sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
2f889712b52e3ad82fa6118287aac8b2715a3af75add1c577c50bc4b8200b9f2 | MATLAB | 1,483 | 52 | function plot_weight
sensor_radius = 0.5;
separating = 0.4999;%0:0.1:0.5;
Lin = 4;
for i = 1:numel(separating)
[d s] = obtain_weights(separating(i),sensor_radius,Lin)
end
function [deep_weight,sup_weight] = obtain_weights(separating_radius,sensor_radius,Lin)
i =1;
deep_weight = zeros(1,... |
a2191bc152edd535e546f61178c1a92f14ba158c828c700074e4471819163cca | MATLAB | 1,483 | 35 | function msBatchMatchSegmentsBetweenSessions(dirName, distThresh)
%MSBATCHMATCHSEGMENTSBETWEENSESSIONS Summary of this function goes here
% Detailed explanation goes here
dataFolders = msBatchFindDataFolders(dirName,[]);
for folderNum1 = 1:length(dataFolders)
currentFolder1 = dataFolders{folderNum1};
... |
4db94e1d951a00939926f99b3389049610d137f822adbdb762a14e071115953d | MATLAB | 1,484 | 29 | function decoding_out = similarity_test(labels_test,data_test,cfg,model)
if isstruct(data_test), error('This method requires training vectors in data_test directly. Probably a kernel was passed method is use. This method does not support kernel methods'), end
switch lower(cfg.decoding.method)
case 'cla... |
105d573461b5db44ee8f8bc8e5b4529168d48cafe3d78712fdced534bf80e5a2 | MATLAB | 1,486 | 48 | function [x_info, num_ava] = loadSimulationRunResults(sim_string, rep_list)
if nargin == 1
rep_list = {''};
ss_str = selectSimulation(sim_string);
else
ss_str = selectSimulation(sim_string, rep_list{1});
end
% rep_list = {''};
setLoadingFunctionNames
x_info = cell(len... |
a70a4eb13a6991c36ba8874dc8314950cf1e929cd32262f18a254eefa5ad6831 | MATLAB | 1,488 | 54 | function [X] = db4idwt(coefficients, levels)
% Imitates the waverec function in wavelet toolbox.
%
% [X] = db4idwt(coefficients, levels)
%
% This is hard coded with values of the 'db4' wavelet taken from
% online resources.
% License:
%=====================================================================
%
% This is p... |
c01af9424e318b08c6dd66c3038cf2d65c1ba433170f09f6bd55b8e77deb4753 | MATLAB | 1,488 | 67 | function [shuffled idx] = shuffle(mat,dim)
% Shuffles the order of a vector or 2D matrix
%
% [shuffled] = shuffle(mat,[dim])
%
% DIM (optional, default = 1), determines which dimension to use to
% shuffle the matrix
%
% Can't deal with >2D matrices. Any suggestions?
% License:
%===========================... |
6275e6657fbc07c8621adebd4014641a6b8c6bce3c3911c3938fc43065505c0e | MATLAB | 1,490 | 43 | % function [sigma,shrinkage] = covshrink_lw2(data)
%
% Function to calculate shrinkage according to Ledoit & Wolf (2004). See
% http://www.econ.uzh.ch/faculty/wolf/publications/wellCond.pdf
%
% Maximal shrinkage is done towards the variances (i.e. the diagonal), i.e.
% shrinkage acts only on covariances.
%
% I... |
781d9ff6dc64bf4cbf7c69ab6de35b136dd9f0c6b46f6f33a33cd91edfdc9b47 | MATLAB | 1,491 | 51 | function field = field_exponentiation_inverse(field)
% function field = field_exponentiation_inverse(field)
%
% Estimates the inverse field using a field exponentiation of
% the provided field.
%
% INPUT ARGUMENTS
% field - Field to perform inverse field exponentiation on
%
% OPTIONAL INPUT ARGUMENTS
% N/A
%
% OUTPUT... |
e02c769eff226ab48809fccf1c43b792a3a4848eb8087509fa1eff3a788d8d6a | MATLAB | 1,491 | 37 | % function check_software(software)
%
% This function checks that the specified software is available (if
% additional software for cfg.software is needed at all).
%
% Internally, a persistent variable is used, so calls to the function does
% not need any time once the software has been checked.
% Kai, 2012-03-20
fun... |
cfdca810dea1da95d7cf99b661df7158222669f4ad243a09bb4dcddef5aa3c46 | MATLAB | 1,492 | 69 | function [beta, P] = robust_ar_fit( y )
warning('off','stats:statrobustfit:IterationLimit')
yf = y;
yb = flipud(y);
bic0 = 1; bic = 0;
P = 0; Pmax = 100;
beta0 = []; beta = [];
while bic0 > bic && P < Pmax
beta0 = beta;
bic0 = bic;
P = P+1;
% forw... |
dce3a57e84e360bb209f7ced96c33773d0967a05e2aa3de0c4055943bc6a3bf7 | MATLAB | 1,492 | 44 | clear all
load('.\Public data\data_social_struct.mat')
Subj_list = [1:32];
for num_sub=Subj_list %num_sub = 1:size(datastruct,2)
y=datastruct(num_sub).Social.data(:,4) .* 0.5 - 0.5;
z=datastruct(num_sub).Social.data(:,5) .* 0.5 - 0.5;
fb=datastruct(num_sub).Social.data(:,2);
isYout ... |
a545afbc44e736760f90c294949d22ebf28a1d196dd86518243fbf371a7d2136 | MATLAB | 1,493 | 52 | function [prob,a] = mdnprob(mixparams, t)
%MDNPROB Computes the data probability likelihood for an MDN mixture structure.
