sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
fc68799d19ebedf3b001e2f0fda549a3aa106f77acd7c040de341441dcb1b659 | MATLAB | 1,508 | 73 | function [x_comp] = comp_distortion(x_dist,k2);
% [x_comp] = comp_distortion(x_dist,k2);
%
% compensates the radial distortion of the camera
% on the image plane.
%
% x_dist : the image points got without considering the
% radial distortion.
% k2: Radial dist... |
0b293784db301979ff0c95b4edea1880ab1e8cecf8509695e740eee781208233 | MATLAB | 1,509 | 44 | load('brain-region-spatial-res', 'lec_s_info', 'mec_s_info', 'ca1_s_info','ca3_s_info');
figure('position', [722 559 641 135]);
tick_length = 0.015*ones(1, 2);
subplot(1, 3, 1);
Y = {lec_s_info, mec_s_info, ca3_s_info, ca1_s_info};
h = plotSpread(Y); hold on;
for i = 1:4
plot(i, median(Y{i}), '.', 'markersi... |
b62a3a1335a990ea09daa5544783e27d37108671c09a54c8b980db21997e3d61 | MATLAB | 1,509 | 60 |
%% cue scores
% figS5
load('allFolders.mat');
thresholds = nan(1,5);
for VR = 1:5
clear folders;
switch VR
case 1 % VAVR
folders = folders_combo;
clr = 'c';
case 2 % AVR1
folders = folders_audio;
clr = 'm';
... |
c1322589bcb49ea2af9bf8cb2d1aa7aecf8d794a61f7f226721bf646db9984fe | MATLAB | 1,509 | 52 | function [Y,V] = TLmask(maskfilein,varargin)
% provide the name of the proper file containing MNI parcels,
% such as Atlas.wmparc.2.nii
% Y = TLmask(maskfilein);
% returns a 3d logical of in-mask voxels for the grey matter mask of
% the subject associated with the call.
% [Y,V]... |
c4a36c7d9e201c3ba016fe342fc70e4e4e1654cd6430163af2668b0e678a3bd0 | MATLAB | 1,509 | 61 |
%%% Extraction of the final intrinsic and extrinsic paramaters:
check_active_images;
if ~exist('solution_error')
solution_error = zeros(6*n_ima + 15,1);
end;
fc = solution(1:2);%***
cc = solution(3:4);%***
alpha_c = solution(5);%***
kc = solution(6:9);%***
fc_error = solution_error(1:2);
cc_error = solution_err... |
e70abcbb60f23c5f81942269b5ca8061419c4e9ed2371e27306fa10dd27fdb74 | MATLAB | 1,509 | 40 | function run3dtriangulate(trkfile1,trkfile2,pptype,varargin)
% Run 3d postproc and resave to trkfiles in place
%
% trkfile1/2: full paths trkfiles (these will be MODIFIED in-place)
% pptype: see PostProcess.triangulate
[crigmat,rois] = myparse(varargin,...
'crigmat',[],... % path to mat-file containing single CalRi... |
f1bd3203d0017ed9d5063414f0c1453d6c05ff57fd32eabac3423537ea292914 | MATLAB | 1,509 | 43 | % SIMULATE_SPIKE_TRAIN accepts a psth and generates a spike train with a given number of trials
% simulateSpikeTrain.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 re... |
53be8f4b9fec8553ff344308136cf2eabadc107b22c90861201d618ec935fbd6 | MATLAB | 1,510 | 55 | function [keys] = loadFOVKeyptsAndFeatures(FOV,round,bigparams)
% Load any Fov, make it global and return
% Note that all keypoints have to be warped back from the downsampled rate
foldername = fullfile(bigparams.EXPERIMENT_FOLDERROOT,...
sprintf('F%.3i',FOV),...
'4_registration',...
sprintf('%s-F%.3i-down... |
4a27c14f1e16dec1acf78184501386458e4532b9ce1d6a774848de8495fa6fea | MATLAB | 1,511 | 58 | %% Demonstrate training a lattice-structured CRF
% Based on http://people.cs.ubc.ca/~schmidtm/Software/UGM/trainApprox
% This file is from pmtk3.googlecode.com
%% Get data
setSeed(0);
X = loadData('Ximg');
Xclean = X;
y = 1+X;
X = Xclean + 0.5*randn(size(Xclean));
figure; imagesc(X); colormap(gray)
[nRows,nCols] ... |
75e2d8234bad329779acff194113d56a9567bcce30bd9f9509cc50dc91ad7f43 | MATLAB | 1,511 | 60 | function SaveColorBar(SaveName, Limits, CTicks, Label,LoadingColorMap)
% Limits=[0 20];
% CTicks=[0 20];
% Label='\DeltaF/F_0';
fig1=figure;
hold on
left=100; bottom=100 ; width=600 ; height=600;
pos=[left bottom width height];
axis off
caxis(Limits)
if ~isempty(LoadingColorMap)
colormap(LoadingColorMap);
end
hcb=col... |
9f65b63788e80aa3ef612e53d431b1e2fd7dff28268b03e602295e0f9c3701cc | MATLAB | 1,511 | 61 |
%%% Extraction of the final intrinsic and extrinsic paramaters:
check_active_images;
if ~exist('solution_error')
solution_error = zeros(6*n_ima + 15,1);
end;
fc = solution(1:2);%***
cc = solution(3:4);%***
alpha_c = solution(5);%***
kc = solution(6:10);%***
fc_error = solution_error(1:2);
cc_error = solution_er... |
b9cf38a2f57f7689d85cbb43087b03be721b92d102e250e94c5b6ae4770c821a | MATLAB | 1,511 | 55 | function [options,params2update] = VBA_fillInPriors(dim,options)
% fills in priors structure with default priors if necessary
% function [priors,params2update] = VBA_fillInPriors(priors,dim,verbose)
% IN: [see VBA_check.m]
% - priors: [can be left empty]
% - dim: [required]
% - verbose: flag for verbose mode
% OU... |
be74fc185ea62f875db61e578e9e819ae044148ad3099aaf4d575db00d685097 | MATLAB | 1,511 | 69 | function [] = plot_2dresp(model)
unpackStruct(model.internals);
%number of time steps
maxt=40;
facto=0.9; %model_tau = 100ms
%%% pulse response in location context (wI(:,3))
clear r
fixed_point1=atanh(fixed_point1');
r(:,1)=fixed_point1;
for i=2:maxt
if(i==2)
r(:,i)=facto*r(:,i-1)+(1-facto)*(model.w... |
58124e4601393de9e156162c768362b10a94d03a3502c6ed74d28331a3c5cfa5 | MATLAB | 1,512 | 47 | function [bestSelectedVars, w] = larsSelectSubsetCV(X,y,varargin)
% Choose amongst the subsets on the LARS regularization path
% using MLE on chosen subset and CV error
% w size d x 1 is the MLE for the chosen subset (offset ignored)
% This file is from pmtk3.googlecode.com
[lambdaRidge, CVnfolds] = process_options(... |
59926d54128b6b2217028db5d134b2692a87f273bee9650e6d50ee6af1fb7ab2 | MATLAB | 1,512 | 28 | function [opt] = ParameterOptions()
%%
%Sequence parameters
opt.gamma=2*pi*42.58*10^6; % Gyromagnetic ratio
opt.G=52; % Diffusion Gradient Amplitude (mT/m)
opt.tau=13.56; % Diffusion Gradient Duration (ms)
opt.TR=28; % Repetition Time (ms)
opt.alpha=24; % F... |
736279b6df098c794597b943f75c4386fea4414295570bd47c30424713ca2e63 | MATLAB | 1,512 | 59 | function value = graysampler(imageHandle)
%GRAYSAMPLER Returns grayscale value of pixel after a button press.
