sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
68ee9a0a5f00bce25743db8fd3e53cdb7444b9973e829f92ecc42a8086f3437c | MATLAB | 780 | 28 | function [Xcr, Ycr, Zcr] = meshcross(q,X,Y,Z)
%meshcross - returns cross product of q with meshgrid input at each point
%on the grid.
siz = size(X);
assert(length(siz) == 3,'Meshgrid dimensions != 3');
assert(siz(1) == siz(2));
assert(siz(2) == siz(3));
assert(siz(3) == siz(1));
%Iterate through all x, y, z values, ... |
7f3d14ed9ff0a0496ca7d68e91352dd374bb08362f8b87d1d046657f925aeb02 | MATLAB | 780 | 21 | %% Script to Load Deafult Directories
% EDIT TO YOUR EXPERIMENTS DIRECTORY:
DefaultPath='C:\Users\Vladimir\Documents\Doctorado\Experimentos\';
if exist(DefaultPath,'dir')==0
DefaultPath=pwd;
end
%% DO NOT EDIT (preferably):
% Folder with all the files with data and processings: EXPID.mat
FolderNamePD='Processed Dat... |
de9c60658be70e7af577886e5bc9824e73b79dbc7fd5b5f7c443eaf094a8bc1f | MATLAB | 785 | 15 | function Vr = Reconstruct_XY_Projected_Vector(Vp,Ap,Ly,Rx)
% Input:
% Vp is the projected vector given as a 3D coordinate [x,y,z] (assuming origin at 0).
% Ap is the rotation angle of the plane in *radians*. The direction (sign) of this angle is from XZ.
% Rx is a function for the rotation matrix around the x-... |
f4439153cf5c65bcb95481a06485854b78b6d5ab4198b85b3b535c76e1f7dc50 | MATLAB | 785 | 23 | function showgrid(ux,uy,downsample,lim)
if nargin<3; downsample = 1; end;
sizex = size(ux,1);
sizey = size(uy,2);
ux = ux(1:downsample:end, 1:downsample:end);
uy = uy(1:downsample:end, 1:downsample:end);
if nargin<4; scale = 3; end; % Scale vector to show sm... |
21495d57b10f5bdcc4772a62b761435c0bd1060ab4df1c2a2a78862dc03a8264 | MATLAB | 786 | 39 | function dll = get_dll(session, channel, unit, fold, trials, times)
% Get true delta log-likelihood of specific neuron
%
% Parameters
% ----------
%
% - fold: integer scalar
% Fold number
% - trials: vector
% Trial indeces
% - times: vector
% Time of study
%
% Returns
% -------
% - dll: scalar
% Delta log-likel... |
7c10e1e1dbe58e82d610691ebdbe800a6ace0ff9b0948377c648997741ec09ad | MATLAB | 786 | 37 | function y = ir_sinc_nopi(x)
%function y = ir_sinc_nopi(x)
%|
%| no pi version of "sinc" function, because matlab's sinc() is in a toolbox
%|
%| Copyright 2001-12-8, Jeff Fessler, University of Michigan
%| Modified by M Allison to not have a pi.
if nargin < 1, help(mfilename), error(mfilename), end
if streq(x, 'test'... |
e73379b57d793827d2f2b4a1adf06a566d8a0ec26cfac8e238ebd716af03ed21 | MATLAB | 787 | 24 | clear;
close all;
addpath('E:\Programs\Baseline Wander Comparison\ECG Normal Sinus\30SecSegmentsParams');
addpath('E:\Programs\Baseline Wander Comparison\ECG Normal Sinus\30SecSegments');
for k = 0:190,
filename = ['seg_' , num2str(k,'%3.3d')];
load(filename,'data','chname');
filename = ['seg_'... |
01514e27f098ecf2c0b45c6ca006f05b18164c362f0d6ad114b457d2887ca246 | MATLAB | 788 | 19 | function plot_lines_area(AX, resection_time)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Dashed line
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
clear line
% axes(AX);
y_lim = get(AX(1), 'YLim');
hl = line([resection_time, resection_time], y_lim);
set... |
bcec53a509c95bf54389037f765a461cbc78f0ed2a50c207256d9dd779cd30c8 | MATLAB | 788 | 27 | function pvals = roc_PSTH(hit_psth, fa_psth, win, testwin)
% ROC_PSTH performs ROC analysis.
% ROC_PSTH(HIT_PSTH, FA_PSTH, TAG, WIN, TESTWIN, STAGE) performs ROC
% analysis of input data (HIT_PSTH and FA_PSTH) of length WIN in a test window
% TESTWIN.
% See also ROCAREA
% Balazs Hangya, Panna Hegedüs
% hangy... |
e6fa05c77639193260b5e2b931cb57c8cb5bdf8c43a3f4fa978cbe5fb831b8b8 | MATLAB | 790 | 30 | %
% Test program for RelativeSpectralPower
%
% Dependencies: RelativeSpectralPower() from the Open Source ECG Toolbox
%
%
% Reza Sameni, June 2022
% reza.sameni@gmail.com
% Open-Source Electrophysiological Toolbox (OSET)
% https://github.com/alphanumericslab/OSET.git
clc
clear
close all;
load('SampleEC... |
c608add229d1e0b675001e612d6c0ed3f15b25d4ad0b6675d78b3edb7c6101df | MATLAB | 791 | 29 | function hMenu = menuCheckbox(menuTag, label, doUncheckOthers)
%MENUCHECKBOX Check the label selected, optionally uncheck the rest
if nargin < 3
doUncheckOthers = 1;
end
hMenu = [];
try
if ischar(menuTag)
hMenu = findobj('Tag', menuTag, 'Type', 'uimenu');
else
... |
a205457f7c7b2fb2ce1db35b28226c1f61cbf23ecde56aafeae904b2b690b215 | MATLAB | 792 | 34 | %%
%Name: char2rgb
%Created by: Pratik
%Created on: 27 July 2018
%
%Description: Converts a character color value into its numerical RGB equivalent
%Input: A lowercase character for any RGBCMYWK color
%Ouput: A 1x3 vector with the equivalent numerical RGB values
%
%Usage: vector = char2rgb('color');
%%
f... |
424c97567d9a19d273e9e3b201ec5cc40250b46888db9529de7d49982eae0646 | MATLAB | 794 | 34 | % test fetal ECG fractal dimension calculation
% Reza Sameni, Copyright March 2006
% Modified June 2018
%
clear;
close all;
clc;
%load patient165_s0323lre; data = data(1:10000,4)';
load FOETAL_ECG.dat; data = FOETAL_ECG(:,4)';clear FOETAL_ECG;
figure;
plot(data');grid;
%plot(data(6:8,:)');grid;
N = length(data);
for ... |
66b7ed41b11e8157846fcadf0552dc32641f41eb58d3c52f65d7731b06131cd4 | MATLAB | 794 | 52 | function get_lcmodel_correlation(d)
for k=1:length(d)
fps=get_subdir_regex_files(d{k},'.*PRINT$');
fps = cellstr(char(fps));
for kk=1:length(fps)
fileid=fopen(fps{kk});
go_after('Correlation',fileid)
go_after('Correlation',fileid)
go_after('Glu',fileid)
go_after('Glu',fileid)
go... |
a27fee623f04bc3e427a563da02c39f646f2fd3f4343ea2b3fb1aa39569cb4ba | MATLAB | 795 | 41 | function out = eigs(ob, varargin)
% compute largest magnitude eigenvalue of object by calling eigs,
% which in turn probably uses the power method.
