sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
d90f6b315dc9e7afa769961eadfef717f0f113388fe1f6b75ef327c32b4b1b9b | MATLAB | 2,152 | 80 | function [linear_score,out]=line_fitting(decoded_event)
FIGURES_ON=0;
[position_bins,time_bins]=size(decoded_event);
time_bins2 = min([time_bins position_bins]);
max_value=max([time_bins2 position_bins]);
slope=(2/max_value):(2/max_value):.999;
slope=[slope 1 fliplr(1./slope)];
if FIGURES_ON
figure
end
for s=1... |
bbad21b75c65724f5e27c948509865edf11c2349d12641b08dd18a4e5e615f6c | MATLAB | 2,154 | 62 | %%% Computes the extrinsic parameters for all the active calibration images
check_active_images;
N_points_views = zeros(1,n_ima);
for kk = 1:n_ima,
if exist(['x_' num2str(kk)]),
eval(['x_kk = x_' num2str(kk) ';']);
eval(['X_kk = X_' num2str(kk) ';']);
if (isnan(x_k... |
057b3e9cd5359ccb6ef0269944c6495ff629b9274b8a24b2f83f8f7e10d5788c | MATLAB | 2,155 | 69 | %% empirical_confint
%
% Confidence intervals for sample statistics based on estimated empirical null distribution
%
% <matlab:open('empirical_confint.m') code>
%
%% Syntax
%
% [xup,xlo] = empirical_confint(alpha,X,ptails,ksmooth)
%
%% Arguments
%
% See also <mvgchelp.html#4 Common variable names and data structure... |
3bdec3ba6977eae204a4d19c2778adb39f99f364fe8a28327d6ca679c3b2afc3 | MATLAB | 2,155 | 43 | dataset = 'defcon_rct_46pp.txt';
% Fixed variables
v = generate_main_variables();
% Run fitting function
[bvc_loglik,fr_loglik, fd_loglik, uniform_loglik, bvc_prob, fr_prob, fd_prob, bvc_logprob, fr_logprob, fd_logprob] = fit_bvc_and_other_models(v, dataset);
df = readtable(dataset);
uniform_logprob = repmat(log(1/... |
4e21ea2aa3bee8dac26a2a4d97010d6b970b544f87f618a8a966bfb603225909 | MATLAB | 2,155 | 88 | %% Detect small calcium transients
Tr = traces;
disp('Detecting SCEs...')
[NCell,Nz] = size(Tr);
% Savitzky-Golay filter
Tr = sgolayfilt(Tr',3,5)';
% figure
% for i = 1:NCell
% plot(time,traces(i,:)+i-1)
% hold on
% end
% Detect Calcium Transients using a sliding window
TrRest = Tr(:,mvm.restEpochsIndex);... |
698ff1cf79921960e2f384a3ea1e6198eaea4b5811b200b76ee8ca03fcb34d81 | MATLAB | 2,155 | 96 | % Infer 1d function from observing its average value over various intervals
function gauss_infer_1d_function_from_avg()
Bs = [1, 5, 10, 20]; % bucket width
sigmas = [1e-3, 1e-1];
for i=1:length(Bs)
for j=1:length(sigmas)
B = Bs(i);
sigma = sigmas(j);
run_demo(B,sigma)
end
end
function r... |
347d1ce7c50236b41c0dfea74078bf332a14ae21abe61e922f81be5a1b230049 | MATLAB | 2,156 | 31 | psthPara.binsize = 10; psthPara.binstep = 10; % ms
tIndex = ([trialAll.stdNum] >= sIndex & [trialAll.correct] & [trialAll.oddballType] == "DEV")|([trialAll.stdNum] >= sIndex-1 & [trialAll.correct] & [trialAll.oddballType] == "STD");
trials = trialAll(tIndex);
trialsSPK = trialsSpike(tIndex);
% spike
spkStd(sInde... |
5db4abf07bb5310fb3b686dea734f909fe362cb6f4a870aa7ce589a53a9b0108 | MATLAB | 2,156 | 51 | function [permutedVector] = randPermContiguous(inputVector)
%Generates a random permutation of a binary vector, maintaining sizes of clusters of 1's.
%That is, if the input vector is [ 0 1 1 1 0 0 1 1 0 1 0 0 0 0 0 0 0 0 0 ...],
%the output will have one cluster of three 1's, one cluster of two 1's,
%a... |
a702ecd6b88265b55cad7e56b46495ee6a2056b5107243ae7d4e7e0a44d36318 | MATLAB | 2,156 | 64 | function M=movcw4at(N,Np);
%MOVCW4AT Four atoms rotating, analyzed by the Choi-Williams distribution.
% M=MOVCW4AT(N,Np) generates the movie frames illustrating the passage
% from the spectrogram to the WVD using different smoothing gaussian
% windows in the smoothed pseudo-WVD.
%
% N : number of points of the analyz... |
fce8b3713cbfe795486d94a1890f0c80f2d1df2e47217b97d3cae94a5ad99b2c | MATLAB | 2,156 | 84 | function anytoavi(inmoviename,outmoviename,varargin)
% function anytoavi(inmoviename,outmoviename[,'firstframe',1][,'endframe',nframes])
% pairs in [] are optional and the default value are as shown above.
[readframe,nframes,fid] = get_readframe_fcn(inmoviename);
[firstframe,endframe,aviparams] = myparse(varargin,'fir... |
3b26d55ee697639264beb2be4cde8f0633493dca64c57b4f71200bb3383abddf | MATLAB | 2,157 | 77 | function [] = transformQuiver(imgPair)
%% Figure out axis convention
% x = [10:10:50];
% y = [10:10:30];
% [x,y] = meshgrid(x,y);
% figure;
% quiver(x,y,2*ones(size(x)),ones(size(x)),0)
% set(gca,'YDir','reverse');
%% real stuff
%decimate transform field
spacing = 20;
mytform = imgPair.moving.F;
sizeTform = size(myt... |
41eecef888004df96098b6f43a6be15d12ad58c837a6e83379d7e97f2d6c63d2 | MATLAB | 2,157 | 70 | function t = subsasgn(t,s,b)
%SUBSASGN Subscripted assignment for sptenmat.
%
% Examples
% X = sptenmat(sptenrand([3 4 2],10),1);
% X(1:2,1:2) = ones(2,2); <-- Calls SUBSASGN
%
% See also SPTENMAT, SPTENMAT/SUBSREF.
