On 9/13/11 1:01 PM, Christopher Jordan-Squire wrote:
Sorry, I cheated by reading the docs. :-)
me too...
""" numpy.resize(a, new_shape)
Return a new array with the specified shape.
If the new array is larger than the original array, then the new array is filled with repeated copies of a. Note that this behavior is different from a.resize(new_shape) which fills with zeros instead of repeated copies of a. """
see the: "this behavior is different from a.resize(new_shape)" so: a.resize(new_shape, refcheck=True) Change shape and size of array in-place. Parameters ---------- new_shape : tuple of ints, or `n` ints Shape of resized array. refcheck : bool, optional If False, reference count will not be checked. Default is True. Returns ------- None
The copying I meant was that numpy.resize will fill the resized array with repeated copies of the data. So np.empty followed by np.append avoids that.
numpy.ndarray.resize is a different method, and I'm pretty sure it should be as fast or faster that np.empty + np.append. It is often confusing that there is a numpy function and ndarray method with the same name and slightly different usage. -Chris -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/OR&R (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception Chris.Barker@noaa.gov