sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
4abc8a417910722fdba2940224ac91056d2717f0b4dc9045eee26f6e1554b270 | MATLAB | 4,391 | 111 | function X = positive_definite_karcher_mean(A)
% Computes a Karcher mean of a collection of positive definite matrices.
%
% function X = positive_definite_karcher_mean(A)
%
% Input: A 3D matrix A of size nxnxm such that each slice A(:,:,k) is a
% positive definite matrix of size nxn.
%
% Output: A pos... |
e73a692b60b333d39ad8e56ba6b809a7f2bd1341e76ad05d1d19e2e820eed607 | MATLAB | 4,391 | 137 | function data = analyze_synapses_cultured(params,roi,synchannels)
%calculates CaMKii volume, signal, and # of objects outside of morphology
%and ABeta channels
folder = params.parentfolder;
%Extract parameters
xystep = params.xystep;
zstep = params.zstep;
nchannels = length(synchannels);
for im1 = 1:nchannels %neste... |
008386d4e100f4f87d74d45e2948c51266df591672e658cb89b8ad3baaa0823e | MATLAB | 4,393 | 133 | function [KendallWBrain, Header] = y_KendallW_Image(RaterImages, MaskData, AResultFilename)
% Calculate Kendall's W for sets of images. (e.g., different raters or Test Re-Test)
% FORMAT [KendallWBrain, Header] = y_KendallW_Image(RaterImages, MaskData, AResultFilename)
% Input:
% RaterImages - Cells of rate... |
6fe3317e67c2cc05f62d1069fee4fc0a4ed1aad5ef90a0cb970e2e76bc5ad87c | MATLAB | 4,393 | 128 | function mix = gmm(dim, ncentres, covar_type, ppca_dim)
%GMM Creates a Gaussian mixture model with specified architecture.
%
% Description
% MIX = GMM(DIM, NCENTRES, COVARTYPE) takes the dimension of the space
% DIM, the number of centres in the mixture model and the type of the
% mixture model, and returns a data str... |
02292c8d02a36928a5877c6d5d90c5126033c9ea85947b26ab21b26e41581966 | MATLAB | 4,396 | 139 | function M = symfixedrankYYfactory(n, k)
% Manifold of n-by-n symmetric positive semidefinite matrices of rank k.
%
% function M = symfixedrankYYfactory(n, k)
%
% A point X on the manifold is parameterized as YY^T where Y is a matrix of
% size nxk. As such, X is symmetric, positive semidefinite. We restrict to
%... |
0502eea70a7a43e1e378b982886f007d507cd1907a9693e02d8deefb996f365e | MATLAB | 4,396 | 124 | function x = VBA_spm_invFcdf(F,v,w)
% Inverse Cumulative Distribution (CDF) of F (Fisher-Snedecor) distribution
% FORMAT x = spm_invFpdf(F,df)
% FORMAT x = spm_invFpdf(F,v,w)
%
% F - CDF (lower tail p-value)
% df - Degrees of freedom, concatenated along last dimension
% Eg. Scalar (or column vector) v & w. Then d... |
49b4a65c4190e2545d066bd6af1aa578ae24d1f204ec035f5c18beca96d32e68 | MATLAB | 4,400 | 193 | function freq_plot_glan(GLAN,cfg)
%
% cfg.
% bl = [s1 s2] ; baseline in seconds
% nor = 'z' or 'a'; Normalizacion por z-score o absoluta
% comp=1Comparaci??n a graficar, anula par??metro cond.\\
% cond=1 Condici??n a graficar si no existe comp.\\
% hh=0;
%
%
% Pablo Billeke
% v.0.0.1
%
% 02.06.2010
% 27.04.2... |
c073fbf5061a602afde5332da84466963c22b2724322444ebc6275ff090cee2e | MATLAB | 4,400 | 118 | function colorcorrection_3D(roundnum)
loadParameters;
if params.DO_DOWNSAMPLE
FILEROOT_NAME = sprintf('%s-downsample',params.FILE_BASENAME);
else
FILEROOT_NAME = sprintf('%s',params.FILE_BASENAME);
end
DIRECTORY = params.deconvolutionImagesDir;
OUTPUTDIR = params.colorCorrectionImagesDir;
if exist(fullfi... |
a265edc3a34ca6f751ae82b3e2eedba506e243f8235eb68d588883f0ea5ce45e | MATLAB | 4,401 | 141 | %% Sparse linear regression with EM on synthetic data
% PMTKreallySlow
% PMTKneedsStatsToolbox boxplot
%%
% This file is from pmtk3.googlecode.com
requireStatsToolbox
setSeed(0);
D=200; % Number of coefficients to estimate
rho=.5; % Correlation
for i=1:D
for j=1:D
correl(i,j)=rho^(abs(i-j));
end
end
C ... |
78aa3c8a4bb3dd032becf9d678f9a9783bcf54a2f81868db93c22c3280104adf | MATLAB | 4,402 | 131 | function a = subsref(t,s)
%SUBSREF Subscripted reference for tensors.
%
% We can extract elements or subtensors from a tensor in the
% following ways.
%
% Case 1a: y = X(i1,i2,...,iN), where each in is an index, returns a
% scalar.
%
% Case 1b: Y = X(R1,R2,...,RN), where one or more Rn is a range and
% the ... |
48a904e286cc71dd0fa729817560998f6072945fc2d2ad7218ae44e962690388 | MATLAB | 4,403 | 95 | function J = convTri( I, r, s, nomex )
% Extremely fast 2D image convolution with a triangle filter.
%
% Convolves an image by a 2D triangle filter (the 1D triangle filter f is
% [1:r r+1 r:-1:1]/(r+1)^2, the 2D version is simply conv2(f,f')). The
% convolution can be performed in constant time per-pixel, independent o... |
4c37119b61ba532564e73ca653a93a1f00ed1c791933ae678b750e38997ffc5f | MATLAB | 4,404 | 167 | function [unmixing, mixing, rho, compdata, time] = bsscca(X, varargin)
% BSSCCA computes the unmixing matrix based on the canonical correlation between
% two sets of (possibly multivariate) signals, the sets may contain time shifted copies.
