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value | path stringlengths 12 229 | size int64 23 843k | source_encoding stringclasses 9
values | md5 stringlengths 32 32 | text stringlengths 23 843k |
|---|---|---|---|---|---|---|---|---|
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | exp_mv2df.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/vector/exp_mv2df.m | 659 | utf_8 | 410b48565ed23cbda996866e44dfb2fa | function [y,deriv] = exp_mv2df(w)
% This is an MV2DF. See MV2DF_API_DEFINITION.readme.
% y = exp(w), vectorized as MATLAB usually does.
if nargin==0
test_this();
return;
end
if isempty(w)
y = @(w)exp_mv2df(w);
return;
end
if isa(w,'function_handle')
outer = exp_mv2df([]);
y = compose_mv(oute... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | vectorized_function.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/vector/templates/vectorized_function.m | 4,600 | utf_8 | 9c5431b821aa6587c3849945d31dd1fd | function [y,deriv] = vectorized_function(w,f,m,direction)
% This is an MV2DF. See MV2DF_API_DEFINITION.readme.
%
% This template vectorizes the given function F: R^m -> R as follows:
% k = length(w)/m;
% If direction=1, X = reshape(w,m,k), y(j) = F(X(:,j)), or
% if direction=2, X = reshape(w,k,m), y(i) = F(X(i,:)... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | logdet_chol.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/scalar/logdet_chol.m | 1,185 | utf_8 | 706e5c1e5b5b660da50408bd221522a0 | function [y,deriv] = logdet_chol(w)
% This is an MV2DF. See MV2DF_API_DEFINITION.readme.
% y = log(det(W)), where W is positive definite and W = reshape(w,...)
if nargin==0
test_this();
return;
end
if isempty(w)
y = @(w)logdet_chol(w);
return;
end
if isa(w,'function_handle')
outer = logdet_chol(... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | sumsquares_penalty.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/scalar/sumsquares_penalty.m | 916 | utf_8 | 8f40fb9f94c7424808c89e165ec9960c | function [y,deriv] = sumsquares_penalty(w,lambda)
% This is an MV2DF. See MV2DF_API_DEFINITION.readme.
% See code for details.
if nargin==0
test_this();
return;
end
if isempty(w)
y = @(w)sumsquares_penalty(w,lambda);
return;
end
if isa(w,'function_handle')
outer = sumsquares_penalty([],lambda);
... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | wmlr_obj.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/scalar/wmlr_obj.m | 2,299 | utf_8 | f450d5fdd89f4854a123b7d7947d32c3 | function [y,deriv] = wmlr_obj(w,X,T,weights,logprior);
% This is a SCAL2DF. See SCAL2DF_API_DEFINITION.readme.
% Weighted multiclass linear logistic regression objective function.
% w is vectorized D-by-K parameter matrix W (to be optimized)
% X is D-by-N data matrix, for N trials
% T is K-by-N, 0/1 class label m... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | boost_obj.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/scalar/boost_obj.m | 1,556 | utf_8 | eaa722fa0cd7b1b492401c4e6adf807b | function [y,deriv] = boost_obj(w,T,weights,logit_prior)
% This is an MV2DF. See MV2DF_API_DEFINITION.readme.
%
% Weighted binary classifier cross-entropy objective, based on 'boosting'
% proper scoring rule. This rule places more emphasis on extreme scores,
% than the logariothmic scoring rule.
%
% Differentiable inpu... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | neg_gaussll_taylor.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/scalar/neg_gaussll_taylor.m | 1,402 | utf_8 | 28e3df82a7d8fed32f5878df634b0760 | function [y,deriv] = neg_gaussll_taylor(w,x)
% This is an MV2DF. See MV2DF_API_DEFINITION.readme.
% This function represents the part of log N(x|0,W) that is dependent on
% W = reshape(w,...), where w is variable and x is given.
%
% y = -0.5*x'*inv(W)*x - 0.5*log(det(W)), where W is positive definite and W = r... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | brier_obj.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/scalar/brier_obj.m | 1,722 | utf_8 | f68fae1776aa1a970b6f329e4c0d1027 | function [y,deriv] = brier_obj(w,T,weights,logit_prior)
% This is an MV2DF. See MV2DF_API_DEFINITION.readme.
%
% Weighted binary classifier cross-entropy objective, based on 'Brier'
% quadratic proper scoring rule. This rule places less emphasis on extreme scores,
% than the logariothmic scoring rule.
%
% Differentiab... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | gauss_ll.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/scalar/gauss_ll.m | 1,532 | utf_8 | b63a817e4a950a1f3580024f362d6d07 | function [y,deriv] = gauss_ll(w,x)
% This is an MV2DF. See MV2DF_API_DEFINITION.readme.
% This function represents the part of log N(x|0,W) that is dependent on
% W = reshape(w,...), where w is variable and x is given.
%
% y = -0.5*x'*inv(W)*x - 0.5*log(det(W)), where W is positive definite and W = reshape(w,.... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | cllr_obj.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/scalar/cllr_obj.m | 1,611 | utf_8 | 374952d66aa4641a000a48cc12baebad | function [y,deriv] = cllr_obj(w,T,weights,logit_prior)
% This is an MV2DF. See MV2DF_API_DEFINITION.readme.
%
% Weighted binary classifier cross-entropy objective, based on logarithmic
% cost function.
%
% Differentiable inputs:
% w: is vector of N detection scores (in log-likelihood-ratio format)
%
% Fixed parame... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | mce_obj.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/scalar/mce_obj.m | 1,711 | utf_8 | 93cfa59b8a57d279ebbdb02376bd696c | function [y,deriv] = mce_obj(w,T,weights,logprior)
% This is an MV2DF. See MV2DF_API_DEFINITION.readme.
%
% Weighted multiclass cross-entropy objective.
% w is vectorized K-by-N score matrix W (to be optimized)
% T is K-by-N, 0/1 class label matrix, with exactly one 1 per column.
% weights is N-vector of objectiv... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | sum_ai_f_of_w_i.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/scalar/templates/sum_ai_f_of_w_i.m | 1,367 | utf_8 | af9137c86c4b6c7456dbd1688c9ba0bb | function [y,deriv] = sum_ai_f_of_w_i(w,a,f,b)
% This is an MV2DF. See MV2DF_API_DEFINITION.readme.
%
% Does y = sum_i a_i f(w_i) + b, where f is non-linear.
%
%Notes:
%
% f is a function handle, with behaviour as demonstrated in the test code
% of this function.
%
% b is optional, defaults to 0 if omitted
if nargi... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | KtimesW.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/linear/KtimesW.m | 778 | utf_8 | aed1b177e8e14e8b52861e48d6fb6fa3 | function [y,deriv] = KtimesW(w,K)
% This is an MV2DF . See MV2DF_API_DEFINITION.readme.
