sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
ec1135e80b40cbb96cbf856dc13443ff00c2daa68e5efc5718842fcb52d8c86c | MATLAB | 2,033 | 65 | function [f1,f2,OUT] = plot_dens_results(OUT)
% function [f1,f2,OUT] = plot_dens_results(OUT)
%
% ----------------------------------------------------------------
% * read input fields into variables
% ----------------------------------------------------------------
N = fieldnames(OUT);
for i = 1:length(N)
eval([N{... |
3260a878d6a33cb87910a9fab733bfaf992c7ca6d18ac9e2a29c2b3f9cbb3693 | MATLAB | 2,034 | 58 | function [lp,dlp] = priorSmoothBox2(a,b,eta,x)
% Univariate smoothed box prior distribution with quadratic decay in the log
% domain and infinite support over the whole real axis.
% The plateau pdf is built by cutting a Gaussian into two parts and
% inserting a uniform distribution from a to b.
% Compute log-likelihoo... |
656c2f345e34836f245a5642fd9e29ad0c7bb5151bb7ba3738393ed8734ad5d0 | MATLAB | 2,034 | 53 | %{
# Compute frequency of abnormal activity
-> experiment.Scan
---
dff: longblob # quality intesity for all fields, length(trace) x nFields
mean_dff: longblob # mean quality intensity trace (df/f) across all fields
prominences: longblob # peak amplitudes of global epileptiform events
widths: longblob ... |
960ed067ed2c9cd3212c3b4a65f2cb4133853d59bcd044e25715ffe510f0af2a | MATLAB | 2,034 | 52 | %% ------------------------------------------------------------------------
% Specify input/output folders
input_folder = '/scratch/shape/oasis/oasis_disc1';
output_folder = '.';
%% ------------------------------------------------------------------------
% Build dataset
file_list = {};
sub = dir(input_folder);
f... |
d5554c2fb07d62a47e751373d431973e47b27cc8b234913daad11932f6db9e87 | MATLAB | 2,034 | 51 | set_up_paths_and_data_directories;
components = {'p', 'g'};
freqs = {'freq4', 'freq3', 'freq2', 'freq1', 'freq0'};
regions = {'Hippocampus', 'EntorhinalCortex', 'vmPFC'};
map_dir = fullfile(folder_project, 'outputs', 'brain_weight_maps', 'PLSbeta', 'brainToTEM', 'MDSseed121', 'iteration32000', 'walkRandomSeed42', 'ni... |
e05a6255404fec43ee133629f04012a578c590d9b100b614aebabb1c627d80b2 | MATLAB | 2,034 | 69 | function varargout = replaceWildcards(stringIn, varargin)
%
% stringOut = replaceWildcards(stringIn[, wildcard1, replacement1, wildcard2, replacement2, ...])
%
% replaceWildcards is a function which takes a string "stringIn" and
% (recursively) replaces all occurrences of {wildcard1, wildcard2, ...} with
% {replacement... |
8d8b05bfcec6cd54bba82de854cf916ed4381bad23c2eb0d46b3d2c4c441df54 | MATLAB | 2,035 | 46 | clear all
close all
clc
data_path='path_to_the_dataset';
colorlabel_layer=brewermap(12,'Paired');
colorlabel_layer=colorlabel_layer([10,4,3,8,2],:);
%%
for idx=1:4
load(fullfile(data_path,['data_BO_session',num2str(idx_session),'.mat']));
BO_Mod=data_BO.BO_index;
%% histogram of BO modulation index
fi... |
76892ddc375d48973dfd9cb2a10a218e33a405044a39204b957d06921edf4d5a | MATLAB | 2,036 | 62 | function [movie,summary]=h5readchunk(fpath,framerange,varargin)
% HELP
% reading chunk of a movie
% SYNTAX
%[frame,summary]= h5readchunk(fpath,framerange) - use 3, etc.
%[frame,summary]= h5readchunk(fpath,framerange,'optionName',optionValue,...) - passing options using a 'Name', 'Value' paradigm frequently used by Matl... |
8ab57059c994f13c49adeada12e8373dc8efbf1d3a51c9e343d7e70d092cf20c | MATLAB | 2,036 | 65 | function c = tapas_rs_precision_whatworld_config
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Contains the configuration for the 'precision' response model according to:
%
% Vossel, S.*, Mathys, C.*, Daunizeau, J., Bauer, M., Driver, J., Friston, K. J., and St... |
be5f521cb8be33b1d6f4095685f2ba7dfc22c799367e1507ae97ae956ded421e | MATLAB | 2,036 | 81 | function [Y] = predict_output(X, Model, parm)
% Prediction from input data
% Input X should be normalized according to 'parm.data_norm' mode
% Time delay embedding for X is done in this function
% Y = predict_output(X, Model)
% = Model.W * X
% Y = predict_output(X, Model, parm)
% = (Model.W * X) * (parm.... |
7ea8c8baa37b238855b73f6f1f3b5366b1f075f5c5a09a8812b017c4b4bb1674 | MATLAB | 2,039 | 58 | function plot_fig4i_right(datadir)
% Plot z-scored latency to poke in the reward port after the reward port
% light turns on following short vs long reard delay trials, averaged
% across rats. N = 16 rats.
%
% INPUTS
% datadir: file path of data downloaded from Zenodo. Link to download can
% be found in README.
load(f... |
016dfe4530b1910853cf0a376c44adbe8ee5b84db195830abaa7110bb9113fe6 | MATLAB | 2,040 | 61 | function TCA_saveModel(tensorPath, savePath, R, titles)
%save the model with the lowest error and corresponding figure
%INPUTS:
% tensorPath = path to tensors
% savePath = path to save in
% R = number of components
% titles = plotting titles e.g. {'neurons' 'time' 'trials'};
matfiles = dir(fullfile(tensorPath... |
2596a6ac92eb3efd6d72e3128ea2d8a5ecb30827aa76d71e82ed87169e64e69d | MATLAB | 2,040 | 78 | function [d,n,p,oldd]=surfing_dir(pat)
% directory listing with support for '?' and '*' wildcard characters
%
% [D,N,OLDD]=PHOEBE_DIR(PAT)
% INPUT:
% PAT File name pattern: either a directory name without wildcard
% characters, or such a directory name followed by a file name
% thay may contain w... |
a4d7cfc1fe7e6f96c9c270d47b692395819fbb0e55aac46defb9e59bc77aabe6 | MATLAB | 2,040 | 66 | function database = DBCreate(database)
%DBCreate - Create database.
