sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
caac332c430bf70ca4fbe71f2c2b8dd855f3dad9cf0860eeb8d889ad6017ec46 | MATLAB | 9,281 | 266 |
%
shifting_key_n = floor(tiling_info.z_pixel./z_truncate);
% shifting_key_n = 20;
% z_truncate = floor(tiling_info.z_pixel./shifting_key_n);
clear stitching_queue tform
kk = 0;
for ii = 1:size(read_file_name,1)-1
for jj = 1:size(read_file_name,2)
kk = kk+1;
stitching_queue(kk).tile_1 = ... |
7260230b3b063aa9b7a3230c39b118bb6de34b48b25a37be5cab70dd42cd8960 | MATLAB | 9,289 | 301 | function [x y pos trials map mapping] = getBehavEvents_linearTrack(pos,bins)
dbstop if error
scatter(pos(:,8),pos(:,10),'.')
% axis([-1 1 -1 1])
[x y]=ginput();
cx = x(end-1:end);
y = y(end-1:end);
dist(:,1)=fastrms(abs(pos(:,8)-x(1))+abs(pos(:,10)-y(1)),120);
dist(:,2)=fastrms(abs(pos(:,8)-x(2))+abs(pos(:,10)-y(2)),1... |
a4e965787687eb63a454c6cfd9041a02096dd4ef9c49ac8c3660ea4677ec6bcf | MATLAB | 9,293 | 328 | function [chansel, trlsel, cfg] = rejectvisual_channel(cfg, data)
% SUBFUNCTION for ft_rejectvisual
% determine the initial selection of trials
ntrl = numel(data.trial);
trlsel = true(1, ntrl);
% determine the initial selection of channels
nchan = numel(data.label);
chansel = true(1, nchan);
% compute the sampl... |
cbee11e016b1f7fa30214bbd572f1c8003405653d3155c9a0c4f69ab6af8d990 | MATLAB | 9,299 | 156 | function [DegreeCentrality_PositiveWeightedSumBrain_LH, DegreeCentrality_PositiveWeightedSumBrain_RH, DegreeCentrality_PositiveBinarizedSumBrain_LH, DegreeCentrality_PositiveBinarizedSumBrain_RH, GHeader_LH, GHeader_RH] = y_DegreeCentrality_Bilateral_Surf(InFile_LH, InFile_RH, rThreshold, OutputName_LH, OutputName_RH, ... |
8de44a684a7df051125a77928f05dd34b64d321699a20734dd66985f1a71c13b | MATLAB | 9,314 | 196 | function model = combineModels(modelArray,simType)
% arguments
% modelArray (1,:) MCmatlab.model
% simType (1,:) char
% end
% Verify that G properties are identical
Gprops = {'nx','ny','nz','Lx','Ly','Lz','mediaPropertiesFunc','mediaPropParams','geomFunc','geomFuncParams'};
for iProp = 1:numel(Gprops... |
b60c6ecdd560f221e83e0c08d8000d6d2541b2c2121629e835a7817f2e1218cb | MATLAB | 9,314 | 231 | function varargout = h_searchForGroupGUI3(varargin)
% H_SEARCHFORGROUPGUI3 M-file for h_searchForGroupGUI3.fig
% H_SEARCHFORGROUPGUI3, by itself, creates a new H_SEARCHFORGROUPGUI3 or raises the existing
% singleton*.
%
% H = H_SEARCHFORGROUPGUI3 returns the handle to a new H_SEARCHFORGROUPGUI3 or t... |
f49f6587e0bf74bf4c2a597666d0980fb90b1c135e79e2a9e9bac7acd6811ee7 | MATLAB | 9,315 | 264 | function [allRct, allSim, allIc] = kernelTracker( I, prm )
% Kernel Tracker from Comaniciu, Ramesh and Meer PAMI 2003.
%
% Implements the algorithm described in "Kernel-Based Object Tracking" by
% Dorin Comaniciu, Visvanathan Ramesh and Peter Meer, PAMI 25, 564-577,
% 2003. This is a fast tracking algorithm that utili... |
22cf94bde726d8787cc004adaa424280331cedc6dacd899f62f954c1cfcc6e3c | MATLAB | 9,316 | 279 | function hh = errorbar2016(varargin)
%ERRORBAR Plot error bars along curve
% ERRORBAR(Y,E) plots Y and draws a vertical error bar at each element of
% Y. The error bar is a distance of E(i) above and below the curve so
% that each bar is symmetric and 2*E(i) long.
%
% ERRORBAR(X,Y,E) plots Y versus X with s... |
303584e1526a1a5af4f813606af3da0f0d02707a3612d76031efc5305663f296 | MATLAB | 9,326 | 223 | function [cfg] = ft_topoplotIC(cfg, comp)
% FT_TOPOPLOTIC plots the topographic distribution of an independent
% component that was computed using the FT_COMPONENTANALYSIS function,
% as a 2-D circular view (looking down at the top of the head).
%
% Use as
% ft_topoplotIC(cfg, comp)
% where the input comp structure ... |
cfcc95954be5d4b641365685187959e1242ca812131639c290b30c890a1aea77 | MATLAB | 9,327 | 356 | % Imbed a file menu to any figure. If file menu exist, it will append
% to the existing file menu. This file menu includes: Copy to clipboard,
% print, save, close etc.
%
% Usage: rri_file_menu(fig);
%
% rri_file_menu(fig,0) means no 'Close' menu.
%
% - Jimmy Shen (jimmy@rotman-baycrest.on.ca)
%
... |
bf59ee8c26bb2a04adb701ebe954357ba9b0da16b7b5be3e4d805e3385a3e39c | MATLAB | 9,331 | 288 | function varargout = ginput_w(arg1)
%GINPUT Graphical input from mouse.
% [X,Y] = GINPUT(N) gets N points from the current axes and returns
% the X- and Y-coordinates in length N vectors X and Y. The cursor
% can be positioned using a mouse. Data points are entered by pressing
% a mouse button or any key on t... |
7f77b3d7d2ec61cb895eeddee547a0c0a4cad63d4e0062e21e436cc3d200c72f | MATLAB | 9,336 | 278 | %--------------------------------------------------------------------------
% Pipeline to analyse DF/F activity for GAD67 project
%--------------------------------------------------------------------------
%
% >>> REQUIRED THIRD-PARTY CODES >>>
% - abfload (F. Collman). https://github.com/fcollman/abfload
%------... |
d66d1c8db023039def67b9ad1079dfea21b453bfd9a9e46f64135e3ab33d5aa2 | MATLAB | 9,337 | 288 | function [Xbest,vbest,idx,totalcost,poslambda,misscost] = ...
