sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
3a843f75a7c02ec9db241c1e4f4268797a21decb8f013c8e368a3f2cab7a82dc | MATLAB | 7,049 | 187 | function [obj] = ft_convert_units(obj, target, varargin)
% FT_CONVERT_UNITS changes the geometrical dimension to the specified SI unit.
% The units of the input object is determined from the structure field
% object.unit, or is estimated based on the spatial extend of the structure,
% e.g. a volume conduction model of... |
71f6f8f5c807aab045392e96a00c3f4f56b5eab6e69ba6a58b5b6e9218da656f | MATLAB | 7,050 | 212 | classdef mediumProperties
properties
name (1,:) char {mustBeNonempty} = 'Unlabeled medium'
mua (1,1) = @defaultnan_41func
mus (1,1) = @defaultnan_41func
g (1,1) = @defaultnan_41func
customPhaseFunc (1,1) = @defaultnan_21func
... |
da78be476f9407ceaeba957ba1d75656ebc791376a9aa993392a7054380030d3 | MATLAB | 7,051 | 183 | function [timelock] = ft_datatype_timelock(timelock, varargin)
% FT_DATATYPE_TIMELOCK describes the FieldTrip MATLAB structure for timelock data
%
% The timelock data structure represents averaged or non-averaged event-releted
% potentials (ERPs, in case of EEG) or ERFs (in case of MEG). This data structure is
% usual... |
c1a5e7a48e4589e509b512c7392a3ae7dd9fbe54d70300ca01abdff77220cff2 | MATLAB | 7,052 | 186 | function [event] = read_yokogawa_event(filename, varargin)
% READ_YOKOGAWA_EVENT reads event information from continuous,
% epoched or averaged MEG data that has been generated by the Yokogawa
% MEG system and software and allows those events to be used in
% combination with FieldTrip.
%
% Use as
% [event] = read_yo... |
59a1ea4395ce85266026c923b92f13a1ae8a1be2db5f379f86f5ff67911b8f34 | MATLAB | 7,054 | 223 | %% (Plot) jointDiffSDO
% Co-plot the background and spike-triggered SDO matrices from the 'sdo'
% datastructure as heatmaps. For use within the SDO Analysis Toolkit.
%
%PREREQUISITES:
% computeSDO()
% INPUT PARAMETERS
% sdo: 'sdo' structure
% XT_SDO_CH_NO: Row index for the sdo structure, pointing to a particular... |
8cc44019407088d62b19052d8950d1c0370ee0fcd1fb6970d85973cf55167137 | MATLAB | 7,054 | 168 | function varargout = DPABI_Utilities(varargin)
% DPABI_UTILITIES MATLAB code for DPABI_Utilities.fig
% DPABI_UTILITIES, by itself, creates a new DPABI_UTILITIES or raises the existing
% singleton*.
%
% H = DPABI_UTILITIES returns the handle to a new DPABI_UTILITIES or the handle to
% the existing si... |
bf971a527d5380e82f747906734e1b62042c2ca1d54a767867a68ad19d722d90 | MATLAB | 7,055 | 292 | function [ fp fn tp matchlist fplist fnlist ] = ...
wlProc_evalEventsVsTruth(evtruth, evtest, bandlim, snrlim, ...
comparefunc)
% function [ fp fn tp matchlist fplist fnlist ] = ...
% wlProc_evalEventsVsTruth(evtruth, evtest, bandlim, snrlim, ...
% comparefunc)
%
% This function compares an event list to a... |
c0f54923906ae21169385e0c749a1be3ab020b5a73281229204f8a40a6a630e7 | MATLAB | 7,056 | 184 | function [Error, Cfg]=y_NetworkConstruction(Cfg,DataDir,OutDir,SubjectListFile)
% FORMAT [Error, Cfg]=y_NetworkConstruction(Cfg,DataDir,OutDir,SubjectListFile)
% Cfg - the parameters for Network Construction.
% DataDir - Define the Data directory to replace the one defined in Cfg
% OutDir - Define the Output dire... |
0d7f11f61008eb30b8fe80f082a9ebfa42befddb3c40de80f147a6c64f42fed7 | MATLAB | 7,058 | 183 | function [timelock] = ft_datatype_timelock(timelock, varargin)
% FT_DATATYPE_TIMELOCK describes the FieldTrip MATLAB structure for timelock data
%
% The timelock data structure represents averaged or non-averaged event-releted
% potentials (ERPs, in case of EEG) or ERFs (in case of MEG). This data structure is
% usual... |
64ceb8bd5e1a45c40de601c5b7ae0507cf53495c3818982bfd4555e04541fb7d | MATLAB | 7,060 | 177 | function [ dataSource ] = loadTableDatasource( path, saveName, omitHeavyCoordinates, omitHeavyLGs, wbh, headpr )
% Don't directly use this function. Use dspace_data.loadCollection instead.
%
%
%
%
%<PRE>
% This file is part of dspace-core.
%
% Copyright (C) 2020 University Zuric... |
8cc0da65f21ead01c60eec9943599daca1e64c7b114f15e2e22d5e0af0fdeca1 | MATLAB | 7,060 | 169 | function [varargout] = bivariate_common(cfg, varargin)
% BIVARIATE_COMMON makes a selection for a specific reference channel from a
% bivariate (i.e. connectivity) dataset and returns that selection as a univariate
% dataset. This is used in singleplot/multiplot/topoplot for both ER and TFR data.
%
% Use as
% [varar... |
211ab9fbcf1e546fe1e2c382fb65e13554847e2c2d638329310cb98a0d4b12f3 | MATLAB | 7,062 | 258 | function [ newevent, error ] = wlProc_fitAmpBasic(hilmag, oldevent, atype)
% function [ newevent, error ] = wlProc_fitAmpBasic(hilmag, oldevent, atype)
%
% This function estimates oscillatory burst amplitude by curve fitting a
% logarithmic or linear ramp in the region of interest. Roll-on and roll-off
% are used if s... |
c8ab778d519b8763c18cc07b23ea8973030c2425ac7b7ed7e5f6b6475ffc22d0 | MATLAB | 7,065 | 317 | function [components1,components2] = localize_model(model,fixed_points,fp_linsys,verbose)
n_units=length(model.wO);
%%% output of the network computed at fixed points in context 1
output1=fp_linsys.o1;
%%% output of the network computed at fixed points in context 2
output2=fp_linsys.o2;
%%% I consider the linear s... |
2b02321336b59d41daad144448fac12befd5c1095c1d50cf508a5813e4378561 | MATLAB | 7,067 | 187 | function [trl,eventslist]= searchTaskTrialFun2(cfg)
% Defines trials with t = 0 at a stimulus onset marker, based on a motor
% response. Defines trial search window as from one stim onset marker to
% the next or EOF otherwise.
