sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
2645b8c9160745a5b91115f241a37dd9edef3bf0ab215258949788c6b3c92de5 | MATLAB | 1,437 | 38 | function [z,p] = SpikeSuprise(count, firingRates, binSize)
%SpikeSuprise - estimate the surprise of a spike count assuming poisson spiking
% Estimate probability of observing a number of spikes ('count')
% counted over a window of a given duration ('binSize')
% given a neuron's average firing rate ('firingRates')
% ass... |
6f07e42d802b1f443b9f744e9a2dd6a06da3149257d42f2b360be619646238cb | MATLAB | 1,437 | 38 | function diffLastFirst = compute_diff_last_first(this, varargin)
% computes difference image between first and last volume of time series
% NOTE: short-cut for compute_stat_image('diff_last_first')
%
% Y = MrImage()
% diffLastFirst = Y.compute_diff_last_first('PropertyName', PropertyValue)
%
% This is a method of c... |
4f57f6add52f991a0cbb324c65e29c121e7bcc676a9a1f9d49792805ee35e194 | MATLAB | 1,438 | 60 | function y = DK_lagembed(x,M,lag)
% DK_lagembed(x,dim,lag) constructs an embedding of a time series on a vector
% DK_lagembed(x,dim) makes an m-dimensional embedding with lag 1
% DK_lagembed(x,dim,lag) uses the specified lag
%
% ------------------------------------------------------------------------------
% Copyright ... |
4fa657fb835e623e3bfde4f95861a8bf5d61ea77b365b2bfae858bf790bcf0b0 | MATLAB | 1,438 | 73 | function H=makeSignificanceBar_jiri(x,y,p,thr)
%makeSignificanceBar produces the bar and defines how many asterisks we get for a
%given p-value & significance threshold 'thr'
% for example:
% x = [0.6923, 0.8462]; % x-axis location for the sigbar
% y = 0.9500; % y-axis location for the sigbar
% p = 0.001; ... |
df5974b14b6856535af338e25d60a931888fbef6020aaf4c319eedc3db7b2786 | MATLAB | 1,438 | 41 | function c = tapas_bayes_optimal_config
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Contains the configuraton for the estimation of Bayes optimal perceptual parameters
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
1ce409e2ca22992e9de7af685a27426c9968d549237c1a05191bff757972c1fa | MATLAB | 1,439 | 60 | function [ defaults ] = nf_request_spm( modality, spm_path )
%[ spm_defaults ] = nf_request_spm( modality )
% Makes sure that SPM is in the path and defaults are sets
% modality and spm_path are optional (default, PET and ltest SPM12)
% firstoff, remove any SPM8's in the path
p=strsplit(path,pathsep);
for i=1:length... |
c5719a7b54dcb9444ff9f02474b62c08f12a51a496babdcf83e152542bf11332 | MATLAB | 1,439 | 48 | function [p,praw] = ClusterCorrectionANOVA(dat, D, nSims, p_crit, p_thresh)
%% Cluster Correct across any number of factors, may only work on 1D
if nargin < 5
p_thresh = p_crit;
end
alpha = 0.05;
gg = false;
[efs,F,cdfs,p]=repanova2D(dat,D,[],gg,alpha);
%[h,p,ci,stats] = ttest(dat);
pObs = p;
FObs ... |
5630c914dd64f175e4baccf757229b86869d71faa0e9350608e77796d290f0d8 | MATLAB | 1,440 | 48 | %% [RDF] = Wrapper_BFR_PDF(totalField,mask,matrixSize,voxelSize,algorParam, headerAndExtraData)
%
% Input
% --------------
% totalField : total field map (background + tissue fields), in Hz
% mask : signal mask
% matrixSize : size of the input image
% voxelSize : spatial resolution of each dimension ... |
8c2b54574d072f2e0b970abd13465f0b5ef973df3605c5a56986d3386019861f | MATLAB | 1,440 | 53 | clear all
close all
clc
% plot simulated grid cells
% load the simulated data:
% modules: gridscale = 2, 4
gridscale = 2;
file_name1 = ['simulated_grid_cells_env_1_module_s', num2str(gridscale),'.mat'];
file_name2 = ['simulated_grid_cells_env_2_module_s', num2str(gridscale),'.mat'];
load(file_name1)
nres = length(gri... |
9c43eb54054b9d83795f747f4cbda68cde5d51082a3d7d9c1c2cd91af8af347d | MATLAB | 1,440 | 57 | function preprocess_nsd_applybrainmask(subjix)
% function preprocess_nsd_applybrainmask(subjix)
%
% <subjix> is 1-8
%
% Apply brainmask to the T1s, T2s, SWIs, TOFs (at all resolutions).
% We save out files named like _masked.nii.gz
% setup
nsdsetup;
outputdir = sprintf('%s/ppdata/%s-structurals',nsddir,allnsdids{subj... |
8523a55f3fb66e9232d437118ed635b79532004c98da6e5548d7ff09b03a2de6 | MATLAB | 1,441 | 57 | %% [pSMWI, dSMWI] = smwi(magn,qsm,thres,m)
%
% Input
% --------------
% magn : image that combines with QSM contrast, can be 3D/4D
% qsm : QSM map (in ppm)
% thres : threshold used to create para-/dia-magnetic contrast
% m : power to enhance QSM contrast
%
% Output
% -------------... |
8c491e155271a0f3e618e93ba3d50535cc8ac3355fe6750748faa225864e89c1 | MATLAB | 1,441 | 53 | function split = split_string(in, sep, varargin)
% splits a string based on a seperator string
%
% P=SPLIT_STRING(S,D) splits a string S based on delimiter D, and
% returns a cell P with the different parts of string S. Both S and D
% should have only one row.
%
% If P contains N occurences of delimeter D, then P conta... |
aa225e23992dd2faf969a40367c27bc4a753fd638d66927d4657ce17faf00a16 | MATLAB | 1,441 | 51 | function [Mout, RHSout] = combineBC1D(MeshStructure, BC, Meq, RHSeq)
%COMBINEBC This function combines the boundary condition equations with the
%main physical model equations, and delivers the matrix of coefficient and
%RHS to be solved for the internal cells.
