sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
55dad33c7664bad28d6c29b79ccf4791444804e9aad25d8c91124a55e9ed3a21 | MATLAB | 4,625 | 145 | function [BCMatrix, BCRHS] = boundaryConditionRadial2D(BC)
% It creates the matrix of coefficient based on the BC structureprovided
% by the user. It also generates the right hand side vector of the linear
% system of equations
%
% SYNOPSIS:
% [BCMatrix, BCRHS] = boundaryConditionRadial2D(BC)
%
% PARAMETERS:
%
%
% RE... |
8f2ae875a06d5219b258c8376797f16ca9ac5f6145acf88832f0f373fee21a8e | MATLAB | 4,627 | 125 | function [select] = parameterselection(param, data)
% PARAMETERSELECTION selects the parameters that are present as a volume in the data
% add that have a dimension that is compatible with the specified dimensions of the
% volume, i.e. either as a vector or as a 3D volume.
%
% Use as
% [select] = parameterselection(... |
ab76846abc0770b16face3c456eec9f623f5c6ddb55e43927a68e12eb651f3e2 | MATLAB | 4,628 | 147 | function out = IN_AutoMutualInfo(y, timeDelay, estMethod, extraParam)
% IN_AutoMutualInfo Time-series automutual information
%
% ---INPUTS:
%
% y: input time series (column vector)
%
% timeDelay: time lag for automutual information calculation
%
% estMethod: the estimation method used to compute the mutual informat... |
3b7155212402e12584f64ddd969821f43751b01ad5f38121c25a8c602bfd0064 | MATLAB | 4,629 | 101 | function task_footprint_GA(sii, PATH, cfg, fieldNames)
% 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_neurCorGa... |
8b8c435f2163b4fd4ac312aea1b6f387e6c86e32817e7dd4569893af5718f035 | MATLAB | 4,629 | 149 | % Example function to demonstrate surface-based voxel selection.
%
% This function uses two surfaces (pial and white matter, from Freesurfer)
% to define circular regions of approximately 50 voxels using a geodesic
% distance measure.
%
% This function is aimed at the ''fingerdata' dataset
%
% NNO Feb 2011
%%%%%%%%%%... |
6181ca94623e7a87955dfcd012c19c6d4315bacfd4e6489fab794d94aec224cf | MATLAB | 4,632 | 109 | function [event_times,calcium_duration,onset_delay] = align_behav_to_calcium(paq_path,event_table,event_times,tag_duration,varargin)
event_fds = {}; data_type = []; pad_name = ''; Fs = 1; sub_session_length = Inf;
for v = 1:numel(varargin)
if strcmpi(varargin{v},'event_fds')
event_fds = varargin{v+1};
... |
e64efc35e98094050b28ece9bb50fe665739a2c81d26ac67d14b0cd75703f7a0 | MATLAB | 4,634 | 145 | % Bang et al (2020) Private-public mappings in human prefrontal cortex
%
% Reproduces Figure 4-figure supplement 2
%
% "Private confidence" is computed by training multinomial regression on
% data from prescan session and then applying weights to data from fMRI
% session while setting context weights to zero
%
% Visual... |
58f8bf5c4d309af1972953d265d28841ec5c880e755d9810a59f98279dde379b | MATLAB | 4,635 | 130 | function data = loadData_mat(dwifile,gradfile_dummy);
data = [];
if not(exist('dwifile')),
[files path] = uigetfile({'*_HARDI.mat', 'All accepted filetypes';'*.*','All files'},'Select HARDI data to open');
if files==0,
return;
end;
dwi... |
eacd6f887e8b4bb80b50774e443d8609a8e1233d3955a54b729ddf25840d99ea | MATLAB | 4,635 | 134 | %function ch2roi_selFreq(params, groupInfo)
% groups channels into defined ROIs (anatomic areas), averages & plots
% based on the following criteria:
% - selected anatomical areas (groups)
% - selected freq. band
% - significance (difference of conditions, from baseline (TO DO), or all)
% settings (subjects, dire... |
1ca17ca7b2db348d26bfb39f4d10bc2fb7114b90e7958eac70e7a8374258fa3a | MATLAB | 4,636 | 92 | function [S,f,varS,C,Serr]=mtspectrumsegc(data,win,params,segave)
% Multi-taper segmented spectrum for a univariate continuous process
%
% Usage:
%
% [S,f,varS,C,Serr]=mtspectrumsegc(data,win,params,segave)
% Input:
% Note units have to be consistent. See chronux.m for more information.
% data (single channel) -... |
3cce70a8eb7fa0fc06c9d89b6b7b76b5f4c9962fe8c5d085b48a9c11fab02b99 | MATLAB | 4,638 | 108 | function [varargout] = likWeibull(link, hyp, y, mu, s2, inf, i)
% likWeibull - Weibull likelihood function for strictly positive data y. The
% expression for the likelihood is
% likWeibull(f) = g1*ka/mu * (g1*y/mu)^(ka-1) * exp(-(g1*y/mu)^ka) with
% gj = gamma(1+j/ka), mean=mu and variance=mu^2*(g2/g1^2-1) where mu... |
9842e3c9e135f3f04b3ffb3782cd29fc07187c46de953588bb2dcf57b9cef2e8 | MATLAB | 4,639 | 151 | %% %%%%%%%%%%%%% Create views in ITK-SNAP
% subj01.
% anterior, right, inferior is the corner that matches 1mm and 1.8mm
%
% from center of first voxel (1,1,1) in 1mm, we achieve correspondence every +9 1mm slices or +5 1.8mm slices.
(.,24,.)
186 - 162 = 24
162 is 9*18.