% this may be slow for big objects because it is iterative.
warn 'todo: i could not get this to work'
% A = Gdft('mask', true(8,6));
% eigs(A, 1)
if numel(varargin) ~= 1... |
be7436de89c5a5b6082cdb4b4563515efca3e7a24de2b1997469e6cfb0c82604 | MATLAB | 796 | 27 | classdef SonoNERFfLossLayer < nnet.layer.RegressionLayer
% This class implements the L1 loss layer for use in neural networks.
methods
function layer = SonoNERFfLossLayer(name)
% Set layer name
layer.Name = name;
% Set layer description
layer.Description... |
c8ce28a5d05f5f30da96c7667ff3f7023a0be4ec9013c24cb7766b2f37e8f08f | MATLAB | 796 | 29 | clear
shrink_ratio = 1;
flat_map_data = load("flat_map_data_10um_v2.mat");
plotting_1 = flat_map_data.plotting_1;
plotting_2 = flat_map_data.plotting_2;
pre_flat_index = flat_map_data.pre_flat_index;
pre_flat_dimention = flat_map_data.pre_flat_dimention;
mask = zeros(pre_flat_dimention, "uint8");
mask(p... |
d6f5e5599abe081d14fb4fb425904e6a012c76218694200fa43b7a85fc03ffbe | MATLAB | 797 | 26 | function peaks1 = LocalPeakDetection(x, half_win_len, number)
N = length(x);
peaks = zeros(N,1);
peaks1 = zeros(N,1);
half_win_len = round(half_win_len);
x = abs(x);
for j = 1:N
index = max(j-half_win_len,1) : min(j+half_win_len,N);
% if (x(j)>=0 && max(x(index))==x(j)) || (x(j)<0 && min(x(index))==... |
4b4c2b853855a383d5fca0e2fd407712fccb4603ed7458199044a08b82a504ef | MATLAB | 799 | 33 | classdef h5_conversion_options < handle
%
% Class:
% adi.h5_conversion_options
%
% See Also:
% adi.channel.exportToHDF5File
properties
max_samples_per_read = 1e8
deflate_value = 3 %(0 - 9 for gzip
%0 - no compression
%9 - most compression
... |
32cded00fb976088815b2d4c55f748a0a6413c29a184b934e66160b5c63db609 | MATLAB | 800 | 24 | function [shiftsBack, shiftsForward] = shiftRange(nSamples, nShifts, shiftFactors)
%SHIFTRANGE
if ~isempty(nShifts)
[shiftsBack, shiftsForward] = deal(cell(nShifts*2 + 1, 1));
shiftFactors = -nShifts:nShifts;
else
[shiftsBack, shiftsForward] = deal(cell(numel(shiftFactors), 1));
... |
2d547651ef2e2779f65ed1d969a2414192d5ef558054d2b3520b38e6cd3077e1 | MATLAB | 801 | 28 | function openLog(obj, logFilename)
%OPENLOG Open the log file
if nargin < 2 || isempty(logFilename)
logFilename = [datestr(now(), 30) '.log'];
end
% no directory specified in filename
if isempty(fileparts(logFilename))
logDirname = fullfile(obj.outputDir, '.jrc');
if exist(l... |
9523325a52ef1fc9d360fb93e29afc726f731024abdb9c0f1f93cf16f2151022 | MATLAB | 802 | 26 | function chain = spa(X,k,M)
% Projections routine for the Successive Projections Algorithm using the
% built-in QR function of Matlab
%
% chain = projections(X,k,M)
%
% X --> Matrix of predictor variables (# objects N x # variables K)
% k --> Index of the initial column for the projection operations
% M --> N... |
b6136423f64770524f9feb23a7b35f9e3c4e4a5971f9eae9023ffd0014394a89 | MATLAB | 802 | 24 | %% compare diffrent sharp track iterations between people
% load all cluster cordinates
clc
clear
[file, path] = uigetfile('*.csv','MultiSelect','on');%When the user clicks the load psetion button, a window should open to enable the user to select a file.
cd(path)
%%
for i = 1:length(file)
cell_coordinates{i} = rea... |
b726721342d1261dcdff340d5d3fe483eecae57a686af8722cf2b577adf17660 | MATLAB | 802 | 36 | function lit = haslight(axish)
%HASLIGHT Check if axis handle has a light attached
%
%Syntax
% lit = haslight(axish);
%
%Description
% LIT = HASLIGHT(AXISH) sets LIT to true if the axis specified by axis
% handle AXISH has a child of type 'light', and sets LIT to false otherwise.
%
%Examples
% > lit=haslight(gca)
% lit... |
1cd3cd4f4314be7aaf96d0f7403e2806d000fe266def0a36af7d113762abc2f3 | MATLAB | 803 | 30 | function bases = make_bases()
% Make basis functions
%
% Returns
% -------
% - bases: struct
% time/delay basis functions
info = get_info();
% bases
% - delay
delay_values = 1:info.num_delays;
delay_delta = 2 * info.probe_time_resolution;
delay_knots... |
14ad030068d014f08107e7ca63ceda4a559a892e830582f48a2bdefdbb8a49f2 | MATLAB | 804 | 36 | function B = stretch(A, sc, st)
asize = [size(A, 1) size(A, 2) size(A, 3) size(A, 4)];
dim = length(asize);
s = ceil(asize ./ st);
newsize = sc .* s;
B = zeros(newsize);
order = cell(dim, 1);
ind = cell(dim, 1);
oldind = cell(dim, 1);
for d = 1 : dim
ind{d} = [];
for i = 1 : sc(d) - st(d)
ind{d} = [ind{d}; sc... |
fa4bd8f5d1322ffb20dbf51b3b8e9ab45463e1dc58063cccbedab58912b3bf1a | MATLAB | 805 | 21 | % Authors : Tatjana Schmitt & Simon Wadle 2019-2023
function dF_F_image_resized = dF_F_resized(resized_image)
%function fits baseline pixelwise with chronux toolbox
%and calculates dF/F for each pixel
total_frames = size(resized_image,3);
time_for_fit = [1:total_frames]';
[x_pixels, y_pixels, z_pixels]= size(r... |
01eb510c063d84bc29d979494f2e77fc137b8c555cafa43728938674e6cca492 | MATLAB | 808 | 29 | function Answers = cleanup_PVT(AllAnswers)
% Take table from AllAnswers, save relevant information and make it in the
% correct format type.
