sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
b5196673b256616cb4a402a84d56f9e9709b4049341552a2f3b833b65389dff9 | MATLAB | 3,261 | 80 | function plot_stage_burst_rate_band(br1_stage, br2_stage, channel_id, lbl_opt)
%% Function: 'plot_stage_burst_rate'
% DESCRIPTION
% Plots burst occurrence rates of two conditions or groups per
% frequency band, averaged over each task stage
% USAGE
% Full Input : plot_stage_burst_rate_band(br1_... |
afa21d11168bc05ae826a7353d8d189bdfce7e00c4f99ff390bb3540bfda0a6a | MATLAB | 3,262 | 74 | function subject_power_2014_FD_only_parse_v3(movement_files,skip_seconds,epi_TR,expected_contiguous_frame_count,varargin)
% FD parsing Nipype wrapper pulling in list of motion files
% Modified to read DVAR_pre_reg, DVAR_post_reg, and DVAR_post_all and store
% values appropriately in the 51x51x3 cell array of structs
%
... |
a824477f6e55dd7d015fad5c82a7205de9aea29c3b6f0a3375648d0413dd48e8 | MATLAB | 3,264 | 98 | %Test FclustGRP function
%
%AUTHOR: Eric Fields
%VERSION DATE: 12 June 2020
global test_xls_output;
if isempty(test_xls_output)
test_xls_output = true;
end
%Load GRP
FMUT_dir = fileparts(fileparts(which('A_setupTest')));
load(fullfile(FMUT_dir, 'testing', 'data', 'Disflu_GroupLevel.GRP'), '-mat');
... |
16a3005ae3c982053d0810e4251cdb20f8784a7e5f1fbdfb036a1ef9ef5def49 | MATLAB | 3,265 | 126 | function [vol, M, tmpdcminfo, mr_parms] = load_dicom_series(seriesno,dcmdir,dcmfile)
% [vol, M, dcminfo] = load_dicom_series(seriesno,<dcmdir>,<dcmfile>)
%
% Reads in a dicom series given:
% 1. The series number and directory, or
% 2. A dicom file from the desired series
%
% If the series number is given but no dcmdi... |
cf4300837cf5e7384cb549294ea5d2dbdf1cce299f836f4c872267a1eb90e8c6 | MATLAB | 3,265 | 99 | clearvars; clc;
num_data = readmatrix("data_mod.csv");
Mean = mean(num_data, 'omitnan');
sd_data = std(num_data,'omitnan');
% Statistical analysis for 2 Hz stimulation
data1 = num_data(:,5);
data2 = num_data(:,6);
% Combine the data and create a grouping variable
allData = [data1; data2];
group = [ones(siz... |
20dd0b03390ef88fa857e6ae041a23c9798c5db308c16f34bf3b9469406cb8d4 | MATLAB | 3,266 | 138 | function hdr = load_analyze(imgfile,hdronly)
% hdr = load_analyze(imgfile,hdronly)
%
% Loads analyze volume and header. The volume is stored
% in hdr.vol. It is not permuted to swap columns and rows.
%
% hdr.dime.dim(1) = number dims
% hdr.dime.dim(2) = number of items in first dim
% hdr.dime.dim(3) = number of items i... |
79576d4f0955001619356ad4393b9476389fe6691c495744492e1142765d5703 | MATLAB | 3,266 | 88 | classdef ProcessingModule < types.core.NWBContainer & types.untyped.GroupClass
% PROCESSINGMODULE A collection of processed data.
% OPTIONAL PROPERTIES
properties
description; % (char) Description of this collection of processed data.
dynamictable; % (DynamicTable) Tables stored in this collection.
nwbd... |
9e37693c7e779170e566ba6d42c7a43c290e6ac43d980c7c0320c7b0fca6df38 | MATLAB | 3,268 | 96 | function [xnora dur amp durprot velprot set np durd]=cycdur(x);
% cycle-based duration
% values are for the cycle strting at the neg peak (np)
% durd: finds neg peaks (np), compute the diff between them (in samples)
% dur = interp1(durd) for the length of x
% nora - x, where each cycle is normalized between 0 and ... |
2232c9c134d7bacf1302a33b7fdc921977b98cf1849de4d80b670f38c115f0c3 | MATLAB | 3,269 | 85 | % This script performs magnetic field computations for a single volumetric
% ring with M wires and compares the result with the analytical
% solution
%
% Copyright SNM 2018-2019
clear all; %#ok<CLALL>
if ~isunix
s = pwd; addpath(strcat(s(1:end-5), '\Engine'));
else
s = pwd; addpath(strcat(s(1... |
f4c1b59dd1b2d000cf45f28a44a1c6445120c7e6606d8334afce96fa9b196459 | MATLAB | 3,269 | 93 | function [m_out] = noise_suppress(m_in, maxall, Fs, nflag, filename)
% batch version of anisotropic diffusion & background removal
% Jinghao Lu, 11/18/2019
h = tic;
if nargin > 4 && ~isempty(filename)
msg = 'Overwrite post registered .mat file (data)? (y/n)';
overwrite_flag = true; % jud... |
ceeada29f097af19e177fefc74e9690b4e86c58072b2fa1162817a6c3371bb7c | MATLAB | 3,270 | 134 | % This script will clean the data set
%% Check for columns with no non-zero elements
[l,w] = size(all_lesions);
del_store = [];
for col = 1:w
non_zeros(1,col) = nnz(all_lesions(:,col));
if nnz(all_lesions(:,col)) < 25
display(['Less than 10% of entries for column ', num2... |
d16dcffb8bb1bba0fe5c89c1af74c6149c93aa8d8e47d6f406022dbfcf8a5523 | MATLAB | 3,270 | 82 | function saveSimulationParts(fullFileName)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Get basic data and load the .mat file
fprintf('Loading mat file...')
