sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
fafcd6109f3741c44cfd8fbd104c7a31a30352990216112b04f1ddd4b7d9f933 | MATLAB | 3,337 | 108 | function N = spreador( I, V, p, n )
% SPREADOR Spread orientation alog a surface for a given oriented point from the surface
% INPUT:
% I - Input binary surface mask
% V - Normal unoriented vector 3D field
% p - initial point coordinate
% n - initial oriented normal in p
% OUTPUT:
% ... |
319f164e8b2b63e9b6cc7c8d95f503d88101be5fbc64cefdd3d79cf06d398ad7 | MATLAB | 3,338 | 90 | function makePlatformSpecificFig(figFile,newFigFile,targetPlatform)
% figFile: name of original .fig file (with extension)
% newFigFile: name of new .fig file (with extension)
% targetPlatform: platform of target.one of {'pc' 'mac' 'unix'}
%
% This file exists to enable cross-platform use of a GUIDE-generated .fig
% wi... |
6f3964a4d91870483c7ae60fccdb747a784cb81855f0430a099102cc047c7fa9 | MATLAB | 3,338 | 100 | function h=subaxis(varargin)
%SUBAXIS Create axes in tiled positions. (just like subplot)
% Usage:
% h=subaxis(rows,cols,cellno[,settings])
% h=subaxis(rows,cols,cellx,celly[,settings])
% h=subaxis(rows,cols,cellx,celly,spanx,spany[,settings])
%
% SETTINGS: Spacing,SpacingHoriz,SpacingVert
% ... |
2b91b2caf8b5fc50f9f1b4d2e178eea13c4551fd1be32a960492e99e584d353c | MATLAB | 3,339 | 107 | % HIFDE_SPDIAG Extract diagonal using hierarchical interpolative factorization
% for differential 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 suc... |
7c03a1673856ea5e1ee1df36ee717048133db1b2a1db820fde3f81117dc93d4d | MATLAB | 3,339 | 124 | % Written specifically to work w/ the Object classes
% Makes the 'SAT.predict.plotter' redundant
function plotErrorStruct(errorStruct, vars)
arguments
errorStruct
vars.fill = 0;
vars.alpha = 0.05;
vars.nShuffles = 1000;
%
vars.saveDirectory = [];
vars.saveFig = 0;
vars.saveFormat {... |
a65f43a447424ecea118bb335c1351fae8fa229d5fbc23f9ed2056069db4a7bc | MATLAB | 3,339 | 122 | function [cdist, dcdistdom, dcdistdT, r, drdom, drdT] = TestFunction(X,om,T,k);
[m,n] = size(X);
[Y,dYdom,dYdT] = rigid_motion(X,om,T);
inv_Z = 1./Y(3,:);
x = (Y(1:2,:) .* (ones(2,1) * inv_Z)) ;
bb = (-x(1,:) .* inv_Z)'*ones(1,3);
cc = (-x(2,:) .* inv_Z)'*ones(1,3);
dxdom = zeros(2*n,3);
dxdom(1:2:end,:) = ((i... |
14abf63589695599e252651cf7f58fee147bda152d6cb5ffd950ac6d26d6c0a3 | MATLAB | 3,341 | 93 | function [comod] = bz_ModIndex(lfp,phaserange,amprange,flagPlot)
% [comod] = bz_ModIndex(lfp,phaserange,amprange,flagPlot)
%This function calculates the modulation index of phase-amplitude between
%phaserange (lower frequencies) to amplitude range (higher frequencies).
%It can really take a long time if you do very sma... |
1533d859fa6831acc5c6c540c0622a05b98fa883f09226cf92cdf72dcb7a1dad | MATLAB | 3,341 | 32 | subjs={
'/m/cs/scratch/networks-pm/pm_denoise/sub-01/sub-01_task-movie_SGdetrend_24HMP-8Phys-Spike_HPF_smooth-6mm.nii'
'/m/cs/scratch/networks-pm/pm_denoise/sub-02/sub-02_task-movie_SGdetrend_24HMP-8Phys-Spike_HPF_smooth-6mm.nii'
'/m/cs/scratch/networks-pm/pm_denoise/sub-03/sub-03_task-movie_SGdetrend_24HMP-8Phys-Spike... |
afaca0bea67a2ff7986da0d2e0b69b6902e12e846d7ade92b1bde4db8589aaa9 | MATLAB | 3,341 | 79 | classdef CorePrevAxesTargetSpec
% Value class holding just the parts of PrevAxesTargetSpec that are persisted:
% iMov, frm, iTgt, gtmode, dxlim, and dylim.
%
% Every CorePrevAxesTargetSpec in existence is fully valid: the constructor
% takes a PrevAxesTargetSpec, a single struct, or name-value pairs, and
% ... |
c1efe73e65f9c325984a41e5f928716378f221d6cb09f536707a26067b4d9d6f | MATLAB | 3,342 | 94 | function plot_kappVsNoise(vcf, summaryInfoTable_raw, devMeasure_all, kecn, kselPercNtr, kselPerc, singleEcnCol, varargin)
%% handle optional inputs (varargin):
nOpVar=0; % counter for optional variable
nOpVar=nOpVar+1; opVars.sortFlag = []; defaultValues{nOpVar} = 0;
nOpVar=nOpVar+1; opVars.limNoisePlotFlag = []; defa... |
8c41b808b9643c754d7390e549da560ece05e90d0777fc07e79a477db9fc691b | MATLAB | 3,343 | 94 | function CBIG_Plot17NetworksCorrMat(fig_num, corr_mat, xhemi, yhemi, clow, chigh, color_map)
% CBIG_Plot17NetworksCorrMat(fig_num, corr_mat, xhemi, yhemi, clow, chigh, color_map)
%
% This function is used to visualize 17 network correlation map. Values
% less than or equal to clow map to the first color in the color_... |
8051c5ba367fd46e71eb7b847f0c65b98833f581a6c1ae5248a1dbc6407438b0 | MATLAB | 3,346 | 67 | function OutputImage=CoordinateImageAdjustments(InputImage,TranslationParams,RotationAngle)
% InputImage=TestImage;
% TranslationParams=[Grouped_Data(RecordingNum).Verified_Quantifications.STORM_AZ_Struct_AZ_Domain_AlignmentParams(Pair).ChannelData(Rotate_Centering_Channel(ClassIndex)).Offset(1),...
