{"id":574,"date":"2024-10-26T12:48:28","date_gmt":"2024-10-26T10:48:28","guid":{"rendered":"https:\/\/bdagroup.nl\/?p=574"},"modified":"2024-10-26T13:06:19","modified_gmt":"2024-10-26T11:06:19","slug":"synchronization-toolbox","status":"publish","type":"post","link":"https:\/\/bdagroup.nl\/?p=574","title":{"rendered":"Synchronization Toolbox"},"content":{"rendered":"\n

This Matlab program (name: warpGUI) synchronizes univariate and multivariate trajectories. There are two different algorithms that can be used. The first algorithm is named symmetric dynamic time warping (SDTW<\/strong>). The second
algorithm is called parametric time warping (PTW<\/strong>). Some
example data sets are automatically loaded in the main workspace of Matlab
when warpGUI is started. The following buttons can be clicked in warpGUI:<\/p>\n\n\n\n

\n
Load
Data<\/span><\/strong><\/div>\n<\/td>
\n
A window is opened that allows you to use a Matlab variable (from the main
Matlab memory space) as a reference and sample vector<\/span><\/div>\n<\/td><\/tr>
\n
Warp<\/span><\/strong><\/div>\n<\/td>
\n
The actual
warping action is performed<\/span><\/div>\n<\/td><\/tr>
\n
Print<\/span><\/strong><\/div>\n<\/td>
\n
Prints
the warping window, including the figures and the settings that are used
for synchronization<\/span><\/div>\n<\/td><\/tr>
\n
SDTW<\/span><\/strong><\/div>\n<\/td>
\n
When this
radio button is selected, the SDTW algorithm is used for synchronization<\/span><\/div>\n<\/td><\/tr>
\n
PTW<\/span><\/strong><\/div>\n<\/td>
\n
When this
radio button is selected, the PTW algorithm is used for synchronization<\/span><\/div>\n<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

When the SDTW option is selected, the following options are avaialable:<\/p>\n\n\n\n

\n
Global
Constraints<\/span><\/strong><\/div>\n<\/td>
\n
Constraints
exclude certain regions from the search area for the best warping path.
These constraints are calculated by the routine and drawn in the plot
(upper right) showing the warping path<\/span><\/div>\n<\/td><\/tr>
\n
Normalize<\/span><\/strong><\/div>\n<\/td>
\n
The SDTW
algorithm is normalized<\/span><\/div>\n<\/td><\/tr>
\n
Direction
Penalties<\/span><\/strong><\/div>\n<\/td>
\n
The direction
penalties implemented make the incorperation of horizontal and vertical
steps in the warping path less favorable. Increasing the size of the penalty
value makes the penalty more severe. The software returns a sensible quess
for this value when the data is loaded for the first time<\/span><\/div>\n<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

Processing
your own data is possible by first loading your own data in the Matlab
main window, then pressing the “load data” button and selecting
the variables that contains your data. This program is tested for Matlab
v6.1 and v6.5. Note that version 6.5 of Matlab requires windows-XP.<\/p>\n\n\n\n

This program was made by Hans Boelens (Process and Analysis group, University of Amsterdam<\/a>), Henk-Jan Ramaker (TIPb<\/a>) and Paul eilers (Department
of Medial Statistics, University of Leiden<\/a>). For questions about SDTW,
comments or source code, please contact Hans Boelens<\/a> (Hans.Boelens@science.uva.nl) )or Henk-Jan Ramaker<\/a> (HJ.Ramaker@tipb.nl). Questions regarding PTW are best answered by Paul Eilers<\/a> (P.Eilers@lumc.nl).<\/p>\n\n\n\n

References<\/em><\/strong><\/p>\n\n\n\n

Henk-Jan Ramaker,
Eric van Sprang, Johan Westerhuis, Hans Boelens and Age Smilde, DYNAMIC
TIME WARPING OF SPECTROSCOPIC DATA, accepted (2003), Analytica Chimica
Acta.<\/em><\/p>\n\n\n\n

warpgui_v2_1lic<\/a>Download<\/a><\/div>\n","protected":false},"excerpt":{"rendered":"

This Matlab program (name: warpGUI) synchronizes univariate and multivariate trajectories. There are two different algorithms that can be used. The first algorithm is named symmetric dynamic time warping (SDTW). The secondalgorithm is called parametric time warping (PTW). Someexample data sets are automatically loaded in the main workspace of Matlabwhen warpGUI is started. The following buttons […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"cybocfi_hide_featured_image":"","footnotes":""},"categories":[18],"tags":[22,21],"class_list":["post-574","post","type-post","status-publish","format-standard","hentry","category-resource","tag-gui","tag-matlab"],"_links":{"self":[{"href":"https:\/\/bdagroup.nl\/index.php?rest_route=\/wp\/v2\/posts\/574","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/bdagroup.nl\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/bdagroup.nl\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/bdagroup.nl\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/bdagroup.nl\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=574"}],"version-history":[{"count":5,"href":"https:\/\/bdagroup.nl\/index.php?rest_route=\/wp\/v2\/posts\/574\/revisions"}],"predecessor-version":[{"id":582,"href":"https:\/\/bdagroup.nl\/index.php?rest_route=\/wp\/v2\/posts\/574\/revisions\/582"}],"wp:attachment":[{"href":"https:\/\/bdagroup.nl\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=574"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/bdagroup.nl\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=574"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/bdagroup.nl\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=574"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}