104 - 162/1.8 = 14
(.,.,73) for 1mm is good
1... |
2468c5ec2664d4e21ce2b24011d68d4d37ec61e1e835d19a16690b77b7846450 | MATLAB | 4,640 | 115 | disp('See http://www.gaussianprocess.org/gpml/code/matlab/doc/ for details.')
disp('Wait 10s, then continue...'); pause(10)
disp(' '); disp('clear all, close all')
clear all, close all
write_fig = 0;
disp(' ')
disp('n1 = 80; n2 = 40; % number of data points from each class')
n1 = 80; n2 = 40;
disp('... |
27aa88375f044e3d7462b3624760f1fa7e59e0bb7a7c004538aab8b142509604 | MATLAB | 4,641 | 108 | clc;clear;close all;
%%
DataManager = FileManager;
dataset_name = 'Lightfield';
stack = 'Zhang2020';
segmentation_version = 'auto';
raw_data_folder = DataManager.fp_raw_data_folder(dataset_name, stack);
mask_folder = DataManager.fp_mask_folder(dataset_name, stack, segmentation_version);
graph_folder = fullfile(DataMana... |
71bcbb2dd2e9be9dc33f89245a3dea29947e5311bcaa8d3b06e74d7b184a53f3 | MATLAB | 4,641 | 139 | function plotNetMetNodeCartography(combinedData, ExpName, Params,HomeDir, figFolder, oneFigureHandle)
% Plots network node cartography of individual recordings
% Parameters
% ----------
% combinedData : struct
% structure with fields of the different groups (eg. genotypes:
% combinedData.WT, combinedData.KO, ..... |
ddef6ddb22ac3b550d2cbde6b15ee14896a783d79068204c7f1efe0d1cfcda20 | MATLAB | 4,643 | 119 | function [cfg] = expDesign(cfg)
%
% This function and its companions creates the sequence of blocks (static/motion)
% and the events (the single directions) for MT+ and MT/MST localizers.
%
% The conditions are consecutive static and motion blocks (fixed in this order gives
% better results than... |
0a26258929eca79713c0c798f8f5c69cde7ec015f222b30afb6f04bfc6d31c04 | MATLAB | 4,645 | 160 | %% %%%%% DERIVE CANONICAL PCS
%% %%%%% [avg across stimuli, select good R2, aggregate across subjects,
%% %%%%% unitlength normalize, cross-validate to decide 3, derive 3 from all data]
% setup
nsdsetup;
% load the GLM SIMPLE results for all 8 subjects
clear a1 a2;
for p=1:size(sessmatrix,1)
ppdir = ppdirs{sessma... |
15247be125805e139b6155c7c549f3df0892e21cc172c3f8d75c734165aea888 | MATLAB | 4,647 | 123 | function out = CO_CompareMinAMI(y, binMethod, numBins)
% CO_CompareMinAMI Variability in first minimum of automutual information
%
% Finds the first minimum of the automutual information by various different
% estimation methods, and sees how this varies over different coarse-grainings
% of the time series.
%
% The fu... |
cc5e2603674dfaa6bfc994c05d6d276da401ca75e24ce585faadc0caffb6c856 | MATLAB | 4,650 | 147 | function out = FANSI_4sepia_v3( phase, magn, alpha, options )
% FANSI wildcard function. This may be used to call the included functions
% globally, for a simplified use.
%
% Parameters:
% phase: local field map data
% magn: magnitude data
% alpha: gradient L1 penalty, regularization weight
% options (structure with o... |
a8963292e4051190ff8d11cda280db8c771879606c83f07f4dbacbf2fd46ef96 | MATLAB | 4,651 | 114 | % Script demo_realign
% Shows realignment for n-dimensional data with different scenarios of 4D
% subsets feeding into estimation, and parameters applied to other subsets,
% e.g.
% - standard 4D MrImageSpm realignment, with or without weighting of
% particular voxels
% - multi-echo data, 1st echo realigned, app... |
747a60e63ea73e653b9998d497d44a729bdf83228857c4c774c5d3295f94f77a | MATLAB | 4,652 | 130 | function out = CP_WaveletVarChg(y, wName, level, maxnchpts, minDelay)
% CP_WaveletVarChg Variance change points in a time series.
%
% Finds variance change points using functions from Matlab's Wavelet Toolbox,
% including the primary function wvarchg, which estimates the change points in
% the time series.
%
% ---I... |
1b6048526da6133ebd2d5c75c7f007ba9b39813b6a0bc484ecda84231a610c6a | MATLAB | 4,654 | 99 | function [numPCs, not_converged, score, sd_score, latent, sd_latent] = parallelAnalysis(prefix, basedir, datafolder, resultsfolder, slices, spv, perm, maxiter, truncate)
%PARALLELANALYSIS compares IAAFT generated surrogates to fMRI timeseries
%data to determine a number of principal components in a region outside the... |
45dee5a95a8e407d3096d41781f223733ecf5ad1b2c0d107003b679860202bb6 | MATLAB | 4,654 | 123 | function SU = makeHeatmat(SU, S, behEvents, wndw, bins, varargin)
% input
% SU struct
% S struct
% behEvents struct
% wndw = [-2,4] usually
% bin = 0.05s usually
% varargin = include raster or not
if nargin<5
bins = 0.05;
end
%side LED on
sideEvents = {S.Lled(:,1) S.Rled(:,1) S.l_opt(:,1) S.r_opt(:,1)}; %pull ti... |
39f713f385523f0d66e9d870349e1c4106c189230cab7018a28a676863b696c3 | MATLAB | 4,656 | 144 | %% Run an optimization on certain parameters with the 1-sided, systemic model
% MJC 5/27/2021
clear all; %close all; clc;
! make clean -f Makefile
! make -f Makefile
! chmod +x sor06
%% Define the inflow
% load('allparam_unweight1.mat');
% opt_values = x.*sc;
% inflow_param = opt_values(:,1:12)';
Qdat = dlmread('DP... |
0283b2ebfdf38fa0fd2edda184c3baee917f9dc8e7be811f7fd6432ca9d732df | MATLAB | 4,660 | 129 | function outputImage = kfilter(this, filterType, applicationDimensions, varargin)
% Filters by multiplication of a specified window function in k-space
%
% Y = MrDataNd()
% outputImage = Y.kfilter(filterType, applicationDimensions)
%
% This is a method of class MrDataNd.
