sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 17k | content stringlengths 1 200k |
|---|---|---|---|---|
7ce9119a4333c87173981758482121841752b34e9366f3afa3aa7b8a8755aec8 | MATLAB | 322 | 16 |
function O = sensor_average(input)
O = [];
addpath('/projects/MINDLAB2017_MEG-LearningBach/scripts/osl/osl-core'); %this add the path (not necessary being in the osl-core directory if you have this one)
osl_startup
D = spm_eeg_average(input);
% perform analysis for subject n using data directory and subject n... |
e8407feb6d8945a1cb9cf5935fc27da75d2e7e3174e3e3b093be65def4cf7431 | MATLAB | 324 | 11 | function contrast = nst_make_basic_contrasts(events_order)
contrast = struct();
for ievent=1:length(events_order)
contrast(ievent).label = events_order{ievent};
con_vec = zeros(1, length(events_order));
con_vec(ievent) = 1;
contrast(ievent).vector = sprintf('[%s]', strip(sprintf('%d ', con_vec)));
end
... |
14c6785d2833e9d0e047f84231f06ce9947e91d48a01fb96da60661b50ad26f3 | MATLAB | 329 | 18 | function [freq]=time_frequency(ft_data1,freqrange,toy)
% Compute spectrogram
cfg = [];
cfg.method = 'mtmconvol';
cfg.taper = 'dpss';
cfg.foi = freqrange;
cfg.t_ftimwin = .1 * ones(size(cfg.foi));
cfg.tapsmofrq = 10;
cfg.toi=toy;
cfg.keeptrials = 'yes';
cfg.output = 'pow';
freq = ft_freqanalysis(cfg, ft_data1)... |
4f5da556e325b6baa290d885dd68eb881e382eeebbcf7ab3f28b0a8edc8bb858 | MATLAB | 329 | 16 | function spt_send_data_to_workspace(data_to_send)
global data listbox
if isempty(data)==1
data=data_to_send;
else
data= horzcat(data,data_to_send);
end
if isempty(data)==1
listbox.String = 'NaN';
else
for i=1:length(data)
names{i} = data{i}.name;
end
listbox.String = names;
... |
68aaacba4103b9825ce7fb8fa04bd6221ca22a7e872e2e0d34e04889b7d82d06 | MATLAB | 331 | 14 | function code=crc( msg )
% function for row by row encoding of msg
% generator polynomial
generator = [1 0 0 0 0 0 1 1 1]; % 8bit CRC
c = [1 0 0 0 0 0 0 0 0]; % x^k
for k=1:size(msg,1)
multip=conv(c,msg(k,:));
[divid, remainder]=deconv(multip,generator);
remainder=mod(remainder,2);
code(k,:)=xor(multip,remai... |
f074363276b3bd671c4d8041e2925f9b16634168259ef5fcc0f4ef08f64da340 | MATLAB | 331 | 13 | function O = cluster_africa(S)
O = [];
addpath('/projects/MINDLAB2017_MEG-LearningBach/scripts/osl/osl-core'); %this add the path (not necessary being in the osl-core directory if you have this one)
osl_startup
D = S.D;
D = osl_africa(D,'do_ica',true,'do_ident',false,'do_remove',false,'used_maxfilter',true);
D.sav... |
e63111a250ef9c17a59eef81b77abc9f8057c2816e3320f38e9ad6965d165048 | MATLAB | 332 | 14 | function [q, P] = kalman_predict_gpu(q, P, A, V_q )
gputimes = @(A, B) pagefun(@mtimes, A, B); % A*B on GPU
gputranspose = @(A) pagefun(@transpose, A); % A'
q=gpuArray(q);
P=gpuArray(P);
A= gpuArray(A);
V_q=gpuArray(V_q);
q = gputimes(A,q);
P = gputimes(gputimes(A,P),gputranspose(A)) + V_q;
q=gather(q);
P=ga... |
48edb33df57c33adc63bd5bed0e30a5168334c49c4f1e1f3fa1c7dd56c660904 | MATLAB | 334 | 12 | data_pi_sort(:,1)=data_pi(:,1);
data_pi_sort(:,2)=data_pi(:,2);
data_pi_sort(:,3)=data_pi(:,8);
data_pi_sort(:,4)=data_pi(:,9);
data_pi_sort(:,5)=data_pi(:,3);
data_pi_sort(:,6)=data_pi(:,5);
data_pi_sort(:,7)=data_pi(:,6);
data_pi_sort(:,8)=data_pi(:,4);
data_pi_sort(:,9)=data_pi(:,7);
data_pi_sort(:,10)=... |
c30eab8e058357a07e9eccde2ce5cab6b9985cb80e6cf19d9d56569bd5690209 | MATLAB | 334 | 14 | function s = nst_protect_fn_str(s)
s = strrep(s, '|', '_');
s = strrep(s, '"', '');
s = strrep(s, ':', '_');
s = strrep(s, '(', '_');
s = strrep(s, ')', '_');
s = strrep(s, '[', '_');
s = strrep(s, ']', '_');
s = strrep(s, '!', '_');
s = strrep(s, '__','_');
s = strrep(s, ' ', '... |
e8628b64850edae0c8a8a8c5317a307a2de815100588c630f82b5d00f79ad999 | MATLAB | 334 | 11 | function h = drawLine(ax, x, y, col)
%DRAWLINE Draw line segment between two points
% ax: axes to draw on
% x: x-y position of beginning point
% y: x-y position of ending point
% col: optional color
if ~exist('col', 'var'), col = 'k'; end
hold(ax, 'on');
h = plot(ax, x, y, 'Color... |
f8e85b8a2ea2cd9ef38d20ec7fd1b5d4c20df78e49c88f049b1c95c25f3df508 | MATLAB | 335 | 14 | function classes_new = group_classes(idx,classes)
idx_classes = classes(idx,:);
temp = idx_classes(:,1);
classes_new{1,1} = vertcat(temp{:});
temp = idx_classes(:,2);
classes_new{1,2} = vertcat(temp{:});
classes_new{1,3} = mean(classes_new{1,2},1);
temp = idx_classes(:,4);
classes_new{1,4} = vertcat(tem... |
6ab1f9e7959bcbbcbaf85a1c6b6bee12e284d6e4146a3b94613eb650505473c8 | MATLAB | 336 | 7 | function [result, problem] = NOW_RUN(problem)
% function [result, problem] = NOW_RUN(problem)
% This function calls the private function "optimize". The repackaging is
% done so that "NOW_RUN" can be acessed by calls from anywhere in the
% matlab structure (unlike optimize, which is restricted).
