sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
e5a6bcef1cc464b28edd9d6df6402559aa2a5a26dc16cc17862b0bbb6c35ed89 | MATLAB | 8,343 | 270 | %% get data from multiple pData files
% delays in sec, neg delay is ephys b/f behavior
tDelay = [-0.5 -0.2 -0.1 -0.05 -0.025 0 0.025 0.05 0.1 0.2 0.5];
% user selects pData files
% prompt user to select pData files
[pDataFNames, pDataPath] = uigetfile('*.mat', 'Select pData files', ...
pDataDir(), 'MultiSelect'... |
a07343c75c5156dc224973f986e86ca374600558b7edfe1aa5682f7ce4ff9046 | MATLAB | 8,344 | 272 | function [seqs,params] = check_suspicious_sequences(dataperfly,annname,seqs,varargin)
[MINERRJUMPFRAC,CLOSELENGTH,MINORIENTCHANGE,MAXMAJORFRAC,MINWALKVEL,MATCHERRCLOSE,...
MINANGLEDIFF] = ...
myparse(varargin,'minerrjumpfrac',.2,'closelength',20,'minorientchange',pi/4,...
'maxmajorfac',2,'minwalkvel',1,'matcherr... |
3e6323f20d4e37de01f39ba2de2ac54df97836ea2f4f4656c53850c312867134 | MATLAB | 8,357 | 254 | % braincircuitsIO_DNa02DNg13_inputs.m
%
% Script for reading in spreadsheets of DNa02 and DNg13 brain inputs (from
% edited version of braincircuits.io output, with column listing category)
% Returns number of shared inputs for cells on left and right side
% Plots bar plots of categories of inputs, both as number of c... |
f5a44ab14a75344d9d72d546bb6c617000fd3dcbe63339b74b67aec77c693150 | MATLAB | 8,365 | 237 | % Function File: filter1
%
% Usage: YF = filter1 (Y, t, HPF, LPF, method)
%
% OR: filter1 (filename, ending, HPF, LPF, method, '-file')
%
% This function combines high- and/or low-pass 1-D filtering at the
% set -3 dB cut-off frequencies, which are defined in the parameters
% HPF and ... |
fd410485841200a34390c0a2a65e2bc399566b84296ffa04979028ecbdc6db11 | MATLAB | 8,366 | 127 | %
% Colors used for drawing various graphs consistently.
%
% RESULT
% colors Struct by submethod
% .(submethod) (1*3) Color
% line_styles Struct by submethod
% .(submethod) (string) line style
% markers Struct by submethod
% .(submethod) (string) marker
%
function [colors line_styles markers] = styles_subme... |
40f4bccfa844b74a58e4ba7976783fbc7745b27ad088f52d4edf118cc083ca70 | MATLAB | 8,367 | 157 | % In this script we will pull in all the regions of the atlas
%clear all
%clc
% Load in Data
%load('M:\Matt Chilvers\Documents\PhD\Project3_WhiteMatterLesion\DataStructure\Subject_Data_UnilateralOnly.mat')
load('M:\Matt Chilvers\Documents\PhD\Project3_WhiteMatterLesion\DataStructure\SubjectsRemoved_Data_Sept7.... |
7597b6d9204adff3a9b9708411bd8f25ec140af4dbcda176a5bef1bb87502c35 | MATLAB | 8,368 | 188 | classdef ImageSeries < types.core.TimeSeries & types.untyped.GroupClass
% IMAGESERIES General image data that is common between acquisition and stimulus time series. Sometimes the image data is stored in the file in a raw format while other times it will be stored as a series of external image files in the host file sy... |
01a27891b05b9c17f10c08be3a5b45537e093bb5df19b81cc86e465028175dd3 | MATLAB | 8,369 | 171 | % EYE TRACKING DATA INTERPRETATION
%% ________________________________
% This script collects information about gaze data and area's of interest
% for specific tasks recorded with a Tobii eyetracker device. An
% I2MC-filter is used to find the fixations is noisy data.
%% OPTIONS
%% Screen options
opt.xres = 1... |
e701778f403b12aa7f505fc00fc66ec792cef061d5cc55146e58bc73c512b297 | MATLAB | 8,369 | 238 | function factor = scalingfactor(old, new)
% SCALINGFACTOR determines the scaling factor from old to new units.
%
% Use as
% factor = scalingfactor(old, new)
% where old and new are strings that specify the units.
%
% For example
% scalingfactor('m', 'cm') % returns 100
% scalingfactor('V', 'uV') ... |
2b7204199a3f0a827a1acbd261a7e3460ba58a621446b41ca699765dae95fe74 | MATLAB | 8,370 | 176 | function displayPairingStatistics(cnmf,pcaica,suite2p,est,varargin)
if nargin > 4
somaList = varargin{1};
end
sL = false(size(est.corrvals));
sL(somaList) = true;
clc
size(sL)
size(est.corrvals)
estCV1 = (est.corrvals>0.1)&sL;
estCV3 = (est.corrvals>0.3)&sL;
estCV5 = (est.corrvals>0.5)&sL;
estCVP1 ... |
5934f150dc66489bf3c67ad3ae15e3388824195991bcf1341d29c1c9910818a5 | MATLAB | 8,370 | 202 | %frequency analysis and TFRs
clear;clc;
%% Load clean MEG file
% data_folder='/rds/projects/j/jenseno-avtemporal-attention/Load/MEG Data/proc_data/'; %Portal
% addpath /rds/projects/j/jenseno-avtemporal-attention/MATLAB/fieldtrip-20200320 %Portal
% load '/rds/projects/j/jenseno-avtemporal-attention/MATLAB/Perceptual Lo... |
683670ec3c9ed54de3f44bb8ec6c495ad41c3fb46805c85c0905e6d427cd6fa0 | MATLAB | 8,372 | 230 | % [results] = figure2(data_dir, id, item_or_loc, spiketable)
%
% this function will plot one of the 4 panels as seen in figure 2
%
% INPUTS:
% data_dir (str): path to source data
% id (int): row number within spiketable of unit to plot
% img_or_pos (int): 1: plot image response, 2: plot location res... |
697e43bfffdf5a9d7ee30edcb4c839754ca51a25d16284accd4ac65bc83e0992 | MATLAB | 8,375 | 178 | function TDMS_retrievingSubsets
%TDMS_retrievingSubsets Documentation for retrieving subsets of raw data from TDMS_readTDMSFile
%
% I created this file as a place to document retrieval of subsets of
% data, instead of making the documentation in the main function rather
% long. All property/value pairs would st... |
966f5b1eeb1b7d364597c82147ebea5159eb6d66b51a2dac2a254b5e75cadf05 | MATLAB | 8,377 | 196 | function [] = CBIG_gwMRF_check_unit_test_result(output_dir)
% [] = CBIG_gwMRF_check_unit_test_result(output_dir)
%
% This function compares the output of unit test with the ref output
% on our HPC server to make sure the codes work fine.
