sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
ec644b3a0df61eae8f5d41e3d49159d0f7523c375877417f008c674354954d79 | MATLAB | 2,376 | 51 | %VL_NNBILIEARSAMPLER CNN spatial bilinear resampling
% Y = VL_NNBILINEARSAMPLER(X,GRID) resamples image X at the spatial
% locations specified by GRID using bilinear interpolation.
%
% X is a array of dimension H x W x C x N, where (H,W) are the
% height and width of the image, C is the number of feature
% c... |
92acb3012259b994a8bab6cd0f4bcd2d54a26c5e10a86f3ecf70720d3d3a70e6 | MATLAB | 2,377 | 71 | function [ events, infos ] = nmri_read_event_edf( edf_file, subject )
% [ events, infos ] = nmri_read_event_edf( subject )
% Reads in EDF annotations from
if ~exist('subject','var') || ~isfield(subject,'hdr') || ~isfield(subject.hdr,'orig') || ~isfield(subject.hdr.orig,'annotation')
error ('Subject not set or HD... |
16f96f6ca89097ed4ca5ff3e876516a2dfc5ca4614bfd316e193d51270adb8d9 | MATLAB | 2,378 | 66 | % coreg_nifti.m
% Chris Davies-Jenkins, Johns Hopkins University 2022.
%
% USAGE:
% [vol_mask, T1_max, voxel_ctr] = coreg_nifti(in, vol_image, maskFile)
%
% DESCRIPTION:
% Creates a SPM volume containing a voxel mask with the same dimensions
% as the SPM volume containing a structural image. The voxel mask is
% crea... |
7296bc30882169ff757db2fc2df416803bb81031814a0abddd4c74006b096674 | MATLAB | 2,378 | 82 | function [ tickLabels ] = parse_labels( dcm, labels, idx )
% Generate labels for axis ticks.
%
% This is a protected method of the tapas_Huge class. It cannot be called
% from outside the class.
%
% Author: Yu Yao (yao@biomed.ee.ethz.ch)
% Copyright (C) 2020 Translational Neuromodeling Unit
% Inst... |
75a92069b942a1d393f13b4b0c89e6f382b5c8baee3158d71f986b3896dfe1bd | MATLAB | 2,378 | 46 | % % % step 0 : to change the dimension of the mask
% % %first initiate CPP_SPM in batchSearchlight.m
% %
% % % suject to run in each group
% % opt.subjects = {'001','002','003','004','005','006','007','008',...
% % '009','010','011','014','015','016','017',...
% % 'pil001','pil002','pil004','... |
91d24a6f0e029fd5ef33d622e65b4236c2fc0e8af2bbb3053de42c6dd9c5127e | MATLAB | 2,378 | 77 | function plotTextLabels(coords_xy,textLabels,fontSize,categoryColumns,categoryColors,categoryLabels)
% plots the set text labels in cell array 'textLabels' at the positions
% 'coords_xy' in the current plot in font size 'fontSize' in black (by
% default) or using category colors specified by optional further arguments... |
5c7660a048dc3bbd59bbec582e2bfdf182d771e5c6dab2513828819c6468d4b0 | MATLAB | 2,379 | 60 | % bids_checkfields() - Check BIDS fields
%
% Usage:
% >> struct = bids_checkfields(struct, fielddefs, fieldname);
%
% Inputs:
% struct - [struct] structure with defined fields
% fielddefs - [fielddefs] field definition
% fieldname - [string] structure name
%
% Outputs:
% struct - checked structure
%
% Au... |
953aea4a0b7796a8bdb6c35463813e9fc7d40959d74633a6c4b206b35d7dc850 | MATLAB | 2,379 | 94 | function [fig] = tapas_sem_plot_constraints(constraints, model)
%% Plot the constraints matrix
%
% Input
% constraints -- Constraints matrix
% model -- String with model (seria or prosa).
%
% Output
% fig -- Handle of the figure created.
%
% aponteeduardo@gmail.com
% copyri... |
aeb334ae38ffa707d24a969202a0823e995a9179dc4a1bbe90d319366a3b6cbf | MATLAB | 2,379 | 35 | function preprocess_nsd_functionaltostructuralalignment(subjix)
% function preprocess_nsd_functionaltostructuralalignment(subjix)
%
% <subjix> is 1-8
%
% Use ANTS to determine an EPIaffine and then an EPIsyn
% to match the EPI (mean of first 5 sessions 1.0-mm resolution)
% to the T2 (1.0-mm version). We use some care... |
c80f23e81d326ca2d2a9085be39a76424479c18ecd0253e18c6bd64a7f8df357 | MATLAB | 2,379 | 76 | function [stats] = boxSwarmPlot(y, x, isDep, colour, noOutliers)
% create boxplot with significance labels and individual data points
% plotted on top (swarmchart);
% INPUT
% y = vector with data to plot;
% x = vector with x-positions for data in y;
% default settings
if nargin<3
isDep = 0;
end
if nar... |
11881413b811fee7279bccf005ea7a9f3477561fa1e492f42ad81a0ace54126b | MATLAB | 2,380 | 67 | function T = spm_type(x, arg)
% Translate data type specifiers between SPM & MATLAB representations
% FORMAT T = spm_type(x, arg)
% x - specifier
% T - type
% arg - optional string argument, can be:
% - 'maxval' - return maximum allowed value.
% - 'minval' - return minimum allowed value.
% ... |
232afdb4b21c8e10fc9bc124915f00478a90b776d620239f4f2ed0f416e57e2c | MATLAB | 2,380 | 71 | function [w] = tapas_physio_conv(u, v, filter_type, padding)
% Wrapper around `conv()` for convolution
% Deals with the padding and time offsets
%
% [w] = tapas_physio_filter_cardiac(u, v, filter_type)
%
% IN
% u Data time series [1-D]
% v Convolutional filter time series [1-D]
% filter_t... |
84194a02c6e07088fd46a730cbfbd7161b0846af5c78e97b8f260975c33657bf | MATLAB | 2,380 | 55 | function updatedWeight = ARTwarp_Average_Weights(weight, inputLengths, inputCategories)
% ARTwarp_Average_Weights warps every category's reference contour (weight)
% uniformly to be the mean length of the contours in that category.
