sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
0a943be24b8cb3007fb13eb922fce0995135f9e37c0cec8189ca1fe147f67ad8 | MATLAB | 9,633 | 242 |
function [] = HumanOdorRep_plot_multimodal_neuron(unitdata, data_path, save_path)
% function [] = HumanOdorRep_plot_multimodal_neuron(unitdata, data_path, save_path)
%
%-----------------------------------------------------------------------------------------
% Plot function for multimodal neurons
%
% Kehl et al. 202... |
b0e9e69eef8f2f4596d60d77f5ab6c1112bcd1a29ed89a56813c8313df94450f | MATLAB | 9,633 | 303 | %% Regular (nonKine) data
ROOTPROJDIR = 'f:\stephenTrainingDataForMayanksTracker';
lblFile1 = fullfile(ROOTPROJDIR,'lbllist_nonKine_noneBodyAxis.txt');
lblFile2 = fullfile(ROOTPROJDIR,'lbllist_bodyAxis_level1.txt');
lbllist1 = importdata(lblFile1);
lbllist2 = importdata(lblFile2);
lbllist1 = fullfile(ROOTPROJDIR,lbllis... |
019964ab9be7ee3e7a18c79e6ff127ec4ba8826bd31f449695abd1050a90ae06 | MATLAB | 9,634 | 235 | function embedding = optimize_layout5(head_embedding, tail_embedding, ...
head, tail, n_epochs, n_vertices, epochs_per_sample, a, b,...
gamma, initial_alpha, negative_sample_rate, verbose, min_dist)
%OPTIMIZE_LAYOUT2 Another version of optimize_layout.m that slightly
% optimizes the speed for MATLAB; in particu... |
4ff541ba40730e5ece03eadd2ebfeba42b0c7e69780a2153a2d839f8ad3da82a | MATLAB | 9,636 | 333 | %% Compares the spatial information vs the temporal information from simulated cells
% 1) Simulate the same networks with different durations of place field
% trajectory traversals
% 2) Combine the activity from the different trials by either time or
% space, then calculate the resulting information
%% Set up
addpat... |
a3a5f109666c6f73d5197f58340a81f57e780491186aa1f0d6bb769c19309cb0 | MATLAB | 9,640 | 237 | function [x, cost, info, options] = steepestdescent(problem, x, options)
% Steepest descent (gradient descent) minimization algorithm for Manopt.
%
% function [x, cost, info, options] = steepestdescent(problem)
% function [x, cost, info, options] = steepestdescent(problem, x0)
% function [x, cost, info, options] =... |
80fe45caabda1d4a463ad800cdcc0d7416e0bf1ee963a7503c87e6e2ffbc78fd | MATLAB | 9,649 | 217 | function [times chans] = ms_detect4(X,opts)
%MS_DETECT4 - Detect super-threshold events in a raw/preprocessed dataset
%
% Consider using mscmd_detect*
%
% Syntax: [times chans] = ms_detect4(X,opts)
%
% Inputs:
% X - MxN array of raw or preprocessed data (M channels by N timepoints)
% opts.detect_interval - minim... |
029565f638a3ed3bc6afbbd8c65a472be5f0c22a35f544dcf8c8597424d5a51b | MATLAB | 9,654 | 347 | %epa_easy Analyze easy trials in endogenous pro/anti experiment
%
% This script analyzes the performance of all the participants during
% the 'easy' (i.e., non-urgent) trials of endogenously driven
% pro/antisaccade (EPA) task. It reproduces Figure S1 (or Figure 1 --
% Supplement 1) of the paper by Goldstein et a... |
eba7acddf81ada55a4665ce35c7ecc5b81284085d522e00ebc6b6d79ececd1d9 | MATLAB | 9,654 | 226 | % function [insitu_transcripts_filtered,puncta_voxels_filtered,puncta_centroids_filtered] = ...
% normalization_qnorm1(puncta_set_cell_filtered)
N = size(puncta_set_cell_filtered{1},1);
readlength = params.NUM_ROUNDS;
% puncta_present = ones(N,readlength);
%Get the total number of voxels involved for the puncta
%u... |
1868fefbd75674de8166226066e86f3e57e04bca5463c16ec8ddf94add014fd4 | MATLAB | 9,660 | 208 | %--------------------------------------------------------------------------
% Author: Georgia Lawlor
% Date: 1/24/21
% Purpose: Create jPSTHs for a set of binned data from a specific input
% file which is described below.
% Revision History:
% 2/18/21 - Simplified code, reformatted code so the jPSTH, coincidence,
... |
7ded0e5434d136beb4dfd87aebe67d763dedb90d4a9182d00a9175a341029bc1 | MATLAB | 9,660 | 335 | function [chansel, trlsel, cfg] = rejectvisual_channel(cfg, data)
% SUBFUNCTION for ft_rejectvisual
% determine the initial selection of trials
ntrl = length(data.trial);
if isequal(cfg.trials, 'all') % support specification like 'all'
cfg.trials = 1:ntrl;
end
trlsel = false(1,ntrl);
trlsel(cfg.trials) = true;
% d... |
f5498fcd69826c14a8ae163401a36acd7904d367ae8ed537b915f3c6cd42a93a | MATLAB | 9,662 | 330 | function [xp,dxpdom,dxpdT,dxpdf,dxpdc,dxpdk,dxpdalpha] = project_points_fisheye(X,om,T,f,c,k,alpha)
%project_points2.m
%
%[xp,dxpdom,dxpdT,dxpdf,dxpdc,dxpdk] = project_points_fisheye(X,om,T,f,c,k,alpha)
%
%Projects a 3D structure onto the image plane of a fisheye camera.
%
%INPUT: X: 3D structure in the world coordina... |
c42201d495d21a2984dd5a3b121ecb23b03fea2598f232b1497f0b78e5659a2f | MATLAB | 9,663 | 359 |
function varargout = boundedline(varargin)
%BOUNDEDLINE Plot a line with shaded error/confidence bounds
%
% [hl, hp] = boundedline(x, y, b)
% [hl, hp] = boundedline(x, y, b, linespec)
% [hl, hp] = boundedline(x1, y1, b1, linespec1, x2, y2, b2, linespec2)
% [hl, hp] = boundedline(..., 'alpha')
% [hl, hp] = boundedli... |
6f5098bb0dca0318d0fb2ef63734a80ade7fb4e7669df4324a165de85df47372 | MATLAB | 9,667 | 330 | function hh = scatter_h(varargin)
%SCATTER Scatter/bubble plot.
