sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 17k | content stringlengths 1 200k |
|---|---|---|---|---|
e7748f10ec8be3d3fae6af1db8c1850971cbd66fd651f60805cace6235ac12c8 | MATLAB | 861 | 36 | % function adapted from the LiNGAM package
% complete software may be downloaded from http://www.cs.helsinki.fi/group/neuroinf/lingam/
function [Wopt,rowp] = permnozeribrutal ( W )
%--------------------------------------------------------------------------
% Try all row permutations, find best solution
%------... |
b39ae471d007ee54159392f8721c29ff8c9ebd53cdf329ae673fdd4712c24c81 | MATLAB | 866 | 44 | %% CHOLESKY DECOMPOSITION WITH DIAGONAL MATRIX
% given A positive definite symmetric matrix, returns a lower triangular
% matrix L and a diagonal matrix D such that A=LDL'
function [L,D]=choldiag(A);
error(nargchk(1,1,nargin));%min e max di input arguments
n=size(A,1);
if sum(sum(A'~=A)), error('A non è si... |
7c00158031d588ae6208efff1e9260edf6ac41104e4f99038b60493bce1c039e | MATLAB | 868 | 27 | function plot_classes_to_group(f,classes)
clf(f);
if length(classes{1,1})<=10
for i = 1:length(classes{1,1})
subplot(1,10,i)
scatter(classes{1,1}{i}(:,1),classes{1,1}{i}(:,2),1,'b','filled')
if i ==1
title(['Number of clusters in the class :',num2str(length(classes... |
cecaca49d32c9d823a91aee238b6a14c1b82af8d0c55e9b78c0d5471ac52a86c | MATLAB | 869 | 36 | function [sigma_b] = grad_descent_sigmab(S_R, G, T, sigma_b, sigma_m)
diff_obj = inf;
obj = 1e10;
old_obj = 0;
step_init=1.0;
tau=0.8;
iter_count=1;
max_count = 1000;
while abs(diff_obj/obj)>=1e-10
if iter_count > max_count
break;
end
R = sigma_m^2*eye(size(G,1)) + sigma_b^2*(G*G');
grad_R = T*... |
da5c9088bb60e620cbf0f4da88640aea52559275c239942df7de848fada19937 | MATLAB | 871 | 41 | function [Fluidity, Dimension] = MA_EEG_Man_Dim_Flui(TS)
% This function compute Manifold Fluidity and local dimension of time serie
% INPUT: TS, your time serie in observation x variables format
quanti=0.98;
STEP = 1;
L = length(TS);
%u = 0;
Dimension = zeros(L,1);
Fluidity = zeros(L,1);
for j = 1:STEP:L
%u=... |
3410b4d63ccad6447d7436d07219b3f7c2407c089ab65d828dd5cb937f91c99f | MATLAB | 876 | 17 | function table_data_plot(data,row_names,column_names,title)
figure('name',title,'NumberTitle','off','units','normalized','position',[0 0.1 1 0.4],'ToolBar','none','MenuBar', 'none');
column_width = {200};
uitable('Data',data,'units','normalized','position',[0 0 1 1],'FontSize',12,'RowName',row_names,'ColumnName',col... |
132bfdcbf1202d7fd9e99f778793d9776ee2e61451611b9edde8396c73cd297d | MATLAB | 878 | 35 | function sel_trls=artRej(fl, bpfilt,chnls)
% sj='P3_grating';
% stem='/project/3016045.05/Experiment3.2_ERC/Data/EEG/';
% bpfilt=[0 0];
data1=do_read_trials(1, bpfilt,fl{1},chnls);
data2=do_read_trials(2, bpfilt,fl{2},chnls);
data3=do_read_trials(3, bpfilt,fl{3},chnls);
data4=do_read_trials(4, bpfilt,fl{4},chnls);
... |
f8ca0950d0eaf165b1a7337160fdcbde6606ec2d0fe32dab184f4872f7b49f6d | MATLAB | 879 | 36 | function [sigma_m] = grad_descent_sigmam(S_R, G, T, sigma_b, sigma_m)
diff_obj = inf;
obj = 1e10;
old_obj = 0;
step_init=1.0;
tau=0.8;
iter_count=1;
max_count = 1000;
while abs(diff_obj/obj)>=1e-10
if iter_count > max_count
break;
end
R = sigma_m^2*eye(size(G,1)) + sigma_b^2*(G*G');
grad_R = T*... |
764e46e249fd985a26054b4abfd21fd6c77a794c7194256718978b3b7666407b | MATLAB | 883 | 38 | function s = classToStructRecursive(c)
%CLASSTOSTRUCTRECURSIVE Convert classes to structs recursively
if isa(c, 'cell')
s = cell(size(c));
for i = 1:numel(c)
s{i} = nla.helpers.classToStructRecursive(c{i});
end
return
end
if ~isobject(c) || isa(c, 's... |
ab097528481c4d652927ad70cfaf3597268ae072a9e1d6bec5545422671e1f36 | MATLAB | 883 | 41 | function writetoPAJ(CIJ, fname, arcs)
%WRITETOPAJ Write to Pajek
%
% writetoPAJ(CIJ, fname, arcs);
%
% This function writes a Pajek .net file from a MATLAB matrix
%
% Inputs: CIJ, adjacency matrix
% fname, filename minus .net extension
% arcs, 1 f... |
ed435b733b1fe0156f5b759303ece5e3bf4567a35f459519413d0e6ff3d6e886 | MATLAB | 886 | 27 | %path('/home/fimm/ii/ash022/tom/spm2/',path);
path('/home/fimm/ii/ash022/tom/spm2/',path);
beh=load('/home/fimm/ii/ash022/tom/beh/MMBT.mat');
behmat = zeros(1,2612);
behmat(beh.onset)=1;
cd /home/fimm/ii/ash022/tom/Session_1;
files = dir('*.img');
%for i=1:length(files)
for i=1:2
v = spm_vol(files(i).name);
[vo... |
37c7aebc135953ca64a59a9e12f78ee5c83738c5c9a25a52b28c9b9777871c8a | MATLAB | 890 | 21 | %% This function transform a 2D mosaic matrix into a 3D one with im_size,im_size,slices
function out_sl = mosaic2slices(mat,im_size, slices)
if ndims(mat) == 2
num = (size(mat,2)/im_size);
aux = mat(:,:);
out = permute(reshape(aux',[size(mat,2),size(mat,2)/num,num]),[2,1,3]); %change the n... |
d8e1bebfef44fd0ea03513ec55f12dabc1697b8f790f56e77af39806354940cd | MATLAB | 890 | 28 | function moveFigToParentUILocation(fig_h, parent_h)
%Intended to fix issue in Windows where plots generated from NLA_GUI
%and NLA_Result get drawn way off top of screen.