% In its default, it implements the algorithm described in [1], computing th... |
d9817f209da7018d687767c66c6d8998fd7627898c5b2fa319b71f64c2fe840c | MATLAB | 4,405 | 136 | function [pnt, tri, nrm] = read_stl(filename)
% READ_STL reads a triangulation from an ascii or binary *.stl file, which
% is a file format native to the stereolithography CAD software created by
% 3D Systems.
%
% Use as
% [pnt, tri, nrm] = read_stl(filename)
%
% The format is described at http://en.wikipedia.org/wi... |
1146f3aa4d005a4cac689530682f447620aa4dd3150ddfaefae6fe065da828f7 | MATLAB | 4,409 | 145 | %% plotSDO_risingFallingState
%Plot the coarse direction of transition of the off-diagonal components
% of the SDO. 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
% ... |
e1309ac7259936e83977c11788cf50472f1aede5e240eb75d32d4e2907447ddb | MATLAB | 4,409 | 175 | function [y2,ntrimmed,spikes, yy] = splinetrim(y,varargin)
% :Usage:
% ::
%
% function [y,ntrimmed,spikes, yfit] = splinetrim(y,[iqrmult],[knotrate],[X],['p'])
%
% Uses a robust measure of deviations in a timeseries gradient
% to find high-velocity 'spikes', presumed to be artifacts
%
% Uses spline interpolation to... |
9bd4319a30a22df047358eaaa4bef6d12d65a6960226c4925c407f263a1e8604 | MATLAB | 4,411 | 160 | function CBLH = cblabel(varargin)
%CBLABEL Adds a label to the colorbar.
%
% SYNTAX:
% cblabel(LABEL)
% cblabel(LABEL,..,TP,TV);
% cblabel(H,...)
% CBLH = cblabel(...);
%
% INPUT:
% LABEL - String (or cell of strings) specifying the colorbar label.
% TP,TV - Optional t... |
c1dc429199d6e96fa253e604952951ddb309f65df82044df9c8da598084f7e4a | MATLAB | 4,411 | 88 | function SOFAinfo(Obj)
% SOFAinfo(Obj) gathers information about the SOFA object and display it.
% Copyright (C) 2012-2013 Acoustics Research Institute - Austrian Academy of Sciences;
% Licensed under the EUPL, Version 1.1 or – as soon they will be approved by the European Commission - subsequent versions of the EUPL ... |
c24e02944673aba2420d2813375512e8c06c32d7d264ec0430f457675ef11314 | MATLAB | 4,413 | 155 | function [p_BMA] = VBA_BMA (p0, F0)
% // VBA toolbox //////////////////////////////////////////////////////////
%
% [p_BMA] = VBA_BMA (p0, F0)
% performs Bayesian Model Averaging (BMA)
%
% IN:
% - p0: a Kx1 array of VBA posterior structures, which are
% conditional onto specific generative models
% - F0: a Kx1 ... |
4c836d36aed28e8910909895b1d00dd757efa400a3a71bae3b07582353d86758 | MATLAB | 4,415 | 156 | function [EEG, com] = FlagTrialsToRemove(EEG, varargin)
% insert a flag into epochs that occur within trials marked as toRemove for
% artefact rejection purposes.
%
% Inputs:
% EEG: EEGLAB data structure, containing EEG.result.data.toRemove
% Flag : value of flag(s) for (0 to 16) to set as trigger.
% ... |
34c81b772bb5be490809f7768b0d4b24ee56235c414fed7b5851c8d11d130f9d | MATLAB | 4,416 | 122 | % Create a canlab_dataset object from a Matlab Table object
%
% The canlab_dataset object provides a standard data format, and allows the use of more methods,
% such as writing the data object to text for backup/export to other
% software, plotting, analysis tools, and more.
%
% Input ::
%
% StudyTable - n x... |
8fb6ae28f2df8df49de7752f101dde6d3b4e11b929ced1d8f9d4f0728e28d5fc | MATLAB | 4,416 | 86 | function [text, excluded] = processExamples(includeTags, excludeTags, pauseTime, doformat, subFolder)
% Examine all of the PMTK demos and return a cell array of formatted names
% corresponding to examples consistent with the specified include and
% exclude tags. The semantics of includeTags and excludeTags are as
% fol... |
15915389fd6a1327d28eb4b6850d9c6f25556744cc28b33492fcc9b4e3507f27 | MATLAB | 4,420 | 107 | %% create figure 11
% _________________________________________________________________________
%
% Robert Dahnke & Polona Kalc
% Structural Brain Mapping Group (https://neuro-jena.github.io)
% Departments of Neurology and Psychiatry
% Jena University Hospital
% ________________________________________________________... |
1efcd548a08ef08de1bdca2ecbb775428e19a98f708114a0513a2fa1b119d0b5 | MATLAB | 4,421 | 150 | % RSKEL_MV Multiply using recursive skeletonization.
%
% Typical complexity for [M,N] = SIZE(A) with M >= N without loss of
% generality: O(M + N) in 1D and O(M + N^(2*(1 - 1/D))) in D dimensions.
%
% Y = RSKEL_MV(F,X) produces the matrix Y by applying the compressed matrix F
% to the matrix X.
%
% Y = ... |
7dd90e59d6103a9edca220e727ab19a8d5510cfa46e933a7782a19885225ad51 | MATLAB | 4,421 | 137 | function [tau, mean_values_yandx,xvals_ofmeanfit,yvals_ofmeanfit,xvals_ofallfits,yvals_ofallfits,F_equation] = display_feature_decay_curve2(varx,vary,varc,fig,showplots)
%%
if nargin<5
showplots = 1;
end
if showplots
if ~isempty(fig)
figure(fig); set(gcf,'color','w')
else
figure... |
05dab2413d71be923081a9a58ef3ec410ac0b456f8cb24748a00f6cae8829518 | MATLAB | 4,422 | 129 | % Formal description of the EEG analysis. Used to get a first intuition on
% how useful the data is before adding the MRI connectivity component.
%% clear workspace
close all;
clear all;
clc;
%% load tf data
% Dt=spm_eeg_load('data/iEEG/tf_spm_ecog.mat');
Dt=spm_eeg_load('D:\ECoG_Atlas\iEEG\iEEG\tf_spm_ecog.mat');
... |
e5abd04ae5ddcdc2f7f68f4b81b24a9e745250ece624dfbebf3917acc25273d1 | MATLAB | 4,422 | 158 | function cmap = crameri(ColormapName,varargin)
% crameri returns perceptually-uniform scientific colormaps created
% by Fabio Crameri.
