FUNCTION fit_proportional, xdata, ydata, ysigdata

; Description: This function fits a single parameter proportional model to a set of input data.
;              The model used is:
;
;              y = G*x
;
;              where x is the independent variable, y is the dependent variable and G is the
;              gradient of the proportional relationship. The function returns both the 
;              gradient and its uncertainty, based on the input uncertainties on the dependent
;              variable.
; 
; Input Parameters:
;   
;   xdata - FLOAT/DOUBLE VECTOR - The one dimensional vector of input data for the independent 
;                                 variable.
;   ydata - FLOAT/DOUBLE VECTOR - The one dimensional vector of input data for the dependent 
;                                 variable. If this vector is not of the same length as "xdata",
;                                 then the function will return the output vector [0.0D, -1.0D].
;   ysigdata - FLOAT/DOUBLE VECTOR - The one dimensional vector of uncertainties on the input 
;                                    data for the dependent variable. If this vector is not of 
;                                    the same length as "xdata", then the function will return 
;                                    the output vector [0.0D, -1.0D]. Any values in this vector
;                                    which are zero or negative will cause the corresponding
;                                    data points to be ignored in the fit.
;
; Return value:
;       
;   The function returns a 2-element vector of DOUBLES. The first element is the fitted gradient, 
;   and the second element is the uncertainty on the gradient. If the fit has failed for any 
;   reason, then the output vector is returned as [0.0D, -1.0D], such that the returned 
;   uncertainty on the gradient of -1.0 does not make sense.
;
; Author: Dan Bramich (dan.bramich@hotmail.co.uk)
;
; History:
;
;   24/04/2009 - Further module optimisation performed (dmb).
;   05/05/2008 - Module created (dmb).

;Check that "xdata", "ydata" and "ysigdata" are one dimensional vectors of the same length

;Determine the set of data points for which the uncertainties on the dependent variable are 
;positive, and return a failed fit if none of the uncertainties are positive

;Calculate the gradient and its uncertainty via the optimal scaling formula. If the calculated
;gradient is infinity, then return a failed fit.

;Return the gradient and its uncertainty