sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
08128a862cbf01a24c4ff9c1fc3b56a487b9eff1b101140a1fb29e81653f4108 | MATLAB | 305 | 18 | function fi=remove_field_string(fi,fieldn,ind_to_remove)
for k=1:length(fi)
str = getfield(fi(k),fieldn);
if isnumeric(ind_to_remove)
str(ind_to_remove)='';
else
[i1,i2] = regexp(str,ind_to_remove);
str(i1:i2) = '';
end
fi(k) = setfield(fi(k),fieldn,str);
end
|
7381fbae65118c5438d44dbd026693c6d1d74b8cd8ff50dd1c4bc1a3f65c84cb | MATLAB | 305 | 17 | function stim = get_stim(session, channel, unit, fold)
% Get stimuli of specific neuron
%
% Parameters
% ----------
%
% - fold: integer scalar
% Fold number
%
% Returns
% -------
% - stim: 2D matrix
% (trial x time) response
result = load_result(session, channel, unit, fold);
stim = result.stim;
end |
5c205a919997557672d3e816c8c4e3173e12a6de3a925664cd0643fd2cd55cb4 | MATLAB | 306 | 11 | function lines = readLines(filename)
%READLINES Read the lines of a text file into a cell array
assert(exist(filename, 'file') == 2, '''%s'' is not a file', filename);
fid = fopen(filename, 'r');
lines = textscan(fid, '%s', 'Delimiter', '\n');
fclose(fid);
lines = lines{1};
end
|
d45b16c8e45775a825eacdaf5bcc01aa9029297ed63f1ae898a2a1f95ce989fb | MATLAB | 306 | 13 | function disp_highest_tvalue(Stats, Chanlocs, String)
% if ~any(Stats.sig)
% return
% end
t = Stats.t;
% t(~Stats.sig) = nan;
Stats.p_fdr = Stats.p_fdr(:);
Stats.N = repmat(Stats.N, numel(Stats.p_fdr), 1);
[~, Indx] = max(abs(t));
disp_stats(Stats, [Indx, 1], [String, ' ', Chanlocs(Indx).labels]);
|
2dd0192e9b02b0789c5a0b0f68a4d384f1007da669a13a18378aa0861aeb3fa8 | MATLAB | 307 | 16 | t=-20:0.01:30
figure;
hold on
tau=3;
plot(t,(t.*exp(-t/tau)/max(t.*exp(-t/tau)).*(t>0)/tau^2))
plot(t,(exp(-t/tau).*(t>0)/tau))
tau=5;
plot(t,(t.*exp(-t/tau).*(t>0)/max(t.*exp(-t/tau))/tau^2))
plot(t,(exp(-t/tau).*(t>0)/tau))
% tau=10;
% plot(t,t.*exp(-t/tau)/max(t.*exp(-t/tau)))
% plot(t,exp(-t/tau))
|
35d95022a5ae2261139c5818a81c0c3cab601ba18016d6acda1ab31f371eb4d6 | MATLAB | 307 | 9 | function [Dis,Dis_coord] = distance(scale,coord1,coord2)
Dis_coord = zeros(1,2);
A = coord1(1,2) - coord1(1,1);
Dis_coord(1,1) = floor((coord1(1,2) + coord1(1,1))/2);
Dis_coord(1,2) = floor((coord2(1,2) + coord2(1,1))/2);
B = coord2(1,2) - coord2(1,1);
AB = sqrt((A^2)+(B^2));
Dis = AB * scale;
end |
56b9be1ad5148a0a7ad3b32eda8ed40d8961e996969c995c772fc52d5b1a509f | MATLAB | 307 | 25 | function fo = average_series_fid_spec(fids)
fo=fids(1);
for nbser = 1:length(fids)
fid = fids(nbser).fid;
fid1m = mean(fid,2);
if ~exist('fm1')
fm1 = fid1m;
else
fm1 = fm1 + fid1m;
end
end
fo(1).fid = [fm1] ./ nbser;
if exist('descr')
fo(nbser).Serie_description=descr;
end
|
f9b0a6178d61019ab41dd87a6bd05394ed21aebb7a531e9485351ef934f6ac3d | MATLAB | 307 | 17 | function fr = get_s_fr(session, channel, unit, fold)
% Get firing rate of specific s-model
%
% Parameters
% ----------
%
% - fold: integer scalar
% Fold number
%
% Returns
% -------
% - resp: 2D matrix
% (trial x time) firing rate
result = load_result(session, channel, unit, fold);
fr = result.fr;
end |
3f14c4f432e703b747191d7089a553a8872086865f9875a74348cbd8f0209ccb | MATLAB | 309 | 11 | function mouseClickFigSim(obj, xyPos, clickType)
%MOUSECLICKFIGSIM Handle callbacks for mouse clicks in sim view
if obj.isWorking
return;
end
xyPos = max(round(xyPos), [1 1]);
if strcmp(clickType, 'normal') % left click
obj.updateSelect(obj.showSubset(xyPos));
end
end |
51195d2fe7365de93d997c4a44fd4028f700e6aa318ef6e10ec298f009c085c4 | MATLAB | 309 | 11 | function Time = peaks2time(Peaks, StartVariable, EndVariable, Pnts)
% turns structure of peaks into a time vector, based on variables indicated
Time = zeros(1, Pnts);
Starts = [Peaks.(StartVariable)];
Ends = [Peaks.(EndVariable)];
for Indx_P = 1:numel(Starts)
Time(Starts(Indx_P):Ends(Indx_P)) = 1;
end |
dafeda2df9cd8170980e881804717c859e06cf611d210e93d7a261d850c1b9f1 | MATLAB | 310 | 13 | % TODO: test for properties: values should be in certain ranges, so plot
% their distribution, and give test problem (eventually) if they're outside
% of range
Properties = fieldnames(AugmentedCycles);
for Property = Properties'
figure
histogram([AugmentedCycles.(Property{1})])
title(Property)
end |
04120a4d4aaedc7d2bdfa3e62ad470d2288533392be7dc2458e0a4d24a4df5ec | MATLAB | 311 | 13 | function ob = power(ob, sup)
%function ob = power(ob, sup)
% array "power" method (A.^2)
% matrix power (mpower) would be for A^2
if isempty(ob.handle_power)
error 'no power method for this object'
end
ob = ob.handle_power(ob, sup);
if isfield(ob, 'scale') && ob.scale ~= 1
ob.scale = ob.scale .^ sup;
end
|
a131b67d11d7b49d3940d9b86716a7b92788abcdc76a0db4aa0258c011c59a12 | MATLAB | 311 | 12 | function Omega = matern_type_kernel(num_dim, h)
% See main paper for definition.
