sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
5e08c8b552f5014e2f357cfb17a4dfd4d6161fe928886f4f28dc27b5f9452232 | MATLAB | 343 | 13 | function [p, t] = nk_PTfromR(r, v, fl)
r(isnan(r))=0;
t = r .* sqrt((v-2) ./ (1 - r.^2));
if ~exist('v','var') || isempty(v)
error('Degrees of freedom missing!')
end
if ~exist('v','var') || isempty(v)
error('One or two-sided p values have to be specified!')
end
x=1-r.^2; p=betainc(x,0.5*(v-2),0.5);
if fl==1, ... |
0644f02ab1d7ed810822fce0c90b3d980b7b38be39c87c4f0e0a70f05b0d61b7 | MATLAB | 345 | 15 | function b = loadobj(a)
% loadobj for file_array class
%__________________________________________________________________________
% Copyright (C) 2005-2017 Wellcome Trust Centre for Neuroimaging
%
% $Id: loadobj.m 7147 2017-08-03 14:07:01Z spm $
if isa(a,'file_array')
b = a;
else
a = permission(a, 'rw');
... |
b76661c84e5f93bfa5880f769e81274655a5fdf53f0e534379d4dd0c9295ed5a | MATLAB | 345 | 5 | % Compiles the MIToolbox functions
mex MIToolboxMex.c MutualInformation.c Entropy.c CalculateProbability.c ArrayOperations.c
mex RenyiMIToolboxMex.c RenyiMutualInformation.c RenyiEntropy.c CalculateProbability.c ArrayOperations.c
mex WeightedMIToolboxMex.c WeightedMutualInformation.c WeightedEntropy.c CalculateProbabi... |
c7fc9e55566e5b00480210a9302151c60e77ae9b82992527c1ef5a6c484918e8 | MATLAB | 345 | 13 | function [RotMat, rotatemat] = nk_Procrustes(TempMat,SourceMat)
% Define coordinate space between orignal and rotated components
temp=TempMat'*SourceMat;
% Orthogonalize space
[V,~,U]=svd(temp);
% Determine procrustean transform
rotatemat=U*V';
% Finally transform SourceMat to minimize difference to TempMat
RotMat ... |
ff99e8d0718d5d6643acb6c8e8f2e63cfd83a61e95ae465d5ecae3883d3a0603 | MATLAB | 348 | 28 | function c = myCallerName()
% c = myCallerName()
%
% OUTPUTS
% c = name of function that called function that called "myCallerName"
%
%
% i.e.
% function foo()
% bar();
% end
%
% function bar()
% c = myCaller();
% % c will be "foo"
% end
%
%
% uses dbstack
ST = dbstack();
if length(ST)<3
c = 'base';
e... |
0462e9aa363589bb7acfd71b5d4084fd86792ae67d6a906ea688401ad129da1b | MATLAB | 349 | 13 | function [X] = proximalL1infnorm(D, tau)
% min_X 0.5*||X - D||_F^2 + tau*||X||_{1,inf}
% where ||X||_{1,inf} = sum_i||X^i||_inf, where X^i denotes the i-th row of X
% X = D; n = size(D,2);
% for ii = 1:size(D,1)
% [mu,~,~] = prf_lb(D(ii,:)', n, tau);
% X(ii,:) = D(ii,:) - mu';
% end
[m,n]=size(D);
[mu,~,~]=pr... |
82a4a3a460fc179609c09475ef42d66744915fba17b96cee077ca0a7addee6ca | MATLAB | 349 | 19 | function blobs(f)
figure
xyz = f.xyz;
state_color = f.state_colors;
cdata = bt_utils.state_cdata;
for j = 1:size(cdata,1)
pts = state_color == j;
if any(pts)
h = bt_utils.alphavol_wrapper(xyz(pts,:),Inf);
hold on
set(h,'FaceColor',cdata(j,:),'EdgeColor','none','FaceAlpha',0.9,'UserData','blob');
... |
a43269ea135d84d03e0ebbffda501688decf26f65e44fcd254ddd8a6304813ae | MATLAB | 350 | 10 | % Inner-product and apply sparse selection
% This function performs the following:
% UV = U * V, out(ii) = UV(iR(ii), iC(ii));
% To use this function
% out = sparse_inp_native (U', V, iR, iC, length(iR))
% U: m x r (for C simplicity, we follow LMaFit to use U')
% V: r x n
% iR: len x 1
... |
6ee71c3def9fd256719e8cdc0c860a7746a9bc1bbfcc7652e1ce37ee5180b0c5 | MATLAB | 354 | 17 | function t = fieldnames(obj)
% Fieldnames of a file-array object
%__________________________________________________________________________
% Copyright (C) 2005-2017 Wellcome Trust Centre for Neuroimaging
%
% $Id: fieldnames.m 7147 2017-08-03 14:07:01Z spm $
t = {...
