sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
81bf5fe5eae7fd8f830358431eb4962e8280ef7b4afc7eac3616462796aa51c2 | MATLAB | 3,571 | 110 | function [weights, trainerr] = cnntrain_inv_mat(layers, weights, train_x, train_y, params)
params = setparams(params);
assert(length(layers) == 2);
assert(length(weights) == 2);
layers{1} = cnnsetup(layers{1}, 0);
if (~iscell(train_x))
layers{1} = initact(layers{1}, train_x);
else
layers{1} = initact(layers{1}, t... |
254ac751d4140624ee98c9cd0a1f9b327ec1bd52528a9ef2c35a50f9381cb6bb | MATLAB | 3,572 | 87 | function [ movie,zeroMask,regCoords ] = registerMovie(p,movie,regCoords)
%REGISTERMOVIE registeres movie using turboreg. first registration
%coordinates are obtained on the a bandpass filtered and inverted version
%of the movie. The original movie is then registered with these coordinates
% registerMovie is running... |
8897dfc92e9b8d4c517a1aa0d524f2277b50a4de4adc1121ec47dce679071a76 | MATLAB | 3,575 | 105 | function [sig_depth, sig_raw2, rawNeuronLength] = getPval_long(p_threshold,folders)
%
% folders={'auc_ishizu','fof_ishizu','mpfc_ishizu'};
%
analysis_dir = eval(folders);
p_task_long=cell(length(analysis_dir),1);
depth_neuron=cell(length(analysis_dir),1);
rawNeuronLength=zeros(length(analysis_dir),1);
for i =... |
c8924f6ac9b9fb855d3ef2ef7d5a03bf55e8cdf33f7cfde462795bb8fe72edb3 | MATLAB | 3,575 | 135 | function [peaks, peak_indexes, R_prominence] = peak_det_advanced_pan_tompkins(data, fs, varargin)
%
% peak_det_modified_pan_tompkins - R-peak detector based on modified
% Pan-Tompkins method. The filters and post-detection R-peak selection
% logic differ from the original algorithm
%
% [peaks, peak_indexes, width... |
83d4106c15e67f8d196b22d672de53f3a90d02c34300b4a20584fcf84174c8bb | MATLAB | 3,578 | 93 | %% Bead plots final for paper
%load("'Q:\OneDrive - The University of Colorado Denver\From Dropbox\STED\STED Data\230822\45nmYG_DyMINvsSTED\DyMIN13_16_STED12_BeadFitResults_ROI15_close8.mat")
fig17=figure(17);
plot(1:num2compare,amp_dymin16_mean/mean(amp_dymin16_mean(1:3)),'+g')
hold on
plot(1:num2compare,amp_dymin1... |
9802efce6fe30a0e581b2dd6818dfb232eb1769df6d95cb5544995823c808c2b | MATLAB | 3,582 | 145 | close all;
clear;
clc;
% parameters
subject = 'Dog_2';
number = 19;
path = ['J:\Seizure\' subject '\'];
mode1 = 'interictal';
mode2 = 'preictal';
ch = 1:16; % desired channels
time = [7 10]*60; % in seconds
nfft = 5000 - 1;
SpectralWinLen = 10; % in seconds
SpectralOverlapPercentage = 50; % [0 99]
% load signals
[x f... |
5d3a4331978018e3f7fdb8c3a7585249e018c154826fe3b9ce97f0b7760c285c | MATLAB | 3,584 | 135 | function [estParams, LL] = fastfa(X, zDim, varargin)
%
% [estParams, LL] = fastfa(X, zDim, ...)
%
% Factor analysis and probabilistic PCA.
%
% xDim: data dimensionality
% zDim: latent dimensionality
% N: number of data points
%
% INPUTS:
%
% X - data matrix (xDim x N)
% zDim - number of factors
%
% OUTPUT... |
6e71ff14008343f73abbca9e61bff5ff2d6efae728c314400d694e656ea39b0e | MATLAB | 3,584 | 95 | function [feature_vec, feature_info] = ecg_svd_features(data, R_peak_indexes, number_eigenvalues)
% function [feature_vec, feature_info] = ecg_svd_features(data, R_peak_indexes, number_eigenvalues)
% Extract features from ECG using Singular Value Decomposition (SVD)
%
% Inputs:
% data: ECG si... |
39c2bd2ba0bf759f2d16dfe7c71b8d95c20d40e0f8801752eb5267f237d2d981 | MATLAB | 3,586 | 87 | function Kopt = senpai_estimateK(path_in, im_in, path_out, crop_idxs)
% senpai_estimateK:
% produces an estimate for the optimal K parameter for the
% senpai_seg_core.m function. The estimation is performed by running
% the segmentation multiple times with different K,
% until one K satisfies the criter... |
56f922b59812da953df36d1ec5d9ae629104a181f90ad0a6c0757fbb8916b04e | MATLAB | 3,588 | 114 | function L = list_lick_v2(listname)
switch listname
case 'ww'
L = {
%#6
'ww_lick_211211_171135'
'ww_lick_211211_172202'
%#7
'ww_lick_211128_153406'
'ww_lick_211207_170728'
'ww_lick_211207_171915'
% 'w... |
48773dd821a8dd148ed3d771baa62ea7f9caa4096b7f65f15e3933e07863bfe5 | MATLAB | 3,591 | 93 | function y = ecg_den_lti_smoother(x, varargin)
% ecg_den_lti_smoother - Linear time invariant (LTI) ECG denoising based
% on penalized least squares with smoothness priors (Tikhonov regularization).
%
% Usage:
% y = ecg_den_lti_smoother(x, filter_param, SmoothnessFactor, mode, stable_pole_mag_th)
%
% Inputs:
% x:... |
0599dcd4dd82b6c955796bdd90e39dd6d0aa044121958e24ba48a79727ce0d26 | MATLAB | 3,595 | 83 | function [lead_fields,UnitMDip] = Forward_OPM_single_sphere_input_dir(x,y,z,source_or,slots_all,normal_unit,sphere_origin)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
mean_sphere_origin = sphere_origin;
%% number of channels
Nch = size(slots_all,1);
%% voxel position in CTF and in metres... |
725d905c23f8603f6d73ac83dfabf62560a8f3b5c9a1922edd96389c162457aa | MATLAB | 3,598 | 110 | function lick_psth_summary(pvcells,resdir,issave)
%LICK_PSTH_SUMMARY Average lick PETH.