assert(isfloat(h), 'h must be a float')
assert(h>0, 'h must be positive')
assert(num_dim > 0, 'num_dim must be positive.')
x = [0 : num_dim - 1];
Omega = (1 + sqrt(3) * abs(x' - x) / h) .* exp(-sqrt(3) * abs(x' - x) / h);
|
d35a6fe7fac5f395cf6b21196390b469094e03b3aeddfbc2e05ff268bef6812a | MATLAB | 311 | 8 | function res = figApply(obj, hFun, varargin)
%FIGAPPLY Apply a function to all figures
if nargout == 0 % "Too many output arguments"
cellfun(@(k) hFun(obj.hFigs(k)), keys(obj.hFigs), varargin{:});
else
res = cellfun(@(k) hFun(obj.hFigs(k)), keys(obj.hFigs), varargin{:});
end
end |
da49acc6b58f98a351b52c13b9ae4d6d2f953756355b02ec2bff6d7a65d986ab | MATLAB | 311 | 7 | function y = gauss_smooth(x, win)
% Gaussian smoothing
win = win + mod(win + 1, 2);
k = (6 / sqrt(2 * pi) / win) * exp(-0.5 * (6 * linspace(-win / 2, win / 2, win) / win) .^ 2);
conv_value = conv(x, k, 'full');
y = 1000 * conv_value((win - 1) / 2 + 1:length(conv_value) - (win - 1) / 2);
end |
ebb32b659913c711978d2229d5492e108e8a066c23cfa326662260c0ceb53c6f | MATLAB | 311 | 5 | function [ECGmean, ECGsd] = ECGBeatVariance2(x, peaks, wlen)
% ECGBeatVariance2 has been deprecated. Use avg_beat_calculator instead.
warning('ECGBeatVariance2 has been deprecated. Use avg_beat_calculator instead.');
offset_method = 'peak';
[ECGmean, ECGsd] = avg_beat_calculator(x, peaks, wlen, offset_method); |
f6e5c3e98e16579c58c41354a7b49aa61524e3d43e2be5ccc69af1ac1d1a5344 | MATLAB | 312 | 17 | function resp = get_resp(session, channel, unit, fold)
% Get true responses of specific neuron
%
% Parameters
% ----------
%
% - fold: integer scalar
% Fold number
%
% Returns
% -------
% - resp: 2D matrix
% (trial x time) response
result = load_result(session, channel, unit, fold);
resp = result.resp;
end |
414917f5d77fbf65b8ebef1d12784b68ef647e7abd27551911d47096f917636d | MATLAB | 313 | 14 | function [success, errmsg] = closeFiltForWriting(obj)
%CLOSEFILTFORWRITING Close the filtered file
success = 0;
errmsg = '';
if obj.filteredFid < 3
errmsg = 'Filtered file is not open';
return;
end
success = (fclose(obj.filteredFid) == 0);
obj.filteredFid = -1;
end
|
e7e3d1bc7569d102d34462ebd939606d2a669a2b05d5d552da1dc58e9defab77 | MATLAB | 313 | 13 | function [normalized] = normBOlDtimeseries(subttimeseries)
% This program is intended to
%
% input:
% subtimeseries:
%
% output:
% normalized:
%
% by Hiroaki Hamada, Araya Inc., 2019/08/29th
subttimeseries = (subttimeseries-mean(subttimeseries))./mean(subttimeseries);
normalized = detrend(subttimeseries); |
364f0d5463439f557a84744c7331f0b5a10b44cc8b3ce452a7a2d19e1520af42 | MATLAB | 314 | 12 | function weights = genweights(layers, params, type)
if (strcmp(type, 'cpu') || strcmp(type, 'gpu'))
weights = genweights_mex(layers, params);
elseif strcmp(type, 'matlab')
weights = genweights_mat(layers, params);
else
error('"%s" - wrong type, must be either "cpu", "gpu" or "matlab"', type);
end;
end
|
58df46d3c95f2b1512e81bcbedb4e0666ad0bea771407350dcd0b8968ec1086d | MATLAB | 314 | 9 | %% Function of histamine inhibition of synthesis of histamine.
%autoreceptors and depends on levels of g-coupled proteins activated (b) by
%histamine and basal levels of g-coupled histamine (c).
% Units in uM.
function a = inhibsynHAtoHA(b, c)
min_a = 0;
a = 1 - (0.1).*(b - c);
a(a<min_a) = min_a;
end
|
aa391bf20a91d4f1242de8f713c9d0a2f901908fac95a2b0c299e560193d7023 | MATLAB | 314 | 15 | function Struct = cat_struct(Struct1, Struct2)
% concatente structures, also when potentially empty.
if isempty(Struct1) || numel(fieldnames(Struct1)) == 0
Struct = Struct2;
elseif isempty(Struct2) || numel(fieldnames(Struct2)) == 0
Struct = Struct1;
else
Struct = cat(2, Struct1, Struct2);
end
|
2374a09787182a3ef644e62807e5b7441b915eb625805d4a01fde0606a8e3f4e | MATLAB | 315 | 8 | % Finder Spiker for Calcium Imaging
% Initial interface to select
% - Multiple-Condition Experiment
% - - Detect Spikes from original .AVI videos and
% - - List of Coordinates (ImPatch) or
% - - ROI coordinates (ImageJ)
% - Single-Condition Experiment
% - - Detect Spikes from Fluorescence Traces (.CSV) |
9afc42b89be4911b443af7f14897861d259347283885315a3b64fc23f3bf0895 | MATLAB | 315 | 10 | function [e] = groupedErrorBar(y, err)
hold on,
ngroups = size(y, 1);
nbars = size(y, 2);
% Calculating the width for each bar group
groupwidth = min(0.8, nbars/(nbars + 1.5));
for i = 1:nbars
x = (1:ngroups) - groupwidth/2 + (2*i-1) * groupwidth / (2*nbars);
e(i) = errorbar(x, y(:,i), err(:,i), '.');
end
|
f8cc4b2d8bf48b067bf842f9cecd8f4d26a66e0ea94eb094986d93b12fd4969a | MATLAB | 315 | 17 | function Q = GramSchmidt(A)
% applying a Gram-Smidt orthogonalization
% http://web.mit.edu/18.06/www/Essays/gramschmidtmat.pdf
[m,n]=size(A);
Q=zeros(m,n);
R=zeros(n,n);
for j=1:n
v=A(:,j);
for i=1:j-1
R(i,j)=Q(:,i)'*A(:,j);
v=v-R(i,j)*Q(:,i);
end
R(j,j)=norm(v);
Q(:,j)=v/R(j,j);
end |
ad155cedfef5e9d120249e9c44aaa8643bb918a8ba4b57579edcabacb01729bb | MATLAB | 316 | 14 | function [cmap]=mnl_GenerateShuffledColourmap(n)
%Generates a shuffled hsv map so that each point would be a unique colour
% n=number of colours wanted
%
% cmap - the colourmap outputted
tcmap=colormap(jet(n));
% h=gcf;
% close(h)
order=randperm(n);
cmap=nan(n,3);
for i=1:n
cmap(i,:)=tcmap(order(i),:);
end
end
|
cb2e5c18dab697f4fef834cab029c3076c17603d9c28fdf0db92ac74e09a7d73 | MATLAB | 316 | 14 | function hAx = addAxes(obj, axKey, varargin)
%ADDAXES Create and store new axes for this figure
if ~obj.isReady
obj.hFig = figure();
end
if obj.hasAxes(axKey)
return;
end
hAx = axes(obj.hFig, varargin{:});
obj.hAxes(axKey) = hAx;
obj.axApply(axKey, @hold, 'on');
end |
dde63d4fdc49296d7a224704f750c96d347c464a8693da8ecd334ceec500acab | MATLAB | 316 | 5 | function [A, B, ang] = RandomMatrices(angle, dim1, flag)
% RandomMatrices has been deprecated. Use random_mat_max_col_space_ang instead.
