sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
cbd836dd907a84a1460dec4352df80d0af9903f5c34eea30e7bd14ff36aec1e3 | MATLAB | 1,760 | 54 | function predcond = PID_DecodeFromSpikeCellArray(tempUnits, tuningAxes)
% temp units has the field spikeCell, cell array of spike counts which has
% the shape of the neural tuning being used
tuningShape = size(tempUnits(1).spikeCell);
numDims = sum(size(tempUnits(1).spikeCell)>1);
nReps = numel(tempUnits(1).spikeCell... |
11ec8fbd59400bc4ce86db4bc43755a74349017c281dab07037a9e695f12b1d8 | MATLAB | 1,761 | 67 | function print_info(fid,filename)
fp = fopen(filename,'w');
suj=char(fid.sujet_name);
[suj,ind]=sortrows(suj);
fid=fid(ind);
[B,I,J] = unique(suj,'rows');
fprintf(fp,'Patient_name,iscompleted,numSer,MC L,MC R, BG L , BG R , OCC , OCC MM , CER , MC L E2 , MC R E2 , BG L E2 , BG R E2 \n');
for k=1:size(B,1)
ff =... |
860b10e4eb59d25cab56768378a56c95119cc88e0457cde2e1398e5913d9d46e | MATLAB | 1,761 | 41 | function [sta, time, sta_z] = getSTA(signal, events, Fs, window)
% Spike Triggered Average (STA) - alignment of signal to event time
%
% [sta, time, sta_z] = getSTA(signal, events, Fs, window)
%
% example: getSTA(fp, beh_onsets, 50, [0 5]); to extract photometry signal
% from t = 0s after movement onset to t = 5... |
f6fc69a70b75e94562490eeea7afe876234100710dedb389b352153a580c8e7b | MATLAB | 1,761 | 50 | function HR = HRCalculationFromPeaks(peaks, fs, trim, method)
%
% HR = HRCalculationFromPeaks(peaks, fs, trim, method),
% Heartrate calculator from the R-peaks impulse vector
%
% inputs:
% peaks: an impulse vector containing the R-peaks
% fs: sampling frequency in Hz
% trim: number of beats to trim from averaging
% met... |
0613a861673982a33a556d076ff47075b16d4d2df58d11d6d950200058f13a91 | MATLAB | 1,762 | 71 | function multiple_boxplot(data,xlab,Mlab,colors)
% data is a cell matrix of MxL where in each element there is a array of N
% length. M is how many data for the same group, L, how many groups.
%
% Optional:
% xlab is a cell array of strings of length L with the names of each
% group
%
% Mlab is a cell array of ... |
d90f15c4493a749c154074426f31c00d1f2914e276ba24edbb28d014c850c25d | MATLAB | 1,763 | 70 | function [S2, Q2, X_new3, qpc] = consensus_comm_wei(C)
% FUNCTION: To identify consistent communities in an ensemble
%
% OUTPUT:
% S2 is a pxn matrix of new community assignments
% Q2 is the associated modularity value
% X_new3 is the thresholded nodal association matrix
% qpc is the quality of the consensus (the low... |
084e3f34f52ac59d499ce5815be9eeb0900c3c828330a0961fb5bf8c75d4c12a | MATLAB | 1,764 | 54 | function electrode_selector()
global pointList; % Declare pointList as global
% Initialize the figure
hFig = figure('Name', '3D Surface Selector', 'NumberTitle', 'off', 'Position', [100, 100, 900, 600]);
% Initialize pointList
pointList = [];
% Create axes for 3D plot
ax3D = ... |
f3bc0038f433ea3e7e43fafa0d0d2b612bd3b8b9120919f592f0d87e7cf7b7ce | MATLAB | 1,765 | 55 | function Plot_polytrode_amplitudes(handles)
USER_DATA = get(handles.wave_clus_figure,'userdata');
par = USER_DATA{1};
classes = USER_DATA{6};
spikes = USER_DATA{2};
colors = [[0.0 0.0 1.0];[1.0 0.0 0.0];[0.0 0.5 0.0];[0.620690 0.0 0.0];[0.413793 0.0 0.758621];[0.965517 0.517241 0.034483];
[0.448276 0.379310 0.241... |
3c707884adc738fa864c2dd6a11dbd5bc5b88e35aecf00d61e28e211cf21cdf5 | MATLAB | 1,766 | 72 | function X = newfft_approx_for(st, x, om)
%function X = newfft_approx_for(st, x, om)
%|
%| (approximate) forward NUFFT
Nd = st.Nd;
Kd = st.Kd;
dims = size(x);
dd = length(Nd);
if ndims(x) < dd, fail 'input signal has too few dimensions', end
if any(dims(1:dd) ~= Nd), fail 'input signal has wrong size', end
% the u... |
14ccfdf1a934614ad4de0af06088c8f75626c14f257ff0f17a63f54a12f4a5bd | MATLAB | 1,767 | 80 | function clear_axis(app)
cla(app.ax_msna_raw)
cla(app.ax_burst_interval_his)
cla(app.ax_burst_duration_his)
cla(app.ax_burst_amplitude_his)
cla(app.ax_burst_integral_his)
cla(app.ax_burst_res)
cla(app.ax_msna_int)
cla(app.ax_1st_phase)
cla(app.ax_last_hist)
cla(app.ax_all_hist)
yyaxis(app.ax_spike_msna, 'left')
cla(ap... |
a291f1ff6d56dfd549b70e435637ea47ac62b62313bec7e89a9cf8c3524bae72 | MATLAB | 1,767 | 50 | % Copyright 2024 Eelke Spaak, Donders Institute.
% See https://github.com/Spaak/rift-phase-and-visibility for readme/license.