%
% Description
% PROB = MDNPROB(MIXPARAMS, T) computes the probability P(T) of each
% data vector in T under the Gaussian mixture model represented by the
% corresponding entries in MIXPARAMS. Each... |
f597a79dd928c60d825e0f9815b9da2c69d9b474814485b2c7016a4201a8ee49 | MATLAB | 1,495 | 82 | function RMSE = findPars_RL(x0)
%%% this function derives RMSE based on a set of RL parameters (beta, bias,
%%% w1). This functions output will be minimized through fmincon
%%% optimization process
global data
global ChanType
%%
OP_cw=[]; CP_purp=[];
OC_cw=[]; CC_purp=[];
for i=1:size(data,1)
beta=x0(... |
0f296a2e536280a4c5fa9309c4c997c0c4b88ecdd2c6c3fe7acd7752551cd8f5 | MATLAB | 1,497 | 67 | function PosSynchro_BlinkingLED(fbasename,nchannels,LedChannel,varargin)
if ~isempty(varargin)
colorvec = varargin{1};
else
colorvec = [1 3];
end
syncS = LoadBinary([fbasename '.dat'],'frequency',20000,'nchannels',nchannels,'channels',LedChannel);
tDat = (0:length(syncS)-1)/2;
epDat = thresholdIntervals(tsd(... |
2f42c76e0298e0a607e38ad7732b8cb07dabe5ac4a3a327b48b3ebf8421658b7 | MATLAB | 1,497 | 49 | function [imfStart, imfPeriod, imfAmplitude] = li_upmemd_cycle(comp, fs)
%LI_UPMEMD_CYCLE calculate cycle start point, period, and amplitude of each
% cycle from the component extracted using LI_UPMEMD
%
% $Author: Peng Li, Ph.D.
% $Date: Mar 24, 2023
%
% find local peaks and cycle lengths
hImf = hilb... |
4add8982b82894b60d7b33771023f8da7c5542204bedd366aca117ae6c91f5b2 | MATLAB | 1,500 | 53 | function unittest_optimisation_DualCoordinateDescent
% Test of optimisation functions
%
% Function: DualCoordinateDescent
%
% The function solves quadratic optimisation problems with box constraints,
% more concretely:
%
% arg min a f(a) = 1/2 a' * Q * a - e' * a
% subject to 0 <= a <= C
%
% A few such pro... |
40628885619f9015381226ce87f6f1c5492ad60147e7aac1d386e9601713ba92 | MATLAB | 1,502 | 34 | % util unit test
%
% squeeze1
tol = 10e-10;
%% special case that X is scalar
X = 12.2;
print_unittest_result('[X scalar]', size(X), size(squeeze1(X)), tol);
%% squeeze = squeeze1 for 2 elements
X = ones(13, 16);
print_unittest_result('[2 dims] no singleton', [13, 16], size(squeeze1(X)), tol);
X = ones(80, 1);
print_u... |
4eaba8b05f469e0af76500ef3c758876a117be30b654872a163643076a11b3f9 | MATLAB | 1,507 | 46 | function [status,txt] = ssh(cmd, isRunAsync)
% USAGE:
% [status,txt] = ssh([cmd, isRunAsync])
% INPUTS:
% - If no inputs provided will return true or false indicating, is ssh
% installed on this computer.
% - cmd - ssh command to run.
% - isRunAsync - when set to true will execute ssh command and ret... |
e6ec12f0cb56497e494c0ec8c972a866247d0ed515af57c63e2d1fb914181fde | MATLAB | 1,507 | 43 | % Preprocessing unit test
%
% zscore
tol = 10e-10;
% Random data
X = randn(6,10,20,30,10) + 1;
% Get default parameters
param = mv_get_preprocess_param('zscore');
%% z-scoring along dimension X should result in all mean=0 and std=1
for dd=1:ndims(X)
param.dimension = dd;
[~, Xd] = mv_preprocess_zscore(param... |
093ebea819254f062d1a3dff372037b38d995c5cb39f363ef55a46cf614ca587 | MATLAB | 1,508 | 42 | function [data, mask] = pSVR_prepare_data(data, mask, voxel_count, fwhm, labels)
% function [data, mask] = pSVR_prepare_data(data, mask, voxel_count, fwhm, labels)
%
% Prepare data for pSVR reconstruction. Get the appropriate number of
% voxels, run feature-space smoothing, adjust the format for TDT and remove
% data... |
7596005da8ceaa94fe241962160ced1c26d435f6fcce20ef7ed3e9500ea13207 | MATLAB | 1,508 | 74 |
% Investigate circularity in EC phases distribution
%% Set up the environment
statpath='/Volumes/ROBBOT/Projects/GridMagination/OfficialData&Results/3Iso/Script/06_HexadirectionalCoding/CircStat2012a';
addpath(statpath)
WorkingDirectory='/Volumes/ROBBOT/Projects/GridMagination/Tables';
%% Load Phases df
% SC 6-Fol... |
90decaba5f8c7d946d8326466c4b22a723fe7bef6318e68341d0193f344513f6 | MATLAB | 1,508 | 46 | function [data_sorted, sort_idx, sort_idx_img] = sort_data_by_activation(data, mask, sub_id, p)
% function [roi_data, roi_idx, roi_idx_img] = extract_roi_index(data, mask, i_sub, p)
%
% Sorts data based on the t-value from a SPM t-image.
%
% Input:
% - data: [n_trial, n_voxel,n_run, .n_tr] array with data.
% - mas... |
13e1638c35f521779784b29c1e26d4fcb387ea905f9e2e86e77d77085aee83fe | MATLAB | 1,509 | 49 | function demhint(nin, nhidden, nout)
%DEMHINT Demonstration of Hinton diagram for 2-layer feed-forward network.
%
% Description
%
% DEMHINT plots a Hinton diagram for a 2-layer feedforward network with
% 5 inputs, 4 hidden units and 3 outputs. The weight vector is chosen
% from a Gaussian distribution as described unde... |
b83c2807c99cfe5022af4ae3672c9cd93d29066f6d7569c2a108aadbe64ba87f | MATLAB | 1,511 | 55 | function [acts scratch] = test_bp(testpats,testtargs,scratch)
% Testing function for BP
%
% [ACTS SCRATCH] = TEST_BP(TESTPATS,TESTTARGS,SCRATCH)
%
% This is the testing function that fits with TRAIN_BP. See that
% for more info
%
% ACTS is an nOuts x nTestTimepoints matrix that contains the
% activations of the output... |
7c6f42d676aa887ce73f03654f5866c10ccbe7f536c9ec7c420518694156a21f | MATLAB | 1,514 | 33 | function [perf] = CalculateASLMap(T1rawSS_reordered_reshaped,T1rawNS_reordered_reshaped,tvalues,ivalues,T1blood)
%UNTITLED3 Summary of this function goes here
% Detailed explanation goes here
opts = optimoptions(@lsqcurvefit,'Algorithm','levenberg-marquardt');
tmax = max(tvalues);
fun = @(coeffs,ival... |
0785323662253059d90f3279e00423b162392924b621cf44b115e4c326223d0c | MATLAB | 1,516 | 58 | function lat = rateChange(data,trailInxArray,curGroup,epoch,plotOption)
% get baseline
baseline_params.SD = 20;
baseline_params.align_to = epoch;
baseline_params.time_before = 500;
baseline_params.time_after = 0;
baseline_params.smoothing_margins = 100;
response_params.time_before = 0;
response_params.time_after =... |
2fb3db27cabfefcdc8a550cb26eca8a9bf1e57de0c2d9a2f132d212c01856ed3 | MATLAB | 1,518 | 49 | function [xf] = ...