warning('RandomMatrices has been deprecated. Use random_mat_max_col_space_ang instead.');
Kmax = 10000;
[A, B, ang] = random_mat_max_col_space_ang(angle, dim1, 3, flag, Kmax); |
ed50235053aa756109f4f4bf630525b4deea9b87a8acd5a5401fe3d36b29ef24 | MATLAB | 316 | 25 | function y = dmatrix(x)
% d=dmatrix(data =[N x p]),
%INPUT: x = [nodes x dimensionality of the coordinates]
%OUTPUT: distance = distance matrix
%NIKOLAOS LASKARIS
%see http://users.auth.gr/~laskaris/index.htm
[m,n]=size(x);
a=x*x';
e=ones(m,m) ;
d=diag(diag(a))*e + e*diag(diag(a))-2*a ;
y=d;
|
3b51acc3927617db62a06f248954455a9c21e33f1d1c9f2062a03c223735665a | MATLAB | 317 | 6 | function [peaks, r] = PeakDetection4(ref, fs, h, fmax, varargin)
% PeakDetection4 has been deprecated. Use peak_det_matched_filter_robust instead.
warning('PeakDetection4 has been deprecated. Use peak_det_matched_filter_robust instead.');
[peaks, r] = peak_det_matched_filter_robust(ref, fs, h, fmax, varargin{:});
|
ecff6ee77bcdca936837ede3ddf914675a5212c52d894dec7b5370341e52c9a1 | MATLAB | 317 | 11 | function out = matrix2vols(data,mask)
%function out = matrix2vols(data,mask)
%
% takes 2d matrix [space x time] and 2d/3d mask [x y (z)]
% and returns 3d/4d data [x y (z) time]
mask2= reshape(mask,numel(mask),1)>0;
out=zeros(numel(mask),size(data,2));
out(mask2,:)=data;
out=reshape(out,[size(mask) size(data,2)]);
|
4adc82e41c4a2052f89f32864e8bef869ec72362f2a54582e597ff8cf80f92f3 | MATLAB | 318 | 4 | function y = TikhonovRegularization(x, diff_order_or_filter_coefs, lambda)
% TikhonovRegularization has been deprecated. Use tikhonov_regularization instead.
warning('TikhonovRegularization has been deprecated. Use tikhonov_regularization instead.');
y = tikhonov_regularization(x, diff_order_or_filter_coefs, lambda); |
afd8b75b0290e106380fabd37a459ea85d4df1ce8de0ac20702946e9fb841695 | MATLAB | 318 | 6 | function index = ChannelIndex13(x,ff,fs, wlen)
% ChannelIndex13 has been deprecated. Use sqi_pseudo_periodicity instead.
warning('ChannelIndex13 has been deprecated. Use sqi_pseudo_periodicity instead.');
method = 'TRACE';
num_peak_det_itr = 1;
[index, ~] = sqi_pseudo_periodicity(x, ff, fs, method, num_peak_det_itr); |
3f280324f70ab2cd473e562fe4574534288baf5bebda2a6b6c44281512c17998 | MATLAB | 319 | 11 | function [BC] = bimodalCoeff(inData)
% function [BC] = bimodalCoeff(inData)
% Returns bimodal coefficient for inData.
% alex.teghipco@uci.edu
m3 = skewness(inData, 0);
m4 = kurtosis(inData, 0) - 3;
n = (m3.^2) + 1;
d1 = ((length(inData)-1).^2 / ((length(inData) - 2)*(length(inData) - 3)));
d2 = (m4+3)*d1;
BC = n/d2;
|
0fb13dc42c1d6b5df0ae747cadbd6faeff1064e415423d9b05332e93fa5ca52d | MATLAB | 320 | 16 | function i = vararginmatch(v,str)
% Copyright 2009-2011 Thomas Koenig
% distributed under the terms of the GNU AFFERO General Public License
if iscell(v(1))
for i = 1:numel(v)
if strcmp(v{i},str)
return
end
end
else
if strcmp(v,str)
i = 1;
end
end
i = 0;
|
ae1b1fccfeb8e51525b10d598627ce6a12c170e331c7302dd22348ed46b16068 | MATLAB | 320 | 24 | function out = end(ob, k, n)
%function out = end(ob, k, n)
%
% handle calls of the following forms, for example:
% ob(:,end)
% ob(end,:)
% ob(end)
%
% see 'doc end' for more explanation
switch n
case 1
if k ~= 1
fail 'bug'
end
out = prod(size(ob));
case 2
out = size(ob, k);
otherwise
fail 'unknown "n"'
end
|
b5578b19b90a987c016b7688983f1ae42bd5330437f5666843e85df6a49d207a | MATLAB | 320 | 18 | function [dim, varargout] = size(ob, varargin)
%function dim = size(ob, varargin)
% or [dim1 dim2] = size(ob)
% "size" method for this class
dim = ob.size;
if numel(varargin) == 1
dim = dim(varargin{1});
return
elseif numel(varargin) ~= 0
error 'bug'
end
if nargout > 1
varargout{1} = dim(2);
dim = dim(1);
end
|
406c79c01ebd4b2fcbd2c243bd8b4517d6710bf1eb8733969fddbefee372e34e | MATLAB | 321 | 17 | function varargout = svd(ob, varargin)
% compute svd of object by converting it to full matrix.
