sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
fa4d7a15b91c0eba58812be8bb5d356dd14933032044d307dc593b05eb1aa426 | MATLAB | 1,481 | 41 | function c = tapas_bayes_optimal_whichworld_config
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Contains the configuraton for the estimation of Bayes optimal perceptual parameters
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
0bcc1a487db3997f1d7d6f312db4c0e5ec6849a62f630190c351838799419e61 | MATLAB | 1,482 | 54 | function TMSCluRep4WM(ResMap,Template,OutDir)
% ResMap = '/mnt/NCPL09/dALFF/SnPM_result_zdALFF_0.01/SnPM_filtered+.nii'
% Template = 25 or 0
if nargin==2
OutDir = pwd;
end
[ProgramPath, fileN, extn] = fileparts(which('TMStarget.m'));
% it provide two template with different probability tract
if Template==25
... |
2db9c26e6eb7128eb966f71cbbf30fd1eb623d8019268b338d8d9a0995786ae9 | MATLAB | 1,482 | 50 | function [ palette,palette_str ] = get_seaborn( )
range = 1;
chosen_palette = 'deep';
switch chosen_palette
case 'deep'
pal = {'#4C72B0', '#DD8452', '#55A868', '#C44E52', '#8172B3','#937860', '#DA8BC3', '#8C8C8C', '#CCB974', '#64B5CD','#000000'};
end
palette = cellfun(@(x) hex... |
51df2c76a2b301d0e37b6ebec2debd7d53522703fa41996e880e3f9baf7b4441 | MATLAB | 1,482 | 41 | function parentNode = traverseFolderDepth2(parentNode, currentFolder)
% Get all contents of the current folder
contents = dir(currentFolder);
% Filter out '.' and '..' directories
contents = contents(~ismember({contents.name}, {'.', '..'}));
[~, sort_idx] = natsort({contents.name});
c... |
645a29ba16e17b364fc7bc0d79fc76cc877c98157b9e38c09d3b1f66ab08492c | MATLAB | 1,482 | 35 | function TMSLargeCluster(FCImgDir,P_df,type)
%% define the target using voxel p and cluster size
[OutDir name ext] = fileparts(FCImgDir);
[fchead fcdata] = TMSReadNii(FCImgDir) ; % individual space
FCImgDir
max(fcdata)
min(fcdata)
VoxThr = invpearson(P_df(1),P_df(2))
... |
8c2ea2ea547d8b80039d4dc23f6ec804a563654a354d0ee9fc92f34fcaf6164b | MATLAB | 1,482 | 49 | function this = MrImageGeometry_create_empty_image(this)
% Unit test for MrImageGeometry.create_empty_image
%
% Y = MrUnitTest()
% run(Y, 'MrImageGeometry_create_empty_image')
%
% This is a method of class MrUnitTest.
%
% IN
%
% OUT
%
% EXAMPLE
% MrImageGeometry_create_empty_image
%
% See also MrUnitTest
% Aut... |
4b3e9da0d396b9be40e0b025126ba227ef568d5fd301f3f86a82dc07ca2255c4 | MATLAB | 1,483 | 53 | function hash = hlp_cryptohash(data,fromfile)
% Compute an MD5 hash of a file, string or generic data structure.
% Hash = hlp_cryptohash(Data,FromFile)
%
% In:
% Data : data to be hashed; can be a filename, a string, or any other MATLAB data structure.
%
% FromFile : if true, data is interpreted as a file name (def... |
773957b4c57347d57062e8b429cf09781fa58a86645a193b586358f8465ddd8c | MATLAB | 1,483 | 52 | function [X, Y, Z] = faceLocations(m)
% [X, Y, Z] = faceLocations(m)
% m is a mesh type
% This function returns the X, Y, and Z
% each one is a face variable itself, and can be used for the calculation
% of face variable as a function of locations
% SYNOPSIS:
%
%
% PARAMETERS:
%
%
% RETURNS:
%
%
% EXAMPLE:
%
% SEE ALSO... |
ab6e9c81447f00ebd3bc6cbb344e44e5a5b44b256f8c2c421ebba3e554b87509 | MATLAB | 1,483 | 49 | function c = tapas_softmax_config
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Contains the configuration for the softmax observation model for multinomial responses
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
c25318196156f59773c318f1387e8fd2de614cf5d465b5725450f1f1c43e8898 | MATLAB | 1,483 | 59 | function [initcond, bestfit, mse] = fit_exp_decay(x, y, iters, varargin)
%uses fmincon to fit exponential to data specified by 'x' and 'y'.
%inputs: x = vector of x values.
% y = vector of y values.
% iter = iterations of random initializations. 10-20 is reasonable.
%cmc 11/3/21
%adding upper and lower bo... |
e9f1e85425a72b141803fb591bd82cb46a0781c44326f2bb44e64e27e273106c | MATLAB | 1,483 | 44 | function artifactDuration = getStimArtifactDuration(Params)
% GETSTIMARTIFACTDURATION Duration (s) blanked out after each stimulus.
%
% Spikes between the stimulus onset and the end of this window have already
% been removed by batchProcessSpikesFromStim (see allArtifactWindowEnd
% there), so any post-stimulus spike c... |
171c0a2859f5e5288bc0ae5284eb365ac619f19a80de3f14e3018262644f09d0 | MATLAB | 1,484 | 50 | function outputImage = imclose(this, structureElement)
% Closes image clusters slice-wise; mimicks imclose in matlab functionality
%
% Y = MrImage()
% Y.imclose(inputs)
%
% This is a method of class MrImage.
%
% IN
% structureElement
% morphological structuring element for morphological closing, e.g.
%... |
30b1f0298ce193243342320d30dcb190b1aaf8cd269e5c9177c9321a08daa9c2 | MATLAB | 1,484 | 47 | function rf_summary
% summarizes the quality of mice
set(groot,'defaultAxesColorOrder', parula(4)*0.7, 'defaultAxesLineStyleOrder', '-|--|:')
fits = pro(aod_monet.Fit, 'radius*pow(contrast,1.5)->score') & 'preprocess_id=3' & 'spike_inference=2';
keys = fetch(vis2p.Experiments & aod_monet.Fit, 'exp_date', 'ORDER BY exp_... |
5bf53759d78f465d43b9b6f9570f593bb065c0d36999ca524a53d2c6f182e8d8 | MATLAB | 1,484 | 41 | function myelin = Oligo_Apoptosis(myelin, threshold_apop, threshold_stopmy)
% OLIGO_APOPTOSIS
%
% Implements oligodendrocyte apoptosis and function loss based on
% accumulated damage in myelin segments.
