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The Waikato Environment for Knowledge Analysis (WEKA), a machine
learning workbench. This version represents the developer version, the
"bleeding edge" of development, you could say. New functionality gets added
to this version.
/*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see
* intervalWidth = Max(1, 3.49*Std.Dev*numInstances^(1/3)) Then the number of
* intervals is calculated by:
* intervals = max(1, Math.round(Range/intervalWidth);
*
* @author Ashraf M. Kibriya ([email protected])
* @version $Revision: 13530 $
*/
public class AttributeVisualizationPanel extends PrintablePanel {
/** for serialization */
private static final long serialVersionUID = -8650490488825371193L;
/** This holds the current set of instances */
protected Instances m_data;
/**
* This holds the attribute stats of the current attribute on display. It is
* calculated in setAttribute(int idx) when it is called to set a new
* attribute index.
*/
protected AttributeStats m_as;
/** Cache of attribute stats info for the current data set */
protected AttributeStats[] m_asCache;
/**
* This holds the index of the current attribute on display and should be set
* through setAttribute(int idx).
*/
protected int m_attribIndex;
/**
* This holds the max value of the current attribute. In case of nominal
* attribute it is the highest count that a nominal value has in the attribute
* (given by m_as.nominalWeights[i]), otherwise in case of numeric attribute
* it is simply the maximum value present in the attribute (given by
* m_as.numericStats.max). It is used to calculate the ratio of the height of
* the bars with respect to the height of the display area.
*/
protected double m_maxValue;
/**
* This array holds the count (or height) for the each of the bars in a
* barplot or a histogram. In case of barplots (and current attribute being
* nominal) its length (and the number of bars) is equal to the number of
* nominal values in the current attribute, with each field of the array being
* equal to the count of each nominal that it represents (the count of ith
* nominal value of an attribute is given by m_as.nominalWeights[i]). Whereas,
* in case of histograms (and current attribute being numeric) the width of
* its intervals is calculated by Scott's(1979) method:
* intervalWidth = Max(1, 3.49*Std.Dev*numInstances^(1/3)) And the number of
* intervals by:
* intervals = max(1, Math.round(Range/intervalWidth); Then each field of this
* array contains the number of values of the current attribute that fall in
* the histogram interval that it represents.
* NOTE: The values of this array are only calculated if the class attribute
* is not set or if it is numeric.
*/
protected double[] m_histBarCounts;
/**
* This array holds the per class count (or per class height) of the each of
* the bars in a barplot or a histogram. For nominal attributes the format is:
* m_histBarClassCounts[nominalValue][classValue+1]. For numeric attributes
* the format is:
* m_histBarClassCounts[interval][classValues+1],
* where the number of intervals is calculated by the Scott's method as
* mentioned above. The array is initialized to have 1+numClasses to
* accomodate for instances with missing class value. The ones with missing
* class value are displayed as a black sub par in a histogram or a barplot.
*
* NOTE: The values of this array are only calculated if the class attribute
* is set and it is nominal.
*/
SparseInstance m_histBarClassCounts[];
/**
* Contains the range of each bar in a histogram. It is used to work out the
* range of bar the mouse pointer is on in getToolTipText().
*/
protected double m_barRange;
/** Contains the current class index. */
protected int m_classIndex;
/**
* This stores the BarCalc or HistCalc thread while a new barplot or histogram
* is being calculated.
*/
private Thread m_hc;
/** True if the thread m_hc above is running. */
private boolean m_threadRun = false;
private boolean m_doneCurrentAttribute = false;
private boolean m_displayCurrentAttribute = false;
/**
* This stores and lets the user select a class attribute. It also has an
* entry "No Class" if the user does not want to set a class attribute for
* colouring.
*/
protected JComboBox m_colorAttrib;
/**
* Fontmetrics used to get the font size which is required for calculating
* displayable area size, bar height ratio and width of strings that are
* displayed on top of bars indicating their count.
*/
private final FontMetrics m_fm;
/**
* Lock variable to synchronize the different threads running currently in
* this class. There are two to three threads in this class, AWT paint thread
* which is handled differently in paintComponent() which checks on
* m_threadRun to determine if it can perform full paint or not, the second
* thread is the main execution thread and the third is the one represented by
* m_hc which we start when we want to calculate the internal fields for a bar
* plot or a histogram.
*/
private final Integer m_locker = new Integer(1);
// Image img;
/**
* Contains discrete colours for colouring of subbars of histograms and bar
* plots when the class attribute is set and is nominal
*/
private final ArrayList m_colorList = new ArrayList();
/** default colour list */
private static final Color[] m_defaultColors = { Color.blue, Color.red,
Color.cyan, new Color(75, 123, 130), Color.pink, Color.green, Color.orange,
new Color(255, 0, 255), new Color(255, 0, 0), new Color(0, 255, 0), };
/**
* Constructor - If used then the class will not show the class selection
* combo box.
*/
public AttributeVisualizationPanel() {
this(false);
}
/**
* Constructor.
*
* @param showColouringOption - should be true if the class selection combo
* box is to be displayed with the histogram/barplot, or false
* otherwise. P.S: the combo box is always created it just won't be
* shown if showColouringOption is false.
*/
public AttributeVisualizationPanel(boolean showColouringOption) {
this.setFont(new Font("Default", Font.PLAIN, 9));
m_fm = this.getFontMetrics(this.getFont());
this.setToolTipText("");
FlowLayout fl = new FlowLayout(FlowLayout.LEFT);
this.setLayout(fl);
this.addComponentListener(new ComponentAdapter() {
@Override
public void componentResized(ComponentEvent ce) {
if (m_data != null) {
// calcGraph();
}
}
});
m_colorAttrib = new JComboBox();
m_colorAttrib.addItemListener(new ItemListener() {
@Override
public void itemStateChanged(ItemEvent ie) {
if (ie.getStateChange() == ItemEvent.SELECTED) {
m_classIndex = m_colorAttrib.getSelectedIndex() - 1;
if (m_as != null) {
setAttribute(m_attribIndex);
}
}
}
});
if (showColouringOption) {
// m_colorAttrib.setVisible(false);
this.add(m_colorAttrib);
validate();
}
}
/**
* Sets the instances for use
*
* @param newins a set of Instances
*/
public void setInstances(Instances newins) {
m_attribIndex = 0;
m_as = null;
m_data = new Instances(newins);
if (m_colorAttrib != null) {
m_colorAttrib.removeAllItems();
m_colorAttrib.addItem("No class");
for (int i = 0; i < m_data.numAttributes(); i++) {
String type = "(" + Attribute.typeToStringShort(m_data.attribute(i))
+ ")";
m_colorAttrib.addItem(new String("Class: " + m_data.attribute(i).name()
+ " " + type));
}
if (m_data.classIndex() >= 0) {
m_colorAttrib.setSelectedIndex(m_data.classIndex() + 1);
} else {
m_colorAttrib.setSelectedIndex(m_data.numAttributes());
}
// if (m_data.classIndex() >= 0) {
// m_colorAttrib.setSelectedIndex(m_data.classIndex());
// }
}
if (m_data.classIndex() >= 0) {
m_classIndex = m_data.classIndex();
} else {
m_classIndex = m_data.numAttributes() - 1;
}
m_asCache = new AttributeStats[m_data.numAttributes()];
}
/**
* Returns the class selection combo box if the parent component wants to
* place it in itself or in some component other than this component.
