sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
e5b7cecac65330be4a86a843ee9009d3c6cb17d8d99d85ea62cf2b4be4362836 | MATLAB | 4,452 | 126 | a = sqrt(ROIdia(ismember(ROITable(:, 4), celltype) & ROISizepix >= 5 & max(ROIQuality.^2, [], 2) >0.1));
ma = median(a);
figure;
h = histogram(a, linspace(0, 5, 25));
h.Normalization = 'Probability';
%% Test if larger ROI size induce difference in frequency tuning
% split the data of each experiments by ROIs... |
9486865e374ae96215b5020b1a3a750f1cd56d3cede6e2e4c00407950e11ad4d | MATLAB | 4,467 | 121 | % Abffile bulk conversion script
%
% Goal: - convert and analyse abf files
% - skip certain protocols that are not analyzable at the moment
% - only analyse channels with something meaning ful associated to it: so check labbook list to see if channel
% was used... |
6364161a007e1eed34a0638194b7453b93b4b66e4f2ca68e91208b31038c70d2 | MATLAB | 4,468 | 151 | function DisplayExcludedTime(handles, hAxes, ml, iCh, chVis, linecolors)
global maingui
if get(handles.checkboxShowExcludedTimeManual, 'value')
mode = 'manual';
elseif get(handles.checkboxShowExcludedTimeAuto, 'value')
mode = 'auto';
elseif get(handles.checkboxShowExcludedTimeAutoByChannel, 'value')
mode =... |
4e22cc006451138a0892b1ef151a8a3d4266becc1576190d6d4c9ee87f6706e0 | MATLAB | 4,469 | 129 | %
%plot PSTH based on spikesToPlot structure that is used to plot rasters
%Also has options to deal with multiple-align rasters
%
%timeRangesToPlot: if set, only plot these ranges (from/to, one per row)
%binsize to use for PSTH
%triallength in ms
%grpRanges till which trial nr is each grp (inclusive),
%ie grpRanges=[1... |
3988afab0bbfc9645fdc50b7d74b8842daea4d3a2cde2b15431ce4548078d556 | MATLAB | 4,472 | 146 | % 1. Add the path of the current script to the search path
% 2. Change the current folder to "Supp Fig9 CFstimulation"
% 3. Using ctrl+enter within each function to run each section
%% Section 1: open files
% ctrl+enter to run this section
clear
co=lines;
co(6,:)=[.5 .5 .5];
cnum=[6 2 4 5];
legendlist=[];
... |
bdc22bbd62ec2cb6eb0beff066497f35ce5d24d46c498a92939357a0c8a29d96 | MATLAB | 4,473 | 126 | function this = m10l5Analysis(this)
%M10L5ANALYSIS Perform nonparametric M10 and L5 analysis on an ACTI object
%
% $Author: Peng Li
% $Date: Jun 15, 2021
% $Modif.: Jun 25, 2021
% instead of calculating per day, average the days first
% see comment where revised
%
x = ... |
e633b70fb2ddd5053c9136bbe698cd25e49549f037a73d0c73b3543143798a53 | MATLAB | 4,478 | 142 | % Classifier unit test
%
% Classifier: liblinear
% Note: the classifier itself is not being tested since it's external but
% rather the MVPA-Light interface.
rng(42) %% do not change - might affect the results
tol = 10e-10;
mf = mfilename;
%% first check whether LIBLINEAR is available
check = which('train','-all'... |
bbd6ea454d2414ba1074a31d20d6c2eca016bf036c4b10ab8bb6eddb0125d8ae | MATLAB | 4,479 | 148 | % Script to compute the branching ratio
% for running locally, can call 'setSederbergAvaProjPaths' instead of
% setting data_dir, print_dir here.
% data_dir is the path to the sample data (can be relative path from cwd)
data_dir = 'sample_simulation_data/';
% where you want to print outputs
print_dir = '';
data_sub_... |
239560bc66c2654bb9e694b6793a37743cd904057df6aebce2a26a99deba1535 | MATLAB | 4,482 | 157 | function net = somtrain(net, options, x)
%SOMTRAIN Kohonen training algorithm for SOM.
%
% Description
% NET = SOMTRAIN{NET, OPTIONS, X) uses Kohonen's algorithm to train a
% SOM. Both on-line and batch algorithms are implemented. The learning
% rate (for on-line) and neighbourhood size decay linearly. There is no
% e... |
4187cb6d9c50b02333ba6ad64c35b6156abff303ed36b24325bb2b5fcd5a1454 | MATLAB | 4,486 | 152 | %Wheel data summary and plotting
%Chris Mount July 2018
%% Load Data
disp('Select Data File')
handle = uigetfile('*.mat','Select data file'); %identify data file
wheelFile = load(handle);
wheelData = wheelFile.rungCounts;
%request categorization of each mouse - genotype, gender, age, manip
wheelNum = input('How many w... |
bf51f9dbb7739d18f61ab95302aa056e522514da1b87a0fa73468e0e9079b2c2 | MATLAB | 4,490 | 115 | function [update] = symmetric_polynomial_expansion_registration(...
moving, fixed, movingDeformed, fixedDeformed, ...
multiModal, transformationModel, varargin)
% OPTICAL_FLOW_REGISTRATION Estimates a displacement field using optical flow
%
% [update] = symmetric_optical_flow_registration(...
% moving, fixe... |
1be5a978191e9b61adb64183979e046583469eb8f9a6c187188f3d6ed56f7799 | MATLAB | 4,493 | 125 | function [K1_new, K0_new, K2_new] = tuneTargetCancellation(K1, K0, K2, ...