generate_gaussian_pulse( image_size, dt, T, amplitude, frequency, sigma, varargin )
% *WAVE*
%
% GENERATE GAUSSIAN PULSE generates a simple test dataset, following
% the model of a space-time separable
% Gaussian pulse.
%
% ... |
5fee3f40e4b7c17aa674b45194e7ce15be7de968bda04e34760e3c510db20975 | MATLAB | 1,518 | 44 | function [consDat, errorMsg, success] = getNoMovingEpi(datTT, fs, thre, minLenghNoMoving)
%GETNOMOVINGEPI identify episodes from 3-D accelerometer signals DATTT that
% correspond to when users do not move (less likely to be moving)
%
% INPUTS
% DATTT: 3-D accelerometer data, unit g, N by 3 timetabl... |
0c773e1281da828e8b257a84959fef7aa0d84ce56cf08896bfcc988d504ecb7b | MATLAB | 1,519 | 40 | function varargout = write_image(software,varargin)
% Typical call
%
% function hdr = write_image(cfg.software, hdr, volume)
%
% or in general
% function varargout = write_image(software,varargin)
% Write image using the software specified by software (typically
% cfg.software from decoding_defaults)
%... |
a8d8377e377d2c5358c935a1bbb6414bcd6c8bbc4c134afc207a2e4e0d931c0c | MATLAB | 1,520 | 88 | % c = str2cell(v)
% c = str2cell(v,delim[s])
%
% creates a cell array <c> from input array <v>
% seperated by delimiter[s] <del>
%
% v : a string/vector of a ML supported data class
% delim : array of delimiter[s] [def: isspace]
% v-class syntax
% ----------------------
% char 'xyz'
% other [1 2 pi]
%
% no... |
64e2b21756e14195b874c7c55a0397555b4552c8807c024f88fe5272b90cac51 | MATLAB | 1,521 | 72 | function O = set(O,varargin)
% Set intervalSet properties and return the updated object (TODO)
%
% TODO: what this function does???
%
% if 'start' is one property, 'stop' must be one, and viceversa
% batta 2001
% starting version
t = [];
property_argin = varargin;
set_start = 0;
set_stop = 0;
while length(prope... |
7dea1480081bdb5753f0fce743c1f4b0f60a99f9b138ff88766e9449391f188f | MATLAB | 1,521 | 27 | %% Load voltage recording of uncaging laser Pockels cell for each recording included in mydata
% Assumes the filename listed in each recording of my data links to a
% folder thatincldues a voltage recording .csv file
% Michelle Cahill 20240111
%%
start_dir = pwd;
condition = fieldnames(mydata);
for cond = 1:l... |
c6b1c2cd8c71c32c1e9de86fc274091082560f15f7632fd42d5ce43611389e3c | MATLAB | 1,525 | 36 | function model = passdata_train(labels_train,data_train,cfg)
% This function pretty much does nothing.
% It serves for the case in which you only want measures about the data
% (e.g. get the number of voxels ("dimension") of the searchlight/ROI or
% the covariance matrix or the like.
%
% Also set
% cfg.deco... |
0d74dfd6e3f5255a313006f5ef0039517393e52b478378620776d470d10217a2 | MATLAB | 1,529 | 50 | %% Import data from text file
% Script for importing data from the following text file:
%
% filename: /dagher/dagher11/filip/Obesity_maps/data/PLS1_geneWeights_BMI_DBM_LH.csv
%
% Auto-generated by MATLAB on 07-Jun-2022 13:21:21
%% Setup the Import Options and import the data
opts = delimitedTextImportOptions("NumVa... |
a6f61c731ce2a1fb7bc45d8a06e39f778334a32b10d81356759a1bc6e0f25214 | MATLAB | 1,529 | 74 | function [RLmodel,opt_fx_out_detail] = sx_fx_findoptim_alpha_nonoverfit(fittedpars,maxalpha)
%%%% this function stops the optimization process when it starts to diverge
%%%% to unreasanoble values (of weights and predictions errors in
%%%% particular), and hence, will lead to overfitting. In short, this
%%%% func... |
44d7c445fc5d0054cb3268b0a8c740dc8282cb89ef1b82015f09b90b791c44cf | MATLAB | 1,532 | 45 | function [DB,V,xy,chanmap,homedir]=setmeup()
%(independent of your naming of directories)
disp("Set Up Workspace");
homedir=pwd;
addpath(genpath(homedir));% add the path of all folders here
% cd('..');
cd('C:\Users\as822\Box\collab-Sinai\project-selectEPs\EEG-dataSumm\eegdata_mean');
meandir=pwd;
cd(homedir);
... |
d7c0521b0652f79af3a2af77ca51ae4824d0442c0e918b53259184eb9481a56f | MATLAB | 1,532 | 44 | function scrapFineAlignment(subjectPath)
% This function clears all fine alignment for sections of subject.
% After reslicing OCT, fine alignment needs to be recomputed from scatch.
% This script make sure fine alignments are cleared.