% Ming Scott's code
% Adapted from
% Sonya Bells's code (taskTrialFun)
% Based on Simeon Wong... |
c0a091076185910d0ac2ac5e44f8f871a4f0ce3caa4101cb645c555f1512d050 | MATLAB | 7,067 | 204 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%% Script for reproducibly generating MATLAB PREP artifacts via CI %%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Author: Austin Hurst
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%% Step 0: Ini... |
2a6f4aab7f132fc670f53b51d61dece7f628a230a0daaa7e84f6428fca30f3c3 | MATLAB | 7,068 | 148 | function [ titleStr, settings, results ] = repertoireDating_dspace_launcher( dataview, settings )
% This function computes/plots repertoire dating statistics and mixing matrices.
% This function can launch the following repertoire dating functions:
%
%
% <a href="matlab:doc('repertoireDating.... |
36927b78769dde85b907a44c286b22a2c6239af4fb9110749e2a19f40b9827c8 | MATLAB | 7,072 | 250 | classdef JavaProperties < handle
properties(SetAccess=private)
p;
fileName;
end
methods
function this=JavaProperties(fileName)
if nargin<1
this.p=java.util.Properties;
else
this.p=File.ReadProperties(fileName, true);
... |
a19e847f07def1b73b717c0d6dc9ff8f0d94d2ca842939ff0100355e5b6dd447 | MATLAB | 7,075 | 219 | function colorspace_demo(Cmd)
% Demo for colorspace.m - 3D visualizations of various color spaces
% Pascal Getreuer 2006
if nargin == 0
% Create a figure with a drop-down menu
figure('Color',[1,1,1]);
h = uicontrol('Style','popup','Position',[15,10,90,21],...
'BackgroundColor',[1,1,1],'Value',... |
0fe280a5d5724957d197f52ab33b5ed08acf89895728442713aabb6aa9b2d2a6 | MATLAB | 7,078 | 190 | % Covariance matrix on the unit square, squared exponential kernel.
%
% This example considers the covariance matrix between regular grid points on
% the unit square with squared exponential covariance function. The matrix is
% square, real, positive definite, and Toeplitz.
%
% We remark on a few key departures from th... |
e39d028000b91ea30d0ccaf0c020c94826e4dc0b7d7078fe10cb4054c2dce10e | MATLAB | 7,079 | 194 | %% Tensors
% Tensors are extensions of multidimensional arrays with additional
% operations defined on them. Here we explain the basics of creating and
% working with tensors.
%% Creating a tensor from an array
% The |tensor| command converts a (multidimensional) array to a tensor
% object.
M = ones(4,3,2); %<-- A 4 x... |
3dc8616b32828e82cfbf4d739fda19a630d181ff1ae6b7124fbc3f944370c95b | MATLAB | 7,082 | 289 | %%cell count
clear all
close all
for i = 1 :2
cd Example_images/
filename1 = ['220311_NS_1_cs2_10X_' num2str(i) '_DAPI.tif'];
filename = extractBefore(filename1,'DAPI');
dapi = imread(filename1);
[px, py] = size(dapi);
% figure
% subplot(1,2,1)
% imshow(dapi)
% subp... |
6ff7da1fdb60bfac1b9745d36ff85a7529f8161226a3c2c5314b6478b51b6ebb | MATLAB | 7,085 | 182 | function varargout = interp_gridded(transform, val, pos_to, varargin)
% INTERP_GRIDDED computes a matrix that interpolates values that were
% observed on positions in a regular 3-D grid onto positions that are
% unstructured, e.g. the vertices of a cortical sheet.
%
% Use as
% [val] = interp_gridded(t... |
6b5fa430f65812e4e2ca99e4b2529b0a3895f3a19793400c8221dd1b710a11f1 | MATLAB | 7,087 | 163 |
%%% center_points tiling_info read_file_name
xxx_min = floor(min(center_points.xxx + min(center_points.xxx_shift,[],2)) - tiling_info.x_pixel./2) ;
xxx_max = ceil(max(center_points.xxx + max(center_points.xxx_shift,[],2)) + tiling_info.x_pixel./2);
yyy_min = floor(min(center_points.yyy + min(center_po... |
393a2d23bc357c445e3830d034be67d8fc0eec074dcaadba5aeb7dffe1c00bb3 | MATLAB | 7,088 | 119 | %% 共空间模式 | common spatial patterns (CSP) 不可在main中调用，仅可单独使用
%% one vs one Multiclass or two-classes 目标函数法
% how：N个类别中任意两个做CSP，共得到CN2=N*(N-1)/2个投影矩阵，对每个投影矩阵取最佳的2m个方向（前后各m个），特征矩阵为2m*N*(N-1)/2=m*N*(N-1)维
% 优点：每次计算CSP投影矩阵时，2个类别都是单纯的类别，更容易找到两类差别最大的投影方向
% 缺点：N类需要计算CN2个投影矩阵，N很大时，计算量会大大增加
% 注意：在计算CSP投影矩阵时，并非使用整个trial，而是将trial... |
eba3495245d486f3d62c0c0eb6248b7b55069acb41172e9f79a23d7e77e37a1b | MATLAB | 7,089 | 189 | function [lfp] = bz_GetLFP(varargin)
% bz_GetLFP - Get local field potentials.
%
% Load local field potentials from disk. No longer dependent on
% FMAT/SetCurrentSession.