ChooseBestTrajectory_MissDetection(X,appearancecost,varargin)
% Select trajectory through CPR-generated replicate clouds
%
% X: [DxTxK] full CPR tracking results
% appearancecost: [TxK] scalar cost for each shape
%
% Xbest: [DxT] selected replicates repre... |
20d928055b1688d42ea1ff4f5ddc80261c6dea6620904957fc6e0ca89119457b | MATLAB | 9,341 | 226 | function [y_p, y_t, acc, pred_stats] = CBIG_KRR_test_cv( bin_flag, kernel_train, kernel_test, ...
y_resid_train, y_resid_test, y_orig_test, with_bias, lambda, threshold, saving_stats )
% [y_p, y_t, acc] = CBIG_KRR_test_cv( bin_flag, kernel_train, kernel_test, ...
% y_resid_train, y_resid_test, y_orig_test, lam... |
b20d45781ffea08f0b903d5dadcb6ff7d8fa2502ee26dca2e14e92daaa3f2df7 | MATLAB | 9,358 | 364 | function [info,meas] = fiff_read_meas_info(source,tree)
%
% [info,meas] = fiff_read_meas_info(source,tree)
%
% Read the measurement info
%
% If tree is specified, source is assumed to be an open file id,
% otherwise a the name of the file to read. If tree is missing, the
% meas output argument should not be specified.
... |
a9fe7f0b3d4cf66a3d2ff66eb795cad4f78895cf794012bc309cb2beba137b2b | MATLAB | 9,360 | 331 | function [chansel, trlsel, cfg] = rejectvisual_trial(cfg, data)
% SUBFUNCTION for ft_rejectvisual
% determine the initial selection of trials
ntrl = length(data.trial);
if isequal(cfg.trials, 'all') % support specification like 'all'
cfg.trials = 1:ntrl;
end
trlsel = false(1,ntrl);
trlsel(cfg.trials) = true;
% de... |
9f14ba4d78102040327c13ed38dd6cf30334cbe596ce358404f76a90017be382 | MATLAB | 9,363 | 240 | function grad = yokogawa2grad_new(hdr)
% YOKOGAWA2GRAD_NEW converts the position and weights of all coils that
% compromise a gradiometer system into a structure that can be used
% by FieldTrip. This implementation uses the new "yokogawa_meg_reader"
% toolbox.
%
% See also FT_READ_HEADER, CTF2GRAD, BTI2GRAD, FIF2GRAD,... |
9d3b733a78eb29b1d1136e7fafc6b39a7c26444a14b95fc41dd3ae60f4105cdd | MATLAB | 9,373 | 260 | function [ adjmat ] = meglegacy_calcConn( catdata, srate, varargin )
%MEGLEGACY_CALCCONN Calculate connectivity from a set of virtual sensor
% time series, across trials.
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% adjmat = meglegacy_calcConn(catdata, srate, ...)
%
%%%%... |
fee98dce8f590ac170e8b292a1a7808d510a0f55684a2e058b8612113d764554 | MATLAB | 9,373 | 260 | function [hRect,api] = imrectLite( hParent, pos, lims, ar, varargin )
% A 'lite' version of imrect [OBSOLETE: use imrectRot].
%
% There are significant problems using imrect in a larger GUI, mostly
% due to the fact that imrect is such a heavy object. This creates a
% simple, fast, and in some ways nicer version of im... |
f9deeb9efeb7012485b3da9dd1c7f4830a677d760118df9585c448e5083bd685 | MATLAB | 9,376 | 225 | % plot_spotcheck.m
% Sarah West
% 12/1/21
% Plots a subset of the saved "spotcheck" frames from preprocessing and
% saves the plots. Makes a plot for each stack, also a plot for each day.
function [] = plot_spotcheck(parameters)
dir_in_base = parameters.dir_in_base;
% For each mouse
for mousei = 1:... |
6c7c22d474df388a041f1bcca929cecb7954e67c6e0bc8150a4e1563d15461bb | MATLAB | 9,378 | 343 | function [xi,eta,F,out,K_opt] = VBEM_GM(y,K,options)
% function [xi,eta,F,theta,K_opt] = VBEM_GM(y,K,options)
% This function is a VB scheme for the MoG classifier.
% IN:
% - y : the pxn data matrix, where n is the number of
% 'observations' to be classified, and p is the dimension of each of
% these observation... |
579132ac0ca9f70426f5aef1baa5681a0c17e500c3216f8986ba316ef351b47f | MATLAB | 9,381 | 179 | function ImageArray_CorrAmp_fix = Advanced_Fix_Splitting(ImageArray_CorrAmp,...
FramesPerSequence, PersistenceChecker, PersistenceOption, MaxPersistence, TrackingMaskMethod, MinAreaTrackingMask,DisplayOn)
warning on all
warning off backtrace
warning off verbose
% PersistenceChecker=1
% MaxPer... |
8c0114331469b1d0f3cecfdbccaff9ba4d2967bd03ebc3b5759a487366940803 | MATLAB | 9,384 | 352 | %% Compare different classification algorithms on a number of data sets
% This is similar to classificationShootout, except we (1) pick a gamma for
% all methods to use, (2) also compare performance on larger data sets
% using linear kernels, (3) cross validate over a sparser range.
%%
% Based on table 2 of
% ""Learn... |
79edf697e82f14533a4b1e69af1658475b8e4ee9cce09e7c25d847c7d6e2da47 | MATLAB | 9,386 | 271 | function [Maxima,MaxPos,Minima,MinPos]=MinimaMaxima3D(Input,Robust,LookInBoundaries,numbermax,numbermin)
% V 1.0 Dec 13, 07
% Author Sam Pichardo.
% This function finds the local minima and maxima in a 3D Cartesian data.
% It's assumed that the data is uniformly distributed.
