sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
d988a9dcc4be8bed780daff2364899442290ce626a5f48e420d970a90bd26c44 | MATLAB | 1,836 | 44 | function ms = msSelectROIs(ms)
%MSSELECTROIS User interface for selection of ROIs for aligment algorithm.
% The motion correction algorithm (sbxalign.m and fftalign.m) came from Dario Ringash,
% https://scanbox.wordpress.com/2014/03/20/recursive-image-alignment-and-statistics/.
% We suggest using a small ROI ro... |
9dc159283fb62077ddcf07d9741fa9a0540457fe19bceed1e02c2a38dc9b969d | MATLAB | 1,837 | 57 | clear all
supPath = 'C:\Users\Noga\Documents\Vermis Data';
load ('C:\Users\Noga\Documents\Vermis Data\task_info');
req_params.grade = 7;
req_params.cell_type = 'CRB';
req_params.task = 'pursuit_8_dir_75and25';
req_params.ID = 4000:5000;
req_params.num_trials = 20;
req_params.remove_question_marks = 1;
raster_params.... |
eaa9d6d6422a058bf13f549ebfb3b99c18cd7218a4dba5df63156c7e45d6dc2e | MATLAB | 1,837 | 60 | function test_suite = test_bids_query_mrs %#ok<*STOUT>
try % assignment of 'localfunctions' is necessary in Matlab >= 2016
test_functions = localfunctions(); %#ok<*NASGU>
catch % no problem; early Matlab versions can use initTestSuite fine
end
initTestSuite;
end
function test_bids_query_asl_basic_2dmrsi()
... |
87c9f08412e5f94ff9d4cd07a1a081feb69099e8be2c0eeb226dbc9a86fd89ee | MATLAB | 1,839 | 70 | function net = vbhafa_z(Y, Qns, maxdim, nIter, tol, pcaflag)
QnsCell = {Qns};
Ycell = Y;
Y = cell2mat(Y);
nStates = size(Qns, 2);
[p n] = size(Y);
k = maxdim + 1;
approach = 1;
net = struct( ...
'model','variational SAFA', ...
'hparams',struct('mcl',[],'psii',[],'pa',[],'pb',[],...
'alpha',[],'alphaa'... |
9f117264cd74845dde9a868492dd332e313fa205fd46376f6231d397f6e6d1a0 | MATLAB | 1,839 | 83 | function unitTest = Homer3(groupDirs, inputFileFormat, unitTest)
% Syntax:
% unitTest = Homer3(groupDirs, inputFileFormat)
%
% Examples:
%
% Homer3({'.'}, '.snirf')
% Homer3({'.'}, '.nirs')
%
global logger
global cfg
setNamespace('Homer3');
if ~exist('groupDirs','var') || isempty(groupDirs)
... |
bcdeb5192b7fb06e9d5dad12a1349a2d392b2002c5bea74c0aeafa37f4c20cf5 | MATLAB | 1,839 | 53 | % if trials var already filtered out trials by condition/locations, then
% just filter out movieIdx to same criteria.
% for fNIRS only
% For sbj 08 and 10
% trials is already 90 trials, movieIdx has 180 trials.
function [trials,varargout] = keepCorrectTrials_Special(sbjNum,trials,behFN,numClasses,movieIdx)
load(be... |
f63e6d33a3e2e3e851f6d7daebd9b17680a480fc574abde864d74e51e1438606 | MATLAB | 1,839 | 53 | function recX = reconstruct_data(mappedX, mapping)
%RECONSTRUCT_DATA Reconstructs data from low-dimensional data representation
%
% recX = reconstruct_data(mappedX, mapping)
%
% The function tries to reconstruct the original data from the
% low-dimensional representation in mappedX. The function requires the
% origin... |
219b248b128945814c79e4ff73d7427a6edbed3b6de2eb9b4ce4164a0bea9508 | MATLAB | 1,840 | 45 | %% Extracting EEG timing test
%% Open EEGlab
eeglab; % run EEGLAB
% Check if variable EEG_timingtest_video_align exists already. If yes, load it.
if exist([output_dir output_general 'VideoBasedMarkers\EEG_timingtest_video_align.mat']) == 2
load([output_dir output_general 'VideoBasedMarkers\EEG_timingtest_v... |
5065f11400b8d5598cbcb21074899171b22e6c069a92887a754f8415a82ce685 | MATLAB | 1,840 | 60 | function [subj] = rename_group(subj,objtype,old_groupname,new_groupname,varargin)
% Changes the groupname for all objects in a group
%
% [SUBJ] = RENAME_GROUP(SUBJ,OBJTYPE,OLD_GROUPNAME,NEW_GROUPNAME,...)
%
% This goes through all the objects of a specific type, finds those
% with group_name OLD_GROUPNAME, and sets it... |
52d9ed4ee57457bfc5643546e7ce0b7998f7ec08ab7483cd5fdd2a40be0997dd | MATLAB | 1,840 | 70 | function [SF,chpt,estsigma]=automated_step_detection(trace,varargin)
%input arguments
%first: position trace with steps
%second: width of moving median filter (this removes short back and forth
%stepping
%third: step size filter (in a single run all steps below the threshold are
%removed and the step function is ... |
0bfc1555b7fe5a0f0c45e80f472903273e09ea934322ad87c0927a6d25224cb8 | MATLAB | 1,842 | 51 | function [all_artifacts] = corr_artifact_blink_sacc_EKG(cfg)
% unpack cfg
compdat = cfg.compdat; %components data
sigdat = cfg.sigdat; % EEG data
sig_index = cfg.sig_index; nindex = length(sig_index);% number/index of EOG channel
p_thresh = cfg.p_thresh; % pvalue thres .05
r_thresh = cfg.r_thresh; % r value th... |
70b1f1f9bf21de20930c6a50281abc3e34252e4629398a230b546baa9823d35d | MATLAB | 1,842 | 66 | function [data, label] = gmmsamp(mix, n)
%GMMSAMP Sample from a Gaussian mixture distribution.