*/
public JComboBox getColorBox() {
return m_colorAttrib;
}
/**
* Get the coloring (class) index for the plot
*
* @return an int value
*/
public int getColoringIndex() {
return m_classIndex; // m_colorAttrib.getSelectedIndex();
}
/**
* Set the coloring (class) index for the plot
*
* @param ci an int value
*/
public void setColoringIndex(int ci) {
m_classIndex = ci;
if (m_colorAttrib != null) {
m_colorAttrib.setSelectedIndex(ci + 1);
} else {
setAttribute(m_attribIndex);
}
}
/**
* Tells the panel which attribute to visualize.
*
* @param index The index of the attribute
*/
public void setAttribute(int index) {
synchronized (m_locker) {
// m_threadRun = true;
m_threadRun = false;
m_doneCurrentAttribute = false;
m_displayCurrentAttribute = true;
// if(m_hc!=null && m_hc.isAlive()) m_hc.stop();
m_attribIndex = index;
if (m_asCache[index] != null) {
m_as = m_asCache[index];
} else {
m_asCache[index] = m_data.attributeStats(index);
m_as = m_asCache[index];
}
// m_as = m_data.attributeStats(m_attribIndex);
// m_classIndex = m_colorAttrib.getSelectedIndex();
}
this.repaint();
// calcGraph();
}
/**
* Recalculates the barplot or histogram to display, required usually when the
* attribute is changed or the component is resized.
*/
public void calcGraph(int panelWidth, int panelHeight) {
synchronized (m_locker) {
m_threadRun = true;
if (m_as.nominalWeights != null) {
m_hc = new BarCalc(panelWidth, panelHeight);
m_hc.setPriority(Thread.MIN_PRIORITY);
m_hc.start();
} else if (m_as.numericStats != null) {
m_hc = new HistCalc();
m_hc.setPriority(Thread.MIN_PRIORITY);
m_hc.start();
} else {
m_histBarCounts = null;
m_histBarClassCounts = null;
m_doneCurrentAttribute = true;
m_threadRun = false;
this.repaint();
}
}
}
/**
* Internal class that calculates the barplot to display, in a separate
* thread. In particular it initializes some of the crucial internal fields
* required by paintComponent() to display the histogram for the current
* attribute. These include: m_histBarCounts or m_histBarClassCounts,
* m_maxValue and m_colorList.
*/
private class BarCalc extends Thread {
private final int m_panelWidth;
public BarCalc(int panelWidth, int panelHeight) {
m_panelWidth = panelWidth;
}
@Override
public void run() {
synchronized (m_locker) {
// there is no use doing/displaying anything if the resolution
// of the panel is less than the number of values for this attribute
if (m_data.attribute(m_attribIndex).numValues() > m_panelWidth) {
m_histBarClassCounts = null;
m_threadRun = false;
m_doneCurrentAttribute = true;
m_displayCurrentAttribute = false;
AttributeVisualizationPanel.this.repaint();
return;
}
if ((m_classIndex >= 0) && (m_data.attribute(m_classIndex).isNominal())) {
SparseInstance histClassCounts[];
histClassCounts = new SparseInstance[m_data.attribute(m_attribIndex)
.numValues()];
// [m_data.attribute(m_classIndex).numValues()+1];
if (m_as.nominalWeights.length > 0) {
m_maxValue = m_as.nominalWeights[0];
for (int i = 0; i < m_data.attribute(m_attribIndex).numValues(); i++) {
if (m_as.nominalWeights[i] > m_maxValue) {
m_maxValue = m_as.nominalWeights[i];
}
}
} else {
m_maxValue = 0;
}
if (m_colorList.size() == 0) {
m_colorList.add(Color.black);
}
for (int i = m_colorList.size(); i < m_data.attribute(m_classIndex)
.numValues() + 1; i++) {
Color pc = m_defaultColors[(i - 1) % 10];
int ija = (i - 1) / 10;
ija *= 2;
for (int j = 0; j < ija; j++) {
pc = pc.darker();
}
m_colorList.add(pc);
}
// first sort data on attribute values
m_data.sort(m_attribIndex);
double[] tempClassCounts = null;
int tempAttValueIndex = -1;
for (int k = 0; k < m_data.numInstances(); k++) {
// System.out.println("attrib: "+
// m_data.instance(k).value(m_attribIndex)+
// " class: "+
// m_data.instance(k).value(m_classIndex));
if (!m_data.instance(k).isMissing(m_attribIndex)) {
// check to see if we need to allocate some space here
if (m_data.instance(k).value(m_attribIndex) != tempAttValueIndex) {
if (tempClassCounts != null) {
// set up the sparse instance for the previous bar (if any)
int numNonZero = 0;
for (double tempClassCount : tempClassCounts) {
if (tempClassCount > 0) {
numNonZero++;
}
}
double[] nonZeroVals = new double[numNonZero];
int[] nonZeroIndices = new int[numNonZero];
int count = 0;
for (int z = 0; z < tempClassCounts.length; z++) {
if (tempClassCounts[z] > 0) {
nonZeroVals[count] = tempClassCounts[z];
nonZeroIndices[count++] = z;
}
}
SparseInstance tempS = new SparseInstance(1.0, nonZeroVals,
nonZeroIndices, tempClassCounts.length);
histClassCounts[tempAttValueIndex] = tempS;
}
tempClassCounts = new double[m_data.attribute(m_classIndex)
.numValues() + 1];
tempAttValueIndex = (int) m_data.instance(k).value(
m_attribIndex);
/*
* histClassCounts[(int)m_data.instance(k).value(m_attribIndex)]
* = new double[m_data.attribute(m_classIndex).numValues()+1];
*/
}
if (m_data.instance(k).isMissing(m_classIndex)) {
/*
* histClassCounts[(int)m_data.instance(k).value(m_attribIndex)]
* [0] += m_data.instance(k).weight();
*/
tempClassCounts[0] += m_data.instance(k).weight();
} else {
tempClassCounts[(int) m_data.instance(k).value(m_classIndex) + 1] += m_data
.instance(k).weight();
/*
* histClassCounts[(int)m_data.instance(k).value(m_attribIndex)]
* [(int)m_data.instance(k).value(m_classIndex)+1] +=
* m_data.instance(k).weight();
*/
}
}
}
// set up sparse instance for last bar?