% VALUE = GRAYSAMPLER(IMAGEHANDLE) returns a grayscale value from an
% image with a handle of IMAGEHANDLE. The value will be the intensity of
% the pixel under the cursor when a mouse button is pressed.
... |
73ccc2534cc37b14b0f71dca3d7464ee8ebe56886dd5849c152e6676a9bef622 | MATLAB | 1,512 | 50 | function FR = FbApply2d( I, FB, shape, show )
% Applies each of the filters in the filterbank FB to the image I.
%
% To apply to a stack of images:
% IFS = fevalArrays( images, @FbApply2d, FB, 'valid' );
%
% USAGE
% FR = FbApply2d( I, FB, [shape], [show] )
%
% INPUTS
% I - 2D input array
% FB - filterban... |
b1abf846367f8592baf0752d97d6511314d9a0f09a5cbc392e4b358fc1054a97 | MATLAB | 1,512 | 101 | function RT = rt_resample(RT,cfg)
% v.0.0.2
% <*LAN)<|
%
%
%
% cfg.newfs = [n] or [n1 ..]
%
%
% Pablo Billeke
% Francisco Zamorano
if nargin == 1
newfs =min(diff(RT.laten));
cfg.newfs = newfs;
else
if isnumeric(cfg)
newfs = cfg;
cfg = [];
cfg.newfs = newfs;
elseif isstruct(cfg)
if isfield(... |
fb0de9f2164fb3b09c9ef0772d56702f27318264cf2cc1f651ed7a011d984006 | MATLAB | 1,512 | 45 | function ph = fill_between_lines_Y(ax,X,Y1,Y2,faceC,varargin)
% fills between curves Y1(X) and Y2(X)
%
%if ischar(faceC)
% faceC = get_color_from_char(faceC);
%end
%if isrow(faceC) && ((numel(faceC) == 3) || (numel(faceC) == 4))
% % faceC is a single color
% faceC = repmat(faceC,numel(... |
1dcefc049bf88fb9afc5721d98d943fe6c6740a7bc71dfe493b098544efe81a9 | MATLAB | 1,513 | 33 | function eventRippleIds = getValidEventIDs(PFresultsStruct_paramPoint, resultsStruct_paramPoint, modelParam)
% eventRippleIds = utils.getValidEventIDs(PFresultsStruct(ithParam1, ithParam2, ithNet), resultsStruct(ithParam1, ithParam2, ithNet), parameters);
%
% Criterion for preplay events are stricter than criterion for... |
773769b8dcea7fc0c70a79e6c1a7542a0da85309241151184c2faee250376705 | MATLAB | 1,514 | 46 | function generate_pseudo_static_PET(PET_dyn_path,time_PET,diagnostic_path,options)
%generate a Pseudo STATIC PET image by averaging the frames acquired from
%minute 40 (or as in options) to the end of the acquisition.
%
%PET_dyn_path: PET dynamic NIFTI file path
%time_PET: time_grid (in seconds)
%out_path: folder whe... |
fa5cecb962d71f6548c1d2cd49c0e77236ddbb77497e717ecf96ea23d5ebc0b6 | MATLAB | 1,514 | 51 | function tests = mex_mergesortfilesTest
tests = functiontests(localfunctions);
end
function setup(testCase)
testCase.TestData.tempDir = '/mp/nvme0/tmp/testworks';
if ~exist(testCase.TestData.tempDir)
mkdir(testCase.TestData.tempDir)
end
n = 4000;
data = {};
for i = 1:4
data... |
118d6b28ae197cba1987e3bd024f031d7ca516e44c86ef8710add8e17c4f3ceb | MATLAB | 1,515 | 44 | function mdiag = kroncovdiag(BB,C,ii)
% Compute diagonal of BCB^T, where C is symmetric and B is kronecker matrix
%
% Ldiag = krondiagBXBtrp(B,C,ii)
%
% Computes diagonal of B*C*B', where B = (Bn \kron ... \kron B2 \kron B1)
%
% INPUT
% BB - cell array with basis matrices {A1, ..., An}
% C - symmetric matri... |
327c9952477896f0766e9fd06c5b97ffb45f25c3a602d494869bd78b839655bb | MATLAB | 1,515 | 42 | function clickWheelData = sequenceWheelData(clickArray, wheelData, params)
% This function sequences wheel data into windowed-timecourses
% corresponding to individual clicks. It returns a matrix where the number
% of rows are the number of samples in a window (specified in params by the
% preStimOffset and postStimOff... |
caa86b1eed359bded2f4fc25a0dbb8131d6549f80c8ef190f7183cc96781d6f4 | MATLAB | 1,516 | 46 | clear all
close all
addpath(genpath('/m/nbe/scratch/braindata/eglerean/narrative/isctoolbox2'))
clabels={
'movGSR6mm'
'mov'
'movGSR'
'mov6mm'
}
for c=0:3
% c is a number that goes from 0 to 3 to follow subjects0.m, subjects1.m, ...
