%% CALCULATE BUBBLE STATISTICS FROM JSON DATA
%{
Description:
This script reads a JSON file containing manually annotated bubble contours.
It then calculates key bubble statistics for each image, aggregates the 
results by heat load, and computes the mean and standard deviation for 
each heat load condition.

Instructions:
0. Define the pixel resolution parameter (l_px) accordingly.
1. Run this script.
2. A dialog will prompt you to select the JSON data file.
3. A second dialog will prompt you to select the folder containing the
   corresponding original images.
4. The script will process the data and display a results table in the
   Command Window.
5. (Optional) Set `save_contour_Mode` to true to save annotated images.

Last modified: 2025/10/08
Author: Lige Zhang
Reference: International Journal of Heat and Mass Transfer 255 (2026): 127894.
%}
clear; close all; clc
format long

%% --------------------- USER SETTINGS ---------------------
% --- Set to true to save images with contours drawn on them ---
save_contour_Mode = true; 

% --- Physical Constants ---
% l_px = 32.26e-3;  % Pixel resolution in [mm/pixel] <- IMPORTANT: need to be updated accroding to the dataset!
l_px = 31.25e-3;
A_px = l_px^2;    % Area of a single pixel in [mm^2/pixel]

%% --------------------- DATA LOADING ---------------------
[jsonFileName, jsonPath] = uigetfile('*.json', 'Select the annotated JSON file');
if isequal(jsonFileName, 0), disp('File selection cancelled.'); return; end
jsonFile = fullfile(jsonPath, jsonFileName);

imageFolderDIR = uigetdir(jsonPath, 'Select the folder containing the original images');
if isequal(imageFolderDIR, 0), disp('Folder selection cancelled.'); return; end

jsonText = fileread(jsonFile);
structData = jsondecode(jsonText);
imageDataNames = fieldnames(structData);

%% ----------------- BUBBLE STATISTICS CALCULATION -----------------
bubbleStat = struct;
disp('Processing images and calculating statistics...');

% --- Create the output directory for contour images ---
if save_contour_Mode == true
    save_contour_DIR = fullfile(imageFolderDIR, "BubbleContours");
    if ~exist(save_contour_DIR, 'dir'), mkdir(save_contour_DIR); end
end

for i = 1:length(imageDataNames)
    currentImageKey = imageDataNames{i};
    currentImageData = structData.(currentImageKey);
    imageFileName = currentImageData.FileName;

    heatLoadToken = regexp(imageFileName, '_(\d+(\.\d+)?W)_', 'tokens');
    if isempty(heatLoadToken)
        warning('Could not parse heat load from filename: %s. Skipping.', imageFileName);
        continue;
    end
    heatLoadStr = heatLoadToken{1}{1};
    heatLoadFieldName = matlab.lang.makeValidName(['load_' heatLoadStr]);
    
    bubbles = currentImageData.Bubbles;
    bubbleNames = fieldnames(bubbles);
    numOfBubbles_i = length(bubbleNames);
    
    if numOfBubbles_i == 0, continue; end

    allBubbleAreas_i = zeros(numOfBubbles_i, 1); 
    for j = 1:numOfBubbles_i
        bubbleName = bubbleNames{j};
        x_coord = bubbles.(bubbleName).x_coordinate;
        y_coord = bubbles.(bubbleName).y_coordinate;
        allBubbleAreas_i(j) = polyarea(x_coord, y_coord) * A_px;
    end
    
    sumAreaBubbles_i = sum(allBubbleAreas_i);
    avgBubbleArea_i = mean(allBubbleAreas_i);
    avgBubbleRadius_i = sqrt(avgBubbleArea_i / pi);
    
    Img_proc = imread(fullfile(imageFolderDIR, imageFileName));
    imageTotalArea = size(Img_proc, 1) * size(Img_proc, 2) * A_px;
    vaporAreaFraction_i = sumAreaBubbles_i / imageTotalArea;
    
    if ~isfield(bubbleStat, heatLoadFieldName)
        bubbleStat.(heatLoadFieldName).NumBubbles = [];
        bubbleStat.(heatLoadFieldName).AvgArea = [];
        bubbleStat.(heatLoadFieldName).AvgRadius = [];
        bubbleStat.(heatLoadFieldName).VaporFraction = [];
    end
    
    bubbleStat.(heatLoadFieldName).NumBubbles(end+1) = numOfBubbles_i;
    bubbleStat.(heatLoadFieldName).AvgArea(end+1) = avgBubbleArea_i;
    bubbleStat.(heatLoadFieldName).AvgRadius(end+1) = avgBubbleRadius_i;
    bubbleStat.(heatLoadFieldName).VaporFraction(end+1) = vaporAreaFraction_i;

    %% --- CORRECTED: Save tightly-cropped image with sanitized filename ---
    if save_contour_Mode == true
        % Create a figure but keep it invisible for faster processing
        fig = figure('Visible', 'off');
        ax = axes(fig); % Create axes in the figure
        imshow(Img_proc, 'Parent', ax);
        hold(ax, 'on');
        for j = 1:numOfBubbles_i
            bubbleName = bubbleNames{j};
            plot(ax, bubbles.(bubbleName).x_coordinate, bubbles.(bubbleName).y_coordinate, 'r--', 'LineWidth', 2);
        end
        hold(ax, 'off');
        
        % --- FIX 1: Sanitize filename to handle '.' correctly ---
        [~, base_name, ~] = fileparts(imageFileName);
        sanitized_name = strrep(base_name, '.', 'd');
        output_image_path = fullfile(save_contour_DIR, [sanitized_name, '.png']);
        
        % --- FIX 2: Use exportgraphics to save without whitespace ---
        exportgraphics(ax, output_image_path, 'Resolution', 150);
        
        close(fig);
    end
end

disp('Calculation finished. Summarizing results...');
%% ------------------- FINAL RESULTS SUMMARY -------------------
loadNames = fieldnames(bubbleStat);
numLoads = length(loadNames);

resultsData = zeros(numLoads, 9); 
for k = 1:numLoads
    loadName = loadNames{k};
    loadValueStr = regexp(loadName, '\d+(\.?\d+)?', 'match');
    loadValue = str2double(loadValueStr{1});
    
    resultsData(k, :) = [
        loadValue, ...
        mean(bubbleStat.(loadName).NumBubbles), std(bubbleStat.(loadName).NumBubbles), ...
        mean(bubbleStat.(loadName).AvgArea), std(bubbleStat.(loadName).AvgArea), ...
        mean(bubbleStat.(loadName).AvgRadius), std(bubbleStat.(loadName).AvgRadius), ...
        mean(bubbleStat.(loadName).VaporFraction), std(bubbleStat.(loadName).VaporFraction)
    ];
end

resultsData = sortrows(resultsData, 1);
resultsTable = array2table(resultsData, 'VariableNames', {
    'HeatLoad_W', ...
    'Mean_NumBubbles', 'StdDev_NumBubbles', ...
    'Mean_AvgArea_mm2', 'StdDev_AvgArea_mm2', ...
    'Mean_AvgRadius_mm', 'StdDev_AvgRadius_mm', ...
    'Mean_VaporFraction', 'StdDev_VaporFraction'
});

disp(resultsTable);