%
% IN
% filterType string of filter to b... |
b6740b1f66bab790ddb5104fc06f23a3e1ff35ef502c0aa848b85a8e8ee38045 | MATLAB | 4,663 | 109 | function [varargout] = likGamma(link, hyp, y, mu, s2, inf, i)
% likGamma - Gamma likelihood function for strictly positive data y. The
% expression for the likelihood is
% likGamma(f) = al^al*y^(al-1)/gamma(al) * exp(-y*al/mu) / mu^al with
% mean=mu and variance=mu^2/al where mu = g(f) is the Gamma intensity, f is... |
1d90854ae4872eb23892a35a1fd5c7bebc809c02e6ba39e785a646f9b17f94e5 | MATLAB | 4,664 | 132 | function [J,h,func_evals,f_0]=jacobiansimple(func,x,varargin)
% SIMPLE JACOBIAN CALCULATION
%
% evaluates the jacobian of a function func at point x. It respects
% bounds, can accept a baseline evaluation (e.g. f_0=func(x)), and
% will provide it for further evaluations to speed up computations.
% Fu... |
bbdb019701c0b4e399736861f435248651a4c47fd4e03e547cb6018b1464beda | MATLAB | 4,665 | 199 | function [efs,F,cdfs,p,eps,dfs,b,y2,sig,mses,msss,partial_eta_squared,effectname]=repanova(d,D,fn,gg,alpha,display_results)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% [efs,F,cdfs,p,eps,dfs,b,y2,sig,mses,msss,partial_eta_squared,effectname]=repanova(d,D,fn,gg,alpha);
% R.Henson, 17/3/03; rik.henson@mrc-cbu... |
306887dfda8ecebf1138e5599b26889dbe6ee6fd003d07fcb7af013a737f4379 | MATLAB | 4,666 | 119 | function tests = tapas_physio_filter_cardiac_test()
% Tests whether bandpass filter on PPU example data works as expected
%
% tests = tapas_physio_filter_cardiac_test()
%
% IN
%
% OUT
%
% EXAMPLE
% tapas_physio_filter_cardiac_test
%
% See also
% Author: Lars Kasper
% Created: 2019-07-02
% Copyright (C) 2019 T... |
b3bf05d29713bf7a4afabecf939c3142e5a36122eb4287f684690f93e8e9faf0 | MATLAB | 4,667 | 127 | function step5RunRFX(maps, funcFWHM2Level)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% maps = 'beta'% 't_maps';
% funcFWHM = 0 % 2;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% addpath(fullfile(fileparts(mfilename('fullpath')), '..'));
% initEnv();
opt = getOptionSearchlight();
i... |
1859780247bec603e34062e35cc34bd9fe67762cd806b62f724916b3538945eb | MATLAB | 4,668 | 143 | function [g_val, err_gain, r_gain] = fit_gain_change(x0,y0,x1,y1,varargin)
ip = inputParser();
addParameter(ip, 'interp_method', 'linear', @(x)validateattributes(x,{'char'},{'nonempty'}));
addParameter(ip,'normalize_error',false, @(x)islogical(x));
addParameter(ip,'normalize_x', false, @(x)islogical(x));
addParameter(... |
1340c2a382b18a9b6710a0231bd52d18987ea39d920abd6e96ae7a98e8e08318 | MATLAB | 4,669 | 128 | function [header,tracks] = trk_read(filePath)
%TRK_READ - Load TrackVis .trk files
%TrackVis displays and saves .trk files in LPS orientation. After import, this
%function attempts to reorient the fibers to match the orientation of the
%original volume data.
%
% Syntax: [header,tracks] = trk_read(filePath)
%
% Inputs:
... |
6c1bd5a735519ae314c746bd9b06f083f35290ea114369d72fb1166e50a4046e | MATLAB | 4,671 | 122 | %% AlignEvent
% Align spike data on a specific event, compute Z-score, and save into <aligned> folder
%% PARAMETERS
TIMEWINDOW_LEFT = -2000; %(ms)
TIMEWINDOW_RIGHT = +2000; %(ms)
TIMEWINDOW_BIN = 50; %(ms)
numBin = (TIMEWINDOW_RIGHT - TIMEWINDOW_LEFT)/TIMEWINDOW_BIN; % number of bins
%% Select Unit data (.mat) path
... |
91762a6d1fd1392d4e7469199c5568eeda0f80788ebb9172015ce4baa23b75c7 | MATLAB | 4,671 | 113 | function [cpulse, verbose] = tapas_physio_get_cardiac_pulses_auto_matched(...
c, t, thresh_min, minPulseDistanceSamples, verbose, ...
methodPeakDetection)
% Automated, iterative pulse detection from cardiac (ECG/OXY) data
% (1) Creates a template of representative heartbeats automatically (as
% deprecated *... |
c818db133d9a1b3bf0463b63afe95c8b16e235161eb997ed23cf57bde4ce6c08 | MATLAB | 4,671 | 126 | function [spectrum,f,s] = MTPointSpectrum(times,varargin)
%MTPointSpectrum - Compute point process spectrum by multi-taper estimation.
%
% The spectrum is computed using the <a href="http://www.chronux.org">chronux</a> toolbox.
%
% USAGE
%
% [spectrum,f,s] = MTPointSpectrum(times,<options>)
%
% times ... |
7c787c30288f6a3e26f5f300672da034993c78caf63019f8f4befaa45c9a0f72 | MATLAB | 4,672 | 137 | function angdataw=angtimewarp(evLatency, newLatency, angdata)
% ANGTIMEWARP - Given two event marker vectors, computes a
% warping of the input angular time series so that its
% evlatencies match newlatencies. Values of the warped
% timeserie that falls between two frames... |
182658322048afe1ba600254dfd11624926e57a85c922fd1cafe3a82eb539069 | MATLAB | 4,675 | 169 | function [ regional_metrics , regional_labels] = nmri_regional_values( full_metrics, ref_surf, opt)
%[ regional_metrics ] = nmri_regional_values( full_metrics, ref_surf, opt )
% Will resample a full brain e.g. SUMA surface (1 value/vertex) metric
% into a regional metric (1 value / region)
% the regional informat... |
22e5820c44b8828677e4c81a2f55627427b4adf6f36b024789873a10cc5135c3 | MATLAB | 4,683 | 126 |
%% predicted
clear;
mypath = '/Users/bo/Documents/data_liujia_lab/analysis_liuP1_greeble';
sub_pool = {'01', '02', '03', '04', '05', '06', '07', '08', '09', '10', '11', '12', '13', '14', '15', '16', '17', '18', '19', '20'};
% sub_pool = {'11', '12', '13', '14', '15', '16', '17', '18', '19', '20'};
cur_struct = MRIre... |
470339e9ff6ac2cd59c30f0a6afc798746693421d2603f2c0cb0c7424e881e8b | MATLAB | 4,683 | 114 | function problem_critpt = criticalpointfinder(problem)
% Creates a Manopt problem whose optima are the critical points of another.