B, I, S, mask_learn, head, target, conds, light, sines)
% Allow the predictive target signal weights to change
% with learning. Don't change anything about K1 (model before learning)
% Set to 0 to used close loop calculation (for nonlinear ... |
b85ccb15f8ce29721423c7d691700206dd4308c8a396813f5184994bb7f0e82f | MATLAB | 4,493 | 137 | %% Bar Plot of d' and LR Bias (Pooled + JK errorbars)
load('../data/behavData.mat')
close all
%% Initialize variables
par_all = cell(1,2);
par_all_mi = cell(1,2);
par_val = cell(1,2);
par_jk_ortho_avg = cell(1,2);
par_jk_mi = cell(1,2);
actual_param = cell(1,2);
actual_param_mi = cell(1,2... |
c3ce102a505c1340d1961efa5972a45be956c0a33ce2493280ca52ffdd9c6fe4 | MATLAB | 4,497 | 180 | % plotSpectrogram plot an array of spectrograms on a single fig
%
% fig = plotSpectrogram( x, y, z, USF, plotmode, zscaling, yscaling, nCycles )
%
% x, y, z time/phase; frequency; power (or any other measure)
% USF {1}; up-sampling factor
% plotmode {'imagesc'} or 'contourf'
% zscaling ... |
b509b8072f5114a1d153f3d257d553a55ae101cf6f4d1cf9bef70b7fbedc1bc3 | MATLAB | 4,499 | 98 | % parameters
if ~exist('zmat_orig_file','var'), zmat_orig_file = '/cluster/projects/p33/users/alexeas/elleke/data/zmat_orig.dat'; end
if ~exist('zmat_perm_file','var'), zmat_perm_file = '/cluster/projects/p33/users/alexeas/elleke/data/zmat_perm.dat'; end
if ~exist('num_eigval_to_keep', 'var'), num_eigval_to_keep = 10;... |
6bc1c77a07066ca2fce1e85d1a24789710b92fb49c57069e3715e5aa8bd3e919 | MATLAB | 4,501 | 141 | %{
Copyright (C) 2023 N. Suhas Jagannathan
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed i... |
64f2edc5b54a6c3cd70a8a567f0a38ac13e4a267f1a547db0b7e58ff158f9bdb | MATLAB | 4,506 | 119 | %This function identifies lines and compute basic alignment (single plane)
%% Inputs
subjectFolder = s3SubjectPath('14','LC');
slideName = 'Slide04_Section02'; %Leve empty for loading of all slides, otherwise specify 'Slide01_Section01'
% How to identify the lines. Can be:
% - 'ByLinesRatio' - use lines rat... |
f21bf89b83ef91bc1b4e9f3edf21cb2301f83e1db613cafdb69c47d3bd028a8e | MATLAB | 4,510 | 118 | %% TRANSIENT COLLECTIVE ANTI-PHASE BEHAVIOR (HFOs, 610 Hz)
% SETTING
clear
rng(19) % seed
Path = [pwd, '\IN_sims\'];
clrs = ["b","r","g","k","c","y"]; % colors
per_clr = [0.9290,0.6940,0.1250]; % periodogram color
% TIME
T = 800; % time span
dt = 0.01;
% COUPLING
eps1 = 0.05;
eps2 = 0.01;
epsilo... |
67f3a4cfb36f525bfde199d8f99c89ed4956b132fbe15be83c96d084cf0bf24e | MATLAB | 4,511 | 117 | load('preprocessed.mat')
load('mutations.mat')
drugs = {'Erlotinib', 'Lapatinib', 'PD0325901', 'PLX_{4720}', 'CHIR_{265}', 'Selumetinib', 'Vandetanib'};
cell_lines = strrep(cell_lines, 'TUMOR-', '');
conc = [2.5e-3, 8e-3, 2.5e-2, 8e-2, 2.5e-1, 8e-1, 2.53e-0, 8e-0];
concLog = log10(conc * 10^3);
%size(data_fit)
%size(d... |
4446719507836d41e8f27d813e6b7aacb13cea0d9169c48511daa26165e9c28d | MATLAB | 4,512 | 143 | function pSVR_plot_bfca_behavior_correlation(p)
%% Plot bfca-behavior correaltion for all subjects
% Get relevant variables from 'p'
delay = p.psvr.delay;
p.psvr.label = 'target';
%%% Prepare data %%%
% Load results
stats_file = dir(fullfile(p.dirs.data, 'analysis', 'all', 'results', ['pSVR_' p.psvr.event '_' p.psv... |
0c295b22abb25d203cc254de5a04b82b4a5644f4cb82c02d36491289191f9f10 | MATLAB | 4,513 | 124 | %LoadBinaryChunk - Load data chunck from an open binary file.
%
% USAGE
%
% data = LoadBinaryChunk(fid,<options>)
%
% fid file id (obtained via fopen)
% <options> optional list of property-value pairs (see table below)
%
% ====================================================================... |
85cdace4bf7b49d142f336488c5ef65ad18d2d6fd5bd50a6bee15bab561e7f64 | MATLAB | 4,513 | 114 | function [pxx,w] = calcWelch(sbjNum,rawDataFN,respData)
saveDir = ['C:\Users\mn0mn\Documents\ResearchProjects\spatailAttentionProject\RawDatafNIRS\Experiment' num2str(sbjNum)];
processedDataDir = ['C:\Users\mn0mn\Documents\ResearchProjects\spatailAttentionProject\ProcessedDatafNIRS\Experiment' num2str(sbjNum)];
% Conve... |
a150dc977e9da1e15ccbdcf4a75e0459f21ae1b93061b3e955b2100baa18b0d5 | MATLAB | 4,515 | 106 | function mri_reconstruction_grid(p)
% Run the pSVR analysis as for a selection of voxel-counts and
% feature-space smoothing FWHM values (-> parameter grid-search). As it is
% not inherently clear which number of voxels or amount of smoothing yields
% the best reconstruction results for a given subject, the optimal va... |
cf46ad20c0d4852a30a9fca826b2efb8a4ce3d7e709a35695b89b3741870e17b | MATLAB | 4,519 | 135 | %DEMHMC3 Demonstrate Bayesian regression with Hybrid Monte Carlo sampling.
