sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
461640ebf4813b7dba30b53e0990117c4e37294d9e8ad7918449b7717bf6f7e3 | MATLAB | 18,404 | 489 | function save = write_to_spm(subj,objtype,objin,varargin)
% Writes an MVPA data object or group to a SPM file.
%
% [] = WRITE_TO_SPM(SUBJ,OBJTYPE,OBJNAME,...)
%
%% Required Fields
%
% Writes an MVPA object in the subject structure SUBJ to an SPM file. This
% structure is to be of type OBJTYPE and must corespond to th... |
e3ed34916d8946a8bc7e25866dd6027c13aa50d1efbfcbb5124d79769d6c71cb | MATLAB | 18,445 | 448 | function DOMnode = xml_write(filename, tree, RootName, Pref)
%XML_WRITE Writes Matlab data structures to XML file
%Downloaded from:
%https://nl.mathworks.com/matlabcentral/fileexchange/12907-xml-io-tools/content/xml_write.m, 1-Mar-2017
%
% DESCRIPTION
% xml_write( filename, tree) Converts Matlab data structure 'tree' ... |
e1c9f156ccb98f00cc56114703dc8961a1eefbc3637d1d778dc14bddd3a9ee2e | MATLAB | 18,463 | 466 | function cf = train_logreg(param,X,clabel)
% Trains a logistic regression classifier with logF or L2
% regularization.
%
% Note: Due to the exponential term in the cost function, it is recommended
% that X (the data) is z-scored to reduce the probability of numerical
% issues due to round-off errors.
%
% Usage:
% cf... |
20ac5c5455306a0562695a1d989bc49228b7a3da3e96f3bd788b2500f8457765 | MATLAB | 18,479 | 448 | % STATUS: outdated.
% use preprocessFNIRS06_CV_GLM_ssBeta_Version02 instead
%
% SYNTAX:
% preprocessFNIRS06_CV_GLM_ssBeta(s,numClasses,rejTrOp,rejChnOp,lpFilt)
%
% DESCRIPTION:
% Cross Validation where SS beta coefficients from training fold is passed to test fold
% Perform classification using 6 different classifi... |
719c0154eafca8af448f5e7ff848832cd22c577599f49251a1dcb6f02d4334be | MATLAB | 18,502 | 345 | function [FigMS,FigSZ,statsOut] = barrierAnalysis_v2( Res, area, varargin )
% Run analyses specific to how BVCs/Border cells respond to barrier insertion.
% ANALYSIS PARAMETERS:
prms.ageBins = [16 18; 19 21; 22 25; 26 36; 40 40];
prms.bslTrial = 2; % Which baseline trial to use classify the tunin... |
a013ce75c5fba11c371ecc8bd475f6f7a6e4a67e9e372690f2ed610673001b1f | MATLAB | 18,538 | 470 | % code for making a beamformer image from regions of interest
clear all;
spm('defaults','eeg');
%% subject settings
subject = 'LN_C10';
[files, sequence, root, details] =dbs_subjects(subject, 0);
image_name = {fullfile(root,'SPMstim/evoked_R_5_i1.nii');...
fullfile(root,'SPMstim... |
994b0b8b8db960957cdf899d64333616067ca5240965cec8f32f1fd649cb8ff2 | MATLAB | 18,565 | 372 | classdef Channel < Sharedmethods
%Channel Object describing amplifier channel
% Each amplifier channel has analog outputs and analog inputs. Here, the mapping of these inputs and outputs onto the
% BNCs of the axon digidata is specified. Also contains the lists of corresponding Analogin and Analogout ob... |
b1447a780f6b7aa4f368b6e5b57202bf1e96ebd24f7abf459e846129f1102496 | MATLAB | 18,583 | 389 | % STATUS: experimental. Not for publication
%
% SYNTAX:
% preprocessFNIRS06_CV_GLM_ssBeta_MultiOnly(s,numClasses,rejTrOp,rejChnOp,...
% lpFilt)
%
% DESCRIPTION:
% Preprocess raw data (light intensities) and perform cross Validation
% where SS beta coefficients from training fold is passed to test fold.
% Perform c... |
37b3b9aff34c91dde400a61c66b53924375caf9d8e1b8d4dba777a7a13d02e2c | MATLAB | 18,587 | 473 | function [Lambda, Psi, T, stats, F] = factoran(X, m, varargin)
%FACTORAN Maximum Likelihood Common Factor Analysis.
% LAMBDA = FACTORAN(X, M) returns maximum likelihood estimates of the
% factor loadings, LAMBDA, in a common factor analysis model with M
% factors. Rows of the N-by-D data matrix X correspond to o... |
c1ddd0eef90ff0c2c84050bed58c41169d754342dd26555b0e474a24b6419589 | MATLAB | 18,791 | 533 | function [sig_out,topographies] = roi_tsss(dataset,leg)
spm('Defaults','eeg')
%MNI_roi = [40 -20 50];%
%MNI_roi = [0 -56 58]; % mni co-ordinate to act as centre of harmonic expansion
MNI_roi = [0 -46 42];%
%MNI_roi = [0 -50 40];
prefix = 'D:\home\Data\DBS-MEG\Phantom\090715\SPMstim';
inversion = 'bf';
if s... |
3b74c31c7c2438cd5f2b0fba1d0b917ad1d206d53f59ce0a24f4040427ac6bbe | MATLAB | 18,831 | 558 | classdef FileClass < matlab.mixin.Copyable
properties
% Same properties as the fields in the file struct returned
% by matlab's dir function
name
fid
date
bytes
isdir
datenum
% FileClass specific properties
namePrev
idx
... |
c5dbd74f38227db3bba5e39e806e5d2578b4e83b03e6fb068f565015f057c402 | MATLAB | 18,838 | 431 | % fighdl = plot_selected_voxels(position_index,sz,brain_data,mask_index,border_images, fighdl, cfg)
%
% This function plots a given voxelselection (e.g. searchlight, ROI), and
% can in addition show a 2d projection of an image.