if (tempClassCounts != null) {
// set up the sparse instance for the previous bar (if any)
int numNonZero = 0;
for (double tempClassCount : tempClassCounts) {
if (tempClassCount > 0) {
numNonZero++;
}
}
double[] nonZeroVals = new double[numNonZero];
int[] nonZeroIndices = new int[numNonZero];
int count = 0;
for (int z = 0; z < tempClassCounts.length; z++) {
if (tempClassCounts[z] > 0) {
nonZeroVals[count] = tempClassCounts[z];
nonZeroIndices[count++] = z;
}
}
SparseInstance tempS = new SparseInstance(1.0, nonZeroVals,
nonZeroIndices, tempClassCounts.length);
histClassCounts[tempAttValueIndex] = tempS;
}
// for(int i=0; i 0) {
m_maxValue = m_as.nominalWeights[0];
for (int i = 0; i < m_data.attribute(m_attribIndex).numValues(); i++) {
if (m_as.nominalWeights[i] > m_maxValue) {
m_maxValue = m_as.nominalWeights[i];
}
}
} else {
m_maxValue = 0;
}
for (int k = 0; k < m_data.numInstances(); k++) {
if (!m_data.instance(k).isMissing(m_attribIndex)) {
histCounts[(int) m_data.instance(k).value(m_attribIndex)] += m_data
.instance(k).weight();
}
}
m_threadRun = false;
m_displayCurrentAttribute = true;
m_doneCurrentAttribute = true;
m_histBarCounts = histCounts;
// Image tmpImg = new BufferedImage(getWidth(), getHeight(),
// BufferedImage.TYPE_INT_RGB);
// drawGraph( tmpImg.getGraphics() );
// img = tmpImg;
AttributeVisualizationPanel.this.repaint();
}
} // end synchronized
} // end run()
}
/**
* Internal class that calculates the histogram to display, in a separate
* thread. In particular it initializes some of the crucial internal fields
* required by paintComponent() to display the histogram for the current
* attribute. These include: m_histBarCounts or m_histBarClassCounts,
* m_maxValue and m_colorList.
*/
private class HistCalc extends Thread {
@Override
public void run() {
synchronized (m_locker) {
if ((m_classIndex >= 0) && (m_data.attribute(m_classIndex).isNominal())) {
int intervals;
double intervalWidth = 0.0;
// This uses the M.P.Wand's method to calculate the histogram's
// interval width. See "Data-Based Choice of Histogram Bin Width", in
// The American Statistician, Vol. 51, No. 1, Feb., 1997, pp. 59-64.
// intervalWidth = Math.pow(6D/( -psi(2,
// g21())*m_data.numInstances()),
// 1/3D );
// This uses the Scott's method to calculate the histogram's interval
// width. See "On optimal and data-based histograms".
// See Biometrika, 66, 605-610 OR see the same paper mentioned above.
intervalWidth = 3.49 * m_as.numericStats.stdDev
* Math.pow(m_data.numInstances(), -1 / 3D);
// The Math.max is introduced to remove the possibility of
// intervals=0 and =NAN that can happen if respectively all the
// numeric
// values are the same or the interval width is evaluated to zero.
intervals = Math.max(
1,
(int) Math.round((m_as.numericStats.max - m_as.numericStats.min)
/ intervalWidth));
// System.out.println("Max: "+m_as.numericStats.max+
// " Min: "+m_as.numericStats.min+
// " stdDev: "+m_as.numericStats.stdDev+
// "intervalWidth: "+intervalWidth);
// The number 4 below actually represents a padding of 3 pixels on
// each side of the histogram, and is also reflected in other parts of
// the code in the shape of numerical constants like "6" here.
if (intervals > AttributeVisualizationPanel.this.getWidth()) {
intervals = AttributeVisualizationPanel.this.getWidth() - 6;
if (intervals < 1) {
intervals = 1;
}
}
double histClassCounts[][] = new double[intervals][m_data.attribute(
m_classIndex).numValues() + 1];
double barRange = (m_as.numericStats.max - m_as.numericStats.min)
/ histClassCounts.length;
m_maxValue = 0;
if (m_colorList.size() == 0) {
m_colorList.add(Color.black);
}
for (int i = m_colorList.size(); i < m_data.attribute(m_classIndex)
.numValues() + 1; i++) {
Color pc = m_defaultColors[(i - 1) % 10];
int ija = (i - 1) / 10;
ija *= 2;
for (int j = 0; j < ija; j++) {
pc = pc.darker();
}
m_colorList.add(pc);
}
for (int k = 0; k < m_data.numInstances(); k++) {
int t = 0; // This holds the interval that the attibute value of the
// new instance belongs to.