%
%% Syntax
%
% crameri
% cmap = crameri('ColormapName')
% cmap = crameri('-ColormapName')
% cmap = crameri(...,NLevels)
% cmap = crameri(...,'pivot',PivotValue)
% cramer... |
f1df092f75abc42292b3cf076c1f4f74e75745e37a2f2bce277822e54ae42495 | MATLAB | 4,422 | 111 | function [volume,volume_frac,min_vol,max_vol] = analyze_mExR_validation_feature_density(fov,params)
% Calculates the volume (and as a fraction of totla volume) in each channel
%Extract parameters
xystep = params.xystep;
zstep = params.zstep; % um/voxel in z
nchannels = params.nchannels;
parentfolder = params.parentfol... |
022ec7d6ff114ff6679d87df78df25a8dbd92e812108169e11a562505381aa16 | MATLAB | 4,423 | 104 | function c_View2SurfView(OriginalName,Surf,Surf_Mask,P_Max,P_Min,N_Max,N_Min,ColorMap,eventdata)
%This is a function which is used to display the result of DPABI_VIEW by DPABISurf_VIEW.
%FORMAT c_View2SurfView(OriginalName,Surf,Surf_Mask,P_Max,P_Min,N_Max,N_Min,ColorMap,eventdata)
%Input:
% OriginalName - The Name... |
bb60c3ea7cc9034a8a0730b52134d791d39fa5cb10c699d9a65655fda30240df | MATLAB | 4,423 | 123 | function [allVec,allTs,allTs_marker,allTs_trigger] = Closed_Loop_AR()
% Closed-loop algorithm using autoregressive forward prediction and hilbert
% transform to detect the peak.
% allVec: Raw EEG (channel*sample)
% allTs: Timestamp of each sample
% allTs_marker: Timestamp of event markers
% allTs_trigger: Timesta... |
0be5d5812e549258220af42004ddad6d60e81067f03a02b8ba38c6e37507bd74 | MATLAB | 4,428 | 123 | function h_dragRoi3
% global h_img2
handles = guihandles(gcf);
h_showRoi3(handles);
point1 = get(gca,'CurrentPoint'); % button down detected
point1 = point1(1,1:2); % extract x and y
roiobj = findobj(gcf,'Tag','ROI3');
annotationROIObj = findobj(gcf, 'tag', 'annotationROI3');
bgroiobj = f... |
bf14c4b30cbc5d40d455698e202ee7b37287ec366facc28dfcdeb384b2ba15c5 | MATLAB | 4,428 | 105 |
% Written by: Adam Wright
% Last modified: 20240823
% This is the main script to run the data-driven segmentation of the major
% cerebral arteries and the SSS.
% Make sure that all the functions in the package are all added to your
% matlab path. Including:
% freesurfer from: https://github.com/freesurfer/freesurfer... |
03ee57cf18a4b34ae49c72eea7053e5feaa2d6463c87c9415877c8062cc82225 | MATLAB | 4,429 | 136 | function V = VBA_spm_vol(P)
% Get header information for images
% FORMAT V = spm_vol(P)
% P - a char or cell array of filenames
% V - a structure array containing image volume information
% The elements of the structures are:
% V.fname - the filename of the image.
% V.dim - the x, y and z dimensions o... |
1b1462efe5b71c0d40ce5f2e9e5169f6af39377ba339e28bf6233b943137c67f | MATLAB | 4,429 | 144 | % Tot pyr
figure
[data] = extract_variables ('dff','dfftot',resultsPath, 'pyr');
for recCounter = 1:size(data,2)
data_mdn(recCounter) = median(data{recCounter});
end
data1 = data_mdn(contains(layer,'deep'));
data2 = data_mdn(contains(layer,'sup'));
subplot(341)
arrange_boxplot(data1,data2)
title('Whole recording py... |
275b86208e63fd16d98c308dd52c14723613e920bcc1351d03ca754aefd4f6bc | MATLAB | 4,429 | 164 | function [y,u,f_fname,g_fname,dim,options] = dcm2vba(DCM,stochastic,augment,confounds)
% maps DCM input structure to VBA inversion scheme input
% function [y,u,f_fname,g_fname,dim,options] = dcm2vba(DCM,stochastic,augment)
% IN:
% - DCM: DCM structure (see spm_dcm_specify.m)
% - stochastic: binary variables that fl... |
4f46ddc6bace8a08807be9c1a5c5a8ad3afaa5aca20498749aa2b23ea4003efa | MATLAB | 4,430 | 136 | clear
load('position_info.mat')
%
figure
set(gcf,'color','w');
set(gcf, 'Position', [230,430,200,400])
for line = 1:2
if line == 1
load('20240207f_00005_analysis.mat', 'Dnum', 'data_compressed','stimuli_start_time','total_trials','RF_weight','p_values','total_ROI')
load('data_20240207f_00... |
8a18dbe441326508d25fcff95baeecde6daba0d3e19b1c18a870c980c82dbd64 | MATLAB | 4,430 | 128 | %% bootstrap_tsdata_to_pwcgc
%
% Calculate sampling distribution for pairwise-conditional time-domain MVGCs
% from time series data, based on a nonparametric bootstrap
%
% <matlab:open('bootstrap_tsdata_to_pwcgc.m') code>
%
%% Syntax
%
% FB = bootstrap_tsdata_to_pwcgc(U,p,nsamps,acmaxlags,acdectol)
%
%% Arguments
... |
4e6787478fd0ecb2f04d63410c354df782fe86da92c953d0d2a559da265f508d | MATLAB | 4,431 | 96 | function res = run_nanocolumn_crosscor_refAlign(params,fov)
%update later with documentation
exp_factor = params.exp_factor; %expansion factor, adjust as needed
parentdir= params.parentdir;
targetdir = params.targetdir;
nChannels = params.nChannels;
rmax = params.rmax;
pixel_size=params.pixel_size;
prepost=params.pr... |
cbed7bda428796de19c42614bd848aff8ef0e57c31f170b79abf23e8cac218cd | MATLAB | 4,431 | 135 | function [pts_in_smallBin, bigbin_idx_in_smallBin, eps] = part_cluster_dbscan(...
pts_in_bigBin, distMat, eps_type, eps_arg, minpts)
% Function part_cluster_dbscan
% Partial clustering using dbscan
% Notation: Mapper does two binning steps. We give the name "bigBins" to
% the bins produced in the f... |
532f4edd16e733117910e38615afe415f97bd3154dce719e46f4d1705fd00ed3 | MATLAB | 4,432 | 115 | function [Error]=DPARSF_run(CfgBasic)
% Adpat the DPARSF basic struct to Advanced struct, and then call DPARSFA_run
% FORMAT [Error]=DPARSF_run(AutoDataProcessParameter)
% Input:
% AutoDataProcessParameter - the parameters for auto data processing
% Output:
% The processed data that you want.
