sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
f10257a62dbb9daf9fe789356baafaee5c40927de68b6de3e8f0561a3405e3ed | MATLAB | 2,420 | 68 | function design_mat = cvBMS_analysis_batch(stud_dir, subj_file, MS_file, LME_img, stat_suff)
% _
% Create batch for manual cvBMS analysis using MACS toolbox
%
% stud_dir - study directory in data/analyses are located
% subj_file - an XLS file containing subject IDs and covariates
% MS_file - a MAT f... |
03565433617a8ab2df76b4b38b5ae766864de9126ed4c7f69fcc06f3fd2b8b1a | MATLAB | 2,421 | 55 | function mff_setup
% MFF_SETUP ensures that the JVM is available and that the MFF java
% implementation is on the java classpath.
% this toolbox requires JAVA to be running and properly configured
if ~usejava('jvm')
error('the EGI_MFF format requires that the java virtual machine is available, see http://fieldtrip.... |
d3eb990d4967b162f04d9896ebdd37cf39a3d08393977c071fbcdc1dece7f90a | MATLAB | 2,423 | 87 | % plotCorrCoeffBehContParam.m
%
% Function to plot output of getCorrCoeffBehContParam_cond_all()
% Heatmap (using MATLAB function) of mean correlation coefficient across
% flies, where each one is its own file (assumes multiple files all have
% same matrix of correlation coefficients)
% Select files through GUI
%
% I... |
2523eb70a41fbdb5e368823214fdc959ada85312bb47663f2870354ed959144c | MATLAB | 2,424 | 50 | function [ns_RESULT, ContCount, Data] = ns_GetAnalogData(hFile, EntityID, StartIndex, IndexCount);
%ns_GetAnalogData Retrieves analog data by index
%
% Usage:
% [ns_RESULT, ContCount, Data] =
% ns_GetAnalogData(hFile, EntityID, StartIndex, IndexCount)
%
% Description:
% Returns the ... |
cd6ee8cea6511ed2cfbcf2e46c49e33e5474eb8ed900e812944a802d15f04b9c | MATLAB | 2,425 | 92 | function [spkwaveform,ttspan,...
HW, AHP, Threshold, Amp,max_slope,min_slope,...
HWidx,AHPidx, Thresholdidx,max_slopeidx,min_slopeidx] = AP_Statistic_HERE(data,peaktime,tspan,Goodidx)
%INPUT
% data : a vector
% tspan: a vector,have the same elememt with data
% NumSpk: successive number of spike to be ... |
c5f9f7e986ad986f91ca828dd30994f1ecf7a4cab0cfaae7bfaa7720da6ddc13 | MATLAB | 2,427 | 75 | % plot sin wave at freq f (Hz) and duration TT (s)
InterpMethod = 'pchip';
% 'nearest' Nearest neighbor interpolation
% 'linear'Linear interpolation (default)
% 'spline' Cubic spline interpolation
% 'pchip' Piecewise cubic Hermite interpolation
% 'v5cubic' Cubic interpolation used in MATLAB 5. This method does no... |
29926a9d0fe577ecdc7ed3feef988d9b5cf6f63b10e58eab3860ea6673f006ca | MATLAB | 2,428 | 69 | function prepare_savedir(stg,prf)
% prepares the directory in which new files, results and folders will be
% saved.
%
% PREPARE_SAVEDIR(STG,PRF) gets the STG and PRF variables and prepares the
% required folders in which the pipeline will save the results and new
% files.
%
% Ehsan Kakaei, Jochen Braun 2021
... |
55e853d343d0e826270ea03e9658fb8ca815b9296641ea5d0683ad46079a2279 | MATLAB | 2,429 | 114 | function [b,c,d,x,y,z,qfac] = vox2rasToQform(vox2ras)
% [a,b,c,x,y,z,qfac] = vox2rasToQform(vox2ras)
%
% Converts a vox2ras matrix to NIFTI qform parameters.
% Note: the vox2ras should be 6 DOF. This code mostly just
% follows CH's mriToNiftiQform() in mriio.c.
%
% hdr.pixdim(1) = qfac;
% hdr.quatern_b = b;
% h... |
128cdc60cad3857c35131d10081af2750fa6c8c33074d210e6035af023ab2f72 | MATLAB | 2,430 | 101 |
clear all
close all
%% create figure 3C
%% janine.thome@zi-mannheim.de
pato=['/###/Figures/']; %% add output path
if ~isdir(pato), mkdir(pato); end
%% set fig
fs=16; lw=2;
%% load feat
load('D_ALS_HC_Fig3C.mat');
%% color def
colHC=[0 0 0];
colALS=[ 252 141 89]/... |
770420332b1ceeff886c7f524ffcfa57d6d5b11657733a294d7adeff81d2624c | MATLAB | 2,430 | 57 | %% Written by Eric Earl, 10/15/2014
function subject_motion_numbers_TXT_parse(movement_files)
% Motion numbers parsing Nipype wrapper pulling in list of motion files
% Outputs motion_numbers to "motion_numbers.mat" file
% movement_files = {'motion_numbers0.txt', 'motion_numbers1.txt', 'motion_numbers2.txt'};
% movement... |
5b83f32ef46eba73d2245d30b3335168df44ec62418288e5d28ef779ca2f1175 | MATLAB | 2,431 | 47 | classdef FilteredEphys < types.core.NWBDataInterface & types.untyped.GroupClass
% FILTEREDEPHYS Electrophysiology data from one or more channels that has been subjected to filtering. Examples of filtered data include Theta and Gamma (LFP has its own interface). FilteredEphys modules publish an ElectricalSeries for each... |
9e63b11c24aabeae870212a74b89602dfbdd797ca0792b64ff00b5a642f7f594 | MATLAB | 2,431 | 75 | function VO = spm_smoothto8bit(V,fwhm)
% 3 dimensional convolution of an image to 8bit data in memory
% FORMAT VO = spm_smoothto8bit(V,fwhm)
% V - mapped image to be smoothed
% fwhm - FWHM of Guassian filter width in mm
% VO - smoothed volume in a form that can be used by the
% spm_*_vol.mex* functions.... |
9e6b864c5f35947118904eb16226fe7214bb80a884843f74b7c1bf26df8141af | MATLAB | 2,431 | 54 | function [BTA, behaviorCounts, BTA_std, BTA_stats] = BehaviorTriggeredAverage(Behaviors, LEDPowers, parameters, bootstrap)
