sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
0b74cf3ba4999a20a225baae2acdfe296bb44b8c1af2cf57a0b5ba94422602fe | MATLAB | 17,973 | 549 | function MakeDemoRawVideo(moviename,varargin)
defaults.fps = 20;
defaults.compression = 'None';
allowedcompressions = {'Indeo3', 'Indeo5', 'Cinepak', 'MSVC', 'RLE', 'None','Uncompressed AVI','Motion JPEG AVI'};
useVideoWriter = exist('VideoWriter','file');
mencoderoptions = '';
mencoder_maxnframes = inf;
[moviename,av... |
8acbc3d2f97f9d01ad3f135ea803c1dd3f2ae4398463c8af0074bac5652acc46 | MATLAB | 17,997 | 621 | clear
clc
% f = gcf;
% exportgraphics(f,'Fig1_Original.png','Resolution',600)
MotionData = load('MotionData.mat');
MusculoskeletalData = load('MusculoskeletalData.mat');
%% Motion Data
MotionData = MotionData.MotionData;
% Joint Angles
SHLa = MotionData.GenericCat.Angles.AngShou.Total*(pi/180);
ELBa = MotionData.Ge... |
2d6083bd3cebe7bfe89520eb4105a96903b80b530e1980e794ae04198772c0a6 | MATLAB | 18,002 | 617 | clear
clc
% f = gcf;
% exportgraphics(f,'Fig1_Original.png','Resolution',600)
MotionData = load('MotionData.mat');
MusculoskeletalData = load('MusculoskeletalData.mat');
%% Motion Data
MotionData = MotionData.MotionData;
% Joint Angles
SHLa = MotionData.GenericCat.Angles.AngShou.Total*(pi/180);
ELBa = MotionData.Ge... |
7be6742294b60796bf1cf6106a41fc1c9cb8bd89e7a23201549fd80ed432ffce | MATLAB | 18,002 | 617 | clear
clc
% f = gcf;
% exportgraphics(f,'Fig1_Original.png','Resolution',600)
MotionData = load('MotionData.mat');
MusculoskeletalData = load('MusculoskeletalData.mat');
%% Motion Data
MotionData = MotionData.MotionData;
% Joint Angles
SHLa = MotionData.GenericCat.Angles.AngShou.Total*(pi/180);
ELBa = MotionData.Ge... |
67c7fa7ca98c833352cce2f1fc76a19c02a06a539a326f31ed18fdedeb4f6c06 | MATLAB | 18,003 | 618 | clear
clc
% f = gcf;
% exportgraphics(f,'Fig1_Original.png','Resolution',600)
MotionData = load('MotionData.mat');
MusculoskeletalData = load('MusculoskeletalData.mat');
%% Motion Data
MotionData = MotionData.MotionData;
% Joint Angles
SHLa = MotionData.GenericCat.Angles.AngShou.Total*(pi/180);
ELBa = MotionData.Ge... |
eb58a225c4e722b6973b0f7270d3c200947b17c6f48146517648952c890917f0 | MATLAB | 18,005 | 617 | clear
clc
% f = gcf;
% exportgraphics(f,'Fig1_Original.png','Resolution',600)
MotionData = load('MotionData.mat');
MusculoskeletalData = load('MusculoskeletalData.mat');
%% Motion Data
MotionData = MotionData.MotionData;
% Joint Angles
SHLa = MotionData.GenericCat.Angles.AngShou.Total*(pi/180);
ELBa = MotionData.Ge... |
7a14b3bf9ca4a79dfc2b7c264729d4a4d1eb2c619d625e597c2b47f2b137ebd8 | MATLAB | 18,007 | 618 | clear
clc
% f = gcf;
% exportgraphics(f,'Fig1_Original.png','Resolution',600)
MotionData = load('MotionData.mat');
MusculoskeletalData = load('MusculoskeletalData.mat');
%% Motion Data
MotionData = MotionData.MotionData;
% Joint Angles
SHLa = MotionData.GenericCat.Angles.AngShou.Total*(pi/180);
ELBa = MotionData.Ge... |
d5313bd7dece1be0597b18e5657859d8ea37b783e958b820a3513af562adeb1a | MATLAB | 18,011 | 619 | clear
clc
% f = gcf;
% exportgraphics(f,'Fig1_Original.png','Resolution',600)
MotionData = load('MotionData.mat');
MusculoskeletalData = load('MusculoskeletalData.mat');
%% Motion Data
MotionData = MotionData.MotionData;
% Joint Angles
SHLa = MotionData.GenericCat.Angles.AngShou.Total*(pi/180);
ELBa = MotionData.Ge... |
f3fbd7d8fc940f8adace46a086fb50b3191e7f6e01fc1f042adb663c3cf6f0d7 | MATLAB | 18,011 | 617 | clear
clc
% f = gcf;
% exportgraphics(f,'Fig1_Original.png','Resolution',600)
MotionData = load('MotionData.mat');
MusculoskeletalData = load('MusculoskeletalData.mat');
%% Motion Data
MotionData = MotionData.MotionData;
% Joint Angles
SHLa = MotionData.GenericCat.Angles.AngShou.Total*(pi/180);
ELBa = MotionData.Ge... |
2bf295ce5542b693ee39b6cc420cafcdb09b70785b79ed4850819dea5788a6f5 | MATLAB | 18,012 | 438 | function bbLabeler( objTypes, imgDir, resDir )
% Bounding box or ellipse labeler for static images.
%
% Launch and click "?" icon for more info.