% Belongs with:
% Spaak, E., Bouwkamp, F. G., & de Lange, F. P. (2024). Perceptual foundation and extension
% to phase tagging for rapid invisible frequency tagging (RIFT). Imaging Neuroscie... |
8f9494aa77879074d222a0820d907cd8087ae53ae06db937bd42b450509903ea | MATLAB | 1,768 | 64 | function Heatmap
cd('C:\Users\C238\CheetahWRLV20220213\Heatmap')
for i=1:117;
file = [num2str(i) 'heatmap.mat'];
data = load(file);
R_gt4 = data.RtPositiveFiringRateArray_gt4;
L_gt4 = data.LtPositiveFiringRateArray_gt4;
R_lt3 = data.RtPositiveFiringRateArray_lt3;
L_lt3 = data.LtPosit... |
91078a1f313b6c85f0173dad784847d419e61560b8bc300eaa7bc371d9b0f54f | MATLAB | 1,768 | 64 | function y = CNN_Test(Training_Frames,Training_Classes,Testing_Frames,Testing_Classes,Frame_Half_Size)
% Display some of the training images
% clf
% for i = 1:20
% subplot(4,5,i);
% imshow(Training_Frames{i});
% end
rng('default');
hiddenSize1 = 100;
autoenc1 = trainAutoencoder(Training_Frames,hiddenSi... |
b11ccef02b551fe50391466a3cebccb405a758f58b13bd1c94a6b00bee498c52 | MATLAB | 1,770 | 65 | % test fECG extraction using an additional synthetic channel
% Reza Sameni, Copyright March 2006
% Modified June 2018
%
clear;
close all;
clc;
%load LOUETTE_07-Oct-2005_20s.txt -mat;data = LOUETTE_20s';clear LOUETTE_20s;
%load patient165_s0323lre;data = data(:,2:end)';
load FOETAL_ECG.dat; data = FOETAL_ECG(:,2:end)';... |
b5f7b775b5825a44d8e9516ef28316ad7d4dcf46a309e2b352e699111c619e68 | MATLAB | 1,770 | 51 | function [e, n] = adaptive_filter(x, delay, taps, mu)
% adaptive_filter - Adaptive Noise-Canceller/Line-Enhancer.
%
% Syntax: [e, n] = adaptive_filter(x, delay, taps, mu)
%
% Inputs:
% x: Input signal.
% delay: Delay in samples for the reference signal.
% taps: Number of filter taps.
% mu: adaptation r... |
d11f3b7cfc13ef484cfc95c2a420f3da1b2ba1e95ff4b0a7ce641ebe3a705dc4 | MATLAB | 1,770 | 47 | % A script showing how two different models can be easily compared. Here,
% we plot control ToR-ORd and the HCM variant in control condition and with
% 50% IKr block
%
% Slow pacing (0.25 Hz) is used to facilitate EADs.
%% Setting parameters
clear
% param is the default model parametrization here
param.bcl = 4000;
pa... |
260cadbf52d64ccb3ead0e63f56b095193a2e931ce946210c49272dce6f9da06 | MATLAB | 1,771 | 59 | function [fBeads]=mnl_RemoveDoubleLabelledBeads(Beads,ImDim)
sz=size(Beads,2);
n=1;
Overlap=[];
for i=1:sz
BeadOneImLimits=Beads(i).ImageLimits;
for dim=1:3
%If it is smaller than 1
if BeadOneImLimits(dim,1)<1
BeadOneImLimits(dim,1)=1;
end
%If it extends beyond the di... |
ef8e14d7f2bfe94dc756bd2531a3542f721d6247cf544fe0a5d1edc1779db513 | MATLAB | 1,771 | 44 | %Recursive Zonal Equal Area Sphere Partitioning: Properties of EQ point sets
%
% Recursive Zonal Equal Area (EQ) Sphere Partitioning Toolbox.
% Release 1.10 2005-06-26
%
%Functions by category
%=====================
%
% Energy and minimum distance
% eq_energy_dist Energy and minimum distance of an EQ point set... |
22f299b5487eeb922da7a4da68a843b21b531d7ae886c14f423d85d673206fc7 | MATLAB | 1,775 | 80 | function clear_axis(app)
cla(app.ax_msna_raw)
cla(app.ax_burst_interval_his)
cla(app.ax_burst_duration_his)
cla(app.ax_burst_amplitude_his)
cla(app.ax_burst_integral_his)
cla(app.ax_burst_res)
cla(app.ax_msna_int)
cla(app.ax_1st_phase)
cla(app.ax_last_hist)
cla(app.ax_all_hist)
yyaxis(app.ax_spike_msna, 'left')
cla(ap... |
91b4f544edce61a7dc07ef79e64ee6d35d8253da6632f0763a03e15020ad9695 | MATLAB | 1,775 | 40 | function auto_hb(app)
%auto_hb checks if hb is already detected and runs hb_det_2 on the ecg if
%not
% Detailed explanation goes here
if isempty(app.hb_res)
if ~isnan(app.settings.channel_idx.ecg)
if app.settings.interval(1,1) < app.data(app.settings.channel_idx.ecg).ts(1)
app.settings.inter... |
1e1942c1ece058d15657e3e41b46d6627dd75f5fb7b6fff3b56141cae92a15a0 | MATLAB | 1,777 | 76 | function Xk = nufft_table_adj(st, X, order, flips, om)
%function Xk = nufft_table_adj(st, X, order, flips, om)
%| adjoint of table-based nufft interpolation.
%|
%| in
%| st structure from nufft_init
%| X [M,nc] DTFT values (usually nc=1)
%| order 0|1 0th or 1st-order interpolation
%| default is 0 for backward compa... |
493370ca176cb60329da15258920bbafe81b1bb16488fb43461e1607e4f0ca76 | MATLAB | 1,777 | 82 | function main()
% Main function
%
% to see log file
% >> type('log.txt');
%
% Notations
% ---------
% - trn : train
% - val : validation
% - tst : test
% - stm : stimulus kernel
% - psk : post spike kernel
% - off : offset kernel
% - idx : indexes
% - r... |
277ee02a23963809c70318db7b49ca2a0e3cca5fa8751c86c933330cbcc6b3e6 | MATLAB | 1,779 | 42 | function nodeinfo(obj,~,t,g,data,h)
%% Response to a mouse left button click on a structure
% autocorrelatemap() and crosscorrelatemaps() depend on this function.
%
% obj: handle of clicked graphics object
% t: array of all structures objects
% g: array of all labels objects
% data: data from graph function
% h... |
3b6421126b69b65820e6ea74078914271124449701e37428faeee2ef836dcd07 | MATLAB | 1,779 | 63 | % test implementation of periodic splines
% UNDER TEST
% Reza Sameni, Copyright 2015
%
close all;
clear;
clc;
fsim = 1000; % Simulation sampling frequency (Hz)
knots = [1 3 5 7 15 25 35]; % knot points (s)
D = 4; % degree
tfirst = 0; % s
tlast = 25; % s
N = length(knots) - 1;
if(D > (N-1))
warning('D may not exc... |
1196c52a36278a2b1d7838cdf4d4a157705bf10cd61f4d2fa7f6cefc943434e3 | MATLAB | 1,782 | 54 | % Function that gets the pdf aprox from the histogram of
% Inter (Ca++) Transient Interval histogram obtained from the raster
% Input
% R: raster data: Cells x Frames
% fs: sampling frequency
% Ouput
% ISIbin: bins of ISI [seconds]
% ISIp: probaility of ISI
% Lengthbin: bins of Transient Length [seconds]
%... |
d059fdeb0d482b7ad3204411c37579f2b88a9943e1324fd5a324b587afe41abc | MATLAB | 1,782 | 52 | function [B] = make_bsplie_bases(L, knots)
% Draw, manipulate and reconstruct B-splines.
