[NET-315] In QC window, apply the remove network to all the different methods#159

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
pollaro merged 1 commit into from
Jul 20, 2026
Merged

[NET-315] In QC window, apply the remove network to all the different methods #159

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
34 changes: 22 additions & 12 deletions +nla/+qualityControl/checkHeadMotion.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
@@ -1,14 +1,24 @@
function checkHeadMotion(fig, input_struct, motion)
function checkHeadMotion(fig, input_struct, motion, remove_index)

network_atlas = input_struct.net_atlas;
functional_connectivity = input_struct.func_conn;
if remove_index ~= 0
[new_netatlas, functional_connectivity] = nla.removeNetworks(input_struct.net_atlas, input_struct.net_atlas.nets(remove_index).name, strcat(input_struct.net_atlas.name, '_-', input_struct.net_atlas.nets(remove_index).name), input_struct.func_conn);
network_atlas = nla.NetworkAtlas(new_netatlas);
if ~isa(functional_connectivity, 'nla.TriMatrix')
functional_connectivity = nla.TriMatrix(functional_connectivity);
end
end

prog = uiprogressdlg(fig, 'Title', 'Generating figures', 'Message', 'Generating head motion figures');
prog.Value = 0.02;
distances = nla.helpers.euclidianDistanceROIs(input_struct.net_atlas);
distances = nla.helpers.euclidianDistanceROIs(network_atlas);
prog.Value = 0.75;
[r_vec, p_vec] = corr(motion, input_struct.func_conn.v', 'type', 'Pearson');
[r_vec, p_vec] = corr(motion, functional_connectivity.v', 'type', 'Pearson');

prob = nla.TriMatrix(input_struct.net_atlas.numROIs());
r = nla.TriMatrix(input_struct.net_atlas.numROIs());
h = nla.TriMatrix(input_struct.net_atlas.numROIs(), 'logical');
prob = nla.TriMatrix(network_atlas.numROIs());
r = nla.TriMatrix(network_atlas.numROIs());
h = nla.TriMatrix(network_atlas.numROIs(), 'logical');
prob.v = p_vec';
r.v = r_vec';
h.v = nla.lib.fdr_bh(prob.v);
Expand All@@ -25,7 +35,7 @@ function checkHeadMotion(fig, input_struct, motion)
ulimit = 0.3;

fig = nla.gfx.createFigure(1800, 900);
matrix_plot = nla.gfx.plots.MatrixPlot(fig, "FC-motion correlation (Pearson's r)", r, input_struct.net_atlas.nets,...
matrix_plot = nla.gfx.plots.MatrixPlot(fig, "FC-motion correlation (Pearson's r)", r, network_atlas.nets,...
nla.gfx.FigSize.LARGE, 'lower_limit', llimit, 'upper_limit', ulimit);
matrix_plot.displayImage();
width = matrix_plot.image_dimensions("image_width");
Expand All@@ -35,14 +45,14 @@ function checkHeadMotion(fig, input_struct, motion)

ax = subplot('Position', [0.780, 0.540, 0.20, 0.40]);
nla.gfx.setTitle(ax, sprintf("FC-motion correlation (Pearson's r) (q < 0.05)\n"));
nla.gfx.drawROIsOnCortex(ax, input_struct.net_atlas, ctx, mesh_alpha, ROI_radius, nla.gfx.ViewPos.DORSAL, false,...
nla.gfx.drawROIsOnCortex(ax, network_atlas, ctx, mesh_alpha, ROI_radius, nla.gfx.ViewPos.DORSAL, false,...
nla.gfx.BrainColorMode.NONE);

for col = 1:input_struct.net_atlas.numROIs()
for row = (col + 1):input_struct.net_atlas.numROIs()
for col = 1:network_atlas.numROIs()
for row = (col + 1):network_atlas.numROIs()
if h.get(row, col)
pos1 = input_struct.net_atlas.ROIs(row).pos;
pos2 = input_struct.net_atlas.ROIs(col).pos;
pos1 = network_atlas.ROIs(row).pos;
pos2 = network_atlas.ROIs(col).pos;

edge_color = nla.gfx.valToColor(r.get(row, col), llimit, ulimit, color_map);

Expand Down
33 changes: 22 additions & 11 deletions +nla/+qualityControl/checkNormalityWithKS.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
@@ -1,4 +1,4 @@
function checkNormalityWithKS(fig, input_struct, test_pool)
function checkNormalityWithKS(fig, input_struct, test_pool, remove_index)

prog = uiprogressdlg(...
fig, 'Title', 'Checking Normaility', 'Message', 'Running Kolmogorov-Smirnov Test'...
Expand All@@ -9,33 +9,39 @@ function checkNormalityWithKS(fig, input_struct, test_pool)
edge_test_result = test_pool.runEdgeTest(input_struct);

prog.Value = 0.5;
ks_result = runKolmogorovSmirnovTest(input_struct, edge_test_result);
ks_result = runKolmogorovSmirnovTest(input_struct, edge_test_result, remove_index);

prog.Value = 0.75;
qcKSOutput(ks_result.p, input_struct)
qcKSOutput(ks_result.p, input_struct, remove_index)

end

function ks_result = runKolmogorovSmirnovTest(input_struct, edge_result)
function ks_result = runKolmogorovSmirnovTest(input_struct, edge_result, remove_index)
import nla.TriMatrix nla.TriMatrixDiag

network_atlas = input_struct.net_atlas;
if remove_index ~= 0
[new_netatlas] = nla.removeNetworks(input_struct.net_atlas, input_struct.net_atlas.nets(remove_index).name, strcat(input_struct.net_atlas.name, '_-', input_struct.net_atlas.nets(remove_index).name));
network_atlas = nla.NetworkAtlas(new_netatlas);
end

ks_result = struct();
number_of_networks = input_struct.net_atlas.numNets();
number_of_networks = network_atlas.numNets();
ks_result.p = TriMatrix(number_of_networks, TriMatrixDiag.KEEP_DIAGONAL);
ks_result.ks = TriMatrix(number_of_networks, TriMatrixDiag.KEEP_DIAGONAL);

for network1 = 1:number_of_networks
for network2 = 1:network1
network_rho = edge_result.coeff.get(input_struct.net_atlas.nets(network1).indexes,...
input_struct.net_atlas.nets(network2).indexes);
network_rho = edge_result.coeff.get(network_atlas.nets(network1).indexes,...
network_atlas.nets(network2).indexes);
[~, p, ks] = kstest(network_rho);
ks_result.p.set(network1, network2, p);
ks_result.ks.set(network1, network2, ks);
end
end
end

function qcKSOutput(ks_result_p_value, edge_test_options)
function qcKSOutput(ks_result_p_value, edge_test_options, remove_index)
% This will open the qc figure for the KS test

network_test_options = nla.net.genBaseInputs();
Expand All@@ -45,15 +51,20 @@ function qcKSOutput(ks_result_p_value, edge_test_options)
edge_test_options.prob_max = 0.05;
default_discrete_colors = 1000;

[~, p_value_max] = network_test_options.fdr_correction.correct(edge_test_options.net_atlas,...
edge_test_options, ks_result_p_value);
network_atlas = edge_test_options.net_atlas;
if remove_index ~= 0
[new_netatlas] = nla.removeNetworks(edge_test_options.net_atlas, edge_test_options.net_atlas.nets(remove_index).name, strcat(edge_test_options.net_atlas.name, '-', edge_test_options.net_atlas.nets(remove_index).name));
network_atlas = nla.NetworkAtlas(new_netatlas);
end

[~, p_value_max] = network_test_options.fdr_correction.correct(network_atlas, edge_test_options, ks_result_p_value);

color_map = nla.net.result.NetworkResultPlotParameter.getColormap(default_discrete_colors,...
p_value_max);

fig = nla.gfx.createFigure();
% Also remember to move this in read the docs
matrix_plot = nla.gfx.plots.MatrixPlot(fig, sprintf("Non-permuted Kolmogorov-Smirnov Test p-value\nSmaller values are less normal"), ks_result_p_value, edge_test_options.net_atlas.nets, nla.gfx.FigSize.LARGE,...
matrix_plot = nla.gfx.plots.MatrixPlot(fig, sprintf("Non-permuted Kolmogorov-Smirnov Test p-value\nSmaller values are less normal"), ks_result_p_value, network_atlas.nets, nla.gfx.FigSize.LARGE,...
'lower_limit', 0.00, 'upper_limit', p_value_max, 'color_map', color_map);
matrix_plot.displayImage();
width = matrix_plot.image_dimensions('image_width');
Expand Down
14 changes: 11 additions & 3 deletions +nla/NetworkAtlas.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -12,10 +12,13 @@
% :param space: (Optional) The mesh that the atlas` ROI locations/parcels are in. Two options - ``Talairach (TT)`` or ``Montreal Neurological Institute (MNI)``

properties (SetAccess = private)
nets % This is the net_names

nets
net_names
ROIs
ROI_key
ROI_pos
ROI_order
net_colors
name
space
anat = false;
Expand All@@ -37,14 +40,16 @@
end

net_names = net_struct.net_names;

obj.net_names = net_names;

net_count = numel(net_names);
ROI_count = size(net_struct.ROI_key, 1);

net_colors = turbo(net_count);
if isfield(net_struct, 'net_colors')
net_colors = net_struct.net_colors;
end
obj.net_colors = net_colors;

ROI_positions = zeros(ROI_count, 3);
if isfield(net_struct, 'ROI_pos')
Expand All@@ -60,6 +65,9 @@
net_struct.ROI_order = net_struct.ROI_order(sort_idx);
ROI_positions = ROI_positions(sort_idx, :);
end
obj.ROI_pos = ROI_positions;
obj.ROI_key = net_struct.ROI_key;
obj.ROI_order = net_struct.ROI_order;

%% Network atlas name
obj.name = net_struct.name;
Expand Down
3 changes: 2 additions & 1 deletion +nla/removeNetworks.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -78,7 +78,8 @@

%% Functional connectivity (optional)
if exist('fc_in', 'var')
fc_ordered = fc_in(atlas_in.ROI_order, atlas_in.ROI_order, :);
fc_in_matrix = fc_in.asMatrix();
fc_ordered = fc_in_matrix(atlas_in.ROI_order, atlas_in.ROI_order, :);
fc_reduced = fc_ordered(ROI_mask, ROI_mask, :);
ROI_order_inverse(atlas_out.ROI_order) = [1:numel(atlas_out.ROI_order)]';
fc_out = fc_reduced(ROI_order_inverse, ROI_order_inverse, :);
Expand Down
Binary file modifiedNLAQualityControl.mlapp
View file
Open in desktop
Binary file not shown.
Loading
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all \u003cpre\u003e\u003ccode\u003e blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks"); } } catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); } })(); (function(){ try { var __m = "github.com"; var __re = new RegExp('^' + "github\\.com" + '
Skip to content

