sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
9ac1fc5babe1dbcfc0abae5f251c028dd34527c831d4e303e78aa2a32b267b0b | MATLAB | 2,234 | 80 | % Author: Birgit Nierula
% nierula@cbs.mpg.de
function esg_prepro_loop2(subject, condition, srmr_nr, sampling_rate)
% set variables
subject_id = sprintf('sub-%03i', subject);
analysis_path = [getenv('ANADIR') subject_id '/esg/prepro/'];
if ~isfolder(analysis_path)
mkdir(analysis_path);
end
% get condition inf... |
10f7e7b6db8f4e62b1a46b1bdb076aa1eef663334a1113094b97679dfd76ac0f | MATLAB | 2,235 | 59 | % Purpose: Convert lh_labels and rh_labels to gifti shape files for later WB
% visualization
% Inputs: lh_labels and rh_labels from generate_network_overlap.m and template gifti
% files in appropriate resolution.
% Outputs: .shape.gii files containing AI values.
%
% Note: Template .shape.gii files can be created using... |
afb746193323c8223900f52fae47006502ae4598bf1bf2eac02ea6aa7a24b075 | MATLAB | 2,235 | 71 | % load sessions csv
metadata = readtable('Y:\laura_berkowitz\behavior_metadata.csv','Delimiter','comma');
% only use the basepaths
basepaths = unique(metadata.basepath);
%% overwrite
overwrite_coords = true;
for i = 1:length(basepaths)
% get channel map from anatomical
basepath = basepaths{i};
cd(ba... |
d8957299e670c2cf9b08db940da07c67a01885cf98489b60e46b5739bcb7c892 | MATLAB | 2,235 | 74 | function [negResp, negIndex, posResp, posIndex] = zscore_response(responses,stimPnt)
%% >>> OPERATION >>>
% Defines significant negative and positive responses based on Z-scores
% INPUTS
% NAME TYPE NOTES
% responses m-by-n array m is the number of trials, n are the
% ... |
8e414bb5b4b11f1dc3ca6ca869705601c81e41b363e87dfab9f6a76aa22a4c1e | MATLAB | 2,236 | 76 | classdef Platform < uint8
% apt.Platform - Enumeration for operating system platform types
%
% This enumeration distinguishes between different operating system families
% to enable platform-specific path handling, command formatting, and file
% system operations within APT.
%
% Enumeration values:
% ... |
9a89cff68174e19c2d6474c00c3dcf7e86c8c6e2ee204a7b486e5e2624f8cc71 | MATLAB | 2,236 | 72 | function renamefile(f,pat1,pat2,opt)
%RENAMEFILE Rename a series of files.
% RENAMEFILE(NAME, P1, P2) renames the files matching NAME, replacing
% the substring P1 by P2. NAME may be a cell array of strings, and may
% contain wildcards (*) and brackets (see RDIR).
%
% RENAMEFILE(NAME, P1, P2, OPT), where OPT i... |
3bf1894f82038bbddd406ac78c28b7bd98bfc0b72f26b01098255d9e074f33a1 | MATLAB | 2,237 | 62 | % Function: PLS and do permutation.
%perform full PLS and plot variance in Y explained by top 15 components
%typically top 2 or 3 components will explain a large part of the variance
%(hopefully!)
% Updata date: 2022.09.18
% Email:luolongcao@163.com
function PLSperm_result = Method_PLSpermutation(X,Y,dim,rep,out_... |
c8275aca76f448f3f596fa71be816f759ef8973e1ca4c51ccdbcb21ee4c08acf | MATLAB | 2,237 | 59 | % Edited by Jerry. 10/26/2023
function [datamean,datastd] = ScatterPlotBehavior_231026...
(data,Title,Xlabels,Ylabels,figsize,SaveDir,alpha,ErrType,Yrange)
% Function to do a scatter plot with error bar of the data
% dataTable: a table with labels corresponding to the categories
% title: the title of ... |
2c916030d36a0af6a6220613bea2cbf9104adca1b035bf08adff7806145b7326 | MATLAB | 2,238 | 50 | ops.chanMap = 'D:\GitHub\KiloSort2\configFiles\neuropixPhase3A_kilosortChanMap.mat';
% ops.chanMap = 1:ops.Nchan; % treated as linear probe if no chanMap file
% sample rate
ops.fs = 32000;
% frequency for high pass filtering (150)
ops.fshigh = 150;
% minimum firing rate on a "good" channel (0 to ski... |
2e6e932b07d760e240c03faab0dab739f891499f59e9f7391e23c6247010f331 | MATLAB | 2,238 | 70 | function dimsiz = getdimsiz(data, field)
% GETDIMSIZ
%
% Use as
% dimsiz = getdimsiz(data, field)
%
% If the length of the vector that is returned is smaller than the
% number of dimensions that you would expect from GETDIMORD, you
% should assume that it has trailing singleton dimensions.
%
% Example use
% dimord... |
ac6dfb79b87994a6187d1d9d80d3d97bcf8d9d1fab8f9d9ac3bb38cb562948bd | MATLAB | 2,238 | 46 | for k = 1:length(Z)
clf;
z = Z(k);
% Display NIFTI slice
I = round(z/d1d2d3(3) + N1N2N3(3)/2);
S = VT(:, :, I)'; % choose the Z cross-section
S = S(:, end:-1:1);
image([-DimensionX/2 +DimensionX/2], [-DimensionY/2 +DimensionY/2], S, 'CDataMapping', 'scaled');
colormap bone; b... |
aee89df6b2d5bc2b7f4bf6c6fa3ebc77b2326429cde7133b7762d2391ad013da | MATLAB | 2,239 | 62 | function [nodeBels, logZ, nodeBelArray] = dgmInferNodes(dgm, varargin)
%% Return all node beliefs (single marginals)
%% Inputs
%
% dgm - a struct created by dgmCreate
%
%% Optional named inputs
%
% 'clamped' - a sparse vector of size 1-by-nnodes.