% LICK_PSTH_SUMMARY plots average lick PETH (beam break time stamps
% aligned to an event). 10 last sessions from mice are used.
%
% See also ULTIMATE_PSTH.
% Panna Hegedus
% Institute of Experimental Medicine, ... |
9191d4e95f136042ad652c2fb83e81cb4d052ef3af2d6131ec926998318b0470 | MATLAB | 3,600 | 111 | function FSIcount20200108
global dpath3
cd(dpath3)
dpath=[dpath3,'\'];
path=[dpath,'CellCell'];
FSIsum=0;
Rtcount=0;
Ltcount=0;
RtLtcount=0;
Touchcount=0;
Woncount=0;
Woffcount=0;
WonWoffcount=0;
Doncount=0;
WoDoncount=0;
tDoncount=0;
Wotcount=0;
tWoDoncount=0;
modBgracount=0;
mod98count=... |
e5fe344506a588ca024154701934ca5cd00f7204910f0acfc9058ce7eb65562d | MATLAB | 3,601 | 98 | function [ V , qDs ]= rjd(A,threshold)
%***************************************
% joint diagonalization (possibly
% approximate) of REAL matrices.
%***************************************
% This function minimizes a joint diagonality criterion
% through n matrices of size m by m.
%
% Input :
% * the n by nm matrix A ... |
50c56a7c0965ea890d876a34a533db25901136dbd741b3ebf90a0c4bee5ad8fe | MATLAB | 3,602 | 122 | 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... |
1e0521cd9d6916d76c9bff849b571529bbff29c90e45b9117b9b9b58849486ab | MATLAB | 3,606 | 139 | function writemda(X,fname,dtype)
%WRITEMDA - write to a .mda file. MDA stands for
%multi-dimensional array.
%
% See http://magland.github.io//articles/mda-format/
%
% Syntax: writemda(X,fname)
%
% Inputs:
% X - the multi-dimensional array
% fname - path to the output .mda file
% dtype - 'complex32', 'int32', '... |
497c9a77aa827d1b9f264a78523b6485e330bde54066d6d3971c21d7d26119ec | MATLAB | 3,610 | 116 | %% Reproduce Fig. 1b from deposited dataset
% David Wolf, 11/2023
%
%% load dataset
clear; clc;
load('C:\Users\David\Documents\GitHub\OXT-Wolf\data\Fig1_AON_data.mat');
% need to be updated
addpath(genpath('C:\Users\David\Documents\GitHub\mseb\'));
addpath(genpath('C:\Users\David\Documents\GitHub\MSTATS\'));
% the ... |
00f396bd0f5d98509775ff22214bcb9e7d6a9359f4b3cddebb7310d8c6046724 | MATLAB | 3,622 | 147 | % fig_nufft_emax
% compare max error of gridding interpolators
% for several choices of scaling factors
if 0 || ~isvar('st'), printm 'kernels'
J = 5;
% note: optimizing sn with N=2^8, starting with Gaussian, yielded
% slightly worse error than nufft with KB scaling factors.
N = 2^8; % for pictures
N = 2^5; % for ... |
ed071f1e879a5c881afa228eae1a1d0fd8eb923148f2b2a4f638c30f23f76694 | MATLAB | 3,622 | 109 | if exist('r_fft', 'var')
clearvars -except r_fft
else clear all
end
close all
base_folder = 'E:\data\uncaging\multi cluster cooperation\022622\cell2';
output_folder = fullfile(base_folder, 'Ca_output');
if ~exist(output_folder, 'dir')
mkdir(output_folder);
end
addpath([pwd,'\main_Caimage']);
basefolder = p... |
44b1ecae25e9a969b89b0ed6f9b846d3a3921a0695294a18200ed50871fd8960 | MATLAB | 3,626 | 112 | %% Links Stats Table Maker ################################################
% Script that makes the table to merge data from Link Statistics
% Figs
%% Read CSV Files
NC = inputdlg('Number of Conditions: ',...
'Links Stats', [1 75]);
NC = ... |
b06c6eea86a559f5fd5c32f3dc2c6f61daf5ec3c86276d5e8e65acbce4a80f7c | MATLAB | 3,626 | 146 | clear
clc
load('89_PNs_array_data.mat')
fnames = {'hex10','hex','iaa','two_oct','hxa','two_hep','ani','hex01',...
'msal','lcar','euc','chex','gua','etha','bza','ger',...
'apin','one_oc3','neem','gar','cit','lin'};
odors = fnames ;
odors2 = fnames;
fnames2=fnames;
for k=1:length(fnames2)
eval(sprin... |
bc3992a88aa461bf263f9d807554221e70f11094abb8d19dba6c0946ef9affae | MATLAB | 3,627 | 156 | function ob = block_diag(varargin)
%|function ob = block_diag(block1, ..., blockM)
%|
%| Construct fatrix2 object from fatrix2 objects
%| block_diag(A_1, A_2, ..., A_M)
%|
%| in
%| blocks{:} fatrix2 blocks
%|
%| options
%|
%| out
%| ob [nd np] nd = sum_m nrow(A_M), np = sum_m ncol(A_m)
%|
%| Copyright 2012-09-09, Je... |
21318c905e62ea725301618e1c76f56a13e1de4c522840f3522b9a19c4e364a0 | MATLAB | 3,636 | 106 | % Function to sparse deconvolve by SParSA Algorithm
% It guarantees empty non-zero drivers
% Input
% XD: Detrended Signal: Row Vectors
% FR: Fluorophore Response Responses x Length
% Mode: arg min{lambda}-> driver:[ +&- or ++ ~=0]
% no entry +&- positive and negative driver
% 0 ++ o... |
258340197358f8ec7b7d1b91a5a4bb43d21df2daecbed9b0289bc27883802eaf | MATLAB | 3,637 | 100 | function [hAxes, viableChannelDists] = plotArray(AD,varargin)
% Manage Inputs ###############################
varInputs = inputParser;
addParameter(varInputs,'hAxes','',@ishandle);
addParameter(varInputs,'view',[],@isnumeric);
parse(varInputs,varargin{:});
varInputs = varInputs.Results;
if isempty(varInputs.h... |
a165f9908c7f35c4418ef3db33e3fc47abcb732c06366d0f5f05daad2b069fa0 | MATLAB | 3,637 | 101 | 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
p = 0.05; %pvalue
numofint = 4; %number of intensities to check for response
mkdir (['significa... |
22013a76318006e6c433ba982eb7807d834d6c4dbbc8aca959dfe8ba8dc437c7 | MATLAB | 3,640 | 143 | function mask = contains(data,strings_or_patterns,varargin)
%x Returns mask on whether each string contains the pattern
%
% mask = sl.cellstr.contains(data,strings_or_patterns,varargin)
%
% Note the current behavior is to 'or' the responses such that a match to
% any pattern will return true.