[NET-315] In QC window, apply the remove network to all the different methods#159

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
pollaro merged 1 commit into from
Jul 20, 2026
Merged

[NET-315] In QC window, apply the remove network to all the different methods #159

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
34 changes: 22 additions & 12 deletions +nla/+qualityControl/checkHeadMotion.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
@@ -1,14 +1,24 @@
function checkHeadMotion(fig, input_struct, motion)
function checkHeadMotion(fig, input_struct, motion, remove_index)

network_atlas = input_struct.net_atlas;
functional_connectivity = input_struct.func_conn;
if remove_index ~= 0
[new_netatlas, functional_connectivity] = nla.removeNetworks(input_struct.net_atlas, input_struct.net_atlas.nets(remove_index).name, strcat(input_struct.net_atlas.name, '_-', input_struct.net_atlas.nets(remove_index).name), input_struct.func_conn);
network_atlas = nla.NetworkAtlas(new_netatlas);
if ~isa(functional_connectivity, 'nla.TriMatrix')
functional_connectivity = nla.TriMatrix(functional_connectivity);
end
end

prog = uiprogressdlg(fig, 'Title', 'Generating figures', 'Message', 'Generating head motion figures');
prog.Value = 0.02;
distances = nla.helpers.euclidianDistanceROIs(input_struct.net_atlas);
distances = nla.helpers.euclidianDistanceROIs(network_atlas);
prog.Value = 0.75;
[r_vec, p_vec] = corr(motion, input_struct.func_conn.v', 'type', 'Pearson');
[r_vec, p_vec] = corr(motion, functional_connectivity.v', 'type', 'Pearson');

prob = nla.TriMatrix(input_struct.net_atlas.numROIs());
r = nla.TriMatrix(input_struct.net_atlas.numROIs());
h = nla.TriMatrix(input_struct.net_atlas.numROIs(), 'logical');
prob = nla.TriMatrix(network_atlas.numROIs());
r = nla.TriMatrix(network_atlas.numROIs());
h = nla.TriMatrix(network_atlas.numROIs(), 'logical');
prob.v = p_vec';
r.v = r_vec';
h.v = nla.lib.fdr_bh(prob.v);
Expand All@@ -25,7 +35,7 @@ function checkHeadMotion(fig, input_struct, motion)
ulimit = 0.3;

fig = nla.gfx.createFigure(1800, 900);
matrix_plot = nla.gfx.plots.MatrixPlot(fig, "FC-motion correlation (Pearson's r)", r, input_struct.net_atlas.nets,...
matrix_plot = nla.gfx.plots.MatrixPlot(fig, "FC-motion correlation (Pearson's r)", r, network_atlas.nets,...
nla.gfx.FigSize.LARGE, 'lower_limit', llimit, 'upper_limit', ulimit);
matrix_plot.displayImage();
width = matrix_plot.image_dimensions("image_width");
Expand All@@ -35,14 +45,14 @@ function checkHeadMotion(fig, input_struct, motion)

ax = subplot('Position', [0.780, 0.540, 0.20, 0.40]);
nla.gfx.setTitle(ax, sprintf("FC-motion correlation (Pearson's r) (q < 0.05)\n"));
nla.gfx.drawROIsOnCortex(ax, input_struct.net_atlas, ctx, mesh_alpha, ROI_radius, nla.gfx.ViewPos.DORSAL, false,...
nla.gfx.drawROIsOnCortex(ax, network_atlas, ctx, mesh_alpha, ROI_radius, nla.gfx.ViewPos.DORSAL, false,...
nla.gfx.BrainColorMode.NONE);

for col = 1:input_struct.net_atlas.numROIs()
for row = (col + 1):input_struct.net_atlas.numROIs()
for col = 1:network_atlas.numROIs()
for row = (col + 1):network_atlas.numROIs()
if h.get(row, col)
pos1 = input_struct.net_atlas.ROIs(row).pos;
pos2 = input_struct.net_atlas.ROIs(col).pos;
pos1 = network_atlas.ROIs(row).pos;
pos2 = network_atlas.ROIs(col).pos;

edge_color = nla.gfx.valToColor(r.get(row, col), llimit, ulimit, color_map);

Expand Down
33 changes: 22 additions & 11 deletions +nla/+qualityControl/checkNormalityWithKS.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
@@ -1,4 +1,4 @@
function checkNormalityWithKS(fig, input_struct, test_pool)
function checkNormalityWithKS(fig, input_struct, test_pool, remove_index)

prog = uiprogressdlg(...
fig, 'Title', 'Checking Normaility', 'Message', 'Running Kolmogorov-Smirnov Test'...
Expand All@@ -9,33 +9,39 @@ function checkNormalityWithKS(fig, input_struct, test_pool)
edge_test_result = test_pool.runEdgeTest(input_struct);

prog.Value = 0.5;
ks_result = runKolmogorovSmirnovTest(input_struct, edge_test_result);
ks_result = runKolmogorovSmirnovTest(input_struct, edge_test_result, remove_index);

prog.Value = 0.75;
qcKSOutput(ks_result.p, input_struct)
qcKSOutput(ks_result.p, input_struct, remove_index)

end

function ks_result = runKolmogorovSmirnovTest(input_struct, edge_result)
function ks_result = runKolmogorovSmirnovTest(input_struct, edge_result, remove_index)
import nla.TriMatrix nla.TriMatrixDiag

network_atlas = input_struct.net_atlas;
if remove_index ~= 0
[new_netatlas] = nla.removeNetworks(input_struct.net_atlas, input_struct.net_atlas.nets(remove_index).name, strcat(input_struct.net_atlas.name, '_-', input_struct.net_atlas.nets(remove_index).name));
network_atlas = nla.NetworkAtlas(new_netatlas);
end

ks_result = struct();
number_of_networks = input_struct.net_atlas.numNets();
number_of_networks = network_atlas.numNets();
ks_result.p = TriMatrix(number_of_networks, TriMatrixDiag.KEEP_DIAGONAL);
ks_result.ks = TriMatrix(number_of_networks, TriMatrixDiag.KEEP_DIAGONAL);

for network1 = 1:number_of_networks
for network2 = 1:network1
network_rho = edge_result.coeff.get(input_struct.net_atlas.nets(network1).indexes,...
input_struct.net_atlas.nets(network2).indexes);
network_rho = edge_result.coeff.get(network_atlas.nets(network1).indexes,...
network_atlas.nets(network2).indexes);
[~, p, ks] = kstest(network_rho);
ks_result.p.set(network1, network2, p);
ks_result.ks.set(network1, network2, ks);
end
end
end

function qcKSOutput(ks_result_p_value, edge_test_options)
function qcKSOutput(ks_result_p_value, edge_test_options, remove_index)
% This will open the qc figure for the KS test

network_test_options = nla.net.genBaseInputs();
Expand All@@ -45,15 +51,20 @@ function qcKSOutput(ks_result_p_value, edge_test_options)
edge_test_options.prob_max = 0.05;
default_discrete_colors = 1000;

[~, p_value_max] = network_test_options.fdr_correction.correct(edge_test_options.net_atlas,...
edge_test_options, ks_result_p_value);
network_atlas = edge_test_options.net_atlas;
if remove_index ~= 0
[new_netatlas] = nla.removeNetworks(edge_test_options.net_atlas, edge_test_options.net_atlas.nets(remove_index).name, strcat(edge_test_options.net_atlas.name, '-', edge_test_options.net_atlas.nets(remove_index).name));
network_atlas = nla.NetworkAtlas(new_netatlas);
end

[~, p_value_max] = network_test_options.fdr_correction.correct(network_atlas, edge_test_options, ks_result_p_value);

color_map = nla.net.result.NetworkResultPlotParameter.getColormap(default_discrete_colors,...
p_value_max);

fig = nla.gfx.createFigure();
% Also remember to move this in read the docs
matrix_plot = nla.gfx.plots.MatrixPlot(fig, sprintf("Non-permuted Kolmogorov-Smirnov Test p-value\nSmaller values are less normal"), ks_result_p_value, edge_test_options.net_atlas.nets, nla.gfx.FigSize.LARGE,...
matrix_plot = nla.gfx.plots.MatrixPlot(fig, sprintf("Non-permuted Kolmogorov-Smirnov Test p-value\nSmaller values are less normal"), ks_result_p_value, network_atlas.nets, nla.gfx.FigSize.LARGE,...
'lower_limit', 0.00, 'upper_limit', p_value_max, 'color_map', color_map);
matrix_plot.displayImage();
width = matrix_plot.image_dimensions('image_width');
Expand Down
14 changes: 11 additions & 3 deletions +nla/NetworkAtlas.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -12,10 +12,13 @@
% :param space: (Optional) The mesh that the atlas` ROI locations/parcels are in. Two options - ``Talairach (TT)`` or ``Montreal Neurological Institute (MNI)``

properties (SetAccess = private)
nets % This is the net_names

nets
net_names
ROIs
ROI_key
ROI_pos
ROI_order
net_colors
name
space
anat = false;
Expand All@@ -37,14 +40,16 @@
end

net_names = net_struct.net_names;

obj.net_names = net_names;

net_count = numel(net_names);
ROI_count = size(net_struct.ROI_key, 1);

net_colors = turbo(net_count);
if isfield(net_struct, 'net_colors')
net_colors = net_struct.net_colors;
end
obj.net_colors = net_colors;

ROI_positions = zeros(ROI_count, 3);
if isfield(net_struct, 'ROI_pos')
Expand All@@ -60,6 +65,9 @@
net_struct.ROI_order = net_struct.ROI_order(sort_idx);
ROI_positions = ROI_positions(sort_idx, :);
end
obj.ROI_pos = ROI_positions;
obj.ROI_key = net_struct.ROI_key;
obj.ROI_order = net_struct.ROI_order;

%% Network atlas name
obj.name = net_struct.name;
Expand Down
3 changes: 2 additions & 1 deletion +nla/removeNetworks.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -78,7 +78,8 @@

%% Functional connectivity (optional)
if exist('fc_in', 'var')
fc_ordered = fc_in(atlas_in.ROI_order, atlas_in.ROI_order, :);
fc_in_matrix = fc_in.asMatrix();
fc_ordered = fc_in_matrix(atlas_in.ROI_order, atlas_in.ROI_order, :);
fc_reduced = fc_ordered(ROI_mask, ROI_mask, :);
ROI_order_inverse(atlas_out.ROI_order) = [1:numel(atlas_out.ROI_order)]';
fc_out = fc_reduced(ROI_order_inverse, ROI_order_inverse, :);
Expand Down
Binary file modifiedNLAQualityControl.mlapp
View file
Open in desktop
Binary file not shown.
Loading
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix"); } } catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

