sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
cbf7d751abeb991f60c40a2d5fc1363dfbb6baf0bbf273e74059ac0a3e1a5128 | MATLAB | 4,910 | 140 | %
% Test program for generating synthetic multichannel maternal/fetal ECGs
% mixtures with additive colored noise
%
% Dependencies: The synthetic ECG generator and noise generator package of
% the Open Source ECG Toolbox
%
% Open Source ECG Toolbox, version 2.0, December 2008
% Released under the GNU General ... |
333bb4939fce2824aad6267c2f53bca0c1a515278d05d2aa019e9a6dc354f9bb | MATLAB | 4,911 | 176 | classdef (Abstract) conicFit < matlab.mixin.CustomDisplay
%A base class for executing and managing 2D conic fits
properties (SetAccess=protected)
XY
angle=0;
end
properties (Dependent,Hidden)
R
theta;
end
methods
function R=get.R(obj)
... |
2a4fbd311fdab630088b86b2b44a520cec1f122fc457e1b75e7ab4121119c956 | MATLAB | 4,916 | 153 | clear;
clc;
%%
[file, path] = uigetfile('best_waveform.mat');
datafile = fullfile(path, file);
load(datafile)
cd(path)
wm = best_waveform.mean;
[file, path] = uigetfile('cluster_info.tsv');
datafile = fullfile(path, file);
w = tdfread(datafile);
%% plot all waveforms
for i = 20:30
... |
244dc63c5e5b6f23e935661b8fced196eeb5ac45f0ad452507e3595e343f09a0 | MATLAB | 4,918 | 144 | function [ChromaticCorrections,ROIs]=mnl_CalculateChromaticAberrationsFromGuideStars
%This function calculates the regression for a volumetric image. What you
%need to have prepared in advance are guide stars containing a fragment labelled in all the required channels (4D images - x*y*c*z)
%where you know which z frame... |
e30f62d6e71034348c6ae1d656f7ea659480ab2851bd2ffeae68ed73034c503a | MATLAB | 4,923 | 117 | function [ eval_accs ] = eval_ae_decoder_per_sub( p,av_trials_all,err_trials_all,trans_data_all,trans_data_err_all,q,trial_idx_ses,aa_sessions,n_tr,nullspace,n_rep,trans_data_all_dr,rand_control,tone_idx)
%%
for rep = 1:n_rep
%% create two versions of trial_idx_ses: one for training, one for testing
... |
37643c0101517e61653dbdea05ab2e19cb04b66290ef225cdc5fe2985cd79d51 | MATLAB | 4,924 | 158 | function [seq, LL] = exactInferenceWithLL(seq, params, varargin)
%
% [seq, LL] = exactInferenceWithLL(seq, params,...)
%
% Extracts latent trajectories given GPFA model parameters.
%
% INPUTS:
%
% seq - data structure, whose nth entry (corresponding to the nth
% experimental trial) has fields
% ... |
56e23657c3d95a408640d26c59a5cb8313939d155db28b4817c61fc38086e555 | MATLAB | 4,924 | 161 | %% Figure 1 plots
clear all
close all
%read raw data
por_data = xlsread('POR_data.xlsx','B2:AA23');
[~,odor_data] = xlsread('POR_data.xlsx','B25:AA46');
[~,gender_data] = xlsread('POR_data.xlsx','B47:AA47');
odors = {'hex','hex01','hex10','iaa','2oct','ani','hxa','gua','bza',...
'cit','neem','gar','chex','l... |
07dd1b3fad3bbdecfff4f80e813f3e1b4ea613525f7c84c9a0bbb9b11ea90bca | MATLAB | 4,927 | 131 | function [sourcepos_vox] = get_AAL_coords(AAL_regions,S)
%% [sourcepos_vox] = get_AAL_coords(AAL_regions,S)
%% get_AAL_coords generates voxel coordinates for each atlas region
% contained in AAL_regions ensuring they remain "inside" the set of valid
% source positions determined by fieldtrip.
%
% Requires:
% A... |
c86ce1e0387f0d8385fa8ed550f9cea6e1a46e015f7966bbb194c1396467bc59 | MATLAB | 4,927 | 110 | function save_trans_results(app)
[int_idxs,~] = listdlg('PromptString',{'Please select intervals ',...
'to be plotted/saved.',''},...
'SelectionMode','multiple','ListString',app.popup_int_transduction.Items);
[form_idxs,~] = listdlg('PromptString',{'Please select fileformat ',...
''},...
'SelectionMod... |
de6c2ad7494c4f0a9c88f7af0a1235277132acd693d058bef2d1303bb258bbe1 | MATLAB | 4,927 | 116 | function [pip, ials, pnn_ss, pnn_as] = heart_rate_fragmentation(rrn_interval , fs)
% function [pip, ials, pnn_ss, pnn_as] = heart_rate_fragmentation(rrn_interval , fs)
% Computes Heart Rate Fragmentation of a NN interval time series.