%
% Create database with figure and variable tables. Use this function
% if you have admin rights to the database server. Otherwise ask
% the DBA to create an empty database with the appropriate access
% rights, and then use <a href="matlab:help DBCre... |
3998debe1085889ae58dbe1d2da6b50b20e7d440cde24ca7579cab6e85dbc7ea | MATLAB | 2,041 | 84 | function [filepath,filename,formatted_string,options]=getFile(varargin)
% EXAMPLE USE WITH ARGUMENTS
% [filepath,filename,formatted_string]=getFile()
% [filepath,filename,formatted_string]=getFile(options)
% This function prompts a window to choose a file, whose path is passed as an output argument
% and corresponding... |
c5b2c37ee6732ab41b5deeb20b3cf1e6ad1942ac87523b76856e94b3c498d441 | MATLAB | 2,042 | 78 | function maxCh=fear_getMaxThetaCh(basename,varargin)
% basename='~/data/Fear/triple/karmeliet190901/karmeliet190901';
% basename='~/data/Fear/triple/achel180320/achel180320';
load([basename '.basicMetaData.mat'])
fprintf('%s start %s with data of %s\n',datestr(now),mfilename,basicMetaData.SessionName)
%%
param.nCh=b... |
e291c8c11346c259708ade0032e8d45e4d079a4269bf675771606772cf5fda10 | MATLAB | 2,042 | 87 | function [su_hdr,ex_hdr,se_hdr,im_hdr,pix_hdr,im_offset] = GE_readHeader(IFileName)
%
% [su_hdr,ex_hdr,se_hdr,im_hdr,pix_hdr,im_offset] = GE_readHeader(IFileName)
% Reads the header info from a GE lx2 or 5.X file
%
%
% Souheil J. Inati
% Dartmouth College
% May 2000
% souheil.inati@dartmouth.edu
%
%%%% Open the IFile ... |
54ae3df1edd4b6b1b02dbd80e499b9c0dcc47949e279cc0c9f14bd1782ca1edd | MATLAB | 2,043 | 54 | function [A, Bx, By] = operator2matrix(Mx, x, y, F, Bx, By, My)
% Forms a matrix representing a linear operator between two tangent spaces
%
% function [A, Bx, By] = operator2matrix(M, x, y, F)
% function [A, Bx, By] = operator2matrix(Mx, x, y, F, [], [], My)
% function [A, Bx, By] = operator2matrix(M, x, y, F, Bx, B... |
19c73e19aa2d3ad1a1ddc4c02daefb95265766e9db9a2ac5f1fde1a947a90964 | MATLAB | 2,044 | 38 |
keyword = 'vector';
ith_freq=7;
export_path = ['/Users/bo/Documents/data_liujia_lab/analysis_liuP1_greeble/MRI_result_sinusoid/periodic_2501_testing_',num2str(ith_freq),'_fieldmap_',keyword,'_mean/'];
% export_path = ['/Users/bo/Documents/data_liujia_lab/analysis_liuP1_greeble/MRI_result_sinusoid/periodic_2501_tes... |
2ff959fa6dc702ae6133d140f382765cfda7824109bf31c61128307a45987b87 | MATLAB | 2,044 | 58 | %{
preprocess.EyePosClusterCenter (computed) # my newest table
# add primary key here
-> preprocess.CircleMap
-> preprocess.ClusterPeaks
-----
# add additional attributes
center_x : smallint # center of the cluster in x dimension (camera
# pixels)
center_y : smallint... |
5122605dc2c927677b513463cc234a3a2bb0f13cf5bb28adbfce292c1e52f76e | MATLAB | 2,044 | 43 | %% sepia_configuration_EchoCombine
%
% Description: a script contains all the echo combine method names and related function names
%
% Kwok-shing Chan @ DCCN
% k.chan@donders.ru.nl
% Date created: 5 June 2021 (v1.0)
% Date modified:
%
% DO NOT change the variable name
% DO NOT change the order of the entities, add a n... |
e66fa26c94b748ae63ac67649a691241b5d8741f2bd14797d5dc6db1cddd4faf | MATLAB | 2,044 | 57 | function S = statscounters(names)
% Create a structure for statsfunhelper to record counters in manopt
%
% function S = statscounters(name)
% function S = statscounters(names)
%
% The input can either be one string containing a chosen name for a
% counter, or a cell containing multiple strings designating multiple
% c... |
efd842120a633b57506fc1e58f212c7a931cfa7cb5f8f97733842b23764930af | MATLAB | 2,045 | 74 | function group = cvalgroup(Dat,type)
%designs labels for cross-validation groups for stratifying indices
%
%inputs:
%Dat: the data from OFC
%type: switch case for which kind of groups
%
%output:
%group: index for each sample that corresponds to a unique group
hits = Dat.hits;
prev_hits = [nan;hits(1:end-1)];
chosenp... |
058ef5affd672a04a96ee7e4892fb2df131e89a16c39567481d81138febb601a | MATLAB | 2,046 | 56 | %% Sample script to compare simulation to binary tumor image
clear all; close all; clc;
load('simulations\simdata\run_demo.mat')
slice_ind = 140;
%Extract simulated tumor
tumor_sim = squeeze(occupancy(:,slice_ind:slice_ind,:));
tumor_sim = imrotate(tumor_sim,90); %To match tumor images orientation
tumor_sim ... |
1cd858e84c160edde26b98dd5bf485980ff83ca0b61950872b4912b6bd16e45a | MATLAB | 2,046 | 73 | % op_naaFit.m
% Jamie Near, McGill University 2014.
%
% USAGE:
% parsFit=op_naaFit(in,ph0,ph1);
%
% DESCRIPTION:
% Perform a Lorentzian lineshape fit to the NAA resonance in a brain
% proton MRS dataset.