% this will be very slow for big objects
ob = full(ob);
[u s v] = svd(ob, varargin{:});
switch nargout
case 1
varargout = {diag(s)};
case 2
varargout = {u, s};
case 3
varargout = {u, s, v};
otherwise
fail 'eig bug'
end... |
15b24dff0953b346ca5b4d1bb74aac0af8e251bf8b078e5bc1d7e324e98aa5cf | MATLAB | 322 | 14 | function [ zmean, zstd ] = z_mean_std( C )
% each col of C is a partition, C is of pxRep
[~,rep] = size(C);
count = 0;
zVec = zeros(rep*(rep-1)/2,1);
for i = 1:rep-1
for j = 2:rep
count = count + 1;
zVec(count) = zrand(C(:,i), C(:,j));
end
end
zmean = nanmean(zVec);
zstd = nanstd(zVec);
en... |
352a089961327a1e75a627dea0557abc984096cc8c378a18d85e3aab73fe9a7d | MATLAB | 322 | 13 | function lim1 = trimLim(lim1, lim0)
%TRIMLIM Find intersection of two limit ranges
dx = diff(lim1);
if lim1(1) < lim0(1)
lim1 = lim0(1) + [0, dx];
end
if lim1(2) > lim0(2)
lim1 = lim0(2) + [-dx, 0];
end
lim1(1) = max(lim1(1), lim0(1));
lim1(2) = min(lim1(2), lim0(2));
en... |
89dbc02930d0219cae411dc9cac8991d39c09f43386eac9c4fcf2d93342276f9 | MATLAB | 322 | 4 | function [y1, y2, Pbar, Phat, PSmoothed, Kgain] = KalmanARFilter(x, b, a, varargin)
% KalmanARFilter has been deprecated. Use arma_kalman_filter instead.
warning('KalmanARFilter has been deprecated. Use arma_kalman_filter instead.');
[y1, y2, ~, Pbar, Phat, PSmoothed, Kgain] = arma_kalman_filter(x, b, a, varargin{:}... |
b04c319dd23bc35f70983eb6d5d68cc67aaf972ae046aa2d3f76c9a6f64255dc | MATLAB | 323 | 4 | function [dipole, teta]= DipoleGeneratorAbnormal(N,fs,f,alphai,bi,tetai,teta0,STM,S0)
% DipoleGeneratorAbnormal has been deprecated. Use vcg_gen_abnormal instead.
warning('DipoleGeneratorAbnormal has been deprecated. Use vcg_gen_abnormal instead.');
[dipole, teta]= vcg_gen_abnormal(N,fs,f,alphai,bi,tetai,teta0,STM,S... |
43a34aeb6c5c82058ae7545d4269a2a7d3e0c573441748c55d15f38e9b8deaa1 | MATLAB | 324 | 15 | function out = fft3s(data, useRescale)
% function out = fft3s(data, useRescale)
%
% Do 3D FFT on first 3 dims of data and fftshift
if nargin < 2
useRescale = 0;
end
out = fft1s(fft2s(data),3);
if useRescale
nx = size(out,1); ny = size(out,2); nz = size(out,3);
out = out / sqrt(nx) / sqrt(ny) / sqrt(nz);... |
75fee6134de8db2b7411ed83c13f020505b75b6672ad8931fa136ab5144ba19e | MATLAB | 324 | 18 | function out = ssos(in,dim)
if nargin > 1
out = sqrt(sum(in.*conj(in),dim));
else
if size(in,4)==1
if size(in,3)==1
out = sqrt(sum(in.*conj(in),2));
else
out = sqrt(sum(in.*conj(in),3));
end
else
out = sqrt(sum(in.*conj(in),4));
end
... |
ca59f2006fc00c102d2cc4759e32a6197428f480da07d83495d788af65c1886c | MATLAB | 324 | 4 | function [peaks, peak_indexes] = PeakDetectionAdaptiveHR(x, ff, fs, varargin)
% PeakDetectionAdaptiveHR has been deprecated. Use peak_det_adaptive_hr instead.
warning('PeakDetectionAdaptiveHR has been deprecated. Use peak_det_adaptive_hr instead.');
[peaks, peak_indexes] = peak_det_adaptive_hr(x, ff, fs, varargin{:}... |
cd0555e16bf0f936b299260c5ecd2a69151621b7cb7f6fcffd89b5bfa21fc5d2 | MATLAB | 324 | 10 | function E = ECGModelError(X,ECGmn,Phasemn,flag)
% ECGModelError has been deprecated. Use ecg_gen_from_phase instead.
warning('ECGModelError has been deprecated. Use ecg_gen_from_phase instead with required changes.');
Z = ecg_gen_from_phase(X, Phasemn);
if flag==0
E = Z - ECGmn;
elseif flag==1
E = Z;
... |
68281932b9ebe8155ae7ae830c6adf982c801e982a4f679e32b79abb0d35a5e3 | MATLAB | 325 | 25 | function [f1 f2 ] = split_fid(f)
for k=1:length(f)
exa = f(k).examnumber;
switch exa
case {'E1','E3'}
if ~exist('f1')
f1(1) = f(k);
else
f1(end+1) = f(k);
end
case {'E2','E4'}
if ~exist('f2')
f2(1) = f(k);
else
f2(end+1) = f(k);
end
end
end
... |
9904b676586c4cfabcdda0fce48f54de8a0501302f36456df9990782190aafd8 | MATLAB | 325 | 4 | function [ARCoefsKF , ARCoefsKS] = TimeVariantAR(data, order, x0, q, R, p0, alpha)
% TimeVariantAR has been deprecated. Use time_variant_ar_kalman instead.
warning('TimeVariantAR has been deprecated. Use time_variant_ar_kalman instead.');
[ARCoefsKF , ARCoefsKS] = time_variant_ar_kalman(data, order, x0, q, R, p0, al... |
995031f77d37f639f370fde4abd78a0b539a29e012251ff088a684d655fca681 | MATLAB | 325 | 14 | clear
clc
cd('I:\My Drive\ELYASHIV\PFC_paper_results_after_revision\eopn3\clusters\clusters_control')
%%
load("intensities_mean.mat")
load("intensities_sem.mat")
%%
psth_highest.mean = squeeze(intensities_mean(:,1,:));
psth_highest.sem = squeeze(intensities_sem(:,1,:));
%%
cd ..
