sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
43bdea37076059f6bc103f126db01a4db5589d4440170e48ce17302d07145822 | MATLAB | 2,066 | 57 | function [Y,N,N2] = nanfft(X,N,DIM);
% NANFFT calculates the Fourier-Transform of X for data with missing values.
% NANFFT is the same as FFT but X can contain missing values encoded with NaN.
% NaN's are skipped, NaN do not result in a NaN output.
%
% Y = NANFFT(X)
% Y = NANFFT(X,N)
% Y = NANFFT(X,[],DIM)
% ... |
64b45966513e6e588afc9b47e5a0a3df6db90bb0caad052b497475b158abbf68 | MATLAB | 2,066 | 57 | function yRoiLo = shcropy(yCents,bbymax,sd,yRoiSz)
% yCents: [nx1] y-centroids
% bb: [nx4] bboxes
% sd: SD to use, will be approximate spread of centroids after crop
% yRoiSz: total y-size of cropped roi
assert(iscolumn(yCents) && iscolumn(bbymax) && numel(yCents)==numel(bbymax));
%sd = 19.5; % from view1, x-dir
ymid... |
7b7ffa20b7578cf5bd519fca4dba8d7ec0e2c7f799b30211ec16a33e8f1c6e75 | MATLAB | 2,066 | 42 | function Obj=SOFAconvertLISTEN2SOFA(LISTEN, subjectID)
% Obj=SOFAconvertLISTEN2SOFA(LISTEN, subjectID) converts the HRTFs described in LISTEN
% (see LISTEN HRTF format) to a SOFA object.
%
% Copyright (C) 2012-2013 Acoustics Research Institute - Austrian Academy of Sciences;
% Licensed under the EUPL, Version 1.1 or ... |
3a41ee992c9611a9ff9ae694e0f65ddbe51997b36d3eaa171096909aee61f5fe | MATLAB | 2,067 | 96 | %% Biosequence analysis Demo
% t = locn
% Z(t)|w ~ Discrete(w(:)), k in {1,2,3,4,k}
% theta(:,t) | Z(t)=k ~ Dir(alpha(:,k))
% x(i,t) | theta(:,t) ~ Discrete(theta(:,t))
% This file is from pmtk3.googlecode.com
%% Data generation
setSeed(1);
Nseq = 10;
Nlocn = 15;
Nletters = 4;
Nmix = 4;
pfg = 0.30;
mixwei... |
66b59151db950c340b6a66231e9136d305b54281dfd5bd8369251ceb6baf53a0 | MATLAB | 2,067 | 75 | clear
% clc
res=2;
dur=66;
all_trials_loc.glm_dd=nan(dur/res,3495);
all_trials_loc.glm_df=nan(dur/res,3495);
all_trials_loc.glm_fd=nan(dur/res,3495);
all_trials_loc.glm_ff=nan(dur/res,3495);
all_trials_loc.glm_time=nan(length(-1:res/100:2),3495);
all_trials_loc.glm_context=nan(length(-1:res/100:2),3495);
all_trial... |
6ec005add684091a484b704c7304d257e601f8d54d368f899c97da39aa4bd31f | MATLAB | 2,067 | 107 | function Gs = mk_all_dags(N, use_file, method)
% MK_ALL_DAGS generate all DAGs on N variables
% G = mk_all_dags(N)
%
% G{i} is the i'th dag
%
% Note: the number of DAGs is super-exponential in N, so don't call this with N > 4.
% This file is from pmtk3.googlecode.com
%PMTKauthor Kevin Murphy, Robert Tseng, Simon Suy... |
c49cb2f49c1dbf386f2ab1b8fe25a844988c44f43f65e40eb15975a92a6abf9b | MATLAB | 2,068 | 94 | function kernels = weights_to_kernels(w)
global glm
curr_index=1;
num=1;
kernels.const=w(curr_index:curr_index+num-1);
curr_index=curr_index+num;
if(isfield(glm,'no_pulse') && glm.no_pulse==1)
num=glm.ntime;
kernels.dd=w(curr_index:curr_index+num-1);
curr_index=curr_index+num;
num=glm.ntim... |
adac6cc2053c29d0882a1dd29897441ff03c38eb8eeb2748574dff2dbdd393ab | MATLAB | 2,070 | 51 | function potential=eeg_forward(dips,forwpar);
% usage: potential=eeg_forward(dips,forwpar);
% makes forward calculation for EEG in realistic volume
% conductors
% dips is an Nx6 matrix; the first 3 columns denote locations
% of N dipoles, and the last three columns the moments (in nAm)
% distances are assum... |
c819b2ea74fa796c220e96f5bb0651863a3bb7a50be4fc414facd3852f753ccc | MATLAB | 2,070 | 58 | %% Simple test of hmmDiscreteFitEm
% We compare how well the true model can decode a sequence, compared to a
% model learned via EM using the best permutation of the labels.
%%
%% Define the generating model
% This file is from pmtk3.googlecode.com
setSeed(0);
nHidStates = 4;
T = [1/6 1/6 1/6 ... |
c9018fec2707da32e7cdf2e282b8b18092a9c15326140ed64f73089eb19027a6 | MATLAB | 2,070 | 50 | function opts=Config_FormatCorr(GlobalOpts, varargin);
opts=GlobalOpts;
opts.PlotShuffle=0;
[varargin,opts.Dates] = Utilities.ProcVarargin(varargin,'Dates',{opts.Dates});
[varargin,opts.shuffle] = Utilities.ProcVarargin(varargin,'Shuffle',opts.shuffle);
[varargin,opts.overwrite] = Utilities.ProcVarargin(va... |
a1f8682cf4d771b967973a8d2d531da375fd6df34754d32a3aca0d26decb8928 | MATLAB | 2,071 | 71 | function Y = scale(X,S,dims)
%SCALE Scale along specified dimensions of tensor.
%
% Y = SCALE(X,S,DIMS) scales the tensor X along the dimension(s)
% specified in DIMS using the scaling data in S. If DIMS contains
% only one dimension, then S can be a column vector. Otherwise, S
% should be a tensor.
