{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "7aad0820-c1b8-4f10-aec4-bcf0056a67fc",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt \n",
"from IPython.display import display, HTML\n",
"\n",
"def recherche_front_montant(t, E):\n",
" for i in range(len(E)-1):\n",
" if (int(E[i+1]) == 1 ) and (int(E[i]) == 0 ):\n",
" m_t = (t[i] + t[i+1]) / 2\n",
" return m_t\n",
" return None\n",
"\n",
"def recherche_front_descendant(t, E):\n",
" for i in range(len(E)-1):\n",
" if (int(E[i+1]) == 0 ) and (int(E[i]) == 1 ):\n",
" m_t = (t[i] + t[i+1]) / 2\n",
" return m_t\n",
" return None"
]
},
{
"cell_type": "markdown",
"id": "110461b9-5c53-4870-a8e6-7569c1caf7d4",
"metadata": {},
"source": [
"## Mesures temporelles - Durée de parcours d'une onde ultrasonore\n",
"\n",
"Lorsque l'utilisateur clique sur le bouton `Mesure` le programme :\n",
" - envoie la commande `mesure` à la carte _Arduino_,\n",
" - reçoit des données sur la liaison série et les affiche sous forme de graphe $E=f(t)$."
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "169afeb4-ad18-4700-9ae5-cebab85262ee",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\t\n",
"\t\n",
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"\t \n",
"\t \n",
"\t \n",
"\t\n",
"\t\n",
"\t\n",
"\t\n",
"\t \n",
"\t \n",
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"\t\n",
"\t\n",
"\t\n",
"\n",
"\t"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from web_sciences import WebSciences\n",
"\n",
"my_init = '''\n",
"mode = \"temporel\";\n",
"var commandes = [{texte_bouton:\"Mesure\", arduino:\"mesure\"}];\n",
"series = [{grandeur: \"E\", unite: \"\"}];\n",
"titre_graphe = \"Célérité des ultrasons dans l'air\";\n",
"axes = [{grandeur: \"Δt\", unite: \"µs\"}, {grandeur: \"E\", unite: \"sans unité\"}];\n",
"'''\n",
"\n",
"interface = WebSciences(my_init)\n",
"interface.affiche()"
]
},
{
"cell_type": "markdown",
"id": "0ea3fcca-35dd-4456-8888-ad74f5da812f",
"metadata": {},
"source": [
"## Affichage du graphique $E = f(t)$"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "84cc755b-b548-4283-ad9d-6e7c0c4723c3",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"# coller vos données ici\n",
"\n",
"t = [4, 40, 60, 88, 112, 140, 160, 184, 216, 236, 264, 284, 316, 336, 364, \n",
"384, 412, 440, 460, 488, 512, 540, 560, 588, 612, 636, 664, 684, \n",
"716, 736, 764, 784, 816, 836, 864, 884, 912, 940, 960, 988, 1016, 1036, \n",
"1064, 1084, 1116, 1136, 1164, 1184, 1212, 1240, 1260, 1288, 1312, \n",
"1340, 1360, 1388, 1412, 1440, 1460, 1484, 1516, 1536, 1564, 1584, 1616, \n",
"1636, 1664, 1684, 1712, 1740, 1760, 1788, 1812, 1840, 1860, 1888, \n",
"1912, 1936, 1964, 1984, 2012, 2040, 2060, 2088, 2112, 2140, 2160, 2188, \n",
"2212, 2240, 2260, 2288, 2316, 2336, 2364, 2384, 2416, 2436, 2464, \n",
"2484, 2512, 2540, 2560, 2588, 2612, 2640, 2660, 2688, 2712, 2740, 2760, \n",
"2784, 2816, 2836, 2864, 2884, 2916, 2936, 2964, 2984, 3012, 3040, \n",
"3060, 3088, 3116, 3136, 3164, 3184, 3216, 3236, 3264, 3284, 3312, 3340, \n",
"3360, 3388, 3412, 3440, 3460, 3488, 3512, 3540, 3560, 3588, 3616, \n",
"3636, 3664, 3684, 3716, 3736, 3764, 3784, 3812, 3840, 3860, 3888, 3912, \n",
"3940, 3960, 3988, 4012, 4036, 4064, 4084, 4116, 4140, 4160, 4188, \n",
"4212, 4240, 4260, 4288, 4312, 4340, 4360, 4388, 4416, 4436, 4464, 4484, \n",
"4516, 4536, 4564, 4584, 4612, 4640, 4660, 4688, 4712, 4740, 4760, \n",
"4788, 4812, 4840, 4860, 4888, 4916, 4936, 4964, 4984]\n",
"E = [0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, \n",
"0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 1.00, 1.00, 1.00, 1.00, \n",
"1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, \n",
"1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, \n",
"1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, \n",
"1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, \n",
"1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, \n",
"1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, \n",
"1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, \n",
"1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, \n",
"1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, \n",
"1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 0.00, 0.00, 0.00, \n",
"0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, \n",
"0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, \n",
"0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, \n",
"0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, \n",
"0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, \n",
"0.00, 0.00, 0.00, 0.00, 0.00]"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "cf056b5d-c8a0-4950-b3cd-b398c7c48215",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
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\n",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"fig_c = plt.figure(\"Célérité des ultrasons\", figsize=(9, 6))\n",
"plt.title(\"Célérité des ultrasons dans l'air\")\n",
"plt.plot(t, E, marker = '*', label = 'E')\n",
"plt.grid()\n",
"plt.xlabel('t (µs)')\n",
"plt.ylabel ('E (sans unité)')\n",
"plt.legend()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "3aa4c7dc-d415-4348-b2d9-af8c9a11baeb",
"metadata": {},
"source": [
"## Détermination de la célérité du son"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "cb6cee74-a745-45aa-9891-0899ed74b264",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"V = 344.8 m.s-1\n"
]
}
],
"source": [
"# --- calcul de la célérité du son ---\n",
"d = 50e-2\n",
"t1 = recherche_front_montant(t, E)\n",
"t2 = recherche_front_descendant(t, E)\n",
"dt = (t2 - t1) * 1e-6\n",
"v = 2 * d / dt\n",
"print('V = {} m.s-1'.format(round(v, 1)))"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "b5cf9587-3e01-4a66-9fa7-83fadd880c39",
"metadata": {},
"outputs": [],
"source": []
}
],
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{
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},
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}
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}
},
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{
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"text": "fichier mesures_us.csv créé\n"
}
]
}
},
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