%
% '[FAILED]' message indicates something wrong with the codes, the
% unit test ... |
f0ad19d04e6888a6876285bb43ccfb096a186ffb7d30c95d0633aeb92b4c4802 | MATLAB | 8,399 | 190 | function [hc] = read_ctf_hc(filename)
% READ_CTF_HC reads the MEG headcoil marker positions from an ascii file
% and computes the coordinate transformation required to get from from
% dewar to head-coordinates
%
% the definition of head coordinates is according to CTF standard:
% - the origin is exactly between LPA an... |
3aa32f20d8db2c4dc132f010bccc1b13cbc0a81ad78bb5379099403681f65b03 | MATLAB | 8,403 | 309 | function [] = ExtDataFig07_Example_AveSong()
% Code for plotting images for the example recordings in Extended Data Fig. 7b,d,g,i.
GT = 'fruD'; % Extended Data Fig. 7b
% GT = 'fru'; % Extended Data Fig. 7d
% GT = 'nsybDnonfru'; % Extended Data Fig. 7g
% GT = 'nsybnonfru'; % Extended Data Fig. 7i
switch GT
case 'f... |
712641c3eae1bb36b246e931283e373b2a88298156f01bf3ae0e8cdce981c0bc | MATLAB | 8,406 | 186 |
function [Spikes,LFP,Theta,Nose,Fs]=getSpikes(File);
%
%Session_str, e.g.,'20150906Thalamus36\20150906Thalamus36_1to...'
%
%Spikes{Nelecs,Nunits}, cell holding spike times in ms from SessionStart
%LFP{Nchannels}, cell, holds LFP data in XXX units. Filtered (1,50)
%Theta[.L;.R], struct holding theta of Left and ... |
9b035e2a755d604a71252109c9349466673c2e5a587d8f62e2913d4398ac0b85 | MATLAB | 8,406 | 221 | %% Script for finding relationships between vasculature and hypoxic pockets in the mouse barrel cortex
% Uses the output of OxygenDynamics_Master analysis script and annotated
% png images for arteries and veins
% Run the script on the masterfolder that contains all the recordings.
% In the masterfolder have ... |
7d30772bc540c2fa16687689df9ab9f4f5666f191a1b3086aac3f9a8cce38541 | MATLAB | 8,418 | 232 | % plotOptoLegStepParam_allFlies.m
%
% Function that takes output files from extractLegStepParamsOpto_fly() and
% generates a plot of the specified legStep param for each leg. Plots
% mean +/- SEM for each fly as well as across flies. Different conditions
% in different columns. Points from the same fly are connect... |
89a22bc7aa5fafb1033e8646c5d5f44a0d89fd2edbb9db8000bfb266e965ddac | MATLAB | 8,419 | 237 | rootdir = '/groups/branson/home/bransonk/behavioranalysis/code/SSRNN/SSRNN';
rootbowldir = '/nearline/branson/bowl_data';
addpath(genpath('.'));
addpath(fullfile(rootdir,'Code'));
%GAL4linestr = 'GMR_71G01_AE_01_TrpA';
%GAL4linestr = 'pBDPGAL4U_TrpA';
%GAL4linestr = 'GMR_91B01_AE_01_TrpA';
GAL4linestr = 'GMR_26E01_AE... |
bf4dcea6c35f89db7aba943ebdf73b6ba470ff97d2ffdd8afecff7f56c5bc5f1 | MATLAB | 8,422 | 275 | function VOR_Summary_Amin_Gen(measure, excel_file, norm )
%{
Required
measure: Data to make into summary graph. Found in the excel file
optional
excel_file: location of the excel file. Default is current folder.
norm: '1' normalize data. '0' use raw values. Default is raw values.
%}
%% Prep Variables
if ~e... |
d0b02e1484008e9908275880ae6fda894b2247ddd2d50f9d691809c4e05679f7 | MATLAB | 8,434 | 203 | % ephysSettings.m
%
% Function that returns all the CONSTANTS for an electrophysiology
% experiment
%
% Modification of twoPhotonSettings.m, which is modification of
% ephysSettings.m from Yvette
%
% OUTPUT:
% dataDir - name of base data directory
% exptFnDir - name of folder containing all experiment functions
%... |
1cd6d0b623386bec7f644d4d13e525428fa06779d5cd51786af2c05b5d038d32 | MATLAB | 8,448 | 231 | close all
clear all
clc
USE_REAL_BEHAVIOUR_DATA = false;
% Settings
video_width_px = 720;
video_height_px = 480;
arena_width_cm = 20;
arena_height_cm = 30;
prob_180_rots = 0.5; % This should be between 0 and 1.
show_field = 0;
numSimCells = 20;
fs = 32000; % sampling rate of neural recordings
noise_rate_hz = 0.5; % A... |
28b2e455f1a3a7d2b4b4457b50ae41579ba18f44b4731577e2fc67dbf5c0662c | MATLAB | 8,458 | 170 | function [neur_ves,vasc_params,neur_ves_all] = simulatebloodvessels(vol_params,vasc_params)
% [neur_ves,vasc_params] = simulatebloodvessels(vol_params,vasc_params)
%
% Function to simulate vasculature in and above a neural volume. The inputs
% to this function are:
% - vol_params - Struct with parameters for th... |
8fbdc0ca3bb3c12f0f0d92629ebadb9f08910f9c1f8be36b57d91cb874b3b7f5 | MATLAB | 8,458 | 235 | function [] = ExtDataFig05_OptStim_TuningCurve_Neuron()
% Code for plotting the tuning curves of calcium signals of each neuron induced by optogenetics in Extended Data Fig. 5d.