fileBase = fullFileName(1:end-4);
m = matfile(fullFileName);
fprintf('done.\n')
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
e2064e5f07e51b550693ef2cdaf3442bf374f28a053f74ebf66033042538f9da | MATLAB | 3,270 | 134 | function plot_velocity_event(velo,ds_events,t,save_yn)
frames=size(velo,3);
num_ds=size(velo,1);
med= median(1:frames);
scaled_start=med-60;
scaled_end= med+120;
%% PLOT VELOCITY DURING EVENTS
figure(99)
clf
set(gcf,'color','w')
% SOM events ---
x = linspace(1,frames,frames)';
y = squeeze(nanmean(velo(:,1,:)... |
d353435b82637bae132991f088cdde3cbe6454e43db1f78c3f4c6f76bf68cc5e | MATLAB | 3,280 | 98 |
function [labeledFrame avCount Av] = updateLabels(Av, labeledFrame, currentTime, currentClusters, prevActive, network, avCount )
t = currentTime;
for i = 1:length(currentClusters)
c = [currentClusters{i}];
%
%first get the active parents
parentcluster = getActiveParent... |
a63e0e58da4a3c00e52401aa4051c0914eb6d7d63d55fe70d4cd78cec41f6534 | MATLAB | 3,282 | 78 | function [psf,x,y,z,intensity] = gaussian_psf_na(na,lambda,sampling,matSize,theta,nidx)
% [psf,x,y,z] = gaussian_psf(psflen,lambda,sampling,matSize,theta)
%
% This function provides a sampled point-spread function (PSF) for use in
% the scanning simulation. Specifically, this function generates Gaussian
% shaped PSFs... |
77edfe2d6affa3cdf90b2a1930cfd9f4039e4f94af678b5faa7a56980c07f9c8 | MATLAB | 3,283 | 92 | load 200128_10s.mat;
load 200128_attention_weights.mat;
%% Visualize attention weights color coded by the sleep states
NREMepochs=find(y_preds==1);
REMepochs=find(y_preds==2);
Wakeepochs=find(y_preds==0);
for i = 1:size(att_weights, 1)
att_weights(i, :) = rescale(att_weights(i, :), 0, 1);
end
%att_weights = resha... |
1abbf52e16fcf5d8b005f9c0ac6effb8e34bde942d891a06ec7748aebd5f2390 | MATLAB | 3,285 | 88 | %confocal scan
f_fin_0 = OPT_S.f_fin.*SC.mask_f_laser;
fx_laser_0 = SC.ramps.fx_laser;
fy_laser_0 = SC.ramps.fy_laser;
fx_cam_0 = SC.ramps.fx_cam;
fy_cam_0 = SC.ramps.fy_cam;
%% confocal settings
n_conf = FOV.n_conf;
d_conf_x = FOV.d_conf_pix;
d_conf_y = FOV.d_conf_pix;
N_conf_x = 2*FOV.n_conf+1;
N_conf_y = 2*FOV.n... |
080d5ff7e12d1c983beae0f7f9df08b2e507e5fa3e8ef9838ebcfd54274cbd2d | MATLAB | 3,286 | 88 | % function invcompE(tol,N)
%
% tol is the absolute tolerance in ms
%
% Two event time (ms) values u and v are within tolerance if:
% abs(u-v) <= tol
%
% A good value for tol is 1.2 ms
%
% The input argument N should be the total number of detections possible.
% N is used in the calculation of TN. If no N argument is... |
280e5e684fc33b7872f23191273f577b99d7a36783d4bb92b8b48e4a336a7119 | MATLAB | 3,287 | 114 | % plotSpikesStepPhase.m
%
% Function to plot timing of spikes relative to leg phase, at different
% time offsets between ephys and behavior. I.e., plots the output of
% getSpikesStepPhase_cell(), but combining multiple flies.
% One figure per delay; 6 subplots, 1 for each leg per figure
%
% INPUTS:
% datDir - direc... |
2ee9944f11894c78aa019a00e08d6d288d2841eff48efe552601cb1a9cfb5c4a | MATLAB | 3,291 | 87 | %% This script computes Membrane Potential (Vm) and Membrane Resistance (Rm) in CC_AS protocol Recordings
% ==================================================
% Authors: Arash Samiee, Knut Kirmse
% last modification: 01/2023
% ==================================================
% How to use:
% (1) Specify paramete... |
3817173cb36ec83f6b49dee72c1d432c85062327e879dc351f17267646ad2d3b | MATLAB | 3,292 | 72 | function [HiddenMarkovModels, info] = HiddenMarkovModel_trn_cross(emission_sequence_cross, number_of_states, number_of_start_condition, init, tol, maxiter, parfor_enabled,info, str_save_append)
%% This function trains Hidden Markov Models (HMMs) using cross-validation.
%% authors: Stefano Diomedi
%% date: 22nd Febr... |
9faba0faca0d038e072ce6646a003ea70e86ecd82280a95608b6b5f151eb4574 | MATLAB | 3,295 | 86 | classdef Images < types.core.NWBDataInterface & types.untyped.GroupClass
% IMAGES A collection of images with an optional way to specify the order of the images using the "order_of_images" dataset. An order must be specified if the images are referenced by index, e.g., from an IndexSeries.
% REQUIRED PROPERTIES
prope... |
13dd3c2e2652e4bb307fa314f71c4f8ed37d3ebe7120992e22c6620d79400885 | MATLAB | 3,298 | 64 | % %%creation of file containing three tables
% % save tables from analysis
% save('unitsTableOF_NoseO.mat');
% save('unitsTableOF_NoseDO2.mat');
% save('unitsTableOF_NoseV.mat');
% % load 3 tables and save in one file
% load('unitsTableOF_NoseO.mat');
% load('unitsTableOF_NoseDO2.mat');
% load('unitsTableOF_Nos... |
1e1fb9fa2735e3a97a18cbe23d48725809528d45cb0e98da37e4eea08170fdf8 | MATLAB | 3,298 | 118 | % writeCFS.m
% prompts to write a CFS file - needs all data to be available first
% needs cfs32.dll and MATCFS32.dll
% 06 Mar 09: version 1 jgc
% 9 May 09: define other
% 17 June 09: transpose vector if not correct dimensions
INT1=0;
WRD1=1;
INT2=2;
WRD2=3;
INT4=4;
RL4=5;
RL8=6;
LSTR=7;
EQUALSP... |
aaa025fa95397cc697304be88f7d8cdab3ce3b37813d604300b3b5e7dceb839d | MATLAB | 3,298 | 75 | function varargout = spm_brainwarp(varargin)
% Part of nonlinear spatial normalisation - a compiled routine
%_______________________________________________________________________
% [Alpha,Beta,Var] = spm_brainwarp(VG,VF,Affine,basX,basY,basZ,...
