sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
ffd216e2fda1d62d246a388e894f31cb5fea0a094dd1f662aea59cce4493f48b | MATLAB | 1,748 | 74 | function [condNumbers,condLabels] = read_ctf_cls(fname)
% READ_CTF_CLS reads the classification file from a CTF dataset
% Copyright (C) 2003, Ole Jensen
%
% This file is part of FieldTrip, see http://www.fieldtriptoolbox.org
% for the documentation and details.
%
% FieldTrip is free software: you can redistribute ... |
1df89cc363a468cc32e951f4451cbd4c9dd46388d6cacb97de7817021c4f3e00 | MATLAB | 1,749 | 32 | function activations = load_encoding_activations_allsubs(paths_activations, tr_duration)
run('set_library_paths.m');
addpath(SPM_PATH); % for spm_hrf convolution
activations = [];
disp('Loading encoding model activation timecourses')
n_subjs = length(paths_activations);
fprintf('Current su... |
52faa6fdf0887bbd0fb7903461f1a7ffbfb77d211d42d3c791ef7fcd2871fe4a | MATLAB | 1,749 | 56 | function [output, firstIndexPoint] = read_bti_hs( filename, outfile)
%read_hs_file Reads in BTI-Headshape files
% filename: file with the headshape informations
% outfile: if present, a ctf ".shape" file is written
% output: if present, a 3xN matrix containing the headshape-points
%
% (C) 2007 by Thomas Hartma... |
6cb35ede793aee0d13e1af8daca0de05866f143596eced2c404a68be18c1c5a3 | MATLAB | 1,749 | 49 | function [] = select_types()
%% Ask user to define which plots to generate and which analyses to save
global info
plottypes = {'Plots Only', 'No Plots', ...
'Distance Ratio', ...
'Mean Speed', 'Pathlength', ...
'Instant Speed', 'Travel Path', ...
'Final location in gradient', 'Change in gradient locati... |
1c78877c440cfa16434cef8742b7b0f5c3ccb266cbcdbb7b027a2f422aaa5c5e | MATLAB | 1,750 | 26 | % startup.m
if ispc
drive = 'Z:' ;
elseif ismac
drive = [filesep 'Volumes' filesep 'lab'] ;
else
drive = [filesep 'mnt' filesep 'lab'] ;
end ;
setenv('DJ_HOST', 'at-database.ad.bcm.edu');
setenv('DJ_USER','spatel');
setenv('DJ_PASS','spatel12');
addpath([drive filesep 'home' filesep 'atlab' filesep 'pipeline... |
dab6627782af1625f07a6f8613be279876bf9772a0d73e678a80c1a793c1419d | MATLAB | 1,750 | 66 | function truncated_svd_bfgs_test(A, p)
% Generate some random data to test the function if none is given.
if ~exist('A', 'var') || isempty(A)
A = randn(402, 500);
end
if ~exist('p', 'var') || isempty(p)
p = 5;
end
% Retrieve the size of the problem and make sure the req... |
f71284f2b2149e21030b03263a267b70bc700d3e3525ca3802497e3fc814484c | MATLAB | 1,750 | 51 | function this = apply_inverse_transformation(this, otherGeometry)
% Applies inverse of given transformation (as an Image geometry) to this
%
%(e.g. given mapping stationary -> transformed image transformation that
% now shall be applied to transformable image to warp into space of
% stationary image )
%
% Y = MrAffin... |
2281619cfeb1564c7bd217bf157dde94334d1160c609d27ea8dd78e19ea56f36 | MATLAB | 1,751 | 51 | function available = buffer_wait_dat(selection, host, port)
% BUFFER_WAIT_DAT implementation that is also backwards compatibility with ft buffer version 1
%
% Use as
% available = buffer_wait_dat(selection, host, port)
% where
% selection(1) = nsamples, 0 indicates not to wait
% selection(2) = nevents, 0 indica... |
3433fac557f1f1f8b81e11b0b46ce9b972228a6600504c439787d5423545e624 | MATLAB | 1,751 | 44 | function out = DN_TrimmedMean(y, n)
% DN_TrimmedMean Mean of the trimmed time series using trimmean.
%
% ---INPUTS:
% y, the input time series
% n, the percent of highest and lowest values in y to exclude from the mean
% calculation
% -----------------------------------------------------------------------------... |
da645afccd3c0d978bd96e2ace2a45ee9bded28c4a3a1f7473b54cf65f7a92cd | MATLAB | 1,751 | 45 | % checkRequiredToolboxes - Checks for required MATLAB toolboxes.
% If any are missing, an error is returned.
function checkRequiredToolboxes(toggles)
if toggles.parallelization
required_toolboxes = {'Optimization Toolbox', ...
'Parallel Computing Toolbox'};
else
required_tool... |
816be1e2fed0bbf3a446354813902d91b3ebdb771fb5b9df56aa9c15bfcd2a0c | MATLAB | 1,753 | 55 | function newTarget = ReturnToGoodies(newRoot)
% Function uses a previously selected vector stored in SelectedVector and
% generates a permutation of the vector at the called position and
% introduces the vector as the new target vector.