%
%MATLAB Tensor Toolbox.
%Copyright 2015, Sandia Corporation.
% This is the MATLAB Tensor ... |
6ecafcece13be72d00f100039097bf3b641ee7c28ca106842e5c3d0f79826fc9 | MATLAB | 2,157 | 64 | function [opts, args] = hcp_getopt(varargin)
% HCP_GETOPT parses the command line to the megconnectome executable
% application, separating the options that start with -- from the file
% names of the scripts to be executed.
%
% Use as
% megconnectome.exe --option1 arg1 --option2 arg2 scriptA.m scriptB.m
% splits the... |
b0e7f8983cb4904167157541f3f638e59dc87f8dfe2c368f625c9d5d8fa3ecdd | MATLAB | 2,157 | 64 | function [opts, args] = hcp_getopt(varargin)
% HCP_GETOPT parses the command line to the megconnectome executable
% application, separating the options that start with -- from the file
% names of the scripts to be executed.
%
% Use as
% megconnectome.exe --option1 arg1 --option2 arg2 scriptA.m scriptB.m
% splits the... |
fa9a7f919998a28caa5f25ef7ef24c891d63de27e38389bc61ffa156a3f2abeb | MATLAB | 2,157 | 42 | %% Create a new dataset with all subjects averaged across mov-nomov
% If a SJ do not have a mov condition, take only nomov
% BEFOREHAND: Load mov and nomov datasets ('12_eeglab2fieldrip') and rename
% *_mov and *_nomov, respectively
% output paths:
path_data_eeg = 'D:/NeVRo/new_HEP_data_filtHP_0_3Hz/';
path_out_eeg ... |
4465a234d728c7f02a22e59d6d1f752d1a6aa1150fd8a765ca9a902e11ee4dc9 | MATLAB | 2,158 | 46 | clear
clc
close all
nb_models = 1000;
stimAmp_step = [-53];
% stimAmp_diffusion = (2:0.1:2.5);%-53*(0.5:0.3:1.5);
t = 0:100;
Istim = get_diffusion_current(t, 1);
max_Istim = max(Istim);
% stimAmp_diffusion = unique(round(stimAmp_diffusion*max_Istim));
stimAmp_diffusion = [11]; % Calibrated to achieve stimulation of... |
3b2e6e7907aa34136f1088d151ce5e28b5fdd8d09c69f8a2d00c1d1955b5a1be | MATLAB | 2,159 | 72 | function Plot_Bump_Examples(DarkData, ttt, Seg)
% Plot 40s examples of the bump for specified trials and segments
PlotWindow=40; % seconds
Time = DarkData.TwoP_Times(ttt,:);
Time = Time - Time(1);
% Get indices for this segment
starttemp = (Seg-1)*PlotWindow;
stoptemp = starttemp + PlotWindow;
logica ... |
6513631fdd907a696e1abbe111ebfcfd12f80604c8959c9f31a211dc067e93b1 | MATLAB | 2,159 | 51 | % makeBarcode3DPlots
function makeBarcode3DPlots(transcriptsDir,groupList,saveDir)
loadParameters;
load('groundtruth_codes.mat');
f = figure;
f.Position=[1000 100 900 900];
xlabel('X'); ylabel('Y'); zlabel('Z');
whitebg('black');
for i = 1:length(groupList)
disp(['group=',groupL... |
825ffb515ad6a48ca94b2b354b1454866d9dbf0be297980613326b8d91ef7adf | MATLAB | 2,159 | 77 | %
% Author: Javier Lopez-Calderon
% Center for Mind and Brain
% University of California, Davis,
% Davis, CA
% 2009
%b8d3721ed219e65100184c6b95db209bb8d3721ed219e65100184c6b95db209b
%
% ERPLAB Toolbox
% Copyright © 2007 The Regents of the University of California
% Created by Javier Lopez-Calderon and Steven Luck
% Ce... |
a4a0c87f14156b4a353f49e26efe5bb80675f08f21db36f1a2552dbb1b4382e4 | MATLAB | 2,159 | 73 | function [model, bestParam, mu, se] = ...
fitCvPath(fitPathFn, predictPathFn, lossFn, X, y, extractPathFn, varargin)
%% Fit regularization path and use cross validation to pick the best point
%
% Inputs:
% models = fitPathFn(Xtrain, ytrain)
% This should return models.lambdas
% yhat = predictFn(models, Xtest): yha... |
e4f05b4f023e38e53375cfa294b014242a3bf70d1f4dbe4161dc88c5ab2c6844 | MATLAB | 2,159 | 81 | function [hEllipse,X,Y] = ellipsearcdrawpatch(theta0,theta1,a,b,x0,y0,phi,lineStyle)
%ELLIPSEDRAW can draw an arbitrary ellipse with given parameters.
% The properties of that ellipse plot can be customized
% by setting the ellipse handle.
%
% hEllipse = ellipsearcdraw(theta0,theta1,a,b,x0,y0,phi,lineStyle)... |
06f2cbbd7c898fc2d000921bf6fc4739cac5309592da8e53ca10561451fc030e | MATLAB | 2,160 | 49 | % Demo for aggregate channel features object detector on Caltech dataset.
%
% See also acfReadme.m
%
% Piotr's Computer Vision Matlab Toolbox Version 3.40
% Copyright 2014 Piotr Dollar. [pdollar-at-gmail.com]
% Licensed under the Simplified BSD License [see external/bsd.txt]
%% extract training and testing image... |
3918e8adcf2302ce987041366e6878f6487882717efdc5a511bf1b4ddeab0043 | MATLAB | 2,160 | 54 | % Support Function which forms of the basis of analysis between a
% ppDataCell and xtDataCell
%_______________________________________
% Copyright (C) 2024 Trevor S. Smith
% Drexel University College of Medicine
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU G... |
eda881eacbe35a0c44c7ada8566ca9a43cdad3b56fdab37505206ddf3adf00a3 | MATLAB | 2,160 | 58 | clear
close all
clc
%% Load atlas
% path to MRI template - must include hdr and img files
atlas = niftiread('/Users/jstrohl/Documents/20230908 Pipelines for neural data analysis/Dependencies/ATLAS-MICE 2/2011-10-30_MRI-template3.hdr', ...
