sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
1210dd850b8c159e8a5159051859f46c5da9ed292a602227d85ec73840dd15a4 | MATLAB | 2,420 | 51 | %% WRAPPER SCRIPT FOR AUTOMATED SEGMENTATION OF SYNAPSES FROM MULTI-EXR IMAGES %%
% Image processing up to this point was: background subtraction, median
% filtering, and automated thresholding in ImageJ
% Last modified 6/13/22
% Note: this script has not been updated or maintained, but has been
% provided in ... |
1212a91db21e572e711a5eadd197e90060ccd80387a19c9f4d7e8a9b468d8ec5 | MATLAB | 2,420 | 76 | function [h, p, stat] = ttest_clustercorr(dat1, dat2)
% wrapper around fieldtrip's cluster-based permutation test on a
% timecourse, behaves similarly to matlab's ttest
% input: nsubjects x time
addpath('~/Documents/fieldtrip'); ft_defaults;
% ============================================= %
% RESHAPE DATA
% =========... |
4b4b7dc5ef8db883b1d6b027f96a2a59867615aa460c243fdf32600b2168cb9c | MATLAB | 2,420 | 70 | function [msmooth, Vsmooth, loglik, VVsmooth, m0smooth, V0smooth, VV0smooth] = ...
ldsInfer(y, A, C, Q, R, init_mu, init_V, varargin)
% Kalman/RTS smoother.
% Input/ output is same as for kalmanFilter
% For learning with EM, we also need to compute
% VVsmooth(:,:,t) = Cov[Z(t+1), Z(t) | y(1:T)] t=1:T-1
% We follow Ma... |
50f4c7ae8bc9d2fecdc1d2feb156a609cd7e02ae1135556b1700cd5e92a8383b | MATLAB | 2,420 | 91 | function setviewpoint(ax, coordsys, viewpoint)
% SETVIEWPOINT changes the viewpoint for a 3D image that contains data in a known coordinate system
%
% Use as
% setviewport(ax, coordsys, viewpoint)
%
% For example
% setviewport(gca, 'mni', 'left')
%
% See alo FT_PREPARE_LAYOUT>getorthoviewpos, COORDSYS2LABEL
if is... |
6cf9915654f1f01da71870a01e83ad6db25b5ff7d7f63da400995a695719b992 | MATLAB | 2,420 | 58 | %% Select the current procotol
% (Note: a Brainstorm folder already exists for this subject)
% Get the protocol index
iProtocol = bst_get('Protocol', ProtocolName);
if isempty(iProtocol)
error(['Unknown protocol: ' ProtocolName]);
end
gui_brainstorm('SetCurrentProtocol', iProtocol);
[sSubject, iSubject] = bst_get(... |
4c00025ad7507f9f646760f2f3f9c2f4e358249e79b983ef8a1413c5f9bd2f10 | MATLAB | 2,421 | 75 | % Runs various limited-memory solvers on 2D rosenbrock function for 25
% function evaluations
maxFunEvals = 25;
fprintf('Result after %d evaluations of limited-memory solvers on 2D rosenbrock:\n',maxFunEvals);
fprintf('---------------------------------------\n');
fprintf('x1 = %.4f, x2 = %.4f (starting point)\n',0,0)... |
3bb727e957e977f59055b634674dbdf03d3ef1836cb2e5aec7fae797a856a3dc | MATLAB | 2,422 | 63 | %% S3 Fig: To plot time course after block averaging for each condition over all subjects
clear all
clc
load incongruent_allsub_2probe_final.mat
load congruent_allsub_2probe_final.mat
load incongruent_allsub_2probe_final_hbr.mat
load congruent_allsub_2probe_final_hbr.mat
% Delete the following subjects due to noise ac... |
60b213bf23e1d56ccc7f35ba4df77f89abd9accf8ab0541802b2cd23339f95cb | MATLAB | 2,422 | 101 | function hout=suptitle(str)
%SUPTITLE puts a title above all subplots.
%
% SUPTITLE('text') adds text to the top of the figure
% above all subplots (a "super title"). Use this function
% after all subplot commands.
%
% SUPTITLE is a helper function for yeastdemo.
% Copyright 2003-2010 The MathWorks, Inc.
% Warni... |
9bbe725d268e8370fb7e36a52e0f7caaecc6d4cf92da4d72b7a77999c183fca2 | MATLAB | 2,423 | 85 | function [synData,synLabels] = generate_synthetic_set(data,labels,varargin)
%
% AUTHORSHIP
% Math Lead & Primary Developer: Connor Meehan <connor.gw.meehan@gmail.com>
% Bioinformatics Lead: Wayne Moore <wmoore@stanford.edu>
% Provided by the Herzenberg Lab at Stanford University
% License: BSD 3 clause
WAR... |
2bc916f7fd1ece8ef89403c045d66ebb57cc4b291ad6c463f6511642c440e006 | MATLAB | 2,425 | 55 | qq=1; %sheet number
[Familiar_object_exploration_start]=xlsread('File.xlsx',qq,'C:C');% Start time point of object exploration period
[Familiar_object_exploration_end]=xlsread('File.xlsx',qq,'D:D');% End time point of object exploration period
[x]=xlsread('File.xlsx',qq,'A:A');% Time
[y]=xlsread('File.xlsx',qq,'... |
cd8d2b3c01739ce93297fd379bf60a232c900a8cf4aa4a078adec1e1746b15ae | MATLAB | 2,426 | 80 | clear
figure
set(gcf,'color','w');
set(gcf, 'Position', [230,430,200,400])
ellipse_ratio = zeros(1,2);
ellipse_angle = zeros(1,2);
semimajor_axis = zeros(1,2);
semiminor_axis = zeros(1,2);
for line = 1:2
subplot(2,1,line)
if line == 1 %R4d
load('ER4d_list.mat')
load ellipse_data_ER... |
54faeae99fb0c1cb3e861121bae9c8c1c3def673c4a79ba441c582de1806f963 | MATLAB | 2,427 | 79 | % Companion function to pca.
