sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 17k | content stringlengths 1 200k |
|---|---|---|---|---|
d95b4dc17d941efc7be29b2f91660e36004eec049283467689cb686c668cee42 | MATLAB | 690 | 14 | load empiricalAwake.mat
load empiricalSleep.mat
create_AALnifti(mean(Hierarchy),'aw_hierarchy.nii.gz',1);
create_AALnifti(mean(Hierarchy2),'sl_hierarchy.nii.gz',1);
create_AALnifti(mean(Hierarchyn2),'sln2_hierarchy.nii.gz',1);
create_AALnifti(mean(SpatialTemporalBroadness_sink),'aw_sink.nii.gz',1);
create_AALnifti(me... |
3a4f535306d80499112a821f5f06850be80cc0198b8fc1a0b0aa3cf744d936f4 | MATLAB | 691 | 23 | function transformations = tc_decomposeMatrix(M)
transformations.translation = M(1:3, 4)';
L = M(1:3, 1:3);
sx = norm(L(:, 1));
sy = norm(L(:, 2));
sz = norm(L(:, 3));
if det(L) < 0
sx = -sx;
end
transformations.scale = [sx, sy, sz];
L_norm = L ./ repmat(transforma... |
2a70163ec9776fc53589ce71333f25a16b934c3475eb45aa1b64e5f313816980 | MATLAB | 692 | 28 | function txt=SurfStatDataCursorP(empt,event_obj)
pos=get(event_obj,'Position');
h=get(event_obj,'Target');
v=get(h,'Vertices');
x=get(h,'FaceVertexCData');
id1=min(find(v(:,1)==pos(1)&v(:,2)==pos(2)&v(:,3)==pos(3)));
tag=get(get(h,'Parent'),'Tag');
[s,a,id0]=strread(tag,'%s %d %d');
id=id1+id0
c=get(get(h,'par... |
2c73b1fdd740f92e0a5aae91a723f47f65aa8703bf13222ec9f78e0554d6fb4b | MATLAB | 693 | 22 | function clusters = loc_list_extract_clusters_from_data(data)
area = data.area;
count(1) = 1;
counter = 1;
for i = 2:length(area)
if area(i)~=area(i-1)
counter = counter+1;
count(counter) = i;
end
end
for i = 1:length(count)
if i== length(count)
clusters{i}(:,1) = data.x_... |
8163ab9b072da16bc32e23a7ee4e37208113199aeb3822f08b9bb9eaa32e05c0 | MATLAB | 694 | 28 | function s=minus(t1,t2)
if (~isa(t1,'term') && numel(t1)>1) || (~isa(t2,'term') && numel(t2)>1)
warning('If you don''t convert vectors to terms you can get unexpected results :-(')
end
t1=term(t1,inputname(1));
t2=term(t2,inputname(2));
if isempty(t1) || isempty(t2)
s=t1;
return
end
n1=size(t1.ma... |
4c0bcb8f6e3f4f3ab9143f9697a491d490a3a6b2060db295abfae40f9755e9f7 | MATLAB | 698 | 27 | function piled_data = loc_list_pile_data(data)
f = waitbar(0,'Piling Data');
for i = 1:length(data)
waitbar(i/length(data),f,'Piling Data');
x{i} = data{i}.x_data;
y{i} = data{i}.y_data;
area{i} = data{i}.area;
end
close(f)
x = vertcat(x{:});
y = vertcat(y{:});
area = vertcat(area{:});
d... |
a9841c0c050c062b0c0c059b224ebbd34bd08c4c8a6ab7327407fa0540a333d2 | MATLAB | 701 | 17 | function O = StandardErrorGaussian(S)
O = [];
%0.1-1Hz
indir = dir('/scratch7/MINDLAB2017_MEG-LearningBach/Leonardo/LearningBach/source/source_localsphere_01_1Hz_AllTrials_BC_2.oat/subj*dir');
DAT = zeros(23,27,23,400,length(indir)); %3D image, time-points and then subjects
for ii = 1:length(indir) %over subjects
... |
c7b00dfb0ca891cff069f6ae4392ee25813ec966246a73f9f80ae45984468769 | MATLAB | 702 | 14 | function out = convert_2_AAL3_indices(in)
AAL3_clusters = [1 2 3 4 5 6 7 8 9 10 11 12 13 14....
15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32....
33 34 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52....
53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70....
71 72 73 74 75 76 77 78 79 80 83 84 85... |
e94dfbe85f2856a4e947ddd7e87ff909ddcfaf6eed229604a54e52e43edade11 | MATLAB | 703 | 35 | function m = resQ_1d_data2fit(signal, xps, opt, ind)
% function m = resQ_1d_data2fit(signal, xps, opt, ind)
if nargin < 4
ind = ones(xps.n, 1, 'logical');
end
if ~all(ind)
signal = signal(ind);
xps = mdm_xps_subsample(xps, ind);
end
s_nrm = median(signal(xps.b<0.5e9));
if isfield(xps, 'sig... |
44008c1d72476b869d1615b551ef079ec4acb96c6555c1c050836d69cf4d2ec6 | MATLAB | 704 | 33 | function [ind_, r_, G_] = set_part_traj(pnts, G, dist_thr, num_sources, T)
n_pnts=size(pnts,1);
ind_ = zeros(num_sources, T);
distMat = inf*eye(num_sources,num_sources);
dmin = 0;
nr = 3*num_sources;
%
while dmin < dist_thr
idx = randperm(n_pnts);
id = idx(1:num_sources);
for i=1:1:num_sources
... |
e194eb220b7518cddc43e9618ffededc5a98eae9ca8ad185274e3a1294261ed5 | MATLAB | 706 | 25 | % function adapted from the LiNGAM package
% complete software may be downloaded from http://www.cs.helsinki.fi/group/neuroinf/lingam/
function [Wopt,rowp] = permnozerihungarian( W )
%--------------------------------------------------------------------------
% Find best row permutation by hungarian algorithm
%... |
651c3dc76334392623d3bc0e4893ba513bfa9f692ca157237533691cc8a8c4a9 | MATLAB | 707 | 28 | function C=clustering_coef_bu(G)
%CLUSTERING_COEF_BU Clustering coefficient
%
% C = clustering_coef_bu(A);
%
% The clustering coefficient is the fraction of triangles around a node
% (equiv. the fraction of node's neighbors that are neighbors of each other).