'/Users/jstrohl/Documents/20230908 Pipelines for neural data analysis/D... |
f25525736d329c8039986e5869acae1298f8fd5f5d44e8eb9a965654da4276fa | MATLAB | 2,160 | 90 | % Sampling from an Ising model using Gibbs
% Based on code by Brani Vidakovic
% http://www2.isye.gatech.edu/~brani/isyebayes/programs.html
function gibbsDemoIsing()
pixelX = 100;
pixelY = 100;
%{
temps = [5 2.5 0.1];
seeds = 1;
Xsamp = zeros(pixelX, pixelY, length(seeds), length(temps));
for t=1:length(temps)
... |
8007a887b0d2379b6b932ea3be576d5a28bf2956adf9c6a8d50ce453a7ff80eb | MATLAB | 2,161 | 69 | function mscmd_bandpass_filter(input_path,output_path,opts)
%MSCMD_BANDPASS_FILTER - Bandpass filter using smooth roll-offs in Fourier space
%
%The is the mountainsort version of ms_filter
%
% Syntax: mscmd_bandpass_filter(input_path,output_path,opts)
%
% Inputs:
% input_path - mda file of MxN input timeseries data... |
a65fcc56a0af49e2efa4253e8c6e05bc2ed10cc29e9a8fca87a8baf928a70309 | MATLAB | 2,161 | 88 | function z = lt(x,y)
%LT Less than for sptensors.
%
% See also SPTENSOR.
%
%MATLAB Tensor Toolbox.
%Copyright 2015, Sandia Corporation.
% This is the MATLAB Tensor Toolbox by T. Kolda, B. Bader, and others.
% http://www.sandia.gov/~tgkolda/TensorToolbox.
% Copyright (2015) Sandia Corporation. Under the terms of Cont... |
1ad5cd0f140e916ee151a963be85632b370c9486f15bc0df1ea86efe97c07eae | MATLAB | 2,162 | 67 | function [muPost, SigmaPost, logZ, lambda] = varInferLogisticGaussMissing(y, W, b, muPrior, SigmaPriorInv, computeLoglik)
% Just like varInferLogisticGauss except y(t) may be NaN
% This file is from pmtk3.googlecode.com
maxIter = 3;
%[maxIter, computeLoglik] = process_options(varargin, ...
% 'maxIter', 3, 'computeLo... |
4bcb2a887c127ab753c901673329c867a133485eb6ea8ab9fc9fdaecf4aec3b6 | MATLAB | 2,162 | 72 | function [Samp, Sph] = waveletSpectro(SIG, FE, FRANGE, ResHz, step)
% [Samp, Sph] = waveletSpectro( SIG, FE, FRANGE, FRANGE,ResHz, step)
% [Fft] = waveletSpectro( SIG, FE, FRANGE, FRANGE,ResHz, step)
% uses a FFT transform to compute the spectral power and phase values, of a matrix of signals 'SIG'.
% The smaller dimen... |
7f22df31a3a968a7cb2f7b83fdb22e3f427798fcdafbad34f651604a8c69e22b | MATLAB | 2,163 | 69 | function [m,dfe,ci,sd,n,t,p] = limo_ttest(type,data1,data2,alphav)
% [m,dfe,ci,sd,n,t,p] = limo_ttest(type,data1,data2,alpha)
% implement the one-sample t-test, paired t-test (type = 1)
% and the two samples t-test (type = 2). The ttest is performed on the last
% non-singleton dimension, which can be subjects or tria... |
971821da34ad6aefbe117ce67d1ce5e0d27bf57e9e8c2e80727413e0b63fa377 | MATLAB | 2,164 | 64 | classdef handle_light < handle
% handle class hiding some methods to not lose overview in list of
% methods of a class
%---------------------------------------------------------------------
% license
%---------------------------------------------------------------------
% Copyright 2015 Id... |
aca42ddc5d576194f2c267ad16f5effa61ce69dd698aa1aa5df112dc9bb55dbd | MATLAB | 2,164 | 62 | function I = localSum( I, dims, shape, op )
% Fast routine for box, max and min filtering.
%
% Same effect as calling 'C=convn( I, ones(dims), shape)', except more
% efficient. Computes local sums by using running sums. To get sum in
% non-overlapping windows, use shape='block'. Equivalent to doing localSum,
% and then... |
c81f168dc187c764bd8daeb21baea20a00b0a8ec072b8fd85d7763c7c0547834 | MATLAB | 2,164 | 88 | function [f,G] = tt_cp_fg(Z,A,Znormsqr)
%TT_CP_FG Computes function and gradient of the CP function.
%
% [F,G] = TT_CP_FG(Z,A) calculates F = (1/2) ||Z - ktensor(A)||^2 where
% Z is an N-way tensor and A is a ktensor or a cell array with N
% factor matrices. It also calculates the gradient of the CP fit
% funct... |
5ca8cf1fb7b250603e1015f5885497eb60da72abfc397a8c1a49758083e96ffe | MATLAB | 2,165 | 64 | function [O_trans,Spacing]=MakeDiffeomorphic(O_trans,Spacing,sizeI)
% This function MakeDiffeomorphic will make the b-spline grid diffeomorphic
% thus will regularize the grid to have a Jacobian larger then zero
% for the whole b-spline grid.
%
% [Grid,Spacing]=point_registration_diffeomorphic(Grid,Spacing,sizeI)
... |
b7b9f825db73d71fc1973f4991096041e3d78083e58f90c7fa8124d330a9c994 | MATLAB | 2,165 | 51 | function [s, cfg] = ft_statfun_diff(cfg, dat, design)
% FT_STATFUN_DIFF computes the difference of the mean in two conditions. Although it
% can be used for statistical testing, it is not very usefull since it will have
% rather limited sensitivity.
%
% The purpose of this function is to show you an example on how to... |
d48fa8dd5491f0acb06c5a2e6c8955b2eed040ac00b2ad5c63d5819d8e54a507 | MATLAB | 2,165 | 77 | function [C,H] = vol3d( M, ax, c )
% VOL3D Measures the size of connected objects along 2D slices
% INPUT:
% M - Binary input tomogram
% ax: Reference axis (1->x, 2->y, otherwise->z)
% c: 2D connectivity, either 4 or 8
% OUTPUT:
% C: Tomograms with components classfied by their volume
% ... |
251162a752ad6fc2bf9996a66e07e4a733faea7102e39322399f0f4ff140ce3e | MATLAB | 2,166 | 53 | areatxt{1} = 'lip'; areatxt{2} = 'fef';
timevector = -0.05:0.001:0.2;
rgb = [0.1 0.4 0.5; 0.7, 0.4, 0.7];
labels = [{'Singleton distr in RF'}; {'Non-singleton distr in RF'}];
for iArea = 1: 2
figtitle = upper(areatxt{iArea});
xlimToPlot = [-0.05 .2];
figure('Name', figtitle , 'NumberTitle', 'off'... |
6950fbe455f9332542cdd2dd1f5717cfa14fe02e99efe75200028868f3814ade | MATLAB | 2,166 | 61 | function CM = confMatrix( IDXtrue, IDXpred, ntypes )
% Generates a confusion matrix according to true and predicted data labels.
