sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
24d9dc43c6b44b9aa080bc96e2b71ad3f757d9d1f206b3f134513f2233db4163 | MATLAB | 2,561 | 78 | function event = read_brainvision_vmrk(filename)
% READ_BRAINVISION_VMRK reads the markers and latencies
% it returns the stimulus/response code and latency in ms.
%
% Use as
% event = read_brainvision_vmrk(filename)
%
% See also READ_BRAINVISION_VHDR, READ_BRAINVISION_EEG
% Copyright (C) 2003, Michael Schulte
% Co... |
ad4d63690c3816f7ee6eb4aeda9466b35712d5da50d7c1b1ccac5225797e8cdf | MATLAB | 2,561 | 67 | function outputImage = shift(this, dr, worldOrVolumeSpace)
% geometric shift of MrImage
%
% Y = MrImage()
% outputImage = Y.shift(dr, worldOrVolumeSpace)
%
% This is a method of class MrImage.
%
% NOTE: This is a method of MrImage rather than MrImageGeometry, because
% the latter is composed on the fly from ... |
5d845537f4e040cac2cf8866b7ef6ca9aaf4d96be609d5384e97e4b20f6442ff | MATLAB | 2,562 | 112 | %% LOAD h5 File
Fs=400;
M=h5read('F:\U01Grant_Mark_20200418\Movie_Spike\MoCoDataCrop2Dfilt.h5', '/movie');
% crop around the 2 opposite-going neurons
ROI=double(M(74:96,181:206,:));
% each one to get the time trace
n1=ROI(13:19,8:14,:);
n2=ROI(5:12,14:19,:);
%% No Standardization
tic;
imdenW=zeros(size(M));
for i=1:s... |
64c7e68c33041bedbc0b50bd1899ca9503680aadcf7574abf67a2e8edb9f86c2 | MATLAB | 2,562 | 56 | function [appliedBasisSet, B] = fit_applynlinOspreyMultiplex(basisSet, x, spl_pos, fitRangePPM)
% 1. Extract parameters
nMets = basisSet.nMets;
nMM = basisSet.nMM;
nMultiplex = size(basisSet.fids, 3);
nBasisFcts = nMets + nMM; % number of basis functions
% 1. Extract parameters
zeroPhase = x(1); % z... |
be6025c29648d08ad8d3bdec6d951364200433ca55442e360108b76b7cdf9cd5 | MATLAB | 2,562 | 75 | function D = knn_calc_dist(X,Xnew,dist_type,pret_type)
% function for calculating distances between samples of X and Xnew
%
% dist_type: 'euclidean' Euclidean distance
% 'mahalanobis' Mahalanobis distance
% 'cityblock' City Block metric
% 'minkowski' Minkowski metric
% ... |
44eecd0342805e8defe6eca054dbb4201a49c74a8c14235b53366e734d9b53fa | MATLAB | 2,563 | 76 | function ft_write_tsv(filename, tsv)
% FT_WRITE_TSV writes a MATLAB table to a tab-separated-values file. Compared to the
% builtin MATLAB function, this implementation deals a bit different with missing
% values, booleans, and NaNs.
%
% Use as
% ft_write_tsv(filename, table)
%
% See also FT_READ_TSV, FT_READ_JSON, ... |
f677843c707b9d0f74277919e4d2c0f04c14b8fc4548073447200b84029d73ab | MATLAB | 2,563 | 81 | function C = figureConstants()
% FIGURECONSTANTS Define global constants for all figures
%
% Purpose:
% Centralizes all constants used across figures to maintain consistency
% and avoid magic numbers in the code.
%
% Outputs:
% C - Structure containing all constants organized by category
%
% Usage Example:
% C ... |
32c949cce5354cac4da8096b784c6284c2ff1b474cff47afd6f06d42ccf2791c | MATLAB | 2,564 | 74 | function band_signal = modwtmra_single_band(wpt, wavelet_type, target_band)
% MODWTMRA_SINGLE_BAND - Reconstruct a single band from MODWT coefficients
%
% Optimized function to reconstruct only ONE wavelet band instead of all bands.
% Eliminates the need to allocate the full (Bands × Samples × Channels) MRA array.
%
% ... |
22752eb40f1f5738aad122b2b5edce1bd946c2acaaf9e2aaf77dc5480ce688d8 | MATLAB | 2,565 | 75 | function result = compute2propXtest(N1, p1, N2, p2, alpha, print_result)
%compute2propXtest Compare two independent proportions using the
% N-1 Chi-squared test (Campbell 2007; Richardson 2011).
% Also computes CI for the difference in proportions (Altman et al. 2000).
%
% Usage:
% result = compareProportions(N1, p1,... |
6bad76ad8e1ca4685ea6c6d045358a65fd10a1385d4bd61b9f2344bde484bafa | MATLAB | 2,566 | 62 | function [fileNameArray, fileNameDeletedArray] = tapas_uniqc_delete_with_hdr(fileNameArray)
% Deletes given files; for .nii (nifti-) files, also deletes .mat-header,
% and _dimInfo.mat (if existing);
% for given .img (analyze) files, also deletes .hdr-header and _dimInfo.mat
%
% fileNameArray = tapas_uniqc_delete_wit... |
c12669e4f844ad3059f78d42717fd0d74d1b8b5c8910984fee9b22ded288a5d5 | MATLAB | 2,566 | 106 | % op_averaging.m
% Jamie Near, McGill University 2014.
%
% USAGE:
% out=op_averaging(in);
%
% DESCRIPTION:
% Combine the averages in a scan by adding the averages together and then
% dividing by the number of averages.
%
% INPUTS:
% in = input data in matlab structure format.
%
% OUTPUTS:
% out = Output following... |
319afb0f4c8d464b7740ddc217ed1def2e78976035efa44e4869dc1ed8e1e803 | MATLAB | 2,567 | 69 | function osp_onRightZ( ~, ~ ,gui)
%% osp_onRightX
% Callback function on process click on left x voxel direction button.