GT = 'TN1dsx';
%% parameters
nTrials = 6;
nStim = 6;
T = 1370; % T
Thre_nTrialOpto = 1;
PreEventImg = 72; % 10 s (71.0443)
OneTrialDur = 2... |
c11ef997f7d9c355da1f385f7ce9ee2c2d45f17cc8dc6d31996e22b848a04f3a | MATLAB | 8,470 | 252 | %-------------------------------------------------------------------------------------
% latencymap.m
% Plots latency maps (onset differences) in 3D brain and produces similarity plots
%
% Requires
% - files: ico5_pial_surf_lh.mat, parcels.csv, so_*folder*.mat (for each folder)
% - functions: mysavefig() (optional, f... |
9ca22d563c72f629d5e0e6042c88cdfd90aadb17b2487abb0b74d2764cf22d78 | MATLAB | 8,471 | 236 | % plotOptomotorOptoLegStepParam_allFlies.m
%
% Function that takes output files from
% extractOptomotorLegStepParamsOptoCond_fly() and generates a plot of the
% specified legStep param for each leg. Plots mean +/- SEM for each fly as
% well as across flies. Different conditions in different columns. Points
% fr... |
b63ccc76fea51ccd5debf52c8c62b80b0abad0ef04f29428a0de5d0f255243ff | MATLAB | 8,478 | 219 | % modified from showmap
% shows only modp2p for cases with Ree > Th_Ree & ReeP < Th_ReeP
% run:
% a loop over Sessions (SesList = {'ses1';'ses2';,...})
% a loop over varaibles (VarList = {'var1';'var2';,...})
% analyze Nmeasures (MeasureList = {'Ree';modp2p}
% For each Session save an array of size: [NVarList,N... |
3a42f2d68be725a25e6ce96e4fe123dfa2ecec905927ccaeef2e7fa30aabeee8 | MATLAB | 8,500 | 200 | %function update_unitsTable(Sesname, elec,unit,field, val)
clear all; close all;
globals; initglobals;
DATA_TYPE = 'OF';
%DATA_TYPE = 'EM';
FigType = 'final';
FigType = 'data';
SHOW_TUNINGS = 'all'; % 'sig', 'all'
INCLUDE_UNITS = 'W'; %'W', 'W+nW', 'nW'
an_baseFig = 100;
%globals;
% unitsTableFilename = [... |
fe197ff1b43f2f5492c8d5b846fece10f0d386d54a1fcd5c52ea087e3de57c93 | MATLAB | 8,510 | 217 | %% MAIN function to generate the Spike Time Histogram, STH (Figure 9)
clear all
clc
[filename, pathname, filterindex] = uigetfile('*.mat', 'Select NetworkBurst file');
if isempty(strfind(filename,'NetworkBurstDetection'))
errordlg('Selection Failed - End of Session', 'Error');
return
end
cd(pathname);
load(fil... |
465e70a74e133e4b5bfba2855c56a34251f9b826af10623ac42d9fc23e0ac791 | MATLAB | 8,514 | 264 | function [grad, elec] = mne2grad(hdr, dewar)
% MNE2GRAD creates gradiometer definition for FIFF dataset
%
% Use as
% [grad, elec] = mne2grad(hdr, dewar)
%
% The optional second argument is a boolean that can be used to return the sensors
% in dewar coordinates (default is head coordinates)
%
% See also CTF2GRAD, BTI... |
edccef2d5aa4368535023dbb5535d6885d4fc588241376955adc521bfb413032 | MATLAB | 8,521 | 153 | %% This script re-applies UFARSA (with different detection parameters)
% on *_events.mat files generated by a previous execution of CATHARSiS
% ("Calcium transient detection harnessing spatial similarity").
% ----------------------------------------------------------------------
% Reference:
% Jürgen Graf, Vahid R... |
8571a4c20d6e6dfb41f216e3d6b013d811bc1d8ca668ff7a5197db589f51e760 | MATLAB | 8,530 | 204 | %This function opens the file created by ExampleCreateFile and reads the marker channels using random marker masks and then copies the masked channels to a new file
% clear workspace
clear;
% add path to CED code
if isempty(getenv('CEDS64ML'))
setenv('CEDS64ML', 'C:\path\to\your\folder\CEDS64ML');
end
cedpath = ge... |
4f8ad225921b817aa134a57f39bb02c7ec7d848861adcc2a3bd7919942546f3e | MATLAB | 8,548 | 242 | function varargout=spm_platform(varargin)
% Platform specific configuration parameters for SPM
%
% FORMAT ans = spm_platform(arg)
% arg - optional string argument, can be
% - 'bigend' - return whether this architecture is bigendian
% - 0 - is little endian
% - 1 - ... |
dbfa5aef3ec9cee769ce528abfba43b712bd57a3017c82274bb30cf735f10f65 | MATLAB | 8,549 | 187 | %% Comments
% intended for analysis of 2PLSM data from the AOD 2PLSM
%% Clean-up
close all;
warning('off', 'MATLAB:print:FigureTooLargeForPage')
%% Specify parameters
% Options.directory = '\\folder\';
Options.directory_lengthFOVid = 16; % number of characters specifying date/animal/FOV in Options.directory
Opt... |
ecc36d2c10fa22e12b851ae21efea44fcbb5dca4bce329f1c67fcafcc309445f | MATLAB | 8,552 | 178 | function TDMS_retrievingSubsets
%TDMS_retrievingSubsets Documentation for retrieving subsets of raw data from TDMS_readTDMSFile
%
% I created this file as a place to document retrieval of subsets of
% data, instead of making the documentation in the main function rather
% long. All property/value pairs wou... |
ae6b2a24707649a316ab00e4e967358c2d973e9e99289165ef52da6e94dedb76 | MATLAB | 8,562 | 232 | function exportFieldtrip( obj )
% EXPORTFIELDTRIP Exports streaming data to .mat file that is readable by
% the fieldtrip toolbox.
%
% NOTE: To export everything in the same file, we opted to consider all
% used channels. This means that if a channel is only used in one of the
% recordings, it will still be present in ... |
cbb18ecc640f4490edaf0b2afc1804acbff90ad0564c0c64be647829a911d796 | MATLAB | 8,564 | 276 | function [M_V] = vox2ras_dfmeas(str_filename, varargin)
%%
%% NAME
%%
%% vox2ras_dfmeas.m (vox2ras_d{etermine}f{rom}meas)
%%
%% AUTHOR
%%
%% Rudolph Pienaar
%%
%% VERSION
%%
%% $Id: vox2ras_dfmeas.m 8776 2013-11-14 09:04:48Z roboos $
%%
%% SYNOPSIS
%%
%% [M_V] = vox2ras_dfmeas(str_filename, ch_override, ...
