sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
c959c6c4204b04b4406ca9af3755209a2c9778342a6658268db506333f3784bd | MATLAB | 2,024 | 77 | function [weiBM,avgWeiBM,binBM,avgBinBM,sizesMat] = get_block_mat(cij,ca,noNan)
% given an adjacency matrix + community affiliations, return a block matrix
%
% inputs:
% cij: adjacency matrix
% ca: community affiliation vector
% noNan: do not count nan edges when getti... |
12735bbf6f7403ad1340d424f17673a6f40398734ec309835683362eed109c42 | MATLAB | 2,025 | 55 | %%
clear all
close all
run(['..' filesep 'def_local'])
addpath(genpath(path_mTRF));
addpath('ERBfilter');
addpath(path_fieldtrip)
ft_defaults
run make_stimuliList.m
%%
all_CorrEnv=[];
StimProfiles_freq=[2 8];
Lists={'A','B'};
Types={'SWS','_voc_7Bds',''};
for nStim=1:80
for nList=1:length(Lists)
StimPro... |
6a70f5a6bdd764a2ee0f78e65b486657f2c338026f3f7de40f9045c220a9e434 | MATLAB | 2,028 | 70 | function headingEsts = runCDModel(nameValueArgs)
%RUNCDMODEL Run Competitive Dynamics model through all or select stimuli
arguments
nameValueArgs.sampleNums (:, 1) double = -1; % -1 means all
nameValueArgs.settings struct = readSettings()
nameValueArgs.runParallel logical = false
end
settings = ... |
10588105dad48e74bfbdce115b565a3a4826c199a7afa0e50dcb3c236c541a56 | MATLAB | 2,031 | 70 | classdef( Abstract ) Flex < handle
%uix.mixin.Flex Flex mixin
%
% uix.mixin.Flex is a mixin class used by flex containers to provide
% various properties and helper methods.
% Copyright 2009-2020 The MathWorks, Inc.
properties( GetAccess = protected, SetAccess = private )
... |
83ce84129667f6d19cfa4005e9ee33b4299a1d0705a87597c070c7628d9ef5e9 | MATLAB | 2,033 | 59 | function plotPSTH_fig1(dataM,idxstimsubset,P,subplt,wpatch,scale,col,line)
%%% Expect a format dataM: time bins x stimulis x animals
if ~exist('wpatch','var')
wpatch = 1;
end
if ~exist('scale','var')
scale = 0;
end
if ~exist('col','var')
col = P.SndColors;
end
i... |
a17030d68682ca34212b1bc84b8c888d89dae89f2c283619765ede32f85c078c | MATLAB | 2,033 | 87 | %% Realign and then smooth functionals
% Subjs = getSubjects;
Subjs = {'Bass','Butch'};
F = getFncDirs';
clear e r
e.quality = 1;
e.sep = 1;
e.fwhm = 2;
e.rtm = 0;
e.interp = 5;
e.wrap = [0 0 0];
e.weight = '';
% r.which = [2 0];
% r.interp = 5;
% r.wrap = [0 0 0];
% r.mask ... |
a3ef9a36f7e4bbc5839533a7e500663ad5767e0d1f516d2675dfade4bf0f15f5 | MATLAB | 2,038 | 70 | function [AdjM,cn] = AdjMtx(Surf,maskvtx)
% AdjM = AdjMtx(Surf,maskvtx)
%
% This function finds the adjacent vertices for all vertices along the
% surface.
%
% Input
% Surf: Surface. It is a structure with Surf.tri = t x 3 matrix of triangle
% indices, 1-based, t=#triangles and Surf.coord = 3 x nv matrix of
% coord... |
a575a2eb708c63ef884f2b846f86faf246115685170de800b99bc9ae0254125d | MATLAB | 2,047 | 58 |
% Written by Sham Tlili and edited by Timothy Saunders
% Code for aligning data of CNS from SPIM data to detwich embryo
% Reads data in "images_original"
% tstart= first time point to be aligned
% tend = final time point to be aligned
% dbin = binning of data
% optimizer allows control of iterations, step lengt... |
38cff30c7bac1387808f3197a93d14880b5d8a6f4014babfdd04d7289fec2d92 | MATLAB | 2,048 | 63 | function progress(count,N,step)
%
% progress(count,N,step)
%
% Placed within a loop, a call to the PROGRESS function displays a progress
% message and some time estimate. This estimate is only exact if each run
% of the loop takes roughly the same amount of time.
%
% Prior to the loop, call the function without argumen... |
4b11cd2327722dfd0f3ea40fcccc7c9ef99aaaf6ce3526e5f361e9647ac3a77f | MATLAB | 2,048 | 71 | function [map] = cr_coherence_vs_psd(val, PeakPos, PowerSpec, CBF)
% This function goes with cr_coherence_ref
% Take the previous reference pixels and scatterplot the coherence versus PSD for that given pixel
% OBS: I need to save the ??
%% Heatmaps of reference pixels
map = zeros(CBF.x, CBF.y, length(C... |
65b602ea253bd34ef25a28f9079e5350425ad74c39b71f92a27ca87d7b885bb1 | MATLAB | 2,053 | 57 | function params=tpreadconfig( tpdirname )
%TPREADCONFIG read twophoton experiment config file
%
%
% PARAMS. =
% params.Main.Total_cycles (total number of cycles)
% params.Main.Scanline_period__us_ (scanline period, in us)
% params.Main.Dwell_time__us_ (pixel dwell time, in us)
% params.Main.Frame_period__us_ (... |
363a7ecec77b60d8e240cb5c48e94c2b397a8884283c3f51390cdff4de9a7552 | MATLAB | 2,055 | 56 | function [J_x J_A] = MVAR_JacCSD(A,x_ext,p)
%Complex Step Differentiation (CSD) for computing the Jacobian matrix
%
% Arguments and variables:
% CH: number of channels
% p: MVAR model order
% x_ext: (CH*p x 1) Input vector of the MVAR model, x_ext(k-1) = [x(k-1); x(k-2); ...; x(k-p)]
% A: (CH*p x CH*p) All MVAR... |
a4c63d8bb997ac5a0d376d2dabfbcc2be50b24d41d0dc8e1bde563720ce91f8a | MATLAB | 2,055 | 74 | function gr = lme_Gradient(X,Zcols,W,invH,L,phi,re,ni)
% gr = lme_Gradient(X,Zcols,W,invH,L,phi,re,ni)
%
% Gradient vector for the restricted log-likelihood.
