clear
clc
A = [ --- spherical coordinates (theta, phi, r) [too long] --- ]; % size(A) is 1369 X 3
B = zeros(1369,3);
B(:,1) = A(:,3).*sind(A(:,1)).*cosd(A(:,2));
B(:,2) = A(:,3).*sind(A(:,1)).*sind(A(:,2));
B(:,3) = A(:,3).*cosd(A(:,1)); % converted to cartesian coordinates
raw_x = (B(:, 1))';
raw_y = (B(:, 2));
raw_z = (B(:, 3));
[X, Y] = meshgrid(raw_x, raw_y); % to use interp2
inter_z = vec2mat((raw_z)', 37);
Z = (inter_z)';
Above I am trying to interpolate and plot a set of spherical coordinates. For interpolation, I need to use below command
interp2(X,Y,Z,xi,yi,'bicubic') % xi and yi will be defined arbitrarily
However, X, Y and Z need to have the same size to use this command. I have size(X) = size(Y) = 1369 X 1369 and size(Z) = 37 X 37. I could not figure out how I can overcome this confusion correctly. Could you help out?
Related
In MATLAB, I am trying to write a program that will take 3 coordinates on a graph, (x,y), use those values to solve a system of equations that will find the coefficients of a polynomial equation, y = ax^2 + bx + c, which I can then use to plot a parabola.
To test my code, I figured I could start with a polynomial, graph it, find the minimum location of the parabola, use its immediate neighbors for my other 2 locations, then run those 3 locations through my code which should spit out the coefficients of my original polynomial. But for some reason, my resulting parabola is right shifted and my values for b and c are incorrect.
Does anyone see where my issue is? I am out of ideas
clear all; close all;
x = -10:10;
%Original Polynomial
y = 6.*x.^2 + 11.*x -35;
% Find 3 Locations
[max_n, max_i] = min(y)
max_il = max_i - 1 % left neighbor of max_ni
max_nl = y(max_il) % value at max_il
max_ir = max_i + 1 % left neighbor of max_ni
max_nr = y(max_ir) % value at max_ir
% Solve for coefficients
syms a b c
equ = (a)*(max_i)^2 + (b)*(max_i) + (c) == (max_n);
equ_l = (a)*(max_il)^2 + (b)*(max_il) + (c) == (max_nl);
equ_r = (a)*(max_ir)^2 + (b)*(max_ir) + (c) == (max_nr);
sol = solve([equ, equ_l, equ_r],[a, b, c]);
Sola = sol.a
Solb = sol.b
Solc = sol.c
% New Polynomial
p = (sol.a).*(x).^2 + (sol.b).*(x) +(sol.c);
%Plot
plot(x,y); grid on; hold on;
plot(x, p);
axis([-10 10 -41 40])
[max_np, max_ip] = min(p)
legend('OG', 'New')
You are confusing the index into your array y, and the corresponding x coordinate.
x = -10:10;
y = 6.*x.^2 + 11.*x -35;
[max_n, max_i] = min(y)
Here. max_i is the index into the y array, the corresponding x coordinate would be x(max_i).
I suggest you find three data points to fit your curve to as follows:
[~, max_i] = min(y);
pts_x = x(max_i + (-1:1));
pts_y = y(max_i + (-1:1));
then use pts_x(i) and pts_y(i) as your x and y values:
syms a b c
equ = a * pts_x.^2 + b * pts_x + c == pts_y;
sol = solve(equ, [a, b, c]);
I am trying to generate a semi ellipsoidal dome shape by using x, y, z values. In my code below, I define the x,y,z values but I am unable to assign those values to sphere.
How do I resolve this?
clc
x = [65 55.2125 50.8267 46.7398 42.9232 39.3476 35.9815 32.7882 29.7175 26.6833 23.4690 18.7605];
y = x;
z = [0.0,0.9,2.7,5.2,8.2,11.8,15.8,20.3,25.2,30.7,37.1,47.5]; % max height of dome is 47.5
[x,y,z] = sphere(20);
x = x(12:end,:);
y = y(12:end,:);
z = z(12:end,:);
r = 65; % radius of the dome
surf(r.*x,r.*y,r.*z);
axis equal;
It will be simpler or at least more elegant to use the parametric equations of an ellipsoide.
