sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
1bf3395daf261aeb2b85154581de745d7b6a3a40ed86081a8de7b84df379e150 | MATLAB | 8,589 | 206 | function [cfg] = ft_definetrial(cfg)
% FT_DEFINETRIAL defines the segments of data that will be used for
% further processing and analysis, i.e. the pieces of data that will
% be read in by FT_PREPROCESSING. Trials are defined by their begin
% and end sample in the data file and each trial has an offset that
% defines... |
d1bc1a572b82405487a3ed4d5e8acd72f1f664a57aaa85ce4dac3929c0ea90a1 | MATLAB | 8,592 | 215 | function ft_select_channel(handle, eventdata, varargin)
% FT_SELECT_CHANNEL is a helper function that can be used as callback function
% in a figure. It allows the user to select a channel. The channel labels
% are returned.
%
% Use as
% label = ft_select_channel(h, eventdata, ...)
% The first two arguments are auto... |
9f2efdbeeee31d4ea87213cdafc41818b1651a7169b6a54b490e14139170a94c | MATLAB | 8,593 | 210 | load(fullfile(dipole_folder, strcat(patno,'_',model_name,'_',dipole_name, ...
'_output_charge_solution')));
%% load additional colormaps
addpath(fullfile("../engines/Colormaps"));
%% XY transverse cross section
% Prepare plane data
planeABCD = [0 0 1 -Z]; % Equation of the plane of the cross-section... |
44c6007fdd23aa481a9b31eb7134a54235b6f6034c399e191d2f0d8ea1b4b601 | MATLAB | 8,594 | 223 | function SelectTrackingAlgorithm(varargin)
% SelectTrackingAlgorithm(lObj,hPar)
% GUI for selecting a deep learning tracking algorithm. After
% selection, it will create a new tracker with the function
% lObj.trackMakeNewTrackerGivenNetTypes(nettypes)
if nargin == 2 && isa(varargin{1},'Labeler'),
lObj = varargin{1}... |
68406a6ba2d3a22d3ac8bde45056567d2e3902b410c623d693751c6b0e9d2196 | MATLAB | 8,594 | 217 | function [spikes] = bz_LoadPhy(varargin)
% Load kilosort/phy clusters
%
% USAGE
%
% [spikes] = bz_loadPhy(varargin)
%
% INPUTS
%
% basepath -path to recording (where .dat are)
% kilosort_path -path to kilosort* folder after phy curing (by default
% .\kilosort_\)
% getWaveforms -logical (... |
c85bd9fa2a3156ea140ff9a15eddfa9890880587dd224e97d2101a4eaef37ef0 | MATLAB | 8,595 | 150 | format compact;
Int_main_folders = ''; % main working directory
ShortNames = {'R1_6hr','R1_24hr','R1_72hr','R2_72hr','R2_24hr','R2_6hr'};
Int_Results_folders = {}; % folders to save the results
Int_RawImage_folders = {'Folder1', 'Folder2', 'Folder3', 'Folder4', 'Folder5', 'Folder6'}; % Raw Tiff image folders
for... |
0e8a4870dcd68eb527e385e1cdc04fb501bec72dd2aca2046a2ea0a32730d227 | MATLAB | 8,598 | 215 | function ft_select_channel(handle, eventdata, varargin)
% FT_SELECT_CHANNEL is a helper function that can be used as callback function
% in a figure. It allows the user to select a channel. The channel labels
% are returned.
%
% Use as
% label = ft_select_channel(h, eventdata, ...)
% The first two arguments are auto... |
335c94a64048babdde4b0cda9bdf799c29b874cd5152884035faa2b29a08d2b9 | MATLAB | 8,601 | 200 | function lambdas = hessianspectrum(problem, x, usepreconstr, storedb, key)
% Returns the eigenvalues of the (preconditioned) Hessian at x.
%
% function lambdas = hessianspectrum(problem, x)
% function lambdas = hessianspectrum(problem, x, useprecon)
% function lambdas = hessianspectrum(problem, x, useprecon, stor... |
f35e9ffc5f0d7d6dcdcf639d97b77003e409ff7baf903bf46626c5c4ef820493 | MATLAB | 8,603 | 192 | function varargout = DPABINet(varargin)
% DPABINET MATLAB code for DPABINet.fig
% DPABINET, by itself, creates a new DPABINET or raises the existing
% singleton*.
%
% H = DPABINET returns the handle to a new DPABINET or the handle to
% the existing singleton*.
%
% DPABINET('CALLBACK',hO... |
116e65806bfe37894bdd41aa1ad22c207e4f61cea01737a72ab49aa317ec7a11 | MATLAB | 8,605 | 247 | function [ACC sensitivity specificity avg_SNR] = harmonic_osc_simulation_TACC_v5(sim_param)
warning('off');
ACC = [];
sensitivity = [];
specificity = [];
%% simulation details for this video
srate = sim_param.srate; % sampling rate in Hz
time = -1:1/srate:4;
pnts = length(time);
osc_amp = sim_param.osc_amp*2;
... |
e744c81cf0137052959f816fdcc23cdcbf235b56638ada2604e2d6394fe8788b | MATLAB | 8,606 | 212 | %% Split NIFTI volumes by major region boundaries
% be aware that neighboring labels will be included as this is just copying a bounding box
% this will include some duplication of labels as well as bstem, and hc
% will have labels from the ctx; cereb will have some labels from bstem
% etc..
vol = niftiread("T:\... |
6dc91d849c4ad5d0013d4db6750a4c5861f804d6abab0fb24f5bbd8948282258 | MATLAB | 8,619 | 202 | function network = create_network(modelParam, varargin)
% network = create_network(modelParam)
%
% Generates the network structure.