%
% SYNOPSIS:
%
%
% PARAMETERS:
%
%
% RETURNS:
%
%
% EXAMP... |
b81510f80b6f825bfb319c9fc7971d1e1b065af7c436e4aa7875e443607c9ca4 | MATLAB | 1,441 | 52 | function result = is_orthonormal_set(A)
%
% Orthonormal Sets
%
% is_orthonormal_set(A) determines if a set of vectors in Euclidean n-space
% is orthonormal. The matrix A is formed from these vectors as its columns.
% That is, the subspace spanned by the set of vectors is the column space
% of A. The value 1 i... |
6bbb5985a1499c57bc2e84b952341bc6565d0346343b0448864ec940071ba963 | MATLAB | 1,442 | 44 | function plot_fig4f(datadir)
% Plot z-scored time to opt-out during mixed blocks conditioned on reward
% delay on the previous trial, averaged across rats. N = 16 rats.
% Short/long delay trials are defined the bottom/top quartile of the reward
% delay distribution across sessions for each rat.
%
% INPUTS
% datadir: fi... |
e8a2122fd982aaa0aef9c06797016b7a40f2855ae7646a73b44d4b4d753f0cc8 | MATLAB | 1,442 | 36 | % using subset1 as an example
% For multicenter fitting, using multi_center_multimodelnlm_global.m instead of multimodelnlm_global.m
% For multicenter fitting, network atrriobutes should be harmonized (Adj_site_effect.m) before using multi_center_multimodelnlm_global.m
%
statdir=[Pathnew,'Forgithub\Code'];
savedi... |
fb9d05eea8361fe2075f6b9fcebf9d4517a9cd7ecf74d97795e3206b678d03dd | MATLAB | 1,442 | 40 | %% EventDecoder_AW_timing
% Relationship between Event Decoder's accuracy vs Avoidance Withdrawal
% timing
addpath('../Behavior/');
%%
BNBResult = load('D:\Data\Lobster\BNB_Result_fullshuffle.mat');
Behavior_Data_path = 'D:\Data\Lobster\BehaviorData';
output = [];
for i_session = 1 : 40
i_session = 19;
val = ... |
c1d6b140baf4ed7f2de40f80b48fbd035f732da141b96982598260f903630363 | MATLAB | 1,443 | 52 | %
% example script that runs a simple simnibs TMS simulation
%
% G. Saturnino, A. Thielscher, 2018
%
%% General information
S = sim_struct('SESSION');
S.fnamehead = 'jgjtest.msh'; % head mesh, prodeced by headreco
S.pathfem = 'tms_minimal'; %Folder for the simulation output
%% Define TMS simulation
S.p... |
ceddfc165431613acfbc1262d4f1e14c7701b270c9be0868f450fbfb3a399c7c | MATLAB | 1,443 | 49 | function handle = addFigureLabel(labelText, position, varargin)
% ADDFIGURELABEL Add a label to a figure at specified position
%
% Syntax:
% h = addFigureLabel(labelText, position)
% h = addFigureLabel(labelText, position, 'Name', Value, ...)
%
% Description:
% Adds a text label to the current axes at a normalize... |
3edcd9eb61dc87d2088345444b078d6b20521dca0156de0f545df076b4ddfa8d | MATLAB | 1,445 | 34 | function outputStruct = organizePairsData(inputStruct, outputStructName, outputStruct)
if isstruct(inputStruct)
fields = fieldnames(inputStruct); % Get all field names
for iField = 1:numel(fields)
currentField = fields{iField}; % Current field name
fieldValue = inputStruct.... |
5ac09996381741dc8a98f258fb4e6e7d8cc8b8ad570030ce0f9f62b7a50c76a5 | MATLAB | 1,445 | 31 | % GET ARTwarp ROOT PATH FOR REFERENCE WHILE RUNNING IN CONTINUOUS
% INTEGRATION
tstDir = fileparts(mfilename("fullpath"));
ARTwarpRoot = fullfile(tstDir, '..');
% Add the ARTwarp root path to the MATLAB path so we can run ARTwarp's
% functions
addpath(genpath(ARTwarpRoot))
% CONVERT .csv FILES TO .ctr
% read from the... |
db8c7525732f60709c35dfee9223e8707fa9a6e0e9f7741b88af32b276adf08c | MATLAB | 1,445 | 49 | function [wSurface, pSurface, faceData] = ft_surf2mat(lh_white, rh_white, ...
lh_pial, rh_pial, save_output)
% Read surfaces
%
% [wSurface, pSurface, faceData] = ft_surf2mat(lh_white, rh_white, ...
% lh_pial, rh_pial, save_output)
%
% Inputs:
% input_white - cell containing filenames of white surface.
% inpu... |
5b1bd01ba96f0d56b5ffdfd3a500caf2c06814207d0fccbc4e98e3490a2b9620 | MATLAB | 1,446 | 33 | function [pvec, pstruct] = tapas_hgf_binary_pu_transp(r, ptrans)
% --------------------------------------------------------------------------------------------------
% Copyright (C) 2012-2015 Christoph Mathys, TNU, UZH & ETHZ
%
% This file is part of the HGF toolbox, which is released under the terms of the GNU General... |
0304dab33301360d651ef28a51d777615560fedd5490207efd1a11e4706896fd | MATLAB | 1,447 | 41 | function outputImage = ifft(this, applicationDimension)
% IFFT (including IFFT-shift and normalization) using image2k
%
% Y = MrImage()
% Y.ifft(applicationDimension)
%
% This is a method of class MrImage.
%
% IN
%
% OUT
%
% EXAMPLE
% Y = MrImage();
% Y.ifft(4); % convert each voxel's time series to frequency s... |
15daab86d6b2a197b81ef9691eca900f809b49b0bb125df08ce72bf1f38aa639 | MATLAB | 1,447 | 68 | %% [r2s,t2s,m0] = R2star_trapezoidal_voxel(s,te,m0mode)
%
% Input
% --------------
% img : multiecho images, time in last dimension
% te : echo times
% m0mode : method to compute m0, 'default','weighted','average'
%
% Output
% --------------
% r2s : R2*
% t2s : T2*
% m0... |
6409bc9ba564fbd79433105d96245b9368c7b9fbdbb8de463fc285f5b6a60346 | MATLAB | 1,447 | 33 | function [pvec, pstruct] = tapas_ehgf_binary_pu_transp(r, ptrans)
% --------------------------------------------------------------------------------------------------
% Copyright (C) 2012-2015 Christoph Mathys, TNU, UZH & ETHZ
%
% This file is part of the HGF toolbox, which is released under the terms of the GNU Genera... |
8ba4e51f47a55f6c734cd337b6d22f692592cb44ec318de3cb44d9344e474486 | MATLAB | 1,447 | 43 | function [headmodel] = ama2headmodel(ama)
% AMA2HEADMODEL converts a dipoli structure with boundary geometries
% and a boundary element method transfer matrix to a volume conduction
% model.
