sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
7092c7032d090f4fd659a20269a237ecfb7606bb8a560c7a162782af61d7c1e6 | MATLAB | 471 | 20 | function [OFC,notOFC] = onlyOFC(all_S,cells,all_SU,all_index)
for i = 1:length(cells)
S = all_S{all_index{cells(i),4}};
SU = all_SU{cells(i)};
try
depth(i,:) = [SU.AP,SU.ML,SU.DV];
location{i} = SU.location;
catch
SU = channelLocation_MD(S,{SU});
depth(i,:) = [SU{1}.AP,SU{1}.ML,SU{1}.DV... |
d359132d4cc921794a8e7580c8653239ab746b1d7ea29c2667e022f9d61606ec | MATLAB | 471 | 15 | function TMSTPCalc
% Written by Dr. Gong-Jun JI, jigongjun@163.com, Anhui Medical University
inpath = spm_select(1,'dir')
outpath = spm_select(1,'dir')
list = dir (inpath);
for i = 3 : length(list)
img=dir([inpath,filesep,list(i).name,filesep,'*.nii']) ;
head = spm_vol([inpath,filesep,list(i).name,filese... |
5a9aee1b8462c5cb89615d801c271330762fe7e928636f1c24c729ff107bf071 | MATLAB | 472 | 22 | %{
#
-> tune.MovieOracle
-> `pipeline_fuse`.`__activity__trace`
-> stimulus.Clip
---
trials : int # number of trials used
pearson : float # per unit oracle pearson correlation over all movies
%}
classdef MovieOraclePearson < d... |
8f76c91431a82b9b629b41e591f082b778f1f1ec62247449e9770ef312f65e42 | MATLAB | 472 | 26 | %% test weighted random selection in fortran
data = dlmread('./testout.txt');
for c = 1:10
counts(c) = nnz(data(:,2)==c);
end
%%
list = 1:10;
plot(list,counts,'.-',list,list.^2/sum(list.^2)*size(data,1))
%% check sampling without replacement
data = dlmread('./testout.txt');
any(data(:,2)==data(:,3))
for c = 1... |
ae271d5b4167403609c442286e7dcc098a54e5faacaf95092c1e7d8e5579fffd | MATLAB | 472 | 22 | function [v] = tapas_mh_mc3_arc(ollh, olpp, nllh, nlpp, ...
ratio, T)
%% Acceptance rejection criterion for metropolis hastings in the context of
% population mcmc.
%
% aponteeduardo@gmail.com
% copyright (C) 2016
%
v = bsxfun(@times, nllh, T) + nlpp - (bsxfun(@times, ollh, T) + olpp) ...
+ ratio;
nansv = isn... |
ccd9e69ec956d6c91c0d6ee3b3571f8627e3665cbc5c89c3ae862e3df89582d7 | MATLAB | 472 | 12 | % This script removes the 'elec' field from the MEG files
meg_files = dir([main_path 'Dataset/*_meg_rest_60sec.mat']);
for i=69%1:length(meg_files)
meg = load([meg_files(i).folder '/' meg_files(i).name]);
if isfield(meg,'elec')
disp(['removing the elec filed from the meg file ' meg_files(i).name])
... |
d4f8fb437810982a1dc5c8fe1d8478e8348316c54e0650c1e58a40c899f3fc54 | MATLAB | 472 | 14 | function [tpl, str] = subst(tpl,handle)
%TEMPLATE/SUBST Substitute a replacement field by its value
% STR = SUBST(TPL,HANDLE) substitute all the known fields of variable HANDLE
% in the template TPL.
% Copyright (C) 2003 Guillaume Flandin <Guillaume@artefact.tk>
% $Revision: 1.0 $Date: 2003/05/05 22:19:51 $
tpl =... |
4dd919c40e0ff0f5fc1bce5e4c34f354959a13335809eb8a1b51a5d86345fcff | MATLAB | 473 | 20 | classdef CellVariable
%CELLVARIABLE Summary of this class goes here
% Detailed explanation goes here
% Copyright (c) 2012-2016 Ali Akbar Eftekhari
% See the license file
properties
domain
value
end
methods
function cv = CellVariable(meshVar, cellval)
i... |
9ccc0096529e33855f03069ff86b4c04e1f89ffe92dfb9056f1cfb81b618c7ad | MATLAB | 473 | 22 | %{
#
-> tune.MonetOracle
-> `pipeline_fuse`.`__activity__trace`
-> stimulus.Monet
---
trials : int # number of trials used
pearson : float # per unit oracle pearson correlation over all movies
%}
classdef MonetOraclePearson < ... |
06e62f84727cf0a8b45ad2602c85796ff4935ab60d88da4894e32a1476b43fd8 | MATLAB | 474 | 22 | %{
pre.ExtractSpikes (computed) # inferences of spikes from calcium traces
-> pre.ExtractTraces
-> pre.SpikeInference
---
%}
classdef ExtractSpikes < dj.Relvar & dj.AutoPopulate
properties
popRel = pre.ExtractTraces * pre.SpikeInference & struct('language','matlab')
end
methods(Access=pro... |
2799a4e6904f097cfc2d0a4cabd4ec2e8f93330f5f4475143fd507c0a2e98140 | MATLAB | 475 | 20 | function c_code_works = test_sttc_c_code()
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
Time = [1, 10];
spike_times_1 = [1, 4, 5, 8];
spike_times_2 = [2, 4.5, 6, 10];
dtv = 0.5; % in seconds, the delay time to look for conincidental spikes
N1v = length(spike_times_1);
N2v = length(s... |
42689e84194d8e38ca596e3671894ecff2e3df721d345480880f06104723a376 | MATLAB | 475 | 17 | function struct_out = concatStruct(struct1,struct2,concatdim);
%function struct_out = concatStruct(struct1,struct2,concatdim);
if nargin<3
concatdim = 1;
end
fields1 = fieldnames(struct1);
fields2 = fieldnames(struct2);
if ~all(ismember(fields1,fields2))
error('Structure fields don''t match!'); end
struct_ou... |
5977621a316622ae1628a23a3648135f6c9fb3cd8c46e718d1ccd8c0fe257cdc | MATLAB | 475 | 23 | %{
aod_monet.DriftResponseSet (computed) # my newest table
-> aod_monet.DriftTrialSet
-> aodpre.ExtractSpikes
---
%}
classdef DriftResponseSet < dj.Relvar & dj.AutoPopulate
properties
popRel = aod_monet.DriftTrialSet*aodpre.ExtractSpikes & aodpre.Spikes
end
methods(Access=protected)
... |
b00268c2936e3383820dc654a43b6a8dabdef5f985368abca7581cda19dcf67e | MATLAB | 475 | 20 | function [clean,isOutlier] = RemoveOutliers(data,whisker)
if ~exist('whisker','var')
whisker = 1.5;
end
% if size(data,2)>0,
% clean = data; isOutlier = zeros(size(data));
% for i=1:size(data,2)
% [clean(:,i),isOutlier(:,i)] = RemoveOutliers(data(:,i));
% end
% end
q1 = quantile(data,0.25... |
17591420bef0bd519dc64842625d8be26ef77f420cb2c9ba7ef557824e9ea618 | MATLAB | 476 | 31 | function r = times(p,q)
%TIMES this function multiplies the x, y, and z values of the structures that I use in
% the FVtool.