%
% Examp... |
a6b3c7109c40773fd3a6a9678414f6f4d35e648dc7aa588fd5b440beb9038578 | MATLAB | 2,071 | 57 | classdef DAQRecording < AudioRecording
methods (Static)
function canLoad = canLoadFromPath(filePath)
canLoad = false;
try
daqread(filePath, 'info');
canLoad = true;
catch
end
end
end
methods
... |
cd17aa8964f748e776d017b781db2cc5782cf61a073625d966b784800d888a23 | MATLAB | 2,071 | 77 | % Infer function on 2d grid using Gaussian MRF prior.
% Based on p141 of "Introduction to Bayesian Scientific Computing"
% Daniela calvetti and Erkki Somersalo
n = 50;
L = gauss_mrf_2d_precmat(n);
B = L'*L;
% Conditioning: I2 defines the points that are known,
% I1 points to free pixels
I = reshape([1:n^2],n,n);
I2 ... |
80c2b7073f9b98b56c9c87430c243ba542e61c98d92f89edf6efe91ad1b52738 | MATLAB | 2,072 | 74 | function data = LoadAuxData(datDir, varargin)
% hard-coded parameters
vScale = 0.0000374;
bytesPerSample = 2;
% default values of optional arguments
timeRange = [0 20];
lowpassCut = 100;
filtOrder = 20;
for i = 1 : 2 : length(varargin)
switch lower(varargin{i})
case 'timerange'
timeRange = v... |
094381778e4e2d3b22b837ad825d1c21afd70da297c12b7476e7a53cfd1c8cde | MATLAB | 2,073 | 105 | function [fx,dF_dX,dF_dTheta] = f_dcm_extension(Xt,Theta,ut,inF)
% nonlinear DCM evolution function
% function [fx,dF_dX,dF_dTheta] = f_dcm_extension(Xt,Theta,ut,inF)
% This function evaluates the evolution function of the neuronal states of
% a nonlinear DCM for fMRI model.
deltat = inF.deltat;
n = size(Xt,1);
nr = l... |
0b7a41ac0282e2e4f71930537caa4c71d7c82871a46dd99e53bb3c8f0cdfb52b | MATLAB | 2,073 | 68 | function [data,mesh]=femdata_BLT(mesh, varargin)
%% check in/out
narginchk(1,3);
nargoutchk(0,2);
%% get optional inputs, handle variable input
% default
solver = get_solver;
OPTIONS = solver_options;
if ~isempty(varargin)
if length(varargin) == 1
if ischar(varargin{1}) || isstring(varargin{1})
... |
a905886116cb02dfb85d255b6bc385566e08f57b2d8ddaff0177b13ff169814c | MATLAB | 2,073 | 60 | function map = jtreeFindMap(jtree)
%% Find the mode, (map assignment) using max-product and traceback
% jtree is a struct as returned by e.g. jtreeCreate
%
%%
% This file is from pmtk3.googlecode.com
maximize = true;
cliques = jtree.cliques;
preOrder = jtree.preOrder;
postOrder = jtree... |
38c9ab7b9bac34e006c7d5084c6eea494fe8db8e4337d3029a79a3632bfb0998 | MATLAB | 2,074 | 78 | % demo operant learning with VB volatile observer (adapted from Mathys,
% Daunizeau et al. 2010)
% This demo simulates a "volatile learner" experiencing feedback to her
% chosen actions in a 2-armed bandit task. VBA estimation then proceeds.
close all
clear variables
clc
% evolution, observation and feedback functi... |
7b2b0023a7321f083edc48537f72d22091c11e9b56821fa709878c274a424221 | MATLAB | 2,074 | 63 | function [logZ, postQuery] = variableElimination(cliqueGraph, queryVars)
%% Sum-product variable elimination
% cliqueGraph is a struct with the following fields:
% Tfac - a cell array of tabular factors
% G - the graph structure: an adjacency matrix
% nstates(j) - the number of states for node j
% ... |
14a8cff3b524c92a3759644c2b451e85eb7b71fffef8dfcc2117e89ff56fc280 | MATLAB | 2,075 | 74 | function [outfiles,outindexfiles] = split_mjpg(infile,inindexfile,outfilestr,chunksize,varargin)
[startframe,endframe,dooverwrite] = ...
myparse(varargin,'startframe',1,'endframe',inf,'dooverwrite',false);
% read in the header
fprintf('Reading index file %s...\n',inindexfile);
header = ReadIndexedMJPGHeader(... |
a69f1fb9a9fc880d3583d3261ea7781299a8f2138a9bc9f01771959c57a605f2 | MATLAB | 2,075 | 68 | function decVec = decode_success(data,winsize,stepsize,prctokeep)
%% test
%close all
%T=969;
%sig=zscore(cumsum(randn(T,18)));
%data=0.5*randn(T,18,32)+repmat(sig,1,1,32);
%winsize=25;
%stepsize=25;
%prctokeep=1;
%
% data is in format time x space x subjects
% winsize is a number of length of windo... |
5349e35816a75485eaf7eebf7bd2cd17e90aed15166a28ed0a084683a101da3f | MATLAB | 2,076 | 68 | function [mdl,r_all,distance_all]=corrVsDist(traces,positions,pyr,int)
% separate_plots = true;
r = corr(traces');
% r = corr(traces.all(:,mvm.mvmEpochsIndex)');
% r = corr(traces.all');
distance = pdist(positions); %Eucledian distance between cells
distance = squareform(distance);
%colour = lines(length(int)); % c... |
5c16baf4d76153e5ce4be831b3aba769e2756eb0705939f4c5e62e3c87055d45 | MATLAB | 2,076 | 35 | %% 包络变异系数（函数输入通常是imfx而非X） | Variation Coefficient of the Envelope (CVE)(based on imfs)
% 基于解析表示的瞬时振幅，反映包络离散程度的绝对值
% 1. 调用hilbert()函数对信号进行Hilbert变换得到信号的解析表示
% 2. 基于信号的解析表示，计算瞬时振幅（即信号包络）和瞬时相位
% 3. 基于信号包络计算包络变异系数CVE = std(envelope)/mean(envelope)
% imfx: IMF component of single channel EEG signal (either a row vector or
%... |
0d19171a54fccd3c234481696a4df9d3abdeb955d236484a34593fb44eba8c6c | MATLAB | 2,077 | 70 | function C = times(A,B)
%TIMES Array multiplication for sparse tensors.
%
% TIMES(A,B) is called for the syntax 'A .* B' when A or B is a
% sparse tensor. A and B must have the same size, unless one is a scalar.
% A scalar can be multiplied by a sparse tensor of any size.