%
% Use as
% headmodel = ama2headmodel(ama)
% Copyright (C) 2008, Robert Oostenveld
%
% This file is part of FieldTrip, see... |
ff39351efb1f2f3388b83d91946027137a720c2d7c122e1ae3d718fe9c333f0e | MATLAB | 1,447 | 41 | function [s,nc]=IAAFT(t,num_surr,maxiter)
%IAAFT generates # of surrogates (num_surr) from template time series (t)
%credit to algorithm by victor.venema@uni-bonn.de available at website:
%https://uni-bonn.viven.org//themes/surrogates/iaaft/iaaft_algorithm.html
%INPUTS
% t: template data (vector)
% num_surr: ... |
323b60e8445cd189c6837da555eb3b0fca6d50a7916316ce8ca60c4a4dc3317d | MATLAB | 1,448 | 51 | function outputImage = times(this, otherImage)
% Multiplies data of other image with this one and writes output in new image
%
% NOTE: If voxel dimensions of 2nd image do not match - or a scalar is
% given as 2nd argument - data in the 2nd argument is automatically
% replicated to match this image geometry.
%
%
% Y =... |
ba5b99696ef2df64fe66a228b959b1d97d98672edeea165e74707b51b4714e8f | MATLAB | 1,448 | 68 | function [err, indx, SubLabel] = WhichSubBricks (InfoStat, Type, Label)
%
% [err, indx, SubLabel] = WhichSubBricks (InfoStat, Type, Label)
%
%Purpose:
%
%
%
%Input Parameters:
%
%
%
%Output Parameters:
% err : 0 No Problem
% : 1 Problems
% indx: a vector containing sub-brick indices (+1 from AFNI indexing)... |
0da06652cec2681ad0a028804c324abbe2334f5128fbb36eda906c2052805c6b | MATLAB | 1,449 | 55 | function map=redscale(N,B)
%function map=redscale(N,B)
%
%PURPOSE
%
%Makes a colormap of shades of red from white to red.
%
%INPUT
%
%[An argument in brackets is optional. If it isn't given or it's
% an empty matrix/string, the function will use a default value.]
%
% N (scalar) number of colors
% [B] (scalar) the R... |
88b067c4727a748d959a9f73fd7e066311010762f8930f0ba1d8f54eee71b16f | MATLAB | 1,449 | 56 | function plot_fig5g(datadir)
% Plot firing rate of example cells aligned to Offer Cue on 3 consecutive
% trials where a big positive/negative RPE on the first trial is followed
% by a negligible RPE on the second trial.
%
% INPUTS
% datadir: file path of data downloaded from Zenodo. Link to download can
% be found in R... |
c72ffbb3c4c65945c9158eb2db7e3857dab7c1d2ec12578076aeb770a604fbf6 | MATLAB | 1,449 | 46 | function [IDX, C, sumd, D] = optimal_kmeans(clustdata, clusnum)
% THe aim of this function is to find the optimal number of clusters based
% on the "clusdata" and the "clusnum" range.
% INPUT:
% clustdata: the data matrix for the componenets. It is the same
% varuable used in EEGLAB pop_clus.m
% clus... |
8317ce269dfa45672375ea0745a9eea02794a380eb5aefbf6ca251caa5a3149f | MATLAB | 1,450 | 47 | function [datfield, dimord] = getdatfield(data)
% GETDATFIELD
%
% Use as
% [datfield, dimord] = getdatfield(data)
% where the output arguments are cell-arrays.
%
% See also GETDIMORD, GETDIMSIZ
datfield = fieldnames(data);
datfield = datfield(:)'; % it should be a row-vector throughout the subsequent code
% thes... |
f7c50cdb08e0d0f5ca8baec16b02a9ae37257b74084e265ffdb0088814c2bd15 | MATLAB | 1,450 | 56 | function [ output_args ] = ICA_ASSEMBLY_DETECTION( CALCIUM_FLUORESCENCE_file )
%ICA_ASSEMBLY_DETECTION( CALCIUM_FLUORESCENCE_file )
%
%
% === Jan Moelter, The University of Queensland, 2018 ===================
%
narginchk(1,1);
fprintf( 1 , [ '\n' ] );
timerVal = tic;
%% > PRINT FUNCTION-CALL
if( isdeployed )
... |
2943f65c2a24abd8ce20ff33c78d5f1d5787a8856c3e9aede00e810e2bd9c4f3 | MATLAB | 1,451 | 46 | function defaultDimLabel = get_default_dim_labels(this, iDim)
% returns default dim label for specified dimensions (nifti-compatible)
% convention: [x y z t coil echo dL7 dL8 ...]
%
% defaultDimLabel = get_default_dim_labels(this,iDim)
%
% This is a method of class MrDimInfo.
%
% IN
% iDim index of d... |
0dc9bb89be6b47a3f06df41f5763d9fc754f3cbf2a863d40d60b356df7ae64eb | MATLAB | 1,452 | 52 | function outputImage = minus(this, otherImage)
% Subtracts data of other image from this one and writes output in new image
%
% NOTE: If voxel dimensions of 2nd image do not match - or a scalar is
% given as 2nd argument - data in the 2nd argument is automatically
% replicated to match this image geometry.