%
% USAGE
% bbLabeler( [objTypes], [imgDir], [resDir] )
%
% INPUTS
% objTypes - [{'object'}] list of object types to annotate
% imgDir - [pwd] directory with images
% re... |
58f6f32c64781bfa9a591cbe12d3846ac4bfa40c9149ba493fce00effcc78091 | MATLAB | 18,013 | 619 | clear
clc
% f = gcf;
% exportgraphics(f,'Fig1_Original.png','Resolution',600)
MotionData = load('MotionData.mat');
MusculoskeletalData = load('MusculoskeletalData.mat');
%% Motion Data
MotionData = MotionData.MotionData;
% Joint Angles
SHLa = MotionData.GenericCat.Angles.AngShou.Total*(pi/180);
ELBa = MotionData.Ge... |
f47213a470706ccfcf196815ce0ac4e4e4e45cd1aefef085908e59c8443385e7 | MATLAB | 18,013 | 618 | clear
clc
% f = gcf;
% exportgraphics(f,'Fig1_Original.png','Resolution',600)
MotionData = load('MotionData.mat');
MusculoskeletalData = load('MusculoskeletalData.mat');
%% Motion Data
MotionData = MotionData.MotionData;
% Joint Angles
SHLa = MotionData.GenericCat.Angles.AngShou.Total*(pi/180);
ELBa = MotionData.Ge... |
a9bedb3c08117a045f3e78c249fbc8eefde074e9e592f7c80fd606c7d621701e | MATLAB | 18,014 | 620 | clear
clc
% f = gcf;
% exportgraphics(f,'Fig1_Original.png','Resolution',600)
MotionData = load('MotionData.mat');
MusculoskeletalData = load('MusculoskeletalData.mat');
%% Motion Data
MotionData = MotionData.MotionData;
% Joint Angles
SHLa = MotionData.GenericCat.Angles.AngShou.Total*(pi/180);
ELBa = MotionData.Ge... |
f4fd963a5cebb35e0b2227593792a6eb436f90e4194e10c13329e03cace03096 | MATLAB | 18,015 | 621 | clear
clc
% f = gcf;
% exportgraphics(f,'Fig1_Original.png','Resolution',600)
MotionData = load('MotionData.mat');
MusculoskeletalData = load('MusculoskeletalData.mat');
%% Motion Data
MotionData = MotionData.MotionData;
% Joint Angles
SHLa = MotionData.GenericCat.Angles.AngShou.Total*(pi/180);
ELBa = MotionData.Ge... |
3f609425b33b1aa9fe71af13485ce0afae831ff8d46d3636c87225f781146aed | MATLAB | 18,022 | 615 | clear
clc
% f = gcf;
% exportgraphics(f,'Fig1_Original.png','Resolution',600)
MotionData = load('MotionData.mat');
MusculoskeletalData = load('MusculoskeletalData.mat');
%% Motion Data
MotionData = MotionData.MotionData;
% Joint Angles
SHLa = MotionData.GenericCat.Angles.AngShou.Total*(pi/180);
ELBa = MotionData.Ge... |
ac2937c1b1a42c57f7414534753881c6cbcd96b1618a4e5bd240e8d013b3af1c | MATLAB | 18,023 | 616 | clear
clc
% f = gcf;
% exportgraphics(f,'Fig1_Original.png','Resolution',600)
MotionData = load('MotionData.mat');
MusculoskeletalData = load('MusculoskeletalData.mat');
%% Motion Data
MotionData = MotionData.MotionData;
% Joint Angles
SHLa = MotionData.GenericCat.Angles.AngShou.Total*(pi/180);
ELBa = MotionData.Ge... |
ac8303977756d4c60d798f0d90ee8287d844655abf1778bb237b56bb4d559524 | MATLAB | 18,025 | 618 | clear
clc
% f = gcf;
% exportgraphics(f,'Fig1_Original.png','Resolution',600)
MotionData = load('MotionData.mat');
MusculoskeletalData = load('MusculoskeletalData.mat');
%% Motion Data
MotionData = MotionData.MotionData;
% Joint Angles
SHLa = MotionData.GenericCat.Angles.AngShou.Total*(pi/180);
ELBa = MotionData.Ge... |
ad0ebe130a85189299c9ba4e36618561130649368504b96318bd1336bf9d0cbb | MATLAB | 18,025 | 618 | clear
clc
% f = gcf;
% exportgraphics(f,'Fig1_Original.png','Resolution',600)
MotionData = load('MotionData.mat');
MusculoskeletalData = load('MusculoskeletalData.mat');
%% Motion Data
MotionData = MotionData.MotionData;
% Joint Angles
SHLa = MotionData.GenericCat.Angles.AngShou.Total*(pi/180);
ELBa = MotionData.Ge... |
b3103197ef9251dad2b43da68129dc96d9fcc650ec1efeb76aa445d492e0a3ca | MATLAB | 18,026 | 554 | % freq_inter_band.m
% v 0.0.2b fix
% Estudios interbandas
% Experimental
%
%-----------------------------------------------------------------------------------
%-----------------------------------------------------------------------------------
%
% LAN = freq_inter_band(LAN)
% parametros definidos en estructura ... |
68cf7ce0e223f6021c58c717854109fadb2d173b272621847792866c2e6fb5f8 | MATLAB | 18,042 | 458 | function [ record ] = saveTableDatasource( path, saveName, dataSource, omitHeavyCoordinates,...
omitHeavyLGs, waitbarhandle, headpr)
% Don't directly use this function. Use dspace_data.saveCollection instead.
%
%
% Note: In many Matlab version file sizes are limited to 2gb or saving
% ... |
e6380fe641a921b3b6b7279676218e1fbbe45044e236da0d496ca864e0c17772 | MATLAB | 18,081 | 430 | function hh = rotateXLabels( ax, angle, varargin )
%rotateXLabels: rotate any xticklabels
%
% hh = rotateXLabels(ax,angle) rotates all XLabels on axes AX by an angle
% ANGLE (in degrees). Handles to the resulting text objects are returned
% in HH.
%
% hh = rotateXLabels(ax,angle,param,value,...) also allows one... |
7e8e4243d01a82b34de639fc62640122c4e14745b1a7e08ac169c66a3593f438 | MATLAB | 18,089 | 492 | function [settings, button] = settingsdlg(varargin)
% SETTINGSDLG Default dialog to produce a settings-structure
%
% settings = SETTINGSDLG('fieldname', default_value, ...) creates a modal
% dialog box that returns a structure formed according to user input. The
% input should be given in the form of 'field... |
0cb26f05a53bad9f16f3e91a09ca428a451bc993e41536785cad9fd35101c84a | MATLAB | 18,093 | 313 | %% File Lists and Locations
home='/Users/meaghanperdue/data_acg';
QC_csv_name = 'SE_PRESS_QC_Metrics_acg.csv';
tissue_csv_name = 'Tissue_CSV_Name_acg.csv';
MRS={
'PS10001_PS14_006_2058/PS10001_PS14_006_2058_P39936.7'
'PS10006_PS14_053_2563/PS10006_PS14_053_2563_P17408.7'
'PS10007_PS14_054_2562/PS10007_PS14_054_2562_P... |
5eee6922f2a72d24e2fd0c7de6ca6fb8e12c61916d23c25152550433881a28fa | MATLAB | 18,104 | 405 | function [map,num,typ] = brewermap(N,scheme)
% The complete selection of ColorBrewer colorschemes (RGB colormaps).
