sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
22bd1febe3dae628e2050c667b08c76fd2f8be241c159297f1cf54b01b85eb08 | MATLAB | 41 | 2 | function [y] = precondDiag(r,D)
y = D.*r; |
4ba9b7cd51dd08405c0760902eb2f4f2fba10c80a69f637bd3717b166bd5f504 | MATLAB | 43 | 1 | function [Idx,C] = FuzzyKmean(s,nbClusters) |
7cdab25101c503a7d2b5cbf26e7d1dd7b7c6cc850122e64220f9d1425cea06bc | MATLAB | 43 | 3 | function n = numel(A, varargin)
n = 1; |
60083fa8904f5531ec3ee2925bb545b5fe73c93a17b8ae40b2a3e5559c850139 | MATLAB | 45 | 4 | function S = computeEstimatedNoiseCov()
end |
ee3ed73abf41f1ff498c78f9f09abd7fc7bd382ca83fb0fba4c98f712f4cbb73 | MATLAB | 48 | 3 | function X = sigm(P)
X = 1./(1+exp(-P));
end |
3c9781f8594e73b8e9a2277d34ef40eb9548232c1b5422e2b61ecb4b705e14f2 | MATLAB | 50 | 2 | function [y] = precondUpper(r,U)
y = U \ (U' \ r); |
218a2bf7b5b801e97aade20f6f987a469a2d132c834cdd08b3c7619f626fc369 | MATLAB | 52 | 3 | function [peth] = pethData
% Under development TODO |
330bd7bbc7f4d4182170c1e3b043de470e700ada76a63d8a7cb7c750e59dc5b3 | MATLAB | 52 | 3 | function dB = a2dB(amp)
dB = 20.*log10(amp);
end |
f8422d460779b055cb8bd3fcf4faa6d416759695f20d01efd8d785045105371c | MATLAB | 53 | 3 | function ExpCorr(data1,data2,data3)
if size(data1,2) |
2d3c187e3e2398bdb5c8b5f44c75eabe3a6f0879e57cf1487821980b04686509 | MATLAB | 54 | 2 | function colors=different_colors(n)
colors=rand(n,3); |
d2e5ae5edeca7c6d14e7c988f885476efbe9fa4daff5d53c7aaf93b1dcf33791 | MATLAB | 54 | 3 | function f=tanh_opt(A)
f=1.7159*tanh(2/3.*A);
end |
e6dd3ab7030a3dfb7f95054bd8175fabe0f305c4f18196df33680a2c1e7ad4b3 | MATLAB | 55 | 3 | function b = isuppercase(s)
b = all(upper(s)==s);
|
07e3e7ebdb08fae46761c6603eac3ab24db06e96de14d51c37d55c0810b22ed9 | MATLAB | 57 | 4 | function y = modifiedExp(x)
y=exp(x);
y(x>0) = x(x>0)+1; |
0d3b6cd60a61710029d49dfcde0a812220d0dbab0695f1cf6352193d559a0a75 | MATLAB | 58 | 2 | function [gx] = g_inverse(x,P,u,in)
gx = 1./(P(1)*x+P(2)); |
6310d898bf33ed00cd1a3c8fd828f17e3ffc76aa909944fb8e2ae9ea29aef092 | MATLAB | 59 | 2 | function [y] = precondUpper(r,U,D)
y = U \ (D .* (U' \ r)); |
3bf3664b68e0e64978064f292f8ed2a51229ea258803442e02515b5516001d47 | MATLAB | 60 | 3 | function [] = parsave(dir,BaseEval)
save(dir,'BaseEval')
end |
b97628bc0f7a89e89f4d8d9743701727801cb6bdb2e0baba47b4c94471a4b095 | MATLAB | 60 | 2 | function colors=distinguishable_colors(n)
colors=rand(n,3); |
c96cf9c8560310cb2a6c90bf546c8f28a72d5685312b78018a0bd62e5899f701 | MATLAB | 60 | 5 | function v = colvec(M)
v = reshape(M,[prod(size(M)) 1]);
|
57712cf9330fc533f93d80d23b268ea874cd32533782403bd51c8e6dfd1dcbc5 | MATLAB | 62 | 2 | function axesData_ButtonDownFcn(hObject, eventdata, handles)