%
% Input: A, binary undirected... |
0be306523c1c6a33edf17421f9237c8db23dc692e5315de3fd28a32943829afe | MATLAB | 711 | 15 | function obj = drawCortexHemi(ax, anat_hemi, mesh, color, mesh_alpha)
% DRAWCORTEXHEMI Draw one hemisphere of the cortex
% ax: axes to display in
% anat_hemi: anatomy mesh of one hemisphere of the brain
% mesh: vertices of anatomy
% color: 3x1 vector, cortex mesh color
% mesh_alpha: tr... |
cf6cb8078b3fbd005f94750e7bdf5446b85d0c372dd0e1551c7d6322194cca39 | MATLAB | 711 | 39 | function [granger,granger2]=granger_automation(input1,input2,freqrange)
label = [{'PFC'}; {'HPC'}];
%% input1
clear Data
fn=1000;
leng=length(input1);
ro=3000;
tm=create_timecell(ro,leng);
Data.label=label;
Data.time=tm;
Data.trial=input1.';
%
cfg.bsfilter = 'yes';
cfg.bsfreq = [49 51];
Data = ft_preprocessing(cfg,... |
bceb11f37d844ed9b9047f9a9f735ae20771b3bb7aab98b6c0ef0e9f51c69b0e | MATLAB | 715 | 41 | function [data, A] = two_source_model(T)
M = 2; %number of sources;
P=2; %order of the model
T0=1000; %length of ignored start
%Generate stable AR matrix
Rmax=50;
%Generate stable AR matrix
while Rmax>3
lambdamax=10;
while lambdamax > 1 || lambdamax < 0.9
A=[];
for k=1:P
aloc = zeros(M);
alo... |
7e6ea9af0cbba10f86b39d59e53ddd7abce1c1393ec89e274f9b8ecb124fd831 | MATLAB | 716 | 19 | function shape_classification_kmeans(data)
input_values = inputdlg({'k-means k value:'},'',1,{'10'});
if isempty(input_values)~=1
parameters = shape_classification_normalized_parameters(data.classes);
kmeans_k = str2double(input_values{1});
idx = kmeans(parameters,kmeans_k);
classes = cluster... |
7e12c4eb1c9225c725ce3459b99ef5f52e8a7ee06961f44402dad31535e9f304 | MATLAB | 719 | 26 | function loc_list_roi(data)
try
coordinates = getline();
data_roi = cell(1,length(data));
for i = 1:length(data)
data_roi{i} = loc_list_roi_inside(data{i},coordinates);
end
data_roi = data_roi(~cellfun('isempty',data_roi));
catch
data_roi = [];
end
loc_list_plot(data_roi)
... |
abb46bd529ce9eb89c54c4910df4822f4cc463043237da982f00235ebbc0a508 | MATLAB | 720 | 34 | function [h, yl] = mipp_plot_histogram(data, lims, do_filter)
if do_filter
data = mipp_parameterFilter(data);
end
mdat = median(data(:));
if strcmp(num2str(abs(mdat), '%0.2f'), '0.00')
mdat = 0;
end
[~, sdat] = iqr(data(:));
hx = linspace(lims(1), lims(2), 51);
h = histogram(data(:), hx, 'FaceColor', [.8 ... |
bcf7a93734a3c05fbfc41d8fbaf4ebde8620bfab3f39653b72f2fd32c752eaf8 | MATLAB | 720 | 32 | %% SPEARMAN or KENDALL test for independence
% null hypothesis: uncorrelation
% if p<alpha, reject -> presence of correlation
% input: X row column
% tipo: 'Spearman', 'Kendall'
function [pM,rho,contarigett,stringout,stringflag]=test_independence(X,tipo,alpha);
M=size(X,1); % n. of signals
N=size(X,2); % l... |
9264645f24d722966f0650abf4528e95ad12b7f34e896985cbf0b500587f60b6 | MATLAB | 721 | 25 | function index = Which_StreamIndex_ThisLink(i,j, dFCstream)
% FUNCTION index = Which_StreamIndex_ThisLink(i,j, dFCstream)
% returns theordinal index of a link in the vector representation of a
% symmetric FC matrix, where the maximum value for (i,j) is equal to the
% number of regions.
% NB: j must be strictly la... |
bde49df2b9cb27b0f01d7e1e6c5700d29970f4db8e4a93e680bc9548cf2c4fd4 | MATLAB | 721 | 25 | function dataERP = eegTimelockOnVC(parameterSettingsVCERP, dataVC)
%% dataERP = eegTimelockOnVC(parameterSettingsVCERP, virtChannels, dataTL)
tc_struct2ws('caller', parameterSettingsVCERP)
newDataTL=[];
newDataTL.trial=dataVC.virtChannels;
newDataTL.time= arrayfun(@(x) {dataVC.time},1:size(newDataTL.trial,2));
newDat... |
b5eaaec9177fab93554aaa837a5c9444e3127f315616928b5246d4f420e53bb7 | MATLAB | 726 | 28 | function [kden,N,K] = density_und(CIJ)
% DENSITY_UND Density
%
% kden = density_und(CIJ);
% [kden,N,K] = density_und(CIJ);
%
% Density is the fraction of present connections to possible connections.
%
% Input: CIJ, undirected (weighted/binary) connection matrix
%
% Output: kden, density
%... |
ef96df666214743ea58c5b554ff5f2cb39a33568a47f0daa0edd8fbff8f10397 | MATLAB | 727 | 17 | % Taken from fileexchange and Matlab 2024a
function hex = rgb2hex(rgb_color)
assert(nargin==1,'This function requires an RGB input.')
assert(isnumeric(rgb_color)==1,'Function input must be numeric.')
sizergb = size(rgb_color);
assert(sizergb(2)==3,'rgb value must have three components in the form [r ... |
ec81b923f18f84d59ab948831e9b1f9c1b64d23dbfd97c3895d51d512cc655d6 | MATLAB | 728 | 21 | function shape_classification_som(data)
classes = data.classes;
input_values = inputdlg({'number of nodes'},'',1,{'8'});
if isempty(input_values)~=1
parameters = shape_classification_normalized_parameters(classes);
nn_dim = str2double(input_values{1,1});
disp('finding k clusters form som')
di... |
52e092e6139bd1e9a80dd8f1d0890a90c459bafa3f583487d6e7858209e831c1 | MATLAB | 730 | 37 | function FC_project = get_ncon_nsub(FC_project)
disp('Getting number of conditions...')