%finds the behavior triggered average, optionally determine the
%significance of the BTA by shuffling transitions randomly and finding
%the BTA
BTA_seconds_before_and_after = 10;
... |
a39a850678f04ef24a9aded4706846a4b6b6babe60aafb4c9515053a0fedf3b1 | MATLAB | 2,432 | 66 | function varName = TDMS_genvarname2(string,replaceStr,prependStr,alwaysPrepend)
%GENVARNAME2: Outputs a valid variable name VARNAME
%
% GENVARNAME2(STRING,*REPLACESTR,*PREPENDSTR,*ALWAYSPREPEND) replaces invalid
% characters in STRING with REPLACESTR. If the first letter is not
% a letter, or ALWAYSPREPEN... |
ad1a3a3664bae4964854849fb551a0ea6cdfaeb25b450e5f25d9deca078a386a | MATLAB | 2,434 | 93 | function [ax] = gridPlot(xmat,ymat,dmat,dtype,suff,figopt)
%gridPlot.m 9/13/22
doYlbl = optCheck(figopt,'doYlbl',[],[]);
doXlbl = optCheck(figopt,'doXlbl',[],[]);
doYRlbl = optCheck(figopt,'doYRlbl',[],[]);
yrmat = optCheck(figopt,'yrmat',[],[]);
hlightCoords = optCheck(figopt,'hlightCoords',[],[]);
prefixMap = optChe... |
3550fd23b4e1d56060ac9c91518dbc89ba5771455e5d49843447abc5fe89cc24 | MATLAB | 2,435 | 79 | %% fitlm between str connectivity, dis, commu and functional connectivity
%% the dis and communicability are calculated by averaging individual auc
%% para
roi_num = 48;
load('unrelated_sub_matrix_str_DBM.mat')
str_data = mean(sub_matrix,3);
load('unrelated_sub_matrix_fun.mat')
fun_data = mean(sub_matrix,3);
load('unr... |
ba2f3129fcddf56de2a0d239c9a932dca2927de1cffb37ad77ec9385ae0cc2ad | MATLAB | 2,435 | 79 | %% fitlm between str connectivity, dis, commu and structural connectivity
%% the dis and communicability are calculated by averaging individual auc
%% para
roi_num = 48;
load('unrelated_sub_matrix_str_DBM.mat')
str_data = mean(sub_matrix,3);
load('unrelated_sub_matrix_fun.mat')
fun_data = mean(sub_matrix,3);
load('unr... |
f0825256328175aaf25b15806bc0f4fa3e9f556f0dc65a0491c81069d5b84d7a | MATLAB | 2,435 | 53 | function fH = makeFigure8_SuppressionLevels_v_pRFParams(ds,lmmResults,subjnrs,roisToPlot,...
cmapROIs,spatialModel,temporalModel,useSTRetParams,saveFigs, saveFigDir)
% Function to reproduce main manuscript figure 8:
% panel a: Suppression level (LMM slopes) vs effective pRF size for each ROI
%... |
69aa1cd464cd5ae0b3508b2988d62b03d67d8b1fd25bb3fda926128fa39d2606 | MATLAB | 2,436 | 68 | % Marc Normandin, Muzzio Lab, Psychological & Brain Sciences, University of Iowa, 2024
function [output] = ml_alg_best_aligned_average_context_maps_for_cell_v2(maps, trialIds, contextIds, comparisonMethod, REFLECT_ONE_CONTEXT)
%%
% sdataMaps should be a MxNxK matrix where K is the number of cells
% sdataCellIds should... |
c2ccaae58965d13a2a5712353e4a2037ea822b99b32c57ac80ff0198fb7e41fc | MATLAB | 2,436 | 75 | cd('M:\Matt Chilvers\Documents\PhD\Project3_WhiteMatterLesion\Scripts\PCA_Regression')
SetUpDataForPCA
%% Run partial least squares regression on 10 components
% X = stnd_predictor_variables;
% y = stnd_response_variable;
% [n,p] = size(X);
%
% [Xloadings,Yloadings,Xscores,Yscores,betaPLS10,PLSPctVar,MSE,PL... |
3eb5e476dd8e861fe53b9619175e2a68999d8c2276243d6a635a21593984a239 | MATLAB | 2,438 | 82 | function [outs] = agplotripraster(rwtrials,postrwtrials,varargin)
fulllength = 1;
colortrig = 0;
sortorder = 'off'; % 'rw' or 'postrw'
cols = [.8 .8 .8; 1 1 1; 0 0 0; 1 0 0];
if (~isempty(varargin))
assign(varargin{:});
end
hold on;
maxtime = 80; % in sec, must be even
center = maxtime/2;
timebin = .01; % 10ms ... |
22276493932cef7b7f7c00a68941beaa7898509691b2220b44c1280775e137b7 | MATLAB | 2,439 | 75 | cd('M:\Matt Chilvers\Documents\PhD\Project3_WhiteMatterLesion\Scripts\PCA_Regression')
SetUpDataForPCA
%% Run partial least squares regression on 10 components
% X = stnd_predictor_variables;
% y = stnd_response_variable;
% [n,p] = size(X);
%
% [Xloadings,Yloadings,Xscores,Yscores,betaPLS10,PLSPctVar,MSE,PL... |
3a7b47e1ef4c25e046fea864516ea002dc15b769730b676d383ab2f5e3df4f4f | MATLAB | 2,440 | 75 | function [cfgs] = exhaustSpacing(probe, spacingAmount)
%EXHAUSTIVESPACING Varies spacing between modules, exhaustively
% Varies the spacing between modules by the amount specified in the row
% vector spacingAmount. Each new configuration is then analyzed. This
% results in a cfgs structure with the number of chan... |
b6f78c4f33a5a37f2d0039c8bb86ce268da5462b9858b2e9454d7946dfecdfa3 | MATLAB | 2,440 | 91 | function akc_out = outlierdetection(dt,mask)
if ~exist('mask','var') || isempty(mask)
mask = ~isnan(dt(:,:,:,1));
end
dt = vec(dt, mask);
load('dirs10000.mat','dir');
nvxls = size(dt, 2);
akc_out = zeros([1 nvxls]);
N = 10000;
nblocks = 10;
for i=1:nblock... |
d0b06b60e4fd78a178831f894955cf56c3894a4af452cd0dc44be3b1a22aaf85 | MATLAB | 2,440 | 71 | % Marc Normandin, Muzzio Lab, Psychological & Brain Sciences, University of Iowa, 2024
function [hFig] = stabilitybfo90table_plot_withinacross_prob(MeanTable, ErrorTable, showExcluded)
numGroups = size(MeanTable,1);
hFig = figure('position', get(0, 'screensize'));
% Each group gets a column with ... |
3665cb00ae2224b28767170d5a50a77aabca7f56117447501907b522a15d048a | MATLAB | 2,442 | 96 | %
% Perform the preferential attachment tests.