'fname'
'dim'
'dtype'
'offset'
... |
9321210021d365d2c3188d4907e61791668fa4a47e57989749c77ed537e9cbff | MATLAB | 355 | 12 | function [ Y, integerformat ] = mp2rage_scale_UNI( Y )
%MP2RAGE_SCALE_UNI converts MP2RAGE to -0.5 to 0.5 scale, if necessary
if min(Y(:))>=0 && max(Y(:))>=0.51
% converts MP2RAGE to -0.5 to 0.5 scale - assumes that it is getting only positive values
Y = (Y- max(Y(:))/2)./max(Y(:));
integerformat=1;
else
... |
78339fb47adf6f85211e6364318383f116199ef4715048ba12b1e3199b62fed0 | MATLAB | 359 | 15 | function graph = array_to_graph(a)
NODES = (1+sqrt(1+(8*length(a))))/2;
adj_m = zeros(NODES);
%a(a>0) = 1;
adj_m(triu(true(NODES),1)) = a;
adj_m = adj_m + transpose(adj_m);
graph.am = adj_m; %reshape(a,[sqrt(length(a)),sqrt(length(a))]);
graph.al = cellfun(@(x) find(x),num2cell(graph.am,2),'un',0);
nodes = 1:size(adj... |
2b97fada9a58ba67eaf9e5a56e7afc5e2c8025116b044aba075fda9f73fabb7e | MATLAB | 361 | 10 | % This make.m is used under Windows
% add -largeArrayDims on 64-bit machines
mex -largeArrayDims -O -c svm.cpp
mex -largeArrayDims -O -c svm_model_matlab.c
mex -largeArrayDims -O svmtrain.c %svm.obj svm_model_matlab.obj
mex -largeArrayDims -O svmpredict.c %svm.obj svm_model_matlab.obj
mex -largeArrayDims -O libsvmrea... |
d855e3488f02297c52191d91a0de7fcd142557b8f149a3d98e84fc249aa75f27 | MATLAB | 361 | 19 | function [res] = elbow(scores, alpha)
b = length(scores);
sigma2 = var(scores,1);
[R, idxs ] = sort(scores,'descend');
k = 1;
while (R(k)==R(k+1))
k = k + 1;
end
while (k<b)&&((R(k)-R(k+1))/sigma2 > alpha)
k = k+1;
end
if k > 1
res = idxs(1:k-1);
els... |
bcda029fe34e65693b9dba9bb167eb1376b68d8f0d079752ed54d4ccd6b966ad | MATLAB | 363 | 13 | function out = full(fa)
% Convert to numeric form
% FORMAT full(fa)
% fa - a file_array
%__________________________________________________________________________
% Copyright (C) 2018 Wellcome Trust Centre for Neuroimaging
%
% $Id: full.m 7501 2018-11-30 12:16:58Z guillaume $
[vo{1:ndims(fa)}] = deal(':');
out = su... |
c2f789b3580d71ad35caa5c998989584e649bfe636e81806ae8fa52fe2ca7734 | MATLAB | 363 | 22 | function [fea] = mrmr_mibase_d(d, f, K)
% function [fea] = mrmr_mibase_d(d, f, K)
%
% Baseline for comparing MRMR
%
% By Hanchuan Peng
% April 16, 2003
%
nd = size(d,2);
nc = size(d,1);
t1=cputime;
for i=1:nd,
t(i) = mutualinfo(d(:,i), f);
end;
fprintf('calculate the marginal dmi costs %5.1fs.\n', cputime-t1);
... |
e87bef8234a72a973f9e60130c9742cbf58fdd58fbe750e81ed83d0b1b432012 | MATLAB | 363 | 8 | % Note, this is used only for App deployment
disp('===>>> Running Opticka via App Deployment…');
disp(['===>>> $HOME is: ' getenv('HOME')]);
disp(['===>>> App root is: ' ctfroot]);
disp(['===>>> PTB root is: ' PsychtoolboxRoot]);
disp(['===>>> PTB config is: ' PsychtoolboxConfigDir]);
o=opticka;
disp(['===>>> Opticka V... |
fc6fb489220fa3d6b731a43722bc27850a1ba56d0a556495c34ed948fa188eee | MATLAB | 363 | 16 | %[2018]-"A Novel Multi-Class EEG-Based Sleep Stage Classification System"
%(5)
function HC = jHjorthComplexity(X,~)
% First & second derivative
x0 = X(:);
x1 = diff([0; x0]);
x2 = diff([0; x1]);
% Standard deviation of first & second derivative
sd0 = std(x0);
sd1 = std(x1);
sd2 = std(x2);
% Complexity... |
a1825b53b159a498be1fbed158b6440f46fa1dcedc19f020a62942e09a56b73c | MATLAB | 364 | 8 | function outputMatrix = assessCounterbalancing(conditionOrder)
%> @fn assessCounterbalancing
%> @brief Compatibility wrapper for taskSequence.assessCounterbalancing.
%>
%> @param conditionOrder ordered integer condition sequence.
%> @return square matrix where A(i,j) is count of i preceding j.
outputMatrix = taskSeque... |
fd842d1fee94a222fce607e648622504cfa55fdee5e41c7fee57d101aa6be5ec | MATLAB | 366 | 27 | function [nAtA,normA,nBtB,normB,nAtB]=normalizeKernelMatrix(AtA,BtB,AtB)
% normalize random kernel
% Yifeng Li
% Feb. 08, 2012
nAtA=[];
normA=[];
nBtB=[];
normB=[];
nAtB=[];
normA=sqrt(diag(AtA));
nAtA=AtA./(normA*normA');
if nargin==1
return;
end
normB=sqrt(diag(BtB));
nBtB=BtB./(normB*normB');
if nargin==2
... |
298c1d496ff2642282a1246b1de1d527a10ff513a156de9ae9591eaef3012a12 | MATLAB | 367 | 13 | function trimmed = mripy_trim_init_resp(x, trim, run_len)
% Trim the initial TRs of each run.
% 2021-03-05: Created by qcc
assert(mod(length(x), run_len)==0);
n_runs = length(x) / run_len;
trimmed = reshape(x, run_len, n_runs);
trimmed = trimmed(1+trim:end,:);
trimmed = trimmed(:);
if size(x, 1)... |
882d14fe8767a551af9ef9afc4f0ca78ce67aad3a847f3af3cc0308c0fd3dc02 | MATLAB | 368 | 12 | function [random,seed]=uniran(seed)
%UNIRAN is the uniform random generator used in mcdcov.m and ltsregres.m
%
% This function is part of LIBRA: the Matlab Library for Robust Analysis,
% available at:
% http://wis.kuleuven.be/stat/robust.html
seed=floor(seed*5761)+999;
quot=floor(seed/65536);
seed=floor... |
b3f3b5c03990df1795602fb6305b141a2ecef0e28357b7a0bca7bbc751383648 | MATLAB | 369 | 13 | function kappa = nk_DiversityKappa(E, L, m, n)
% function A = nk_DiversityKappa(P, vec, m, n)
% Compute entropy-based measure of ensemble diversity
if ~exist('m','var'), m = size(E,1); end
if ~exist('n','var'), n = size(E,2); end
rL = repmat ( L, 1, n);
cE = bsxfun(@eq, E , rL);
sCE = sum(cE,2);
p = mean(sCE./m);
kap... |
e88c7fbd5e1743b27119c0d484054fd8aa19911e3733f055bd851adddcc3294e | MATLAB | 369 | 19 | function [hEPerf, hE] = nk_EnsPerf(E, L)
global MODEFL EVALFUNC
% Compute ensemble performance
switch MODEFL
case 'classification'
hE = sign(mean(E,2));
% throw a coin on the zeros
hE = nk_ThrowCoin(hE);
case 'regression'
hE = mean(E,2);
end
% Measure accuracy or some ... |
ec3f71c8792f84c617e93179a4d4d68be11ce5a0e7e956bbd609f11411ab6ab5 | MATLAB | 371 | 18 | function [ f_y, Df_y ] = pnopt_quad( P, q, r, x )
% pnopt_quad : PNOPT local quadratic approximation
%
% $Revision: 0.8.0 $ $Date: 2012/12/01 $
%
global subprob_Dg_y
if isa( P, 'function_handle' )
H_x = P( x );
else
H_x = P * x;
end
f_y = 0.5 * x' * H_x + q' * x + r;
if nargout > 1
sub... |
82e69bc581b05b3d03493d8c8f19834ebf1ee8efdf6726e1917fc493dc584dbc | MATLAB | 373 | 12 | %% run_all_core_oracle.m
% Convenience script for the core oracle benchmark pipeline.