cd(FC_project.CONN_preprocessing_dir)
% Get number of conditions
i = 1;
j = 1;
while i==1
if numel(dir(sprintf('*_Condition%03d.mat',j))) < 1
ncon = j-1; % number of conditions in CONN output folder
... |
2bf786345e092d99cad9a4106df940e37c7972dcf2c20bfd5caffe9333c5cb74 | MATLAB | 731 | 15 | function root_path = findRootPath()
%FINDROOTPATH Find the root path of the NLA toolbox
% path_split = split(string(which('nla.VERSION')), "/");
% path_joined = join(path_split(1:end-2), "/");
% root_path = char(path_joined + "/");
root_path_no_ending_slash = fileparts(which('nla.VERSION'));
%r... |
9f863a1f9b409d7780a933132667833eb5b69bf8c1045e2b51a8a0bc4eba859b | MATLAB | 731 | 29 | function [ind_new, Vr] = LW_model(loc, delta, p)
n = size(loc,1);
N = size(loc,2);
nverts=size(p,1);
a = (3*delta - 1)/(2*delta);
h2 = 1 - a^2;
mean_ = a.*loc + repmat((1-a)*mean(loc,2), [1 N]);
Vt = (var(loc,0,2)'+ 1e-8).*eye(n);
Vr=h2*Vt;
loc = mean_ + chol(Vr)*randn(n,N);
% h2 = 1-((3*c-1)/2*c)^2;
% a = sqrt(1-h2);... |
f41d0fa1ac1b7e24fe184279cb30db99a9c2c0ae054a315dd9d8170251032fae | MATLAB | 734 | 21 | %% data
data=xlsread('X:\Elite\LARS\2013\oktober\bsa dmso test\BSAN2DMSO3med.xlsx');
%data=xlsread('X:\Elite\LARS\2013\oktober\bsa dmso test\BSAhigh.xlsx');
%% compare area
plot(log(median(data(:,6:7)')),log(median(data(:,8:10)')),'r.')
ylabel('DMSO')
[h,p,ci] = ttest(median(data(:,6:7)'),median(data(:,8:10)'... |
c67fce896c09412363ce88f30697daac8a46ca55cb93a7ac445a3db65e6ae7cf | MATLAB | 736 | 31 | function dFC = dFCstream2dFC(dFCstream)
% FUNCTION dFC = dFCstream2dFC(dFCstream)
% takes dFCstream as input ('2D' or '3D') and calculates dFC [FxF] matrix,
% where F is the number of network frames in the input dFCstream.
%
% Example: dfc = dFCstream2dFC(dfcstream)
if (ndims(dFCstream) == 3)
dFC... |
c468ca62e19929cf31eb2eef5ab6cdc90ab5bf61baee52c02b127268cb68eccb | MATLAB | 738 | 32 | classdef ContrastInput < handle & matlab.mixin.Copyable
properties
dataTable = [];
name = '';
contrastVector = [];
end
methods
function isValidFlag = isValid(obj)
if any(~isspace(obj.name))
isValidFlag = true;
else
... |
e00d7815f7ac7db5bbab14fffb75e5326b4b33d7840853e0aba36fb9620c927b | MATLAB | 740 | 22 | classdef OrdinaryLeastSquares < nla.edge.test.SandwichEstimator
methods
%Hacky way to change name and coeff_name in superclass is to change
%properties in constructor
function obj = OrdinaryLeastSquares()
obj = obj@nla.edge.test.SandwichEstimator();
... |
06485eae759fba1f0db9e65bbd72bbef0998081803e2df119c37b23ae531529c | MATLAB | 742 | 15 | function shape_classification_coeff_of_variation(data)
classes = data.classes;
N = cellfun(@(x) length(x), classes(:,1));
for i=1:size(classes,1)
variation(i,:) = abs(std(classes{i,2},0,1)./mean(classes{i,2},1));
end
similarity_measure = sum(N.*variation);
variation = variation(:,[1:2,7:8]);
similarity_meas... |
c8a400fd7d58ac535e69af9def589fa300ea6b1c28adbeb4696fa15c8a466714 | MATLAB | 742 | 28 | function [R] = dcor_dc(X,Y)
% [R] = dcor_dc(X,Y)
% Computes the double centered distance correlation between X and Y.
% Rows represent the examples, and columns the variables.
% Based on: http://www.mathworks.com/matlabcentral/fileexchange/49968-dcorr--x--y--
% and, the R package energy and papers by Szekely and Rizz... |
2fd1ecd77fdd4e0230c3b71d5caf1267eb57b21e91925d28b5e7cbbd6cc4e950 | MATLAB | 745 | 30 | function tc_compress_files(folder, name, zipname, deleteind)
%% tc_compress_betas(folder, name, zipname, deleteind)
%
% zip files in folder and delete
%
% folder: folder containing the files
% name: regexp of file names
% zipname: archive name
% deleteind: whether to delete
disp('compressing files...')
% get files in f... |
db5f558426ec0ca3111213b14096cdedcf555c8810c3dc6f91bd5e8255920d55 | MATLAB | 745 | 21 | function W = morlet_wavelet(t,fc,sigma_tc);
% function W = morlet_wavelet(t,fc,sigma_tc)
%
% Returns the complex Morlet wavelet for a specified central frequency and standard deviation
%
% INPUTS:
% t: timepoints where the wavelet will be calculated
% fc: central frequency
% sigma_tc: standard deviation o... |
03c457945a07826f71cbe3c9df5b76f67d62aaa3266eed2a9629e33c3f5a7b49 | MATLAB | 748 | 24 | function [v_id_mne, hemi, v_id] = map_locs_to_mne(avg_loc, mesh, incl_vert, src_l, src_r)
num_sources = size(avg_loc,1)./3;
v_id = zeros(num_sources,1);
m=size(mesh.p(incl_vert,:),1);
for i=1:1:num_sources
d = sqrt(sum((mesh.p(incl_vert,:) - repmat(avg_loc((i-1)*3 + 1 : 3*i, 1)', m, 1)).^2, 2));
v_id(i,... |
a257ec8c66017e79ae9b6276b9cdce8c5a7af5a7871226b43e889316bf78056b | MATLAB | 750 | 36 | function cb = SurfStatColLim( clim );
%Sets the colour limits for SurfStatView.
%
% Usage: cb = SurfStatColLim( clim );
%
% clim = [min, max] values of data for colour limits.
%
% cb = handle to new colorbar.
a=get(gcf,'Children');
k=0;
for i=1:length(a)
tag=get(a(i),'Tag');
if strcmp(tag,'Col... |
5b975483c95a2e0afbee617a9fe39e817a72fb0df65bdc64158724e4bc9dae76 | MATLAB | 751 | 19 | function interp_compartments = tc_interpolate_compartments(compartments, varargin)
%% interp_compartments = tc_interpolate_compartments(compartments)
%
% Interpolates layers (cubic).