[result, problem] = op... |
76146066ebf9a617c71a89a569b657eb6e55e1439b206e8931cf44101d5f6ac2 | MATLAB | 337 | 15 |
function O = combining_planar_cluster(input)
O = [];
addpath('/projects/MINDLAB2017_MEG-LearningBach/scripts/osl/osl-core'); %this add the path (not necessary being in the osl-core directory if you have this one)
osl_startup
D = spm_eeg_combineplanar(input);
% perform analysis for subject n using data directory... |
6df9131b42b9cc123602c6049d5cdbfaca9de8af65d4c5637b47609918440d13 | MATLAB | 343 | 16 | %% read file
filename='Ecoli.sff';
%M = 100;
%sf = sffread(filename, 'block', [1 M], 'feature', 'f')
%all = sffread(filename, 'block', [1 M], 'feature', 'sqc');
sf = sffread(filename, 'feature', 'hf');
%% extract flow
x=rand(1,10)
sf10=sf(1).FlowgramValue(:);
sfh10=sfh(1).Header(:)'
for i 1:10
blastval(i)=[sfh(i... |
612466f0bb4ed120b18cb64fdb3883c5bf8555d4c7f66f7018a86b9c8a628a49 | MATLAB | 345 | 12 | function [] = tc_move_spm_results(from, to, name)
%% tc_move_spm_results(from, to, which)
%
% copies data with regexp file names in the row cell array "name" from "from" to "to"
for this = name
try
movefile([from filesep this{1}], [to filesep])
catch
warning(['file ' from filesep this{1} ' does... |
b626a22c7eeb918a1ef828d8a628afa6caaf3fd873f2bf6467240b7f244aaa69 | MATLAB | 345 | 11 | function [ind_, r_, G_] = set_part_traj_mcmv_prior(Y, noise_cov, G, pnts_e, included_sp, num_sources, T)
[loc_est, id_est, G_mcmv, ~] = MCMV_beamformer_localizer(Y, noise_cov, G, pnts_e, included_sp, num_sources);
for j=1:1:num_sources
ind_(j,:) = repmat(id_est(j), [1 T]);
end
r_ = repmat(loc_est,[1 T]);
G_ =repma... |
bdea291891735cc3f5de35244ede6f9024385c0c52873d6a758a5752277e9cf0 | MATLAB | 346 | 10 | function M_t = compute_Bt(P_ks, P_ks1, M, nq, ny, N)
M_t = zeros(3*nq+ny, 3*nq+ny, N);
M_t(1:nq,1:2*nq,:) = [P_ks, M];
M_t(1:nq,2*nq+ny+1:end,:) = P_ks;
M_t(nq+1:2*nq,1:2*nq,:) = [M, P_ks1];
M_t(nq+1:2*nq,2*nq+ny+1:end,:) = M;
M_t(2*nq+ny+1:end, 1:2*nq,:) = [P_ks, M];
M_t(2*nq+ny+1:end, 2*nq... |
e6e8b10e89e3301c8e695552387dcd0fca8c7ea7f9174094c2bcc9acc69a5f3b | MATLAB | 347 | 7 | function [ll] = compute_complete_ll(T, stats, V_q, A, E, G_s)
logdetV = 2*sum(log(diag(chol(V_q))));
logdetE = 2*sum(log(diag(chol(E))));
ll= -1/2*(T*logdetV + trace(V_q\(stats.Phi - stats.Psi*A' - A*stats.Psi' + A*stats.Sigma*A'))...
+ T*logdetE + trace(E\(stats.Omega - stats.Lambda*G_s' - G_s*stats.Lambda' + ... |
b9ea9b4ee5a63c2af407450ef6b0a6ebcbf01da4cec267ac394c389acf0ba525 | MATLAB | 348 | 16 | function Cell_slice = pl_cell_slice(Cell,ndx)
%
% Slices cell elements keeping the indices 'ndx'
% This function is part of the permutationlab software:
% Author: Dimitrios Pantazis
% The code is currently under development, please do not share
N = length(Cell);
%compute mean
for i = 1:N
Cell_slice{i... |
36ddb6ddd05ce2571b6bee436b3bbd694a76e2334aefe3ecc05405bbbbf9129d | MATLAB | 349 | 15 | function image_save_video(data)
[file,path] = uiputfile('*.avi');
if path~=0
save_to = fullfile(path,file);
video = VideoWriter(save_to);
video.FrameRate = 10;
open(video);
for i = 1:length(data)
images = data{i}.image{1};
writeVideo(video,images);
clear I
end... |
88d61efb863cf8fefabbbd2aff71d146356203dcb04372465586233aa5e88a2f | MATLAB | 350 | 16 | function network_names = get_schaefer_networks(FC_project)
old_path = pwd;
cd(FC_project.CONN_results_dir)
names = schaefer_roi_names();
network_names = cell(numel(names),1);
for i=1:numel(names)
split_name = split(names{i},'_');
network_names{i} = split_name{3};
end
network_names = unique(networ... |
c29a12e3d8a08334210cb2257f43f248e9ad82c3a42453146145b68ab3302973 | MATLAB | 356 | 16 | function xy = mni2xy_v2(x, y, z, view)
x_scale = 0.87;
y_scale = 0.95;
switch view
case 'sagittal'
xy(:,1) = x_scale*y+98;
xy(:,2) = y_scale*z+110;
case 'axial'
xy(:,1) = x_scale*x + 8;
xy(:,2) = y_scale*y + 2;
case 'coronal'
xy(:,1) = x_scale*x + 8;
... |
5b0e0facb2a11b2ac9c7dccc77d73ee22f4072c9238ad368afdae28732aa194e | MATLAB | 357 | 18 | clear
% S0 D Dr Vi Vir Va Var Ci Ca
beta = [1 0.8 .5 .2 .1 .2 .1 .02 .01];
opt = resQ_opt();
load('resQ_xps_example.mat');
xps = resQ_check_xps(xps);
s = resQ_1d_fit2data(beta, xps);
e = resQ_1d_data2fit(s, xps, opt);
difference = beta-resQ_unitSwap(e, 1)... |
0eb0e754d55859ca4142057e9044013371f0565b7249549a00a2e0b36237a940 | MATLAB | 358 | 22 | function flag = all_close(v1, v2, rtol, atol)