%
% PARAMETERS
% $network The network
%
% INPUT FILES
% dat/split.$network.mat
% dat/info.$network
%
% OUTPUT FILES
% dat/pa.$network.mat
% Parameters of the fits
% .pa
% .a, .u, .v (existence depending on the format)
% .$method (see konect_pa_full_full.m in KONEC... |
c924683cbb03d628d4bdd7520b21f6819d45f8d3aa09b3adba1c03b924fd863c | MATLAB | 2,442 | 125 | %
% Test Helmholtz particle FMMs in R^3
%
zk = complex(1.1);
N = maxNumCompThreads
nsource = 2000;
source = zeros(3,nsource);
idist=1;
if( idist == 1 ),
theta=rand(1,nsource)*pi;
phi=rand(1,nsource)*2*pi;
source(1,:)=.5*cos(phi).*sin(theta);
source(2,:)=.5*sin(phi).*sin(theta);
source(3,:)=.5*cos(theta);
end
if... |
f46a464b4e638ba79c8fa8a97957da574dcdf656d80713d018cf1575089b759d | MATLAB | 2,442 | 94 | % this function outputs two alternate time bases (x) to use with FP y data
% original time base is timeFP_RS, derived from FP x data, nominally 100Hz
% or whatever the FP data was resampled to
% video time = camtime
% timeFP_RSretime warps timeFP_RS to match the variable frame rate expressed in c... |
60813053867d05d07bf8a6db47dcb7adc189b6669aaa9e8491742b15d9cdea3b | MATLAB | 2,444 | 67 | classdef fuzzy_rect_AOI < rectangle_AOI
methods
function self = fuzzy_rect_AOI(all_aois, trail, allowed_angle)
%UNTITLED2 Construct an instance of this class
% Detailed explanation goes here
argin{1} = all_aois;
argin{2} = trail;
argin{3} = all... |
a8447005ab2d82dbd6e1608e90a10bd34a8f4c76850a53328c23979595edc065 | MATLAB | 2,444 | 75 | function FM = ft_preproc_online_filter_init(B, A, x)
% function FM = ft_preproc_online_filter_init(B, A, x)
%
% Initialize an IIR filter model with coefficients B and A, as used in filter and butter etc.
% One sample x of the signal must be given as a column vector.
%
% This function will calculate the filter delay st... |
0130585e28b262398995657fa635b1a04e809102c9641cf6f8430a98c468bf99 | MATLAB | 2,447 | 45 | function mltp_plot_bfo_90_dc(obj)
numAngles = 4;
best_fit_orientations_different_contexts = zeros(obj.Experiment.getNumSessions(), numAngles);
plotlegend = cell(obj.Experiment.getNumSessions(), 1);
for iSession = 1:obj.Experiment.getNumSessions()
session = obj.Experiment.getSession(iSession);
... |
060636778878cd9ed08cab3f97d9c5f3dbd7ab6c3acc4621700aec7875118a11 | MATLAB | 2,449 | 91 | %{
Use the group clustering and the centroids for each
k to produce the cluster validity indices to produce the elbow plot, where
lower values are better.
Adapts code from:
https://github.com/trendscenter/gift
Output:
metric_group.h5 Contains the CVI values for each k for the group.
%}
%Define command line arguments.... |
382e2fd03376942e2d81cb53a9eb84cbd510376a08271167282d038817fa4e14 | MATLAB | 2,449 | 86 | function results = vl_test_kdtree(varargin)
% VL_TEST_KDTREE
vl_test_init ;
function s = setup()
randn('state',0) ;
s.X = single(randn(10, 1000)) ;
s.Q = single(randn(10, 10)) ;
function test_nearest(s)
for tmethod = {'median', 'mean'}
for type = {@single, @double}
conv = type{1} ;
tmethod = char(tmethod) ;... |
a85a32b6284d1f4cbb911effa8e1fca6b3bee7d86cd8e37c9de597e63702c478 | MATLAB | 2,449 | 54 | function subject_FD_parse_HCP(FD_movement_files,skip_seconds,epi_TR,brain_radius_in_mm)
% FD parsing Nipype wrapper pulling in list of motion files
% All variables (skips, TR, CurrentDirectory) set within Nipype
% Iterates over range of values from 0.1 to maximum of 0.5 FD threshold
% Outputs to .mat file
% FD_movement... |
c77a5978c90c0b60bfd454999c716c012063468fca48ee35281beebdf61b1fd4 | MATLAB | 2,452 | 93 | function createStim()
sizeStimBlockWDeg = 4; % deg
sizeStimBlockHDeg = sizeStimBlockWDeg;
% screenWidth = 38; %104; % cm (old CNI = 104cm at both 16ch and 32ch)
screenHeight = 20; % cm
scanCoil = 16;
if scanCoil == 32
viewingDist = 272; % cm; CNI = 270-273cm at 32ch, 265 at 16ch;
else
viewingDi... |
3f57e91fa103c517b2f301bf651bc4322003d0f5c46cc5d7c7af1337770ec277 | MATLAB | 2,453 | 66 | %{
Copyright (C) Cambridge Electronic Design Limited 2014
Author: Greg P. Smith
Web: www.ced.co.uk email: greg@ced.co.uk
This file is part of CEDS64ML, an SON MATLAB interface.
CEDS64ML is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License... |
6670a1d542131e3d33a3045b811dab8a9357e7e2be060783be8353771bbb1d89 | MATLAB | 2,454 | 65 | % initASLEyeTracker.m
%
% $Id: initASLEyeTracker.m 203 2007-03-19 15:41:00Z justin $
% usage: initASLEyeTracker.m()
% by: justin gardner, eric dewitt
% date: 02/24/05
% copyright: (c) 2006 Justin Gardner; 2009 Eric DeWitt (GPL see mgl/COPYING)
%
function myscreen = initASLEyeTracker(myscreen,... |
5f46ba96ef4373681eddeaac9fceafdbd2f518c056e8a8ffe189bcbd584f501f | MATLAB | 2,455 | 65 | %% function density_plot(spikes, idx)
% creates density plot of the spikes
%
%
% Portions of this code were adapted from work by Simeon Knieling, with
% permission.
