sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
56ef4a93614a85beaa7dea9ada34305dd18207118107fe89177422b46fb60b43 | MATLAB | 9,282 | 52 | close all
clear variables
clc
%Varun Mannam
%date: 24th Sep 2019
%calculate the PSNR on test-mix data no bn
format long
font = 14;
size = 60;
lr1=[31.0013994757380,38.5682173013864;32.4355944495239,37.0147119119919;30.8389376260123,38.5027520432416;30.1446963613668,37.4353527244578;22.8898419300006,32.0962535000397;25... |
986867672e7a1e03e5340cacab81690e8d918a6af1757c0543c49ac49f0f7113 | MATLAB | 9,282 | 227 | % internal function
% - Jimmy Shen (jimmy@rotman-baycrest.on.ca)
function save_nii_hdr_bis(hdr, fid)
if ~exist('hdr','var') | ~exist('fid','var')
error('Usage: save_nii_hdr_bis(hdr, fid)');
end
if ~isequal(hdr.hk.sizeof_hdr,348),
error('hdr.hk.sizeof_hdr must be 348.');
end
... |
a05f6a398c347873776781365f4659590f16124626d72531e9e025dd95208957 | MATLAB | 9,283 | 224 | function Vo = spm_imcalc(Vi,Vo,f,flags,varargin)
% Perform algebraic functions on images
% FORMAT Vo = spm_imcalc(Vi, Vo, f [,flags [,extra_vars...]])
% Vi - struct array (from spm_vol) of images to work on
% or a char array of input image filenames
% Vo (input) - struct array (from spm_vo... |
cc30dfd4a90ae1b18f4ee7bd2f5105703a22ae5e1615f3dea2dc99c170f705e3 | MATLAB | 9,288 | 213 | function plot_population_vector_shuffles(bayesian)
% Marta Huelin _ February 2020
% Plot comparison between global and rate remapping, and real data.
save_path = 'X:\BendorLab\Drobo\Lab Members\Marta\Analysis\HIPP\Chapter 1\Population_vector_analysis\';
cd(save_path)
load('global_shuffle_population_vector_data_excl.m... |
a81ca95b08fd701e760c9ebf708eb3eae79fbf8286498cfc56e5c5191a5c4aa8 | MATLAB | 9,300 | 226 | function Optical_fitting_7694(ref, ret, s_seg, z_seg, datapath)
% Fitting scattering and retardance of brain tissue
% co: volume data for co pol
% cross: volume data for cross pol
% s_seg: slice number
% Z_seg: tile number
% datapath: datapath for original data
cd(datapath);
opts = optimset('Display','off','To... |
4a1d3fdd9b3484a775740541b9f43a2ad238956dbf19a6f3e3addae6a4123f2a | MATLAB | 9,304 | 380 | function ftab = de_ftab(xrs, mas, varargin)
%function ftab = de_ftab(xrs, mas, [options])
%|
%| For multiple-kVp X-ray imaging, we must evaluate functions f_m(s_1, ..., s_L)
%| for m=1,..,M, where M is the number of kVp settings,
%| and L is the number of material components.
%| f_m(s1, s2) = -log( \int exp(- (m1(E) s... |
7865240eccfee16d6a8f30a0b4eebced2fc4ae6242cc7ea0374700df993d97d0 | MATLAB | 9,309 | 212 | function SBJ08h_HFA_plot_crRT_LME(SBJ, proc_id, an_id, model_id, stat_id, plt_id, save_fig, varargin)
%% Plots LME beta time series per electrode
% INPUTS:
% SBJ [str] - ID of subject
% proc_id [str] - ID of preprocessing pipeline
% an_id [str] - ID of the analysis parameters to use
% model_id [str] - ID of the... |
f6b20094238e75ff3ca599af95eb3bd3fdd6d859aa180bfce8e34095ed73c7ce | MATLAB | 9,310 | 195 | clear all
rec_path = 'C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\';
dpath='C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\';
spath = 'C:\Users\xscogno\Dropbox\SfN2019\Development\Rasterplots\L9M1\';
mouse='L9M1'; %Name of the animal
load([rec_path,strcat('recording_dates_',mouse,'.mat')]);
%% Data and runni... |
e04a260ec4985987b03bbc7379b163974cd521c87a42513a6c382d0eb2768736 | MATLAB | 9,311 | 185 | function all_regressors = select_and_prepare_regressor_data_for_subject_level_glm(subID,session,condition,all_responses,stim_streams, mean_stim_streams,vertical,vertical_stim_streams)
%PREPARE_REGRESSOR_DATA_FOR_SUBJECT_LEVEL_GLM
% Collects all regressors for the convolutional GLM from behavioural and stimulus data
%
%... |
2530dd60c87ba9aafc34830b41beebeeec08ea264eb07eabaf1db1778e3ff3a3 | MATLAB | 9,313 | 241 | function SBJ08a_HFA_crRT_mGLM(SBJ, proc_id, an_id, model_id, stat_id)
%% function SBJ08a_crRT_mGLM(SBJ,an_id,stat_id)
% Run GLM with sliding windows for given time-frequency analysis
% Correlation with RT and regression of RT as confound supported
% Model based on log fit to behavior:
% reward prediction, s... |
3633070d8793888339bb518fb46145f76bb5ab22098e30b562c0212ff1eae1e0 | MATLAB | 9,314 | 422 | function fit = de_ftab_fit_exp3(xrs, mac, varargin)
%|function fit = de_ftab_fit_exp3(xrs, mac, [options])
%|
%| Fit to DE table fm(), suitable for subsequent interpolation / extrapolation.
%| Uses a special experimental exponential model:
% todo -log(sum_k p_k exp(-m_k . s))
% fit a 3-term exponential model that has... |
e11213605f0f4881cf9914c5878479b6169d84524c332c828d7caba915a468f6 | MATLAB | 9,321 | 246 | % bjli @ Feb 11 2023.
% bjlistat@nus.edu.sg
% refered to Z. Yao, J. Su, B. Li, and S.T., Yau, Manifold Fitting
i_job = 3;
Jobs = {
1, 'Visualization of the output';...
2, 'Boxchart of Comparision';...
3, 'Boxchart asymptotic property N Comparision';...