% HRF describes short-term fragmentation patterns in heart rate dynamics
... |
81612e263ba248d5b7555a06874b3fcad7c47aab084ac49fa9b9499af18fa6f2 | MATLAB | 4,930 | 128 | function [ProcessedData_SAVE,varnamesDATA_SAVE] = fixedBLperZscoreV4(Data,Dts,TrialParam,varnames,varnamesDATA)
ST1 = {'Raw'; 'Recentered'; 'DecayAdj';};
inUseST = fieldnames(Data);
STidx = zeros(1,numel(ST1));
for i = 1:numel(ST1)
if ismember(ST1(i),inUseST)
STidx(i) = 1;
end
end
S... |
6f13f6f4acfac80c0c1cac9a4feb4dcbf211932f81586e83bbb18c788e7b54ce | MATLAB | 4,932 | 210 | % gg_Gnufft_test.m
% Test the Gnufft object (vs exact Gdsft)
% create Gnufft class object
% lets try a 1-d comparison instead
npow = [5:10];
%npow = 8*ones(10);
dispimgs = 0;
doexact = 1;
%npow = 10;
%Jval = [3:12];
for ii = 1:length(npow)
%for ii = 1:length(Jval)
disp 'setup Gnufft_test'
N = [2^npow(ii) 2^npow(ii... |
49a7ef0ac903a5d4f17d08579ea430e9fc69f745237048cbd68e374eca06d75a | MATLAB | 4,933 | 104 | %Step 1 of CBIG Kong2019 Brain Parc Pipeline
%
%To run: 1. Open Matlab using salloc (ex: `salloc --mem-per-cpu 200G --time 2:00:00 --x11`)
% 2. source your config file containing the $CBIG_CODE_DIR variable
% -It might be helpful to `cd` to the $CBIG_CODE_DIR/stable_projects/brain_parcellation/Kong2019_MSHBM/step1..... |
d03c6596a3469a854656640f12027e7210bbe9fe8e591763fbfda78e3715f5c6 | MATLAB | 4,934 | 167 | function intervalHistrelative20190604
%Ϊ Á½Æ±ëÌC^[oÌqXgOðìé
%ÔC^[o
% cd('C:\Users\C238\Desktop\CheetahWRLV20180729\119\2017-6-7_20-8-33 11901-51');
% dpath=('C:\Users\C238\Desktop\CheetahWRLV20180729\119\2017-6-7_20-8-33 11901-51\');
% dpath3=('C:\Users\C238\Desktop\C... |
49aa1e5b74b0f08bf28c6a0f5ec2bacf15ac9da85a7a50b5a0441ee16b3b778c | MATLAB | 4,939 | 187 | % JRCLUST v4
% Alan Liddell, Vidrio Technologies
% Originally written by James Jun
function hJRC_ = jrc(varargin)
%JRC
if nargout > 0
hJRC_ = [];
end
if nargin < 1
disp(jrclust.utils.help()); % later: GUI
return;
end
% discard try-catch here for now as the... |
3f80ccb25e9a0650caa8edc204f0b56d2625290146760d991721f98bfc758af5 | MATLAB | 4,943 | 125 | % Script to accumulate Rate of Ensembles(RoE)
% of each Ensmble 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
% Output
% ... |
c72d8f1c16445bed25e1136e6d0ceb4f6272385d56264a60c3b7bc45dc44dcfe | MATLAB | 4,948 | 165 | function X = nufft(x, st)
%function X = nufft(x, st)
%|
%| Compute d-dimensional NUFFT of signal/image x
%|
%| in
%| x [N1 N2 ... Nd (L)] L input image(s) of size
%| N1 x N2 x ... x Nd
%| st structure precomputed by nufft_init()
%| out
%| X [M (L)] output spectra
%|
%| Copyright 2003-5-30, Jeff Fessler, Univer... |
53e878b67034b8e45707ccffaf50a3e9a2743ca6f53fd4f0276a4003a82cffc4 | MATLAB | 4,951 | 111 | function [emg_quant, synch_emg2, ecg_estimate2_bl, time_vec] = emg_quantification(emg_data, fs, emg_onset_sampl, varargin)
%
% [emg_quant, synch_emg2, ecg_estimate2_bl, time_vec] = emg_quantification(emg_data, fs, emg_onset_sampl)
% [emg_quant, synch_emg2, ecg_estimate2_bl, time_vec] = emg_quantification(emg_data, fs,... |
5459274ac05cfdc4cfe541dd2a3d0c37ef186406a1b68c250254db7b3d1d511b | MATLAB | 4,954 | 152 | function [burst_amp_D1,burst_amp_D4,burst_amp_D1_std,burst_amp_D4_std] = peak_VE_hmm_burst_amp(sub,ses,project_dir)
restoredefaultpath
% close all
clc
run = 'run-001';
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
addpath(genpath('.\HMM_bursts-master\')) %from https://github.com/ZS... |
871c7dfcefda3f6dfb7a36c55f2c3c6625b401ede9c4d871064378fd69012af7 | MATLAB | 4,954 | 160 | function [ V , D ] = joint_diag(A,jthresh)
% Joint approximate diagonalization
%
% Joint approximate of n (complex) matrices of size m*m stored in the
% m*mn matrix A by minimization of a joint diagonality criterion
%
% Usage: [ V , D ] = joint_diag(A,jthresh)
%
% Input :
% * the m*nm matrix A is the concatenation ... |
448d0a58c98e078c30c2a312b43a495180f58c0cd70b6edf25aaa0c885eac2f7 | MATLAB | 4,962 | 144 | function res = splitUnit(obj, spikeClusters, unitID, unitPart, metadata)
%SPLITUNIT Speculatively split a unit, returning a snapshot of the
%spike table and metadata fields.
if nargin < 5
metadata = struct();
end
res = struct('spikeClusters', [], ...
'metadata', []);
nS... |
571dc18ff6601e0e050ffcacb1f37f2c2ccfdbf6d99944fb74ed2517de99bd03 | MATLAB | 4,962 | 157 | function [nCIJtree CIJtree mdeg globalcosteffmax costmax E]=threshold_omst_gce_wu_fast(CIJ,flag)
% threshold_omst_gce_w Optimizing the formula GE-C via orthogonal MSTs.
%
% [nCIJtree CIJtree mdeg degree vector cost ]=threshold_omst_gce_wu(CIJ)
%
% This function thresholds the connectivity matrix by abso... |
d2d442fc5201283564594a537fd3b937d4a86fefb7884224e619eca036d1727f | MATLAB | 4,962 | 105 | function [ECG_mean, ECG_median, ECG_cov, ECG_mean_robust, ECG_median_robust, stacked_beats_all_channels, beats_sqi] = ecg_features_phase_domain(data, peaks, params)
% ecg_features_phase_domain - Extracts phase-domain ECG mean and median beats, and beat covariance matrix.