% semi axis parameters
a = 65; % x-axis
b = 65; % y-axis
c = 47.5; % z-axis
%% Parametrisation
%
% To reach each point of the ellipsoide we need two angle:
% phi ∈ [0,2𝜋]
% theta ∈ [0, 𝜋]
%
% But since we only need half of an ellipsoide we can set
% theta ∈ [0,𝜋/2]
[theta,phi] = ndgrid(linspace(0,pi/2,50),linspace(0,2*pi,50));
x = a*sin(theta).*cos(phi);
y = b*sin(theta).*sin(phi);
z = c*cos(theta);
%plot
surf(x,y,z)
axis equal
Result:
You can remove the bottom half of the sphere by assigning NaNs to the approptiate elements of x and y:
[x,y,z] = sphere(20);
I = (z<0);
x(I) = NaN;
y(I) = NaN;
surf(x,y,z)
I want to plot a curve like this using a periodic spline:
I have the following values:
And so, I have created the following matlab code to plot this function:
%initializing values
t = [1,2,3,4,5,6,7,8,9,10,11,12,13];
tplot = [1:0.1:13];
x = [2.5,1.3,-0.25,0.0,0.25,-1.3,-2.5,-1.3,0.25,0.0,-0.25,1.3,2.5];
y = [0.0,-0.25,1.3,2.5,1.3,-0.25,0.0,0.25,-1.3,-2.5,-1.3,0.25,0.0];
[a1, b1, c1, d1] = perspline2(t,x);
[a2, b2, c2, d2] = perspline2(t,y);
for i = 1:12
xx = linspace(x(i), x(i+1), 100);
xxx = a1(i) + b1(i)*(xx-x(i)) + c1(i)*(xx-x(i)).^2 ...
+ d1(i)*(xx-x(i)).^3;
yyy = a2(i) + b2(i)*(xx-x(i)) + c2(i)*(xx-x(i)).^2 ...
+ d2(i)*(xx-x(i)).^3;
h3=plot(xxx, yyy, 'r-');
hold on
end
plot(x,y,'k.', 'MarkerSize', 30)
hold off
With perspline2() looking like this:
function [a1,b1,c1,d1] = perspline2(xnot,ynot)
x = xnot';
y = ynot';
n = length(x) - 1;
h = diff(x);
diag0 = [1; 2*(h(1:end-1)+h(2:end)); 2*h(end)];
A = spdiags([[h;0], diag0, [0;h]], [-1, 0, 1], n+1, n+1);
% Do a little surgery on the matrix:
A(1,2) = 0;
A(1,end) = -1;
A(end,1) = 2*h(1);
A(end,2) = h(1);
dy = diff(y);
rhs = 6*[0; diff(dy./h); dy(1)/h(1)-dy(end)/h(end)];
m = A \ rhs; % Solve for the slopes, S''(x_i)
% Compute the coefficients of the cubics.
a1 = y;
b1 = dy./h - h.*m(1:end-1)/2 - h.*diff(m)/6;
c1 = m/2;
d1 = diff(m)./h/6;
So basically, I know that I must use a parametric spline in order to find the correct points to plot.
I use t = [1,2,3,4,5,6,7,8,9,10,11,12,13]; as my indexes. So, I find the coefficients for the cubic spline polynomial of t vs. x and then find the coefficients for t vs. y, and then I attempt to plot them against each other using values from t in order to plot the parametric curve. However, I keep getting this curve:
I am really not sure why this is occurring.
P.S I know I can use the matlab spline function but when I do, it results in the right cusp being a bit bigger than the other cusps. I want all cusps to be equal in size and the assignment says that we must use a cubic spline.
Any help is greatly appreciated.
I need to extract the isoline coordinates of a 4D variable from a 3D surface defined using a triangulated mesh in MATLAB. I need the isoline coordinates to be a ordered in such a manner that if they were followed in order they would trace the path i.e. the order of the points a 3D printer would follow.
I have found a function that can calculate the coordinates of these isolines (see Isoline function here) but the problem is this function does not consider the isolines to be joined in the correct order and is instead a series of 2 points separated by a Nan value. This makes this function only suitable for visualisation purposes and not the path to follow.
Here is a MWE of the problem of a simplified problem, the surface I'm applying it too is much more complex and I cannot share it. Where x, y and z are nodes, with TRI providing the element connectivity list and v is the variable of which I want the isolines extracted from and is not equal to z.
If anyone has any idea on either.....
A function to extract isoline values in the correct order for a 3D tri mesh.
How to sort the data given by the function Isoline so that they are in the correct order.
.... it would be very much appreciated.
