sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
774832a18139a77f8262d6d8c26da894fb1bc57770ff614714f8c8dcc599c95a | MATLAB | 7,426 | 280 | function h=grPlot(V,E,kind,vkind,ekind,sa)
% Function h=grPlot(V,E,kind,vkind,ekind,sa)
% draw the plot of the graph (digraph).
% Input parameters:
% V(n,2) or (n,3) - the coordinates of vertexes
% (1st column - x, 2nd - y) and, maybe, 3rd - the weights;
% n - number of vertexes.
% If V(n,2), we ... |
1292c4291bd7c1aecf0c5c39d4302e25f1fe9186e6371443eccd868323c2541a | MATLAB | 7,430 | 244 | function [C,h,Ph,F,Fa,Fc,Eh,Ch,hE,hC,Q] = spm_reml_sc(YY,X,Q,N,hE,hC,V)
% ReML estimation of covariance components from y*y' - proper components
% FORMAT [C,h,Ph,F,Fa,Fc,Eh,Ch,hE,hC,Q] = spm_reml_sc(YY,X,Q,N,[hE,hC,V])
%
% YY - (m x m) sample covariance matrix Y*Y' {Y = (m x N) data matrix}
% X - (m x p) design mat... |
6fa78269f041ced1cf71b8f13591eac13571497171f71d66b8b4fcdaa4d913a6 | MATLAB | 7,432 | 271 | % df_example1.m
% parallel-beam image reconstruction:
% comparing direct Fourier (DF) reconstruction vs FBP.
% Copyright 2005-8-10, Jeff Fessler, University of Michigan
if ~isvar('sino'), printm 'simulate data'
down = 4;
% slightly larger than 80cm fov
sg = sino_geom('par', 'nb', 1500, 'na', 700, 'dr', 0.55, ...
... |
b30fc2f5174943462ddecd60e7c43fe76f3ca493bb816d09f1b40ad54e36c083 | MATLAB | 7,432 | 154 | function Compute_Avalanches_MEG_Destrieux(path_file_MI, path_file_Rest, subject_IDs, db_path, labels_Destrieux, freq_band_def, z_thresh, fs, min_size_aval)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Compute Avalanches x dataset - 20 subj. - Sess. 4 - MEG - Desikan-Killiany
% A... |
b342833ebea31d7c254b6e7d71d20104e813613b293a34250c0b6f8e974aae7e | MATLAB | 7,440 | 154 | function Compute_Avalanches_EEG_Destrieux(path_file_MI, path_file_Rest, subject_IDs, db_path, labels_Destrieux, freq_band_def, z_thresh, fs, min_size_aval)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Compute Avalanches x dataset - 20 subj. - Sess. 4 - EEG - Desikan-Killiany
% A... |
e093f2757059fd3f888dcc7791f713ba66f6e26ffc4db86c3923a3b8e7f4431b | MATLAB | 7,440 | 186 | %% This script is written to perform statistical analysis on information
%% reconstructed using the gpr reconstruction approach applied on time-
%% continous data.
% This script is a merge between a script by Joram Soch to estimate
% balanced accuracy from gpr based reconstructions and a script by Gi-Yeul
% Bae to co... |
4121e4609f833f7a22c3043f4d6600caae44228319fbbea0c305f85bd6b785d2 | MATLAB | 7,449 | 245 | function supplFigS6(analDir,rrmDir,tsDir,figDir)
% function supplFig6(analDir,rrmDir,tsDir,figDir)
%
% plot supplFig6: PSTHs across sessions separately for M1 and M2, Movement
% index across all units.
% save figure as *fig and pdf
%
% input:
% analDir path to directory of results for model-free analysis
% r... |
4454c71b6cd857ee5d466cadc5c97b447982b7971919827c6f1c6ef7b44dd10c | MATLAB | 7,457 | 190 | function [fig, cPnl] = openCPanelFig(clientList, subPanels)
% function [fig, cPnl] = openCPanelFig(clientList, subPanels)
%
% Opens a figure with clientPanels. Each clientPanel can monitor (control)
% remote (local) paradigms. Closing the figure also cleans up all the
% connections made by the clientPanels.
%
% Clie... |
1679ee2b306f58ea95700308ea6d253054c16036c3ecf945a907f641e3bbd61d | MATLAB | 7,471 | 201 | function str = spm_file(str,varargin)
% Character array (or cell array of strings) handling facility
% FORMAT str = spm_file(str,option)
% str - character array, or cell array of strings
% option - string of requested item - one among:
% {'path', 'cpath', 'fpath', 'basename', 'ext', 'filename',
... |
a63a9aeca32c22599aea08477c3a150cf7ed0421184c850e56d1a1ff7612f7e9 | MATLAB | 7,473 | 268 | function [block] = spm_vb_init_block(Y,block)
% Initialise Variational Bayes for GLM-AR models
% FORMAT [block] = spm_vb_init_block(Y,block)
%
% Y - [T x N] time series with T time points, N voxels
% block - data structure (see spm_vb_glmar)
%_______________________________________________________________________... |
0b5b410dcd8279b8a71effe256a51f9b6936b6efe0b910f1e282b433a26cdc6a | MATLAB | 7,474 | 309 |
%%
% FINAL parameters based on the GLM fitting to NEST data in script
% defaults
% (seconds)
% p(1) - delay of response (relative to onset) 6
% p(2) - delay of undershoot (relative to onset) 16
% ... |
a2d404edd6475ceccef730a19e33673ca4e07b0cf23242be8950c54213491e72 | MATLAB | 7,475 | 163 | function [labels, names, colors, line_styles, markers] = fn_condition_label_styles(grp_id)
%% Converts the name of a set of conditions into labels, plotting colors/styles
% Mostly for Target Time, but also some Oddball conditions
% INPUTS:
% grp_id [str] - label for group of conditions to select
% 'Dif': {'Ez... |
8e083726920e7cc64bfa9386595d58100ce64ca75f05734f1c42586a5a458a6b | MATLAB | 7,481 | 192 | % epoch() - Extract epochs time locked to specified events from continuous EEG data.
%
% Usage:
% >> epocheddata = epoch( data, events, timelim);
% >> [epocheddata, newtime, indices, rerefevent, rereflatencies ] = ...