%
% CM(i,j) denotes the number of elements of class i that were given label
% j. In other words, each row i contains the predictions for elements whos
% actual class was i. If IDXpred is pe... |
8e6496de9c241baf9301e145a3a5d0cf5a1e0b83723a88eea22dcc1fbfa523bf | MATLAB | 2,168 | 109 | function tests = mex_semaphoreTest
tests = functiontests(localfunctions);
end
function setup(testCase)
semaphore('/t','unlink');
end
function teardown(testCase)
semaphore('/t','unlink');
end
% normal test cases
function testOpen(testCase)
ret = semaphore('/t','open',3);
verifyEqual(testCase,ret,... |
a42a2da1178a4e4a2e1ae2d85d6ac67cb8475a7033f5e922b6b96980a728660d | MATLAB | 2,168 | 58 |
function [parameters] = ncomponents_std_correlate(parameters)
MessageToUser('Running ', parameters);
if ~isfield(parameters, 'ncomponents_concatenated')
parameters.ncomponents_concatenated = [];
parameters.sigmas_concatenated = [];
end
% Get the list of mice not to... |
95f4c62dd9a6db07c115200cacc43b75765b87f2a05bb8915a8c5797622179b8 | MATLAB | 2,169 | 42 | function [y,u,f_fname,g_fname,dim,options,in] = VBA_getDefaults()
% outputs default input to VBA_NLStateSpaceModel.m
% function [y,u,f_fname,g_fname,dim,options,in] = VBA_getDefaults()
%
% This function provides the defaults inputs to the main
% VBA_NLStateSpaceModel.m routine. See VBA_check.m routine.
%------- ... |
0a8d334c2e70068e6fa6b923cf8c6c38d30004ee4bd82d9be115f546a84c4918 | MATLAB | 2,170 | 55 | function onesample_t(out_dirs,scans,covariates)
for ii=1:length(out_dirs)
%model specification
matlabbatch=[];
matlabbatch{1}.spm.stats.factorial_design.dir = out_dirs(ii);
matlabbatch{1}.spm.stats.factorial_design.des.t1.scans = scans{ii};
if ~isempty(covariates)
for jj=1:length(covariates... |
156fbba2ff5296eb0ec69dea36cacfa16fd2dfc170695997716b875b72763960 | MATLAB | 2,170 | 76 | %% fMRI analysis script for:
%% The transformation of sensory to perceptual braille letter representations
%% in the visually deprived brain
% Marleen Haupt and Monika Graumann
% 22.02.2024
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Preprocessed fMRI data has to be downloaded to data folder
%%%%%... |
1957051e75ecce115414323970f220932c2513c029caf12bcec890e29995724e | MATLAB | 2,170 | 66 | function [ddydphi, d2gdx2, logL, dy, dy2, vy]= VBA_get_dL (gx, dG_dPhi, y, type, Qy, sigmaHat)
% // VBA toolbox //////////////////////////////////////////////////////////
%
% [ddydphi, d2gdx2, logL, dy, dy2, vy]= VBA_get_dL (gx, dG_dPhi, y, type, Qy, sigmaHat)
% Compute usefull intermediate values describing the misfit... |
6ec9c75b38c5638658d00648b7e1e3fb5c1251585570779f76544656a0978ecf | MATLAB | 2,170 | 62 | %%% Computes the extrinsic parameters for all the active calibration images
check_active_images;
N_points_views = zeros(1,n_ima);
for kk = 1:n_ima,
if exist(['x_' num2str(kk)]),
eval(['x_kk = x_' num2str(kk) ';']);
eval(['X_kk = X_' num2str(kk) ';']);
if (isnan(x_k... |
3f88edaa83ee613f7346ed88f4abecf63112939fbe087343f89090a24b555a44 | MATLAB | 2,172 | 108 | function results=VBA_bDCM_lesion(posterior,out)
%% Get normal profile
%% test lesions of each area
nx = size(out.options.inF.A,1);
out.options.verbose = 0;
out.options.displayWin = 0;
out.options.multisession.expanded = 1;
out.dim = VBA_check_struct(out.options.dim, ... ,
'u',size(out.u,1) ,...
'n_t... |
0a43187f1ea05cf1ccb3ccb83015bd2fa093cb4667a158770fe33653c457a9fc | MATLAB | 2,173 | 57 | function [FRorig, FR] = getDataForDPCA(AllTrialData,timeWindow,Phase,varargin)
[varargin,SmoothingKernel]=Utilities.ProcVarargin(varargin,'SmoothingKernel',.55);
[varargin,meanThresh]=Utilities.ProcVarargin(varargin,'meanThresh',1.5);
[varargin,TaskLabel]=Utilities.ProcVarargin(varargin,'TaskLabel','XBodySpec');
... |
599a949313a35ebfe5e59b67ad79b5480a04b36cbb5ac6d80ed05423a54c5d45 | MATLAB | 2,173 | 88 | function [perf_matrix_loc,perf_matrix_frq] = compute_model_psychometrics(model)
unpackStruct(model)
n_units=length(wO);
facto=0.9; %model_tau = 100ms
easiest=4; %evidence strength for easiest trial
ntrials=10; %number of trials per condition
gi=linspace(-easiest,easiest,6);
for i=1:length(gi)
for j=1:leng... |
ca8c2c6c6f49266f93e8aa5704b6549f0fa31a30d5d28fbcad34debf4ee34db2 | MATLAB | 2,173 | 49 | %this function will return a threshold value for a minimum number of spots
%at a single pixel that have been filtered the same way that the maps have
%to determine a lower limit for RF selection
function Threshold=SpotThresholdFinder(NumEvents,NumRecordings,FilterSize,FilterSigma)
SpotTestImage=zeros(20,20);
... |
d8c8e8c3ad24cd3ca92893e1a76e6809b737c15f267d001814b6882565c3b90d | MATLAB | 2,173 | 61 | function [num,dims]=dimnum(dimord, dim)
% This function returns the number of the given dimention 'dim' in the dimord string.