% ... |
493f659a4c443f3bcf1e32d1787dda045db951b556b17229da1ff73a7b0f71ec | MATLAB | 3,347 | 78 | function [lpffdCensoredVolumes] = lpfFDcensoredVolumes(MPs,TR,LPF_FD_Threshold)
% This function returns a logical vector denoting which volumes are
% targeted for removal using GEV-DV based on input time series, a gray
% matter mask in the same space as the input time series, the TR (for
% low-pass filtering)... |
99770bcca7bc9021ab6b77a6096f862e275c9b32d80b14b46da4ad8a6b978053 | MATLAB | 3,349 | 102 | function pairsOut=View_Clear_Brain_ROI_Corr(Anat,IM,M,Pnn,Proi,C,Pmax,params,g)
%
% This function draws ROIs on the brain and connecting rods colored by sign
% of correlation values in C. This can be the fc correlation itself if that
% is passed, or it can be the correlation of brain fc with behavior if that
% matrix... |
f6d0944109543ad73540ba374ca0ce80fd48e8b898f8271d7519b85178e9d735 | MATLAB | 3,349 | 108 | %% PLCA/svm analysis
[first2PCs,analysisInfo] = PCA_DN_analysis(300,true);
%% PCA/svm stability analysis
% eq. weight thresholds
thresh2Cons = [0,50,100:100:1700];
% initialize vectors
nThresh2Cons = length(thresh2Cons);
PCexplained = zeros(nThresh2Cons,3);
CVLoss_type = zeros(nThresh2Cons,1);
CVLoss_LR = zeros(nThres... |
27de01bc8c44cf666a71962e92e047b68c8aa2309a90f47e3d792cacc26de5e6 | MATLAB | 3,350 | 64 | function selected_color = color_picker_4(object_type, data_dir)
% COLOR_PICKER_4 assigns all colors to be plotted in a synthetic image.
% Each object should have a representative color, a distribution, or
% alternative data to support color selection.
% In this version, color are randomly selected from Excel spreadshe... |
7a6b8da01d2eadc7bf8e07aefa46628d463ca2745cdb513ae39e877967cd6bdb | MATLAB | 3,350 | 134 | %% PCA test set reconstruction error vs likelihood as K increases
% Show that reconstruction error on test set gets lower
% as K increases for PCA, but likelihood for PPCA has U shaped curve
%PMTKslow
%%
% This file is from pmtk3.googlecode.com
setSeed(0);
if 0
loadData('olivettiFaces');
% 0 to 255, from http... |
c4ada90d553938d16bada280351fe8656439b117392d3239667d16d27145396c | MATLAB | 3,350 | 100 | function [UnitIDs,UnitLabels] = FindInterestingUnitsAction(TaskLabel,varargin)
%ISINTERESTINGUNIT Returns list of "interesting" units.
[varargin,PThresh]=Utilities.ProcVarargin(varargin,'PThresh',.001);
datafile = fullfile(env.get('results'),'FaceScratch','SUAnal',[TaskLabel '-Go'],'PopData','p1-AllDays.mat');
... |
bab78e709727f29b4392f6e11bd2d99670288074096d5de80a3da30d8bad17b5 | MATLAB | 3,351 | 92 | function statsfun = statsfunhelper(inp1, inp2)
% Helper tool to create a statsfun for the options structure of solvers.
%
% function statsfun = statsfunhelper(name, fun)
% function statsfun = statsfunhelper(S)
%
% Usage with (name, fun):
%
% Input 1: name is a string which is a valid field name (no spaces, star... |
49d43564f5b4eb77c6bd844d112baebd60fd3efee5b4968c719fea01148f2751 | MATLAB | 3,353 | 120 | function [imp_i RT] = BA2json(cfg)
% <*LAN)<]
% v.0.1
%
% BA2jsonwrite to _chanels.tsv
% _electrodes.tsv files
% [imp] aditional imput for impedance to bluid _electrode.tsv (see BVpoint2txt)
% BA2json(cfg)
% cfg.
% filename = 'sujeto.eeg'
% elec_name = {'Cz', ... |
bb51386e2f02a33b33e0b3ab7999c7e01e660ef78b21e4c4db268cdbcc07797d | MATLAB | 3,353 | 102 | function [ppt_marker_summary, cluster] = getMarkerSummary(paths)
config = load_config(paths, paths.name);
config = config.config;
step = 'fcp1';
% check for matched MRI and MEG data
subj_match = ds_pid_match(paths,step);
ssSubjPath = @(x) paths.(subj_match.pid{x});
% initialize output files
getMark... |
558f2f5e0bec42fb9f3afe592262414253322b1e3dc9a8b518c4e3f0d2ae0226 | MATLAB | 3,354 | 134 | % This function runs the regression, filtering and rectification steps to
% the functional data series
% 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 future... |
8f17d773c437a204a7eee856860c013ef518bd50877f8917a9f507443b41a89c | MATLAB | 3,354 | 87 | function [eid,emsg,varargout]=statgetargs(pnames,dflts,varargin)
%
% needed to copy this function because it was in the private folder of
% the stats toolbox
%
%STATGETARGS Process parameter name/value pairs for statistics functions
% [EID,EMSG,A,B,...]=STATGETARGS(PNAMES,DFLTS,'NAME1',VAL1,'NAME2',VAL2,...)
% acc... |
940f2a5104708f4aa79071da407d2eed64e0306363c80c7dc7066a5509aabf26 | MATLAB | 3,354 | 129 | %% Plot the full L1 regularization path for the prostate data set
%PMTKauthor Mark Schmidt, Kevin Murphy
% This file is from pmtk3.googlecode.com
clear all
load prostateStnd
[N,D] = size(X); %#ok
wOLS = X\y;
tmax = norm(wOLS, 1);
%% First use LARS
wLars = lars(X, y, 'lasso');
%lambdas = recoverLambdaFromLarsWeight... |
036709293331d45ec0f9d904d946fa19f1343f458d7a46b27f7e9c5647e91d95 | MATLAB | 3,355 | 69 | function mat=firstlevel_4d(data, out_path, TR, model_deweight_path)
%%model specification
matlabbatch=[];
matlabbatch{1}.spm.stats.fmri_spec.dir = {out_path};
matlabbatch{1}.spm.stats.fmri_spec.timing.units = 'secs';
matlabbatch{1}.spm.stats.fmri_spec.timing.RT = TR;
matlabbatch{1}.spm.stats.fmri_spec.timing.fmri_t = ... |
3418c30d0586da1cd2ed4cde5d7774e86fa5b529e3728e26b6122810711727b1 | MATLAB | 3,355 | 134 | function model = parcs(x,M)
% PARCS: Paired Adaptive Regressors for Cumulative Sum, Algorithm 1, as
% described in Toutounji and Durstewitz (2018) Front Neuroinform.
