Understanding the Discrete Cosine Transform in Java
Java Programming Notes # 2444
- Preface
- General Background Information
- Preview
- Discussion and Sample Code
- Run the Programs
- Summary
- What's Next?
- References
- Complete Program Listings
Preface
This lesson is one in a series designed to teach you about the inner workings of data and image compression. The first lesson in the series was Understanding the Lempel-Ziv Data Compression Algorithm in Java. The previous lesson was Understanding the Huffman Data Compression Algorithm in Java.
JPEG image compression
One of the objectives of the series is to teach you about the inner workings of JPEG image compression. According to Wikipedia,
"... JPEG (pronounced jay-peg) is a commonly used standard method of lossy compression for photographic images. ... The name stands for Joint Photographic Experts Group. JPEG itself specifies only how an image is transformed into a stream of bytes, but not how those bytes are encapsulated in any particular storage medium. A further standard, created by the Independent JPEG Group, called JFIF (JPEG File Interchange Format) specifies how to produce a file suitable for computer storage and transmission (such as over the Internet) from a JPEG stream. ... JPEG/JFIF is the most common format used for storing and transmitting photographs on the World Wide Web."
Entropy encoding
Without getting into the technical details at this point, let me tell you that one of the central components of JPEG compression is entropy encoding. Huffman encoding, which was the primary topic of the previous lesson is a common form of entropy encoding.
The Discrete Cosine Transform
Another central component of JPEG compression is the Discrete Cosine Transform, which is the primary topic of this lesson. Again, according to Wikipedia,
"The discrete cosine transform (DCT) is a Fourier-related transform similar to the discrete Fourier transform (DFT), but using only real numbers. It is equivalent to a DFT of roughly twice the length, operating on real data with even symmetry ..."
In order to understand JPEG ...
In order to understand JPEG image compression, you must understand Huffman encoding, the Discrete Cosine Transform, and some other topics as well, such as spectral re-quantization. I plan to teach you about the different components of JPEG in separate lessons, and then to teach you how they work together to produce "the most common format used for storing and transmitting photographs on the World Wide Web"
Viewing tip
You may find it useful to open another copy of this lesson in a separate browser window. That will make it easier for you to scroll back and forth among the different listings and figures while you are reading about them.
Supplementary material
I recommend that you also study the other lessons in my extensive collection of online Java tutorials. You will find those lessons published at Gamelan.com. However, as of the date of this writing, Gamelan doesn't maintain a consolidated index of my Java tutorial lessons, and sometimes they are difficult to locate there. You will find a consolidated index at www.DickBaldwin.com.
In preparation for understanding the material in this lesson, I also recommend that you also study the lessons referred to in the References section.
General Background Information
Although the Discrete Cosine Transform (DCT) may be "similar to the discrete Fourier transform", it is not a Discrete Fourier Transform (DFT) as described in my earlier lesson entitled Fun with Java, How and Why Spectral Analysis Works. There are some major differences between DFT and DCT. Nonetheless, the DCT is very interesting from a technical viewpoint and is a central component of JPEG image compression.
The DFT and symmetrical real data
To get started, I'm going to show you the results of applying the DFT to symmetrical real data. In the earlier lesson entitled Spectrum Analysis using Java, Forward and Inverse Transforms, Filtering in the Frequency Domain, I introduced you to a program named Dsp035, which:
"... illustrates the reversible nature of the Fourier transform. This program transforms a real time series into a complex spectrum, and then reproduces the real time series by performing an inverse Fourier transform on the complex spectrum. This is accomplished using a DFT algorithm."
The program named Dsp043
Listing 11 contains a complete listing of a program named Dsp043, which is designed to demonstrate that the imaginary part of the Fourier transform of a real symmetrical time series is all zeros if the origin is properly located.
(The code in this program is very similar to the code in the program named Dsp035 that I explained earlier, so I won't repeat that explanation in this lesson. Rather, I will just explain the results of executing the program named Dsp043.)
The program output
Figure 1 shows the results of executing the program named Dsp043 shown in Listing 11.
Figure 1 |
The first graph at the top of Figure 1 shows a 300-sample symmetrical time series. Note that this time series is symmetrical about its center point.
The spectral results
The DFT was applied to this time series. The next three graphs going down the page in Figure 1 show the spectral results of applying the DFT to the time series. The three spectral graphs are plotted from a frequency of zero to the sampling frequency.
(Recall that the Nyquist folding frequency occurs half way between zero and the sampling frequency, and that the spectrum shown above the folding frequency is the mirror image of the spectrum below the folding frequency. Therefore, we are usually interested only in the spectral results below the folding frequency. Therefore, you can ignore the right half of the spectral graphs.)
What do the five graphs show?
The five graphs in Figure 1 show (in order from top to bottom):
- The 300-sample symmetrical real time series to which the DFT was applied.
- The real part of the output from the DFT.
- The imaginary part of the output from the DFT.
- The magnitude of the output from the DFT.
- The result of applying an inverse DFT to the spectral data in order to reconstruct the original time series from the spectral data.
The important points
The most important points illustrated by Figure 1 are:
- The time series is purely real.
- The time series is symmetrical about its center point.
- The imaginary part of the spectrum has all zero values.
Therefore, Figure 1 demonstrates that the imaginary part of the Fourier transform of a real symmetrical time series is all zeros if the origin is properly located. This is important because I will use that fact to develop the rationale for the Discrete Cosine Transform, and why it works the way that it does.
Equations for the DFT
Referring back to the equations in my earlier lesson, you can see that the real part of the output from the DFT results from a sum of products involving a cosine term, and that the imaginary part of the output results from a sum of products involving a sine term.
Can sometimes avoid the sine computation
When computing the DFT, if we already know that the input time series is symmetrical and that the imaginary part of the output will be zero, we can simply forego the computation of the imaginary part that involves the sine term, thereby reducing the computational requirements.
Can make the cosine computation less burdensome
In addition, if we know that the input time series is symmetrical, we can reformulate the computation of the real part of the transform involving the cosine term wherein we perform the computation on one-half of the time series only and then double the result. Thus for a symmetrical time series having a length of 2N+1 samples, we can reduce the number of real-part computations to N+1.
How does the DCT work?
Basically the DCT works by implicitly doubling the length of the input time series by concatenating it to a mirror image of itself. The concatenation of the original time series to the mirror image results in a symmetrical time series.
(You don't actually see the doubling of the time series. Rather, the doubling is implicit in the formulation of the equations for the DCT.)
Because the new time series is symmetrical, it is known in advance that if we were to perform a DFT on the new double-length time series, the imaginary part would be zero. Thus, it is also known in advance that we can forego the computation of the imaginary part that uses the sine term in the DFT.
No need to double the number of cosine computations
In addition, because the new double-length time series is symmetrical, we don't need to double the number of real-part computations involving the cosine term (but we will have to reformulate the real-part computation relative to a straight DFT computation).
The definition of the DCT
The definition of the DCT is very similar to the definition of the DFT but the computation of the imaginary part using the sine term simply isn't part of the definition.
