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Commit 5a11171e authored by Nicolas Bellot's avatar Nicolas Bellot Committed by hhakim
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header demo matlab folder tools

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misc/demo/tools/cum_dvp.m deleted 100644 → 0
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function [Ddvp, cum_dvp] = cum_dvp(D)
%dvp. Development of the input factorized matrix.
% Ddvp = dvp(D) develops the cell-array of matrices D into the matrix Ddvp
% which is the product of the matrices contained in D:
% Ddvp = D{1}*D{2}*...*D{n}.
%
% References:
% [1] Le Magoarou L. and Gribonval R., "Learning computationally efficient
% dictionaries and their implementation as fast transforms", submitted to
% NIPS 2014
% Luc Le Magoarou
% PANAMA team
% Inria, Rennes - Bretagne Atlantique
% luc.le-magoarou@inria.fr
%
% June 2014
Nlayers = size(D,2);
cum_dvp=cell(1,Nlayers);
if Nlayers==0
Ddvp = 1;
else
cum_dvp{1} =D{1};
for i = 2:Nlayers
if size(D{i},1) == size(cum_dvp{i-1},2)
cum_dvp{i} = cum_dvp{i-1} * D{i};
end
end
Ddvp=cum_dvp{1,Nlayers};
end
end
misc/demo/tools/f_mult.m deleted 100755 → 0
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function y = f_mult(facts,x)
% y=ones(size(facts{1},2),size(x,2));
% disp('bla');
% for i=1:100
% end
y=x;
for i=length(facts):-1:1
y=facts{i}*y;
end
if issparse(y)
y=full(y);
end
end
misc/demo/tools/faust_transpose.m deleted 100755 → 0
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function facts_transpose = faust_transpose(facts)
facts_transpose=cell(1,length(facts));
for i=1:length(facts);
% length(facts)+1-i
facts_transpose{i}=facts{length(facts)+1-i}';
end
end
misc/demo/tools/gen_artificial_faust.m
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%% script pour generer des Faust avec un RCG, une Dimension et un nombre de facteur fixe
% lancer l'executable multiply_comptime ensuite pour effectuer les tests de performances
% puis display_multiply_comptime pour afficher les resultats
%% Description gen_artficial_faust
% facts=gen_artficial_faust(Dim,RCG,nb_fact,constraint)
% create a random Faust factor with :
% a given dimension Dim,
% a relative complexity gain RCG,
% a number of factor nb_fact,
% a type of sparsity 'sp' random support,
% 'sp_row', fixed number of non-zeros per row
% 'sp_col', fixed number of nonzeros-per-col
%
% For more information on the FAuST Project, please visit the website of
% the project : <http://faust.gforge.inria.fr>
%
%% License:
% Copyright (2016): Nicolas Bellot, Adrien Leman, Thomas Gautrais,
% Luc Le Magoarou, Remi Gribonval
% INRIA Rennes, FRANCE
% http://www.inria.fr/
%
% The FAuST Toolbox is distributed under the terms of the GNU Affero
% General Public License.
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU Affero General Public License as published
% by the Free Software Foundation.
%
% This program is distributed in the hope that it will be useful, but
% WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
% See the GNU Affero General Public License for more details.
%
% You should have received a copy of the GNU Affero General Public License
% along with this program. If not, see <http://www.gnu.org/licenses/>.
%
%% Contacts:
% Nicolas Bellot : nicolas.bellot@inria.fr
% Adrien Leman : adrien.leman@inria.fr
% Thomas Gautrais : thomas.gautrais@inria.fr
% Luc Le Magoarou : luc.le-magoarou@inria.fr
% Remi Gribonval : remi.gribonval@inria.fr
%
%% References:
% [1] Le Magoarou L. and Gribonval R., "Flexible multi-layer sparse
% approximations of matrices and applications", Journal of Selected
% Topics in Signal Processing, 2016.
% <https://hal.archives-ouvertes.fr/hal-01167948v1>
%%
function facts=gen_artficial_faust(Dim,RCG,nb_fact,constraint)
%% cas 1
% RCGs = [2 4 6 8 10];
......
misc/demo/tools/hadamard_mat.m
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......@@ -7,7 +7,8 @@
% the project : <http://faust.gforge.inria.fr>
%
%% License:
% Copyright (2016): Luc Le Magoarou, Remi Gribonval
% Copyright (2016): Nicolas Bellot, Adrien Leman, Thomas Gautrais,
% Luc Le Magoarou, Remi Gribonval
% INRIA Rennes, FRANCE
% http://www.inria.fr/
%
......@@ -26,17 +27,17 @@
% along with this program. If not, see <http://www.gnu.org/licenses/>.
%
%% Contacts:
% Nicolas Bellot : nicolas.bellot@inria.fr
% Adrien Leman : adrien.leman@inria.fr
% Luc Le Magoarou: luc.le-magoarou@inria.fr
% Remi Gribonval : remi.gribonval@inria.fr
% Nicolas Bellot : nicolas.bellot@inria.fr
% Adrien Leman : adrien.leman@inria.fr
% Thomas Gautrais : thomas.gautrais@inria.fr
% Luc Le Magoarou : luc.le-magoarou@inria.fr
% Remi Gribonval : remi.gribonval@inria.fr
%
%% References:
% [1] Le Magoarou L. and Gribonval R., "Flexible multi-layer sparse
% approximations of matrices and applications", Journal of Selected
% Topics in Signal Processing, 2016.
% <https://hal.archives-ouvertes.fr/hal-01167948v1>
%%
function [H,Fact] = hadamard_mat(M)
......
misc/demo/tools/make_sparse.m deleted 100755 → 0
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function new_facts = make_sparse(facts)
%UNTITLED9 Summary of this function goes here
% Detailed explanation goes here
for i=1:length(facts)
new_facts{i}=sparse(facts{i});
end
end
misc/demo/tools/normalizeCol.m
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%% Description normalizeCol
% A_normalize = normalizeCol(A,varargin)
% each column of the ouput matrix is normalized (norm(A_normalize(:,i))=1)
% - A can be a matrix or cell-array representing a matrix
% - an optional scalar multiplicator can added in input
%
% For more information on the FAuST Project, please visit the website of
% the project : <http://faust.gforge.inria.fr>
%
%% License:
% Copyright (2016): Nicolas Bellot, Adrien Leman, Thomas Gautrais,
% Luc Le Magoarou, Remi Gribonval
% INRIA Rennes, FRANCE
% http://www.inria.fr/
%
% The FAuST Toolbox is distributed under the terms of the GNU Affero
% General Public License.
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU Affero General Public License as published
% by the Free Software Foundation.
%
% This program is distributed in the hope that it will be useful, but
% WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
% See the GNU Affero General Public License for more details.
%
% You should have received a copy of the GNU Affero General Public License
% along with this program. If not, see <http://www.gnu.org/licenses/>.
%
%% Contacts:
% Nicolas Bellot : nicolas.bellot@inria.fr
% Adrien Leman : adrien.leman@inria.fr
% Thomas Gautrais : thomas.gautrais@inria.fr
% Luc Le Magoarou : luc.le-magoarou@inria.fr
% Remi Gribonval : remi.gribonval@inria.fr
%
%% References:
% [1] Le Magoarou L. and Gribonval R., "Flexible multi-layer sparse
% approximations of matrices and applications", Journal of Selected
% Topics in Signal Processing, 2016.
% <https://hal.archives-ouvertes.fr/hal-01167948v1>
%%
function A_normalize = normalizeCol(A,varargin)
nb_input=length(varargin);
......
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