compute_pdf

 COMPUTE_PDF: 

    GENERAL

      pdf_values = compute_pdf(image_set, points_set, keep, label, norm_type, shape_weight)

    INPUT/S

      

    OUTPUT/S

      -pdf_values:

    PENDING WORK

      -

    KNOWN BUG/S

      -None.

    COMMENT/S


    RELATED FUNCTION/S

      

    ABOUT

      -Created:     February 2004
      -Last update: February 2004
      -Revision:    0.0.1
      -Author:      R. S. Schestowitz, University of Manchester
 ==============================================================

0001 function pdf_values = compute_pdf(image_set, points_set, kernel, shape_weight)
0002 % COMPUTE_PDF:
0003 %
0004 %    GENERAL
0005 %
0006 %      pdf_values = compute_pdf(image_set, points_set, keep, label, norm_type, shape_weight)
0007 %
0008 %    INPUT/S
0009 %
0010 %
0011 %
0012 %    OUTPUT/S
0013 %
0014 %      -pdf_values:
0015 %
0016 %    PENDING WORK
0017 %
0018 %      -
0019 %
0020 %    KNOWN BUG/S
0021 %
0022 %      -None.
0023 %
0024 %    COMMENT/S
0025 %
0026 %
0027 %    RELATED FUNCTION/S
0028 %
0029 %
0030 %
0031 %    ABOUT
0032 %
0033 %      -Created:     February 2004
0034 %      -Last update: February 2004
0035 %      -Revision:    0.0.1
0036 %      -Author:      R. S. Schestowitz, University of Manchester
0037 % ==============================================================
0038 
0039 % [intensity_model.pcs,intensity_model.variances,intensity_model.params, intensity_model.mean, intensity_model.var_r, intensity_model.total_var, intensity_model.impdata] = st_pca(image_set', keep);
0040 % [shape_model.pcs,shape_model.variances,shape_model.params, shape_model.mean, shape_model.var_r, shape_model.total_var, shape_model.impdata] = st_pca(points_set', keep);
0041 %    % get shape and intensity model
0042 % c_model.shape_weight = ones(1,size(shape_model.pcs,2));
0043 %    % set weight to be a column vector of 1's? Would that mean equal weighing for shape and intensity?
0044 % intensity_model.sd = std(intensity_model.params);
0045 %   % get and record standard deviation
0046 % shape_model.sd = std(shape_model.params);
0047 % if(strcmp(norm_type,'variance'))
0048 %     % combine params - initially normalise to variance described in model
0049 %     total_shape_variance = sum(shape_model.variances);
0050 %     total_intensity_variance = sum(intensity_model.variances);
0051 %     if(total_shape_variance ~= 0)
0052 %         c_model.shape_weight(:) = sqrt(total_intensity_variance/total_shape_variance);
0053 %     end
0054 % %     disp(['Shapeweight: ',num2str(c_model.shape_weight(1))]);
0055 for i = 1:size(image_set,2),
0056        current_intensity_sample = image_set(:,i);
0057        % paramater used to be 1 and passed in as a single parameter to pdf
0058        % function
0059        if (strcmp(kernel,'Normal')),
0060           parameter = mle(kernel,current_intensity_sample);
0061           pdf_values(i,:) = pdf(kernel, current_intensity_sample, parameter(1), parameter(2))';
0062        elseif (strcmp(kernel,'Exponential')),
0063            parameter = 1;
0064                   % this is an arbitrary useless value that needs to be
0065                   % tested
0066            pdf_values(i,:) = pdf(kernel, current_intensity_sample, parameter)';
0067        % EXTENSIONS NEED TO BE PLACED HERE UNDER <ELSEIF> STATEMENTS
0068        else
0069            parameter = 1;
0070                   % this is just a generic expression that makes sure all
0071                   % kernels work.
0072            pdf_values(i,:) = pdf(kernel, current_intensity_sample, parameter)';
0073        end
0074 end      
0075 %       c_model.shape_weight(:) = shape_weight;
0076 % elseif(strcmp(norm_type,'edge'))
0077 %       edges = abs(diff(image_set,1,2));
0078 %       mean_edge_strength = sum(edges(:))/size(edges(:),1);
0079 %       c_model.shape_weight(:) = mean_edge_strength;
0080 % %     disp(['edge weight: ',num2str(mean_edge_strength)]);
0081 %
0082 % [c_model.pcs, c_model.variances, c_model.params, c_model.mean, c_model.total_var, c_model.impdata] = make_combined_model(shape_model, intensity_model, c_model.shape_weight);
0083 % c_model.sd = sqrt(c_model.variances);
0084 % c_model.intensity_model = intensity_model;
0085 %
0086 % % intensity_model
0087 % % shape_model
0088 % % figure;
0089 % % plot(intensity_model);
0090 %         % attempt to look at the models built from the data (RSS)
0091 %
0092 % c_model.shape_model = shape_model;
0093 % c_model.n_shape_modes = size(shape_model.sd,2);
0094 % c_model.label = label;
0095 %    % save some of the values to be returned by the function