%
% Assumes the workspace already contains:
% EEG_all_epochs, EOG_all_epochs, EMG_all_epochs, and optionally fs.
%
% Steps:
% 1) build benchmark dataset
% 2) run validation-set oracle sweeps
run('scripts/build_decomp_benchmark_... |
c48502cb8031831c2d8cfca860837b1f213905da30c56852be6c0a47a6ee1816 | MATLAB | 373 | 17 | % GETENVIRONMENT Read value of "global" variable
%
%
% Copyright 2009 :: Michael E. Tipping
%
% This file is part of the SPARSEBAYES baseline implementation (V1.10)
%
% Contact the author: m a i l [at] m i k e t i p p i n g . c o m
%
function value = getEnvironment(variable)
VA = get(0,'UserData');
if isfield(VA,varia... |
daec576cd9c92e4c9619fd72536653f32f60ebf4a3520811dbae6e166c0e6eec | MATLAB | 374 | 20 | clear;
%clc;
U = rand(500, 3);
V = rand(3, 10000);
iR = [1, 3, 3];
iC = [2, 4, 6];
len = length(iR);
out_us_mex = sparse_inp(U', V, iR, iC)';
out_us_net = sparse_inp_native(U, V, iR, iC); % call native
if nnz(out_us_mex ~= out_us_net)>0
warning('inconsistent results found in sparse_inp_native')
else
dis... |
20ca9580c4f994ac827fa35dfd55efb36e346555461e1c10ec809817d80c09ad | MATLAB | 375 | 13 | function res = im2row(im, winSize)
%res = im2row(im, winSize)
[sx,sy,sz] = size(im);
res = zeros((sx-winSize(1)+1)*(sy-winSize(2)+1),prod(winSize),sz);
count=0;
for y=1:winSize(2)
for x=1:winSize(1)
count = count+1;
res(:,count,:) = reshape(im(x:sx-winSize(1)+x,y:sy-winSize(2)+y,:),...
... |
8cf39399d044886204b7053960e5bfa19c4df9a5138ca731ca175420a3429a94 | MATLAB | 375 | 32 | function y = rescale(x,a,b)
% rescale - rescale data in [a,b]
%
% y = rescale(x,a,b);
%
% Copyright (c) 2004 Gabriel Peyr?
if nargin<2
a = 0;
end
if nargin<3
b = 1;
end
if iscell(x)
for i=1:length(x)
y{i} = rescale(x{i},a,b);
end
return;
end
m = min(x(:));
M = max(x(:));
if M-m<eps
... |
ebc7c2140c7c63270fa7c0400c3d125c8343f39776426a1fc1b220f88535f54a | MATLAB | 375 | 14 | function [trainExtr, testExtr, outTrain, outTest] = nk_NNMFFeatRank(Y, label, Ynew)
feMethod='nmf';
optionFE.facts=15;
Y=Y';
[trainExtr,outTrain]=featureExtractionTrain(Y,[],label,feMethod,optionFE);
if exist('Ynew','var') && ~isempty(Ynew) && nargout==4
Ynew = Ynew';
[testExtr,outTest]=featureExtrationTest(... |
ab31e55f236cd4a77c523e1033a43e72a5e7a2ff1fb19292b14408964e6ed396 | MATLAB | 376 | 17 | % ========================================================================
%> @brief
%>
%> Copyright ©2014-2022 Ian Max Andolina — released: LGPL3, see LICENCE.md
% ========================================================================
classdef rewardManager < handle
properties
end
methods
fu... |
5d62c3acb09a1ca305e4281249c2c86605194f34814b702c1510f25b03bd066a | MATLAB | 377 | 16 | % Function to start parallel pool with number of workers as currently
% accessible CPUs
%
% Jeff Eilbott, 2016, jeilbott@surveybott.com
function pool = start_parpool()
numCores = feature('numCores');
pool = gcp('nocreate');
if ~isempty(pool) && pool.NumWorkers < numCores
delete(pool);
pool = gcp('nocreate');
e... |
36411872afaace73a73a633d5f5a9556dc7ad2dd386e680912d024368ffb15bb | MATLAB | 381 | 15 | function tso = restrict(tsin, t0 ,t1)
% R = Restrict(tsa, t0, t1)
% Returns a new tsa (ts) R so that only D.Data is between
% timestamps t0 and t1, where t0 and t1 are in units
%
% If units are not specified, assumes t has same units as D
% t0 and t1 can be arrays
%
% ADR 2011
% version L6.0
% converts to tsd ... |
6e9599a6cf23c90211de9a22a8163bcb8e7eb25b158b2e5d7502d5744341b77b | MATLAB | 382 | 16 | function [menustr, menuact] = nk_CheckCalibAvailMenu_config(menustr, menuact, calibuse)
global CALIBAVAIL
if CALIBAVAIL
if exist('calibuse','var') && ~isempty(calibuse) && calibuse
calibstr = 'yes';
else
calibstr = 'no';
end
menustr = [sprintf('Use calibration data [ %s ]|',c... |
c18644cddbf6befb9eafb8444c53b0052f3eadb04dab634c30226ec8973e1e74 | MATLAB | 382 | 20 | function D = nk_BhattacharyaFeatRank(Y, L)
% Y : Data
% L : Target Labels
[~,n] = size(Y);
ix = unique(L(~isnan(L)));
indP = L==ix(1); indM = L==ix(2);
YP = Y(indP,:); YM = Y(indM,:);
D = zeros(1,n);
warning off
try
for i=1:size(Y,2)
ind = true(1,n); ind(i)=false;
D(i) = bhattacharyya(YP(:,i... |
fa5508f204b16b9a5761aeb442edaf7226e3919cf2725e2e284bd54a0f79cb54 | MATLAB | 384 | 14 | function t = numel(obj)
% Number of simple file arrays involved.
