Title: CS1371 Introduction to Computing for Engineers
1CS1371Introduction to Computing for Engineers
2Administrivia
- First exam Histogram
- Make up exam will be next Tuesday. Should have
contacted me and David Smith by now. - HW7 not there yet, will be soon, due as usual.
- Reading
- Still Plotting, Smith Ch. 15
3Plotting Multiple Curves (contd)
- Or we could do
- Or we could do this
- What if we did this?
- Do a help plot for more markers.
- How could we see the data points more distinctly?
gtgt plot(X,Y1,X,Y2,X,Y3,X,Y4)
gtgt Z Y1Y2Y3Y4 gtgt plot(X,Z)
gtgt plot(X, Z, 'o')
4Example of Log Plots
- Using a log scale can reveal large dynamic ranges
gtgt xlinspace(.1,10,1000) gtgt damp0.05 gtgt
y1./sqrt((1-x.2).2 (2.damp.x).2) gtgt
plot(x,y) gtgt semilogx(x,y) gtgt loglog(x,y)
Describes the behavior of vibrating systems
5Subplot Command
- There are times when it is better to create
several smaller plots arranged in some kind of
grid subplot(m,n,k) does this - mrows, ncolumns in the grid
- kcurrent focus (numbered row-wise)
- Lets define a 2x3 subplot grid for
subplot(2,3,1) with the focus on the first plot.
3
1
2
3
2
6
4
5
6On Your Own
X00.550 Y5x.2 subplot(2,2,1), plot(X,Y),
title(Polynomial Linear/Linear), ...
ylabel(y), grid subplot(2,2,2), semilogx(X,Y),
title(Polynomial Log/Linear), ...
ylabel(y), grid subplot(2,2,3), semilogy(X,Y),
title(Polynomial Linear/Log), ...
ylabel(y), grid subplot(2,2,4), loglog(X,Y),
title(Polynomial Log/Log), ... ylabel(y),
grid
7Specialized 2D Plots
- There are a number of other specialized 2D plots
- area(x,y) builds a stacked area plot
- pie() creates a pie chart (with options)
- bar(x,y) creates a vertical bar chart (with many
options) - stairs(x,y) similar to bar() but shows only
outline - errorbar(x,y,e) plots x vs y with error bars
defined by e - scatter(x,y) creates a scatter plot with options
for markers - semilogx(x,y) plots x vs y with x using a log
scaling - semilogy(x,y) plots x vs y with y using a log
scaling - loglog(x,y) plots x vs y using log scale for
both axes - And many others (explore these yourself you may
find a good use in a later course)
8Plotting a Function
- Suppose have some cool function as function of
ONE variable. - Function sindub sin2(x)
- Takes sin of 2x
- Sindub sin(2x)
- Fplot(sin2(t),150, r)
9Doing fplot
- Function sindub sin2(x)
- Takes sin of 2x
- Sindub sin(2x)
- fplot(sin2(t),150, r)
103D Plotting
- Plotting in 3D is where Matlabs power really
becomes apparent! - Matlab defines a number of different kinds of 3D
plots but you will probably find 3 or 4 to be the
most useful - x,y,z 3D line plot (plot3( ))
- mesh plot
- surface plot
- contour plot
- combo surface/mesh with contour
- The surface plotting can be applied to create
realistic 3D objects by defining and plotting
their exterior surfaces! - We can only touch lightly on this vast area of
Matlab
11Anatomy of a 3D Plot
- There are MANY options for plotting in 3D but we
will consider only the basics - Plotting a curve in 3D plot3(x,y,z)
- Plotting a surface, zf(x,y), in 3D
- There are also several other plotting topics that
we will not cover or discuss in class (but you
might find interesting to explore on your own) - ribbon plots
- quiver plots (showing vectors)
- volume plots
- advanced colormap use
122D Plots vs 3D Line Plots
- Actually, every 2D plot is simply a 3D plot
without the 3rd dimension being specified.