if nargin < 3
rtol = 1e-5; %default relative tolerance
end
if nargin < 4
atol = 1e-5; %default absolute tolerance
end
% Convert to vectors if needed:
if ndims(v1) == 2
v1 = v1(:)';
end
if ndims(v2) == 2
v2 = v2(:)';
end
flag = all(abs(v1 - v2) <= (atol ... |
7816d0b64296e5f5a9d0cf8e55bed25376bf3e673e4ed9d71a8048d6c3f32010 | MATLAB | 358 | 15 | function mfs_fn = resQ_4d_data2fit(s, mfs_fn, opt, ind)
% function mfs_fn = resQ_4d_data2fit(s, mfs_fn, opt, ind)
if (nargin < 3), opt = []; end
% Verify the xps
resQ_check_xps(s.xps);
% Loop over the volume and fit the model
xps = s.xps;
f = @(signal) resQ_1d_data2fit(signal, xps, opt, ind);
mfs_fn =... |
5d81922a2d886222d9a8e7e242ec1a333eaa029eea0499944cd0bb501a8197b9 | MATLAB | 360 | 15 | function PlotSpeedHisto(Histo,color)
% Plots a histogram plot from a dFC speed structure Histo
col1=[.4,0,.5];
col2=col1;
c=Histo.BinCenters;
lo=Histo.BinCounts_low;
hi=Histo.Bincounts_high;
h=fill([c fliplr(c)], [lo fliplr(hi)],col1);
set(h,'facealpha',.2);hold on
plot(c,Histo.BinCounts,'-o','Color',color,'linew... |
fbaf5c2e905a7ad5dcd672a01230082a23356b171d8f2b851cf9d5291bcb7521 | MATLAB | 360 | 16 | function network_names = get_schaefer_networks_200(FC_project)
old_path = pwd;
% cd(FC_project.CONN_results_dir)
names = schaefer_roi_names_200();
network_names = cell(numel(names),1);
for i=1:numel(names)
split_name = split(names{i},'_');
network_names{i} = split_name{3};
end
network_names = uni... |
98273d7bcced68f9457c00277dbbce8a2bfe3297a6afe95989484a309db37af9 | MATLAB | 363 | 13 | function str = humanReadableList(list)
%HUMANREADABLELIST Print a cell-array of strings in a human-readable list format
n = numel(list);
if n == 1
str_cell = list(1);
elseif n == 2
str_cell = join(list, ' and ');
else
str_cell = join([join(list(1:n - 1), ', '), list(n)], ', a... |
71d6e22a7103d1e85a6defce76dc046b62287fd01ea281ebfea540074b815338 | MATLAB | 366 | 17 | classdef ROI
%ROI Region of interest in the brain
% Right now this class isn't so useful but in the future there could
% be more metadata associated with each region such as more detailed
% bounds, etc.
properties
pos
end
methods
function obj = ROI(pos)
... |
b149028e675c4041befa1b357888fa004c079e1b9546cb8235ad2d3a7810b9ef | MATLAB | 367 | 21 | function str = cstring(x)
%
%CSTRING Print to a string like c
% CSTRING(x) takes an array x, of type char, and prints it to
% a string the way C would.
% the first null, or non-ascii character is the terminator
i=1;
while (x(i)>0 & x(i)<128 & i<length(x))
i=i+1;
end
if i==1
str = char(0);
else
str = char(x(... |
96cb61a0a58ea44f6194ac4d1c56f25a963f42bb0748898370e11bf7efade281 | MATLAB | 368 | 15 | % perspect = [1 0.25 0.5];
% cmap1 = jet(64);
% part1 = cmap1(1:31,:);
% part2 = cmap1(34:end,:);
% mid_tran = gray(64);
% mid = mid_tran(57:58,:);
% cmap = [part1;mid;part2];
perspect = [1 0.25 0.5];
cmap1 = jet(64);
part1 = cmap1(1:31,:);
part2 = cmap1(34:end,:);
mid_tran = gray(64);
mi... |
c881e9a315e98c95f9f8eb84897b442838e117be7d7684853cf09f47ea53cdd1 | MATLAB | 369 | 18 | function rad = angleFrom(a, b)
%ANGLEFROM Angle from point a to point b, in radians
x = b(1) - a(1);
y = b(2) - a(2);
rad = abs(atan(y / x));
if x < 0 && y >= 0
% Q2
rad = pi - rad;
elseif x < 0 && y < 0
% Q3
rad = rad + pi;
elseif x >= 0 && y < 0
... |
f1a12729961d368a14349cbd116a60cacac1e11a4ce39e219d28d806d8cdba8e | MATLAB | 369 | 18 | function O = cluster_rembadcomp(S)
O = [];
addpath('/projects/MINDLAB2017_MEG-LearningBach/scripts/osl/osl-core'); %this add the path (not necessary being in the osl-core directory if you have this one)
osl_startup
D = S.D;
% S = rmfield(S,'D');
D = osl_africa(D,'do_ident',false,'do_remove',true);
D.save();
% D =... |
40bc119e798f02b3a1cd8441f73f19f68d27ccc66db2dd0e80a3ca4a324f370d | MATLAB | 370 | 9 | classdef BehaviorVec < nla.edge.permutationMethods.Base
methods
function permuted_input_struct = permute(obj, orig_input_struct)
permuted_input_struct = orig_input_struct;
permuted_behavior = nla.helpers.permuteVector(orig_input_struct.behavior);
permuted_input_struct.beh... |
b5658a8b7e2b84f625f7971a189a24a7a00eeebd0ef2d8aa776f568f168a0216 | MATLAB | 370 | 11 | function [logp] = logpdf(x, mu, Sigma)
%Author : Narayan Subramaniyam
%Aalto/NBE
m = size(x,1);
CONST = -m * 0.5 * log(2*pi);
logDetSigma = 2*sum(log(diag(chol(Sigma))));
%logp = CONST - 0.5*logDetSigma - 0.5*((x-mu)' * ...