%
% Usage:
% [ECG_mean, ECG_median, ECG_cov, E... |
8d9cd899afe36da2fbdcb1eddd520cf7f887471f683b5ae249de196a4b5cfadd | MATLAB | 4,963 | 188 | function preprocess_subj(s_num, study_folder)
subj_struct_fold = [study_folder,'/last_events/Subj_', num2str(s_num)];
load(fullfile(subj_struct_fold,'last_event_times.mat'))
is.highpass=0.5;
const_pad = 3000; % this is 3 seconds that we add to the end of the block
spL = fullfile(study_folder,['Preprocessed_Data/Subj... |
b36986ac166af681304073f45e692419be9a390bf7b0b2694a9a057fabd3d556 | MATLAB | 4,969 | 93 | function Syuusei
PositiveTouchesPointArray=zeros(1,6);
FRCVLPWTouches=[];
FRCVRPWTouches=[];
cd('C:\Users\C238\Desktop\touchcellLtRt_terashita\38');
LS1=ls;
for j=1:length(LS1(:,1))
TrimFolder2=strtrim(LS1(j,:));
if length(TrimFolder2)>22 && strcmp(TrimFolder2(end-21:end),'Spike... |
1104dff3b28a410f95310654eb55d3c2043b6cbd0499d6077220b601e46c72fb | MATLAB | 4,971 | 195 | close all;
datasetName = 'MNIST';
%datasetName = 'CIFAR';
%datasetName = 'CIFAR-100';
%datasetName = 'SVHN';
if (ispc)
kBaseFolder = ['C:\Users\sergeyd\Workspaces\' datasetName];
else
kBaseFolder = ['/media/sergeyd/OS/Users/sergeyd/Workspaces/' datasetName];
end;
kWorkspaceFolder = fullfile(kBaseFolder, 'mnist... |
e8817a9da6809ed6ce78b82b56a9fe69b904788e0776d3fdafefda28adefa9a4 | MATLAB | 4,984 | 138 | function Reconstruct_Vertices(W,Display_Image)
Path1 = uigetdir;
Scale_Factor = W.User_Input(1).Scale_Factor;
% SmoothingParameter = 5000000;
D = 10;
Dxy = 20;
[Rows,Cols] = size(W.Image0);
if(nargin == 2)
imshow(W.NN_Probabilities);
hold on;
%{
if(isfield(W,'Medial_Axis') && ~isempty(... |
fd5cd89f3d2fe8288a04a779295f1582050836d64bc1cf013c40c7de91024717 | MATLAB | 4,985 | 157 | function making_nnd_csv(nnd_distance_map_2,atlas_map,fol_name)
csv_name = '16bit_allen_csv_20200916.csv';
nnd_distance_map_2(nnd_distance_map_2(:)<0) = 0;
nnd_distance_map_2(nnd_distance_map_2(:)>100) = 100;
% [xxx,yyy,zzz] = ind2sub(size(nnd_distance_map_2), [1:1:length(nnd_distance_map_2(:))]' );
... |
72e6f1c573f9c480320f09eda9dd1ccd2d86e3aa51fc1fda3172486c8ee8e86e | MATLAB | 4,986 | 124 | function DataHigh(varargin)
% DataHigh is a graphical user interface to interact with and
% visualize high-dimensional population activity.
%
% Usage: DataHigh(D, ...)
%
% INPUT:
%
% D: struct (where D(i) refers to the ith trial or ith condition)
% data [neurons x 1ms time bins] (for DimReduce) or
% ... |
364037c3c9d1ef04dc90e82c8668df2bd3f96fe9116e577f999dc39fadfce6db | MATLAB | 4,992 | 131 | % Function that analyze if the two main branches of the
% cluster analysis (using hierarchichal clustering)
% have other cluster that helps to classfify better
% the neural ensembles
% Input
% Rclust: Thresholded Raster to Analyze
% Ouput
% frame_ensembles Labeled Frames of the Neural Ensemble
function [f... |
d1d864f301f387c407f8a0862b0f6e27fcd88184e381f4e38a55cfc6ef9acb83 | MATLAB | 4,992 | 142 | function NW3_Pattern_4_20201208
path=['C:\Users\C238\Desktop\touchcellLtRt_Hirokane'];
cd(path);
LS=ls;
LtNWFRUnit=[];
RtNWFRUnit=[];
LtNW123Point=0;
LtNW123Fire=0;
LtNW234Point=0;
LtNW234Fire=0;
LtNW124Point=0;
LtNW124Fire=0;
LtNW134Point=0;
LtNW134Fire=0;
RtNW123Point=0;
RtNW123Fire=0;
RtNW234Po... |
d701fd525cd57be495d2d5d03bba2f32147b1bdc15abfe9fdacae450331bc03f | MATLAB | 4,993 | 142 | function NW3_Pattern_4_20200303
path=['C:\Users\C238\Desktop\touchcellLtRt_terashita'];
cd(path);
LS=ls;
LtNWFRUnit=[];
RtNWFRUnit=[];
LtNW123Point=0;
LtNW123Fire=0;
LtNW234Point=0;
LtNW234Fire=0;
LtNW124Point=0;
LtNW124Fire=0;
LtNW134Point=0;
LtNW134Fire=0;
RtNW123Point=0;
RtNW123Fire=0;
RtNW234P... |
eedb1ea62d293e7dff7f89592caa225db9cdaabe4e12e008eebf5040a31611a5 | MATLAB | 5,001 | 189 | function [Beads]=mnl_ReadROIsFromImageJ(fn,Data)
%Function that uses the code written by Dylan Muir Dylan Muir (2021).
%ReadImageJROI (https://github.com/DylanMuir/ReadImageJROI), GitHub.
%Retrieved June 3, 2021. And then ammends the values to fit the required
%format for mnl_Pipeline_MeasurePSFandCA
% Inputs
% fn - th... |
03758bd7d287d1b1d0f4c950dafc50906a99a05c0858943082d512ed19fe3d2c | MATLAB | 5,004 | 127 | % this scripts calculates mean of neurobehav scores in MS and HC subjs,
% disease modifying therapy, etc...
clearvars
close all
addpath(genpath('/storage/stella/MATLAB_toolboxes/'));
addpath('/storage/stella/Analysis/matlab_scripts/');
run('/storage/stella/Analysis/DTI_FreeWaterFraction_May2022/SCRIPTS_MATLAB/T1_auto... |
996fbddfaf9dee2c0a8c7fe827ba2c215da155a6852e4dc094245fae117d429a | MATLAB | 5,005 | 86 | function par = set_parameters()
% LOAD PARAMS
par.segments_length = 5; % length (in minutes) of segments in which the data is cutted (default 5min).
par.sr = 30000; % sampling rate (in Hz). This parameter will be only used if the data file don't have a sr.
% PLOTTING PARAMETERS
par.c... |
bcdba8b242bf709c030df5cf1d9f46af331a41fa49b7955ca84c0a7c29ac7c98 | MATLAB | 5,005 | 118 | address_data = 'ebos_data_breast.xlsx';
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% CTC day 33
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
min_value_CTC_33 = 0.000393;
column_CTC_33 = 'CD';
[CTC_33s, CTC_33_d, norm_CTC_33s, norm_CTC_33_d] = load_compu... |
55239d69426e438fe4f49e522015de66d265ca12a8069e1f1e6e692a5390b02a | MATLAB | 5,008 | 309 | %plot Slice Variables
olddir = pwd; %così sto in NE.MO.
mkdir(sprintf('%s\\PLOT', olddir'));
pathname1 = sprintf('%s\\PLOT', olddir');
mkdir(sprintf('%s\\P_Slice', pathname1));
pathname2 = sprintf('%s\\P_Slice', pathname1);
numberslice = str2num(cell2mat(inputdlg('How many slices do you want to analyze?', 'Slice Num... |
d123430421fb273d554f8ab14176fb28ceb2bdeb3b23d894c1c8e1dcb544da4d | MATLAB | 5,009 | 132 | % This script is used to rescale neuropil and raw traces by a scaling factor.