In addition to eliminating the computation of the imaginary part, the definition of the DCT also reformulates the DFT to take advantage of the symmetry of the time series relative to the computation of the real part using the cosine term.
Let's see some equations
Rather than to deal with the somewhat difficult task of producing equations in this HTML document, I have provided three separate references that contain the equations for the DCT. The equations in these three references are essentially the same (to within a scale factor).
I elected to formulate my DCT program for this lesson using the one-dimensional form of the DCT equations that you will find at National Taiwan University - DSP Group - Discrete Cosine Transform.
(The next lesson in this series will deal with the two-dimensional formulation of the DCT.)
No sine term
If you examine those equations, you will find that there is no sine term in either the forward or the inverse DCT. Only the cosine term is included, and it is included in such a way as to take advantage of the symmetry of the double-length time series.
(While you are at the site mentioned above, also note that the author provides an explanation of the doubling of the length of the time series in order to produce a new symmetrical time series for which the Fourier Transform is guaranteed to have a zero imaginary part.)
The forward Discrete Cosine Transform (DCT) code
Listing 12 provides a class named ForwardDCT01, which is an implementation of the forward DCT equation discussed above.
The code for the forward DCT is amazingly simple, considering what it is capable of accomplishing.
(Perhaps the simplicity of the code had something to do with why the DCT was selected to be a standard part of JPEG image compression.)
The transform method
The static method named transform belonging to the class named ForwardDCT01 performs a forward Discreet Cosine Transform (DCT) on an incoming time series and returns the DCT spectrum.
Input and output
The incoming parameters are:
- double[] x - incoming real data
- double[] y - outgoing real data
Thus, the input time series is provided by way of a double[] array object referred to by x. The transform method populates an output double[] array object referred to by y.
(Insofar as practical, the variable names and terms used in the transform method match the terms used in the equations discussed earlier.)
Knowing the equation that the method is designed to implement, you should find the code in Listing 12 to be straightforward.
The inverse Discrete Cosine Transform (DCT) code
Listing 13 provides the code for a class named InverseDCT01, which is an implementation of the inverse DCT equation discussed earlier.
The static method named transform of the InverseDCT01 class performs an inverse Discreet Cosine Transform (DCT) on an incoming DCT spectrum and returns the DCT time series.
(As before, insofar as practical, the variable names and terms used in the method match the terms used in the equations discussed earlier.)
Input and output
Incoming parameters to the method are:
- double[] y - incoming real data
- double[] x - outgoing real data
Thus, the DCT spectrum to be transformed is provided by the user in an array object of type double[] referred to by y. The method named transform populates an array object of type double[] referred to by x with the time-series resulting from the transform.
As before, you should find the code in Listing 13 to be straightforward.
Preview
The program named Dsp042
The program named Dsp042 illustrates the application of the forward and inverse Discrete Cosine Transform (DCT) to three different waveforms, all concatenated into a single time series. This program is very similar to Dsp035, which was explained in the earlier lesson entitled Spectrum Analysis using Java, Forward and Inverse Transforms, Filtering in the Frequency Domain.
The program named Dsp035
The program named Dsp035 applies the full forward and inverse Discrete Fourier Transform (DFT) to the same three waveforms producing the output shown in Figure 2.
Figure 2 |
Figure 2 does not contain new material. You saw a figure similar to this one in the earlier lesson.
What do the five graphs show?
The five graphs in Figure 2 show the following information, in order from top to bottom:
- A 256-sample input time series consisting of three waveforms in sequence with values of zero between the waveforms. (Note that even though the display is 300 points wide, the actual data being plotted on each of the five graphs ends at 256 samples.)
- The real part of the frequency spectrum produced by the forward DFT, plotted from a frequency of zero on the left to the sampling frequency (twice the Nyquist folding frequency) on the right.
- The imaginary part of the frequency spectrum on the same scale as the real part of the transform.
- The magnitude of the frequency spectrum, also on the same scale.
- The result of applying the inverse DFT to the spectral data in order to reconstruct the original time series from the spectral data.
The most important thing to note in Figure 2 is that the imaginary part of the DFT output is clearly not zero for this time series input. The time series output in the bottom graph can only be produced by performing a complex transform on the real and imaginary parts of the frequency spectrum.
Back to the program named Dsp042
The material shown in Figure 3, which is the output produced by the program named Dsp042 is new to this lesson.
Figure 3 |
The three graphs in Figure 3 show:
- A 256-sample input time series consisting of the same three waveforms shown in Figure 2. (As with Figure 2, even though the display is 300 points wide, the actual data being plotted on each of the three graphs ends at 256 samples.)
- The real frequency spectrum produced by the forward DCT. In this case, the spectrum is plotted from a frequency of zero on the left to the Nyquist folding frequency on the right.
- The result of applying the inverse DCT to the spectral data in order to reconstruct the original time series from the spectral data.
Where is the imaginary part of the spectrum?
There is no imaginary part of the spectrum plotted in Figure 3, simply because the DCT doesn't produce an imaginary part. Since there is no imaginary part, there is also no need for a plot of the magnitude spectrum for the DCT. (It would look exactly like the real part of the spectrum, with all negative values converted to positive values, if it were computed and plotted.)
If you compare Figure 3 with Figure 2, you will see that the DFT and the DCT both appeared to do an equally good job of reproducing the original time series when the inverse transform was applied to the spectral data. The big difference between Figure 2 and Figure 3 is that this was accomplished with the somewhat more economical DCT in Figure 3.
Water to ice and back to water
There is one point that I would like to make here, because it will become very important in a future lesson that deals with the inner workings of JPEG. The second and third graphs in Figure 2 represent the same information as the first graph in Figure 2. Similarly, the second graph in Figure 3 represents the same information as the first graph in Figure 3. In other words, the spectral data represents the same information as the time-series data. They simply represent that information in different forms.
As an analogy, if we lower the temperature of a container of water to less than 32 degrees Fahrenheit, the form of the water will change from a liquid to a solid. If we warm it back up, the form will change back to a liquid. This is roughly analogous to transforming a time series into the frequency domain and then transforming the frequency spectrum back into the time domain. The same information is represented in both cases. That information is simply represented in different forms.
Sub-dividing the input
When performing spectral analysis, it is common practice to perform a DFT (or perhaps a DCT) on the entire time series as was the case in Figure 1, Figure 2, and Figure 3. However, in a future lesson we will learn that this is not the case for JPEG image compression. Instead, the JPEG procedure sub-divides the image into a set of small images where each small image consists of an 8x8 block of 64 pixels.
Then the DCT is performed on each individual block of 64 pixels. Several additional processing steps are performed on the spectra produced for the set of 8x8 blocks to produce the compressed image. Later on, when the image is reconstructed, the 8x8 blocks are individually reconstructed and are then assembled into a larger image that approximates the original image.
The program named Dsp044
The program named Dsp044 is designed to investigate the impact of sub-dividing the time series into eight-sample segments and processing those segments individually in order to be more consistent with the 8x8-pixel block concept in JPEG. As it turns out, there appears to be no noticeable impact. As you can see in Figure 4, the reconstructed output shown in the second graph is a very good replica of the input shown in the first graph.