%
% (c) 2014 Stephen Cobeldick
%
% ### Function ###
%
% Returns any RGB colormap from the ColorBrewer colorschemes, especially
% intended for mapping and plots with attractive, distinguishable colo... |
51c3cee595cba7f3d3b04c4aa183debd27e222c8ca81e5e96f5ee32a4f7468f9 | MATLAB | 18,115 | 567 | function data = ft_denoise_pca(cfg, varargin)
% FT_DENOISE_PCA performs a principal component analysis (PCA) on specified reference
% channels and subtracts the projection of the data of interest onto this orthogonal
% basis from the data of interest. This is the algorithm which is applied by 4D to
% compute noise can... |
8cb44877472198db63f95e3bd2034a19d9077b1321d691e80658667f6d92e7a7 | MATLAB | 18,124 | 601 | function tfrqview(tfr,sig,t,method,p1,p2,p3,p4,p5);
%TFRQVIEW Quick visualization of time-frequency representations.
% TFRQVIEW(TFR,SIG,T,METHOD,P1,P2,P3,P4,P5) allows a quick
% visualization of a time-frequency representation.
%
% TFR : time-frequency representation (MxN).
% SIG : sign... |
f0bd61f34eb4fa9d40c98186dcf56c1f8e746dea60a3b680425a13077e1e8e02 | MATLAB | 18,140 | 524 | function [h, T2] = ft_plot_slice(dat, varargin)
% FT_PLOT_SLICE plots a 2-D cut through a 3-D volume and interpolates if needed
%
% Use as
% ft_plot_slice(dat, ...)
% or
% ft_plot_slice(dat, mask, ...)
% where dat and mask are equal-sized 3-D arrays.
%
% Additional options should be specified in key-value pairs an... |
c344eafe7bee8a8f35c962338f9911db25e14c02f8d37b0ae28ccba5c911f931 | MATLAB | 18,164 | 452 | function [dat] = read_edf(filename, hdr, begsample, endsample, chanindx)
% READ_EDF reads specified samples from an EDF datafile. It neglects all trial or
% data block boundaries as if the data was acquired in non-continous mode.
%
% Note that since FieldTrip only accommodates a single sampling rate in a given
% datas... |
b26ab368a5e4cdd7ade223607285ec5fc684f9667ad29da68580de5f9fe211e4 | MATLAB | 18,175 | 521 | function [data] = ft_math(cfg, varargin)
% FT_MATH performs mathematical operations on FieldTrip data structures,
% such as addition, subtraction, division, etc.
%
% Use as
% data = ft_math(cfg, data1, data2, ...)
% with one or multiple FieldTrip data structures as the input and the configuration
% structure cfg in ... |
a88b5197eb62d97c46920ae268c8b02486f2dc16e10db54b880643b43866ac7c | MATLAB | 18,181 | 706 | function [mask Header_Out] = w_Automask(Data, OutputFile, Verb)
% function [mask Header_Out] = w_Automask(Data, OutputFile, Verb)
% Input:
% Data - Could be the following format:
% 1. A single file (.img/hdr, .nii, or .nii.gz), give the path and filename.
% 2. A directory, under which... |
7727bb9a3135f0fe46bfce7d9d3a6ccb1dc813bc40ab025c30e7eb25b4f065af | MATLAB | 18,191 | 489 | function replaytrajectory = decode_events(modelParam, animalprefix, savedir, savedata, varargin)
% Adapted from code for Shin et al., 2019, Jadhav Lab
% Previous function name was preplay_decoding_CA1_singleday.m
% Original function name from Wenbo was replay_decoding_CA1_singleday.m
%
% INPUTS:
% animalprefix = ani... |
184e4a64e6b31448ff6198303dc256939aed8e0093290f9e62ae4394f71f5d65 | MATLAB | 18,224 | 433 | function mri = ctf_read_mri(file)
% ctf_read_mri - read a CTF .mri file
%
% mri = ctf_read_mri(fileName)
%
% The CTF MRI File format used by MRIViewer consists of a binary file with
% a 1,028 byte header. The MRI data can be in 8-bit (unsigned character) or
% 16-bit (unsigned short integer) format and consists of 256 ... |
da9159a3588d484a951426776c75543d0766f58ae059022dc2801698e7f248c9 | MATLAB | 18,230 | 449 | % Author: Milena Capiglioni, University of Bern
% Contact: milena.capiglioni@extern.insel.ch
% Last update: Nov.2023
% If you use/modify this code for your future publication, please cite the
% corresponding article: "Stimulus-Induced Rotary Saturation imaging of
%visually evoked neuroelectric response: preliminary r... |
125304f621dee955dcb17b68d86e1b9e5a67444302b67a76787a8541b6a218c4 | MATLAB | 18,238 | 463 | classdef (Abstract) SurpassObjectReader < matlab.mixin.SetGet & dynamicprops
% SurpassObjectReader Surpass object reader base class
%
% © 2015–2016, Peter Beemiller (pbeemiller@gmail.com)
%
% See also CellsReader | FilamentsReader | SpotsReader | SurfacesReader
properties (SetAcc... |
74be17a3b37408d49419dd711241feca0d06c4efc97ff4c79657acdfb6068f39 | MATLAB | 18,257 | 567 | function data = ft_denoise_pca(cfg, varargin)
% FT_DENOISE_PCA performs a principal component analysis (PCA) on specified reference
% channels and subtracts the projection of the data of interest onto this orthogonal
% basis from the data of interest. This is the algorithm which is applied by 4D to
% compute noise can... |
8d5d2c8dd47c0b9a153f9b48f176fd1f595f6260e862949ab806f346aaf98601 | MATLAB | 18,263 | 417 | function [Yc,Ye,Ya,clscor] = boney_segment_refineSPM(Yo,Ym,Yc,Ya,Ybraindist0,tis,tismri,refine)
% == REFINE SPM DATA ==
% * Create meninges class?
% - This is not realy working cause the intensities are changing too much.
% Hence, it is better to evaluate the whole mid structure.