%
% Example usages:
% plot_selected_voxels(position_index,sz)
% Plot currentl... |
a43d85e19fc5086f10237bb5687de798d13a0904553ec8ea1a2d8dc5fedf030a | MATLAB | 18,854 | 550 | %% Plot PC activity during VORD and cancellation
function [fH_vord, fH_canc, fH_traces, P_gain_vor_mean, P_gain_canc_mean] =...
plotVorCancSplit(I, K1, K2, K0, pop, B, S)
% Makes one complete figure for VORD, and one figure for VORC
% One for gain up, and one for gain down
%% Plotting parameters
swap_order = 1;... |
f5f6bcb24cd0456824f1dfda6566731f3fc1690850dc01bb54056a8e9fc670f4 | MATLAB | 18,900 | 453 | % STATUS: active.
%
% SYNTAX:
% preprocessFNIRS06_CV_GLM_ssBeta_Version02(s,numClasses,...
% rejTrOp,rejChnOp,lpFilt)
%
% DESCRIPTION:
% Preprocess raw data (light intensities) and perform cross validation
% where SS beta coefficients from training fold is passed to test fold.
% Perform classification using 6 diff... |
2acf8907ad6adf0e786700ca4c6bcf76c04cab7508de1881fc96f156614ea6e1 | MATLAB | 18,907 | 421 | %% Scatter plots for AFR 300s Linear model
%% load prerequisites
clear
clc
close all
%Loading prerequisites
load("D:\Brewer lab data\HFS\Temporal Analysis\No Stim\dataInfo.mat")
% load("D:\Brewer lab data\HFS\No Stim\23-Nov-2021_A\allregion_unit_matched_stim.mat")
load("D:\Brewer lab data\HFS\Temporal Analysis\No Stim... |
042ee099871cb39e1cba0f236c9605242fb275bfbbfade2711857fa8c372afc2 | MATLAB | 19,008 | 481 | % function [p,results] = decoding_statistics(cfg,results,reference)
%
% Calculates statistical results of a given analysis at the decoding level.
% For example, if decoding was done within subject, the statistics is
% returned within subject, too. If decoding was done between subject, the
% statistics reflects bet... |
3299f8a778d8ec8bf93e7bbeb2f7c13a9bd0230423ad8ea5d54cd1bcb2d1c355 | MATLAB | 19,132 | 484 | % option to re-run training and classifying or pull from saved data
% sbjList is cell array of experiment "number". Ex: sbjList = {'01','02'};
% sbjList = {'08','10','12','13','14','15'};tInd = 8;featureName = 'Cumulative Sum';numRept = 5;numClasses = 2;saveOp = 0;rerunOp = 1;
% Group channels by "islands" of probe.
f... |
b2127251d4e5fd96f8c636e99242a9680fdbab21e653c44a83c67faaef89b6b5 | MATLAB | 19,140 | 601 | %% Plot PC activity during VORD and cancellation
function [fH_vor_pop, fH_canc_pop, fH_vord, fH_canc, fH_vord_split, fH_canc_split] =...
plotCancellationPop(I, K1, K2, K0, pop, B, S)
% [fH_vor_pop, fH_canc_pop, fH_vord, fH_canc, fH_vord_split, fH_canc_split, fH_traces] =...
% plotCancellationPop(I, K1, K2, K0... |
e6ae05f4798f439c521d73ae1c1b4f82647d6c4acfeaae8d70b6d713e3fee2ec | MATLAB | 19,164 | 458 | % STATUS: active.
%
% SYNTAX:
% preprocessFNIRS06_CV_GLM_ssBeta_Parallel(s,numClasses,...
% rejTrOp,rejChnOp,lpFilt)
%
% DESCRIPTION:
% Parallel computing version of
% preprocessFNIRS06_CV_GLM_ssBeta_Version02.m
% Preprocess raw data (light intensities) and perform cross validation
% where SS beta coefficien... |
b1964a1faa6f840001ccb9c08a34b17a8d6538713e3d3fd7826328ece5f89f62 | MATLAB | 19,246 | 401 | % function [passed_data, misc, cfg] = decoding_load_data(cfg, misc, passed_data)
%
% Function to load data for decoding.m
%
% INPUT
% cfg: Struct that specifies which data should be loaded.
% Required fields:
% cfg.files.mask: 1xm cell with filename(s) of mask(s) as strings
% cfg.files.name: 1xn cell ... |
1859ad25c4e3cda1420def574e3787c30bda5b63e38e87eeabcb8b2b9480a57d | MATLAB | 19,301 | 271 | %% Aggregate together individual AQuA res files
% into a structured array called 'mydata', each condition is a field
% within mydata and rows contain individual AQuA res files & information specific
% to that recording
%
% From Aggregate_MC_ftsFilter_uncMod_MultCond_20210302.m section 1
%
% All MATLAB work... |
a36a6b9ef213223ba07b060513e8bfb9e47a2198eaa72da684aaee6474b4825f | MATLAB | 19,328 | 381 | classdef NWBfile < Sharedpaths & Sharedmethods
% NWBfile:
% This uses matlab's built in hdf5 functions to load electrophysiology data from a
% NWB file (Neurodata Without Borders, see https://neurodatawithoutborders.github.io/)
% -----------------------------------------------------------... |
4fe57229bfd59ce447f310c01352e43e4a72cf465fcc2bf7278a908a1b60f194 | MATLAB | 19,466 | 425 | %% Update 4/25/22: updated to have sliding time step
% added non uniform time scale
clear
clc
% outfolder = "D:\Brewer lab data\HFS\Temporal Analysis\40 HFS\AFR Output";
load("D:\Brewer lab data\HFS\Temporal Analysis\40 HFS\dataInfo.mat")
outfolder = "D:\Brewer lab data\HFS\Temporal Analysis\40 HFS\AFR Output Full Inde... |
e2e1f64f1714ed2f098c49b6f832d140ad387ff3beaaaa7490eaa49b9a1b614a | MATLAB | 19,468 | 512 | % code for making a beamformer image from regions of interest
clear all;
spm('defaults','eeg');
%% subject settings
subject = 'LN_C10';
[files, sequence, root, details] =dbs_subjects(subject, 0);
image_name = {fullfile(root,'SPMstim/evoked_R_5_i1.nii');...
fullfile(root,'SPMstim... |
6ff49b0e353195fcb68cd0c58a4ecf8ab13d6922ca09d515603a36f967ae2352 | MATLAB | 19,575 | 489 | % @title Main script for in silico organoid simulation
% @file sim_organoid.m
% @author Romain Beaubois
% @date 14 Jan 2021
% @copyright
% SPDX-FileCopyrightText: © 2021 Romain Beaubois <refbeaubois@yahoo.com>
% SPDX-License-Identifier: GPL-3.0-or-later
%
% @brief Main script for in silico organoid... |
3a5d833bb3fd9ea6179ea0e264cc8ccc3b46c499c33bfa9d624b14095e032708 | MATLAB | 19,638 | 334 | %Parts of figures: 3, S3B.
