sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
ad08367610081f20047e5f7fd2c619b841494f45baaae7c8774e2d05f68b5b8a | MATLAB | 3,005 | 128 | clear all;
close all; clc;
matrixBeforeHex = ([0 1 0 1 1 1 0 0 0 0
0 0 0 1 1 0 0 0 1 1
1 0 1 0 1 1 0 0 0 0
1 1 1 1 0 1 0 1 1 1
1 0 0 0 0 0 0 0 0 0
1 0 0 1 0 1 0 0 1 0
0 0 0 1 0 0 1 0 1 0
1 1 1 1 1 1 1 1 1 1
1 0 0 1 0 1 1 0 1 0
1 1 0 0 1 1 1 0 0 0
]);
matrixAfterHex = ([1 0 1 1 1 1 0 0 1 0
1 0 0 1 0 0 ... |
bcedd9642d3948280aed1838b6cf32acea8a1c0b8e79d9b849edddbf82bf7b20 | MATLAB | 3,006 | 115 | function multiple_boxplot_bee_bar(data,xlab,Mlab,colors)
% data is a cell matrix of LxM 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 ... |
3e9238a785e6d4f862d844e81a05f2b8f2c80a824a64462f52cf99663c97f5fd | MATLAB | 3,010 | 119 | function pred=sopls_pred(varargin)
% sopls_pred Applies a sequential and orthogonalized PLS model to new data
% The function sopls_pred applies a sequential and orthogonalized PLS (SO-PLS)
% multi-block regression model (calculated by sopls_mod or sopls_cv) on
% a new set of data (for validation on a test ... |
18c7bda588931549ae782a5534a314538b82e808e3d5ee45c1f6380883e1ce28 | MATLAB | 3,011 | 95 | function corrected_p = bonferroni_correction(p_values)
% Applies the Bonferroni correction to a vector of p-values.
%
% This function adjusts a set of p-values to control the family-wise error rate
% using the Bonferroni correction method. It is commonly used in multiple hypothesis
% testing to reduce the risk of Typ... |
475625a29e9ad6774907ead0a79677b03958962f3be2dcc467ea4694b04d971e | MATLAB | 3,011 | 95 | %%% this script provides benchmarks for how many cycles it takes to produce
%%% a given patch in a time-frequency plot
clear
clc
close all
Parameters = analysisParameters();
PlotProps = Parameters.PlotProps.Manuscript;
SignalCycles = 1:5;
Frequencies = [1:20];
Frequencies = reshape(Frequencies, 4, []);
MaxFrequen... |
b0f7b958a1f98c1044ec61b5b2489fe185a206e37e46c3425baebe29320d0977 | MATLAB | 3,011 | 103 | function [P, Q, R, S, T] = ecgWavesSoI_RRT(ecg, Rpeak, fs, RRf)
%
% 'RR interval & time based' version.
% This function approximately finds the peaks and borders of the Q and T waves
% in the input ECG signal using RR intervals and time-based information.
%
% Inputs:
% ecg: Single channel ECG signal
% Rpea... |
cda9e6174bfce53df90f159e1f3cce2865bed254c2f7ba33459b03012e7148a1 | MATLAB | 3,011 | 87 | function varargout = AboutDataHigh(varargin)
% AboutDataHigh
%
% Tells information about DataHigh.
%
% Copyright Benjamin Cowley, Matthew Kaufman, Zachary Butler, Byron Yu, 2012-2013
% ---GNU General Public License Copyright---
% This file is part of DataHigh.
%
% DataHigh is free software: you can redistribute it ... |
824ecba42d3b2ca265ee285a986b9f2ea5c919d5fcadf9ac16395897cd716249 | MATLAB | 3,015 | 76 | function MergeNlxFiles20180118
%tetrodeÌ{Ƶ½¢tH_¼ð·×ÄLü
%uÅÌtH_+}EX¼{joinvÆ¢¤tH_ªì¬³êeg[h²Æɳê½nttt@CÆ
%Event.matªÛ¶³êéB
clear all;
CoreFolder='C:\Users\B133_2\Desktop\CheetahData';
% Folder{1}=[CoreFolder '\' '2018-4-13_18-45-0 500... |
eda407ba89c45f33904e89533afc8f6d0154a9c949b0a49a478c749dd9448449 | MATLAB | 3,016 | 76 | function MergeNlxFiles20190212
%tetrodeÌ{Ƶ½¢tH_¼ð·×ÄLü
%uÅÌtH_+}EX¼{joinvÆ¢¤tH_ªì¬³êeg[h²Æɳê½nttt@CÆ
%Event.matªÛ¶³êéB
clear all;
CoreFolder='C:\Users\C238\Desktop\CheetahData';
% Folder{1}=[CoreFolder '\' '2018-4-13_18-45-0 500... |
b65959d676f627a72ca76a3cae874c945b8e4d434ac4d5fb924dc9e4cec2cae9 | MATLAB | 3,017 | 113 | function CV=plsldacv(X,y,A,K,method,weight,OPT,order)
%+++ K-fold Cross-validation for PLS-LDA
%+++ Input: X: m x n (Sample matrix)
% y: m x 1 (measured property)
%%
% A: The maximal number of LVs for cross-validation
% K: fold. when K = m, it is leave-one-out CV
% metho... |
07f4b4c992d68201b5b360abd9111cb44bb5bd80fa10d935717648143e5d54d5 | MATLAB | 3,018 | 72 | function centroid = train_kmeans(features,labels,nBoot,ratio)
% train_kmeans unsupervised clustering using the k-means algorithm. Robust
% centroids are obtained by bootstrapping the data such that the proportion
% of seizure free and non-seizure free patients are equal to the variable
% 'ratio'.
%
% centroid ... |
40b9a5b0d7c69bd51bdb657526388f130b964ca1145e37a5c254156b705b4bb8 | MATLAB | 3,020 | 108 | %%
[cols,alpha] = chooseColors;
this_cols{1} = 'k';
this_cols{2} = cols(2,:);
this_cols{3} = [.7 .7 .7];
%% plot accs over time for using all 5 dimensions
figure('Position',[100 100 300 300])
hold on
for config = 1:3
dc_means = cellfun(@(x) squeeze(mean(x,1))',td_accs,'UniformOutput',false);
rep_mean = mea... |
464f2840c7379bc0d644ac67f13b93157b15de79b5bffb184a8457e68eaeb522 | MATLAB | 3,021 | 112 | function F=randomfrog_pls(X,Y,A,method,N,Q,criterion)
%+++ Random Frog for variable selection for high dimensional data.
