mirror of https://github.com/jlizier/jidt
Adding MI Auto Analyser GUI, plus minor bug corrections to TE Auto Analyser GUI
This commit is contained in:
joseph.lizier
parent
ed34c39660
commit
f23b0c6abb
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@ -0,0 +1,8 @@
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@ECHO OFF
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REM Make sure the latest example source file is compiled.
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javac -classpath "..\java;..\..\infodynamics.jar" "..\java\infodynamics\demos\autoanalysis\AutoAnalyserMI.java"
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REM Run the example:
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java -classpath "..\java;..\..\infodynamics.jar" infodynamics.demos.autoanalysis.AutoAnalyserMI
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#!/bin/bash
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# Make sure the latest example source file is compiled.
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javac -classpath "../java:../../infodynamics.jar" "../java/infodynamics/demos/autoanalysis/AutoAnalyserMI.java"
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# Run the example:
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java -classpath "../java:../../infodynamics.jar" infodynamics.demos.autoanalysis.AutoAnalyserMI
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@ -3,6 +3,6 @@
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REM Make sure the latest example source file is compiled.
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javac -classpath "..\java;..\..\infodynamics.jar" "..\java\infodynamics\demos\autoanalysis\AutoAnalyserTE.java"
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# Run the example:
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REM Run the example:
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java -classpath "..\java;..\..\infodynamics.jar" infodynamics.demos.autoanalysis.AutoAnalyserTE
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@ -300,8 +300,12 @@ public abstract class AutoAnalyser extends JFrame
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// Set up for ~18 rows maximum (the +6 is exact to fit all props
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// for Kraskov TE in without scrollbar)
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Dimension d = propertiesTable.getPreferredSize();
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int rowHeight = propertiesTable.getRowHeight();
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propsTableScrollPane.setPreferredSize(
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new Dimension(d.width,propertiesTable.getRowHeight()*17+6));
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new Dimension(d.width,rowHeight*17+6));
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propsTableScrollPane.setMinimumSize(
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new Dimension(d.width,rowHeight*17+6));
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System.out.println("Row height was " + rowHeight);
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// Button to compute
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@ -650,7 +654,8 @@ public abstract class AutoAnalyser extends JFrame
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calcContinuous.getClass().getSimpleName() + "\n";
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matlabConstructorLine = "calc = javaObject('infodynamics.measures.continuous.gaussian." +
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calcContinuous.getClass().getSimpleName() + "');\n";
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} else if (selectedCalcType.equalsIgnoreCase(CALC_TYPE_KRASKOV)) {
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} else if (selectedCalcType.startsWith(CALC_TYPE_KRASKOV)) {
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// The if statement will work for both MI Kraskov calculators
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// Cover the calculator and any references to conditional MI calculator properties
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javaCode.append("import infodynamics.measures.continuous.kraskov.*;\n");
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javaConstructorLine = " calc = new " + calcContinuous.getClass().getSimpleName() + "();\n";
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@ -1106,7 +1111,8 @@ public abstract class AutoAnalyser extends JFrame
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classSpecificPropertyNames = gaussianProperties;
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classSpecificPropertiesFieldNames = gaussianPropertiesFieldNames;
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classSpecificPropertyDescriptions = gaussianPropertyDescriptions;
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} else if (selectedCalcType.equalsIgnoreCase(CALC_TYPE_KRASKOV)) {
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} else if (selectedCalcType.startsWith(CALC_TYPE_KRASKOV)) {
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// The if statement will work for both MI Kraskov calculators
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classSpecificPropertyNames = kraskovProperties;
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classSpecificPropertiesFieldNames = kraskovPropertiesFieldNames;
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classSpecificPropertyDescriptions = kraskovPropertyDescriptions;
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@ -0,0 +1,221 @@
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/*
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* Java Information Dynamics Toolkit (JIDT)
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* Copyright (C) 2015, Joseph T. Lizier
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*
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* This program is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with this program. If not, see <http://www.gnu.org/licenses/>.
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*/
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package infodynamics.demos.autoanalysis;
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import infodynamics.measures.continuous.ChannelCalculatorCommon;
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import infodynamics.measures.continuous.MutualInfoCalculatorMultiVariate;
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import infodynamics.measures.continuous.gaussian.MutualInfoCalculatorMultiVariateGaussian;
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import infodynamics.measures.continuous.kernel.MutualInfoCalculatorMultiVariateKernel;
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import infodynamics.measures.continuous.kraskov.MutualInfoCalculatorMultiVariateKraskov;
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import infodynamics.measures.continuous.kraskov.MutualInfoCalculatorMultiVariateKraskov1;
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import infodynamics.measures.continuous.kraskov.MutualInfoCalculatorMultiVariateKraskov2;
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import infodynamics.measures.discrete.MutualInformationCalculatorDiscrete;
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import javax.swing.JOptionPane;
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import javax.swing.event.DocumentListener;
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import java.awt.event.ActionListener;
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import java.awt.event.MouseListener;
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/**
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* This class provides a GUI to build a simple mutual information calculation,
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* and supply the code to execute it.
