diff --git a/rms_vs_tinterrupt.ipynb b/rms_vs_tinterrupt.ipynb index 55b7c77..63dc00b 100644 --- a/rms_vs_tinterrupt.ipynb +++ b/rms_vs_tinterrupt.ipynb @@ -1,79 +1,8 @@ { "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "source": [ - "import numpy as np\r\n", - "import matplotlib.pyplot as plt\r\n", - "from functions import *\r\n", - "\r\n", - "frec, ampl = 1, 1\r\n", - "periode = 1 / frec\r\n", - "rms_unit = (np.sqrt(2) / 2) * ampl\r\n", - "\r\n", - "def function(tInt_perc, bias=0):\r\n", - " frec, ampl = 1, 1\r\n", - " rms_unit = (np.sqrt(2) / 2) * ampl\r\n", - " rms_dimmer = fun_rms_simbolic(tInt_perc, frec=frec, amp=ampl) / rms_unit\r\n", - " return rms_dimmer - bias\r\n", - "\r\n", - "def plot():\r\n", - " t_perc_serie = np.arange(0, 100, 1)\r\n", - " vt_serie = [(function(t) * 100) for t in range(100)]\r\n", - " plt.plot(t_perc_serie, vt_serie)\r\n", - " plt.xlabel(\"Porcentaje semi periodo [%]\")\r\n", - " plt.ylabel(\"Porcentaje RMS normalizado [%]\")\r\n", - " plt.grid()\r\n", - "\r\n", - "plot()" - ], - "outputs": [ - { - "output_type": "display_data", - "data": { - "text/plain": [ - "
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- }, - "metadata": { - "needs_background": "light" - } - } - ], - "metadata": {} - }, { "cell_type": "code", "execution_count": 2, - "source": [ - "from scipy.optimize import newton, bisect\r\n", - "root = bisect(function, 0, 100, args=(0.10))\r\n", - "\r\n", - "# for i in range(100):\r\n", - "# root = bisect(function, 0, 100.0, args=(i / 100))\r\n", - "# print(\"rms({:.4f}%)= {:.2f}%\".format(root, function(root) * 100))\r\n", - "\r\n", - "\r\n", - "print(\"rms(half_periode * {:.2f}%)= {:.4f}%\".