%
%
% USAGE:
% osp_onRightX( ~, ~ ,gui);
%
% INPUT: gui = gui class containing all handles and the MRSCont
%
% OUTPUT: Changes in gui parameters and MRSCont are written i... |
608d9ee75d5fe32fa452e96a7d2f6cba42bd7dcc1618bc34a18f310fc32e7bd2 | MATLAB | 2,567 | 75 | close all
clear all
tt1 = load('Z:\CLOOSE benchmark tests\testing_bci_bench_marktest\halfimage_uint8_external.mat');
tt2 = load('Z:\CLOOSE benchmark tests\testing_bci_bench_marktest\fullimage_uint8_external.mat');
tt3 = load('Z:\CLOOSE benchmark tests\testing_bci_bench_marktest\halfimage_uint16_external.mat');
tt4 = l... |
74d60f4bfc4c4aef056e99db0066134bde3b5c6874ff68329d83b2286dc1e848 | MATLAB | 2,567 | 69 | function osp_onRightY( ~, ~ ,gui)
%% osp_onRightX
% Callback function on process click on left y voxel direction button.
%
%
% USAGE:
% osp_onRightY( ~, ~ ,gui);
%
% INPUT: gui = gui class containing all handles and the MRSCont
%
% OUTPUT: Changes in gui parameters and MRSCont are written i... |
ae2c2c1b27ee7c7c6adaede2424409e92a678287a1c1dafe46017f865ec9bc3b | MATLAB | 2,567 | 69 | function osp_onRightX( ~, ~ ,gui)
%% osp_onRightX
% Callback function on process click on left x voxel direction button.
%
%
% USAGE:
% osp_onRightX( ~, ~ ,gui);
%
% INPUT: gui = gui class containing all handles and the MRSCont
%
% OUTPUT: Changes in gui parameters and MRSCont are written i... |
c6e0848e221856f500319c1c7b688475e06f8f7fd55bc3ed785d0641a6aa8984 | MATLAB | 2,567 | 94 | % extract features for the ICLabel Classifier
% if there are any issues, report them to lpionton@ucsd.edu
function features = ICL_feature_extractor(EEG, flag_autocorr)
%% check inputs
if ~exist('flag_autocorr', 'var') || isempty(flag_autocorr)
flag_autocorr = false;
end
ncomp = size(EEG.icawinv, 2);
% check for i... |
dab925756f73e51fa39d7e6a9e3df9cc5a7a2b7aebb7c3fc40bac076c9917269 | MATLAB | 2,567 | 47 | function [answer] = EnsemblesGUI_linker_SGC(ffo, pars)
disp(" - MAT SGC: Finding significant dFF coactivity")
[activity_raster, activity_raster_threshold, activity_raster_peaks] = findSignificantDF_FCoactivity(ffo', pars);
% From SGC_ASSEMBLY_DETECTION
disp(" - MAT SGC: Getting activity patterns")
... |
846c09babff8bcc969b7629a8aa90098c862984ad45b5c190d4e54062a5c8fd5 | MATLAB | 2,568 | 115 | function [v,f]=freesurfer_asc_load(varargin)
% Loads freesurfer ascii surface files
%
% [V,F]=FREESURFER_LOAD(FN)
% INPUT:
% FN Filename of ascii freesurfer to load
% OUTPUT
% V Nx3 coordinates for N nodes
% F Px3 indices for nodes for P faces (base1)
%
% If multiple filenames are given, say Q, then V... |
10a22aca282b12788473cbc18d1f485b5443129338e761a0b970112b10913292 | MATLAB | 2,569 | 68 | % PLUGIN_UIFILTER - support function for plugin_menu
% Copyright (C) 2019 Arnaud Delorme
%
% This file is part of EEGLAB, see http://www.eeglab.org
% for the documentation and details.
%
% Redistribution and use in source and binary forms, with or without
% modification, are permitted provided that the following condi... |
67babb1b36d10f31a5ec12355a5d8c61eb02b59182e1da48b593cc45d6418ed1 | MATLAB | 2,569 | 72 | function Latencydynamics =...
block_latencydynamics_macro_stages(twin, smoothfactor, prctile_cutoff,...
f_ratlist, RatBehaviorData)
%% average change in latency around block dynamics. cmc 11/03/21.
%inputs:
%twin = time window, or number of trials around each block transition (40 is good).
%smoothfactor is smoo... |
cbe18fca46ae4d31c113be80ac0011febab9ac9f78395723817c6bf7e435537f | MATLAB | 2,569 | 66 | clc;
clear all;
% this code calculate the distance dependence of MFC
% the geodesic distance betweeen vertices is measured on the mnid-thickness surface
subj = 'CC00056XX07'; % the demo subject
sess = '10700'; % the demo session of the subject
%%%% load geodesic distance matrix on the mid-thickness surafce
load('di... |
2450884368c1c4c93b450f2c5ac002324d41a6d87814a570041d8262a52a4c18 | MATLAB | 2,570 | 58 | % This script converts the tracked points from Universal Probe Finder into
% insertion trajectories which can be read in by the IBL alignment GUI.
% load atlas
sAtlasParams = PF_getAtlasIni();
cellAtlases = {sAtlasParams.name};
[intSelectAtlas, boolContinue] = listdlg('ListSize', [200, 100], 'Name', 'Atlas Selection',... |
4633cee92c719319741343365627f358c4688c2f98f6160e79c1a1484f10e198 | MATLAB | 2,570 | 83 | function [Y, I, J] = shake(X,dim)
% SHAKE - Randomize a matrix along a specific dimension
% Y = SHAKE(X) randomizes the order of the elements in each column of the
% 2D matrix. For N-D matrices it randomizes along the first non-singleton
% dimension.
%
% SHAKE(X,DIM) randomizes along the dimension DIM.
%... |
25dc51f01db513b24e386819dc69b6a03154645797de34979d3203cc3eb42304 | MATLAB | 2,571 | 132 | function showCase
% Example showing a variety of effects possible with notBoxPlot
%
% function NBP.showCase
%
%
% Purpose
% Showcase notBoxPlot
%
%
% No inputs or outputs
%
%
% Rob Campbell
W=which(['NBP.',mfilename]);
fprintf('Running example located at %s\n',W)
hFig=figure(1984);
set(hFig,...
