sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
e7d13dbc78b71df4b3af1fac059713fcab2879cd9ccb0e3a0f8c58f6c2f7ee03 | MATLAB | 1,105 | 30 |
function [dip, p_value, xlow,xup]=hartigansdipsigniftest_ss(xpdf,nboot)
% function [dip,p_value,xlow,xup]=HartigansDipSignifTest(xpdf,nboot)
%
% calculates Hartigan's DIP statistic and its significance for the empirical p.d.f XPDF (vector of sample values)
% This routine calls the matlab routine 'HartigansDipTest... |
f23561cb464383a43fbff884dc4562f0635b260548cbc79bf44ae7fbee84a6b0 | MATLAB | 1,105 | 44 | function L = discreteDAGlogEv(X, G, alpha, ns, prior)
% G is a D*D binary adjacency matrix for a DAG
% X is an N*D matrix where X(i,j) in {1,..,K}
% L = log p(X|G) assuming BDeu(alpha) parameterization
% This file is from pmtk3.googlecode.com
[N,D] = size(X);
L = 0;
if nargin < 3
alpha = 1;
end
if nargin < 4
... |
144df53338cab9a2f3fdacda42b1e7e659958102a9fce90cdb3cb6fca9a880a8 | MATLAB | 1,106 | 51 | function F = angauss( I, s, r )
% ANGAUSS Anisotropic gaussian filtering.
% INPUT:
% Is - Input tomogram
% s - Gaussian standard deviation
% r - Aspect ration in Z axis, if 1 isotropic
% OUTPUT:
% S - Filtered output
%
% See also: diff3d
%
% AUTHOR: Antonio Martinez-Sanchez (an.ma... |
30bb95ce08fe0fc766db06c6bd9eaf4866bfd646e2e4ef84f28596a96fc2de96 | MATLAB | 1,106 | 52 | %% bifft
%
% "Block" Inverse Fast Fourier Transform (IFFT)
%
% <matlab:open('bifft.m') code>
%
%% Syntax
%
% AF = bifft(A,q)
%
%% Arguments
%
% See also <mvgchelp.html#4 Common variable names and data structures>.
%
% _input_
%
% A n1 x n2 x p matrix
% q frequency resolution (default: p)
... |
56b00893089f16d11de5de6fc9dc6a136baed9b5e83025e0cc02700367ba9866 | MATLAB | 1,106 | 59 | function err_total = error_depth_list(param_dist,xcn_list,xpn_list,R,T,X_shape_list,ind_list);
N_view = length(ind_list);
err_total = [];
N_pts = zeros(1,N_view);
for kk = 1:N_view,
xcn = xcn_list{kk};
xpn = xpn_list{kk};
ind = ind_list{kk};
xpn = xpn([1 3],:);
X_shape = X_shape_list{kk}... |
970bc580366b5ccccdbcf1b64d639cb498817e9387a5b60e386dbc2fc59c27a2 | MATLAB | 1,106 | 33 | function pdfcrop(h,hborder,vborder)
%Make the paper size, the same as the figure size, (plus an optional
%border). This is important when exporting figures to pdf for inclusion in
%latex for example.
%
%h is the handle to the current figure and is returned by the matlab figure
%command as in 'h = figure;' when a new f... |
d459684e1716f7849195ddd2fd1921b0f42d35eaf4444a430427b811919cc304 | MATLAB | 1,106 | 32 | function y=modulo(x,N);
%MODULO Congruence of a vector.
% Y=MODULO(X,N) gives the congruence of each element of the
% vector X modulo N. These values are strictly positive and
% lower equal than N.
%
% See also REM.
% O. Lemoine - February 1996.
% Copyright (c) 1996 by CNRS (France).
%
% This program is free softwar... |
b36c746030ec82f92563d374dd04ef87e087fff0dc08d1a3fa3b2089acfab708 | MATLAB | 1,107 | 52 | function [cr,ci,wins]=pwidentification(simmat,labels)
% pwidentification -- perform pairwise identification from similarity matrix
% matrix
% function pwidentification(simmat,labels,p)
%
% [Inputs]
% -simmat: Similarity matrix [pred x correct]
% -labels: index matrix
%
%
%
% [Outputs]
% -cr: all correct... |
bb667c9a7636d84979a0af48a6d1c2ea21c3ee3802b9608cca407967d9ea5866 | MATLAB | 1,107 | 39 | function basicexample()
% Verify that Manopt was indeed added to the Matlab path.
if isempty(which('spherefactory'))
error(['You should first add Manopt to the Matlab path.\n' ...
'Please run importmanopt.']);
end
% Generate the problem data.
n = 1000;
A = ra... |
c988ac0d3fa316cb84476ce8437185d72d3ad24f8be1311e7cb1c4c2268f6c76 | MATLAB | 1,107 | 34 | function offsetAxes(ax, offset)
% this function 'despines' the x- and y-axes, letting them begin at the
% first tick mark
% thanks to Pierre Morel & undocumented Matlab
% and https://stackoverflow.com/questions/38255048/separating-axes-from-plot-area-in-matlab
%
% by Anne Urai, 2016
if ~exist('ax', 'var'), ax = gca; e... |
cf8d143c7ad883c86fd8c1b84ef16b0ba98fd46d9f34ca782ad00084616c72ee | MATLAB | 1,108 | 41 | function [matrix_FDR Nsig_FDR pval tval matrix_uncorr001 Nsig_uncorr001] = network_onesample_ttest(matrix,alpha_FDR);
% ========================================================================
% Ruslan Masharipov, October, 2023
% email: ruslan.s.masharipov@gmail.com
% ==================================================... |
2a0f3e383a2d049c4fb1d8a11cf15368e0041eca6cfd970bad7c153bcb341d20 | MATLAB | 1,109 | 30 | function xRoiLo = shcropx(xCents,xRoiSz,xFarLeftThresh)
xmid = xRoiSz/2; % a little sloppier here than in shcropy but shouldn't matter
fprintf('Median of non-far-left: %.3f\n',median(xCents(xCents>xFarLeftThresh)));
tfFarLeft = xCents<xFarLeftThresh;
tfRegLeft = xFarLeftThresh<=xCents & xCents<=xmid; % normal distro... |
467e493c7dfbd7121fbf6a0beda5c9329fb36dea0989109fe48f3cefd6522624 | MATLAB | 1,109 | 37 | function injection_time=extract_injection_time
[data,timestamps,info]=read_neuralynx_file('Events.nev');
if ~isempty(data)
%FOR DREADDS%%%%%%%%%%%%%%%%%%%%%%%%%%%%
injection_time=1e-6*CNO_injection(timestamps,data.EventStrings);
else
injection_time=[];
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if isempty(injection_ti... |
4bb913e035aab20118b95db2f92f3913e53516332a864b381b3d9eb9da99e034 | MATLAB | 1,109 | 48 | function [Cp,Cpint,time,TAC_extended,weights]=setPatlak(plasma,plasma_time,time,TAC_extended,weights) %reference
%Check Plasma
t_Cp=plasma_time;
Cp=plasma;
if t_Cp(1)~=0
t_Cp=[0;t_Cp];
Cp=[0;Cp];
end
%Check Tissue
if time(1)~=0
%DIM=size(TAC_extended);
temp=zeros(length(TAC_extended)+1,1);
... |
8e301db36b31ee638f7994a96ea8254095a1a2cf0d355c1457f6a648b9c3a472 | MATLAB | 1,109 | 32 | function locs = mypeakseek(x,minpeakdist)
% Alternative to the findpeaks function. This thing runs much much faster.