%
% Description
% The problem consists of one input variable X and one target variable
% T with data generated by sampling X at equal intervals and then
% generating target data by computing SIN(2*PI*X) and adding Gaussian
% noise. The model is ... |
9007e307dc581f5aea19e8742798b556c57cd36cec0a39b846df3f8348f644b8 | MATLAB | 4,522 | 161 |
clear
[task_info,supPath,~,task_DB_path] = loadDBAndSpecifyDataPaths('Vermis');
PLOT_CELL = false;
EPOCH = 'cue';
req_params = reqParamsEffectSize("both");
req_params.cell_type = {'PC cs'};
%req_params.ID = 4778;
lines = findLinesInDB (task_info, req_params);
cells = findPathsToCells (supPath,task_info,lines);
... |
1d81d5e1300195c9e66e4b56ec8cef9c413b639b33902d8f31bc4b7046dfa4cc | MATLAB | 4,534 | 176 | function [R, il] = Restrict(tsa, varargin)
% Restrict TSD to a new timestamp
%
% USAGE:
% R = Restrict(tsa, varargin)
%
% There are two main ways to invoke this function: in the first an array
% of timestamps is specified, and the tsd made out of the points in tsa that
% approximated those timestamps is retur... |
112d12aae9267c1d59c049a8b4dabd50bce324e6cd314ee2d9e5811edf7fef02 | MATLAB | 4,538 | 128 | function [subj] = dimred_template(subj,data_patname,selname,new_map_patname,extra_arg)
% Template for dimensionality reduction methods
%
% [SUBJ] = DIMRED_TEMPLATE(SUBJ,DATA_PATNAME,SELNAME,NEW_MAP_PATNAME,EXTRA_ARG)
%
% Adds the following objects:
% - dimensionality-reduced pattern object
% - possibly also patterns o... |
97d8e02ecbea85e03eb4bdb10cf7049d27a58cec98da91f2413b9dbfa2298168 | MATLAB | 4,540 | 106 | % function results = decoding_generate_output(cfg,results,decoding_out,i_decoding,curr_decoding,data)
%
% This function calls all decoding_transform_results for all entries in
% cfg.results.output and saves the returning outputs at results.(outname).
%
% It also handles initialization of output fields if they are... |
09f3ba2dca5770eb8e2d187db2fe5620c952f0fc4bef831dfc7e2df469e88afe | MATLAB | 4,544 | 121 | function output_filenames = create_sessions_tsv(varargin)
%
% Create a simple sessions.tsv for each participant of a BIDS dataset.
%
% USAGE::
%
% output_filename = bids.util.create_sessions_tsv(layout_or_path, ...
% 'use_schema', true, ...
% ... |
7b6edfd17879548df517dc0497fba44f9a494c920c1799ddb59583c7edeb1f96 | MATLAB | 4,544 | 100 | %% Figure S8: Plot Retinotopy/target position
RETINO_FILES = {...
'Monkey', 'Chamber', 'File'; ...
"Homer", "Left", "Data/M16D20151120R0Retinotopy.mat";
"ThorL", "Left", "Data/M21D20180612R0Retinotopy.mat";
"ThorR", "Right", "Data/M21D20170307R2Retinotopy.mat";
};
TARGET_COORD = ... |
b5b401538889c2ebf90f422c425602a331c26c408742534d24817da027a9d001 | MATLAB | 4,549 | 91 | % This script is a template that can be used for an encoding analysis on
% brain image data using cross-validated Mahalanobis distance. It is for
% people who have betas available from an SPM.mat (for AFNI, see
% decoding_tutorial) and want to automatically extract the relevant images
% used for calculation of th... |
4f548e3c3398ce92d8daff7d090a3623bb3583beb7c89ccdf759a23310934c20 | MATLAB | 4,550 | 92 |
%%% Add analysis scripts and required toolboxes to the search path %%%
% Analysis scripts
addpath(genpath('/.../WM_VI_EVC/code/analysis/'));
addpath(genpath('/.../WM_VI_EVC/code/revisions/'));
% Toolboxes
% 1. SPM12
% https://www.fil.ion.ucl.ac.uk/spm/software/download/
addpath('/.../spm12/');
% 2. The Decoding To... |
85483fb11cfa405d11ee0354b2c37df65438d91fdaf6b09f6baefed088606dff | MATLAB | 4,550 | 121 | % Plot voltage for article figure
% Note: SpikeReader returns entries with 1 less index then NeuronReader.
% E.g., length(stel_nV.v) vs. length(stel_nS).
% Todo: This could be looked into to see if the indices are offset by 1.
initOAT;
plot_voltage=0; % choose to plot current or voltage
% read in voltages
stel_nR = Ne... |
b8a5a7b72d925e33eecac0ea6358f5a3e46321da801bcce375a93130108c53eb | MATLAB | 4,552 | 142 | function [mstruct, param,f] = defineModel(modelname)
%build structure mstruct, which contains the hard-coded parameters in this
%function according to string input modelname
if strcmp(modelname,'jointRL')
mstruct.modelname = 'Joint-action RL model with perseveration';
mstruct.modelshort = 'jointRL';
mstru... |
26955193ed20109ae1f406f451e1caf94744204ca184b58f80dbd4e6ada39bee | MATLAB | 4,554 | 171 | function data = open_rwd(filepath,params)
Fluorescence_path = filepath;
recording_config = params.recording_config;
config = load_rwd_config(Fluorescence_path);
sep = strfind(filepath,filesep);
dataRoot = filepath(1:sep(end)-1);
Fluorescence_unaligned_path = [dataRoot filesep 'Fluorescence-unaligned.csv'];
raw_data... |
6f3132693c324504aa6c14f2fc9e19c1b1a1b32ed46259c61b3a368cb145df0f | MATLAB | 4,554 | 101 | function BarPlotGrouped_PreVPostTSMeanERROR_IndTrials(STRUCT, CONDITION, COLORS, TITLE, YLABEL, XLABEL, ERRORBARS)
%BarPlotGrouped_PreVPostTSMeanERROR_IndTrials plots a grouped bar chart with a bar for pre-stim
% mean and post-stim mean for each condition
% Individual trials will be plotted over the bars +- errorbar... |
ada75d9af8c85716b4c4a23bb9d54f1c2d3ada4c5fd4b4bd16735f0296807366 | MATLAB | 4,554 | 111 | function histologyInstructionsTextToStackConfig(subjectPath)
% This function converts histology instructions text file to stack config.
% (used by LC and some LD) Written at Jan 10, 2020.
%%
if ~exist('subjectPath','var')
subjectPath = s3SubjectPath('02','LC');
end
readFileFromOperational = false; % Set... |
ec70507299d70e554435632490edba42139c9f2b4eb3f2a58d22b2227a2d1029 | MATLAB | 4,554 | 108 | function CV = mv_get_crossvalidation_folds(cv, y, k, stratify, frac, fold, preprocess, preprocess_param)
% Defines a cross-validation scheme and returns a cvpartition object with
% the definition of the folds.
