On Feb 20, 2012, at 6:15 PM, Ümit Seren wrote: > I guess using the slice operator on the table should probably also > load the entire table into memory: > > a = f.root.path.to.table[:]
Much, much better :) > This will return a structured array tough. Yes, but nothing that cannot be solved: a = f.root.path.to.table[:].view(np.float32).reshape(-1, 4) Quick explanation: * Operator [:] reads out all the table and creates and structured array * Method `view(np.float32)` makes the data look like homogeneous float array * Method `reshape(-1, 4)` returns an homogeneous array with 4 columns. This does not require an additional data copy to obtain the homogeneous array. -- Francesc Alted ------------------------------------------------------------------------------ Try before you buy = See our experts in action! The most comprehensive online learning library for Microsoft developers is just $99.99! Visual Studio, SharePoint, SQL - plus HTML5, CSS3, MVC3, Metro Style Apps, more. Free future releases when you subscribe now! http://p.sf.net/sfu/learndevnow-dev2 _______________________________________________ Pytables-users mailing list Pytables-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/pytables-users
