YTHON/JUPYTER Journals given the connected fourier information : # Estimations of fourier information information = [ [-2.00, - 9.37], [-1.00, 10.00], [-1.14, 10.83], [-0.29, - 13.88], [0.00, - 18.00], [0.57, - 1.83], [1.00, 14.00], [1.43, 14.5], [2.00, 0.00], [2.29, - 1.38], [3.00, 28.00], [3.14, 35.64], [4.00, 37.88], [5.00, - 23.00], [4.86, - 17.52], [5.71, - 14.63], [6.00, - 1.00], [6.50, - 15.00], [6.57, - 1.73], [7.00, 12.00], [7.43, 5.97], [7.50, 2.00], [8.29, 22.78], [9.00, 1.00], [9.14, - 6.41], [10.0, - 9.37] Fit the information with the straight least-squares fit strategy utilizing Fourier premise capabilities. Utilize 15 sets of sines and cosines and make the plots/results beneath. x_vec = [ 1.591 - 0.4
PYTHON/JUPYTER Journals
given the connected fourier information :
# Estimations of fourier information
information = [
[-2.00, - 9.37], [-1.00, 10.00], [-1.14, 10.83], [-0.29, - 13.88],
[0.00, - 18.00], [0.57, - 1.83], [1.00, 14.00], [1.43, 14.5],
[2.00, 0.00], [2.29, - 1.38], [3.00, 28.00], [3.14, 35.64],
[4.00, 37.88], [5.00, - 23.00], [4.86, - 17.52], [5.71, - 14.63],
[6.00, - 1.00], [6.50, - 15.00], [6.57, - 1.73], [7.00, 12.00],
[7.43, 5.97], [7.50, 2.00], [8.29, 22.78], [9.00, 1.00],
[9.14, - 6.41], [10.0, - 9.37]
Fit the information with the straight least-squares fit strategy utilizing Fourier premise capabilities. Utilize 15 sets of sines and cosines and make the plots/results beneath.
x_vec = [ 1.591 - 0.42 5.684 - 5.112 - 2.257 0.36 4.546 - 7.626 0.341 - 4.391 1.092 1.878 4.286 7.783 - 3.427 - 4.608 1.763 - 0.957 - 1.751 3.441 2.857 - 2.624 2.96 0.911 - 2.538 2.782 - 1.943 - 8.819 1.635 2.123 2.123]
Local Relative Error (discarding y values < 0.1):
mean [%] = 17.08
std [%] = 89.43
max, min [%] = 450.00, -45.00
discarding |?| values < 0.1
Step by step
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