%choleskeyinverse(chol(Sigma)) * (x-mu));
logp = CONST - 0.5*logDetSigma - 0.5*((x-mu)'/Sigma *... |
1a912b87256514a04114e47ac8668b2e0b3724810688082714c2a27b1e926ae8 | MATLAB | 371 | 9 | function loc_list_clusters_count_clusters(data)
for i = 1:length(data)
number_of_clusters(i,1) = length(unique(data{i}.area));
names{i} = data{i}.name;
end
number_of_clusters(end+1,1) = sum(number_of_clusters);
names{end+1} = 'Total Number of Clusters';
table_data_plot(number_of_clusters,names,{'Total Nu... |
9a9df7a0927965298973391dc1ae35a9de17e738770ffc178ce1d68751a847fb | MATLAB | 376 | 12 | function O = cluster_oat_save_nii_stats(S2)
O = [];
addpath('/projects/MINDLAB2017_MEG-LearningBach/scripts/osl/osl-core'); %this add the path (not necessary being in the osl-core directory if you have this one)
osl_startup
% addpath('/projects/MINDLAB2017_MEG-LearningBach/scripts/scripts_osl_learningbach/Cluster')
... |
f4b1474cbdd622289bfcfd71674ab1a7f4aeaf4fc36d00757075c82287e1b0e1 | MATLAB | 377 | 11 | function trajectory = tracks_convert_space_time_units(trajectory,space_units,time_units,pixel_s,frame_interval)
for i = 1:length(trajectory)
if isequal(space_units,'pixels')
trajectory{i}(:,2:3) = trajectory{i}(:,2:3)*pixel_s;
end
if isequal(time_units,'frames')
trajectory{i}(:,1... |
5b43a6626b2919e48a38804d6126f9e98a22baa31871d9295c18fbc4b2c0bf16 | MATLAB | 379 | 18 | function [R, t] = rigid_transform_3D(A, B)
% A and B are Nx3 matrices of corresponding points
centroid_A = mean(A, 1);
centroid_B = mean(B, 1);
Am = A - centroid_A;
Bm = B - centroid_B;
H = Am' * Bm;
[U,~,V] = svd(H);
R = V * U';
if det(R) < 0
V(:,3) = -V(:,3);
R = ... |
a894ca34d0cce43896f2cd15b71b7e2a9a54368faeea33de6ffbc864fad674ef | MATLAB | 380 | 13 | function d = nst_pdist(x,y)
% D = nst_pdist( X,Y) returns the distance between each pair of
% observations in X and Y using the euclidean distance
% Equivalent to pdist2(x,y); Might be slower
% see also pdist2
d = zeros(size(x,1), size(y,1));
for i = 1:size(x,1)
for j = 1:size(y,1)
d(i,j) ... |
c241ed70641e124cf03aac57d1289a58a49525bc2162417c0b15b32a020ddc8f | MATLAB | 380 | 12 | function [eta, data_cov_reg] = compute_LCMV_reg(h, noise_cov, data_cov)
reg=0.05;
alpha=reg*trace(data_cov)/length(data_cov);
nchan = size(data_cov,2);
data_cov_reg=data_cov+alpha*eye(nchan);
alpha=reg*trace(noise_cov)/length(noise_cov);
nchan = size(noise_cov,2);
noise_cov_reg=noise_cov+alpha*eye(nchan);
eta = (h' *... |
1189faf831f7f6747e6de67d02327e99d798125d5fcda35b4e5b0cdb3117d224 | MATLAB | 382 | 13 | function [M] = init_M_gpu(I, Kf, G, P_kf, A)
gputimes = @(A, B) pagefun(@mtimes, A, B); % A*B on GPU
gpurdivide = @(A, B) pagefun(@mrdivide, A, B); % A/B on GPU
gputranspose = @(A) pagefun(@transpose, A); % A'
I=gpuArray(I);
Kf = gpuArray(Kf);
G=gpuArray(G);
P_kf = gpuArray(P_kf);
A=gpuArray(A);
M = gputimes... |
fcce4023a8a07b9491a034ee1eee7672ab86fc798d2298d51cec294d1cb0fcad | MATLAB | 384 | 14 | function image_motion_filter(data)
InputValues = inputdlg({'length:','theta:'},'',1,{'2','10'});
if isempty(InputValues)==1
return
else
len = str2double(InputValues{1});
theta = str2double(InputValues{2});
h = fspecial('motion',len,theta);
for k=1:length(data)
data{k}.image = imf... |
7ff16b5dabcdcc7409a62855ac6e187af15e0affccd0aa2c93ef3ce4592f9aaa | MATLAB | 385 | 16 | function O = red_dim(S)
O = [];
addpath('/projects/MINDLAB2017_MEG-LearningBach/scripts/osl/osl-core'); %this add the path (not necessary being in the osl-core directory if you have this one)
osl_startup
p = S.p;
D = spm_eeg_load(S.filepath);
D = D.montage('switch',S.montage);
D = ROInets.get_node_t... |
6e34d6de977c21497b3d1d9d89bb1c682aaa272f47eeb9cd904e97dd160a9565 | MATLAB | 390 | 18 | function [str] = strengths_und(CIJ)
%STRENGTHS_UND Strength
%
% str = strengths_und(CIJ);
%
% Node strength is the sum of weights of links connected to the node.
%
% Input: CIJ, undirected weighted connection matrix
%
% Output: str, node strength
%
%
% Olaf Sporns, Indiana University, 20... |
e6b31f05b6b5ce6ec84c1389cc408ffb38f7037a6da0b855d1ae560433466e59 | MATLAB | 391 | 14 | function image_log_filter(data)
InputValues = inputdlg({'filter size:','sigma value:'},'',1,{'2','1'});
if isempty(InputValues)==1
return
else
hsize = str2double(InputValues{1});
sigma = str2double(InputValues{2});
h = fspecial('log',hsize,sigma);
for k=1:length(data)
data{k}.imag... |
db56b94d8c88ef3e52bb3da60d20aa7547c3f80cc93f88a5b318ce445daabdd3 | MATLAB | 392 | 8 | function annotation50CHANGEDannolabelIDs = readXML_Lables(xml_file)
%% Import the data
[~, ~, annotation50CHANGEDannolabelIDs] = xlsread(xml_file);
annotation50CHANGEDannolabelIDs = annotation50CHANGEDannolabelIDs(2:end,5);
annotation50CHANGEDannolabelIDs = string(annotation50CHANGEDannolabelIDs);
annotation50CH... |
0f4f5c4e007174b86eff067892dd3ec1c1f331075c452c13e25b8146e796cf54 | MATLAB | 393 | 12 | load('ERD_ERS_noise.mat')
figure,imagesc(timeVec_zoom,freqVec_zoom,ERD_ERS_noise_zoom),title('ERD/ERSgram')
set(gca,'YDir', 'normal')
caxis([-70 70]);
colormap('jet')
colorbar
smarterd = TFfindRespFreq2_scirep(ERD_ERS_noise_zoom,timeVec_zoom,freqVec_zoom,thr_max)
hold on
plot(timeVec_zoom(find(timeVec_z... |
dd045cebbe548075d7f7494375f9633310277a75a02d19758357f5dac006c93c | MATLAB | 394 | 30 | %% demo gso
hold on
grid on
axis equal
x=-5:5;
plot(2,3,'ro')
plot(x,3*x/2,'k-')
plot(x,3*x/2+65/26,'k-')
plot(1,4,'go')
plot(x,4*x,'c-')
plot(-15/13,10/13,'bo')
plot(x,-2*x/3,'y-')