%--------------------------------------------------------------------------
function density_plot(spikes, idx)
color_ = [0 0 0];
if ~exist('idx', 'var'... |
1cd5d5f2680cc5706d1f31c2f8bcbf0dfb122cdc45305bf3324250be6af455d0 | MATLAB | 2,457 | 93 | %
% Make the X axis labels by correct for year numbers.
%
% PARAMETERS
% t_min, t_max Minimum and maximum values to be plotted, in
% Unix times
%
function time_xaxis_unix(t_min, t_max)
t_min
t_max
assert(t_max > t_min);
NUM = 7; % Maximum number of ticks to show on the date axis (X axis)
YEAR = 3600 * 24 *... |
b5868266fd04d6e53ba86e89768ad5527db52ad1869dce582f20bec90c250947 | MATLAB | 2,457 | 91 | % displayRawSignals.m
%
% Function that plots dF/F over time for each ROI, as well as raw
% fluorescence before background subtraction as separate plot. Displays
% average image with ROIs overlaid
%
% INPUT:
% frameTimes - time at which each frame occured
% avSignal - raw fluorescence before background subtractio... |
bd99bcbdd239ef148789b304149058e95e769103d8f69a213457b82ddaa0bb7d | MATLAB | 2,457 | 63 | function SC=init_system(SC)
%% ramps
SC.N_PG=2*SC.n_PG+1;
n=SC.n;
SC.r0 = 1046; %main camera 00
SC.c0 = 953; %main camera 00
SC.ramp_fx_laser=1; %DC offset laser SLM x
SC.ramp_fy_laser=0; ... |
74801f3607a6acf55463be51574c1c96155c28215024214b3281a42fe4b5113c | MATLAB | 2,458 | 62 | function [p] = ml_cai_scopecam_alignvideo( dataFolder, varargin )
p = inputParser;
p.CaseSensitive = false;
addRequired(p,'dataFolder', @isstr);
%addRequired(p, 'dataFolder', @isstr);
addParameter(p, 'videoFolder', dataFolder, @isstr);
addParameter(p, 'outputFolder', dataFolder, @isstr);
... |
5575995f0329c72cef48d68185eae5501517173382eb8ca8f74d20264e9932fd | MATLAB | 2,459 | 102 | % theta = choose_orientations_generic(theta,wtheta,appearancecost)
%
% we will set the orientation to theta_t = theta_t + s_t * pi
% we want to choose s_t to minimize
% \sum_t cost(s_t|s_{t-1})
% cost(s_t|s_{t-1}) = [wtheta_t*d(\theta_t,\theta_{t-1}) +
% appearancecost(s_t,t)]
%
% we will find the ... |
8fe02621b21a36afe27f1b1c21ce2ca68b5b29ee2d93e99f9f17e40d45c8f01e | MATLAB | 2,459 | 51 | function NamedUnitNames = getSesNames(Sesname,var)
%globals;
NamedUnitNames=[];
switch var
case 'nose.o',
switch Sesname,
case '20160601Thalamus45_opF_W',
case '20160602Thalamus48_opF_W',
case '20160602Thalamus49_opF_W',
case '20160603Thalamus39_opF_W... |
357cbaaa7d5fda00b5ced5347b4eedfe379f0a27da63dc2b1c5f88f20fade6ba | MATLAB | 2,461 | 80 | % computeEnvelopeStepParamsPData.m
%
% Function that computes a continuous estimate of AEP, PEP, step length,
% and step direction on multiple selected pData files (selected through
% GUI).
% pData file must have legTrack, legSteps, and moveNotMove structs
% This functionality has now been added to extractLegStepsF... |
791fe9e04e220a38b28e2a35c95c1f4af7301ace6e5709c4a0e14e14d1ce76ec | MATLAB | 2,462 | 55 | function yml=mbmling(xml,plt)
%MBMLING_CELL converts any XML into MbML (Matlab Markup Language) compliant string
%
%Syntax: yml=mbmling(xml,plt)
%
%Description:
% Converts any XML syntax into Matlab Markup Language (MbML)
%
% Jonas Almeida, almeidaj@musc.edu, 18 May 2002, MAT4NAT Tbox
if nargin<2;plt=0;end
if plt==... |
08ca8911a0bda043efc0ab1e80566d4704cfb08ae990f15e0c56974dc1c23c12 | MATLAB | 2,464 | 57 | function ok = clearStage(cfg,micID,varargin)
% Empty the managed stage folder without uploading. Never throws
%
% function ok = webupload.clearStage(cfg,micID,'Param1',val1,...)
%
% Purpose
% Call once at the start of a new run so a previous run's recipe and log can never be
% sent with the ... |
b39096afdfb977f53b082f273866b25c81d392f7b620be4f691194648bf0d9b7 | MATLAB | 2,464 | 77 | % merge forward/backward replay onsets to single file
folder = [pathResults '/'];
%% merge replay onsets for mental simulation task
mkdir([folder '/merged/cued_mental_simulation_replay'])
mkdir([folder '/merged/cued_mental_simulation_prob'])
f_fwd = dir([folder 'onsets-fwdMentalSimulation/sub*fwdMentalSimulation*rep... |
c910f020576967beb67667adf3be762f80748bc646d8e7b3af6e7e8c6f7f9dc8 | MATLAB | 2,464 | 77 | % takes each "bout" of activity from frame [C1] to [C2]
% and calculates a running total of df/f over multiple bouts
% input bouts as RxC w C1 = start C2 = end
% make an array to store the integrated bout df/f
% need to find the longest bout to create the array
function[boutArray,boutInteg,CumBoutInteg] = boutDFF(bou... |
ca0fc83b6f609a7c48ada36c4f4872d2ac9002050f7ba4c926569def1f76a958 | MATLAB | 2,464 | 59 | % Marc Normandin, Muzzio Lab, Psychological & Brain Sciences, University of Iowa, 2024
function [s] = load_dataset(folder)
[BestAligned, analysisSettings] = load_best_aligned(folder);
[MapsData] = load_maps_data(folder, analysisSettings);
% Verify the integrity of the data because we have to index between... |
998375deb0271ecda2ed352d8e39ef5f7a18563973f1888382d30efd80366cf7 | MATLAB | 2,465 | 53 | fig = figure;
fig.Units = 'centimeters';
fig.Position = [0 28 22 28];
colours = brewermap(3,'accent');
featurenames = {'LogVariance', 'Skew', 'Kurtosis', 'DeltaV',...