% It really leaves findpeaks in the dust. It also can handle ties between
% peaks. Findpeaks just erases both in a tie. Shame on findpeaks.
%
% x is a row vector input (generally a timecourse)
... |
b6e2edcb0aa5c5e76d72894de3c809a2512cb682b5cbf858e2500cc2821c7e18 | MATLAB | 1,109 | 24 | PIC = min(IB(1:t_array(2)*10));
PICdesc = min(IB(t_array(2)*10+1:length(Itotal)));
subplot(5,5,pos1+ib);
plot(timeV,Itotal,'k','LineWidth',lwidth);
hold on;
plot(timeV,IB,'r','LineWidth',lwidth);
hold on ;
ylabel(' ', 'FontSize',10,'FontWeight','Bold');
xlabel(' ');
% txt_PICs;
if abs(PIC) < 0.1 && abs(PICdesc) < 0.1
... |
b7613a421b102388b13ae7adc0d37ce528f9f58f7be80426aa576458dccced8a | MATLAB | 1,109 | 38 | function varargout = loadvar(mat_file, var_name, varargin)
%LOADVAR Loads one or more variables from a MAT file.
% Usage:
% X = loadvar(mat_file) % returns first variable in MAT file
% X = loadvar(mat_file, var_name)
% [X1, X2, ..., XN] = loadvar(mat_file, var_name1, var_name2, ..., var_nameN)
% C = loadvar(mat... |
c374334812d474a0f6b796775a10441843c78036a2289176d871ef3f2d1e1fca | MATLAB | 1,109 | 50 | function [key, precomp_grads] = MakeKeypoint(pix, xyScale, tScale, x, y, z, sift_params, precomp_grads)
k.x = x;
k.y = y;
k.z = z;
k.xyScale = xyScale;
k.tScale = tScale;
[key precomp_grads] = MakeKeypointSample(k, pix, sift_params, precomp_grads);
return;
end
function [key prec... |
23861625ba7182da6d5f4b16b4b829e39074a4c5f0f26c662eabc1e42d455cbe | MATLAB | 1,111 | 35 | function disp(t, name)
%DISP Command window display for a ktensor.
%
% DISP(T) displays a Kruskal tensor with no name.
%
% DISP(T,NAME) display a Kruskal tensor with the given name.
%
% See also DISP, KTENSOR/DISPLAY, KTENSOR
%
%MATLAB Tensor Toolbox.
%Copyright 2015, Sandia Corporation.
% This is the MATLAB Ten... |
88cd634630fe140389062c0995d324566b2cfbc2082d04f1ab2d85e6cb587d8b | MATLAB | 1,111 | 25 | % Constructor for the Error Structure
function errorStruct = errorStruct_new(N_FIELDS)
%// Precast empty
errorStruct= struct( ...
'fieldname', cell(1,N_FIELDS), ...
'reference', cell(1,N_FIELDS), ...
'x0States', cell(1,N_FIELDS), ...
'dof_px_correct', ... |
97427979a45b560456ffeaf4df5b2b2a2ad7dfcb6ce6ff2bd9bff044d3cc96d9 | MATLAB | 1,111 | 39 | function [p, np] = permtst1(dif, Nit)
%PERMTST1 Permutation test for means of paired replicates
%
% [p, np] = permtst1(dif, Nit)
%
% The data vector dif contains the differences between two
% 'treatments' or conditions. The function makes Nit Monte Carlo sign
% permutations to find whether the two data sets that produ... |
bfc40e433b1087022bfdd4a0257dc7f2d5e2593294667935279467151a7552d8 | MATLAB | 1,111 | 36 | function h_imstack3ResizingFcn(handles)
[currentInd, handles, currentStruct, currentStructName] = h_getCurrendInd3(handles);
str = get(handles.hideControls, 'String');
pos = get(handles.h_imstack3, 'position');
if strcmp(str, '<<') %large state
defaultWidth = 801;
elseif strcmp(str, '>>') %small state
... |
d1e95ae157ca43938431a6d6ba3aa16dd9f422d6469ff35ffe03a5cb0ee56e33 | MATLAB | 1,111 | 32 | function hs = binaryTreeApply( X, tree, maxDepth, minWeight, nThreads )
% Apply learned binary decision tree classifier.
