sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
9cfe0f9aca1862fe8d9123b56246debef933a455c467ac9daa8690ade2d992f2 | MATLAB | 3,740 | 109 | function [dy_values, Ny] = set_up_dy(G)
% Set up adaptive mesh
increase_factor = G.increase_factor_y;
G.Na_channel_start_y = (G.Na_channel_end_y+G.Na_channel_start_y)/2 - 1;
G.Na_channel_end_y = G.Na_channel_start_y + 2;
G.K_channel_start_y = (G.K_channel_end_y+G.K_channel_start_y)/2 - 1;
G.K_channel_end_y = G.K_chan... |
363bcd88b8383e62b1d32a904c0a5d835ef084641e5ace173ff7fc94f8ee7fe6 | MATLAB | 3,754 | 124 |
% returns scoreMean, scoreSTD
maxTime = 10;
scoreMean = 0;
scoreSTD = 0;
if size(validationEmission, 2) ~= size(finalDynamicsStream,2)
disp(['Test data must have ' num2str(originalDataSize(1)) ' CHANNELS']);
return;
end
if size(validationEmission, 1) ~= size(validationModel,2)
disp(['Emission matrix mu... |
b4f13dbef3fb6702309f48a64d0af607e69f3732678c9c989983d64439279ad5 | MATLAB | 3,754 | 130 | function Spikes = pp_sort_session( subject, session, block, datadir, Threshold )
%
% pp_sort_session( subject, session)
% Loads Phys struct to run data through UMS spike sorting algorithm, and
% creates the main output Spikes.clustered, which contains all relevant
% sorting info and results from UMS. Note:... |
d99d7f8706c64bd221706cb5950d1a8037d076b4c3f43f0e4f37be98c3f1c883 | MATLAB | 3,754 | 125 | function gr = lme_mass_RgGradient1(X,Zcols,SIGMA,W,invH,L,phi,re,ni,G,GDa,GDb)
% gr = lme_mass_RgGradient1(X,Zcols,W,invH,L,phi,re,ni,G,GDa,GDb)
%
% Gradient vector of the restricted log-likelihood for a whole region. This
% is less computationally efficient than lme_mass_RgGradient but more
% numerically stable.
%
%... |
0999ae8762a691144d2e0cb9ec294663ba5f52a458860ad723fe5f51d8d4b011 | MATLAB | 3,760 | 132 | clc;clear;close all;
rng(2^28)
Fig10 = figure();
N_mu=50; %There are \mu independent embedded patterns, 500 simulations (number of simulations)
N_psn=30; %number of post-synaptic neurons
em=10; % number of embedded patterns
delt = 0.1; %integration steps
TP=50/delt; %pattern length (ms/delt= steps)
w_m... |
82fcdbd07122d24fe0c03d0615bb43583f7e5f7c213e5e8b30b31e8804ee5cdd | MATLAB | 3,762 | 171 | %%
win = [0.03 0.6];
binsize = 0.005;
unit = getpref('DB_BROWSER_SELECTION','units');
st = DB_GetSpiketimes(unit);
P = DB_GetParams(unit,'unit');
[data,vals] = shapedata_spikes(st,P,{'BuID'},'win',win,'binsize',binsize, ...
'returntrials',true);
%%
pn = 'D:\Dropbox\PROJECTS\Electrophysiology\Dan''s Project... |
5fab24a6f186275c089f08e43943476bc08e324e4d319f31b74e5c481ab5b856 | MATLAB | 3,766 | 73 |
%% This function has been adopted and edited from a matlab file exchange function. The original function is freely avalibale at the following: "https://www.mathworks.com/matlabcentral/fileexchange/58262-shaded-area-error-bar-plot".
% ----------------------------------------------------------------------- %
% Fu... |
1fa082e694a6c157dfd808af9959a68ec8b35670d623bc4ef62ec2298991a4df | MATLAB | 3,768 | 126 | function dose_response_linearFit(inData,cluster, cluster2Plot,xValues,in_plotFit,yTitle, xTitle, xTitleMod)
%UNTITLED5 Summary of this function goes here
% inData: sweeps_Sorted matrix
% cluster2Plot: cluster_hits{clusterCol}, index with cluster hits for
% cluster of interest
% xValues: forceSteps_Sorted
% ... |
706a51a13ba0eddd288f4c938e2f022d1f03b9405e9fe560b76af67231471df9 | MATLAB | 3,770 | 78 | %% GMLM.computeMLE
% optimizes the log-likelihood of the GMLM using quasi-newton optimization
%
% inputs:
% params_init (OPTIONAL) :a param struct of the initial value of the optimization. If not given or empty, a random initialization point will be generated by GMLM.getRandomParamStruct
%
% optional ke... |
136166e2f2f58df69b4f8f70c75d10315434768df6eba7522d95f9106d4d54c6 | MATLAB | 3,772 | 96 | % Training an LSTM
function [ trainPerformance,testPerformance, trainrmse, testrmse ] = LSTM_Net (Input,Target,Inds,trial)
trainrmse= cell(1,size (Inds,1)); % cell array for saving the RMSE values for train set
testrmse= cell(1,size (Inds,1)); % cell array for saving the RMSE values for test set
... |
66df4779d357082bdb360886d21de073cffe20ed0a94c65e42b94103315edb44 | MATLAB | 3,776 | 98 | function [NextTrialID,LastTrialID,Next_trial_type,repeat_flag] = ...
appetitive_trialselect_SanesLab(TRIALS,remind_row,...
trial_type_ind,LastTrialID,repeat_flag,varargin)
%[NextTrialID,LastTrialID,Next_trial_type,repeat_flag] = ...
% appetitive_trialselect_SanesLab(TRIALS,remind_row,trial_type_ind,...
% ... |
9bccfc0d070d8a2e9532d10b89d354453a97701d2f769f97e2c9429765c4e447 | MATLAB | 3,785 | 127 | function [ ] = draw_convergence_sequence(problem, opt_sol, algorithms_list, w_history, cost_history)
% Draw convergence sequence.