%
%
%
if nargin==0
test_this();
return;
end
if isempty(w)
map = @(w) map_this(w,K);
transmap = @(y) transmap_this(y,K);
y = linTrans(w,map,transmap);
return;
end
if isa(w,'funct... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | scaleRows.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/linear/scaleRows.m | 798 | utf_8 | c848225d200f35d733b8bb76c2495127 | function [y,deriv] = scaleRows(w,scales)
% This is an MV2DF. See MV2DF_API_DEFINITION.readme.
%
% w --> bsxfun(@times,reshape(w,m,[]),scales(:))
%
% where m = length(scales);
%
% Note: this is a symmetric linear transform.
if nargin==0
test_this();
return;
end
if isempty(w)
map = @(w)map_this(w,scale... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | sumcolumns_fh.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/linear/sumcolumns_fh.m | 602 | utf_8 | 7a2cd01c3b7076cda20fa6a96cae0069 | function fh = sumcolumns_fh(m,w)
% This is almost an MV2DF, but it does not return derivatives on numeric
% input, w.
%
% w -> W = reshape(w,m,[]) -> sum(W,1)'
if nargin==0
test_this();
return;
end
map = @(w) map_this(w,m);
transmap = @(y) transmap_this(y,m);
fh = linTrans([],map,transmap);
if exist('w'... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | columnJofN_fh.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/linear/columnJofN_fh.m | 634 | utf_8 | 23448c0cc436ac53b95d5e4ec48c7b35 | function fh = columnJofN_fh(j,n,w)
% This is almost an MV2DF, but it does not return derivatives on numeric
% input, w.
%
% w -> W = reshape(w,[],n) -> W(:,j)
if nargin==0
test_this();
return;
end
map = @(w) map_this(w,j,n);
transmap = @(y) transmap_this(y,j,n);
fh = linTrans([],map,transmap);
if exist(... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | scaleColumns.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/linear/scaleColumns.m | 811 | utf_8 | cacb0b80cb3f3871595674e741382d26 | function [y,deriv] = scaleColumns(w,scales)
% This is an MV2DF. See MV2DF_API_DEFINITION.readme.
%
% w --> bsxfun(@times,reshape(w,[],n),scales(:)')
%
% where n = length(scales);
%
% Note: this is a symmetric linear transform.
if nargin==0
test_this();
return;
end
if isempty(w)
map = @(w)map_this(w,s... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | subvec.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/linear/subvec.m | 733 | utf_8 | ed189df10ecad63eca1130710c559631 | function [y,deriv] = subvec(w,size,first,length)
% This is an MV2DF . See MV2DF_API_DEFINITION.readme.
%
% w --> w(first:first+length-1)
%
if nargin==0
test_this();
return;
end
last = first+length-1;
if isempty(w)
map = @(w) w(first:last);
transmap = @(w) transmap_this(w,size,first,last);
y... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | identity_trans.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/linear/identity_trans.m | 495 | utf_8 | aec19df7ff1e1fa5079b22973d9122fc | function [y,deriv] = identity_trans(w)
% This is an MV2DF . See MV2DF_API_DEFINITION.readme.
%
% w --> w
%
if nargin==0
test_this();
return;
end
if isempty(w)
map = @(w) w;
y = linTrans(w,map,map);
return;
end
if isa(w,'function_handle')
f = identity_trans([]);
y = compose_mv(f,w,[])... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | WtimesK.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/linear/WtimesK.m | 778 | utf_8 | 535204cc831c21ab905f5c3d933c7501 | function [y,deriv] = WtimesK(w,K)
% This is an MV2DF . See MV2DF_API_DEFINITION.readme.
%
%
%
if nargin==0
test_this();
return;
end
if isempty(w)
map = @(w) map_this(w,K);
transmap = @(y) transmap_this(y,K);
y = linTrans(w,map,transmap);
return;
end
if isa(w,'funct... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | transpose_mv2df.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/linear/transpose_mv2df.m | 700 | utf_8 | 58016f72134e4ccf6256f2ea1f952a43 | function [y,deriv] = transpose_mv2df(w,M,N)
% This is an MV2DF . See MV2DF_API_DEFINITION.readme.
%
% vec(A) --> vec(A'),
%
% where A is M by N
%
% Note: this is an orthogonal linear transform.
if nargin==0
test_this();
return;
end
if isempty(w)
map = @(w) reshape(reshape(w,M,N).',[],1);
transmap... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | fusion_mv2df.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/linear/fusion_mv2df.m | 1,182 | utf_8 | df0b186cde5dcc42aea6490f13d6d479 | function [y,deriv] = fusion_mv2df(w,scores)
% This is an MV2DF. See MV2DF_API_DEFINITION.readme.
%
% The function is a 'score fusion' computed thus:
% y.' = w(1:end-1).'*scores + w(end)
%
% Here w is the vector of fusion weights, one weight per system and
% an offset.
%
% Parameters:
% scores: is... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | addSigmaI.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/linear/addSigmaI.m | 824 | utf_8 | 64919abf02bcf0fb402652f121f6dd95 | function [y,deriv] = addSigmaI(w)
% This is an MV2DF . See MV2DF_API_DEFINITION.readme.
%
%
%
if nargin==0
test_this();
return;
end
if isempty(w)
map = @(w) map_this(w);
transmap = @(w) transmap_this(w);
y = linTrans(w,map,transmap);
return;
end
if isa(w,'function_... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | addOffset.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/linear/addOffset.m | 1,057 | utf_8 | 38390e8a3f92c5a6b760571e3ba340e3 | function [y,deriv] = addOffset(w,K,N)
% This is an MV2DF. See MV2DF_API_DEFINITION.readme.
%
% w = [vec(A);b] --> vec(bsxfun(@plus,A,b))
%
% This function retrieves a K by N matrix as well as a K-vector from w,
% adds the K-vector to every column of the matrix
% and outputs the vectorized result.
% Note this... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | const_mv2df.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/linear/templates/const_mv2df.m | 856 | utf_8 | 541e86c2041370727a8705935c4d575e | function [y,deriv] = const_mv2df(w,const)
% This is an MV2DF. See MV2DF_API_DEFINITION.readme.
%
% y = const(:);
%
% This wraps the given constant into an MV2DF. The output, y, is
% independent of input w. The derivatives are sparse zero vectors of the
% appropriate size.
if nargin==0
test_this();
return;
... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | linTrans.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/linear/templates/linTrans.m | 1,012 | utf_8 | 5c26cd329441fa971c05127c464dfae5 | function [y,deriv] = linTrans(w,map,transmap)
% This is an MV2DF. See MV2DF_API_DEFINITION.readme.