'Name','notBo... |
e5656d5f089ed8f1557ec97d317efba2caa1561306d65c2fb810e4dc7e1441a7 | MATLAB | 2,571 | 81 | %% PREPARE GUIDELINES
% ensure SUBJECTS_DIR is correct in MATLAB environment
% load in what the fsaverage flat surface looks like
surfL = cvnreadsurface('fsaverage','lh','full.flat.patch.3d','orig');
surfR = cvnreadsurface('fsaverage','rh','full.flat.patch.3d','orig');
% map to individual subject's surface (LH)
subj... |
f8b7fb89a903e8c78f426ebe0f81bdb2a3a1918d6f93b9a7895c4fa54a0aa132 | MATLAB | 2,571 | 77 | function pred = knnpred(Xtest,X,class,K,dist_type,pret_type)
% prediction of new samples with calculated model
%
% pred = knnpred(Xtest,X,class,K,dist_type,pret_type)
%
% ------------ INPUT ---------------------------------------------------
% Xtest: dataset to be predicted [n_test x p] n objects, p variables
%... |
0927aefea721752e28f10a67e17c6e867128e0224138e5944789160582fdc5ca | MATLAB | 2,572 | 78 | function this = load_par(this, filename)
% Loads Par (Philips)-Header information referring to geometry into object
%
% Y = MrImageGeometry()
% Y.load_par(fileName)
%
% This is a method of class MrImageGeometry.
%
% NOTE: This is based on the header read-in from GyroTools ReadRecV3
%
% IN
%
% OUT
%
% EXAMPLE
% lo... |
165f38315d466a7f70adef9e60e210df593980476508fce1b32fbf2b80bbb1a2 | MATLAB | 2,572 | 76 | % load
file0 = sprintf('~/nsd/nsddata/information/b3pcnum_%s.tsv','func1pt8mm');
a1 = load(file0);
% compute
tempmd = [];
temppp = [];
for subjix=1:8
tempmd(subjix) = nanmean(a1(:,subjix));
temppp(:,subjix) = prctile(bootstrapdim(a1(:,subjix),1,@(x) nanmean(x,1),1000),[16 84]);
end
% visualize
figureprep([100 100... |
1dc5d593c3965109c963cb2120bc5250ffda9bb450ebbf3c0fceea9d33613a1e | MATLAB | 2,572 | 83 | function [Y, I, J] = shake3D(X,dim)
% SHAKE - Randomize a matrix along a specific dimension
% Y = SHAKE(X) randomizes the order of the elements in each column of the
% 2D matrix. For N-D matrices it randomizes along the first non-singleton
% dimension.
%
% SHAKE(X,DIM) randomizes along the dimension DIM.
... |
276ace3f0406a30cb900c1596444537b1f199e89f6f98debb15fd97ceb01eb65 | MATLAB | 2,572 | 90 | function addMECEtoSleepState(basename)
% remove short (<1sec) gaps automatically and longer gaps manually
% then added MECE field to the SleepState.mat
load([basename '.basicMetaData.mat'])
fprintf('%s start %s with data of %s\n',datestr(now),mfilename,basicMetaData.SessionName)
load([basicMetaData.Basename '.SleepSt... |
c3d301c894d87d4f83bb3fe27154264d7f803617af258895f70d9eda57c613c5 | MATLAB | 2,572 | 78 | %% ClassifyUnits
% Classify units into groups
%% Load All Unit Data
dataset = load('..\AllUnitData.mat');
Unit = dataset.output;
%% Extract zscores
zscoreMatrixHE = zeros(632, 80);
zscoreMatrixHW = zeros(632, 80);
zscoreMatrixHW_A = zeros(632, 80);
zscoreMatrixHW_E = zeros(632, 80);
for cell = 1 : 632
zscoreMatr... |
2a9e2a50a77a04e76cf8afc7f62fcd52c3e7590686fd392eba99065df60b3c39 | MATLAB | 2,573 | 69 | function [y,best] = BF_Whiten(y,preProc,beVocal,randomSeed)
% BF_Whiten Whiten a time series by comparing a range of preprocessings.
% ------------------------------------------------------------------------------
% Copyright (C) 2013-2026, Ben D. Fulcher <ben.d.fulcher@gmail.com>,
% <http://www.benfulcher.com>
%
... |
f34da80b5553e66fd046dd1159d5494b9ba91d454c9169960290bc14f2edae68 | MATLAB | 2,573 | 80 | function processEphysData(ephysPath, codePath, savePath)
% process firing rate resoponses for 20ul trials before and after the first
% incongruent trial
%INPUTS:
% ephysPath = local path to ephys folder downloaded from zenodo for the
% recording area you want to analyze
% codePath = local path to where code... |
99b353d2eeb6a4c19b47697088878d96e847eaba7762b46befb119b6b3919b90 | MATLAB | 2,574 | 71 | function this = coregister(this)
% Affine coregistraton of given images to a stationary image (geometry only)
%
% Y = MrSeries()
% Y.coregister(inputs)
%
% This is a method of class MrSeries.
%
% IN
% parameters.coregister ->
% .nameStationaryImage (e.g. 'mean')
% .nameTransfor... |
a7f52b095c7f4fe32f08718b837dc07aff48c75c8ebc3e68170011f3b7b61211 | MATLAB | 2,575 | 75 | % SUM - sum of memory mapped underlying array
%
% Author: Arnaud Delorme, SCCN, INC, UCSD, Nov. 2008
% Copyright (C) 2008 Arnaud Delorme, SCCN, INC, UCSD
%
% This file is part of EEGLAB, see http://www.eeglab.org
% for the documentation and details.
%
% Redistribution and use in source and binary forms, with or withou... |
e189ec7778b0b468093d0ac1fba557f6adcce1a5028b91f9b20fac6ff4bb4dc2 | MATLAB | 2,575 | 89 | % An interal function to parse input arguments for MEDI_L1
% Created by Tian Liu on 2011.03.16
% Modified by Tian Liu and Shuai Wang on 2011.03.15
% Last modified by Tian Liu on 2013.07.24
% Date last modified: 27 Feb 2020 (v0.8.0, KC)
function [N_std,iMag,lam,pad,delta_TE,CF,B0_dir,merit,smv,radius,data_weighti... |
0e5da082efa6b1bc05287f993952f5798a1eebb62a402236f5f632227d9a23ca | MATLAB | 2,577 | 68 | function Avg = CPi_data
%generates the CPi figure data
%% load Jonny DCS
load("Z:\histology\Jonny\Analysis\RUN25 heatmats\RUN25_slide1 heatmats\RUN25_1_3.mat")
R1 = Count.VTA;
load("Z:\histology\Jonny\Analysis\RUN26 heatmats\RUN26_slide1 heatmats\RUN26_1_2.mat")
R2 = Count.VTA;
load("Z:\histology\Jonny\Analysis\X01... |
3e068999e1970587d0d1ae01ca6fd1ea4771370d361c90a9dbadfff6fe39e081 | MATLAB | 2,578 | 99 | function [LatOpt, RPE, Kappa, Rewards] =...