'LogHalfHzPwr', 'Lambda', 'Fiterror', 'DeltaLambda', 'DeltaFiterror',...
'DeltaLogPower', 'ThetaLambda', 'ThetaFiterror', 'ThetaLogPower',...
... |
d737d9a0a8d6e63509ceee0167b6135b8e8f9651e60e3ee3393f426a5c3ca20a | MATLAB | 2,465 | 78 | %run getSpikes
clear all;
globals;
DEBUG=0;
PLOTALL=1; % plot also non significant cases
[spikes, LFP, theta, nose,FPS, Files] = getSpikes('20150906Thalamus36');
Nframes = length(nose.x);
[Nelecs, Nunits]=size(spikes);
if DEBUG,
Nelecs=1; Nunits=1;
end;
tt=0:1/FPS:(Nframes-1)/FPS;
figure(1); clf;
p... |
61c40ef2bd36e170be777763f30b50a934c7ec726e4811786011388d6c8dd3ac | MATLAB | 2,466 | 75 | function lat = fcn_bilaterality(c,hemi,nrand)
%FCN_BILATERALITY measures laterality of partition
%
% lat = fcn_bilaterality(c,hemi,nrand) takes a [node x 1] partition, a
% [node x 1] vector of hemisphere labels (1 = RH, 2 = LH), and a number
% of random permutations. It returns the laterality index from Lohse ... |
c8eadf6de6d4320ffff3909ed7dc0920010408740f12cee18f37a2310b4384da | MATLAB | 2,467 | 76 | % visstimFictrac.m
%
% Trial Type Function
% Presents visual stimulus on G3 panels, records FicTrac behavior data
%
% INPUTS:
% settings - struct of ephys setup settings, from ephysSettings()
% duration - duration of trial, in seconds
%
% OUTPUTS:
% rawData - raw data measured by DAQ, matrix where each column is... |
426411d8e28dd80e008aef947d3237654a3fd88904fca5bed3e035c103e64a49 | MATLAB | 2,470 | 69 | % VL_KDTREEBUILD Build randomized kd-tree
% FOREST = VL_KDTREEBUILD(X) returns a structure FOREST containing
% the kd-tree indexing the data X. X is a M x N dimensional matrix
% of class DOUBLE or SINGLE with one data point per column. Use
% VL_KDTREEQUERY() to query the index.
%
% VL_KDETREEBUILD() accepts ... |
cf1da79b5c91edfa10b406d0420d00f24e858c9f6e3356f00fc3efb1e0af77ca | MATLAB | 2,473 | 80 | %% Set up
clear;clc;
A = chanData;
% open Excel File
A.excelFile = 'C:\Users\Public\RaymondLabCode\Projects\Max - CF Project\Monkey Metadata by Max.xlsx';
%A.excelFile = 'C:\Users\Public\RaymondLabCode\Projects\Max - CF Project\Monkey Metadata by Max (Akira).xlsx';
A.expmt_table = readtable(A.excelFile);
A.expmtDataF... |
5b4cbaad5f41447a1dd64bd0d2007fd1c10ff213fb68c1ab438e9499a084c4cf | MATLAB | 2,474 | 79 | function [A coords] = grid_graph(varargin)
% GRID_GRAPH Generate a grid graph or hypergrid graph
%
% [A xy] = grid_graph(m,n) generates a grid graph with m vertices along the
% x axis and n vertices along the y axis. The xy output gives the 2d
% coordinates of each vertex.
% [A xyz] = grid_graph(m,n,k) generates a ... |
ec6b2423475f0bf51045fe714e7fc2196909dcf49b78e17d9a861e8b49a89146 | MATLAB | 2,474 | 71 | function fH = plotLMMfittedRegressionSlopesCummulative(deltasGroup,deltasSubj, ...
deltasSE,deltaLabels,cmapROIs, saveFigs,saveFigDir)
% Function to plot the cummuluative effect of suppression slopes across the
% visual hierarchy (Suppl Figure 2A)
%% Check inputs
if ~exist('saveFigs','var') || isempty(saveFig... |
77e011f6072712ca2845eb4e266838f3330b764be2a2075e15de24b88191b774 | MATLAB | 2,475 | 78 | function ndx = sub2ind_faster(siz,varargin)
%SUB2IND Linear index from multiple subscripts.
% SUB2IND is used to determine the equivalent single index
% corresponding to a given set of subscript values.
%
% IND = SUB2IND(SIZ,I,J) returns the linear index equivalent to the
% row and column subscripts in the arra... |
78f3ccb3d64e7f7af9bfed5fee2e7b5068d99f2c62c039af836dc5cd4d8abc51 | MATLAB | 2,475 | 104 | %
% Plot the plots for one PA variant.
%
% PARAMETERS
% network
% letter For output filename
% pa_x Curve fitting values (see konect_pa_full.m)
% pa_data_x Plotting data (see konect_pa_full.m)
%
% OUTPUT FILES
% plot/pa.[a...]$letter.$network.eps
%
function pa_plot_one(network, letter, pa_x, pa_data_x)
network... |
d1291c404f17da54c1e22f6b7cd56e1e21c691407328f888ca0773fc4a9bd3da | MATLAB | 2,475 | 76 | function [tok] = tokenize(str, sep, rep)
% TOKENIZE cuts a string into pieces, returning the pieces in a cell array
%
% Use as
% t = tokenize(str)
% t = tokenize(str, sep)
% t = tokenize(str, sep, rep)
% where
% str = the string that you want to cut into pieces
% sep = the separator at which to cut (default ... |
33afff96743b3cfa4de5113b7b8d7e3f36e552af28a3cc4d9f78169392ab5bea | MATLAB | 2,476 | 62 | % Marc Normandin, Muzzio Lab, Psychological & Brain Sciences, University of Iowa, 2024
function [output] = compute_cell_rate_difference_matrix_by_context_v0(firingRates, trialIds, contextIds, rateMatrixNumTrials)
if rateMatrixNumTrials <= 0 || length(rateMatrixNumTrials) ~= 1
error('rateMatrixNumTrials must... |
3d01227c8cf602bc7e8b45dcedd0f3b3a938d4bee2e7351f81873b0388adbadc | MATLAB | 2,476 | 74 | function spm_extract_anatomical_rois(cfg)
% Extracts ROIs from one subject.