%
% Input: n x layer matrix where n is the number of voxel and each layer
% column should hold a value representing the fraction of to wh... |
797e17e52a20f506c9abd5917127acab6f22f8cef020cfa72bd0ecdbb4db0928 | MATLAB | 753 | 22 | function fn = resQ_pipe(s, paths, opt, ind)
% function fn = resQ_pipe(s, paths, opt, ind)
if (nargin < 2) || isempty(paths), paths = [fileparts(s.nii_fn) filesep]; end
if (nargin < 3), opt.present = 1; end
if (nargin < 4), ind = ones(s.xps.n, 1, 'logical'); end
opt = mdm_opt(opt);
opt = resQ_opt(opt);
paths ... |
d8c69c35fe0a350398c22ac6c0fc76d51da301fb7d0d8208c146a0f2262b6919 | MATLAB | 753 | 16 | function AS_WTA_SepRes_bat(indir,outdir,TARGETROIdir)
% indir = uigetdir(pwd,'OrigData');
% outdir = uigetdir(pwd,'Outputdir');
% [TargetROI,FilPa,Filext] = uigetfile({'*.nii';'*.img'},'TargetROI');
% [vtar,dtar] = Dynamic_read_dir_NIFTI(fullfile(FilPa,TargetROI));
[vtar,dtar] = Dynamic_read_dir_NIFTI(TARGETROIdir... |
bd5d71445d756bfe87d4ec17fdc9f738fbda1ed5b46a3052d96393affea21406 | MATLAB | 754 | 19 | classdef HolmBonferroni < nla.net.mcc.Base
properties (Constant)
name = "Holm-Bonferroni"
end
methods
function [is_sig_vector, p_max] = correct(obj, net_atlas, input_struct, prob)
[is_sig_vector, adjusted_pvals, ~] = nla.lib.bonferroni_holm(prob.v, input_struct.prob_max);
... |
af0d927fa8cb55b30b8125879f77cb2313278fc8e77086b91817d709d1486bf1 | MATLAB | 756 | 28 | %% read
data=mzxmlread('F:\promec\Davi\_QE\BSAs\20150512_BSA_The-PEG-envelope.mzXML');
pkl=csvread('F:\promec\Davi\_QE\BSAs\20150512_BSA_The-PEG-envelope.pkl')
%% plot
pkli=pkl(pkl(:,2)>100000,:)
scatter(pkli(:,1),log(pkli(:,2)))
hist(pkli(:,1))
hist(log(pkli(:,2)))
pdpkl=pdist(pkl(:,1));
[nelements,centers]... |
e82bb2fea406f1291b9de88a929127d6e140b32249d975df617972060cb3f55e | MATLAB | 757 | 28 | function shape_classification_merge_shape_classes(data)
for i = 1:length(data)
classes{i} = open_classes(data{i}.classes);
end
classes = vertcat(classes{:});
data_to_plot.classes = classes;
data_to_plot.name = 'merged_classes';
data_to_plot.type = 'shape_class';
shape_classification_plot(data_to_plot);
end... |
1623e7981f91ced3652afd1ecc01014cf201d5ec21dca2c1b1a631f3c7fa9589 | MATLAB | 758 | 28 | %% ESTIMATES STRICTLY CAUSAL MVAR MODEL GIVEN EXTENDED MVAR MODEL
% output: Am=[A(1)...A(p)], M*pM matrix of strictly causal MVAR coeffs
% output: Su, input covariance matrix of strictly causal MVAR model
% input: Bm=[B(1)...B(p)], M*pM matrix of extended MVAR coeffs
% input: B0, M*M matrix of instantaneous ef... |
94636a797498153c3e465af23be40f21e7987ab0ce54d5f8621baced1e8054f9 | MATLAB | 759 | 34 | function FC = TS2FC(TS, format)
% FUNCTION FC = TS2FC(TS, format)
% takes time-series (TS) as input and calculates static functional connectivity
% (FC) as output.
%
% inputs: TS(t,n) --> rows are t different time-points;
% columns are n different regions;
% format --> '2D' (default) provi... |
f3cbc8d9e0387aad6b0af392aeaf28daaada646a589c7f4efaa3b774f5d8b8de | MATLAB | 759 | 18 | function data = load_gradient(name,idx)
% LOAD_GRADIENT loads template gradients.
%
% data = LOAD_GRADIENT(name,idx) loads template gradients. For functional
% connectivity gradients set name to 'fc', for microstructural profile
% covariance gradients set it to 'mpc'. idx can be set to 1 for the first
% gradi... |
4864c450687e46599eb7275a932d044e52a3d264baef26c337089911205b00cf | MATLAB | 760 | 30 | function [status]=emabv1(TOFfn, m1, s1, m2, s2)
% Program for TOF-MRA segmentation to obtain air and bone mask.
% USAGE:
% [status]=emabv1(TOFfn, m1, s1, m2, s2);
% Empirical values for inputs:
% m1=6; s1=4; m2=100; s2=50;
%
% Algorithm adapted from Wilson & Noble, IEEE TMI 1999 18(10) 938-945.