%
% Usage:
% CV = mv_get_crossvalidation_folds(cv, y, k, stratify, frac, fold)
%
%Parameters:
% cv - ... |
2b1be1c7fd21c654c147edebc7baa2d647e0021485570d9046469d55f24cdd46 | MATLAB | 4,556 | 118 | %% COLLECTIVE ANTI-PHASE SYNCHRONY (transient HFOs, 740 Hz)
% SETTING
clear
rng(17) % seed
Path = [pwd, '\DP_sims\'];
clrs = ["b","r","g","k","c","y"]; % colors
per_clr = [0.9290,0.6940,0.1250]; % periodogram color
% TIME
T = 500;
dt = 0.01;
% COUPLING
eps1 = 0.25;
eps2 = 0.05;
epsilon = [ eps1, ep... |
e48952bb06288c3654e0b6ceaff4240043c2b21e18378764949d07a18fba570a | MATLAB | 4,556 | 159 | clear
[task_info,supPath] = loadDBAndSpecifyDataPaths('Vermis');
req_params.grade = 7;
req_params.cell_type = {'PC ss','CRB','SNR','BG msn'};
req_params.cell_type = {'SNR'};
req_params.task = 'choice';
req_params.num_trials = 120;
req_params.remove_question_marks = 1;
req_params.remove_repeats = false;
EPOCH = 'cue... |
a7acb1c976d395aea25f137d02046f392d73af18605ab78556cecee514668dbe | MATLAB | 4,570 | 90 | function [fs_data,skip_feature_selection] = decoding_prepare_feature_selection(cfg,i_train,i_test,i_step,current_data,subindex,previous_fs_data)
% Pack feature selection data (subfunction of decoding.m)
% Martin 2014/01/12
% TODO: this is still quite dirty and error prone, best move the reading of
% external ... |
d2701bbf50fdf71141d67510ff3a88174d82c73845a85090449ef00b2623f7d8 | MATLAB | 4,574 | 158 | function [run_log, full_log, experiment] = load_log(sub_id, p)
% function [run_log, full_log, Experiment] = load_log(sub_id, p)
%
% Load experimental logfiles of all sessions for one subject. Includes
% exceptions for each subject according to their specific experiment.
%
% Input:
% - i_sub: ID of the current subjec... |
0c24a4fe2f4e892162d2329f8fc052cb7367e18542fef027d23dcdda1a550c46 | MATLAB | 4,580 | 140 | #import <UnityAds/UADSBanner.h>
#import "UnityAdsUtilities.h"
typedef void (*UnityAdsBannerShowCallback)(const char* placementId);
typedef void (*UnityAdsBannerHideCallback)(const char* placementId);
typedef void (*UnityAdsBannerClickCallback)(const char* placementId);
typedef void (*UnityAdsBannerUnloadCallback)(cons... |
2ad2a0574d411c6ae112957a7710187e746b92ee15a024030f5ab6b9a6efebc0 | MATLAB | 4,587 | 120 | % for sbj 08 and 10
function [pxx,w] = calcWelch_OldProbe(sbjNum,rawDataFN,respData)
saveDir = ['C:\Users\mn0mn\Documents\ResearchProjects\spatailAttentionProject\RawDatafNIRS\Experiment' num2str(sbjNum)];
processedDataDir = ['C:\Users\mn0mn\Documents\ResearchProjects\spatailAttentionProject\ProcessedDatafNIRS\Experime... |
fcec112eb39b893559192d3120f8a1c789b11590f51b20772973b0de8fbc28b6 | MATLAB | 4,590 | 92 | % ----------------------------------------------------------------------- %
% M U L T I P L E T E S T I N G %
% ----------------------------------------------------------------------- %
% Function 'mt_fisher' computes the Combined Probability of Fisher for %
% multiple c... |
59c43a98495f425e0cbf33ecbc909b5386c1b9f641893d4a3bfe3b5635c19efd | MATLAB | 4,593 | 152 | %DEMGMM1 Demonstrate density modelling with a Gaussian mixture model.
%
% Description
% The problem consists of modelling data generated by a mixture of
% three Gaussians in 2 dimensions. The priors are 0.3, 0.5 and 0.2;
% the centres are (2, 3.5), (0, 0) and (0,2); the variances are 0.2,
% 0.5 and 1.0. The first figu... |
b553ed1e58f1f270b134725daa0a72533f2b123341ff3d8a81ca3ea802bb3644 | MATLAB | 4,596 | 136 | function this = plot(this, varargin)
%PLOT plot error ellipse on a clock axis
%
% see also: FIT, CI, COSINOR
%
% $Author: Peng Li
% Brigham and Women's Hospital
% Harvard Medical School
% $Date: Dec 13, 2021
%
% only works for one component fit
if ~isscalar(this.CycleLeng... |
77bd7608f570cb17a3585bb32dbb9d8a396f2b72dcb5c7e1a53a8625c266ea54 | MATLAB | 4,605 | 130 | clear all
load('../data/opt.mat')
for pair = 1:length(opt.participant_pair)
clear segemented_trial_p segemented_trial_o event_no_error_p event_no_error_o
fprintf('Event correction for pair session %d: %s - %s \n',...
pair,opt.participant_pair{pair,1},opt.participant_pair{pair,2})
... |
3db9dc2f2a5d34b19546e825077c77837c6661b97d310c468e6b8d2cdd4cb84a | MATLAB | 4,612 | 153 | % This demo shows how a simple searchlight decoding runs on simulated 3D
% toy data. The toy data are Matlab matrices and no real fMRI or EEG data,
% i.e. results do not necessarily generalize to real data.