[NET-315] In QC window, apply the remove network to all the different methods#159

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
pollaro merged 1 commit into from
Jul 20, 2026
Merged

[NET-315] In QC window, apply the remove network to all the different methods #159

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
34 changes: 22 additions & 12 deletions +nla/+qualityControl/checkHeadMotion.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
@@ -1,14 +1,24 @@
function checkHeadMotion(fig, input_struct, motion)
function checkHeadMotion(fig, input_struct, motion, remove_index)

network_atlas = input_struct.net_atlas;
functional_connectivity = input_struct.func_conn;
if remove_index ~= 0
[new_netatlas, functional_connectivity] = nla.removeNetworks(input_struct.net_atlas, input_struct.net_atlas.nets(remove_index).name, strcat(input_struct.net_atlas.name, '_-', input_struct.net_atlas.nets(remove_index).name), input_struct.func_conn);
network_atlas = nla.NetworkAtlas(new_netatlas);
if ~isa(functional_connectivity, 'nla.TriMatrix')
functional_connectivity = nla.TriMatrix(functional_connectivity);
end
end

prog = uiprogressdlg(fig, 'Title', 'Generating figures', 'Message', 'Generating head motion figures');
prog.Value = 0.02;
distances = nla.helpers.euclidianDistanceROIs(input_struct.net_atlas);
distances = nla.helpers.euclidianDistanceROIs(network_atlas);
prog.Value = 0.75;
[r_vec, p_vec] = corr(motion, input_struct.func_conn.v', 'type', 'Pearson');
[r_vec, p_vec] = corr(motion, functional_connectivity.v', 'type', 'Pearson');

prob = nla.TriMatrix(input_struct.net_atlas.numROIs());
r = nla.TriMatrix(input_struct.net_atlas.numROIs());
h = nla.TriMatrix(input_struct.net_atlas.numROIs(), 'logical');
prob = nla.TriMatrix(network_atlas.numROIs());
r = nla.TriMatrix(network_atlas.numROIs());
h = nla.TriMatrix(network_atlas.numROIs(), 'logical');
prob.v = p_vec';
r.v = r_vec';
h.v = nla.lib.fdr_bh(prob.v);
Expand All@@ -25,7 +35,7 @@ function checkHeadMotion(fig, input_struct, motion)
ulimit = 0.3;

fig = nla.gfx.createFigure(1800, 900);
matrix_plot = nla.gfx.plots.MatrixPlot(fig, "FC-motion correlation (Pearson's r)", r, input_struct.net_atlas.nets,...
matrix_plot = nla.gfx.plots.MatrixPlot(fig, "FC-motion correlation (Pearson's r)", r, network_atlas.nets,...
nla.gfx.FigSize.LARGE, 'lower_limit', llimit, 'upper_limit', ulimit);
matrix_plot.displayImage();
width = matrix_plot.image_dimensions("image_width");
Expand All@@ -35,14 +45,14 @@ function checkHeadMotion(fig, input_struct, motion)

ax = subplot('Position', [0.780, 0.540, 0.20, 0.40]);
nla.gfx.setTitle(ax, sprintf("FC-motion correlation (Pearson's r) (q < 0.05)\n"));
nla.gfx.drawROIsOnCortex(ax, input_struct.net_atlas, ctx, mesh_alpha, ROI_radius, nla.gfx.ViewPos.DORSAL, false,...
nla.gfx.drawROIsOnCortex(ax, network_atlas, ctx, mesh_alpha, ROI_radius, nla.gfx.ViewPos.DORSAL, false,...
nla.gfx.BrainColorMode.NONE);

for col = 1:input_struct.net_atlas.numROIs()
for row = (col + 1):input_struct.net_atlas.numROIs()
for col = 1:network_atlas.numROIs()
for row = (col + 1):network_atlas.numROIs()
if h.get(row, col)
pos1 = input_struct.net_atlas.ROIs(row).pos;
pos2 = input_struct.net_atlas.ROIs(col).pos;
pos1 = network_atlas.ROIs(row).pos;
pos2 = network_atlas.ROIs(col).pos;

edge_color = nla.gfx.valToColor(r.get(row, col), llimit, ulimit, color_map);

Expand Down
33 changes: 22 additions & 11 deletions +nla/+qualityControl/checkNormalityWithKS.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
@@ -1,4 +1,4 @@
function checkNormalityWithKS(fig, input_struct, test_pool)
function checkNormalityWithKS(fig, input_struct, test_pool, remove_index)

prog = uiprogressdlg(...
fig, 'Title', 'Checking Normaility', 'Message', 'Running Kolmogorov-Smirnov Test'...
Expand All@@ -9,33 +9,39 @@ function checkNormalityWithKS(fig, input_struct, test_pool)
edge_test_result = test_pool.runEdgeTest(input_struct);

prog.Value = 0.5;
ks_result = runKolmogorovSmirnovTest(input_struct, edge_test_result);
ks_result = runKolmogorovSmirnovTest(input_struct, edge_test_result, remove_index);

prog.Value = 0.75;
qcKSOutput(ks_result.p, input_struct)
qcKSOutput(ks_result.p, input_struct, remove_index)

end

function ks_result = runKolmogorovSmirnovTest(input_struct, edge_result)
function ks_result = runKolmogorovSmirnovTest(input_struct, edge_result, remove_index)
import nla.TriMatrix nla.TriMatrixDiag

network_atlas = input_struct.net_atlas;
if remove_index ~= 0
[new_netatlas] = nla.removeNetworks(input_struct.net_atlas, input_struct.net_atlas.nets(remove_index).name, strcat(input_struct.net_atlas.name, '_-', input_struct.net_atlas.nets(remove_index).name));
network_atlas = nla.NetworkAtlas(new_netatlas);
end

ks_result = struct();
number_of_networks = input_struct.net_atlas.numNets();
number_of_networks = network_atlas.numNets();
ks_result.p = TriMatrix(number_of_networks, TriMatrixDiag.KEEP_DIAGONAL);
ks_result.ks = TriMatrix(number_of_networks, TriMatrixDiag.KEEP_DIAGONAL);

for network1 = 1:number_of_networks
for network2 = 1:network1
network_rho = edge_result.coeff.get(input_struct.net_atlas.nets(network1).indexes,...
input_struct.net_atlas.nets(network2).indexes);
network_rho = edge_result.coeff.get(network_atlas.nets(network1).indexes,...
network_atlas.nets(network2).indexes);
[~, p, ks] = kstest(network_rho);
ks_result.p.set(network1, network2, p);
ks_result.ks.set(network1, network2, ks);
end
end
end

function qcKSOutput(ks_result_p_value, edge_test_options)
function qcKSOutput(ks_result_p_value, edge_test_options, remove_index)
% This will open the qc figure for the KS test

network_test_options = nla.net.genBaseInputs();
Expand All@@ -45,15 +51,20 @@ function qcKSOutput(ks_result_p_value, edge_test_options)
edge_test_options.prob_max = 0.05;
default_discrete_colors = 1000;

[~, p_value_max] = network_test_options.fdr_correction.correct(edge_test_options.net_atlas,...
edge_test_options, ks_result_p_value);
network_atlas = edge_test_options.net_atlas;
if remove_index ~= 0
[new_netatlas] = nla.removeNetworks(edge_test_options.net_atlas, edge_test_options.net_atlas.nets(remove_index).name, strcat(edge_test_options.net_atlas.name, '-', edge_test_options.net_atlas.nets(remove_index).name));
network_atlas = nla.NetworkAtlas(new_netatlas);
end

[~, p_value_max] = network_test_options.fdr_correction.correct(network_atlas, edge_test_options, ks_result_p_value);

color_map = nla.net.result.NetworkResultPlotParameter.getColormap(default_discrete_colors,...
p_value_max);

fig = nla.gfx.createFigure();
% Also remember to move this in read the docs
matrix_plot = nla.gfx.plots.MatrixPlot(fig, sprintf("Non-permuted Kolmogorov-Smirnov Test p-value\nSmaller values are less normal"), ks_result_p_value, edge_test_options.net_atlas.nets, nla.gfx.FigSize.LARGE,...
matrix_plot = nla.gfx.plots.MatrixPlot(fig, sprintf("Non-permuted Kolmogorov-Smirnov Test p-value\nSmaller values are less normal"), ks_result_p_value, network_atlas.nets, nla.gfx.FigSize.LARGE,...
'lower_limit', 0.00, 'upper_limit', p_value_max, 'color_map', color_map);
matrix_plot.displayImage();
width = matrix_plot.image_dimensions('image_width');
Expand Down
14 changes: 11 additions & 3 deletions +nla/NetworkAtlas.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -12,10 +12,13 @@
% :param space: (Optional) The mesh that the atlas` ROI locations/parcels are in. Two options - ``Talairach (TT)`` or ``Montreal Neurological Institute (MNI)``

properties (SetAccess = private)
nets % This is the net_names

nets
net_names
ROIs
ROI_key
ROI_pos
ROI_order
net_colors
name
space
anat = false;
Expand All@@ -37,14 +40,16 @@
end

net_names = net_struct.net_names;

obj.net_names = net_names;

net_count = numel(net_names);
ROI_count = size(net_struct.ROI_key, 1);

net_colors = turbo(net_count);
if isfield(net_struct, 'net_colors')
net_colors = net_struct.net_colors;
end
obj.net_colors = net_colors;

ROI_positions = zeros(ROI_count, 3);
if isfield(net_struct, 'ROI_pos')
Expand All@@ -60,6 +65,9 @@
net_struct.ROI_order = net_struct.ROI_order(sort_idx);
ROI_positions = ROI_positions(sort_idx, :);
end
obj.ROI_pos = ROI_positions;
obj.ROI_key = net_struct.ROI_key;
obj.ROI_order = net_struct.ROI_order;

%% Network atlas name
obj.name = net_struct.name;
Expand Down
3 changes: 2 additions & 1 deletion +nla/removeNetworks.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -78,7 +78,8 @@

%% Functional connectivity (optional)
if exist('fc_in', 'var')
fc_ordered = fc_in(atlas_in.ROI_order, atlas_in.ROI_order, :);
fc_in_matrix = fc_in.asMatrix();
fc_ordered = fc_in_matrix(atlas_in.ROI_order, atlas_in.ROI_order, :);
fc_reduced = fc_ordered(ROI_mask, ROI_mask, :);
ROI_order_inverse(atlas_out.ROI_order) = [1:numel(atlas_out.ROI_order)]';
fc_out = fc_reduced(ROI_order_inverse, ROI_order_inverse, :);
Expand Down
Binary file modifiedNLAQualityControl.mlapp
View file
Open in desktop
Binary file not shown.
Loading
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length \u003e 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms"); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