%Inputs are:
% fig_h - figure handle
% parent_h - UIFigure handle to move to (matlab.ui.Figure)
figPos = ... |
d8f173b67f2c2b0a140835872319160c6130ae924e460342a5ea466ef5c93951 | MATLAB | 892 | 31 | function [id,od,deg] = degrees_dir(CIJ)
%DEGREES_DIR Indegree and outdegree
%
% [id,od,deg] = degrees_dir(CIJ);
%
% Node degree is the number of links connected to the node. The indegree
% is the number of inward links and the outdegree is the number of
% outward links.
%
% Input: CIJ, direct... |
b0e00b098480eb252cfe88753fca8044980f422820a1791baf6affbcc24037aa | MATLAB | 893 | 30 | function [] = image_mat(subj,objtype,objname)
% [] = IMAGE_MAT(SUBJ,OBJTYPE,OBJNAME)
%
% Visualize the contents of an object or group with
% IMAGESC. Automatically shifts to black&white colormap for binary
% matrices.
if exist_object(subj,objtype,objname)
mat = get_mat(subj,objtype,objname);
elseif exist_group(subj... |
94dc797d92d29a5c5f6aff0ddfb55282bd72a71ffe4002b636821e2629cf081d | MATLAB | 894 | 30 | function O = averaging_TRF(S)
O = [];
S = [];
%OLD
PP = zeros(306,74,700,70);
for ii = 1:71
if ii ~= 39
load(['/scratch5/MINDLAB2017_MEG-LearningBach/Leonardo/LearningBach/Time_frequency_MEGsensors/Subject_' num2str(ii) '_Old_Correct.mat']);
PP(:,:,:,ii) = P;
end
disp(ii)
end
P = mean(PP,4... |
22994c56f5f7b4914fe4a7c0afe388e6102df9ea19ac37996b33bfd81063e2c8 | MATLAB | 897 | 21 | function data_simulated = loc_list_gaussian_point_pattern_simulation()
input_values = inputdlg({'Sigma Range:','Number of Gaussian Clusters:','Number of Points in Clusters:','Image Size:'},'',1,{'0 5','10','200','50'});
if isempty(input_values)==1
data_simulated = [];
else
sigma_input = str2num(input_value... |
bc45b8dc7638b87654aadd2ce5a354699589840817cbb771c5e0d1ef7146f6fe | MATLAB | 897 | 23 | function plot_model(ax, x, mu, se, fillCol, lwModel, hasBL)
if hasBL
[hl, hp] = boundedline(ax, x, mu, se, 'alpha', 'cmap', [0 0 0]);
try, set(hp, 'FaceColor', fillCol, 'FaceAlpha', 0.35, 'EdgeColor', 'none'); end
if isgraphics(hl)
set(hl, 'Color', 'k', 'LineWidth',... |
36b72b6891060f9938bbceef972ce56dc0a92aa2bff74741d6908a58eaebeb11 | MATLAB | 899 | 38 | function [id, r_, G_] = set_all_part_traj(pnts, G, dist_thr, num_sources, N)
%source_ids = 1:length(pnts);
M=length(pnts);
dist_sources=zeros(1,N);
r_=zeros(3*num_sources,N);
G_=zeros(size(G,1),num_sources,N);
min_dist = 0;
while min_dist < dist_thr
% unique_flag=0;
% while unique_flag==0
for nn=1:N
... |
d26e5ed1f2840dfb0ad148a612c388441064ccb65882076222c0810c622b08c2 | MATLAB | 903 | 38 | SimFile=spm_load('spike_detector-21-0.gdf')
Neurons=zeros(20,2000);
%Neurons_conv = Neurons;
for i=1:length(SimFile)
Neurons(round(SimFile(i,1)),round(SimFile(i,2)/0.01))=1;
end
hrf01=spm_hrf(0.1);
for i=1:size(Neurons,1)
Neurons_conv(i,:)=conv(Neurons(i,:),hrf01);
end
nrows = size(Neurons_conv,2);
... |
2c93b4cdb730f27a14073214457c9fe8faaf5fd8e5bb34a6294a59972a15cd20 | MATLAB | 906 | 27 | function [ax,srf,cam] = make_surface_plot(~,data,surf,pos,view,clim)
% Constructs a single axis with a hemisphere in it. Called exclusively by
% plotter.
%
% For more information, please consult our <a
% href="https://brainspace.readthedocs.io/en/latest/pages/matlab_doc/visualization/plot_hemispheres.html">ReadThe... |
789f808da55d68a1c14eeaafaf38e44dd0422c679a64875e3e7e03380b079eb4 | MATLAB | 908 | 29 | load('svm_mat555');
[s v t]=size(svm_mat);
sn=Design_Para(:,6)';
mn=Design_Para(:,4)';
corrcoef(mn,sn)
for i = 1:size(svm_mat,1)
for j = 1:size(svm_mat,3)
%svm_mat_norm(i,:,j)=mat2gray(svm_mat(i,:,j));
svm_mat_std(i,:,j)=(svm_mat(i,:,j)-mean(svm_mat(i,:,j)))/std(svm_mat(i,:,j));
end
end
voxmean_std=resh... |
bfb9366f8f1ea79738dcb9bbbda150d354b44ee2cc8dbf7340303a1ca1d46a38 | MATLAB | 908 | 27 | function loc_list_clusters_area_histogram(data)
input_values = inputdlg({'Percentile:'},'',1,{'0 95'});
if isempty(input_values)==1
return
else
percentile =str2num(input_values{1});
counter = 0;
for i = 1:length(data)
data_to = unique(data{i}.area);
if length(data_to)>1
... |
8934faf2c1c688ee64abfb7f15ef3d30dfc386f8f43e4cdf6ceed7100a2633cd | MATLAB | 910 | 28 | function [LocsTable,AllClusters] = calcLocs(data)
LocsTable = cell(1,length(data));
AllClusters = cell(1,length(data));
for i = 1:length(data)
if ~isempty(data{i})
Clusters = extract_clusters(data{i});
LocsTable{i} = NaN(length(Clusters),8);
for j = 1:length(Clusters)
... |
9bb44bdd60b636686649d0faa6518bc90ea9872477f97a9406156aa70c490219 | MATLAB | 910 | 29 | function is_connected = graph_is_connected(G)
% GRAPH_IS_CONNECTED Assesses whether a graph is fully connected.