%
% INPUTS:
% myelin - structure containing myelin state and oligodendrocyte info
% threshold_apop ... |
ff9573e0bf4c4f49d0154714a26cd6c172ad2f72892c0927860d7269bbb0314b | MATLAB | 1,484 | 38 | function [SFC,STA,fSTA,STP,f] = LFP_Coherence(LFPData,SpikeLoc,NoPoints,SampFreq)
%% Calculate the Spike Field Coherence
%
% Inputs
% LFPData -- local field potential data for a single channel
% SpikeLoc -- corresponding locations of the spikes
% NoPoints -- number of data points either side ... |
27403545e36ec8223a8c11bb22d6966156aa38357fff4224892b9939758f5156 | MATLAB | 1,485 | 53 | function [RHSdiv, RHSdivx, RHSdivy] = ...
divergenceTermRadial2D(F)
% This function calculates the divergence of a field using its face
% average value and the vector u, which is a face vector
%
% SYNOPSIS:
%
%
% PARAMETERS:
%
%
% RETURNS:
%
%
% EXAMPLE:
%
% SEE ALSO:
%
% Copyright (c) 2012-2016 Ali Akbar ... |
865cb4ff94576caf14c9f295bece4a7690bb3a4d81a1a090f05f792a5e8fa350 | MATLAB | 1,486 | 41 | function c = tapas_bayes_optimal_categorical_config
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Contains the configuraton for the estimation of Bayes optimal perceptual parameters
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
07744514478266deb8750874176b44e59a14c7e3f678afb82dd49c88dfd40c5b | MATLAB | 1,487 | 31 | % GET ARTwarp ROOT PATH FOR REFERENCE WHILE RUNNING IN CONTINUOUS
% INTEGRATION
tstDir = fileparts(mfilename("fullpath"));
ARTwarpRoot = fullfile(tstDir, '..');
% Add the ARTwarp root path to the MATLAB path so we can run ARTwarp's
% functions
addpath(genpath(ARTwarpRoot))
% CONVERT .csv FILES TO .ctr
% read from the... |
2f5799435cf81dc9266d643a5a83c8c7b280059aebfe5895297fa336a03f119d | MATLAB | 1,487 | 55 | function [abpl, ubpl] = tapas_ti_bpl(llh, t)
%% Computes the Bayesiand predictive log likelihood.
%
% Input
% llh Multidimensional array of preditive likelihood. Dimensions are
% Number of subjects x number of chains x number of samples
% t Temperature schedule of size 1 x number o... |
4cefb9d7efe6fa5da4f2ee26ce63766c531242780afd8a58c2c936b9559ecd39 | MATLAB | 1,487 | 49 | function P=participation_coef(W,Ci,flag)
%PARTICIPATION_COEF Participation coefficient
%
% P = participation_coef(W,Ci);
%
% Participation coefficient is a measure of diversity of intermodular
% connections of individual nodes.
%
% Inputs: W, binary/weighted, directed/undirected connection matrix
%... |
a152eda4f9463129af44d22e877eb5182bb2b57bdeb0d30d2c89051163d5b0ce | MATLAB | 1,487 | 47 | %% [RDF] = Wrapper_BFR_PDF(totalField,mask,matrixSize,voxelSize,algorParam, headerAndExtraData)
%
% Input
% --------------
% totalField : total field map (background + tissue fields), in Hz
% mask : signal mask
% matrixSize : size of the input image
% voxelSize : spatial resolution of each dimension ... |
f2f2747a42ca905f897ae66222ccf9fe71da0653deb9afbdfa6cd7cd1f88a07b | MATLAB | 1,487 | 48 | function imgt = aux_imscale(img, range)
%% AUX_IMSCALE: Scale an image to fit the range
% This function scales the values of an image to fit the range.
%
% INPUT:
% img = The image.
% range = The min target value. (def=[0,1])
% OUTPUT:
% imgt = The image scaled.
%
% AUTHORS: Jizhou Li, Flor... |
1bec09f77e51b4ddcd883ec7da1f5683a3aa12c9ae2d5b25ed2c0e370fa244b1 | MATLAB | 1,488 | 35 | function [df_sta_traces, sta_traces] = make_sta_df_traces(input_traces, stim_frames, pre_frames, post_frames,varargin)
baseline_frames = 1:pre_frames-1; % use the entire pre stim window for baselining unless specified
baseline_method = 'average';
for v = 1:numel(varargin)
if strcmpi(varargin{v},'baseline_frames... |
53b03394c7197e36f99fd0c6548023b0a789f04e9c6dec89ed32b843ac06b473 | MATLAB | 1,488 | 46 | function outputImage = minip(this, applicationDimension)
% Computes minimum intensity projection image along specified dimension,
% uses Matlab min function
%
%
% Y = MrImage()
% Y.minip(applicationDimension)
%
% This is a method of class MrImage.
%
% IN
% applicationDimension image dimension along which oper... |
df094b458a19e3743d6ffd847eb6e5407572ab08e91d3ea5584bcdfdbfd7f2cd | MATLAB | 1,488 | 46 | function outputImage = combine_complex(this)
% combines dimensions with complex parts (magnitude/phase or
% real/imaginary) into a complex array with N-1 dimensions
%
% Y = MrImage()
% outputImage = Y.combine_complex()
%
% This is a method of class MrImage.
%
% NOTE: The dimensions reflecting the complex parts are ... |
fa077a7de233d0ddd0185df83e6d8ebdd27bde01e6d3f2cbb1242764d2d987b4 | MATLAB | 1,488 | 48 | function [err,data] = afni_ni_checkfordata()
global comm;
data = [];
err = 1;
if (comm.sockcon < 0),
comm.sockcon = pnet('tcpsocket',sprintf('%d', comm.socknum));
if (comm.sockcon < 0),
fprintf(2,'Could not open socket %d\n', comm.socknum);
return;
end
if (comm.dbg... |
aacbd2d34fc86bb0fcc2b68a20a38f2bd53899ea20f01a92a6c24efcdcda70ff | MATLAB | 1,489 | 43 | function outputImage = zoom(this, zoom_factor)
% Geometric shear of MrImage
%
% Y = MrImage()
% Y.zoom(inputs)
%
% This is a method of class MrImage.