[NET-315] In QC window, apply the remove network to all the different methods#159

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
pollaro merged 1 commit into from
Jul 20, 2026
Merged

[NET-315] In QC window, apply the remove network to all the different methods #159

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
34 changes: 22 additions & 12 deletions +nla/+qualityControl/checkHeadMotion.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
@@ -1,14 +1,24 @@
function checkHeadMotion(fig, input_struct, motion)
function checkHeadMotion(fig, input_struct, motion, remove_index)

network_atlas = input_struct.net_atlas;
functional_connectivity = input_struct.func_conn;
if remove_index ~= 0
[new_netatlas, functional_connectivity] = nla.removeNetworks(input_struct.net_atlas, input_struct.net_atlas.nets(remove_index).name, strcat(input_struct.net_atlas.name, '_-', input_struct.net_atlas.nets(remove_index).name), input_struct.func_conn);
network_atlas = nla.NetworkAtlas(new_netatlas);
if ~isa(functional_connectivity, 'nla.TriMatrix')
functional_connectivity = nla.TriMatrix(functional_connectivity);
end
end

prog = uiprogressdlg(fig, 'Title', 'Generating figures', 'Message', 'Generating head motion figures');
prog.Value = 0.02;
distances = nla.helpers.euclidianDistanceROIs(input_struct.net_atlas);
distances = nla.helpers.euclidianDistanceROIs(network_atlas);
prog.Value = 0.75;
[r_vec, p_vec] = corr(motion, input_struct.func_conn.v', 'type', 'Pearson');
[r_vec, p_vec] = corr(motion, functional_connectivity.v', 'type', 'Pearson');

prob = nla.TriMatrix(input_struct.net_atlas.numROIs());
r = nla.TriMatrix(input_struct.net_atlas.numROIs());
h = nla.TriMatrix(input_struct.net_atlas.numROIs(), 'logical');
prob = nla.TriMatrix(network_atlas.numROIs());
r = nla.TriMatrix(network_atlas.numROIs());
h = nla.TriMatrix(network_atlas.numROIs(), 'logical');
prob.v = p_vec';
r.v = r_vec';
h.v = nla.lib.fdr_bh(prob.v);
Expand All@@ -25,7 +35,7 @@ function checkHeadMotion(fig, input_struct, motion)
ulimit = 0.3;

fig = nla.gfx.createFigure(1800, 900);
matrix_plot = nla.gfx.plots.MatrixPlot(fig, "FC-motion correlation (Pearson's r)", r, input_struct.net_atlas.nets,...
matrix_plot = nla.gfx.plots.MatrixPlot(fig, "FC-motion correlation (Pearson's r)", r, network_atlas.nets,...
nla.gfx.FigSize.LARGE, 'lower_limit', llimit, 'upper_limit', ulimit);
matrix_plot.displayImage();
width = matrix_plot.image_dimensions("image_width");
Expand All@@ -35,14 +45,14 @@ function checkHeadMotion(fig, input_struct, motion)

ax = subplot('Position', [0.780, 0.540, 0.20, 0.40]);
nla.gfx.setTitle(ax, sprintf("FC-motion correlation (Pearson's r) (q < 0.05)\n"));
nla.gfx.drawROIsOnCortex(ax, input_struct.net_atlas, ctx, mesh_alpha, ROI_radius, nla.gfx.ViewPos.DORSAL, false,...
nla.gfx.drawROIsOnCortex(ax, network_atlas, ctx, mesh_alpha, ROI_radius, nla.gfx.ViewPos.DORSAL, false,...
nla.gfx.BrainColorMode.NONE);

for col = 1:input_struct.net_atlas.numROIs()
for row = (col + 1):input_struct.net_atlas.numROIs()
for col = 1:network_atlas.numROIs()
for row = (col + 1):network_atlas.numROIs()
if h.get(row, col)
pos1 = input_struct.net_atlas.ROIs(row).pos;
pos2 = input_struct.net_atlas.ROIs(col).pos;
pos1 = network_atlas.ROIs(row).pos;
pos2 = network_atlas.ROIs(col).pos;

edge_color = nla.gfx.valToColor(r.get(row, col), llimit, ulimit, color_map);

Expand Down
33 changes: 22 additions & 11 deletions +nla/+qualityControl/checkNormalityWithKS.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
@@ -1,4 +1,4 @@
function checkNormalityWithKS(fig, input_struct, test_pool)
function checkNormalityWithKS(fig, input_struct, test_pool, remove_index)

prog = uiprogressdlg(...
fig, 'Title', 'Checking Normaility', 'Message', 'Running Kolmogorov-Smirnov Test'...
Expand All@@ -9,33 +9,39 @@ function checkNormalityWithKS(fig, input_struct, test_pool)
edge_test_result = test_pool.runEdgeTest(input_struct);

prog.Value = 0.5;
ks_result = runKolmogorovSmirnovTest(input_struct, edge_test_result);
ks_result = runKolmogorovSmirnovTest(input_struct, edge_test_result, remove_index);

prog.Value = 0.75;
qcKSOutput(ks_result.p, input_struct)
qcKSOutput(ks_result.p, input_struct, remove_index)

end

function ks_result = runKolmogorovSmirnovTest(input_struct, edge_result)
function ks_result = runKolmogorovSmirnovTest(input_struct, edge_result, remove_index)
import nla.TriMatrix nla.TriMatrixDiag

network_atlas = input_struct.net_atlas;
if remove_index ~= 0
[new_netatlas] = nla.removeNetworks(input_struct.net_atlas, input_struct.net_atlas.nets(remove_index).name, strcat(input_struct.net_atlas.name, '_-', input_struct.net_atlas.nets(remove_index).name));
network_atlas = nla.NetworkAtlas(new_netatlas);
end

ks_result = struct();
number_of_networks = input_struct.net_atlas.numNets();
number_of_networks = network_atlas.numNets();
ks_result.p = TriMatrix(number_of_networks, TriMatrixDiag.KEEP_DIAGONAL);
ks_result.ks = TriMatrix(number_of_networks, TriMatrixDiag.KEEP_DIAGONAL);

for network1 = 1:number_of_networks
for network2 = 1:network1
network_rho = edge_result.coeff.get(input_struct.net_atlas.nets(network1).indexes,...
input_struct.net_atlas.nets(network2).indexes);
network_rho = edge_result.coeff.get(network_atlas.nets(network1).indexes,...
network_atlas.nets(network2).indexes);
[~, p, ks] = kstest(network_rho);
ks_result.p.set(network1, network2, p);
ks_result.ks.set(network1, network2, ks);
end
end
end

function qcKSOutput(ks_result_p_value, edge_test_options)
function qcKSOutput(ks_result_p_value, edge_test_options, remove_index)
% This will open the qc figure for the KS test

network_test_options = nla.net.genBaseInputs();
Expand All@@ -45,15 +51,20 @@ function qcKSOutput(ks_result_p_value, edge_test_options)
edge_test_options.prob_max = 0.05;
default_discrete_colors = 1000;

[~, p_value_max] = network_test_options.fdr_correction.correct(edge_test_options.net_atlas,...
edge_test_options, ks_result_p_value);
network_atlas = edge_test_options.net_atlas;
if remove_index ~= 0
[new_netatlas] = nla.removeNetworks(edge_test_options.net_atlas, edge_test_options.net_atlas.nets(remove_index).name, strcat(edge_test_options.net_atlas.name, '-', edge_test_options.net_atlas.nets(remove_index).name));
network_atlas = nla.NetworkAtlas(new_netatlas);
end

[~, p_value_max] = network_test_options.fdr_correction.correct(network_atlas, edge_test_options, ks_result_p_value);

color_map = nla.net.result.NetworkResultPlotParameter.getColormap(default_discrete_colors,...
p_value_max);

fig = nla.gfx.createFigure();
% Also remember to move this in read the docs
matrix_plot = nla.gfx.plots.MatrixPlot(fig, sprintf("Non-permuted Kolmogorov-Smirnov Test p-value\nSmaller values are less normal"), ks_result_p_value, edge_test_options.net_atlas.nets, nla.gfx.FigSize.LARGE,...
matrix_plot = nla.gfx.plots.MatrixPlot(fig, sprintf("Non-permuted Kolmogorov-Smirnov Test p-value\nSmaller values are less normal"), ks_result_p_value, network_atlas.nets, nla.gfx.FigSize.LARGE,...
'lower_limit', 0.00, 'upper_limit', p_value_max, 'color_map', color_map);
matrix_plot.displayImage();
width = matrix_plot.image_dimensions('image_width');
Expand Down
14 changes: 11 additions & 3 deletions +nla/NetworkAtlas.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -12,10 +12,13 @@
% :param space: (Optional) The mesh that the atlas` ROI locations/parcels are in. Two options - ``Talairach (TT)`` or ``Montreal Neurological Institute (MNI)``

properties (SetAccess = private)
nets % This is the net_names

nets
net_names
ROIs
ROI_key
ROI_pos
ROI_order
net_colors
name
space
anat = false;
Expand All@@ -37,14 +40,16 @@
end

net_names = net_struct.net_names;

obj.net_names = net_names;

net_count = numel(net_names);
ROI_count = size(net_struct.ROI_key, 1);

net_colors = turbo(net_count);
if isfield(net_struct, 'net_colors')
net_colors = net_struct.net_colors;
end
obj.net_colors = net_colors;

ROI_positions = zeros(ROI_count, 3);
if isfield(net_struct, 'ROI_pos')
Expand All@@ -60,6 +65,9 @@
net_struct.ROI_order = net_struct.ROI_order(sort_idx);
ROI_positions = ROI_positions(sort_idx, :);
end
obj.ROI_pos = ROI_positions;
obj.ROI_key = net_struct.ROI_key;
obj.ROI_order = net_struct.ROI_order;

%% Network atlas name
obj.name = net_struct.name;
Expand Down
3 changes: 2 additions & 1 deletion +nla/removeNetworks.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -78,7 +78,8 @@

%% Functional connectivity (optional)
if exist('fc_in', 'var')
fc_ordered = fc_in(atlas_in.ROI_order, atlas_in.ROI_order, :);
fc_in_matrix = fc_in.asMatrix();
fc_ordered = fc_in_matrix(atlas_in.ROI_order, atlas_in.ROI_order, :);
fc_reduced = fc_ordered(ROI_mask, ROI_mask, :);
ROI_order_inverse(atlas_out.ROI_order) = [1:numel(atlas_out.ROI_order)]';
fc_out = fc_reduced(ROI_order_inverse, ROI_order_inverse, :);
Expand Down
Binary file modifiedNLAQualityControl.mlapp
View file
Open in desktop
Binary file not shown.
Loading
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links"); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + '
Skip to content

