Hello list, I am not sure, if I understood everything of the discussion on the named-axis-idea of numpy-arrays, since I am only a *user* of numpy. I never subclassed the numpy-array-class ;-)
However, I have the need to store meta-information for my arrays. I do this with a stand-alone class with the name 'Wave' that stores its data in a n-dimensional numpy-array as a member. The meta-information I store (using dicts and lists) is * coordinateLabel per axis * x0 per axis * dx per axis This concept is taken from the data structures in the commercial software IGOR, that are also called 'Waves'. An example would be an image I took with a microscope. The data would be 2d, say shape = (640, 480) holding the intesity information per pixel. x0 could then be [-1e-6, -2e-6] and dx [100e-9, 100e-9] meaning that the image's pixel index [0,0] corresponds to a position of -1micrometer/-2micrometer and the pixels have a spacing of 100nanometers. coordinateLabels would be ['x(m)', 'y(m)']. If I have a movie, the data would be 3d with x0 = [-1e-6, -2e-6, 0], dx = [100e-9, 100e-9, 100e-3] and coordinateLabels = ['x(m)', 'y(m)', 't(s)'] for a frame rate of 10 fps. What I would like to say with this is the following (as a user...) : * Meta-information is often necessary * A string-label per axis is often not enough. Scaling is also important * I like the idea of a most-basic-as-possible numpy-array. In my opinion, the meta-data-management should be done by another (sub-?) class. This way, numpy-arrays are simple enough for new users (as I was roughly two years ago...). I would be very interested in a class that *uses* numpy-arrays to provide a datastructure for physical data with coordinate labels and scaling. Regards, Lars Friedrich -- Dipl.-Ing. Lars Friedrich Bio- and Nano-Photonics Department of Microsystems Engineering -- IMTEK University of Freiburg Georges-Köhler-Allee 102 D-79110 Freiburg Germany phone: +49-761-203-7531 fax: +49-761-203-7537 room: 01 088 email: [email protected] _______________________________________________ Numpy-discussion mailing list [email protected] http://projects.scipy.org/mailman/listinfo/numpy-discussion