%
% Inputs:
% - modelParam: Structure containing model parameters
%
% Optional:
% - seed: random number generator seed
%
% Output:
% - network: The network structure for a given net
... |
ed43ecc8db7c5956b16f6313d146ae49bc09514571d03e68eff97de8c2d48c56 | MATLAB | 8,620 | 231 | % Optional 4th step of the multivariate moderation model framework
%%% Bootstrapping on the voxels' moderation (CR) coefficients %%%
% The idea is to reduce the fMRI contrast in the chosen voxels to a number
% of principal components and use them in a multivariate regression. The
% regression weights are then be map... |
9db0a5c3e578b06e38e74c6058ce6460f1720da3630704d0a6eb08aa307692ca | MATLAB | 8,622 | 281 | function [ CF ] = Cost_Function (xopt)
NineMuscleMorphParaInitial = load('NineMuscleMorphParaInitial.mat');
NineMuscleMorphParaInitial = NineMuscleMorphParaInitial.NineMuscleMorphParaInitial;
G = 4; % Muscle Group Number (G = 1 to 9)
MotionData = load('MotionData.mat');
MotionData = MotionData.MotionData;
% 40 Mu... |
b9877f49dfb244d1924f734b92e1cc6c5a339e45396f421759fee94870015250 | MATLAB | 8,622 | 259 | function [results]=VBA_Shapley(posterior,out,varargin)
% [results]=VBA_Shapley(posterior,out,[options])
%
% Compute the Shapley values of the model's factors (inputs or paramters).
% These scores measure the relative influence of these factor on the variaince
% explained by the model.
% ------------------------------... |
140e412bc0a3f0921f43105d06804fc9f3a1191c096f4a803e1f099ab3d65f8e | MATLAB | 8,629 | 256 | function [eout,thresh] = coloredge(a,varargin)
%COLOREDGE Find edges in intensity image.
% EDGE takes a color image I as its input, and returns a
% binary image BW of the same size as I, with 1's where the function
% finds edges in I and 0's elsewhere.
%
% COLOREDGE uses the Canny method for edge detection:
%... |
814955838b27e6da36197c30ff0c1ed2abe170a0ca9f6933c6191cd4d1871f30 | MATLAB | 8,630 | 210 | % Second-kind integral equation on the unit sphere, Laplace double-layer.
%
% This example solves the Dirichlet Laplace problem on the unit ball by using a
% double-layer potential, which yields a second-kind boundary integral equation
% on the unit sphere, represented using flat triangles. The system is
% discretized ... |
14629f8be720d3770907ba553790fe46e325c6f183ca8c4a55f7b5f99879f331 | MATLAB | 8,633 | 273 | function [flags,keyvals,varargout] = SOFAarghelper(posdepnames,definput,arglist,callfun)
%SOFAARGHELPER Parse arguments for SOFA
% Usage: [flags,varargout] = SOFAarghelper(posdepnames,definput,arglist,callfun);
%
% Input parameters:
% posdepnames : Names of the position dependant parameters.
% definput... |
414012777ce690695c152e518e65356926dbf03c756e17858dfd72c35423c544 | MATLAB | 8,637 | 218 | % AUTHORSHIP
% Primary Developer: Stephen Meehan <swmeehan@stanford.edu>
% Math/Statistics: Connor Meehan <connor.gw.meehan@gmail.com>
% Guenther Walther <gwalther@stanford.edu>
% Primary inventors: Wayne Moore <wmoore@stanford.edu>
% David Parks <drparks@stanford.edu... |
df5adf44f94b53f1ef5ce0329df6c7209d6ea8f336e3836d621caa9c949e3184 | MATLAB | 8,637 | 229 | function low_rank_matrix_completion()
% 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... |
f9b1c3d6ec9928a60026ea2b25f23dfd5f2e07146e7e689caab503b7583115d8 | MATLAB | 8,640 | 189 | clear;
%%
% This script creates ten files: In current directory (can move them
% later)
% 1) significat network for group1 (matlab data file)
% example: patients_group_13-29Hz_signetwork_cerebellum.mat
% patients_group_<freq>_signetwork_<network>.mat
% 2) significat network for group2 (matlab... |
83f2397336c33f29962bc9fb397d736874c8462b381c56aa410622f7101e25e5 | MATLAB | 8,647 | 212 | function [X_rows, X_cols, F_rows, F_cols, N_rows, N_cols] = fdct_wrapping_param(C,M,N)
% fdct_wrapping_param.m - Gives the location of each curvelet in phase space
%
% Inputs
% C Cell array containing curvelet coefficients (see
% description in fdct_wrapping.m)
% M, N Size of the ori... |
46a831a8d48d90b2a4bd7cb6d35b64da7524301a77ad15c9965650d98622c0be | MATLAB | 8,652 | 212 | function GonzalezPereyra_etal_Fig_07
Color_300=[3 168 158]./255;
Color_500=[0 85 212]./255;
ThisColors=[repmat(Color_300,5,1);repmat(Color_500,5,1)];
newColors=[Color_300;Color_500];
%load /Users/pavel/LocalDocuments/Data/MiceRecordings/Data_GonzalezPereyra_etal_Fig_07.mat %#ok<*LOAD>
load ([pwd '/Data_Gonzal... |
0352af4b8c3622cb6b3c71d23f8fa0d8d430e910215291f69a8ae566969df7ee | MATLAB | 8,656 | 256 | function [eout,thresh] = thresholdBSE(a,mag,varargin)
%COLOREDGE Find edges in intensity image.
% EDGE takes a color image I as its input, and returns a
% binary image BW of the same size as I, with 1's where the function
% finds edges in I and 0's elsewhere.
%
% COLOREDGE uses the Canny method for edge detec... |
9289eeff615bb0d2b5399b48abf3073b8127708a0218f8589764a5b79a0efa1c | MATLAB | 8,657 | 266 | function PlotFigure3(timelock)
% plot mean ERP, difference waves, diff-difference waves
% mean ERPs, indiv-pp mean ERPs, and regressions of means vs beh, a
if nargin==0
timelock = 'Figure 3 - Source Data 1.mat';
end
if regexp(timelock, '.mat')
% try loading this as a file name
data... |
a02de3d09aaf1b277fb51263b73c1f4913d95a12a7c2f2962ff2e8f05dd9f56c | MATLAB | 8,661 | 235 | % Author: Daniel J. Beall
% Email: DJBEALL1101@gmail.com
%
% beall_horizontal() - Returns list of ICA components marked with
% horizontal eye movement
%
% Usage:
% >> [horizontal] = beall_horizontal(cwb,topog,chanlocs,n);
%
% Inputs:
% cwb - list of components with bumps
% t... |
5cec234bfa1fa2a41ab541ff06e51511bd03dfbaf58646b415d8448ca11964f4 | MATLAB | 8,664 | 253 | function corr_mat_parcelOrder = CBIG_ASDf_Plot400Schaefer19Subcor17Networks_thresholded(corr_mat_row, ...