% version 1.5.0.0 (21.1 KB) by Levente Hunyadi
% link: https://www.mathworks.com/matlabcentral/fileexchange/27374-b-splines
n = 3; % order = 2
t = min(knots):max(knots); B = [];
for index = 0:numel(knots)-n... |
67d71f885ba9fcf8ee1ab791fa66c9c193a3dd6dae756eb78800c01517c48cc9 | MATLAB | 1,783 | 57 | function x = gaussian_mixture_model(params, t)
% gaussian_mixture_model - Generate synthetic Gaussian mixture model.
%
% Syntax:
% x = gaussian_mixture_model(params, t)
%
% Inputs:
% params: A vector of length 3*L, where L is the number of Gaussian kernels structured as follows:
% - alpha = params(1:L... |
2a534b0627bf093e436d511a84c4cd447b3d7b4fd8256eb4601a62a889479cee | MATLAB | 1,785 | 58 | function savefig(fname, fig, skipeps, capstr, dpi)
%savefig(fname, fig, skipeps, capstr, dpi)
if nargin < 5
dpi = 300;
end
if nargin < 4
capstr = '';
end
if nargin < 3
skipeps = false;
end
if nargin < 2
fig = gcf();
end
figure... |
4f1228ac1e5a314f6d53817137164380817518f5d24bf03eb57b7aad882a0e46 | MATLAB | 1,785 | 60 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Reduce an image applying Gaussian Pyramid.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function IResult = GPReduce(I) %#codegen
Wt = [0.0500 0.2500 0.4000 0.2500 0.0500];
dim = size(I);
newdim = ceil(dim*0.5);
IResult = zeros(newdim,class(I)); % Initialize the a... |
68aa40f11dd66300c00d88fdb2e3fc683b93856d008f5cf2b8e77215f0f3f4c9 | MATLAB | 1,785 | 54 | function [H Wp] = boxstat(d1,d2,l1,l2,alpha,str)
%BOXSTAT Box plot with statistics.
% [H WP] = BOXSTAT(D1,D2,L1,L2,ALPHA) plots box plot (H, figure handle)
% of data sets D1 and D2 using x axis labels L1 and L2. It performs
% Mann-Whitney U-test with significance level ALPHA (default is 0.05) and
% retur... |
722f527ea77e5a3a6e8242f4f0b02abcbfc3f491a6355fe341f7db131c6f7e4e | MATLAB | 1,788 | 45 | %average together the 9 session/person - output: a matrix for the scalp map
clear all;
% close all;
%-------------------------------------------------------------------------
subjects = ['A_'; 'B_';'C_';'D_';'E_';'F_';'G_';'J_';'K_'; 'L_';'M_';
'N_'; 'P_'; 'Q_'; 'R_'; 'S_'; 'T_'; 'U_'; 'V_'; 'X_'; 'Y_'; ... |
7b049e64881312b4a513e61ff9b4efdaf013e4d8ca73476ed7b0901fc86997a8 | MATLAB | 1,788 | 73 | function [binTable_SAVE] = eventwindowBins(ProcessedEventWindowData,BinParam,TrialParam,x)
ST = BinParam.type;
VN1 = {'signal' 'sigsubref' 'dFFentire_sig' 'dFFentire_sigsubref' 'Zentire_sig' 'Zentire_sigsubref' 'dFFbytrial_sig' 'dFFbytrial_sigsubref' 'Zbytrial_sig' 'Zbytrial_sigsubref'};
if contains(BinParam.process... |
fdf497ab373153f718c8f6e148e373a4b84dfeee14bf8bd8d49e0d4eba921d96 | MATLAB | 1,790 | 53 | function [A, B] = pica_matrices(x, peaks)
% pica_matrices - Calculates covariance and lagged-covariance matrices
% required for the pseudo-periodic component analysis algorithm (PiCA).
%
% Usage:
% [A, B] = pica_matrices(x, peaks)
%
% Inputs:
% x: Matrix of input signals (rows represent channels, and colu... |
01e0fb1f819e3d037848e7ace4040b7742cb117262f5ad84197b0f1202eef21f | MATLAB | 1,791 | 63 | function diam_bound = max_diam_bound_of_regions(regions)
%MAX_DIAM_BOUND_OF_REGIONS The maximum diameter bound in an array of regions
%
% diam_bound = max_diam_bound_of_regions(regions);
% Copyright 2004-2005 Paul Leopardi for the University of New South Wales.
% $Revision 1.10 $ $Date 2005-06-01 $
% Function s2e chan... |
9160f95a8eafc54222870146180bbf2ca00f56bab920ea9fbc0c52e06d5303f6 | MATLAB | 1,791 | 54 | function property = eq_regions_property(fhandle,dim,N)
%EQ_REGIONS_PROPERTY Property of regions of an EQ partition
%
%Syntax
% property = eq_regions_property(fhandle,dim,N);
%
%Description
% PROPERTY = EQ_REGIONS_PROPERTY(FHANDLE,dim,N) does the following:
% 1) uses the recursive zonal equal area sphere partitioning a... |
0cabb494d56f79d32fc58957b4d9acd4f485953f2a37d3d787ac96977cf10b67 | MATLAB | 1,794 | 61 | close all
clear
clc
% Convert all dat files in bash using this command: find ./*/ -type f -execdir wfdb2mat -r {} \;
datafilepath = '../../../../DataFiles/PTBDataset/Physionet.org/files/ptbdb/1.0.0/';
directory_list = dir([datafilepath 'patient*']);
filelist = dir(fullfile([datafilepath, '**/*lr*.mat'])); % get lis... |
0d9351ebc1755853c6c07333e4518742d8ea5b3a8b8dd4bf0655ca9359af7c8f | MATLAB | 1,796 | 61 | clear
clc
close all
% Generate a synthetic fHR sequence
x = zeros(1, 300);
x(50) = x(50) + 1000;
x(51) = x(51) - 1000;
x = cat(2, x, 15.0*ones(1, 50));
x = cat(2, x, zeros(1, 180));
x = cat(2, x, -28.0*ones(1, 30));
x = cat(2, x, zeros(1, 80));
x = cat(2, x, linspace(0, 35.0, 80));
x = cat(2, x, 35.0*ones(1, 70));
x =... |
c9733b3959973922faa2b4c75005f80afd938f33412b609e2fdee42b6caedd37 | MATLAB | 1,796 | 55 | function orientation=hbf_CheckTriangleOrientation(p,e)
%HBF_CHECKTRIANGLEORIENTATION tests, how triangle mesh is oriented
% orientation=HBF_CHECKTRIANGLEORIENTATION(mesh)
% orientation=HBF_CHECKTRIANGLEORIENTATION(points,elements)
% mesh: hbf struct for triangle mesh
% points: mesh vertices, [N x 3]
% elements:... |
bf68176f6b160781f8f3cd986aa837a3d26067140c8238c725b938d828e63220 | MATLAB | 1,797 | 67 | kDatasetFolder = '/media/sergeyd/OS/Users/sergeyd/Workspaces/SVHN/data';
load(fullfile(kDatasetFolder, 'train_32x32.mat'));
samplesNum = size(X, 4);
xSize = [size(X, 1) size(X, 2) size(X, 3)];
classesNum = 10;
%TrainX = single(X) / 255;
TrainX = X;
TrainY = single(zeros(samplesNum, classesNum));
for j = 1 : classesN... |
33018f4b540c2a429b3ced6646079a1e33c24e83a9f85645749b791187fd2f60 | MATLAB | 1,799 | 38 | function [ inputMovie ] = downsampleMovie(p,inputMovie,dimension)
%downsampleTime downsamples a movie in time, uses floor to calculate downsampled dimensions.