%
% NOTE: This is a method of MrImage rather than MrImageGeometry, because
% the latter is composed on the fly from affineTransformation and
% dimInfo to ... |
34cd0678d65ea3950daf677345e4cc6dabb7ef082707e3f34a5d276860ab04a4 | MATLAB | 1,490 | 43 | function plotNContactsDistributions(eventInfo)
% Plot bar plots for the number of contacts within 1s of the cue
fig;
hold on;
axis off
% Get counts
[countsR, ~] = histcounts([eventInfo.nGrasps_R], 'BinMethod', 'integers', 'Normalization', 'probability');
[countsL, ~] = histcounts([eventInfo.nGrasps_L], 'BinMethod', 'i... |
e83c73b3a12ad0eb10bc9bbd3baf2677908ac58ad97fe528498d359fa00aa3be | MATLAB | 1,490 | 52 | function [stats] = boxplot_hmt(y, x, isDep, names)
% create boxplot with significance labels;
% INPUT
% y = vector with data to plot;
% x = vector with x-positions for data in y;
% default settings
if nargin<3
isDep = 0;
end
if nargin<4
names = {"A", "B"};
end
% determine number and xPositions ... |
1d06fca85a7b7d5957dafbfa9a30e4570a19c5d58b9c22be04cce36376378cd4 | MATLAB | 1,491 | 71 | function [posterior] = tapas_sem_hier_prepare_posterior(data, model, ...
inference, states)
%%
%
% aponteeduardo@gmail.com
% copyright (C) 2016
%
T = model.graph{1}.htheta.T;
posterior = struct('data', data, 'model', model, 'inference', inference, ...
'samples_theta', [], 'fe', [], 'llh', []);
np = numel(sta... |
7bbd7b7589826e81b587b253d3390cf4cd88082cc98d51c6257009b6fdd603f8 | MATLAB | 1,491 | 44 | function outputImage = shear(this, shear_dr)
% Geometric shear of MrImage
%
% Y = MrImage()
% Y.shear(inputs)
%
% This is a method of class MrImage.
%
% NOTE: This is a method of MrImage rather than MrImageGeometry, because
% the latter is composed on the fly from affineTransformation and
% dimInfo to i... |
975c6d8a49350c2c3f53a5124340effe9b41cebb415236d9b7face2be98616cb | MATLAB | 1,491 | 51 | function [Xrot, Yrot, Portxrot, Portyrot] = rotationmatrix(tracksx, tracksy, portx, porty);
% A rotation matrix is used to perform a rotation in Euclidean space. It
% establishes a cartesian coordinate system, and rotates the points in the
% plane around the origin.
% Written by Astra S. Bryant 4/4/2019
% When rotat... |
b04d306a25f4154b861b199303df9d35e9e486021721a668de26c0474e769cff | MATLAB | 1,491 | 45 | dataFileName = fullfile('results', 'doseResponseData.mat');
load(dataFileName);
data = dff;
%% apply PCA, treat each concentration a uniq sample
dataTall = permute(data, [1 3 2]);
dataTall = reshape(dataTall,[],size(data,2),1);
[coeff, score, ~, ~, explained, mu] = pca (dataTall);
%% plot the data projection onto t... |
c4b1d14cbcf0cc197df7b8aba30fbb49511f9e08f18f8e1cdd806ddcfa0883f8 | MATLAB | 1,491 | 52 | %% function [r2s, M0final] = R2starmapping_ARLO_complex(img,te)
%
% Description: Fast monoexponential fitting of R2* by auto-regression
% echo spacing should be the same across time series
% Assuming time series in last dimension
% M0 map is calculated by weighted sum method
% ref: Pei et al. MRM 73:843?850(2015)
%
% K... |
f9e2eb7dec911b15b8be03be783d7c515088514e976843c39685495d00c1fd3b | MATLAB | 1,491 | 46 | function fear_EIseparation(basename)
% load('~/data/Fear/triple/hoegaarden181115/hoegaarden181115.basicMetaData.mat')
% basename=basicMetaData.Basename
param.threshold=[0.5,0.6];
load([basename '.basicMetaData.mat'])
fprintf('%s start %s with data of %s\n',datestr(now),mfilename,basicMetaData.SessionName)
load([ba... |
56c78685c8b8174883c5c0a509e0acdb6e74b1a47f4605a3e5df554f42a21943 | MATLAB | 1,492 | 59 | function [itiMdl, itiOpt, V, rpe, alpha, G, belief] =...
generate_deltabelief_mdl(...
R, alpha0, D)
% generate_deltabelief_mdl - generates data for Delta-Belief model
% INPUTS:
% R - reward vector. Must be 1:5
% alpha0 - Base learning rate
% D - Scale parameter
% OUTPUTS:
% itiMdl - trial intiation time... |
23d3fe88a6c9d940985dbfb63e98a710db68e0b81bbac620461df0b5ac3ce826 | MATLAB | 1,493 | 47 | function otherImage = circshift(this, nShiftSamples, applicationDimensions)
% circularly shifts data matrix by nShiftSamples for all given dimensions
%
% Y = MrImage()
% Y.circshift(nShiftSamples, iDim)
%
% This is a method of class MrImage.