%
% Input
% X: Ordered design Matrix (according to time for each subject).
% Zcols: Vector with the indices of the colums of X that will be considered
% as rando... |
1d7bf44f22e68053d18072b644578cf99889627128e194636ee9c3ee566ef86b | MATLAB | 2,061 | 62 | function [accVid,accSnd,p] = plotDecoding(acc,decP,sideTransec,chanceLevel,pltInset)
if ~exist('pltInset','var')
pltInset = 0;
end
idxviddim = size(acc,3); % usually the way it goes
idxsnddim = 1;
p(1) = signrank(acc(1,:,idxviddim),chanceLevel(1),'tail','right');
p(2) = si... |
e6f10185505c0af1dd12ae294fdae0474b09af250e55b22af6872a4726990ba4 | MATLAB | 2,062 | 88 | function [wfa, wfb] = dib_wf_pte()
% function [wfa, wfb] = dib_wf_pte()
%
% By Filip Szczepankiewicz
%
% Planar tensor encoding (PTE)
% for the "data in brief 2019" project.
%% PTE
wfa = [
0 0 0
0 -0.7301 0.6840
0 -0.7289 0.6853
0 -0.7263 0.6880
0 -0.7222 0.6924... |
9563b5496a4b5fde625abec688c3e72a0d34b8d38ce019dbe6701b1afc1173cd | MATLAB | 2,063 | 51 | function [spikes, new_clust] = break_minicluster(spikes, mini)
% UltraMegaSort2000 by Hill DN, Mehta SB, & Kleinfeld D - 07/12/2010
%
% break_minicluster - splits a mini cluster into two mini-clusters
%
% Usage:
% [spikes, new_clust] = break_minicluster(spikes, mini)
%
% Description:
% Splits a mini-cluster int... |
cfa9015e2f5ca64277bc13418d949a2340e7980d56f2c952a1c2cb864c279e70 | MATLAB | 2,063 | 40 | function fiberCenter = remove_fiber_overlap(fiberCenter, fiberR, placedFiberCenters, placedFiberRs, availableArea, minFiberDist, fibp)
rhRatio = 1/cos(pi/fibp); % Ratio of radius on apotheme of inscribed reg. polygon.
% [x, y] = centroid(availableArea);
% destCentroid = [x, y];
availableAreaFib = availableArea;
w... |
d86e1eb12335eafa642d883ee92cfff8bcbfc641f98d55d19db3c91c547bcf72 | MATLAB | 2,066 | 64 | function [im,params]= previewprairieview(dirname, numFrames, firstFrames, channel)
% PREVIEWPRAIRIEVIEW - Preview PrairieView image data
%
% IM = PREVIEWPRAIRIEVIEW(DIRNAME, NUMFRAMES, FIRSTFRAMES,CHANNEL)
%
% Read a few frames to create a preview image. DIRNAME is the
% directory name to be opened, and NUMFRAM... |
fcfe177ebda846dedd21c8bfc217c3706601ef7e958e5bfad905ca228f7fbe32 | MATLAB | 2,069 | 67 | %=====================================================
% FileName: extract_online_traces.m
% Designby: Zhe
% Modified: 03/09/2021
% Describe: Extract fluorescence traces from the calcium image dataset.
% Suppose C: Number of cells; T: Number of frames
% traces <C,T>
%===============================... |
1d650f058a9007bff37a7dde7b82b082ba14313b9737c104c45b242c0253683f | MATLAB | 2,071 | 76 |
%% Script to generate Figure 8
clear all
close all
runs = 10;
epochs = 1000;
hunits = {'4', '8'};
runsstrings = {'Run1','Run2','Run3','Run4','Run5',...
'Run6', 'Run7','Run8','Run9','Run10'};
rmseGRUT = zeros(runs,epochs,length(hunits));
rmseGRUV = zeros(runs,epochs,length(hunits));
% All GRU
for hu = 1:length(h... |
a2037726afde3dd2f1ebf7eb2ed30d2fac709a9768a980d5c84283d990a6b4dd | MATLAB | 2,071 | 67 | function model = qtip_data2fit_NLLSdc(model,signal,bten,ind)
% function m = qtip_data2fit_NLLSdc(model,signal,bten,ind)
%
% fits the QTI parameters using NLLSdc
if (nargin < 4), ind = ones(size(bten,1),1)>0; end
signal = signal(ind);
bten = bten(ind,:);
bt2 = convert_1x6_to_1x21(bten);
model = double(model... |
227d9d19693ad955a2a70fb1d5bc724bbe1cf5b1d439489f03cfabe6acb3e78f | MATLAB | 2,072 | 68 | function [phi, v0, v_direction, fullStruct] = orderParameter(vx, vy)
% Function to calculate order parameter, from equation 1 in Collective
% Motion by Vicsek & Zafeiris.
% VX and VY must be NxMxtime vectors giving the x and y components of the
% vector field. If VX and VY have more than 3 dimensions, extra dimensions
... |
524bc655c02caaaff240e00842982824e4810e3f5801266a986d0581c490ea2a | MATLAB | 2,073 | 79 | function plotSnapshotsAndVfs(snaps, vfx, vfy, allPatternLocs, isPhase, plotSeparate, nsnaps)
% Function to plot consecutive snapshots with their corresponding velocity
% fields. VFS can either be a complex matrix where real gives x-coords and
% imag gives y-coords, or can be input as two varibles. Default is to overla... |
28af5ea5451def502f41e14a9b6e23c423cfe1dcba1edd0ee2354d1c48ffc9bc | MATLAB | 2,074 | 76 | %% Two arbitrary partitions
p1 = [1 2 3 3 2 1 1 3 3 1 2 2];
p2 = [3 2 3 2 2 1 1 2 3 1 3 1];
% Compute the unadjusted rand index
ri = rand_index(p1, p2);
assert(ri == 7/11);
% Compute the adjusted rand index
ari = rand_index(p1, p2, 'adjusted');
assert(ari == 1/12);
%% Two perfect partitions
p1 = [1 1 1];
p2 = [1 1 1... |
3301af8101e921d93832bc3de66164aa7b9cc12815199ad7d9c783fb451f1e09 | MATLAB | 2,075 | 66 | function Assemblies = MakebestEnsembleAssemsCrossShufflePosthoc(UnitsReal, Ltrials_,Rtrials_,MaxSize,CorrsToDestroy,noTrials,nReps,unitSelection)
Assemblies= struct;
%@TODO: add shuffling of trial labels between cells to non- trial-resampled version
InfoCriteria = 'max';
nReps = 50;
noTrials ... |
480cdccf6b05d6f3db3ad2b63c1520a2af29d208bc6d68ff8875f3fdacd2b1f4 | MATLAB | 2,075 | 61 | % function for randomizing spike times
% Spike times are randomized within and across MEA channels
% Arguments:
% tb = table containing all the metadata
% index = row of tb to run (i.e. recording number)
function fx_randomize_spike_times(tb, index)
% Get all the relevant metadata for recording
file_id... |
9daec457a2a746a8fe4a8ec8f1b7bd91a6868dbf5c6ea91f4ea86020e6d7ed56 | MATLAB | 2,075 | 70 | function res = estPsychFnc(Data)
% res = estPsychFnc(Data)
%
% Fit Psychometric function and plot using the psignifit toolbox
% https://github.com/wichmann-lab/psignifit.git
%
% Input:
% Data ... Structure of Data from running the NHP joystick sound
% localization task.
