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POPython - efficient representation of pixels and associated values
 

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  1. POPython - efficient representation of pixels and associated values
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    <p>I'm using python to work with large-ish (approx 2000 x 2000) matrices, where each <code>I</code>, <code>J</code> point in the matrix represents a single pixel.</p> <p>The matrices themselves are sparse (ie a substantial portion of them will have zero values), but when they are updated they tend to be increment operations, to a large number of adjacent pixels in a rectangular 'block', rather than random pixels here or there (a property i do not currently use to my advantage..). Afraid a bit new to matrix arithmetic, but I've looked into a number of possible solutions, including the various flavours of <code>scipy</code> sparse matrices. So far co-ordinate (COO) matrices seem to be the most promising. So for instance where I want to increment one block shape, I'd have to do something along the lines of:</p> <pre><code>&gt;&gt;&gt; from scipy import sparse &gt;&gt;&gt; from numpy import array &gt;&gt;&gt; I = array([0,0,0,0]) &gt;&gt;&gt; J = array([0,1,2,3]) &gt;&gt;&gt; V = array([1,1,1,1]) &gt;&gt;&gt; incr_matrix = sparse.coo_matrix((V,(I,J)),shape=(100,100)) &gt;&gt;&gt; main_matrix += incr_matrix #where main_matrix was previously defined </code></pre> <p>In the future, i'd like to have a richer pixel value representation in anycase (tuples to represent RGB etc), something that numpy array doesnt support out of the box (or perhaps I need to use <a href="http://mail.scipy.org/pipermail/numpy-discussion/2009-April/041801.html" rel="nofollow">this</a>). </p> <p>Ultimately i'll have a number of these matrices that I would need to do simple arithmitic on, and i'd need the code to be as efficient as possible -- and distributable, so i'd need to be able to persist and exchange these objects in a small-ish representation without substantial penalties. I'm wondering if this is the right way to go, or should I be looking rolling my own structures using <code>dicts</code> etc?</p>
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    1. COI doubt that you could produce something better than scipy and numpy capabilities. But I am not enough skilled in them to be more affirmative. By the way, I dislike the use of the word 'vector'. On one hand, there is no built-in data structure named 'vector' in Python. On the other hand, a bidimensional table is unlikely to be called 'vector' in the mathematical sense. So, your entity is nor a Python object named 'vector', nor a mathematical structure called 'vector'
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    2. COthat is true - it should indeed say matrix instead of vector (?) :)
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    3. CO2000x2000 isn't very big at all. There's no need to use sparse arrays. You should get much better performance out of just using normal numpy arrays. And incidentally, numpy _very_ much supports "something like" RGB "vectors" for each pixel... It's just a 2000x2000x3 array! It works _very_ well, and it's _very_ efficient!
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