% - Would thresholding by thi... |
8bc662b63bc1efcfb02256e88acb5957dc0c2211ccfbb5fc329897eee058f0f1 | MATLAB | 18,282 | 384 | function [] = Twave_personalisation_POMs_ToRORd_IKs_IKr_not_converged(nb_models, celltype, stimAmp, stimulus_function_str, result_dir)
% Population of models generation for T-wave personalisation
% Adapted from scriptDemonstration_2_ParameterComparison.m:
%% Setting parameters
param_baseline.bcl... |
ffb12f25ab8b926a491be51498c31ca050ddc87560dd429f74f27673c609b93e | MATLAB | 18,285 | 526 | function data = ft_math(cfg, varargin)
% FT_MATH performs mathematical operations on FieldTrip data structures,
% such as addition, subtraction, division, etc.
%
% Use as
% data = ft_math(cfg, data1, data2, ...)
% with one or multiple FieldTrip data structures as the input and the configuration
% structure cfg in wh... |
25f5a12220d2376cc13fcee779ff88d85a298bb9de3ebb4c2eb4b1cae4aa89d8 | MATLAB | 18,297 | 489 | % Address the basic question, when x is the salient category, what
% percentage of units are tuned to x.
function SlidingTimeDPrimeMotorVersion(config,varargin)
[varargin,DateName] = Utilities.ProcVarargin(varargin,'DateName',[]);
[varargin,Pmethod] = Utilities.ProcVarargin(varargin,'Pmethod','fdr');
[va... |
cb3b2fb8f08f4cee410e6d93bd57eff622ce72c1a1d4493befdedb090b0f1967 | MATLAB | 18,302 | 656 | % paper_figures_2019.m
%% setup
gd = '/Users/rachel/Google Drive';
% gd = '/Local/Users/denison/Google Drive';
dataDir = sprintf('%s/NYU/Projects/Temporal_Attention/Code/Expt_Scripts/Behav/data', gd);
fitDir = sprintf('%s/NYU/Projects/Temporal_Attention/Code/Models/TA_Model/fit/startpoints', gd);
mrDir = sprintf('%s/... |
93da9341afaa1649d29d1eb394d22a8a7e8677420aa1b67efae30b5aa1b4ced1 | MATLAB | 18,338 | 537 | function parcel = ft_sourceparcellate(cfg, source, parcellation)
% FT_SOURCEPARCELLATE combines the source-reconstruction parameters over the parcels, for
% example by averaging all the values in the anatomically or functionally labeled parcel.
%
% Use as
% output = ft_sourceparcellate(cfg, source, parcellation)
% ... |
ca1644f7b071dcc1efedbde27c2bae6596d3621348de6b1fa59de7a7bc07ad26 | MATLAB | 18,358 | 422 | function loc_list_plot(data)
if isempty(data)~=1
fig = figure();
set(gcf,'name','Localizations List (2D)','NumberTitle','off','color',[0.1 0.1 0.1],'units','normalized','position',[0.3 0.15 0.4 0.7],'menubar','none','toolbar','figure');
defaultToolbar = findall(fig,'Type','uitoolbar');
a = ... |
7d74d4cb31da0c3dfbb7c76689e2cf9b56a737e0cb4dc6eab95d1244e5438fbe | MATLAB | 18,371 | 472 | function ft_volumewrite(cfg, volume)
% FT_VOLUMEWRITE exports anatomical or functional volume data to a Analyze
% or BrainVoyager file. The data in the resulting file(s) can be
% further analyzed and/or visualized in MRIcro, SPM, BrainVoyager,
% AFNI or similar packages.
%
% Use as
% ft_volumewrite(cfg, volume)
% wh... |
d97d51009bb57ee46a8bd8cd2202e16bada6326e8af0d9656c71cab60e57d6b5 | MATLAB | 18,379 | 329 | function y_T1ImgDefacer(AutoDataProcessParameter)
% FORMAT y_T1ImgDefacer(AutoDataProcessParameter)
% Input:
% AutoDataProcessParameter - the parameters for auto data processing
% AutoDataProcessParameter.DataProcessDir='/home/data/YCG_AllData/YAN_Work/Monkey/Analysis/Cebus/CP1F/T1CoregAverage';
% AutoData... |
2ca1ba980554f02daf53b1af72a511d0bec6748d7734d749f0c045a370b1cc6f | MATLAB | 18,382 | 278 | function spindle_calculation_default()
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Calculate spindle data summary (from .csv format output)
%
% Info: Opens csv output from 'detect_spindles' pipeline and computes
% summary stats.
%
% Download: https://github.co... |
05902234b5a5300a2be738f83c53b641be16086b584bcf7a3fd1b41e7eed5fed | MATLAB | 18,385 | 472 | function ft_volumewrite(cfg, volume)
% FT_VOLUMEWRITE exports anatomical or functional volume data to a Analyze
% or BrainVoyager file. The data in the resulting file(s) can be
% further analyzed and/or visualized in MRIcro, SPM, BrainVoyager,
% AFNI or similar packages.
%
% Use as
% ft_volumewrite(cfg, volume)
% wh... |
0d94a412b9909d97dced2a062d511113ad4117532fa71bbc5193a825023a0642 | MATLAB | 18,411 | 501 | function [SleepScoreLFP,PickChannelStats] = PickSWTHChannel(basePath,scoretime,SWWeightsName,...
Notch60Hz,NotchUnder3Hz,NotchHVS,NotchTheta,SWChannels,ThetaChannels,...
rejectchannels,OVERWRITE,varargin)
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
% Optional
% 'noPromp... |
d7bbb7a18f55ebd74123a4cd2ce7f19db806757378a20c1ab99632c72a65e6c6 | MATLAB | 18,432 | 543 | function [cfg] = ft_movieplotTFR(cfg, data)
% FT_MOVIEPLOTTFR makes a movie of the time-frequency representation of power or
% coherence.
%
% Use as
% ft_movieplotTFR(cfg, data)
% where the input data comes from FT_FREQANALYSIS or FT_FREQDESCRIPTIVES and the
% configuration is a structure that can contain
% cfg.pa... |
e5dd2a2155f7ca1df86beac40a998f930d164c12e73a033527ca3c7923aec21f | MATLAB | 18,443 | 403 | classdef SpectrogramPanel < TimelinePanel
properties
audio
% The frequency range is shared by all panels and is stored in the second half of obj.controller.displayRange.