%
% Output:
% res ... |
2b9a5f7e38138f0c8402c1dcc28089f97be32fb2ef79a817d508e29d797e4caa | MATLAB | 2,076 | 77 | function step1_tempConverter(rootDir)
%
% Convert weird temp files from TC Central into table with same file name
% (but different extension)
try
% Define paths
if nargin == 0
rootDir = Cloudstation('Vowels\Noise\Cooling\Data');
% rootDir = Cloudstation('Vowels\Spatial_Unmasking\Cooling\Data');
end
%
% sour... |
cd16c826b67aaf5f87f0cc0f4b64fb845b4884e2384f3fa3b053c4fa2fb63322 | MATLAB | 2,076 | 56 | % Convert bin-epoched EEG to a bin-organized EEG structure
% may be useful for subsequent decoding scripts
% axs 2020
%
% Inputs:
% EEG - an EEG set, which must have been processed with ERPLAB, with
% valid EventList, and be bin-epoched EEG data
% write_file_path - optional full path to write file to, str... |
ae65bc15dd8873a2e756054c0351ffb3da5aeab27448534c0d78ce43395d07c1 | MATLAB | 2,081 | 84 | close all;
clear all;
netName = "squeezenet";
net = eval(netName);
inputSize = net.Layers(1).InputSize(1:2);
classes = net.Layers(end).Classes;
layerName = activationLayerName(netName);
im = imread('ngc6543a.jpg');
imResized = imresize(im,[inputSize(1),inputSize(2)]);
imageActivations = activations(net,imResized,lay... |
dd9ffa533187d32a4887ea8365577df92511d1037b325a0c1e4f43d43a07e45c | MATLAB | 2,081 | 74 | function [ciu,Aall,anull,A,ciall] = get_SCmodules_MRCClite(K,sam1,sam2,maxC,r1,r2,tau)
%
% INPUTS:
% K: network data
% sam1: samples communities first loop
% sam2: samples communities second loop
% maxC: max num communities
% r1: initial gamma low
% r2: initial ... |
0a9d7de0254de62281ccac614beab273eae990de1cdd7994e43d459f683b07f0 | MATLAB | 2,082 | 67 | function [pgonOut, G, graphNodes] = edges_to_polyshape(segments, useXor)
arguments
segments
useXor = false
end
% Generate graphs of the segmented points and edges
edgeCoords = reshape(segments, [size(segments, 1)*2 3]);
graphNodes = unique(edgeCoords(:, 1:2), 'rows');
nEdges = size(segments, 1);
G = ... |
72b9eb7169e1293d0e86994fc004c04a71db8b175912cd3ad893f903be8d1216 | MATLAB | 2,084 | 67 | % Quality control Q1a
% Check imaging parameters and plot them across all the participants
% Xin Di, July 13, 2022
clear
subjfolder = dir('F:\fMRI_QC\fmri-open-qc-rest_bias_corrected\sub*');
% Read image information for every participant
for subji = 1:length(subjfolder)
fprintf('Processing subject %d ...',subji)... |
e85f594010a70125bd4f84cbe800058f8868bb316797dad1d03476cd556bbd06 | MATLAB | 2,085 | 50 | function pw = lme_plannedPower(Zi,ZiCol,Dhat,phisqhat,effsz,dr,sz1,sz2,alpha)
% pw = lme_plannedPower(Zi,ZiCol,Dhat,phisqhat,effsz,dr,sz1,sz2,alpha)
%
% Power calculation for a planned ba... |
cd7359013023e4e5aae1746f36ecf642d60386a4755014b9b3f9476677a775aa | MATLAB | 2,086 | 62 | function [phase_patch,pos] = calc_phase_patch(data, complist, CBF)
% This function calculates the phase angles for a given patch at the peak
% frequency of that patch
% data = the raw data (usually aligned)
% complist = patch border information from the frequency segementation code
% CBF = the parameter structur... |
947e20874d36bcfba5976b0da0ece91556efaeab334631fbbc42d05bec398763 | MATLAB | 2,087 | 70 | function [xgp,wt] = generalized_phase_vector( x, Fs, lp )
%
% GENERALIZED PHASE VECTOR calculate the generalized phase of input vector
%
% INPUT:
% x - data column vector (t,1)
% Fs - sampling rate (Hz)
% lp - low-frequency data cutoff (Hz)
%
% OUTPUT:
% xgp - output datacube
% wt - instantaneous frequency estimate
... |
fea8be81812158ad1c6cd6914d6e2fe75dc46e643f696002a110693a75461273 | MATLAB | 2,087 | 86 | function [ netsimile ] = netsimile_dist_wu(amat,bmat)
% weighted implementation of netsimile algo for comparing networks
% https://arxiv.org/abs/1209.2684
% get the netsimile of each network
ns_a = feat_extract(amat) ;
ns_b = feat_extract(bmat) ;
% canbera distance
canbdist = @(a_,b_) sum(abs(a_-b_)./(abs(a_)+abs(b_)... |
b6622314bd54ff9143dc63488c349231fc7e566d01c3e06a63477b6b820fd0be | MATLAB | 2,088 | 65 | function SOEA20_Liley(M,run_number,population_size)
% Script runs the sinlgeobjecitve evolutionary algorithm SOEA20. See paper
% for details.
