Fourier Model

[xmnlab]

Hi,

I'm trying to apply a Fourier model fit on some data, but the result using Matlab curve fiitting toolbox is so different comparing that I have using pymodelfit.

this is the code using Matlab curve fitting:

function [fitresult, gof] = createFit2()

x = 1:200;
y2 = [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,9,9,10,10,10,10,15,15,15,18,18,18,18,20,20,20,20,20,22,22,22,22,22,22,22,21,21,12,15,16,22,22,23,23,23,20,21,15,15,14,13,11,11,17,17,15,14,14,18,19,19,19,13,9,16,16,16,16,16,14,14,14,6,6,12,11,11,9,9,9,9,3,3,3,3,3,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0];

[xData, yData] = prepareCurveData( x, y2 );

% Set up fittype and options.
ft = fittype( 'fourier2');
opts = fitoptions( ft );
opts.Display = 'Off';
opts.Lower = [-Inf -Inf -Inf -Inf -Inf -Inf];
opts.StartPoint = [0 0 0 0 0 1.82746553632962];
opts.Upper = [Inf Inf Inf Inf Inf Inf];
opts.Normalize = 'on';

% Fit model to data.
[fitresult, gof] = fit( xData, yData, ft, opts );

% Plot fit with data.
figure( 'Name', 'untitled fit 1' );
h = plot( fitresult, xData, yData );
legend( h, 'y2 vs. x', 'untitled fit 1', 'Location', 'NorthEast' );
% Label axes
xlabel( 'x' );
ylabel( 'y2' );
grid on

this is the code using python and pymodelfit:

import numpy as np
from pymodelfit import FourierModel
from matplotlib import pyplot as plt

x = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200])
y = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 9, 9, 9, 10, 10, 10, 10, 15, 15, 15, 18, 18, 18, 18, 20, 20, 20, 20, 20, 22, 22, 22, 22, 22, 22, 22, 21, 21, 12, 15, 16, 22, 22, 23, 23, 23, 20, 21, 15, 15, 14, 13, 11, 11, 17, 17, 15, 14, 14, 18, 19, 19, 19, 13, 9, 16, 16, 16, 16, 16, 14, 14, 14, 6, 6, 12, 11, 11, 9, 9, 9, 9, 3, 3, 3, 3, 3, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])

model = FourierModel(2)
model.fitData(x, y)
model.plot()
plt.show()

any idea?

thanks