|
af85862ea032467f6cbafa739f7d39553bdbe4bae5e65fa6baf9325d8d38176b | MATLAB | 62 | 5 | function n = numel(A, varargin)
% Under development
n = 1; |
f2ed02a7951c41099fb038949bed4f14f7463a99fe9f8ee6069c097d32994c59 | MATLAB | 65 | 4 | function a = vectorSparseness(v)
a= (mean(v)).^2 / mean(v.^2);
|
ee2f16f939b395a712e0c82e9927109befecfcf4b9cae3862c45f50111fa989b | MATLAB | 66 | 3 | function shuffled = shuffle(x)
shuffled = x(randperm(length(x))); |
593361f00b809f062798e0702d73d11f0a1914b0a686cbcb24a0f2ba20c92ceb | MATLAB | 67 | 7 | function y = HarrisExp(x)
if x<0
y = exp(x);
else
y = x+1;
end |
372880f90c02b1834d9d66b4cd3bd7b56c4b77fec60c97380d4368c879a938ea | MATLAB | 74 | 3 | function bn = bn(v, VTraub)
bn = 0.5*exp_t((10-v2(v, VTraub))/40);
end |
c2832c335fcdc94889d150216681ee8bd79056e5b4a4eb67b8955c2356de16cb | MATLAB | 74 | 5 | function tu = TimeUnit(tsa)
% Returns TSD time units
tu = tsa.time_unit; |
6a5d641c3c6eb26ac0460925f6f14455960bf7da2d9742941f62db23e0ccf58e | MATLAB | 75 | 3 | function an = an(v, VTraub)
an = 0.032*vtrap((15-v2(v, VTraub)),5);
end |
50bfe2a41b141bc679d420980cb3952bf2df2fac3b414abd7c2ee6052db377ca | MATLAB | 80 | 3 | function antest = anantest(v)
antest = (15-v2(v))/(exp((15-v2(v)/5)-1));
end |
2d1aab6e1cfef4614ba7078dc1459a7961cc8deca5cdf1a471898fd0a2ea3275 | MATLAB | 81 | 7 | function UsedSets=GetUsedSets()
UsedSets=[10 25 28 30 39 75 94 99 103 106];
|
b944b6ada8baa3dddf84df30ba6a89ff9798db14e14f3a84332575df3b374ae8 | MATLAB | 82 | 3 | function f=atan_ap(params,x)
f=params(1)*atan(params(2)*(x-params(3)))+params(4); |
d109a37a1d7f89701dbf1cbdd745449889a225b9780f75122f7dcaf0bca02881 | MATLAB | 82 | 5 | function ov = condexp(c,vtrue,vfalse)
if c, ov = vtrue; else ov = vfalse; end;
|
aa0665290a9f72a3220602d76c204fd4af45267c32de1993d07d8bfbde446970 | MATLAB | 83 | 4 | % g
function g = VMMix_g(x, mu, k)
g = exp(k*cos(x - mu))/(2*pi*besseli(0, k));
end |
2b48df257cd0f8c64ea14a75a5538c9ab1d107b76f8ebb3b866d88727757f474 | MATLAB | 84 | 4 |
function movieList = updateMovieList(allS,movieList)
movieList(:,6) = allS;
end |
13b012453ab39fec90518ea81648e92c5672dc4d68c120a2d65c9253706ab16d | MATLAB | 86 | 6 | function Jp = calcMaxLvlDWT(Y,M)
N = size(Y,1);
Jp = fix(log2(N/(M-1)));
end |
4c8a02fa2c8b48013e7b745df3589e0fdee48405716534b08581097857e03f5d | MATLAB | 86 | 3 | function n_exp = n_exp(v, Dt, VTraub)
n_exp = 1 - exp_t(-Dt/tau_n(v, VTraub));
end |
ca9a5418ebcfe2e519464f0a127cab17cb9187cde436feab0b6276cd19be086e | MATLAB | 86 | 3 | function output = tanh(input)
output = cellfun(@tanh, input, 'uniformoutput', false); |