%
% INPUTS:
% in = input data in matlab stucture format.
% ph0 = zero order phase to add to the input data... |
b6144b4e57454552bf97c4915c2ac09ac811ca5d5fd4372786a23c9733718d73 | MATLAB | 2,046 | 57 | % SIZE - size 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 forms, with or with... |
f56fe88f22217bce28a7b2d01b2f90d17dfce137aafc5237b09c3dcab9bd3fdc | MATLAB | 2,047 | 81 | function ft_deface(file_in, file_other, write_mask)
% MRI defacing
%
% ft_deface(file_in, file_other, write_mask)
%
% Inputs:
% file_in - file name of input image.
% file_other - file names (cell array) of other images.
% write_mask - save binary.
%
% This function defaces an MRI image using the SPM function s... |
65e2e6691e5d3894230e074545891c351a953f512bda32c4c2b4a57604b3d7bb | MATLAB | 2,048 | 52 | function params = preprocDownsample_GetMetaParams(Arg)
% Usage: params = preprocDownsample_GetMetaParams(Arg)
%
% ML 2012.11.16
params.class = 'preprocDownsample';
switch Arg
case 1
% Simple box average, for TR=1, imhz=15
params.dsType = 'box';
params.imHz = 15; % movie / image sequenc... |
01dfc6409f8ae75e495d8ee7d34b1319fee4efdb23530a152c75ebd776069ed5 | MATLAB | 2,049 | 46 | function [optimalThreshold, maxSENSAIScore] = SENSAI_fminbnd(minThreshold, maxThreshold, refCOV, Eval, Evec, noise_multiplier, COV, evecs_Template_cov)
max_number_of_epochs = 500; % if EEG recording is long (default = 500 epochs)
number_of_epochs = size(COV, 3);
if number_of_epochs > max_number_of_epochs
rng(2,"twis... |
3ae73c9b8e9774d3ae1313a7bcde42d4fad800be61271444d78e339235defa7e | MATLAB | 2,049 | 76 | function [xpos, ypos] = Unbiased_Movement(xpos, ypos, PB)
% UNBIASED_MOVEMENT
%
% Performs unbiased random movement of agents on a 2D grid with optional
% probabilistic boundary crossing (e.g. blood-brain barrier).
%
% INPUTS:
% xpos - x-coordinates of agents
% ypos - y-coordinates of agents
% PB - structure c... |
94173f2d431515994e6024e20f92a0896a825e90e7a92cd16f1f07d3affac43e | MATLAB | 2,049 | 80 | function Y = delay_embed(X, k, step, shift)
% DELAY_EMBED - Delays-embed a signal
%
% Y = delay_embed(x, k, tau, shift)
%
% Where
%
% K is te embedding dimension
%
% TAU is the embedding delay
%
% SHIFT is the embedding shift
%
% Y is the delay-embedded reconstructed state space, i.e. a KxT matrix
%
%
%... |
2b03efb829807c1cc00979d2a3b36ffaa7be0f7ea341dd24620c922fd59da1c9 | MATLAB | 2,050 | 86 | function [LatOpt, LatMdl, RPE, Kappa] =...
GenerateLatencyData_RPEAlpha(params, ratTrial,...
gen_arg, noise_arg, noise_params)
%GenerateLatencyData_VanillaAlpha
% params - model parameters
% params(1) = learning rate, in [0, 1]
% params(2) = scale parameter, [0, 1]
% ratTrial - trial data. Usual... |
4f275a6a8f723304ece0d7dd9978a3c60e1e4df0e9072becee269e7723ed53ef | MATLAB | 2,050 | 52 | function [ensmat_in, enscells_in, nens, time_comp] = get_carrillo_ens(raster, param)
% Gets the activation sequence and core-cells by Carrillo's algorithm.
% INPUT:
% raster: <logical> N-by-T matrix with the raster. N is the number of total neurons
% and T is the number of total frames.
% param: [optional] <str... |
cb9bcc1aab6ecf7e565bf7a60bf1d722291a7d19a48a49e21c8e306a1416eddb | MATLAB | 2,050 | 42 | %% load libraries
run('set_library_paths.m');
addpath(SPM_PATH); % per spm docs, do not genpath it
addpath(genpath(CANLABTOOLS_PATH));
%% VARIABLES THAT MUST BE DEFINED BEFORE THE SCRIPT IS SOURCED
% THIS SCRIPT IS DESIGNED TO RUN ACROSS A SINGLE SUBJECT/TASK
% with multiple runs per subject
% the nested cell arrays a... |
efd35fb7b6ce61e4f3bc0ee8113639a8953dda999fd146173e879f877a49e0a4 | MATLAB | 2,050 | 87 | function [ SGEdirs]= nmri_run_multiple(subjects,cfg,cmd,params)
% [ SGEdirs , sge_ids]= nmri_run_multiple(subjects,cfg,cmd,params)
% Function to run jobs via nmri_parrun & nmri_qsub on multiple subjects
%
% Sets some defaults for MEG/EEG processing and makes sure params are
% attached to subject structs
%
% wil... |
fd661063b539ebe9904232a174cf46c9b2f842fdb7f7a9fdd86a112fac829cbd | MATLAB | 2,050 | 56 | function [detector lgraph options] = TrainSqueakDetector(TrainingTables,layers)
% Estimate Anchor Boxes
blds = boxLabelDatastore(TrainingTables(:,2:end));
imds = imageDatastore(TrainingTables.imageFilename);
anchorBoxes = estimateAnchorBoxes(blds,8);
% Load unweighted mobilnetV2 to modify for a YOLO net
load('BlankNe... |
69004760725ba4d68f32b95cf8d5b94c49f6aa68140a6e59fadf0b6fe1655cd4 | MATLAB | 2,051 | 80 | function c = tapas_logrt_linear_binary_config
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Contains the configuration for the linear log-reaction time response model according to as
% developed with Louise Marshall and Sven Bestmann
%
%%%%%%%%%%%%%%%%%%%%%%%%%... |
15559d88df1da2fd4e0345d81d0016d74a7623b4de63aea10cf9e99fc8877d07 | MATLAB | 2,052 | 51 | function AssessVar
global run filename sheetname numComb textWidth activateVAR replicate numCells
global intraVarAlgo interVarAlgo Xint Uint PCint Xfin Ufin PCfin
global XlogScoreR UlogScoreR PClogScoreW interExpVarCV intraExpVarCV
global PCintRangeR PCfinRangeR DataSet
% Use coefficient of variation (100x(s... |
97f396325758fb65e17878c70379badea0332c9afcccf122337380a23060926b | MATLAB | 2,052 | 80 | function [traj, infStates] = tapas_rw_binary(r, p, varargin)
% Calculates the trajectories of v under the Rescorla-Wagner learning model
%
% This function can be called in two ways:
%
% (1) tapas_rw_binary(r, p)
%
% where r is the structure generated by tapas_fitModel and p is the parameter vector in native spa... |
dc9d9fd989e83ff051c774c5b453e063681bd0eb1be4f8424f2c6490f5ab5ed4 | MATLAB | 2,052 | 64 | % Create example colormap
% (cbrewer YlGnBu-colormap)
% https://mathworks.com/matlabcentral/fileexchange/34087
cm = [0.8431 0.1882 0.1529; ...