%
% Syntax: [num,dims]=dimnum(dimord, dim)
%
% e.g. when dimord='rpt_chancmb_freq_time' and dim='time', dimnum returns num=4
% and dims contains {'rpt','chancmb','freq','tim'}.
% e.g. when... |
e10caac910db6e724f343bb969eadd349af65c093142208fd48452223ff71faf | MATLAB | 2,173 | 57 | function [varargout] = isfolder(varargin)
%ISFOLDER Determine if the input path points to a folder
% TF = ISFOLDER(PATH) returns true if PATH points to a folder and false otherwise.
%
% This is a compatibility function that should only be added to the path on
% MATLAB versions prior to R2017b.
%%%%%%%%%%%%%%%%%%%%%... |
6e4f51829ccd27941640b21e702ff60aea9d5012b5a69df6b073e238fb8e6d4a | MATLAB | 2,174 | 84 | % By Ariel Zylberberg
%%
do_save_flag = 1;
[t, TIN, TOUT, EC, EI, CHOICE, RT, COH, SESSION] = get_and_prep_data();
save(fullfile(saveLoc, 'data_for_corr_analysis'), 't', 'TIN', 'TOUT', 'EC', 'EI', 'CHOICE', 'RT', 'SESSION')
%%
X = {EC-EI,EC, EI, EC,TOUT,cumsum(EC-EI,2)};
Y = {TIN, TIN, TIN, EI,TIN, TIN};
XLABEL = ... |
7ef4414b0c7b3ddf4ac517e8bb9cc70aadbf5671039cccf23378babce56acf6a | MATLAB | 2,174 | 59 | % Author: Birgit Nierula (Feb, 2020)
% nierula@cbs.mpg.de
%% SRMR_01: automatic R-peak detection
% This script was run after the sript SRMR1_00_importData.m and
% 1) performs an automatic R-peak detection on the ECG channel
ana_dir = '/data/pt_02068/';
cfg_path = [ana_dir 'analysis/manuscript_sep/scripts/cfg_srmr1/... |
bb74e0a35cdfd77181059b90fe0755801132e2a6be0283a794a1fe66ab195e67 | MATLAB | 2,175 | 73 | %% cpsd_to_autocov
%
% Calculate autocovariance sequence from cross-power spectral density
%
% <matlab:open('cpsd_to_autocov.m') code>
%
%% Syntax
%
% [G,q] = cpsd_to_autocov(S,q)
%
%% Arguments
%
% See also <mvgchelp.html#4 Common variable names and data structures>.
%
% _input_
%
% S cross-power spec... |
474ae8e93c96a91d553a48e2ea2de5e9a8dc53d62004bebd741279f41df55098 | MATLAB | 2,176 | 81 | function [Model Info parm W] = testjob(xdata, ydata, xtest, ytest)
% --- training method ID
method_id = 2;
% 1: linear_sparse_space
% 2: linear_sparse_space_vec
% 3: linear_sparse_stepwise
% 4: linear_sparse_stepwise_vec
% --- Basic Learning Parameters
parm.Ntrain = 100; % # of total training iteration ... |
72a16d65150a9344d6b1d87628f667b9cb7b909750b8079a7d81420082d55c24 | MATLAB | 2,176 | 55 | function [h,p] = plotDistribution(logprobFn, varargin)
%% Plot a density function in 2d
% handle = plot(logprobFn, 'name1', val1, 'name2', val2, ...)
%
% '-xrange' - [xmin xmax] for 1d or [xmin xmax ymin ymax] for 2d
% '-useLog' - true to plot log density, default false
% '-plotArgs' - args to pass to ... |
d4ebbaf657f61df7df8883658e40595fc64d8de670978bc6f79035e24e34efcf | MATLAB | 2,176 | 75 | function plotContours(fov,cell_n,centroids,centroid_color,background_type,background_color)
%% >>> OPERATION >>>
% Plot contours of selected cells for defined field of view
% >>> INPUT VARIABLES >>>
% NAME TYPE, DEFAULT DESCRIPTION
% fov double field of view (image or mov... |
e27abe3d20101d54c5d6308d4643f60741150469a60310bf8c75cfa2ef2bdca5 | MATLAB | 2,176 | 70 | %% Fit an HMM and an equivalent DGM, making sure the results agree
%
%% sample data
%
% Note, unlike hmmFit, dgmTrain does not use cell arrays,
% instead it takes an NaN-padded matrix of size
% nobs-by-d-max(seqLength). You can use the localEv2HmmObs
% and hm... |
0671f950bab2dfa8a0d1e3a2103ba262948b77af4158a6e0eddbb35087c01fb9 | MATLAB | 2,177 | 50 | %% ------------------------------------------------------------------------
% configuration
% every line contains three fields:
% 'filename'
% 'legend text'
% 'Marker'
% 'Color'
% 'MarkerFaceColor'
% 'TextPosition': [x, y]
% ----------------------------------------------------... |
7c078cd531b35e04c8a8b9c3668e8a1ad5ba8c649dcc8faa04c5fd8e0f2584ce | MATLAB | 2,177 | 44 | for k = 1:length(Y)
clf;
y = Y(k);
% Display NIFTI slice
I = round(y/d1d2d3(2) + N1N2N3(2)/2);
S = squeeze(VT1(end:-1:1, I, :))'; % choose the Y cross-section
S = S(:, :);
image([-DimensionX/2 +DimensionX/2], [-DimensionZ/2 +DimensionZ/2], S, 'CDataMapping', 'scaled');
colorm... |
b4888bbf85b9b6b95d0b7f4cc3ed80b2c2b7499f9af31d7bc4a55baa71c3bdd1 | MATLAB | 2,177 | 90 | function [Xc,Xp] = Compute3D(xc,xp,R,T,fc,fp,cc,cp,kc,kp,alpha_c,alpha_p);
% [Xc,Xp] = Compute3D(xc,xp,R,T,fc,fp,cc,cp,kc,kp,alpha_c,alpha_p);
%
% Reconstruction of the 3D structure of the striped object.