%
% is_connected = GRAPH_IS_CONNECTED(graph) tests whether the graph is
% fully connected. Graph must be a graph, a 2D logical matrix, or a data type that
% may be converted to a 2D logical matrix; i... |
52dfa993c1d001698d543be63db5b443707ca6be7a0815ea08b5bea61f7104a6 | MATLAB | 916 | 24 | function y = cvx_default_dimension( sx )
%CVX_DEFAULT_DIMENSION Default dimension for SUM, MAX, etc.
% DIM = CVX_DEFAULT_DIMENSION( SX ), where SX is a size vector, returns the
% first index DIM such that SX(DIM)>1, if one exists; otherwise, DIM=1. This
% matches the behavior by functions like SUM, MAX, ANY, ... |
5537e58e70fcb28a36cdd1ee2dfd5ed9d1f0404defa9e09029dba54b05290a3f | MATLAB | 916 | 30 | clear all;
close all;
dataFolder = 'C:\Users\frada\Desktop\WORK in PROGRESS\LAB\TouchScreen_project\Data\Datasets\';
filenameSpikes = [dataFolder 'ID2055_chs0_128_ave_bpass300_6.0k_Int16_r_4_unsorted.mat'];
filenameEvents = [dataFolder 'ID2055_data.csv'];
filenameCSMS = [dataFolder 'ID2055_CSMS_chs0_128_ave_bpas... |
6d6d9df62f990d23a84c3523037a3ced0e93be71ab029cbca72f691d37aad227 | MATLAB | 917 | 27 | function [coreness,kn] = kcoreness_centrality_bd(CIJ)
%KCORENESS_CENTRALITY_BD K-coreness centrality
%
% [coreness,kn] = kcoreness_centrality_bd(CIJ)
%
% The k-core is the largest subgraph comprising nodes of degree at least
% k. The coreness of a node is k if the node belongs to the k-core but
% ... |
cfa4159c787ef6cc7c4e0db1e227fdd6f5a5107747cd258e85731d178cc066c3 | MATLAB | 920 | 21 | function [aN] = compute_aN_fast(r_pf_t, r_pf, q_kf, P_kf, V_r, ...
omega_t, lambda_t, num_sources, w, N, CONST, log_det)
lam = zeros(num_sources,num_sources,N);
eta = zeros(N,1);
logw_rb = zeros(N,1);
for i=1:1:N
gamma = chol(P_kf(1:num_sources,1:num_sources,i));
lam(:,:,i) = gam... |
653104a5d596967f6e7b967e638ea2d2bc52de373cc6e3e3323506ba93aa6e6c | MATLAB | 922 | 29 | function [CIJ] = maketoeplitzCIJ(N,K,s)
%MAKETOEPLITZCIJ A synthetic directed network with Gaussian drop-off of
% connectivity with distance
%
% CIJ = maketoeprandCIJ(N,K,s)
%
% This function generates a directed network with a Gaussian drop-off in
% edge density with increasing distance fro... |
321e85096eb1473a9ace9247d3d3d21e77a1d67f21ddaf01e54f54f883045846 | MATLAB | 924 | 32 | function output = tc_make_sliding_windows(start, stop, steps, sizes)
%% output = tc_make_sliding_windows(start, stop, steps, sizes)
%
% Computes different variations of sliding windows for respective analyses.
%
% Input:
% start: start time point
% stop: end time point
% steps: 1 x n containing in which steps t... |
7f56e5b1f493d1026db4ef005029c2431c1e54327c981879e159f158c487596b | MATLAB | 929 | 24 | function O = time_frequency_MEGsensors_dim(S)
O = [];
%starting up some of the functions that I wrote for the following analysis
addpath('/projects/MINDLAB2017_MEG-LearningBach/scripts/MITDecodingToServer/BrainstormDemo_CodesTimeFrequencyDecomposition/functions') %to Dimitrios Morlet transform function
%preparing da... |
9db716ab5149bd1c2c2ea3dbaed0d86525a37665e84cf7487068d7e66a7aba71 | MATLAB | 929 | 24 | function spt_tracks_convert_tracks_to_image(data)
input_values = inputdlg({'pixel size:','image width:','image height:'},'',1,{'0.117','419','680'});
if isempty(input_values)==1
return
else
pixel_size = str2double(input_values{1});
width = str2double(input_values{2});
heigts = str2double(input_va... |
0c1a1655e0345726ce3ee3348b50a70eb255ca182c5fbf9fbed6f88dd0a4741e | MATLAB | 935 | 32 | function image_crop(data)
rec_coordinates=getrect;
if isempty(rec_coordinates)
return
else
x1 = round(rec_coordinates(1));
x2 = round(x1+rec_coordinates(3));
y1 = round(rec_coordinates(2));
y2 = round(y1+rec_coordinates(4));
for k=1:length(data)
x_data = 1:size(data{k}.... |
679116afc8bc40fcc2dfda042f2721c4dd5d465d5842a2d0cfacbf52f8d3bfe4 | MATLAB | 937 | 25 | function data_load = spt_simulate_random_brownian_motion()
input_values = inputdlg({'number of particles:','time step:','number of time steps:','diffusion coefficient: (um^2/s)','size:'},'',1,{'10','0.05','100','0.001','2'});
if isempty(input_values)==1
data_load = [];
else
num_of_particles = str2double(in... |
059225f36a146f6ec44f61ba73289a144c3fc04498f918ecd2b33f4fb22f2fe8 | MATLAB | 940 | 29 | function T=transitivity_wu(W)
%TRANSITIVITY_WU Transitivity
%
% T = transitivity_wu(W);
%
% Transitivity is the ratio of 'triangles to triplets' in the network.
% (A classical version of the clustering coefficient).
%
% Input: W weighted undirected connection matrix
%
% Output: T ... |
42ea85dc7fd380d86ff02ae13e3c3cc515b3d1df4e9b0e46f9246ff961adec70 | MATLAB | 942 | 35 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%% cor2mni
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function mni = cor2mni(cor, T)
% function mni = cor2mni(cor, T)
% convert matrix coordinate to mni coordinate
%
% cor: an Nx3... |
d11d46f54ac1e40db71f1e7286eba46eacb51a1d0498cdd8ed6e7d23a0e34600 | MATLAB | 942 | 29 | function SC = combine_surfaces(S1,S2,format)
% COMBINE_SURFACES combines two surfaces into a single structure.