%
% Applies linear transform y = map(w). It needs the transpose of map,
% transmap for computing the gradient. map and transmap are function
% handles.
if nargin==0
test_this();
return;
end
if isempty(w)
y ... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | affineTrans.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/linear/templates/affineTrans.m | 1,378 | utf_8 | f1c4abd92c1dca63db5b0ccf3915a631 | function [y,deriv] = affineTrans(w,affineMap,linMap,transMap)
% This is an MV2DF. See MV2DF_API_DEFINITION.readme.
%
% Applies affine transform y = affineMap(w). It needs also needs
% linMap, the linear part of the mapping, as well as transMap, the
% transpose of linMap. All of affineMap, linMap and transMap are funct... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | logsoftmax_trunc_mv2df.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/multivariate/logsoftmax_trunc_mv2df.m | 1,380 | utf_8 | 7933852f24348cedbc4c8750142e51de | function [y,deriv] = logsoftmax_trunc_mv2df(w,m)
% This is a MV2DF. See MV2DF_API_DEFINITION.readme.
%
% Does:
% (i) Reshapes w to m-by-n.
% (ii) effectively (not physically) append a bottom row of zeros
% (iii) Computes logsoftmax of each of n columns.
% (iv) Omits last row (effectively)
if nargin==0
test_this... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | mm_special.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/multivariate/mm_special.m | 1,465 | utf_8 | 735b9c605bad33588197fcc0c0d59eb5 | function [prod,deriv] = mm_special(w,extractA,extractB)
% This is an MV2DF. See MV2DF_API_DEFINITION.readme.
%
% [vec(A);vec(B)] --> vec(A*B)
%
% where
% A is extractA(w)
% B is extractB(w)
if nargin==0
test_this();
return;
end
if isempty(w)
prod = @(w)mm_special(w,extractA,extractB);
return;... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | sums_of_squares.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/multivariate/sums_of_squares.m | 898 | utf_8 | 1fa8d45eea9355807d8ef47606407b36 | function [y,deriv] = sums_of_squares(w,m)
% This is a MV2DF. See MV2DF_API_DEFINITION.readme.
% Does:
% (i) Reshapes w to m-by-n.
% (ii) Computes sum of squares of each of n columns.
% (iii) Transposes to output n-vector.
if nargin==0
test_this();
return;
end
if isempty(w)
y = @(w)sums_of_squares(w,m)... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | gemm.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/multivariate/gemm.m | 1,283 | utf_8 | b9245303ab8248f450ad033cde69bf29 | function [prod,deriv] = gemm(w,m,k,n)
% This is an MV2DF. See MV2DF_API_DEFINITION.readme.
%
% [vec(A);vec(B)] --> vec(A*B)
%
% where
% A is m-by-k
% B is k-by-n
if nargin==0
test_this();
return;
end
if isempty(w)
prod = @(w)gemm(w,m,k,n);
return;
end
if isa(w,'function_handle')
outer =... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | XtKX.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/multivariate/XtKX.m | 849 | utf_8 | 0298041dbd9ce1171c7cf66e0edb8a09 | function [y,deriv] = XtKX(w,K)
%This is an MV2DF.
%
% vec(X) --> vec(X'KX)
%
if nargin==0
test_this();
return;
end
m = size(K,1);
if isempty(w)
y = @(w) XtKX(w,K);
return;
end
if isa(w,'function_handle')
outer = XtKX([],K);
y = compose_mv(outer,w,[]);
return;
end
X = reshape(w,m,[]);... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | UtU.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/multivariate/UtU.m | 945 | utf_8 | 086256cb24f7c7b69d69614ceff1519b | function [prod,deriv] = UtU(w,m,n)
% This is a MV2DF. See MV2DF_API_DEFINITION.readme.
% U = reshape(w,m,n), M = U'*U, prod = M(:).
if nargin==0
test_this();
return;
end
if isempty(w)
prod = @(w)UtU(w,m,n);
return;
end
if isa(w,'function_handle')
outer = UtU([],m,n);
prod = compose_mv(outer... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | bsxtimes.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/multivariate/bsxtimes.m | 1,144 | utf_8 | 599b65f85120f5dec9d1a62d06393c35 | function [y,deriv] = bsxtimes(w,m,n)
% This is an MV2DF
%
% w = [vec(A); vec(b) ] --> vec(bsxfun(@times,A,b)),
%
% where A is an m-by-n matrix and
% b is a 1-by-n row.
%
if nargin==0
test_this();
return;
end
if isempty(w)
y = @(w) bsxtimes(w,m,n);
return;
end
if isa(w,'function_... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | calibrateScores.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/multivariate/calibrateScores.m | 1,095 | utf_8 | 36a554ff63a06324896dbea86ca33308 | function [y,deriv] = calibrateScores(w,m,n)
% This is an MV2DF. See MV2DF_API_DEFINITION.readme.
%
% [vec(A);scal;offs] --> vec(bsxfun(@plus,scal*A,b))
%
% This function retrieves from w:
% (i) an m-by-n matrix, 'scores'
% (ii) a scalar 'scal', and
% (iii) an m-vector, 'offset'
%
% Then it scales ... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | solve_AXeqB.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/multivariate/solve_AXeqB.m | 1,054 | utf_8 | cff7830e92caa23fabdd038a4e53750d | function [y,deriv] = solve_AXeqB(w,m)
% This is an MV2DF.
%
% [A(:);B(:)] --> inv(A) * B
%
if nargin==0
test_this();
return;
end
if isempty(w)
y = @(w)solve_AXeqB(w,m);
return;
end
if isa(w,'function_handle')
outer = solve_AXeqB([],m);
y = compose_mv(outer,w,[]);
return;
end
[A,B... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | logsoftmax_mv2df.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/multivariate/logsoftmax_mv2df.m | 1,248 | utf_8 | 1c29a9da21772e72c800bb7be4025fe6 | function [y,deriv] = logsoftmax_mv2df(w,m)
% This is a MV2DF. See MV2DF_API_DEFINITION.readme.
%
% Does:
% (i) Reshapes w to m-by-n.
% (ii) Computes logsoftmax of each of n columns.
if nargin==0
test_this();
return;
end
if isempty(w)
y = @(w)logsoftmax_mv2df(w,m);
return;
end
if isa(w,'function_h... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | sqdist.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/multivariate/sqdist.m | 1,235 | utf_8 | b5b2962cbdd97ba90d9fc21255464dc8 | function [y,deriv] = sqdist(w,dim)
% This is an MV2DF. See MV2DF_API_DEFINITION.readme.