switch dimension
case 'time'
% downsample the movie in time by downsampling the X*Z 'image' in the Z-plane
% an... |
83ab1ee2ac65e0a0e36563d1f7d6f3bd1a3d65655d428294a107509698fd1008 | MATLAB | 1,799 | 62 | function [alphas, beta] = nufft_alpha_kb_fit(N, J, K, varargin)
%function [alphas, beta] = nufft_alpha_kb_fit(N, J, K, varargin)
%|
%| Return the alpha and beta corresponding to LS fit of L components
%| to optimized Kaiser-Bessel scaling factors (m=0, alpha=2.34J).
%| This is the best method I know currently for choo... |
d6f0111c2b07c4e98181c4376cf66ac82452370c560bb45e266bbd90c9df84ba | MATLAB | 1,799 | 60 | clear
p = params_2DAA;
saveFig = 1;
% load raw frames and std-frames
fpath = 'G:\E7_2DAA\misc\raw_data_snippets\raw_frames';
load(fpath,'raw_frames')
fpath = 'G:\E7_2DAA\results\std_frames';
load(fpath,'frames_aligned')
fpath = fullfile(p.rootDir,'results','filters.mat');
load(fpath,'filters')
%%
for sub = 11%1:12
... |
69fd408fe72878ccf13eb06d9a3a182a102821068f446759cbd281143a3cff40 | MATLAB | 1,801 | 71 | clc, clear;
addpath(genpath('D:\QcData\XxMatlabUtils'));
%% calculate OTF0
% OTFPath = 'Detection_OTF_488_NAo0p6_NAi0p505.mrc';
OTFPath = 'Detection_OTF_560_NAo0p6_NAi0p505.mrc';
% OTFPath = 'Detection_OTF_642_NAo0p6_NAi0p505.mrc';
SaveOTF2d = [OTFPath(1:end-4) '_2D.mrc'];
% parameter of 3D OTF files
nx = 512;
ny = 5... |
7231480d31817db68c4b69007cc60b559976071eef3fecc48a075c1b8049961f | MATLAB | 1,803 | 65 | %% quantify and plot
[cols,alpha] = chooseColors;
% calc mean over reps
action_full = mean(action_vals);
tone_full = mean(tone_vals);
% restrict to end period
action_end = action_full(41:70);
tone_end = tone_full(41:70);
% find timepoint with maximal drop for action start / tone end alignment
[~,max_drop_action] = m... |
b5cfb30d6d7fca15ae74a266f0a9d2f9854f3af8207d0d1b5a40d5091fe6257e | MATLAB | 1,803 | 59 | %
% Test program for phase calculation of ECG signals.
%
% Dependencies: The baseline wander and ECG filtering toolboxes of the Open Source ECG Toolbox
%
% Open Source ECG Toolbox, version 1.0, November 2006
% Released under the GNU General Public License
% Copyright (C) 2006 Reza Sameni
% Sharif University of... |
0aea16ba163b79675d57b9b17176c3f62cc53a88218778a86b3902649a95d4ef | MATLAB | 1,804 | 42 | function target_sep(h,data)
%% Draw number of targets per brain area for separate experiments
% autocorrelatemap() and crosscorrelatemaps() depend on this function.
load('structures','structures','groups');
subplot(h);
% Create plot with double y-axes
ax = plotyy(0,0,0,0);
hold(ax(1),'on');
hold(ax(2),'on');
... |
bb447165d82e0495563afd476fad0d1d09c63063d08647797c63f050d9b3821a | MATLAB | 1,806 | 59 | function print_info_ww(fid,filename)
fp = fopen(filename,'w');
suj=char(fid.sujet_name);
[suj,ind]=sortrows(suj);
fid=fid(ind);
[B,I,J] = unique(suj,'rows');
fprintf(fp,'Patient_name,iscompleted,numSer,MC L,MC R, BG L , BG R , OCC , OCC MM , CER , MC L E2 , MC R E2 , BG L E2 , BG R E2 \n');
for k=1:size(B,1)
f... |
81f2c41e1d84ace36e4d6a94d195d7e0e78125c6630b166da52ef6ae0bfbc236 | MATLAB | 1,807 | 60 | function touchparameterplot20191128
path=['C:\Users\C238\Desktop\CheetahWRLV20180729Part1'];
cd(path)
MaxA1RtArray=[];
MaxZRArray=[];
MaxA2LtArray=[];
MaxZLArray=[];
LS1=ls;
for i=1:length(LS1(:,1))
trimFolder=strtrim(LS1(i,:));
if ~strcmp(trimFolder,'.') && ~strcmp(trimFolder,'..') && length(tr... |
c72e5c97f9f4e0bf0ee81dd3011583223e5cd37a395f13f51d6101062512a9f4 | MATLAB | 1,807 | 54 | function medsubDat(nChan,memToUse)
%medsubData - Median Subtraction from dat file
%
% Usage:
% medsubDat(nChan,memToUse)
%
% Description: This function takes dat files containing the raw data from
% in vivo electrophysiology recordings and performs a median subtraction
% on the data to decrease th... |
4f34b8185de2290c3090598d19f545dfdf9971bee72f0b1af42e4f21b0f5ea28 | MATLAB | 1,809 | 40 | function summarize(obj)
%SUMMARIZE Summarize a JRCLUST session's results
summaryText = cell(5, 1);
countsPerSite = cellfun(@numel, obj.hClust.spikesBySite);
[minCount, argMin] = min(countsPerSite);
[maxCount, argMax] = max(countsPerSite);
medCount = median(countsPerSite);
summaryText{1} = ... |
d1eaa924d2fa18738386ef4600f96bdb219d37228cfdaabec2e61a690d573e6d | MATLAB | 1,809 | 39 | %% Get all CG pixel conn mats from 3*3 HC schemes
function [C_SS_meanU,C_CS_meanU,C_IS_mean,...