3c30347b59e28f8b70d00c87ac81a5726fc708c05f13ea057fbb02c42d51861d | MATLAB | 89 | 4 | function f=cos_ap(params,x)
%f=params(1)*cos(x-params(2));
f=params(1)*cos(x-params(2)); |
dcc52645c66e91268701f9c48c02f32c9f21aaf6beb304c8ff3ccd4a976f97fc | MATLAB | 90 | 3 | function output = double(input)
output = cellfun(@double, input, 'uniformoutput', false); |
e9674c445faf820dc630aa295aabb40490905db6620f2c3799b6e315f60dd65e | MATLAB | 90 | 2 | function output=dirproject(dir,midpoint,coords)
output=dot(dir,coords)-dot(dir,midpoint); |
e675e0e021d4e805171432625a1baab76f5502ef6ff6320ee794c6249e2cca9b | MATLAB | 91 | 2 | function rawdata = load_imetronic_rawdata(filepath)
rawdata = dlmread(filepath,'\t',13,0);
|
13dc5b3b90db00a97233d7427306149901d292e1e822654b5d7557ae51927c7f | MATLAB | 93 | 7 | %% Function to convert radians to degrees 29-10-12
function d = r2d(r)
d = r * 180/pi;
end |
2b28ce3ed4ad4fc5621d5fc782ee3359727abd21c95edc81b70c6ddb9a5e15c8 | MATLAB | 93 | 7 | %% Function to convert degrees to radians 29-10-12
function r = d2r(d)
r = d * pi/180;
end |
ead1646cddfb3a71eed6c5b25db971154fa8a6b42dcffa0e568b0cb2bd884765 | MATLAB | 94 | 3 | function n_inf = n_inf(v, VTraub)
n_inf = an(v, VTraub)/(an(v, VTraub)+bn(v, VTraub));
end |
430acd2a840ae8bd5b8bb8566c894770ead5632402ad509847cd37f6870dd42d | MATLAB | 96 | 5 | function pnew=condp(pin)
p = pin./max(pin(:));
p = p+eps;
pnew=p./repmat(sum(p,1),size(p,1),1); |
f7063a57e20cbc798209925c4196003ef4149ac8cb0b1067480684e9706e2d53 | MATLAB | 97 | 3 | function save_step2(s,s2)
save([s.figure.folder filesep s.figure.prefix '_step2.mat'],'s2');
end |
63ca49972c8abc4a11c883936fdce17fefc197e21f0b42ae77cdbc4de86a6ca7 | MATLAB | 98 | 4 | function save_data_mean(Data_mean,Eventname,data_folder)
save([Eventname '_data_mean.mat']);
end |
09cfd3b3b16eecc1abc2709233576007f4e4fbd6e7663ef72a8dff7fb82e6a96 | MATLAB | 99 | 4 | function [z,p] = proportiontest(p,p0,n)
z = (p-p0) / sqrt(p0*(1-p0)/n);
[~,p] = ztest(z,0,1);
|
294f4d7fa806885dc83b7154b53de48fdbcc07afe21c144c9f6814d8bc147826 | MATLAB | 100 | 3 | function y = resample(x,frames)
y = interp1(1:length(x),x,linspace(1,length(x),frames));
end
|
cb30ff1038f0e9c2635595b25b2ab2c22e7adcf8992f69755320f48dc7dfd871 | MATLAB | 100 | 6 | function y = roundto(x,n)
%
% function y = roundto(x,n)
y = RoundDecimalPlaces(x,n);
end
|
e91cdce7fb0c0c490fb446305e0b2b661f95854c63ad1bfb113bbd0db273865e | MATLAB | 101 | 5 | % dg/dmu
function dgdmu = VMMix_dg_dmu(x, mu, k)
g = VMMix_g(x, mu, k);
dgdmu = k*sin(x - mu).*g;
end |
a590d82193f2810e3d1301bc98e3311ba28ac9ee0d5f2946e9c1f83286e942ea | MATLAB | 104 | 5 | function y = activation(x)
y = x;
y(x<0) = 0.01 * x(x<0);
y(x>0.5) = 1 - 0.25./x(x>0.5);
end |