};
job = Jobs{i_job,2};
switch job... |
412e08bf43a8e92f1b2457f3605302addc2dcb5d07f28d9648427ab4a82d9596 | MATLAB | 9,328 | 255 | function Bfg_stitch(target, P2path, datapath,disp,mosaic,pxlsize,islice,pattern,sys,ds,stitch)
%% stitch the fitting result using the coordinates from AIP stitch
%% define grid pattern
% add subfunctions for the script
addpath('/projectnb/npbssmic/s/Matlab_code');
% displacement parameters
% xx=92;
% xy=-4;
% yy=97;
r... |
a4741f50f15aeacfe7f3cd7be00bf183efc9e986e55269f86c6732e6d81fb43e | MATLAB | 9,335 | 275 | %% Analyzing Neural Time Series Data
% Matlab code for Chapter 4 script B
% Mike X Cohen
%
% This code accompanies the book, titled "Analyzing Neural Time Series Data"
% (MIT Press). Using the code without following the book may lead to confusion,
% incorrect data analyses, and misinterpretations of results.
... |
6303858a993a348b408eb216f7d42a31c7caaff8dda769f801f5e4996dae0e2e | MATLAB | 9,336 | 237 | function SBJ11a_HFA_conn_mGLM(SBJ, proc_id, an_id, model_id, stat_id, conn_id, pmask, nbins)
%% Set up paths
if exist('/home/knight/hoycw/','dir');root_dir='/home/knight/hoycw/';ft_dir=[root_dir 'Apps/fieldtrip/'];
else root_dir='/Volumes/hoycw_clust/';ft_dir='/Users/colinhoy/Code/Apps/fieldtrip/';end
addpath([root_dir... |
cf9a00df6fc31599eb1fb66bf1b86ec80bb00a5f3b9ebce3629e099ed69d9775 | MATLAB | 9,359 | 237 | %% this file allows to create fit Z-spectrum data with BM simulation
%%it also allows to fit single offset QUESP and QUEST formulaes
%% 1.1A load XLS_qCEST file
% this creates a stack of Z-spectra Z_x and teh parameters struct P
[w_x, Z_x, P, rowname, Ztab]=LOAD_xls_qCEST_2_Ztab({'25degC'});
expname=Ztab{rowname,... |
c60279b8d6bb8e36a97df54434ff3c138c6cf0fe85562b03c2b87e747e0aa243 | MATLAB | 9,361 | 160 | function [Objects] = f_imageAnalysis(Label, ch1, ch2, ch3, ch4, PreviewPath, MetaTable)
%vol(ch1, 0, 5000) Hoechst
%vol(ch2, 0, 4000) 647 MAP2 (270 Mouse)
%vol(ch3, 0, 5000) 568 TH (111 Chicken)
%vol(ch4, 0, 5000) 488 Caspase3
ObjectsThisOrganoid = table();
%% Max projections
%NucMax = max(... |
c5e2c2c2f50c36da2ed28f9f3eba25044a12194385f70daf13f442c8e2c4c2ae | MATLAB | 9,378 | 182 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% MAIN - MEG - Desikan-Killiany
% Authors: MCC
% Date: 21/03/2022
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
close all; clear; clc;
%% To be updated
root_path='/Users/marie-constance.corsi/Documen... |
2ecd25d8a6f41c9c62ef64d8f6df3bfe13a0a914a06de9b411651e42ea88671b | MATLAB | 9,379 | 284 | %Extended data Figure 14
%% Ramp
clear all
close all
number_seq=1;
factor_v=[0.01,0.1,0.5,2,4];
fk=4;
factor_t=factor_v(fk);
g = 1.5; % Used to initialize the weight matrix
N = 500; % Number of cells
%Time vectors
dtData = 0.0641*factor_t; % dt at which the data is sampled. Using the same dt that I use for calcium... |
45dec19fe5121e03428793030a946ea8acfe54afb6275f7ff25c29c537f629c9 | MATLAB | 9,395 | 253 | function [Dtf, Dtph] = spm_eeg_tf(S)
% Compute instantaneous power and phase in peri-stimulus time and frequency
% FORMAT [Dtf, Dtph] = spm_eeg_tf(S)
%
% S - input structure
%
% fields of S:
% S.D - MEEG object or filename of M/EEG mat-file with
%
% S.channels - cell arr... |
0d72eb09af3f93dc9589d2f824e8c5751827e5e3c4280c36efe8700ff37f54c3 | MATLAB | 9,397 | 358 | function back = my_cbct_back(proj, cg, ig, varargin)
% function back = cbct_back(proj, cg, ig, varargin)
%|
%| cone-beam backprojector for feldkamp.m
%| in
%| proj [ns nt na] cone-beam projection views
%| option
%| 'use_mex' 1|2|3 default: 1 mex with loop in mex
%| 2 mex with loop in matlab
%| 3 mex with "st... |
327d35c92cf81f6aaa250733874dd0031b27ac6238b1f70cdf6e1e99ab8d7cb6 | MATLAB | 9,398 | 304 | function varargout = pm_unwrap(varargin)
% Unwrapping of phasemap
% When measuring phase one cannot easily distinguish between e.g. a phase
% of 182 degrees, and one of -178 degrees. One tries to distinguish these
% cases by using neighbourhood information. So in the example above, if we
% find that a neighbouring voxe... |
3dc35dfd37a35473b6725eda89bab291b6eff8366c750dfc8f6941bb427cf515 | MATLAB | 9,400 | 217 | function [self] = getDistByTimeSpike(self,condNdx,key,opts,plotFig)
%% Set up the data
% lump all kinematic changes caused by ORN activity into one category
spkTrigKinNdx = find([cellfun(@(x) strcmp(x,'below'),key,'UniformOutput',true) |...