global numFact numDose
global TabuList
% Generate a pool of vec... |
87a438e73196979ff8a2275210eb25d36b6860fc734ee0c5765092eb01f941a8 | MATLAB | 1,753 | 58 | function features = FD_clVAE_extractFeatures(img)
newMin = 0;
newMax = 1;
redChannel = double(img(:, :, 1));
greenChannel = double(img(:, :, 2));
blueChannel = double(img(:, :, 3));
gray = double(rgb2gray(img));
% relative channel proportions
rd = redChannel./(redChannel + greenChannel + blueChannel);
... |
c10eecddffca054cd2f3d6c288d42873a03c820a2de60d6a6db5e44d6062689d | MATLAB | 1,753 | 72 | function [fid, pnt, label] = read_ctf_pos(filename)
% READ_CTF_POS reads Polhemus file created with the CTF digitizer application
%
% Use as
% [fid, pnt, label] = read_ctf_pos(filename)
% Input:
% filename - Polhemus ASCII file containing digitized points
%
% Output:
% fid - fiducial locations of fiducial... |
6361fbf3d989ab1153ab5641fdb0de082243cd6a032ba8ee12f33195c5924536 | MATLAB | 1,754 | 44 | function colormap = BF_MakeBrightenedColorMap(rgb,numGrads)
% BF_MakeBrightenedColorMap Given an rgb vector, progressively brightens into a colormap
% ------------------------------------------------------------------------------
% Copyright (C) 2013-2026, Ben D. Fulcher <ben.d.fulcher@gmail.com>,
% <http://www.benfu... |
7f8286ada1c38106eef1a5d57b9d4904a344b8bd78e5691480e0034258b20d85 | MATLAB | 1,754 | 58 | %% [h_text,h_edit] = sepia_construct_text_edit(parent,fieldString,defaultValue,pos,subratio)
%
% Input
% --------------
% parent : parent of the constructs
% fieldString : text to be displayed in the 'text' field
% defaultValue : default value in the 'edit' field
% pos : position of the constructs, ... |
1b9c76a4a5fbeea110e4ac61196a28e60bcdeb11321de210d7dc7c0c469f0197 | MATLAB | 1,755 | 56 | function this = permute(this, order)
% Permutes image geometry
%
% Y = MrImageGeometry()
% Y.permute(order)
%
% This is a method of class MrImageGeometry.
%
% IN
% order [1, 3] vector or permutation of 1:3 indicating order
% of dimensions after permutation.
% Note: if only a subset of 1:3 i... |
1e352359b2b44c94607b6e037947876e8a549f4f1e27bb7bfaa58eb20dd706aa | MATLAB | 1,755 | 83 | %% [r2s, t2s, m0] = R2star_pi(img,te,m0mode,method)
%
% Input
% --------------
% img : multiecho images, time in last dimension
% te : echo times
% m0mode : method to compute m0, 'default','weighted','average'
% method : method to compute R2* ('interleaved; or '1stecho')
%
% Output
% ... |
72c5cda97d008301b1d0110f8c2fe44d2eb2ad51867a85e40b4ad3055483ee7c | MATLAB | 1,755 | 54 | %PDIST vl_nnpdist dagnn wrapper
% Accepts 2 or 3 inputs, where third input is used as variable
% 'instanceWeights' parameter. Derivatives for the 3rd input are not
% computed.
% By default aggregates the element-wise loss.
classdef PDist < dagnn.Loss
properties
p = 2;
aggregate = true;
noRoot = false;... |
7747525f49a5e65d46b0b0f9e40e20ef0146516a111ee8dbcf53bec77e1a2219 | MATLAB | 1,755 | 39 | % Bidirectionally aligns 3D movie
% Input: movie, an x*y*t 3D array
% Output: movieL, an x*y*t 3D array
function movieL = bidi_align(movie)
% subpixel computation of the shift for each image of the stack
shifts = zeros(size(movie,3),1);
cross_template = zeros(size(movie,2),1)';
cross_template2 = zeros... |
77975f8b8425dc049ef4bebe4e61bfe109bada5ba76ce528c301d6c7db69d99a | MATLAB | 1,755 | 65 | x = rawData(:,1);
%% sgolay
wSize = 251;
ord = 2;
tic;
sgData = sgolayfilt(x, ord, wSize);
tSg=toc;
%% asg
wSize = 251;
ord = 2;
rOffset = 0.1*500;
tic;
%smoothKernel = SavitzkyGolay([-(wSize-rOffset-1),rOffset],'PolynomialOrder',ord); !!! WRONG, has to be in reversed order???
smoothKernel = flipdim(SavitzkyGolay([... |
924cdb6cebd19d9be8e364f954e5b2610faa3fdb0d96f1e25f0ea94d6ef30b10 | MATLAB | 1,755 | 65 | function h = mysigstar(ax, xpos, ypos, pval, color, pexact,pname,fz)
% replaces sigstar, which doesnt work anymore in matlab 2014b
if ~exist('fz','var'); fz = 16; end %add name of test
if ~exist('pname','var'); pname = ''; end %add name of test
if ~exist('pexact','var'); pexact = false; end %print exact pvalue instead... |
b742a3ce0c1b83ecde565c1983198514fac7747d0cec7214c127342ffd7f3541 | MATLAB | 1,755 | 54 | function [sideOnByDelay, AUC, baseline] =...
DA_ResponseByDelay(pdata, bdata, bins,...
auc1, auc2, bl1, bl2)
% DA_ResponseByDelay - calculates average DA response by reward delay
% INPUTS:
% pdata - photometry data
% bdata - corresponding behavioral data
% bins - bins for delays
% auc1 - time point for ... |
c50b7797b3aca358c86ca8bf63c5d92b2c4d55c2a3b6dd446ea0642211c54602 | MATLAB | 1,756 | 74 | function obj = update_latent(obj)
N = numel(obj.data);
D = prod(obj.lat);
% ----------------------------------
% precision (common across subjects)
% ----------------------------------
% Common to all subjects so we pre-compute the value
% > Az = A + lam * (U'*L*U + inv(Au))
obj.Az = ... |
ef6a3437fad7b12b48a638c29d2ec234e16119ce60cbc49d9bc85f4331ef9900 | MATLAB | 1,756 | 60 | function makeGifti(file,varargin)
% function rsa_makeGifti(file,varargin)
% Convert file into the GIFTI file format and write it into
% the same directory. Aligns surface with the volume anatomical for the
% subject.
%
% INPUTS
% file: full path and file name for the file to be converted
%
% USEROPTIONS / VARARGIN:
... |
4113697d90ffa2e12a6d9e378a9e7057caac9d5ee372e3be90346154ff8c3e72 | MATLAB | 1,757 | 45 | function band_signal = modwt_single_band(data, wavelet_type, level, target_band)
% MODWT_SINGLE_BAND - Decompose and reconstruct a single wavelet band
%
% Convenience wrapper that performs MODWT decomposition and then reconstructs
% only the requested band. Optimized for memory efficiency in incremental
% band processi... |
97aa4015ad5207a2fbfe7ba8535b67ac0ba2933aeaa618040dd7652c57ee7acc | MATLAB | 1,757 | 61 | function [spatial] = Setup_Storage(step_cap, C1, C2, C3, myelin)
% SETUP_STORAGE
%
% Preallocates storage for spatial simulation outputs across all timesteps.
