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Maple densityplot的Matlab等价物

maple matlab-figure plot matlab

smyslov · 技术社区 · 9 年前

我想创建此函数的密度图:

在Maple中,可以使用 densityplot

然而,我不确定在MATLAB中绘制类似图形时使用什么。

x = [0:10:100];
y = [-50:10:50];
s = [10, 0];
i = [50,25];
for ii = 1 : length(x)
    sir(ii) = -10 * 9.8 * log10((power((x(ii) - s(1)),2) + power((y(ii) - s(2)),2)) / (power((x(ii) - i(1)),2) + power((y(ii) - i(2)),2)));  
end

对于Maple中的密度图,我使用了

densityplot(sir(x,y), x=0..100, y=-50..50, axes=boxed, style=patchnogrid, scaletorange=-5..50, colorscheme = [black, "green", "white"])

1 回复 | 直到 9 年前

Wolfie Radu Stefan 9 年前

您可以使用 surf (一个3D曲面图)来实现这一点,但你需要一个比10步更精细的网格才能看起来很好!

此外,您还需要 meshgrid x 和 y 协调。

请参阅评论了解更多详细信息。

% Set up grid points
x = 0:0.1:100;
y = -50:0.1:50;
[x,y] = meshgrid(x,y);
% Set up parameters i, s and g
i = [50 25]; s = [10 0]; g = 9.8;
% Work out density  
% - no need for loop if we use element-wise operations ./ and .^
% - power(z,2) replaced by z.^2 (same function, more concise)
% - You forgot the sqare roots in your question's code, included using .^(1/2)
% - line continuation with "...", could remove and have on one line
sir = -10*g*log10( ((x-s(1)).^2 + (y-s(2)).^2).^(1/2) ./ ...
                   ((x-i(1)).^2 + (y-i(2)).^2).^(1/2)        ); 
% Plot, and set to a view from above
surf(x,y,sir,'edgecolor','none','facecolor','interp');
view(2);
% Change the colour scheme
colormap('bone')

匹配您的示例

你使用了Maple命令 scaletorange=-5..50 -5 和 50 ( docs sir

% Restrict sir to the range [-5,50]
sir = min(max(sir,-5),50);
% Of course we now have to replot
surf(x,y,sir,'edgecolor','none','facecolor','interp');
view(2);

现在,如果你想要黑色/绿色,你可以使用定制的 colormap ,这也将平滑由 'bone' 颜色表 只有64种颜色。

% Define the three colours to interpolate between, and n interpolation points
black = [0 0 0]; green = [0 1 0]; white = [1 1 1]; 
n = 1000; 
% Do colour interpolation, equivalent to Maple's 'colorscheme = [black, "green", "white"]'
% We need an nx3 matrix of colours (columns R,G,B), which we get using interp1
colormap(interp1(1:3, [black; green; white], linspace(1,3,n)));

具有 g=3.5