Figure 4 |
(Figure 4 shows only the input and output time series. In order to display the spectral results, it would have been necessary to display 32 individual spectra, one computed for each 8-sample segment of the input time series. That would have been fairly impractical.)
Testing
Both programs were tested using J2SE 5.0 under WinXP. (Both programs require J2SE 5.0 or later due to the use of static import of Math class.)
Discussion and Sample Code
The program named Dsp042
The class definition for Dsp042 begins in Listing 1 by declaring and initializing some instance variables.
class Dsp042 implements GraphIntfc01{ int len = 256; double[] timeDataIn = new double[len]; double[] realSpect = new double[len]; double[] timeDataOut = new double[len]; int zero = 0; |
Note that the class named Dsp042 implements the interface named GraphIntfc01.
The constructor for Dsp042
The constructor begins in Listing 2.
public Dsp042(){//constructor //Create the raw data pulses timeDataIn[0] = 0; timeDataIn[1] = 50; //code deleted for brevity timeDataIn[20] = -2; timeDataIn[21] = -1; timeDataIn[240] = 80; timeDataIn[241] = 80; //code deleted for brevity timeDataIn[254] = -80; timeDataIn[255] = -80; |
The code in Listing 2 creates the first and last waveforms shown in the first graph in Figure 3. Note that I deleted quite a lot of code from Listing 2 for brevity. You can view the code that I deleted in Listing 14.
Create the sinusoidal waveform
Listing 3 creates the truncated sinusoidal waveform shown near the center of the first graph in Figure 3.
for(int x = len/3;x < 3*len/4;x++){ timeDataIn[x] = 80.0 * Math.sin(2*PI*(x)*1.0/20.0); }//end for loop |
Perform the forward Discrete Cosine Transform
Listing 4 invokes the static transform method of the ForwardDCT01 class to compute the forward DCT of the time data and to save the results in the array referred to by realSpect, which was created in Listing 1.
ForwardDCT01.transform(timeDataIn,realSpect); |
Perform the inverse Discrete Cosine Transform
Listing 5 invokes the static transform method of the InverseDCT01 class to compute the inverse DCT of the spectral data and to save the results in the array referred to by timeDataOut, which was created in Listing 1.
InverseDCT01.transform(realSpect,timeDataOut); }//end constructor |
Listing 5 also signals the end of the constructor for the class named Dsp042.
The remaining code
The remaining code in the class named Dsp042 consists of six methods, which are required by the interface named GraphIntfc01. The purpose of these methods is simply to plot the data contained in three arrays, producing the three graphs shown in Figure 3. I explained those six methods in the earlier lesson entitled Plotting Engineering and Scientific Data using Java and won't repeat that explanation here. You can view the methods in Listing 14.
The class named Dsp044
This class is a modification of the class named Dsp042 designed to investigate the impact of sub-dividing the input time series into eight-sample segments in order to be consistent with the 8x8 blocks in JPEG.
Listing 6 shows the beginning of the class and the beginning of the constructor.
class Dsp044 implements GraphIntfc01{ int len = 256; double[] timeDataIn = new double[len]; double[] timeDataOut = new double[len]; int zero = 0; public Dsp044(){//constructor //Create the raw data pulses timeDataIn[0] = 0; timeDataIn[1] = 50; //code deleted for brevity timeDataIn[20] = -2; timeDataIn[21] = -1; timeDataIn[240] = 80; timeDataIn[241] = 80; //code deleted for brevity timeDataIn[254] = -80; timeDataIn[255] = -80; //Create raw data sinusoid for(int x = len/3;x < 3*len/4;x++){ timeDataIn[x] = 80.0 * Math.sin(2*PI*(x)*1.0/20.0); }//end for loop |
Once again, note that the class named Dsp044 implements the interface named GraphIntfc01.
As before, I deleted some of the code from Listing 6 for brevity. The code in Listing 6 is very similar to the code that I explained earlier with respect to the class named Dsp042.
Eight-element array objects
The real difference between Dsp042 and Dsp044 begins in Listing 7 where I create some eight-element array objects to handle the eight-sample segments.
double[] workingArrayIn = new double[8]; double[] workingArrayOut = new double[8]; double[] realSpect = new double[8]; |
Process eight samples at a time
Listing 8 shows the beginning of a while loop, which computes a forward and an inverse DCT on each successive eight-sample segment of the input time series. Code inside the while loop also concatenates the output segments from the inverse DCT to produce the output signal, which is shown by the bottom graph in Figure 4.
int segmentCnt = 0; while((segmentCnt + 8) <= len){ System.arraycopy(timeDataIn, segmentCnt, workingArrayIn, 0, 8); |
During each iteration of the while loop, the code in Listing 8 copies the next eight samples from the input time series into an eight-element working array.
Compute the forward and the inverse transforms
Listing 9 performs a forward DCT on the contents of the eight-element working array. Then it performs an inverse DCT on the eight-samples of spectral data produced by the forward transform.
ForwardDCT01.transform(workingArrayIn,realSpect); InverseDCT01.transform(realSpect,workingArrayOut); |
Concatenate the output time-series segments
Listing 10 copies the eight samples of output time-series data produced by the inverse transform into the next eight samples of the array designated to hold the final output. This concatenates the eight-sample segments into the time series shown in the bottom graph in Figure 4.
System.arraycopy(workingArrayOut, 0, timeDataOut, segmentCnt, 8); segmentCnt += 8; }//end while }//end constructor |
Then Listing 10 increments the segment counter by 8 and control is transferred back to the top of the while loop shown in Listing 8.
Listing 10 also signals the end of the constructor.
The remaining code
As before, the remaining code in the class named Dsp044 consists of six methods, which are required by the interface named GraphIntfc01. The purpose of these methods is to plot the data contained in two arrays, producing the graphs shown in Figure 4. You can view the methods in Listing 15.
Run the Programs
I encourage you to copy, compile, and execute the code from the listings in the section entitled Complete Program Listings. Experiment with the code, making changes and observing the results of your changes. For example, as one experiment you can see what happens if you make changes to the computed argument for the cosine function in either the forward or the inverse transform.
Run under control of Graph03
Dsp042, Dsp043, and Dsp044 must all be run under the control of the program named Graph03.
(The program named Graph03 is a plotting program. See the earlier lesson entitled Spectrum Analysis using Java, Sampling Frequency, Folding Frequency, and the FFT Algorithm, which was the first lesson in which the plotting program named Graph03 was used. Also see Graph01, which was a predecessor of Graph03, in the lesson entitled Plotting Engineering and Scientific Data using Java.)
The source code for Graph03 is provided in Listing 16.
The source code for the interface named GraphIntfc01, which is required by these programs, is provided in Listing 17.
Running the programs
To run these programs, first compile the programs and then enter one of the following statements at the command prompt.
java Graph03 Dsp042 java Graph03 Dsp042 java Graph03 Dsp044Support classes
You will need some support classes in order to run these programs. In those cases where the source code for a required support class is not included in this lesson, you should be able to find the source code in the lessons referred to in the References section.