% The FFT window shared by all panels and is stored in obj.controller.windowSize.
saturation = [0.01 0.99]
... |
512a5334b6b6d87297c572f4eb8ab6ac7424893c60bb2fb7533aaac5df042832 | MATLAB | 18,458 | 711 | function RT = rt_read(cfg,LAN)
% v.2
% <*LAN)<|
% Read event file for reaction time analysis and modeling
%
% RT = rt_read(cfg)
%
% :: file or variable name where the data are.
% cfg.filename = 'nombredearchivo.log'
%
% :: Format
% cfg.type = 'presentation' --> .log
% ... |
187d09686fae845ae3c747c4c94b2d6a0c37b92a8e2f2e8c4d59e0ed05315fc7 | MATLAB | 18,462 | 562 | function errorbarjitter(data,h,varargin)
% SYNTAX
%
% errorbarjitter(data)
% errorbarjitter(data,h,param1,val1,param2,val2,...)
%
% e.g.
% errorbarjitter(data,1,'barends','yes','colors',color_array)
%
%
% Plots mean (or median)±SD plus jitter plot of raw data
% Columns are categories, rows are individual sampl... |
d645c118b1df5cffc20bf5ff485a32f9725ebccdcee17ae53762cd90247d2e08 | MATLAB | 18,462 | 399 | function grpData = h_plotGroupFcn3(handles)
% global FV_img
[currentInd, handles, currentStruct, currentStructName] = h_getCurrendInd3(handles);
fig = findobj('Tag','h_imstack3Plot','Selected','on');
if isempty(fig)
fig = figure('Tag','h_imstack3Plot','ButtonDownFcn','h_selectCurrentPlot3','Selected','on... |
8db8b6fb726562be235bbd7e16c9516589af6f445d5c2815b1ad03b50975a5e3 | MATLAB | 18,483 | 503 | function [varargout] = ft_plot_vector(varargin)
% FT_PLOT_VECTOR visualizes a vector as a line, similar to PLOT.
%
% Use as
% ft_plot_vector(Y, ...)
% or as
% ft_plot_vector(X, Y, ...)
% where X and Y are similar as the input to the MATLAB plot function.
%
% Optional arguments should come in key-value pairs and ca... |
ec107bca5d565deedb8cdeabe3fb49254bc7dce311b731c8922f4a81da60de49 | MATLAB | 18,484 | 541 | % calib_stereo
% Script for Calibrating a stereo rig (two cameras, internal and external calibration):
%
% It is assumed that the two cameras (left and right) have been calibrated with the pattern at the same 3D locations, and the same points
% on the pattern (select the same grid points). Therefore, in particular, the... |
2e7bf652ae2bd993c20e7d9a0aa193ed975476b11a9f7b569ef6e636021507ff | MATLAB | 18,496 | 529 | function data_view_update(input)
global time
global play
global data
global t
global FIG
global GUI_handle
global replay_index;
global parameters
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if strcmp(input,'load') %load data
parameters=list_of_parameters;
replay_index=[];
GUI_handle=gcbf;
FIG=figure;
if exist... |
55fb1103ed6b67a5aec011b37252911c956a812532c3e00114ecacef02bade8d | MATLAB | 18,519 | 307 | % TSCOMBINEOVER Combine Time Stamped Data one level up the heirarchy.
% TSCOMBINEOVER(STATNAME,USESTAT, MODEFLAGS) creates a stat called
% STATNAME that is the collection of USESTAT (appended end to end) and
% stored a level up in the Experiment hierarchy. Statname represents the
% name for the new stat and U... |
8f96b381b825470f3a4549053db0b1e82064cd8e0bf45658a447d827b1475f95 | MATLAB | 18,528 | 459 | function [dat] = read_edf(filename, hdr, begsample, endsample, chanindx)
% READ_EDF reads specified samples from an EDF datafile. It neglects all trial or
% data block boundaries as if the data was acquired in non-continuous mode.
%
% Note that since FieldTrip only accommodates a single sampling rate in a given
% data... |
7e65a7be3d597cabe0a141a62ae7f4b513b36e507bcca61473e8c136b3c93773 | MATLAB | 18,533 | 366 | % TSAPPLYSTAT Apply a function to a statistic or statistics to
% generate another statistic or statistics or to make a graph
%
% Syntax ER = TSAPPLYSTAT(NEWSTAT,USESTATS,FUN,arg1,arg2,etc)
% NEWSTAT is a string or cell array of strings; USESTATS is likewise a
% string or cell array of strings; FUN is a function to b... |
16791b5716c2e43a6b44332890232aea5f379c08a42bc22ce86b3b965825e7a9 | MATLAB | 18,537 | 405 | function [expanded_matrix, comparison_type_matrix_time, comparison_type_matrix_session, comparison_type_matrix_decay, comparison_type_matrix_time_from_onset_firstday, comparison_type_matrix_time_from_onset_secondday] = ...
scale_time_course_matricies(input_matrix, all_imaging_days, included_days, latest_date, rept... |
e4a007abdcc820d6e6011b349e2e6ea0513477968a38a45553cb6d938719ee95 | MATLAB | 18,548 | 601 |
% adjusted_ADJUST() - Automatic EEG artifact Detector optimized for
% pediatric data
%
% Usage:
% >> [art, horiz, vert, blink, disc,...
% soglia_DV, diff_var, soglia_K, med2_K, meanK, soglia_SED, med2_SED, SED, soglia_SAD, med2_SAD, SAD, ...
% soglia_GDSF, med2_GDSF, GDSF, soglia_V, med2_V, nuovaV, s... |
698d8770b4980274f9f40bec20962dd55bd5cf5f32d192ec6b25ce4ecf89b3cc | MATLAB | 18,553 | 413 | function grpData = h_frameAnalysisGrpPlot3(handles)
[currentInd, handles, currentStruct, currentStructName] = h_getCurrendInd3(handles);
fig = findobj('Tag','h_imstack3Plot','Selected','on');
if isempty(fig)
fig = figure('Tag','h_imstack3Plot','ButtonDownFcn','h_selectCurrentPlot3','Selected','on');
end
f... |
723b8e014a0bbf9d48815dda7b94f2c8c9dd77299ba8b4d57b634b3e38b83891 | MATLAB | 18,586 | 541 | classdef LabelCoreTemplateController < LabelCoreController
% Template-based labeling controller
%
% Owns all graphics for template labeling mode. Receives GUI callbacks,
% extracts GUI state (mouse position, modifiers), delegates data logic
% to LabelCoreTemplateModel, and syncs graphics in response to model events.