cellfun(@(x) strcmp(x,'above'),key,'UniformOutput',true)]);
% update t... |
370a35833861aef2a110999c3c8a5ccbf9bd4435f458982c826b4aeb4f467f6a | MATLAB | 9,407 | 258 | %aim to calculate the latency of the response, find the time and CI, and
%the bootstrap
% close all;
clearvars;
addpath ('/data/local/u0114568/ephysio/test');
listname=['targetRight'];
cn1={'sp','color', 'con', 'incon', 'att', 'congruency','fac','int'}; % condition names length=8
cn={ [cn1{1}],[cn1{2}]};
condnames=li... |
96a6c6610423bf7a9f52549931159cb56319b58a072038a96c67b4380c6d2344 | MATLAB | 9,413 | 150 | % THETA SEQUENCES DETECTION AND DECODING
% MH 2020
% Bins theta based on spike phases. Converts phase bins to time, and decodes entire tracks using the new bins. Then divides in theta windows
% (peak to peak), and applies thresholds to discard the noisy cycles. Finally, split the theta windows based on direction
% Load... |
96f196cc8003f311881c8830e0d6c03d84796957d05d0f51c20c285de63489b6 | MATLAB | 9,417 | 230 | function [Z, A, Ainvb, dia] = BMsolution(x0, xZspec, tspan, z0, y0, y1)
% comments here
% last change: 2014/04/02 by PS
% BM solution solves the Bloch-McConnell equations stepwise
% set kCA=0 and fC=0, if MT is disabled
if x0(1,3) == 0; % (x0(1,3) = Sim.MT)
x0(4,2) = 0; y0(15) = 0;
end
% set ex... |
b56423a8ec135ee0ea60517bd6d57dfdf8ccc679babd53b222c7a778750860d2 | MATLAB | 9,418 | 261 | function [EEG, misc] = c_TMSEEG_prepareForPreprocessing(varargin)
%% this function does several miscellaneous data input tasks to prepare for other preprocessing
% (implemented here to not duplicate this common code in multiple dataset-specific analysis scripts)
% Main steps include:
% - (If needed) Load data
% - (If ... |
51bb46b9df58291369575ca993f9ae3236c042865d8bb6bb69760c8aa23f0888 | MATLAB | 9,421 | 162 | function parametersOK = checkCopulaExtractions(draws, mcmc, modelParameters, model, environment)
% function checkCopulaExtractions(draws, mcmc, model, environment)
% Checks if the parameters extracted by the copula at the end of the
% identification are ok.
%
% Input:
% - draws: a structure which contains the parame... |
64936456e98da3ad23ed3987b27f9404de6d22261a544264e6bf9dd5419ac565 | MATLAB | 9,431 | 235 | classdef Neuron < handle
%NEURON A neuron.
%
% A neuron has a position within an image, color, list of potential
% IDs, probabilities associated with these IDs, and methods to draw
% it within a GUI.
properties
% Neuron position & color.
position % neuron pixel positio... |
3bb37e8786fda308edef785d5d7574d98cbbfb21ec94362b24aa5faf44ebf3bb | MATLAB | 9,439 | 432 | function [Gx, Gy, kxvec, kyvec, sx, sy] = ir_gen_spiral_vd(D, N, nl, gamp, gslew, dsamp)
%function [Gx, Gy, kxvec, kyvec, sx, sy] = ir_gens_piral_vd(D, N, nl, gamp, gslew, dsamp)
%| Subroutine for generating slew-rate-limited spirals.
%| Returns length of resulting gradients, after adding downramp.
%| Craig Meyer, Cop... |
5e19fb0882393f5b2d890fbe0085115e45634a7c3e29842669a65dcb22eb45b1 | MATLAB | 9,440 | 226 | function Optical_fitting_7688(ref, ret, s_seg, z_seg, datapath)
% Fitting scattering and retardance of brain tissue
% co: volume data for co pol
% cross: volume data for cross pol
% s_seg: slice number
% Z_seg: tile number
% datapath: datapath for original data
cd(datapath);
opts = optimset('Display','off','To... |
21ae030b3d5ac3b45d11649c39f3bd99ffada7dd1fa317e4df1046c224885e95 | MATLAB | 9,445 | 182 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% MAIN - Analysi fatta sul dataset a disposizione - 20 soggetti - Sess. 4 - EEG - Desikan-Killiany
% Authors: MCC
% Date: 21/03/2022
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
close all; clear; clc;... |
ea3c6274acedfc117d5c909ba3614b562b3f4a2828a411b51999de867527e321 | MATLAB | 9,454 | 205 | function extract_replay_rate(epoch)
% Looks at the exponentials curves representing the cumulative sum of events and finds the coefficients of the equation (A and B)
% Parameters
load('extracted_replay_plotting_info.mat')
load('extracted_time_periods_replay.mat')
PP = plotting_parameters;
bin_width = 60; %1 min
% S... |
22f461073681498eeaca75a96a7fb1ba5ff6547dd6388a1be9e7137255b04e13 | MATLAB | 9,464 | 241 | % bjli @ Feb 11 2023.
% bjlistat@nus.edu.sg
% refered to Z. Yao, J. Su, B. Li, and S.T., Yau, Manifold Fitting
Jobs = {
1, 'Visualization of the output';...
2, 'Boxchart of Comparision';...
3, 'Boxchart asymptotic property N Comparision';...
};
job = Jobs{i_job,2};
switch job
case '... |
bd81a94407ae7f4b83dfb3fe8f529e8e2122807024432d8eabe08dc173861fd7 | MATLAB | 9,492 | 389 | function ob = Gsparse(arg1, varargin)
%function ob = Gsparse(file.wtf | sparse | cell, options)
%|
%| Construct Gsparse object, either from a sparse matrix itself,
%| or from the arguments that would be passed to matlab's sparse() command,
%| or from an Aspire binary .wtf file.
%|
%| The Gsparse object overcomes some ... |
2a438f5335216e4c15e2496dd3e36f9d50860b64753625d4d5ca6959d535d834 | MATLAB | 9,511 | 258 | function [task] = runRPE(subNum,runNum)
% % RUNRPE.m $%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% usage: [ task ] = runRPE( subNum, runNum )
%
% subNum && runNum are scalar
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% dependencies:
%
% (subID)_rpe_inp... |
03ae05f9552986ef780e93353a7f068febc5663b1a76dee736b41176a3495c79 | MATLAB | 9,513 | 216 | %Uses either the Garvey et all method or the SD limit method
%specify which method and if there are 50% algorithm checks
%Inputs:app data, PreStimData, SelectedTrialsData, PreStim stdv, MCD or SD ('MCD' or 'SD'), varargin(OnsetFifty, OffsetFifty (boolean))
%Outputs: All Onset and Offset time for each trial
function [A... |
689c53d834d87a23a8d8506eb4471e52f87dd5a13475dbb8e4533cca54ee0750 | MATLAB | 9,519 | 175 | function [Objects] = f_imageAnalysis(Label, ch1, ch2, ch3, ch4, PreviewPath, MetaTable)
%vol(ch1, 0, 5000) Hoechst
%vol(ch2, 0, 4000) 647 TH
%vol(ch3, 0, 5000) 568 Tuj1
%vol(ch4, 0, 5000) 488 MAP2
ObjectsThisOrganoid = table();
%% Max projections
%NucMax = max(ch1, [],3); imtool(NucMax,[])
... |
05a2ec7f3902179108f09a8900cecb6e900fea7940e51c0cf75ff58a39a14974 | MATLAB | 9,525 | 308 | %% Figure 3a & b (right panel)
% this script rungs additional analysis required for the plots of figure
% 3a & 3b.