%
% Description
%
% DATA = GSAMP(MIX, N) generates a sample of size N from a Gaussian
% mixture distribution defined by the MIX data structure. The matrix X
% has N rows in which each row represents a MIX.NIN-dimensional samp... |
620141977193dedbec38e55cc844739029fbb2634446aa43a3697eeb49e53421 | MATLAB | 1,843 | 63 | function [eye, p] = eye_pp(i_sub, p)
% Get subject ID as string
sub_str = num2str(i_sub,'%02i');
% Initialize output variables
eye = [];
% Check if subject has the right number of .asc files (each only has one
% per session)
f1 = dir(fullfile(p.base_dir, 'Nifti', ['sub-' sub_str], 'ses-01', 'eye', '*.asc'));
f2 = di... |
03534660b64bfa5281b9582442cacd5610a3d2b00a992c27908b44492c096692 | MATLAB | 1,845 | 48 | function [sig_cells_sb, areas_sb] = NWB_SB_plotCell_Sternberg(nwbAll,all_units,params)
%NWB_SB_PLOTCELL_STERNBERG Plots example cells from Kyzar et al 2023
% Outputs results of calcSelective_SB
%% Speficy unit filter
unit_examples = [... % Specify by sub-id, ses-id, unit_id
% See Daume et al. Fig 3a
5, 1, 29; ... |
15419f948e5e18207cfcb1f73fc545ed454c39349cbf557b149424f206780585 | MATLAB | 1,845 | 64 | function chirp = yOCTLoadInterfFromFile_ThorlabsLoadChirp(fp)
%This function loads a chirp file for thorlabs system.
%fp - can be the exact file path of the chirp file or a path to the
%thorlabs datafolder
%% Get file path pointing on to the chirp file
[~,fname] = fileparts(fp);
if isempty(fname)
%We got ... |
825b590eabcba35f29f34dc3539bdd329236b4ba7fe7108abc46a8569a42f613 | MATLAB | 1,846 | 59 | function [subj] = remove_objfield(subj,objtype,objname,fieldname)
% Removes a field from the object
%
% [SUBJ] = REMOVE_OBJFIELD(SUBJ,OBJTYPE,OBJNAME,FIELDNAME)
%
% If OBJTYPE == 'subj', removes a field from the SUBJ root. Can't
% be used to delete any of the main types or any required fields
% License:
%============... |
fc33f02f0e20283694ec1eb43e2645292662303eeb543b7273628b24a8b89fe0 | MATLAB | 1,848 | 61 | function Results = getRespLatencies(d,minDate,maxDate,maxBin,RespWin,minRespDelay,sessionFilter)
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
if nargin < 5, RespWin = Inf; end
if nargin < 6, minRespDelay = 0; end
if nargin < 7 || isempty(sessionFilter); selectSessions = 0;
elseif(is... |
f4fed798ade334b58a5588499de194fa2723c26b4b193c48b39875d64feb175f | MATLAB | 1,851 | 77 | function [HdI,pHdI] = HDIndex(S,ang,ep,varargin)
% USAGE
% HdI = HDIndex(S{c},ang,ep)
%
% Inputs:
% S: spike train
% ang: a tsd object of head orientation
% ep: an intervalSet object defining the time of valid pos tracking
%
% options:
% [h,d,mu,p,kappa] = HDIndex(S,ang,ep,nbBins,sdSm... |
c02603e2e5d582e3097c17f3c04704516ed5965ca792cfea7b1a127ae603ebff | MATLAB | 1,852 | 63 | function r = sbxalign(vidobj,idx, ROI,plotting)
% based on work of Dario Ringach
% https://scanbox.org/2014/03/20/recursive-image-alignment-and-statistics/
if(length(idx)==1)
hLarge = fspecial('average', 40);
hSmall = fspecial('average', 2);
imgA = msReadFrame(vidobj,idx,true,false,false);
imgA = (fi... |
07bf78c7f57177ec383bc0cd0f56b9af123c9afee848fa000836163d6fd24f6c | MATLAB | 1,854 | 56 | function intoFolder(parentNode, topFolder, expd, varargin)
% INTOFOLDER walk subfolders (1 level) and create child nodes to parent
% node treeHandle
%
% It supports multiple topFolders, and the parentNode should have the
% same numel return as topFolder
%
% VARARGIN
% context menu: Op... |
aa928a9799f3f3211739ce27e069542476a3877f27bef316b97862a65685d9b2 | MATLAB | 1,854 | 72 | function [snirf, nirsfiles] = Nirs2Snirf(dirname, nirsfiles0, replace, ntimebases)
%
% Syntax:
% snirf = Nirs2Snirf(dirname, nirsfiles)
% snirf = Nirs2Snirf(dirname, nirsfiles, replace)
% snirf = Nirs2Snirf(dirname, nirsfiles, replace, ntimebases)
%
% Description:
% Convert all .nirs files in the folder dirname... |
4b5ed531bc7c42da55c9b23128a0c24b57b552254a63655d0d07dc30b2c73f8a | MATLAB | 1,855 | 50 | function [dFFTraces] = dFF_lowerXPercent_20220127(RawTraces, SecPerFrame, MovingWindow, LowerXPercent)
% dFF_lower calculates the dF/F from raw traces, taking the lower X% of
% frames in the moving window to calculated the mean fluorescence
% Michelle Cahill 20220127 (adapted from Nicole DelRosso and from dFF_lower_... |
e3e950bb49c4636504463346340ce3623572b451c80165ea93960bc0ab04354b | MATLAB | 1,855 | 81 | function pth = resolve_bids_uri(uri, layout)
%
% Resolve a bids URI to a fullpath.
%
% USAGE::
%
% res = bids.internal.endsWith(str, pattern)
%
% :param uri: BIDS URI (taken from an IntendedFor field)
% :type uri: char or cellstr
%
% :param layout: BIDS layout where the URI is resolved.
% :ty... |
023bdb2258c3e77fcb2b54836c930dc21a352eba142e1b7a47e220e81c11ef42 | MATLAB | 1,858 | 60 | % JN 2022-04-26
% Convert sorted combinato output to Matlab files in Matlab.
% This is useful for working with Combinato outputs
% without using Python at all.
folder = '/home/johannes/Downloads/';
chan = 29;
label = 'joh';
sign = 'pos';
ffolder = fullfile(folder, sprintf('CSC%d', chan));
dfile = fullfile(ffolder, ... |
1836a9fc0845d9b547e3a81d174de8ec1cba59f57ae05c187c35af3a528c12ec | MATLAB | 1,859 | 53 | % function [cfg,data_train_trans,data_test_trans,score] = transfeat_PCA(cfg,data_train,data_test)
%
% no help available, please check code
% Update: 2016-08-25: Removed call of princomp, because direct call is faster
function [cfg,data_train_trans,data_test_trans,score] = transfeat_PCA(cfg,data_train,data_test)... |
4dd4159dd460709dc6dae96aea3c44b53881e88ba0fb5b8339f3fba3c4148677 | MATLAB | 1,860 | 65 | function [y, z, a] = mlpfwd(net, x)
%MLPFWD Forward propagation through 2-layer network.