%
% Inputs:
% problem function (cost/grad/hess)
% algorithms_list algorithms to be evaluated
% w_history solution history produced by each algori... |
3610460c458df9baa784c43a63ddc4fccb1f1c15da03a2e7eee656ce7902c8e0 | MATLAB | 3,786 | 98 | function model = qtip_pipe_SDPdc_SDPdcm(data,btensors,mask,nvox,mcheckflag,ind,parallel,cvxsolver)
% function qtip_pipe_SDPdc_SDPdcm()
%
%
% utility to not have to reshape the data between fits
% reshape data and retain voxels within the mask
siz = size(data);
data = reshape(data, prod(siz(1:3)), siz(4))';
... |
732d70fc96b36b348706bcc53c4d37ef9c143dd4954172f2da48989845514c73 | MATLAB | 3,786 | 106 |
function [PeaksData, PercAct, Good_TC ]= Func_EventDetection(T_Cells_DF_nosub,t , mskNrn, im_stack, T_date, T_num)
amp = 1; % min Amplitude of Peak in %
prom = 2 ;% min Prominance of Peak in %
minWid = .05; % min Width of peaks in sec
maxWid = 200; % min Width of... |
94278ae116a5b6cd56874f3cd211fcf814cb8296eb7e81ca4871f7e8c4d6f83d | MATLAB | 3,786 | 168 | %% Compute correlation coefficeients for all compenents between groups from GIFT output
GroupAnii = 'H:\DataProcessing\GIFT_Output_161208\g161208_mean_component_ica_s_all_.nii';
GroupBnii = 'H:\DataProcessing\GIFT_ED_161213\ED_mean_component_ica_s_all_.nii';
% GroupAnii = 'H:\DataProcessing\GIFT_Output_161208\g161208_... |
3f20681d41fd238aead33dc45d42f78a621a96cacf3b64552e55ef338c3fd668 | MATLAB | 3,792 | 101 | % PURPOSE: updates marks for artifactual channels (EEG.reject)
%
% Format
%
% EEG = update_rejEfields(EEG)
%
%
% *** This function is part of ERPLAB Toolbox ***
% Author: Javier Lopez-Calderon & Steven Luck
% Center for Mind and Brain
% University of California, Davis,
% Davis, CA
% 2009
%b8d3721ed219e65100184c6b95db2... |
220aead0ee559c07c4954ed2852b978e065384c272ea8f11501a4b98d091575d | MATLAB | 3,798 | 115 | % CALCULATEFINGERSHARING - calculate the finger sharing at peak force for each trial
function [meancontribution,contributions] = calculateFingerSharing(subject,toplot,insubplot,dirnames,filtered,forcerate,ages,blacklist)
if nargin<4
global dirnames MVCs filtered time m blacklist;
ages = ages;
end
if nargin<... |
17282f1435ad0099e13dd6ab8293d248db92ed2603880629158f42a88a7f73d1 | MATLAB | 3,800 | 112 | function [ ] = display_regression_result(problem, w_opt, algorithms_list, w_list, y_pred_list, mse_list, x_train, y_train, x_test, y_test)
% Display results of regression problem.
%
% Inputs:
% problem function (cost/grad/hess)
% w_opt solution
% algorithms_list algorithms... |
7cc4b675b192c71175f42066152c317cb57b2e2d82ab5e4fc0b60a3057e4d8d9 | MATLAB | 3,802 | 132 | function [stats,st] = lme_FSfit(X,Zcols,y,ni,e)
% [stats,st] = lme_FSfit(X,Zcols,y,ni,e)
%
% Linear mixed-effects estimation by the Fisher scoring algorithm.
%
% Input
% X: Ordered (according to time for each subject) design matrix (nmxp, nm
% total # of maps, p # of fixed effects).
% Zcols: Vector with the indices o... |
dc17ce60828c7ebfd38856e499afb2584d42e40ab5057cbeb12a8db18dbeb707 | MATLAB | 3,803 | 130 | function [Hits,FAs] = EuclideanDistanceClassifier(Data1,Data2,prop_trials,Dconvolve,tau)
Nogo = Data1;
Go = Data2;
num_iterations = 250; % number of decoder iterations for each stimulus
Hits = nan(num_iterations,1);
FAs = nan(num_iterations,1);
for i = 1:num_iterations
%---Go trials---%
nGos = size(Go,1... |
2e1c359b301ff93c6124ad1b1396a81d5b22d73d78d144e07c24fa3e9eb411f1 | MATLAB | 3,808 | 172 | % PURPOSE: pop_suffixerp.m
% add suffix to ALLERP names
%
% FORMAT:
% [ALLERP, erpcom] = pop_suffixerp( ALLERP, 'suffixstr',suffixstr,...
% 'Saveas', 'off', 'History', 'gui');
% Inputs:
%
%ALLERP -ALLERP structure
%suffixstr -strings for erpsets
% *** This function is part of AL... |
480d5580c476d0ae0a296cab2562e84b1446cf34bdce6b55768fb1760dd49197 | MATLAB | 3,809 | 74 | % CSD - Current Source Density (CSD) transformation based on spherical spline
% surface Laplacian as suggested by Perrin et al. (1989, 1990)
%
% (published in appendix of Kayser J, Tenke CE, Clin Neurophysiol 2006;117(2):348-368)
%
% Usage: [X, Y] = CSD(Data, G, H, lambda, head);
%
% Implementation of algo... |
62f851da064b1390672fdf1c907c98a89408fc332b4186932e93afcae4b9ab9c | MATLAB | 3,809 | 114 | function KM_wrapper(fpath,k,delta_f_0,xi,a_max,n_a,f0_min,f0_max,n_f0,...
zeta,PRCfName,N,n_tr,n_pulses,dt,f_stim,freqSet,n_same,rndCycling)
%%% Wrapper for computing the rotation number, mean instantaneous frequency, and PLV
%%% in the Kuramoto model with and without dithering/frequency toggling.
%%% Designed to ... |
88f813980524835ebf6891ef3e5908b7b131d469aa2d12b07e921a28dcbe0504 | MATLAB | 3,809 | 88 | function [endo_correct] = correct_endo_geom(endo, electrode)
% CORRECT_ENDO_GEOM Subtract the geometry of the electrode to the
% endoneuriums volume.