%
% If W = reshape(w,dim,n), then Y = vec of symmetric n-by-n matrix of
% 1/2 squared euclidian distances between all columns of W.
if nargin==0
test_this();
return;
end
if isempty(w)
y = @(w)sqdist(w,... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | dottimes.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/multivariate/dottimes.m | 884 | utf_8 | 7e8e3dedc670c1f93364db61f3d2b41d | function [y,deriv] = dottimes(w)
% This is an MV2DF
%
% [a; b ] --> a.*b
%
% where length(a) == length(b)
%
if nargin==0
test_this();
return;
end
if isempty(w)
y = @(w) dottimes(w);
return;
end
if isa(w,'function_handle')
f = dottimes([]);
y = compose_mv(f,w,[]);
return;
end
... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | solveChol_AXeqB.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/multivariate/solveChol_AXeqB.m | 1,391 | utf_8 | f2ded36f846a5e9904fd8299ba4a5ed1 | function [y,deriv] = solveChol_AXeqB(w,m)
% This is an MV2DF.
%
% [A(:);B(:)] --> inv(A) * B
%
% We assume A is positive definite and we solve using Choleski
if nargin==0
test_this();
return;
end
if isempty(w)
y = @(w)solveChol_AXeqB(w,m);
return;
end
if isa(w,'function_handle')
outer = solve... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | test_MV2DF.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/test/test_MV2DF.m | 2,104 | utf_8 | 1f7eea1823322c4c0741c86792fc73c4 | function test_MV2DF(f,x0,do_cstep)
%id_in = identity_trans([]);
%id_out = identity_trans([]);
%f = f(id_in);
%f = id_out(f);
x0 = x0(:);
if ~exist('do_cstep','var')
do_cstep = 1;
end
if do_cstep
Jc = cstepJacobian(f,x0);
end
Jr = rstepJacobian(f,x0);
[y0,deriv] = f(x0);
m = length(y0);
n = length(x0);
J2 ... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | tracer.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/test/tracer.m | 1,081 | utf_8 | 5e8d7ea9aefc9d1c1cc8161546bd9483 | function [w,deriv] = tracer(w,vstring,gstring,jstring)
% This is an MV2DF. See MV2DF_API_DEFINITION.readme.
%
% Applies linear transform y = map(w). It needs the transpose of map,
% transmap for computing the gradient. map and transmap are function
% handles.
if nargin==0
test_this();
return;
end
if nargin<2... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | test_MV2DF_noHess.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_library/test/test_MV2DF_noHess.m | 1,183 | utf_8 | 17fa2b2d5e45675e9b014cd995337fb0 | function test_MV2DF_noHess(f,x0)
%id_in = identity_trans([]);
%id_out = identity_trans([]);
%f = f(id_in);
%f = id_out(f);
x0 = x0(:);
Jc = cstepJacobian(f,x0);
Jr = rstepJacobian(f,x0);
[y0,deriv] = f(x0);
m = length(y0);
n = length(x0);
J2 = zeros(size(Jr));
for i=1:m;
y = zeros(m,1);
... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | inv_lu2.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/utils/inv_lu2.m | 1,091 | utf_8 | e31e7aae6bc92b7b147e7afcc12707ee | function [inv_map,bi_inv_map,logdet,invA] = inv_lu2(A)
% INV_LU2
% Does a LU decomposition on A and returns logdet, inverse and
% two function handles that respectively map X to A\X and A\X/A.
%
if nargin==0
test_this();
return;
end
[L,T,p] = lu(A,'vector');
P = sparse(p,1:length(p),1);
... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | invchol2.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/utils/invchol2.m | 968 | utf_8 | 936256e3c3a28ed65ad0c15d9fbb04cd | function [inv_map,bi_inv_map,logdet,invA] = invchol2(A)
% INVCHOL2
% Does a Cholesky decomposition on A and returns logdet, inverse and
% two function handles that respectively map X to A\X and A\X/A.
%
if nargin==0
test_this();
return;
end
if isreal(A)
R = chol(A); %R'*R = A
inv_map = @(X) R\(R'\X);... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | invchol_or_lu.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/utils/invchol_or_lu.m | 1,482 | utf_8 | fcbd42d472280dcbdf4a0c207e95a1e2 | function [inv_map,bi_inv_map,logdet,invA] = invchol_or_lu(A)
% INVCHOL_OR_LU
% Does a Cholesky decomposition on A and returns logdet, inverse and
% two function handles that respectively map X to A\X and A\X/A.
%
if nargin==0
test_this();
return;
end
if isreal(A)
R = chol(A); %R'*R = A
... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | invchol_taylor.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/utils/invchol_taylor.m | 1,304 | utf_8 | d90675998987dc9d1432da41ceb87c54 | function [inv_map,logdet] = invchol_taylor(A)
% Does a Cholesky decomposition on A and returns:
% inv_map: a function handle to solve for X in AX = B
% logdet (of A)
%
% This code is designed to work correctly if A has a small complex
% perturbation, such as used in complex step differentiation, even though
... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | train_system.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/discrim_training/train_system.m | 4,969 | utf_8 | 69b1726b853595599d4a79414b256c8b | function [w,mce,divergence,w_pen,c_pen,optimizerState,converged] = train_system(classf,system,penalizer,W0,lambda,confusion,maxiters,maxCG,prior,optimizerState)
%
% Supervised training of a regularized K-class linear logistic
% regression. Allows regularization via weight penalties and via
% label confusion prob... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | sum_of_functions.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_combination/sum_of_functions.m | 1,094 | utf_8 | af1885792c3ce587c098ffc61a10cc06 | function [y,deriv] = sum_of_functions(w,weights,f,g)
% This is an MV2DF (see MV2DF_API_DEFINITION.readme) which
% represents the new function, s(w), obtained by summing the
% weighted outputs of the given functions:
% s(w) = sum_i weights(i)*functions{i}(w)
%
% Usage examples:
%
% s = @(w) sum_of_functions(w,[1,... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | scale_function.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_combination/scale_function.m | 856 | utf_8 | fae26a24cbea0fcc7ae35cf1642b18e4 | function [y,deriv] = scale_function(w,scale,f)
% This is an MV2DF (see MV2DF_API_DEFINITION.readme) which
% represents the new function,
%
% g(w) = scale(w)*f(w),
%
% where scale is scalar-valued and f is matrix-valued.
%
%
% Here scale and f are function handles to MV2DF's.
if nargin==0
test_this();
r... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | outerprod_of_functions.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_combination/outerprod_of_functions.m | 1,085 | utf_8 | 731782f761b675bb6d3567ddb560c950 | function [y,deriv] = outerprod_of_functions(w,f,g,m,n)
% This is an MV2DF (see MV2DF_API_DEFINITION.readme) which
% represents the new function,
%
% g(w) = f(w)g(w)'
%
% where f(w) and g(w) are column vectors of sizes m and n respectively.