% Arguments:
% cfg: A struct with the following fields
%
% target_dir: path to subject's first level analysis
% results.
%
% adjust: 0 to not adjust, NaN to adjust
% ... |
9c8329dbdc2793a73ec26a36a609210ee5ca2b3c5ed5d136168c073c03544ca2 | MATLAB | 2,476 | 74 | function [allAngles, allDistances] = ml_cai_egocentric_compute_distances(mousePosition, mouseHeadingDeg, mouseEgocentricAngles, poly)
Mv = mousePosition; %[mousePosition(2) mousePosition(1)];
mhdr = mouseHeadingDeg;
angles = mouseEgocentricAngles; % egocentric angle 0 corresponds to mouse heading direction
numPoly = l... |
b64e5289080d8fb58df47375604b4b6229c9e558f22a3fb22740760006edc66c | MATLAB | 2,476 | 71 | function [t] = neuralynx_timestamp(filename, num)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SUBFUNCTION for reading a single timestamp of a single channel Neuralynx file
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Copyright (C) 2007, Robe... |
d640af661cb84efd50f0999f15f849c9b0e2971ca2c214e3f4a3e2103950e37b | MATLAB | 2,476 | 78 | % saveAllKernels.m
%
% Function to compute kernels for all selected date directories.
% Calls extractAllKernels()
%
% INPUT:
% dateFolderPaths - [] if gui to select one date folder; otherwise,
% cell array of full paths to date folders
% winLen - length of window, in seconds that averages are computed over
% ... |
a2314f068a7d1a13dfd3100e48e4cb4efc66d4887834970082821d0d41a12408 | MATLAB | 2,478 | 86 | function output = pomdp_observer(stimulus_sequence,sigma,alpha_pos,alpha_neg,...
softmax_temperature,memory_strength_positive,memory_strength_negative,value_init)
% reward storage
reward = zeros(length(stimulus_sequence),1);
% response storage
response = zeros(length(stimulus_sequence),1);
% value storage
value ... |
55a61413f5e51d0edbb26158cb9fbdcdcf046efa87a2d8a8490f10093bf2713e | MATLAB | 2,480 | 60 | function success = calculate_behaviors(folder_name)
% given tracks that has embeddings, classify every time point into a
% behavior
addpath(genpath(pwd))
%set up parameters
parameters = load_parameters(folder_name);
if parameters.TrackOnly
success = true;
return
end
load('referen... |
bbad392a0c990b9e97ee5beb80f1022cd8381165144dd79739705ed859a9ad9c | MATLAB | 2,480 | 82 | function [trainingSetData,trainingSetAmps,projectionFiles] = ...
runEmbeddingSubSampling(data,parameters)
%runEmbeddingSubSampling generates a training set given a set of .mat files
%
% Input variables:
%
% data -> spectralgram
% parameters -> struct containing non-default choices for paramete... |
9e16f624109130e7d9a69c3edec424d1f9c0cd51fdeb07dcbed8050ae99f9b2e | MATLAB | 2,481 | 75 | clear;
ft_path = '/Users/wenwen/Documents/MatlabToolbox/fieldtrip-20240704';% require fieldtrip toolbox
addpath(ft_path);
ft_defaults
txtCell = {'','','','';'_lap','_dephase','_corrTrials','_bl2preDelay'};
subj_files = {'DMSS053_resp_LCMV.mat','DMSS056_resp_LCMV.mat','DMSS061_resp_LCMV.mat'};
%%
for s = 1:le... |
8af8999c55a2c0b9f451a213399f051bdb97efa0d3bc0af46e4b1599afa7040d | MATLAB | 2,483 | 68 | %% binary_classification to HC and MS with edge
roi_num = 48;
load('group_data_DBM.mat')
edge_data = cat(3,data.HC,data.MS,data.NMO);
net_mask = logical(tril(ones(roi_num),-1));
Features = zeros(size(edge_data,3),sum(net_mask(:)));
for isub = 1:size(edge_data,3)
edge_data_i = edge_data(:,:,isub);
Features(isu... |
9192f0e177974b482ca075f3e05017af239479e19c2e55bd92409620c0f77815 | MATLAB | 2,483 | 48 | function test_on_single_vnc_experiment()
% Where does this script live?
this_script_folder_name = fileparts(mfilename('fullpath')) ;
flytracker_folder_path = fileparts(this_script_folder_name) ;
flydisco_folder_path = fileparts(flytracker_folder_path) ;
flytracker_test_files_folder_path = fullfile(... |
e08c21f1134421b83484f1d18fab7b09ebbb3af91e7bf3fe39f95a50de6bdd2c | MATLAB | 2,483 | 56 | function [order_in, order_out, frac_X] =...
