sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
1c362bfea28ad30e81b16126df8467c6a6d3f3d7900852923f2d5d1167dd2b69 | MATLAB | 1,430 | 40 | % PURPOSE: gets current pointer for ALLERP structure and its size
%
%
% *** This function is part of ERPLAB Toolbox ***
% Author: Javier Lopez-Calderon
% Center for Mind and Brain
% University of California, Davis,
% Davis, CA
% 2009
%b8d3721ed219e65100184c6b95db209bb8d3721ed219e65100184c6b95db209b
%
% ERP... |
2b629ce6b21dcc8d0e19351deef70bb74ad578950d1a3adbe79499f0c6120f45 | MATLAB | 1,430 | 55 | function Dab = lap_spect_dist(aij,bij,nComps,minkp)
% https://github.com/aiavenak/matlab_code/blob/master/f_lap_dist.m
% calculate the edit distance between two graphs A and B
% reference: Thomas Thorne and Michael P. H. Stumpf
% evolution Graph spectral analysis of
% protein interaction network
... |
e22640ee28829a677d4f1bd2b02a671ae013d9ebf45f13d9d55543eb73119efd | MATLAB | 1,431 | 39 | function [values, oldmin, oldmax] = rescale(values, newmin, newmax);
% UltraMegaSort2000 by Hill DN, Mehta SB, & Kleinfeld D - 07/09/2010
%
% rescalde - Linearly rescales a data set between a min and max value
%
% Usage:
% [values, oldmin, oldmax] = rescale(values, newmin, newmax)
%
% Description:
% [VALUESOUT, O... |
e22d371c07ba5e7e806c1c93b2400cb009ab21c73a6f79f27e70ca5c3df94001 | MATLAB | 1,431 | 51 | function [k k0] = circ_kurtosis(alpha, w, dim)
% [k k0] = circ_kurtosis(alpha,w,dim)
% Calculates a measure of angular kurtosis.
%
% Input:
% alpha sample of angles
% [w weightings in case of binned angle data]
% [dim statistic computed along this dimension, 1]
%
% If dim ... |
0532bc6f3bedca4a589f1c223cc11ce33de918c69316f20743eed2e09b5fdf44 | MATLAB | 1,432 | 40 | % PURPOSE: gets current pointer for ALLBEST structure and its size
%
%
% *** This function is part of ERPLAB Toolbox ***
% Author: Aaron Simmons
% Center for Mind and Brain
% University of California, Davis,
% Davis, CA
% 2023
%b8d3721ed219e65100184c6b95db209bb8d3721ed219e65100184c6b95db209b
%
% ERPLAB Too... |
823b423f61bc486f758f07a2fbba3a32f543c54f2387e9108a43d94b14a211f7 | MATLAB | 1,432 | 34 | function t2_update
addpath('../code');
% Here we go over how to update the adaptive procedure on a trial-by-trial basis.
% 1. Create the Palamedes structure as shown in 01_setup
params.whichStair = 1;
params.alphaRange = linspace(0,45,1e2);
params.fitBeta = 2;
params.fitLambda = 0.0... |
e53d7042656249c8e6afe210097b0923a8908c9b65969f4e28657d3e019becce | MATLAB | 1,432 | 40 | % PURPOSE: gets current pointer for ALLMVPC structure and its size
%
%
% *** This function is part of ERPLAB Toolbox ***
% Author: Aaron Simmons
% Center for Mind and Brain
% University of California, Davis,
% Davis, CA
% 2023
%b8d3721ed219e65100184c6b95db209bb8d3721ed219e65100184c6b95db209b
%
% ERPLAB Too... |
6a984d8c8adc3b319fe996df3010be25cafa5af02dc97cb4e12a54dca8970b86 | MATLAB | 1,435 | 40 | function pval = lme_mass_LR(statsfull,statsred,q)
% pval = lme_mass_LR(statsfull,statsred,q)
%
% Likelihood ratio test for the random effects. It can be used to test if a
% model with q+1 random effects is significantly better than a model with q
% random effects.
%
% Input
% statsfull: Structure array containing stat... |
40a5044a2e1731acc74e33df42bbd6466ac8e53985bdbe89757e1723eeb7140d | MATLAB | 1,436 | 66 | function [ verts, normals ] = CirclePatch( numPts, radius, axis )
%CIRCLEPATCH Return a Nx3 matrix defining a set of verticies around a
%unit circle
axis = axis ./ norm(axis);
step = (2*pi) / numPts;
verts = zeros(numPts,3);
normals = zeros(numPts,3);
for(theta = 0:step:(2*pi) - step)... |
080144cb6357ebb6223c49797826598682db82a6ed9e5921b6882e2594319055 | MATLAB | 1,437 | 68 | function run_simulation_Part2(wNa, Le)
% Load solution Part 1
load(sprintf('mat/rest_Ly300nm_Li1000nm_Le%dnm.mat', Le))
% Simulation time
if wNa == 2
Tstop = 5e-4;
dx_end = 1;
elseif wNa == 6
Tstop = 5e-4;
dx_end = 2;
elseif wNa == 14
Tstop = 5e-4;
dx_end = 4;
elseif wNa == 30
Tstop = 1e-4... |
285a7ad75afc37235aaacd9be7d668de54c5798fb78375847c8c31581ba60f4d | MATLAB | 1,438 | 51 | function [ cosdiff, origcos ] = hub_cossim(mat,distmat,hubmethod,Nreps)
% the probability that hubs remain after 100% rewire
if nargin < 4
Nreps = 100 ;
end
% n = size(mat,1) ;
% enfore und
mat = (mat + mat') ./ 2 ;
triunroll = @(x_) x_(logical(triu(ones(size(x_)),1))) ;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
432ae36f207389163e046724a96e579d1d7a2a52c2c4837394928702d951271c | MATLAB | 1,438 | 47 | %% Read SPIKEs from Plexon file
[plxfile,path2plx] = uigetfile({'*.plx','Plexon file (*.plx)'}, ...
