sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
3e686f3f782c72d54452656e0ddb22ef147dd2019056373f1a3c0284fa986d3d | MATLAB | 1,977 | 74 | % Symmetrize
% Mode 1: Symmetrize a Field with some noise
% Mode 2: add symmetric perturbations
% PertMode: 'add' add the Pert to one HC
% 'prod' multiply to one HC
function L4EUseOut = symmHCs(L4EUse,N_HCOut,NPixX,NPixY,varargin)
if isempty(varargin)
FlagPerturb = false;
else
FlagPerturb = true;
... |
bac1d9389020bbe2a5a92ea5fe4fb719d4f9b68310d2a713e7d8d38d5b3d1d27 | MATLAB | 1,977 | 55 | function save_session (app)
datafile = app.settings.file_path;
savestruct = struct();
tmp = find(datafile == '\',1,"last");
[file, path] = uiputfile ('*.ssf' , 'select file / path to save the session', [datafile(tmp:end) '_' num2str(app.settings.interval(1,1)) '-' num2str(app.settings.interval(1,2)) '_save.ssf'] );
sa... |
3a10096afbc3393919c922e601708cea58c5a5c1cd1d8a0d1681cdb30d5c0637 | MATLAB | 1,979 | 48 | function auto_hb(app)
%auto_hb checks if hb is already detected and runs hb_det_2 on the ecg if
%not
% Detailed explanation goes here
if isempty(app.hb_res)
if ~isnan(app.settings.channel_idx.ecg)
if app.settings.interval(1,1) < app.data(app.settings.channel_idx.ecg).ts(1)
app.settings.inter... |
74e1c428c78943b9520e4aa67a17d29b410e8654e433cd8b9a5a07a78c8da82f | MATLAB | 1,979 | 66 | function supp_fig6_compare(folder, save)
%% Supplemental Figure 7: Sex difference in connectivity
% Subplots/information:
% - Imagesc of difference maps
%% Load
if nargin == 0
folder = 'diff';
end
load(fullfile(folder, 'data'), 'map');
map = map.density;
N = size(map, 1);
ipsi = map(:, 1:N);
contra = map(:, N+1:e... |
27260094aff8399d545273067e9aef93435c3de0f0f46eeceb776e81e1ab3c34 | MATLAB | 1,980 | 45 | function [cleanSignal,filt] = filterFP(rawSignal,sampleRate,cutoff,order,filtType)
%filterFP - Filter raw photometry signals
%
% [cleanSignal,filt] = filterFP(rawSignal,sampleRate,cutoff,order,filtType)
% [cleanSignal,filt,adjustedSamplingRate] = filterFP(rawSignal,sampleRate,cutoff,order,filtType,downsamplefac... |
ab0e30669ff99094e510202d248ef1828eec00c2a708fb05641325238417b88a | MATLAB | 1,980 | 60 | function [data] = processFP(data,params)
%Process Fiber Photometry
%
% [data] = processFP(data,params)
%
% Description: This function is designed to process fiber photometry data
% for the lab. The function performs demodulation (if selected),
% filtering, baselining, and downsampling for all photometry ... |
85b0c58a368604f209cae52f152a748db4af89bfa2d10d1f5af4d820a5228870 | MATLAB | 1,981 | 64 | function plotAllFigures(obj)
%PLOTALLFIGURES Plot all figures
if isempty(obj.hFigs)
obj.spawnFigures();
elseif ~all(obj.figApply(@(hFig) hFig.isReady)) % clean up from an aborted session
obj.closeFigures();
obj.spawnFigures();
end
% plot sim score figure
if obj.hasFig('F... |
8677edc185c3dab9f51cdcf993ff18d4ce2a00b9dba3d8b98db4db0dbc32f327 | MATLAB | 1,982 | 56 | function P=select_data()
rootdir = '/home/romain/data/spectro/PROTO_SPECTRO_DYST/Sujet_dicom';
sujet_dir_wc = {'Sujet'};
%sujet_dir_wc = {'2008_06'};
%sujet control
%for BGL
%sujet_dir_wc = {'Sujet03','Sujet04','Sujet05','Sujet07','Sujet08','Sujet10','Sujet15','Sujet02','Sujet22','Sujet11','Sujet01'};
%for MCL
suj... |
8dd274fc3e6ac99a8795c1b73758729c47bf7debdcc1ef325f916d8e9052f19e | MATLAB | 1,982 | 69 | function make_profile(session, channel, unit)
% Make neural profiles
%
% Parameters
% ----------
% - session: scalar
% Session number with format: yymmdd
% - channel: scalar
% Channel number
% - unit: scalar
% Unit number
info = get_info();
profi... |
4463cd6aede5446ec529520a9cf57fbe9d4346e1b7db967893fb199d01a9b5c3 | MATLAB | 1,984 | 59 | function [ProcessedEventWindowData_SAVE,varnamesDATA_SAVE] = relativeBLperDFFV2(EventWindowData,EventWindowDts,varnames,varnamesDATA,setupParam)
ST1 = {'Raw'; 'Recentered'; 'DecayAdj';};
inUseST = fieldnames(EventWindowData);
STidx = zeros(1,numel(ST1));
for i = 1:numel(ST1)
if ismember(ST1(i),inUseST)
... |
ebac47fa8b9eab3d9386c5709238fc41fed47726f5802a6fe6ff0bcb2502f2b9 | MATLAB | 1,986 | 70 |
%time in s
%conc in uM
%V in um3
%Atotal and Acluster in um2
function[relTot]=plot_dynamin_fromODE(time, conc, V, Atotal, Acluster, n)
copies=conc*602*V;%conc is in units of uM. convert to copies.
c=copies(:,4)/Atotal;
ac=copies(:,2)/Atotal;
acd=copies(:,5)/Acluster;
ad=copies(:,6)/Acluster;
f=figure(n);
ax=axes('P... |
13708bece0004c0aafa1a554366eddffcdc1a150456647ce8d7506f0cf6ebdcb | MATLAB | 1,988 | 61 | function [ maxTimestamp ] = maxTimestampInTicks( nexFile )
%[result] = maxTimestampInTicks(nedFile) -- calculates maximum timestamp
% of the variables in nexFile data structure.
