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[NET-309] Move Freedman-Lane and Westfall-Young to mcc #146

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Merged
pollaro merged 4 commits into from
Apr 15, 2026
Merged

[NET-309] Move Freedman-Lane and Westfall-Young to mcc #146

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85bb43b
moved westfallyoung and freedmanlane to mcc
pollaro Apr 14, 2026
36bb388
Exported mlapp files
actions-user Apr 14, 2026
dd14693
removed unused variable
pollaro Apr 14, 2026
c352794
fixed unit tests
pollaro Apr 15, 2026
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15 changes: 15 additions & 0 deletions +nla/+net/+mcc/FreedmanLane.m
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@@ -0,0 +1,15 @@
classdef FreedmanLane < nla.net.mcc.Base
properties (Constant)
name = "Freedman-Lane"
end

methods
function [is_sig_vector, p_max] = correct(obj, net_atlas, input_struct, prob)
p_max = input_struct.prob_max;
is_sig_vector = prob.v < p_max;
end
function correction_label = createLabel(obj, net_atlas, input_struct)
correction_label = sprintf("P < %.2g", input_struct.prob_max);
end
end
end
15 changes: 15 additions & 0 deletions +nla/+net/+mcc/WestfallYoung.m
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@@ -0,0 +1,15 @@
classdef WestfallYoung < nla.net.mcc.Base
properties (Constant)
name = "Westfall-Young"
end

methods
function [is_sig_vector, p_max] = correct(obj, net_atlas, input_struct, prob)
p_max = input_struct.prob_max;
is_sig_vector = prob.v < p_max;
end
function correction_label = createLabel(obj, net_atlas, input_struct)
correction_label = sprintf("P < %.2g", input_struct.prob_max);
end
end
end
388 changes: 0 additions & 388 deletions +nla/+net/+result/+plot/NetworkTestPlot.m
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61 changes: 14 additions & 47 deletions +nla/+net/+result/+plot/NetworkTestPlotApp_exported.m
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Expand Up @@ -8,8 +8,6 @@
Panel matlab.ui.container.Panel
PlotScaleDropDownLabel matlab.ui.control.Label
PlotScaleDropDown matlab.ui.control.DropDown
RankingDropDownLabel matlab.ui.control.Label
RankingDropDown matlab.ui.control.DropDown
UpperLimitEditFieldLabel matlab.ui.control.Label
UpperLimitEditField matlab.ui.control.NumericEditField
LowerLimitEditFieldLabel matlab.ui.control.Label
Expand Down Expand Up @@ -89,15 +87,6 @@ function getPlotTitle(app)
if isequal(app.CohensDThresholdCheckBox.Value, true)
app.title = sprintf("%s (D > %g)", app.title, app.CohensDThresholdEditField.Value);
end
if ~isequal(app.test_method, "no_permutations")
if isequal(app.RankingDropDown.Value, "nla.RankingMethod.FREEDMAN_LANE") % Look at me, I'm MATLAB. I have no idea why enums are beneficial or how to use them
app.title = strcat(app.title, "\nRanking by Freedman-Lane Method");
elseif isequal(app.RankingDropDown.Value, "nla.RankingMethod.WESTFALL_YOUNG")
app.title = strcat(app.title, "\nRanking by Westfall-Young Method");
else
app.title = strcat(app.title, "\nUncorrected data");
end
end
end

function [width, height] = drawTriMatrixPlot(app)
Expand All @@ -106,15 +95,6 @@ function getPlotTitle(app)
if ~isequal(app.matrix_plot, false)
app.save_plot_settings();
end

if isfield(app.settings, "ranking")
app.network_test_options.ranking_method = app.settings.ranking;
if isobject(app.matrix_plot)
app.matrix_plot.removeLegend();
delete(app.matrix_plot.image_display);
delete(app.matrix_plot.color_bar);
end
end