You can also find the source code by searching for it on Google. For example, searching for the following keywords on Google will identify the earlier lesson entitled Spectrum Analysis using Java, Sampling Frequency, Folding Frequency, and the FFT Algorithm containing the source code for the class named ForwardRealToComplex01.
java Baldwin "ForwardRealToComplex01.java"
Summary
I introduced you to the basics of the Discrete Cosine Transform (DCT) by:
- Explaining some of the underlying theory behind the transform.
- Demonstrating the use of the transform in two one-dimensional cases.
What's Next?
The next lesson will explain the use of the two-dimensional Discrete Cosine Transform and will illustrate its use to transform images into the wave-number domain and back into the space or image domain.
Future lessons in this series will explain the inner workings behind several data and image compression schemes, including the following:
- Run-length data encoding
- GIF image compression
- JPEG image compression
References
General
2440 Understanding the Lempel-Ziv Data Compression Algorithm in Java
2442 Understanding the Huffman Data Compression Algorithm in Java
1468
Plotting Engineering and Scientific Data using Java
1478 Fun
with Java, How and Why Spectral Analysis Works
1482
Spectrum Analysis using Java, Sampling Frequency, Folding Frequency, and the FFT
Algorithm
1483
Spectrum Analysis using Java, Frequency Resolution versus Data Length
1484
Spectrum Analysis using Java, Complex Spectrum and Phase Angle
1485
Spectrum Analysis using Java, Forward and Inverse Transforms, Filtering in the
Frequency Domain
1486 Fun
with Java, Understanding the Fast Fourier Transform (FFT) Algorithm
1489
Plotting 3D Surfaces using Java
1490 2D
Fourier Transforms using Java
1491 2D
Fourier Transforms using Java, Part 2
Discrete Cosine Transform equations
Discrete
cosine transform - Wikipedia, the free encyclopedia
The Data Analysis Briefbook -
Discrete Cosine
Transform
National Taiwan University -
DSP Group -
Discrete Cosine Transform
Complete Program Listings
/* File Dsp043.java Copyright 2006, R.G.Baldwin Revised 01/05/06 The purpose of this program is to demonstrate that the imaginary part of the Fourier transform of a symmetrical time series is all zeros if the origin is properly located. Illustrates forward and inverse Fourier transforms on a symmetrical time series using DFT algorithms. Passes resulting real and complex parts to inverse Fourier transform program to reconstruct the original time series. Run with Graph03. Enter the following to run the program: java Graph03 Dsp043 Exection of this program requires access to the following class files: Dsp043.class ForwardRealToComplex01.class Graph01.class GraphIntfc01.class GUI$MyCanvas.class GUI.class InverseComplexToReal01.class Tested using J2SE 5.0 under WinXP. **********************************************************/ import java.util.*; class Dsp043 implements GraphIntfc01{ final double pi = Math.PI; int len = 300; double[] timeDataIn = new double[len]; double[] realSpect = new double[len]; double[] imagSpect = new double[len]; double[] angle = new double[len];//unused double[] magnitude = new double[len]; double[] timeDataOut = new double[len]; int zero = 0; public Dsp043(){//constructor //Create raw waveform consisting of mirror image // sinusoidal segments with a sample having a value // of 0 in the center. //Set shift to a nonzero value to cause the imaginary // part of the transform to be non zero. for(int x = 0;x < len/4;x++){ timeDataIn[len/2 + x + 1] = 80.0 * Math.sin(2*pi*(x)*1.0/20.0); timeDataIn[len/2 - x - 1] = timeDataIn[len/2 + x + 1]; }//end for loop //Compute DFT of the time data and save it in // the output arrays. ForwardRealToComplex01.transform(timeDataIn, realSpect, imagSpect, angle, magnitude, zero, 0.0, 1.0); //Compute inverse DFT of the spectal data and // save output time data in output array InverseComplexToReal01.inverseTransform(realSpect, imagSpect, timeDataOut); }//end constructor //-----------------------------------------------------// //The following six methods are required by the interface // named GraphIntfc01. public int getNmbr(){ //Return number of curves to plot. Must not exceed 5. return 5; }//end getNmbr //-----------------------------------------------------// public double f1(double x){ int index = (int)Math.round(x); if(index < 0 || index > timeDataIn.length-1){ return 0; }else{ return timeDataIn[index]; }//end else }//end function //-----------------------------------------------------// public double f2(double x){ int index = (int)Math.round(x); if(index < 0 || index > realSpect.length-1){ return 0; }else{ //scale for convenient viewing return 5*realSpect[index]; }//end else }//end function //-----------------------------------------------------// public double f3(double x){ int index = (int)Math.round(x); if(index < 0 || index > imagSpect.length-1){ return 0; }else{ //scale for convenient viewing return 5*imagSpect[index]; }//end else }//end function //-----------------------------------------------------// public double f4(double x){ int index = (int)Math.round(x); if(index < 0 || index > magnitude.length-1){ return 0; }else{ //scale for convenient viewing return 5*magnitude[index]; }//end else }//end function //-----------------------------------------------------// public double f5(double x){ int index = (int)Math.round(x); if(index < 0 || index > timeDataOut.length-1){ return 0; }else{ return timeDataOut[index]; }//end else }//end function }//end sample class Dsp043 |
/*File ForwardDCT01.java Copyright 2006, R.G.Baldwin Rev 01/03/06 The static method named transform performs a forward Discreet Cosine Transform (DCT) on an incoming time series and returns the DCT spectrum. See http://en.wikipedia.org/wiki/Discrete_cosine_transform #DCT-II and http://rkb.home.cern.ch/rkb/AN16pp/node61.html for background on the DCT. This formulation is from http://www.cmlab.csie.ntu.edu.tw/cml/dsp/training/ coding/transform/dct.html Incoming parameters are: double[] x - incoming real data double[] y - outgoing real data Tested using J2SE 5.0 under WinXP. Requires J2SE 5.0 or later due to the use of static import of Math class. **********************************************************/ import static java.lang.Math.*; public class ForwardDCT01{ public static void transform(double[] x, double[] y){ int N = x.length; //Outer loop interates on frequency values. for(int k=0; k < N;k++){ double sum = 0.0; //Inner loop iterates on time-series points. for(int n=0; n < N; n++){ double arg = PI*k*(2.0*n+1)/(2*N); double cosine = cos(arg); double product = x[n]*cosine; sum += product; }//end inner loop double alpha; if(k == 0){ alpha = 1.0/sqrt(2); }else{ alpha = 1; }//end else y[k] = sum*alpha*sqrt(2.0/N); }//end outer loop }//end transform method //-----------------------------------------------------// }//end class ForwardDCT01 |