% epoch( data, events, timelim, 'key1', value1, ... );
%
% Inputs:
% data ... |
ddbcaf6720662624499493821da4ee8829b164f2dae9d009b6eb03988a18998c | MATLAB | 7,483 | 186 | function [cp_horz, p_horz, cp_vert, p_vert, cp_combined, p_combined, countingmatrix_custom] = cross_validate_multicoder(data, labels, varargin)
% cross_validate_multicoder Perform cross-validated decoding using model
% of your choice. Uses `multicoder` architecture
% ... |
a1fd7a97a6d5f640270b8621c01972ab4c69d124b07a13136a0eef1c0d4d57f1 | MATLAB | 7,498 | 163 | function [ ev_ho_x, ev_ho_y, lawn_limit_line] = geteventhorizon_freehand(background, outer_boundary_mask, lawn_limit_line, pixpermm, th)
%GETEVENTHORIZON_ROUGH.M this function takes in the background image (not
%blurred) and extracts the convex hull -- the limits of the lawn boundary,
%not taking into consideration all... |
06f43a8abbb3594ade001e1f5c8e709b74e9017bb7667764a40d79710e01f4bd | MATLAB | 7,506 | 138 | function linker_features = fun_graph_get_linker_features(linker_str_array, vessel_graph)
% fun_graph_get_linker_features computes features for fake linker
% classifier from linker_str
% Input:
% linker_str_array: structure array computed by fun_graph_connect_gap_p2p
% Output:
% linker_features: linker features
% ... |
ec737c9b809c09c57b6227ea2d156f764eb3d1fb2bcabf0059b1244ce6334659 | MATLAB | 7,506 | 328 | % Gcone_test.m
% test the Gcone object
% Copyright 2008-1-1, Jeff Fessler, University of Michigan
printm 'todo: check user_source_zs vs hct2 with file_source_z'
pn = jf_protected_names;
f.sf1 = {'sf1', ...
'sf1,p:ts,b:st', 'sf1,p:st,b:st', ...
'sf1,p:ts,b:ts', 'sf1,p:st,b:ts'};
f.sf2 = {'sf2', ...
'sf2,p:ts,b:st'... |
01ecec305f3faf5326e1ae1f812928f030cabdaa6e7eb189008eccd589fa9f42 | MATLAB | 7,507 | 196 | function [bhv] = SBJ03_behav_parse(SBJ, block_ix, proc_id, plot_it, save_it)
%
% SBJ [str] -- uniquely identifies the subject, e.g., 'IR54'
% block [int] -- index of which block of data should be analyzed
% proc_id [str] -- name of the processing pipeline (to get resample rate)
% plot_it [0/1] -- optional. plot_it... |
408970f1ffad0878776c5a90ccc6d597a24a1bb38ba86baf68a7f67c9a88767e | MATLAB | 7,507 | 146 | function total = keyBuffer(duration,varargin)
% This buffer stores behavioral responses over a period of time specified
% in duration. In addition, it terminates if a specified number of responses
% on "good keys", "neutral keys" or "bad keys" is reached.
% To use this feature specify at least the position of the good,... |
9b4e4298c5215fec2a27bc190f17b7bc6d70288c24f01c9e045d75ea5022dd1a | MATLAB | 7,507 | 220 | function EEG = c_EEG_epoch(varargin)
p = inputParser();
p.addRequired('EEG',@isstruct);
p.addParameter('timeBeforeEvent',0,@isscalar); % in s
p.addParameter('timeAfterEvent',0,@isscalar); % in s
p.addParameter('timespan',[],@(x) isempty(x) || (isvector(x) && length(x)==2) || (ischar(x) && strcmpi(x,'auto'))); % in s
p... |
efb48eeecd2ebe33abce92d35be0e16f6d1b1792ec9c874eb03d6628bf64f513 | MATLAB | 7,529 | 179 | % plot cluster determined group bar plots
clear all;close all;clc
fn_ext = '_cue_responseive_yes'
baseline = [ '_cond_spec_prestim' fn_ext]
lock = 'onset' % onset % response
exp_type = 'tuning_correct'% 'encoding' 'tuning_correct'
ref = 'LM'
plot_4_conds = ''
addpath('/mnt/yassamri/iEEG/sandra/an... |
33f5308c9de734811dcfcaf4425be8e3673c1b609409b073ab35b40e89a6c35d | MATLAB | 7,538 | 163 | function [negLogLik prWord_log] = hills2015_model_decay_softmax_hybrid_concat2_wordECDF(best_params, obs);
% SOFTMAX local search model (allows saliencies <= 0)
%
% _vers2 does not explicitly model a 'general' saliency with
% semantic_weighting [0, 1] to arbitrate semantic vs lexical similarity.
% Instead it directly f... |
55e897efdef795427851f1a658f95be6a5b075a8ad130ff05d29570b4490dbac | MATLAB | 7,540 | 192 | function [rm,tbl,A,C,D] = simple_mixed_anova(datamat, varargin)
% tbl = simple_mixed_anova(datamat, between_factors, within_factor_names,
% between_factor_names)
%
% Repeated-measures or mixed ANOVA with any number of factors.
%
% Function built on top of existing MATLAB functions in an attempt to
% simplify user inp... |
41557bfb904418210e4af1c9becb8a9c1d1d5944513e0f2a26e2488588419cef | MATLAB | 7,544 | 154 | % TIME SHUFFLE
% Disrupts temporal/phase domain. Random shuffle of the phases of the average theta cycle (columns). Keep relationship between spike
% probability and position intact, but disrupts relationship between phase and position.