%
% USAGE
% hs = binaryTreeApply( X, tree, [maxDepth], [minWeight], [nThreads] )
%
% INPUTS
% X - [NxF] N length F feature vectors
% tree - learned tree classification model
% maxD... |
e39faf26e86936d72bdaeea7b4b39ffdc7319b2ae71dbcf42a8cfa0d8b50e342 | MATLAB | 1,111 | 45 | %% Display various plots of a multimodal 2D function, peaks()
%
%%
% This file is from pmtk3.googlecode.com
[X, Y] = meshgrid(linspace(-2.5,2.5,40),linspace(-3,3,50));
Z = peaks(X,Y);
%% find optimum by exhaustive search
Zmax = max(Z(:)); % 8.0752
[rowMax, colMax] = find(Zmax==Z); % max row 38, col 25
Zmin = min(Z(... |
23b16bf9a2eb5ec0675e7971fe9d83005798ff7c61da3b0bbfc8d7cefd832576 | MATLAB | 1,112 | 67 |
%{
_ _
___ _ __ __ _| |__ ___ ___ _ __| |_
/ __| '__/ _` | '_ \/ __|/ _ \| '__| __|
| (__| | | (_| | |_) \__ \ (_) | | | |_
\___|_| \__,_|_.__/|___/\___/|_| \__|
# displayStatus
**Syntax**
```
C.displayStatus()
```
**Des... |
e6d6876829711b26ce5dca4301cff409ed62501d20ee5ca1ee0b47aae9405765 | MATLAB | 1,112 | 25 | function trx = ComputeRelativeLandmarkPos_Body(trx)
pos2 = trx.pos;
nfrm = numel(trx.bodytrx.x);
t0 = trx.bodytrx.firstframe; t1 = trx.bodytrx.endframe;
pos2(:,1,t0:t1) = pos2(:,1,t0:t1) - reshape(trx.bodytrx.x,[1,1,nfrm]);
pos2(:,2,t0:t1) = pos2(:,2,t0:t1) - reshape(trx.bodytrx.y,[1,1,nfrm]);
c = reshape(cos(trx.body... |
f1babf1e6f99c3be0dc55fac93f9bbaa0e85a01f4e5e12013965e87b22584f88 | MATLAB | 1,112 | 37 | %% Learn GGM structure using graphical lasso on flow cytometry data
% HTF 2e p637
%%
% This file is from pmtk3.googlecode.com
loadData('sachsCtsHtf'); % 7466 x 11
%lambdas = 36; %[36 27 7 0];
lambdas = [36 27 7 0]; % same as HTF p637
%lambdas = [logspace(5,0,5) 0];
S = cov(X)/1000; % same as http://www-stat.stanford.... |
1aaaa5795e4fe026ca3863548a8eec8aee6aad625eaa6d19e69aaef32d8d51a9 | MATLAB | 1,113 | 38 | function rd_saveAllFigs(f, figNames, figNamePrefix, figDir, fileType)
%
% function rd_saveAllFigs(f, figNames, [figNamePrefix], [figDir], [fileType])
%
% f is a vector of figure handles. [] to save all open figures.
% figNames is a cell array of figure names
% figNamePrefix is a string that will be the start of all fig... |
83754ba065f7b2b8c8fd8157eb823eb65159a55189ca9370cc497e564d900152 | MATLAB | 1,113 | 34 | function [Y,alpha] = VBA_spm_resample(X,alpha)
% Basic resample function (when no Signal Proc. Toolbox)
% FORMAT [Y,alpha] = spm_resample(X,alpha)
% IN:
% - X: a nXm matrix of n time series
% - alpha: the ration of input versus output sampling frequencies. If
% alpha>1, spm_resample(X,alpha) performs upsampling o... |
8841731adf56ede49046584b5c5966e20e22dc3e071120a352a1be0d6f727d0c | MATLAB | 1,113 | 44 | function [ ] = NiceSave(figname,figfolder,baseName,varargin)
%NiceSave(figname,figfolder,baseName,figtype) formats the figure for best viewing
%and saves it as a .pdf in figfolder with name recname_figname.pdf
%
%INPUTS
% figname string with title of figure
% figfolder folder to save figure to
% baseName ... |
c568e37e58ab90e5d278b12dca182b16633c6ba39bc957c81543161e87fd48b0 | MATLAB | 1,113 | 20 | function [ypeak, xpeak, MaxValue] = CorrRegionImage(CroppedImage, Image, yMinRange, yMaxRange, xMinRange, xMaxRange)
if (nargin == 2) % Only two input arguments, search for max correlation over all image range
CC0 = normxcorr2(CroppedImage,Image); % correlate CroppedImage(small area) and BestImage(full image)
... |
2ea1d908f311ef77b218b56e10b3ecd47e08f6e3ad3bee8b3ab05f216f418a46 | MATLAB | 1,114 | 42 | function [stimmat, stimparams] = getGratingFlashStimulus(stimdesc, spX, spY, bwflag)
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
Nwidths = numel(stimdesc.stripewidths);
Nstimuli = sum(stimdesc.Nphases .* stimdesc.Norientations);
stimparams = zeros(Nstimuli, 3);
stimmat = zer... |
d0f490baa5a35ff9f66288b55ddd749bb19a1064507055668c258376ca4525a3 | MATLAB | 1,114 | 37 | function [Xtrain, ytrain, Xtest, ytest] = mnistLoad(classes, Ntrain)
% Load a subset of mnist corresponding to chosen classes
% Optionally take a subset of those to reduce training set size
% There are about 6000 training examples of each class, 1000 test
% This file is from pmtk3.googlecode.com
if nargin < 1, class... |
e24b3e4654d25e04f9498c6e0cadd7bebc842ecd0de09ff726dae694f0926300 | MATLAB | 1,114 | 35 | function SetLblFilePathRoot(oldlblfile,newlblfile,oldroot,newroot)
% oldlblfile = '/groups/branson/bransonlab/DataforAPT/JumpingMice/projects/202308avgc.lbl';
% newlblfile = '/groups/branson/home/bransonk/202308avgc.lbl';
% oldroot = 'X:\DataForAPT\JumpingMice'
% newroot = '/groups/branson/bransonlab/DataforAPT/Jumpin... |
44b11eab0de6cf79c27dd3d780b4f878653710a5d0a437f3a66a80eb446762dc | MATLAB | 1,115 | 60 | % _ _
% ___ _ __ __ _| |__ ___ ___ _ __| |_
% / __| '__/ _` | '_ \/ __|/ _ \| '__| __|
% | (__| | | (_| | |_) \__ \ (_) | | | |_
% \___|_| \__,_|_.__/|___/\___/|_| \__|
%
% estimateDelay
%
% computes delays between all channels
% and stores it in common
% this is mean... |
5595c2fca508b3656927adf3dda474d91dffbbb44926b7378030cc4af029b2a3 | MATLAB | 1,115 | 51 | function [fx,dfdx,dfdp] = f_DCMwHRFext(Xt,Theta,ut,inF) %
% DCM for fMRI evolution function (including Balloon model)
% function [fx,dF_dX,dF_dTheta] = f_DCMwHRF(Xt,Theta,ut,inF)
% This function evaluates the evolution function DCM for fMRI, including
% the Balloon HRF model.
ut = ut(inF.confounds.indu);
nx = length... |
8859d09cd5f5d66f083fbc6e13828c7e9a14fb96c28b60c5bf6162440565a5a5 | MATLAB | 1,115 | 35 | function channel_map = channel_mapping( subject )
%
% CHANNEL MAPPING
%
% INPUTS
% subject - 'W' | 'T'
%
% OUTPUTS
% channel_map - 2d array of channel numbers (rows, cols)
%
if strcmp( subject, 'W' )
% subset of MT channels
channel_map = ...