'Locate Plexon File');
SPIKE = ft_read_spike(fullfile(path2plx,plxfile));
%% Read SPIKES directly from TDT Tank (with sort codes if available)
cfg = [];
cfg.tank = tank;
cfg.block = block;
cfg.blockroot = [t... |
5705b6542b5be4d3dd887a5bc1abae135635e3861c8d05de69c7d0b6c6c3c53a | MATLAB | 1,442 | 37 | function [] = validateData(LOOPERData, validateData, validateInputs, validateOutputs)
rawData = validateData;
rawData = convertToCell(rawData);
lastEnd = 0;
for i = 1:length(rawData)
trialData(lastEnd + (1:size(rawData{i}, 2))) = i;
lastEnd = lastEnd + size(rawData{i}, 2);
end
... |
5cf8b1024dae3d1dde20c32440a5d80a027a06609fb7910903b95f6edb85c11c | MATLAB | 1,443 | 38 | 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_ (... |
9820e25e07140cd8a7915c31bd5bc7a42709a075c0bdcaa75b41fee5d62f30c9 | MATLAB | 1,444 | 69 | %%
unit = getpref('DB_BROWSER_SELECTION','units');
st = DB_GetSpiketimes(unit);
P = DB_GetParams(unit,'unit');
%%
uRate = P.lists.Rate;
fpidx = find(diff(P.VALS.Rate))+1;
P.VALS = structfun(@(x) (x(fpidx)),P.VALS,'UniformOutput',false);
clear opts
opts.clustering_exponent = -2;
opts.unoccupied_bins_strat... |
fdda60c93e3149d83721d7232726baae5ae831c07671580cdfde9e8db8022eb7 | MATLAB | 1,447 | 80 | clear all;
%% Load data
% Gives me: X (labels), Y (data), time, label
tmp = load('../data/testdata_orientation.mat');
Y = tmp.Y; % Y: features x time x trials
X = tmp.X';
time = tmp.time;
label = tmp.label;
numF = size(Y, 1);
numN = size(Y, 3);
%% Single time opint
% Select time point
sel_t = find(time... |
b8ec1fd884ebf0ce8a8eef9047d7a6cf786f7ce27bcd3b1f3822bff9d05cc6bf | MATLAB | 1,450 | 63 | function pulse_ind = getDitheredPulseInd(zeta_freq,f_stim,n,n_stim,dt,n_phi,freqSet,n_same,rndCycling)
%%% 11-02-21 adding toggling options
%%% 29-11-21 removing negative i_p's
%%% 28-06-21 first revision
%%% might not be exact
i = 1;
i_p = i;
if isempty(freqSet)
while i <= n
if zeta_freq == 0
... |
45c0d2c574c56b88a5c04f0911e88515520450fdef713b530f5632d9be867a3d | MATLAB | 1,452 | 53 | close all; clear all;
gt_dir = '/home/zxi/refinenet/datasets/gtea/SegmentationClass/testset';
pred_dir = '/home/zxi/refinenet/cache_data/Multiscale_evaluation_refinenet/gtea/test/predict_result_mask';
im_dir = '/home/zxi/refinenet/datasets/gtea/JPEGImages/testset';
dir1 = dir(fullfile(pred_dir));
%remove '.' and ... |
5eb545cf6495f740e0a3098dfd13191fed48ae8f109b6c83dec36b327238de03 | MATLAB | 1,454 | 45 | function [ IOU, Precision, Recall,MCR ] = getIOU( pred_map,gt_map,get_other_scores)
%this function computes IOU when given a prediction map and respective
%ground truth map. Both pred_map and gt_map should be 2D binary maps.
% INPUT: pred_map: a binary image prediction map
% gt_map: a binay image ground tru... |
9a6e108f4ca57d1a195770ac9d530486fb7c43e5e7c205b8e14ed504b4f3b247 | MATLAB | 1,454 | 46 |
function self = EvaluateConfidenceScorer(self)
confScorer = self.ConfidenceScorer;
if self.VerboseLevel > 1
fprintf(' - %s scorer\n', confScorer.Method);
end
tmpS = struct;
tmpS.Properties.Method = confScorer.Method;
if self.VerboseLevel > 1
fprintf(' - Training set\n');
end
isSet = self.ClipTable.Set ... |
3a260377105a61137438ac55c992fae266c4693021b4eb2b8cd4a4edb29e01e1 | MATLAB | 1,455 | 46 | function h = mplot(t, matrix, varargin)
% UltraMegaSort2000 by Hill DN, Mehta SB, & Kleinfeld D - 07/12/2010
%
% mplot - Plot rows of a data matrix.
%
% Usage:
% h = mplot(t, matrix, varargin)
%
% Description:
% MPLOT(MATRIX) makes a line plot of the rows of an (M x N) matrix using
% a single line object. ... |
37cbaf8bc813f213e6f21b34f7edb1f0a9af3d5cbd8d198093515bcf55e2b9d5 | MATLAB | 1,461 | 23 | function c0 = initial_conditions(x, y, z, G, c_idx)
%c0 = initial_conditions(x, y, z, G, c_idx)
c0 = (x < G.Li).*G.c0i(c_idx) + (x > G.Li+G.Lm).*(x < G.Li+G.Lm+G.Le).*G.c0e(c_idx) + ...
(x > G.Li+G.Le+2*G.Lm).*G.c0i(c_idx) + ...
(c_idx == 1).*(x >= G.Li).*(x <= G.Li+G.Lm).*...
(y > G.Na_channel_start_y-G.dy... |
3f031492683e48f93297d849f13ccb868c451e78e0e68cfca96a398fe46ba1c2 | MATLAB | 1,461 | 49 | function demo()
% demonstration file for SparseGDLibrary.
%
% This file illustrates how to use this library in case of "lasso"
% problem. This demonstrates FISTA and ADMM algorithms.
%
% This file is part of SparseGDLibrary.
%
% Created by H.Kasai on Apr. 24, 2017
clc;
clear;
close all;
%% prep... |
bdc70d4d3297e1ce21da831e477b91d247f27d824feecf9bb3e25e3f25befa9a | MATLAB | 1,461 | 50 | function [p,U2_obs,U2_H0]=watsons_U2_perm_test(A1,A2,N)
%
% [p,U2_obs,U2_H0]=watsons_U2_perm_test(A1,A2,N)
%
% Computes the probability that two samples of circular data (angles) come
% from the same distribution, or from distributions with the same direction
% (null hypothesis), using a permutation test and Wats... |
fcbbe3285559e44f4f72580a3816f9973e4883ae777cd9c87decded9ed6e2cd0 | MATLAB | 1,463 | 48 | function visualPolar2(h,x,prop)
persistent p p2
%Define the shape and colour of the dot based on elevation and target
%heading
if x(6) <= -1*prop(3)
dotColour = 'b';
dotMarker = 'o';
elseif x(6) <= prop(3)
if (x(5) > (prop(2,prop(1)) - prop(3))) && (x(5) < (prop(2,prop(1)) + prop(3)))
dotColour = '... |
a07151f354b7f8f62c56bc743c981c54a12317014d9db5fbf5270feac7b286ee | MATLAB | 1,466 | 48 | function visualPolar4(h,x,Target,Head,Tol)
persistent p p2
%Define the shape and colour of the dot based on elevation and target
%heading
if x(6) <= -15
dotColour = 'b';
dotMarker = 'o';
elseif x(6) <= 15
if (x(5) > (Head(Target) - Tol(Target))) && (x(5) < (Head(Target) + Tol(Target)))
dotColour = ... |
dc5fec16317341a822bf465a765b56f9ee8769d7b086f8ae1709281f377c65ae | MATLAB | 1,468 | 39 | function TPPreviewImageFunctionListAddCache(filename, pvimg, params, parameters, dirname, tpfnameparameters, total_frames, dirnames, videoinfo)
% TPPREVIEWIMAGEFUNCTIONLISTADDCACHE - Add preview image parameters to the cache
%
% TPPREVIEWIMAGEFUNCTIONLISTADDCACHE(FILENAME, PREVIEWIMAGE, PARAMS, PARAMETERS, ...