maxTimestamp = 0;
if(isfield(nexFile, 'neurons'))
for i = 1:size(nexFile.neurons, 1)
if size(nexFile.neurons{i}.timestam... |
65d16065a9dc97a5876934c7e570f2fbf1b433ca91622a94c97aea37c2c6dce9 | MATLAB | 1,990 | 50 | function [T_ISA,startinds,endinds]=hbf_TM_Phi_LC_ISA2(D,ci,co,ISAsurf)
% HBF_TM_PHI_LC_ISA2 makes a BEM transfer matrix for potential using LC
% BEM and isolated source approach
%
% [T,startinds,endinds]=HBF_TM_PHI_LC_ISA2(D,ci,co,ISAsurf)
% D: D matrix, cell [N(meshes) x N(meshes)]
% ci: conductivity inside ea... |
fffe9c0ae0c5948c604dbb45b2e66a76f6b53e44a050c1faa984192c924cd3d4 | MATLAB | 1,990 | 46 | filt_const = 1e-2;
vel_th = 0.01;
%Mass constants
%M_h = 1e8; %Head mass
M_h = 0.2; %Head mass make it bigger or make grapser mass smaller
% M_g = 0.4; %Grasper mass
M_g = 0.1; %Grasper mass
M_f = 0.05; %Food mass
%Spring constants
K_sp_h = 2.0; %spring constant representing neck a... |
d2663fe03d1eb4a56d544b5287490624a823e2fc34d459babc48a6c11b2d83f3 | MATLAB | 1,991 | 45 | % Computes the metastatic mass via a first order quadrature
% Growth PT follows model growth_model_PT (with parameters param_PT)
% Growth of Mets follows model growth_model_met (with parameter set param)
% flagNb = 0 or 1 depending on whether we want the number of mets to be
% computed or not
% Model is designed to be... |
3163083b09ca85f86ca2eb32aff485833b03c889e164bbfd20cb9acf6c84ed3b | MATLAB | 1,993 | 57 | %% YT 10/19
% Simplified versions of efcross3Array.m
classdef EFcross3_Array_v2 < handle
properties
mouseName = '';
sessionDate = '';
trialNums
blockType
trialType
trialResponse
visStimType
somStimType
end
... |
5c2a237d4b5f6c26a759f1d1faae1f6befaa319450b4dae3506041183e5163cb | MATLAB | 1,995 | 67 | %% CROSS-CORRELATION
cross=zeros(chNO,chNO);
delay=zeros(chNO,chNO);
CorrLength = (2*size(A,2))-1;
meancorr=zeros(chNO,CorrLength);
% ALL THE CHANNELS
for channel=1:chNO
Correlations=zeros(59,CorrLength);
y1=A(channel,:);
j=0;
valmax1=zeros(1,chNO-channel);
lag1=zeros(1,chNO-channel);... |
a5b098d8fd6910082b99e7aad5b1ce8afddf64163805198ca37fa085cd93fdb0 | MATLAB | 1,996 | 81 | % Test the instantaneous correlation of different signals
% Reza Sameni, 2009
%
clc;
clear;
close all;
% Typical ECG data. Download from: http://homes.esat.kuleuven.be/~smc/daisy/daisydata.html
load('FOETAL_ECG.dat'); data = FOETAL_ECG(:,2:end)'; time = FOETAL_ECG(:,1)'; clear FOETAL_ECG; fs = 250;
L = size(data,1)... |
a9994292e9f31b4fffe58bb58c1421fd2e1a33ef8f54778eedffbbdacede8209 | MATLAB | 1,996 | 65 | function fname = spmup_resize(P,bb,vs)
% routine that resizes one or more images to match the desired bounding box
% and voxel size
%
% FORMAT: fname = spmup_resize(P,bb,vs)
%
% INPUT: P is a cell string with images to resize (see spm_select)
% bb is the bounding box (default is [-78 -112 -70; 78 76 86])
% ... |
6f7ddc8c90bf708ceb028c3629999b9e9932d47f898fc13023bbccd7344e924a | MATLAB | 1,997 | 57 | %% YT 03/19
% Simplified versions of EFcross3_switchArray.m
classdef EFcross3_switchArray_v2 < handle
properties
mouseName = '';
sessionDate = '';
trialNums
blockType
trialType
trialResponse
visStimType
somStimType
end
... |
9e714a5ca85be7f6f79672ed779755ed181bdeb19279b7ea4472c77ba6d08abd | MATLAB | 1,997 | 58 | function V = model_ther(param, time, t_start, k_e, Ci, Vc, Vi) % param: alpha0, beta, k
alpha0 = param(1); % relative growth rate at size V0 = 1 cell
beta = param(2);
k = param(3);
M = length(Ci);
Ci = reshape(Ci, 1, M);
tau = t_start:1:t_start + M - 1; % administration times
tau = reshape(tau,siz... |
7f5706cfe348df48682282fc74e81126a60914294f3e3421c2f23185d912bf01 | MATLAB | 1,999 | 60 | clear
clc
%cluster cordinates load
[file, path] = uigetfile('clusters_coordinates.csv');
datafile = fullfile(path, file);
[~,~,raw] = xlsread(datafile);
cd(path);
%load cell display outpute (analyzed data)
[file, path] = uigetfile('*.mat');
datafile = fullfile(path, file);
load(datafile);
if ~iscell(all_data)
... |
2127723efc318fa5224d6d419333eb12907384db819c65d8e9de4e7f3cfd77a5 | MATLAB | 2,001 | 80 | function X = nufft_table_interp(st, Xk, order, flips, om)
%function X = nufft_table_interp(st, Xk, order, flips, [om])
%|
%| table-based nufft
%|
%| in
%| st structure formed by nufft_init (through nufft_init_table)
%| Xk [*Kd nc] over-sampled DFT coefficients
%| order 0|1 0th or 1st-order interpolation
%| default... |
30d2341e9a161a65160189dc77dee469c06716737603a73fb42533b3fe07e0d0 | MATLAB | 2,003 | 91 | function dist=KLdist(TRANS_1,TRANS_2)
ns=size(TRANS_1,1);
EMIS_1 = eye(ns);
EMIS_2 = eye(ns);
% check row full of zeros
%--------------------------------------
flag_zeros = 0;
S1 = sum(TRANS_1,2);
S2 = sum(TRANS_2,2);
if sum(S1)<ns
flag_zeros = 1;