%
% Description
% Y = MLPFWD(NET, X) takes a network data structure NET together with a
% matrix X of input vectors, and forward propagates the inputs through
% the network to generate a matrix Y of output vectors. Each row of X
% ... |
bf6342b28db4087e582c9b564212790fb5c7a0daa497c493bcfce3ae21f20844 | MATLAB | 1,860 | 53 | function step1_data = analysis_step1(params, f)
switch params.acquisition_system
case 'Doric'
%% LOAD DORIC DATA
step1_data = open_doric(f, params);
case 'RWD'
step1_data = open_rwd(f, params);
end
step1_data.sfreq = 1/mean(diff(step1_data.time));
rc = params.re... |
92b3371db1bf6c5cc11810589ca4ae08c78dba77b77f9389697794900f607061 | MATLAB | 1,861 | 44 | clear all;
outdir='/Volumes/LASA/TBI_OpenNeuro/TBI_openneuro/Hopf_model/TBI_ON_Lesions_Hopf_mask1halfSD_weight_corr/outputs/Trials/';
addpath(outdir)
addpath('/Volumes/LASA/TBI_OpenNeuro/Shared_code/TBI_ON_Lesions_Hopf_mask1halfSD_weight/');
addpath('/Volumes/LASA/TBI_OpenNeuro/TBI_openneuro/Hopf_model/TBI_ON_Hopf_... |
a61df4d7ac322042aafbde1082ee014366dddfc6947c3070beb5127d9840af96 | MATLAB | 1,861 | 44 | clear all;
outdir='/Volumes/LASA/TBI_OpenNeuro/TBI_openneuro/Hopf_model/TBI_ON_Lesions_Hopf_mask1halfSD_weight_corr/outputs/Trials/';
addpath(outdir)
addpath('/Volumes/LASA/TBI_OpenNeuro/Shared_code/TBI_ON_Lesions_Hopf_mask1halfSD_weight/');
addpath('/Volumes/LASA/TBI_OpenNeuro/TBI_openneuro/Hopf_model/TBI_homogene... |
6a2405f478fae99be5d00b44b45b6b4443c87daba77868f3a434fb2a27bfb7d1 | MATLAB | 1,866 | 65 |
%% Add path
addpath(genpath('../../Ionnic Channel'),genpath('../../Tools'), genpath('../../Synapses'), genpath('../../Datas'));
%% Import data from neuron (FS)
dt = 2^-6;
Vmem = -90:dt:60;
l_V = length(Vmem);
Vtraub = -55;
%% Anonymous function
minf_simp ... |
9a963ea02a2b69bcd99c354c947f82ae0fe6cf25a2e2f7cd408b0731e16577e9 | MATLAB | 1,866 | 62 | function behav = msSelectPropsForTracking(behav)
%MSSELECTPROPSFORTRACKING Summary of this function goes here
% Detailed explanation goes here
userInput = 'N';
green = cat(3, zeros(behav.height,behav.width), ...
ones(behav.height,behav.width), ...
zeros(behav.height,behav.width));
frame = double... |
a3c279a766bcc256edc3ba87a4ec591cb5c4f4832272c512d7d194766fee113b | MATLAB | 1,867 | 75 | function [area,conduction_time]= Spike_Hist_Area_210406(hist_vec,z,current_elec_pair)
% Sam Lassers Brewer Lab 1/8/21
% Starting out, this function has an arbitrary bounding method
% Make minimum bin size (get distribution of spikes)
%% TODO
% Create a running list of last created png images created.
% Compare area t... |
19591d7dbc82a0816e563bf48c6cb097227e6a94380c0bcebc8f43571d941762 | MATLAB | 1,869 | 51 | % dip test
% this code tests that the elekta co-ordinate system for SSS basis sets
% works...by imaging simulated sources within it
clear all;
close all;
spm('defaults','eeg');addpath 'C:\home\Data\4AshO'
%spmfile = 'C:\home\Data\DBS-MEG\Phantom\090715\SPMstim\spmeeg_uespmeeg_phantom090715_BrainampDBS_20150709_02.mat... |
aded9267af20e1cfb77ed5ef2dabc9e149ef6bb99bc1a4f46d248c16169c67e7 | MATLAB | 1,874 | 78 | function [Hp,Hs]=shadeplot(x,y,sd,linestyle,shadecolor)
% function [Hp,Hs]=shadeplot(x,y,sd,linestyle,shadecolor)
%
% Plot x,y with shaded regions to indicate y +/- sd.
%
% x,y,sd - Vectors of identical length.
% linestyle - Attributes as per standard plot function.
% shadecolor - RGB vector for color of shaded ... |
c1a302cad14a02af27c52b2e1fed641bbdab6c3c2d42b6e1a9709fab3bc9feb5 | MATLAB | 1,874 | 71 | function status = UnitTestsAll_Snirf(standalone)
global DEBUG1
global QUICK_TEST
global procStreamStyle
global testidx;
global logger
t_local = tic;
if ~exist('standalone','var')
standalone = true;
end
DEBUG1=0;
testidx=0;
procStreamStyle = 'snirf';
% Clean up before we start
UnitTests_Init(standalone, true, 'U... |
ddcb4b6e157ed9901917d3497670076474c6a100fdc00d4e699623d46efa6cef | MATLAB | 1,874 | 70 | %initialize matlab
close all
clearvars
clc
% Determine where your m-file's folder is.
folder = fileparts(which(mfilename));
% Add that folder plus all subfolders to the path.
addpath(genpath(folder));
%user input
[file, path]=uigetfile('.txt','Select single MINFLUX data file');
if isequal(file,0)
d... |
bb9e3fd6dc1b969ca7d75c3a1aeac489a8bdfc3df9f6c34cb4d548bbbd74cb12 | MATLAB | 1,875 | 62 | function data = PrairieLink_ReadRawFile(varargin)
% Read binary file generated by PrairieLinkRawDataStream
% Lloyd Russell 2017
% Varargin:
% 1: full path to file
% 2: first frame to read
% 3: number of frames to read
% To do:
% * allow direct resaving to tiff?
% Open the file
if nargin
filePath = ... |
bc7aedf9dccfaf1fd34fe963bd783247e8db2d87862677f09bbc2ead9f4e6555 | MATLAB | 1,875 | 91 | function [G,sup_scale,deep_scale] = GsGd(L,N,R,Norm)
% this is the matrix which will be multiplied by the alpha coefficients in
% order to get data for the superficial or deep components.
if isempty(L)
L = 7;
end
if isempty(N)
N = 7;
end
if isempty(R)
R = [0.06 0.17];
end
if isempty(Norm)
Norm = 0;
end
%... |
e892a3f925c134cf845b658e7a6d840fc6c77656c5ab1b608bdd5be12df49035 | MATLAB | 1,875 | 52 | % if trials var already filtered out trials by condition/locations, then
% just filter out movieIdx to same criteria.
