example.m

%% Example Script
% This Script is meant to demonstrate the capabilities of the PlotID tool.

%% Clear Environment
clear; clc; close all;

try
    delete testdata2.h5;
end

%% Set ProjectID
% ProjectID can also be set in the config file 

% Leave empty for using the ID from the config file
ProjectID = 'Example';

%% Data
% only necessary for this example

% Creating Random Data to use as data-file
x = linspace(0,7); y = rand(1,100)+2;
dataset1 = 'test_data.mat';

% Use absolute paths for good practise
dataset1 = fullfile(pwd,dataset1);
save(dataset1,'x','y');

% some data for the .h5 file
x1 = linspace(0,2*pi); y1 = sin(x1)+2;

% define filepath & name
dataset2 = 'testdata2.h5';
dataset2 = fullfile(pwd,dataset2);
fpath = dataset2;

% create hdf5 file and dataset > write data to hdf5 file / dataset
h5create(fpath, "/x1", size(x1), "Datatype", class(x1))
h5create(fpath, "/y1", size(y1), "Datatype", class(y1))
h5write(fpath, "/x1", x1)
h5write(fpath, "/y1", y1)

%% function calls
% Place for post-processing of the data, or additional related code.
% example_fcn is a dummy function to show the functionality
a = 1; a = example_fcn(a); 
% Uncomment to include the Statistics and Machine learning Toolbox
% p = betacdf(0.5,1,1); % to test toolboxes

%% Plotting
% This is still part of a normal script to produce plots.
% Make sure to save each figure in a variable
% to pass it to PlotID-functions.
fig(1) = figure;
plot(x,y,'-k');
box off; hold on;
plot(x1,y1,'-r');
set(gca, 'TickDir', 'out', 'YLim', [0,4]);

%% Example 1: single plot based on two data-sets

%% Tag the plot
% PlotID Implementation starts here.
% TagPlot adds a visible ID to the figure(s) and to the figures property
% 'Tag'
[fig, IDobj] = PlotID.TagPlot(fig, 'ProjectID', ProjectID);

%% Publishing
% Second part of plotID 
% The functions needs the file location of the script, the location of the
% data and the figure and can take several options (see readme). 

% filename of the m.script, extension must be added!
scriptPath = [mfilename('fullpath'),'.m']; 

% file names of the datasets

%(defined above:) dataset1 = 'test_data.mat'; dataset2 = 'testdata2.h5'
locations =  {dataset1,dataset2} ; % don't forget the extension
locations =  {string(dataset1),dataset2}

%call publishing
PlotID.Publish(locations,scriptPath, fig(1), 'Location', 'local' ,'Method','individual')

%% Example 2: multiple plots plot, all based on dataset2 (hdf5)
% for individual data-sets, use an appropriate array

fig(2) = figure;
plot(x,y,'-b');
box off; hold on;
plot(x1,y1,'--k');
set(gca, 'TickDir', 'out', 'YLim', [0,4]);

% tag both plots 
[fig, IDs] = PlotID.TagPlot(fig,'ProjectID', ProjectID);

% data locations
script = [mfilename('fullpath'),'.m']; % filename of the m.script
% file names of the datasets
rdata =  dataset2 ; % don't forget the extension

% publsihing via a for-loop
for i=1: numel(fig)
    PlotID.Publish(rdata, script, fig(i), 'Location', 'local',...
        'Method','individual');
end

%% Second Plot with identical data to test centralized method
% A central data folder is used for saving the research data files, the
% subfolders contain linked hdf5-files (if hdf5 is used). This is
% recommended, if many plots are made from the same data set.  Attention,
% the linked HDF5 will not work when a subfolder was moved or the data
% folder was deleted

fig2 =figure;
plot(x,y,'-k');
hold on
plot(x1,y1,'-r');

[fig2, ID] = PlotID.TagPlot(fig2,'ProjectID', ProjectID);

PlotID.Publish(locations,scriptPath, fig2, 'Location', 'local','Method','centralized')