print_performace_statistics_and_plot.m

function [matching_candidate_index_from_target_index, matching_target_index_from_candidate_index] = ...
        print_performace_statistics_and_plot(what_are_these, ...
                                             xyz_from_target_index, ...
                                             feature_struct_from_candidate_index, ...
                                             heckbert_origin_xyz, ...
                                             stack_shape_xyz, ...
                                             spacing_at_zoom_level_xyz, ...
                                             mip, ...
                                             mip_origin_xy, ...
                                             mip_spacing_xy, ...
                                             mip_clim, ...
                                             do_plot_candidates)
    %  heckbert_origin_xyz, stack_shape_xyz are for the full stack,
    %  regardless of what region the targets and components are drawn from
                                         
    is_there_a_mip = exist('mip', 'var') && ~isempty(mip) ;
    if is_there_a_mip ,        
        if ~exist('mip_clim', 'var') || isempty(mip_clim) ;
            mip_clim = [min(min(mip)) max(max(mip))] ;
        end
    else
        mip = [] ;
        mip_origin_xy = [] ;
        mip_spacing_xy= [] ;
        mip_clim = [] ;
    end
    
    if ~exist('do_plot_candidates', 'var') || isempty(do_plot_candidates) ,
        do_plot_candidates = true ;
    end
    
    % Figure out what targets are in what candidates
    target_count = size(xyz_from_target_index, 1) ;
    candidate_count = length(feature_struct_from_candidate_index) ;
    origin_at_zoom_level_xyz = heckbert_origin_xyz + spacing_at_zoom_level_xyz/2 ;
    matching_candidate_index_from_target_index = ...
        match_targets_and_components(xyz_from_target_index, feature_struct_from_candidate_index, origin_at_zoom_level_xyz, spacing_at_zoom_level_xyz) ;
    matching_target_index_from_candidate_index = invert_partial_map_array(matching_candidate_index_from_target_index, candidate_count) ;
    is_there_a_matched_candidate_from_target_index = isfinite(matching_candidate_index_from_target_index) ;
    is_there_a_matched_target_from_candidate_index = isfinite(matching_target_index_from_candidate_index) ;

    %
    % End of new way
    %

    % Compute hit counts, precision, recall for the candidates
    fprintf('\n\n%s:\n', what_are_these) ;
    target_count
    candidate_count
    hit_count = sum(is_there_a_matched_candidate_from_target_index)
    assert( sum(is_there_a_matched_target_from_candidate_index) == hit_count ) ;
    miss_count = sum(~is_there_a_matched_candidate_from_target_index)
    chase_count = sum(~is_there_a_matched_target_from_candidate_index)

    recall = hit_count / target_count 
    precision = hit_count / candidate_count 


    % Plot the MIP image
    f = figure('color', 'w', 'name', sprintf('targets-and-%s', what_are_these)) ;
    a = axes(f, 'YDir', 'reverse') ;
    if is_there_a_mip ,
        mip_shape_ji = size(mip) ;
        mip_shape_ij = mip_shape_ji([2 1]) ;
        mip_far_corner_xy = mip_origin_xy + mip_spacing_xy .* (mip_shape_ij-1) ;
        image(a, 'CData', mip, ...
                 'XData', [mip_origin_xy(1) mip_far_corner_xy(1)], ...
                 'YData', [mip_origin_xy(2) mip_far_corner_xy(2)], ...
                 'CDataMapping', 'scaled') ;         
        xlim([mip_origin_xy(1) mip_far_corner_xy(1)] + mip_spacing_xy(1)/2*[-1 +1]) ;
        ylim([mip_origin_xy(2) mip_far_corner_xy(2)] + mip_spacing_xy(2)/2*[-1 +1]) ;
        a.CLim = mip_clim ;
    end
    colormap(gray(256)) ;
    axis image    
    xlabel('x (um)') ;
    ylabel('y (um)') ;


    % plot each target, and each candidate, and draw a line between matches
    hold on ;
    for target_index = 1 : target_count ,
        target_xyz = xyz_from_target_index(target_index,:) ;
        marker_color = fif(is_there_a_matched_candidate_from_target_index(target_index), [0 0.5 1], [1 0 0]) ;    
        plot(target_xyz(1), target_xyz(2), 'Marker', '+', 'Color', marker_color) ;            
        %text(target_xyz(1)+5, target_xyz(2)+5, sprintf('t%d', target_index), 'Color', 0.5*[1 1 1]) ;            
    end
    if do_plot_candidates ,
        for candidate_index = 1 : candidate_count ,
            candidate_xyz = feature_struct_from_candidate_index(candidate_index).centroidoid_xyz ;
            marker_color = fif(is_there_a_matched_target_from_candidate_index(candidate_index), [0 0.5 1], [1 0 0]) ;    
            plot(candidate_xyz(1), candidate_xyz(2), 'Marker', 'o', 'MarkerSize', 6, 'Color', marker_color) ;
            %text(candidate_xyz(1)-5, candidate_xyz(2)-5, sprintf('g%d', candidate_index), 'Color', 0.5*[1 1 1]) ;            
        end
        for target_index = 1 : target_count ,
            target_xyz = xyz_from_target_index(target_index,:) ;
            if is_there_a_matched_candidate_from_target_index(target_index) ,
                candidate_index = matching_candidate_index_from_target_index(target_index) ;
                candidate_xyz = feature_struct_from_candidate_index(candidate_index).centroidoid_xyz ;
                plot([target_xyz(1) candidate_xyz(1)], [target_xyz(2) candidate_xyz(2)], 'Color', [0 0.5 1]) ;    
            end
        end
    end
    hold off ; 
    
    fprintf('\n\n') ;
end