% clamped(t) = j means node t is clamped to state j
% ... |
c2db7c59e7701c890f5332917fb111922a4508554edd1190c1df40568fef8415 | MATLAB | 2,239 | 82 | %% Mulitlayer Perceptron HMC Regression Demo
% Based on Netlan's DEMHMC3
% We modified the code so the model is as similar as possible
% to the one in demev1, so we can compare MCMC with Laplace approx
%% Create the data and do EB on the network
% This file is from pmtk3.googlecode.com
mlpRegEvidenceDemo;
% use the... |
fe1d7ed6915d6a5d04a32d9620be38ae6e0f7b02671f839b79665c236b0f7da8 | MATLAB | 2,239 | 76 | function is_same = compare_hdf5_images(srcDir, dstDir, ds, avgErrTol)
srcFiles = dir(fullfile(srcDir,'*.h5'));
dstFiles = dir(fullfile(dstDir,'*.h5'));
if length(srcFiles) == 0
disp('no hdf5 file.');
is_same = false;
return;
end
if length(srcFiles) ~= length(dstFiles)
... |
618b82cd2bf0a5da999b0f925316bddeb03f89b99c7d35e1586fe6d57cb037c0 | MATLAB | 2,240 | 69 | %% NVR Copy ICA weights from HP-1Hz dataset to dataset
% 2024 by Antonin Fourcade
% Beforehand, need to run ICA decomposition on a copy of the data high-pass filtered at
% 1Hz!
function NVR_06_copy_ICA(cropstyle, mov_cond, path_data)
%% 1.Set Variables
%clc
%clear all
%1.1 Set different paths:
path_data_eeg = [path_... |
ac74ca77c6da97b662592ee246364bdf3a04aa4db95cdddc5bd053cef1a8d805 | MATLAB | 2,240 | 69 | function AutoPlaybackBig(ImageArray,PauseInterval,IntensityLimits)
SizeScaleFactor=1.5;
figure();
set(gcf, 'color', 'white');set(gca,'XTick', []); set(gca,'YTick', []);
BringAllToFront();
Beeper(5,0.15)
ArraySize=size(ImageArray);
ScreenSize=get(0, 'screensize');
if ScreenSize(3)>ArraySize(2)*SizeScaleFactor+40&&... |
e0fc71179270ad4fd677d8135398801e2556fe37699346ab00652e0bb8b0fe75 | MATLAB | 2,240 | 86 | function y = wkeep2_gpu(x,siz,varargin)
%WKEEP2 Keep part of a matrix.
% Y = WKEEP2(X,S) extracts the central part of the matrix X.
% S is the size of Y.
% Y = WKEEP2(X,S,[FIRSTR,FIRSTC]) extracts the submatrix of
% matrix X, of size S and starting from X(FIRSTR,FIRSTC).
% M. Misiti, Y. Misiti, G. Oppenhe... |
f004448e410a397bd1cffac537035f849372a662df73e818f256cdfce99a67ea | MATLAB | 2,240 | 71 | %% SAT - app_input ::
%% getAppXtCellFromXtCell
% Name: Phone Kyaw
% Date: 09/10/2024
%_______________________________________
% Copyright (C) 2024 Phone Kyaw
% Drexel University College of Medicine
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Publi... |
29f998aacfe50ad89202b094088ad351c32e03d13aa1508ea1057809d9db168c | MATLAB | 2,241 | 68 | %% pxTools_getXfromPx
% Assign a single state from a distribution, using a given metric;
% if passing an MxN array, evaluate each column as a distribution;
%
% If input is a doubles array, output a doubles array.
% If input is a struct, output a struct, with x calculated over all fields
%
% Current methods in... |
2572f318713f0540084b1a1aeeaa742490e1d12cf73a5921f65135743b992ba6 | MATLAB | 2,242 | 85 | %% Demonstrate a non-parametric (parzen) density estimator in 1D
%%
% This file is from pmtk3.googlecode.com
function parzenWindowDemo
setSeed(2);
[data, f] = generateData;
n = size(data,1);
domain = 0:0.001:1;
kernels = {'gauss', 'unif'};
for kk=1:2
kernel = kernels{kk};
switch kernel
case 'gauss', hv... |
fe4590ad8923c0a94c7195a8da01e91430188f3fad7447552b77acf2d7140dd9 | MATLAB | 2,242 | 65 | function surr = CBIG_RL2017_get_PR_surrogate(TC , n_surr)
% surr = CBIG_RL2017_get_PR_surrogate(TC , n_surr)
% This function generates phase randomized (PR) surrogates. The two
% mandatory inputs are:
% 'TC' original time course of size (num_timepoints,num_variables)
% In this cas... |
75a7c9f2d29b2d6f645c66e2d260cba2e214edc96a42a39e85d592e1be09708b | MATLAB | 2,243 | 52 | function [data_filter_above,data_filter_below] = loc_list_clusters_filter_aspect_ratio(data)
answer = inputdlg({'Major Axis to Minor Axis Aspect Ratio Threshold:'},'Input',[1 50],{'1.5'});
if isempty(answer)~=1
min_aspect_ratio = str2double(answer{1});
f = waitbar(0,'Filtering Based On Aspect Ratio...');... |
04d52acfbf702c0bf02150496745c05cdc822608686af5f1ae2b201b7b127411 | MATLAB | 2,244 | 86 | function pairs(X,vnames,plotsymbol,diagonal)
% PURPOSE: Pairwise scatter plots of the columns of x
%---------------------------------------------------
% USAGE: pscatter(x,vnames,pltsym,diagon)
% or pscatter(x) which relies on defaults
% where:
% x = an nxk matrix with columns containing variables
%... |
c9b48449af6052f5c9255681d023f5b07c38c4cd58ff50793ed862efdb56d1c8 | MATLAB | 2,245 | 81 | % read_eeglabheader() - import EEGLAB dataset files
%
% Usage:
% >> header = read_eeglabheader(filename);
%
% Inputs:
% filename - [string] file name
%
% Outputs:
% header - FILEIO toolbox type structure
%
% Author: Arnaud Delorme, SCCN, INC, UCSD, 2008-
%1234567890123456789012345678901234567890123456789012345... |
0526671df35853011d12d12d8a47acd90bfde50175717ab3403018ebc659e2fa | MATLAB | 2,246 | 94 | % This program is free software; you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation; either version 2 of the License, or
% (at your option) any later version.
%
% This program is distributed in the hope that it will be useful,... |
3a4f624d74f0914a2a5c6a3674b5c3fcc2d543d4bb6b9e031d9060537bc92956 | MATLAB | 2,246 | 94 | % This program is free software; you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation; either version 2 of the License, or
% (at your option) any later version.