%
% Use pca to retrieve the principal components U and the mean mu from a
% set fo vectors X1 via [U,mu,vars] = pca(X1). Then given a new
% vector x, use y = pca_apply( x, U, mu, vars, k ) to get the first k
% coefficients of x in the space spanned by the columns of U. See pca for
% genera... |
d0b2a7d818ae66a8974b30427be9e4c389e169bf45a3bfd8e18efafbd51355e8 | MATLAB | 2,427 | 71 | function [s,baseused] = structoverlay(sbase,sover,varargin)
% [s,baseused] = structoverlay(sbase,sover,varargin)
% Overlay 'leaf nodes' of sover onto sbase
%
% sbase: scalar base struct
% sover: scalar overlay struct
%
% s: scalar struct, result of overlay
% baseused: cellstr of 'paths' specifying fields where sbase va... |
f421921364cc1af5ddb65f37bde2e631255f130788e15d3f72d07479039fae7d | MATLAB | 2,427 | 98 | % This function runs the Normalize substraction to
% the functional data series (+ high pass filtering)
% Author: Milena Capiglioni, University of Bern
% Contact: milena.capiglioni@extern.insel.ch
% Last update: Nov.2023
% Feel free to use the software and report any bugs!
% If you use/modify this code for your futur... |
fe64df25703bf0bba0179ed15cbf0cbf778ab0cf01e6e44a92c29eb9f36b9e80 | MATLAB | 2,427 | 58 | % This script plots mesh cross-sections and NIfTI data when availble
%;
% Copyright SNM/WAW 2018-2023
%
addpath('../engines/graphics');
VT = VT1;
f = figure('WindowState','maximized');
%% below is XY-code
y = Y(1);
% Display NIFTI slice
I = round(y/d1d2d3(2) + N1N2N3(2)/2);
S = squeeze(VT1(end:-1:1, I, :))'; ... |
26b87beff872fff5c7bd23db8f93870f4c47f32630b16b3f24871db81766a4b2 | MATLAB | 2,428 | 70 | addpath('../engines/bem_fmm_engine/');
addpath('../engines/graphics/')
load(fullfile(model_path,strcat(patno,'_',model_name,'_NIfTIOverlap.mat')));
%% Dipole location in mm
dip_center_pos = (strdipolePplus + strdipolePminus)/2;
X = dip_center_pos(1)*1e3;
Y = dip_center_pos(2)*1e3;
Z = dip_center_pos(3)*1e3;
%% Calcul... |
b7d864b2ea81489ca1b24e8ad4822215c09a33f1d646ed5385554828425c8aeb | MATLAB | 2,428 | 76 | function h5save(filepath, X, dset, varargin)
%H5SAVE Create and save a variable to an HDF5 file.
% Usage:
% h5save(filepath, X)
% h5save(filepath, X, dset)
%
% Args:
% filepath: path to HDF5 file
% X: variable to save
% dset: name or path to dataset (optional if variable name can be determined by inputname)
... |
cda8561e5a97e7d65dd904ee2e3f43f5027392bbe4c48fd47adb44ad3fb14faa | MATLAB | 2,428 | 81 | %% Generates the figure 4d
%% Requires set:
% - fn_timing
% - res_path
% - mapper_name
% - CHANGE_POINTS
workspace = getenv('WORKSPACE');
fn_timing = [workspace, '/data/cme/timing.csv'];
res_path = [workspace, '/results/cme/ch10_mappers_cmev3_disp.json'];
mapper_name='BDLMapper_12_30_60';
CHANGE_POINTS = 10;
% Get th... |
5896a49f414bab21fc77ad2e6d2a3c49323ffa6f8036fad777494db4549bdd20 | MATLAB | 2,429 | 57 | % SVD_forMSI.m
% Sarah West
% 8/6/20
% Runs SVD on all the data from a given animal. Must be done with MSI or everything will die.
% For each mouse, loads the filtered and blood vessel regressed data, concatenates it all
% together, runs SVD, then saves the outputs.
clear all;
n_compressions=200;
pixels=256; %size of... |
a987836b9d73f69c949e2735e230e8e6af7481d5cd17ab0cc61cbbb8c0b3a484 | MATLAB | 2,429 | 96 | %% Interpolate some data using a joint Gaussian
% Based on p140 of "Introduction to Bayesian scientific computation"
% by Calvetti and Somersalo
clear all
setSeed(1);
D = 150;
Nobs = 10;
xs = linspace(0, 1, D);
perm = randperm(D);
obsNdx = perm(1:Nobs);
hidNdx = setdiff(1:D, obsNdx);
% Noisy observations of the x v... |
03460ab8facb9b7d428b5b56a9a8e963de9c22f7575ded907978c8211e83ed46 | MATLAB | 2,430 | 69 | function [y,iflaw]=dopnoise(N,Fs,f0,d,v,t0,c);
%DOPNOISE Complex noisy doppler signal.
% [Y,IFLAW]=DOPNOISE(N,FS,F0,D,V,T0,C) generates a complex
% noisy doppler signal, normalized so as to be of unit energy.
%
% N : number of points.
% FS : sampling frequency (in Hertz).