953aad49a3fa9b4a8d6a69e7ddadf5d90730af0f53079c70e3c2e4e32cc7cd2d | MATLAB | 105 | 4 | function y = modifiedGaussConv(x,a)
Y = normpdf(-100:100,a(2),a(3));
x = a(1)*conv(x,Y,'same');
y=exp(x); |
ee6df655d07bc7e735135d8f73fe233daa85f4cb37a967ed629afad8cec04251 | MATLAB | 106 | 2 | function [legal] = isLegal(v)
legal = sum(any(imag(v(:))))==0 & sum(isnan(v(:)))==0 & sum(isinf(v(:)))==0; |
79d5c5eb0bf38f718abf3e636bbf69058aeb56e5de7c1c129333c4c1a9808bba | MATLAB | 107 | 3 | function pnew=condexp(logp)
pmax=max(logp,[],1); P =size(logp,1);
pnew = condp(exp(logp-repmat(pmax,P,1))); |
f003707cba90556c00aa093622f32d7c851e61bd25ec1fbb30de8f7f8daac36b | MATLAB | 107 | 6 | function [ labels ] = dwt1expand(l)
labels = [];
for i = 1:numel(l)-1
labels(end+1:end+l(i)) = i;
end |
1769e14b70c6e648844878a238990170feb0b76c53dcc58a9d9031488b64a74d | MATLAB | 108 | 5 | function mi_a = get_mi(a)
mi_a = (a(:,1:2) - ((a(:,4)+a(:,3))./2))./(a(:,1:2) + ((a(:,4)+a(:,3))./2));
end |
21952d933b119aae66cc578a72cd9d4bca08e0baaf149449f697e39bcf10b1f2 | MATLAB | 108 | 4 | function r = meanR(Rmat)
I = ones(size(Rmat));
Ids = tril(I, -1)==1;
r = mean(Rmat(Ids(:)), 'omitnan');
|
93abcad8aea8ea3adbb220a9faced4e64eb3a13c420eadb09348b5b99031ab00 | MATLAB | 108 | 5 | function y = modifiedGaussConv(x,a)
Y = normpdf(-100:100,0,a(1).^2);
x = conv(x,Y,'same');
y = exp(a(2)*x); |
ed9e571488f4b18c0aef63aa9580ac7784b8ae2bfa6df0331f80f4402f4478dc | MATLAB | 108 | 9 | function S = sem(X)
if min(size(X)) == 1;
X = X(:);
end
S = nanstd(X) ./ sqrt(sum(~isnan(X)));
|
47defa7dc28541de8fb441039e38d0741ebdba625608d68d7a448f05ea037f48 | MATLAB | 111 | 3 | function [L grad] = peerPrediction(weights,pop)
SpkTrainValuation(S,modifiedExp(pop*x),rg,r) - 0.25*sum(x.^2); |
59aef6c69632b576ac480abb8749bb1940d58777fc540c84e5683ebe20f36169 | MATLAB | 112 | 7 | function MAfilt = MAfilt(rg,deeg);
fn = [0.01:0.01:0.98];
cfirpm(50,fn,1./fn);
deegF = filtfilt(20,fn,1./fn)
|
6b8052ee6eba79fc4ef77fe4b6bc62ac3922bc603c394929aa52607e17ba4a96 | MATLAB | 112 | 4 | function r = medianR(Rmat)
I = ones(size(Rmat));
Ids = tril(I, -1)==1;
r = median(Rmat(Ids(:)), 'omitnan');
|
1d22a427fbb8f63c764dcc86a7532924ad2d3268e83d9c27ef78ec62de535b84 | MATLAB | 113 | 9 | function VX = Vel2d(X)
t = Range(X, 'ts');
dt = diff(t);
vx = diff(Data(X)) ./ dt;
VX = tsd(t(1:end-1), vx);
|
b557d38fd26f7f7e4d7efe583cb10fc3d8483af63bab7576279b355e53686c79 | MATLAB | 113 | 4 | function bins = edges2bins(edges)
% gets bin centers from edges vector
bins = (edges(1:end-1) + edges(2:end))/2; |
777aa501b2d7e76acedd53ad2371648c9b04e232d8276584d54d9b2a43f89df4 | MATLAB | 114 | 7 | % calculate number of good subjects for given channel, R stat, etc.