%
% problem_critpt = criticalpointfinder(problem)
%
% Given a Manopt problem structure 'problem', this tool returns a new
% problem structure, 'problem_critpt', such that the global optima ... |
b717554765ace2392c3181759ed29ae3ae70e060336b4791dd56d5012681dd24 | MATLAB | 4,683 | 139 | function [result] = fit_happy_model_responsibility(mtx,happyscore,constant)
%assumes that each row of the cell array is a different subject
rptfit = 5; %repeat N times jittering the betas
tempf=fieldnames(mtx);
for n=1:length(tempf), eval(sprintf('mtx.%s=double(mtx.%s);',tempf{n},tempf{n})); end;
data = mtx;
data.hap... |
6f6a143a4ed7be7c92616407b47309a685a29dad4a314d7baab4d03a77cfa7f0 | MATLAB | 4,689 | 89 | function osp_onQuant( ~, ~ ,gui)
%% osp_onQuant
% Callback function on quantify button click.
%
%
% USAGE:
% osp_onQuant( ~, ~ ,gui);
%
% INPUT: gui = gui class containing all handles and the MRSCont
%
% OUTPUT: Changes in gui parameters and MRSCont are written into the
% gui ... |
cd3addb6fd5f46dc116d147a727e2a6c5c7501864bbde9a4c0c568e3ff138291 | MATLAB | 4,689 | 185 | function OUT = citation_mca(file)
% OUT = citation_mca(file)
% Citations are output from Endnote in APA 5th format
% Save as MS-DOS text
% example: 'citation_list1.txt'
%
% Multiple people with the same name, e.g., Zhang, are not counted
% correctly!
% read text file
s = textread(file,'%s','delimiter',',\n');
% find ... |
f3ddfdb494f2119ee054194d995108ef8fd7634f5b2acf7a05091cfa400698ce | MATLAB | 4,689 | 120 | function tapas_hgf_categorical_plotTraj(r)
% Plots trajectories estimated by fitModel for the hgf_categorical perceptual model
% Usage: est = tapas_fitModel(responses, inputs); tapas_hgf_plotTraj(est);
%
% --------------------------------------------------------------------------------------------------
% Copyright (C... |
16840ebc7824e8a9db979045737ae9b62b7aa68cbd5f1277481e7dcdd37dd2c8 | MATLAB | 4,690 | 150 | function allenMapPolyCentered(dorsalMaps, bregma, side, colorFill, scaleBar, hAx)
% allenMapWithLabels(dorsalMaps [, side] [, colorFill] [, scaleBar])
%
% Produce a dorsal-view Allen atlas map using polygons instead of an image
% (as allenMapWithLabels.m does).
%
% Input "dorsalMaps" should be from allenDorsalMap.mat.... |
7b43317e2200bdaecd98b28f31476f1e9c5cc0a11db472ce8370f8bc0dd4cabc | MATLAB | 4,691 | 125 | function [peaks,majorpower]=fft_neuron(imageprofile,filename,timeinterval)
%% to run:
imageprofile=double(imageprofile);
ll=length(imageprofile);
cinfo=strrep(filename,'.tif','_output/');
[~,savename,~]=fileparts(filename);
%colorofcurve = 'r';
%scrsz = get(0,'ScreenSize');
%figure('Position',[scrsz(3)*... |
c84a86d7fbeb17f7289d435aa8953b964026d74cb179537f5a4640ccd3d20882 | MATLAB | 4,692 | 153 | function s = mfileparse(mfile, mdirs, names, options)
%MFILEPARSE Parsing of an M-file to obtain synopsis, help and references
% S = MFILEPARSE(MFILE, MDIRS, NAMES, OPTIONS) parses the M-file MFILE looking
% for synopsis (function), H1 line, subroutines and todo tags (if any).
% It also fills in a boolean array indi... |
ca1a85243b7750eac9c347bd65cb002cbe5f3024d26f2f2931e2066038931d29 | MATLAB | 4,692 | 138 | function [result] = fit_happy_model_responsibility_redux(mtx,happyscore,constant)
%assumes that each row of the cell array is a different subject
rptfit = 5; %repeat N times jittering the betas
tempf=fieldnames(mtx);
for n=1:length(tempf), eval(sprintf('mtx.%s=double(mtx.%s);',tempf{n},tempf{n})); end;
data = mtx;
da... |
56fee600ebf51c5ff412942edcabc293f2126b03b25f14350978c8137235df4f | MATLAB | 4,694 | 142 | %% %%%%%%%% Organize the data
% manually organize dicom directories
% quick check of directory sizes
du -s ~/nsd/rawdata/*stru*/dicom/*
%% %%%%%%%% Prepare some templates
% get MNI152_T1_1mm templates
cd /opt/local/fsl-5.0.7/fsl/data/standard
rsync -av MNI152_T1_1mm* /home/stone/generic/Dropbox/nsddata/templates/
... |
7b718b88f0cc12eae1a494b7171981421cb36e1ab0bfdb65f4c0c2c2e519fb8b | MATLAB | 4,694 | 96 | %% This document shows how fsaverage-defined ROIs are converted to individual-subject
%% surface ROIs, and then how those individual-subject surface ROIs are converted
%% to the anat0pt8, func1mm, and func1pt8mm spaces.