try {
if (!m_data.instance(k).isMissing(m_attribIndex)) {
// 1. see footnote at the end of this file
t = (int) Math.ceil((float) ((m_data.instance(k).value(
m_attribIndex) - m_as.numericStats.min) / barRange));
if (t == 0) {
if (m_data.instance(k).isMissing(m_classIndex)) {
histClassCounts[t][0] += m_data.instance(k).weight();
} else {
histClassCounts[t][(int) m_data.instance(k).value(
m_classIndex) + 1] += m_data.instance(k).weight();
// if(histCounts[t]>m_maxValue)
// m_maxValue = histCounts[t];
}
} else {
if (m_data.instance(k).isMissing(m_classIndex)) {
histClassCounts[t - 1][0] += m_data.instance(k).weight();
} else {
histClassCounts[t - 1][(int) m_data.instance(k).value(
m_classIndex) + 1] += m_data.instance(k).weight();
// if(histCounts[t-1]>m_maxValue)
// m_maxValue = histCounts[t-1];
}
}
}
} catch (ArrayIndexOutOfBoundsException ae) {
System.out
.println("t:"
+ (t)
+ " barRange:"
+ barRange
+ " histLength:"
+ histClassCounts.length
+ " value:"
+ m_data.instance(k).value(m_attribIndex)
+ " min:"
+ m_as.numericStats.min
+ " sumResult:"
+ (m_data.instance(k).value(m_attribIndex) - m_as.numericStats.min)
+ " divideResult:"
+ (float) ((m_data.instance(k).value(m_attribIndex) - m_as.numericStats.min) / barRange)
+ " finalResult:"
+ Math
.ceil((float) ((m_data.instance(k).value(m_attribIndex) - m_as.numericStats.min) / barRange)));
}
}
for (double[] histClassCount : histClassCounts) {
double sum = 0;
for (double element : histClassCount) {
sum = sum + element;
}
if (m_maxValue < sum) {
m_maxValue = sum;
}
}
// convert to sparse instances
SparseInstance[] histClassCountsSparse = new SparseInstance[histClassCounts.length];
for (int i = 0; i < histClassCounts.length; i++) {
int numSparseValues = 0;
for (int j = 0; j < histClassCounts[i].length; j++) {
if (histClassCounts[i][j] > 0) {
numSparseValues++;
}
}
double[] sparseValues = new double[numSparseValues];
int[] sparseIndices = new int[numSparseValues];
int count = 0;
for (int j = 0; j < histClassCounts[i].length; j++) {
if (histClassCounts[i][j] > 0) {
sparseValues[count] = histClassCounts[i][j];
sparseIndices[count++] = j;
}
}
SparseInstance tempS = new SparseInstance(1.0, sparseValues,
sparseIndices, histClassCounts[i].length);
histClassCountsSparse[i] = tempS;
}
m_histBarClassCounts = histClassCountsSparse;
m_barRange = barRange;
} else { // else if the class attribute is numeric or the class is not
// set
int intervals;
double intervalWidth;
// At the time of this coding the
// possibility of datasets with zero instances
// was being dealt with in the
// PreProcessPanel of weka Explorer.
// old method of calculating number of intervals
// intervals = m_as.totalCount>10 ?
// (int)(m_as.totalCount*0.1):(int)m_as.totalCount;
// This uses the M.P.Wand's method to calculate the histogram's
// interval width. See "Data-Based Choice of Histogram Bin Width", in
// The American Statistician, Vol. 51, No. 1, Feb., 1997, pp. 59-64.
// intervalWidth = Math.pow(6D/(-psi(2, g21())*m_data.numInstances()
// ),
// 1/3D );
// This uses the Scott's method to calculate the histogram's interval
// width. See "On optimal and data-based histograms".
// See Biometrika, 66, 605-610 OR see the same paper mentioned above.
intervalWidth = 3.49 * m_as.numericStats.stdDev
* Math.pow(m_data.numInstances(), -1 / 3D);
// The Math.max is introduced to remove the possibility of
// intervals=0 and =NAN that can happen if respectively all the
// numeric
// values are the same or the interval width is evaluated to zero.
intervals = Math.max(
1,
(int) Math.round((m_as.numericStats.max - m_as.numericStats.min)
/ intervalWidth));
// The number 4 below actually represents a padding of 3 pixels on
// each side of the histogram, and is also reflected in other parts of
// the code in the shape of numerical constants like "6" here.
if (intervals > AttributeVisualizationPanel.this.getWidth()) {
intervals = AttributeVisualizationPanel.this.getWidth() - 6;
if (intervals < 1) {
intervals = 1;
}
}
double[] histCounts = new double[intervals];
double barRange = (m_as.numericStats.max - m_as.numericStats.min)
/ histCounts.length;
m_maxValue = 0;
for (int k = 0; k < m_data.numInstances(); k++) {
int t = 0; // This holds the interval to which the current
// attribute's
// value of this particular instance k belongs to.
if (m_data.instance(k).isMissing(m_attribIndex)) {
continue; // ignore missing values
}
try {
// 1. see footnote at the end of this file
t = (int) Math.ceil((float) ((m_data.instance(k).value(
m_attribIndex) - m_as.numericStats.min) / barRange));
if (t == 0) {
histCounts[t] += m_data.instance(k).weight();
if (histCounts[t] > m_maxValue) {
m_maxValue = histCounts[t];
}
} else {
histCounts[t - 1] += m_data.instance(k).weight();
if (histCounts[t - 1] > m_maxValue) {
m_maxValue = histCounts[t - 1];
}
}
} catch (ArrayIndexOutOfBoundsException ae) {
ae.printStackTrace();
System.out
.println("t:"
+ (t)
+ " barRange:"
+ barRange
+ " histLength:"
+ histCounts.length
+ " value:"
+ m_data.instance(k).value(m_attribIndex)
+ " min:"
+ m_as.numericStats.min
+ " sumResult:"
+ (m_data.instance(k).value(m_attribIndex) - m_as.numericStats.min)
+ " divideResult:"
+ (float) ((m_data.instance(k).value(m_attribIndex) - m_as.numericStats.min) / barRange)
+ " finalResult:"
+ Math
.ceil((float) ((m_data.instance(k).value(m_attribIndex) - m_as.numericStats.min) / barRange)));
}
}
m_histBarCounts = histCounts;
m_barRange = barRange;
}
m_threadRun = false;
m_displayCurrentAttribute = true;
m_doneCurrentAttribute = true;
// Image tmpImg = new BufferedImage(getWidth(), getHeight(),
// BufferedImage.TYPE_INT_RGB);
// drawGraph( tmpImg.getGraphics() );
// img = tmpImg;
AttributeVisualizationPanel.this.repaint();
}
}
/****
* Code for M.P.Wand's method of histogram bin width selection. There is
* some problem with it. It always comes up -ve value which is raised to the
* power 1/3 and gives an NAN. private static final int M=400; private
* double psi(int r, double g) { double val;
*
* double sum=0.0; for(int i=0; i
* returns "count <br> [<bars Range>]" if mouse is on the first
* bar. returns "count <br> (<bar's Range>]" if mouse is
* on some bar other than the first one. Otherwise it returns ""
*
* @param ev The mouse event
*/
@Override
public String getToolTipText(MouseEvent ev) {
if (m_as != null && m_as.nominalWeights != null) { // if current attrib is
// nominal
float intervalWidth = this.getWidth()
/ (float) m_as.nominalWeights.length;
double heightRatio;
int barWidth, x = 0;
// if intervalWidth is at least six then bar width is 80% of intervalwidth
if (intervalWidth > 5) {
barWidth = (int) Math.floor(intervalWidth * 0.8F);
} else {
barWidth = 1; // Otherwise barwidth is 1 & padding would be at least 1.