% trials var should have 90 trials
% Important, keep number of trials in trials and movieIdx the same
% for fNIRS only
% For sbj 08 and 10, use keepCorrectTrials_Special
function [trials,varargout] = k... |
1c5380d75fcf26ca2f2a6b3f7d84faa74ba21ce88b6512bfe5df7ce3ed9b6fba | MATLAB | 1,876 | 54 | function BC=betweenness_bin(G)
%BETWEENNESS_BIN Node betweenness centrality
%
% BC = betweenness_bin(A);
%
% Node betweenness centrality is the fraction of all shortest paths in
% the network that contain a given node. Nodes with high values of
% betweenness centrality participate in a large number ... |
4542215f9b27817407357d70d1553c273430aa02bc3256a971fefd1164c33b9d | MATLAB | 1,876 | 59 | function [all_same,diff_vol,diff_ind,maxabs_diff] = compare_volumes(fnames,writeout)
% function [all_same,diff_vol,diff_ind,maxabs_diff] = compare_volumes(fnames,writeout)
%
% Function to compare multiple volumes. Should be provided as list of file
% names. If writeout == 1, then write difference image to pwd, b... |
71a860f1667692e1145f0de3dd6d09179d7980f2f2d733e6ebfbcca43b3607e1 | MATLAB | 1,877 | 66 | supPath = 'C:\noga\TD complex spike analysis\Data\albert\speed_2_dir_0,50,100';
load ('C:\noga\TD complex spike analysis\task_info');
req_params.grade = 7;
req_params.cell_type = 'PC ss';
req_params.task = 'speed_2_dir_0,50,100';
req_params.ID = 4000:5000;
req_params.num_trials = 30;
req_params.remove_question_marks ... |
e6f29860b5cd7197017e0fa21632c2449fb2570e05d9c8010b903e30a78fb6ea | MATLAB | 1,877 | 51 | function output = hidden_state_estimate(steps,chpt,L,stsz)
% transition states assignment 1=initial dummy state to assure all possible
% initial states / 2=bound to bound / 3=bound to unbound / 4=unbound to bound / 5=bound to
% bound (reduced stepsize)/ 6=unbound to unbound (enhanced stepsize)
xemi=1:1:100; % pos... |
1c52a07bdf693b2f95f18a658d4a874d43cb07e83be64fe2f3071c397b56b751 | MATLAB | 1,879 | 61 |
clear all
%% Load data
load(fullfile('Data','SpikeData'),'S');
load(fullfile('Data','BehavEpochs'),'wakeEp');
load(fullfile('Data','Angle'));
load(fullfile('Data','CellTypes'));
led1 = load(fullfile('Data','LED1_TS.csv'));
baseEp = intervalSet(led1(1,1),led1(2,1)); % we can take the du... |
1f267614b8902c7062a01944e6b3cd9fd6105f7e9a8a0fdb2585fd6deb1f23b5 | MATLAB | 1,881 | 77 | function [h,B,mu,p,kappa,h0] = HeadDirectionField(tsa,ang,GoodRanges,varargin)
% USAGE
% [h,B,mu,p,kappa] = HeadDirectionField(tsa,ang,GoodRanges)
%
% Inputs:
% tsa: a ts object (typically a cell!)
% ang: a tsd object of head orientation
% GoodRanges: an intervalSet object defining the time of... |
42e87948816956ab5abf7b6e9cdbb7fa530e748e4c7cd7c11fde4d3d8fa73211 | MATLAB | 1,881 | 58 | clear; clc
[task_info, supPath ,~,task_DB_path] = ...
loadDBAndSpecifyDataPaths('Vermis');
req_params.grade = 7;
req_params.cell_type = 'CRB|PC';
req_params.task = 'speed_2_dir_0,50,100';
req_params.ID = 4000:6000;
req_params.num_trials = 50;
req_params.remove_question_marks = 1;
raster_params.time_before = -100;... |
e901abe53b1e37be6ae1a02d5e3e1f8b76356f02cc276ad3750f4b27435e187c | MATLAB | 1,884 | 37 | %Plots flicker stimulus on plot.
%2024/02/25
function plot_flicker(freq,y_lim,duration,patch_color,single_pulse,varargin)
%COMMENTS EXPLAINING BELOW?
if ~isempty(varargin)
height_divider=varargin{1};
else
height_divider=5;
end
yrange=[y_lim(2) y_lim(2)+((y_lim(2)-y_lim(1))/height_d... |
107a75c9ffa76aa6d1e438c143e922fb8a932640cff06502e6c1858b38b3c0e7 | MATLAB | 1,885 | 81 | function [h,B,hdi,mu,p,kappa,h0] = HeadDirectionField(tsa,ang,GoodRanges,varargin)
% USAGE
% [h,d,mu,p,kappa] = HeadDirectionField(tsa,ang,GoodRanges)
%
% Inputs:
% tsa: a ts object (typically a cell!)
% ang: a tsd object of head orientation
% GoodRanges: an intervalSet object defining the tim... |
c3c784ca1b84ed888ce5b9832f3dbcccae81b5b8ec51c092f9ccd5f4804b5ec5 | MATLAB | 1,885 | 61 | %
% For a linear classifier (SVM, LDA), define the hyperplane and the signal axis
%
% Beta/Bias: parameters as derived from fitclinear or fitcdiscr
% P: Dimensionality of the data
%
%urut/Aug'23
function [signalVector_derived, signalVector_fromModel_norm, fHyperplane, fBoundLine] = LinearClassifier_getSignalAxis(Betas,... |
9f573b5e510d858e3b13b212d199b5075ecfcb5a195829211a836a97a0530a92 | MATLAB | 1,886 | 69 | function [spkBurstIx,burstLg,burstIdx,burstLgInd] = BurstSpikes(S,varargin)
%
% [spkBurstIx,burstLg] = BurstSpikes(S)
%
% Detects burst spikes and computes burst index
% Input:
% S: a ts object of spike timing.
