relax SVN archive

Implemented the exponential curve second partial derivative C functions.

These are declared in the exponential.h header file and are now used by the Python function
target_functions.relax_fit.d2func().

Partly implemented the front end target_functions.relax_fit.d2func() C module Python function.

This is not fully implemented as the exponential curve double partial derivatives are not
implemented.

Comment fixes and formatting changes in all of the target_functions C files and headers.

Comment fix in the target_functions/c_chi2.c file.

Clean up of the header and includes of the target_functions/c_chi2.c file.

The square() function macro has been shifted to the header file and the stdio.h and math.h standard
library headers are no longer included as they are not used.

The target_functions/exponential.c file no longer includes exponential.h.

This is not needed as exponential.h only contains the function definitions of the exponential.c
file.

All of the C code chi-squared functions now have the array argument dimensions explicitly declared.

Better commenting in the C header files.

Standardisation of the array dimensionality in the target function C code.

The new target_functions/dimensions.h header file defines MAX_PARAMS and MAX_DATA which is then
included in the header files of all the other C files. All array declarations now explicitly
specify the length of each dimension.

The values of MAX_PARAMS and MAX_DATA have increased from 3 and 50 to 20 and 5000. This is to allow
for models with more parameters and to allow a much larger number of input data points to be
supported before memory corruptions happen. The data structures now take up more memory, but as the
functions do not loop up to maximum but only the number of parameters and points specified, this
will not make the code slower.

Changed the internal variables of the chi-squared gradient C code to match the Python code.