On Friday 23 February 2007 14:53:05 Zachary Pincus wrote: > Scipy's ndimage module has a function that takes a generic callback > and calls it with the values of each neighborhood (of a given size, > and optionally with a particular "mask" footprint) centered on each > array element. That function handles boundary conditions, etc nicely. > > Unfortunately, I'm not sure if it works with masked arrays, and I > think it hands a ravel'd set of pixels back to the callback function. > You could probably hack masking in there by passing it the mask > concatenated to the array, and then deal with the mask explicitly.
Without really thinking about it: The easiest would be to process the masked array in steps: * process the _data part of the maskedarray (or its filled version) with the function: that will be your new _data. * if the mask is not nomask, process the _mask part of the maskedarray to get a new _mask * Set to True any element of the new mask that contains a True value: in other terms, mask the values that have a masked neighbor. _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
