# Hello, Quadratic and power curve fitting

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Charitha Heshan on 18 Mar 2018
Commented: Charitha Heshan on 18 Mar 2018
pressure=[10 15 25 40 50 55];
flow=[94 116 147 183 215 220];
a = -0.0170 ; b = 3.8870 ; c = 59.0062 ;
p = 5 : 60 ;
f = 5 : 300 ;
f_par = a* p.^ 2 +b * p + c
alpha = 72.0144 ; beta = 2.7842 ;
f_exp = alpha * p.^beta;
plot (pressure,flow,'o',p,f_par,p,f_exp,'--')
legend ('eperimental data','parabolic fit','exponential fit')
xlabel ('pressure psi') , ylabel ('flow gpm'),grid
Could some one correct my code where Y axis (f = flow rate) would stop plotting at value 400. currently it plots to 7*10^6.
thank you very much

John D'Errico on 18 Mar 2018
Edited: John D'Errico on 18 Mar 2018
What do you expect? As you generated it, we see:
f_exp
f_exp =
Columns 1 through 13
6360.5 10567 16231 23540 32675 43815 57130 72791 90962 1.1181e+05 1.3549e+05 1.6215e+05 1.9197e+05
Columns 14 through 26
2.2509e+05 2.6165e+05 3.0182e+05 3.4573e+05 3.9354e+05 4.4539e+05 5.0142e+05 5.6178e+05 6.266e+05 6.9602e+05 7.7019e+05 8.4923e+05 9.333e+05
Columns 27 through 39
1.0225e+06 1.117e+06 1.2169e+06 1.3224e+06 1.4336e+06 1.5505e+06 1.6734e+06 1.8024e+06 1.9376e+06 2.0791e+06 2.2271e+06 2.3816e+06 2.5429e+06
Columns 40 through 52
2.7109e+06 2.886e+06 3.0681e+06 3.2574e+06 3.4541e+06 3.6582e+06 3.8698e+06 4.0892e+06 4.3163e+06 4.5514e+06 4.7946e+06 5.0459e+06 5.3055e+06
Columns 53 through 56
5.5735e+06 5.85e+06 6.1352e+06 6.4291e+06
The problem is NOT the plot. The problem is that somehow, you generated a garbage model.
ALWAYS look at what you got from a computation. Plotting garbage and expecting to magically see what you want to see is a good path to failure.
And since we have not been shown where those coefficients came from, how can we realistically help you?
Perhaps you wanted to do this:
mdl = fittype('power1')
mdl =
General model Power1:
mdl(a,b,x) = a*x^b
fittedmdl = fit(pressure',flow',mdl)
fittedmdl =
General model Power1:
fittedmdl(x) = a*x^b
Coefficients (with 95% confidence bounds):
a = 29.17 (23.95, 34.4)
b = 0.5049 (0.456, 0.5538)
f_exp = fittedmdl.a*p.^fittedmdl.b;
plot (pressure,flow,'o',p,f_par,p,f_exp,'--')
legend ('eperimental data','parabolic fit','exponential fit')
xlabel ('pressure psi') , ylabel ('flow gpm'),grid That presumes the Curve fitting TB.
Charitha Heshan on 18 Mar 2018
Thank you for your response ,
if true
% code
x=[10 15 25 40 50 55]; y=[94 116 147 183 215 220];
n = length (x) sx = sum(x) sy = sum(y) sx2 = sum(x.^2) sx3 = sum(x.^3) sx4 = sum(x.^4) sxy = sum(x.*y) sx2y= sum(x.*x.*y)
A = [ n sx sx2; sx sx2 sx3;sx2 sx3 sx4] b = [sy;sxy;sx2y]
w= A\b
a2 = w(3) a1 = w(2) a0 = w(1)
end
This is the model i used to find the coefficients a0 a1 a3 .
if true
% code
function [a1 , a0] = linearRegression (x,y)
x=[10 15 25 40 50 55]; y=[94 116 147 183 215 220];
n=length(x) sx= sum(x) sy= sum(y) sxx= sum(x.*x) sxy= sum(x.*y) den = n*sxx - sx^2 a1 = (n*sxy - sx*sy) /den a0 = (sxx*sy - sxy*sx) /den
l = zeros (n,1) for i = 1:n, l(i) = a1*x(i) + a0; plot (x,y,'o') hold on plot (x,l) end
end
the above model was used to obtain a linear equation y= n0x+n1 and converted it to a power function as follows = alpha = 72.0144 ; beta = 2.7842 ;
function = alpha * p.^beta;
so i'm suppose to plot both quadratic and power functions on the same graph .
the original plot model was provided to me by the professor, i honestly lack knowledge to come up with by my self.