%
... |
50994d25205f1ecfc03170797fbe9d495459b4c3fcfbede08660fded07fb709b | MATLAB | 18,602 | 546 | function [outim] = ft_sliceinterp(cfg, ininterp)
% FT_SLICEINTERP plots a 2D-montage of source reconstruction and anatomical MRI
% after these have been interpolated onto the same grid.
%
% Use as
% ft_sliceinterp(cfg, interp)
% or
% [rgbimage] = ft_sliceinterp(cfg, interp), rgbimage is the monatage image
%
%... |
aa2e93267aecf326e89372e1b296037cebc136c0863a4eb3a661e1b30ae6d706 | MATLAB | 18,618 | 586 |
%load data: contact lead author
%%
allIdx=unique([aoCellIdx;vsCellIdx;aoRewardIdx;vsRewardIdx]);
otherIdx=setdiff([1:1:size(dfofUse,1)],allIdx);
otherIdx=[otherIdx intersect([aoCellIdx;aoRewardIdx],[vsCellIdx;vsRewardIdx])'];
save('otherIdx.mat','otherIdx')
dfofOther=dfofUse(otherIdx,:);
dfofFOther=fieldDistri... |
e145e2181658ba068d654a84acd626b9fa740819f8bb3a4369ee4e40843b8544 | MATLAB | 18,629 | 481 | classdef MetaPath < apt.ShellToken
% apt.MetaPath - Locale and role-aware path representation for multi-context execution
%
% This class extends apt.Path with additional metadata required for APT's
% multi-backend execution environment. It tracks both the execution locale
% (where the path will be used) and t... |
c7a19928d810f506da4e4873ab2241a6d3fc93c0b77a5e6106edfc3cf7f4a400 | MATLAB | 18,635 | 618 | %go_calib_optim_iter_fisheye
%
%Main calibration function. Computes the intrinsic and extrinsic parameters.
%for fisheye cameras.
%Runs as a script.
%
%INPUT: x_1,x_2,x_3,...: Feature locations on the images
% X_1,X_2,X_3,...: Corresponding grid coordinates
%
%OUTPUT: fc: Camera focal length
% cc: Principa... |
a23f46a52769a25a27b396bca79ac0fdb31ed73f1136fc2b23b7be33d5a9808c | MATLAB | 18,640 | 633 |
% load data
% contact Lead Author for data
% SPATIAL SELECTIVITY ANALYSIS in common vs unique populations
% 1 - number of fields
% 2 - width of fields
% 3 - infield-nonInField
%% width and number of fields
% % for avr1-vvr1
% useData = allFields_1; mice = 1:31; % 4-19 / 1-31;
% trackLen = 2... |
88768a86c11eea6ea6d7d1b13954c257b187acde39a002cb61202baa38123164 | MATLAB | 18,673 | 383 | classdef Introduction_to_Dataspace
% Dataspace (short: dspace) is a set of data structures, analysis functions and
% a graphical user interface intended to facilitate data analysis in various
% fields of science.
%
% Dataspace is build with practical application in mind - to be
% as ... |
9f35560137593beaf4a1d5b1d014b0373948dbadbe1bd1684ed5a7e8a11c3f2e | MATLAB | 18,689 | 430 | % Parse params.json and set default values if not specified
%
% Cristina Gil, TUM, 01.02.2024
function params = define_params(fname)
%% Read json file with all the parameters
if isempty(fname)
fname = 'params_example.json';
end
fid = fopen(fname);
raw = fread(fid,inf);
str = char(raw');
fclose(fid);
params = jsond... |
4935c023019e4cea2d2b00d3475957ddf9881f0c94fa5a9270821f7cf706a682 | MATLAB | 18,693 | 218 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Script to perform batch tissue correction on LCM .csv files
% Script is designed to analyze LCM .csv files saved in participant folders in a
% larger study directory (example on line below) with the ID of the csv
% folder matching that of ... |
e48e99d13c352002dcb28fd168ef955ce8fa4e29b1b8ac8dd1847ad8e7b20e7b | MATLAB | 18,717 | 431 | function [visual_feats] = GetVisualFeatures(trk, calib, subject_ID,target_ID, samplerate, frame_range, nose, plotit)
%
% GETVISUALFEATURES calculates estimated visual features of a target fly
% in a subject fly's visual field during free behavior assays that have been
% tracked with FlyTracker (https://github.com/kris... |
615442e9d0263a5d72bcdb9371124093362e4e1c0f352d28b276129b287eac9c | MATLAB | 18,718 | 548 | %% choose session
datRoot = '/Volumes/LaCie/Farries recordings/';
rat = 'IM1055';
sesList = dir([datRoot rat '/20*']);
sesList = arrayfun(@(x) x.name, sesList, 'UniformOutput', false)
iSes = 10;
sesDir = [datRoot rat filesep sesList{iSes} filesep]
% load behavior data
load([sesDir 'behavior - RL.mat'])
nTr = length(t... |
c03748f1e37566b6fca1c956f09d4647497b466f4d64106e27c9387f143d9d09 | MATLAB | 18,722 | 466 | function dataout = ft_denoise_tsr(cfg, varargin)
% FT_DENOISE_TSR performs a regression analysis, using a (time-shifted set
% of) reference signal(s) as independent variable. It is a generic
% implementation of the method described by De Cheveigne
% (https://doi.org/10.1016/j.jneumeth.2007.06.003), or can be
% used t... |
376964a0090fcb22d83d16d350e24e3cfd3e4b3d2d702540d8ae10d6b8c3b4e9 | MATLAB | 18,732 | 566 | function data = loadjson(fname,varargin)
%
% data=loadjson(fname,opt)
% or
% data=loadjson(fname,'param1',value1,'param2',value2,...)
%
% parse a JSON (JavaScript Object Notation) file or string
%
% authors:Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2011/09/09, including previous works from
%
% ... |
c95fca208c26a1fb81fcd93e3f91d6b322f4afd27cf7cda99b3c646d42633b4c | MATLAB | 18,774 | 412 | function [J,data] = jacobian_spec_FD(mesh,varargin)
% JACOBIAN_SPEC_FD Calculates spatial distributions of sensitivity of
% field registerd on the mesh boundary to changes of chromophores
% concentrations and Mie scattering amplitudea nd power per mesh node.