% Load data
load('Control_EEG_data.mat')
data = Control_EEG_data(M,:)-mean(Control_EEG_data(M,:));
data = zscore(data);
data = filter_b_f(data, 2, 256,'high',4);% 2 Hz... |
d8e9bce20d2449cb1f60e90144e035a3286174b32c3271f49053b418155725c7 | MATLAB | 2,091 | 64 | function [h,T,perm] = polardendrogram(Z,varargin)
%POLARDENDROGRAM plots a polar dendrogram plot, taking same options as
%dendrogram and giving same outputs.
% Example:
% X= rand(100,2);
% Y= pdist(X,'cityblock');
% Z= linkage(Y,'average');
% [H,T] = polardendrogram(Z,'colorthreshold','default');
%Plot a normal dendrog... |
37a9c626d83dfef40087dd306364fe09ad348616b5985b1bf49d3f3e5a86f92e | MATLAB | 2,093 | 54 | function Xhat = decode_beamformer(cfg0, decoder, Y)
% [Xhat] = decode_beamformer(cfg, decoder, Y)
% Estimate the activity of latent components using a linear decoder, obtained from an
% appropriate training function. Several components may be estimated independently.
%
% decoder The linear decoder obtained... |
20a9ac9ebd5703c5b51fbfbf7f7eda8d288d2733dbacd904092bebe70a82cbcc | MATLAB | 2,094 | 66 | % Add information on erroneous behavioural outcomes for import scripts if missing
%
% Aleksander PF Domanski PhD UoB 2015
% aleks.domanski@bristol.ac.uk
%
clear all
close all
target= 'physostigmine';
if ispc
home = 'C:\'; % [getenv('HOMEDRIVE') getenv('HOMEPATH')];
pat = [home 'Analysis\AssemblyAnalysis\raw\'... |
d94da2984017ad555a035d68936527da8a4057e6ea963355f56d9cfccbc39acc | MATLAB | 2,096 | 65 | tr=4;
for p=0:5
fileLoc = '\\158.182.15.58\test2\Junhao';
% % File name
fileName = ['result_of_p' num2str(p) '_trial' num2str(tr) ];
cd(fileLoc)
load(fileName)
% Sampling frequency (in Hz)
Fs = 100;
% Spatial selection of recording to keep (set to empty or zero to use full
% recording)
keepRows = 1:50;
keepCols = 1:50;... |
04116a93ce01b48050dcbe19b120d981a6494019e4fa9b4455aabb6f5d69f14f | MATLAB | 2,098 | 62 | function out = convert_1x21_to_6x6(in)
% function convert_1x21_to_6x6()
%
% converts a tensor from a 1x21 to a 6x6 representation
%
% in_1x21 = [
% [xx*xx yy*yy zz*zz]
% [xx*yy xx*zz yy*zz] * sqrt(2)
% [xx*yz yy*xz zz*xy xx*xy xx*xz... |
70dc18a89d58473c47961b0974a5c57b15f353ca15e2c6c892a8369f9c4097fb | MATLAB | 2,098 | 65 | %
% Script to show a demographic overview of the included patients in this
% study. This is based on the patients from whom the detected N1s are saved
% in a folder called derivatives/av_ccep/. This is performed in script
% ccep01_averageCCEPs.m
%
% Dora Hermes, Dorien van Blooijs, 2020
%
%% Set paths
clc
clear
myDat... |
e7671b159307e77a47eeee846cd6f01b88e421ead54e45457031fe8da53c016c | MATLAB | 2,098 | 68 | function crop_static_lightfield(cropped_size, overlap, source_path, save_path)
overlap_px = floor(overlap * cropped_size);
wrap_content = false;
if mod(overlap_px, 2) == 1
overlap_px = overlap_px + 1;
end
file_list = dir(source_path);
file_num = length(file_list);
... |
0c1f8d61b0a4592072623247dee2a1b5c4244929c7d8b4a604aa95d56812e152 | MATLAB | 2,102 | 85 | %% Bar sweeps
tank = 'DILL_VISUAL_1';
block = 2;
win = [0 1];
data = TDT2mat(tank,sprintf('Block-%d',block),'type',[2 3],'silent',true);
%
% emap = [17 31 19 29 21 27 23 25 18 32 20 30 22 28 24 26 1 15 3 13 5 11 7 9 2 16 4 14 6 12 8 10];
% emap = [];
emap = [1 3 5 7 2 4 6 8 10 12 14 16 9 11 13 15 17 19 21 23 18 20 2... |
4bbc75282746bb9991bdb2eb1fb509672e94cd2c1baf4009a30a35dc09ac6e10 | MATLAB | 2,102 | 87 | function [H] = generateH(R, prior_setup, generate_with_t, use_log_scale_for_mean)
if(nargin < 3)
generate_with_t = false;
end
if(nargin < 4)
use_log_scale_for_mean = false;
end
if(prior_setup.include_rank_constant)
nd = sum([prior_setup.T(:).on]) + prior_setup.V.on;
rank_scale = -log(R)/nd;
else
r... |
ede1b5e6219d5b9fd3a2b0caaba0b2bf5d9918645859c6bcf41d3b08858b252b | MATLAB | 2,105 | 41 | function plotAllSounds(mainFigDat,behFigDat)
neurTrace = squeeze(zscore(nanmean(mainFigDat.dataMPC(:,:,1,:)-nanmean(mainFigDat.dataMPC(mainFigDat.mainFigP.bins<0,:,1,:)),4)));
behTrace = squeeze(zscore(nanmean(behFigDat.dat(find(strcmp({behFigDat.dat.name},'Body motion'))).dataMPC(:,:,1,:)- ...
nanmean(... |
4b64353f421742d6f80bec0c5f076140fab95d74c1cb81dfa4815d1957b9ef49 | MATLAB | 2,107 | 83 | function visualiseActivationMap(act_map, occ_map, newfig)
% This function plots the activation map provided. NaN values are
% interpreted as obstructions, and -1 values are interpreted as unactivated
% locations
%%% COLORMAP SET UP
% Load in the plasma colour map
load('extra_colormaps.mat','plasma');
% D... |
4131543bcffc9e077e0ab2162a71890a03fdb239008389a44c927f94c54c04e1 | MATLAB | 2,110 | 63 | %% An object in OH/OHA/TOH/TOHA at a specific moment in time.