switch app.MultipleComparisonCorrectionDropDown.Value
case "Benjamini-Hochberg"
Expand All @@ -123,13 +103,16 @@ function getPlotTitle(app)
mcc = "BenjaminiYekutieli";
case "Holm-Bonferroni"
mcc = "HolmBonferroni";
case "Freedman-Lane"
mcc = "FreedmanLane";
case "Westfall-Young"
mcc = "WestfallYoung";
otherwise
mcc = app.MultipleComparisonCorrectionDropDown.Value;
end
app.getPlotTitle();

if isequal(app.old_data, true)
app.RankingDropDown.Enable = false;
if ~isfield(app.network_test_result.full_connectome, 'd')
app.CohensDThresholdCheckBox.Enable = false;
app.CohensDThresholdEditField.Enable = false;
Expand All @@ -141,7 +124,7 @@ function getPlotTitle(app)
app.edge_test_options.net_atlas, app.network_test_options);
probability_parameters = app.parameters.plotProbabilityParameters(app.edge_test_options, app.edge_test_result,...
app.test_method, probability, sprintf(app.title), mcc, app.createEffectSizeFilter(),...
app.RankingDropDown.Value, app.PlotValueDropDown.Value);
app.PlotValueDropDown.Value);

% if ~isequal(app.UpperLimitEditField.Value, 0.3) && ~isequal(app.LowerLimitEditField.Value, 0.3)
probability_parameters.plot_max = app.pvalueThresholdEditField.Value;
Expand Down Expand Up @@ -189,7 +172,6 @@ function save_plot_settings(app)
app.matrix_plot.display_legend.Visible = app.LegendVisibleDropDown.Value;
app.matrix_plot.plot_title.String = {};
app.network_test_options.prob_max = app.pvalueThresholdEditField.Value;
app.settings.ranking = app.RankingDropDown.Value;
end

function load_plot_settings(app)
Expand Down Expand Up @@ -298,7 +280,7 @@ function drawChords(app, event)
p_value = strcat("uncorrected_", probability);
probability_parameters = app.parameters.plotProbabilityParameters(app.edge_test_options, app.edge_test_result,...
app.test_method, p_value, sprintf(app.title), app.MultipleComparisonCorrectionDropDown.Value, app.createEffectSizeFilter(),...
app.RankingDropDown.Value);
app.PlotValueDropDown.Value);

chord_plotter = nla.net.result.chord.ChordPlotter(app.edge_test_options.net_atlas, app.edge_test_result);

Expand All @@ -309,7 +291,7 @@ function drawChords(app, event)
% Value changed function: ColormapDropDown,
% LegendVisibleDropDown, LowerLimitEditField,
% MultipleComparisonCorrectionDropDown, PlotScaleDropDown,
% RankingDropDown, UpperLimitEditField
% UpperLimitEditField
function PlotScaleValueChanged(app, event)
if isequal(app.settings, false)
app.settings = struct();
Expand All @@ -329,7 +311,6 @@ function PlotScaleValueChanged(app, event)
app.settings.cohensD = app.CohensDThresholdCheckBox.Value;
app.settings.cohensDValue = app.CohensDThresholdEditField.Value;
app.settings.legend = app.LegendVisibleDropDown.Value;
app.settings.ranking = app.RankingDropDown.Value;
end

% Value changed function: ROIcentroidsonbrainplotsCheckBox
Expand Down Expand Up @@ -470,20 +451,6 @@ function createComponents(app)
app.PlotScaleDropDown.Position = [78 297 100 22];
app.PlotScaleDropDown.Value = 'nla.gfx.ProbPlotMethod.DEFAULT';

% Create RankingDropDownLabel
app.RankingDropDownLabel = uilabel(app.Panel);
app.RankingDropDownLabel.HorizontalAlignment = 'right';
app.RankingDropDownLabel.Position = [226 297 50 22];
app.RankingDropDownLabel.Text = 'Ranking';

