{"title":"PySOFI:用于SOFI的开源Python包","authors":"Yuting Miao, S. Weiss, Xiyu Yi","doi":"10.1101/2021.10.16.464651","DOIUrl":null,"url":null,"abstract":"Super-resolution optical fluctuation imaging (SOFI) is a highly democratizable technique that provides optical super-resolution (SR) without requirement of sophisticated imaging instruments. An open source package for SOFI algorithm is needed to support not only the utilization of SOFI, but also the community adoption and participation for further development of SOFI. In this work, we developed PySOFI, an open source python package for SOFI analysis that offers the flexibility to inspect, test, modify, improve and extend the algorithm. We provide a complete documentation for the package and a collection of Jupyter Notebooks to demonstrate the usage of the package. We discuss the architecture of PySOFI, illustrate how to use each functional module, and demonstrate how to extend the PySOFI package with additional modules. We expect PySOFI to facilitate efficient adoption, testing, modification, dissemination and prototyping of new SOFI-relevant algorithms.","PeriodicalId":72402,"journal":{"name":"Biophysical reports","volume":"43 1","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2021-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"PySOFI: an open source Python package for SOFI\",\"authors\":\"Yuting Miao, S. Weiss, Xiyu Yi\",\"doi\":\"10.1101/2021.10.16.464651\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Super-resolution optical fluctuation imaging (SOFI) is a highly democratizable technique that provides optical super-resolution (SR) without requirement of sophisticated imaging instruments. An open source package for SOFI algorithm is needed to support not only the utilization of SOFI, but also the community adoption and participation for further development of SOFI. In this work, we developed PySOFI, an open source python package for SOFI analysis that offers the flexibility to inspect, test, modify, improve and extend the algorithm. We provide a complete documentation for the package and a collection of Jupyter Notebooks to demonstrate the usage of the package. We discuss the architecture of PySOFI, illustrate how to use each functional module, and demonstrate how to extend the PySOFI package with additional modules. We expect PySOFI to facilitate efficient adoption, testing, modification, dissemination and prototyping of new SOFI-relevant algorithms.\",\"PeriodicalId\":72402,\"journal\":{\"name\":\"Biophysical reports\",\"volume\":\"43 1\",\"pages\":\"\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2021-10-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biophysical reports\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1101/2021.10.16.464651\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BIOPHYSICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biophysical reports","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2021.10.16.464651","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOPHYSICS","Score":null,"Total":0}
Super-resolution optical fluctuation imaging (SOFI) is a highly democratizable technique that provides optical super-resolution (SR) without requirement of sophisticated imaging instruments. An open source package for SOFI algorithm is needed to support not only the utilization of SOFI, but also the community adoption and participation for further development of SOFI. In this work, we developed PySOFI, an open source python package for SOFI analysis that offers the flexibility to inspect, test, modify, improve and extend the algorithm. We provide a complete documentation for the package and a collection of Jupyter Notebooks to demonstrate the usage of the package. We discuss the architecture of PySOFI, illustrate how to use each functional module, and demonstrate how to extend the PySOFI package with additional modules. We expect PySOFI to facilitate efficient adoption, testing, modification, dissemination and prototyping of new SOFI-relevant algorithms.