% Yi Su, 11/1... |
00cd314196c167c755aa078924889f318fccde12d7cb2449868643aeb37a80e5 | MATLAB | 762 | 20 | if ~exist('dFC_project','var') || ~isfield(dFC_project,'dFC')
msgbox('You must load or create a dFC project before running connectivity states analyis')
else
maxk = inputdlg('What maximum value of k would you like to use? ', 'Choose max k value to try...', [1 45]);
[condition,tf] = listdlg('SelectionMod... |
4c0fb3c5f26141fe4dac69ac2a67db76e26307522f4c79e45512253089f1598b | MATLAB | 762 | 26 | clc;
clear all;
close all;
G1 = 1; % row number of gene 1 in the data set
G2 = 2; % row number of gene 2 in the data set
% [filename, pathname] = uigetfile({'*.txt';'*.xls';'*.*'},'Select file');
% gene_raw=load(strcat(pathname,filename));
% gene_raw=xlsread('SigAll.xlsx');
c1 = 3; % number of samples in c... |
d5da4bc33a7170bf6409d3bb08abb81197c82dcc558e71e5f1fab6cf07c0c84e | MATLAB | 765 | 36 | function out = slices2mosaic(mat,fillValue)
if nargin < 2
fillValue = 0; % Default to filling with zeros
end
x=size(mat,1);
y=size(mat,2);
z=size(mat,3);
if ndims(mat) == 4
t = size(mat,4);
else
t = 1;
end
% find the side length of the mosaic image ... |
232af0a9d3da7250ad2e3300f80e43e811c6cb7135ac09a5c4ad043000321616 | MATLAB | 766 | 29 | %% read
lfq = tblread('L:\Elite\Aida\RawFiles\Samples\LFQcc.txt','\t');
ss = tblread('L:\Elite\Aida\RawFiles\Samples\SScc.txt','\t');
ssc=tblread('L:\Elite\Aida\RawFiles\CellLines RawFiles\hierarchical-data-1col.txt','\t');
%% linearize
lfqr=lfq(:)
ssr=ss(:)
lfqr(isnan(lfqr))=1
ssr(isnan(ssr))=1
%% plot
p... |
fc90ec31513a08e725209374765ea8dae1b428df937664431c0f7f76e8492df5 | MATLAB | 766 | 27 | function [PDC_sig, PDC_bin, f] = get_significant_pdc(x, Am, S, numsurr, nfft, fc, Ns, p)
S1=S .* eye(Ns);
for is=1:numsurr
for ii=1:Ns
for jj=1:Ns
if ii~=jj
xs=surrVCFTd(x,Am,S1,ii,jj);
[Ams,Sus]=idMVAR(xs,p,2);
Sus = Sus .* eye (Ns);
... |
9b3ec7dbe96166b1cc2f528468b9f21761eceafe751349c613950b453d65a746 | MATLAB | 767 | 26 | function parameters = loc_list_extract_parameters(data)
area = unique(data(:,3));
[~,data] = pca(data(:,1:2));
major_axis_length = max(data(:,1))-min(data(:,1));
minor_axis_length = max(data(:,2))-min(data(:,2));
x_r = data(data(:,1)>=0,:);
x_l = data(data(:,1)<=0,:);
u_r = x_r(x_r(:,2)>=0,:);
l_r = x_r(x_r(:... |
7c9112d9325940f5de8a6e483e244bb2468236eba7ba35c8be8eb7284d4e7ffe | MATLAB | 768 | 25 | [project_file,project_path] = uigetfile(pwd,'Select dFC project file',which('findme.m'));
app.DynamicFunctionalConnectivityToolboxUIFigure.Pointer = 'watch';
x = app.center_x;
y = app.center_y;
fig = uifigure('Position',[x-85 y-35 170 70]);
uitextarea(fig,'Value','Loading Project...','Position',[10 10 150 50])... |
c8e3721d55b17ac2f43f7ded852eb40248da89cd7be7d44329eb67d65fd64c2f | MATLAB | 769 | 26 | function [B,proj_X] = nst_glm_fit_B(model,y, method)
% nst_glm_model_fit_B - fit the model to compute B using either SVD or the
% pseudo-inverse
if nargin < 3
method='SVD';
end
X=model.X;
switch method
case 'SVD'
[X_u, X_s, X_v] = svd(X,0);
X_diag_s = diag(X_... |
212b042031b49965408ee402b7c02ba99e3249609bd3a74e0f5fb2373cba8cd7 | MATLAB | 770 | 33 | % Imbed a zoom menu to any figure.
%
% Usage: rri_zoom_menu(fig);
%
% - Jimmy Shen (jimmy@rotman-baycrest.on.ca)
%
%--------------------------------------------------------------------
function menu_hdl = rri_zoom_menu(fig)
if isnumeric(fig)
menu_hdl = uimenu('Parent',fig, ...
'Label','... |
76952e4c0cc33f4ebc4940d146eca7c9ef49aaa8c140fb4a6456fc28ad90cb6d | MATLAB | 771 | 25 | function P = morlet_transform_singlesub(ts,fc, fwhm,srate,baseline)
% INPUTS:
% ts: time series for each trial (time x trial)
% fc: central frequency of the wavelet
% fwhm: full width half maximum of the wavelet
% srate : sampling rate of the data
% baseline: array that contains the time indices for normali... |
94d946398436617a20a7be4a354c87be6c64f09712c229343de4d86bb8ef2536 | MATLAB | 771 | 18 | function loc_list_add_scale_bar(data)
subplot = @(m,n,p) subtightplot (m, n, p, [0 0], [0 0], [0 0]);
answer = inputdlg({'Pixel Size (nm per pixel):','Scale Bar Size (x-axis um):','Scale Bar Size (y axis um):'},'Input',[1 50],{'116','2','0.5'});
if isempty(answer)~=1
pixel_size = str2double(answer{1});
s... |
d379fbd11450302c1cd7e9bc196113b565dd5acea471ecccacae84963976157f | MATLAB | 771 | 33 | %% read
el=xlsread('X:\Qexactive\130529_Incremental\Multiconsensus from 3 ReportsPepSNPG.xlsx')
el=xlsread('X:\Qexactive\130529_Incremental\ELINP.xlsx')
%% plot
hist(el(:,18)) % charge
hist(el(:,19),[100]) % detect
hist(el(:,20)) % MZ
hist(el(:,22),[100]) % RT
hist(el(:,21),[1000]) % RT
... |
b4830c2b1c0ae54e8fb4bc97378edcf11b41e4f0e198fd27a493aad288606fa9 | MATLAB | 773 | 29 | function utest_bst_setup(gui, server_mode)
% Run brainstorm with no user interface, if not already running.
% Force brainstorm to run in server mode (no user interaction).