disp(['subjects' num2str(c) '.m'])
run(['subjects' num2str(c) '.m'])
for s=... |
f107465697e4aee6b5c8392858b575e15c2e14a4d5172de5ef1c4ba10dbb055c | MATLAB | 1,516 | 43 | %-----------------------------------------------------------------------------------------
% Plot mean respiratory track locked to odor onset
%
% Kehl et al. 2024 (DOI:XX)
% Single-Neuron Representations of Odors in the Human Brain
% Figure 1d
% Author: Marcel Kehl
% License: MIT License
%---------------------------... |
60637391718dcabdb217120fe1aa7e15352566c0d0b79eb17ebadf7896b77b25 | MATLAB | 1,517 | 45 | function [logZ, bels] = bruteForceInferQuery(factors, queries, clamped, localFactors)
%% Run inference using brute force enumeration
% factors- cell array of tabular factors
% queries - cell array of vectors of integers specifying which joints to
% compute; can also be just a vector for a single query
% clamped - po... |
aeb38772ce8c531b1e951426a281733a093ef51b394eb942ba8325f860288841 | MATLAB | 1,517 | 57 | %% init
clear all
addpath(genpath('src'));
parameters;
%%
% files = dir(fullfile('input', '*.tif'));
% Display the names
% names = {files.name};
files = dir(fullfile('input/bw_reruns_of_reruns', '*.tif'));
names = {files.name};
n_files = max(size(names));
disp(['number of files: ' num2str(n_files)]);
results = {'... |
7b2ed740ed14877e636e2fda64f5e0a13bd9822a43b61a01653cf9bb6e4a23c6 | MATLAB | 1,518 | 42 | clear
clc
%{
delete(gcp('nocreate'))
myCluster.NumWorkers = 8;
parpool('local',8)
%}
NineMuscleMorphParaInitial = load('NineMuscleMorphParaInitial.mat');
NineMuscleMorphParaInitial = NineMuscleMorphParaInitial.NineMuscleMorphParaInitial;
MaxFunctionEvaluations_Data = 10^300;
MaxIterations_Data = 100;
OptimalityTole... |
2d54bae3bd3b740a98c1a115507fac1b91a32fd72912650895312ca3ea975464 | MATLAB | 1,519 | 48 | function hout = imhistpanel(parent,himage)
%IMHISTPANEL histogram display panel
% HOUT = IMHISTPANEL(PARENT,HIMAGE) creates a histogram display panel
% associated with the image in specified by the handle HIMAGE, called the
% target image. HPARENT is the handle to the figure or uipanel object that
% will contai... |
d17e0d8d36549a1e2e9f2b85d432f725bbdddf0ea1e68da9db54565af47aff96 | MATLAB | 1,519 | 39 | %function calib_gui_no_read,
cell_list = {};
%-------- Begin editable region -------------%
%-------- Begin editable region -------------%
fig_number = 1;
title_figure = 'Fisheye Camera Calibration Toolbox';
cell_list{1,1} = {'Image names','data_calib_no_read;'};
cell_list{1,2} = {'Read images','ima_read_calib_... |
340777437ce7802809d3823fb108d428277717206ba9d1c635deae9b37dbef99 | MATLAB | 1,520 | 56 | %% Plot a Gamma Distribution
%
%%
%as = [1 1.5 2 1 1.5 2]; bs = [1 1 1 1.5 1.5 1.5];
% This file is from pmtk3.googlecode.com
as = [1 1.5 2];
b = 1;
bs = b*ones(1,length(as));
figure;
[styles, colors, symbols] = plotColors;
legendStr = cell(1, length(as));
%styles = {'k:', 'b--', 'r-'};
for i=1:length(as)
a = ... |
8e3ecb413ccf63adce31e349cb5135337d798a84bdf0e2e398fde4939a5f1565 | MATLAB | 1,520 | 40 | %% Getting individual connectivity values
subj1 = {'POGO_11' 'POGO_13' 'POGO_23' 'POGO_25' 'POGO_29' 'POGO_31' 'POGO_32' 'POGO_34' 'ST02' 'ST03' ...
'ST05' 'ST06' 'ST08' 'ST14' 'ST20' 'ST27' 'ST36' 'ST45' ...
'ST47' 'ST48' 'ST49' 'ST50' 'ST51' 'ST56'};
subj2 = {'H_02_48' 'H_03_49' 'H_05_50' 'ST10' 'ST12... |
e4ced091b7f837f13872cc79494b548297ef51efdcd637cff4ad25bd9e1a0b3f | MATLAB | 1,520 | 56 | function [clusters,imax] = RFT_clusters(X,xc,verbose)
% identifies the clusters on a thresholded RF defined on a regular lattice
% [out] = RFT_clusters(X,xc,verbose)
% This function finds the connected clusters of points Pi on a regular
% lattice, such that their value X(Pi) exceeds the threshold xc.
% IN:
% - X: the... |
2e5dd98e12fa0a64b12a649a41653e2528c4b6a69b7e0da16de2420bee5511d2 | MATLAB | 1,521 | 47 | %% SAT - app_input::
%% helper.getFiles
% Name: Phone Kyaw
% Date: 09/19/2024
% Description: Get the user selected file path
% Parameters: None
% Return Value: files - Nx1 cell containing all the files' path inside the
% directory user selected
%______________________________... |
9e9b5dc4aef64391b04e84420636c925c48c21d0c9900cc5523fbe6ff8a6ee0a | MATLAB | 1,521 | 44 | %% Compare paired and unpaired Bayesian posteriors on contingency table differences
%PMTKneedsStatsToolbox ksdensity
%%
% This file is from pmtk3.googlecode.com
requireStatsToolbox
setSeed(1);
thetaX = [0.3 0.4 0.45];
thetaY = [0.5 0.5 0.5];
Nthetas = length(thetaX);
N = 10;
Ntrials = 9; nr = 3; nc = 3;
for t=1:Nth... |
f9333c8f340973413e85bdf00b07a6c5b0b3e4e265e1a428d3684d5b17a5c845 | MATLAB | 1,521 | 38 | disp(' ');
disp('fdct_wrapping_demo_disp.m -- Displays the curvelet coefficients of an image');
disp(' ');
disp('1. The low frequency (coarse scale) coefficients are stored at');
disp(' the center of the display.')
