sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
dcd9bd454b4dda1c43afaa3b3ee9ca3e1ea19e35cfbdd94e12bd874b8606e6a4 | MATLAB | 4,278 | 141 | function [F] = VBA_FreeEnergy(posterior,suffStat,options)
% computes free energy of the sDCM generative model
% function [F] = VBA_FreeEnergy(posterior,suffStat,options)
% This function evaluates the free energy associated with the nonlinear
% state-space model inverted by the main inversion routine
% VBA_NLStateSpaceM... |
7b862c4947771618f30001ee08ed7484529287d79f64550cc38c8e7e0008c559 | MATLAB | 4,281 | 92 | function CBIG_AuthorTopic_RunExample
% CBIG_AuthorTopic_RunExample
%
% Example of performing coordinate-based meta-analysis with the author-topic model
% to discover cognitive components of self-generated thought
% The inference was performed with the following hyperparameters
% - K = 2:3 - number of cogni... |
0e4920f90ac5f4f3ee3b962eaf00c6d256c3afe7a57e2b5b94570cc591172f76 | MATLAB | 4,282 | 89 | function parallel_calculate_FIR_PPIs_no_centering(stat_path,exp_folder,N,N_ROIs)
% ========================================================================
% Ruslan Masharipov, July, 2024
% email: ruslan.s.masharipov@gmail.com
% ========================================================================
tic
for subji = ... |
2d54ff82ff864b789932d9737d16c83c7a3b84739161fce0764a394f5bfd4f56 | MATLAB | 4,282 | 115 | %% Plot Figure 4 a) and b)
function figureOut = PlotFigure4ab(condData, BhatArr, figNr)
% Plot the evolution of Bhat for placebo (low cue) and nocebo (high cue)
% trials across conditioning (suplot 1), and the expected pain for each
% trial (subplot 2)
% ==== Input ===
% conditioning data: condData = 1xnParticipant s... |
18796d0e1c4735baa17a1f347768c8b6442c7487cd20c94ba5980a77619b7bfb | MATLAB | 4,283 | 118 | function [basis,gradbasis]=legs(x,dir,n)
% usage: [basis,gradbasis]=legs(x,dir,n)
%
% returns the values and directional derivatives of (n+1)^2
% spherical harmonics at locations given in x and, for the
% gradients, for (in general non-normalized) directions given in dir.
%
% input: x set of N locations giv... |
9bc9b4b6772547eec5d65deb7ca63b716d879499d1e8f5122f62ab43e9d2ad89 | MATLAB | 4,283 | 100 | % MATLAB code provided by Seyed Mohammad Ali Rahmati
% Affiliation: Biomechanics and Motor Control Lab, Department of Biological Sciences, Georgia Institute of Technology, Atlanta, GA.
% Description:
% This script computes a sensitivity analysis of the mean maximum muscle-tendon (MT) moment to changes in
% muscle para... |
42f2b11b8d0330e546cab795e99c8f60c96b22f6458d1201ceec201d8f0651ab | MATLAB | 4,285 | 102 | function [name, tissue, cond, enclosingTissueIdx] = tissue_index_read(index_name, mesh_path)
% This function reads a tissue index file, and extracts the name, conductivity,
% and enclosing tissue of each tissue listed in the tissue index file.
% Copyright WAW/SNM 2019-2020
%Attempt to open index file
in... |
31bb7d686a497f5c5f70ef459e599b429600242705f1614f5a3064884dc84b48 | MATLAB | 4,288 | 99 | % MATLAB code provided by Seyed Mohammad Ali Rahmati
% Affiliation: Biomechanics and Motor Control Lab, Department of Biological Sciences, Georgia Institute of Technology, Atlanta, GA.
% Description:
% This script computes a sensitivity analysis of the mean maximum muscle-tendon (MT) moment to changes in
% muscle para... |
77fb13620a6c3d3d75b0d74eca9f70445a6e5ae9d2c019715810b49656df7160 | MATLAB | 4,288 | 94 | % Author: Birgit Nierula
% nierula@cbs.mpg.de
function eeg_prepro_loop4(subject, condition, srmr_nr)
%% loop 4: further automatic processing: re-reference, filter, artifact rejection
subject_id = sprintf('sub-%03i', subject);
analysis_path = [getenv('ANADIR') subject_id '/eeg/prepro/'];
% define stimulation condit... |
e2921aa5395cd58af236ea18e6cb816017e238b503a70a31f6c46e4f3ac9a7e5 | MATLAB | 4,288 | 105 | function varargout = DPABI_Analysis(varargin)
% DPABI_ANALYSIS MATLAB code for DPABI_Analysis.fig
% DPABI_ANALYSIS, by itself, creates a new DPABI_ANALYSIS or raises the existing
% singleton*.
%
% H = DPABI_ANALYSIS returns the handle to a new DPABI_ANALYSIS or the handle to
% the existing singleton... |
ed698415591b6ea6ac5dce806f2237f59185bd09b5320ca26029600f6f45d03c | MATLAB | 4,288 | 173 | function cfg = pregunta_lan(cfg,campos, opciones,label)
% Para conficuraciones no explicitadas
% v.0.1.3
%
% Pablo Billeke
%
%
% 26.08.2010
% 04.05.2010
% 26.11.2009
% function cfg = gui_cfg(cfg,text)
%
%
%
% end
LAN = cfg;
if nargin < 4
label = [' '];
else
label = [ ' para ' label ];
end
%----... |
23efa4c20cb896e9606616022bd0a79eeb809bb94a97521ba3c5a2f457321562 | MATLAB | 4,290 | 134 | function [] = plotRaster(spikenums,rasterOptions);
%% >>> OPERATION >>>
% Plots spike raster for a 2D array in which rows are cells and columns
% are data points.
% Options: - plot time vector as x
% - highlight specific cells in red
% - highlight specific time windows (e.g. behavi... |
1d0fae757cd0b3840cf87f7e40dcd2f2e7ec2a8545166967e9aca9ffa8024880 | MATLAB | 4,291 | 82 | % GET_FIELD_FD_CPU Solves sparse system of linear equations using BiCGStab
% solver and FSAI preconditioning. Parallelized for multithreading with
% OpenMP. Uses all available CPU power.
