sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
229930bf0a59ec6f6456d2223b2b2c77438f77abc7ff164ecc708cc332e67949 | MATLAB | 1,609 | 47 | function [TrainBatch,TestBatch] = train_test_division(stg,cls)
% gets the data of all classes and subjects and divides them into
% training and testing sets
%
% [TRAINBATCH,TESTBATCH] = TRAIN_TEST_DIVISION(STG,CLS) get the class data
% CLS and divides them into test and training sets TRAINBATCH and
% TESTBATCH.
... |
bf925ec370970e4e6fc338f31eba0c4e3d3f6aa2eb365531400ef3ff2ce55524 | MATLAB | 1,609 | 49 | function f = kummer(a,b,x)
% This function is downloaded from MATLAB center:
% http://www.mathworks.com/matlabcentral/fileexchange/29766-confluent-hypergeometric-function/content/kummer.m
%
% This function estimates the Kummer function with the specified tolerance
% the generalized hypergeometric series, noted below. ... |
deb633f768bc069d1386e8dd8a6cbe8870280b2bbb028c9136dada8a0cb996a4 | MATLAB | 1,609 | 42 | function [largest_percent_change, baseline_mean, exp_max, exp_min, baseline_std, exp_mean, exp_std, p] = percent_change_above_baseline(data,baseline_start,baseline_end,exp_start,exp_end)
%finds a baseline value by averaging the first part of the data, finds
%the max deviation from baseline, and calculate how much devia... |
453f652b0366ce4c4bc1aee97f34430eb9e75884712df80533a367f738d0c878 | MATLAB | 1,610 | 53 | function gridmap = showGrid_DownSamplingImage(image, segments)
% Overaly segmentation
[sx,sy]=vl_grad(double(segments), 'type', 'central') ;
s = find(sx | sy) ;
% gridmap = image ;
% gridmap(s) =244;
% gridmap(s+numel(image(:,:,1))) =164;
% gridmap(s+2*numel(image(:,:,1))) =96;
% gridmap = uint8(zeros(size(imag... |
e22942034a58e9adb671fc8ab8e756c430ff6a802a3cd757018d0879c17d996a | MATLAB | 1,610 | 55 | function plotCouplingSeq(curve1,curve2, couplingSeq, pairDist, curveLabels, figOrAxesHandle)
% Make a nice plot illustrating the Frechet couplings and highlighting
% where the maximal Frechet distance is
if nargin<5 || isempty(curveLabels)
curveLabels = {'curve1','curve2'};
end
if nargin<6 || isempty(figOrAxesHand... |
427429f6db582136c1ab4580bc5f8f8181a794a2821b0644875e7b820b64e249 | MATLAB | 1,611 | 44 | %% BLOCK_AVERAGING
% Performs a first quick analysis based on the grand average of the nirs data
% over participants (without Bayesian statistics).
%
% INPUT:
% - sub-*_trialsnirs.mat: the epoched fNIRS data of each participant
%
% OUTPUT:
% - plots (and videos) of the block average of each participant and plots of ... |
87810fa65e8261e5d01ab772f6c7f66b6d4b0412335811037a11a0bd4febdcd3 | MATLAB | 1,611 | 66 | function out = combineCells(x,dim,d)
%combines a collection of cells either horizontally or vertically,
%depending on the initial orientation
x = x(returnCellLengths(x) > 0);
if isempty(x)
out = [];
else
L = length(x);
lengths = returnCellLengths(x)... |
167ffe3861f7a79a255136ea9f602fc35db9e6d44a5f4e6a95db0bc0ee93178e | MATLAB | 1,613 | 45 | clear
file=dir('ACC*uncertain*.mat');
k=1;
for jj=1:length(file)
load(file(jj).name)
hit=find(outcome(:,1)==1);
rewardtime=outcome(hit,2)+60;
N=Info.Cellnumber;
for j=1:N
for i=1:length(hit)
reward.uncertain_hitDF{k}(:,i)=eachDF{j}(rewardtime(i)-14:rewardtime(i)+30,hit(... |
1f115a030ebcf2c38814f9d48653f683cb3a2b00f587be6e44f9f40e7e5e1df1 | MATLAB | 1,613 | 47 | function params = getParamsSTPRF()
% Function to get additional, default spatiotemporal pRF model parameters
%
% params = getParamsSTPRF()
%
% INPUTS
% none
%
% OUTPUTS
% params : (struct) default parameters, including:
% - params.spatialModel : 'onegaussianFit'
% - params.temporal... |
91a5cf8579f8c712dd8a066661663c9502c38cc8302915c3058ddf2eadde310a | MATLAB | 1,613 | 51 | %% corr the coupling R2 or P-value with functional sPET
roi_num = 48;
load('Edge_GLM_fun_str_dis_commu_DBM.mat')
AR = cat(1,results(:).AR);
AR_p = cat(1,results(:).AR_moran_p);
load('Sub_spet.mat')
spet = mean(sub_spet,2);
data = spet;
data_name = {'spet'};
rand_time = 10000;
load('dis_whole.mat', 'dis_matrix_bi')... |
b9761f2b271aa0092d14f8c9c7318b693ede59d3429ce7ed8e3dcb7a7ad95ce7 | MATLAB | 1,614 | 46 | function [speed_cm_per_s, speed_smoothed_cm_per_s, vx, vy, vx_smoothed, vy_smoothed] ...