% SCATTER(X,Y,S,C) displays colored circles at the locations specified
% by the vectors X and Y (which must be the same size).
%
% S determines the area of each marker (in points^2). S can be a
% vector the same length a X and Y or a scalar. If S... |
a8e4072865b922c665ffb3367e8df4f97def1cc674ab4d117125878fff075025 | MATLAB | 9,672 | 75 | function map = viridis(N)
% Colormap from MatPlotLib 2.0. Perceptually uniform and very attractive!
%
%%% Syntax:
% map = viridis
% map = viridis(N)
%
% Colormap designed by Eric Firing, Nathaniel J. Smith, and Stefan van der Walt.
%
% For MatPlotLib 2.0 improved colormaps were created in the perceptually
% uniform c... |
544e0d3dce2ce331ba761554263d13714e81804c20cb33fc13383cbc8852f2df | MATLAB | 9,677 | 198 | function extract_replay_events
% based on Davidson, Kloosterman, and Wilson(2009,Neuron) criteria.
% - events detected by MUA only
% - zscore of 3 minimum, and edges detected by zscore of 0.
% modificiation- If event is too long, then edge criteria shifted to
% zscore of 0.25, then 0.5
% - events wi... |
85cf901450f250aa3f257527e41f80e33da48fc6181052e59442bd4225a0b222 | MATLAB | 9,688 | 201 |
function [glob_avg] = assembly_trig_avg_single (traces, nCells, si_img, SCE, assemblies)
%clear glob_avg1 glob_avg2 glob_avg3 glob_avg4 glob_avg5 glob_avg6
%event(find(SCE.RasterRace(8,:))) = 1;
windowSize = 200;
x = -windowSize/2:1:windowSize/2;
n_int_in_assembly = sum(sum(assemblies.CellCl(:,nCells.int)));
pyr... |
2ae8e2d70bc190c9230f0164ce4df644e852585f78ed3db539c580a26d86fca0 | MATLAB | 9,690 | 241 | % BATCH ANALYSIS PIPELINE
function remapping_pipeline(option,RExp)
% EXTRACT SPIKES, WAVEFORMS AND DROPPED SAMPLES
%use one of these depending on how you clustered
if strcmp(option,'EXTRACT_SPIKES_MARTA')
extract_spikes_phy; % for clusters extracted from PHY
extract_events;
extract_dropped_samples;
pro... |
aa841bf21ec8bf9f41bd3c4a3fede47fe599e665f76ece977fc4550151593844 | MATLAB | 9,692 | 279 | function ft_write_event(filename, event, varargin)
% FT_WRITE_EVENT writes an event structure to a file, a message daemon
% listening on a network socked, or to another computer connected through
% the serial port.
%
% Use as
% ft_write_event(filename, event, ...)
%
% The first argument is a string containing the fi... |
2a40c598b3b1f82188d7e0192baf6d4cce83163cc211acf876d800ea3f5142ec | MATLAB | 9,695 | 214 | function CBIG_KRR_generate_kernels( feature_mat, sub_fold, outdir, ker_param, similarity_mat )
% CBIG_KRR_generate_kernels( feature_mat, sub_fold, outdir, ker_param, similarity_mat )
%
% This function calculates the inner-loop and training-test kernels for
% kernel ridge regression.
%
% Inputs:
% - feature_mat
% ... |
8aa328d62d369e53f7d197a6f69f103c4c9cfdd0e19163d27fcb059c5ede158c | MATLAB | 9,695 | 243 | %% Plot example GP trials for a representative animal. Show detected TWs.
% also show representative phase map and phase vs distance plot
clear
clc
% repTrial = [97,98,99,100];%15 22 23 *32 %D:\InVivo\M1-Muscimol\2022-01-10_Muscimol-M1\2-Saline_220110_123444
repTrial =[83 56];%48 52 59 56
%wave 7 for T83 and w... |
cd1a6097954da56754db226ffae170600d6727a99fa500b095ce01b6a2277a06 | MATLAB | 9,698 | 251 | %Load the
%% Download all the data
%uses yamlfile,save_dir, called as a script to help debug
combined_transcriptsfile_refined = strrep(combined_transcriptsfile,'.mat',sprintf('-h%i.mat',USABLE_HAMMING));
if ~exist(combined_transcriptsfile,'file') && ~exist(combined_transcriptsfile_refined,'file')
transcript_obje... |
3cb714b2865f2a7e50d535bea117c7a5dab8b3963b5f80904ee0e0e34d38f407 | MATLAB | 9,699 | 289 | function voldata = iimg_reconstruct_vols(dat, volInfo, varargin)
% Reconstruct a 3-D or 4-D volume from a "dat" matrix of vectorized images
%
% :Usage:
% ::
%
% voldata = iimg_reconstruct_vols(dat, volInfo, [optional args])
%
% :Optional Inputs: If entered, will write .img file to disk
%
% **'outname':**
% ... |
f11074fa7425c15f2e5cc51937c8ebd02a2bd9e8b724283914ff02cae84377fe | MATLAB | 9,699 | 258 | function CBIG_glm_regress_vol(fMRI_list, output_list, regressor_list, polynomial_fit, censor_list, per_run)
% CBIG_glm_regress_vol(fMRI_list, output_list, regressor_list, polynomial_fit, censor_list, per_run)
%
% This function does GLM regression for fMRI volumetric data. It will:
%
% 1) read in fMRI volumetric data f... |
c82adefa2a733ac9fb4c296b1aa21c718559688799a5427e26bd54d7015cf560 | MATLAB | 9,702 | 417 | function Social_entries(basename,tet2use,unit,session,boundarie_1,boundarie_2)
SR=20000;
SR_trk=50;
cells= unit;
resofs=load([basename '.resofs']);
sessionfile = [basename(1:9) '_' num2str(session,'%02.f') '.mat'];
load(sessionfile,'trk');
whl = trk;
value_new=300;
res=load([basename '.res.', num2str(tet... |
877dd9eb66e24977c0daa57089ff666f459c16116ca9104f78bbce9ebdff518b | MATLAB | 9,704 | 267 | function varargout = ICVAE_settings(varargin)
% ICVAE_SETTINGS MATLAB code for ICVAE_settings.fig
% ICVAE_SETTINGS, by itself, creates a new ICVAE_SETTINGS or raises the existing
% singleton*.