%
% SYNTAX:
% [PHI] = GET_FIELD_FD_CPU(I_INDEX, J_INDEX, S_VALUE, QVEC)
% [PHI] = GET_FIELD_FD_CPU(I_INDEX, J_INDEX, S_VALU... |
9b81a3fe270c45cedaacef369706309877116d47a9aa92989b97fa87cb90fd53 | MATLAB | 4,291 | 138 | function [count edges mid loc] = histcn(X, varargin)
% function [count edges mid loc] = histcn(X, edge1, edge2, ..., edgeN)
%
% Purpose: compute n-dimensional histogram
%
% INPUT
% - X: is (M x N) array, represents M data points in R^N
% - edgek: are the bin vectors on dimension k, k=1...N.
% If it is a scalar ... |
8071c4b419b1202bba7d26da8770d5fa26db132d283160cde6c6eaf0833bdf6a | MATLAB | 4,292 | 213 | % crabsort.database.build
% builds a database in a xlsx sheet
%
function T = build(varargin)
try
data_loc = getpref('crabsort','data_loc');
catch
error('data_loc not set! ')
end
% get a list of all experiments in the crabsort spikes folder
spikesfolder = getpref('crabsort','store_spikes_here');
all_exps = dir(... |
3809d603a21cbba6bf80f179644f93e567d39c9cf84a6fab9334cd2da4254092 | MATLAB | 4,296 | 103 | % FT_POSTAMBLE_PROVENANCE is a helper script that reports the time and memory used by
% the calling function and that stores this information together with user name, MATLAB
% version and other provenance information in the cfg structure. This script is to be
% used together with FT_PREAMBLE_PROVENANCE, which records t... |
61e1acc7fcdcc62e8683dc3a0d1915b684c4d13c4896b1c88c7a305f7222ae45 | MATLAB | 4,296 | 138 | function [mellin,beta]=fmt(X,fmin,fmax,N);
%FMT Fast Fourier Mellin Transform.
% [MELLIN,BETA]=FMT(X,FMIN,FMAX,N) computes the Fast Mellin
% Transform of signal X.
%
% X : signal in time (Nx=length(X)).
% FMIN,FMAX : respectively lower and upper frequency bounds of
% the analyzed sign... |
61fe66cfbc67f1803a349e07bebdfd938a060cc1540dd69cd0d4b8e7d3016d78 | MATLAB | 4,297 | 150 | function [xyz_final,matrix_first_flag,matrix_second_flag, mat_IDIF_final, peaks,number_of_final_voxels]=voxels_select(mask,PET_dyn,t_IDIF_emi,number_of_final_voxels)
n_sampling = size(PET_dyn,4);
for t=1:n_sampling
curr_PET=PET_dyn(:,:,:,t);
PET2D(:,t)=curr_PET(:);
end
matrix=PET2D(find(mask),:);
%... |
fa66fac13458d186cb5590f9fbb911c6a16c5cbbb2a53688f1cc72bcdab4a462 | MATLAB | 4,299 | 182 | function [DCM] = VBA_spm_sdcm_estimate2(P)
% Estimate parameters of a stochastic DCM for fMRI data (deconv HRF)
% FORMAT [DCM] = spm_sdcm_estimate2(DCM)
%
% DCM - the DCM or its filename
%__________________________________________________________________________
% Copyright (C) 2008 Wellcome Trust Centre for Neuroi... |
255e518a5adca9607d710cc7e3c84918bbf6b935cdcc4c12407634b747739201 | MATLAB | 4,300 | 116 | classdef Set < handle_light
% Square subset of R^n
%---------------------------------------------------------------------
% license
%---------------------------------------------------------------------
% Copyright 2015 Idse Heemskerk and Sebastian Streichan
%
% This file is part of... |
3a4692c9a6e77ef3f30fde02718ae20658c9b607260e9ce0ec0fcd6543f674c1 | MATLAB | 4,300 | 120 | classdef NavigationTable < handle
% A row-selectable table that fires a callback when the user clicks a
% row. Wraps a uitable; the parent passed to the constructor should
% ultimately be rooted in a uifigure, since the modern uitable
% properties used here (SelectionType, Selection, SelectionChangedFcn)
% r... |
a4cd89b34044fc2d0890fd7d80cfc4f9aa9e1167c52fd1ee730f416e84bc4407 | MATLAB | 4,302 | 120 | % Second-kind integral equation on the unit circle, Laplace double-layer.
%
% This example solves the Dirichlet Laplace problem on the unit disk by using a
% double-layer potential, which yields a second-kind boundary integral equation.
% The integral is discretized with the trapezoidal rule; the resulting matrix is
% ... |
942412eba0770aee214b037221bb066e8036ed75e13c89f6aeecb9cc16a49d28 | MATLAB | 4,303 | 156 | % header = ufmf_read_header(filename)
function header = ufmf_read_header(filename)
MAXNMEANSCACHED = 5;
header.filename = filename;
% open the file for reading, binary, little-endian
fp = fopen( filename, 'rb' , 'ieee-le');
if ~exist(filename,'file'),
error('File %s does not exist',filename);
end
if fp < 0,
erro... |
0b0c8cd96b4d43ef80ac30c5f4f83af52bbedcc6892d8300e709d34da4184d71 | MATLAB | 4,304 | 90 | function CBIG_AuthorTopicEM_RunEMwithRandInitExample
% CBIG_AuthorTopicEM_RunEMwithRandInitExample
%
% Wrapper function to unit-test a coordinate-based meta-analysis with
% the author-topic model and expectation-maximization (EM) algorithm.