% First, we will take various ROIs defined on fsaverage and transfer these ROIs
% via nearest-neig... |
32db9fca7fc9371e6e78b9dd5c701f2953cbde1f9fffc6d270bcf6ff9bd5582c | MATLAB | 4,695 | 155 | binwidth = 10; % ms
range = [2000 3000]; % ms
for data = 1:2
if data == 1
load('dataOKT03901')
else
load('dataOKT04906')
end
[bb,aa] = butter(3,5/(TQsRate/2),'low');
fTQ = filtfilt(bb,aa,TQ);
% dfTQ = diff(fTQ);
% fdfTQ = filtfilt(bb,aa,dfTQ);
... |
f3fe6837e1604b9f8389317ec73df288aa973d551cc7b15b26a58cf229bd44ec | MATLAB | 4,695 | 110 | %% TestBFRMatrixPhantom - Tier 2 synthetic-phantom background-field-removal method regression matrix
%
% Mirrors TestQSMMatrixPhantom.m: runs the one-stop SEPIA pipeline on the
% synthetic phantom once per background-field-removal method in
% methodBFRName (sepia_universal_variables.m) AND per matrix size (the
% same 5... |
d58e2ec0c4ea9a0677df3ed0341aff49f421f87c106cadae2bb63c5046057da7 | MATLAB | 4,697 | 180 | function test94()
% Test for fixedrankNewGHquotientfactory geometry (low rank completion)
%
% Test CG scheme
% This file is part of Manopt: www.manopt.org.
% Original author: Bamdev Mishra, Dec. 30, 2012.
% Contributors:
% Change log:
clc; close all;
% reset(RandStream.getDefaultStream);
% randnfoo = rand... |
ee47aebbaf9d4fc4bca09558458c615f72a181e4da936d19677255765c293899 | MATLAB | 4,697 | 142 | function varargout=detectFreezeByHMM(basename,varargin)
%%
load([basename '.basicMetaData.mat'])
fprintf('%s start %s with data of %s\n',datestr(now),mfilename,basicMetaData.SessionName)
load([basicMetaData.Basename '.olfactorySpec.lfp.mat'])
load([basicMetaData.Basename '.acceleration.lfp.mat'])
load([basicMetaData.B... |
0c4f8af99f32c419b0d466c0791200554a62b2d84e05fefec10ecad1a796990d | MATLAB | 4,699 | 148 | function [T1, PD, R1] = MP2RAGE_dictionaryMatching(MP2RAGE, INV1,INV2,B1map,varargin)
% function that computes T1 and PD maps using a dictionary matching
% approach.
% input variables are:
% MP2RAGE is a structure that should have the following fields
% MP2RAGE.TR
% MP2RAGE.TIs,
% MP2RAGE.NZslices,
% ... |
1971af6cd2b7f6682caebff1bb6d8eef83407adc4063bb83b17eaf2991418928 | MATLAB | 4,705 | 126 | function brain = brainVolumes_load(params, file2load, struct_plotBrain)
% loads 3D brain volume (MRI, CT, anatomic areas, ...) sepcified in file2load
% interpolates if different vosel size is specified
% returns brain =
% SPM package MUST be included in Matlab path
% (c) Jiri, Nov21, Jan17
% based on: getBrainData.m
... |
794780e89139873138ec70ae1dd882731a668c3a35cf8f3f3f05c7c761230aec | MATLAB | 4,707 | 175 | %% markCropBox
% video annotation GUI built on top of movieAnalyser
classdef verifyFlyPositions < movieAnalyser
properties
all_objects
full_images
parent_dir
x_scale
y_scale
original_file_names
end % end properties
methods
function a = createGUI(a)
createGUI@movieAnalyser(a);
a.ui_handles.f... |
03a449784a72663daa64a852b67ef62a02bebad1425ab802d74675d1e6dda55a | MATLAB | 4,708 | 97 | function filename = env_translatepath(filename)
% Translates platform-independent directories into a system-specific directories.
% SystemPath = env_translatepath(IndependentPath)
%
% BCILAB supports platform-independent paths for all its scripts and IO functions, which allows for
% script portability from system to sy... |
4461fbdf69579e2cef5787d6d1c48367fa90c0c5487967a437839f17e7bfef17 | MATLAB | 4,709 | 143 | function [unsrtR,S,srtR] = palm_competitive(X,ord,mod)
% Sort a set of values and return their competition
% ranks, i.e., 1224, or the modified competition ranks,
% i.e. 1334. This makes difference only when there are
% ties in the data. The function returns the ranks in
% their original order as well as sorted.
%
% U... |
1adb4c0fc3462a7937d84fe14224cea50a6998ffdadec6776e0a9f6e28593138 | MATLAB | 4,710 | 126 | % postprocessing for all ofc data (stratified and non-stratified)
%location of analysis codebase
codepath = '~/projects/constantinoplelab/Analysis/';
% add code paths
addpath(genpath(codepath))
addpath(genpath(codepath + "david"))
addpath(genpath(codepath + "maggie"))
%for saving pds correctly so illustrator can mo... |
6b5ff9f9983400e3f614912bbdb2131f822bcef80bc4b8883c2e8089c4bd5a2e | MATLAB | 4,710 | 138 | %Funciona bien LC2014.
%Algoritmos intuitivos que funcionan para detectar los estados de una red
%asumiendo que los picos de sincronia en diferentes tiempos no tienen una
%variacion enorme, esto es que el numero de celulas totales involucradas en
%los picos no varie de 4 a 100 por ejemplo. En dichos casos el S_index e... |
2802d87a1d995125edde92b781f0b251ae51ee480873c9044a2461ef43a30186 | MATLAB | 4,712 | 142 | function [result] = fit_happy_model_inequalityActPass(mtx,happyscore,constant)
%assumes that each row of the cell array is a different subject
rptfit = 5; %repeat N times jittering the betas
tempf=fieldnames(mtx);
for n=1:length(tempf), eval(sprintf('mtx.%s=double(mtx.%s);',tempf{n},tempf{n})); end;
data = mtx;
data.... |
a3d9c2f8f80230af7c3157202e9ec215b8a8ce6689062f3cfdb5b682796f8be0 | MATLAB | 4,713 | 104 | function [deconvolved,t] = DeconvolvePETH(signal,events,varargin)
%DeconvolvePETH - Compute a deconvolved version of PETH which removes the
% smoothing effects of the events' autocorrelogram
%
% INPUTS
% signal signal to find events for
% events events for PETH
% <options> option... |
0305f706410831de0726602329489b7a1f60edd77562ec5e00d00e43129d0514 | MATLAB | 4,715 | 118 | % ROBUST_KMEANS - an extension of Matlab KMEANS that removes outlier
% components from all clusters.