% dbasX,dbasY,dbasZ,T,fwhm,VW,VW2)
% V... |
007a2c5e6594fc288cf8a93236e5adf9119e9523b93750c879733e16221bba71 | MATLAB | 3,301 | 64 | function P = check_free_T(T_s,edges_s,edge_type,P)
% check which triangles formed by spectrin bundles (edge_type = 0 ) do not have myosin
% attached.
P.myosin_Tfree = [];
for l = 1:size(T_s,1)
aux_e1 = find(edges_s(edge_type == 0,1) == T_s(l,1) & edges_s(edge_type == 0,2) == T_s(l,2));
if ~ise... |
2abaff82aadf116c351f866ab79da090ddd447b0e3278d9e933c4a455c72a212 | MATLAB | 3,301 | 97 | function [ACTIVITY, MOBILITY, COMPLEXITY,m0,m1,m2] = hjorth(S,UC,A)
% HJORTH calculates ACTIVITY, MOBILITY, COMPLEXITY
%
% [ACTIVITY, MOBILITY, COMPLEXITY] = hjorth(...)
%
% [...] = hjorth(S,0)
% calculates stationary Hjorth parameter
% [...] = hjorth(S,UC) with 0<UC<1,
% calculate... |
d966afae9a343e4837f4b06b0bebc550444bf5b0d6c475a14d2694c80e39eb00 | MATLAB | 3,303 | 122 | % plotContLegStepParamCond_bouts_ipsiContra.m
%
% Function to plot overlay of ipsi and contra legs for output of
% saveContLegStepParamCond_bouts(), 1 file.
%
% INPUTS:
% whichParam - name of parameter to plot
% datDir - directory with output files
% yScale - y scale for plots, as [min max]
% semError - boole... |
6a4d6fe2282066e97ce78750e14fdf18b99db38fe24eb43741f284acb125f81b | MATLAB | 3,304 | 120 | % Marc Normandin, Muzzio Lab, Psychological & Brain Sciences, University of Iowa, 2024
function [hFig] = plot_normal_bfo90_table_all(NormalBFO90, DaysToSessions)
SessionsEarly = DaysToSessions(ismember(DaysToSessions.dayNum, [1,2]),:);
MatchEarly = get_match_table_by_sessions(SessionsEarly, NormalBFO90);
... |
3dce34b88be0a3f67531fbce03cbf0ccdba1cfa67b72bc7a2416d24c6a396c57 | MATLAB | 3,306 | 89 | function out = toUint8(img)
% Convert a gray (HxW) or RGB (HxWx3) numeric image to rounded uint8
%
% function out = webupload.toUint8(img)
%
% Purpose
% Pure (no I/O). The image must be at least 2x2: vectors and scalars are not images.
% Classes: uint8, uint16, int16, single, double; others ... |
4bf162d6b2741958bab0d515912a70567574f5a1dec631c4070b433d9c9a8a92 | MATLAB | 3,308 | 120 | function [M_V] = vox2ras_ksolve(M_R, Vc_Ps, varargin)
%%
%% NAME
%%
%% vox2ras_ksolve.m (vox2ras_k{-space column}solve)
%%
%% AUTHOR
%%
%% Rudolph Pienaar
%%
%% VERSION
%%
%% $Id: vox2ras_ksolve.m 8776 2013-11-14 09:04:48Z roboos $
%%
%% SYNOPSIS
%%
%% [M_V] = vox2ras_ksolve(M_R, Vc_Ps, Vr_logicalSpace)
%%
%% ... |
b31ba8cfa6f03c04e6fdaa856b9035de0763ed848ae731a73e5117a9be59adc7 | MATLAB | 3,308 | 76 | function subject_power_2014_FD_only_parse_v3_gaby(movement_files,skip_seconds,epi_TR,expected_contiguous_frame_count,varargin)
% FD parsing Nipype wrapper pulling in list of motion files
% Modified to read DVAR_pre_reg, DVAR_post_reg, and DVAR_post_all and store
% values appropriately in the 5 1x51x3 cell array of stru... |
3a1746f57f6c080ac57dd11536ffe85d21a19fd9b11845fb909bdca3af66ecb4 | MATLAB | 3,310 | 88 | %Calculate the Greenhouse-Geisser, Hyunh-Feldt, or lower bound estimate
%of epsilon at all time points and electrodes
%
%EXAMPLE USAGE
% >> epsilon = estimate_epsilon(data, [], 3, 'gg');
%
%REQUIRED INPUTS
% data - An electrode x time points x conditions x subjects array
% of ERP data... |
0dfd30509e024e8103903e4b951d442f699d1b3d80545fbcf5811623e67e997e | MATLAB | 3,311 | 102 | % mglGetMouseEvent.m
%
% $Id$
% usage: mglGetMouseEvent(<waitTime>,<getAllEvents>)
% alt usage: [buttons when x y] = mglGetMouseEvent(<waitTime>,<getAllEvents>)
% by: justin gardner
% date: 09/12/06
% copyright: (c) 2006 Justin Gardner, Jonas Larsson (GPL see mgl/COPYING)
% purpose: retur... |
3204b9fc1a9fb3100326644ee6454aead61bbb3f2dec3ea3cbd49f548c8f2a97 | MATLAB | 3,311 | 114 | % 1_190129_150035.rhs IS THE IN VIVO FILE
%% Setup
clear;clc;close all
dbstop if error
% Load file 19 11 31 3
folder = 'G:\My Drive\Expmt Data\MultiElectrode Data\In_vivo_Cerebellar_Vermis_Exp3and4\New folder';
% Remove everything that is not an .rhs file
recFiles = dir([folder '\**\*.rhs']);
% Window around Stim A... |
3bdd683d38aff3395ec9c84bc83940cac12c1cf46d84f81f301d15a528b81178 | MATLAB | 3,311 | 105 | function [nse] = read_neuralynx_nse(filename, begrecord, endrecord)
% READ_NEURALYNX_NSE reads a single electrode waveform file
%
% Use as
% [nse] = read_neuralynx_nse(filename)
% [nse] = read_neuralynx_nse(filename, begrecord, endrecord)
% Copyright (C) 2005-2007, Robert Oostenveld
%
% This file is part of Field... |
7d362b8f7e4a59d8fa649ea44a09293a27ccbc60a4da3a0ef038348e49b81d6d | MATLAB | 3,311 | 76 | % Marc Normandin, Muzzio Lab, Psychological & Brain Sciences, University of Iowa, 2024
function [predictionDataset] = filter_prediction_dataset(predictionDataset, params)
nRows = size(predictionDataset,1);
nCellsBeforeFiltering = nan(nRows,1);
nCellsAfterFiltering = nan(nRows,1);
emptyRows = [];
fo... |
070050cd7278150066979fc05064131da92ea72c5210404783bcf09a8e3a8765 | MATLAB | 3,313 | 104 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Code for the numerical simulations and computational results
% in the manuscript "Fibromyalgia pathogenesis explained by
% a neuroendocrine multistable model"
% by Ilaria Demori, Serena Losacco, Giulia Giordano, Viviana Mucci,
% Franco Blanchi... |
633f87694a5c3bc06b1f262e67c3e0ac776af6319a02accabba1142fe1e9c8f5 | MATLAB | 3,313 | 86 | function result = filterI2MC(raw_data, opt)
% FILTERI2MC Find the fixations in eyetrackingdata with the I2MC algorithm.