% The function subtract the geometry of the electrode from the fascicles
% geometry. This is necessary in order to avoid the neural fiber to run
% over the electr... |
fa5393acea0d6c5d35a7cf1c1b8782af6bd4129bba70e2a4ee37200b0debb1dc | MATLAB | 3,819 | 153 | clc
close all
clear all
c = 299792457; % Speed of Light
dx = 1.1e-3;
dT = dx / (c*sqrt(2)); %time interval
Nt=1000;
centre_frequency = 1e9 ;
t=-5:0.1:5;
pulse2=sinc(t);%creating copy of the radiating signal
Ts=1/200; %sampling period
first=41; last=61; mid=(first+last)/2;
ypat=pulse2(first:last); % tr... |
fa000ad4dcff610a175b1618d5ca3633c5f5b9a45d13c434585fc79ef0a024b1 | MATLAB | 3,820 | 98 | function [trl,event] = trialfun_tdt(cfg)
% [trl,event] = trialfun_tdt(cfg)
%
% Returns trl and event structures for use with FieldTrip
%
% cfg.tank ... registered tank name (or full path to tank)
% .block ... scalar integer of a single tank block to process
% .blockroot ... root ... |
609b138c1e5849655df7431fb26159da3426c0191766fcc415ab3dc0c9280948 | MATLAB | 3,821 | 110 | classdef Model
properties
epi,
endo,
electrode,
activeSites,
iAS,
fascIds,
fibers,
Q,
fiberActive,
nrnModel = '',
motorFasc = 0,
refFasc = 0,
fiberType = logical.empty, % logical iFiber x iFiberType
fibe... |
cb4ba6fa75016f759adc26e53cb6d1f9dd3ee5148c5894461684e6758231da8c | MATLAB | 3,827 | 154 | function FracCorr=DecodePredErrCrossTemporal_CV_GPU_old(FR,evt0,reg)
%
% (c) 2020 Aleksander PF Domanski PhD UoB
% aleks.domanski@bristol.ac.uk
% Input Variables:
% FR: Firing rate matrix [units,time x no. trials]
% evt0: Event category labels (either 1 or 2) [no. trials]
% reg: Regularization parameter
%
%... |
61a52d87f34c85093a507e9f1b9e0cced04bc96d59862efd14f7985c9c65f78c | MATLAB | 3,837 | 116 | function [drref,drls] = tpdriftcheckls(thedirname, channel, searchx, searchy, refdirname, refsearchx, refsearchy, howoften, avgframes, writeit, brightnesscorrect, domedfilter, doplotit)
% TPDRIFTCHECKLS - Checks two-photon linescan data for drift
%
% [DRREF,DRLS] = TPDRIFTCHECKLS(DIRNAME,CHANNEL,SEARCHX, SEARCHY,
... |
07894f32adc46511fea9701209f6debd3561a87d555db119e23f7f99bb854ec7 | MATLAB | 3,839 | 93 | function [fibers] = place_fiber_cross_inv_square(endos, idFascicle, diam, diamCounts, fibp, startCross, minFiberDist, log)
% PLACE_FIBERS Places fibers of each population in minimal cross-sectional
% area of the fascicle fascicles.
%
% [fiberPos] = place_fiber_cross(populations, fascID, nbPop, diam, ...
% d... |
b471f277332c1d8202cdcbd10db6bbf57f596653af682598f7218ac8f3745cee | MATLAB | 3,839 | 129 | function [] = test_image_inpainting()
% This code partially comes from https://github.com/dlaptev/RobustPCA.
clc;
clear;
close all;
%% Set algorithms
if 0
algorithms = gd_solver_list('ALL');
else
algorithms = {'ADMM-robustPCA'};
end
%% prepare... |
e606c83399b9c5919b7d8f36745d300a2df7ae6778cc39ac4696b35cb816a6dd | MATLAB | 3,844 | 125 | function varargout = acqmat2mat(acqmatfile, acqmatpath, chans, plotOK, saveOK)
% ACQMAT2MAT Convert Acknowledge Matlab (.mat) to EDA Toolbox Matlab (.mat)
% file format.
% ACQMAT2MAT(acqmatfile, acqmatpath)
%
% Optional input arguments:
% acqmatfile - ACQ file name
% acqmatpath - ACQ path name
% cha... |
da2992c6393413be4b464e829c23f580c475053aad114704149ff598242b7e06 | MATLAB | 3,845 | 85 | function [trainedModel, validationRMSE, validationPredictions] = trainRegressionModel(trainingData)
% [trainedModel, validationRMSE] = trainRegressionModel(trainingData)
% Returns a trained regression model and its RMSE. This code recreates the
% model trained in Regression Learner app. Use the generated code to
% auto... |
2f451df366055006ba166dadfad2b942b887f798a689a02c52b7ce4cf89a7b38 | MATLAB | 3,851 | 148 | function LMER_MODES_PID_RAW
% Function to prepare the regression table for Linear Mixed-Effects Regression Model
% in R
%
% Fran Hancock
% Dec 2021
% fran.hancock@kcl.ac.uk
%
%
% Function to investigate the relationships between time varying measures
% of CHI OCC HC and PID and the random effect of RUN
%
%
% Run 1: 1 ... |
996cef8c0050326b1a64f5fdd4ec268a9ca653d9480e444a4dacf268e3994dbb | MATLAB | 3,851 | 148 | function LMER_MODES_PID_RAW
% Function to prepare the regression table for Linear Mixed-Effects Regression Model
% in R
%
% Fran Hancock
% Dec 2021
% fran.hancock@kcl.ac.uk
%
%
% Function to investigate the relationships between time varying measures
% of CHI OCC HC and PID and the random effect of RUN
%
%
% Run 1: 1 ... |
f7c15663693e6ddc8d65811e74cf7323066469a8d7b05921d4136e56f5f7dd4f | MATLAB | 3,851 | 133 | clc; clear; close all
rng(2^22)
Fig2c=figure();
i_t=randi(500); %i'th trial (choose the i'th trial randomly.)
N_psn=1; %number of post-synaptic neuron
desired_S = 2; % desired number of spikes r0 = 2 Hz
w_max = 1; % maximum amount of synapsis.