%
% USAGE
%
% [lfp] = bz_GetLFP(channels,<options>)
%
% INPUTS
%
% channels(required) -must be first input, numeric
% ... |
bce2fe6a9e797600262f91580872736af15bc564d49c02edfe5f23502277e62f | MATLAB | 7,090 | 194 | function [mri_unbias] = ft_volumebiascorrect(cfg, mri)
% FT_VOLUMEBIASCORRECT corrects the image inhomogeneity bias in an anatomical MRI
%
% Use as
% mri_unbias = ft_volumebiascorrect(cfg, mri)
% where the input mri should be a single anatomical volume organised in a structure
% as obtained from the FT_READ_MRI func... |
b41077377ba517508dc19d1deaa19f8708bca4e9f1ff642d7ac443cedc84bbae | MATLAB | 7,094 | 263 | function meg_plotGroup()
%% make group data structure 2
% how many channels to inspect? (max 7, if >7 rerun analyses)
nC = 5;
% cue conds
groupD2.cueT1 = [];
groupD2.cueT2 = [];
groupD2.neutral = [];
groupD2.cueT1All = [];
groupD2.cueT2All = [];
groupD2.neutralAll = [];
fields = fieldnames(groupD2);
% c... |
67fac9fbf4426780d03fae0cb2fdeca8e55770eeb79cf282228e1c5704fd0c30 | MATLAB | 7,098 | 203 | function bz_ConcatenatedTimes(basepath,sortFiles)
% bz_ConcatenatedTimes(basepath)
% This function generates the events.mat file that saves all the merge
% information. Useful if you dind't do this when you merged the dats.
%
% USAGE
%
% bz_ConcatenateDats(basepath,sortFiles)
%
% INPUTS
%
% basepath ... |
39da6a2342bc984c0b050c5dfc026339129470d5f4165f27cabce21d78e7d4ac | MATLAB | 7,099 | 158 |
% Written by: Tianyin Xu
% Edited by: Qiuting Wen, Adam Wright
% Last modified: 20240925
%Modifications:
%20240925 -- Updated the UBA mask to be UBA_exclude_VA_PCOM_fmri.nii.gz
% Inputs:
% fMRI_path -- the scans path -- this path must include the following
% files:
% - UBA_exclude_VA_PCOM_fmri.nii.gz Modified: 2... |
1c7987c912da9e59fd869c9aaf9b5e448b2091d83a3d4dacdb646134b1561bb5 | MATLAB | 7,101 | 239 | function str = printstruct(name, val)
% PRINTSTRUCT converts a MATLAB structure into a multiple-line string that, when
% evaluated by MATLAB, results in the original structure. It also works for most
% other standard MATLAB classes, such as numbers, vectors, matrices, and cell-arrays.
%
% Use as
% str = printstruct(... |
563e281eef769b727e94e136c7c362f5db65f08e0751a9c21c808300ee9f3354 | MATLAB | 7,101 | 176 | function varargout = w_StructuralSelect(varargin)
% W_STRUCTURALSELECT MATLAB code for w_StructuralSelect.fig
% W_STRUCTURALSELECT, by itself, creates a new W_STRUCTURALSELECT or raises the existing
% singleton*.
%
% H = W_STRUCTURALSELECT returns the handle to a new W_STRUCTURALSELECT or the handle to
%... |
dfb1e4905360df26b140e27669f5a34e6a7042851b8c461cd9191afb0672653b | MATLAB | 7,101 | 248 | %%%%%%%%%%%%%%%%%%%% REPROJECT ON THE IMAGES %%%%%%%%%%%%%%%%%%%%%%%%
if ~exist('n_ima')|~exist('fc'),
fprintf(1,'No calibration data available.\n');
return;
end;
if ~exist('no_image'),
no_image = 0;
end;
if ~exist('nx')&~exist('ny'),
fprintf(1,'WARNING: No image size (nx,ny) available. Setting nx=640 an... |
d03ddf4ec9c4eb238f9eb08986547d7e673a61cd1fe80fd379c18a492068dae1 | MATLAB | 7,105 | 165 | function [result, done]=run_HiD_match(trainingSet, trainingIds, testSet, ...
testIds, varargin)
%%RUN_HiD_MATCH runs the QF match algorithm
% on the subsets found within a training test set of data.
%
% The publication that introduces the algorithm is
% https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5818510/
... |
ec9cdec44f44070a2f635371bb0fbbb3c5d26ef3366d5e98c9bc405bfedf86a4 | MATLAB | 7,105 | 291 | %%% epoch_lan.m
%%% v.1.0.1 (migrating to lan_epoch)
%%% V.1 (for epochs.m v2.)
%%%
%%% 04.04.2012
%%% 14.04.2009 %%% en proceso
%%% Pablo Billeke
%%%
%%% create epochs for continuos data (2D matrix)
%%% for EEGLAB, condition is 1, the output is a 3D matrix. default
%%% for LAN, condition is 2, the output... |
b4be87cf9a23caf67ab6e52e549af885d7fba48fab90db7e8db8826f584b5fb3 | MATLAB | 7,106 | 237 | function bz_LFPfromDat(basepath,varargin)
% perform lowpass (2 X output Fs) sinc filter on wideband data
% subsample the filtered data and save as a new flat binary
% basename must have basename.dat and basename.xml
% basepath is the full path for basename.dat
%
% note that sincFilter was altered to accomodate GPU filt... |
a95d587a1ebfa892f8f5c5d8bcf141eb19e9973de1c5538bedf0fcde87b94dcc | MATLAB | 7,107 | 178 | function [ titleStr, settings, results ] = localGraphAnalysisLabels( dataview, settings )
% This function function can summarize the connected nodes for each datapoint
% in the current filter in several ways.
%
% If the graph is a nearest-neighbour graph, this module function computes
% stati... |
18241e62fe72e77b257decb6f8b736f392ec0e8d4cd8578b19f492200b8da26a | MATLAB | 7,109 | 261 | function [hfig,savename,sortederrs] = PlotFracInliersPerLandmark_AR(varargin)
[gtdata,net,pttypes,colors,exptype,...
conddata,labeltypes,datatypes,statname,...
maxerr,minerr,...
hfig,figpos,savedir,savename,dosavefig,prcs,maxprc,...
annoterrdata,annotcolor,annoterrprc,plotannfracinliers,...
APthresh] = mypar... |
bacf7313aac83674cb3f555ce224414d8d662b83f45a5310d2692abee8f71eb5 | MATLAB | 7,109 | 1 | % TSLIMIT Limit the range of subjects, sessions, phases, or trials.