%... |
dac5811bb0e5fd832ffbc5bd270aefb86efc7ba5b620fd224e686c02b119d1de | MATLAB | 8,564 | 201 | %This script allows the user to pick a watershed region in a t-SNE map and
%finds when the animal stays in that region and plots their behaivor, not used in paper
%% STEP 1: establish plotting constants
N_rows = 4;
N_columns = 4;
N = N_rows*N_columns;
fps = 14;
frames_before = 1.5*fps-1;
frames_after = 1.5*fps;
dura... |
5d559d61166a401ecac797e5aa58b5506630428bf3addeb70e058b2110502d78 | MATLAB | 8,569 | 296 | % fig2_shuf_illustrate.m
% generates figure 2 using stored values used for manuscript
%%
clear all;
close all;
clc;
%% addpath if not added yet
% assumes script run within local directory
scriptdirs = {'../../plot';'../../helper_functions'};
addpath(scriptdirs{:})
datadir = pwd;
datafile = 'figs_2_3_shuf_res_illustrat... |
994df0339db5b03c482e550143b50ba58937ba1e696918f59ab4361976182f97 | MATLAB | 8,572 | 233 | function [strout,R2] = spm_str_manip(strin,options)
% miscellaneous string manipulation options
% FORMAT string_out = spm_str_manip(string_in,options)
% string_in - input string, string matrix, or cell array of strings
% string_out - output sring, string matrix, or cell array of strings
% options - a string of opti... |
a022258b803ac8d0e646b0f7adae943c344c9330bc5dccdeace9c47fd2c56857 | MATLAB | 8,578 | 217 | function [minimum,fval] = anneal(loss, parent, options)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% If you use this code, then please cite:
% Kirkpatrick, S., Gelatt, C.D., & Vecchi, M.P. (1983). Optimization by
% Simulated Annealing. _Science, 220_, 671-680.
% joachim.vandekerckhove@psy... |
5a64df976334c20acfa2b53a7824d4de1fc216287fb1ae7e331e9a86c7f2e356 | MATLAB | 8,583 | 275 | function [pks,locs] = findpeaksIBEI(X,varargin)
%FINDPEAKS Find local peaks in data
% PKS = FINDPEAKS(X) finds local peaks in data set X where is a
% vector
%
% [PKS,LOCS]= FINDPEAKS(X) also returns the indices LOCS at which the
% peaks occur.
%
% [...] = FINDPEAKS(X,'MINPEAKHEIGHT',MPH) finds only those peak... |
459f1aa7d8fb9ef5bd421fd36117413722713db64eab68ffa9d753ef8d3220ac | MATLAB | 8,588 | 231 | function [data] = tdmsreader(tdmsfilename, channel, datalen)
% Decode TDMS file, which is saved as DAQmx raw data format for PXIe-6368.
% Syntax:
% [data, rawdata] = TDMSREADER(tdmsfilename, channel, datalen)
% tdmsfilename: the name of tdms file
% channel: channel number
% datalen:
% if datalen is s... |
89805b52cf3a8db8284ee7f13e235c2f4151a5108d1dab326151796e36a89fac | MATLAB | 8,590 | 270 | % script that prompts user for mat, annotation, and movie files, parameters
% for computing suspicious frames, then computes suspicious frames, then
% brings up the labelerrors gui
%% set all defaults
moviename = '';
moviepath = '';
setuppath;
%% read last settings
pathtolabelerrors = which('labelerrors');
savedsett... |
2dfef87fe83abebbed798495f378a22948fc42f64f21ce54b263cd9aea96fbec | MATLAB | 8,595 | 252 | % plotOpto_AEPPEP_allFlies.m
%
% Function that takes output from extractLegStepParamsOpto_fly() and
% plots the AEP/PEP in the XY plane, either as the actual values or as the
% difference from the no stimulation condition
% Has option to plot mean across flies (X) and/or mean for each individual
% fly (dot).
% Sele... |
37dfce943885fa659338756487fe563bc23ccb989a1f6679a3b33eca743fc8c4 | MATLAB | 8,603 | 250 | % plotOptomotorOpto_DiffAEPPEP_allFlies.m
%
% Function that takes output from
% extractOptomotorLegStepParamsOptoCond_fly() and plots the AEP/PEP in the
% XY plane, as the difference between steps from 2 different time periods
% (different output files, matched by name).
% Has option to plot mean across flies (X) a... |
3a4fa4a10967885e97030c3e04e8b8caba024c9dc684fe89f268a91e915fd978 | MATLAB | 8,607 | 273 | %% creating two ERSP plots for the paper
% one plot will show an ERSP spectrogram for one specific participant
% (Subject 1) and the other one will show it for all participants
%% to restart everything
% % do not run when running it automatically
clear variables
close all;
clc;
%% Load necessary code
% paths to st... |
fd075ddc476dab8afd926a92942785532eedde327ad9da82439e0b5d789de812 | MATLAB | 8,610 | 274 | % Script to produce figure 4
clearvars; clc;
addpath('cli_and_cil')
load('cli_cil_heatmap.mat')
load("colour.mat")
load('rainbow_cmap.mat')
% Hopf curves
load('HB1.dat')
load('HB2.dat')
load('HB3.dat')
% limit points
load('LP1v1.dat')
% homoclinic bifurcation
load('HOM1.dat')
load('HOM2.dat')
load... |
5b68f5f36dba96b48599891c589655a12fa916ddd988efc54760613e2fbcb28a | MATLAB | 8,619 | 203 | % fixStairInitTask.m
%
% $Id$
% usage: [fixTask myscreen] = fixStairInitTask(myscreen)
% by: justin gardner
% date: 09/07/06
% copyright: (c) 2006 Justin Gardner (GPL see mgl/COPYING)
% purpose: Implements a fixation task. In this task, the fixation cross
% starts out cyan and ... |
27213a9b0817d0851f5dd61697848f4a1dbe2e600d8f123f7f06e508db1c16f7 | MATLAB | 8,628 | 191 | clc;
%Recreate needed property constants defined in nilibddc_m.h
DDC_FILE_NAME = 'name';
DDC_FILE_DESCRIPTION = 'description';
DDC_FILE_TITLE = 'title';
DDC_FILE_AUTHOR = 'author';
DDC_FILE_DATETIME = 'datetime';
DDC_CHANNELGROUP_NAME = 'name';
DDC_CHANNELGROUP_DESCRIPTION = 'description';
... |
57c4585bb0b0286e9e1aec6989a08657402ee31879c3adcecc49639d5ea4359a | MATLAB | 8,628 | 242 | % f_findHFOxSTF.m [As a part of HFO Detection Project]
% Written by:
% Miguel G. Navarrete Mejia
% Electrical Engineering MS candidate
% UNIVERSIDAD DE LOS ANDES
% Colombia, 2012
% mnavarretem@gmail.com
function m_HFOEvents = f_findHFOxSTE(pstr_SignalPath,ps_SignalIdx,st_DatA,...