%
% Xc : The 3D coordinates of the points in the camera reference frame
% Xp : The 3D coordinates of the poi... |
f84881679c4db3e7d26e7c8850df50ce7e2d9ea11f8008b8920ef8a41042e734 | MATLAB | 2,177 | 66 | function keyPressCallback(self,~,value)
if self.verbosity > 9
disp(mfilename)
end
if strcmp(value.Key,'escape')
self.channel_to_work_with = [];
elseif strcmp(value.Key ,'uparrow') && any(strcmp(value.Modifier,'shift'))
self.jumpToOutlier('up')
elseif strcmp(value.Key ,'downarrow') && any(strcmp(value.Modifier,'shi... |
291a5986c6fdcb18902ba4b93d087b1c0fe9df3a329541f0d8edee4dccf899f2 | MATLAB | 2,178 | 62 | function [FitDetails]=LinearPoly3DFitting(TempXData,TempYData,TempZData)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
clear FitDetails
FitDetails.XRange=[min(TempXData(:)):max(TempXData(:))/1000:max(TempXData(:))];
FitDetails.YRange=[min(TempYData(:)):max(TempYData(:))/1000:max(TempYData(:)... |
8d61cdfb3d7962bf24cdcb33b82b02676a5dabf9964fd9a179e3c75f6b68ebde | MATLAB | 2,178 | 52 | % SOFA API - demo script
% Copyright (C) 2012-2013 Acoustics Research Institute - Austrian Academy of Sciences
% Licensed under the EUPL, Version 1.1 or – as soon they will be approved by the European Commission - subsequent versions of the EUPL (the "License")
% You may not use this work except in compliance with the ... |
90a6a87828263676bf6e276f6587d391194ed354b65c597b5516261341ba3e0b | MATLAB | 2,178 | 57 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This script selects a subset of links according to the chosen networks %
% and then, it organizes the adjacency matrices into links %
% %
% Author: ana.tr... |
d49a09fae4995f7f64b3e587e6d3df9b6fb50dae87ec79023037ac29f83f92a4 | MATLAB | 2,178 | 87 | %% diagonal filter
%// Apply a zero-order filter ('filtfilt' to each matrix diagonal of a
% (SDO) matrix, smoothing motifs for interpretation.
% Optionally maintains linearity of SDO matrix using post-hoc conform.
%
% Input matrix is 'sheared' to align diagonals to rows, then filtered using
% 'filtfilt' to apply... |
986cac9233a9bedf1fce8f556168f68f49007ed5b4f980cf97f0cd1548ec1bcf | MATLAB | 2,179 | 61 | function [spikenums_shuffled,syncEvents_shuffled,SCEthresh] = circshiftRaster (spikenums,number_of_surrogates,plotting);
%% >>> OPERATION >>>
% Reshuffles spike raster to generate:
% - surrogate spike raster (same size as original raster)
% - surrogates for synchronous events (n surrogates x n data points 2D array)
%... |
c79239a533ae4ceeaa13b725f6486873e2306e412091017e1ea617fd647d9b86 | MATLAB | 2,179 | 80 | %% Kalman Filter Tracking Demo: move point in 2d plane
% State = (x y xdot ydot). We only observe (x y).
%
% X(t+1) = F X(t) + noise(Q)
% Y(t) = H X(t) + noise(R)
%%
% This file is from pmtk3.googlecode.com
ss = 4; % state size
os = 2; % observation size
F = [1 0 1 0; 0 1 0 1; 0 0 1 0; 0 0 0 1];
H = [1 0 0 0; 0 1... |
fc72448f3e62f9f8f41eae446b92b38c2cb8eca2e40fb78406ca55b7bff8a4f9 | MATLAB | 2,179 | 64 | % Main script for the state switching MR practice (October 2017)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% enter subject ID & task variant %%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
prompt = {'Enter subject ID:','Enter paradigm (dynamic/words/visual):'};
dlg_title = 'StateSwitch Input';
num_lines = 1;
defaultans = {'00... |
af921dbb93f02597a2d2a548810cf301b0ec93a2f799ffb86c79397bf231a05f | MATLAB | 2,180 | 79 | % :Usage:
% ::
%
% function XYZout = mm2voxel(XYZ, M, [uniqueness options])
%
% :Inputs:
%
% **M:**
% VOL must contain M or mat field, which is mat file matrix in SPM
%
% **XYZ:**
% can be either 3 rows or 3 columns
% by transforming to x y z in ROWS, coords in COLUMNS
% so if you ha... |
c9886c83a0e5fdd13e3bbf0fcdfe419d4add71923bcf73ff4c765fbfd537b1d7 | MATLAB | 2,180 | 67 | %resnet 18 for feature extraction 26/3/2020
%acuracy 90.39 data set of 10 printer
%acuracy 90.51 with new imagedatastore of datasets of 10 printer
clc
close all
clear
%images=testreaddata();
%D:\Doaa_PHD\PHD2020\DataSets\ck\CK48.......D:\Doaa_PHD\PHD2020\DataSets\jaffedbase - Copy
images=imageDatastore('... |
c2ade794ba7166665f43ac50263f7b79fd77dd51e3830e67c36cafe61115e037 | MATLAB | 2,181 | 58 | function [data,timestamps,info]=read_neuralynx_file(filename, varargin)
if exist('raw')==7
filename=strcat(['raw/' filename]);
end
data=[]; timestamps=[]; info=[];
if exist(filename)==2
[~,~,filetype] = fileparts(filename);
if ~any(strcmp(filetype,{'.ncs','.nvt','.ntt','.nev'}))
error('File extens... |
d7c3ecc416fcb7985dcb06fe97eecfa7511d3988169cc2aa2304d8360c014573 | MATLAB | 2,181 | 50 | function phi = phi_comp_probs(type_of_dist, type_of_phi, Z, probs, options)
% Compute phi from probability distributions
%
% INPUTS:
% type_of_dist:
% 'Gauss': Gaussian distribution
% 'dis': discrete probability distribution
% type_of_phi:
% 'SI': phi_H, stoch... |
f1f7b43a6978899121bede60fadc5075b11b38a3d9cc5112029011d74107b638 | MATLAB | 2,181 | 59 | % Purpose: Convert lh_labels and rh_labels to gifti shape files for later WB
% visualization
% Inputs: lh_labels and rh_labels from generate_network_overlap.m and template gifti
% files in appropriate resolution.
% Outputs: .shape.gii files containing AI values.