% F0 : target frequency (in Hertz).... |
44b240230e0b6aad6920e26b31cfc404999220982b1e5a23f528f1210dfff86d | MATLAB | 2,431 | 74 | function [r2, rmse] = rsquare(y,f,varargin)
% Compute coefficient of determination of data fit model and RMSE
%
% [r2 rmse] = rsquare(y,f)
% [r2 rmse] = rsquare(y,f,c)
%
% RSQUARE computes the coefficient of determination (R-square) value from
% actual data Y and model data F. The code uses a general version of ... |
3b6402e8914eedb3f6ace95dd7eb8041a6301909108b5db41bf9e8f221d82ea6 | MATLAB | 2,432 | 40 | clear r_other_asbl_int_on r_other_asbl_int_off r_out_asbl_int_on r_out_asbl_int_off
[traces] = extract_variables ('traces',[],resultsPath, 'all', [],conditionType,conditionValue);
[pyr_id,int_id] = extract_variables ('nCells',[],resultsPath, 'pyr', 'int',conditionType,conditionValue);
[si_img] = extract_variables ('s... |
528bdfbf4907623b17f6617df26549a6ee99d4a53a8eaf5b8d4ea4148ebc30bc | MATLAB | 2,433 | 91 | function spkDat = SplitAll(spkDat, varargin)
Fs = spkDat.Fs;
wvFs = Fs * spkDat.upsample;
clustList = setdiff(unique(spkDat.id), 0);
[wL, nChan, ~] = size(spkDat.waves);
pk = spkDat.peakLoc;
wP = spkDat.wavePad;
wL = wL - 2*wP;
win = 1000 * [1 - pk wL - pk] / wvFs;
chanList = 1:nChan;
subtractMean = true;
method = 'is... |
db253ed421942465f7056ff0e9dad5ea07bcec20905451f0274fa863a5b8cf13 | MATLAB | 2,434 | 122 | %
% Test Helmholtz particle FMMs in R^3
%
zk = complex(1.1);
N = maxNumCompThreads
nsource = 2000;
source = zeros(3,nsource);
idist=1;
if( idist == 1 ),
theta=rand(1,nsource)*pi;
phi=rand(1,nsource)*2*pi;
source(1,:)=.5*cos(phi).*sin(theta);
source(2,:)=.5*sin(phi).*sin(theta);
source(3,:)=.5*cos(theta);
end
if... |
f870bb893667dbde2ccdad2d97703e36a5e195bcfc44f767c626f4dbd34fb6dc | MATLAB | 2,434 | 44 | classdef sourceIntensityDistribution
% sourceIntensityDistribution Summary of this class goes here
% Detailed explanation goes here
properties
radialDistr (1,:) double {mustBe012OrNaNOrNonnegativeArray} = NaN % Radial near or far field distribution - 0: Top-hat, 1: Gaussian, 2: Cosine (Lambertian), Array... |
a6c1865bcdbca3b59019b9d67425cf7ab46315a571fd936ec3d13ea241afabdf | MATLAB | 2,435 | 87 | function [badChannels,resMat] = detectBadChannels(cfg,task)
thr = cfg.bchthr;
sections = cfg.sections;
dataset = cfg.dataset;
if strcmp(task, 'Rest')
sample_epochs = cfg.epochs;
else
disp('Non-Rest');
end
%import raw data
cfg.dataset = cfg.dataset; %
cfg.channel = {'MEG'};
sens... |
d58b19ec40aaee11d45312a35917ba8da966dd8a0dd99bc4ee1b212e29bfb848 | MATLAB | 2,435 | 95 | function [VarStruct, StatOpt, IsMAT]=w_uiLoadMat(varargin)
if nargin==0
PDir=pwd;
elseif nargin==1
PDir=varargin{1};
else
error('Invalid Input');
end
if exist(PDir, 'file')==2
PDir=fileparts(PDir);
elseif exist(PDir, 'dir')==7
PDir=PDir;
else
PDir=pwd;
end
VarStruct=[];
StatOpt=[];
[File, Pat... |
07777af42ee58f799773cb3eb2742852ab77ab657e9cadab77788aa78fe24067 | MATLAB | 2,436 | 66 | function data = loadHastieMixtureData()
% Load Hastie mixture data from
% http://www-stat.stanford.edu/~tibs/ElemStatLearn/datasets/mixture.example.data
% http://www-stat.stanford.edu/~tibs/ElemStatLearn/datasets/mixture.example.info
%
%% Data
% Data is a struct with the following fields:
% x - 200 x 2 m... |
ca927b1515c20c903321d6d2046e77790e20c5ac5629f7ac83ee9f15b47db4a4 | MATLAB | 2,436 | 83 | % plot_Fig6d
% Plot leverage of Min activity on behavior
%% Load data
medA = load(fullfile(saveLoc, 'for_plots_mediation_norm_to_se'));
%% Plot settings
mediatedDimsA = [3 11 27]; % MinC, MinI, Tin ('for_plots_mediation_norm_to_se')
rows = 1; colms = 2;
sFont = 6;
xLims = [0.2 0.55];
yLimCho = [-3 ... |
0d14f37e39b89490ba870d5353e2a0edc0929b9698b31eb7c41ddef4faade715 | MATLAB | 2,437 | 78 | function G = filterGauss( dims, mu, C, show )
% n-dimensional Gaussian filter.
%
% Creates an image of a Gaussian with arbitrary covariance matrix. The
% dimensionality and size of the filter is determined by dims (eg dims=[10
% 10] creates a 2D filter of size 10x10). If mu==[], it is calculated to be
% the center of t... |
f115961c960fef8be5a5e8cea73fb03e0be90ff686e06d7e4c1d611cd9b83c17 | MATLAB | 2,437 | 102 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% To fit a 2-D gaussian
% m = Image
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% [cx,cy,sx,sy,PeakOD] = Gaussian2D(m,tol);
%
% [sizey sizex] = size(m);
% [x,y] = MeshGrid(1:sizex,1:sizey);
% fit = abs(PeakOD)*(exp(-0.5*(x-cx).^2./(sx^2)-0.5*(y-cy... |
7152d978c7860460a3e9a30ae56f9737334401405c9f89fa50b0b22b72031b44 | MATLAB | 2,438 | 54 | function projectDir = afxFirstlevel(subjects,denoisingOptions,rois,projectName,analyses,incl)
% default analyses
if nargin < 5
analyses = {'fc_wholebrain','fc_network'};
end
% load subjects, options and rois if necassary
if ischar(subjects), load(subjects); end
if ischar(d... |
ccc1f730014b4d87ce546f293efbb5e7788e5136261d38adb2455a770146d95d | MATLAB | 2,438 | 101 | % theta = choose_orientations2(x,y,phi,wtheta,wphi)
%
% we will set the orientation to theta_t = phi_t + s_t * pi
% we want to choose s_t to minimize
% \sum_t cost(s_t|s_{t-1})
% cost(s_t|s_{t-1}) = [wtheta_t*d(\theta_t,\theta_{t-1}) +
% wphi(||v_t||^2)*d(\theta_t,angle(v_t))]
%
% we will find the ... |
def8618ce26eb1c74dadb15abc12b9e9bb7ea0854f6266b9c2fe7f00ea6b77a9 | MATLAB | 2,438 | 52 | %% 功率谱密度 | power spectral density
%% 非参数方法-周期图法 | Periodogram
% 直接调用bandpower(X, fs, [f_low, f_high])完成功率谱估计和相对average band power特征提取
% 功率谱使用默认的modified periodogram函数估计
% X: single channel EEG signal (either a row vector or a column vector)
% opts.fs: sampling frequency 信号采样率
% opts.f_low: freqrange — Frequency range f... |
5809be253f56522ada08b62bd7351655f9fa2989dc284d7755a4a5014780e00a | MATLAB | 2,439 | 80 | classdef Singleton < handle
properties (Constant)
instances = containers.Map;
end
properties
name
end
methods
function obj = Singleton(name, varargin)
% Create a new instance or return an existing instance with the same name.
