{"id":22964,"date":"2015-09-14T16:18:00","date_gmt":"2015-09-14T16:18:00","guid":{"rendered":"http:\/\/ahay.org\/blog\/?p=22964"},"modified":"2015-12-16T04:20:24","modified_gmt":"2015-12-16T04:20:24","slug":"program-of-the-month-sfsimilarity","status":"publish","type":"post","link":"https:\/\/ahay.org\/blog\/2015\/09\/14\/program-of-the-month-sfsimilarity\/","title":{"rendered":"Program of the month: sfsimilarity"},"content":{"rendered":"<p><a href=\"\/RSF\/sfsimilarity.html\">sfsimilarity<\/a> computes the <a href=\"\/RSF\/book\/tccs\/attr\/paper_html\/node7.html\">local similarity attribute<\/a> between two datasets. <\/p>\n<p>The following example from <a href=\"\/RSF\/book\/tccs\/ortho\/orthofair.html\">tccs\/ortho\/orthofair<\/a> shows two 2-D sections and their local similarity.<\/p>\n<p><img decoding=\"async\" src=\"\/RSF\/book\/tccs\/ortho\/orthofair\/Fig\/fairdeblended2fx2.png\" alt=\"\" title=\"\" \/> <img decoding=\"async\" src=\"\/RSF\/book\/tccs\/ortho\/orthofair\/Fig\/fairdeblended2dif-fx2.png\" alt=\"\" title=\"\" \/> <img decoding=\"async\" src=\"\/RSF\/book\/tccs\/ortho\/orthofair\/Fig\/fairdif-simi.png\" alt=\"\" title=\"\" \/><\/p>\n<p>The second dataset for computing the local similarity is specified by <strong>other=<\/strong>. The program performs iterations of <a href=\"\/RSF\/book\/tccs\/shape\/paper_html\/\">shaping regularization<\/a>. The main controling parameters are the number of iterations <strong>niter=<\/strong> and the smoothing radii in different dimensions <strong>rect1=<\/strong>, <strong>rect2=<\/strong>, etc. The iterations can be additionally accelerated using the <strong>eps=<\/strong> parameters. To suppress the output of iteration statistics on the screen, use <strong>verb=n<\/strong>.<\/p>\n<h3 id=\"10previousprogramsofthemonth\">10 previous programs of the month:<\/h3>\n<ul>\n<li><a href=\"\/blog\/2015\/07\/10\/program-of-the-month-sfmutter\/\">sfmutter<\/a><\/li>\n<li><a href=\"\/blog\/2015\/06\/10\/program-of-the-month-sfintbin\/\">sfintbin<\/a><\/li>\n<li><a href=\"\/blog\/2015\/05\/01\/program-of-the-month-sfbox\/\">sfbox<\/a><\/li>\n<li><a href=\"\/blog\/2015\/04\/21\/program-of-the-month-sfslant\/\">sfslant<\/a><\/li>\n<li><a href=\"\/blog\/2015\/03\/04\/program-of-the-month-sfgrey\/\">sfgrey<\/a><\/li>\n<li><a href=\"\/blog\/2015\/03\/01\/program-of-the-month-sfhistogram\/\">sfhistogram<\/a><\/li>\n<li><a href=\"\/blog\/2015\/01\/30\/program-of-the-month-sfmf\/\">sfmf<\/a><\/li>\n<li><a href=\"\/blog\/2014\/12\/01\/program-of-the-month-sfbin\/\">sfbin<\/a><\/li>\n<li><a href=\"\/blog\/2014\/11\/12\/program-of-the-month-sfthreshold\/\">sfthreshold<\/a><\/li>\n<li><a href=\"\/blog\/2014\/10\/08\/program-of-the-month-sfsigmoid\/\">sfsigmoid<\/a><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>sfsimilarity computes the local similarity attribute between two datasets. The following example from tccs\/ortho\/orthofair shows two 2-D sections and their local similarity. The second dataset for computing the local similarity is specified by other=. The program performs iterations of shaping regularization. The main controling parameters are the number of iterations niter= and the smoothing radii [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_import_markdown_pro_load_document_selector":0,"_import_markdown_pro_submit_text_textarea":"","activitypub_content_warning":"","activitypub_content_visibility":"local","activitypub_max_image_attachments":4,"activitypub_interaction_policy_quote":"","footnotes":""},"categories":[3],"tags":[],"class_list":["post-22964","post","type-post","status-publish","format-standard","hentry","category-programs"],"_links":{"self":[{"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/posts\/22964","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/comments?post=22964"}],"version-history":[{"count":8,"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/posts\/22964\/revisions"}],"predecessor-version":[{"id":41174,"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/posts\/22964\/revisions\/41174"}],"wp:attachment":[{"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/media?parent=22964"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/categories?post=22964"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/tags?post=22964"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}