% The minima and maxima are calculated usi... |
4392f61c124da53041b48eda62b3fe372b0297e8ac71829574e971604a51b923 | MATLAB | 9,388 | 251 | %% computeSDO_testStatSig
% Having calculated SDO significance w/ computeSDO_performstats,
% screen significant combinations for later plotting;
% --> We can elementwise recreate these, as necessary
%// We use 2 types of stats: Sum-of-squared errors of the SDO (or
% derivative values) between the shuffles and unit, o... |
76bc97f35b573c939358d42012af09a387c5084dcd29b45247fd3367c2d6a90d | MATLAB | 9,388 | 259 | %% for passive touch, finds the onset of the first peak, late wave, and also the peak times
clear
close all
Fs = 2500;
%paths to the relevant data sets for Figure 2
dataPaths{1} = '/Users/danielgonzales/Desktop/Grids manuscript/Data/Passive Touch/1-2022-04-19_Baclofen_3-baseline/';
dataPaths{2} = '/Users/danielgonz... |
ac66853d879f2db73568f3b8e555f75bf93ad9c501dfe585a953fe8e63ba6933 | MATLAB | 9,391 | 298 | function [diagnostics,out] = VBA_getDiagnostics(posterior,out)
% derives post-hoc diagnostics of VBA's model inversion
% function [diagnostics,out] = VBA_getDiagnostics(posterior,out)
% Post-hoc diagnostics include: goodness-of-fit metrics, Volterra kernels,
% null model evidence, posterior entropies, etc...
% IN:
% ... |
ed7f6e9cd4fd95261fa4c7b75e26a994a2ff573112ecfd9764d01090df513c8d | MATLAB | 9,392 | 281 | function params = metamerAnalysis(oim,m,opts)
%
%-----------------------------------------
% params = metamerAnalysis(oim,m,opts)
%
% computes statistical parameters of an image
% within a family of overlapping, tiling
% regions defined by windows
% (see metamerParams.m and metamerSynthesis.m)
%
% oim: original image
... |
8282976e56abd2c64019fa20f5fd04250deab32aee2d7b8328664b5699b5dac5 | MATLAB | 9,398 | 247 | function Perm_Mixed_LCS_Figs2(dataOut,IM,B,params)
% This function is the same as Perm_Mixed_LCS_Figs except that it does not
% plot the block-wise FPR values. Also, it plots the FPR-p-vals for both
% Chi-squared and HG to see dynamic range
if ~exist('B','var'),B=1;end
Pth=0.05./B;
PthMcN=0.05;
[NNidx,Tidx,TNi... |
ae74abc64010f436b03bfc055f0ecb4a700f77d13879781ed6272d30dbb86de9 | MATLAB | 9,401 | 234 | ti = 0;
vs = 40;
tauk = 5; %Cambiar también dentro de la funcion de histeresis_model
gH = 1.6*10^-6;
gL = 0.5*10^-6;
Cm = 1*10^-9;
Vm = 0.1;
V1 = 2;
lamda_ini = 0;
Rs = 250000;
Vs = 0.7;
Vr = -0.4;
ns = 1;
nr = 1;
nt = (1/ns + 1/nr)^-1;
vt = (Vs/ns + Vr/nr)*nt;
I_tot = simulate_histeresis(vs,ti,tauk,gH,... |
016021a67ee73c3e78ec393172f64cfd439328168f457d883205afcfc5034963 | MATLAB | 9,408 | 263 | function [eta, Heta, inner_it, stop_tCG] ...
= tCG(problem, x, grad, eta, Delta, options, storedb, key)
% tCG - Truncated (Steihaug-Toint) Conjugate-Gradient method
% minimize <eta,grad> + .5*<eta,Hess(eta)>
% subject to <eta,eta>_[inverse precon] <= Delta^2
%
% See also: trustregions
% This f... |
c23ecc439932ab11dad8ae05eae6ecb80b054cdf2758f86a1bcc8c1f101603b7 | MATLAB | 9,409 | 223 | function [ acc_corr_train, acc_corr_test, mse_test, y_predict] = ...
CBIG_LRR_workflow_1measure( params )
% [ acc_corr_train, acc_corr_test, mse_test, y_predict] = ...
% CBIG_LRR_workflow_1measure( params )
%
% Inputs:
% params is a struct containing the following fields:
%
% --> Compulsory fields:
% - p... |
3f45b39bf4135d1a8bcc8825eae37837e2e50365fc1807c239f3cfa7b9f0c412 | MATLAB | 9,413 | 301 | function [fH,figNames,Pk] = meg_selectChannels(sessionDir,data)
% MEG_SELECTCHANNELS(sessionDir)
%
% INPUTS
% sessionDir
% data
% matrix time x channel x trial
%
% Karen Tian
% January 2020
%% channel selection method
selectPeak = 0; % sorts channels by ERF peak
selectThreshold = 1; % selects channels that cr... |
d9f0f93a9ec0ad62212ef527896ad09c816717da53dfd0d04cbd7bd6e20df263 | MATLAB | 9,414 | 271 | function [Maxima,MaxPos,Minima,MinPos]=MinimaMaxima3D(Input,Robust,LookInBoundaries,numbermax,numbermin)
% V 1.0 Dec 13, 07
% Author Sam Pichardo.
% This function finds the local minima and maxima in a 3D Cartesian data.
% It's assumed that the data is uniformly distributed.
% The minima and maxima are calculated usi... |
37dc02a0ccccff0212cc6978f5c6f8d6008582d6a0df590781348948087a06c6 | MATLAB | 9,415 | 277 | %% prediction Error
% Output Class for carrying the error predictions associated with the
% output measurement of two pxtDataCells
%
% Implemented as a class to reduce overhead w/ predictions.
%_______________________________________
% Copyright (C) 2024 Trevor S. Smith
% Drexel University College of Medicine
%
% Thi... |
5d5bfa7fe12e8ffe33508703844b8f8a2647672e153ce856d11445041ca026c7 | MATLAB | 9,425 | 261 | function [result] = VBA_susceptibility(posterior,out,ind)
% scores the susceptibility of u->y relationships w.r.t. model parameters
% [result] = VBA_susceptibility(posterior,out,ind)
% IN:
% - out/posterior: the output structures of the VBA inversion
% - ind: a structure containing the following fields:
% .u ... |
7c75850cec86bc7adae377a3941a47836c485aff51bd0e4931f7cd9771e6f35b | MATLAB | 9,426 | 173 |
function shuffled_track = run_shuffles(shuffle_choice,analysis_type,num_shuffles,decoded_replay_events)
% computes shuffles on replay events
% shuffle_choice- determines what type of shuffles will be performed, entered as a string
%
% analysis type- vector of 0's and 1's for which replaying
% scoring method is used [l... |
094488715ececd5617068f60b06b63ecdefb5bd5afcc40c6d6a405b34333a762 | MATLAB | 9,427 | 229 |
% Written by Tianyin Xu
% Edited by: Adam Wright
% Last modified: 20140711
% This function will create an R2 mean map from 100 randomly sampled
% datasets.