%
% IN
% nShiftSamples [1, nShiftDims] number of samples to shift
... |
4c3f64a117febd1e054a3f24be9261edf72cb919a19b74541d8ea827c86989a9 | MATLAB | 1,493 | 62 | function analyzebehavior_floc_visualize(ppdirs,outputdir)
% load
alldata = {};
for p=1:length(ppdirs)
alldata{p} = load([ppdirs{p} '/behavioralresults_floc.mat']);
end
% look at duration
figureprep([100 100 1000 300]); hold on;
cnt = 0;
for p=1:length(ppdirs)
n = length(alldata{p}.totaldur);
plot(cnt+(1:n),alld... |
0accd58fde979f41fb157726ae3914bcb5edaff38ad00fe02226d729899109dd | MATLAB | 1,495 | 43 | function sizes = getVarSizes(obj, inputSizes)
%GETVARSIZES Get the size of the variables
% SIZES = GETVARSIZES(OBJ, INPUTSIZES) computes the SIZES of the
% DagNN variables given the size of the inputs. `inputSizes` is
% a cell array of the type `{'inputName', inputSize, ...}`
% Returns a cell array with sizes ... |
25fd95494f57d9d901de2a7ebacd9c6f7228f80ea157f55655b9cb345d495ab9 | MATLAB | 1,495 | 68 | function [croppedImage, boundbox] = autoCropImage(image, varargin)
% DESCRIPTION
%
% SYNTAX
%
% EXAMPLE
%
% CONTACT: StanfordVoltageGroup@gmail.com
%% GET DEFAULT OPTIONS
options.plot=false;
options.verbose=true;
options.boundbox=[];
options.threshold=0.1; % remove 10% of above background level
options.savePath=[];
... |
892d620c52b00a8893f124aefe6db5bab2a7ad03908254c87250996eadd5cccf | MATLAB | 1,495 | 43 | clear all %#ok<CLALL> % Clear all workspace variables
close all
filename = 'C:\Users\Harnettlab\OneDrive\Desktop\Voltage_Data\Sq_camera.bin';
nrow = 96;
ncol = 200;
stack = readBinMov(filename, nrow, ncol);
IPv4 = '127.0.0.1';
% Define TCP/IP communication parameters.
port = 30001; % Set the port number for commu... |
8cac437610acdde74560a3299a7fd12468aa756c33661d78786642102cbdbe13 | MATLAB | 1,495 | 55 | function m = copymatrix(varargin)
% function m = copymatrix(m,sub,val)
%
% <m> is a matrix. can be [] when <sub> is a logical, in which case
% we assume <m> is zeros(size(<sub>)).
% <sub> is
% (1) some sort of index (e.g. vector of indices, logical mask)
% (2) a function that accepts <m> and outputs an index
% ... |
bc5b5ed5a05c714bcef49243e2f960c8417e6746417389490f89853b0bba6067 | MATLAB | 1,495 | 53 | function [pA,pG,pAG,pD,pAD] = runlmestability(behavior, eigenvalue, toi)
eigenvalue = permute(eigenvalue,[1 3 2 4]);
behavior.Group = categorical(strtrim(string(behavior.Group)));
nt = size(eigenvalue,4);
pA = nan(2,2,nt);
pG = nan(2,2,nt);
pAG = nan(2,2,nt);
pD = nan(2,2,nt);
pAD = nan(2,2,nt);
for... |
c3e978ae684203dd16872a3661cca52d1366055eee1af09ac1a8313a70b8b5bf | MATLAB | 1,495 | 32 | %T=readtable('../Test_Data/csv/Sb_HICEAS1706_20170913_AD259_S123_sel22_220035.csv')
% GET ARTwarp ROOT PATH FOR REFERENCE WHILE RUNNING IN CONTINUOUS
% INTEGRATION
tstDir = fileparts(mfilename("fullpath"));
ARTwarpRoot = fullfile(tstDir, '..');
% Add the ARTwarp root path to the MATLAB path so we can run ARTwarp's
% ... |
ee230f26af27e667940fca5358feac78018d5cc23901d9f65c480e6ef5a5807b | MATLAB | 1,495 | 45 | function [markersize] = OptimiseMarkersize(data, I, markertype, markersize, bar_intervals, x_lim, y_lim) % by Julia Becker, 14/10/2021
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
ui = markersize;
threshold = ceil(max(data.modulus));
heatmap_scale = hot(threshold);
data1 = data;... |
21c698dcc5afbb5fe5fbfb93e28c09479e68172f32486892b667d853ed6b74ac | MATLAB | 1,496 | 64 | function [spsmf_out] = spsmf_detector(hsi_img,tgt_sig,mask)
%
%function [spsmf_out] = spsmf_detector(hsi_img,tgt_sig,mask)
%
% Subpixel Spectral Matched Filter
% matched filter derived from a subpixel mixing model
% H0: x = b
% H1: x = alpha*s + beta*b
%
% inputs:
% hsi_image - n_row x n_col x n_band hyperspectral... |
2cce15205fa76f15385112cc5f8b9a0c6e40532b98f5d0641b2f244521a853a5 | MATLAB | 1,496 | 47 | %% [h_checkbox,h_edit] = sepia_construct_checkbox_edit(parent,fieldString,defaultValue,pos,wratio)
%
% Input
% --------------
% parent : parent of the constructs
% fieldString : text to be displayed in the 'checkbox' field
% defaultValue : default value in the 'edit' field
% pos : position of the co... |
cedf899d756aac73276eb55de9e17c938360a5b4ee16e8c15478227959d8af86 | MATLAB | 1,497 | 40 | % Example using the phantom Fibercup (2D version)
% Data can be downloaded in http://www.tractometer.org/original_fibercup/data/
%
% Author: Aina Frau-Pascual
% Load Input image, generated with DSI Studio
%dsi_studio_run --action=src --source=data.nii.gz --bval=bvals --bvec=bvecs --output=data.src.gz'
%dsi_studio_run... |
59469c43cb8bf95ca37a472c476dc614deebd66b7f3395b66366f06a8aecb517 | MATLAB | 1,498 | 55 | function colormap = colormapHSV(colormap, hueMultiplier, satMultiplier, valMultiplier)
if ~isempty(hueMultiplier)
colormap = colormapHue(colormap, hueMultiplier);
end
if ~isempty(satMultiplier)
colormap = colormapSat(colormap, satMultiplier);
end
if ~isempty(valMultiplier)
colormap = colormapVal(colormap,... |
c62472d7cd015ae511f23f2b34be8bc00d27dc6c30d2feece8d3f8408c72fbfe | MATLAB | 1,498 | 32 | function [pvec, pstruct] = tapas_ehgf_binary_pu_tbt_transp(r, ptrans)
% --------------------------------------------------------------------------------------------------
% Copyright (C) 2024 Anna Yurova, Irene Sophia Plank, LMU University Hospital;
% ehgf adaptation based on the function tapas_hgf_binary_pu_tbt_trans... |
c67120c85fba18a7427066ec0507f7e965cf7c2bdab2cbd61dfd54be81b10724 | MATLAB | 1,498 | 38 | function R = tapas_physio_scaleorthmean_regressors(cardiac_sess)
% create orthogonalized cardiac regressors (Fourier expansion) to ensure
% numerical stability of SVD in spm_spm, if regressors are highly
% correlated (e.g. after triggered acquisition)
%
% USAGE:
% R = tapas_physio_scaleorthmean_regressors(cardiac_ses... |
4c646e6e3a47705590eaf380b6650a3812c01a000875a54a043ea5533b0955ee | MATLAB | 1,499 | 45 | function [ratBlk, mdlBlk] =...