}
// initializing x to maximum of 1 or 10% of interval width (i.e. half of
// the padding which is 20% of interval width, as there is 10% on each
// side of the bar) so that it points to the start of the 1st bar
x = x
+ (int) ((Math.floor(intervalWidth * 0.1F)) < 1 ? 1 : (Math
.floor(intervalWidth * 0.1F)));
// Adding to x the appropriate value so that it points to the 1st bar of
// our "centered" barplot. If subtracting barplots width from panel width
// gives <=2 then the barplot is not centered.
if (this.getWidth()
- (m_as.nominalWeights.length * barWidth + (int) ((Math
.floor(intervalWidth * 0.2F)) < 1 ? 1 : (Math
.floor(intervalWidth * 0.2F)))
* m_as.nominalWeights.length) > 2) {
// The following amounts to adding to x the half of the area left after
// subtracting from the components width the width of the whole barplot
// (i.e. width of all the bars plus the width of all the bar paddings,
// thereby equaling to the whole barplot), since our barplot is
// centered.
x += (this.getWidth() - (m_as.nominalWeights.length * barWidth + (int) ((Math
.floor(intervalWidth * 0.2F)) < 1 ? 1 : (Math
.floor(intervalWidth * 0.2F)))
* m_as.nominalWeights.length)) / 2;
}
for (int i = 0; i < m_as.nominalWeights.length; i++) {
heightRatio = (this.getHeight() - (double) m_fm.getHeight())
/ m_maxValue;
// if our mouse is on a bar then return the count of this bar in our
// barplot
if (ev.getX() >= x
&& ev.getX() <= x + barWidth
&& ev.getY() >= this.getHeight()
- Math.round(m_as.nominalWeights[i] * heightRatio)) {
return (m_data.attribute(m_attribIndex).value(i) + " ["
+ Utils.doubleToString(m_as.nominalWeights[i], 3) + "]");
}
// otherwise advance x to next bar and check that. Add barwidth to x
// and padding which is max(1, 20% of interval width)
x = x
+ barWidth
+ (int) ((Math.floor(intervalWidth * 0.2F)) < 1 ? 1 : (Math
.floor(intervalWidth * 0.2F)));
}
} else if (m_threadRun == false && // if attrib is numeric
(m_histBarCounts != null || m_histBarClassCounts != null)) {
int x = 0, barWidth;
double bar = m_as.numericStats.min;
// if the class attribute is set and it is nominal
if ((m_classIndex >= 0) && (m_data.attribute(m_classIndex).isNominal())) {
// there is 3 pixels of padding on each side of the histogram
// the barwidth is 1 if after removing the padding its width is less
// then the displayable width
barWidth = ((this.getWidth() - 6) / m_histBarClassCounts.length) < 1 ? 1
: ((this.getWidth() - 6) / m_histBarClassCounts.length);
// initializing x to 3 adding appropriate value to make it point to the
// start of the 1st bar of our "centered" histogram.
x = 3;
if ((this.getWidth() - (x + m_histBarClassCounts.length * barWidth)) > 5) {
x += (this.getWidth() - (x + m_histBarClassCounts.length * barWidth)) / 2;
}
if (ev.getX() - x >= 0) {
// The temp holds the index of the current interval that we are
// looking
// at
int temp = (int) ((ev.getX() - x) / (barWidth + 0.0000000001));
if (temp == 0) { // handle the special case temp==0. see footnote 1
double sum = 0;
for (int k = 0; k < m_histBarClassCounts[0].numValues(); k++) {
sum += m_histBarClassCounts[0].valueSparse(k);
}
// return the count of the interval mouse is pointing to plus
// the range of values that fall into this interval
return (""
+ Utils.doubleToString(sum, 3) + "
" + "["
+ Utils.doubleToString(bar + m_barRange * temp, 3) + ", "
+ Utils.doubleToString((bar + m_barRange * (temp + 1)), 3) + "]" + " ");
} else if (temp < m_histBarClassCounts.length) { // handle case
// temp!=0
double sum = 0;
for (int k = 0; k < m_histBarClassCounts[temp].numValues(); k++) {
sum += m_histBarClassCounts[temp].valueSparse(k);
}
// return the count of the interval mouse is pointing to plus
// the range of values that fall into this interval
return (""
+ Utils.doubleToString(sum, 3) + "
("
+ Utils.doubleToString(bar + m_barRange * temp, 3) + ", "
+ Utils.doubleToString((bar + m_barRange * (temp + 1)), 3) + "] ");
}
}
} else { // else if the class attribute is not set or is numeric
barWidth = ((this.getWidth() - 6) / m_histBarCounts.length) < 1 ? 1
: ((this.getWidth() - 6) / m_histBarCounts.length);
// initializing x to 3 adding appropriate value to make it point to the
// start of the 1st bar of our "centered" histogram.
x = 3;
if ((this.getWidth() - (x + m_histBarCounts.length * barWidth)) > 5) {
x += (this.getWidth() - (x + m_histBarCounts.length * barWidth)) / 2;
}
if (ev.getX() - x >= 0) {
// Temp holds the index of the current bar we are looking at.
int temp = (int) ((ev.getX() - x) / (barWidth + 0.0000000001));
// return interval count as well as its range
if (temp == 0) {
return (""
+ m_histBarCounts[0] + "
" + "["
+ Utils.doubleToString(bar + m_barRange * temp, 3) + ", "
+ Utils.doubleToString((bar + m_barRange * (temp + 1)), 3) + "]" + " ");
} else if (temp < m_histBarCounts.length) {
return (""
+ m_histBarCounts[temp] + "
" + "("
+ Utils.doubleToString(bar + m_barRange * temp, 3) + ", "
+ Utils.doubleToString((bar + m_barRange * (temp + 1)), 3) + "]" + " ");
}
}
}
}
return PrintableComponent.getToolTipText(m_Printer);
}
/**
* Paints this component
*
* @param g The graphics object for this component
*/
@Override
public void paintComponent(Graphics g) {
g.setColor(Color.WHITE);
g.fillRect(0, 0, this.getWidth(), this.getHeight());
g.setColor(Color.BLACK);
if (m_as != null) { // If calculations have been done and histogram/barplot
if (!m_doneCurrentAttribute && !m_threadRun) {
calcGraph(this.getWidth(), this.getHeight());
}
if (m_threadRun == false && m_displayCurrentAttribute) { // calculation
// thread is not
// running
int buttonHeight = 0;
if (m_colorAttrib != null) {
buttonHeight = m_colorAttrib.getHeight()
+ m_colorAttrib.getLocation().y;
}
// if current attribute is nominal then draw barplot.