%2024/02/26
%% define dirs and fetch data:
root_dir=define_flicker_root_dir;
source_data=[root_dir '/stg-analyses/NatureComm2024-figures/Source Data']; %where source data for figures is stored
figures_dir=[root_dir '/stg-analyses/NatureComm2024-figures'];
all_subjects=fetch_flicker_subjectI... |
0a4e88bb11159f555f0c4513f75d9a7f5cc0a4adb6bae6257371ac6fdf4c4cc0 | MATLAB | 19,673 | 508 | % 1. Add the path of the current script to the search path
% 2. Change the current folder to "Fig7 and Supp Fig7 8 Airpuff_map plasticity\probability"
% 3. analyze the data within the folder of "Fig7 and Supp Fig7 8 Airpuff_map plasticity\probability"
% 4. Using ctrl+enter within each function to run each section
... |
a14fef95ac4fd46064896fcd55463ba93e31d43f6b114604fc3cbbc8fac49dbf | MATLAB | 19,698 | 588 | %% Field Synthesis Proof Illustration Live Script
% Supplementary Material to:
%
% *Universal Light-Sheet Generation with Field Synthesis*
%
% Bo-Jui Chang, Mark Kittisopikul, Kevin M. Dean, Phillipe Roudot, Erik Welf
% and Reto Fiolka.
%% Field Synthesis Theorem for an Ideal Line Scan
% We want to prove tha... |
3cb891c39f02e1ac6ec85bb3a7deb91263612e8c41e487af0865a8535bef231a | MATLAB | 19,723 | 375 | %
%2024/02/26
%% define dirs:
root_dir=define_flicker_root_dir;
source_data=[root_dir '/stg-analyses/NatureComm2024-figures/Source Data']; %where source data for figures is stored
figures_dir=[root_dir '/stg-analyses/NatureComm2024-figures'];
metadata_tbl=readtable([root_dir '/FlickerStudyMetadata.xlsx'],'Sheet','Su... |
65c18f9bef4e870aa936a8675719b9d6c6c1be06bdf96c1e8431aa751d24337d | MATLAB | 19,802 | 434 | %% Update 4/25/22: updated to have sliding time step
% added non uniform time scale
clear
clc
% outfolder = "D:\Brewer lab data\HFS\Temporal Analysis\40 HFS\AFR Output";
load("D:\Brewer lab data\HFS\Temporal Analysis\40 HFS\dataInfo.mat")
outfolder = "D:\Brewer lab data\HFS\Temporal Analysis\40 HFS\AFR Output Full Inde... |
c4dcd16f02364466cfe59709e29c3bdcb9fec0fc3f5624de2853ff46bc225175 | MATLAB | 19,909 | 430 | %% Update 4/25/22: updated to have sliding time step
% added non uniform time scale
clear
clc
% outfolder = "D:\Brewer lab data\HFS\Temporal Analysis\40 HFS\AFR Output";
load("D:\Brewer lab data\HFS\Temporal Analysis\40 HFS\dataInfo.mat")
outfolder = "D:\Brewer lab data\HFS\Temporal Analysis\40 HFS\AFR Output Full Inde... |
8554db8a1d42d0ce350128bcddec108b947558c075bda4f086703195d5178bf0 | MATLAB | 20,054 | 422 | function [mappedA, mapping] = compute_mapping(A, type, no_dims, varargin)
%COMPUTE_MAPPING Performs dimensionality reduction on a dataset A
%
% mappedA = compute_mapping(A, type)
% mappedA = compute_mapping(A, type, no_dims)
% mappedA = compute_mapping(A, type, no_dims, ...)
%
% Performs a technique for dimension... |
d4cecf8c2bf1018aacf834aad718ecccc0b86849ac6d04a0dc22e97e8c731aac | MATLAB | 20,055 | 754 | function Duszkiewicz2024_Figure_Stability
% This script reporoduces panels from:
% Figure 2, Extended Data Figure 2
% Dependencies:
% TStoolbox
% CircStat
%TODO: script dependencies, links to external functions
% Copyright (C) 2023 by Adrian Duszkiewicz and Adrien Peyrache
%
% This program is free software; you ca... |
50bd327e48a4ea0cf1ca738ea1ab4f2061d3f86182e0f2e4298b252bda798f57 | MATLAB | 20,198 | 475 | close all; clear; clc;
%%
Topic = 'Ai148_AAV-Grm6Cre';
BCTerminalPath = '\\storage1.ris.wustl.edu\kerschensteinerd\Active\Emily\BipolarCellTerminal\Analysis';
SpotPath = '\\storage1.ris.wustl.edu\kerschensteinerd\Active\Emily\Circle\Analysis\';
addpath('\\storage1.ris.wustl.edu\kerschensteinerd\Active\Emily\BasicF... |
913db6f15446fcaf6fab6cc01b4638a6fa71764859fca9b9975802d1f5890877 | MATLAB | 20,270 | 473 | % rtDCCA - Real-time detrended cross-correlation analysis of multiple
% time series components.
%
% Contains a custom defined class in which 'single-click' DCCC
% calculations can be performed on custom analysis scales. The
% class also contains methods to simplif... |
c777a612d9c741eb8b92a5a3e3e9be9bad6dcfe736a03d0feb9b2d82099fffc9 | MATLAB | 20,302 | 487 | function [Summary, missing] = ecodeAnalysis(cellname, celldir, destinpath, cellinfo)
%UNTITLED5 Summary of this function goes here
% Detailed explanation goes here
a=dir(celldir);
tmp=endsWith({a.name}, '.abf');
files=fullfile({a(tmp).folder},{a(tmp).name});
Summary=table;
Summary.Cellname(1) = {cellname}... |
9dd5b01a5d7e18429dbcef6f502a546d7d3bb033faf78835fbdab5013ca35539 | MATLAB | 20,354 | 521 | % 1. Add the path of the current script to the search path
% 2. Change the current folder to "Fig7 and Supp Fig7 8 Airpuff_map plasticity"
% 3. analyze the data within the folder of "Fig7 and Supp Fig7 8 Airpuff_map plasticity\probability"
% 4. Using ctrl+enter within each function to run each section
%% Section ... |
ef7201aa2a1fbcbd64966b13b12ac2d6e5ae8dfbc2be758f631d3f01084de920 | MATLAB | 20,381 | 630 | classdef ConfigFileClass < handle
properties
filenames
fids
linestr;
params;
err
end
methods
% ----------------------------------------------------
function obj = ConfigFileClass(rootdir)
obj.linestr = '';
obj... |
b59557536ecf38b6858705a2bba3fdc84a3bc3239cda84364050b9aa4efa162d | MATLAB | 20,415 | 450 | function varargout = batchviewer(varargin)
% BATCHVIEWER MATLAB code for batchviewer.fig
% BATCHVIEWER, by itself, creates a new BATCHVIEWER or raises the existing
% singleton*.