% Stores positions of cell populations (C1, C2, C3) and myelin state data.
%
% INPUTS:
% step_cap - total number of timesteps
% C1, C2 - initial ... |
c462c31cd8c8b87f8d4e9a1d0df0dc2723ce4c2499e686ec840eb546a8aaf120 | MATLAB | 1,757 | 64 | %specify clusters to load
% load rezFinal
% ScalD = 10;
SelectCh =[1:32];
% [d, timestamps, info] = load_open_ephys_data(sprintf('100_CH%d.continuous',1));
% [b1, a1] = butter(3, [rez.ops.fshigh/rez.ops.fs,rez.ops.slow/rez.ops.fs]*2, 'bandpass');
% inx1 = round(1:length(d)/30);
% inx2 = round([length(d)/2:(length(d)/... |
8a009b0b1d070450b893ca29bd55155c78e428c91042c7376dce04fd57994299 | MATLAB | 1,758 | 39 | %{
preprocess.CircleMap (computed) # my newest table
# add primary key here
-> preprocess.Eye
-> preprocess.CirclesLookup
-----
# add additional attributes
map : mediumblob # map of cluster membership, i.e. how many eye
# positions lie within a radius centered at each element in the map
x... |
c474dc7b01330ce7f87f781887bda625c4e771938b7d39c3ffd49d2703f42448 | MATLAB | 1,758 | 54 | %PDIST vl_nnpdist dagnn wrapper
% Accepts 2 or 3 inputs, where third input is used as variable
% 'instanceWeights' parameter. Derivatives for the 3rd input are not
% computed.
% By default aggregates the element-wise loss.
classdef PDist < dagnn_bc.Loss
properties
p = 2;
aggregate = true;
noRoot = fal... |
e597ad1793a67c7b1c4af0be47b6d3820111b34468784d27d471336336e2ed38 | MATLAB | 1,758 | 48 | function [fileNameArrayMatch, fileNameArrayResiduals] = ...
tapas_uniqc_find_info_file(fileNameArray, matchString)
% Searches a fileNameArray for uniqc file names except for matchString
%
% output = tapas_uniqc_find_info_file(fileNameArray, matchString)
% dimInfoFiles = tapas_uniqc_find_info_file(fileNameArray,... |
ffae6f831fa98eb7720a00e3bdf97a2f79d6b064c8d6437e22d32dc58e6d88e4 | MATLAB | 1,759 | 62 | function S=afni_niml_readsimpleroi(fn)
% Reads a AFNI NIML ROI dataset (extension ".niml.roi")
%
% S=AFNI_NIML_READSIMPLEROI(FN) reads an AFNI NIML .niml.roi dataset and
% returns a struct S with the ROIs.
% If FN specifies N rois, then S is a Nx1 cell with structs with the
% following fields:
% .Label string ... |
187af734440b9c7e9fedc72b0ab87d97142ad6a3cdb0c7d2e6ebcfce4504e77e | MATLAB | 1,760 | 61 |
function [Mout,Qout,num_repeats] = mod_consensus_cluster_iterate(adjM,threshold,repNum)
% Written by H Smith, Cambridge, 2020
% Consensus clustering method from Lancichinetti & Fortunato, 2012, to
% produce modularity groups from methods of community detection that can
% produce different groups for each clas... |
5078fc9783eed16f64a03ac8e67759368dfda2cb75d653dc07140ef0cb0d929b | MATLAB | 1,760 | 53 | function [patternId,stimPatterns] = checkStimPattern(candidatePattern, stimPatterns, stimTimeDiffThreshold)
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
% Parameters
% -----------
% stimTimeDiffThreshold : consider these patterns the same if the mean difference in stim times
% is le... |
2901e36371e4c9cda3425a33fed6d6377ef46e4ddbdb34fe1afb7f044e56b43f | MATLAB | 1,761 | 51 | function model_object = SLM_model(data_obj, tc, alpha, dta, r, f0)
%% the below is based on ChatGPT's translation of Ryan Greenhalgh's slm_hyp1f1_model in models.py from pyforce
%% created 7/4/2025
% Extract the necessary data
f = data_obj.fdt(1, :); % force or signal
d = data_obj.fdt(2, :); ... |
2dc10a31cb69b8e22a6b03cb5c337c39b44358bb46f66461b84eee6c7ae76d34 | MATLAB | 1,761 | 54 | function [p,tbl,stats] = multcmp_stats_on_struct( input_struct, varargin )
test_type = 'anova';
displayopt = 'off';
for v = 1:numel(varargin)
if(strcmp(varargin{v},'test_type'))
test_type = varargin{v+1};
elseif (strcmp(varargin{v},'displayopt'))
displayopt = varargin{v+1};
elseif (... |
6a0d0ebb10a2eef712198be40779cb914fdb8fa22f7f805d5a7374a5783a3f5f | MATLAB | 1,761 | 53 | function this = specify_and_estimate_1st_level(this)
% Specifies the 1st level design of the MrSeries.
% Uses SPM's specify 1st level function.
%
% Y = MrSeries()
% Y.specify_1st_level(inputs)
%
% This is a method of class MrSeries.
%
% IN
%
% OUT
%
% EXAMPLE
% specify_1st_level
%
% See also MrSeries
% Author:... |
70f141572226d35486585ecac5a641c904a25eb90361ef046d712ddf66e8990d | MATLAB | 1,761 | 47 | function varargout = covSE(mode, par, varargin)
% COVSE Squared Exponential covariance function with unit amplitude.
%
% Report number of hyperparameters
% s = COVSE (mode)
% s = COVSE (mode, par)
% s = COVSE (mode, par, hyp)
%
% Evaluation of k(x,x)
% k = COVSE (mode, par, hyp, x)
% k = COVSE (mode, par... |
846fe665a1eed0ce2bda43d825a3503054b681bd0d7b6e1c2f86fee17d33f79b | MATLAB | 1,761 | 65 | function sliceThick = sero_pulseq_plotSliceProfile(rfShape, rfTime, gAmp, flipAngle, sliceThick, dz, do_rewind)
% function pulseq_plotSliceProfile(rfShape, rfTime, gAmp, flipAngle, sliceThick, dz, do_rewind)
[M, z, sliceThick] = sero_pulseq_sliceProfile(rfShape, rfTime*1000, flipAngle, mr.convert(gAmp, 'Hz/m', 'mT/m')... |
bb9e8c5b9c7fb329decf5135a80b8742109ea30d31a69ebc9469f555c6dc5fd7 | MATLAB | 1,761 | 56 | % 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... |
c4ec71b007f6570d6d22b162518f194906ab352f6fd23c1b691544dce4f2be28 | MATLAB | 1,761 | 64 | function [state] = tapas_sem_multiv_init_state(data, model, inference)
%% Generate the structure of the states of the sampler.