%__________________________________________________________________________
% Copyright (C) 2005-2017 Wellcome Trust Centre for Neuroimaging
%
% $Id: numel.m 7147 2017-08-03 14:07:01Z spm $
% Should be this, but it causes problems when accessing
% obj ... |
b9d3c3ce636d37e5fb0bf791a5695daaad721d169fdf3536daed90d04f592715 | MATLAB | 385 | 17 | function OK = FillFeatures(self)
% CalculateFeatures and save them
MCS = MClust.GetSettings();
% Which features need to be calculated
featuresToCalc = MCS.FeaturesToUse;
try
[self.FeatureTimestamps, self.Features] = MClust.CalculateFeatures(featuresToCalc);
OK = true;
catch ME
disp('Failed to fill (calculate) feat... |
79c54d43e5a3ca2def4a16272fb2f6574c3412d691d3e5c42c3ee7e1b38049fa | MATLAB | 386 | 23 | function [PP, fPP] = nk_CheckFileExist(P)
PP=[]; fPP=[];
if iscell(P), P = char(P);end
for i=1:size(P,1)
iP = deblank(P(i,:));
if ~exist(iP,'file')
if isempty(PP)
PP = iP;
else
PP = char(PP,iP);
end
else
if isempty(fPP)
fPP = iP;
... |
0f9767460e102cc97b7d592e715abd780d89fad4b310ef00cd09cb107ca754f1 | MATLAB | 387 | 16 | function [ecovs, eind] = nk_ExtractCovs(covs, ACTPARAM)
lact = numel(ACTPARAM); ecovs=[];eind=[];
for i=1:lact
if ~isempty(ACTPARAM{i}) && strcmp(ACTPARAM{i}.cmd,'correctnuis')
ecovs = covs(:,ACTPARAM{i}.COVAR); break
end
end
for i=1:lact
if ~isempty(ACTPARAM{i}) && strcmp(ACTPARAM{i}.cmd,'no... |
15db0d4badf6f331be825bd967ff108ba0b9d348624c4dffcb32cbc59abdc7ab | MATLAB | 391 | 23 | function DIRSTACK = pushdir(newdir);
% dirstack = pushdir(newdir)
%
% Pushes the current dir onto the directory stack.
% Then cd's to the newdir if given.
% Maintains the directory stack in a global variable.
% ADR 1998
% version L4.1
% status PROMOTED
global DIRSTACK
if isempty(DIRSTACK)
DIRSTACK = {pwd};
else
... |
153597c08d97192a1e62ccb218a07a520f10ebde099816f20516e334c8d0f0e9 | MATLAB | 392 | 12 | function ClusterFunc__ToggleUnaccountedForSpikesOnly( self )
% ShowUnaccountedForSpikesOnly
% remove all points from the cluster
%================================================
% PARAMETERS
%================================================
%================================================
% MAIN CODE
%==============... |
a573e0fed59428db0254114ffd5a999ef1c8e60ba44e8c1d8635fe016f57725f | MATLAB | 392 | 22 | function ClusterFunc_DeleteLimit(self)
% Convex Hull clsuter add limit
MCC = self.getAssociatedCutter();
MCC.StoreUndo('Delete Limit');
% get axes
xFeat = MCC.get_xFeature();
yFeat = MCC.get_yFeature();
iL = self.findLimit(xFeat, yFeat);
if ~isempty(iL)
self.featuresX(iL) = [];
self.featuresY(iL) = []; ... |
1ff8ea94458eb69a9450663fa70903a1d15a27914471680305a79873775646e9 | MATLAB | 393 | 20 | function results = run_tests()
% results = run_tests()
% run all tests in this caffe matlab wrapper package
% use CPU for testing
caffe.set_mode_cpu();
% reset caffe before testing
caffe.reset_all();
% put all test cases here
results = [...
run(caffe.test.test_net) ...
run(caffe.test.test_solver) ...
run(caf... |
73d4b9f66d0bab178eda562ce97da9b0038e9bb72d197100d9acc72262c05419 | MATLAB | 393 | 18 | function rX = ranking(X)
% Transform an arbitrarily distributed signal to a uniformly distributed
% one.
nX = size(X,2);
sortX = zeros(size(X));
sI = sortX;
rX = sortX;
for n=1:nX
% Determine sort index
[sortX(:,n),sI(:,n)]=sort(X(:,n));
% Resort ascending sequence according to
% the corresponding sort ... |
26a6d0a73377d41e835865986521e87e30385f119cc50cf88d2cc7e7c44777c4 | MATLAB | 394 | 16 | function print_figure(handles, objnames, savename)
tmpfig = figure;
%tmpfig = figure('visible','off');
n_obj = numel(objnames);
h = [];
for i= 1:n_obj
hi = handles.(objnames{i});
h =[hi h];
end
newax = copyobj(h,tmpfig);
set(newax, 'units', 'normalized', 'position', [0.13 0.11 0.775 0.815]);
%I = getframe(t... |
372b94e400b2e7a6538e1ebed96c1e88df4699d851d1a028a041bb19bc24a6c7 | MATLAB | 395 | 17 | function [selectedFeatures scoreVector] = MIM(k, data, labels)
%function [selectedFeatures scoreVector] = MIM(k, data, labels)
%
%Mutual information Maximisation
%
% The license is in the license.txt provided.
numf = size(data,2);
classMI = zeros(numf,1);
for n = 1 : numf
classMI(n) = mi(data(:,n),labels);
end
[sco... |
83dfc4cbb1210f77d526d70d218aaa5b12b002e43b08b7af5d20eb2071bf7766 | MATLAB | 395 | 15 | function t = mystruct(obj)
%__________________________________________________________________________
% Copyright (C) 2005-2017 Wellcome Trust Centre for Neuroimaging
%
% $Id: mystruct.m 7147 2017-08-03 14:07:01Z spm $
if numel(obj)~=1
error('Too many elements to convert.');
end
fn = fieldnames(obj);
for i=1:le... |
72f129f3b0f182e0ab59be294caf0bfea8f7436f153c7a3775f7eac4eb9f9d88 | MATLAB | 398 | 13 | % Predicts class scores using a trained ELM model.
%
% scores = mexElmPredict( inW, bias, outW, X );
%
% INPUT :
% inW - input weights matrix (trained model)
% bias - bias vector (trained model)
% outW - output weights matrix (trained model)
% X - samples matrix (vectors in colu... |
d41d67be388e1b4578bb7e43aec8d4539fd8321a67b128e0541b0cec8b148161 | MATLAB | 399 | 16 | % Notation: This fitness function is for demonstration
function cost = jFitnessFunction1(r , X, Ps)
if sum(X == 1) == 0
cost = 1;
else
cost = jwrapper(r.Y(:, X), r.YL, r.T(:, X), r.L, Ps );
end
function cost = jwrapper(xtrain, ytrain, xvalid, yvalid, Ps)
global TRAINFUNC
[~, FullModel] = TRAINFUNC(xtrain, ytrai... |
f9e1301f7c8beeacfd0917dc03e7cb04d16d3cd2c8f12733316f460f3620a13f | MATLAB | 399 | 12 | function h = alphavol_wrapper(a,r)
if nargin < 2 || isempty(r)
r = Inf;
end
[V,S] = utils.alphavol(a,r);
k = S.bnd;
map = unique(k(:));
map(:,2) = 1:length(map); % First col is the index in k, second row is the new index
vertices = a(map(:,1),:); % A final list of vertices
faces = arrayfun(@(b) map(find(map(... |
2f1836a8db3d73b914927ca7440d19ae6efe1b788a5af470bd842b760b1f3010 | MATLAB | 400 | 16 | function R = restrict(tsa, t0, t1)
% R = Restrict(tsa, t0, t1)
% Returns a new tsa (ts) R so that only D.Data is between
% timestamps t0 and t1, where t0 and t1 are in units
%
% If units are not specified, assumes t has same units as D
% t0 and t1 can be arrays
%
% ADR 2011
% version L6.0
timerestricted = tsa... |
ea996437be24c9fdaeed67a362ac114486adad711a4f2b41426cf07782feec1c | MATLAB | 400 | 19 | function set_SubInd(handles, act)
SubInd = true(size(handles.label));
switch act
case 'set'
SubInd = get(handles.txtSubgroupSet,'Value');
if ~isempty(SubInd) && ~strcmp(SubInd,'')
try
SubInd = evalin('base',SubInd);
catch
en... |
9d81bbc9dacfc0d74acf6a3ef1130b00a4689a61f4ba877c49543de9224fdcb9 | MATLAB | 402 | 15 | function dispsig(signalMatrix, range, titlestr);
%DISPSIG - deprecated!