0.9569 0.4275 0.2627; ...
0.9922 0.6824 0.3804; ...
0.9961 0.8784 0.5451; ...
1.0000 1.0000 0.7490; ...
0.8510 0.9373 0.5... |
f54762fde2543bba3a915df741a587349c629c3e3110c101cbadb8b56c293720 | MATLAB | 2,052 | 44 | function datastruct = fitF0smoother (datastruct, widthfactor)
if nargin<2
%Timescale over which to look for a local minimum
widthfactor = 20;
end
for j = 1:numel(datastruct)
%extize
numframes = size(datastruct(j).rawF, 2);
numcells = size(datastruct(j).rawF,1);
uncertainty = 99999999*on... |
eb567cb12dac31301521b59e7c6c338d209bcc997d5e40ee0f4772b9f867f3e1 | MATLAB | 2,053 | 58 | % PERMINV - returns the inverse permutation vector
%
% Usage: >> [invvec] = perminverse(vector);
%
% Author: Scott Makeig, SCCN/INC/UCSD, La Jolla, 11-30-96
% Copyright (C) 11-30-96 Scott Makeig, SCCN/INC/UCSD, scott@sccn.ucsd.edu
%
% This file is part of EEGLAB, see http://www.eeglab.org
% for the documentation and ... |
76daf2734954d16607306e96da6bbef8ed5457153ec198d4184bd0e23e95c336 | MATLAB | 2,054 | 54 | % (C) Copyright 2021 Remi Gau, Marco Barilari
function opt = demoGetOption()
%
% returns a structure that contains the options chosen by the user to run
% slice timing correction, pre-processing, subject and group level analysis.
%
% for more info see:
% <https://cpp-spm.readthedocs.io/en/lates... |
14d3a9a2d2ce289c1125b1d8aca43593d2d53379f3d69976de876254ab6d94bb | MATLAB | 2,055 | 55 | %% Based on files from alex white, refine.
zz = 8;
subjid = sprintf('subj%02d',zz); % which subject
cmap = jet(256); % colormap for ROIs
rng = [0 7]; % should be [0 N] where N is the max ROI index
roilabels = {'OWFA' 'VWFA-1' 'VWFA-1b' 'VWFA-2' 'MFS-WORDS' 'ATL-words' 'unlabeled'}; % 1 x N cell vector ... |
931d40aa8ef70923ee92272789b9c7905bc71d497a02c3cb753171f46c3fd490 | MATLAB | 2,055 | 62 | function [omega,R2,loglike]=fitModelOLS(Model,dist,varargin);
% function [omega,theta]=rsa_fitModelOLS(Model,Data,varargin);
% Does a linear fit to some data
% INPUT:
% Model: numDist x numReg: Design matrix or model structure
% dist: numObs x numDist: Data, with obserations stacked in rows
% OUTPUT:
% ... |
dc9964bee0b4188a072d5bf3b7e0bbf0adbe09ceb2a839902f5d7847b71047d9 | MATLAB | 2,055 | 60 | function approxgrad = getApproxGradient(problem, x, storedb, key)
% Computes an approximation of the gradient of the cost function at x.
%
% function approxgrad = getApproxGradient(problem, x)
% function approxgrad = getApproxGradient(problem, x, storedb)
% function approxgrad = getApproxGradient(problem, x, storedb, k... |
f04637e0cd21a737c9491ffb559cdee1f8359d0c3d99359446ddc365116f1ce0 | MATLAB | 2,055 | 66 | function p = PlotSpikeWaveforms(W,varargin)
%PlotSpikeWaveforms - Plot spike waveforms.
%
% USAGE
%
% p = PlotSpikeWaveforms(W,<options>,<options2>)
%
% W waveforms obtained using <a href="matlab:help GetSpikeWaveforms">GetSpikeWaveforms</a>
% <options> optional list of property-value pairs... |
166de8dd6358260b9aeec0bdc4f776e42e5bbc9bc6798e1049a1a7da54608ac0 | MATLAB | 2,056 | 49 | function [fr_pdf, fr_mean, fr_std, edges] = get_fr_pdf_mean_std(fr, fr_max, bin_width)
% GET_FR_PDF_MEAN_STD
% Syntax:
% [fr_pdf, fr_mean, fr_std, edges] = get_fr_pdf_mean_std(fr, fr_max, bin_width)
% Description:
% Compute the firing-rate PDF (normalized as a density), mean, and std.
% Avoids magic numbers by ma... |
653e60960545e6fc389521b9c5c602a21416a1d310380164ad8fd7847b1e5cb4 | MATLAB | 2,057 | 75 | function [nstate] = tapas_sampler_mixedlinear_gibbs_node(data, model, ...
inference, state, node)
%% Samples from a linear multivariate model with fixed and random effects
% and a diagonal covariance matrix.
%
% Input
%
% Output
%
% This level assumes only and unknown mean with known variance for some the
% the el... |
5f8bdb2646c3d14901c094c421e11521d2586143c7784aea44a495ffe1b96064 | MATLAB | 2,059 | 76 | function [m,boundaries] = CircularConfidenceIntervals(angles,alpha,nBootstrap)
%CircularConfidenceIntervals - Compute circular mean and confidence intervals.