%
% This program is distributed in the hope that it will be useful,... |
58537e4fb0eff9e69b62223980cbeebceeaf6f155bdc951731131426afbdef45 | MATLAB | 2,247 | 76 | function [file] = read_bti_ascii(filename)
% READ_BTI_ASCII reads general data from a BTI configuration file
%
% The file should be formatted like
% Group:
% item1 : value1a value1b value1c
% item2 : value2a value2b value2c
% item3 : value3a value3b value3c
% item4 : value4a value4b value4c ... |
8e73be3db1e37518fb5dd9f6b4a895c56f39b6278c678979bb3080de53047a13 | MATLAB | 2,247 | 124 | function [r,t,p]=spear(x,y)
%Syntax: [r,t,p]=spear(x,y)
%__________________________
%
% Spearman's rank correalation coefficient.
%
% r is the Spearman's rank correlation coefficient.
% t is the t-ratio of r.
% p is the corresponding p-value.
% x is the first data series (column).
% y is the second data series, a matri... |
ce65d838303f8b5b98ee2f7b31602365865903b9ca3faad25f72c010483faae8 | MATLAB | 2,247 | 56 | % QGIF evolution function:
%
% [fx] = f_CaBBI_QGIF(Xt,Theta,Isyn,inF)
%
% this function contains the equations and parameters of the QGIF neuron
% model, and the over-time integration scheme
function [fx] = f_CaBBI_QGIF(Xt,Theta,Isyn,inF)
dt = inF.dt;
Tau_Ca0 = inF.Tau_Ca0;
% hidden variables
V = ... |
c86c8067d0f913481f740db5931f7a6bff296a10e582b8e62e3985dac3e377c0 | MATLAB | 2,249 | 65 | % This script plots the electric potential of the primary, secondary, or
% the full field for any brain compartment surface
%
% Copyright SNM/WAW 2017-2020
eps0 = 8.85418782e-012; % Dielectric permittivity of vacuum(~air)
mu0 = 1.25663706e-006; % Magnetic permeability of vacuum(~air)
%% ... |
98c07b4c8692d1550a43cb6f4d312996050e093af2f7162e501a0809a8533e37 | MATLAB | 2,250 | 44 | function y_Call_dcm2nii(InputFilename, OutputDir, Option)
% function y_Call_dcm2nii(InputFilename, OutputDir, Option)
% Call Chris Rorden's dcm2nii for different platform as well as for parfor usage. ('eval' is not suitable for 'parfor')
% Input:
% InputFilename - The Input File name. Could be one of the DICOM file... |
d766c197b95e81ebb2b9bcafaf4a45330c3ed233ee0ad2cbdba46e42e9ebf546 | MATLAB | 2,250 | 65 | function t = getLinesearch(problem, x, d, storedb, key)
% Returns a hint for line-search algorithms.
%
% function t = getLinesearch(problem, x, d)
% function t = getLinesearch(problem, x, d, storedb)
% function t = getLinesearch(problem, x, d, storedb, key)
%
% For a line-search problem at x along the tangent di... |
6ae35b6233cc6ea418065d6b629029fbac67c88c3ab689647223068c415eb979 | MATLAB | 2,252 | 76 | % This demo compares exponential vs hyperbolic temporal discounting.
% This script simulates an agent making choices between two options, which
% differ in terms of the expected reward and temporal horizons, under both
% an hyperbolic and an exponantial temporal discounting model.
% The choice data are then inverted us... |
938dfceec6993b9c4df5eb36203f66cd8b37f27c6380a090c550a2b5b22357a0 | MATLAB | 2,252 | 49 | % Filters can constrain what data is currently displayed and analyzed. They
% are specified as MATLAB expressions that evaluate to logical vectors.
% They can access the label table of the datasource through a table
%
% >> P.
%
% The filter expression can also access variables a and... |
287b4bd0286aaef92b64c7e43a52d80e7738d3b1a38db14e63afee2fcc5d461b | MATLAB | 2,253 | 82 | function out = linregPostSummary(model, varargin)
% Return summaries of the posterior distribution of the regression weights
% You must call linregFitBayes first
% out is a structure containing
% what % posterior mean
% stderr % posterior standard deviation
% credint(i,1:2) % 95% credible interval
%
% If you set dis... |
2a273c0bb37b34c2a271999fbed0475f5b318dfcfa12931e74becf23860eb9ba | MATLAB | 2,253 | 87 | function newlist = wlAux_mergeEventLists(oldlistarray, ...
comparefunc, binsecs, huntbins)
% function newlist = wlAux_mergeEventLists(oldlistarray, ...
% comparefunc, binsecs, huntbins)
%
% This function merges multiple event lists, removing duplicates.
% Duplicates are those that match according to "comparefunc".... |
8a3b19d93f444720342edac6cf1c56d67e2331552ae76a4e82c449a965275f0b | MATLAB | 2,253 | 58 | function [ServerIP,ServerName]=Server_Picker(LabDefaults)
[OS,~,~,~,~,~]=WhereAmIRunning(1);
if any(strfind(OS,'MAC'))
CurrentIP='Unknown IP';
else
try
[~,result] = system('arp -a');
Index1=strfind(result,'Interface: ');
Index2=strfind(result,' ---... |
c0a93826f552f083c466e57dc4543b194d5911381c191aaf89e77a9c302fdd83 | MATLAB | 2,253 | 67 | function [res, sampleinfo] = selectSpike(spikeDataset, trials, CTLParams, segOption)
narginchk(2, 4);
if nargin < 3
CTLParams.temp = [];
end
if nargin < 4
segOption = "trial onset";
end
NoveltySU.utils.parseStruct(CTLParams);
if exist("devonset_Win", "var")
Window = devonset_Win;
end
win... |
f00a16c8106cf36d17a1b44e9166cb702d445cac79b7e0085f20290c404292b6 | MATLAB | 2,253 | 68 | % Author: Birgit Nierula
% nierula@cbs.mpg.de
function bs_preprocessing_loops(srmr_nr, loop_number, subjects, conditions)
switch loop_number
case 1
%% combine selected EEG and ESG channels
% load cleaned EEG + ESG data
% load excluded epochs
% select epochs that are present in... |
2c50f5678b129b9241532e4f233a19a5d03124182bfbdce8b2005c616a0bf1d3 | MATLAB | 2,255 | 62 | function outputImage = interpolateVolume(inputImage)
%Assumes that there are 0s in the input image where the original image was
%not able to warp into. To ensure this, a nominal f
%Add a nominal amount to the tileM for the interpolation step at the end of
%this function
%It is rounded back to integers at the very end... |
74b3e287ac799c327e99a7e1c7e85af317aa40c210ad4a2bd74e5e0a62c1219c | MATLAB | 2,255 | 80 | function toolboxUpdateHeader
% Update the headers of all the files.