%
% Here f,g are function handles to MV2DF's.
if nargin==0
test_thi... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | interleave.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_combination/interleave.m | 2,028 | utf_8 | 0cdd5849311559d9813888914f7530cd | function [y,deriv] = interleave(w,functions)
% interleave is an MV2DF (see MV2DF_API_DEFINITION.readme) which
% represents the new function, s(w), obtained by interleaving the outputs of
% f() and g() thus:
%
% S(w) = [f(w)';g(w)'];
% s(w) = S(:);
if nargin==0
test_this();
return;
end
if isempty(w)... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | shift_function.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_combination/shift_function.m | 954 | utf_8 | d8152bd043265ba68a3de573d28ccf30 | function [y,deriv] = shift_function(w,shift,f)
% This is an MV2DF (see MV2DF_API_DEFINITION.readme) which
% represents the new function,
%
% g(w) = shift(w)+f(w),
%
% where shift is scalar-valued and f is matrix-valued.
%
%
% Here shift and f are function handles to MV2DF's.
if nargin==0
test_... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | dotprod_of_functions.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_combination/dotprod_of_functions.m | 952 | utf_8 | 2999899143500736ecbc06d5afc09df0 | function [y,deriv] = dotprod_of_functions(w,f,g)
% This is an MV2DF (see MV2DF_API_DEFINITION.readme) which
% represents the new function,
%
% g(w) = f(w)'g(w)
%
% where f(w) and g(w) are column vectors of the same size.
%
% Here f,g are function handles to MV2DF's.
if nargin==0
test_this();
return;
en... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | dottimes_of_functions.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_combination/dottimes_of_functions.m | 641 | utf_8 | 45195e5dddb789f3431e2f84495b06c7 | function [y,deriv] = dottimes_of_functions(w,A,B)
% This is an MV2DF (see MV2DF_API_DEFINITION.readme)
%
% w --> A(w) .* B(w)
%
% Here A and B are function handles to MV2DF's.
if nargin==0
test_this();
return;
end
if isempty(w)
s = stack(w,A,B);
y = dottimes(s);
return;
end
if isa(w,'fun... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | replace_hessian.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_combination/replace_hessian.m | 1,399 | utf_8 | 1e948d50795df5102876278fd5022da8 | function [y,deriv] = replace_hessian(w,f,cstep)
% This is an MV2DF. See MV2DF_API_DEFINITION.readme.
%
if nargin==0
test_this();
return;
end
if isempty(w)
y = @(w)replace_hessian(w,f,cstep);
return;
end
if isa(w,'function_handle')
outer = replace_hessian([],f,cstep);
y = compose_mv(outer,w,[... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | product_of_functions.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_combination/product_of_functions.m | 745 | utf_8 | ae86bc0a8429bacd6044704a6a8a0e06 | function [y,deriv] = product_of_functions(w,A,B,m,k,n)
% This is an MV2DF (see MV2DF_API_DEFINITION.readme)
%
% w --> vec ( reshape(A(w),m,k) * reshape(B(w),k,n) )
%
% Here A and B are function handles to MV2DF's.
if nargin==0
test_this();
return;
end
if isempty(w)
s = stack(w,A,B);
y = gemm(s,... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | stack.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_combination/stack.m | 3,136 | utf_8 | cbfe5ccd3255b5021692c3eb13e1798f | function [y,deriv] = stack(w,f,g,eqlen)
% STACK is an MV2DF (see MV2DF_API_DEFINITION.readme) which
% represents the new function, s(w), obtained by stacking the outputs of
% f() and g() thus:
% s(w) = [f(w);g(w)]
if nargin==0
test_this();
return;
end
if ~exist('eqlen','var')
eqlen = false;
end
if i... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | scale_and_translate.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_combination/scale_and_translate.m | 1,341 | utf_8 | 121b1cd2e23a3d7111f310db8e3b6a05 | function [y,deriv] = scale_and_translate(w,vectors,params,m,n)
% This is an MV2DF (see MV2DF_API_DEFINITION.readme) which
% represents the new function, obtained by scaling and translating the
% column vectors of the output matrix of the function vectors(w). The
% scaling and translation parameters, params(w) is also... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | compose_mv.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/utility_funcs/Optimization_Toolkit/MV2DF/function_combination/compose_mv.m | 2,958 | utf_8 | 108f7eb78b4ff77e907d369fc9ae14db | function [y,deriv] = compose_mv(outer,inner,x)
% COMPOSE_MV is an MV2DF (see MV2DF_API_DEFINITION.readme) which represents
% the combination of two functions. If 'outer' is an MV2DF for a function
% g() and 'inner' for a function f(), then this MV2DF represents g(f(x)).
%feature scopedaccelenablement off
if nargin==0... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | pav_calibration.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/calibration/pav_calibration.m | 2,716 | utf_8 | 2a9298835be5d7757fb4d660a5a2d7b3 | function [pav_trans,score_bounds,llr_bounds] = pav_calibration(tar,non,small_val)
% Creates a calibration transformation function using the PAV algorithm.
% Inputs:
% tar: A vector of target scores.
% non: A vector of non-target scores.
% small_val: An offset to make the transformation function
% invertible. ... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | align_with_ndx.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/classes/@Scores/align_with_ndx.m | 2,628 | utf_8 | 5899b5e5bd43dea8280d84cea8fdf0ec | function aligned_scr = align_with_ndx(scr,ndx)
% The ordering in the output Scores object corresponds to ndx, so
% aligning several Scores objects with the same ndx will result in
% them being comparable with each other.
% Inputs:
% scr: a Scores object
% ndx: a Key or Ndx object
% Outputs:
% aligned_scr: scr res... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | filter.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/classes/@Scores/filter.m | 2,622 | utf_8 | ebaa2297b42e23384ffa07c12bdcc005 | function outscr = filter(inscr,modlist,seglist,keep)
% Removes some of the information in a Scores object. Useful for
% creating a gender specific score set from a pooled gender score
% set. Depending on the value of 'keep', the two input lists
% indicate the models and test segments (and their associated
% scores) t... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | filter.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/classes/@Key/filter.m | 3,047 | utf_8 | 9274e13ab0bf80ca9a90fd6f46da8ff0 | function outkey = filter(inkey,modlist,seglist,keep)
% Removes some of the information in a key. Useful for creating a
% gender specific key from a pooled gender key. Depending on the
% value of 'keep', the two input lists indicate the strings to
% retain or the strings to discard.
% Inputs:
% inkey: A Key object.
... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | read_hdf5.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/classes/@Key/read_hdf5.m | 1,196 | utf_8 | 4057278a996259de22fed6ee29c5d3b2 | function key = read_hdf5(infilename)
% Reads a Key object from an hdf5 file.
% Inputs:
% infilename: The name for the hdf5 file to read.
% Outputs:
% key: A Key object created from the information in the hdf5
% file.
assert(nargin==1)
assert(isa(infilename,'char'))
key = Key();
key.modelset = h5strings_to_ce... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | filter.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/classes/@Ndx/filter.m | 2,788 | utf_8 | 6d39760ecafc786f43259d1adb98a810 | function outndx = filter(inndx,modlist,seglist,keep)
% Removes some of the information in an Ndx. Useful for creating a
% gender specific Ndx from a pooled gender Ndx. Depending on the
% value of 'keep', the two input lists indicate the strings to
% retain or the strings to discard.