% Currently, limiting by date is not supported.
%
% TSLIMIT(fieldname,INDEX-SPECIFICATION) sets limits on the range that
% will be used for statistics computations. fieldname must be either
% 'Subjects', 'Sessions', 'Phases', or 'Trials'.
%... |
75551298f0350c5524d7450793180ddaa721a8a76b4bbfde1d3ddc666ac53dfc | MATLAB | 7,110 | 282 | function [xp,dxpdom,dxpdT,dxpdf,dxpdc,dxpdk] = project_points(X,om,T,f,c,k)
%project_points.m
%
%[xp,dxpdom,dxpdT,dxpdf,dxpdc,dxpdk] = project_points(X,om,T,f,c,k)
%
%Projects a 3D structure onto the image plane.
%
%INPUT: X: 3D structure in the world coordinate frame (3xN matrix for N points)
% (om,T): Rigid mo... |
8c676f75cda9ce8d661be8a5603c267700c9ef187bf40521a977f95ef926b225 | MATLAB | 7,111 | 221 | function [fs1, fs2, er] = compareStructs(s1,s2,n1,n2,p,tol)
% check two structures for differances - i.e. see if strucutre s1 == structure s2
% function [fs1, fs2, er] = compareStructs(s1,s2,n1,n2,p,tol)
%
% inputs 6 - 5 optional
% s1 structure one class structure
% s2 structure ... |
86ea279f1ec2099a9eda4fdbfb392d032e3cd9413351eb2d49c29745715f538e | MATLAB | 7,121 | 242 | function [out1,out2,out3] = ginput4(arg1)
[out1,out2,out3] = ginput(arg1);
return;
%GINPUT Graphical input from mouse.
% [X,Y] = GINPUT(N) gets N points from the current axes and returns
% the X- and Y-coordinates in length N vectors X and Y. The cursor
% can be positioned using a mouse (or by using the Ar... |
3a78559652edbf17229478f820d411ce0dc7e838b57625a7590e5bbe1317c065 | MATLAB | 7,130 | 183 | function StatsTableExporter(PvaluesTable,OverallPValue,GroupNames,TestName,SaveDir)
FullLabelTableDisplay=0;
for i=1:length(GroupNames)
GroupNamesNumberedList{i}=[num2str(i),': ',GroupNames{i}];
GroupNamesNumbers{i}=[num2str(i)];
end
if FullLabelTableDisplay
MaxLength=14;
... |
b0b8ace03e55a006e549e4444a6b3dc50a66e6062f68538a396b569e7b1c0869 | MATLAB | 7,130 | 203 | function command = trainCodeGenBase(dmc, varargin)
% Generate a base command for training. Returned command uses WSL paths (see
% DLBackEndClass documentation). This is a static method of DLBackEndClass.
[nativeAptRootAsChar,...
confparamsextra,...
val_split,...
ignore_local,...
do_just_generate_db] = ...
myparse... |
4884aa9f559e0395ac0f900d87e4e930f4c0abdae15f8916804804e327bd9804 | MATLAB | 7,131 | 251 | function [tfr,t,f]=tfrunter(X,time,form,fmin,fmax,N,trace);
%TFRUNTER Unterberger time-frequency distribution.
% [TFR,T,F]=TFRUNTER(X,T,FORM,FMIN,FMAX,N,TRACE) generates the
% auto- or cross-Unterberger distribution (active or passive form).
%
% X : signal (in time) to be analyzed. If X=[X1 X2], TFRUNTER
% compute... |
29f548f7b6b4cde9b34620664fe43a680719b567a243758de848c14662b7bf64 | MATLAB | 7,135 | 210 | function [] = makeProbeMapKlusta2(folder, xmlfile)
%% this function takes an xml file with spike groups already assigned and
%% generates *.prb files for each shank for spike detection/masking/clustering
%% IMPORTANT: this function ASSUMES that the order of the channels for each shank
%% in the spike groups map onto ... |
259aa10a34a075f143ce56587b369f89c92a0dfc69a760d4f222631951f34c28 | MATLAB | 7,137 | 121 | function [ mov ] = recordBrain( M, vcontribs, subjstructs, stimuluscode, stimulusstrcell, range, cmapstruct, viewstruct, filename, pos )
%RECORDBRAIN Capture activateBrain's graphical output into an avi file.
%
% Iteratively calls activateBrain with an activation data column of
% passed activation matrix and... |
d22f2875cbf969576f67adb85e92db9389ddb4e36e37a27ea23e1fe98411d34a | MATLAB | 7,141 | 137 | %% Line (Trapezoid)
disp('######################################');
disp('#### Design a circular trajectory ####');
disp('#### ####');
disp('######################################');
disp(' ');
kx = linspace(-5,5, 256)';
ky = linspace(-5,5, 256)';
kz = 0*ky;
C = [kx ky kz];
[C_riv, time_ri... |
16738c974804a3865abf3aab388b5025f78a91e49c480af8459ee82897b7b1be | MATLAB | 7,144 | 240 | function [results] = get_ndRMS(data,layout,IED,sample_freq,bad_channels,varargin)
%%% requirements
%add the latest version of FieldTrip toolbox
%(https://www.fieldtriptoolbox.org/) to your path.
%%% ------------ inputs:
% data: raw data [channels x time]
% layout: electrode location in the grid (e.g. [1,2,3;4,5,6;7,8,... |
307ea4d6295003031cd816fa012add2f7f8cdd4a565cd7375eac590d0fad0aca | MATLAB | 7,144 | 323 | clear
clc
close all
%%% Compute mTDR using rat FOF data from Pagan et al., 2025
addpath('mbtdr/functionFiles')
addpath('mbtdr/functionFiles/tools_kron')
addpath('mbtdr/minFunc')
addpath('mbtdr')
%% plotMarinoResults
%%% load rat dataset
fileDir = 'Arrays_Pagan/';
load(['data/' fileDir 'dataT_Pagan'])
paramFi... |
30c02a0fef10fcdd1ef01e4c4bfe947ef3f605415150fced7b44db1d19640d60 | MATLAB | 7,145 | 134 |
%%% shifting_key shifting_key_n z_truncate
%%% trform
%%% tiling_info.z_pixel tiling_info.x_pixel tiling_info.y_pixel
%%% tiling_info.x_overlap tiling_info.y_overlap
%%% tiling_info.x_tiles, tiling_info.y_tiles, ~, tiling_info.ch_num
tiling_info_xy = [tiling_info.x_tiles, tiling_info.y_tiles];
clear center_po... |
cf4afa1cdc23674010832e43adcd9f6154e13aa3d636235b5fe49eef06fd9408 | MATLAB | 7,145 | 220 |
function [posterior, out] = demo_dynamicalSystem ()
% // VBA toolbox //////////////////////////////////////////////////////////
%
% [posterior, out] = demo_dynamicalSystem ()
% Demo of dynamical system simulation and inversion
%
% This demo provides a simple example of the simulation and the estimation
% for a simple ... |
66413d542350aad56933c8ff40dece313b1b5e3f63813d193ba431d487370e2c | MATLAB | 7,148 | 194 | function histDataStruct = getHistogramData_KB(hImage,ClimInit)
% GETHISTOGRAMDATA Returns data needed to create the image histogram.