spreading_func(aij, data_run, seed)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% If you use this code, then please cite:
% 1.- Ana P. Millan, et al. "Individualized epidemic spreading models
% predict epilepsy surgery outcomes: a pseudo-prospective s... |
ab558ad2a9714415f0f012d44e47150d1de204237c80de7fdbd58f059b3f423d | MATLAB | 2,484 | 82 | % VL_DEMO_DSIFT Demo: DSIFT
randn('state',0) ;
rand('state',0) ;
% read a test image
I = imread(fullfile(vl_root,'data','roofs1.jpg')) ;
I = single(vl_imdown(rgb2gray(I))) ;
% --------------------------------------------------------------------
% Basic benchmark
%... |
8745e82bfa03e13f37c2e6e8f4e6deb4ad3ef6a26c937fc82c37d0300448975d | MATLAB | 2,485 | 68 | %% binary_classification to HC and NMO with edge
roi_num = 48;
load('group_data_DBM.mat')
edge_data = cat(3,data.HC,data.MS,data.NMO);
net_mask = logical(tril(ones(roi_num),-1));
Features = zeros(size(edge_data,3),sum(net_mask(:)));
for isub = 1:size(edge_data,3)
edge_data_i = edge_data(:,:,isub);
Features(is... |
8ee77229cba8e382fd85e736d2bed91cc3344093f8d05dccec8835e559c780e7 | MATLAB | 2,485 | 65 | %%Data for this tutorial is available here: dx.doi.org/10.6084/m9.figshare.26597269
%% Tutorial
clear all
close all
%% Step 1: Load data
%Here we are loading a raster that has been downsampled from 18 to 1 kHz
%Data was initially processed with a second-order bandpass Butterworth
%filter in the forward and re... |
0571c957cdff330f6dc307057da9c57306302cf07821fbcbc16234749d6d9fb2 | MATLAB | 2,486 | 68 | %% binary_classification to NMO and MS with edge
roi_num = 48;
load('group_data_DBM.mat')
edge_data = cat(3,data.HC,data.MS,data.NMO);
net_mask = logical(tril(ones(roi_num),-1));
Features = zeros(size(edge_data,3),sum(net_mask(:)));
for isub = 1:size(edge_data,3)
edge_data_i = edge_data(:,:,isub);
Features(is... |
5db609ed2a5ba6a29e61df64733f9adc222ce5578a7eb72e57abc7377e0fab9f | MATLAB | 2,486 | 103 | function [C, KSq] = conv_kernel_rot_c0(Params, R, datatype, kerneltype)
% [C, KSq] = conv_kernel_rot_c0(Params, R, datatype, kerneltype)
% Author: Xu Li
% Affiliation: Radiology @ JHU
% Email address: xuli@mri.jhu.edu
%
% Updated X.L., 2019-07
% Updated X.L., 2020-10-10
if nargin < 3
datatype = 'double';
kerne... |
922be5d0a16d5e3f5b2995e970f4b59320f301492678ae9641948ae590187a14 | MATLAB | 2,488 | 70 | function [output,metaStruct] = TDMS_getStruct(filePath,structVersion,readOptions,structConvOptions)
%TDMS_getStruct A wrapper for simplifying data retrieval from TDMS_readTDMSFile
%
% output = TDMS_getStruct(*filePath,*structVer,*readOptions,*structConvOptions)
%
% OPTIONAL INPUTS
% =======================... |
e0444334f89d495218aef123e4b3eefa97fe6927d32dd79e1dd8b510f8f68ac0 | MATLAB | 2,488 | 68 | %% para
path = pwd;
load('node_name')
load('Edge_compare_DBM.mat')
load('group_data_DBM.mat')
fdr = 0.05;
p_correct = 1/1001;
post = struct;
%% tidy
PT_FDR = gretna_FDR(results.TFNBS_t_pval_sig_edge + p_correct,fdr);
if isempty(PT_FDR), PT_FDR = -1; end
for i = 1:results.N_sig_edge
post(i).data = {squeeze(data.... |
b46fdf05ed9925ee73eb2164ee0a2cfbe5116b4c79a647749e588a3ddc5704c3 | MATLAB | 2,489 | 70 | function [ anon ] = createAnonymized( obj )
% CREATEANONYMIZED
% Import and Anonymize Medtronic Percept PC json files
% This funtion anonymizes selected parameters from json files, Percept PC.
% The variables are the following:
% from Patient Information Initial / Final:
% PatientFirstName
% PatientLastName
% PatientG... |
dce91ad17066a040a4210b40f2b3a920094d6a59c07dc1a3dd6517bb1cd1bfe6 | MATLAB | 2,489 | 82 | % plotAllKernels.m
%
% Function to plot all kernels. Also shows variance explained. Generates
% separate plots for spikeRate and medFiltV.
% Requires the structs generated by computeKernels_pData()
%
% Adapted from plotAllKernels() in 2PAnalysisCode-Helen
%
% INPUT:
% kernels - kernels struct from computeKernels_pDa... |
fc34fabd17f108fbbc203e844ae22e9b07dcb357020f64fda1c40149c39c3c98 | MATLAB | 2,490 | 112 | function bw_out = aedes_roifill(bw,seed)
% AEDES_ROIFILL - Do flood fill operation (4-conn) for binary image
%
%
% Synopsis:
% bw_out = aedes_roifill(bw_in,seed);
%
% Description:
% Flood fill operation (4-connected) for binary 2D images.
%
% Examples:
%
% See also:
% AEDES
% This function is a p... |
2bd7f3d62472653e011840c61ad4d3d6bf2274efec464d3c4dfb0bde85d17d9d | MATLAB | 2,493 | 42 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%% Install NAOMi Simulation %%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%... |
7c837025b79ff0ce1d57828827eff491038aa4eae310c93c617b4646808916fa | MATLAB | 2,493 | 60 | %% Restable nogocue
clear
file=dir('ACC*restable*.mat');
k=1;
for jj=1:length(file)
load(file(jj).name)
n=length(outcome);n1=fix(n*0.15);
early=[find(outcome(1:n1,1)==3);find(outcome(1:n1,1)==4);];%early phase
late=[find(outcome(n1+1:n,1)==3);find(outcome(n1+1:n,1)==4)]+n1;%late phase
for... |
8186dc3dafd28e78e26ce2c9933651a553d83854235cc8a33b040631173ce9d7 | MATLAB | 2,493 | 68 | function fH = plotpRFModelcvR2Distributions(diffR2Resampled)
r2bins = -100:5:100;
clear histR2 h
for sj = 1:length(subjnrs)
for idx = 1:length(roisToPlot)
for mm = 1:3
if sum(isnan(diffR2Resampled(sj,idx,mm,:)))~=length(diffR2Resampled(sj,idx,mm,:))
h = histogram(squeeze(d... |
e3a42524616e2150b25add94875f0442e923f08b1d363baaa94b6ee411a86898 | MATLAB | 2,494 | 72 | function cfg_artifacts=st_repair_grid(cfg_artifacts)
% ST_REPAIR_GRID determines the repair grid/matrix
%
% Use as:
% cfg=st_repair_grid(cfg)
%
% Required configuration parameters:
% cfg.grid = structure containing segment-based artifact grids
%
% Output:
% cfg = artifact configuration with... |
ec8f54ce35b4a8fe9f28a7f7b240fd5dcf8d7c71f3c5563c09f5f75e5173b868 | MATLAB | 2,495 | 78 | function imdb = setupCaltech256(datasetDir, varargin)
% SETUPCALTECH256 Setup Caltech 256 and 101 datasets
% This is similar to SETUPGENERIC(), with modifications to setup
% Caltech-101 and Caltech-256 according to the standard
% evaluation protocols. Specific options include:
%
% Variant:: 'caltech256'
... |
a7187ed8cf346d558d633e21a3502737c51307e4c2c7ae4b970c4acc995b8fa0 | MATLAB | 2,496 | 67 | function logfile = importfile_logfilenew(filename, startRow, endRow)
%IMPORTFILE Import numeric data from a text file as a matrix.