\r\n", - " format(root, function(root) * 100))" - ], - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "rms(half_periode * 88.40%)= 10.0000%\n" - ] - } - ], - "metadata": {} - }, - { - "cell_type": "code", - "execution_count": 3, "source": [ "from dimmer import Dimmer\r\n", "import matplotlib.pyplot as plt\r\n", @@ -85,27 +14,18 @@ "rms_series = [dimmer.solve_tint_for_duty(duty) for duty in duty_series]\r\n", "plt.plot(duty_series, rms_series)\r\n", "plt.ylabel(\"time [s]\")\r\n", - "plt.xlabel(\"duty [%]\")" + "plt.xlabel(\"duty [%]\")\r\n", + "plt.grid()" ], "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": [ - "Text(0.5, 0, 'duty [%]')" - ] - }, - "metadata": {}, - "execution_count": 3 - }, { "output_type": "display_data", "data": { "text/plain": [ "
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CQASIi4mkf4cGfHFHd8Zfk0Zyzf/uR1j/s/oRpOzSpSGRPCIijJ5NE+jZNIHlW3Yydnb27/0IZ6UmMCi9kcYjSJmjIBDJR2qdyr/3I7w+dz1vzl/PlGXb9HwEKXOOGwRmtvMEnzfgB+fcqcVXkkjpUrNyLH85uwk39Ujmn19tZvzstdzydmBeo2u7NOTy0+tRKTY61GWKFNmJ/jmzxjlX+Tg/lQBdPBVfODIeYeqd3Rk9oB2Jp8Tx8Mcr6PToNB7+aDmbf/0t1CWKFMmJLg1dXIDvKMg2ImVGRIRxVrNanNWsFt9t+pUxs9byypx1vDJnHee1qM0N6Y1oUTc+1GWKFNhxzwicc9kAZlbBzCKCr081sz5mFp13GxE/alm3Ci/0a8PMe3pwbeeGTFv5Ixe8OJsrRs9l6optHD6s6bCl9CtoT9dMINbMEoHPgAHAq14VJRJuEqvE8bfzU5kzvCd/Pfc0Nvy8l+tfW8SZz8zg7QUb2HfwUKhLFMlXQYPAnHN7gYuAfzjnLgWaeVeWSHiqHBvNDd0aMeOeHjx3RWtioyMZ/sESuo6YxvNTV7Njz4FQlyjyBwW9fdTMrBPQH7g+uC7Sm5JEwl90ZAR9WyfSp1Ud5mb/zOiZ2Tz9+ff8IzOLy9LqcX3XJBpUqxDqMkWAggfBbcBw4F/OuWVm1giY7l1ZImWDmdE5uTqdk6vz/bZdjJmZzdsLNvDmvPX0bl6Lwd2SaV2vSqjLFJ8r0KUh59xM51wf59yI4HK2c+7WE33OzHqb2SozyzKzYcd4f4iZLTGzb8xstpmlFr4JIuHh1IRKPHFpK2bf25M/d09m1urtXDjySy57WR3LElrHDQIze+BEX5DfNmYWCYwEzgFSgX7H+EU/wTnXwjnXGngcePrEJYuEt4TKsdzbuylzh/fib+edxqYdgY7ls5+dybuLNnIg93CoSxSfOdGloUEnGF1swBXAA8d4rz2QlecW1IlAX2D5kQ2cc3m/uwKgfxKJb1QsF8Wg9EYM7NyQj77bwsszsrnn/e946rNVXN81iX7t62vEspQIcy7/371mdn8BvmO3c+6pY3z2EqC3c25QcHkA0ME5N/So7W4G7gRigJ7OudXH+K7BwGCAhISEdhMnTixAWccodPduKlasWKTPhjM/tjsc2+ycY+n2Q0xee5AVOw4TFwU96kVzVoMoqsQW7Aa/cGz3yfJjm6Hw7e7Ro8di51zasd47bhCcjIIGQZ7trwTOds4NPN73pqWluUWLFhWppszMTDIyMor02XDmx3aHe5uXbMrhpZlr+GTJD0RFRHBxu0QGd0