% Inputs:
% inndx: An Ndx object... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | read_hdf5.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/classes/@Ndx/read_hdf5.m | 838 | utf_8 | 424ae971c22eb22cf8c27af6130b9698 | function ndx = read_hdf5(infilename)
% Creates an Ndx object from the information in an hdf5 file.
% Inputs:
% infilename: The name of the hdf5 file contain the information
% necessary to construct an Ndx object.
% Outputs:
% ndx: An Ndx object containing the information in the input
% file.
assert(nargin=... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | filter_on_right.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/classes/@Id_Map/filter_on_right.m | 1,885 | utf_8 | deb124220c828ae065475bc93957d53f | function out_idmap = filter_on_right(in_idmap,idlist,keep)
% Removes some of the information in an idmap. Depending on the
% value of 'keep', the idlist indicates the strings to retain or
% the strings to discard.
% Inputs:
% in_idmap: An Id_Map object to be pruned.
% idlist: A cell array of strings which will be ... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | read_hdf5.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/classes/@Id_Map/read_hdf5.m | 777 | utf_8 | 47581f23817e49ffc325aed95a088106 | function idmap = read_hdf5(infilename)
% Creates an Id_Map object from the information in an hdf5 file.
% Inputs:
% infilename: The name of the hdf5 file containing the information
% necessary to construct an Id_Map object.
% Outputs:
% idmap: An Id_Map object containing the information in the input
% file.... |
github | StevenLOL/Research_speech_speaker_verification_nist_sre2010-master | filter_on_left.m | .m | Research_speech_speaker_verification_nist_sre2010-master/SRE2010/utils/bosaris_toolkit/classes/@Id_Map/filter_on_left.m | 1,871 | utf_8 | 27abe0c92b6ff488892e389fee1fb5e9 | function out_idmap = filter_on_left(in_idmap,idlist,keep)
% Removes some of the information in an idmap. Depending on the
% value of 'keep', the idlist indicates the strings to retain or
% the strings to discard.
% Inputs:
% in_idmap: An Id_Map object to be pruned.
% idlist: A cell array of strings which will be c... |
github | sgbasel/neuritetracker-master | neuritetracker_gui.m | .m | neuritetracker-master/trunk/neuritetracker_gui.m | 23,644 | utf_8 | cf2e7dbab4c1ef864011863a7f646b78 | function varargout = neuritetracker_gui(varargin)
% NEURITETRACKER_GUI MATLAB code for neuritetracker_gui.fig
% NEURITETRACKER_GUI, by itself, creates a new NEURITETRACKER_GUI or raises the existing
% singleton*.
%
% H = NEURITETRACKER_GUI returns the handle to a new NEURITETRACKER_GUI or the handle to
%... |
github | sgbasel/neuritetracker-master | renderU.m | .m | neuritetracker-master/trunk/IO/renderU.m | 1,313 | utf_8 | 1aeaf44fcc7a3698e5d4a5bc8e84fb61 | function mv = renderU(U, ImagesBody, parameters)
%GEODESIC_DISTANCE_NEURITE_THRESH = NeuriteDetectionParams.GEODESIC_DISTANCE_NEURITE_THRESH;
ProbThresh = parameters.NeuriteProbabilityThresh;
% figure; imagesc(exp(-U{1}));
%
%
% figure; imagesc( exp(-U{1}) > ProbThresh);
% h1 = figure;
% h... |
github | sgbasel/neuritetracker-master | trkRenderText.m | .m | neuritetracker-master/trunk/IO/trkRenderText.m | 2,875 | utf_8 | cfbb6b65b35096bb4fe5962a7ff5eb77 | %by Davide Di Gloria
%with the great contribution of Franz-Gerold Url
%
%Render RGB text over RGB or grayscale images
%
%out=rendertext(target, text, color, pos, mode1, mode2)
%
%target ... MxNx3 or MxN matrix (grayscale will be converted to RGB)
%text ... string (NO LINE FEED SUPPORT)
%color ... vector in... |
github | sgbasel/neuritetracker-master | smooth.m | .m | neuritetracker-master/trunk/Common/smooth.m | 20,220 | utf_8 | 143fbea2dc52a855b70a898fc2f13cb1 | function [c,ww] = smooth(varargin)
%SMOOTH Smooth data.
% Z = SMOOTH(Y) smooths data Y using a 5-point moving average.
%
% Z = SMOOTH(Y,SPAN) smooths data Y using SPAN as the number of points used
% to compute each element of Z.
%
% Z = SMOOTH(Y,SPAN,METHOD) smooths data Y with specified METHOD. The
% availa... |
github | sgbasel/neuritetracker-master | color_list.m | .m | neuritetracker-master/trunk/Common/color_list.m | 452 | utf_8 | 3cf607f56271aaf55d9eff89e93b716b | %% generate a list of colors for rendering the results
function cols = color_list()
% cols1 = summer(6);
% cols1 = cols1(randperm(6),:);
% cols2 = summer(8);
% cols2 = cols2(randperm(8),:);
% cols3 = summer(180);
% cols3 = cols3(randperm(180),:);
% cols = [cols1; cols2; cols3];
cols1 = jet(6);
cols1 = cols1(randperm(... |
github | sgbasel/neuritetracker-master | trkTreeStructureFromBinaryFilament.m | .m | neuritetracker-master/trunk/NeuritesDetection/trkTreeStructureFromBinaryFilament.m | 2,710 | utf_8 | 3fa0ebeaf1aca370bbc1753ea0d2c45d | function [parents, numkids] = trkTreeStructureFromBinaryFilament(Filaments, Soma, imSize)
% [parents, numkids] = trkTreeStructureFromBinaryFilament(Filaments, Soma)
%
%
% Input: Filaments - list of points that form the tree
% the filament is assumed to be computed using the
% Back... |
github | sgbasel/neuritetracker-master | trkTrackNeurites.m | .m | neuritetracker-master/trunk/NeuritesTracking/trkTrackNeurites.m | 3,811 | utf_8 | 5025cd671168c15d8a01a4e511f45326 | function [TrackedNeurites, TrackedNeuritesList, trkNSeq, timeNSeq] = trkTrackNeurites(Cells, CellsList, timeSeq, parameters)
NEURITE_STABILITY_LENGTH_THRESHOLD = parameters.NeuriteStabLenghtThresh;
W_THRESH = parameters.NeuriteWeightThresh;
MIN_TRACK_LENGTH = parameters.Neu... |
github | sgbasel/neuritetracker-master | struct2xml.m | .m | neuritetracker-master/trunk/temp/Evaluation/GroudTruth/struct2xml.m | 7,457 | utf_8 | 24791efbc3f8e2ee07c5fc9e192b90c9 | function varargout = struct2xml( s, varargin )
%Convert a MATLAB structure into a xml file
% [ ] = struct2xml( s, file )
% xml = struct2xml( s )
%
% A structure containing:
% s.XMLname.Attributes.attrib1 = "Some value";
% s.XMLname.Element.Text = "Some text";
% s.XMLname.DifferentElement{1}.Attributes.attrib2 ... |
github | sgbasel/neuritetracker-master | xml2struct.m | .m | neuritetracker-master/trunk/temp/Evaluation/GroudTruth/xml2struct.m | 7,178 | utf_8 | 84a4dcd204aa6550fc4c66f4861b4316 | function [ s ] = xml2struct( file )
%Convert xml file into a MATLAB structure
% [ s ] = xml2struct( file )
%
% A file containing:
% <XMLname attrib1="Some value">
% <Element>Some text</Element>
% <DifferentElement attrib2="2">Some more text</Element>
% <DifferentElement attrib3="2" attrib4="1">Even more t... |
github | sgbasel/neuritetracker-master | patchline.m | .m | neuritetracker-master/trunk/temp/Evaluation/NeuriteTrackingEvaluation/patchline.m | 3,812 | utf_8 | eb106a55c884f31c460bacfead7472aa | function p = patchline(xs,ys,varargin)
% Plot lines as patches (efficiently)
%
% SYNTAX:
% patchline(xs,ys)
% patchline(xs,ys,zs,...)