%+++ Input: X: m x n (Sample matrix)
% Y: m x 1 (measured property)
% A: The maximal number of latent variables for
% cross-validation
% method: dat... |
cf92aaaeffa0cbc0c30ea4ae15d151374f1552119f546c7340811bc515708665 | MATLAB | 3,021 | 73 | function varargout = ballistic_subj_gui(varargin)
% BALLISTIC_SUBJ_GUI MATLAB code for ballistic_subj_gui.fig
% BALLISTIC_SUBJ_GUI, by itself, creates a new BALLISTIC_SUBJ_GUI or raises the existing
% singleton*.
%
% H = BALLISTIC_SUBJ_GUI returns the handle to a new BALLISTIC_SUBJ_GUI or the handle to
%... |
8b50da76bb3d27ea329b1acdfc16029acbe10519680ebfa0b27d5298b1a8f080 | MATLAB | 3,024 | 101 | function RM = spmup_auto_reorient(P,which_image)
% FORMAT: reorientation_matrix = spmup_auto_reorient(p,which_image)
%
% IMPUT: p is a cell string of images to process (see spm_select)
% which_image is a integer for wich image to obtain RM
%
% OUTPUT: RM is the reorientation matrix obtain from affine reg to the... |
db9a08bfc59fc9952cb94ba11610b485fb2be57394daaa32a9c65e2a3644c7f3 | MATLAB | 3,024 | 69 | % ConnectionMat_Fix.m is a function generating connetivity matrices
% Input:
% N_Post,NnPost,Size_Post: number, index projection, and grid size of
% presynaptic neurons
% N_Pre,NnPre,Size_Pre: Same for postsynaptic neurons
% Peak_EE: Peak connectivity prob... |
0e9eef79aadbb94aa780683004ae25c123bd78c654f47ba65d4cddeea559b8e6 | MATLAB | 3,027 | 91 | function [peakLocs, peaks, siteThresh] = detectPeaksSite(samplesIn, siteThresh, hCfg)
%DETECTPEAKSSITE Detect peaks on a given site, computing threshold if necessary
% determine threshold if it has still escaped us
MAX_SAMPLE_QQ = 300000;
if ~isempty(hCfg.evtManualThreshSamp)
siteThresh = hCfg.... |
5321e236a4310c43c0d86d3766f0b233f0e756bc70b761135809a166e930aaff | MATLAB | 3,027 | 116 | clear; clc; close all; rng('default')
assert(~isempty(strfind(pwd, 'embanded/examples/matlab')), 'Please change folder to the examples directory')
run(strrep(pwd,'examples/matlab','setup.m'))
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Simulate data.
% Generate some training data
num... |
7e5da4d356b527c197b8b5c82b3278627c3d8aa1e7bbb3c5d055b4522fe394a6 | MATLAB | 3,027 | 80 | function [x,info] = get_grn_data(NETWORK,path_dream5)
% GET_GRN_DATA Load gene regulatory network of the DREAM5 challenge.
% [X,INFO] = GET_GRN_DATA(NETWORK,PATH_DREAM5) for path PATH_DREAM5 and index NETWORK returns
% gene expression levels X (#genes-by-#samples) and network information
%
% INFO.tfidx i... |
141b26a529448f093110ea28075eecf95537d567ea0afce0d8ef7b8277d3d43a | MATLAB | 3,028 | 75 | function MergeNlxFiles20180118debug
%tetrodeÌ{Ƶ½¢tH_¼ð·×ÄLü
%uÅÌtH_+}EX¼{joinvÆ¢¤tH_ªì¬³êeg[h²Æɳê½nttt@CÆ
%Event.matªÛ¶³êéB
clear all;
CoreFolder='C:\Users\B133_2\Desktop\CheetahData';
% Folder{1}=[CoreFolder '\' '2018-4-13_18-45-... |
a933f12270028c6d3ccd9516b9e9d80708a611f05033be99419677e717ce26b9 | MATLAB | 3,030 | 81 | function x = ACR(p,n,alpha);
%ACR Upper percentiles critical value for test of single multivariate normal outlier.
% From the method given by Wilks (1963) and approaching to a F distribution
% function by the Yang and Lee (1987) formulation, we provide an m-file to
% get the critical value of the maximun squared Mahala... |
6f07177b1f3e485f14fe80b0dcd7408319761d352f676a5933bb30e5a2786776 | MATLAB | 3,031 | 97 | function updateSelect(obj, iClusters, force)
%UPDATESELECT Select a (pair of) cluster(s) across all views
iClusters = min(max(iClusters, 1), obj.hClust.nClusters);
if numel(iClusters) > 2
iClusters = iClusters(1:2);
elseif isempty(iClusters)
iClusters = 1;
end
if numel(iClusters)... |
2373c5146bd2258bf7c845f304aa5029600d377f5f9c616aca577cfde13a9408 | MATLAB | 3,032 | 62 | % Get Data from Several Analysis Variables
function [Rasters,LENGHTRASTER,NGroups,SIG_FRAMES,LABELS,THR,...
ExperimentRaster,signif_frames,labels_frames,CummFrames,CummGroups,...
TotalNG]=get_ensemble_intel(NN_data_Read)
NC=numel(NN_data_Read);
% DATA PER CONDITION
Rasters={}; % ... |
668c4bfb82cf16f49ad045a5bb3f60e39a66a9c819aad593f73e97be030db2db | MATLAB | 3,035 | 90 | function [OptF1mean,OptThresh,OptF1median,OptThreshMedian]=mnl_OptimumEuThreshViaF1Star_MagWeighted(efPxTrace)
EuThreshVals=0.05:0.01:1;
szTh=size(EuThreshVals,2);
dim=efPxTrace(1).dim;
n=1;
for i=1:szTh
EuThresh=EuThreshVals(i);
[FinalClusters,FinalClusterIDs,~,~,~]=mnl_EuclideanCrawler_Mag_Weighted_v3(efPxTra... |
5f7d27cff5de78f2fa2a570d72614253bcb622178d12f11380a4982ce7961582 | MATLAB | 3,036 | 109 | function [D,P] = all_shortest_paths(A,varargin)
% all_shortest_paths Compute the weighted all pairs shortest path problem.
%
% D = all_shortest_paths(A) returns the distance matrix D for all vertices
% where D(i,j) indicates the shortest path distance between vertex i and
% vertex j.