C_SC_meanU,C_CC_meanU,C_IC_mean,...
C_SI_mean, C_CI_mean, C_II_mean] = ...
GetCGConnMats(...
C_SS_Pixel_Us,C_CS_Pixel_Us,C_IS_Pixel_Us,...
C_SC_Pixel_Us,C_CC_Pixel_Us,C_IC_Pixel_Us,...
C_SI_Pixel_Us,C_CI_... |
0477915fa60d767f6ca54630cbc54c6d38614755f2841c31f007223f422e9031 | MATLAB | 1,813 | 49 | function NN_Probabilities = Apply_Trained_Network(Net,Im0)
% This function gets a trained neural network and a grayscale image and produces a matrix of probabilities.
% Each pixel in the output matrix contains the probability of the corresponding pixel in the grayscale image of being
% a neuron pixel or a non-neur... |
100805587d553cb507b6342ed945eb849cda958e697df83515de8b6d3da6514e | MATLAB | 1,815 | 34 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [pops_PT, pops_met] = simulate_pop_PT_met_struct(...
temps,...
model_struct,...
fixed_effects,...
psi,... % covariance of the random effects
param_transform,...
resect... |
5bfc7866b8c092d502a8eb69ac96ba79c4e3d7a5817368639b1461634e5927e0 | MATLAB | 1,816 | 36 | % Date: 17-08-2021 Programmed by: D. Bolger
% Script to call the channel rejection and ICA functions.
% Each section can be run separately by selecting the individual section
% and running "Run Section".
% For each operation (channel rejection and ICA), the functions allow you
% to manually choose the datas... |
61e9ea4d93a7f8da5b4b9173ef8345952c1521f40a9c0887813273e6be86cc20 | MATLAB | 1,816 | 44 | %Purpose: Implement Hungarian Matching Algorithm for MSHBM and k-means parcellations
%parcellations.
%Inputs: MSHBM and k-means parcellations (run directly following
%parcellation BEFORE visualization)
%Outputs: Individual parcellations with matched values (e.g., network 1 is the same across parcellation methods.
%
%... |
10d80281c93143eee41691eb9f8e4628d45d60c9b059659b24aef9ec7299f62b | MATLAB | 1,817 | 59 | function [feature_vec, feature_info] = ecg_hjorth_features(data, fs)
% [feature_vec, feature_info] = ecg_hjorth_features(data, fs)
% Extract features related to the complexity analysis of ECG signal
%
% Inputs:
% data: ECG signal as a vector (in microvolts (uv)) (1D array).
% fs: Sampling frequency (Hz)
%
% Outpu... |
4329e41ee056a67cccb2d8f50e20716c082d352ebcd93a784bc6a8d6814afa9b | MATLAB | 1,819 | 59 | function fig_alluvial_coms_9G(Rep_part,options,atlas,save)
% Alluvial pplot between flex n => flex n+1
atlas_name = options.atlas{atlas};
From_To = [1 2; 2 3];
for gI = 1:2
for ft = 1:length(From_To)
fg = figure;
% from communities rest
Par1 = Rep_part{gI}{... |
516bc04365ec61ffbc24ea48398b5ea710dccd7a5193f460688c2b768caa6238 | MATLAB | 1,819 | 48 | function img_regist = XxRegistration(img, ref, Regis_scale, maxshift, fix_y, fix_x, ShowRegisFlag)
if nargin < 7, ShowRegisFlag = 0; end
if nargin < 6, fix_x = 0; end
if nargin < 5, fix_y = 0; end
if nargin < 4, maxshift = uint16(2e15); end
if nargin < 3, Regis_scale = 3; end
maxshiftn = maxshift * Regis_scale;
% cal... |
c185d84c3a63ec5cdf519f8e9bb8a176c43830bbf58a0066d91c8bd21785739a | MATLAB | 1,819 | 40 | function plotLickAlignData(data,choice)
if isfield(data,'lick')
mouseName = data.mouse;
expDate = data.date;
nFP = data.final(1).nFPchan;
nSweeps = size(data.final,2);
left_color = [0 0.7 0];
right_color = [0 0 0];
time = data.lick.time;
avgVel = data.lick.avgVel;
velMat = ... |
eb38f1be4b8ae5ea49992f298355c6ae4ee772d280f3e2c33dc14c3d66a0dd26 | MATLAB | 1,820 | 49 | %Prerequest
%rhd file with neural activity and behavioral data (ch4)
%the first time point of ch4 is set as 10000ms, which means it needs at
%least 10s before ch4 signaling
%check session (wsq,ws,..) at the last line
disp('select the RHD file');
read_Intan_RHD2000_file
disp('select a spike csv file');
[file... |
93d3da962d8488c3d6684f40e91b49b827c07624fbd9f77de145dc3c8ef4771f | MATLAB | 1,821 | 33 | function [MI, p_MI, ratio] = compute_MI_lme(data, demographics_tbl)
MI = nan(size(data,1),1);
p_MI = nan(size(data,1),1);
for roi = 1:size(data,1)
%tic
% Extract data for this ROI
this_roi = squeeze(data(roi,:,:))';
this_roi(:,roi)=[]; %remove nans to fit GLM (diagonal in FC data)
missin... |
beb3d5e1ceb8c9493c93c73490452401947fe3f9659f9ba9f9e1151797954044 | MATLAB | 1,821 | 36 | % 测试文件夹中所有的Muli图片
clc
clear
load E:\SemanticSegmentation_Scale\CPL\GTruth_Revolve_1433.mat;
load E:\SemanticSegmentation_Scale\Results\MuliImageSS_ResNet50_SeriesClass_ResAttention\trainedNet_resnet50.mat;
InputPicBG_XPL = 'E:\B\*.png';% 背景原图的存放位置里的tif文件
InputPicPath_XPL = 'E:\B\';% 背景原图的存放位置
InputPicBG_CPL = 'E... |
7d7f161a2cbd726b310b61d53c238efe92289743c328822370f8bff87fc9b3e9 | MATLAB | 1,822 | 51 | close all
clc
clear
% Load data files
load 89_PNs_array_data.mat
% Load the four odorants used for conditioning experiments
% Hexanol, Benzaldehyde and Linalool
% For each odorant 10 trials