%
%
% Y = ... |
1b7eb7075b47e6670442ccb9d1a80a03c6ee8a6a6c38815214283ef61b92e771 | MATLAB | 1,452 | 49 | function psdmed = eeg_rpsd(EEG, nfreqs, pct_data)
% clean input cutoff freq
nyquist = floor(EEG.srate / 2);
if ~exist('nfreqs', 'var') || isempty(nfreqs)
nfreqs = nyquist;
elseif nfreqs > nyquist
nfreqs = nyquist;
end
if ~exist('pct_data', 'var') || isempty(pct_data)
pct_data = 100;
end
% setup constants
... |
31d6881299483a833e7c6289fd3f0d975244bf9d94a296ae2929a4586603e799 | MATLAB | 1,452 | 50 | function S = randskew(n, N)
% Generates random skew symmetric matrices with normal entries.
%
% function S = randskew(n)
% function S = randskew(n, N)
%
% S is an n-by-n-by-N array where each slice S(:, :, i) for i = 1..N is a
% random skew-symmetric matrix with upper triangular entries distributed
% independently fol... |
366a23da9a64c9829f7c4cfe338a7137683d9356f644e019581a26583fc48ecf | MATLAB | 1,452 | 55 | function output = getMeanDevPath(path_shut3, path_lob1)
%% getMeanDevPath
% get mean of deviation from the center row line of the Path.
% When the path from the nest to the encounter zone is not straight,
% then this value increases.
% Main purpose of this script is to measure the change of behavior between shut 3 and... |
53dd10ce5f68035c6b3c77c9a1c6b4be69f8a39729ef9cf36c9389a332475df2 | MATLAB | 1,452 | 42 | function m1 = placematrix(m1,m2,pos)
% function m1 = placematrix(m1,m2,pos)
%
% <m1> is a 2D matrix, with potentially some extra stuff in the third dimension.
% <m2> is a 2D matrix, with potentially some extra stuff in the third dimension.
% note that size(m1,3) must equal size(m2,3).
% <pos> (optional) is [R C] wit... |
79893d264ed1ffdebe7ac00061262d99793d8749ac3da30e4723db0761d0923f | MATLAB | 1,452 | 47 | function [dyn_IAC, mean_IAC] = dyn_env(data)
% Computes the Instantaneous Amplitude Correlation (IAC) without
% leakage correction
% Tewarie et al., 2019 Tracking dynamic brain networks using high temporal
% resolution MEG measures of functional connectivity
%
% Input: - data or time... |
e697265ce2654f35f24dea65aa2d8098dfafe91ed484dd39603cae7517237a8d | MATLAB | 1,452 | 49 | function [wSurface, pSurface, faceData] = ft_surf2mat(lh_white, rh_white, ...
lh_pial, rh_pial, save_output)
% Read surfaces
%
% [wSurface, pSurface, faceData] = ft_surf2mat(lh_white, rh_white, ...
% lh_pial, rh_pial, save_output)
%
% Inputs:
% input_white - cell containing filenames of white surface.
% inpu... |
84cc44e4aaa0d689027071856310f8e36804e6cb973a71f305a8069fdf25cd7a | MATLAB | 1,453 | 67 | function obj = train_internal(obj)
% ----------
% Initialise
% ----------
obj.init_model();
obj.init_latent();
obj.init_elbo_parts();
obj.elbo_obs();
obj.elbo_latent();
obj.elbo_mean();
obj.elbo_subspace();
obj.elbo_latent_precision();
obj.elbo_residual_precision()... |
a7bbd9695110afb1314f0eed65baf39e60fd0671c160867c05d2f1372121b4c6 | MATLAB | 1,453 | 33 | function [cellTypeMatrix, cellTypeNames] = getCellTypeMatrix(cellTypesTable, channels)
%GETCELLTYPEMATRIX Convert input cell type table to binary matrix of cell
%types
% Detailed explanation goes here
% cellTypesTable : Info.CellTypes
% this is a table (read from csv) which contains the cell type of ROIs
% ... |
61314dcbb451eb2dc7aadbe7a45e0682ddf6e53290de920046e7433b89c3a682 | MATLAB | 1,456 | 45 | function s = saveobj(obj)
%SAVEOBJ Save a DagNN to a vanilla MATLAB structure
% S = OBJ.SAVEOBJ() saves the DagNN OBJ to a vanilla MATLAB
% structure S. This is particularly convenient to preserve future
% compatibility and to ship networks that are pure structures,
% instead of embedding dependencies to code.... |
6d59addc57d6594d86b5b4c038b7b65419743709090b6dfad1015aea1e6b953f | MATLAB | 1,456 | 40 | function [Mdl] = run_svmR(params)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% run_svmR returns Mdl structure including function handles of fit,
% predict and score functions for support vector regression.
%
% Arguments:
% params: Structure including following hyperparameters:
% ... |
e1b9bdbb7db30d9509ecfd1a0eeba4cfeb320c25374557c63c89c9289f5e1fa3 | MATLAB | 1,457 | 48 | %% write_bids_dataset_description(outputDir)
%
% Input
% --------------
% outputDir : output directory of a SEPIA processing pipeline
%
% Description: Writes a minimal BIDS-Derivatives 'dataset_description.json'
% at the root of a SEPIA output directory, if one does not
% already exist. Ex... |
fd0a0334290d245eb038b30216738d32382fa85b9b2af0c361c56e6777474f58 | MATLAB | 1,458 | 57 |
% Reproduce topoplot error with missing coordinates
% 1. Create a chanlocs struct with mixed valid and empty coordinates
clear chanlocs
chanlocs(1).labels = 'Ch1';
chanlocs(1).X = 1;
chanlocs(1).Y = 0;
chanlocs(1).Z = 0;
chanlocs(1).type = 'EEG';
chanlocs(2).labels = 'Ch2';
% Leave X, Y, Z empty (implicitly [])
chan... |
fea3f13cc2269f602ec2165c3e65573142617ba53b8d28f3c189a2674ff46755 | MATLAB | 1,458 | 42 | function ProcessData_ExtendedData4(datadir, savedir, codedir)
%ProcessData_ExtendedData4 - Process raw data saved under datadir such that it can be plotted by PlotExtendedData4.