[NET-315] In QC window, apply the remove network to all the different methods#159

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
pollaro merged 1 commit into from
Jul 20, 2026
Merged

[NET-315] In QC window, apply the remove network to all the different methods #159

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
34 changes: 22 additions & 12 deletions +nla/+qualityControl/checkHeadMotion.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
@@ -1,14 +1,24 @@
function checkHeadMotion(fig, input_struct, motion)
function checkHeadMotion(fig, input_struct, motion, remove_index)

network_atlas = input_struct.net_atlas;
functional_connectivity = input_struct.func_conn;
if remove_index ~= 0
[new_netatlas, functional_connectivity] = nla.removeNetworks(input_struct.net_atlas, input_struct.net_atlas.nets(remove_index).name, strcat(input_struct.net_atlas.name, '_-', input_struct.net_atlas.nets(remove_index).name), input_struct.func_conn);
network_atlas = nla.NetworkAtlas(new_netatlas);
if ~isa(functional_connectivity, 'nla.TriMatrix')
functional_connectivity = nla.TriMatrix(functional_connectivity);
end
end

prog = uiprogressdlg(fig, 'Title', 'Generating figures', 'Message', 'Generating head motion figures');
prog.Value = 0.02;
distances = nla.helpers.euclidianDistanceROIs(input_struct.net_atlas);
distances = nla.helpers.euclidianDistanceROIs(network_atlas);
prog.Value = 0.75;
[r_vec, p_vec] = corr(motion, input_struct.func_conn.v', 'type', 'Pearson');
[r_vec, p_vec] = corr(motion, functional_connectivity.v', 'type', 'Pearson');

prob = nla.TriMatrix(input_struct.net_atlas.numROIs());
r = nla.TriMatrix(input_struct.net_atlas.numROIs());
h = nla.TriMatrix(input_struct.net_atlas.numROIs(), 'logical');
prob = nla.TriMatrix(network_atlas.numROIs());
r = nla.TriMatrix(network_atlas.numROIs());
h = nla.TriMatrix(network_atlas.numROIs(), 'logical');
prob.v = p_vec';
r.v = r_vec';
h.v = nla.lib.fdr_bh(prob.v);
Expand All@@ -25,7 +35,7 @@ function checkHeadMotion(fig, input_struct, motion)
ulimit = 0.3;

fig = nla.gfx.createFigure(1800, 900);
matrix_plot = nla.gfx.plots.MatrixPlot(fig, "FC-motion correlation (Pearson's r)", r, input_struct.net_atlas.nets,...
matrix_plot = nla.gfx.plots.MatrixPlot(fig, "FC-motion correlation (Pearson's r)", r, network_atlas.nets,...
nla.gfx.FigSize.LARGE, 'lower_limit', llimit, 'upper_limit', ulimit);
matrix_plot.displayImage();
width = matrix_plot.image_dimensions("image_width");
Expand All@@ -35,14 +45,14 @@ function checkHeadMotion(fig, input_struct, motion)

ax = subplot('Position', [0.780, 0.540, 0.20, 0.40]);
nla.gfx.setTitle(ax, sprintf("FC-motion correlation (Pearson's r) (q < 0.05)\n"));
nla.gfx.drawROIsOnCortex(ax, input_struct.net_atlas, ctx, mesh_alpha, ROI_radius, nla.gfx.ViewPos.DORSAL, false,...
nla.gfx.drawROIsOnCortex(ax, network_atlas, ctx, mesh_alpha, ROI_radius, nla.gfx.ViewPos.DORSAL, false,...
nla.gfx.BrainColorMode.NONE);

for col = 1:input_struct.net_atlas.numROIs()
for row = (col + 1):input_struct.net_atlas.numROIs()
for col = 1:network_atlas.numROIs()
for row = (col + 1):network_atlas.numROIs()
if h.get(row, col)
pos1 = input_struct.net_atlas.ROIs(row).pos;
pos2 = input_struct.net_atlas.ROIs(col).pos;
pos1 = network_atlas.ROIs(row).pos;
pos2 = network_atlas.ROIs(col).pos;

edge_color = nla.gfx.valToColor(r.get(row, col), llimit, ulimit, color_map);

Expand Down
33 changes: 22 additions & 11 deletions +nla/+qualityControl/checkNormalityWithKS.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
@@ -1,4 +1,4 @@
function checkNormalityWithKS(fig, input_struct, test_pool)
function checkNormalityWithKS(fig, input_struct, test_pool, remove_index)

prog = uiprogressdlg(...
fig, 'Title', 'Checking Normaility', 'Message', 'Running Kolmogorov-Smirnov Test'...
Expand All@@ -9,33 +9,39 @@ function checkNormalityWithKS(fig, input_struct, test_pool)
edge_test_result = test_pool.runEdgeTest(input_struct);

prog.Value = 0.5;
ks_result = runKolmogorovSmirnovTest(input_struct, edge_test_result);
ks_result = runKolmogorovSmirnovTest(input_struct, edge_test_result, remove_index);

prog.Value = 0.75;
qcKSOutput(ks_result.p, input_struct)
qcKSOutput(ks_result.p, input_struct, remove_index)

end

function ks_result = runKolmogorovSmirnovTest(input_struct, edge_result)
function ks_result = runKolmogorovSmirnovTest(input_struct, edge_result, remove_index)
import nla.TriMatrix nla.TriMatrixDiag

network_atlas = input_struct.net_atlas;
if remove_index ~= 0
[new_netatlas] = nla.removeNetworks(input_struct.net_atlas, input_struct.net_atlas.nets(remove_index).name, strcat(input_struct.net_atlas.name, '_-', input_struct.net_atlas.nets(remove_index).name));
network_atlas = nla.NetworkAtlas(new_netatlas);
end

ks_result = struct();
number_of_networks = input_struct.net_atlas.numNets();
number_of_networks = network_atlas.numNets();
ks_result.p = TriMatrix(number_of_networks, TriMatrixDiag.KEEP_DIAGONAL);
ks_result.ks = TriMatrix(number_of_networks, TriMatrixDiag.KEEP_DIAGONAL);

for network1 = 1:number_of_networks
for network2 = 1:network1
network_rho = edge_result.coeff.get(input_struct.net_atlas.nets(network1).indexes,...
input_struct.net_atlas.nets(network2).indexes);
network_rho = edge_result.coeff.get(network_atlas.nets(network1).indexes,...
network_atlas.nets(network2).indexes);
[~, p, ks] = kstest(network_rho);
ks_result.p.set(network1, network2, p);
ks_result.ks.set(network1, network2, ks);
end
end
end

function qcKSOutput(ks_result_p_value, edge_test_options)
function qcKSOutput(ks_result_p_value, edge_test_options, remove_index)
% This will open the qc figure for the KS test

network_test_options = nla.net.genBaseInputs();
Expand All@@ -45,15 +51,20 @@ function qcKSOutput(ks_result_p_value, edge_test_options)
edge_test_options.prob_max = 0.05;
default_discrete_colors = 1000;

[~, p_value_max] = network_test_options.fdr_correction.correct(edge_test_options.net_atlas,...
edge_test_options, ks_result_p_value);
network_atlas = edge_test_options.net_atlas;
if remove_index ~= 0
[new_netatlas] = nla.removeNetworks(edge_test_options.net_atlas, edge_test_options.net_atlas.nets(remove_index).name, strcat(edge_test_options.net_atlas.name, '-', edge_test_options.net_atlas.nets(remove_index).name));
network_atlas = nla.NetworkAtlas(new_netatlas);
end

[~, p_value_max] = network_test_options.fdr_correction.correct(network_atlas, edge_test_options, ks_result_p_value);

color_map = nla.net.result.NetworkResultPlotParameter.getColormap(default_discrete_colors,...
p_value_max);

fig = nla.gfx.createFigure();
% Also remember to move this in read the docs
matrix_plot = nla.gfx.plots.MatrixPlot(fig, sprintf("Non-permuted Kolmogorov-Smirnov Test p-value\nSmaller values are less normal"), ks_result_p_value, edge_test_options.net_atlas.nets, nla.gfx.FigSize.LARGE,...
matrix_plot = nla.gfx.plots.MatrixPlot(fig, sprintf("Non-permuted Kolmogorov-Smirnov Test p-value\nSmaller values are less normal"), ks_result_p_value, network_atlas.nets, nla.gfx.FigSize.LARGE,...
'lower_limit', 0.00, 'upper_limit', p_value_max, 'color_map', color_map);
matrix_plot.displayImage();
width = matrix_plot.image_dimensions('image_width');
Expand Down
14 changes: 11 additions & 3 deletions +nla/NetworkAtlas.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -12,10 +12,13 @@
% :param space: (Optional) The mesh that the atlas` ROI locations/parcels are in. Two options - ``Talairach (TT)`` or ``Montreal Neurological Institute (MNI)``

properties (SetAccess = private)
nets % This is the net_names

nets
net_names
ROIs
ROI_key
ROI_pos
ROI_order
net_colors
name
space
anat = false;
Expand All@@ -37,14 +40,16 @@
end

net_names = net_struct.net_names;

obj.net_names = net_names;

net_count = numel(net_names);
ROI_count = size(net_struct.ROI_key, 1);

net_colors = turbo(net_count);
if isfield(net_struct, 'net_colors')
net_colors = net_struct.net_colors;
end
obj.net_colors = net_colors;

ROI_positions = zeros(ROI_count, 3);
if isfield(net_struct, 'ROI_pos')
Expand All@@ -60,6 +65,9 @@
net_struct.ROI_order = net_struct.ROI_order(sort_idx);
ROI_positions = ROI_positions(sort_idx, :);
end
obj.ROI_pos = ROI_positions;
obj.ROI_key = net_struct.ROI_key;
obj.ROI_order = net_struct.ROI_order;

%% Network atlas name
obj.name = net_struct.name;
Expand Down
3 changes: 2 additions & 1 deletion +nla/removeNetworks.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -78,7 +78,8 @@

%% Functional connectivity (optional)
if exist('fc_in', 'var')
fc_ordered = fc_in(atlas_in.ROI_order, atlas_in.ROI_order, :);
fc_in_matrix = fc_in.asMatrix();
fc_ordered = fc_in_matrix(atlas_in.ROI_order, atlas_in.ROI_order, :);
fc_reduced = fc_ordered(ROI_mask, ROI_mask, :);
ROI_order_inverse(atlas_out.ROI_order) = [1:numel(atlas_out.ROI_order)]';
fc_out = fc_reduced(ROI_order_inverse, ROI_order_inverse, :);
Expand Down
Binary file modifiedNLAQualityControl.mlapp
View file
Open in desktop
Binary file not shown.
Loading
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default"); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