% The inference was performed with the following hard-coded hyperpara... |
27c89d60114cc2b61b43c5aa8d82ec30df4cf0c17e3eab4c31a3fc23654c46c0 | MATLAB | 4,305 | 128 | function [info] = prepare_agent(model,game,role)
% set basic params for different sorts of agents engaging in dyadic games
% function [info] = prepare_agent(model,game,role)
% info: structure containing the following fields:
% .f_p = handle of evolution function
% .g_p = handle of observation function
% .theta = ev... |
5af78292a88273725d9cd7d4d630c546020a0dbc7d34a44000d03a72a6a0cab7 | MATLAB | 4,305 | 131 | function ax = animate_trial(input_file_name,output_file_name,Tmax,show_target,show_holes,arena_bg_color,real_time,hole_check_data,fig_prop)
% input_file_name -> for example, the name of the .mat input file containing the trajectory
% output_file_name -> true, false, or the name of the output video file
% Tmax ... |
97b9120dd903f905a89adf9e55ef431957e654e8e893000e30e172f9f941626f | MATLAB | 4,305 | 162 | % This is a simplified version of 'discreteDensityModelsShootout'
% It should give the same results as 'exptKevin2'
% Stop it from being included in list of automatic demos
%PMTKinprogress
%% Data
% data.discrete is D*N where discrete(d,n) in {1..nClass(d)}
clear all
seed = 1;
dataName = 'ases4';
pcTrain = 0.5; pcT... |
77fa9bad4819657a1a972cdf6ec553621b126c4abfe6b9d164e2bc7fd12b86b8 | MATLAB | 4,306 | 161 | %%% INPUT THE IMAGE FILE NAME:
graphout = 0;
if ~exist('fc')|~exist('cc')|~exist('kc')|~exist('alpha_c'),
fprintf(1,'No intrinsic camera parameters available. Maybe, need to load Calib_Results.mat\n');
return;
end;
KK = [fc(1) alpha_c*fc(1) cc(1);0 fc(2) cc(2) ; 0 0 1];
disp('Program that undistorts a whole s... |
3359a5b90db8e6a72b858684c88cf20cadbe5e59de312add5e28473741dacea9 | MATLAB | 4,307 | 205 | function [DAT, StudyTable] = struct2canlab_dataset(data_struct)
% Take an ad hoc data structure data_struct and return a Table format
% object (StudyTable) and a canlab_dataset object DAT.
%
% - field names become variable names
% - Column vectors of numbers or text becomes Subj_Level data
% - Cell vectors containing c... |
257d68016a19adc6939e7a4aab97986d5e6d6cd8dda8a6ba18c94d736bde70f8 | MATLAB | 4,308 | 137 | %% Compare L1, L2, allSubsets, and OLS linear regression on the prostate data set
% Approximately reproduces table 3.3 and fig 3.7 on p63 of "Elements of statistical
% learning" 2nd edn
% According to http://statweb.stanford.edu/~tibs/ElemStatLearn/datasets/prostate.info.txt
% "The features must first be scaled to h... |
73c271f615a908d4a639a601ce88357b9fa762dfc01bfc8d5161bc49bacfcdd7 | MATLAB | 4,309 | 119 | function F = VBA_spm_Fcdf(x,v,w)
% Cumulative Distribution Function (CDF) of F (Fisher-Snedecor) distribution
% FORMAT F = spm_Fpdf(x,df)
% FORMAT F = spm_Fpdf(x,v,w)
%
% x - F-variate (F has range [0,Inf) )
% df - Degrees of freedom, concatenated along last dimension
% Eg. Scalar (or column vector) v & w. Then... |
9f08b65bbe601acc1e1d11742c6d0451610d2c006bd643f5b25ceddbcb9db24d | MATLAB | 4,309 | 100 | function y_ICC_Image_ReML(Rate1Dir,Rate2Dir,OutputName,MaskFile)
% function y_ICC_Image_ReML(Rate1Dir,Rate2Dir,OutputName,MaskFile)
% Calculate the Intraclass correlation coefficient for brain images.
% Note: the ICC calculation is based on Xi-Nian Zuo's LFCD_lmm0
% Use ReML Model; Zuo, X.N., Xing, X.X., 2011. Effe... |
b8ed4e0c0eecf70f054f196359543f003ab342aa5635a1f4c14f8cbb276c3bef | MATLAB | 4,310 | 81 | function y_WarpByANTs(SourceFile,OutFile,RefFile,TransformFile,Interpolation,Dimensionality,InputImageType,DefaultValue,IsFloat0,DockerName)
% FORMAT y_WarpByANTs(SourceFile,OutFile,RefFile,TransformFile,Interpolation,Dimensionality,InputImageType,DefaultValue,IsFloat0,DockerName)
% Warp a file with ANTs' antsApplyTr... |
b5497287aff987b784a338e0dbf7f9a82e34b00f72dc2d98137eead43ac4d185 | MATLAB | 4,311 | 87 | % Written by Xiuming Zhang and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
% IMPORTANT This file is specific to our PNAS paper and our computing cluster. As a result,
% you need to modify the paths at places with comment "please change"
close all; clear; clc;
cd ../lib/
%% Pre... |
04551b60cfbb76d87a96b859b2273d841c368cbb77c5cdbc8f3ca6a7cda1680c | MATLAB | 4,312 | 148 |
function [ csd ] = bz_CSD (lfp, varargin)
% [ CSD ] = bz_CSD (lfp, varargin)
% Calculates the 1D approximation of current source density (CSD) from a
% linear array of LFPs
% INPUT
% lfp a buzcode structure with fields lfp.data,
% lfp.timestamps
% ... |
6fb6f8c769e4623cc622e41f3c00b7be8e753eb10064b3052fd067b04190a04d | MATLAB | 4,313 | 169 | function [ projdata ] = fiff_read_proj(fid,node)
%
% [ projdata ] = fiff_read_proj(fid,node)
%
% Read the SSP data under a given directory node
%
%
% Author : Matti Hamalainen, MGH Martinos Center
% License : BSD 3-clause
%
%
% Revision 1.7 2006/05/16 00:39:32 msh
% Fixed error in mne_ex_read_raw: All proje... |
11848f10328cc4957d8659c2c290b33a2ba9021c378069f407698ad8052f253c | MATLAB | 4,315 | 115 | function [ha,hf,lr] = unwrapVBvolatileOTO(posterior,out)
% OTO: recovers posterior sufficient statistics from VB inversion
if isempty(posterior)
ha =[];
return
end
[n,n_t] = size(posterior.muX);
if n==5
ka = out.options.inF.lev2* VBA_sigmoid(posterior.muTheta(1), 'scale', out.options.inF.kaub);
o... |
328a5590bd0196c5efe8f92bd2d6a118fc6c02ed54e3c8622b979a8d0c8a9ea3 | MATLAB | 4,315 | 152 | function CPD = condGaussCpdCreate(mu, Sigma, varargin)
%% Create a conditional Gaussian distribution for use in a graphical model
%
% mu is a matrix of size d-by-nstates
% Sigma is of size d-by-d-by-nstates
%
% 'prior' is a Gauss-inverseWishart distribution, namely, a struct with
% fields mu, Sigma, dof, k
% Set 'prio... |
b139adc8ac4fee02fbf817924283dd0953a5d76ec7afda215ae569867386a8f0 | MATLAB | 4,315 | 145 | % meg_plotTopo
% MEG_PLOTTOPO
%
% Karen Tian
% August 2020
%% input
expt = 'TANoise';
saveFigs = 1;
figDir = '/Users/kantian/Dropbox/Data/TANoise/MEG/Group/figures/ITPCUpDown';
user = 'karen';
[sessionNames,subjectNames,ITPCsubject,ITPCsession] = meg_sessions(expt);
%% load data
% average data
avgData = nanmea... |
ec908032bd88a7d933917f8d2a1e8578e99350cac06bd6d31f0e989a7c97e27e | MATLAB | 4,316 | 113 | function dataout = ft_globalmeanfield(cfg, datain)
% FT_GLOBALMEANFIELD calculates global mean field amplitude or power of input data
%
% Use as
% [gmf] = ft_globalmeanfield(cfg, data)
%
% The data should be organised in a structure as obtained from the
% FT_TIMELOCKANALYSIS function. The configuration should be acc... |
c8c6a1ccd75f940387204fffbae01d82aea35eb1bf2ed2cee3bf6fb49574dec5 | MATLAB | 4,317 | 180 | % [param1,param2,...] = read_ann2(filename,'param1','param2',...)