scalelim, filename_prefix, blk_indices)
% corr_mat_parcelOrder = CBIG_ASDf_Plot400Schaefer19Subcor17Networks_thresholded(corr_mat_row,
% scalelim, filename_prefix, blk_indices)
%
% Plots thresholded 419x419 matri... |
45dce03296a78424d056498466e5f69dbd479aa0a59cfcf0a726cadee7a1ddbf | MATLAB | 8,665 | 231 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% To get the 2d coordinates of EMG channels over the grid
% To check the EMG signals (automatic or visual)
% Input:
% signal: row-wise signal
% gridname: name of the OTB grid of electrodes
% check EMG: 1 = Visual checking of EMG channels
% O... |
c2ceadedbf1e3ad3aecbcba9638e14a5978484568393c7eea61a6c0b80246493 | MATLAB | 8,669 | 241 | function [stats,st] = lme_mass_fit(X,Xcols,Xrows,Zcols,Y,ni,prs,e)
% [stats,st] = lme_mass_fit(X,Xcols,Xrows,Zcols,Y,ni,prs,e)
%
% Location-wise linear mixed-effects estimation. Allows to have different
% models across locations (this is useful when there are either missing
% values at some locations or the number o... |
cee03793c6f8f1bf82ef90b8d02b7acdefd184e5e9163e7f2c4095ccaeb7320d | MATLAB | 8,671 | 208 | % Author: Birgit Nierula
% nierula@cbs.mpg.de
function esg_preprocessing_loops(loop_number, subjects, conditions, srmr_nr, sampling_rate)
switch loop_number
case 1
%% loop 1: prepares data
% loads raw bids data
% removes stimulus artifact
% downsample to sampling rate of R-pea... |
7a73ae51392ffc56e5fec314c9062097b55ef4d9e7ec4afc6b8ce42f4492fd83 | MATLAB | 8,676 | 303 | function varargout=sigstar(groups,stats,nosort)
% sigstar - Add significance stars to bar charts, boxplots, line charts, etc,
%
% H = sigstar(groups,stats,nsort)
%
% Purpose
% Add stars and lines highlighting significant differences between pairs of groups.
% The user specifies the groups a... |
1944343770d1dcc862451eb4df35b3f96298f449f41865dee55bd1015c95c2a3 | MATLAB | 8,681 | 213 | function data = load_microscopy_file_FramesCut()
%%%%%% file type can be either "bin", "locb" or "csv".
%%%%%% example: data = load_microscopy_file('bin');
%%%%%% example: data = load_microscopy_file('locb');
%%%%%% example: data = load_microscopy_file('csv');
[file_names,path] = uigetfile({'*.bin;*.locb;*.csv'},'... |
df35ee12e3953acfd299b90a8fb0002a43d961ed9c7571ac90c199edbc27674b | MATLAB | 8,684 | 168 |
function [glob_avg1,glob_avg2,glob_avg3,glob_avg4,glob_avg5,glob_avg6] = assembly_trig_avg_pool (traces, pyr_id, int_id, si_img, TRace, RasterRace, CellCl, PCl, C0)
windowSize = 200; %in frames
x = -windowSize/2:1:windowSize/2;
n_int_in_assembly = sum(sum(CellCl(:,int_id)));
pyr_out_assemblies = intersect(pyr_id,fi... |
02ce47d3ffbd4d59b8a86a5ef5c55d6bd5068d0611f6a82d83de698bb3bb9757 | MATLAB | 8,685 | 274 | function plotBrain(regions, values, cm, varargin)
% PLOTBRAIN Create simple line-art SVG brain plots.
%
% PLOTBRAIN(REGIONS, VALUES, CM) creates brain plot with regions having
% colors as specified by the REGIONS and VALUES vectors with a colormap
% defined by the matrix CM. Colormap CM can have any number of rows, but... |
4e2ff054ad8e249f7b7639bda4f13194df93f5fbc27377ab5ef719e1ef49a1ac | MATLAB | 8,687 | 188 | function [EEG,com] = pop_detect_spindles(EEG)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Detect Spindles in EEG data
%
% INPUT: EEG = EEGLab structure
% PARAM = structure of parameters (see below)
%
% OUTPUT: EEG = same structure with spindle markers (EEG.event)
% ... |
4411c978ac13bf064ca199890f8af7be3202de8c8d2106260575648e2e15231e | MATLAB | 8,689 | 193 | %% Sort data based on the cue and stimulation in each trial
function [ xhat, xhat_] = SortData(data, dataType)
% Sort data based on the cue and stimulation in each trial and store in two
% structs, xhat for perceived pain and xhat_ for expected pain. Each struct
% has fields for different conditions:
% If dataType = ... |
0eed742cf2935b5497fbe61ff1329d572e5f6093fc2d8012212c51ab8bfc63fa | MATLAB | 8,711 | 230 | %% pxTools_getTrialwisePxt
% Generates probability distributions from the supplied timeseries
% data cell ('xtDataCell'), using the queried time points and parameters.
% Used for multiple-comparisions/extractions. Not optimial for single
% comparisions
%
% PREREQUSITE: xtDataCell has been processed by 'createXtStateMap... |
77c1d5a6edf47fb902fc8e71cd44921e5ae5296e41ecf8668a8b551940f13745 | MATLAB | 8,716 | 229 | function subjExtractedTimeSeries = getBadVols(eyeClosureFile,TR,subjExtractedTimeSeries)
%SETBADVOLS This function identifies indices of "bad volumes" as determined
%by eye closure onsets
% EDIT BY PNT 06/23/23: implemented cleaning and merging eye closures
%Rules:
% 1. In SBU data, if the eye clo... |
9c8383cc34c885bbbe89b81dacee49ac29978ea79b9e79b32577483528bdb681 | MATLAB | 8,724 | 322 | function spm_movie(Action,Orient,F,p,nloops,mode)
% Runs a movie of a plane from a series of images
% FORMAT spm_movie
%
% This is a simple command-line utility which you can use if you
% wish.