% This is a helper function called from POP_CLUST.
% Copyright (C) 2006 UCSD
%
% This file is part of EEGLAB, see http://www.eeglab.org
% for the documentation and details.
%
% Redistribution and use i... |
b4649e1a19dc22ed83542e782304d98ae840b86e6d6ca540c084e87440e36b57 | MATLAB | 4,715 | 141 | function M = symfixedrankYYcomplexfactory(n, k)
% Manifold of n x n complex Hermitian pos. semidefinite matrices of rank k.
%
% function M = symfixedrankYYcomplexfactory(n, k)
%
% Manifold of n-by-n complex Hermitian positive semidefinite matrices of
% fixed rank k. This follows the quotient geometry described
% in S... |
bcaea42ca516ef7584ce6bba355198386cf0a4ba537557fe3a58b5ed63c155c0 | MATLAB | 4,715 | 129 | function [coeff,local] = CV(timestamps,varargin)
%CV - Compute coefficient of variation for a point process.
%
% Three alternative measures can be computed: regular CV, CV in operational time
% (Gestri and Petracchi, 1970; Nawrot et al., 2008) or CV2 (Holt et al., 2006).
%
% While the CV is typically computed for cons... |
dfe633a721fa0a1d5143df5217418174558831152052c1ad580748a20ef4ebaa | MATLAB | 4,715 | 154 | function [t_aligned, t_21, v_21, t_9, v_9] = extract21PointsFromPeaks(loc, volt, fs, num_points, varargin)
p = inputParser;
addRequired(p, 'loc', @isvector);
addRequired(p, 'volt', @isvector);
addRequired(p, 'fs', @isscalar);
addRequired(p, 'num_points', @isscalar);
addParameter(p, '... |
7a983b2586c97be6f05bc777bd6ed81959fee5e9c302cdad8583f59ab99df1e0 | MATLAB | 4,718 | 121 | function plotEigenvaluePostHoc(data, behavior, toi, significantResults, outputFolder)
uniqueAges = unique(behavior.Age);
uniqueGroups = unique(behavior.Group);
data = permute(data, [1 3 2 4]); % subjects × components × epochs × time
[~, numComponents, numEpochs, ~] = size(data);
colors = {[0 0 0], [1 0.5 0], ... |
13b6dbb5e3e386f843b72f20b298d1536597b715748d06b5e478e1556a60028a | MATLAB | 4,719 | 118 | function [interpolated,discarded] = Interpolate(samples,timestamps,varargin)
%Interpolate - Interpolate samples (positions, spikes, LFP, etc.) at given timestamps.
%
% Interpolate samples (positions, spikes, LFP, etc.) at given timestamps. As a special
% case, a point process can also be 'interpolated' by changing eac... |
a0ef677ca701277699cfaad2f13e77cf2feef3436308d8fd410736feec373a3c | MATLAB | 4,722 | 124 | function out = CO_Embed2_Basic(y, tau)
% CO_Embed2_Basic Point density statistics in a 2-d embedding space.
%
% Computes a set of point-density statistics in a plot of y_i against y_{i-tau}.
%
% INPUTS:
% y, the input time series.
%
% tau, the time lag (can be set to 'tau' to set the time lag the first zero
% ... |
17aeef410bd3984b09fffa88b23a86a665229f1948445a767f736e466c54c85a | MATLAB | 4,723 | 126 | function [tMin,fMin,tBreak1,tBreak2,tMinAll]=essential_distMinAnglePair_base(Q211,Q212)
flagCheckFirstDer=true;
flagUseNewton=true; %Note: requires flagCheckFirstDer=true
tolMZero=1e-15;
tMinAll=[];
[tBreak1,~,~,c1,m1,p1]=essential_distMinAnglePair_discontinuityDistance(Q211);
[tBreak2,~,~,c2,m2,p2]=essential_dist... |
94fe4477965b2fcef05639c910a9786c2acb579edeada642381e9e868a7d5b4e | MATLAB | 4,724 | 126 | function Test_fixedrankembeddedfactory()
% Given partial observation of a low rank matrix, attempts to complete it.
%
% function low_rank_matrix_completion()
%
% This example demonstrates how to use the geometry factory for the
% embedded submanifold of fixed-rank matrices, fixedrankembeddedfactory.
% This geometry is ... |
6a16ade0c3bc25feb546ab5b03922f84b42be56392cfad92694a74ae36422a53 | MATLAB | 4,726 | 95 | %% create Roi which are non-overlapping
% This script takes the Mt and Mst rois which are created using method2
% and removes the overlapping volume to create non-overlapping MT and Mst Rois
%
% Method2:
% it is important to use these masks so that we identify the clusters which are not connected to other regions
% h... |
1171c0d86937209e042aa6303bc000ed7bf0c095beb3a443a5a9e34eb622fdd3 | MATLAB | 4,731 | 151 | function Stat=clusterstat(S,partition,between)
%function Stat=clusterstat(S,partition,[between])
%
%PURPOSE
%
%To compute various intra- and extra-cluster statistics.
%
%INPUT
%
%[An argument in brackets is optional. If it isn't given or it's
% an empty matrix/string, the function will use a default value.]
%
% S ... |
3474d9db7c24f2485b51ab80a771db72af40aa4cf3ece7627b44c6621e6486ee | MATLAB | 4,733 | 96 | function [cpulse, verbose] = tapas_physio_get_cardiac_pulses(t, c, ...
cpulse_detect_options, cardiac_modality, verbose)
% extract heartbeat events from ECG or pulse oximetry time course
%
% cpulse = tapas_physio_get_cardiac_pulses(t, c, cpulse_detect_options, cardiac_modality, verbose);
%
% IN
% t ... |
0a4eef795568c12209e110b51bdc5cbaa9ecbe3d8806473764f017fb96dea1dd | MATLAB | 4,734 | 158 | function ir=icassoRindex(sR,L)
%function ir=icassoRindex(sR,[L])
%
%PURPOSE
%
%To return and/or plot a relative clustering validity index.