% Activate exception bypassing. It requires to override bst_error, bst_call
% and bst_process with the ones from nirstorm
% -> use nst_install('lin... |
772f3bfdba2c349a817b30bf3730d732056234e211d2d45f13e8ba25ed3b5b4f | MATLAB | 775 | 22 | function loc_list_voronoi_clusters_loc_list_plot(data)
f=waitbar(0,'Please wait...');
for i=1:length(data)
color = linspace(0,1,length(data{i}.clusters_points));
color = color(randperm(length(color)));
for j = 1:length(data{i}.clusters_points)
points{j} = data{i}.clusters_points{j};
c... |
6a9549fb16da3100bb3f52221b62e5729c685dbfd7bd566555d9245765a34fe1 | MATLAB | 776 | 29 | classdef Network < handle & nla.interfaces.IndexGroup
%NETWORK Network meta-information and contained regions of interest
properties
name
color
indexes % indexes of ROIs(regions of interest) that make up the network
end
methods
function obj = Network(name, color... |
a5eda05f0c9ec4ebe64c5b8265f6c968c58d7dabe7fa2cea3527f3b18b5e2ffc | MATLAB | 781 | 27 | function v2 = smooth_vol_osl(vol_as_matrix, mask_fname, fwhm)
%computing spatial smoothing
% vol_as_matrix = data (voxels x time-points)
% mask_fname = character with path to a standard brain mask
% fwhm = paramter for spatial smoothing (e.g. 100)
[mask,res,xform] = nii.load(mask_fname);
mask(mask>0) = 1; % ... |
10086bcc2dccada5c279b0d04ae5034303929c06e274fad2365386e1bc3fcefa | MATLAB | 787 | 29 | function [loc_est, id_est, G_mcmv, data_cov_inv] = MCMV_beamformer_localizer(Y, noise_cov, G, pnts, included_sp, num_sources)
%addpath('/m/nbe/scratch/braintrack/pnas_mne_results')
num_trials = size(Y,3);
T = size(Y,2);
data_cov = compute_cov(Y, num_trials, T);
for i=1:1:size(G,2)
eta_ai(i) = compute_ai(G(:,i), no... |
1b6fb0965908f22f6850038ab8539990652f6e4fb4a1e863504bfb8f0c8cdcb1 | MATLAB | 787 | 20 | function gains = nst_headmodel_get_gains(HeadModel, unused_iWL, sChannel, selected_channels)
warning('This function is depracted. For more information, consult https://github.com/Nirstorm/nirstorm/pull/266')
% Old head model
if ndims(HeadModel.Gain) == 3
HeadModel = process_nst_import_head_mod... |
5bb7801f54d7471252df6c92557d8439162506df7d1c135362c2bf75b1adb121 | MATLAB | 787 | 30 | %%
function O = coregfuncp(S) % apparently function need a 0 and no end to run in the cluster (!?), set the name of the function and the input variable
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 o... |
abd3c13572206be142cf5a9fbded1cd489282a6ef45d4965c7e3b7ab7c5c5109 | MATLAB | 787 | 34 |
function [x]=varEM(fstr,varname,numswitch)
% function for finding specified variable from EM config file (produced automatically using MATLAB)
%% Find Variable
ind=strfind(fstr,[varname,'=']);
%% Loop incase of more than 1 start found (i.e. t=)
if numel(ind) > 1
for j=1:numel(ind)
k=strcmp(fstr... |
9c5ff31edde2e98e94ced92ac38db3ee2605f5e51822ac1bda07e6fbcc984e65 | MATLAB | 790 | 20 | protmut='GAMGQLKPMEINPEMLNKVLSRLGVAGQWRFVDVLGLEEESLGSVPAPACALLLLFPLTAQHENFRKKQIEELKGQEVSPKVYFMKQTIGNSCGTIGLIHAVANNQDKLGFEDGSVLKQFLSETEKMSPEDRAKCFEKNEAIQAAHDAVAQEGQCRVDDKVNFHFILFNNVDGHLYELDGQMPFPVNHGASSEDTLLKDAAKVCREFTEREQGEVRFSAVALCKAA'
protwt='GAMGQLKPMEINPEMLNKVLSRLGVAGQWRFVDVLGLEEESLGSVPAPACALLLLFPLTAQHENFRKKQIEELK... |
1747f63c027c32b4406ab5bbf99c55c86f45fbbe6560d1856a63307b0dc4920d | MATLAB | 792 | 13 | function num_volumes = tc_num_volumes(num_trials, num_volumes_per_trial, skip_first_N_volumes, TR, pseudo_TR, TEEG)
%% num_volumes = tc_num_volumes(num_trials, num_volumes_per_trial, skip_first_N_volumes, TR, pseudo_TR, TEEG)
%
% computes the number of volumes given certain parameters:
%
% num_trials: number of trials
... |
2bd8100ada67c1db5c5d7bd519a26f5bea6ad9d9f15471de249b2115022a9fc8 | MATLAB | 793 | 35 | %% sqrt newton method
x=1;
for k=1:10
x=x-(x^2-2)/(2*x)
end
x=linspace(-10,0.1,10);
plot(x,x.^2,2*x,(x.^2)/(2*x))
%% secant method
clear x
x(1)=1
x(2)=x(1)+rand(x(1))
for k=2:5
x(k+1)=x(k)-(x(k)^2-2)*(x(k)-x(k-1))/(x(k)^2-2-x(k-1)^2+2)
end
plot(x,x.^2-2,'r-')
... |
42a50fa5bffd860d9a7c9b6c8e35985e2def90b5053f491126ac7e143fc33d42 | MATLAB | 801 | 47 | %% prob 2
rng(0,'v5uniform');
n=100;
m=300;
A=rand(m,n);
b=A*ones(n,1)/2;
c=-rand(n,1);
plot(c,A'*b,'r.')
%% simple_portfolio_data from https://class.stanford.edu/courses/Engineering/CVX101/Winter2014/courseware/
n=20;
rng(5,'v5uniform');
pbar = ones(n,1)*.03+[rand(n-1,1); 0]*.12;
rng(5,'v5normal')... |
8dda41552661f71463edee33829f11388451e68e4899c8bdde3ab584560d1326 | MATLAB | 801 | 21 | function spt_filter_tracks(data)
input_values = inputdlg({'minimum number of frames','maximum number of frames'},'',1,{'5','20'});
if isempty(input_values)==1
return
else
cutoff_min = str2double(input_values{1});
cutoff_max = str2double(input_values{2});
for i = 1:length(data)
fo... |
27af519975df259850199c3c0036aec1dee9656fecb4aceba23000edda544b7f | MATLAB | 803 | 20 | function y = cvx_check_dimension( x, zero_ok )
%CVX_CHECK_DIMENSION Verifies that the input is valid dimension.
% CVX_CHECK_DIMENSION( DIM ) verifies that the quantity DIM is valid for use
% in commands that call for a dimension; e.g., SUM( X, DIM ). In other words,
% it verifies that DIM is a positive integer... |
2ea3e68d99a6916423d459c9515d9adbbdcc6c4e3de26b87f1d64bb9cfaff87d | MATLAB | 803 | 30 | %TIMINGTEST Works out the average cputime required to run
% nearestneighbour
% This is a support function for nndemo.m
% T = TIMINGTEST(P, X, MODE)
% Runs NEARESTNEIGHBOUR(P, X, 'DelaunayMode', MODE) for at least one
% second, and returns the average cputime for a single execution
%
% ... |
736096b7ffef3cc80e7d20c46a8e6cac695f7afadc3612e0ca7fde3fd9f3d54f | MATLAB | 808 | 27 | clc;clear all;close all
[file,path] = uigetfile('*.mat','Select the .mat file containing the tracks');
name = fullfile(path,file); % Make it a full name to save it as later.