% The function makes the algoritm written by Hessels et al compatible
% with the functions used in this project.
% The I2MC algorithm was designed to accomplish fixation detection in... |
d12e7c58f0f8cbc71ba564efba9575c3b6459ac67a2d4a5b0888e0a031c23b49 | MATLAB | 3,313 | 47 | % The script "demo_UFARSA_realData.m" applies UFARSA to the "sample_data.mat" file containing a number of fluorescence
% traces (i.e. time-courses), which can be assumed to be extracted from different region of interests (ROIs). Simply run
% this script and see UFARSA's spiking activity reconstruction results for th... |
bdfe1b611025c049ff8447cde5d0386b447c210a94cc3047b2946daf7bc15f30 | MATLAB | 3,314 | 100 | % This example takes in a hexagonal shape and varies the spacing from 0 to
% a specified amount. The number of channels, brain sensitivity, and
% spatial multiplexing groups are calculated for each spacing.
clear all
% Lumo modules
probe.module = createModule(6, 18);
y1 = 10;
probe.module.srcposns = [0, ... |
07a27f8907f6fa9c8c3da3da10518afdf0ea8f2369880d091926e45f64bfc383 | MATLAB | 3,320 | 92 | function gretna_Sim_PDF_matrix(Data_path, File_filter, Npoints, PDFType, SIMType)
%==========================================================================
% This function is used to calculate similarity among different probability
% distribution functions based on the Jensen¨CShannon (JS) divergence,
% Kullback¨CLe... |
21d5d21d7b371a33b6a78efc1f6f14f2ab4582bce5bda2443984ceff37a9b71a | MATLAB | 3,320 | 131 | function chi_S = SFCR_s_SB(deltaB, D_k, DPWeight, maskErode, maskSSV, wG, lambdaSet, titermax)
% chi_S = SFCR_s_SB(deltaB, D_k, DPWeight, maskErode, maskSSV, wG, lambdaSet, titermax)
% SFCR S-step using Split-Bregmen L1 solver
%
% Input: deltaB, D_k, DPWeight, maskErode, maskSSV, wG, lambdaSet, x
% DPWeight is ki... |
dbcb0dc0be213f95c45bac86128ff05cb57933aae497503ad7d8ab93636557a2 | MATLAB | 3,320 | 96 | % DeviceInit Loading MATLAB Driver for robotic device and initialization.
% The script begins by loading the PI_MATLAB_Driver_GCS2, which is a driver for the PI GCS controller.
% It establishes a connection to the controller through RS232 or TCP/IP based on the parameters set in the script.
% The connection settings su... |
5121c41865e647c591abf7a084bdf1af4f0019fe2d69902ac96577153775b260 | MATLAB | 3,323 | 153 | function outmat = logic_truth_table3(EXP,idx,newfig,scale)
NODEMULT = false; % use actual voltages
LABELMULT = true;
if nargin<2 || isempty(idx)
idx = size(EXP.TestMeasurements,3);
elseif idx < 0
idx = size(EXP.TestMeasurements,3)+idx+1;
end
idx(idx<0) = idx(idx<0)+EXP.MES+1;
outputs = EXP.Te... |
35622d0fba73810e8ee3d07d8e95d60b8c180dd3b11f2e8e24584b30be754465 | MATLAB | 3,324 | 131 | % getTaskVarnames.m
%
% $id:
% usage: [varnames varnamesStr] = getTaskVarnames(task)
% [varnames varnamesStr] = getTaskVarnames(v)
% by: justin gardner
% date: 03/14/07
% purpose: returns all the names of the variables in the task
% as a cell array (second optional o... |
82c5296cba67b7dce07e64d9737bded7c1082b076ad94564fff354a618ef095e | MATLAB | 3,326 | 114 | close all
clear all
%% create figure 2G
%% janine.thome@zi-mannheim.de
%% paths
pato=['/###/Figures/']; %% add output path
if ~isdir(pato), mkdir(pato); end
%% fig set
fs=16; lw=2;
basevalue=0; %baseline of background color
height=[.6]; %height... |
aca93bd7162e94390e36da94d5c0891ae0f3cd0db345db36ab281ea5acbbcf2e | MATLAB | 3,327 | 79 | function exportFieldtrip( obj, filename )
% 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 p... |
70006600c97cbe9964ae27d9fb4714d4fa34ef80d9fc5bc00546bd5f4ef53471 | MATLAB | 3,328 | 93 | function [siguse, roiuse, seedsuse, buse, bfuse, datasmthuse, cutoffuse, pkcutoffuse] = iter_seeds_select(m_in, mask, Params, P, options, flag)
%%% variables initialization %%%
siguse = [];
roiuse = [];
% buse = [];
% bfuse = [];
seedsuse = [];
datasmthuse = [];
cutoffuse = [];
pkcut... |
11c65c369096617e13190848bcc2e0a2c6d1ec497c5f54f21c8b6b61ec4c4774 | MATLAB | 3,332 | 69 | classdef SequentialRecordingsTable < types.hdmf_common.DynamicTable & types.untyped.GroupClass
% SEQUENTIALRECORDINGSTABLE A table for grouping different sequential recordings from the SimultaneousRecordingsTable table together. This is typically used to group together sequential recordings where a sequence of stimuli ... |
82d2cfcdb6dccdc9bff1dfbadbc2de224659627ca8904a52db62423c48accbb9 | MATLAB | 3,337 | 104 | % getNTLinLoc.m
%
% Function to generate digraph arrays for neurons' hemilineage, location,
% and neurotransmitter (info for both nodes and edges)
%
% INPUTS:
% ntCSVfile - full path to neurotransmitter CSV file
% s - array of source nodes for digraph
% names - array of node names for digraph
%
% OUTPUTS:
% si... |
55d4edcf155fee6e4d7f1aa332391804e7993c7891f4f6c2943e6d23dacc229a | MATLAB | 3,338 | 88 | function filt = filter_with_correction(B,A,dat,dir,usefftfilt)
% FILTER_WITH_CORRECTION applies a to the data and corrects
% edge-artifacts for one-pass filtering.
