.. _td1acythoneditcorrectionrst: ================================================= 1A.soft - Calcul numérique et Cython - correction ================================================= .. only:: html **Links:** :download:`notebook `, :downloadlink:`html `, :download:`PDF `, :download:`python `, :downloadlink:`slides `, :githublink:`GitHub|_doc/notebooks/td1a_soft/td1a_cython_edit_correction.ipynb|*` .. code:: ipython3 from jyquickhelper import add_notebook_menu add_notebook_menu() .. contents:: :local: Exercice : python/C appliqué à une distance d’édition ----------------------------------------------------- On reprend la fonction donnée dans l’énoncé. .. code:: ipython3 def distance_edition(mot1, mot2): dist = { (-1,-1): 0 } for i,c in enumerate(mot1) : dist[i,-1] = dist[i-1,-1] + 1 dist[-1,i] = dist[-1,i-1] + 1 for j,d in enumerate(mot2) : opt = [ ] if (i-1,j) in dist : x = dist[i-1,j] + 1 opt.append(x) if (i,j-1) in dist : x = dist[i,j-1] + 1 opt.append(x) if (i-1,j-1) in dist : x = dist[i-1,j-1] + (1 if c != d else 0) opt.append(x) dist[i,j] = min(opt) return dist[len(mot1)-1,len(mot2)-1] %timeit distance_edition("idstzance","distances") .. parsed-literal:: 188 µs ± 28.6 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each) solution avec notebook ---------------------- Les préliminaires : .. code:: ipython3 %load_ext cython Puis : .. code:: cython %%cython --annotate cimport cython def cidistance_edition(str mot1, str mot2): cdef int dist [500][500] cdef int cost, c cdef int l1 = len(mot1) cdef int l2 = len(mot2) dist[0][0] = 0 for i in range(l1): dist[i+1][0] = dist[i][0] + 1 dist[0][i+1] = dist[0][i] + 1 for j in range(l2): cost = dist[i][j+1] + 1 c = dist[i+1][j] + 1 if c < cost : cost = c c = dist[i][j] if mot1[i] != mot2[j] : c += 1 if c < cost : cost = c dist[i+1][j+1] = cost cost = dist[l1][l2] return cost .. raw:: html Cython: _cython_magic_f072b3f10e4cb6a87b39cd12da494e91.pyx

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.. code:: ipython3 mot1, mot2 = "idstzance","distances" %timeit cidistance_edition(mot1, mot2) .. parsed-literal:: 16.9 µs ± 3.47 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each) solution sans notebook ---------------------- .. code:: ipython3 import sys from pyquickhelper.loghelper import run_cmd code = """ def cdistance_edition(str mot1, str mot2): cdef int dist [500][500] cdef int cost, c cdef int l1 = len(mot1) cdef int l2 = len(mot2) dist[0][0] = 0 for i in range(l1): dist[i+1][0] = dist[i][0] + 1 dist[0][i+1] = dist[0][i] + 1 for j in range(l2): cost = dist[i][j+1] + 1 c = dist[i+1][j] + 1 if c < cost : cost = c c = dist[i][j] if mot1[i] != mot2[j] : c += 1 if c < cost : cost = c dist[i+1][j+1] = cost cost = dist[l1][l2] return cost """ name = "cedit_distance" with open(name + ".pyx","w") as f : f.write(code) setup_code = """ from distutils.core import setup from Cython.Build import cythonize setup( ext_modules = cythonize("__NAME__.pyx", compiler_directives={'language_level' : "3"}) ) """.replace("__NAME__",name) with open("setup.py","w") as f: f.write(setup_code) cmd = "{0} setup.py build_ext --inplace".format(sys.executable) out,err = run_cmd(cmd) if err is not None and err != '': raise Exception(err) import pyximport pyximport.install() import cedit_distance from cedit_distance import cdistance_edition mot1, mot2 = "idstzance","distances" %timeit cdistance_edition(mot1, mot2) .. parsed-literal:: 11.4 µs ± 1.93 µs per loop (mean ± std. dev. of 7 runs, 100000 loops each) La version Cython est 10 fois plus rapide. Et cela ne semble pas dépendre de la dimension du problème. .. code:: ipython3 mot1 = mot1 * 10 mot2 = mot2 * 10 %timeit distance_edition(mot1,mot2) %timeit cdistance_edition(mot1, mot2) .. parsed-literal:: 11.5 ms ± 561 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) 724 µs ± 30 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)