{ "cells": [ { "cell_type": "code", "execution_count": 0, "metadata": { "collapsed": false }, "outputs": [ ], "source": [ "# Name:Makayla Roberts\n", "# I worked on this code with: Sonia\n", "\n", "# Please do all of your work for this week's lab in this worksheet. If\n", "# you wish to create other worksheets for scratch work, you can, but\n", "# this is the one that will be graded. You do not need to do anything\n", "# to turn in your lab. It will be collected by your TA at the beginning\n", "# of (or right before) next week’s lab.\n", "\n", "# Be sure to clearly label which question you are answering as you go and to\n", "# use enough comments that you and the grader can understand your code.\n" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": "\n\n", "text/plain": [ "Graphics3d Object" ] }, "execution_count": 3, "metadata": { }, "output_type": "execute_result" } ], "source": [ "#1\n", "var (\"x,y\")\n", "plot3d(3*x + 5*y, (x, -5,5), (y, -5,5), aspect_ratio= [1,1,.1])" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "Graphics object consisting of 2 graphics primitives" ] }, "execution_count": 2, "metadata": { }, "output_type": "execute_result" } ], "source": [ "#2\n", "#when y=0, f(x,y)= x^2+ y^2 just becomes f(x,y)= x^2. The tangent line is y=0\n", "plot (x^2, axes_labels= [\"X\", \"Z\"]) + plot (0, color=\"red\", thickness=3)" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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HjVId0L9/f+rUqUP37t0BuPTSSzn55JOpW7cu/fr1o0yZMkfdJzY2ltjY2MB/AyIScBkZduNWy5b25BA5togckQK7e698eXjhBddJRPytcOHCVK9endTU1MOuT01NpXbt2tneZ/fu3RQ4Yh90TEwMYEeyRCS8TZoEv/5qByXk+CK2kCpYELp3h7fftrv4ROTYunbtytixYxk3bhyrV6+mS5cubNy48eBUXc+ePUk6ZO9z48aNee+99xg5ciTr169nwYIFdOzYkcsvv5wzzzzT1bchIgGQlWUHIZo0gYoVXafxv4ic2jugTRt46inbA+MYu7hFBGjevDl//PEHffv2ZcuWLVSuXJkZM2ZQrlw5ALZs2XJYT6k2bdqwc+dOhg8fziOPPELx4sW59tprGTBggKtvQUQC5IMPYM0aGD/edZLwYAIwDO/rcfxnn4VnnoGff4ZjLPcQEQfS09OJj48nLS2NuLg413FEBNs2qHZt2/Jg7lzXaU4o+90wIRaxU3sHPPSQfUEMHeo6iYiIiL/Nm2cPJ+7Rw3WS8BHxhdSpp8KDD9peGOr/JyIicmwDBkDlytCwoesk4SPiCymwPTB27bI9MURERORo330HM2bYnXrHaCEn2YiKQuqss+Cee2xPjIwM12lERET854UX4JxzoEUL10nCS1QUUmBbIfz6q+2NISIiIv/z888weTJ07WrXFUvORU0hVbEi3HKLrbizslynERER8Y9BgyA+Htq1c50k/ERNIQX2MOM1a+D9910nERER8Yft22HsWHj4YTj5ZNdpwk9UFVJXXAFXXQX9+9teGSIiItFu6FD7O/Hhh10nCU9RVUgB9OoFX30Fc+a4TiIiIuJWWpotpJKToWRJ12nCU9QVUvXrQ/XqtuO5iIReSkoKCQkJJCYmuo4iEvVGjIB//oFu3VwnCV8Rf0RMdqZNg9tvh/nzoU4d12lEopOOiBFxa9cuOPdcuPPOsD2P1hfdrqJuRArs7r1KlTQqJSIi0WvMGPjrLx0Hk19