% after running this script, run 'deconvolution_rescaled_traces.py' and
% then 'merge_spks_w_Fall.m' to add the according spike traces to the
% respective Fall file for further analysis
clearvars
scalingFactor = 0.86; %Trace is s... |
fbfe973833f9aad0582ac4105901c4d73cb27e644c6f5a020e201377e4bc09da | MATLAB | 5,009 | 183 |
clear
p = params_2DAA;
fpath = fullfile(p.processed_data_dir,'allData.mat');
load(fpath,'evs','tis','bvs','traces')
[cols,alpha] = chooseColors;
%% get ITI data
speed_control = 0;
[av_trials_all,err_trials_all,trans_data_all,trans_data_err_all,err_trials_full_all,trans_data_all_dr] = prepare_data_task_subspaces(p, tr... |
8171215a6b9cdfc68b5412fb11761d2ad02bf974ab61e789f890b1476afdd889 | MATLAB | 5,010 | 114 | global Vinj
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Load data and build models
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
import_data;
build_models_met_PT;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Settings
%%%%%%%%%... |
af1975fb3db14fe647e2806b6e58eb3332d0636ccf746988f5ee9d61b0538a0b | MATLAB | 5,010 | 105 | function AutoLFP
%21sÚÉBreakPointðu¢Ägp·é
close all;
clear all;
cd('C:\Users\kit\Desktop\WR_LVdata');
% dpath = uigetdir('C:\Users\kit\Desktop\WR LVdata');
[fname2,dpath] = uigetfile('*');%ÅÌt@Cðwè
cd C:\Users\kit\Desktop\CheetahData
Spath=uigetdir;
eval(['fnameEV=''',Spath,'\Event... |
dccdd747ade92f26269593740a62496b936473012e5400b7a9bf27e0bfcbce35 | MATLAB | 5,017 | 153 | % create psth vector from all data
%% load all data files
clear
clc
[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
%% calulate
count = 0;
nds = [10,8,6,4,3,... |
c741bcc60eb855a6b49591cda4666e3366a4a528ad692c8b6582cb3854c4df10 | MATLAB | 5,022 | 128 | function eeg_synth = Synth_EEG(sig, fs, varargin)
%
% eeg_synth = Synth_EEG(sig, fs)
% eeg_synth = Synth_EEG(sig, fs, duration, win, AR_ord)
%
% *************************************************************************
% * Generating synthetic EEG signal using Autoregressive (AR) model and *
% * innovation filter. ... |
e438e37b00fb83628b038cdeba21fa215ecbc476ff0e8707bec621719c84d77b | MATLAB | 5,023 | 127 | % Function that Look for Euler Cycles at Hebbian Sequence of Neural Ensembles
%
% A cycle is the realization of all ensembles j,k,..,z from ensemble i-th
% Until ensmeble i-th relizae again
%
% Input:
% ET: Hebbian Sequence of Neural Ensembles
% E: List of ALL Ensembles
% Ouput:
% TableCycle: Cell :
% Typ... |
f1eedecd59645f73079d84d13ee25a62b8461f04e30d239c9c969ff47dec1ec0 | MATLAB | 5,025 | 146 | %Author: Tatjana Schmitt, 2019-2023
function [idx_vectors, radial_vectors, radial_vectors_BF, radial_vectors_mean_BF, ...
radial_vectors_mean_BF_smoothed] = vector_analysis(BF, stats, varargin)
% creates vectors with specific step size and plots BFs along these
% vectors, calculates mean BFs and smoothes data p... |
6d7772ec5c9120e7fa7b49634289e8b63f556779765dafec06892903251aff62 | MATLAB | 5,029 | 166 | function [h,M,CI,p] = rst_2ttest(gp1,gp2,varargin)
% performs a robust two samples test, ie a percentile bootstrap on the
% difference of the estimators
%
% FORMAT
% [h,M,CI] = rst_2ttest(X,Y)
% [h,M,CI,p] = rst_2ttest(X,Y,'alphav',0.05,'estimator','median','newfig','yes')
%
% INPUTS
% - X and Y are a n-by-p matrix,... |
7bd4af1ba2e205c19fafabbac132f9f5605496c881ca37f374848f63dc24c985 | MATLAB | 5,035 | 103 | function hFigTime = plotFigTime(hFigTime, hClust, hCfg, selected, maxAmp, iSite, channel_idx)
%DOPLOTFIGTIME Plot features vs. time
timeLimits = double([0, abs(hClust.spikeTimes(end))/hCfg.sampleRate]);
% construct plot for the first time
if ~hFigTime.hasAxes('default')
hFigTime.addAxes('defaul... |
371c1b6947b52db980d8c6cd3b127fa2d81110063a79494e73c4dc2ac8c6089a | MATLAB | 5,040 | 152 | % This program is to calculate and plot the results of COPE between tphssk and control.
%
% Figure 3 & Supplementary Figure S4
%
%
% by Hiro Taiyo Hamada, Araya Inc.