%%
clear
ft_defaults
%% - SUBJECTS - %%
% ID 18 missing because of LP at 50Hz
subjects = {'OSL13', 'OSL14', 'OSL17', 'OSL21', 'OSL24', 'OSL26', 'OSL27', 'OSL28', ...
'OSL29', 'OSL30', 'OSL31', 'OSL... |
7ae2c00f7afec09134086df2240f72f7e00109ccbec8706c5a8a4d2a2c9e2665 | MATLAB | 9,531 | 297 | clear all
close all
dbeh_path='C:\Users\xscogno\MATLAB\Flavio2\Waves\Tracking data\';
rec_data_path = 'C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\';
dpath_spikes='C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\';
dpath_sorting='C:\Users\xscogno\MATLAB\Flavio2\Waves\Sorting\';
dpath='C:\Users\xscogno\MATLAB\F... |
8c6f63758f6c7f4b76e70dcaeb7ca9d9b5cf0612d7ebd6484297ce8e5b9d1134 | MATLAB | 9,531 | 266 | function Bfg_stitch_NC(target, P2path, datapath,disp,mosaic,pxlsize,islice,pattern,sys)
%% stitch the fitting result using the coordinates from AIP stitch
%% define grid pattern
% add subfunctions for the script
addpath('/projectnb/npbssmic/s/Matlab_code');
% displacement parameters
% xx=92;
% xy=-4;
% yy=97;
result=t... |
09b6b98746c0f5526d032b8163afa754e0f9434e3f8825bb534f97f4d2982fd8 | MATLAB | 9,532 | 219 | classdef SuhDemo < handle
% AUTHORSHIP
% Primary Developer: Stephen Meehan <swmeehan@stanford.edu>
% Copyright (c) 2022 The Board of Trustees of the Leland Stanford Junior University; Herzenberg Lab
% License: BSD 3 clause
methods(Static)
function gt=Omip47_wayne
gt=FlowJoTree.NewOrReuse(...
... |
d6a13cc6e56334c08833ec8a0eec61bde02fbd67843408c9acecc59de9992651 | MATLAB | 9,535 | 266 | function Bfg_stitch_6692(target, P2path, datapath,disp,mosaic,pxlsize,islice,pattern,sys)
%% stitch the fitting result using the coordinates from AIP stitch
%% define grid pattern
% add subfunctions for the script
addpath('/projectnb/npbssmic/s/Matlab_code');
% displacement parameters
% xx=92;
% xy=-4;
% yy=97;
result... |
01e40cf03e06dbb39d5a0f0f8b42f466b810ee14471a74d86d0af2e367646c90 | MATLAB | 9,537 | 252 | function Mus_stitch_True(datapath,disp,mosaic,pxlsize,islice,pattern,sys)
%%% ---------------------- %%%
% function version of mosaicing & blending
% input: displacement parameters: four elements array [xx xy yy yx]
% mosaic parameters: four elemetns array [number of x tile, number of y tile,
% ... |
e2b77ae00a337b8cb1f7398f829c12f9390a81a6c3b7d1c35b186efae71aab21 | MATLAB | 9,541 | 267 | function Bfg_stitch_8921(target, P2path, datapath,disp,mosaic,pxlsize,islice,pattern,sys)
%% stitch the fitting result using the coordinates from AIP stitch
%% define grid pattern
% add subfunctions for the script
addpath('/projectnb/npbssmic/s/Matlab_code');
% displacement parameters
% xx=92;
% xy=-4;
% yy=97;
% yx=-... |
f38e6cb8323a6efc8210a2f6fcf22b9388b41644043862d30d27343436f16288 | MATLAB | 9,543 | 241 | % Evaluation of S-BLIF model output in respect to the neurophysiological
% experiments by Miller et al. (2011) JARO article as described in
% Takanen and Seeber: “A Phenomenological Model Reproducing Temporal Response
% Characteristics of an Electrically Stimulated Auditory Nerve Fiber”,
% Trends in He... |
00fd3cc1951aabe75fc97e5dc14e5a2d3c0c1d39f5c05379d0446043673d9a0b | MATLAB | 9,553 | 159 | function [Objects] = f_imageAnalysis(Label, ch1, ch2, ch3, ch4, PreviewPath, MetaTable)
%vol(ch1, 0, 5000) Hoechst
%vol(ch2, 0, 4000) 647 Sox2
%vol(ch3, 0, 5000) 568 Edu
%vol(ch4, 0, 5000) 488 Ki67
ObjectsThisOrganoid = table();
%% Max projections
%NucMax = max(ch1, [],3); imtool(NucMax,[]... |
6a531fee1d69b2dbd0eb666d97889e7eddd411eb2bc3432aaac8292812c4f2b1 | MATLAB | 9,553 | 243 | function [outMeanRoughness,outSortedList,outRoughness,outRoughnessFreq,outUsedSection] = ...
IPEMRoughnessOfSoundPairs (varargin)
% Usage:
% [outMeanRoughness,outSortedList,outRoughness,outRoughnessFreq,...
% outUsedSection] = ...
% IPEMRoughnessOfSoundPairs(inFiles,inPaths,inSection,...
% ... |
1399ab99a7fd05a36da94e430e2e582b4c9c4bfcef7870eed498fa4040d16b36 | MATLAB | 9,555 | 229 | function plot_decoding_both_tasks(subjects,with_stats,analysis)
%PLOT_DECODING_BOTH_TASKS Plot the results from object decoding, averaged over
%all participants for both tasks (categorization and distraction).
%
%Input: subject IDs, with_stats (1 plot with stats, 0 plot without),
%analysis ('object_decoding' or 'catego... |
da77b607e37ecd265436e34c2a143ca3bd2df542278fb2cde1a856773ae54fe2 | MATLAB | 9,557 | 314 | function [B Bgx Bgy Bgz] = makeB(ig, kg, varargin)
%|function [B Bgx Bgy Bgz] = makeB(ig, kg, [?])