%
% Use as
% [filt] = filter_with_correction(B,A,dat,dir);
% where
% B,A filter coefficients
% dat data matrix (Nchans X Ntime)
% dir... |
7564238ae28b2fbcad16e7196bc870182bf00d03416a62340c4bfa8172b2bc4e | MATLAB | 3,342 | 85 | function nulldist(interval, perm)
% NON PARAMETRIC SIG ESTIMATION OF SPEARMAN RHO COEFF
% This script assesses significance of the correlations maps at the group level by pooling correlation
% values across participants using Fisher's z-transform. By generating the null distribution at the group
% level, it considers... |
ef75c8767344524b9eec23172523de54b7390cad63cfe3e06028ee93b8863ed0 | MATLAB | 3,342 | 56 | function [X_timespent_binned, X_at_spikes_binned, X_firing_rate, X_firing_rate_smoothed, prefered_X, Rayleigh_length, information_per_spike] ...
= Arseny_gen_1D_tuning ...
(X_video, X_spikes, X_bins_vector_of_centers, time_spent_minimum_for_1D_bins, frames_per_second, smoothing_window_1D,perform_circular_smoo... |
3c54c64e1893fff3446cee0df5778cb6ced13fedae172e52f32ed3f1f76c746f | MATLAB | 3,345 | 107 | function [sel1, sel2] = match_str(a, b, fullout)
% MATCH_STR looks for matching labels in two listst of strings
% and returns the indices into both the 1st and 2nd list of the matches.
% They will be ordered according to the first input argument.
%
% [sel1, sel2] = match_str(strlist1, strlist2)
%
% The strings can be ... |
f15eb4dd554a0bcaef7886fd717e1fee0657fb2e51c5f39231070b863995dec1 | MATLAB | 3,345 | 119 | % Marc Normandin, Muzzio Lab, Psychological & Brain Sciences, University of Iowa, 2024
% This makes Figure 2E.
%
% Note that the figures were post-processed in Adobe Illustator.
close all
clear
clc
% Paths
run('../load_figure_config.m')
INPUT_FOLDER = CHENGS_TASK_2C_FIGURES_CONFIG.DATA_FOLDER;
OUTPUT_FOLDER = CHENGS_T... |
088b79e61676f8a0c3bd32589a4a4183b69b42412a0607ab395da30ca8c6470a | MATLAB | 3,347 | 101 | function [fid, sens, label] = read_polhemus_fil(Fname_pol,skip)
% Reads Polhemus files:
% either sensor file or headshape file or both
%
% FORMAT [fid, sens, label] = read_polhemus_fil(Fname_pol,skip)
% Input:
% Fname_pol - Polhemus ASCII file containing sensor locations (cm)
% (headshape can also be con... |
4d699a63e24d4115c04ebfd741857c812be14890a9447cb31551c4e8b6e0e3f7 | MATLAB | 3,348 | 84 | function [neur_ves,conn] = connToVol(nodes,conn,nv,idxs,neur_ves)
% [neur_ves,conn] = connToVol(nodes,conn,nv,idxs,neur_ves)
%
% Function to add vasculature connectivity to a volume. Inputs to this function
% are:
%
% - nodes - struct array containing blood vessel node information
% .num - identifying... |
600a5a1e3ff24968bc37f1073f94b70304d2704700e4a006fa76febb303fbe0a | MATLAB | 3,348 | 78 | function [] = plot_worm_frame_post_analysis(I, center_lines, centerline_color, centerline_stimulus, debugimage,in_track_index,current_ellipse_ratio)
% % % % % % [] = plot_worm_frame(I, center_lines, centerline_color, UncertainTips, centerline_stimulus, debugimage,in_track_index,current_ellipse_ratio)
% IWFig = fi... |
8cd986ddcea3efef1d944739d7a50f7852906874020ceef4cd2f1167af81f28d | MATLAB | 3,348 | 85 | %function stsum(x,y,STS,elec,unit,cc);
function STS = rmap(spikes,y,y2,STS);
% updates the STS global struct: STS.sts[], response map
% input:
% x, spike frames,
% y, variable binned along x-axis
% y2, variable binned along y-axis
%
if length(spikes)<2, return; end;
globals;
DEBUG = GDEBUG;
if DEBUG>1, fig... |
2ea72a2915d504cb1147371afdc2241f92bfd36f3bcb98213b76f8656a3b44d8 | MATLAB | 3,351 | 106 | function [artifact] = detect_MA(data, bad_chan)
% DETECT_MA
% This detects motion artifacts with a moving average and is an adapted version from Homer 3: hrmR_MotionArtefactByChannel
% The parameters are defined at the beginning of the function (tMotion =
% 0.5; tMask = 1; std_thresh = 65; amp_thresh = 0.05)
%
% INPUT:... |
a7af582a443306bf5e53046e4024feee7219cff7d3e61a0c7703128bc22275ea | MATLAB | 3,351 | 99 | function trajPlot(uspikes,Y,X)
% presents spikes over trajectories of pairs of kinematic variables (X, Y)
% Oct 2016, ehud.
