Simple least-squares curve fitting example
Here is a linear least squares curvefitting example for the distribution if you would like to use it. James Phillips http://zunzun.com import scipy.linalg.basic xdata = [5.357, 5.457, 5.797, 5.936, 6.161, 6.697, 6.731, 6.775, 8.442, 9.769, 9.861] ydata = [0.376, 0.489, 0.874, 1.049, 1.327, 2.054, 2.077, 2.138, 4.744, 7.068, 7.104] matrix = [] for x in xdata: matrix.append([1.0, x, x*x]) # for y = a + bx + cx^2 coeffs = scipy.linalg.basic.lstsq(matrix, ydata)[0] print "scipy.linalg.basic.lstsq curve fitting example" print "fitting data to quadratic equation y = a + bx + cx^2" print "yields: x data y data calc value error" for i in range(len(xdata)): ycalc = coeffs[0] + coeffs[1] * xdata[i] + coeffs[2] * xdata[i] * xdata[i] error = ycalc - ydata[i] print " % .3f % .3f % .3f % .3f" % (xdata[i], ydata[i], ycalc, error) print
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