smqfrx7zQK93YXhR/bDIVvt5nlGwRezj66GaiXZ7lucF1+JgKjPKxHJGy0qBvPyCvbsm77HsbMyua9xZuYuHAj5zSvxZDuybSsWyXUJUoZ4uUcuguBFDNLMrMYAn0Jk/JuYGYpeRbPA/5wWUjEzxpWr8Ajf2rBl/f25MbgnUZ9XvyS/mPn8WXWdrw6oxd/8eyMwDmXa2ZDgSkEBp+ND45BeAhY5JybBAw1szOAg8AvwHEvC4n4VY1K5bind1NuzEjmrfkbGDd7Lf3HzqdV3XhuzEjmrNRaREToYTlSNAUKAjM7lcBlmwTnXHMzawn0cc49fLzPOecmA5OPWndfnte3Fb5kEf+qFBvNkO7JXNO5IR98tZmXZ65hyJtfkVyjAkO6J3OKxiJIERT00tAYAiOLDwI4574jcKlHREIgNjqSKzvUZ+qd3Xm+XxuiIyO4+/3vuHfmb7w2Z50muZNCKWgQlHfOLThqXW5xFyMihRMVGUGfVnX45LZ0xl+Tximxxv2TltF1xDRGZa5h176DoS5RwkBB+wi2m1kywQFfwVtDf/CsKhEpFDOjZ9MErEMscQ1aMnJ6FiM+XcmozCyu6ZLEdV0aUqV8TKjLlFKqoEFwMzAaaGpmm4G1wFWeVSUiRWJmdGxUjY6NqvHtxl95cXoWz09dzbhZ2VzVqQE3pDeiesVyoS5TSpkCBUFwmogzzKwCEOGc2+VtWSJyslrVq8KYq9NYtXUXI6dnMWZmNq/NWUe/9vUZ0j2ZhMqxoS5RSomC3jVUBbgaaAhEmQVuUyvIDKQiElpNalXi+X5tuP2MFEZOX8Prc9fz1vwNXJ5WjxszkqlTJS7UJUqIFfTS0GRgHrAE0NSIImGoUY2KPHVZK27rlcKoGVlMXLiBiQs3cGlaPW7snky9quVDXaKESEGDINY5d6enlYhIiahfrTyPXtSSoT1TeClzDe8s3Mi7CzdySbu63NyjsQLBhwp6++gbZnaDmdU2s6pHfjytTEQ8lVgljr9f2JwZ92TQv0N9Pvh6Mz2ezGTYP79j4469oS5PSlBBzwgOAE8Af+X/nhnggEZeFCUiJad2fBwP9m3OjRmNeWnGGiYs2MD7izdxaVrgDKHuKTpDKOsKGgR3AY2dc9u9LEZEQqdWfCwP9GnGkO7JjMrM4u0FG4OBUI+hPRqrU7kMK+iloSxA54oiPlArPpYH+wYuGV1+ej3eW7SRjCcyeWDSMn7cuS/U5YkHCnpGsAf4xsymA/uPrNTtoyJlV+34OB6+sAVDuifz4rQs3pi3nrcXbGBg54YM6Z5M1QoaqVxWFDQIPgz+iIjP1D2lPI9d3JIbM5J5bupqxs7K5q1567muaxKD0hsRH6fnKoe7go4sfs3rQkSkdGtQrQJPX9aaG7sn8+wXq3lhWhavz13/+7TYcTGRoS5Riui4fQRm9m7wv0vM7Lujf0qmRBEpTVISKjGyf1s+uqUrbepXYcSnK+n2xHTemLeeg4c03jQcneiM4MiDY873uhARCS/NE+N59dr2LFi7gyemrOT/fbiUsbOyufPMU7mgZR09MS2MHPeMwDl3ZKrpm5xz6/P+ADd5X56IlHbtk6ry7p87Mf6aNOKiI7lt4jdc8OJsZq3+KdSlSQEV9PbRM4+x7pziLEREwteR5yFMvjWdZy5vRc5vBxkwbgH9x85j6eacUJcnJ3CiPoIbzWwJ0OSo/oG1gPoIROS/REQYf2pTl6l3dee+81NZvmUn578wm9snfq1pK0qxE/URTAA+AR4FhuVZv8s5t8OzqkQkrJWLiuS6rklcklaXlzLXMG72WiYv2crAzg0Y2iOF+PK65bQ0OW4QOOdygBygX8mUIyJlSeXYaO7p3ZQBnRrw9GffM3b2Wt5bvIlbe6ZwVccGxEQV9Oq0eElHQUQ8