= ml_core_compute_motion(x_cm, y_cm, timestamps_ms, velocity_lowpass_wpass)
% This computes the speed and then smoothes it
% Convert from microseconds to seconds
timestamps_s = timestamps_ms ./ 10^3;
... |
81030f00fbf625390ed9809ebcdc15728719f9587f9868ee76a802acff73e206 | MATLAB | 1,615 | 40 | % mglFrameGrab.m
%
% $Id$
% usage: mglFrameGrab(<[x y width height])
% by: justin gardner
% date: 03/01/08
% copyright: (c) 2006 Justin Gardner, Jonas Larsson (GPL see mgl/COPYING)
% purpose: does a frame grab of the current mgl screen and
% returns it as matrix of dimensions w... |
438898f9f21777b31704dcfcf5c0edfb0e0e68d517a7cbb7f4d53706cbeff119 | MATLAB | 1,616 | 38 | % ===== load behavioural data =============================================
% Overall, the code prepares and preprocesses perceptual time series data
% for subsequent analysis, including correlation calculations and z-scoring.
dataPath = 'datapath/';
load(fullfile(dataPath, 'KDE_groups'));
%% ===== preprocess percep... |
85a6e5de9ae60a5ceeb0ddab4d3e9819eaac5f8d757fd494fd32614c9760f3b1 | MATLAB | 1,617 | 51 | % kaiserbeta() - Estimate Kaiser window beta
%
% Usage:
% >> beta = pop_kaiserbeta(dev);
%
% Inputs:
% dev - scalar maximum passband deviation/ripple
%
% Output:
% beta - scalar Kaiser window beta
%
% References:
% [1] Proakis, J. G., & Manolakis, D. G. (1996). Digital Signal
% Processing: Prin... |
e011d977f52443fc52802eacc142381c2c4484c56488f5e20b7865d1681e0b01 | MATLAB | 1,619 | 51 | % mglSetParam.m
%
% $Id: mglMovie.m,v 1.1 2007/10/23 22:21:23 justin Exp $
% usage: mglSetParam('paramName',paramValue,<makePersistent>);
% by: justin gardner
% date: 12/30/08
% purpose: Set MGL parameters, if perisistent is set to 1, then
% the parameter will be saved in a file... |
eb2ec01b0d402ca222a4b526c0f8b14f6239502e9b13ec074a17fff28288e45c | MATLAB | 1,619 | 40 | %{
Copyright (C) Cambridge Electronic Design Limited 2014
Author: James Thompson
Web: www.ced.co.uk email: james@ced.co.uk, softhelp@ced.co.uk
This file is part of CEDS64ML, a MATLAB interface to the SON64 library.
CEDS64ML is free software: you can redistribute it and/or modify
it under the t... |
b61f0abd37fc0d3ba3ef3d403d09d1784b8c70d4e9f33c46182a2ac47a505d54 | MATLAB | 1,620 | 46 | function makemda( inputfile, channel)
%% makemda creates a new mda file with a specific channel data from an smr file
% .mda is the input file format that MountainSort uses
% For more informaiton on mda file formats and MountainSort see -
% https://github.com/magland/mountainlab/blob/master/old/doc/mda_format.md
%
% I... |
8725833c7349f47f8da1869cf5eab34877ea97955be26ba5d007e11a330f5d74 | MATLAB | 1,623 | 55 | function setupEyeAnalysis
%% DEFAULT PARAMETERS
% Pupil radius initial parameters
radiiPupil = 50; % default radius in pixels
% X & Y Padding around Pupil in pixels
xpad = 100;
ypad = 40;
% corneal refleaction radii bounds
radiiCR1 = [6 12];
radiiCR2 = [6 12];
% Fraction features needed for pupil detection
minfea... |
8cde4dbc37801f53fefb3edd7093be682bbbe1a383629e6c7e1bbf64faf8bef1 | MATLAB | 1,623 | 56 | function plot_kinematics(mov_dist,mov_duration,max_speed,Nbins)
%% plot_kinematics plots the correlation between movement distance, duration and distance
%
% INPUTS
% mov_dist: a cell array containing Nbins cells. Each cell contains a vector with the
% distance of each movement within a duration bin.
%
% mov_duration: ... |
b5d3646f64dd27dcb9be072d7cb4947531ba1857740456b669f7ada8fa0b6e20 | MATLAB | 1,623 | 42 | function handles = fix_StorePanelPositions(handles)
% store the positions of the panels in the GUI
% splintered from fixerrorsgui 6/23/12 JAB
% store positions of right side panels
handles.rightpanel_tags = {'seqinfopanel','frameinfopanel','navigationpanel',...
'seekpanel','editpanel',...
'deletepanel','interpolat... |
3050887150a5870401f0187df67f87975f8b14488dbc9a52d9430e326b26a894 | MATLAB | 1,624 | 49 | function result = linearModel(param, prfResponse, t)
% Function to compute linear model response to given pRF response
%
% result = linearModel(param, prfResponse, t)
%
% INPUTS:
% params : (struct) should contain the following fields:
% * shift: time between stimulus onset and when the signal
% ... |
6efa60806db1a435e16aa37571f3b2ef8f8ad106cf1ecc7551492a5986d95629 | MATLAB | 1,624 | 15 | function results = vl_test_alphanum(varargin)
% VL_TEST_ALPHANUM
vl_test_init ;
function s = setup()
s.strings = ...
{'1000X Radonius Maximus','10X Radonius','200X Radonius','20X Radonius','20X Radonius Prime','30X Radonius','40X Radonius','Allegia 50 Clasteron','Allegia 500 Clasteron','Allegia 50B Clasteron','Al... |
efbe46a0ea4a91f7950f273cee4f974b1603b2a686ce330593d6de12f2c730fb | MATLAB | 1,624 | 83 | function J=vl_xyz2luv(I,il)
% VL_XYZ2LUV Convert XYZ color space to LUV
% J = VL_XYZ2LUV(I) converts the image I in XYZ format to the image J
% in Luv format.
%
% J = VL_XYZ2LUV(I,IL) uses the specified illuminant. The following
% illuminant are supported: A, B, C, E, D50, D55, D65, D75, D93. IL
% is the na... |
a1fdc32a64d472990c3f63b92a90cb0ab7a900cc7c1400908098418131a1c3cf | MATLAB | 1,625 | 57 | %% updated 2024/3/26 mw
%%
% rain_dot_box_plot_v is plot vertical bars
% rain_dot_box_plot is plot horizontal bars
%% raincloud_plot - plots a combination of half-violin, boxplot, and raw
% datapoints (1d scatter).