%
% params:
%
% trx: trajectories
%
% version, bg_type, n_bg_std_thresh, n_bg_std_thresh_low, bg_std_min,
% bg_std_max n_bg_frames, min_nonarena, max_nonarena, arena_center_x,
% arena_center_y, arena_radius, do_set_circular_arena, bg_algorithm,
% backgro... |
3e31ad3f9d1d0ad00f80bc83f4f52f793a1df3466b03aa8062bf20bcb0f10f5b | MATLAB | 4,318 | 113 | function [dataout] = ft_globalmeanfield(cfg, datain)
% FT_GLOBALMEANFIELD calculates global mean field amplitude or power of input data
%
% Use as
% [gmf] = ft_globalmeanfield(cfg, data)
%
% The data should be organised in a structure as obtained from the
% FT_TIMELOCKANALYSIS function. The configuration should be a... |
a9569d0bc6afcb2f201abe3a3b725075aab57539d98540d7c032d16daa97e4be | MATLAB | 4,319 | 127 | function [KendallWBrain, GHeader] = y_KendallW_Image_Surf(RaterImages, MaskData, AResultFilename)
% Calculate Kendall's W for sets of images. (e.g., different raters or Test Re-Test)
% FORMAT [KendallWBrain, GHeader] = y_KendallW_Image_Surf(RaterImages, MaskData, AResultFilename)
% Input:
% RaterImages - C... |
16cb3888fa925d90d9aaebbd48710d80c503be8d44b420a4d8bfa0b8a30d1db2 | MATLAB | 4,320 | 170 | datRoot = '/Volumes/LaCie/Farries recordings/';
rat = 'IM1025';
sesList = dir([datRoot rat '/20*']);
sesList = arrayfun(@(x) x.name, sesList, 'UniformOutput', false)
iSes = 6;
sesDir = [datRoot rat filesep sesList{iSes} filesep]
load([sesDir 'behavior - RL.mat'])
rwd = TrialFilter(tsRL, 'x1', 'L');
fileDat = dir([ses... |
765ac34ad47bc095150b6e5b2921116658e7ce8b8fb4c9dd6ebc2a60b3a631a1 | MATLAB | 4,321 | 115 | function mat_rs = resizeMatrix(varargin)
%RESIZE Resize a matrix.
% DESCRIPTION:
% Resize a matrix to a given size using interp2 (2D) or interp3
% (3D).
% Use interpolation to redivide the [0,1] interval into Nx, Ny, Nz
% voxels, where 0 is the center of first voxel, and 1 is the center
% ... |
41904454d77715492c9f15710363871a61c42682c101b785d819cf96bea93798 | MATLAB | 4,323 | 103 | function h_autoMakeMovie3(handles)
global h_img3
[currentInd, handles, currentStruct, currentStructName] = h_getCurrendInd3(handles);
if isfield(currentStruct.state, 'movieContentOpt')
movieContentOpt = currentStruct.state.movieContentOpt.value;
else
movieContentOpt = get(handles.movieContentOpt, 'v... |
b7d3aa90510fb228fa700a385883d6aca484b1a3dd1c9ec8bc662715f20ba893 | MATLAB | 4,325 | 139 | function [fx,J,dfdP] = VBA_evalFun(flagFun,Xt,P,ut,options,dim,t)
% smart wrapper for evolution and observation functions
% function [fx,J,dfdP] = VBA_evalFun(flagFun,posterior,u,options,dim)
%
% This function evaluates the evolution or observation function (eof) at
% the mode of the posterior densities of hidden state... |
fb49f3165dc3b3230217a04e78ed12132867a31967a3bc640b215f0fdf4a95b8 | MATLAB | 4,326 | 110 | function [Xsol, Ssol] = generalized_eigenvalue_computation(A, B, p)
% Returns orthonormal basis of the dominant invariant p-subspace of B^-1 A.
%
% function [Xsol, Ssol] = generalized_eigenvalue_computation(A, B, p)
%
% Input: A is a real, symmetric matrix of size nxn,
% B is a symmetric positive definite ... |
e26ee8f3235b533b3bec8e532efabfa9c34e0086b0d5217a81d3128f72f707d3 | MATLAB | 4,329 | 116 | function y_ICC_Image_LMM_CallR(RateDir,OutputName,MaskFile,CovWCell, CovBCell)
% function y_ICC_Image_LMM_CallR(RateDir,OutputName,MaskFile, CovW, CovB)
% Calculate the Intraclass correlation coefficient for brain images.
