Added @dseries/mpower method (element-by-element powers).

time-shift
Stéphane Adjemian (Charybdis) 2013-12-03 08:41:04 +01:00
parent ba31ac7ade
commit deed4df569
2 changed files with 166 additions and 0 deletions

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@ -9789,6 +9789,36 @@ ans is a dseries object:
@sp 1
@deftypefn{dseries} {@var{C} =} mpower (@var{A}, @var{B})
Overloads the @code{mpower} (@code{^}) operator for @dseries objects and computes element-by-element power. @var{A} is a @dseries object with @code{N} variables and @code{T} observations. If @var{B} is a real scalar, then @code{mpower(@var{A},@var{B})} returns a @dseries object @var{C} with @code{C.data(t,n)=A.data(t,n)^C}. If @var{B} is a @dseries object with @code{N} variables and @code{T} observations then @code{mpower(@var{A},@var{B})} returns a @dseries object @var{C} with @code{C.data(t,n)=A.data(t,n)^C.data(t,n)}.
@examplehead
@example
>> ts0 = dseries(transpose(1:3));
>> ts1 = ts0^2
ts1 is a dseries object:
| power(Variable_1,2)
1Y | 1
2Y | 4
3Y | 9
>> ts2 = ts0^ts0
ts2 is a dseries object:
| power(Variable_1,Variable_1)
1Y | 1
2Y | 4
3Y | 27
@end example
@end deftypefn
@sp 1
@deftypefn{dseries} {@var{C} =} mrdivide (@var{A}, @var{B})
Overloads the @code{mrdivide} (@code{/}) operator for @dseries objects, element by element division (like the @code{./} Matlab/Octave operator). If both @var{A} and @var{B} are @dseries objects, they do not need to be defined over the same time ranges. If @var{A} and @var{B} are @dseries object with @math{T_A} and @math{T_B} observations and @math{N_A} and @math{N_B} variables, then @math{N_A} must be equal to @math{N_B} or @math{1} and @math{N_B} must be equal to @math{N_A} or @math{1}. If @math{T_A=T_B}, @code{isequal(A.init,B.init)} returns 1 and @math{N_A=N_B}, then the @code{mrdivide} operator will compute for each couple @math{(t,n)}, with @math{1<=t<=T_A} and @math{1<=n<=N_A}, @code{C.data(t,n)=A.data(t,n)/B.data(t,n)}. If @math{N_B} is equal to @math{1} and @math{N_A>1}, the smaller @dseries object (@var{B}) is ``broadcast'' across the larger @dseries (@var{A}) so that they have compatible shapes, @code{mrdivides} operator will divide each variable defined in @var{A} by the variable in @var{B}, observation per observation. If @var{B} is a double scalar, then the method @code{mrdivide} will divide all the observations/variables in @var{A} by @var{B}.

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matlab/@dseries/mpower.m Normal file
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@ -0,0 +1,136 @@
function A = mpower(B,C) % --*-- Unitary tests --*--
%@info:
%! @deftypefn {Function File} {@var{A} =} mpower (@var{B},@var{C})
%! @anchor{@dseries/mpower}
%! @sp 1
%! Overloads the mpower method for the Dynare time series class (@ref{dseries}).
%! @sp 2
%! @strong{Inputs}
%! @sp 1
%! @table @ @var
%! @item B
%! Dynare time series object instantiated by @ref{dseries}, with T observations and N variables.
%! @item C
%! Real scalar or a dseries object with T observations and N variables.
%! @end table
%! @sp 1
%! @strong{Outputs}
%! @sp 1
%! @table @ @var
%! @item A
%! dseries object with T observations and N variables.
%! @end deftypefn
%@eod:
% Copyright (C) 2013 Dynare Team
%
% This file is part of Dynare.
%
% Dynare is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your option) any later version.
%
% Dynare 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 General Public License for more details.
%
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
if isdseries(B) && isnumeric(C) && isreal(C) && isscalar(C)
A = dseries();
A.freq = B.freq;
A.init = B.init;
A.dates = B.dates;
A.nobs = B.nobs;
A.vobs = B.vobs;
A.name = cell(A.vobs,1);
A.tex = cell(A.vobs,1);
for i=1:A.vobs
A.name(i) = {['power(' B.name{i} ',' num2str(C) ')']};
A.tex(i) = {[B.tex{i} '^' num2str(C) ]};
end
A.data = B.data.^C;
return
end
if isdseries(B) && isdseries(C)
if isequal(B.nobs,C.nobs) && isequal(B.vobs,C.vobs) && isequal(B.freq,C.freq)
A = dseries();
A.freq = B.freq;
A.init = B.init;
A.dates = B.dates;
A.nobs = B.nobs;
A.vobs = B.vobs;
A.name = cell(A.vobs,1);
A.tex = cell(A.vobs,1);
for i=1:A.vobs
A.name(i) = {['power(' B.name{i} ',' C.name{i} ')']};
A.tex(i) = {[B.tex{i} '^{' C.tex{i} '}']};
end
A.data = B.data.^C.data;
else
error('dseries::mpower: If both input arguments are dseries objects, they must have the same numbers of variables and observations and common frequency!')
end
return
end
error(['dseries::mpower: Wrong calling sequence!'])
%@test:1
%$ % Define a datasets.
%$ A = rand(10,2); B = randn(10,2);
%$
%$ % Define names
%$ A_name = {'A1';'A2'}; B_name = {'B1';'B2'};
%$
%$
%$ % Instantiate a time series object.
%$ try
%$ ts1 = dseries(A,[],A_name,[]);
%$ ts2 = dseries(B,[],B_name,[]);
%$ ts3 = ts1^ts2;
%$ t = 1;
%$ catch
%$ t = 0;
%$ end
%$
%$ if t(1)
%$ t(2) = dyn_assert(ts3.vobs,2);
%$ t(3) = dyn_assert(ts3.nobs,10);
%$ t(4) = dyn_assert(ts3.data,A.^B,1e-15);
%$ t(5) = dyn_assert(ts3.name,{'power(A1,B1)';'power(A2,B2)'});
%$ t(6) = dyn_assert(ts3.tex,{'A1^{B1}';'A2^{B2}'});
%$ end
%$ T = all(t);
%@eof:1
%@test:2
%$ % Define a datasets.
%$ A = rand(10,2);
%$
%$ % Define names
%$ A_name = {'A1';'A2'};
%$
%$
%$ % Instantiate a time series object.
%$ try
%$ ts1 = dseries(A,[],A_name,[]);
%$ ts3 = ts1^2;
%$ t = 1;
%$ catch
%$ t = 0;
%$ end
%$
%$ if t(1)
%$ t(2) = dyn_assert(ts3.vobs,2);
%$ t(3) = dyn_assert(ts3.nobs,10);
%$ t(4) = dyn_assert(ts3.data,A.^2,1e-15);
%$ t(5) = dyn_assert(ts3.name,{'power(A1,2)';'power(A2,2)'});
%$ t(6) = dyn_assert(ts3.tex,{'A1^2';'A2^2'});
%$ end
%$ T = all(t);
%@eof:2