% Use as h = raincloud_plot(X, cl), where X is a data vector and cl is an
% RGB value. h is a... |
7851fb957050fe6fb2bf1f5e065a9e0c5013cf9df54c9482bdfad4af205269c7 | MATLAB | 1,627 | 39 | % GIfTI Class for MATLAB
%
% Geometry format under the Neuroimaging Informatics Technology Initiative
% (NIfTI):
% http://www.nitrc.org/projects/gifti/
% http://nifti.nimh.nih.gov/
%
% This MATLAB class is part of SPM:
% http://www.fil.ion.ucl.ac.uk/spm/
%
% It reli... |
191b4cb9a9c4118f4cc2e7e3bbe656d068f49c4670859f9049bee5b87ac28479 | MATLAB | 1,629 | 50 | function tree = copy(tree,subuid,uid)
% XMLTREE/COPY Copy Method (copy a subtree in another branch)
% FORMAT tree = copy(tree,subuid,uid)
%
% tree - XMLTree object
% subuid - UID of the subtree to copy
% uid - UID of the element where the subtree must be duplicated
%______________________________________... |
f2ea6cbd3e24d947ed1d4df3138190f43dbe7d4957768aee2feb29d92d189d0d | MATLAB | 1,629 | 46 | % Marc Normandin, Muzzio Lab, Psychological & Brain Sciences, University of Iowa, 2024
function [R] = compute_average_rate_differences_within_across_for_table(T)
% Input should be a table that was created with one of the
% compute average rate matrix tables. Each DAY should have ONE rate matrix.
unique... |
ef503a18d8b72fc64477d0d4ec87cace8420c054ea2a8ee36be3b0b4d3ac3bed | MATLAB | 1,630 | 35 | function spikeTimes_mus = ml_nlx_load_mclust_spikes_as_mus(nlxNvtTimeStamps_mus, tFilename, numBits)
isVerbose = false; % Set to true for debugging.
if numBits == 32
spikeTimes_mclust = ml_nlx_mclust_load_spikes_32bit(tFilename);
spikeTimes_mus = spikeTimes_mclust .* 10^6;
elseif numBi... |
e897024ad865e13bef4c6b53554402013ae92d82cba41e4fb8fb4ad65fd3ccd5 | MATLAB | 1,632 | 62 | close all
clear all
%% create figure 3A
%% janine.thome@zi-mannheim.de
%% paths
pato=['/###/Figures/']; %% add output path
if ~isdir(pato), mkdir(pato); end
%% load
file = 'DYN_performance.mat';
load(file)
%% plot Balanced Accuracy
% create colored fig
h1=figure('c... |
6e1a7b96cfc4cc81069bdff9e4df0791bea19fcbda62ec626c29b956afb739fc | MATLAB | 1,633 | 64 | function newmap = rdbu_sym(h)
%rdbu_sym Blue, white, and red color map.
% rdbu_sym(M) returns an M-by-3 matrix containing a blue to white
% to red colormap, with white corresponding to the CAXIS value closest
% to zero.
% If only negative values are present, only the blue end will be used; if
% only... |
f4c4ddc3378974678a7b0da4301559c4414dbeb1864924aa90300003b462a41b | MATLAB | 1,633 | 49 | function [myscreen] = initEyeTracker(myscreen, varargin)
% initEyeTracker.m
%
% $Id: initEyeTracker.m 203 2007-03-19 15:41:00Z justin $
% usage: myscreen = initEyeTracker(myscreen, [tracker])
% by: eric dewitt
% date: 2009-03-10
% copyright: (c) 2006 Justin Gardner (GPL see mgl/COPYING)
% ... |
0eecfe1a5560568a8ec70ff4350317209019e89fc15a696f4f8719a2980196bb | MATLAB | 1,634 | 59 | function [n, npw, ts, wave] = plx_waves_v(filename, channel, unit)
% plx_waves_v(filename, channel, unit): read waveform data from a .plx or .pl2 file
%
% [n, npw, ts, wave] = plx_waves_v(filename, channel, unit)
%
% INPUT:
% filename - if empty string, will use File Open dialog
% channel - 1-based channel n... |
14b22c282b60df631d2cb26b6032e2d8f20922d640e1b12ae0468a5ac77d1d32 | MATLAB | 1,634 | 36 | function [predNeural, params] = getPredictedNeuralResponse(params, prfResponse)
% Function to get predicted neural response (n,time,space) given
% spatial pRF response and choice of temporal model
%
% predNeural = time (ms) x space (xy collapsed)
%
% INPUTS:
% params : (struct) should contain the follow... |
e7cc6eb32d39ff780b4148abfaebedcf7e740b47ef44068a18ff9bb40393b724 | MATLAB | 1,634 | 40 | function ret=SONSetRealMarkChan(fh, chan, sPhyCh, bufsize, comment,...
chantitle, rate, minimum, maximum, units, points)
% SONSETREALMARKCHAN creates a REALMARK channel
%
% RET=SONSETREALMARKCHAN(FH, CHAN, SPHYCH, BUFSIZE, COMMENT,...
% CHANTITLE, RATE, MINIMUM, MAXIMUM, UNITS, POINTS)
%... |
7a55a14690d8643c67cbfa0284178f94ac9dff96c5d1fc115e26449a01a28e58 | MATLAB | 1,635 | 58 | function data = simseq_loadEventRelatedData(simSeqSessionDir, roiName, varargin)
% data = simseq_loadEventRelatedData(simSeqSessionDir, roiName, ...
% [dataType], [scansToLoad], [recomputeFlag], [preserveCoordsFlag])
%% Parse inputs
p = inputParser;
p.addRequired('simSeqSessionDir', @ischar);
p.addRequired... |
e5e9c55d243e51570f5045c231b0da54be4234b69aaf29dcc874293311e38e59 | MATLAB | 1,635 | 51 | % this function will call figure2_subplanels to create all 4 subplots of
% figure2.
%
% figure2(data_dir, read_from_excel)
% INPUTS:
% data_dir (str): Path to source data (default: 'source_data').