GenerateLatencyData_VanillaAlpha_cg(params, ratTrial, opto_arg,...
gain_arg, fig)
%% Pull Parameters
alpha = params(1);
if gain_arg
rpe_gain = params(2);
end
%% Pull Data from Rat Trial
% Only use trials where we have data from the rat (basically covers all
% no... |
813c7bab2072257112590e4a8c5e6ad305f3c207769ed48993456df75bd11d6d | MATLAB | 2,578 | 97 | %% load MEG data (see NeuroImage 2004 paper)
load megdata
%% Estimation
% Reduce dimension from 122 ordinal signals to 20
% Resample 25 times using random initial conditions and bootstrapping
% (use FastICA parameters: kurtosis as non-linearity,
% symmetric estimation approach
sR=icassoEst('both', megdata, 25, 'la... |
f1e420f6a572052a7c4e82ed849897bff1031b7fb654ba688c7df242e56d57f1 | MATLAB | 2,578 | 74 | function egrad = getPartialEuclideanGradient(problem, x, I, storedb, key)
% Computes the Euclidean gradient of a subset of terms in cost function.
%
% function egrad = getPartialEuclideanGradient(problem, x, I)
% function egrad = getPartialEuclideanGradient(problem, x, I, storedb)
% function egrad = getPartialEuclidean... |
b30464b645c38ecacb65cc299e35a814c0f374cc3b891b7ae2d3111b2e694679 | MATLAB | 2,579 | 66 | % Script demo_image_geometry
% Exemplifies creation and usage of MrImageGeometry from nifti files,
% dimInfo and affineTrafo and par/re files
%
% demo_image_geometry
%
%
% See also MrImageGeometry
% Author: Saskia Bollmann & Lars Kasper
% Created: 2017-10-30
% Copyright (C) 2017 Institute for Biomedical Engineer... |
ee3981fbe5119e802c03ae26fe5c1f9ec11ed712c10258f0037a19999f3598f6 | MATLAB | 2,579 | 64 | % This script runs multiple stochastic simulations (pp) of the agent based model and will store either
% spatial or population level outputs.
% Please note that results are saved at each timestep
%% Simulation settings
save_spatial_data = 0; % Choose whether to save spatial outputs or population level results
s... |
aedbd77a46d1f629c1671d9996fa236549afef2d167939b69e0a605bd70a2c52 | MATLAB | 2,580 | 89 | %% fig: subtighplot - examplary figure
% useful for copy-pasting
% (c) Jiri, Jul23
%% examplary figure
% f = fig_make;
f = fig_make('fig_W',20, 'fig_H',20);
nRows = 6;
nCols = 6;
nPlot = 1;
marg_h = [0.10 0.05]; % margin from [bottom, top]
marg_w = [0.10 0.05]; % margin from [L, R] side
gap = [0.05, 0.01]; ... |
d350025c35154ae345abd97633dc13446a924b1f0cbe353d894ea356ac02ff44 | MATLAB | 2,580 | 89 | function [movie_dns,optiRank]=denoising1Movie(h5Path,varargin)
options.windowSize=1000;
options.spatialChunk=false;
options.dataset='mov';
options.ranks=100;
if nargin>=3
options = getOptions(options,varargin(1:end)); % CHECK IF NUMBER OF THE OPTION ARGUMENT OK!
end
meta=h5info(h5Path);
disp('h5 file detected')
... |
66ed937ba764774550e052054263df43fc0bac7b4f1bfc885bf6110ca8945b2e | MATLAB | 2,581 | 96 | a1 = load('/research/papers/2022 nsd/figures/INSPECTIONS/ROTATINGBRAIN/b3nc.mat');
allvals = [];
for p=1:8
a = cvnloadmgz(sprintf('~/Dropbox/nsddata/freesurfer/subj%02d/label/lh.prf-visualrois.mgz',p));
allvals(:,p,1) = nsd_mapdata(p,'lh.white','fsaverage',a(:),'nearest');
a = cvnloadmgz(sprintf('~/Dropbox/nsdd... |
9948883ba1c97684c18a2d806c716e27fe4a50426e23a9960a56015367f6b5a0 | MATLAB | 2,581 | 69 | function reducedIDs = TS_ReduceFeatureSet(whatData,distThreshold,useSpearman)
% Unsupervised clustering to a reduced feature set
%
%---Output:
% reducedIDs, A set of Operation IDs that forms the new reduced feature set
% ------------------------------------------------------------------------------
% Copyright (C) 201... |
ba9c7095541b60dfaee220cea3fb12b4ea0021d29dd5c5c819ea64e21b365841 | MATLAB | 2,582 | 127 | function tapas_sem_display_posterior_summary(results, summary)
%% Display the posterior summary.
%
% Input
% results -- Results structure
% summary -- Summary structure of the posterior.
% Output
%
% aponteeduardo@gmail.com
% copyright (C) 2019
%
CONG = 0;
INCONG = 1;
data = results.data;
% Off... |
941ec79d9d8a2ef29ceecf44bd0528b9028a8c9b7acfedd2d414699f9675407c | MATLAB | 2,583 | 97 | function run_conductance_model(data_folder)
% Compute conductance maps from tensors computed with DSIstudio
% This is a generic example.
% Adapt paths and file names to your own!
%
% Example: run_conductance_model(your_path)
%
% Author: Aina Frau-Pascual
%%% Load folders and code
% Add code folders to path
folder_ni... |
5900998988fe63f2d15137c733bae10c93d650eb0f93503cc809706934c603e4 | MATLAB | 2,584 | 107 | function [LatOpt, LatMdl, BlkInf, RPE, Belief, Kappa] =...
GenerateLatencyData_BayesModel(params, ratTrial,...
gen_arg, noise_arg, noise_params)
%%Similar to GenerateSynthData_Bayes, but with two new parameters: lambda
%%(prior weighting) and lapse rate. cmc 8/19/21.