% patchline(xs,ys,zs,'PropertyName',propertyvalue,...)
% p = patchline(...)
%
% PROPERTIES:
% Accepts all parameter-values accepted by PATCH.
%
% DESCRI... |
github | sgbasel/neuritetracker-master | annotation_tool_neurite2.m | .m | neuritetracker-master/trunk/temp/Evaluation/NeuriteTrackingEvaluation/annotation_tool_neurite2.m | 22,199 | utf_8 | 25737265fb481561e316a96e6a2f964a | function varargout = annotation_tool_neurite2(varargin)
% ANNOTATION_TOOL MATLAB code for annotation_tool.fig
% ANNOTATION_TOOL, by itself, creates a new ANNOTATION_TOOL or raises the existing
% singleton*.
%
% H = ANNOTATION_TOOL returns the handle to a new ANNOTATION_TOOL or the handle to
% the ex... |
github | sgbasel/neuritetracker-master | print2im.m | .m | neuritetracker-master/trunk/temp/Evaluation/CellBodyDetectionEvaluation/print2im.m | 7,938 | utf_8 | c36ec20620bf599a24eb42336f47939e | %PRINT2IM Prints cropped, anti-aliased figures to image file and/or array
%
% Examples:
% print2im filename
% print2im(..., fig_handle)
% print2im(..., '-alpha')
% A = print2im(...)
% [A alpha] = print2im(...)
%
% This function saves and/or outputs a figure as an image nicely, without
% the need to... |
github | sgbasel/neuritetracker-master | boundingpolygon.m | .m | neuritetracker-master/trunk/temp/Evaluation/CellBodyDetectionEvaluation/boundingpolygon.m | 4,279 | utf_8 | e57adedac554f53b4ab46df836cd8d65 | %BOUNDINGPOLYGON - finds bounding polygons of regions in a binary mask
% image.
%
% [x, y] = boundingpolygon(BWin) finds the bounding polygon for each
% region in the binary mask image BWin and returns the
% corresponding vertex coordinates in arrays x and y.
% If onl... |
github | sgbasel/neuritetracker-master | annotation_tool.m | .m | neuritetracker-master/trunk/temp/Evaluation/CellBodyTrackingEvaluation/annotation_tool.m | 22,614 | utf_8 | 12284ef804aa477a56f8ac2f1df2bf30 | function varargout = annotation_tool(varargin)
% ANNOTATION_TOOL MATLAB code for annotation_tool.fig
% ANNOTATION_TOOL, by itself, creates a new ANNOTATION_TOOL or raises the existing
% singleton*.
%
% H = ANNOTATION_TOOL returns the handle to a new ANNOTATION_TOOL or the handle to
% the existing si... |
github | sgbasel/neuritetracker-master | vl_compile.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/vl_compile.m | 5,060 | utf_8 | 978f5189bb9b2a16db3368891f79aaa6 | function vl_compile(compiler)
% VL_COMPILE Compile VLFeat MEX files
% VL_COMPILE() uses MEX() to compile VLFeat MEX files. This command
% works only under Windows and is used to re-build problematic
% binaries. The preferred method of compiling VLFeat on both UNIX
% and Windows is through the provided Makefile... |
github | sgbasel/neuritetracker-master | vl_noprefix.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/vl_noprefix.m | 1,875 | utf_8 | 97d8755f0ba139ac1304bc423d3d86d3 | function vl_noprefix
% VL_NOPREFIX Create a prefix-less version of VLFeat commands
% VL_NOPREFIX() creats prefix-less stubs for VLFeat functions
% (e.g. SIFT for VL_SIFT). This function is seldom used as the stubs
% are included in the VLFeat binary distribution anyways. Moreover,
% on UNIX platforms, the stub... |
github | sgbasel/neuritetracker-master | vl_pegasos.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/misc/vl_pegasos.m | 2,837 | utf_8 | d5e0915c439ece94eb5597a07090b67d | % VL_PEGASOS [deprecated]
% VL_PEGASOS is deprecated. Please use VL_SVMTRAIN() instead.
function [w b info] = vl_pegasos(X,Y,LAMBDA, varargin)
% Verbose not supported
if (sum(strcmpi('Verbose',varargin)))
varargin(find(strcmpi('Verbose',varargin),1))=[];
fprintf('Option VERBOSE is no longer supported.\n');
en... |
github | sgbasel/neuritetracker-master | vl_svmpegasos.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/misc/vl_svmpegasos.m | 1,178 | utf_8 | 009c2a2b87a375d529ed1a4dbe3af59f | % VL_SVMPEGASOS [deprecated]
% VL_SVMPEGASOS is deprecated. Please use VL_SVMTRAIN() instead.
function [w b info] = vl_svmpegasos(DATA,LAMBDA, varargin)
% Verbose not supported
if (sum(strcmpi('Verbose',varargin)))
varargin(find(strcmpi('Verbose',varargin),1))=[];
fprintf('Option VERBOSE is no longer suppor... |
github | sgbasel/neuritetracker-master | vl_override.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/misc/vl_override.m | 4,654 | utf_8 | e233d2ecaeb68f56034a976060c594c5 | function config = vl_override(config,update,varargin)
% VL_OVERRIDE Override structure subset
% CONFIG = VL_OVERRIDE(CONFIG, UPDATE) copies recursively the fileds
% of the structure UPDATE to the corresponding fields of the
% struture CONFIG.