[NET-315] In QC window, apply the remove network to all the different methods#159

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
pollaro merged 1 commit into from
Jul 20, 2026
Merged

[NET-315] In QC window, apply the remove network to all the different methods #159

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
34 changes: 22 additions & 12 deletions +nla/+qualityControl/checkHeadMotion.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
@@ -1,14 +1,24 @@
function checkHeadMotion(fig, input_struct, motion)
function checkHeadMotion(fig, input_struct, motion, remove_index)

network_atlas = input_struct.net_atlas;
functional_connectivity = input_struct.func_conn;
if remove_index ~= 0
[new_netatlas, functional_connectivity] = nla.removeNetworks(input_struct.net_atlas, input_struct.net_atlas.nets(remove_index).name, strcat(input_struct.net_atlas.name, '_-', input_struct.net_atlas.nets(remove_index).name), input_struct.func_conn);
network_atlas = nla.NetworkAtlas(new_netatlas);
if ~isa(functional_connectivity, 'nla.TriMatrix')
functional_connectivity = nla.TriMatrix(functional_connectivity);
end
end

prog = uiprogressdlg(fig, 'Title', 'Generating figures', 'Message', 'Generating head motion figures');
prog.Value = 0.02;
distances = nla.helpers.euclidianDistanceROIs(input_struct.net_atlas);
distances = nla.helpers.euclidianDistanceROIs(network_atlas);
prog.Value = 0.75;
[r_vec, p_vec] = corr(motion, input_struct.func_conn.v', 'type', 'Pearson');
[r_vec, p_vec] = corr(motion, functional_connectivity.v', 'type', 'Pearson');

prob = nla.TriMatrix(input_struct.net_atlas.numROIs());
r = nla.TriMatrix(input_struct.net_atlas.numROIs());
h = nla.TriMatrix(input_struct.net_atlas.numROIs(), 'logical');
prob = nla.TriMatrix(network_atlas.numROIs());
r = nla.TriMatrix(network_atlas.numROIs());
h = nla.TriMatrix(network_atlas.numROIs(), 'logical');
prob.v = p_vec';
r.v = r_vec';
h.v = nla.lib.fdr_bh(prob.v);
Expand All@@ -25,7 +35,7 @@ function checkHeadMotion(fig, input_struct, motion)
ulimit = 0.3;

fig = nla.gfx.createFigure(1800, 900);
matrix_plot = nla.gfx.plots.MatrixPlot(fig, "FC-motion correlation (Pearson's r)", r, input_struct.net_atlas.nets,...
matrix_plot = nla.gfx.plots.MatrixPlot(fig, "FC-motion correlation (Pearson's r)", r, network_atlas.nets,...
nla.gfx.FigSize.LARGE, 'lower_limit', llimit, 'upper_limit', ulimit);
matrix_plot.displayImage();
width = matrix_plot.image_dimensions("image_width");
Expand All@@ -35,14 +45,14 @@ function checkHeadMotion(fig, input_struct, motion)

ax = subplot('Position', [0.780, 0.540, 0.20, 0.40]);
nla.gfx.setTitle(ax, sprintf("FC-motion correlation (Pearson's r) (q < 0.05)\n"));
nla.gfx.drawROIsOnCortex(ax, input_struct.net_atlas, ctx, mesh_alpha, ROI_radius, nla.gfx.ViewPos.DORSAL, false,...
nla.gfx.drawROIsOnCortex(ax, network_atlas, ctx, mesh_alpha, ROI_radius, nla.gfx.ViewPos.DORSAL, false,...
nla.gfx.BrainColorMode.NONE);

for col = 1:input_struct.net_atlas.numROIs()
for row = (col + 1):input_struct.net_atlas.numROIs()
for col = 1:network_atlas.numROIs()
for row = (col + 1):network_atlas.numROIs()
if h.get(row, col)
pos1 = input_struct.net_atlas.ROIs(row).pos;
pos2 = input_struct.net_atlas.ROIs(col).pos;
pos1 = network_atlas.ROIs(row).pos;
pos2 = network_atlas.ROIs(col).pos;

edge_color = nla.gfx.valToColor(r.get(row, col), llimit, ulimit, color_map);

Expand Down
33 changes: 22 additions & 11 deletions +nla/+qualityControl/checkNormalityWithKS.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
@@ -1,4 +1,4 @@
function checkNormalityWithKS(fig, input_struct, test_pool)
function checkNormalityWithKS(fig, input_struct, test_pool, remove_index)

prog = uiprogressdlg(...
fig, 'Title', 'Checking Normaility', 'Message', 'Running Kolmogorov-Smirnov Test'...
Expand All@@ -9,33 +9,39 @@ function checkNormalityWithKS(fig, input_struct, test_pool)
edge_test_result = test_pool.runEdgeTest(input_struct);

prog.Value = 0.5;
ks_result = runKolmogorovSmirnovTest(input_struct, edge_test_result);
ks_result = runKolmogorovSmirnovTest(input_struct, edge_test_result, remove_index);

prog.Value = 0.75;
qcKSOutput(ks_result.p, input_struct)
qcKSOutput(ks_result.p, input_struct, remove_index)

end

function ks_result = runKolmogorovSmirnovTest(input_struct, edge_result)
function ks_result = runKolmogorovSmirnovTest(input_struct, edge_result, remove_index)
import nla.TriMatrix nla.TriMatrixDiag

network_atlas = input_struct.net_atlas;
if remove_index ~= 0
[new_netatlas] = nla.removeNetworks(input_struct.net_atlas, input_struct.net_atlas.nets(remove_index).name, strcat(input_struct.net_atlas.name, '_-', input_struct.net_atlas.nets(remove_index).name));
network_atlas = nla.NetworkAtlas(new_netatlas);
end

ks_result = struct();
number_of_networks = input_struct.net_atlas.numNets();
number_of_networks = network_atlas.numNets();
ks_result.p = TriMatrix(number_of_networks, TriMatrixDiag.KEEP_DIAGONAL);
ks_result.ks = TriMatrix(number_of_networks, TriMatrixDiag.KEEP_DIAGONAL);

for network1 = 1:number_of_networks
for network2 = 1:network1
network_rho = edge_result.coeff.get(input_struct.net_atlas.nets(network1).indexes,...
input_struct.net_atlas.nets(network2).indexes);
network_rho = edge_result.coeff.get(network_atlas.nets(network1).indexes,...
network_atlas.nets(network2).indexes);
[~, p, ks] = kstest(network_rho);
ks_result.p.set(network1, network2, p);
ks_result.ks.set(network1, network2, ks);
end
end
end

function qcKSOutput(ks_result_p_value, edge_test_options)
function qcKSOutput(ks_result_p_value, edge_test_options, remove_index)
% This will open the qc figure for the KS test

network_test_options = nla.net.genBaseInputs();
Expand All@@ -45,15 +51,20 @@ function qcKSOutput(ks_result_p_value, edge_test_options)
edge_test_options.prob_max = 0.05;
default_discrete_colors = 1000;

[~, p_value_max] = network_test_options.fdr_correction.correct(edge_test_options.net_atlas,...
edge_test_options, ks_result_p_value);
network_atlas = edge_test_options.net_atlas;
if remove_index ~= 0
[new_netatlas] = nla.removeNetworks(edge_test_options.net_atlas, edge_test_options.net_atlas.nets(remove_index).name, strcat(edge_test_options.net_atlas.name, '-', edge_test_options.net_atlas.nets(remove_index).name));
network_atlas = nla.NetworkAtlas(new_netatlas);
end

[~, p_value_max] = network_test_options.fdr_correction.correct(network_atlas, edge_test_options, ks_result_p_value);

color_map = nla.net.result.NetworkResultPlotParameter.getColormap(default_discrete_colors,...
p_value_max);

fig = nla.gfx.createFigure();
% Also remember to move this in read the docs
matrix_plot = nla.gfx.plots.MatrixPlot(fig, sprintf("Non-permuted Kolmogorov-Smirnov Test p-value\nSmaller values are less normal"), ks_result_p_value, edge_test_options.net_atlas.nets, nla.gfx.FigSize.LARGE,...
matrix_plot = nla.gfx.plots.MatrixPlot(fig, sprintf("Non-permuted Kolmogorov-Smirnov Test p-value\nSmaller values are less normal"), ks_result_p_value, network_atlas.nets, nla.gfx.FigSize.LARGE,...
'lower_limit', 0.00, 'upper_limit', p_value_max, 'color_map', color_map);
matrix_plot.displayImage();
width = matrix_plot.image_dimensions('image_width');
Expand Down
14 changes: 11 additions & 3 deletions +nla/NetworkAtlas.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -12,10 +12,13 @@
% :param space: (Optional) The mesh that the atlas` ROI locations/parcels are in. Two options - ``Talairach (TT)`` or ``Montreal Neurological Institute (MNI)``

properties (SetAccess = private)
nets % This is the net_names

nets
net_names
ROIs
ROI_key
ROI_pos
ROI_order
net_colors
name
space
anat = false;
Expand All@@ -37,14 +40,16 @@
end

net_names = net_struct.net_names;

obj.net_names = net_names;

net_count = numel(net_names);
ROI_count = size(net_struct.ROI_key, 1);

net_colors = turbo(net_count);
if isfield(net_struct, 'net_colors')
net_colors = net_struct.net_colors;
end
obj.net_colors = net_colors;

ROI_positions = zeros(ROI_count, 3);
if isfield(net_struct, 'ROI_pos')
Expand All@@ -60,6 +65,9 @@
net_struct.ROI_order = net_struct.ROI_order(sort_idx);
ROI_positions = ROI_positions(sort_idx, :);
end
obj.ROI_pos = ROI_positions;
obj.ROI_key = net_struct.ROI_key;
obj.ROI_order = net_struct.ROI_order;

%% Network atlas name
obj.name = net_struct.name;
Expand Down
3 changes: 2 additions & 1 deletion +nla/removeNetworks.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -78,7 +78,8 @@

%% Functional connectivity (optional)
if exist('fc_in', 'var')
fc_ordered = fc_in(atlas_in.ROI_order, atlas_in.ROI_order, :);
fc_in_matrix = fc_in.asMatrix();
fc_ordered = fc_in_matrix(atlas_in.ROI_order, atlas_in.ROI_order, :);
fc_reduced = fc_ordered(ROI_mask, ROI_mask, :);
ROI_order_inverse(atlas_out.ROI_order) = [1:numel(atlas_out.ROI_order)]';
fc_out = fc_reduced(ROI_order_inverse, ROI_order_inverse, :);
Expand Down
Binary file modifiedNLAQualityControl.mlapp
View file
Open in desktop
Binary file not shown.
Loading
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers"); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

