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POHow to get data in a histogram bin
 

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  1. POHow to get data in a histogram bin
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    <p>I want to get a list of the data contained in a histogram bin. I am using numpy, and Matplotlib. I know how to traverse the data and check the bin edges. However, I want to do this for a 2D histogram and the code to do this is rather ugly. Does numpy have any constructs to make this easier?</p> <p>For the 1D case, I can use searchsorted(). But the logic is not that much better, and I don’t really want to do a binary search on each data point when I don’t have to.</p> <p>Most of the nasty logic is due to the bin boundary regions. All regions have boundaries like this: [left edge, right edge). Except the last bin, which has a region like this: [left edge, right edge]. </p> <p>Here is some sample code for the 1D case:</p> <pre><code>import numpy as np data = [0, 0.5, 1.5, 1.5, 1.5, 2.5, 2.5, 2.5, 3] hist, edges = np.histogram(data, bins=3) print 'data =', data print 'histogram =', hist print 'edges =', edges getbin = 2 #0, 1, or 2 print '---' print 'alg 1:' #for i in range(len(data)): for d in data: if d &gt;= edges[getbin]: if (getbin == len(edges)-2) or d &lt; edges[getbin+1]: print 'found:', d #end if #end if #end for print '---' print 'alg 2:' for d in data: val = np.searchsorted(edges, d, side='right')-1 if val == getbin or val == len(edges)-1: print 'found:', d #end if #end for </code></pre> <p>Here is some sample code for the 2D case:</p> <pre><code>import numpy as np xdata = [0, 1.5, 1.5, 2.5, 2.5, 2.5, \ 0.5, 0.5, 0.5, 0.5, 1.5, 1.5, 1.5, 1.5, 1.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, \ 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 1.5, 1.5, 1.5, 1.5, 1.5, 1.5, 1.5, 1.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 3] ydata = [0, 5,5, 5, 5, 5, \ 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, \ 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 30] xbins = 3 ybins = 3 hist2d, xedges, yedges = np.histogram2d(xdata, ydata, bins=(xbins, ybins)) print 'data2d =', zip(xdata, ydata) print 'hist2d =' print hist2d print 'xedges =', xedges print 'yedges =', yedges getbin2d = 5 #0 through 8 print 'find data in bin #', getbin2d xedge_i = getbin2d % xbins yedge_i = int(getbin2d / xbins) #IMPORTANT: this is xbins for x, y in zip(xdata, ydata): # x and y left edges if x &gt;= xedges[xedge_i] and y &gt;= yedges[yedge_i]: #x right edge if xedge_i == xbins-1 or x &lt; xedges[xedge_i + 1]: #y right edge if yedge_i == ybins-1 or y &lt; yedges[yedge_i + 1]: print 'found:', x, y #end if #end if #end if #end for </code></pre> <p>Is there a cleaner / more efficient way to do this? It seems like numpy would have something for this.</p>
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    1. COJust out of curiosity; why do you use comments like #end if in your code? "Every pixel counts" By doing that you are ignoring the purpose of indentation.
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    2. CO2 reasons. I am a C++ developer first, and a python developer second. Python's lack of braces irritates me to no end. When I have complicated code blocks with lots of varying indentation, I don't want to be counting whitespace. And I do most of my development in Emacs. By putting closing comments on code blocks, it lets me press TAB on every line and Emacs won't try to wrongly indent something.
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