%% Pull Parameters
H0 = 1/40;
kappa_mi = p... |
d545e051ed375c3b87e35588add18183faddc91a346b23b5b46555528f8963a3 | MATLAB | 2,585 | 75 | function [low2hi,ds]=surfing_maplow2hires(clow, chigh, epsilon)
% finds mapping between nodes from low and high res surfaces
%
% [L2H,D]=SURFING_MAPLOW2HIRES(CLOW,CHIGH[,EPSILON])
% INPUTS:
% CLOW: 3xNLOW coordinates for N nodes from low resolution surface
% CHIGH: 3xNHIGH " " hig... |
77858bd200fe93fc6362be6bc8ff8091125d7512fb117913d0330f57a7a084a9 | MATLAB | 2,586 | 85 | %% LOAD DATABASE
clear all
t1 = tic;
% load('/Users/tor/Documents/Tor_Documents/Presentations/2010/Columbia_fMRI_Prediction_Workshop_2010/NBC/full_data.mat', 'MC_Setup')
%
% volInfo = MC_Setup.volInfo;
% MC_Setup.cl = [];
% MC_Setup.unweighted_study_data = logical(MC_Setup.unweighted_study_data);
load('/Users/tor/Do... |
be5b9eebc1fd5b3ed1ed0b51a8a6b7e82bc66ab7af86a4d68163e2833aa94f33 | MATLAB | 2,586 | 77 | % fit_runFitMultiplex.m
% Georg Oeltzschner, Johns Hopkins University 2019.
%
% USAGE:
% [fitParams, resBasisSet] = fit_runFitMultiplex(dataToFit, basisSet, fitModel, fitOpts);
%
% DESCRIPTION:
% This function performs multiplexed spectral fitting of the datasets stored
% in the cell array dataToFit, using the basis s... |
084271e64d98fd01ad91989301c7d988bb540f14ecf74d42d08ffa031c58effc | MATLAB | 2,587 | 71 | function [datafit, f0Significant, FvalSig, aSig, fSig, sig]= ...
fitSignificantFrequencies(data, f0, lineNoise)
% Fits significant sine waves to specified peaks in continuous data
%
% Usage:
% [datafit, f0Significant] = fitSignificantFrequencies(data, f0, lineNoise)
%
% Parameters:
% ... |
1bcdd80802c1bae59a3c26a2559bc3db7f09d7099e87c0f6e52fabff24ebb138 | MATLAB | 2,588 | 71 | function [stats] = boxplot2_hmt(x, bp, left, isDep, names)
% Generates paired boxplot where significantly different pairs of boxes are
% labeled with an asterisk. Data points of box pairs can be dependent or
% independent samples, which is specified by isDep and defines the
% statistical test (permutation test with... |
c441bcd1a4824a4c32f3d8b4d49ec339a75e0674f344bc66e57deca1c7b6f18a | MATLAB | 2,588 | 65 | function [T1map, M0map, R1map]=T1M0estimateMP2RAGE(MP2RAGEnii,MP2RAGEINV2nii,MP2RAGE,varargin)
% usage
% [T1map, M0map, R1map]=T1M0estimateMP2RAGE(MP2RAGEnii,MP2RAGE,varargin)
% MP2RAGEnii is the nii structure resulting from loading the MP2RAGE
% UNI image
% with load_nii or load_untouch_nii
% MP2RAGEINV2nii is the nii... |
d28ca5f0c32d5e00398d70a61e6d5d11d49a7c3c0a6840920017b2e4819d6632 | MATLAB | 2,588 | 56 | function [p,h,stat] = test_global_measure(A,B,group1str,group2str,parameterName,freqs)
% where A and B the input data, which have the size Subjects x Frequencies
% perform nonparametric Mann-Whitney-Wilcoxon test and plot the figures
% based on work of Adham and Yiwen, see there papers. Adopted a bit to work
% with t... |
e0349ba282b902c2f3cd942ee5e663068173990a729fe81d65b9d1e3175ced0f | MATLAB | 2,588 | 65 | function out = osp_add_nii_mrs_field(in,OspreyVersion)
%% nii_hdr_ext = osp_add_nii_mrs_field(in,OspreyVersion)
% This function adds nii_mes field to input data matlab structure format
% following the standard described in "Clarke WT, Bell TK, Emir UE,
% Mikkelsen M, Oeltzschner G, Shamaei A, Soher BJ, Wilson M. ... |
f4bae2a80e4830ab2f3b7bd10e4dc3f0f9fbc71685e06e588f57c926324e1fc9 | MATLAB | 2,588 | 99 | function [traj, infStates] = tapas_hmm(r, p, varargin)
% Estimates a hidden Markov model (HMM)
%
% This function can be called in two ways:
%
% (1) hmm(r, p)
%
% where r is the structure generated by fitModel and p is the parameter vector in native space;
%
% (2) hmm(r, ptrans, 'trans')
%
% where r is the ... |
07527e3c162885a2cdc8064f212a26d220c6e0de90686461fb65ad2383be8686 | MATLAB | 2,589 | 59 | %% Calculate firing times, frequency and spiketrain from membrane potential
%
% Copyright 2025 Laura Schmid
% Permission is hereby granted, free of charge, to any person obtaining a
% copy of this software and associated documentation files (the
% “Software”), to deal in the Software without restriction, including
% ... |
0b3791956587b998b55ef82ad0ec7e4f15dcbd77eae154c34e9a3d0875dfac80 | MATLAB | 2,590 | 86 | function [fieldNames, fieldValues] = get_nonempty_fields(obj)
% Returns field names and values of all empty fields of MrCopyData-object
%
% Y = MrCopyData()
% Y.get_nonempty_fields(inputs)
%
% This is a method of class MrCopyData.