%
% read_from_excel (bool): Flag to read from Excel (true)
% or .mat files (false) (... |
6cf7470673bbaacc846d93e9bd71157ecca089113d936d72a118c5c7a90ac2a1 | MATLAB | 1,636 | 51 | % mglDeleteTexture.m
%
% $Id$
% usage: mglDeleteTexture(tex)
% by: Benjamin Heasly
% date: 03/18/2022
% copyright: (c) 2008 Justin Gardner, Jonas Larsson (GPL see mgl/COPYING)
% purpose: Deletes a texture. This will free up memory for
% textures that will not be drawn again. No... |
d966064cf064c729ddb2202927ab880b25598c2ccb9951e056665bffbac43b3f | MATLAB | 1,636 | 83 | <<<<<<< HEAD
function [EER, EERlow, EERhigh, index] = computeEERIndex(FAR,FRR)
%es. [EER, EERlow, EERhigh, iEER] = computeEERIndex(FMR,FNMR);
% calcolo le posizioni di confine
%t1 = min(find(FRR>=FAR));
%t2 = max(find(FRR<=FAR));
%distribuzione con valori grandi tipici degli impostori (es. iride)
t1 = min(find(FRR<... |
35bce36a5f09e6c006c9d4dfd83f94bf6d9432073179e7475b906b42ae9927cb | MATLAB | 1,637 | 64 | % mglDefaultScreenParams.m
%
% $Id:$
% usage: mglDefaultScreenParams()
% by: justin gardner
% date: 04/26/10
% purpose: Get a default screen parameters
%
% screenParams = mglDefaultScreenParams
%
function screenParams = mglDefaultScreenParams(screenParams)
% get host/display name
if nargi... |
777ed138cdbeb2ab012620a4cc0bd65aae21a7f472af1a74a09b1f8e04b3f391 | MATLAB | 1,637 | 47 | function GREPhase = mcpcc(GREMag, GREPhase, Params)
% GREPhase = mcpcc(GREMag, GREPhase, Params)
%
%% Author: Xu Li
% Affiliation: Radiology @ JHU
% Email address: xuli@mri.jhu.edu
%
% Multiple channel phase combination - constant
% updated 2017-03-15, X.L.
%% get virtual reference phase using mcpcc method first
cen... |
526d1815d75d7107ab12aeb83dc36011c95dd94de34e344d92a1c75facd6c6a1 | MATLAB | 1,638 | 55 | % "Coil tester line magnetic" tool for the entire coil. Outputs
% total magnetic field (or any of the field components) along the line given I0 A
% of conductor current
% Copyright SNM 2017-2019
clear all; %#ok<CLALL>
if ~isunix
s = pwd; addpath(strcat(s(1:end-5), '\Engine'));
else
s = pwd; ... |
90ad5d9614fe2da7ac0407e6ab0e2fd5f4cee124da30541a47201d0f0aadb61f | MATLAB | 1,639 | 59 | function decompressed = openmaestro(filename)
% OPENMAESTRO reads in the raw analog electrophysiology file sepcified by
% filename and outputs the decompressed signal
%
% Hannah Payne
% Raymond lab 3/28/13
%
% Algorithm based on https://sites.google.com/a/srscicomp.com/maestro/data-analysis/data-file-format/data-compr... |
f279f49278addc28c90c6cc02c91be94b97a282842951696d68569876912dd31 | MATLAB | 1,639 | 33 | function d = stageDirFor(cfg,micID,stageRoot,source)
% The managed stage folder <stageRoot>/brainsaw_webpreview/<siteID>/<micID>/<source>
%
% function d = webupload.stageDirFor(cfg,micID,stageRoot,source)
%
% Purpose
% The one place that decides where staged files live. clearStage deletes the re... |
a05d6ccd1bd106cf0e4f9f36d65d8033d51b034201fd61a364b3e598ef787c5e | MATLAB | 1,640 | 1 | % LOWPASSFILTER - Constructs a low-pass butterworth filter.
%
% usage: f = lowpassfilter(sze, cutoff, n)
%
% where: sze is a two element vector specifying the size of filter
% to construct [rows cols].
% cutoff is the cutoff frequency of the filter 0 - 0.5
% n is the order of the f... |
e24fba9e72532e74e51d6e069dc83f856cff9c06a0c63e970930103f8d1c1984 | MATLAB | 1,640 | 52 | function CBIG_ASDf_CCA_plotBar(score_names, struc_coeff, output_name)
% CBIG_ASDf_CCA_plotBar(score_names, struc_coeff, output_name)
%
% This function plots the CCA behavioral score structure coefficients vs raw behavioral scores as
% bar plot. If output_name is specified, the plot will be saved.
%
% Input:
% - sco... |
13fcf85c021a6abe1501d1b328636dc82ca8ff8896d9eedd7c055013314bae27 | MATLAB | 1,641 | 23 | function [Coherence_1_150Hz,Coherence_5bans,comments] = Compute_Coherence(Selected_Signal,wpli_para)
if size(Selected_Signal,2)>size(Selected_Signal)
Selected_Signal = Selected_Signal';
end
Freq_Range_5bands = [4 8;8 12;12 30;30 60;60 150]; % theta alpha beta low-gamma high-gamma
params.tapers = [3 5];% ¡¾TW K¡¿... |
1be81c20792233d83f87ac58bc41cd3398d3e07ff649e4fb793b464724b38c99 | MATLAB | 1,641 | 60 | function [wout] = combineWeights(dm, w)
% Combine the weights per column in the design matrix per covariate
%
% Input
% dm: design matrix structure
% w: weight on the basis functions
%
% Output
% wout.(label).data = combined weights
% wout.(label).tr = time axis
dspec = dm.dspec;
binSize = dspec.expt.binSize;
... |
2cde1c51882b1f615ec1cb22a6c56f1203d023bd242287fd2978cd9d042cfa7b | MATLAB | 1,641 | 70 | %
% Labels of methods and decompositions.