load(name);
path = uigetdir('*.xlsx','Please specify the folder where you want to save the csv files');
for j = 1:size(data,2)
cle... |
dab1fbeb3230fc607199030e39393e1fbbf3071aea5951f826088bcaa38d1923 | MATLAB | 810 | 23 | function [J, q_ks, P_ks] = kalman_smoother_gpu(P_kf_t, P_kp_t1, q_kf_t,q_kp_t1, q_ks_t1, P_ks_t1, A, N, Jt)
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'
P_kf_t=gpuArray(P_kf_t);
P_kp_t1=gpuA... |
f62e0c86270aeebb7cf96fce811807b95acf7c25bf9c785b18279468250ab4cd | MATLAB | 810 | 24 | function unpiled_data = unpile_data(data,name)
f = waitbar(0,'Unpiling Data');
unpiled_data = [];
for i = 1:length(data)
waitbar(i/length(data),f,'Unpiling Data');
DataConcat = horzcat(data{i}.x_data,data{i}.y_data,data{i}.area);
DataSplit = splitapply(@(x){(x)},DataConcat(:,1:3),data{i}.channel);... |
fb3f4c1af86fff74b5ccc5daaeff41b001391cbcd527753b20888e6b8e9a4d38 | MATLAB | 814 | 30 | function Reordered = HCPexOrdering(inputMat,direction)
% ReorderMat = HCPexOrdering(inputMat,direction)
%
% Input: inputMat, Matrix (360x360 or 412x412) based on HCPMMP or HCPex
% direction, old > new = 1; new > old = -1
%
% Output: ReorderMat, Reordered Matrix (412x412 or 360x360)
%
% Note: HCPex_LabelID.ma... |
05c9aa5adfda8529f82cea57de0f73d2ad836506ec61ed4b76678f520dbc08fd | MATLAB | 815 | 21 | function [q, P, Kf] = gpu_kalman_update(q, P, Y_, G, G_, XI, N, Jt)
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'
ny=size(Y_,1);
nq=size(q,1);
ns=size(G,2);
Kf = gpurdivide(gputimes(P(:,1:ns,... |
66235dddf3da72f586a23486eeca2bbf031715184f089a5ba09b67eb3c2bd0ad | MATLAB | 815 | 30 | function Reordered = HCPexOrdering(inputMat,direction)
% ReorderMat = HCPexOrdering(inputMat,direction)
%
% Input: inputMat, Matrix (360x360 or 412x412) based on HCPMMP or HCPex
% direction, old > new = 1; new > old = -1
%
% Output: ReorderMat, Reordered Matrix (412x412 or 360x360)
%
% Note: HCPex_LabelID.ma... |
bf9721d8cd73ba3909e5e0bb14d6c9137f1b883d8e9ce3ad3d9e8cdcf70b78a0 | MATLAB | 820 | 19 | function [metric_lh,metric_rh] = load_marker(name)
% LOAD_MARKER loads metric data.
%
% [metric_lh,metric_rh] = LOAD_MARKER(name) loads data on the cortical
% surface. Set to 'thickness' for cortical thickness, 'curvature' for
% curvature, or 't1wt2w' for t1w/t2w intensity. Left hemispheric data is
% stored i... |
84d4cf9f863fac29f8f1dd5ba4600958cdf340bdc0b292a43b5abd8eb8812a23 | MATLAB | 826 | 30 | function [status]=emartv1(TOFfn, m1, s1, m2, s2, m0, s0)
% Program for TOF-MRA segmentation to obtain arterial mask.
% USAGE:
% [status]=emartv1(TOFfn, m1, s1, m2, s2, m0, s0);
% Empirical values for inputs:
% m1=6; s1=4; m2=100; s2=50; m0=300; s0=100;
%
% Algorithm adapted from Wilson & Noble, IEEE TMI 1999 18... |
119e8760f759ed7ee8587fa12cf9403d29bdd48df2a71a7244ecb6993362bfbe | MATLAB | 828 | 33 | function spt_log_log_plot(data)
for i = 1:length(data)
temp = data{i}.msd;
for k=1:length(temp)
temp_temp_x = real(log(temp{k}(:,1)));
temp_temp_y = real(log(temp{k}(:,2)));
I = temp_temp_x==Inf;
temp_temp_x(I) = [];
temp_temp_y(I) = [];
... |
3b6ed24b2d579f922166c78d4ea714720e2eb75e86923b834709fdd658fe8b70 | MATLAB | 828 | 21 | %% file
prot=xlsread('L:\Tony\121005_CSR_SILAC_Velos_pro\combo.xlsx');
mrna=prot(:,9:14);
%% extract plot and correlate
mm=2
pm=5
sum(mrna(:,mm)>0&mrna(:,pm)>0|mrna(:,mm)<0&mrna(:,pm)<0)
corr(mrna((mrna(:,mm)>0&mrna(:,pm)>0|mrna(:,mm)<0&mrna(:,pm)<0),mm),mrna((mrna(:,mm)>0&mrna(:,pm)>0|mrna(:,mm)<0&mrna(:,pm... |
bb133143d55676692677d063e24b26ef66fd1f146f0f820c1a650507f5d86ce0 | MATLAB | 828 | 32 | function s=plus(t1,t2)
if (~isa(t1,'term') && numel(t1)>1) || (~isa(t2,'term') && numel(t2)>1)
warning('If you don''t convert vectors to terms you can get unexpected results :-(')
end
t1=term(t1,inputname(1));
t2=term(t2,inputname(2));
if isempty(t1)
s=t2;
return
end
if isempty(t2)
s=t1;
... |
ce9bcb18f0d8781757520b676c6913c744d140ab22377c97f4c611f673ec31d5 | MATLAB | 829 | 16 | classdef FCWildBootstrap < nla.edge.permutationMethods.Base
methods
function permuted_input_struct = permute(obj, orig_input_struct)
permuted_input_struct = orig_input_struct;
permuted_input_struct.func_conn = orig_input_struct.func_conn.copy();
fcData = permuted_input_st... |
d005d1f2f2d53ce00282d65176e92d7d61c678285e201e0d91853ddc9a4b8ea4 | MATLAB | 836 | 33 | function f = var2fac( x, str );
%Converts a numeric variable or term of this to a cell array of strings.
%
% Usage: f = var2fac( x [, str] );
%
% x = n x 1 numeric vector or term of this.