%Inputs:
% fMRI_data -- the fMRI object (created from load_nifti.m)
% physio -- the physiology file.
% Files created:
% R2mean_100trial_wholeBrain.nii.gz -- t... |
14f7c9c10182e586c8022a15a41e5a3d9bbd414a1e9ace1671dbf49b2d99363b | MATLAB | 9,431 | 304 | %% Gen splits, round1 track
trkSet50Tst200 = any(parts50(:,end-3:end),2);
nnz(trkSet50Tst200)
trkSet50Comp = any(parts50(:,2:end-4),2);
nnz(trkSet50Comp)
unique(trnSet50+trkSet50Tst200+trkSet50Comp)
save trnSplits_20180418T173507.mat -append trkSet50Tst200 trkSet50Comp
%% Browse results, round* track
load trnDataSH_... |
d6521afbc42eb62d4e8dfcc0d9d7c69a428aab982748386f733bb76b3901c552 | MATLAB | 9,435 | 246 | function [grandavg] = ft_sourcegrandaverage(cfg, varargin)
% FT_SOURCEGRANDAVERAGE averages source reconstructions over either multiple
% subjects or conditions. It computes the average and variance for all
% known source parameters. The output can be used in FT_SOURCESTATISTICS
% with the method 'parametric'.
%
% Alt... |
738298ceda42af3d884765981f3e9bd92ded1c57a602b4cf626d1d9fcb852e23 | MATLAB | 9,436 | 233 | function [spectrum,freqoi,timeoi] = ft_specest_wavelet(dat, time, varargin)
% FT_SPECEST_WAVELET performs time-frequency analysis on any time series trial data
% using the 'wavelet method' based on Morlet wavelets, doing convolution in the time
% domain by multiplication in the frequency domain.
%
% Use as
% [spectr... |
b4cc9621f6481b4035215883ae21cc82a64b948922b7ab56f1fb8afc7e160572 | MATLAB | 9,437 | 337 | %% Compare different classification algorithms on a number of data sets
% This is similar to classificationShootout, except we (1) pick a gamma for
% all methods to use, (2) also compare performance on larger data sets
% using linear kernels, (3) cross validate over a sparser range.
%%
% Based on table 2 of
% ""Learn... |
0246812228dc4006e4b75d6f7ae4ae43ad809c12cbe602457573bd202b6d7427 | MATLAB | 9,441 | 246 | classdef UncertainFramesModel < handle
% Holds computed data about bouts of frames with low tracker confidence
% for the current movie.
properties (Access=private)
quantileConfidenceThreshold_ = 0.99
% scalar double, the quantile threshold (0-1) for filtering bouts.
end
properties (Transient, Acce... |
7992935941afc9b553d23e311be8bbeab1dffc3884b3e775acd56d6f3757e007 | MATLAB | 9,441 | 186 | %% connectivity_and_cytoarchitecture
for init_project = 1
% set directories
GH = '/Users/cpaquola/Documents/GitHub/'; % github repo location
homeDir = [GH '/DMN']; % home directory
bbwDir = [GH '/BigBrainWarp']; % BigBrai... |
b23d58612b08e498353a0a9d6748eb7037314d3b298c64532a95f0416802b83e | MATLAB | 9,443 | 234 | function [data, varargout] = femdata_stnd_FD(mesh, frequency, varargin)
% FEMDATA_STND_FD Calculates data (phase and amplitude) for a given standard
% mesh at a given frequency (Hz). Outputs phase and amplitude in the
% structure DATA.
%
% SYNTAX:
% [DATA] = FEMDATA_STND_FD(MESH, FREQUENCY)
% [DATA] = FEMDATA_ST... |
fc1b4a113225854d18e7f785e1745112ccfadeca7a3cf4a41aa1f22ab47c93bd | MATLAB | 9,443 | 297 | classdef Container < handle
%uix.mixin.Container Container mixin
%
% uix.mixin.Container is a mixin class used by containers to provide
% various properties and template methods.
% Copyright 2009-2016 The MathWorks, Inc.
% $Revision: 1602 $ $Date: 2018-05-01 10:23:15 +0100 (Tue, 01 May... |
56dd12826e7e9e20ddc2b611cb9c8ffd6dbc2560175732070d8fd0fce3dcd2ef | MATLAB | 9,444 | 329 | % Cleaned-up version of init_calib.m
fprintf(1,'\nProcessing image %d...\n',kk);
eval(['I = I_' num2str(kk) ';']);
if exist(['wintx_' num2str(kk)]),
eval(['wintxkk = wintx_' num2str(kk) ';']);
if ~isempty(wintxkk) & ~isnan(wintxkk),
eval(['wintx = wintx_' num2str(kk) ';']);
... |
a9901069f989c68ce5ba7a2910447f0efbfaee94ab116893d2b682fe522d6660 | MATLAB | 9,446 | 304 | function F = srskelf(A,x,occ,rank_or_tol,pxyfun,opts)
% SRSKELF Strong recursive skeletonization factorization (symmetric
% positive definite only).