elseif sum(S2)<ns
flag_zeros = 2;
end
if f... |
d71b7430fac03774731327205c3d6c16d7b58ee97ddfc8feabe0d403688c7e13 | MATLAB | 2,006 | 54 | function [modularity, nCommunity,meanCommuntiySize,stationarity,S,flexibility] = multiSliceCommunityStats(A,gplus,gminus,omega,varargin)
%% parameters and Output:
% A : cell array
% Modularity : the value of the modularity function
% NCommunity : the number of communities
% meanCommunt... |
da57c0ea097403bf434a151f9df94a5d7baaadd0d209a25badc8f5f53568ab5f | MATLAB | 2,008 | 77 | function plot_mean_resp(session, channel, unit, fold, tlim, prb, win)
% Plot response of specific s-model for given trial
%
% Parameters
% ----------
%
% - fold: integer scalar
% Fold number
% - tlim: [scalar, scalar]
% Time limits from saccade
% - prb: 2-by-1 integer vector
% [x, y] postion of a probe
% - window... |
2404b18c5ecadcb39263b695ba21f9202198d36e57d58c73359b61520914e5a0 | MATLAB | 2,009 | 32 | function PeakTouchInterval
% NXRIOÌC^[oÌs[Nªz
global CCresultRtouchWon CCresultLtouchWon RpegTouchallWon LpegTouchallWon SpikeArrayWon tfile pegpatternname trimFolder2 IntervalCount PeakInterval
findpeaks(CCresultLtouchWon,'MinPeakDistance',30);
[Lpks,Llocs]=findpeaks(CCresultLtouchWo... |
8b77418c8471fc56e9468255c73890e2eb936efd12d828e7bb22abd70e36826e | MATLAB | 2,009 | 59 | %% interactive create waveforms_file
clear
clc
[file, path] = uigetfile('cluster_info.tsv');
datafile = fullfile(path, file);
w = tdfread(datafile);
cd(path)
gwfparams.dataDir = path; % KiloSort/Phy output folder
gwfparams.fileName = 'temp_wh.dat'; % .dat file containing the raw
gwfparams.da... |
a95b0f98a907b8564f2b951832fb4b3dcbcda4ff4d6c73567f975e7a62853a19 | MATLAB | 2,009 | 46 | function [ nexFile ] = nexAddContinuousWithMultipleFragments( nexFile, fragmentTimestamps, fragmentIndexes, adFreq, values, name )
% [nexFile] = nexAddContinuousWithMultipleFragments( nexFile, fragmentTimestamps, fragmentIndexes, adFreq, values, name )
% -- adds continuous variable to nexFile data structure
... |
d7f21969cc208864381192cd84a801b2d2b33eb74ed382ffb672021a1bed7143 | MATLAB | 2,009 | 57 | function [] = supple_weight5HT(htR, err)
% This program is intended to visualize regression weights.
% Figure 5d
%
% weights session1,session2,session3,session4
% 5-ht1a: [-1.0804, -0.4457, -0.6127, -0.1996]
% 5-ht1b: [-0.9963, -0.6573, -0.1008, -0.2822]
% 5-ht1f: [-0.2012, -0.3286, -1.1479, -0.1028]
% 5-ht2a: [ 0.211... |
750f6d6d36cadf587da1a5d97f035809ee2e3f00f9d5d1520240c044c828999b | MATLAB | 2,012 | 86 | % Run the "pre" or "post" on lines 5-6 and 9-10 as appropriate
smooth = 5;
odors = {'hex','iaa','oct','cyhex','bza','cit'};
% load('pre_training_data.mat')
load('post_training_data.mat')
o = [];
for i = 1:6
% eval(sprintf("d = %s_pre;",odors{i}))
eval(sprintf("d = %s_post;",odors{i}))
s = [];... |
cc887f9b7ca009df6b21270773b128a9c5d84b6f6fc6d6d64670d31b3bfe8b44 | MATLAB | 2,012 | 69 | function makeSpikeTrain(folders)
analysis_dir = eval(folders);
disp(folders);
for i = 1:length(analysis_dir)
disp([num2str(i),'/',num2str(length(analysis_dir))]);
workfolder = analysis_dir{i};
cd(workfolder);
mkdir('spike_ch');
savefolder=[workfolder,'\spike_ch'];
%Make spike_de... |
2a14ddf6d64a26de702f079d7d029588c38c25bb5a142de24ef69d020556c655 | MATLAB | 2,013 | 71 | clear all; clc; close all
load('alldata.mat');
%% plot heatmaps for different conditions
% Odor on period: 2 to 6s, off period: 6 to 10s
conditions = {'hexon','hexoff_05s','iaaon', 'bzaon', 'bzaoff_05s', 'citon'};
onum = [1,1,4,2,2,3]; %which odor to plot in paper
odors = {'hex','bza','cit','iaa'};
time = 1/30... |
c8f11d3b20dff7a67ab9b3dde5016b132db77886cda9dbbc2d8d4e190ea518b1 | MATLAB | 2,014 | 68 | function f1 = plotFullResult(AD)
% Manage Inputs ###############################
if isstr(AD) %path to .AD file
AD = load(AD,'-mat');
end
%delete me!
AD.inputs.minRho = 15;
% Plotting ###############################
f1 = figure('Units','Normalized','Position',[0 0 1 1],'Color','w');
subplot(1,2,1);
hAxis1 = p... |
e8698497debfc52e1777fd9ba297379b4fe885d46cfa835758e5e23b85c5afa4 | MATLAB | 2,016 | 53 | function [BIC,AIC] = bicCluster(X,Y)
% [BIC,AIC] = bicCluster(X,Y)
%
% Returns BIC and AIC criteria for a clustering solution. BIC (or AIC) is
% being computed based on the log-likelihood distance, which in this case,
% is determined using within-cluster variances. Like the Calinski-Harabasaz
% index, BIC and AIC penal... |
7e22ec5bf3c0ae27dd4d02a615e5f271fc05379393535d2f78f4713318ca95e8 | MATLAB | 2,018 | 65 | function [newVectors, whiteningMatrix, dewhiteningMatrix] = whitenv ...
(vectors, E, D, s_verbose);
%WHITENV - Whitenv vectors.
%
% [newVectors, whiteningMatrix, dewhiteningMatrix] = ...