... |
988764a55c82750790162015446df7f4c8737af2fca198f5bc129445cb07c25f | MATLAB | 8,628 | 191 | clc;
%Recreate needed property constants defined in nilibddc_m.h
DDC_FILE_NAME = 'name';
DDC_FILE_DESCRIPTION = 'description';
DDC_FILE_TITLE = 'title';
DDC_FILE_AUTHOR = 'author';
DDC_FILE_DATETIME = 'datetime';
DDC_CHANNELGROUP_NAME = 'name';
DDC_CHANNELGROUP_DESCRIPTION = 'description';
... |
5ffb2d64d5fe29be015a27bae3fcc252ca188154fd084ac42ed3fd19b27e97c8 | MATLAB | 8,630 | 233 | % getSpikerateAutocorr_cell.m
%
% Function that computes the autocorrelation of the spike rate for a single
% cell, only during walking and only under additional conditions on
% behavioral parameters, specified by cond.
% Across trials within the same fly, weight by number of valid points
% during that trial
% Selec... |
6efbce088aba87ad0584e2787cb845b6636c0619e999cbc231092bdf423dde2d | MATLAB | 8,634 | 213 | function [] = D4_BehavioralModulation(badSubs,append)
% Calculates behavioral modulation indices
%badSubs = code of bad subjects ([23,28])
%append = 1-> load conditions combined 2-> load conditions separately
data_folder = 'Z:\Load\MEG Data\proc_data\'; %Windows
save_folder = 'Z:\MATLAB\Perceptual_Load\FieldTrip\Resu... |
32cef6ab3622f0c9dd32b4532e2bfd1b49ca6ffc31edea0bd44bea903f415a6b | MATLAB | 8,643 | 226 | %% Initialize Parameters and Process Data
% Run config.m
% Process data for each animal using the processAnimalData function
[psth, response, visI] = processAnimalData(cell_activity_allday, stim_type_allday, trials, nanimals, nstim_type, win, threshold, ngratings);
%% Post-process the data, use average LED/no-LED re... |
fc05da7b03739c011003ebd99352e33fdbb018f5261f671e48ee3e3c36525288 | MATLAB | 8,647 | 158 | function [trainedClassifier, validationAccuracy] = trainPixelClassifier(trainingData)
% [trainedClassifier, validationAccuracy] = trainPixelClassifier(trainingData)
% 学習済み分類器とその 精度 を返します。このコードは分類学習器アプリで学習させた分類モデル
% を再作成します。生成されるコードを使用して、同じモデルでの新規データを使用した学習の自動化
% や、プログラミングによってモデルに学習させる方法の調査を行います。
%
% 入力:
% ... |
fe7d7c863712d86cc354341f48bb897bc8f001ddc11cb9829c4659dd1b34aad7 | MATLAB | 8,653 | 223 | % output:
% Fig. 101 - number of Cneurons (neurons who pass the criteria)
% Fig. 201 - Ree (only for Cneurons)
% Fig. 301 - ReeP (only for Cneurons)
% Fig. 401 - modp2p (only for Cneurons)
%
% run:
% a loop over Sessions (SesList = {'ses1';'ses2';,...})
% a loop over varaibles (VarList = {'var1';'var2';,...})
... |
afefde0185e005747cc3b706f7de23622d5e33e90e09d378358caafd7f9e364d | MATLAB | 8,664 | 208 | clear all; close all; clc
%%%% janine.thome@zi-mannheim.de
%% RF classifier reported in "Classification of amyotrophic lateral sclerosis by brain volume, connectivity, and network dynamics" (HBM)
%% SPECIFY:
groupN = [0,1]; % group coding
groupL = ["Controls... |
3f7053ca2795a76a2e34d464e935dae468be325894346c8ece53a5663ca99771 | MATLAB | 8,665 | 243 | % not used in paper
%% STEP 1: set up parameters
parameters.numProcessors = 15;
parameters.numProjections = 19;
parameters.pcaModes = 5;
parameters.samplingFreq = 14;
parameters.minF = 0.3;
parameters.maxF = parameters.samplingFreq ./ 2; %nyquist frequency
parameters.trainingSetSize = 55000;
parameters.subsamplingIter... |
63513a0a9740d1aecd17f9cd79d687e899e0a4fd851c15a12bdd9ccd11b82f4c | MATLAB | 8,665 | 302 | function [im_rgb,im,cmap,minmaxT]=fmri_blob_overlay(ImBlob,ImAnat,thold,varargin)
% FMRI_BLOB_OVERLAY - Display fmri blobs over an anatomical image.
%
% Synopsis:
% [ImRGB,ImIDX,CMap,minmaxT]=fmri_blob_overlay(ImBlob,ImAnat,THold,
% param1,value1,param2,value2,...)