% Please refer to 10.3389/fninf.2018.00067 for details
% INPUT:
% x: time series matrix of size TxN
% M: number of change points
% OUTPUT:
% model: PAR... |
779307fc720332f594f8e6e2dd61267186752876ba93e5614569feb4866daa0b | MATLAB | 3,355 | 121 | function varOptBarber()
% Variational Optimisation
% https://davidbarber.github.io/blog/2017/04/03/variational-optimisation/
% f(x) is a simple quadratic objective function (linear regression sq loss)
% p(x|theta) is a Gaussian
function out=E(W,x,y)
out=mean(0.5*(W*x-y).^2);
end
function [g,G]=gradE(W,x,y)
G=repma... |
e2fc5e73fe3fd2e91b9de2832cccf1e213948330931607911cb2b8b713bfff71 | MATLAB | 3,355 | 109 | function [e p st] = improve_mesh_use_stellar(e, p, opt_params)
% Use Stellar to improve mesh quality. Note that this routine will add more
% nodes/elements to mesh and hence alter it.
% Therefor no material/region property can be used after this routine is
% done.
if size(e,2) < 4, error(' Can only handle tetrahedral ... |
3c0f04616c9ac5f4be14db2cbcd2f4c5bca07b2684344e50419196dce3418bee | MATLAB | 3,356 | 121 | function [leg0,gradleg]=legs_n0(x,dir,n,type)
% usage: [basis,gradbasis]=legs(x,dir,n,scale)
%
% returns the values and directional derivatives of (n+1)^2-1 basis functions
% constructed from spherical harmonics at locations given in x and, for the
% gradients, for (in general non-normalized) directions given in dir... |
48cc31197552451da6ad4953081148715e2d23c3b84c22040da5c0e591853ece | MATLAB | 3,356 | 142 | function [out, varargout] = vocoder(in, fmin, nbch, erbscale, Fs)
% out = vocoder(in, fmin, nbch, erbscale, Fs)
% out is tone vocoded using a gammatone filterbank
% envelope filter cutoff @ 64Hz
% in: In signal
% fmin: Minimum frequency of the filterbank, 1st center frequency
% nbch: Number of channels
% erbscale: Filt... |
750151c0977be192255ee2607253fe07b7086fe4cd2f96d56135988c028e8565 | MATLAB | 3,357 | 68 | function lan_fill_gui(LAN)
% LAN.nbchan = size(LAN.data{1}, 1); % static
% LAN.pnts = size(LAN.data{1}, 2); % static
% LAN.trials = 1; % static
% LAN.name = '';
% LAN.cond = '';
% LAN.group = 'iEEG';
% LAN.srate = 512;
% LAN.unit = 'uV';
figure('name', 'Fill specifications', 'position', [450 400 300 450]);
str = mat2s... |
82f869441d42695ca07f59f0f5e5c662e80840919d10528373d04b3d9adcd614 | MATLAB | 3,357 | 89 | function [W,output] = boundOptL1overrelaxed(X, Y, lambda)
% Fit the weights for L1 penalized multinomial logistic regression via
% overrelaxed bound optimization in O((cd)^3)) where c is the number of
% classes and d is the number of dimensions.
%
% Inputs:
%
% X nexamples-by-ndimensions
% Y ne... |
b963505d571a9655e3eeaeb9dd0d64790d4988c3ff995f071bfa1b07e1667309 | MATLAB | 3,358 | 86 | function CBIG_AuthorTopic_ConvertBrainImagesToCVBData(dataDir, cvbDataFile)
% CBIG_AuthorTopic_ConvertBrainImagesToCVBData(dataDir, cvbDataFile)
%
% Convert binary-smoothed brain images of activation foci to data input
% for the Collapsed Variational Bayes (CVB) algorithm.
% The binary-smoothed brain images are produce... |
e27bdaa664ad575d366c1a259b2a7b9e649d80e7e76aae39ae176bd9f5a9caa8 | MATLAB | 3,361 | 146 | function [options] = prepare_fullDCM(A,B,C,D,TR,microDT,homogeneous,hA,hB,hC,hD,sources)
% precalculates intermediary variables for the VB inversion of DCM for fMRI
% function [options] = prepare_fullDCM(A,B,C,D,TR,microDT,homogeneous)
% IN:
% - A: binary matrix indicating where the connections are
% - B: cell-arra... |
8549c37599f5cc60117c1b18dede02ec1e635d336935da03c775b4f6d1c475fa | MATLAB | 3,362 | 95 | function [stepsize, newx, newkey, ssstats] = ...
stepsize_sg(problem, x, d, iter, options, storedb, key) %#ok<INUSD>
% Standard step size selection algorithm for the stochastic gradient method
%
% Given a problem structure, a point x on the manifold problem.d and a
% tangent vector d at x, prod... |
4b451563ca12b79ff5630f997edcafd36005606b620ef08727be9284c73123c5 | MATLAB | 3,363 | 87 | function ft_postamble(cmd, varargin)
% FT_POSTAMBLE is a helper function that is included in many of the FieldTrip
% functions and which takes care of some general settings and operations at the end
% of the function.