% whitenv(vectors, E, D, verbose);
%
% Whitens the data (row vectors) and reduces dimension.... |
84e4735dc707fbb07aac5327b5cb9424a56383cabe78ab3e741413c2c7700925 | MATLAB | 2,018 | 78 | function [CB_Pixels,CB_Perimeter] = Detect_Cell_Body(Im,GS2BW_Threshold,Scale_Factor,Plot1)
Perimeter_Connectivity = 4;
% GS2BW_Threshold = 0.9;
Open_Close_Disk = 1.5;
Dilation_STREL_Size = 10;
% Convert to BW and do opening & closing:
I1 = im2bw(Im,GS2BW_Threshold);
sec = strel('disk',ceil(Open_Close_Disk/S... |
14ac3bcac4ce210310244b2137774d15e32c3c44c7be05370aca51b680ddd197 | MATLAB | 2,020 | 48 | % Dependencies: carcinom, model_metastases
%% Import data
import_data
import_survival
import_covariates
%% Plot simulation of therapy on mets using parameters estimated from a vehicle group. Approximation GR = 0
% Results exported in ./ther_mets/
% Vehicle groups
manips_plot_popfit_PT_met_param_2016
% Treated groups
... |
4f618fcb95594cf1f125d2024633f78e9f22a9be1a3ab49a5d8aede563eb5012 | MATLAB | 2,021 | 68 | clearvars
close all
%addpath(genpath('cubric/scratch/sapac10/MATLAB_toolboxes'));
addpath(genpath('/storage/stella/MATLAB_toolboxes/'));
% script using the bitensorial model
%% this is the fraction of free water map, registered to the S0
fmat = load_untouch_nii('FW_reg.nii');
fmat = double(fmat.img);
disp(size(fmat)... |
58751e483d4892fe98f8ece4e904b644c632773610592d57ad93906e70837c54 | MATLAB | 2,021 | 67 | function conc = correct_water_content(conc,par)
%if ~isfield(par,'scale_fact')
% par.scale_fact=1;
%end
if ~isfield(par,'water_faction')
par.water_fraction = [0.78 0.65 0.97];
% par.water_fraction = [0.83 0.71 1%];
end
if ~isfield(conc(1),'fgray')
fprintf('no field fgray so no correction ...\n');
return
end
... |
3c8e63f67ba51cd359da6fe29e153df0d3d0b5c1171e6cff8dc373956790d894 | MATLAB | 2,022 | 73 | % 1-d example of leslie greengard's gaussian kernel-based nufft
% (type 2)
R = 4; % oversampling ratio
Msp = 12; % spreading parameter - the number of neighbors to spread
% to in each direction
M = 32; % dimension of uniform grid on which we evaluate nufft
tau = 1/M/M*pi/R/(R-0.5)*Msp; % width of gaussian
Mr... |
46bff042186c3b19287be8f66ddfe21de13ac13b0f26ca341e9412a566046258 | MATLAB | 2,022 | 93 | close all;
clear;
clc;
% parameters
subject = 'Dog_3';
number = 10;
path = ['E:\Sameni\Projects\Seizure\' subject '\'];
mode1 = 'interictal';
mode2 = 'preictal';
ch = 1:16; % desired channels
time = [1 10]*60; % in seconds
nfft = 10000;
SpectralWinLen = 10; % in seconds
SpectralOverlapPercentage = 50; % [0 99]
% load... |
8c624776352bbf7b081feed7eb5f8923a01dfe3c9bde257280e372e9c4b508a5 | MATLAB | 2,022 | 57 | classdef intch_wc_reader < handle
properties
sr
max_segments
opened_file
segmentLength
open_file
t0_segments
end
methods
function obj = intch_wc_reader(par, raw_filename)
load('intan_meta_data.mat','sr','lts','channels');
... |
1b3b2a26b8ea90c907c3f3ec99f046a47b1a08c06ba184da39753a8a059ee97a | MATLAB | 2,027 | 59 | function y = bp_filter_complex_ma_alt(x,fc,bw,order)
% bp_filter_complex_ma_alt - Bandpass filter using multi-stage moving average filter with
% frequency shift (an alternative implementation for bp_filter_complex_ma)
%
% Syntax: y = bp_filter_complex_ma_alt(x,fc,bw,order)
%
% Inputs:
% x: vector or matrix o... |
4000b53c9002562b22bae994678828198a31b2934ed47cc2bbe4e1c29202742b | MATLAB | 2,027 | 59 | function [y, W, A] = sca_nsca_component_analysis(x, f1, f2, I, order)
% sca_nsca_component_analysis - Sort components by spectrally desired components vs nonstationary components.
%
% Usage:
% [y, W, A] = sca_nsca_component_analysis(x, f1, f2, I, order)
%
% Inputs:
% x: Input data array (channels x samples).... |
55c01c343960a8cb69a5f9cc9aadecb5d9ef3161c173307a128941ca9dcbea32 | MATLAB | 2,027 | 43 | function Workspace1 = Vertex_Shape1(Workspace1)
for i=1:numel(Workspace1.Vertices)
if(length(Workspace1.Vertices(i).Rectangles_Angles) == 3)
% Vertices Angles Diffs:
Arr1 = zeros(3,4); % One row for each angle.