%|
%| Create a Fatrix B operation of warping based on cubic B-spline
%|
%| in:
%| 'ig' image geometry
%| 'kg' knot geometry
%|
%| out:
%| B fatrix operation for warping
%| Bgx fatrix operation for warping
%| Bgy f... |
e55378a5107e9e0ee9009b9be2e850e085a757e283b0a26236b4df21f95b016a | MATLAB | 9,558 | 292 | % Save NIFTI dataset. Support both *.nii and *.hdr/*.img file extension.
% If file extension is not provided, *.hdr/*.img will be used as default.
%
% Usage: save_nii_bis(nii, filename, [old_RGB])
%
% nii.hdr - struct with NIFTI header fields (from load_nii.m or make_nii.m)
%
% nii.img - 3D (or 4D) matrix of N... |
56364e9e5b6a2ad6cc64630eee94784e54d88d2bf2cc25f836346255d03ad700 | MATLAB | 9,568 | 250 | % bjli @ Feb 11 2023.
% bjlistat@nus.edu.sg
% refered to Z. Yao, J. Su, B. Li, and S.T., Yau, Manifold Fitting
Jobs = {
1, 'Visualization of the output';...
2, 'Boxchart of Comparision';...
3, 'Boxchart asymptotic property N Comparision';...
};
i_job = 2;
job = Jobs{i_job,2};
switch j... |
3131d75235a5d553242da1b3cec90360032b63cef79ab6a0dea1f2fb4b90beda | MATLAB | 9,583 | 268 | function Bfg_stitch_7688(target, P2path, datapath,disp,mosaic,pxlsize,islice,pattern,sys)
%% stitch the fitting result using the coordinates from AIP stitch
%% define grid pattern
% add subfunctions for the script
addpath('/projectnb/npbssmic/s/Matlab_code');
% displacement parameters
% xx=92;
% xy=-4;
% yy=97;
% yx=-... |
a6df45d4d0387bb4ef68258799a66341ba151f875e2371fd8cd40babf80b74d0 | MATLAB | 9,583 | 268 | function Bfg_stitch_7694(target, P2path, datapath,disp,mosaic,pxlsize,islice,pattern,sys)
%% stitch the fitting result using the coordinates from AIP stitch
%% define grid pattern
% add subfunctions for the script
addpath('/projectnb/npbssmic/s/Matlab_code');
% displacement parameters
% xx=92;
% xy=-4;
% yy=97;
% yx=-... |
f34383c82bcf49c6df7ad8876e33adfbc9fb46a9fc4461fcae81219d90a81203 | MATLAB | 9,584 | 268 | function Bfg_stitch_PTSD1(target, P2path, datapath,disp,mosaic,pxlsize,islice,pattern,sys)
%% stitch the fitting result using the coordinates from AIP stitch
%% define grid pattern
% add subfunctions for the script
addpath('/projectnb/npbssmic/s/Matlab_code');
% displacement parameters
% xx=92;
% xy=-4;
% yy=97;
% yx=... |
31404df829c3465c638bc8a321af02c067c155855e565bcd421df5f8189a8ddd | MATLAB | 9,595 | 213 |
clear all;%close all;clc
fn_ext = 'cue_resp' %
group_plots = 'yes'
subj = ''
cond = 'lure+'
freq_range = 'deltatheta'
fpass = [4 5]
time1 = '0'
time2 = '1'
plot_type = 'magnitude' % main phase % magnitude
lock = 'onset'
%... |
32c5c57b883af453f6bc57dd2094b7350e109df73795a77dd6893c619a0ad4ca | MATLAB | 9,599 | 260 | function physiologicalPlausibility = checkPhysiologicalPlausibility(data,modelParameters,draws,environment,model,sensors,mcmc,dss)
% function physiologicalPlausibility = checkPhysiologicalPlausibility(data,modelParameters,draws,environment,model,sensors,dss)
% Replays the given scenario defined by the given data.
%
% ... |
763c46e0b0d8f8e3d899a91497aecd9662126046bf51de543b494e9ca628d9dd | MATLAB | 9,608 | 181 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% MAIN - MEG - Destrieux
% Authors: MCC
% Date: 21/03/2022
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
close all; clear; clc;
%% To be updated
root_path='/Users/marie-constance.corsi/Documents/GitH... |
b9493d987149bc70d095dc607975d4e95c068ce84ef31a1e5d1a44a03aa11756 | MATLAB | 9,608 | 181 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% MAIN - EEG - Destrieux
% Authors: MCC
% Date: 21/03/2022
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
close all; clear; clc;
%% To be updated
root_path='/Users/marie-constance.corsi/Documents/GitH... |
e9c19905f9195b05148ac431a521e6d4c5a1a51cfff60bcff8d1bf6c67f56ec5 | MATLAB | 9,612 | 376 | function ob = Gtranslate(mask, varargin)
%function ob = Gtranslate(mask, options)
%|
%| Construct Gtranslate object for image registration.
%| (Internally stores image-sized arrays so not very memory efficient.)
%|
%| See Gtranslate_test() below for example usage.
%|
%| in
%| mask size(image) logical array of object s... |
e766ba36a4dbec1405db9b59c87b71f7f1a8857df3e42ff6f6d3f2230268a3b0 | MATLAB | 9,623 | 210 | classdef FlowJoUtil < handle
% AUTHORSHIP
% Primary Developer & Math Lead: Connor Meehan <connor.gw.meehan@gmail.com>
% Secondary developer: Stephen Meehan <swmeehan@stanford.edu>
% Copyright (c) 2022 The Board of Trustees of the Leland Stanford Junior University; Herzenberg Lab
% License: BSD 3 clause
... |
fe92aa1f64f90e907f70c45d69a704fe2b55c1cdaf417136ca29bf2b43bab8bd | MATLAB | 9,627 | 238 | function spm_defaults
% Set the defaults which are used by SPM
%__________________________________________________________________________
%
% If you want to customise some defaults for your installation, do not
% modify this file directly, but create a file named spm_my_defaults.m
% instead, accessible from MATLAB sea... |
6ebc5943d7ee32d8f12ef9faef6eaff74e6d33b8b1fcb2295cf293707c6e35c5 | MATLAB | 9,643 | 253 | function sync_vr_to_np_driftCorrect(data_dir, save_data_dir, session_name, tracklength, save_fig_bool)
fprintf('Start syncing session: %s @ %s\n',session_name,datestr(now,'mmmm dd, yyyy HH:MM:SS AM'));
addpath(genpath('C:\code\spikes'));
addpath(genpath('C:\code\npy-matlab'));
addpath(genpath('C:\code\AlexA_Library\'... |
b095cc4b1eca548db530a437fcf0fa02651dd1b468b9add7c2197d65fea76aa5 | MATLAB | 9,646 | 255 | function ellipse_t = fit_ellipse( x,y,axis_handle )
%
% fit_ellipse - finds the best fit to an ellipse for the given set of points.