Here is the MWE,
% Create coordinates
[x y] = meshgrid( -10:0.5:10, -10:0.5:10 );
z = (x.^2 + y.^2)/20; % Z height
v = x+y; % 4th dimension value
% Reshape coordinates into list to be converted to tri mesh
x = reshape(x,[],1); y = reshape(y,[],1); z = reshape(z,[],1); v = reshape(v,[],1);
TRI = delaunay(x,y); % Convertion to a tri mesh
% This function calculates the isoline coordinates
[xTows, yTows, zTows] = IsoLine( {TRI,[x, y, z]}, v, -18:2:18);
% Plotting
figure(1); clf(1)
subplot(1,2,1)
trisurf(TRI,x,y,z,v)
hold on
for i = 1:size(xTows,1)
plot3( xTows{i,1}, yTows{i,1}, zTows{i,1}, '-k')
end
hold off
shading interp
xlabel('x'); ylabel('y'); zlabel('z'); title('Isolines'), axis equal
%% This section is solely to show that the isolines are not in order
for i = 1:size(xTows,1)
% Arranging data into colums and getting rid of Nans that appear
xb = xTows{i,1}; yb = yTows{i,1}; zb = zTows{i,1};
xb = reshape(xb, 3, [])'; xb(:,3) = [];
yb = reshape(yb, 3, [])'; yb(:,3) = [];
zb = reshape(zb, 3, [])'; zb(:,3) = [];
subplot(1,2,2)
trisurf(TRI,x,y,z,v)
shading interp
view(2)
xlabel('x'); ylabel('y'); zlabel('z'); title('Plotting Isolines in Order')
axis equal; axis tight; hold on
for i = 1:size(xb,1)
plot3( [xb(i,1) xb(i,2)], [yb(i,1) yb(i,2)], [zb(i,1) zb(i,2)], '-k')
drawnow
end
end
and here is the function Isoline, which I have slightly adpated.
function [xTows, yTows, zTows] = IsoLine(Surf,F,V,Col)
if length(Surf)==3 % convert mesh to triangulation
P = [Surf{1}(:) Surf{2}(:) Surf{3}(:)];
Surf{1}(end,:) = 1i;
Surf{1}(:,end) = 1i;
i = find(~imag(Surf{1}(:)));
n = size(Surf{1},1);
T = [i i+1 i+n; i+1 i+n+1 i+n];
else
T = Surf{1};
P = Surf{2};
end
f = F(T(:));
if nargin==2
V = linspace(min(f),max(f),22);
V = V(2:end-1);
elseif numel(V)==1
V = linspace(min(f),max(f),V+2);
V = V(2:end-1);
end
if nargin<4
Col = 'k';
end
H = NaN + V(:);
q = [1:3 1:3];
% -------------------------------------------------------------------------
% Loop over iso-values ----------------------------------------------------
xTows = [];
yTows = [];
zTows = [];
for k = 1:numel(V)
R = {[],[]};
G = F(T) - V(k);
C = 1./(1-G./G(:,[2 3 1]));
f = unique(T(~isfinite(C))); % remove degeneracies by random perturbation
F(f) = F(f).*(1+1e-12*rand(size(F(f)))) + 1e-12*rand(size(F(f)));
G = F(T) - V(k);
C = 1./(1-G./G(:,[2 3 1]));
C(C<0|C>1) = -1;
% process active triangles
for i = 1:3
f = any(C>=0,2) & C(:,i)<0;
for j = i+1:i+2
w = C(f,q([j j j]));
R{j-i} = [R{j-i}; w.*P(T(f,q(j)),:)+(1-w).*P(T(f,q(j+1)),:)];
end
end
% define isoline
for i = 1:3
X{i} = [R{1}(:,i) R{2}(:,i) nan+R{1}(:,i)]';
% X{i} = [R{1}(:,i) R{2}(:,i)]'; % Changed by Matt
X{i} = X{i}(:)';
end
% plot isoline
if ~isempty(R{1})
% hold on
% H(k) = plot3(X{1},X{2},X{3},Col);
% Added by M.Thomas
xTows{k,1} = X{1};
yTows{k,1} = X{2};
zTows{k,1} = X{3};
end
end
What you will notice is that the isolines (xTows, yTows and zTows) are not in order there "jump around" when plotted sequentially. I need to sort the tows so that they give a smooth plot in order.
I tried to fit a line using 2D points. By using the SVD, I've successfully fit lines. However, in the one case, I failed to fit lines. Please, give me some advise and let me know the reasons.
% Data
X = [487,520.40,553.81,587.22,620.63,654.04,500,533.01,566.02,599.03,642,674.61,707.22,517,552.35,587.71,647,682.35,717.71,522,555.97,589.94,623.91,657.88];
Y = [521,558.20,595.40,632.60,669.80,707.00,533,570.55,608.10,645.66,695,732.90,770.80,564,599.35,634.71,694,729.35,764.71,562,598.68,635.37,672.06,708.75];
% b1*x + b2*y +b3 = 0
M = [X', Y', ones(size(X'))];
[~, ~, V] = svd(M);
B = V(:, 3);
b1 = B(1);
b2 = B(2);
b3 = B(3);
% Draw points
figure(111)
hold on;
plot(X, Y, 'ro');
% Draw line
minX = min(X);
maxX = max(X);
valY_minX = -(b3 + b1*minX) / b2;
valY_maxX = -(b3 + b1*maxX) / b2;
Pt1 = [minX; valY_minX];
Pt2 = [maxX; valY_maxX];
plot([Pt1(1), Pt2(1)], [Pt1(2), Pt2(2)]);
I've got succeed fit the line when I changed to 'V(:, 2)'. Why the second largest eigen value brings the best solution??