Arr1 = [[1:3]',Workspace1.Vertices(i).Rectangles_Angles'];
Arr1 = sortrows(Arr1,2); ... |
d399888e89cb0fb538e0f29323895fc5d5b74b0449eabb8a83663e29b7d2c6fb | MATLAB | 2,027 | 38 | clear;
close all;
cd 'C:\Users\Admin\Git\repo\ZS-DeconvNet\Python_MATLAB_Codes\data_augment_recorrupt_matlab'; % change this path to your cloned path
addpath(genpath('./XxUtils'));
addpath(genpath('./GenData4ZS-DeconvNet-SIM'))
% necessary field
system_params = {};
system_params.NA_ex = 1.17; ... |
05584d3ad7f261ad5d7a7a8308b8d01f237035b10e85d7d673d988b65b2a5908 | MATLAB | 2,028 | 78 | % Test Adults ECG/VCG scatter plots
%
clear;
close all;
% % % fs = 1000;
% % % data = load('s0010_re.txt');
% % % % data = load('s0014lre.txt');
% % % time = data(:,1)';
% % % data = data(:,2:end)';
% % % I = 1:10*fs;
% % % data = data(:,I);
fs = 1000;
load patient165_s0323lre; data = data(101:50100,2:e... |
1afe476b19eefe562277f83ddfc78e48269ee0f90a84f287208047aec1838372 | MATLAB | 2,028 | 54 | % 3D reconstruciton for sLFM
% 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 LU... |
a2a6ecfc750a799956a3faac85459ec0c966cf807b9fa2b7e269397d372ca25d | MATLAB | 2,030 | 59 | % ¶«½cellEChE2ÂAE«½cellEChE1Â@LEChE34AREChEP
WR3_90=0;
WL3_90=0;
WL4_90=0;
CountL0R0_90L23R2=0;
CountL1R0_90L23R2=0;
CountL2R0_90L23R2=0;
CountL0R1_90L23R2=0;
CountL1L2_90L23R2=0;
CountL1R1_90L23R2=0;
CountL2R1_90L23R2=0;
CountL1L2R1_90L23R2=0;
for n=1:(length(SpikeAr... |
dc52e1bac9201fdeb8a17b8f4e867c8ae57cd4eeb77fa03f47bc6feeeb71f914 | MATLAB | 2,030 | 83 | clear all
close all
clc
folder = './fit_PT_met_SAEM';
fit_r = load([folder '/fit.mat']);
iwres = fit_r.stats.iwres;
colors = get(gca,'ColorOrder');
% Scatter plots of the residuals
type_data = [];
for j = 1:fit_r.N
data_met_loc = fit_r.data_met{j};
time_met_loc = fit_r.time_met{j};... |
948069e96ae2f2a7741cbafb34c57fbd04ae1c3c932b2e414be8313ebeb53dd1 | MATLAB | 2,031 | 52 | %% compare number of responsive cells per exp in 2 data sets
clear
clc
%load responsive cells per exp (output of calculate IR responsive from data
%set 1 (PFC)
[PFC_file, path] = uigetfile('C57 cells per exp.mat');
cd(path)
X1 = load(PFC_file);
X1 = X1.responsvie_and_ie_table2;
%load responsive cells per ... |
1b75769b37b11eae76bebf1a5a923d7e0d920aa5387efa324b858fb6d5506a04 | MATLAB | 2,032 | 50 | function [movieCutouts, traceCutouts, cellOutlines, neighborOutlines] = getEventMovies(movie, traces, filters, events)
% get event movies for all events of all cells
[ areas,centroids,cvxHulls,cvxAreas,outlines ] = getFilterProps( filters );
windowSpace = 20;
windowTime = 20;
for c = 1:length(eve... |
5fa2b10aa736c1a4146c226879bb4814be03ad189e03f1218964314151913792 | MATLAB | 2,032 | 43 | function hFigMap = plotFigMap(hFigMap, hClust, hCfg, selected, channel_idx)
%PLOTFIGMAP Plot probe map
iWaveforms = hClust.meanWfGlobal(:, :, selected(1));
clusterVpp = squeeze(max(iWaveforms) - min(iWaveforms));
vpp = repmat(clusterVpp(:)', [4, 1]);
if ~hFigMap.hasAxes('default')
hFigMap.a... |
9a75be8bf61a87c7c1fe963ebf16bcfaa06e142d62824f353de26fc79ab6ae1c | MATLAB | 2,032 | 88 | function epochs = find_epochs( cc, threshold, sign,gap )
% *WAVE*
%
% FIND EPOCHS locate epochs in a logical array, based on some simple
% heuristic parameters
%
% INPUT
% cc - correlation array (1,t)
% threshold - thresholding value, to produce a logical array (sc)
% Edits by DBP 2022
% thre... |
35e3cb4af0853fc8b0867aa19b62a55421e1d0952685d6bd36957a85bc73796f | MATLAB | 2,033 | 75 | function cdata = iconRead(filename,guessalpha)
% ICONREAD read an image file and convert it to CData for a HG icon.
%
% CDATA=ICONREAD(FILENAME)
% Read an image file and convert it to CData with automatic transparency
% handling. If the image has transparency data, PNG files sometimes do,
% the transparency data ... |
ba7ea723179945275cb8c8b21e8dc593ce4c6acc0ee07f898326cb14fcedc0e3 | MATLAB | 2,033 | 61 | function [main] = shadederrbar(x,y,sem,varargin)
%Name: shadederrbar
%Created By: Pratik Mistry
%Created On: 27 July 2018
%Updated: 31 July 2018 -- Turned the main plot into a output variable.
%
%[main] = shadederrbar(x,y,sem,color)
%
%Description: This code creates a plot of the main graph with transparent
%s... |
995a9b2b40175bfebdb16ee4a0932aa461f51f9bb3e54d76ad13d4393503b0df | MATLAB | 2,035 | 69 | % ecg_gen_dtw Test Script
%
% This script demonstrates the usage of the ecg_gen_dtw function to generate
% synthetic ECG signals using the warping transformation from the phase domain.
%
% Revision History:
% 2023: First release.
%
% Reza Sameni, 2023
% The Open-Source Electrophysiological Toolbox
% https://github.co... |
d11c3cd3ea39eba73d593e3497160ecac589d22f71f380e965262911f9a46d5a | MATLAB | 2,036 | 73 | function modulation20190709
global ACresult ACresultW CCresultDrinkOn SpikeArray TurnMarkerTime RpegTouchallWon LpegTouchallWon render...
RpNum LpNum CCresultSpike locsP1time locsP2time locsP1time2 locsP2time2 pksA1 pksA2 CCresultRtouchWon CCresultLtouchWon dpath3...
StartTime FinishTime DiffMaxMinR Dif... |
97833ffd022d6b82f25e42c4716360ef2c7ce8bea45d06b94a04ad4c5075deb4 | MATLAB | 2,037 | 76 | function f = nufft_diric(k, N, K, use_true_diric)
%function f = nufft_diric(k, N, K, use_true_diric)
%|
%| "regular fourier" Dirichlet-function WITHOUT phase
%| nufft_diric(t) = sin(pi N t / K) / ( N * sin(pi t / K) )
%| \approx sinc(t / (K/N))
%|
%| caution: matlab's version is different: sin(N * x / 2) / (N * sin(x... |
997b29677c6ca234f8ccce591bb564ae91885fe382c1f03593e1d8d5b4a0d158 | MATLAB | 2,037 | 77 | clear
clc
cd('I:\My Drive\ELYASHIV\PFC_paper_results_after_revision\figure4 ( PHb)')
PHB = importdata("PHB_IR_all_ints_data.mat");
PFC = importdata("PFC_IR_all_ints_data.mat");
%% add tags
PHB.tag = repmat({'PHB'}, size(PHB, 1), 1);
PFC.tag = repmat({'PFC'}, size(PFC, 1), 1);
%% CANGE PHb CLUSTER NUMBERS... |
82c6d91f01b011ef0c67f3958a8c88ed644778b94327893991732827d44391f2 | MATLAB | 2,038 | 75 | function file_obj = readFile(file_path,varargin)
%x Opens up a LabChart file and extracts meta data.