%
% Determine for... |
4878c07b90a57c70cada755adb7b345298377beb2341b7ae2f809c6fb0eb4f1d | MATLAB | 3,640 | 72 | function [ConInc,FinalCompLevel,err1,datestamp] = NoiseCheckFineFitFun(ImWidth,PropComp,CheckSize,NumImages);
% [ConInc,FinalCompLevel,err1,datestamp] = NoiseCheckFineFitFun(ImWidth,PropComp,CheckSize,NumImages);
%
% function to find a likely ConInc (contrast increment) for a patch of
% noise with given dimensions to l... |
8dab90ba34a3020f163ed9470b10de136a5d3fd838d114c95d87addff4c31324 | MATLAB | 3,640 | 88 | %% Tabula rasa in Matlab and an informed user on the console :-)
clearvars
clearvars -global
close all
clc
% The following script demonstrates the currently implemented script
% capacities of Ragu. The idea is to permit the user to run the
% time-consuming parts of the analysis, namely the randomization stats in
% an ... |
c8fcb8d944cb5f29c86fac16ce45fc03bf0791b1731d5617ae5b86b85c3eca46 | MATLAB | 3,644 | 104 |
%what do you want your interval to be?
interval = 0.5; %in seconds
behav = 'Grooming';
for s = 1:length(mouseData)
% get start and stop timestamps
bouts(s).startTS = mouseData(s).discreteBehavior.(behav).timeStamp(1:2:end-1);
bouts(s).stopTS = mouseData(s).discreteBehavior.(behav).timeStamp(2:2:end)... |
ab3aee64d6ecaeb17264da8083b83b913c893828e1b5fd5ec30e49000f160306 | MATLAB | 3,646 | 89 | function WF = loadWF(data,datPath,varargin)
%LoadWF - Load waveforms
%
% WF = loadWF(data,datPath);
% WF = loadWF(data,datPath,params);
%
% Description: This code utilizes organized cluster data (with max channel
% information) to pull the mean waveforms of all the spikes from the raw
% data and it st... |
17b5b9cf974048ec73718e6a21798b7ac9b9fc0141a3c23aac9ac295bca46466 | MATLAB | 3,652 | 81 | function [clusters] = getClusterBoundary(clusters, allFaces)
% Determines the boundary vertices of given clusters within a mesh.
%
% This function identifies and updates the boundary vertices for each cluster
% provided in the 'clusters' cell array. A boundary vertex is defined as a vertex
% that is part of a fac... |
dd7afb2a5bb0fb29c4341b4689afa0fd125337cb4b41108987b1332d90b8038c | MATLAB | 3,652 | 99 | function PLV = PLV_PhaseSeq(varargin)
%
% PLV = PLV_PhaseSeq(phase_sig)
% PLV = PLV_PhaseSeq(phase_sig1, phase_sig2, phase_sig3, ...)
%
% *************************************************************************
% * Calculating Phase Locking Value (PLV) matrix (Pairwise) using phase *
% * sequences. Refer to the Us... |
bd6fae77366764c7a3aa43be1dbee9533e1209a94ecef0493e3a1c2d6c20c584 | MATLAB | 3,653 | 112 | function quickanalysis_pavlovian_PV(cellids, resdir)
%QUICKANALYSIS_PAVLOVIAN_PV Analysis of in vivo neuronal recordings.
% QUICKANALYSIS_PAVLOVIAN_PV(CELLIDS, RESDIR) is designed as an offline
% analysis tool for tetrode data and behavior, which can be executed in
% an unsupervised manner on a daily bases. ... |
8c26368f3f5c1cff799d09b61acfaf1215581ce05f2230957c7c902d8cf8fea8 | MATLAB | 3,656 | 81 | % 语义分割
clear;
clc;
load E:\TYUT\岩石薄片识别\盒8\SemanticSegmentation_Scale\CPL\GTruth_Revolve_12903.mat;
imageDir = 'E:\TYUT\岩石薄片识别\盒8\SemanticSegmentation_Scale\NET_Muli_CPL_XPL_All\Revolve_Imds_Train\';
imds = imageDatastore(imageDir,...
'IncludeSubfolders',false,...
'FileExtensions','.mat',...
'Lab... |
262b71b018594c5b15dea1c78fe75b9989237301e70f73a137ac5f7c9ded994f | MATLAB | 3,659 | 90 | function [sign, exponent, mantissa] = double_to_binary(x, dtype)
% FUNCTION: double_to_binary
%
% DESCRIPTION:
% This function converts a given number from either double- or single-precision IEEE Standard 754 format to its binary representation. It extracts the sign, exponent, and mantissa components of the number and ... |
6d2c9f8944e6b5d27d229afabc5f8116401f202fa50d2605745e6aa9da383591 | MATLAB | 3,661 | 122 | function Bursts = burst_shape_properties(Bursts, EEG)
% Gets all the information about the peaks in the burst that are not used
% to determine the bursts in the first place
% Part of Matcycle 2022, by Sophia Snipes.
fs = EEG.srate;
for Indx_B = 1:numel(Bursts)
B = Bursts(Indx_B);
Wave = B.Sign*EEG.data(B.Cha... |
9177e03cc59e000bd79f364d5ff99731f7dc1b8f3f98ec3bbaa48aaa907d09b6 | MATLAB | 3,661 | 100 | function Scores = Rect_Scan_Generalized(im,Origin0,Angle,Rect_Width,Rect_Length,Rotation_Range,Rotation_Res,Origin_Type,Im_Rows,Im_Cols,Plot0)
if(nargin < 11)
Plot0 = 0;
end
% 1---------2
% | | ------>
% 4---------3
% Origin0 is the rotation origin coordinates (x,y).