% The fields inside of HISTDATASTRUCT are:
% histRange Histogram Range
% finalBins Bin locations
% counts Histogram counts
% nBins Number of b... |
9055f246d0166cf6e455cc45bd1906901f4197abe1420183742cece6cdfb110d | MATLAB | 7,148 | 138 | %% Line (Trapezoid)
disp('######################################');
disp('#### Design a circular trajectory ####');
disp('#### ####');
disp('######################################');
disp(' ');
kx = linspace(-5,5, 256)';
ky = linspace(-5,5, 256)';
kz = 0*ky;
C = [kx ky kz];
[C_riv, time_ri... |
295bfc5ebd171c45370c76e647110692514bc3c4d227a1621d1ead4550a58e26 | MATLAB | 7,149 | 177 | function grad = yokogawa2grad(hdr)
% YOKOGAWA2GRAD converts the position and weights of all coils that
% compromise a gradiometer system into a structure that can be used
% by FieldTrip. This implementation uses the old "yokogawa" toolbox.
%
% See also CTF2GRAD, BTI2GRAD, FIF2GRAD, MNE2GRAD, ITAB2GRAD,
% FT_READ_SENS,... |
5f889d23c800ccaefc9df25718dc306d1e0fd28a3b4f7c62166d084eefd79d19 | MATLAB | 7,149 | 189 | function Obj = SOFAload(fn,varargin)
%SOFALOAD
% Obj = SOFAload(FN) reads the SOFA object OBJ with all data from
% a SOFA file FN.
%
% FN can point to a remote file (containing '://') or to a local file:
% Remote file: FN will be downloaded to a temporary directory and
% loaded.
% Local file: If ... |
9246508b0bf360ec76a98777ba1e8fb93cb98134eda50ab0d232a96fa7d2fffc | MATLAB | 7,154 | 265 | function [hfig,savename,sortederrs] = PlotFracInliersPerLandmark_ARannotator(varargin)
[gtdata,net,pttypes,colors,exptype,...
conddata,labeltypes,datatypes,statname,...
maxerr,minerr,...
hfig,figpos,savedir,savename,dosavefig,prcs,maxprc,...
annoterrdata,annotcolor,annoterrprc,plotannfracinliers,...
APthresh... |
9bbf3190048e957a787782891087795f86a8d93fe54f788eacf01a5a4a9f7050 | MATLAB | 7,155 | 178 | function checkhessian(problem, x, d)
% Checks the consistency of the cost function and the Hessian.
%
% function checkhessian(problem)
% function checkhessian(problem, x)
% function checkhessian(problem, x, d)
%
% checkhessian performs a numerical test to check that the directional
% derivatives and Hessian def... |
94a2a8500fcfff209b989e5a4f6a97fe6741d2f9e9155364d6a8afcfe1d09b3d | MATLAB | 7,156 | 190 | function [obj] = ft_convert_units(obj, target, varargin)
% FT_CONVERT_UNITS changes the geometrical dimension to the specified SI unit.
% The units of the input object is determined from the structure field
% object.unit, or is estimated based on the spatial extend of the structure,
% e.g. a volume conduction model of... |
9e91f61beb9c250301b10298842e30fe848f35442c5d677affe5984d71d5fffe | MATLAB | 7,161 | 191 | function grad = ricoh2grad(hdr)
%% RICOH2GRAD converts the position and weights of all coils that
%% compromise a gradiometer system into a structure that can be used
%% by FieldTrip. This implementation uses the "ricoh_meg_reader" toolbox.
%%
%% See also FT_READ_HEADER, CTF2GRAD, BTI2GRAD, FIF2GRAD, YOKOGAWA2GRAD_NEW... |
37d6414d79cec4f734a9b7b39a4cb5967c5f43196c9f078de7e4fe7582fc077d | MATLAB | 7,162 | 206 | function [corr_LxLy_tr,corr_LxLy_te,pvals_corr_LxLy_te] = CBIG_VK2019_crossval(X,Y,signif_LC,grouping,k,nPerms)
% This function computes PLS in k-fold cross-validation.
% The sample is first divided into training & test set, accounting for the
% diagnostic groups.
% PLS is computed on the training data to obtain the ... |
2915c59d48605f2edb49865eba821345258ad3c4e8564fea09d3fc404d15d199 | MATLAB | 7,165 | 188 | % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Cluster Ictal Signal
% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% REFERENCE Kameneva2017_Article_NeuralMassModelsAsAToolToInves.pdf
%% First Identify the B,G value range
clear
A = '5.50';
p_m = '90';
p_v = '12... |
a744dbcb406607fc100a5a963f4595adfdb8f73130040b22e0a1bcb7541da41a | MATLAB | 7,166 | 133 | %% NATSORTFILES Examples
% The function <https://www.mathworks.com/matlabcentral/fileexchange/47434
% |NATSORTFILES|> sorts filenames or filepaths in an array (cell/string/struct)
% taking into account number values within the text. This is known as
% _natural order_ or _alphanumeric order_. Note that MATLAB's inbu... |
c131b2f0acbcad878a70bda5dc8d3702c1ca0f5d4a49ec60cfd0d594cb10afd7 | MATLAB | 7,169 | 207 | function varargout=shadedErrorBar(x,y,errBar,varargin)
% generate continuous error bar area around a line plot
%
% function H=shadedErrorBar(x,y,errBar, ...)