%
% file_obj = adi.readFile(*file_path,varargin)
%
% file_obj = adi.readFile(*file_path,options)
%
% This function reads some preliminary data from the specified LabChart
% or simple data file and exposes access... |
52dc4431b5fe6fa3d2d6e6dec7aa369f0c09d4a2565461443c2ba6101562506c | MATLAB | 2,039 | 68 | function [s, W, A, B, C] = sca_notch_filter(x, fc, Q, fs)
%
% Multichannel notch filter using Spectral Component Analysis (SCA). Designed
% for removing powerline and its harmonics from multichannel recordings.
%
% Usage:
% [s, W, A, B, C] = sca_notch_filter(x, fc, Q, fs);
%
% Inputs:
% x: Multichannel input signa... |
89ea86f0f10f19cf841d49e8b168c2867b688d19ca8e2f7f9a3a7c8aa76ff0df | MATLAB | 2,039 | 64 | function[t, pvals_corr,X] = plot_PermT(Data,time,lim,green_on)
% *********************************************************************
% Date: Octobre 2014 Programmé par: D. Bolger
% Function to carry out a permutation test with correction fdr entre
% deux vecteur de données (le grande moyen pour deux co... |
cb724198ef130f385edba284819d3cb3d749c6d7a41f738a6f7d447c57c522f4 | MATLAB | 2,039 | 65 | function volume = sphereIntersection(circleCenters,radius)
% Used to estimate the SOZ, resected, and resected SOZ volume by
% inflating each channel by a sphere and computing the total volume of
% the resulting mask
if size(circleCenters,1) == 0
volume = 0;
return
end
%... |
10b73e523a0947e65474f5e76e5c075f933d89bfe49fb8f6e37db1541a66d71f | MATLAB | 2,040 | 64 | function density = calc_packing_density(dim,N,min_euclidean_dist)
%CALC_PACKING_DENSITY Density of packing given by minimum distance
%
%Syntax
% density = calc_packing_density(dim,N,min_euclidean_dist);
%
%Description
% DENSITY = CALC_PACKING_DENSITY(dim,N,MIN_EUCLIDEAN_DIST) sets DENSITY to
% be the density of a packi... |
1af586e2a272dc97d7b0d03c5fb85f1b8edfb38e7749336b581e41c2ece6bd6e | MATLAB | 2,042 | 70 | function precomp = causalInferencePrecomp(params, Tmax, varargin)
%
% precomp = causalInferencePrecomp(params,...)
%
% Perform precomputations for causalInference.m.
%
% INPUT:
%
% params - GPFA model parameters
%
% Tmax - number of timesteps of the longest trial in dataset
%
% OUTPUT:
%
% precomp - data structu... |
3f5093be5002c8076a8be979be0b3c014818eeba237f4613c314bc22296d5f22 | MATLAB | 2,044 | 58 | function [D,A,L,phi,out] = Get_Corrected_Cylinder_Params(D0,A0,L0,R4)
% Input arguments:
% D0 is midline distance (distance of vertex center from closest midline point).
% A0 is midline orientation (angle relative to tangent of the closest midline point).
% L0 is the rectangle length.
% R3 and R4 are the ter... |
0ea977b74ea6aad413d986586b19f766ad0b4ca0b79cc8af177347b9bef7a368 | MATLAB | 2,047 | 69 | % ecg_gen_dtw Test Script
%
% This script demonstrates the usage of the ecg_gen_dtw function to generate
% synthetic ECG signals using the warping transformation from the phase domain.
%
% Revision History:
% 2023: First release.
%
% Reza Sameni, 2023
% The Open-Source Electrophysiological Toolbox
% https://github.co... |
e5b8822e74a19c5bb9186b7bbf3f2076740cf0e305caaa17df09df4242ba71ea | MATLAB | 2,047 | 47 | %Authors: Adrià Tauste /Raul Adell
%Description: Function to estimate tau coefficient for each neuron separately
%Date: 5/9/2023
function [tau, resnorm, exitflag, fittedParams] = Intrinsic_timescale(spikeCounts, maxLag, win_size, win_step)
% Compute autocorrelation for different lags using sliding square filt... |
f7a044c6720f8b0c78d7eaf58bf851f3c99e20765ad6bf947a673138762b0190 | MATLAB | 2,049 | 92 | function tf = isvar(name, varargin)
%function tf = isvar(name, varargin)
%|
%| Cetermine if "name" is a variable in the caller's workspace.
%|
%| If argument is of the form 'name.field' or 'name.field1.field2' etc.