clear all;
close all;
addpath(fullfile(pwd, '/programs'))
datafolder1 = '/data/COPEResults/session3';
datafolder2 = '/data/COPEResults/session4';
% tp... |
573d3e24fad7ad3aa96dcf99b41ce77e9a9f76015b9d0b5531d446d6e9aef6cc | MATLAB | 5,040 | 130 | close all;
clear;
clc;
resultfname = 'testProcessSeizureEEGAllSpectralFeatures3.txt';
% this is the same as the previous one; except that the feature vectors are
% kept in the frequency domain (look at F, F1, and F2 and how they are
% transposed). This gives equal number of features for all subjects
% regardless of the... |
e068ea69cdfb4bfde7c0909b563c10c7894dac08dc964c12f2cb55bec3daa98f | MATLAB | 5,049 | 173 | function [spec_out res] = get_water_width(spec_in,do_plot)
if ~exist('do_plot'), do_plot=1,end
base_line_cor=1;
get_integral = 1;
spec_out=spec_in;
for nbser = 1:length(spec_in)
fid= mean(spec_in(nbser).fid,2);
info = spec_in(nbser);
spec = info.spectrum;
resolution1 = spec.spectral_widht... |
72f5cdca67a5db65404d205e67dea790446dd563c733cdb2e7dcd5c07f452be6 | MATLAB | 5,050 | 185 | function F=irf(X,y,N,w,Q,A,method)
%%%%%% interval random frog (IRF) for wavelength interval selection method %%%%%%
%+++ X: The data matrix of size m x p
%+++ y: The reponse vector of size m x 1
%+++ N: the number of iterations
%+++ w: the fixed window size to move over the whole spectra
%+++ Q: the initialized ... |
32334a126f34feaca467f7b78270e4b5698f6d238487342497de1e1fe7d64bc7 | MATLAB | 5,051 | 175 | function Get_spikes_pol(polytrodes, varargin)
% function Get_spikes_pol(polytrodes, par_input)
% Make polytrode spikes detecting and concatenating the spikes of all the
% channels in the polytrodeN.txt used.
% Saves spikes, spike times (in ms) and used parameters in filename_spikes.mat.
% input must be a vector with ... |
98f076772509d86946e276160a7e4e80dd75bb1cc8531d0a07a402de87c1df34 | MATLAB | 5,051 | 135 | function output = calcPopulationGeoMetrics(neuralTrajectory, weights, timeBinVector, initialSSIdx, finalSSIdx, nWins)
%% input args
% - neuralTrajectory is array of factor scores (itime, idim)
% - weights is the fraction of shared variance explained by each component
% (optional)
% - timeBinVector is the times (first ... |
2c7f26681c48e49daaed4cc7f37ba374634cb51c9124abd3646660b903cbdfa9 | MATLAB | 5,052 | 120 | % az összes személy összes session-jén (grandmean) méri a csúcslatenciát
% ezt felhasználva tudjuk a késõbbiekben mérni az amplitúdót
% epoch length: -0.1 0.9 (512 points)
% measures the peak latency on all sessions of all persons (grandmean)
% epoch length: -0.1 0.9 (512 points)
clear all;
% close all;
%-... |
e880a870d6f4c4c0769a9469cff208207bb76b499386d4913068286ef546adfc | MATLAB | 5,054 | 127 | close all
clearvars -except Behav_path Path_figures Path_variables MEG_path
% find sensors at which ASSR is significant for Placebo sessions
SubjectID={'S01' 'S02' 'S05' 'S15' 'S19' 'S20' 'S22' 'S24','S21','S25','S23'};
Drug=[3 1 1 2 3 2 3; 3 1 3 2 1 2 0; 2 1 1 3 2 3 0; 1 3 3 2 2 1 0; 2 3 1 2 1 3 0; 1 2 3 1 3 2 0; ... |
bf3cd4b7ed7e8ffd1997f0dcbc8fac3f72814485292193114c2bd1c01e95ec15 | MATLAB | 5,055 | 168 | function mnl_VisualiseSomasDiscriminable(Somas)
EuThresh=0:0.01:0.5;
nSomas=size(Somas,2);
maxDim=size(Somas(1).VecNormMean,2); %The maximum number of dimensions
Chans=1:1:maxDim;
for i=1:maxDim
[PermCombo]=mnl_PermsNoColumnBias(Chans,i);
Perms(i).PermCombo=PermCombo;
end
%% Create the matrix to compare
SomaVal... |
479175c7cedb447c649d3244e7f626bc6da7bc7830cd321bd4bba6172dc9abaf | MATLAB | 5,056 | 123 | function [cout,h]=contourspline(varargin)
%CONTOURSPLINE Contour Plot with Cubic Spline Fit Contours.
% CONTOURSPLINE(X,Y,Z,N) creates a contour plot having N contour levels
% from the matrix Z, treating the values in Z as heights above the X-Y
% plane. X and Y are either vectors defining the X- and Y-axes with
% lengt... |
7cb744b30866c007951d305365d843660ed3417007bc974ab2edc75245581ac9 | MATLAB | 5,056 | 99 | %% Date: July 26th 2021 Programmed by: Deirdre Bolger (ILCB)
% Script to prepare the *.mat file with the pre-processing and analysing
% parameters for the EEG-VR_LearnL2 project.
%*********************************************************************************
function EEGVR_L2_create_matfile()
mystruct = []... |
897c197c526f9a50d5eb423dcbee29dfa4907121eb1830ac91a7fe69753e73b5 | MATLAB | 5,057 | 170 | function [conc result]=get_result(dir_sel,waterref,res_freq)
if exist('res_freq','var')
RESONANCE_FREQ = res_freq;
else
%for 3T data
RESONANCE_FREQ = 123.25;
%for 7T data
%RESONANCE_FREQ = 296.5917;
fprintf('taking default resonance frequency to %f, to change add as 3 input argument, this will ... |
5973bdffa1135accbc9406406525f7c5ed0f959b3df53d7d2eb5f2c4415dc685 | MATLAB | 5,059 | 119 | function supp_fig2_euclidean(folder, save)
%% Supplemental Figure 2: Density vs Euclidean distance
% Subplots/information:
% - Imagesc of difference maps
if nargin == 0
folder = 'All';
end
[eu, dens] = load_euclidean(folder);
ipsi = dens.ipsi; contra = dens.contra;
load('structures', 'structures', 'regions');
[~,... |
18a0288fcb2f010b5907a80e7edb9fbbb529ef04ff9a1fafb51964eee01400d1 | MATLAB | 5,065 | 158 | % Copyright (c) 2008-2026 the MRtrix3 contributors.
%
% This Source Code Form is subject to the terms of the Mozilla Public
% License, v. 2.0. If a copy of the MPL was not distributed with this
% file, You can obtain one at http://mozilla.org/MPL/2.0/.
%
% Covered Software is provided under this License on an "as is"
%... |
42f50311df31a30c8526c9046bf78442273a676d3808d4936c6edfcfb7b7acbb | MATLAB | 5,074 | 146 | function [h,CI,p] = rst_pttest(varargin)
% performs a robust paired t test, ie tests if an estimator of the
% difference between pairs differs from zeros.