resy = 0.0; %resting potential
threshy = 1; % thres... |
1abbc20fc5d5ce2c21f6a803cc72351889bf808fb6bbfcb26ed183a000cb5b33 | MATLAB | 3,853 | 132 | function [Hits,FAs] = CorrelationCoefficientClassifier(Data1,Data2,prop_trials)
Nogo = Data1;
Go = Data2;
num_iterations = 250; % number of decoder iterations for each stimulus
Hits = nan(num_iterations,1);
FAs = nan(num_iterations,1);
for i = 1:num_iterations
%---Go trials---%
nGos = size(Go,1);
% xma... |
70a5dde42aa1a9520110e8fc03fc23f798104c10f68211e175a9e389b033fa83 | MATLAB | 3,856 | 126 | function Phase_sync_metrics
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% LEADING EIGENVECTOR DYNAMICS ANALYSIS
%
%
% Function to compute the Kuramoto order parameter, Synchronisation, and
% Metastability when state is dominant derived from LAU LEiDA
% anaysis for all subjects
%
%
% Fran Hancock
% Nov 2021
% fran.... |
aa4a9750f648ddb9de44f69e5aa436f432f8a32fed0db75157edaf1351d2e2e1 | MATLAB | 3,857 | 116 | classdef DeepActionProject
properties
ProjectPath % Path to project folder
ProjectName % Name of project
VerboseLevel = 2 % Level of output to display (0-2)
ConfigFile % ConfigFile object for project's config.txt file
ClipTable % Table containing project clip data
La... |
f0460dd070910624e93d5be5e989ca98ce5510abd233801886ed28308fc76a86 | MATLAB | 3,857 | 154 | % fresh start
clearvars
close all
%% run config
config_file='config_mammals_1.m';
addpath(strcat(pwd,'/config'))
run(config_file);
%% read in proc spreadsheet
filename = [ DD_PROC '/MamiNum_corrected_proc.txt' ] ;
ssheet = readtable(filename,'Delimiter','\t') ;
%% read in outlier info
filename = [ DD_INTERM '/' O... |
c543014f31e539569dca7e18502c1defc8f0acda2587474808c9e16669a3687b | MATLAB | 3,859 | 137 | function [RP,RUNTIME] = SetupRPexpt(C)
% [RP,RUNTIME] = SetupRPexpt(C)
%
% Used by ep_RunExpt when not using OpenEx
%
% Where C is an Nx1 structure array with atleast the subfields:
% C.OPTIONS
% C.MODULES
% C.COMPILED
%
%
% RUNTIME.RPread_lut is a lookup table indicating which RP array index
% correspo... |
8fb066a838cc6ba978fb7c97a8eafbb6ad3c3117be91bb18d3e29687a95c9c1b | MATLAB | 3,863 | 133 | function [messgStr,erpanelIndex]= f_check_erptab_panelchanges()
messgStr = '';
erpanelIndex = 0;
MyViewer_chanbin = estudioworkingmemory('ERPTab_chanbin');
if ~isempty(MyViewer_chanbin) && MyViewer_chanbin==1
messgStr = char( 'Changes on "Bin and Channel Selection" have not been applied');
erpanelIndex =1;
... |
df71c93d60c02b90136916dbfa60039b83bfa5467beb960ca7853dd32997b820 | MATLAB | 3,867 | 114 | function [B,E,K] = evaluate_generative_model2(A,Atgt,D,modeltype,modelvar,params,whicheval)
% EVALUATE_GENERATIVE_MODEL Generation and evaluation of synthetic networks
%
% [B,E,K] = EVALUATE_GENERATIVE_MODEL(A,Atgt,D,m,modeltype,modelvar,params)
%
% Generates synthetic networks and evaluates their energy funct... |
a3de3f6b345ae8dfe7226e9a0f2b7094f46ceae35bff90fcf1e726d3fa5e4054 | MATLAB | 3,874 | 111 | %% A script to automate running all OH, OHA, TOH, and TOHA trials
% The "tree" of function calls is for this script to call
% processMultipleOHFiles.m for each block of trials in a task; this calls
% processSingleOHFile.m for each trial in the block; and this calls the
% necessary series of function to convert a co... |
fe5ff56e535bb609e4a639888c58f31e5867717e4fa5636ae8c1d8a6b0eadcb8 | MATLAB | 3,882 | 136 | function [U, S, V] = plotcsvd(vf, nmodeplot, realTime, useComplexSVD, vectorScale)
% PLOTCSVD performs a singular vector decomposition of a vector field.
% Plots most dominant spatial modes and their time courses, and the
% trajectory of the top 3 most dominant modes.
%
% INPUTS:
% VF, a complex velocity field., Mu... |
77522f6799ed57232fdce2bc60dc34aa12897133b34b9c7510f97f05a7eeae8f | MATLAB | 3,884 | 100 | % Plot the specific role of Assembly-member units in decoding behavioural out come
%
% (c) 2014, Daniel Durstewitz, Dept. Theoretical Neuroscience, CIMH
% Mannheim/ Heidelberg University
clear all
close all
pat='data/';
% A=dir([pat '*TAUpairs10.mat']);
A=dir('*.mat')
avgIFin=zeros(length(A),4); avgIFout=avgIFin; a... |
5b07a9eb300515dd85a2a020a4928e614c9eb80139cc12d93964e5a898e91363 | MATLAB | 3,888 | 107 | function Assemblies = MakebestSUAssemsCrossShuffle(RankIn_,ScoreIn_, Ltrials_,Rtrials_,MaxSize,CorrsToDestroy,noTrials,nReps)
%@TODO: add shuffling of trial labels between cells to non- trial-resampled version
Areas = {'PFC','HP','Joint'};
InfoCriteria = 'max';
nReps = 50;
verbose = false;
Ltr = size(Ltrials_{1}{1},1);... |
536779e12c7127ceffbb8eae088bc4be4e651ca536d5887909adc34ff315408f | MATLAB | 3,889 | 116 | function celllist = import_centriods(parameters, inputs)
% IMPORT_CENTROIDS - Import a cell list from drawing of centroids.
%
% CELLLIST = IMPORT_CENTROIDS(PARAMETERS, INPUTS)
%
% PARAMETERS should be a structure with the following entries:
% diameter Diameter to include around the centr... |
6e254ef7cc9bede293f43a0c81a309622e22aae1a193a8cafb9573b0fc0a3a84 | MATLAB | 3,890 | 132 | function b = stack2ndi(tpstack_file, S, options)
% STACK2NDI - export data from a vhlab-TwoPhoton-matlab to an NDI session
%
% B = STACK2NDI(TPSTACK_FILE, S, subjectname)
%
% Given a stack file TPSTACK_FILE and an ndi.session S, and the subjectname,
% export the subject and neurons.
%
% Needs to have subject.txt file i... |
3d06fb0685b52fe49de67c1e4825bde07e3158f0902397eb6ebab3a1b8a81429 | MATLAB | 3,892 | 128 | function [U0, S0, V0, U, S, V, reUav] = plotcsvd(vf, nmodeplot, realTime, useComplexSVD, vectorScale, intermx)
% PLOTCSVD performs a singular vector decomposition of a vector field.
