normalise_to_bounds

 ==============================================================
 NORMALISE_TO_BOUNDS: Normalise data to lie within boundaries.

 Code written by Katherine Smith, 2003

    GENERAL

      normalised_data = normalise_to_bounds(data, lower_bound, upper_bound)

    INPUT/S

      -data:
           Input images data.

      -lower_bound:
           Lower bound that the data must not lie under.
           
      -upper_bound:
           Upper bound for the data to lie below.

    OUTPUT/S

      -normalised_data:
           The data in normalised state.

    PENDING WORK

      -

    KNOWN BUG/S

      -None.

    COMMENT/S

      -What is the exact nature of normalisation?

    RELATED FUNCTION/S

      

    ABOUT

      -Created:     November 23rd, 2003
      -Last update: Novermber 26th, 2003
      -Revision:    0.0.2
      -Author:      R. S. Schestowitz, University of Manchester
 ==============================================================

0001 function normalised_data = normalise_to_bounds(data, lower_bound, upper_bound)
0002 % ==============================================================
0003 % NORMALISE_TO_BOUNDS: Normalise data to lie within boundaries.
0004 %
0005 % Code written by Katherine Smith, 2003
0006 %
0007 %    GENERAL
0008 %
0009 %      normalised_data = normalise_to_bounds(data, lower_bound, upper_bound)
0010 %
0011 %    INPUT/S
0012 %
0013 %      -data:
0014 %           Input images data.
0015 %
0016 %      -lower_bound:
0017 %           Lower bound that the data must not lie under.
0018 %
0019 %      -upper_bound:
0020 %           Upper bound for the data to lie below.
0021 %
0022 %    OUTPUT/S
0023 %
0024 %      -normalised_data:
0025 %           The data in normalised state.
0026 %
0027 %    PENDING WORK
0028 %
0029 %      -
0030 %
0031 %    KNOWN BUG/S
0032 %
0033 %      -None.
0034 %
0035 %    COMMENT/S
0036 %
0037 %      -What is the exact nature of normalisation?
0038 %
0039 %    RELATED FUNCTION/S
0040 %
0041 %
0042 %
0043 %    ABOUT
0044 %
0045 %      -Created:     November 23rd, 2003
0046 %      -Last update: Novermber 26th, 2003
0047 %      -Revision:    0.0.2
0048 %      -Author:      R. S. Schestowitz, University of Manchester
0049 % ==============================================================
0050 
0051 
0052 
0053 
0054 if(nargin ==1) % set some range defaults if no arguments given
0055   lower_bound = 0;
0056   upper_bound = 1;
0057 end
0058 
0059 mins = min(data); 
0060                 % get minimum of data
0061 data_less_mins = data - repmat(mins,size(data,1),1); 
0062                 % subtract minimum from data, i.e. shift it as close
0063                 % as possible to x axis without reaching negative values
0064 maxs = max(data_less_mins);
0065                 % get maximum of the data above (global maxima of curve)
0066 normalised_data = lower_bound + (data_less_mins ./ repmat(maxs,size(data,1),1))*(upper_bound-lower_bound); 
0067                 % where is this formulation from?? Result appearance?
0068                 % Is it scaled to fit inside boundaries?