%
% USAGE
% toolboxUpdateHeader
%
% INPUTS
%
% OUTPUTS
%
% EXAMPLE
%
% See also
%
% Piotr's Computer Vision Matlab Toolbox Version 3.50
% Copyright 2014 Piotr Dollar. [pdollar-at-gmail.com]
% Licensed under the Simplified BSD License [see extern... |
276caf11d8bd0c2f426b18b42a30f23cf37a2664a39ec2fbf029be722ad36ade | MATLAB | 2,256 | 69 | function s = angle_stddev(v,avg_type,to_deg)
% v -> sample of 2d vectors (1 vector per row)
%
% returns the stddev of the angles of each vector in v relative to the "average" of v
%
% the average of v can be one of the following:
% - centroid = average of vectors in v weighted by each vector magnitude
% - mean ... |
6fd4f74b659043f3a2c25af9e8b63eb87e029d648bf09470de4d9b9a78b9098d | MATLAB | 2,256 | 55 | %% 非线(神经动力学)性特征 | nonlinear features
%% permutation Lempel-Ziv complexity, PLZC （P219）
% 相比普通的LZC_mean、LZC_median、LZC_midpoint、LZC_kmeans，PLZC具有计算简单、鲁棒性/稳定性强、计算复杂度低等优点
% LZC的值越大，代表序列越复杂，越接近随机状态
% X: single channel EEG signal (either a row vector or a column vector)
% opts.pattern：将信号表示为由不超过m!种模式组成的序列，如3,4
%% Refe... |
34fd3a21edcfd96f67abc2799a0bd0e25f5a86f4110fbf68a1e6ebd7608a9b4a | MATLAB | 2,257 | 69 | function [bels, converged] = beliefPropagation(cg, queries, varargin)
%% (Loopy) belief propagation algorithm
%
%% Inputs
%
% cg - a cliqueGraph, see cliqueGraphCreate
%
% queries - a cell array of queries
%
%
%% Optional named inputs
%
% 'updateProtocol' - ['async'], 'sync', or 'residual', ... |
81e00bdb22287876a6aca5bd0dc6b1f863ab2c96c7eb71d72f88c6119b238dd4 | MATLAB | 2,257 | 118 | function RT = rt_check(RT,cfg)
% <*LAN)<] toolbox
% v.1.2
%
% 12.12.2023 rt / response -99 if empty
% 22.03.2022 .good
% 11.12.2014 .est .rt .resp MUST BE MATRIX
% 01.04.2014 fix error
% 31.03.2014 agrege ifsort option
% 20.12.2012
if nargin <2
cfg=[];
end
getcfg(cfg,'ifsort',false);
% stimuli
if ~isfield... |
dfdaaf6561e8acf30e83f7ee10a7d03f15da6c3da01296b0f5afe1b4a216d847 | MATLAB | 2,257 | 80 |
clear;
basefolder = fileparts(fileparts(mfilename('fullpath')));
codefolder = [basefolder,'/code'];
toolsfolder = [basefolder,'/tests/tools'];
addpath(genpath(codefolder));
addpath(genpath(toolsfolder));
% Load Data
data_path = [basefolder, '/hasegan_et_al_netneuro_2024/data/trefoil_knot/data_treefoil.1D'];
fn_tim... |
48c2a0b996fd5117bb746faa8868fae38c123f85a4b6383ea105707b0d4111aa | MATLAB | 2,258 | 64 | %% Demonstrate the use of a Hopfield network for associative memory.
% Requires the neural network and image processing toolboxes
% PMTKneedsImagesToolbox
% PMTKneedsNnetToolbox
% PMTKslow
%%
% This file is from pmtk3.googlecode.com
requireImageToolbox
loadData('binaryImages'); % 7 binary images, each 150x150
new... |
814c764906eef5cb161f46e514817dc0b8808b6ae3d12a68449134bfe48c2b0a | MATLAB | 2,259 | 63 | function plot_fluorescence_trace_and_ratio(fluG, fluR, deltaR_R0, varargin)
figure
% various arguments in oder: curvature of head, fwd, bkw, turn
N = size(deltaR_R0, 1);
% odd column for red vs. green fluorescence
for i=1:N
subplot(N,2,2*i-1);
plot(fluR(i,:),'r','LineWidth',1.5);hold on;
... |
a619aa782c09d79892b22c1c30042873cd4396bdca931d299d3f4f41ff31d703 | MATLAB | 2,259 | 44 | clear all
load('X.mat'); % single channel EEG signal (either a row vector or a column vector)
% X = X';
%% You can call and test each feature extraction function separately.
% power spectral density (PSD), welch method
opts.fs = 128; % sampling frequency
opts.f_low = 1; opts.f_high = 45; % frequency range... |
bff3c2092286950a5413343fa9785b6fa2059d3047cc181f1f9805a0541d139b | MATLAB | 2,259 | 54 | function h = filledCircle(center,r,N,color)
%---------------------------------------------------------------------------------------------
% FILLEDCIRCLE Filled circle drawing
%
% filledCircle(CENTER,R,N,COLOR) draws a circle filled with COLOR that
% has CENTER as its center and R as its radius, by using N point... |
5ac63d3a39fb0346ee8f208ea0ede0b23eccbd1bb197b4ba6fb1a7454382e2fe | MATLAB | 2,260 | 59 | function [bels, converged] = belPropAsync(cg, varargin)
%% Belief propagation with a simple asynchronous update schedule
% By asynchronous, we mean that a node can update itself without having to
% wait for everyone else to first be ready. A node is ready once it has
% messages from each of its neighbors.
