February 26, 2017

Homework Help: Python Programming

Posted by Anonymous on Sunday, January 13, 2013 at 2:50am.

We have created a set of data values that sample a function y(x). The sample points are stored in two arrays: xVals and yVals. These represent measurements of a physical process that is subject to noise so that if a is the i'th entry of xVals (i.e. a = xVals[i]) then yVals[i] is an approximation of y(a).

Write a procedure called findOrder that finds the lowest order polynomial model that fits the data to an accuracy of 1.0e-1, as measured by the residual error. findOrder should return the array of coefficients provided by pylab.polyfit. Recall that pylab.polyfit takes as arguments an array of x values, an array of y values, a degree of polynomial fit, and an optional argument full, which, if True, will cause pylab.polyfit to return:

an array of coefficients
the residual of the fit
Three additional parameters that should not concern you.

You may assume that the modules pylab and numpy are already imported into the environment. You may use anything you wish from the numpy module, but only pylab.polyfit and pylab.array are available from the pylab module.

def findOrder(xVals, yVals, accuracy = 1.0e-1):
# Your Code Here

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