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Okay, my first reply is to myself, with all the bits I forgot to add. Angus McMorland wrote:
[snip] import numpy as n import scipy.interpolate def nvals(n, dims): '''Returns xvals-like volumes, indexing over any dimension n. Will probably crash and burn if n >= len(dims).''' evList = '' for i in range( len(dims) - 1): if i < n: evList = evList + '%d' % dims[i] else: evList = evList + '%d' % dims[i + 1] if i < len(dims) - 2: evList = evList + ', ' evList = 'xvals( (%d,' % dims[n] + evList + ')' + ')' xs = eval( evList ) evList = '' for i in range( len(dims) ): if i < n: ind = i + 1 elif i == n: ind = 0 else: ind = i evList = evList + '%d' % ind if i < len(dims) - 1: evList = evList + ', ' evList = 'xs.transpose(' + evList + ')' return eval( evList )
def congrid(a, nud, method='neighbour', centre=False, minusone=False): '''Arbitrary resampling of source array to new dimension sizes.
[snip] Also the docstring should have something about the first couple of params: Usage: arg0: input array arg1: tuple of resulting dimensions Example: rebinned = rebin.congrid( raw, (2,2,2), \ method=[neighbour|linear|cubic|spline], \ minusone=[True|False], \ centre=[True|False]) Let's try again. -- Angus McMorland email a.mcmorland@auckland.ac.nz mobile +64-21-155-4906 PhD Student, Neurophysiology / Multiphoton & Confocal Imaging Physiology, University of Auckland phone +64-9-3737-599 x89707 Armourer, Auckland University Fencing Secretary, Fencing North Inc.