% See belie... |
69a4dc4aaba7a9690d54895f08da9da9862f79e9f71a036f171889a8ee1e4fee | MATLAB | 2,261 | 59 | function p_pairwise = CBIG_MMLDA_glmfit_hypotest_forestplot(k, X, y, dependency, out_dir, out_name, compare_factor_names, CI_scale, p_thresh)
% CBIG_MMLDA_glmfit_hypotest_forestplot(k, X, y, dependency, out_dir, out_name, compare_factor_names, CI_scale, p_thresh)
%
% This function will do glmfit, hypothesis tests and f... |
91f7a5eae17683995cfc9200f052f35b3c2ceaabba252555c8ddab7de1fc8c9e | MATLAB | 2,261 | 50 | clear
clc
close all
nb_models = 1000;
stimAmp_step = [-53];
% stimAmp_diffusion = (2:0.1:2.5);%-53*(0.5:0.3:1.5);
t = 0:100;
Istim = get_diffusion_current(t, 1);
max_Istim = max(Istim);
% stimAmp_diffusion = unique(round(stimAmp_diffusion*max_Istim));
stimAmp_diffusion = [11]; % Calibrated to achieve stimulation of... |
e17501c88b4dc5024c684254ec64375ad45ae587e77f190104c9ab9a6f101c0c | MATLAB | 2,261 | 65 | function g = gaussn(f0,n)
% function gn = gaussn(f0,n) : generates the order n derivative of the
% gaussian window, centered at frequency f0
% The wavelet gn is real, but it is its analytic form that is
% synthetized first. The real part is then normalized by the analytical
% value of its energy (so, L2 normalizatio... |
fb54d297f32a3040061240feb3624df5db23bd6b7c27206d689fd3403d236a31 | MATLAB | 2,261 | 109 | %% demo of mixture of linear regression experts on an inverse problem
% Based on Bishop fig 5.21
% This file is from pmtk3.googlecode.com
clear all
close all
setSeed(0);
n = 200;
y = rand(n,1);
% eta = normrnd(0,0.05,n,1);
eta = randn(n,1)*0.05;
x = y + 0.3.*sin(2.*pi().*y) + eta;
data = [x(:) y(:)];
K = 3;
figure... |
09fae5d0e20e9443ee312c348588128b4f43838f16d58e0badaa19b1aac60004 | MATLAB | 2,262 | 50 | %Step 3 of CBIG Kong2019 Brain Parc Pipeline
%
%To run: 1. Open Matlab using salloc (ex: `salloc --mem-per-cpu 6G --time 2:00:00 --x11`)
% 2. source your config file containing the $CBIG_CODE_DIR variable
% 3. `cd` to the $CBIG_CODE_DIR/stable_projects/brain_parcellation/Kong2019_MSHBM/step3... folder
% 4. `cp` thi... |
23762f6272a25f1babcfa3907b77a3b5538d5118cce21d81f1a57df5d507c23f | MATLAB | 2,263 | 73 | function S = CP_Init(file)
%% Unload variables from file and initialize
[t_lim,L,div,s,D0,N_neur,tpr,uprr,uprt,uprd] = readvars(file,'Range','A1:J2');
[Kt,Kc,Kr] = readvars(file,'Range','K1:M5');
t = 0;
f = 0;
[X,Y] = meshgrid(1:div);
% Neuron matrix: [position mesh number ; upr(-1) ; upr]
NEUR = zeros(N_neur,3);
% F... |
514549ef3b43047c677d8e35979229dc532d321c18b492bb609da86d7504b692 | MATLAB | 2,263 | 94 | % This program is free software; you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation; either version 2 of the License, or
% (at your option) any later version.
%
% This program is distributed in the hope that it will be useful,... |
cabdf1855a3cfff50ed57c6071e4599676a4f54067841cccc947fdd6de0bfb2b | MATLAB | 2,263 | 64 | function [H] = rigidbody(f)
% RIGIDBODY creates the homogenous spatial transformation matrix
% for a 6 parameter rigid-body transformation
%
% Use as
% [H] = rigidbody(f)
%
% The transformation vector f should contain the
% x-shift
% y-shift
% z-shift
% followed by the
% pitch (rotation around x-axis, in d... |
0b59d3baceef30b8b71d8f7b9d649aa3888273654ff00b10ab103c625f099591 | MATLAB | 2,265 | 62 | function CBIG_VK2019_plot_loadings(out_dir,LC_behav_loadings,behav_names,LC_RSFC_loadings,nRois,signif_LC)
%
% This function plots the RSFC and behavior loadings of all
% significant latent components (LCs). Behavior loadings are plotted as
% barcharts and RSFC loadings are plotted as correlation matrices.
%
% Inpu... |
a8b19ed09e93eaca15d1d3b6f09ee859b2dc235857c7a102e56b175aef97479a | MATLAB | 2,265 | 85 | function vol = read_hdr(fname)
% Get a variety of information from a NIFTI-1 header.
% FORMAT vol = read_hdr(fname)
% fname - filename of image
% vol - various bits of information
% _______________________________________________________________________
% Copyright (C) 2008 Wellcome Trust Centre for Neuroimaging
%
%... |
0d3742600b5eb4afa919f11176fe4383bcc26a8050cfd8c05a19721e228fc8eb | MATLAB | 2,266 | 62 | function normalizeImage(src_folder_name,dst_folder_name,fileroot_name,channels,roundnum)
loadParameters;
%Check for any missing image file
for c_idx = 1:length(channels)
filename = fullfile(src_folder_name,sprintf('%s_round%.03i_%s.%s',...
fileroot_name,roundnum,channels{c_idx},params.... |
1a625637922b70b7ab6ca7439ec644cc8135295b9111a42ac58dec4849c7ed70 | MATLAB | 2,266 | 53 | % LineWithSphere - Determine intersection(s) of a line defined by
% two points in space with a sphere
%
% (published in appendix of Kayser J, Tenke CE, Clin Neurophysiol 2006;117(2):348-368)
%
% Usage: [P] = LineWithSphere ( P1, P2, Os, r );
%
% Implementation of simple linear geometric principl... |
4d5136d09126ab97286d88f798128bf26f4362d84e511d8fb0aa1ac2de3244a9 | MATLAB | 2,266 | 69 | function C = multiDiv( A, B, type )
% Matrix divide each submatrix of two 3D arrays without looping.