% INPUTS:
% datadir - Local directory where 'Golden_Nature/RawData_ExtendedData4.mat' from Zenodo was saved
% codedir - Local directory wh... |
2460b24b03e63ab19803441cffaf2c5ad02650731bc511c74d6bd1597696cf88 | MATLAB | 1,459 | 36 | % Define a global variable warpFactorLevel for testing (needed for the
% warp.m function to run, but cleared at the end of this script)
global warpFactorLevel;
warpFactorLevel = 3;
% Define an input contour and a weights matrix (containing 2 reference
% contours) for testing. The first ref contour is [1,2,3,4,5]'=inpu... |
3833121c4cfe24527d813603a3c0a64051836fa37d0b6e37c0db5f9dbcf495a6 | MATLAB | 1,459 | 47 | function [hi, lo, mix, p] = iticurves(A)
%iticurves - Average trial intiation time by block
% INPUTS:
% A - Rat behavioral data. Usually BestFitEarly.(RAT_ID).All.ratTrial
% OUTPUTS:
% hi, lo, mix - First row is average ITI in second (raw) and z-scored (z)
% for each rat in high block (hi), low block (lo), o... |
9d66b4b531f77535340c887fe4fdc0bdfc8f6e1f6acd612631b5b59bfae5c209 | MATLAB | 1,459 | 52 | % Sophisticated Harmonic Artifact Reduction for Phase data (SHARP)
% RDF = SHARP(iFreq, Mask,matrix_size,voxel_size, radius,threshold)
%
% output
% RDF - the relative difference field, or local field
%
% input
% iFreq - the unwrapped field map
% Mask - a binary 3D matrix denoting the Region Of Interest
% ... |
cd4fc6fc63230aa64138bd75cbaa1633a96039e365cdfa77468600cee204c42d | MATLAB | 1,459 | 34 | function suite2pMode = appCheckSuite2pData(app)
%APPCHECKSUITE2PDATA Summary of this function goes here
% Detailed explanation goes here
files = dir(app.MEADataFolderEditField.Value); % get a list of all files and folders
dirFlags = [files.isdir]; % find all items that are directories
subfolders =... |
dc673845ac34ba4894242e4a33248b5fc0eb8c2b3fd30a465a9a11f3cfaba0df | MATLAB | 1,459 | 53 | %glinspace - Gamma-corrected linearly spaced vector.
%
% USAGE
%
% x = glinspace(d1,d2,gamma,n)
%
% d1 start value
% d2 stop value
% gamma gamma value
% n number of values
%
% SEE ALSO
%
% See also linspace.
%
% Copyright (C) 2013 by Michaël Zugaro
%
% ... |
f7803c3044fb91b9599ca310971bad13036d158b47501b3d34872c39053b4fa7 | MATLAB | 1,459 | 63 | function fh = plot_gradient(G, t)
% plots gradient time-course in 3 linked sub-plots, plus 2-norm of G
%
% output = plot_gradient(input)
%
% IN
% G [nSamples, 3] matrix of [G_x, G_y, G_z] vectors
% t [nSamples, 1] time vector corresponding to G
% OUT
% fh figure handle of created plot
%
% EXAMPLE
% plot_... |
30067be5d7139859dbbd85867d8e73c2248b44380f292988e35a3b52673b883e | MATLAB | 1,460 | 43 | function ops = glm_ofcOps()
%commonly used forms of all options for OFC trials
ops = glm_defaultOps(); %load all of the options
%make the changes for ofc
ops.fname = 'ofc_default';
ops.gamma = 1e-7; %L2 term
ops.beta = 0; %L1 term
%ops.kfoldSupplied = false; %an option to do grid search of hyperparameters. not impel... |
cf413e2fc078ad303d9afc244b0d0bd3eb9ebdfb2df1bb5a429b22c861e21d3d | MATLAB | 1,460 | 32 | function varargout = spm_slice_vol(varargin)
% Return a section through an image volume - a compiled routine
% FORMAT X = spm_slice_vol(V,A,dim,hold)
% V - spm_vol structure
% A - 4 x 4 transformation matrix
% dim - [i j] defining the two dimensions of the output image.
% The coordinat... |
2ae079f79ca0d9b276e9b855d328e337de5a843b7ebb656c369d17234442fdd8 | MATLAB | 1,461 | 69 | %perm_mesh
addpath("~/ER_Ca_rot/networkSpreadFVM-main/scripts/");
addpath("~/ER_Ca_rot/networkSpreadFVM-main/examples/");
dirname = "~/ER_Ca_rot/networkSpreadFVM-main/examples/inf_Perm_op";
ar = [0.0001,0.0005,0.0024,0.0111,0.0500];
ar = ar*0.3/0.0025;
s_a = string(ar);
l2 = length(ar);
dirn = strings(1,4);
filen = ce... |
51d8ea3a356be6896db6fb079c9a462ed6acb4a022f9e2963e5144c8593735c2 | MATLAB | 1,461 | 44 | function getTriggers_carGame_onTurns(params)
% extracts discrete turns from car game paradigm
% (c) Jiri, Oct16
for sess = 1:size(params.storage.sessionCacheFiles,2)
% load road
load(params.storage.sessionCacheFiles{sess}, 'road','time_raw');
assert(size(road,1) == size(time_raw,1));
% road deri... |
627a239a7f52dfa27f82bf4ccf791d4a018628051961a96c983834670580c348 | MATLAB | 1,461 | 44 | function fear_refineDelta(basename)
% basename='~/data/Fear/triple/hoegaarden181115/hoegaarden181115';
%%
load([basename '.basicMetaData.mat'])
fprintf('%s start %s with data of %s\n',datestr(now),mfilename,basicMetaData.SessionName)
load([basicMetaData.AnalysesName '-deltaProperty.mat'])
%%
if ~exist([basicMetaData.B... |
879f731e327a65055bf3a1f2a4b94a1e0b743ddcec4db61331466a12b798d37e | MATLAB | 1,461 | 60 | function [outputArg1,outputArg2] = PlotSubjectRMSError_Reliability(sn, TitleStr, lp_Color, hp_Color, bb_Color)
if ~exist('TitleStr','var')
% title parameter does not exist, so default it to something
TitleStr = ' ';
end
% --- RGB vector for grey
grey = 0.75*[1 1 1];
% --- "Realiability" of RMS-error per... |
5888fb9162163a13a8f4d07a660121e3454eae9f730f7c9483f837bcfecdbf6e | MATLAB | 1,463 | 47 | function ft_create_buffer(port)
% FT_CREATE_BUFFER starts the thread with the TCP server attached to the local
% MATLAB instance. The TCP server will listen to the specified network
% port, and accept incoming read and write requests.