%
% The movie can be displayed as transverse, coronal or sagittal
% in movie mode or slider mode which allows slide selection ... |
7905ef60dc7424661b8826f2d7c24e03ec2dccd6a4ba63b63b7172db66495fc1 | MATLAB | 8,726 | 274 | %PMTKauthor Jarno Vanhatalo
% Same as demo_spatial1 from GPstuff-2.0 except
% we only run Laplace, not MCMC, for speed
%DEMO_SPATIAL1 Demonstration for a disease mapping problem
% with Gaussian process prior and Poisson likelihood
%
% Description
% The disease mapping problem consist of a dat... |
367140901fa6f6aaca7d212dd46daa71675a4c55077cb3507eeef150399f8cfe | MATLAB | 8,729 | 308 | function SPT_analysis_entries_Ca(basename)
miniscope_data=load([basename '_Test.mat']);
fs3=20;
temp_fields=fieldnames(miniscope_data);
% if length(temp_fields)==1
% miniscope_data=miniscope_data.data;
% end
traces = miniscope_data.AllData;
FR2 = traces;
trk = load([basename '_Test_trk.mat']);
... |
eb11302b7ef30ac42d0fbecbc5b216e620dfb85fb623d207feccdb1fd1984af2 | MATLAB | 8,733 | 343 | function wlPlot_plotMatrixErrorStats(cfg, serieslist, figtitle, filelabel)
% function wlPlot_plotMatrixErrorStats(cfg, serieslist, figtitle, filelabel)
%
% This function creates bar plots and scatter-plots of specified error
% metrics for a specified series of event matrices.
%
% Bar plots show a histogram of event co... |
b630d665ca78c6c8da0198387ff9876bbe4bbf28ac2153225f25680888e1dc25 | MATLAB | 8,734 | 203 | % boney_eval_readCSV. Read and evaluate CSV files to setup parameters.
%
% _________________________________________________________________________
%
% Robert Dahnke & Polona Kalc
% Structural Brain Mapping Group (https://neuro-jena.github.io)
% Departments of Neurology and Psychiatry
% Jena University Hospital
% ____... |
0a8d09d9bd86a2dcc7b335ea56aae94e6cf20aaa72976514b838ab299557405c | MATLAB | 8,735 | 221 | %%Open tiffs of separate channel stacks to show mult-color max projection.
%%This script assumes that each channel is separated into it's own stack
%%and is in .tiff format. This script is formatted for 3 channels
%%currently, and can be adjusted to fewer or more channels if desired.
clear;
file0 = 'filename'; %Enter ... |
f77bbda5d1a61ec2e0b2b8714e5e405ff5b69e3e8b4ac7369b3ab67c0d30cde6 | MATLAB | 8,742 | 223 | function varargout = w_ApplyVertexMask(varargin)
% W_APPLYVERTEXMASK MATLAB code for w_ApplyVertexMask.fig
% W_APPLYVERTEXMASK, by itself, creates a new W_APPLYVERTEXMASK or raises the existing
% singleton*.
%
% H = W_APPLYVERTEXMASK returns the handle to a new W_APPLYVERTEXMASK or the handle to
% t... |
12234175ba58b9a56a7d75de6fb83acac09113d8b8eebd58643813de42e20d79 | MATLAB | 8,744 | 307 | function varargout=sigstar(groups,stats,nosort)
% sigstar - Add significance stars to bar charts, boplots, line charts, etc,
%
% H = sigstar(groups,stats,nsort)
%
% Purpose
% Add stars and lines highlighting significant differences between pairs of groups.
% The user specifies the groups an... |
b89f1d890653c3a4eeb5cd61f363d06b6fc29ce257bb291dc0e3a57339fb1bb5 | MATLAB | 8,746 | 297 | %% Overview
%
% Here we load in our source parcellated MEG data from the preprocessing stage,
% perform some normalisation and compute an Time-Delay-Embedded HMM.
%
config = utils.get_studydetails;
%%
% Find preprocessed data files
datapath = fullfile( config.analysisdir,'spm_sss_processed' );
s = study(datapath,'Gi... |
602c20f7207905561a044217623e81b7434013e23e4d78f99658d85943dbb966 | MATLAB | 8,748 | 260 | % Author: Birgit Nierula
% nierula@cbs.mpg.de
function figure_stackedplot_seps(condition, srmr_nr, subjects)
% set path
savepath_ga = getenv('GADIR');
% condition info
cond_info = get_conditionInfo(condition, srmr_nr);
cond_name = cond_info.cond_name;
nerve = cond_info.nerve;
str_stimulation = cond_info.str_stimulat... |
353be6d87f298adebc6664d8b582579c9100058a0b8c6eb1ba5a2b8540d16ace | MATLAB | 8,752 | 199 | classdef monteCarloSimulation
%monteCarloSimulation This class includes all properties and methods
%related to the Monte Carlo simulation in an MCmatlab.model.
properties
%% Input properties
silentMode (1,1) logical = false % Disables command window text and progress indication
useAllCPUs (1,1) logic... |
5809cab6f6037ae6558cbfbe2d269dc438526ce5d00f0b515c0a6351dfdbdef3 | MATLAB | 8,752 | 236 | % FADE-SAME: Figure S4
clear
% close all
%%% Step 1: load data %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% set results files
FADE_file = '../FADE_scores/FADE_SAME_scores_2021_01_11_FADE_only.xls';
covs_file = 'covariates/covariates_FADE.xls';
% define cohorts
cohs = {'middle-aged' ,'older'};
cohs_cols =... |
99bc71da158ee2d9101cd25fdaf846f22d6ce20c676ef45d2ab024d4291b726e | MATLAB | 8,755 | 212 | function StatsTableExporterFull(Statistics,PvaluesTable,OverallPValue,GroupNames,TestName,SaveDir)
OS=computer;
if strcmp(OS,'MACI64')
dc='/';
else
dc='\';
end
FullLabelTableDisplay=0;
for i=1:length(GroupNames)
GroupNamesNumberedList{i}=[num2str(i),': ',GroupNames{i}];... |
a533177cb42880f9116b4b559fb3860cece7465f8e539b5118c14a1116ab0b74 | MATLAB | 8,755 | 307 | function varargout=sigstar(groups,stats,nosort)
% sigstar - Add significance stars to bar charts, boxplots, line charts, etc,
%
% H = sigstar(groups,stats,nsort)
%
% Purpose
% Add stars and lines highlighting significant differences between pairs of groups.
