Method: CArray#fit_nonlinear

Defined in:

lib/carray-gsl/core.rb

#fit_nonlinear(xx, sigma, procf, procdf, parms, errs) ⇒ Object

# File 'lib/carray-gsl/core.rb', line 270

def fit_nonlinear (xx, sigma, procf, procdf, parms, errs)
  n  = self.elements
  np = parms.size
  parms = GSL::Vector[*parms]
  gf = Proc.new { |a, x, y, sigma, f|
    f.ca[] = (procf.call(x, a.to_a) - y) / sigma
  }
  gdf = Proc.new { |a, x, y, sigma, jac| 
    cjac = jac.ca
    df   = procdf.call(x, a.to_a)
    a.size.times do |i|
      cjac[nil, i] = df[i] / sigma
    end
  }
  func   = GSL::MultiFit::Function_fdf.alloc(gf, gdf, np)
  func.set_data(xx, self, sigma)
  lmsder = GSL::MultiFit::FdfSolver::LMSDER
  solver = GSL::MultiFit::FdfSolver.alloc(lmsder, n, np)
  solver.set(func, parms)

  iter = 0
  begin
    iter += 1
    status = solver.iterate
    status = solver.test_delta(*errs)
  end while status == GSL::CONTINUE and iter < 500

  coef  = solver.position.to_a
  chi2  = GSL::pow_2(solver.f.dnrm2)
  dof   = n - np
  covar = solver.covar(0.0).ca
  err   = Array.new(np){|i| Math::sqrt(chi2/dof*covar[i,i]) }
  return coef, err, chi2, dof, covar
end