%
% H = ICVAE_SETTINGS returns the handle to a new ICVAE_SETTINGS or the handle to
% the existing singleton... |
362bc42ba18fe7c747bf0b3c9fbcf0bf50a32e6f864f57eaade9d37b23e29301 | MATLAB | 9,708 | 321 |
% cmps={[1 2],[1 3],[2 3],[ 1 2 3],1,2,3};
%%
% [~,Type] = Utilities.ProcVarargin(pltFCNArgs,'Type','T');
% ConditinList={{'T','F','L0'},...
% {'F','L0','L1'}}
FigHandels=[];
% if Type=='T'
% condName='TFL0';
% L={'TFL0','','FL0','','TF','','TL0',''};
% else
% condName='FL0L1';
% L... |
bf22ad4df7a499d8bac678e7cb89a65ebe1bc27d98036c7dd42eea30f3146647 | MATLAB | 9,714 | 198 | function make_BNV_ready(paths, brainnet)
% To make *.node and *.edge files for viewing connectivity results from NBS
% or custom max-T analysis on BrainNet Viewer (BNV).
%
% PLEASE NAME the saved NBS workspace variable as
% [nickname]_NBSResults_[freq].mat
%
% INPUT--------------------------------------------------... |
c87a62cce7b325441b7510cdda88060c08a927ebd2c1cdfcaf33c53724e24386 | MATLAB | 9,737 | 270 | %{
Copyright (c) 2025 Axion BioSystems, Inc.
Contact: support@axion-biosystems.com
All Rights Reserved
%}
classdef CombinedBlockVectorHeaderEntry < Entry
%CombinedBlockVectorHeaderEntry Entry which contains the entirety of a
%block vector
%
% VersionMajor: Writing version (Major number) th... |
4a0dea3b930aa20811bf1cdd7dd0e1d9885708c00a3404e69cbf15fcf191f1b1 | MATLAB | 9,738 | 241 | function [dfield,moving_reg] = imregdemons_ZN(moving,fixed,varargin)
%IMREGDEMONS Estimate displacement field that aligns two 2-D or 3-D images.
%
% [D,MOVING_REG] = IMREGDEMONS(MOVING,FIXED) estimates the displacement
% field D that aligns the moving image, MOVING, with the fixed image,
% FIXED. MOVING and FIXED... |
698190a04b8ea4c36974a762afc99b6ad212157d64a22a5c2b8af67315fc641a | MATLAB | 9,739 | 360 | %%
load trnDataSH_Apr18.mat
load trk__vw2_all.mat
load trk_Igt_crop_vw2_all
%%
nGT = height(tGT);
pGT = reshape(xyLbl_GT_crop(:,:,:,2),nGT,10);
ids = tGT.id2_nonunique;
idxs = randsample(nGT,20);
Shape.montage(Igt_crop(:,2),pGT,'nr',4,'nc',5,'p2',pTstTRed,'idxs',idxs,...
'framelbls',ids(idxs));
%%
PAT = 'trk__res_IF... |
9ef76c286fe7f6aeff964d493e80299cd06ed3b4f5bcbfa567985a883da8897d | MATLAB | 9,740 | 376 | function LAN = merge_lan(LAN1,varargin)%LAN2,
% merge two LAN
% form: LAN = merge_lan(LAN1,LAN2,LAN3,...)
% LAN = merge_lan(LAN)
% LAN = merge_lan(cfg)
% cfg.lan1 = estructura lan o 'srt' con nombre de variable en workspace
% .lan2 = idem
% .sort = vector del orden de epoc... |
251fce03b2cdaa5619306de411f05a42333fd03d86c9ae614b4e66661559d953 | MATLAB | 9,744 | 211 | function [intersect, t, u, v, xcoor] = TriangleRayIntersection (...
orig, dir, vert0, vert1, vert2, varargin)
%TRIANGLERAYINTERSECTION Ray/triangle intersection.
% INTERSECT = TriangleRayIntersection(ORIG, DIR, VERT1, VERT2, VERT3)
% calculates ray/triangle intersections using the algorithm proposed
% B... |
afba0cc63d670309d3cec3d56f48d226ba5ec17c288a5c7ef4197ab8c765be24 | MATLAB | 9,745 | 268 | function [c, v, outcnt] = ft_connectivity_corr(input, varargin)
% FT_CONNECTIVITY_CORR computes correlation, coherence or a related quantity from a
% data-matrix containing a covariance or cross-spectral density. It implements the
% methods as described in the following papers:
%
% Coherence: Rosenberg et al, The Four... |
4ecfd877afe1a44c6a20727c4ca7e04b35159aa9ffebfc4b057abaf72f0ba0df | MATLAB | 9,747 | 250 | classdef Field < handle_light
% Map defined over the whole manifold, which is a collection of Map
% objects defined on different sets in the topology, here referred to
% as patches.
%---------------------------------------------------------------------
% license
%-----------------------... |
8a872d77d9a2d4e27a5d062cee65079245d0d8382999372e7d1c9377f021ebe7 | MATLAB | 9,748 | 200 | function currents = getCurrentsStructure_ToRORdLand(time, X, beats, parameters, ignoreFirstSpikes)
% Extraction of parameters
cellType = 0; if (isfield(parameters,'cellType')) cellType = parameters.cellType;end
nao = 140;if (isfield(parameters,'nao')) nao = parameters.nao; end
cao = 1.8;if (isfield(parameters,'cao')) ... |
446897b9e8cf19024fc7a51cea29456c5cff62d5afb6b613e03935566f9385fa | MATLAB | 9,753 | 286 | %% Function for analysis of ICP on an insult-basis
function [ICP_insults] = func_ICP(ICP, outcome)
% Input:
% ICP_data: ICP time series (optionally filtered to remove noise)
% outcome_data: to make the correlation plot, individual ICP data
% needs to be correlated to individual outcome scores (e.... |
76c97fcde1c53f4fc27b95d4eed68ac995423910a815fdda2f36008adb6f221b | MATLAB | 9,753 | 161 | function sPPI_and_gPPI_with_deconv_FIR(stat_path,exp_folder,N,N_ROIs,q_level,ground_truth)
% ========================================================================
% Ruslan Masharipov, October, 2023
% email: ruslan.s.masharipov@gmail.com
% ========================================================================
tic... |
3f43e982ee12f1f02d0b58ae12ebd6b85a949b0d90dc89716bb0e348d6d83477 | MATLAB | 9,759 | 252 | function [h, coordsys] = ft_headcoordinates(fid1, fid2, fid3, fid4, coordsys)
% FT_HEADCOORDINATES returns the homogeneous coordinate transformation matrix
% that converts the specified fiducials in any coordinate system (e.g. MRI)
% into the rotated and translated headcoordinate system.