%
% RESULT
% labels
% .(method) Label of method
%
function [labels] = get_labels_method()
labels = struct();
labels.zero = '0';
labels.pref = 'PA';
labels.mask = 'Mask';
labels.neib = 'Neib.';
labels.neib3 = 'P3';
% Decompositions
labels.sym = 'A';
labels.sym_n ... |
c9741119682bc117821c039d0dc53259a8544a1f35506ffc5b20bdff6c04845d | MATLAB | 1,641 | 57 | function modpath()
this_file_path = mfilename('fullpath') ;
this_folder_path = fileparts(this_file_path) ;
addpath(fullfile(this_folder_path, 'params')) ;
addpath(fullfile(this_folder_path, 'scripts')) ;
addpath(fullfile(this_folder_path, 'tests')) ;
addpath(degit(genpath(fullfile(this_fold... |
ec49711408c83e46314496fc683b0e9182b062319e9ce92d9112d41199cd2a17 | MATLAB | 1,641 | 48 | function [wing_pxls,pts] = track_segment_fit_wings(fg_size,imsize,wing_cc,ws,rot_vec,center,bbox,pos,calib)
wing_pix = vertcat(wing_cc.PixelIdxList{ws});
% if only one wing, split it along the fly's major axis
if numel(ws) == 1
wing_img = zeros(fg_size);
wing_img(wing_pix) = 1;
%center = detect.body_props(bods(... |
799095fdfde2e2c4991aeeaaceac582fe968c2adbcbc5ffb60c157f82f51909d | MATLAB | 1,642 | 57 | % getPhaseDiffPDFs.m
%
% Function that takes phase differences (from getLegPhaseDiffs()) and
% converts them into probability density functions (PDFs)
%
% INPUTS:
% phaseDiffs - struct of phase differences from getLegPhaseDiffs()
% numBins - number of bins to divide PDF into
% units - 'radians' or 'degrees' for ... |
d95392c8e83c31cec464c4cc29eadbc4d6e58f5f36a7bdcd41763f0cc2fe092c | MATLAB | 1,642 | 38 | function fH = makeFigure3_exampleVO12Data(ds, fLMM, lmmResults, projectDir,subjnr, saveFigs, saveFigDir)
% Function to reproduce main manuscript figure 3:
% panel a: VO1 time series for each stimulus condition
% panel b: VO1 SEQ vs SIM amplitude voxel scatter plot for each stimulus condition
%
% From the paper:
% T... |
46dd24afa05ea3f38df21175a94b5d84f70e3dd34aae83eea065e3b269cfd068 | MATLAB | 1,643 | 59 | function [xc_out] = one_event_xcorr(src_spk,targ_spk,stevt,endevt,xcorr_prefs)
% one_event_xcorr.m
% for autocorr, src = targ
assert(isvector(src_spk) && isvector(targ_spk),'only vector inputs accepted for spks');
store_input = optCheck(xcorr_prefs,'store_input',false,[true false]);
lags_msec = optCheck(xcorr_prefs,'... |
8b9aee7e91c9526b3348ee1e41458283a5ebd29178181481862e6b7e42773827 | MATLAB | 1,643 | 41 | function mltp_user_define_session_arenaroi(obj, session)
% We need to define the ROI for each slice of data, not just the trials
% because the user may find problems with the slices and not use them
% as trials.
if obj.isVerbose()
fprintf('Defining the ROI for all trials of the session.\n')... |
e32badb12300b77f1bf4fea88a02eddf8e73b13ac90f4ab09496959f079eee10 | MATLAB | 1,643 | 51 | function relativeDeviation(numOfReturnedImages, queryImageFeatureVector, dataset, folder_name, img_ext)
% input:
% numOfReturnedImages : num of images returned by query
% queryImageFeatureVector: query image in the form of a feature vector
% dataset: the whole dataset of images transformed in a matrix of
% feat... |
6e9d6cce66b698f97397c206cb8d0a1e116fc29a5773810777a5b5e67031114b | MATLAB | 1,644 | 49 | % mglMirrorActivate: Selects which primary and/or mirrored windows are active.
%
% $Id$
% usage: mglMirrorActivate(indices)
% by: ben heasly
% date: 08/29/2022
% copyright: (c) 2006 Justin Gardner, Jonas Larsson (GPL see mgl/COPYING)
% purpose: Selects which primary and/or mirrored windows... |
9dd83a22d88d73e607300a63032a02343e184499968ab7b1cf88b67e4d13e50b | MATLAB | 1,644 | 68 | function out = decoding_interval_timeshift(IN,L)
[nsig,ntime] = size(IN);
nL = length(L);
% for circshift
shift = 4;
nshift = round(ntime/shift);
TCshift = zeros(nshift,ntime);
for ns = 1:nshift
TCshift(ns,:) = circshift(IN(3,:),shift*ns);
end
A = zeros(1,nL); UA = A; DIFF = A; DIFFiqr = A;
ACC_AUA =... |
cbc5c7964e86666a41b74cb8f08ac452916ade624a05ce0dd78944dc0fab57b2 | MATLAB | 1,645 | 46 | clc;clear variables; close all;
%% parameter parsing
[descPara, ~] = makeDefaultParameters;
if descPara.testinVocformat
path_dataset = fullfile(descPara.folderPath_trainSet, 'JPEGImages');
testFiles = fullfile(descPara.folderPath_trainSet, 'ImageSets', 'Main', 'saliency_test.txt');
fid = fopen(tes... |
371a857bee70d7c73493a8f9427257f167cd62474c16c950d6f2d2edc6a846ff | MATLAB | 1,646 | 62 | % plot1KernelPred.m
%
% Function that plots the kernel, the scatterplot of predicted vs. measured
% responses with best fit line, and predicted and measured responses for 1
% kernel.
% NOTE: kernel and responses should be on same time basis
%
% INPUTS:
% kernel
% lags - time points for kernel
% inv - flag for ... |
8d6f4b2ad88d9cfe578d5851b3dfcc92f42d7b8e88f518fb5f3c21c2c1a52045 | MATLAB | 1,651 | 49 | classdef EyeTracking < types.core.NWBDataInterface & types.untyped.GroupClass
% EYETRACKING Eye-tracking data, representing direction of gaze.
% OPTIONAL PROPERTIES
properties
spatialseries; % (SpatialSeries) SpatialSeries object containing data measuring direction of gaze.
end
methods
function obj = EyeTra... |
df59b9a1f9f47f6975358d1b793a96fc81ae11fa6da2fda05fa5e7c8284547d8 | MATLAB | 1,651 | 54 | % loadMetadataSpreadsheet.m
%
% Function to load information in metadata spreadsheet into a data struct,
% to allow selection of specific subset of data for analysis.