Answers = AllAnswers(:, {'Participant', 'Session'});
Answers.Participant = string(Answers.Participant);
Answers.Session = string(Answers.Session);
Answers.Trial = cell2mat(AllAn... |
f4c82c819610ca346797a7fb09ecfa8897bfaab6e5dcdf2320d9e4e65c923700 | MATLAB | 808 | 20 | function [nLoads, nSamplesLoad, nSamplesFinal] = partitionLoad(nSamples, nSamplesMax)
%PARTITIONLOAD Compute the number of samples to load from a file
nLoads = min(max(ceil(nSamples / nSamplesMax), 1), inf);
nSamplesLoad = min(nSamples, nSamplesMax);
if nLoads == 1 % first load is last load, use nSamp... |
8a168fe0309b2a30ccb3578d1c95f16f0ee6e260842993a2b9b573fb33b5ab2a | MATLAB | 809 | 32 | %%
[cols,alpha] = chooseColors;
lims = [-8 12];
tone_trace = tone_trace * lims(2);
tone_trace(tone_trace == 0) = lims(1);
figure('Position',[100 100 1200 300])
hold on
plot(proj_trace,'k')
area(tone_trace,'FaceColor',[.7 .7 .7],'FaceAlpha',alpha,'LineStyle','none','BaseValue',lims(1))
ylim(lims)
set(gca,'XTick',[0:3... |
8d2fa514473d482270ca3daffc703e670631f9b8304560f57a593bcf9ccab0a0 | MATLAB | 811 | 43 | load('D:\Data\LSM\Preprocessed\Clean\Waves\LAT\P01_LAT_BaselineBeam_Clean.mat')
freqs = 1:20;
[Power, ~, TF.times] = wavetransform(EEG.data(68, :), EEG.srate, freqs, 3, 15);
Power = squeeze(Power);
EEGw = EEG;
EEGw.data = Power;
EEGwe = pop_epoch(EEGw, {'S 3'}, [-2 4]);
t= linspace(-2, 4, 1500);
%%
close all
Me... |
2bf080fbd5450d8dd1db61ceae6b1578dffcb110a8c5480693a4565975cc4d9e | MATLAB | 812 | 25 | function p = fpval1(x,df1,df2)
%FPVAL F distribution p-value function.
% P = FPVAL(X,V1,V2) returns the upper tail of the F cumulative distribution
% function with V1 and V2 degrees of freedom at the values in X. If X is
% the observed value of an F test statistic, then P is its p-value.
%
% The size of P is t... |
6f3cf523c9957be23639150447bf41c9b8830c706ce6517f4e0bdd0803005637 | MATLAB | 812 | 19 | function [Clusters_Indices,Clusters_Centroids] = Cluster_Data(Data_Mat,Algorithm_Name,Clusters_Vector)
switch Algorithm_Name
case 'k-means'
eva = evalclusters(Data_Mat,'kmeans','silhouette','KList',Clusters_Vector);
[Clusters_Indices,Clusters_Centroids] = kmeans(Data_Mat,eva.OptimalK);
case 'Gaussian Mixtu... |
b7c48653c1e54c0c5f79b23d0ed8d737a91877051e1134c8403fdec785b438e2 | MATLAB | 812 | 18 | function [templates, maxdist, pointdist] = build_templates(classes,features)
% function [templates maxdist] = build_templates(classes,inspk,pointdist)
max_class = max(classes);
feature_dim = size(features,2);
templates = zeros(max_class, feature_dim);
maxdist = zeros(1,max_class);
pointdist = zeros(max_class,feature_... |
d3d1884aa9d83165a6ac7b7ff0dc8f18a14469b2549fde95c74168eb10f807e3 | MATLAB | 812 | 25 | clear
clc
%% cluster cordinates load
cd('E:\')
[file, path] = uigetfile('clusters_coordinates.csv');
datafile = fullfile(path, file);
X = readtable(datafile);
%load all_cell_parameters
cd('E:\2022\all_cell_parameters')
[file, path] = uigetfile('cell_type_parameters.mat');
datafile = fullfile(path, file);
loa... |
24327b82d234034f809e8812893af697666a50dcd5aee789870543fd74434835 | MATLAB | 813 | 26 | function terashita20191021
cd('C:\Users\C238\Desktop\CheetahData\2019-10-16_15-13-58 17301-04');
dpath=('C:\Users\C238\Desktop\CheetahData\2019-10-16_15-13-58 17301-04\');
dpath3=('C:\Users\C238\Desktop\CheetahData\2019-10-16_15-13-58 17301-04');
% data=load([dpath '15103_190313_98__'],'-ascii');
dpath3
load 17... |
a6c7a4b9ac2334b5c407c8e5f0e065241c147158e9e4ff4f08a85a371e154c95 | MATLAB | 813 | 40 | function [gl_node gl]=global_efficiency_wu(w)
%calculate global efficiency
%INPUT: w = inverse FCG (functional connectivity graph)
%OUTPUT:gl_node = global efficiency per node
% gl = total global efficiency of the network
% distance = matrix which preserve the weighted shortest path length
% binary = m... |
f4e69e83e2d4883961fb5b4557e90f63f18e0ff8c51f3604dcdcbdf4d7742945 | MATLAB | 813 | 46 | function PlotElectrode(x,y,r,Label,Gray,zl,fs)
% Copyright 2009-2011 Thomas Koenig
% distributed under the terms of the GNU AFFERO General Public License
if (r == 1)
xc = [x-1 x+1 x+1 x-1 x-1];
yc = [y-1 y-1 y+1 y+1 y-1];
patch(xc,yc,ones(size(xc))*zl,[0 0 0]);
return
end
if numel(Gray) == 1
Gray... |
0ce58027a83aed8af9d7970973b1fe114a4f6d8c57f80a861f2b1cf3ebbfbc2c | MATLAB | 816 | 40 | function [vtx, vty, vtz] = dipolefan(rx,ry,rz,theta_t)
sizr = size(rx);
% GRIDS
% Get back R and unit vectors from passed grid
R = sqrt(rx.^2 + ry.^2 + rz.^2); %calculate |r| at each point
%getting normal vectors
erx = rx./R;
ery = ry./R;
erz = rz./R;
%Get theta and phi for each point in grid
theta = acos(rz./R);
... |
69444613bcb81932b0fff1fd7fa61dfa2eedf58912b213eb7503afdf745ea13e | MATLAB | 816 | 31 | function [mrprot] = parse_siemens_shadow_mrprot
(dcm)
% [ mrprot] = parse_siemens_shadow(dcm)
% function to parse siemens numaris 4 shadow data
% returns mrprot info
% does not work with arrayed dcm()
if (size(dcm,2) > 1)
error('parse_siemens_shadow does not work on arrayed dicominfo data!')