%
% F = SRSKELF(A,X,OCC,RANK_OR_TOL,PXYFUN) produces a factorization F of
% the interaction matrix A on the points X using tree occupancy
% paramet... |
d5ac9173982b212ed7f7cf26b2f11a2e12ef298f7b1e19f61c83a590fb7486d6 | MATLAB | 9,446 | 328 | %% Nodes intelligence theories
% Scope: Determining nodes corresponding to intelligence theories
% Date: 10.03.2023
% Author: Jonas A. Thiele
%% Multidemand (MD) Diacheck
schaefer_atlas = niftiread('Schaefer2018_100Parcels_17Networks_order_FSLMNI152_2mm.nii.gz');
multidemand_atlas = niftiread('Multiple dema... |
9703ac71170f078f59e18e4bb1e5c66e43ce76e92c6db7bce3ca249f3cbd9c39 | MATLAB | 9,448 | 183 | function PARAMS = initializeParameters( subjectName, subjectID )
% (c) Coraline Rinn Iordan 10/2017, 03/2018
if nargin < 2, error( 'Must provide subject name and ID.' ); end
initStartTime = GetSecs;
%%%%%%%%%%%%%
%%% SETUP %%%
%%%%%%%%%%%%%
rng( 'shuffle' );
PARAMS.SUBJECTNAME = subjectName;
PARAMS.SUBJECTID = su... |
9eda699bfeca8fc8b02bf0059e8a0a05230231e28326fefd8260852c1141763c | MATLAB | 9,449 | 320 | function [tbls,medmindist,kvals,savename] = ComputePixelPrecisionTable(gtdata,varargin)
[kfracs,nets,legendnames,colors,exptype,...
conddata,labeltypes,datatypes,...
pttypes,annoterrdata,...
savedir,savename,dosavefig,...
threshmethod,threshprctile,modeli,...
kvals] = myparse(varargin,'kfracs',.25:.25:2,...
... |
031e0b8e7f41b77e4ebc6c1cbbb65b21915a0ff1081c1a45f86a141c833177d0 | MATLAB | 9,454 | 236 | function VBA_spm_defaults
% Set the defaults which are used by SPM
%__________________________________________________________________________
%
% If you want to customise some defaults for your installation, do not
% modify this file directly, but create a file named spm_my_defaults.m
% instead, accessible from MATLAB... |
01b84b74832fa1fb308ccf8bbce6243486de9d52f8d94c6477aa7f585f5b95aa | MATLAB | 9,455 | 283 | classdef LabelLegendRoi < handle
properties(SetAccess=private)
xyData;
javaLegend;
btnCreate;
btns;
btnLbls;
map;
asked=false;
buildingMultiplePolygons=false;
dfltFile;
save_output=false;
output_folder=[];
ax;
ro... |
e59359e096f37f363e3542c42824d7799ddc463cba8ee3dab4a2a9a62d0cf55a | MATLAB | 9,471 | 296 | function [stat] = ft_networkanalysis(cfg, data)
% FT_NETWORKANALYSIS computes various network graph measures from
% between-channel or between source-level EEG/MEG signals. This function
% acts as a wrapper aroun the network metrics implemented in the brain
% connectivity toolbox developed by Olaf Sporns and colleague... |
3699db003f83c804575c59eeda62a8750987647e04e54887a36e97ee53e7b531 | MATLAB | 9,473 | 190 | classdef FlySongDetector < FeaturesDetector
properties
recording
% Multi-spectral analysis properties
taperTBP = 12;
taperNum = 20;
windowLength = 0.1;
windowStepSize = 0.01;
pValue = 0.05;
% Sine song properties
sineFreq... |
ff1de3e181c67a492f854f890686e6c8e6f8055c970ad2e20dfeda1f0f671383 | MATLAB | 9,474 | 448 | function [dat] = read_neuralynx_sdma(dataset, begsample, endsample, chanindx)
% READ_NEURALYNX_SDMA read specified channels and samples from a Neuralynx splitted DMA dataset
%
% Use as
% [hdr] = read_neuralynx_sdma(dataset)
% [dat] = read_neuralynx_sdma(dataset, begsample, endsample, chanindx)
%
% The splitted D... |
a04960d2a96fc5ec557864526f6c90f48ff3dd3042a24781cebdb18c0471fb45 | MATLAB | 9,478 | 295 | % add dependencies
addpath(genpath('C:/Code/wjn_toolbox-master'))
addpath(genpath('C:/Code/wjn_toolbox'))
addpath(genpath('C:/Code/leaddbs'))
addpath(genpath('C:/Code/spm12'))
%% Parcellate and export conmaps
input_images = {'alpha_functional_network.nii', 'beta_functional_network.nii'};
% parcellation_image = 'Autom... |
aa58e9f034abe451f7f2b944d02d005b1dcc0e3297e09150dac7c1a7b9e8d0e6 | MATLAB | 9,481 | 178 | function plot_rate_remapping(option,varargin)
f1= figure('units','normalized','outerposition',[0 0 1 1]);
parameters=list_of_parameters;
if strcmp(option,'TRACK_PAIRS')
if ~isempty(varargin)
switch varargin{1}
case 'wcorr'
load('rate_remapping_analysis_TRACK_PAIRS_wcorr');
... |
fccd5933ab147b5df9a7e237c16664092484bb73b212a2516c708b8656567122 | MATLAB | 9,488 | 218 | function [exclusion_info, varargout] = detect_bad_data(Dm, varargin)
% [out] = detect_bad_data(Dm)
% Detect bad rows/cols in matrix Dm.
% Detection is based on
% - the mode (most common) value along each row/col
% - the standard deviation of each row/col
% Also flags dataset for exclusion based ... |
1761cb8c826c0a521c78828eb60e5ddb30369e03bef168100acd643ab2bda4cb | MATLAB | 9,489 | 226 | function [bestpar, bestval, bestat, step, delay, p] = ...
fitparam (model, startpar, goalstat, typestat, randiter, optiter, tuneiter, nosession, statweight, parange)
% function [bestpar, bestval, bestat, step, delay, p] = ...
% fitparam (model, startpar, goalstat, typestat, randiter, optiter, tuneiter, nosession,... |
54736f6c9fe8d58700bb880803807e483daa994b0b2b5f7687ac120851cd136d | MATLAB | 9,490 | 213 | %% Script to make struct array for ACR1 tracked data
% This only works with speicific folder,subfolder arrangement as in
% selected_60-30_powdered_ACR1
subFolders = dir(pwd);
realSubFolders = subFolders([subFolders.isdir]');
realSubFolders = realSubFolders(3:end);
% Initialise video temporal parameters
fps = 3... |
9d62c66d0c4dcba47e7d01da33eff532981d97fa5c0b8d5d26d2ce2313118c91 | MATLAB | 9,495 | 206 | %Analyze_Frontloading_Demo.m
%This script analyzes alcohol drinking patterns to assess if
%alcohol front-loading is present using the following
%criteria:
%1*. Of three detected change points, the change point with the best fit
%is the earliest and/or is within the first half of the session. This
%becomes the referenc... |
b310f85fffab5b65df7bbb637aaa5c9698d5b60c34dad342a9753160aa5caba8 | MATLAB | 9,495 | 240 | function [struct_edgevec, func_edgevec, common_ids, Initialization_Parameters] = ...
fcn_SFC_Initialization_hl(work_dir, expected_ids, thresh_mode, preserve_percent, results_dir)
% FCN_SFC_INITIALIZATION_HL Prepare SC and FC data for the SFC Toolbox.