%
% H = BATCHVIEWER returns the handle to a new BATCHVIEWER or the handle to
% the existing single... |
868df09e482ed9dae29b255f67c71b89e1f719e8bcfe56155a4c156302c95814 | MATLAB | 20,453 | 496 | % This script loads all slides of one subject, compute trends
%run this script twice to correct slide alignment based on stack trned
%% Inputs
%Set to true if you would like these results to be saved to the cloud,
%false if saved locally only
isUpdateCloud = false;
subjectFolder = s3SubjectPath('21','LFM');
... |
8d6065b3b81a03e3c1e65494f2a82d9bb46d31d4ab42a37148462bc918525882 | MATLAB | 20,631 | 591 | classdef DataFilesClass < handle
properties
files;
filesErr;
filetype;
dirFormats;
err;
errmsg;
rootdir;
config;
nfiles;
logger
end
properties (Access = private)
lookupTable
end
methods
... |
bab04f20188158efb33ec31bfee7e5cce923a265f456eac8190f47ba3f3838b8 | MATLAB | 20,632 | 527 | %% No Stim
clear
clc
close all
%Loading prerequisites
load("D:\Brewer lab data\HFS\Temporal Analysis\No Stim\dataInfo.mat")
load("D:\Brewer lab data\HFS\Temporal Analysis\No Stim\full_idx_allregion_unit_matched_stim.mat")
allregion_unit_matched=convert_allregion_unit_matched_220222(allregion_unit_matched_stim);
% ful... |
9c5f7196cd71963257fbd62bcb5f3f40e0ebf9e1f523b358f45ca2f7fc25a768 | MATLAB | 20,737 | 497 | % Preprocessing level 1. This level of preprocessing includes: changing
% sampling rate, applying filters, faster, ICA, Adjust, etc.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This is an EEG data preprocessing script based on the MADE pipeline (Debnath et al., 2020).
%%%%%%%%%... |
a314b80c4ff8ac2e7a650e30ab05bf233caed5e75149cf0bbf3b1a641d25fa33 | MATLAB | 20,787 | 489 | % Goal Visualize if spike events is in an individual trials
% combine @CircleAnalysis_BipolarCellTerminal &
% @CircAnalysis_ResponseScreening072122_MorphSeg &
% @ReanalyzeVG3Circle_withoutintensitycorrection
% run CircleAnalysis_ResponseScreening072122_MorphSeg.m or
% CircleAnalysis_ResponseScreening071222_Morp... |
12c19b6ff9d80288a062386a5884230d78b2c39c143a434154c8dc005ecf0038 | MATLAB | 20,813 | 581 | function [A, b, c, params] = make_Abc_fast(signal, spatial_size, ...
region_of_interest, options)
% [A, b, c] = make_Abc_fast(signal, spatial_size, region_of_interest, options)
% or
% [A, b, c, params] = make_Abc_fast(signal, spatial_size, ...
% region_of_interest, options)
%
... |
791b867d0ff2602a3da494ea8f1efbaa6414848e7ee59d6145b5b135c620a640 | MATLAB | 20,950 | 619 | function [subj] = statmap_3dDeconvolve(subj,data_patname,regsname,selname,new_map_patname,extra_arg)
% Use AFNI's 3dDeconvolve to select features that vary
% between conditions
%
% See the TutorialAdv MVPA wiki page for more information.
%
% [SUBJ] = STATMAP_3DDECONVOLVE(SUBJ,DATA_PATNAME,REGSNAME,NEW_MAP_PATNAME,EXTR... |
27f7b87d2e40ba42709fd22b8447a5159a3ba1291ff4880b68566e21f81dd5a4 | MATLAB | 21,024 | 380 | classdef Spike2Sweep < Sharedmethods & Trace
%SWEEP A vector of continuously recorded samples
% Sweep objects are a subclass of timeseries with access to all timeseries methods. Further,
% Sweeps inherit a few methods from Sharedmethods. The default time unit is milliseconds. Note time series collecti... |
75e3f371dc1e6cea924744ed8e7ea1a526df53dac0e53e732295a71ea50c77c5 | MATLAB | 21,139 | 520 | function [tf, lthresh, uthresh, center] = isthisanoutlier(a,varargin)
% ISOUTLIER Find outliers in data
% TF = ISOUTLIER(A) returns a logical array whose elements are true when
% an outlier is detected in the corresponding element. An outlier is an
% element that is greater than 3 scaled median absolute deviati... |
6d11235fd97a72d079868703e4ce41d3c5435b02ac959c47cd018b96878988a2 | MATLAB | 21,180 | 383 | % Measuring baseline event frequencies in chosen cells/regions:
% Calculate baseline event frequency per cell/region using the res file for each tseries
% Modified from CompBLEventFrequency_XSecStatBins_MultCond_MC20230830.m
% Only written for param_name 'Number'
%
% 1. Load 'AQuA_CytoGCaMP_2Puncaging_WTCx43CBX_F... |
32ab0049a4fbcb08b4350647ed61d37ee344564fd67cb2ca6cd7ca8fa2868bda | MATLAB | 21,232 | 535 | function preprocessfmri(SubjectI, ConfigFile)
spm_path = ''; % path for spm8 or spm12
spmpreprocscript_path = ''; % path for spm tempaltes
sprintf('adding SPM path: %s\n', spm_path);
addpath(genpath(spm_path));
sprintf('adding SPM based preprocessing scripts path: %s\n', spmpreprocscript_path);
addp... |
757b0c7939ced6a8bdfd9b21ad56db7299f7cb71749d06bc354e04d9427e6cd5 | MATLAB | 21,262 | 485 | %
clear all
close all
clc
%%
% Code lines for Optical Flow Post-processing
masterImportpost='D:\Michael_Shannon\MartinezMaster\PIV_analysis_CD18only\';
masterPlotspost='D:\Michael_Shannon\MartinezMaster\PIV_analysis_CD18only_OUTPUT_relvalpoint01magval1_9-6-2022\';
% headers=[];
SHOWPLOTSANDFIGS=1;
MAKEQUIVERMOVI... |
007fe6c5b95882bfc58e39229becdb10ef78bae5acbedccb180364b7c8f63114 | MATLAB | 21,418 | 676 | clear all;
clc;
load('E1Sep_ConjPF.mat')
load('E2Sep_ConjPF.mat')
load('E1_Mix.mat')
load('rndE1_Mix.mat')
load('rndE1_Sep.mat')
load('E2_Mix.mat')
load('E1_Sep.mat')
load('E2_Sep.mat')
load('ChMatTest.mat')
E1mix_ori=E1_Mix(E1_Mix(:,7)==1,:);
E1mix_clr=E1_Mix(E1_Mix(:,7)==2,:);
E1mix_cnj=E1_Mix(E1_Mix(:... |
c232d9557f199e0271b44ce2c54d488b94740383fb299825c93425fa53a73d64 | MATLAB | 21,471 | 381 | % Parts of figures: 1D, 1F, S2, S3A.