RWUgVKGDXSn38MXz9tes0IiIiofXvv/Dii7ZZ9bnnuk4T3qKykAJo1gzOPx+ee851EhERkdCaMAG2bIGePV0nCX9RW0gVLGj7Sr33Hqxe7TqNiIhIaOzdaw8nbtYMKlRwnSb8RW0hBZCUZM/h69/fdRIREZHQePNN+Oknu8RF8i+qC6nChe0ZfG++CevXu04jIiISXJmZdklLkyZw6aWu00SGqC6kwJ4rdNppdphTREQkkr37LqxdC717u04SOaK+kDrpJHjkEbvw7pdfXKcREREJDs+zbX9uuAEuv9x1msgR9YUUQPv2tqB66SXXSURERILjo4/g22/h8cddJ4ksKqSAuDjo2BFGj4bff3edRkREJLA8D/r1gyuvhKuucp0msqiQ2q9jR9uoc/Bg10lEREQCa84c+PJLjUYFQ1SetXcsjz4Ko0bZbaGnneY6jUhk01l7IqFz9dX2bL0vvwTjixPqAsIX34lGpA7RrRvs26dRKRERiRzz58Pnn9udehFURPmGCqlDlCplF54PGQI7drhOIyIikn/PPguVK9veURJ4KqSO0L077NljiykRCbyUlBQSEhJITEx0HUUk4i1ZAjNn2i7mBfQbPyi0RiobXbrYvlI//QTx8a7TiEQmrZESCb7GjWHNGnumbEyM6zQB54uJStWn2Xj0UfjnHxg61HUSERGRvFmyxPaO6tMnIoso39CI1DF07AgTJ9pRKX1YFgk8jUiJBNfNN8OPP8LKlRFbSGlEys969LBbRYcPd51EREQkd776Cv77X41GhYJGpI7j4Ydh8mQ7KnXKKa7TiEQWjUiJBE+jRrB+PaxYEdGFlEak/O6xx+DvvyElxXUSERGRnPniC5gxQ6NRoaIRqRNo3x7eeQc2bIBixVynEYkcGpESCY6GDe1MynffRXwhpRGpcNCzJ6SlwYgRrpOIiIgc3+LF8PHHGo0KJY1I5UD79vD223ZUSmulRAJDI1IigdegAWzcCN9+GxWFlEakwkXv3natlLqdi4iIXy1aZLuYazQqtDQilUOdOsHrr9tRqeLFXacRCX8akRIJrJtugs2b7WhUlBwHoxGpcNKzJ2RkwMsvu04iIiJyuEWLYNYsePLJqCmifEMjUrnQrRu88oodlTr9dNdpRMKbRqREAqd+fdiyBb75JqoKKY1IhZsePSArC156yXUSERERa8ECSE3VaJQr+ivPhZIl7Rl8Q4fCtm2u04iIiMBTT8Ell8Dtt7tOEp1USOVSt25QsCC88ILrJCLhKSUlhYSEBBITE11HEQl78+fDnDkajXJJa6Ty4KmnYMAAe45RmTKu04iEJ62REskfz4NrroEdO+Drr6OykNIaqXDVuTMUKQL9+7tOIiIi0WrOHPj8c+jXLyqLKN/QX30eFC9up/hGj4ZNm1ynERGRaON5tll0zZrQqJHrNNFNhVQedexoj4t59lnXSUREJNp88AF89ZX9HWR8McEVvVRI5dEpp9h2CK++avtKiYiIhEJWFjzxhF0fdd11rtOICql86NDBNubs1891EhERiRZTp8J332lGxC9USOXDSSfZo2Neew1++MF1GhERiXT79tlWB40aQa1artMIqJDKtwcftC0Q+vRxnURERCLd66/D2rWaCfETFVL5VKSI7Sv11luwbJnrNCIiEqkyMuDpp6FpU6hSxXUaOUCFVAC0bg0VKkCvXq6TiIhIpBozBjZvhr59XSeRQ6mQCoCCBe2iv5kz4bPPXKcREZFIs3u3/T3TqhVcfLHrNHIoFVIBcvvtUKOGXXye/1N3REJvxIgRlC9fniJFilC9enXmzZt33NtnZGTQu3dvypUrR2xsLOeffz7jxo0LUVqR6DJsGPzxh11oLv5S0HWASGEMPP88XH+9bZR2yy2uE4nk3JQpU+jcuTMjRoygTp06jB49mgYNGrBq1SrOOeecbO/TrFkzfvvtN1599VUuuOACtm3bxr59+0KcXCTy/fmn/f1y//1QvrzrNHIkHVocYDfcAL/+Ct9+CzExrtOI5EzNmjWpVq0aI0eOPHhdxYoVufXWW+mfzaGSM2fOpEWLFqxfv57TTjstT8+pQ4tFcubRR2HECFi3DkqXdp3GV3zR011TewH23HOwahVMnOg6iUjO7Nmzh6VLl1K/fv3Drq9fvz4LFy7M9j4ffPABNWrU4IUXXuCss87ioosuolu3bvzzzz/HfJ6MjAzS09MPu4jI8W3aBEOH2vNdVUT5kwqpAEtMhDvvtH2lMjJcpxE5se3bt5OZmUnpI96lS5cuzdatW7O9z/r165k/fz4rVqxg2rRpDB48mHfeeYcOHToc83n69+9PfHz8wUvZsmUD+n2IRKInn4S4OHjkEddJ5FhUSAVBv37wyy8wapTrJCI5Z444+dTzvKOuOyArKwtjDJMmTeLyyy+nYcOGDBo0iAkTJhxzVKpnz56kpaUdvGzatCng34NIJFmxwp6c0aePPd9V/EmFVBBUqAD33msLqp