save('psth_highest_control'... |
2f2d23a48be1af2964a61e9e1aafb392f764932cc61dfafbbfabc1d7aa1f7dc2 | MATLAB | 326 | 19 | function [y] = dphi(x, param)
% Derivative of scaled/biased logarithmic sigmoid: a * s(x - b) (1 - s(x - b))
%
% Parameters
% ----------
% - x: array
% Input
% - param: [scalar, scalar]
% Scale and bias parameters
%
% Returns
% -------
% - y: array
% Output
s = logsig(x - param(2));
y = param(1) .* s .* (1 - s);... |
623290e7b2b0724bcff8cdced30856b7ac0cf412411c4f553a6417f03d8651da | MATLAB | 326 | 11 | function [leny,yes_rowvec] = get_len_yvec(y)
% function [leny,[yes_rowvec]] = get_len_yvec(y)
sizey = size(y);
if length(sizey) > 2 || ((sizey(1) > 1) && (sizey(2) > 1))
error('y must be either a row or column vector');
end
leny = max(sizey);
if nargout > 1
if sizey(1) > 1, yes_rowvec = 1; else, yes_rowvec = 0; en... |
686347ecfa1cd65ee4ef4a8de5c7841d53733a178a4998054ad0b55a46011b71 | MATLAB | 326 | 16 | function Struct = remove_empty_fields_from_struct(Struct)
% removes empty fields
if isempty(Struct)
warning('empty struct')
return
end
Fieldnames = fieldnames(Struct);
for Indx_F = 1:numel(Fieldnames)
if isempty(Struct.(Fieldnames{Indx_F}))
Struct = rmfield(Struct, Fieldnames{Indx_F});
end
e... |
338e554761a6559d5d2b831ae51ee6fba7327ac3a7f451db1fa6f85fc873f641 | MATLAB | 328 | 12 | function car = getCAR(samplesIn, CARMode, ignoreSites)
%GETCAR Get common average reference for samples (mean or median)
if ~isempty(ignoreSites)
samplesIn(:, ignoreSites) = [];
end
if strcmpi(CARMode, 'median')
car = median(samplesIn, 2);
else
car = mean(samplesIn, 2);
... |
b5205297d24007f379d5cc58733bd7379f276bfa236938c785c7b512c5bafa2c | MATLAB | 328 | 11 | function y = RemoveEEGSeizureNoise(x, fsx, probth, wlen, keep)
% NSCA
lx = round(wlen*fsx);
Ex = sqrt(filter(ones(1, lx), lx, x.^2, [], 2));
eex = mean(Ex, 1);
thx = quantile(eex, probth);
Ix = find(eex >= thx);
Jx = 1:length(Ex); %find(eex < thx);%
[s , ~, A] = NSCA(x, Ix, Jx);
y = A(:, end-keep+1:end)*s(end-keep+1:e... |
6eb86c0650e8db5fe3e75ff34138fa37ac563b77545fded65da92b11a797e114 | MATLAB | 329 | 16 | function out = ifft3s(data, useRescale)
% function out = ifft3s(data, useRescale)
%
% Do 3D FFT on first 3 dims of data and fftshift
if nargin < 2
useRescale = 0;
end
out = ifft1s(ifft2s(data),3);
if useRescale
nx = size(out,1); ny = size(out,2); nz = size(out,3);
out = out * sqrt(nx) * sqrt(ny) * sqrt... |
b0e6af42bf64b081bdd36a82cb22c26fa78a9087639cfcb3d6e882b0624432c8 | MATLAB | 329 | 13 | function Find_Longitudinal_Axis_Segments(Workspace,Cxy)
% List CB vertices:
F1 = find([Workspace.Vertices.Order] < 0);
S = struct('Branch_index',{},'Segments',{},'Vertices',{});
for i=1:length(F1) % For each CB vertex (also CB branch).
while % Trace the branch until a termination condition is met.
end... |
d8cb3b78edd4bc04991b509f9442644c500ab4e0e913eee3bcf1558fd7c75ac7 | MATLAB | 329 | 16 | function [map_states] = mapstates_mode(st_post)
NT = size(st_post,1);
nsubs = size(st_post,2);
map_states = zeros(NT, nsubs);
for sub = 1:nsubs
for i = 1:NT
tbl = tabulate(squeeze(st_post(i,sub,:)));
counts = tbl(:,2);
[~,ind] = max(counts);
map_states(i,sub) = tbl(ind,1);
end
... |
f2f0586fd926689e0f7b1af417a61d0337bb3d78a5bd965f18ea72d3ed80f139 | MATLAB | 329 | 13 | function [err, bad, pred] = cnntest(layers, weights, params, test_x, test_y, type)
pred = cnnclassify(layers, weights, params, test_x, type);
[~, pred_ind] = max(pred, [], 2);
[~, y_ind] = max(test_y, [], 2);
bad = find(pred_ind ~= y_ind);
err = length(bad) / size(pred_ind, 1);
%bad = [];
%err = sum((pred - y).^2) /... |
0682a007a9840f19038faee81f290b045bd684389d90b638e805e95226cf8e75 | MATLAB | 330 | 19 | function T2 = find_T2(f)
for k=1:length(f)
te(k) = f(k).TE/1000;
y1(:,k) = f(k).integral_real;
y2(:,k) = f(k).integral_real_all;
y3(:,k) = f(k).integral_fid_abs;
end
[a,b] = fit_ax_b(te,log(y1));
T2(1,:) = -1./a;
[a,b] = fit_ax_b(te,log(y2));
T2(2,:) = -1./a;
[a,b] = fit_ax_b(te,log(y3));
T2(3,:)... |
2a9b947c97decadda8c00d39b2443eca54a27762538dcdc55ac09cb400e720a4 | MATLAB | 330 | 7 | function ExcludedCycles = is_only_exclusion_criteria(CyclesMeetCriteria, IdxCriteria)
% identifies all cycles that were excluded only because of this criteria
I = 1:size(CyclesMeetCriteria, 2);
I(IdxCriteria) = [];
Remaining = all(CyclesMeetCriteria(:, I), 2);
ExcludedCycles = Remaining & ~CyclesMeetCriteria(:, IdxCrit... |
89a8ebc8c08ddd3c0e50a671f5d0962af03b03deafe1473e8a58d2d9ee91e727 | MATLAB | 330 | 8 | function metafile = findMeta(binfile)
%FINDMETA Given a path to a recording (.bin, .dat), find its meta file
% Returns absolute path to meta file if it exists, otherwise empty
% string.