%
% The script creates multiple volumes in the shape of an ellipsoid where
% all entries are filled with r... |
4c2711e444fa72d212f32c14744ae5bcc7440f8f60966e869162c1f53465b5c9 | MATLAB | 4,612 | 103 | function [update] = symmetric_phase_registration(...
moving, fixed, movingDeformed, fixedDeformed, ...
movingCertainty, fixedCertainty, ...
movingDeformedCertainty, fixedDeformedCertainty, ...
transformationModel, currentScale)
% PHASE_REGISTRATION Estimates a displacement field using phase-difference
%... |
0653982ebfad3e5705e792359186976b02a5eb3276770da3e5c4d47586bb6ee7 | MATLAB | 4,613 | 156 | function EEG_buildGND(dir,fin,model,inprefix,regtype,eeginfix,framewin)
% settings
% framewin = [-1 0.5]; %time of interest
nChan = 64; %number of channels
%get input folder
filedir = fullfile(dir.dir_eeg, inprefix, regtype);
% get behavior from simluations
[BEH] = EEG_loadVars(dir,fin,model);
nS = length(BEH);
%p... |
c91fc87add892c6cc1475175ff81395c84e3a72a53d4ef8c3f5a0ed1ef613f0c | MATLAB | 4,614 | 127 | function [IS, IV, xPeriod, PercMissingData, PercMissingBin] = isiv(x, epoch, scale, period, varargin)
%ISIV inter-daily stability and intra-daily variability for locomotor activity data
%
% epoch: sampling time (in min)
% scale: at what scale IS and IV are estimated (in min)
% period: a range (in hr) used for search... |
f5002d0ceae299d43cd35aa5dece95f8268d639f2679641b26e3053e7ab512ce | MATLAB | 4,614 | 160 | %DEMGP Demonstrate simple regression using a Gaussian Process.
%
% Description
% The problem consists of one input variable X and one target variable
% T. The values in X are chosen in two separated clusters and the
% target data is generated by computing SIN(2*PI*X) and adding Gaussian
% noise. Two Gaussian Processes,... |
bc217eddcc534c1810ae54f47cbeed3fc48ba4167e2676e8bd6ed832d4283515 | MATLAB | 4,615 | 136 | function runHistPreprocess_base(runAutomatic)
%This function runs all the preprocessing steps of histology.
%1) Importing to aws
%2) Aligning H&E slides with Flourecense microscope images
%This script is run as stand alone and would propt user with all required
%inputs
%No need to change any parameter, just ... |
e1b95925f88939e95af0c16a798b44470623939a61f8c9c07ab6641e27d6a23d | MATLAB | 4,615 | 147 | function outStatus = histSVSImport(histologyFP,subjectFolder,slideSections,isDelayedUpload,tmpFolderSubjectFilePath)
%This function imports H&E Images from SVS format
%INPUTS:
% - histologyFP - file path pointing to .svs
% - subjectFolder - pointer to the cloud where the subject is
% - slideSections - what slides ... |
1dd48dd9303c5152f26b8e4c176277bd6f724e9bcb7ca5eb703186f3433ca0ab | MATLAB | 4,616 | 146 | %% Bar Plot of d' and LR Bias (Pooled + JK errorbars)
% data_path = 'E:\Adi\Copy_of_V4_FEF_Project\Code_Plotting\data';
% functions_path = 'E:\Adi\Copy_of_V4_FEF_Project\Code_Plotting\functions';
% addpath(functions_path);
% addpath(data_path)
%% Initialize variables
par_all = cell(1,2);
par_all_mi = cell... |
8d6cfb757e9cf92a52a7047e83887bed2e9e00abaaaee9c58d0cb0e3cbe74a7e | MATLAB | 4,618 | 118 | function [clabel, dval, prob] = test_naive_bayes(cf,X)
% Applies a Naive Bayes classifier to test data.
%
% Usage:
% clabel = test_naive_bayes(cf, X)
%
%Parameters:
% cf - classifier. See train_naive_bayes
% X - [samples x features] matrix of test data or
% [samples x ... x .... |
9bd77c97fbb4badf4d7fadee0fcc077cb88857efe22cdee1afb7265d3f4dc053 | MATLAB | 4,622 | 149 | function unittest_optimisation_TrustRegionDoglegGN
% Test of optimisation functions
%
% Function: TrustRegionDoglegGN
%
% Standard test functions are used to check whether the optimisation
% converges to the correct solution. Most test functions are found in
% https://en.wikipedia.org/wiki/Test_functions_for_optimizat... |
29a2430486275f2d2de8fb1868c7c65ad53ed4223cca27b686e63b60fb54300b | MATLAB | 4,623 | 136 | function this = plot(this, varargin)
%PLOT plot error ellipse on a clock axis
%
% see also: FIT, CI, COSINOR
%
% $Author: Peng Li
% Brigham and Women's Hospital
% Harvard Medical School
% $Date: Dec 13, 2021
%
% only works for one component fit
if ~isscalar(this.CycleLeng... |
19aee647f2e44f37009dea5fe0b136d97f23c7243c1c7b4cd573c2bfc34b0206 | MATLAB | 4,635 | 158 | % During Reward
clear
[task_info,supPath] = loadDBAndSpecifyDataPaths('Vermis');
req_params.grade = 7;
req_params.ID = 4000:6000;
req_params.remove_question_marks = 1;
req_params.num_trials = 50;
req_params.task = 'saccade_8_dir_75and25|pursuit_8_dir_75and25';
req_params.remove_question_marks = 1;
lines = findCspkSs... |
24f46e2701e953fbe5dbed31fff6356d215a2533eae169703a237d8d15a9409e | MATLAB | 4,651 | 142 | function [corrected_data, sigmas,dn, correctionMatrix] = SOUND_fast_SSP(data, LFM, iter,lambda0,U, inputData, sigmas, estimate_just_noise)
% This function performs simultaneous SSP_SIR and SOUND: SSP is performed
% withing SOUND iterations without mixing the channels
%input:
% data: (channels x time points x tr... |
795677e688829375225477014a25e33f45878b3872c9512a35cc04c39bb0fb47 | MATLAB | 4,652 | 134 | function [X,clabel,Y] = simulate_checkerboard_data(nsamples, nchecker, nclasses, prop, scale, do_plot)
% Creates checkerboard data in two dimensions. The space is split into an
% nchecker x nchecker checkerboard. Each checker contains data from one
% single class.
%
% Note that checkers are filled row-by-row, cycling t... |
414256d7a43ea4dca7a8e7936c1db952b70dc6d58ff520d4a347d09d5e026bbc | MATLAB | 4,667 | 170 | function [subj] = create_xvalid_oddeven(subj,runs_selname,varargin)
% Create split-halves xvalid indices
%
% [SUBJ] = CREATE_XVALID_ODDEVEN(SUBJ,RUNS_SELNAME,VARARGIN)
%
% Defines odd runs as training and even runs as testing
% for selector 1, and vice versa for selector 2.
