{"id":103205,"date":"2022-02-06T15:36:40","date_gmt":"2022-02-06T13:36:40","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/vypusk-scipy-1-8-0-biblioteki-dlya-nauchnyh-i-inzhenernyh-raschyotov"},"modified":"2022-02-06T15:36:40","modified_gmt":"2022-02-06T13:36:40","slug":"vypusk-scipy-1-8-0-biblioteki-dlya-nauchnyh-i-inzhenernyh-raschyotov","status":"publish","type":"post","link":"https:\/\/prohoster.info\/pt\/blog\/news\/vypusk-scipy-1-8-0-biblioteki-dlya-nauchnyh-i-inzhenernyh-raschyotov","title":{"rendered":"Lan\u00e7amento do SciPy 1.8.0, uma biblioteca para c\u00e1lculos cient\u00edficos e de engenharia.","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Foi lan\u00e7ado a biblioteca para c\u00e1lculos cient\u00edficos, matem\u00e1ticos e de engenharia SciPy 1.8.0. SciPy oferece uma grande cole\u00e7\u00e3o de m\u00f3dulos para tarefas como c\u00e1lculo de integrais, solu\u00e7\u00e3o de equa\u00e7\u00f5es diferenciais, processamento de imagens, an\u00e1lise estat\u00edstica, interpola\u00e7\u00e3o, aplica\u00e7\u00e3o de transforma\u00e7\u00f5es de Fourier, busca de extremos de fun\u00e7\u00e3o, opera\u00e7\u00f5es vetoriais, convers\u00e3o de sinais anal\u00f3gicos, manipula\u00e7\u00e3o de matrizes esparsas, etc. O c\u00f3digo do projeto \u00e9 distribu\u00eddo sob a licen\u00e7a BSD e utiliza a implementa\u00e7\u00e3o de alto desempenho de arrays multidimensionais do projeto NumPy. <\/p>\n

Na nova vers\u00e3o do SciPy, foi proposta uma implementa\u00e7\u00e3o inicial da API para trabalhar com matrizes esparsas, onde a maioria dos elementos \u00e9 igual a zero. Para realizar c\u00e1lculos com grandes conjuntos de dados esparsos, foi inclu\u00edda a biblioteca SVD PROPACK, cujas fun\u00e7\u00f5es est\u00e3o dispon\u00edveis atrav\u00e9s do subm\u00f3dulo 'scipy.sparse.svds' quando o par\u00e2metro 'solver=PROPACK' \u00e9 definido. Um novo subm\u00f3dulo 'scipy.stats.sampling' foi adicionado, fornecendo uma interface para a biblioteca C UNU.RAN, destinada \u00e0 amostragem de distribui\u00e7\u00f5es cont\u00ednuas e discretas homog\u00eaneas e n\u00e3o homog\u00eaneas unidimensionais. Todos os espa\u00e7os de nomes privados, nos quais o s\u00edmbolo de sublinhado n\u00e3o \u00e9 utilizado, foram declarados obsoletos.
\n
Fonte: opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

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