%
% Input
%
% Output
%
% aponteeduardo@gmail.com
% copyright (C) 2016
%
nc = size(model.graph{1}.htheta.T, 2);
ns = size(data, 1);
mu = model.graph{4}.htheta.y.mu;
nb = numel(mu... |
3d0dead0ca321f1016fab2b4592d06f4d49f2464bdbcd7365a1917d9d6af7dc8 | MATLAB | 1,763 | 67 | function DBRemove(database)
%DBRemove - Remove database.
%
% Actual removal will require confirmation from the user.
%
% USAGE
%
% DBRemove(database)
%
% database database name
%
% SEE
%
% See also DBRemove, DBRemoveFigures, DBRemoveVariables.
%
% Copyright (C) 2007-2016 by Michaël Zugaro
%
% This p... |
6c547e9ebefaaa6a6eae714d6b200bf47310c8f272e6c090620fdd5b78bd8da5 | MATLAB | 1,763 | 36 | % NDIMS - number of dimension of memory mapped underlying array
%
% Author: Arnaud Delorme, SCCN, INC, UCSD, Nov. 2008
% Copyright (C) 2008 Arnaud Delorme, SCCN, INC, UCSD
%
% This file is part of EEGLAB, see http://www.eeglab.org
% for the documentation and details.
%
% Redistribution and use in source and binary for... |
afdf917330508e02ca217c5cd627bd8220365bfe0fe2c037deae050232ec811b | MATLAB | 1,763 | 52 | % Phantom 2D small example. Compare potentials in 3 points.
% Validating superposition property
% Author: Aina Frau-Pascual
% Input image
im = phantom(10);
im = im(2:end-1,3:end-2);
% Construct mesh structure
Lx = size(im, 1); % domain length
Nx = size(im, 1); % number of cells
Ly = size(im, 2); % domain length
Ny ... |
d39332a3f25f0ffdfac205d88a34e4313f4599c1ee4a5fde3368e6f794d5ea35 | MATLAB | 1,763 | 56 | function [AR, RI, MI, HI] = RandIndex(c1, c2)
%RANDINDEX - calculates Rand Indices to compare two partitions
% ARI=RANDINDEX(c1,c2), where c1,c2 are vectors listing the
% class membership, returns the "Hubert & Arabie adjusted Rand index".
% [AR,RI,MI,HI]=RANDINDEX(c1,c2) returns the adjusted Rand index,
% the unadjust... |
1e0824ed3a8cc357f65b413eccad018bcc2b9e6a0d8311da3bc64c52ac708207 | MATLAB | 1,764 | 56 | function outputImage = smooth(this, varargin)
% Smoothes image (or image time series) spatially with sinc-truncated Gaussian kernel,
% i.e., using spm_smooth and mimicking its functionality
%
% Y = MrImageSpm4D()
% sY = Y.smooth('fwhm', fwhm)
%
% outputImage is a method of class MrImageSpm4D.
%
% NOTE: For comple... |
e1a0c971619b17cb2af7352f37c7e1b7e22586bd443ba660964cc4bbc5e1338e | MATLAB | 1,765 | 51 | function outputImage = mean(this, applicationDimension)
% Computes mean along specified dimension, uses Matlab mean function
%
%
% Y = MrImage()
% Y.mean(applicationDimension)
%
% This is a method of class MrImage.
%
% IN
% applicationDimension image dimension along which operation is
% ... |
13de4bc811953768ba16aaa6702ded83e17400fff5beeb480b77bd2729812482 | MATLAB | 1,766 | 61 | function rho = WeightedCorrCirc(weights,x,alpha)
% Provide a matrix of weights, and this function will check the
% correlation between the X and Y dimensions of the matrix.
% You can provide the X-values and the (angular) Y-values for
% each column and row.
if exist('x','var') && ~isempty('x'),
if isvector(x), ... |
be02ad31d200f570c5451ef043e98f23a2e9b437a388cc1757cfc9771108f639 | MATLAB | 1,766 | 65 | %% ext = get_nifti_extension_from_input(input)
%
% Input
% --------------
% input : input directory (char/string) or structure containing input
% NIfTI filenames, as accepted by the SEPIA I/O wrappers
%
% Output
% --------------
% ext : '.nii' if the input data uses uncompressed NIfTI,
% ... |
80b83931f70da534c17eb626855540b45b190a8263a83ce824d6647b4d1aa0cb | MATLAB | 1,767 | 57 | function [ijkoffsets,distbox,m3]=surfing_spherical_mask(radius,voxelsize)
% constructs a sphere-shaped mask for use in a 3D volume (e.g. searchlight)
%
% [OFFSETS,BOX,M]=SURFING_SPHERICAL_MASK(R,VOXSIZE) returns
% a set of linear offset values and a box with computed distances from the
% center, using a mask radius R... |
d3831f7faf32cf87bfa68d9fcaabf148fca9fb3623e066d0ed8ce45decd74038 | MATLAB | 1,769 | 41 | %{
aod_monet.DriftTrial (computed) # noise drift trials
-> aod_monet.DriftTrialSet
drift_trial : smallint # trial index
---
-> psy.Trial
direction : float # (degrees) direction of drift
onset : double # (s) onset ti... |
bde68701ee4645fcfac9845980e09b655da054ceb330fa2e77ef3255236be230 | MATLAB | 1,770 | 50 | 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 structure, a... |
d3d94bb4e592ac420f933df31734d58fac523f270f270609dc24205fa374f656 | MATLAB | 1,770 | 54 | %% unitTest.m
% This function performs a command line unit test based on the jobTesting.m file in the
% ci folder. All Osprey modules are tested in dependence of the
% included dataset. You can change the jobTesting.m file according to your desired
% needs. The results unittest class includes detailed informati... |
db66f2e06452f306769d8b7a676e59cb26b8d62078fc6a50cc10d80bd576027f | MATLAB | 1,770 | 63 | function params = SEI_job_classDefinitions(params, clzDefName)
% defines the classes which the triggers of which are extracted from trials
% (c) Jiri, Apr22
%% job-specific settings: E-I vs. I-E
if strcmp('switchin_EI_IE', clzDefName)
% define paradigm classes
params.triggering.classes = {...