compare_rat_and_model(BestFit)
% compare_rat_and_model - function to compare rat trial intiation time
% and corresponding model predictions
% INPUTS:
% BestFit - Fit to rat's data, e.g., BestFitLate.(RAT_ID)
% Outputs:
% ratBlk - First row is average rat trial initiation time by b... |
d677ff6450a6fe9419adee3be41fe88331995b98848991860cfd2ba306c9cf14 | MATLAB | 1,499 | 43 | function [logp, yhat, res] = tapas_cdfgaussian_obs(r, infStates, ptrans)
% Calculates the log-probability of response y under a cumulative Gaussian distribution. This
% model has no free parameters.
%
% --------------------------------------------------------------------------------------------------
% Copyright (C) 20... |
054e20fb3cfe992e146270712a8092077f2e7baace599a14c8c7f9132d1474e6 | MATLAB | 1,500 | 68 | % [x,y] or x = MS_embed(z,lags) or MS_embed(z,dim,lag)
% embed z using given lags or dim and lag
% embed(z,dim,lag) == MS_embed(z,[0:lag:lag*(dim-1)])
% negative entries of lags are into future
%
% If return is [x,y], then x is the positive lags and y the negative lags
% Order of rows in x and y the same as sort(lags)
... |
328845281c3b12aff37994ee2d5d1cf376c3d19d11df8e0d558f8a03298e6d2e | MATLAB | 1,500 | 38 | function [Ne_adj]=Adj_site_effect(NodalE_All,indall_select_All,Site_info,Brainsz_All,Age_gender_sp_All)
Ne_adj=NodalE_All;
NodalE_Alln=NodalE_All(indall_select_All,:);
Site_infon=Site_info(indall_select_All);
Brainsz_Alln=Brainsz_All(indall_select_All);
Age_Alln=Age_gender_sp_All(indall_select_All,1);
Gender_Alln... |
8beb238b92d9acb48ee7a3e9d3e13291ea9ba217c2f09de9129591d2fb7f5407 | MATLAB | 1,500 | 38 | function [time_projection] = assembly_activity(AssemblyTemplates,SpikeCount)
% Activities = assembly_activity(Patterns,Activitymatrix): computes the
% time course of the activity of assembly patterns defined in Patterns in
% the spike matrix Activitymatrix with single bin resolution.
%
% Description of inputs: ... |
1135b5109a715f3df87bb299685f55ad0910e35cb950a0fb6b8200d91b7ec4b4 | MATLAB | 1,501 | 42 | function p = tapas_physio_prctile(x, percentile)
%returns the approximate value corresponding to a percentile for a given data vector
%
% p = tapas_physio_prctile(x, percentile)
%
% uses a sorting/interpolation approach as the original perctile in the
% Matlab Statistics Toolbox
%
% IN
% x [N,1] data ... |
09e7b936d9a14f2d609ae8bdcbbaea63315711cf650602a86570a76ebabbbe57 | MATLAB | 1,503 | 74 | function gotoDir(varargin)
% gotoDir(path, dir)
% Goes to path; then goes to dir, making it if necessary.
%
% gotoDir(path)
% Goes to path, making all required directories on the way.
%__________________________________________________________________________
% Copyright (C) 2010 Medical Research Council
impo... |
3c63de4cfaa86ea00241aa278b4c286919cf8200076423fde1faaed992bdc9b2 | MATLAB | 1,503 | 46 | function outputImage = maxip(this, applicationDimension)
% Computes maximum intensity projection image along specified dimension,
% uses Matlab max function
%
%
% Y = MrImage()
% Y.maxip(applicationDimension)
%
% This is a method of class MrImage.
%
% IN
% applicationDimension image dimension along which oper... |
7981ca626ce15f801fdb7850d04bb3f7714811cee3717a34a1d41043c0f10e38 | MATLAB | 1,503 | 52 | %% function m0 = ComputeM0GivenR2star(r2s,te,img,method)
%
% Input
% --------------
% r2s : R2* map
% te : echo times
% img : multiecho images
% method : '1stecho','weighted','average'
%
% Output
% --------------
% m0 : T1-weighted images
%
% Description: compute T1-wigh... |
4ed17c8eefb69e4acfe436a5dab081298d160ce866d71fb282c7018cbc074cc6 | MATLAB | 1,504 | 61 | function [palm_out] = palm_detector(hsi_img,tgt_sig,mask,n_comp)
%
%function [palm_out] = palm_detector(hsi_img,tgt_sig,mask,n_comp)
%
% Pairwise Adaptive Linear Matched Filter
%
% inputs:
% hsi_image - n_row x n_col x n_band hyperspectral image
% tgt_sig - target signature (n_band x 1 - column vector)
% mask - bina... |
588771f73942f4ae786f5f9f63bb2a3d80137c59ab85184720838238be19a8aa | MATLAB | 1,504 | 56 | function int = compute_int(mu,j,delta,eta,LL,strategy,extra)
%COMPUTE_INT: Determine which Lanczos vectors to reorthogonalize against.
%
% int = compute_int(mu,eta,LL,strategy,extra))
%
% Strategy 0: Orthogonalize vectors v_{i-r-extra},...,v_{i},...v_{i+s+extra}
% with nu>eta, where v_{i} are the... |
2b921dd46839b71c291be29e7098c60bf213e0ccfc7635ae12a7cb8ebaba1814 | MATLAB | 1,505 | 52 | function [isObjectEqual, out_left, out_right] = comp(...
obj, input_obj, tolerance)
% Returns non-empty properties where obj and input_obj differ ...
%
%
% Y = MrCopyData()
% Y.comp(inputs)
%
% This is a method of class MrCopyData.