%
% Use as
% ft_create_buffer(port)
% where port is the TCP port to which the serv... |
7648588a8c5b2909fa80b315e1c077563ab6171af3b83eab8311b8cebf15a5ca | MATLAB | 1,463 | 72 | function Q = qMul( Q1, Q2, Q3, Q4, Q5, Q6, Q7, Q8, Q9, Q10 )
% qMul: quaternion multiplication
% Q = qMul( Q1, Q2, Q3, ..., Q10 );
% IN:
% Q1 - first quaternion
% Q2 - second quaternion
% Q3 - third quaternion
% ....
%
% OUT:
% Q - output quaternion, Q = Q1*Q2*Q3*Q4*....
%
% REMARKS:
% 1... |
4117abe56b5d3d4addc9535a1f4ec491ee8e789cafab69085c977302c0b3bebd | MATLAB | 1,464 | 46 | function params = update_derived_parameters(params)
% UPDATE_DERIVED_PARAMETERS - Recalculate parameters that depend on others
%
% H1 Line: Update parameters derived from base parameters
%
% Syntax:
% params = update_derived_parameters(params)
%
% Description:
% Recalculates parameters that depend on other paramete... |
04382c34f39704c1535ed0e0d0e80ac3e02dee9cfb7de144282a60a4cc118dbd | MATLAB | 1,465 | 34 | function [pvec, pstruct] = tapas_hgf_whatworld_transp(r, ptrans)
% --------------------------------------------------------------------------------------------------
% Copyright (C) 2013 Christoph Mathys, TNU, UZH & ETHZ
%
% This file is part of the HGF toolbox, which is released under the terms of the GNU General Publ... |
9c2c2d266761fa74da5f8d3b09e3736dbda6197230ab17d53d21c729dcf47364 | MATLAB | 1,465 | 51 | % X : M x Tx x Nr
% Y : N x T x Nr
% dY : N x T x Nr
% dYX : N x (M*D)
% W : N x (M*D)
% Xdelay(t) = [X(t+tau*(D-1)); ... ; X(t+tau); X(t)]
% Error calculation in time embeded space
% dY = Y - Xdelay * W
[dY] = error_delay_time(X,Y,W,T,N,M,D,tau);
% Correlation of dY and X in time embeded space
%... |
d0f1c6fab690bd1006536448755c1d1b272c71e62a7855ccfbdb1386b03280b4 | MATLAB | 1,465 | 41 | function [R, verbose] = tapas_physio_load_other_multiple_regressors(...
filename_other_regressors, verbose)
% reads other multiple regressors from .txt-file or as variable R from .mat
%
% R = tapas_physio_load_other_multiple_regressors(filename_other_regressors)
%
% IN
% filename_other_regressors filename (.m... |
e10ac72f76d9187305ffc4cae6826cd3d45f2802b26d69a457a3f6e6777f7e67 | MATLAB | 1,465 | 35 | function candoit = canGetGradient(problem)
% Checks whether the gradient can be computed for a problem structure.
%
% function candoit = canGetGradient(problem)
%
% Returns true if the gradient of the cost function can be computed given
% the problem description, false otherwise.
%
% See also: canGetCost canGetDirecti... |
f20aab02d304f8b25c9fd7993c9b70652f8d3b86d523c8da35449fed608a8127 | MATLAB | 1,465 | 47 | %% [unwrappedField] = Wrapper_Unwrap_LaplacianMEDI(wrappedField,mask,matrixSize,voxelSize,algorParam, headerAndExtraData)
%
% Input
% --------------
% totalField : total field map (background + tissue fields), in Hz
% mask : signal mask
% matrixSize : size of the input image
% voxelSize : spatial res... |
e952728d244b2a1cac1c546954a005e036f52cbab0c066dc92d1f4f58185de62 | MATLAB | 1,466 | 41 | function X = sylvester_nochecks(A, B, C)
% Solve Sylvester equation without input checks.
%
% function X = sylvester_nochecks(A, B, C)
%
% Solves the Sylvester equation A*X + X*B = C, where A is an m-by-m matrix,
% B is an n-by-n matrix, and X and C are two m-by-n matrices.
%
% This is a stripped-down version of Matlab... |
8821448c9ba984c05fac039ddd299b0bcb5165e491be205ba8347dc8af6c3b3a | MATLAB | 1,467 | 41 | function rename_chNames_H(params, filterName, dataTag)
% renames selCh_names (selCh_names_pred or selCh_names_resp)
% needed after spatial filter is applied
% (c) Jiri, Nov18
%% load 'H' & selCh
varName = ['selCh_H_' dataTag]; % = 'selCh_H_pred' or 'selCh_H_resp'
load(params.storage.cacheFile, 'H', varNa... |
897b67b51618fd8ee3cb5da0f8c465409b4b7a25dec2ac9dc05f4ffbd4d4d474 | MATLAB | 1,471 | 53 | function glm_floc(subjix,ppdirname,tr,runix,stimversion,glmdirname)
% approach: assume HRF, condition split, no boots
% setup
nsdsetup;
ppdir = regexprep(nsdscreeningfun2(subjix),'rawdata','ppdata');
glmdir = regexprep(ppdir,'ppdata',glmdirname);
mkdirquiet(glmdir);
stimdur = 4;
reps_per_run = 6;
% load data
data = ... |
289efbe62aad8d33d9a7322e6f875a28fe0bd1234a1278bf7a7853e6a8fa75f7 | MATLAB | 1,472 | 60 | function [classVector,f] = FLD_classifier_lure(respMat_novel, respMat_familiar, respMat_test)
% classVector is a row vector with size equal to the number of columns of
% respMat_test. Each of its column shows which class the corresponding
% column in respMat_test belongs to: 0:Familiar, 1:Novel
% Linear classifie... |
2a1a7fbb128f34a133897e4836f088dc15fb2c8165fa0b4baf6ae1c688021d59 | MATLAB | 1,472 | 55 | % reconstruct mask for a study, given indicator
% v2 = meta_reconstruct_mask(indic, xyzlist, V.dim(1:3), [use values], [V], [imagename]);
%
% This function returns 3D mask values and optionally writes an image file
% if V and imagename are entered as additional arguments
%
% dims are mask dimensions; V is spm_vol struc... |
39ab3a7a8513a413d1903d5d485b6be0446e865a595a88b884b3d9dd7302bcad | MATLAB | 1,472 | 32 | function MM_spectrum = MM_spectrum_model(input,ppm)
%ppm is the axis that defines the ppm sampling of MM_spectrum
%Spectrum is based upon shifts in Giapitzakis et al.