%
% SYNOPSIS:
%
%
% PARAMETERS:
%
%
% RETURNS:
%
%
% EXAMPLE:
%
% SEE ALSO:
%
% Copyright (c) 2012-2016 Ali Akbar Eftekhari
% See the license file
if (isa(p, 'CellVariable')&&isa(q, 'CellVariab... |
af0ef17f245f652d8eebf65b512eecae390468f8b2a8aa2f7f0b9c87a8126205 | MATLAB | 476 | 31 | function r = power(p,q)
%power this function power (.^) the x, y, and z values of the structures that I use in
% the FVtool.
%
% SYNOPSIS:
%
%
% PARAMETERS:
%
%
% RETURNS:
%
%
% EXAMPLE:
%
% SEE ALSO:
%
% Copyright (c) 2012-2016 Ali Akbar Eftekhari
% See the license file
if (isa(p, 'CellVariable')&&isa(q, 'CellVariab... |
eeffdf91d6d8555ebdb367ac3d8a1ed46e0ca77531188ad8881f1a30d8140fb3 | MATLAB | 476 | 20 | classdef NormOffset < dagnn.ElementWise
properties
param = [1 0.5]
end
methods
function outputs = forward(obj, inputs, params)
outputs{1} = vl_nnnoffset(inputs{1}, obj.param) ;
end
function [derInputs, derParams] = backward(obj, inputs, param, derOutputs)
derInputs{1} = vl_nnnoffset(... |
79c5786a6f8fb38357db7026ce17f5b3111399c4e28e11dca518e0c4f1667070 | MATLAB | 477 | 22 | classdef FaceVariable
% Copyright (c) 2012-2016 Ali Akbar Eftekhari
% See the license file
properties
domain
xvalue
yvalue
zvalue
end
methods
function fv = FaceVariable(meshVar, facevalX, facevalY, facevalZ)
if nargin>0
fv.domain = meshVar... |
8f31ca0b7ab1af0332eee4bde1473c589727bd9e836b366f788e8854e1e18820 | MATLAB | 477 | 31 | function r = rdivide(p,q)
%RDIVIDE this function divides the x, y, and z values of the structures that I use in
% the FVtool.
%
% SYNOPSIS:
%
%
% PARAMETERS:
%
%
% RETURNS:
%
%
% EXAMPLE:
%
% SEE ALSO:
%
% Copyright (c) 2012-2016 Ali Akbar Eftekhari
% See the license file
if (isa(p, 'CellVariable')&&isa(q, 'CellVaria... |
be85138e3057467915da5580e75d9b444a3ba7f87d22ea717aba7fd6f02d1d2b | MATLAB | 477 | 21 | function h=setfpos(x,y)
%setfpos Set figure position.
%
%
% h = setfpos(X,Y)
% X - Horizontal length.
% Y - Vertical height.
% h is the figure handle to the figure just handled
% Sets current figure lower left position to X by Y pixels (measured from
% lower left corner of screen. On image, max pixels are about
% ... |
086c7bc888748a9267c8bf86bd497784f9042e6f9aa8c498efc3d8ef45b04df8 | MATLAB | 478 | 21 | %{
rf.Lens (lookup) # objective lens list
setup : char(4) # two-photon setup
lens : char(4) # objective lens
---
%}
classdef Lens < dj.Relvar
methods
function fill(self)
self.inserti({
'2P1' '16x'
'2P1' '25x'
... |
41f31f5d8f6447dfd073e6859b25fde0af8557415ed26e77b58cd0c944adac48 | MATLAB | 478 | 20 | classdef LRN < dagnn.ElementWise
properties
param = [5 1 0.0001/5 0.75]
end
methods
function outputs = forward(obj, inputs, params)
outputs{1} = vl_nnnormalize(inputs{1}, obj.param) ;
end
function [derInputs, derParams] = backward(obj, inputs, param, derOutputs)
derInputs{1} = vl_nnn... |
52be0a8b4f37e0c08aa50dedcc5818125bb357de1b817b7174ed3c0c80ac6564 | MATLAB | 478 | 18 | function [SY,ix] = compo_init_index(xx,YX,YY,T)
%
% --- Initialization: Find input component with maximum correlation
%
% N # of output
% M # of input
% T Total number of data
% xx = diag(XX)' % 1 x M_all
[N, M_all] = size(YX);
R = sum(YX.^2,1) ./xx; % (YX)^2/(XX) : correlation of Y & X
[Rmax, ... |
57ee7762084d36ee3c559663f7ace2fd206a6fefefc313e4897ec019c0c9677d | MATLAB | 478 | 23 | %{
trk.SelectedFrame (computed) # This schema only contains detected frames that meet a particular quality criterion
-> trk.EyeFrameDetection
-> trk.SelectionProtocol
---
%}
classdef SelectedFrame < dj.Relvar & dj.AutoPopulate
properties
popRel = trk.EyeFrameDetection*trk.SelectionProtocol % !!! update the popul... |
8b2397fce94186d0a0188c1aebc3d457c7fe7ca959798ecbedd0dd99c039424b | MATLAB | 478 | 14 | function [popt] = screen_optrate(S)
%calculate the probability of opting out for each session, ignoring violation trials.
%inputs: S struct.
%outputs: opt-out probability for each session.