% ... |
f011de51f40f25cbf6d03eaf7b2b49038b23a8bdcec18e53e96d24e473a8a09c | MATLAB | 1,468 | 63 | %% MYDEMO: Demonstrate usage of mym utilities
% Example: mydemo (Oh, the FEX code metrics..)
%% List available functions
lookfor mym
%% Connect to MySQL
myisopen
myopen('localhost','root','fairfax')
myisopen
%% List available databases
dblist
%% Create database 'test2'
dbadd('test2')
%% Confirm th... |
a93abaa5c62292fb4f48c34aa95d1ffde7ee0dd8648a1bc6128d78cbd63ab245 | MATLAB | 1,469 | 36 | function [nerveModel, electrodeType, electrodePlacement, paramSet] = select_model()
% TODO group all into a single modelSelection struct
[modeList, electrodeTypeList, placementList, paramList] = get_models_list();
iSubject = listdlg('PromptString', {'Select Subject Id'}, ...
'SelectionMode', 'single', 'Lis... |
3a0ba7717ed198bf2c08ebabd3e133541d15a15c1dd097f618c29059c85a54a9 | MATLAB | 1,470 | 41 | function [ev,lb,ub,RPV] = ss_rpv_contamination( spikes, use )
% UltraMegaSort2000 by Hill DN, Mehta SB, & Kleinfeld D - 07/09/2010
%
% ss_rpv_contamination - wrapper for rpv_contamination.m
%
% Usage:
% [lb,ub,ev] = ss_rpv_contamination(spikes,use)
%
% Description:
% Estimates contamination of a cluster based on ... |
a33e9bdba0d726123105af82c21b01a9be6b39a7b3cfae6b9ec0037f7efce1b3 | MATLAB | 1,470 | 50 | close all; clear all;
gt_dir = '/home/zxi/refinenet/datasets/ADE20K_hand_images/SegmentationClass/test';
pred_dir = '/home/zxi/refinenet/cache_data/Multiscale_evaluation_refinenet/ade_on_ade/test/predict_result_mask';
im_dir = '/home/zxi/refinenet/datasets/ADE20K_hand_images/JPEGImages/test';
dir1 = dir(fullfile(pre... |
58415208dbb0048da10e6942e9f3902e0b11c2b6ff47463b5a9d5b9910a201c0 | MATLAB | 1,472 | 53 | clc; clear; close all
Fig4b=figure();
Ntrials_3=60000;
%Ntrials_3: number of learning cycles to learn the background.
%There is no embedded pattern in afferents.
%(Note initial conditions in this step are from step 2)
N_mu=500; %There are \mu independent embedded patterns, 500 simulations (number of simula... |
8c5a6f076290264e3637c7ed76b4637718baeaba518d01f6bf8b66217dab35f6 | MATLAB | 1,474 | 50 | function varargout = ep_LaunchPad(varargin)
% ep_LaunchPad
%
% Buttons to launch the different GUIs associated with the ElectroPsych
% toolbox.
%
% Daniel.Stolzberg@gmail.com 2015
% Copyright (C) 2016 Daniel Stolzberg, PhD
% Edit the above text to modify the response to help ep_LaunchPad
% Last Modified by GUIDE v2... |
8c982b1bb741ffc97eeb983718409f03fcf34a857b2c86afc380f45eeea60d26 | MATLAB | 1,474 | 46 | % *** This function is part of ERPLAB Toolbox ***
% Author: Javier Lopez-Calderon
% Center for Mind and Brain
% University of California, Davis,
% Davis, CA
% 2009
%b8d3721ed219e65100184c6b95db209bb8d3721ed219e65100184c6b95db209b
%
% ERPLAB Toolbox
% Copyright © 2007 The Regents of the University of California
% Creat... |
308f0d6be7a2c517213b204388c2c6afacb71b4d0f622ec40274886e2709682a | MATLAB | 1,478 | 46 | function [lmatrix_new, complist] = bmf_fill_holes_patches(lmatrix, complist)
% This function ensures that every patch is continuous within
% lmatrix = a three-dimensional matrix with a mask for each patch
% separately
% complist = patch border information from the frequency segementation code
% output
% lmatr... |
83f1b86c91d33caa2319cc2f17e037e6fa4494c90c0dcf044a3706c37d4ea71f | MATLAB | 1,480 | 50 | function model = dtip_pipe_SDPd(data,btensors,mask,nvox,ind,parallel,cvxsolver)
% function model = qtip_pipe_SDPdc()
%
% reshape data and retain voxels within the mask
siz = size(data);
data = reshape(data, prod(siz(1:3)), siz(4))';
mask = reshape(mask, prod(siz(1:3)),1)';
si = find((mask>0).*(~all(data==0,1)));
data... |
a66022090359bc3476b85d436189d1f582b14d377d53b8c1eebef68504051aa1 | MATLAB | 1,480 | 56 | function PlotDataRasters
clear all
close all
clc
% Created 22 April 2016 JDY
%---FLAGS---%
Behavior = 1;
subject = '230115';
% subject = '235107';
session = 'CA';
Block = '126';
Path = '/Users/justinyao/Sanes Lab/Experiments/PROJECTS/AM RATE/Ephys/processed_data/';
DataFile = [Path subject '/' subject '_se... |
11948acb8a337fc92a437bf7ac4fde275b50a01bb8a589d7757802846c10adc8 | MATLAB | 1,482 | 45 | function json = readSettings(varargin)
% Reads in from file, parses, and returns the JSON-formatted config file
% (e.g. export and stimulus paths).
