{"id":140,"date":"2022-01-25T10:54:24","date_gmt":"2022-01-25T09:54:24","guid":{"rendered":"https:\/\/yb-isn.fr\/2021\/nsi\/carla\/?p=140"},"modified":"2022-01-25T11:51:30","modified_gmt":"2022-01-25T10:51:30","slug":"mardi-25-janv","status":"publish","type":"post","link":"http:\/\/yb-isn.fr\/2021\/nsi\/carla\/?p=140","title":{"rendered":"comprehension tri"},"content":{"rendered":"

duree  d’execution d’un programme<\/p>\n\n\n

import random\nimport time\ndebut=time.time()\nt=[]\nfor i in range(100000):\n    t.append(random.randint(0,10))\nduree=time.time()-debut\nprint(duree)\n    \n>>>>0.15374755859375<\/pre>\n\n\n
nuage de points<\/p>\n\n\n
import matplotlib.pyplot as plt\nx=[i for i in range(10)]\ny=[-2*xval+10 for xval in x]\nplt.scatter(x,y)\nplt.show()<\/pre>\n\n\n\n
\"\"<\/figure>\n\n\n
visualiser la duree de cr\u00e9ation d\u2019un tableau en fonction de sa longueur n<\/strong><\/p>\n\n\n
import matplotlib.pyplot as plt\nimport time\nimport random\ndef duree_tableau_alea2(n):\n    t=[]\n    debut=time.time()\n    for i in range(n):\n        t.append(random.randint(0,10))\n    duree=time.time()-debut\n    return duree\nx=[i*10**5 for i in range(10)]\ny2=[duree_tableau_alea2(val) for val in x]\nplt.scatter(x,y2)\nplt.show()<\/pre>\n\n\n\n
\"\"<\/figure>\n\n\n\n
#toute cette partie c'est de la mise en page, couleur et presentation.\n\nplt.scatter(x,y, color='coral', linestyle='solid', label='liste en compr\u00e9hension')\nplt.scatter(x,y1, color='navy', linestyle='solid', label='tableau numpy')\nplt.scatter(x,y2, color='green', linestyle='solid', label='liste avec append')\n\nax = plt.gca()\nax.spines['right'].set_color('none')\nax.spines['top'].set_color('none')\nax.xaxis.set_ticks_position('bottom')\nax.spines['bottom'].set_position(('data',0))\nax.yaxis.set_ticks_position('left')\nax.spines['left'].set_position(('data',0))\nplt.title('dur\u00e9e de c\u00e9ation d''un tableau de n valeurs al\u00e9atoires ',color=\"navy\", fontsize=12)\nax = ax.set(xlabel='n ', ylabel='dur\u00e9e (en s)')\nplt.legend(loc='center right');<\/pre>\n\n\n\n
#partie d'import\n\nimport time\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport random\n\n#definition des tableaux\n\ndef duree_tableau_alea(n):\n    debut=time.time()\n    t=[random.randint(0,10) for i in range(n)]\n    duree=time.time()-debut\n    return duree\ndef duree_tableau_alea1(n):\n    debut=time.time()\n    t=list(np.random.randint(10,size=n))\n    duree=time.time()-debut\n    return duree\ndef duree_tableau_alea2(n):\n    t=[]\n    debut=time.time()\n    for i in range(n):\n        t.append(random.randint(0,6))\n    duree=time.time()-debut\n    return duree\n#calculs et show\n\nx=[(i)*10**5 for i in range(5)]\ny=[duree_tableau_alea(val) for val in x]\ny1=[duree_tableau_alea1(val) for val in x]\ny2=[duree_tableau_alea2(val) for val in x]\nplt.show()<\/pre>\n\n\n
ici les resultats de la comparaison de tri:<\/p>\n\n\n
\"\"<\/figure>\n\n\n
L’ordinateur viens de tester 3 techniques de tri et a calcul\u00e9 leur temps d’execution. On peut voir que le tri s\u00e9lection, code que nous avons cod\u00e9 et celui d’insertion ont beaucoup plus de temps d’execution que le tri sort qui est fait par python. Plus, il n’augmente pas celon la grandeur des tableaux. Pour les grandes entreprises la methode sort est bien meilleure.<\/p>\n
Test avec des tableaux de 20<\/p>\n\n\n
\"\"<\/figure>\n\n\n\n
#j'ai seulement modifi\u00e9 cette partie\ndef duree_tris(n):\n    t1=list(np.random.randint(20,size=n))\n    t2=t1.copy()\n    t3=t1.copy() \n    debut=time.time()\n    tri_selection(t1)\n    duree_selection=time.time()-debut\n    debut=time.time()\n    tri_insertion(t2)\n    duree_insertion=time.time()-debut\n    debut=time.time()\n    t3.sort()\n    duree_sort=time.time()-debut\n    return duree_selection,duree_insertion,duree_sort\nx=[(i)*5**3 for i in range(20)]\ny=[duree_tris(val) for val in x]\ny1=[y[i][0] for i in range(20)]\ny2=[y[i][1] for i in range(20)]\ny3=[y[i][2] for i in range(20)]<\/pre>\n\n\n
On voit que on a obtiens une echelle plus petite et donc plus precise. Le tri sort est la methode la plus rapide.<\/p>","protected":false},"excerpt":{"rendered":"
duree  d’execution d’un programme nuage de points visualiser la duree de cr\u00e9ation d\u2019un tableau en fonction de sa longueur n ici les resultats de la comparaison de tri: L’ordinateur viens de tester 3 techniques de tri et a calcul\u00e9 leur temps d’execution. On peut voir que le tri s\u00e9lection, code que nous avons cod\u00e9 et… Poursuivre la lecture comprehension tri<\/span><\/a><\/p>\n","protected":false},"author":5,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[1],"tags":[],"_links":{"self":[{"href":"http:\/\/yb-isn.fr\/2021\/nsi\/carla\/index.php?rest_route=\/wp\/v2\/posts\/140"}],"collection":[{"href":"http:\/\/yb-isn.fr\/2021\/nsi\/carla\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/yb-isn.fr\/2021\/nsi\/carla\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/yb-isn.fr\/2021\/nsi\/carla\/index.php?rest_route=\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"http:\/\/yb-isn.fr\/2021\/nsi\/carla\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=140"}],"version-history":[{"count":7,"href":"http:\/\/yb-isn.fr\/2021\/nsi\/carla\/index.php?rest_route=\/wp\/v2\/posts\/140\/revisions"}],"predecessor-version":[{"id":152,"href":"http:\/\/yb-isn.fr\/2021\/nsi\/carla\/index.php?rest_route=\/wp\/v2\/posts\/140\/revisions\/152"}],"wp:attachment":[{"href":"http:\/\/yb-isn.fr\/2021\/nsi\/carla\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=140"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/yb-isn.fr\/2021\/nsi\/carla\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=140"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/yb-isn.fr\/2021\/nsi\/carla\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=140"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}