'E-I',{'E... |
7aa8ac4cdf78e78f4bf9640738bda3d3ca559c90b548b13c9fced2ca51bf95ac | MATLAB | 1,771 | 57 | % load in master information on the manifold
a1 = load('~/Dropbox/nsddata/templates/hrfs_func1mm.mat'); % hrfs is TR x different-hrfs
% fit parameters
options = optimset('Display','final','FunValCheck','on','MaxFunEvals',Inf,'MaxIter',Inf,'TolFun',1e-6,'TolX',1e-6);
fun = @(pp) pp(7)*subscript(conv(spm_hrf(0.1,[pp(1:... |
7c176722050877d79d340431ef0d8b13b28fa9370e94e4f21d6497ffecdf3869 | MATLAB | 1,771 | 49 | function [lp,dlp] = priorSmoothBox1(a,b,eta,x)
% Univariate smoothed box prior distribution with linear decay in the log domain
% and infinite support over the whole real axis.
% Compute log-likelihood and its derivative or draw a random sample.
% The prior distribution is parameterized as:
%
% p(x) = 1/w*sigm... |
c51e4deabc0823fd3a345a8278fd3b98a7170735c55668e334233d2eafbbb694 | MATLAB | 1,771 | 48 | function [rez,chan] = split_cluster(rez)
M_clust = length(unique(rez.st(:,end)));
chan = NaN(1,2*M_clust);
Nrank = 3;
del = [];
for i =1:M_clust
Spike_id = find(rez.st(:,end)==i);
channel = rez.Merge_cluster{i,5};
Nchan = length(channel);
PC = rez.PC{i};
if isempty(PC)
rm = rez.st(:,end)==... |
e453c63ccdd6a42085041f21493f6bdb12672104d640f595aa27b14c3f6050b9 | MATLAB | 1,771 | 48 | function [rez,chan] = clean_cluster(rez)
M_clust = length(unique(rez.st(:,end)));
chan = NaN(1,2*M_clust);
Nrank = 3;
del = [];
for i =1:M_clust
Spike_id = find(rez.st(:,end)==i);
channel = rez.Merge_cluster{i,5};
Nchan = length(channel);
PC = rez.PC{i};
if isempty(PC)
rm = rez.st(:,end)==... |
1eb45d4d5234e7065dcca68ce3fd9d8fd02103731eb03d156e7be495195d3af9 | MATLAB | 1,772 | 90 | load(fullfile('.', 'data', 'dataFigureS3D.mat'));
colormap1 = [204,236,230; ...
153,216,201; ...
102,194,164; ...
44,162,95; ...
0,109,44]/255;
colormap2 = [253,212,158; ...
253,187,132; ...
252,141,89; ...
227,74,51; ...
179,0,0]/255;
figure; hold on;
for ff = 1:2
switch ff
case 1
data... |
cf46375de969728d8ea8f5dbe0279d83bed9e83eb84a5cb0d0015e2d1efa22bc | MATLAB | 1,772 | 48 | function plotOptoTrajectories(kinematics, plotParams)
% Plot trajectories from an opto dataset
% Make figure
fig;
hA = gca;
axis off
hold on;
hA.View = [-22,4];
axis equal
% Plot only right trials, opto in blue and normal in gray
optocount = 0;
normalcount = 0;
target = 2; % Rights only
for tr = 1:length(kinematics)
... |
d505567ad16f10631215d693cea8b98bf162e51aec9aab4577d4e7cf72487f74 | MATLAB | 1,772 | 57 | function tuning_summary
% summarizes the quality of mice
set(groot,'defaultAxesColorOrder', parula(4)*0.7, 'defaultAxesLineStyleOrder', '-|--|:')
von = monet.VonMises & 'segment_method=2' & 'spike_inference=2';
keys = fetch(pro(common.Animal, rf.Session, 'max(session_date)->sess_date') & monet.VonMises, 'sess_date', 'O... |
1d28ce2efe9f20bdec1b43535393aeb9d1a82ea040e0fa99a5a4a0acc2f78b60 | MATLAB | 1,773 | 63 | classdef Conv < dagnn.Filter
properties
size = [0 0 0 0]
hasBias = true
opts = {'cuDNN'}
end
methods
function outputs = forward(obj, inputs, params)
if ~obj.hasBias, params{2} = [] ; end
outputs{1} = vl_nnconv(...
inputs{1}, params{1}, params{2}, ...
'pad', obj.pad, ..... |
9d59b4d2063d988c2ca83f99e624444121d55f505f0b36b7d4e027ec94d0658f | MATLAB | 1,773 | 53 | function s = export(this,target)
% Export a GIfTI object into specific MATLAB struct
% FORMAT s = export(this,target)
% this - GIfTI object
% target - string describing target output [default: Matlab]
% s - a structure containing public fields of the object
%______________________________________________________... |
a3741caf913af40eb5ea553b6d3257b82bb1659fa98e8e23ed4ef1518c129389 | MATLAB | 1,773 | 57 | %issamples - Test if parameter is a list of samples satisfying an optional list of tests.
%
% A list of <a href="matlab: help Samples">samples</a> is a vector or matrix of doubles containing at least one column
% for (sorted) timestamps, and optionally more for continuous variables.
%
% USAGE
%
% test = issamples... |
a3eb8abeff1e9ee1f05d3f55e90c5811bcb47a3ff1e2e505a24af69b0b1d4512 | MATLAB | 1,773 | 60 | function [handleImageArray, nameImageArray] = get_all_image_objects(this, type)
% Returns cell of handles & names for all/selected image objects in MrSeries
%
% Y = MrSeries()
% [handleImageArray, nameImageArray] = Y.get_all_image_objects(inputs)
%
% This is a method of class MrSeries.