% INPUT -
% num_shuffles: integer
function [time_bin_shuffles,time_shuffle]... |
7b5e61e9f38484b2b433ca78ebf8e2c8cc4e6fd902531b61cc3e70421d8c0352 | MATLAB | 7,544 | 230 | function[prm] = pbups_psych_gamma(data, varargin)
p = inputParser;
addParameter(p,'h_ind', []);
addParameter(p,'pR_ind', []);
addParameter(p,'trial_back', +1);
% +1 means 1 trial after the conditioned trial
addParameter(p, 'xreg','gamma'); % gamma/ Delta
addParameter(p, 'binwd_delta', 2); % binwidth for deltaclicks ... |
96febb410269ce1cc399300f049760d51032490b57c982c690665b9129f4e7ff | MATLAB | 7,545 | 290 | function Answer = c_inputdlg(varargin)
if nargin == 0, testfn(); return; end;
persistent pathModified;
if isempty(pathModified)
mfilepath=fileparts(which(mfilename));
addpath(fullfile(mfilepath,'./ThirdParty/findjobj'));
addpath(fullfile(mfilepath,'./GUI'));
pathModified = true;
end
p = inputParser();
p.addRequir... |
b40ce89d92ed1c0221da8bd7afb951c840bbed1fff1d6c1c8f1fa262a887df42 | MATLAB | 7,546 | 222 | function co_stitch(target, datapath,disp,mosaic,pxlsize,islice,pattern,sys)
%% stitch the fitting result using the coordinates from AIP stitch
%% define grid pattern
% add subfunctions for the script
addpath('/projectnb/npbssmic/s/Matlab_code');
% displacement parameters
% xx=92;
% xy=-4;
% yy=97;
% yx=-4;
result=targ... |
024b3d10a5e4be187eb4a45da87335fb02efad849250f894cba0e1295774d5a4 | MATLAB | 7,553 | 166 | % Proportion of significant replay events
function proportion_of_sig_events(computer)
% Load name of data folders
if strcmp(computer,'GPU')
sessions = data_folders_GPU;
session_names = fieldnames(sessions);
elseif isempty(computer) %normal computer
sessions = data_folders;
session_names = fieldnames(s... |
a350d946432b7028c8df36258daf0299889f8edffb3fe082d0e8e148a9e38e39 | MATLAB | 7,553 | 222 | function co_stitch(target, datapath,disp,mosaic,pxlsize,islice,pattern,sys)
%% stitch the fitting result using the coordinates from AIP stitch
%% define grid pattern
% add subfunctions for the script
addpath('/projectnb/npbssmic/s/Matlab_code');
% displacement parameters
% xx=92;
% xy=-4;
% yy=97;
% yx=-4;
result=targ... |
7fd48a018dbbc4ec74123f2d8c16c210022f3f8ac0bff7451e99daaba1d9d87f | MATLAB | 7,554 | 201 | function model = spm_mvb(X,Y,X0,U,V,nG,sG)
% Bayesian optimisation of a multivariate linear model with a greedy search
% FORMAT model = spm_mvb(X,Y,X0,U,V,nG,sG)
%
% X - contrast or target vector
% Y - date feature matrix
% X0 - confounds
% U - patterns
% V - observation noise covariance
% nG ... |
db3b43d0d48eab0c1c50521adadd2d9776eb971cadbe7701b3a8eda5babc3230 | MATLAB | 7,567 | 206 | function out = bIO(pinNr, status)
% This function handles the IO communication of the IO pins on the
% Raspberry Pi 2 and 3.
% bIO(inputNumber) returns the status of the selected input
% bIO(outputNumber, status) sets the selected output to either 1 or 2
%
% The hardware provides 5 inputs and 6 outputs. That number is ... |
faf022e92c7aae6176cf5e87dbb685ecc60f6a9c9e40051be7050bea69fba4f2 | MATLAB | 7,573 | 159 | function [PlaceCells,Tinfo,infoScoreThresh] = permutingSpike_speed(neuron,behav,thresh,deltaTall,occThresh,nboot,binsize,Stype,Method)
% This function aims to identify place cells by shuffling neuron
% spikes over a course of random time shift. Get a distribution of shuffled
% information scores and make 95% of the dis... |
46b851ea3171b91955f7b429100f8958238ff2860390ed28ea71bdd1f61a2ab2 | MATLAB | 7,575 | 185 | function cameracontrol(cameras, varargin)
% Record up to 8 ip cameras with matlab
% More cameras is easily possible with copy/paste
% Argument cameras is a cell array with every ip as a string in a single
% cell and can be predefined or put in as an argument
% Preview is 1 or 0 if the matlab preview window should be op... |
238e3dc5cb10f3a132080313aab4a5c203569522e94c9daf2ecc64442687b287 | MATLAB | 7,590 | 276 | %requires SPM to be installed and in the path
clear all
rng shuffle
for ttt = 1:5
switch ttt
case 1
trials = 25;
case 2
trials = 50;
case 3
trials = 100;
case 4
trials = 200;
case 5
trials = 400;
end
runs = 5000;
trials1 = trials*7;
ts = zeros(runs, trials1);
ts_est = ... |
23a4d916e7dc47183bf7aafd93af526be753b42fcfd2a2e64eff099f158dac2c | MATLAB | 7,608 | 329 | function M = qpwls_precon(type, sys, C, mask, varargin)
%function M = qpwls_precon(type, sys, C, mask, varargin)
%|
%| build a preconditioner for QPWLS problems:
%| approximations to inv([A'WA + C'C])
%|
%| usage:
%| M = qpwls_precon('circ0', {T}, C, mask);
%| M = qpwls_precon('circ0', {A, W}, C, mask);
%|
%| in
%| ty... |
4527e17b66b2aaa974cdfcc374b79ef0d98aaa41dd28f2a0b877b24963d6c669 | MATLAB | 7,611 | 205 | function db_out = SBJ00b_view_preclean(SBJ,block_ix,keep_db_out,varargin)
%% View SBJ00_preclean output with channels colored by type
% INPUTS:
% SBJ [str] - name of patient
% block_ix [int] - which block to plot
% keep_db_out [0/1] - return the output of ft_databrowser to save epochs
% varargin:
% bad_ep... |
f30b5fa0ca96fca03d68bc98d0f2839f651b4dbed4a3266777f4bb729e5a18d1 | MATLAB | 7,611 | 189 | classdef AbstractFW < handle
% AbstractFW Base class for Frank-Wolfe algorithms. Handles outer loop
% and convergence checks.
%
% For example, the run() loop can handle some callbacks at a given
% interval.
properties
algoName
obj
dualityGap
opts
... |
29dd7d517493fe3ff40943e8f5813ba29bac39ddddc2e3b0d0f8e8e1497d556f | MATLAB | 7,613 | 183 | function bHand = createButton(text, varargin)
% Creates a button (framed text) on the stimulus window.
%
% Draws the given text with a frame around it and returns the bounding box
% as a handle. Use getButtonClick (or the Psychtoolbox function GetMouse) to
% check whether the user clicked inside the button.