[ 45 53 36 60 13 21 4 28;
... |
ab26a25d49bb7e6b24497990ffd633730b2cc56e3eebaae94126e5d1292f1a59 | MATLAB | 1,115 | 58 | function [anybad,wh] = iimg_check_volinfo(maskInfo,imgInfo)
% Checks a series of image .mat files and dims against a reference
% (maskInfo)
%
% :Usage:
% ::
%
% anybad = iimg_check_volinfo(maskInfo,imgInfo)
%
% :Inputs:
%
% **maskInfo** and **volInfo :**
% are spm-style volume info structures
%
% see spm_v... |
ba89d01e1c5010fb79bc8b09aef67fb37c2e0769c4eeb90f214bcd79e787fd07 | MATLAB | 1,115 | 50 | function [rho pval] = circ_corrcl(alpha, x)
%
% [rho pval ts] = circ_corrcc(alpha, x)
% Correlation coefficient between one circular and one linear random
% variable.
%
% Input:
% alpha sample of angles in radians
% x sample of linear random variable
%
% Output:
% rho correlation coeffic... |
f57b1e79747220e71d70a9cb387b18fdbe0f1a581e69bca599206de214ff1894 | MATLAB | 1,115 | 46 | function [gx,dgdx,dgdp] = g_rigid2D(x,P,u,in)
% apply rigid body 2D spatial transform (rotation and translation)
% function [gx,dgdx,dgdp] = g_rigid2D(x,P,u,in)
% IN:
% - x: [useless]
% - P: the 3 rigid body transform parameters
% - u: [useless]
% - in: contains the original image (in.Y)
% OUT:
% - gx: vector... |
48785b91cf32a88171e53d2324052b82b6bdcfa339b8b7922611ba2421db228a | MATLAB | 1,116 | 49 | %% Fit loopy MRF 1-2-3-1 using iterative proportional fitting
%
%%
% This file is from pmtk3.googlecode.com
clqs = {[1 2], [2 3], [1 3]};
NC = length(clqs);
N = 3;
% Some count data
C = reshape([53 414 11 37 0 16 4 139], [2 2 2]);
C = normalize(C);
Cpot = tabularFactorCreate(C, 1:N);
counts = cell(1, NC);
for c=1:NC... |
72291f9c6af2882ccfdf7f74edaa182c179dc2010086e4c5de3e46a84f322ce9 | MATLAB | 1,116 | 36 | function y = pinvNx2(x)
% PINVNX2 computes a pseudo-inverse of the slices of an Nx2xM real-valued matrix.
% Output has dimensionality 2xNxM. This implementation is generally faster
% than calling pinv in a for-loop, once M > 2
siz = [size(x) 1];
xtx = zeros([2,2,siz(3:end)]);
xtx(1,1,:,:) = sum(x(:,1,:,:).^2,1);
xtx... |
ad2bfd5f15cb9f7111deb46795e9a1b5bb15254506993feeece1a6c676126fd0 | MATLAB | 1,116 | 56 | function X = gaminv(P,A,B)
assert((isequal(size(A),size(P)) && isequal(size(B),size(P))),'P, A and B must be of common size or scalars');
sz = size(P);
X = zeros(sz);
k = find((P < 0) | (P > 1) | isnan(P) | ~(A > 0) | ~(B > 0));
if (any(k))
X(k) = NaN;
end
k = find((P == 1) & (A > 0) & (B > 0));
if any(k)
X... |
c2bea7e85ddac6e422b67ba63472cdbe6a8321ed88549ca2fa4a608570defac9 | MATLAB | 1,116 | 38 | % HIFDE_MV Multiply using hierarchical interpolative factorization for
% differential equations.
%
% Typical complexity: O(N) in all dimensions.
%
% Y = HIFDE_MV(F,X) produces the matrix Y by applying the factored matrix F
% to the matrix X.
%
% Y = HIFDE_MV(F,X,TRANS) computes Y = F*X if TRANS =... |
0bab574a402269646e4cf908f916402432df16b756b8946a08cffc6e4351dfa4 | MATLAB | 1,117 | 43 | % Written by Einat Peled
% einatspeled@gmail.com
%
% Input: OneImage, should contain one spot (one mini event)
% Output: keep only the top NumMaxPixels of OneImage
function OneImage_CorrAmp_thresh_MaxPixels = GetMaxPixels(OneImage_CorrAmp_thresh, NumMaxPixels);
% [i,j,v] = find(X) row, column, value
OneIm... |
1b38c5a78120d75608093a0105aef780d9b258ca26ecadd28663a4678803f4a7 | MATLAB | 1,117 | 36 | function saveLbl(old_bundled_lbl,new_bundled_lbl,new_lbl_obj_savestruct)
tname = tempname;
mkdir(tname);
try
fprintf('Untarring old project %s into %s\n',old_bundled_lbl,tname);
fnames = untar(old_bundled_lbl,tname);
% AL20190424: untar() function output in blatant contradiction with
% M-help
ntname = numel... |
552db51c7147076f393bea57ccfe3468520f484dc8fa4f25bea58986e47720b5 | MATLAB | 1,117 | 38 | function v = calculate_bvc_tunings(v)
sig_d0 = v.bvc.sig_d0;
beta = v.bvc.beta;
max_d = v.bvc.max_tuning;
n_eqns = v.bvc.n_dist_tunings;
alpha = sym('alpha');
eqn_vars = alpha;
for i = 1:(n_eqns-1)
eval(sprintf("x%i = sym('x%i');",i,i));
eval(sprintf('eqn_vars = [eqn_vars, x%i];',i));
end
eqn1 = x1 == (x1/... |
8013e4375272f22de010f7fe58639c30d1ed338f328e78303c863112f57f0152 | MATLAB | 1,117 | 41 | function [isAFirst, ppInds] = GetTrihexyDrugConds(fNames)
% function [conds, ppInds] = GetTrihexyDrugConds()
% Load up the drug conditions from the TrihexyDrugConds.xlsx file, return
% whether each person did A or B on their first session
%
% Inputs:
% fNames is a cell array of strings containing TRI_000_0 (ID numbe... |
3a1d7a317ce9de04080f2df694b8f34524acf9f73cccf1af3e588423e28c21d7 | MATLAB | 1,121 | 35 | function h_saveAnnotationROI3(handles)
global h_img3
[currentInd, handles, currentStruct, currentStructName] = h_getCurrendInd3(handles);
roiobj = sort(findobj(handles.imageAxes,'Tag', 'annotationROI3'));
bgRoiobj = sort(findobj(handles.imageAxes,'Tag', 'BGROI3'));
fiducialObj = findobj(handles.imageAxes, 'T... |
e0494505e7802184e8b5769617da076e1a61e77741b93c8de65aaf7a31ae5a73 | MATLAB | 1,121 | 45 | genename='MYC';
choose_pool=1;
time=[0.5 1 2 4 8 16 24 48 72 96];
x=strcmp(c_name,genename);
a=[];
a1=[];
a2=[];
a3=[];
gene_profile=c_pool(x,:);
a(:,1)=mean(gene_profile(:,1:3),2);
a(:,2)=mean(gene_profile(:,4:6),2);
a(:,3)=mean(gene_profile(:,7:9),2);
a(:,4)=mean(gene_profile(:,10:12),2);
a(... |
b9fc8848365c7298d183fbdbdc2cec8e170a9ee6481300492c081287c7f1855b | MATLAB | 1,122 | 38 | % HIFDE_SV Solve using hierarchical interpolative factorization for
% differential equations.