%
% Use as
% [h, coordsys] =... |
4b9e1955cf76d5e4e32c358d133aba62f4511f335ed225fab4c5a654aef39e96 | MATLAB | 9,759 | 276 | function CBIG_ASDf_Plot400Schaefer19Subcor17Networks_419by419Input(corr_mat, scalelim, filename_prefix)
% CBIG_ASDf_Plot400Schaefer19Subcor17Networks_419by419Input(corr_mat, scalelim, filename_prefix)
%
% This function draws the 419x419 correlation matrix (400 cortical ROIs +
% 19 subcortical ROIs).
% Major networks a... |
6206ebf8255194f295717f02bbd3b8448e9e4554900faeb9895a9f0c3f124147 | MATLAB | 9,762 | 313 | %% CellVCat ("Cellwise Vertical Concatenation")
% perform vertical concatenation of array elements down a cell (dim 1)
% assumes that the 2nd dimension is constant across all rows; tranpose if
% this assumption is violated
% Potential Inputs and Behaviors:
% ---------------
% Nx1 cell array:
% - Each element of... |
6ca66ac7b649f149517f593b9727fdb87fa26a7c1d8fd68e5c3cf3776f9b64b4 | MATLAB | 9,762 | 265 | % Author: Daniel J. Beall
% Email: DJBEALL1101@gmail.com
%
% beall_blink_detection() - Returns list of ICA components marked as a blink
%
% Usage:
% >> [blinks]=beall_blink_detection(cwb,topog,chanlocs,n);
%
% Inputs:
% cwb - list of components with bumps
% topog - topographies vector
% ... |
1e65d379a583fcb73742f2658121c78b57bfbecb0d308a3b42a52fe05513a777 | MATLAB | 9,777 | 289 | function CrossMahalanobisDistance(AllTrialData,Labels,TimeWindow,OutDir,Tag,varargin)
% Train on dim 1 to classify dim 2, test on how well it generalizes.
% e.g. train on nancy to diff bp, test how well bp diff'd in Tyson.
[~,PThresh] = Utilities.ProcVarargin(varargin,'PThresh','fdr');
% [~,NIter] = Utilities.Pr... |
fb3c06d9828ac0dede41cde07466a0849890d5cc121b332dbc433fad1728a035 | MATLAB | 9,779 | 262 | function ft_uilayout(h, varargin)
% FT_UILAYOUT is a helper function to make a consistent graphical user interafce with
% multiple control elements. This function will find all elements with a specific tag
% and style, and update or position them consistently.
%
% Use as
% ft_uilayout(h, 'tag', '...', 'style', '...'... |
fb2b2bcdc0fe15477c61114d287feafd0909b0431cc4880ec5b2f096231dd64f | MATLAB | 9,781 | 262 | function ft_uilayout(h, varargin)
% FT_UILAYOUT is a helper function to make a consistent graphical user interafce with
% multiple control elements. This function will find all elements with a specific tag
% and style, and update or position them consistently.
%
% Use as
% ft_uilayout(h, 'tag', '...', 'style', '...'... |
6904dbe24799320107bbff6389cbfc42372f5cb73d7931234db1948357975fca | MATLAB | 9,783 | 262 | % Author: Birgit Nierula
% nierula@cbs.mpg.de
function [out] = ga_combineData(subjects, condition, srmr_nr, is_raw, dat_level)
out = {};
% get condition info
[cond_info] = get_conditionInfo(condition, srmr_nr);
cond_name = cond_info.cond_name;
nerve = cond_info.nerve;
trigger_name = cond_info.trigger_name;
str_stimu... |
8274fa23ee68f49e05de0999ba1d09e50d6c98c287a43bbf858b7e2bf89c0218 | MATLAB | 9,786 | 302 | %%
TDFILE = '/groups/branson/bransonlab/apt/experiments/data/trnDataSH_20180503.mat';
BASEPROJ = '/groups/branson/bransonlab/apt/tmp/sh_empty_base_proj_5pts_2vws.lbl';
FLY2CALIB = '/groups/branson/bransonlab/apt/experiments/data/fly2DLT_lookupTableAL.csv';
td = load(TDFILE);
tMain = td.tMain;
fly2calib = readtable(FLY2... |
edcc82228e8d4417093780b6af3cf6014d3f5d7f2186363de94e95775b0ba1af | MATLAB | 9,790 | 308 | %% initialize settings
% Controls how far apart the frames we are analyzing. Setting 'fs' to 15
% means that every 15 frames are analyzed out of our video.
fs = 1;
sizeThresh = 10;
% A decimal value used during background subtraction. A typical value would
% be from -0.1 to 0.1. Can be negative. The higher this valu... |
cbcc56164ac34aac84f742b531298c6950165de11d578a0cdc20a4825c037e76 | MATLAB | 9,796 | 233 | function [] = actionAnalysis(dataset,folders,params)
close all
JAABA_folder = folders.JAABA_folder;
%'C:\Users\lt532\Desktop\Aggression Project\JAABA Stuff\JAABA-master\MirrorChamberData\';
warning('off','stats:gmdistribution:MissingData')
d = dir(JAABA_folder);d(1:2) = [];
JAABA_subfolder = {d.name}';
thrust_thresh =... |
18bd8980334bb4bef6da56a28547afdbd87a6d8259f1efe2c75e06a99a329ef9 | MATLAB | 9,800 | 295 | function h_hotKeyControls3(handles, keyData)
[currentInd, handles, currentStruct, currentStructName] = h_getCurrendInd3(handles);
key = keyData.Key;
modifier = keyData.Modifier;
switch(key)
case {'rightarrow', 'leftarrow', 'uparrow', 'downarrow'}
switch(key)
case 'rightarrow'
... |
ead8c09a5972fc26fb90f6bbdfb116e77a5571df37568694bbe04c778b3e7479 | MATLAB | 9,802 | 311 | % [sbfmfnames,rois] = avitosbfmf(...)