%
% SC = COMBINE_SURFACES(S1,S2) takes two surfaces in a format readable
% by convert_surface and combines them into a single one.
%
% SC = COMBINE_SURFACES(S1,S2,format) outputs surface in the d... |
544d481738333c283d7126eb35c10039391e2db58e779dbe33304849b95424e5 | MATLAB | 945 | 30 | function colormaps(obj,maps)
% Sets colormaps for plot_hemispheres. Maps must either be a n-by-3 color
% map, or a cell array with the same number of elements as columns in
% obj.data, each containing n-by-3 colormaps.
%
% For more information, please consult our <a
% href="https://brainspace.readthedocs.io/en/latest/p... |
aa45a5edf4a12af7dd485110717d5a3ad8efb41b13b703dc20b95b4d5483fcbc | MATLAB | 945 | 34 | cd('/home/adrian/Documents/GitHub/RGS14/spiking_activity')
% RGS14
%load('Name_Confirming_Data.mat');
load('New_Wake_Data_Extra_Units_clean.mat');
x=New_Wake_Data_Extra_Units;
%%
v=[];
v_name={};
for i=1:length(x) % 107 pyr units
v(i,:)=[x(i).Presleep x(i).Trial_1 x(i).Post_Trial_1 x(i).Trial_2 x(i).Post_Tr... |
56003bba4a477b2a115c0538d6e84fd03ff2a29c5f00ba6a79abe5768f4d2992 | MATLAB | 946 | 37 | function filenames = SurfStatListDir( d, exclude );
%Lists all the file names in a directory.
%
% Usage: filenames = SurfStatListDir( dir [, exclude] );
%
% d = directory, including wildcards such as '*'.
% exclude = matrix with rows as strings; any file name containing
% any of these str... |
c24053c761c842ff5c4e4626b11f871af50c2888b987c2aa75761d7d01c0be9f | MATLAB | 946 | 48 | function [t] = pl_cell_tstat2_unequalvar(Cell1,Cell2)
% Computes a 2-sample t-statistic (does not assume equal variance).
%
% The variables are expressed in cells for speed
% This function is part of the permutationlab software:
% Author: Dimitrios Pantazis
% The code is currently under development, please do... |
0a02cb0644adcc1746f46f3eb90433cf5872aa561310bd5128230da5a59fb1cf | MATLAB | 947 | 26 | function matchingFiles = getFileContainingString(folderPath, searchStr, extension)
% Check if an extension is provided
if nargin < 3
extension = ''; % Default to empty string if not provided
end
% List all files in the folder
files = dir(folderPath);
% Initialize a cell array to store ... |
d37b58f3dcde73d3708e5c6f555bccd60d9410e67e6d6b00f0d3e66753c731b7 | MATLAB | 947 | 30 | function [Spos,Sneg,vpos,vneg] = strengths_und_sign(W)
%STRENGTHS_UND_SIGN Strength and weight
%
% [Spos Sneg] = strengths_und_sign(W);
% [Spos Sneg vpos vneg] = strengths_und_sign(W);
%
% Node strength is the sum of weights of links connected to the node.
%
% Inputs: W, undirect... |
a92f5ddb8176b056f89e990f1e4c88ca6825d6566ce46c4d53a570f02f7b60ee | MATLAB | 950 | 27 | function loc_list_clusters_no_of_locs_histogram(data)
input_values = inputdlg({'Ppercentile:'},'',1,{'0 95'});
if isempty(input_values)==1
return
else
percentile =str2num(input_values{1});
counter = 0;
for i = 1:length(data)
data_to = unique(data{i}.area);
if length(data_to)>1
... |
59308a10b95a9e4a0387e842df9e18bdadcd0dffb5a164b812eef51b56e8323b | MATLAB | 953 | 40 | function y = diff(x)
% DIFF Difference and approximate derivative.
% DIFF(X), for a vector X, is [X(2)-X(1) X(3)-X(2) ... X(n)-X(n-1)].
% DIFF(X), for a matrix X, is the matrix of row differences,
% [X(2:n,:) - X(1:n-1,:)].
% DIFF(X), for an N-D array X, is the difference along the first
% non-si... |
5edf9b4454511775b1ab61c62dc52f89456cd2dc5b7bf8abeaa5e47967964bec | MATLAB | 954 | 15 | function image_plot_right_click(data,name)
ax = gca; cla(ax);
mouse_location = get(gca,'CurrentPoint');
imagesc(data)
colormap(gray)
title({'',regexprep(name,'_',' ')},'Interpreter','latex','fontsize',14)
line([mouse_location(1,1) mouse_location(1,1)],[1 size(image,1)],'Color','r','LineStyle','--')
line([1 size(... |
d5d4ac47d50ef455434a2bbcb3907b72d9ae744351e098140557a3600f8f4ba7 | MATLAB | 954 | 46 | function mipp_plotParVsTime(T, xnam, ynam, fnam, flev)
% function mipp_plotParVsTime(T, xnam, ynam, fnam, flev)
uID = unique(T.ID);
for i = 1:numel(uID)
ind = T.ID == uID(i);
% f = T.(fnam)(ind);
x = T.(xnam)(ind);
tmp = T.(ynam)(ind);
clear y
for j = 1:numel(tmp)
tmp2 = tmp{j};... |
b537e552ddd84e23f052d18c42db1078223c78f09e857bf70025ff44907048f7 | MATLAB | 955 | 23 | function data_down_sample = loc_list_down_sample_data(data)
answer = inputdlg({'Number of Localizations:'},'Input',[1 50],{'50000'});
if isempty(answer)~=1
scatter_num = str2double(answer{1});
data_down_sample = cell(1,length(data));
for i = 1:length(data)
if length(data{i}.x_data)>scatter_num... |
f2de91d15095e0bdbaa697340ca3366d79e825fafde5e30af4c6b66470671ad3 | MATLAB | 955 | 39 | function M0 = matching_ind_und(CIJ)
%MATCHING_IND_UND matching index
%
% M0 = MATCHING_IND_UND(CIJ) computes matching index for undirected
% graph specified by adjacency matrix CIJ. Matching index is a measure of
% similarity between two nodes' connectivity profiles (excluding their
% mutual connect... |
6667685d96bfd003eeb7dcd215442df87eae3f5107a35f382b06c613b3a8b95c | MATLAB | 956 | 31 | function [subject_name, sSubject, iSubject] = bst_create_test_subject(template_name, use_default_anatomy)
if nargin < 1
template_name = 'Colin27_4NIRS_lowres';
end
if nargin < 2
use_default_anatomy = 0;
end
bst_create_test_protocol(use_default_anatomy);
% Add test subject
subject_name = 'test_subject';
[sSu... |
7b0956154cfe5e9353fa3963b194dd15b446be76766f39c5877a7fe6df3448b0 | MATLAB | 959 | 27 | clear;
addpath('/home/common/matlab/fieldtrip')
sj='S52';
%task=['B' num2str(blknr)];
stem='/project/3018037.01/Experiment3.2_ERC/AnalysisFolder/';
%S8/rawData/eegfiles'
%/project/3018037.01/Experiment3.2_ERC/AnalysisFolder/subjectData/S30/6_EEG/ica
bpfilt=[0 0];
chnls ={'all','-ECG'};%,'-F3',... |
0818ba67c1967fd72dd15310c096050e7b273463674dd008b9abb276b3e5f587 | MATLAB | 960 | 63 | %% motivated by http://grasshoppernetwork.com/showthread.php?tid=629
%% create signal
a=5;
c=1;
m=2;
f=50;
n=10;%no of sample per second?