%R-index is originally defined in Levine & Dormay (2001),
%"Resampling method for unsupervised estimation of cluster
%validity. Neural Computation 13(11)) and redescribed in
%public... |
562ea9b51479c048ce988e0adcfcb3cdf1f606dbb9a3b6e6bcbf7e5f16a22690 | MATLAB | 4,734 | 147 | function coactPaper_tableS01()
close all
height=9.6;
fontsize=6;
fh=initFig('width',18.6,'height',height,'font','Arial','fontsize',fontsize);
panel_01(7)
drawnow()
print(fh,sprintf('~/Dropbox/FearAnalyses/paper/figure/tableS01_%s.pdf',datestr(now,'yyyymmdd')),'-dpdf','-painters','-r300')
end
function panel_01(fs)
o... |
0fdb50685fe4ee173738e2646b5fbb6b62435a8017d9921ddbeca5e658e7fffe | MATLAB | 4,739 | 132 | %% Generate Figure 5d
% Note: This model was trained and evaluated using raw (non-normalized) values
% to preserve interpretability in millimeters
%%
clear; clc;
set_participant_information
addpath(morph_path)
% Paths to change
save_path = fullfile(morph_path, 'REVISION','Figure_4d');
file_path = fullfile(morph_pat... |
3ae023c005338658b0532364c5b154b7c3a89729d6f823c19330a9aee0e2970a | MATLAB | 4,739 | 122 | % concatdata - concatenate data stored into a cell array into a single
% array. only concatenate along the last dimension
% Usage:
% [dataarray len dims] = concatata(cellarraydata);
%
% Input:
% cellarraydata - cell array containing data
%
% Output:
% dataarray - single array containing all data
%... |
1e3b0132570665bad90f0d7bad92f98e2db99df77655d3ab016d129e53206a69 | MATLAB | 4,744 | 93 | function data=rmlinesc(data,params,p,plt,f0)
% removes significant sine waves from data (continuous data).
%
% Usage: data=rmlinesc(data,params,p,plt,f0)
%
% Inputs:
% Note that units of Fs, fpass have to be consistent.
% data (data in [N,C] i.e. time x channels/trials or a single vector) - required.
% ... |
71b145306aa645259078a64ec217d5d20d722049ac86a0f32779a734abf6b931 | MATLAB | 4,744 | 117 | function currentMousePosition = tapas_uniqc_lineplot_callback(hObject, eventdata, Img, ...
hAxLinePlot, fnConvertMousePosToSelection)
% provides a callback function to plot the non-displayed dimension in a
% figure display
%
% currentMousePosition = tapas_uniqc_lineplot_callback(hObject, eventdata, Img, ...
% ... |
de61d7841a57cf3a1a97134521716f6a35c87161db804d285721dbbcf3f7ae7e | MATLAB | 4,744 | 141 | function filtered = Filter(samples,varargin)
%Filter - Filter samples.
%
% USAGE
%
% filtered = Filter(samples,<options>)
%
% samples <a href="matlab:help samples">samples</a> to filter
% <options> optional list of property-value pairs (see table below)
%
% ====================================... |
0fb7a8628fc2b7b11347ed78f4207e43381b26863245ddb08b13c74bf0528d9f | MATLAB | 4,745 | 148 | function fear_tripleActTrigWaveletNREM(basename,varargin)
% basename='~/data/Fear/triple/hoegaarden181115/hoegaarden181115';
load([basename '.basicMetaData.mat'])
fprintf('%s start %s with data of %s\n',datestr(now),mfilename,basicMetaData.SessionName);
load([basicMetaData.AnalysesName '-nremWaveletPow.mat'])
param.l... |
94d7dd05d93645b354a8ff642aca65d8e43e4d75b4fc07941a6ebf4ba596cbf1 | MATLAB | 4,747 | 108 | % Script demo_set_geometry
% Illustrates the different components that define an image geometry.
%
% demo_set_geometry
%
%
% See also definition_of_geometry
%
% Author: Saskia Bollmann & Lars Kasper
% Created: 2018-11-05
% Copyright (C) 2018 Institute for Biomedical Engineering
% University of ... |
af4a135db583ed2ea2eb539ee3b52e18cfa0367d938b74b44ffdaf15ac2181b2 | MATLAB | 4,747 | 118 | % inherited from analysis_prf_maps.m
%
% this script just makes a bunch of maps.
%% %%%%%%%% Prep special colormaps
cmfecccmapA = cmfecccmap(4); % to green
cmfecccmapB = cmfecccmap(4); % to green
cmfecccmapC = cmfecccmap(7); % to cyan
vals = linspace(0,12,257);
vals = vals(1:256) + diff(vals(1:2))/2;
whval = [0.... |
1ee0f5697582265582ef9b39da2df3f72477b8ad7945af596259cab07170d37a | MATLAB | 4,750 | 155 | function [unmixsource,umxcoeff,options]=umxICA(source,reference,varargin)
% GOAL: Unmix the two signal using Blind Source Separation method.
%
% INPUT:
% - source: source trace 'sce' to be unmixed from the reference trace 'ref'.
% - reference:
% - options (as input struct or variable arguments):
% ... |
06def1927e146eb3212145c7a1819a7959d8b5e66062805f8516fc9b74d00d26 | MATLAB | 4,751 | 156 | %% script that loads data from effective connectivity (dDTF) from all subj
% warning: harcoded paths, ...
% (c) Jiri, Sep22
loadDataAgain = false;
% set subjects
params_default;
params.paradigm.usedParadigm = 'switchEI';
params.paradigm.specificType = 'switchEI';
params.storage.dir_shareData = 'G';
[params.storage.p... |
f02871213ad5c9220000735477a5e3112c8d981fae5f113b4e09fb6bfde27cd1 | MATLAB | 4,751 | 154 | function run_permuchi2_examples
%RUN_PERMUCHI2_EXAMPLES Run permutation Chi-square test examples.
% Generates random multivariate categorical data for a sample X,
% containing 20 variables. The first 10 variables contain a weak
% association, while the remaining 10 variables are completely
% independent. Each ... |
9f4dba7b1020811fceec2c371ae6db515b5c37111a17138d5a6dd732dac43138 | MATLAB | 4,753 | 133 | function DBAddVariable(v,eid,name,comments,parameters,mfiles)
%DBAddVariable - Save variable in current database.