% Output:
% spkBurstIx: a vector same length as S, indicating spike index in each
% burst (0 f... |
0af56eb32245bc886f025444f0859eb1decab582951fab38ec72bac73b71a3c6 | MATLAB | 1,888 | 44 | clear all;
outdir='/Volumes/LASA/TBI_OpenNeuro/TBI_openneuro/Hopf_model/TBI_ON_Lesions_Hopf_mask2SD_bin_corr/outputs/Trials/';
addpath(outdir)
addpath('/Volumes/LASA/TBI_OpenNeuro/TBI_openneuro/Hopf_model/TBI_homogeneous/outputs/Trials/HC/');
addpath('/Volumes/LASA/TBI_OpenNeuro/Shared_code/TBI_ON_Lesions_Hopf_mask... |
88d929c9af4db334077cc4174deddf797a439599db0d6444ec384e83e3871eb9 | MATLAB | 1,888 | 44 | clear all;
outdir='/Volumes/LASA/TBI_OpenNeuro/TBI_openneuro/Hopf_model/TBI_ON_Lesions_Hopf_mask2SD_bin_corr/outputs/Trials/';
addpath(outdir)
addpath('/Volumes/LASA/TBI_OpenNeuro/TBI_openneuro/Hopf_model/TBI_ON_Hopf_hc_tp2/outputs/Trials/');
addpath('/Volumes/LASA/TBI_OpenNeuro/Shared_code/TBI_ON_Lesions_Hopf_mask... |
1a6a2cc55b3501cec137869f6c9f98daee343fdb0fb31e9ed3a9b93e3c1ea248 | MATLAB | 1,889 | 54 | % In order to bring an old version of datafiles up to speed (to convert to
% current format) use this script. It runs over all subjects of some
% library for the purpose of finding old / unsupported data files and
% converting them to current version
%% Inputs
% Which library to run on
[subjectsPath,subjects... |
6bd4761737f26eb903b46ba65c057b06d527c8ad934f36b194511185c38d1f5b | MATLAB | 1,889 | 62 | function [scratchpad] = train_template(trainpats,traintargs,in_args,cv_args)
% Template for creating custom training functions
%
% [SCRATCHPAD] = TRAIN_TEMPLATE(TRAINPATS,TRAINTARGS,IN_ARGS,CV_ARGS)
%
% See 'Creating your own training function' in manual.htm
%
% See the related TEST_TEMPLATE function that gets called
... |
1ddf7ff0a34ea5b6a6572467979c30dbf691508623491f7c0ba4f0245f8926a3 | MATLAB | 1,892 | 54 | function L= Computer_laplacian_matrix(W)
if W == W'
fprintf('Run the first case undirected graph')
% out-degree matrix
D=diag(sum(W,2));
Wsymm=D^(-1/2)*W*D^(-1/2);
Wnew=Wsymm;
n_ROI = size(W,1);
% compute normalized undirected graph Laplacian: L^=D^(-1/2)... |
e3b0d0dcdbda08d29041106393d72ba7b7a65ecf0bfd94ec452a7bed3e533af4 | MATLAB | 1,893 | 69 | function data_detrended = detrend_spline(data, n_nodes)
% function data = detrend_spline(data, n_nodes)
%
% Remove slow temporal drifts from the data of each voxel using cubic
% spline interpolation.
%
% Input:
% - data: [n_tr, n_voxel, n_run] array with data.
% - n_nodes: Number of nodes for spline fitting (reco... |
0c85de9a443bbc801df3c10e98a7b6899a30747322c164fc72577830f95d0eed | MATLAB | 1,895 | 43 | function new_matched=convert_allregion_unit_matched_220413(allregion_unit_matched)
new_matched=[];
for i=1:length(allregion_unit_matched)
recording_data=[];
Subregion=unique(allregion_unit_matched{i}.Subregion,'stable');
for j=1:length(Subregion)
tunnels=cellstr(allregion_unit_matched{i}.("Electrod... |
87b0ea4d5acba000712a029b87a2e22b83124fd5ce93f1db736f96514671157f | MATLAB | 1,895 | 62 | function [downsampled_array] = downsample_HD(array, factor,varargin)
% Default method is mean
method = 'mean';
for v = 1:numel(varargin)
if strcmpi(varargin{1},'sum')
method = 'sum';
elseif strcmpi(varargin{v},'median')
method = 'median';
elseif strcmpi(varargin{v},'prctile')
met... |
6b2132838134ca2988121fbe1482977a6cbeac2bf98b11f40e1d9d312c493c09 | MATLAB | 1,896 | 73 | function im = intervalMean(tsa, is, varargin)
% Computes mean of of data in each of subset of a given interval
%
% USAGE:
% im = intervalMean(tsa, is, options)
%
% INPUTS:
% tsa - a tsd object
% is - an intervalSet
%
% OUTPUTS:
% im - a tsd object, where the timestamps correspond to each inter... |
dd09989ea8e7f743fe21c532dfbfccc54da02181c828160133a275a6c7799836 | MATLAB | 1,896 | 51 | % Vm = vsh_modified_in_fast(theta,phi,l,m,p0)
%
% Vector spherical harmonic funtion modified from Hill's function
% V_lm for quantum numbers l and m. Angles theta and phi should be
% given in radians. p0 contains the values of the Legendre polynomial.
