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POExtending a series of nonuniform netcdf data in a numpy array
 

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  1. POExtending a series of nonuniform netcdf data in a numpy array
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    <p>I am new to python, apologies if this has been asked already.</p> <p>Using python and numpy, I am trying to gather data across many netcdf files into a single array by iteratively calling <code>append()</code>.</p> <p>Naively, I am trying to do something like this:</p> <pre><code>from numpy import * from pupynere import netcdf_file x = array([]) y = [...some list of files...] for file in y: ncfile = netcdf_file(file,'r') xFragment = ncfile.variables["varname"][:] ncfile.close() x = append(x, xFragment) </code></pre> <p>I know that under normal circumstances this is a bad idea, since it reallocates new memory on each <code>append()</code> call. But two things discourage preallocation of x:</p> <p>1) The files are not necessarily the same size along axis 0 (but should be the same size along subsequent axes), so I would need to read the array sizes from each file beforehand to precalculate the final size of x. </p> <p>However...</p> <p>2) From what I can tell, pupynere (and other netcdf modules) load the entire file into memory upon opening the file, rather than just a reference (such as many netcdf modules in other enviroments). So to preallocate, I'd have to open the files twice.</p> <p>There are many (>100) large (>1GB) files, so overallocating and reshaping is not practical, from what I can tell.</p> <p>My first question is whether I am missing some intelligent way to preallocate.</p> <p>My second question is more serious. The above snippet works for a single-dimension array. But if I try to load in a matrix, then initialisation becomes a problem. I can append a one-dimensional array to an empty array:</p> <pre><code>append( array([]), array([1, 2, 3]) ) </code></pre> <p>but I cannot append an empty array to a matrix:</p> <pre><code>append( array([]), array([ [1, 2], [3, 4] ]), axis=0) </code></pre> <p>Something like x.extend(xFragment) would work, I believe, but I don't think numpy arrays have this functionality. I could also avoid the initialisation problem by treating the first file as a special case, but I'd prefer to avoid that if there's a better way to do it.</p> <p>If anyone can offer help or a suggestion, or can identify a problem with my approach, then I'd be grateful. Thanks</p>
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