% Angle is angle of the vector (in d... |
ad29572ed155adf51037077f09d65724eab1a0633442d904c96e120118c3255b | MATLAB | 3,661 | 110 | function uninstall_eq_toolbox(arg)
%UNINSTALL_EQ_TOOLBOX Uninstall using Toolbox Installer.
%
%Syntax
% uninstall_eq_toolbox(arg);
%
%Description
% UNINSTALL_EQ_TOOLBOX uses Toolbox Installer to uninstall this toolbox.
% It must be run from the top level directory of this toolbox, which must
% contain the file info.ins... |
f713a10c4898f61cba6a631b48ce5e0f4dd6732283466d3a4100986b5a028458 | MATLAB | 3,661 | 128 | function out = orthoview(vol,varargin)
% function orthoview(vol,...)
[cvox voxdim clims useColorbar useMip useMeanip useTitles drawIms interpFact useNewFig useZeroCrop] = process_options(varargin,...
'centre',[],'voxdim',[],'clims',[],'colorbar',0,'mip',0,'meanip',0,'useTitles',1,'drawIms',1,'interpFact',1,'useNew... |
fc9c18e522a644a927c16c0f50db495e3e80b16f61b10b27496a3075e095eb3e | MATLAB | 3,663 | 76 | function update_transduction_axis(app)
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
int_idx = find(strcmp(app.popup_int_transduction.Value,app.popup_int_transduction.Items));
int_name = app.popup_int_entropy.Value;
%sel_cluster = find(strcmp(app.popup_cluster.Value,app.popup_cluster.... |
7124b07033808d2774302061b95013c856c12cf7a3cfe73a276e4a58b60d7f35 | MATLAB | 3,665 | 118 |
%{
----------------------------------------------------------------------------
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... |
952d835976aa73d1e694204bc220fec173e1d111bc5baab5d87628aadbacaff6 | MATLAB | 3,667 | 79 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% MAIN - Plot results obtained from the analysis made
% Authors: Marie-Constance Corsi
% Date: 21/07/2023
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
clear all; close all; clc;
%% paths to be update... |
ebc2d1e77ee2bdf3df8bd6100898b49989357ad82630e55b8f2b11e87f2df6ea | MATLAB | 3,668 | 76 | function update_transduction_axis(app)
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
int_idx = find(strcmp(app.popup_int_transduction.Value,app.popup_int_transduction.Items));
int_name = app.popup_int_transduction.Value;
%sel_cluster = find(strcmp(app.popup_cluster.Value,app.popup_clu... |
de25ee49e2431e4c4677cb684e769d342b842ee69386fa379e31d60493eeb7b8 | MATLAB | 3,669 | 120 | function Pnew = NewParCon2(P,nameRegs)
ParControlG = P{1};
ParPTSDG = P{2};
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
PRC1 = ParControlG{1};
% for the first regime => Com 1 = Associative; Com 2 = Sensory + limbic
newPRC1 = zeros(length(PRC1),1);
newPRC1(PRC1 == 1) = 1;
newPRC1(PRC1 == 2) ... |
4d4c13702ede627b1068656eff6be5da5def1843d92b164435d253814ced2c41 | MATLAB | 3,670 | 100 | %
% Test program for colored noise generation.
%
% Dependencies: The baseline wander toolbox 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 Technology, Tehran, Iran --... |
e62f0a8bc6583476fde884ae24b16a6233512f4bdfaf71e5ef8581e89f8fcab3 | MATLAB | 3,671 | 82 | function [spikeWindowsOut, spikeWindows2Out] = cancelOverlap(obj, spikeWindows, spikeWindows2, spikeTimes, spikeSites, spikeSites2, siteThresh)
% Overlap detection. only return one stronger than other
[spikeTimes, spikeWindows, spikeWindows2] = jrclust.utils.tryGather(spikeTimes, spikeWindows, spikeWindows2);
... |
b51e1899bbb61f4f5b70354d19cbe4e275998f71152e0e28b3dbc83296492c17 | MATLAB | 3,672 | 101 | function [burst] = getBurst(st, varargin)
%Burst characterization
%
% Description: This function will use spike times for a given unit to
% characterize burst events, defined as 3+ spikes with ISI < 50ms
%
% [burst] = getBurst(st, varagin)
%
% INPUT
% 'st' - vector of spike times for a single unit, in seco... |
db724f990faa306942d2ee70be18aa0ee5049149a59c0c49a91547dfaa96c477 | MATLAB | 3,672 | 146 | function fid = import_brucker(fi)
if ~exist('fi')
fi = get_subdir_regex;
end
if iscell(fi)
ff = get_subdir_regex_files(fi,'fid$');
%ff = get_subdir_regex_files(p,'fid.raw$');
for kk=1:length(ff)
fid(kk) = import_brucker(ff{kk});
end
return
end
%[FileName,PathName] = uigetfile('*');
[PathName,FileName] = filepar... |
35f61646a8192e0c32eae3f402b79dc01a741ebf3f9c447696692aef06885884 | MATLAB | 3,673 | 86 | function organize_miniscope_data(p)
% organization of miniscope data for all experiments
for sub = 1:p.nSubjects
sub
thisSub = p.subjects(sub);