%
function Vm = vsh_modified_in_fast(theta,phi,l,m,p0)
% Copyright ... |
0a4cfbba25f6d8b871dbb4e7e27281c6cd4029eca658582693427adcf403e24e | MATLAB | 1,898 | 54 | function this = cosinorAnalysis(this)
%COSINORANALYSIS Perform cosinor analysis on an ACTI object
%
% $Author: Peng Li
% $Date: Jul 01, 2020
%
period = this.CosinorInfo.HarmonicsInHour;
minLen = this.CosinorInfo.MinimumLengthInDays;
epoch = this.Epoch; % in sec
x = this.Data;
x(this.GapSeries)... |
7b38c811ef2bc6970cf6d7c30e017bef59a5a6c76b4222d91f53275d839ee58f | MATLAB | 1,898 | 86 | clear
DEGREES = 0:45:315;
GAUS_WIDTH = [5:5:150];
PD = 180;
NOISE_STD = 0:0.1:3;
NUM_TRIALS_PER_COND = 100;
REPEATS = 1000;
figure;
ax1 = subplot(1,2,1); hold(ax1,"on")
for i = 1:length(GAUS_WIDTH)
% DEGREES = DEGREES(randperm(length(DEGREES),2));
disp ([num2str(i) '/' num2str(length(GAUS_WIDTH))])
... |
e9ce79d12bc58ea2b66db9703fa58fdce0d7fae722b611517c3ee1280928d893 | MATLAB | 1,898 | 70 | %% SI ANALYSIS: Simulating 2-ADC Model by varying criterion with fixed d'
% This is to show that varying criterion alone is a valid strategy to
% increase percent correct in a mADC task with high cue validity
%% Initializing parameters
cols=[1,0,0;0,1,0;0,0,1]; % Colors
% Sensitivity
d1=1;
d2=1;
d=[... |
5f39226f327e4c5aef6863fc5b695ba12487f34a3101509c0a0d8230770aca7c | MATLAB | 1,899 | 49 | function refreshGaps(this, actigraphy)
% REFRESHGAPS Update gap patches from ACTIGRAPHY
%
% $Author: Peng Li
% $Date: Feb 29, 2026
%
ax = actigraphy.actiAxis;
yrange = actigraphy.Decoration.YLim;
delete(findobj(ax, 'Tag', 'GapPatch'));
delete(findobj(ax, 'Tag', 'GapText'));
if ~isempty(this.Gap)
... |
02450ffe505a0ddeb8b04addddf8c79e8bb92622e5612c36b0dad7380acdc2dd | MATLAB | 1,908 | 82 | function [ang,GoodRanges,ep] = HeadDirection_Wrapper(fbasename,varargin)
% loads head-direction from a position file file (ending in .whl)
%
% USAGE
% [ang,GoodRanges] = HeadDirectionWhl(fbasename,options)
%
% INPUT:
% fbasename: session file basename
% whlStruct (optional): a structure containing po... |
d10e3a3c0382819856bdd5b7013e6f5fd095e1591863fc0751701aefcdf0b560 | MATLAB | 1,912 | 75 | function L = CrossValidationPeerHDCheck(Starget,Qassembly,Qtarget,ang,ep)
nbEp = 10;
fprintf('Launching Cross-validated Peer info\n')
epV = regIntervals(ep,nbEp);
dQ = Data(Qtarget);
nbC = size(dQ,2);
L = NaN(nbEp,nbC);
% weights = zeros(nbC,nbEp,nbC-1);
angq = Restrict(ang,Qtarget);
for ii=1:nbEp
fprintf('.'... |
8c29d7018891ae82cd1530dd88f3c98837d82b38f6231104b283dd74fca271c6 | MATLAB | 1,916 | 53 | function plotSine(K1, K2, K0, I, learn_color)
% (temmporarly?) helper function -- plot VORD sine for PC
freq = 0.5;
dt = K1.dt;
tt_sine = (0:2/dt)'*dt;
head_curr = sin(2*pi*freq*tt_sine);
% TODO: make sure these match!!!
[Ehat_orig, Phat_orig] = modelImpulse(getImpulse(K1, I, 1), I, head_curr, zeros(size(head_curr)),... |
bde2e974b799d0bcfe048ffc628cee7d4a9be598197c1b76c8070a94bec31fc5 | MATLAB | 1,916 | 60 | clear,clc
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% This script is used to perform CCA for brain-behavior analysis
%
% Jin
% 7/25/2022
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% set the file path
current_path = pwd;
working_path = current_p... |
5ac8494d6e9a8b59c9453fa357547664a6844dc4ed34b7a780975bd9a824c1af | MATLAB | 1,920 | 61 | addpath(genpath('/dagher/dagher11/filip/Software/BrainSpace-0.1.2'));
addpath(genpath('/dagher/dagher11/filip/Software/gifti-main'));
addpath(genpath('/dagher/dagher11/filip/Software/netneurotools'));
addpath(genpath('/dagher/dagher11/filip/Software/neuromaps'));
[v_dkt_lh, l_dkt_lh, ct_dkt_lh]=read_annotation('/dagh... |
b3e178449273b2fd10ead2de2c3ffd267f24adab63cdb72a6cdc83dcd143e801 | MATLAB | 1,921 | 51 | function updateSubmodulesWithoutGit(submodules, branch)
if isempty(submodules)
return;
end
if isempty(branch)
return;
end
for ii = 1:size(submodules,1)
url = submodules{ii,1};
submodulepath = submodules{ii,3};
[~, submodulename] = fileparts(url);
filenameDownload = sprintf('.... |
4839644650d044a2c9da949d318353a2f16c31901f1b4414ab4f2c8d34a1ea04 | MATLAB | 1,922 | 43 | clear all;
outdir='/Volumes/LASA/TBI_OpenNeuro/TBI_openneuro/Hopf_model/TBI_ON_Lesions_Hopf_mask1halfSD_bin_corr/outputs/Trials/';
addpath(outdir)
addpath('/Volumes/LASA/TBI_OpenNeuro/TBI_openneuro/Hopf_model/TBI_homogeneous/outputs/Trials/HC/');
addpath('/Volumes/LASA/TBI_OpenNeuro/Shared_code/TBI_ON_Lesions_Hopf_... |
9e3e094b264f2d5c08c88abbb447868159c7339bc4705938fdea092bfdd41bd6 | MATLAB | 1,922 | 43 | clear all;
outdir='/Volumes/LASA/TBI_OpenNeuro/TBI_openneuro/Hopf_model/TBI_ON_Lesions_Hopf_mask1halfSD_bin_corr/outputs/Trials/';
addpath(outdir)
addpath('/Volumes/LASA/TBI_OpenNeuro/TBI_openneuro/Hopf_model/TBI_ON_Hopf_hc_tp2/outputs/Trials/');
addpath('/Volumes/LASA/TBI_OpenNeuro/Shared_code/TBI_ON_Lesions_Hopf_... |
ad75ca234dec34f56c334012df294b7d6dedd9111115e3f9c0667b93c8c84a9f | MATLAB | 1,922 | 61 | addpath(genpath('/dagher/dagher11/filip/Software/BrainSpace-0.1.2'));
addpath(genpath('/dagher/dagher11/filip/Software/gifti-main'));
addpath(genpath('/dagher/dagher11/filip/Software/netneurotools'));
addpath(genpath('/dagher/dagher11/filip/Software/neuromaps'));
[v_dkt_lh, l_dkt_lh, ct_dkt_lh]=read_annotation('/dagh... |
dff9443b8ad55bf718a76d0baf98ab43f0428b6691fc984939972dd18d23d388 | MATLAB | 1,924 | 47 | function M=fEPIa_shortTR(Mx0,My0,Mz0,nExt,nStartExt,TR,TE,shortTR,T1,T2,FAdeg,FreqOffset)
%% Simulate the multiple measurment of EPI CSF signal and more saturated signal at the last measurement
FA = FAdeg*pi/180; % radian
M0=1;
bettaTT=2*pi*FreqOffset*TE;
Dtt=[ exp(-TE/T2)*cos(bettaTT) exp(-TE/T2)*sin(bettaTT) ... |
9672ad3b3676b6098c867e46d0647ca1edb0a2b919f39fb7f69d0cf4e3ee80e6 | MATLAB | 1,925 | 67 | %% Plot choice vs mADC scatter plot ( Pooled across sessions + angles )
load('choice_vs_madc_RFTrials.mat')
%% Monkey G
sens_madc{1} = best_thet_est.G{1}(1,1:4);
c_madc{1} = best_thet_est.G{1}(1,5:8);
for iLoc=1:4
bias_madc{1}(iLoc)=exp(-(sens_madc{1}(iLoc)*(c_madc{1}(iLoc)-(0.5*sens_madc{1}(iLoc)))... |
98c4741fd442ba448d8ce771cf52eccf8038f09b3b2886187ef25353b03f2c32 | MATLAB | 1,925 | 59 | function VBpost = mstep_VBVAR(data,Ybar,VBprior,Gammas,barAlpha,Lambda,state)
[VBpost.mua VBpost.Lambda_a] = updata_Qa(data,Ybar,barAlpha,Gammas,Lambda,state);
[VBpost.nuN, VBpost.WN,VBpost.Lambda] = update_QLambda(data,Ybar,Gammas,VBprior,VBpost.mua,VBpost.Lambda_a,state);
[VBpost.aN,VBpost.bN,VBpost.barAlpha] = upd... |
a19d79003f0acb9fd7c42156747637e5192cffb5c5d4a98bb6f8994b9025a679 | MATLAB | 1,925 | 50 | function [ranks,decoding_out] = RFE(cfg,ranks,final_n_vox,iteration,data_train,labels_train,data_test,labels_test)
% This is a subfunction for feature_selection_embedded. The general
% structure is (also for other such functions):
% INPUT:
% cfg: contains all configuration information
% ranks: index which pa... |
f7afa08d9f4478f01aa75250f1812b03b9237df9096fb4e5d620cf75eb77b406 | MATLAB | 1,925 | 53 | function [pparam, X, clabel] = mv_preprocess_undersample(pparam, X, clabel)
% Undersamples the majority class(es) in unbalanced data.