%
% ... = all_shortest_paths(A,u... |
939f09b08d81e9e112473262b271537dab2a954222df982af776ca727571c498 | MATLAB | 3,036 | 68 | %% Figure 5A
dt = 5e-5;
load(fullfile(pwd, 'datasets', 'highcond_multibranch_decode.mat'))
idx_cell = 12;
idx_trials = [1, 2];
idx_cond = 3;
t = -500*dt:dt:dt*(size(data(data_decode(idx_cell).idx(idx_trials(1))).EPSP_highcond{idx_cond}, 1)-1-500);
for i = 1:length(idx_trials)
figure
subplot(131)
for j ... |
f7f73e8e3903a8731efe8a850948945f7ff2b582e9eae1adeaf10bd519d28a51 | MATLAB | 3,038 | 57 | function Project = Workspace_To_Project(Workspace)
Project = struct('Segments',{},'Vertices',{},'Points',{},'Neuron_Axes',{},'Parameters',{},'Info',{});
for w=1:numel(Workspace) % For each Project.
Project(w).Segments = Workspace(w).Workspace.Segments;
Project(w).Vertices = Workspace(w).Workspace.Vertices;
... |
37cce725e6bd325bc5234c2ee0cd4c6853995eeed16d66be4ee1d5a92ad13ce3 | MATLAB | 3,040 | 100 | function [P, Q, R, S, T] = ecgWavesSoI_cRR(ecg, Rpeak, RRf)
%
% Approximates peaks and borders of the P, Q, R, S, and T waves in the input ECG.
%
% Usage:
% [P, Q, R, S, T] = ecgWavesSoI_cRR(ecg, Rpeak, RRf)
%
% Inputs:
% ecg: Single-channel ECG signal
% Rpeak: R-peak positions (if RRf is false) or R-pea... |
80668e877296eccb562f803a0de2b68fd88d32379ade01dca4f49f8b770d78e9 | MATLAB | 3,041 | 99 | function [mn, vr_mn, varargout] = robust_weighted_average(x)
% robust_weighted_average - Robust weighted averaging
%
% Usage:
% [mn, vr_mn, md, vr_md, best_beat, vr_best_beat, best_beat_index] = robust_weighted_average(x)
%
% Inputs:
% x: An (N x T) matrix containing N ensembles of a noisy event-related sign... |
519a2d85e12858180bab4ac21600123eebdad3e8f3bdf445e6843b4bf6ab1519 | MATLAB | 3,042 | 89 | %% Import data from text file
% Script for importing data from the following text file:
%
% filename: Q:\OneDrive - The University of Colorado Denver\From Dropbox\STED\STED Data\230822\45nmYG_DyMINvsSTED\BarGraphResults\ROI1.csv
%
% Auto-generated by MATLAB on 18-Oct-2023 16:33:09
%% Set up the Import Options and i... |
6d5c47ed17d27943387f64ef5e6f6b844c670333154b1d70835a1e664ab38e74 | MATLAB | 3,042 | 94 | function h=mnl_boxplot2(data,ColumnNames,YvalueLabel,IncSD,IncIP)
% Marcus' version of boxplot where outliers are not recorded, and raw data
% points are plotted too
%
% Red line is the mean, red whiskers are the standard deviation, blue line
% is the median, blue box is the interquartile range, and the blue whiskers
%... |
a7d9c9f59a02b43344fc1c833e46ce6706e3aa0f1d57571d1642801dc1fe60e9 | MATLAB | 3,042 | 87 | % Matlab structure to Python dictionary
% all_beh in python
% Index(['block_type', 'cluster_name', 'correct', 'date', 'first_lick',
% 'identified', 'last_lick', 'licks_left', 'licks_right', 'mouse_name',
% 'response', 'session_type', 'spike_times', 'spike_times(stim_aligned)',
% 'stim_durati... |
798d330ae8445da2d910165013baa901aaf392c2582388e76e9a334c31edac22 | MATLAB | 3,044 | 72 | function [y, B, conv] = easi_source_separation(x, nsou, lambda, nlintype)
% easi_source_separation - An adaptive blind source separation algorithm using the EASI (equivariant adaptive separation by independence) algorithm
%
% Syntax: [y, B, conv] = easi_source_separation(x, nsou, lambda, nlintype)
%
% Inputs:
% x: in... |
7f8eca4756aa5c73341e73ac1543a94d04398b20d8aa56550e3f6c000db28449 | MATLAB | 3,045 | 76 | function data = alignData2Mov(data,tBefore,tAfter)
%alignData2Mov - Align photometry and velocity data to movement onset and
%offset
%
% Usage:
% data = alignData2Mov(data,tBefore,tAfter)
%
% Description: This function aligns data to movement bouts
% within a specified window.
%
%
% Input:
% ... |
6efb80e7d594d48abb7dc10ff23e024d16f3cd75719dd7ea626bbddea5e860f7 | MATLAB | 3,047 | 83 | % This program is intended to extract
%
%
% 1. extract time series of BOLD signals from session3 and 4
% 2. contract between sessions
%
%
% by Hiro Taiyo Hamada, Araya Inc.