%
% Usage: ... |
c688c0fee018a2285019732e3cfe3411b0100da1051bbf2699d72804ffd0a6e3 | MATLAB | 7,615 | 164 | % TIME SHUFFLE
% Disrupts temporal domain.
% INPUT -
% num_shuffles: integer
% thresholded_decoded_thetaSeq_option: 1 if using theta sequences that have passed the position threshold (not happening neither at the
% start or end of track)
function time_shuffle = average_theta_sequences_timebins_shuffle(n... |
d2ebc160faa961450ff8bfab9202caf52bd13bd27edf276b4c2db8a123782065 | MATLAB | 7,629 | 223 | function [result] = bfopen(id, varargin)
% Open microscopy images using Bio-Formats.
%
% SYNOPSIS r = bfopen(id)
% r = bfopen(id, x, y, w, h)
%
% Input
% r - the reader object (e.g. the output bfGetReader)
%
% x - (Optional) A scalar giving the x-origin of the tile.
% Default: 1
%
% y - (Optional) ... |
2e237320452e009d4e7023c8cff4fd19df763adadf8fb71415b07954185acbd1 | MATLAB | 7,634 | 216 | function Mus_stitch(target, P2path, datapath,disp,mosaic,pxlsize,islice,pattern,sys,ds,stitch)
%% define grid pattern
% add subfunctions for the script
addpath('/projectnb/npbssmic/s/Matlab_code');
result=target;
id=islice;
xx=disp(1);
xy=disp(2);
yy=disp(3);
yx=disp(4);
% mosaic parameters
numX=mosaic(1);
numY=mosaic... |
bf85400242a5480f2d02677f94382d143eefce72e49c2c2bcdac4a995cfa83d1 | MATLAB | 7,641 | 219 | function MIP_stitch(target, P2path,datapath,disp,mosaic,pxlsize,islice,pattern,sys,stitch, aip_threshold)
%% stitch the retardance using the coordinates from AIP stitch
% add subfunctions for the script
addpath('/projectnb/npbssmic/s/Matlab_code');
id=islice;
filepath=strcat(datapath,'mip/vol',num2str(islice),'/');
cd(... |
c5b22100954599a2d90266be29c5df569e2dfec53380c13dbfa324d5ac790192 | MATLAB | 7,641 | 194 | function vdm = FieldMap_Run(job)
% Auxillary file for running FieldMap jobs
% FORMAT vdm = FieldMap_Run(job)
%
% job - FieldMap job structure containing various elements:
% Common to all jobs:
% defaults - cell array containing name string of the defaults file
% options - structure containing the... |
83285e9299aa6ef4e58dbba505b6d01cd589a5c3f626954f00d6f67d5d08cca7 | MATLAB | 7,643 | 192 | function [tbl,rm] = simple_mixed_anova(datamat, varargin)
% tbl = simple_mixed_anova(datamat, between_factors, within_factor_names,
% between_factor_names)
%
% Repeated-measures or mixed ANOVA with any number of factors.
%
% Function built on top of existing MATLAB functions in an attempt to
% simplify user inputs an... |
ecf2579ca9223900f407d345f26a464e3bb2118cbd2c3ead6a368a33cc4a3c97 | MATLAB | 7,643 | 138 | function linker_features = fun_graph_get_linker_features(linker_str_array, vessel_graph)
% fun_graph_get_linker_features computes features for fake linker
% classifier from linker_str
% Input:
% linker_str_array: structure array computed by fun_graph_connect_gap_p2p
% Output:
% linker_features: linker featu... |
6f56b14f3cbaa9a4b2025796e2bdb000c032ba2dcf8dc1951cb1dee73c4ea698 | MATLAB | 7,651 | 178 | classdef LoopyModelCollection
properties
%Properties & Definitions
models;
x_train; x_test;
computed_true_logZ;%archaic
hidden_model;%arhaic
end
methods
function self = LoopyModelCollection(models,params)
self.models = models;
... |
17ecea06557df5adf98a9e7ef84d2253237fd890b0b112c4301327a95aaf151f | MATLAB | 7,652 | 238 | function [RCM,BMC,BMA] = spm_dcm_bmr(P,field)
% Bayesian model reduction (under Laplace approximation)
% FORMAT [RCM,BMC,BMA] = spm_dcm_bmr(P,[field])
%
% P - {Nsub x Nmodel} cell array of DCM filenames or model structures
% of Nsub subjects, where each model is reduced independently
%
% field - paramete... |
b527a3c58301b7bc22b761434451892b41ec1735430326794c52289ea3621e47 | MATLAB | 7,660 | 255 | clc;clear;close all
rng(1,'twister');
% computing PSTHs
clear
all_units=0;
rootpath='..\dataset\Mice\result\total_clusterArea_paper_results_kernel_0\_clustering\';
postfix='';
if(all_units)
postfix=[postfix,'_allUnits'];
end
matPath=[rootpath,'_dpca\'];
load([rootpath,'clusteringFeature',postfix])
%as described... |
ade752de32ffe669e533498316b2afc0b8e3333f1c66965c10777dcf8f3baec8 | MATLAB | 7,661 | 171 | function Figure_8A_S7C_plot
%
% Written by Ayaka Matsumoto, October 2023
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Output: Figures 8A and S7C
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
49f399f74a4bcc9596827d876d3e549ba2e29d0437e6faa90bebfd2f1aac20ed | MATLAB | 7,668 | 121 | % COMPARISON SHUFFLE TO REAL DATA HISTOGRAM OF PVALS
% MH 2020
% Compare population vector analysis distributions versus shuffles.
% INPUT:
% remap: 'global' or 'rate' for different types of remapping
function protocol = compare_shuffle_PV_corr_pvalues(remap)
if strcmp(remap,'global')
load('X:\BendorLab\Drob... |
9af371ed31d22a3906628e7e95caf75d56d72f996a2d425015c4cbafdfe3b773 | MATLAB | 7,668 | 248 | function [Dice]=ribbon_adf(subject, th_pval)
% For each subject "subject":
% Computes the Dice coefficients measuring the overlap of the
% Cortical Ribbon volume computed
% 1- from the subcortical labeling
% 2- as the space between the white and the pial surface
%
% Uses the pvalues, tr... |
9427b4be1b272db991266bb7438c1fe1ed26e605d591472df264b1883ce24dba | MATLAB | 7,676 | 165 | % GIBBS_SAMPLER receives parameters of a Markov Random Field in the
% Ising Model and through stochastic methods samples the variables and
% determines the marginals of each random variable.