% This function is specialized to be called for NIRFAST... |
4d84c999128cd24cfacde85b3b9af4a84867f6bcff283479aafebebd146b5402 | MATLAB | 18,782 | 462 | function dataout = ft_denoise_tsr(cfg, varargin)
% FT_DENOISE_TSR performs a regression analysis, using a (time-shifted set
% of) reference signal(s) as independent variable. It is a generic
% implementation of the method described by De Cheveigne
% (https://doi.org/10.1016/j.jneumeth.2007.06.003), or can be
% used to... |
9dd3469d77df67ebe52a33f97c251935245e1688ef85fc8062ca33b64321d407 | MATLAB | 18,789 | 414 | %% This file creates the figures and table data for the simulated experiments
% Figures 1-4 and Table 1
%% Figure 1
% make sure you have run Simulation_varyDelta_SetParameters with the
% correct parameters first.
fontsize=10;
Variable = {'Dfit', 'beta_fit', 'K_fit'};
SNR = [5,10,20];
Dvec = [3e-4,5e-4];
be... |
5851aa689b3082d5c5d4212b649fdd17aea853e8ab50f9aac2b65b60e5792d82 | MATLAB | 18,791 | 461 | function [data] = ft_megrealign(cfg, data)
% FT_MEGREALIGN interpolates MEG data towards standard gradiometer locations by
% projecting the individual timelocked data towards a coarse source reconstructed
% representation and computing the magnetic field on the standard gradiometer
% locations.
%
% Use as
% [interp]... |
a64f63e7244d82d69023bd4c8c853a818edc043843b60a3e12a9ce7396ac7b57 | MATLAB | 18,794 | 499 | clearvars -except datastruct
cellNames = fieldnames(datastruct.ANESTH.D1);
idx = {};
% Loop through each field
for i = 1:numel(cellNames)
currentField = datastruct.ANESTH.D1.(cellNames{i});
if isfield(currentField, 'ResponsiveMetrics_WN') && ~isempty(currentField.ResponsiveMetrics_WN{1,1})
idx{... |
4db39ca323959014f8029d46c2e8399f6786c713314f607de779549b81c6b6de | MATLAB | 18,810 | 474 | function GLCM_3D(varargin)
% GLCM on 3D space
[fileList,maskFiles,OPT,SPACE] = ParseParams(varargin);
tlboxDir = fileparts(mfilename('fullpath'));
currentDir = pwd;
MNIMaskVol = load_untouch_nii([tlboxDir '/data/T1_Mask.nii']);
maskMNI = MNIMaskVol.img>0;
fprintf('Starting Time: %s\n',datestr(now));
for i=1:len... |
4fd6f879f26becdba285055ae2fc3571d2cd27bb7d77f0bdf73ae1691202e4ad | MATLAB | 18,814 | 500 | function hs = ft_plot_sens(sens, varargin)
% FT_PLOT_SENS visualizes the EEG, MEG or NIRS sensor array.
%
% Use as
% ft_plot_sens(sens, ...)
% where the first argument is the sensor array as returned by FT_READ_SENS or
% by FT_PREPARE_VOL_SENS.
%
% Optional input arguments should come in key-value pairs and can incl... |
1746b3479d7e46e09d2a0dfc323143e6818c294e57084d8bd1164b7d15bbac05 | MATLAB | 18,887 | 346 | % Copyright (c) 2016, Jordan Sorokin
% All rights reserved.
%
% Redistribution and use in source and binary forms, with or without
% modification, are permitted provided that the following conditions are met:
%
% * Redistributions of source code must retain the above copyright notice, this
% list of conditions and ... |
ec746126659d7f5f8fa6c20d45dce3e118a5213c193a62e9e10adfd9c3414885 | MATLAB | 18,928 | 454 | classdef FilamentsReader < SurpassObjectReader
% FilamentsReader Read Imaris ims file Filaments object data
%
% © 2015–2016, Peter Beemiller (pbeemiller@gmail.com)
%
% See also ImarisReader | SurpassObjectReader
properties (SetAccess = 'immutable', GetAccess = 'public', Transient... |
93bc66f8afb73d3bdbc6f690fdcf948cde4cf614cc28a52f7c6d695dc51f80f3 | MATLAB | 18,971 | 470 |
function [map,num,typ,scheme] = brewermap(N,scheme) %#ok<*ISMAT>
% The complete selection of ColorBrewer colorschemes (RGB colormaps).
%
% (c) 2014-2020 Stephen Cobeldick
%
% Returns any RGB colormap from the ColorBrewer colorschemes, especially
% intended for mapping and plots with attractive, distinguishable colors.... |
a7a4b25806ab8317b9d4e41a728e9c6729f845710bae10bc9f9c1ef751ec3f27 | MATLAB | 18,971 | 470 | function [map,num,typ,scheme] = brewermap(N,scheme) %#ok<*ISMAT>
% The complete selection of ColorBrewer colorschemes (RGB colormaps).
%
% (c) 2014-2020 Stephen Cobeldick
%
% Returns any RGB colormap from the ColorBrewer colorschemes, especially
% intended for mapping and plots with attractive, distinguishable colors.
... |
1de64849ad8ee4c9ca4ebccc6dfd288767b4506d8877b5bf0293e1df06daecb9 | MATLAB | 18,972 | 420 | function [Yc,Ye,Ya,clscor] = boney_segment_refineSPM_R3(Yo,Ym,Yc,Ya,Ybraindist0,tis,tismri,refine)
% == REFINE SPM DATA ==
% * Create meninges class?
% - This is not realy working cause the intensities are changing too much.
% Hence, it is better to evaluate the whole mid structure.
% - Would thresholding by ... |
4997a983b00ece10522774582d4ff1caee892c554071c858c83ccd5e7085abdb | MATLAB | 18,981 | 523 | function varargout = DPABI_CALCULATOR_TOOL(varargin)
% DPABI_CALCULATOR_TOOL MATLAB code for DPABI_CALCULATOR_TOOL.fig
% DPABI_CALCULATOR_TOOL, by itself, creates a new DPABI_CALCULATOR_TOOL or raises the existing
% singleton*.