plot(x,-2*x/3+7,'m-')
plot(x,-2*x/3+14/3,'k-')
plot(14*2/13,14*3/13,'ko')
hold off
%% sphering - decorrelation and normalization wit... |
903a7c5c167fe529e160381f137e5484cfd0d1fd08d1578873bc27e9c84b7be8 | MATLAB | 396 | 16 | function [Y, sigma_b, sigma_m, est_snr] = gen_MEG_simu(q,G,source_ids, meas_snr, bio_snr, num_bio_ns)
%GEN_MEG_SIMU Summary of this function goes here
% Detailed explanation goes here
Y_brain_sig = G(:, source_ids) * q;
% add brain noise
[Y, sigma_b] = add_brain_noise(Y_brain_sig, G, bio_snr, num_bio_ns);
%add me... |
73817aee705945d3ad46093477358adec9de60e61a975e49aa37ceee4fe7a1c0 | MATLAB | 401 | 19 | classdef CortexAnatomy
%CORTEXANATOMY Anatomical model of the cortex
properties
hemi_l
hemi_r
space
end
methods
function obj = CortexAnatomy(fname)
anat_struct = load(fname);
obj.hemi_l = anat_struct.ctx_l;
obj.hemi_r = anat_s... |
92911729ffdd3ad552c464c657cfc2a5176aabb69d23fc110cb4d437458a272b | MATLAB | 401 | 11 | function voronoi_data = loc_list_voronoi_segmentation(data)
for i=1:length(data)
counter(1) = i;
counter(2) = length(data);
voronoi_data{i}.vor = loc_list_construct_voronoi_structure(data{i}.x_data,data{i}.y_data,counter);
voronoi_data{i}.name = [data{i}.name,'_vor'];
voronoi_data{i}.type = 'v... |
3d8edaa41aca8f1b30beef497244baf98ee889a80de3e871f888e2d97d380735 | MATLAB | 402 | 12 | function data_center = loc_list_center_data(data)
data_center = cell(1,length(data));
for i = 1:length(data)
data_center{i} = loc_list_center_data_inside(data{i});
end
loc_list_plot(data_center)
end
function data = loc_list_center_data_inside(data)
data.x_data = data.x_data - (max(data.x_data)+min(data.x_... |
574d0c2640b4aa6c128cc4df07088eca6bc3b99620b1501f7919b71557879d0a | MATLAB | 403 | 11 | function clean_data = tc_regress_out_confounds(in_data, confound_regs)
%% clean_data = tc_regress_out_confounds(in_data, confound_regs)
%
% confound_regs: shape: data_point x regressor
% in_data: shape: feature x data_point
% demeaning
confound_regs = [confound_regs ones(size(confound_regs, 1), 1)];
betas_confound = ... |
876058581a635d9d39003d6814e98481e61270eace14f9eea5cf048d148327b9 | MATLAB | 404 | 15 | function T_tkr2scan = tc_tkr2scanner(V)
M_vox2ras = V.mat;
D = sqrt(sum(V.mat(1:3,1:3).^2));
N = V.dim;
center = N / 2;
T_tkr2vox = [ 1/D(1), 0, 0, center(1);
0, 1/D(2), 0, center(2);
0, 0, 1/D(3), center(3);
0, ... |
80a78a3e93a97ab1897236405db2762eff2be374be270ea13f332f76b5fee53a | MATLAB | 407 | 10 | function [x_pdf,y_pdf,x_cdf,y_cdf] = calculate_pdf_cdf(data,percentile)
I1 = prctile(data,percentile(1));
I2 = prctile(data,percentile(2));
wanted = data(data<I2 & data>I1);
x_hist = linspace(min(wanted),max(wanted),1000);
y_pdf = histcounts(wanted,x_hist,'normalization','probability');
y_cdf = histcounts(wanted,... |
2f863c638f141324b01eccb96bbd756ea32cb712376434b6b9bd193c3741972f | MATLAB | 410 | 15 | classdef Precalculated < nla.edge.result.Base
%SIMULATED The output result of a Simulated edge-level result
methods
function obj = Precalculated(size, prob_max)
if nargin == 0
size = 2;
prob_max = -1;
end
% Superclass ... |
172fd11d465184d48eb202221dc9e2a167ddba3f63d503c3136cbadb36a487f5 | MATLAB | 412 | 12 | function measure_types = nst_measure_types()
% NST_MEASURE_TYPES return an enumeration of measure types (eg wavelength, Hb)
%
% MEASURE_TYPES = NST_MEASURE_TYPES()
% MEASURE_TYPES: struct with numerical fields listing all available
% channel types:
% - MEASURE_TYPES.WAVELENGTH
% ... |
580efcbf6fdf56fef1ae457864beebb3c2f51c4a9757c3703887030f5ca6c216 | MATLAB | 412 | 14 | function [D,R] = calc_correlationdist(zmat)
% Jiaxin Cindy Tu 2022.11.22
% Calculates the correlation for NxN matrix but excludes the diagonal
% check that the matrix is the right format
assert(size(zmat,1)==size(zmat,2));
assert(length(size(zmat))==2);
zmat(eye(size(zmat))==1) = NaN;% this calcul... |
b8d6f55c0fa1c9f191e3c1ffe51f0c9fc9505f80eff7595dd53ba7386168be12 | MATLAB | 412 | 12 | function M = one_lag_gpu(A, P_kf, J_tm1, M_tp1, J_t)
gputimes = @(A, B) pagefun(@mtimes, A, B); % A*B on GPU
gputranspose = @(A) pagefun(@transpose, A); % A'
P_kf = gpuArray(P_kf);
J_tm1=gpuArray(J_tm1);
M_tp1=gpuArray(M_tp1);
J_t=gpuArray(J_t);
A=gpuArray(A);
M = gputimes(P_kf, gputranspose(J_tm1)) + gputime... |
d44637d9b51c921921c9b62c7ce18fe64c8b942214a89cdd5e57b863ef71afaa | MATLAB | 412 | 13 | function [A_reconst] = re_arrange_A(loc_true,loc_est, A_est, num_sources, P)
%UNTITLED3 Summary of this function goes here
% Detailed explanation goes here
[comb_id, ~, ~] = check_loc_error(loc_true, loc_est, num_sources);
A_reconst=zeros(size(A_est));
for p=1:P
for i=1:num_sources
for j=1:num_sources
... |
6f3be80922acf23c810dee36cb1cbff2c94520f1193e1269c92d78bb77044d4e | MATLAB | 413 | 16 | function O = cluster_beamgrouplevel(oat)
O = [];
addpath('/projects/MINDLAB2017_MEG-LearningBach/scripts/osl/osl-core'); %this add the path (not necessary being in the osl-core directory if you have this one)
osl_startup
addpath('/projects/MINDLAB2017_MEG-LearningBach/scripts/osl/ohba-external/fmt')
oat = osl_chec... |
ec29aa378132f8f81190277455f7bafb48bed08d88d5c28805f75ef34cc3339a | MATLAB | 416 | 14 | function xps = resQ_check_xps(xps)
% function resQ_check_xps(xps)
f = {'n', 'b', 'b_shape', 'm', 'm_shape', 'bm_shape'};
for c = 1:numel(f)
assert( isfield( xps, f{c} ), ['xps.' f{c} ' required']);
end
if ~isfield(xps, 'wf_ind')
warning('Supplying a wf index assuming m/b*b_shape is unique!')