%
% Usage
% sampler = gibbs_sampler(node_potentials, edge_potentials, (optional) burn_in, (optional) gap)
%
% Input
% node_p... |
6df5522434e54440f159fe74ccb4496d9c9ca9e7abe6e09fcf695dd63c72cd1f | MATLAB | 7,677 | 222 | clc;clear;close all;
root='..\';
addpath(genpath([root,'NeuralCorrelateEvidenceAcc']))
addpath(genpath([rootpath,'npy-matlab-master\']))
addpath(genpath([rootpath,'steinmetz-et-al-2019-master\']))
%%
datapath='..\dataset\Mice\';
rootpath=[datapath,'9598406\spikeAndBehavioralData\'];
outpath=[datapath,'result\'];
regCl... |
73ac4c409502e89b0ccdb9c3bf36b113a5e093b3a09da288fd97ab1290b47159 | MATLAB | 7,678 | 177 | function [significantVarWei,significantVarMax,pValWei,pValMax] = distances_both_tasks_weighted_cluster_perm_stats(subjects,category,if_save,numPermutations,method)
%DISTANCES_BOTH_TASKS_WEIGHTED_CLUSTER_PERM_STATS Perform weighted cluster permutation stats to calculate the
%significance of the timepoints in the distanc... |
cd7dbfbd8e3392a2130d2df4561a5daaefe2683f57f7e9d66797833b2caba48c | MATLAB | 7,682 | 246 | function [wmap, wconv] = mri_field_map_reg(yik, etime, varargin)
%function [wmap, wconv] = mri_field_map_reg(yik, etime, varargin)
%|
%| MRI field map estimation using regularization and optimization transfer,
%| based on a multiple image model:
%| y_ik = mag_i * phase_ik * decay_ik + noise_ik
%| phase_ik = exp(1i * w... |
4627541a87c470445e00ec0eb6c135106fef5c98be2dbd2351e29de8e8fd9835 | MATLAB | 7,692 | 146 | % THETA SEQUENCES QUANTIFICATION: SPIKE TRAIN CORRELATION
% MH, 2020
% From Feng et al (2015,J Neuro). For each theta sequence, calculate Pearson's linear correlation coefficient between spike timing and place cell peak
% firing positions for spikes emitted during 45-315 degrees of individual theta cycle (referenced to... |
99a0955c884fa7266888b639c3da157849210cc0ff81271d7e708ff26b12bc6d | MATLAB | 7,696 | 151 | function modelParameters = setDefaultModelParameters(data,BW,model,environment)
% function setDefaultModelParameters(data,BW,model,environment)
% Function that sets the default model parameter values.
%
% Input:
% - data: timetable which contains the data to be used by the tool;
% - BW: the patient's body weight;
%... |
3effaba8c7e9679c42d8d04d51d28267865ca759c383260ad55ecd1dfed70ca1 | MATLAB | 7,697 | 176 | % plot cluster determined group bar plots
clear all;close all;clc
reg = 'NC'
fn_ext = '_cue_responseiveyes'
baseline = [ '_cond_spec_prestim' fn_ext]
lock = 'onset' % onset % response
exp_type = 'tuning_correct'% 'encoding' 'tuning_correct'
ref = 'LM'
plot_4_conds = ''
addpath('/mnt/yas... |
3049a3171bdb4da7f44b1ec5d199cf23ff0c8678e5f7da2ef67e76369277d1a7 | MATLAB | 7,706 | 142 | function [ratemapt_LRm, frLRm, countLRm, timeLRm] = match_smooth_trim_ratemap(neuronIndivLR, behavIndivLR, thresh, condition)
% This function performs multiple steps for ratemap analysis
% 1. downsample data to match bahavior coverages across left and right cpp
% experment chambers or across different sessions;
% 2. ca... |
1d6e1f5c79ed312e74921fbc508f717cbcaa7092c88a973dd4d52a33df0866bb | MATLAB | 7,709 | 224 | %% Check which root directory
if exist('/home/knight/hoycw/','dir');root_dir='/home/knight/hoycw/';ft_dir=[root_dir 'Apps/fieldtrip/'];
else root_dir='/Volumes/hoycw_clust/';ft_dir='/Users/colinhoy/Code/Apps/fieldtrip/';end
%% Set Up Directories
addpath([root_dir 'PRJ_Error/scripts/']);
addpath([root_dir 'PRJ_Error/sc... |
1d5d6ed3ad031593ca0f7e96b650bf0763b06680d50b62c7b9acf96c531af3f2 | MATLAB | 7,714 | 175 | function lf = fun_graph_get_link_w_1_ep_features(link_cc, vessel_image, vessel_mask_dt)
% fun_graph_get_link_w_1_ep_features computes the features derived from the
% position and orientation of endpoints and their nearest neighbor
% Input:
% ep_sub: N-by-3 numerical array, where N is the number of endpoint and 3
% ... |
5e81624a5e18952c405adc1f3b91ee46b6ca927450d4031c8c71f66cdf13620d | MATLAB | 7,714 | 314 | function xrs = xray_read_spectra(stype, varargin)
%|function xrs = xray_read_spectra(stype, [options])
%|
%| Read X-ray spectra data and initialize a structure that describes "M"
%| piecewise constant polyenergetic X-ray spectra, where M=2 for dual-kVp case.
