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    <p>Based on the representation of your "array", it looks like you're working with a <code>numpy.ndarray</code>. This becomes quite a simple problem if that is the case -- You can transform to a 1-D iterable simple by using the <code>.flat</code> attribute. To make it unique, you can just use a <code>set</code>:</p> <pre><code>set(array.flat) </code></pre> <p>This will give you a set, but you could easily get a list from it:</p> <pre><code>list(set(array.flat)) </code></pre> <p>Here's how it works:</p> <pre><code>&gt;&gt;&gt; array = np.zeros((10,12,42,53)) &gt;&gt;&gt; list(set(array.flat)) [0.0] </code></pre> <p>As a side note, there's also <code>np.unique</code> which will give you the unique elements of your array as well.</p> <pre><code>&gt;&gt;&gt; array = np.zeros((10,12),dtype=int) &gt;&gt;&gt; print array [[0 0 0 0 0 0 0 0 0 0 0 0] [0 0 0 0 0 0 0 0 0 0 0 0] [0 0 0 0 0 0 0 0 0 0 0 0] [0 0 0 0 0 0 0 0 0 0 0 0] [0 0 0 0 0 0 0 0 0 0 0 0] [0 0 0 0 0 0 0 0 0 0 0 0] [0 0 0 0 0 0 0 0 0 0 0 0] [0 0 0 0 0 0 0 0 0 0 0 0] [0 0 0 0 0 0 0 0 0 0 0 0] [0 0 0 0 0 0 0 0 0 0 0 0]] &gt;&gt;&gt; np.unique(array) array([0]) &gt;&gt;&gt; array[0,5] = 1 &gt;&gt;&gt; array[4,10] = 42 &gt;&gt;&gt; np.unique(array) array([ 0, 1, 42]) </code></pre> <hr> <p>I think I finally got this one figured out:</p> <pre><code>from itertools import product items = set(tuple(a[itr+(slice(None),)]) for itr in product(*[range(x) for x in a.shape[:-1]])) print items </code></pre> <p>Seems to work. Phew!</p> <p>How this works -- the pieces that you want to keep as triplets are accessed as:</p> <pre><code>array[X,Y,:] </code></pre> <p>So, we just need to loop over all of the combinations of <code>X</code> and <code>Y</code>. That is exactly what <code>itertools.product</code> is good for. We can get the valid <code>X</code> and <code>Y</code> in an arbitrary number of dimensions:</p> <pre><code>[range(x) for x in array.shape[:-1]] </code></pre> <p>So we pass that to product:</p> <pre><code>indices_generator = product(*[range(x) for x in array.shape[:-1]]) </code></pre> <p>Now we have something that will generate the first to indices -- We just need to construct a tuple to pass to <code>__getitem__</code> that numpy will interpret as <code>(X,Y,:)</code> -- That's easy, we're already getting <code>(X,Y)</code> from indices_generator -- We just need to tack on an emtpy slice:</p> <pre><code>all_items = ( array[idx+(slice(None),)] for idx in indices_generator ) </code></pre> <p>Now we can loop over all_items looking for the unique ones with a set:</p> <pre><code>unique_items = set(tuple(item) for item in all_items) </code></pre> <p>Now turn this back into a list, or a numpy array or whatever you want for the purposes of passing it back to PHP.</p>
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    1. POHow to simplify array into only unique values in Python
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    1. POHow to simplify array into only unique values in Python
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    1. COthanks for your suggestion. It's close, but I forgot to mention that I need to maintain the inner sets [135, 121, 81]. These are R, G, B values and I'm tying to group sets that occur more than once.
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    2. CO@stwhite -- See update.
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    3. CO@stwhite: Are you actually using a 3D `numpy` array, as mgilson suspected? Or a `list` of `list`s of `list`s, as it sounds like from your question? Or something in between, like a `list` of 2D `np.array`s or something?
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