%
% This ft_postamble m-file is a function, but internally it executes a number of
% private scripts ... |
70afac3efb9c9d93a6cad5acb958ccb60d1d0e252885028413fa0c2505aa2cca | MATLAB | 3,363 | 123 | function [Iphi,SigmaPhi,deltaMuPhi,suffStat] = VBA_Iphi_UNL(phi,y,posterior,suffStat,dim,u,options)
% Gauss-Newton update of the obs. parameters, for un-normalized likelihoods
if options.DisplayWin % Display progress
try
STR = 'VB Gauss-Newton on observation parameters... ';
set(options.display.hm... |
97f32d7d536e8922d878e3d5d83f965ec543e4be9e11b3a749efd341701532db | MATLAB | 3,363 | 110 |
clc, clear, close all
workDir = getenv('bodyDir');
cd(workDir)
% Folder with the raw mkv files from the Azure Kinect Camera
dataDir = 'Raw\';
% Subject or participant or test folder.
testDir = 'test';
%
targetVideo = 'FULL PATH TO TARGET MKV';
targetData = 'FULL PATH TO OPENPOSE MAT';
vide... |
a0db99ccbca9bab8f975d65ff3a81d67d69ef3c8198d3e70c68bb7d2c16858ea | MATLAB | 3,363 | 98 | classdef SceneReader < matlab.mixin.SetGet & dynamicprops
% DatasetReader Read Imaris ims file Surpass Scene information
%
% © 2015–2016, Peter Beemiller (pbeemiller@gmail.com)
%
% See also ImarisReader
properties (SetAccess = 'immutable', GetAccess = 'public', Transient = true)
... |
ee2a60feaa854ef76368849369751d65d3bad0b091a19519512bac72d209651a | MATLAB | 3,363 | 107 | clear
close all
clc
%% Select measurement rate (MR): 0.25, 0.10, 0.04 or 0.01
mr = '0.25';
mr_str = mr(3:end);
fprintf('Measurement Rate = %s \n', mr)
%% Initializations
% Dataset for testing
test_images_dir = './test_images';
test_images = dir(test_images_dir);
test_images = test_images(3:end);
o... |
0789703dcdee8f1ad785bada44d7971464825af482f4e1255fc8e6fa0b6dadf9 | MATLAB | 3,364 | 119 | %% Get Prediction Matrices
% Segregated function for calling and evaluating the different predictions;
%
% Used as a single common method to call and create these elements;
%
function H_Struct = getPredictionMatrices(sdo, xtdc, ppdc, XT_CH_NO, PP_CH_NO, vars)
arguments
sdo % either sdoStruct, sdoMat, sdoMultiMa... |
09016a7cb5b4aed53107cc76f3165cd9c92aaa2d2521ca3153d03dd2b6413249 | MATLAB | 3,364 | 127 | addpath('../generic/');
addpath('../analysis_reclassif/');
%%
[t, TIN, TOUT, EC, EI, CHOICE, RT, COH, SESSION] = get_and_prep_data();
%%
X = {EC-EI};
Y = {TIN};
XLABEL = {'Time, M_{in}^{contra}-M_{in}^{ipsi} [s]'};
YLABEL = {'Time, T_{in} [s]'};
for k = 1:length(X)
p = publish_plot(1,1);
set(gcf,'Position... |
91b04cd22f854a7f4e7f8e0c4c393892aae537031d14bca97b3c2dcc1e79520b | MATLAB | 3,364 | 101 | function [Matrix_Coeff,Reconstruction,Residual,Error,dError,Max_Coeff] = Snake_kSVD_reconst(Data,Dictionary,NoAtoms,Overlap,sdRemoved,draw)
if nargin==5
draw = 0;
elseif nargin==4
draw = 0;
sdRemoved = 4;
end
% Initialize Parameters
counter = 0;
counter... |
84919d05a7889eebfd9e25b9fe4cd24c482c6568a43f6ee9b15a02f653f1c4b6 | MATLAB | 3,366 | 129 | %% Sparse linear regression with EM on biscuits data
% PMTKreallySlow
%%
% This file is from pmtk3.googlecode.com
loadData('biscuits');
ings = [1:4]; % fat, sucrose, flour, water
for dim=1:length(ings)
ing = ings(dim);
Xtrain = A_train;
Xtest = A_test;
ytrain = y_train(:, ing);
ytest = y_test(:, ing);
[N,D] = s... |
1758661c74e683ce3b6e89a5a7498b756e2b372311842b2910a4b58335dd0d82 | MATLAB | 3,367 | 92 | %%
%This code is to clean the bad functional data after you know your final dataset
%This assumes you have already run main_just_for_movment.m and count_repairee_acc_update.m.
filenm='final_sample.xlsx';
%This is your data_to_keep excel after you screen the repeated runs (based on your criteria, say mv, acc, or bo... |
07f5c7aea91e4f2ec4ee69675e37b077f43c3519f53f18f5992d0a578200e163 | MATLAB | 3,368 | 78 | function params = CBIG_AuthorTopic_EM_InitParams(exp_acts, paradigm_by_exp, params)
% params = CBIG_AuthorTopic_EM_InitParams(exp_acts, paradigm_by_exp, params)
%
% Initialize parameters of the author-topic model
%
% Input:
% - exp_acts = D x 1 cell where D is the number of experiments
% ... |
3e4e19a7f1b53a0e84ef9811c7572523b7ff58749811fa51a5b6634ee1c2bde0 | MATLAB | 3,370 | 94 | %% Plot figure 7
function figureOut = PlotFigure7( OA_xhat, control_xhat, OA_x, ...
control_x, ivls, figNr)
% 1. Compute median, upper and lower quartile across simulations
% 2. a) Compute median of median within each specified interval
% 2. b) Compute error bars as median of median p... |
ea5ac2205367010c64bf20b106aa7d4cda31fba6d1411db7ddb099009b7c2322 | MATLAB | 3,370 | 73 | function [ titleStr, settings, results ] = dspace_moduleFcn_template( dataview, settings )
% Use this as a starting point for new module functions.
%
% Dataspace-Module functions are Matlan functions that can be called with 0, 1, or 2 arguments.
% Depending on the number of input arguments the behav... |
f17f810893cdd351b13c4c1a9ad53b754e16809ad0cef55bd54fa489ecef340e | MATLAB | 3,371 | 111 | function events = wlProc_getEvSegmentsByComparing( ...
databigger, datasmaller, samprate, threshfactor, maxglitch, maxdrop);
% function events = wlProc_getEvSegmentsByComparing( ...