%
% You can run this without arguments if you use the default io.json in the config folder
args = parseInputs(varargin);
% try to open the settings.... |
a23300b989d9fc6ffefa985de7bbb10b6dd7c850918e79a2f3617a93523e60e7 | MATLAB | 1,482 | 46 | % PURPOSE : To view the ERPLAB Toolbox User's manual
%
% FORMAT :
%
% pop_erphelp
%
% INPUTS :
%
% - No inputs necessary
%
% OUTPUTS :
%
% - Will open the ERPLAB Toolbox User's Manual in an html file
%
% *** This function is part of ERPLAB Toolbox ***
% Author: Javier Lopez-Calderon
% Cent... |
459ef3bf97a5d2b5038eb0cd3ca143c002b8f7704b52bb1fe7b06a244c39bacb | MATLAB | 1,483 | 46 | % PURPOSE : To view the ERPLAB Toolbox Tutorial
%
% FORMAT :
%
% pop_erphelptut
%
% INPUTS :
%
% - No inputs necessary
%
% OUTPUTS :
%
% - Will open the ERPLAB Toolbox Tutorial in an html file
%
% *** This function is part of ERPLAB Toolbox ***
% Author: Javier Lopez-Calderon
% Center for ... |
a4c80539d61416eba3602952b5aba52ab794fd18ddff4fecdd028f0f31f6c8e9 | MATLAB | 1,485 | 58 | function [im] = tpquickmap(dirname,channel,resps,pixels,plotit,method,param1,param2)
% TPQUICKMAP - Produces a colored map of responses
% IM=TPQUICKMAP(DIRNAME,CHANNEL,RESPS,PIXELS,PLOTIT,METHOD,PARAM1,PARAM2)
%
% Generates a color map of neural responses.
%
% DIRNAME is the name of the directory. A preview im... |
fa07996900311a5b8aedbbfc3689fe2698888fe4950b79580aa00f5117c77217 | MATLAB | 1,485 | 31 | function writeplxchannelhdr(plx_id,ch,npw)
% now the single PL_ChanHeader
pad256(1:256) = uint8(0);
% assume simple channel names
DSPname = sprintf('DSP%03d',ch);
SIGname = sprintf('SIG%03d',ch);
fwrite(plx_id, DSPname, 'char');
fwrite(plx_id, pad256(1:32-length(DSPname)));
fwrite(plx_id, SIGname, 'char');
fwrite(plx... |
d2cf547aaf80e9adcc1363a2803b4f3ddf86a8bc60e8e979cb0a6e55d845cec0 | MATLAB | 1,489 | 35 | %% Calculate x- and y-bounds for an OH/OHA/TOH/TOHA trial's workspace
% Determine the minimum and maximum values in the x- and y-dimensions of
% the workspace for an OH/OHA/TOH/TOHA task.
% Copyright (C) 2022 Richard Hugh Moulton
%
% This program is free software: you can redistribute it and/or modify
% it under ... |
da908bd0e486585482ad4591f86341a4cb4e3f5ddc0bc881d712be499df8e049 | MATLAB | 1,489 | 49 | function [linehandles, patchhandles] = errorarea(x,y,l,u)
% UltraMegaSort2000 by Hill DN, Mehta SB, & Kleinfeld D - 07/12/2010
%
% errorarea - Plot line with confidence region.
%
% Usage:
% [linehandles, patchhandles] = errorarea(x,y,l,u)
%
% Description:
% ERRORAREA(X,Y,L,U) is similar to ERRORBAR(X,Y,L,U), e... |
77b05f8c06f934ff1c6664fec66433eaa89afcc0a775b14e03a020f68ecf1f98 | MATLAB | 1,490 | 63 | function [stds, d_log_scales] = scaledGaussianComponent(ws, log_scales_0, grps, dU_0, stds)
% i.i.d. multivariate zero-mean normal prior distribution over columns of ws with covariance matrix
% defined in GMLMprior_dmcStimVar
%
% calculates prior and all derivatives
compute_D1 = nargout > 1;
precomputed_portion ... |
9c860af8a64fd75a8643b76c6387f725c3ad1a5e39fb34c8e17660b00eab655c | MATLAB | 1,490 | 48 | function visualPolar3(h,x,Target,prop)
persistent p p2
%Define the shape and colour of the dot based on elevation and target
%heading
if x(6) <= -15
dotColour = 'b';
dotMarker = 'o';
elseif x(6) <= 15
if (x(5) > (prop(2,prop(1)) - prop(3,prop(1)))) && (x(5) < (prop(2,prop(1)) + prop(3,prop(1))))
do... |
4d9fa6c2031ff6492f82a9d634325c7e077b867ca982c39021068d0fa6a82383 | MATLAB | 1,492 | 41 | function confusion = ss_gaussian_overlap( spikes, use1, use2 )
% UltraMegaSort2000 by Hill DN, Mehta SB, & Kleinfeld D - 07/12/2010
%
% ss_gaussian_overlap - wrapper for gaussian_overlap.m
%
% Usage:
% C = ss_gaussian_overlap( spikes, use1, use2 )
%
% Description:
% Estimates the overlap between 2 spike cluste... |
93ca995d1c9c71ada94ef6d153da1741d82034f9d455a4dce609a54da0c9b8ac | MATLAB | 1,492 | 57 | clc; clear; close all
Fig8c=figure();
r0_t = 2:1:9; %r_0 (desired number of spikes)
N_mu=100; %There are \mu independent embedded patterns, 500 simulations (number of simulations)
RESULTS=zeros(4,numel(r0_t));
for p1=1:numel(r0_t)
SD=r0_t(p1);
for p2=1:N_mu
eval(['load Learning_B... |
0e0159999fdbb55b40bffd4488b0e29280713d5ae6784abcaad3f73c2dd26272 | MATLAB | 1,493 | 60 | function fx = filterSignal(x, fLow, fHigh, Fs, dim, hilbertFlag)
% FILTERSIGNAL band-pass filters the signal X with the desired cutoff
% frequencies FLOW and FHIGH, given the sampling frequency FS. Data will be
% filtered along dimension DIM (default 1) and if boolean HILBERTFLAG is
% true, FX will be the analytic sign... |
72ae2acedcb276895c685bc3a7aeb839ca84ea8a8b9e38b2f47232a383203318 | MATLAB | 1,493 | 49 | function [p,mu,stdev,n,x] = ss_undetected(spikes,use)
% UltraMegaSort2000 by Hill DN, Mehta SB, & Kleinfeld D - 07/12/201
%
% ss_undetected - wrapper for undetected.m
%
% Usage:
% [p,mu,stdev,criteria] = ss_undetected(spikes,use)
%
% Description:
% Estimates how fraction of spikes associated with a given clus... |
757804fa494e7ea96e4460d16c03b876ef1d8ecf0699742d5957196a0426da92 | MATLAB | 1,494 | 79 | function [zp,Overlap] =assignment(z,type,Size)
% [zp,Overlap] = assignment(z,type,Size);
%
% Input
% z: nx2 or 2xn coordinates
% type: if z is raw data or representing in Cartesian coordinates then
% type = 'raw'
% type: if z is representing Pixel Coordinates then
% type = 'pixel'
%
% Size: is the frame ... |
d780af23b0782b50fa2eefc665057e7433f48abec82cbf8d43030565601bb1d2 | MATLAB | 1,494 | 38 | function baseline = compute_baseline(basetimes, baselinemethod, isidata, isitimes, isidatam, isitimesm, blankdata, blanktimes, blankdatam, blanktimesm)
% COMPUTE_BASELINE - Compute baseline F for dF/F for two-photon data
%
% BASELINE = COMPUTE_BASELINE(BASETIMES, BASELINEMETHOD, ...