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*
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*
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* @author Joseph Lizier
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*
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*/
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public class AutoAnalyserMI extends AutoAnalyser
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implements ActionListener, DocumentListener, MouseListener {
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/**
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* Need serialVersionUID to be serializable
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*/
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private static final long serialVersionUID = 1L;
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protected static final String DISCRETE_PROPNAME_TIME_DIFF = "time difference";
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protected static final String CALC_TYPE_KRASKOV_ALG1 = CALC_TYPE_KRASKOV + " alg. 1";
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protected static final String CALC_TYPE_KRASKOV_ALG2 = CALC_TYPE_KRASKOV + " alg. 2";
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/**
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* Constructor to initialise the GUI for MI
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*/
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protected void makeSpecificInitialisations() {
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// Set up the properties for MI:
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measureAcronym = "MI";
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appletTitle = "JIDT Mutual Information Auto-Analyser";
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calcTypes = new String[] {
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CALC_TYPE_DISCRETE, CALC_TYPE_GAUSSIAN,
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CALC_TYPE_KRASKOV_ALG1, CALC_TYPE_KRASKOV_ALG2,
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CALC_TYPE_KERNEL};
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unitsForEachCalc = new String[] {"bits", "nats", "nats", "nats", "bits"};
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// Discrete:
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discreteClass = MutualInformationCalculatorDiscrete.class;
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discreteProperties = new String[] {
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DISCRETE_PROPNAME_BASE,
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DISCRETE_PROPNAME_TIME_DIFF
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};
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discretePropertyDefaultValues = new String[] {
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"2",
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"0",
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};
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discretePropertyDescriptions = new String[] {
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"Number of discrete states available for each variable (i.e. 2 for binary)",
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"Time-lag from source to dest to consider MI across; must be >= 0 (0 for standard MI)",
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};
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// Continuous:
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abstractContinuousClass = MutualInfoCalculatorMultiVariate.class;
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// Common properties for all continuous calcs:
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commonContPropertyNames = new String[] {
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MutualInfoCalculatorMultiVariate.PROP_TIME_DIFF
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};
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commonContPropertiesFieldNames = new String[] {
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"PROP_TIME_DIFF"
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};
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commonContPropertyDescriptions = new String[] {
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"Time-lag from source to dest to consider MI across; must be >= 0 (0 for standard MI)"
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};
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// Gaussian properties:
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gaussianProperties = new String[] {
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};
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gaussianPropertiesFieldNames = new String[] {
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};
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gaussianPropertyDescriptions = new String[] {
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};
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// Kernel:
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kernelProperties = new String[] {
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MutualInfoCalculatorMultiVariateKernel.KERNEL_WIDTH_PROP_NAME,
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MutualInfoCalculatorMultiVariateKernel.DYN_CORR_EXCL_TIME_NAME,
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MutualInfoCalculatorMultiVariateKernel.NORMALISE_PROP_NAME,
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};
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kernelPropertiesFieldNames = new String[] {
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"KERNEL_WIDTH_PROP_NAME",
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"DYN_CORR_EXCL_TIME_NAME",
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"NORMALISE_PROP_NAME"
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};
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kernelPropertyDescriptions = new String[] {
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"Kernel width to be used in the calculation. <br/>If the property " +
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MutualInfoCalculatorMultiVariateKernel.NORMALISE_PROP_NAME +
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" is set, then this is a number of standard deviations; " +
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"otherwise it is an absolute value.",
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"Dynamic correlation exclusion time or <br/>Theiler window (see Kantz and Schreiber); " +
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"0 (default) means no dynamic exclusion window",
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"(boolean) whether to normalise <br/>each incoming time-series to mean 0, standard deviation 1, or not (recommended)",
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};
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// KSG (Kraskov):
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kraskovProperties = new String[] {
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MutualInfoCalculatorMultiVariateKraskov.PROP_NORMALISE,
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MutualInfoCalculatorMultiVariateKraskov.PROP_K,
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MutualInfoCalculatorMultiVariateKraskov.PROP_ADD_NOISE,
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MutualInfoCalculatorMultiVariateKraskov.PROP_DYN_CORR_EXCL_TIME,
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MutualInfoCalculatorMultiVariateKraskov.PROP_NORM_TYPE,
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MutualInfoCalculatorMultiVariateKraskov.PROP_NUM_THREADS,
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};
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kraskovPropertiesFieldNames = new String[] {
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"MutualInfoCalculatorMultiVariateKraskov.PROP_NORMALISE",
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"MutualInfoCalculatorMultiVariateKraskov.PROP_K",