%
% Inputs an AVI movie and converts to an SBFMF movie.
% Also allows user to specify regions of interest,
% in which case each region of interest is saved to a
% different SBFMF.
%
% Usage:
% The parameters to avitosbfmf can be specified as pairs
% consisting of a string speci... |
9eb4185ee134285330bb5620048e7ab06d538c58d4de7ba0cd8985daf6ef56ee | MATLAB | 9,805 | 391 | % Minimal tutorial script - Comparing ground truth and detected burst events
% with synthetic data.
% See LICENSE.md for distribution information.
%
%
% Configuration.
%
% Paths.
addpath('lib-wl-synth', 'lib-wl-proc', 'lib-wl-ft', 'lib-wl-aux', ...
'lib-wl-plot');
%
% Data files.
outputfile = 'output/minimal-s... |
a9a2d92b73ad5d5469a83c11e749a2ff13ce8ae3f7885227bef11da2a958f489 | MATLAB | 9,806 | 261 | function embedding = optimize_layout4(head_embedding, tail_embedding, ...
head, tail, n_epochs, n_vertices, epochs_per_sample, a, b,...
gamma, initial_alpha, negative_sample_rate, verbose, min_dist)
%OPTIMIZE_LAYOUT2 Another version of optimize_layout.m that slightly
% optimizes the speed for MATLAB; in particu... |
f158c907261924306135ca34cb202284b850c2a93db402f8fb594ede40d04a62 | MATLAB | 9,806 | 301 | function ie_sphere(n,nquad,occ,p,rank_or_tol,store,method)
% IE_SPHERE An example usage of strong skeletonization, solving a
% second-kind integral equation (Laplace double-layer potential) on the
% unit sphere. Sane defaults are provided for all parameters.
%
% IE_SPHERE(N,NQUAD,OCC,P,RANK_OR_TOL,STORE,METHOD) r... |
f749ebdf54a5bf3b2dce557a64c1af536e3bb99c9cfc08dbb2c075928df1130b | MATLAB | 9,815 | 279 | function varargout = w_QCList(varargin)
% W_QCLIST MATLAB code for w_QCList.fig
% W_QCLIST, by itself, creates a new W_QCLIST or raises the existing
% singleton*.
%
% H = W_QCLIST returns the handle to a new W_QCLIST or the handle to
% the existing singleton*.
%
% W_QCLIST('CALLBACK',hObject,ev... |
19a97fecb927a26a1baaf0af6051f207bda53cef19154fddc5b554ddc19cb224 | MATLAB | 9,821 | 220 | function [spk, spkMap, spkView, par] = reformDat(par, dd)
%% Generate spiking histograms for all trials and neurons
% Inputs
% - par = basic information about the recording session and parameters
% including
% the time vectors par.tsl (time aligned to motion onset in ms)
% and par... |
00a20e285bdeb844362f0235889ce383fb66e5bec9adcd74f875317f338cb018 | MATLAB | 9,825 | 225 | %-------------------------------------------------------------------------
% Author: Brandon S Coventry
% Goal: To transform data from raster into Infotheory toolbox (Timme) form
% Date: 01/10/2023
%--------------------------------------------------------------------------
%Data storage shape
% n stimulus conditionsxre... |
cf2391983b0b1855acf6b5ff2f36764961f68eb6548d9422dff676317709b6c7 | MATLAB | 9,827 | 254 | function t = CritT(alfa,v,tail)
% File name : 'CritT.m'. This file can be used
% for quickly obtaining the critical t-value for
% alfa values of 0.01, 0.05, 0.10 and degrees of freedom
% between 1 and 100
%
% One input values : 'alfa','v','tail'
% One output value : 't'
%
% alfa: significance level (0.0... |
8c3c09c220a2e2dab602b38af0807e0f380451dc9bff11024e0d86e797633d42 | MATLAB | 9,833 | 286 | classdef DateTime
% This class enclapsulates date time value but behaves in a very
% similar way as typical array of timestamps in datenum format
%======================================================================
%{
Copyright (c) 2011
This program is a result of a joined cooperation of Energocent... |
b9b899dfcf6883e488226117fbae292b0b0eef5e06bb1e4f8bd47544831750be | MATLAB | 9,835 | 277 | function arr = exindex(arr, varargin)
%EXINDEX extended array indexing
% ARROUT = EXINDEX(ARRIN, S1, S2, ...) indexes a virtual array made by
% extending ARRIN with zeros in all directions, using subscripts S1, S2
% etc.
%
% ARROUT = EXINDEX(ARRIN, S1, R1, S2, R2, ...) extends ARRIN using rule
% R1 on ... |
bdf0cb564107cdbab3d6fb9014ff498ed233e13cdae8ee093308758f40b9b73d | MATLAB | 9,837 | 200 | function currents = getCurrentsStructure_ToRORd(time, X, beats, parameters, ignoreFirstSpikes)
% Extraction of parameters
cellType = 0; if (isfield(parameters,'cellType')) cellType = parameters.cellType;end
nao = 140;if (isfield(parameters,'nao')) nao = parameters.nao; end
cao = 1.8;if (isfield(parameters,'cao')) cao ... |
cbee9688dbf04e877a485b2b430c2c3d423939b03fd522190c4715aa44c0795d | MATLAB | 9,838 | 305 | %% set up paths
JAABAcodedir = '/groups/branson/home/bransonk/behavioranalysis/code/Jdetect/Jdetect';
labelfiles = {
'/tier2/hantman/Jay/videos/M186hm4dBPN/labeler/M186hm4dBPN_manualEndpoint1stCNO.lbl'
'/tier2/hantman/Jay/videos/M186hm4dBPN/labeler/M186hm4dBPN_manualEndpoint2ndCNO.lbl'
'/tier2/hantman/Jay/videos... |
f2178891587553cbf0f83d6ea99c428f9ee0c4af73451b60e4fc9fba64e655ae | MATLAB | 9,839 | 270 | function [im_hatch,colorlist] = applyhatch_pluscolor(h,patterns,CvBW,Hinvert,colorlist, ...
dpi,hatchsc,lw)
%APPLYHATCH_PLUSCOLOR Apply hatched patterns to a figure in BW or Color
% APPLYHATCH_PLUSCOLOR(H,PATTERNS) creates a new figure from the figure H by
% replacing d... |
4de8601cb08ba5fc8786d748e7d6eea824e909add9020e8e04c68727f2e331bb | MATLAB | 9,849 | 306 | % HIFDE3 Hierarchical interpolative factorization for differential equations
% with nearest-neighbor interactions on a regular mesh in 3D.