% ISIDATA, ISITIM... |
3029df4070ba8109accc857b3a968f1bdef61f897bcdbb6786390d9a8667069e | MATLAB | 1,495 | 44 | function activeArray = makeActivePatternsArray(patterns, npat, nt)
%MAKEACTIVEPATTERNSARRAY converts pattern matrix to activity array.
% This function takes the PATTERNS matrix output by FINDALLPATTERNS
% giving the start and end of each pattern, and converts to a PxT matrix
% giving the number of patterns of eac... |
777be375d7c992d6fb6932da65f88592702e747e3b3a6dcf99ce5aa533dd2382 | MATLAB | 1,495 | 36 | function [TmtxS,iFRs,usel_out]=SelTrialsCellsWholeTrial(fn,twin,minFR,critCvBW)
% Select cells from PFC and HC data sets & cut out event periods (trial case)
% outputs
% Tmtxs {no. trials} time axes for selected trials
% iFRs {no. brain areas}{no. trials}(timerange,no. neu... |
e7e68373a2e814adddf460e743e0823fab2c643818274265aa6cf010a5c1c52d | MATLAB | 1,498 | 67 | function [C,X]=TrimMesh(C,Trim,X)
% Trims mesh according to bounding box in Trim
% INPUT:
% trim=[xmin xmax ymin ymax zmin zmax] coordinates of trimmming box for mesh. NaN=no trimming.
% OUTPUT:
% C(e,:)=connectivity of element e
% X(i,:)=(x,y,x) coordinates of node i
% Select nodes on x
nodesc=cell(6,1);
for ... |
9374f450465d240e2fa4dfbdd97cbdb085b6be0162b84427a18a4e3f0080466f | MATLAB | 1,499 | 32 | % Example 2: Feature selection of saved model
%
% In this Example, feature selection using class-activation maps (CAMs) is executed.
% It is assumed that Example 1 has been run before running this Example.
% Running Example 1 will save model files in Models/Run.. folder and also the
% data file either Out1.mat (if no... |
d1112f04fa73ed3140264a585b6adc0cc32fd1e88018eced68434a6349a26060 | MATLAB | 1,500 | 39 | % defualt params and upper/lower bounds for the Liley model
param.he_rest = -69.6952;
param.hi_rest = -74.4255;
param.Nee_beta = 2847.80;
param.Nei_beta = 4422.60;
param.Nie_beta = 744.01;
param.Nii_beta = 173.86;
param.Gamma_e = 1.9827;
param.Gamma_i = 0.4169;
param.gamma_e = 0.3030;
param.gamma_i = 0.0486;... |
e2bae9997101bf39fc5047b69af55fffafe5da874c607dcc53fa796cf1d5d8a2 | MATLAB | 1,500 | 60 |
%% plot vectors
function [] = plotVectors(ax, dirs, colors, includeBoundary, markedDirection, arc)
hold(ax, 'on');
%plot requested arcs
if(nargin >= 6)
for ii = 1:size(arc, 1)
theta_1 = min(dirs(arc(ii,:)));
theta_2 = max(dirs(arc(ii,:)));
... |
4726e046fabf91aca11fe699a21d6a89346293cdb5ac33b5a7a304db69b789ab | MATLAB | 1,505 | 72 | function fit1 = fitness_moea45(A1, paramsvec, eegdata1, paramstoest, T1,tcut, fhz1)
paramsinput = [paramsvec, zeros(1,10)];
paramsinput(paramstoest) = A1;
% load in the data to fit against
eegautocor = eegdata1{1};
eegdatadegdist = eegdata1{4};
z = eegdata1{2};
z2 = eegdata1{3};
a4=[];
fithvg=[];
parfor Run... |
525f05299b32ca2d3f5126ce640e4ce641852307d17fd19653e82c277c300b63 | MATLAB | 1,505 | 28 | function [crossEntropy,dev,yhat,beta] = GLM_logit_constantCV(features,y,CVfolds)
% Performs unregularized regression using logistic link function on binary (logical) response data y from the features.
% Uses stratified k-fold cross-validation using the pre-partitioning of the data y appearing in CVfolds,
% and calculat... |
ebcdf1518821cd1cd1422ca6290ae31556e9eba1b89b7d53e3e696abe89ceaa7 | MATLAB | 1,505 | 36 | function [avgReversal, avgReversalRT] = ...
behaviorReversal(filePath,dataFiles,reversalCritereon)
%% calculate behavioral reversal
% (=three consecutive correct trials after a block ended)
for session=1:size(dataFiles,1) %for all sessions
load(fullfile(filePath,dataFiles(session,:)))
%sequence ident... |
446fc5868d64bc61977ee8870075873dade5db1baf5fae5d6f30f5416a5c009a | MATLAB | 1,506 | 30 | %%% Although the code should be run on a supercomputer to get Arnold tongues with a
%%% good resolution, this is a test call that can be used on a local machine.
%%% The predefined parameters below will generate the data for a dithering level
%%% zeta = 0.047
%%% 26-01-23 first commit
clearvars
close all
fpath ... |
38d00d2d3d5592e080e25bd18ad0e00dd7feb68bd242103e7d0eeee0e8c7d2b3 | MATLAB | 1,507 | 46 | function cdf_validation(iSubject, rootDir)
%PDF_VALIDATION Summary of this function goes here
% cdf_validation(1, '..')
[numFibersAtPercepThreshold, placements, percepThresholdsExp] = num_fibers_for_perception(iSubject, rootDir);
qMaxnC = 120;
% How to treat this missing data?
percepThresholdsExp(isnan(pe... |
f36472cbbb99a1261e5c82a626bb888cea2dcdf7dbcf04963d879f8c18257105 | MATLAB | 1,507 | 51 | % Assigns the given value to the named property of an object or structure.