% Note: the ICC values were derived by linear mixed models (LMMs) as in Zuo et al. (2013): Zuo,... |
babcf2c286bf850fcce70b3d394d2147f3130a882550f548a3e0ca481fad9158 | MATLAB | 4,330 | 82 | % Example 1
%
%
% Citation: Cannavo' F., Sensitivity analysis for volcanic source modeling quality assessment and model selection, Computers & Geosciences, Vol. 44, July 2012, Pages 52-59, ISSN 0098-3004, http://dx.doi.org/10.1016/j.cageo.2012.03.008.
clear all
home
% create a new project
pro = pro_Create();
% ad... |
6fa40219de8fa72f882c33f1034992b7b128139c7d4a840add534535ee66e0db | MATLAB | 4,331 | 154 | %% cpsd_to_var
%
% Spectral factorisation: calculate VAR parameters from cross-power spectral density
%
% <matlab:open('cpsd_to_var.m') code>
%
%% Syntax
%
% [H,SIG,iters] = cpsd_to_var(S,G0,maxiters,numtol)
%
%% Arguments
%
% See also <mvgchelp.html#4 Common variable names and data structures>.
%
% _input_
%
% ... |
bccd4c299eb3ea6e410304e2426b4949e601ed69bd1ca89461569979f09c69ee | MATLAB | 4,331 | 104 | function make_NBS_ready(paths, group_names, conn, nickname)
% To make data matrix and design matrix for NBS exercise
% modified from NBS_sam by Sonya - May 9, 2018
% modified by Liz - Sept 2018, Jan 2020
% function-ified by Julie - March 2020
% INPUT-------------------------------------------------------------------... |
f821100c13f283241e859e45ab8fe498be1d9a1e83dccbc0d75bc337a86ae03f | MATLAB | 4,332 | 153 | function [beta,R2,beta_ts,R2_ts] = CircularRegression(x,angles,slope)
%CircularRegression - Non-parametric linear-circular regression.
%
% Fit 'barber-pole' lines to the data. The model consists of three parallel lines
% y = a.x + b + k*2pi (k in {-1,0,1}). The distance of a point to the model is
% defined as the m... |
71389914ec9f955f6f934ccf9ce730cdcb8b1e8de33d3cd9df35a617449aa82e | MATLAB | 4,335 | 89 |
%General:
% To visualize e.g. a cross-spectrum or coherence in a 'head-in-head',
% plot you need some functional data (e.g. a cross-spectral matrx cs)
% and the locations of the channels. A location-variable for N channels
% is either an Nx3 matrix, if the locations are given in 3D, or a
% Nx2 matrix if they are g... |
9f1013b0584c6b7c532a23d299c1de67dcafad324687d6676975dced7b7d13f2 | MATLAB | 4,337 | 179 | %% Visualize soft thresholding behavior of different log priors
% PMTKauthor Francois Caron
% PMTKmodified Kevin Murphy
%%
% This file is from pmtk3.googlecode.com
function normalGammaThresholdPlotDemo()
%z=-10:.1:10;
z=-10:0.5:10;
x=-10.005:.05:10;
function out=generalizedStudentPenalty(w,a,b)
%out = -log(a) + lo... |
ff9a89cfeca1a5b2085e7d5fd390adcb88d9c03a62bf87191673dc7297222160 | MATLAB | 4,337 | 140 | function [param,stat]=sigm_fit(x,y,fixed_params,initial_params,plot_flag)
% Optimization of parameters of the sigmoid function
%
% Syntax:
% [param]=sigm_fit(x,y)
%
% that is the same that
% [param]=sigm_fit(x,y,[],[],[]) % no fixed_params, automatic initial_params
%
% [param... |
5062b9c85594b64a8654a3573863fe0071dd48d742f45a99d58bb0a2e4d8e7af | MATLAB | 4,338 | 104 | % Function: PLS and do bootstrape.
% Updata date: 2022.09.18
% Updata date: 2022.11.5
% Updata date: order the gene symbol!!!!2023.04.12
% Updata date: order the gene symbol!!!!2023.05.19
% Email:luolongcao@163.com
function test2 = Method_PLSbootstrap(X,Y,dim,max_dim,boot,geneSymbol,out_path,fig_name)
% X: the p... |
8a63bbac08c77d74eca9b42f39a91a227bad196c5055238a367332d96634db98 | MATLAB | 4,340 | 131 | function [wbest, hbest, normbest, dbest] = nnmf_modified(a, k, tries, options, specfx, concfx)
% NNMF Non-negative matrix factorization with fixed spectra and concentrations.
% This function attempts to decompose matrix A into W and H, minimizing the Frobenius norm.
% Arguments:
% a: non-negative N-by... |
3be27734dbc17bac543984931bd19183cd9667349f88981d56baba310e233142 | MATLAB | 4,341 | 126 | function [zest, xest, zsamples, w] = rbpfSlds(N, par, y, u, resamplingScheme)
% Rao-Blackwellised particle filtering for switching linear dynamical system
% See Doucet, Gordon, Krishnamurthy
% "Particle filers for state estimation of Jump Markov Lienar Systems", 2001.
%
% N: num samples
% par: parameters of SLDS (se be... |
1c6640ec6110db1ae434b6c0c81d50126fd2a82b32ebd11f111d3ab4507bba2c | MATLAB | 4,342 | 130 | %% Ridge and lasso regression:
% visualize effect of changing lambda on degree 14 polynomial
%
% This is a simplified version of linregPolyVsRegDemo.m
%ns = [21 50];
%for n=ns(:)'
n = 21;
setSeed(0);
[xtrain, ytrain, xtest, ytestNoisefree, ytest, sigma2] =...
polyDataMake('sampling','thibaux','n',n);
deg = 14... |
be7331bf6dacf64f52baf9eba27ea9ab12b58ee2f2c600e8e3c94287eb41a325 | MATLAB | 4,342 | 118 | function CBIG_ABCD_rest_proc_compute_motion_outlier(id,output_dir,raw_path,manufacturer,FD_th,DV_th,discard_run,discard_seg,motion_filter)
% CBIG_ABCD_proc_compute_motion_outlier(id,output_dir,raw_path,manufacturer,FD_th,DV_th,discard_run,discard_seg,motion_filter)
%
% Inputs:
% - id:
% subject id
%
% - output... |
2b08eeba29045155685b9a283eb16f58bf6b708f8c984bfb2e583d5486daed40 | MATLAB | 4,344 | 102 | % KMEANS K-means clustering.
% IDX = KMEANS(X, K) partitions the points in the N-by-P data matrix
% X into K clusters. This partition minimizes the sum, over all
% clusters, of the within-cluster sums of point-to-cluster-centroid
% distances. Rows of X correspond to points, columns correspond to
% variables. KMEANS ... |
b2ea99c9919d025790eb9b6be852fa2eb6f4f00e6394211a841b1e84e9f652f6 | MATLAB | 4,344 | 131 | function [V] = ft_write_mri(filename, dat, varargin)
% FT_WRITE_MRI exports volumetric data such as anatomical and functional
% MRI to a file.