%|
%| in
%| stype char which spectrum model:
%| 'mono,6... |
75756d04f9065b3ed6718877648b1a20a47ab7c7992e7b81fb03b45e9e87ec1d | MATLAB | 7,720 | 198 | function [S Rex] = rho_s(Sim)
% comments here
% last change: 2014/04/03 by PS
P = Sim;
xZspec = Sim.xZspec;
w_ref = 2*pi*P.FREQ;
w1 = P.B1*gamma_2pi;
da = (xZspec-P.dwA)*w_ref;
theta = atan(w1./da);
S.theta = theta;
S.Reff_sincos = -P.R1A*cos(theta).^2 -(P.R2A)*... |
0c05ee8ea1b9d00386377f09f7e9d4f16ca385548b82763525c049330d6e0790 | MATLAB | 7,727 | 287 |
% Notes
% -----
% This code runs five time, for each of these conditions listed by H_flag
H_flag = 5;
if (H_flag == 1)
H2 = Hb;
elseif (H_flag == 2)
H2 = Hr;
elseif (H_flag == 3)
H2 = Hrg;
elseif (H_flag == 4)
H2 = Hgb;
elseif (H_flag == 5)
H2 = Hgb;
end
% Image of orange on a tree and he... |
403f5a19944d7fa0669a0c2cc5d541aea6c8a15d88b49b90caa346ed5e60b621 | MATLAB | 7,730 | 218 | %subjectList = [ 16, 18:21, 24, 26, 27, 28, 29, 31, 32, 33, 34, 35, 39, 40, 41, 42, 43, 47, 50, 51, 52, 54, 55, 57, 58];
subjectList = [ 16, 18:21, 24, 26, 27, 28, 29, 31, 33, 34, 35, 42, 43, 47, 50, 51, 52, 54, 55, 57, 58];
%subjectList = [ 19,21,24,26,27,31,33,35,39,40,41,47,50,55];
subjectList = [62:64,66,68,70]; % ... |
9a3d336d5c8184e020bc9ba08652de6b9d69c17eaf7a5dca12eb90b7735e068f | MATLAB | 7,733 | 203 | function [all_plv, all_iplv] = channelwise_plv(data_1, data_2, foi, nseed, Niterations, ...
fsample, padding, time2use, method)
% #########################################################################
% ---- INPUT ---- %
% 1. data_1 = seed data
% 2. data_2 = data that is used to compute PLV to ... |
8ba453bbc2c121eb36ded072335aa75826e4d1eaa7457b7caf1323f8dddbbc89 | MATLAB | 7,746 | 283 | function proj = cylinder_proj(cg, params, varargin)
%function proj = cylinder_proj(cg, params, [options])
%|
%| Compute set of 2d line-integral projection views of (elliptical) cylinder(s).
%| Works for these 3D geometries:
%| parallel beam
%| flat-detector cone-beam
%| arc-detector cone-beam (3rd generation CT)
%| to... |
d2068a39fd4bcbf879dbdd7a13b2dbb9b540ebf8ecb1fa6602203cdfcc7cf915 | MATLAB | 7,746 | 213 | % PLOT AVERAGE PHASE PRECESSION SCORES PER PROTOCOL
% MH 2020
% Loads phase precession scores per track and session ('extracted_phase_precession_absolute_location.mat').
% First plot - calculates the mean phase precession scor per track and protocol (1,2,3,4,8,16 laps and re-exposures). Plots as a line plot with error... |
ce88baee466ae8ffb69d4ad4f152f3e9406e21dfdd972cd96ddd4bbc3e8106d5 | MATLAB | 7,754 | 141 | %% NATSORTFILES Examples
% The function <https://www.mathworks.com/matlabcentral/fileexchange/47434
% |NATSORTFILES|> sorts filenames or filepaths in an array |A| (cell/string/struct)
% taking into account number values within the text. This is known as
% _natural order_ or _alphanumeric order_. Note that MATLAB's ... |
7a7a4ac1a75fcb0186894cc7e1f86b0f37d4411c229fb163977befbb6d313ec0 | MATLAB | 7,756 | 193 | %% Prepare Matlab
clear
clc
addpath(genpath('S:\Libraries\hcsforge\LCSBMatlabLibrary'))
%% Document script
%SavePathMainDirectory = 'S:\HCS_Platform\Data\SilviaBolognin\HumanSamples\LAMNB1\';
SavePathMainDirectory = 'S:\HCS_Platform\Data\IsabelRosety\Confocal\GBA_LAMP1_MAP2\20211209_488LAMP1_568GCase_647MAP2';
Analys... |
3c93c87328501b105224b9ddb3a1322557c7d8019c82ca456ee47003f0c3a430 | MATLAB | 7,763 | 187 | function control_plots_phase_precession(track)
% Sanity check plots at different time points of theta phase precession extraction code
% Uses output from main code 'phase_precession_absolute_location', which is a structure called TPP
load('extracted_phase_precession_absolute_location.mat')
load('extracted_position.ma... |
e3d972a549b1f4d29b8aafb61cd8b1edee09bad7d1a41cae1a2a5948b772b803 | MATLAB | 7,782 | 191 | function Optical_fitting_6692_fix_rayleigh(co, cross, s_seg, z_seg, datapath)
% Fitting scattering and retardance of brain tissue
% co: volume data for co pol
% cross: volume data for cross pol
% s_seg: slice number
% Z_seg: tile number
% datapath: datapath for original data
cd(datapath);
opts = optimset('Disp... |
c18af246b84c3dfb12a21ae76228627b218c20ed6f3088465871dcedb18f5b26 | MATLAB | 7,791 | 281 | function makeMapMovie(obj,iterSequence, RGCidx, SCidx, resolution, frameRate)
if(~exist('iterSequence') | isempty(iterSequence))
% Load the iter sequence of the current object.
iterSequence = obj.loadIterSequence();
end
if(~exist('RGCidx'))
RGCidx = [];
end
if(~exist('SCidx'))
SCidx = [... |
6d28b3a555f4bac7d1dec6f009b009e49ee851cf4ee7e3afe7c05412f707b3a6 | MATLAB | 7,794 | 261 | function varargout = roipoly_adv(varargin)
global CERRADO;
%MODIFY VERSION OF ROIPOLY TO BE USED WITH ROI
%
%ROIPOLY Select polygonal region of interest.
% Use ROIPOLY to select a polygonal region of interest within an
% image. ROIPOLY returns a binary image that you can use as a mask for
% masked filt... |
a9ec507061722fc12bb7f480b4f95fc62b32f478a2552f4abf12dd83c6afa216 | MATLAB | 7,795 | 226 | function ob = fatrix2(varargin)
%function ob = fatrix2('odim', odim, 'mask', mask, 'arg', arg, [options])
%|
%| Construct fatrix2 object, a matrix generalization for representing
%| any linear operator. The 'f' might stand for 'fake' or 'function-based'
%| or 'fancy' or maybe a last name?