%
% See also SPTENSOR.
%
%MATLAB Tens... |
51ab629dfb94117eb02bdeb3bba09806466ea95b8ec091cde27e7c4955bf9873 | MATLAB | 2,077 | 59 | function [event] = read_bucn_nirsevent(filename)
% READ_BUCN_NIRSEVENT reads the event information of ASCII-formatted NIRS
% data acquired with the UCL-BIRKBECK machine and postprocessed by the
% Paris group. The first line contains the header-info and the rest of
% the file contains per line an event. The first colu... |
67e775f73b5cb49f418906a35ed83ba1c19f6be4a899ebfbac0ffb8ac08df8ea | MATLAB | 2,077 | 89 | %% Demonstrate inference in a 2d grid of a multi-state noisy image of an X
% Based on http://www.cs.ubc.ca/~schmidtm/Software/UGM/alphaBeta.html
% This file is from pmtk3.googlecode.com
%% Get model and data
setSeed(0);
loadData('XimgRgb');
Xclean = Xrgb;
X = Xclean + 0.5*randn(size(Xclean));
[nRows, nCols, ncolors... |
ec742574f3212a59cd74df8f99aba88b68e5248abe656e5055fe444a33fc374c | MATLAB | 2,077 | 72 | function A = makehatch_plus(hatch,n,m)
%MAKEHATCH_PLUS Predefined hatch patterns
%
% Modification of MAKEHATCH to allow for selection of matrix size. Useful whe using
% APPLYHATCH_PLUS with higher resolution output.
%
% input (optional) N size of hatch matrix (default = 6)
% input (optional) M width of ... |
3343e57d41bcf964308bc8fb8a2148a36219e7191813b69370f72686afc7c543 | MATLAB | 2,078 | 56 | %% load data
load("../data/FIG2_preprocessed.mat")
%% fitting of board neurons to known input brightness
mon_pos = mon_vals(1:2:end,:,:);
mon_neg = mon_vals(2:2:end,:,:);
fits = {};
figure;
for i = 1:2
for j = 1:2
[mon_pos_grid,mon_neg_grid] = meshgrid(mon_pos(i,j,:),mon_neg(i,j,:));
ft ... |
288d7fd3b30692c22a016bcd356fb1135e67cd599b52633b05eee1eab7b794ef | MATLAB | 2,080 | 64 | function [ varfast, varslow ] = ...
wlProc_calcVarFastSlow(data, samprate, fdc, flong, fshort)
% function [ varfast, varslow ] = ...
% wlProc_calcVarFastSlow(data, samprate, fdc, flong, fshort)
%
% This function calculates the fast-changing and slowly-changing portions
% of the variance of a supplied signal wavefo... |
3d92a5c5ed8d140720a298cbcf5b81156b5412048bfdc7bced87f60ffd18c2ff | MATLAB | 2,082 | 75 | %%
FLYNUM2CALIB = '/groups/huston/hustonlab/flp-chrimson_experiments/fly2DLT_lookupTableStephen.csv';
fly2calib = readtable(FLYNUM2CALIB,...
'Delimiter',',',...pwd
'ReadVariableNames',false,...
'HeaderLines',0);
fly2calib.Properties.VariableNames = {'fly' 'calibfile'};
fly2calibMap = containers.Map(fly2calib.fly... |
bf5d56ea01974d47da3d2590b55b39536e40130df8709943669968ed26bf25c0 | MATLAB | 2,082 | 57 | function afxConnWholeBrain(y,yRoi,brainMask,rois,dim,mat,outDir,subjectName)
% calculation of functional connectivity
fprintf(' Calculating whole brain functional connectivity ...\n')
% prepare whole brain time series
% keep only data within the brain mask (saves memory in the parfor-loop)
... |
d217660d69ee8e3836f0d42dcbde452d0699a56207dacc17579e39e69a2cbd97 | MATLAB | 2,082 | 72 | %Convert the 3D sift features into a usable array
function correspondences = find_correspondences(keys_moving, keys_fixed)
DM = []; %M for moving
LM = [];
for i = 1:length(keys_moving)-1
DM(i,:) = keys_moving{i}.ivec;
LM(i,:) = [keys_moving{i}.y, keys_moving{i}.x, keys_moving{i}.z];
end... |
76c23462a16a39dd9a8fb06877b368932a0a1431bf2009a502c79f6bfcd337f6 | MATLAB | 2,083 | 100 | %% Demo of minimum spanning tree
function minSpanTreeDemo()
% This file is from pmtk3.googlecode.com
%% Example from Cormen, Leisersen, Rivest p508
a=1; b=2; c=3; d=4; e=5; f=6; g=7; h=8; i=9;
G = zeros(9,9);
G(a,b)=4; G(a,h)=8;
G(b,c)=8; G(b,h)=11;
G(c,d)=7; G(c,i)=2; G(c,f)=4;
G(d,f)=14; G(d,e)=9;
G(e,f)=10;
G(f,... |
3174c1f9add008811bc463771d046b108a52b7ed3230e79bdeaf8e9021eb5a1a | MATLAB | 2,084 | 71 | % SYNTAX
% example_global_smoothing_lumped_laplace
% DESCRIPTION
% This script performs global (or local) iterative Laplacian mesh
% smoothing using the lumped-smoothing algorithm. The smoothing improves
% triangle quality and increases min edge length but deforms the mesh
%
% Low-Frequency Electromagne... |
7384798fc1ae3613d209325845d6317e2a047bb171400b421f9de1307453ea5f | MATLAB | 2,084 | 86 | function [volume, flipvec] = volumeflip(volume, flipvecin)
% VOLUMEFLIP
%
% See also VOLUMEPERMUTE
if nargin<2
flipvecin = 'auto';
end
% do a low-level check on the input data
if ~isfield(volume, 'transform'), ft_error('the input volume needs a transformation matrix'); end
if ~isfield(volume, 'dim'), ft_erro... |
85b2288b61786ca4efdcf4a262cdd95b09a876e47e8ca07d39c3472949c4871f | MATLAB | 2,084 | 71 | function s = collapse(t,dims,fun)
%COLLAPSE Collapse sparse tensor along specified dimensions.
%
% S = COLLAPSE(T,DIMS) sums the entries of T along all dimensions
% specified in DIMS. If DIMS is negative, then T is summed across
% all dimensions *not* specified by -DIMS.