[... |
f36e9cc7e3de682fac66bd697acb277185016aa9fb82672687d4f7402ccefca5 | MATLAB | 418 | 16 | function [pa_ind, wf_ind] = resQ_xps2paind(xps, tol)
% function [pa_ind, wf_ind] = resQ_xps2paind(xps, tol)
if nargin < 2
tol = 0.2;
end
data = [xps.b xps.b_shape xps.m];
data = data./max(data,[],1);
% Get index for powder average (including b-val)
[~, ~, pa_ind] = uniquetol(data, tol, 'ByRows', true);
% Get in... |
cc50725baee16289a46b9439e3c7b89eda299c0f960a668f3c46104aeaa09d2c | MATLAB | 422 | 15 | function data_flip = loc_list_flip_ud(data)
data_flip = cell(1,length(data));
for i = 1:length(data)
data_flip{i} = loc_list_flip_inside(data{i});
end
end
function data_flip = loc_list_flip_inside(data)
max_y = max(data.y_data);
data_flip.x_data = data.x_data;
data_flip.y_data = max_y-data.y_data;
data_... |
cd38960395654139ad0020718b3c0f6c2d547e7bd151f0f4c68f611c4318eeb7 | MATLAB | 422 | 15 | function data_flip = loc_list_flip_lr(data)
data_flip = cell(1,length(data));
for i = 1:length(data)
data_flip{i} = loc_list_flip_inside(data{i});
end
end
function data_flip = loc_list_flip_inside(data)
max_x = max(data.x_data);
data_flip.x_data = max_x-data.x_data;
data_flip.y_data = data.y_data;
data_... |
eeb0f2639c18c644d9cbd9bbb9452b5623c55833d845aba31cdcac0b7d542d0d | MATLAB | 424 | 18 | function [path_table_1,path_table_2] = separate_table(path)
table = load(path);
table_1 = table(1:end/2,:);
table_2 = table(end/2+1:end,:)-table(end/2+1,:);
[dir_to_save,name,~] = fileparts(path);
path_table_1 = [dir_to_save filesep name '_side1.txt'];
writematrix(table_1,path_table_1,'Delimiter','tab')
path_tab... |
53a585390fcc61d330ffcc9e2ca5b7e290b3df616b58ef0ff2944cbe298d1ddd | MATLAB | 425 | 15 | function [outputArg1,outputArg2] = setTitle(ax, txt, is_subtitle)
%SETTITLE Set the title of an axes
% ax: Axes to set the title on
% txt: Title/subtitle text
% is_subtitle: boolean, whether to display as a subtitle
if ~exist('is_subtitle', 'var'), is_subtitle = false; end
if is_subti... |
b209ff9e692445ad16ed67ca190fd92dbc9fe856d5e4cd888f2a3f64959a4d58 | MATLAB | 432 | 11 | function [x_pdf,y_pdf,x_cdf,y_cdf] = calculate_pdf_cdf_reverse(data,percentile)
data = 1./data;
I1 = prctile(data,percentile(1));
I2 = prctile(data,percentile(2));
wanted = data(data<I2 & data>I1);
x_hist = linspace(min(wanted),max(wanted),1000);
y_pdf = histcounts(wanted,x_hist,'normalization','probability');
y... |
7ddff1052137d0da9b3444260a1d4465f74b77402855eb4d245731a96e4c9f78 | MATLAB | 433 | 16 | function results = nst_misc_unpack_glm_result(results, model,method_name,mask)
results.B(:,mask)=model.B;
if strcmp(method_name,'OLS_prewhitening')
results.covB(:,:,mask)=model.covB;
else
results.covB(:,:,mask)=repmat(model.covB,1,1,length(mask));
end
results.residuals(:,mask)=... |
8989376c63e073ed03e1dc3c63067c5e296924a4eb95295694b8f8d9e8f4e126 | MATLAB | 433 | 15 | rawdata=xlsread('96wellPLateData.xlsx');
step=10;
fresult = fopen('combo.txt','w');
for i=1:size(rawdata,1)
if rem(i,step)==1
ceil(i/step)
fprintf(fresult,'Plate-%d\n',ceil(i/step));
elseif rem(i,step)<11
reshape(rawdata(i,:),size(rawdata,2),1)
if ~isnan(rawdata(i,:))
... |
7757509eb3d049257159a33ef2afb9cb0a622a1695629db94a57e40be668dd41 | MATLAB | 435 | 9 | function [status,cmdout] = tc_wrapper_fssurf2fsnifti(subjectsDir, o_file, s_file_l, s_file_r)
command = sprintf('%s\n', ...
['subjectsDir=' subjectsDir], ...
'export SUBJECTS_DIR=$subjectsDir',...
['mri_surf2vol --o ' o_file ' --subject fsaverage \'], ...
['--so $subjectsDir/fsaverage/surf/lh.white ' s_... |
c43b0aed271a26f574ea70a4d8bfd59e204e2ff34a8030966ac72ac4e433260b | MATLAB | 435 | 22 | function [deg] = degrees_und(CIJ)
%DEGREES_UND Degree
%
% deg = degrees_und(CIJ);
%
% Node degree is the number of links connected to the node.
%
% Input: CIJ, undirected (binary/weighted) connection matrix
%
% Output: deg, node degree
%
% Note: Weight information is discarded.
%
%
% O... |
4f8ce8fb462d9e47f9a3d4b33f838045b7a9246052db07126e5bdf434a6096e3 | MATLAB | 440 | 26 | %% data
[prot gene ~]=xlsread('L:\Elite\Celine\final.xlsx');
a=[10 20 12 131 31];
b=[4 5 6 7 8];
c=[0.9 1 2 3 4];
d=[0.2 0.4 0.6 0.8 1];
t=[1 2 3 4]
%b=rand()*a/2
%c=rand()*a/4
%d=rand()*a/8
%% trending
plot(prot(end,:),prot(1:end-1,:))
plot(prot(end,:),prot(16,:),'r.')