%2024/02/26
%% define dirs and fetch data:
root_dir=define_flicker_root_dir;
source_data=[root_dir '/stg-analyses/NatureComm2024-figures/Source Data']; %where source data for figures is stored
figures_dir=[root_dir '/stg-analyses/NatureComm2024-figures']; %figures dir
if ~exist(so... |
fa0f5d3f8f93c9981f5253037bbb2a663b6b56ebea00a743b046516fd6078c94 | MATLAB | 21,636 | 528 | classdef ProbeClass < FileLoadSaveClass
properties
wavelengths
wavelengthsEmission
sourcePos2D
detectorPos2D
landmarkPos2D
landmarkPos3D
sourcePos3D
detectorPos3D
frequencies
timeDelays
timeDelayWidths
momentOrders
... |
598e23eff4095129e598cf2a188617d374b53bd84bd2995230e2dfa53f87507d | MATLAB | 22,085 | 346 | function [Res, LUT_out] = generateAllBVCResponses(ModMaps,DataIn,varargin)
% Generate and save the complete BVC response map for every dataset.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Analysis Parameters %
prms.usePCModMaps = 0;
prms.ke... |
a0d43ae973a663a186246c918a885bcbb961467855037e5ca49d0be455c7e41d | MATLAB | 22,114 | 488 | classdef OverlayPicker_exported < matlab.apps.AppBase
% Properties that correspond to app components
properties (Access = public)
OverlayPickerUIFigure matlab.ui.Figure
ThresholdEditField matlab.ui.control.NumericEditField
ThresholdEditFieldLabel matlab.ui.contr... |
47baada5b6cee42049e03c5929578ce8c834020c51eba5a78ee41cdc5306864d | MATLAB | 22,145 | 471 | %%% AUTHOR: Mitch Butler (MPB)
%%% DATE: 21 October 2021
%%% Last Mod Date: 13 November 2021
%%%
%%% PROJECT LEAD SCIENTIST: Rachael Smith
%%% PROJECT LEAD ENGINEER: Biswajit Maharathi
%%%
%%% Mod Log.
%%% -(11/13)
%%% turning this into a function to be batch-run !
%%% Rachael fo... |
e97dbbcf534153b3c354fb84721dc138d8a719f9eb4ea44727fd6d8bbb1b09f1 | MATLAB | 22,425 | 663 | %% Field Synthesis Proof Illustration Live Script
% Supplementary Material to:
%
% *Universal Light-Sheet Generation with Field Synthesis*
%
% Bo-Jui Chang, Mark Kittisopikul, Kevin M. Dean, Phillipe Roudot, Erik Welf
% and Reto Fiolka.
%% Field Synthesis Theorem for a Non-Ideal Line Scan
% We want to prove ... |
005fcba9fc1cc653b3dd42e025a0e0974761db2b2f23f5e8546262b90fc698c7 | MATLAB | 22,601 | 423 | % function [fs_index,fs_results,fs_data] = decoding_feature_selection(cfg,fs_data)
%
% This function performs feature selection of decoding data and is an
% integral part of the decoding toolbox. This function is called from
% decoding.m and should not be called directly. Currently there are two
% forms of feat... |
a8878d991ddcd9484849efd804819077963baeb7dc22f35b40b7b8fcd679ec4f | MATLAB | 22,656 | 427 |
%% retrieve all data:
%fetch all flicker sessions:
root_dir=define_flicker_root_dir;
figures_dir=[root_dir '/stg-analyses/NatureComm2024-figures'];
[~,all_sessions]=fetch_flicker_subjectIDs(root_dir,'all');
all_sessions(strcmp(all_sessions.task,'spep'),:)=[];
selected_examples=readtable([figures_dir '/NatureComm202... |
7246fb53811b0c01cd714ceffe4dd972c608c36cd6a1d15d5a95a636bf2b195c | MATLAB | 22,851 | 499 | % % multilevel regression with BSETS data
% lines calling the export_fig external function creating scatterplots are
% commented out. The may be used again if the user downloads this function.
templatedata=readtable('Multilevel raw data.xlsx'); %add the appropriate path to the xlsx file next to this code
ids=unique... |
ccc5984c5cd2d75ccd1e138907dc1b70c569bd166b3c41a8ee6a5aa3c56cbc59 | MATLAB | 22,915 | 663 | % mv_classify unit test
rng(42)
tol = 10e-10;
mf = mfilename;
% In the first part we will replicate behaviour of the other high-level
% functions (mv_classify_across_time, mv_classify_timextime) to mv_classify
% output
nsamples = 100;
nfeatures = 10;
nclasses = 2;
prop = [];
scale = 1;
do_plot = 0;
[X, clabel] = sim... |
826a82967d18a21ff9caa67d65a2986757701654123e6c2c545727534e14eecc | MATLAB | 22,967 | 876 |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Slice by slice SIM processing
%
% -edge mirroring added
% -Unmixing at native resolution, then upsampling via zero
% padding
% -throw... |
a0ec06527961894424f0fbbed920bec9af8800d59b9a2a744fd2bbedfc16905f | MATLAB | 23,042 | 443 | classdef Spike2Epoch < Sharedmethods & Trace
%EPOCH An Epoch object
% Epochs are sections of sweeps and describe the analog output signal within that section. Most common is the epoch
% "step", which means a constant current or voltage of a given amplitude was applied to the cell during this epoch.