%
% Note: Template .shape.gii files can be created using... |
3acad8ccbc39913efc849bceb349f7257a38810c9351ebb74869e2c7381c8920 | MATLAB | 2,182 | 84 | % Load the dataset into MATLAB
load('dataset.mat');
load Multivariate_NTs.mat
% Specify the response variable and predictor variables
colnames = {'beta_fmap','A4B2', 'CB1', 'DA', 'GABAa','H3', 'M1', 'mGluR5', 'MU', 'NAT', 'NMDAR','5HT'};
[~, colidx] = ismember(colnames, data.Properties.VariableNames);
response = datas... |
66e7dd11fd027cf80c5a1e7646e80d6b2b21abda7e7f41866666adf9146ebdbc | MATLAB | 2,182 | 69 | %% SAT - app_input ::
%% getAppPpCellFromPpCell
% Name: Phone Kyaw
% Date: 09/10/2024
%_______________________________________
% Copyright (C) 2024 Phone Kyaw
% Drexel University College of Medicine
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Publi... |
88943841de0db7e7ff4e222778591e04cb28675edb4da90fcc647d0d96393788 | MATLAB | 2,182 | 60 | % Combining the data from 30 simulation trials
% This has to be run on a high-performance computing cluster.
% NB: modify the path to the folder, name of the files to read from and
% name of the file to save according to needs (lines 16-23)
% Load data where the spike counts have been saved (option.saveSpkCounts=1)
% ... |
052c0ae99d2721a49a71bd193287c77f5ee260f58a2a00a145766d938678a9d7 | MATLAB | 2,183 | 58 | %{
Copyright (c) 2025 Axion BioSystems, Inc.
Contact: support@axion-biosystems.com
All Rights Reserved
%}
classdef BlockVectorHeaderExtension < Entry
%BlockVectorHeaderExtension: Contains additional metadata about a loaded
% Block vector set.
%
% ExtensionVersionMajor: Latest and greate... |
3104567fab7e86ec051c140588b0a4b73ded2d84f0a9d97b577e595dad87b73b | MATLAB | 2,183 | 85 | function [varargout] = getargs(argcell, tags, def)
%GETARGS Scan varargin cell and match a list of tags
%
% [varargout] = getargs(argcell, tags, def)
%
% This function allows one to use numbers of [parameter, value] pairs
% in function calls. It parses the varargin cell that is used in
% another function call. What ... |
9d381f4c44a7f11e00a6406f5dddc1eab5afbbbf7265ebae59ab2ceddb8c0e86 | MATLAB | 2,183 | 46 | clear
clc
close all
nb_models = 10000;
stimAmp_step = [-53];
% stimAmp_diffusion = (2:0.1:2.5);%-53*(0.5:0.3:1.5);
t = 0:100;
Istim = get_diffusion_current(t, 1);
max_Istim = max(Istim);
% stimAmp_diffusion = unique(round(stimAmp_diffusion*max_Istim));
stimAmp_diffusion = [11]; % Calibrated to achieve stimulation o... |
4de0b16947b46d51bb577d5122be323a0766f8f0e9437f107a4b64fe8d4000d1 | MATLAB | 2,184 | 72 | function [varargout] = plinproj(varargin)
% PLINPROJ projects a point onto a line or linepiece
%
% Use as
% [proj, dist] = plinproj(l1, l2, r, flag)
% where l1 and l2 are the begin and endpoint of the linepiece, and r is
% the point that is projected onto the line
%
% the optional flag can be:
% 0 (default) proj... |
990292c7703e513e4db4d159b0960b8a4aa581d2b588eea490c0d8cea3238b51 | MATLAB | 2,184 | 56 |
TRANSCRIPT_OBJ_FILE = ‘’; %put in the _transcriptobjects.mat output in the 6_base-calling directory
XY_SIZE = [2048,2048]; %How big (by pixels) is a single image from microscope
READ_SIZE = 8; %how big dots do you want to make?
%Load transcript_objects into the memory:
load(TRANSCRIPT_OBJ_FILE);
%Get the list of all... |
d28ebc76f5fb5a4954bacd39c5d3d0878bbc9bab5bacf2d06934fa51c101b366 | MATLAB | 2,184 | 44 | for k = 1:length(X)
clf;
x = X(k);
% Display NIFTI slice
I = round(-x/d1d2d3(1) + N1N2N3(1)/2); % minus here!
S = squeeze(VT(I, :, :))'; % choose the X cross-section
S = S(:, :);
image([-DimensionY/2 +DimensionY/2], [-DimensionZ/2 +DimensionZ/2], S, 'CDataMapping', 'scaled');
... |
f4b02e42f16678d5e9506a09c868797420651585c7bed196d38d761da3710a57 | MATLAB | 2,184 | 62 | % this funciton takes an input signal and num_images, plots them,
% gets the user to select the points between light onset and light offset, and then
% replaces the trace between these points straight line. this improves curve fitting
% for detrending correction. fit the curve to this output and then subtract
% the cu... |
094730148f8f2570d2efce3350e5b0d8a40a6d83dc5413b54f981b7ee5995970 | MATLAB | 2,185 | 55 | %-----------------------------------------------------------------------------------------
% Correlation of firing rate of odor-modulated amygdala neurons
% with reference valence ratings
%
% Kehl et al. 2024 (DOI:XX)
% Single-Neuron Representations of Odors in the Human Brain
% Figure 4e
% Author: Marcel Kehl
% Li... |
f048d1e8707f0aeacf68328d869172132a3ae5e47afcf7d9aef559eb093edaf6 | MATLAB | 2,185 | 70 | %% Demonstrate training a chain-structured CRF
% Based on
% http://www.cs.ubc.ca/~schmidtm/Software/UGM/trainCRF.html
% This file is from pmtk3.googlecode.com
%% Get data
setSeed(0);
load rain.mat % X is 1059*28
y = X+1; % Convert from {0,1} to {1,2} representation
[nInstances,nNodes] = size(y);
% test using a sub... |
4af521daa97325eb65608fec61317f7b247270c304ebf8e910109cee90460ce5 | MATLAB | 2,186 | 100 | %% LLA and LQA approximation - fig 1 of Zou & Li 2008
%
%%
% This file is from pmtk3.googlecode.com
function scadPlot()
z = -10:0.01:10;
a = 3.7; lambda = 2;
if 0
% Reproduce fig 1c of Fan & Li 2001
p = penalty(z, a, lambda);
figure;
plot(z, p, 'k-', 'linewidth', 3);
title(sprintf('scad penalty rule, %s=%5.3f, a=%5... |
4d3b06d7069140d9fde8a585198529d6412488b2b917b20c0b9f139beb01d3f3 | MATLAB | 2,186 | 64 | function passed = ft_test_moxunit_run(unused,varargin)
% FT_TEST_MOXUNIT_RUN
% Copyright (C) 2017, Nikolaas N. Oosterhof
%
% This file is part of FieldTrip, see http://www.fieldtriptoolbox.org
% for the documentation and details.