% UPDATEDWEIGHT = ARTwarp_Average_Weights(WEIGHT, INPUTCONTOURS, INPUTCATEGORIES)
%... |
d26e8aae6f45f516027d119fbeca98441e5bfea3f812b7433d7b70ee7b5f8d50 | MATLAB | 2,380 | 106 | function [posterior, summary] = tapas_sem_example_mixed_estimate(model, param)
%% Example for inversion with a mixed effects model as prior.
%
% Input
% model -- String. Either seria or prosa
% param -- String. Parametric distribution.
% Output
% posterior -- Structure. Contains the post... |
71ad0692fd44a2ebbd726b8d2338802af93c326d1ed11ebbb36f4cc3c8ee7fa2 | MATLAB | 2,381 | 79 | function [stats,message] = anova1_repmeas_onMatrix(data)
%
% function stats = anova1_repmeas(data)
%
% One-factor, within-subject repeated measures ANOVA.
% For designs with one within-subject factor.
%
% Parameters:
% data dependent variable (numeric), where:
% ROWS are OBSERVATIONS
% ... |
db60defd7986c49c8e235ea4c46ca93eb8338b0757f3b9bb361665c3727634cb | MATLAB | 2,382 | 65 | function subjList = subjList_updateAnalyzed(params)
% updates subject list based on those that were analyzed (e.g. if some paradigm parts could not be run)
% (c) Jiri, Jul22
if exist([params.storage.dir_results filesep params.storage.outName],'dir') ~= 7
error(['output directory for results not found, dir = ' par... |
113f9f3a494a9abf5733704231955631cee7843b59ba5fa938fe68c8d50615d2 | MATLAB | 2,384 | 68 | function ni_def = afni_ni_defs()
persistent cached_ni_def
% for efficency reasons generate the definitions only once;
% upon each subsequent call the cached data is used
if ~isstruct(cached_ni_def)
cached_ni_def=generate_ni_def();
end
ni_def=cached_ni_def;
function ni_def=generate_ni_... |
c18570f4607200e569c2d2220929256594d2ca1d2a61b1ad733bf9832460e983 | MATLAB | 2,384 | 73 | function options=getUserOptions(newOptions,defOptions,allowed);
% function Opt=getUserOptions(options,Opt);
%
% Deals with user-option structure. It allows the user to specify user
% options as a structure, or as a set of fieldnames and values
%
% INPUTS
% options: either a structure of user options or a cell array
... |
e04e399cc05275298187abd4407be1e9276e05e18212b8370716e20f158d7c20 | MATLAB | 2,384 | 65 | % CONVOLVE - convolve two matrices (normalize by the sum of convolved
% elements to compensate for border effects).
%
% Usage:
% >> r = convolve( a, b );
%
% Inputs:
% a - first input vector
% b - second input vector
%
% Outputs:
% r - result of the convolution
%
% Autho... |
ef8948d22fa5c94b13be45877ec437b4cdef78655428f7e157f7efb22a6dae51 | MATLAB | 2,384 | 68 | function X = thomson_problem(n, d)
% Simple attempt at computing n well distributed points on a sphere in R^d.
%
% This is an example of how Manopt can approximate the gradient and even
% the Hessian of a cost function based on finite differences, even if only
% the cost function is specified without its derivatives.
... |
ba99a6cb4f8755f64fda4a8c1f21c276cb5da1ff83df5d79e0eb46f15c8cb945 | MATLAB | 2,385 | 95 | function fir = SavitzkyGolay(n,varargin)
% Version 1.4 - 31/03/00 - rotter@biologie.uni-freiburg.de
%
% fir = SavitzkyGolay([nl,nr]) gives a Savitzky-Golay smoothing filter
% of total width nr-nl+1. It extends -nl data points to the left and nr
% data points to the right of the point of operation. Works by least
% squ... |
a1a948686f25c8d2b3a63e7668212ebc6f29557274e3bec4c7f1c93819c0125e | MATLAB | 2,386 | 92 | % LDA - MATLAB subroutine to perform linear discriminant analysis
% by Will Dwinnell and Deniz Sevis
%
% Use:
% W = LDA(Input,Target,Priors)
%
% W = discovered linear coefficients (first column is the constants)
% Input = predictor data (variables in columns, observations in rows)
% Target = target var... |
46ec2820d4841f2a4c3706bf0e1ba91aa1960a51f95800a24653dedee40b3776 | MATLAB | 2,389 | 62 | % EEG_GETICA - get ICA component activation. Recompute if necessary.
%
% >> mergelocs = eeg_getica(EEG, comp);
%
% Inputs:
% EEG - EEGLAB dataset structure
% comp - component index
%
% Output:
% icaact - ICA component activity
%
% Author: Arnaud Delorme, 2006
% Copyright (C) Arnaud Delorme, CERCO, ... |
348584f4a0d90be26477e700e51bbe9013d91b3644342db7a2af0a6cac5908c1 | MATLAB | 2,390 | 58 | function G = minimize_lbfgsb_gradfun(X,varargin)
% extract input arguments
varargin = varargin{1}; strctX = varargin{2}; f = varargin{1};
% global variables serve as communication interface between calls
global minimize_lbfgsb_iteration_number
global minimize_lbfgsb_objective
global minimize_lbfgsb_gradie... |
b326c406c8e326e89e127e9eac40de41a36ca1de73071024211db0399a14b863 | MATLAB | 2,390 | 68 | function clr_RGB = msSwitch_get_clr4aa(aa_name)
% returns color for anatomic area name
% (c) Jiri, Jun23
aa_found = false; % init
clr_RGB = [0 1 0]; % init, green
%% was aa_name from: Yeo7 networks ?
% area_color_yeo7 = { ...
% 'Default', [255 198 82]./255; ...
% 'Dorsal Attention', [181 66 107... |
f14ac27e74b570cba008fb17bbc6725a9b5966d71e7c8797aa835b9c835d21d1 | MATLAB | 2,391 | 102 | function [mu, S, nu] = fitt_fast(x)
% FITT(x)
%
% Fit a t-distribution using the ECME algorithm (Lui & Rubin, 1995)
%
% C Liu and D B Rubin, (1995) "ML estimation of the t distribution using EM and
% its extensions, ECM and ECME", Statistica Sinica, 5, pp19-39
% http://www3.stat.sinica.edu.tw/statistica/oldpdf/A5n12.pd... |
b809aebad296b504d2e6b5cc247682f7881a7cf65069d2ee57247b344a6b19fd | MATLAB | 2,392 | 64 | % lookupchantemplate - look up channel template.