... |
e93e28a95f5f61de685f137e2084f439889f4a848360a4af6b80107d8ad06a90 | MATLAB | 2,440 | 123 | function cls = cluster_stata(carta,elec_adj,n)
%
% cluster de significancia en 3 dimenciones siendo
%
%
% en construccion
% v.0.0.1
% P.Billeke
dm = size(carta,3);
el = size(carta,1);
if dm == 1
els = size(carta,1);
for ad = 1:length(elec_adj)
rcarta = carta(elec_adj{ad},:);
paso = bwlabel(rc... |
3e3d1e742c430d19c1e5d79ca163b550577cb80a18748a6ee0e5a5fa602c036c | MATLAB | 2,441 | 125 | % this function reads raw data and pulls out metadata from them
% such as temperature and pH
% and saves it to a .metadata file with spikes
function cacheTemperature(exp_name)
spikesfolder = getpref('crabsort','store_spikes_here');
if nargin == 0
% do it for all of them
allexps = dir(spikesfolder);
for i = lengt... |
77cc8e7570f2f34d7bb9e1a2a7e50e94629a74f9b69b9e46dd2f85e2e1cfe770 | MATLAB | 2,441 | 90 | %% choose session
datRoot = '/Volumes/LaCie/Farries recordings/';
%datRoot = '/Volumes/Elements/';
%srvRoot = '/Volumes/Recordings/Michael/';
rat = 'IM1261';
sesList = dir([datRoot rat '/20*']);
sesList = arrayfun(@(x) x.name, sesList, 'UniformOutput', false)
%sesList2 = dir([srvRoot rat '/20*']);
%sesList2 = arrayfu... |
e84493fe863f25c0e6716217fe8da5f003777919ed46ed4c6ddde14d3ae7d3bd | MATLAB | 2,441 | 78 | function EEG = InsertSaccadeTriggersIntoEEG(EEG, behDataFolder, minSaccSize, blinksToo)
% call InsertSaccadesAsTriggers without having to do entire trioEEGLoad
% script. it will insert them right into the EEG structure
%
if ~exist('minSaccSize','var') || isempty(minSaccSize)
minSaccSize = 1 / .0203; % size of min... |
ff81e33d31346c355f4a1358cd474d1e502b0ccd608b4e15c4941260eda2a9a8 | MATLAB | 2,441 | 51 | classdef CBIG_VK2019_unit_test < matlab.unittest.TestCase
% Written by Valeria Kebets and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
methods (Test)
function test_example(testCase)
% create output folder
current_dir = fileparts(mf... |
3b380feb3e54166894261b12dd6bba569f4b03ac9de41be49bb16c43c30dec4d | MATLAB | 2,442 | 105 | % 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
% the Free Software Foundation; either version 2 of the License, or
% (at your option) any later version.
%
% This program is distributed in the hope that it will be useful,... |
651d7d66fbf5ccb0a2c4705f5dadae56c31d28b84deec28727a6fd77e43d5ccb | MATLAB | 2,442 | 101 | [t,TIN, TOUT,EC,EI,CHOICE,RT,COH,SESSION] = get_and_prep_data();
%%
e = EC-EI;
tind = t>=0.1 & t<=0.4;
ee = nanmean(e(:,tind),2);
%
p = publish_plot(2,1);
p.next();
curva_media(CHOICE, COH, ee<nanmedian(ee), 2);
hold all
curva_media(CHOICE, COH, ee>nanmedian(ee), 2);
hl = legend('low contra-ipsi Min', 'high contr... |
9dd6ccb2c5cd90f23bc929d496793ce8dcc8c2a63ddf1fd4a9d6dc4366e6ebe6 | MATLAB | 2,442 | 99 | % [newX, snr1, snr2, Mx, My] = adjustCorr2s(X, Cx, Y, Cxy, MODE, p)
%
% Linearly adjust variables in X to have correlation Cx, and cross-correlation Cxy.
% Rows of X, Y, and newX are samples of (random) row-vectors, such that:
% 1: newX = X * Mx + Y * My
% 2: newX' * newX = Cx
% 3: newX' * Y = Cxy
%
% MODE is... |
2c8eb6cb0a83715e2d08bfef429ee21f61de7c41c78cfb2b5691785a09220984 | MATLAB | 2,444 | 73 | function [XL,XR] = stereo_triangulation(xL,xR,om,T,fc_left,cc_left,kc_left,alpha_c_left,fc_right,cc_right,kc_right,alpha_c_right),
% [XL,XR] = stereo_triangulation(xL,xR,om,T,fc_left,cc_left,kc_left,alpha_c_left,fc_right,cc_right,kc_right,alpha_c_right),
%
% Function that computes the position of a set on N points giv... |
ecc3a093ade1dcf121322767f1569203eb2486929f87590db6aea92ee982959f | MATLAB | 2,444 | 74 | % Author: Birgit Nierula
% nierula@cbs.mpg.de
function [EEGorig, EEG, cfg] = eeg_prepro_loop7_1_allBlocks(subject, veog_channames, heog_channames)
%% loop 7: check ICA components with SASICA
% define variables
subject_id = sprintf('sub-%03i', subject);
analysis_path = [getenv('ANADIR') subject_id '/eeg/prepro/'];
... |
1dac53cd37e4b468958d8aa243b5c958e0872c6921f4c85139e8e07e9c56e808 | MATLAB | 2,445 | 79 |
%% ---------------------------- Plot Linear -----------------------------
linear_fig = figure();
plot(rr, intersections, 'linewidth', 2 );
grid;
xlabel('r, \mum', 'interpreter','Tex')
ylabel('Intersections');
print(linear_fig, ['results/' name '/sholl_linear_' name '.png'], '-dpng');
savefig(linear_fi... |
6cb2eff62ec47a79ca8fda03a7bfb6b7a5c994879c568859df7b9fad733f552a | MATLAB | 2,445 | 102 | function [S,P] = simRace2DDM(t, varargin)
% returns stucture S with fields
% .decTime (decision timer)
% .choice (0 or 1)
% .dvTin (dv of the positive choice)
% test
% t = (0:0.001:1); [X,P] = simRace2DDM(t);
% simRace2DDM(t,'seed',P.seed);
% varargin
pSet = inputParser;
addParameter(pSet,'coh',0); % -1..1 scale
ad... |
8321b7387a6b3854c8ed299360b2ea687d84eeb5443b784c3043bfead50d17a7 | MATLAB | 2,445 | 72 | function [X,X1,X2] = VBA_Fourier2DBF(L1,L2,N,dct)
% creates 2D Fourier basis functions
% function X = create2dbf(g1,g2,N)
% This function evaluates Fourier basis function sets, evaluated on a 2D
% domain defined by 2 grids g1 and g2. Let z(x) be a 1D-field of length L.