%--------------... |
942c80349be4ba4aded0460e151bac9499b2169487a2f46b9bb3258f9ced2bc5 | MATLAB | 4,432 | 130 | load autoData;
setSeed(3);
% number of latent variables
Dz = 2;
% CONTINUOUS DATA FA
% initialize
fprintf('\n\n*****demoFAemt cts\n\n')
opt=struct('Dz', Dz);
[params0, data] = initFA(data, [], opt);
dataC = data; dataC.discrete = [];
params0.a = 1;
params0.b = 1;
% Learn theta with EM ... |
ac8224158701f949aa45d46f9cff32b47f9799a3d6443826a52e22f753fde59a | MATLAB | 4,432 | 96 | function [b,r,SSE,SSR, T, TF_ForContrast, Cohen_f2] = y_regress_ss(y,X,Contrast,TF_Flag)
% [b,r,SSE,SSR, T, TF_ForContrast, Cohen_f2] = y_regress_ss(y,X,Contrast,TF_Flag)
% Perform regression.
% Revised from MATLAB's regress in order to speed up the calculation.
% Input:
% y - Independent variable.
% X - Depe... |
c48a7b88f4372bdf4638b36ec5d64499f6c537ead8d7dd570a7415238324e8fd | MATLAB | 4,432 | 134 | function plot_attenuationeffect(subjects, nerve)
%% set paths
savepath_ga = getenv('GADIR');
%% load data
load([savepath_ga 'data4stats.mat'], 'wide')
%% set variables
stimType = 1; % sensory nerve stimulation
if nerve == 1
nerve_name = 'median';
title_names = {'EEG' 'cervical CCA' 'upper arm'};
target_... |
e011fff1d5f2cfd5cad825bd6812d5c70947d5d94dec2f933fbacc785f22ec2c | MATLAB | 4,433 | 165 | function varargout=shadedErrorBar(x,y,errBar,lineProps,transparent)
% function H=shadedErrorBar(x,y,errBar,lineProps,transparent)
%
% Purpose
% Makes a 2-d line plot with a pretty shaded error bar made
% using patch. Error bar color is chosen automatically.
%
% Inputs
% x - vector of x values [optional, can be left em... |
70463bfbfcdfc068dd373030d1ac66d22fbe22f8a2cf52debd540c221686ac83 | MATLAB | 4,434 | 120 | function I = tagReport(root, excludedAuthors)
%% Gather info on all of the tags in the specified repository
% I is a struct with the following fields:
% files............a list of all of the files with at least one tag
% tags.............tags{i} are the tags for files{i}
% tagtext..........tagtext{i}{j} is the re... |
0029ef93895a46a214acdccb49e281c5a38fb46b14f37b6bcdecafd84f7c0723 | MATLAB | 4,435 | 127 | function E(O,F,varargin)
% Reads contents of field F of Subject S, Session s, Trial t into variable
% O in the Matlab workspace (or in the workspace from which this function
% is called. This is a sort of hotkey function that saves having to type
% out full expressions like
% "D = Experiment.Subject(2).Session(3).TSdat... |
98c130548c67999c91d9c1cc96e8da285a8bbb453989fdb72c76fa2c2a34702a | MATLAB | 4,435 | 154 | function [T,Xinit] = tucker_sym(S,R,varargin)
%TUCKER_SYM Symmetric Tucker approximation.
%
% T = TUCKER_SYM(S,R) computes the best rank-(R,R,...,R) approximation of
% the symmetric tensor S, according to the specified dimension R. The
% result returned in T is a ttensor (with all factors equal), i.e.,
% T = G ... |
e10f0d893b0751075692136b04da12132eeebf7c05c59f51b95d057b1fdcb8d3 | MATLAB | 4,436 | 145 | %% rgb_colorGen
%
% A method used to generate a spectrum of RGB triplets, within range [0-1].
% Attempt to generate a color spectrum into N aesthetically pleasing
% elements for plotting
%
% INPUTS
% - N_COLORS;
% [integer] The number of colors to produce
% - method
% {'sin'/'default', 'linear', 'pola... |
584fd5a184763ea2346003dc5adec7689bcb6cc747ff110efb24eea9760247e4 | MATLAB | 4,437 | 133 | function [gamma2] = DTF(ts,low_freq,high_freq,p,fs)
% DTF - perform Directed Transfer Function analysis among multi-channel time series.
%
% Usage: gamma2 = DTF(ts,low_freq,high_freq,p,fs)
%
% Input: ts - the time series where each column is the temporal data from a
% single channel
% low_fr... |
6ba451d0b235bbfc4d7632da917953d3651a3ecf987ac4712f219c415372474b | MATLAB | 4,441 | 114 | function Stack_Writer(ExportArray)
FileDir=cd
FileName=SaveName
ExportArray=uint16(Reference_Data_3D_MeanProj_Reg);
imwrite(ExportArray(:,:,1),[CurrentSaveDir,SaveName,'Reg Ref Stack','.tif'])
for z=2:size(ExportArray,3)
imwrite(ExportArray(:,:,z),[CurrentSaveDir,SaveName,'Reg Ref Stack','.tif'],'WriteMode','ap... |
7a1e41427049de0e5158bc9040dcb67ad5a92b8ebc41b7bc0b13428bc7b41a3a | MATLAB | 4,441 | 120 | function jbm_dragROI3()
global jbm;
global h_img3;
[currentInd, handles, currentStruct, currentStructName] = h_getCurrendInd3;
currentObj = gco;
state = currentStruct.state;
% data = currentStruct.image.data;
% point1 = get(gca,'CurrentPoint'); % button down detected
% point1 = point1(1,1:2); ... |
4f491813894eb15a8010e7ce09826ab1313df7726ef90b98f3426589c9730528 | MATLAB | 4,444 | 142 | %% getPeriEventIndices
%
% Given event times, get the indices of elements around, and
% including, the event time, given the associated parameters.