%
% IN
%
% OUT
% handleImage... |
266d85e86cdf0b9d91b86c59cc1d4654104d3ec18c4656addf7db5c653f7dfbc | MATLAB | 1,774 | 51 | function download_toolboxes()
% One-stop setup: checks every SEPIA add-on that can be fetched
% automatically (FANSI, HEIDI, Tensor-MP-PCA) and downloads whichever
% ones are missing, instead of you having to call each
% download_<toolbox>_toolbox() script separately.
%
% Safe to run repeatedly - each individual setup ... |
0215daf384fcf93ef54879026e05848664bae24913506a02f7fbb35b09310ab4 | MATLAB | 1,775 | 40 | function [edges, nodes] = load_inputs(cfg)
% LOAD_INPUTS Load edges and optional nodes; ensure RSN columns on edges.
% Load edges
epath = fullfile(cfg.data_dir, cfg.edges_file);
[~,~,ext] = fileparts(epath);
switch lower(ext)
case '.csv', edges = readtable(epath);
case '.mat', S = load(epath); assert(isfield(... |
2119f7c0d31773fce9240e7cf3e09b97c734f48374764c1d2d199f67a22690ad | MATLAB | 1,775 | 104 | function c = perform_contour_extraction(M, t)
% perform_contour_extraction - exctract the geometry of
% a black contour.
%
% c = perform_contour_extraction(M, t);
%
% the output is a sampled curve in [0,1]x[0,1]
%
% Copyright (c) 2004 Gabriel PeyrŽ
if nargin<2
t = mean(M(:));
end
if M(1)<t
M = 2*t-M... |
fed46b0799b68cffa8c9197b60f277cb16ad22c8502b7c1bfed94f3a077701d2 | MATLAB | 1,775 | 39 | function LowDimDisplayTopLoadings(numTopLoadFeat,numPCs,pcCoeff,pcScore,TS_DataMat,Operations)
% LowDimDisplayTopLoadings Display feature-loading-onto-PC info to screen
% ------------------------------------------------------------------------------
% Copyright (C) 2013-2026, Ben D. Fulcher <ben.d.fulcher@gmail.com>,... |
2ef0bc9d12a8f63d5a5a22433c9539f3a76fe4a39e55c3d22c895681cd7dcb23 | MATLAB | 1,776 | 63 | classdef Conv < dagnn_bc.Filter
properties
size = [0 0 0 0]
hasBias = true
opts = {'cuDNN'}
end
methods
function outputs = forward(obj, inputs, params)
if ~obj.hasBias, params{2} = [] ; end
outputs{1} = vl_nnconv(...
inputs{1}, params{1}, params{2}, ...
'pad', obj.pad,... |
603b7cb8d2f8b49ac2b9327ab06abdd7633ba3d7b061d1a3bcd3ca3a170dca0a | MATLAB | 1,777 | 54 | function spikeTimesStimRemoved = removeStimSpikes(allStimTimes, spikeTimes, Params)
%REMOVESTIMSPIKES Remove spike times around the stimulation time
% INPUTS
% ----------
% allStimTimes : vector
% vector of size (numStimTimes, 1)
% stimulation times in seconds
% spikeTimes : cell
% cell of size (1, numChan... |
6f703f268f28e74ae42221ee8036e385522346d3f3efe48ec2037aebc0b6de30 | MATLAB | 1,777 | 39 | function mask = transientmask(trace, dTmin, nsigmarise, nsigmadecay, sigma)
% Make a mask that identifies the significant transients in a calcium
% recoridng that cross the nsigmarise and last until crossing nsigmadecay.
% Adapted from Dombeck et al., 2007.
% Note H.-L. Chen: dTmin is in unit of frame numbers (inde... |
ff9eba2f26c8f30aa610391fd113dc3208d51548f4ee7cebd0afeaf45b349042 | MATLAB | 1,777 | 49 | % Script demo_bayes
% 1st level model specification and estimation using a Bayesian estimation
%
% demo_bayes
%
%
% See also
% Author: Saskia Bollmann & Lars Kasper
% Created: 2018-05-04
% Copyright (C) 2018 Institute for Biomedical Engineering
% University of Zurich and ETH Zurich
%
% This fi... |
0519e201be58ed59e1f6f40f8cdf7ad47a61ad226bd1a9a4df0dc90172021328 | MATLAB | 1,778 | 41 | function [U,pivcol,nonpivcol] = ref(A,tol)
%REF The (R)educed (E)chelon (F)orm of A.
% Computes the reduced row echelon form of A using partial pivoting.
%
% Formats: U = ref(A)
% U = ref(A,tol) User specifies tolerance to determine
% when ... |
212db817ddcb2860943f0e3d99a27ad0eb9e7f2ce76a789051df372309367b8f | MATLAB | 1,778 | 89 | function S=smooth3D(X,FWHM,vox)
% will apply a 3D gaussian smoothing filter to a 3D image, call with
% S=smooth(X,FWFHM,voxdims)
% FWHM is in mm - (FWHM = 2.35 * stdev)
%zero fill to required just in case it is not even elements
dimsorig=size(X);
dim = round(dimsorig(1:3)./2)*2;
if dimsorig(1:3) ~= dim
X = zero... |
98b9071daad36603497e6fead273f331dfd9e35cc468b82515e2b4b4208828a8 | MATLAB | 1,778 | 58 | function [diffGeometry, isEqual, isEqualGeom3D] = diffobj(this, targetGeometry, tol)
% Compares image geometries, and gives detailed info about differences
% (2D/3D/4D, other params)
%
% Y = MrImageGeometry()
% Y.diffobj(inputs)
%
% This is a method of class MrImageGeometry.