disp(['2. The Cartesian concentric coronae show the coefficients at different']);
disp(' scales; t... |
426ec554a92f7a45ef668c6e0973917cb650b50559100a6cf5f810c6c95eb1cf | MATLAB | 1,522 | 42 | function rois = afxConn(func,masks,rpFile,denoisingOptions,rois,firstlevelDir,conditionName,subjectName,analyses)
% output directory
outDir = fullfile('results',firstlevelDir,'firstlevel',['cond_' conditionName]);
% load functional data (smoothed/unsmoothed)
if denoisingOptions.unsmoothed
... |
7c4fdde82ab1a0e686b52a73348967834a7038548ce6e321ef7523cd9ace2f3e | MATLAB | 1,522 | 44 | function spm_save_thr_SPM(SPM, con, FWE, p, k, fname)
% _
% Save Thresholded Statistical Parametric Map
% FORMAT spm_save_thr_SPM(SPM, con, FWE, p, k)
% SPM - a structure specifying an estimated GLM
% con - an integer indexing the contrast to be queried
% FWE - a logical indicating family-wise error c... |
801bf1e94a8efc0d8d43c0c1f32012ec1219e8c3fcc7e7de4e939e13f4e67525 | MATLAB | 1,522 | 42 | function varargout = rowFcn(fcn, A, varargin)
% Description: apply fcn to each row of matrix (based on cellfun)
% Notice:
% Inputs can be all data type valid for mat2cell()
%
% Input:
% fcn: function handle, function to apply to each row
% A: a 2-D matrix or a vector
... |
a5be1c8cfac3d7711e5e6e5bd5d5d4e7b943b4d3313b8e5c157a3c8476b8565f | MATLAB | 1,522 | 53 | % Clustering demo.
%
% Used to test different clustering algorithms on 2D and 3D mixture of
% gaussian data. Alter demo by edititing this file.
%
% USAGE
% demoCluster
%
% INPUTS
%
% OUTPUTS
%
% EXAMPLE
% demoCluster
%
% See also KMEANS2, MEANSHIFT
%
% Piotr's Computer Vision Matlab Toolbox Version 2.0
% Copyrig... |
c6a02b7c8ef82786b346d75d7935e3af69df93fcb71d95c6575819c4b95f2a35 | MATLAB | 1,522 | 43 | function [RF_weight, p_values] = statistical_test_by_stack_v10(Dnum, data_compressed, total_ROI, stimuli_start_time, dataset)
load(['data_' dataset '.mat'])
replicates = 10;
time_point = 2*1000*2;
positions = 38;
color = 1;
trials = replicates*positions*color;
RF_weight = zeros(positions, total_ROI);
p_values = zer... |
df203504a1bec979606ebd12bedd2100947a00a17e49e6ff43c9edb5e9b2e865 | MATLAB | 1,522 | 54 | % ReorderRegions.m
% Sarah West
% 1/31/22
% Starting with the LocaNMF map you want, reeorders regions into a logical
% order based on ant-post location of subdivided atlas.
function [] = ReorderRegions(parameters)
% Load subdivided basline atlas.
load(parameters.dir_subdivided_atlas);
% Grab list of ... |
3509a648f1a1b993aef6498f16cccfcc6ab8b825fee14ca81257e5e2a747f55a | MATLAB | 1,523 | 74 | function [res,info] = mydir(dirname,varargin)
iscond = nargin > 1;
if iscond,
[name,daterange,isdir,recursive,maxdepth] = myparse(varargin,'name','','daterange',[],'isdir',[],'recursive',false,'maxdepth',inf);
end
[p,f] = myfileparts(dirname);
if ~any(f == '*'),
p = fullfile(p,f);
end
s = dir(dirname);
res = {};
... |
ba61f0f50be330d7497c19c65165c02a9b7dfff7aa39a503e5aed2e5d4a9e809 | MATLAB | 1,523 | 48 | function ind_regions = GetIndRegions(ele,p)
% Assuming all the elements in ele are sharing one material ID (i.e. they
% all belong to a certain region/material) and 'ele' defines only manifold
% surfaces, this routine returns individual
% closed surfaces/loops that constitute the entire 'ele'
% This routine assumes tha... |
c8db1d5a63fff0f2d43105a8c228e28b1a4cfd0e9c8fa7e987025599dec2455e | MATLAB | 1,523 | 52 | function out = logregPostSummary(model, varargin)
% Return summaries of the posterior distribution of the regression weights
% You must call logregFitBayes first
% out is a structure containing
% what % posterior mean
% stderr % posterior standard deviation
% credint(i,1:2) % 95% credible interval
%
% If you set dis... |
018f1a7697e4384b7afbee6b0f0060f3ad6becfbcf059ddb9f77d26ba9297ffa | MATLAB | 1,524 | 77 | %load data: contact lead author
%%
figure;
subplot(121)
hold on
xx1 = overlapPerc{1,1} * 100;
xx2 = overlapPerc{1,2} * 100;
a=xx1';
b=xx2';
c={};
c{1}='AVR';%common
c{2}='VVR';%unique
color=[1 0 1;0 1 0];
% color=repmat(color,2,1);%all use the same color
%data
All=[];
for n=1:size(a,2);
All=[A... |
8223ddf5de4f174f1eacbb39764590544e59fd01f236370350268afeb1251f9c | MATLAB | 1,524 | 36 | function [trl, event] = ft_trialfun_edf(cfg)
% FT_TRIALFUN_EDF is an example trial function. It searches for events
% of type "up" in an analog data channel, as indentified by thresholding.
% This threshold can be a hard threshold, i.e. a numeric, or flexibly defined
% by an executable string (e.g., calculating the ... |
3f80d7098edd7536200a776815884ad2be4e056452b0aa222808753ffb453aeb | MATLAB | 1,525 | 63 | function [model, yhat, loglikHist] = linregCensoredFitEm(X, y, censored, varargin)
%% Fit a censored model by EM
% X: N*D matrix
% y: N*1 vector
% censored(i) = true if censored
%
% yhat(i) = E[z(i)] computed during EM
%PMTKauthor Hannes Bretschneider
%PMTKmodified Matt Dunham
%%
% This file is from pmtk3.googlecode... |
e823d4ca9b77401ebb30ba758a51c4a3ff4bf7473dd6d0d465f5774bcc1400f4 | MATLAB | 1,525 | 43 | function stats = applyStatsfun(problem, x, storedb, key, options, stats)
% Apply the statsfun function to a stats structure (for solvers).