%
% Format: ellipse_t = fit_ellipse( x,y,axis_handle )
%
% Input: x,y - a set of points in 2 column vectors. AT LEAST 5 points are needed !
% axis_handle - optional.... |
00ef56e2cab93ebef2a4d8ed5bcd6bd42b54da802c1a15e9d7ff739dd8933407 | MATLAB | 9,664 | 355 | function [B, C, hk, zk] = mri_exp_approx(ti, zmap, LL, varargin)
%|function [B, C, hk, zk] = mri_exp_approx(ti, zmap, LL, [options])
%|
%| Build approximations to exponentials for iterative MR image reconstruction,
%| generalizing "time segmentation" and "frequency segmentation" methods.
%| This is a key part of the ... |
02ed1f8a578b6b043fc4d24b6bae36e4d5fac9c281f7dfd236b79bc491b623ec | MATLAB | 9,665 | 213 | % PLOT SHUFFLE DISTRIBUTIONS FOR AVERAGE THETA SEQUENCES
%MH 2020
% INPUT:
% method: either 'quadrant_ratio' or 'weighted_corr'
function plot_average_thetaseq_shuffles(method)
sessions = data_folders;
session_names = fieldnames(sessions);
PP = plotting_parameters;
% yn34 = [280,260,240,220,200];
% yn84 = [110,100,90... |
5bac58ef6010afded4f248a1cdf2b008660bb48b05a6ef5433aa66da3ea667c5 | MATLAB | 9,667 | 227 | classdef ieegStructClass
% The ieegStructClass is a class for handling iEEG data with various operations.
% It provides methods for common average referencing, band-pass filtering, high-gamma extraction,
% normalization, permutation cluster analysis, and more.
properties
data % channels x ... |
932d7f09ed4cc2da8f435c4b325e70c9887b7daa75e433188f0c5b013aebbb32 | MATLAB | 9,671 | 247 | % sessions = dir('/Volumes/groups/giocomo/export/data/Projects/JohnKei_NPH3/fkm_analysis/fr_corr_matrices/*.mat');
sessions = dir('/Users/KeiMasuda/Desktop/fkm_analysis/fr_corr_matrices_noSpeedFilter/*.mat');
sessions = filterSessions(sessions, 'mec');
%%
for n = 1:numel(sessions)
try
matPath = fullfile... |
cd2366530fff15bc7f615ffe297e710f8879f93be572db0d3a5da4163720374f | MATLAB | 9,679 | 254 | function sendExperiment2Host(host, localFolder, keepRemoteFiles)
% Copies the files of an experiment from the control computer to an
% experimental computer such as a Raspberry Pi. The experimental computer
% has to be reachable through a Windows share named OTBRToolboxShare; the
% files go into the folder Experiment i... |
aec98f8c60206ead94b00ca7f3caff57debd7095667a362c1828de3dfb5c9326 | MATLAB | 9,681 | 270 | function ZF_stitch(target, P2path, datapath,disp,mosaic,pxlsize,islice,pattern,sys,ds,stitch)
%% stitch the fitting result using the coordinates from AIP stitch
%% define grid pattern
% add subfunctions for the script
addpath('/projectnb/npbssmic/s/Matlab_code');
% displacement parameters
% xx=92;
% xy=-4;
% yy=97;
% ... |
c20007dbdf7b88bc1b363945c6db9ef5d1712eb8905cf24ce589451123a8161e | MATLAB | 9,683 | 223 | %% Experiment: Parameter Estimation for Real data
% Description:
% - Learn multiple structures with various regularizers (lambda) and
% tolerance values
% - Train the parameters with respect to each of the structure learned
% in the previous step with various values of parameter estimation
% regula... |
15296b61db0c4bb13c64c3958188716d57977383cfd26bf6bffe564a73cd4102 | MATLAB | 9,690 | 212 | function [FitAllParams, IC] = FitData(Input,config)
% Zilong Ji, UCL, zilong.ji@ucl.ac.uk
% Wrapper function
% ===================================================================================
%load configurations necessary for the script
Model_Name = config.ModelName;
if Model_Name == "sigma_nu" %simp... |
f336177904f404756634d69481c737fcb421bd9931c722a0e968fc14a72ddc66 | MATLAB | 9,691 | 393 | function psino = rebin_fan2par(fsino, sf, sp, varargin)
%|function psino = rebin_fan2par(fsino, sf, sp, varargin)
%|
%| Rebin fan-beam sinogram into parallel-beam (or mojette) sinogram.
%| (Also useful for parallel-to-mojette rebinning.)
%|
%| in
%| fsino [ns nbeta (L)] fan-beam sinogram (or possibly parallel)
%| sf ... |
a26c793a2eb431e26948a85031c56b711870e1cf06a0d7e0e8f3a845ed1296ce | MATLAB | 9,698 | 305 | %function [] = DataGeneration()
%% This code works correctly as of 230511, please do not change anything (SPW)
clear all; close all;
%--------------------------------------------------------------------------
addpath(genpath([fileparts(which(mfilename)) '\matlab']));
addpath(genpath([fileparts(which(mfilename)) ... |
0a2d1d461709401035a4fe016c6933c85e19bea972c4acad40749c2b5ad4c4d7 | MATLAB | 9,707 | 261 | function a=rdrawhd(d)
% rdrawhd - parses MCS data header (version 1) (datastream method)
% a=rdrawhd(d) parses MCS data header
% To use this function data-files must be open already
% (fid is input parameter). ChannelID is incremented by 1
% because the first channel sampled is 0, i.e. its index
% in the sampl... |
dfdb4250de60e7a7b3e387f04b77557cf0a0c7bce311b0e645c4b9d55867c557 | MATLAB | 9,722 | 253 | %This is a companion script to the labeling GUI that allows you to plot
%your data against your labels.