%
% INPUTS
% - 'st' A [N_SHUFFLE, N_OBS] or {N_PP_CH,1} cell of [N_SHUFFLE, N_OBS] indices (integers)
% corresponding to event times
% NAME-VALUE Pairs
% - 'n_shift... |
72cd60ab1660c299661251b3fa1ebcd25281ae1e511d0c1f792ec3fc21e53d70 | MATLAB | 4,444 | 103 | function [text, excluded] = processExamples(includeTags, excludeTags, pauseTime, doformat, subFolder)
% Examine all of the PMTK demos and return a cell array of formatted names
% corresponding to examples consistent with the specified include and
% exclude tags. The semantics of includeTags and excludeTags are as
% fol... |
cfe9cc344e5e614586cec6c424568541ff282175c948fa26293e5d3fb3e731ce | MATLAB | 4,444 | 133 | function [AUC, cutoff] = rocPMTK(confidence, label)
% Compute ROC curve
% This is based on rocCardillo, by Giuseppe Cardillo
% confidence(i) is a real value
% label(i) is 0 or 1
% Created by Giuseppe Cardillo
% giuseppe.cardillo-edta@poste.it
%
% To cite this file, this would be an appropr... |
083904182b319dcd99d790f47f5fd528da2df8567694f1529f5d5b5a5939a043 | MATLAB | 4,445 | 157 | % MATLAB code provided by Seyed Mohammad Ali Rahmati
% Affiliation: Biomechanics and Motor Control Lab, Department of Biological Sciences, Georgia Institute of Technology, Atlanta, GA.
%
% Description:
% After running the optimization process (A_Optimization), the optimal
% muscle activations is created and saved in Ac... |
5af3e4fb512e95b1a4dfd90fd5622182391854078cea2d68932749707d277ba3 | MATLAB | 4,445 | 128 | % CALCULATE DISTANCE TRAVELED DURING AN ASSAY
% Jeff Stafford
%% initialize
% How long is the assay (in seconds)? If one of the csv files is shorter
% than this, defaults to the shorter time.
total_time = 90;
% Bin size for distance calculations (in seconds). Distance is calculated
% once per "bin size" by comparing... |
754b00ad43f8d22769a4c9c0c1465f0ad5910d74244a65b86ea4855adeec6381 | MATLAB | 4,445 | 101 | clear;clc;close
n_perm=10000; % Number of the permutation data
rdfile='Results_exp2.xlsx'; % File for reading data
rdsheet1='Each participant'; % Sheet for reading individual mTRs
t_range='E2:N2'; % Range for reading TSs
r_range={'E4:N19','E20:N35','E36:N51','E52:N67'}; % Range for reading individual mTRs {... |
7743b61501030eca29e01db467c5856901dab7555d1f530e3419d5e68a13d519 | MATLAB | 4,445 | 103 | function [EditedPeaks,Edits]=MaxArrayEdit(DeltaGFP, MaxImageArray, Edits, NewEdits)
%NewEdits=1; start from scratch
%NewEdits=0; only use previous edits and no involvement
%NewEdits=2; apply previous edits but allow further edits
if NewEdits==1
for i=1:size(DeltaGFP,3)
Edits(i).EditRegions=[];
Ed... |
c690ed8bfaedc72fd4d309fd0ca12e32dec50c6f268c028aefc63579557025a0 | MATLAB | 4,445 | 101 | clear;clc;close
n_perm=10000; % Number of the permutation data
rdfile='Results_exp1.xlsx'; % File for reading data
rdsheet1='Each participant'; % Sheet for reading individual mTRs
t_range='E2:N2'; % Range for reading TSs
r_range={'E4:N19','E20:N35','E36:N51','E52:N67'}; % Range for reading individual mTRs {... |
e52aef9e336941616757207ff132aa33520243980d31dc4e0d9a69bc2d6e0d15 | MATLAB | 4,445 | 112 | function [VolumeAfterRemoveCov,Header] = y_RegressOutCovariates_NonAggressive(InFile,CovariablesDef,AResultFilename,MaskFilename)
% FORMAT [VolumeAfterRemoveCov,Header] = y_RegressOutCovariates_NonAggressive(InFile,CovariablesDef,AResultFilename,MaskFilename)
% Non agressively regressed out the covariates from data
... |
d7fbf5f8370c6464fd53aa710280b29a03b37ae54aab3dcd503c0455d116079c | MATLAB | 4,449 | 139 | function [Aout,header,err] = h_OpenTif(filename, frame_numbers, varargin)
% [Aout,header] = h_OpenTif(filename, frame_numbers, varargin)
% Modified from genericOpenTif
% h_OPENTIF - Opens an Image file with TIF extension. It can retrieve
% only the frames specified by frame_numbers.
% h_OPENTIF opens a TIF fi... |
48fcdd9bacb0d0adb4548c8e70f31c078f292e1770b844026154a7eac475b477 | MATLAB | 4,451 | 111 | function varargout = DPABI_BrainImageNet(varargin)
% DPABI_BRAINIMAGENET MATLAB code for DPABI_BrainImageNet.fig
% DPABI_BRAINIMAGENET, by itself, creates a new DPABI_BRAINIMAGENET or raises the existing
% singleton*.
%
% H = DPABI_BRAINIMAGENET returns the handle to a new DPABI_BRAINIMAGENET or the hand... |
dedc205aef00823c0ccf6a50e4eb2c719638b6e27a3b87e7ea226d4f755cf0ac | MATLAB | 4,454 | 119 | function [stepsize, newx, newkey, lsstats] = ...
linesearch_decrease(problem, x, d, f0, ~, options, storedb, key)
% Backtracking line-search aiming merely for a decrease in cost value.
%
% function [stepsize, newx, newkey, lsstats] =
% linesearch_decrease(problem, x, d, f0, df0, options, storedb... |
3cfae2b183b228e9ae85aa001c50fc71509b6c99fe07922454836d538f29e390 | MATLAB | 4,455 | 132 | function [FailedID WaitingID SuccessID]=y_GetSegmentSubregionsFailedSubjects(Cfg,WorkingDir,SubjectListFile, SubjectID)
% FORMAT [FailedID WaitingID SuccessID]=y_ReRunfmriprepFailedSubjects(Cfg,WorkingDir,SubjectID)
% Cfg - the parameters for auto data processing.