... |
6f4a48d972c027912511762bc722042d742d9e850e71dc788b29669b311f5084 | MATLAB | 23,108 | 949 | % Arithmetic average of HRFs
% Light line color, plot ind HRFs
% Different processing for sbj 08 and 10 because they use old SD design and
% has both single and multi conditions
% new codes, ignore grpPlotHRF
function plotAllHRF_Grp_ChnCriteria_Fig4(saveOp)
goodSbjList = {'08','12','13','16','19','21','24'};
badSbjLi... |
a891871c2b0383deb876bcb656b13bd87d0515df0e2d216787dd7adbec6b3d61 | MATLAB | 23,133 | 849 | classdef Schema
%
% Class to interact with the BIDS schema
%
% USAGE::
%
% schema = bids.Schema(use_schema)
%
% use_schema: logical
%
%
% (C) Copyright 2021 BIDS-MATLAB developers
% TODO use schema to access regular expressions
properties
content
verbose = false %
is_bids_sc... |
593970c74dd35a8fee9a60eb830fd5f089bf44a4571cfeb6f9cac738b5dd50ba | MATLAB | 23,212 | 443 | classdef Epoch < Sharedmethods & Trace
%EPOCH An Epoch object
% Epochs are sections of sweeps and describe the analog output signal within that section. Most common is the epoch
% "step", which means a constant current or voltage of a given amplitude was applied to the cell during this epoch.
% ... |
424e78f2ec3f3b3d2f3b0b24af0b69d066f700313fbb03beb85eff9ef92f1490 | MATLAB | 23,342 | 613 | classdef SessClass < TreeNodeClass
properties % (Access = private)
runs;
end
methods
% ----------------------------------------------------------------------------------
function obj = SessClass(varargin)
obj@TreeNodeClass(varargin);
... |
7e626ad0fd291a680c62616a6b6ef131ed0b1ed9b7d9b9d01a0bda4085b3308b | MATLAB | 23,379 | 588 | function varargout = DFAFit(varargin)
% DFAFIT MATLAB code for DFAFit.fig
% DFAFIT, by itself, creates a new DFAFIT or raises the existing
% singleton*.
%
% H = DFAFIT returns the handle to a new DFAFIT or the handle to
% the existing singleton*.
%
% DFAFIT('CALLBACK',hObject,eventData,handles,... |
45c9924de7f65a6bb67dce35711e101cf9ab8ce79e84a422a163fc791c485963 | MATLAB | 23,400 | 856 | %% Length FF
region=["EC-DG","DG-CA3","CA3-CA1","CA1-EC"];
regLabel1ff=[];regLabel1fb=[];
set(0,'defaultAxesFontSize',16)
set(0,'defaultAxesTickLength',[0.04,0.08])
set(0,'defaultaxeslinewidth',2)
region=["EC-DG","DG-CA3","CA3-CA1","CA1-EC"];
well_regList={"EC-DG","DG-CA3","CA3-CA1","CA1-EC"};
figOrder=[1 2 4 3];
if ~e... |
f2fb8bd455cc0b0bf700c306171c20a7d1e0ab9b9f00f197f3c74e0a0266d077 | MATLAB | 23,419 | 794 | function varargout = PlotProbeGUI(varargin)
gui_Singleton = 1;
gui_State = struct('gui_Name', mfilename, ...
'gui_Singleton', gui_Singleton, ...
'gui_OpeningFcn', @PlotProbeGUI_OpeningFcn, ...
'gui_OutputFcn', @PlotProbeGUI_OutputFcn, ...
... |
1f485d7c2c89ad7f9429e7b6b8bef343cc3d3a0eff08aaf1b5847b7880abbaa9 | MATLAB | 23,519 | 832 | % Author : Andreas Seas
% Created : 22-10-28
% Edited : 22-10-28
% Descr : generate figure 3 and its subfigures
%% clear slate
close all;clear;clc
%% Inputs
CBcolor = [255, 215, 0]/255;
FMcolor = [255, 0, 0]/255;
CCcolor = [0, 0, 213/255];
% save figs?
savefigs=false;
% set up fonts
s = set... |
ddc26c46977a0e38bbc17fa081034daa205808e5e8fbdc0de1dd3ea73fdad374 | MATLAB | 23,602 | 602 | % ADVANCED CLASSIFICATION
%
% This tutorial covers more complex classification scenarios such as
% higher-dimensional data (time-frequency), searchlight analysis across
% multiple dimensions and precomputing of kernels.
%
% Contents:
% (1) Create a time-frequency dataset
% (2) Classification of 4D time-frequency data
%... |
17a8ae8077433b36a26da81b4f520e4b8ac8bc99d1b1b1794435589982247b5b | MATLAB | 23,688 | 582 | %% Make Flow Figure Images
function FlowFigureMovies(fileParams, flowFigureImageParams)
%% Start FlowFigureImages Script
fprintf('\n\n- - - Starting FlowFigureMovies - - -\n\n');
%% Import Parameters
% Input parameters
numMicrons = 10;
% File Parameters
pxPerMicron = fileParams.pxPerMicron;
secBtwFrames = fileParams... |
1c79c975c82bc95bf829ca309779d1cb355a5e0559bcd97187b92d3c8919146c | MATLAB | 23,764 | 471 | % For figure 6 in Draft 3
% 2 subplots (1,2). HbT. Show only high performing group.
% Only show LDA classifier.
% 2-class classification at left panel.
% 3-class classification at right panel.
% look at 7-color scheme for readability.
% preprocessFNIRS06_CV_GLM_ssBeta_PostVsAnt_MultiOnly
function grpPlotPerf_PostVsAnt... |
5380ce07f1d937150ae38fa3474ffdb9d7a2b086a63cd196c944965617c478a5 | MATLAB | 23,764 | 598 | % Script for fitting power law models to the avalanche data generated by
% simulation
% 1. use MLE estimate to get slope parameters for discrete distributions
% 2. use KS statistic between empirical and model distribution to determine
% x_min.