%modified by cmc 10/19/21.
popt = nan(length(S.pd),1);
for j = 1:length(S.pd)
if isstruct(S.pd{j})
goods = ~isn... |
c964c8d47f8cae5be9fbf49d170796dd6f6760a521a6ad5b8770ec655b417ebf | MATLAB | 478 | 14 | function map2surf = BoSurfStatMakeParcelData(mapOnParcel, S, parcel)
% map2surf = BoSurfStatMakeParcelData(mapOnParcel, S, parcel)
% makes a surfacefile with 1 x v points from a 1 x p parcellation data,
% needs to supply a 1 x p surface parcellation (with p unique elements)
%
% author: boris@bic.mni.mcgill.ca
map2su... |
8b5d9a06726a868e658c5f7cb3137b487e875f7f82fc607ef2863f22148f1452 | MATLAB | 479 | 20 | classdef NormOffset < dagnn_bc.ElementWise
properties
param = [1 0.5]
end
methods
function outputs = forward(obj, inputs, params)
outputs{1} = vl_nnnoffset(inputs{1}, obj.param) ;
end
function [derInputs, derParams] = backward(obj, inputs, param, derOutputs)
derInputs{1} = vl_nnnoffs... |
aff4cba6153cbb41fbb5c979b8a0183f7a10bd387a4ff3c952ff1d62a2a4c26c | MATLAB | 479 | 34 | function curfol()
% EXAMPLE USE WITH ARGUMENTS
% curfol() - use 1
% HELP:
% Simple opening of the current folder in Windows explorer.
%
% HISTORY
% - 19-04-24 17:34:40 - created by Radek Chrapkiewicz
%
% ISSUES
% #1 - issue 1
%
% TODO
% *1 - get the first working version of the function!
%% CONSTANTS
%% VARIABLE CHE... |
df820800fd912da19d3394510edc31ac9c5d9ed653a3c7e8b6a05383e4cc4b61 | MATLAB | 479 | 20 | classdef SpatialNorm < dagnn.ElementWise
properties
param = [2 2 10 2]
end
methods
function outputs = forward(obj, inputs, params)
outputs{1} = vl_nnspnorm(inputs{1}, obj.param) ;
end
function [derInputs, derParams] = backward(obj, inputs, param, derOutputs)
derInputs{1} = vl_nnspnor... |
ed5d50973e20cbd022b012dab6ae2dd55ae7f39b461ac54aa133d77176b99d34 | MATLAB | 479 | 12 | function[xvalscm, yvalscm] = convert_to_cm(xvals, yvals, ppcm)
%%convert_to_cm converts between pixels and cm
% [xvalscm, yvalscm] = convert_to_cm(xvals, yvals, ppcm)
% This function takes worm tracks, represented as
% x-, y-coordinates in pixels, and turning them in to cm values.
%
%% Convert Camera Data from p... |
efab0f07d3719e6dde91296431f558bdd63315af579c0852002485b40970d1a4 | MATLAB | 479 | 8 | function [indmin mdall notenough]=multimodelnlm_global(Age_gender,Brainsz,data_r,ylabelname,Plotornot,indall_select,betarealinitial)
for i=1:size(indall_select,2);
Age_gender_new=Age_gender(indall_select(:,i),:);
Brainsz_new=Brainsz(indall_select(:,i));
data_r_new=data_r(indall_select(:,i));
[indmin(:,:,i) mdall{i... |
89a2c1f7d6a249d135dee493b36a8056f3e696e41afbdb36ed65e9177af77e75 | MATLAB | 480 | 17 | function txt=SurfStatDataCursor(empt,event_obj)
pos=get(event_obj,'Position');
h=get(event_obj,'Target');
v=get(h,'Vertices');
x=get(h,'FaceVertexCData');
id1=min(find(v(:,1)==pos(1)&v(:,2)==pos(2)&v(:,3)==pos(3)));
tag=get(get(h,'Parent'),'Tag');
[s,a,id0]=strread(tag,'%s %d %d');
id=id1+id0
txt = {['x: ',num2str(pos(... |
46d220b2dc33e62109c00fe384d68bb61629c5595aa59848e7a5786414898bd0 | MATLAB | 481 | 20 | classdef LRN < dagnn_bc.ElementWise
properties
param = [5 1 0.0001/5 0.75]
end
methods
function outputs = forward(obj, inputs, params)
outputs{1} = vl_nnnormalize(inputs{1}, obj.param) ;
end
function [derInputs, derParams] = backward(obj, inputs, param, derOutputs)
derInputs{1} = vl_... |
9857a3c73897e78517a70e2f99e5b28f67d10e6e115ef78c1ca0ed33465c573b | MATLAB | 481 | 23 | function [scut] = calc_scut(data)
% calculate threshold of similarity values from shuffled data
num_shuff = 20;
p = 0.98;
dims = size(data);
% calculate similarity matrix
warning('off')
S = zeros(dims(2),dims(2),num_shuff);
for n = 1:num_shuff
data_shuff = shuffle(data,'time');
S(:,:,n) = 1-pdist2(data_shuff'... |
bd860f5e1c735961b4ba16c84039130e2a4cfcd1208bb130e28ccd437b147fb8 | MATLAB | 481 | 22 | %{
# individual units corresponding to <module>.ScanSet.Unit
-> `pipeline_experiment`.`scan`
-> `pipeline_shared`.`#pipeline_version`
-> `pipeline_shared`.`#segmentation_method`
unit_id : int # unique per scan & segmentation method
---
-> fuse.ScanSet
%}
classdef ScanSetU... |
cf6e46d28aa782f0c1f1b264c678e6cf38d86ee02d025fa6d6891f948295d641 | MATLAB | 481 | 21 | function [v] = tapas_mh_mc3g_arc(ollh, olpp, nllh, nlpp, ...
ratio, T)
%% Acceptance rejection criterion for metropolis hastings in the context of
% population mcmc generalized for hierarchical models.