% Copyright (C) 2022 Richard Hugh Moulton
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or... |
166f873b9409f97ca8c848075f8acbe3f2cb16cfcaf8a9d5abcc79133ec86e25 | MATLAB | 2,111 | 62 | function find_placement_by_fiber_count(nerveModel)
% find_placement_by_fiber_count('Subject1')
electrodeType = 'TIME4H';
[numFibersAtPercepThreshold, placements, percepThresholds] = num_fibers_for_perception(nerveModel, electrodeType, false);
% Find the average number of fibers recruited at the perceptual thres... |
8e3ff82b2f8660e6252e5c7a284e5c3754bc6e82e2d911d3062e93f20dde8ff5 | MATLAB | 2,113 | 83 | function plot_evLFP(W,P,param,cfg)
% plot_evLFP(W,P,param,cfg)
%
% For use with DB_QuickPlot
%
% DJS 2013
win = [cfg.win_on cfg.win_off] / 1000; % ms -> s
svec = floor(win(1)*P.wave_fs):round(win(2)*P.wave_fs);
% Organize by stimulus onsets
onsamp = round(P.VALS.onset * P.wave_fs);
% Reorganize ... |
5b7d49c7b7f22d492bb97b6b1aa8074e7e1e308a77b85a402314522de377003e | MATLAB | 2,115 | 69 | clc;clear;close all;
Figb = figure();
Ntrials = 5000; %total number of time steps (learning cycles)
N_mu=500; %There are \mu independent embedded patterns, 500 simulations (number of simulations)
N_psn=7; %number of post-synaptic neurons
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
9c890d0acf7df39d1752b51e45695cfc6b4abfeae6ad66db250fc5a61a346ea7 | MATLAB | 2,116 | 65 | function speech=newMakeVowel2009(dur,sampleRate, F0, f1,f2,f3,f4)
% y=jansMakeVowel(dur,sampleRate, F0, f1, f2, f3);
% makes a very simple artificial vowel
% adapted from Slattery's auditory toolbox makevowel.m
% dur is duration in seconds
% sample rate is in Hz
% F0 is the fundamental (pitch)
% f1-f3 are t... |
42100a3087c49e1f5e7bb1f2bff08b2211e33ab7639f15b30fbfd21a648ec049 | MATLAB | 2,117 | 63 | function [startIndices, endIndices, outputArray] = findRuns(...
binaryArray, minLength, maxLength, ignoreZeros)
% FINDRUNS finds the start and end indices of runs of consecutive 1's in
% BINARYARRAY that are longer than MINLENGTH (default is 0) and shorter
% than MAXLENGTH (default infinity). IGNORENZEROS is an opt... |
39f61707a7b9c8c82a1d26bc14068677ccc0e3813b3b9698eafe018972797671 | MATLAB | 2,118 | 81 | clear all;
addpath('~/-pimmos/decoding/');
% Gives me: X (labels), Y (data), time
tmp = load('../examples/testdata_2class.mat');
Y = tmp.Y; % Y: features x time x trials
X = tmp.X';
time = tmp.time;
label = tmp.label;
numF = size(Y, 1);
numT = size(Y, 2);
numN = size(Y, 3);
% Select time points, senso... |
e162e630b931cd2379a29a4621c0a126cf2fdca840b5ff91cdec522a2f262c61 | MATLAB | 2,118 | 25 | % REMOVE BAD CHANNELS - Display %
function channel_exclusion_table = bst_ast_remove_bad_channels_display(channel_amp_data_Cutoff_logical, channel_grad_data_Cutoff_logical, low_sig_range_all_channels_val_logical,output_channel_names)
%Prepare the bad channels for display
channels_removed_amp_display_labels = t... |
6fb25c0c1892686c7c1269a0e1b2c9ef4a4bfb49be21b00eb161f7b85731109a | MATLAB | 2,119 | 56 | % Script to find all patterns in a sequence of velocity vector fields and
% display some of their properties
%% Set pattern detection parameters
params = setPatternParams(Fs);
% %% Find all patterns
% [patterns, pattTypes, colNames, pattLocs] = ...
% findAllPatterns(real(vfs), imag(vfs), params);
% change from si... |
d998032dea27ea1ef0afd550722a34abe46a476eb1ea9ff92134a1ad2c75c7e3 | MATLAB | 2,120 | 65 | function speech=newMakeVowel2009(dur,sampleRate, F0, f1,f2,f3,f4)
% y=jansMakeVowel(dur,sampleRate, F0, f1, f2, f3, f4);
% makes a very simple artificial vowel
% adapted from Slattery's auditory toolbox makevowel.m
% dur is duration in seconds
% sample rate is in Hz
% F0 is the fundamental (pitch)
% f1-f3 a... |
6cba955b81b08f6ba574fae6e45dc37179e5b8014d7255874d4e7f9e2fbd7c91 | MATLAB | 2,123 | 76 | %=========================================================
% FileName: linear_classifier_train.m
% Designby: Zhe
% Modified: 09/02/2021
% Describe: Training linear classifier for the position decoding
% from FPGA recorded traces.
%=========================================================================
cle... |
57110126818eca028ca7821cdef5a7b802210094c48397af37f008fed5b8b78a | MATLAB | 2,124 | 82 | function [r, c, error] = circle_approx(poly, a, center, plotc)
% CIRCLE_APPROX Approximates a concave polygon with a circle of radius the
% mean of the vertices distances to center.
% Units are the same as input units.
%
% [r, c, error] = circle_approx(poly, a, center, plotc)
%
% Inputs: - poly: vector of x a... |
b3edb044daf391f87263d3a9571ff8e0276e9b2d49234be0bc2892bc5ff0aa03 | MATLAB | 2,124 | 71 | function valve_WE(n, time_on, pulseN)
%
% This script allows you to control the solenoids for any length of time
% and number of pulses. It's designed with the ACME 2000 in mind, but may
% be suitable for expansion in the future.