[dirname, filename] = fileparts(binfile);
metafile = jrclust.utils.absPath(fullfile(dirname, [filename '.meta'... |
402d7e1f9aa8ad3c3516dc7a8e4d5aefcefd1c809a7eab4f1830f2b25891e730 | MATLAB | 331 | 14 | function out = fft2s(data,useRescale)
% function out = fft2s(data,useRescale)
%
% Do 2D FFT on each slice of data and fftshift
if nargin < 2
useRescale = 0;
end
out = fftshift(fftshift(fft2(ifftshift(ifftshift(data,1),2)),1),2);
if useRescale
nx = size(out,1); ny = size(out,2);
out = out / sqrt(nx) / sq... |
9564ef0e8a83166eb59c8fe8a758fbed40ea9bfb6b132e35e0be5ecd8c6eceab | MATLAB | 331 | 11 | function im = warpIm(im,mask)
targetRowLen = size(im,2);
% go through rows and do interpolation
for i = 1:size(im,1)
startIdx = find(mask(i,:),1,'first');
rowLen = targetRowLen - (startIdx-1);
im(i,:) = interp1(1:rowLen,single(im(i,startIdx:end)),linspace(1,rowLen,targetRowLen));
... |
85c300690ed4fa4f5705794471c89aeffef086275f3c50b44acd95fcc9b2a7e5 | MATLAB | 332 | 16 | function SaveITS
global ITS fname tfile FLName dpath3
tfiletrim=strtrim(tfile);
fnametrim=strtrim(fname);
FLName
if strcmp(fnametrim(end-7),'C');
OLD=cd;
path=[dpath3,'\R_LPhaseFolder'];
cd(path);
FLname=[tfiletrim(1:end-2),fnametrim(1:end-4),'ITS'];
ITS
save(FLname,'ITS');
c... |
7cbf78721d076550fc1f4073ebb507a6ccea792ca0b7d18d513e7dc4b3818072 | MATLAB | 333 | 12 | function StructMain = add_fields_to_struct(StructMain, StructNew)
% add all fields and their respective values of StructNew
% to every struct in StructMain.
Fieldnames = fieldnames(StructNew);
for n = 1:numel(StructMain)
for Fieldname = Fieldnames'
StructMain(n).(Fieldname{1}) = StructNew.(Fieldname{1});
... |
e7e9750adc5a3661f761c098def33ead00c50d7e7b288a8f23ea18a64d45b0ae | MATLAB | 334 | 10 | function status = spmup_check_matlab_version()
status = 0;
% matlab 2019a
% see https://en.wikipedia.org/wiki/MATLAB#Release_history
matlabVersion = '9.6.0';
if verLessThan('matlab', matlabVersion)
warning('Some features are not implemented for MATLAB version < R2020a.');
status = 1... |
07bbe4519c2b155534d65be61791fdd89b7903f58156f315f30ed4e999c0f808 | MATLAB | 335 | 13 | function [spikeMin, spikeMax, vpp] = spikeMinMax(spikeWindows)
%SPIKEMINMAX Summary of this function goes here
spikeMin = shiftdim(min(spikeWindows))';
spikeMax = shiftdim(max(spikeWindows))';
if nargout == 3
vpp = spikeMax - spikeMin;
end
spikeMin = abs(spikeMin);
spikeMax = abs(s... |
26c47e02cb95444d94b4d4deb75fca696725a080e1fbf7baa458e48a4e405dfd | MATLAB | 335 | 14 | function out = ifft2s(data, useRescale)
% function out = ifft2s(data, useRescale)
%
% Do 2D FFT on each slice of data and fftshift
if nargin < 2
useRescale = 0;
end
out = fftshift(fftshift(ifft2(ifftshift(ifftshift(data,1),2)),1),2);
if useRescale
nx = size(out,1); ny = size(out,2);
out = out * sqrt(nx) ... |
a24defcd3d4002e4260f188c46ca4746c47e78e04137ff5a7bf19e9b17d0e9d9 | MATLAB | 335 | 7 | function rescaleFigTime(hFigTime, timeScale)
%RESCALEFIGTIME
YLim = hFigTime.axApply('default', @get, 'YLim');
hFigTime.axApply('default', @set, 'YLim', [0, YLim(2)*timeScale]);
hFigTime.axApply('histogram',@set,'YLim', [0, YLim(2)*timeScale]);
imrectSetPosition(hFigTime, 'hRect', [], [0, YLim(2)*ti... |
c88584dd715c2bb6b565ef1346f9111f2b2f4dfbcf0f8b0b4018fb0e9d00a320 | MATLAB | 335 | 14 | % loop over folders and call get celltype_parameters_function
clear
clc
n = 1;% number of experiments to cell
for i =1:2
[file{i}, path{i}] = uigetfile('temp_wh.dat');
exp_id{i} = inputdlg(path{i}, 'PHB',[1 50], "PHB");
end
%%
for i =1:2
get_celltype_parameters_function(path{i}, file{i}, exp_id{i}... |
f22682714aafb0a1123798354a0619463e2198302e7a64b5ccab85f79cfc3c63 | MATLAB | 335 | 4 | function [stacked_events, num_non_zeros] = EventStacker(signal, event_indexes, event_width, varargin)
% EventStacker has been deprecated. Use event_stacker instead.
warning('EventStacker has been deprecated. Use event_stacker instead.');
[stacked_events, num_non_zeros] = event_stacker(signal, event_indexes, event_width... |
fb2225450929167d163e1a060803d3da6866acea6b3ae7cb7cc9f9d3fb004c79 | MATLAB | 335 | 13 | %% devide right and left
%load brain render table
clc
clear
[filename, path] = uigetfile("MultiSelect","off", ".csv");
datafile = fullfile(path, filename); %save path
cd(path)
T = readtable(datafile);
%%
right_T = T(T.x < 5500, :);
left_T = T(T.x > 5500, :);
writetable(left_T, 'left_cells.csv')
writetable(right_T, 'rig... |
72d29c750b35c208a9d210b9a49343774608e6fd4690ae244868e903a51830d3 | MATLAB | 336 | 15 | function ShowProgress(Prog,handle)
% Copyright 2009-2011 Thomas Koenig
% distributed under the terms of the GNU AFFERO General Public License
if ~ishandle(handle)
return
end
axes(handle);
h = barh(0.5,Prog);
set(h,'BarWidth',1,'EdgeColor',[1 0 0],'FaceColor',[1 0 0]);
set(gca,'XTick',[],'YTick',[]);
axis([0 ... |
bc49eb64462fbebaf9eb78ddf3e1a8f94383e1b70e061427e325023a5a68b016 | MATLAB | 336 | 14 | function [coef,pval ] =nancorr(x, varargin)
if nargin == 1
x = x(~any(isnan(x),2),:);
[coef,pval] = corr(x);
else
if ~ischar(varargin{1})
y = varargin{1};
vidx = ~any(isnan(x),2) & ~any(isnan(y),2);
x = x(vidx,:);
varargin{1} = y(vidx,:);
end
[coef,pval] = corr(x,var... |
c7b5be9bef51fe508a6aa8d5bd9552aada1fb664a4825b302e715cfef1399267 | MATLAB | 336 | 11 | function [train_x] = normalize(firstlayer, train_x)
if (isfield(firstlayer, 'norm'))
datanorm = sqrt(sum(sum(sum(train_x.^2, 1), 2), 3));
datanorm(datanorm <= firstlayer.eps) = firstlayer.norm;
train_x = train_x ./ repmat(datanorm, [firstlayer.mapsize firstlayer.outputmaps 1]);
train_x = train_x * firstlayer.n... |
2c8afbfd3815e886ae7a917ccb8c284c2bc6a707fd2184a57de50e8fbda1c108 | MATLAB | 338 | 15 | function knl = get_a_knl_stm(session, channel, unit)
% Get average of estimated stimulus kernels of specific a-model
%
% Parameters
% ----------
%
%
% Returns
% -------
% - knl: 4D array
% (width x height x time x delay) stimulus kernel of s-model
model = load_avg_model(session, channel, unit);
knl = model.set_of_ke... |
7312bd7ece238a1c234c31c1770e5653d09d4e845fa884507cfc68685b24cf41 | MATLAB | 338 | 4 | function [theta_min, theta_max, theta_mean, theta_med, ang] = ColumnSubspaceAngle(A, B)
% ColumnSubspaceAngle has been deprecated. Use column_subspace_angle instead.