end
% n... |
264655ef1874f7a50600f825daf29795bc728543e9646e0bde54e85bb7b3dd84 | MATLAB | 818 | 22 | function [c_partition,allegianceMatrix,modularity] = genRobustCommunityFromASeries(A, gplus, gminus)
% for consensus_comm_wei
% C is a pxn matrix of community assignments where p is the number of optimizations
% that have been performed. n is the number of nodes in the system. C gives the real partitions.
n = size... |
c6808c508da678625f45d05cb2f22d920de4053bd46da79f17e506d0e78daaa2 | MATLAB | 818 | 24 | function subsetFields(obj, keepMe)
%SUBSETFIELDS Subset all data fields, taking only those indices we want
% to keep, prior to rearranging or deleting
vectorFields = obj.unitFields.vectorFields;
hFun = @(vals, indices) vals(indices);
for i = 1:numel(vectorFields)
fn = vectorFields{i};
... |
f3af828cbb57ad2d24492fef2729431b934c0bf800999179ccda740b5d7ed70d | MATLAB | 819 | 33 | function MIClustering(x,kneig,algo)
% hierarchical clustering using the grouping property of mutual information
% output: dendrogram
% x....input data mxn m...channelnummer n...sampling points m<<n
% kneig... k nearest neigbor for MI algorithm
% algo ... 1=cubic 2=rectangular
%default-values
if ~exist('kneig'),... |
ca5241925286dde42cb647affc1f7a74977a27e7f180b93f78b0a37d744b746d | MATLAB | 820 | 24 | function Bursts = burst_averages(Bursts)
% gets mean values of all the peaks in a burst, so long as the fieldname is
% lowercase, and the number of items is equal to the number of peak ids.
% Part of Matcycle 2022, by Sophia Snipes.
Fields = char(fieldnames(Bursts));
uppercase = isstrprop(Fields,'upper');
Fields = str... |
e6e6f3e8ca374a4eef7adb3a82d28e1e3d48f2ef8c36f6d0b41d8380580328c1 | MATLAB | 820 | 21 | % A self contained function to present cell connectivity
% ScatAdj between S and other celltype
function [] = Paper2FigS1_ConnCell(NnS, PreSInd, SX, SY, ScatAdj,...
N_HC, n_S_HC, CellType,Color)
hold on
S = scatter(NnS.X(PreSInd),NnS.Y(PreSInd), '.');
S.MarkerEdgeColor = Color;
scatt... |
81a67415e900f3fd79ef04d40eac6e57c6acda8dc393638326bc0514f651b52d | MATLAB | 821 | 30 | function [sortCH, sortSQI] = VotingSQIs(SQIInds)
%
% [sortCH, sortSQI] = VotingSQIs(SQIInds)
% Voting between different SQIs
%
% Fahimeh Jamshidian Tehrani,
% jamshidian.t@cse.shirazu.ac.ir,
% fahimeh.jt@gmail.com
% February 2020
%
% input:
% SQIInds: different input SQIs
% output:
% sortCH: ranked channel number a... |
b2405e81efd59d5dad4ca51bc4ef7915d38abfdc110d03b47e4ff293636acfc6 | MATLAB | 822 | 30 | function out = Intense2rgb(data,cmap,clims)
% function out = Intense2rgb(data,cmap,clims)
% take 2d data and return rgb image, based on given colormap (gray is
% default)
if nargin < 3
clims = [min(data(:)) max(data(:))];
end
if ( nargin < 2 || isempty(cmap) )
cmap = repmat(linspace(0,1,64)',1,3);
end
cmapLe... |
4f533ce853b778c6b16c0b1c1ab760bb32223428e5640615b9f2cddd85d029b9 | MATLAB | 823 | 28 | function ob = gg_Gnufft(om,M,Msp,R)
%function ob = gg_Gnufft(om, M, Msp, R)
%
% Object constructor for Leslie Greengard's 2-dimensional NUFFT using separable
% gaussian interpolator.