%| then this uses isfield(st, 'field') recursively as needed>
%|
%| To have isvar always return false wh... |
849573510cfbe27d100ba494e4b96c0ac49266e38ba41e5f67db9d2ab976b0fb | MATLAB | 2,050 | 61 | % Pre-process MEG in analysis app (Filter 1-150Hz, add the triggers in, notch,
% remove bad channels, mean field correct, remove bad trials, then export
% to workspace. Run convert_2_FT.m
% Sections for analysing both MEG and EEG
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Hous... |
2e5d85005975d465f655ba2b7876b695d2e7b59b3b5f3d89615c41f1a0ce2646 | MATLAB | 2,051 | 68 | function [R_Dis_statistics,C_Dis_statistics] = Length_statistics(A)
% A应当为测试所需的label图
scale = 1.226994;
[x,y] = size(A);
for i = 1:x
for j = 1:y
if A(i,j) == 94
% if A(i,j) == 1
A(i,j) = 255;
else
A(i,j) = 0;
end
end
end
[L,N] = bwlabel(A,8);... |
8d7565239a23346c86a5e10446d1e66d03ec2667502a2b4356b1aeb3e05957a1 | MATLAB | 2,051 | 75 | function String = disp_stats(Stats, P, Label)
% displays as string a statistic of interest
% From Lapse-causes
Fieldnames = fieldnames(Stats);
if any(strcmp(Fieldnames, 't')) % paired t-test
if isfield(Stats, 'p_fdr')
pValue = Stats.p_fdr(P(1), P(2));
pString = 'p_fdr';
else
pValue =Stats.p(P(1), P(2));
... |
615ba36bd12dadfda7c0de19d33606e66965e0731561405dd92ae542dd5f91e3 | MATLAB | 2,053 | 47 | function Data = Vertices_Analysis_Index(Im,Data)
% assignin('base','Workspace_Pre_0',Data);
CB_BW_Threshold = Data.Parameters.Cell_Body.BW_Threshold;
Scale_Factor = Data.Info.Experiment(1).Scale_Factor;
% Scale_Factor = Data.User_Input.Scale_Factor;
[CB_Pixels,CB_Perimeter] = Detect_Cell_Body(Im,CB_B... |
9c249575d69143351b93b2cbfec025aaea6dee055bde4c921d0de517e4288044 | MATLAB | 2,053 | 62 | function [I,check]=plane_line_intersect(n,V0,P0,P1)
%plane_line_intersect computes the intersection of a plane and a segment(or
%a straight line)
% Inputs:
% n: normal vector of the Plane
% V0: any point that belongs to the Plane
% P0: end point 1 of the segment P0P1
% P1: end point 2 of the... |
74cb248f8de866ececeb5db15fc3729b4b08f913276a8c3d1d10f7e13204ffab | MATLAB | 2,054 | 64 | function [ accs, dec_dims, weights,ve ] = tone_iterative_removal(p,t_pool_tone,n_rep,n_iter,rand_control,precomputed_dims,time_dependent,n_tr,nullspace)
% project data into motion / avoid nullspace
tone_null = [];
for t = 1:size(t_pool_tone,2) % loop over time
tone_null(:,t,:) = nullspace' * squeez... |
28d0d937889bfb5167514d6aeadee2bd56a2cca6fdd9af8830ff9d17be04b356 | MATLAB | 2,059 | 70 | function spmup_setparallel(varargin)
% simple routine to set the up the parallel processing
%
% FORMAT spmup_setparallel(N)
% set N if you want to use a specific number of processors
% useful on servers with dynamic attribution to limit oneself
%
% Cyril Pernet & Remi Gau
% --------------------------
% Copyright (C)... |
63264c1026e9990bef49bdb62bc972c9e53bf95bb02611d3ea099c63455578f5 | MATLAB | 2,059 | 60 | function CollectAllData20180804
clear all;
close all;
TargetDirectory='C:\Users\B133_2\Desktop\CheetahWRLV20180729';
cd(TargetDirectory);
% cd('C:\Users\B133_2\Desktop\CheetahWRLV20180729');
H=ls;%CheetahWRLVƒtƒHƒ‹ƒ_“à
disp('H=');
disp(H);
for n=1:length(H(:,1))
TrimStr1=strtrim(H(n,:));
if ~st... |
7577031992db6d5a2218f89376854e23102a3011e9d200d6873cc4e33d24228a | MATLAB | 2,059 | 80 | [cols,alpha] = chooseColors;
%% plot av1/2 over sessions
time_win = 6:15;
this_cols = {};% need to reverse order for some reason..
this_cols{1} = [208 28 139]/255;
this_cols{2} = [241 182 218]/255;
this_cols{3} = [77 172 38]/255;
this_cols{4} = [184 255 134]/255;
this_cols{5} = [67 162 202]/255;
this_cols{6} = [.7 ... |
9cc3bdfd738a70940f6539122c48366eb82bf6576cdb7ebddb43c9cc280aad79 | MATLAB | 2,059 | 58 | function groupinfo(obj,~,t,g,data,h)
%% Response to a mouse left button click on a structure
% autocorrelatemap() and crosscorrelatemaps() depend on this function.
%
% obj: handle of clicked graphics object
% t: array of all structures objects
% g: array of all labels objects
% data: data from graph function
%... |
7d389bf7b7e7275e2dfde523e2fc94ca021c6f03363b378bd7b754b57511cb30 | MATLAB | 2,062 | 62 | clear all
clc
odors = {'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'};
c = 1/255*[[33 125 255];[33 125 255];[33 125 255];...
[33 125 255];[33 125 255];[86 105 105];[86 105 105];...
... |
261b388261fdc2446fdeef1c1ecee636872101d2c8becf3d1478c2315883c37b | MATLAB | 2,065 | 64 | function [data] = JT_processFP(data,params)
%Process Fiber Photometry
%
% [data] = processFP(data,params)
%
% Description: This function is designed to process fiber photometry data
% for the lab. The function performs demodulation (if selected),
% filtering, baselining, and downsampling for all photomet... |
6340d1f50405b28f95b93eee92a4aa507dda0db201af69f27a7b6d02bdacc5d2 | MATLAB | 2,066 | 74 | function S = LoadSpikes(tfilelist)
%
% S = LoadSpikes(tfilelist)
%
% inp: tfilelist is a cellarray of strings, each of which is a
% tfile to open. Note: this is incompatible with version unix3.1.
% out: Returns a cell array such that each cell contains a ts
% object (timestamps which correspond to times at w... |
012bec44e17827219034c44c0dee5538554b6df43a04232779dce639c47272f1 | MATLAB | 2,067 | 55 | function data = alignData2Lick(data,tBefore,tAfter)
if isfield(data,'final')
Fs = data.gen.Fs;
if tBefore > 0
tBefore = tBefore*-1;
end
tBefore = tBefore * Fs; tAfter = tAfter * Fs;
nSamp = length(tBefore:tAfter);
data.lick.time = [tBefore:tAfter]'/Fs;
if isfield(data.final,... |
0bcc632769264a155c86a9a46ae2810f2a5a09f6a3f78f5b092ada86bcf60f07 | MATLAB | 2,067 | 61 | % load data from .npy files
% trainFolder = 'trainRecord_anti_R_5_1';
b1 = readNPY(sprintf('data/%s/b1.npy',trainFolder));
b2 = readNPY(sprintf('data/%s/b2.npy',trainFolder));
eta = readNPY(sprintf('data/%s/eta.npy',trainFolder));
lambda = readNPY(sprintf('data/%s/lambda.npy',trainFolder));
w1 = readNPY(sprin... |
3c3c939786f8cfcda26529fd3965c8a584506ba8401e17da66b54a4a357e1f2e | MATLAB | 2,068 | 60 | function [y, W, A] = spectral_component_analysis_ma(x, f0, bw, order)
% spectral_component_analysis_ma - Spectral component analysis (SCA) using multi-stage moving average (MA) filtering approach. Extracts and ranks linear mixtures of multichannel data with maximal energy in a given frequency band.