warning('ColumnSubspaceAngle has been deprecated. Use column_subspace_angle instead.');
[ang, theta_min, theta_max, theta_mean, theta_med] = column_sub... |
3b68fe90a7d6ff499a0b35e54142528890016b02ba808ce6b3c9a123c90c8df0 | MATLAB | 339 | 12 | function plotAuxRate(obj, selectedOnly)
%PLOTAUXRATE
if selectedOnly
corrData = jrclust.views.plotAuxCorr(obj.hClust, obj.selected(1));
else
corrData = jrclust.views.plotAuxCorr(obj.hClust, []);
end
if ~isempty(corrData)
jrclust.utils.exportToWorkspace(corrData, obj.hCfg.ver... |
543aef4754a6f8867e1506458c028e6f320680ecf392e215c924511b740898d9 | MATLAB | 339 | 7 | for k=1:size(P,1)
[p f] = fileparts(P(k,:)) ;
[p f] = fileparts(p);
mkdir(fullfile('/home/romain/tmp/MM_for_g',f))
cmd=['!cp -pr ' P(k,:) ' ' fullfile('/home/romain/tmp/MM_for_g',f... |
c2196a8bb489fc694750b99bce89226bf818e2794e22594cdf57072d19f3df86 | MATLAB | 339 | 14 | function data = XxReadTiffSmallerThan4GB(TiffPath)
pic_info = imfinfo(TiffPath);
[frame_CCD,~] = size(pic_info);
row_CCD = pic_info.Height;
colum_CCD = pic_info.Width;
data = zeros(row_CCD,colum_CCD,frame_CCD);
for frame_temp = 1:frame_CCD
data(:,:,frame_temp) = imread([TiffPath],'Index',frame_temp);
end
% data =... |
04e67aa574d4acea62d81e38e9f2ca95ddd00134a0adca0b9c0ea3d39cf15eb8 | MATLAB | 340 | 4 | function [e, n] = AdaptiveFilterMultipleDelay(x, mindelay, maxdelay, taps, mu)
% AdaptiveFilterMultipleDelay has been deprecated. Use adaptive_filter_multi_lag instead.
warning('AdaptiveFilterMultipleDelay has been deprecated. Use adaptive_filter_multi_lag instead.');
[e, n] = adaptive_filter_multi_lag(x, mindelay, ... |
095019ab996ab31178501968a5c8099161abad9455a6f053529e8dc5fc3274f6 | MATLAB | 340 | 13 | function success = writeFilt(obj, filteredData)
%WRITEFILT Write filtered data to a file
success = 0;
if ~obj.openFiltForWriting()
warning('Failed to open filtered file');
return;
end
count = fwrite(obj.filteredFid, filteredData, ['*' obj.dataType]);
success = (count == numel(f... |
0ebd36fdcce7eb338222b98d560a812651febb68585b4d0b90b7e1a8f41989c5 | MATLAB | 340 | 16 | function r = InstCorr (x,tau)
% Instantaneous signal correlation calculator
% Reza Sameni, 2010
x = x(:);
N = length(x);
M = ceil(max(abs(tau))/2);
xx = [zeros(1,M) x' zeros(1,M)];
r = zeros(N,length(tau));
t = 1:N;
for i = 1:length(tau)
tt1 = t - round(tau(i)/2);
tt2 = t + round(tau(i)/2);
r(:,i) = xx(tt... |
b697f8cf2178dc6f32d1025ac24599d52ee179012e9c3d5abcb180e47cd81df5 | MATLAB | 340 | 20 | function file = load_file(filename)
% Load file
%
% Parameters
% ----------
% - filename: char vaector
% Filename which would be loaded
%
% Returns
% -------
% - data: structure array
% Loaded data
fprintf('Load `%s`: ', filename);
tic();
file = load(filena... |
6516fd199643cb8e4fdea2d8de0fdbaa81de7945d19579c720a6f8554e452ad0 | MATLAB | 343 | 14 | function [Xout, Yout, Zout] = surfscale(q,X,Y,Z)
%surfscale - takes a surface scalar and surface vectors as input, returns
%input grid scaled by q as output. Ensure X,Y,Z is 3D and has equal
%dimensions.
siz = size(X);
assert(length(siz) == 2,'Surface dimensions != 2');
assert(siz(1) == siz(2));
Xout = q.*X;
Yout = ... |
45d689c922e978fc31d9408167532172b12540a68aa46d664f9eee87226684c3 | MATLAB | 344 | 12 | A = all_psthT.position;
B = T.acronym;
for i = 1:length(A)
idx(i) = contains(A{i}, B{i})
end
T2 = readtable("cells_coordinates_map.csv");
T2.in_struct_prob = T.in_structure_prob;
for i = 1:length(T2.id)
rowname{i}= [T2.exp_name{i} '_cell_' num2str(T2.id(i))];
end
T2.Properties.RowNames = rowname;
row... |
7c0e6f79b14fe0f0efe87d4282658548088e96188a290b42dfef3ee6299bbdad | MATLAB | 344 | 4 | function [lambda, AIC, MDL, NEW, ENSTh, ENS, fhand] = EstimateDimension(x, noisevar, flagplot)
% EstimateDimension has been deprecated. Use dimension_estimation instead.
