<\/p>\n
Python’da kar\u015f\u0131la\u015fabilece\u011finiz bir hata:<\/span><\/p>\n Bu hata, tan\u0131m\u0131 gere\u011fi determinant\u0131 s\u0131f\u0131r olan ve ters \u00e7evrilemeyen bir matris olan tekil bir matrisi ters \u00e7evirmeye \u00e7al\u0131\u015ft\u0131\u011f\u0131n\u0131zda ortaya \u00e7\u0131kar.<\/span><\/p>\n Bu e\u011fitimde bu hatan\u0131n pratikte nas\u0131l \u00e7\u00f6z\u00fclece\u011fi a\u00e7\u0131klanmaktad\u0131r.<\/span><\/p>\n NumPy kullanarak a\u015fa\u011f\u0131daki matrisi olu\u015fturdu\u011fumuzu varsayal\u0131m:<\/span><\/p>\n \u015eimdi matrisin tersini hesaplamak i\u00e7in NumPy’nin inv()<\/strong> fonksiyonunu kullanmaya \u00e7al\u0131\u015ft\u0131\u011f\u0131m\u0131z\u0131 varsayal\u0131m:<\/span><\/p>\n Olu\u015fturdu\u011fumuz matrisin ters matrisi olmad\u0131\u011f\u0131 i\u00e7in hata al\u0131yoruz.<\/span><\/p>\n Not<\/strong> : Ters matrisi olmayan 10 farkl\u0131 matris \u00f6rne\u011fini g\u00f6steren Wolfram MathWorld’den bu sayfaya<\/a> g\u00f6z at\u0131n.<\/span><\/p>\n Tan\u0131m gere\u011fi bir matris tekildir ve s\u0131f\u0131r determinant\u0131na sahipse ters \u00e7evrilemez.<\/span><\/p>\n Belirli bir matrisi tersine \u00e7evirmeyi denemeden \u00f6nce, determinant\u0131n\u0131 hesaplamak i\u00e7in NumPy’nin det()<\/strong> i\u015flevini kullanabilirsiniz:<\/span><\/p>\n Matrisimizin determinant\u0131n\u0131n s\u0131f\u0131r olmas\u0131 neden hatayla kar\u015f\u0131la\u015ft\u0131\u011f\u0131m\u0131z\u0131 a\u00e7\u0131kl\u0131yor.<\/span><\/p>\n Bu hatay\u0131 a\u015fman\u0131n tek yolu tekil olmayan bir matris olu\u015fturmakt\u0131r.<\/span><\/p>\n \u00d6rne\u011fin, a\u015fa\u011f\u0131daki matrisi tersine \u00e7evirmek i\u00e7in inv()<\/strong> i\u015flevini kulland\u0131\u011f\u0131m\u0131z\u0131 varsayal\u0131m:<\/span><\/p>\n Matris tekil olmad\u0131\u011f\u0131 i\u00e7in matrisi ters \u00e7evirirken herhangi bir hata alm\u0131yoruz.<\/span><\/p>\n A\u015fa\u011f\u0131daki e\u011fitimlerde Python’daki di\u011fer yayg\u0131n hatalar\u0131n nas\u0131l d\u00fczeltilece\u011fi a\u00e7\u0131klanmaktad\u0131r:<\/span><\/p>\n Nas\u0131l d\u00fczeltilir: ‘numpy.float64’ nesnesi \u00e7a\u011fr\u0131labilir de\u011fil<\/a> Python’da kar\u015f\u0131la\u015fabilece\u011finiz bir hata: numpy.linalg.LinAlgError: Singular matrix Bu hata, tan\u0131m\u0131 gere\u011fi determinant\u0131 s\u0131f\u0131r olan ve ters \u00e7evrilemeyen bir matris olan tekil bir matrisi ters \u00e7evirmeye \u00e7al\u0131\u015ft\u0131\u011f\u0131n\u0131zda ortaya \u00e7\u0131kar. Bu e\u011fitimde bu hatan\u0131n pratikte nas\u0131l \u00e7\u00f6z\u00fclece\u011fi a\u00e7\u0131klanmaktad\u0131r. Hata nas\u0131l yeniden olu\u015fturulur? NumPy kullanarak a\u015fa\u011f\u0131daki matrisi olu\u015fturdu\u011fumuzu varsayal\u0131m: import numpy as np #create 2×2 matrix my_matrix = […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"class_list":["post-3027","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n numpy.linalg.LinAlgError: Singular matrix\n<\/strong><\/pre>\n
Hata nas\u0131l yeniden olu\u015fturulur?<\/strong><\/h3>\n
import<\/span> numpy as<\/span> np\n<\/span>\n#create 2x2 matrix\nmy_matrix = np. array<\/span> ([[1., 1.], [1., 1.]])\n<\/span>\n#display matrix\nprint<\/span> (my_matrix)\n\n[[1. 1.]\n [1. 1.]]<\/span><\/span><\/strong><\/span><\/pre>\n from<\/span> numpy import<\/span> inv<\/span>\n\n#attempt to invert matrix\ninv(my_matrix)\n\nnumpy.linalg.LinAlgError: Singular matrix<\/span><\/span><\/strong><\/span><\/pre>\n from<\/span> numpy import<\/span> det\n\n#calculate determinant of matrix\n<\/span>det(my_matrix)\n\n0.0\n<\/strong><\/span><\/pre>\n Hata nas\u0131l d\u00fczeltilir?<\/strong><\/h3>\n
import<\/span> numpy as<\/span> np\nfrom<\/span> numpy. linalg<\/span> import<\/span> inv, det\n\n#create 2x2 matrix that is not singular\n<\/span>my_matrix = np. array<\/span> ([[1., 7.], [4., 2.]])\n\n#display matrix\n<\/span>print<\/span> (my_matrix)\n\n[[1. 7.]\n [4. 2.]]\n\n#calculate determinant of matrix\n<\/span>print<\/span> (det(my_matrix))\n\n-25.9999999993\n\n#calculate inverse of matrix\n<\/span>print<\/span> (inv(my_matrix))\n\n[[-0.07692308 0.26923077]\n [0.15384615 -0.03846154]]\n<\/strong><\/span><\/pre>\n Ek kaynaklar<\/strong><\/span><\/h3>\n
Nas\u0131l d\u00fczeltilir: ‘numpy.ndarray’ nesnesi \u00e7a\u011fr\u0131labilir de\u011fil<\/a>
Nas\u0131l d\u00fczeltilir: ‘numpy.float64’ nesnesi bir tamsay\u0131 olarak yorumlanam\u0131yor<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"