%% stabdardize
a=zscore(a)
b... |
242d9cfd450b4231db93d37e0854a35aa9fd7e5d305bcb889f8eabcfab8cb204 | MATLAB | 443 | 13 | function spt_combine_tracks(data)
for i = 1:length(data)
to_combine_tracks{i,1} = data{i}.tracks;
to_combine_msd{i,1} = data{i}.msd;
end
to_combine_tracks = vertcat(to_combine_tracks{:});
to_combine_msd = vertcat(to_combine_msd{:});
data_combined{1}.tracks = to_combine_tracks;
data_combined{1}.msd =... |
266a8d117a5bd57c98ad03b59884f6aaf10d289facbcf458f1366e5db70f7ab7 | MATLAB | 444 | 21 | function [TF,transition] = compute_TF(sub_clust,TR)
nsub = size(sub_clust,2);
nvol = size(sub_clust,1);
duration = nvol*TR/60;
TF = zeros(nsub,1);
transition = zeros(nvol,nsub);
for i=1:nsub
transitions = zeros(nvol,1);
for j=2:nvol
if sub_clust(j,i) ~= sub_clust(j-1,i)
trans... |
c8bbe0725d30ed4066afe20ba9491faa73dbf3c54d9e7c109b4e981358481af8 | MATLAB | 448 | 20 | function dFCstream_2D = Matrix2Vec(dFCstream_3D)
% FUNCTION dFCstream_2D = Matrix2Vec(dFCstream_3D)
% takes '3D' dFCstream as input and convert it to '2D' dFCstream
% or
% takes '2D' FC matrix as input and convert it to '1D' FC vector
n = size(dFCstream_3D, 1);
l = n*(n-1)/2;
F = size(dFCstream_3D, 3);
xo = find(tril... |
497fddada2f87f174ca4cbfd222a5ad8f7276acd9d86ad0f81cd7aab4d7c08d7 | MATLAB | 449 | 14 | function [comb_id, min_mean_err, err] = check_loc_error(loc_true, loc_est, nq)
aa=perms(1:nq);
for jj=1:1:length(aa)
for i=1:1:nq
dip_err(jj,i) = sqrt(sum((loc_est((3*i-3)+1:3*i,end) - loc_true((3*aa(jj,i)-3)+1:3*aa(jj,i),end)).^2));
end
end
mean_err = mean(dip_err,2);
... |
e5258e43a0b64293274f4fc6093fb2facc6cd621c7a5e01247f652ca27e71380 | MATLAB | 450 | 19 | function spt_tracks_filter_tracks_time_zero(data)
for i = 1:length(data)
for j=1:length(data{i}.tracks)
if check_for_zero(data{i}.tracks{j})
data{i}.tracks{j} = [];
end
end
data{i}.tracks = data{i}.tracks(~cellfun('isempty',data{i}.tracks));
end
spt_plot(data);
end
f... |
5435bb79aece1047a17d7100640e7425e25d212ede034d17ac0111cd2b16d808 | MATLAB | 453 | 12 | function spectrum_1d_plot(data)
figure()
set(gcf,'name','Spectrum 1D','NumberTitle','off','color','w','units','normalized','position',[0.3 0.2 0.4 0.6],'menubar','none','toolbar','figure')
hold on
for i = 1:length(data)
plot(data{i}.x_data,data{i}.y_data)
names{i} = data{i}.name;
end
set(gca,'TickLength... |
f987e9f5a81a8238fc7ae0774e342b7a27c08523567466e1eaf0fc7f8985ea38 | MATLAB | 454 | 13 | function [Y, sigma_b] = add_brain_noise(Y, G, snr, n_noise_sources)
%UNTITLED2 Summary of this function goes here
T=size(Y,2);
ind_noise_rand=randperm(size(G,2));
noise_ids=ind_noise_rand(1:n_noise_sources)';
pn = mkpinknoise(T, n_noise_sources)';
Y_brain_noise = G(:, noise_ids)*pn;
bio_snr_=trace(Y*Y')./trace(Y_bra... |
0a57f87081611675d63123050f90683f72cfff7dda891979496d51a3a81ffb86 | MATLAB | 457 | 14 | function mycsvwrite(filename,var,header)
% writes a CSV file with headers
% mycsvwrite(filename,var,header)
% header is a comma separeted list of names
% for example, if you have a 25x4 matrix M you can do:
% mycsvwrite('datafile.csv',M,'id,wage,age,educ')
outid = fopen(filename, 'w+');
fprintf(outid, '%s\n', header... |
66531b5328e5c49fbceeabc3083b1d3790e14a3a5edfb05c3870de4174e3a278 | MATLAB | 458 | 11 | function shape_classification_clustergram(classes)
if size(classes,1)<500
parameters = shape_classification_normalized_parameters(classes);
disp('plotting clustergram')
clustergram(parameters,'Standardize','row', 'RowPdist', 'correlation', 'ColumnPdist', 'correlation', 'ImputeFun', @knnimpute)
... |
8c2792fca31342a96c10e1476ea335871edc20d1c747a9b8a64fff49ccbf083a | MATLAB | 458 | 7 | function [feature_template, feature_template_centered] = tc_make_feature_template(betas, compartments)
%% [feature_template, feature_template_centered] = tc_make_feature_template(betas, compartments)
beta_indices = reshape(ones(size(compartments, 1), 1) * (1:size(betas, 1)), [], 1);
feature_template = compartments .* b... |
73785d2f35c823cc28da02a4314927a9233fb3da2b7f7c97965c39d3ca3c9cd5 | MATLAB | 465 | 17 | function display(model)
display(model.mean);
names=char(model.variance);
v=double(model.variance);
[n2,l]=size(v);
n=sqrt(n2);
for k=1:l
disp(names{k});
% d=[repmat('| ',n,1) num2str(reshape(v(:,k),n,n)) repmat(' |',n,1)];
% disp(['+' repmat('-',1,size(d,2)-2) '+']);
% disp(d);
% disp(['+... |
526b5c4831a0504c9ee0eae045033cc472da07a1c383a977909488213c8ba241 | MATLAB | 468 | 22 | function O = cluster_epoch_osl(S2)
O = [];
addpath('/projects/MINDLAB2017_MEG-LearningBach/scripts/osl/osl-core'); %this add the path (not necessary being in the osl-core directory if you have this one)
osl_startup
D_continuous = S2.D_continuous;
S2 = rmfield(S2,'D_continuous');
[epochinfo.trl, epochinfo.condition... |
9ec2204a829c9cd50d16f4cf6ac3dd463af912dcc5e811e4bd72a7d5070b0665 | MATLAB | 470 | 20 | function x = fac2var( f, v )
%Converts a cell array of strings or term of this to a numeric variable.
%
% Usage: x = fac2var( f [,v] );
%
% f = n x 1 cell array of strings or term of this.
% v = 1 x k numeric vector of values for the k unique strings in f, in
% ascending order, =1:k if absent.