%
globals;
% pars
%SHOW_TIME = [0,0]; %s, session time to show
%MarkerSize = 8;
Xin=X; Yin=Y; fnum = get(gcf,'Number'); % get entrance values
hold off;
if 0
fnum = get(gcf,'... |
5d2369209f92c9f3c54584cf74b051c87b5c10b7ef1ca2744d28c9b121f61e56 | MATLAB | 3,354 | 88 | % Marc Normandin, Muzzio Lab, Psychological & Brain Sciences, University of Iowa, 2024
function [hc_group, prob_group, totalSamples, numCells, numSamplesExcluded] = compute_bfo_using_percell_table(PerCell, rotationsDeg, fieldNamesWanted, BFO90_MIN_MAPS, BF90_MIN_CORRELATION)
fieldNamesPossible = {'any', 'context1',... |
520ad99fcb43d29a95e93b1d189466574542b82907ede4cd7b25da91e6c29c66 | MATLAB | 3,356 | 71 | function MD5 = CalcMD5(Data, InClass, OutClass) %#ok<STOUT,INUSD>
% 128 bit MD5 checksum: file, string, byte stream [MEX]
% This function calculates a 128 bit checksum for arrays and files.
% Digest = CalcMD5(Data, [InClass], [OutClass])
% INPUT:
% Data: Data array or file name. Either numerical or CHAR array.
% ... |
c1bad20b6489ddbde6d4b0faf8079122e888d016a91509c24ecfb0c7c845f3b0 | MATLAB | 3,357 | 88 | function result = twoChansmodel(param, prfResponse, t)
% Function to predict neural response to time course using the 2-channel
% temporal model with a sustained channel (using a exponential decay) and
% a transient channel (using a nonlinear on/off sigmoidal function)
%
% result = twoChansmodel(params, stimulus, ... |
f6c8c88be6579b995e0604af16324379083a00484374b5780223e384d423d8c8 | MATLAB | 3,358 | 111 | function colorAutoCorrelogram = colorAutoCorrelogram(image)
% input: image in uint8 form, from wich to extract the color auto correlogram
% output: 1x64 feature vector containing the color auto correlogram
% quantize image into 64 colors = 4x4x4, in RGB space
[img_no_dither, map] = rgb2ind(image, 64, 'nodither');
% fi... |
0eed04604bf57bfc45522d92442b81621ef425ec4015dcf9c6c318cbcd785b46 | MATLAB | 3,364 | 103 | function fH = plotSingleVoxelLocationAndTs(roiVoxelData, prfData, onsetTimeSecs, selectedVoxels, TR, conditions, pths, roiName, subFolder, saveFigs, savePth)
%% Plot location and timseries of single voxel
fH = figure(99); clf; set(gcf, 'position', [73,555,1904,555], 'color', 'w')
roisplit = strsplit(roiName, '_');
ro... |
46858081efd609c875303bfe2aaf696bae6486ac4caf60a636306c71b92ff57c | MATLAB | 3,365 | 125 | function Behaviour_spikes_per_trial(Session,Area,Ndir,Ntrial)
%% Behaviour_spikes_per_trial plots the timing, movement kinematic and neural activity of a selected trial
% Behaviour_spikes_per_trial(Session,Area,Ndir,Ntrial) plots:
% 1) The hand speed of the trial Ntrial of the behavioural session Session.
% The times ... |
e0a2404103bc8cdd339840c6e9a2cc5f6e251e75e8a3c03b7847238aba34f87e | MATLAB | 3,366 | 78 | function [] = plot_worm_frame_post_analysis_original(I, center_lines, centerline_color, centerline_stimulus, debugimage,in_track_index,current_ellipse_ratio)
% % % % % % [] = plot_worm_frame(I, center_lines, centerline_color, UncertainTips, centerline_stimulus, debugimage,in_track_index,current_ellipse_ratio)
% I... |
ffffc339056f9b6b3594d5ec496122660c6fb85ed682f37f43db267e12fde08a | MATLAB | 3,366 | 87 | clear all; close all;
%% Simulate mice with parameters estimated from neutral sequences
nSimulations = 100;
%% Load regression parameters
parameters = readtable('coeffs.csv');
% extract mouseNames
mice = unique(parameters.mouseName);
% only keep parameters of one environment
parameters = parameters(parameters.environ... |
67effb55a891af7f865a2d8233d5cba8cd54553f5141201a07bfbfff9e12e441 | MATLAB | 3,367 | 67 | function mltp_tfiles_to_singleunits(obj, session)
% Due to the problem with the 32bit vs 64bit, we need
% to load the NLX timestamps for comparison
nvtFilename = fullfile(session.getSessionDirectory(), obj.Experiment.getNvtFilename());
%[nlxNvtTimeStamps_mus, ~, ~, ~, ~, ~, ~] = Nlx2MatV... |
5ff24b0f370b8519dff344da2374256337ebeca63776aa2f7d9ff688d38734fa | MATLAB | 3,370 | 87 | % Vectorized function for computing Pearson's correlation coefficient (RHO)
% between each of the respective columns in two data vectors or matrices.
%
% -- Function File: RHO = cor (X, Y)
% -- Function File: R2 = cor (X, Y, 'squared')
%
% 'RHO = cor (X, Y)' computes Pearson's correlation coefficient (RHO)
% b... |
aa055f372dcd2b97d30ffcc585d93b5797c124c4a25415b97c4bed4e6785bfc8 | MATLAB | 3,372 | 76 | %Calculate F-test cluster mass permutation effect.
%
%EXAMPLE USAGE
% >> test_results = calc_Fclust(data, [], [3, 4], 1e4, 0.05, chan_hood, 0.05)
%
%REQUIRED INPUTS
% data - An electrode x time points x conditions x subjects array of ERP
% data. Array will vary in number of dimensions ba... |
1d6846d834fdb903411c1c5c4da22ccb061de3b8a818b6dc5099c2c1d0750c3c | MATLAB | 3,374 | 113 | % plotSpikePhaseLockExTrace.m
%
% Quick script to plot leg phase and ephys trace
%% plotting parameters
jPot = 13; % junction potential (to be subtracted from Vm)
Vmscale = [-70 -50];
Vmscale = [-65 -45];
phaseScale = [0 360];
xScale = [180 181]; % DNa02
xScale = [176.58 177.58]; % DNg13
xScale = [176.15 177.15]; % ... |
ac3416d10fedfa932a0e63fcce4d77f103f07b383c8b05874ad32c04d3e5510d | MATLAB | 3,374 | 100 | % displayFictracVelocityDistribution.m
%
% Function that prompts user for trial.mat file for a fictracOnly type
% experiment and processes that FicTrac data to display a heatmap
% representing the distribution of counts across yaw and forward
% velocities.