%
%Usage:
% [pparam, X, clabel] = mv_preprocess_undersample(pparam, X, clabel)
%
%Parameters:
% X - [samples x ... x ...] data matrix
% clabel - [samples x 1] vector... |
db8b5ac70c0352691cf5791a6503f66df3f751d378988e20d52b8867d7181839 | MATLAB | 1,926 | 73 | function status = UnitTestsAll_Nirs(standalone)
global DEBUG1
global QUICK_TEST
global procStreamStyle
global testidx;
global logger
t1 = tic;
reg = RegistriesClass('reset');
if ~exist('standalone','var')
standalone = true;
end
DEBUG1=0;
testidx=0;
procStreamStyle = 'nirs';
UnitTests_Init(standalone);
logger =... |
d74334cae74f2db7f5b4c310379ca96df0628d11a65b7b69af78e23dbbd96cb9 | MATLAB | 1,928 | 72 | function S = smooth(tsa, l, varargin)
% Smooth a TSD
%
% USAGE:
% S = smooth(tsa, l, OptionName, OptionValue, ...)
% %
% This is intended for continuously sampled tsd-s, the sampling rate is
% guessed with the median inter-event interval method (see MEDIAN_DT)
% If there are some missing values, they ... |
7ed1140e7230192b056cbb5126060c7de693e56adb404965882470bc9624da6a | MATLAB | 1,930 | 63 | function pass = print_unittest_result(msg,expect, actual, tol)
% Prints the unittest result. Compares the expected result to the actual
% result. If the difference is < tol, the test is passed. Otherwise it is
% failed.
%
% Parameters:
% msg - [char] message string
% expect - [double] expected result
... |
3653454524e0d51cd9796a0cfe307e2116326eceafe83c2a9555b06c9e2681ad | MATLAB | 1,931 | 66 | %% Behavior figure
clear all
[task_info,supPath,MaestroPath] = loadDBAndSpecifyDataPaths('Golda');
req_params.grade = 7;
req_params.cell_type = 'CRB|PC ss';
req_params.task = 'speed_2_dir_0,50,100';
req_params.ID = 5600:6000;
req_params.num_trials = 60;
req_params.remove_question_marks =0;
behavior_params.time_aft... |
3d6ab97702e67439b54f76ef4d08cbef7090458b85032f4bf5f0dd14d9a4bf40 | MATLAB | 1,932 | 43 | % function for fitting the model and
% checking if it provides a perfect prediction of all choice data,
% in which case, a better model is where the scaling factor is infinite
function [bestb,out] = fitandcheckmodel(startingpoints,lb,ub,DVH,data,type)
b = nan(size(startingpoints));
negLLlist = nan(size(b,1),... |
74af570f7b4a8ccdeca6b3a33a743d65809995f76b55b46f8c292c0e662b822c | MATLAB | 1,932 | 59 | function [extra, invhess] = fevbayes(net, y, a, x, t, x_test, invhess)
%FEVBAYES Evaluate Bayesian regularisation for network forward propagation.
%
% Description
% EXTRA = FEVBAYES(NET, Y, A, X, T, X_TEST) takes a network data
% structure NET together with a set of hidden unit activations A from
% test inputs X_TEST,... |
57677013f04f5b761d9ebcedf2c0d549b8a470791e7b4cd4b14b240fbf049bfb | MATLAB | 1,936 | 57 | function p = genpath_nosvn(d)
%GENPATH Generate recursive toolbox path (ignoring .svn entries)
% P = GENPATH returns a new path string by adding
% all the subdirectories of MATLABROOT/toolbox, including empty
% subdirectories.
%
% P = GENPATH(D) returns a path string starting in D, plus, recursively, all
... |
756304c784e912ac391fb81bad342175faea723fd28d3a076bb0bb997b3682f4 | MATLAB | 1,936 | 60 | %% Significance as function of time, trials without saccade
clear all
supPath = 'C:\noga\TD complex spike analysis\Data\pursuit_8_dir_75and25';
load ('C:\noga\TD complex spike analysis\task_info');
req_params.grade = 7;
req_params.cell_type = 'PC ss';
req_params.task = 'pursuit_8_dir_75and25';
req_params.ID = 4000:5... |
b41c5124f206b9efdf77399268eb2bc7f1ce863ab63006ce7d92ae9b8e229bd6 | MATLAB | 1,936 | 63 | % STATUS: Active
%
% SYNTAX:
% [singleTrialHRFHbOM, singleTrialHRFHbRM, singleTrialHRFHbTM] ...