% Plots most dominant spatial modes and their time courses, and the
% trajectory of the top 3 most dominant modes.
%
% INPUTS:
% VF, a... |
25685b63241ada7dc11f68638107067d1309b8b96fb3c771437960befce80de3 | MATLAB | 3,893 | 110 | function celllist = import_imagejrois(parameters, inputs)
% IMPORT_CENTROIDS - Import a cell list from drawing of centroids.
%
% CELLLIST = IMPORT_CENTROIDS(PARAMETERS, INPUTS)
%
% PARAMETERS should be a structure with the following entries:
% default_filename The file of the ROIs (relative to t... |
bd5141781226c66102db2aec65058512e91d082173a0723858a3fab56f8f98ae | MATLAB | 3,894 | 146 | function Q = S_region(prediction,GT)
% S_region computes the region similarity between the foreground map and
% ground truth(as proposed in "Structure-measure:A new way to evaluate
% foreground maps" [Deng-Ping Fan et. al - ICCV 2017])
% Usage:
% Q = S_region(prediction,GT)
% Input:
% prediction - Binary/Non binary... |
8b9fe7a5091a337ab5c9541df49a91a858e700c4b0bf8d8a7cc4c301b522899c | MATLAB | 3,898 | 113 | function params=tpreadconfig( tpdirname )
%TPREADCONFIG read twophoton experiment config file - TiffStack
%
% PARAMS = TPREADCONFIG(TPDIRNAME)
%
% Reads parameters for a generic TiffStack directory.
%
% There must be a text file with the extension .tiffstack
% This file should contain the following lines:
% parameter... |
7513fc5af9118bcf91f9a7f6e79b1177955d0eb9fc6ea8d62a364d62a26b8abc | MATLAB | 3,901 | 112 | function params=tpreadconfig( tpdirname )
%TPREADCONFIG read twophoton experiment config file
%
%
% PARAMS. =
% params.Main.Total_cycles (total number of cycles)
% params.Main.Scanline_period__us_ (scanline period, in us)
% params.Main.Dwell_time__us_ (pixel dwell time, in us)
% params.Main.Frame_period__us_ (... |
81b90c782b9bf328cc0d725969d60b9631bea3604c537a665dd050770333dabc | MATLAB | 3,902 | 157 |
%function FM_sweep_testing()
close all;
handles.RPfile = 'C:\gits\epsych\UserFiles\SanesLab\RPVdsCircuits\KP\circuit_wav_stim_wav.rcx';
% handles.RPfile = 'C:\gits\epsych\UserFiles\SanesLab\RPVdsCircuits\KP\FM_sweep_test_manualcircuit.rcx';
%Load in speaker calibration file
% [fn,pn,fidx] = uigetfile('C:\gits\epsy... |
c64303fea008e32fec3d23fdbd2224f48b00dabbf64aa19f29e14e5e72841a31 | MATLAB | 3,904 | 143 | clc; clear; close all
rng(1101)
Fig2a=figure();
i_t=randi(500); %i'th trial (choose the i'th trial randomly.)
N_psn=1; %number of post-synaptic neuron
desired_S = 2; % desired number of spikes r0 = 2 Hz
w_max = 1; % maximum amount of synapsis.
resy = 0.0; %resting potential
threshy = 1; % thres... |
d6e9896e757f45307c568de3680aefa632373eaf8e93c3dea5dcd11246a8b0b6 | MATLAB | 3,904 | 112 | function params=tpreadconfig( tpdirname )
%TPREADCONFIG read twophoton experiment config file
%
%
% PARAMS. =
% params.Main.Total_cycles (total number of cycles)
% params.Main.Scanline_period__us_ (scanline period, in us)
% params.Main.Dwell_time__us_ (pixel dwell time, in us)
% params.Main.Frame_period__us_ (... |
66fe90fdbfdb497becae463d1615cf74d69b0a3334aa442638175a7d5d1dec01 | MATLAB | 3,906 | 121 | % PURPOSE: f_display_binstr_chanstr.m
% display the names of channels and bins for the selected ERPsets
% Inputs:
%
%ALLERP -ALLERPset
%ERPArray -index of the selected ERPset/bin/channel(e.g., [1 4])
%diff_mark -has two elements, 0/1; 0 represents channels/bins are
% ... |
ccdc8d6256e4ae25412e440d40550954853c43fff6ab33d247633487799f1530 | MATLAB | 3,912 | 135 | function TDT2PLX(tank,blocks,varargin)
% TDT2PLX(TANK,BLOCKS)
% TDT2PLX(...,parameter,'value',..)
%
% TANK is a string (char) to the absolute path to the tank or the name of
% a registered tank.
%
% BLOCKS is a cell array of block names. All blocks from the specified
% tank will be selected if left emp... |
4674936cf0029a1881b94220a05c4ce6515c7e2c95fc9f9a75dd9b15ea02f835 | MATLAB | 3,914 | 99 |
%==================== SingleCellSizeDistanceHeatmap.m ====================
% Plot a heatmap of the responses across all size and distance combinations
% for each individual cell. For those presented select Cell 43 (Figure 2)
% as well as Cell 15 and Cell 46 (Figure 3)
%================================================... |
54ff8ccd32c442669ee34f9b5dd5296210917ff37edcd2d6d2c653fa45155dbf | MATLAB | 3,916 | 86 | function [tempData, trialData, procesedTrialSwitches, dataMean, dataSTD] = preprocessData(rawData, rawInput, inputLambda, rawOutput, outputLambda, rawTrialData, trialLambda, isTrainingData, smoothingAmount, shouldZScore, delayTime, delayCount, dataMean, dataSTD)
tempData = rawData';
dataIndices ... |
94101241a301b6659fc72aeeacb695611870f07afa2d9f3f9d4a1fe330fa0f81 | MATLAB | 3,924 | 136 | function Plot_repertoire_5_modes_reduced
%%%%%%%%
%
% Function to plot the LEiDA as horizonetal bar plots
%
% Joana Cabral Jan 2020
%
% Fran Hancock Feb 2021
% Adapted to HCPUN100
%
%%%%%%%%%%%
% Set up the correct folders
%
PROJECT='/Users/HDF/Dropbox/Fran/Academics/PhD/matlab/projects/COBRA_COMPLEXITY_PHASE_FD/';... |
d2e403bcb32842ea5e10507ba007894338d3b58c23b0c2cd88069fa3e1e970a3 | MATLAB | 3,927 | 127 | function h=plotMarginal(result,dim,plotOptions)
% plots the marginal for a single dimension
%function plotMarginal(result,dim,plotOptions)
% result should be a result struct from the main psignifit routine
% dim is the parameter to plot
% 1=threshold,2=width,3=lambda,4=gamma,5=eta
% ... |
718208b1a60f7a47a9f5a8712b900f5ee767cc5bf0c896a86b2ca8308a8948ee | MATLAB | 3,932 | 94 | function Assemblies = MakebestEnsembleAssemsPosthoc(UnitsReal,Ltrials_,Rtrials_,MaxSize,JointOnly,DestroyNoiseCorrs,noTrials,nReps,unitSelection)
%%
% ** Takes IDs of groupings previously identified as optimal **
%
% Compared decoding performance from aggregated cell assemblies.
