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I'm relatively new to scipy and I'm looking for a guidance. I have an unconstrained minimization problem of the form:

function

Where a and b are coefficients and x is a vector of unknowns (can be of different length). I'm wondering about how to solve this problem using python. I looked through the scipy reference guide but couldn't find the answer.

Thank you

Mad Physicist
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Alexander
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    Start by checking out the [tutorial](http://scipy.github.io/devdocs/tutorial/optimize.html) and not the API-reference. It's very easy (to implement *something*; it might not be the best) and those examples should be enough to get you going. – sascha Apr 10 '17 at 12:22
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    Could you show your attempts and where you got stuck? – Cleb Apr 10 '17 at 12:54

1 Answers1

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Let A be the sum of the a's and X that of the x's. Then you want to choose X to minimise

Sum{ i | square( A-X-b[i])}

The value of X that minimises this will be the mean (over i) of A-b[i], that is A - mean(b)

dmuir
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    This does not answer the question of how to apply Python to the problem. Just because the question is bad does not mean that your answer can be as well. – Mad Physicist Apr 12 '17 at 16:53