%
% function stats = applyStatsfun(problem, x, storedb, key, options, stats)
%
% Applies the options.statsfun user supplied function (if it was provided)
% to the stats struct... |
031eed143bb5c81fd8533f27c7dd52ce4ecec9f9476929d5100fd63672cdcfde | MATLAB | 1,526 | 58 | function C = and(A,B)
%AND Logical AND (&) 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... |
97ae7928ea925d0b2f24fbd44b77e147c3117ed04dfdeefbc96fe59c6a84a01b | MATLAB | 1,526 | 51 | %% Fit a rbf kernelized logistic regression model
% We follow the same train/test split as linearKernelDemo
% so that results are comparable
% This file is from pmtk3.googlecode.com
%loadData('crabs');
loadData('fglass'); % 6 classes, X is 214*9
X = [Xtrain; Xtest];
y = canonizeLabels([ytrain; ytest]); % class 4 is... |
b230179aaabf729e4a0c546deae369b576eb8b9c7aa3d52f97bc9303b7146aad | MATLAB | 1,526 | 45 | function debugMsg(level, msg)
% Set the debugging level
%
% debugMsg(level, msg)
%
% level 1: function names
% level 2: function details
% level 3: map call
% msg: string containing debugging message
%---------------------------------------------------------------------
% ... |
b65a42bb2d975fe29aba964611615d752fe48e872bfe8f687b701f2c1d7c93c2 | MATLAB | 1,526 | 34 | function h_doubleClickLoadQCaMImg3
UserData = get(gco,'UserData');
t0 = clock;
if ~isfield(UserData,'timeLastClick') || ~(etime(t0,UserData.timeLastClick) < 0.4)
% disp(etime(t0,UserData.timeLastClick))
UserData.timeLastClick = t0;
set(gco,'UserData',UserData);
return;
else
UserData.timeL... |
cbf4118d3c2b11938707ac172141e560ab38535ebdb010770960534046304e3c | MATLAB | 1,526 | 47 | function d = check(f, X, e, P1, P2, P3, P4, P5);
% checkgrad checks the derivatives in a function, by comparing them to finite
% differences approximations. The partial derivatives and the approximation
% are printed and the norm of the diffrence divided by the norm of the sum is
% returned as an indication of accurac... |
3bfad084e7e679d09b565fa71d23856922fb4eadc66cb4b561ef8f4271d74fb1 | MATLAB | 1,527 | 59 | function j = CBIG_MFMem_rfMRI_diff_P1(func,para,houtput,num)
%------------------------------------------------------------------------
% j = CBIG_mfm_rfMRI_diff_P1(func,para,houtput,num)
%
% Function for Newton-forwards first order derivative approximation
%
% f(x0+h)-f(x0)
% diff(f(x0) = ... |
b07faf6c6d551a574e436bae5f2afae19388347a8a647bd35582488f3bdc11c8 | MATLAB | 1,527 | 40 | %% Getting individual connectivity values
subj1 = {'POGO_11' 'POGO_13' 'POGO_23' 'POGO_25' 'POGO_29' 'POGO_31' 'POGO_32' 'POGO_34' 'ST02' 'ST03' ...
'ST05' 'ST06' 'ST08' 'ST14' 'ST20' 'ST27' 'ST36' 'ST45' ...
'ST47' 'ST48' 'ST49' 'ST50' 'ST51' 'ST56'};
subj2 = {'H_02_48' 'H_03_49' 'H_05_50' 'ST10' 'ST12... |
dc9dcab4fb1e7ea446bceccd561e932d22da052525c2c818a54ff47d1d1e3afe | MATLAB | 1,527 | 58 |
% Computation of the errors:
fc = param(1:2);
cc = param(3:4);
alpha_c = param(5);
kc = param(6:10);
e_cam = [];
for kk = 1:n_ima,
omckk = param(11+(kk-1)*6:11+(kk-1)*6+2);
Tckk = param(11+(kk-1)*6+3:11+(kk-1)*6+3+2);
eval(['Xkk = X_' num2str(kk) ';']);
eval(['xkk = x_' num2str(kk) ';']);
ekk... |
dfe0d70eb32b6be96329a0c56ca57761a15d8eb9768ecc2e3a1fafb3cd951508 | MATLAB | 1,527 | 80 | % _ _
% ___ _ __ __ _| |__ ___ ___ _ __| |_
% / __| '__/ _` | '_ \/ __|/ _ \| '__| __|
% | (__| | | (_| | |_) \__ \ (_) | | | |_
% \___|_| \__,_|_.__/|___/\___/|_| \__|
%
% shows all sorted spikes in all channels
function showSpikes(self, channels)
if nargin == 1
c... |
74e53b7b10637335a22ecb558d95b0840321886bf145b35112443b00aad8a3b5 | MATLAB | 1,529 | 37 | function flag=istfr1(method);
% flag=istfr1(method) returns true is method is a
% time frequency representation of type 1 (positive and negative frequencies).
% See also istfr2, istfraff.
% F. Auger, may 98
% Copyright (c) CNRS - France 1998.