%
% This is an optimization of HIFDE3X for the special case of nearest-neighbor
% interactions on a regular mesh in 2D. A given mesh node is allowed to
% interact ... |
eea8bed8ad41800b4416dff434b7dc8fcaf946979dc2c1bf0cab6cea525c623b | MATLAB | 9,873 | 161 | function sPPI_and_gPPI_with_deconv_no_centering_FIR(stat_path,exp_folder,N,N_ROIs,q_level,ground_truth)
% ========================================================================
% Ruslan Masharipov, July, 2024
% email: ruslan.s.masharipov@gmail.com
% ===================================================================... |
eba8d25295bca4a7359db9020d7371cf6d91d4edc2c553002916ef30f9cc798c | MATLAB | 9,885 | 209 | % Comparison of freq and amp on RF size
addpath("HelperFunctions")
load(fullfile(DataPath, 'IntraDayVariability_Processed.mat'))
load(fullfile(DataPath, 'AmpFreqSurvey_Processed.mat'))
AmpFreqResults = struct();
%% Remove CRS02 from IntraDay structure
IntraDayVariability = IntraDayVariability(strcmp({IntraDayVariabil... |
e2c9d373b2f933cfdb60d8749816569ec4d7b9d7430d89d042d86c026359fb2c | MATLAB | 9,890 | 281 | function [dipout] = beamformer_sam(dip, sens, headmodel, dat, all_cov, varargin)
% BEAMFORMER_SAM scans on pre-defined dipole locations with a single
% dipole and returns the CTF Synthetic Aperture Magnetometry (SAM)
% beamformer estimates. location. Dipole locations that are outside
% the head will return a NaN value... |
ffd3d568c566e700f9b449327024b3d4931252bad2fda84c5fb8a526c4be2367 | MATLAB | 9,895 | 278 | function CleanReview(spkDat, cleanDat, clust, errCriterion, varargin)
maxScale = 2;
sameScale = true;
convertToVolt = true;
nSampTarget = 300;
nSampReject = 25;
nSampAccept = 25;
minIsi = 1;
Fs = spkDat.Fs;
spkDat.waves = double(spkDat.waves);
wvFs = Fs * spkDat.upsample;
for i = 1:2:length(varargin)
switch lower... |
928334032b5f3ffd3f2b12ff8e8fe1f7fb320624f00abbf865c8702b3203fc02 | MATLAB | 9,896 | 291 | function varargout = DPARSF_ScrubbingSetting_gui(varargin)
% varargout = DPARSF_ScrubbingSetting_gui(varargin)
% GUI for setting parameters for Scrubbing.
% Input: FDType, FDThreshold, PreviousPoints, LaterPoints, ScrubbingMethod.
% Output: FDType, FDThreshold, PreviousPoints, LaterPoints, ScrubbingMethod.
... |
32265ec7fe6523b15d019a6b11f33f3afbb80402c6d5821927e292d743c72bdb | MATLAB | 9,898 | 353 | function eventmatrixdata = wlFT_doFindEventsInTrials( trialftdata, ...
bandlist, segconfig, paramconfig, bandoverrides, tattleprogress )
% function eventmatrixdata = wlFT_doFindEventsInTrials( trialftdata, ...
% bandlist, segconfig, paramconfig, bandoverrides, tattleprogress )
%
% This function calls wlProc_doSegm... |
7717723d943fa5a344d5ad559652389eaba8795cb84805c7dfa3ec43992f49b6 | MATLAB | 9,898 | 253 | function [stat] = ft_sourcestatistics(cfg, varargin)
% FT_SOURCESTATISTICS computes the probability for a given null-hypothesis using
% a parametric statistical test or using a non-parametric randomization test.
%
% Use as
% [stat] = ft_sourcestatistics(cfg, source1, source2, ...)
% where the input data is the resul... |
0ba2694069cede86f6389f8715f126524de6374d15940e661f8c42c6fc8f5974 | MATLAB | 9,905 | 202 | function [J] = build_jacobian_FD(mesh,data,varargin)
% BUILD_JACOBIAN_FD Calculates spatial distributions of sensitivity of
% field registerd on the mesh boundary to changes of optical properties
% per mesh node. It deliveres up to 4 distributions:
% If data are real (CW - continuous wave):
% - J_{mua}^{A} ... |
de4c82cbec3a4a65a0ab1144a61a070a036b286a68ec84855d748abe5ff87851 | MATLAB | 9,913 | 275 | % header = mmf_read_header(filename)
% TODO: handle multichannel data, non 8-bit data
% mmf format documentation:
% Set of Image Stacks representing a movie. Beginning of file is a header, with this format:
% 10240 byte zero padded header beginning with a textual description of the file, followed by \0 then the follow... |
22dac1fae20ac9e56df1fb86716033ee87551e152aa8122082010055430fc4e6 | MATLAB | 9,921 | 352 | function eventmatrixdata = wlFT_doFindEventsInTrials_MT( trialftdata, ...
bandlist, segconfig, paramconfig, bandoverrides, tattleprogress )
% function eventmatrixdata = wlFT_doFindEventsInTrials_MT( trialftdata, ...
% bandlist, segconfig, paramconfig, bandoverrides, tattleprogress )
%
% This function calls wlProc_... |
ba41d4603f023cf290f7328c33b27e2240f31d6c4252877c8bf2c4cc183ac6ce | MATLAB | 9,925 | 252 | function [spectrum,freqoi,timeoi] = lan_specest_wavelet(dat, time, cfg)
% LAN_SPECEST_WAVELET picks up the equivalent fieldtrip function,
% FT_SPECEST_WAVELET, and replaces calls to other fieldtrip functions.
% Optional arguments should be provided within a single structure, unlike
% the original implementation.
%
%... |
fdbc4a8faf0c365623104722661512843894ee112f40c1312b0b69d34e8f4e45 | MATLAB | 9,939 | 254 | function [stat] = ft_sourcestatistics(cfg, varargin)
% FT_SOURCESTATISTICS computes the probability for a given null-hypothesis using
% a parametric statistical test or using a non-parametric randomization test.