gtgt clf gtgt x00.12.pi gtgt plot(x,sin(x))
Rotate 3D button experiment with how it works
13Do plot and rotate
- clf
- gtgt x00.12.pi
- gtgt plot(x,sin(x))
143D Line Plot
- This is the simplest (and least useful) 3D plot
and is really just a generalization of the 2D
function
gtgt x00.13.pi gtgt z1sin(x) gtgt
z2sin(2.x) gtgt z3sin(3.x) gtgt
y1zeros(size(x)) gtgt y3ones(size(x)) gtgt
y2y3./2 gtgt plot3(x,y1,z1,'r',x,y2,z2,'b',x,y3,z3
,'g') gtgt grid on gtgt xlabel('x-axis'),
ylabel('y-axis'), zlabel('z-axis')
153D Line Plot (2)
- These examples may be a little more useful
gtgt clf gtgt turns40.pi gtgt thetalinspace(0,turns,
4000) gtgt xcos(theta).(turns-theta)./turns gtgt
ysin(theta).(turns-theta)./turns gtgt
ztheta./turns gtgt plot3(x,y,z) gtgt grid on gtgt
text(0.5,0.5,0.75,'Here is a piece of text!')
gtgt theta00.110.pi gtgt plot3(sin(theta),cos(the
ta),theta) gtgt grid on
163D Surface Plots
- It is often desirable to plot functions of the
form zf(x,y) - for each (x,y), we can compute a value for z
- this defines a surface in 3D space
- If we can define (x,y) at regular intervals,
Matlab provides powerful ways to plot the
resulting function as a grid or surface in 3D. - There are tools in Matlab to handle the situation
with (x,y) defined at irregular intervals, but we
won't consider them in this course. - We will look into how colors can be employed to
add the equivalent of a 4th dimension
17Defining the (x,y) Values
- We need a way to create the range of (x,y) values
needed to compute f(x,y)
This won't work because we need all values of y
for each value of x and vice versa to evaluate
function over entire region shown
x -3 -2 -1 0 1 2 3 y -3 -2 -1 0
1 2 3 zf(x,y)
This works corresponding elements of xx yy
contain the x and y coordinates to be used for
f(x,y) at that point
xx -3 -2 -1 0 1 2 3 -3
-2 -1 0 1 2 3 -3 -2
-1 0 1 2 3 -3 -2 -1
0 1 2 3 -3 -2 -1 0
1 2 3 -3 -2 -1 0 1
2 3 -3 -2 -1 0 1 2
3 yy -3 -3 -3 -3 -3 -3 -3
-2 -2 -2 -2 -2 -2 -2 -1
-1 -1 -1 -1 -1 -1 0 0
0 0 0 0 0 1 1 1
1 1 1 1 2 2 2 2
2 2 2 3 3 3 3 3
3 3 zf(xx,yy)
NOTExx varies along ROWS while yy varies along
COLUMNS
18The meshgrid() Function
- Matlab provides a function to compute these
arrays
gtgt x-3.53.5 gtgt y-2.52.5 gtgt
xx,yymeshgrid(x,y) xx -3.5 -2.5 -1.5
-0.5 0.5 1.5 2.5 3.5 -3.5 -2.5 -1.5
-0.5 0.5 1.5 2.5 3.5 -3.5 -2.5 -1.5
-0.5 0.5 1.5 2.5 3.5 -3.5 -2.5 -1.5
-0.5 0.5 1.5 2.5 3.5 -3.5 -2.5 -1.5
-0.5 0.5 1.5 2.5 3.5 -3.5 -2.5 -1.5
-0.5 0.5 1.5 2.5 3.5 yy -2.5 -2.5
-2.5 -2.5 -2.5 -2.5 -2.5 -2.5 -1.5 -1.5
-1.5 -1.5 -1.5 -1.5 -1.5 -1.5 -0.5 -0.5
-0.5 -0.5 -0.5 -0.5 -0.5 -0.5 0.5 0.5
0.5 0.5 0.5 0.5 0.5 0.5 1.5 1.5
1.5 1.5 1.5 1.5 1.5 1.5 2.5 2.5
2.5 2.5 2.5 2.5 2.5 2.5
NOTE 1xx varies along ROWS while yy
varies along COLUMNS
NOTE 2For any (i, j), the value in xx is the x