% WorkingDir - Define the working directory to ... |
e61ef06eba7ad68db00ff325ca0619a044b5850fa8b9e9c8013b90b513c02b9f | MATLAB | 4,456 | 114 | function A = allcomb(varargin)
% ALLCOMB - All combinations
% B = ALLCOMB(A1,A2,A3,...,AN) returns all combinations of the elements
% in the arrays A1, A2, ..., and AN. B is P-by-N matrix is which P is the product
% of the number of elements of the N inputs. This functionality is also
% known as the ... |
76d1d7219a5ededecf04ea22a57c7c673087e5fce61249c540fcf20409400a28 | MATLAB | 4,458 | 123 | function [cmbindx, n, blocklabel] = blockindx2cmbindx(labelcmb, blockindx, block)
% This is a helper function that is needed for the bookkeeping of the data,
% when requesting (conditional)-blockwise granger causality estimates. Its
% single use is in ft_connectivityanalysis, but in order to keep that code
% clean, it... |
c722bbd671cf3a02404e2769e9ca8ef0368dee3980cf94cdfce6bb5d6d9fa76e | MATLAB | 4,458 | 137 | % written by J. Sohl-Dickstein
% based on "The natural gradient by analogy to signal whitening", arxiv
% 2012
function natgradDemo
make_vector_field_plots();
make_convergence_plots();
end
function make_vector_field_plots
[theta1, theta2] = meshgrid( -1:(1/4):1, -1:(1/4):1 );
sf = 3;
theta = [theta1(:)'; theta2(:... |
51539cb7ff88933ae49b242258cb46574aadc0dea83a6d517cd19ec1fa70ea8e | MATLAB | 4,459 | 147 | function [T, T2] = mk_grid_world(nrows, ncols, psucc_act, obstacle, terminal, absorb, wrap_around, noop)
% MK_GRID_WORLD Make the transition matrix for a grid world with stochastic actions.
% T = mk_grid_world(nrows, ncols, psucc_act, obstacle, terminal, absorb, wrap_around)
%
% An action succeeds with prob. p = psucc_... |
54a1d5173ee5f825b763904b151c7fa692d39ba6936bc05452bdbba75a9af702 | MATLAB | 4,459 | 204 | % Minimal tutorial script - Extracting burst events from FT data.
% See LICENSE.md for distribution information.
%
%
% Configuration.
%
% Paths.
addpath('lib-wl-synth', 'lib-wl-proc', 'lib-wl-ft', 'lib-wl-aux', ...
'lib-wl-plot');
%
% Data files.
inputfile = 'thilo-data/LFP_B_tmplate_01.mat';
outputfile = 'outp... |
54b440389c286f96d55cb40036324ab1bc8c161c0cb8930408214ad74ad888d4 | MATLAB | 4,460 | 87 | function h_selectCurrentAnnotationROI3(handles, currentObj, isDeletion)
[currentInd, handles, currentStruct, currentStructName] = h_getCurrendInd3(handles);
if ~exist('currentObj', 'var') || isempty(currentObj)
currentObj = findobj(handles.imageAxes, 'Tag', 'annotationROI3', 'Selected', 'on');
end
if ~ex... |
58fc1673e464674a6edc605080df5d2ff2b163f060cc0fe088cae927a0be0836 | MATLAB | 4,460 | 128 | function qvec = gen_source_point(mesh,source,varargin)
% GEN_SOURCE_POINT Calculates FEM sources vector for those active in mesh.link.
%
% [QVEC] = GEN_SOURCE_POINT(MESH, SOURCE) MESH is NIRFAST mesh
% structure. SOURCES is a cartesian coordinate (2D or 3D in mm) of a
% source or the source logical mask (M length,... |
827d8131d84b9fae98d73a6f5346c9fc5cfb4b384976d97f1f920b92b1d7b450 | MATLAB | 4,461 | 150 | function [tfr,rtfr,hat] = tfrrpmh(x,t,N,h,trace);
%TFRRPMH Reassigned pseudo Margenau-Hill time-frequency distribution.
% [TFR,RTFR,HAT] = TFRRPMH(X,T,N,H,TRACE)
% computes the pseudo Margenau-Hill distribution
% and its reassigned version.
%
% X : analysed signal,
% T : time instant(s) (default : 1:... |
bc5b95d2e79ad29c27c42f235572763b245bb00bf4e898fc57fcac00655a4d10 | MATLAB | 4,461 | 149 | function d = defaultDict(keys, values, default)
% A simple default dictionary (hashmap) similar to python's
%
% ** note, this is not an efficient data structure for large numbers of
% key-value pairs, (i.e. more than a few hundred!).
%
% Consider java.util.Hashmap, (which you can call from Matlab) or
% contai... |
1064860e66d89a94b9e5b3558bd40126aa7d3cd1b4061ac2deeb0de5c484d1bc | MATLAB | 4,462 | 195 | function pdf = paracyl(V, X)
% A more efficient implementation of the parabolic cylinder function
% Input: x --- Argument of Dv(x)
% v --- Order of Dv(x)
%
% see mpbdv for details
%
% PMTKmodified Matt Dunham
% Sped up by a factor of 11
%
% PDF is of size length(V)-by-length(X)
% This file is from pmtk3.go... |
fff73d17018e93b06fbdc573a1e2a6fcd65a476ba3a238bfb98c210ff66a5f0e | MATLAB | 4,462 | 64 |
function MarkerPlotter(StackSaveName,YLocation,YTextLocation,BinDimension,XMultiplier)
if exist([StackSaveName '_MarkerSet2.mat'])==2
disp('Plotting marker')
load([StackSaveName '_MarkerSet2.mat'],'MarkerSetInfo2')
if ~isfield(MarkerSetInfo2,'MarkerTextOn')
MarkerSetInfo2.MarkerTextOn=1;
e... |
328edf072e969c318b7d5b206a80c6f9f624de09971c32d1dcfdd3ec0244d0ca | MATLAB | 4,465 | 151 | function [fx,dfdx,dfdp] = f_HRF3(Xt,P,ut,in)
% Balloon (HRF) model evolution function in log-space
% function [fx,dfdx,dfdp] = f_HRF2(Xt,P,ut,in)
% This function evaluates the evolution function derived from the balloon
% model for the hemodynamic response function. It can be called in two
% ways: (i) as a "stand-alone... |
344e63b7e6be3ac38e1daba5d3480647a716cd203b6d92d3888f041092f84355 | MATLAB | 4,468 | 101 | function [regional_SFC, StatCorr_SFC_Parameters] = ...
fcn_calculate_StatCorr_SFC_multilevel_hl(struct_edgevec, func_edgevec, corr_type, min_sc_degree, results_dir, common_ids, parallel_workers)
% FCN_CALCULATE_STATCORR_SFC_MULTILEVEL_HL
% Regional-only SFC analysis using statistical correlation.