if (m_as.nominalWeights != null
&& (m_histBarClassCounts != null || m_histBarCounts != null)) {
double heightRatio, intervalWidth;
int x = 0, y = 0, barWidth;
// if the class attribute is set and is nominal then draw coloured
// subbars for each bar
if ((m_classIndex >= 0)
&& (m_data.attribute(m_classIndex).isNominal())) {
intervalWidth = (this.getWidth() / (float) m_histBarClassCounts.length);
// Barwidth is 80% of interval width.The remaining 20% is padding,
// 10% on each side of the bar. If interval width is less then 5 the
// 20% of that value is less than 1, in that case we use bar width
// of
// 1 and padding of 1 pixel on each side of the bar.
if (intervalWidth > 5) {
barWidth = (int) Math.floor(intervalWidth * 0.8F);
} else {
barWidth = 1;
}
// initializing x to 10% of interval width or to 1 if 10% is <1.
// This
// is essentially the LHS padding of the 1st bar.
x = x
+ (int) ((Math.floor(intervalWidth * 0.1F)) < 1 ? 1 : (Math
.floor(intervalWidth * 0.1F)));
// Add appropriate value to x so that it starts at the 1st bar of
// a "centered" barplot.
if (this.getWidth()
- (m_histBarClassCounts.length * barWidth + (int) ((Math
.floor(intervalWidth * 0.2F)) < 1 ? 1 : (Math
.floor(intervalWidth * 0.2F)))
* m_histBarClassCounts.length) > 2) {
// We take the width of all the bars and all the paddings (20%
// of interval width), and subtract it from the width of the panel
// to get the extra space that would be left after drawing. We
// divide that space by 2 to get its mid-point and add that to our
// x, thus making the whole bar plot drawn centered in our
// component.
x += (this.getWidth() - (m_histBarClassCounts.length * barWidth + (int) ((Math
.floor(intervalWidth * 0.2F)) < 1 ? 1 : (Math
.floor(intervalWidth * 0.2F)))
* m_histBarClassCounts.length)) / 2;
}
// this holds the count of the bar and will be calculated by adding
// up the counts of individual subbars. It is displayed at the top
// of each bar.
double sum = 0;
for (SparseInstance m_histBarClassCount : m_histBarClassCounts) {
// calculating the proportion of the components height compared to
// the maxvalue in our attribute, also taking into account the
// height of font to display bars count and the height of the
// class
// ComboBox.
heightRatio = (this.getHeight() - (double) m_fm.getHeight() - buttonHeight)
/ m_maxValue;
y = this.getHeight();
if (m_histBarClassCount != null) {
for (int j = 0; j < m_histBarClassCount.numAttributes(); j++) {
sum = sum + m_histBarClassCount.value(j);
y = (int) (y - Math.round(m_histBarClassCount.value(j)
* heightRatio));
// selecting the colour corresponding to the current class.
g.setColor(m_colorList.get(j));
g.fillRect(x, y, barWidth, (int) Math
.round(m_histBarClassCount.value(j) * heightRatio));
g.setColor(Color.black);
}
}
// drawing the bar count at the top of the bar if it is less than
// interval width. draw it 1px up to avoid touching the bar.
if (m_fm.stringWidth(Utils.doubleToString(sum, 1)) < intervalWidth) {
g.drawString(Utils.doubleToString(sum, 1), x, y - 1);
}
// advancing x to the next bar by adding bar width and padding
// of both the bars (i.e. RHS padding of the bar just drawn and
// LHS
// padding of the new bar).
x = x
+ barWidth
+ (int) ((Math.floor(intervalWidth * 0.2F)) < 1 ? 1 : (Math
.floor(intervalWidth * 0.2F)));
// reseting sum for the next bar.
sum = 0;
}
}
// else if class attribute is numeric or not set then draw black bars.
else {
intervalWidth = (this.getWidth() / (float) m_histBarCounts.length);
// same as in the case of nominal class (see inside of if stmt
// corresponding to the current else above).
if (intervalWidth > 5) {
barWidth = (int) Math.floor(intervalWidth * 0.8F);
} else {
barWidth = 1;
}
// same as in the case of nominal class (see inside of if stmt
// corresponding to the current else above).
x = x
+ (int) ((Math.floor(intervalWidth * 0.1F)) < 1 ? 1 : (Math
.floor(intervalWidth * 0.1F)));
// same as in the case of nominal class
if (this.getWidth()
- (m_histBarCounts.length * barWidth + (int) ((Math
.floor(intervalWidth * 0.2F)) < 1 ? 1 : (Math
.floor(intervalWidth * 0.2F)))
* m_histBarCounts.length) > 2) {
x += (this.getWidth() - (m_histBarCounts.length * barWidth + (int) ((Math
.floor(intervalWidth * 0.2F)) < 1 ? 1 : (Math
.floor(intervalWidth * 0.2F)))
* m_histBarCounts.length)) / 2;
}
for (double m_histBarCount : m_histBarCounts) {
// calculating the proportion of the height of the component
// compared to the maxValue in our attribute.
heightRatio = (this.getHeight() - (float) m_fm.getHeight() - buttonHeight)
/ m_maxValue;
y = (int) (this.getHeight() - Math.round(m_histBarCount
* heightRatio));
g.fillRect(x, y, barWidth,
(int) Math.round(m_histBarCount * heightRatio));
// draw the bar count if it's width is smaller than intervalWidth.