% load data
fpath = fullfile(p.rootDir,'miniscope',['subject' num2str(thisSub)],'jointExtraction','extracted','norm_traces.mat');
... |
7dd924230160ef7897e48d2eccc6925b083e8c095fbe359c447d3fbbc50d72c4 | MATLAB | 3,684 | 116 | % 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,... |
9874c809e63a02683a2f3edd55519d95638682686f6ea9920b18d9d8ac0e0edd | MATLAB | 3,684 | 87 | function [data] = processIso(data,params)
%Process Dual Color Photometry
%
% [data] = processDual(data,params)
%
% Description: This function is designed to process photometry
% experiments with an isosbestic control. The code takes the photometry
% channel and asks the user for the modulation frequencie... |
dfc5dc89aa5da2424bc157c2bfaf7df71607fca62b1d12c75d97fa8ac78bc50d | MATLAB | 3,684 | 154 | function [mConAmpCor mSPhase mT2used] = LineShapeExtract(fid,sw)
% Provides amp and phase corrections from water only signal
% ASSUMES APODIZATION USED FIRST (Dataa first point has been halved) *******
% Checks for excessive corrections
% Assumes files already added (or a single file)containing only water
% FID... |
e4d838803ee58b6f7bb7e2d69c7c5509b863816b56b26f383692414cf2988db0 | MATLAB | 3,686 | 128 | function SpikeArray1=GetSpikeBehavior(spikes,TimeStamps, EventStrings, Evt,StartTime, FinishTime)
% global StartTime FinishTime %fname
% StartTime
% FinishTime
DurationB=FinishTime-StartTime;
LenE=length(TimeStamps);
StartT=[];
StopT=[];
for n=1:LenE
if Evt(n,end-14)=='1'
StartT=[StartT Time... |
179563abd78ae892d821021a7ebe1459d7c0b1b35d2c8a04fd330793ca02d4a8 | MATLAB | 3,687 | 77 | % 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
% NeEx, Map_Ext: Extended index proje... |
6b63b00f0a273d1e0399c8a2f5e371dc07f54ccdc094866445b45c7af8e36540 | MATLAB | 3,687 | 153 | clear
close all
clc
% load ECG1
% s = data;
load ECG2
% s = data([1 4 5 6 12 15], round(0.3*fs):round(6.3*fs));
% s = data([1 3 4 5 6 7 8 12 15], round(0.3*fs):round(6.3*fs));
s = data(:, round(0.3*fs):round(6.3*fs));
s = LPFilter(s - LPFilter(s, 1.0/fs), 100.0/fs);
DiffOrder = 2; % smoothness constraint order great... |
00e7e149db79645c7a33737d4b980abbafb67f9502cb67a7251da5e50d8c2a3b | MATLAB | 3,688 | 98 | function varargout = lda_engineDH(D,dims)
% 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 and/or modify
% it under the terms of the GNU General Public... |
59b2e474daa006a013645b9b8286dde823ef1e9f943e2ad7bba0261a506a0dab | MATLAB | 3,690 | 81 | %% Figure 6A-C
dt = 5e-5;
load(fullfile(pwd, 'datasets', 'highcond_multibranch_decode.mat'))
idx_cell = 19;
idx_trials = [12,13,14,16];
idx_cond = 2;
t = -500*dt:dt:dt*(size(data(data_decode(idx_cell).idx(idx_trials(1))).EPSP_singleclust, 1)-1-500);
figure
plot(t, data(data_decode(idx_cell).idx(idx_trials(1))).EPSP... |
15de64be79bdc02beb7c11f2c4efb14c1edfc2193686fa565be31cc5e63c0db5 | MATLAB | 3,698 | 132 | function controlfilename = createLCmodel_control_laserCRE(metabname,l1,l2,l3,preproc_dir)
basis_set_file_path = '/home/romain/data/spectro/Basis_set/Gosia/First/basis_LASER_TE=65_CENIR.BASIS';
basis_set_file_path = '/home/romain/data/spectro/Basis_set/Gosia/laser/LASER/Cr/basis_Cr_TE=65.BASIS';
%basis_set_file_path ... |
8480c74a5383e8236d8d531d3f6b56985736dfa115120ac5ddd24e9ffc3c9988 | MATLAB | 3,698 | 100 | function Both_RLt_Pattern_6Seq_20200304
path=['C:\Users\C238\Desktop\touchcellLtRt_terashita'];
cd(path);
LS=ls;
RLtouchPoint=zeros(1,5);
RLtouchFire=zeros(1,5);
X=[];
RLtouchUnit=[];
RLtouchPointUnit=[];
for i=1:length(LS(:,1))
TrimFolder=strtrim(LS(i,:));
if ~strcmp(TrimFolder,'.') &&... |
393a6a2420c3e52f8d7357951b1a5fc3a4a6a87eec1f80eb44faf7b4a7ee3d46 | MATLAB | 3,699 | 96 | function model=rmsmageplot(rmsecv, lvcomb,selcrit, plottype)
% rmsmageplot Mage plot based on SO-PLS cross-validation results
% The function rmsmageplot uses the results of sequential and orthogonalized
% PLS (SO-PLS) multi-block regression model in cross-validation, to
% display the RMSECV as a function of t... |
c5ce807ba86aaf04c3e9c753c2b3741fbc19e3f1e09981baa9756b93e9685dfc | MATLAB | 3,705 | 122 | %This file was me messing around with the COM interface via .NET
%
%Due to the interface code I would need to write most of what I need in C#
%and then call my code.
%
%The COM interface exposes the raw data where as the C SDK only exposes
%data as floating point data (single).