%
% Use as
% ft_write_mri(filename, img, ...)
% where img represents the 3-D array with image values.
%
% The specified filename can already contain the filename extention, b... |
f0f76781f23fef6cee7a59f364b37ff5fe2dc8bcd003c0fac4ba7ea511d361a7 | MATLAB | 4,345 | 159 | function draw_figure3D(p,decRes)
%
% This code is for drawing figure 3ABC and S1C
% Umap analysis (umap_on_emotion_scores.ipynb) must be finished before executing this script.
%
%
%% settings
mapPath = [p.rootPath,'res/umap_on_emotion_scores/'];
% prepare label inf. for score based coloring
dpath = sprintf('%s%s/rois/... |
735b97c12d170c55b65798adf29c7a341dbd49802d6e26675a5c931faf3221f9 | MATLAB | 4,346 | 165 | function wlPlot_plotEventFreqQAmp(cfg, events, f1, f2, figtitle, filelabel)
% function wlPlot_plotEventFreqQAmp(cfg, events, f1, f2, figtitle, filelabel)
%
% This function makes a scatter-plot of frequency and duration (in periods)
% for detected bursts, and a scatter-plot of frequency and detected
% amplitudes.
%
% P... |
35703a62861bca9072c06202da6edb2f0347fa153a51f8dc764d5cacc056c604 | MATLAB | 4,347 | 137 | function [P, P0, output] = cp_opt(Z,R,varargin)
%CP_OPT Fits a CP model to a tensor via optimization.
%
% K = CP_OPT(X,R) fits an R-component CANDECOMP/PARAFAC (CP) model
% to the tensor X. The result K is a ktensor. The function being
% optimized is F(K) = 1/2 || X - K ||^2.
%
% K = CP_OPT(X,R,'param',value,..... |
d86ccf4ed404c9415f22549e06667b886d3e8a8329cacd668f9182afccb3c274 | MATLAB | 4,348 | 127 | %% (Predict Spike Plotter -- Plot) Error rate vs. State
%
% Plots the average prediction error by states, as calculated from the
% prespike components
%
% The errorStruct, 'Lx_x_state' components are the total cumulative error,
% normalized by the number of predictions from that state; effectively a
% mean. If w... |
3417f474f3aadb885fbd91cc2828129f65c9438f735579a13f5c9e171ea4b0d5 | MATLAB | 4,349 | 127 |
%Load the set of all pixels of all puncta across all rounds from the
filename_pixels = sprintf(fullfile(params.punctaSubvolumeDir,sprintf('%s_punctavoxels.mat',params.FILE_BASENAME)));
load(filename_pixels)
fprintf('Loaded.\n');
%This is the size of the cropped images, corresponding to ~15um pre-ExM
filename_punct... |
fbe06014b5211782ed8a509d50972699c5eb4729787a5ca3b7dadd62a3701d3f | MATLAB | 4,349 | 113 | function [ titleStr, settings, results ] = localGraphAnalysisFeatures( dataview, settings )
% This function can compute graph based density estimates.
%
% This function is meant for k-NN graphs.
%
% The parameter k determines which neighbor to consider.
%
% Depending on the dimension... |
86619a200214a2df863d6a0a90346e2ad4dd4c65307d50733c100f4d7dea1161 | MATLAB | 4,350 | 120 | function [dgm, loglikHist] = dgmTrainEm(dgm, data, varargin)
%% Fit a dgm with partially observed data via EM
%
% See dgmTrain
%%
% This file is from pmtk3.googlecode.com
[localEv, EMargs] = process_options(varargin, 'localev', []);
if ~isempty(localEv) && ndims(localEv) < 3 && dgm.nnodes > 1
localEv = insertSingl... |
7c112f49477f0f62cafbc6a8c5cae32fe2c1991fc3b147625a28d394b72d32a8 | MATLAB | 4,357 | 136 | %% MVGC Multivariate Granger Causality Toolbox - Function Reference
%
%% Toolbox initialisation
%
% * <startup.html startup>
%
%% Demonstration scripts
%
% * <mvgc_demo.html mvgc_demo>
% * <mvgc_demo_bootstrap.html mvgc_demo_bootstrap>
% * <mvgc_demo_GCCA.html mvgc_demo_GCCA>
% * <mvgc_demo_nonstationary.html mvgc_demo... |
0bc5ab78ec41a33cdf09b71cc0b20889c20c730df8f974a1bc02ea290a2ba7d6 | MATLAB | 4,359 | 170 | function [p2,W2] = violinPlotsStats(data,opts)
% significant box of violins
% setup commonly used values
nCond = size(data,2);
nObs = size(data,1);
nPt = 200;
if ~isfield(opts,'yl') || isempty(opts.yl)
yl = [min(data(:)) max(data(:))];
opts.yl = yl+diff(yl).*[-0.1 0.1];
end
if ~isfield(opts,'sigLe... |
7abbf077587cdccb84ab1542ec9f7a3a4e2e96722ff7ba7ad5efc9578c1d4d7e | MATLAB | 4,359 | 104 | % Subtract first response before correlation to second response, iterate until no more responses:
% while max value is larger than Corr_Thresh:
% get first (largest) max value.
% check that index is within range (lags range 0-23)
% shift TemplateResponse and subtract from sequence
% Run correlation again and look ... |
a4a1adedc8d12f7d91fe5a1a6fdb202db3b2ff239d8410936f3d781300f5adb7 | MATLAB | 4,359 | 163 | % FADE-SAME: Table S5
% clear
% close all
%%% Step 1: load data %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% set results files
FADE_file = '../FADE_scores/FADE_SAME_scores_2021_01_11_FADE_only.xls';
vols_file = 'covariates/HC_volumes_FADE.xls';
% load results files
[num, txt, raw1] = xlsread(FADE_file);
... |
ae4515b46f7c693fa91a090845e219164e268755c909569293b41d418af69cdf | MATLAB | 4,360 | 121 | %% movingstat - will summarize up a vector based on N values specified
% Well....talk about reinventing the wheel, only slower...turns out there
% was a function in matlab to do most of what I was attempting. Using the
% median as a summary statistic seems to be the only function not doable
% using conv or filt... |
3181a8129f51fe8edf75beae7aeacba4099d030dfd2034e30274c3ab7e8f5673 | MATLAB | 4,361 | 101 | function lan_master_gui_filt(LAN_var, mainfig, parent_)
LAN = LAN_var;
if nargin < 2
mainfig = figure;
end
figure(mainfig);
cfg_control(1) = uicontrol('style', 'text', 'units', 'norm',...