%
% S = COLLAPSE(T) is shorthand for S = COL... |
d054a1d2c449034dc73696ed2471aee5fd04e40e60a9c5470a24f1a7f8c36808 | MATLAB | 2,084 | 78 | function obj = customtrim(obj,nrmv,varargin)
% trim both images and MP at the same time
if isempty(varargin)
prf = 't';
else
prf = varargin{1};
end
runloop=1;
% only providing rawMNI data
if isfield(obj,'rawMNI_run') && ~isfield(obj,'sMNI_run') && ~isfield(obj,'tMNI_run') ... |
23bec549d5d58ddd32aecf19190a978e717302b0c58dd472eabba2debd9395ec | MATLAB | 2,085 | 59 | function [Y,XYZ] = VBA_spm_read_vols(V,mask)
% Read in entire image volumes
% FORMAT [Y,XYZ] = spm_read_vols(V,mask)
% V - vector of mapped image volumes to read in (from spm_vol)
% mask - implicit zero mask?
%
% Y - 4D matrix of image data, fourth dimension indexes images
% XYZ - 3xn matrix of XYZ locations ret... |
b91bb531ff9f82152b2b22803661838a9832ef47a6b9a1984bd51214e97d8b29 | MATLAB | 2,085 | 77 | %% Classify some MNIST digits using a deepBelNet
%PMTKauthor Andrej Karpathy
%PMTKmodified Kevin Murphy
%PMTKreallySlow
% This file is from pmtk3.googlecode.com
%% Data
setSeed(0);
clear all
if 0
%all datasets above must conform to the following naming conventions:
%for training: 'data' NxD, 'labels' Nx1
%for... |
d5c7c61f19b4be695647467e1cbf6b30adcfb9d62e3109d5a04936965495a8ff | MATLAB | 2,085 | 74 | %% Fit a mixture of Gaussians and mixture of Students to some data
% and use the resulting models to classify
% This example is based on fig 3.3 of Kenneth Lo's PhD thesis,
% "Statistical methods for high throughput genomics", UBC 2009
%PMTKauthor Hannes Bretschneider
%%
% This file is from pmtk3.googlecode.com
funct... |
31adf600b43514c3eb3936b745a000b6c5509a8215187b4a5281186acc24f50f | MATLAB | 2,086 | 105 | function RT = rt_fourier(RT,cfg)
% v.0.0.1
% <*LAN)<| version
%
%
% Pablo Billeke
%
%
if nargin > 1 && isstruct(cfg)
%%% ifplot
try
ifplot = cfg.ifplot;
catch
ifplot = 0;
end
%%%%
try
NFFT = cfg.nfft;
ifnfft = 1;
catch
... |
5ce8378a57ed6479753a83c09034e2caf27e25e9bd912d833fa3ba1047b1ee0c | MATLAB | 2,086 | 57 | function [tf,reason,where] = SOFAcompare(Obj1, Obj2, varargin)
%SOFASOFAcompare
% TF = SOFAcompare(A, B) compares A and B and
% returns logical 1 (true) if they are identical.
%
% [TF,REASON,WHERE] = SOFAcompare(A, B) provides the REASON
% and shows WHERE the difference arose.
%
% ... = SOFAcompare(A, B, 'i... |
5d05ff07ab5a6054f2c95ddab8e7e95f9b6e5d57f70dbf9212b01bab098ea1a0 | MATLAB | 2,086 | 54 | function H = histcImWin( I, edges, wtMask, shape )
% Calculates local histograms at every point in an image I.
%
% H(i,j,...,k,:) will contain the histogram at location (i,j,...,k), as
% calculated by weighing values in I by placing wtMask at that
% location. For example, if wtMask is ones(windowSize) then the
% histo... |
11033911276abc5d96f8c595f886c2764c2817777e6a028ae1aa14146d866a73 | MATLAB | 2,087 | 34 | clear;clc;close all
ROOTPATH = strcat(NoveltySU.utils.getRootDirPath(mfilename("fullpath"), 4), "Data\Processed Data\");
cd(NoveltySU.utils.getRootDirPath(mfilename("fullpath"), 2))
protStr = "Active duration";
temp = NoveltySU.utils.dirItem(strcat(ROOTPATH, protStr), "spkData.mat");
popRes_behav = cell2mat(cellfu... |
34a3d50204385a1c32d60e7f1751d07c7ae1998d8865569f69580ded81e068df | MATLAB | 2,087 | 63 | function [AUC, fpr, tpr, EER, cutoff, tprAtThresh, fprAtThresh, thresh] = ...