%
% IN
% input_obj
% tolerance allowed difference seen still as equal
% ... |
677a1ba9cc881a70b4cb05d00aea0c399844b2fe8f46327f73c58af4040e3d70 | MATLAB | 1,505 | 65 | function FigureS1(datadir, codedir)
%FigureS1 - Trial initiation time in units of seconds
% datadir = directory of dataset
% codedir = director of code
%% Set up paths
s = pathsep;
pathStr = [s, path, s];
onPath = contains(pathStr,...
codedir, 'IgnoreCase', ispc);
if ~onPath % only add code dir to path if ... |
d7c8601195fa387ba222196f086612c85e4fed704f432f33a4e9dfc73cdb841f | MATLAB | 1,505 | 40 | %VL_NNNORMALIZE CNN Local Response Normalization (LRN)
% Y = VL_NNORMALIZE(X, PARAM) computes the so-called Local Response
% Normalization (LRN) operator. This operator performs a
% channel-wise sliding window normalization of each column of the
% input array X. The normalized output is given by:
%
% Y(i,j,... |
39cc453cf0b1e6002e9e37770f8ad775f78d0d51e2846534d5e8cbd3966574d7 | MATLAB | 1,506 | 40 | function [keptIdx, droppedIdx] = stratify(labels)
% Stratifies a set of 2-class labels
% Returns the indices for the stratified subset in keptIdx, and the
% remainder in droppedIdx
% Does so by reducing the number of labels in the larger group to match
% the smaller group
ulabels = unique(... |
7bf665bb0b0958ea5c2b98b63f76c4fee2d6dac5cb35598d2143fe785dff347e | MATLAB | 1,506 | 41 | % load_nii(char(fullfile(maskDir,roiName1)));
name1 = 'crossMod-Ext.nii';
name2 = 'crossMod-ext-allClusterst.nii';
name3 = 'rrhMT_fwe0pt05_currentCluster.nii';
name4 = 'rrhMT_p0pt05_currentCluster.nii';
name5 = 'rsub-ALL_hemi-R_space-MNI_label-rhMT_radiusNb-8.nii';
% cluster1 = load_nii(name1);
% notZero=length(find(... |
9ca8c9cf5f5ae97517b2096a20bc291af77351b4c91c2bff12112d4339ef66e2 | MATLAB | 1,506 | 26 | % Root diagnostics file.
% Argument should be a plaintext file listing the qcr's to be loaded
% newFolder=$(date +%Y_%m_%d_%H_%M_%S)
function main_diagnostics(filePath)
% Generate unique csv file
[~,fMod] = system('(date +%Y_%m_%d_%H_%M_%S)');
fName = ['diag_',strtrim(fMod),'.csv'];
fOut = fopen(fName,'... |
9d1cc74aca531191c5e6bc242665e3ddbd7bf37627d8a0b9af97cbf3256cac10 | MATLAB | 1,506 | 61 | function [ Y I ] = shuffle( X , DIM )
%SHUFFLE Shuffles elements.
% For vectors, SHUFFLE(X) shuffles the elements of X.
% For matrices, SHUFFLE(X) shuffles the rows of X.
% For N-D arrays, SHUFFLE(X) shuffles along the first non-singleton
% dimension of X.
%
% SHUFFLE(X,DIM) shuffles along the dimension DI... |
bc075ee94ee0e03b58795662323f6fbbcafbac54ef360440d4a497841996cb80 | MATLAB | 1,506 | 44 | function [K,dK] = covEye(hyp, x, z)
% Independent covariance function, i.e. "white noise", with unit variance.
% The covariance function is specified as:
%
% k(x^p,x^q) = \delta(p,q)
%
% \delta(p,q) is a Kronecker delta function which is 1 iff p=q and zero
% otherwise in mode 1).
% In cross covariance mode 2) two data... |
045e9ef7580beab13de585f4405ce64f5629252dbe40078807bcbb620552e2ac | MATLAB | 1,507 | 55 | function features = LoadSpikeFeatures(filename,rate)
%LoadSpikeFeatures - Load spike times, cluster IDs and features from disk.
%
% USAGE
%
% features = LoadSpikeFeatures(filename,rate)
%
% filename spike file name (either .clu, .res or .fet)
% rate sampling rate
%
% OUTPUT
%
% ... |
6141954c098c1fda67fe801bde04378a21d8e00ebbaa90fa6cf5f31d574b287e | MATLAB | 1,507 | 44 | function [stack,info] = aux_stackread(filename)
%AUX_STACKREAD: Read a stack of images and convert it to a double 3D
% matrix.
%
% USAGE: [stack,info] = aux_stackread(filename)
% It reads the stack named 'filename'
% and returns a 3D double matrix 'stack' and the stack info 'info'.
%
% INPUT:
% filen... |
a79c8e6a5cefaa1c743be866f1919f42d076fcbfa930ab265c3e84ef1fd463b4 | MATLAB | 1,507 | 58 | function W = get_estimated_weight2(Model,parm,wmode);
% Return Full Weight matrix from 'Model'
% W = get_estimated_weight2(Model,parm);
% W = get_estimated_weight2(Model,parm,wmode);
% --- input
% Model.W : Weight matrix for active input [Ydim x Nactive]
% Model.ix_act : active input index
% parm.Dtau
% parm.... |
a99a088ab033dcd29b1584a99b2a5f0254fa8f030841949345108fefd5baf669 | MATLAB | 1,507 | 26 | % EEGLAB Toolbox to process EEG data
% Version - see eeg_getversion()
%
% eeglab() - Matlab graphic user interface environment for
% electrophysiological data analysis incorporating the ICA/EEG toolbox
% (Makeig et al.) developed at CNL / The Salk Institute, 1997-2001.
% Released 11/2002- as EEGLAB (Delorme, M... |
e3ef7f7cbe5549097adca20ae2d76c5e0df8ab7ce6c098612f440c95f898cb87 | MATLAB | 1,507 | 58 | function R = quatToMat(b, c, d, qx, qy, qz, qfac, pixdim)
%
% R = quatToMat(qb, qc, qd, qx, qy, qz, qfac, pixdim)
%
% Convert a quaternion to a 4x4 rotation/scaling/translation matrix. Based on the
% nifti1 spec implemented in nifti1_io.c.
%
% 2008.10.01 RFD: wrote it.
