functions.d2chi2.d2chi2

d2chi2(self, params, diff_type, diff_params, model, relax_data, errors, print_flag=0)

Function to create the chi-squared hessian.

Function arguments
~~~~~~~~~~~~~~~~~~

1:  params - a list containing the parameter values specific for the given model.
The order of parameters must be as follows:
        m1 - {S2}
        m2 - {S2, te}
        m3 - {S2, Rex}
        m4 - {S2, te, Rex}
        m5 - {S2f, S2s, ts}
2:  diff_type - string.  The diffusion tensor, ie 'iso', 'axial', 'aniso'
3:  diff_params - array.  An array with the diffusion parameters
4:  model - string.  The model
5:  relax_data - array.  An array containing the experimental relaxation values.
6:  errors - array.  An array containing the experimental errors.


The chi-sqared hessian
~~~~~~~~~~~~~~~~~~~~~~

Data structure:  self.data.d2chi2
Dimension:  2D, (parameters, parameters)
Type:  Numeric array, Float64
Dependencies:  self.data.ri, self.data.dri, self.data.d2ri
Required by:  None


Formula
~~~~~~~
                              _n_
             d2chi2           \       1      /  dRi()     dRi()                         d2Ri()     \ 
        ---------------  =  2  >  ---------- | ------- . -------  -  (Ri - Ri()) . --------------- |
        dthetaj.dthetak       /__ sigma_i**2 \ dthetaj   dthetak                   dthetaj.dthetak / 
                              i=1

Class d2chi2

d2chi2(self, params, diff_type, diff_params, model, relax_data, errors, print_flag=0)