function calcGroupSummaryStat(sbjList)
end |
543778fc9030da5072d3714c4f985c124bc4cc7db7c7b733e5ec25ac4545ba45 | MATLAB | 115 | 4 | function anew=logsumexp(a,b)
amax=max(a);
A =size(a,1);
anew = amax + log(sum(exp(a-repmat(amax,A,1)).*b)+1e-310); |
93ef70f80557848d5b8da6c38ae01a9585870b2db57616f828b6cf37f4e78897 | MATLAB | 115 | 3 | function nchan = nchan(v, npre, Dt, VTraub)
nchan = npre + n_exp(v,Dt, VTraub) * (n_inf(v, VTraub) - npre);
end |
a324b27d1f5c4e64f07b3d2f81799f870c143067dcde127fea917fb168f0a4f1 | MATLAB | 115 | 10 | function b = isblankline(s)
b = true;
if all(isspace(s))
return;
end
if isempty(s)
return;
end
b = false;
|
a328aff0d743c32205c9801d795423288fa9fda178b2a6d071cdfe9461695f4d | MATLAB | 117 | 4 | function [y, x_norm] = normoverdim(x, dim)
x_norm = sqrt(sum(abs(x).^2,dim));
y = bsxfun(@rdivide, x, x_norm);
|
343d436f6afd3410b09a112f16f9d0fe258c3790b4148ea345f7261f1fd16e93 | MATLAB | 120 | 8 | function plot_tajectory(x,y)
f = figure();
hold on
title('video-tracking result')
axis equal
axis off
plot(x,y,'k');
end |
ec94e0499b6287f8a70a18e65e2f4de0eeec2b29ddb03ef7ca61352da0e66016 | MATLAB | 121 | 5 | function convertMeasListOrder2dotNirs()
DeleteDataFiles(pwd, 'nirs')
Snirf2Nirs
DeleteDataFiles(pwd, 'snirf')
Nirs2Snirf
|
574ef92f02ec565641d42c3343a578eff172e2358fd61559d94e966f0e674f6e | MATLAB | 122 | 11 | cd("scripts")
opt_make
Event_alignPair
Data_Preprocessing
Data_ICAcomputation
Data_ICArejection
bbci_CalcERP
cd('..')