%
% D... |
6e55e3407df29eec59b11fd7d8e53dd6add7e5b01cc3433da28fe341d9b8cbe3 | MATLAB | 8,667 | 207 | clear all; close all; clc
%%%% janine.thome@zi-mannheim.de
%% RF classifier reported in "Classification of amyotrophic lateral sclerosis by brain volume, connectivity, and network dynamics" (HBM)
%% SPECIFY:
groupN = [0,1]; % group coding
groupL = ["Controls... |
6a4f0ce8671aa6681e078763165c58a0c4981b159d80a7421dd307a87b59cf33 | MATLAB | 8,671 | 207 | clear all; close all; clc
%%%% janine.thome@zi-mannheim.de
%% RF classifier reported in "Classification of amyotrophic lateral sclerosis by brain volume, connectivity, and network dynamics" (HBM)
%% SPECIFY:
groupN = [0,1]; % group coding
groupL = ["Controls... |
bf9e04a40240bc2609ee20d8eab7355c4ab9732e75e60e7fceb3139d53b06c7f | MATLAB | 8,676 | 159 | % In this script we will pull in all the regions of the atlas
%clear all
%clc
% Load in Data
%load('M:\Matt Chilvers\Documents\PhD\Project3_WhiteMatterLesion\DataStructure\Subject_Data_UnilateralOnly.mat')
%load('M:\Matt Chilvers\Documents\PhD\Project3_WhiteMatterLesion\DataStructure\SubjectsRemoved_Data_Sept7... |
a833a98b47b7dfec494b1bf6f176372c488a28b46c5df812f21267927b361fc4 | MATLAB | 8,677 | 181 | function [r,v,g] = reduce_L4(Delta_e, Delta_i, Iattn, ratio_sens_attn, allTime, stimIn)
%ONCE run the simulation once including five conditions
% INPUT arguments includes parameters of the column model
% OUTPUT arguments are the results of computation, including the time
% courses of firing rate, average membrane... |
4c4a20dc4543494c6323f470a8b8f8b1dfd51b83e1b3f2735340a0dad3684381 | MATLAB | 8,678 | 190 | function compute_mcmappy(obj, session, trial)
% Call this one for the maps using the actual geometry (like a
% rectangle).
% Load the trace maximums. Isabel said she didn't want this any more.
% traceMaximumsFilename = fullfile(session.getAnalysisDirectory(), sprintf('%s_trace_%s_maximums.mat', ses... |
d5d1409e942ff4c6f48c8b3b8645a01785331b23cdc3f6fe02d14356305e8f9c | MATLAB | 8,678 | 207 | clear all; close all; clc
%%%% janine.thome@zi-mannheim.de
%% RF classifier reported in "Classification of amyotrophic lateral sclerosis by brain volume, connectivity, and network dynamics" (HBM)
%% SPECIFY:
groupN = [0,1]; % group coding
groupL = ["Controls... |
25b555e5a3711571380e02824c04e42d0abdd8b4c2f6d5029ac4a92186a5d2ef | MATLAB | 8,682 | 241 |
% Estimate background model.
%
% To compute a background model, use:
%
% bg = calib_bg_estimate(vinfo, [PPM], [frame_range])
%
% where [] denotes an optional parameter and:
%
% vinfo - handle to input video (see video_open)
%
% PPM - pixels per millimeter (default 20)
%
% frame_range. - ... |
2d2962ed369c77acc7d1b3e43e26184b5eeb9db35a28a12612b1b0f55a219f33 | MATLAB | 8,686 | 328 | function [saccadeLocs, eye_pos_filt, eye_vel_pfilt] = desaccadeVel_A(data, samplerate, freq, presaccade, postsaccade, thresh, minDataLength)
accel = 0;
% STEP 1: LOW PASS ON POSITION
N = 4;
fc = 15;
nq = samplerate / 2;
[bb, aa] = butter(N, fc / nq, 'low');
eye_pos_filt = filtfilt(bb,aa,data);
% STEP 2: CALC VEL - ... |
6dd4b6c146aa37000da8fb7bb2c9776af12a1c8633728406d503ff90fc1b975f | MATLAB | 8,691 | 236 | % plotAEPPEPbySpikeRate.m
%
% Function to plot mean and standard deviation of leg AEPs or PEPs (user
% specified), colored by spike rate.
% User specified delay between ephys and behavior. Negative times are ephys
% before behavior.
% User specifies number of bins in which to divide spike rate or the edges
% of the... |
70af63105fe844199595951f685bac254fa1d2a8961813de23902c61836ae6a4 | MATLAB | 8,695 | 233 | function [data] = tdmsreader(tdmsfilename, channel, datalen)
% Decode TDMS file, which is saved as DAQmx raw data format for PXIe-6368.
% Syntax:
% [data, rawdata] = TDMSREADER(tdmsfilename, channel, datalen)
% tdmsfilename: the name of tdms file
% channel: channel number
% datalen:
% if datalen is s... |
2380720507ad94d84323988e5b8336d6ba0e80bae64ab7bac3a23ddaf84fb2d6 | MATLAB | 8,715 | 249 | % mglOpen: Open an mgl window
%
% $Id$
% usage: mglOpen(whichScreen, screenWidth,screenHeight,frameRate,bitDepth)
% by: justin gardner
% date: 04/10/06
% copyright: (c) 2006 Justin Gardner, Jonas Larsson (GPL see mgl/COPYING)
% purpose: Opens an a drawing window.
