{"id":36622,"date":"2019-10-31T22:12:44","date_gmt":"2019-10-31T19:12:44","guid":{"rendered":"https:\/\/prohoster.info\/blog\/vypusk-python-biblioteki-dlya-nauchnyh-vychislenij-numpy-1-17-0\/"},"modified":"2019-10-31T22:12:44","modified_gmt":"2019-10-31T19:12:44","slug":"vypusk-python-biblioteki-dlya-nauchnyh-vychislenij-numpy-1-17-0","status":"publish","type":"post","link":"https:\/\/prohoster.info\/es\/blog\/news\/vypusk-python-biblioteki-dlya-nauchnyh-vychislenij-numpy-1-17-0","title":{"rendered":"Lanzamiento de la biblioteca Python para c\u00e1lculos cient\u00edficos NumPy 1.17.0","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p><noindex><a rel=\"nofollow\" href=\"https:\/\/www.mail-archive.com\/python-announce-list@python.org\/msg08700.html\">Se realiz\u00f3<\/a><\/noindex> lanzamiento de la biblioteca de Python para c\u00e1lculos cient\u00edficos <noindex><a rel=\"nofollow\" href=\"http:\/\/www.numpy.org\/\">NumPy 1.17<\/a><\/noindex>, orientada a trabajar con arreglos y matrices multidimensionales, proporcionando tambi\u00e9n una gran colecci\u00f3n de funciones con la implementaci\u00f3n de varios algoritmos relacionados con el uso de matrices. NumPy es una de las bibliotecas m\u00e1s solicitadas para c\u00e1lculos cient\u00edficos. El c\u00f3digo del proyecto est\u00e1 escrito en Python con optimizaciones en C y <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/numpy\/numpy\/\">se distribuye<\/a><\/noindex> bajo licencia BSD.<\/p>\n<p>lanzamiento de NumPy 1.17 <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/numpy\/numpy\/blob\/master\/doc\/release\/1.17.0-notes.rst\">se destaca<\/a><\/noindex> con la incorporaci\u00f3n de optimizaciones que mejoran significativamente el rendimiento de ciertas operaciones, y el cese del soporte para Python 2.7. Ahora se requiere tener Python 3.5-3.7. Entre otros cambios:<\/p>\n<ul>\n<li class=\"l\">  La implementaci\u00f3n del m\u00f3dulo FFT (Transformadas R\u00e1pidas de Fourier) para llevar a cabo la transformada r\u00e1pida de Fourier ha sido trasladada de fftpack a un m\u00f3dulo m\u00e1s r\u00e1pido y preciso <noindex><a rel=\"nofollow\" href=\"https:\/\/gitlab.mpcdf.mpg.de\/mtr\/pocketfft\">pocketfft<\/a><\/noindex>.\n<li class=\"l\"> Se ha incluido un nuevo m\u00f3dulo extensible<br \/>\nrandom, que ofrece cuatro generadores de n\u00fameros seudoaleatorios (MT19937, PCG64, Philox y SFC64) y que implementa un m\u00e9todo mejorado para formar entrop\u00eda en condiciones de uso en procesos que se ejecutan en paralelo.  <\/p>\n<li class=\"l\"> Se han a\u00f1adido algoritmos de ordenaci\u00f3n por distribuci\u00f3n (radix) y ordenaci\u00f3n h\u00edbrida (<noindex><a rel=\"nofollow\" href=\"https:\/\/ru.wikipedia.org\/wiki\/Timsort\">timsort<\/a><\/noindex>) que se seleccionan autom\u00e1ticamente en funci\u00f3n del tipo de datos.\n<li class=\"l\"> Por defecto, se ha incluido la posibilidad de redefinir funciones de NumPy.