% databigger, datasmaller, samprate, threshfactor, maxglitch, maxdrop);
%
% This function identifies the location of events in a data... |
31a3dc066cb792a38aef3fc57c63994acfd3dd1d2efd7d303fa3830b6c59a458 | MATLAB | 3,372 | 113 | %ISOLATE_AXES Isolate the specified axes in a figure on their own
%
% Examples:
% fh = isolate_axes(ah)
% fh = isolate_axes(ah, vis)
%
% This function will create a new figure containing the axes/uipanels
% specified, and also their associated legends and colorbars. The objects
% specified must all be in the same f... |
9debadf3a41f66d190a6012c1498160034ffb2a2381622807f6c5104d096e417 | MATLAB | 3,373 | 83 | %% SAT - app_input ::
%% determinePpFileType
% Name: Phone Kyaw
% Date: 09/19/2024
% Description: Return a pp_cell when a user inputs PP files
% Parameter: None
% Return Value: pp_cell - Nx1 cell array where each row contains Mx2 cell for
% each trial (N = Trials, M = No. o... |
061c85a9fd1b1e20e79ee0e559ce6e7b3a20f68eb1ce7fd37ba52ac852616302 | MATLAB | 3,374 | 54 | classdef CBIG_MMLDA_unit_test < matlab.unittest.TestCase
% Written by Nanbo Sun and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
methods (Test)
function test_example(testCase)
% create output folder
CBIG_CODE_DIR = getenv('CBIG_CODE_DIR');
... |
42399116b899b7c86d75fe9cf3377b030f698f3db32a28893fb924ff75e9bbbc | MATLAB | 3,375 | 182 | %%% ERROR_ANALYSIS
%%% This simulation helps coputing the acturacies of calibration
%%% Run it after the main calibration
N_runs = 200;
%N_ima_active = 4;
saving = 1;
if 1, %~exist('fc_list'), % initialization
% Initialization:
load Calib_Results;
check_active_images;
fc_list = [];
cc_list ... |
1c12fc5a0ce33347cca3d878bcb83ee7c08345fcad694b7ed254f3a5bb26a7da | MATLAB | 3,376 | 130 | function out = CP_Run(S,vid)
%% Unload variables
[ t,t_lim,f,div,uprd,uprt,s, ...
NEUR,N2M,K,PART,ALPHA,updm,RES,MOV ] = structvar(S);
[X,Y] = meshgrid(1:div);
N_neur = size(NEUR,1);
% UPR tracking
UPR = zeros(1,1+N_neur);
WB = waitbar(0);
clear S;
%% Body
while t<t_lim && sum(PART,'all')
for n=... |
d5cb50e46829f7627c6cfb3fea7f97422ce67a76222fea027a6568559fd1da07 | MATLAB | 3,376 | 82 | function Cfg = y_GenerateQCHTML(Cfg)
% function Cfg = y_GenerateQCHTML(Cfg)
% Generate QC HTML file based on results by fmriprep.
% Input:
% Cfg - DPARSFA Cfg structure
% Output:
% see /QC.
%___________________________________________________________________________
% Written by YAN Chao-Gan 190915.... |
d8ace9f09a56e0ec25a909e712ed14a0eaf2623472fc610febd49e212ca832c6 | MATLAB | 3,376 | 85 | %-----------------------------------------------------------------------------------------
% Decoding performance as a function of the neuron count included in the
% analysis
%
% Kehl et al. 2024 (DOI:XX)
% Single-Neuron Representations of Odors in the Human Brain
% Figure 2c
% Author: Marcel Kehl
% License: MIT Lic... |
dc9275ac6b75c61e97c970997e218f9ef07b18816069905b1660fe6e23ff9a9c | MATLAB | 3,377 | 99 | function h=holder(tfr,f,n1,n2,t,pl)
%HOLDER Estimate the Holder exponent through an affine TFR.
% H=HOLDER(TFR,F,N1,N2,T) estimates the Holder exponent of a
% function through an affine time-frequency representation of it,
% and plots the frequency marginal and the regression line.
%
% TFR : affine time-frequency r... |
ede0db29d0364ea98c02d1797ce0fc3578c18a407282c2d8e9af12a08dfb8051 | MATLAB | 3,377 | 73 | %%
%NOTE - x axis in Figure 8c of the manuscript should be labelled radius, not diameter - this has been updated in this script
%%
clear all
%%
%Define Parameters
[opt] = ParameterOptions();
%%
%Modify default parameter options
opt.Precision=10^-10; % Cut off for pathway amplitudes
opt.nPeriods=2; % Ma... |
ea37255407cf1af1f570749938b7c535d484adf07f6070982711f8cc8d3433ce | MATLAB | 3,378 | 119 | function [D0,phisq0,st] = lme_fit_FSinit(X,Zcols,y,ni,e)
% [phisq0,D0,st] = lme_fit_FSinit(X,Zcols,y,ni,e)
%
% Starting values for linear mixed-effects estimation.This function is
% intended to be used to provide starting values for the lme_fit_NR
% function by mean of some initial iterations of the Fisher scoring a... |
455b3f0e5bfc82089e993a0cd8e6d469e19dfbcb462e9aa6e4e85b999a407300 | MATLAB | 3,379 | 95 | % FADE-SAME: Figure 5
% clear
% close all
%%% Step 1: load data %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% set results files
FADE_files = {'../FADE_scores/FADE_SAME_scores_2021_01_11_ref_FADE.xls';
'../FADE_scores/FADE_SAME_scores_2021_01_11_ref_yFADE.xls'};
% load results files
num_files... |
8e6637903ccc702f9b104d3202b499723fd6a86f7524a93481372128c95ddc05 | MATLAB | 3,379 | 109 | function folds = cvfolds_FK(Y,family,CVscheme,allcs)
% allcs can be a N x 1 vector with family memberships; an (N x N) matrix
% with family relationships; or empty.