% This function receives all settings from the GUI, verifies SC/F... |
627a1e673db83550e2996bb7fbc217a682e70607267af9cf5886878e96c18782 | MATLAB | 9,504 | 229 | function embedding = optimize_layout3(head_embedding, tail_embedding, ...
head, tail, n_epochs, n_vertices, epochs_per_sample, a, b,...
gamma, initial_alpha, negative_sample_rate, verbose, min_dist)
%OPTIMIZE_LAYOUT2 Another version of optimize_layout.m that slightly
% optimizes the speed for MATLAB; in particu... |
04b17d26382f57750f86e244dc2df40af606bacd76bb1f74050e82f0605ac824 | MATLAB | 9,515 | 163 | function st = spm_cfg_st
% SPM Configuration file for Slice Timing Correction
%__________________________________________________________________________
% Copyright (C) 2005-2016 Wellcome Trust Centre for Neuroimaging
% $Id: spm_cfg_st.m 7591 2019-05-15 10:57:38Z john $
%---------------------------------------------... |
9d6695fdf97e2feb68c863fe09920b5436335cc81a49492609164ce40b3cc46e | MATLAB | 9,519 | 300 | %% tsdata_to_infocrit
%
% Calculate Akaike and Bayesian information criteria for VAR models from time series
% data
%
% <matlab:open('tsdata_to_infocrit.m') code>
%
%% Syntax
%
% [aic,bic,moaic,mobic] = tsdata_to_infocrit(X,morder,regmode,verb)
%
%% Arguments
%
% See also <mvgchelp.html#4 Common variable names and ... |
ee259565b85fb83f413869454eb97a301b8fe0c7b5cdce02e79d510977330915 | MATLAB | 9,520 | 126 | function DPABI_Stability_run(Cfg)
% FORMAT DPABI_Stability_run(Cfg)
% Perform Stability Analysis. Based on Li, L., Lu, B., Yan, C.G., 2019. Stability of dynamic functional architecture differs between brain networks and states. Neuroimage, 116230.
%
% Input:
% Cfg - the parameters for stability analysis.
% Output:
% ... |
c673ceca203d4258442b44de02ee9353b0c55b76e472e1ef351bd227d57c7266 | MATLAB | 9,521 | 111 | function map = colmap(col,inv)
% create colormap
%
% make colormaps based on pycortex:
% https://gallantlab.github.io/colormaps.html
%
% colorset
% {'Paired','viridis','terrain','rainbow','Spectral','Pastel1_r','RdBu_r','coolwarm'}
%
% inv: if 1 inverse color map;
%
%
%
%
% Written by horikawa-t 20200225
%% ... |
39523a5b9629b0ec63f61acd112f180b261e08f973d82c1bc30ce0805dc5f161 | MATLAB | 9,522 | 251 | % MAIN SCRIPT
% 3rd step of the multivariate moderation model framework:
% runs the actual multivariate moderation model presented below
% with the selected number of PCs
% The idea here is to reduce the fMRI contrast in the chosen voxels to a
% number of principal components and use them in a multivariate regressi... |
c44d9219eca3d18f21ee1e4a68c8da67848b4279d7fde09d5700cdf5d2bc5d6a | MATLAB | 9,524 | 262 | function [distance_errors] = DG_ExSeq_reg_quality_vMS(img1,img2,params)
% Originally written by Dan Goodwin, modified by Margaret Schroeder
% Last update 12/14/22 (with comments), although original modifications
% made far earlier in 2022
XRANGE = params.xrange;
YRANGE = params.yrange;
%determine... |
4ee4962dbd8663aa82b68bf3cef52fd17eb4cf7934a497a0024f8ead84ca6af2 | MATLAB | 9,525 | 298 | function M = essentialfactory(k, strSigned)
% Manifold structure to optimize over the space of essential matrices.
%
% function M = essentialfactory(k)
% function M = essentialfactory(k, 'signed')
% function M = essentialfactory(k, 'unsigned')
%
%
% Quotient representation of the essential manifold: deals with ... |
a49b1e4846f12ac104e9c91e0299d1f643b569a67fe7973e81035b3a6c60feaf | MATLAB | 9,534 | 336 | function Result = Gradient_Calculation( ...
InputData, InputFiles, InputType, ...
OutDir, AlignmentType, ReferenceUI, ...
nIterations, SparsityThreshold,nComp)
% =========================================================
% DPABI_Gradient
% =========================================================
% Function... |
445d02685d1179f01e37ca45285a93d38764b02ec9fce4e970907c9c87e43a4d | MATLAB | 9,553 | 255 | function [grandavg] = ft_timelockgrandaverage(cfg, varargin)
% FT_TIMELOCKGRANDAVERAGE computes ERF/ERP average and variance
% over multiple subjects or over blocks within one subject
%
% Use as
% [grandavg] = ft_timelockgrandaverage(cfg, avg1, avg2, avg3, ...)
%
% where
% avg1..N are the ERF/ERP averages as obtai... |
eb9cb8837613d117f4e0444463c34b877b2922cadfc4068604e38e73de6938c9 | MATLAB | 9,553 | 255 | function [grandavg] = ft_timelockgrandaverage(cfg, varargin)
% FT_TIMELOCKGRANDAVERAGE computes ERF/ERP average and variance
% over multiple subjects or over blocks within one subject
%
% Use as
% [grandavg] = ft_timelockgrandaverage(cfg, avg1, avg2, avg3, ...)
%
% where
% avg1..N are the ERF/ERP averages as obtai... |
78124136a272d07592a8ed96e99f0fcb07e7edd034368dc85632060e3c45f84c | MATLAB | 9,558 | 252 | function ft_audiovideobrowser(cfg, data)
% FT_AUDIOVIDEOBROWSER reads and vizualizes the audio and/or video data
% corresponding to the EEG/MEG data that is passed into this function.