% str = either a single string, or a 1 x k cell array of strings of names
% for the k unique values of x in ascend... |
223952a31dcd814cd7ee696b7f6cdb31dc2ffe2f660c090ed895431070d7c497 | MATLAB | 837 | 37 | function coordinate = mni2cor(mni, T)
% function coordinate = mni2cor(mni, T)
% convert mni coordinate to matrix coordinate
%
% mni: a Nx3 matrix of mni coordinate
% T: (optional) transform matrix
% coordinate is the returned coordinate in matrix
%
% caution: if T is not specified, we use:
% T = ...
% [-4... |
34bd4d6b7382930f3d125defaf027a9909842818e1d0f6ae010158544bb5845a | MATLAB | 837 | 31 | function data = shape_classification_set_class_color(data)
input_values = inputdlg({'Class Number:'},'',1,{'1'});
if isempty(input_values)~=1
class_number = str2double(input_values{1});
for i = 1:length(data)
data{i}.classes = open_classes(data{i}.classes,class_number);
end
end
end
fu... |
655ff55fcf9da2d254a34a6d6da9cc8247c99a99d547335669041a0e5a4e18a5 | MATLAB | 837 | 36 | %% read data
d=load('C:\Users\animeshs\SkyDrive\chum\Sample.mat')
[r c]=size(d.d)
plot(d.d(r,:))
%% check
plot(d.d(1:50,:))
autocorr(d.d(r,:)')
%% symbolic test
% source http://blogs.mathworks.com/loren/2012/07/27/using-symbolic-equations-and-symbolic-functions-in-matlab/?s_eid=PSM_1986
besselODE = 't^2*D2y+t*Dy+(t... |
d6cc2276c75f83402702b18038ab8e9a3ad94378efebb2bc5e0377c3bdcd47af | MATLAB | 840 | 20 | function [mask_lh, mask_rh] = load_mask(name)
% LOAD_MASK loads cortical masks.
%
% [mask_lh,mask_rh] = LOAD_MASK(name) loads masks on the conte69-32k surfaces of
% the left (mask_lh) and right (mask_rh) hemispheres. Name can be set to
% 'midline' for a midline mask and 'temporal' for a temporal mask.
%
% For... |
eee6c715f70be79d48eee0cda14f456015997662714353daaeb55c39eadb8ce3 | MATLAB | 841 | 27 | function [is,os,str] = strengths_dir(CIJ)
%STRENGTHS_DIR In-strength and out-strength
%
% [is,os,str] = strengths_dir(CIJ);
%
% Node strength is the sum of weights of links connected to the node. The
% instrength is the sum of inward link weights and the outstrength is the
% sum of outward link weights.
%
... |
ab7f302e1600739c178a3d215c77031229d2ff44f440a79d718088747dc4709e | MATLAB | 844 | 25 | function plotFSsurf(faces,vertices,data,custommap,mincol,maxcol,viewangle)
%Plot data on surface rendering.
% FORMAT plotFSsurf(faces,vertices,data,custommap,mincol,maxcol,viewangle)
% faces - faces returned from freesurfer_read_surf
% vertices - vertice corodinates returned from freesurfer_read_surf
% data ... |
332780e44a4fa894912a1f63dcc49226f154872be1b00ab7a3c3377f03255731 | MATLAB | 847 | 28 | function fig = makefigure(width,height)
%MAKEFIGURE Make a publication-ready figure
% Width (in cm) can be 3.0, 9.0, 14.0, or 19.0 aka minimum size, single column, 1.5-column, or double column
% Wiley: 8 cm (small) or 18 cm (large)
% Height can be 24.0 cm max
% Note that wide PowerPoint slides are 33.87 wide by 19.05 h... |
8bd7ad0a9b15c74a47a436d9a835e15c15364acd11c72e0884aae0085d182ddb | MATLAB | 851 | 29 | function tc_make_reg_setups()
%% tc_make_reg_setups()
%
% makes setup for loop over multiple conditions
% current working directory needs to be /path/to/scripts
mainpath = pwd;
addpath([mainpath filesep 'fmriRegAnalysis'])
best_percs = {'5'};%, '10', '15'};
data_types = {...
%{'L', 'R', 'preference'};...
{'L-... |
b9307de3f2f723caeb4dd3ec3012c20128cf9c3f7e83447bea2855e849ff2231 | MATLAB | 853 | 32 | classdef ScriptTest < matlab.unittest.TestCase
properties
tmp_dir
end
methods(TestMethodSetup)
function create_tmp_dir(testCase)
tmpd = tempname;
mkdir(tmpd);
testCase.tmp_dir = tmpd;
end
end
methods(TestMethodTeardown)
fun... |
3dc0a2011b4b5e83963d91f021b33f3b189b07ee77f3d86e4a4c0ebeeb0ce06b | MATLAB | 854 | 27 | function [classes,classes_new] = check_classes_in_bubble(classes,classes_grouped)
bubble_center = mean(classes_grouped{1,2},1);
bubble_max = max(classes_grouped{1,2})-bubble_center;
bubble_min = min(classes_grouped{1,2})-bubble_center;
bubble_max = bubble_max(:,[1,7:8]);
bubble_min = bubble_min(:,[1,7:8]);
to_c... |
7ab0320944d14efdcee65a523d109ef158005383be12f90adef1ee3ff92724d8 | MATLAB | 854 | 44 | function m = fl_cell_mean(Cell,w)
% Computes the mean of a cell
%
% The cell must be 1-dimensional
% (The function does not make an internal copy of the cell variable, which
% is critical for large data sets)
% This function is part of the permutationlab software:
% Author: Dimitrios Pantazis
% The code is c... |
598eba57d6d8d0c5315b805696157eb748ba7d51288beb35c1c9b449ed715400 | MATLAB | 857 | 29 | für Native:
subj = 'sub-20Slicer';
baseDir = '/mnt/data1/lmu_or_reconstructions/20/derivatives/leaddbs/';
recoFile = fullfile(baseDir, subj, 'reconstruction', [subj '_desc-reconstruction.mat']);
load(recoFile);
coords_native = reco.native.coords_mm;
for i = 1:length(coords_native)
fprintf('Elektrode%d (Native):\n', i... |
8e4b297520ef3e59ef646f7c169d6847000355cf3d6373d434c245e21932e391 | MATLAB | 860 | 35 | function [ Y, Ym ] = SurfStatStand( Y, mask, subtractordivide);
%Standardizes by subtracting the global mean, or dividing by it.
%
% Usage: [ Y, Ym ] = SurfStatStand( Y [,mask [,subtractordivide] ] );
%
% Y = n x v matrix of data, v=#vertices.
% mask = 1 x v, 1=inside, 0=outside, v=#v... |
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