'position', [.04 .92 .6 .05], 'string', 'channel(s) : ',...
'horizontalalignment', 'right');
cfg_control(2) = uicontro... |
ff18eab9bf85f7e435b3d7a35c79614441e89f7f05a2935f9016029a9a740d6d | MATLAB | 4,362 | 171 | function c = ttt(varargin)
%TTT Sparse tensor times sparse tensor.
%
% Z = TTT(X,Y) computes the outer product of tensors X and Y.
%
% Z = TTT(X,Y,XDIMS,YDIMS) computes the contracted product of
% tensors X and Y in the dimensions specified by the row vectors
% XDIMS and YDIMS. The sizes of the dimensions spe... |
45bd4cb0c8342e277fa3293bbca6756e64947c76aaebf7246452f5655e729cc0 | MATLAB | 4,363 | 163 | function varargout=shadedErrorBar(x,y,errBar,lineProps,transparent)
% function H=shadedErrorBar(x,y,errBar,lineProps,transparent)
%
% Purpose
% Makes a 2-d line plot with a pretty shaded error bar made
% using patch. Error bar color is chosen automatically.
%
% Inputs
% x - vector of x values [optional, can be left em... |
aa5bfd86d1787a4406ff3e4761d58b484fa14e25104ab3cb6b57af8731dbcf9c | MATLAB | 4,363 | 200 | % this function adds the spikes in some channel
% to a global dataset that a global network can be trained on
%
% usage:
% C.addToGlobalTrainingData() % where C is your crabsort object
function addToGlobalTrainingData(self, nerve_name)
arguments
self (1,1) crabsort
nerve_name char
end
if isempty(self.channel_to... |
0556d55cc98f879e7f3037fb2c32814dca8527d021f87950a1722c166c36affc | MATLAB | 4,364 | 152 | % Author: Birgit Nierula
% nierula@cbs.mpg.de
function prepro_applyCCAfilters(subject, nerve, srmr_nr, is_eeg)
%% set variables
subject_id = sprintf('sub-%03i', subject);
if is_eeg
save_path = [getenv('EEGDIR') subject_id '/'];
else
save_path = [getenv('ESGDIR') subject_id '/'];
end
cfg_path = getenv('CFGDIR... |
362e267981dadeed7e3dbcf35c873733d6835a0b7578aa6270b1d086ddf85b24 | MATLAB | 4,364 | 132 | function uv = conformalParametrization(mesh, constrVidx, constrV)
% compute conformal parametrization
%
% SCP minimizes a functional u'*L_C*u + lambda*(u'*B*u-1)
% where the first term is the conformal energy with L_C the Laplacian
% minus the the area matrix
% and the second adds a constraint ... |
cfe5566fa3eff0208eb052b76e7603479899fb1a229c800422d1b1df8d0bd38f | MATLAB | 4,365 | 144 | function [count edges mid loc] = histcn(X, varargin)
% function [count edges mid loc] = histcn(X, edge1, edge2, ..., edgeN)
%
% Purpose: compute n-dimensional histogram
%
% INPUT
% - X: is (M x N) array, represents M data points in R^N
% - edgek: are the bin vectors on dimension k, k=1...N.
% If it is a scalar ... |
5fc227b9a48bf9588d62e49bec8c2cb8356be37745e8931ba3b32a70b97e79be | MATLAB | 4,367 | 161 | function wlPlot_plotAllMatrixEventsDebug(cfg, evmatrix, ...
figtitle, figlabel, plotsperband, trialstride, channelstride, eventstride)
% function wlPlot_plotAllMatrixEventsDebug(cfg, evmatrix, ...
% figtitle, figlabel, plotsperband, trialstride, channelstride, eventstride)
%
% This function plots all or some of th... |
2c7fb2c9bd01ba4b2314b70b9b57248a6a7daf81a7c52a385b49afd74c17a00f | MATLAB | 4,368 | 125 | function [tfr,t,f] = tfrspwv(x,t,N,g,h,trace);
%TFRSPWV Smoothed Pseudo Wigner-Ville time-frequency distribution.
% [TFR,T,F]=TFRSPWV(X,T,N,G,H,TRACE) computes the Smoothed Pseudo
% Wigner-Ville distribution of a discrete-time signal X, or the
% cross Smoothed Pseudo Wigner-Ville representation between two
% signals... |
774927e3ac3b62d3a79b952542d8406bbab357738161a8a24f2a0a8f826dd9b9 | MATLAB | 4,369 | 122 | function s = reorganizeDLParams(s)
% s = reorganizeDLParameters
% called by lblModernize
if isfield(s,'trackParams'),
return;
end
% KB 20190212: reorganized DL parameters -- many specific parameters
% were moved to common, and organized common parameters
sPrm_common = APTParameters.defaultParamsStructDeepTrack();
f... |
9d3f539868330b8b64b5f7638cce6c1f12d032059587072ba095e59072b43469 | MATLAB | 4,371 | 136 | function complete_bool = check_lfp(basepath, varargin)
%check_lfp Verify completeness of LFP file relative to the DAT file
% This function checks whether a downsampled LFP file (.lfp) is complete
% by comparing it against the corresponding raw wideband data file (.dat).
% If an LFP file exists, the function reads... |
6496625d8724dd5c2c293429cf360808df71cfcdba59e7d316e51f35313f784d | MATLAB | 4,372 | 110 | %% This file performs a simulation and saves the data used in figure 4 and table 1.
% This simulation computes R^2 values for all combinations of reduce b values
% to determine the optimal b-values to use in the b-value reduction.
%% Machine and simulation parameters
N = 1000; % Number of simulations
NDirs = 64... |
b86eab14cebdd4b6c37f3a0b6d5ee9ea6792f3fad983372febb2e8e1d8e88b74 | MATLAB | 4,373 | 107 | function [cluster, total] = findcluster(onoff, spatdimneighbstructmat, varargin)
% FINDCLUSTER returns all connected clusters in a 3 dimensional matrix
% with a connectivity of 6.
