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Analytical Plotting with Symbolic Math Toolbox

Symbolic Math Toolbox™ provides analytical plotting of mathematical expressions without explicitly generating numerical data. These plots can be in 2-D or 3-D as lines, curves, contours, surfaces, or meshes.

These examples feature the following graphics functions that accept symbolic functions, expressions, and equations as inputs:

  • fplot

  • fimplicit

  • fcontour

  • fplot3

  • fsurf

  • fmesh

  • fimplicit3

Plot Explicit Functions y=f(x) Using fplot

Plot the function sin(exp(x)).

syms x

Plot the trigonometric functions sin(x), cos(x), and tan(x) simultaneously.


Plot a Function Defined by y=f(x,a) for Various Values of a

Plot the function sin(exp(x/a)) for a=1,2, and 4.

syms x a
expr = sin(exp(x/a));
legend show

Plot the Derivative and Integral of a Function

Plot a function f(x)=x(1+x)+2, its derivative df(x)/dx, and its integral f(x)dx.

syms f(x)
f(x) = x*(1 + x) + 2
f(x) = xx+1+2
f_diff = diff(f(x),x)
f_diff = 2x+1
f_int = int(f(x),x)
f_int = 


legend({'$f(x)$','$df(x)/dx$','$\int f(x)dx$'},'Interpreter','latex','FontSize',12)

Plot a Function y=g(x0,a) with a as the Horizontal Axis

Find the x0 that minimizes a function g(x,a) by solving the differential equation dg(x,a)/dx=0.

syms g(x,a);
g(x,a) = a*x*(a + x) + 2*sqrt(a)
g(x, a) = 2a+axa+x
x0 = solve(diff(g,x),x)
x0 = 


Plot the minimum value of g(x0,a) for a from 0 to 5.

fplot(g(x0,a),[0 5])
title('Minimum Value of $g(x_0,a)$ Depending on $a$','interpreter','latex')

Plot an Implicit Function f(x,y)=c Using fimplicit

Plot circles defined by x2+y2=r2 with radius r as the integers from 1 to 10.

syms x y
r = 1:10;
fimplicit(x^2 + y^2 == r.^2,[-10 10])
axis square;

Plot Contours of a Function f(x,y) Using fcontour

Plot contours of the function f(x,y)=x3-4x-y2 for contour levels from –6 to 6.

syms x y f(x,y)
f(x,y) = x^3 - 4*x - y^2;
fcontour(f,[-3 3 -4 4],'LevelList',-6:6);
title 'Contour of Some Elliptic Curves'

Plot an Analytic Function and Its Approximation Using Spline Interpolant

Plot the analytic function f(x)=xexp(-x)sin(5x)-2.

syms f(x)
f(x) = x*exp(-x)*sin(5*x) -2;

Create a few data points from the analytic function.

xs = 0:1/3:3;
ys = double(subs(f,xs));

Plot the data points and the spline interpolant that approximates the analytic function.

hold on
plot(xs,ys,'*k','DisplayName','Data Points')
fplot(@(x) spline(xs,ys,x),[0 3],'DisplayName','Spline interpolant')
grid on
legend show
hold off

Plot Taylor Approximations of a Function

Find the Taylor expansion of cos(x) near x=0 up to 5th and 7th orders.

syms x
t5 = taylor(cos(x),x,'Order',5)
t5 = 


t7 = taylor(cos(x),x,'Order',7)
t7 = 


Plot cos(x) and its Taylor approximations.

hold on;
fplot([t5 t7],'--')
axis([-4 4 -1.5 1.5])
title('Taylor Series Approximations of cos(x) up to 5th and 7th Order')
legend show
hold off;

Plot the Fourier Series Approximation of a Square Wave

A square wave of period 2π and amplitude π/4 can be approximated by the Fourier series expansion


Plot a square wave with period 2π and amplitude π/4.

syms t y(t)
y(t) = piecewise(0 < mod(t,2*pi) <= pi, pi/4, pi < mod(t,2*pi) <= 2*pi, -pi/4);

Plot the Fourier series approximation of the square wave.

hold on;
n = 6;
yFourier = cumsum(sin((1:2:2*n-1)*t)./(1:2:2*n-1));
hold off

The Fourier series approximation overshoots at a jump discontinuity and the "ringing" does not die out as more terms are added to the approximation. This behavior is also known as the Gibbs phenomenon.

Plot a Parametric Curve (x(t),y(t),z(t)) Using fplot3

Plot a helix that is defined by (sin(t),cos(t),t/4) for t from –10 to 10.

syms t
fplot3(sin(t),cos(t),t/4,[-10 10],'LineWidth',2)
view([-45 45])

Plot a Surface Defined by z=f(x,y) Using fsurf

Plot a surface defined by log(x)+exp(y). Analytical plotting using fsurf (without generating numerical data) shows the curved areas and asymptotic regions near x=0.

syms x y
fsurf(log(x) + exp(y),[0 2 -1 3])

Plot a Multivariate Surface (x(u,v),y(u,v),z(u,v)) Using fsurf

Plot a multivariate surface defined by




where f(u)=exp(-u2/3)sin(u)+3/2.

Set the plot interval of u from –5 to 5 and v from 0 to 2π.

syms f(u) x(u,v) y(u,v) z(u,v)
f(u) = sin(u)*exp(-u^2/3)+1.5;
x(u,v) = u;
y(u,v) = f(u)*sin(v);
z(u,v) = f(u)*cos(v);
fsurf(x,y,z,[-5 5 0 2*pi])

Plot a Multivariate Surface (x(s,t),y(s,t),z(s,t)) Using fmesh

Plot a multivariate surface defined by




where r=8+sin(7s+5t). Show the plotted surface as meshes by using fmesh. Set the plot interval of s from 0 to 2π and t from 0 to π.

syms s t
r = 8 + sin(7*s + 5*t);
x = r*cos(s)*sin(t);
y = r*sin(s)*sin(t);
z = r*cos(t);
fmesh(x,y,z,[0 2*pi 0 pi],'Linewidth',2)
axis equal

Plot an Implicit Surface f(x,y,z)=c Using fimplicit3

Plot the implicit surface 1/x2-1/y2+1/z2=0.

syms x y z
f = 1/x^2 - 1/y^2 + 1/z^2;

Plot the Contours and Gradient of a Surface

Plot the surface sin(x)+sin(y)-(x2+y2)/20 using fsurf. You can show the contours on the same graph by setting 'ShowContours' to 'on'.

syms x y
f = sin(x)+sin(y)-(x^2+y^2)/20
f = 



Next, plot the contours on a separate graph with finer contour lines.

fcontour(f,[-5 5 -5 5],'LevelStep',0.1,'Fill','on')

Find the gradient of the surface. Create 2-D grids using meshgrid and substitute the grid coordinates to evaluate the gradient numerically. Show the gradient using quiver.

hold on
Fgrad = gradient(f,[x,y])
Fgrad = 


[xgrid,ygrid] = meshgrid(-5:5,-5:5);
Fx = subs(Fgrad(1),{x,y},{xgrid,ygrid});
Fy = subs(Fgrad(2),{x,y},{xgrid,ygrid});
hold off

See Also