%
% Use as
% [stat] = ft_sourcestatistics(cfg, source1, source2, ...)
% where the input data is the resul... |
6d5c421b7151de4afbf9237b7c0269e2cc1c9c09e5d03ac0b25b657e5cd88a7b | MATLAB | 9,940 | 233 | % SubtractContinuousVariables.m
% Sarah West
% 6/13/22
% Removes Beta * continuous Y response variable from X explanatory variables
% after continuous variable regressions.
function [parameters] = ResidualsFromContinuous_Inverted(parameters)
MessageToUser('Residuals from ', parameters);
dataset_info = param... |
aa35eade9b4addec0c77f762d4e38b21a76a0b89795ac1dc721e302be1cc0dac | MATLAB | 9,940 | 283 |
%
shifting_key_n = floor(tiling_info.z_pixel./z_truncate);
% shifting_key_n = 20;
% z_truncate = floor(tiling_info.z_pixel./shifting_key_n);
clear stitching_queue tform
kk = 0;
for ii = 1:size(read_file_name,1)-1
for jj = 1:size(read_file_name,2)
kk = kk+1;
stitching_queue(kk).tile_1 = ... |
e1906661a05a01f82e25a829369aefddb59c7be0d428727592718dc33c2689a9 | MATLAB | 9,941 | 264 | function [cROIs, Cs, cROIs_BG, Cs_BG, coherence, skew, sz, patch_ID, A0] = DNMF_General(paths_to_videos, options)
% [cROIs, Cs, cROIs_BG, Cs_BG, coherence, skew, sz, patch_ID, A0] = DNMF_General(paths_to_videos, options)
%
% Jason Moore, 2025
%Extract options
maxVal = options.maxVal;
s... |
30cd80674b49428f590c1041757029619fe82890a7458d24d2822d4a7da0a9af | MATLAB | 9,943 | 315 | function [source] = ft_appendsource(cfg, varargin)
% FT_APPENDSOURCE concatenates multiple volumetric source reconstruction data
% structures that have been processed separately.
%
% Use as
% combined = ft_appendsource(cfg, source1, source2, ...)
%
% If the source reconstructions were computed for different ROIs or ... |
da4370947a1d71e3435182c0630aef15cc3c42d53300cc144cde8f6bae1566c3 | MATLAB | 9,946 | 258 | %% dataCellSuperClass
%
% || -- Superclass for generic methods of working w/ dataCell classes
% Copyright (C) 2023 Trevor S. Smith
% Drexel University College of Medicine
%
% 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
% t... |
7434f522fac8987f3cc673971ad2d0a28f00fc5827221ee343d223cf2fbeb09e | MATLAB | 9,950 | 246 | function csi(filename, experimentName)
if isempty(filename)
quit(2);
end
data = load(filename);
NeuP = data.NeuP;
HeadX = data.HeadX;
HeadY = data.HeadY;
Speed = data.Speed;
% Determine how many segments
[seg,frame]=size(NeuP);
seg = 1:seg;
num_seg = numel(seg);
... |
cd7abbe9bcbb243d92f110b491503bf1730b932b6dac3a1ad1671b1db6c701b2 | MATLAB | 9,952 | 341 |
% load data
% contact Lead Author for data
%% number of cells - AO vs VS
% panel 2F
figure; hold on
% AO1-VS1;
xx = cellRatioNcells{1}; k = size(xx, 1);
plot([ones(1,k); ones(1,k)*2], xx', 'Color', [1 1 1]/2);
yy = xx(:,1); clr = 'm';
bar(1, mean(yy), clr, 'FaceAlpha', 0.5);
errorbar(1, mean(yy), st... |
354e881bff982cf5bdd2ba7e90f8758163b234b7ad80ac8fb70f4144b2b21c9f | MATLAB | 9,955 | 285 | function [spike] = ft_read_spike(filename, varargin)
% FT_READ_SPIKE reads spike timestamps and waveforms from various data
% formats.
%
% Use as
% [spike] = ft_read_spike(filename, ...)
%
% Additional options should be specified in key-value pairs and can be
% 'spikeformat' = string, described the fileformat (defa... |
00bec7ab235b40f33f353d98649df95e290b3e6a60b3ea6f47eae249c2fb00e9 | MATLAB | 9,957 | 268 | function ClusterStates_MakeFigure(SleepState,basePath,noprompts)
%Check needed here if Sleep state has the right stuff
v2struct(SleepState.detectorinfo.detectionparms.SleepScoreMetrics)
v2struct(SleepState.detectorinfo.StatePlotMaterials)
v2struct(SleepState.detectorinfo.detectionparms.SleepScoreMetrics.histsandthre... |
0d2c46014989fe82f091c53cf34081550536184b1ff45662b4760b0f76be6267 | MATLAB | 9,961 | 315 | function [source] = ft_appendsource(cfg, varargin)
% FT_APPENDSOURCE concatenates multiple volumetric source reconstruction data
% structures that have been processed seperately.
%
% If the source reconstructions were computed for different ROIs or different slabs
% of a regular 3D grid (as indicated by the source pos... |
e1ee14eaef8a53e36cfbb75e5d8b6cd5f90e83675ea4d1fcaf4f9aaae72eedaf | MATLAB | 9,964 | 165 | function sPPI_and_gPPI_without_deconv(stat_path,exp_folder,N,N_ROIs,q_level,ground_truth)
% ========================================================================
% Ruslan Masharipov, October, 2023
% email: ruslan.s.masharipov@gmail.com
% ========================================================================
tic
... |
f7ec55c6d6791799fe41c88f91c95584fbd74d3870b03b16b490ee0a5d9c8a51 | MATLAB | 9,971 | 254 | function [X tcens]=ms_extract_clips2(Y,times,T,beta,betaonesnap)
%MS_EXTRACT_CLIPS2 - Extract clips from raw/preprocessed data array centered
% at a collection of event times, possibly upsampling/shifting
%
%Consider using mscmd_extract_clips
%
% Syntax: [X tcens] = ms_extract_clips2(Y,times,clip_si... |
3cbb9857bfa8e67474d94056e62e1a0b2a1bfb862c2568ff7fb2fca498a15cae | MATLAB | 9,972 | 293 | function [out1,out2,out3] = ginput2(arg1)
%GINPUT Graphical input from mouse.