%
% This program is free software; you can redistribute it and/or modify
%... |
af3e6a29f378914bde4be6a7fc6bcb31a5c1ca991bfd5d774ef712c529d44514 | MATLAB | 1,529 | 51 | function systemcommand = GetSystemCommand(command_name)
% systemcommand = GetSystemCommand(command_name)
% Determines the platform that matlab is running and calls the appropriate
% executable file using following convention:
% command_name-mac.exe For Mac
% command_name-linux.exe For Linux
% command_name.exe For Win... |
fc5fe942804a0c8460b7c96f543ec166910fa26d32c89f268a5cc28d74c4d20a | MATLAB | 1,529 | 61 | function [ img_3d ] = volume_filtering( img_3d, take_maximal_volume)
% 3D Volume filtering operations
parameters;
% filtered 3d mask
% imshow(cmp_z_proj(img_3d));
% find connected volumes
CC = bwconncomp(img_3d);
S = regionprops(CC,'Centroid', 'Area', 'PixelIdxList');
% center_xyz = floo... |
13325b55a165fcb8f8754aacd18951aaf5c8d0ede85c937354aadab91356f755 | MATLAB | 1,531 | 28 | function rgb = cdat2rgb(cdat, cmap, clim, highlight)
% This funcxtion changes the color of pixels to white, regardless of colormap, without using opengl
% It does by converting by:
% 1) convert the to-be-plotted data to their respective rgb color values (determined by colormap)
% 2) convert these rgb color values to h... |
425fe8d1386592d6dc382b111bc982852112099d03e73a5542548e5403cea3b0 | MATLAB | 1,531 | 36 | function PlotFigure1_S1(vars,varNames)
% plot sRT vs velres, incentive effects
% then separated by drug condition
if nargin==0
load('Figure 1 - Source Data 1.mat', 'vars', 'varNames')
% vars is struct with fields of [nPP, nConds, nDrug] trial means
end
[nPP, nConds, nDrugs] = size(vars... |
453a0814e1e197047d1537f7f61e0f4a1c17721266fa0099bb1231315ebb2cd8 | MATLAB | 1,531 | 53 | % Demonstrate LDA/QDA on 2d 3class iris data
% From http://www.mathworks.com/products/statistics/demos.html?file=/products/demos/shipping/stats/classdemo.html
requireStatsToolbox();
% "Resubstitution error" is the training set error
load fisheriris
if 0
figure
gscatter(meas(:,1), meas(:,2), species,'r... |
553978e7c3a471938067e67d8c554d7203b7dfacba1c742cf750f6fa1ef578bd | MATLAB | 1,531 | 55 | %% Linear/ quadratic discriminant analysis for Height Weight data
%
%%
% This file is from pmtk3.googlecode.com
clear all
rawdata = loadData('heightWeight');
data.Y = rawdata(:,1); % 1=male, 2=female
data.X = [rawdata(:,2) rawdata(:,3)]; % height, weight
maleNdx = find(data.Y == 1);
femaleNdx = find(data.Y == 2);
cla... |
17707b15f3f1d92ded5b7f78a07276c44bea7efe91db91b4a13cce474e5a1026 | MATLAB | 1,532 | 53 | function W = AngularVelocity(X,smooth)
%AngularVelocity - Compute instantaneous angular velocity.
%
% Compute angular velocity for a time-varying vector X. This is computed as
% the vector product of X and its derivative DX: W(t) = X(t) ^ DX(t)
%
% USAGE
%
% omega = AngularVelocity(X,smooth)
%
% X ... |
3e31bff2e258883c17e3193848d06f486e472624d866b298b1bc4d009c37ab05 | MATLAB | 1,532 | 54 | function mask = maskSphere( d, r, show )
% Creates an 'image' of a n-dimensional hypersphere.
%
% Useful for testing visualization procedures.
%
% Create a d-dimensional matrix mask of dimensions [s x s x s x ... x s]
% where s=2r+1. Each element mask(x1,x2...,xd) is 1 if (x1,...xd) falls
% inside the centered hypersp... |
956c1ae737326fb01b30947e1a26b7e73984cecd10a6abeb356aaef3dd9bbe1e | MATLAB | 1,532 | 51 | function h_autoSetAxesRatio3(handles)
global h_img3
[currentInd, handles, currentStruct, currentStructName] = h_getCurrendInd3(handles);
header = currentStruct.info;
dispAxes = get(handles.viewingAxisControl,'Value');
if strcmpi(header.fileType,'scanimage') && exist('calculateFieldOfView', 'file')
try... |
13e237ea84f176eb71c2c36a9e62c96c84ca6f793dfc354f6ef6fd9d2f65ec73 | MATLAB | 1,533 | 25 | function [optScanner,optSample,optSSFP,optSE] = ParameterOptionsSNROscillating()
%%
%Scanner properties
optScanner.MaxReadout=inf; % Maximum Readout Duration (ms)
optScanner.GMax=1000; % Maximum Gradient Stength (mT/m)
optScanner.gamma=2*pi*42.58*10^6; % G... |
419bae54d8ea66820ca6586dd7a738f47564d153180e672a467fe4f3b869ada6 | MATLAB | 1,534 | 61 | function [k,g,s,time,Ck] = vdSpiralDesign(ST, Nitlv, res, fov,radius , Gmax, Smax, T, interpType)
% [k,g,s,time] = vdSpiralDesign(Nitlv, res, fov,radius , Gmax, Smax, T, interpType)
%
% This function designs a variable density spiral
%
% Input:
% ST - type of solution (0 for rotationally variant, 1 for
% ... |
96539225ac393e21d6650b01984a548f7f069e59ea5f83c6ceda0c92d428e3d8 | MATLAB | 1,534 | 61 | function [med,mad] = compute_bg_med(readframe,nframes,varargin)
[bgstartframe,bgendframe,bgnframes,roi,maxmem,verbose] = ...
myparse(varargin,'bgstartframe',1,'bgendframe',nframes,...
'bgnframes',200,'roi',[],...
'maxmem',2^20*50,'verbose',1);
if isempty(roi),
im = readframe(bgstartframe... |
b9c76f0307a91b0852e9e543a620c8a14670293e1fadda6e6e361f5b778c7628 | MATLAB | 1,534 | 41 | function [lat,pol]=sph2hor(azi,ele)
%SPH2HOR transform spherical to horizontal-polar coordinates.
% [lat,pol]=sph2hor(azi,ele)
%
% Input:
% azi ... azimuth (in degrees)
% ele ... elevation (in degrees)
%
% Output:
% lat ... lateral angle (-90 <= lat <= 90)
% pol ... polar angle (-90 <= ... |
dde154a1cd0a7f710c5eb3353def64cfe8c2a658454c5127dcfa7192bb2cd094 | MATLAB | 1,534 | 73 | function error = wlProc_calcWaveErrorRelative( ...
bigwave, bigstart, subwave, substart)
% function error = wlProc_calcWaveErrorRelative( ...
% bigwave, bigstart, subwave, substart)
%
% This function calculates the "error" between an event waveform and a
% reference waveform.