% INPUTS:
% subjectPath / slidePaths - can be a string containing path to subj... |
947d11c1abb007ad3a78ddaac5ace4c4ed199cc7dccd38b86bbeaed8e4641fde | MATLAB | 1,534 | 36 | function [allCountList, allAngList, trackCountList, trackAngList] = AccumulateTrackAngles(tracks, angRange, angStepSize)
if strcmp(angRange, '90') == 1
allCountList = zeros(1, length(0:angStepSize:90) - 1);
trackCountList = zeros(1, length(0:angStepSize:90) - 1);
elseif strcmp(angRange, '360') == 1
allCount... |
a6bb7ff8ed48602a1dc465bcc7821511d4a3e9f4f466f49f101d9c8d33c87d30 | MATLAB | 1,534 | 40 | function FigureB_NoParams(fileExportFolder, numA, imageAshow, vxMatShowA, vyMatShowA, relMatShowA)
imageBmasks = cell(1);
xIdxB = cell(1);
yIdxB = cell(1);
for i = 1:numA
h = figure;
dispImage = mean(imageAshow{i}, 3);
dispImage = RenormalizeImage(dispImage, .1);
dispImage(dispImage(:) == 0) = mean(disp... |
2103f5299ba93660eb41421b970f71e1a343c467fb60965b23cc5874a2d63c13 | MATLAB | 1,536 | 44 | % Wm = vsh_modified_out(theta,phi,l,m)
%
% Vector spherical harmonic funtion modified from Hill's function
% W_lm for quantum numbers l and m. Angles theta and phi should be
% given in radians.
%
function Wm = vsh_modified_out(theta,phi,l,m)
% Copyright (c) 2016, Elekta Oy
% ---------------------------------------
% ... |
5bd42051ab499dc1d9f207b29d39be0c09a646bc93c4fd57ccd196d10c10a8c2 | MATLAB | 1,536 | 51 | function stats = get_zones_stats(x, y, dff_synchronized, video_freq_Hz, frame0, zones, debug_mode)
n_zones = max(size(zones));
n_pos = length(x);
in_zones = nan(n_pos,n_zones);
stats = [];
for i_zone=1:n_zones
xz = zones{i_zone}.x;
yz = zones{i_zone}.y;
in_zones(:,... |
94d9c2c48b9e9b77d9e3d01186e101c18de90b59e75c13847fd4edb35358779e | MATLAB | 1,536 | 56 | function TrackFlowClusters(exportFolder, clusterTrackParams, diffImage, enhImage, optFlow)
%% Create folder
trackFolder = [exportFolder, 'TrackFigure', filesep];
if ~exist(trackFolder, 'dir')
mkdir(trackFolder);
end
%% Import params
pxPerMicron = clusterTrackParams.pxPerMicron;
clusterFil = clusterTrackParams.clus... |
3c782eebe9541b24f418d411a221614695fc6c91ac69e45a76f99ff542989cd6 | MATLAB | 1,537 | 36 | function decoding_out = passdata_test(labels_test,data_test,cfg,model)
% This function pretty much does nothing.
% It serves for the case in which you only want measures about the data,
% e.g. get the number of voxels ("dimension") of the searchlight/ROI or
% the covariance matrix or the like.
%
% Also set
% ... |
4e6f2c9e5b2bdd99f6882ca27f9c0323be163c50011ef1897ad3177dc6b4deb1 | MATLAB | 1,537 | 57 | function S = EPGX_BM_shift_matrices(Nmax)
% Generates shift matrices up to order Nmax for 6 component 2 pool Bloch
% McConnell case
% Layout of state vector is [F0A F0*A Z0A F0B F0*B Z0B F1A F-1A Z1A F1B F-1B Z1B ... etc]
% i.e. 6 states per n-value
%
% Shaihan Malik 2017-07-19
N = (Nmax+1) * 6;
S = zeros([N N]);
... |
96cfc0a804646b82d1286daa716f8d1e94e0e02927f74fab7f9ccfe45c480790 | MATLAB | 1,537 | 59 | function p = awsModifyPathForCompetability (p,isAWS_CLI)
%This function excepts path and output AWS compatible path.
%If p is not AWS path will modify it to be compatible with windows
%INPUTS:
% p - path
% isAWS_CLI - will this path be used with AWS CLI? if so, spaces are
% defined slightly differently. If... |
ff4658de11302fd221e085a1eb648b2c9738d160f49d241183bd3b7be9cf441c | MATLAB | 1,537 | 54 | % This script updates QA metric
%% Inputs
% Set subject path an slide/section programaticaly
lib = 'LG';
subjectPath = s3SubjectPath('01',lib); % Get latest subject path
sectionName = 'Slide01_Section01';
% Set to true to override selection above and let user select subject using
% a dialog box
if true
... |
0ba4966df89ca3bc9765cbf3c9bf2fa1672bda84e3717c392b1196dfc1910839 | MATLAB | 1,538 | 71 | function S = LoadSpikes(tfilelist)
% S = LoadSpikes(tfilelist)
% inp: tfilelist is a cellarray of strings, each of which is a
% tfile to open. Note: this is incompatible with version unix3.1.
% out: Returns a cell array such that each cell contains a ts
% object (timestamps which correspond to times at which the c... |
eef8ce7f6dce1b8a5cebe1756e538ea5bd321474d17b0d86e194fba6d438c2af | MATLAB | 1,538 | 37 | function [regFrame,dv0,cx] = return_offsets_phasecorr(frame,ops)
% Do phase correlation registration (sub-pixel with kriging) on a single
% frame using pre-calculated registration variables (ops)
% use with setup_registration_phasecorr.m
% e.g:
% [ops] = setup_registration_phasecorr(refImg)
% [dv0,cx] = return_offsets... |
18719e2ecb7478b9322c2f97de9faeb3fb668af37c715192875945e6061c0efe | MATLAB | 1,540 | 58 | % Classifier unit test
%
% Classifier: multiclass_lda
rng(42)
tol = 10e-10;
mf = mfilename;
%% for two classes, multiclass_lda should give the same result as lda
X = randn(1000,10);
clabel = randi(2, size(X,1),1);
% Get classifier params for multiclass LDA and binary LDA
param = mv_get_hyperparameter('multiclass_ld... |
e0a000490457d1a6aeae62dfd631f546cf6f47466b7a8f3b3e86ee139badea9a | MATLAB | 1,540 | 63 | function [S,shank,cellIx] = LoadSpikeData(fbasename,varargin)
% Load spikes times from a clu and res file
%
% USAGE:
% [S,groups,cellIx] = LoadSpikeData(fbasename)
%
% INPUT:
% fbasename: session file basename
%
% OUTPUT:
% S: a tsdArray of spike trains
% groups: a vector giving electrode group for each n... |
71e3eb831b9017b819699ff335b1cf7c15b969b78c7e11726a255466e0539684 | MATLAB | 1,542 | 61 | function [actives] = and_bool_selectors(subj,selnames)
% Takes in multiple boolean selectors and ANDs them
%
% [ACTIVES] = AND_BOOL_SELECTORS(SUBJ,SELNAMES)
%
% Returns another boolean vector of the same size.