%
% Save variable and code used to compute it.
%
% USAGE
%
% DBAddVariable(v,eid,name,comments,parameters,mfiles)
%
% v variable
% eid experiment ID (identifier string)
% ... |
124c9473c3dc81ea92c9aa447b066d676b69eeed6099a1d29c1d5f839d742c34 | MATLAB | 4,754 | 124 | % EEGFILTFFT - (high|low|band)-pass filter data using inverse fft
% (without using the Matlab signal processing toolbox)
% Usage:
% >> [smoothdata] = eegfiltfft(data,srate,locutoff,hicutoff);
% >> [smoothdata] = eegfiltfft(data,srate,locutoff,hicutoff,epochframes,filtorder,revfilt);
%
% Inputs:
% ... |
32411126c4af0974233ab764083d0105b5eb12d0d99dc803e570be43c64279e0 | MATLAB | 4,755 | 141 | function res = permutation_null_spin(img_data, geneset, expressions, gene_symbols)
% PERMUTATION_NULL_BRAIN(...) performs permutation testing to examine
% whether imaging profiles associate with gene expression profiles, based
% on the null-brain model (where random genes were selected from
% brain-expressed genes).
%... |
5a78d85fc3c08acd0a6c03077af1ea78a14e1b90df9a925b2c5b6ce26056fbc9 | MATLAB | 4,756 | 140 | function [C_store]=NumericalSolver3D(M,ds2,dt,nt,Diff,S0,Q,kapa,tp,T,rate,f,alpha,sc,Mask,Cb, BC)
%Extract source coordinates
Sy=S0(1);
Sx=S0(2);
Sz=S0(3);
Mx=M(2);
My=M(1);
Mz=M(3);
dy2=ds2(1);
dx2=ds2(2);
dz2=ds2(3);
ds=sqrt(ds2);
sc_z=sc*(ds2(1))/(ds(... |
afde10b4186f62323484961dacfd62a54ba586e79d331f34dfc47c3aac30b40b | MATLAB | 4,756 | 144 | function analyzebehavior_nsdsynthetic(datadir,expfile)
nsdsetup;
ppdir = regexprep(datadir,'rawdata','ppdata');
mkdirquiet(ppdir);
%% BEHAVIORAL PERFORMANCE
% find behavioral files
files = matchfiles([datadir '/mat_files_from_scan/*nsdsynthetic*subj*run*.mat'])
assert(length(files)==8);
% HACK FOR FIXING DIFFERENT ... |
aab76bb46ea233ce2a230a04740dc501f97a934b418b940e62ef9f608165d4de | MATLAB | 4,758 | 81 | function osp_onNii( ~, ~,gui)
%% osp_onSave
% Callback function on nii button click. Opens the external Nifti Viewer.
%
%
% USAGE:
% osp_onNii( ~, ~ ,gui);
%
% INPUT: gui = gui class containing all handles and the MRSCont
%
% OUTPUT: Changes in gui parameters and MRSCont are written into th... |
fffc1f719e0ea7c75822999934b32dab91c28a848c752d37c53e5bcca8049b48 | MATLAB | 4,759 | 117 | function varargout = halfViolin(data,varargin)
%halfViolin - generate half violin plots for visualizing the distribution
% of data across multiple columns.
% halfViolin - Generate half violin plots for visualizing the distribution
% of data across multiple columns. Each column of "data" should represent a
% dif... |
68856d9510eb9bf38d590f1632f215ac4debba3c04b0b85260ebfbb59ba2c63e | MATLAB | 4,760 | 139 | % JOINTPROB - rejection of odd columns of a data array using
% joint probability of the values in that column (and
% using the probability distribution of all columns).
%
% Usage:
% >> [jp rej] = jointprob( signal );
% >> [jp rej] = jointprob( signal, threshold, jp, normalize, discret)... |
70a8676021ce6ac2c619b933889d0dcb828e0bd150ee291547ed31d9d44080ba | MATLAB | 4,760 | 160 |
% Define parameters
inputSize = 2;
hiddenSize = 100;
outputSize = 1;
numSequences = 20;
numTestSequences = 20;
sequenceLength = 1;
numEpochs = 15000;
supervised_rate = 0.01;
topdown_rate = 0.001;
% Generate XOR data for training
[x1, x2, Y] = generate2bitparity(numSequences);
inputs = [x1, x2];
X = z... |
3f6366ded50b6bbfc81d024faa5804175b6bb291342d6e9da557fc8201d3012d | MATLAB | 4,763 | 107 | function [avgITIbyblock_opto, errITIbyblock_opto,...
avgITIbyblock_nonopto, errITIbyblock_nonopto] =...
CompareOptoITIbyBlock(optoafterdate, Aligned, S) %controlafterdate, varargin
%input: ratlist (e.g. {'G060'})
%afterdate is the date after opto surgery for control sessions
%G071: optoafte... |
aabf552289ae08c36ec22c1dbcd693dfd05499ba3259c40d99ce4c63627b097d | MATLAB | 4,764 | 185 | function [cs,coh,nave]=data2cs_event(data,segleng,segshift,epleng,maxfreqbin,para);
% usage: [cs,coh,nave]=data2cs_event(data,segleng,segshift,epleng,maxfreqbin,para)
%
% calculates cross-spectra from data for event-related measurement
% input:
% data: ndat times nchan matrix each colum is the time-series in one
% ... |
b55680ab2346eab16c3310bdb13bc16297a0129a633619b5d0e57f5697743c79 | MATLAB | 4,765 | 96 | %{
preprocess.PrepareGalvo (imported) # basic information about resonant microscope scans, raster correction
-> preprocess.Prepare
---
nframes_requested : int # number of valumes (from header)
nframes : int # frames recorded
px_width ... |
6d4b869e30b5d3b56551d43693c19b1662962ab6505d1f266c4387969e4ebfbb | MATLAB | 4,766 | 135 | % EEG_COUNTEPOCHS Count how many epochs there are of each type
%
% Usage:
% >> eeg_countepochs(EEG);
%
% Inputs:
% EEG - input dataset
% epochmarker - ['type'|'eventtype'] indicates which part of the
% EEG.epoch structure the different trial types are stored in. Depending
% on what system the da... |
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