%
% H = DPABI_CALCULATOR_TOOL returns the handle to a new DPABI_CALCULATOR_TO... |
cb26973f1739b5326518abc23a7f3a9704f4de68e5e15416da2e16c5ced02204 | MATLAB | 18,990 | 517 | function [hs] = ft_plot_mesh(mesh, varargin)
% FT_PLOT_MESH visualizes a surface or volumetric mesh, for example describing the
% realistic shape of the head. Surface meshes should be described by triangles and
% contain the fields "pos" and "tri". Volumetric meshes should be described with
% tetraheders or hexaheders... |
8cc2822278f57906d7beabd7485551fc6d997af09f04a952ada730261068a8a7 | MATLAB | 18,991 | 471 | %% computeSDO_populateSDOArray (V4)
% Given supplied point-process and time series data sets, compute the
% stochastic dynamic operator for every supplied combination.
%
% Hardfork update to actually pass in the xtDataCell and ppDataCell classes
% directly; making the evaluation more straightforward and function-calls... |
8f3ef5d5845457c279173dc965b896e1bb2f1132b767e014c8741b59f3e86544 | MATLAB | 18,992 | 455 | function out = htmlTable(varargin)
% Display a Matlab cell array or numeric matrix as an html table
%
%PMTKauthor Gus Brown
%PMTKurl http://www.mathworks.com/matlabcentral/fileexchange/18329
%PMTKmodified Matt Dunham
%
% INPUTS:
% 'data' the data to display, an array or cell array
% 'rowNames' ... |
95a074e2fee5472e22b6d9688042ea78636e5528b169e53b4a5091db090b7380 | MATLAB | 18,995 | 587 | function [cl, dat, cl_extent, dat_extent] = iimg_multi_threshold(inname, varargin)
% :Usage:
% ::
%
% [cl, dat, cl_extent, dat_extent] = iimg_multi_threshold(inname, varargin)
%
% Multi-threshold application and orthview display of blobs
%
% :Inputs:
%
% **inname:**
% Either the name of an image file or a ... |
1872f5332dea1a754def0bfb7f6c1dc7b0b0eea8f00b9ac6ffef87b7cabae2bc | MATLAB | 19,029 | 508 | function [varargout] = ft_plot_vector(varargin)
% FT_PLOT_VECTOR visualizes a vector as a line, similar to PLOT.
%
% Use as
% ft_plot_vector(Y, ...)
% or as
% ft_plot_vector(X, Y, ...)
% where X and Y are similar as the input to the MATLAB plot function.
%
% Optional arguments should come in key-value pairs and ca... |
10ebbf9ba5be453c65fa926eb870b354a5765aaf0fa19ccdb4111ecfdb522169 | MATLAB | 19,048 | 494 | function [coef,alphas,offset,looe] = fracridge(X,fracs,y,tol,mode,standardizemode,wantlooe)
% function [coef,alphas,offset,looe] = fracridge(X,fracs,y,tol,mode,standardizemode,wantlooe)
%
% <X> is the design matrix (d x p) with different data points
% in the rows and different regressors in the columns.
% <fracs> is... |
1481cd7e1dc365be0078d5aa195f663dc594e003101122f1e33b2ec89f5f6cc8 | MATLAB | 19,068 | 377 | %% Script for analysis of food-blob interactions (Sapkal et al 2024 Fig. 5f-h)
% This only works with speicific folder,subfolder arrangement as in
% superfolder/genotype subfolders/fly folders/tracking data
% add path of edmond.de folder
% run each section in order from start to end, one section at a time.
subFo... |
baf0fa03a64a0e7b3a6d9eb70e17802597faddeb5c1a254e59cc8f792db175d5 | MATLAB | 19,125 | 403 | function [RawData, AllVolume] = yw_Harmonization(ImgCells, MaskData, MethodType, AdjustInfo, ParallelWorkersNum,OutputDir)
% [HarmonizedBrain, Header, OutNameList] = yw_Harmonization(ImgCells, MaskData, MethodType, OutputDir, Suffix)
% Harmonizes brain imaging data across multiple sites using various methods.
%
% Input... |
e7fd5cf1b7eebd2494b93f7ddfc3be62aa7e1f2320a00965cf78b868ddb3c9e9 | MATLAB | 19,135 | 332 | %% Analysis of free walking FlyTracker output from co-activation experiments (Fig2)
% This only works with speicific folder,subfolder arrangement as in this
% data
subFolders = dir(pwd);
realSubFolders = subFolders([subFolders.isdir]');
realSubFolders = realSubFolders(3:end);
% Initialise video temporal par... |
e854b747fa6aa9e2fe866cd18a826e5c70d6504aa17a8ce5df25009d5890c20f | MATLAB | 19,189 | 394 | function Multi_Histogram_Figures(AllHistogramData,TempSaveDir)
OS=computer;
if strcmp(OS,'MACI64')
dc='/';
else
dc='\';
end
FigPosition=[50 50 800 800];
FigAxesPosition=[0.2 0.2 0.6 0.6];
FigFontSizes=[22 20];
close all
if ~isempty(AllHistogramData.Ov... |
c35ee0e8cbf17b88cb10dd0503e3f43b9460a3ce4a0e7850635aebe93b8f041f | MATLAB | 19,192 | 297 | function event_related_results(stat_path,exp_folder,q_level,ground_truth)
% ========================================================================
% Ruslan Masharipov, July, 2024
% email: ruslan.s.masharipov@gmail.com
% ========================================================================
load([stat_path filesep... |
93a92d5c85c12c3aabb0b9802bf314a600f262f19ef72a3b20ba85da2b76b2c3 | MATLAB | 19,238 | 422 | function [Yc,Ye,Ya,clscor] = boney_segment_refineSPM_R3(Yo,Ym,Yc,Ya,Ybraindist0,tis,tismri,refine)
% == REFINE SPM DATA ==
% * Create meninges class?
% - This is not realy working cause the intensities are changing too much.
% Hence, it is better to evaluate the whole mid structure.
% - Would thresholding by ... |
6132b52d20a388aebc56ee6d89bee4950d4529c39100d7bb97cd3156d150fc3e | MATLAB | 19,249 | 496 | function [type] = ft_senstype(input, desired)
% FT_SENSTYPE determines the type of acquisition device by looking at the channel
% names and comparing them with predefined lists.
%
% Use as
% [type] = ft_senstype(sens)
% or
% [flag] = ft_senstype(sens, desired)
%
% The output type can be any of the following
% 'c... |
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