%
% IN
% inputGeom MrImageGeometry ... |
6c0e9b5b44b0a1c64ec8abc3ec1801e9e898cd926aa4b458a9a4c9ce2782cbcd | MATLAB | 1,779 | 64 | function fear_tripleCCG(basename)
% basename='~/data/Fear/triple/hoegaarden181115/hoegaarden181115'
load([basename '.basicMetaData.mat'])
fprintf('%s start %s with data of %s\n',datestr(now),mfilename,basicMetaData.SessionName)
load([basicMetaData.AnalysesName '-tripleCCGact.mat'])
load([basicMetaData.AnalysesName '-t... |
e2d0ad35b03e09ab1cb9e64be8312140b88d614be69decee521df48c4e63f140 | MATLAB | 1,779 | 63 | function Y = SurfStatReadData1( filename )
%Reads data (e.g. thickness) from a single .txt or FreeSurfer file.
%
% Usage: Y = SurfStatReadTxt( filename );
%
% filename = .txt or FS file name, either new version binary or ASCII.
%
% Y = n x v vector of data, v=#vertices.
[pathstr,name,ext] = fileparts(filename);
sw... |
f22e00958c00f3feca46a170dffccb94073d22d67aa10c743ff2cdac54957f43 | MATLAB | 1,779 | 64 | function [template,summary]=generateTemplate(movie,varargin)
% generate an acurate template for motion correction using n last,
% first or random frames. Inspired from Normcorr template estimation
% DEPENDENCIES > NormCorr package
%% GET DEFAULT OPTIONS
options.nFrames=20;
options.order='last'; % options: 'last' (def... |
528ccd56a2bbde2c6b14b464b6c06824b9b540ef6f740955d8c25f662d3701f4 | MATLAB | 1,780 | 54 | function manualMask = draw_mask(this, varargin)
% Displays slices of a 3D volume to manually draw a polygonal mask on
% them and combines output into 3D mask with same image dimensions.
%
% Y = MrImage()
% manualMask = Y.draw_mask('z', Inf, 't', 1)
%
% This is a method of class MrImage.
%
% IN
%
% z def... |
5ff20f36ce6b9800c37233c16d74bf89bd0f092039d86105031b7a272c71cb04 | MATLAB | 1,780 | 63 | function orthonormal_basis = Gram_Schmidt_Process(A)
%
% Gram-Schmidt Process
%
% Gram_Schmidt_process(A) produces an orthonormal basis for the subspace of
% Eucldiean n-space spanned by the vectors {u1,u2,...}, where the matrix A
% is formed from these vectors as its columns. That is, the subspace is the
% co... |
7e7e577dcb3db5b4dc189798dfeb8a430007b3ce9ffbf52aa86de10f8877a300 | MATLAB | 1,780 | 64 | function [raw, hdr] = tsvload(filename)
% _
% Load TSV-file with non-numeric data
% FORMAT [raw, hdr] = tsvload(filename)
%
% filename - a string, the filepath to the TSV file
%
% raw - an n x c cell array of file contents
% hdr - a 1 x c cell array of file header names
% o n = ... |
86982d726f1ea4b1551d199a58a22b4d3ec8511ae0fb5e7f72c5db7456c02de9 | MATLAB | 1,780 | 52 | function varargout = preprocess_data(data,scalingMethod)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% preprocess_data performs preprocessing on data provided.
% Preprocessing consists of rescaling and, if provided, removing
% confounds from data.
%
% Arguments:
% data: Structure compr... |
afc6ad0073ccd7fcf3d04bd55039da058869f5a2c5ed5e6f960e1ed413fca702 | MATLAB | 1,780 | 40 | % This script implements the regularization proposed in:
%
% O’Brien, et al, 2014.
% Robust T1-Weighted Structural Brain Imaging and Morphometry at 7T Using
% MP2RAGE.
% PLOS ONE 9, e99676. doi:10.1371/journal.pone.0099676
%
% which allows the creation of MP2RAGE T1w images without the strong
% background noise in ... |
2b4dda838d0d2dca4fec83198344f7db090479ca03f2a98985c3acdd7945e521 | MATLAB | 1,782 | 53 | function [ spike_probability , spike_probability_raster , spike_probability_raster_thresholds , oopsi_deconvolution ] = findDF_FSpikeProbability( dF_F , dT , t1_2 )
%FINDDF_FSPIKEPROBABILITY( dF_F , dT , t1_2 )
%
% PARAMETERS:
% \_ dF_F [TxN matrix]: dF/F-signal for N units in T time steps
% \_ dT: signal temporal res... |
4073a6762f87bd022927f7e066420a002f44bda5134691b88bd59f8a6ce473c4 | MATLAB | 1,782 | 64 | function tapas_BLT_initDatafile(params)
% tapas_BLT_initDatafile initializes the main data file for the BLT
% ________________________________________________________________________%
%
% EVENTS (Time stamps for screen on and offsets)
% __________________________________________________________________... |
a09bbba079188f5f5852f3d31f5ab1f6cc5491b5d539f7c188951ca626ff729a | MATLAB | 1,782 | 62 | function [m,r,p] = meanangle(angles,weights,d)
% Computes the mean of a set of angles (in radians).
%
% Usage: [m,r,pvalue] = meanangle(angles,weights,dim/groups)
% where m is the mean angle, and r is the mean vector length
%
% 'angles' is a vector or matrix of angles (in radians).
% 'weights' is the relative weight g... |
75180a77c0e00385d3abefd1dd24e22c6cb544fdf8b7a22c343af76da7ab8169 | MATLAB | 1,783 | 60 | function [xsmooth, Vsmooth, VVsmooth, loglik] = kalman_smoother(y, A, C, Q, R, init_x, init_V, varargin)
% Kalman/RTS smoother.
% [xsmooth, Vsmooth, VVsmooth, loglik] = kalman_smoother(y, A, C, Q, R, init_x, init_V, ...)
%
% The inputs are the same as for kalman_filter.