%% Plot Mean Trace selected times PIS (GREEN)
recTimes=cell2mat(label_struct.G_preictal_mean.labels);
recTimes=recTimes(:,1);
figure
plot(t_2p,mean(data.Fc1Gdff_flt2),'color',[0 1 0])
hold on
line([recTimes recTime... |
c07b955b8212c0695876b7f2fe8691cb6d0c216bea31657caa6e88feccf4ad3e | MATLAB | 9,730 | 219 | function out = loadSound(sh, filename)
% Load an audio file and hand it to the sound device for playback.
%
% The file is read, converted to the sample rate of the open audio device
% if necessary, and stored inside PsychPortAudio as a ready to play buffer.
% The returned struct is the handle you pass to controlSound t... |
48976fb77d22b3dbe133450907f5747e93567e2b13caa7ed27a30b58c76191eb | MATLAB | 9,737 | 353 | function [B, C, hk, wk] = mri_fun_approx(ti, uj, vj, f1, f2, varargin)
%|function [B, C, hk, wk] = mri_fun_approx(ti, uj, vj, f1, f2, [options])
%|
%| UNDER DEVELOPMENT
%| For certain iterative MR image reconstruction problems, we have
%| signals of the form f1(uj ti) f2(vj ti), for some functions f1() and f2(),
%| a... |
7a45747ac890c7e7bf3274f3debf1dbb7d7aa35055cea9329fd3ae138d82432b | MATLAB | 9,741 | 255 | % description:
% 1) plot ERP for both conditions in a desired region,
% 2) plot region specific spectrograms w/ or w/o ERP removal
% 3) plot ERP for a given chan, and mean(trials-ERP) in the same chan
% 4) plot idividual trials and trials-erp
% 5) individual channel PSD
close all;
reg = 'CA3'
cue_responsive = 'yes'
s... |
90b0046b1a0e8b5ec679e5d7b2abf0a5b3569c28f51e2f71ed57fb28a531cbc2 | MATLAB | 9,742 | 274 | %% Script to create output for Fig. 5 - receiver operating characteristic curve for proportional errors
% Andrea Castegnaro, UCL, 2022 andrea.castegnaro@ucl.ac.uk
% Using support vector machine (SVM) to classify two groups based on their
% fitted parameters using an holdout strategy (60% training set 40% testing
% set... |
1f04ecaaa0d421100ed8b09ac71cdc96f47454da91083fe8ebc9a09431697fcd | MATLAB | 9,753 | 319 | function spm_eeg_review(D,flag,inv)
% General review (display) of SPM meeg object
% FORMAT spm_eeg_review(D,flags,inv)
%
% INPUT:
% D - meeg object
% flag - switch to any of the displays (optional)
% inv - which source reconstruction to display (when called from
% spm_eeg_inv_imag_api.m)
%____________________... |
d83890beb458ee4c3bdf09fa7ffdf0b45a1c9a2df7f7f1976fc15ef43101340c | MATLAB | 9,760 | 168 | function [Objects] = f_imageAnalysis(Label, ch1, ch2, ch3, ch4, PreviewPath, MetaTable)
%vol(ch1, 0, 5000) Hoechst
%vol(ch2, 0, 4000) 647 Sox2
%vol(ch3, 0, 3000) 568 LAMINB1
%vol(ch4, 0, 3000) 488 TUJ1
ObjectsThisOrganoid = table();
%% Max projections
%NucMax = max(ch1, [],3); imtool(NucMax... |
d031a0c8926824511f69b88fa7186b1396c510bcc33a8986062b3a62d916ee54 | MATLAB | 9,763 | 192 | function [Objects] = f_imageAnalysis(Label, ch1, ch2, ch3, ch4, PreviewPath, MetaTable)
%vol(ch1, 0, 5000) Hoechst
%vol(ch2, 0, 4000) 647 MAP2
%vol(ch3, 0, 5000) 568 Sox2
%vol(ch4, 0, 5000) 488 TH
%% Max projections
%NucMax = max(ch1, [],3); imtool(NucMax,[])
%% Segment Nuclei
% ... |
7fabef639044cbc43438efc7bab89e9fa129c5ab0c8c199c8055373dd6deb692 | MATLAB | 9,782 | 173 | function [Objects] = f_imageAnalysis(Label, ch1, ch2, ch3, ch4, PreviewPath, MetaTable)
%vol(ch1, 0, 5000) Hoechst
%vol(ch2, 0, 4000) 647 Sox2
%vol(ch3, 0, 3000) 568 LAMINB1
%vol(ch4, 0, 3000) 488 TUJ1
ObjectsThisOrganoid = table();
%% Max projections
%NucMax = max(ch1, [],3); imtool(NucMax... |
cee6156cd1807faf983a49dbb80d4f878fe5cf5a647c5a45f82d2b166f9d5fc3 | MATLAB | 9,783 | 209 | % PLOT AVERAGE THETA SEQUENCE SCORES PER PROTOCOL FOR SPEED DATA
% MH 2020
% Loads theta sequence scores per track and session ('quantification_scores.mat', from extract_sessions_thetaseq_scores.mat).