fs=100*f;% @least twice by nequist
ts=1/fs;
t=0:ts:n/f;
x = c+a*sin(2*pi*f*t)+a*sin(2*pi*m*f*t)+a*sin(2*pi*2*m*f*t);
plot(x);
fx=fft(x);
plot(real(fx))
[idx val]=max(real(fx))
%% o... |
3b6a66466d36dc4f25cf749012036c09467e05aa9016a553c5f056bfff0d6270 | MATLAB | 961 | 37 | %READ_WRITE_ENTIRE_TEXTFILE Read or write a whole text file to/from memory
%
% Read or write an entire text file to/from memory, without leaving the
% file open if an error occurs.
%
% Reading:
% fstrm = read_write_entire_textfile(fname)
% Writing:
% read_write_entire_textfile(fname, fstrm)
%
%IN:
% fn... |
68232a43bcd28b4e83b78097ba2ba812e5cd7bccbc2a2dcd6ae6051e0ce190d6 | MATLAB | 962 | 41 | function [freq,power] = ft_power(mat,TR)
Fs = 1/TR; % Sampling frequency
if ndims(mat) == 4
L = size(mat,4); % Length of signal
elseif ndims(mat) == 2
L = length(mat);
end
freq = Fs*(0:(L/2))/L;
if ndims(mat) == 4
power = zeros([size(m... |
e2b8790b806568ad462c16db19f1480dccaa3f879e5ed34776eb9ca6967dd896 | MATLAB | 962 | 55 | %% kernel projection demo
datac0=[rand(10,1);-rand(10,1)];
plot(datac0,0,'r.')
datac1=[randi(10,10,1)',-randi(10,10,1)']';
hold
plot(datac1,0,'b.')
hold off
train=[datac0;datac1]
figure
class=[zeros(20,1);zeros(20,1)+1];
train2d=[train,train.*train]
svmStruct = svmtrain(train2d,class,'showplot',true);
%% svm circl... |
5699d2f1749a4ef967986052392888d81ac9e6be56d0c702a244ea320ba4f934 | MATLAB | 968 | 35 | function create_AALnifti(aalvector,name,symm)
% script to create AAL nifti file for rendering
% aalvector is a 1x90 vector with a value for each AAL region
% name is the name of the output file
% symm is a flag that if >0 means that ordering is symmetrical
aalnii=load_nii('aal_2mm.nii.gz')
% create new image
newni... |
8cd21725c0c8da727097b5a07f08b022383ac04dd93926966027e679c9c4ec55 | MATLAB | 972 | 29 |
function [S] = suff_stats_gpu(q_ks, q_ks1, Y_, N, nq, ny, w_1, J, T)
gputimes = @(A, B) pagefun(@mtimes, A, B); % A*B on GPU
gputranspose = @(A) pagefun(@transpose, A); % A'
gputimes_e = @(A, B) pagefun(@times, A, B); % A*B on GPU
q_ks = permute(q_ks, [1 3 4 2]);
q_ks1 = permute(q_ks1, [1 3 4 2]);
Y... |
ad1a1562b46bece62f9027443c67325a3bb1fcf5164850294bdab96315b4df90 | MATLAB | 973 | 55 | function [comm_diff, perm_needed, V1, V2] = find_comm_diff(V1, V2)
comm_diff1 = sum(V1~=V2)/length(V1);
count = 0;
for i=1:max(V1)
if sum(V1==i)<2
V1(V1==i) = 0;
count = count + 1;
else
V1(V1==i) = i-count;
end
end
count = 0;
for i=1:max(V2)
if sum(V2==i)<2
... |
0cf41347fb1a433877ea9fe5c61c65f19f0f42daf25cb56ef42b8df0e535fb7b | MATLAB | 974 | 53 | %% load data
%load('svm_mat555');
%% extract zone
data_STS=svm_mat(:,ind_STS,:);
%% plot zone
temp=data_STS(7,round(33.0078),:);
temp=Design_Para(:,1);
plot(squeeze(temp));
axis equal;axis off;
plot(Design_Para(:,4))
hold
plot(Design_Para(:,6),'r')
hold off
%% Extract musicness
[s v t]=size(svm_mat);
temp=reshape(sv... |
6762ed65569ca504370349887268afc2f9f45c3be4dd8f816b9fcccac73df091 | MATLAB | 976 | 26 | function events_mat = nst_make_event_regressors(events, filter, time)
% NST_MAKE_EVENT_REGRESSORS build event design matrix from given events and filter
%
% EVENTS_MAT = NST_MAKE_EVENT_REGRESSORS(EVENTS, FILTER, TIME
%
% EVENTS (struct array):
% events as brainstorm structure (see DB_TEMPLATE('event')... |
967e6d65aafbea3f2ead8b63b8449b1d81501f20348e5b6e505f04d5a52f1cbf | MATLAB | 977 | 29 | function results = runTests()
import matlab.unittest.TestSuite matlab.unittest.TestRunner
import matlab.unittest.plugins.CodeCoveragePlugin
import matlab.unittest.plugins.codecoverage.CoverageReport
root_path = nla.findRootPath();
% get all unittests folders
filelist = dir(fullfile(root_path,... |
c7bc7de31bc08da747ba6bc4af4e86d4041452a029b8d620caf20fbbaeb2bc06 | MATLAB | 977 | 38 | % Save NIFTI header extension.