% The "Relative" version computes this... |
e4b2cc2bc7bba9c7398c127fc78a0d13cdad867245ffe92612b1b98d5720a68b | MATLAB | 1,534 | 52 | % Author: Birgit Nierula
% nierula@cbs.mpg.de
function eeg_prepro_loop7_2_allBlocks(subject, sasica_comps)
%% loop 7: save ICA components
% define variables
subject_id = sprintf('sub-%03i', subject);
analysis_path = [getenv('ANADIR') subject_id '/eeg/prepro/'];
save_path = [getenv('EEGDIR') subject_id '/'];
% sav... |
385a235552d3724793f04d696a3a9c04e2cbbf9e3b4dd0af33b148e69c093d1a | MATLAB | 1,535 | 45 | % Author: Birgit Nierula
% nierula@cbs.mpg.de
function eeg_prepro_loop3(subject, condition, srmr_nr)
%% loop 3: remove identified bad channels and interpolate them
% set important variables
subject_id = sprintf('sub-%03i', subject);
analysis_path = [getenv('ANADIR') subject_id '/eeg/prepro/'];
% define stimulation... |
5b70b33b1ece8393a6f895b619d9c7bc379f3a1e480147a9e01a42655100a3bf | MATLAB | 1,535 | 62 | function locs_new=adjust_elecs(names,locs);
[nchan ndum]=size(locs);
elec_suf=zeros(nchan,1);
locs_new=locs;
for i=1:nchan;
nloc=names{i};
n=length(nloc);
if strcmp(nloc(n),'z');
locs_new(i,1)=0;
%disp(nloc)
%[locs(i,:),locs_new(i,:)]
else
kont=0;
while kont==0
... |
37fe26ecd56dd95a31ab0b86c601bc3e232a193a132bc806c5e3e8102928be10 | MATLAB | 1,537 | 61 | function dy = CBIG_MFMem_rfMRI_mfm_ode1(y,parameter,SC)
%-----------------------------------------------------------------------------
% dy = CBIG_MFMem_rfMRI_MFMem_ode1(y,parameter,SC)
%
% Function for dynamical mean field model diffiential equation 1st order
%
% Input:
% - y: current neural state
% -... |
48dfcc047ceba48717e8d17b92eb0835f7e4a6b09430a7512f601674efa4ccff | MATLAB | 1,537 | 49 | function t = subsasgn(t,s,b)
%SUBSASGN Subscripted assignement for ktensor.
%
% See also KTENSOR.
%
%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... |
7e9431de4022b1c2f3d426b0b2662c4f1f1f474eef64250fa602f14179e4de97 | MATLAB | 1,537 | 52 | %% convolve joint sdo
% given a (recovered) joint matrix/distribution, appropriately convolve the matrix
% N_STEPS.
% jsdo is first scaled to px0 (colsum), and 1's are added to the matrix
% diagonal to ensure the matrix functions as a transition matrix.
% It is multipled N_STEP times, and then row elements are
%... |
d37a0d9efa70241b715c7fa62cb31b5ec3e67ffba6ccd345716dc618aeb430fc | MATLAB | 1,537 | 40 | % EQUATION3 computes the raw JPSTH of spike_1 and spike_2
%
% to compile enter the following command at the MATLAB Command Window
% >> mex('equation3.c')
%
% MATLAB equivalent to equation3.c listed below
% equation3.m
%
% Copyright 2008 Vanderbilt University. All rights reserved.
% John Haitas, Jeremiah Cohen, and J... |
e40cad77889b378d956eb8f2d7cca64f851a111db2b360bb7869030bc591ec27 | MATLAB | 1,537 | 76 | % [intpx,extpx] = ellipseintextpixels(im,ells,r0,r1,r2)
function [intpx,extpx] = ellipseintextpixels(im,ells,r0,r1,r2,debug)
if ~exist('debug','var'),
debug = false;
end
[nr,nc,ncolors] = size(im);
bw = false(nr,nc);
if r0 < 0,
se0 = strel('disk',-r0);
end
if r1 > 0,
se1 = strel('disk',r1);
end
if r2 > 0,
se... |
3c6d8e3248caa66ba07ec24b16ff47f084d94294675968cb7c513a0cb8129096 | MATLAB | 1,538 | 54 | function projectfun = get_project_fcn(caldata)
% [XYZ,uv_re,err] = reconstructfun(uv)
% reconstructfun(uv) takes input uv which is [2 x nviews x n]
% and produces outputs:
% XYZ: [3 x n] 3-d reconstructed points
% uv_re: [2 x nviews x n] reprojections
% err: [1 x n] reprojection error per view
if isa(caldata,'CalRigS... |
56f4e5478dc6dc47c1246e36c5d526a1a2f5d21fc9d236e8dc889d6b031639aa | MATLAB | 1,538 | 64 | %% warn_if
%
% Test a condition and warn if true
%
% <matlab:open('warn_if.m') code>
%
%% Syntax
%
% wcond = warn_if(wcond,msgstr,warnfunc)
%
%% Arguments
%
% _input_
%
% wcond condition to test
% msgstr string specifying warning message
% warnfunc string specifying which function issued the ... |
0d9af6b5fba2343cabec072d07dae267dc52e719352a8ef259972daacf892078 | MATLAB | 1,539 | 41 | function [wsM] = WinMat(M, win, step)
% WinMat(M, win, step); uses data from signal matrix 'M'
% to construct a 3D matrix wsM using 'win' succesive rows
% The sorting procedes on the columns, by taking the first 'win' rows.
% Then, separated by 'step', the following 'win' rows and so on.
%
% Ej: M =[ 1 4
%... |
725057e6094fef4eff4d90c8b2a4b3394374f439ddee36352754bc8ac4b4ff1e | MATLAB | 1,539 | 49 | function probs = Cov_comp(X,tau,isjoint)
%: Compute covarance matrices from time series data X
%
%-----------------------------------------------------------------------
% INPUTS:
% X: time series data in the form (units X time)
% tau: time lag between past and present states
% isjoint: wh... |
97ed2cf45e922610269de50c0574f4da5ee0a2451aae30e32cb7d622746708cc | MATLAB | 1,539 | 50 | % RSKELF_CHOLMV Multiply using generalized Cholesky factor from recursive
% skeletonization factorization.
%
% Typical complexity: about half that of RSKELF_MV.