%
% in
% om [Min,2] "digital" frequencies in radians
% M [1] image dimensions (N1,N2,...,Nd)
% Msp [1] # of neighbors used
% R [1] ove... |
5b651040ba6ac8759b55d9390099bbfcb8aae9a8aa6d87e2ffe4299f177acc2e | MATLAB | 825 | 20 | function inconsistencies = inconsistentFields(obj)
%INCONSISTENTFIELDS Check all fields have the correct sizes
inconsistencies = inconsistentFields@jrclust.interfaces.Clustering(obj);
% also check all clusterCenters are unique
if ~ismember('clusterCenters', inconsistencies)
% find all putative ... |
66033f7d990b034994f3c74130b48963d2e3dcb46862de32ca3f02c1f2f9305d | MATLAB | 826 | 29 | % create the negative Gamma model
% ------------------------------------------
% This file is part of the adaptative_threshold SPM plug-in
% Copyright (C) Cyril Pernet and Chris Gorgolewski 2012
classdef NegativeGamma < Gamma
methods
function obj = NegativeGamma(shape, scale, mu)
if nargin == ... |
957afa3845e4b34c3059dd259dbdd8d8dbd117bba58dbbb0bdbff1c6c90f924a | MATLAB | 826 | 21 | function computeQualityScores(obj, updateMe)
%COMPUTEQUALITYSCORES Get cluster quality scores
computeQualityScores@jrclust.interfaces.Clustering(obj, updateMe);
unitVmin = squeeze(min(obj.meanWfGlobal));
unitPeaks_ = jrclust.utils.rowColSelect(unitVmin, obj.clusterSites, 1:obj.nClusters);
try
... |
200d3e01dc287ea148d5e97b966361466ac683560e4aaefed2f6aaf5e9782b8d | MATLAB | 827 | 34 | function out = Ragu_CollapseMSFeatures(in,BetweenDesign,WithinDesign)
[ngroups,nconds,~,~] = size(in);
out = nan(size(in));
if isempty(BetweenDesign)
BetweenDesign = ones(ngroups,1);
end
if isempty(WithinDesign)
WithinDesign = ones(nconds,1);
end
if ngroups ~= numel(BetweenDesign)
error('Group sizes mis... |
8f1e787ce8adfea235cbc3697faae3644f1d77fe4cac138714bffd8c51a5efed | MATLAB | 827 | 31 |
%% clear
clear
close all
clc
%% load ecg
load ecgptb.mat
%% prepare data
ecg=ecg(10*fs+1:20*fs,:); % 10 sec multichannel ecg
L=size(ecg,1); % ecg length
tst=(1:L)/fs; % time stamp
w1=.75; % window length of the first median filter used in base line removing
w2=.9; % window length of the second median filter used in ... |
be3e2718305747beb391515d3b3e46e1318beef548bd75b8a168c6788535fa63 | MATLAB | 827 | 27 | function [skw, m, sd] = skew(data)
% skew - Skewness of a matrix data (over the second dimension).
%
% Syntax: [skw, m, sd] = skew(data)
%
% Inputs:
% data: N channels x T samples data matrix.
%
% Outputs:
% skw: Skewness vector (N x 1).
% m: Mean vector (N x 1).
% sd: Standard deviation vector (N x 1).
%
%
% ... |
e5502cb17e74d1a65f7ba0d9ff7334e808feb39fb9d2e4e121ae42584c100369 | MATLAB | 828 | 30 | % Only if flag_location_legend = 1 the function deals with the position of the
% legend
function set_fonts_lines(...
ha, ...
flag_location_legend)
line = 1.5;
marker = 8;
font = 20;
fontaxes = 18;
set(0, 'ShowHiddenHandles', 'on')
hl = findobj(ha, 'Type', 'line', '-not', 'LineStyle', 'none');
set(hl, ... |
2c0a5cf7c577f86a92659ed2a9373a9939a17b67d4a75955a4cc9a88443abd37 | MATLAB | 829 | 24 | function clusterMean = nanmeanInt16(spikeWindows, iSite, sites, hCfg)
%NANMEANINT16
iSiteNeighbors = hCfg.siteNeighbors(:, iSite);
trWav = nan([size(spikeWindows, 1), numel(iSiteNeighbors), numel(sites)], 'single');
uniqueSites = unique(sites);
nUniqueSites = numel(uniqueSites);
uniqueNeighbor... |
b133ed573c8122dcb826e3c145b5a6ed226f623a2e3de96baa9fb4c5c8d437be | MATLAB | 829 | 26 | Experiment=Experiment(Experiment~='\'); % NAMES PATCH
%% PLOTS
[New_Index_Merged,~,RASTER_COND]=SortNeuronsCondition(R_merged);
% Plot_Raster_V(RASTER_WHOLE(New_Index,:),fs);
RASTER_COND=RASTER_COND(New_Index_Merged,:);
Plot_Raster_Ensembles(RASTER_COND,fs)
Label_Condition_Raster(Names_Conditions,R_Condition,fs); ... |
d6f126a739784c8a71249d5787451d2ed36f16090d718ea2fa606e24ae19a514 | MATLAB | 829 | 34 | % Author: Corentin Wicht, LCNS, 2018
% corentin.wicht@unifr.ch
% This work is licensed under a Creative Commons Attribution-NonCommercial
% 4.0 International License (CC BY-NC)
function Fig=MessageBox(Text,Title,FontSize,Width,Height)
% This function is an updated version of msgbox () enabling to resize the
% message... |
8776412fab993184efa2daa89790725d6373ab4a22df4e800a03cd10b3f5d936 | MATLAB | 830 | 23 | clear
[file, path] = uigetfile('*.mat');%When the user clicks the load data button, a window should open to enable the user to select a file.
datafile = fullfile(path, file); %save path
load(datafile)
close all
%%
f4 = figure;
set(f4,'color', [1 1 1]);
set(f4,'position',[50 50 500 750]);
cells_matrix = ~contains(clust... |
067e80977c0600bbb0c9c331ce704b9e89946d701a8cb1e9a24696e3544c78b0 | MATLAB | 831 | 36 | function D=hbf_BEMOperatorsPhi_LC(meshes)
% HBF_BEMOPERATORS_PHI_LC makes the double-layer (D) matrices for LC BEM
%
% D=HBF_BEMOPERATORS_PHI_LC(meshes)
% meshes: BEM geometry, [N x 1] cell array of hbf structs
%
% D: Double-layer matrices (D) in [N x N] cell array
%
% v160229 Matti Stenroos
nsurf=length(meshes);
... |
e237dfb81dfb367a4b68c4ee3459ff8b700cec98c7e6f2e6c7f8e320e0ef3463 | MATLAB | 831 | 17 | function [signalPeaksArray] = getPeaks( p,signalMatrix )
% This might not be entirely accurate, since how many and which peaks
% are found is dependent on the minTimeBtEvents paramter
warning('off','signal:findpeaks:largeMinPeakHeight')
for i=1:size(signalMatrix,1)
inputSignal = signalMatrix(i,... |
9cac2050cdbe936d588540524a899a8c2187bd6931d3ac4a7f4f3e087c69187e | MATLAB | 833 | 30 | % rawDataFile = ''; % <-- this must already be set before calling this script
if ~exist(rawDataFile,'file')
disp(['File ' rawDataFile ' not found, trying locally instead.'])