%
% Usage: save_nii_ext(ext, fid)
%
% ext - struct with NIFTI header extension fields.
%
% NIFTI data format can be found on: http://nifti.nimh.nih.gov
%
% - Jimmy Shen (jimmy@rotman-baycrest.on.ca)
%
function save_nii_ext(ext, fid)
if ~exist('ext','var') | ~exist('fid','var')
... |
4bc05413c23c27de7620545c4c24759bface705fe654e900bf9c4d311416ef8d | MATLAB | 978 | 24 | function plot_histogram(x_pdf,y_pdf,x_cdf,y_cdf,names,x_label,percentile)
figure()
set(gcf,'name','histogram','NumberTitle','off','color','w','units','normalized','position',[0.15 0.2 0.7 0.5],'menubar','none','toolbar','figure')
subplot(1,2,1)
hold on
for i = 1:length(x_pdf)
plot(x_pdf{i},y_pdf{i})
en... |
23f5852a9309eda9d7383705b3bac6cfced8a37980ae10d0c01e8604a16d5bbe | MATLAB | 983 | 47 | function [t] = pl_cell_tstat_2sample(Cell1,Cell2)
% Computes a 2-sample t-statistic assuming equal variance.
%
% The variables are expressed in cells for speed
% This function is part of the permutationlab software:
% Author: Dimitrios Pantazis
% The code is currently under development, please do not share
... |
8078ed1595da20d9f79840fa550eb72bfc7730e1d4838240fa6dce5372c47e1e | MATLAB | 994 | 23 | function [origin, rad_origin, radius] = findCircleFromTwoTangents(a, b, rad_a, rad_b)
%FINDCIRCLEWITHTWOTANGENTS Find the origin and radius of a circle,
% given two tangent points and slopes
% Points and slopes MUST be ordered clockwise from the perspective of
% the circle you are trying to locate (cann... |
3ca3c9612bc631228829131f5a3322eaf225640e11f21d204f8d4e6f02a86e66 | MATLAB | 996 | 41 | function map = spectral( m );
%Black-purple-blue-green-yellow-red-white color map.
%
% Usage: map = spectral( m );
%
% m = number of colours; default is the length of the current colormap.
%
% map = m x 3 matrix containing a "spectral" colormap.
%
% E.g. colormap(spectral) resets the colormap of the current... |
24df3683b62691e98a9d0ade6df4fb4c8ab6d55967d61e87d398081c4fcd1b42 | MATLAB | 1,002 | 20 | function shape_classification_iterative_linkage_coeff_var_clustering(data)
input_values = inputdlg({'Length and Width Coeff. of Variation Threshold Variation:'},'',1,{'0.05:0.01:0.17'});
if isempty(input_values)~=1
coeff_var = eval(input_values{1});
size_c_o_v = size(data.classes{1,3},2);
coefficient_o... |
8178e1ab6ae5cd0d426069d47abd8f694338cf9a3a4fb6b78a2277a30721509f | MATLAB | 1,002 | 34 | function formatNBP(h,plotColours, plotAlpha)
%FORMATNBP Formats a notBoxPlot
% Formats colours, alpha values, line widths, and point size of the notBoxPlot.
%
% h: handle to notBoxPlot
% plotColours (optional): desired colours (you need to provide at least as many as
% your conditions) as a numberOfColours X 3 ... |
8e039a5922979c130a4ed878f4415bb65499a0dc342b6bfbaa595a27671b3164 | MATLAB | 1,003 | 26 | function [omega_t, lambda_t] = compute_omega_lambda_fast(A, V_q, G_pf, Y, XI, num_sources, p, N, T)
nq = num_sources*p;
F_ = chol(V_q(1:num_sources, 1:num_sources));
% F_ = zeros(nq,nq);
% F_(1:num_sources, 1:num_sources) = F;
% F_(num_sources+1:num_sources*p, 1:num_sources)=0;
% F_(1:num_sources*p, num_sources+1:end)=... |
2117b6fe356b69818016d9da338ec45326cb6748857eee7b2537179ddf23d841 | MATLAB | 1,004 | 20 | function shape_classification_iterative_distance_coeff_var_clustering(data)
input_values = inputdlg({'Length and Width Coeff. of Variation Threshold Variation:'},'',1,{'0.05:0.01:0.17'});
if isempty(input_values)~=1
coeff_var = eval(input_values{1});
size_c_o_v = size(data.classes{1,3},2);
coefficient_... |
7dd5548b162fc267a081977d2b021b2d32618fb29c61c5407d3ab6ffd8d6efcf | MATLAB | 1,004 | 51 | %% load file
load('svm_mat_UMS_svm_20110520.mat')
whos
%% write csv
a=csvread('voxel_index.csv');
csvwrite(svm_mat,'dysl,csv');
%% extract voxel coordinates
v=size(ind,1);
P_in='svm_mat_UMS_svm_20110520.mat';
for i=1:v
i
[voxcoords] = svm2mni(P_in, i);
vxcrds(i,1)=voxcoords.XYZmm(1);
vxcrds(i,2)=voxcoor... |
3bccb1eb056f89b7b83d4c19f996333b5674d0e5ab6bc6b2c0e50682d6b6a6c3 | MATLAB | 1,006 | 23 | function [data_clustered,data_not_clustered] = voronoi_data_get_voronoi_cluster(data,type)
if type ==1
answer = inputdlg({'Area Threshold:','Minimum Number of Localizations per Cluster:'},'Input',[1 50],{'0.013','5'});
else
answer = inputdlg({'Area Threshold:','Minimum Number of Localizations per Cluster:'},... |
c5c4706b5bd06f8f537094d799de81a6347f07c7ac86ab8e371e51466c75aba8 | MATLAB | 1,009 | 43 | function t=emart(I,NI, m1, s1, m2, s2)
%dm1=1;
%dm2=1;
%ds1=1;
%ds2=1;
w0=0.001;
w1=0.6;
w2=0.399;
N=sum(NI);
%disp([m1, s1, m2, s2, w0, w1, w2]);
%while (dm1>.1 || dm2>.1 || ds1>.1 || ds2>.1)
iter=0;
while iter<80,
p0=1/I(end);
p1=exp(-1/2*((I-m1)/s1).^2)/sqrt(2*pi*s1^2);
p2=exp(-1/2*((I-m2)/s2).^2)/sqrt... |
c5a1d3500065b6791a153c817c23020f71efcb56f78e183b35df3c012075c255 | MATLAB | 1,010 | 43 | function [p_vec, t_vec, dof_vec] = welchT(x1, x2)
%WELCHT 2-sample Welch T-test
%% Prepare data
x1_size = size(x1);
if x1_size(end) == 1
x1_size(end) = [];
end
x2_size = size(x2);
if x2_size(end) == 1
x2_size(end) = [];
end
ndim = length(x1_size);
%... |
bbf3bf924caec5943700e1f21918d17c62f44f8404a9b5fc44147cc6e64ad179 | MATLAB | 1,015 | 38 | % Save NIFTI header extension.