%
% Usage:
% [ found transform ] = lookupchantemplate( filename, template_struct);
%
% Inputs:
% filename - channel location file name
% template_struct - template structure as defined in dipfitdefs
%
% Outputs:
% found - [0|1] 1 if a transformation was... |
e66f34698d1628bbef7666575b839e17d49369e86e7a9816ebb7e3f941d8a367 | MATLAB | 2,392 | 66 | %% This file is used to identify cell masks for compartmental area
clear all
close all
parent_folder = 'Y:\20241208 D54D2 in b2KD and WT_APP\Analysis';
dirs = dir(parent_folder);
for m = 1%:length(dirs)
if dirs(m).isdir && ~strcmp(dirs(m).name, '.') && ~strcmp(dirs(m).name, '..')
folder_path = fullfile(p... |
fbbc813fd2a38cc9aef3ec75085de1811aef9ba014eb7f336045d68bde3a9171 | MATLAB | 2,392 | 64 | function [matlabbatch, indValidContrasts] = tapas_physio_check_prepare_job_contrasts(fileSPM, ...
model, SPM, indReportPhysContrasts, namesPhysContrasts)
% adapts contrast generator for physiogical regressors to actual SPM-file
% (directory & design matrix columns)
%
%
% IN
% fileSpm
% model
% SPM
% indR... |
0351f2cccf5ccc5480db7004d6974295ee278b9b060c053aece9039aedb3be35 | MATLAB | 2,393 | 65 | function sqrtPd = getSqrtPrecon(problem, x, d, storedb, key)
% Applies the square root of the Hessian preconditioner at x along d.
%
% function sqrtPd = getSqrtPrecon(problem, x, d)
% function sqrtPd = getSqrtPrecon(problem, x, d, storedb)
% function sqrtPd = getSqrtPrecon(problem, x, d, storedb, key)
%
% Returns as sq... |
14e34281ed5445542ea3611492324732045d267e63679a729463dad33dd5f201 | MATLAB | 2,393 | 69 | function [ output ] = tapas_rdcm_compute_statistics(DCM, output, options)
% [ output ] = tapas_rdcm_compute_statistics(DCM, output, options)
%
% Computes statistics for the posterior parameter estimates
%
% Input:
% DCM - model structure
% output - model inversion results
% options -... |
dc03180f831f0ed02bf3d631f592980709304f42a0ccdc332f36022a38957b76 | MATLAB | 2,393 | 81 | function [meg] = read_ctf_dat(filename)
% READ_CTF_DAT reads MEG data from an ascii format CTF file
%
% meg = read_ctf_dat(filename)
%
% returns a structure with the following fields:
% meg.data Nchans x Ntime
% meg.time 1xNtime in miliseconds
% meg.trigger 1xNtime with trigger values
% meg.... |
0ca914fbdd0a9015ece1dfb6e7b05b7ea9989b5f2ae510cfce027d2c25301363 | MATLAB | 2,394 | 72 | function [] = Intensity(filename,filetime,diameter,sigma_threshold)
stack_info = imfinfo(filename);
[~,savename,~]=fileparts(filename);
mkdir(savename);
image_width = stack_info(1).Width;
image_height = stack_info(1).Height;
image_count = length(stack_info);
image_stack = zeros(image_height,image_width,image... |
7a6f3442808fc34c354685a5828a7b86537e1e1c454f5cfeaa490c7c4f3df7de | MATLAB | 2,394 | 100 | function play(movie,varargin)
% EXAMPLE USE WITH ARGUMENTS
%[options]= play(movie) - use 1
%[options]= play(movie,movie2) - use 1
%
% HELP
% Simple player for movies, inspired by 'playMovie' by Biafra.
% Just provide 3D matrix of the movie and terminate by pressing a character 'e'
% speed up or slow down with keyboard ... |
eaa14585ccba453f41c8434aa95d7a9ff1d6e97778cede5357b80aac5751c969 | MATLAB | 2,394 | 88 | function [ DCM ] = tapas_ceode_synData_erp()
% [ DCM ] = tapas_ceode_synData_erp()
%
% Sets parameters and function handles to create a synthetic DCM
% structure. The resulting structure can then be used to generate
% artificial data with tapas_ceode_gen_erp.m
%
% INPUT
%
% OUTPUT
% DCM struct DCM st... |
e9bba4416b9a9b5ea355f3b068f22a79ce0bf39abce220467102aec744ad73b7 | MATLAB | 2,395 | 63 | % Please cite this paper if you use any component of this software:
% D. Cunefare, L. Fang, R.F. Cooper, A. Dubra, J. Carroll, S. Farsiu, "Open source software for automatic detection of cone photoreceptors in adaptive optics ophthalmoscopy using convolutional neural networks," Scientific Reports, 7, 6620, 2017.
% Re... |
31a7a7ff66c39f2504531c9ec47d035208a571e08d8268e0ce111cb89b023bc7 | MATLAB | 2,397 | 74 | % createQuadratureLogGaussianFiltersSpace.m
function [bpP1,bpfP1,bpP2,bpfP2,xCenterPix,yCenterPix] = createQuadratureLogGaussianFiltersSpace(fovPix,fovDeg,g1_sigma,g2_sigma,xCenter,yCenter,g2_amp)
if mod(fovPix,2) == 0
fovPix = fovPix + 1;
end
if ~exist('g2_amp','var')
g2_amp = 1;
end
if g1_sigma > g2_sigma... |
1deec9f5d9b2b3078cb57a630f2cd4e9c50b40be3d1980c79ef6e69cac8998ac | MATLAB | 2,399 | 78 | function dendplot(topology,labels,fontsize)
% DENDPLOT: Plots a dendrogram given a topology matrix.