// draw it 1px above to avoid touching the bar.
if (m_fm.stringWidth(Utils.doubleToString(m_histBarCount, 1)) < intervalWidth) {
g.drawString(Utils.doubleToString(m_histBarCount, 1), x, y - 1);
}
// Advance x to the next bar by adding bar-width and padding
// of the bars (RHS padding of current bar & LHS padding of next
// bar).
x = x
+ barWidth
+ (int) ((Math.floor(intervalWidth * 0.2F)) < 1 ? 1 : (Math
.floor(intervalWidth * 0.2F)));
}
}
} // <--end if m_as.nominalCount!=null
// if the current attribute is numeric then draw a histogram.
else if (m_as.numericStats != null
&& (m_histBarClassCounts != null || m_histBarCounts != null)) {
double heightRatio;
int x = 0, y = 0, barWidth;
// If the class attribute is set and is not numeric then draw coloured
// subbars for the histogram bars
if ((m_classIndex >= 0)
&& (m_data.attribute(m_classIndex).isNominal())) {
// There is a padding of 3px on each side of the histogram.
barWidth = ((this.getWidth() - 6) / m_histBarClassCounts.length) < 1 ? 1
: ((this.getWidth() - 6) / m_histBarClassCounts.length);
// initializing x to start at the start of the 1st bar after
// padding.
x = 3;
// Adding appropriate value to x to account for a "centered"
// histogram
if ((this.getWidth() - (x + m_histBarClassCounts.length * barWidth)) > 5) {
// We take the current value of x (histogram's RHS padding) and
// add
// the barWidths of all the bars to it to us the size of
// our histogram. We subtract that from the width of the panel
// giving us the extra space that would be left if the histogram
// is
// drawn and divide that by 2 to get the midpoint of that extra
// space. That space is then added to our x, hence making the
// histogram centered.
x += (this.getWidth() - (x + m_histBarClassCounts.length
* barWidth)) / 2;
}
for (SparseInstance m_histBarClassCount : m_histBarClassCounts) {
if (m_histBarClassCount != null) {
// Calculating height ratio. Leave space of 19 for an axis line
// at
// the bottom
heightRatio = (this.getHeight() - (float) m_fm.getHeight()
- buttonHeight - 19)
/ m_maxValue;
y = this.getHeight() - 19;
// This would hold the count of the bar (sum of sub-bars).
double sum = 0;
for (int j = 0; j < m_histBarClassCount.numValues(); j++) {
y = (int) (y - Math.round(m_histBarClassCount.valueSparse(j)
* heightRatio));
// System.out.println("Filling x:"+x+" y:"+y+" width:"+barWidth+
// " height:"+
// (m_histBarClassCounts[i][j]*heightRatio));
// selecting the color corresponding to our class
g.setColor(m_colorList.get(m_histBarClassCount.index(j)));
// drawing the bar if its width is greater than 1
if (barWidth > 1) {
g.fillRect(
x,
y,
barWidth,
(int) Math.round(m_histBarClassCount.valueSparse(j)
* heightRatio));
} else if ((m_histBarClassCount.valueSparse(j) * heightRatio) > 0) {
g.drawLine(
x,
y,
x,
(int) (y + Math.round(m_histBarClassCount.valueSparse(j)
* heightRatio)));
}
g.setColor(Color.black);
sum = sum + m_histBarClassCount.valueSparse(j);
}
// Drawing bar count on the top of the bar if it is < barWidth
if (m_fm.stringWidth(" " + Utils.doubleToString(sum, 1)) < barWidth) {
g.drawString(" " + Utils.doubleToString(sum, 1), x, y - 1);
}
// Moving x to the next bar
x = x + barWidth;
}
}
// Now drawing the axis line at the bottom of the histogram
// initializing x again to the start of the plot
x = 3;
if ((this.getWidth() - (x + m_histBarClassCounts.length * barWidth)) > 5) {
x += (this.getWidth() - (x + m_histBarClassCounts.length
* barWidth)) / 2;
}
g.drawLine(x, this.getHeight() - 17, (barWidth == 1) ? x + barWidth
* m_histBarClassCounts.length - 1 : x + barWidth
* m_histBarClassCounts.length, this.getHeight() - 17); // axis
// line --
// see
// footnote
// 2.
g.drawLine(x, this.getHeight() - 16, x, this.getHeight() - 12); // minimum
// line
g.drawString(Utils.doubleToString(m_as.numericStats.min, 2), x,
this.getHeight() - 12 + m_fm.getHeight()); // minimum value
g.drawLine(x + (barWidth * m_histBarClassCounts.length) / 2,
this.getHeight() - 16, x
+ (barWidth * m_histBarClassCounts.length) / 2,
this.getHeight() - 12); // median line
// Drawing median value. X position for drawing the value is: from
// start of the plot take the mid point and subtract from it half
// of the width of the value to draw.
g.drawString(
Utils.doubleToString(m_as.numericStats.max / 2
+ m_as.numericStats.min / 2, 2),
x
+ (barWidth * m_histBarClassCounts.length)
/ 2
- m_fm.stringWidth(Utils.doubleToString(m_as.numericStats.max
/ 2 + m_as.numericStats.min / 2, 2)) / 2, this.getHeight()
- 12 + m_fm.getHeight()); // median value
g.drawLine((barWidth == 1) ? x + barWidth
* m_histBarClassCounts.length - 1 : x + barWidth
* m_histBarClassCounts.length, this.getHeight() - 16,
(barWidth == 1) ? x + barWidth * m_histBarClassCounts.length - 1
: x + barWidth * m_histBarClassCounts.length,
this.getHeight() - 12); // maximum line
g.drawString(
Utils.doubleToString(m_as.numericStats.max, 2),
(barWidth == 1) ? x
+ barWidth
* m_histBarClassCounts.length
- m_fm.stringWidth(Utils.doubleToString(m_as.numericStats.max,
2)) - 1 : x
+ barWidth
* m_histBarClassCounts.length
- m_fm.stringWidth(Utils.doubleToString(m_as.numericStats.max,
2)), this.getHeight() - 12 + m_fm.getHeight()); // maximum
// value --
// see 2.