%
% Please use icaplot instead.
%
% See also ICAPLOT
% @(#)$Id: dispsig.m,v 1.2 2003/04/05 14:23:57 jarmo Exp $
fprintf('\nNote: DISPSIG is now deprecated! Please use ICAPLOT.\n');
if nargin < 3, titlestr = ''; end
if nargin < 2, range = 1:siz... |
3df2d189f33ff8dad1d4267002e453d6b8078398ea7982cb20423d5b12afc859 | MATLAB | 403 | 16 | clear, clf, clc
data = readmatrix('../../experiment/field_intensity.dat');
field = data(:,1)
% ==== Experiment
Exp.mwFreq = 179.818;
Exp.Range = [min(field) max(field)];
Exp.nPoints = 401;
Exp.Harmonic = 0;
% ==== Theory
Sys = orca2easyspin('./PYD_epr.out');
Sys.lwpp = 0.5 ;
[ field, spec ] = pepper(Sys, Exp);
data =... |
a0a30c37a5ea3efd6450c95bf9f689c7a258a30754288c069260f83b734b8f0b | MATLAB | 403 | 26 | function r=getRank(v)
% rank the values in column vector v
% Yifeng Li
% October 24, 2012
% example:
% v=[ 0.5;0.2;0.4;0.6;0.2;0.1;0.9;0.5;0.5]
% r=getRank(v)
n=numel(v);
r=zeros(n,1);
[vS,ind]=sort(v);
i=1;
while i<=n
c=1;
su=i; % sum
while i<n && vS(i)== vS(i+c)
su=su + i+c;
c=c+1;
end
... |
80c0a6469f9063a75e69ef94f47b79509888f6a665f42faab2727f23eb3820b1 | MATLAB | 404 | 13 | clf
tm = 1.84e4;
plot([1:tm]/(60*30),proc.pupil(1).area_raw(1:tm),'color',[0 .6 0],...
'linewidth',1.5)
hold all;
plot([1:tm]/(60*30),proc.pupil(1).area(1:tm),'k','linewidth',.5)
axis tight;
box off;
ylim([0 400])
xlabel('time (minutes)')
ylabel('area (pixels^2)');
text(.78,.65,'raw trace','color',[0 .6 0],'units',... |
9be756ee47a9e59eabafb68ead941e25be26419e5e53cface194e54cefe5ee44 | MATLAB | 404 | 14 | function y = ObjectiveFunction1(n, c, L, T, tL, tY, Ps)
global TRAINFUNC RFE
[~, model] = feval(TRAINFUNC, tY, tL, 1, Ps);
switch RFE.Wrapper.datamode
case 1
param = nk_GetTestPerf(tY, tL, [], model, tY);
case 2
param = nk_GetTestPerf(T, L, [], model, tY);
case 3
param = nk_GetTe... |
835687467fc8d426bfe9bbd5e3ef2e1697cc475d3c6e7e4f7c8c15c23fce98c1 | MATLAB | 405 | 10 | function [verts, faces] = mripy_read_asc(fname)
%MRIPY_READ_ASC Read FS/SUMA surface (vertices and faces) in *.asc format.
% 2017-08-12: Created by qcc
n = dlmread(fname, '', [1, 0, 1, 1]); % Undocumented feature: \s as delimiter
n_verts = n(1);
n_faces = n(2);
verts = dlmread(fname, '', [2, 0, 1+n_ve... |
93d078804fe8c0b6051ac3505781be1c747e8abb81b802265e6fdef4f1e638b2 | MATLAB | 405 | 17 | function w = TGL_projection_rowise(v, lambda_3)
%% FUNCTION TGL_projection_rowise
% projection of temporal group Lasso (l21 projection).
%
%% OBJECTIVE:
% argmin_w { 0.5 \|w - v\|_2^2
% + lambda_3 * \|v\|_2 }
% This is a simple thresholding:
% w = max(\|v\|_2 - \lambda_3, 0)/\|v\|_2 * v
nm = norm(v, 2);
i... |
9b80f55cc447b35bb53eadafde5d53afa3eb0ea42ed952328dac971141cbf1a8 | MATLAB | 407 | 16 | function output = h(X)
%function output = h(X)
%X can be a matrix which is converted into a joint variable before calculation
%expects variables to be column-wise
%
%returns the entropy of X, H(X)
if (~isa(X,'double'))
error('Error, inputs must be double vectors or matrices')
end
if (size(X,2)>1)
mergedVector = MI... |
9fd8cbbdcf5f5ded1427527cd34b8870e7f2f7bf0df3bb5c1215e2abb7d99f35 | MATLAB | 408 | 18 | function en = end(a,k,n)
% Overloaded end function for file_array objects.