%
% x =... |
563e12d93bcf2b5b4125563496c12842c0f566ee3753373392cc64cb3b672b91 | MATLAB | 473 | 21 | function item = nst_parse_bst_item_name(item_name)
%TODO: handle error scenarios
item.comment = '';
item.subject_name = '';
item.condition = '';
split_re = '(?<root>.*/)?(?<item>[^/]+)';
toks = regexp(item_name, split_re, 'names');
if ~isempty(toks)
item.comment = toks.item;
if ~isempty(toks.root)
t... |
2cf9ab2b43b6eb3e2c5e04370354ef813f4a533f9d582626ccd9197fde1cb88e | MATLAB | 474 | 16 | function clusters = loc_list_find_clusters(data,idx)
idx_unique = unique(idx);
clusters = cell(length(idx_unique),1);
%boundary = cell(length(idx_unique),1);
for i = 1:length(idx_unique)
I = idx == idx_unique(i);
x = data(I,1);
y = data(I,2);
clusters{i}(:,1) = x;
clusters{i}(:,2) = y;
... |
52494aeb8060a330a7a4a0dc161b4134021543fd085fbd9413e791e476363066 | MATLAB | 476 | 22 | function [granger,freq]=createauto_timefreq(data1,freqrange,toy)
equis=0.5;
cfg = [];
cfg.method = 'mtmconvol';
cfg.taper = 'hanning';
cfg.pad=8;
cfg.foi = freqrange;
cfg.t_ftimwin = 0.5.*ones(size(4./cfg.foi'));
cfg.tapsmofrq = equis*cfg.foi;
cfg.toi=toy;
cfg.output = 'fourier';
cfg.keep... |
f722fb4f4912898df0ce0be827345c98c39a5d2bca1917c1be440f81e6b65897 | MATLAB | 476 | 13 | function [x_pdf,y_pdf,x_cdf,y_cdf] = calculate_pdf_cdf_norm(data,percentile)
temp = data;
temp(isnan(temp)) = [];
data = data/mean(temp);
I1 = prctile(data,percentile(1));
I2 = prctile(data,percentile(2));
wanted = data(data<I2 & data>I1);
x_hist = linspace(min(wanted),max(wanted),1000);
y_pdf = histcounts(want... |
4df9eed3ee43f7d07296c330298edcbb654079c92ad717768d2e4d5d53f7ffb6 | MATLAB | 478 | 20 | function send_data_to_workspace(data_to_send)
global data listbox
if isempty(data)==1
data=data_to_send;
else
if size(data_to_send,1) > 1
data_to_send = data_to_send';
end
data_to_send = data_to_send(~cellfun('isempty',data_to_send));
data= horzcat(data,data_to_send);
end
if i... |
e9935b2399c8e38cf44d9038ef6440ebe78e93c8d272a5f855048f2a27b2e73e | MATLAB | 483 | 29 | clear
% Fig 1
% mipp_fig_vol_vs_time
% mipp_fig_morphologyVStime_v2
% Fig 2 is partially created outside of matlab
% mipp_fig_histology (insets)
% Fig 3
% mipp_fig_gwf_v2
% Fig 4 mouse 2 and 103
% mipp_fig_parammaps_treatevsuntreated
% Fig 5
% mipp_fig_par_vs_time_inc_stats
% Fig 6, case 1 and 4
% mipp_fig_signal... |
93e75348158e8c046353c71ca15c37b619a2d9ab40386506ab66cbaf0554825f | MATLAB | 485 | 23 | function [data_cell] = pl_mat2cell(data)
%
% Converts an N dimensional array (n x m1 x m2 x ...) into a cell (n x 1)
% of N-1 dimensional arrays (m1x m2 x ...)
% Data in this form will be processed faster in permutationlab
%
% This function is part of the permutationlab software:
% Author: Dimitrios Pantazis
... |
ad25a04b668526b6a8e6f7d427b9be8b6c0f7974a94fd4306f1dab176270a8a3 | MATLAB | 488 | 19 | function utest_reset_bst()
% Remove unit test protocol from brainstorm DB
% Reset stored messages.
global GlobalData;
% Delete unit test protocol
ProtocolName = 'nst_utest';
gui_brainstorm('DeleteProtocol', ProtocolName);
db_dir = bst_get('BrainstormDbDir');
nst_protocol_dir = fullfile(db_dir, ProtocolName);
if exist... |
49656f155c02ba10de0108ab35523e0f07e665844797418902a7685c55b581d3 | MATLAB | 489 | 17 | function FC_project = get_conds(FC_project)
condition_choices = split(num2str([1:FC_project.ncon]),' ');
condition_prompt = 'Which conditions would you like to include?';
tf = 0;
while tf==0
if ~isfield(FC_project,'include')
[conds,tf] = listdlg('PromptString',condition_prompt,'ListString',conditio... |
68089bf6f9a6f09a6e30ed11f1714a900eca6588102cdc2d5857c750fef9b721 | MATLAB | 489 | 16 | function area = Area(TRI,Vertice_Location)
Tri_Num = size(TRI,1);
area = zeros(Tri_Num,1);
%area2 = zeros(Tri_Num,1);
for i=1:Tri_Num
v1 = Vertice_Location(:,TRI(i,1)) - Vertice_Location(:,TRI(i,2));
v2 = Vertice_Location(:,TRI(i,1)) - Vertice_Location(:,TRI(i,3));
sinus = sqrt(... |
28bbbb3a90bbfc14f06e864f82ac63272bcbbd345072c00cfac40f2b3002a7ac | MATLAB | 491 | 15 | classdef None < nla.net.mcc.Base
properties (Constant)
name = "None"
end
methods
function [is_sig_vector, p_max] = correct(obj, net_atlas, input_struct, prob)
p_max = input_struct.prob_max;
is_sig_vector = prob.v < p_max;
end
function ... |
d8e4efa188db8a584f083b7357c28808cbcafafafe5f4d81a8bb6ef0019212a0 | MATLAB | 492 | 18 | % Load the session you want to analyze
clc;close all;clear
[file,path] = uigetfile('*.mat','Load the MATLAB file');
% Do the analysis
if isequal(file,0)
disp('User selected Cancel'); % Stop the script.
else
filename = fullfile(path,file);
load(filename,'data');
textdata = cell(numel(data),1... |
da98483dc1efe0a2fb41b4f84c0052de0bb0c4c6a7bbc89047e32db888173086 | MATLAB | 492 | 16 | function data_scaled = loc_list_add_by_number(data)
answer = inputdlg({'Number:'},'Input',[1 50],{'1000'});
if isempty(answer)~=1
number = str2double(answer{1});
data_scaled = cell(1,length(data));
for i = 1:length(data)
data_scaled{i} = loc_list_scale_data_inside(data{i},number);
end
... |
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