Vzs+jicubcXHt6TTvE48D320nLOfnclny7binDvxF4inFAQiUmJS61Tmjevb88o1pxMZYQx+YzFXjpnP8i07Q12arykIRKREmRk9mtbkk9vSeahvM1Zu3cl5L8xi+AdL2L57/4m/QIqdgkBEQiI6MoKrOzUk8y89uLZzEu8t2kiPJzIZOytbI5RLmIJAREIqvnw0912Qyqe3d6Ntg1N4+OMV9H52pgaklSAFgYiUCo1rVuTVa09n3MA0cg87BoxbwODXF2n8QQlQEIhIqWFm9Dotgc/u6MbdZzdh1urtnPnMDF6Yupp9Bw+FurwyS0EgIqVOuahIbu7RmC/u6k7PpjV56vPv6f3sTGZ+r8tFXlAQiEiplVgljn/0b8cb17fHzLh6/AJunvAVW3P0yMzipCAQkVIvPaUGn9yWzp1nnsrny7dxxtMzeG3OOg4d1mC04qAgEJGwEBsdya29Uvj8jm60qV+F+yct46J/fMn6neo7OFkKAhEJKw2qVeD169rz3BWt2fzrbzw4dx+PfbJSncknQUEgImHHzOjbOpEv7uxOlzpRvDRjDb2fncncNT+HurSwpCAQkbBVpXwM17cox1uDOnDYQb8x8/jrv5awe39uqEsLKwoCEQl7XRpXZ8rt3RjUNYkJCzZw9jO61bQwPA0CM+ttZqvMLMvMhh3j/TvNbHnwqWdTzayBl/WISNkVFxPJ385P5Z83diY2OoKrxy9g+Ac6OygIz4LAzCKBkQSebZwK9DOz1KM2+xpIc861BN4HHveqHhHxh7b1T+HjW9P5c/dGTFy4QX0HBeDlGUF7IMs5l+2cOwBMBPrm3cA5N905d2QikXlAXQ/rERGfiI2OZPg5p/H+kE5ERRj9xszj7x8t151F+TCvng5kZpcAvZ1zg4LLA4AOzrmh+Wz/IrDVOffwMd4bDAwGSEhIaDdx4sQi1bR7924qVqxYpM+GMz+2249tBn+2+0Rt3n/I8e6qA0zdkEtiRePPLctRv3JkCVbojcIe6x49eix2zqUd803nnCc/wCXA2DzLA4AX89n2KgJnBOVO9L3t2rVzRTV9+vQifzac+bHdfmyzc/5sd0HbPH3lNpf28Oeu8f987EbPWOMOHTrsbWEeK+yxBha5fH6venlpaDNQL89y3eC6/2JmZwB/Bfo45/R4IhHxREaTmky5vRs9mtTkkckrGPjKAn7cpTmLwNs+goVAipklmVkMcAUwKe8GZtYGeJlACPzoYS0iIlStEMPLA9rx8IXNWbB2B+c+N4sZus3UuyBwzuUCQ4EpwArgXefcMjN7yMz6BDd7AqgIvGdm35jZpHy+TkSkWJgZV3VswH9u6Uq1CuUYOH4BT0xZSa6PH48Z5eWXO+cmA5OPWndfntdneLl/EZH8nJpQiQ9v7sKD/1nGyOlrWLj2F57v14Za8bGhLq3EaWSxiPhWXEwkj13ckmcvb83SLTmc/8Is5qzZHuqySpyCQER878I2iUwa2oX4uGiuGjufUZlrjtzR6AsKAhERoHHNSvx7aFfOaV6bEZ+u5MY3v2KPT6anUBCIiARVLBfFi1e24a/nnsZny7dy8ag5bPh574k/GOYUBCIieZgZN3RrxGvXteeHnH30GTmbOVllu99AQSAicgzpKTWYNLQLNSqW4+rxC3h7wYZQl+QZBYGISD4aVKvABzd1pkvj6gz/YAmPfLycQ4fLXieygkBE5DgqxUYzbmAaAzs1YMystdz45uIyN4upgkBE5ASiIiN4sG9z7r8glc9XbKP/2Pn8uvdAqMsqNgoCEZECurZLEi/2a8uSTTlcPGoOm34pG3cUKQhERArhvJa1ef369vy4az+XjJpL1o+7Q13SSVMQiIgUUsdG1Xj3z53IPey47OW5LN2cE+qSToqCQESkCE6rXZn3hnQiLjqSfmPmsWjdjlCXVGQKAhGRIkqqXoF3h3T6fazBwjANAwWBiMhJSKwSx8TBHakVH8s14xeE5ZmBgkBE5CTVrBzLxBs6klA5loHjF7B4fXiFgYJARKQY1Kwcy9uDO1KzcizXjF8YVh3ICgIRkWKSUDmWCTd0oHJcNAPHLyD7p/C4tVRBICJSjGrHx/H69e0BGDBuAT/k/Bbiik5MQSAiUsySa1Tk1Wvbk/PbQa4et4Cc3w6GuqTjUhCIiHigRd14Rl/djnU/7+Hmt77i4KHDoS4pXwoCERGPdE6uziN/asHsrO3cP2lZqX0OclSoCxARKcsuS6vH2u17GJW5hkbVKzAovVGoS/oDnRGIiHjs7rOacE7zWjwyeQWzV5e+x14qCEREPBYRYTx1WSsa16jIbRO/ZmvOvlCX9F8UBCIiJaB8TBSjrmrHvoOHuHlC6eo8VhCIiJSQxjUr8tjFLVm8/hcenbwy1OX8TkEgIlKCLmhVh2s6N2T8l2uZtnJbqMsBFAQiIiVu+LlNaZJQiWH/XFIqnn2sIBARKWHloiJ56rJW7NhzgPv+vSzU5SgIRERCoXliPLf2SmHSt1v4+LsfQlqLgkBEJERuykimVd14/vbhErbv3h+yOhQEIiIhEhUZwZOXtmLXvlye+mxVyOpQEIiIhFBKQiUGdm7IxIUbQ/YwGwWBiEiI3dorharlY3ggRBPTKQhEREIsPi6au89uwqL1vzDp2y0lvn8FgYhIKXBpWj1aJMbz6OSV7D2QW6L79jQIzKy3ma0ysywzG3aM97uZ2Vdmlmtml3hZi4hIaRYZYdx/QSpbd+7jrXkbSnTfngWBmUUCI4FzgFSgn5mlHrXZBuAaYIJXdYiIhIu0hlXpnFyNsbOz2Z97qMT26+UZQXsgyzmX7Zw7AEwE+ubdwDm3zjn3HVB6puETEQmhGzOS2bZzP//6anOJ7dPLIEgENuZZ3hRcJyIi+ejauDotEuN5eWY2hw6XzB1EYfGoSjMbDAwGSEhIIDMzs0jfs3v37iJ/Npz5sd1+bDP4s91lsc3dauQy8pv9PPXOVNrXPvav6eJst5dBsBmol2e5bnBdoTnnRgOjAdLS0lxGRkaRCsrMzKSonw1nfmy3H9sM/mx3WWxz+mHHJ5tmMOOnSO6+oitm9odtirPdXl4aWgikmFmSmcUAVwCTPNyfiEiZEBlhDOmezLItO5mz5mfP9+dZEDjncoGhwBRgBfCuc26ZmT1kZn0AzOx0M9sEXAq8bGahn49VRKQU6NO6DpXKRfHvb7zvNPa0j8A5NxmYfNS6+/K8XkjgkpGIiOQRGx3JmakJTFm2jYcvPExMlHcXcDSyWESklDqvZW1yfjvIl2u2e7ofBYGISCnVNaU6lWKjPH9wjYJARKSUKhcVyVmptZiybCsHcr0bd6sgEBEpxc5vWZtd+3KZtfonz/ahIBARKcW6NK5OfFy0p5eHFAQiIqVYTFQEZzdL4PPl29h30JuJ6BQEIiKl3Hkt67Brfy6zVntz95CCQESklOucXI0eTWpQzqOxBGEx6ZyIiJ9FR0bwyrXtPft+nRGIiPicgkBExOcUBCIiPqcgEBHxOQWBiIjPKQhERHxOQSAi4nMKAhERnzPnXKhrKBQz+wlYX8SPVwe8fcJD6eTHdvuxzeDPdvuxzVD4djdwztU41hthFwQnw8wWOefSQl1HSfNju/3YZvBnu/3YZijeduvSkIiIzykIRER8zm9BMDrUBYSIH9vtxzaDP9vtxzZDMbbbV30EIiLyR347IxARkaMoCEREfM43QWBmvc1slZllmdmwUNfjBTOrZ2bTzWy5mS0zs9uC66ua2edmtjr431NCXWtxM7NIM/vazD4KLieZ2fzg8X7HzGJCXWNxM7MqZva+ma00sxVm1sknx