rawDataFile = fullfile(script_pwd,rawDataFile);
if ~exist(rawDataFile,'file')
disp(['Error: file ' rawDataFile ' not found e... |
82b21a9dc61f8053e92719f03be437ea9692f70dc51d05c489424d9c9a20bd86 | MATLAB | 834 | 30 | function viewdicom(I, rot)
% Function to view dicom file with a scrollbar
if nargin < 1
handles.rot = 0;
else
handles.rot = rot;
end
handles.figImg = figure;
handles.imgI = imagesc(imrotate(I(:,:,1), rot), [min(I(:)) max(I(:))])
colorbar
%axis square
colormap jet
sizefig = get(handles.figImg, ... |
60ab281b16a92ac06cc83570c8d7812b325a01f0bb7d449d368cc25c1d8a8238 | MATLAB | 835 | 32 | function nrgSig = nrg_calc(data,dsmtx,nMSD,nTR)
% Inputs
% data = data organised at TIME x NODES
% dsmtx = onsets for different events - list of TRs associated with each event type
% nMSD = maximum MSD range
% nTR = number of TRs to track
% Outputs
% nrg = MSD x TR x Energy
nReg = siz... |
a11577c374df45cdab5fd1c093ef4bdb8303a272515819d145cda8c81cecd22f | MATLAB | 836 | 26 | function data = decimateTLab(rawData,rawFs,dsRate)
%decimate - Reduce sampling rate of data
%
% [data] = decimateTLab(rawData,rawFs,dsRate)
%
% Description: This function reduces the sampling rate of a data set by
% applying a 10-th order butterworth filter at a cut-off frequency that
% is 45% of the new... |
7d7374b336717c58b0d49eda7e37195ada72aa72d7c63a88114d26325c94be2a | MATLAB | 837 | 27 | function FD = calc_framewiseDisplacements(Amats)
% Calculation 'framewise displacement' motion scores, based on
% Tisdall et al, MRM 2012
nT = size(Amats,3);
FD = zeros(nT-1,1);
for iT = 2:nT
% get difference in affine matrices:
thisDiff = Amats(:,:,iT) / Amats(:,:,iT-1);
mpars = mats2pars(thisDiff... |
3f0154703be674d6cb3107690f599b76e6c3d4b05a357c04a6da6a8d25b06062 | MATLAB | 839 | 29 | function vel = getVel(distTravel,Fs,winSize)
% Get Velocity
%
% vel = getVel(rawData,radius,Fs,winSize);
%
% Description: This function performs the simple manipulations to obtain
% velocity information from raw rotary encoder data.
%
% Input:
% - disTravel - Vector of distance traveled over time
% ... |
a75161048e4507824027a53c410de585663ede996d4edea8255269820f64b71c | MATLAB | 841 | 43 | function co = remove_big_lw(c1)
field_list = fieldnames(c1);
co=c1;
for npool = 1:length(c1)
nlw = c1(npool).linewidth;
seuil = mean(nlw) + 2 * std(nlw);
indrem1 = find(nlw>seuil);
nlw = c1(npool).water_width;
seuil2 = mean(nlw) + 2 * std(nlw);
indrem2 = find(nlw>seuil2... |
0085d225181462ccf4b0163fc666581c9d87443e6b7981ba783a40de07cf17df | MATLAB | 842 | 26 | function supp_fig3_gephi(folder)
%% Code for supplemental Figure 3: Mouse brain export to gephi
if nargin == 0
folder = 'All';
end
load(fullfile(folder, 'data'), 'map', 'nodelist');
load('structures', 'structures');
map = map.density;
map(map<0.005) = 0;
[a, b] = ismember(nodelist, structures.name);
nodelist = n... |
26a53bbc67573de2e26f2d4fce3e8444f4f12577efe5507376db9edd442c720c | MATLAB | 842 | 29 | function [Power, Freqs] = compute_power(Data, SampleRate, WindowLength, Overlap)
% Data is a channel x time marix matrix. SampleRate is a single value in
% Hz, WindowLength is a single value in seconds, overlap is a ratio from 0
% to 1.
% e.g.: [Power, Frequencies] = compute_power(Data, fs, 4, 0.5);
% Power is a Chann... |
ebc1ebec93f0bd9bf6be3367de936891efb2c1f0e067190611e2ed0432745ce3 | MATLAB | 842 | 30 | function [beta,modelfunc]=mnl_FitExponentialDecay_v2(X,Y,beta0)
%This is a much more streamlined version of mnl_FitExponentialDecay. Where
%it doesn't work out the RMSE etc.. it simply provides the co-ordinates.
%Also it doesn't faff around making a table. The addition is that I prevent
%negative numbers
%
%Marcus Leiw... |
057978dee4680817a2ed954515c179c531cb529adb79f48238ea7537274b0d4d | MATLAB | 843 | 44 | function co = remove_big_SD(c1,seuil)
if iscell(c1)
for k=1:length(c1)
co{k} = remove_big_SD(c1{k},seuil)
end
return
end
field_list = fieldnames(c1);
co=c1;
for npool = 1:length(c1)
for nf=1:length(field_list)
ind = findstr(field_list{nf},'SD');
if ind
cSD = getfield... |
73297197480ddda92b67ab859c6f7d99dc30f90d2ec547c414f0ca3ae8353041 | MATLAB | 843 | 45 | function concat_ps_file(d)
cwd=pwd;
for k=1:length(d)
dd=d{k};
cd(dd);
[p f] = fileparts(dd);
[p f] = fileparts(p);
[p pool] = fileparts(p);
pool = [pool,'_',f];
fps=get_subdir_regex_files(d{k},{'.*PS$','.*ps$'});
fps=char(fps);
cmdmerge = sprintf('LD_LIBRARY_PATH= ;psmerge -o%s.ps ',po... |
cfd033783f3c8e8b4a86875a73f428d2b8b5d6f91697bf1006ca1e9b11664d01 | MATLAB | 844 | 26 | % Copyright 2024 Eelke Spaak, Donders Institute.
% See https://github.com/Spaak/rift-phase-and-visibility for readme/license.
% Belongs with:
% Spaak, E., Bouwkamp, F. G., & de Lange, F. P. (2024). Perceptual foundation and extension
% to phase tagging for rapid invisible frequency tagging (RIFT). Imaging Neuroscience,... |
ec8734df99038b4df4c5f65f4791a0b9c074a01a026050b96250591dca615be7 | MATLAB | 844 | 19 | function [X,Y] = Rescale_Midline_Distance_And_Orientation(X0,Y0,R3,R4)
% Rescale midline distance to PVD raddi:
F3 = find(abs(X0) <= R3); % Find points that are between the midline and half-radius.
F4 = find(abs(X0) > R3 & abs(X0) <= R4); % Find points that are between the half-radius and radius.
