|
{
|
|
"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": "3.8.3"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 4
|
|
}
|