I want to fit a function with integer parameters

Question

I want to fit a function with GNUPLOT that is like a Fourier expansion. I have 3 terms with many parameters that should be integer and real.

I don't know how to set some variables to fit as integer numbers

I have something like that, where n1,n2,n3 should be integer, and the other parameters real:

g(x)=(A1*(1+cos(n1*x-b1))+A2*(1+cos(n2*x-b2))+A3*(1+cos(n3*x-b3)))/2

fit g(x) file u ($1+4):(f($2,E_min)) via A1,A2,A3,b1,b2,b3,n1,n2,n3

Answer 1

Maybe this could be an oversimplification to your problem, but I hope to help you. Suppose you have a file like this:

# data.dat
  0.000    4.313
 10.417    4.868
 20.833    5.115
 31.250    4.858
 41.667    3.942
 52.083    3.213
 62.500    2.153
 72.917    1.403
 83.333    0.967
 93.750    1.130
104.167    1.439
114.583    2.175
125.000    2.699
135.417    3.319
145.833    3.448
156.250    3.319
166.667    2.884
177.083    2.352
187.500    1.933
197.917    1.530
208.333    1.611
218.750    2.046
229.167    2.375
239.583    2.826
250.000    3.213

You can perform a first fit to find parameters values and then write a file with such values within and pass it for a second fit command.

# Function
g(x) = (A1*(1+cos(n1*x-b1))+A2*(1+cos(n2*x-b2))+A3*(1+cos(n3*x-b3)))/2

# Initial values
A1 = 1.0; n1 = 1.0; b1 = 1.0
A2 = 1.5; n2 = 2.0; b2 = 2.0
A3 = 2.0; n3 = 3.0; b3 = 3.0

set fit prescale

# First fit command
fit g(x) "data.dat" u 1:2 via A1,A2,A3, b1,b2,b3, n1,n2,n3

The trick is round the values with you want.

# File to second fit command
set print "parameters.dat"
    print sprintf("A1 = %g", A1)
    print sprintf("A2 = %g", A2)
    print sprintf("A3 = %g", A3)
    print sprintf("b1 = %g", b1)
    print sprintf("b2 = %g", b2)
    print sprintf("b3 = %g", b3)
    print sprintf("n1 = %.0f # FIXED", n1)
    print sprintf("n2 = %.0f # FIXED", n2)
    print sprintf("n3 = %.0f # FIXED", n3)
unset print

The parameters.dat file look like this:

A1 = 1.15639
A2 = 1.61595
A3 = 2.45079
b1 = 46.054
b2 = 12.2914
b3 = 65.8431
n1 = 1 # FIXED
n2 = 2 # FIXED
n3 = 3 # FIXED

Now the second fit command and the final graph:

# Second fit command
fit g(x) "data.dat" u 1:2 via "parameters.dat"

plot "data.dat" u 1:2 w p ls -1 pt 7, g(x) w l lc "red" lw 2

Of course the parameters now are little bit different.

A1 = 0.901065
A2 = 1.59511 
A3 = 2.63525 
b1 = 29.8406 
b2 = 34.2084 
b3 = 60.7824  

The result:

I hope to help you.