% This function can deal with nested properties.
%
% Input arguments:
% obj:
% the structure, handle or value object the value should be assigned to
% name:
% a property name with dot (.) separating property names at
% different... |
c8a10f34c7d4a42173f70fe38e0409f0caaf7a9750a7d631b2a93043f662274f | MATLAB | 1,508 | 49 | function [param, ev, ssVal, model] = fitReduceEEG(EEG, velocity, retinalP, initCond, bd)
param = [];
model = [];
ev = [];
ssVal = [];
vlb = bd(1,:);
vub = bd(2,:);
parfor i = 1:size(initCond,1)
optObj = opti('fun', @(pSolve) sumLsqTSDAB(pSolve, EEG, velocity, retinalP), 'sense', 1, 'lb', vlb', 'ub... |
16ac72bbe0564bad19c8dda5fa5768cba80d8bc59119271d5291ef56cce07e1e | MATLAB | 1,510 | 59 | function popup(ah,fh,varargin)
% POPUP - copies a subplot into a full figure
% POPUP(ah, fh) copies the object <ah> into the figure <fh> if this exists.
% If it doesn't a new one is created. <fh> is optional. Instead of a handle
% <fh> may be a name of a figure.
%
% Example:
% fh = figure;
% ah = gca;
% ...
% ... |
21b6a23a7848d62a988a117fc9d39575990705942ce3e27faee821d2dd87cdc2 | MATLAB | 1,510 | 47 | function plot_histograms2(parameter_set,subplot1,subplot2,color,parameters_to_plot,subplot,text)
% This function plots hisotgrams of parameter locations
FS1=7;
paramnames= {
'h_{e}^{rest}' ,'h_{i}^{rest}','N_{ee}^{\beta}','N_{ei}^{\beta}','N_{ie}^{\beta}','N_{ii}^{\beta}','\Gamma_e',...
'\Gamma_i','\gamma_e','... |
4c0b70766ea190bfbe66817307b01da8c7c97b25c9138b48168b8cbbe270d9bd | MATLAB | 1,511 | 46 | function [hr,pval] = SStat_mass_HR(x1,x2,y1,y2,stats)
% [hr,pval] = SStat_mass_HR(x1,x2,y1,y2,stats)
%
% Vertex/voxel-wise hazard ratio estimates for Cox models.
%
% Input
%
% x1: Row vector with the covariate values for the first group (1xp).
% x2: Row vector with the covariate values for the second group (1xp) .
% y... |
bdc779a88fab1737a41634d1ae61716df212220c6e97af1b5acf04ae5a289658 | MATLAB | 1,513 | 46 | % PURPOSE : To view the ERPLAB Toolbox Script Tutorial
%
% FORMAT :
%
% pop_erphelpscript
%
% INPUTS :
%
% - No inputs necessary
%
% OUTPUTS :
%
% - Will open the ERPLAB Toolbox Script Tutorial in an html file
%
% *** This function is part of ERPLAB Toolbox ***
% Author: Javier Lopez-Calder... |
cb3d6373c5e12b48fddcea3a1dcb889369cbd14e8e07d51feb3d035d62b98c9b | MATLAB | 1,513 | 54 | function mni_coords = ccep_mni305linear(elecmatrix,FSdir)
%
% Convert electrodes in native space to MNI using linear transformation
%
% Input:
% elecmatrix: nElec x 3 in the original T1 space (before freesurfer)
% hemi: hemisphere to load for each electrode (l/r)
% FSdir: subjects freesurfer director
%
% Example:... |
20ddec992fd30a7df73f69b388681629b51cfdc2d11ec050779a96cb7526fce6 | MATLAB | 1,514 | 44 | %this is a program that generates trial averages and forms clusters based
%on that/Choose folder : DMDLBRDLCB_allbrainpoolPL. Created by Haleh Fotowat.
close all
clearvars
path=uigetdir;
cd(path)
%read the pooled clustering data
load('DMDLBRDLCB_082628_091112_HA.mat')
RegData=csvread('DMDLBRDLCB_celltypes_registered... |
13902b4501561b3997d5e7fd5bff59c238eff3a3dc21f9be4900e53faf098c44 | MATLAB | 1,516 | 55 | function varargout = TDT_TankSelect(varargin)
% [tanks,ok] = TDT_TankSelect(varargin)
%
% Optional Input Parameters:
% 'SelectionMode' ... 'multiple' or 'single' (default)
% 'Name' ... dialog title
% 'OKString'
% 'CancelString'
% 'TankList' ... optional tank li... |
6c10ba386616d9c1e19583f88695665c628688b417b131ce50c287af7230208f | MATLAB | 1,517 | 55 | function [chk, msgboxText] = f_ERP_chckbinandchan(ERP, binArray, chanArray,Bin_Chan_label)
chk=[0 0];
msgboxText = '';
% if numel(Bin_Chan_label)==1
% Bin_label
%
% end
if Bin_Chan_label==1
if isempty(binArray)
msgboxText = 'You have not specified any bin';
chk(1) = 1;
return
... |
0c167a344c1ddeb2c3c56f11a8163fbf760f2d877eed2ab6503ed2171fc4bbd2 | MATLAB | 1,520 | 46 | function KL = dist_KLdiv(P, Q, doWarning)
% Compute the Kullback–Leibler divergence between probability distributions
% P and Q. Note that KL is not symmetric. KL(Post, Prior) quantifies the
% information gain when moving from the prior to the posterior.