%
% Use as
% ft_audiovideobrowser(cfg)
% or as
% ft_audiovideobrowser(cfg, data)
% where the input data is the result from FT_PREPR... |
ba7fa7ec495afb5e7ee59c3715a568786f741ef59fb2837430d96f217c365d5f | MATLAB | 9,558 | 277 | function arr = exindex(arr, varargin)
%EXINDEX extended array indexing
% ARROUT = EXINDEX(ARRIN, S1, S2, ...) indexes a virtual array made by
% extending ARRIN with zeros in all directions, using subscripts S1, S2
% etc.
%
% ARROUT = EXINDEX(ARRIN, S1, R1, S2, R2, ...) extends ARRIN using rule
% R1 on the fir... |
5dbc12b2a38af76cb26a61c578d9f225a8e1a534f86c14d807250c94051ae76b | MATLAB | 9,559 | 282 |
loadParameters;
params.registeredImagesDir = '/Users/Goody/Neuro/ExSeq/exseq20170524/4_registration-cropped';
params.basecallingResultsDir = '/Users/Goody/Neuro/ExSeq/exseq20170524/6_base-calling';
params.punctaSubvolumeDir = '/Users/Goody/Neuro/ExSeq/exseq20170524/6_base-calling';
% filedir = 'C:\Users\chenf\... |
b9bf9ac2d5abe614be636fa5de25f23ea86cda7e7af1e10966035a91efb80a71 | MATLAB | 9,561 | 177 | function [Data_Corrected, ClusterSize, Header]=y_GRF_Threshold(StatsImgFile,VoxelPThreshold,IsTwoTailed,ClusterPThreshold,OutputName,MaskFile,Flag,Df1,Df2,VoxelSize,Header, dLh)
% function [Data_Corrected, ClusterSize, Header]=y_GRF_Threshold(StatsImgFile,VoxelPThreshold,IsTwoTailed,ClusterPThreshold,OutputName,MaskFil... |
e056b983181b464c9d7bfce9e38917b896cb416aacbf8f91cf2477568ff4c43e | MATLAB | 9,562 | 237 | function [nev] = read_neuralynx_nev(filename, varargin)
% READ_NEURALYNX_NEV reads the event information from the *.nev file in a
% Neuralynx dataset directory
%
% Use as
% nev = read_neuralynx_hdr(datadir, ...)
% nev = read_neuralynx_hdr(eventfile, ...)
%
% Optional input arguments should be specified in key-valu... |
11501ff240a4642acb3565481ac2fa978a994dc6d9265be868594b970c984353 | MATLAB | 9,563 | 208 | function [] = Twave_personalisation_POMs_ToRORdLand(nb_models,celltype)
% Population of models generation for T-wave personalisation
% Adapted from scriptDemonstration_2_ParameterComparison.m:
% TODO: rename all endo_ variables to not say endo_
%% Setting parameters
param.bcl = 800; % basic cycle length in ms
param.mod... |
5f21ea9df4c890d5f0ed2074592e911fa33b2c57c90f95a4290e7c347e3ef79a | MATLAB | 9,564 | 234 | % 431-400 Year Long Project
% LA1 - Medical Image Processing 2003
% Supervisor : Dr Lachlan Andrew
% Group Members : Alister Fong 78629 a.fong1@ugrad.unimelb.edu.au
% Lee Siew Teng 102519 s.lee1@ugrad.unimelb.edu.au
% ... |
7b4b42d019b6255e521572d70ecc2ae19debd1acff4886ceb7b4adf6aea0ae5f | MATLAB | 9,566 | 275 | function [np_marker] = np_readmarker (filename, idx_begin, data_length, option)
%
% function [np_marker] = np_readmarker (filename, idx_begin, data_length, option)
%
% np_readmarker reads marker from a NEURO PRAX marker file (*.EE_).
%
% Syntax:
%
% [np_marker] = np_readdata(filename,idx_begin,data_length,'samples');... |
502dfca17147b25954f027d0eec1334475cc2b83573083745a25d34877995a87 | MATLAB | 9,568 | 297 | function [stats,st] = lme_mass_fit_Rgw(X,Zcols,Y,ni,Th0,Rgs,Surf,fname,...
Dtype,sptm,prs,e)
% [stats,st] = lme_mass_fit_Rgw(X,Zcols,Y,ni,Th0,Rgs,Surf,fname,Dtype,sptm,prs,e)
%
% Region-wise linear mi... |
e4278ffa7d802af04bf477e4cdce1b92a2d6bc6604c379226bb14d5411239971 | MATLAB | 9,569 | 313 | function wlPlot_plotMatrixBurstRates(cfg, ...
rate_avg, rate_dev, rate_sem, bg_avg, bg_dev, bg_sem, ...
timebins, bandtitles, bandlabels, channelnames, ...
figtitle, filelabel, timetitle)
% function wlPlot_plotMatrixBurstRates(cfg, ...
% rate_avg, rate_dev, rate_sem, bg_avg, bg_dev, bg_sem, ...
% timebins, b... |
60f995f4ca18c4ef1e4020426c27d89d32258aaddc3fd5472e8e8c7ede6abdda | MATLAB | 9,572 | 215 | function write_plexon_nex(filename, nex)
% WRITE_PLEXON_NEX writes a Plexon *.nex file, which is a file
% containing action-potential (spike) timestamps and waveforms (spike
% channels), event timestamps (event channels), and continuous variable
% data (continuous A/D channels).
%
% Use as
% write_plexon_nex(filenam... |
a9525166fc6b4fc4d2fd69fe2811a8f8b0ef1012bdb64f86a9b9a86c7bd2d6a1 | MATLAB | 9,576 | 249 | function [timelock] = ft_timelockanalysis(cfg, data)
% FT_TIMELOCKANALYSIS computes the timelocked average ERP/ERF and
% optionally computes the covariance matrix.
%
% Use as
% [timelock] = ft_timelockanalysis(cfg, data)
%
% The data should be organised in a structure as obtained from the
% FT_PREPROCESSING functio... |
3a0d9e27557c37e7acdc2b9c0073511414d82bc972205902ec0294decfca5722 | MATLAB | 9,580 | 228 | function [X, maxdot] = packing_on_the_sphere(d, n, epsilon, X0)
% Return a set of points spread out on the sphere.
%
% function [X, maxdot] = packing_on_the_sphere(d, n, epsilon, X0)
%
% Using optimization on the oblique manifold, that is, the product of
% spheres, this function returns a set of n points with uni... |
4da8264696888f8504936cf5317c0d757a88cc64785ab2cbfdc9464e92f8cbde | MATLAB | 9,581 | 228 | % create_mice_all_randomMotorizedTreadmill.m
% Sarah West
% 11/30/21
% Creates and saves the lists of data you'll use for the given experiement
% (mouse names and days of data collected).