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"MutualInfoCalculatorMultiVariateKraskov.PROP_ADD_NOISE",
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"MutualInfoCalculatorMultiVariateKraskov.PROP_DYN_CORR_EXCL_TIME",
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"MutualInfoCalculatorMultiVariateKraskov.PROP_NORM_TYPE",
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"MutualInfoCalculatorMultiVariateKraskov.PROP_NUM_THREADS",
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};
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kraskovPropertyDescriptions = new String[] {
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"(boolean) whether to normalise <br/>each incoming time-series to mean 0, standard deviation 1, or not (recommended)",
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"Number of k nearest neighbours to use <br/>in the full joint kernel space in the KSG algorithm",
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"Standard deviation for an amount <br/>of random Gaussian noise to add to each variable, " +
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"to avoid having neighbourhoods with artificially large counts. <br/>" +
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"(\"false\" may be used to indicate \"0\".). The amount is added in after any normalisation.",
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"Dynamic correlation exclusion time or <br/>Theiler window (see Kantz and Schreiber); " +
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"0 (default) means no dynamic exclusion window",
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"<br/>Norm type to use in KSG algorithm between the points in each marginal space. <br/>Options are: " +
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"\"MAX_NORM\" (default), otherwise \"EUCLIDEAN\" or \"EUCLIDEAN_SQUARED\" (both equivalent here)",
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"Number of parallel threads to use <br/>in computation: an integer > 0 or \"USE_ALL\" " +
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"(default, to indicate to use all available processors)",
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};
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}
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/**
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* Method to assign and initialise our continuous calculator class
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*/
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protected ChannelCalculatorCommon assignCalcObjectContinuous(String selectedCalcType) throws Exception {
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if (selectedCalcType.equalsIgnoreCase(CALC_TYPE_GAUSSIAN)) {
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return new MutualInfoCalculatorMultiVariateGaussian();
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} else if (selectedCalcType.equalsIgnoreCase(CALC_TYPE_KRASKOV_ALG1)) {
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return new MutualInfoCalculatorMultiVariateKraskov1();
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} else if (selectedCalcType.equalsIgnoreCase(CALC_TYPE_KRASKOV_ALG2)) {
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return new MutualInfoCalculatorMultiVariateKraskov2();
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} else if (selectedCalcType.equalsIgnoreCase(CALC_TYPE_KERNEL)) {
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return new MutualInfoCalculatorMultiVariateKernel();
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} else {
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throw new Exception("No recognised continuous calculator selected: " +
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selectedCalcType);
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}
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}
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/**
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* Method to assign and initialise our discrete calculator class
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*/
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protected DiscreteCalcAndArguments assignCalcObjectDiscrete() throws Exception {
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String timeDiffPropValueStr, basePropValueStr;
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try {
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timeDiffPropValueStr = propertyValues.get(DISCRETE_PROPNAME_TIME_DIFF);
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} catch (Exception ex) {
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JOptionPane.showMessageDialog(this,
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ex.getMessage());
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resultsLabel.setText("Cannot find a value for property " + DISCRETE_PROPNAME_TIME_DIFF);
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return null;
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}
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try {
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basePropValueStr = propertyValues.get(DISCRETE_PROPNAME_BASE);
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} catch (Exception ex) {
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JOptionPane.showMessageDialog(this,
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ex.getMessage());
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resultsLabel.setText("Cannot find a value for property " + DISCRETE_PROPNAME_BASE);
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return null;
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}
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int timeDiff = Integer.parseInt(timeDiffPropValueStr);
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int base = Integer.parseInt(basePropValueStr);
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return new DiscreteCalcAndArguments(
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new MutualInformationCalculatorDiscrete(base, timeDiff),
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base,
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base + ", " + timeDiff);
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}
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protected void setObservations(ChannelCalculatorCommon calc,
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double[] source, double[] dest) throws Exception {
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// We know this is a MutualInfoCalculatorMultiVariate
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MutualInfoCalculatorMultiVariate miCalc = (MutualInfoCalculatorMultiVariate) calc;
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miCalc.setObservations(source, dest);
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}
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/**
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* @param args
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*/
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public static void main(String[] args) {
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new AutoAnalyserMI();
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}
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}
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@ -219,7 +219,7 @@ public class AutoAnalyserTE extends AutoAnalyser
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} catch (Exception ex) {
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JOptionPane.showMessageDialog(this,
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ex.getMessage());
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resultsLabel.setText("Cannot find a value for property " + DISCRETE_PROPNAME_BASE);
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resultsLabel.setText("Cannot find a value for property " + DISCRETE_PROPNAME_K);
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return null;
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}
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try {
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