rocPMTK(confidence, testClass, fprThresh)
% Compute ROC curve
% confidence(i) is a real value
% label(i) is 0 or 1
%
% AUC is area under curve
% cutoff is the threshold that gives equal error rate (EER)
% EER is the fpr=tpr at cut... |
8f6915fde6c9d4efbee77ce59261c9277d29d0ead799b4cd44826cf724bc4679 | MATLAB | 2,087 | 55 |
%Define paramters
simparams.IMAGE_RESOLUTION_XY = .165; %microns
simparams.IMAGE_RESOLUTION_Z = .165; %microns
simparams.IMAGE_FOVSIZE_XY = 150;
simparams.IMAGE_FOVSIZE_Z = 50;
%puncta size (I think u=10 and s=3.5 is correct but it's slow)
simparams.PUNCTA_SIZE_MEAN = 8; %FWHM
simparams.PUNCTA_SIZE_STD = 3;
simparams... |
028f92982ed30d51e512aa3df948a069b268708d866c9b707df3e59d914d798f | MATLAB | 2,088 | 54 | function CBIG_RF_find_nearestVertex_fsaverage2MNI_mapping(map_dir)
% function CBIG_RF_find_nearestVertex_fsaverage2MNI_mapping(map_dir)
%
% This wrapper function reads the RF-ANTs fsaverage-to-MNI152 mapping and convert the spherical
% coordiantes in fsaverage to their nearest vertices
%
% Input:
% - map_dir:
% ... |
2461184f1fb8d3676f2334be277e9289dbbd642609c8b14e0d96a67b02f77eac | MATLAB | 2,088 | 71 | %%
A = load('/groups/branson/home/kabram/bransonlab/pose_hourglass/pose_hg_demo/mpii_human_pose_v1_u12_2/mpii_human_pose_v1_u12_1.mat');
A = A.RELEASE;
%%
ff = fopen('/groups/branson/home/kabram/bransonlab/pose_hourglass/pose_hg_demo/annot/valid_images.txt');
G = textscan(ff,'%s');
fclose(ff);
G = G{1};
%%
imdir = '/gr... |
4204e4abced6571a533eb67a5e9c4d7a179edecb8166a06593e607b9ad829cd9 | MATLAB | 2,088 | 50 | function pw = lme_plannedPower(Zi,ZiCol,Dhat,phisqhat,effsz,dr,sz1,sz2,alpha)
% pw = lme_plannedPower(Zi,ZiCol,Dhat,phisqhat,effsz,dr,sz1,sz2,alpha)
%
% Power calculation for a planned ba... |
5eca92faec1eb78916bc1004118fc8b9fb1025073fcc234a5838800b180c615a | MATLAB | 2,088 | 48 | % This script computes the induced surface charge density for an
% inhomogeneous multi-tissue object given the primary electric field, with
% accurate neighbor integration
%
% Copyright SNM/WAW 2017-2020
%% Global accurate primary field
tic
gaussRadius = 2*R;
[Epri, Ppri] = bemf3_inc_field_electric_gauss_sel... |
e828c4205c50985730c0b0adcb64833fedb76f183dcb5a6ba508c76258b74aa7 | MATLAB | 2,088 | 85 | %% Interpolate some data using a joint Gaussian
% Based on p140 of "Introduction to Bayesian scientific computation"
% by Calvetti and Somersalo
setSeed(1);
D = 150;
Nobs = 10;
xs = linspace(0, 1, D);
perm = randperm(D);
obsNdx = perm(1:Nobs);
hidNdx = setdiff(1:D, obsNdx);
xobs = randn(Nobs, 1);
% Make a (D-2) * D... |
d963535722b27d8c6f7e74c275250964ff64ad2b8ccd16951044b573c66645c9 | MATLAB | 2,089 | 67 | clear all;
%load ../phi/phi_0_25_1089.mat %Load the measurement matrix for measurement rate of 0.25 to sense patches of 33 by 33.
load ../phi/phi_0_04_1089.mat %Load the measurement matrix for measurement rate of 0.04 to sense patches of 33 by 33.
%load ../phi/phi_0_10_1089.mat %Load the measurement matrix for measure... |
e78f312620b986ec4ebd42b3c05d299edef90c457b7f71ee357bc83b40e03cf7 | MATLAB | 2,089 | 78 | % This program is free software; you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation; either version 2 of the License, or
% (at your option) any later version.
%
% This program is distributed in the hope that it will be useful,... |
22f256ef0751dd2559b7b287cdde5c3d44080c44d45f0622d7d467c7595cb11c | MATLAB | 2,090 | 77 | %% Illustration of the bias variance trade off as we vary the L2 regularizer.
%
%%
% This file is from pmtk3.googlecode.com
function biasVarModelComplexity
setSeed(0);
n = 25; d = 1;
lambdas = [exp(6),exp(0.5),exp(-2.5)];
ndataSets = 100;
showNsets = 20;
f = @(x) sin(2*pi*x);
domain = (0:0.0005:1)';
fs = 16;
figure... |
68b24478acca21c0f6ab07c0e660b007c7c63fb7bbf9fbd692ba28fc5911e9f8 | MATLAB | 2,091 | 77 | function sea_salt
% general parameters
alpha = 0.1;
trials = 100;
% parameters of reward basis model
w_norm = [-1, 1];
w_depl = [0.5, 1];
%simulating models
VTD = TD_learner (alpha, trials);
VRB_bases = RB_learner (alpha, trials, w_norm);
VRB_norm = w_norm * VRB... |
d669e16145b84183ab282b26e696bc017f40b80004cd88ad131d5c9a1bb4ae7a | MATLAB | 2,091 | 71 | function S = varstruct(var1, var2, varargin)
%VARSTRUCT Creates a structure out of a set of variables. Fieldnames are inferred from variable names.
% Usage:
% S = varstruct(var1, var2, ...)
% S = varstruct('field1', val1, 'field2', val2, ...) % same as struct()
%
% Args:
% var1, var2, ...: variables used to crea... |
375e6143d68e48b1061d48610d0eaaba672191bdabdc0ed9de8febe6e578be3c | MATLAB | 2,092 | 105 | classdef RC
% Configuration file
properties (Constant)
FILE = lclInitFile();
end
methods (Static)
function v = getpropdefault(name,dfltval)
% get prop if it exists; if not, set prop to default val and return
% it
rc = RC.load;
if isfield(rc,name)
v = rc.(na... |
b1c94442d38b9927bdf4730f699ca8a8bd0fdcbc852486aabaa249d10c2ed07d | MATLAB | 2,092 | 69 | function mask = mesh_mask(mesh, uidx, minv, minu, vsize, usize)
% create a binary mask on a texture coordinate grid
%
% mask=mesh_mask(mesh, minv, minu, vsize, usize)
%
% mesh: struct elements f,v,vn,u,b
% minv, minu: offset of u,v grid
% vsize, usize: texture coordinate grid size
%-----------------... |
0a7bfca2079bd2e6266cda7d517c72a87d1353a777749210a3e69d6b6109ec2b | MATLAB | 2,094 | 77 | function Transform_Curvelet(num_, p, q)
% Validate input arguments
if nargin < 3
error('Not enough input arguments. Usage: Transform_Curvelet(num_, p, q)');
end
% p: 1 for sweep, 0 for neutral
% q: 1 for sweep, 0 for neutral
if ~isnumeric(num_) || num_ < 0
error('Invalid in... |
91ff7bb592accd9327b8dd9a14b8a12180188def6aaf3d36efb02316c4ad9a2e | MATLAB | 2,094 | 83 | function varargout = compileRunAndSave(fname,varargin)
% Similar to compileAndRun except the mex file is not deleted.
