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POBest way to write a Python function that integrates a gaussian?
 

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  1. POBest way to write a Python function that integrates a gaussian?
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    <p>In attempting to use scipy's quad method to integrate a gaussian (lets say there's a gaussian method named gauss), I was having problems passing needed parameters to gauss and leaving quad to do the integration over the correct variable. Does anyone have a good example of how to use quad w/ a multidimensional function?</p> <p>But this led me to a more grand question about the best way to integrate a gaussian in general. I didn't find a gaussian integrate in scipy (to my surprise). My plan was to write a simple gaussian function and pass it to quad (or maybe now a fixed width integrator). What would you do?</p> <p>Edit: Fixed-width meaning something like trapz that uses a fixed dx to calculate areas under a curve.</p> <p>What I've come to so far is a method make___gauss that returns a lambda function that can then go into quad. This way I can make a normal function with the average and variance I need before integrating.</p> <pre><code>def make_gauss(N, sigma, mu): return (lambda x: N/(sigma * (2*numpy.pi)**.5) * numpy.e ** (-(x-mu)**2/(2 * sigma**2))) quad(make_gauss(N=10, sigma=2, mu=0), -inf, inf) </code></pre> <p>When I tried passing a general gaussian function (that needs to be called with x, N, mu, and sigma) and filling in some of the values using quad like</p> <pre><code>quad(gen_gauss, -inf, inf, (10,2,0)) </code></pre> <p>the parameters 10, 2, and 0 did NOT necessarily match N=10, sigma=2, mu=0, which prompted the more extended definition.</p> <p>The erf(z) in scipy.special would require me to define exactly what t is initially, but it nice to know it is there.</p>
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    1. COA gaussian distribution of numbers or data. It looks like bump or "bell curve" if plotted.
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    2. COColloquially, gaussian is used as a noun to represent a gaussian curve or distribution (it's somewhat common in the Wikipedia entry for example). I suppose we should writing with capitalization too, but SO is quite a colloquial place, no?
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    3. COA gaussian is a gaussian is a gaussian, no matter what noun it's modifying. Quit with the stupid semantics arguments that add nothing.
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