% The user specifies the groups a... |
1404eb2ec756bd281b694b9dc28d7009ee300d93da7ad1b27cc21dff751d4357 | MATLAB | 8,756 | 256 | function M = grassmanngeneralizedfactory(n, p, B)
% Returns a manifold struct of "scaled" vector subspaces.
%
% function M = grassmanngeneralizedfactory(n, p)
% function M = grassmanngeneralizedfactory(n, p, B)
%
% Generalized Grassmann manifold: each point on this manifold is a
% collection of "scaled" vector s... |
5e4e2e40705e69195e3df1cd30953b9f4ab8c32c5790ea627eed46f70fe22f0c | MATLAB | 8,759 | 239 | function varargout = DPABI_BrainImageNet_Local(varargin)
% DPABI_BrainImageNet_Local MATLAB code for DPABI_BrainImageNet_Local.fig
% DPABI_BrainImageNet_Local, by itself, creates a new DPABI_BrainImageNet_Local or raises the existing
% singleton*.
%
% H = DPABI_BrainImageNet_Local returns the handle to a... |
6733fca9bfcd7d73c1a34ecd0c4b5a9f07c79419ffb61f58e831fdc55ab0353a | MATLAB | 8,762 | 191 | % MotorFindFullBehaviors.m
% Sarah West
% 5/22/22
% Runs with RunAnalysis.m. Uses behavior ranges from
% MotorBehaviorPeriodsTable.m to put together full trainsition behaviors
% (from "warning" to "finished" portions).
function [parameters] = MotorFindFullBehaviors(parameters)
% Load & define full_periods_table.
... |
624571f4db770a411f7e98b5878b7958e8d271fc58e9ce2698099a4a699a1d1b | MATLAB | 8,772 | 308 | function [post,out] = VB_CRP(y,alpha,options)
% function [post,out] = VB_CRP(y,alpha,options)
% VB scheme for the CRP-MoG classifier.
% IN:
% - y : the pxn data matrix, where n is the number of
% 'observations' to be classified, and p is the dimension of each of
% these observations
% - alpha : CRP concentratio... |
6fd199d089bd0992133c0b9ed56d44363b533519b5031c65bfc8312d52c344b6 | MATLAB | 8,772 | 237 | %% Calculate SWI for randNet across nclusters and mnc
% swiGrid.m
addpath(fullfile("..", "..", "src"))
Config = utils.setConfig;
myPlotSettings()
% Select which panel to plot
panelToPlot = '8b'; % 1g, 8a, 8b, 8c
%% Main script parameters
switch panelToPlot
case '1g'
modelParam.conn_prob = 0.08; % Use {... |
2dfa3132476590d516d247138112ba1aa9617fc6f47400a3386063581560f0b6 | MATLAB | 8,774 | 248 | function [data, mri, grid] = nutmeg2fieldtrip(cfg, fileorstruct)
% NUTMEG2FIELDTRIP converts from NUTMEG either a sensor data structure
% ('nuts') to a valid FieldTrip 'raw' structure (plus 'grid' and 'mri' if
% available), OR a source structure 'beam' to a valid FieldTrip source
% structure
%
% Use as
% [data, mri... |
96dc2cb36154ddb2a68889b364dc13a6385ab02ec90b1c6fb9c7893eed2f644d | MATLAB | 8,783 | 251 | function varargout=VBA_spm_platform(varargin)
% Platform specific configuration parameters for SPM
%
% FORMAT ans = spm_platform(arg)
% arg - optional string argument, can be
% - 'bigend' - return whether this architecture is bigendian
% - 0 - is little endian
% - 1 ... |
260afa45e38a16a19163fe14f763d7413c193e3f7f93d259557c62ebf8ae2424 | MATLAB | 8,793 | 191 | function eps2pdf(source, dest, crop, append, gray, quality, gs_options)
%EPS2PDF Convert an eps file to pdf format using ghostscript
%
% Examples:
% eps2pdf source dest
% eps2pdf(source, dest, crop)
% eps2pdf(source, dest, crop, append)
% eps2pdf(source, dest, crop, append, gray)
% eps2pdf(source, de... |
f6a9280623e14b9a6b58e5d2368fadf5882ee8a49df813205834205ce98a710e | MATLAB | 8,806 | 167 | function varargout = DPARSF_main(varargin)
% DPARSF_MAIN MATLAB code for DPARSF_main.fig
% DPARSF_MAIN, by itself, creates a new DPARSF_MAIN or raises the existing
% singleton*.
%
% H = DPARSF_MAIN returns the handle to a new DPARSF_MAIN or the handle to
% the existing singleton*.
%
% D... |
856358107f176db08b75fc7b55198a5919ae1a49395486ed8a90c23da544f9f2 | MATLAB | 8,810 | 210 | function embedding = trans2_optimize_layout(head_embedding, tail_embedding, ...
head, tail, n_epochs, n_vertices, epochs_per_sample, a, b,...
gamma, initial_alpha, negative_sample_rate, verbose, min_dist, move_point)
%OPTIMIZE_LAYOUT2 Another version of optimize_layout.m that slightly
% optimizes the speed for ... |
318f62c6a518d4b9f2109d8a4b624a13ab961a23e653153b67c7403311622329 | MATLAB | 8,815 | 222 | %% Read two greyscale images of Lena
imgDir = '/Users/paultillberg/Documents/MATLAB/Image registration/SIM before after from Fei 140109/';
Iafter=imread([imgDir 'B5_3_3_MAX_After.tif']);
Ibefore=imread([imgDir 'B5_3_stack_MAX_before.tif']);
%Scale both images to max pixel value for uint16
Ibefore = uint16(... |
84f91861fff3dcb05e6e6fdb53250ca3daacd2c931eba9858eb63cbbb07090b4 | MATLAB | 8,819 | 281 | % HIFDE2 Hierarchical interpolative factorization for differential equations
% with nearest-neighbor interactions on a regular mesh in 2D.