%
% Typical complexity: same as HIFDE_MV.
%
% Y = HIFDE_SV(F,X) produces the matrix Y by applying the inverse of the
% factored matrix F to the matrix X.
%
% Y = HIFDE_SV(F,X,TRANS) computes Y = F\X if T... |
c05aed49ffd8b9739f8b0330fe57fb03d5b405fa69d940c8f4db169abaa44b90 | MATLAB | 1,122 | 38 | function [adj, sz_links] = CBIG_components_subgraphs(adj)
% Script to get components sub-graph.
%
% function [adj, sz_links] = CBIG_components_subgraphs(adj)
% Input:
% adj:adjacency matrix with values going from 1 to number of components with
% more than 1 node. The script assues that the adj matrix is a symm... |
d30779f276a9462920be4570cbf98e6c65dba53d7dcc615444250989ab42b7f7 | MATLAB | 1,122 | 41 | function FBC = FbCrop( FB, delta )
% Crop a 2D filterbank (adjusting filter norms).
%
% Takes a filter bank and crops it by cropping off delta pixels from each
% side. Ensures that the mean response of each filter is 0 and that the L1
% norm is 1, i.e. sum(sum(abs(F)))==1.
%
% USAGE
% FBC = FbCrop( FB, delta )
%
% INP... |
5f3a4efc7d0321d388be7c3095849fe5d75af5f40d9cccb52ac8149ada4f22f9 | MATLAB | 1,123 | 37 | % +------------------------------------------------------+
% | Phase Difference Measurement |
% | with MATLAB Implementation |
% | |
% | Author: M.Sc. Eng. Hristo Zhivomirov 12/01/14 |
% +--------------------... |
f928984eb3fc08fff36000ea43517b0d1d9cd157bb9443e723fba15270106890 | MATLAB | 1,123 | 51 | % Geometry of Ridge Regression
%{
setSeed(0);
mu = [3; 3];
sigma2 = 1;
Sigma = [3,0;0,1];
N = 100;
X = gaussSample(mu, Sigma, N);
xbar = mean(X);
mleCov = X'*X;
%}
xbar = [3;3];
S = [3,0;0,1];
Mu0 = [0;0];
Sigma0 = eye(2);
hold on;
%axis([-5 8 -4 8], 'nolabel');
axis equal
gaussPlot2d(xbar,S,'color','r');
%gaussPl... |
260a52dec93cb0f0bcbe8f113d4c17cf52b2194938f68b019fcd02bc1108d9c1 | MATLAB | 1,124 | 30 | % CROSSCORRELATIONHISTOGRAM calculates cross correlation histogram at a given
% crossCorrelationHistogram.m
%
% Copyright 2008 Vanderbilt University. All rights reserved.
% John Haitas, Jeremiah Cohen, and Jeff Schall
%
% This file is part of JPSTH Toolbox.
%
% JPSTH Toolbox is free software: you can redistribute... |
8b2e0940403a45529a7eceeafd8943cb6cca2605b188c8e12af28e9abdc43c16 | MATLAB | 1,124 | 40 | function outpoints = tal2mni(inpoints)
% Converts coordinates to MNI brain best guess
% from Talairach coordinates
% FORMAT outpoints = tal2mni(inpoints)
% Where inpoints is N by 3 or 3 by N matrix of coordinates
% (N being the number of points)
% outpoints is the coordinate matrix with MNI points
% Matthew Brett 2/2/... |
a1681f537b341b5edded1e4bfcbaf7b306acec52cf3da799916f3f4f2414624d | MATLAB | 1,124 | 43 | function [flyid,trial,movpath] = parseSHfullmovie(m,varargin)
noID = myparse(varargin,'noID',false);
[flyid,idx] = regexp(m,'[\\/]fly?(\d+)[\\/]','tokens','start');
if isempty(flyid)
[flyid,idx] = regexp(m,'[\\/]fly?(\d+)[\\/_]','tokens','start');
end
if isempty(flyid)
[flyid,idx] = regexp(m,'[\\/]fly_?(\d+)[\\/]'... |
60c24bc10111aa33ab58276d5fe6b236b82a947760d4ce11e0cdf580a67ec776 | MATLAB | 1,125 | 36 | function distance = distancePointToLineSegmentV(p, a, b)
% distance = distancePointToLineSegmentV(p, a, b)
% p is a matrix of points (d x n)
% a is a matrix of starts of line segments
% b is a matrix of ends of line segments
% copied from
% http://stupidmatlabhacks.tumblr.com/post/18727965430/distance-from-point-to-th... |
ea3672471937235348b5a99a863f8a3b156d1a61b46f20bc35e2d1ffb3d8e4a4 | MATLAB | 1,125 | 43 | function outTable = convertToTableCore(featureLexicon,inParams)
% deal with optional arguments
if nargin<2 || isempty(inParams)
inParams=struct();
end
%featureLexicon = ReadXMLParams(featureconfigfile);
allpf = fieldnames(featureLexicon.perframe);
pftypeList = {};
for pfndx = 1:numel(allpf)
curpf = allpf{pfndx};
... |
7f657a717e979e0a086a5623633d5bdef72e2c99d55a0102c1dc17d8bbadaac4 | MATLAB | 1,126 | 40 | function crc = CRC8(Vector, Len)
%
% COMPUTE CRC
% CRC is the acronym of Cyclic Redundancy Check, and represents a function whose
% input is a set of bytes (also called byte stream), and whose output is a numerical value,
% usually a 16 or 32 bit integer.