coordinate, while the value in yy is the y
coordinate xx(3,1) -3.5 yy(3,1) -0.5 So
(x,y) (-3.5, -0.5)
NOTE 3Matlab calls these arrays "plaids"
NOTE 4We can use array math to efficiently
compute the z values when zf(x,y)
19Calculation of f(x,y) the Hard Way
- In this case we will plot z (x2 y2) over the
range -3 ? x ? 3 and -3 ? y ? 3
Element-by-element Calculation of z f(x,y)
gtgt nclength(x) number of columns in z gtgt
nrlength(y) number of rows in z gtgt
zzeros(nr,nc) initialize z (for speed) gtgt for
kc1nc for kr1nr z(kr,kc)
x(kc).2 y(kr).2 end end gtgt
mesh(xx,yy,z)
NOTEIt can be very tricky to keep track of the
row and column indices in this kind of
calculation
20Calculation of f(x,y) the Matlab Way
- In this case we use Matlabs scalar operations
gtgt x-33 gtgt y-33 gtgt xx,yymeshgrid(x,y) xx
3 -2 -1 0 1 2 3
-3 -2 -1 0 1 2 3 -3
-2 -1 0 1 2 3 -3 -2
-1 0 1 2 3 -3 -2 -1
0 1 2 3 -3 -2 -1 0
1 2 3 -3 -2 -1 0 1
2 3 yy -3 -3 -3 -3 -3 -3
-3 -2 -2 -2 -2 -2 -2 -2
-1 -1 -1 -1 -1 -1 -1 0
0 0 0 0 0 0 1 1
1 1 1 1 1 2 2 2
2 2 2 2 3 3 3 3
3 3 3 gtgt zzxx.2 yy.2 gtgt
mesh(xx,yy,zz)
NOTEMatlab's array instructions make this a
deceptively simple calculation for all values at
once
21Go to Demo script
22Key Concepts for zf(x,y) Plots
- 3D plotting introduces several key concepts
- Meshes versus surfaces
- Hidden line removal
- Pedestals and contours
- Color maps and pseudo-coloring
- Viewpoints and camera control (advanced!)
- Shading and lighting (advanced)
- The following figures demonstrate these concepts,
but you are encouraged to check this out for
yourself (using Matlabs graphic brings out the
real fun in using this powerful software!).
23Exploring Hidden Line Removal
- This uses an interesting built-in function
sphere( ) - Hidden lines
- ON shows white inside mesh
- OFF shows transparent mesh
X,Y,Z sphere(12) subplot(1,2,1) mesh(X,Y,Z),
title('Figure 26.5a Opaque') hidden on axis
square off subplot(1,2,2) mesh(X,Y,Z),title('Fig
ure 26.5b Transparent') hidden off axis square
off
24Let's Explore the mesh( ) Function
- We'll use peaks( ) to create a zf(x,y) function
that is interesting and shows off the 3D plotting - Note you should check help peaks and help mesh
and also the textbook for further details on
these functions
gtgt x,y,zpeaks(30) gtgt mesh(x,y,z) gtgt axis
tight gtgt xlabel('x-axis') gtgt ylabel('y-axis') gtgt
zlabel('z-axis')
SuggestionTry using hidden off and hidden on to
see what happens.
25Demo
26Exploring meshc Plots
- meshc( ) adds a contour plot directly below the
mesh - helps visualize the contours
- can locate the peaks and dips
gtgt x,y,zpeaks(30) gtgt meshc(x,y,z) gtgt axis
tight gtgt xlabel('x-axis') gtgt ylabel('y-axis') gtgt
zlabel('z-axis')
HintIf you just finished the previous example,
you need only type in the new meshc( ) command.