% 3. goodness of fit: using the best-fit parameters, generate simulated
% ... |
a8e1477b0f514947a6ff3026ff0ab00d0805022616759f9a9eda654b51672d93 | MATLAB | 23,773 | 441 | function [sig_cells,areasSternberg] = NWB_calcSelective_SB(nwbAll, all_units, params)
%NWB_CALCSELECTIVE Takes the output of NWB_SB_extractUnits and runs
%selectivity tests for the sternberg task. Optionally plots trial aligned
%spikes
if isfield(params,'rateFilter') && ~isempty(params.rateFilter) && params.rateFilter... |
1a8da0314121c10d52549bae6c594af7e39ed4aa31e3f6250014d41fb91a5633 | MATLAB | 23,811 | 520 | % find good subject and channel
% ISI bins: 27s, 27-30s, 30-33s, 33-36s, 36-39s, >39s
% For sbj 8 and 10
function plotHRF_ISI(sbjNum,rawDataFN,respData)
srcIdxGrp = {[1 2 3 4] [5 6] [8 9 10 11] [12 13 14 15] [16 17 18 19] [20 21] [23] [25] ...
[27 28 29] [31 32 33] [35 36] [37 38] [40] [42]};
figSaveDir = ['C:\U... |
6ac373dd9542a4bc110469c5f8e6594d4abd456a2934e5dd23905e2a6eb69573 | MATLAB | 23,814 | 905 | % Arithmetic average of HRFs
% Light line color, plot ind HRFs
% Different processing for sbj 08 and 10 because they use old SD design and
% has both single and multi conditions
% new codes, ignore grpPlotHRF
function plotAllHRF_Grp_ChnCriteria_Fig3(saveOp)
sbjList = {'08','12','13','14','15','16','19','21','22','23'... |
f64a7796a010f12c1c9238280e5efb13c730f8f661a78d850a6db106349ccded | MATLAB | 24,015 | 431 | %% Event features pre- and post-stim (area, duration and propagation)
% Fig. 1f-h: dose-response curves for various event features (avg. change in feature post-pre)
% Modified from 'DistOfEvtsPrePost_SpecTimeWindow_NoRegions_MultCond_MC_20210907.m'
% Ext. Data Fig. 1g: CDFs of event features pre- and post-stim. Modi... |
12f6bdeb480074e39b526e4b60780b38cfe0445b765a93c1245029ff74be82da | MATLAB | 24,048 | 414 | function natsortfiles_test()
% Test function for NATSORTFILES.
%
% (c) 2014-2022 Stephen Cobeldick
%
% See also NATSORTFILES TESTFUN NATSORT_TEST NATSORTROWS_TEST
fnh = @natsortfiles;
chk = testfun(fnh);
%
c2s = @(c)struct('name',cellstr(c));
rmf = @(s)rmfield(s,setdiff(fieldnames(s),'name'));
%
try pad(s... |
03cf03459d8a0a71a8ae35bd5c6a2e525327851700a503b1c26ba2484ac72a51 | MATLAB | 24,066 | 693 | function varargout = mapping_parameters(varargin)
% MAPPING_PARAMETERS M-file for mapping_parameters.fig
% MAPPING_PARAMETERS, by itself, creates a new MAPPING_PARAMETERS or raises the existing
% singleton*.
%
% H = MAPPING_PARAMETERS returns the handle to a new MAPPING_PARAMETERS or the handle to
... |
85952e50e3cffe46672b579acbd9d459d74ec50887d36a0632f3148d1bed0541 | MATLAB | 24,085 | 620 | % STATUS: analysis. For internal report.
%
% SYNTAX:
% plotAllHRF(sbjNum,opCI,opTTest,opSave)
%
% DESCRIPTION:
% Plot hemodynamic response functions for each condition and choromophore
% for all channels.
% Figure legend:
% 1) If line is bold, then that condition is statistically
% significant with th... |
acb29d001afe3e1f765b65aa7921fec36deffe467fc01a37bc10bc4c04d26e53 | MATLAB | 24,165 | 617 | %% ISI comparison bar graphs and anova
clear
clc
load('D:\Brewer lab data\HFS\No Stim\02-Oct-2022_A\spike_burst_dyn_table_stim.mat') %5 SD
nostim_table=spike_burst_dyn_table_stim;
load('D:\Brewer lab data\HFS\Theta Stim\27-Sep-2022_A\spike_burst_dyn_table_stim.mat') % 5SD
hfs5_table=spike_burst_dyn_table_stim;
... |
7aa15e3bdd2ceb4a59ae56a90ed3c7a373a37c8f428bc3d87d2b72052127488c | MATLAB | 24,188 | 431 | function st = generateStatusReportByLibrary(libraryNames)
% Go over all subjects in library(by library name) and returns status per
% slide. Sorted by subject name.
%
% INPUTS:
% libraryNames - can be a string or a cell containing library names.
% Examples: 'LA' or {'LA','LB'}
% OUTPUTS:
% st - secti... |
679e8899f2de1d775b8496747436941cf622c6d6f53c359faed268457d639c38 | MATLAB | 24,240 | 603 | %% spnb comparison bar graphs and anova
clear
clc
ff_colors=["#3869EE","#FF2303","#EE9B00"];
fb_colors=["#4fb7ff","#FF9B9B","#FFDA49"];
%% Feedforward
nostim=load('no_stim_ff_ancova_vars_spnb.mat');
theta=load('theta_stim_ff_ancova_vars_spnb.mat');
hfs=load('HFS_ff_ancova_vars_spnb.mat');
subregions_ff=... |
eb51b535521a56d33dcbaefcf4f5d5ef66f93daa7efe7535b3d20b9c37254a30 | MATLAB | 24,321 | 569 | function identification_step(data,neurons_cleaned,outputpath,voxel_size)
% vanno passati gli argomenti del grafico
disp('Starting')
% insert axes
% automatic identity
% apdvlr axes
addpath('./Functions/');
% variables initialization
if nargin < 4
voxel_size = [0.267 0.267 2];
end
zratio = voxel_s... |
1a73d0aad7efc4459237fb570bf2eb03ac915b44217fdcc85d5790e4442518de | MATLAB | 24,333 | 986 | % Plot average p-val for each channel, and number of sbjs with p-val below
% critical value.