%
% Use as
% [cluster, num] = findcluster(onoff, spatdimneighbstructmat, minnbchan)
% or ar
% [cluster, num] = findcluster(onoff, spatd... |
d967e93e10cf2cba73c45e85ba47cdf9101d9866de68d01cc4e0f5e91d15c53f | MATLAB | 4,374 | 163 | function varargout=shadedErrorBar(x,y,errBar,lineProps,transparent)
% function H=shadedErrorBar(x,y,errBar,lineProps,transparent)
%
% Purpose
% Makes a 2-d line plot with a pretty shaded error bar made
% using patch. Error bar color is chosen automatically.
%
% Inputs
% x - vector of x values [optional, can be left em... |
f9ce7156f4c3f25ea52633c1113971c9bcfad86c96d30fe6cf38cfc5c549e8db | MATLAB | 4,377 | 100 | function [cfg] = ft_movieplotER(cfg, data)
% FT_MOVIEPLOTER makes a movie of the the event-related potentials, event-related
% fields or oscillatory activity (power or coherence) versus frequency.
%
% Use as
% ft_movieplotER(cfg, timelock)
% where the input data is from FT_TIMELOCKANALYSIS and the configuration
% ca... |
50c9adca0aa68d66f9854b61900acfa2cdbf8a4b688270fbfbb793b4dfdddf16 | MATLAB | 4,378 | 154 | scrsz = get(0,'ScreenSize');
scrWidth = scrsz(3);
scrHeight = scrsz(4);
datRoot = '/Volumes/LaCie/Farries recordings/';
% choose rat
rat = 'IM1153';
sesList = dir([datRoot rat '/20*']);
sesList = arrayfun(@(x) x.name, sesList, 'UniformOutput', false);
for i = 1:length(sesList)
fprintf('%d) %s\n', i, sesList{i})
en... |
0b0876e31304e6e2ac72f249cacbf07614f8e1324c1421f098a7f9c3d624273a | MATLAB | 4,380 | 123 | % DoG then threshold then zscore
% but also watershed and then use max zscore stuff on watershed components
%% get imgs
% change RUN_NUM to not overwrite files..
RUN_NUM = 321;
filedir = 'C:\Users\Maryann\Desktop\leBoyden\imgRegistration\DATA\';
ns = {'C1-PL(L)', 'C2-PL(L)', 'C3-PL(L)', 'C4-PL(L)'};
% cell ... |
392bc2ab00de2f34475097b307608b92c53ad058a506ca1d5d90be983869d996 | MATLAB | 4,384 | 171 | function [E, D] = multivariate_decomp(C,x,y,method,realflag,thr)
% MULTIVARIATE_DECOMP does a linear decomposition of multivariate time series,
% based on the covariance matrix.
%
% Use as:
% [E, D] = multivariate_decomp(C,x,y,method)
%
% Input arguments:
% C = covariance matrix (or csd) between input time series
... |
0f6cd3e05da0a40cf00978e15ebd00c98fd702e57eac7c77ac8f8ee65ccf0071 | MATLAB | 4,385 | 157 | % Demo for (stochastic) DCM for fMRI.
% This demo inverts the DCM for fMRI model, which contains the ballon model
% as a generalized observation function (not affected by stochastic
% innovations).
% NB: currently, there is a ratio 1e2 between the expected standard
% deviations of neural versus hemodynamic (states) noi... |
bb66ecfb8911cf8862a7022818ce6ea97e6565487b30ff09bda77604b0e444c3 | MATLAB | 4,385 | 100 | function h_loadProteinGelImg3(handles)
global h_img3;
[currentInd, handles, currentStruct, currentStructName] = h_getCurrendInd3(handles);
channelToLoadForGelOpt = get(handles.channelToLoadForGel,'value');
[fname,pname] = uigetfile('*.tif','Select an imaging file to open');
fname = fullfile(pname,fname... |
9ba0ba52135e5a0c6590919e463196119787d9e2d96c9b01929747e472e92bcf | MATLAB | 4,386 | 98 | function rt_all = reactionTime_MSIT_correct(cfg)
%% LOAD METADATA
% here's the header
hdr = ft_read_header(cfg.dataset);
% create functions to calculate:
timeToSamp = @(t) round(t * hdr.Fs); % time x sampling rate = sample
sampToTime = @(s) s / hdr.Fs; % sample / sampling rate = time
% extract list of eve... |
94ecbd0ee2575537eac7baa31600b1a902dd18b9c88d5b9fd284d1c5fe4c043a | MATLAB | 4,387 | 125 | function [lf] = eeg_leadfieldb(dippos, elc, vol)
% EEG_LEADFIELDB computes the electric leadfield for a dipole in a volume
% using the boundary element method
%
% Use as
% [lf] = eeg_leadfieldb(dippos, elc, vol)
% with the input arguments
% dippos = position dipole, 1x3 or Nx3
% elc = electrode positi... |
eb2081d898adae178451c4fb8ff1cb2b5fa12edf49f64ae95e6e3d798aecd837 | MATLAB | 4,387 | 138 | function [lf] = eeg_slab_monopole(rd, elc, vol)
% EEG_SLAB_MONOPOLE calculate the strip medium leadfield
% on positions pnt for a monopole at position rd and conductivity cond
% The halfspace solution requires a plane dividing a conductive zone of
% conductivity cond, from a non coductive zone (cond = 0)
%
% [l... |
de3a0a595277564703a4ee98df82c4d783b37ccb68910872bfa63f7d80124b3b | MATLAB | 4,388 | 129 | % PlotMiceStrideAveragess.m
% Sarah West
% 7/18/23
% For a given behavior period plots the average, resampled stride
% (normalized to be 10 data points long) across mice. Uses the standard
% error of the mean as error bars.
% Runs with RunAnalysis
function [parameters] = PlotMiceStrideAverages(parameters)
... |
0a7bc93fa4a946d74ea7fd9071afdc82f417bef61d449e5e2a8f1b6eb671d88e | MATLAB | 4,389 | 115 | %% filterSpiketimeContinuous
% // A collection of methods to convert a set of impulses, input as a point
% process, into a continous function by convolving with a selected finite
% inpulse response (FIR) function
%
% INPUTS:
% timestamps = (1xN) array of event times (in Sec)
% SIG_HZ = Int. Sample frequency... |
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