% The outputs are almost the same, except we cond... |
c25064e5f7558d6465506312e2dcce49bb0ec37c1a6cc8ddce0e556c725a063e | MATLAB | 1,783 | 50 | function PATH = naj_postICAopt_paths()
% set all relevant folders, create them if they do not exist yet
% add toolbox paths, start eeeeglab w/o GUI
%
% version 1.0, written by Nadine Jacobsen, Uni Oldenburg, April 2022
if strcmp(getenv('COMPUTERNAME'), 'LAPTOP-796NEANK')
PATH.main = 'E:\nadine\otto_projects... |
e9319d910d5c767d252fb0f355a1924c49e6136b0ee52bc040d33dc3ea3c9bb4 | MATLAB | 1,783 | 19 | function contrasts = calc_contrasts_level1_naturalistic(condition_names)
contrasts = cell(1, 8);
contrasts{1}.tcon.name = 'dog';
contrasts{1}.tcon.weights = contains(condition_names, "dog") - (contains(condition_names, "cat") + contains(condition_names, "frog") + contains(condition_names, "spider") + contai... |
22a6618e041bca956c93cb66a48fd3b86b0938a5a458b41bdc8d98dd66bf2010 | MATLAB | 1,784 | 47 | function plotMetricAlignedToStim(frAlignedToStim, rasterBins, Info, Params, ...
ylabel_txt, figFolder, figName, figureHandle)
%PLOTMETRICALIGNEDTOSTIM Summary of this function goes here
% Detailed explanation goes here
% figureHandle = figure;
numChannels = size(frAlignedToStim, 1);
set(figureHandle, '... |
0e865a722e6265112cb69d7c4cc146fad31f902ce707c5f2ba24b522a73f44fb | MATLAB | 1,785 | 72 | function [UMX, a]=sh_PieceWiseUMX(signal, reference, scale, FrequencyBand, Fs)
% for now, only work with vectors for both inputs
% first scale is always correspond to 4 slices
signal=zscore(signal);
reference=zscore(reference);
n=length(signal);
alpha=zeros(n,scale);
% default scale =5 from [4 8 16 32 64], number o... |
63f2f4cbaa3f72886cd7c3d094ea58ec68c1e4b19449087b483ec528e376a7a9 | MATLAB | 1,785 | 83 | function [Stat] = VectStat (M)
%
% [Stat] = VectStat (M)
%
%Purpose:
% calculates very basic stats of vectors
%
%
%Input Parameters:
% M : MxN matrix
% NAN or Inf values are not considered and the user is warned of their existence
%
%Output Parameters:
%
% Stat is an Mx1 vector of structures with the follo... |
efc31327baa5981c9874945a3b1a408177294fa947e58d79082966a4c741d5b6 | MATLAB | 1,785 | 70 | function Test_symYY()
% function test98()
% Test for symfixedrankYYquotientfactory geometry (low-rank PSD matrix completion)
%
% Paper link: http://www.di.ens.fr/~fbach/journee2010_sdp.pdf
%
% This file is part of Manopt: www.manopt.org.
% Original author: Bamdev Mishra, July 11, 2013.
% Contributors:
% Change log:
... |
f27a2b311e71dcbe22f021316afc38206713f2851b302d2a49a28c709610e48f | MATLAB | 1,785 | 56 | function json = ft_read_json(filename)
% FT_READ_JSON reads information from a JSON file and represents it as a MATLAB structure
%
% Use as
% json = ft_read_json(filename)
%
% See also FT_WRITE_JSON, FT_READ_TSV, FT_WRITE_TSV, JSONDECODE, JSONENCODE
% Copyright (C) 2018-2022, Robert Oostenveld
%
% This file is part... |
3ebb7fdca5cbea19de98622c0df3943bc62bad9eba7a678392521b8b83641d2a | MATLAB | 1,787 | 49 | % parsebvmrk() - convert Brain Vision Data Exchange format marker
% configuration structure to EEGLAB event structure
%
% Usage:
% >> EVENT = parsebvmrk(MRK);
%
% Inputs:
% MRK - marker configuration structure
%
% Outputs:
% EVENT - EEGLAB event structure
%
% Author: Andreas Widmann, University o... |
f16b2c8d8087b85807ad330d90f69ee39df53dd8383c9fd4b32967b6220d0e63 | MATLAB | 1,787 | 52 | function [outermost, inside] = find_outermost_boundary(bnd)
% FIND_OUTERMOST_BOUNDARY locates outermost compartment of a BEM model
% by looking at the containment of the triangular meshes describing
% the surface boundaries
%
% [outermost] = find_innermost_boundary(bnd)
%
% with the boundaries described by a struct-a... |
9a9c048280d7027b0c7b2a2c024c945a3035690135e6eb193ff13ea109cc3092 | MATLAB | 1,788 | 54 | function Data = CreateData(subjectID, nconditions, viewdist, scrnvbl, stimdur)
%nconditions = nstaircases
ScrnRes = [1280 1024];
ScrnPPI = [];
conditions = [];
Data.SubjectID = subjectID;
Data.ViewingDistance = viewdist;
Data.ScreenSpecs.ScrnRes = ScrnRes;
Data.ScreenSpecs.ScrnVbl = scrnvbl;
Data.Scre... |
ee677049e3d18daa096562c03eb7c667061e0bcb3370361b177cd45806e52d23 | MATLAB | 1,788 | 50 | function out = DN_MinMax(y, minOrMax)
% DN_MinMax The maximum and minimum values of the input data vector
%
% ---INPUTS:
%
% y, the input data vector
%
% minOrMax, either 'min' or 'max' to return either the minimum or maximum of y
% ------------------------------------------------------------------------------
% C... |
afc20cc9fdcdf6775c90a460f7701bc928186bb206d52abe3bdfa859b9abbf99 | MATLAB | 1,789 | 64 |
path='F:\GEVI_Wave\Preprocessed\Visual\m14\20210322\meas00\mat';
temp=dir(fullfile(path,'*.mat'));
load(fullfile(temp(1).folder,temp(1).name));
summaryG=summary;
load(fullfile(temp(1).folder,temp(2).name));
summaryR=summary;
frameG=summaryG.framesDroppedVec;
frameR=summaryR.framesDroppedVec;
timeG=summaryG.intervalD... |
b0e5e4586a02a09300219297a0188118587a8053995150475008d0d0391f79b0 | MATLAB | 1,789 | 57 | % Compare potentials in 3 points.
% Author: Aina Frau-Pascual
% Input image generated to have 2D tensors
im = zeros(3) + 0.5;
im(1, :) = 0.8;
im(:, 1) = 0.8;
im(:,:,2) = 1 - im(:,:,1);
im(im==1) = 0;
% Construct mesh structure
Lx = size(im, 1); % domain length
Nx = size(im, 1); % number of cells
Ly = size(im, 2); %... |
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