%
% bit - bit number for required solenoid (e.g. left = 4; right = i; center = ... |
17c4e8841a86653366943b5f0b9258113d81129dd202a6b172f5e449e69825a5 | MATLAB | 2,125 | 69 | %
% Downloaded from MathWorks File Exchange (LB 2020/01/11)
%
% Log:
% First log by LB on 2020/08/10- nothing changed.
function runs = contiguous(A,varargin)
% RUNS = CONTIGUOUS(A,NUM) returns the start and stop indices for contiguous
% runs of the elements NUM within vector A. A and NUM can be vectors of
% i... |
8435a8b8a8bed0e80848d801bb2e7a640fac91c8fe81078e7808641739e7b5e5 | MATLAB | 2,125 | 62 | function spindleActivation = compute_spindle_activation(muscleState)
% Input:
% muscleState is a table with columns 't' [s], 'Elongation' [relative] and
% activation [normalized EMG]
% Output:
% spindleActivation is a table with columns 't' [s], 'Recruitment' [%],
% and FiringRate [Hz]
% Creation of auxiliary variab... |
7fbce3e61013306c119430a90f33cb096117ea605cec4a45171a8fa6940b24e0 | MATLAB | 2,129 | 48 | function fibersCompartmentalized = get_comp_coords(fibersPerFascicle, ...
fascIdsByAs, MRG, log)
% GET_COMP_COORDS place the individual fiber compartments on a spline fit
% to the fiber coordinates, in fascicles reached by an active site
% fibersCompartmentalized = GET_COMP_COORDS(fibersPerFascicle, MRG)
% ... |
f6cbffaf5809ad1911eadd72b07b09fb1121f17abb3335aa569d0f49a54f9d7c | MATLAB | 2,129 | 62 | function [dataMPC,M,dataMPC_odd,dataMPC_even,dataA] = getMainFigData(db,P,mainFigP)
%% get PCs for all mice
P.focusOn = mainFigP.focusOn;
dataMPC = nan(numel(P.bins),P.nGroupsSnd,numel(mainFigP.pc2Keep),P.nMice);
dataMPC_odd = nan(numel(P.bins),P.nGroupsSnd,numel(mainFigP.pc2Keep),P.nMice);
... |
aaa270717c53fec6d71f868db8bc186c1076d3da04af3bf92ae0e9b27ac7e233 | MATLAB | 2,135 | 52 | function DM=MakeDM(Subject_Details,MDI,AnalType)
% Computes a design matrix DM used in subsequent analyses (RunAnalysis.m).
%
% INPUTS:
% - Subject_Details: structure of demographic information for the analysis cohort e.g. age,
% gender, brain volume,...
% - MDI: Motion Degradation Index values for each... |
9525a23cde15d66842c298d38f67e267107d10070d7c1d67189370f347152775 | MATLAB | 2,136 | 89 | function SaveResults(self, varargin)
if self.VerboseLevel > 1
fprintf('Saving results...\n')
end
Results = self.Results;
Clips = struct;
Clips.Train = CreateClipDataToSave(self.NetworkData.Train);
Clips.Validate = CreateClipDataToSave(self.NetworkData.Validate);
Clips.Test = CreateClipDataToSave(self.NetworkData.... |
d6f67a031f69412ed4bb3ccc42422fd3b8310cf0c25baddc3091b263696f38ac | MATLAB | 2,137 | 75 | clc; clear; close all
Fig5e = figure();
Ntrials_5=10000;
%Ntrials_2: number of learning cycles to learn the background containing a new embedded pattern (step 5).
%(Note initial conditions in this step come from step2)
N_mu=500; %There are \mu independent embedded patterns, 500 simulations (number of simula... |
0fa90341b75b5257e111f54723275046a94990a1fc3b03aef6ae426269635eb5 | MATLAB | 2,138 | 88 | function [H] = generateH(R, prior_setup, generate_with_t, use_log_scale_for_mean)
if(nargin < 3)
generate_with_t = false;
end
if(nargin < 4)
use_log_scale_for_mean = false;
end
if(prior_setup.include_rank_constant)
nd = sum([prior_setup.T(:).on]) + prior_setup.V.on;
rank_scale = -log(R)/nd;
% rank... |
0212e40df1410e934afa13761fcf7f87ab5c3921f0f8d583f96652eabde7cc1f | MATLAB | 2,139 | 82 |
%% plot hemifield
function [] = plotHemifield(ax, dir, major_dir_eb, color_vec, color_region)
hold(ax, 'on');
dirs = dir + [0 180];
%plot region
if(nargin > 3 || ~isempty(color_region))
rr = 1.2;
%% region 1
cs = color_region(1, :);
theta = linspace(ma... |
5c01dfe8ebf3bf843be61b3d7b18dc0267bfb8ed03532ad620d8a596e9024c15 | MATLAB | 2,139 | 90 | function [ netsimile ] = netsimile_dist_bu(amat,bmat)
% weighted implementation of netsimile algo for comparing networks
% https://arxiv.org/abs/1209.2684
% enfore binary
amat = amat > 0 ;
bmat = bmat > 0 ;
% get the netsimile of each network
ns_a = feat_extract(amat) ;
ns_b = feat_extract(bmat) ;
% canbera distanc... |
c99e01dffe4f025be79edbca01e0f869193e9a114599e86866a0c4b2d1b74df5 | MATLAB | 2,140 | 59 | function [subject, session, channel, Spikes] = pp_launch_manual_sort(Pname,subject,session,channel,Spikes)
%
% pp_launch_manual_sort( subject, session, channel )
% Basically just launches the splitmerge tool from UMS. But if called
% with output arugments, will add all relevant variable to workspace,
% which ... |
e9fbdde15f8553c1afd4b53ec3faba802edf4b8911cf472e341ead7df9699b88 | MATLAB | 2,140 | 66 | function speech=newMakeVowel(dur,sampleRate, F0, f1,f2,f3,f4)
% y=jansMakeVowel(dur,sampleRate, F0, f1, f2, f3);
% makes a very simple artificial vowel
% adapted from Slattery's auditory toolbox makevowel.m
% dur is duration in seconds
% sample rate is in Hz
% F0 is the fundamental (pitch)
% f1-f3 are the f... |
05c52201de5460311526766d694cb165f2ae1a0bb7474ce124dcfc3ed3c5d76f | MATLAB | 2,145 | 65 | function [evtB,Clr]=ShowMSUA(Tmtx,iFR,CL,iFRred,ret,TrCol,sc)
% Plot a heatmap timeseries showing the firing rates of all single units
%
% (c) 2014 Daniel Durstewitz, Bernstein Center for Computational Neuroscience, CIMH/ Heidelberg University
% Edited by Aleksander PF Domanski PhD UoB 2015
% aleks.domanski@bristol.ac... |
3042bad7de5386a3e233f22859768dc879875f1354988dca6cc61975c5314bbe | MATLAB | 2,145 | 71 | clc
close all
clear variables
%date: 6th Feb 2021
%VM
font = 14;
linewidth = 2;
format long;
%addpath('/Users/varunmannam/Desktop/Spring21/Research_S21/Feb21/SPIE_SR/old_SR_files/mse_plots/');
addpath('/Users/varunmannam/Desktop/Spring21/Research_S21/Feb21/0702/SR_new_results/mse_loss/'); %new simulations
lr1 = load... |
ea0a1663548663b8532d463ea1585888391decdd1c2acef37cf49f71a63d1f2f | MATLAB | 2,146 | 56 | function [pc1_ipsi,pc1_contra,lags_xc] = getPCIpsiContra_1ms(db,P,ipsiContraP)
window = ipsiContraP.window;
psthBinSize = ipsiContraP.psthBinSize;
mouseRefUni = unique(P.mouseRef);
pc1_ipsi = cell(1,numel(mouseRefUni));
pc1_contra = cell(1,numel(mouseRefUni));
lags_xc = cell(1,numel(mouseRefUn... |
f3c74974f0ae062181f42939b76d8b83797979427b3081f93e04dc3e698d59ec | MATLAB | 2,147 | 75 | function SCRATCH_view_block_FRFs(unitid)
%% Plot all FRFs from currently selected block in DB_Browser
if nargin == 1 && ~isempty(unitid)
IDs = mym('SELECT * FROM v_ids WHERE unit = {Si}',unitid);
else
IDs = getpref('DB_BROWSER_SELECTION');
end
U = mym(['SELECT v.unit,u.pool,c.channel FROM v_ids v ', ...