% usage:
% ... |
ae4ae48359c9eddf2e8d29b489741ffbe6ea1f4ea965103989f41f1b73031fa6 | MATLAB | 8,717 | 189 | % getTuning -
%%
globals;
strPlt = ''; for ii=1:length(PLOT_TYPE), strPlt = [strPlt cell2mat(PLOT_TYPE(ii)) '-']; end; strPlt=strPlt(1:end-1);
strQs = ''; for ii=1:length(ShowUnitsQs), strQs = [strQs cell2mat(ShowUnitsQs(ii)) '-']; end; strQs=strQs(1:end-1);
strVars = ''; for ii=1:length(VarList), strVars = [strVa... |
18fd76a6145f8f11b0bde522f654053330242ee1ade2d61035e6fa9cff89f7ce | MATLAB | 8,724 | 180 | function [r,v,g] = reduce_L46(Delta_e, Delta_i, Iattn, ratio_sens_attn, allTime)
%ONCE run the simulation once including five conditions
% INPUT arguments includes parameters of the column model
% OUTPUT arguments are the results of computation, including the time
% courses of firing rate, average membrane potent... |
78580c1c8f549adb13183e80a5734abc5b8f54330ed148df3be3859ce6b30453 | MATLAB | 8,732 | 189 | % getTuning -
%%
globals;
strPlt = ''; for ii=1:length(PLOT_TYPE), strPlt = [strPlt cell2mat(PLOT_TYPE(ii)) '-']; end; strPlt=strPlt(1:end-1);
strQs = ''; for ii=1:length(ShowUnitsQs), strQs = [strQs cell2mat(ShowUnitsQs(ii)) '-']; end; strQs=strQs(1:end-1);
strVars = ''; for ii=1:length(VarList), strVars = [strVa... |
daeecdb3d42165df245fc5c453c3923dfbfc476d4131f8e0791b7ac74d7cb540 | MATLAB | 8,737 | 213 | function [status, p] = ml_cai_daq_videorecords_create(trialFolder, dataFolder, subjectName, dataset, dateString, timeString, varargin)
p = inputParser;
p.CaseSensitive = false;
addRequired(p,'trialFolder', @isstr);
addRequired(p,'dataFolder', @isstr);
addRequired(p,'subjectName', @isstr);
a... |
f8058776e6e2601faba4d75b85c622d7cca7fceacf33df4ec6477fc1f168a4f8 | MATLAB | 8,742 | 201 | function data = TDMS_readFileHelper_v1(fid,optionStruct,metaStruct,paramsStruct)
%TDMS_readFileHelper_v1
%
%
% Time stamps in TDMS are stored as a structure of two components:
% (i64) seconds: since the epoch 01/01/1904 00:00:00.00 UTC (using the Gregorian calendar and ignoring leap seconds)
% (u64) positive fractions... |
84fc6b2a972a456c11bc234cf0b0ef607682cb79cbcedb389486be018fb26d92 | MATLAB | 8,752 | 250 | % findCondYawVelPeaksFT2P.m
%
% Helper function for saveDFFCond_bouts() that takes in fwdVelCond,
% fictracSmo, and cond and returns times for valid yaw
% velocity peaks as well as start/end times for corresponding bouts.
% Boolean for whether to extract right or left turns
%
% Adapted from findCondYawVelPeaksFT(), ... |
1bb7eee4e60ebc708eba5d52006b51abc0a376e78b5f507d415fa1867150916a | MATLAB | 8,757 | 204 | % fixStairInitTask.m
%
% $Id$
% usage: [fixTask myscreen] = fixStairInitTask(myscreen)
% by: justin gardner
% date: 09/07/06
% copyright: (c) 2006 Justin Gardner (GPL see mgl/COPYING)
% purpose: Implements a fixation task. In this task, the fixation cross
% starts out cyan and ... |
1a88b52313fbc08c2de66d2239768e17abfe00b9c67a299dbb7dfbb136b1271d | MATLAB | 8,762 | 201 | %% Set up data for PCA
clear all
clc
cd('M:\Matt Chilvers\Documents\PhD\Project3_WhiteMatterLesion\Scripts\PCA_Regression')
% Load in Data
load('M:\Matt Chilvers\Documents\PhD\Project3_WhiteMatterLesion\DataStructure\Subject_Data_UnilateralOnly.mat')
%% Extract data
for i = 1:length(Subject_Data)
... |
793878d94a72497aec09159c4a33ef46dd9c258906ef612d7d7476a75d5ac457 | MATLAB | 8,762 | 241 | function varargout = subsref(opt,subs)
% Subscript referencing
%
% Fields are:
% dat - a file-array representing the image data
% mat0 - a 9-parameter affine transform (from qform0)
% Note that the mapping is from voxels (where the first
% is considered to be at [1,1,1], to m... |
df74d5880bf3a1787f8466fea6acdcf348917430fec03e78232e2ea31f704955 | MATLAB | 8,796 | 214 | % computeLegFictracOpto_1Fly.m
%
% Function that extracts the individual leg traces and FicTrac, in response
% to optogenetic stimulation of different durations and intensities (ND
% filters) for a single fly.
% User selects all pData for that fly through the file selection GUI
% Saves the data as a struct in path sp... |
026193099d0d90ad5639fdbda1344e367621581fa0ba693ccaab7e89eebb6fa6 | MATLAB | 8,811 | 219 |
% Compute features from raw tracking data.
%
% To compute features, use:
%
% feat = feat_compute(trk, calib)
%
% where:
%
% trk - tracking structure, obtained from previous steps of
% tracker (stored in *-track.mat)
% calib - calibration structure, obtained from calibration ste... |
445eb4a4e776f9a03d1efc7579dcc4b6c5af3491c44be827a2d9202caab54de1 | MATLAB | 8,817 | 283 | function sR=icassoEst(mode,X,M,varargin)
%function sR=icassoEst(mode,X,M,['FastICAparamName1',value1,'FastICAparamName2',value2,...])
%
%PURPOSE
%
%To compute randomized ICA estimates M times from data X. Output of
%this function (sR) is called 'Icasso result structure' (see
%icassoStruct). sR keeps the on all the meth... |
6984cd407af58ea85f134c381be6661bc2fd0f8e3b2bf0c235504c3503aa911e | MATLAB | 8,820 | 261 | function varargout = peakfinder(x0, sel, thresh, extrema, include_endpoints)
%PEAKFINDER Noise tolerant fast peak finding algorithm
% INPUTS:
% x0 - A real vector from the maxima will be found (required)
% sel - The amount above surrounding data for a peak to be
% identified (default = (max... |
8c16cc240c3ae7c7d3db508871e7ded7e360f6969085fba788e5f94f502f79d7 | MATLAB | 8,823 | 259 | % plotIInj_AEPPEP_allFlies.m
%
% Function that takes output from extractLegStepParamsIInj_fly() and
% plots the AEP/PEP in the XY plane, either as the actual values or as the
% difference from the no stimulation condition
% Has option to plot mean across flies (X) and/or mean for each individual
% fly (dot).