%__________________________________________________________________________
% Copyright (C) 2005-2017 Wellcome Trust Centre for Neuroimaging
%
% $Id: end.m 7147 2017-08-03 14:07:01Z spm $
dim = size(a);
if k>length(dim)
en = 1;
else
i... |
d1b5c037fbe14d2e34a7ab3d18b43feb0eed95b73cc5991356f948e7194bc049 | MATLAB | 410 | 3 | mex -I../../ mRMR_D_Mex.c ../../src/MutualInformation.c ../../src/ArrayOperations.c ../../src/CalculateProbability.c ../../src/Entropy.c
mex -I../../ DISR_Mex.c ../../src/MutualInformation.c ../../src/ArrayOperations.c ../../src/CalculateProbability.c ../../src/Entropy.c
mex -I../../ CMIM_Mex.c ../../src/MutualInfor... |
fdacbb92bc6c3cd04c64156fb7fa345f45a26978aa504f374bbe2dc5129bc4a1 | MATLAB | 411 | 18 | function oECOC = nk_OneVsAll(Classes, number_classes)
nc = size(Classes,2);
oECOC=zeros([number_classes nc]);
tECOC=-1*ones([number_classes number_classes]);
% Create multi-group coding matrix for one-vs-one
for i=1:number_classes
tECOC(i,i)=1;
end
% Assign dichotomizers to class vector
for i=1:number_classes
... |
3892cbaae03dc328faf682afa3d86dc9f524d536495140db8013323dc34d8aac | MATLAB | 414 | 16 | function [mcX,mX]=mcenter(x)
%MCENTER mean-centers the data matrix x columnwise
%
% Required input arguments:
% x : Data matrix (n observations in rows, p variables in columns)
%
% This function is part of LIBRA: the Matlab Library for Robust Analysis,
% available at:
% http://wis.kuleuven.be/stat... |
b0a8d76139f9e2ee01a02f03d52632475f33ebf2df6714f24a3eed7f01d02795 | MATLAB | 415 | 13 | function s = perlin (m)
%m is the size of the patch, will always return a square
s = zeros(m); % output image
w = m; % width of current layer
i = 0; % iterations
while w > 3
i = i + 1;
d = int... |
6b682fcf35ec2b307671182674b1a96a0786c2aa6636fe24a02eea9bf8bde22c | MATLAB | 418 | 14 | function [ fvP ] = primalObj( X, y, W, lambda1, lambda2)
%PRIMALOBJ Summary of this function goes here
% Detailed explanation goes here
% primal objective (without augmented terms)
% P(W) sum_i^m ||Xi wi - yi|| + lambda1 ||W||_{1,2} + lambda2/2 ||W||_F^2
fvP = lambda1 * sum(sqrt(sum(W.^2, 2))) + lambda2 /2 * sum(... |
fbf9597c39fb63018ef50f44f0e1b8b20e6cc3f7f130b5df327d31788d0fbe92 | MATLAB | 419 | 16 | function E = isemptycell(C)
% ISEMPTYCELL Apply the isempty function to each element of a cell array
% E = isemptycell(C)
%
% This is equivalent to E = cellfun('isempty', C),
% where cellfun is a function built-in to matlab version 5.3 or newer.
if 0 % all(version('-release') >= 12)
E = cellfun('isempty', C);
else
... |
11144b339516fdb2d302f4338d0a48e7010f4b6a304cd7733f8bfd07aa73f9b7 | MATLAB | 420 | 19 | function D = nk_DirSelector(titlestr, D)
global SPMAVAIL
if isempty(SPMAVAIL), SPMAVAIL = logical(exist('spm_select','file')); end
if ~exist('D','var') || ~exist(D,'dir'),
D = {pwd};
elseif ischar(D)
D = {D};
end
if ~exist('titlestr','var') || isempty(titlestr)
titlestr = 'Select Directory';
end
if SP... |
15f5ec1641b0f9376744d702c2461005a6dce6db08d4f9d5aa6e1e518bf8ced4 | MATLAB | 420 | 14 | function set_panel_visibility(handles,flag)
% Visualization panel
set(handles.pnVisual,'Visible',flag);
set(handles.pn3DView,'Visible',flag);
% Classification / Regression plot
set(handles.pnBinary,'Visible',flag);
% Model performance
set(handles.pnModelPerf,'Visible',flag);
% Binary classifier selector
set(handles.po... |
a2999123b9ce0d872853f1158ec2ea8a798ee69e9b002230058a29aa96c0a98e | MATLAB | 421 | 15 | function ClusterFunc_DeleteAllSpikes( self )
% DeleteAllSpikes
% remove all points from the cluster
%================================================
% PARAMETERS
%================================================
%================================================
% MAIN CODE
%===========================================... |
89281451787a954bf0f1ba8e7dbd27ecd7866e5831545a015c448831c01a48cb | MATLAB | 422 | 14 | function [AUC] = getAUC (Actual,Predicted)
if length(unique(Actual))~=2 ||max(unique(Actual))~=1
error('Strange input for AUC analysis');
end
nTarget = sum(double(Actual == 1));
nBackground = sum(double(Actual ~= 1));
% Rank data
R = tiedrank(Predicted); % 'tiedrank' from Statistics Toolbox
% Calculate AUC
A... |
e3b4f1bc7f5b7fc89a143689806becf4777a69f31d9d5396053924826938827c | MATLAB | 423 | 17 | function PlotSelf(self, xFD, yFD, ax ,xFeat, yFeat)
% Redraw cluster using xFD and yFD on a given axes
S = self.GetSpikes();
h = plot(ax, xFD(S), yFD(S), '.', ...
'marker', self.marker, ...
'markerSize', self.markerSize, ...
'color', self.color);
% is x,y one of the limits
iL = self.findLimit(xFeat, yFeat... |
fc836f35636f8a7679e982331b72306c0f21ca32dd1dae0d9e8b141db57affce | MATLAB | 423 | 18 | function K = WLKernel_rowsInput(Y, height)
%K = zeros(size(Y,1));
%size(K)
gList = []
for i = 1:size(Y,1)
i
%for j = 1:size(Y,1)
graph = array_to_graph(Y(i,:));
%gB = array_to_graph(Y(j,:));
gList = [gList, graph];
end
%height = 3;
... |
0a2cbab92c5a4e2738cdd1feaf2591a359c594c9a400ec939590c24ae6452e08 | MATLAB | 424 | 19 | function result = normalizekm(km)
% Copyright 2012 Nino Shervashidze, Karsten Borgwardt
% normalizes kernelmatrix km
% such that diag(result) = 1, i.e. K(x,y) / sqrt(K(x,x) * K(y,y))
% @author Karsten Borgwardt
% @date June 3rd 2005
% all rights reserved
nv = sqrt(diag(km));
nm = nv * nv';
knm = nm .^ -1;
for i = 1... |
1522133940f55eac55c1a78d5a23161c7d67a24cbfa4e74e737cf7b8acfdff25 | MATLAB | 424 | 15 | function hdr = empty_hdr(fmt)
% Create an empty NIFTI header
% FORMAT hdr = empty_hdr
%__________________________________________________________________________
% Copyright (C) 2005-2017 Wellcome Trust Centre for Neuroimaging
%
% $Id: empty_hdr.m 7147 2017-08-03 14:07:01Z spm $
if ~nargin, fmt = 'nifti1'; end
org =... |
2a5ac0d28f167d0526b7a761c9373d1c247f2876df5e4a5119c2150980ed702a | MATLAB | 425 | 21 | function RecalculateProjection(self)
% Recalculate Projection (self)
%
% Modified from Jadin Jackson's original code.