%
% Usage: dendplot(topology,{labels},{fontsize})
%
% topology = [(n-1) x 4] matrix summarizing dendrogram topology:
% col 1 = 1st OTU/cluster being grouped at current step
% ... |
2c0e621ff7bb2cc20c58b07ef7bd98fb3fa1b6a20a35f93d69c348888f543eba | MATLAB | 2,399 | 83 | function [sidxs,r2]=surfing_selectkfirstidxs(k,idxs,inclmsk)
% selects approximately the first k non-zero unique indices
%
% SIDXS=SURFING_SELECTKFIRSTIDXS(K,IDXS,[ROWHINT])
%
% INPUT:
% K: number of indices to select
% IDXS: NxP matrix with indices, corresponding to N nodes with at most P
% indice... |
2dcbc42e802d464fcc0c88205d8fad0482534eda7d4ab4a5f2c1fce6f7e079ab | MATLAB | 2,399 | 87 | function [chunksFirstLast,summary]=chunkFrames(chunkSize,frameFirstLast)
% Prepare ranges of frames to load from a files - chunks to load without overfilling the memory.
% SYNTAX
% [chunksFirstLast,summary]= chunkFrames(chunkSize,frameFirstLast)
%
% INPUTS:
% - chunkSize - an interger e.g. 500 if that's reasonable to l... |
a6f6f29daf7c7cceaf11723b99520a7839be0750d31028b57f74c7871c341be5 | MATLAB | 2,399 | 89 | function out = tor_conv_sphere(mask,vox_radius,mmethod,varargin)
%function out = tor_conv_sphere(mask,vox_radius,mmethod,[norm factor])
% norm factor is optional. scaling factor to divide all values by
% in spherical convolution.
% used because the convolution does not return a max height of 1 given
% one input poin... |
f7296ed96c90fb100cf4a3fc17d24e0fa79a80d8c7ecede687bbdb507be35e71 | MATLAB | 2,399 | 67 | function numFolds = HowManyFolds(groupLabels,numClasses)
% Set the number of folds for k-fold cross validation using a heuristic
% (for small datasets with fewer than 10 examples per class):
%
%---INPUTS:
% groupLabels, labels of groups in the dataset
% numClasses, the number of classes of time series
% --------------... |
9823ee2d19adfc3545b682ad80eee5f9f9bfc1c985f8206227b72e2520940c8d | MATLAB | 2,400 | 74 | function plotTargetClassifierTimingAll(output)
% Plots distributions of crossing times for classifier projections
% time runs vertically
% Figure
fig;
hold on
axis off
ax = gca;
% Params
bxw = 0.25;
alpha = 0.35;
dotSize = 15;
spacing = [1,1.75];
buff = 2.5;
axlocs = [spacing; spacing + buff; spacing + buff*2; spacin... |
d4dd813606e399f59b95d6c071047784ccad8ce82a8f2b87ee476826321b660e | MATLAB | 2,400 | 74 | %% h = sepia_handle_panel_qsm_CFS(hParent,h,position)
%
% Input
% --------------
% hParent : parent handle of this panel
% h : global structure contains all handles
% position : position of this panel
%
% Output
% --------------
% h : global structure contains all new and other handle... |
033f84e69764a343a6903c3153988c09ac5a6ac3f4f856a552e6fe038f798c51 | MATLAB | 2,401 | 125 | function H=demoOctave_shadedErrorBar
% demo function for shadedErrorBar
%
% function demo_shadedErrorBar
%
% No input or output arguments.
%
%
%
rows=2;
cols=2;
clf
subplot(rows,cols,1)
%Plot the mean and standard deviation then overlay the raw data
y=randn(30,80)*5;
x=(1:size(y,2))-40;
yP = sin( linspace(-2*p... |
64fd707637210edf58c942c85711a60f952221c80da015e3f2466f925266e557 | MATLAB | 2,401 | 106 | function [Ydev] = predict_variance(X, Model, parm)
% Variance of posterior predictive distribution
% [Ydev] = predict_variance(X, Model, parm)
%
%
%
%
% 2009-11-5 M. Sato
if ~exist('parm','var'), parm = []; end;
if ~isfield(parm,'Tau')
tau = 1 ;
D = 1 ;
else
tau = parm.Tau;
D = par... |
8f5405a749a59039b2672068eb8d93875825ed8ab3610b4edc3734619d54667a | MATLAB | 2,401 | 90 | function [x,w] = fnnls(XtX,Xty,tol)
%FNNLS Non-negative least-squares.
%
% Adapted from NNLS of Mathworks, Inc.
%
% x = fnnls(XtX,Xty) returns the vector X that solves x = pinv(XtX)*Xty
% in a least squares sense, subject to x >= 0.
% Differently stated it solves the problem min ||y - Xx|| if
% XtX = X'*X and ... |
c880a35411bb93b335ffb20daf4efff783470518d0fcb81cfeded97dfbf2a182 | MATLAB | 2,401 | 71 | function mra = modwtmra_custom(wpt, wavelet_type)
%(Inverse Stationary Wavelet Transform)
%
% Usage:
% mra = modwtmra_custom(wpt, wavelet_type)
%
% Inputs:
% wpt - (Bands x Samples x Channels) matrix
% Order: [W1, ..., WJ, VJ]
% wavelet_type - 'haar'
%
% Output:
% mra - (B... |
ea1c1e64a57ad5e7da2e4d9f40712850cb74e351c7645a894bdbec51e0d37c6b | MATLAB | 2,401 | 70 | function [Mout, RHSout] = combineBC2D(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... |
039d9b2f656903302f18629aec28886d5bddc07c173bdb53464a58477eedfea3 | MATLAB | 2,402 | 52 | %VL_NNBILIEARSAMPLER CNN spatial bilinear resampling
% Y = VL_NNBILINEARSAMPLER(X,GRID) resamples image X at the spatial
% locations specified by GRID using bilinear interpolation.
