{"id":100591,"date":"2021-06-24T10:23:07","date_gmt":"2021-06-24T08:23:07","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/vypusk-python-biblioteki-dlya-nauchnyh-vychislenij-numpy-1-21-0"},"modified":"2021-06-24T10:23:07","modified_gmt":"2021-06-24T08:23:07","slug":"vypusk-python-biblioteki-dlya-nauchnyh-vychislenij-numpy-1-21-0","status":"publish","type":"post","link":"https:\/\/prohoster.info\/es\/blog\/news\/vypusk-python-biblioteki-dlya-nauchnyh-vychislenij-numpy-1-21-0","title":{"rendered":"Lanzamiento de la biblioteca Python para c\u00e1lculos cient\u00edficos NumPy 1.21.0.","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p>Est\u00e1 disponible la versi\u00f3n 1.21 de la biblioteca Python NumPy para c\u00e1lculos cient\u00edficos, enfocada en el trabajo con arreglos y matrices multidimensionales, y que ofrece una gran colecci\u00f3n de funciones para implementar diversos 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 se distribuye bajo la licencia BSD.      <\/p>\n<p>En la nueva versi\u00f3n:  <\/p>\n<ul>\n<li class=\"l\"> Se ha continuado el trabajo de optimizaci\u00f3n de funciones y plataformas utilizando instrucciones vectoriales SIMD.\n<li class=\"l\"> Se propone una implementaci\u00f3n inicial de una nueva infraestructura para la clase dtype y la conversi\u00f3n de tipos.\n<li class=\"l\"> Se han propuesto paquetes wheel universales (para arquitecturas x86_64 y arm64) de NumPy para Python 3.8 y Python 3.9 en la plataforma macOS.\n<li class=\"l\"> Se han mejorado las anotaciones en el c\u00f3digo.\n<li class=\"l\"> Se ha a\u00f1adido un nuevo generador de bits PCG64DXSM para n\u00fameros aleatorios.    <\/ul>\n<p>Fuente: <a content=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/www.opennet.ru\/opennews\/art.shtml?num=55381\">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 1.21, \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-100591","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 NumPy 1.21, \u043e\u0440\u0438\u0435\u043d\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u043e\u0439 \u043d\u0430 \u0440\u0430\u0431\u043e\u0442\u0443 \u0441 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