%
% Usage:
% KL = dist_KLdiv(P, Q, doWarning)
% NB: doWarning: ... |
3283c56334358c000d27b6ba99f5869614086cde512e49ca7ac6a99a2a3ae67b | MATLAB | 1,520 | 67 | function varargout = plot(varargin)
% plot method for GIfTI objects
%__________________________________________________________________________
% Copyright (C) 2008 Wellcome Trust Centre for Neuroimaging
% Guillaume Flandin
% $Id: plot.m 5888 2014-02-19 19:54:12Z guillaume $
% if ishandle(varargin{1})
% ... |
f973b0b44d255a110fceb0ad587827b9c12102d0f52205a199d15f00ffe58022 | MATLAB | 1,522 | 38 | function [beta_out] = merge_into_large_tbl(beta_table)
%MERGE_INTO_LARGE_TBL Create one large table from the beta_tables variable
% taste strings from Variable names
taste_strings = beta_table.Properties.VariableNames;
% Create a copy for merging
beta_out.merged = beta_table;
beta_out.single = beta_table;
for taste_i... |
a0ffefdc19159adc27ac296da9769fade3ac8f8d7481180047f8b6ce8ba7f330 | MATLAB | 1,524 | 55 | function [rou,diffu] = scaled_routing_n_diffusion_und(mat,reps,rwiter,transform)
if nargin < 2
reps = 10 ;
end
if nargin < 3
rwiter = 1 ;
end
if nargin < 4
transform = 'inv' ;
end
% clean up mat
gg = get_components(mat) ;
ggmode = mode(gg) ;
if any(gg~=ggmode(1))
warning('more than one component, wil... |
f67a1f7a42b846f4dff1be23c7c1c0594edd96df16aaf276b07c912085ce437c | MATLAB | 1,524 | 69 | function TrialFcn_PumpControl(ID,rate)
% TrialFcn_PumpControl
% TrialFcn_PumpControl(ID)
% TrialFcn_PumpControl(ID,rate)
%
% This function sets and controls the pump variables for the Aversive AM
% Detection task.
%
% Optional: ID = inner diameter of the syringe
%
% Daniel.Stolzberg@gmail.com 2014. Edited by MLC 10/30/... |
97817791afb889400ca4f1db5a4a038bd93be9d4bd126f01c56e62bd5de0ed80 | MATLAB | 1,525 | 64 | function sandrine2vhlabtstack_dir(dirname)
% SANDRINE2VHLABTSTACK_DIR - convert a whole directory of Sandrine experiments to vhlab t-stack format
%
% SANDRINE2VHLABTSTACK_DIR(DIRNAME)
%
% Coverts a whole directory of files in .lif format to vhlab t-stack format.
%
% Expects the name of the .lif files to be:
%
% YYYYMMD... |
ce6e701ed9ea28c288c8dd05636799a30d0e75180be36adf648332c29eda6470 | MATLAB | 1,525 | 70 | function TrialFcn_PumpControl(ID,rate)
% TrialFcn_PumpControl
% TrialFcn_PumpControl(ID)
% TrialFcn_PumpControl(ID,rate)
%
% This function sets and controls the pump variables for the Aversive AM
% Detection task.
%
% Optional: ID = inner diameter of the syringe
%
% Daniel.Stolzberg@gmail.com 2014. Edited by MLC 10/30/... |
1f1942ecb51ca2bb4b25d87bf0802033cbda28192dc6f49c925b5d25e7bd7847 | MATLAB | 1,526 | 41 | function fascIdsByAs = check_active_sites_ranges(endo, ...
activeSitesCoord, asRange)
% CHECK_ACTIVE_SITES_RANGES determines whether or not any point in a
% fascicle is in reach of the electrodes' active sites
%
% fascIdsByAsPerElec = check_active_sites_ranges(endo, activeSites)
%
% Inputs: - endo
% - acti... |
03d33ba669f32693df66d89e489d522ba8497ebf16750c74ec95278dca35b269 | MATLAB | 1,529 | 70 | function [roiid,m,idx] = do_barplot(pow_parcel,rois, nroi)
figure,
bar(pow_parcel);
L = length(rois);
set(gca,'Xtick', 1:L,'XtickLabel',1:L);
box off
set(gca,'color','none');
xlim([0,L+1])
xlabel('ROI');
ylabel('Source power');
set(gcf, 'Position', [1000 100 1200 500]);
set(gca,'FontSize',10,'XTickLabelRotation'... |
13af549dab67224bce5bfe642eacc5ebb0b40aee0d26ce3f9e1356fcf75cd75f | MATLAB | 1,530 | 54 | function sRGB = spectrumRGB(lambdaIn, varargin)
%spectrumRGB Converts a spectral wavelength to RGB.
%
% sRGB = spectrumRGB(LAMBDA) converts the spectral color with wavelength
% LAMBDA in the visible light spectrum to its RGB values in the sRGB
% color space.
%
% sRGB = spectrumRGB(LAMBDA, MATCH) co... |
4fa8dc7bfb3ce85a11213d75d35f9cc2a7990313a8e9140a65ed97693392f2e6 | MATLAB | 1,530 | 56 | function [ y ] = modelfun_dHEC( beta, x )
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
stim_az = x(:, 1); % stimulus azimuth
FP_az = x(:, 2); % fixation point azimuth
nof_AV_stims = x(:, 3);
AV_data = x(:, 3+(1:(3*nof_AV_stims)));
AV_data = reshape(AV_data, [nof_AV_stims 3... |
e89347bb381fae394d9c9e88e3d4eb0d0932b3be82fa7c88dd18e8a0c32ff0a3 | MATLAB | 1,530 | 43 | function F = ccep_fitpiecewiselinear(pp,Y,x)
% fitting a piecewise linear function with 2 segments to ccep data
% Copyright (C) 2020 D Hermes and D van Blooijs
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
%... |
08786b04a9102d9f09017eb6fd02dcff3f1cc6f7da40c430edd7c80b6fdee105 | MATLAB | 1,531 | 65 |
%% Script to generate Figure 6
clear all
close all
runs = 10;
epochs = 1000;
hunits = {'2', '4', '8', '16', '32','64'};
runsstrings = {'Run1','Run2','Run3','Run4','Run5',...