addpath(fullfile(pwd, '/programs'))
%% contrast between anesthesia 1st and 2nd
% Anesthesia 1st
datapath1 = fullfile(pwd, '/data/session3');
li... |
d401fa6cb2011762716d69466dffca9d66756ce896f65cd5b78c23929c956e3e | MATLAB | 3,050 | 121 | function multiple_boxplot_mmp(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 stri... |
67e98480672a6355101dfff122aaf06d0fb28cfdf680307c68a1612a83ee74bd | MATLAB | 3,051 | 94 | function data_subBG = XxSubBackground(data, thresh, radius, tmin, tmax)
show = 0;
n_perSIM = 9;
ndirs = 3;
nphases = 3;
[height,width,nframe] = size(data);
num_SIM = size(data, 3) / n_perSIM;
data_subBG = zeros(height,width,nframe);
for j = 1:num_SIM
d = double(data(:,:,(j-1)*n_perSIM+1:j*n_perSIM));
% calculat... |
4fd661a9ce528ed74138e6b3ea6b7811834e4d26b7eff27db2e0c1ee853bdac7 | MATLAB | 3,052 | 99 | % test baseline wander removal by curve fitting
% Status: UNDER TEST
% Reza Sameni, 2005
clear;
close all;
% load LTE07102005_40s.txt -mat;data = LOUETTE_40s';clear LOUETTE_40s
% load fortict_20-Jan-2006.datfortict_20-Jan-2006.dat_acq.mat;
% load fortict5_20-Jan-2006.datfortict5_20-Jan-2006.dat_acq.mat;data = data';
%... |
1985e8b57677b27b3dea6bae11cda1a7fc134230ed4c8b65b2b1b713c9c04398 | MATLAB | 3,054 | 88 | function cbars = createBrainColorbar(colormapSG, ticksSG, varargin)
% createBrainColorbar Creates simple colorbars for brain visualizations
% Parse inputs
p = inputParser;
addRequired(p, 'colormapSG');
addRequired(p, 'ticksSG');
addParameter(p, 'FontSize', 8);
addParameter(p, 'BarWidth', 0.015);
parse(p, colormapSG, ti... |
c2c91ed79b49b1971b9b6dda0d46fd4a3768d9f27fb468d562fcce5c323b614e | MATLAB | 3,054 | 92 | function [spikeMatrix, peak_idxs, peakTimes_ms, classes, peak_vals, dip1, dip2 ]=comBIN_wave_clus(cluster,data,sr)
npointsbeforepeak=20;
npointsafterpeak=20;
peakTimes_ms=cluster.cluster_class(:,2)';
peak_idxs=uint32(cluster.cluster_class(:,2)'*sr/1000);
clear index clear spikes
classes = (cluster.cluster_class(:,1... |
eb6936ac2ba627ac9180bbdc0da5138b20548025945fff12132c53d64c66055e | MATLAB | 3,055 | 106 | % A test code for Signal quality indexes based on different methods
% The channel selection method tries to rank the components according to
% their similarity to the fetal mixtures.
%
% Fahimeh Jamshidian Tehrani,
% jamshidian.t@cse.shirazu.ac.ir,
% fahimeh.jt@gmail.com
% February 2020
%
% The Open Source Electrophysi... |
70a81570fccd190a5f49c1d335fd59f26f778ae73e144d62bd78436d7e13c9b4 | MATLAB | 3,056 | 124 | function b_model = RaguEEG_Mod_AAHC(eeg,n_mod,ProgBar, IgnorePolarity, max_n,repidx)
% Copyright 2009-2011 Thomas Koenig
% distributed under the terms of the GNU AFFERO General Public License
if nargin < 6
repidx = [];
end
if nargin < 3
ProgBar = true;
end
if nargin < 4
IgnorePolarity = false;
end
if (... |
1b3aa8aecea251b71eff23842e2e4bd70a60f2fef9f2f90dc439d5aabaf8d0db | MATLAB | 3,061 | 123 | disp('This code is just a front-end to check that the real implementation');
disp('of JADE does run as seen on TV.');
disp(' ');
disp('This is indeed just a toy problem... Please run JADE on your real data.');
disp(' ');
disp(' ');
disp('The demo will display a figure with 3 rows: ');
disp('o First row: three `source s... |
e183ba7882f6e145c5cd2f814e65007b9283aa8fe56c203c1f236fad237f7427 | MATLAB | 3,061 | 78 | %% HPC for large amount of IC tests
% RadiusInd: 10^-RadiusInd when using
% SampleSize: specify an integer. Fix
% SaveID Just for saving tag
function [] = HPCICTest(RadiusInd,SampleSize,SaveID)
CurrentFolder = pwd
FigurePath = [CurrentFolder '/Figures/Demo022722/'];
addpath(CurrentFolder)
addpath([CurrentFolder '/Utils... |
93efffb7e097e96f8ee0c768888afa25b09617024e5c2cee0494cfaa19b13d43 | MATLAB | 3,062 | 84 | clear
p = params_2DAA;
fpath = fullfile(p.processed_data_dir,'allData.mat');
load(fpath,'evs','tis','bvs','traces')
[cols,alpha] = chooseColors;
%% run DR and decoding procedure for different trial samples
fpath = fullfile(p.data_dir,'eval_avoid_decoders_per_ses');
saveData = 1;
saveFigs = 1;
n_rep = 80;
n_rep_eval ... |
f733d82c6ad56f96166dbe14caf4da966edc970bbb18c040fb62e45a003b13c9 | MATLAB | 3,064 | 68 | %% Analyze Data
clear all;
[FPfiles,FPpath] = uigetfile('*.mat','Select FP Files to Analyze','MultiSelect','On');
if isempty(FPfiles)
fprintf('No Files Selected');
else
if (~iscell(FPfiles))
FPfiles = {FPfiles};
end
nFiles = length(FPfiles);
[analysisOpt,ind] = listdlg('PromptStr... |
2eab5405e675db7bad5e2e585e8042c33a950d9e49df654d98cda16ca5f03164 | MATLAB | 3,069 | 116 | function [bad_subject] = find_group_outliers(SPM_file)
% routine that checks for outliers among subjects
% using a modified boxplot rule, each voxel is analyzed
% looking for outlier subjects and the proportion of outlying
% voxels is obtained per subjet allowing to decide, using again
% a modified box-plot rule, if a... |
a201b30d9f54d1c2844d2c26efc3da9229f739b1359c15f898ef95fe73bd0691 | MATLAB | 3,073 | 79 | %%% Train the model
addpath('~/matconvnet/matlab');
vl_setupnn