% The term CRC is used to refer to both the function a... |
f8e3f4dc11d526ffccac4c34827e7b351a37d8f07b1a0d28120bb3535038a5ad | MATLAB | 1,126 | 27 | function DV = fplayer(P,beta,player,game)
% derives the player's decision variable given a 2x2x2 payoff table
% function DV = fplayer(P,beta,player,game)
% The payoff table is such that game(:,:,i) is the Ui(a,b), the payoff
% player i receives given that player 1 has played a and player 2 has
% played b. The agent hol... |
3b21a01dbe20f436dbe35462bc18f8bf9959fd2a424af6a5b63da7b184749cb4 | MATLAB | 1,127 | 43 | function [lpos,lposTS,lpostag] = toarray(s,varargin)
% Convert to old-style full arrays
%
% lpos: [npt x 2 x nfrm x ntgt]
% lposTS: [npt x nfrm x ntgt]
% lpostag: [npt x nfrm x ntgt] logical
[nfrm,ntgt] = myparse(varargin,...
'nfrm',[],... % num frames in return arrays
'ntgt',[] ... % num tgts "
... |
696a8038193b811556f7287fe7882f5a34081a6b1221e69cdaa3e399574a973b | MATLAB | 1,127 | 34 | function [theta,phi,inF,inG,x0] = prepare_metaToM(kToM_level,seq_length,game,role)
% set basic params for meta-ToM learner engaging in dyadic games
% function [f,g,theta,phi,inF,inG,x0] = prepare_metaToM(kToM_level,seq_length,game,role)
%
theta = [-2;-2]; % prior log-volatility (k-ToM & BSL)
phi = [-1;0]; % (log-) te... |
b03fd8e1c9faae927962f6df0d41c986aa1b070e100da0255bfa42c548246dc4 | MATLAB | 1,127 | 37 | function [Dm, varargout] = do_variance_normalization(Dm)
% [Dm] = do_variance_normalization(Dm)
% Do variance normalization of rows.
% Assumes stats/pandas representation:
% rows are observations, cols are data dimensionality (or variables).
%
% Parameters
% ----------
% Dm : matrix
% ... |
d2915538ca8741c516e008077d97b44624b275e6c402150bdd4b3d7e2d7b1dca | MATLAB | 1,127 | 44 | %% Reproduce figure 3 of Zou and Hastie JRSSB 2005
%
%%
% This file is from pmtk3.googlecode.com
loadData('prostate');
ndx = find(istrain);
y = y(ndx); X = X(ndx,:);
X = centerCols(X);
X = mkUnitNorm(X);
y = centerCols(y);
[n p] = size(X);
lambda2 = 1000;
w0 = larsen(X, y, lambda2, 0, 1);
wLS = X\y; denom = sum(ab... |
329c2727995f5f2b5bf7d2d43f2b10513185b9463e7c6795c656895aedb750d8 | MATLAB | 1,128 | 47 | %% Get Cell Centered Grid
%
% Creates a cell centered grid matrix in either two or three dimensions.
% the outputs are matrices (in two of three dimensions) containing cell
% centers. Inputs are the cell dimension vectors for the three dimensions.
% Note that they can be different sizes.
%
%
% [X,Y,Z] = getCellCentere... |
47a4688596bc66f201930f3f11fba8fa98d00baaa9bf77d5b9c7f25dc7cd213d | MATLAB | 1,128 | 34 | function [dat] = ft_preproc_rectify(dat)
% FT_PREPROC_RECTIFY rectifies the data, i.e. converts all samples with a
% negative value into the similar magnitude positive value
%
% Use as
% [dat] = ft_preproc_rectify(dat)
% where
% dat data matrix (Nchans X Ntime)
%
% See also PREPROC
% Copyright (C) 2008, Ro... |
b81e10ac55ba636748a860747a40844336ed30e6f902043faf05278d10a99611 | MATLAB | 1,128 | 38 | function m = size(t,idx)
%SIZE Tensor dimensions.
%
% D = SIZE(T) returns the sizes of each dimension of tensor X in a
% vector D with ndims(X) elements.
%
% I = size(T,DIM) returns the size of the dimension specified by
% the scalar DIM.
%
% Examples
% A = rand(3,4,2,1); T = tensor(A,[3 4 2 1]);
% size... |
f6a89824486e446540091c0eca5c2c1ca416485b8ee6eb09e0bf5fb54ee9ae91 | MATLAB | 1,128 | 1 | function plotegfit(data, params, nbins)
% Plots an histogram of data and overlay ex-Gaussian PDF with parameters params = [mu sigma tau]
% data must be a vector
% nbins is optional and allows explicitly setting the number of bins
% (c) Yves Lacouture, Universite Laval
% Version 2.0 27/02/03
[n,m]=size(data);
if min(n,m... |
29ac6bf6d32b8e150d84e3da254103e3fb200ef160a12a87f9d9560f983da0ae | MATLAB | 1,129 | 47 | %% Demonstrate training a chain-structured MRF
% Based on
% http://www.cs.ubc.ca/~schmidtm/Software/UGM/trainMRF.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
% Plot what data looks like
figure;
imagesc(y(1:1... |
41a4baa24890acbd20eaeca61f23dddb280e93ecec2c62978a5e90c9fccfe5c2 | MATLAB | 1,129 | 43 | function [m,s,Y]=MD_mean_std(X)
% Autoscaling function for MD
%
% INPUTS
% X: data matrix
%
% OUTPUTS
% m: mean
% s: covariance matrix
% Y: autoscaled data matrix
%
% Copyright (C) 2016 A. Folch-Fortuny and F. Arteaga
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the ... |
ec8854c30f38837914c84b71d1e51e1720182b3b1321f7ec28b70698e8310db2 | MATLAB | 1,129 | 51 | %% Several ways of implementing weighted least squares
% This file is from pmtk3.googlecode.com
setSeed(0);
N = 100; D = 5;
X = randn(N,D);
w = randn(D,1);
y = X*w + 0.1*randn(N,1);
rk = rand(N,1); % positive weights
% Method 1
RRk = sqrt(diag(rk));
W1 = ((RRk*X) \ (RRk*y));
yhat = X*W1;
sigma2_1 = sum(rk .* (y-yha... |
543438a9c26277234f2daeea839a58bf0fc5f22f2c38d0709535493cea53143a | MATLAB | 1,130 | 43 | function Xrbf = rbfComputeFtrs( X, rbfBasis )
% Evaluate features of X given a set of radial basis functions.
%
% See rbfComputeBasis for discussion of rbfs and general usage.