%
% type controls the matrix multiplication to perform (for each i):
% 1 - C(:,:,i) = A(:,:,i)\B(:,:)
% 2 - C(:,:,i) = A(:,:,i)\B(:,:,i)
% 3 - C(:,i) = A(:,:,i)\B(:,i)
% Corresponding dimensions of A and B m... |
59e73023d173eecde8826cd377486ba1b49516402f80cfa60656639a6d005008 | MATLAB | 2,266 | 56 | function I=affine_registration_image(par,scale,I1,I2,type)
% This function affine_registration_image, uses affine transfomation of the
% 3D input volume and calculates the registration error after transformation.
%
% I=affine_registration_image(parameters,scale,I1,I2,type);
%
% input,
% parameters (in 2D) : Ri... |
bfb99a4a06c1815f308656214614775a6f129b33fa2a8b40d3efffc8104c8fa9 | MATLAB | 2,267 | 66 | function num=getfilenum(f,pat,opt)
%GETFILENUM Get the index of a series of files.
% NUM = GETFILENUM (NAME, P) returns an array of numbers indexing
% the filenames (or directory names) matching NAME from the current
% directory. The indices are searched in the strings following the
% substring P. Wildcar... |
c1a0b20febacf4f21512af9dad4cf4631b3485bc6f0ba99203a0ae3163270e0a | MATLAB | 2,267 | 80 | %% Reproduce table 1 from "Robust statistical modeling using the T distribution
% Lange et al, JASA 1989
% The estimated coefficients are similar
% However, this does *not* reproduce the log likelihoods correctly
% The reason for this is not clear - is Lange evaluating the expected
% complete data loglik instead?
%
% P... |
94e07a1f6782a6b34fdac53ed37ac50a2a7f6a4279d6ebe46c906738111e92ea | MATLAB | 2,268 | 79 | function [shift] = xcorr3fft(image1,image2)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% xcorr2fft computes offsets between images image1 and image2 based
% on Phase Correlation method. image1 & image2 are assumed to have
% the same dimensions.
%
% Written by: Sebastian J Streich... |
d1bd5ec2849cdccea22302c497aad1331c18d870d21d048bb053ea02c60edb7c | MATLAB | 2,268 | 64 | function E=strain(Ux,Uy,Uz)
% Calculate the Eulerian strain from displacement images
%
% E = STRAIN(Ux,Uy) or (3D) E = STRAIN(Ux,Uy, Uz)
%
% inputs,
% Ux,Uy: The displacement vector images in
% x and y direction (same as registration variables Tx, Ty)
% Uz: The displacement vector image in z d... |
da12b53ba19e64d32b7bd0ade56c4b326f44bc9debd0bc2b55ad87fa34852ce7 | MATLAB | 2,268 | 89 | % This program is free software; you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation; either version 2 of the License, or
% (at your option) any later version.
%
% This program is distributed in the hope that it will be useful,... |
db004e9e625e79d9247403685109c1531ff9d8d2daeab9686a1a80583d04623c | MATLAB | 2,269 | 66 | % MONTAGES2 [4D] Used to display R sets of T images each.
%
% Displays one montage (see montage2) per row. Each of the R image sets is
% flattened to a single long image by concatenating the T images in the
% set. Alternative to montages.
%
% USAGE
% varargout = montages2( IS, [montage2prms], [padSiz] )
%
% INPUTS
% ... |
156b78f4c500e2a3c20f34c673255f8ad963790364a5c0c43cb9763bd7906f8a | MATLAB | 2,270 | 50 | %Step 3 of CBIG Kong2019 Brain Parc Pipeline
%
%To run: 1. Open Matlab using salloc (ex: `salloc --mem-per-cpu 6G --time 2:00:00 --x11`)
% 2. source your config file containing the $CBIG_CODE_DIR variable
% 3. `cd` to the $CBIG_CODE_DIR/stable_projects/brain_parcellation/Kong2019_MSHBM/step3... folder
% 4. `cp` thi... |
1722806115de3994db8ce8685322980a752067529451435c4de3b6d96d9e8492 | MATLAB | 2,270 | 50 | %Step 3 of CBIG Kong2019 Brain Parc Pipeline
%
%To run: 1. Open Matlab using salloc (ex: `salloc --mem-per-cpu 6G --time 2:00:00 --x11`)
% 2. source your config file containing the $CBIG_CODE_DIR variable
% 3. `cd` to the $CBIG_CODE_DIR/stable_projects/brain_parcellation/Kong2019_MSHBM/step3... folder
% 4. `cp` thi... |
fb4c45293cab244e854d33cecfef8ae16ce7153cb1dec9be02d8cb8d9d6a6211 | MATLAB | 2,270 | 81 | % read_eeglabheader() - import EEGLAB dataset files
%
% Usage:
% >> header = read_eeglabheader(filename);
%
% Inputs:
% filename - [string] file name
%
% Outputs:
% header - FILEIO toolbox type structure
%
% Author: Arnaud Delorme, SCCN, INC, UCSD, 2008-
%1234567890123456789012345678901234567890123456789012345... |
b3fcf403c8ab5e45a827ac19edc0b34be9cf93095738e2787629b123c2834181 | MATLAB | 2,271 | 95 | %% EPOD DTI ROI analysis
%
% Saves to tracts_mean_XXX.txt in maindir defined below
%
% Toolbox dependencies:
% - DIPimage (dilation function can be reimplemented using other software if needed)
% - toolboxes-amc/gfx (optional, code at the end for visualization)
%
% maindir should point to TBSS-output folder
... |
e08682feaaa52808ff9677561dcd5b1c45c95d762eb3e6eab06665b4be572852 | MATLAB | 2,271 | 60 | function res = run_nanocolumn_autocorr_refAlign(params,fov)
%update later with documentation
exp_factor = params.exp_factor; %expansion factor, adjust as needed
parentdir= params.parentdir;
targetdir = params.targetdir;
nChannels = params.nChannels;
rmax = params.rmax;
pixel_size=params.pixel_size;
channels_rounds =... |
d6d4c265f9e199fa911db431362c7803051f4315e9e23f9250979e990f43382a | MATLAB | 2,272 | 73 | function tests = quantilenorm_cudaTest
tests = functiontests(localfunctions);
end
function setup(testCase)
if ~exist('logs')
mkdir('logs');
end
testCase.TestData.tempDir = '/mp/nvme0/tmp/testworks';
if ~exist(testCase.TestData.tempDir)
mkdir(testCase.TestData.tempDir)
end
... |
1bd8082102016c53eb2ba170221c6315e49c73c3fade152775e7c4ef15fba631 | MATLAB | 2,273 | 76 | function s = appendstruct(varargin)
% APPENDSTRUCT appends a structure to a structure or struct-array.