... |
f166235198236a134e45a4cc118e44bf4833ebae5b3267cd414f04f170ab9a48 | MATLAB | 2,148 | 85 | function DB_CheckAnalysisParams(n,d,u,conn)
% DB_CheckAnalysisParams(n,d)
% DB_CheckAnalysisParams(n,d,u)
% DB_CheckAnalysisParams(n,...,conn)
%
% check to see if necessary parameters already exist on db_util and add if
% not there
%
% Where n is a cellstr array of parameter names and d is a cell string
% arra... |
5460e18c83d8bdb174d4cfdde58aaf78ddebcb421b577bfc37ed9e899e098f40 | MATLAB | 2,149 | 60 | function [D, ni] = find_nn(X, k)
%FIND_NN Finds k nearest neigbors for all datapoints in the dataset
%
% [D, ni] = find_nn(X, k)
%
% Finds the k nearest neighbors for all datapoints in the dataset X.
% In X, rows correspond to the observations and columns to the
% dimensions. The value of k is the number of neighbors t... |
fe9b4092a431321364194d2e1842b91b6a6dabd3339d103e9e7fc45b455324ba | MATLAB | 2,149 | 101 | function [fit1,a5,a6,d4,eegz4] = fitness_calc(A1, numreps,subject)
% function simulated model
Liley_params;
% Load data
load('Control_EEG_data.mat')
data = Control_EEG_data(subject,:)-mean(Control_EEG_data(subject,:));
data = zscore(data);
data = filter_b_f(data, 2, 256,'high',4);% 2 Hz high pass filter
dat... |
e57faf1eca66e51467a072d750770581d6266c0742d0e78951107b9e35c283b5 | MATLAB | 2,152 | 71 | function signalGrid = interpolateDeadElectrodes(signalGrid, deadElectrodes, angleFlag)
% Interpolate dead electrodes to be the median value of surrounding nodes.
% Input signalGrid can be a 2D matrix with dimension [X Y] or a 3D matrix
% with dimension [X Y T], where t gives time. badElectrodes is
% an array containing... |
33d3eae5614cf1ff71748bef8be387a3e37e67fa14441abf68681751e65c5d6f | MATLAB | 2,154 | 76 | % Sets public properties of a MatLab object using a name-value list.
% Properties are traversed in the order they occur in the class definition.
% Copyright 2008-2009 Levente Hunyadi
function obj = constructor(obj, varargin)
assert(isobject(obj), ...
'Function operates on MatLab new-style objects only.');
... |
e60bbb41aa50fcaf43077baf2f6876de9bf8d6284ee91c02461bf02259bc8627 | MATLAB | 2,155 | 75 | function [BC,nApplied]=ApplyDispPIV(dx,PIV,Set,X,X0)
% Applies displacement of PIV data. PIV struct contains:
% PIV.X(i,:): x annd y positions of PIV node i
% PIV.U(i,:): x annd y displacement of PIV node i
% X(i,:) : x coordinates of mesh node i. 3rd dimension is computed.
nPIV=size(PIV.X,1);
BCu=zeros(0,3);
nn... |
a225c8b18f5c3695eddd803da5edcdde25f09fc199d4c602a1247720b5442a60 | MATLAB | 2,156 | 99 | function Pout = MySPM_BatchMasking2(P,Pm)
% Pout = MySPM_BatchMasking2(P,Pm)
%
% Input:
% P ... Path(s) to NIfTI files in a cell array
% Pm ... Path to one mask file
%
% Output:
% Pout ... Resulting masked images prefixed with 'm'
%
% NOTE: If this function does not work for 4D files, then you may hav... |
b8a3b5ca1b9ebc940791b6fa1e9a0a4a258d5e67966f063ee4c8e487863b0991 | MATLAB | 2,156 | 60 | % Example 3: Feature selection using iterative procedure
%
% In this Example, feature selection using CAMs is performed in an iterative
% manner. There are 3 steps in the iterative procedure:
% 1) conversion of tabular data to image
% 2) estimating/validating CNN net using training and validations
%... |
cc7a309e38a4c57341b7c5e284a0e374378308674a47159863f8491e231db019 | MATLAB | 2,157 | 79 | function step1_tempConverter(rootDir)
%
% Convert weird temp files from TC Central into table with same file name
% (but different extension)
try
% Define paths
if nargin == 0
rootDir = Cloudstation('Vowels\Noise\Cooling\Data');
% rootDir = Cloudstation('Vowels\Spatial_Unmasking\Cooling\Data');
e... |
a9feb6691a351c63451a92d3fd2ff3389833b42f66448682fde0343f01559aad | MATLAB | 2,159 | 86 | function LMER_ALL_PID_RAW_reduced
% Function to prepare the regression table for Linear Mixed-Effects Regression Model
% in R
% The metric variables are d here
%
% Fran Hancock
% Dec 2021
% fran.hancock@kcl.ac.uk
%
%
% Function to investigate the relationships between time varying measures
% of CHI OCC HC and PID and t... |
65576795b2a27f13e890b6d056d02fe86434765717c4ef0e86a59ada4e6512f4 | MATLAB | 2,161 | 50 | function [B,C,K,n,m,p,Bnorm,commsizes] = comm_mat(W,ci)
%COMM_MAT Returns the block matrix of the community structure of a graph W with given membership vector ci
%
% Inputs W, undirected weighted/binary network.