[NET-315] In QC window, apply the remove network to all the different methods#159

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
pollaro merged 1 commit into from
Jul 20, 2026
Merged

[NET-315] In QC window, apply the remove network to all the different methods #159

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
34 changes: 22 additions & 12 deletions +nla/+qualityControl/checkHeadMotion.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
@@ -1,14 +1,24 @@
function checkHeadMotion(fig, input_struct, motion)
function checkHeadMotion(fig, input_struct, motion, remove_index)

network_atlas = input_struct.net_atlas;
functional_connectivity = input_struct.func_conn;
if remove_index ~= 0
[new_netatlas, functional_connectivity] = nla.removeNetworks(input_struct.net_atlas, input_struct.net_atlas.nets(remove_index).name, strcat(input_struct.net_atlas.name, '_-', input_struct.net_atlas.nets(remove_index).name), input_struct.func_conn);
network_atlas = nla.NetworkAtlas(new_netatlas);
if ~isa(functional_connectivity, 'nla.TriMatrix')
functional_connectivity = nla.TriMatrix(functional_connectivity);
end
end

prog = uiprogressdlg(fig, 'Title', 'Generating figures', 'Message', 'Generating head motion figures');
prog.Value = 0.02;
distances = nla.helpers.euclidianDistanceROIs(input_struct.net_atlas);
distances = nla.helpers.euclidianDistanceROIs(network_atlas);
prog.Value = 0.75;
[r_vec, p_vec] = corr(motion, input_struct.func_conn.v', 'type', 'Pearson');
[r_vec, p_vec] = corr(motion, functional_connectivity.v', 'type', 'Pearson');

prob = nla.TriMatrix(input_struct.net_atlas.numROIs());
r = nla.TriMatrix(input_struct.net_atlas.numROIs());
h = nla.TriMatrix(input_struct.net_atlas.numROIs(), 'logical');
prob = nla.TriMatrix(network_atlas.numROIs());
r = nla.TriMatrix(network_atlas.numROIs());
h = nla.TriMatrix(network_atlas.numROIs(), 'logical');
prob.v = p_vec';
r.v = r_vec';
h.v = nla.lib.fdr_bh(prob.v);
Expand All@@ -25,7 +35,7 @@ function checkHeadMotion(fig, input_struct, motion)
ulimit = 0.3;

fig = nla.gfx.createFigure(1800, 900);
matrix_plot = nla.gfx.plots.MatrixPlot(fig, "FC-motion correlation (Pearson's r)", r, input_struct.net_atlas.nets,...
matrix_plot = nla.gfx.plots.MatrixPlot(fig, "FC-motion correlation (Pearson's r)", r, network_atlas.nets,...
nla.gfx.FigSize.LARGE, 'lower_limit', llimit, 'upper_limit', ulimit);
matrix_plot.displayImage();
width = matrix_plot.image_dimensions("image_width");
Expand All@@ -35,14 +45,14 @@ function checkHeadMotion(fig, input_struct, motion)

ax = subplot('Position', [0.780, 0.540, 0.20, 0.40]);
nla.gfx.setTitle(ax, sprintf("FC-motion correlation (Pearson's r) (q < 0.05)\n"));
nla.gfx.drawROIsOnCortex(ax, input_struct.net_atlas, ctx, mesh_alpha, ROI_radius, nla.gfx.ViewPos.DORSAL, false,...
nla.gfx.drawROIsOnCortex(ax, network_atlas, ctx, mesh_alpha, ROI_radius, nla.gfx.ViewPos.DORSAL, false,...
nla.gfx.BrainColorMode.NONE);

for col = 1:input_struct.net_atlas.numROIs()
for row = (col + 1):input_struct.net_atlas.numROIs()
for col = 1:network_atlas.numROIs()
for row = (col + 1):network_atlas.numROIs()
if h.get(row, col)
pos1 = input_struct.net_atlas.ROIs(row).pos;
pos2 = input_struct.net_atlas.ROIs(col).pos;
pos1 = network_atlas.ROIs(row).pos;
pos2 = network_atlas.ROIs(col).pos;

edge_color = nla.gfx.valToColor(r.get(row, col), llimit, ulimit, color_map);

Expand Down
33 changes: 22 additions & 11 deletions +nla/+qualityControl/checkNormalityWithKS.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
@@ -1,4 +1,4 @@
function checkNormalityWithKS(fig, input_struct, test_pool)
function checkNormalityWithKS(fig, input_struct, test_pool, remove_index)

prog = uiprogressdlg(...
fig, 'Title', 'Checking Normaility', 'Message', 'Running Kolmogorov-Smirnov Test'...
Expand All@@ -9,33 +9,39 @@ function checkNormalityWithKS(fig, input_struct, test_pool)
edge_test_result = test_pool.runEdgeTest(input_struct);

prog.Value = 0.5;
ks_result = runKolmogorovSmirnovTest(input_struct, edge_test_result);
ks_result = runKolmogorovSmirnovTest(input_struct, edge_test_result, remove_index);

prog.Value = 0.75;
qcKSOutput(ks_result.p, input_struct)
qcKSOutput(ks_result.p, input_struct, remove_index)

end

function ks_result = runKolmogorovSmirnovTest(input_struct, edge_result)
function ks_result = runKolmogorovSmirnovTest(input_struct, edge_result, remove_index)
import nla.TriMatrix nla.TriMatrixDiag

network_atlas = input_struct.net_atlas;
if remove_index ~= 0
[new_netatlas] = nla.removeNetworks(input_struct.net_atlas, input_struct.net_atlas.nets(remove_index).name, strcat(input_struct.net_atlas.name, '_-', input_struct.net_atlas.nets(remove_index).name));
network_atlas = nla.NetworkAtlas(new_netatlas);
end

ks_result = struct();
number_of_networks = input_struct.net_atlas.numNets();
number_of_networks = network_atlas.numNets();
ks_result.p = TriMatrix(number_of_networks, TriMatrixDiag.KEEP_DIAGONAL);
ks_result.ks = TriMatrix(number_of_networks, TriMatrixDiag.KEEP_DIAGONAL);

for network1 = 1:number_of_networks
for network2 = 1:network1
network_rho = edge_result.coeff.get(input_struct.net_atlas.nets(network1).indexes,...
input_struct.net_atlas.nets(network2).indexes);
network_rho = edge_result.coeff.get(network_atlas.nets(network1).indexes,...
network_atlas.nets(network2).indexes);
[~, p, ks] = kstest(network_rho);
ks_result.p.set(network1, network2, p);
ks_result.ks.set(network1, network2, ks);
end
end
end

function qcKSOutput(ks_result_p_value, edge_test_options)
function qcKSOutput(ks_result_p_value, edge_test_options, remove_index)
% This will open the qc figure for the KS test

network_test_options = nla.net.genBaseInputs();
Expand All@@ -45,15 +51,20 @@ function qcKSOutput(ks_result_p_value, edge_test_options)
edge_test_options.prob_max = 0.05;
default_discrete_colors = 1000;

[~, p_value_max] = network_test_options.fdr_correction.correct(edge_test_options.net_atlas,...
edge_test_options, ks_result_p_value);
network_atlas = edge_test_options.net_atlas;
if remove_index ~= 0
[new_netatlas] = nla.removeNetworks(edge_test_options.net_atlas, edge_test_options.net_atlas.nets(remove_index).name, strcat(edge_test_options.net_atlas.name, '-', edge_test_options.net_atlas.nets(remove_index).name));
network_atlas = nla.NetworkAtlas(new_netatlas);
end

[~, p_value_max] = network_test_options.fdr_correction.correct(network_atlas, edge_test_options, ks_result_p_value);

color_map = nla.net.result.NetworkResultPlotParameter.getColormap(default_discrete_colors,...
p_value_max);

fig = nla.gfx.createFigure();
% Also remember to move this in read the docs
matrix_plot = nla.gfx.plots.MatrixPlot(fig, sprintf("Non-permuted Kolmogorov-Smirnov Test p-value\nSmaller values are less normal"), ks_result_p_value, edge_test_options.net_atlas.nets, nla.gfx.FigSize.LARGE,...
matrix_plot = nla.gfx.plots.MatrixPlot(fig, sprintf("Non-permuted Kolmogorov-Smirnov Test p-value\nSmaller values are less normal"), ks_result_p_value, network_atlas.nets, nla.gfx.FigSize.LARGE,...
'lower_limit', 0.00, 'upper_limit', p_value_max, 'color_map', color_map);
matrix_plot.displayImage();
width = matrix_plot.image_dimensions('image_width');
Expand Down
14 changes: 11 additions & 3 deletions +nla/NetworkAtlas.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -12,10 +12,13 @@
% :param space: (Optional) The mesh that the atlas` ROI locations/parcels are in. Two options - ``Talairach (TT)`` or ``Montreal Neurological Institute (MNI)``

properties (SetAccess = private)
nets % This is the net_names

nets
net_names
ROIs
ROI_key
ROI_pos
ROI_order
net_colors
name
space
anat = false;
Expand All@@ -37,14 +40,16 @@
end

net_names = net_struct.net_names;

obj.net_names = net_names;

net_count = numel(net_names);
ROI_count = size(net_struct.ROI_key, 1);

net_colors = turbo(net_count);
if isfield(net_struct, 'net_colors')
net_colors = net_struct.net_colors;
end
obj.net_colors = net_colors;

ROI_positions = zeros(ROI_count, 3);
if isfield(net_struct, 'ROI_pos')
Expand All@@ -60,6 +65,9 @@
net_struct.ROI_order = net_struct.ROI_order(sort_idx);
ROI_positions = ROI_positions(sort_idx, :);
end
obj.ROI_pos = ROI_positions;
obj.ROI_key = net_struct.ROI_key;
obj.ROI_order = net_struct.ROI_order;

%% Network atlas name
obj.name = net_struct.name;
Expand Down
3 changes: 2 additions & 1 deletion +nla/removeNetworks.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -78,7 +78,8 @@

%% Functional connectivity (optional)
if exist('fc_in', 'var')
fc_ordered = fc_in(atlas_in.ROI_order, atlas_in.ROI_order, :);
fc_in_matrix = fc_in.asMatrix();
fc_ordered = fc_in_matrix(atlas_in.ROI_order, atlas_in.ROI_order, :);
fc_reduced = fc_ordered(ROI_mask, ROI_mask, :);
ROI_order_inverse(atlas_out.ROI_order) = [1:numel(atlas_out.ROI_order)]';
fc_out = fc_reduced(ROI_order_inverse, ROI_order_inverse, :);
Expand Down
Binary file modifiedNLAQualityControl.mlapp
View file
Open in desktop
Binary file not shown.
Loading
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode"); } } catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); } })(); })();
Skip to content