X = abs(X0);
... |
0e2e59db705d8147b4dae88747e7be4058936de1587cd64688961c841856a164 | MATLAB | 845 | 39 | function [s,peaks] = PiCA5(dat,refslice,th,wlen,Itr)
N = size(dat,2);
w = floor(size(refslice,2)/2);
ref = dat(1,:);
% % % peaks = zeros(1,N);
% % % peaks(160:round(1025/2.4):end) = 1;
% % %
% % % [s,W,A] = PiCA(dat,peaks);
% % % ref = s(1,:);
% % % refslice = W*refslice;
for k = 1:Itr
refframe = ... |
ed84e0196a750de1a84e4acf4dc76f5da7a209ca4cc9fbe607c20e69793cb852 | MATLAB | 848 | 42 | function [N, S, W, E] = getCropCoords( im )
% takes away edges containing ones until all edges are all zeros
% set up initial parameters
[rows,cols] = size(im);
N = 1;
S = rows;
W = 1;
E = cols;
% shrink image until no more ones exist
finished = 0;
while ~finished
% get ratio of ones
rN = sum(im(N,W:E)... |
a0ea9e0fda3e8b27e6218f799aad7259232a560cb13b0e1ca960a03ede173548 | MATLAB | 849 | 25 | % Copyright 2024 Eelke Spaak, Donders Institute.
% See https://github.com/Spaak/rift-phase-and-visibility for readme/license.
% Belongs with:
% Spaak, E., Bouwkamp, F. G., & de Lange, F. P. (2024). Perceptual foundation and extension
% to phase tagging for rapid invisible frequency tagging (RIFT). Imaging Neuroscie... |
e432e05adb82ed32d157ba533e789c5b60a6563f0eab652f16c8ef6ff204ac6c | MATLAB | 850 | 30 | function freqs = genFreqs(freqName)
switch freqName
case 'HFB'
freqs = 2.^(6.15:0.05:7.4);
case 'HFB_raw'
freqs = 2.^(6.15:0.05:7.4);
case 'HFB_db'
freqs = 2.^(6.15:0.05:7.4);
case 'Spec'
freqs = 2.^([0:0.5:2,2.3:0.3:5,5.2:0.2:8]);
case 'SpecDenseLF'
freqs... |
01b6e34e8600152eca2b57536f5129980a9e0beaaf81bb91f466ad3f2ef19ab4 | MATLAB | 851 | 32 | %% load Data
load('../../Additional_Data/ONimageS.mat')
load('../../Additional_Data/OFFimageS.mat')
%% Calculate refpic
refpic = squeeze(mean(mean(ONimageS+OFFimageS,1),2)/2);
imshow(refpic/1e3)
save refpic refpic -v7.3
%% Using correlation to find trails with large artifact
ref = imgaussfilt(refpic,1);
CMat... |
4d19f543d4ed769845d562426c1eebd1358ba1f542efa35748eddb5456d29462 | MATLAB | 851 | 44 | function [params] = setparams(params)
if (~isfield(params, 'batchsize'))
params.batchsize = 128;
end;
if (~isfield(params, 'numepochs'))
params.numepochs = 1;
end;
if (~isfield(params, 'balance'))
params.balance = 0;
end;
if (~isfield(params, 'alpha'))
params.alpha = 1;
end;
if (~isfield(params, 'beta'... |
ed823d72ea6b5ec4d6ff9de2988d4b62110aca5d7a6f86b048b5d9da4fc0607e | MATLAB | 854 | 29 | function [test_indices train_indices ind]=cv_stratified_multilabel_DBP_speed(N,n_folds,bestmodel)
% N is the label matrix
%Stratifies by discretizing multiclass tracking data into one unique label
%after bining individual classes. The final discretized label makes up an
%combination of individual classes labels.
... |
68474b39b4b9fc1066bfe1db50d0ba72b7614cd9b9c967851228bf9bf302256a | MATLAB | 856 | 8 | function [peaks, peak_indexes] = PeakDetection2(x, fs, varargin)
% PeakDetection has been deprecated. Use
% peak_det_modified_pan_tompkins instead (with the new ksigma
% parameter), or replace PeakDetection2(data, fs, wlen, fp1, fp2, th, flag), with:
% peak_det_modified_pan_tompkins(data, fs, wlen, fp1, fp2, th, ks... |
c41adba68908689fc693237558fcf27cd95e150af3c2f57e5d4c9b4aed449ce6 | MATLAB | 857 | 27 | function output = XxNorm(data, tmin, tmax)
% ------------------------------------------------------------------------
% XxNorm: perform percentile normaliztion to data
%
% usage: output = XxNorm(data, tmin, tmax)
% where,
% output -- [0, 1] normalized data, data type is double
% data -- data to be n... |
cd620235f4c33037d08418ad5b9fa245f963f6df7ad1d9a170e376d1becbb0dc | MATLAB | 859 | 43 | function [vtx, vty, vtz] = tangdipoles(rx,ry,rz,theta_t)
sizr = size(rx);
sizt = size(theta_t);
assert(sum(sizt) == 2);
% GRIDS
% Get back R and unit vectors from passed grid
R = sqrt(rx.^2 + ry.^2 + rz.^2); %calculate |r| at each point
%getting normal vectors
erx = rx./R;
ery = ry./R;
erz = rz./R;
%Get theta and... |
97af8ed054cc0c933e8d65350cd50e1b9394bc7d9593f358aa886fe716d7dddf | MATLAB | 860 | 21 | %% add timing to
[file, path] = uigetfile('*.mat','MultiSelect','on');%When the user clicks the load psetion button, a window should open to enable the user to select a file.
datafile = fullfile(path, file); %save path
cd('H:\mPFC\shiras_data\PFC')
cd('E:\2023 - ledramp')
%%
for i = 1:length(file)
all_dat... |
cf3612f4ede88b0f2439d4d3e1652d3b05bf7b7c69083fbbec57a5aa3d799def | MATLAB | 860 | 23 | function startinfo(h,data)
% autocorrelatemap() and crosscorrelatemaps() depend on this function.