%
% INPUT:
% none - but brings up GUI to allow user to select metadata spreadsheet
%
% OUTPUT:
% metaDat - struct of metadata
%
% CREATED: 9/27/20... |
11aa414b14b8a749530754f2040b8aef361f7ca88a1c7bf9d76d5789b5cb6cb4 | MATLAB | 1,652 | 48 | classdef WriteStatusTest < matlab.unittest.TestCase
% Tests for webupload.writeStatus.
properties
Dir
end
methods (TestClassSetup)
function addPackageToPath(tc)
tc.applyFixture(matlab.unittest.fixtures.PathFixture( ...
fullfile(fileparts(mfilename('fullpath'... |
69143218a65eac5d7d5161d2fcb0d2f8122b0e7f95bbfa6d15df29817f32b858 | MATLAB | 1,652 | 51 | %% This script computes Membrane Potential (Vm) in CC_AS_puff protocol Recordings
% ==================================================
% Authors: Arash Samiee, Knut Kirmse
% last modification: 07/2024
% ==================================================
% How to use:
% (1) Specify parameters
% (2) Run the script... |
a7b9cf429857298755653bc78e4c4de1bbe557d4d3cc9a0669f5fa403115de3e | MATLAB | 1,653 | 53 | function L1(numOfReturnedImages, queryImageFeatureVector, dataset, folder_name, img_ext)
% input:
% numOfReturnedImages : num of images returned by query
% queryImageFeatureVector: query image in the form of a feature vector
% dataset: the whole dataset of images transformed in a matrix of
% features
%
% outpu... |
1eb3731edc4333aa3ba0ca511cd11aa8238e0d14c8093b694ad3f3534e458b12 | MATLAB | 1,654 | 42 | % Marc Normandin, Muzzio Lab, Psychological & Brain Sciences, University of Iowa, 2024
function [Classifications] = classify_stability_registered_cells_on_specified_day(BestAligned, CellRegTable, SessionsToGroups, CLASSIFICATION_GROUP_LABEL, BESTALIGNED_STABILITY_THRESHOLD_CRITERIA)
% This code returns a list of re... |
66e3e53e2147baf0227823f4bed042e7dcc8058cf6327ea9a785e366b48697d3 | MATLAB | 1,654 | 64 | close all
clear all
%% create figure 2A
%% janine.thome@zi-mannheim.de
%% path
pato=['/###/Figures/']; %% add output path
if ~isdir(pato), mkdir(pato); end
%% load
file = 'VOL_performance.mat';
load(file)
%% plot Balanced Accuracy
% create colored fig
h1=figure('co... |
d4fac4184545c2dd7ae1f1edbf24ed34e276480679e098322d615e0ce364c786 | MATLAB | 1,654 | 60 | clear;
tbl_dir = pwd;
tbl_name = fullfile(tbl_dir,'S4_Data.xlsx');
[~, sheetNames] = xlsfinfo(tbl_name);
groupStr = {'Young','Old'};
condStr = {'Load 1','Load 2','Load 4','Load 4'};
% # The third position is included for cases where I use ss = 1:3 rather than ss = [1 2 4]
%% Fig.S1C
figure('Name','DMS_wen_FigS1C')
lin... |
05f5d22d00d6d2c6c3622c53cf315d0d935c56a88f4cc55ab3bb8924b3732ade | MATLAB | 1,655 | 60 | function [h,txh] = aedes_calc_wait(str)
% AEDES_CALC_WAIT - Wait message box
%
% Synopsis:
% [h,txh] = aedes_calc_wait(str)
%
% Description:
% Displays wait message box with text 'str'. Output argument 'h' is
% handle to message box and 'txh' is handle to text string.
%
% Examples:
% [h,txh] = aedes_calc_wait('Demo... |
8fb378a13010cb188256130c9a0c56a35ddcc002b8f8d61fafd5a8336768a940 | MATLAB | 1,655 | 62 | function [distance,branch] = breadth(CIJ,source)
%BREADTH Auxiliary function for breadthdist.m
%
% [distance,branch] = breadth(CIJ,source);
%
% Implementation of breadth-first search.
%
% Input: CIJ, binary (directed/undirected) connection matrix
% source, source vertex
%
% ... |
cd27f13ece50d201af4c60c2e9994cab7a1bf7b8d6bd2a9121208ea5880a746d | MATLAB | 1,655 | 72 | function imdata=addicon(filename,fieldname)
% ADDICON
%
% Synopsis:
%
% Description:
%
% Examples:
%
% See also:
%
% Copyright (C) 2006 Juha-Pekka Niskanen <Juha-Pekka.Niskanen@uku.fi>
%
% Department of Physics, Department of Neurobiology
% University of Kuopio, FINLAND
%
% This program may be used under the ... |
808609644c5817759886fa984b6ea4f743a35ab1f5b0909f6b3ac31a5a2f872e | MATLAB | 1,656 | 51 | %% corr the coupling R2 or P-value with functional gradient
roi_num = 48;
load('Edge_GLM_fun_str_dis_commu_DBM.mat')
AR = cat(1,results(:).AR);
AR_p = cat(1,results(:).AR_moran_p);
load('unrelated_gradient.mat','Gt_fun')
fun_grad = Gt_fun.gradients{1, 1}(:,1);
data = fun_grad;
data_name = {'Grad1'};
rand_time = 100... |
815ddbb6034c107abe1623c9af4a95301860f3cdd8e899b7bcafbb0c8b5c37eb | MATLAB | 1,657 | 58 | function subj_variablity_response_ft(sn)
% post-response variance of each set size
load('subs.mat');
subname = subs.name{sn};
set_name = fullfile(Dir.prepro,[subname,'_clean.set']);
EEG = pop_loadset('filename',set_name);
EEG = pop_select(EEG,'nochannel',{'LHEOG','RHEOG','BVEOG','TVEOG'});
X = [EEG.chanl... |
d50defee567114ad7728948cb03be76ad12e2755fdcdf411462fd22570f89b17 | MATLAB | 1,658 | 62 | close all
clear all
%% create figure 2F
%% janine.thome@zi-mannheim.de
%% paths
pato=['/###/Figures/']; %% add output path
if ~isdir(pato), mkdir(pato); end
%% load
file = 'FC_performance.mat';
load(file)
%% plot Balanced Accuracy
% create colored fig
h1=figure('co... |
d25f08dd0f76b4372589e91f0b0e662a95ba05f2cef898ceed29dbe9fda768b8 | MATLAB | 1,659 | 53 | % this script create a 3-D scatter plot showing different pattern of the
% dynamics, including ON-ON, OFF-ON, OFF-OFF and ON-OFF
% 3 dimensions are: DeltaE (x), DeltaI (y), and Isens(z)
rootFolder = "figure_Iattn_0.02_2d_4000/";
% ON-ON
data = readFilename(rootFolder+"agree/*_*_*_*_*_*.png",'%f_%f_%f_%f_%f_%f');
data( ... |
df35f0547aeca3253e359544da1955e8a379037f142a7757cc0e7d77b385bbbe | MATLAB | 1,659 | 60 | function [wout] = combineWeights(dm, w)
% Combine the weights per column in the design matrix per covariate
%
% Input
% dm: design matrix structure
% w: weight on the basis functions
%
% Output
% wout.(label).data = combined weights
% wout.(label).tr = time axis
dspec = dm.dspec;
binSize = dspec.expt.binSize;
... |
7afb09a3982ed5521373fcf1177f4f8993f2b384437eccf5b22622ddfe891b0c | MATLAB | 1,660 | 39 | classdef CBIG_MSHBM_unit_test < matlab.unittest.TestCase
% Written by Ru(by) Kong and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
methods (Test)
function test_example(testCase)
% create output folder
CBIG_CODE_DIR = getenv('CBIG_CODE_DIR');
... |
a0b5537cc06bf276a30529e7edbee61e7c18832e130e62254eef4a40d6920e48 | MATLAB | 1,661 | 49 | function [ status ] = fillSetupONParameters( obj, data )
% Fill setup LFP recordings ON stimulation class
%
% Syntax:
% [ status ] = FILLSETUPONPARAMETERS( obj, data );
%
% Input parameters:
% * obj - object containg data
% * data - data from json file(s)
%
% Output parameters:
% * status
%
% Example:
% [ ... |
d23a804aa15dd10166a2496a7d624e1a2ce83b7b78497e99ec5332f9caad5851 | MATLAB | 1,661 | 56 | % computeVarianceExplained.m
%
% Function that takes in predicted response and actual response and returns
% the variance explained given specified form of nonlinearity.