%
% aponteeduardo@gmail.com
% copyright (C) 2016
%
v = nllh .* T + nlpp - (ollh .* T + olpp) + ratio;
nansv = is... |
d14a1cadb767a5b1c78eecbc3bfb2ae711b6990fc6763ab5a8f166bcf4b373c9 | MATLAB | 481 | 24 | function [rx1,pxy,frq] = NormedSingleCurveLength(x,lag,fs,figurep,nrmdegree)
% this function computes crossed curve length for single time series x
rx1 = zeros(1,lag+1);
for delay=0:lag
rx1(delay+1) = norm(x(1:end-delay) - x(delay+1:end),nrmdegree);
end
rx = [fliplr(rx1) rx1(2:end)];
pxy = abs(fft(rx));
frq =... |
20d2fb630da164839a25c3909aa3eb2e018128532facf229a7c5242025202aa7 | MATLAB | 482 | 44 | function WriteAveragedStack(fn, Nplanes)
Nfiles = numel(fn);
im = loadTifFast(fn{1})./Nfiles;
for i = 2:Nfiles
im = im+loadTifFast(fn{i})./Nfiles;
end
figure;
for i = 1:Nplanes
subplot(1,Nplanes, i);
imagesc(mean(im(:,:,i:Nplanes:end), 3));
axis image;
end
pth = fileparts(fn{1});
... |
4781f2886ea2e94dbecdf3b2e0fa20d578cbe19a5a604002a6c6d8d2f631d602 | MATLAB | 482 | 23 | function [jcut] = calc_jcut(data)
% calculate threshold of similarity values from shuffled data
num_shuff = 20;
p = 0.99;
dims = size(data);
% calculate similarity matrix
warning('off')
S = zeros(dims(2),dims(2),num_shuff);
for n = 1:num_shuff
data_shuff = shuffle(data,'time');
S(:,:,n) = 1-pdist2(data_shuff'... |
e908115a69e551fca8dcf14989d42a15b0d0eff586b29d5df18bd58e77490d77 | MATLAB | 482 | 20 | classdef SpatialNorm < dagnn_bc.ElementWise
properties
param = [2 2 10 2]
end
methods
function outputs = forward(obj, inputs, params)
outputs{1} = vl_nnspnorm(inputs{1}, obj.param) ;
end
function [derInputs, derParams] = backward(obj, inputs, param, derOutputs)
derInputs{1} = vl_nnsp... |
16a8c5c494760f8a16202b8215a0f5ac29b0c28d51bc7d4a34c52feec850e237 | MATLAB | 483 | 19 | function A = invPD(A)
% FORMAT iA = brca.utils.invPD(A)
% A - A positive-definite square matrix
% iA - Its inverse
%
% Stable inverse of a positive-definite matrix.
% Eigendecomposition is used to compute a more stable inverse.
% John Ashburner
[V,D] = eig(A);
if any(diag(D) <= 0)
warning('Matrix has... |
afe9b57c35feacbf33b430e6b920bf752ecd144e48b9735bc3bcdae1ad4ffb9d | MATLAB | 483 | 25 | %{
rf.Fluorophore (lookup) # calcium-sensitive indicators
fluorophore : char(10) # fluorophore short name
-----
notes = '' : varchar(2048)
%}
classdef Fluorophore < dj.Relvar
methods
function fill(self)
self.inserti({
'OGB' ''
'GCaMP6s' ''
... |
e58dbd7212ce5e210a2a47827a34f022d629965b64d30975253971becab3c542 | MATLAB | 483 | 25 | %close all
%clear all
% path(path,'.\AGORA\FUZZCLUST')
%the data
data.X =Z(:,[1 2]);
[N,n]=size(data.X);
%data normalization
data = clust_normalize(data,'range');
plot(data.X(:,1),data.X(:,2),'.')
hold on
%parameters given
%param.c = [.821 .7132
% 0.1 .5
% .1535 .7775]
param.c=ii;
param.vis=1;
par... |
3a843431fce5e77cc0ea0c363299ba90b8fe5103c92b4a0d49a62b286eba8fd9 | MATLAB | 484 | 18 | function Y = multiskew(X)
% Returns the skew-symmetric parts of the matrices in the 3D matrix X.
%
% function Y = multiskew(X)
%
% Y is a 3D matrix the same size as X. Each slice Y(:, :, i) is the
% skew-symmetric part of the slice X(:, :, i).
%
% See also: multiskewh multiprod multitransp multiscale multisym
% This f... |
3c08197b43a51aab48d7e0d0100ea3946a03238cbfaae53a0ee597f83511660e | MATLAB | 484 | 18 | function Y = multiherm(X)
% Returns the Hermitian parts of the matrices in the 3D matrix X
%
% function Y = multiherm(X)
%
% Y is a 3D matrix the same size as X. Each slice Y(:, :, i) is the
% Hermitian part of the slice X(:, :, i).
%
% See also: multiprod multitransp multihconj multiscale multiskew multiskewh
% This ... |
63b1b697a03a6b0f4a24b6969075d97feb22d81a3a585d5220d33272ff0b4f74 | MATLAB | 484 | 12 | function ret = findFivePercentageOutliers(flatdata)
%isoutlier(..., 'percentiles', [5 95]) written to treat all values at once
numelems = numel(flatdata);
ret = false(size(flatdata));
if numelems < 1
return
end
numexclude = floor((numelems + 9) / 20); %in R2021a, isoutlier excludes 0 for... |
6c2f03dd082297af735c029936b684a738c84c955d94bea9fd297fef5598d3cd | MATLAB | 484 | 20 | function [p,tval] = ttestfast(x)
%function [p,tval] = ttestfast(x)
dim = 1;
nans = isnan(x);
if any(nans(:))
samplesize = sum(~nans,dim);
else
samplesize = size(x,dim); % a scalar, => a scalar call to tinv
end
df = max(samplesize - 1,0);
%xmean = nanmean(x,dim);
%sdpop = nanstd(x,[],dim);
xmean = mean(x,... |
9c1c62cb53a70121a5f16db803ae2a039c663d92187a871f26cc9dacfac40ce8 | MATLAB | 484 | 14 | %{
experiment.LaserCalibrationPowerMeasurement (manual) #
-> experiment.LaserCalibration
wavelength : int # wavelength of the laser
attenuation : tinyint # power setting
bidirectional : tinyint # 0 if off 1 if on
gdd : int # G... |
f5083da6d0d64581c24f5c2ef9b4dc5ea87c663caeba6a7513e13769b62fd22a | MATLAB | 484 | 11 | % This function calculates mean and correlation with respect to the pairwise MEM
% with given h and J.
function [modelMean, modelCorrelation] = mfunc_ModelMeanCorrelation(h,J)
nodeNumber = size(h,1);
vectorlist = mfunc_VectorList(nodeNumber);
prob = mfunc_StateProb(h,J);
modelMean = mean((vectorlist.*(ones(nod... |
8a79fc7fb6e3e5f489e67eb4ebd34df8a723bf190c62d67692ed500ffe857ebf | MATLAB | 485 | 17 | function dfBreak=essential_distMinAnglePair_computeDfBreak(tBreak,Q21)
c=cos(tBreak);
s=sin(tBreak);
% The code below is an optimization exploiting the structure of RBreak to
% substitute the following code
% RBreak=Q1'*[c -s 0; s c 0; 0 0 1]*Q2;
%
% %compute v0 such that RBreak=rot(pi*v0)
% [U,~,~]=svd(R... |
9dc20df7c7bbccbad5c0a8ed07111048fc6a283db606d383e531a4eb6c0c8c84 | MATLAB | 486 | 31 | function r = lt(p,q)
% this function compares the less than condition of x, y, and z values of the structures that I use in
% the FVtool.