%
% USAGE
% Xrbf = rbfComputeFtrs( X, rbfBasis )
%
% INPUTS
% X - [N x d] N points of d dimensions each
% rbfBasis - rbfBasis struct... |
734b7d4917d02be2a988079433abf2bf03c952b903511b797681108521d178d5 | MATLAB | 1,130 | 40 | clear all
clc
tmp=pwd;
cd ..
addpath(genpath(fullfile(pwd, 'utils/')));
addpath(genpath(fullfile(pwd, 'spmutils/')));
cd(tmp);
% prefix of the subject folders
folder_prefix='Subj';
% prefix/suffix of corresponding T1 files
file_prefix='Subj';
file_suffix='.nii';
image_dir=fullfile(pwd, 'imgs');
group_m... |
783933e317098c0e9dd93ba13a1ac63216548f1ad2180eab8b2db923ce4f79e9 | MATLAB | 1,130 | 33 | function [h] = boxplot_grouped(data,group,group1_label,group2_label,color,legend_flag)
%Boxplot for 2 independent variables
% INPUTS TYPE DESCRIPTION
%
% group double categorical array describing conditions (4 in total) for data
% array
% group1_label cell... |
edeab26ecd6fbeac54c3f21bdaa44b3867ec0a15474116f5b2a8aeadcff3e1a8 | MATLAB | 1,130 | 24 | clear all
%%
%Define Parameters
[opt] = ParameterOptions();
%%
%Generate Pathway Amplitude & Gradient Waveform basis set
%First Dictionary
[PathwaySignalFirstOrder,GwaveFirstOrder,TransFirstOrder] = PathwayOperatorOrder(opt,'First');
%Second Dictionary
[PathwaySignalHigherOrder,GwaveHigherOrder,TransHigherOrder] = Path... |
0450bb6a22e478ac2977b6b4b84713a1a8ac5dd6e77ba9f0ae36fb43024bb404 | MATLAB | 1,132 | 45 | % DurationPlaceForFluorescencePLSR.m
% Sarah West
% 7/27/23
% Takes duration_place for cont. rest & walk averaged across 1 second
% You don't have to worry about rolling overlap, becuase you don't do that
function [parameters] = DurationPlaceForFluorescencePLSR(parameters)
MessageToUser('Duration for ', parame... |
37bd9affe826c943c6ac6becd59aa2d7426ecf03673a96feae587d25213b6684 | MATLAB | 1,132 | 23 | %% Hjorth parameters
% Hjorth Activity 活动性：衡量信号波幅的偏离程度，是时间函数的方差var
% Hjorth Mobility 移动性：衡量坡度的变化，为信号一阶导数方差的平方根 除以 信号方差的平方根
% Hjorth Complexity 复杂性：衡量一个振幅上有多少个标准的坡
% X: single channel EEG signal (either a row vector or a column vector)
% See also:
% feat_HjorthActivity, feat_HjorthComplexity
%% Reference
% ... |
5c907d3bd2a42eb3de58f83571d985e862a20210a9a0c76ee9dc304845d6c881 | MATLAB | 1,132 | 47 | % _ _
% ___ _ __ __ _| |__ ___ ___ _ __| |_
% / __| '__/ _` | '_ \/ __|/ _ \| '__| __|
% | (__| | | (_| | |_) \__ \ (_) | | | |_
% \___|_| \__,_|_.__/|___/\___/|_| \__|
%
% callback when channel_label_picker is used
function updateChannel(self, src, ~)
d = dbstack;
i... |
b49ca2cafc02a85b70f2d3116869fe14eba9da7383e07fd05a13ef24b431ae8f | MATLAB | 1,132 | 39 | function f = filterBinomial1d( r, show )
% 1D binomial filter (approximation to Gaussian filter)
%
% Creates a binomial filter of size 2*r+1 x 1. This can be used to
% approximate the Gaussian distribution with sigma=sqrt((2*r+1)/4). For
% large r, should give same output as:
% g = fspecial( 'Gaussian', [2*r+1,1],sqr... |
bf68151043ded1e2c751e5cf572a45f073a5b1260724e7464bd5449eea21d11a | MATLAB | 1,132 | 43 | function [pg, name] = pmlChapterPages(tocfile)
% Return a list of the starting, (hard cover) pages of the chapters in PML.
% (skips the preface so that pg(1) = 1, not e.g. xxv)
%% Input
% tocfile - the path to the pml.toc file
% (default = C:\kmurphy\local\PML\Text\pml.toc)
%
%% Output
%
% pg - a list of the startin... |
5265a81114a9659d41b3e5cb4d0bb8fc7342f4fd0d9edf0adb54078d6d314e91 | MATLAB | 1,133 | 40 | function [ ] = computeTBrain( ws )
%The function generates a vector of t values comparing the consistencies
%along the blue and red dimensions for all voxels in the brain
%write message to screen
sprintf('Computing voxels'' temporal consistency asymmetry cofficients')
%% set empty vectors
[t_vec, p_vec] = deal(nan(s... |
5e5cb45ccdaee7cc2bf26136a76c44427d65009929f2933234313e4f46592301 | MATLAB | 1,133 | 37 | function C = mrdivide(A,B)
%MRDIVIDE Slash right division for sparse tensors.
%
% MRDIVIDE(A,B) is called for the syntax 'A / B' when A is a sparse
% tensor and B is a scalar.
%
% Example
% X = sptenrand([4 3 2],5);
% X / 3
%
% See also SPTENSOR.
%
%MATLAB Tensor Toolbox.
%Copyright 2015, Sandia Corporation... |
88e5b1bb1309edfbd61c7e810d070eb86a4117d52ceefa709d858d7057c13041 | MATLAB | 1,133 | 37 | function C = mldivide(A,B)
%MLDIVIDE Slash left division for sparse tensors.
%
% MlDIVIDE(A,B) is called for the syntax 'A \ B' when A is a scalar and B
% is a sparse tensor.
%
% Example
% X = sptenrand([4 3 2],5);
% 3 \ X
%
% See also SPTENSOR.
%
%MATLAB Tensor Toolbox.
%Copyright 2015, Sandia Corporation... |
a171940e1a74bba75003f609abe6913586e810e1535a9c07dc04fa66f2aaaadb | MATLAB | 1,133 | 37 | classdef (Sealed) NetworkTypes
% defines the available network types
% as enumeration (available at R2013a)
enumeration
LinLatt,
SqrLatt,
CircSqrLatt,
CubLatt,
ComplGraph,
BarabAlbGraph,
HolmeKimPLGraph,
WattsStrogGraph,
ConnWaStGraph,
... |
c4f883f13335037a85ae2934cb7f6d1ccc3336ccc1f997420ec82c636aec11cb | MATLAB | 1,133 | 28 | %% Draw from truncated normal distribution
function samples = DrawFromTruncatedNormal( mu, sigma2, lowerBound, ...
upperBound, nSamples)
% Draw nSamples from a truncated normal distribution with mean mu and
% cariance sigma. Truncation is acheived by resampling if the drawn ... |
ee16223a2d5a73212840304efc4aea987bfb0cd2500fc0be96764c72f0aa9d37 | MATLAB | 1,133 | 32 | function DM = ft_preproc_online_downsample_init(factor)
% function DM = ft_preproc_online_downsample_init(factor)
%
% Initialize an downsampling model with the given factor.