iPath = self.projectionPath.GetI();
%fprintf('Recalculating using projection path %d\n', iPath);
switch (iPath)
case 1
self.Projection1();
case 2
self.Projection2();
case 3
self.Projection3(... |
ede5ea5f133df93e76f1e7e15a365bd53954fee57fb1e53a518fccf2fef020c0 | MATLAB | 426 | 20 |
function RBA = jRatioBandPowerAlphaBeta(X,opts)
% Parameters
f_low1 = 8; % 8 Hz
f_high1 = 12; % 12 Hz
f_low2 = 12; % 12 Hz
f_high2 = 30; % 30 Hz
% sampling frequency
if isfield(opts,'fs'), fs = opts.fs; end
% Band power alpha
BPA = bandpower(X, fs, [f_low1 f_high1]);
%... |
f9e57b939025a9c114dd581b2384ffd2fde04facd5969dfcfc7d17d9aead616a | MATLAB | 428 | 16 | %[2018]-"Improved binary dragonfly optimization algorithm and wavelet
%packet based non-linear features for infant cry classification" (4)
function ReEn = jRenyiEntropy(X,opts)
% Parameter
alpha = 2; % alpha
if isfield(opts,'alpha'), alpha = opts.alpha; end
% Convert probability using energy
P = (X... |
24e4335c0bfa324c4965c0e97518e73d46618e852cf92bf7af8a5222611b0034 | MATLAB | 432 | 16 | %[2018]-"Improved binary dragonfly optimization algorithm and wavelet
%packet based non-linear features for infant cry classification" (5)
function TsEn = jTsallisEntropy(X,opts)
% Parameter
alpha = 2; % alpha
if isfield(opts,'alpha'), alpha = opts.alpha; end
% Convert probability using energy
C = ... |
d2fc330c4d1d1cadde262bfee1f5cdeb9167722b702d681a76647e50c3f1171b | MATLAB | 435 | 33 | function P = Permutationmatrix3
P = zeros(8,8);
for a = 0:1
for b = 0:1
for c = 0:1
am = [0, a, b;
a, 0, c;
b, c, 0;];
perm=perms([1 2 3]);
for k=1:6
P(graphlettype(am), graphlettype(am(perm(k,:),perm(k,:)) )) = 1;
end
end
end
end
end
function result = graphlettype(am)
% determine grap... |
f6b7c6d98c60c3d5898eeb6aca9d31ec5254699fa1402557a4fe6172b5efe245 | MATLAB | 435 | 15 | function CutterOption_SelectAndDelete(self)
self.StoreUndo('Select and Delete');
names = self.getClusterNames;
clustersToDelete = listdlg(...
'ListString', names, ...
'Name', 'Delete clusters', ...
'PromptString', 'Select clusters to delete...', ...
'OKString', 'DONE', 'CancelString', 'Cancel', ...
... |
3cbbece6a69776ca1540d40dc47a950cb9e38891ed56d50a0e341428a5ec5852 | MATLAB | 437 | 24 | function G = nk_CompGridFreq(V1, V1ind, V2, V2ind)
vl1 = length(V1ind);
vl2 = length(V2ind);
G = zeros(vl1,vl2);
G1 = zeros(length(V1),1);
G2 = zeros(length(V2),1);
for z=1:length(V1ind)
ind = V1 == V1ind(z);
G1(ind) = z;
end
for z=1:length(V2ind)
ind = V2 == V2ind(z);
G2(ind) = z;
end
for z=1:length... |
0ce3b58091da87796103b3c5d434fd59ba13945b432fd72966cfc3100e217942 | MATLAB | 438 | 15 | function sVimg = nk_SmoothImage(Vdat, Vm, indvol, SmoothKern)
% if exist('badcoords','var') && ~isempty(badcoords),
% indvol = indvol(~badcoords);
% end
Vol = Vm;
Vol.dim = [Vm.dim(1:3)];
Vol.dt = [64,0];
Vimg = zeros(Vm.dim(1:3));
sVimg = Vimg;
Vimg(indvol) ... |
3f782a17f05418401fd77f2df253204e8756d07541e73a0c732920f48ebddd3b | MATLAB | 440 | 13 | function runConcatStep8(path)
%% Pipeline for the proper concatenation of miniscope data across sessions
% Developed by Daniel Almeida Filho July/2020 (SilvaLab - UCLA)
% If you have any questions, please send an email to
% almeidafilhodg@ucla.edu
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
4b3ba106c3ed32b8919fb3fca704d7898c42102ef1377e428ab99ad407e34abf | MATLAB | 440 | 26 | function H = nk_FeatGenEntropy(X, dim, skipzeros)
if dim==2;
X=X';
end
[Cl, kFea] = size(X); % # features , # observations
H = zeros(kFea,1);
for q=1:kFea
if skipzeros
Xx = X(X(:,q)~=0,q);
Cl = length(Xx);
else
Xx = X(:,q);
end
Cu = unique(Xx);
Cux = length(Cu);
... |
133ebcceb3b4fb9c821ebc2c1e6e2e5013b99a052ce520f77b296ae2fd0f334f | MATLAB | 441 | 15 | % Trains an ELM model on the provided dataset.
%
% [inW bias outW] = mexElmTrain( X, Y [, nhn, C ] );
%
% INPUT :
% X - samples matrix (samples in columns)
% Y - labels vector
% nhn - number of hidden neurons (default: dims / 2)
% C - regularization parameter (default: 1)
... |
d0da39ab9bdf5c32edd8546f92aed26c1c055424761b2a031610c4017b3e1415 | MATLAB | 441 | 12 | function data = mripy_dataset2json(asc, anat, func)
%MRIPY_DATASET2JSON Save surface dataset as three.js data in *.json.