% It also works if the initial structure is an empty structure or
% an empty double array. It also works if the input structures have
% different fields.
%
% Use as
% ab = appendstruct(a, b)
%
% See also PRINTSTRUC... |
1cda47f68afff1195512b08433605d40c53a279fb9a47be9d4d62aba80ff6bfc | MATLAB | 2,274 | 68 | %% Setup path to engine
addpath(fullfile('Engine'));
%% Setup parallel port
numThreads = 24; % number of cores to be used
tic
ppool = gcp('nocreate');
if isempty(ppool)
tic
parpool(numThreads);
disp([newline 'Started parallel pool in ' num2str(toc) ' s']);
end
%% Load/process base... |
7f01dc70ff92ea4b414fa716b02eec7e82791a3fa5df2fe15b81033c4ee924f4 | MATLAB | 2,274 | 64 | function [D, ni] = find_nn(X, k)
%FIND_NN Finds k nearest neigbors for all datapoints in the dataset
%
% [D, ni] = find_nn(X, k)
%
% Finds the k nearest neighbors for all datapoints in the dataset X.
% In X, rows correspond to the observations and columns to the
% dimensions. The value of k is the number of neighbors t... |
bc2519be0ae485013a7a5c075e7ddb63d42bca95ed732b484f284cd792c69b40 | MATLAB | 2,274 | 54 | function plot_gaussian_kernel_replay(folder)
cd folder
load('significant_replay_events_wcorr.mat');
replay_idx= randi(length(significant_replay_events.track(1).spikes));
replay_event= significant_replay_events.track(1).spikes{replay_idx};
replay_dur= significant_replay_events.track(1).event_duration(replay_idx);
repla... |
c1468231a2270001b0c0bfc6b2331388c6058f3dad9fcf7b4be177ddc9138a4e | MATLAB | 2,274 | 64 | function model = hmmFitFullyObs(Z, Y, type, varargin)
%% Fit a fully observed HMM via mle/map
%
% Z - a cell array of observations of the discrete Markov backbone;
% each observation j is 1-by-seqLength(j).
%
% Y - a cell array of emission observations; each observation j is
% d-by-se... |
e577e089358d9b0da2f4c3247e5a817b305372b12ad9f9cc08a1524553801bb1 | MATLAB | 2,274 | 105 | % computes metrics on a bunch of data generated
% by crabsort.consolidate
function data_out = computePeriods(data, varargin)
if length(data) > 1
for i = 1:length(data)
data_out(i) = crabsort.computePeriods(data(i), varargin{:});
end
return
end
options.neurons = {};
options.ibis = [];
options.min_spikes_per_... |
659496a999c49c928e6e49d9b0b381b0bfb9c77631ef63784b33235625ff3a0f | MATLAB | 2,276 | 48 | for k = 1:length(Y)
clf;
y = Y(k);
% Display NIFTI slice
I = round(y/d1d2d3(2) + N1N2N3(2)/2);
S = squeeze(VT1(:, :, I)); % choose the Y cross-section
S = S(end:-1:1, end:-1:1)';
image([-DimensionX/2 +DimensionX/2], [-DimensionZ/2 +DimensionZ/2], S, 'CDataMapping', 'scaled');
c... |
a776cfd87c6bce7581598edb93c9135e1aca864a0476c123bad09b5f82e458f2 | MATLAB | 2,276 | 100 | %% Test inference on the Alarm Network
%
%%
% This file is from pmtk3.googlecode.com
ntrials = 50;
setSeed(1);
loadData('alarmNetwork');
G = alarmNetwork.G;
CPT = alarmNetwork.CPT;
nstates = alarmNetwork.nodeSizes;
nnodes = 37;
if libdaiInstalled
engines = {'jtree', 'libdaiJtree'};
else
engines = {'jtree'};... |
dbfd5cf184464910a9a74b181d6030038ac155437b3f493383acef47f600d29c | MATLAB | 2,276 | 86 | function [tMin,fMin,Q2Flip,output]=essential_distMinAngle(Q1,Q2,varargin)
NQ1=size(Q1,3);
NQ2=size(Q2,3);
if NQ1==1 && NQ2>1
Q1=repmat(Q1,[1 1 NQ2]);
NQ1=NQ2;
end
if NQ1>1 && NQ2==1
Q2=repmat(Q2,[1 1 NQ1]);
end
if NQ1>1
tMin=zeros(NQ1,1);
fMin=zeros(NQ1,1);
Q2Flip=zeros(6,3,NQ1)... |
a3004f3cd747377c31968511e3d92afa58d4c4c0eefc433e511eafd67087ce91 | MATLAB | 2,277 | 43 | % align ImageArray and keep result in ImageArray_Reg
function [ImageArray_Reg DeltaX DeltaY MaxValue] = Coarse_Reg(ImageArray, AlignRegion, MaxShiftX, MaxShiftY, MinCorrValue)
LastImageNumber = size(ImageArray,3);
BestImage = ImageArray(:,:,1); % Best Image should be first in ImageArray
RegionsProps = regionpro... |
f0bc30dc10abfa54b5724cb8b400f617ba2bd36caf3b89c6b32c35452004c794 | MATLAB | 2,277 | 85 | function v = VBA_indicator (x, S, inverse)
% // VBA toolbox //////////////////////////////////////////////////////////
%
% x = VBA_indicator (x, S, inverse)
% indicator (aka incidence or characteristic) vector of x wrt set S.