/*File InverseDCT01.java Copyright 2006, R.G.Baldwin Rev 01/03/06 The static method named transform performs an inverse Discreet Cosine Transform (DCT) on an incoming DCT spectrum and returns the DCT time series. See http://en.wikipedia.org/wiki/Discrete_cosine_transform #DCT-II and http://rkb.home.cern.ch/rkb/AN16pp/node61.html for background on the DCT. This formulation is from http://www.cmlab.csie.ntu.edu.tw/cml/dsp/training/ coding/transform/dct.html Incoming parameters are: double[] y - incoming real data double[] x - outgoing real data Tested using J2SE 5.0 under WinXP. Requires J2SE 5.0 or later due to the use of static import of Math class. **********************************************************/ import static java.lang.Math.*; public class InverseDCT01{ public static void transform(double[] y, double[] x){ int N = y.length; //Outer loop interates on time values. for(int n=0; n < N;n++){ double sum = 0.0; //Inner loop iterates on frequency values for(int k=0; k < N; k++){ double arg = PI*k*(2.0*n+1)/(2*N); double cosine = cos(arg); double product = y[k]*cosine; double alpha; if(k == 0){ alpha = 1.0/sqrt(2); }else{ alpha = 1; }//end else sum += alpha * product; }//end inner loop x[n] = sum * sqrt(2.0/N); }//end outer loop }//end transform method //-----------------------------------------------------// }//end class InverseDCT01 |
/* File Dsp042.java Copyright 2006, R.G.Baldwin Revised 01/05/06 Note: Dsp044 will investigate the impact of breaking the time series into eight-sample segments to be consistent with the 8x8 blocks in JPEG. Illustrates the application of forward and inverse Discrete Cosine Transform (DCT) to three different waveforms. Very similar to Dsp035, which applies full forward and inverse Fourier transforms to the same three waveforms See http://en.wikipedia.org/wiki/Discrete_cosine_transform #DCT-II, http://rkb.home.cern.ch/rkb/AN16pp/node61.html, and http://www.cmlab.csie.ntu.edu.tw/cml/dsp/training/ coding/transform/dct.html fortechnical background information on the Discrete Cosine Transform. Shows a plot of the input time series, the DCT spectrum, and the output time series resulting from the inverse DCT. Run with Graph03. Enter the following to run the program: java Graph03 Dsp042 Execution of this program requires access to the following class files: Dsp042.class ForwardDCT01.class Graph01.class GraphIntfc01.class GUI$MyCanvas.class GUI.class InverseDCT01.class Tested using J2SE 5.0 under WinXP. Requires J2SE 5.0 or later due to the use of static import of Math class. **********************************************************/ import java.util.*; import static java.lang.Math.*; class Dsp042 implements GraphIntfc01{ int len = 256; double[] timeDataIn = new double[len]; double[] realSpect = new double[len]; double[] timeDataOut = new double[len]; int zero = 0; public Dsp042(){//constructor //Create the raw data pulses timeDataIn[0] = 0; timeDataIn[1] = 50; timeDataIn[2] = 75; timeDataIn[3] = 80; timeDataIn[4] = 75; timeDataIn[5] = 50; timeDataIn[6] = 25; timeDataIn[7] = 0; timeDataIn[8] = -25; timeDataIn[9] = -50; timeDataIn[10] = -75; timeDataIn[11] = -80; timeDataIn[12] = -60; timeDataIn[13] = -40; timeDataIn[14] = -26; timeDataIn[15] = -17; timeDataIn[16] = -11; timeDataIn[17] = -8; timeDataIn[18] = -5; timeDataIn[19] = -3; timeDataIn[20] = -2; timeDataIn[21] = -1; timeDataIn[240] = 80; timeDataIn[241] = 80; timeDataIn[242] = 80; timeDataIn[243] = 80; timeDataIn[244] = -80; timeDataIn[245] = -80; timeDataIn[246] = -80; timeDataIn[247] = -80; timeDataIn[248] = 80; timeDataIn[249] = 80; timeDataIn[250] = 80; timeDataIn[251] = 80; timeDataIn[252] = -80; timeDataIn[253] = -80; timeDataIn[254] = -80; timeDataIn[255] = -80; //Create raw data sinusoid for(int x = len/3;x < 3*len/4;x++){ timeDataIn[x] = 80.0 * Math.sin( 2*PI*(x)*1.0/20.0); }//end for loop //Compute forward DCT of the time data and save it in // the output array. ForwardDCT01.transform(timeDataIn,realSpect); //Compute inverse DCT of the time data and save it in // the output array. InverseDCT01.transform(realSpect,timeDataOut); }//end constructor //-----------------------------------------------------// //The following six methods are required by the interface // named GraphIntfc01. public int getNmbr(){ //Return number of curves to plot. Must not exceed 5. return 3; }//end getNmbr //-----------------------------------------------------// public double f1(double x){ int index = (int)round(x); if(index < 0 || index > timeDataIn.length-1){ return 0; }else{ return timeDataIn[index]; }//end else }//end function //-----------------------------------------------------// public double f2(double x){ int index = (int)round(x); if(index < 0 || index > realSpect.length-1){ return 0; }else{ //Scale for convenient viewing return 0.22*realSpect[index]; }//end else }//end function //-----------------------------------------------------// public double f3(double x){ int index = (int)round(x); if(index < 0 || index > timeDataOut.length-1){ return 0; }else{ return timeDataOut[index]; }//end else }//end function //-----------------------------------------------------// public double f4(double x){ return 0; }//end function //-----------------------------------------------------// public double f5(double x){ return 0; }//end function //-----------------------------------------------------// }//end sample class Dsp042 |
/* File Dsp044.java Copyright 2006, R.G.Baldwin Revised 01/03/06 Update of Dsp042 to investigate the impact of breaking the time series into eight-sample segments in order to be consistent with the 8x8 blocks in JPEG. There appears to be no impact. The output is a very good replica of the input. Illustrates the application of forward and inverse Discrete Cosine Transform (DCT) to three different waveforms. Very similar to Dsp035, which applies full forward and inverse Fourier transforms to the same three waveforms See http://en.wikipedia.org/wiki/Discrete_cosine_transform #DCT-II, http://rkb.home.cern.ch/rkb/AN16pp/node61.html, and http://www.cmlab.csie.ntu.edu.tw/cml/dsp/training/ coding/transform/dct.html fortechnical background information on the Discrete Cosine Transform. Shows a plot of the input time series, and the output time series resulting from the inverse DCT. Can't show the spectrum because a new spectrum is produced every eight samples. Run with Graph03. Enter the following to run the program: java Graph03 Dsp044 Execution of this program requires access to the following class files: Dsp044.class ForwardDCT01.class Graph01.class GraphIntfc01.class GUI$MyCanvas.class GUI.class InverseDCT01.class Tested using J2SE 5.0 under WinXP. Requires J2SE 5.0 or later due to the use of static import of Math class. **********************************************************/ import java.util.*; import static java.lang.Math.