%
% Usually CONFIG is interpreted as a list of paramters with their
... |
github | sgbasel/neuritetracker-master | vl_quickvis.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/quickshift/vl_quickvis.m | 3,696 | utf_8 | 27f199dad4c5b9c192a5dd3abc59f9da | function [Iedge dists map gaps] = vl_quickvis(I, ratio, kernelsize, maxdist, maxcuts)
% VL_QUICKVIS Create an edge image from a Quickshift segmentation.
% IEDGE = VL_QUICKVIS(I, RATIO, KERNELSIZE, MAXDIST, MAXCUTS) creates an edge
% stability image from a Quickshift segmentation. RATIO controls the tradeoff
% bet... |
github | sgbasel/neuritetracker-master | vl_demo_aib.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/demo/vl_demo_aib.m | 2,928 | utf_8 | 590c6db09451ea608d87bfd094662cac | function vl_demo_aib
% VL_DEMO_AIB Test Agglomerative Information Bottleneck (AIB)
D = 4 ;
K = 20 ;
randn('state',0) ;
rand('state',0) ;
X1 = randn(2,300) ; X1(1,:) = X1(1,:) + 2 ;
X2 = randn(2,300) ; X2(1,:) = X2(1,:) - 2 ;
X3 = randn(2,300) ; X3(2,:) = X3(2,:) + 2 ;
figure(1) ; clf ; hold on ;
vl_plotframe(X... |
github | sgbasel/neuritetracker-master | vl_demo_alldist.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/demo/vl_demo_alldist.m | 5,460 | utf_8 | 6d008a64d93445b9d7199b55d58db7eb | function vl_demo_alldist
%
numRepetitions = 3 ;
numDimensions = 1000 ;
numSamplesRange = [300] ;
settingsRange = {{'alldist2', 'double', 'l2', }, ...
{'alldist', 'double', 'l2', 'nosimd'}, ...
{'alldist', 'double', 'l2' }, ...
{'alldist2', 's... |
github | sgbasel/neuritetracker-master | vl_demo_ikmeans.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/demo/vl_demo_ikmeans.m | 774 | utf_8 | 17ff0bb7259d390fb4f91ea937ba7de0 | function vl_demo_ikmeans()
% VL_DEMO_IKMEANS
numData = 10000 ;
dimension = 2 ;
data = uint8(255*rand(dimension,numData)) ;
numClusters = 3^3 ;
[centers, assignments] = vl_ikmeans(data, numClusters);
figure(1) ; clf ; axis off ;
plotClusters(data, centers, assignments) ;
vl_demo_print('ikmeans_2d',0.6);
[tree, assig... |
github | sgbasel/neuritetracker-master | vl_demo_svm.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/demo/vl_demo_svm.m | 1,235 | utf_8 | 7cf6b3504e4fc2cbd10ff3fec6e331a7 | % VL_DEMO_SVM Demo: SVM: 2D linear learning
function vl_demo_svm
y=[];X=[];
% Load training data X and their labels y
load('vl_demo_svm_data.mat')
Xp = X(:,y==1);
Xn = X(:,y==-1);
figure
plot(Xn(1,:),Xn(2,:),'*r')
hold on
plot(Xp(1,:),Xp(2,:),'*b')
axis equal ;
vl_demo_print('svm_training') ;
% Parameters
lambda =... |
github | sgbasel/neuritetracker-master | vl_demo_kdtree_sift.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/demo/vl_demo_kdtree_sift.m | 6,832 | utf_8 | e676f80ac330a351f0110533c6ebba89 | function vl_demo_kdtree_sift
% VL_DEMO_KDTREE_SIFT
% Demonstrates the use of a kd-tree forest to match SIFT
% features. If FLANN is present, this function runs a comparison
% against it.
% AUTORIGHS
rand('state',0) ;
randn('state',0);
do_median = 0 ;
do_mean = 1 ;
% try to setup flann
if ~exist('flann_search'... |
github | sgbasel/neuritetracker-master | vl_impattern.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/imop/vl_impattern.m | 6,876 | utf_8 | 1716a4d107f0186be3d11c647bc628ce | function im = vl_impattern(varargin)
% VL_IMPATTERN Generate an image from a stock pattern
% IM=VLPATTERN(NAME) returns an instance of the specified
% pattern. These stock patterns are useful for testing algoirthms.
%
% All generated patterns are returned as an image of class
% DOUBLE. Both gray-scale and colou... |
github | sgbasel/neuritetracker-master | vl_tpsu.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/imop/vl_tpsu.m | 1,755 | utf_8 | 09f36e1a707c069b375eb2817d0e5f13 | function [U,dU,delta]=vl_tpsu(X,Y)
% VL_TPSU Compute the U matrix of a thin-plate spline transformation
% U=VL_TPSU(X,Y) returns the matrix
%
% [ U(|X(:,1) - Y(:,1)|) ... U(|X(:,1) - Y(:,N)|) ]
% [ ]
% [ U(|X(:,M) - Y(:,1)|) ... U(|X(:,M) - Y(:,N)|) ]
%
% where X... |
github | sgbasel/neuritetracker-master | vl_xyz2lab.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/imop/vl_xyz2lab.m | 1,570 | utf_8 | 09f95a6f9ae19c22486ec1157357f0e3 | function J=vl_xyz2lab(I,il)
% VL_XYZ2LAB Convert XYZ color space to LAB
% J = VL_XYZ2LAB(I) converts the image from XYZ format to LAB format.
%
% VL_XYZ2LAB(I,IL) uses one of the illuminants A, B, C, E, D50, D55,
% D65, D75, D93. The default illuminatn is E.
%
% See also: VL_XYZ2LUV(), VL_HELP().
% Copyright ... |
github | sgbasel/neuritetracker-master | vl_test_gmm.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_gmm.m | 1,332 | utf_8 | 76782cae6c98781c6c38d4cbf5549d94 | function results = vl_test_gmm(varargin)
% VL_TEST_GMM
% Copyright (C) 2007-12 Andrea Vedaldi and Brian Fulkerson.
% All rights reserved.
%
% This file is part of the VLFeat library and is made available under
% the terms of the BSD license (see the COPYING file).
vl_test_init ;
end
function s = setup()
randn('st... |
github | sgbasel/neuritetracker-master | vl_test_twister.m | .m | neuritetracker-master/trunk/vlfeat-0.9.18/toolbox/xtest/vl_test_twister.m | 1,251 | utf_8 | 2bfb5a30cbd6df6ac80c66b73f8646da | function results = vl_test_twister(varargin)
% VL_TEST_TWISTER
vl_test_init ;
function test_illegal_args()
vl_assert_exception(@() vl_twister(-1), 'vl:invalidArgument') ;
vl_assert_exception(@() vl_twister(1, -1), 'vl:invalidArgument') ;
vl_assert_exception(@() vl_twister([1, -1]), 'vl:invalidArgument') ;
function te... |
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