Hi Steve, This is also interest to us - although about 2 million data points is our maximum so far.
Here is a decimating filter module based on the Savtsky-Golay method. Brett McSweeney steve george <[EMAIL PROTECTED]> Sent by: [EMAIL PROTECTED] 31/05/2007 06:07 AM To Matplotlib Users <matplotlib-users@lists.sourceforge.net> cc Subject [Matplotlib-users] Handling LARGE data sets Hi, We are starting to require plotting large data sets. 600K samples is one second, and we have 20 sec runs This takes approx 5 min to draw the plots on screen. Then if you want to zoom, ... well go get a cup of coffee, ... not very productive. 1) Is MatPlotLib the right tool for large data sets, .. should I be looking at something else? 2) Given nothing else better, I'm looking for suggestions how to handle this size data. My initial thoughts, ... display a low res graph, then have some movable markers in the low res graph and the main graph would only show the contents between those markers. ( ala some sound editing programs ) This would mean I need to filter/decimate the data for the low res graph, .. and a quick search on the web didn't seem to turn up any python way of doing this, .. anyone know of any existing python tool set to do this, before I re-invent the wheel? Thanks for any input Steve ------------------------------------------------------------------------- This SF.net email is sponsored by DB2 Express Download DB2 Express C - the FREE version of DB2 express and take control of your XML. No limits. Just data. Click to get it now. http://sourceforge.net/powerbar/db2/ _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users ______________________________________________________________________ This email has been scanned by the MessageLabs Email Security System. For more information please visit http://www.messagelabs.com/email ______________________________________________________________________ UNITED GROUP This email message is the property of United Group. The information in this email is confidential and may be legally privileged. It is intended solely for the addressee. Access to this email by anyone else is unauthorised. If you are not the intended recipient, you may not disclose, copy or distribute this email, nor take or omit to take any action in reliance on it. United Group accepts no liability for any damage caused by this email or any attachments due to viruses, interference, interception, corruption or unauthorised access. If you have received this email in error, please notify United Group immediately by email to the sender's email address and delete this document.
SGfilter.py
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