% NOTE: The predicted response and actual response should be on the same
% time basis.
%
% INPUTS:
% actResp - actual response
% predResp - pred... |
f127d878b60df0402085705e83e3c90b3b89025a94b288ea656b0151e9750e84 | MATLAB | 1,661 | 48 | %{
Copyright (C) Cambridge Electronic Design Limited 2014
Author: James Thompson
Web: www.ced.co.uk email: james@ced.co.uk, softhelp@ced.co.uk
This file is part of CEDS64ML, a MATLAB interface to the SON64 library.
CEDS64ML is free software: you can redistribute it and/or modify
it under the t... |
4b7a5927758af995db91b6e5bdcf1d27f52a426059d6aa7e4b9d0c0d1ffe1d74 | MATLAB | 1,662 | 60 | close all
clear all
%% create figure S1
%% janine.thome@zi-mannheim.de
%% paths
pato=['/###/Figures/']; %% add output path
if ~isdir(pato), mkdir(pato); end
%% load
file = 'Age_performance.mat';
load(file);
%% plot Balanced Accuracy
% create colored fig
h1=figure('... |
28c846bfdbcbf7c87fa1a1d59dfb73381052ffb90928e66ca8c7c571b196df65 | MATLAB | 1,663 | 73 | function [h, hFill] = fillerror(x,mean,err,c,lineon, lighten,varargin)
% h = fillerror(x,mean,error,c,lineon, lighten,varargin)
%
% INPUTS
% x - x positions to plot
% mean - y positions to plot (usually the mean)
% error - width of error bars ie SEM
% c - optional color ('r' etc). Will be lightened
% lineon - include t... |
5079b99e9e5d5d130cefaf9fda065dd9b96aa5d8398b651d93bad616cb973f87 | MATLAB | 1,664 | 55 | function bases = makeSmoothTemporalBasis(shape, duration, nBases, binfun)
%
% Input
% shape: 'raised cosine' or 'boxcar'
% duration: the time that needs to be covered
% nBases: number of basis vectors to fill the duration
% binfun:
%
% Output
% BBstm: basis vectors
nkbins = binfun(duration); % number of bin... |
9b257046fa0a49a55ee38e31769f8d16d8042cc26fa44ef40659bd2b8711b36f | MATLAB | 1,664 | 59 | function save_nii(data,fname,prop)
% SAVE_NII saves files with .nii format using the NifTI Toolbox
% (nifti.nimh.nih.gov/nifti-1/). Please download and include it in the
% path.
%
% SAVE_NII(DATA,FNAME,PROP) saves a nifti file named as FNAME containing
% the data DATA (2D,3D or 4D) with the properties PROP. PROP ... |
aa6c36c5e61eb3e389467bad7744e41483a9772c26f5bf09d609545d015741c4 | MATLAB | 1,664 | 52 | % mglMetalSetRenderTarget.m
%
% usage: results = mglMetalSetRenderTarget(tex)
% by: Benjamin Heasly
% date: 03/11/2022
% copyright: (c) 2006 Justin Gardner, Jonas Larsson (GPL see mgl/COPYING)
% purpose: Set mglMetal's render target -- screen or offscreen texture.
% usage: mglMetalSetRenderT... |
04fb013405f7213fea63aad2d2538c57cc6d330a37cf8f38f091fc406c9b67d6 | MATLAB | 1,665 | 63 | function keep(varargin)
%KEEP keeps the caller workspace variables of your choice and clear the rest.
% Its usage is just like "clear" but only for variables.
%
% Xiaoning (David) Yang xyang@lanl.gov 1998
% Revision based on comments from Michael McPartland,
% michael@gaitalf.mgh.harvard.edu, ... |
13100607a36ef384a9e886b60457e8477ef2a6692c44d4935d2afce5609327e5 | MATLAB | 1,665 | 54 | function [] = plotBrainSensitivity(probe, channeltype)
%PLOTBRAINSENSITIVITY Plot spatial brain sensitivity
% Generate a spatial plot of channels color-coded by their brain
% sensitivity. Can plot all channels, intra module channels, or inter
% module channels only with the channeltype input. Channeltype can be... |
2021b197b55c9c0d0440f9d54050de5f97a3b88e80c7b4e4640fe2990c270158 | MATLAB | 1,665 | 55 | %Add useful formatting to FMUT output spreadsheets
%
%EXAMPLE USAGE
% >> format_xls('results.xlsx')
%
%REQUIRED INPUTS
% spreadsheet - name of spreadsheet file to format
%
%VERSION DATE: 18 April 2019
%AUTHOR: Eric Fields
%
%NOTE: This function is provided "as is" and any express or implied warranties
%are... |
6b51f851826e7a8f920e48c432580933ab12dc54379ecb5259397ec8b468ac29 | MATLAB | 1,665 | 61 | function D = agreement(ci,buffsz)
%AGREEMENT Agreement matrix from clusters
%
% D = AGREEMENT(CI) takes as input a set of vertex partitions CI of
% dimensions [vertex x partition]. Each column in CI contains the
% assignments of each vertex to a class/community/module. This function
% aggregates the partit... |
981edc1b85370179350ebc75d14166ac1e9c03066ad9fc8a079511c2ed67ec76 | MATLAB | 1,666 | 75 | function output = smooth(input, window, kernel_type)
% Smoothing function:
% output = smooth(input, window, type)
% "Type" should be set to 'gauss' for a gaussian kernel or to 'boxcar'
% for a simple moving window average. "Window" is the total kernel width.