% If family is 'multinomial', it will stratify the estimation
% Diego Vidaurre
%
% adapted to randomise folds taking family structure into account
% NOTE: ... |
d62547c827b4e7146c5b48bf00e5b0742732cde3c3280af8558bd0d1e735d820 | MATLAB | 3,379 | 140 | % 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,... |
997d7704296e3e36aa36539e416881b75c2da6a11070b7c77b5aee7be26fc2c8 | MATLAB | 3,380 | 105 | %% lasso on polynomial regression
%
% This file is from pmtk3.googlecode.com
ns = [21];
for n=ns(:)'
setSeed(0);
[xtrain, ytrain, xtest, ytestNoisefree, ytest, sigma2] =...
polyDataMake('sampling','thibaux','n',n);
deg = 14;
addOnes = false;
if ~addOnes
% To avoid the need to add 1s to X, let us center the resp... |
947c7751365d843fc00f3b51930d40e045bc29d9c4f6d74b3f7d524996cc7067 | MATLAB | 3,382 | 104 | function [mappedX, mapping] = lltsa(X, no_dims, k, eig_impl)
%LLTSA Runs the linear local tangent space alignment algorithm
%
% [mappedX, mapping] = lltsa(X, no_dims, k, eig_impl)
%
% The function runs the linear local tangent space alignment algorithm on
% dataset% X, reducing the data to dimensionality d. Th... |
b91e098cc5f778166a14afd60a8926137446a7c0f0e968a68740c8813c5a18cb | MATLAB | 3,382 | 130 | function [p,out] = corr_with_RT_choice(choice, RT, coh, times, dv, dv_mediator, minRT,maxRT, start_t, end_t,do_plot,flags)
if do_plot ==0
p = [];
end
%
norm_to_se_flag = flags.norm_to_se; % testing
%
filt = RT>minRT & RT<maxRT;
ucoh = nanunique(coh);
% residuals
dv_res = nan(size(dv));
dv_res_choice = nan(siz... |
f81fa964cc88da4fa53b93bd6cc6f36726d1c7c6a01916abc089a3f02943a079 | MATLAB | 3,383 | 103 | %% Main function to generate tests
%
% These tests can be run from the command window with "runtests myTests"
% while in the test folder, or with "runtests("test/myTests.m")" from the
% project folder
%
% Capture the results by saving the output: e.g. testResults = runtests("test/myTests.m")
%
% See different types of ... |
02bb10d775b432c1dd94097c495e67708c37638cb2e19ea2b4a75238045287e1 | MATLAB | 3,384 | 107 | clear all;
path0=pwd;
path2=[ '../../Nonequilibrium'];
addpath(path2);
for FLAG=1:4
FLAG
indexN=[1:31 50:80];
N=62;
Tau=2;
NSUB=176;
% Parameters of the data
TR=1; % Repetition Time (seconds)
% Bandpass filter settings
fnq=1/(2*TR); % Nyquist frequency
... |
f6684dc1040d87120f7edc680f4051d6988231c00e115eb79d07e329937ca411 | MATLAB | 3,385 | 85 | %% computeSDO_xtDataCell_new()
% Generates a data structure for time series data ('xtDataCell'),
% pre-populated with fields used in the SDO Analysis toolkit.
%
% PREREQUSITE: None
%
% INPUT PARAMETERS:
% N_TRIALS : A postive integer, corresponding to the number of
% independent recording trials/sessions used... |
8cca69116d6ad76378e2afce7d1fcc107be8d33741b0c844dc3800e1088076fd | MATLAB | 3,386 | 117 | function saveAsJSON(data, jsonFileName)
% saves the values in the structure 'data' to a file in JSON format.
% Based on the work of Lior Kirsch at: https://uk.mathworks.com/matlabcentr
% al/fileexchange/50965-structure-to-json
%
% Modification by Arthur Y.C. Liu 24/06/2020
%
% Example:
% data.name = 'chair';
% ... |
289eb60bd5277857d66db42156bea3be91b0a7b844eec097d667699ec2daea5e | MATLAB | 3,388 | 141 | % _ _
% ___ _ __ __ _| |__ ___ ___ _ __| |_
% / __| '__/ _` | '_ \/ __|/ _ \| '__| __|
% | (__| | | (_| | |_) \__ \ (_) | | | |_
% \___|_| \__,_|_.__/|___/\___/|_| \__|
%
% checks all ABF files to make sure they
% have the same number of channels, and
% that all chan... |
cf744a5bd94dbcfc7f555a25f6209d190d60e09acef6a79418682c7b879e4f4c | MATLAB | 3,388 | 111 | function detectors2vtk(mesh,output_fn,varargin)
% DETECTORS2VTK Saves detectors of a FEM mesh in NIRFAST format into a *.vtk file.
%
% DETECTORS2VTK(MESH,OUTPUT_FN) Saves detectors (MESH.meas.coord) of a FEM
% MESH in NIRFAST format into a *.vtk file. Usefull for visualization
% with e.g. ParaView.
% MESH - mes... |
be47e893ec76bb26aead743356ad8c7b5364ac002fb3689efa3130bf1ffd540f | MATLAB | 3,391 | 92 | function ort = match_seg(pl,al,bwd)
% match segmentation labels from a hemisphere to canonical layers
% obtained from the symmetrical D99 atlas.
%
% Alexandru V. Avram, Ph.D.
% NIH 2022
%
% inputs
% pl - map segmentation (left/right hemi)
% al - symmetric d99_layers segmentation (left/right hemi)
% bwd -... |
18f28e463655f33af3e49bed29001dd2ed7ef4c61f19ddc14e7010e30c997f83 | MATLAB | 3,393 | 86 | function addPaths(root)
%
%
%
%<PRE>
% This file is part of dspace-core.
%
% Copyright (C) 2020 University Zurich, Sepp Kollmorgen
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU Affero General Public License as publish... |
43b7bf0343f56eea946252f49493baddac22cd68d1ee9278b89bcbcfabf16977 | MATLAB | 3,393 | 141 | clear;
clc;
close all;
%%
warning('off');
load example_non_sinusoidal_data_v1.mat
srate = 400;
timex = linspace(-1500,0,srate*1.5);
param.plot = 1;
param.minimum_cycles = 2;
param.ovlp_threshold = 0.50;
param.frequency_axis = 1:40;
[cho_outputs] = CHO_v22(raw_data, srate, param);
%%... |
0eb0c688af5f37daabe00b4cc86fe1654e00c3bab25e92a4687d1b0d5a7cf763 | MATLAB | 3,395 | 110 | function clf = clfLdaTrain( clf, X, Y )
% Train a Linear Discriminant Analysis (LDA) classifier.