%
% IN
%
% OUT
%
% EXAMPLE
% Y.get_nonempty_fields
%
% See also MrCopyData
% Aut... |
c7ede6daf2d9af6856fda630dec28f1a2ca9cc3d77f8c8babbc414bb90fceca3 | MATLAB | 2,591 | 76 | function task_clean_e(sii, PATH, cfg)
% Add task description here
% - sii: vector of subject IDs to be processed
% - PATH: structure with all paths leading to diff processing steps
% generated in naj_neurCorGait_paths
% - cfg: structure with all processing variables generated in naj_neurCorGait_config
% di... |
68754ab1f29dba7d40367323ecec889038726931760c4454b64b8020448a415f | MATLAB | 2,592 | 71 | %% [RDF] = Wrapper_BFR_PDF(totalField,mask,matrixSize,voxelSize,algorParam, headerAndExtraData)
%
% Input
% --------------
% totalField : total field map (background + tissue fields), in Hz
% mask : signal mask
% matrixSize : size of the input image
% voxelSize : spatial resolution of each dimension ... |
44660420160afe56955103e3afd0a238503cfa5984db32ff55f7bf990e74ce92 | MATLAB | 2,593 | 77 | function outputImage = threshold(this, threshold, caseEqual)
% sets all voxel values < (=) threshold(1) to zero, and, optionally ceils
% all voxel values above threshold(2) to threshold(2);
%
% NOTE: Nans are set to zero, Infs are kept, if at/above threshold
%
% Y = MrImage()
% Y.threshold(threshold, caseEqual)
%
%... |
c98888a6b24050b7f70fbde254c2791c6fdca860d462d4ac33d258ce590b2014 | MATLAB | 2,593 | 90 | function test_sphere_distance
n = 5;
M = spherefactory(n);
% Pick a deterministic point&vector or a random pair.
% Advantage of deterministic: reduces errors due to M.exp()
x = M.rand();
u = M.randvec(x); % has unit norm
% x = [1 ; zeros(n-1, 1)];
% u = [0 ; 1 ; zeros(n-2, 1)];
% The three distances we compare
dist1... |
484d951bc862022bc5e3313060bc3bff251eb209c602f5e1599bc752a5a623ab | MATLAB | 2,594 | 63 | function [fixedVols, clrmap, inds_vol] = brainVolumes_fixed(params, struct_plotBrain)
% returns/loads pre-defined brain volumes (fixed, same for all channels) & colormap
% with indices for each brain volume specied in: struct_plotBrain.volumes2plot
% input:
% - params
% - struct_plotBrain = params.plot_brainSlice... |
58693bed35fefa7ca9b66922090dd582dee8d040537f6aab6ac36ed80a8a1eac | MATLAB | 2,594 | 104 | function [traj, infStates] = tapas_sutton_k1_binary(r, p, varargin)
% Calculates the trajectories of v under the Rescorla-Wagner learning model
%
% This function can be called in two ways:
%
% (1) tapas_sutton_k1_binary(r, p)
%
% where r is the structure generated by tapas_fitModel and p is the parameter vector... |
07c0cfc4b8954a25f79cbde1e9c100025685d77b26c7c7acac3ddc7950d2980f | MATLAB | 2,595 | 126 | %% chi = FANSI_4sepia(phase,magn,spatial_res,alpha,mu,noise,options,B0_dir)
%
% Description: Wrapper to use FANSI under Sepia
%
% Kwok-shing Chan @ DCCN
% k.chan@donders.ru.nl
% Date created: 1 April 2019
% Date last modified:
%
%
function chi = FANSI_4sepia(phase,magn,spatial_res,alpha,noise,options,B0_dir)
params =... |
773d096bd06c98cfa0becba6109378dcbef0de4eaf4597d98438d5a351c2e1e7 | MATLAB | 2,596 | 72 | function binMatrix = BF_ToBinaryClass(groupLabels,numClasses,makeLogical)
% BF_ToBinaryClass Converts a group vector to a binary class coded matrix
%
% Columns code observations, rows represent classes
%
%---INPUTS:
% groupLabels, a vector of integers (or categorical labels) coding the class of each observation
% numCl... |
4f023a1fe6e4ef729fa9971f4cec2fb095ecc14dd9b654acb7f1a5271ac46857 | MATLAB | 2,597 | 80 | %
% This function allows you to manually add or remove peaks that would not
% have been correctly detected
% Inputs
% ----------
% time_vec = time vector (in s and horizontal format)
% fs = sampling frequency (in Hz)
% time_series = signal time serie
% peak_time = previous detect... |
862e64f52ab1c30e67d67ca4f5da763440defbd3dedf92a4eaa8dff0008f7b42 | MATLAB | 2,597 | 87 | function fMRIStats_SummaryCSV(citiFile, varargin)
% fMRIStats_SummaryCSV(citiFile, varargin)
%
% Loads fMRIStats output from a single CIFTI dscalar file and writes
% summary CSV with cortex/subcortex regional averages.
%
% Arguments:
% citiFile - Path to CIFTI dscalar file
%
% Optional name-value arguments:
% 'Car... |
c4703fab2e1a577c73bf08f53ba8f9dacd674f3509537579910d4e87b4905164 | MATLAB | 2,597 | 79 | % create rectangular patches for displaying a meshed network
function [X,Y,patchind] = meshPatches(MSH,NT,radii,extend)
% convert a mesh of a network into coordinates for plotting
% patch rectangles along the edges
% patchind gives the order of mesh indices for the patches
% to get the right field values for the color... |
c98157876bf43bf7b54b0e4b8871673e57a0fd3453289de4f93d702ba912ad61 | MATLAB | 2,597 | 113 | function [posterior] = tapas_sem_example_single_subject_estimate(model, param)
%% Example for estimate for single subjects.
%
% Input
% model -- String. Either seria or prosa
% param -- String. Parametric distribution.
% Output
% posterior -- Structure. Contains the posterior estimates.
... |
4877baadf1fee093bfada2031a866c9c272f202ff8e2c78f165b7f8e4b8d2c9a | MATLAB | 2,598 | 71 | function [cell_metrics,basepath] = ExportCellExplorer(basepath,varargin)
% brainRegions = session.brainRegions;
[~,basename] = fileparts(basepath);
filename = fullfile(basepath,[basename '.cell_metrics.cellinfo.mat']);
if exist(filename,'file')
load(filename,'cell_metrics');
return
end
[~,animalName] = file... |
97875634c6a07742685e857d369120831750875437ea1d0e3e59a19bdb370629 | MATLAB | 2,598 | 66 | function outputFilename = debias(inputFilename, outputFilename)
%DEBIAS Debias nifti image using N4ITK.
%
% DESCRIPTION:
% debias debiases a nifti image using the N4ITKBiasFieldCorrection
% module that is packaged with 3D Slicer. The number of iterations is
% set to 50,40,30,20,10 to give an output image wi... |
f80d16de686f4374f442c92962d52da88549f98633c6fd0f2e7c3287f1deca32 | MATLAB | 2,598 | 75 | function [ D ] = hausDim( I )
% HAUSDIM Returns the Haussdorf fractal dimension of an object represented by
% a binary image.