%
% FORMAT
% [h,CI] = rst_pttest(X,Y)
% [h,CI,p] = rst_pttest(X,Y,estimator,plot_option,alpha,nboot)
%
% INPUTS
% - X,Y are either vectors or a matrices, in the lat... |
6666d7f01d4006b1ec327b663060d8de1c08ef3a9f39288cbafed7294ff7a447 | MATLAB | 5,076 | 253 | function varargout = plot_lcmodel_result(r,field_list,par)
if ~exist('par')
par.scale_to_pool_mean = 0;
par.same_fig =0;
par.xshift = 0.2;
par.markersize = 6;
par.markerstring = 'o';
par.dottest = 0;
par.ylim='';
par.ygrid=0;
par.xgrid=0;
par.save_dir='';
par.ind_group='';
end
if nargin==0
va... |
c25ed367920cfd642cb78d5d25132c691896f145bf9f8a8c2cf830e03f68f9cb | MATLAB | 5,076 | 135 | % személyenként az összes session-jén (grandmean) méri a csúcslatenciát
% ezt felhasználva tudjuk a késõbbiekben mérni az amplitúdót
% epoch length: -0.1 0.9 (512 points)
% measures the peak latency on all sessions (grandmean) per person
% we can use this to measure the amplitude later
% epoch length: -0.1 0.9 (51... |
32fa514ff7a3a9cafde1950cc94f4e2b376bd64e6b7613f0f11838c8c1d52034 | MATLAB | 5,078 | 181 | % A test file for Uterine Contraction
%
% Reza Sameni
% Aug 2020
clear;
clc;
close all;
% fs = 4000; % Sampling frequency
% alpha = -0.1;
% UC_iden_wlen = 5.0;
% UC_avg_wlen = 15.0;
% Tachysystolic_th = 40;
% EHG_fl = 2.0;
% EHG_fu = 400;
% EHG_env_win_param = 0.02; % envelope calculation window length
% data = load(... |
96467320eefd2876aaec3ce494a934e459d5dd2a3f277e68327addc004ad822d | MATLAB | 5,084 | 183 | %% Speed Time series analysis https://www.sciencedirect.com/science/article/pii/S2211124718316437#fig3
%Zé Henrique T.D. Góis - Characterizing Speed Cells in the Rat Hippocampus
rng shuffle
clear all
close all
%%
load sample_data.mat
%%
speed_score=table;
numofshuffle=1000; %number of shuffle
sr=60; %sampling rate of... |
8d5918445614f2ad5808fe87d1c1928879df2b14516be89687614297144765bd | MATLAB | 5,086 | 150 | % 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 Neuroscience,... |
c6397e67e1d5d8ffb81a614fcb623a27261d768f478420b081b7c5d96642b3aa | MATLAB | 5,093 | 95 | %% single cell simulation: to collect mean V (and firing rates)
% Input: NeuronType 'e' or 'i'
% InitialStates V and all Gs
% NeuronNum Number of NeuronSimulated. Generally we don't
% want this number too large.
% Output: meanV, fr Collected from all neurons, ... |
51e1092cab4ccdf34591e45ef1385a3b804311b6f79a70ee0d65d5f8666147bf | MATLAB | 5,094 | 167 | close all; clear mex;
%datasetName = 'CIFAR';
datasetName = 'CIFAR-100';
funtype = 'gpu';
%funtype = 'cpu';
%funtype = 'matlab';
kCNNFolder = '..';
addpath(kCNNFolder);
addpath(fullfile(kCNNFolder, 'matlab'));
if (strcmp(funtype, 'gpu') || strcmp(funtype, 'cpu'))
kMexFolder = fullfile(kCNNFolder, 'c++', 'build'... |
c4f25f0fa997b7f98244088e76272fdf2d3af1acdcb068cc1ebb514044f8a2fd | MATLAB | 5,094 | 111 | function [mat, staMaxImm, staZeroImm, staShuff50, staShuff95] = getFP2syncSpike(units, beh)
%
% [mat, staMaxImm, staZeroImm, staShuff50, staShuff95] = getFP2syncSpike(units, beh)
%
%
%%
bin = 0.02; window = [-0.01 0.01]; % window for PETH
uni = unique({units.rec}); % How many unique recordings are t... |
c88d5bbcf937fe8a961cdb353a6daebbc8a2d60c2014574ffe75262eb3cd6734 | MATLAB | 5,095 | 109 | % This program is intended to extract
%
%
% time series of BOLD signals from session4(awake)
%
%
% by Hiro Taiyo Hamada, Araya Inc.
%close all; clear all;
addpath(fullfile(pwd, '/programs'))
% Anesthesia2nd
datapath_session4th = fullfile(pwd, '/data/session4');
listing_tph = makeList(datapath_session4th , '*TPH*')... |
6280245f28569cc184210ec7e162375d6053160f6160be9f6999e22186ee404a | MATLAB | 5,099 | 148 | close all
clc
clear
% results = importdata('J:\ECGData\PTB\AllDataSmootherResultsPTB06_ComparisonWithWavelet2_Backup.txt'); fs = 1000;
% results = importdata('G:\Sameni\Documents\Papers\Journal 40 (Spline ECG Filtering)\CODES\AllResultsRawFiles\AllDataSmootherResultsArrhythmia06_ComparisonWithWavelet2_Backup.txt'); fs ... |
6c0de0988bfd5c2e925054f1e21a8ef34b09bc99ef5d439693e5b463ce7a38d8 | MATLAB | 5,099 | 183 | % This program is to calculate and plot the results of COPE between tphssk and control.
%
% Figure 2b & Figure 5a
%
% Procedure:
% 1. extract COPE results of tph blue, tph yellow, wt blue, and wt
% yellow.