rng('default')
sigma_min_array=40;%[ 0, 10, 20, 40, 60, 80,100,150,300, 500];
sigma_max_array=60;%[10, 20, 40, 60, 80,100,150,300,500,1000];
for i=1:length(sigma_min_array)
gpuDevice();
sigma_min = sigma_min_array(i);
sigma_max ... |
9807c44f39bcc79b19e712aa3ee4c5001bcb78d5d41a798ae437f76af4c7e771 | MATLAB | 3,075 | 65 | function [index, rank, yy] = sqi_power_level_crossing(x, w, th, varargin)
% Channel selection based on the number of level crossings of the signal power envelope
%
% Usage:
% [index, rank, yy] = sqi_power_level_crossing(x, w, th, ranking_mode, normalize)
%
% Inputs:
% x: ECG signal (rows represent channels, ... |
cbd80909dbb973b138800f1db3f8e13a449577bfabe9f59cb5fd30aea7263b04 | MATLAB | 3,077 | 62 | function [fig_TM,PTTMHistoCell MedianPTTM Max]=TouchAlignByTM(PegTouchCell,TurnMarkerTime,yhight)
%TouchAlignByPeg(PegTouchCell,pegTimeArray2D,100,30)
%Called by PegTouch,Detach
%Touch aligned By Pegs
global PTpegHistoCell OneTurnTime ShowFig
PegTouchByTM1=[];PegTouchByTM2=[];PegTouchByTM3=[];PegTouchByTM4=[];P... |
8742061c766bed97eae90571424e89807eb927e43b2f806f9ae28f48d79d9fa0 | MATLAB | 3,080 | 78 | %% Setup
% Plot EXPERIMENT_ID.mat file from FinderSpiker
% It states the anlaysis status and make the following plot:
% - Raster of Raw Activity
% - Sorted Raster by Activity
% - Sorted Raster by Changed Groups between conditions
% - Neuronal Ensembles Raster
% - Sorted Neuronal Ensembles Raster
%
% Functions:
%... |
111755dc7dcc58d7dd1a902e2da71d7e7a7b74bcfa48872195301ccbc22a500b | MATLAB | 3,081 | 101 |
%% clear
clear
% close all
clc
%% load ecg
load ecgptb.mat
%% prepare data
ecg=ecg(10*fs+1:20*fs,:); % 10 sec multichannel ecg
L=size(ecg,1); % ecg length
tst=(1:L)/fs; % time stamp
w1=.75; % window length of the first median filter used in base line removing
w2=.9; % window length of the second media... |
0fceeabea414cb385962d7f16f2b0f23bb40bc636780a2d6d72350fd80473a0d | MATLAB | 3,082 | 90 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%% This script is used to test whether the functions in this %%%%%%%%%%
%%%%%%%%%% package can run smoothly. %%%%%%%%%%
%%%%%%%%%% Suggest: every time you make some modification of codes ... |
ebd8cf4a6fb343198261c8f24afecf01d1af52ecf4312ec8e609ab58aac4bfd5 | MATLAB | 3,084 | 109 | function wc = get_coresponding_water_content(rawname)
if findstr(rawname,'PROTO_SPECTRO_DYST')
anat_dir='/home/romain/data/spectro/PROTO_SPECTRO_DYST/anat';
roi_dir='/home/romain/data/spectro/PROTO_SPECTRO_DYST/fid_pos_nii';
preproc_subdir='vbm5';
anatdir_wc = '*t1mpr*';
%elseif findstr(rawname,'/PROTO_U731_C... |
2e28d2056a14b2b707ce518e217c229eefb6be63ca9eb70a16b7e6679b3e91e1 | MATLAB | 3,089 | 79 | clear
close all
clc
fname = 'sample';
load(fname, 'sampling_rate', 'channel_names');
% Load the data from the CSV file to have a similar quantization effect
sample_raw = importdata('sample_raw.csv');
signal = sample_raw.data';
% QUANTIZE THE DATA AND CONVERT IT TO WFDB FORMAT USING mat2wfdb
% Set parameters for da... |
d83a30cba3367501c2b2f3ef28fb00609570f8bfbae51f755970d77ecc0923b4 | MATLAB | 3,089 | 94 | %% Function to order Neurons by Condition (influented by Plot_Clusterin_from_NN.m)
% Input
% NumberofVideos: Number of Videos for Each Condition (vector)
% Raster: Raster per viedo per condtion (cell)
% Output
% NewIndex: Sorted Neurons by Condition
% Raster_Conditon: Raster p... |
672f4684a0e7acef34a50ded3c5313b7dcebade3425f89c66992ca9428574efd | MATLAB | 3,092 | 126 | %compute T2 from c result structure
metab_list = { 'Glu','Ins','sIns','sNAA','mNAA','GSHd','sNAA_NAAG','Glu_Gln','PCho_GPC','CrCH3_PCrCH3','CrCH2_PCrCH2','sNAA_mNAA'};
metab_list = { 'Ins','NAA_NAAG','Glu_Gln','PCho_GPC','Cr_CH3_PCrCH3','Cr_CH2_PCrCH2'};
figdir='/home/romain/data/spectro/hipo/resume/T2fig_all';
res... |
aa8a48a44ef7fd3fa2d0a03663664cd5364fb9175d5f21d8b08f4cce0bd85837 | MATLAB | 3,093 | 85 | function out_ch=postprocessing_v2(out,fs,num_chans)
% John's postprocessing code
% POST PROCESSING JANCA DETECTOR DETECTIONS
% @========================================================================
% Authors: Sayeed, John Thomas
% DATE CREATED: 23-April-2021
% DATE MODIFIED: 22-Spetember-2022
% Wrote a co... |
0f0809942edaf193e675b2bb658c4f4cddb0bdb42af3116419dcb64526c7878f | MATLAB | 3,094 | 66 | %% Prerequest
% 1. combined rhd file (use RHD file merger
% https://intantech.com/downloads.html?tabSelect=Software)
% 2. single trial behavioral data, generated from 'Lick_BehavDat.m'
%% 1. read rhd file
disp('select the RHD file');
read_Intan_RHD2000_file; %read RHD file
file_num = extractAfter(filename,asMany... |
84237af9dde36711e7f3c85cd768da2c68f1d0c9d87e0f35a6b69da1561d78a0 | MATLAB | 3,096 | 93 | function [cs,index] = XxSort(c,mode)
% ------------------------------------------------------------------------
% sort_nat: Natural order sort of cell array of strings.
% usage: [S,INDEX] = sort_nat(C)
%
% where,
% C is a cell array (vector) of strings to be sorted.
% S is C, sorted in natural order.