%
% SYNOPSIS:
%
%
% PARAMETERS:
%
%
% RETURNS:
%
%
% EXAMPLE:
%
% SEE ALSO:
%
% Copyright (c) 2012-2016 Ali Akbar Eftekhari
% See the license file
if (isa(p, 'CellVariable')&&isa(q... |
2de7b79b2fd630aec14ca8ee8eda2c4af40d8ef871a7e94e619f3b7598989344 | MATLAB | 487 | 19 | function in = zscorein(in)
for i = 1: numel(in)
d = cell2mat(in(i).data');
for ch = 1: size(d,3);
d(:,:,ch) = zscore(squeeze(d(:,:,ch)),0,'all');
end
numtrialspercell = cell2mat(cellfun(@(x) size(x,1), in(i).data,'un',0));
C = cell(1, numel(in(i).data));
trialstart = 1;
for c = 1:numel(in(i)... |
ccfc9ed41921bd8e91479a0728335f38446a52a4ba314c38d812b2a47e14c5df | MATLAB | 487 | 19 | function plot_proba(rez,i)
f=figure;
channel = rez.Merge_cluster{i,5};
Nchan = length(channel);
h=0.001;
for k=1:Nchan
PDF = rez.PDF{i,k};
subplot(Nchan,1,k)
N = histcounts(PDF,0:h:1);
bar(0:h:1-h,(N))
title(['Channel:', num2str(channel(k))... |
34be7f467a20cc9ad138dadc92aebc45331367890218158aef67fce452a619ed | MATLAB | 488 | 17 | function setDefaultFigProps
set(groot,{'DefaultAxesXColor','DefaultAxesYColor','DefaultAxesZColor'},{'k','k','k'})
set(groot, 'DefaultFigureColor', [1 1 1])
set(groot, 'defaultLineLineWidth',1)
set(groot, 'defaultAxesLineWidth',1)
set(groot, 'defaultAxesFontName','Arial')
set(groot, 'defaultTextFontName', 'Arial')
s... |
53fbf02c614b67e566953556d554245b1972248f187a6ad9d18e00d655bf5f79 | MATLAB | 488 | 31 | function r = eq(p,q)
% this function compares the equality condition of x, y, and z values of the structures that I use in
% the FVtool.
%
% SYNOPSIS:
%
%
% PARAMETERS:
%
%
% RETURNS:
%
%
% EXAMPLE:
%
% SEE ALSO:
%
% Copyright (c) 2012-2016 Ali Akbar Eftekhari
% See the license file
if (isa(p, 'CellVariable')&&isa(q,... |
853413914a83ecc757562ff0b8e163106a09d19210d40e571c74fd36cd82fffd | MATLAB | 489 | 16 | %{
# threshold for masks created manually
-> reso.Segmentation
---
threshold_type : tinyint # 1=in SD relative to mean, 2=absolute pixel value
threshold_value : float # depending on type, this is the tresholding value
entry_time=CURRENT_TIMESTAMP : timestamp # time ... |
8a5b1f38ed77a4db21a2546a9274804b00fdd2fc7c667b38a931c52027e267b2 | MATLAB | 489 | 31 | function r = gt(p,q)
% this function compares the greater than condition of x, y, and z values of the structures that I use in
% the FVtool.
%
% SYNOPSIS:
%
%
% PARAMETERS:
%
%
% RETURNS:
%
%
% EXAMPLE:
%
% SEE ALSO:
%
% Copyright (c) 2012-2016 Ali Akbar Eftekhari
% See the license file
if (isa(p, 'CellVariable')&&is... |
8bdfd21fce35d43d123954c2859671c2174521ee12ff5e5ae50795d4fe7ac43c | MATLAB | 489 | 25 | function Wd = diagW(WM)
% build huge diag gram matrix
%
% W = diag(W_1, W_2, ..., W_M)
%
% Inputs: WM, N-by-N-by-M matrix, M N-by-N gram matrix
%
% Output: Wd, N*M-by-N*M diag gram matrix
[row,col,num] = size(WM);
B = zeros(row,col);
P = cell(num);
for i = 1:num
for j = 1:nu... |
27c09a1c30bf4f25cd11ab35a9adc6b6b6c47b1f90b7a62935fd7dcd7213822f | MATLAB | 490 | 31 | function r = ne(p,q)
% this function compares the inequality condition of x, y, and z values of the structures that I use in
% the FVtool.
%
% SYNOPSIS:
%
%
% PARAMETERS:
%
%
% RETURNS:
%
%
% EXAMPLE:
%
% SEE ALSO:
%
% Copyright (c) 2012-2016 Ali Akbar Eftekhari
% See the license file
if (isa(p, 'CellVariable')&&isa(... |
a8663b8ce97b41d6f09ce7a982312e57c15dec430b64ec4981c216619ff75ade | MATLAB | 490 | 20 | %{
# inferred background components
-> meso.SegmentationCNMF
---
masks : longblob # array (im_height x im_width x num_background_components)
activity : longblob # array (num_background_components x timesteps)
%}
classdef SegmentationCN... |
b856a637d6260c2ad80fdbc28bc7c2e09a6a3269106b58faaf8917e91f9c1138 | MATLAB | 490 | 25 | function x=normalise(x,dim)
% normalise(X)
% Removes the Average or mean value and makes the std=1
%
% normalise(X,DIM)
% Removes the mean and makes the std=1 along the dimension DIM of X.
if(nargin==1),
dim = 1;
if(size(x,1) > 1)
dim = 1;
elseif(size(x,2) > 1)
dim = 2;
end;
end;
dims = siz... |
c6088f7a893fb4ae67d49294461a5e109ace5a4d843f4092686bc9faf5b0eb30 | MATLAB | 490 | 20 | %{
# inferred background components
-> reso.SegmentationCNMF
---
masks : longblob # array (im_height x im_width x num_background_components)
activity : longblob # array (num_background_components x timesteps)
%}
classdef SegmentationCN... |
d4c96a59093f2ea3ce73518c8af60cf5f5005f99448fb6292347e1cc3998e0ac | MATLAB | 490 | 15 | function [nirs, partName] = loadSubjectData(subjectName)
% Loads NIRS data for a specific subject from file and ensures proper data
% structure formatting. Initialises measurement activity list if not
% present in the original data.
