135 lines
53 KiB
Plaintext
135 lines
53 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 3,
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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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"text/plain": [
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"<Figure size 432x288 with 1 Axes>"
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]
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},
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"metadata": {
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"needs_background": "light"
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},
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"output_type": "display_data"
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}
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],
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"source": [
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"from math import cos, pi\n",
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"import matplotlib.pyplot as plt\n",
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"\n",
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"def f(x):\n",
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" return cos(x*pi/2)\n",
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"\n",
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"images = []\n",
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"antecedants = []\n",
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"\n",
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"for x in range(20):\n",
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" images.append(f(x))\n",
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" antecedants.append(x)\n",
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"\n",
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"plt.plot(antecedants, images)\n",
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"plt.show()"
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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": 12,
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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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"text/plain": [
|
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|
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"<Figure size 432x288 with 1 Axes>"
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]
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},
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"metadata": {
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"needs_background": "light"
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},
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"output_type": "display_data"
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}
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],
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"source": [
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|
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"from math import sin, pi\n",
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"import matplotlib.pyplot as plt\n",
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"\n",
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"def f(x):\n",
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" return sin(x*pi/2)\n",
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"\n",
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"min_x = -2\n",
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"max_x = 2\n",
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"\n",
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"images = []\n",
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"antecedants = []\n",
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"\n",
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"x = min_x\n",
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"while x <= max_x:\n",
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" antecedants.append(x)\n",
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" images.append(f(x))\n",
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" x += 1\n",
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"\n",
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"plt.plot(antecedants, images)\n",
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"\n",
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"\n",
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"images = []\n",
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"antecedants = []\n",
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"\n",
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"x = min_x\n",
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"while x <= max_x:\n",
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" antecedants.append(x)\n",
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" images.append(f(x))\n",
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" x += 0.5\n",
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"\n",
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"plt.plot(antecedants, images)\n",
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"\n",
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"\n",
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"images = []\n",
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"antecedants = []\n",
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"\n",
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"x = min_x\n",
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"while x <= max_x:\n",
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" antecedants.append(x)\n",
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" images.append(f(x))\n",
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" x += 0.1\n",
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"\n",
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"plt.plot(antecedants, images)\n",
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"\n",
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"plt.show()"
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]
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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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||
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"name": "ipython",
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},
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"name": "python",
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"version": "3.7.2"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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||
|
|
}
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