%
if(isstruct(b))
c = b.quatern_c;
d = b.... |
63808e533b483a6c38706c1a9d912b583d45ed2e11531e4ae735bab6bb8219c3 | MATLAB | 1,508 | 52 | load(fullfile('.', 'data', 'dataFigureS4H.mat'));
%% setup the fitting function
hillEq = @(a, b, c, x) a./(1+ exp(-b*(x-c)));
ft = fittype( 'a/(1+ exp(-b*(x-c)))', 'independent', 'x', 'dependent', 'y' );
opts = fitoptions( 'Method', 'NonlinearLeastSquares' );
opts.Display = 'Off';
opts.Robust = 'Bisquare';
opts.Lowe... |
3f0ea8d923551b97c5cda18f3bf377a9936fa5cc86b0bb801a09e5dd14b5bef6 | MATLAB | 1,510 | 34 | function fit_res = interpolate_fit(fit,Dims_steps,res_step,Model)
%interpolate_fit(fit 'struct', Dims_steps 'double', res_step 'double', Model 'string')
% interpolate parametermaps to new size
%
% fit : struct containing fitting results
% Dims_steps : array containing Downsampling steps
% res_step : i... |
5d53eb0904eb77db5ececb8745634724c49335b008913954edb70b824b8c4402 | MATLAB | 1,511 | 84 | function fn_par = sero_srr_nii2fit_average(nii_fn, xps_fn, mask_fn, do_t1, opt)
% function fn_par = sero_srr_nii2fit(nii_fn, xps_fn, mask_fn, do_t1, opt)
if isempty(xps_fn) || nargin < 2
xps_fn = mdm_fn_nii2xps(nii_fn);
end
if isempty(mask_fn) || nargin < 3
mask_fn = [];
end
if nargin < 5
opt = sero_srr_... |
c683511ea83fe19740f1787e9b461480307a52e58c5deadf483a7fe760045718 | MATLAB | 1,511 | 48 | %% [unwrappedField] = Wrapper_Unwrap_LaplacianMEDI(wrappedField,mask,matrixSize,voxelSize,algorParam, headerAndExtraData)
%
% Input
% --------------
% totalField : total field map (background + tissue fields), in Hz
% mask : signal mask
% matrixSize : size of the input image
% voxelSize : spatial res... |
76b8be448aa8a6a893279813d33dcc4329e801b0b3641588b32870dc5c1262a1 | MATLAB | 1,512 | 50 | %% isHam(Matriz)
%
% Determina si la Matriz es un Ciclo Hamiltoniano.
%
% Matriz = |a11 a12 ... a1n|
% |a21 a22 ... a2n|
% | . . ... . |
% |an1 an2 ... ann| nXn
%
% Propiedad del Ciclo Hamiltoniano
%
% 1) La Matriz Hamiltoniana e... |
fbed94ec9e0a8526e2e5c6e07d572f1936883594a2993b748699a4e58b847543 | MATLAB | 1,512 | 51 | function plotEC_plotband2axes(y_avg, y_sem, timeAxis, EC_info)
% plots EC to axes as plotband
% (c) Jiri, Nov22
%% >>> plot G_src -> G_trg <<<
for clz = 1:size(y_avg,2)
plotband(timeAxis, y_avg(:,clz), y_sem(:,clz), EC_info.info.colors(clz,:));
end
axis tight;
%% paradigm-specific times
if isfield(EC_info.info,... |
33ee4da82ec92c9d81db9452e67dbad4dbba1b634e7e7ea5d574690fb4715ca0 | MATLAB | 1,513 | 63 | function opt=surfing_afni_opts2string(varargin)
% translates options as used in AFNI from arguments to a string
%
% OPT=SURFING_AFNI_OPTS2STRING(...) takes the input arguments and converts
% them to a string as used in AFNI programs.
% The input arguments can be of any type accepted by surfing_struct, e.g. a
% struct ... |
27de5e17b7965e041843ab1c1d31b7af8f1f2c20a637e90aac9d8d622456d159 | MATLAB | 1,515 | 47 | function coals = calccoalitions(ths, thr)
N = length(ths);
coals = 1:N;
while(true)
phis = zeros(N,N);
% find the two most synchronous oscillators/coalitions
for i=1:N
thsi = angle(calcphi(ths(coals == i)'));
for j=i+1:N
phis(i,j) = ...
calcphi([thsi, angle(... |
3fd5b7de63cde36cec8a547d946dd38140a82174a736b4a44b1c411494423910 | MATLAB | 1,515 | 39 | %% key = sepiatest.qsm_method_toolbox_key(qsmMethod)
%
% Description: maps a QSM dipole-inversion method name (as it appears in
% methodQSMName, sepia_universal_variables.m) to the field name in
% sepiatest.discover_toolboxes()'s output struct that gates whether it
% can run on this machine. Returns 'none' for methods ... |
8b8dba1fc86bd297dd4548fbe4aa2618544a2f6e3dfa31183f4b05c4ecfafac1 | MATLAB | 1,515 | 45 | function outputImage = cumsum(this, applicationDimension)
% Computes cumulative sum along specified dimension, uses Matlab cumsum function
%
%
% Y = MrImage()
% Y.cumsum(applicationDimension)
%
% This is a method of class MrImage.