% = createSingleTrialHRF_MultiOnly_NoSave(trialsCont, allSMultiple)
%
% DESCRIPTION:
% Reformat continuous data format (channels x time) into epoched data
% format (channels x time x trials). Split into 3 different chr... |
bcef1490ac56503b8e00709ae6c054beba5a1b36f8e3ee37012943793a829f36 | MATLAB | 1,937 | 54 | function imetronic_DB= synchronize_imetronic_data(filepath, recording_config, data)
[filepath_,name,ext] = fileparts(filepath);
filelist = dir([filepath_ filesep '*.dat']);
if ~length(filelist)
imetronic_DB = []
return
end
imetronic_path = [filepath_ filesep filelist(1).... |
70ccc50b8ed1f6a159636403c5b163699ea7792cf2b9528018b87373e269f80c | MATLAB | 1,939 | 74 | function photo_plots(data, plotname)
if strcmp(plotname,'deinterleaved signals')
fig=figure();
title('deinterleaved data')
hold on
plot(data.dein_signals.time,data.dein_signals.iso,'m')
plot(data.dein_signals.time,data.dein_signals.physio,'b')
legend({'iso', 'physio'... |
c46739aa3a21b11d0a7e96fafcc43e61b95fb7f64db8caef40ef5f75105346ff | MATLAB | 1,942 | 79 | function hdv = mlphdotv(net, x, t, v)
%MLPHDOTV Evaluate the product of the data Hessian with a vector.
%
% Description
%
% HDV = MLPHDOTV(NET, X, T, V) takes an MLP network data structure NET,
% together with the matrix X of input vectors, the matrix T of target
% vectors and an arbitrary row vector V whose length eq... |
0a380073695c5cb58bac81b44cc2700b139071c2cd166e9c0d85b6c6f55a9525 | MATLAB | 1,945 | 84 | function [theta_est_choice] = ...
est_param_choice(monkey, RF, sessions, beh_dat, sessions_type)
%% Function to estimate parameters on pooled across sessions
onebyN_flag = 1;
%% Code for both pooled and Jack-Knife Fitting
if(sessions_type == "indiv_sessions")
sessions_looped = sessions;
... |
579e0ddbe71006feb3a889febecf67b3494e28f01633e7210a5772de44c1a8ed | MATLAB | 1,945 | 67 | function [subj] = init_subj(exp_name,id,varargin)
% Returns an empty initialized SUBJ structure
%
% [SUBJ] = INIT_SUBJ(EXP_NAME,ID,...)
%
% The empty SUBJ structure contains no patterns, regressors, selectors
% masks. Adds some rudimentary header info, including the following
% string arguments
%
% EXP_NAME: The name ... |
b3b38153b9faae5dde908082bc71d91a47c168746592265a167fd8e058a6ae57 | MATLAB | 1,945 | 62 | function [subj] = create_norest_sel(subj,regsname,varargin)
% Creates a selector with 1s for non-rest timepoints
%
% [SUBJ] = CREATE_NOREST_SEL(SUBJ,REGSNAME,...)
%
% Creates a boolean selector from the REGSNAME regressors with 1s
% everywhere except where there are rest timepoints
% (i.e. timepoints with no non-zero... |
4daca70d355fb572f62f5f9814c608b22a096d3270dfb33308967770c3d9f2e0 | MATLAB | 1,946 | 63 | addpath(genpath('/dagher/dagher11/filip/Software/BrainSpace-0.1.2'));
addpath(genpath('/dagher/dagher11/filip/Software/gifti-main'));
addpath(genpath('/dagher/dagher11/filip/Software/netneurotools'));
addpath(genpath('/dagher/dagher11/filip/Software/neuromaps'));
[v_dkt_lh, l_dkt_lh, ct_dkt_lh]=read_annotation('/dagh... |
82da4a5349006d49a09834111ebd6201d83ac8bd3cd7a78bf6195aa353e39c74 | MATLAB | 1,951 | 88 | clear all
close all
mkdir tempMAout
mkdir MAout
data=readtable('../../results/results_organized.xlsx');
%data=readtable('../../../PMmeta/AAL3/myAAL3/results_organized.xlsx');
dtistudies={
'P18' % there would be also study P13 but we keep it since it has fMRI results
'P19'
'P20'
'P21'
'P22'
'P40'
'P48'
'P49'
'P50'
'P59... |
46148730acb0dd3abaf987c9e8b768f628297da38bac1f89d1333750fe983aad | MATLAB | 1,957 | 62 | function [e, edata, eprior] = mlperr(net, x, t)
%MLPERR Evaluate error function for 2-layer network.
%
% Description
% E = MLPERR(NET, X, T) takes a network data structure NET together
% with a matrix X of input vectors and a matrix T of target vectors,
% and evaluates the error function E. The choice of error function... |
7452717cd4fd557ab89f504c38d26042aefce5bcc680f1eec453dee62b980c1e | MATLAB | 1,957 | 74 | clear all
close all
format compact
clc
% script to calculate distances have been measured for all included scans (UsedSets)
gt_dataPath = '/home/dichang/datasets/SampleSet/MVS_Data'
[dataPath,resultsPath]=getPaths();
dataPaths = {'/home/dichang/code/related_work/u-mvsnet'}
resultsPaths = {'/home/dichang/code/rel... |
be2f798a9cbd0e8f6a99a2a1de6095a0c63d2ca3a18a91e23593ea8c9d1f38ed | MATLAB | 1,958 | 59 | function [subj] = rename_object(subj,objtype,old_objname,new_objname)
% Rename an object OLD_OBJNAME TO NEW_OBJNAME
%
% [subj] = rename_object(subj,objtype,old_objname,new_objname)
%
% Note: this could cause friction in your scripts, if you've
% forgotten to update the new name later. Also, other parts of the
% toolbo... |
892b9a77fffb5ee24ecc61c0d723cf70708186e48c17686bf79315c7a80f40c7 | MATLAB | 1,961 | 74 | function [S] = wavescram(X, N, M)
% WAVESCRAM - Efficient, toolbox-free wavelet scrambling.
%
% Usage:
%
% [S] = WAVESCRAM(X, N)
% [S] = WAVESCRAM(X, N, M)
%
% WAVESCRAM takes an input signal X, performs an N-level discrete
% wavelet transform using the Debauchies-4 wavelet, and then
% generates M new signals that ha... |
a355aa3b1525efa71af94b39eecbefda0012826b26a45c101fa834430dc9f161 | MATLAB | 1,962 | 65 | function PlotOpticalFlow(OriginalImage, OpticalFlow, s, fac, varargin)
im = OriginalImage.Image(:, :, :, OriginalImage.ActinChannel);
vx = OpticalFlow.vxMat;
vy = OpticalFlow.vyMat;
% vx = imfilter(vx, fspecial('gaussian', 7, 1));
% vy = imfilter(vy, fspecial('gaussian', 7, 1));
rel = OpticalFlow.relMat;
flag = 0;
if l... |
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