% First plot - For each quantification method (quadrant ratio, weighted corr, line fitting scores and slope),
% c... |
3d670cdc2fc02d0a8139bbbc273662d5252f9ec65f1f3f66c46fba6bf48f8089 | MATLAB | 9,785 | 182 | % LAP PRE SPIKE TRAIN CIRCULAR SHIFT
% Disrupts temporal domain. Shuffle used when analysing laps separately
% INPUT:
% decoded_thetaSeq, directional_place_fields,theta_spike_count - data structs
% track: current track ID being analysed
% lap_id: current lap ID being analysed
% num_shuffles: integer
... |
d9209eca54bcb299c13c242212feae769f6aa9d5f84146947b703940d1936aaa | MATLAB | 9,790 | 271 |
% NOTE: this script is meant to be run with the matlab GUI to make figures
clear all
% Add package to read NPY files into matlab
addpath('/Users/askeller/Documents/npy-matlab/')
% List the cognitive variables:
cog_vars = {'PicVocab','Flanker','Pattern','Reading','Picture','List','CardSort','LMT','RAVLT'};
% Specif... |
5346d4c8d246dd7229e04011745fe0b9733c38214139e1f0094a1f3cfa796c43 | MATLAB | 9,796 | 268 | function R2_stitch_NC(target, P2path, datapath,disp,mosaic,pxlsize,islice,pattern,sys)
%% stitch the fitting result using the coordinates from AIP stitch
%% define grid pattern
% add subfunctions for the script
addpath('/projectnb/npbssmic/s/Matlab_code');
% displacement parameters
% xx=92;
% xy=-4;
% yy=97;
% yx=-4;
... |
2bb91bffb97210eb8cdc6f65acd6bb94e51851c539f0227fa5e53984a530fe33 | MATLAB | 9,797 | 268 | function R2_stitch_8921(target, P2path, datapath,disp,mosaic,pxlsize,islice,pattern,sys)
%% stitch the fitting result using the coordinates from AIP stitch
%% define grid pattern
% add subfunctions for the script
addpath('/projectnb/npbssmic/s/Matlab_code');
% displacement parameters
% xx=92;
% xy=-4;
% yy=97;
% yx=-4... |
cb069835620cd3751a2fba6777b5f73faf10510de1869628cb33cb9248f93736 | MATLAB | 9,797 | 268 | function R2_stitch_7694(target, P2path, datapath,disp,mosaic,pxlsize,islice,pattern,sys)
%% stitch the fitting result using the coordinates from AIP stitch
%% define grid pattern
% add subfunctions for the script
addpath('/projectnb/npbssmic/s/Matlab_code');
% displacement parameters
% xx=92;
% xy=-4;
% yy=97;
% yx=-4... |
0f42420117a622eaa9c09b4ee536c362ac08d015a8a930b2ad3f147671dbaa26 | MATLAB | 9,809 | 231 | %% >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> DESCRIPTION
% DIS_rev2_fig_1
% Script to analyse data and produce Fig. 1 for:
% Grieves, Shinder, Rosow, Kenna and Taube (2022)
% The neural correlates of spatial disorientation in head direction cells. eNeuro
%
% USAGE:
% MAP_generate_maps... |
9a1b79ac4a7e63f05ba9e4429eef56e555b54dd885b38eb932d18f34caa95520 | MATLAB | 9,814 | 274 | function freezeColors(varargin)
% freezeColors Lock colors of plot, enabling multiple colormaps per figure. (v2.3)
%
% Problem: There is only one colormap per figure. This function provides
% an easy solution when plots using different colomaps are desired
% in the same figure.
%
% freezeColors freeze... |
8dbc710a8a7d67ab771169ffdf4b7ec8b8c47c3e8977c6be0793df473ca200fc | MATLAB | 9,815 | 301 | function [B,ndx,dbg] = natsortfiles(A,rgx,varargin)
% Natural-order / alphanumeric sort of filenames or foldernames.
%
% (c) 2014-2023 Stephen Cobeldick
%
% Sorts text by character code and by number value. File/folder names, file
% extensions, and path directories (if supplied) are sorted separately to
% ensure... |
303c3c142f980a56c92d1d07f1ddb3266373d222a330572d7c1a9b809309fff7 | MATLAB | 9,819 | 257 | function varargout = dartel3(varargin)
% DARTEL 3D image registration stuff
%
%_______________________________________________________________________
%
% FORMAT v = dartel3(v,g,f,param)
% v - flow field n1*n2*n3*3 (single precision float)
% g - first image n1*n2*n3*n4 (single precision float)
% f - second ... |
4ce5d094d65f7c0b9d5ae147608a60abacf11228f134bee56e3b7f58c586f72e | MATLAB | 9,826 | 267 | function [FWHM,VRpv,R] = spm_est_smoothness(V,VM,ndf)
% Estimation of smoothness based on [residual] images
% FORMAT [FWHM,VRpv,R] = spm_est_smoothness(V,VM,[ndf])
%
% V - Filenames or mapped standardized residual images
% VM - Filename of mapped mask image
% ndf - A 2-vector, [n df], the original n & dof of t... |
5334b7127cc26754f6d3300904b73e6124cc4ef2d784a29cca498b9b292b842a | MATLAB | 9,837 | 295 | clear all
close all
dbeh_path='C:\Users\xscogno\MATLAB\Flavio2\Waves\Tracking data\';
rec_data_path = 'C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\';
dpath_spikes='C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\';
dpath_sorting='C:\Users\xscogno\MATLAB\Flavio2\Waves\Sorting\';
dpath='C:\Users\xscogno\MATLAB\F... |
bc92142bcf089d4240d97f09a1615dcdedd1455325fed4744182a30429797039 | MATLAB | 9,844 | 255 | function SBJ01b_align_nlx_evnt(SBJ, proc_id, block_ix, save_it)
% Load, resample, and align photodiode from neuralynx system to clinical data
% INPUTS:
% save_it == 0: don't save plots, compare to raw data
% == 1: save plots and data, compare to import
% OUTPUTS:
%% Load, preprocess, and save out photodiode
... |
871e255016b608e351c681996acf9b49ef91287b21efad5c6ef1fc7f180383bb | MATLAB | 9,845 | 181 | % GET PLACE FIELDS WITHIN LAPS
% loads list_of_parameters.m, extracted_clusters.mat,extracted_position.mat, extracted_waveform.mat
% uses function extract_laps.m, skaggs_information.m
% INPUTS:
% track_id: track being analysed
% lap_start & lap_end: set laps to analyise by inputing start and end lap IDs
%... |
bdfdeeb4c1049dd7f0734523577d4fbd5dcb4745206db0994d31a59370c9c35d | MATLAB | 9,854 | 202 | function gap_linking_str = fun_graph_get_linker_ep2skl(vessel_image, vessel_mask, vessel_skl, ep_sub, ep_all_sub)
% fun_graph_get_linker_ep2skl use threshold relaxation and shortest path on
% designed metric to find a 3D line segment that connect the inut endpoint
% to a skeleton voxel in the nearby connected component... |
5ea024bb63a37e93b1b431119b09aea132dbd1409ab660641a60bca1a2c7a13b | MATLAB | 9,858 | 286 | clc;clear;close all;
root='..\';
addpath(genpath([root,'NeuralCorrelateEvidenceAcc']))
%% settings --------------------------------------------------------------
subdir='total';
clusterName='clusterArea_paper';
regCluster=1;
if(regCluster)
subdir=[subdir,'_',clusterName];
end
shuffel=100;
type='dp';%cp,dp,contra
a... |
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