% Each trial is 40 s of data collection binned into 50 ms time bins - 800
% time bins per trial
% Odor presented during 1... |
815e226b5c53de700d78cd7b18e9bb76dff646e050b4f1758d07809b6847a27c | MATLAB | 1,822 | 59 | function SIs = Sp_Inf_Cont_2022_update(OccupancyMap, frs, count)
% Computes spatial information scores (SIs) based on occupancy and count data
% Input:
% OccupancyMap - Occupancy map data
% frs - Firing rates data
% count - Count data
% Output:
% SIs - Spatial information scores
... |
82d33b6ca5f929b91df90c98961a64385aadacaea49a299ceede5303ac45e340 | MATLAB | 1,824 | 56 | % A script to test the vcg_construction.m function for generating VCG with
% physical coordinates from multilead ECG data
clear; close all; clc;
datafilepath = '../../../../../DataFiles/physionet.org/files/ptbdb/1.0.0/'; fs = 1000.0;
filelist = dir(fullfile([datafilepath, '**/*.mat'])); % get list of all mat files
... |
e4463f49f6947354c34d469fc7ba9a9db413d24321a71c74078425a0af1b50e7 | MATLAB | 1,824 | 58 | % Function that fits deconvolution
% Input
% X_SPARSE
% Xest
% XDupdate
% FR
% LAMBDASS
% DRIVER
% ActiveNeurons
% Output
% LAMBDASS
% X_SPARSE
% DRIVER
function [LAMBDASS,X_SPARSE,DRIVER]=fit_sparse(X_SPARSE,Xest,XDupdate,LAMBDASS,FR,DRIVER,ActiveNeurons)
% AllStdNoises=std(XDupdate'-Xest');
for c=... |
9f1c47195e57136df6bde3c6d1fe2932152d271789caea88c1f24a0cb79ea647 | MATLAB | 1,829 | 87 | %% this script can be used to generate coarse alignment coordinates
% we do this if the automatic alignment fails because there are
% large scale rotations or translations
%% load maps
p = params_FC;
sub = 11; % thisSub = 861
for ses = 1:p.nSessions
thisSub = p.subjects(sub);
fpath = fullfile(p.rootDir,'minis... |
db0149b23c03612a013bebff0643292754f6b004c7300db8f9e986a49a4e20a0 | MATLAB | 1,830 | 60 | function phasecorelation20190522
cd('C:\Users\C238\Desktop\CheetahWRLV20180729\119\2017-6-7_20-8-33 11901-51\RtInLtFolder');
LS=ls;
RtInLtPhaseArray98=[];
RtInLtPhaseArrayCx=[];
for i=1:length(LS(:,1))
RtInLtPhaseFL=strtrim(LS(i,:));
if length(RtInLtPhaseFL)>2 && strcmp(RtInLtPhaseFL(end-7:end-4),'... |
be279bbfd12b244c2a2f1c59caab6aeb9a8584349da34e2a1f19587810aaa200 | MATLAB | 1,831 | 61 |
clear all
close all
%% Setup figure and image matrix
width_height = [516 490]; % should result in A being 400 x 400
FontSize = 300; % chosen to fit 'W' and 'Q' (largest letters)
fig1 = figure('Color', 'White', 'Position', [100 100 width_height]);
fig2 = figure('Color', 'White', 'Position', [100 100 width_height]);
ax... |
c07af3a56efbcf3104c71df1060434d951f30d904412b76bf4e92ff1acc0556b | MATLAB | 1,831 | 39 | % function [Distance_Matrix_Num,Distance_Matrix_Length] = Find_Tree_Center(Workspace1)
function [Cxy_Num,Cxy_Length] = Find_Tree_Center(Workspace1)
Vertices1 = Workspace1.Vertices;
Segments1 = Workspace1.Segments;
Mv = max(abs([Vertices1.Vertex_Index]));
Distance_Matrix_Num = zeros(Mv,Mv);
Distance_Matrix_Length... |
e0904ff91c0641448460af3f5781643b714d7cfc4b384793e0b1b47a3ad3491f | MATLAB | 1,834 | 53 | function bvs = add_dlc_data(p,bvs)
for sub = 1:p.nSubjects
sub
thisSub = p.subjects(sub);
for ses = 1:p.nSessions
% load csv file
trackPath = fullfile(p.rootDir,'results','behavior','dlc_results',['subject' num2str(thisSub) '_session' num2str(ses) '.csv']);
... |
bb5edc844047bb0dc0540edad3f220250a22f9cf524afda15415f6b2a8f315df | MATLAB | 1,835 | 43 | % GIfTI Class for MATLAB
%
% Geometry format under the Neuroimaging Informatics Technology Initiative
% (NIfTI):
% http://www.nitrc.org/projects/gifti/
% http://nifti.nimh.nih.gov/
%
% This MATLAB class is part of SPM:
% https://www.fil.ion.ucl.ac.uk/spm/
%... |
3408bd840013f34b685e51aca5d101c5b85294968a5a5051fbd7a99ffc630ce5 | MATLAB | 1,836 | 53 | function [baseline, baseline1] = baseline_sliding_window_twice(x, L1, L2, approach)
% baseline_sliding_window_twice - Baseline wander extraction from biomedical recordings using two stages of median or moving average filtering.
%
% Syntax: [baseline, baseline1] = baseline_sliding_window_twice(x, L1, L2, approach)
%... |
a048d64eec24a3c29d939d5d9a4fe7b28aad684c84b7f12255e8e980ee135e12 | MATLAB | 1,837 | 60 | function Intervalcorelation20190527
cd('C:\Users\C238\Desktop\CheetahWRLV20180729\119\2017-6-7_20-8-33 11901-51\LtIntervalFolder');
LS=ls;
LtIntervalArrayBgra=[];
LtIntervalArrayCx=[];
for i=1:length(LS(:,1))
LtIntervalFL=strtrim(LS(i,:));
if length(LtIntervalFL)>2 && strcmp(LtIntervalFL(end-7:end-... |
326e3e1b0738626dbd30b3b5bfa83d41969f9893a6f306e7a7bd316df1721568 | MATLAB | 1,838 | 50 | function y = bp_filter_complex_equiripple(x, fc, bw, factor)
% bp_filter_complex_equiripple - Bandpass filter using an equiripple FIR filter
% y = bp_filter_complex_equiripple(x, fc, bw, factor)
% Bandpass filter using an equiripple FIR filter.