% Each row of the structure is a different mouse.
%% Parameters for directories
clear all;
experiment_name='Random Motorized ... |
47650ed4c0fe76c69f180caa5665fae92ccea1ad2f077859775adc9a3fe87e5b | MATLAB | 9,583 | 266 | function CBIG_GraphVis_17network(data, netw_used, hemi, fileout, seed_in)
% CBIG_GraphVis_17network(data, netw_used, hemi, fileout, seed_in)
% Example usage:
%
% CBIG_GraphVis_17network(corr_mat, [1 3 4 6 7 9 10 11 12 15 16], 'lh', 'test', 20);
% will plot graph with left hemisphere ROIs of networks 1 3 4 6 7... |
0c35ca7d23a21ca92a02882524346e8697fd5e20ee2bafabef1ced4d6dd47a60 | MATLAB | 9,592 | 299 | function [result] = ft_test_run(varargin)
% FT_TEST_RUN
% Copyright (C) 2017, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.fieldtriptoolbox.org
% for the documentation and details.
%
% FieldTrip is free software: you can redistribute it and/or modify
% it under the terms of the GNU Gener... |
29597da1a1a2fe8b23391c68b6a3c081e05e6eed3d63abd61472f180a1d25cf1 | MATLAB | 9,598 | 180 | function plot_correlation_sleep_evolution(folders, method, epoch, option)
switch option
case 'time'
bin_edges= 60*[[0:15:60]' [30:15:90]'];
case 'events'
bin_edges= [[1:70:(300-70)]' [70:70:300]'];
end
folders= folders(:,1);
master_folder= 'X:\BendorLab\Drobo\Neural and Behavioural Data\Rate r... |
88c294c9769158fd1ebca7426ca3f8433df969e97a28e9321715396b8c8d6969 | MATLAB | 9,607 | 243 | %% var_to_autocov
%
% Return autocovariance sequence for a VAR model
%
% <matlab:open('var_to_autocov.m') code>
%
%% Syntax
%
% [G,info] = var_to_autocov(A,SIG,acmaxlags,acdectol,aitr,maxiters,maxrelerr)
%
%% Arguments
%
% See also <mvgchelp.html#4 Common variable names and data structures>.
%
% _input_
%
% A ... |
7b6c7655e902df7b1ed78f3d86bd88d5c01581949b653d05e4ac79eb8041bf76 | MATLAB | 9,608 | 162 | function sPPI_and_gPPI_with_deconv(stat_path,exp_folder,N,N_ROIs,q_level,ground_truth)
% ========================================================================
% Ruslan Masharipov, October, 2023
% email: ruslan.s.masharipov@gmail.com
% ========================================================================
tic
for... |
4392eee7bd345796083f3e8943daf09b2848b9697eabb6213c26ba3ab6d52fc2 | MATLAB | 9,611 | 285 | function [regional_SFC, GSP_SFC_Parameters] = fcn_calculate_GSP_SFC_regional_hl(results_dir, common_ids, roi_signals_dir, opts)
% FCN_CALCULATE_GSP_SFC_REGIONAL_HL Regional SFC using Graph Signal Processing.
%
% This toolbox version receives all inputs from SFC_Toolbox and requires SC
% source input to be a folder. It ... |
2f6e1f22378ba0d443b3205b5a38d602fa44f27065c4f5f05c9f2c3a584bb5fa | MATLAB | 9,617 | 229 | function varargout = seqReaderPlugin( cmd, h, varargin )
% Plugin for seqIo and videoIO to allow reading of seq files.
%
% Do not call directly, use as plugin for seqIo or videoIO instead.
% The following is a list of commands available (srp=seqReaderPlugin):
% h = srp('open',h,fName) % Open a seq file for reading ... |
38100d0a7a161281c28ae31e71edcda3eb646af76cf364f2d1e3d6f4b4b14b75 | MATLAB | 9,617 | 217 | function [spectrum,ntaper,freqoi] = ft_specest_irasa(dat, time, varargin)
% FT_SPECEST_IRASA estimates the powerspectral arrythmic component of the
% time-domain using Irregular-Resampling Auto-Spectral Analysis (IRASA)
%
% Use as
% [spectrum,ntaper,freqoi] = ft_specest_irasa(dat,time...)
% where
% dat = m... |
4762a8dd828a622aa6ce2eff67c5e010c67b8184abf82f19c93de1e59ceb2afa | MATLAB | 9,617 | 281 | function get_maze_XY(varargin)
% getXY allows user to obtain xy coordinates of maze corners and objects
% (center/edge) from a video. Saves csv for each folder.Uses ffmpeg to
% generate frame from video (faster than VideoReader).
%
% ASSUMPTIONS:
% Videos must be in format compatible with Video Reader (see matlab... |
61e21f733ded32997177c0c97a431140f21a376ac4669a1a90d71a98540a200e | MATLAB | 9,620 | 231 | %% Function for CPPopt analysis
function [CPPopt] = func_CPPopt(CPP, PRx)
% Input:
% CPP: CPP time series (optionally filtered to remove noise),
% can also be calculated as the difference between synchronized MAP
% and ICP time series. Comes with a time axis t.
% PRx: PRx as calculated by ... |
f696ae36bb3e6894bdc76444b78a38cf93d7ac6cd03e60424fe51459645b5203 | MATLAB | 9,626 | 360 | function [CMAP,CLIM,WIDTH,REF,LEVELS] = ...
cmfit(CMAP,CLIM,WIDTH,REF,CENTER,varargin)
%CMFIT Sets the COLORMAP and CAXIS to specific color bands.
%
% SYNTAX:
% cmfit
% cmfit(CMAP)
% ... |
abb2553a8fc8a5f8eb29b14316e6d2f8593ff2f65dfea724412cd0f1487b9f91 | MATLAB | 9,632 | 286 |
% Procedure for processing electrophysiology data in the SNLab
%
% Dependencies
% - schafferlab/github/Kilosort
% - schafferlab/github/CellExplorer
% - schafferlab/github/neurocode
%
% Data organization assumptions
% - Data should be organized with each recordding session saved within an animal folder i.e. 'an... |
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