{"id":86096,"date":"2020-06-21T13:42:25","date_gmt":"2020-06-21T11:42:25","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/vypusk-python-biblioteki-dlya-nauchnyh-vychislenij-numpy-1-19"},"modified":"2020-06-21T13:42:25","modified_gmt":"2020-06-21T11:42:25","slug":"vypusk-python-biblioteki-dlya-nauchnyh-vychislenij-numpy-1-19","status":"publish","type":"post","link":"https:\/\/prohoster.info\/es\/blog\/news\/vypusk-python-biblioteki-dlya-nauchnyh-vychislenij-numpy-1-19","title":{"rendered":"Lanzamiento de la biblioteca de Python para c\u00e1lculos cient\u00edficos NumPy 1.19","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\/msg08971.html\">Disponible<\/a><\/noindex> lanzamiento de la biblioteca de Python para c\u00e1lculos cient\u00edficos <noindex><a rel=\"nofollow\" href=\"http:\/\/www.numpy.org\/\">NumPy 1.19<\/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>En NumPy 1.19 se ha terminado el soporte para Python 3.5 y se ha eliminado el c\u00f3digo para su funcionamiento con Python 2 (la capa numpy.compat se ha dejado). Las versiones admitidas son Python 3.6, 3.7 y 3.8. Se ha continuado el desarrollo del m\u00f3dulo <noindex><a rel=\"nofollow\" href=\"https:\/\/numpy.org\/devdocs\/reference\/random\/index.html\">numpy.random<\/a><\/noindex> para trabajar con muestras aleatorias. Se ha mejorado el soporte para paquetes wheel de NumPy en la arquitectura Aarch64 y al usar la implementaci\u00f3n de Python <noindex><a rel=\"nofollow\" href=\"https:\/\/www.opennet.ru\/opennews\/art.shtml?num=52089\">PyPy<\/a><\/noindex>. <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/numpy\/numpy\/releases\/tag\/v1.19.0\">Se ha ampliado<\/a><\/noindex> la funcionalidad numpy.frompyfunc, np.str_, numpy.copy, numpy.linalg.multi_dot, numpy.count_nonzero y numpy.array_equal. Se ha mejorado la detecci\u00f3n de las capacidades de la CPU, como el soporte AVX. Se ha a\u00f1adido una implementaci\u00f3n 5-7 veces m\u00e1s r\u00e1pida  <noindex><a rel=\"nofollow\" href=\"https:\/\/numpy.org\/doc\/stable\/reference\/generated\/numpy.exp.html\">np.exp<\/a><\/noindex> basada en AVX512, utilizada para entradas con el tipo np.float64.<\/p>\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=53203\">opennet.ru<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>\u0414\u043e\u0441\u0442\u0443\u043f\u0435\u043d \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 1.19, \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-86096","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=\"\u0414\u043e\u0441\u0442\u0443\u043f\u0435\u043d \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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