% Create RankingDropDown
app.RankingDropDown = uidropdown(app.Panel);
app.RankingDropDown.Items = {'Uncorrected', 'Freedman-Lane', 'Westfall-Young'};
app.RankingDropDown.ItemsData = {'nla.RankingMethod.UNCORRECTED', 'nla.RankingMethod.FREEDMAN_LANE', 'nla.RankingMethod.WESTFALL_YOUNG'};
app.RankingDropDown.ValueChangedFcn = createCallbackFcn(app, @PlotScaleValueChanged, true);
app.RankingDropDown.Position = [291 297 100 22];
app.RankingDropDown.Value = 'nla.RankingMethod.UNCORRECTED';

% Create UpperLimitEditFieldLabel
app.UpperLimitEditFieldLabel = uilabel(app.Panel);
app.UpperLimitEditFieldLabel.HorizontalAlignment = 'right';
Expand Down Expand Up @@ -534,41 +501,41 @@ function createComponents(app)
% Create ColormapDropDownLabel
app.ColormapDropDownLabel = uilabel(app.Panel);
app.ColormapDropDownLabel.HorizontalAlignment = 'right';
app.ColormapDropDownLabel.Position = [9 177 58 22];
app.ColormapDropDownLabel.Position = [221 297 58 22];
app.ColormapDropDownLabel.Text = 'Colormap';

% Create ColormapDropDown
app.ColormapDropDown = uidropdown(app.Panel);
app.ColormapDropDown.Items = {};
app.ColormapDropDown.ValueChangedFcn = createCallbackFcn(app, @PlotScaleValueChanged, true);
app.ColormapDropDown.Position = [78 177 100 22];
app.ColormapDropDown.Position = [290 297 100 22];
app.ColormapDropDown.Value = {};

% Create LegendVisibleDropDownLabel
app.LegendVisibleDropDownLabel = uilabel(app.Panel);
app.LegendVisibleDropDownLabel.HorizontalAlignment = 'right';
app.LegendVisibleDropDownLabel.Position = [233 177 84 22];
app.LegendVisibleDropDownLabel.Position = [231 147 84 22];
app.LegendVisibleDropDownLabel.Text = 'Legend Visible';

% Create LegendVisibleDropDown
app.LegendVisibleDropDown = uidropdown(app.Panel);
app.LegendVisibleDropDown.Items = {'On', 'Off'};
app.LegendVisibleDropDown.ItemsData = {'on', 'off'};
app.LegendVisibleDropDown.ValueChangedFcn = createCallbackFcn(app, @PlotScaleValueChanged, true);
app.LegendVisibleDropDown.Position = [332 177 59 22];
app.LegendVisibleDropDown.Position = [330 147 59 22];
app.LegendVisibleDropDown.Value = 'on';

% Create MultipleComparisonCorrectionDropDownLabel
app.MultipleComparisonCorrectionDropDownLabel = uilabel(app.Panel);
app.MultipleComparisonCorrectionDropDownLabel.HorizontalAlignment = 'right';
app.MultipleComparisonCorrectionDropDownLabel.Position = [11 147 178 22];
app.MultipleComparisonCorrectionDropDownLabel.Position = [11 177 178 22];
app.MultipleComparisonCorrectionDropDownLabel.Text = 'Multiple Comparison Correction';

% Create MultipleComparisonCorrectionDropDown
app.MultipleComparisonCorrectionDropDown = uidropdown(app.Panel);
app.MultipleComparisonCorrectionDropDown.Items = {'None', 'Bonferroni', 'Benjamini-Hochberg', 'Benjamini-Yekutieli', 'Holm-Bonferroni'};
app.MultipleComparisonCorrectionDropDown.Items = {'None', 'Bonferroni', 'Benjamini-Hochberg', 'Benjamini-Yekutieli', 'Holm-Bonferroni', 'Freedman-Lane', 'Westfall-Young'};
app.MultipleComparisonCorrectionDropDown.ValueChangedFcn = createCallbackFcn(app, @PlotScaleValueChanged, true);
app.MultipleComparisonCorrectionDropDown.Position = [226 147 165 22];
app.MultipleComparisonCorrectionDropDown.Position = [226 177 165 22];
app.MultipleComparisonCorrectionDropDown.Value = 'None';