|
85eafa7d3248c089f2d76b908f8dcb2a8c7aa8fd9301d77814172ab4efd8f115 | MATLAB | 122 | 10 |
inferQnu;
XmState_old = XmState;
Ybar_old = Ybar;
inferAR3;
inferQX;
inferQL;
inferpsii2;
infermcl;
computeLogOutProbs;
|
966b15f0055b2e096de110cff9c30d526739914d04d3a9b1f011c8b81b3748c5 | MATLAB | 122 | 4 | function save_step2(s,step2)
step1 = s ;
save([s.figure.folder filesep s.figure.prefix '_step2.mat'],'step1','step2');
end |
466327255bd74c241a047fd7f5a64f36f52f30eb3d52e1dd39031d0e498dda34 | MATLAB | 124 | 5 | function tIncCh = tIncCh_Initialize(tIncCh, d, ml)
if isempty(tIncCh)
tIncCh = [ones(size(d,1), size(ml,1)); ml'];
end
|
338b3bdec322b62c4f2330959c678729ad77e0ff9e80349e0a24e5487972579e | MATLAB | 125 | 3 | %This script runs runHistPreprocess_base with manual alignment
runAutomatic = false;
runHistPreprocess_base(runAutomatic); |
acf54b0c9451ee031860e2ed63b18fe1ac184fb2610862daa1d19d031f975981 | MATLAB | 126 | 6 | function VB = set_ARhyperpriors(data)
M = size(data{1},1);
VB.ao = 10^-3; VB.bo = 10^-3;
VB.no = M + 2;
VB.Wo = 10^3*eye(M);
|
c36b91bd100a49e8c816f0bdb130678a708f217053beea558e913b436e959f38 | MATLAB | 126 | 14 | function L = HarrisLogLhood(s,Q)
sa = s*w;
n = Q(:,cellIx);
end
function y = g(x)
if x<0
y = exp(x);
else
y = x+1;
end |
0413a8691117b349ea17536b113a0dfb38971e06c01e23056b0945e690b937e5 | MATLAB | 128 | 3 | version https://git-lfs.github.com/spec/v1
oid sha256:8c094435a518cdd201f1e336352e2b94af006c6991b0ab033e5c53356e98039d
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1780ffb36e00c419da8274c5bb266d74da660514195c12d0107a38490e747421 | MATLAB | 128 | 3 | version https://git-lfs.github.com/spec/v1
oid sha256:f97ea75ea7708ae523ec459b0051405c75e15587e845a433eb9970ad6fcb216c
size 401
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291ce404c339e2bcd8073dc4a1660893758cc03070165bd4dd50642927188ec7 | MATLAB | 128 | 3 | version https://git-lfs.github.com/spec/v1
oid sha256:d4c49831ef06df42c109148116b25fc5fc80942fbf557349ca59f3500c68ddad
size 437
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2adf781cf8ca2405b0b59a66d0e81497eee1aa9c7dc68c65353976e298859f25 | MATLAB | 128 | 3 | version https://git-lfs.github.com/spec/v1
oid sha256:78d93455fdfbcac9dae45e7e0cc82deca6f8d5962e050197e9b85e80923a3f65
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30d786503dc88b3572782af9339bf2f0a1a544245601cbae68765eafad0ead73 | MATLAB | 128 | 3 | version https://git-lfs.github.com/spec/v1
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4d68fa10765edfff3d7a1699c1ea05eb2705a579061f85929a92ffc10e38eac2 | MATLAB | 128 | 3 | version https://git-lfs.github.com/spec/v1
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4e7b2e7bf36b048a7ed1e53e19c399fc8566d9ac4126787c9efd23c48927946c | MATLAB | 128 | 3 | version https://git-lfs.github.com/spec/v1
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8073e6ec89e38654160c5cd917480a25106ad5e87c237440d965d7906a0d1e78 | MATLAB | 128 | 3 | version https://git-lfs.github.com/spec/v1
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84091deac0a6398cec6471414d5dbdd6a70a562318bc721bb3ec1f00b2068e28 | MATLAB | 128 | 3 | version https://git-lfs.github.com/spec/v1