% If the mex file exists, then this function tries to use it and only
% compiles a new copy if that fails. This version is useful when a function
% will be called over and over again with the same sized... |
ba7e0ccfbfe1c7da0479d2464f935b8f2af6e8edd2b613ad6279e8ec7b89e51f | MATLAB | 2,094 | 65 | %% GSA_GetTotalSy: calculate the total sensitivity S of a subset of inputs
%
% Usage:
% [Stot eStot pro] = GSA_GetTotalSy(pro, iset, verbose)
%
% Inputs:
% pro project structure
% iset cell array or array of inputs of the considered set, they can be selected
% ... |
07cbee253528bda7103d73a857156ed98cb73740e4d3c2737538c3d8b37db42e | MATLAB | 2,095 | 42 | function Bpri = bemf3_inc_field_magnetic(strdipolemvector, strdipolemcenter, strdipolemstrength, Points, mu0)
% Computes incident magnetic field from the dipole distribution via the FMM
% in terms of the pseudo electric potential
%
% Copyright SNM 2018-2020
% Compute dipole positions, directions, and ... |
e51aaf51ca60b3800131a818559c4456d6c5fa13f15039624a45facb3f185c2b | MATLAB | 2,095 | 57 | function [ridiff,cilohi,p] = ridiffci(r1,r2,n1,n2,alpha)
% function [ridiff,cilohi,p] = ridiffci(r1,r2,n1,n2,alpha)
%
% computes a confidence interval (CI) for the difference of two INDEPENDENT Pearson
% correlation coefficients and tests whether they are significantly different
%
% INPUTS
% r1 Pearson correl... |
2dde35e5c0d3c085f606aed2d78541abf6ee372f7c1469054cd7e1ac85499e21 | MATLAB | 2,096 | 84 | %% filtfilt xt
%// Variation of filt-filt which is better designed for short signals
%(which will be more affected by signal endpoint artifacts).
%
% Reduce endpoint artifacts by appending 0-value rows to the passed
% elements.
%
% B = input filtering coefficient (as filtfilt)
% A = input filtering coefficien... |
4b443527378a78503bd489c366c393814f7221e6813600bd0ad4d0ce0e24fd4b | MATLAB | 2,096 | 69 | function [Y,V] = maskMaker(format, maskFile, varargin)
% Y = obj.mask;
% returns a 3d logical of in-mask voxels for the grey matter mask of
% the subject associated with the call. Does not work on top-level
% (TIPPstudy) objects, or subject-level or below (below it will search paren... |
7153256e4639466ed030b40074e0de4f7f89708ddaa2dee7c05dc53da697bc18 | MATLAB | 2,096 | 67 | %%
% Primary Data Dependencies
% Used for the classes which directly interact with data, ensuring good
% handling between interconversion and sampling;
%_______________________________________
% Copyright (C) 2024 Trevor S. Smith
% Drexel University College of Medicine
%
% This program is free software: you can re... |
7f12d090acc83d1c37755bc6d1b11ebe9580603a5aff284d96500ed2bce516f2 | MATLAB | 2,096 | 70 | function [allVec_rest,allTs_rest,fullCycle] = Closed_Loop_ETP_train()
% Closed-loop algorithm using ETP to train the prediction algorithm based
% on a resting state recording to use in real time.
% allVec_rest: Resting EEG (channel*sample)
% allTs_rest: Timestamp of each sample
% fullCycle: Adjusted period based ... |
bb01b38bdc783891edae11a5c8c6a2a083c6b1dcf71fca90b81b374774da2f12 | MATLAB | 2,096 | 103 | function Feng_fit = feng_fit_wrapper(IDIF_path, qc_path, anatomy, options)
if nargin<6
options = get_default_options();
end
load(fullfile(IDIF_path,['IDIF_' anatomy '.mat']),'IDIF');
IDIF_raw = IDIF.IDIF_raw;
t_IDIF_emi = IDIF.t_IDIF_raw;
t_IDIF_delta = IDIF.t_IDIF_delta;
%%%%%%%
%%Fit%%
%%%%%%%
%settin... |
d83130ac3a692b07add331658122b437881fd77ab8adfa372be9532c30561128 | MATLAB | 2,096 | 78 | function [xs, idxs, phis_to_go, pAp] = conjgrad(eval_Ap, b, x0, maxiters, miniters, cg_tol)
%% Implementation of the conjugate gradient method. See Martens, 2010.
% phi(x) = 1/2 x' * A * x - b' * x is the quadratic function to be minimized.
gapratio = 0.1;
mingap = 10;
maxgap = max(ceil(maxiters * gapratio), mingap) + ... |
3ae65b2940c224a7a0d65f9434fce2b86ad2d7da3c72a6ad130ddc5f87e4942b | MATLAB | 2,097 | 56 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%% bem3_save_forwardp.m %%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
if n_shells <= 3
error("This script is meant to be used with models of more than three ... |
034edaff77e10878814057941d1e97f2683907990d4cf42cee2a5f98088d38ad | MATLAB | 2,098 | 73 | function [EEG, epochFlags] = GetEpochFlags(EEG, updateManual)
% [EEG, epochFlags] = GetEpochFlags(EEG, updateManual)
% converts the binary flagged events within each epoch into indices of
% flags for each trial (across all events within an epoch). This is stored
% in EEG.epoch.trailFlags.
% If updateManual = 1, then i... |
41b476cb8a21b8148236b9585dc00e5e6247f36a47a650f7ee534f62cc8191af | MATLAB | 2,098 | 44 | function TSaddeventcodes(varargin)
% TSADDEVENTCODES Adds individual event codes to the Experiment structure
% TSaddcodes( name, value ) adds event code definitions to the
% Experiment structure. Name is a string for 1 code or a cellstr for
% multiple codes, indicating the names of the codes to add, and Value is... |
795af4f6c107ce5900c979807cec7acf0bc25890a8c2cbd9f5737165a2076f57 | MATLAB | 2,098 | 70 | %% Plot a 2D Gaussian and its decorrelated and whitened transformations
%
%%
% This file is from pmtk3.googlecode.com
function gaussPlot2dDemo2()
setSeed(0);
mu = [1 0]'; % mean (must be row vector for mvnpdf)
S = [2 1.5; 1.5 4]; % covariance
plotSurf(mu, S, 'Full')
%% U = eigenvectors, D = diagonal mat... |
982cd07f30301ef3b3e9d90362e8c195f77b5eb3f676cdc62b271d0db9f2553e | MATLAB | 2,099 | 75 | function htmlTableSimple(varargin)
% Display a Matlab cell array or numeric matrix as an html table
% Similar to htmlTable, but the resulting generated html
% text is very bare bones, and hence easier to edit
% and include in published documents
%
% format can be 'int', 'float' or 'str'
% If str, we assume data{i,j} i... |
a0cfa2e90bf60991300e6b28682048c2ed55a2b01590399ab8e99f162c3c3a42 | MATLAB | 2,099 | 83 | % This program is free software; you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation; either version 2 of the License, or
% (at your option) any later version.