%
% IN:
% - x: K x N values to be converted. Indicator vectors are computed for
% eac... |
bf92bcd5a7cdf494eb1bea4fb2ae43d50905b44e6e268078a9e598063a59933e | MATLAB | 2,278 | 79 | %% Empirical Bayes Missouri Cancer Example
% Johnson and Albert p67, p24
% See also cancerRatesMh
%% Setup Data
% This file is from pmtk3.googlecode.com
clear data
data.y = [0 0 2 0 1 1 0 2 1 3 0 1 1 1 54 0 0 1 3 0];
data.n = [1083 855 3461 657 1208 1025 527 1668 583 582 917 857 ...
680 917 53637 874 395 581 588 ... |
1a2963324949d4ce3aa14b235582c02a1a7aca93e0655d0048f85ca98d94a9b0 | MATLAB | 2,279 | 128 | function LAN = hilbert_ind(LAN, Fre, Norm, baseline ,r_s, texto)
% v 0.0.1
% 3.12.2009
%
% Falta optimiza memoria
%
Sig = LAN.data;
srate = LAN.srate;
%if nargin < 7, cuantos= 1; end
if nargin < 6, texto = plus_text([' Hilbert']); end
if nargin < 5, r_s = []; end
if nargin < 4, baseline = []; end
if nargin < 3, N... |
fe42b1f0f7fa993b5f1201b5f1a32cb150c5fa4d4ace47f497869e1d3ed1d3d7 | MATLAB | 2,279 | 52 | classdef (Abstract = true) AdjMatrixFromNetX < adjmatrix.AdjMatrixFromFile
properties (Access = protected)
Method;
end
methods
function this = AdjMatrixFromNetX(method, params, loadOnInit, delAfterLoad)
% creates an adjacency matrix with NetworkX
%
% met... |
05ce9e1d5d635cc7ba64f8a2fc1a7e657c27b9e81b3dc2e737107574988facce | MATLAB | 2,280 | 69 | function rowNumber = selectMuscle_from40()
% Define the list of muscles
muscles = {
'Acromiodeltoideus'
'Anconeus'
'Biceps Brachii'
'Brachioradialis'
'Brachialis'
'Coracobrachialis'
'Extensor Carpi Radialis'
'Extensor Digitorum Communis 2'
... |
6150fd503840dfe8057602df03770fd86ce34a891762b163a092691eadf04388 | MATLAB | 2,280 | 100 | function [pval] = stata_cluster(c_cls, stat, nrandom,elec)
% v.0.0.9
%
% Realiza Cluster-Randomization-Analysis en cartas timepo-frecuencia
% en prueba por cambio de algoritmo de clusters
%
% un electrodo por ahora
% cls -> custers detectados por corrention.m , en { [cluste1] [cluster2] }
%
% P Billeke
%
%
% 9 agosto ... |
77acff1a7acad1d07a754739c643eb1b7719664eaf757db32ad85116f42fde68 | MATLAB | 2,280 | 87 | %% Illustrate EM for PCA
%PMTKauthor Cody Severinski
% Some code has been reused by pcaFitEm
setSeed(10);
n = 25; d = 2;
mu0 = mvnrnd(eye(1,d),eye(d),1);
Sigma = [1,-0.7;-0.7,1];
X = mvnrnd(mu0,Sigma,n);
k = 1;
mu = mean(X);
X = X - repmat(mu, n, 1);
X = X'; % algorithm in book uses [d,n] dimensional X
% Generating ... |
d91d1f9690cd560df3906318d719343972a51d8436264b7e6b2b7c9013ea1d9e | MATLAB | 2,281 | 71 | function errorbar_tick(h,w,xtype)
%ERRORBAR_TICK Adjust the width of errorbars
% ERRORBAR_TICK(H) adjust the width of error bars with handle H.
% Error bars width is given as a ratio of X axis length (1/80).
% ERRORBAR_TICK(H,W) adjust the width of error bars with handle H.
% The input W is given as a rat... |
4663c260ba31e2b80fc30d4aa916f67504bcbc1129e046e37a7be6808603f635 | MATLAB | 2,282 | 102 | function subSuperGaussPlot()
% Plot sub-Gaussian, Gaussian, and super-Gaussian (Laplace) distributios
% in 1d and 2d
%Generalized Gaussian distribution with mean 0, scale 1, and shape 8
%(see http://en.wikipedia.org/wiki/Generalized_normal_distribution)
%PMTKauthor Kevin Swersky
setSeed(0);
figure; hold on... |
4a1f5d5081c23d829004e1ffaf224edecfc1039d08b9d0bdfabdefad8eef504d | MATLAB | 2,282 | 50 | clear
clc
close all
nb_models = 1000;
stimAmp_step = [-53];
% stimAmp_diffusion = (2:0.1:2.5);%-53*(0.5:0.3:1.5);
t = 0:100;
Istim = get_diffusion_current(t, 1);
max_Istim = max(Istim);
% stimAmp_diffusion = unique(round(stimAmp_diffusion*max_Istim));
stimAmp_diffusion = [11]; % Calibrated to achieve stimulation of... |
a9376f8f3eefcc880abccd62059b502d2e41c38ee58146f65551cc7618f1127a | MATLAB | 2,282 | 54 | function [GwaveInterp]=WaveformCalculate(Gwave,G,delta,TR,nbins,nOscillations,Waveform)
%%
%Define constants
G=G*10^-5;
%%
%Correct for short pulse approximation
if nbins==1
G=G*delta/TR;
end
%%
%Generate Full Gradient Waveform
GwaveFull=zeros([1,abs(Gwave(end))]);
GwaveFull(abs(Gwave))=1.*sign(Gwave).*G;
%%
%Inter... |
b91e04ebb535e0e83abbb29da8b7da2a736f81b8ba7be577143975a2d1582b12 | MATLAB | 2,282 | 75 | function labels = saveSensorsToFile(paths, subj_match, ss, output)
numView = 10;
cfg = [];
cfg.dataset = cellfun(@(x) [paths.rawdata '/' x], subj_match.ds, 'UniformOutput', false);
cfg.dataset = cfg.dataset{ss};
cfg.channel = {'MEG'};
sensor_level... |
caf7644403a223e115da4b0ee68249b36cd58178d7231d25703507a66c1b2e5c | MATLAB | 2,282 | 75 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%% wrapper_full_calibration.m -- A wrapper for the calibration runtime. %%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function []=set_dipoles(pat_ix)
model = 'german7';
inverse_model = 'german3';
pat_cell ... |
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