% INDEX... |
fc9c7b93c8da401bb71eb4e58b7c52c904c07ff54ada9055e0da3ecfd6d96eb9 | MATLAB | 3,096 | 98 | %% Convert Scan Image Files
% Author: Pratik
clear all
data = struct('mouse',[],'date',[],'acq',struct());
data.acq = struct('FPnames','','nFPchan',[],'FP',[]);
%% Pull Wheel Data
choice = menu('Are you adding Wheel Data?','Yes','No');
switch choice
case 1
[fFiles,fPath] = uigetfile('*.mat','... |
65daccf267ce3e655d56b27e3bf243f0aa9b423756e5ddb5228cc45e43e44dcb | MATLAB | 3,098 | 109 |
%{
----------------------------------------------------------------------------
Determine the time window for task relevant neurons
%Start of task
%Sound on
%Sound off
%Before choice
%After choice (0sec)
%After choice (1sec)
%After choice (2sec)
%p = 0.001
%Each epoch, predict the prior, sensory and choice... |
1c9b35ccf3efd8460a7cd8bb8f193fdd94b2af0b687a26ed738efea77cee3ddf | MATLAB | 3,100 | 103 | close all
clear all
%% Load (or compute and save) data
% check if data file already exists
filename = './sim_data.mat';
if exist(filename,'file')
fprintf('previously computed data found.\n')
fprintf('loading previously computed data....\n')
load(filename)
% if it doesnt, recompute data
else
fprintf... |
6184cf5a05517483f811d82a2a5b3567e9a368fecf6d6104aaa15653aa3a3f98 | MATLAB | 3,100 | 86 | function [anUnits, cond] = getBinnedSpikeCounts(trials, units, varsOfInterest, options)
% outputs are:
% - spikeCounts (trials,units) array for each trial condition (this is a
% useful object for decoding
% - high dim tuning object for each unit
% - mean 1d tuning for each object + pref var value
% example inputs:
%t... |
fa11fc0a755649bf68cf87ab9c73836d27d4e3b4c94d4cd79e97e1e25794c66d | MATLAB | 3,101 | 123 | clear; clc; close all; rng('default')
assert(~isempty(strfind(pwd, 'embanded/examples/matlab')), 'Please change folder to the examples directory')
run(strrep(pwd,'examples/matlab','setup.m'))
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Simulate data.
% Generate some training data
num... |
a50c61516c37266de6fe01ad517c0acb05344426a26195ebc778eca17403c611 | MATLAB | 3,103 | 86 | function [samplesOut, channelMeans] = filtCAR(samplesIn, windowPre, windowPost, trimPad, hCfg)
%FILTCAR Apply user-specified filter and common-average referencing
if nargin < 3
windowPre = [];
end
if nargin < 4
windowPost = [];
end
if nargin < 5
trimPad = 1;
end
... |
1ad263a7e9c2423ee2463c52a09132e653969dd98fc3b658acea762feac00da9 | MATLAB | 3,107 | 82 | % 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... |
48d4a3933a8b388609c83eca799927e15530df72220342ef6e39f0c85206da94 | MATLAB | 3,107 | 100 | clear
p = params_2DAA;
fpath = fullfile(p.processed_data_dir,'allData.mat');
load(fpath,'evs','tis','bvs','traces')
[cols,alpha] = chooseColors;
%%
fpath = fullfile(p.data_dir,'identification_of_motion_dims');
saveData = 1;
saveFigs = 1;
n_rep = 80;
aa_sessions = 3:9;
n_pc = 10;
% default number of trials
n_tr = 300; ... |
6352e50faf99732cf7007ca1ad27fd263bb461cc6888a40a763333b1ff34ea45 | MATLAB | 3,107 | 101 | function [info_o] = concatenate_fid(info,str_concat)
if nargin==1
str_concat=''; %concatexam
end
if strfind('subject',str_concat)
concat_OK=1;
else
concat_OK=0;
end
correct_center_freq = 0;
io=1;
while length(info)>1
info_o(io) = info(1);
info(1) = [];
ind_to_remove=[];
... |
2761a35fa084c1fad51464c7ce6f0efb456bea35394dcd50ac4f37959756829c | MATLAB | 3,108 | 46 | function params = echtparams(varargin)
% This function loads basic parameters for processing the ECHT output,
% unless otherwise specified. Requires the finputcheck function from
% EEGLAB
%
% Written Tylor J Harlow 9/12/2023 - tylor.harlow@uconn.edu
params = finputcheck(varargin,...
{
% LabVi... |
4d726f9fae40fabccfbf20df5098760d1480a5af299e078fa0df16b0a1dabdf1 | MATLAB | 3,108 | 117 | function y = mtimes(ob, x)
%function y = mtimes(ob, x)
% A * x
% A' * y
% y' * A
% x' * A'
% B * A (calls private/fatrix2_mtimes2)
% etc
if isnumeric(ob)
if isscalar(ob) % scalar * object
y = fatrix2_scalar_times(ob, x);
else % row_vector(s) * object
y = (x' * ob')'; % trick: x <-> ob
end
return
end
if ~isnu... |
27a10490711591a126c71440f2d250a1029c70753fbaa27e06c6da23ce37e928 | MATLAB | 3,114 | 126 | function [gm,Labels,CondLabels,GroupLabels] = RaguGrandMeans(V,Group,Cond,L1,L2,Gl)
% Copyright 2009-2011 Thomas Koenig
% distributed under the terms of the GNU AFFERO General Public License
if nargin < 3
Cond = (1:size(V,2))';
end
if isempty(Cond)
Cond = (1:size(V,2))';
end
if isnan(Cond)
Cond = ones(... |
2c40c468e2e2d29339601c270373c7867ee2f8ecb383e66faff150488c630284 | MATLAB | 3,116 | 83 | function [finalData, flagMatrix] = unwrapBeh(rawData)
% [finalData, flagMatrix] = unwrapBeh(rawData)
%
% Summary: This function converts the periodic encoder trace to a smooth
% measure of number of wheel rotations. It can work for any periodic signal
% that goes from 0 to 1. Should be robust to extra data poin... |
5dfe08f2c79c5b64abe16aedd2ce6ce7e4503386024bc1a8a95b8b22612e678b | MATLAB | 3,116 | 51 | function GUI_Params(P)
P(1).GUI_Handles.Software_Name = 'Neuronalyzer';
P(1).GUI_Handles.Software_Version = '2.0.0';
P.GUI_Handles.UI = 1; % 0 = figure. 1 = uifigure.
P.GUI_Handles.Multi_View = 0; % 0 = Single-view project. Multiple files are loaded as separate projects. 1 = Multi-view project. All files are lo... |
678847ea5770c453afe943a0621dfaf5110df57e7ac8e7f11b2abbcf0a0566b1 | MATLAB | 3,116 | 65 | % Cardiac model ToR-ORd
% Copyright (C) 2019 Jakub Tomek. Contact: jakub.tomek.mff@gmail.com
%
% 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 3 of the Licens... |
216df8c7d549f84e86189aedaa9ee0771f692e3689f80cc08769b4c9bed7461c | MATLAB | 3,118 | 74 | % 3D reconstruciton for csLFM
% The Code is created based on the method described in the following paper
% ZHI LU, SIQING ZUO, MINGHUI SHI etc.