%
% See CREATE_XVALID_INDICES.M for more inf... |
47487f502c95bc4314d083ab622802588e8a6590f8688b078db826d0e7766459 | MATLAB | 4,668 | 122 | % run CircleAnalysis_ResponseScreening072122_MorphSeg.m or
% CircleAnalysis_ResponseScreening071222_MorphSeg.m first
clear all; clc;
GroupData.Days = {...
% 1 2 3 4 5 6 7 8 9 10
'092519', '093019', '100319', '100719', '103118', '110318', '110... |
99bd0bd4b8ac7e8bd933e63784f33140ccd065502683569e16bb537c8ce5de86 | MATLAB | 4,673 | 159 | function [pval table] = circ_wwtest(varargin)
% [pval, table] = circ_wwtest(alpha, idx, [w])
% [pval, table] = circ_wwtest(alpha1, alpha2, [w1, w2])
% Parametric Watson-Williams multi-sample test for equal means. Can be
% used as a one-way ANOVA test for circular data.
%
% H0: the s populations have equal m... |
95937e60930a007b8d69a4400670d484742fbf198c3e85d147bb7cf13f74ab5a | MATLAB | 4,674 | 164 | function [err, ErrMessage] = WriteBrikHEAD (FileName, Info)
%
% [err, ErrMessage] = WriteBrikHEAD (FnameHEAD, Info)
%
%Purpose:
% Create the header file for an AFNI Brik
%
%
%Input Parameters:
% FnameHEAD the name of the header file
% Info, a structure detailed in function BrikInfo
%
%Output Parameters... |
b3cab8f0900d8badc27499f8b7626f99917eeaf2b4350e02dcaae03e47e8708b | MATLAB | 4,679 | 117 | function cf = train_libsvm(param,X,y)
% Trains a kernel support vector machine (SVM) or a support vector
% regression (SVR) using LIBSVM. The sym_type parameter controls whether
% classification or regression is performed, see below.
%
% For installation details and further information see
% https://github.com/cjlin1/l... |
ae7a51104d3fee4d944efc0451f3684df91ad028cf53c763bd32ff5fcb0b1886 | MATLAB | 4,682 | 132 | close all
labelIO = true;
modelName = 'KEGGnet';
network = IO([modelName '-Model.tsv']);
annotation = readtable([modelName '-Annotation.tsv'], 'FileType', 'text');
inputNodes = annotation.code(ismember(annotation.ligand, 'True'));
outputNodes = annotation.code(ismember(annotation.TF, 'True'));
uniprot2gene = containers... |
b11bb5ec23426b124c8e7ea6799cc22b661a7b549b5ea93352bf4d128dec4537 | MATLAB | 4,694 | 127 | % figure 5D: suffeled vs insertion mirror-symmetric viewpoint tuning index
% last update: October 28 2022
% Amirhossein Farzmahdi
clear
close all
clc
% fixed random seed for regenerating same result
seed = 42; rng(seed)
% add path
addpath(genpath('functions'))
images_dir = 'mat_files/';
% loading data
load (images_... |
b5f167e7b8b0492f05756b0e9842eea6b8d0b06167733b865ae5cc745a755ca7 | MATLAB | 4,697 | 128 |
%% Compute delay maps from astrocytic in vivo calcium imaging data
% Code written by Peter Rupprecht (rupprecht@hifo.uzh.ch) in 2023
% Code is deposited in this repository: https://github.com/HelmchenLabSoftware/Centripetal_propagation_astrocytes
% See this repository for an explanation of the code
% Please... |
f42e6d91687a3ee8e91fc705b3f0b7bb2bb9fb91d95466e93a647164333301fe | MATLAB | 4,708 | 175 | function [s,mxy] = isochromat_GRE_MT(theta,phi,B1SqrdTau,TR,T1x,T2a,f,ka,G,Niso)
% [F0,Fn,Zn,F] = isochromat_GRE_MT(theta,phi,B1SqrdTau,TR,T1x,T2a,f,ka,G,Niso)
% Isochromat based simualtion of Pulsed MT systems w/ gradient echo sequences
%
% arguments:
% theta: vector of flip angles (rad... |
a3257ad9081cf1131fbda7efc294d5aeb91b617e965905c75c4fd3eb0c883d65 | MATLAB | 4,710 | 110 | %% Flow Distribution Data and Plots
function FlowDistributionOverTime(fileParams, flowDistParams, flowDistOverTimeParams)
%% Make Flow Distribution Data
fprintf('\n\n- - - Starting FlowDistributionOverTime - - -\n');
%% Figure Parameters
distOption = flowDistParams.distOption;
dataBinWidth = flowDistParams.dataBinWidt... |
2de5d2032d478824aec1e25f63c8d5d735ec1274bed0c13f73efec30d46fc68b | MATLAB | 4,715 | 168 | function [x, options, flog, pointlog] = conjgrad(f, x, options, gradf, ...
varargin)
%CONJGRAD Conjugate gradients optimization.
%
% Description
% [X, OPTIONS, FLOG, POINTLOG] = CONJGRAD(F, X, OPTIONS, GRADF) uses a
% conjugate gradients algorithm to find the minimum of the function
... |
312acec68d9c8fc5d318f5c1d3f915fd9e3d085c155ff5f52bea9bf0a4008c2b | MATLAB | 4,719 | 176 | folder = fileparts(which('trainLSTM.m'));
addpath(genpath(folder));
clear all
load('data/ParamsTrain.mat')
load('data/DataTrain.mat')
computeStatsTrain
computeRelevance=0;
prm.vx = [0.325 0.325 2];
prm.normVx=prm.vx./min(prm.vx);
X=squeeze(blobDataNan(:,:,:));
Y=y;
numPos=length(Y(Y>0));
num... |
a463fdb2b49dcc65f599fe39e253e6ad92d059db4e219949e77191ec3e866da5 | MATLAB | 4,728 | 128 |
%% Compute delay maps from astrocytic in vivo calcium imaging data
% Code written by Peter Rupprecht (rupprecht@hifo.uzh.ch) in 2023
% Code is deposited in this repository: https://github.com/HelmchenLabSoftware/Centripetal_propagation_astrocytes
% See this repository for an explanation of the code
% Please... |
da67d6504ed8380eb56c4f784868fad6992e7f19771580cb2c366a9001c2dd99 | MATLAB | 4,729 | 132 | function hi_lo_wave_clus_batch_211020(folder_address,electrodes,rec_leng)
%low wave clus
disp('Getting Low Spikes...')