% Create CohensDThresholdCheckBox
Expand Down
33 changes: 12 additions & 21 deletions +nla/+net/+result/NetworkResultPlotParameter.m
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Expand Up @@ -27,7 +27,7 @@
end

function result = plotProbabilityParameters(obj, edge_test_options, edge_test_result, test_method, plot_statistic,...
plot_title, fdr_correction, effect_size_filter, ranking_method, plot_value)
plot_title, fdr_correction, effect_size_filter, plot_value)
% plot_title - this will be a string
% plot_statistic - this is the stat that will be plotted
% effect_size_filter - this will be a boolean or some sort of object (like Cohen's D > D-value)
Expand All @@ -48,7 +48,7 @@
end

% Grab the data from the NetworkTestResult object
statistic_input = obj.getStatsFromMethodAndName(test_method, plot_statistic, ranking_method);
statistic_input = obj.getStatsFromMethodAndName(test_method, fdr_correction);

% Get the scale max and the labels
if isstring(fdr_correction) || ischar(fdr_correction)
Expand All @@ -60,15 +60,6 @@
p_value_breakdown_label = fdr_correction.createLabel(obj.network_atlas, obj.updated_test_options);
name_label = sprintf("%s %s\n%s", obj.network_test_results.test_display_name, plot_title,...
p_value_breakdown_label);
% else
%
% name_label = sprintf("%s %s\nP < %.2g (%s)", obj.network_test_results.test_display_name, plot_title,...
% p_value_max, p_value_breakdown_label);
% if p_value_max == 0
% name_label = sprintf("%s %s\nP = %.2g (%s)", obj.network_test_results.test_display_name, plot_title,...
% p_value_max, p_value_breakdown_label);
% end
% end

% Filtering if there's a filter provided
significance_plot = TriMatrix(obj.number_of_networks, "logical", TriMatrixDiag.KEEP_DIAGONAL);
Expand Down Expand Up @@ -162,7 +153,7 @@ function brainFigureButtonCallback(network1, network2)
function result = plotProbabilityVsNetworkSize(obj, test_method, plot_statistic)
% Two convience methods
network_size = obj.getNetworkSizes();
statistic_input = obj.getStatsFromMethodAndName(test_method, plot_statistic, obj.updated_test_options.ranking_method);
statistic_input = obj.getStatsFromMethodAndName(test_method, obj.updated_test_options.fdr_correction);

negative_log10_statistics = -log10(statistic_input.v);

Expand Down Expand Up @@ -204,8 +195,8 @@ function brainFigureButtonCallback(network1, network2)
end
end

function statistic = getStatsFromMethodAndName(obj, method, plot_statistic, ranking_method)
import nla.RankingMethod nla.NetworkLevelMethod nla.net.result.NetworkTestResult
function statistic = getStatsFromMethodAndName(obj, method, fdr_correction)
import nla.NetworkLevelMethod nla.net.result.NetworkTestResult

switch method
case "no_permutations"
Expand All @@ -216,18 +207,18 @@ function brainFigureButtonCallback(network1, network2)
test_method = "within_network_pair";
end

switch ranking_method
case "nla.RankingMethod.FREEDMAN_LANE"
ranking = "freedman_lane_";
case "nla.RankingMethod.WESTFALL_YOUNG"
ranking = "westfall_young_";
switch lower(erase(fdr_correction, "-"))
case "freedmanlane"
fdr_method = "freedman_lane_";
case "westfallyoung"
fdr_method = "westfall_young_";
otherwise
ranking = "uncorrected_";
fdr_method = "uncorrected_";
end

probability = NetworkTestResult().getPValueNames(method, obj.network_test_results.test_name);

statistic = obj.network_test_results.(test_method).(strcat(ranking, probability));
statistic = obj.network_test_results.(test_method).(strcat(fdr_method, probability));
end
end