% S1LOGFILE = IMPORTFILE(FILENAME) Reads data from text file FILENAME for
% the default selection.
%
% S1LOGFILE = IMPORTFILE(FILENAME, STARTROW, ENDROW) Reads data from rows
% ... |
c78e47d8c37185ac7c50daa23cacce2440ede474476c509ed1c67619d3f2d9c9 | MATLAB | 2,496 | 74 | function vl_demo_gmm_3d
% VL_DEMO_GMM_3D Show how to initialize GMM learning with a custom set of modes
%% Initialize points clustered in 3D
numClusters = 5 ;
dimension = 3 ;
cc = hsv(numClusters) ;
randn('state',0) ;
X = [] ;
for i=1:numClusters
delta = 5*[i;0;0] ;
%num = ceil(1000 / i) ;
num = 500 ;
s = di... |
d31049af63502e4d7986b12829df49626be32370928812bbe545ff77ba5e196f | MATLAB | 2,496 | 86 | %% corr the coupling R2 or P-value with gene expression via PLS
%% para
path = pwd;
pls_dim = 1;
roi_num = 48;
rand_time = 10000;
p_thr = 0.05;
gen_results = struct;
%% data
% AR data
load('Edge_GLM_gene_str_dis_commu_DBM.mat')
roi_index = cat(1,results(:).roi);
AR = cat(1,results(:).AR);
AR_p = -log10(cat(1,result... |
f96f2f3f20d2e2f2d4a7eddf8218f47a349fb83bba0f9aa579efd161b583bcf4 | MATLAB | 2,496 | 74 | %{
Copyright (C) Cambridge Electronic Design Limited 2014
Author: James Thompson
Web: www.ced.co.uk email: james@ced.co.uk, softhelp@ced.co.uk
This file is part of CEDS64ML, a MATLAB interface to the SON64 library.
CEDS64ML is free software: you can redistribute it and/or modify
it under the t... |
0ff72afd0df70a4c7040e2eb1e8ff8763bb9ed66333ee0c3cccf0a4474dd9b2a | MATLAB | 2,497 | 46 | function mltp_plot_bfo_90_wc(obj)
numAngles = 4;
best_fit_orientations_within_contexts = zeros(obj.Experiment.getNumSessions(), numAngles);
plotlegend = cell(obj.Experiment.getNumSessions(), 1);
for iSession = 1:obj.Experiment.getNumSessions()
session = obj.Experiment.getSession(iSession);
... |
8e29d73a6ebdd925c43a8a3869bb3fa403a81ae1f5d10f48d3888a0f37d8448c | MATLAB | 2,497 | 60 | function SONLoad()
% SONLOAD loads the son32.dll library and defines global constants
%
% Version 32 of the SON library works only under Windows and requires
% version 7 of MATALAB and a copy of CED's son32.dll.
%
% The routines use CEDs son32.dll to provide I/O. This file must be present
% in a 'c:\Spike5' directory (... |
75412293f7a919cbdda0696b1fa9b27d8b3e95bb136e8b73d77c0c29e0cd86f6 | MATLAB | 2,498 | 76 | function [paths,pathnums] = dilateDendritePathAll(paths,pathnums,obstruction)
% [paths,pathnums] = dilateDendritePathAll(paths,pathnums,obstruction)
%
% Function to simultaneously dilate all the dendrite paths in the volume.
% This function looks for empty space around the established dendrite
% positions to allocate ... |
5093438978686beebe464fccae876de245e7aca26fe0054f9fbf192133d73956 | MATLAB | 2,499 | 57 | function plot_avg_burst_rate(burst1_rates, burst2_rates, channel_id, lbl_opt)
%% Function: 'plot_avg_burst_rate'
% DESCRIPTION
% Plots trial-averaged burst occurrence rates of two conditions or
% groups
% USAGE
% Full Input : plot_avg_burst_rate(burst1_rates, burst2_rates, channel_id, lbl_opt)
... |
f79827472509eba7d6b645c4a027b5e456acb3bd4f9e48f30381b95906b37ed7 | MATLAB | 2,500 | 72 | function grad = fif2grad(filename)
% FIF2GRAD constructs a gradiometer definition from a Neuromag *.fif file
% The resulting gradiometer definition can be used by Fieldtrip for forward
% and inverse computations.
%
% Use as
% grad = fif2grad(filename)
%
% See also CTF2GRAD, BTI2GRAD, MNE2GRAD, ITAB2GRAD, YOKOGAWA2GRAD... |
46b7b6691237d1150cc70878266cc9be1f765beebc8aeb99d2bae5ae8c68ce4e | MATLAB | 2,501 | 69 | %% Fig3E
% Examples of FI and FS cells
data_path = '/Users/celia/Documents/two_context_data'; % change this
cal = load(fullfile(data_path, 'calcium_20220516_170618/analysis_results.mat'));
tet = load(fullfile(data_path, 'tetrodes_20220316_100902/analysis_results.mat'));
best_aligned = [cal.analysisResults.BestAligned... |
f3bdcf7327a59e8040679f8abde7a6d9c44ceb074839e03651a42e105d63a4a9 | MATLAB | 2,501 | 92 | function polarPlotVectorsMean(File)
% open up csv file containin the gain and phase
[~, ~, array] = xlsread(File);
[row, ~] = size(array);
rLimits = [0, .62];
myfig = figure();
% cycle through each entry and plot them on one
% polar figure
for i = 1:row
% get Title ( optional)
% theTitle = vals(((i-1) * 4... |
c37af675a887378b947ab87bbe3cdf3b5b46419e69aa5bcbea42fd7c98c9e214 | MATLAB | 2,503 | 73 | function [indx] = labelcmb2indx(labelcmb, label)
% LABELCMB2INDX computes an array with indices, corresponding to the order
% in a list of labels, for an Nx2 list of label combinations
%
% Use as
% [indx] = labelcmb2indx(labelcmb, label)
% or
% [indx] = labelcmb2indx(labelcmb)
%
% Labelcmb is an Nx2 cell-array wit... |
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