'Run6', 'Run7','Run8','Run9','Run10'};
rmseGRUT = zeros(runs,epochs,length(hunits));
rmseGRUV = zeros(runs,epochs,length(hunits));
% All G... |
21c7bdd41cdb2069c9c6c95f4206119c241a48ed40814458cbb67aba08ff08e7 | MATLAB | 1,531 | 48 | function test_normality(iSubject, rootDir)
%TEST_NORMALITY Summary of this function goes here
% Detailed explanation goes here
[numFibersAtPercepThreshold, ~, percepThresholds] = num_fibers_for_perception(iSubject, rootDir);
% Filter values, 50 makes it more regular
% percepThresholds = percepThresholds(perc... |
073e7df0ddfb756fb8e9ef496e2a0d5965d8cebf6c36e4562f917fb01a51a009 | MATLAB | 1,532 | 66 | %%This function is to display the summary of trial information
%
% FORMAT :
%
% pop_erp_ar_summary(ALLERP,ERPArray);
%
% ALLERP - structure array of EEG structures
% ERPArray -index of erpsets
%EEGNames -EEGset names
% *** This function is part of ERPLAB Studio Toolbox ***
% Author: Guanghui Zhan... |
97973f847a7230dac60476490ab098a2e544b4363bfa68bcb3316012d7371b2a | MATLAB | 1,532 | 73 | % PURPOSE :
function erplab_running_version(varargin)
erpcom = '';
if nargin < 1
help erplab_running_version
return
end
%
% Parsing inputs
%
p = inputParser;
p.FunctionName = mfilename;
p.CaseSensitive = false;
p.addParamValue('version', []); % erpset index or input file
p.addParamValue('tooltype', ''); ... |
28190e3bbf1dc48e329d5910af3bc6ff224a778c867a35973f21971d12f842aa | MATLAB | 1,533 | 46 | function [xc,lags_xc,w,lags_w] = getLags(db,P,lagP)
%% Get the binned data
[~,neurProj,motDat,baseIdx] = getDataBinnedToVideoFrames(db,P,lagP);
for k = 1:P.nMice
% Take only baseline
neurProj{k}(~baseIdx{k},:) = nan;
% Subselect only 1st component
neurProjPC1{k} = neurProj... |
9587c9b6b2bc8c80bf65239d1e30bb8417ce1a78653d57ee7efe1b47b75cfc06 | MATLAB | 1,535 | 53 | function [tag,datatype] = ReadRPvdsTags(RPfile)
% tag = ReadRPvdsTags(RPfile);
% [tag,datatype] = ReadRPvdsTags(RPfile);
%
% Read parameter tags from an RPvds file. RPfile is the full path and
% filename to an RCX file.
%
% Daniel.Stolzberg@gmail.com 2014
% Grab parameter tags from an existing RPvds file
... |
2dddd732d2376956916ab89c5adf02d5dc12b00089878d8eb823572bc66dba23 | MATLAB | 1,536 | 26 | function D = diffusion_coefficient(x, y, z, G, c_idx)
%D = diffusion_coefficient(x, y, z, G, c_idx)
if isfield(G, 'sodium_open')
sodium_open = G.sodium_open;
else
sodium_open = [0,0];
end
D = (x < G.Li-G.dx_min/2).*G.D(c_idx) + (x > G.Li+G.Lm+G.dx_min/2).*(x < G.Li+G.Lm+G.Le-G.dx_min/2).*G.D(c_idx) + ...
... |
cba089f6907f026b44f6305bcfcb43a2a0c1cbbdd5c7c380c6923b29c02cc634 | MATLAB | 1,536 | 55 | function plotMap_slopeBased(w,f0Vect,aVect,fpath,withMask,clab,xlims,ylims,clims,...
adjustFt,tol_w,tol_dw,spanFact,method)
%%% 26-01-23 first commit
figure
if strcmp(clab,'mean instantaneous frequency (Hz)')
colormap(inferno(256))
elseif strcmp(clab,'PLV 1:1') || strcmp(clab,'PLV 1:2') || strcmp(clab,'P... |
fb770b1f3026cc73c698897e0d423d23d9e41c763501d0bd070295f6208d546f | MATLAB | 1,536 | 45 | % PURPOSE: gets current ERPLAB GUI's background color
%
% FORMAT:
%
% bcolor = geterplabcolor;
%
%
% *** This function is part of ERPLAB Toolbox ***
% Author: Javier Lopez-Calderon
% Center for Mind and Brain
% University of California, Davis,
% Davis, CA
% 2009
%b8d3721ed219e65100184c6b95db209bb8d3721ed219e65100184c6... |
96af1f0858f5640bc3a7f4ece5a02b910e3842409ab5474970636a8beb3d480a | MATLAB | 1,537 | 37 | function h_mask = significance_FDR_corrected(p_values, alpha_level)
% Indicates which null hypothesis are rejected based on the matrix of p
% values p_values, with the FDR bound alpha_level in [0,1].
% NaN values in the matrix p_values are ignored (they are not considered as
% hypotheses).
%
% Reference: Genove... |
aecd82fe2b4bfc64d2e46af6bca1cc8389de6fcea73cd53b7018055baeb0e63e | MATLAB | 1,538 | 52 | function GenerateFrames(self, varargin)
%GENERATEFRAMES Generates spatial/temporal frames
% GENERATEFRAMES(SELF) generates frames for streams and cameras specified
% in the config file
%
% GENERATEFRAMES(..., 'PARALLELIZE', TRUE) parallelizes the process (by
% default, no parallelization is used)
p = inputPar... |
2e782f10982245149d3cbcee96eb187bd8510f0df7189b9312f93c593fb1bba8 | MATLAB | 1,540 | 68 | % CALCULATEMVC - CALCULATE THE MAXIMUM VOLUNTARY CONTRACTION
%
% [MVCs,MVCs_per_trial] = calculateMVC(subject,toplot,parent,LR)
%
% MVCtype = 1 -> sensors 1-4
%
% LR = 0 regular
% = 1 Left
% = 2 Right
function [MVCs,MVCs_per_trial] = calculateMVC(subject,toplot,parent,LR)
MVCtype = 1;
if nargin... |
c1276a500ce42cede1d47960ce6b35526daa55777b261d8a36a8800587c21c0c | MATLAB | 1,540 | 48 | function plot_histograms(parameter_set,subplot1,subplot2,row,color,Label,parameters_to_plot,subplot,FS1)
% This function plots hisotgrams of parameter locations
paramnames= {
'h_{e}^{rest}' ,'h_{i}^{rest}','N_{ee}^{\beta}','N_{ei}^{\beta}','N_{ie}^{\beta}','N_{ii}^{\beta}','\Gamma_e',...
'\Gamma_i','\gamma_e','... |
5da22198bcd634e8b940bb6956a253173109b8616a2d38908358fc70699c0c3e | MATLAB | 1,544 | 50 | function model = qtip_pipe_SDPdc(data,btensors,mask,nvox,ind,parallel,cvxsolver)
% function model = qtip_pipe_SDPdc()
%
% reshape data and retain voxels within the mask
siz = size(data);
data = reshape(data, prod(siz(1:3)), siz(4))';
mask = reshape(mask, prod(siz(1:3)),1)';
si = find((mask>0).*(~all(data==0,1)... |
035336342e1785853e7f2dcdff325e3220b0b872b405e3d405e3d34ea79b7326 | MATLAB | 1,545 | 75 | function RunAMDiscrimination
clear all
close all
clc
Path = '/Volumes/JUSTIN EXHD/PROJECTS/AM Discrimination/Data/';
%-NH-%
NH = [Path 'NH/'];
nh = getfiles(NH);
subplot(1,2,1)
plotdata(nh,'NH')
%-HL-%
HL = [Path 'HL/'];
hl = getfiles(HL);
figure(1)
subplot(1,2,2)
plotdata(hl,'HL')
%---Local... |
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