%
% Usage: save_nii_ext(ext, fid)
%
% ext - struct with NIFTI header extension fields.
%
% NIFTI data format can be found on: http://nifti.nimh.nih.gov
%
% - Jimmy Shen (jimmy@rotman-baycrest.on.ca)
%
function save_nii_ext(ext, fid)
if ~exist('ext','var') | ~exist('fi... |
dcd665edbcff7419d79e3d27b00e7addb189eebe355067dd41c1f2fb06269625 | MATLAB | 1,015 | 30 | function C=clustering_coef_wu(W)
%CLUSTERING_COEF_WU Clustering coefficient
%
% C = clustering_coef_wu(W);
%
% The weighted clustering coefficient is the average "intensity"
% (geometric mean) of all triangles associated with each node.
%
% Input: W, weighted undirected connection matrix
... |
301299b7a0f9238652e364dc9833bd15d5cf6358ab76008f804ade9d15610b04 | MATLAB | 1,019 | 28 | function loc_list_clusters_norm_density_histogram(data)
input_values = inputdlg({'Percentile:'},'',1,{'0 95'});
if isempty(input_values)==1
return
else
percentile =str2num(input_values{1});
counter = 0;
for i = 1:length(data)
data_to = unique(data{i}.area);
if length(data_to)>1
... |
65a8d402707f1918c5208eaf13e88d37678f1b2d24020ce74ef570129eafa3e7 | MATLAB | 1,020 | 28 | function D = agreement_weighted(CI,Wts)
% AGREEMENT_WEIGHTED Weights agreement matrix
%
% D = AGREEMENT_WEIGHTED(CI,WTS) is identical to AGREEMENT, with the
% exception that each partitions contribution is weighted according to
% the corresponding scalar value stored in the vector WTS. As an example,
... |
9a0b47f98202ed9dd0398f4630c6567a06f84a37232475f81bdc2e99874d317f | MATLAB | 1,020 | 26 | function shape_classification_extract_classes(data)
number_of_classes = size(data.classes,1);
if number_of_classes == 1
input_values = inputdlg({'Classes to Exctract:'},'',1,{'1'});
else
input_values = inputdlg({'Classes to Exctract:'},'',1,{['1:',num2str(number_of_classes)]});
end
if isempty(input_val... |
af6fc083878d0c94b58a32099cad63679578ec2849f63eb90d4dd67f61b020c8 | MATLAB | 1,023 | 32 | function loc_list_clusters_total_clusters_area(data)
counter = 0;
for i = 1:length(data)
data_to = unique(data{i}.area);
if length(data_to)>1
counter = counter+1;
data_to_send{counter} = data{i};
end
end
if exist('data_to_send','var')
f = waitbar(0,'Finding Total Cluster Area')... |
23c1e85db45a23243de921374ca157e13136ca19613729d334e1dc04b5589a64 | MATLAB | 1,028 | 31 | function spt_compute_mean_velocity_correlation(data)
f = waitbar(0,'calculating mean msd');
for i=1:length(data)
mean_velocity_correlation{1} = calculate_mean_velocity_correlation(data{i}.velocity_correlation);
data_to_send{i}.velocity_correlation = mean_velocity_correlation;
data_to_send{i}.name = [da... |
23537e53285b550689cdc2ed9619cd67a28b7ca7830c1d3cdcc2b2d4b96044a0 | MATLAB | 1,032 | 42 | function create_HCP_MMP1_nifti_LBPD(vector,name)
% script to create HCP-MMP1 nifti file for rendering
% INPUTS: vector: a 1x90 vector with a value for each AAL region
% name: the name of the output file
if length(vector) == 180
MMP1 = load_nii('HCP-MMP1_on_MNI152_ICBM2009a_nlin.... |
713f74b0033bd8a33128ea1f778a421840022e79947b2a4aa07f05738e541929 | MATLAB | 1,036 | 66 | function [data, A] = three_source_model(T, type)
%if type = 0, one non-interacting source else source 1 -> source 2 ->
%source 3
M = 3; %number of sources;
P=2; %order of the model
T0=1000; %length of ignored start
Rmax=50;
%Generate stable AR matrix
while Rmax>3
lambdamax=10;
while lambdamax > 1 || lambda... |
4d8785b28abdecd677118a8f1258befb489b9e996e4f504c79b485f80152c81c | MATLAB | 1,039 | 29 | function loc_list_clusters_density_histogram(data)
input_values = inputdlg({'Percentile:'},'',1,{'0 95'});
if isempty(input_values)==1
return
else
percentile =str2num(input_values{1});
counter = 0;
for i = 1:length(data)
data_to = unique(data{i}.area);
if length(data_to)>1
... |
0dd4cb687a9dda6c69f9a2cfd002062032aab805fe498d2c8f1f78e8d5d10bfe | MATLAB | 1,040 | 36 | function dataTFR = eegFreqAnalysis(parameterSettingsTF, dataVC)
%% dataTFR = eegFreqAnalysis(parameterSettingsTF, dataVC, dataTL)
tc_struct2ws('caller', parameterSettingsTF)
% prepare data struct for fieldtrip
dataTFR=[];
dataTFR.trial=dataVC.virtChannels; % set virtual channels to be the data
dataTFR.time= arrayfun(... |
c0bde50575c1e66da3c656ef20776ae8261d56d72bbd794a9bf8742612d111f0 | MATLAB | 1,041 | 35 | function data_load = load_image()
[file_name,path] = uigetfile({'*.jpg;*.png;*.jpg;*.tif;*.tiff;*.jpeg'},'Select Image File(s)','MultiSelect','on');
if isequal(file_name,0)
data_load=[];
else
file_name = cellstr(file_name);
f=waitbar(0,'Loading Image(s)...');
for i = 1:length(file_name)
... |
4d4bd4aecc6b425af3352fc68b3f0add3c47929631b38ad5eb24e93465ae34bb | MATLAB | 1,052 | 33 | function [Rate_on_mean]=data_reduction(Rate_on,StringFunc)
if strcmp(StringFunc,'mean')
Rate_on_mean=[mean(getfield(Rate_on,'Presleep'))...