%
% This is an optimization of HIFDE2X for the special case of nearest-neighbor
% interactions on a regular mesh. A given mesh node is allowed to interact
% only w... |
ed8d4c307cb5b0f845ec3fcf41336faace987fd837c9f9a86f5ef41669497943 | MATLAB | 8,825 | 209 | function embedding = optimize_layout2(head_embedding, tail_embedding, ...
head, tail, n_epochs, n_vertices, epochs_per_sample, a, b,...
gamma, initial_alpha, negative_sample_rate, verbose, min_dist)
%OPTIMIZE_LAYOUT2 Another version of optimize_layout.m that slightly
% optimizes the speed for MATLAB; in particu... |
d35f078b0ce6c065e9b04031b4f37179b2684549d1af233516739b07bb088cb1 | MATLAB | 8,826 | 188 |
clear
% close all
Monkey = ['Monkey2']; % ['Monkey1' or 'Monkey2']
%----------------------------
Base = ['PER_ON']; %'Fig_ON' 'PER_ON'
%----------------------------
Align = [{'GO'} {'MOV'}];
% ---------------------------
SIGNAL = 'Difference' % 'Difference' 'Beta' 'Gamma'
% -------------... |
fa3d9fa929aadc743223f5cab9603f1fd1f11e987e0b5d66b49f269e1057c8e1 | MATLAB | 8,828 | 248 | % Imports
addpath("HelperFunctions")
load(fullfile(DataPath, "WeberData.mat")) % Weber fraction
load(fullfile(DataPath, "AmpDiscrim.mat")) % ICMS amp discrim
load(fullfile(DataPath, "AmpDiscrimBioLin")) % Amp discrim bio vs lin
load(fullfile(DataPath, "MechAmpDiscrim.mat"))
load(fullfile(DataPath, "MagEstBiovsLin.mat")... |
85d589a74886e58c1f0a609a499f92e1bda9e510ba8bbe18c598a6eb37113697 | MATLAB | 8,831 | 279 | % Author: Birgit Nierula
% nierula@cbs.mpg.de
function figure_spinalTFplots(subjects, condition, is_evoked)
% set path
savepath_ga = getenv('GADIR');
% condition info
srmr_nr = 1;
cond_info = get_conditionInfo(condition, srmr_nr);
cond_name = cond_info.cond_name;
nerve = cond_info.nerve;
trigger_name = cond_info.tri... |
ce134c652cf128d29148ab6955dd54a522c1b172c9a62a1b7a20e9d90429737b | MATLAB | 8,832 | 208 | function [cfg] = ft_topoplotIC(cfg, comp)
% FT_TOPOPLOTIC plots the topographic distribution of an independent
% component that was computed using the FT_COMPONENTANALYSIS function,
% as a 2-D circular view (looking down at the top of the head).
%
% Use as
% ft_topoplotIC(cfg, comp)
% where the input comp structure ... |
5b45e724fd1ad2c9ac174f039a5ffc7c025ca69d8183ab0ff37d6729f9fc96b5 | MATLAB | 8,840 | 257 | function ROCdata=roc(varargin)
% ROC - Receiver Operating Characteristics.
% The ROC graphs are a useful tecnique for organizing classifiers and
% visualizing their performance. ROC graphs are commonly used in medical
% decision making.
% If you have downloaded partest
% http://www.mathworks.com/matlabcentral/fil... |
d983dc182e3163d6b8ebca2b3153db829dc8773456a2c64797fd2da4493e4111 | MATLAB | 8,840 | 254 | function pmlFigureCodeReport(dest, includeEx, includeSol)
%% Generate an html report of figures in PML and their source files
%
%% Inputs
%
% dest - this script creates a whole directory structure, specify the root
% destination.
%
% includeEx - [false] if true, pml exercises are included
% includeSol - [... |
e2e4a5385336f88dcb1767eecef6b36e81a0406f21f32e6120cc944449c1bac1 | MATLAB | 8,841 | 254 | function [mt_grid, mt_length, mt_state, grids, growths] = simTauMap6(params)
%SIMTAUMAP6 Summary of this function goes here
% Detailed explanation goes here
%% Load and validate inputs
% load params via input parser
input = inputParser;
addRequired(input, 'params', @(x) isstruct(x) && ~isempty(x));
parse(input, para... |
e6d3dc3ea147c5fb5585bf79932da105c01c844fd79b52a457d8d89b603ff6fe | MATLAB | 8,841 | 224 | function [freq] = ft_freqdescriptives(cfg, freq)
% FT_FREQDESCRIPTIVES computes descriptive univariate statistics of
% the frequency or time-frequency decomposition of the EEG/MEG signal,
% thus the powerspectrum and its standard error.
%
% Use as
% [freq] = ft_freqdescriptives(cfg, freq)
% [freq] = ft_freqdescrip... |
805050e5b71147c38593ca2711843ea409302f343db8e67ea8bf62fcab2f1373 | MATLAB | 8,844 | 226 | function STATS = cuzick(x,varargin)
% CUZICK: Perform the Cuzick's test on trend.
% This function provides a Wilcoxon-type test for trend across a group of
% three or more independent random samples.
%
% Assumptions:
% - Data must be at least ordinal
% - Groups must be selected in a meaningful order i.e. ordered... |
e7c68f6bb2164695ac943788a28ef4402f5ff3d81d891736d8ce8703b0374043 | MATLAB | 8,844 | 279 | function [posterior,out] = VBA_onlineWrapper(y,u,f_fname,g_fname,dim,options)
% online VB inversion of nonlinear stochastic DCMs
% function [posterior,out] =
% VBA_onlineWrapper(y,u,f_fname,g_fname,dim,options)
% This function inverts a nonlinear state-space model 'on line', i.e.