%
% Compute circular mean and confidence intervals of circular data (see Fisher,
% Analysis of circular data, p. 88). If fewer than 25 angle measurements are
% p... |
0e4a64821467536bb119f437d232e8766b6160bae33c4df212ad470d5cc80820 | MATLAB | 2,060 | 67 | classdef LossSmoothL1 < dagnn.Loss
%LossSmoothL1 Smooth L1 loss
% `LossSmoothL1.forward({x, x0, w})` computes the smooth L1 distance
% between `x` and `x0`, weighting the elements by `w`.
%
% Here the smooth L1 loss between two vectors is defined as:
%
% Loss = sum_i f(x_i - x0_i) w_i.
%
% where f is the func... |
10600dfcbd17d3cb7cecbd81740b35d9bb2f3f190c57e1725e19a2856b513932 | MATLAB | 2,061 | 61 | function varargout = ColorMap(axis,varargin)
%ColorMap - changes the current axis' color map to a custom color map
%
% ColorMap - changes the current axis' color map to a custom color map,
% a gradient of the desired colors. The desired colors should be 2 at the minimum
% [start stop], and can be any number above tha... |
39deb68c7d26126a9581a21b72ff832050c31c60d03c7b62b58fa3cf134e82dc | MATLAB | 2,061 | 68 | %% 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
% ... |
d607c7a9a75d63b05e241e010d58ce5dec2361988ec655cb807b9e918063b23d | MATLAB | 2,061 | 69 | classdef ReLU < dagnn.ElementWise
properties
useShortCircuit = true
leak = 0
opts = {}
end
methods
function outputs = forward(obj, inputs, params)
outputs{1} = vl_nnrelu(inputs{1}, [], ...
'leak', obj.leak, obj.opts{:}) ;
end
function [derInputs, derPar... |
38e221576fdb633169f1093502e6e261010f0729d245b69530742076981051a6 | MATLAB | 2,062 | 59 | function [ gamma ] = EmergenceGamma(X, V, tau, method)
%% EMERGENCEGAMMA Compute causal decoupling criterion from data
%
% GAMMA = EMERGENCEGAMMA(X, V) computes the causal decoupling criterion
% gamma for the system with micro time series X and macro time series Y.
% Micro data must be of size TxD and macro... |
8b7acad4e950f325bc60791156918bbce08bd75d01a1bbc033bec68b75edbea1 | MATLAB | 2,062 | 68 | function [loader, channel] = create_loader(key, do_squeeze)
if nargin < 2
do_squeeze=1;
end
reader = preprocess.getGalvoReader(key);
fluorophore = fetch1(experiment.SessionFluorophore & key,'fluorophore');
switch fluorophore
case 'Twitch2B'
channel= [1,2];
loader = @(islice, varargin)(twitch_loa... |
c21aa74896aad58f658ae850b7f3998b103b1c7a48a136411b879c8ed8740767 | MATLAB | 2,062 | 50 | function TellMeAboutLabeling(whatData)
% Tells the user information about the class-labeling of their data
%------------------------------------------------------------------------------
% If you use this code for your research, please cite these papers:
%
% (1) B.D. Fulcher and N.S. Jones, "hctsa: A Computational Fra... |
0d12cc02ebfd5a3a0b0a83328e0068c4ed67a26e3a18f96cf11f594e92b77e14 | MATLAB | 2,063 | 63 | function lesionNorm (finalChar)
if ~exist('finalChar','var')
finalChar = ''
%for parallel e.g. use '1' to only process files which end with 1
end
inDir = pwd;
outDir = '/Users/chris/norm';
tempDir = ['/Users/chris/temp', finalChar];
ext = '.nii.gz';
pth = fullfile(inDir,['*_lesion', ext]);
lesions = dirVisible... |
24ff9cc8e96033d7d21981c49c0bd0de434ec58dd73f4d70382ac3e0584f1ad6 | MATLAB | 2,063 | 63 | function plotJointKinematicsCVPCALoss(lossTests, lossSEMs, mouseN, maxDims)
% Loss curve plot of cvPCA results
% Figure
fig;
axis off
hold on
% Params
colors = [[0, 0, 0]; [0.5,0.5,0.5]];
% Only one mouse is plotted
% Angles
mouseLoss = lossTests(mouseN,2:end,1);
mouseSEMs = lossSEMs(mouseN,2:end,1);
plot(2:maxDims,... |
35f8e4c8a3ffe841eda700c332e222a07b37e351aec4085fcf7f73a4f5c485da | MATLAB | 2,063 | 114 | function [err, Vo, DS] = AFNI_OrientCode (V)
%
% [err, Vo, DirSign] = AFNI_OrientCode (V)
%
%Purpose:
% Changes the orientation code from number to letters and vice versa
%
%
%Input Parameters:
% V, a 3x1 vector of numbers or characters
% like [0 2 4] or 'RPI'
%
%
%Output Parameters:
% err : 0 No Problem
%... |
6da115357306382dc727576256ac9265628c841da52c87a0714998c7fd8df6ea | MATLAB | 2,064 | 62 | function [val] = filetype_check_extension(filename, ext)
% FILETYPE_CHECK_EXTENSION helper function to determine the file type
% by performing a case insensitive string comparison of the extension.
% Copyright (C) 2003-2012 Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.fieldtriptoolbox.org
% fo... |
b3a095ffd59ce5ee3fe28bce666e9737d1f4236b6c2d96a3ad27fc19b229824b | MATLAB | 2,064 | 69 | classdef ReLU < dagnn_bc.ElementWise
properties
useShortCircuit = true
leak = 0
opts = {}
end
methods
function outputs = forward(obj, inputs, params)
outputs{1} = vl_nnrelu(inputs{1}, [], ...