% Search is two... |
edde0cb190dca3cad626a40dac962549274bc07f4fcc0e33ae90274dc19da203 | MATLAB | 3,942 | 87 | % Make raster of units higlighting those tagged as assembly members
%
% Aleksander PF Domanski PhD UoB 2016
% aleks.domanski@bristol.ac.uk
threshold = 5;
% adjust the peak assembly activation times... according to 'threshold' parameter
for region=1:3 % {PFC HP joint}
if ~isempty(FactorScores{region})
... |
6a4f825100dc71ad710bac5b1ae8c7b5732f50c79c1d0aa5e7ca0791f7af64a5 | MATLAB | 3,945 | 93 | function activeSites = extract_active_sites(FEM)
%% Extract data
disp('Extracting active sites...');
physTag = find_physics_tag(FEM, 'ec');
assert(~isempty(physTag), 'No Electric Current physics detected.');
assert(strcmp(FEM.geom(geom_tag(FEM)).lengthUnit(), 'mm')); % TODO check this always at load
physChildren... |
7b9d31555e3b16889684b4abfdc25f844d0925b25e6cff17e82c1c0b57380343 | MATLAB | 3,945 | 122 | %% CNN MODEL (Confounding Factor)
clear
clc
githubpath = '/home/bonilha/Documents/GitHub/Bonilha';
% githubpath = 'C:\Users\allen\Documents\GitHub\Bonilha';
cd(githubpath)
allengit_genpath(githubpath,'imaging')
save_path='/media/bonilha/AllenProj/PatientData/smallSet';
%% Setup for CNN model
% Load Res... |
b429a34fba1963aa3385a07b973a0224cc84dc714d8962c7fe6bc778165b1932 | MATLAB | 3,948 | 80 | %% A script set up to run experiments using the SimpleSerialSystem set-up.
%
% Specify the task environments based on the difficulty modifiers for the
% different modules.
% Specify the module processing capacities for the various systems.
% Run simulations for all acceptable capacity settings and record the
% res... |
bf23ff1bef7319406790108c446da0b35553f89f8539783441212fd1a548ad17 | MATLAB | 3,949 | 111 | function s1 = crsOpenSerialPort(deviceName, mode, portNumber)
% handle = crsOpenSerialPort(deviceName, mode, portNumber)
%
% Opens the USB CDC virtual serial port to deviceName and returns the
% object handle.
%
% Supported deviceName types are: Bits#, BlueGain, BOLDscreen, ColorCAL,
% Display++, LM1, LiveTrack, Spectr... |
c0a46142c6df91b5b071ae627a8c1144bc8bdc3d993c45898d7d127ebb346e78 | MATLAB | 3,950 | 161 |
%function FM_sweep_testing()
% close all;
% Define RCX file
handles.RPfile = 'C:\gits\epsych\UserFiles\SanesLab\RPVdsCircuits\Sandbox\KP\AM_specShift_test.rcx';
%Load in speaker calibration file
pn = 'C:\gits\epsych\UserFiles\SanesLab\SpeakerCalibrations\';
fn = 'rig1012-CeilingB_Noise_Mar072016.cal';
fidx=1;
% [f... |
f6a43ec6d0110118a475f0a7b1bfbe38038b6290cd6a0ff513a4049ff33e54a8 | MATLAB | 3,950 | 117 | function segments = generic_cross_section(tri, planeP, planeV, roundPrec)
arguments
tri triangulation
planeP (1, 3) % Point in plane, if given scalar it is auto-broadcasted to vector
planeV (1, 3) = [0, 0, 1] % Vector perpendicular to plane
roundPrec (1, 1) = Inf;
end
planeV = planeV./norm(plane... |
11b8b1fb6820f97de43558df6579b0d287d2e37279f39d24338badfcc7437843 | MATLAB | 3,951 | 112 | function pos = get_pos_on_grid( grid_pos, params, h, impose_margins )
% UltraMegaSort2000 by Hill DN, Mehta SB, & Kleinfeld D - 07/12/2010
%
% get_pos_on_grid - get 'Position' values for a new object in a sliderFigure
%
% Usage:
% pos = get_pos_on_grid( grid_pos, params, h, impose_margins )
%
% Description:
% ... |
c785db659e0f22595337f538cce1fbd7cc73450332553f6cca99bfc8df888514 | MATLAB | 3,961 | 116 | datasets = strvcat('Synthie');
for ith_data = 1: size(datasets, 1)
dataset = strcat(datasets(ith_data, :));
path2data = [dataset '/']; % path to folder containing data
% graph labels
graph_labels = dlmread([path2data dataset '_graph_labels.txt']);
num_graphs = size(graph_labels, 1);
... |
f95270127e0606714424bfa1603ca036bc21928477cce47d8a18c26898005756 | MATLAB | 3,968 | 155 | % fresh start
clearvars
close all
%% run config
config_file='config_mammals_1.m';
addpath(strcat(pwd,'/config'))
run(config_file);
%% setup
ff = [ PROJ_DIR '/reports/figures/animal_colors.mat' ] ;
load(ff,'anicmap')
%% setup vars
thr_vals = [ 0 0.05 0.1 0.15 ] ;
odir = [ PROJ_DIR '/reports/figures/fragility/' ] ... |
2b002d9f211a4c4984f8ece611cb6ecddbfcbc1b5d04f00412178053f72d6fb4 | MATLAB | 3,972 | 131 | function Phase_sync_metrics
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% LEADING EIGENVECTOR DYNAMICS ANALYSIS
%
%
% Function to compute the Kuramoto order parameter, Synchronisation, and
% Metastability when state is dominant derived from LAU LEiDA
% anaysis for all subjects
%
%
% Fran Hancock
% Nov 2021
% fran.... |
9af0ee5c1de9e8eeab53b5f6b84714390a6aa4566bb4a6b9cd2e14c3ee3dafca | MATLAB | 3,972 | 131 | function Phase_sync_metrics
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% LEADING EIGENVECTOR DYNAMICS ANALYSIS
%
%
% Function to compute the Kuramoto order parameter, Synchronisation, and
% Metastability when state is dominant derived from LAU LEiDA
% anaysis for all subjects
%
%
% Fran Hancock
% Nov 2021
% fran.... |
e1b6d99623085051b87ddbfbc5a2909742fc0fd0f8d91a45c42fb1df281f8482 | MATLAB | 3,980 | 94 | clear all
close all
target= 'PostSleep';
if ispc
home = 'C:\'; % [getenv('HOMEDRIVE') getenv('HOMEPATH')];
pat = [home 'Analysis\AssemblyAnalysis\Sleep'];
separator='\';
elseif ismac
path(path,'/Users/aleksanderdomanski/Documents/Bristol_work/assembly_analysis')
home = getenv('HOME');
... |
311c71f3c213c75ceaa74819593c613892ed9bfac44e5f3b21dea7b123c16123 | MATLAB | 3,991 | 140 | function [] = test_background_subtraction()
% This code partially comes from https://github.com/dlaptev/RobustPCA.