% High-fidelity long-term intravital subcellular imaging with confocal scanning light-field microscopy
% in submission, 2023.
%
% Contact: ZHI L... |
e9a739f3b2af1eb45da56225c16006708e4f03b816464168b1b409697eed7562 | MATLAB | 3,122 | 84 | function [myState myMap]=StateSpace_v1(myState,myMap,opt)
% input: myState (with current ".state_history" and ".action_history"
% parameter: myMap.action1, myMap.action2, myMap.reward
% output: myState (with updated ".index", ".state_history" and ".reward_history"
% opt.use_data=0; >> normal state transition
% opt.use... |
94b93e137ca4c926c898225a352c0949c5230560be4cc4cf6ff449ac4b005224 | MATLAB | 3,124 | 57 | function [Im1_NoiseReduction,Im1_branchpoints,Im1_endpoints,Im_Skel_Rad] = Pixel_Trace_Post_Proccessing(Im1,Scale_Factor)
% TODO: get params from the Parameters struct.
EndPoint_Min_Distance = 3;
% Min_Object_Pixel_Size = 30; % 30.
Min_Object_Size_Ratio = round(10 ./ Scale_Factor); % um to pixels.
% Fill "bl... |
4389c0722312bce8aef4c380a988498f1c18295d632edeab2b16bd31e71143ea | MATLAB | 3,125 | 72 | clear,clc
close all
fnames = {'hex10','hex','iaa','two_oct','hxa','two_hep','ani','hex01',...
'msal','lcar','euc','gua','chex','bza','ger','etha',...
'apin','one_oc3','neem','gar','cit','lin'};
odors = {'Hexanol 10%','Hexanol','IAA','2-octanol','Hexanal','2-heptanone','Anisole','Hexanol 0.1%',...
'M... |
9c92879175bcafc2e46cf666c5cdb60969d15327f394ef9db78966c307b2e030 | MATLAB | 3,129 | 107 | close all;
clear;
clc;
resultfname = 'testWeightedHistogramAveraging02.txt';
% parameters
subject = {'Dog_1', 'Dog_2', 'Dog_3', 'Dog_4', 'Dog_5', 'Patient_1', 'Patient_2'};
f0 = 60; % powerline frequency Hz
Q = 30; % notch filter Q-factor
wlen = [0.5 1.0 3.0 5.0 10.0]; % energy window lengths in seconds
drop = 200; % ... |
d01888069edea863fcc20602aa49ab8d16d0e0bef8069f3d1ad8b60305dc7d84 | MATLAB | 3,129 | 100 | a = 45;
b = 45;
xyz0 = [0,0,1];
xyz0_p = [0,0,0];
xyz1 = [cosd(0),sind(0),1]; % The length of this vector is 1.
xyz1_p = [cosd(0),sind(0),0]; % The length of this vector is 1.
xyz2 = [cosd(90),sind(90),1]; % The length of this vector is 1.
xyz2_p = [cosd(90),sind(90),0]; % The length of this vector is 1.
xyz3 = [co... |
f8b51b3724994a11e27c89c9bafb55d1a97f817068dba8a35a6d6b771382d7f7 | MATLAB | 3,129 | 79 | function [ av_trials,err_trials ] = collect_ae_trials_for_tone_analysis(p, traces, bvs, tis, speed_control,alignment_type)
%alignment_types:
% 1: tone start
% 2: action start
% 3: tone end
spd_dims = 18:22; %dlc
pre_steps = 15;
post_steps = 15;
for sub = 1:p.nSubjects
... |
4f688cef21a4dad79535068b65cee817433560393d5780e81961fdfae8fe9e53 | MATLAB | 3,130 | 87 | function [brst_files, int_templ, path] = find_xls(app)
path = uigetdir(pwd, 'please select master folder that contain all *.xls files to combine');
files = dir(fullfile(path,'**','*.xls'));
tmp = string([]);
for i = 1: length(files)
tmp(i)= string(files(i).name);
end
[~, tmp_idx] = sort(tmp);
files(tmp_idx) = fil... |
b7894933c66f9f6dd149bfd070e645b907da0dc58a2ba32dc711106f5d6ef9c0 | MATLAB | 3,132 | 104 | % Function to accumulate Simmilitude Matrices
% of each Ensemble Analysis For each Experiment of the same
% experimental setup, i.e., same experimental conditions
%
% Input
% Load experiment manually from different folder: one by one
% R_Condition: Selected rasters of the Experiment
% fs: Sampling Frequency
% O... |
cf39432edd4650d627c953e6178ad7237c8fd4e0407e279ab4a8eb66b510e3c3 | MATLAB | 3,132 | 80 | function [grp,node] = layereddiagram(h,data)
%% Set dimensions of the graph
% autocorrelatemap() and crosscorrelatemaps() depend on this function.
load('structures','groups','regions');
subplot(h);
set(h,'DataAspectRatio',[1 1 1],'Visible','off','NextPlot','add');
gr = length(groups.name); % Number of hyperstru... |
dd334b8b4248f13b9604983f899f32ab48cf986cefc567f643cc92ab342aeae3 | MATLAB | 3,134 | 135 | %% plot projections of DR data trial average (not per task) onto spd_dims
[cols,alpha] = chooseColors;
this_cols = {};
this_cmap = spring;
this_cols{1} = this_cmap(30,:);
this_cols{2} = this_cmap(50,:);
this_cmap = winter;
this_cols{3} = this_cmap(1,:);
this_cols{4} = this_cmap(35,:);
this_cols{5} = this_cmap(64,:);
... |
38c87584074fb695de308a4488b82020a72d2e733bf1bb8be613cd70e4f07bfb | MATLAB | 3,135 | 93 | %% Graph two groups of traces
function [testStats pvals sigIdx sigP] = graphSetsOfAverageTraces(treatTraces, nullTraces, test, span, binLengthStart, binLengthEnd, yLimits, behaviorName)
% treatTraces = allTracesTreat; %data to analyze
% nullTraces = allTracesNull; %data to analyze
% test = true %run ttests across t... |
c6baa63e579f25f7bc5d76cafa54f164931d1884a814d8caff869a468b97f7ed | MATLAB | 3,135 | 97 | function seqNew = getTrajNewTrials(ws, dat, varargin)
%
% seqNew = getTrajNewTrials(ws, dat,...)
%
% Extract neural trajectories from a set of new trials using previously-fitted
% model parameters.