/qO4J/vpWb2tpnFlrXjbWbjzexHM1uaZ90xj60FPB9s+3dm1raw+/NFEJhZJDASOAdIBfqZWWpoq/JELnCXcy4V6AjcHGznMGCqcy4FmBpcLmtuA1bkWR4BPOOcawz8Alwfkqq89RzwqXOuKdCKQPvL9LE2s0TgViDNOdcciASuoOwd71eB3kety+/YngOkBH8GA6MKuzNfBAHQHshyzmU75w4AE4G+Ia6p2DnnfnDOfRV8vYvAL4ZEAm19LbjZa8CFISnQI2ZWFzgPGBtcNqAn8H5wk7LY5nigGzAOwDl3wDn3K2X8WAdFAXFmFgWUB36gjB1v59xMYMdRq/M7tn2B113APKCKmdUuzP78EgSJwMY8y5uC68osM2sItAHmAwnOuR+Cb20FEkJVl0eeBe4BDgeXqwG/Oudyg8tl8XgnAT8BrwQviY01swqU8WPtnNsMPAlsIBAAOcBiyv7xhvyP7Un/fvNLEPiKmVUE/gnc7pzbmfc9F7hfuMzcM2xm5wM/OucWh7qWEhYFtAVGOefaAHs46jJQWTvWAMHr4n0JBGEdoAJ/vIRS5hX3sfVLEGwG6uVZrhtcV+aYWTSBEHjLOfdBcPW2I6eKwf/+GKr6PNAF6GNm6whc8utJ4Np5leClAyibx3sTsMk5Nz+4/D6BYCjLxxrgDGCtc+4n59xB4AMCfwbK+vGG/I/tSf9+80sQLARSgncWxBDoXJoU4pqKXfDa+DhghXPu6TxvTQIGBl8PBP5d0rV5xTk33DlX1znXkMBxneac6w9MBy4Jblam2gzgnNsKbDSzJsFVvYDllOFjHbQB6Ghm5YN/3o+0u0wf76D8ju0k4Org3UMdgZw8l5AKxjnnix/gXOB7YA3w11DX41EbuxI4XfwO+Cb4cy6Ba+ZTgdXAF0DVUNfqUfszgI+CrxsBC4As4D2gXKjr86C9rYFFweP9IXCKH4418CCwElgKvAGUK2vHG3ibQB/IQQJnf9fnd2wBI3BX5BpgCYE7qgq1P00xISLic365NCQiIvlQEIiI+JyCQETE5xQEIiI+pyAQEfE5BYEIYGYPmNlfTrBNazM7twjfu9nMHgouXxycOXOWmVULrks2s3fyfCbOzL4xswNmVr0o7REpDAWBSMG1JjAuo7Cecc7dF3x9C3A68DJwZXDdw8DfjmzsnPvNOdca2FLkSkUKQUEgvmVmfzWz781sNtAkz/pMM0sLvq5uZuuCI9IfAi4P/mv98uC88DWC20UE54OvcYLdHiYwAKo8cNDM0oGtzrnVXrRRpCCiTryJSNljZu0ITEnRmsDfg68IzGJ5TM65A2Z2H4FRm0OD39EU6E9g9tMzgG+dcz+dYNePEhgVugW4isAo2CtOpi0iJ0tnBOJX6cC/nHN7XWCG1qLMPTUeuDr4+jrglRN9wDn3uXOunXPuAgKzaE4GTg0+aWyMmZUvQh0iJ0VBIPJHufzf343Y/DZyzm0kMCNkTwIPP/qkoDsI/sK/hsAcMQ8SmERsNoEzDJESpSAQv5oJXBi8Q6cScEGe99YB7YKvL8mzfhdQ6ajvGQu8CbznnDtUiP3fDTzvAlMpxxGYLPAwgb4DkRKlIBBfcoFHer4DfEvgX/IL87z9JHCjmX0N5L19czqQeqSzOLhuElCRAlwWOsLM6gDtnXMfBle9ENz/EGBC4VsjcnI0+6jISQjeXfSMcy49n/cfAHY7554swnevI9A5vf2kihQ5AZ0RiBSRmQ0j8DS44cfZbDcw+MiAsgJ+b5yZfQNE83/PYRbxjM4IRER8TmcEIiI+pyAQEfE5BYGIiM8pCEREfE5BICLic/8fYHDO/ZyM5RgAAAAASUVORK5CYII=" 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