%
% Inputs:
% x: vector or matrix of input data (channels x sam... |
3467abd78108f42eb6396ff4fdbc4555d0de85850b4b2a990d47114a114fa3cc | MATLAB | 1,838 | 49 | clear
clc
%% ir
x = [15.4000000000000;14.9000000000000;14.4000000000000;13.9000000000000;12.9000000000000;11.4000000000000;9.40000000000000];
cd('C:\Users\elyashivz\OneDrive - huji.ac.il\מחקר\current_analysis\DREEDS_VS_control\plot_control_vs_drreedds_per_cluster(figure5g)')
load('dreedds_IR_mean_sem.mat', 'ir_m... |
99fa0f8c8a11a7c2b417911a8194c15ba2dcb2765f6f022b0bdee0e4b0ef8e1e | MATLAB | 1,838 | 57 | function [pred, loss, loss2] = classify_ext_mat(layers, weights, test_x, test_y, ceps)
layers{1} = cnnsetup(layers{1}, 0);
layers{1} = initact(layers{1}, test_x);
layers{2} = cnnsetup(layers{2}, 0);
layers{2} = setweights(layers{2}, weights{2});
assert(size(test_x, 1) == layers{1}{1}.mapsize(1) && ...
size(... |
9c20353920d2e9061ee0bf8035d1cff56a9a8a09fb1df65a7e4bc056e6d73e2b | MATLAB | 1,838 | 83 | function clear_axis(app)
cla(app.ax_msna_raw)
cla(app.ax_burst_interval_his)
cla(app.ax_burst_duration_his)
cla(app.ax_burst_amplitude_his)
cla(app.ax_burst_integral_his)
cla(app.ax_burst_latency_his)
cla(app.ax_burst_res)
cla(app.ax_msna_int)
cla(app.ax_1st_phase)
cla(app.ax_last_hist)
cla(app.ax_all_hist)
yyaxis(app... |
677c342fd206a33d0f0b4ade962cda968f70156c503659ee8bc2a0d32d544b8a | MATLAB | 1,839 | 79 | function [T, reuse] = build_gram(ob, W, reuse, varargin)
%|function [T, reuse] = build_gram(ob, W, reuse, varargin)
%| build "gram matrix object" T = A' W A
%| in
%| ob the system matrix A
%| W typically diag(wi), having size [1 1]*size(ob,1)
%| reuse stuff returned by previous call that can be reused
%| the nex... |
1fa76bf044a0c4f93c09e0e1bccd21ee241bf8e71d706b88f7343e68093cf04f | MATLAB | 1,840 | 89 | % function RunningXcorr for ECG phase wrapping analysis
% Reza Sameni, 2015
%
close all;
clear;
clc
data = load('ECG1.txt');
fs = 1000;
% data = load('16265m.mat'); data = data.val(1,:);
% fs = 128;
data = LPFilter(data - LPFilter(data,5/fs),50/fs);
% x = data(1001:11000);
% y = data(1001:11000);
x = data(1:5000);
... |
2bf1f0716e91261185114528b0f47724c7c3f69034bff933a8b5f9a23f6fcbc4 | MATLAB | 1,840 | 84 | % Kalman filter of sleep signals sample entropy
clear all
close all
% Data Sampling Rate: 100 Hz
fs=100;
% Read sleep signals
[hdr, record] = edfread('original\SC4001E0.edf');
EEG1=record(1,30630*fs+1:31170*fs);
% [hdr, record] = edfread('original\SC4011E0.edf');
% EEG1=record(1,21540*fs+1:22200*fs);
... |
0b6e6d4ce41aaf88a710d32ed069f48f12fd0c40c10722312617a5684bb91e49 | MATLAB | 1,842 | 58 | %% GC_Analysis
% This script visualizes the GC-MS results of the blackberry leaf
% headspace.
%
% Version:
% 05-Jan-2024 (R2023a)
% Prepare
clc; clear all; close all
warning('off')
% Add toolboxes
% A MATLAB toolbox for exporting publication quality figures
% (https://github.com/altmany/export_fig)
addpath(genpath('.... |
575c1dae9d4cfae4bae6b6e7e8c9c51b0a57cd7f362b290123b6c513c20e1960 | MATLAB | 1,842 | 53 | function [numchannels,numfrequencies,numblocks,samplingrate,channels,frequencies,thedata]=openfreq(openfilename)
% openfreq: opens a Cartool frequency data file (.freq)
%
% inputs: full path and name of the file to open
%
% outputs: number of channels, number of frequencies, number of blocks and
% sampling rate as 1-D... |
94207ecbd901edcbb84c849c6ab40d58a3a242478b7096db82c23dd29e01d9ed | MATLAB | 1,843 | 62 | %% Interclsuter Coefficient (ICC) & Effective N (Neff)
% As defined in AArts et al. 2021
%
% Input
% X: numerical input data
% Y: category of input data
% Ouput
% ICC: VarB/[VarB + VarW], where:
% VarB: variance between research objects
% VarW: the sum of the variance within research objects
%
% ICC... |
7eb67122ef79905e04ed223b4be9453855705a41b291bcb16a47ec6bb9ee8eb6 | MATLAB | 1,844 | 53 | function h = fig(varargin)
% function h = fig(varargin)
%
% Copyright (c) 2011, Rafael Oliveira
% All rights reserved.
%
% Redistribution and use in source and binary forms, with or without
% modification, are permitted provided that the following conditions are
% met:
%
% * Redistributions of source code must re... |
aaf388b1b8989f08b49628f7027fa71d80ad6bb9cbd044b7ea5aac9dc2eb2ca5 | MATLAB | 1,844 | 49 | function [p1_output, f] = getFft(rawS)
%%Discrete Fourier transform.
%
% [p1_output, f] = getFft(rawS)
%
% Description: Discrete Fourier transform of multiple photometry signals,
% previously extracted from data files using extractRaw_fft.