%
% If SELNAMES is just a string, treats it as a cell array
% of length 1
% License:
%======================... |
4cc16dc596f490e0bfcfafab4abeac9e00a8e9e0bfac9df78028f0a388a815fa | MATLAB | 1,543 | 46 | % Vm = vsh_modified_in(theta,phi,l,m)
%
% 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.
%
function Vm = vsh_modified_in(theta,phi,l,m)
% Copyright (c) 2016, Elekta Oy
% ---------------------------------------
%
%... |
8273916266b64154a042ef0c1b3d758b15a3d30dedafaaedb04349d94f0be6b3 | MATLAB | 1,544 | 32 | function gamma_fit_arr = consolidateGammaFits(x_reps_uf1, eps_ind_trace, eta_ind_trace)
gamma_fit_arr = cell(length(x_reps_uf1)+1, length(eps_ind_trace));
for i_xra = 1:length(x_reps_uf1)+1
for jj = 1:length(eta_ind_trace)
if i_xra > length(x_reps_uf1)
g_fit = x_reps_f1.all_gamma_pfit{eps_ind_t... |
6bfc78b6dfe01857733265548794c73129da91a6ca9b244833d79b2078de942f | MATLAB | 1,545 | 61 | function [trajectory] = generate_trajecotry(behav,tsdata,Lap,Cam0,Cam1)
%GENERATE_TRAJECOTRY
% produce time-dependent coordinates of animals movement
data1 = tsdata.data;
ts0 = data1(data1(:,1)==Cam0,:);
ts1 = data1(data1(:,1)==Cam1,:);
ts0(1,3) = 1;
ts1(1,3) = 1;
m = size(ts0,1);
% m1 = size(ts1,1)... |
97f50b63554907a5bfe11edaed8e8a091dc788cfecb21dcb601658425d7b4c4a | MATLAB | 1,545 | 53 | function st = loadStatusReportByLibrary(libraryNames)
% Loads status report generated for each library (from nightly blild) and
% loads it to one st. see generateStatusReportByLibrary for full information
%
% INPUTS:
% libraryNames - can be a string or a cell containing library names.
% Examples: 'LA' or... |
7edd0f1599bdee6e9e0422a63f64069921d4fa9f16bcb9e12be1719f418c9405 | MATLAB | 1,547 | 58 | % makegaussfir for 1D smoothing
%
% gwin = makegaussfir( sd, Fs )
%
% sd Gaussian SD [sec]
% Fs sampling rate [Hz]
% 26-dec-12 ES
function gwin = makegaussfir( sd, Fs, support )
n = 2 * floor( sd * Fs / 2 ) + 1; % make odd
if ~exist( 'support', 'var' )
support = 6;
end
switch length( sd )... |
da474cb8c61dfdb1881f8494f6418b3c7b59b0ce6ddd54c4096b6760a8c5ee92 | MATLAB | 1,550 | 46 | function stdshade(amatrix,alpha,type,acolor,F,smth,r)
% usage: stdshading(amatrix,alpha,acolor,F,smth)
% plot mean and sem/std coming from a matrix of data, at which each row is an
% observation. sem/std is shown as shading.
% - acolor defines the used color (default is red)
% - F assignes the used x axis (default... |
437e41ee451833416403ce99e9f14161f649abdb64408ae7c70ea6ec2dbf45f1 | MATLAB | 1,551 | 48 | function Image4_WholeImageWithOutlines(imageExportFolder, fileParams, flowFigureImageParams, imageA, xIdx, yIdx, numMicrons)
%% Check exist
fileName = 'WholeImage_WithOutlines.png';
%% Import parameters
% File Params
pxPerMicron = fileParams.pxPerMicron;
% Flow Figure Params
frameNum = flowFigureImageParams.frameNum... |
d76bf58fa4ca4f1f7f30976074a0e9e2104a768d41d17289679770f3353de5ee | MATLAB | 1,551 | 44 | function [sequence, mask, correct_flow] = read_yosemite
% [SEQUENCE, MASK, CORRECT_FLOW] = READ_YOSEMITE
%
% Read 15 frames from the Yosemite sequence. These are originally
% numbered yos2--yos16, with the correct flow being known for the middle
% frame yos9.
%
% SEQUENCE - 252x316x15 array with gray values.
% MASK... |
1b188e09c0d26911dc8d2890a4bbd380df74e52873298e8654fc628397c04680 | MATLAB | 1,553 | 40 | function [t,x,ie] = simInterneuron(K,params,x_0,T,dt,shift,sigma_noise)
%SIMINTERNEURON K, params, x_0, T, dt, shift, sigma_noise
% Simulates coupled populations of N interneuron models.
% K coupling matrix (N x N non-negative matrix)
% params model parameters (structure)
% x_0 initi... |
f676b8812aa62908b73c1e6403fc7369da5f950df9f9390fa5a28f947cdcb168 | MATLAB | 1,553 | 37 | function R = getRegularization(B, I)
% ************ Eye fit: first to get scaling for kPE (kEP*kPE = PF)**********
R = struct;
R.reg_weights_eye = [I.scale_EH*(1:nnz(B.bEH_maskE)).^I.reg_exp ...