% It can be decomposition using the Following Four... |
93a38e0552add6d055cdfabe432c6ec1a8e4cbe3189de0563573c7aa2e43a39b | MATLAB | 2,445 | 118 |
% Z -> Xj -> Yj
% Z is mixture node
% Xj is binary tag
% Yj is response of tag detector
% We generate some synthetic correlated binary data
% consisting of 10s and 01s
setSeed(0);
D = 4; % num bits/ nodes
mixWeights = normalize(ones(1,D));
N2 = 20;
X1 = repmat([1 0 0 1], N2, 1);
X2 = repmat([0 1 1 0], N2, 1);
X = [X... |
a07a14088bb03da0ddf86abfb248c53cc368ba0fe1513a726de0a00a5a3b8a0f | MATLAB | 2,445 | 71 | function [records,party,senators,bills,nmissedVotes] = senateDataLoad()
% Senate Voting data from 109th Congress 2004-2006
%
% records
% 542-by-100 matrix of -1, 0, +1 representing the voting records
% of 100 Senators on 542 bills.
%
% party
% the party to which each senator is affiliat... |
a6f9ec09d41778b323b4733edafe52d23a969971fd9844dd7362713e7324438c | MATLAB | 2,445 | 62 | % This script shows how to process and manipulate loaded datasources and
% how to call dataspace module-functions on them.
%
% The same exact procedures apply to programatically loaded datasources (not involving the GUI).
%
%
%
%<PRE>
% This file is part of dspace-core.
%
... |
f8e45f7428fdca5d5b3b514379d18c36224ec5338f8249d803494ce5e9f1a014 | MATLAB | 2,445 | 83 | function [closestPtBef,closestPtAft,idxB] = findBeforeAfter(A,B,type)
% findBeforeAfter This function finds the closest value of B to each value of A.
%
% Inputs:
% A: A matrix of values
% B: A matrix of reference values
% Type: Type of points we want to return (3 options)
% 'both' = find the closest p... |
0b2ff7598389d423806c3075e5d7adb6321ca8fbcf06bb30c39105955d7b23b6 | MATLAB | 2,446 | 50 | function CBIG_preproc_unit_tests_cmp_clusters( your_clusters, cmp_dir )
% CBIG_preproc_unit_tests_cmp_clusters( your_clusters, cmp_dir )
%
% Compare your 100 subjects clustering result with the ground-truth unit
% test result.
%
% Inputs:
% - your_clusters
% Your 17 network clustering result by running the s... |
cd3b17d1d6b46bd0ac1e5320868821832c3f144f586cd2fb1b759fed5927ad1f | MATLAB | 2,446 | 59 | %%
% =================== BEHAVIORAL ANALYSIS: MIXED MODEL ====================
% Mixed model to study the impact of run and instruction on the error rate.
%%
clc; clear all; close all
responses_description = ...
readtable('F:\SEM_mri\MRI\Behavioral analysis\responses_description.xls');
qi_data = readta... |
273a8547507967062fdd1c7bea55e808094236b62980a2c0f444e3bfa8fefa6c | MATLAB | 2,447 | 106 | function [myfft, freq, handle] = fft_plot_scnlab(dat, TR, varargin)
% :Usage:
% ::
%
% [myfft, freq, handle] = fft_plot_scnlab(dat, TR, varargin)
%
% :Inputs:
%
% **dat:**
% is a data vector (column)
%
% **TR:**
% is the sampling rate of the data you put in
% in seconds / sample, or 1/Hz
%... |
a9233999be9217303eb6c5b90e10767c6465dcc279036888315182b3986499b8 | MATLAB | 2,447 | 86 | % Renamed from calc_Fig4a_S9
%% Decoder performace: fixed time window
%% weights from 450ms applied to all time points for
%% 1. all neurons,
%% 2. only Tin neurons,
%% 3. no Tin neurons,
%% 4. no Tin or Min neurons
load(fullfile(saveLoc, 'par_sess'))
%% Aligned to motion onset
% Take out the... |
b56e0d2ccb439e38b594af364c5e853e17d5d89d5932876e671dd2ec62816ec2 | MATLAB | 2,447 | 69 | function [Kernel, features, D] = build_kernels_PCAstates(datadir, hmmdir, kerneldir, HMM_name, Fn, Kn)
% [Kernel, features, D] = build_kernels_PCAstates(datadir, hmmdir, kerneldir, HMM_name, Fn, Kn)
%
% build kernels from HMMs using PCA-reduced state parameters and transition
% probabilities/initial state probabilitie... |
3a869f9aecd6feb6966a6519eb8599919d8527969f690f26a0eef8a1bd578481 | MATLAB | 2,448 | 93 | classdef DataAugMontage < handle
properties
idx % [nx3] (m,f,t)
ims % [n imnr imnc 3]
locs % [n x npts x d x ntgt].
mask % [n x imnr x nc]
isMA
name = '' % character description
maskrgb = [0 1 1];
end
methods
function obj = DataAugMontage
end
function init(obj,ma... |
9c547483058d00f542995b1f038881013e20d6864032cc2a4b08b1b2aec12571 | MATLAB | 2,448 | 66 | clear tilling_queue
kk = 0;
for ii = 1:size(read_file_name,1)
for jj = 1:size(read_file_name,2)
for ll = 1:size(read_file_name,4)
kk = kk+1;
tilling_queue(kk).channel = ll;
tilling_queue(kk).side = iamge_set_folder_detail(ii,jj,ll);
tilling_queue(k... |
bb476c3fdf9af8e16756bcb00dddb595aabed9302cec664823b8e337fcf9e56f | MATLAB | 2,448 | 81 | function l = filelist(directory, filemask, recursive)
% Return a list of all files of the specified type in a directory structure
% * .svn files and directories are ignored
% * directories are not included in the list even for *.* - see dirs()
%
%% Inputs [default]
% directory [pwd()] the top level directory
% file... |
82a118d411c3505fd68383a203381189dcc3358021d5e29dcd9eb9c0856026c1 | MATLAB | 2,449 | 77 | function [CIJtree,CIJclus] = my_backbone_wu(CIJ,avgdeg)
%This is a modification of the original Brain Connectivity Toolbox function
%to allow the computation of only minimum spanning trees with an average
%degree of 0
%BACKBONE_WU Backbone
%
% [CIJtree,CIJclus] = backbone_wu(CIJ,avgdeg)
%
% The network back... |
1e2c8be2c04f55a0c57b6a1ae0fde82dd38c84f54154304c308399a5de4ccdbc | MATLAB | 2,450 | 67 | function CBIG_preproc_DVARS_FDRMS_Correlation(DVARS_file,FDRMS_file,output_dir_name)
%CBIG_preproc_DVARS_FDRMS_Correlation(DVARS_file,FDRMS_file,output_dir_name)
%
% This function is used to compute the correlation between DVARS and FDRMS.