% Used to check FicTrac calibration, as existing data sugge... |
bb63e727f91305eb969edebe9cf06a8deb613017568c66b1247389b628872d16 | MATLAB | 3,374 | 50 |
base = 'X:\Potter et al datasets\';
conditions = {'SOM', 'PV'};
% MAKE SO THAT THERE IS EXCLUSION CRITERION FOR SOM AND PV EVENTS
% what is events_per_min supposed to be about?
event_frame = 120;
load('Y:\Christian\Processed Data\Event Analysis\standard_ds_onsets.mat')
%% GET MEAN ACTIVITY BY EVENTS
% divided int... |
e69666d361a619e20cf9c872a64054fa96f82d6852c71c617e6b6f05674b5e31 | MATLAB | 3,374 | 146 | function [c1,c2,r1,r2,ratio] = BDFT(j,pitch)
i=pitch;
thre=200;
f=abs(fft2(i)/256);
s=fftshift(f);
smap=uint8(s);
smap=imresize(smap,[800,800]);
figure;
set(gcf,'Position',[0,0,800,800]);
imshow(smap,'border','tight','initialmagnification','fit');
hold on
[d... |
54b70791bf72d4176432f69887115579f63362202a2786d937d99245c7885aec | MATLAB | 3,375 | 113 | function [ ] = Patlak_twotimepoints(workingDir,concentrationmap1File,concentrationmap2File,maskFile)
% Patlak - Calculates the ki and vp maps, i.e. Ki and Vp per voxel.
% Based on script "kimap_20141111.m" of Joost de Jong and "Patlak.m" of
% Lisanne Canjels
% Adapted for 2 MP2RAGE timepoints after contrast injection ... |
85e7e6bacfe1d1b3a4ae922768735caa5df15644d465a0dc96e4063a926576a5 | MATLAB | 3,376 | 94 | function [tblPeaksIntegrated, tblSpectra] = extractSpectraAndIntegrate(csvDataDir, outputSpectraDir)
%extractSpectraAndIntegrate(csvDataDir, outputSpectraDir)
% Analyzes the GCMS data in the directory csvDataDir. The data should be
% converted into CSV files. Indetifies peaks in the total ion chromatogram,
% extract... |
aeaa77a9ad5913addc1015cfb78a59c78ad1ff6744b7b388627851663b790ea1 | MATLAB | 3,378 | 98 | function event = read_serial_event(filename)
% READ_SERIAL_EVENT
%
% changed A.Hadjipapas 2010
%
% The only thing transmitted is the event.value (no info about sample) but it works
% Copyright (C) 2007, Christian Hesse
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% for the documenta... |
b94b27d01d8c08b6ab30f84b7530c90486e4af01dfc65692dcc58ce025d1b835 | MATLAB | 3,379 | 106 | % computeLRrunCorr_pDataGUI.m
%
% Function to compute the running correlation between the left and right
% cells' dF/F, given a window size to compute the correlation over
% Runs on all pData files selected through GUI
% Saves correlation and window size back into selected pData file
% Correlation computed on img.filt... |
624c8b2c9488f7661c470fae2dcb940b284d3f8f50024e84ed42cbde31de1192 | MATLAB | 3,380 | 106 | function [corrs] = get_partial_correlations(ds_events,activity_length,bin_size,type,ex_thresh)
start=0;
corrs=cell(3,length(ds_events));
%%
for d = 1:12
ds_som_corrs=[];
ds_pv_corrs=[];
ds_ex_corrs=[];
load(['Z:\Potter et al datasets\' ds_events(d).tag 'activity.mat'])
velocity= combined_inf... |
7c00ff523fccbdb7c6ee08fe172b366024576e99357e94ad72873106bfcb8e51 | MATLAB | 3,380 | 81 | function ml_two_contexts_plot_best_fit_alignment(projectConfig)
plot_day_averaged(projectConfig, projectConfig.analysisFeaturePoorFolder, 'poor', 'all');
plot_day_averaged(projectConfig, projectConfig.analysisFeaturePoorFolder, 'poor', 'within');
plot_day_averaged(projectConfig, projectConfig.analysisFeatur... |
125d2bca36abe0974f9802feae915a23d467b57ac1c727d4961438441534ff9b | MATLAB | 3,382 | 89 | %Bar plots with the individual data points for different cohorts
%You can use Prism Program instead :)
%author: Chernysheva Maria
%version:01.09.22
function SEM_Input = bar_plots_open_field(InputData,Legend_Cohort,Color_Cohort, Title,YLabel,FontSize, paired)
%some arbitrary numbers for the plot's design:
... |
2ae24bd2b4d9bed39e14c3204aacb22b828212b2497a2112d7de8d83ada73d2f | MATLAB | 3,384 | 118 | function view_kspace(DATA,ROI,AddInfo)
% VIEW_KSPACE - Aedes plugin for viewing k-space of vnmr files
%
%
% Synopsis:
%
% Description:
%
% Examples:
%
% See also:
%
% This function is a part of Aedes - A graphical tool for analyzing
% medical images
%
% Copyright (C) 2006 Juha-Pekka Niskanen <Juha-Pekka.Niskanen@... |
a6b856fb1b7d3391a139a4de7eb1140ec6c492e7662489b8abdb0cdbb8719782 | MATLAB | 3,384 | 145 | function [fullD_results] = cluster_masks (intensities,red_vect,flatwave_identities,info,img,red_cellocs)
mean_image=img.sum_proj; % change if you want a different image
numpocks=length(info.pockels);
numwaves=length(info.wavelengths);
mouse=info.mouse;
date=info.date;
cell_idx=1:length(red_vect);
t=[mouse,' ',dat... |
52bf4c30106b9e69d55c74644af3677fff759500a5600ed5a209f46074f14250 | MATLAB | 3,387 | 90 | function MNE_out = CMNE_opt(MNE_in,P_tmp,t_tmp)
%%% define the maximum allocated current to each coil in this script
Gx = MNE_in.Gxu;
Gy = MNE_in.Gyu;
Gz = MNE_in.Gzu;
G = cat(1,Gx,Gy,Gz);
[U S V]=svd(G,'econ');
n_cutoff = 14;
S_tmp_diag = diag(S);
... |
317f199ace6347466dd7b7b45aa90227d64e74bc1f5f61cf85c35d9be41ff742 | MATLAB | 3,388 | 98 | % analyzeKernelsPooled.m
%
% Script to compute kernels averaged over multiple trials. Saves the
% kernels as well as the corresponding figures
%
% run extractKernels.m on all selected trials, save data, save figures
%
% UPDATED:
% 8/29/19
% 9/4/19 - autocorrelation computation now working
datPath = '/Users/hyang/... |
a0f1481cf1dda787c318e394e51a24624d937ea57d3b892dbac21a0bdcdd0731 | MATLAB | 3,388 | 111 | %% Script for the extraction of the amplitude histograms %%
% no worning on names
%% Set up
% nbins=100;
clear
close all
binwidth = 1;
Ampl_ECM_18_all = []; % manual setting (select all and modify)
Ampl_ECM_18_el = []; % manual setting
[end_folder]= selectfolder('Select the result folder');
if strcmp(num2str(... |
c65993b1d0c9426f7240e13a09f5ea16cf717a568a0f95103d2df94a90a849cc | MATLAB | 3,389 | 106 | function [TChannel]= SONChannelInfo(fid,chan)
% SONCHANNELINFO reads the SON file channel header for a channel
% Output follows the CED disk header structure but a FileName field
% is added to tag the returned structure with its source file.