%
%For now I'm going to hold off on doing... |
4455c5e361bfd69f4bee3a6eb1882ed3669e5b3822c6b421a73de1d8f3a94647 | MATLAB | 3,710 | 118 | function processSession_r2overTime(inputFileName,outputFileName,dataDir)
%% load session
load(fullfile(dataDir,inputFileName))
%% process trials
% fitler trials to the ones we want to analyse and sort according to
% behavioural state
trialsSpeed2D = trials.Speed2D;
trialsSpeed2D(1) = [];
tsd = trialsSpeed2D;
% spl... |
b8617d903230518dc333f82245907eb38e89a16835d2fa27c36df199f8a263ad | MATLAB | 3,710 | 63 | % Authors : Simon Wadle 2019-2023
%function reads time point from PrairieView voltage recording files and
%converts it to frame time points
function time_points = voltage_time_points_frames_random_order(csv_filename, varargin)
% normalizes frames to real time points in ms and frames
% output is a cell array with... |
5c2dda2652750880e3d290cc9e0559ed1c0cf8452ef90bbd1e3f01464a3a55d8 | MATLAB | 3,712 | 112 | %% Silicon probe recordings
% File paths for MSessionExplorers
load('E:\seFilePaths_SiProbe');
% load data array
load('E:\Data_array\AllTrials_10bin_Smooth\data_array.mat')
% load('E:\Data_array\AllTrials_100bin_noSmooth\data_array.mat')
% Select sessions with interested recording areas
recSites = {'left S1... |
6af2010733e5fdc71d634383f0f2472d7cb5b11da67a59126caac9eb655b69e0 | MATLAB | 3,712 | 113 | function supp_fig5_weighted_dos(folder, save)
%% Supplemental figure 6: Weigted DOS: # of synapses along shortest path
% Bilateral synapse matrices
% Distribution for synapses, ipsi/contra
% Per region
%% Load
if nargin == 0
folder = 'All';
end
load('structures', 'structures', 'regions');
load(fullfile(folder, 'd... |
0f1366465cceff14263b1984c8f78c3450dcd8b92c7a9c89e776a1052651986f | MATLAB | 3,715 | 75 | function [ shuttle_trials,no_shuttle_trials,action_start_times,trial_nums,trial_spds ] = collect_t2_d1_shuttles(p, traces, bvs, tis, speed_control,action_aligned)
spd_dims = 18:22; %dlc
if action_aligned
pre_steps = 15;
post_steps = 5;
else
pre_steps = 25;
post_steps = 75;
... |
7f7dc21f91435ba4833cf8430bd335d6e138e9d7036b198528512a45cd51c014 | MATLAB | 3,717 | 90 | function calculate_IE_responsive_fun(file, path)
if ~exist("file", "var")
[file, path] = uigetfile('*.mat','MultiSelect','on');
end
windows = {40:50, 40:60, 40:45, 40:55, 65:125, 75:125, 85:125, 95:125, 100:130, 140:150, 140:160, 140:155};
relevant_windows = [1, 5, 10];
win = ["early"; "steady"; "off"];
cd(path)
d... |
c1ab91d3366a2d1c9fb6c4893146e6cda22d3bbd2841c031be52536204c72e86 | MATLAB | 3,717 | 98 | %% PERMANENT NOTES # # # # # # # # # # # # # # # # # # # # # # # # # # # #
%
% Manual Mode is divided in two parts->Automatic and Standard:
% [ Necessary to know the statistical power of the Automatic Mode,
% Getting insohgts about -+ and -- (false+ & false-)]
% Transients are calculated from denoised signal (wavelet... |
3385e3f2863876b6ec6c9aaff81d2759927d0f3cdc2fca7ba98da6891ae948d1 | MATLAB | 3,718 | 68 | function cellcount20190716
path='C:\Users\C238\CheetahWRLV20220213';
cd(path)
LS1=ls;
Cellsum=0;%% SÄÌ×E
Rtcountsum=0;%% E«Ì^b`ɽµ½×E
Ltcountsum=0;%% ¶«Ì^b`ɽµ½×E
RtLtcountsum=0;%% ¶EÌ«Ì^b`ɽµ½×E
Woncountsum=0;%% Water onÌƫɽ·é×E
Woff... |
0132681af5d1f4b8f30dbe95b99e0d90799862e5b46531c1b7339b8cf81bf6c9 | MATLAB | 3,719 | 137 | clear
close all
clc
% load ECG1
% s = data;
load ECG2
s = data(14, 1:end);
% s = randn(1, 10000); fs = 1000;
% load ECG3
% s = data(2, 1:end);
% s = resample(s, 0.3*fs, fs);
% fs = 0.3*fs;
s = LPFilter(s - LPFilter(s, 1.0/fs), 100.0/fs);
s = s(:)';
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
12d900fdefea8649bfdb347b194bce537827379925773246aba27db7ca2f1744 | MATLAB | 3,719 | 109 | function [prms,mdl,error,approach] = ECGBeatFitterAuto(ECGmean,meanphase),
% clc
% clear all
% close all;
%
% load('SampleECG2.mat'); data = data(1:15000,8)';
%
% fs = 1000;
% t = [0:length(data)-1]/fs;
%
% f = 1; % approximate R-peak frequency
%
% bsline = LPFilter(... |
b1f939c0238d845f83458acf33b3193518a3f454ced1dfac640abe04a0782007 | MATLAB | 3,719 | 132 | %% DESCRIPTION *******************************************************
% Script To Make Raster Toy for
% Hierarchichal Clustring of
% Neural Coactivity for
% Multiple & Simultaneous Neural Activity by
% Calcium Imaging Recording
%% NEST TASKS
% Add Factor of CLuster: 0.5,1-> When Creatiing Ensembles
%% SETUP
clc; cle... |
3122783accce0e2c05a52717a83eb94e8d1842e7d6acef4885497a1167c92dd4 | MATLAB | 3,720 | 144 | function [TPR FPR PREC REC L AUROC AUPR P_AUROC P_AUPR] = DREAM5_Challenge4_Evaluation(gold_positives, prediction_raw, pdf_aupr, pdf_auroc)
%% preprocess gold standard to get graphs G and H
idx = find(gold_positives(:,3));
gold_positives = gold_positives(idx,:); %% make sure they are really positives
[gold_compl... |
6878fbfb6f60ec69a8bff7e260cdfb9abd4e01ad5dc315731b92f07f6d18d893 | MATLAB | 3,720 | 102 | close all
% clear all
clear V_sub Istep_sub out Vm Im length
idx_f = 2;
path = 'E:\data\DNAnanopore\022423\cell2_positive';
% path = 'E:\data\uncaging\physiological characterization\112120\cell5';
filename = sprintf('220226_001.sub and supra.%d.wcp', idx_f);
out=import_wcp(fullfile(path, filename),'debug');
clear len... |
acddd51b4f9d314c5222a2f6d27c119059561b65ba9497aca4431bcaada30b1c | MATLAB | 3,724 | 115 | function samplesOut = fftClean(samplesIn, fftThresh, hCfg)
%FFTCLEAN Remove high-frequency noise from samples
if fftThresh == 0 || isempty(samplesIn)
samplesOut = samplesIn;
return;
end
hCfg.updateLog('fftClean', 'Applying FFT-based cleanup', 1, 0);
nSamples = size(samplesIn, 1); %... |
3d47fdaeda32c9d069bcb15569f948b7e5b47f7a3c40e11b7c0570251098c0b2 | MATLAB | 3,731 | 68 | function wf = getWaveForms2(gwfparams)
% function wf = getWaveForms(gwfparams)
%
% Extracts individual spike waveforms from the raw datafile, for multiple
% clusters. Returns the waveforms and their means within clusters.