%| The caller can provide a ... |
aaf66d46c1d0c8211fcef65fc84aba7ac4e58a642b45e1dead1d2b89140e2312 | MATLAB | 7,800 | 215 | function Mosaic(datapath,disp,mosaic,pxlsize,islice,pattern,sys)
%%% ---------------------- %%%
% function version of mosaicing & blending
% input: displacement parameters: four elements array [xx xy yy yx]
% mosaic parameters: four elemetns array [number of x tile, number of y tile,
% ... |
458c02fcaead7f54bda59416cb7e83b5880dbda3c31b1a2cefc0e3a51c4ec60b | MATLAB | 7,805 | 256 | %% Computes sequence score by calculating the probability and asking for it to be larger than 3 ensembles
%Without significance
clear all
close all
rec_data_path = 'C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\';
dpath='C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\';
save_data_path = 'C:\Users\xscogno\MATLAB... |
ceefb4370c09daa45a546dd0c8e3497f1812c60d425af9dae1ea5c77674a317f | MATLAB | 7,815 | 186 | function results = validate_CAP_A1(dbDir, records, outCsv)
% VALIDATE_CAP_A1 Benchmark YOUR rule-based CAP A1 detector against the
% expert annotations of the PhysioNet CAP Sleep Database (capslpdb v1.0.0).
%
% Addresses Reviewer 1, Comment 1 (and the Editor note): reports sensitivity,
% specificity, PPV, F1, and Cohe... |
a453ec558056309f5727046125ec9cddebbf134287a3bb724504d1289b402a3f | MATLAB | 7,823 | 246 | function [V,h,Ph,F,Fa,Fc] = spm_reml(YY,X,Q,N,t,hE,hP)
% ReML estimation of [improper] covariance components from y*y'
% FORMAT [C,h,Ph,F,Fa,Fc] = spm_reml(YY,X,Q,N,t,hE,hP)
%
% YY - (m x m) sample covariance matrix Y*Y' {Y = (m x N) data matrix}
% X - (m x p) design matrix
% Q - {1 x q} covariance components
%
%... |
01e9faab6990d2801df114383019bdfec12f9111974f1eb3fb2cfa962c2cad88 | MATLAB | 7,824 | 114 | % Common functions of the IPEM Toolbox
%
% IPEMToolbox\Common
% ------------------------------------------------------------------------------
%
% General:
% IPEMAdaptLevel - Adapt RMS level of signal to specified dB level
% IPEMBellShape - Generate bell-shaped curve
% I... |
59106d0f3b5abf71a902048522b10f9874cb694435771dba11fef2a871c283f6 | MATLAB | 7,826 | 221 | function res = tnueeg_spm_eeg_artefact_eyeblinks_for_correction(S)
%TNUEEG_SPM_EEG_ARTEFACT_EYEBLINKS_FOR_CORRECTION Modified SPM function:
%Detects eyeblinks in SPM continuous data file
% S - input structure
% fields of S:
% S.D - M/EEG object
% S.chanind - vector of i... |
17f6d90b86c06d2ab38605a70cb1f686ff29353be750846a0c872d93e2f75ce8 | MATLAB | 7,829 | 248 | function [handles] = spm_uitab(hparent,labels,callbacks,tag,active,height,tab_height)
% Create tabs in a figure
% FORMAT [handles] = spm_uitab(hparent,labels,callbacks,tag,active,height,tab_height)
% This function creates tabs in the SPM graphics window.
% These tabs may be associated with different sets of axes and ui... |
69cf665de4eb66b7f396994bc3c3d70c84ee7257337bd9e0a7bed21b05cccb13 | MATLAB | 7,830 | 244 | % eopn3_closedloop_openfield_pooled_graphs
% Pool the GFP and eopn3 data together inot one graph, by loading the workspace of the Pooled GFP and Pooled eOPN3 animals
%%
close all; clear variables; clc;
set(0,'defaultfigurecolor',[1 1 1])
%%
filedirectory = uigetdir('select folder'); %select the overall fold... |
9a908067d60238543007d0c48bce237f7feeb01e4a4c7394661e24f6a82e3549 | MATLAB | 7,836 | 298 | function [sino, pos, ang] = rect_sino(sg, rects, varargin)
%function [sino, pos, ang] = rect_sino(sg, rects, [options])
%|
%| Create sinogram projection of one or more rectangles.
%| Works for both parallel-beam geometry and for fan-beam geometry.
%|
%| in
%| sg sinogram geometry object from sino_geom()
%| rects [ne... |
10b1508a5ed48e7648534b7825aa5de5f2977fc406ebee5958704881df5a288c | MATLAB | 7,839 | 346 | function ob = Cdiffs(isize, varargin)
%function C1 = Cdiffs(isize, [options])
%|
%| Construct C1 object that can compute C1 * x and the adjoint C1' * d
%| for a "finite differences" matrix C for roughness penalty regularization.
%| This "stacks up" multiple Cdiff1() objects, e.g., akin to using vertcat(),
%| for possi... |
30e873119b73852ae40c86a40355fd257d6322ebe7f89e42f6461990ba050159 | MATLAB | 7,840 | 278 | function [dr,dl]=cc_cut_adf(subject, name,th_pval)
% For each subject "subject":
% Computes the Dice coefficients measuring the overlap
% of the WM volume in right and left hemispheres to check
% if the corpus_callosum is correctly located.
%
% Uses .lta transform and p values
%
%
% cc_cut_afd.m
%
% O... |
35c94e5da8e8ac165b5e2d4935e8a61c778348458b079c8d5aa6ad03e0a7a8f1 | MATLAB | 7,860 | 230 | function [fly2] = PostHocAnalysis(fly,sArena,vertices,badFlies,regions)
addpath('C:\Nicholas Data\Image Processing New Rig\Util')
f = 30;
cF = sArena.cF;
for k = 1:regions
if any(k == badFlies) || ~isfield(fly{k},'Center')
fly{k} = [];
else
ang = fly{k}.ang;
xTmp = fly{k}.Cent... |
66165845230ae2c9cb7ef8f8822568a60a156f98efe18c9e0175bb4e5afd2aa7 | MATLAB | 7,866 | 211 | %% Run scripts for SfN 2019 abstract
if exist('/home/knight/hoycw/','dir');root_dir='/home/knight/hoycw/';ft_dir=[root_dir 'Apps/fieldtrip/'];
else root_dir='/Volumes/hoycw_clust/'; ft_dir='/Users/colinhoy/Code/Apps/fieldtrip/';end
%%
addpath([root_dir 'PRJ_Error/scripts/']);
addpath(genpath([root_dir 'PRJ_Error/scrip... |
073a34003cd59c3588cb650606260a63cd258f0b2c51e224aaa55ca72dd2bac3 | MATLAB | 7,871 | 237 | function [fields,fstats,config] = graphPEAK(ratemap,varargin)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% ################################################################# %% DESCRIPTION
%graphPEAK Measure properties of image regions.