% Copyright (C) 2010, Stefan Klanke
%
% This file is part of FieldTrip, see http://www.fieldtriptoolbox.org
% for the documentation and details.... |
f52491fd0fbf20654adacef287c2b21cd06ab4ce126feac869010586097a10a3 | MATLAB | 1,133 | 53 | %% Reproduce Figure B.1 p447 from Bernardo94
%
%%
% This file is from pmtk3.googlecode.com
ns = [5 20];
[styles, colors, symbols] = plotColors;
for ni=1:length(ns)
n = ns(ni);
mus = -1.8:0.1:1.8;
M = length(mus);
n0 = 1;
n0B = 5;
mu0 = 0;
r1 = (1/n) * ones(1,M);
r2 = (pi/(2*n)) * ones(1,M);
r3 = (mus-mu0).^2;
r4 = ... |
0730025c2ab089e7f34108c744fd1103d7829609ba277e0395f859dd09204238 | MATLAB | 1,134 | 48 | function outIndex = multinomialR(inIndex,q);
% PURPOSE : Performs the resampling stage of the SIR
% in order(number of samples) steps.
% INPUTS : - inIndex = Input particle indices.
% - q = Normalised importance ratios.
% OUTPUTS : - outIndex = Resampled indices.
% AUTHORS : Arnaud Doucet an... |
14144ff2a5a96a29c9b8636888b4ac26e5ce6e04177d1fa42097ad1a808f5c34 | MATLAB | 1,134 | 29 | function timeout(fExpr, fTimeout)
% TIMEOUT Interrupt execution of script of function after specified period of time
%
% fExpr - MATLAB expression, function or script to run
% fTimeout - timeout in seconds
%
% This function uses undocumented command window method to
% programatically send Ctrl+C after sp... |
8ec7dc92816c62472a7b6d83d18700465f63eef09d6d60e0dc734458278e22fb | MATLAB | 1,134 | 30 | function Draw_Foci(foci,faces)
% This function draw spheres of a specified color and radius at the
% location given by the structure foci. Fields include: location, color,
% radius. It is assumed that coordinate space and voxel-index space are
% exactly aligned. foci.color are rows of RGB values [0,1].
if ~exi... |
9bc0a96d54bdeebcc04a8569e86a7e5a7afe7c319d2cb914558d39c320dbdc4e | MATLAB | 1,134 | 21 | function test_AR_GRONe_SA_training_conda()
% Test training on a project using some of AR's flybubble videos.
% That project is a multianimal project.
if ispc() ,
warning('conda backend is not supported on Windows, so %s always passes on Windows', mfilename());
return
end
linux_project_file_path... |
eb0f3db87058cf349d1fa9c91c24ab6f06d878e21eb4218b01a44d2a9deb8d6c | MATLAB | 1,134 | 33 | function [N,M]=divider(N1);
%DIVIDER Find dividers of an integer.
% [N,M]=DIVIDER(N1) find two integers N and M such that M*N=N1 and
% M and N as close as possible from sqrt(N1).
%
% Example :
% N1=258; [N,M]=divider(N1)
% F. Auger - November 1995.
% Copyright (c) 1996 by CNRS (France).
%
% This program is free so... |
2d315f98739c1e92e3524bdac096ba2ae37a3c7b8215d28a1cafb16322c8cd5c | MATLAB | 1,135 | 30 | function [tau] = fit_tau_to_data(euclidean_distances,similarity_distribution,df,v)
fun = @(x) tau_fit(df, v, similarity_distribution, euclidean_distances, x(1));
tau = ...
fmincon(fun, ...
v.fit.tau_init, [],[],[],[], v.fit.tau_lb, v.fit.tau_ub, [], ...
optimset('TolX', 0.0001, 'TolFun', 0.0001, 'MaxFunEv... |
6b3278346a733718a1acdff3aef34771b44b98fcd5bf31951605175d666b9b41 | MATLAB | 1,135 | 36 | function [lh,th,mm] = annotate_ttest_data(ax,x1,x2,y_level,capSize,y_symbol_mult,label,symbol,labelArgs,symbolArgs,lineArgs)
if (nargin < 5) || isempty(capSize)
capSize = 2;
end
if (nargin < 6) || isempty(y_symbol_mult)
y_symbol_mult = 2;
end
if (nargin < 7) || isempty(label)
... |
fb9d6602a8fd52ed7f2c3054cc111eab8f8c300c8b415cd60b4763d42e4f610f | MATLAB | 1,135 | 28 | function [kept,added]= ...
setDifferencesScoreFeatures(scoreFeaturesOld,scoreFeaturesNew)
% Given an old and new scoreFeatures, computes a boolean array that tells
% which elements of the old one are retained in the new one (kept), and a
% boolean array indicating which elements of the new one are not present in
% th... |
320bd72493c02cd48d892a42fd95002c0837356ef81108a2f3042908d9e260c9 | MATLAB | 1,136 | 33 | function [h,p] = VBA_groupBMC_btwGroups(Ls,options)
% test for between-groups difference in model frequencies
% function [h,p] = VBA_groupBMC_btwGroups(Ls,options)
% IN:
% - Ls: {nmXns_1, nmXns_2} array of log-model evidences matrices of each group (nm models; ns_g subjects in the group).
% - options: a structure c... |
a47ea2ca9b7294d7816b6728996238b040b153f032ce2f5197662c7e93895697 | MATLAB | 1,136 | 43 | function [u] = get_U_basis(T,dt,n,btype)
% build input basis function set on temporal grid
% function [u] = get_U_basis(T,dt,n,btype)
% IN:
% - T: end time (in sec) {1e2}
% - dt: temporal resolution (in sec) {1}
% - n: number of basis functions {16}
% - btype: 'Fourier' or 'RBF' {'Fourier'}
% OUT:
% - u: nX(T... |
66ecf2702cfe9b8d5075d949790f69297a933ee4ddfdb67e8c3a3a477741dc5d | MATLAB | 1,137 | 45 | function model = rvmSimpleFit(X, y, gamma, varargin)
%% Fit a relevence vector machine, i.e. logreg + rbf kernel + ard
% Does not use sparseBayes package, so is much slower
% This file is from pmtk3.googlecode.com
pp = preprocessorCreate('kernelFn', @(X1, X2)kernelRbfGamma(X1, X2, gamma));
K = nunique(y);
if K <= ... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.