mean(getfield(Rate_on,'Post_Trial_1'))...
mean(getfield(Rate_on,'Post_Trial_2'))...
mean(getfield(Rate_on,'Post_Trial_3'))...
mean(getfield(Rate_on,'Post_Trial... |
bd4dc94aa1fe9303982dae56dee3874c9df668cbc3b4370b7291a7c66a1b49d5 | MATLAB | 1,052 | 39 | function [R,D] = breadthdist(CIJ)
%BREADTHDIST Reachability and distance matrices
%
% [R,D] = breadthdist(CIJ);
%
% The binary reachability matrix describes reachability between all pairs
% of nodes. An entry (u,v)=1 means that there exists a path from node u
% to node v; alternatively (u,v)=0.
%
% The ... |
f076755daffec6ee7c73ae80947e617404b7086a4d4082faa1c2b44552f9460d | MATLAB | 1,052 | 28 | function D = remove_bad_components_l(D,S)
% Take in a D object with D.ica.bad_components
% Make a new montage where all the channels stay the same but
% they have had the bad ICA components subtracted from them
D = D.montage('switch',0);
if strcmp(S.modality,'EEG')
chantype = 'EEG';
... |
17317645539ff970f9a9de5636663a0150c35936b24bb10da1ec83de3995554e | MATLAB | 1,054 | 35 | classdef EdgeResultsTest < matlab.unittest.TestCase
properties
variables
end
methods (TestClassSetup)
end
methods (TestClassTeardown)
function clearTestData(testCase)
clear
end
end
methods (Test)
function precalculatedInitTest(testCase)
... |
773a0149227ffc0149c265c0c4973edf2456599a453ed6e814c58b1cebc36608 | MATLAB | 1,056 | 24 | function Cs = subgraph_centrality(CIJ)
% SUBGRAPH_CENTRALITY Subgraph centrality of a network
%
% Cs = subgraph_centrality(CIJ)
%
% The subgraph centrality of a node is a weighted sum of closed walks of
% different lengths in the network starting and ending at the node. This
% function returns a vector of s... |
e1ae5e9fe6d358401248ce035bcd3fe91e2af584ff21055852e58100e1247e89 | MATLAB | 1,056 | 34 | classdef utils_tests < matlab.unittest.TestCase
methods(Test)
function test_graph_is_connected(testCase)
% Tests the graph_is_connected function against MathWorks'
% conncomp.
one_disconnected = ones(5);
one_disconnected(:,5) = 0;
one... |
00e88343c8454d9237eda1f9bd6f554e4f17d78cd821c3a4b372c51f017d4d5a | MATLAB | 1,058 | 59 | function V3 = harmonize_comm(V1, V2)
comm_diff1 = sum(V1~=V2)/length(V1);
count = 0;
for i=1:max(V1)
if sum(V1==i)<2
V1(V1==i) = 0;
count = count + 1;
else
V1(V1==i) = i-count;
end
end
count = 0;
for i=1:max(V2)
if sum(V2==i)<2
V2(V2==i) = 0;
... |
9e5078a1edb336ee5ef59bd5572af8f8694c322fc77c4d2736a374e099252de1 | MATLAB | 1,060 | 25 | function [valid_nodes,dis2cortex] = nst_headmodel_get_FOV(ChannelMat, cortex, thresh_dis2cortex, ChannelFlag)
%% define the reconstruction FOV
if nargin < 4
ChannelFlag = ones(1, length(ChannelMat.Channel));
end
montage_info = nst_montage_info_from_bst_channels(ChannelMat.Channel, Chan... |
b89647fb25d1a08136a7aaaad389ad53d7135e0dae586ea15ac5d2649e5b731e | MATLAB | 1,063 | 28 | function fig2svg(name, w, h, folder)
if nargin < 4
% Determine figure folder from name (e.g., "Fig2C" -> output/fig2/)
repoRoot = fileparts(fileparts(mfilename('fullpath')));
tokens = regexp(name, '(?i)(S?Fig)[_]?(\d+)', 'tokens', 'once');
if ~isempty(tokens)
prefix = low... |
3c8a56f3ad7616f4f2447a4f7ffabb3863df7981104a36946bb486d23b4bb27a | MATLAB | 1,064 | 41 | function loc_list_crop(data)
try
coordinates = getrect();
data_crop = cell(1,length(data));
for i = 1:length(data)
data_crop{i} = loc_list_crop_inside(data{i},coordinates);
end
data_crop = data_crop(~cellfun('isempty',data_crop));
catch
data_crop = [];
end
loc_list_p... |
62936f10fe16013033917a9c833ff768a4e309a3bd7b07c0e543969503352922 | MATLAB | 1,064 | 24 | function opt = resQ_opt(opt)
% function opt = resQ_opt(opt)
opt.resQ.present = 1;
opt.resQ = msf_ensure_field(opt.resQ, 'fig_maps', ...
{'s0', ...
'D', 'R', 'Vi','Va','Vt', ...
'VRi', 'VRa', 'XDRi', 'XDRa', ...
'D_lo', 'D_hi', 'Vi_hi','Va_hi','Vt_hi', ...
'Xi_hi', 'Xa_hi', 'Xt_hi', ...
... |
cdfcbd55fa9975f865339f30e5b23138d5bd5c7aab1d612e02109d1618ca1aaa | MATLAB | 1,065 | 32 | classdef Homoskedastic < nla.helpers.stdError.AbstractSwEStdErrStrategy
properties (SetAccess = protected)
REQUIRES_GROUP = false;
end
methods
function contrastStdErr = calculate(obj, sweStdErrInput)
%Calculation of standard error assuming homoskedasti... |
55c170bad58f3e0bcdde63da164fe07c74ad77e2c133cf60b0cd62bff1c86469 | MATLAB | 1,067 | 58 | %% microglia image
tiffread
for i=1:size(ans,2)
microglia(:,:,i)=ans(i).data;
end
% figure;imshow(reference_image)
figure;imagesc(microglia(:,:,1))
reference=[350,350]
reference=round(reference);
mask=zeros(size(microglia(:,:,1)));
mask(reference(2),reference(1))=1;
% figure;imagesc(mask)
% pixel
... |
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