% estimate hidden states, observation/e... |
97d1ab2395a1ef11dac13677c137d4e6375c654c05ba43497c57dfc36eac92d1 | MATLAB | 8,849 | 282 | function M = productmanifold(elements)
% Returns a structure describing a product manifold M = M1 x M2 x ... x Mn.
%
% function M = productmanifold(elements)
%
% Input: an elements structure such that each field contains a manifold
% structure.
%
% Output: a manifold structure M representing the manifold obtai... |
e7e6827c9d7e8ceacaa6663f636d64dac8b81e897a891f2df92c1b0249966afb | MATLAB | 8,851 | 237 | function [response, timing, quitProg] = showScanStimulus(display,...
stimulus, t0, timeFromT0)
% [response, timing, quitProg] = showStimulus(display,stimulus, ...
% [time0 = GetSecs], [timeFromT0 = true])
%
% Inputs
% display: vistaisp display structure
% stimulus: vistadisp stimulus struc... |
668487bbf9903331e65ce173da65e581b7d6d84cfbdabb7a1661cc5a54e55508 | MATLAB | 8,853 | 215 | function [cfg, artifact] = ft_artifact_clip(cfg, data)
% FT_ARTIFACT_CLIP scans the data segments of interest for channels that
% clip. A clipping artifact is detected by the signal being completely
% flat for some time.
%
% Use as
% [cfg, artifact] = ft_artifact_clip(cfg)
% with the configuration options
% cfg.da... |
80a36f19163e9cdd22116c820a4dcfa625af28de65658599a767158474951bbe | MATLAB | 8,856 | 196 | %% This is the script that generates the sectored colony images
%% Steps for each training image
% 1. Create background of the table color
% 2. Create inner circle
% 3. Color inner circle with the plate with the same color as the plate
% 4. Plot colonies whose centers are in the inner circle and match the
% c... |
237acb634aac20bb3aea7dff025e6149e01dbd2d1f1107caa4cf2abb0074de35 | MATLAB | 8,860 | 259 | function [combined] = ft_appendlayout(cfg, varargin)
% FT_APPENDLAYOUT concatenates multiple layout descriptions that have been constructed
% separately.
%
% Use as
% combined = ft_appendlayout(cfg, layout1, layout2, ...)
% where the input layouts result from FT_PREPARE_LAYOUT and the configuration
% should contain
... |
e44cc76bc127885b7cec9bb783b4559dcc7340b717646f56cef6481f1dade8de | MATLAB | 8,860 | 213 | load(fullfile(dipole_folder, strcat(patno,'_',model_name,'_',dipole_name, ...
'_output_charge_solution')));
%% load additional colormaps
addpath(fullfile("../engines/Colormaps"));
%% XY transverse cross section
% Prepare plane data
planeABCD = [0 0 1 -Z]; % Equation of the plane of the cross-section... |
ca1a177b377416d8d4c40a0478a9e0d21d947aa3aabe5647a82f3711835a353f | MATLAB | 8,866 | 247 | function varargout = w_ClusterSize(varargin)
% W_CLUSTERSIZE MATLAB code for w_ClusterSize.fig
% W_CLUSTERSIZE, by itself, creates a new W_CLUSTERSIZE or raises the existing
% singleton*.
%
% H = W_CLUSTERSIZE returns the handle to a new W_CLUSTERSIZE or the handle to
% the existing singleton*.
%
% ... |
ceac1832e1302cdeb156d8c02ecbe8fef58a3bab4c0ab8aa5be5072c815e1638 | MATLAB | 8,867 | 214 | function [spectrum,freqoi,timeoi] = ft_specest_hilbert(dat, time, varargin)
% FT_SPECEST_HILBERT performs a spectral estimation of data by repeatedly applying a
% bandpass filter and then doing a Hilbert transform.
%
% Use as
% [spectrum,freqoi,timeoi] = ft_specest_hilbert(dat,time,...)
% where
% dat = matri... |
eed7d07a0c2f6e1afcf0d4f26b054ddb69cb64b1f7a1f89f3b67a7acaac6f188 | MATLAB | 8,867 | 324 | function graphviz(adj, varargin)
% Calls graphviz to generate a pretty layout of an adjacency matrix
% You must first install graphviz from http://www.graphviz.org/
% This function converts the adjmat to a .dot file,
% and then calls graphviz to generate a .ps file.
% Finally we convert this to a .pdf file.
% Unlike gr... |
751f48c46ba50a711088aca3e6459aecefcaa7188bad596c797918db6228f5e6 | MATLAB | 8,870 | 226 | function [LF2B, HF2B, B2LF, B2HF] = BHImodel(TFR_EEG, TFR_HRV_HF, TFR_HRV_LF, time, t_RR, FS, RR, window)
% This function quantifies directional Brain-Heart Interplay (BHI)
% through the model proposed by Catrambone et al.(2019) [1].
% INPUT variables:
% TFR_EEG = Time course of EEG power spectral density (PSD). This... |
2a8b8a2b959141ae355ae940e306849beb3802e12fec585effe179b9ab4a0fd0 | MATLAB | 8,873 | 227 | function [dat] = read_neuralynx_ds(dirname, hdr, begsample, endsample, chanindx)
% READ_NEURALYNX_DS reads multiple single-channel Neuralynx files that are
% all contained in a single directory. Each file is treated as a single
% channel of a combined multi-channel dataset.
%
% Use as
% [hdr] = read_neuralynx_ds(dir... |
9f4e6729d399aa929fc8a2827b98426e39b94d7cd76e0081e585e3e888fb5f0a | MATLAB | 8,875 | 228 | function [dat] = read_neuralynx_ds(dirname, hdr, begsample, endsample, chanindx)
% READ_NEURALYNX_DS reads multiple single-channel Neuralynx files that are
% all contained in a single directory. Each file is treated as a single
% channel of a combined multi-channel dataset.