% This correlation shows whether DVARS and FDRMS are able to caputure
% ... |
6a90b3462dda6a6a4b49fdff0627cdc17b438fae65fc6e21b51d43974884027f | MATLAB | 2,450 | 76 | function errorbarT(h,w,t,xtype)
%errorbarT Adjust the width and thickness of errorbars
% errorbarT(H,W,T) adjust the width of error bars with handle H.
% The input W is given in the units of the current x-axis.
% The input T is the 'LineWidth' of the errorbar
% errorbarT(H,W,T, 'RATIO') adjust the width o... |
b4c6e69e40776a414d885506afdbcc4f8f42e3476c0378d237545f609be249bf | MATLAB | 2,450 | 81 | function tocStatus( id, fracDone )
% Used to display the progress of a long process.
%
% For more information see ticStatus.
%
% USAGE
% tocStatus( id, fracDone )
%
% INPUTS
% id - unique id of progress indicator
% fracDone - value in (0,1] indicating percent operation completed
%
% OUTPUTS
%
% EXAMPLE
%... |
7a250297e62ca35aa0d21eed2bd3e70ae9aec08ca66d18765b689c76a95ab1d1 | MATLAB | 2,451 | 68 | function X = thomson_problem(n, d)
% Simple attempt at computing n well distributed points on a sphere in R^d.
%
% This is an example of how Manopt can approximate the gradient and even
% the Hessian of a cost function based on finite differences, even if only
% the cost function is specified without its derivati... |
d10f3f5ca9f2ae86ef0322ce602e10316b4b2a3b13d2b8a7fc606a8f331309a9 | MATLAB | 2,451 | 97 | function [no,xo,idx] = myhist(varargin)
% almost the same as hist, except it can take weights
% Parse possible Axes input
i = find(strcmpi(varargin,'weights'));
if ~isempty(i),
weights = varargin{i(end)+1};
varargin([i,i+1]) = [];
end
error(nargchk(1,inf,nargin,'struct'));
[cax,args,nargs] = axescheck(varargin{:})... |
0ae9ec1276d298e907a10191327872ddf57eeb4343ac49b39a5290c742d38c76 | MATLAB | 2,452 | 75 | %% set up paths
JAABAcodedir = '/groups/branson/home/bransonk/behavioranalysis/code/Jdetect/Jdetect';
labelfiles = {
'Y:\Jay\videos\M186hm4dBPN\labeler\labels.lbl'
'Y:\Jay\videos\M187hm4dBPN\labeler\labels.lbl'};
rootdatadir = '/tier2/hantman';
addpath ..;
addpath ../misc;
addpath(fullfile(JAABAcodedir,'filehandl... |
2e9465c442867c087a0731da2f4c5cf3f760ba309b8dcd6bfd3762612ac9b2f1 | MATLAB | 2,452 | 82 | clear srcinfo
ns = 4000;
srcinfo.sources = rand(3,ns);
srcinfo.stoklet = rand(3,ns);
srcinfo.strslet = rand(3,ns);
srcinfo.strsvec = rand(3,ns);
nt = 3999;
targ = rand(3,nt);
eps = 1e-5;
ntests = 2;
ipass = zeros(ntests,1);
errs = zeros(ntests,1);
ntest = 10;
stmp = srcinfo.sources(:,1:ntest);
ttmp = targ(:,1:ntest... |
61dbeabe39c6f7efaa93fd53babcdbd93a95f8613625b7638930bfac7b7d79d6 | MATLAB | 2,452 | 86 | function [source] = fixinside(source, opt)
% FIXINSIDE ensures that the region of interest (which is indicated by the
% field "inside") is consistently defined for source structures and volume
% structures. Furthermore, it solves backward compatibility problems.
%
% Use as
% [source] = fixinside(source, 'logical');
... |
a18e35033043ff4ed0d074222d9f3136d3e088318b349df1d3f1e5823a19a056 | MATLAB | 2,452 | 93 | function newevlist = wlAux_getReconFromWave(oldevlist, label)
% function newevlist = wlAux_getReconFromWave(oldevlist, label)
%
% This function fills in "times", "wave", "mag", "freq", and "phase" in a
% seires of event records by copying a set of signal traces stored in
% "auxwaves" that begin with the specified pref... |
f81550467ea370de1e22b202670a9f16940b083720ba5b92d608f1381531b355 | MATLAB | 2,452 | 62 | %-----------------------------------------------------------------------------------------
% Plot decoding performance for chemical vs. perceived odor identity
%
% Kehl et al. 2024 (DOI:XX)
% Single-Neuron Representations of Odors in the Human Brain
% Figure 4h
% Author: Marcel Kehl
% License: MIT License
%---------... |
1d82e710f2223844835619f0cda9d2b8844e2e5e78631d25d268795c5eb9ba7e | MATLAB | 2,453 | 51 | function [estimate_frequency,complexity] = simpleHjorth(test,Fs)
%% ============================= Inputs =================== %%
% test : is the input vector signal
% Fs : is the sampling freqeuncy used to derive the frequency from Radians
% to Hz.
%% ============================= Outputs ============================ %... |
8468458a29eb0d968519a72a5a5e2015d6f7328421afa7422e2e5368ad2ca57d | MATLAB | 2,453 | 70 | function [Num_Bins,Bin_Edges,Bin_Labels,Bin_Centers,Histogram,Normalized_Histogram,...
Cumulative_Histogram,Normalized_Cumulative_Histogram]=Multi_Histogram(Data,Bin_Range,Bin_Size)
if any(Data==Inf)
warning on
warning('Removing Inf values!')
Data(Data==Inf)=NaN;
end
if an... |
ae00d0b538aa1ae7493572ca8095d461cb5b61ccd0ed3fafcd21ab69b5992d6b | MATLAB | 2,453 | 98 | function [video,n_frames] = tif_to_video(filename,frame_rate)
%
% >>> OPERATION >>>
% Converts series of TIFF files into an AVI video. Uses MPEG-4 compression by default.