% Load .nirs data
partName = subjectName;
nirs = load(partName, '-mat')... |
f2897f7660b076de9e8f801051fb05e8e48ee67a6de08e432c3d144eead7804c | MATLAB | 490 | 23 | function [alpha, beta] = tapas_gamma_moments_to_ab(m1, m2)
%% Transforms the central moments of a Gamma distribution into the alpha beta
% parametrization where x^alpha-1 b^alpha exp(-x * beta)
%
% Input
% m1 -- First central moment (mean)
% m2 -- Second central momement (variance)
%
% Output
% ... |
3678fb8e3d30dba9e2622b87796baf608c8a5d350d414135adaa02825d03cf1a | MATLAB | 491 | 23 | function [jcut] = calc_jcut(data)
% calculate threshold of similarity values from shuffled data
num_shuff = 20;
p = 0.99;
dims = size(data);
% calculate similarity matrix
warning('off')
S = zeros(dims(2),dims(2),num_shuff,'single');
for n = 1:num_shuff
data_shuff = shuffle(data,'time');
S(:,:,n) = 1-pdist2(da... |
667a64dd63a903eb15fe691dc31090ab86367836b69bd8d3b0b02c476d11d12c | MATLAB | 491 | 22 | function [Result] = Feta(eta,y,sig2)
%Implemented by Christian Beckmann
if nargin<3
sig2=1;
end
bm=sig2*(1-sqrt(y))^2;
bp=sig2*(1+sqrt(y))^2;
Result=zeros(size(eta));
teta=bm:1/1000:bp;
feta=zeros(size(teta));
feta=((2*pi*y*teta).^(-1)).*sqrt((teta-bm).*(bp-teta));
% fig... |
f679bfc9eabcdfdb3f53cc4b4fbdf4dbe09a783a53eaffdec87cefb903f79043 | MATLAB | 491 | 18 | function string=compactPvalueString(p)
% given a numeric p-value returns a string that expresses it in scientific format.
%__________________________________________________________________________
% Copyright (C) 2012 Medical Research Council
import rsa.*
import rsa.fig.*
import rsa.fmri.*
import rsa.rdm.*
import rsa... |
75a5a83c33b84d78769f5c4c86985c5ced4e7085c794f18c2a82a46bdfd44baf | MATLAB | 492 | 8 | %% This file specifies the Python environment and Checkpoint of QSMnet+
% Specify the directory of the QSMnet+ code from Github
QSMnet_HOME = '/home/common/matlab/sepia/external/QSMnet/QSMnet-9ca283a';
% Specify the Python environment that has QSMnet+ installed
python_interpreter = '/home/common/matlab/sepia/... |
02b846407d59b152970a07da1781714a7df4cbef2ec0b559a13b634fead5a578 | MATLAB | 493 | 30 | function [version] = tapas_get_current_version()
%% Get the current version of tapas.
%
% Input
%
% Output
% version -- A string with the the three version digits.
% aponteeduardo@gmail.com
% copyright (C) 2018
%
f = mfilename('fullpath');
[tdir, ~, ~] = fileparts(f);
logname = fullfile(tdir, 'log_tapas.tx... |
0a95f4adc720c0cf63b20b888e13309f026802c6107f655cd25467fee227749d | MATLAB | 493 | 20 | function [ out ] = nf_update_struct( orig, update )
%[ out ] = nf_update_struct( orig, update )
% will update all fields in orig by respective fields in update
%
items=fieldnames(update);
for i=1:length(items)
if isfield(orig,items{i})
if isstruct(orig.(items{i}))&&isstruct(update.(items{i}))
orig.(items{i}... |
6383e72089468f72367594ae9b5c55e2322f45cb1aee9ecebfee1675e92d1ab3 | MATLAB | 493 | 22 | function correctedStackTiff(key,filepath,direction)
% direction can be 'normal' or 'reverse'
if nargin <3
direction='normal';
end
stk = stack.loadCorrectedStack(key);
switch direction
case 'normal'
ind = 1:size(stk,4);
case 'reverse'
ind = size(stk,4):-1:1;
otherwise
error('dir... |
8962b6375fc6654d63502ee8d5e9f0e5ce1870af95e1a55bee27cbacaed86fad | MATLAB | 493 | 22 | function [ss] = dabest(csvFile, varargin)
d = readtable(csvFile);
identifiers = d(:,{'Identifiers'});
identifiers = table2cell(identifiers);
data = d(:,{'Values'});
data = table2array(data);
close(gcf);
if length(varargin) > 0;
if strcmp(varargin{1},'Paired');
[ss] = FscatJit2(identifiers, data,'Y');
... |
8dc997af18c8f0dd4898a78105e93b0ac62d89e7e00fc9f8b1e91577df0f0709 | MATLAB | 493 | 17 | %{
#
-> eye.FittedContour
frame_id : int # frame id with matlab based 1 indexing
---
center=null : tinyblob # center of the ellipse in (x, y) of image
major_r=null : float # major radius of the elli... |
425d55c3ac305b0b1a10075073c0cd65c93c6a39715750dd662e497b76fdbf2a | MATLAB | 494 | 21 | %{
#
-> preprocess.ManualCellLocations
cell_id : smallint # cell identifier
---
x : float # x coordinate of the cell
y : float # y coordinate of the cell
%}
classdef ManualCell... |
560d4e170794694ffc1198387780b551305f88e63914bf93cbda3b74324776f0 | MATLAB | 494 | 18 | function Y = multiskewh(X)
% Returns the skew-Hermitian parts of the matrices in the 3D matrix X.
%
% function Y = multiskewh(X)
%
% Y is a 3D matrix the same size as X. Each slice Y(:, :, i) is the
% skew-Hermitian part of the slice X(:, :, i).
