{"id":685,"date":"2013-03-04T12:00:44","date_gmt":"2013-03-04T03:00:44","guid":{"rendered":"http:\/\/www.lookingatnothing.com\/?p=685"},"modified":"2013-06-23T18:05:47","modified_gmt":"2013-06-23T09:05:47","slug":"papers-one-of-mine-and-one-on-detector-data-read-in","status":"publish","type":"post","link":"https:\/\/lookingatnothing.com\/index.php\/archives\/685","title":{"rendered":"Papers! One of mine and one on detector data read-in"},"content":{"rendered":"<p>It has been a long time in the making, but now the day has finally come where the 1D Monte Carlo method has been published! To top it off, the publication is <a href=\"http:\/\/en.wikipedia.org\/wiki\/Open_access\">open access<\/a> (courtesy of my current institute: NIMS), and has a wicked showcase document as supplementary material. Feel (very) free to <a href=\"http:\/\/dx.doi.org\/10.1107\/S0021889813001295\">check it out here<\/a>!<!--more--><\/p>\n<p>In short: the MC method can retrieve form-free particle size distributions from isotropic scattering patterns, complete with uncertainties. There is more to it than that, but the details are in the paper. The <a href=\"http:\/\/www.python.org\">Python 2.7<\/a> code is available in a Git repository as indicated<a href=\"http:\/\/www.lookingatnothing.com\/?p=665\"> in this post<\/a>, available under a <a href=\"http:\/\/creativecommons.org\/licenses\/by-sa\/2.5\/\">creative commons attribution sharealike license<\/a>.<\/p>\n<p>In the same <a href=\"http:\/\/journals.iucr.org\/j\/issues\/2013\/02\/00\/issconts.html\">J. Appl. Cryst. edition<\/a> that my paper appears in, there is another paper which caught my interest. This is a <a href=\"http:\/\/dx.doi.org\/10.1107\/S0021889813000150\">paper by\u00a0E. B. Knudsen,\u00a0<em>et al.<\/em><\/a>, which presents a bunch of code under the name of <a href=\"http:\/\/sourceforge.net\/projects\/fable\/files\/fabio\/\">FabIO<\/a> that can be used in Python to read in detector images (under a <a href=\"http:\/\/www.gnu.org\/licenses\/gpl.html\">GPL license<\/a>). There is even some code there for the more obscure of image formats, with improvements to follow. For me, this is part of what I was looking for to augment my own procedures, so I really appreciate it when others make their stuff available with a suitable license!<\/p>\n<p>That FabIO package is part of\u00a0<a href=\"http:\/\/sourceforge.net\/projects\/fable\/\">larger<\/a>\u00a0<a href=\"https:\/\/github.com\/kif\/pyFAI\">programs<\/a> for XRD and data reduction, respectively. Given that this is a program which is sustained by the efforts of a variety of user-driven institutes (ESRF, for example), I am very much looking forward to see which direction it will be taken into. One of the authors has assured me that if there is a need and an example (say, for supporting an imageplate image format or some of the stranger wire-arrays), they are more than willing to implement that particular image format. Naturally, that open-source project is available for collaborative efforts as well!<\/p>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<div class=\"mh-excerpt\"><p>It has been a long time in the making, but now the day has finally come where the 1D Monte Carlo method has been published! <a class=\"mh-excerpt-more\" href=\"https:\/\/lookingatnothing.com\/index.php\/archives\/685\" title=\"Papers! One of mine and one on detector data read-in\">[&#8230;]<\/a><\/p>\n<\/div>","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"activitypub_content_warning":"","activitypub_content_visibility":"","activitypub_max_image_attachments":4,"activitypub_interaction_policy_quote":"anyone","activitypub_status":"","footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[62,1,52],"tags":[101,118,21,125],"class_list":["post-685","post","type-post","status-publish","format-standard","hentry","category-ann","category-uncategorized","category-lit","tag-data-analysis","tag-data-correction","tag-polydispersity","tag-publication"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/p1gZ2v-b3","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/lookingatnothing.com\/index.php\/wp-json\/wp\/v2\/posts\/685","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lookingatnothing.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lookingatnothing.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lookingatnothing.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/lookingatnothing.com\/index.php\/wp-json\/wp\/v2\/comments?post=685"}],"version-history":[{"count":7,"href":"https:\/\/lookingatnothing.com\/index.php\/wp-json\/wp\/v2\/posts\/685\/revisions"}],"predecessor-version":[{"id":794,"href":"https:\/\/lookingatnothing.com\/index.php\/wp-json\/wp\/v2\/posts\/685\/revisions\/794"}],"wp:attachment":[{"href":"https:\/\/lookingatnothing.com\/index.php\/wp-json\/wp\/v2\/media?parent=685"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lookingatnothing.com\/index.php\/wp-json\/wp\/v2\/categories?post=685"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lookingatnothing.com\/index.php\/wp-json\/wp\/v2\/tags?post=685"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}