%
% USAGE
% clf = clfLdaTrain( clf, X, Y )
%
% INPUTS
% clf - model to be trained
% X - nxp data array
% Y - nx1 array of labels (or cell array, see classify.m)
%
% OUTPUTS
% clf - a trained LDA mo... |
94cda9690053ca58d2898f5fce78743a04b467e2e0d462526f5642dbe6579e4b | MATLAB | 3,396 | 109 | function h = viewClassTree(varargin)
% View a class inheritence hierarchy.
% Same args as getClasses
% Needs graphViz4Matlab
% Classes must use classdef syntax not old style
% PMTKneedsMatlab 2008
% This file is from pmtk3.googlecode.com
args = process_options(varargin,'source',pwd(),'ignoreDirs',{'unitTests',ful... |
d13e11ad183b6514725d0f2e5aaad30435035adba7d471bcf110007fa6dd4e1e | MATLAB | 3,397 | 94 | loadParameters;
if ~params.DO_DOWNSAMPLE
fprintf('Skipping downsample because the parameter file says not necessary\n');
fprintf('[DONE]\n');
return;
end
for rnd_indx = 1:params.NUM_ROUNDS
precheck = true;
for c = 1:params.NUM_CHANNELS
filename_full = fullfile(params.deconvolutionImagesDi... |
5d9af3b615b2e53db8c3d8602929df75dfd3fdcad882a02d795adaa35cb20906 | MATLAB | 3,399 | 130 | function [B,MSEs]=jisotonic(A,direction,weights)
% jisotonic - isotonic regression (jfm, may 2105)
%
% [B,MSEs] = jisotonic(A,direction,weights)
% A is the input a vector
% direction = 'increading', 'decreasing', 'updown', or 'downup'
% weights is the optional input weight vector (same size as A)
% B is the out... |
79859d8270b625d32d03862421197bda02fa065be7b3984e1dfe73392cae998c | MATLAB | 3,399 | 139 | function LAN = fftamp_thr_lan(LAN,cfg)
% <*LAN)<
% v.0.1
%
% Detec amplitud variation en fourier space
% cfg.thr = [1 0.1] (sd %spectro)
% .tagname= 'bad:A'
% .frange= [1 60]
% .cat =
% .method = 'f' or 'mt'
% ... |
d56ae59202074472ceb76eb4e6998d4840c361ce897fa917c8408109e651e4c3 | MATLAB | 3,399 | 116 | % AUTHORSHIP
% Primary Developer: Stephen Meehan <swmeehan@stanford.edu>
% Math Lead & Secondary 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
%
function [jd,... |
09415d3a55519f151b9eddfa65b33fc249c68f8cb2e3aeef2715ac7e1a11af9d | MATLAB | 3,400 | 108 | function [] = randnetPlaceFieldsManuscript(modelParam, network, opS_PF, opV_PF, opGin_PF, linfields, varargin)
% plots.randnetPlaceFields(modelParam, network, opS_PF, opV_PF, opGin_PF, linfields, ithEnv=1, ithTrial=1)
%
% Plot results from place field simulations of randnet for manuscript
%
% Inputs:
% - modelParam: ... |
73170ae090cac0af255fdeebbf6030dbc5a037bf2880f03271f588694d21894f | MATLAB | 3,400 | 97 | function mix = gmminit(mix, x, options)
%GMMINIT Initialises Gaussian mixture model from data
%
% Description
% MIX = GMMINIT(MIX, X, OPTIONS) uses a dataset X to initialise the
% parameters of a Gaussian mixture model defined by the data structure
% MIX. The k-means algorithm is used to determine the centres. The
% p... |
7dadbd57b51a74dbd6740a2f3f3dbd3825f0f731de0f8cdb5e60bd16c6f0bc1b | MATLAB | 3,400 | 76 | load('Y:\Sarah\Analysis\Experiments\Random Motorized Treadmill\behavior\gait analysis\stride segmentations\concatenated periods\FL\1087\stride_segmentations.mat')
b = vertcat(stride_segmentations{192,1}{:});
figure; hold on; for i = 1:2984; plot(b{i}); end
title('startwalk FL velocity strides');
savefig('Y:\Sarah\Anal... |
896d76d1f202d52158c74250b5048039c525ec6096bbd6daa3d12d69a8d4d354 | MATLAB | 3,400 | 128 | function [model, logev] = linregNetlabFit(X, y, alpha)
% PMTK interface to netlab
% X is n*d, y is d*1
% Do not add a column of 1s
% alpha is fixed, beta is optimized
% Computes log marginal likelihood with Gaussian prior
% This file is from pmtk3.googlecode.com
x = X; targets = y;
% Compute posterior p(w|D,alpha) ... |
04f38ee99c1f560bfef47ca2ebdf3ecc589f21a911f9efa4a5e53b92650691b7 | MATLAB | 3,401 | 108 | function signal = openOTBplus(pathname, filename, ref_exist, nbelectrodes)
%Reads files of type OTB+, extrapolating the information on the signal,
%in turn uses the xml2struct function to read file.xml and allocate them in an easily readable Matlab structure.
% Isn't possible to read OTB files because the internal s... |
d3d9b9344bee304274ee65448cdae4fd4fc1865dbab5897d273a5ef938c0e515 | MATLAB | 3,401 | 104 | % plot_singleTrials_highlights
%% Plot settings
%% Single trials Tin-c, PC1, Ramp
sess = 1; % Example trials taken from session 1
set(gcf, 'renderer', 'Painters');
% for sig = 1 : length(pltSig)
for d = 1 : length(plotSig)
dim = plotSig{d};
clear sl
assignSignal
clear rl
maxY = 0; m... |
0ea6abf352987d427839660184a3c8da6bcc39311f0379f8533012682edce0b2 | MATLAB | 3,402 | 83 | function markerParams=cookMarkerParams(markerParamsRaw)
% Take an unprocessed markerParamsRaw structure, and 'cook' it to make sure
% it conforms to the proper format.
% Process nextra_markers field
if isfield(markerParamsRaw,'nextra_markers') && ~isempty(markerParamsRaw.nextra_markers),
nextra_markers=markerParamsR... |
ff405c4cf648b98fcee76eba590c2dc7e05602dcfe756191e6be27acad3acd12 | MATLAB | 3,402 | 99 | function Draw_ROIs_Through_Cortex(Anat,ROI,Conn,params)
%
% This function will draw ROI spheres on a model of the cortical surface.