%
% X is a array of dimension H x W x C x N, where (H,W) are the
% height and width of the image, C is the number of feature
% c... |
0d813d9027e8a5568abce90d827213dc6df199301533c2e052e937aaca2e3680 | MATLAB | 2,402 | 64 | function [wtNorm_mean, wtRaw_mean] = prev10Rews(A, ntrials, inferredMixArg)
% Compute wait times conditioned on the sum over the previous (ntrials)
% trials
%INPUTS:
% A = .mat file of individual rat behavior data
% ntrials = number of trials to sum over
% inferredMixArg = whether to also filter by trials infer... |
eed5919918a36e84e51681790ca905312c02d70807e0848daac26b044c01b941 | MATLAB | 2,402 | 59 | function c = tapas_unitsq_sgm_mu3_config
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Contains the configuration for the unit square sigmoid observation model for binary responses
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
e24097b80a7ba04818623d6ff3179fd0c18a2c72dcad9600857a5443f2588205 | MATLAB | 2,403 | 83 | function MS = createMeshCylindrical1D(varargin)
% MeshStructure = createMeshCylindrical1D(Nr, Lr)
% MeshStructure = createMeshCylindrical1D(facelocationR)
% builds a uniform 1D mesh (1D axial symmetry):
% Nx is the number of cells in r (radial) direction
% Width is the domain radius in r direction
%
% SYNOPSIS:
% Mes... |
d0396670330a7352a19c02c870e565a38d61db192ac098347eb61498dd4e383a | MATLAB | 2,404 | 140 |
% What can Panel do?
%
% This demo just shows off what Panel can do. It is not
% intended as part of the tutorial - this begins in
% demopanel2.
%
% (a) It's easy to create a complex layout
% (b) You can populate it as you would a subplot layout
% (c) You can export it to a "camera-ready" image file
%
% Now, move on t... |
7d911424bf11c51be9e8e079a46e225f2bde327ef4b5c6828bc73f5ef798e350 | MATLAB | 2,406 | 69 | function [ delta, v_mi, x_mi ] = EmergenceDelta(X, V, tau, method)
%% EMERGENCEDELTA Compute downward causation criterion from data
%
% DELTA = EMERGENCEDELTA(X, V) computes the downward causation criterion
% delta for the system with micro time series X and macro time series Y.
% Micro data must be of size... |
808d047d44fa83b91fc5dd5c345e43a3db5e951952c51f2d2defdbe9ccfc0e9e | MATLAB | 2,406 | 63 | % EEG_EPOCH2CONTINUOUS - convert epoched dataset to continuous dataset
% with data epochs separated by boundary events.
% Usage:
% >> EEGOUT = eeg_epoch2continuous(EEGIN);
%
% Inputs:
% EEGIN - a loaded epoched EEG dataset structure.
%
% Inputs:
% EEGOUT - a continuous EEG datase... |
b0975ecacb424e834399694c588d9095bc57d57281e83717f1407407256fdf6f | MATLAB | 2,406 | 62 | function [norm_ratio, pdf_density, edges] = get_norm_ind_distr(sim_file, upper_lim, bin_width)
% GET_NORM_IND_DISTR
% Syntax:
% [norm_ratio, pdf_density, edges] = get_norm_ind_distr(sim_file, upper_lim, bin_width)
% Description:
% Load three simulations (suffixes _1, _2, _3) and compute the ratio
% (rate_1 + rate... |
0f67cc5073f6b1edf44bf0ad281a2bd477ac4ebe4d14ecd3ca2e1a459829e1cb | MATLAB | 2,407 | 64 | %io_writelcmraw.m
%Jamie Near, McGill University 2014.
%
% USAGE:
% RF=io_writelcmraw(data_struct,outfile,metab);
%
% DESCRIPTION:
% Take a simulated metabolite basis spectrum in matlab structure format, and
% output it into LCModel RAW format to be used in an LCModel basis spectrum.
%
% INPUTS:
% data_struct = si... |
7f04f5ae10a9e82bea3ebb4f334149f6e4fe8ab9055ce5f9ab628c0da6cb27e5 | MATLAB | 2,407 | 60 | function selectionIndexArrayCell = tapas_uniqc_convert_selection_range_to_array(selectionIndexRangeCell)
% Converts selection name/range pairs to cells of single selections
%
% selectionIndexArrayCell = tapas_uniqc_convert_selection_range_to_array(selectionIndexRangeCell)
%
% IN
% selectionIndexRangeCell cell(1... |
e766804f0c14df060a22a2b2c7a0240abdfb737e1ef56e909d79c384a1742e19 | MATLAB | 2,407 | 101 | function dat = bar_interactive_btnupfcn;
% [dat] = bar_interactive_btnupfcn;
%
% function for loading and plotting hewma data from a voxel. must have declared globals f,f2,VOL,EXPT
% see hewma_timeseries_plot, the shell function.
global han % handle of gui
global P % names of images
global xnames % x-a... |
f1ecc280c010e65ba3baac79f83f1072b26f348454bbffdf5721c46e32881c1b | MATLAB | 2,407 | 93 | function atlasName = anatomicalAreas_atlas4AA(aaName)
% returns name of the atlas given an anatomical area (or n.a. if not found)
% (c) Jiri, Aug22
atlasName = 'n.a.'; % init (not found)
%% was aaName part of the Yeo7 atlas?
AA_list = {
'Visual';
'Somatomotor';
'Dorsal Attention';
'Ventral Attenti... |
5a9254b8d987433cffe2151b38df6767b51da43cee1c4c24088c898b89e7d665 | MATLAB | 2,408 | 80 | %% DistanceTuningCurve
% Draw firing map of units
%% Dataset Paths
datasetBasePath = 'D:\Data\Lobster\FineDistanceDataset\';
resultBasePath = 'D:\Data\Lobster\FineDistanceResult_syncFixed_May';
filelist = dir(datasetBasePath);
sessionPaths = regexp({filelist.name},'^#\S*','match');
sessionPaths = sessionPaths(~cellfu... |
75a583bc18982f8ed383810131b14f8ece569dff44df6044b3d7e4a44cb879a5 | MATLAB | 2,409 | 70 | function fnPhysLogArray = tapas_physio_find_matching_scanphyslog_philips(...
fnImageArray, pathLogFiles)
%returns file name(s) of matching SCANPHYSLOG-file for a given .nii-file
%whose exported name is the original Philips name
%
% fnPhyslogArray = tapas_physio_find_matching_scanphyslog_philips(...
% fnImag... |
77abf621c3c8475e1e93da3c1e6825a2a6ce7c543584b26bd4353a7adf6ec850 | MATLAB | 2,409 | 109 | function [posterior, summary] = ...
tapas_sem_example_multiv_estimate(model, param)
%% Example for inversion with a single prior for the whole population.
%
% Input
% model -- String. Either seria or prosa
% param -- String. Parametric distribution.
