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Homework 0: Transformations & OpenGL Warmup
The goal of this warmup assignment is to get comfortable with the
programming environment you will be using for this class and
familiarize yourself with a simple library that we will use for linear
algebra. It's also
an opportunity for a crash course in C++ and OpenGL (if you're not
already familiar with them).
This assignment is only worth 1/4 of the points of a
regular homework assignment. It will not be rigorously graded, but
you are expected to work through and submit the exercises. Please try
to finish this assignment by the end of the first week of classes;
however, there is no firm deadline for this assignment.
Here are a couple tutorials you may want to check out:
The incidental goal is also to have fun with bizarre fractal objects.
IFS are self-similar fractals: a subpart of the object is similar to
the whole. The classic example of an IFS is Barnsley's fern, where
each subpart of the fern is exactly the same as the whole fern. IFS
are described by a set of affine transformations (rotations,
translations, scale, skew, etc.) These transformations capture the
self-similarity of the object. IFS can be defined in any dimension,
and we will play with both two-dimensional and three-dimensional ones.
Formally, an IFS is defined by n affine transformations. Each
transformation fi must be contractive: The
distance between points must be reduced. An attractor of the
IFS is the object such that A = U fi (A).
A is unchanged by the set of transformations: It is a fixed
point.
We can render an IFS by iterating the transform on random input points
from the unit square. We approximate the fixed point by applying the
transformation many times. The algorithm is as follows:
for "lots" of random points (x0, y0)
for k=0 to num_iters
pick a random transform fi
(xk+1, yk+1) = fi(xk, yk)
display a dot at (xk, yk)
To reduce the number of points necessary to make an image of
reasonable quality, probabilities are assigned to each transformation,
instead of choosing a transformation with uniform probability.
Tasks
- Download the provided source code and set up your C++ development
environment. To receive full credit, your homework assignments must
compile and run without errors using gcc/g++. Even if you plan to do
much of your development in another environment, you'll probably still
want to set up gcc so that you can test it before submission. For
interactive display of your IFS, you will use the OpenGL API that uses
graphics hardware for fast rendering of 3D primitives. Note: in some
much older configurations, software emulation might be used, resulting
in slower rendering. Here are some installation & setup notes:
A Makefile is provided for use with either Linux, FreeBSD, MacOSX,
and Cygwin. Once OpenGL is installed, simply type: make .
If your installation is a little different you may need to adjust the
CC, INCLUDE_PATH, and LIB_PATH lines of the Makefile for your
particular installation to point to the right files. Please see the
TA or instructor in office hours if you have trouble setting up your
development environment.
All files implementing OpenGL code should include the OpenGL
header files:
#include <GL/gl.h>
#include <GL/glu.h>
#include <GL/glut.h>
The initial executable should launch an OpenGL window and draw a
cube and you should be able to navigate the scene with the mouse (left
button rotates, middle button translates, right button zooms). Try
this at the command prompt:
./ifs
- Now you're ready to start coding. Write a C++ class
IFS that renders iterated function systems, including the
class declaration (in the header file ifs.h) and the
implementation (ifs.C). The IFS class should include:
- a field to store n, the number of transformations,
- an array/vector of matrices representing the n transformations,
- an array/vector of the corresponding probabilities for choosing a
transformation,
- a paint method which makes appropriate OpenGL calls to draw points
or polygons to the OpenGL window, and
- When you're done, adjust the main function (provided in
main.C) and other code, as necessary.
- Use the linear algebra library for the point and transformation
representations.
- Consider the performance of your programming environment.
How many polygons/points can you render interactively? What
improvements could you make to your code?
Possible Extensions
A small amount of extra credit is available for creative
extensions. Examples include:
x
- design a new IFS --- figure out the transformations and probabilities,
- automatically determine the bounding box of the fractal object,
- change the color scheme,
- implement anti-aliasing,
- experiment with depth-first vs. breadth-first, etc.
Include a short paragraph in your README.txt file describing
your extension(s).
Hints
- The (included)
MersenneTwister random number generator can be used to generate
random integers and random floating point numbers.
- To debug your code, set the number of iterations to one. This
will allow you to check that you got the transformations right.
- Be careful, arrays are indexed from 0 to n-1 in
C++. Reading beyond the bounds of the array will probably result in a
segmentation fault.
- Use assert() to check function pre-conditions, array
indices, etc.
- To perform transformations in OpenGL, read about the Modelview
matrix stack and the OpenGL commands glMatrixMode(),
glPushMatrix(), glPopMatrix(), and
glMultMatrix() in the
OpenGL Programming Guide, Chapter 3.
- Linear Algebra Library (vectors.h & matrix.h & matrix.cpp)
Linear algebra support for floating point vectors with 3 and 4
elements (Vec3f and Vec4f) and 4x4 floating point
matrices (Matrix). For this assignment, the void
Matrix::Transform(Vec3f &v) function will be handy.
- Parsing code for command-line arguments and input files
(argparser.h)
The program takes a number of command line arguments to specify the
input file (-input), number of points (-points),
number of iterations (-iters), and window height & width
(-size). Your program should render points by default, or
cubes if -cubes is specified. Examples are shown below.
Code to parse input files and command line arguments is provided.
- OpenGL and main code (main.cpp, ifs.h, ifs.cpp, glCanvas.h,
glCanvas.cpp, camera.h, camera.cpp)
OpenGL programs can be tricky to set up from scratch. This base code
should do all that work for you.
- Makefile for g++
On the command line simply type make . To force a re-build
of all object files, type make clean first.
- Data files (fern.txt, dragon.txt, sierpinski_triangle.txt, and giant_x.txt)
The input data for an IFS is a file which contains n,
the number of transforms, followed by the probability of choosing each
transform and a 4x4 floating point matrix representation of the
transform.
Sample Results
./ifs -input sierpinski_triangle.txt -points 10000 -iters 0 -size 200
./ifs -input sierpinski_triangle.txt -points 10000 -iters 1 -size 200
./ifs -input sierpinski_triangle.txt -points 10000 -iters 2 -size 200
./ifs -input sierpinski_triangle.txt -points 10000 -iters 3 -size 200
./ifs -input sierpinski_triangle.txt -points 10000 -iters 4 -size 200
./ifs -input sierpinski_triangle.txt -points 10000 -iters 30 -size 200
./ifs -input fern.txt -points 50000 -iters 30 -size 400
./ifs -input giant_x.txt -points 10000 -size 400 -iters 0
./ifs -input giant_x.txt -points 10000 -size 400 -iters 1
./ifs -input giant_x.txt -points 10000 -size 400 -iters 2
./ifs -input giant_x.txt -points 10000 -size 400 -iters 3
./ifs -input giant_x.txt -points 10000 -size 400 -iters 4
Now here's an example using the -cubes argument. Each cube
represents the bounding box of the cloud of random 3D points that are
transformed in each iteration. There are a couple different ways to
implement this rendering mode.
./ifs -input giant_x.txt -size 400 -iters 0 -cubes
./ifs -input giant_x.txt -size 400 -iters 1 -cubes
./ifs -input giant_x.txt -size 400 -iters 2 -cubes
./ifs -input giant_x.txt -size 400 -iters 3 -cubes
./ifs -input giant_x.txt -size 400 -iters 4 -cubes
Please read the Homework information page again before submitting.
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