% Light line color, plot ind HRFs
% Different processing for sbj 08 and 10 because they use old SD design and
% has both single and multi conditions
% new codes, ignore grpPlotHRF
% Channel numbers include SS.
%
% Finalized cha... |
2d00a9a0c82c181d3119a16e8c7924036d212895c550578955442b1edce912e3 | MATLAB | 24,455 | 992 | % Plot average p-val for each channel, and number of sbjs with p-val below
% critical value.
% Light line color, plot ind HRFs
% Different processing for sbj 08 and 10 because they use old SD design and
% has both single and multi conditions
% new codes, ignore grpPlotHRF
% Channel numbers include SS.
% FEF 5, 18
% sPS... |
1b2b7b2fcc19d38f225b1e9769ff33e0d8c41dc51723df38d31941da5ed0abe3 | MATLAB | 24,531 | 716 | % 1. Add the path of the current script to the search path
% 2. Change the current folder to "Fig6 and Supp Fig6 Airpuff_stimulus dependence"
% 3. analyze the data within the folder of "Fig6 and Supp Fig6 Airpuff_stimulus dependence"
% 4. Using ctrl+enter within each function to run each section
%% Section 1: O... |
5b822e1e7e62273319234fb8e3866968cbf9e0eeff4ed4d36ed22d89653677b4 | MATLAB | 24,824 | 680 | function [T, params] = make_tensors_fast(signal, spatial_size, ...
region_of_interest, options)
% T = MAKE_TENSORS_FAST(SIGNAL, SPATIAL_SIZE, REGION_OF_INTEREST, OPTIONS)
% or
% [T,PARAMS]=MAKE_TENSORS_FAST(SIGNAL,SPATIAL_SIZE,REGION_OF_INTEREST,OPTIONS)
%
% Compute orientation tensors in up to four dimensions. ... |
0531ef8a1530b409e7fbc3cf21d559f9d7ee65e9d92f0ac054841a952c9ea8a9 | MATLAB | 24,890 | 556 | % statcond() - compare two or more data conditions statistically using
% standard parametric or nonparametric permutation-based ANOVA
% (1-way or 2-way) or t-test methods. Parametric testing uses
% fcdf() from the Matlab Statistical Toolbox.
% Usage:
% >> [stats, d... |
4e74e0715ef7b919bca6064e1f6194c0ed9d39f1551d2afa951023331ca090e3 | MATLAB | 25,176 | 345 | function run_jsonlab_test(tests)
%
% run_jsonlab_test
% or
% run_jsonlab_test(tests)
% run_jsonlab_test({'js','jso','bj','bjo'})
%
% Unit testing for JSONLab JSON, BJData/UBJSON encoders and decoders
%
% authors:Qianqian Fang (q.fang <at> neu.edu)
% date: 2020/06/08
%
% input:
% tests: is a cell array of strings... |
20d256eac8e6cf5b9537dc8207391b56df1c5a3a6cc163626749ad1cc78056d2 | MATLAB | 25,219 | 672 | % STATUS: analysis. For internal report.
%
% SYNTAX:
% plotAllHRF_Special(sbjNum,opCI,opTTest,opSave)
%
% DESCRIPTION:
% Plot hemodynamic response functions for each condition and choromophore
% for all channels.
% Figure legend:
% 1) If line is bold, then that condition is statistically
% significant... |
b34b4581ce27436093b5b002cdf1d1aba9c36061f2eaa7f42f68c9d8b4f8fb6a | MATLAB | 25,222 | 520 | function [areas,total_bins,overlap_bins, total_area, overlap_area]=...
ISI_interunit_peak_finding_211108...
(spon,stim,spon_dir,stim_dir,times_struct_spon,times_struct_stim,spon_duration,...
stim_duration,parent_dir,if_cw)
% Testing peak finding capabilities across multiple units for elimination
% of zeros
... |
7767a3dafc5a77cbe8ec86e24f7added6806cb2475616dd5ccb10f0eedf8a1b8 | MATLAB | 25,242 | 519 | classdef TransformParameterEditor_exported < matlab.apps.AppBase
% Properties that correspond to app components
properties (Access = public)
TransformParameterEditorUIFigure matlab.ui.Figure
InPlaneOnlyCheckBox matlab.ui.control.CheckBox
CancelButton matlab... |
204f1db1182a05eed2a2a3e865c811727daffb00ab65465be751b0c421bcc20f | MATLAB | 25,266 | 754 | classdef StimClass < FileLoadSaveClass
properties
name
data
dataLabels
states % Stim marks enabled/disabled. Not part of SNIRF
end
% Properties not part of the SNIRF spec. These parameters aren't loaded or saved to files
properties (Access = private)
err... |
94d8ecee67366acbe6e18fc8960e766c418a5f6f25b73151728c7fee3e122093 | MATLAB | 25,285 | 785 | function [r, cout] = polyexp(signal, certainty, basis, ...
spatial_size, sigma, options)
% R = POLYEXP(SIGNAL, CERTAINTY, BASIS, SPATIAL_SIZE, SIGMA, OPTIONS)
% or
% [R COUT] = POLYEXP(SIGNAL, CERTAINTY, BASIS, SPATIAL_SIZE, SIGMA, OPTIONS)
%
% Compute polynomial expansion in up to four dimensions. The expansi... |
15e1021d5565e09654d34d819dfb158f4f9430c367374fc915a133c6291bf0ba | MATLAB | 25,389 | 475 | classdef Sweep < Sharedmethods & Trace
%SWEEP A vector of continuously recorded samples
% Sweep objects are a subclass of timeseries with access to all timeseries methods. Further,
% Sweeps inherit a few methods from Sharedmethods. The default time unit is milliseconds. Note time series collections
... |
f61d7b6ea34f3c6e6bdf1a32a5e303c4d7aa433f6d4296d2bedfcab31799857e | MATLAB | 25,474 | 475 | classdef Sweep < Sharedmethods & Trace
%SWEEP A vector of continuously recorded samples
% Sweep objects are a subclass of timeseries with access to all timeseries methods. Further,
% Sweeps inherit a few methods from Sharedmethods. The default time unit is milliseconds. Note time series collections
... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.