% Output
% posterior -- Structure... |
2ace2c6bee0298891e8ae60b44acb060ba8f63dc40715afed967f1dbfc078614 | MATLAB | 2,412 | 66 | % SIZE - size of memory mapped underlying array
%
% Author: Arnaud Delorme, SCCN, INC, UCSD, Nov. 2008
% Copyright (C) 2008 Arnaud Delorme, SCCN, INC, UCSD
%
% This file is part of EEGLAB, see http://www.eeglab.org
% for the documentation and details.
%
% Redistribution and use in source and binary forms, with or with... |
5067bb03140a11fedec13fa920848f996001a7f8a59c4025cf368067f5811cb7 | MATLAB | 2,412 | 66 | %% RVn1.csv ¿¡¼ location »Ì¾Æ³»±â
% Bridge¿¡¼ ÃßÃâÇÑ RVn1.csv ÆÄÀÏÀ» Parsing Çؼ Location data¸¦ ÃßÃâ
%% Load Data
[filename, pathname] = uigetfile('.csv','À§Ä¡ÆÄÀÏ "*RVn1.csv ÆÄÀÏÀ» ¼±ÅÃÇØ ÁÖ¼¼¿ä.');
fileID = fopen([pathname,filename],'r');
formatSpec = '%*s%s%f%d%*d%*d%d';
dataArray = textscan(fileID,formatSpec,... |
0f6c0691401bc94fbb7d4da9ac6211905ff62a4482811d726c703907a7f08ab0 | MATLAB | 2,413 | 77 | function tapas_BLT_runPrediction(params,iTrial)
% tapas_BLT_runPrediction is showing the prediction screen
% Show cue + prediction combo
if params.cue(iTrial) == 1
Screen('DrawTexture', params.screen.window, params.text.imgcue1, [], params.screen.fit, 0);
elseif params.cue(iTrial) == 2
Screen('DrawTexture', pa... |
1e3199a95900c2f1eb255cb24e088312b44fcdc00176076cc0173b07a454ccd4 | MATLAB | 2,413 | 81 | function equateRmsWav(subjName)
% function equateRmsWav(subjName)
% Not used during the experiment itself but allows to root mean square the sounds of a given
% subject.
if nargin < 1
subjName = input('Enter Subjects name: ', 's');
end
referenceDir = fullfile(pwd, 'Static');
subject... |
717161af286510ef0ca5a787d409e6f51d83858bcb6c1adbf10f7873dbe2e868 | MATLAB | 2,414 | 68 | function out = DN_Cumulants(y, cumWhatMay)
% DN_Cumulants Distributional moments of the input data.
%
% Very simple function that uses the skewness and kurtosis functions in
% Matlab's Statistics Toolbox to calculate these higher order moments of input
% time series, y
%
% ---INPUTS:
%
% y, the input time series
%
% c... |
adaadcc5a982dd5109ae42002546e385c399303a0c1325942eb91a7e7a4c2f54 | MATLAB | 2,414 | 76 |
% Cargar Datos Chema
orden_PFC=[1 3 30 5 28 7 26 2 31 6 17 4 29 9 18 8 27 11 19 10 25 13 20 12 24 15 21 14 23 16 22 22]; %Duplico el último canal para que sean 32
orden_PFC=[1 3 30 5 28 7 26 2 31 6 17 4 29 9 18 8 27 11 19 10 25 13 20 12 24 15 21 14 23 16 22];
orden_HC =[1 32 3 30 5 28 7 26 2 31 6 17 4 29 9 18... |
8a50e3f77e19da87b966c38dfe665f7a7d2d60de7f8e74d2c450de3572119575 | MATLAB | 2,415 | 56 | % VL_NNROIPOOL CNN region of interest pooling.
% Y = VL_NNROIPOOL(X, ROIS) pools each feature channel in X in
% the specified regions of interest ROIS. ROIS is a 5 x K array
% containing K regions. Each region has five coordinates `[t, u0,
% v0, u1, v1]` where `u0`, `v0` is the upper-left corner of a ROI,
% ... |
d257bc89902f9ae3163a374692148b3c5c0d0907ec2261eee990a8f0a8b06266 | MATLAB | 2,415 | 73 | function propvalSplitArray = tapas_uniqc_split_propval(propvalArray, nSplits)
% Splits PropertyName/Value pairs with cell/multi-element inputs into
% several varargins to be used separately
%
% vararginSplit = tapas_uniqc_split_propval(propvalArray, nSplits)
%
% IN
%
% OUT
%
% EXAMPLE
% tapas_uniqc_split_propval
%
... |
0c1365ebf5496052b98db278a992de024f65842a687b28c75ca38fcb19b1100b | MATLAB | 2,416 | 82 | %% unitTest.m
% This function performs a command line unit test based on the jobTesting.m file in the
% ci folder. All Osprey modules are tested in dependence of the
% included dataset. You can change the jobTesting.m file according to your desired
% needs. The results unittest class includes detailed informati... |
2a199f8b7fb88354dcd1d1db626a7615e703e079823b00a23713a831555c3d79 | MATLAB | 2,416 | 78 | function zone = DefineZone(s,shape,points)
%DefineZone - Define a restricted zone to which analyses can be circumscribed.
%
% Define a restricted zone in the environment, to which analyses can subsequently be
% circumscribed using <a href="matlab:help IsInZone">IsInZone</a>. Multiple zones can easily be combined (see ... |
234989520d66304794eba9c464d577e647c868c9913f78c4784bbf0561cd6fea | MATLAB | 2,417 | 69 | function setFigureProperties(varargin)
% SETFIGUREPROPERTIES Set consistent properties across figure elements
%
% Syntax:
% setFigureProperties()
% setFigureProperties('Name', Value, ...)
%
% Description:
% Apply consistent formatting to all axes, labels, and text in figure.
%
% Inputs (Name-Value pairs):
% 'Fi... |
3c8f0ac33e3cb1c7a2bb3d78bb0a30ac4c4002757ddb860b8358f2e9c2909948 | MATLAB | 2,417 | 66 | % op_eccKlose.m
% Jamie Near, McGill University 2014.
% Georg Oeltzschner, Johns Hopkins University 2019.