I.scale_EP*(1:nnz(B.bEP_maskE)).^I.reg_exp_EP];
% Get mask where coeffients switch from one filter to another
n_eye = le... |
089262b80959fd37f43b99cb051061a40d1eeff8258c6a62551cd91d768a6c58 | MATLAB | 1,555 | 54 | function [acts scratch] = test_svm(testpats,testtargs,scratch)
% Testing function for SVM
%
% [ACTS SCRATCH] = TEST_SVM(TESTPATS,TESTTARGS,SCRATCH)
%
% This is the testing function that fits with TRAIN_SVM. See that
% for more info
%
% License:
%=====================================================================
%
%... |
3003cbbddec762f590fef03b09c0d6da3d0db3c89c7339470210aae31a4f0a4a | MATLAB | 1,555 | 60 | %% Plotting Example Neurons FEF and FEF traces
%% FEF Traces
load('V4_FR_egNeurons_select_dat.mat')
load('V4_FEF_egNeurons/V4_quad.mat')
bins{1} = 1:31;
bins{2} = 36:48;
% units = [1, 21];
qid = input('quadrant: ');
if qid == 1
units = 1;
elseif qid == 3
units = 21;
end
cnt=1;
for iWindow = ... |
cd0a825495b173c1288b787f643a272a840be5d39ec5726692f957d17200f7e0 | MATLAB | 1,556 | 55 |
ndip = 20;
snr = 0.9;%[0.6 0.5];
snr2 = 0.9;%[0.5 0.8];
amp = [0.4 0.5 0.6];%[0 0.2 0.3 0.4 0.5 0.6 0.7 0.8];
phs = 2.*pi.*[0 1/17 2/17 4/17 8/17];
patchsigma = 0;
N = [50 150];%100;
state = rng(1,'twister');
%state = output.state;
%list = reshape(1:100,[10 10])';
list = reshape(1:100,[5 20])';
for i0 = 1:si... |
799ae71caba81a08e3348bf65b3285faa90fddb657e59790eeeefc725431a073 | MATLAB | 1,557 | 46 | function [RP] = rp_plot(data, delay, dE)
% RP_PLOT Generates a recurrence plot (RP) from time series data.
%
% [RP] = rp_plot(data, delay, dE) calculates the recurrence plot for the given
% time series data using specified delay and embedding dimension.
%
% Inputs:
% data - A vector of time series da... |
c71ec289490bd7488f6abc2401ed63c98040cae88c7372671b16560288175835 | MATLAB | 1,559 | 39 | function Movie1and2_WholeImageWithFlow_and_WithFlowColoredByDirection(v, g1, g2, intIm, vxMat, vyMat, intGamma, barSize, secPerFrame, varargin)
numFrames = size(intIm, 3) - 1;
for frameNum = 1:numFrames
%% Create dispImage
dispImage = intIm(:, :, frameNum);
dispImage(dispImage(:) == 0) = mean(dispImage(disp... |
f668d8f3aa6682cebde70b9870f3acd0fb36c44bdd8cc114b2ec38cd2a113991 | MATLAB | 1,560 | 56 | function [g, gdata, gprior] = gbayes(net, gdata)
%GBAYES Evaluate gradient of Bayesian error function for network.
%
% Description
% G = GBAYES(NET, GDATA) takes a network data structure NET together
% the data contribution to the error gradient for a set of inputs and
% targets. It returns the regularised error gradie... |
b00843ad1a2d08d1377c82bb879cd809f3e65ef2e595e6353a76bb4d255bb1d6 | MATLAB | 1,562 | 71 | function [pval,Factual,Fdist] = randanova1(m,group,num)
% function [pval,val,dist] = randANOVA1(m,group,num,mode)
%
% Estimate p-value for one-way ANOVA using permutation.
% For further information on using permutation to calculate signficance
% tests see Anderson (doi:10.1139/cjfas-58-3-626).
%
% <m> is a vector to b... |
b690e000662d4139c49d0f8e4dd730e8fbf6b7678a2b2392194fe04e4a51bd98 | MATLAB | 1,562 | 34 | function f = antigradient(g, mu, n)
% ANTIGRADIENT Reconstruction from gradients in 2D and 3D.
%
% f = antigradient(g) computes the function f which has a gradient
% as close as possible to g. The vector field g must either be an
% MxNx2 array or an MxNxPx3 array.
%
% f = antigradient(g, mu) does the same thing ... |
52d0d899c3f748687386afdc990075668daa87abb8f13692e788190afbd64814 | MATLAB | 1,563 | 41 | % [SN_new,sss_indices] = basis_condition_adjustment(SN,dim_in,cond_threshold)
%
% Improve the condition number of the SSS basis by dropping unnecessary
% vectors from the basis. Input argument SN is the original normalized SSS
% basis, Lin is the order number of the internal basis, and cond_threshold
% is the acceptabl... |
42538528c76b9b09ffb2b10afd03f42ea8f450fbb804963e148d372bc0e750be | MATLAB | 1,564 | 53 | function model = lvl1_estimate(sub_id, p)
% function model = lvl1_estimate(sub_id, p)
%
% Performs a SPM first-level analysis.
%
% Input:
% - sub_id: ID of the current subject.
% - p: Structure with analysis parameters.
%
% Output:
% - model: Structure with all SPM settings used for this analysis
% step (w... |
02242f7e8eaa97b994640a1415f8b650a62ee06e94d25a1d023c92d1d7fb8b3b | MATLAB | 1,565 | 40 | function plot_time_comp_210511(spon_areas_table_ff,stim_areas_table_ff,spon_areas_table_fb,stim_areas_table_fb,subregion)
[pre_ff,post_ff]=pre_post_time_comp_210511(spon_areas_table_ff,stim_areas_table_ff);
[pre_fb,post_fb]=pre_post_time_comp_210511(spon_areas_table_fb,stim_areas_table_fb);
figure
hold on
x_pre_post=c... |
08e55aba3f9fb376fbf2283dc1000e2fb0bb07e87a044c7b1ceb737ffef45cf4 | MATLAB | 1,565 | 59 | function BEH_parafit(dir,fin,model,options,outfix)
% S - VP structure
% fn - filename for data
% model - case name for model
% options - specifying environmental and fitting parameters
if ~exist('outfix','var')
outfix = '';
end
%% information on model
infopt.type = options.type;
infopt.nstarts = options.nstarts; ... |
87da7826771cbb039731a515e220f49a23bbe9ea93b105bef0198949d94cb252 | MATLAB | 1,566 | 57 | function stats=deriveCM_pvals(svm_class,teLabels,nC)
% function stats=deriveCM_pvals(svm_class,test_lbs,nClass)
% FWS 13/9/2011 Centre for Brain & Mind, UWO
% if you use this code for analysis - please cite Smith & Muckli 2010 PNAS
% Non-stimulated early visual areas carry information about surrounding context
% PNAS,... |
7983eee8e5a2e31754832e8d55fc4ad4e947a346a2a279e9d2f5f2add9626f09 | MATLAB | 1,567 | 54 | function decoding_gui
% This is a simple graphical user interface using the Matlabbatch system of
% SPM. At the moment, it allows only running very simple decodings as
% specified by decoding_example.