07XacROb4SJUoQExNz1OjTtm3bjhqlOqBMmTKcddZZxMfHH7yuYsWKeJ7H5s2bs71PbGwscXFxh11E5Nh69YJzz4UHHnCdRI5HhVSQPPmkLaIGDXKdROT4ChcuTPXq1UlNTT3s+tTUVGrXrp3tferUqcOvv/7K33//ffC6tWvXUqBAAc4+++yg5hWJBvPmwYcf2t5RhQu7TiPHo0IqSM4+G/7zH3jpJfj9d9dpRI6va9eujB07lnHjxrF69Wq6dOnCxo0bSU5OBuy0XFJS0sHb33333Zx++unce++9rFq1irlz59K9e3fuu+8+ihYt6urbEIkIngc9ekC1atCsmes0ciIqpILoscegQAG7k0/Ez5o3b87gwYPp27cvVapUYe7cucyYMYNy5coBsGXLFjZu3Hjw9sWKFSM1NZUdO3ZQo0YNWrZsSePGjRk6dKirb0EkYrz/PixaBAMG2N8h4m/qIxVk/frBM8/Y07r3/04SEdRHSiQ7+/bBJZdA2bIwe7brNL6nPlLRoHNnOPVUePxx10lERMTvJkyA77+3ncwlPKiQCrJixexJ3RMnwtKlrtOIiIhf7d5tNyrddZddHyXhQYVUCNx3HyQk2M60OtBYRESyM3So3ZzUr5/rJJIbKqRCoGBBePFF+Owz+Ogj12lERMRv/vjDTuclJ8N557lOI7mhQipEGjSAa6+1h0/u2+c6jYiI+En//pCZqfW04UiFVIgYY3tKrVkDY8e6TiMiIn7x888wbBh07w6lSrlOI7ml9gch1ro1zJwJP/6os5Mkuqn9gYjVqpVtdbBund2gJDmm9gfRqF8/SE+HF15wnURERFxbssTu6n7mGRVR4UojUg706gWDB9smnTqWTKKVRqQk2nke1KsHf/4Jy5fbjUmSKxqRilaPPWY/eTzxhOskIqGXkpJCQkICiYmJrqOIODV9uj2ceOBAFVHhTCNSjqSk2EONly2Dyy5znUYk9DQiJdFszx6oVAnOP9+um5U80YhUNHvgAbjwQjXpFBGJRiNGwPr1dje3hDcVUo4UKmQXnM+ZA7NmuU4jIiKh8uef9uiwdu2gcmXXaSS/NLXn0IGFhn/9ZRcaxsS4TiQSOprak2jVtSuMGWPb4JQu7TpNWNPUXrQ70KRzxQoYP951GhERCbYff4Thw+2mIxVRkUEjUj7QsqWd4vvhB9AHc4kWGpGSaHTHHfDVV/aUi6JFXacJexqREmvAAPj7b534LSISyebNg/feg+eeUxEVSTQi5RPPPGMvK1fa3XwikU4jUhJNMjMhMdGuhf3iCyigYYxA0IiU/E+3blCmDDzyiOskIiISaBMm2L6BQ4eqiIo0+nH6RNGiduH5hx+qHYKISCRJS7NHg7VsCbVquU4jgaapPR/xPLj6avj9d/jmG9trSiRSaWpPokW3bjBypD1f9ayzXKeJKJrak8MZA0OGwPff2390IiIS3tasse/rvXqpiIpUGpHyoQcfhKlTbTuEEiVcpxEJDo1ISTS4+Wa7iWjVKu3UCwKNSEn2+vWz03x9+rhOIiIiefXxx/Df/8LAgSqiIplGpHzq5ZftvPqyZXDppa7TiASeRqQkku3ZY9+7zzwTPvnELt2QgPPF36pGpHyqQwfbT6pzZzs6JRIpUlJSSEhIIDEx0XUUkaBJSbHLMwYPVhEV6TQi5WMffwwNG8K778Ltt7tOIxJYGpGSSLVtm/0g3LIljBjhOk1E80WJqkLK5xo1sosUV6+GIkVcpxEJHBVSEqkeeADeeceOSJ1+uus0Ec0XhZSm9nxu0CDYvNl+FRERf1uyBMaOhaefVhEVLTQiFQYeeQRGjbL9pcqWdZ1GJDA0IiWRJjPTdi7fs8cWVAULuk4U8TQiJTnTpw/ExekcPhERPxs7Fr76yi40VxEVPVRIhYH4eHsO39tvQ2qq6zQiInKk7duhZ09o0wbq1HGdRkJJU3th4sA5fFu3wrffQmys60Qi+aOpPYkk7drZHdZr1kCpUq7TRA1N7UnOGWOHi9ets806RUTEHxYvhldfhWefVREVjTQiFWa08FwihUakJBJkZkJiov2w++WXEBPjOlFU0YiU5N6TT9qF5127uk4iIiKjRsHy5bbxpoqo6KRCKszExdkDMN95B2bPdp1GRCR6/fYb9O5t10fVrOk6jbiiqb0w5HlwzTWwZYsWnkv40tSehLs2beDDD+0C8xIlXKeJSprak7w5dOG5Op6LiITe/Pnw2mvw/PMqoqKdRqTCWLdudl5+5UooX951GpHc0YiUhKt9+6BaNShaFBYtggIaknBFI1KSP089ZT8JPfSQne4TEZHgGz4cVqywH2RVRIleAmGsWDE7xTdzpu16LhIOUlJSSEhIIDEx0XUUkVz79Vd7bFdyMlSv7jqN+IGm9iLAHXfAwoWwejUUL+46jUjOaGpPwtHdd9ujutauhVNPdZ0m6mlqTwJj6FDYtQt69XKdREQkcs2aBZMn27NPVUTJARqRihDDhkGnTrBgAdSq5TqNyIlpRErCya5dULkynHcezJljd0+Lc774KaiQihCZmbaA+vdfWLoUChVynUjk+FRISTjp3t0uMv/uO7jgAtdpZD9fFFKa2osQMTHwyiuwapV6S4mIBNLXX9v31T59VETJ0TQiFWEO9JZascIOQYv4lUakJBzs2wdXXAF79mi034c0IiWB99RTULKkekuJiATCsGF2RGrMGBVRkj0VUhHmQG+pWbNg6lTXaUREwtdPP8Hjj8PDD+tQYjk2Te1FqDvvtGdBff+9ekuJP2lqT/zM86BRI7u4fNUqOOUU14kkG5rak+AZMgR274bHHnOdREQk/EydCh9/bEf4VUTJ8aiQilBnnWVPJR89Gj7/3HUaCQcjRoygfPnyFClShOrVqzNv3rwc3W/BggUULFiQKlWqBDegSIj8+Sd07GhH9ps0cZ1G/E6FVARLToa6daFtWzs6JXIsU6ZMoXPnzvTu3Ztly5ZRt25dGjRowMaNG497v7S0NJKSkrjuuutClFQk+B59FDIy7KkRIieiNVIRbu1auOwy6NDBHmsgkp2aNWtSrVo1Ro4cefC6ihUrcuutt9K/f/9j3q9FixZceOGFxMTEMH36dJYvX57j59QaKfGjzz+Hq6+GUaPgwQddp5ET0BopCb6LLoK+feHll2HxYtdpxI/27NnD0qVLqV+//mHX169fn4ULFx7zfuPHj2fdunU8+eSTOXqejIwM0tPTD7uI+Mnu3dCuHdSpA/ff7zqNhAsVUlGgSxeoXh3uu88OV4scavv27WRmZlK6dOnDri9dujRbt27N9j4//PADjz32GJMmTaJgwYI5ep7+/fsTHx9/8FK2bNl8ZxcJpCefhE2b4NVXoYB+O0oO6aUSBQoWhHHj4McfoV8/12nEr8wRp7B6nnfUdQCZmZncfffdPP3001x00UU5fvyePXuSlpZ28LJp06Z8ZxYJlC+/tMfAPP00VKjgOo2Ek5x9lJSwV7ky9O4NzzwDd9wB2mAlB5QoUYKYmJijRp+2bdt21CgVwM6dO1myZAnLli3j4YcfBiArKwvP8yhYsCCzZ8/m2muvPep+sbGxxMbGBuebEMmHjAw7Yl+1KjzyiOs0Em40IhVFevaEhAT7hrF3r+s04heFCxemevXqpKamHnZ9amoqtWvXPur2cXFxfPfddyxfvvzgJTk5mQoVKrB8+XJqqgW0hJlnn7Ubc8aPtyP4Irmhl0wUKVzYTvHVrAkvvgi9erlOJH7RtWtXWrVqRY0aNahVqxavvPIKGzduJDk5GbDTcr/88guvv/46BQoUoHLlyofdv1SpUhQpUuSo60X8btky6N/fjthfconrNBKOVEhFmRo1oHt3uw7g1lvtCJVI8+bN+eOPP+jbty9btmyhcuXKzJgxg3LlygGwZcuWE/aUEgk3GRmQlGSXPuiDpeSV+khFoX/+sWukTjvNnscXE+M6kUQj9ZES13r2hIEDYelSjUaFKfWREjeKFrVTfF98Yd9ERESizeLF8MILdnReRZTkh0akolj37vYIhKVL7dC2SChpREpc2b3b7tArXhwWLNAC8zCmESlx65ln4IIL7BqBPXtcpxERCY1evWDjRnjtNRVRkn8qpKJYkSLw+uvw3Xd2+6+ISKT77DMYMgSeew4uvth1GokEmtoTnn7ajk4tWgSJia7TSLTQ1J6E2s6dcOmlcM458OmnOgYmAvhiak+FlLB3L9SqZdcNLF1qF6OLBJsKKQm15GSYOBG+/RbOO891GgkAXxRSqseFQoXsWoH16+Hxx12nEREJvFmzYPRoeOklFVESWBqRkoNeegkefdSuIbjqKtdpJNJpREpCZccOuzM5IcEWVNmcxS3hyRc/SRVSclBmJlx9NfzyC3zzDZxyiutEEslUSEmoJCXB++/DihVQtqzrNBJAviikNLUnB8XE2Cm+33+Hjh1dp5FIlZKSQkJCAona2SAhMGUKvPEGDBumIkqCQyNScpQJE+Dee2HqVGja1HUaiVQakZJg27TJ7tK78UaYPFlTehHIFz9RFVJyFM+DZs3gk0/s7pazz3adSCKRCikJpsxMuO46u4nmm2/g1FNdJ5Ig8EUhpak9OYoxdnfLSSdB69aQleU6kYhI7rz0Esyda5sOq4iSYFIhJdk67TT7BvTppzBokOs0IiI59/XX8MQTdhfy1Ve7TiORTlN7clzdu9vjFL78EqpUcZ1GIomm9iQYdu+GatXg5JPtaQ2FC7tOJEGkqT3xv379oFIluPtu+Ocf12lERI6vWzd7IPGkSSqiJDRUSMlxxcbaN6QNG+wblIiIX334IYwcaZcj6EBiCRUVUnJCCQn2jWnECHj3XddpRESOtnmzbdvSuDE8+KDrNBJNtEZKcuRAS4TUVFi2DMqXd51Iwp3WSEmg7Nv3v1YHy5fD6ae7TiQhojVSEj6MgTFj7G6+Fi1gzx7XiURErGeegfnz4c03VURJ6KmQkhwrXhzeestuLe7d23UaERHbouWZZ+Dpp6FuXddpJBppak9ybdAgeOQR+OgjaNTIdRoJV5rak/zats22ZalYEWbPtueFSlTxxdSeCinJNc+DJk1sj5bly3WEjOSNCinJj6ws+0Fu6VJ7BEyZMq4TiQO+KKQ0tSe5ZgyMHw9Fitj+Uvv2uU4kItFm4ECYORPeeENFlLilQkrypEQJe5r6ggXQt6/rNCISTRYvhl69oEcPuPFG12kk2qmQkjyrW9cWUf36wSefuE4j4SIlJYWEhAQSExNdR5Ew9NdfcNddkJhoF5mLuKY1UpIvmZn2E+GKFXadQunSrhNJuNAaKcmtrCy45RY7Er5sGZQr5zqROKY1UhL+YmJg4kS7AL1lS1tYiYgEw/PPw3//a4+tUhElfqFCSvLtjDNsI7xPP4Unn3SdRkQi0Zw58MQT9tKgges0Iv+jqT0JmP797QLQDz6w512JHI+m9iSnNm+GqlWhWjWYMUP9ouQgX0ztqZCSgMnKgttug88/t71dzj/fdSLxMxVSkhN79kC9evDLL/ZUhRIlXCcSH/FFIaWpPQmYAgXgtdegZEm44w7Yvdt1IhEJd9262Q9m77yjIkr8SYWUBFTx4vDuu7B2LbRvbxehi4jkxeTJMGwYDBkCl1/uOo1I9lRIScBdeim88gq8/jqMHu06jYiEo5UroV07uxs4Odl1GpFj0xopCZoOHWDMGJg3D2rWdJ1G/EZrpORYduyw7xmFCsEXX8DJJ7tOJD6lNVIS2V5+GWrUgNtvhy1bXKcRkXCQmWlHobZtg2nTVESJ/6mQkqApXNiulwK7+Dwjw20eEfG/xx+3hxG/9RZceKHrNCInpkJKgqpMGXjvPbvr5uGHtfhcRI5tyhTbvXzAAB1GLOFDhZQEXc2adtH52LEwapTrNCLiR8uXw7332mm9Rx5xnUYk57TYXEKmUycYMQI++QSuusp1GnFNi83lgN9/t+spS5SA+fOhaFHXiSRMaLG5RJeXXoK6deHOO2HDBtdpRMQP9u6Fpk3h339h+nQVURJ+VEhJyBQqBFOnQlwc3HwzpKW5TiQupKSkkJCQQGJiouso4gNdusDChXZjStmyrtOI5J6m9iTk1qyBK66wnYr/+18oWNB1InFBU3uSkmI3oYweDQ884DqNhCFN7Ul0qlDBfvr8v/+Djh21k08kGs2YYf/9d+miIkrCmwopceLaa2HkSHsZOtR1GhEJpW+/hebN7RT/iy+6TiOSP5pUEWfatbOHG3ftChdcAI0auU4kIsG2ZYstoC68ECZNgpgY14lE8kcjUuLU889DkybQogV8843rNCISTLt323/vmZnw4YdQrJjrRCL5p0JKnCpQACZOhIsusp9SdSafSGTKyoJWrWDVKvjoIzjrLNeJRAJDhZQ4d/LJ8MEH9o22SRP7qVVEIkvPnvYQ4smToWpV12lEAkeFlPjCWWfZT6mrVkFSki2qRCQyjB0LL7wAgwbZD0sikUSFlPhG1ar20+p779mzttQWQST8/fe/kJwM7dvbY6JEIo0KKfGVJk1sk77Bg7UtWiTcffGFPf7l5pth2DAwvmifKBJYan8gvtO+PWzdCj16QKlS0KaN60Qikltr19qWJgdGmtXmQCKVRqTEl556ynY7btfOTg1I8I0YMYLy5ctTpEgRqlevzrx584552/fee48bbriBkiVLEhcXR61atZg1a1YI04qfbdkCN95oPwh9+KEOIpbIpkJKfMkYGDECGje2UwOLFrlOFNmmTJlC586d6d27N8uWLaNu3bo0aNCAjRs3Znv7uXPncsMNNzBjxgyWLl3KNddcQ+PGjVm2bFmIk4vfpKdDw4awZw/MnAmnneY6kUhw6dBi8bV//rGfbFesgPnzISHBdaLIVLNmTapVq8bIkSMPXlexYkVuvfVW+vfvn6PHqFSpEs2bN6dPnz45ur0OLY48e/bYImrJEpg3Dy65xHUiiXC+WHWnESnxtaJFbY+ps8+2BdXmza4TRZ49e/awdOlS6tevf9j19evXZ+HChTl6jKysLHbu3Mlpxxl+yMjIID09/bCLRI7MTGjZ0hZQ77+vIkqihwop8b3ixe0UQYECtpj680/XiSLL9u3byczMpHTp0oddX7p0abZu3Zqjxxg4cCC7du2iWbNmx7xN//79iY+PP3gpW7ZsvnKLf2Rl2TWN06bB1KlQr57rRCKho0JKwsKZZ8KsWfDbb3bd1K5drhNFHnPE3nTP8466LjuTJ0/mqaeeYsqUKZQqVeqYt+vZsydpaWkHL5s2bcp3ZnHP82zft3HjYMIEuOUW14lEQkuFlISNiy+GGTPg229tv6l//nGdKDKUKFGCmJiYo0aftm3bdtQo1ZGmTJlC27ZtmTp1Ktdff/1xbxsbG0tcXNxhFwl/ffvavm8pKXDPPa7TiISeCikJK5dfbtshLFoEd95pF7dK/hQuXJjq1auTmpp62PWpqanUrl37mPebPHkybdq04c0336RRo0bBjik+NHiwbVXy3HPw0EOu04i4oUJKws5VV8H06TBnDtx9N+zb5zpR+OvatStjx45l3LhxrF69mi5durBx40aSk5MBOy2XlJR08PaTJ08mKSmJgQMHcsUVV7B161a2bt1KWlqaq29BQmzcOOjSxTbO7dnTdRoRd1RISViqXx/eftvuDrr3Xh1ynF/Nmzdn8ODB9O3blypVqjB37lxmzJhBuXLlANiyZcthPaVGjx7Nvn376NChA2XKlDl46aTD1KLCxIm2We6DD0IOu2OIRCz1kZKwNmWKHZVq2xZGj9ZZXuFEfaTC06RJkJQErVvD2LF2N62II754x9dZexLWmjeHf/+15/EVKgTDh6uYEgmWyZNtEZWUpCJK5AAVUhL2WreGvXvh/vvtVuzhw/UGLxJoU6bYXXmtWqmIEjmUCimJCO3a2ZGoA8VUSore6EUCZepU27W8ZUt49VWIiXGdSMQ/VEhJxGjb1hZT7drZxecjR6qYEsmvd96x6xBbtIDx41VEiRxJhZRElPvus8XTfffZkalRo1RMieTV22/DXXfZtYivvaYiSiQ7KqQk4rRpY0em7r3Xrp0aMwYK6pUukiuvvWY/kLRooSJK5Hj060UiUuvWdhdfUpI9l2/iRChc2HUqkfAwYgR06GDXHI4cqSJK5Hg06SER6+677fqO99+H227T2XwiOfHii7aI6tzZ9mZTESVyfCqkJKLdeit89BF89hk0bAg7d7pOJOJPngdPPgmPPgpPPAGDBqknm0hOqJCSiHfDDTBrFnz9NVx/Pfzxh+tE0S0lJYWEhAQSExNdR5H9srKga1fo2xcGDLBfVUSJ5IyOiJGosXQp3HQTlCwJM2fCOee4ThTddESMP+zZYzdmTJ5s+6+1b+86kUiO+aLc14iURI3q1WHBArtWqlYt+O4714lE3Pr7b2jSxK4lnDJFRZRIXqiQkqhy0UWwcCGUKgV168Lcua4TibixfTtcd539cPHxx9C0qetEIuFJhZREnTJl4PPP7QhV/frw7ruuE4mE1rp1UKcObNhgN2Jce63rRCLhS4WURKW4OJgxw+7qa9rU9s0RiQYLF8IVV9hdegsX2g8UIpJ3KqQkasXGwptvQqdOtm9O166Qmek6lUjwvP22HX2qWBEWLYILLnCdSCT8qZCSqFagALz8MgwdCkOG2Madf//tOpVIYHkevPACNGsGd9wBqalw+umuU4lEBhVSIsB//vO/xp1XXgmbNrlOJBIY+/ZBcjL06GEbbU6caEdjRSQwVEiJ7NeggV0zsmMHXH45fPWV60Qi+bN9O9x4I4wbZy9qtCkSeCqkRA5RuTJ88QWcey7Uq2fXlIiEo2XLoEYN2y9tzhzbdFNEAk+FlMgRSpeG//s/u6OvWTPo2VOL0CW8TJoEtWtDiRKwZIn9UCAiwaFCSiQbRYvaX0YvvmgX6TZqBH/+6TqVyPHt22d3n95zDzRvDvPm6SgkkWBTISVyDMZAt272XL6vvoLERB0rI/71+++2wezQofYyfrz9QCAiwaVCSuQEbrjBTo8UK2YbGb7xhutEIof7+mu7HmrFCvjkE7sLVYvKRUJDhZRIDpQvb3f0NW0KSUnQti3s3u06lQi89po97qVUKVi6VOuhREJNhZRIDp18MkyYYKdMJk+GmjVh9WrXqcJPSkoKCQkJJCYmuo4S1v7+G1q3hjZtoEULewB32bKuU4lEH+N5Xn4fI98PIBJuVq60O/p++glGjYJWrVwnCj/p6enEx8eTlpZGXFyc6zhhZflyu5j8l19g5Ei9/iRq+WICWyNSInlQqRJ8+eXhU327drlOJZHO82D4cDsaetJJdm2UiigRt1RIieTRoVN9b70FVava4kokGLZvh9tvtwvJk5Nh8WK46CLXqUREhZRIPrVpY7tIFy9umyD27Wv7+YgEyvTpdhR03jz730OG6Lw8Eb9QISUSABddBAsWQO/e8PTTULcu/Pij61QS7v76y07d3XYb1Kpl1+bdcovrVCJyKBVSIgFSqJAtoubPh23b4NJLYeBAjU5J3nz8sT378cMP4fXXYdo0e3yRiPiLCimRAKtVC775Bh54ALp3t3/+9lvXqSRcpKdDu3bQsCFccoltstmqlRpsiviVCimRIChWDAYPtk08d++G6tXhiScgI8N1MvGzWbNs8TRlCrzyih2VOvts16lE5HhUSIkE0RVX2C3qvXvDgAF2Z9/Cha5Tid9s2WL7Qt10E1x4oT3T8f77NQolEg5USIkEWWwsPPWU3dkXFwdXXmm3sO/Y4TqZuJaZCSkpcPHF8Omn9hzH1FQ491zXyUQkp1RIiYRIpUp2Z9/LL9veUxUq2K9ZWa6TiQtffmnXzz38sD3iZc0auOcejUKJhBsVUiIhFBMDnTrZX5rXXQf33Wd7Ty1Z4jqZhMrmzbYbfs2ads3c/PkwejSceqrrZCKSFyqkRBw46yx480347DO7GP3yy+0BtJs2uU4mwbJ7t22PUaECzJxpi6evv4Y6dVwnE5H8UCEl4lC9evaXaUqK/eV60UXQq5fdAi+RISsLJk2yBdRzz9mpvB9+sO0xYmJcpxOR/FIhJeJYwYLQvr3thN6tm22bcMEF9hiQf/5xnS7wUlJSSEhIIDEx0XWUoPI820yzalW79unyy2HVKrt7Mz7edTqR6GKMKWCMWWSM8YwxQ09w23OMMTv337bBCR/b87z85sv3A4jI/2zeDH362G7WpUrBY4/ZrfBFi7pOFljp6enEx8eTlpZGXFyc6zgB9ckntuXFF1/YUcdnn9UUnkgQ5GprhjGmEvA1UBCo63lets1ojDEzgAbAJM/z7jnR42pESsRnzj4bxo2D77+H+vWhSxc4/3wYNgz+/dd1OjkWz7Nr3q69Fq6/3v559mzb1kBFlIh7nuetBPpja5+xxpijjv42xrTEFlHbgc45eVwVUiI+dcEFMGGCLahuuAE6d/5fQbV7t+t0ckBWFkyfblsZXHMN/PknvP8+LF5sf25qZyDiK88Bq4CKwOOH/g9jTAlg8P4/dvI8b3tOHlCFlIjPXXghvPYarF5tWyZ07gxly8Ljj9uO2OLG3r3251K5Mtx2m228OmOGbbzapIkKKBE/8jxvD9AWyAJ6GGMuOeR/DwZKADM8z3szp4+pQkokTFx0kV039cMP9hDbIUOgXDnbNmH5ctfposevv9pO9eXKQZs2duRwwQL4/HNo0EAFlIjfeZ63GEgBCgGvGmNijDE3AS2Bv4H2uXk8LTYXCVNpaTB2rC2oNm2yi5ofeABuvx2KFHGd7sTCabG558G8ebZNxXvv2dGnVq1sK4NKlVynE4laef7YYowpBqwAygFPAffu/+//eJ43PFePpUJKJLzt2wfvvgsjR9pRkdNOs52z778fEhJcpzu2cCiktm6Ft96yi/+/+86OCnboYEcB1cJAxLl8jf/uH4X6+JCrFmJ38+Xq4C4VUiIRZM0aO0o1YQJs3w5XXGHPcWvaFM4803W6w/m1kNq1yy4enzjR7rqLiYGbb7a9vq67DgpoQYSIX+R7It0Y8wZwD7AHqOJ53upcP4YKKZHIk5Fhd45NnGg7pu/bB1ddZYuqO+6AkiVdJ/RXIbV3r21TMHGinbrbtQuuvNI20mza1I7yiYjvBKKQagOMB372PO/cPD2GCimRyPbXX3aEZcoUmDPHXnfttXYt1c03275VLrgupNLSbJH5/vt2t11amp26a9UKWraE8uVDHklEckeFlIiE1u+/2xGXqVPteqrMTLtY+rrr7KVevdCt/Ql1IbV3L3z1lR15+r//s4vH9+61R7g0aQK33AJVqmjXnUgYUSElIu789RfMmmVHqT75BH76ya7/qVHDFlXXXAOJiVC8eHCeP9iF1N698M03hxdOu3ZBXJyd5rzxRltAnXNOwJ9aREIjSgqprCz444/8PoeIBNlPP9liY948mD8fft/f07f8uXDppXDZZfZy6aWBKa7Sd+4k/vzzSVu3jrhTTsnXY/39N6xdaxfbr1xpm2J++y38mwEnFbWL7uvUgbp14ZJL7EHRIuJjp5+ek50dUVJI/f67PXlVROQQ6UA8kAb4Z8+eiPjCtm052RXji0IqX5/LjDEmLS3t+DfauTM/TyEiESr9iK8iIgft3Gk73x5HfHx8HLDTC8CIUH7kd4D7lHh1pRORfCjrOoCI+M/55+fkVmnYgW2nn8fyNbW3f0Tq+B1At2/P6V+IiESRdGwRtQlN7YnIEdatgxIljnuTeDuSE94jUjkKX6wYbNvGzp07Oe/881m/bh2n5HNh6YnUqVOHBQsWBPU59Dx5p9eCngdg56+/QpUqmOXLiQty2/VI+nsL9XOF5LWg9wQ9D0e8Ds4994SLzT3P88XKgODvXSlQAEqWxIuNZTvglShh9x8H0d2dOoWkdbOeJ2/0WtDzAHgZGfbr6acH/bki6e8t1M8VkteC3hP0PBzxOgijs5hC1kfKdRdj8Q+9FgRg8+bNlC1blk2bNnG2q/bq4gt6TxDI0+vAF+1zQ1byxcbG8uSTTxJ7glX4Evn0WhDg4M9frwPRe4JA+L4O1NlcRJzQKISI5JMvRqQCUUiJiOSaMSaO/duX/bJoVEQkt1RIiYgTxhgDnIIPti+LiOSVCikRERGRPAqf/YUiIiIiPhPUQsoY09sYs9AYs9sYsyOH9zHGmKeMMb8aY/4xxnxmjKkUzJwSXMaYU40xbxhj0vZf3jDGFD/BfSYYY7wjLotDFFlEAswY85AxZoMx5l9jzFJjTN3j3PbqbP79e8aYi0OZWQLLGHOVMebD/b/fPWPMrTm4T739r5d/jTHrjTHJIYiaK8EekSoMvA2MzMV9HgW6Ag8DicBWINUYE9x2txJMbwJVgJv2X6oAb+TgfjOBModcGgYnnogEkzGmOTAYeBaoCswDPjbGnHOCu1bg8PeAH4IYU4LvZOAb7O/3EzLGlAdmYF8vVYHngKHGmDuCljAPQrJGyhjTBhjseV7xE9zOAL/uv+2A/dfFAr8BPTzPGx3kqBJgxpiKwCrgCs/zvth/3RXAIuBiz/PWHON+E4DinufdGqKoIhIkxpgvgK89z2t/yHWrgeme5/XM5vZXA58Cp3qetyNEMSWEjDEecJvnedOPc5sBQBPP8yoect0o4DLP82oFP2XO+G2NVHngDGD2gSs8z8sAPgdquwol+VILSDtQRAF4nrcYu+39RD/Tq40x24wxa40xY4wxpYIZVEQCzxhTGKjOIe/r+83mxO8By4wxW4wxnxhjrglKQPGzWhz9upkF1DDGFHKQJ1t+K6TO2P/1tyOu/+2Q/yfh5QxgWzbXb+P4P9OPgZbAtcAj2Gne/9s/Qiki4aMEEEPu3te3AA8AdwC3A2uAT4wxVwUrpPjSGWT/uimIfV35Qq4PLTbGPAU8eYKbJXqetyRPiawj5xtNNteJQzl9Hez/mt3P7rg/U8/zphzyxxXGmCXAz0Aj4L2cJxURn8jx+/r+Kf9Dp/0XGWPKAt2AucGJJz6V3esmu+udyXUhBQwH3jrBbX7Kw+OCXVgOtgrdcsj1pTi6KhW3cvo6uBQonc3/K0kufqae520xxvwMXJjT+4iIL2wHMjl69Cm37+uLgXsCFUrCwlayf93sA/4IfZzs5bqQ8jxvO/YfRjBswP7F3QAsg4Pz6/WAHkF6TsmDnL4OjDGLgHhjzOWe5325/7qaQDywMKfPZ4w5HSjL4QW2iPic53l7jDFLse/r0w75XzcA7+fioaqif//RZhHQ+Ijr6gNLPM/b6yBPtoLdR+ocY0wV4BwgxhhTZf+l2CG3+d4YcxvA/mMiBgO9jDG3GWMqAxOA3dgt9BJmPM9bjW1jMMYYc8X+HXtjgI8O3bF36OvAGFPMGPOSMaaWMebc/Tt4PsQWbtOOehIR8btBQDtjzH3GmIrGmJexvxdGARhj+htjXj9wY2NMZ2PMrcaYC40xlYwx/bHrpYY7SS8Bsf+9vcr+ugCg/P4/n7P//x/2OsC+PsoZYwbtf93cB7QFXgpt8uPLy9RebvQFWh/y52X7v14DfLb/vytgRycOeAEoCowATgW+AOp7nrczqEklmFoCQ/nf7osPOLqPyKGvg0zgEiAJKI79FPop0FyvA5Hw43nelP2jyn2w/aBWAA09z/t5/03KYAurAwpjf1meBfwDrAQaeZ43I3SpJQhqYN/LDxi0/+trQBuOeB14nrfBGNMQeBnogG2P1NHzvHdDkjaHdNaeiIiISB75rf2BiIiISNhQISUiIiKSRyqkRERERPJIhZSIiIhIHqmQEhEREckjFVIiIiIieaRCSkRERCSPVEiJiIiI5JEKKREREZE8UiElIiIikkcqpERERETySIWUiIiISB79P3uYgEU6jfjTAAAAAElFTkSuQmCC", "text/plain": [ "Graphics object consisting of 2 graphics primitives" ] }, "execution_count": 3, "metadata": { }, "output_type": "execute_result" } ], "source": [ "#3\n", "var (\"x,y\")\n", "plot (y^2, axes_labels=[\"Y\", \"Z\"]) + plot (0, color=\"red\", thickness=3)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": "\n\n", "text/plain": [ "Graphics3d Object" ] }, "execution_count": 4, "metadata": { }, "output_type": "execute_result" } ], "source": [ "#4\n", "var (\"x,y\")\n", "z=0*x+0*y\n", "plot3d(x^2+ y^2, (x, -5,5), (y, -5,5), aspect_ratio= [1,1,.1]) + plot3d (0, (x, -5,5), (y, -5,5), color=\"red\")" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": "\n\n", "text/plain": [ "Graphics3d Object" ] }, "execution_count": 5, "metadata": { }, "output_type": "execute_result" } ], "source": [ "#5\n", "var (\"x,y\")\n", "z= 2*(x-2)-1*(y-3)-7\n", "plot3d (2*(x-2)-1*(y-3)-7, (x, -20,20), (y, -20,20), color=\"red\", opacity= .5) + point3d ([2,3,-7], aspect_ratio= [1,1,.1], size= 10, color= \"black\")" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": "\n