clc;
clear;
close all;
%% set algorithms
if 0
algorithms = gd_solver_list('ALL');
else
%algorithms = {'Inexact-robustPCA', 'ADMM-robustPCA'};
... |
3b1d074268252c4d535898ea0d702f26a645df74b971bd443994b0c9cdaa337e | MATLAB | 3,992 | 80 | %% A script for combining the desired values from multiple .mat files.
%
% 3 December, 2021
function matFileCombiner(varargin)
if nargin == 4
ohListNames = varargin{1};
ohaListNames = varargin{2};
tohListNames = varargin{3};
tohaListNames = varargin{4};
% Allows running the function as a script for th... |
b5de01e940f37346b25549bbe651204fd9f0ef89a66bef51b8152138ff32f1ec | MATLAB | 3,993 | 133 | function map_COBRE_top_3ns_aal116
%
% function to map the TOP ns term to each AAL116 region
%
% Fran Hancock
% July 2022
% fran.hancock@me.com
%
PROJECT='/Users/HDF/Dropbox/Fran/Academics/PhD/matlab/projects/META_ANALYSIS/';
CondMax=3;
run=4;
Smax=5;
Cmax=Smax-1;
Rmax=4;
Thres=2; % 3.1 as for 24 topics from Marglies
Th... |
49490e6a4549859b7dbbcb7c76cee0bb17fcdda4dce47dc1b2a9e084352b6ce9 | MATLAB | 3,994 | 95 | % A tensor component-wise rescaling Metropolis-Hastings step.
% Useful for slighlty faster HMC mixing - plain HMC doesn't force any components to be normalized/orthogonal and this explores the scaling dimension faster.
% Important: This step assumes that the prior distributions are normal with mean 0!
function [params,... |
f2d89d8b40ad11d866cfad96f5ed660e984527d329d83e01acbf5e4c41fb8b7b | MATLAB | 3,994 | 110 | function kristen2vhlab(source, destination, prefix_str__, ref__)
% KRISTEN2VHLAB - Convert from Kristen Ade's style to VHLAB style
%
% KRISTEN2VHLAB(SOURCE, DESTINATION)
%
% SOURCE and DESTINATION should have full paths
%
% Example:
%
% kristen2vhlab('C:\mydataorig\2012-05-20','C:\myvhdata\2012-05-20')
%
% ... |
4a421812372aff9b57432be719abe36f759d259b83c36bfd82046fba71abfc47 | MATLAB | 3,995 | 44 | function out = qtip_mcheck(model)
% function qtip_mcheck()
%
% checks if condition (m) is satisfied using SDP
%
% assumes model is [28,nvox]
nvox = size(model,2);
% get d and c and change units
d = arrayfun(@(i)convert_1x6_to_3x3(model(2:7,i).*1e9), 1:nvox, 'UniformOutput', false);
c = arrayfun(@(i)convert... |
0b21737d61124b3f914377f2f61e2c263cc7fc7c32c8060c8071e838f3b075f3 | MATLAB | 3,997 | 107 | function [C, lags] = pxcorr(x, varargin)
% UltraMegaSort2000 by Hill DN, Mehta SB, & Kleinfeld D - 07/09/2010
%
% pxcorr - Efficient cross-correlation for point process data
%
%
% Description:
% C = PXCORR(A,B,Fs) returns the cross-correlation between A and B at
% sampling rate Fs for the point process whose time... |
320aeb892a9703046e7fa46eb086055b5648549685a165a7c86b6f768cc59da6 | MATLAB | 4,001 | 120 | % Mofified version of the original SAVE2PDF of Gabe Hoffmann (gabe.hoffmann@gmail.com)
%
% Saves a figure as a properly cropped pdf, eps, jpeg, or tiff
%
% save2pdf(FileName,handle,dpi)
%
% - FileName: Destination to write the file to.
% - handle: (optional) Handle of the figure to write to a file. If
%... |
39797d1ac2858671116f1cf35a9834a4e4dd748c440e642b41a427b9a665e629 | MATLAB | 4,003 | 101 | %% demo.m
%
% part of https://github.com/LudgerS/MRSartifactRemoval
%
% Demonstration script calling the artifact subtraction and phase
% estimation functionality of
% fitPeakAndCoupledArtifacts.m
% and
% automaticPhaseCorrection_voigt.m
%
% To run the script, ensure that both exampleData.mat, priors.m... |
c12a406860eea9d775cd4f0d9d76ac42c989f1c7c69131513ee27385dcdce1f0 | MATLAB | 4,007 | 113 | % Intraparietal stimulation disrupts negative distractor effects in human multi-alternative decision-making
% Kohl, C., Wong, M.X.M., Wong, J.J., Rushworth, M.F.S. & Chau, B.K.H.