for i=1:length(folder_address)
disp(strcat('Getting Low Spikes ',string(i)))
cd(folder_address{i})
mkdir lo
Get_spikes('Files.txt')
end
disp('Clustering Low Spikes...')
for i=1:lengt... |
1620dceeeae0c0ef784e64339175f1ede8a0ce2c6e6f1fbdeaebfb0afb0ba556 | MATLAB | 4,737 | 125 | function percent_change_210704(table1, table2, table3, table4, subregion)
% Creates pre stim post stim dot charts for upreg and down reg for either
% ff or fb axons and plots percent change
% Table 1/3 correspond to prestim and respectively correlate to table 2/4,
% ie table 1 is prestim ff table 2 is post stim ff, ta... |
e3e518955ae7d5a4d65c8ab6cf39e128cf9101d99ed4bc1fcf0dcf190853985d | MATLAB | 4,750 | 125 | %% load dataset
% load('dataset_201.mat', 'df'); % load data of 201 brain regions
load('dataset_53.mat', 'df'); % or load data of 53 brain regions
% load('dataset_64.mat', 'df'); % or load data of 64 brain regions
load('onto.mat', 'onto');
ivol = cat(1, df.Volume{:}); % get volume of each... |
fd7e80bea11c101f829ae4bc338aab9f91ad5b6bed6df078c92e450ce039aec6 | MATLAB | 4,752 | 134 | function batch_SurpriseMinimization
% in order to replicate the results from Wurm, Walentowska, Ernst, Severo,
% Pourtois, Steinhauser (2021), download the preprocessed EEG data and
% regression results via figshare
% (https://figshare.com/articles/dataset/2023_Wurm_SurpriseMinimization/23055974).
% Unzip and change... |
86f169771de7c3d6d8cc95b77b0e73c6d7cddd1b99982a76a060665c58ca8ccb | MATLAB | 4,755 | 125 | function percent_change_nopad_210704(table1, table2, table3, table4, subregion)
% Creates pre stim post stim dot charts for upreg and down reg for either
% ff or fb axons and plots percent change
% Table 1/3 correspond to prestim and respectively correlate to table 2/4,
% ie table 1 is prestim ff table 2 is post stim ... |
5dc3a4e8f330b2a88c5ddfdc1b46fe3023935dabdc80665b5854efb280c7ba5c | MATLAB | 4,758 | 98 |
% PERMUTATION ANALYSIS TO SEE WHICH BRAIN AREAS SURVIVE DURING NAV > MATH TASK (Nav-Math Experiment)
% The permutation have been computed usign the neurosynth mask (https://www.neurosynth.org/) obtained by
% searching 'Navigation' as topic
%% Set up the environment
clc
clear
restoredefaultpath
SPMPath = '/Applicatio... |
09cd3c93964a8f2b1ed093d4b799ce0f42fb49e28e6c480be66eeb14d0037339 | MATLAB | 4,759 | 110 | chdata=load('C:\Users\DBHeyer\Documents\PhD\China\Djai\Recordings\mats\180705_000.mat');
%settings
ch='Ch1';
secch='Ch2';
StringCh='Ch31';
CCStepkey='a';
stopkey='s';
sweeplength=4000; %length of each sweep in ms
%find beginning and end of CC step protocol
CCStepkey=unicode2native(CCStepkey);
stopkey=unicode2native(st... |
3789bdb0faabaa0c4a9fac96c546903c01026b16fe5f3c3ba6c58ac5e9585ed1 | MATLAB | 4,765 | 149 | % Add repts and CI. Used for publication
%
% Each array is channels x time x trial
% This use cross-validation where GLM is computed for each training fold
% and SS beta coefficients from training folds are used for test fold.
%
% Used for subset of channels
% DiffTLen!!!
% baselinePerf is classification accuracy for c... |
4d4d1a4bcb1a10d94dd16a9e1d183a22f4aa29f149919aed1b5e968b48187072 | MATLAB | 4,765 | 102 | % function decoding_out = libsvm_test(labels_test,data_test,cfg,model)
%
% Wrapper function for libsvm.
%
% See libsvm_train.m for details.
% Adapted to passing kernel as .kernel
% Brief explanation of decision values and how they are used to get the
% predicted labels:
% In two-class classification, there ... |
c7a7f4dfe36ad16a7c95fbed18940b0a3c8a259d2a38ba8fe9b87cc189ec37d4 | MATLAB | 4,769 | 136 |
data_location = TFR_Clustered_Data;
save_data_location = Stats_data;
condition_label = cond_labels;
% Channel list
Channels = cluster_labels;
%% PT vs. Color
for chan=1:length(Channels)
%% load 1st condition
tf_data = [];
data_file1 = [data_location condition_label{1} , '_tf_', Channe... |
c8912b9c9bc7b2f8f84a148190a7a8b4fad7f4de5a5822933d397a540a71de71 | MATLAB | 4,770 | 143 | function out=cntrd(im,mx,sz,interactive)
% out=cntrd(im,mx,sz,interactive)
%
% PURPOSE: calculates the centroid of bright spots to sub-pixel accuracy.
% Inspired by Grier & Crocker's feature for IDL, but greatly simplified and optimized
% for matlab
%
% INPUT:
% im: image to process, particle should be bright spots ... |
5d83fb16e27643605cf4b5243cdcf297049895d275d40e88276e5acb8cae6182 | MATLAB | 4,775 | 158 | function [d, state, num, val, nvox, coeff_v] = analyze_cluster2(clus, sourcemodel, target, sgn)
% ANALYZE_CLUSTER analyzes the array of clusters clus and returns for each element
% the following quantities:
% d = the distances between the centre of gravity of the legs of the 6D cluster
% and the target,
... |
ceea3b9e9ed6b3640cb5ff5cd0dc3c9ea31a4f0ea95e0dcdb0a47c7273894d4f | MATLAB | 4,778 | 159 | function [subj] = statmap_anova(subj,data_patname,regsname,selname,new_map_patname,extra_arg)
% Use the anova to select features that vary between conditions
%
% [SUBJ] = STATMAP_ANOVA(SUBJ,DATA_PATNAME,REGSNAME,NEW_MAP_PATNAME,EXTRA_ARG);
%
% Adds the following objects:
% - statmap pattern object
%
% Updates... |
4962b416512453974d404c16c021fb4d29b9221d7a8a5d20cd57d05954fcc68f | MATLAB | 4,792 | 138 | % tsss_rawdata_enm(infile,outfile,r_sphere,t_window,corr_limit,Lin,Lout,badchs)
%
% Perform tSSS on rawdata file 'infile' acquired with an Elekta Neuromag
% 306-channel MEG system. The tSSS-processed data are written into 'outfile'.