'leak', obj.leak, obj.opts{:}) ;
end
function [derInputs, der... |
24e63d7d5705591084a63456cb0f686b0a2eb7d15266e5d31ea849fff109e5a8 | MATLAB | 2,065 | 68 | function pos = getorthoviewpos(pos, coordsys, viewpoint)
% GETORTHOVIEWPOS obtains the orthographic projections of 3D positions
% based on a given coordinate system and viewpoint
%
% Use as
% getorthoviewpos(pos, coordsys, viewpoint)
%
% For example
% getorthoviewpoint(pos, 'mni', 'superior')
%
% See alo SETVIEWPO... |
3509f657fa4c51d4c4e35a1a36ca769d40e2177918c6908f47d0bc73e7b97124 | MATLAB | 2,065 | 66 | function [] = plotAnalysis01C(saveFigures)
% Produces plots to visualize the results of analysis01C.
% save figures by default
if nargin==0
saveFigures = true;
end
analysisName = 'analysis01C';
% get file paths
paths = addPaths();
% get names of all files in analysis directory
files = dir(fullfile(paths.outputs,... |
8cdce6ae17fd71b093391f10deebd73f68f3bf3839d6d43d72c00c248f1d1343 | MATLAB | 2,065 | 57 | function [binRDM, nCatCrossingsRDM]=categoricalRDM(categoryVectors,figI,monitor)
% Given a single vector of category indices, this function returns a binary
% representational dissimilarity matrix (binRDM) containing a zero for each
% pair of conditions falling into the same category, and a one for each
% pair of con... |
7957b37ebf79479b78e6c3ee6c502aa410312b8de35350f9c427aba79d44ade2 | MATLAB | 2,067 | 58 | function [out] = GetResponseMatrices(sdf, nTrialsPerCondition)
%%
% Wrapper function for preprocessing results from localization test.
% Function takes in the sdf-format results of a single subject and returns
% three matrices containing the responses for low-pass, high-pass and
% broadband stimulus conditions.
%
% ... |
234e567761371303773e7380c19653597bf4b53e6e647505d72a0364c27f4ada | MATLAB | 2,068 | 55 | function [T1map, R1map]=T1estimateMP2RAGE(MP2RAGEnii,MP2RAGE,varargin)
% usage
% [T1map, R1map]=T1estimateMP2RAGE(MP2RAGEnii,MP2RAGE,varargin)
% MP2RAGEnii is the nii structure resulting from loading the MP2RAGE
% with load_nii or load_untouch_nii
% MP2RAGE is a structure containing all the relevant sequence
% informat... |
89b448ecf976cba2718a57e72b22aeaca8f2f609a36279b89e178f887b93275f | MATLAB | 2,068 | 71 | % load behavioral data
bdata = {};
for subjix=1:8
file0 = sprintf('~/nsd/nsddata/ppdata/subj%02d/behav/responses.tsv',subjix);
a1 = importdata(file0);
bdata{subjix} = a1.data;
end
% bdata =
%
% 1x8 cell array
%
% Columns 1 through 5
%
% {30000x19 double} {30000x19 double} {24000x19 double} {22... |
bbfbeeee78e233830935ed5c1e51b58acca5c08c623907d5fe989f14b2fad5e8 | MATLAB | 2,069 | 59 |
function [ha, pos] = tight_subplot(Nh, Nw, gap, marg_h, marg_w)
% tight_subplot creates "subplot" axes with adjustable gaps and margins
%
% [ha, pos] = tight_subplot(Nh, Nw, gap, marg_h, marg_w)
%
% in: Nh number of axes in hight (vertical direction)
% Nw number of axes in width (horizontald... |
cc8f76d643862cc53b6ae8a242a7be1a7f403a858d03d6274b8ce698c7f7e98d | MATLAB | 2,069 | 71 | function [K,dK] = covPref(cov, hyp, x, z)
% covPref - covariance function for preference learning. The covariance
% function corresponds to a prior on f(x1) - f(x2).
%
% k(x,z) = k_0(x1,z1) + k_0(x2,z2) - k_0(x1,z2) - k_0(x2,z1).
%
% The hyperparameters are:
%
% hyp = [ hyp_k0 ]
%
% For more help on design of covarian... |
9a7b57f31d005292e6e3686bd991d038a963b9959c5b70109dcfc2887f953e3f | MATLAB | 2,070 | 73 | function [g] = gen_BAnet(n,m0,m)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% GEN_BANET scale-free network based on Barabasi-Albert model.
%
% Arguments:
% n: Number of nodes in the network (default = 100).
% m0: Initial number of nodes in the network. (default = 5)
% m... |
26dbcbf94ee4958bfb5eeb1529bad8e0440951a1a8873962bb4c4a79cb8e1894 | MATLAB | 2,071 | 55 | % DATLIM - return min and max of a matrix
%
% Usage:
% >> limits_vector = datlim(data);
%
% Input:
% data - numeric array
% Outputs:
% limits_vector = [minval maxval]
%
% Author: Scott Makeig, SCCN/INC/UCSD, May 28, 2005
% Copyright (C) Scott Makeig, SCCN/INC/UCSD, May 28, 2005
%
% This fil... |
b5ba2d70a74d827e1099c7a8470852d65acb24b0a914c386328941f6ba3f2ecd | MATLAB | 2,072 | 38 | function preprocessed_data = preproc_fmri_data_canlabtools(trs_to_use, n_runs, tr_duration, paths_nifti, paths_confounds)
% this is designed to read in one subject/task's worth of fMRI data, across all of their runs
% and then preprocess and return the whole-brain data for masking and etc elsewhere
% NB: 3 ... |
f336cf95d5043f8cc753d7a789313aa2d11ea22d6bf0a39a93179e158f7b6f3e | MATLAB | 2,073 | 61 | % dipfit_reject() - remove dipole models with a poor fit
%
% Usage:
% >> dipout = dipfit_reject( model, reject )
%
% Inputs:
% model struct array with a dipole model for each component
%
% Outputs:
% dipout struct array with a dipole model for each component
%
% Author: Robert Oostenveld, SMI/FCDC, Nijmegen 2003
... |
4382b333f22d8a63cde3a79b7959f67aa28314cd8383bf1ac427ab3dc1847061 | MATLAB | 2,074 | 51 | %% ds = sepiatest.get_real_dataset()
%
% Description: locates the real dataset used by the Tier-2 toolbox-dependent
% regression matrix. Looked up from (in order):
% 1. environment variables SEPIA_TEST_REAL_DATA_DIR (input directory) and
% SEPIA_TEST_REAL_DATA_MASK (brain mask NIfTI)
% 2. a test/config/real_da... |
47347eea5bad787184fe53c2f0858943c3553cd4f8f38e253157490ebad60ea5 | MATLAB | 2,075 | 80 | function X_physio = create_hr_basis_dt(hr,TR)
% create physiological basis set, based on the time and
% dispersion derivatives of each gamma in the RRF, and each gamma
% in the CRF.
