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

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

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34 changes: 22 additions & 12 deletions +nla/+qualityControl/checkHeadMotion.m
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Original file line number Diff line number Diff 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
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Original file line number Diff line number Diff 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
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Original file line number Diff line number Diff 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
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Original file line number Diff line number Diff 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
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