% Input array must be one-dimensional.
%
% last modified 5/... |
b7afeef2545176683ac164ebb2a8d35a28da9706682efb0519a58ac2dd93a6f9 | MATLAB | 1,666 | 58 | % Marc Normandin, Muzzio Lab, Psychological & Brain Sciences, University of Iowa, 2024
function [hFig] = plot_per_day_cell_averaged_rate_difference_matrix_table(T)
%T = compute_per_day_cell_averaged_rate_difference_matrix(DaysToSessions, RateMatrices, perCellNormalizationMethod);
hFig = figure('position', get... |
bcef3cfc02727536cc1208f0a791f689dcf678695234357b01b97bc4d825dc3b | MATLAB | 1,666 | 36 | function [HiddenNeuralStatesProbability] = DecodingHiddenNeuralStates(Best_HiddenMarkoModels, emision_sequence_cross, info,str_save_append)
%% Decode hidden neural states probability based on the best Hidden Markov Models.
%% authors: Stefano Diomedi
%% date: 22nd February 2024
%
%% Inputs:
% - Best_HiddenMarkoM... |
df52edbf7c1e6620e611d26d6b1779358c87c59aca92a0e73594852e02f6a3dc | MATLAB | 1,667 | 69 | function dxdt = GBMFuncoptimal(t,x,p)
% Anderson et al. (2024) model of treatment-free glioblastoma-immune dynamics
% to be used in conjunction with the optimal control code.
% The purpose of this code is to determine system dynamics pre- and
% post-treatment.
%------------------------------------------------------... |
30a4e2185d578722d8baca2e28b009aed670ef31e6009837a20b065c600a2b33 | MATLAB | 1,668 | 33 | function Einc = bemf3_inc_field_electric(strcoil, Points, dIdt, mu0)
% Computes electric field from the coil via the FMM
% in terms of the pseudo electric potential evaluated for segment centers
%
% Copyright SNM 2017-2020
% Compute pseudo potentials
N = size(Points, 1);
segvector = ... |
d9fb95353f61db00872ab72ff7644865bf1e06d2e231c3bd13cad91d4e738360 | MATLAB | 1,670 | 55 | % "Coil tester line electric" tool for the entire coil. Outputs
% solenoidal electric field -dA/dt (or any of the field components) along
% the line given I0 A of conductor current and frequency freq
% Copyright SNM 2017-2019
clear all; %#ok<CLALL>
if ~isunix
s = pwd; addpath(strcat(s(1:end-5), '\... |
fb14824d6aa685ca89e57a971c4291cc6a390b4e3f2e140437077f43c7dce0b6 | MATLAB | 1,670 | 41 | function varargout = nifti_stats(varargin)
% Conversion among various statistics
% FORMAT P = nifti_stats(VAL,CODE,OPT,PARAM)
% CODE can be one of
% 'CORREL' 'TTEST' 'FTEST' 'ZSCORE'
% 'CHISQ' 'BETA' 'BINOM' 'GAMMA'
% 'POISSON' 'NORMAL' 'FTEST_NONC' 'CHISQ_NON... |
5aab85966769639e0cf5abe053f16e6253f5577bf957cc38f03266abb375b590 | MATLAB | 1,671 | 45 | function vecIndName = addVecInd(DynamicTable, colName)
%ADDVECIND Add VectorIndex object to DynamicTable
validateattributes(colName, {'char'}, {'scalartext'});
vecIndName = [colName '_index']; % arbitrary convention of appending '_index' to data column names
if isprop(DynamicTable, colName)
VecData = DynamicTable.... |
9c57907ed0d6a098afd7f20e08a2ce3f7dfadca2fc0993217a3593b5dd21178b | MATLAB | 1,673 | 40 | function ret=SONSetRealMarkChan(fh, chan, sPhyCh, bufsize, comment,...
chantitle, rate, minimum, maximum, units, points)
% SONSETREALMARKCHAN creates a REALMARK channel
%
% RET=SONSETREALMARKCHAN(FH, CHAN, SPHYCH, BUFSIZE, COMMENT,...
% CHANTITLE, RATE, MINIMUM, MAXIMUM, UNITS, POIN... |
357ad3bf42bc090127dcee2036517bb8f454fc419d666e81183930785028cfaf | MATLAB | 1,675 | 56 | %% batchBuildMDA creates a new mda file with a specific channel data from an smr file
% .mda is the input file format that MountainSort uses
% For more informaiton on mda file formats and MountainSort see -
% https://github.com/magland/mountainlab/blob/master/old/doc/mda_format.md
% Maxwell Gagnon 10/2017
activateC... |
3bc921951804a79e6438f05e024192fd169521a6753ca3299110910858f2d179 | MATLAB | 1,675 | 48 | % ficTracDatPosVel.m
%
% Extracts FicTrac position and velocity from unwrapped position output
% from .dat file
%
% INPUTS:
% unwrappedPos - unwrapped position in radians
% sampleRate - Rate the data was aquired at (samples/second)
% lowPassFilterCutOff - frequency that the position signal will be low
% pa... |
d30b1d08c5bd0150fe03b8da27829e7574195e76dc1f84198a67e96d9838b383 | MATLAB | 1,675 | 46 | % Example 2: Seamless blending of real and synthetic texture in an
% image, using Portilla-Simoncelli texture analysis/synthesis code,
% based on alternate projections onto statistical constraints in a
% complex overcomplete wavelet representation.
%
% See Readme.txt, and headers of textureAnalysis.m and
% textureSynt... |
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