% as in Chen et al. NI 2020
% This function will be called. Just keep it saved.
% time axis
dt = TR;
t = [0:dt:40]; % assume 40-s long
... |
0f4aa5dfea9b0e6dad3da6e00970295059c7cec1116eda7247867299a341fe50 | MATLAB | 2,076 | 56 | function Scalebar(bar_length, bar_thickness, fontsize, PathName) % JB 14/10/2021
%SCALEBAR Will add a scalebar and label in the lower left corner of the
%plot
% Input:
% - bar_length: in µm, will convert the text label to mm if entered number >= 1000
% - bar_thickness: line width as a... |
43627aaee38d874e9369d3ebc8492aa051b6a7007005ed855ec62f2b209e8dcc | MATLAB | 2,077 | 86 | % op_takeextras.m
% Jamie Near, McGill University 2018.
%
% USAGE:
% out=op_takeextras(in,index);
%
% DESCRIPTION:
% Extract the extras with indices corresponding to the 'index' input
% array.
%
% INPUTS:
% in = input data in matlab structure format.
% index = vector indicating the indices of the extras you wo... |
fa41ae6ea7359724bcec80d93d039c776a83d7bcb38230b6bf5e2f5c9dde1574 | MATLAB | 2,077 | 61 | function output = decodePartialD2S(kinematics, neurons, tBins, ROIs, kinematicField, neuralField)
% Fit instantaneous regression of joint angles with linear correlation of
% centroid distance to the spout removed
% Format kinematics
outcomes = kinematics([kinematics.locked]);
% Subselect to desired time period
for tr ... |
fc99271577cd5b16ea852b2df3104f490b48b869af933608dedd46ada81c2026 | MATLAB | 2,077 | 67 | function this = set_from_affine_geometry(this, affineTransformation, nVoxels, TR_s)
% Sets dimInfo from affine affineTransformation, assuming 4D nifti data
%
% Y = MrDimInfo()
% Y.set_from_affine_geometry(affineTransformation, nVoxels, TR_s)
%
% This is a method of class MrDimInfo.
%
% IN
%
% OUT
%
% EXAMPLE
% se... |
1a2edc557bf9456d3db6ab6b8a46f3d3a0655910e51dad24b4f2b8a4a1051995 | MATLAB | 2,078 | 56 | function osp_onCoreg( ~, ~ ,gui)
%% osp_onCoreg
% Callback function on coreg button click.
%
%
% USAGE:
% osp_onCoreg( ~, ~ ,gui);
%
% INPUT: gui = gui class containing all handles and the MRSCont
%
% OUTPUT: Changes in gui parameters and MRSCont are written into the
% gui cla... |
2614503e15e435a18f79831eaf448c94fd4712866f6a2355e0e4f63e4b347118 | MATLAB | 2,078 | 57 | function phiFaceAverage = geometricMean(phi)
% This function gets the value of the field variable phi defined
% over the MeshStructure and calculates the geometric average on
% the cell faces, for a uniform mesh.
%
% SYNOPSIS:
% phiFaceAverage = geometricMean(phi)
%
% PARAMETERS:
%
%
% RETURNS:
%
%
% EXAMPLE:
%
% SEE... |
1a0d76bc3b8918b47979848ae230f10564899d7e14b4c3445bcef062a4ab3857 | MATLAB | 2,080 | 73 | % Test how accurately we can orthogonalize ill-conditioned bases of tangent
% vectors. We test three metrics:
% 1) Is Q actually orthonormal (the figure displays log(|Q'Q|); since Q'Q
% should be identity, we hope to see 0 on diagonal and -inf everywhere
% else.)
% 2) Is A = QR? This is in the title of the pl... |
740ecb9651a90b36e065ad00b808ede59101546c71dda0999553c6a7ff60e11f | MATLAB | 2,080 | 56 | function cellvar = createCellVariable(meshvar, cellval, varargin)
% cellvar = createCellVariable(MeshStructure, cellval)
% cellvar = createCellVariable(MeshStructure, cellval, BC)
% this function creates a cell variable based on the dimension of the
% problem. The cell variable does not include the ghost cells, unless
... |
3b60b1c222a5f3ce4a061f7aa811fa82963ab3a6387503521eb946d75e271ded | MATLAB | 2,081 | 59 | function [Y,XYZ] = spm_read_vols(V,mask)
% Read in entire image volumes
% FORMAT [Y,XYZ] = spm_read_vols(V,mask)
% V - vector of mapped image volumes to read in (from spm_vol)
% mask - implicit zero mask?
%
% Y - 4D matrix of image data, fourth dimension indexes images
% XYZ - 3xn matrix of XYZ locations returne... |
fa7f93cf1050edf95b8bcb84626c10dce57d2eb4736e9b9f01185e6c09157e4d | MATLAB | 2,081 | 86 |
% Packing is very flexible - it doesn't just do grids.
%
% (a) Pack a pair of columns.
% (b) Pack a bit into one of them, and then pack some more.
% (c) Pack into the other using absolute packing mode.
% (d) Call select('all'), to show off the result.
% (e) What you can't (currently) do.
%% (a)
% create the root p... |
0e1258f1b286d9f201537257f03411c914101dd7fd5d6b9d9217902a7c4547ac | MATLAB | 2,082 | 66 | function [ ] = save( filename, obj, varargin )
% Save properties of HUGE object to mat file.
%
% INPUTS:
% filename - File name.
% obj - A tapas_Huge object.
% OPTIONAL INPUTS:
% Names of property to be saved. See examples below.
