relax SVN archive

The parameter index is now passed into exponential_dI0() and exponential_dR().

This is for the relaxation curve-fitting C module so that the indices are not hardcoded.

Modified all of the exponential curve functions and gradients in the C target function module.

Instead of passing in the parameter vector, now the I0 and R values are passed in separately. This
is for greater code flexibility as the parameter order does not need to be known.

Changed the argument and variable names in the C code chi-squared gradient function.

Clean up of the target function C files (spacing fixes and removal of unused code).

Fixes for all of the exponential functions in target_functions/exponential.c.

The condition whereby Rx is zero is now setting the value correctly - the exponential will be 1, not
zero, hence the intensity and gradient values should not be zero.

Fixes for the target function chi-squared gradient C function.

Clean up of the end of the target_functions.relax_fit.dfunc() function.

The exponential curve-fitting gradient is now scaled by the scaling matrix.

Implementation of the specific_analyses.relax_fit.optimisation.dfunc_wrapper() function.

This interfaces with the target_functions.relax_fit C module and converts the gradient from a Python
list to a numpy array.

Implemented the target_functions.relax_fit.dfunc() gradient function.

This is using the Python/C interface to provide a Python function for calculating and returned the
chi-squared gradient for the exponential curves.