%
% Returns the Haussdorf fractal dimension D of an object represented by the
% binary image I. Nonzero pixels belong to an object and 0 pixels
% constitute the background.
%
%... |
4379e458af4b9a93985d7b8db6f77211a04f154d0161ab493e761296822424ee | MATLAB | 2,599 | 85 | function [verbose, c_outliers_low, c_outliers_high, r_hist] = tapas_physio_plot_raw_physdata_diagnostics(cpulse, yResp, ...
thresh_cardiac, verbose, t, c)
% plots diagnostics for raw physiological time series as monitoried by the
% MR scanner breathing belt/ECG
% Author: Lars Kasper
%
% Copyright (C) 2013, Institu... |
a0bf50aa324245335ae5d1b270d8d33e11b64a1e24213b4dda56e5d3b5daf2e5 | MATLAB | 2,599 | 69 | function anorm = update_gbound(anorm,alpha,beta,j)
%UPDATE_GBOUND Update Gerscgorin estimate of 2-norm
% ANORM = UPDATE_GBOUND(ANORM,ALPHA,BETA,J) updates the Gersgorin bound
% for the tridiagonal in the Lanczos process after the J'th step.
% Applies Gerscgorins circles to T_K'*T_k instead of T_k itself
% since ... |
f064a8425692fa05956a351256ab063357b35c0129932b523e9678c9df8d8d41 | MATLAB | 2,600 | 89 | classdef ConvTranspose < dagnn.Layer
properties
size = [0 0 0 0]
hasBias = true
upsample = [1 1]
crop = [0 0 0 0]
numGroups = 1
opts = {'cuDNN'}
end
methods
function outputs = forward(obj, inputs, params)
if ~obj.hasBias, params{2} = [] ; end
outputs{1} = vl_nnconvt(...
... |
41f7373920b120ea52b40cce8b946e4c1f50fdcb0566900e832af582e15199ee | MATLAB | 2,602 | 64 | function [postLow, postHigh, postLow_q1, postHigh_q1, postLow_q1Con, ...
postHigh_q1Con] = quartileAnalysis_SS(data)
% split mixed blocks into quartiles to look at changes in wait time over
% the course of a block
% INPUTS:
% data = data struct containing behavior data containing wait_time,
% reward, etc field... |
764ef5463312747452c1cc7fab7019b44de32771c839b50a34c1415aeb75f803 | MATLAB | 2,603 | 56 | %{
preprocess.ClusteredEyePos (computed) # my newest table
# add primary key here
-> preprocess.EyeTrackingFrame
-----
center_x : smallint # center of the circle with the largest percentage of points,
# x dim, and this point is a member of that
# circle
ce... |
f4104e6d451df928ed8855af766cf77128206e4ece8340f5b7e10a74747ace36 | MATLAB | 2,603 | 89 | classdef ConvTranspose < dagnn_bc.Layer
properties
size = [0 0 0 0]
hasBias = true
upsample = [1 1]
crop = [0 0 0 0]
numGroups = 1
opts = {'cuDNN'}
end
methods
function outputs = forward(obj, inputs, params)
if ~obj.hasBias, params{2} = [] ; end
outputs{1} = vl_nnconvt(...... |
8a2139d60792b88a55a4854407ae4d87120c1549bbc31666f1776dc48f9499c1 | MATLAB | 2,604 | 93 | function run_all_modalities()
% RUN_ALL_MODALITIES
% Convenience driver to run the pipeline for multiple FC modalities.
%
% Adapt the lists below to your setup. For each modality, you can:
% - give it a label (used for subfolder under out/)
% - point to an edges CSV
% - optionally override which levels to run
% ... |
cb3fe7720f797889f8bc46a4afb5c83faae4a0aa5e802312e1d94d9cc48b49e4 | MATLAB | 2,604 | 95 | %% h = sepia_handle_panel_bkgRemoval(hParent,h,position)
%
% Input
% --------------
% hParent : parent handle of this panel
% hFig : handle of the GUI
% h : global structure contains all handles
% position : position of this panel
%
% Output
% --------------
% h : global stru... |
36b33e5de227e8e9789e61a61ade9fab3c30e5fb014f10dda99ac19162292375 | MATLAB | 2,606 | 77 | function ft_write_json(filename, json, varargin)
% FT_WRITE_JSON writes a MATLAB structure to a JSON file. Compared to the builtin
% MATLAB function, this implementation deals a bit different with missing values,
% booleans, and NaNs, and results in a more human-readable file.
%
% Use as
% ft_write_json(filename, st... |
80bfd37fcce4b91c9ea9c074d89b6510ccfa3c49164d7ab0a6a426df49f354ab | MATLAB | 2,606 | 88 | function GenTrialVectors
% Function outputs trial vectors (U, product of crossover).
global filename numFact numDose numComb sheetname vectorState countVectors
global mutCon crossCon
global XdoseRangeR UdoseRangeW VectorSet
% Generate a matrix R that contains r1, r2, r3 for the mutation of the
% target ... |
a0d3c8579bd31a18fb552a27972f88f2049ba2219f7123b9f09dff9729002b50 | MATLAB | 2,606 | 111 | function [posterior, summary] = tapas_sem_example_hier_estimate(model, param)
%% Example for inversion with a linear model for the prior.
%
% Input
% model -- String. Either seria or prosa
% param -- String. Parametric distribution.
% Output
% posterior -- Structure. Contains the poster... |
a10284e90305eb65d4ae283123e8988d070300c51e92557f8c1a25e4342cafdc | MATLAB | 2,606 | 60 | clear all %#ok<CLALL> % Clear all variables from the workspace
close all % Close all open figure windows
%% INSERT YOUR RECEIVER IPv4 ADDRESS HERE
IPv4 = '127.0.0.1';
%% RUN THE REST
% Define Image Dimensions and Preallocate Storage
xpixels = 512; % Image height (number of rows)
ypixels = 796; ... |
eafdf996bef6737fb79b01fe0b5ede7c6a7ebaa46a93bdbe2d295732fe0961a7 | MATLAB | 2,606 | 63 | function [bestParam,bestParamScore,bestParamIdx] = randomSearch(objFun,...
data,paramGrid,varargin)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% randomSearch performs pure random search over parameters provided.