%
% Use as
% [hdr] = read_neuralynx_ds(dir... |
a109f72f26c8769a5abcb912707dc1d179dfbe4a972ec90b338d379c14feba39 | MATLAB | 8,878 | 321 | function [chansel, trlsel, cfg] = rejectvisual_trial(cfg, data)
% SUBFUNCTION for ft_rejectvisual
% determine the initial selection of trials
ntrl = numel(data.trial);
trlsel = true(1, ntrl);
% determine the initial selection of channels
nchan = numel(data.label);
chansel = true(1, nchan);
% compute the samplin... |
381f8a000f3cbcc16d06580ddbe558dea8f7200642f1da1cefc669aaeab51e60 | MATLAB | 8,880 | 249 | function [data, mri, sourcemodel] = nutmeg2fieldtrip(cfg, fileorstruct)
% NUTMEG2FIELDTRIP converts from NUTMEG either a sensor data structure
% ('nuts') to a valid FieldTrip 'raw' structure (plus 'sourcemodel' and
% 'mri' if available), OR a source structure ('beam') to a valid FieldTrip
% source structure.
%
% Use a... |
4e7a75c62812719dab9ebf371cb1aa32054e8a805037faca40407b046ce73794 | MATLAB | 8,880 | 220 | %% To make data matrix and design matrix for NBS exercise
% modified from NBS_sam by Sonya - May 9, 2018
% modified by Liz - Sept 2018, Jan 2020
% load path to parpticipant data matrix files for participants
spath = '/mnt/sda/juanita/MEGneto/analysis/Right/analysis';
%% create data matrix - PLI adj. matrix (subjects... |
f2546cb2d706b817dea4b1a2cb1f1cc64b960114dc40055ec3527862c3193167 | MATLAB | 8,886 | 166 | classdef geometry
%GEOMETRY This class contains all properties related to the geometry of
%an MCmatlab.model.
% This class defines the properties of a geometry to be used in a
% monteCarloSimulation, fluorescenceMonteCarloSimulation or
% heatSimulation.
properties
silentMode (1,1) logical = false... |
8c1f82486b963080e9db432e0d92095c87526b6e347d3978485430dc8cfd5331 | MATLAB | 8,893 | 242 | function [conjunction] = ft_conjunctionanalysis(cfg, varargin)
% FT_CONJUNCTIONANALYSIS finds the minimum statistic common across two or
% more contrasts, i.e. data following ft_xxxstatistics. Furthermore, it
% finds the overlap of sensors/voxels that show statistically significant
% results (a logical AND on the mask... |
45e1a7a6834890308599af187b3652d6f68451d2126707df8edb2b142a8996dd | MATLAB | 8,905 | 196 | function[vect_PO, vect_POCI_dist, vect_POCI, CI_under_45, OS, OS_CI, OSnn, OSnn_CI, vect_PD, pref_stim, pref_stim_resp, DS] = ...
vect_PO_boot(mean_resp_dir_rep,stim_dir_correction,showplot)
% in order to keep rep number equal across stims, if there is a nan in a
% rep for any stim, that whole rep is removed
m... |
2975102680d8df4a3d34be3a9e0c434a0782b776eaa6b4d9b6166b92937205ff | MATLAB | 8,906 | 255 | function [fx] = f_AVL(x,Theta,u,in)
% OTO: associative learning evolution function
% function [fx] = f_AVL(x,Theta,u,in)
% This function implements the VB recognition of audio-visual cue/outcomes
% pairs (it learns about the cue/outcome association). The recognition
% process expects:
% - sensory cue (u). This is a v... |
a6fde655c91ad5e5e6245a8725b9610fd5894aa2cd0f6becd515a3ea2e6952c3 | MATLAB | 8,908 | 249 | function [nsout] = read_neuroshare(filename, varargin)
% READ_NEUROSHARE reads header information or data from any file format
% supported by Neuroshare. The file can contain event timestamps, spike
% timestamps and waveforms, and continuous (analog) variable data.
%
% Use as:
% hdr = read_neuroshare(filename, ...)
... |
e5271561bb61a6aea776803e01a5a1ae34cd69ebc2fa3546e517c80a909aaa60 | MATLAB | 8,910 | 264 | % mediation_zeta_control
load(fullfile(saveLoc, 'sig_allSessions'),...
'sigSL')
S = sigSL;
% Analysis parameters
max_coh = 0.1;
minRT = 0.67;
maxRT = 2;
start_t = 0;
end_t = 0.55;
session = S.session;
times = S.t;
dt = times(2) - times(1);
choice = S.choice;
RT = S.rt;
coh = S.sig_coh;
str = ... |
504673a490bead929db39f84f6b03ac52a00b87c9a8b3d35390507f5be0bb9cb | MATLAB | 8,911 | 293 | function allppobj = RunPostProcessing_HeatmapData2(hmdir,varargin)
% Run single-view heatmap postproc
ncores = feature('numcores');
if isdeployed,
fprintf('Starting RunPostProcessing_HeatmapData, ncores = %d...\n',ncores);
end
if ncores == 1,
ncores = 0;
end
if isdeployed,
varargin = DeployedChar2NumberArgs(va... |
7fa85dce3d09824e5bcb635e036e1a41e52be251d7f406087f5e367c0d7d26a6 | MATLAB | 8,916 | 266 | function create = spm_cfg_opm_create
% configuration file for creating OPM objects
%__________________________________________________________________________
% Copyright (C) 2018 Wellcome Trust Centre for Neuroimaging
% Tim Tierney
% $Id: spm_cfg_opm_create.m 7521 2019-01-30 18:16:03Z tim $
%------------------------... |
4d02ae8049475fce083ed2c084f13bd096c1619a741df559a09c1ae8fbd0231e | MATLAB | 8,917 | 329 | function [PI,out] = MixtureOfBinomials(y,K,options)
% This function inverts a binomials mixture model (BMM).
% [PI,out] = MixtureOfBinomials(y,K,options)
%
% IN:
% - y: the Dxn binary data matrix, where n is the number of samples, and
% D the dimension of the data.
% - K: the number of classes to be used. As a g... |
44e3a6445f18216b7cfbcc9a53dd2718ff17260b2654f7fe48b133afc46c2d3f | MATLAB | 8,918 | 231 | function hdr = read_yokogawa_header_new(filename)
% READ_YOKOGAWA_HEADER_NEW reads the header information from continuous,
% epoched or averaged MEG data that has been generated by the Yokogawa
% MEG system and software and allows that data to be used in combination
% with FieldTrip.
%
% Use as
% [hdr] = read_yokogaw... |
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