%
% Purpose
% Makes a 2-d line plot with a pretty shaded error bar made
% using patch. Error bar color is chosen automatically.
%
%
% Inputs (required)... |
e8c2f38c184c0fb2c3f7a7a5be71fd2ebd5b8a77ca4229564f3103883e36066b | MATLAB | 7,169 | 187 | function [dataout] = ft_denoise_prewhiten(cfg, datain, noise)
% FT_DENOISE_PREWHITEN applies a spatial prewhitening operation to the data using the
% inverse noise covariance matrix. The consequence is that all channels are expressed
% in singnal-to-noise units, causing different channel types to be comparable. This
%... |
2fb6d8cc94e5142cd4b383536d9439b3de7e492686138e21a450779199bdc134 | MATLAB | 7,170 | 169 | function [h,lh,sh] = myboxplot(ax,data_cell,x_pos,significance_matrix,labels,colors,box_alpha,box_width,label_angle,show_caps,show_outliers,data_avg_symbol,whiskerArgs,medianArgs,avgArgs,significanceArgs)
if isempty(ax)
ax = gca;
end
if (nargin < 3) || isempty(x_pos)
x_pos = 1:numel(data_cel... |
b282944e4c99f43487545a2a2d62d746ec43d394fdb19641d9c7c4abf06de592 | MATLAB | 7,170 | 166 | function [s, cfg] = ft_statfun_depsamplesFmultivariate(cfg, dat, design)
% FT_STATFUN_DEPSAMPLESFMULTIVARIATE calculates the MANOVA dependent samples
% F-statistic on the biological data in dat (the dependent variable), using the
% information on the independent variable (ivar) in design.
%
% Use this function by call... |
afc28dad492e545760f7608b354ae168fa1d71e51a9cca7991ad063a978803d3 | MATLAB | 7,177 | 176 | function Aout = h_executeFrameAnalysisCalc3(handles)
global h_img3
[currentInd, handles, currentStruct, currentStructName] = h_getCurrendInd3(handles);
fname = get(handles.currentFileName,'String');
[filepath, filename, fExt] = fileparts(fname);
zLim(1) = str2num(get(handles.zStackStrLow,'String'));
zLim(... |
e579b5161b59932c175225dcf134532cfbbc66fe906d24f7f411b47dd409e1e8 | MATLAB | 7,177 | 210 | function M = fixedrankfactory_3factors(m, n, k)
% Manifold of m-by-n matrices of rank k with polar quotient geometry.
%
% function M = fixedrankfactory_3factors(m, n, k)
%
% The first-order geometry follows the balanced quotient geometry described
% in the paper,
% "Linear regression under fixed-rank constrain... |
b284aa95c0786b4d0718b019f85507571952661cc012377ab99d13f20b55a989 | MATLAB | 7,182 | 267 | function [hfig,savename,sortederrs] = PlotFracInliersPerGroup(varargin)
[gtdata,net,pttypes,colors,exptype,...
conddata,labeltypes,datatypes,statname,...
maxerr,minerr,...
hfig,figpos,savedir,savename,dosavefig,prcs,maxprc,...
annoterrdata,annotcolor,annoterrprc,plotannfracinliers,...
APthresh,someallonly,la... |
f658b4803c58d9f563e39725c3be6db8e10552b719b03afac16a8f2ac3f58e9e | MATLAB | 7,182 | 188 | function trl = includesBasedTrialFun(cfg)
% Defines trials with t = 0 at a stimulus onset marker, based on inclusion and exclusion of specific
% markers within the trial.
%
% Simeon Wong
%%% REQUIRED INPUTS %%%
% cfg.dataset - path to CTF dataset
%
% cfg.trialdef.t0marker - defines the t = 0 of each tri... |
1d08d0c6e305a9b9aa61f769b6c9a50662f05585c00a08656778279d89e337ff | MATLAB | 7,183 | 174 | % function emotion2020_analysis_BATCH
%
% This code include
% - Data preparations for delineating indivual ROIs, including WholeBrain, HCP360 ROIs, subcortical regions
% - (regularized) linear regression analyses (encoding/decoding) between MRI data
% and labels (category, dimension, vision, semantic) associa... |
9691b46b73c631dcaadf04a944c1471befe33b882e4079835d5ce7145781548a | MATLAB | 7,186 | 248 | function headmodel = ft_headmodel_dipoli(mesh, varargin)
% FT_HEADMODEL_DIPOLI creates a volume conduction model of the head
% using the boundary element method (BEM) for EEG. This function takes
% as input the triangulated surfaces that describe the boundaries and
% returns as output a volume conduction model which c... |
9a0ef08584ff327e4d22300e7698259b43c1b8eb68ea395c234916e8b7a33026 | MATLAB | 7,186 | 235 | function markdown2matlab(infile,outfile,varargin)
% MARKDOWN2MATLAB converts a Markdown file to a MATLAB script or function. All text
% is converted to comments, headings are converted to comment lines starting with %%
% sections with code are properly formatted, and words that appear in bold, italic or
% monospace ar... |
ef8d1709de35133982a9958a206274e47a5b52f7edcf088f809ed57f1150c939 | MATLAB | 7,187 | 207 | function [N,X,sp] = smoothHistogram(varargin)
% HISTOGRAM generates a histogram using the "optimal" number of bins
%
% If called with no output argument, histogram plots into the current axes
%
% SYNOPSIS [N,X,sp] = histogram(data,factor,normalize)
% [...] = histogram(data,'smooth')
% [...] = h... |
07c39e6dfdae9c485c095d2de14a18bbe90e877e6a304c4d414f579b04f09b52 | MATLAB | 7,188 | 162 | function CBIG_AuthorTopic_VisualizeComponentsOnBrainSurface(paramsPath, ...
outputDir, discretizationRes, minThresh, maxThresh, ...
colorscaleName, doRemoveSmallClusters)
% CBIG_AuthorTopic_VisualizeComponentsOnBrainSurface(paramsPath, ...
% outputDir, discretizationRes, minThresh, maxThresh, ...