\n<\/ul>\n<p><noindex><a rel=\"nofollow\" name=\"link\"><\/a><\/noindex><\/p>\n<p>Fuente: <a \ncontent=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/www.opennet.ru\/opennews\/art.shtml?num=51186\">opennet.ru<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>\u0421\u043e\u0441\u0442\u043e\u044f\u043b\u0441\u044f \u0440\u0435\u043b\u0438\u0437 Python-\u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0438 \u0434\u043b\u044f \u043d\u0430\u0443\u0447\u043d\u044b\u0445 \u0432\u044b\u0447\u0438\u0441\u043b\u0435\u043d\u0438\u0439 NumPy 1.17, \u043e\u0440\u0438\u0435\u043d\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u043e\u0439 \u043d\u0430 \u0440\u0430\u0431\u043e\u0442\u0443 \u0441 \u043c\u043d\u043e\u0433\u043e\u043c\u0435\u0440\u043d\u044b\u043c\u0438 \u043c\u0430\u0441\u0441\u0438\u0432\u0430\u043c\u0438 \u0438 \u043c\u0430\u0442\u0440\u0438\u0446\u0430\u043c\u0438, \u0430 \u0442\u0430\u043a\u0436\u0435 \u043f\u0440\u0435\u0434\u043e\u0441\u0442\u0430\u0432\u043b\u044f\u044e\u0449\u0435\u0439 \u0431\u043e\u043b\u044c\u0448\u0443\u044e \u043a\u043e\u043b\u043b\u0435\u043a\u0446\u0438\u044e \u0444\u0443\u043d\u043a\u0446\u0438\u0439 \u0441 \u0440\u0435\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u0435\u0439 \u0440\u0430\u0437\u043b\u0438\u0447\u043d\u044b\u0445 \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c\u043e\u0432, \u0441\u0432\u044f\u0437\u0430\u043d\u043d\u044b\u0445 \u0441 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435\u043c \u043c\u0430\u0442\u0440\u0438\u0446. NumPy \u044f\u0432\u043b\u044f\u0435\u0442\u0441\u044f \u043e\u0434\u043d\u043e\u0439 \u0438\u0437 \u043d\u0430\u0438\u0431\u043e\u043b\u0435\u0435 \u0432\u043e\u0441\u0442\u0440\u0435\u0431\u043e\u0432\u0430\u043d\u043d\u044b\u0445 \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a, \u043f\u0440\u0438\u043c\u0435\u043d\u044f\u0435\u043c\u044b\u0445 \u0434\u043b\u044f \u043d\u0430\u0443\u0447\u043d\u044b\u0445 \u0440\u0430\u0441\u0447\u0451\u0442\u043e\u0432. \u041a\u043e\u0434 \u043f\u0440\u043e\u0435\u043a\u0442\u0430 \u043d\u0430\u043f\u0438\u0441\u0430\u043d \u043d\u0430 \u044f\u0437\u044b\u043a\u0435 Python \u0441 \u043f\u0440\u0438\u043c\u0435\u043d\u0435\u043d\u0438\u0435\u043c \u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0446\u0438\u0439 \u043d\u0430 \u044f\u0437\u044b\u043a\u0435 \u0421\u0438 \u0438 \u0440\u0430\u0441\u043f\u0440\u043e\u0441\u0442\u0440\u0430\u043d\u044f\u0435\u0442\u0441\u044f [&hellip;]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[702],"tags":[],"class_list":["post-36622","post","type-post","status-publish","format-standard","hentry","category-news"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.2 - aioseo.com -->\n\t<meta name=\"description\" content=\"\u0421\u043e\u0441\u0442\u043e\u044f\u043b\u0441\u044f \u0440\u0435\u043b\u0438\u0437 Python-\u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0438 \u0434\u043b\u044f \u043d\u0430\u0443\u0447\u043d\u044b\u0445 \u0432\u044b\u0447\u0438\u0441\u043b\u0435\u043d\u0438\u0439\" \/>\n\t<meta name=\"robots\" content=\"max-image-preview:large\" \/>\n\t<meta name=\"author\" content=\"Yuri Gagarin\"\/>\n\t<link rel=\"canonical\" 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