%
%
% INFO=SONCHANNELINFO(FID, CHAN)
% where FID is the matlab file handle and... |
da27db15af4274166a1f42b54927517b694907d81007bcff66bd35179d3b7bdf | MATLAB | 3,390 | 87 | classdef DynamicTableRegion < types.hdmf_common.VectorData & types.untyped.DatasetClass
% DYNAMICTABLEREGION DynamicTableRegion provides a link from one table to an index or region of another. The `table` attribute is a link to another `DynamicTable`, indicating which table is referenced, and the data is int(s) indicat... |
2d2b7835203fb43ea80cb7ff9ad781d8e9b9cc699af41dd2338a0bc12bb76036 | MATLAB | 3,391 | 98 | % This code takes an individual TIFF stack and outputs a series of CSV files, each representing individual slices.
% It can handle up to 4 channels as long and by default name them as red, green, blue, and white (in that order)
slices = 25;
width = 1012;
height = 424;
redT = 0; %T is for the threshold of that channel
... |
ae4c3aad415b7fee30fea30d175f93c3b7b33f718c692f972fe93a75ca0f1765 | MATLAB | 3,392 | 71 |
clear; close all;
%maindir = fileparts(convert("fullpath"));
maindir = fullfile('/ZPOOL/data/projects/rf1-sra');
warning off all
%subs = [10317, 10369, 10402, 10418, 10462, 10478, 10486, 10529, 10541, ...
% 10572, 10581, 10584, 10585, 10589, 10590, 10596, 10603, 10606, 10608, 10617, ...
% 10636, 10638, 106... |
6129cd92ee8e8056c739b91a89d91a78342f74c1d76c18ca8918f394e88cfa26 | MATLAB | 3,393 | 98 | % analyzeMoveCondKernels.m
%
% Script to extract movement conditioned kernels
%
% run extractMoveCondKernels.m on all selected trials, save data, save
% figures
%
% NOTE: with current set of movement conditioned data and current kernel
% parameters (or with winLen = 1.5), the bouts are too short to extract
% valid ... |
0da0e5db8357f5376fe0dd9216135e34fffdf6c5ad8ce9c05afc0f48d02bf608 | MATLAB | 3,394 | 113 |
function my_batch_run_config(opts, imdb, work_info, net_config, work_info_epoch, work_info_batch)
do_init_work_info_batch(opts, imdb, work_info, net_config, work_info_epoch, work_info_batch)
work_info_batch.ref.batch_skip=false;
batch_size=work_info_epoch.ref.batch_size;
torun_task_subidxes=... |
d3765a02b8ff3ff413c5578a0d214f45f3f960442b5fda7accb1b57fa5085a03 | MATLAB | 3,394 | 116 | function [ax_C,ax_H,order]=consensusPlot(C,Sc,Tree,varargin)
% consensusPlot Plot hierarchical consensus clustering results
%
% Syntax
%__________________________________________________________________________
%
% consensusPlot(C,Sc,Tree)
%
% consensusPlot(__,Name,Value)
%
% [ax_C,ax_H]=consensusPlot(__)
%
%
% D... |
0ecfc66c7b34095d4269394526bebda0fd6c7ded12583a4eb21368ea697951cb | MATLAB | 3,397 | 51 | function [psth, response, visI] = processAnimalData(cell_activity_allday, stim_type_allday, trials, nanimals, nstim_type, win, threshold, ngratings)
% This function processes data for all animals and returns the psth, response, and visI structures.
% Initialize structures
psth = struct();
response ... |
36d46d447c195e071098edc2bb9cc7976fbc60a8e85bd4b197d2d0bedd28a617 | MATLAB | 3,397 | 123 | function ExampleAnalog()
% function OutputAnalogVector = ExampleAnalog()
% Prompt for the correct DLL
disp(' '); % Blank line
DLLName = input('DLL Name: ', 's');
% Load the appropriate DLL
[nsresult] = ns_SetLibrary(DLLName);
if (nsresult ~= 0)
disp('DLL was not found!');
return
end
% Find out the data file... |
41f01797b612104ed6f7e36c510d4d8db5feee0b964345b6528e37bc1a622771 | MATLAB | 3,397 | 111 | % mglValidateScreenParams.m
%
% $Id:$
% usage: mglValidateScreenParams()
% by: justin gardner
% date: 07/23/09
% purpose: Validates a screenParams structure to make sure that it
% has all necessary fields
%
% screenParams = mglDefaultScreenParams;
% screenParams = mglValidateS... |
6d1484b4dd49ba0b7baa6480d687f784b37aaf78c1d7414d892eb957e3664ceb | MATLAB | 3,402 | 138 | figure; plot(legXShiftRot(40000:41500,refPts.headPtInd),legYShiftRot(40000:41500,refPts.headPtInd), 'x');
hold on;
plot(legXShiftRot(40000:41500,refPts.abdPtInd),legYShiftRot(40000:41500,refPts.abdPtInd), 'x');
plot(legXShiftRot(40000:41500,refPts.thxMidInd),legYShiftRot(40000:41500,refPts.thxMidInd), 'x');
figure; p... |
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