%
% USAGE:
% [out,outw]=op_eccKlose(in,inw);
%
% DESCRIPTION:
% Perform a classic Klose eddy current correction (Klose, Magn Reson Med
% 14:26-30 (1990). The complex signal vector of the water-suppressed FID is
%... |
9af794f02f777b85933f3695ff6993bee4c2e031e6ea09626a1a2d7653807d01 | MATLAB | 2,417 | 104 | function m = sero_srr_data2fit_1d_reg_v2(S, tr, b, w, do_t1, do_v, reg_str, mode, x0, opt, wght, te)
% function m = sero_srr_data2fit_1d(S, tr, b, w, do_t1, opt, x0, wght, te)
if nargin < 7 || isempty(reg_str)
% Define the regularization parameter
reg_str=0;
end
if nargin < 8 || is... |
f514279c512006ca4d4a24c7d8757ae2f1424b325e6a6fb299e8a6dceeb6bde8 | MATLAB | 2,417 | 87 | function cmd=surfing_afni_vol2surf(volpat,specfn,varargin)
% Wrapper function to run AFNI SUMA Vol2Surf
%
% CMD=SURFING_AFNI_VOL2SURF(VPAT,SPECFN,...)
% INPUTS:
% VPAT Pattern of HEAD volumefiles to project (wildcards allowed)
% SPECFN SUMA spec file, or a directory with such a file. In the
% la... |
0a3d24b88c87e416afeb4e2295464feb5511b32d97aa891bf36fc3182f56cbcf | MATLAB | 2,418 | 53 | %function [haloInd] = haloAssign(dist, clustInd, dc, rho, isHalo)
function [haloInd] = haloAssign(dist, clustInd,centInd,isHalo)
% Reference paper: Herzog et al. 2020 "Scalable and accurate automated method
% for neuronal ensemble detection in spiking neural networks"
% https://www.biorxiv.org/content/10.1101/2020.10.... |
69c1a19f2537ec35f23d4040d25a32d0935467a282094ab09255603a00139c48 | MATLAB | 2,418 | 89 | function [xdata,parm] = normalize_data(xdata,norm_mode,parm)
% Normalize data
% --- Usage
% 1. Normalize data and set mean & norm to 'parm'
% [xdata, parm] = normalize_data(xdata)
% [xdata, parm] = normalize_data(xdata, norm_mode)
%
% 2. Normalize data using 'parm'
% [xdata] = normalize_data(xdata, norm_m... |
a138e55b46bcb6843a9b30f3bc7e085d2c9f72a0d354cf279d28d2ea2413dd0d | MATLAB | 2,418 | 61 | function ncopies = checkworkspace(obj);
stack = dbstack;
stack(1:2) = [];
stack = rmfield(stack, 'line');
ncopies = 0;
if ~isempty(stack)
% empty stack means the base workspace
% check if we are in a different workspace
if ~isequal(stack, obj.workspace)
% is the current stack a subset of the o... |
f37e3a6eb1e524529e465d89d498699228d57ad5ba1dcfcbe48196218329b5dc | MATLAB | 2,418 | 72 | % UIGETFILE2 - same as uigetfile but remember folder location.
%
% Usage: >> uigetfile2(...)
%
% Inputs: Same as uigetfile
%
% Author: Arnaud Delorme & Hilit Serby, Scott Makeig, SCCN, UCSD, 2004
% Thanks to input from Bas Kortmann
%
% Copyright (C) Arnaud Delorme & Hilit Serby, Scott Makeig, SCCN, UCSD, 2004
... |
111dfa3293a81812e98db04c7941884b6bbd2a0e64719bce85ec5429fe038202 | MATLAB | 2,419 | 93 | function [barhandle, cfg] = plotsigbar(pcorr,cfg)
% plot sig bars %
nt = length(pcorr);
cfgfields = fieldnames(cfg);
if ~ismember(cfgfields,'plotcolor')
cfg.plotcolor = [0.0 0.0 0.0];
end
if ~ismember(cfgfields,'linewidth')
cfg.linewidth = 4;
end
if ~ismember(cfgfields,'pthresh')
cfg.pthresh = 0.05;
end
i... |
3924157fafa0e7b31bd5576c15f81026d2f4a4bbeaf0831830050bd7ccbd40d5 | MATLAB | 2,419 | 43 | function [acceleration,instantaneous_correlation_acceleration,velocity,instantaneous_correlation_speed]=compute_velocity(instantaneous_correlation_tensor)
% Computes the instantanaeous acceleration and velocity
% The time unit is the sample (each point in the second dimension is a
% sample)
% The position (r) unit ... |
07d150421b769d4ad19997f8a5214b8203059259590422f8d31fd2a99ed16f64 | MATLAB | 2,420 | 67 |
function [cc] = circumcenter(coil1,coil2,coil3)
% CIRCUMCENTER determines the position and orientation of the circumcenter
% of the three fiducial markers (MEG headposition coils).
%
% Input: X,y,z-coordinates of the 3 coils [3 X N],[3 X N],[3 X N] where N
% is timesamples/trials.
%
% Output: X,y,z-coordinates of ... |
3ad67f8570bc79207aee2157bc61df9480e108b971efb983de83b2b8b0c44147 | MATLAB | 2,420 | 79 | function [file_info,summary]=h5addmeta(h5path,meta_structure,varargin)
%
% HELP
% Saving metadata to the file from a structure. Creating datasets whose names correspond to the structure fieldnames.
% SYNTAX
%[file_info,summary]= h5addmeta() - use 1 if no arguments are allowed
%[file_info,summary]= h5addmeta(h5path) - u... |
025c0e880f4fde26fe03df047dab1af556d1086d063e08b5b7ddc291789b2f8d | MATLAB | 2,421 | 38 | function cifti_write_from_template(ciftitemplate, data, filename, varargin)
%function cifti_write_from_template(ciftitemplate, newdata, filename, ...)
% Use a template cifti struct with a dense or parcels diminfo and a new data
% matrix to write a new cifti file. The file extension is used to figure ou... |
369a5e0471e8eda37e3e8969f4cc80045a6d9e5773e00dd60c4f11a988a5c508 | MATLAB | 2,424 | 86 | function [ output_args ] = CALCIUM_FLUORESCENCE_CONVERSION( output_directory , id , dF_F_field , dT_duration , calcium_T1_2 )
%CALCIUM_FLUORESCENCE_CONVERSION( output_directory , id , dF_F_field , dT_duration , calcium_T1_2 )
% Usage: CALCIUM_FLUORESCENCE_CONVERSION( '~/' , 'TEST_1' , dF_F , 0.5 , 1 )
if( exist( outpu... |
fc729a647af1f84b866ede252f1f6a36f2bcd117e7f8dec8aefb7f0a3612f73a | MATLAB | 2,424 | 79 | function evaluate_ref_models()
% Evaluate MatConvNet reference models to validate them
addpath(fullfile(fileparts(mfilename('fullpath')), '..','examples', 'imagenet')) ;
models = {...