% The function will pad each signal such that the vector to be an... |
db2f550d32d3453f5bd595de400d970252213a4ff566101d76dd233923d20260 | MATLAB | 1,844 | 71 | % Function to plot Calcium Transiens clean and raw
% in a sliding window for a simultaneous video (other script)
function showmeyoursignals(X_SPARSE,XD,Raster,SlideWin,NameOutSignals)
%%Setup
% if isempty(varargin{1})
% SlideWin=500;
% else
% SlideWin=varargin{1};
% end
disp('>>Started to Visualize:')
[Ns,Fram... |
689a3f6e83de1097e453a861fbb9cbaecef20367e329fb38512bbffcbf6397c3 | MATLAB | 1,845 | 64 | clear all, close all
%% Plot time data, with Membrane off-on-off
load Freq_res_data.mat
fig = figure(1);
fig.Color = [1 1 1];
fig.Position = [30 30 600 500];
ax = semilogx(freq_res.f, freq_res.Z, 'LineWidth', 1, 'Color', '#F5266D');
xlabel('Frequency (Hz)')
ylabel('|{\itH}_{AB}| (dB)')
ylim([-0.3 0.101])
... |
629c8a838eb2c0ea6b87bf8de47a8ed35da8296667ee68374c73e16d837cdf1d | MATLAB | 1,849 | 47 | % Script To Evaluate Which Category of Features
% Classify the Best the Measured Conditions
%% Setup
%% Load Dataset
Dirpwd=pwd;
slashesindx=find(Dirpwd=='\');
CurrentPathOK=[Dirpwd(1:slashesindx(end))]; % Finder Spiker Main Folder
% Load File
[FileName,PathName,MoreFiles] = uigetfile({'*.csv';'*.xlsx'},' Dataset file... |
a88160bda5083c8d26edba82f54585cdc06ca9b5b99763b22c8fd7eee54e7c27 | MATLAB | 1,851 | 80 | function c = get_water_content(cmet,c1,c2,c3,Wat,lesions)
%% c = get_water_content(cmet,c1,c2,c3,Wat,lesions)
%
% Function to extract % of classes from a spectroscopy voxel
%
% Added lesions (optional) to add a lesions voxel
marsbar('on');
%if ischar(c1), c1=cellstr(c1);end
%if ischar(c2), c2=cellstr(c2);end
%if i... |
04284393f42c0598ae76c56ed089575522f0266f0cd658cc7de755e894f4fb6c | MATLAB | 1,852 | 66 | %% PLOT PSTH BY STUFF like for phb
[file, path] = uigetfile('*.mat','MultiSelect','on');%When the user clicks the load psetion button, a window should open to enable the user to select a file.
cd(path)
datafile = fullfile(path, file); %save path
%shift = 0.116;
pretime = 3;
shiras_shift = 1.1;
binsize = 0.01;
%% create... |
add9e57d15a6c133c18c5f04b31baeefedfe70d255ccf7d80cff9ffab45b2c38 | MATLAB | 1,852 | 66 | function out = fatrix2_subsref_brace(ob, iblock)
%function out = fatrix2_subsref_brace(ob, iblock)
%|
%| Manage subscript references of the form ob{iblock}
%| This will called from ../subsref with ob
%|
%| User can use subset_starts to select blocks in other orders
%| in which case this "iblock" is really "istart"
%|
... |
c3cc8f93f8de6d012b40e5aa39c469b3a78c367ac4c100ad0610e521f1000251 | MATLAB | 1,854 | 56 | function [] = amodel(session, channel, unit)
% Approximates the fitted S-kernels with Gaussian functions
%
% Parameters
% ----------
% - session: scalar
% Session number with format: yymmdd
% - channel: scalar
% Channel number
fprintf('===== A-Model =====\n\n');
main_timer = tic();
info = get_info();... |
e550045ae4d3d89cecd37bd97599fcc7584d5e94d292a16188e7579604db43fa | MATLAB | 1,855 | 94 | function sn = nufft_scale(Nd, Kd, alpha, beta, Nmid)
%function sn = nufft_scale(Nd, Kd, alpha, beta, Nmid)
%|
%| Compute scaling factors for NUFFT
%|
%| in
%| Nd,Kd
%| alpha {d}
%| beta {d}
%|
%| option
%| Nmid [d] midpoint: floor(Nd/2) or default (Nd-1)/2
%|
%| out
%| sn [[Nd]] scaling factors
%|
%| Copyright 2004-... |
16ea12f96046e78a289dd55398fbb1f684fe49fe52efa99c4f16284a985847d3 | MATLAB | 1,856 | 52 | function [tunedStart, tunedFinish, nBouts, tunedDuration, ...
tuneFlagWeak, tuneFlagMed, tuneFlagStrong] = ...
getTuningTimeInfo_paper(R2Vector, R2pVector)
%% get tuning start and finish times + logical tuning flag
binSize = 0.01;
windowLength = 0.2;
binVector = -0.2:binSize:1.8;
binVector = round(binVector... |
e929c43feecec714c30afbf414aec273f3dcdb982d09a48d5a6e1fd0f3d97ae0 | MATLAB | 1,857 | 41 | function ratios = relative_spectral_power(x, fs, freqs, Q_factor)
% relative_spectral_power - Calculation of relative signal power in narrow frequency bands
%
% Syntax: ratios = relative_spectral_power(x, fs, freqs, Q_factor)
%
% Inputs:
% x: multi-channel input signal (channels x samples)
% fs: sampling frequency... |
7a9e09ab6423e1750d9a58d6f3db734b66bf4d8b0acf004e2b66373fb25e1236 | MATLAB | 1,858 | 70 |
function [ channel_observation , channel_hidden_states ] = generate_chmm_time_series( T , channel_num_states , channel_dim_observ , chmm_gmm_para , transition_chmm , pi_0_chmm )
C = length(pi_0_chmm);
weight_state_column = cumprod( channel_num_states(C:-1:2) );
weight_state_column = [1;weight_state_column(:)];
wei... |
f4756aae283bd62ad92f8db01e546b47783b7dd1baa3b37abb46640ad24c76bf | MATLAB | 1,859 | 48 | function check_input(F,y,X,opts)
% Check that things are in order.
% ------------------------------------------------------------------------
% Check F, y and X
num_obs = size(y,1);
num_features = size(F,2);
assert(iscell(F), 'F should be a cell')
assert(ismatrix(y),'y should be a matrix')
assert(num_obs > 1,'y shou... |
b7499593c7950f04966ab70478036875a88cf5bf3a0e736549e2ea8c61b10f61 | MATLAB | 1,860 | 57 | function Generate_Orders_Result_Demo()
% Run Example: Apply_To_AllFiles_SubDirs('tif');
Dir1 = uigetdir; % Let the user choose a directory.
Files_List = dir([Dir1,filesep,'**',filesep,'*.','mat']); % List all .mat files under this directory (including subdirectories).
Save_Dir = 'D:\Dropbox (Technion Dropbox)\O... |
c89f5db7089fd3db13ca3f41310e47b973d4e41f85bf9c07b1b4ad4e365fb94a | MATLAB | 1,863 | 54 | function samplesOut = sgFilter(samplesIn, nDiffOrder)
%SGFILTER Savitzky-Golay filter
% works for a vector, matrix and tensor
fInvert_filter = 0;
useGPU = isa(samplesIn, 'gpuArray');
n1 = size(samplesIn,1);
if n1 == 1
n1 = size(samplesIn,2);
end
if nDiffOrder == 0
sampl... |
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