This might help you I am not familiar with the Matlab engine, but looking at the error, the first thing you need to correct is to give it floats and not interested, since this is what it is complaining about: eng.hub(1.0, 0.0, 0.0, 184602.030,(75.2)**4)). Notice the decimal points in the first three arguments. code :
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Solving polynomial equations in Python
By : Dominiquedk
Date : March 29 2020, 07:55 AM

C++ solving for quartic roots (fourth order polynomial)
By : john
Date : March 29 2020, 07:55 AM
I wish this helpful for you Probably the most efficient way to solve this equation in closed form for real roots is to solve it in closed form for all roots and then discard the roots which are imaginary. You might think you could use try/catch pairs to determine if imaginary numbers are cropping up, but this isn't a very good strategy because some of the intermediate values you generate in calculating a real root may be imaginary.

Solving polynomial 3rd order polynomial equation for intensity mapping
By : raid3r
Date : March 29 2020, 07:55 AM
like below fixes the issue Not sure if this is what you need, but try this simple approach, which uses the [10,10) values range for x,y and z: code :
class Program
{
static void Main(string[] args)
{
int x = 0, y = 0, z = 0;
int x1 = 10, x2 = 10,
y1 = 10, y2 = 10,
z1 = 10, z2 = 10;
for (int ix = x1; ix < x2; ix++)
{
for (int iy = y1; iy < y2; iy++)
{
for (int iz = z1; iz < z2; iz++)
{
var result = (2 * ix) + (5 * iy) + 6 * (Math.Pow(iz, 2));
if (result > 0)
{
Console.WriteLine("x {0} y {1} z {2} : {3}",
ix, iy, iz, result);
}
}
}
}
}
}

Generic function for solving norder polynomial roots in Julia
By : S M Abdullah
Date : March 29 2020, 07:55 AM
like below fixes the issue The package PolynomialRoots.jl provides the function roots() to find all (real and complex) roots of polynomials of any order. The only mandatory argument is the array with coefficients of the polynomial in ascending order. For example, in order to find the roots of code :
6x^5 + 5x^4 + 3x^2 + 2x + 1
julia> roots([1, 2, 3, 4, 5, 6])
5element Array{Complex{Float64},1}:
0.2941950.668367im
0.670332+2.77556e17im
0.294195+0.668367im
0.3756950.570175im
0.375695+0.570175im
julia> r = roots([94906268.375, 189812534, 94906265.625]);
julia> (r[1], r[2])
(1.0000000144879793  0.0im,1.0000000144879788 + 0.0im)
julia> r = roots([BigFloat(94906268.375), BigFloat(189812534), BigFloat(94906265.625)]);
julia> (Float64(r[1]), Float64(r[2]))
(1.0000000289759583,1.0)

Why isn't this centered fourthorderaccurate finite differencing scheme yielding fourthorder convergence for solving p
By : steve hutton
Date : March 29 2020, 07:55 AM
With these it helps You used the wrong error metric. If you compare the fields on a pointbypoint basis you'll get the convergence rate you were after.