%
% 2015/02/11 Martin Hebart
%% first check if path of TDT in toolbox path exists
cfg = decoding_defaults;... |
dff9acfb283f7ed49add9a3b26a7b2c34b69d606b140a2bbb227e54877339235 | MATLAB | 1,569 | 46 | function Process_RemoveOptoArtifacts(datName,nchannels,optoTimes,maxT)
% Process_RemoveOptoArtifacts
%
% USAGE
%
% Process_RemoveOptoArtifacts(datName,nchannels,optoTimes)
%
% datName file base name of the dat file (e.g. 'datName' for datName.dat).
% nchannels number of channels
% optoTimes ... |
e65a56d08eebd02d13f7416a8d9e404c691f853aa1c9793ce15b7b9a0a685249 | MATLAB | 1,569 | 43 | function sig_diff = pairwise_CI(data1,data2,num_boots,sig_alpha,min_duration)
[trials_nb_1,time_nb] = size(data1);
[trials_nb_2,~] = size(data2);
observed_difference = mean(data1,1)-mean(data2,1);
if trials_nb_1>2 && trials_nb_2>2
data_boots = zeros(num_boots, time_nb);
CI = zeros(2,time_nb);
for b=... |
f8d51366d648bd4b4b73f4ac9aed74c1398ab52ef30acd44774bb92435e27609 | MATLAB | 1,569 | 57 | % build test pattern movement record
output_file_a = fopen('test_data_angles.cpp','w');
output_file_s = fopen('test_data_speeds.cpp','w');
output_file_x = fopen('test_data_x.csv','w');
output_file_y = fopen('test_data_y.csv','w');
x=0;y=0;
speed = 5;
timebin = 20; % each move command lasts this long
onemovems = 1000/(... |
4e4082ed98049b1200cfbef1bb3b105c117d962c7e82bc4d586fcc672acf057b | MATLAB | 1,570 | 65 | function [CellDif] = specify_cell(NeuronSL,explap,Lap)
%SPECIFY_LAP ´Ë´¦ÏÔʾÓйش˺¯ÊýµÄÕªÒª
% ´Ë´¦ÏÔʾÏêϸ˵Ã÷
[n,m] = size(NeuronSL);
% neuronBinLapS = binActivity.neuronBinLapS;
% laps_theta_post = binActivity.laps_theta_post;
% [n,nbin, lapnum] = size(neuronBinLapS);
explap1 = explap.explap1;
explap... |
8b684f15ab21ad38fbeb8ee57371b8f698aec4e4ebf55cabf3e73fbe1d797c2c | MATLAB | 1,570 | 33 | function [u,v,h] = transformToOctSlide(...
histologyToOCTT,new2OriginalAffineTransform,topLeftCornerXmm,topLeftCornerZmm,octScale_umperpix, planeDistanceFromOrigin_mm)
% Using 2 transformation, what is the single plane fit of the slide
% INPUTS:
% histologyToOCTT - 2D Transformation matrix
% new2OriginalAf... |
652263b8230df20e8b064eb5e72bf71fe061a834bbcc2f343112f234051f8616 | MATLAB | 1,571 | 42 | % generate gridscore from rate map plot
% note: set use_hopper and hopper_run in high_res_traj.m if wanting to use hopper data
% while running locally.
% reference: https://www.mathworks.com/matlabcentral/answers/456241-how-to-apply-command-line-arguments-in-matlab
% run_on_hopper: run from hopper's system
% use_hopp... |
8301020f0eef09f9c49c5149cdf5ade4fe69cd76a6bad02d95d1212df093affc | MATLAB | 1,576 | 51 | function [y, sigsq] = gpfwd(net, x, cninv)
%GPFWD Forward propagation through Gaussian Process.
%
% Description
% Y = GPFWD(NET, X) takes a Gaussian Process data structure NET
% together with a matrix X of input vectors, and forward propagates
% the inputs through the model to generate a matrix Y of output
% vectors. ... |
a68ec2644c898500f464002adfe98967643fd012ccf03046ebf131ccc990f5a7 | MATLAB | 1,577 | 37 |
% Gets a list of strings specifying paths of elements in inputFolder that
% match pattern.
function filePathsOfInterest=getElementPaths(inputFolder,pattern,varargin)
if isempty(varargin)
typeOfElement='file';
elseif length(varargin)==1
typeOfElement=varargin{1};
end
elements_... |
3f4ee04bec23c6e2017d04c62d49086b9c66370b50f379e2b4a3f4ee3a16bf00 | MATLAB | 1,578 | 47 | function test_suite = test_bids_query_nirs %#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_nirs_basic()
%
... |
d149ac3fb3aac5634f1e7382dcb7ce74cd7bb0128bc0852e87c305fd243ba32b | MATLAB | 1,578 | 60 | function [y] = cellsubselect(x, boolvec, dim)
% [Y] = CELLSUBSELECT(X, BOOLVEC, DIM) outputs a cell-arry Y with the same dimension as X
% but from each input cell a subset of rows or columns are kept according
% to boolvec (which assumes the input data to be concatenated across cells)
%
% X should be a linear cell-ar... |
96f4256594e1a8e43dc966a67f900c9d8b2db04ce8b44817c2164d480076ee05 | MATLAB | 1,579 | 35 | function reconstructed_links=reconstruct_links(mutual_position_based_links,max_gap_closing_mutual_distance)
if ~isempty(mutual_position_based_links)
links_backup=mutual_position_based_links;
ex_indices = find(mutual_position_based_links(:,3)>max_gap_closing_mutual_distance);
mutual_position_based_link... |
fcf0a87082aa32b55536a2058607275a7322339ee8afd0c9856317beb585c7b2 | MATLAB | 1,581 | 41 | % Determine trials for each condition
% Check if variable Exclusion_Info exists already. If yes, load it.