warning('EstimateDimension has been deprecated. Use dimension_estimation instead.');
[lambda, AIC, MDL, NEW, ENSTh, ENS, fhand] = dimension_estimation... |
60a15e731ca8ac648a28c1a468099b6464f005405c57264b4552e3e41cb67189 | MATLAB | 345 | 16 | n_state = 2
n_covariate = 4
Xi_old = rand(n_state,n_state+n_covariate)
Z = [0,1;0,1;0,1;1,0;1,0;0,1;0,1;1,0;0,1;1,0]
Exo = randn([n_covariate,10])
a = 0
b = 10
S = 2
Y = [randn(4,1);5*randn(6,1)]
Omega = reshape([1,5],[1,1,2]);
Xi_new = Holsclaw_Param(Xi_old, Z, Exo, a, b)
[states, probs, t_prob] = Holsclaw_State(Xi... |
ed2ed57aa6cef249a3768ffd74a194020bfe2de701cccdf1c74a7157433feeaf | MATLAB | 345 | 12 | function hRec = newRecording(rawPath, hCfg)
%NEWRECORDING Create a new RawRecording based on recordingFormat
switch hCfg.recordingFormat
case 'Intan'
hRec = jrclust.detect.IntanRecording(rawPath, hCfg);
otherwise % SpikeGLX .bin/.dat
hRec = jrclust.detect.Recording(rawPa... |
22325412d7c986006dbea9878de3ce80597329c88cd9c0b24ea6d88d9e690981 | MATLAB | 347 | 16 | function supp_fig1_experiments(save)
%% Supplemental Figure 1: Auto- and cross-correlation figures
if nargin == 0
save = "";
end
autocorrelatemap('100140949');
if save
get_save_figure(gcf, 'Figures', 'supp_fig1_auto');
end
crosscorrelatemaps('100140756', '100140949');
if save
get_save_figure(gcf, 'Figure... |
b7a45ea1303690043f35715f3eb984450b3d87ec0ce384499cbf8364db37e5b9 | MATLAB | 347 | 15 | function fo = remove_first_points(fi,numberofpoints)
if ~exist('numberofpoints')
numberofpoints=1;
end
fo = fi;
for nbs = 1:length(fi)
fo(nbs).fid = fi(nbs).fid(numberofpoints+1:end,:);
fo(nbs).spectrum.np = fo(nbs).spectrum.np -numberofpoints;
fo(nbs).spectrum.n_data_points = fo(nbs).spectrum.n_data_poin... |
3bba0cea9e12152cf52af2d6cd4387cf6c29fabd6140171feab3866abd9ba76e | MATLAB | 348 | 10 | function sampleRMS = estimateRMS(samplesIn, nSubsamples)
%ESTIMATERMS Estimate RMS of samples using median
if nargin < 2 || isempty(nSubsamples)
sampleRMS = median(abs(samplesIn));
else
sampleRMS = median(abs(jrclust.utils.subsample(samplesIn, nSubsamples, 1)));
end
sampleRMS = sing... |
07d9f7c3ea66ba8ac522ec1df011bb1a074284643528b23f3f90345795e445ed | MATLAB | 349 | 12 | function tracesOut = bit2uV(tracesIn, hCfg)
%BIT2UV Transform collected trace values to uV
if strcmp(hCfg.filterType, 'sgdiff')
nrm = sum((1:hCfg.nDiffOrder).^2) * 2;
elseif strcmp(hCfg.filterType, 'ndiff')
nrm = 2;
else
nrm = 1;
end
tracesOut = single(tracesIn) * single... |
74eed7c15df4c48b5bb7342ae9e8298a0b8aefc6a10d151e1f555e7887bf04d9 | MATLAB | 349 | 11 | function openRaw(obj)
%OPENRAW Open the raw recording file for reading
if obj.rawIsOpen
return;
end
obj.rawData = memmapfile(obj.rawPath, 'Offset', obj.headerOffset, ...
'Format', {obj.dataType, obj.dshape, 'Data'}, ...
'Writable', false... |
55357bb952a1e831a1847b642a9414ec8b0ce1d3ee23902378dadd2ca2b8786d | MATLAB | 350 | 10 | function process_segs_batch(foldernames, Fs)
% process segments by the batch
% foldernames : cell array of strings
% Fs : in seconds
% Assumes that the working directory is where this matlab file is
for i=1:length(foldernames)
fprintf("----SEG %d\n----", i);
process_single_segment(fo... |
aa0f8c257bc69ddcebc68494f7e8c64a3128dc13e1f7e8a8a8fa58679beed899 | MATLAB | 350 | 11 | function updateFigWav(obj)
%UPDATEFIGWAV
if ~obj.hasFig('FigWav')
return;
end
hFigWav = obj.hFigs('FigWav');
obj.showSubset = 1:obj.hClust.nClusters;
jrclust.views.plotFigWav(hFigWav, obj.hClust, obj.maxAmp, obj.channel_idx, obj.showSubset);
setFigWavXTicks(hFigWav, obj.hClust, ... |
028009226d6829784dea0052c1508b7bb14e29157f8856f6dd87d6e32d1e45b3 | MATLAB | 351 | 7 | m = loadMovie('G:\E7_2DAA\miniscope\subject13\session1\preprocessed\preprocessedMovie.h5',1,1000);
savePath = 'G:\E7_2DAA\misc\example_movie_data\preprocessed.h5';
saveMovie(m,savePath)
m = loadMovie('\\DROBO6\Public\E7_miniscope_concat\M13\Session1\rawMovie.h5',1,4000);
savePath = 'G:\E7_2DAA\misc\example_movie_data\... |
0a3a03b4722dd51e662f42c433e3e60a407da59c68bd8f2f94622f120b7460a9 | MATLAB | 351 | 17 | function display(ob)
%function display(ob)
% "display" method for this class
name = inputname(1);
printf('"%s" is an object of class "%s":', name, class(ob))
ob = struct(ob);
disp(ob)
fnames = fieldnames(ob);
for ii=1:length(fnames)
fname = fnames{ii};
if isstruct(ob.(fname))
printf('%s.%s :', inputname(1), fnam... |
e30a8df0faf93801693271d4ebc7b422f78ca24f01a01b9eefd2f81f77b6ac79 | MATLAB | 351 | 20 | function W = tukey(n,kc,w)
% function W = tukey(n,kc,w)
%
% Tukey windowing function, as described on p496 of Bernstein2004
if nargin < 3, w = 0.15; end
if nargin < 2, kc = 0.85; end
if length(n)==1
kvals = linspace(-1,1,n);
else
kvals = n;
end
W = cos((pi*(abs(kvals)-kc))/(2*w)).^2;
W(abs(kvals) < kc) = 1;
... |
1be95d994973454959493a5867764dd698778bf99cf4a85b4717773726f74dbb | MATLAB | 352 | 11 | function [logdet] = matrix_cholesky_logdet(A)
% Compute the logarithm of the determinant of a positive definite symmetric
% matrix (i.e. log|A|) based on the cholesky factor of A, i.e., L L' = A.
assert(ismatrix(A), 'A has to be a matrix of size (M X M)')
assert(isreal(A), 'Please check A')
L = chol(A,'lower');
logd... |
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