%
% Contributed by C. Schoonover and A. Fink
%
% % EXAMPLE INPUT
% gwfparams.dataDir = '/... |
9caa3bb9d881de8da0ecac52c1bfd89442001374476c673ebb5f1d9591c56ec8 | MATLAB | 3,732 | 106 | %% unit testing for spmup_realign_qa
close all;
%% get data
test_data_folder = fullfile(test_folder(), 'data');
time_series = spm_select('FPlistRec', test_data_folder, '^sub.*bold.nii');
plot_figures = 'off';
%%
new_files = spmup_realign_qa(time_series, ...
'Motion Parameters', 'off', ... |
de3720218358e8e21a43c12c5678e0b7932e7479ea6678baef044c2c60947720 | MATLAB | 3,737 | 123 | function [HDQ,CIQ] = rst_hd(varargin)
% Compute the Harrell-Davis estimate of the qth decile
% The vector x contains the data, and the desired decile is q
%
% FORMAT [HDQ,CIQ] = rst_hd(x,q,nboot)
%
% INPUT x is a vector or a matrix, in this case HD estimates are computed column-wise
% note that matrices can ... |
5d24c1b6e8b17d0a0bf3762a1b409d793c3d38ee5e4682598c2bea1b51ab365f | MATLAB | 3,740 | 70 | % ----------------------------------------------------------------------- %
% Function plot_areaerrorbar plots the mean and standard deviation of a %
% set of data filling the space between the positive and negative mean %
% error using a semi-transparent background, completely customizable. %
% ... |
11b7b33f34588aa41aab56c4448160db06c727710db376bdb820687c6c0e12d6 | MATLAB | 3,745 | 72 | function Tracing_Step(Image0,Vertices,Segments,Step_Params)
% 1. Scan for signal:
Scores = Rect_Scan_Generalized(Image0,Step_Params.Rotation_Origin,Step_Params.Angle,Step_Params.Width, ...
Step_Params.Scan_Length,Step_Params.Rotation_Range,Step_Params.Rotation_Res,Step_Params.Origin_Type);
% 2. Normaliz... |
502c4fe938db644bc676227ca6ec630fe134f530bdfacd8250726527f403c93e | MATLAB | 3,745 | 78 | %Author: Tatjana Schmitt, 2019-2023
function [subfield_maps_filled, subfield_borders_rotated_switched, subfield_maps, tonotopy_axes] = ...
subfield_assignment(BF_borders_broad,subfield_borders_rotated, coordinates_BF_map_rot_norm,...
coordinates_BF_map, tonotopy_axes_rotated)
%% transform subfield borders b... |
c7c181978b6268580d84c33105468061dd57ccf6a72b5a099d75f9751dce438b | MATLAB | 3,745 | 111 | function [efPxTrace,fPxTrace]=mnl_MakeSeperateMasksForEachImage(Trace,Scale,dim)
% Function to make maps for each trace
% Inputs
% Trace - The Sturctured Matrix with the points
% Scale - The scale
% Dim - dimensions of the Image
%% Step 1 - Convert the Numbers back to Pixels
szT=size(Trace,2);
PxTrace=struct('Points'... |
104043a3c4d5fd4f06ca2cc6dfc7e590a7437cc98af2789b4eb6312efb7e5408 | MATLAB | 3,748 | 108 | function [sig_neuron_longtone,sig_neuron_sustain,sig_neuron_choice,sig_neuron_prior,p_tone,p_choice]=...
getPval_afterchoice(p_threshold,folders)
%
% folders={'auc_ishizu','fof_ishizu','mpfc_ishizu'};
%
analysis_dir = eval(folders);
p_task_long =cell(length(analysis_dir),1);
p_task2_long =cell(length(anal... |
366098f917b4d54f4ec6c91bf15f1b01c9e80fe4793cca6f814282c39947f2b6 | MATLAB | 3,749 | 83 | function par = edit_par(par_in)
fields = { 'max_spikes_plot', 'to_plot_std', 'all_classes_ax',...
'mintemp', 'maxtemp', 'tempstep',...
'SWCycles', 'KNearNeighb', 'min_clus',...
'randomseed', 'temp_plot', 'c_ov',...
'elbow_min', 'int_factor', 'interpolation',...
'min_... |
98c4f5c2520426452c62cd59f30d17cbba179237474896841200611328a96ec6 | MATLAB | 3,749 | 90 | %% CorSE Algorithm for Functional Connectivity
% This algorithm calculates the correlated spectral entropy (CorSE) based functional
%connectivity between % two time series. For more information,
%<http://journal.frontiersin.org/article/10.3389/fncom.2016.00112/full Kapucu et al.(2016)>. Please cite the paper if you h... |
13637efd40ad2d62da5e3e653c8b489190a98c31503a4288fa2692c5c07145b2 | MATLAB | 3,753 | 102 | function computeQualityScores(obj, updateMe)
%COMPUTEQUALITYSCORES Get cluster quality scores
if nargin < 2
updateMe = [];
end
obj.hCfg.updateLog('qualScores', 'Computing cluster quality scores', 1, 0);
unitVmin = squeeze(min(obj.meanWfGlobal));
unitVmax = squeeze(max(obj.meanWfGlobal)... |
a6d115a38b07f22e10bfd6bf11dd20684c858b06bfe8a74269b6896eb9971c89 | MATLAB | 3,757 | 81 | %% Process Parameters for Photometry Analysis
%Created By: Pratik Mistry
%Created On: 31 January 2019
%Edited On: 26 September 2019
%
%Description: This is a script with different variables whose values can be
%adjusted depending on the photometry signal that is being processed. The
%name of this file can and sh... |
b04d2ae868042007e006063d85266c98f4919ca64659174ddf37fa01daca30c8 | MATLAB | 3,757 | 100 | function twix_hdr = read_twix_hdr_wrapper(inFile)
% wrapper to call read_twix_hdr which requires a file id already...