[nsub, nedge] = s... |
d1ea79b409577e950b497a4bfbf24eb0c772c16db441eb9c338820dca073dafe | MATLAB | 4,468 | 114 | function [data_clustered,data_not_clustered,area_threshold] = construct_clusters(data,area_threshold,min_number_of_localizations,type,waitbar_counter)
f = waitbar(0,['Please Wait...',num2str(waitbar_counter(1)),'/',num2str(waitbar_counter(2))]);
voronoi_areas = data.vor.voronoi_areas;
neighbors = data.vor.neighbors;... |
01ee4d0b22e7c57c12527b5c61af98632d6cc46e47813811c7fcde84aa0acfca | MATLAB | 4,469 | 115 | %% Function to generate white-centered color maps
% Author: Matteo Courhoud
% Website: https://matteocourthoud.github.io/
% Github: https://github.com/matteocourthoud
function centeredmap = centered(name, m)
% Generate colormap centered on zero
%
% Parameters
% ----------
% ... |
7145388dafb762153d965ae8ee7fb6d2c54cd01b9ef683eec520af97e3a11eaf | MATLAB | 4,469 | 113 | % This is a mesh processor script: it adds adaptive b-refinement to the
% model mesh based around the given target point (e.g., dipole position)
%
% Copyright SNM/WAW 2017-2024
%% Refinement parameters
method = 'manifold'; % default
TAUBIN = 'yes'; % Taubin low-pass filtering: yes... |
dbd9d87a2c2e9d1fdca31f71aa5f33a0519b77d457eb57a04d6ed335ca06d2f1 | MATLAB | 4,469 | 130 | function [ behavior ] = bz_ConcatenateBehavior( behaviorName, basePath, varargin)
%[ behavior ] = bz_ConcatenateBehavior( behaviorName, basePath)
%Concatenates buzcode behavior.mat files from subfolders, using the
%MergePoints from bz_ConcatenateDats. Automatically adjusts timestamps from
%each of the subfiles to refl... |
abe14409b9b24038f3e09013d2ef58dde3d0a9d13403114ef07500785c0da9f4 | MATLAB | 4,470 | 130 | %% mvgc_cdfi
%
% Sample MVGC thoretical asymptotic inverse cumulative distribution function
%
% <matlab:open('mvgc_cdfi.m') code>
%
%% Syntax
%
% x = mvgc_cdfi(P,X,p,m,N,nx,ny,nz,tstat)
%
%% Arguments
%
% See also <mvgchelp.html#4 Common variable names and data structures>.
%
% _input_
%
% P vector of ... |
fbe93287fea81079ac58ad8296218068cda5bf8564bfac0d5200651023ac7afb | MATLAB | 4,471 | 122 | function CBIG_ABCD_task_proc_compute_motion_outlier(id,output_dir,raw_path,manufacturer,FD_th,DV_th,discard_run,discard_seg,motion_filter)
% CBIG_ABCD_task_proc_compute_motion_outlier(id,output_dir,raw_path,manufacturer,FD_th,DV_th,discard_run,discard_seg)
%
% Inputs:
% - id:
% subject id
%
% - output_dir:
% ... |
85f27ec5e863b026ad012dcaf38d702441a1624f44a3715912a5ef973eb705fc | MATLAB | 4,475 | 154 | function EEG = DeletePracticeTrialTriggers(EEG)
% function EEG = DeletePracticeTrialTriggers(EEG)
% deletes the triggers for the practice trial(s) (if exist)
%
% Should be run after merging files, but before saccade triggers are
% inserted, and before DeleteTriggersForTrials()
%
if ~isfield(EEG, 'result')
EEG = In... |
b1a82cf7a67a6e3f8b39264640233181f331557216be560f6e03a917f6a1568f | MATLAB | 4,475 | 131 | function generatePmtkDataTable(dataSource)
%% Generate the PMTK data table from the meta files
% The html table is stored in the dataSource directory.
% dataSource is the location of the pmtkData local copy of the svn
% repository.
% PMTKneedsMatlab
%%
% This file is from pmtk3.googlecode.com
excludedDirs = tokenize... |
32f57bab855fcd7b074a85404b09faa1f08413484a7f40484b602e44418cbd70 | MATLAB | 4,477 | 155 | function [varargout] = VBA_spm_diff(varargin)
% matrix high-order numerical differentiation
% FORMAT [dfdx] = spm_diff(f,x,...,n)
% FORMAT [dfdx] = spm_diff(f,x,...,n,V)
% FORMAT [dfdx] = spm_diff(f,x,...,n,'q')
%
% f - [inline] function f(x{1},...)
% x - input argument[s]
% n - arguments to differentiat... |
afe3876c9bd7a5f5bea7f8919611233b23887eb0b7babd01b8017fcfecd5e05c | MATLAB | 4,477 | 138 | function test_bashLex()
% Tests that the function bashLex() correctly tokenizes bash-style strings.
% bashLex() should correctly parse strings that have been escaped for bash.
% Seed the RNG for reproducibility.
% Restore it afterwards. Can't hurt...
t = rng() ;
rng(42) ;
oc = onCleanup(@()(rng(t))) ;
... |
5c125c4ea6243605dd2fb956170d145651b5de5ac5e77fadab3ef793f88276e2 | MATLAB | 4,478 | 119 | function [mappedX, mapping] = fastmvu(X, no_dims, k, finetune, eig_impl)
%FAST_MVU Runs the Fast Maximum Variance Unfolding algorithm
%
% [mappedX, mapping] = fastmvu(X, no_dims, k, finetune)
%
% Computes a low dimensional embedding of data points using the Fast
% Maximum Variance Unfolding algorithm. The data is spe... |
be449931c4e6705ab93e72e99b6078f7d54acf5fd373f083960320d1cf3357f3 | MATLAB | 4,479 | 93 | function KL = kldiv(varValue,pVect1,pVect2,varargin)
%KLDIV Kullback-Leibler or Jensen-Shannon divergence between two distributions.