%
% FieldTrip is free software: you can redistribute it and/or modify
% it under t... |
1eb31f2b950c0c568a5fb83712bf8f2617e53be4f2fceeabc3e773a9e3aee605 | MATLAB | 2,187 | 63 | function [out_table, out_matrix, colnames] = table_long2wide(dat, outcomevarname, varname1, varname2, sidname)
% Converts long-format table to wide-format, averaging values within-participant for each combo of conditions in varname1 and varname2
%
% [out_table, out_matrix, colnames] = table_long2wide(dat, outcomevarn... |
36973b8a645be92343da30e7f5d7285220f76b0c5c47cc91dfbdc431662bb16a | MATLAB | 2,187 | 64 | function passed = ft_test_moxunit_run(unused,varargin)
% FT_TEST_MOXUNIT_RUN
% Copyright (C) 2017, Nikolaas N. Oosterhof
%
% This file is part of FieldTrip, see http://www.fieldtriptoolbox.org
% for the documentation and details.
%
% FieldTrip is free software: you can redistribute it and/or modify
% it under t... |
91e87506b76a963386e1c6adb366e32b32d81c0322669759b58ce093dbe89c43 | MATLAB | 2,187 | 50 | function params = CBIG_AuthorTopicEM_CreateEmptyParams(seed, K, brain_mask2mm, init_type, init_file)
% params = CBIG_AuthorTopicEM_CreateEmptyParams(seed, K, brain_mask2mm, init_type, init_file)
%
% Generate a struct of parameters for the author-topic model
%
% Input:
% - seed = seed used by Matlab's random ... |
bd7a9a4fbd5ebb5226f9100e6bbdc9906b90c643a966e06f0f78242fd866a51f | MATLAB | 2,187 | 53 | function loc_list_three_channel(data,scatter_size,scatter_num)
global Int
if length(data)~=3
msgbox('Number of files selected should be equal to 3')
else
figure()
set(gcf,'name','Montage Plot','NumberTitle','off','color',[0.1,0.1,0.1],'units','normalized','position',[0.15 0.2 0.7 0.6],'menubar','n... |
0055e0b61e550eb188d7edcdfa6c7045260b3d5c1e451bb8a3b213f50cf37d5e | MATLAB | 2,188 | 64 | function [ phi_G, Cov_E_p, A_p ] = phi_G_Gauss( Cov_X, Cov_XY, Cov_Y, Z, method, normalization )
% Calculate integrated information "phi_G" based on information geometry.
% See Oizumi et al., 2016, PNAS for the details.
% http://www.pnas.org/content/113/51/14817.full
%
% INPUTS:
% Cov_X: covariance of data X (pas... |
bd5daab55a7a5511fad6fde78ea9e4d3877facfedbd917026b9736dda082b1ab | MATLAB | 2,188 | 67 | function Rx=correlmx(x,p,Rxtype);
% Rx=correlmx(x,p,Rxtype) correlation matrix of a signal
%
% Rx : correlation matrix (p+1) x (p+1)
% x : analyzed signal
% p : last autocorrelation lag
% Rxtype : computation algorithm (default : 'fbhermitian')
% possible values : 'hermitian', 'fb... |
c4bf19bb92ef7d0b869ebd67c25b8053d164825e7f3161cfdc4b9fc6527de7fa | MATLAB | 2,188 | 66 | function Y = interpolate_nans(varargin)
% FILLNANS replaces all NaNs in array using inverse-distance weighting.
%
% Y = interpolate_nans(X) replaces all NaNs in the vector or array X by
% inverse-distance weighted interpolation:
% Y = sum(X/D^3)/sum(1/D^3)
% where D is the distance (in pixel... |
06ab4e2b83fd924204f8340901b3ae4f37f76157e80bde323e6e7275e06a6ca8 | MATLAB | 2,189 | 65 | function [model] = obsModelFit(X, Y, obstype)
% Fit a model of the form Xj -> Yj
% where X(i,j) is discrete value of node j in case i
% and Y(i,j,:) is a feature vector
% There are several types of obs model.
% - 'gauss': we fit a model to the features
% p(Y(i,j,:)|X(i,j)=k) = gauss(mu(:,j,k), Sigma(:,:,j,k)
% - 'qua... |
cd45809568d5a8c581113fb3978e1e1c1964cf3be4b3d6a900589e4dd7adc1d7 | MATLAB | 2,189 | 50 | %% ------------------------------------------------------------------------
% configuration
% every line contains three fields:
% 'filename'
% 'legend text'
% 'Marker'
% 'Color'
% 'MarkerFaceColor'
% 'TextPosition': [x, y]
% ----------------------------------------------------... |
fc5ab2d9ad57d9689cde788a6bb34d5467c23a6549d4062a3b6ce9f871af0aa1 | MATLAB | 2,189 | 64 | function [path_score,best_path]=pacman(decoded_event)
psize = size(decoded_event);
[forward_score,forward_path] = find_path(decoded_event);
[reverse_score,reverse_path] = find_path(flipud(decoded_event));
%compare the upper-left lower-right score to the lower-left
%upper-right score, take the higher one
if forward_sc... |
387a10449920c50e112dd21fa6784798ff41c908fd7eadc233ef3359fe14a475 | MATLAB | 2,190 | 61 | function [bWeights,bWeightsPos,bLong] = bWeightAcc(bLong,bTrunc,LossArr)
%%
%For each array, determine number of repeats of each element
for k=1:length(bLong)
maxbLong(k)=max(bLong{k}(:));
end
bArr=[0:max(maxbLong).^0.5].^2;
bLong{1}=bArr;
for k=1:length(bLong)
bRepeats{k}=histc(bLong{k},[bLong{1}]',1);
end
%%
... |
8d54870687af40e880e349abfd10721653fccf8d6d0d35c8c978e0dd956cd747 | MATLAB | 2,191 | 78 | function str = h_copy(vector,direction, title)
if ~exist('direction', 'var')||isempty(direction)
direction = 'vertical';
end
if ~exist('title', 'var')||isempty(title)
title = '';
end
if ischar(vector) && ~iscell(vector)
vector = {vector};
end
siz = size(vector);
% if ischar(vector)
% ... |
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