%
% See also: multiskew multiprod multitransp multiscale multisym multiher... |
82fc2cf4de2dd4ef5e382330b720182b32c67b72c855b21216bc3a5e2d083349 | MATLAB | 494 | 15 | function DB = meta_study2contrast(DB)
% DB = meta_study2contrast(DB)
% helper function to turn unique studies stored in DB.Study
% into unique contrast codes stored in DB.Contrast
%
% in case contrasts are not manually entered.
% contrast numbers in order -- unique with no sorting
[u,ii]=unique(DB.Study); ii = sort(ii... |
6877b776ddd6b66789f153794c4fb1ffa194d2ce09f954ff32b367f8df5ad523 | MATLAB | 495 | 18 | function h = sero_pulseq_plot_pns(seq, blockInd, hw)
% function h = sero_pulseq_plot_pns(seq, blockInd, hw)
%
% This function requires the SAFE nerve stimulation framework:
% https://github.com/filip-szczepankiewicz/safe_pns_prediction
if nargin < 2 || isempty(blockInd)
blockInd = [1 numel(seq.blockEvents)];
end
... |
171ee80c74d1634ef4d6705788f8e8a3f6eed28c04767db1b0be1a741b617934 | MATLAB | 496 | 21 |
function [Mask0,zstack]=OpenImage(NameMask,aux)
Info=imfinfo(NameMask);
NumberImages=length(Info);
zstack=NumberImages > 1;
if zstack
C=zeros(Info(1).Height,Info(1).Width ,NumberImages);
for i=1:NumberImages
A=imread(NameMask, 'Index', i);
C(:,:,i)=A;
e... |
549176ed178d02c2311eb78af3c304fc77244d4b81c041a1a734953f46ecb5fa | MATLAB | 496 | 21 | function ratlist = loadRats(datadir, sensortype)
% load list of dopamine or acetylcholine rats
% sensortype: 'da' or 'ach'
if strcmpi(sensortype, 'da')
sensortype = 'da';
elseif strcmpi(sensortype, 'ach')
sensortype = 'ach';
end
load(fullfile(datadir, 'data-published', 'ratlist.mat'), 'sensorList')
allrats = ... |
74292a56f2e745c7887648c519621df0f6b58ab2948bf4a602b405f8e26f7278 | MATLAB | 496 | 20 | function p=relRankIn_includeValue_lowerBound(set,value)
% returns the relative rank of value within set.
% the relative rank is the proportion of set smaller than value.
%__________________________________________________________________________
% Copyright (C) 2009 Medical Research Council
import rsa.*
import rsa.fi... |
9fd623b62056b410d17c7fad1eb9c6ef68e78918a5c7e697238953f399254e6a | MATLAB | 496 | 13 | function [mouse_heatmap] = get_mouse_heatmap(mouse_position,frame_size)
mouse_heatmap = zeros(frame_size);
for p = 1:size(mouse_position,1)
if sum(isnan(mouse_position(p,:)))<1&&(mouse_position(p,2)<=frame_size(1))&&(mouse_position(p,1)<=frame_size(2))
mouse_heatmap(mouse_position(p,2),mouse_position(... |
253a190662494ef6861beb734c0baa11648b62a61300d72a4c03208807045884 | MATLAB | 497 | 23 | function [ ID_info] = get_mat_ID_INFO( AA,L)
subgraph=zeros(4,4);
kk=1;
A=AA;
ll=size(A,1)/4;
ss=size(A,2)/4;
ID_info=ones(2,ll*ss);
for i=0:ll-1
for j=0:ss-1
for ii=1:4
for jj=1:4
subgraph(ii, jj)= A(ii + i*4, jj + j*4);
end
end
... |
624aa65613ece58b1e775e72f909f17797ab2739ed0818e7f9186a55f112f5f0 | MATLAB | 497 | 25 | function h = axisNotSoTight(h)
% after axes tight, enable a bit of white space
if ~exist('h', 'var'); h = gca; end
% enforce axis tight
axis(h, 'tight');
% find the current limits
xlims = get(h, 'xlim');
ylims = get(h, 'ylim');
% get the range
xrange = range(xlims);
yrange = range(ylims);
% enlarge with X percent ... |
6c77a72f9c12620d3d42ea27369185bda2f58de850d9d4c5e44b953217155a6d | MATLAB | 497 | 17 | function [P] = likelihood_fun_local(x0Mean,x0Std,AMean,Astd,data,nMean,nStd,Conc,noiseStd)
%% data -- rows are concentrations, columns are trials. There's one x0 and
% one A guess for every trial
Ptrial = ones(1,size(data,2));
for ii = 1:size(data,2) %loop over trials
rr = permute(data(:,ii),[3,2,1]); %one dose ... |
7c8086500fd728467775e8c9f367ffc070ecdaa49d4a4584814861546b865670 | MATLAB | 498 | 24 | %% function export_nii(img,fn,v_size)
%
% Description: Directly save to nii.gz format
%
% Kwok-shing Chan @ DCCN
% k.chan@donders.ru.nl
% Date created: ??