% colorsca... |
a10fcb97c484f46d6c6d1ee0fd531764c70c9bae6f57121a2af7699e0c37ee39 | MATLAB | 7,191 | 204 |
function [EEG ] = pop_loadeeg_lan(filename, filepath, range_chan, range_sweeps, range_typeeeg, range_response, datformat);
% EEGLAB origial scripts
%
% comvertions per Pablo Billeke
% 10.11.2010
% command
EEG = [];
%command = '';
if nargin < 1
% ask user
[filename, filepath] = uigetfile('*.eeg;*.EEG', 'Choose an ... |
760b0d72794e5f0d0f200bb9a4001c2b12228bd4c61d623661d2680653301838 | MATLAB | 7,192 | 248 | function headmodel = ft_headmodel_dipoli(mesh, varargin)
% FT_HEADMODEL_DIPOLI creates a volume conduction model of the head
% using the boundary element method (BEM) for EEG. This function takes
% as input the triangulated surfaces that describe the boundaries and
% returns as output a volume conduction model which c... |
0e8aaef3e7ab3bff64242a7967c490779bcffe0af1308925bb81991a93cde4a3 | MATLAB | 7,194 | 157 | classdef TrackerCreateInfo
% Represents the information needed to create a 'fresh' tracker.
% This is meant to replace the "augmented class" cell array data structure
% that used to be used for such info. Having it be a proper class allowed
% better type checking and leads to more readable code. However, we s... |
331268fdb5b86c8a19922709ad8a97755a53eb0be52edfdc55958534e55bfb49 | MATLAB | 7,194 | 187 | function [features, values_m, values_a] = MARA_extract_time_freq_features(EEG)
% function [features, values_m, values_a] = MARA_extract_time_freq_features(EEG)
%
% values_m = avg. resid value btw 20 and 50 Hz
% values_a = avg. resid value btw 8 and 13 Hz
% features = list of components with bumps
... |
a7cf1c7acca22b215a7c5489bf13fdde79877c8421331b9997a4137cd579ffba | MATLAB | 7,196 | 134 |
%%% shifting_key shifting_key_n z_truncate
%%% trform
%%% tiling_info.z_pixel tiling_info.x_pixel tiling_info.y_pixel
%%% tiling_info.x_overlap tiling_info.y_overlap
%%% tiling_info.x_tiles, tiling_info.y_tiles, ~, tiling_info.ch_num
tiling_info_xy = [tiling_info.x_tiles, tiling_info.y_tiles];
clear center_po... |
c1399da27fb66e3bf66c31a61a60028a5a2b44837b3ca73f675942852ea20bd0 | MATLAB | 7,196 | 173 | %%
% ================= KEYPRESS ANALYSIS =================
%%
clear all; close all; clc;
%%
for s = 1:21
if s < 10
sub = strcat('P0',num2str(s));
else
sub = strcat('P',num2str(s));
end
if sub == "A09" || sub == "A15"
runs = [1:5];
else
ru... |
886830c73d54f76d0aa6d89952989ad6cc1beb3244b0da0c4a56be1afa437210 | MATLAB | 7,200 | 189 | % Function that generates the spikes in the input layer.
% Chengcheng Huang's code:
% https://github.com/hcc11/SpatialNeuronNet
% https://github.com/hcc11/FI_SpatialNet
function sx=genXspk(p,Nx,T)
% p: param struct
% sx=genXspk(stim_type,rX, Nx,cx,sigmac,Nsource,T,dt,taucorr,varargin)
switch p.stim_type
case 'Lo... |
9f88154d6c02443de91927666eea49ddafa36d72410d56935c7796f3300fa7a1 | MATLAB | 7,206 | 196 | function [label] = atlas_lookup(atlas, pos, varargin)
% ATLAS_LOOKUP determines the anatomical label of a location in the given atlas.
%
% Use as
% label = atlas_lookup(atlas, pos, ...);
%
% Optinal input arguments should come in key-value pairs and can include
% 'method' = 'sphere' (default) searches surrou... |
90c49c09b97857afc6a9962764e73dd8052fc5d71bb923ca8e350f9a09d59107 | MATLAB | 7,208 | 164 |
%% Compare wave dynamics with task outcome
% Do analysis by trial type as well as touch times
%%% Spatial map of traveling wave
FG = struct();
win = 1;
win = [win win+floor(min(Exp.TrialEnd-Exp.TrialStart)/20)]; %Lets look at the full trial response
FG.Hit = waveAnalysis(Waves.wavesHit,win);
FG.CR = waveAnal... |
0fc9cb18d4cd1e9f49a82ff1cee70990b134ab787c6e91ae77477343cd4faf8a | MATLAB | 7,210 | 210 | function [result, M] = ft_warp_optim(input, target, method)
% FT_WARP_OPTIM determine intermediate positions using warping (deformation)
% the input cloud of points is warped to match the target.
% The strategy is to start with simpelest linear warp, followed by a more
% elaborate linear warp, which then is followed b... |
86fdb6461b0c26549169d30d45a63c47f3b67b32ed7c8135acfb7c783f363942 | MATLAB | 7,212 | 208 | function curr_net = CBIG_Plot17NetworksRearrCorrMat_WhiteGrid_newscale(lh2lhcorrmat, lh2rhcorrmat, rh2rhcorrmat, scalelim, filename_prefix)
% curr_net = CBIG_Plot17NetworksRearrCorrMat_WhiteGrid_newscale(lh2lhcorrmat, lh2rhcorrmat, rh2rhcorrmat, scalelim, filename_prefix)
% Example : CBIG_Plot17NetworksRearrCorrMat_Wh... |
ba8dc853ff7d1f492c7926f9a10876f0adbd31d64a66a5b91decd0a1dd9a548a | MATLAB | 7,212 | 255 | function [h] = plotDensity(f_fname,g_fname,u,n_t,options,dim,pX,gX,pY,gY)
% plot predictive density
% function [hp] =
% plotDensity(f_fname,g_fname,u,n_t,options,dim,pX,gX,pY,gY)
% IN:
% - f_fname: name/handle of the evolution function
% - g_fname: name/handle of the observation function
% - u: input to the sys... |
f064912c317339d9e61e890880087e20f96a094b4add047602a270a8ae9b0d29 | MATLAB | 7,213 | 191 | function [mri] = align_ctf2acpc(mri, opt, template)
% ALIGN_CTF2ACPC performs an approximate rigid body alignment of the anatomical
% volume from CTF towards ACPC coordinates. Only the homogeneous transformation
% matrix is modified and the coordsys-field is updated.
