2.Дьяконов В.П. Справочник по MathCAD PLUS 6.0 PRO. - М.: СК-Пресс, 1997.
7-Лабораториялық сабағы.
Тақырыбы: MatLab-та сызықты, сызықты емес теңдеулерді шешу, туындыны және интегралды есептеу
Функция шақырылған жалпы параметрлер санын тексеруге болады. Осы мақсат үшін Matlab жүйесінде nargin атымен айнымалы көрсетілген. Оның мәні болып аргумент мөлшері табылады. Онда параметр санына тексеру келесі түрде орындалады:
if nargin~=3
error (‘Bad numbr of parameters’)
end
Matlab жүйесінде nargout айнымалысы да қараытырылған. Мысалы,
[s1, s2, s3]=MatrProg1(X1, X2, x)
үш қайтару мәнін алады.
MatrProg1 функция шақыруын жүзеге асыру үшін және пайдаланушыға сандардың сәйкес келмеуін ескертіп функция денесінде nargout айнымалысын келесі түрде көрсетуге болады:
if nargout ~=2
error(‘Must be 2 return values’)
end
Функцияны тек кіру параметрінің санымен және қайтару мәнімен шақыруға болады. Біз алдында кіру параметрінің әр түрлі санымен шақырылған Matlab жүйесіндегі салынған функциялармен кездескенбіз. Онда мысалға plot функциясы функция графигінің салыну атымен жүзеге асқан болатын.
М-функцияны өңдеуде әр түрлі кіру аргументінің санында көп нұсқаулы жұмыс мүмкіндігі бар; оларды санын тексеру кезінде көрсету және жұмысты тоқтатудың орнына функцияға әр түрлі орындалуды жүзеге асыру керек.
М-функция мәтінінде бірінші және екінші максимальді санды пайдалану керек.
TestFunc2 функция
Function [res1, res2]=TestFunc2(var1, var2)
Switch nargin
Case 1
If nargout==1, res1=var1*2;
Elseif nargout==2, res1=var1*2; res2=var1+3;
Else error (‘Must be 1 or 2 return values’);
End
Case 2
If nargout==1, res1=var.*var2;
Elseif==1, res1=var1.*var2; res2=var1+3;
Else error (‘Must be 1 or 2 return values’);
End
Otherwise error (‘Must be 1 or 2 parameters’);
End
Алдын ала көрсетілген формат шақыруына рұқсат етеді. Қорыта келе дәрежені тексеру функциядан тұрады. Егер М-функция меншік қолдануда жазылса, онда тексеру қатты болуы мүмкін. Қате жағдайлар автоматты түрде осы жүйеде өңделеді және командалық терезеге сәйкес диагностикалық хабарлама береді.
Егер функция сыртқы қажет етуге жақын болса, онда тексерулерді берікті ету керек. Matlab жүйесі санмен жазылған М-функцияны штатты түрде қояды. Осы функциялардың мәтіні командалық терезеге келесі командамен шақырылады.
type имя_функции
кейбір алгоритм функцияның деталін үйренумен қатар, кіру параметрін және шығу мәнін тексеру әдістерін үйренген жөн.
Команданы орындап және енгізіп repmat функциясын қарастырайық:
type repmat
нәтижесінде оның толық мәтінін аламыз:
function B=repmat(A, M, N)
%REPMAT Replicate and tile an array.
% B= REPMAT(A, M, N) replicates and tiles the matrix a
% to produce the M-by-N block matrix B.
%
% B= REPMAT(A, [M N]) produces the same thing.
%
% B= REPMAT(A, [M N P…]) tiles the array a to
% produce a M-by-N-by-P-by-… block array. a can be N-D.
%
% REPMAT(A, M, N), when a is a scalar, is commonly used to
% produce an M-by-N matrix filled with A’s value.
% This can be much faster than A*ONES(M, N)
% when M and/or N are large.
%
% Example:
% repmat(magic (2), 2, 3)
% repmat(NaN, 2, 3)
%
% See also MESHGRID.
%
% Copyright (c) 1984-98 by The MathWorks, Inc.
% $Revision: 1.11 $ $Date: 1997/11/21 23:30:13 $
if nargin<2
error (‘Reguires at least 2 inputs.’)
elseif nargin= =2
if prod(size(M))= =1
siz=[M M];
else
siz=M;
end
else
siz=[M N];
end
if length(A)= =1
% This produces the same answer as B=A(ones(siz));
% but uses less memory.
B=…
Reshape (A(ones(1, siz(1)), ones(1, prod(siz(2:end)))), siz);
Elseif ndims(A)= =2 & length(siz)= =2
[m, n]=size(A);
mind=(1:m)’;
nind=(1:n)’;
mind=mind(:, ones(1, siz(1)));
nind=nind(:, ones(1, siz(2)));
B=A(mind, nind);
Else
Asiz=size(A);
Asiz=[Asiz ones (1, length(siz)-length(Asiz))];
siz= [siz ones (1, length(Asiz)-length(siz))];
for i=length(Asiz):-1:1
ind=(1:Asiz(i))’;
subs{i}=ind(:, ones(1, siz(i)));
end
B=A(subs{:});
end
Ұсынылатын әдебиет:
1.Статистический анализ данных в пакете Mathcad Радченко Т.А., Дылевский А.В, Воронеж, 2004
2.Дьяконов В.П. Справочник по MathCAD PLUS 6.0 PRO. - М.: СК-Пресс, 1997.
8-Лабораториялық сабағы.
Тақырыбы: MatLab-та жаңа функциялар құру, дифференциалдық теңдеулерді шешу
Repmat функциясының мәтіні үйренуге пайдалы. Себебі мұнда эффективті алгоритм шешімі М рет вертикаль бойынша және N рет горизанталь бойынша берілген А матрицасы көрсетілген.
Мысалы, міне repmat функциясының жұмыс істелінуі
4![](data:image/png;base64,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) -сурет
Функцияның жұмыс жасау облысы.
Әрбір М-функциядан Matlab жүйесінің жұмыс істеу облысымен қиылыспайтын жадының қосымша облысы болады. Matlab жүйесімен жұмыс атқарғанда жүйенің жұмыс істеу облысында немесе функцияның жұмыс жасау облысында орналасқан тек айнымалыға ғана жол алуға болады. Егер айнымалы глобальді деп хабарланса, онда оны бірнеше жұмыс жасау облысына тәуелді деп қарастыруға болады. Функцияның шақыруымен nargin және nargout функциялары аргументтерінің кіретін және шығатын сандарын анықтауға мүмкіндік береді. Бұл ақпаратты кейін есептеу жүрісін өзгерту шартты операторында пайдалануға болады.
Мысал: 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)
Достарыңызбен бөлісу: |