% The ROI spheres may be connected by tubes that are sized by correlation
% strength and colored by sign. The cortical surface with have a
% transparency.
% Anat is a structure that descri... |
ca0283ae539cbbf2e2d5516b1684fa026377248c2a5f091b62ece6709bb51a20 | MATLAB | 3,403 | 87 | %{
Copyright (c) 2025 Axion BioSystems, Inc.
Contact: support@axion-biosystems.com
All Rights Reserved
%}
classdef ViabilityImpedanceEvent < Tag & matlab.mixin.CustomDisplay
%VIABILITYIMPEDANCEEVENT Tag for acquiring viability data
properties(GetAccess = private, Constant = true)
Curren... |
fe88b3e32a8514f0e9954edc230c5f78669a62d91b1801f9cc41b14a9ff05de0 | MATLAB | 3,403 | 97 | %{
Copyright (c) 2025 Axion BioSystems, Inc.
Contact: support@axion-biosystems.com
All Rights Reserved
%}
classdef EntryRecord
%ENTRYRECORD Structure representing an area of data in an Axis file
%
% Type: Type of data in the associated entry. See: EntryRecordID.m
%
% Length: Length... |
8efdbd9f62a3f9c0aae0f571cecc1d0044346d178013600b6891b95f17489e49 | MATLAB | 3,404 | 110 | function tpl = set(tpl,action,varargin)
%TEMPLATE/SET Edit data stored in a Template object
% TPL = SET(TPL,ACTION,VARARGIN)
% ACTION 'root'
% ACTION 'unknowns'
% ACTION 'file'
% ACTION 'block'
% ACTION 'var'
% Copyright (C) 2003 Guillaume Flandin <Guillaume@artefact.tk>
% $Revision: 1.0 $Date: ... |
1fe58a8f32782eacaf8f4763f14f8d49aae07bc8cd5a3b69c8b7f3e94034a0ca | MATLAB | 3,406 | 101 | function result = interpSurfBiLinear(inputGrids, stack, ssGrids, ss)
% interpolate 2D data set over gridded 2D inputs
%
% interpSurfBiLinear(inputgrids, stack)
%
% inputGrids is cell array of 2D grids {X,Y}
% stack is a 2D numeric array
%-------------------------------------------------... |
0bf6149e01628f643f8a3eab102490150e912641c8f145cbd500b5535599df21 | MATLAB | 3,408 | 115 | function status = makessense(data, field)
% MAKESSENSE determines whether a some specific fields in a FieldTrip data structure
% make sense.
%
% Use as
% status = makessense(data, field)
%
% See also GETDIMORD, GETDIMSIZ, GETDATFIELD
% Copyright (C) 2018-2019, Robert Oostenveld
%
% This file is part of FieldTrip, s... |
3fe78928e94638a2b338dfc57fc57906fcc1d79fdeaa374b15fb96343cac6c19 | MATLAB | 3,408 | 94 | %-----------------------------------------------------------------------------------------
% Plot piriform neuron responding to the image of garlic
%
% Kehl et al. 2024 (DOI:XX)
% Single-Neuron Representations of Odors in the Human Brain
% Figure 5b
% Author: Marcel Kehl
% License: MIT License
%---------------------... |
790d792736ded3e742810a07cf01fe6db98ca30c1ab9826c4a052786ea169ee0 | MATLAB | 3,409 | 106 | function [A] = VBA_spm_matrix(P, order)
% Return an affine transformation matrix
% FORMAT [A] = spm_matrix(P [,order])
% P(1) - x translation
% P(2) - y translation
% P(3) - z translation
% P(4) - x rotation about - {pitch} (radians)
% P(5) - y rotation about - {roll} (radians)
% P(6) - z rotation about - {yaw} ... |
a48da7794e796812ce12859b5182b0566b7a2d81e6417c059db1dff5d7b47095 | MATLAB | 3,412 | 99 | function newdata = wlProc_calcShortLowpass(olddata, fcorner, samprate, fact)
% function newdata = wlProc_calcShortLowpass(olddata, fcorner, samprate, fact)
%
% This function implements low-pass filtering using raised cosine windows
% as FIR filters. The farthest any disturbance can propagate is the width
% of the wind... |
dcdf185c6033b6f81679e58a667f8f3bf077468f9611e348ba201eae856f30d4 | MATLAB | 3,412 | 131 | classdef ProgressMeter < handle
% This is a model class for a waitbar. Designed to be used with a Labeler and
% (optionaly) a LabelerController.
properties
labeler_
title_ = ''
message_ = ''
denominator_ = nan
numerator_ = nan
doShowFraction_ = true
isActive_ = false % maps 1-to-1 t... |
fe1856beea2d34e3e04c8a1df414cde6f74a047146605f981f0d215fa771b46b | MATLAB | 3,412 | 93 | clear;clc;
%% data
load fisheriris;
X = -meas./max(meas)*0.005*9.8;
y = species;
[unique_labels, ~, label_indices] = unique(y);
num_labels = numel(unique_labels);
one_hot_labels = eye(num_labels);
one_hot_labels = one_hot_labels(label_indices, :);
split_ratio = 0.7;
num_train_examples = round(size(X, 1) * split_ratio)... |
b1029cd5cf3f385e59b6a0cd70632ff4ca5f0568d9354c167b98a8ab4f8cd84d | MATLAB | 3,414 | 67 | function [S,f,Serr]=mtspectrumc_lan(data,params)
% Multi-taper spectrum - continuous process
%
% Usage:
%
% [S,f,Serr]=mtspectrumc(data,params)
% Input:
% Note units have to be consistent. See chronux.m for more information.
% data (in form samples x channels/trials) -- required
% params: structur... |
dd8b3299b30f353b8549d95b19a33e496a8159c0439d105bbf24145d322685b3 | MATLAB | 3,414 | 88 |
%
clear stitching_queue tform
kk = 0;
for ii = 1:size(read_file_name,1)-1
for jj = 1:size(read_file_name,2)
kk = kk+1;
stitching_queue(kk).tile_1 = [ii, jj];
stitching_queue(kk).tile_2 = [ii+1, jj];
stitching_queue(kk).res_i = tiling_info.y_pixel;
stitching_que... |
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