% 2017-08-18: Created by qcc
[verts, faces] = mripy_read_asc(asc);
data = mripy_write_geometry([], verts, faces);
ds = cosmo_surface_dataset(anat);
data.underlay = ds.samples';
... |
e7481545223ed66ccb8f5b4c9e0a05b660fef188ae5695aaf26bcd39f40dd591 | MATLAB | 441 | 19 | function s = merge_struct( s1 ,s2 )
% merge_struct : Merge two structures
%
% $Revision: 0.1.0 $ $Date: 2012/6/15 $
%
s = s1;
names = fieldnames( s2 );
for k = 1:length( names )
if isfield( s, names{k} )
if isstruct( s.(names{k}) )
s.(names{k}) = merge_struct( s.(names{k}), s2.(names{k})... |
87768f1c36ece4d9f266f096b883e9de16f6e6435b4531d0dce122503401d90b | MATLAB | 442 | 24 | function LabelMatrix = nk_MakeRVMTargetMatrix(LabelVector)
uL = unique(LabelVector);
if numel(uL) > 1
if min(LabelVector) == -1
LabelVector(LabelVector == -1) = 2;
LabelVector(LabelVector == 1) = 1;
end
uL(~uL) = [];
nclass = numel(uL);
else
nclass = 2;
end
lx = size(LabelVector,1)... |
4bb14fb999761631228a852673d43867962cd051aa995074b9f691bb95135384 | MATLAB | 446 | 13 | function [P, Pfdr, Z, I] = nk_SignBasedConsistencySignificance(E)
% Computed sign-based consistency [0= no consistency, 1=absolute
% consistency]
I = nk_SignBasedConsistency(E);
% Compute Z score
Z = I ./ std(I);
% Compute P value of Z score (right-tailed one-sided test of Z)
P = nm_normcdf(-Z,0,1);
% Correct for mult... |
958b36b97f8738f086d4118432d46cacaa9eec596d3e90306ada39838cb21eed | MATLAB | 447 | 24 | function [L, F, m] = CalculateLRatio( self )
% Calculate LRatio
% ADR 2012/12
% construct components
% 1. FD for each element of ClusterSeparationFeatures
MCS = MClust.GetSettings();
[T, F] = MClust.CalculateFeatures(MCS.ClusterSeparationFeatures);
nSpikes = length(T);
nFeat = length(F);
FD = nan(nSpikes, nFeat);
... |
11ce5b78885d5f269ae8050b63640de823ae2ed2c9a98f0cdc404b06e2e87286 | MATLAB | 448 | 16 | %% Execute this script with fastAUC.cpp in the current directory
%Compile
mex fastAUC.cpp
%Test - needs the statistics toolbox
labels = [1,1,1,1,1,-1,1,1,1,-1,1,1,-1,-1,1,1,1,1,1,1];
scores = rand(1,numel(labels));
posclass = 1;
AUC = fastAUC(labels,scores,posclass);
[~,~,~,AUC2] = perfcurve(labels,scores,posclass... |
7fe3fa9453e08c2c11bfdcf6e0c1a8a2829acabe213c2d1e63f695b2c9e3c871 | MATLAB | 449 | 15 | function [ThreshPerc, ThreshProb, Time] = EvalCoxPH(Models)
[ix, jx, nclass] = size(Models);
Time = cell(ix,jx,nclass);
ThreshPerc = zeros(ix,jx,nclass);
ThreshProb = zeros(ix,jx,nclass);
for h=1:nclass
for k = 1:ix
for l= 1:jx
ThreshPerc(k,l,h) = Models{k,l,h}{1}.cutoff.val;
Thres... |
751c1e033b76e7d03e34a3131177b7e74e733341257329d02e57fc246dbd5cb5 | MATLAB | 451 | 20 | function output = mi(X,Y)
%function output = mi(X,Y)
%X & Y can be matrices which are converted into a joint variable
%before computation
%
%expects variables to be column-wise
%
%returns the mutual information between X and Y, I(X;Y)
if (size(X,2)>1)
mergedFirst = MIToolboxMex(3,X);
else
mergedFirst = X;
end
if (... |
b997eb297cd9abfed6c46c44d6c4a3321c572850286118186b41db4cb604bbeb | MATLAB | 451 | 21 | %
% RT (295)
%
% EEG.icaact = [30x2000x295 single]
%
ic=7;
[Y,I]=sort(RT);
baseline=reshape(EEG.icaact(ic,1:500,I),500,224);
[PB, freqs, times]=timefreq(baseline, 250, 'wavelet', 0, 'freqs', [3 45], 'winsize', 128, 'padratio',2);
PB=10*log10(PB.*conj(PB));
PB=mean(PB,2);
PB=reshape(PB, 44, 224); % 44 x 295
PB_aler... |
24af29df21906a123296b20f5cf879c8d4daf34d80b1523e5e6683b9b2dbd2b4 | MATLAB | 453 | 22 | function [TimeData, TimeNames,TimePars] = feature_Time(V, ~, ~)
% MClust
% [TimeData, TimeNames] = feature_Peak(V, ttChannelValidity)
% Calculate time feature
%
% INPUTS
% V = TT tsd
% ttChannelValidity = nCh x 1 of booleans
%
% OUTPUTS
% Data - nSpikes
% Names - "Time"
%
% ADR April 2008
% version M1.0
... |
73967378eed98b2bd1cbcf2529542ec0aa022e3226bb0804799f7d6a8a79c788 | MATLAB | 459 | 19 | function p_map = nk_ComputeSVMPmap( Y, labels, model)
p = sum(labels==1)/max(size(labels));
if ~isfield(model,'w')
w = model.SVs' * model.sv_coef;
else
w = model.w';
end
X = Y;
[r,c] = size(Y);
J = ones(r,1);
K = X*X';
Z = inv(K)+(inv(K)*J*inv(-J'*inv(K)*J)*J'*inv(K));
C ... |
89006a9f60ee8dd565ca7d6060d4b8411c0d3e9e3f58420f2f98df1ef05fa4c6 | MATLAB | 459 | 15 | function param = NNP(expected, predicted)
if isempty(expected), param = []; return; end
ind0 = expected ~=0;
expected = expected(ind0);
predicted = predicted(ind0);
TP = sum( predicted > 0 & expected > 0 );
FP = sum( predicted > 0 & expected < 0 );
TN = sum( predicted < 0 & expected < 0 );
FN = sum( predicted < 0 & e... |
d8fe01b316744fc303c26c5aa13ee21a007ee98c44d8ae5ec1aa86310acd4ff0 | MATLAB | 459 | 15 | function [newVectors, meanValue] = remmean(vectors);
%REMMEAN - remove the mean from vectors
%
% [newVectors, meanValue] = remmean(vectors);
%
% Removes the mean of row vectors.
% Returns the new vectors and the mean.
%
% This function is needed by FASTICA and FASTICAG
% @(#)$Id: remmean.m,v 1.2 2003/04/05 14:23:58 ja... |
45f4dbd92eb651659199c1a466342610f221161220898f7277381377575dd9be | MATLAB | 460 | 15 | function param = PSI(expected, predicted)
if isempty(expected), param = []; return; end
ind0 = expected ~=0;
expected = expected(ind0);
predicted = predicted(ind0);
TP = sum( predicted > 0 & expected > 0 );
FP = sum( predicted > 0 & expected < 0 );
TN = sum( predicted < 0 & expected < 0 );
FN = sum( predicted < 0 & e... |
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