set(h,'Visible','off');
subplot(h);
cla;
inj = data.inj;
if length(inj)==1
str = sprintf('Experiment:\n%s\n',data.exp_id);
else
str = sprintf('Experiments:\n%s\n%s\n',data.exp_id{:});
end
str = [str ... |
47f674d097a6b2c4922cebcb253464035d7783bc6c9032db0f067d5bceefb7b8 | MATLAB | 861 | 46 | function s=get_spectrum(f)
for k=1%1:length(f)
s = fftshift(fft(f(k).fid),1);
end
if 0
aa=1:32:256;
az=(32:32:256 )
fid= f.fid;
for kk=1:length(aa)
f(:,kk) = mean(fid(:,[aa(kk):az(kk)]),2);
end
spec = f(1).spectrum;
resolution1 = spec.spectral_widht/(spec.n_data_points-1)/spec.synthesizer_frequency;
... |
00859f7e1aa5a505066a94386a3e7077fa894878b539254eaa05e229e31150d6 | MATLAB | 864 | 39 | function sample = time2sample(ts, varargin)
% defaults
FS = 195312.5;
T1 = 0;
T2 = 0;
TO_TIME = 0;
VALID_PARS = {'FS','T1','T2','TO_TIME'};
% parse varargin
for ii = 1:2:length(varargin)
if ~ismember(upper(varargin{ii}), VALID_PARS)
error('%s is not a valid parameter. See help time2sample.... |
4d0cf3a2f6511dfdaeeb2f890caca40644159c4ae814515e109e0f99cf2d29ab | MATLAB | 864 | 24 | function scatterplot(h,data)
%% Set dimensions of the graph
% draw1experiment() and draw2experiments() depend on this function.
load('structures','groups');
subplot(h);
set(h,'DataAspectRatio',[1 1 1],'Color','None','Box','off','Fontsize',8);
hold on;
gr = length(groups.name); % Number of hyperstructures, 15
... |
5f1c32741d47a8e38f48c54cd58afb594b6de676550263867a0af0b42120e21a | MATLAB | 864 | 29 | % Find the taus of the biexponential funtion
% that fit a linear predictor
% computed from linear prediction
% Input
% tau_0 & tau_0: vector of starting taus
% r_data: vector from the response function computed from lp
% t_data: vector of time
% Output
% taus, paramteres that fit the biexponential the r_data
% r ... |
c184bf10018f30304108daf063f3ca0ad78abd9468e55d1db0a756c63136d06c | MATLAB | 864 | 25 | function [temp] = find_temp(tree, par)
% Selects the temperature.
num_temp = floor((par.maxtemp-par.mintemp)/par.tempstep); % total number of temperatures
min_clus = par.min_clus;
aux = diff(tree(:,5)); % Changes in the first cluster size
aux1 = diff(tree(:,6)); % Changes in the second cluster size
aux2 = di... |
563255db2fc96b5f49237dc3ae1db1620659db8e5e35db9b50c2e31a39118665 | MATLAB | 865 | 31 | %% unit testing for spmup_temporalSNR
%
% the model is simple with 4 'boxes': GM, WM, CSF, background
% noise is white noise everywhere (std = 1), and the signal is a simple cos
% added with amplitude 1 (background) 2 (GM) 3 (WM) and 4 (CSF)
% ------------------------------
% Cyril Pernet 05 January 2016
%% get data
... |
9ccc9e82dd0c83c8301802a20719d6fde9f5e6ec13f517f84f2554888a78b65a | MATLAB | 865 | 29 | function Extend_Margins_Multiple()
R = 0.2; % Ratio of rows # and cols # for border extension.
Path1 = uigetdir; % Let the user to manually choose a directory.
Files_List = List_All_Files(Path1,'tif'); % List all .tif files in this directory (including sub-directories).
for f=1:numel(Files_List)
Im = i... |
a849b810d70508a39e0ca6c96da7e1ddfaafe21553a0c2580fde1be724043a77 | MATLAB | 865 | 29 | % function to plot Cummulative Distribution Function
% of the data at input cell
function plot_cdf_cell(RoA_All,Names_Conditions,ColMap)
NC=size(ColMap,1);
CDFfig=figure;
CDFfig.Name='Cummulative Function Distribution';
ax1=subplot(1,1,1);
hold(ax1,'on');
for c=1:NC
% if ~isempty(RoA_All{c})
if c<=numel(RoA_Al... |
33c688b18beadbf5d175fdf86eb05ae54d73b5b19ad35ce3220afb07d6d3d0fb | MATLAB | 866 | 36 | function DI=dunns(clusters_number,distM,ind)
%%%Dunn's index for clustering compactness and separation measurement
% dunns(clusters_number,distM,ind)
% clusters_number = Number of clusters
% distM = Dissimilarity matrix
% ind = Indexes for each data point aka cluster to which each data point
% belongs
% Julian Ra... |
3d2439db30873d464db5ccc44c72fdbf2b70bb07e7d8c2ffd9ac2ee98f7870c6 | MATLAB | 866 | 33 | function ScorePAth = ScorePatho(subIDX)
%fn = fullfile(Dpath,'Scores_Neuropsycho_Psychopatho_TOUT_Manon_cp');
%ALL_data = readtable(fn);
ScorePAth = {};
RCMAS = [26;17;22;19;26;10;25;14;16;14;7;3;26;...
17;18;21;25];
ScorePAth.RCMAS = RCMAS(subIDX);
CDI = [18;26;15;24;41;20;31;19;8;1... |
9edfc776cb45aa0d643cea1e6d8d651295c094987d437c5de373e81bc4111d40 | MATLAB | 866 | 37 | function y = reshaper(x, dim)
%|function y = reshaper(x, dim)
%|
%| reshape function that is more flexible, allowing for "multiples".
%| example: reshape(rand(2*3*5,7), [2 3 5]) will become [2 3 5 7]
%|
%| in
%| x [*dim (Ld)]
%| dim short row or column
%| if dim is '2d' then y is 2d with first n-1 dims collapsed
%|
... |
c52ce6916fabb87adbd5a9a20fa3646439e0c774ad807a93d7c4cf630c55e8d9 | MATLAB | 867 | 20 | function spikeWindows2 = samplesToWindows2(obj, samplesIn, spikeSites, spikeTimes)
%SAMPLESTOWINDOWS2 Get spatiotemporal windows around SECONDARY peaking
% events as 3D arrays (filtered samples assumed)
nSpikes = numel(spikeSites);
nSitesEvt = 1 + obj.hCfg.nSiteDir*2; % includes ref sites
% nSample... |
6a53660ebec77928691fa8a8b5a48cc679f82040b7e42d7084d95271baff677b | MATLAB | 868 | 24 | function Segment = Connect_Using_Skeleton(Segment,Im_Rows,Im_Cols,Scale_Factor)
[Ys,Xs] = ind2sub([Im_Rows,Im_Cols],Segment.Skeleton_Linear_Coordinates);
X1 = Segment.Rectangles1(end).X;
Y1 = Segment.Rectangles1(end).Y;
D1 = ( (Xs-X1).^2 + (Ys-Y1).^2 ) .^ 0.5; % The distances of all skeleton coordinates from the... |
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