%
% Usage:
% [... |
3d967bf29966881df8d947ccd1c8c9169c98c9e91ecefb919427075790811ede | MATLAB | 2,068 | 69 | function making_heatmap(mat_file_after_converting, dir_root_OG )
% mat_file_after_converting = "HB329.mat";
% dir_root_OG = 'HB329/';
csv_name = '16bit_allen_csv_20200916.csv';
label_file_name = append(dir_root_OG, '/tubemap/elastix_labels_to_resampled/result.tiff');
load(mat_file_after_converting);
i... |
0d1f9df65543b0c0dd8c2c93426448aa3377d80e23bacc1e31d17b8d02f9c959 | MATLAB | 2,070 | 63 | function [h pi] = fdr(p, q)
% FDR false discovery rate
%
% Use as
% h = fdr(p, q)
%
% This implements
% Genovese CR, Lazar NA, Nichols T.
% Thresholding of statistical maps in functional neuroimaging using the false discovery rate.
% Neuroimage. 2002 Apr;15(4):870-8.
% Copyright (C) 20... |
1c38b2c123bf526170b459c7315fa6f9312d7348d64706809140a0d7f60b54fa | MATLAB | 2,070 | 54 | % 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"
%... |
4af400bf2251d63beed23fa6d106bad305661e423ede2d88c40db8b95667a5db | MATLAB | 2,070 | 59 | clear all
close all
%% S-curve with load line, V(I)
load Scurve_data_VI.mat
f = figure(1);
f.Position(3:4) = [600 500];
lines_width = 1.5;
% rectangle('Position',[0.77 1.44e-4 0.29 3.76e-4],'LineWidth',0.5,'LineStyle','-','FaceColor','#F5CD8B')
hold on
ax2 = scatter(Scurve_meas.V(1:2:length(Scurve_meas.V)/... |
f678a6f349d566207e57975bee6f0b8d2ebc36a4762f5a06c53cb7cb49ec66a1 | MATLAB | 2,070 | 65 | function [x_SAVE,y_SAVE,eb_SAVE] = plotFormatEntireSession(superStackAVG,varnamesENTIRE,setupParam)
All = superStackAVG.all.average;
VN = varnamesENTIRE;
ST1 = {'Raw'; 'Recentered'; 'DecayAdj'; 'RefDecayAdjExp'; 'RefDecayAdjPoly'};
inUseST = fieldnames(All);
STidx = zeros(1,numel(ST1));
for i = 1:numel(ST1)
... |
ef182fcb1e2fdf02c5b26a873bdd8b15b4c6276cfae375ba2315cf7e3589d518 | MATLAB | 2,071 | 60 | function varargout = subsref(this,subs)
% Subscript referencing for GIfTI objects
%__________________________________________________________________________
% Copyright (C) 2008 Wellcome Trust Centre for Neuroimaging
% Guillaume Flandin
% $Id: subsref.m 7291 2018-04-12 08:43:08Z guillaume $
if length(this) >... |
4f5862bea9afed2c71fa29cbb52aedd184c9f78f8f074dddb69ee8a869ea1dc6 | MATLAB | 2,073 | 69 | function [R_Dis_R,R_Dis_C,C_Dis_R,C_Dis_C,R_suffix,C_suffix,A] = MainFunc_Draw_Line(A)
% 将语义分割鉴定之后的图片转为Label作为输入
% R_Dis_R
% R_Dis_C
% C_Dis_R
% C_Dis_C
format='um';% 文件格式
Num = 200;
scale = 1.226994;
[x,y] = size(A);
for i = 1:x
for j = 1:y
if A(i,j) == 1
A(i,j) = 255;
els... |
6d0f5f4084cd1f5d557524009ee906244c1c4d8da289d869a4196511739c9763 | MATLAB | 2,073 | 57 | function predictionperactual = importfile(filename, startRow, endRow)
%IMPORTFILE Import numeric data from a text file as a matrix.
% PREDICTIONPERACTUAL = IMPORTFILE(FILENAME) Reads data from text file
% FILENAME for the default selection.
%
% PREDICTIONPERACTUAL = IMPORTFILE(FILENAME, STARTROW, ENDROW) Reads da... |
fae874774eb70403f53c1f40f1478fbfc0fe6d565c64439cbec6ff21380c2ea4 | MATLAB | 2,073 | 66 | function deleteClusters(obj, deleteMe)
%DELETECLUSTERS Delete clusters either specified or selected
if obj.isWorking
jrclust.utils.qMsgBox('An operation is in progress.');
return;
end
if nargin < 2 && numel(obj.selected) > 1
return;
elseif nargin < 2
deleteMe = obj.s... |
707e01ec8434e70503e00bc4d3ae2ebf7dfc7851dd8c639dafc7073ed11827a6 | MATLAB | 2,074 | 57 |
%% get necessary data
clear
p = params_2DAA;
sub = 11;
sub = p.subjects(sub);
% get heuristic sorting if any
fpath = fullfile(p.rootDir,'miniscope',['subject' num2str(sub)],'jointExtraction','sorted','heuristic_sorting.mat');
if exist(fpath)
sData = load(fpath,'heurist... |
95dfe713c66ac07c94db7afe438208cba4debe41247704bc45e112f45ef3e62f | MATLAB | 2,074 | 65 | %% plot pupil deluted VS regular
X = all_data;
nac_3 = [4 6 26];
nac_5 = [13 37 48 108 115];
nac_2 = [49 131];
cluster_6 = [17 96 98 99 103 127];
cluster_1 = [92 104 106 109 115];
delay = 1.1;
%%
Y = nac_5;
regular = [];
pupil = [];
for i = 1:length(Y)
cell_name = (['cell_' num2str(Y(i))]);
regul... |
c1045b06fb1ee6e1afe78825a11178ecf51bd6b9461e7b58660b11abc16bb8ca | MATLAB | 2,075 | 53 | function [ av_trials,err_trials ] = collect_ae_trials_tone_end_alignment(p, traces, bvs, tis, speed_control,tone_start_control)
spd_dims = 18:22; %dlc
pre_steps = 15;
post_steps = 5;
for sub = 1:p.nSubjects
% first collect all av trials and keep track of the action
% start times tha... |
567bff740430bd39a45b999c86318fe8b3d916e2af3a5e843e38fa777a3015a0 | MATLAB | 2,077 | 56 | function updateFigHist(obj)
%UPDATEFIGHIST Plot ISI histogram
if isempty(obj.selected) || ~obj.hasFig('FigHist')
return;
end
plotFigHist(obj.hFigs('FigHist'), obj.hClust, obj.hCfg, obj.selected);
end
%% LOCAL FUNCTIONS
function hFigHist = plotFigHist(hFigHist, hClust, hCfg, selected)
%PLOT... |
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