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8b701e296daeb92d59644ff4dea660f25d59888b7c07ee340ad2e2fb0ffdf506 | MATLAB | 128 | 3 | version https://git-lfs.github.com/spec/v1
oid sha256:1e24f86e4a258e3655b97fb1a1943f62e83bf042b8fb00f1e86a884f8396f6ca
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|
a14222eaabb1955a2e1fe3dd9cdeda2bed000b3b539300169c0a6222b6199e3c | MATLAB | 128 | 3 | version https://git-lfs.github.com/spec/v1
oid sha256:080fb2015c2810389c291ed8ab35010cfe9981eda87e0c103509fe77dd038239
size 421
|
a59c51bb98b3047b2db6aa1f6014def71ddac52eebb03d2753d0b5ff079f9bb8 | MATLAB | 128 | 3 | version https://git-lfs.github.com/spec/v1
oid sha256:5dd1de8727f740bc0b414403b3fbd92a6986b2bd726c704abe327602f86df76e
size 435
|
b3c4561dece26b1c8fac9951428b09bbaa12ff0695c4e1e921557ea44ff02f11 | MATLAB | 128 | 3 | version https://git-lfs.github.com/spec/v1
oid sha256:71aabbc63bc46c2cb16c720193bb30b6a6b3ee113033f672c0c7f0414ca722e3
size 433
|
b48ac776f674032c81da10a5096e427a447ae9dedca4aaa1c4f1f75d8070caee | MATLAB | 128 | 3 | version https://git-lfs.github.com/spec/v1
oid sha256:ecf2e5843e222cdb77a9ac289c71719ddd260e39f2dd6f7d37727122dbc1ac49
size 429
|
b861018cdad2218d269d2efed603195a81d7870c35424dde0024186f8dab1506 | MATLAB | 128 | 3 | version https://git-lfs.github.com/spec/v1
oid sha256:4b2261a4087873c2716f37d539032072b44325bc97625a8c15b1859091d234a3
size 442
|
c24ea306288721797dd03e32d1ed57f13adde5236c5529c8a213838ba7fd54cb | MATLAB | 128 | 3 | version https://git-lfs.github.com/spec/v1
oid sha256:807a0f42961487b9f0cdea1a29875c3d149551b19aac6d6ab738da0fbc0be39b
size 444
|
cbea39126a2a746b0c87c66a8d48a1ad22bc83c31a5b291d9e67ff3bc5dd6442 | MATLAB | 128 | 3 | version https://git-lfs.github.com/spec/v1
oid sha256:8dc9ce94b710649394c3bd39cd91e92bf4199fb455f398d5ee668c69c487441e
size 434
|
d7251faf2768a37078735ccebf153f4534c22d1a8fb6b38749b447de345700b1 | MATLAB | 128 | 3 | version https://git-lfs.github.com/spec/v1
oid sha256:62ee6a5313c4065050b2905f01b1a1ec5a96077b2e870b8e8ebae345c4c70f0d
size 449
|
dcab7607b285415f60b6bebe76becf9c5db474496c6c1fff61341ceba49fb0d5 | MATLAB | 128 | 3 | version https://git-lfs.github.com/spec/v1
oid sha256:e3696ebdb6ef0f7d7505a569552e4207874b98accd991761471120bba80e58b2
size 437
|
e275a429186908a520d389b70afa1e012004717017a23f1c85d8caeba083907c | MATLAB | 128 | 3 | version https://git-lfs.github.com/spec/v1
oid sha256:54b9615df2c9b3c55d9659d26ebfe524abb43406677f53b47f15e120f385b868
size 425
|
f003c2d93a658432615d0fd0e8d002e9d85c57b6fa89de92be754fafff680b54 | MATLAB | 128 | 3 | version https://git-lfs.github.com/spec/v1
oid sha256:3c88d9a1e2f4c4ddcbc61ff4edb313049fd8421f30b3391bea09a4c32c6f04dc
size 438
|
f5070574c8fefc931e155e53fea7e5d9ab5fc838472f0f14d16428f5e67cce20 | MATLAB | 128 | 3 | version https://git-lfs.github.com/spec/v1
oid sha256:02db801dbea4b6556da3278de8a1a6cd8eac31aff5541b10fa01a914bb198f68
size 448
|
72165c94d198979bd0826445dc55375d2ad731c00ab342421201b4813fbb422f | MATLAB | 129 | 5 | % dg/dk
function dgdk = VMMix_dg_dk(x, mu, k)
g = VMMix_g(x, mu, k);
dgdk = (cos(x - mu) - (besseli(1, k)/besseli(0, k))).*g;
end |
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