*; class Dsp044 implements GraphIntfc01{ int len = 256; double[] timeDataIn = new double[len]; double[] timeDataOut = new double[len]; int zero = 0; public Dsp044(){//constructor //Create the raw data pulses timeDataIn[0] = 0; timeDataIn[1] = 50; timeDataIn[2] = 75; timeDataIn[3] = 80; timeDataIn[4] = 75; timeDataIn[5] = 50; timeDataIn[6] = 25; timeDataIn[7] = 0; timeDataIn[8] = -25; timeDataIn[9] = -50; timeDataIn[10] = -75; timeDataIn[11] = -80; timeDataIn[12] = -60; timeDataIn[13] = -40; timeDataIn[14] = -26; timeDataIn[15] = -17; timeDataIn[16] = -11; timeDataIn[17] = -8; timeDataIn[18] = -5; timeDataIn[19] = -3; timeDataIn[20] = -2; timeDataIn[21] = -1; timeDataIn[240] = 80; timeDataIn[241] = 80; timeDataIn[242] = 80; timeDataIn[243] = 80; timeDataIn[244] = -80; timeDataIn[245] = -80; timeDataIn[246] = -80; timeDataIn[247] = -80; timeDataIn[248] = 80; timeDataIn[249] = 80; timeDataIn[250] = 80; timeDataIn[251] = 80; timeDataIn[252] = -80; timeDataIn[253] = -80; timeDataIn[254] = -80; timeDataIn[255] = -80; //Create raw data sinusoid for(int x = len/3;x < 3*len/4;x++){ timeDataIn[x] = 80.0 * Math.sin( 2*PI*(x)*1.0/20.0); }//end for loop double[] workingArrayIn = new double[8]; double[] workingArrayOut = new double[8]; double[] realSpect = new double[8]; int segmentCnt = 0; //Compute forward and inverse DCTs on the input signal, // eight samples at a time. Concatenate the output // segments from the DCT to represent the output // signal. while((segmentCnt + 8) <= len){ System.arraycopy(timeDataIn, segmentCnt, workingArrayIn, 0, 8); //Compute forward DCT of the time data and save it in // the output array. ForwardDCT01.transform(workingArrayIn,realSpect); //Compute inverse DCT of the time data and save it in // the output array. InverseDCT01.transform(realSpect,workingArrayOut); //Concatenate the new output with the old output. System.arraycopy(workingArrayOut, 0, timeDataOut, segmentCnt, 8); segmentCnt += 8; }//end while }//end constructor //-----------------------------------------------------// //The following six methods are required by the interface // named GraphIntfc01. public int getNmbr(){ //Return number of curves to plot. Must not exceed 5. return 2; }//end getNmbr //-----------------------------------------------------// public double f1(double x){ int index = (int)round(x); if(index < 0 || index > timeDataIn.length-1){ return 0; }else{ return timeDataIn[index]; }//end else }//end function //-----------------------------------------------------// public double f2(double x){ int index = (int)round(x); if(index < 0 || index > timeDataOut.length-1){ return 0; }else{ return timeDataOut[index]; }//end else }//end function //-----------------------------------------------------// public double f3(double x){ return 0; }//end function //-----------------------------------------------------// public double f4(double x){ return 0; }//end function //-----------------------------------------------------// public double f5(double x){ return 0; }//end function //-----------------------------------------------------// }//end class Dsp044 |
/* File Graph03.java Copyright 2002, R.G.Baldwin This program is very similar to Graph01 except that it has been modified to allow the user to manually resize and replot the frame. Note: This program requires access to the interface named GraphIntfc01. This is a plotting program. It is designed to access a class file, which implements GraphIntfc01, and to plot up to five functions defined in that class file. The plotting surface is divided into the required number of equally sized plotting areas, and one function is plotted on cartesian coordinates in each area. The methods corresponding to the functions are named f1, f2, f3, f4, and f5. The class containing the functions must also define a method named getNmbr(), which takes no parameters and returns the number of functions to be plotted. If this method returns a value greater than 5, a NoSuchMethodException will be thrown. Note that the constructor for the class that implements GraphIntfc01 must not require any parameters due to the use of the newInstance method of the Class class to instantiate an object of that class. If the number of functions is less than 5, then the absent method names must begin with f5 and work down toward f1. For example, if the number of functions is 3, then the program will expect to call methods named f1, f2, and f3. It is OK for the absent methods to be defined in the class. They simply won't be invoked. The plotting areas have alternating white and gray backgrounds to make them easy to separate visually. All curves are plotted in black. A cartesian coordinate system with axes, tic marks, and labels is drawn in red in each plotting area. The cartesian coordinate system in each plotting area has the same horizontal and vertical scale, as well as the same tic marks and labels on the axes. The labels displayed on the axes, correspond to the values of the extreme edges of the plotting area. The program also compiles a sample class named junk, which contains five methods and the method named getNmbr. This makes it easy to compile and test this program in a stand-alone mode. At runtime, the name of the class that implements the GraphIntfc01 interface must be provided as a command-line parameter. If this parameter is missing, the program instantiates an object from the internal class named junk and plots the data provided by that class. Thus, you can test the program by running it with no command-line parameter. This program provides the following text fields for user input, along with a button labeled Graph. This allows the user to adjust the parameters and replot the graph as many times with as many plotting scales as needed: xMin = minimum x-axis value xMax = maximum x-axis value yMin = minimum y-axis value yMax = maximum y-axis value xTicInt = tic interval on x-axis yTicInt = tic interval on y-axis xCalcInc = calculation interval The user can modify any of these parameters and then click the Graph button to cause the five functions to be re-plotted according to the new parameters. Whenever the Graph button is clicked, the event handler instantiates a new object of the class that implements the GraphIntfc01 interface. Depending on the nature of that class, this may be redundant in some cases. However, it is useful in those cases where it is necessary to refresh the values of instance variables defined in the class (such as a counter, for example). Tested using JDK 1.4.0 under Win 2000. This program uses constants that were first defined in the Color class of v1.4.0. Therefore, the program requires v1.4.0 or later to compile and run correctly. **************************************/ import java.awt.*; import java.awt.event.*; import java.awt.geom.*; import javax.swing.*; import javax.swing.border.