% ci, membership vector
%
% Outputs: B, block matrix of community structure.... |
e79b0fd0ca04cfd352ac8f8240711ca8b006c2c5fae9441184941c4a17cf5d7d | MATLAB | 2,161 | 64 | function manipulate_prairie_data(dirname, channel, shift, rotation)
disp(['Warning! This script manipulates prairie data with shifts or rotations']);
disp(['Warning! This should be used only on a COPY of original data, for diagnostic purposes.']);
disp(['Warning! Document which directory is manipulated, so no o... |
6718ded3117a2b04f417b753c02af624d7ea5aa27534116dc06693c591647ef1 | MATLAB | 2,162 | 60 | function [ colormap ] = ReadColorsFile( filename, varargin )
%READCOLORSFILE Returns a colormap with [ID R G B A] entries mapped to an ID
optargin = size(varargin,2);
%Parse the optional arguments
DefaultAlpha = 1;
if optargin > 0
DefaultAlpha = varargin{1};
end
colorm... |
b3ed21301052ee8c91b9172861675bc85805fc622dc6ef22cf5a31cdd124cfa0 | MATLAB | 2,168 | 30 | % REMOVE BAD CHANNELS - VARIABILITY METHOD Formula %
function [channel_amp_data_CombinedCutoff_logical, channel_grad_data_CombinedCutoff_logical, low_sig_range_all_channels_val_logical] = ...
bst_ast_remove_bad_channels_variability_formula(all_amp_data, all_grad_data, chanAmpDevThreshold, chanGradDevThreshold)
... |
f4c550c08a6ddfe17e786f7e82b804093e13896256fd64e48b2c046bed77066c | MATLAB | 2,171 | 65 | function [ha hb hc] = shadedplot(x, y1, y2, varargin)
% SHADEDPLOT draws two lines on a plot and shades the area between those
% lines.
%
% SHADEDPLOT(x, y1, y2)
% All of the arguments are vectors of the same length, and each y-vector is
% horizontal (i.e. size(y1) = [1 N]). Vector x contains the x-axis va... |
efdb141bcaaed2736534c2e770bfc4d3d75fba690ee827eb7a4e2ecb674a7dd3 | MATLAB | 2,172 | 66 | function [startIndices, endIndices, outputArray] = findRuns(...
binaryArray, minLength, maxLength, ignoreZeros)
% FINDRUNS finds the start and end indices of runs of consecutive 1's in
% BINARYARRAY that are longer than MINLENGTH (default 0) and shorter
% than MAXLENGTH (default infinity). IGNORENZEROS is an option... |
d4a8b1f752acd70a705d334155e5564a4ad728602a995ccb1329d072300a83bb | MATLAB | 2,175 | 55 | function [] = compileCUDAMexLibs(idx)
[~, CUDAdirectory, ~, ~, sourceDir, objDir] = kgmlm.CUDAlib.myCUDAPaths();
fNames = {[sourceDir 'kcBase.cu ' sourceDir 'kcGMLM_dataStructures.cu ' sourceDir 'kcGMLM_computeBlock.cu ' sourceDir 'kcGMLMPop_computeBlock.cu ' sourceDir 'kcGMLM.cu '];
[sourceDir 'kcBase.cu ' ... |
a7f18abaeba306554fd3b37cab2157619ea47eb099b5bb080fa9510e80424dc7 | MATLAB | 2,177 | 53 | function [fiber_c] = store_fiberCenter(section_pop, fiberCenterx, ...
fiberCentery, grid_x, grid_y)
% STORE_FIBERCENTER Convert fibers center in the cross-sectional area
% from a x and y cartesian coordinates to percentage x, y coordinates: each
% center coordinate is normalized on the total x and y grid ava... |
ef6210ce5dcb483372f6eaacca105b4cea08e76e908c7a99657955cadc284e49 | MATLAB | 2,177 | 69 | function handles = updateSoundLevelandFreq_SanesLab(handles)
%handles = updateSoundLevelandFreq_SanesLab(handles)
%
%Custom function for SanesLab epsych
%
%This function updates sound level and frequency in the rpvds circuit.
%
%Input:
% handles: GUI handles structure
%
%Written by ML Caras 7.28.2016
global AX RUNTI... |
30562064e49cce2d058fc3e56ffa8e4c8662199a820671d117f03e9ee3eee8cd | MATLAB | 2,178 | 70 | %% Response Latency
function RL = NHP_PlotResponseLatency(Data,ax)
persistent Lo
IND = NHP_decodeResponseCode([Data.ResponseCode]);
Angle = [Data.Behavior_Speaker_Angle];
uAngle = unique(Angle);
rl = cell(size(uAngle));
for i = 1:length(uAngle)
ind = uAngle(i) == Angle;
ind = ind & ~(IND.Abort | IND.NoR... |
18c91661aa58daa135e87a1c722f5a739481fd75d905702036282fcd109b02e1 | MATLAB | 2,180 | 42 | function t3_calibrate
addpath('../code');
% Here we go over how to calibrate the adaptive procedure to obtain consistently reliable thresholds.
%
% This is a bit of a hack that I've worked on through trial and error across 3 published psychophysics experiments
% and across too many pilot sessions to count. It works... |
e566509899db809ceefaf181f047046cdfbe37a8c51e5c0b7c5c4b720a8812e7 | MATLAB | 2,180 | 69 | function [score]= Emeasure(FM,GT)
% Emeasure Compute the Enhanced Alignment measure (as proposed in "Enhanced-alignment
% Measure for Binary Foreground Map Evaluation" [Deng-Ping Fan et. al - IJCAI'18 oral paper])
% Usage:
% score = Emeasure(FM,GT)
% Input:
% FM - Binary foreground map. Type: double.
% GT - Binary ... |
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