% Each parameter or combination of parameters are selected from a unifo... |
d49e03acd6a607c5d31442069cf726d9aa411a3032de5b40674a7f6a505623e2 | MATLAB | 2,607 | 78 | function [this, matlabbatch] = get_matlabbatch(this, module, varargin)
%ONE_LINE_DESCRIPTION
%
% Y = MrGlm()
% Y.get_matlabbatch(inputs)
%
% This is a method of class MrGlm.
%
% IN
% module 'specify_1st_level'
% varargin limited set of options to be determined for each module
%
% OUT
% matlabbatch spm... |
8070cb554e0fca8e0200de530403631b7f42064f7a088c572cc9dbef2e08f445 | MATLAB | 2,608 | 50 | function handles = renderEpochSpectogram(hObject, handles)
%Plot current spectogram window
handles.data.lastWindowPosition = handles.data.windowposition;
windowsize = round(handles.data.audiodata.SampleRate * handles.data.settings.spect.windowsize);
noverlap = round(handles.data.audiodata.SampleRate * handles.data.se... |
aeb21f544963a96d370b2ef368ddfc458ae29e166133216f95a21950f799dbd0 | MATLAB | 2,608 | 62 | function ord = BF_LinkageOrdering(distMat,links)
% BF_LinkageOrdering attempts to use optimalleaforder for dendrogram orderings
% ------------------------------------------------------------------------------
% Copyright (C) 2013-2026, Ben D. Fulcher <ben.d.fulcher@gmail.com>,
% <http://www.benfulcher.com>
%
% If you ... |
0c180ac1afbdce8d44f11e8348d3ff6cd0632bbdc80c993a89d8a982a46393da | MATLAB | 2,611 | 80 | function [ output_args ] = SGC_ASSEMBLY_DETECTION( ACTIVITY_RASTER_file )
%SGC_ASSEMBLY_DETECTION( ACTIVITY_RASTER_file )
%
%
% === Jan Moelter, The University of Queensland, 2018 ===================
%
narginchk(1,1);
fprintf( 1 , [ '\n' ] );
timerVal = tic;
%% > PRINT FUNCTION-CALL
if( isdeployed )
printCons... |
9ebdf72d3d221fba1b5b1119e62a64a1c0b7a6ca5895808bf0eb21c4bd16b02f | MATLAB | 2,611 | 57 | function ProcessData_ExtendedData7(datadir, savedir, codedir)
%ProcessData_ExtendedData7 - Process raw data saved under datadir such that it can be plotted by PlotExtendedData7.
% INPUTS:
% datadir - Local directory where 'Golden_Nature/RawData_ExtendedData7.mat' from Zenodo was saved
% codedir - Local directory wh... |
0da8e8b28c251b660e5d34525fdcd55d8a898e271dd3ff83f3efcc1aec644127 | MATLAB | 2,612 | 76 | % orchestrator_run_minimal.m
% Minimal pipeline orchestrator: set grid, export to base, verify steps, run.
% Edit the grid below as needed.
%% 0) grid / seeds (edit here)
seedList = 1:30;
Nvals = [10 20 30];
sparsityList = 0.05:0.05:0.50;
snr_vals = [0 5 10];
Tval = 12000;
% expose to base work... |
231f21c22877d31e09ad583ad624f3981bc1861ff15a77ca072506c12b00d473 | MATLAB | 2,612 | 103 | function [amplitude,tau,drift,noise]=estimateSpikeParam(trace,fs)
%%
options.minPeakProm=0.01;
options.maxPeakWidth=20; % in ms
options.minPeakHeight=0.01;
options.spikeDelay=25; % in ms
options.savePath=[];
options.plotFigure=false;
%%
trace=double(trace);
trace=trace-mean(trace);
% estimate drift parameter
temp... |
0f522ec023c31763824555717d49aa267ac422d18f5e80719d093fc45b1aa7a1 | MATLAB | 2,613 | 83 | function fear_frzTrigCoact_opt_meanShift(basename,varargin)
load([basename '.basicMetaData.mat'])
fprintf('%s start %s with data of %s\n',datestr(now),mfilename,basicMetaData.SessionName)
param.binSize=0.02;
param.halfWindow=5;
param.targetHC=3;
param.targetSes=2;
param.varName='frzTrigCoactChamber';
param.saveFile=[... |
01f02d69350409ef2b008833456d4007de4fbbb388180779079ad6d63f95eb75 | MATLAB | 2,614 | 73 | function [varargout] = likUni(hyp, y, mu, s2, inf, i)
% likUni - Uniform likelihood function for classification. The expression for
% the likelihood is
% likUni(t) = 1/2.
%
% There are no hyperparameters:
%
% hyp = [ ]
%
% Several modes are provided, for computing likelihoods, derivatives and moments
% respectivel... |
90fe49b1b1ac7b4857b2187d59bdd6793160cd49c7717573b8db46b00ea425ea | MATLAB | 2,614 | 84 | %% Kmeans clustering
clear all;
clc;
random_concept = false;
addpath(genpath('lib'));
load("lib\vik.mat");
for i=1:30
if i == 1
load("lib\Yumodel_RDM_eval_TransE_21to30.mat");
elseif i == 11
load("lib\Yumodel_RDM_eval_TransE_31to40.mat");
elseif i == 21
load("l... |
9333890d8e781eea2b38d52ce76e5bab91069925473aaefae3dece45a4eaf748 | MATLAB | 2,615 | 78 | function varargout = preprocDownsample(S, params)
% Usage: [Spp, params] = preprocDownsample(S, params)
%
% Downsamples stimuli to (fMRI or other) sampling rate; e.g., takes frames
% of a movie presented at 15 Hz and downsamples them to an fMRI sampling
% rate (TR) of .5 Hz (2 seconds / measurement).
%
% Inputs:
% ... |
eaf7b1a69451f310eaa942a37e3f613076c83000fd7386663c844efa2d68786b | MATLAB | 2,615 | 95 | %CONVERTUNITS Convert energy, frequency and wavelength units
%
% Description
%
% Using fundamental physical constants, there is a unique way of
% converting an energy into different units. For example, we often want
% to know the energy, wavelength or frequency of a photon. This function converts between th... |
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