%%
% >>> USE >>>
%Select first TIFF file in the folder. The remaining files will be
%automatically found and concatenated
%If not provided, frame r... |
0bb6ddda1641833b811e0bab308f4c0393e86ded9c841c5dd691b8826499b11c | MATLAB | 2,454 | 58 | function sens = undobalancing(sens)
% UNDOBALANCING removes all balancing coefficients from the gradiometer sensor array
%
% This is used in CHANNELPOSITION, FT_PREPARE_LAYOUT, FT_SENSTYPE
while isfield(sens, 'balance') && isfield(sens.balance, 'current') && ~strcmp(sens.balance.current, 'none')
fnames = setdiff(fi... |
1c786016c6b61a20d0c6930c7c6c0aaf380d7abc32d4f65d6a754ab56b4f601b | MATLAB | 2,455 | 89 | function [swf] = read_besa_swf(filename)
% READ_BESA_SWF
%
% Use as
% [swf] = read_besa_swf(filename)
%
% This will return a structure with the header information in
% swf.label cell array with labels
% swf.data data matrix, Nchan X Npnts
% swf.npnt
% swf.tsb
% swf.di
% swf.sb
% Copyright (C) 2... |
265b5fadea882485959791a71bd4bc1cd5219ffd9e923a8a2ffce2046f19c5f9 | MATLAB | 2,455 | 58 | % This script plots mesh cross-sections and NIfTI data when availble
%
% Copyright SNM 2017-2022
addpath('../engines/graphics');
addpath('../engines/bem_fmm_engine');
VT = VT1;
f = figure('WindowState','maximized');
x = X(1);
% Display NIFTI slice
I = round(-x/d1d2d3(1) + N1N2N3(1)/2); % minus here!
S = squ... |
885ddd9855965727a835813d473ca8484ee2d7fa250062eb2c958872a73f4227 | MATLAB | 2,455 | 65 | function sqrtPd = getSqrtPrecon(problem, x, d, storedb, key)
% Applies the square root of the Hessian preconditioner at x along d.
%
% function sqrtPd = getSqrtPrecon(problem, x, d)
% function sqrtPd = getSqrtPrecon(problem, x, d, storedb)
% function sqrtPd = getSqrtPrecon(problem, x, d, storedb, key)
%
% Return... |
898a38c3ac4b3ea6da18e350784a8c65dc08ff7fd243ab580d624790b2d4fd70 | MATLAB | 2,455 | 68 | function im_out = nii2mat(data_path,x1_range,x2_range,x3_range,size_factor,up_thresh)
% this function extracts the img from the NIfTI file and returns the desired
% range and desired rescaled image as a double with no processing or
% interpolation
%
% Input:
% >>> x1_range = range of rows
% >>> x2_range = rang... |
481a3f496c1b83e3602c931a62c43ef659b0045f156dab2b4c2257696c033c8a | MATLAB | 2,456 | 71 | % Author: Birgit Nierula
% nierula@cbs.mpg.de
function [eeg_chans, esg_chans, bipolar_chans] = get_channels(subject_nr, includesEcg, includesEog, study_nr)
if isempty(subject_nr) % subject_number is set to [] for general use
subject_nr = 12; %this is just a dummy-subject number
end
%% returns EEG, ESG and bipol... |
53a8d051f5772fb2f7bded7619d6a22bdc1b527150bc1a737704cc81ed98f100 | MATLAB | 2,456 | 84 | function [meg] = read_ctf_dat(filename)
% READ_CTF_DAT reads MEG data from an ascii format CTF file
%
% meg = read_ctf_dat(filename)
%
% returns a structure with the following fields:
% meg.data Nchans x Ntime
% meg.time 1xNtime in miliseconds
% meg.trigger 1xNtime with trigger values
% meg.... |
990136789201295909e78c6731630e7b8ca4278e059dcbe930767adf61cdd168 | MATLAB | 2,456 | 61 | function [ss,p,pwmd] = dabest3(data,identifiers,p,pwmd,varargin)
%--------------------------------------------------------------------------
% Data inputs have two valid options:
% Option 1:
% data: nx1 vector of values (double, int, etc)
% identifiers: nx1 cell array of labels
% Option 2:
% d... |
aaa631e205651b80b8587302dac3a781a0d3d17a4391f93d193b8f5983cb2a23 | MATLAB | 2,456 | 83 | function demo_excludeData ()
% // VBA toolbox //////////////////////////////////////////////////////////
%
% [posterior, out] = demo_excludeData ()
% Demo of simulation and inversion of a dynamical system that is sampled on
% an irregular grid (not all timepoints are observed)
%
% More generally, this demo shows how to... |
b10b4c152e9929262ef29ede67bd65834fa54d578bdf1208dd08a6dd55cd1b1e | MATLAB | 2,456 | 105 | %% Illustration of some subderivatives of a function at point x0.
%
%%
% This file is from pmtk3.googlecode.com
figure('Color',[1,1,1]);
blueX = [-1 , 0 , 0.75 , 1.15 ,1.3 , 1.8];
blueY = [0.35 , 0.2 , 0.3 , 0.8 ,1.05 , 2 ];
f1 = @(x) 0.4*x; %tangent line
f2 = @(x) 0.7333*x - 0.25; %tangent line... |
b9b0ae0d0429a21f3385e8d4d681f4d20e3b8f06ddd7e91cd9b597a838a473d5 | MATLAB | 2,456 | 86 | function [PL_PET] = PL_PET_atlas(PET_scan,MRI_atlas)
save_imgs = 0;
%% Slices
regions = cell(6,1);
regions{1} = [96 75;96 96;87 96;87 75]; %slice=155
regions{2} = [96 75;96 96;87 96;87 75]; %slice=156
regions{3} = [93 75;93 96;87 96;87 75]; %slice=157
regions{4} = [93 75;93 96;87 96;87 75]; %slice=158
regions{5} = [... |
2368ff6bed4b4c112a9b355ddfe2335c4cf96bd6dd8a368e3de5791a2d6e3254 | MATLAB | 2,457 | 76 | function [c_source_file,c_other_file] = coregister_4d(source_file, target_file, other_file, out_path, com_flag)
% Source and target should be a single volume (3D). Other can be a 4D file
% which will be expanded.
matlabbatch = [];
tag = 0;
%Expand "other" filenames
other_vols=[];
for i=1:length(other_file)
[other_p... |
b3bb3c0dbcee6814e36d40e33733042e4b4f91a193a54594ba6adbf9b881a3eb | MATLAB | 2,457 | 88 | % 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
% the Free Software Foundation; either version 2 of the License, or
% (at your option) any later version.