% fields = graphPEAK(ratemap) counts the number of f... |
3e379b0f89e3f6994a901d08d4692870d4d1520b1f026ccf982d3aef78291425 | MATLAB | 7,880 | 232 | function[]=co_cross_stitch(id,datapath, depth, thickness)
% add path of functions
addpath('/projectnb/npbssmic/s/Matlab_code/fitting_code');
addpath('/projectnb/npbssmic/s/Matlab_code/PostProcessing');
addpath('/projectnb/npbssmic/s/Matlab_code/PSOCT_code');
addpath('/projectnb/npbssmic/s/Matlab_code/ThorOCT_code');
ad... |
6c13476ba51f7393f138d520f1372b817a932774095ebf86c78986d5c98f4486 | MATLAB | 7,880 | 303 | function ob = Gblur(mask, varargin)
%function ob = Gblur(mask, options)
%|
%| Construct Gblur object for image restoration.
%|
%| See Gblur_test.m for example usage.
%|
%| in
%| mask size(image) logical array of object support.
%|
%| options
%| 'chat' verbose printing of debug messages
%| 'psf' point spread function... |
5de414e0c558f1d8cf7d25e90b76452e8491bdb4df26fd7d1009b75618143615 | MATLAB | 7,883 | 158 | function [hout] = plotAdded_modified(varargin)
%plotAdded Added variable plot
% plotAdded(LM,CNUM) produces an added variable plot for the term that
% multiples coefficient number CNUM in the LinearModel LM. An added
% variable plot illustrates the incremental ef... |
c9343c56d52847c312b360368d1e5c3467ac8f907380bfe264ccc26fbdf5eeb8 | MATLAB | 7,885 | 192 | function buffer = shuffleVectorRestricted(in, constrains, maxRep)
% This function randomizes a given vector using several constraints.
% The number of constraints is not limited, but should not exceed a
% reasonable level, otherwise randomisation is not possible and an error
% occurs. Constraints have to be defined as ... |
3e092e2f1d2c1ab61c37f1a7e17ab36ff839258fd8ba745578a1301b1d3a6628 | MATLAB | 7,887 | 286 | function nvr_writewavefile(Fs,nbits,wavefile,wavefile2)
%WAVWRITE Write Microsoft WAVE (".wav") sound file.
% WAVWRITE(Y,FS,NBITS,WAVEFILE) writes data Y to a Windows WAVE
% file specified by the file name WAVEFILE, with a sample rate
% of FS Hz and with NBITS number of bits. NBITS must be 8 or 16.
% Ster... |
7d2b2e1572e6f9cf1e54df5752ef26ccab8be09cf08fa6ee7dedd11cfde673c0 | MATLAB | 7,888 | 175 | function lf = fun_graph_get_link_w_1_ep_features(link_cc, vessel_image, vessel_mask_dt)
% fun_graph_get_link_w_1_ep_features computes the features derived from the
% position and orientation of endpoints and their nearest neighbor
% Input:
% ep_sub: N-by-3 numerical array, where N is the number of endpoint and 3... |
2299c5ecce6522386aa8c09e49ba1dbe4771da33aecfe8782868a7f57ac0343d | MATLAB | 7,890 | 285 | function [smap, sinit] = ir_mri_sensemap_admm(ykj, varargin)
%function [smap, sinit] = ir_mri_sensemap_admm(ykj, [options])
%|
%| Regularized estimation of sensitivity maps for parallel MRI
%| using augmented Lagrangian methods with variable splitting.
%| See M.J. Allison et al., IEEE TMI, 32(3), 556-564, Mar. 2013.
%... |
b3d107d50fe245bf816b7442251413eaadaf38d7116725cb6f995741fe7449a9 | MATLAB | 7,907 | 206 | %aim to calculate the latency of the response, find the time and CI, and
%the bootstrap
% close all;
clearvars;
addpath ('/data/local/u0114568/ephysio/test');
cn1={'sp','color', 'con', 'incon', 'att', 'congruency','fac','int'}; % condition names length=8
cn={ [cn1{5}],[cn1{7}]};
condnames='Att-Faci-Int'; % note the ... |
cc9dff280bdddff943408d8f08b16608cc7b94d870f77daac35e35cddf0b9996 | MATLAB | 7,907 | 205 | %% Prep environment & load the data w/ pruned segments
% Data.Graph.edges is a [N, 2] matrix, where each row contains the
% indices that the edge connects.
% Data.Graph.nodes is a [N, 3] matrix, where each row contains the [x,y,z]
% coordinates of the node.
% Data.Graph.nB is a 1D array containing the number of bifruca... |
2371b3f85b101ea70cd3901f1bd5b12a442c1f396dfa190dad25f563384355a5 | MATLAB | 7,908 | 220 | function Ret_stitch(target, P2path, datapath,disp,mosaic,pxlsize,islice,pattern,sys,stitch, aip_threshold)
%% stitch the retardance using the coordinates from AIP stitch
% add subfunctions for the script
addpath('/projectnb/npbssmic/s/Matlab_code');
id=islice;
filepath=strcat(datapath,'retardance/vol',num2str(islice),'... |
1e6ddcae1b17b004710902d7b8b30778d4da919cd2ab599509ace907c663eee4 | MATLAB | 7,913 | 196 | %% Manually scoring the participants trajectory
% In order to the model to fit the data the participant had to demonstrate
% a clear intention of completing the triangle.
% This did not happen all of the time and therefore we had to exclude some
% data. Also we noticed by looking at the tracking data that participants
... |
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