% gallichand@cardiff.ac.uk
fid = fopen(inFile,'r','l','US-ASCII');
% start of actual measurement data (sans header)
fseek(fid,0,'bof');
firstInt = fread(fid,1,'uint32');
secondInt = fread(fid,1,'ui... |
ac3dcb5049e9409c2da4ebf08375365b53546781882ce7cf19d743b75f6cd79d | MATLAB | 3,759 | 106 | base_path = 'H:\neuro-dynamic-covariance\datasets\task\rockland\analysis\masks\final';
raw_prob_map_path = fullfile(base_path, 'raw_probability_maps');
resized_prob_map_path = fullfile(base_path, 'resized_probability_maps');
segmentation_path = fullfile(base_path, 'MNI_segmentation');
binarized_map_path = fullfile(base... |
273f29a37261ec76f042d568be968ee8562cde2381b5da5ba5da68930d0c2131 | MATLAB | 3,760 | 86 | function Points = Find_Distance_From_Midline(Points,Axes,Scale_Factor,Step)
% This function computes the signed distance of each point from the midline.
% Dorsal is defined as positive distance and ventral as negative.
% The midline points are given from head to tail.
% Step=1 indicates that the other axes (besid... |
59b38f2f6b260f0d12dffba7ea6fb3f69e7f8a35a8e19ae40fb42a7d01480095 | MATLAB | 3,761 | 95 | %Copyright (C) 2019, Adria Tauste Campo
%Contact details: adria.tauste@gmail.com
%Copyright (C) 2079, Jiantao Jiao
%DESCRIPTION:
% Function `compute_DI_MI' calculates the directed information I(X^n-->
% Y^n), mutual information I(X^n; Y^n) and reverse directed information I(Y^{n-1}-->X^n)
% for any positive integer n ... |
6313c7dda5733a3c8607782333224a86019441131262cd6ef8d5718944222e66 | MATLAB | 3,764 | 82 | function []=mnl_ScaleBar(scale,dist,location,Label)
% draws a scale bar on the current figure
% Inputs
% scale - distance per pixel, if blank default is 1
% dist - how big do you want the scale bar to be
% location - what position on the figure do you want the scale bar (e.g.
% 'northeast','northwest','southeast','sout... |
29a677660e45b6a5b850050f66b128898b3dae83387ba92bcc92a14547e00e9d | MATLAB | 3,766 | 118 | function [spikes,thr,index] = amp_detect(x, par)
% Detect spikes with amplitude thresholding. Uses median estimation.
% Detection is done with filters set by fmin_detect and fmax_detect. Spikes
% are stored for sorting using fmin_sort and fmax_sort. This trick can
% eliminate noise in the detection but keeps the spikes... |
408aedb060d9af1323e13d933d3ef7b806d7fd356b0b9cb7ad09a28094bac76e | MATLAB | 3,767 | 132 | function out = spmup_movie(P,varargin)
% simple routine to create a movie of a time series
%
% FORMAT: spmup_plotmotion
% spmup_plotmotion(data,'coordinates',vector,'filename',name)
%
% INPUTS: data can be the fmri name or actual data, if not providing, user is prompted
% 'coordinates' (optional) are t... |
2fec3001c4cdb8484e6b318fece667436b1c8dfa85d53625b7ebd08fded12e48 | MATLAB | 3,771 | 67 | %% Create MSessionExplore filepaths for all mice
% MouseNames = {'EF0147' 'EF0148' 'EF0149' 'EF0150' 'EF0151' 'JL005' 'YT027' 'YT080' 'YT081'...
% 'YT043' 'YT044' 'YT059' 'YT071' 'YT083' 'YT084' 'YT085' 'YT086'...
% 'EF0076' 'EF0081' 'EF0084' 'EF0114'};
% SiProbe
MouseNames = {'EF0147' 'EF0148' 'EF0149' 'E... |
9fe918e48c7e6911a2ee21442b685b898987599e38316fe848812fc86869793f | MATLAB | 3,771 | 152 | function X = dtft(x, omega, varargin)
%function X = dtft(x, omega [,options])
%|
%| Compute d-dimensional DTFT of signal x at frequency locations omega
%|
%| in
%| x [(Nd) L] signal values
%| omega [M dd] frequency locations (radians), dd = numel(Nd)
%|
%| option
%| 'n_shift' [dd 1] use [0:N-1]-n_shift (default [0 ..... |
a9d51fe2a8acde382e42debc0b7bab87dbb666d60f4c050ffcb03757e4bc1ee2 | MATLAB | 3,772 | 80 | function HelpGUI()
% Check Actual Figures
List_of_Figures = findobj(groot,'Type','figure');
naux=1;
CHK=true;
HelpExist=false;
if numel(List_of_Figures)>0
while CHK
if strncmpi( List_of_Figures(naux).Name,'Keyboard',7)
CHK=false;
HelpExist=true;
else
naux=naux+1;
... |
10aebbb0d5b893904086882f19ffc99d5b9a9c90f841900aee353b88b81db9f0 | MATLAB | 3,777 | 112 | % Model of Cholinergic system influence on 2 excitatory and one strong
% inhibitory node
% Example:
%sys = StochasticWilsonWTA_Tash_Sigmoid_bd(tau_H_L,tau_H_R,c);
% gui = bdGUI(sys)
function sys = StochasticWilsonWTA_Tash_Sigmoid_adapt(sigma,d,a)
% Handles to our SDE functions
sys.sdeF = @sdeF; ... |
d8937fdf67a5f6f4f0ee6d4bc9eeca337492f4b104d619825853e72c6ae7a294 | MATLAB | 3,779 | 117 |
function p = patchline(xs,ys,varargin)
% Plot lines as patches (efficiently)
%
% SYNTAX:
% patchline(xs,ys)
% patchline(xs,ys,zs,...)
% patchline(xs,ys,zs,'PropertyName',propertyvalue,...)
% p = patchline(...)
%
% PROPERTIES:
% Accepts all parameter-values accepted by PATCH.
%
% DESCRIPTION:
% ... |
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