%input(1) is an amplitude and input(2) a width, etc.
%input29 is a slope and input30 an offset
%last input parameter input(end) is a ppm referencing sh... |
4ba6d26a968409fb705784fa64b7bd983c35250eef20819334ddedd19146d747 | MATLAB | 1,472 | 44 | function res = hlp_findscaling(X, scaling)
% Obtain information necessary to scale the given data. Works with hlp_applyscaling.
% Scale-Info = hlp_findscaling(Data, Scale-Mode)
%
% This is just a convenience tool to implement simple data (e.g. feature) scaling operations.
%
% In:
% Data : data matrix of [Obser... |
e4652f5331b1a1dd34ed0c0a14ace6db290c7b3119b3bc59a7cb0eb7d40d17d8 | MATLAB | 1,472 | 48 | %{
aodpre.Set (imported) # Points in space and timeseries for each scan
-> aodpre.Scan
-----
sampling_rate : float # sampling rate reported by the acquisition computer
%}
classdef Set < dj.Relvar & dj.AutoPopulate
properties
popRel = aodpre.Scan
end
methods(Access=protected)
function makeTuples(self, key... |
ee470ecff4b21e79807e626f8d0b91ddd98c22c57fc30896fa083f92fa2c1ef9 | MATLAB | 1,472 | 52 | function [fx,h,Xrange,Yrange]=KDE2(Xi,Yi,h,Xrange,Yrange)
%
% Kernel Density Estimate for 2 vairable
% for diagonal type h and multivariate normal kernel
% Each "Smoothing parameter" h is estimated from the SJ method
% unless it is provided
% The X and Y range is devided 30 along the min and max
% of historica... |
fa70ba1a361fab59975abdd275c4bfbe7794dd9fc6d9b814582e05d3303b02e6 | MATLAB | 1,472 | 37 | function ImportFromMUPET_Callback(hObject, eventdata, handles)
[mupetname, mupetpath] = uigetfile('*.csv','Select MUPET Log');
MUPET = readtable([mupetpath mupetname]);
[audioname, audiopath] = uigetfile({
'*.wav;*.ogg;*.flac;*.UVD;*.au;*.aiff;*.aif;*.aifc;*.mp3;*.m4a;*.mp4' 'Audio File'
'*.wav' 'WAVE'
'*... |
3dfd4ced7d46ef47c520db7be4c02200f64f8c3435cf5fa9d9e0d24b7f0586d3 | MATLAB | 1,473 | 53 | function [b_wait, b_iti, dwt, diti, b_iti_rew] =...
regress_trials_blocksv2(A, tback)
%%Convert blocks into interpretable regressors
A.block(A.block==3) = 0.5;
A.block(A.block==2) = 3;
A.block(A.block==1) = 2;
A.block(A.block==0.5) = 1;
A.wait_time(A.optout==0) = nan;
%convert rewards to ordinal (log) scale
[A.re... |
2cb6814717415803803999b80a8d356360f750add3477d327a93afeaf2c0dacb | MATLAB | 1,474 | 44 | % Load bvecs and bvals
bvecs = load('E:\Neuroimage\demo_data\TWD_AF\derivatives\qsiprep_20241128\sub-AF0237\ses-01\dwi\sub-AF0237_ses-01_acq-b4000_space-ACPC_desc-preproc_dwi.bvec');
bvals = load('E:\Neuroimage\demo_data\TWD_AF\derivatives\qsiprep_20241128\sub-AF0237\ses-01\dwi\sub-AF0237_ses-01_acq-b4000_space-ACPC_... |
3eeb6d0b2b1aad82bd0772e387fa7da5a9ae66912d02c83560ad2bbf629a4ac1 | MATLAB | 1,475 | 65 | function [p,pobs] = fishers_exact(tab)
%
% m x n generalization of Fisher's exact test
%
% See Agresti, 1992. Exact inference for contingency tables. Statistical
% Science
%
% Eric W. Weisstein. "Fisher's Exact Test." From MathWorld--A Wolfram Web
% Resource. http://mathworld.wolfram.com/FishersExactTest.html
%
% Inp... |
4b67d6a596b379274a807976b047b2c05b1eb09a50c1627802875766154bbad9 | MATLAB | 1,475 | 44 | function outputImage = rmse(this, varargin)
% Computes root mean squared error along specified dimension, i.e. sqrt(mean(Y-mean(Y)).^2))
%
%
% Y = MrImage()
% Y.rmse(applicationDimension)
%
% This is a method of class MrImage.
%
% IN
% applicationDimension image dimension along which operation is
% ... |
e9325a9c32adaf50e9f171cdeb53ebb945eac66ad99715d4d3c1b9bc0a8508cf | MATLAB | 1,475 | 41 | function c = tapas_bayes_optimal_binary_config
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Contains the configuraton for the estimation of Bayes optimal perceptual parameters
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
f4639a088277ef4a8c3f27376ec05c3b9d3e273e56ea1295cfeeaff5c0d8387f | MATLAB | 1,475 | 43 | function plot_mean_squared_errors_RNNs
close all
clear all
clc
% Plot mean squared errors (MSE) of RNN models trained using control or APP-KI mice data.