*; class Graph03{ public static void main( String[] args) throws NoSuchMethodException, ClassNotFoundException, InstantiationException, IllegalAccessException{ if(args.length == 1){ //pass command-line paramater new GUI(args[0]); }else{ //no command-line parameter given new GUI(null); }//end else }// end main }//end class Graph03 definition //===================================// class GUI extends JFrame implements ActionListener{ //Define plotting parameters and // their default values. double xMin = 0.0; double xMax = 400.0; double yMin = -100.0; double yMax = 100.0; //Tic mark intervals double xTicInt = 20.0; double yTicInt = 20.0; //Tic mark lengths. If too small // on x-axis, a default value is // used later. double xTicLen = (yMax-yMin)/50; double yTicLen = (xMax-xMin)/50; //Calculation interval along x-axis double xCalcInc = 1.0; //Text fields for plotting parameters JTextField xMinTxt = new JTextField("" + xMin); JTextField xMaxTxt = new JTextField("" + xMax); JTextField yMinTxt = new JTextField("" + yMin); JTextField yMaxTxt = new JTextField("" + yMax); JTextField xTicIntTxt = new JTextField("" + xTicInt); JTextField yTicIntTxt = new JTextField("" + yTicInt); JTextField xCalcIncTxt = new JTextField("" + xCalcInc); //Panels to contain a label and a // text field JPanel pan0 = new JPanel(); JPanel pan1 = new JPanel(); JPanel pan2 = new JPanel(); JPanel pan3 = new JPanel(); JPanel pan4 = new JPanel(); JPanel pan5 = new JPanel(); JPanel pan6 = new JPanel(); //Misc instance variables int frmWidth = 408; int frmHeight = 430; int width; int height; int number; GraphIntfc01 data; String args = null; //Plots are drawn on the canvases // in this array. Canvas[] canvases; //Constructor GUI(String args)throws NoSuchMethodException, ClassNotFoundException, InstantiationException, IllegalAccessException{ if(args != null){ //Save for use later in the // ActionEvent handler this.args = args; //Instantiate an object of the // target class using the String // name of the class. data = (GraphIntfc01) Class.forName(args). newInstance(); }else{ //Instantiate an object of the // test class named junk. data = new junk(); }//end else //Create array to hold correct // number of Canvas objects. canvases = new Canvas[data.getNmbr()]; //Throw exception if number of // functions is greater than 5. number = data.getNmbr(); if(number > 5){ throw new NoSuchMethodException( "Too many functions. " + "Only 5 allowed."); }//end if //Create the control panel and // give it a border for cosmetics. JPanel ctlPnl = new JPanel(); ctlPnl.setLayout(//?rows x 4 cols new GridLayout(0,4)); ctlPnl.setBorder( new EtchedBorder()); //Button for replotting the graph JButton graphBtn = new JButton("Graph"); graphBtn.addActionListener(this); //Populate each panel with a label // and a text field. Will place // these panels in a grid on the // control panel later. pan0.add(new JLabel("xMin")); pan0.add(xMinTxt); pan1.add(new JLabel("xMax")); pan1.add(xMaxTxt); pan2.add(new JLabel("yMin")); pan2.add(yMinTxt); pan3.add(new JLabel("yMax")); pan3.add(yMaxTxt); pan4.add(new JLabel("xTicInt")); pan4.add(xTicIntTxt); pan5.add(new JLabel("yTicInt")); pan5.add(yTicIntTxt); pan6.add(new JLabel("xCalcInc")); pan6.add(xCalcIncTxt); //Add the populated panels and the // button to the control panel with // a grid layout. ctlPnl.add(pan0); ctlPnl.add(pan1); ctlPnl.add(pan2); ctlPnl.add(pan3); ctlPnl.add(pan4); ctlPnl.add(pan5); ctlPnl.add(pan6); ctlPnl.add(graphBtn); //Create a panel to contain the // Canvas objects. They will be // displayed in a one-column grid. JPanel canvasPanel = new JPanel(); canvasPanel.setLayout(//?rows,1 col new GridLayout(0,1)); //Create a custom Canvas object for // each function to be plotted and // add them to the one-column grid. // Make background colors alternate // between white and gray. for(int cnt = 0; cnt < number; cnt++){ switch(cnt){ case 0 : canvases[cnt] = new MyCanvas(cnt); canvases[cnt].setBackground( Color.WHITE); break; case 1 : canvases[cnt] = new MyCanvas(cnt); canvases[cnt].setBackground( Color.LIGHT_GRAY); break; case 2 : canvases[cnt] = new MyCanvas(cnt); canvases[cnt].setBackground( Color.WHITE); break; case 3 : canvases[cnt] = new MyCanvas(cnt); canvases[cnt].setBackground( Color.LIGHT_GRAY); break; case 4 : canvases[cnt] = new MyCanvas(cnt); canvases[cnt]. setBackground(Color.WHITE); }//end switch //Add the object to the grid. canvasPanel.add(canvases[cnt]); }//end for loop //Add the sub-assemblies to the // frame. Set its location, size, // and title, and make it visible. getContentPane(). add(ctlPnl,"South"); getContentPane(). add(canvasPanel,"Center"); setBounds(0,0,frmWidth,frmHeight); if(args == null){ setTitle("Graph03, " + "Copyright 2002, " + "Richard G. Baldwin"); }else{ setTitle("Graph03/" + args + " Copyright 2002, " + "R. G. Baldwin"); }//end else setVisible(true); //Set to exit on X-button click setDefaultCloseOperation( EXIT_ON_CLOSE); //Guarantee a repaint on startup. for(int cnt = 0; cnt < number; cnt++){ canvases[cnt].repaint(); }//end for loop }//end constructor //---------------------------------// //This event handler is registered // on the JButton to cause the // functions to be replotted. public void actionPerformed( ActionEvent evt){ //Re-instantiate the object that // provides the data try{ if(args != null){ data = (GraphIntfc01)Class. forName(args).newInstance(); }else{ data = new junk(); }//end else }catch(Exception e){ //Known to be safe at this point. // Otherwise would have aborted // earlier. }//end catch //Set plotting parameters using // data from the text fields. xMin = Double.parseDouble( xMinTxt.getText()); xMax = Double.parseDouble( xMaxTxt.getText()); yMin = Double.parseDouble( yMinTxt.getText()); yMax = Double.parseDouble( yMaxTxt.getText()); xTicInt = Double.parseDouble( xTicIntTxt.getText()); yTicInt = Double.parseDouble( yTicIntTxt.getText()); xCalcInc = Double.parseDouble( xCalcIncTxt.getText()); //Calculate new values for the // length of the tic marks on the // axes. If too small on x-axis, // a default value is used later. xTicLen = (yMax-yMin)/50; yTicLen = (xMax-xMin)/50; //Repaint the plotting areas for(int cnt = 0; cnt < number; cnt++){ canvases[cnt].repaint(); }//end for loop }//end actionPerformed //---------------------------------// //This is an inner class, which is used // to override the paint method on the // plotting surface. class MyCanvas extends Canvas{ int cnt;//object number //Factors to convert from double // values to integer pixel locations. double xScale; double yScale; MyCanvas(int cnt){//save obj number this.cnt = cnt; }//end constructor //Override the paint method public void paint(Graphics g){ //Get and save the size of the // plotting surface width = canvases[0].getWidth(); height = canvases[0].getHeight(); //Calculate the scale factors xScale = width/(xMax-xMin); yScale = height/(yMax-yMin); //Set the origin based on the // minimum values in x and y g.translate((int)((0-xMin)*xScale), (int)((0-yMin)*yScale)); drawAxes(g);//Draw the axes g.setColor(Color.BLACK); //Get initial data values double xVal = xMin; int oldX = getTheX(xVal); int oldY = 0; //Use the Canvas obj number to // determine which method to // invoke to get the value for y. switch(cnt){ case 0 : oldY = getTheY(data.f1(xVal)); break; case 1 : oldY = getTheY(data.f2(xVal)); break; case 2 : oldY = getTheY(data.f3(xVal)); break; case 3 : oldY = getTheY(data.f4(xVal)); break; case 4 : oldY = getTheY(data.f5(xVal)); }//end switch //Now loop and plot the points while(xVal < xMax){ int yVal = 0; //Get next data value. Use the // Canvas obj number to // determine which method to // invoke to get the value for y. switch(cnt){ case 0 : yVal = getTheY(data.f1(xVal)); break; case 1 : yVal = getTheY(data.f2(xVal)); break; case 2 : yVal = getTheY(data.f3(xVal)); break; case 3 : yVal = getTheY(data.f4(xVal)); break; case 4 : yVal = getTheY(data.f5(xVal)); }//end switch1 //Convert the x-value to an int // and draw the next line segment int x = getTheX(xVal); g.drawLine(oldX,oldY,x,yVal); //Increment along the x-axis xVal += xCalcInc; //Save end point to use as start // point for next line segment. oldX = x; oldY = yVal; }//end while loop }//end overridden paint method //---------------------------------// //Method to draw axes with tic marks // and labels in the color RED void drawAxes(Graphics g){ g.setColor(Color.RED); //Lable left x-axis and bottom // y-axis. These are the easy // ones. Separate the labels from // the ends of the tic marks by // two pixels. g.drawString("" + (int)xMin, getTheX(xMin), getTheY(xTicLen/2)-2); g.drawString("" + (int)yMin, getTheX(yTicLen/2)+2, getTheY(yMin)); //Label the right x-axis and the // top y-axis. These are the hard // ones because the position must // be adjusted by the font size and // the number of characters. //Get the width of the string for // right end of x-axis and the // height of the string for top of // y-axis //Create a string that is an // integer representation of the // label for the right end of the // x-axis. Then get a character // array that represents the // string. int xMaxInt = (int)xMax; String xMaxStr = "" + xMaxInt; char[] array = xMaxStr. toCharArray(); //Get a FontMetrics object that can // be used to get the size of the // string in pixels. FontMetrics fontMetrics = g.getFontMetrics(); //Get a bounding rectangle for the // string Rectangle2D r2d = fontMetrics.getStringBounds( array,0,array.length,g); //Get the width and the height of // the bounding rectangle. The // width is the width of the label // at the right end of the // x-axis. The height applies to // all the labels, but is needed // specifically for the label at // the top end of the y-axis. int labWidth = (int)(r2d.getWidth()); int labHeight = (int)(r2d.getHeight()); //Label the positive x-axis and the // positive y-axis using the width // and height from above to // position the labels. These // labels apply to the very ends of // the axes at the edge of the // plotting surface. g.drawString("" + (int)xMax, getTheX(xMax)-labWidth, getTheY(xTicLen/2)-2); g.drawString("" + (int)yMax, getTheX(yTicLen/2)+2, getTheY(yMax)+labHeight); //Draw the axes g.drawLine(getTheX(xMin), getTheY(0.0), getTheX(xMax), getTheY(0.0)); g.drawLine(getTheX(0.0), getTheY(yMin), getTheX(0.0), getTheY(yMax)); //Draw the tic marks on axes xTics(g); yTics(g); }//end drawAxes //---------------------------------// //Method to draw tic marks on x-axis void xTics(Graphics g){ double xDoub = 0; int x = 0; //Get the ends of the tic marks. int topEnd = getTheY(xTicLen/2); int bottomEnd = getTheY(-xTicLen/2); //If the vertical size of the // plotting area is small, the // calculated tic size may be too // small. In that case, set it to // 10 pixels. if(topEnd < 5){ topEnd = 5; bottomEnd = -5; }//end if //Loop and draw a series of short // lines to serve as tic marks. // Begin with the positive x-axis // moving to the right from zero. while(xDoub < xMax){ x = getTheX(xDoub); g.drawLine(x,topEnd,x,bottomEnd); xDoub += xTicInt; }//end while //Now do the negative x-axis moving // to the left from zero xDoub = 0; while(xDoub > xMin){ x = getTheX(xDoub); g.drawLine(x,topEnd,x,bottomEnd); xDoub -= xTicInt; }//end while }//end xTics //---------------------------------// //Method to draw tic marks on y-axis void yTics(Graphics g){ double yDoub = 0; int y = 0; int rightEnd = getTheX(yTicLen/2); int leftEnd = getTheX(-yTicLen/2); //Loop and draw a series of short // lines to serve as tic marks. // Begin with the positive y-axis // moving up from zero. while(yDoub < yMax){ y = getTheY(yDoub); g.drawLine(rightEnd,y,leftEnd,y); yDoub += yTicInt; }//end while //Now do the negative y-axis moving // down from zero. yDoub = 0; while(yDoub > yMin){ y = getTheY(yDoub); g.drawLine(rightEnd,y,leftEnd,y); yDoub -= yTicInt; }//end while }//end yTics //---------------------------------// //This method translates and scales // a double y value to plot properly // in the integer coordinate system. // In addition to scaling, it causes // the positive direction of the // y-axis to be from bottom to top. int getTheY(double y){ double yDoub = (yMax+yMin)-y; int yInt = (int)(yDoub*yScale); return yInt; }//end getTheY //---------------------------------// //This method scales a double x value // to plot properly in the integer // coordinate system. int getTheX(double x){ return (int)(x*xScale); }//end getTheX //---------------------------------// }//end inner class MyCanvas //===================================// }//end class GUI //===================================// //Sample test class. Required for // compilation and stand-alone // testing. class junk implements GraphIntfc01{ public int getNmbr(){ //Return number of functions to // process. Must not exceed 5. return 4; }//end getNmbr public double f1(double x){ return (x*x*x)/200.0; }//end f1 public double f2(double x){ return -(x*x*x)/200.0; }//end f2 public double f3(double x){ return (x*x)/200.0; }//end f3 public double f4(double x){ return 50*Math.cos(x/10.0); }//end f4 public double f5(double x){ return 100*Math.sin(x/20.0); }//end f5 }//end sample class junk |
/* File GraphIntfc01.java Copyright 2004, R.G.Baldwin Rev 5/14/04 This interface must be implemented by classes whose objects produce data to be plotted by programs such as Graph03 and Graph06. Tested using SDK 1.4.2 under WinXP. ************************************************/ public interface GraphIntfc01{ public int getNmbr(); public double f1(double x); public double f2(double x); public double f3(double x); public double f4(double x); public double f5(double x); }//end GraphIntfc01 |
Copyright 2006, Richard G. Baldwin. Reproduction in whole or in part in any form or medium without express written permission from Richard Baldwin is prohibited.
About the author
Richard Baldwin is a college professor (at Austin Community College in Austin, TX) and private consultant whose primary focus is a combination of Java, C#, and XML. In addition to the many platform and/or language independent benefits of Java and C# applications, he believes that a combination of Java, C#, and XML will become the primary driving force in the delivery of structured information on the Web.Richard has participated in numerous consulting projects and he frequently provides onsite training at the high-tech companies located in and around Austin, Texas. He is the author of Baldwin's Programming Tutorials, which have gained a worldwide following among experienced and aspiring programmers. He has also published articles in JavaPro magazine.
In addition to his programming expertise, Richard has many years of practical experience in Digital Signal Processing (DSP). His first job after he earned his Bachelor's degree was doing DSP in the Seismic Research Department of Texas Instruments. (TI is still a world leader in DSP.) In the following years, he applied his programming and DSP expertise to other interesting areas including sonar and underwater acoustics.
Richard holds an MSEE degree from Southern Methodist University and has many years of experience in the application of computer technology to real-world problems.