% Date last modified: 1 Oct 2022
%
function export_nii(img,fn,v_size)
% load_module_NIfTI;
try filename=fn; catch; filename='Result';end
try voxel_size = v_size; ca... |
a5e687107038f33f4baf06c6c2d90b4aa33165d67be9ce9f8f882de473586e95 | MATLAB | 498 | 20 | function plotAutoCorrelogram(spikeRaster,Fs,varargin)
nTrace=size(spikeRaster,2);
BW=100; %for gamma
figure('defaultaxesfontsize',16,'color','w')
for iTrace=1:nTrace
[r,lags] = xcorr(spikeRaster(:,iTrace),Fs,'coeff');
r((length(r)+1)/2)=0;
subplot(nTrace,2,2*(iTrace-1)+1)
plot(lags,r,'k','linewid... |
d848a7a44da5b05b8022472a14206b740149581d7c901736dafcbca5bfcdb8f2 | MATLAB | 498 | 14 | function spectogramMax = get_spectogram_max(hObject, handels)
spectogramMax = str2double(get(handels.SpectogramMax,'String'));
contents = cellstr(get(handels.spectogramScalePopup,'String'));
scale = contents{get(handels.spectogramScalePopup,'Value')};
if ( isnan(spectogramMax) | spectogramMax ... |
e0871e0436523a70f2a495d8294ee3135e2ae0022854d5a0d8c6582f3861944f | MATLAB | 498 | 10 | function [verbose] = tapas_physio_plot_sync_bundles(Nallvols, t, SLICELOCS, verbose)
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
stringTitle = 'Sync: Slice bundles belonging to 1 volume';
verbose.fig_handles(end+1) = tapas_physio_get_default_fig_params();
set(gcf, 'Name'... |
0ff7129c47738004b9f8d291822e536f92ad51083668fd6ccb72c563dbd1cbec | MATLAB | 499 | 17 | function [directionsCondition1, directionsCondition2] = getDirectionBaseVectors(cfg)
%
% [directionsCondition1, directionsCondition2] = getDirectionBaseVectors(cfg)
%
%
% (C) Copyright 2020 CPP visual motion localizer developers
% Set directions for static and motion condition
% condition1... |
4d4dd2be39a4289e53e4683625e0f5c5e106fa1482814f91150811f59fdc57df | MATLAB | 499 | 20 | %{
# motion correction for each slice in the stack
-> stack.RasterCorrection
---
y_shifts : longblob # y motion correction shifts (num_slices x num_frames)
x_shifts : longblob # x motion correction shifts (num_slices x num_frames)
%}
clas... |
0182a6b11a28cc4b041bd56ba84f9a5d145e1f43271d6e3c603a1d5426d32176 | MATLAB | 500 | 13 | function data = extract_VAE_embeddings(encoderNet, options, ClusteringData)
% Resize the images to match the input image size
images = zeros([options.imageSize, size(ClusteringData, 1)]);
for i = 1:size(ClusteringData, 1)
images(:,:,:,i) = imresize(ClusteringData.Spectrogram{i}, options.imageSize(1:2));
end
images... |
303424d599f4f2b1d99ab635e37d779b31c07c0608a95950eeb70c16948256e2 | MATLAB | 500 | 15 | function s = char(tpl)
%TEMPLATE Convert a template object in a one line description string
% S = CHAR(TPL) is a class convertor from Template to a string, used
% in online display.
%
% See also DISPLAY
% Copyright (C) 2003 Guillaume Flandin <Guillaume@artefact.tk>
% $Revision: 1.0 $Date: 2003/05/05 22:19:51 $
... |
5c8bb182002ac710e8c7543e7f9e13038fe51c3403c7ed889c83c06e6ef7c2c4 | MATLAB | 500 | 23 | function [da_rats, T, bins, delay_legend] = DelayEffectAcrossRats(ratlist,...
block, delaybins, event, Bstruct, Pstruct)
%input
%block = behavior block to use
%numbins = number of delay bins
da_rats = cell(length(ratlist), 1);
for rat = 1:length(ratlist)
ratname = ratlist{rat};
disp(ratn... |
7cca40b00c70e80c0dbf13d80b46a74cf7d5116412b4f41275b5a846f388548c | MATLAB | 500 | 20 | function indic = make_indicator(aus,aulistr)
% indic = make_indicator(aus,aulistr)
%
% aus is list of cell arrays with words (rows of indic are cells)
% aulistr is string matrix of words for columns of indic
indic = zeros(length(aus),size(aulistr,1));
% Make study table
for i = 1:length(aus)
for j = 1:length(aus{i... |
8492c939b0100100a9bcf712d9bb15bf1cb273a03d66577462a92989819b4ca1 | MATLAB | 500 | 15 | %{
# most exciting images generated from multiple models
mei_id : int # image id
-> experiment.BrainArea
-> experiment.Layer
model : varchar(12) #
---
image : longblob # image
std ... |
a6a4073d7a957268acf0cb8fea0d7c6c0b1872fc0572dd5cac2b4a1f5fbca2ff | MATLAB | 500 | 20 | function [dWU,top] = SVD_topchan(dWU,criteria)
[~, ~ ,Nfilt] = size(dWU);
top = zeros(Nfilt,1);
dWU(isnan(dWU)) = 0;
for i=1:Nfilt
if(isempty(nonzeros(dWU(:,:,i))))
else
[Ws,~,Us] = svd(dWU(:,:,i));
%To get the correct sign for the peak deep
[~, imax] = max(abs(Ws(:,1)));
Us(:,1) = -Us(:,... |
c6a557d7d6cd76fcdc02c11d686b95dfaa840c60a8a519bc84ab637084d82246 | MATLAB | 500 | 23 | % performs transformation from geometry of
% recon-code to output of spm_read_vols
%
%
% INPUT
% Y - congruent with FullImReconStackData & imagesc-orientation
%
% OUTPUT
% newY - from spm_read_vols
function newY = tapas_uniqc_transform_matrix_matlab2analyze(Y)
nSlices = size(Y,3);
nVolumes = size(Y,4);
... |
346d5c53c0f88928d77581910871382555684c50e6f6d43af6e076d6cc8167ca | MATLAB | 501 | 22 | classdef (Abstract) base < handle
% brca.dot.base
% Abstract base class for dot products of the form <x,y> = x'*L*y
% Dot products are handle classes that must implement the methods
% `solve`, `dot` and `logdet`.
methods (Abstract)
x = solve(obj,x)
% y = obj.solve(x)
% Compute L*x... |
4dc513f6e51745304d108f2189a95f3569074c99ca575c4a2d5e9ae8d68edf88 | MATLAB | 501 | 19 | function R = TMSfastCorr(X, Y)
%
% XiNian.Zuo@nyumc.org
[numSamp1 numVar1] = size(X); % n*p1
[numSamp2 numVar2] = size(Y); % n*p2
if (numSamp1 ~= numSamp2)
disp('The two matices must have the same size of rows!')
else
X = (X - repmat(nanmean(X), numSamp1, 1))./repmat(nanstd(X, 0, 1), numSamp1, 1);
Y = (Y ... |
8fbed2213e8765a57c3a5f8cca8700b6f4b7e274c999a794ee1a7432da601df0 | MATLAB | 501 | 18 | function [AUC_byrat, DA_normalized_mixed_byrat] =...
RewardEffectByBlockAcrossRats_stages(window, Stages, ratlist,...
Pstruct, Bstruct)
%initiate variables
AUC_byrat = cell(1,length(ratlist));
DA_normalized_mixed_byrat = cell(1,length(ratlist));
for rat = 1:length(ratlist)
ratname = ratlist{rat};
disp(... |
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