% 2. plot ROI names
% 3. plot results
%
%
% by Hiro Taiyo Hamda, Araya Inc.,
clear all;
close all;
addpa... |
f137cfad57cc739b8884b97688080ac5dd0dbe57da4f1ae43d307eda994bb61f | MATLAB | 5,102 | 129 | function penalty_factor = OptimalSmoothnessFactor(xx, bb, ss, mode, SmoothnessFactor, penalty_factor0, signorm, ACCURACY, MAX_ITERATION, FORGETTING_FACTOR, penalty_factor00)
if(mode == 0)
penalty_factor = SmoothnessFactor; % gamma
elseif(mode == 1)
penalty_factor = 1/SmoothnessFactor; % lambda
elseif(mode == 2)... |
c46be055a5a9e498be6830e41f7cb8775d3becf65e8860617b322bb4c7e0d14a | MATLAB | 5,103 | 133 | % This program is intedended to contrast of peak intensity between CBV from Grandjean2019
% and %BOLD under anesthesia
%
%
% by Hiro Taiyo Hamada, Araya Inc.
close all; clear all;
addpath(fullfile(pwd, '/programs'));
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% data preparation
%%%%%%%%%%%%%%%%%... |
3c2e66663aab47c54bb336a18d475019f21b23afdbed454bbed886b693df7869 | MATLAB | 5,105 | 156 | % Event related potential extraction using nonstationary component analysis
%
% Reza Sameni (reza.sameni@gmail.com)
% Copyright June, 2019
%
clear
close all
clc
load BPFilter_1_20Hz.mat h
template = load('SampleEEGwithERPtemplatesRefMethod.txt')'; % Reference ERP templates provided by Dr. Marco Congedo (marco.congedo@... |
e5e7b7e6ec933a907c5ad3998cfc38a2c25dfd027a1b2d2bd0bcd5f79c090753 | MATLAB | 5,109 | 140 |
%{
----------------------------------------------------------------------------
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... |
686ec9521bfdae139c3ac1e918f0cb9e16be5b411ba1730426e8216a63bdb835 | MATLAB | 5,110 | 109 | % This program is intended to extract
%
%
% time series of BOLD signals from session3(anesthesia)
%
%
% by Hiro Taiyo Hamada, Araya Inc.
%close all; clear all;
addpath(fullfile(pwd, '/programs'))
% Anesthesia1st
datapath_session3rd = fullfile(pwd, '/data/session3');
listing_tph = makeList(datapath_session3rd , '*TP... |
5dea167cb41fda100c3d2d4dc93df8f5dc6b9a70b13a45508fed69cd7d9b316b | MATLAB | 5,112 | 157 | function success = save(obj, filename, exportAdv)
%SAVE Write parameters to a file
success = 0;
if nargin < 2
filename = obj.configFile;
end
if nargin < 3
exportAdv = 0;
end
if isempty(filename) && isempty(obj.configFile) % passed an empty string and no config file
... |
abd270c19de7d879d9b811d9fed9150b9bce3f4eca9720cf8316b03123c77c94 | MATLAB | 5,117 | 121 | function Rects = Projection_Correction(W,v)
% function Rects = Projection_Correction(Iw,v,Im,XY_Eval,Cxy,Rects,At,Medial_Tangent,Rx,Rz,Scale_Factor,Corrected_Plane_Angle_Func)
% At
Cxy = [W.Vertices(v).X , W.Vertices(v).Y]; % Just for readability.
Midline_Distance = W.Vertices(v).Midline_Distance; % abs(W.Verti... |
3d5656b6611f069fa63d4d1889acbd4c71428a9c9a079c636401144c4ce69b19 | MATLAB | 5,120 | 145 | % extract traces in .smt and save as .txt, a file or all file in a folder //MJ 2121
% included option to write as a time series file (only works for two channels) // ATB nov. 6, 2021
clear all
%% Settings
%path = '/Users/brunger/Dropbox/archive/publications/2021/airway_project/source_code/smCamera_conversion/smt_conv... |
36f83f8980323f697a67de2b9b658c64c826ca662ce30eb6aa9f781fab9ecf41 | MATLAB | 5,121 | 174 | % This program is to contrast peak and timing of BOLD across session 1 vs.2
%
%
%
% by Hiro Taiyo Hamada, Araya Inc.
clear all; close all;
visualizeAllTimeSeriesSession1st
visualizeAllTimeSeriesSession2nd
color = zeros(2, 3);
blue = [0, 1, 1];
black = [0, 0.2, 0.2];
color1(1,:) = blue;
color1(2,:) = black;
ROIpath... |
d18c428bea76ba4d5176d0adbe34fe619981d95f6965a429366cc4c4d169da3a | MATLAB | 5,121 | 159 |
clear all
close all
cd 'I:\My Drive\ELYASHIV\PFC_paper_results_after_revision\effect size\f5\G_DECAY'
PHb_tmp=load('persistence_table_PHb.mat');
PFC_tmp=load('persistence_table_PFC.mat');
intensity=7; % highest intensity
smooth_factor=1;
%% Process PHb
PHb_psth=PHb_tmp.presistenceT.full_psth_matrix;... |
3d20c9ff4a67e5e5d28778f79682812969de3d4930b58e37acb9b1b105cf7e52 | MATLAB | 5,122 | 180 | function model=sopls_mod(X, Y, LV, pret)
% sopls_mod Trains a sequential and orthogonalized PLS model
% The function sopls_mod calculates a sequential and orthogonalized PLS
% (SO-PLS) multi-block regression model on training data.