Expand Down
1 change: 0 additions & 1 deletion +nla/+net/+result/NetworkTestResult.m
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Expand Up @@ -355,7 +355,6 @@ function createPValueTriMatrices(obj, number_of_networks, test_method)
test_options = result_struct.input_struct;

network_test_options = result_struct.net_input_struct;
network_test_options.ranking_method = "Uncorrected";
network_test_options.no_permutations = network_test_options.nonpermuted;
network_test_options.full_connectome = network_test_options.full_conn;
network_test_options.within_network_pair = network_test_options.within_net_pair;
Expand Down
1 change: 0 additions & 1 deletion +nla/+net/genBaseInputs.m
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Expand Up @@ -6,7 +6,6 @@
'full_connectome', true,...
'within_network_pair', true,...
'prob_plot_method',nla.gfx.ProbPlotMethod.DEFAULT,...
'ranking_method', "Uncorrected",...
'edge_chord_plot_method', nla.gfx.EdgeChordPlotMethod.PROB,...
'fdr_correction', nla.net.mcc.Bonferroni(),...
'd_thresh_chord_plot', true...
Expand Down
12 changes: 6 additions & 6 deletions +nla/+net/unittests/NetworkResultPlotParameterTestCase.m
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Expand Up @@ -91,8 +91,8 @@ function plotProbabilityParametersDefaultPlottingTest(testCase)
probability = NetworkTestResult().getPValueNames("full_connectome", permutation_result.test_name);

probability_parameters = plot_parameters.plotProbabilityParameters(testCase.edge_test_options,...
testCase.edge_test_result, "full_connectome", probability, 'Title', nla.net.mcc.Bonferroni(),...
false, nla.RankingMethod.UNCORRECTED, "nla.gfx.PlotValue.PVALUE");
testCase.edge_test_result, "full_connectome", probability, 'Title', "Bonferroni",...
false, "nla.gfx.PlotValue.PVALUE");

expected_p_value_max = testCase.network_test_options.prob_max / testCase.network_atlas.numNetPairs();
expected_plot = nla.TriMatrix(plot_parameters.number_of_networks, "double", nla.TriMatrixDiag.KEEP_DIAGONAL);
Expand All @@ -119,8 +119,8 @@ function plotProbabilityParametersLogPlottingTest(testCase)
probability = NetworkTestResult().getPValueNames("full_connectome", permutation_result.test_name);

probability_parameters = plot_parameters.plotProbabilityParameters(testCase.edge_test_options,...
testCase.edge_test_result, "full_connectome", probability, 'Title', nla.net.mcc.Bonferroni(),...
false, nla.RankingMethod.UNCORRECTED, "nla.gfx.PlotValue.PVALUE");
testCase.edge_test_result, "full_connectome", probability, 'Title', "Bonferroni",...
false, "nla.gfx.PlotValue.PVALUE");

expected_p_value_max = testCase.network_test_options.prob_max / testCase.network_atlas.numNetPairs();
expected_plot = nla.TriMatrix(plot_parameters.number_of_networks, "double", nla.TriMatrixDiag.KEEP_DIAGONAL);
Expand Down Expand Up @@ -157,8 +157,8 @@ function plotProbabilityParametersNegLogTest(testCase)
probability = NetworkTestResult().getPValueNames("full_connectome", permutation_result.test_name);

probability_parameters = plot_parameters.plotProbabilityParameters(testCase.edge_test_options,...
testCase.edge_test_result, "full_connectome", probability, 'Title', nla.net.mcc.Bonferroni(),...
false, nla.RankingMethod.UNCORRECTED, "nla.gfx.PlotValue.PVALUE");
testCase.edge_test_result, "full_connectome", probability, 'Title', "Bonferroni",...
false, "nla.gfx.PlotValue.PVALUE");

expected_p_value_max = 2;
expected_plot = nla.TriMatrix(plot_parameters.number_of_networks, "double", nla.TriMatrixDiag.KEEP_DIAGONAL);
Expand Down
5 changes: 0 additions & 5 deletions +nla/RankingMethod.m
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