%
% This program is distributed in the hope that it will be useful,... |
c59282f53f0ffcd033de6e086f7f55c12ebe52e170436fed2b6b8a14c61f9b84 | MATLAB | 2,099 | 66 | % This program is free software; you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation; either version 2 of the License, or
% (at your option) any later version.
%
% This program is distributed in the hope that it will be useful,... |
073ee3c2f546960d6b4fab83f9b2df06c63f0dc4a610351486a2a4c93c4678df | MATLAB | 2,100 | 54 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This script corrects the obtained results for multiple comparisons using%
% the Benjamin and Hochberg approach %
% %
% Author: ana.tr... |
e3982400f23a8d9a8511e6fd5b750f4fb1fb3a3a8e79d5299d49577275d7d6a2 | MATLAB | 2,100 | 58 | function [y,iflaw]=anafsk(N,Ncomp,Nbf);
%ANAFSK Frequency Shift Keying (FSK) signal.
% [Y,IFLAW]=ANAFSK(N,NCOMP,NBF) simulates a phase coherent
% Frequency Shift Keying (FSK) signal. This signal is a succession
% of complex sinusoids of NCOMP points each and with a normalized
% frequency uniformly chosen between NBF di... |
6789070543f87375bd2098f2725834a007c55f44cc298fb5b12fc202ee0c20c6 | MATLAB | 2,102 | 86 | % _ _
% ___ _ __ __ _| |__ ___ ___ _ __| |_
% / __| '__/ _` | '_ \/ __|/ _ \| '__| __|
% | (__| | | (_| | |_) \__ \ (_) | | | |_
% \___|_| \__,_|_.__/|___/\___/|_| \__|
%
% updates various elements when a new channel is selected
function updateControlsOnChannelChange... |
77d2ca43d7460d5da9419e95b20ea45965e26bfd42a33aa70bd35c99242aa78e | MATLAB | 2,104 | 85 | %XMLDEMO2 Demonstrate how to read an XML file, modify it and save it
%
% Description
% This script demonstrates the use of the xmltree class to
% open an XML file, access data stored in it, modify a value
% and save the new XML file.
%
% This demonstration script need the file 'example.xml' created
% in the... |
0674bd0a3978f9aa1f5180e422df3cb7b74a4e781f6c7be6a6483984697aecc7 | MATLAB | 2,105 | 83 | function A = fast_ica(x,pcomponents,nit)
% Originally written by the Finish (Aapo) team;
% Modified by the PIB team in Aug. 21, 2007
% PIB - Biological Information Processing Lab - UFMA - Brazil
% Modified by V�tor Lopes dos Santos Aug. 2011.
if nargin < 3, nit=100; end
% fprintf ('Removing mean...\n');
%----------... |
302e765cb3f0532c129a699e97a0ef9d5f7e0f0e2c8354759425f2635b2aed4b | MATLAB | 2,105 | 88 | function path = viterbi_path(prior, transmat, obslik)
% VITERBI Find the most-probable (Viterbi) path through the HMM state trellis.
% path = viterbi(prior, transmat, obslik)
%
% Inputs:
% prior(i) = Pr(Q(1) = i)
% transmat(i,j) = Pr(Q(t+1)=j | Q(t)=i)
% obslik(i,t) = Pr(y(t) | Q(t)=i)
%
% Outputs:
% path(t) = q(t), wh... |
52eaee3e63ba6f907c23fe068639c255dab7318902adaef4f0b9d843fda15fe8 | MATLAB | 2,105 | 62 | % RSKELF_PARTIAL_MV Multiply using partial recursive skeletonization
% factorization.
%
% Like RSKELF_MV but using a user-supplied function of the form
% Y = MVFUN(X,TRANS) to apply the compressed skeleton submatrix. More
% specifically, denote by A the original matrix, and let SK and S be ... |
5cf732582937320b1553abc728d232a34b000eef0e7f1baffe5159b2bd1b44b4 | MATLAB | 2,106 | 86 | function [theta,e,hy,hp] = GLM_covComp(y,X,Qy,Qp,my,mp)
% wraps GLM with multiple covariance components estimation into VBA
% function [theta,e] = GLM_covComp(y,X,Qy,Qp,my,mp)
% IN:
% - y: px1 data vector
% - X: pxn_phi GLM design matrix
% - Qy: nqyx1 cell array of data covariance components
% - Qp: nqpx1 cell ... |
fb86409de33cecdb922ed31e589a77803e220e808b28deddca2f059ed91d07d1 | MATLAB | 2,106 | 73 | function S = NB_Init(file)
%% Unload variables from file and initialize
[t_lim,L,div,s,D0,N_neur,tpr,uprr,uprt,uprd] = readvars(file,'Range','A1:J2');
[Kt,Kc,Kr] = readvars(file,'Range','K1:M3');
t = 0;
f = 0;
[X,Y] = meshgrid(1:div);
% Neuron matrix: [position mesh number ; upr(-1) ; upr]
NEUR = zeros(N_neur,3);
% F... |
4a6b29c96e81eb0f6beef0632c0600a8498ed4b27f1a2ea2701fd8dd84e132e2 | MATLAB | 2,107 | 56 | function [varargout] = narginchk(varargin)
% NARGINCHK is a drop-in replacement for the same function that was
% introduced in MATLAB R2011b.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% see https://github.com/fieldtrip/fieldtrip/issue... |
8de88d264e93237141fedb59bd087c890d8e89a04d658aadf3f2e6898658d86f | MATLAB | 2,108 | 74 | function xout = scale(x,varargin)
% Centers and scales column vectors to mean 0 and st. deviation 1
%
% :Usage:
% ::
%
% x = scale(x,[just center])
%
% Notes:
% - This function will remove NaNs, but will remove ENTIRE row if any
% observation is NaN. This may be suboptimal for some applications.
% - In the future, ... |
b1b15aa01b843c39e16387f2a1e7f1f9348b6274ba4270c846ba8c7ccee7ae7d | MATLAB | 2,108 | 58 | % FT_POSTAMBLE_HISTORY is a helper script that stores the configuration structure that
% is present in the present workspace (i.e. the workspace of the calling function) in
% the output variable.