%
% Y = RSKELF_CHOLMV(F,X) produces the matrix Y by applying the generalized
% Cholesky factor C of the factored matrix F = C*C' to th... |
9a1b20ef22535a741800790018e8d5ae1a2ac473fec44bddb7a215ada00c3678 | MATLAB | 1,539 | 79 | function jumpToOutlier(self,direction)
arguments
self (1,1) crabsort
direction char
end
if self.verbosity > 9
disp(mfilename)
end
% find outliers
if isempty(self.channel_to_work_with)
return
else
channel = self.channel_to_work_with;
end
[spiketimes, labels] = self.getLabelledSpikes;
if isempty(spiketimes)
sel... |
dd44d7b3ed52009bf13a3442ef8f9969162a5d237f729f44c68a871adb04e62f | MATLAB | 1,539 | 25 | %% 非线性（动力学）特征：基于时域的熵 | nonlinear features: time-domain-based entropy
%% Renyi Entropy
% X: single channel EEG signal (either a row vector or a column vector)
% See also:
% feat_ShannonEntropy, feat_LogEnergyEntropy, feat_TsallisEntropy, feat_MeanEnergy, feat_MeanTeagerEnergy
%% Reference
% [1] Şen, B., Pe... |
41a9a91ea0785527a743f61d68a0357f0a409223da6e1d995ac7ee9534b95e83 | MATLAB | 1,540 | 61 | function [DCM] = VBA_spm_sdcm_estimate(P,stochastic,augment,DisplayWin,confounds)
% Estimate parameters of a stochastic DCM for fMRI data
% FORMAT [DCM] = spm_sdcm_estimate(DCM,stochastic,augment)
%
% DCM - the DCM or its filename
% stochastic - flag for s/d DCM
% augment - structure for input basis ... |
95314018741456e5961abc01f05415816a302fdac6af47ae33e2eb20d5c65105 | MATLAB | 1,540 | 87 | function [dataKT] = meg_subjectNames_RD2KT(dataRD)
% function [dataKT] = subjectNames_RD2KT(dataRD,subjectIdx)
% Inputs:
% - dataRD: data matrix organized in RD subject order
% Rearrange data matrix from RD subject odering to KT subject ordering
% dataRD must be 1 x 10?
% Subject oder RD
% 1. R0817
% 2. R1187
%... |
9f50f37c39f1d9efc48e30264fe0ab0a302c1b78ed38364605dfe496367c263b | MATLAB | 1,540 | 53 | function res = innerprod(X,Y)
%INNERPROD Efficient inner product with a ktensor.
%
% R = INNERPROD(X,Y) efficiently computes the inner product between
% two tensors X and Y. If Y is a ktensor, the inner product is
% computed using inner products of the factor matrices, X{i}'*Y{i}.
% Otherwise, the inner produc... |
c9a200313b2cc6fa460ce845dc899be061f03b8a083ad93c0947a4f037f4101d | MATLAB | 1,540 | 45 | function [x,mx,sx] = nanstandardise(x,dim)
% X = NANSTANDARDISE(X, DIM) computes the zscore of a matrix along dimension
% dim, taking nans into account
% has similar functionality as the stats-toolbox's zscore function
% Copyright (C) 2010, Jan-Mathijs Schoffelen
%
% This file is part of FieldTrip, see http://www.ru... |
ecfc66be64ae2345d1b1ec026364088319bd77b7cf700169ca4372236b0f816b | MATLAB | 1,540 | 68 | % [x,npadl,npadu] = padset(x,padv,l1,u1,l2,u2,...)
function [x,npadl,npadu] = padset(x,padv,varargin)
% parse arguments
usagestring = 'Usage: padset(x,padv,l1,u1,l2,u2,...)';
nd1 = ndims(x);
if mod(numel(varargin),2) ~= 0 || isempty(varargin),
error(usagestring);
end
isones = cellfun(@(x) x == 1, varargin(1:2:end-1)... |
0ad74cd9e64ca90c183c17ba8a8e75a1963f568a55556bdc4a75355e30162697 | MATLAB | 1,541 | 62 | function [numt0marker] = plotTriggers( dataset, t0marker , varargin )
%PLOTTRIGGERS Plot all the triggers in the file over time
p = inputParser;
addParameter(p, 'showFigure', false);
addParameter(p, 'savePath', []);
addParameter(p, 'xUnits', 'samples', @(x) any(strcmp(x, {'samples', 'sec', 'msec'})));
parse(p, varargi... |
16c31920ea4ec459a5f8f55caaaaa7c4a9c3de60f064ad2e99dd15cfded8f9c7 | MATLAB | 1,541 | 43 | basepath = pwd
dat_files = dir(fullfile(basepath,'**','*amplifier.dat'));
recordingnames = {dat_files.folder}
names2sort = cellfun(@(X) str2num(X(end-5:end)),recordingnames,'UniformOutput',false);
names2sort = cell2mat(names2sort);
[~,I] = sort(names2sort);
recordingnames = recordingnames(I);
dat_files = dat_files(I)... |
6c623e805304bc4bf56ed4a25c8f35ee646ca83b7a89e9ed3ca6cab5ad53fb16 | MATLAB | 1,541 | 55 | % This program is free software; you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation; either version 2 of the License, or
% (at your option) any later version.
%
% This program is distributed in the hope that it will be useful,... |
891fee86dda103eaaf07b9446cd8394d291b8e11448521e9a8ac7850471235ad | MATLAB | 1,541 | 93 | function p = mahdist(x, m, S, V)
% mahalanobis distance from x to m by S
% mahdist([x(:)';y(:)';z(:)'],mu,[],S)
% See NORMPDF for argument description.
% [d, n] = size(x)
% [d, 1] = size(m)
% S = []
% V = cov
[d, n] = size(x);
if nargin == 1
dx = x;
elseif isempty(m)
dx = x;
else
% m specified
sz = size(m);
... |
c5079f86915b2c92d334013ee376ea563b10d3645171b22cdd1fb87ac5a761e3 | MATLAB | 1,541 | 53 | function [sector_endpoints, num_sectors] = generate_sector_points_3(sector_vector, num_sector_weights, min_sector_spacing, have_min_sector_spacing)
num_sectors = datasample(sector_vector, 1, 'Replace', true, 'Weights', num_sector_weights);
sector_endpoints = zeros(2*num_sectors, 1);
num_endpoints = length(sector_endpo... |
1612b439ff844fb57277fb37f8d142720be8fee31d575c86e0e5ac9a4cab7c59 | MATLAB | 1,542 | 64 | function logp = studentLogprob(arg1, arg2, arg3, arg4)
% Multivariate student T distribution, log pdf
%
% - model is a structure containing fields mu, Sigma, dof
% - logp(i) = logp(X(i, :) | model)
%
% For the scalar case, Sigma is the variance not the standard deviation
%
% logp = studentLogprob(model, X); OR logp =... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.