oil.m

本程序是用matlable求任意一个二维矩阵的边界矩阵

function oil(x,y)
%OIL    Create plot of datasets and fits
%   OIL(X,Y)
%   Creates a plot, similar to the plot in the main curve fitting
%   window, using the data that you provide as input.  You can
%   apply this function to the same data you used with cftool
%   or with different data.  You may want to edit the function to
%   customize the code and this help message.
%
%   Number of datasets:  1
%   Number of fits:  2

 
% Data from dataset "y vs. x":
%    X = x:
%    Y = y:
%    Unweighted
%
% This function was automatically generated

% Set up figure to receive datasets and fits
f_ = clf;
figure(f_);
legh_ = []; legt_ = {};   % handles and text for legend
xlim_ = [Inf -Inf];       % limits of x axis
ax_ = subplot(1,1,1);
set(ax_,'Box','on');
axes(ax_); hold on;

x=[1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003];
y=[46808
49416
53094
57237
56677
56198
59673
61826
64158
65220
63108
60944
59543
58779
59822
60087
61825
63104
64963
66092
66443
67061
67273
67372
68679
69955
71522
73292
73932
75826
76954
78105
78439
79813];
% --- Plot data originally in dataset "y vs. x"
x = x(:);
y = y(:);
h_ = line(x,y,'Parent',ax_,'Color',[0.333333 0 0.666667],...
     'LineStyle','none', 'LineWidth',1,...
     'Marker','.', 'MarkerSize',12);
xlim_(1) = min(xlim_(1),min(x));
xlim_(2) = max(xlim_(2),max(x));
legh_(end+1) = h_;
legt_{end+1} = 'y vs. x';

% Nudge axis limits beyond data limits
if all(isfinite(xlim_))
   xlim_ = xlim_ + [-1 1] * 0.01 * diff(xlim_);
   set(ax_,'XLim',xlim_)
end


% --- Create fit "fit 1"
st_ = [31950 556 1.605 -3159 4e-006 0.02366 ];
ft_ = fittype('a1+a2*cos(a3*x+a4)+a5*exp(a6*x)' ,...
     'dependent',{'y'},'independent',{'x'},...
     'coefficients',{'a1', 'a2', 'a3', 'a4', 'a5', 'a6'});

% Fit this model using new data
cf_ = fit(x,y,ft_ ,'Startpoint',st_);

% Or use coefficients from the original fit:
if 0
   cv_ = {31950, 556, 1.604999972619, -3159, 1.238523818602e-016, 0.02365999999998};
   cf_ = cfit(ft_,cv_{:});
end

% Plot this fit
h_ = plot(cf_,'fit',0.95);
legend off;  % turn off legend from plot method call
set(h_(1),'Color',[1 0 0],...
     'LineStyle','-', 'LineWidth',2,...
     'Marker','none', 'MarkerSize',6);
legh_(end+1) = h_(1);
legt_{end+1} = 'fit 1';

% --- Create fit "fit 1 copy 1"
st_ = [31950 556 1.605 -3159 4e-006 0.02366 ];
ft_ = fittype('a1+a2*cos(a3*x+a4)+a5*exp(a6*x)' ,...
     'dependent',{'y'},'independent',{'x'},...
     'coefficients',{'a1', 'a2', 'a3', 'a4', 'a5', 'a6'});

% Fit this model using new data
cf_ = fit(x,y,ft_ ,'Startpoint',st_);

% Or use coefficients from the original fit:
if 0
   cv_ = {31950, 556, 1.604999972619, -3159, 1.238523818602e-016, 0.02365999999998};
   cf_ = cfit(ft_,cv_{:});
end

% Plot this fit
h_ = plot(cf_,'fit',0.95);
legend off;  % turn off legend from plot method call
set(h_(1),'Color',[0 0 1],...
     'LineStyle','-', 'LineWidth',2,...
     'Marker','none', 'MarkerSize',6);
legh_(end+1) = h_(1);
legt_{end+1} = 'fit 1 copy 1';

hold off;
legend(ax_,legh_, legt_);