%
% Use as
% mri = align_ctf2acpc(mri)
% mri = ... |
4f92733c6356d3efd4cac4a259ddf6d05ef659bb340724590cee577996520846 | MATLAB | 7,214 | 190 | %% Demo of what constitutes plausible sparsity prior for linear regression
% MODEL: y = Ax + noise; s.t. card(x) = k
%
% =============================================================================
%
% MODEL: y = Ax + noise; s.t. card(x) = k
%
% QUESTION: what constitutes a "plausible" sparsity-inducing prio... |
9b597e8c856427f0549686acd7658bb5ee704f3e81aa539b94a0e0ff45ac18c4 | MATLAB | 7,216 | 258 | % this script displays the voltage trace from the .wcp file from a patched
% cell.
% It imports the first five (V input, I input, light TTL output,
% camera frame input, blue light activation TTL input) channels
% Applies a gaussian filter to data.
% Returns dummy data for ALL the returned (and thus required) variab... |
321ab433c16ff8c5fcfb4dc5266305313798930e9a70b54a726080e044d7ad45 | MATLAB | 7,218 | 173 | % Wrapper script to turn parcellation files into FreeSurfer annotation
% files. Then you can calculate surface area of parcellations!
%
% Assumes ind_parcellation output from Kong2019 CBIG pipeline.
% Written by M. Peterson, Nielsen Brain and Behavior Lab
%To run:
% 1. Claim computing resources using salloc (ex: `sa... |
788ffdec25a9b0fd150315344c372c2e8b6b4d55ae7a03dd7722ae629591af7f | MATLAB | 7,219 | 143 | function h_spineAssignment3(handles2, flag)
global h_img3;
[currentInd2, handles2, currentStruct2, currentStructName2] = h_getCurrendInd3(handles2);% "2" is "Current"
structNames = fieldnames(h_img3);
for i = 1:length(structNames)
if ~strcmpi(structNames{i}, currentStructName2) && ~strcmpi(structNames{... |
86c28acff0617aa6cef4a90be289bb04b87050d3e5933d0535c45fa0f26427ca | MATLAB | 7,219 | 184 | function p = prepare_roidata_individual(param)
%
% This script was written for creating preprocessed MRI data for cowen &
% keltner movie clip presentation data.
%
% written by Tomoyasu Horikawa horikawa-t@atr.jp 2020/03/11
%
%
% Called from prepare_roidata.m
%
% Required functions:
% setdir.m, merge.m
%
% Required ... |
83b72419248eb3938a8c806e0085fee755f17d79c13f3b94d25c47a1a8aea269 | MATLAB | 7,226 | 268 | function hh = myErrorbar(varargin)
%MYERRORBAR Adds errorbars to existing plot (unlike errorbar.m, which creates a new plot, and allows only bars for y values)
% MYERRORBAR(X,Y,L,U) adds error bars to the graph of vector X vs. vector Y with
% error bars specified by the vectors L and U. L and U contain the
% ... |
fd702ab002222d8b7b753b7084afe88f1606f9224c10a82f515ab4bd5ac2a351 | MATLAB | 7,229 | 245 | function spm_run_bms_vis(varargin)
% Show results for Bayesian Model Selection Maps
% SPM job execution function
% takes a harvested job data structure (or no input) and calls SPM
% functions to show results from Bayesian Model Selection of
% Log. Evidence Maps
%
% Input:
% Varargin - can be harvested job data stru... |
e693e9aaa37086b9a11080f6a78dbe452b6d15d6a565be4fd1ec3b10d7b8d343 | MATLAB | 7,232 | 286 | function [postdata,ppobj] = RunPostProcessing_HeatmapData(hmdir,varargin)
ncores = feature('numcores');
if isdeployed,
fprintf('Starting RunPostProcessing_HeatmapData, ncores = %d...\n',ncores);
end
savefile = '';
trxfile = '';
nframes = [];
lblfile = '';
expname = '';
expdir = '';
nviews = 1;
npts = [];
d = 2;
sca... |
e7c303c6e26480fea4f659c38fff83cba88dccf7ddab68ef0c04710c35812d7c | MATLAB | 7,232 | 245 | addpath('../generic/');
addpath(genpath('../az_matlab_files/'));
%%
ndatasets = 8;
names = {'all','Tin','Tout','Min_C','Min_i','allButTin','allButTinOut'};
AUC = nan(ndatasets, length(names));
for idataset = 1:ndatasets
dt_ms = 25; % 100
% dt_ms = 50;
dataset = idataset;
dat = get_data(dt_ms,[]... |
cbeab5be9c69cba299159f0c1aa6092221e632e629878ee9b60bca25e3a65fc7 | MATLAB | 7,234 | 214 | function [R, Rm] = rotate_3D(V, mode, theta, u, angle_unit)
%% rotate_3D : function to compute the rotation of a vector or an array of vectors in 2D or 3D space.
%
% Author && support : nicolas.douillet (at) free.fr, 2017-2020.
%
%
% Syntax
% R = rotate_3D(V, mode, theta);
% R = rotate_3D(V, mode, theta, u);
%... |
67e3a61368638945fca22dd0376b54171e47fb4a054324aa6047414a22f5f1d1 | MATLAB | 7,238 | 183 | function [s, cfg] = ft_statfun_depsamplesFunivariate(cfg, dat, design)
% FT_STATFUN_DEPSAMPLESFUNIIVARIATE calculates the univariate repeated-mesures ANOVA
% on the biological data (the dependent variable), using the information on
% the independent variable (ivar) in design.
%
% Use this function by calling one of th... |
d077bde95fa5b17a5ac030cca7725a023e2f9c70a976421c143d19460d53a815 | MATLAB | 7,239 | 183 | function [s, cfg] = ft_statfun_depsamplesFunivariate(cfg, dat, design)
% FT_STATFUN_DEPSAMPLESFUNIIVARIATE calculates the univariate repeated-mesures ANOVA
% on the biological data (the dependent variable), using the information on
% the independent variable (ivar) in design.
%
% Use this function by calling one of th... |
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