%
% This program is distributed in the hope that it will be useful,... |
3db65ffb4e85edf16c7d828ed791e542b8b250a5aab040cbc1b6a141ebdd6440 | MATLAB | 2,458 | 57 | % SOFA API - demo script
% Copyright (C) 2012-2013 Acoustics Research Institute - Austrian Academy of Sciences
% Licensed under the EUPL, Version 1.1 or – as soon they will be approved by the European Commission - subsequent versions of the EUPL (the "License")
% You may not use this work except in compliance with the ... |
d5ebfd2c7a4683d8035259e6355285361846bc2784446b2788e69ab85cbc6dbd | MATLAB | 2,458 | 78 | function dat = ft_preproc_medianfilter(dat, order)
% FT_PREPROC_MEDIANFILTER applies a median filter, which smooths the data with a
% boxcar-like kernel, except that it keeps steps in the data. This function requires
% the MATLAB Signal Processing toolbox.
%
% Use as
% [dat] = ft_preproc_medianfilter(dat, order)
% w... |
34ed9274cf6cef2156c42e0ca4c7904b76198127ad0a2fc33f842a467ef04cad | MATLAB | 2,459 | 68 | % Wrapper script to turn GROUP-AVERAGED parcellation files into FreeSurfer annotation
% files.
%
% Assumes ind_parcellation output from Kong2019 CBIG pipeline.
% Written by M. Peterson, Nielsen Brain and Behavior Lab
%To run:
% 1. Claim computing resources using salloc (ex: `salloc --mem-per-cpu 6G --time 2:00:00 -... |
86501c2e6d8f315698952ae02a7ca597d1e38739f3fbdb118a4218df8068bd00 | MATLAB | 2,459 | 88 | % outfilenames = SaveFigLotsOfWays(hfig,basename,[formats])
function outfilenames = SaveFigLotsOfWays(hfig,basename,formats)
if nargin < 3,
formats = {'fig','png','pdf','svg'};
end
[path,basename] = myfileparts(basename);
basename0 = basename;
outfilenames = {};
for iteri = 1:2,
if iteri == 2,
... |
d2a1e44e92cbd65d7301afd1a14c63802c0e7a8dfc25e0b0f3f5785501da85a8 | MATLAB | 2,459 | 123 | function [u,ss,K,v]=PCA_MoG(y,varThresh,verbose)
if ~exist('varThresh','var')
varThresh = 0.95;
end
if ~exist('verbose','var')
verbose = 1;
end
n = size(y,2);
p = size(y,1);
[u,s,v] = svd(y',0);
ss = diag(s);
va = cumsum(ss.^2./sum(ss.^2));
ind = find(va>=varThresh);
K = min(ind);
u = u(:,1:K);
if ~verbos... |
f315eb8adfaadd455f2e194c628c7b094de393ab80fb42cd721477f7d1aad9b0 | MATLAB | 2,459 | 84 | % HIFIE_SPDIAG Extract diagonal using hierarchical interpolative factorization
% for integral equations via sparse apply/solves.
%
% This algorithm computes each diagonal entry by multiplying from the left
% and right by unit coordinate vectors, taking advantage of the sparsity of
% each such op... |
de7e65d73d73367ac0b373104eb0d7be95a41243f1c2af7e1a6e97c6f6daf03b | MATLAB | 2,460 | 118 |
if ~exist('n_ima'),
data_calib_no_read;
end;
check_active_images;
n_col = floor(sqrt(n_ima*nx/ny));
n_row = ceil(n_ima / n_col);
ker2 = 1;
for ii = 1:n_col,
ker2 = conv(ker2,[1/4 1/2 1/4]);
end;
ny2 = length(1:n_col:ny);
nx2 = length(1:n_col:nx);
%II = I_1(1:n_col:end,1:n_col:end);
%[ny2,nx2] = size(I... |
e5a43eea298a8b33f98762eb78833cfac7a3c491c18eb7978f1398ad00bb80f5 | MATLAB | 2,461 | 81 | function [times,id,group] = CCGParameters(varargin)
%CCGParameters - Reformat time series for CCG computation
%
% USAGE
%
% [times,id,group] = CCGParameters(series1,group1,series2,group2,...)
%
% series1... time series (one column) with optional IDs (in the second
% column, such as obtaine... |
e9b149917d917d2a5ab09c87043b9338666cd8c8ae30098d29d4bc7342248094 | MATLAB | 2,461 | 63 | % EXPERIMENTSMANAGER Goes through the input and output directories
% Detailed explanation goes here
%
% First, get the experiment numbers
function [experiments,crops,keypts,registrations,cell_detections] = ExperimentsManager()
loadExperimentParams;
% filename = fullfile(params.INPUTDIR,sprintf('%sround%d_%s.tif',... |
dce6ce62f8b1fbc084d40d91ac29c4b6a8eda77b59b1d58aaa88e0b84ce99b17 | MATLAB | 2,462 | 72 | % PhotoreceptorModelLinWrapper
%
% Purpose:
% Evaluates the fit of a linear model to the response of a photoreceptor.
% Used in optimization routines to find the best-fitting linear model parameters.
%
% Input:
% coef - A vector containing the coefficients of the linear model.
% coef(1) - Scaling factor
... |
40d3c58200755f3ef81d400e173cf0d6d7e429f3436202b10fe3ded840c01051 | MATLAB | 2,463 | 81 | function [A,Wout]=mkfilt_eloreta(L,regu,W);
% makes spatial filter according to eLoreta
% usage A=mkfilt_eloreta(L); or A=mkfilt_eloreta(L,regu);
%
% input L: NxMxP leadfield tensor for N channels, M voxels, and
% P dipole directions. Typically P=3. (If you do MEG for
% a spherical volume cond... |
96bd27def51a03bff37ab00ccfa740d2ed76fa81df730748af240383b03a77c6 | MATLAB | 2,463 | 75 | function [Tmatches, setts] = TrajPlotPars(type,animal)
if type==1% CorrIncorr, All Correct, active stimuli
setts{1} = 1:2;
setts{2} = [1 2 7 8];
setts{3} = 7:8;
setts{4} = [1 2 7 8];
setts{5} = 1:2;
setts{6} = 7:8;
elseif type==2% Cross-modulated
setts{1} = 13:16;
setts{3} = 17:20;... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.