% Sele... |
a4ff1a15a3fc64973459fb86595a2d2e00593702e09da88cab1f3f87b8d3f3e7 | MATLAB | 8,841 | 278 | function [output] = ml_alg_best_aligned_average_context_maps_for_cell(cellId, sdataMaps, sdataCellIds, sdataTrialIds, sdataContextIds, comparisonMethod)
% sdataMaps should be a MxNxK matrix where P is the number of cells
% sdataCellIds should be a Kx1 array where each element is the cell id
% corresponding to the map
%... |
f332d6dac96a95318109373f9fd466d62ec1047ad115784008bf05dc925c3a92 | MATLAB | 8,846 | 262 | % DETECTPUPILCR detects pupil and corneal reflection in the eye image
%
% Input:
% img = input image
% pupilStart = start point for starburst algorithm for pupil
% radiiPupil = guess of pupil radius
% edgeThresh = threshold for detecting pupil
%
% radiiCR = guess of CR radius
% CRthresh = ... |
9b44ee27c4a5a6bd6605c1c4a78cb809f0b8a4d6b4717c9f3f04f256b1f38834 | MATLAB | 8,848 | 171 | function [certain_head, certain_tail, uncertain_tips, has_ring, thin_image, BW, new_worm_radius] = find_tips_centerline_image(I, prev_head, prev_tail, worm_radius, dilation_size, best_threshold)
%loop through threholds to see if there is a hole in the image, if so,
%get the branching tips when the hole is the... |
18f097048fce6809d65e803d4c353a79a827a7d3943ae2360322a293ad085902 | MATLAB | 8,851 | 242 | % plotIInjLegStepParam_allFlies.m
%
% Function that takes output files from extractLegStepParamsIInj_fly() and
% generates a plot of the specified legStep param for each leg. Plots
% mean +/- SEM for each fly as well as across flies. Different conditions
% in different columns. Points from the same fly are connect... |
27013dd94aef87bf573f8e595c0896840113fbea432ebf6a50a267415b456cf1 | MATLAB | 8,856 | 256 | function [h] = emmip(emm, groupformula, varargin)
% Plotting estimated marginal means (only for categorical vars)
% Copyright 2019, J. Hartman, Cornell University
% written using Matlab version R2016a
% (errorbar,linkaxes behavior or output changes in later versions)
%
% INPUTS:
% emm is output from emmeans.m
... |
9bd0752c9836cc98a14038557ec430f623780929a0e641c1aa9904068bd988f4 | MATLAB | 8,860 | 256 | function [h] = emmip_JT(emm, groupformula, varargin)
% Plotting estimated marginal means (only for categorical vars)
% Copyright 2019, J. Hartman, Cornell University
% written using Matlab version R2016a
% (errorbar,linkaxes behavior or output changes in later versions)
%
% INPUTS:
% emm is output from emmeans... |
c23c0233a7f352b3f56286fe4fabd636098b21bdd0f3c9a808f9e2cc0209bcee | MATLAB | 8,865 | 268 | % script that prompts user for mat, annotation, and movie files, parameters
% for computing suspicious frames, then computes suspicious frames, then
% brings up the labelerrors gui
%% set all defaults
moviename = '';
moviepath = '';
setuppath;
%% read last settings
pathtolabelerrors = which('labelerrors');
savedsett... |
4512b8ddcd276deb03ad7dfb99d7f61ea7544cc16c52f3cc5a29e46f5cf06aec | MATLAB | 8,866 | 300 | function varargout=shpath(MM,ri,ci,rf,cf)
% SHPATH - shortest path with obstacle avoidance
%
% USAGE:
%
% [r,c] = shpath(M,ri,ci,rf,cf)
% [r,c,da] = shpath(M,ri,ci,rf,cf)
%
% VARIABLES:
%
% M = terrain grid matrix of ones and zeros, where ones represent
% grid squares containing obstacles,... |
7bab7c4fa5e8e66a7930ff983d8c82b07df590dedff582b725b12b6cd2d825c2 | MATLAB | 8,867 | 247 | % Data analysis for FADE-BMS
% _
% This script performs the entire data analysis for the FADE-BMS study.
%
% written by Joram Soch <Joram.Soch@DZNE.de>, 07/08/2020, 13:28;
% adapted: 09/11/2020, 11:46
%%% Step 0: analysis parameters %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% directories and subjects
stud_dir =... |
33de7c9b0201c1e92d78cbd2addc7d087ab17ba3f723a3e1f2761c05750efbeb | MATLAB | 8,872 | 300 | function varargout=shpath(MM,ri,ci,rf,cf,maxIt)
% SHPATH - shortest path with obstacle avoidance
%
% USAGE:
%
% [r,c] = shpath(M,ri,ci,rf,cf)
% [r,c,da] = shpath(M,ri,ci,rf,cf)
%
% VARIABLES:
%
% M = terrain grid matrix of ones and zeros, where ones represent
% grid squares containing obst... |
10fa1628ba668ab7b3f251314fc1cb162543088450f74b11f22ddc3e0a53e847 | MATLAB | 8,876 | 262 | function convertUG_BIDS_2021(subj)
maindir = pwd;
usedir = '/data/projects/istart-data/';
%try
% 11-18-21 | This is the code I am using for the bids converter.
% Plan now is to use the BIDs converter for only the simple regressors. Ie:
% Export the endowments (cue onsets) and the decision phases
% (accept/reject), ... |
087c55e8ab9a598881bcdcb99c204a0852ace670b25523266fad9dce86ea4561 | MATLAB | 8,883 | 193 | % getTuning -
%%
globals;
strPlt = ''; for ii=1:length(PLOT_TYPE), strPlt = [strPlt cell2mat(PLOT_TYPE(ii)) '-']; end; strPlt=strPlt(1:end-1);
strQs = ''; for ii=1:length(ShowUnitsQs), strQs = [strQs cell2mat(ShowUnitsQs(ii)) '-']; end; strQs=strQs(1:end-1);
strVars = ''; for ii=1:length(VarList), strVars = [strVa... |
7260ac4500d6902b4b32b7f208be0c18a22743a18b63057befad707d739135fa | MATLAB | 8,883 | 193 | % getTuning -
%%
globals;
strPlt = ''; for ii=1:length(PLOT_TYPE), strPlt = [strPlt cell2mat(PLOT_TYPE(ii)) '-']; end; strPlt=strPlt(1:end-1);
strQs = ''; for ii=1:length(ShowUnitsQs), strQs = [strQs cell2mat(ShowUnitsQs(ii)) '-']; end; strQs=strQs(1:end-1);
strVars = ''; for ii=1:length(VarList), strVars = [strVa... |
b740755f4c694a1cec4c4f1a9e0e9eeb6127da747cee9476b9d2480892664d50 | MATLAB | 8,891 | 275 | % createImgLegFictracMovie.m
%
% script to generate movie showing dF/F, legVid, FicTrac variables
trialPath = ...
'/Volumes/Samsung_2tb/Wilson Lab/RAW DATA/190507/fly01/fov02/trial01';
tVid = [520 540]; % start and end times, in seconds
cd(trialPath);
% load relevant data
load('imDat.mat', 'alignedSeries', 'fra... |
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