% [X,Y] = GINPUT(N) gets N points from the current axes and returns
% the X- and Y-coordinates in length N vectors X and Y. The cursor
% can be positioned using a mouse. Data points are entered by pressing
% a mouse button or any ke... |
e5ad54d7e66eea86199e443d69ac17000ec640fe6acd6dbdef590c20f7d97c68 | MATLAB | 9,972 | 360 | function [CMAP,CLIM,WIDTH,REF,LEVELS] = cmfit(CMAP,CLIM,WIDTH,REF,CENTER,varargin)
%CMFIT Sets the COLORMAP and CAXIS to specific color bands.
%
% SYNTAX:
% cmfit
% cmfit(CMAP)
% cmfit(CMAP,CLIM)
... |
948723fed9a5a603956ac57c66bb5b24482ca1a9ff607fd379ee1cdfe0eb6bf5 | MATLAB | 9,973 | 248 | function [spectrum, freqoi, timeoi] = ft_specest_tfr(dat, time, varargin)
% FT_SPECEST_TFR performs time-frequency analysis on any time series trial data using
% the 'wavelet method' based on Morlet wavelets, doing convolution in the time
% domain.
%
% Use as
% [spectrum,freqoi,timeoi] = ft_specest_convol(dat,time,.... |
fe6d04002d6f1b4508b8ab7c72b32a8d2c934b47fa3f7f25293eb7bad3c315e3 | MATLAB | 9,994 | 58 | function plot_model(COR,ind,chanlocs,t,alfa)
if nargin < 5
alfa=0.05;
end
%electrode =
chanlocs = chanlocs ;
coef = size(COR.models(ind).t,2);
if strcmp(t,'t')
topo = figure('Colormap',...
[1 1 1;0.972972989082336 0.999628365039825 0.999628365039825;0.945945918560028 0.999256730079651 0.999256730079651;0.918... |
126b60d1e31e07bbd74c0e1716c7e3ba6d6d290c90f76cc7c083f8f238061a75 | MATLAB | 9,997 | 336 | function [volInfo, dat] = iimg_read_img(inputimgs, extended_output_flag, reading_data, first_vol)
% :Usage:
% ::
%
% [volInfo, dat] = iimg_read_img(inputimgs, [extended_output_flag (1|2)], [reading_data (0|1)], [first vol only (0|1)]);
%
% - reads 3-D or 4-D img/nii files, with extended volInfo output
% - flag to r... |
da6356291e4714e248147bc4a0d3e7b91445f778e0fcbe79b6fd00cfb19b73c1 | MATLAB | 10,002 | 153 | %% RELAX EEG CLEANING PIPELINE, Copyright (C) (2024) Aron Hill & Neil Bailey
% 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
% any later... |
13032f031f126e7e06c1878f4a80bad2d0aedac53d3746834e3b837613603fb8 | MATLAB | 10,005 | 347 | function [C,Ceq] = Constraint_Function (xopt)
NineMuscleMorphParaInitial = load('NineMuscleMorphParaInitial.mat');
NineMuscleMorphParaInitial = NineMuscleMorphParaInitial.NineMuscleMorphParaInitial;
G = 4; % Muscle Group Number (G = 1 to 9)
x0(1) = NineMuscleMorphParaInitial{G, 1}.MorphologicalParameters.a1;
x0(2) ... |
3ec0efd7feb0fd49d33e06638b5de5bef9b616c3cf58d63351073bb25946350d | MATLAB | 10,011 | 349 | function [C,Ceq] = Constraint_Function (xopt)
NineMuscleMorphParaInitial = load('NineMuscleMorphParaInitial.mat');
NineMuscleMorphParaInitial = NineMuscleMorphParaInitial.NineMuscleMorphParaInitial;
G = 2; % Muscle Group Number (G = 1 to 9)
x0(1) = NineMuscleMorphParaInitial{G, 1}.MorphologicalParameters.a1;
x0(2) ... |
19bcee509ca94ae8924b0e801512fbed252849c54b9fa9ae4bb9031cfebb1912 | MATLAB | 10,021 | 213 | %Analyze_Frontloading.m
%This script analyzes alcohol drinking patterns to assess if
%alcohol front-loading is present using the following
%criteria:
%1*. Of three detected change points, the change point with the best fit
%is the earliest and/or is within the first half of the session. This
%becomes the reference cha... |
e730e8ad854c06a533d6c350c9b15a28647debda0ab9b05998e78f7dffe5195d | MATLAB | 10,027 | 194 | function [Si, Stm, sROI] = boney_segment_create_bone_surface ...
(Vo, Ybonepp, Ybonemarrow, Ybonethick, Yheadthick, Ya, Ymsk, YaROIname, YaROIid, out, job)
%create_bone_surface. Surface-based processing pipeline.
% Final bone processing function that creates the bone surfaces to extract
% values from the surrounding ... |
727c1a39f09869e315ebf2cf23d16bdca94ba46ab4624361c68af9514fe80e00 | MATLAB | 10,029 | 303 | function ReclassifyReview(spkDat, reclassDat, varargin)
% convert waveform data from int16 to double-precision floating point
spkDat.waves = double(spkDat.waves);
minIsi = 1;
[wL, nChan, ~] = size(spkDat.waves);
pk = spkDat.peakLoc;
wP = spkDat.wavePad;
wL = wL - 2*wP;
vScale = spkDat.vScale;
maxScale = 1;
sameScale ... |
86e99bcacc1ec9c82aea9fbce3df3ef945dfd922753480de93244afa7a085b36 | MATLAB | 10,040 | 243 | function seizureInfo = getSeizureTimingInfo(seizurePath, seizureCell, params)
% This function reads a seizure's mat file and extracts information about
% the baseline times, seizure times, postictal times, recovery times, and
% control times. It also extracts information about lick and click times.
% INPUTS:
% - sei... |
2e46f364f22702c74a56b0d0e7c983f2ff552a45c0ab0c7d6dacefef1044571a | MATLAB | 10,041 | 269 | function save(this,filename,encoding,ordering)
% Save GIfTI object in a GIfTI format file
% FORMAT save(this,filename,encoding)
% this - GIfTI object
% filename - name of GIfTI file to be created [Default: 'untitled.gii']
% encoding - optional argument to specify encoding format, among
% ASCII, Base6... |
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