% Select a folder containing data.
folder_name = uigetdir;
cd(folder_name)
% Load data.
load('RNN_mean_squared_error.mat')
control_MSE = MSE.control;
APP_MSE = MSE.... |
fe2356626c39e46bb1f3337aefe13dd37c285886a9eef9d908df76eb94051d6c | MATLAB | 1,475 | 46 | function c = tapas_condhalluc_obs3_config
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Contains the configuration for the response model used to analyze data from conditioned
% hallucination paradigm by Powers & Corlett, AS MODIFIED FOR COUPLED PRIOR WEIGHTING... |
0d3e3935e943df7427d153da32912f2ea0bf36f74cc697a5ab2bb2e33da0801f | MATLAB | 1,476 | 42 | % (C) Copyright 2019 bidspm developers
clear;
clc;
bidspmDir=fullfile(fileparts(mfilename('fullpath')),'..', 'lib','bidspm');
addpath(fullfile(fileparts(mfilename('fullpath')),'..', 'lib','bidspm'))
bidspm();
bids_dir = fullfile(fileparts(mfilename('fullpath')),'..', '..','inputs','raw');
output_dir = fullfile(filep... |
945545620380eacc1f80f38d81460de0180a13556d67e1b960588a29990c74e1 | MATLAB | 1,477 | 34 | function [pvec, pstruct] = tapas_hgf_whichworld_transp(r, ptrans)
% --------------------------------------------------------------------------------------------------
% Copyright (C) 2013 Christoph Mathys, TNU, UZH & ETHZ
%
% This file is part of the HGF toolbox, which is released under the terms of the GNU General Pub... |
c9ecd2f6c7eb8d401c451a72839ce4b2fec92ace31348c3224f3e41a8d41a717 | MATLAB | 1,477 | 41 | function c = tapas_bayes_optimal_whatworld_config
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Contains the configuraton for the estimation of Bayes optimal perceptual parameters
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
ac1baa724491a80e75e7c1b9b066df95eebbdc86c532075568f474bb960c9fd3 | MATLAB | 1,478 | 48 | function [K,dK] = covLINone(hyp, x, z)
% Linear covariance function with a single hyperparameter. The covariance
% function is parameterized as:
%
% k(x,z) = (x'*z + 1)/t^2;
%
% where the P matrix is t2 times the unit matrix. The second term plays the
% role of the bias. The hyperparameter is:
%
% hyp = [ log(t) ]
%
%... |
d426f1a2b6caaffa08d62c557e72ed2e6b6cb0153b5676d8836b913ded33416b | MATLAB | 1,479 | 39 | %VL_NNNORMALIZE CNN Local Response Normalization (LRN)
% Y = VL_NNORMALIZE(X, PARAM) computes the so-called Local Response
% Normalization (LRN) operator. This operator performs a
% channel-wise sliding window normalization of each column of the
% input array X. The normalized output is given by:
%
% Y(i,j,... |
d7f377f48b978bf1d1de6be2cbcff3219c6aa1522f1b61f0411f970c4b14997e | MATLAB | 1,479 | 50 | function [effectiveRank, normEigenV] = calEffRank(spikeMatrix, method)
%{
Computes Effective Rank of a matrix
Parameters
------------
spikeMatrix : matrix
matix of dimensions nSamples x nChannels,
containing 0 = no spike, 1 = spike
method : str
'covariance' : do eigendecomposition on the covariance ... |
06d828003bc7207ae9ba1bff75ef9bf4fca16d6b8a47f173228c0fd8474fd942 | MATLAB | 1,480 | 53 | function [eff,p,sig,pt_given_a,pt,success,yp] = nonparam_specificity(y,X,iter,varargin)
% [eff,p,sig,pt_given_a,pt,success,yp] = nonparam_specificity(y,X,iter,[w])
%
% weights should be mean = 1
if length(varargin) > 0, w=varargin{1};, else, w=ones(size(y));, end
[n,k] = size(X); % number of obs. and tasks
% weig... |
5043920733a7e78b63abfcda45639a9e68343e0eccd37b923096743a18ce7f60 | MATLAB | 1,480 | 47 | function defaultDimUnit = get_default_dim_units(this, iDim)
% returns default dim label for specified dimensions (nifti-compatible)
% convention: [x y z t coil echo dL7 dL8 ...]
%
% defaultDimUnit = get_default_dim_units(this,iDim)
%
% This is a method of class MrDimInfo.
%
% IN
% iDim index of dimen... |
884c8e7c1c2cc3fd45c07bf134613d82ad4fbe5b6091db913c0b55dc0db1322c | MATLAB | 1,480 | 57 | function [bw_out] = score_hylid_perpixel(hylid_struct,detector_img,targ_filt,title_str,varargin)
%
%function [bw_out] = score_hylid_perpixel(hylid_struct,detector_img,targ_filt,title_str,varargin)
%
% scores the detection performance of the given detector output image using Bullwinkle
% optionally plots an annotated ... |
ab9f5c2e3f7e3b6df893d410d83a9715b3234883fbf3a3d53881c0948863b906 | MATLAB | 1,480 | 46 | %%%%%%%%%%%%%%%%%%%%%%%%
% %
% Write SPM mat file %
% %
%%%%%%%%%%%%%%%%%%%%%%%%
function M = GE_createSPMmat(im_hdr, scandir)
%
% Put the appropriate translations and rotations to the M matrix
% given the information in the image header and the direction of
% acquisition
%
%... |
e4eaf5f68d147dbbeb22100cce9a8de646b16c9bb9546f1b2920b35b64770160 | MATLAB | 1,480 | 44 | function c = tapas_softmax_mu3_config
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Contains the configuration for the softmax observation model for multinomial responses with phasic
% volatility exp(mu3) as the decision temperature
%
%%%%%%%%%%%%%%%%%%%%%%%%%%... |
0e9cf55de37f3a77d45e512e86cc79e26501c9e24ccdfe6204afd51d244a2338 | MATLAB | 1,481 | 50 | function params = validateInputsAndSetDefaults(params)
% Validates required inputs for data processing, checking for correct data
% types. Creates a params structure with default values for optional
% parameters.
% Check required fields exist
requiredFields = {'dataRawLoc', 'dataOutLoc', 'statsOutLoc', 'co... |
33f197b205f772e46cc1b85574e258e071605bf4e1d74c7fd8471d2a2dd16fe5 | MATLAB | 1,481 | 40 | function [aPort] = align_to_ROIs(xvals, yvals, Ports, pixelpercmarray)
%%align_to_ROIs aligns tracks relative to two user-provided references
% Commonly used in single-camera chemosensory assays to scale and align
% tracks relative to gas ports or odorant point sources.
% Converts pixels to cm
global tracks
% Genera... |
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