% KLDIV(X,P1,P2) returns the Kullback-Leibler divergence between two
% distributions specified over the M variable values in vector X. P1 is a
% length-M vector of probabilities re... |
c23b4adb78569b9f074696e83605bf2031d726b25727554711cd53c9cc22b1b4 | MATLAB | 4,479 | 127 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Align F data to motion initiation and termination
%Chad Heer
%INPUTS
%data = struct with Fc from axon analysis
%beh = struct with all behavioral variables
%nplanes = number of planes imaged
%frames = matrix with the frame numbers for each task
... |
521266a80ce8e95425f1880d6086b7a274b88505cffd5e306fa729ece7b476d9 | MATLAB | 4,481 | 132 | %% setMaxMin_
% Method for identifying the key minimum and maximum values across
% xtDataCell for assigning state values.
% Copyright (C) 2023 Trevor S. Smith
% Drexel University College of Medicine
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU Gener... |
581744c4f71c8bf8729287f29bcd721da1429dc1a5b34f41b3f270254d96b3f4 | MATLAB | 4,482 | 135 | function filterVisualize( f, show, arg )
% Used to visualize a 1D/2D/3D filter.
%
% For 1d filters:
% Marks local filter maxima with a green '+' and minima with a red '+'.
% Also shows the fft response of the filter.
%
% For 2d filters:
% Marks local filter maxima with a green '+' and minima with a red '+'.
% Also ... |
01c88643ccbef6598bbb782b417d073aa273bbe6b0b9a66c9d8ee5e06656fa69 | MATLAB | 4,483 | 130 | function partitionMask = partition(this, time, chartIndices, margin)
% For some set of charts generate masks to get the non-overlapping
% parts
%
% partitionMask = partition(time, chartIndices, margin)
%
% partitionMask: cell array of binary masks for each of the charts
% ... |
a85035a2e71f37fad65735e6bda73c2f2ff24e2b0efac434e4fe3b6fb6112deb | MATLAB | 4,483 | 98 | function [ moduleFcns ] = define_modulefcns( )
% Do not edit this file.
%
% Note: To add custom module functions, you should edit the file dataspaceExtensions_defineModuleFunctions().
%
% <a href="matlab:edit dataspaceExtensions_defineModuleFunctions">Edit dataspaceExtensions_defineModuleFuncti... |
27d2382f7dd6f25892889923a0f160e449ba251439a729441d48fcb3b7e86376 | MATLAB | 4,487 | 91 | function [totalNumFrames,targetedVariance,targetedRs,randomRs,FDcutoffs,gevDVcutoffs, totalNumFramesRemaining] = ...
mseParameterSweep(subjExtractedTimeSeries,useGSR,parameterSweepFileName,TR,continueBool, numOfSecToTrim, minSecDataNeeded,...
numRunsDataNeededPerSubject,minSecDataNeededPerSubject,minNum... |
491e10f8fd1021a9458b51edde52ee19d5b69621d3ad6869871ded6e26b1ea18 | MATLAB | 4,487 | 69 |
function MarkerPlotter(StackSaveName,YLocation,YTextLocation,BinDimension,XMultiplier)
if exist([StackSaveName '_MarkerSet.mat'])==2
%disp('Plotting marker')
load([StackSaveName '_MarkerSet.mat'],'MarkerSetInfo')
try
if ~isfield(MarkerSetInfo,'MarkerTextOn')
MarkerSetInfo.MarkerTextOn=1;
en... |
2756327bb82349951f0650b2d77bfc105aa44e8fb1599361b4c40aa1546ab1a7 | MATLAB | 4,488 | 116 | function peaks = AMPD_P(sig1,L,gr)
%% Automatic Multiscale Based Peak Detection
%% Inputs :
% sig : vector of data points or one dimensional signal to be analyzed
% L : Length for which we compute Scalogram. Note that you can leave it
% free and the algorithm autmatically would set it to half the length of
% the signal... |
9d70825ea8623ff8f009c2d0007216ce3634d0aff351d9b0c3a6ae1212a13d2a | MATLAB | 4,490 | 134 | function [res, preprop_deets] = run_preprocess(config, data)
% RUN_PREPROCESS runs a whole preprocessing configuration on an input data.
% The steps are applied in the order of the configuration.
%
% :param config: the preprocessing configuration details
% :type config: list of struct
%
% :param data: the data to prep... |
924ad2604500ab5704e84a0dc7391545dd6fcf8d1486f96e37b9dee5a40e26b9 | MATLAB | 4,493 | 137 | function [hdr, dat] = read_neurosim_evolution(filename, varargin)
% READ_NEUROSIM_EVOLUTION reads the "evolution" file that is written
% by Jan van der Eerden's NeuroSim software. When a directory is used
% as input, the default filename 'evolution' is read.
%
% Use as
% [hdr, dat] = read_neurosim_evolution(filename... |
9a06d42f1412f87c6d6ff70ef2b02e8e3d249099a384625e5be44b2b752923e6 | MATLAB | 4,493 | 129 | function [filteredTrialData]=HookedReaches(varargin)
%% HookedReaches: Find Center-out data with the largest hook at the
% beginning.
% Focus on first 500ms, before subject has time to compensate.
% Note: throughout each session's day, subject tends to compensate over
% time.
% Goal is to find some of these reaches to... |
7505c4fd335ce571c3734643ebec2a59e02b2cb05ee3e92fa67077a1f683032e | MATLAB | 4,495 | 106 | function [OutVolume OutHead] = y_Reslice(InputFile,OutputFile,NewVoxSize,hld, TargetSpace)
% FORMAT [OutVolume OutHead] = y_Reslice(InputFile,OutputFile,NewVoxSize,hld, TargetSpace)
% Input:
% InputFile - input filename
% OutputFile - output filename
% NewVoxSize - 1x3 matrix of new vox size.
% hld - inte... |
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