%
% IN
% applicationDimension image dimension along which operation is
% ... |
de63a8829260e23c84eba03d8db9dd8d9cc993017b5c0ca185b4ff294e1c892c | MATLAB | 1,516 | 59 | function [ surf_con ] = nf_concat_surf( surf_A, surf_B )
%[ surf_con ] = nf_concat_surf( surf_A, surf_B )
% Vertically concatenates two surface struct (taking care of special fields)
% expects .faces/.vertices (Matlab-style) or .pos/.tri (Fieldtrip style)
f_A=fieldnames(surf_A);
f_B=fieldnames(surf_B);
f_all=unio... |
1c7aa588ecfd58e434100938aa35d84998d417033bf362366393914aac199cc9 | MATLAB | 1,517 | 47 | function plotPvalHistograms(pvals, labels, colors, outname)
if nargin < 4 || isempty(outname), outname = 'pval_histograms'; end
if nargin < 3 || isempty(colors) || size(colors,1) < numel(pvals)
colors = lines(numel(pvals));
end
figure('Color','w','Position',[300 300 700 450]); hold on; bo... |
47e3fccb58a7c0ff3ea96a391eaf4f8df338d10e29ef70410914918e02d91fd2 | MATLAB | 1,517 | 43 | %% bgColor = sepia_theme_bg_color()
%
% Output
% --------------
% bgColor : background colour (RGB triplet) for interactive uicontrols
% (edit/popup/pushbutton fields)
%
% Description: Returns a background colour for interactive uicontrols
% that keeps them legible under both MATLAB's classic light deskto... |
74c0129b0f01322d785512b0e9598bc0247968a6df418ed4ed878eb70c09d172 | MATLAB | 1,517 | 56 | function [output,options]=bpAssistMoco(input,varargin)
% perform motion correction in 2 steps, with a band-pass spatial filtering
% first. User can input as a variable arguemnt a computed shift
options.findBestBP=false;
options.vectorBandPassFilter=[2 20];
options.applyshit=[];
options.windowSize=1000;
options.spatial... |
aec4e0965e2923daa0591b998fabbb3ab6534a812b8f7d85f4a251c265be8b3a | MATLAB | 1,518 | 53 | function [axishan, pointhan, surfhan] = plot_points_near_regions_on_surface(DB, r, wh_points, color)
% [axishan, pointhan, surfhan] = plot_points_near_regions_on_surface(DB, r, wh_points, color)
%
% DB: Database of meta-analysis coordinates, from Meta_SETUP.m
% r: region object with clusters of regions
% wh_points: 1/... |
7fc21ca60fbe0118f1e12158da20bc05e4b5ff5a4c4dbf86b66ddafd31c4a92b | MATLAB | 1,519 | 34 | function [ Hc, coals] = coalitionentropy(ths, Cth)
if nargin < 2
Cth = 0.8;
end
% For data Xt, consisting of channels Xi,t, i = 1, ?, n, we consider two channels to be in synchrony at time t if the absolute value of the difference between their instantaneous Hilbert phases is less than 0.8 radians (approximately 45... |
4eaff061fa7cb0697bc102f165e79c86033e8cf9974b5f1d732e6865796bb348 | MATLAB | 1,520 | 46 | function this = apply_transformation(this, otherGeometry)
% Performs affine transformation on Geometry by multiplying of 4x4 affine matrix
%
% Y = MrImageGeometry()
% Y.apply_transformation(otherGeometry)
%
% This is a method of class MrImageGeometry.
%
% IN
% otherGeometry MrImageGeometry holding the affine tr... |
e763fd60f0ed679d6ab376bea4c705ee1fdda9271a10cdc8da3c77004f0a04e3 | MATLAB | 1,520 | 71 | function [gwf, rf, dt, ti, rwf] = sero_pulseq_getBlockWaveforms(seq, blockInd)
% function [gwf, rf, dt, ti, rwf] = sero_pulseq_getBlockWaveforms(seq, blockInd)
if nargin < 2 || isempty(blockInd) || all(blockInd == 0)
blockInd = [1 numel(seq.blockEvents)];
end
if isscalar(blockInd)
blockInd = [1 1]*blockInd;
e... |
34022c3e3cb8a6093e53216b307193c1de6231654bd03f1a00cee3cbd29b4516 | MATLAB | 1,521 | 58 | function M = diffusionTermCylindrical1D(D)
% This function uses the central difference scheme to discretize a 1D
% diffusion term in the form \grad . (D \grad \phi) where u is a face vactor
% It also returns the x and y parts of the matrix of coefficient.
%
% SYNOPSIS:
%
%
% PARAMETERS:
%
%
% RETURNS:
%
%
% EXAMPLE:
%
... |
c2766ccbbd61890d0d84a715c918d352a8fde536f6e711a2e34f9f6ad6f22167 | MATLAB | 1,521 | 44 | % Please cite this paper if you use any component of this software:
% D. Cunefare, L. Fang, R.F. Cooper, A. Dubra, J. Carroll, S. Farsiu, "Open source software for automatic detection of cone photoreceptors in adaptive optics ophthalmoscopy using convolutional neural networks," Scientific Reports, 7, 6620, 2017.
% Re... |
da382837a548cbb2e883ae5feb61bf45a6891bf8eef8171ad12f07381b6bfb61 | MATLAB | 1,521 | 65 | function data = getImageBatch(imagePaths, varargin)
% GETIMAGEBATCH Load and jitter a batch of images
opts.useGpu = false ;
opts.prefetch = false ;
opts.numThreads = 1 ;
opts.imageSize = [227, 227] ;
opts.cropSize = 227 / 256 ;
opts.keepAspect = true ;
opts.subtractAverage = [] ;
opts.jitterFlip = false ;
opts.jitt... |
bc9141ac969fedbcd9424d9139e85b35bf06872523683a19b67c84093d7cf652 | MATLAB | 1,522 | 53 | function t = ARFIT_tquant(n, p)
% TQUANT Quantiles of Student's t distribution
%
% TQUANT(n, p) is the p-quantile of a t distributed random variable
% with n degrees of freedom; that is, TQUANT(n, p) is the value below
% which 100p percent of the t distribution with n degrees of freedom
% lies.
% Modified 13-J... |
db98770c1cafbe5395390de9a37aeb013664a52db20c9ab60a0eef72f1c755a3 | MATLAB | 1,522 | 51 | classdef nnroipool < nntest
properties
x
end
properties (TestParameter)
method = {'avg', 'max'}
subdivisions = {[1 1], [2 1], [1 2], [3 7], [16 16]}
end
methods (TestClassSetup)
function data(test,device)
% make sure that all elements in x are different. in this way,
% we can com... |
022beb624debb4ef843dbd1f4926e33f7ceed302aa821f27cebd521f4f78a763 | MATLAB | 1,523 | 64 | function [data, V, ve] = pca4Regression(data, nPCs, rotate, denoise, meanSubtract)
% data is a struct of matrices in the field "data", each matrix is
% observations x variables
nChunks = length(data);
dataMat = vertcat(data.data);
nCols = size(dataMat, 2);
if nPCs < 1 % accept a fractional percentage of total number... |
2a37f1b05489c11c66644dbe80d0439e058f9bad512bf4e52d6499d1442fb24e | MATLAB | 1,524 | 53 | %% get_set_bfr_lbv(h,mode,input)
%
% Input
% --------------
% h : structure contains all handles of SEPIA
% mode : 'set' - extract information from GUI to config file
% 'get' - extract information from config file to GUI
% input : if mode is 'set' then input should be fid
% ... |
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