if exist([output_dir output_specific 'Exclusion_Info.mat']) == 2
load([output_dir output_specific 'Exclusion_Info'],'Exclusion_Info');
end
for s=1:length(subject_list)
subject = subject_list... |
9f71c507ffbcd683bd1ec776293248d6a86f3e093af9acf24f2735cbdbc18a64 | MATLAB | 1,582 | 59 | 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... |
44f9ae9331cc1df6d3b1c0ac1de8cb8e78ec7622074979b8ccc64909c95103d4 | MATLAB | 1,585 | 69 | function [] = test_mem2()
% [] = test_mem2()
%
% This is just like test_mem, except that this is more akin to how
% init_object works. Either way, the conclusions are the
% same. Matlab only duplicates the particular cell in the cell
% array whose contents you changed.
disp('Clearing and packing');
clear all
pack
su... |
b85a1f8caed3632d000863db61c66221174a85fe95d924ca0c19c1e58a25f247 | MATLAB | 1,586 | 53 | %% Plot V4 MI Firing Rate d' and bias split at cued and cue-opposite locations (histogram)
%% Code
loc = ["cued","opp"];
loc_flag = 1;%input('neural data at cued location or cue-opposite location: 1-cued, 2-opp: '); % loc_flag = 1 for Fig 4C-D
% cue epoch
win_start = 500;
win_end = 2500;
win_str = num2str(win_start)+... |
9d3cb321891b1bed3708489002aab75b8e2062edc3b3f6388ef6edb6b5c4d5b2 | MATLAB | 1,587 | 54 | % @title Associate xy coordinates to neurons
% @file XY_placement.m
% @author Romain Beaubois
% @date 06 Aug 2021
% @copyright
% SPDX-FileCopyrightText: © 2020 Romain Beaubois <refbeaubois@yahoo.com>
% SPDX-License-Identifier: GPL-3.0-or-later
%
% @details
% > **20 Apr 2020** : file creation (RB)
... |
0fbf31a860c8f63d623a56dff7a58f99057b64a009a48340b5cfca7767091f73 | MATLAB | 1,590 | 40 | function msBatchSegment(dirName)
%MSBATCHSEGMENT Summary of this function goes here
% Detailed explanation goes here
dataFolders = msBatchFindDataFolders(dirName,[]);
parfor folderNum = 1:length(dataFolders)
currentFolder = dataFolders{folderNum};
temp = load([currentFolder '\ms.mat']);
... |
6b68004dfad6647a29f77174178819de3a02e0741a99d41dc8ea960d2a2dd681 | MATLAB | 1,590 | 48 | function [allregion_unit_matched]=directory_peak_train_assembly_220103(well_folder,time_idx,direction)
cd(well_folder)
current_folder=dir;
folders=current_folder([current_folder.isdir]);
folders=folders(3:end); %removes relative pathing
recordings=string({folders.name});
for rec=1:length(recordings)
cd(strca... |
337803ed9df60751f4e045aa07f083f0bb993c5f64826e83987ab563a999d4ec | MATLAB | 1,592 | 39 | %% Indexing V4-FEF pairs to take only pairs belonging to FEF units that have (fMI (cued), fMI(opp) ) lying in a particular quadrant
% Code for rank sum test - All Units
%% Code
cols = [0.3010, 0.7450, 0.9330;0.4660, 0.6740, 0.1880;0.4940, 0.1840, 0.5560;0.6350, 0.0780, 0.1840];
load('V4_FR_full_500_to_250... |
40a7ee83361b062fda9c759aaefd017b351f7b211040a5f7f44350fe8dc10433 | MATLAB | 1,592 | 82 | clear
[task_info,supPath,~,task_DB_path] = loadDBAndSpecifyDataPaths('Vermis');
EPOCH = 'cue';
PLOT_CELL = false;
req_params = reqParamsEffectSize("both");
lines = findLinesInDB (task_info, req_params);
cells = findPathsToCells (supPath,task_info,lines);
cellType = cell(length(cells),1);
for ii = 1:length(cells)
... |
f0452208c7efc04f8759f4f6a1ea60b49f290dbb4b22205932fcf3eb5998516a | MATLAB | 1,592 | 45 | function vbl = draw_grating(Experiment, tilt, phase, fixcolor, flip, flipTime)
% requires 'tilt' and accepts 'phase' as additional argument. If 'phase' is
% not passed, it is set to 0 by default
% takes flipTime as additional argument to specify exact time of flip
% (script waits until time is reached)
Display = Expe... |
fafe84c14caca7aacc07aaaacc87989a56b50d89b9bff1ed91deaaa641cc11c5 | MATLAB | 1,592 | 47 | function [Tortuosity, Pathlength] = Tortuosity_AnyTraj(Traj)
numTraj = size(Traj,1);
if numTraj == 0
Pathlength = [];
Tortuosity = [];
else
% for each trajectory, take start and end position and calculate the distance
for i = 1:numTraj
e... |
701fe8ba91885df281bfda79d9f26b418e928be50903cf56a158594dd894b811 | MATLAB | 1,593 | 53 | function vmr = bv_readvmr(fname)
% vmr = bv_readvmr(fname)
%
% :description
%
% Reads in a version 0, 1 or 2 (BrainVoyager 2000, QX) VMR file.
% Does not read in the positioning data added to the end of the file
% in QX (version 2)
%
% :inputs
%
% fname file to read, e.g. 'myproj.vmr'
%
% :outputs
%
% vmr ... |
91c0907a05811f53c2a207b9a7c4fbf601d4afe766972884c445ac994b21530b | MATLAB | 1,594 | 41 | function [subjects, dirs, subj_date] = PDbb2_SETUP()
% Setup PDbb2 in MATLAB
%
% Vinding, M. C., Eriksson, A., Low, C. M. T., Waldthaler, J., Ferreira, D., Ingvar, M., Svenningsson, P., & Lundqvist, D. (2021). Different features of the cortical sensorimotor rhythms are uniquely linked to the severity of specific sympto... |
b7ee8269b4b1c2289d229a06475b4e989f2895fe6c2905ae2a7f40b6f21fcd6b | MATLAB | 1,596 | 41 | function SmoothImages(exportFolder, smoothParams, image)
%% Params
smoothSig = smoothParams.smoothSig;
smoothOneSidedNumSig = smoothParams.smoothOneSidedNumSig;
smoothPadSize = smoothParams.smoothPadSize;
smoothMeanFac = smoothParams.smoothMeanFac;
smoothSigFac = smoothParams.smoothSigFac;
%% Smooth Image
% Pad Image
... |
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