% eLife 2022
% Script to generate Figure 2d
clear all; close all; clc;
% GLM2
nPartic = 31; % nr of participants
modelStep1 = '[hv(idx) + ... |
493db66768d78fd2040d10c9a6cc66e8c8980c1592f4ece07c7fdc6b056ade35 | MATLAB | 4,016 | 174 | % fresh start
clearvars
close all
%% run config
config_file='config_mammals_1.m';
addpath(strcat(pwd,'/config'))
run(config_file);
VIZIT = 0 %#ok<NOPTS>
%% big loop
for tDx = 1:length(THRDENS)
%%
filename = [ DD_INTERM '/con_mat_gn_repani_stack_thr' num2str(THRDENS(tDx)) '_.mat' ] ;
ll = load(filename) ;
c_aCon... |
34789ee8b03b9045426fbb4f0bdba9ec8ef4bfe7bc96c1ff58b4d59932949384 | MATLAB | 4,018 | 323 | % Steps taken from Muller - Transfer-Function Measurement with Sweeps
% (p.16)
%
% Also see: Chan - Swept Sine Chirps for Measuring Impulse Response (fig 4)
%
% NOT WORKING YET
clear all
% close all
Fs = 96000;
F1 = 20;
F2 = 20000;
T = 0.5;
tREF = 0:1/Fs:T-1/Fs;
% 1. Synthesize Log-Swept Sine =====... |
0f8e115abcc8051365c1f2bd6ba5ab1236ebf1171ac69341bdb876438ac69bc3 | MATLAB | 4,024 | 107 | %this script generates final prediction maps after averaging the scoremaps
%across different scales.
% This code assumes that the prediction scoremaps have already been
% generated for the mentioned destination folder with following naming
% convention: <folder_name>_<scale> e.g. egohands_0.6, egohands_0.8 and
% egoh... |
65fe3860182838859f3a287f8569246fb4d420c33e23358ca289f59cc7f2259b | MATLAB | 4,029 | 142 | function self = CreateClipTable(self, varargin)
p = inputParser;
addOptional(p, 'IncludeFeatures', true);
parse(p,varargin{:});
inclFeats = p.Results.IncludeFeatures;
if self.VerboseLevel > 0
if inclFeats
fprintf(' Dividing project annotations & features into clips\n')
else
fprintf(' Dividi... |
19fed8dd1613d401515ea8fddd0baba8125dce3f2ef33b70ea1d9fd6a045210c | MATLAB | 4,031 | 136 | % PURPOSE : Smooth ERP data (ERPLAB ERP structure)
%
% FORMAT :
%
% ERP = pop_smootherp(ERP, npoints, stype);
% ERP = pop_smootherp(ERP, npoints, stype, issaveas);
%
% INPUTS :
%
% ERP - ERP structures (ERPset)
% npoints - odd number of points. An even value is rounded up.
%... |
53ace1d6e7403509c320db6255e72221be986d3ef4e1ca994ad31c2dc94c1520 | MATLAB | 4,031 | 89 | % Intraparietal stimulation disrupts negative distractor effects in human multi-alternative decision-making
% Kohl, C., Wong, M.X.M., Wong, J.J., Rushworth, M.F.S. & Chau, B.K.H.
% eLife 2022
% Script to generate Figure 3 - figure supplement 2b
clear all; close all; clc;
% Load data
load InterimData\Collaps... |
dda808a0c59cdf1575942f3a8f66bff108549335f9834760bb39df9ba6ea7a8c | MATLAB | 4,036 | 131 | function NextTrialID = TrialFcn_AversiveAnimalTrig(TRIALS)
% NextTrialID = TrialFcn_AversiveAnimalTrig(TRIALS)
%
% This is the default function for selecting the next trial and can be
% overridden by specifying a custom function name in ep_ExperimentDesign.
% The code in this function serves as a good template for cus... |
286318f84eab1d32de93b2724f4efdc53296b947fc9a83f556f8001279261212 | MATLAB | 4,039 | 100 | function Xhat = decode_arrayGeneralization(cfg0, decoder, Y)
% [Xhat] = train_arrayGeneralization(cfg, decoders, Y)
% Decodes the data along a specified dimension, e.g. time, using an array of decoders. Additionally,
% each decoder is also applied to all other points along this dimension. For example, this functi... |
627fa813c5c43181e456bb92e898a3da874d8297f98f2b0a4a67efda93c182af | MATLAB | 4,041 | 152 | % PURPOSE: subroutine for ploterpGUI.m
% identifies minimum and maximum values of ERP amplitudes for Y scaling.
%
% FORMAT
%
% [yylim, serror] = erpAutoYLim(ERP, binArray, chanArray, xxlim)
%
% INPUTS
%
% ERP - ERPset
% binArray - indices of bins from where to get the amplitude values
% chanArray ... |
9f52284edba16c490173df98e863afdac3df0864d8ac076401c4c5db9b21ceef | MATLAB | 4,041 | 102 | %% Preamble, get file list
clear all; close all
set(0,'DefaultFigureWindowStyle','docked')
flags.plotIndividualChanges = false;
% pat{1} - % location of the processed assembly memberships
% pat{2} - % location of raw spike times
if ispc
% pat{1} = 'C:\Analysis\AssemblyAnalysis\Sleep\Decoding vs flanking peri... |
cc14d12b03b440378bc23f59505c31bf2b59367b96ac97e09609a68d6a494b8a | MATLAB | 4,051 | 104 | function [] = saveSampleToFile(obj, samples_file, paramStruct, paramStruct_rescaled, sample_idx, scaled_WB, scaled_VT, save_H, saveUnscaled) %#ok<INUSL>
J = numel(paramStruct(1).Groups);
for jj = 1:J
if(save_H.Groups(jj).H)
for sample_c = 1:numel(paramStruct)
sample_idx_c = sample_idx(sa... |
183ec2eae42478fa277bd92f6d38812746bce35dce2d42c9128d161f92236d8b | MATLAB | 4,054 | 85 | function [populations_primary_motor] = ...
get_motor_fascicle_primary_pop(idFascicles, fibersCompart, numDisp)
% output initialization
populations_primary_motor.IaFiberId = {};
populations_primary_motor.IbFiberId = {};
populations_primary_motor.AlphaFiberId = {};
% Generate Random ... |
6eda88ea23f12942262858c83b38363f4f4532ded8f96dbeb90676b014058c11 | MATLAB | 4,058 | 157 | classdef o_DECODEDAT < handle
properties
ALLBEST
BEST
CURRENTBEST
Count_currentbest
Process_messg
Best_between_panels
Reset_Best_paras_panel
ALLMVPC
MVPC
CURRENTMVPC
Count_currentMVPC
end
events
allbest_chan... |
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