How to make contour plot of given matrices
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Cute Doll
am 12 Okt. 2015
Kommentiert: Cute Doll
am 12 Okt. 2015
f= [0;
0.0492;
0.0969;
0.1431;
0.188;
0.2316;
0.274;
0.3152;
0.3554;
0.3946;
0.4328;
0.4702;
0.5067;
0.5424;
0.5775;
0.6118;
0.6455;
0.6786;
0.7111;
0.7432;
0.7747;
0.8058;
0.8365;
0.8668;
0.8968;
0.9264;
0.9557;
0.9847;
1.0135;
1.042;
1.0703;
1.0984;
1.1263;
1.1541;
1.1816;
1.2091;
1.2364;
1.2635;
1.2906;
1.3175;
1.3444;
1.3712;
1.3979;
1.4245;
1.4511;
1.4776;
1.504;
1.5305;
1.5568;
1.5831;
1.6094;
1.6357;
1.6619;
1.6881;
1.7143;
1.7405;
1.7666;
1.7927;
1.8188;
1.8449;
1.871;
1.8971;
1.9231;
1.9492;
1.9752;
2.0013;
2.0273;
2.0533;
2.0793;
2.1054;
2.1314;
2.1574;
2.1834;
2.2094;
2.2354;
2.2614;
2.2874;
2.3134;
2.3394;
2.3654;
2.3914;
2.4174;
2.4434;
2.4694;
2.4954;
2.5214;
2.5473;
2.5733;
2.5993;
2.6253;
2.6513;
2.6773;
2.7033;
2.7293;
2.7553;
2.7813;
2.8072;
2.8332;
2.8592;
2.8852;
2.9112]
h=[0;
0.001;
0.004;
0.0091;
0.0163;
0.0257;
0.0372;
0.0509;
0.0669;
0.0852;
0.1058;
0.1287;
0.154;
0.1817;
0.2118;
0.2444;
0.2794;
0.317;
0.357;
0.3996;
0.4447;
0.4924;
0.5426;
0.5954;
0.6508;
0.7088;
0.7694;
0.8326;
0.8984;
0.9668;
1.0378;
1.1115;
1.1878;
1.2666;
1.3481;
1.4323;
1.519;
1.6083;
1.7003;
1.7948;
1.892;
1.9917;
2.0941;
2.199;
2.3066;
2.4167;
2.5294;
2.6446;
2.7625;
2.8829;
3.0058;
3.1314;
3.2594;
3.3901;
3.5233;
3.659;
3.7973;
3.9381;
4.0814;
4.2273;
4.3757;
4.5267;
4.6801;
4.8361;
4.9946;
5.1557;
5.3192;
5.4853;
5.6539;
5.825;
5.9986;
6.1747;
6.3534;
6.5345;
6.7182;
6.9043;
7.093;
7.2842;
7.4778;
7.674;
7.8727;
8.0739;
8.2776;
8.4838;
8.6925;
8.9037;
9.1174;
9.3336;
9.5523;
9.7735;
9.9972;
10.2235;
10.4522;
10.6834;
10.9171;
11.1533;
11.392;
11.6332;
11.8769;
12.1232;
12.3719
]
how i can make contour plot in (x,y)
if we have following relation
g(x,y)=x*f(y)+0.95*h(y)
Note# (See attached figure of plot)
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Akzeptierte Antwort
Thorsten
am 12 Okt. 2015
x = -10:0.2:10;
y = 1:101;
[X Y] = meshgrid(x, y);
G = X.*f(Y)+0.95*h(Y);
contour(G, [-5 -3 -1 -0.1 0 0.1 1 3 5])
Weitere Antworten (1)
Mike Garrity
am 12 Okt. 2015
It's going to look something like this:
nrows = length(f);
ncols = 150;
x = linspace(-10,10,ncols)
y = linspace(0,9,nrows);
g = repmat(x,[nrows,1]).*repmat(f,[1,ncols]) + .95*repmat(h,[1,ncols]);
contour(x,y,g)
Although the X & Y coordinates appear to be a bit off from your picture.
The basic idea is you can use repmat to expand a row vector or a column vector into a 2D array. Once you've got all of your variables as 2D arrays, you can do the math on them and hand them to contour.
Does that make sense?
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