%
% Use as
% ft_postamble history outputvar
%
% See also FT_PREAMBLE, FT_POSTAMBLE, FT_POSTAMBLE_PROVENANCE
% Copyright (... |
ced67ac01489ee969ae39aaac72ce176372f0df46f07c06f770118d1a4fa9ef9 | MATLAB | 2,108 | 81 | % demo for calcium imaging of spike trains
% The script first simulates the response of a Fitz-Hugh-Nagumo (FHN)
% neuron to spiky input current. It then inverts a FHN-neuron model,
% without the input current info. Practically speaking, this means
% deconvolving the FHN-neuron response to estimate its input.
% [see de... |
4a50b89a74ce3cbf24f73db8b3f15b58c394fc6a056ec6267459636b9a7271b6 | MATLAB | 2,109 | 68 | % read_erplabdata() - import ERPLAB dataset files
%
% Usage:
% >> dat = read_erplabdata(filename);
%
% Inputs:
% filename - [string] file name
%
% Optional inputs:
% 'begtrial' - [integer] first trial to read
% 'endtrial' - [integer] last trial to read
% 'chanindx' - [integer] list with channel indices to ... |
779eae0850ef217be411dfed4224f77fce0f707b61e5f097bfc5749b27b91bc9 | MATLAB | 2,109 | 70 | function rt = isParsableDspaceArg(arg)
% This function returns true if the function dspace() could parse the argument as part of
% a Dataspace datasource.
% Internal function used by dspace().
%
%
%
%<PRE>
% This file is part of dspace-core.
%
% Copyright (C) 2020 Universi... |
c6307a0447d0abcc2c1249ec1488f09e2d912b1185f5ee42087590fe0b3c9728 | MATLAB | 2,109 | 61 | function [varargout] = isrow(varargin)
% ISROW is a drop-in replacement for the same function that was
% introduced in MATLAB R2010b.
v = version;
if v(1) ~= '7'
p = mfilename('fullpath');
p = p(1:end-6);
rmpath(p);
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
d455085ca2710ba1c20b28d4c92cebf2a02fc00b6e074c176045bc5bb32f9fc2 | MATLAB | 2,109 | 110 | clear
clc
close all
load data/taskswitch_all_rats
%%% (generated by save_taskswitch_all.m)
prevstart=5;
prevend=30;
lenprev=prevend-prevstart+1;
newend=30;
xvals=(1:lenprev+newend)-26.5;
figure; subplot(1,2,1); hold on
plot(xvals,az1d2f,'k-','LineWidth',1,'MarkerSize',30)
plot(xvals,az2d2f,'b-','LineWidth',1,'M... |
0b0ecd4cfe22831876ada15924b32d0d7ba97b8f284a95871109e0388a3b6dda | MATLAB | 2,110 | 76 | %% Multiclass Logistic Regression
% In this demo, we fit a multiclass logistic regression model by first
% performing various basis expansions of the input features. This is a
% simplification of logregMultinomKernelMinfuncDemo.
%%
% This file is from pmtk3.googlecode.com
%function logregMultinomKernelDemo()
%% Setu... |
a9c80c95bd33151e41fca300d849edfcdc0a948461ea2c5bc76c9869718e5e3e | MATLAB | 2,110 | 60 | function approxgrad = getApproxGradient(problem, x, storedb, key)
% Computes an approximation of the gradient of the cost function at x.
%
% function approxgrad = getApproxGradient(problem, x)
% function approxgrad = getApproxGradient(problem, x, storedb)
% function approxgrad = getApproxGradient(problem, x, store... |
fdfb88e50f481740d807e8ca86dda49281f984c17abf481b8774db3e724caca4 | MATLAB | 2,110 | 64 | addpath C:\code\wjn_toolbox
addpath C:\Code\wjn_toolbox-master
addpath C:\code\spm12
addpath(genpath('C:\code\leaddbs\leaddbs'))
addpath(genpath('C:\code\spm12'))
addpath(genpath('C:\code\wjn_toolbox-master'))
spm('defaults','eeg')
%%
load ECoG_Atlas_Master_Table_New.mat
% load ECoG_Atlas_Master_Table.mat
itheta = find... |
9b445e47df1f4adfa9910a13868b8852a6a6c22fca8e5ad1be000d5a7f7d734f | MATLAB | 2,111 | 58 | %% S2 Fig: To plot time course after block averaging for each condition over all subjects
clear all
clc
load incongruent_allsub_2probe_final.mat
load congruent_allsub_2probe_final.mat
load incongruent_allsub_2probe_final_hbr.mat
load congruent_allsub_2probe_final_hbr.mat
D_con = cat(3, congruent_allsub_2probe_final{:... |
01da832892f52338b5b7a53110ab250300eccb881618139aa262936aef1342a2 | MATLAB | 2,112 | 64 | clear all;
tic;
global mInst mpInst pInact qInst
global NaF NaP M CaL KCa kCain
%% MODEL CONFIG
%currents and concentrations included into neuron model if 1
% NaF NaP Kdr KM CaL KCa Cain
% 1 2 3 4 5 6 7
neu = [ 1 1 1 1 1 1 1 ];
NaF = neu(1); NaP = neu(2); M = neu(4);
CaL = neu(... |
721fbcdb07476065cdc064163f7569e536257a319c2f0b00af3e8cc5071c3c87 | MATLAB | 2,112 | 64 | clear endtime simdir starttime sumres_xyz;
ctopdir = '/home/amonreal/Documents/PhD/tools/check_grad_idea_Des';
simdir = uigetdir(ctopdir, 'pick the simulation results directory');
if simdir==0
error('need directory input');
end
if ~exist(simdir,'dir')
error('directory does not exist');
end
cd(simdir);
gaxes = ... |
7325e0d3c2892ef3f95add45c097146ab5c69baf37547df8c690e64a660a5669 | MATLAB | 2,112 | 47 | function lan_master_gui_xcor(LAN_var, mainfig)
LAN = LAN_var;
figure(mainfig);
cfg_control(1) = uicontrol('style', 'text', 'units', 'norm', 'position', [.3 .92 .44 .05],...
'string', 'channel(s) : ', 'horizontalalignment', 'right');
cfg_control(2) = uicontrol('style', 'edit', 'units', 'norm', 'position', [.75 .92... |
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