%
% EXAMPLES:
% SAVE(filename,obj) Save properties of 'obj' as individual... |
3abd25ecb32472bea8d2fad8c523860b053a6b01f08d66dd1ed9699f33324502 | MATLAB | 2,082 | 55 | % VAR - variance 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 forms, with or w... |
ec36a412db1213bffd5e0d19204356157f5dd41d7d4ccaaffe9dd11a36d814bc | MATLAB | 2,082 | 72 | % op_autophase.m
% Jamie Near, McGill University 2015.
%
% USAGE:
% [out,phaseShift]=op_autophase(in,ppmmin,ppmmax,ph,dimNum);
%
% DESCRIPTION:
% Search for the peak located between ppmmin and ppmmax, and then phase the
% spectrum so that that peak reaches the desired phase.
%
% INPUTS:
% in = input data in ... |
2b3563bc685a7be74715e543f262448ce30c8df1348ef8f9e46c768a832bc103 | MATLAB | 2,083 | 66 | function [ha, pos] = tight_subplot(Nh, Nw, gap, marg_h, marg_w)
% tight_subplot creates "subplot" axes with adjustable gaps and margins
%
% [ha, pos] = tight_subplot(Nh, Nw, gap, marg_h, marg_w)
%
% in: Nh number of axes in hight (vertical direction)
% Nw number of axes in width (horizontald... |
556f1c53109aa98881cff7e55be6831c149c2f94399e860ef13979795e6b4787 | MATLAB | 2,083 | 72 | %isdvector - Test if parameter is a vector of doubles satisfying an optional list of tests.
%
% USAGE
%
% test = isdvector(x,test1,test2,...)
%
% x parameter to test
% test1... optional list of additional tests (see examples below)
%
% EXAMPLES
%
% % Test if x is a vector of doubles
% ... |
8939103df9dabd9dab2bd1cbf1f3152720bc9b3bb2c7f1a12d7f1abd55453348 | MATLAB | 2,083 | 55 | function trainnew_Callback(hObject, eventdata, handles)
%% Train a new neural network
cd(handles.data.squeakfolder);
% Apparently, "wind" is a function name, so initialize it as empty
wind = [];
%% Select the tables that contains the training data
waitfor(msgbox('Select Image Tables'))
[trainingdata, trainingpath] = ... |
9aaf0cb7f5243aca0cf651fd5ca60162eb997f1db30a2e8297803d2a00a4717f | MATLAB | 2,083 | 56 | % bids_gettaskfromfolder() - Scan bids folders to get the list of tasks
%
% Usage:
% >> tasklist = bids_gettaskfromfolder(bidsfolder);
%
% Inputs:
% bidsfolder - a loaded epoched EEG dataset structure.
%
% Outputs:
% tasklist - [cell array] list of tasks
%
% Authors: Arnaud Delorme, SCCN, INC, UCSD, March, 2021... |
c48cb2339f566f21cad605d501d1824ecd2104bf70fbfe804f3365fcf8696373 | MATLAB | 2,083 | 81 | % (C) Copyright 2020 CPP visual motion localizer developpers
function diplayDesign(cfg, displayFigs)
%% Visualize the design matrix
if displayFigs
close all;
figure(1);
% Shows blocks (static and motion) and events (motion direction) order
directions = cfg.design.directions;... |
2d401acc80c08e23c36959a9e0355fdf378c4c8fbd28ec56695a51e93d07ded2 | MATLAB | 2,084 | 54 | function cos_amp = mahalTune_func_fast(data,theta,num_features,weights,foldvar)
% computes the mahalanobis distances between the data of single test-trial of a particular orientation and the rest of the data,
% averaged into specific orientation bins relative to orientation of the test-trial.
%% input
% data i... |
7e4f6276b0b557d636e7d28eda4ad631f6a22ff1aebe604cee76841f0982eac1 | MATLAB | 2,084 | 87 | function [ccace_out,segs,U,C] = ccace_detector(hsi_img,tgt_sig,mask,n_comp)
%
%function [ccace_out,segs,U,C] = ccace_detector(hsi_img,tgt_sig,mask,n_comp)
%
% Class Conditional ACE
%
% inputs:
% hsi_image - n_row x n_col x n_band hyperspectral image
% tgt_sig - target signature (n_band x 1 - column vector)
% mask - ... |
aed82317a0895fea786ef91632070efbca3b6d3310ec5171d8446caf09195f24 | MATLAB | 2,085 | 80 | % TEXTSC - places text in screen coordinates and places
% a title at the top of the figure.
%
% Usage:
% H = textsc(X,Y,TXT) places the text string, TXT
% at the normalized coordinates X and Y. H is the
% handle to the text object.
%
% H = textsc(TXT) or H = textsc(TXT,'title') or
% H = textsc('t... |
f040f4479269d083f4f47ba1e2fbd6b2725f396fe0757a86d9776ca44c8be2f9 | MATLAB | 2,085 | 53 | function [postLow, postHigh, postLow_q1, postHigh_q1] = quartileAnalysis_MD(data,bins)
% split mixed blocks into quartiles to look at changes in wait time over
% the course of a block
% INPUTS:
% data = data struct containing behavior data containing wait_time,
% reward, etc fields
% OUTPUTS:
% mean z-scored wait-... |
5539c191dbbc4ccf045c7dc75b5f18f94a4ae719737bdd0782238b72ad35ff66 | MATLAB | 2,086 | 86 | function DBConnect(host,user,password)
%DBConnect - Connect to the database server.
%
% Open connection to MySQL database server. Connection information can
% be either passed explicitly as arguments, or read from your .my.cnf
% configuration file.
%
% USAGE
%
% DBConnect(host,user,password)
%
% host ... |
6edf62c4ab5fd745c7e508a0f7a62b9da9b25fc06f9347aff17895db62e5b61e | MATLAB | 2,086 | 59 | function [event] = read_bucn_nirsevent(filename)
% READ_BUCN_NIRSEVENT reads the event information of ASCII-formatted NIRS
% data acquired with the UCL-BIRKBECK machine and postprocessed by the
% Paris group. The first line contains the header-info and the rest of
% the file contains per line an event. The first colu... |
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