} else { // if class attribute is numeric
// There is a padding of 3px on each side of the histogram.
barWidth = ((this.getWidth() - 6) / m_histBarCounts.length) < 1 ? 1
: ((this.getWidth() - 6) / m_histBarCounts.length);
// Same as above. Pls inside of the if stmt.
x = 3;
if ((this.getWidth() - (x + m_histBarCounts.length * barWidth)) > 5) {
x += (this.getWidth() - (x + m_histBarCounts.length * barWidth)) / 2;
}
// Same as above
for (double m_histBarCount : m_histBarCounts) {
// calculating the ration of the component's height compared to
// the maxValue in our current attribute. Leaving 19 pixels to
// draw the axis at the bottom of the histogram.
heightRatio = (this.getHeight() - (float) m_fm.getHeight()
- buttonHeight - 19)
/ m_maxValue;
y = (int) (this.getHeight()
- Math.round(m_histBarCount * heightRatio) - 19);
// System.out.println("Filling x:"+x+" y:"+y+" width:"+barWidth+
// " height:"+(m_histBarCounts[i]*heightRatio));
// same as in the if stmt above
if (barWidth > 1) {
g.drawRect(x, y, barWidth,
(int) Math.round(m_histBarCount * heightRatio));
} else if ((m_histBarCount * heightRatio) > 0) {
g.drawLine(x, y, x,
(int) (y + Math.round(m_histBarCount * heightRatio)));
}
if (m_fm.stringWidth(" "
+ Utils.doubleToString(m_histBarCount, 1)) < barWidth) {
g.drawString(" " + Utils.doubleToString(m_histBarCount, 1), x,
y - 1);
}
x = x + barWidth;
}
// Now drawing the axis at the bottom of the histogram
x = 3;
if ((this.getWidth() - (x + m_histBarCounts.length * barWidth)) > 5) {
x += (this.getWidth() - (x + m_histBarCounts.length * barWidth)) / 2;
}
// This is exact the same as in the if stmt above. See the inside of
// the stmt for details
g.drawLine(x, this.getHeight() - 17, (barWidth == 1) ? x + barWidth
* m_histBarCounts.length - 1 : x + barWidth
* m_histBarCounts.length, this.getHeight() - 17); // axis line
g.drawLine(x, this.getHeight() - 16, x, this.getHeight() - 12); // minimum
// line
g.drawString(Utils.doubleToString(m_as.numericStats.min, 2), x,
this.getHeight() - 12 + m_fm.getHeight()); // minimum value
g.drawLine(x + (barWidth * m_histBarCounts.length) / 2,
this.getHeight() - 16, x + (barWidth * m_histBarCounts.length)
/ 2, this.getHeight() - 12); // median line
g.drawString(
Utils.doubleToString(m_as.numericStats.max / 2
+ m_as.numericStats.min / 2, 2),
x
+ (barWidth * m_histBarCounts.length)
/ 2
- m_fm.stringWidth(Utils.doubleToString(m_as.numericStats.max
/ 2 + m_as.numericStats.min / 2, 2)) / 2, this.getHeight()
- 12 + m_fm.getHeight()); // median value
g.drawLine((barWidth == 1) ? x + barWidth * m_histBarCounts.length
- 1 : x + barWidth * m_histBarCounts.length,
this.getHeight() - 16, (barWidth == 1) ? x + barWidth
* m_histBarCounts.length - 1 : x + barWidth
* m_histBarCounts.length, this.getHeight() - 12); // maximum
// line
g.drawString(
Utils.doubleToString(m_as.numericStats.max, 2),
(barWidth == 1) ? x
+ barWidth
* m_histBarCounts.length
- m_fm.stringWidth(Utils.doubleToString(m_as.numericStats.max,
2)) - 1 : x
+ barWidth
* m_histBarCounts.length
- m_fm.stringWidth(Utils.doubleToString(m_as.numericStats.max,
2)), this.getHeight() - 12 + m_fm.getHeight()); // maximum
// value
}
// System.out.println("barWidth:"+barWidth+
// " histBarCount:"+m_histBarCounts.length);
} else {
g.clearRect(0, 0, this.getWidth(), this.getHeight());
g.drawString(
"Attribute is neither numeric nor nominal.",
this.getWidth() / 2
- m_fm.stringWidth("Attribute is neither numeric nor nominal.")
/ 2, this.getHeight() / 2 - m_fm.getHeight() / 2);
}
} // <--end if of calculation thread
else if (m_displayCurrentAttribute) { // if still calculation thread is
// running plot
g.clearRect(0, 0, this.getWidth(), this.getHeight());
g.drawString("Calculating. Please Wait...",
this.getWidth() / 2 - m_fm.stringWidth("Calculating. Please Wait...")
/ 2, this.getHeight() / 2 - m_fm.getHeight() / 2);
} else if (!m_displayCurrentAttribute) {
g.clearRect(0, 0, this.getWidth(), this.getHeight());
g.drawString("Too many values to display.",
this.getWidth() / 2 - m_fm.stringWidth("Too many values to display.")
/ 2, this.getHeight() / 2 - m_fm.getHeight() / 2);
}
} // <--end if(m_as==null) this means
}
/**
* Main method to test this class from command line
*
* @param args The arff file and the index of the attribute to use
*/
public static void main(String[] args) {
if (args.length != 3) {
final JFrame jf = new JFrame("AttribVisualization");
AttributeVisualizationPanel ap = new AttributeVisualizationPanel();
try {
Instances ins = new Instances(new FileReader(args[0]));
ap.setInstances(ins);
System.out.println("Loaded: " + args[0] + "\nRelation: "
+ ap.m_data.relationName() + "\nAttributes: "
+ ap.m_data.numAttributes());
ap.setAttribute(Integer.parseInt(args[1]));
} catch (Exception ex) {
ex.printStackTrace();
System.exit(-1);
}
System.out.println("The attributes are: ");
for (int i = 0; i < ap.m_data.numAttributes(); i++) {
System.out.println(ap.m_data.attribute(i).name());
}
jf.setSize(500, 300);
jf.getContentPane().setLayout(new BorderLayout());
jf.getContentPane().add(ap, BorderLayout.CENTER);
jf.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
jf.setVisible(true);
} else {
System.out.println("Usage: java AttributeVisualizationPanel"
+ " [arff file] [index of attribute]");
}
}
}
/*
* t =(int) Math.ceil((float)(
* (m_data.instance(k).value(m_attribIndex)-m_as.numericStats.min) / barRange));
* 1. This equation gives a value between (i-1)+smallfraction and i if the
* attribute m_attribIndex for the current instances lies in the ith interval.
* We then increment the value of our i-1th field of our histogram/barplot
* array. If, for example, barRange=3 then, apart from the 1st interval, each
* interval i has values in the range (minValue+3*i-1, minValue+3*i]. The 1st
* interval has range [minValue, minValue+i]. Hence it can be seen in the code
* we specifically handle t=0 separately.
*/
/**
* (barWidth==1)?x+barWidth*m_histBarClassCounts.length-1 :
* x+barWidth*m_histBarClassCounts.length 2. In the case barWidth==1 we subtract
* 1 otherwise the line become one pixel longer than the actual size of the
* histogram
*/
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