[NET-315] In QC window, apply the remove network to all the different methods#159

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
pollaro merged 1 commit into from
Jul 20, 2026
Merged

[NET-315] In QC window, apply the remove network to all the different methods #159

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
34 changes: 22 additions & 12 deletions +nla/+qualityControl/checkHeadMotion.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
@@ -1,14 +1,24 @@
function checkHeadMotion(fig, input_struct, motion)
function checkHeadMotion(fig, input_struct, motion, remove_index)

network_atlas = input_struct.net_atlas;
functional_connectivity = input_struct.func_conn;
if remove_index ~= 0
[new_netatlas, functional_connectivity] = nla.removeNetworks(input_struct.net_atlas, input_struct.net_atlas.nets(remove_index).name, strcat(input_struct.net_atlas.name, '_-', input_struct.net_atlas.nets(remove_index).name), input_struct.func_conn);
network_atlas = nla.NetworkAtlas(new_netatlas);
if ~isa(functional_connectivity, 'nla.TriMatrix')
functional_connectivity = nla.TriMatrix(functional_connectivity);
end
end

prog = uiprogressdlg(fig, 'Title', 'Generating figures', 'Message', 'Generating head motion figures');
prog.Value = 0.02;
distances = nla.helpers.euclidianDistanceROIs(input_struct.net_atlas);
distances = nla.helpers.euclidianDistanceROIs(network_atlas);
prog.Value = 0.75;
[r_vec, p_vec] = corr(motion, input_struct.func_conn.v', 'type', 'Pearson');
[r_vec, p_vec] = corr(motion, functional_connectivity.v', 'type', 'Pearson');

prob = nla.TriMatrix(input_struct.net_atlas.numROIs());
r = nla.TriMatrix(input_struct.net_atlas.numROIs());
h = nla.TriMatrix(input_struct.net_atlas.numROIs(), 'logical');
prob = nla.TriMatrix(network_atlas.numROIs());
r = nla.TriMatrix(network_atlas.numROIs());
h = nla.TriMatrix(network_atlas.numROIs(), 'logical');
prob.v = p_vec';
r.v = r_vec';
h.v = nla.lib.fdr_bh(prob.v);
Expand All@@ -25,7 +35,7 @@ function checkHeadMotion(fig, input_struct, motion)
ulimit = 0.3;

fig = nla.gfx.createFigure(1800, 900);
matrix_plot = nla.gfx.plots.MatrixPlot(fig, "FC-motion correlation (Pearson's r)", r, input_struct.net_atlas.nets,...
matrix_plot = nla.gfx.plots.MatrixPlot(fig, "FC-motion correlation (Pearson's r)", r, network_atlas.nets,...
nla.gfx.FigSize.LARGE, 'lower_limit', llimit, 'upper_limit', ulimit);
matrix_plot.displayImage();
width = matrix_plot.image_dimensions("image_width");
Expand All@@ -35,14 +45,14 @@ function checkHeadMotion(fig, input_struct, motion)

ax = subplot('Position', [0.780, 0.540, 0.20, 0.40]);
nla.gfx.setTitle(ax, sprintf("FC-motion correlation (Pearson's r) (q < 0.05)\n"));
nla.gfx.drawROIsOnCortex(ax, input_struct.net_atlas, ctx, mesh_alpha, ROI_radius, nla.gfx.ViewPos.DORSAL, false,...
nla.gfx.drawROIsOnCortex(ax, network_atlas, ctx, mesh_alpha, ROI_radius, nla.gfx.ViewPos.DORSAL, false,...
nla.gfx.BrainColorMode.NONE);

for col = 1:input_struct.net_atlas.numROIs()
for row = (col + 1):input_struct.net_atlas.numROIs()
for col = 1:network_atlas.numROIs()
for row = (col + 1):network_atlas.numROIs()
if h.get(row, col)
pos1 = input_struct.net_atlas.ROIs(row).pos;
pos2 = input_struct.net_atlas.ROIs(col).pos;
pos1 = network_atlas.ROIs(row).pos;
pos2 = network_atlas.ROIs(col).pos;

edge_color = nla.gfx.valToColor(r.get(row, col), llimit, ulimit, color_map);

Expand Down
33 changes: 22 additions & 11 deletions +nla/+qualityControl/checkNormalityWithKS.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
@@ -1,4 +1,4 @@
function checkNormalityWithKS(fig, input_struct, test_pool)
function checkNormalityWithKS(fig, input_struct, test_pool, remove_index)

prog = uiprogressdlg(...
fig, 'Title', 'Checking Normaility', 'Message', 'Running Kolmogorov-Smirnov Test'...
Expand All@@ -9,33 +9,39 @@ function checkNormalityWithKS(fig, input_struct, test_pool)
edge_test_result = test_pool.runEdgeTest(input_struct);

prog.Value = 0.5;
ks_result = runKolmogorovSmirnovTest(input_struct, edge_test_result);
ks_result = runKolmogorovSmirnovTest(input_struct, edge_test_result, remove_index);

prog.Value = 0.75;
qcKSOutput(ks_result.p, input_struct)
qcKSOutput(ks_result.p, input_struct, remove_index)

end

function ks_result = runKolmogorovSmirnovTest(input_struct, edge_result)
function ks_result = runKolmogorovSmirnovTest(input_struct, edge_result, remove_index)
import nla.TriMatrix nla.TriMatrixDiag

network_atlas = input_struct.net_atlas;
if remove_index ~= 0
[new_netatlas] = nla.removeNetworks(input_struct.net_atlas, input_struct.net_atlas.nets(remove_index).name, strcat(input_struct.net_atlas.name, '_-', input_struct.net_atlas.nets(remove_index).name));
network_atlas = nla.NetworkAtlas(new_netatlas);
end

ks_result = struct();
number_of_networks = input_struct.net_atlas.numNets();
number_of_networks = network_atlas.numNets();
ks_result.p = TriMatrix(number_of_networks, TriMatrixDiag.KEEP_DIAGONAL);
ks_result.ks = TriMatrix(number_of_networks, TriMatrixDiag.KEEP_DIAGONAL);

for network1 = 1:number_of_networks
for network2 = 1:network1
network_rho = edge_result.coeff.get(input_struct.net_atlas.nets(network1).indexes,...
input_struct.net_atlas.nets(network2).indexes);
network_rho = edge_result.coeff.get(network_atlas.nets(network1).indexes,...
network_atlas.nets(network2).indexes);
[~, p, ks] = kstest(network_rho);
ks_result.p.set(network1, network2, p);
ks_result.ks.set(network1, network2, ks);
end
end
end

function qcKSOutput(ks_result_p_value, edge_test_options)
function qcKSOutput(ks_result_p_value, edge_test_options, remove_index)
% This will open the qc figure for the KS test

network_test_options = nla.net.genBaseInputs();
Expand All@@ -45,15 +51,20 @@ function qcKSOutput(ks_result_p_value, edge_test_options)
edge_test_options.prob_max = 0.05;
default_discrete_colors = 1000;

[~, p_value_max] = network_test_options.fdr_correction.correct(edge_test_options.net_atlas,...
edge_test_options, ks_result_p_value);
network_atlas = edge_test_options.net_atlas;
if remove_index ~= 0
[new_netatlas] = nla.removeNetworks(edge_test_options.net_atlas, edge_test_options.net_atlas.nets(remove_index).name, strcat(edge_test_options.net_atlas.name, '-', edge_test_options.net_atlas.nets(remove_index).name));
network_atlas = nla.NetworkAtlas(new_netatlas);
end

[~, p_value_max] = network_test_options.fdr_correction.correct(network_atlas, edge_test_options, ks_result_p_value);

color_map = nla.net.result.NetworkResultPlotParameter.getColormap(default_discrete_colors,...
p_value_max);

fig = nla.gfx.createFigure();
% Also remember to move this in read the docs
matrix_plot = nla.gfx.plots.MatrixPlot(fig, sprintf("Non-permuted Kolmogorov-Smirnov Test p-value\nSmaller values are less normal"), ks_result_p_value, edge_test_options.net_atlas.nets, nla.gfx.FigSize.LARGE,...
matrix_plot = nla.gfx.plots.MatrixPlot(fig, sprintf("Non-permuted Kolmogorov-Smirnov Test p-value\nSmaller values are less normal"), ks_result_p_value, network_atlas.nets, nla.gfx.FigSize.LARGE,...
'lower_limit', 0.00, 'upper_limit', p_value_max, 'color_map', color_map);
matrix_plot.displayImage();
width = matrix_plot.image_dimensions('image_width');
Expand Down
14 changes: 11 additions & 3 deletions +nla/NetworkAtlas.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -12,10 +12,13 @@
% :param space: (Optional) The mesh that the atlas` ROI locations/parcels are in. Two options - ``Talairach (TT)`` or ``Montreal Neurological Institute (MNI)``

properties (SetAccess = private)
nets % This is the net_names

nets
net_names
ROIs
ROI_key
ROI_pos
ROI_order
net_colors
name
space
anat = false;
Expand All@@ -37,14 +40,16 @@
end

net_names = net_struct.net_names;

obj.net_names = net_names;

net_count = numel(net_names);
ROI_count = size(net_struct.ROI_key, 1);

net_colors = turbo(net_count);
if isfield(net_struct, 'net_colors')
net_colors = net_struct.net_colors;
end
obj.net_colors = net_colors;

ROI_positions = zeros(ROI_count, 3);
if isfield(net_struct, 'ROI_pos')
Expand All@@ -60,6 +65,9 @@
net_struct.ROI_order = net_struct.ROI_order(sort_idx);
ROI_positions = ROI_positions(sort_idx, :);
end
obj.ROI_pos = ROI_positions;
obj.ROI_key = net_struct.ROI_key;
obj.ROI_order = net_struct.ROI_order;

%% Network atlas name
obj.name = net_struct.name;
Expand Down
3 changes: 2 additions & 1 deletion +nla/removeNetworks.m
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -78,7 +78,8 @@

%% Functional connectivity (optional)
if exist('fc_in', 'var')
fc_ordered = fc_in(atlas_in.ROI_order, atlas_in.ROI_order, :);
fc_in_matrix = fc_in.asMatrix();
fc_ordered = fc_in_matrix(atlas_in.ROI_order, atlas_in.ROI_order, :);
fc_reduced = fc_ordered(ROI_mask, ROI_mask, :);
ROI_order_inverse(atlas_out.ROI_order) = [1:numel(atlas_out.ROI_order)]';
fc_out = fc_reduced(ROI_order_inverse, ROI_order_inverse, :);
Expand Down
Binary file modifiedNLAQualityControl.mlapp
View file
Open in desktop
Binary file not shown.
Loading