%
% INPUT:
%
% ws - saved workspace variables that include the previously-fitted
% model parameters 'es... |
de88a5f55c283337a15d4d63368455ee1beb7b915032f2a02de8076be192877e | MATLAB | 3,135 | 110 | function [total_error, max_error] = eq_area_error(dim,N)
%EQ_AREA_ERROR Total area error and max area error per region of an EQ partition
%
%Syntax
% [total_error, max_error] = eq_area_error(dim,N)
%
%Description
% [TOTAL_ERROR, MAX_ERROR] = EQ_AREA_ERROR(dim,N) does the following:
% 1) uses the recursive zonal equal a... |
60258bfd7bc4d854bc5654e92f0b7e00fcb47afdaec86b5ce8b3bf8a9c2548f7 | MATLAB | 3,141 | 94 | function [features1, features2, features3] = spikePCA(spikeWindows, hCfg)
%SPIKEPCA Project spikes onto their principal components
% if strcmpi(hCfg.vcFet, 'pca')
prVecs = spikePrVecs(spikeWindows, hCfg);
% else
% mrPv_global = get0_('mrPv_global');
% if isempty(mrPv_global)
% ... |
13d6373f446be534a2151e45cd946d458e3680336d46a346426224fbe830ab63 | MATLAB | 3,144 | 104 | function prot = read_twix_hdr_DICOM(DICOMfile)
% modified version of Philip Ehses' read_twix_hdr.m to run on DICOM files
% and extract the Siemens parameters from the Private_1029_1020 tag
%
% It is not clear if the XML part of this header is actually useful - but
% the ASCCONV section clearly contains all the 'regular... |
83206a2e6e4bcee4b351bb8dad36111e70b4c9d6fd91e924a749dec229b85ad2 | MATLAB | 3,144 | 93 | function [MAMA,MHMA,MH2MA] = precompute_moments(x,preNodes,postNodes,par);
% PRECOMPUTE_MOMENTS Computes moment tensors used in CORRECT_GRN_NETWORK.
% [MAMA,MHMA,MH2MA] = PRECOMPUTE_MOMENTS(X,PRENODES,POSTNODES,PAR) for gene expression levels X, ... and parameters PAR returns
%
% MAMA,MHMA,MH2MA moment tens... |
1704a4b343913f6449baea75cd585446a0440c734ae400a1b95a78669a990079 | MATLAB | 3,145 | 79 | function y = lp_filter_zero_phase_2nd(x, fc)
% lp_filter_zero_phase_2nd - Fourth-order zero-phase Butterworth lowpass filter
% built from a second-order (biquad) IIR section applied via zero-phase
% forward-backward filtering.
%
% Syntax: y = lp_filter_zero_phase_2nd(x, fc)
%
% Inputs:
% x: Vector or matrix of i... |
68ece29c43acc89e5e4a452d94e050f26d94af583b0cb815247e5c87427c44d7 | MATLAB | 3,145 | 113 | function [energy,dist] = eq_energy_dist(dim,N,s,varargin)
%EQ_ENERGY_DIST Energy and minimum distance of an EQ point set
%
% Syntax
% [energy,dist] = eq_energy_dist(dim,N,s,options);
%
%Description
% [ENERGY,DIST] = EQ_ENERGY_DIST(dim,N,s) does the following:
% 1) uses the recursive zonal equal area sphere partitioning... |
9326ae0a4ac672eb0f8ae0dd53dfdd39e5053b6d7a5977e7478874e7e6f9b4d9 | MATLAB | 3,151 | 119 | function y = kaiser_bessel_ft(u, J, alpha, kb_m, d)
%function y = kaiser_bessel_ft(u, J, alpha, kb_m, d)
%|
%| Fourier transform of generalized Kaiser-Bessel function,
%| in dimension d (default 1).
%| shape parameter "alpha" (default 2.34 J)
%| order parameter "kb_m" (default 0)
%| See (A3) in lewitt:90:mdi, JOSA-A, ... |
3fce5d8cf5d10eaca897580a38518fe8b2497ce6d40c538eb0a463398462d17b | MATLAB | 3,155 | 89 | function varargout = RaguSTT(varargin)
% RAGUSTT M-file for RaguSTT.fig
% RAGUSTT, by itself, creates a new RAGUSTT or raises the existing
% singleton*.
%
% H = RAGUSTT returns the handle to a new RAGUSTT or the handle to
% the existing singleton*.
%
% RAGUSTT('CALLBACK',hObject,eventData,handl... |
40c0c3cc53cf39ff1ddd97c25f7aadac68ba0015e4bd8f02a609762ed26c73d2 | MATLAB | 3,155 | 103 | close all;
clear;
clc;
resultfname = 'testProcessSeizureEEG_EnergyDistributions01.txt';
% parameters
subject = {'Dog_1', 'Dog_2', 'Dog_3', 'Dog_4', 'Dog_5', 'Patient_1', 'Patient_2'};
f0 = 60; % powerline frequency Hz
Q = 30; % notch filter Q-factor
wlens = [3.0 10.0 30.0]; % energy window lengths in seconds
x = [];
... |
3bb0bb148873a6e7e00542d1ce4c0c1c1ee89ed5abd8eddc89ad9c5089dab24a | MATLAB | 3,158 | 114 | function[haxe,h1]= plot_ConfInt2(varargin)
% Programmer: Deirdre Bolger
% Input Variables:
% DataIn = the input matrix of data;
% no. data points X no. subjects
% points
% T= time vector (vertical)
% ... |
388e8171794a8552428973fe580ace174364cf21f4a6ff6c74465a4009a812c9 | MATLAB | 3,159 | 89 | % Hierachichal Clustering of Raster Coactivity
% .
% Input
% R: Raster of Neural Activity(Frames x Cells Raster)
% CAG_TH: Coactivity Threshold
% Nensembles: Number of Ensembles to Cluster
% SimMethod: Method of Simmilarity
% Ouput
% Raster Structur with Fields:
% Data.Data=R; % Frames x ... |
c03869e4478606f989c645069fb19d9bc91af3cfb4ee6de24c2814e1d2d77248 | MATLAB | 3,160 | 170 | function fid = read_basis_and_save_raw(filename)
if ~exist('filename')
filename = spm_select([1 inf],'any','select files','',pwd)
end
for k =1:size(filename,1)
[p f e]=fileparts(filename(k,:))
file_in = fullfile(p,[f,'.IN']);
if exist(file_in)
fp = fopen(file_in)
s='qsdf';
while ~isemp... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.