chi2(self,
params,
diff_type,
diff_params,
model,
relax_data,
errors,
print_flag=0)
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Function to calculate the chi-squared value.
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 equation
~~~~~~~~~~~~~~~~~~~~~~~
Data structure: self.data.chi2
Type: Double precision floating point value.
Dependencies: self.data.ri
Required by: None
Formula
~~~~~~~
_n_
\ (Ri - Ri()) ** 2
Chi2 = > ----------------
/__ sigma_i ** 2
i=1
where:
Ri are the values of the measured relaxation data set.
Ri() are the values of the back calculated relaxation data set.
sigma_i are the values of the error set.
Returned is the chi-squared value.
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