%
% INPUTS:
% X = cell array of predictor blocks (of length nblo... |
8e6c9084a0ff23eac5c7be38307691b03bfe630b42e4fa7cc242f2ec4a3e12ea | MATLAB | 5,124 | 177 | function gui_s (x, y)
%
% This file is used by FASTICAG
% The save dialog for saving the results
% 24.8.1998
% Hugo Gävert
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Global variables
% Handle to the window
global hf_FastICA_Save;
% Handles to some of the contr... |
dc5d937b83074cf45e90a55a7611aad1becd31a08fde61c66d5714041ce3ed0d | MATLAB | 5,125 | 167 | 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,'svm_reg');
saveData = 1;
saveFigs = 1;
n_rep = 80;
aa_sessions = 3:9;
n_tr = 300;
... |
883223f0f708ce0e77f69f98bd02ca3cd6023c373d72334283eef7be0e8dcce0 | MATLAB | 5,126 | 145 | % extract traces in .smt and save as .txt, a file or all file in a folder //MJ 2121
% included option to write as a time series file (only works for two channels) // ATB nov. 6, 2021
clear all
%% Settings
%path = '/Users/brunger/Dropbox/archive/publications/2021/airway_project/source_code/smCamera_conversion/smt_conv... |
14e9148caf00c2622ec91e3a2a011bbb2c65268fbfec054ac62e6e99b9997e05 | MATLAB | 5,127 | 94 | CurrentFolder = pwd
FigurePath = [CurrentFolder '/Figures'];
addpath(CurrentFolder)
addpath([CurrentFolder '/Utils'])
addpath([CurrentFolder '/Data'])
SaveFolder = [CurrentFolder '/Figures/Demo082721/'];
addpath(SaveFolder)
DataFolder = [CurrentFolder '/Figures/Demo082121/'];
addpath(DataFolder)
load('AllMFPixPara.mat... |
299bae5db2b2561cefa21a4fa0ceb4c06ab7aa1f8796172931c99bca74529be7 | MATLAB | 5,129 | 134 | function [spec_cor] = processing_spec(fid_struct,par)
% fid_struct_cor = processing_spec(fid_struct,par)
% fid_struct is the matlab fid structure (output of explore_spectro_data.m,
% reading the raw dicom files)
% fid_struct_cor is the output containing the corrected fid
%
% par = processing_spec will return the ... |
ed45b938e6b061207b25f1ff644c607ba515d917caa3bcfd480a23ec718c67a4 | MATLAB | 5,129 | 158 | clear all
% this script contains code to reproduce Figure 4b-c, e-f
%% load data
% drag and drop corresponding file (S4 Data)
%% data content description
% Displace_ex contains the x and y displacement values for an example
% recording session alongside the corresponding running trace
% M2_drift and ... |
41e8da89bb15ebf1522ad4b45d9a3133bab79cdbe2af2dd0ea3a4f338852c32b | MATLAB | 5,132 | 122 | function [interpeaks, ref_to_out_lag] = intermediate_peak_det(x, peaks, wlen, n_peaks, varargin)
% intermediate_peak_det - Searches for intermediate peaks between a
% set of readily found landmark peaks. Useful for detecting P and T wave
% peaks from the reference R-peaks or for PCG S1 and S2 detection from ECG
... |
9712d233e3f1062465508d7172193f138fe9cb0edc05e155d3d51ffe942ccd5e | MATLAB | 5,133 | 134 | close all; clear all; clc; % cleanup the workspace
addpath('nex') % add child directory for NEX export functions in it
addpath('../') % add parent directory with TDTbin2mat in it
% change to your block path
BLOCKPATH = 'C:\\TDT\\TDTExampleData\\Algernon-180308-130351';
% set to 0 to only export timestamps ... |
7d8a6fa1608c4452af5d07d1a5fe63bccc6e583248e7a0298b1c42167fc3a04e | MATLAB | 5,135 | 140 | function p = params_2DAA(varargin)
%% set paths for reproducing analysis / plots here
% folder containing the results of data processing (signal extraction etc.)
p.processed_data_dir = 'C:\Users\Benjamin Ehret\Desktop\paper_data_final\processed_data';
% folder containing the results of data analyses
... |
eaec7b1c245a00b13d2ab3510a9089c7f0702475237a64e58d97be4244b1b14c | MATLAB | 5,136 | 197 | % Run and advance each cell and output is generated appropriately
clear all;
figure;
%% Plotting single X errorbar
clear all;
clf;
supererr(1, 1, 0.2);
xlim([0 2]);
ylim([0 2]);
title('Plotting single X errorbar');
%% Plotting single X errorbar, empty Y
clear all;
clf;
supererr(1, 1, 0.2, []);
xlim([0 2]);
ylim([0 2]... |
c5907d66bb55ca8a3eb18f7a857ad81917cbbccb60749cd586bd715ae7a21dd7 | MATLAB | 5,137 | 180 | function [bc,K]= rst_RASH(varargin)
% Computes the density estimate of data using ASH or RASH
% - Average Shifted Histogram is taken from Martinez and Martinez - Comp
% statistics handbook with Matlab.
% - Random Average Shifted Histogram algorithm is coded based on Bourel et
% al. Computational Statistics and Data An... |
baec817e748ed694e934e3561aee9565a542f7534efb61bd247d73c7904cbe95 | MATLAB | 5,140 | 148 | function W1_Pattern_2_20201208
path=['C:\Users\C238\Desktop\touchcellLtRt_Hirokane'];
cd(path);
LS=ls;
LtWFRUnit=[];
RtWFRUnit=[];
LtW1Point=0;
LtW1Fire=0;
LtW2Point=0;
LtW2Fire=0;
LtW3Point=0;
LtW3Fire=0;
LtW4Point=0;
LtW4Fire=0;
LtW5Point=0;
LtW5Fire=0;
RtW1Point=0;
RtW1Fire=0;
RtW2Point=0;
RtW2F... |
1d1b4cb90ca9f31504033001dad5390d0e630c12004a800edd6bfff9ca5b601c | MATLAB | 5,141 | 148 | function W1_Pattern_2_20200302
path=['C:\Users\C238\Desktop\touchcellLtRt_terashita'];
cd(path);
LS=ls;
LtWFRUnit=[];
RtWFRUnit=[];
LtW1Point=0;
LtW1Fire=0;
LtW2Point=0;
LtW2Fire=0;
LtW3Point=0;
LtW3Fire=0;
LtW4Point=0;
LtW4Fire=0;
LtW5Point=0;
LtW5Fire=0;
RtW1Point=0;
RtW1Fire=0;
RtW2Point=0;
RtW2... |
a3199ac239293650d4c3a07a7785a527685545344b6146a07daee12864ac5b27 | MATLAB | 5,141 | 220 | clear all
close all
sigma=0.5;
Veq=-76.72;
Vth=-39.51;
Vr=-41.70;
tau=11.85;
R=118.5;
C=0.098;
tau_Ref=1;
P=10;
taus=20;
epsilon=0.02;
Areward=0.9;
Apostpre=1;
Aprepost=-1;
N_pres=100;
dt=0.1;
% Coeffs=1;
PLOTS=0;
ncoeffs=50;
Coeffs=linspace(0.11,20,ncoeffs);
wmaxmin=0.1;
wmaxmax=0.6;
nwmax=50;
Wmaxes=linspac... |
a44292741ad971fe900b4e5c0249d5fd2b527af9b4929238a1c6dc71b89df010 | MATLAB | 5,143 | 202 | %PGDRAW Sample from the PolyaGamma distribution
% X = pgdraw(...) generates random variates from PG(1, z)
%
% This file implements the Polya-gamma sampler PG(1,z).
% This is a MATLAB implementation of Algorithm 6 in PhD thesis of Jesse
% Bennett Windle, 2013
% URL: https://repositories.lib.utexas.edu/bitstr... |
5ca6d86c1f4f56a49e9a6b1c3c80cc0a5def9c0023cedb329a1ad923797469d9 | MATLAB | 5,144 | 123 | % 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 Neuroscience,... |
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