{"id":86205,"date":"2020-06-22T13:42:25","date_gmt":"2020-06-22T11:42:25","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/vypusk-scipy-1-5-0-biblioteki-dlya-nauchnyh-i-inzhenernyh-raschyotov"},"modified":"2020-06-22T13:42:25","modified_gmt":"2020-06-22T11:42:25","slug":"vypusk-scipy-1-5-0-biblioteki-dlya-nauchnyh-i-inzhenernyh-raschyotov","status":"publish","type":"post","link":"https:\/\/prohoster.info\/en\/blog\/news\/vypusk-scipy-1-5-0-biblioteki-dlya-nauchnyh-i-inzhenernyh-raschyotov","title":{"rendered":"Release of SciPy 1.5.0, a library for scientific and engineering calculations","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\/msg08972.html\">Took place<\/a><\/noindex> Release of the library for scientific, mathematical, and engineering calculations <noindex><a rel=\"nofollow\" href=\"https:\/\/www.scipy.org\/\">SciPy 1.5.0<\/a><\/noindex>SciPy provides a large collection of modules for tasks such as integral calculation, solving differential equations, image processing, statistical analysis, interpolation, applying Fourier transforms, optimizing functions, vector operations, signal processing, working with sparse matrices, etc. The project code <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/scipy\/scipy\">is distributed<\/a><\/noindex> is licensed under BSD and utilizes a high-performance implementation of multidimensional arrays from the project <noindex><a rel=\"nofollow\" href=\"http:\/\/www.numpy.org\/\">NumPy<\/a><\/noindex>.<\/p>\n<p>In SciPy 1.5, support for new subprograms from the linear algebra package was added to the scipy.linalg.lapack layer  <noindex><a rel=\"nofollow\" href=\"https:\/\/ru.wikipedia.org\/wiki\/LAPACK\">LAPACK<\/a><\/noindex>  (Linear Algebra PACKage). Improved use of 64-bit integer types in the linear algebra backends. For <noindex><a rel=\"nofollow\" href=\"https:\/\/ru.wikipedia.org\/wiki\/%D0%9A%D1%80%D0%B8%D1%82%D0%B5%D1%80%D0%B8%D0%B9_%D1%81%D0%BE%D0%B3%D0%BB%D0%B0%D1%81%D0%B8%D1%8F_%D0%9A%D0%BE%D0%BB%D0%BC%D0%BE%D0%B3%D0%BE%D1%80%D0%BE%D0%B2%D0%B0\">the Kolmogorov-Smirnov uniformity criterion<\/a><\/noindex> support for the addition of probability distributions has been implemented. Improvements have been made to the modules scipy.cluster, scipy.fft, scipy.io, scipy.linalg, scipy.optimize, scipy.signal, scipy.sparse, scipy.spatial, scipy.special, and scipy.stats.<\/p>\n<p>Dependency requirements have increased; now Python 3.6+ and NumPy 1.14.5 or PyPy3 6.0+ and NumPy 1.15.0 are required. <\/p>\n<p><noindex><a rel=\"nofollow\" name=\"link\"><\/a><\/noindex><\/p>\n<p>Source: <a \ncontent=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/www.opennet.ru\/opennews\/art.shtml?num=53210\">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 \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0438 \u0434\u043b\u044f \u043d\u0430\u0443\u0447\u043d\u044b\u0445, \u043c\u0430\u0442\u0435\u043c\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0445 \u0438 \u0438\u043d\u0436\u0435\u043d\u0435\u0440\u043d\u044b\u0445 \u0440\u0430\u0441\u0447\u0451\u0442\u043e\u0432 SciPy 1.5.0. SciPy \u043f\u0440\u0435\u0434\u043e\u0441\u0442\u0430\u0432\u043b\u044f\u0435\u0442 \u0431\u043e\u043b\u044c\u0448\u0443\u044e \u043a\u043e\u043b\u043b\u0435\u043a\u0446\u0438\u044e \u043c\u043e\u0434\u0443\u043b\u0435\u0439 \u0434\u043b\u044f \u0442\u0430\u043a\u0438\u0445 \u0437\u0430\u0434\u0430\u0447, \u043a\u0430\u043a \u0432\u044b\u0447\u0438\u0441\u043b\u0435\u043d\u0438\u0435 \u0438\u043d\u0442\u0435\u0433\u0440\u0430\u043b\u043e\u0432, \u0440\u0435\u0448\u0435\u043d\u0438\u0435 \u0434\u0438\u0444\u0444\u0435\u0440\u0435\u043d\u0446\u0438\u0430\u043b\u044c\u043d\u044b\u0445 \u0443\u0440\u0430\u0432\u043d\u0435\u043d\u0438\u0439, \u043e\u0431\u0440\u0430\u0431\u043e\u0442\u043a\u0430 \u0438\u0437\u043e\u0431\u0440\u0430\u0436\u0435\u043d\u0438\u0439, \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0439 \u0430\u043d\u0430\u043b\u0438\u0437, \u0438\u043d\u0442\u0435\u0440\u043f\u043e\u043b\u044f\u0446\u0438\u044f, \u043f\u0440\u0438\u043c\u0435\u043d\u0435\u043d\u0438\u0435 \u043f\u0440\u0435\u043e\u0431\u0440\u0430\u0437\u043e\u0432\u0430\u043d\u0438\u0439 \u0424\u0443\u0440\u044c\u0435, \u043f\u043e\u0438\u0441\u043a \u044d\u043a\u0441\u0442\u0440\u0435\u043c\u0443\u043c\u0430 \u0444\u0443\u043d\u043a\u0446\u0438\u0438, \u0432\u0435\u043a\u0442\u043e\u0440\u043d\u044b\u0435 \u043e\u043f\u0435\u0440\u0430\u0446\u0438\u0438, \u043f\u0440\u0435\u043e\u0431\u0440\u0430\u0437\u043e\u0432\u0430\u043d\u0438\u0435 \u0430\u043d\u0430\u043b\u043e\u0433\u043e\u0432\u044b\u0445 \u0441\u0438\u0433\u043d\u0430\u043b\u043e\u0432, \u0440\u0430\u0431\u043e\u0442\u0430 \u0441 \u0440\u0430\u0437\u0440\u0435\u0436\u0435\u043d\u043d\u044b\u043c\u0438 \u043c\u0430\u0442\u0440\u0438\u0446\u0430\u043c\u0438 \u0438 \u0442.\u0434. \u041a\u043e\u0434 \u043f\u0440\u043e\u0435\u043a\u0442\u0430 \u0440\u0430\u0441\u043f\u0440\u043e\u0441\u0442\u0440\u0430\u043d\u044f\u0435\u0442\u0441\u044f \u043f\u043e\u0434 \u043b\u0438\u0446\u0435\u043d\u0437\u0438\u0435\u0439 BSD \u0438 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u0435\u0442 [&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-86205","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 \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0438 \u0434\u043b\u044f \u043d\u0430\u0443\u0447\u043d\u044b\u0445, \u043c\u0430\u0442\u0435\u043c\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0445 \u0438 \u0438\u043d\u0436\u0435\u043d\u0435\u0440\u043d\u044b\u0445 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