% The SSS operation is performed in the head coordinate system with the
% expansion or... |
9421d5410e22b6845a06a60c9344942e8db248ab04fbb572ee32ce251eacbde8 | MATLAB | 4,798 | 145 | %DEMHMC1 Demonstrate Hybrid Monte Carlo sampling on mixture of two Gaussians.
%
% Description
% The problem consists of generating data from a mixture of two
% Gaussians in two dimensions using a hybrid Monte Carlo algorithm with
% persistence. A mixture model is then fitted to the sample to compare
% it with the true... |
96f84947dc24cd19e9677e86c408feef0bd26c2d0b4486a2278f93ee25b7014a | MATLAB | 4,805 | 167 | % unwrapPhase into discrete cycles
%
% receives
% phs vector, phases 0-2*pi
% t0 center
%
% uphs unwrapped phases
%
% does
% -looks for the trough (phase pi) closest to t0. defines this as the
% trough of cycle0
% -goes forward through the data, define a peak as a 0-phase crossing
% preceeded b... |
8b250b9303a85b2683b7297af633f5b7ff06f12341fb1198259db9d97767585f | MATLAB | 4,806 | 185 | function [K1, K2] = Estimate_Number_of_Clusters_SIMLR(X, NUMC)
D_Kernels = multipleK(X);
distX = mean(D_Kernels,3);
W = max(max(distX)) - distX;
W = Network_Diffusion(W,max(ceil(size(X,1)/20),10));
[Quality] = Estimate_Number_of_Clusters_given_graph(W, NUMC);
[Quality_plus] = Estimate_Number_of_Clusters_given_graph(... |
3510430bc9e253131b51eac313500c4aa6357d0c5e6013c3583e95bdc264d405 | MATLAB | 4,808 | 134 | % manually load file 'BCtype_augdata_aligned_33023.mat'
clc; %close all;
addpath('\\storage1.ris.wustl.edu\kerschensteinerd\Active\Emily\BasicFunctions');
DistanceType = 'correlation';%'correlation''euclidean'
X = Dfull;
nP = size(X, 1);
BCTypes = [50 51 57 58 6 7 89];
BCTypelabels = {'BC5o', 'BC5i', 'BC5t', 'XB... |
f258187e902289de529602df9ed765f213328df7d543ce45e58381ec84b40dcc | MATLAB | 4,808 | 149 | classdef SoftmaxLayerClass < nnet.cnn.layer.Layer & nnet.internal.cnn.layer.Externalizable
% SoftmaxLayer Softmax layer
%
% To create a softmax layer, use softmaxLayer.
% This layer is useful for classification problems.
%
% SoftmaxLayer properties:
% Name ... |
4bb504c4178f33422f23931bd60d326540de8b163c50ad1e2d820532c1c658fb | MATLAB | 4,819 | 123 | function refreshSleep(this, actigraphy)
% REFRESHSLEEP Update sleep elements from ACTIGRAPHY
%
% $Author: Peng Li
% $Date: Feb 19, 2026
% $Modif.: Feb 20, 2026
% Facilitate lagecy plot (patches only)
% Apr 16, 2026
% Added gray-out patches for intermediate partial/abno... |
5f0582b9d70fb537dedfbd9ac3daddc6ba2a46747ec7823e60dee0af80bc6814 | MATLAB | 4,825 | 131 | function [labels] = enforceMinDuration(labels, limits, enforceInOrder, setUndef)
% enforceMinDuration Remove sleep stage bouts that are shorter than a threshold
% Zeke Barger 040920
% This function replaces bouts of each sleep stage that are shorter than
% some limit with the surrounding stage, assuming the l... |
d84631b8a1fc419e17b278e26ca9360485bc704aebf81cbf9f7822c18fa90d33 | MATLAB | 4,840 | 119 | function [results_data] = plot_cue_opp_separate_evokResp_bin_rsc_raw(cue_rsc, opp_rsc, ortho_rsc, evokResp_quad, evokResp, iWindow, iMonkey, yl, trial_type)
%% Plots V4 noise corr. raw values (not MI) at cue, opp, and ortho for pairs binned based on the Geometric Mean of their evoked responses.
%% windows
window_nam... |
7e592ebecc0a07a7a62ca9697980f49623e148d412bbd6794bc58f0d88f0ad6b | MATLAB | 4,841 | 120 | function [subj2get_11, subj2get_12, subj2get_com,...
subj2get_21, subj2get_22, subj2get_com2] = getLongSubj(volThresh,gaFilt,kidoScore)
serverDir = '/data/mril/users/all/mrdata/research/processed/CNMC/';
pretermDemo = readtable('/home/sdamera/Documents/DBI/fullPretermDemoSheet.csv');
pretermDemo.Project = regexprep... |
08d78c33b4d5d43ae96ce359114c2b2d9220be2aa3c79b31d991ad65d95ad80a | MATLAB | 4,843 | 167 | clear all
supPath = 'C:\noga\TD complex spike analysis\Data\albert\pursuit_8_dir_75and25';
load ('C:\noga\TD complex spike analysis\task_info');
MaestroPath = 'C:\Users\Owner\Desktop\DATA\albert\';
req_params.grade = 7;
req_params.cell_type = 'PC ss';
req_params.task = 'pursuit_8_dir_75and25';
req_params.ID = 4000:50... |
6877f8f701dc47b2afefb76ddf403ed73d6d5f8e2144b3b79b9ee457157923f8 | MATLAB | 4,844 | 139 | function [output] = ebc_feature_rater(subj, results, inum, subjnum, subfile, ...
varargin)
% Create EBC Feature_Rater submission file
%
% [OUTPUT] = EBC_FEATURE_RATER(SUBJ, RESULTS, INUM, ...
% SUBJNUM, SUBFILE, VARARGIN)
%
% SUBJ is the subject that t... |
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