'resnet-50-dag', 2015, ...
'resnet-101-dag', 2015, ...
'resnet-152-dag', 2015, ...
'matconvnet-alex', 2012, ...
'matconvnet-... |
033ff7b3f1386292c6fd3b41a0d2cfd6a9c37faebdc994a97d62535c80c07062 | MATLAB | 2,425 | 66 | % fit_OspreyMM.m
% Georg Oeltzschner, Johns Hopkins University 2019.
%
% USAGE:
% [fitParams] = fit_Osprey(dataToFit, resBasisSet, fitOpts);
%
% DESCRIPTION:
% This is the function describing the Osprey fitting model, which is
% performed with the resampled basis set resBasisSet on the data contained
% in the FID-A da... |
f3d5826a33c6846641185f297bf81b92e35eebd3738b03e9d764349d25419a1e | MATLAB | 2,425 | 64 | function phiFaceAverage = harmonicMean(phi)
% This function gets the value of the field variable phi defined
% over the MeshStructure and calculates the harmonic average on
% the cell faces, for a uniform mesh.
%
% SYNOPSIS:
% phiFaceAverage = harmonicMean(phi)
%
% PARAMETERS:
%
%
% RETURNS:
%
%
% EXAMPLE:
%
% SEE AL... |
c597056a554957e0d9ec394eccd79b821e71116156d2c79cd53177b5ffbbc241 | MATLAB | 2,426 | 42 | function AFI_GroupAverageCorrectedMaps(AvgIndCorrMyelinFile, AvgIndCorrMyelinAsymmOutFile, IndCorrMyelinAllFile, GoodVoltagesFile, rAFIFile, AFIStatsFile, CSFStatsFile, RegressedMyelinOutFile, CovariatesOutFile)
AvgICorrMyelinMap = cifti_read(AvgIndCorrMyelinFile);
surfasymmnorm(AvgICorrMyelinMap, AvgIndCorrMye... |
cde62eab814b8d1eff361bcb64148fd5bc99247c7430d009c158b7a6b08e1bbb | MATLAB | 2,427 | 82 | %% unitTest.m
% This function performs a command line unit test based on the jobTesting.m file in the
% ci folder. All Osprey modules are tested in dependence of the
% included dataset. You can change the jobTesting.m file according to your desired
% needs. The results unittest class includes detailed informati... |
6eaa74c8abba5b02f85480269780c93ed2c9acb99f4a21638322107a0f5e698d | MATLAB | 2,429 | 48 | function thisAA = ch2roi_assignAA(brainAtlas_name, chAss_isargAtlas, groupInfo, list_AA)
% returns thisAA (string) of assigned anatomical area (AA aka ROI)
% thisAA = a row in the first column of 'list_AA' or 'n.a.' (if not assigned)
% based on 'brainAtlas_name' (case insensitive!), selects the corresponding field in
... |
f6b57bf98b6a27c94b53bce086c2abc65d746862322123ba1f35566ea90d560f | MATLAB | 2,429 | 73 | function gradfd = getGradientFD(problem, x, storedb, key)
% Computes an approx. of the gradient w/ finite differences of the cost.
%
% function gradfd = getGradientFD(problem, x)
% function gradfd = getGradientFD(problem, x, storedb)
% function gradfd = getGradientFD(problem, x, storedb, key)
%
% Returns a finite diffe... |
00575094a6c200b41adfd354f2493fb3debe31305787efd8929c3b1f12ad0180 | MATLAB | 2,431 | 83 | %-------------------------------------------------------------------------------
% mi_cont_cont: mutual information using the first method in [1]
%
% Syntax: mi = mi_cont_cont(x, y, k)
%
% Inputs:
% x - input vector (length-N)
% y - input vector (length-N)
% k - number of nearest neighbours (default 3)
%
%... |
0d7a00e7d9b000275d11e07e3327ff4422596d98b0e6773387c1902d11fc66a9 | MATLAB | 2,431 | 59 | function [isSpmOnPath, pathSpm] = tapas_physio_check_spm(doCorrectPath)
% Checks whether SPM exists in path, using also its check_installation for
% correct subfolder addpath
%
% [isSpmOnPath, pathSpm] = tapas_physio_check_spm();
%
% IN
% doCorrectPath if true, erroneous subfolders from SPM will be removed
% ... |
8b77da0ab116b09fa8b705ce2cd9013eee488200f44a858b72c08bb2421715eb | MATLAB | 2,431 | 78 | function plotVE(output, inverty)
% Plot the variance explained as violins and scatter plots
% Params
prox_cmap = repmat([215, 15, 175]/255, 7,1);
dist_cmap = repmat([255, 160, 25]/255, 17,1);
cmap = [prox_cmap; dist_cmap];
axvals = {[1,2,3], [5], [7,8,9], [12,13,14,15], [17,18,19,20], [22,23], [25,26,27], [29,30... |
cc8e8a9faaf84a7c08a9b439789e33441bff9a75de9b82e665e14a9c2fd142b9 | MATLAB | 2,432 | 76 | function [MRSCont] = osp_orderProcessFields(MRSCont)
%% [MRSCont] = osp_orderProcessFields(MRSCont)
% This function orders the processed struct fields to match the GUI order
%
% USAGE:
% MRSCont = OspreyProcess(MRSCont);
%
% INPUTS:
% MRSCont = Osprey MRS data container.
%
% OUTPUTS:
% MRS... |
152b4a361de91fef9f7231be70db1d1a438088ae830b01834872b0b2da108ce3 | MATLAB | 2,433 | 78 | function OUT = meta_analysis_table(XYZlist,r,varargin)
% OUT = meta_analysis_table(XYZlist,r,[master file name])
% takes a list of XYZ mm points, and, for each point you specify, makes a table of
% other studies in the meta-analysis files that report peaks within r mm (radius) of
% the point.
% Looks for a file on the ... |
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