27Exploring meshz Plots
- This special variation allows you to emphasize
the zero plane in the mesh plot
gtgt x,y,zpeaks(30) gtgt meshz(x,y,z) gtgt axis
tight gtgt xlabel('x-axis') gtgt ylabel('y-axis') gtgt
zlabel('z-axis')
28Exploring waterfall Plots
- This is another variation on the mesh plot and
can also be useful in some special cases
gtgt x,y,zpeaks(30) gtgt waterfall(x,y,z) gtgt axis
tight gtgt xlabel('x-axis') gtgt ylabel('y-axis') gtgt
zlabel('z-axis')
29Let's Explore the surf( ) Function
- So far we have only been able to plot meshes to
represent the surface - can hide hidden lines to clarify the surface
shape - still appears as a wireframe-like shape
- Matlab provides a function that will fill in the
mesh with facets (surfaces with 3 or 4 corners
but not necessarily plane surfaces) - we'll see that these can produce very realistic
appearing surfaces in 3D - can control appearance of mesh
- can change color mapping to reveal other
information - can add lighting
30Exploring surf Plots (shading faceted)
- The basic function uses the default shading
faceted and this shows the mesh
gtgt x,y,zpeaks(30) gtgt surf(x,y,z) gtgt axis
tight gtgt xlabel('x-axis') gtgt ylabel('y-axis') gtgt
zlabel('z-axis')
31Exploring surf Plots (shading flat)
- shading flat will eliminate the mesh and leave
the facets colored with a constant color value
gtgt x,y,zpeaks(30) gtgt surf(x,y,z) gtgt shading
flat gtgt axis tight gtgt xlabel('x-axis') gtgt
ylabel('y-axis') gtgt zlabel('z-axis')
32Exploring surfc Plots (shading interp)
- surfc acts much like meshc with a contour plot
drawn below the surface - shading interp interpolates color over each facet
gtgt x,y,zpeaks(30) gtgt surfc(x,y,z) gtgt shading
interp gtgt axis tight gtgt xlabel('x-axis') gtgt
ylabel('y-axis') gtgt zlabel('z-axis')
NOTEshading interp can take time to execute and
the figure may cause plotting problems
33Changing the Viewing Direction
- You can change the orientation of the object
- Viewing direction view(az,el) or you can use
the rotate3d button on the view toolbar on the
figure window menu - Camera direction this is best controlled from
the camera toolbar on the figure window menu
z
viewpoint
view(-45,60)
y
elev
x
azimuth
34Adding a Colorbar
- You can use the colorbar command to add a color
bar that defines the color used in the plot. Use
help colorbar to find out what the other options
are
NOTE You should check out the instructions on
how to use the Property Editor and the tools in
the Figure window to interactively add text and
labels to various parts of this 3D graph.
35Using Color as a 4th Dimension
- Matlab associates a colormap with each figure
window - this is a 3 column array in which columns 1-3
control the Red, Blue Green colors (0-1 range) - each row defines a specific color
- rows are limited by the color display
capabilities of the computer - these, along with a few fixed colors, are the
colors Matlab will use in the figure window (each
figure window has a separate colormap) - Matlab predefines a number of useful colormaps
- JET, HSV, GRAY, HOT, COOL, BONE, COPPER, PINK,
FLAG, PRISM - see help graph3d for more information and other
colormaps - use colormap hsv or colormap(hsv) to change
- colormap default restores the colormap to default
values - use the colorbar command to display the color bar
by itself or alongside a plot (see help)
36Using Color as a 4th Dimension (2)
- Matlab uses pseudo-color to change the color in
a mesh or surf plot - colors can be based on the z values (default)
- you can specify the color variable in mesh() and
surf() - Use caxis(cmin cmax) to define the max and min
values that are mapped to the colormap
gtgt caxis(-5 5) gtgt colorbar
gtgt caxis(-50 50) gtgt colorbar
37Using Color as a 4th Dimension (3)
- mesh() and surf() can accept a "color" argument
that defines the color used over the plaid.
gtgt Cdel2(z) compute Laplacian gtgt
surf(x,y,z,C) gtgt axis tight gtgt colorbar
gtgt caxis('auto') gtgt surf(x,y,z,y) gtgt axis
tight gtgt ylabel('y-axis')
This shows curvature of the surface as the color
variable.
Here we have used the y values as the color
variable.
38Contour Plots
- Matlab provides several functions to draw
contours - contour() draws simple contour map with N
intervals - contourf() draws a contour with filled contours
- contour3() draws a contour map in 3D
x,y,zpeaks(30) contourf(x,y,z,10)
colorbar xlabel('x-axis') ylabel('y-axis')
x,y,zpeaks(30) contour(x,y,z,10)
colorbar xlabel('x-axis') ylabel('y-axis')
NOTE See textbook for other options.
39Example
- Here is a simple example to illustrate 3D
plotting - it is the sinc function (sin(r)/r) where
rradius - we need to add eps to avoid inf when dividing by
zero
xx,yymeshgrid(-4.pipi./54.pi)
Rsqrt(xx.2 yy.2)eps radius
zzsin(R)./R surf(xx,yy,zz) axis tight
Question How could you handle a situation when
the data are not defined on a regular grid (when
the points are unevenly spaced)?
40And finally.
41Do Globe