org.numenta.nupic.encoders.LogEncoder Maven / Gradle / Ivy
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* Numenta Platform for Intelligent Computing (NuPIC)
* Copyright (C) 2014, Numenta, In Unless you have an agreement
* with Numenta, In, for a separate license for this software code, the
* following terms and conditions apply:
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU Affero Public License version 3 as
* published by the Free Software Foundation.
*
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
* See the GNU Affero Public License for more details.
*
* You should have received a copy of the GNU Affero Public License
* along with this program. If not, see http://www.gnu.org/licenses.
*
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package org.numenta.nupic.encoders;
import gnu.trove.list.TDoubleList;
import gnu.trove.list.array.TDoubleArrayList;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Set;
import org.numenta.nupic.FieldMetaType;
import org.numenta.nupic.model.Connections;
import org.numenta.nupic.util.MinMax;
import org.numenta.nupic.util.Tuple;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
/**
* DOCUMENTATION TAKEN DIRECTLY FROM THE PYTHON VERSION:
*
* This class wraps the ScalarEncoder class.
* A Log encoder represents a floating point value on a logarithmic scale.
* valueToEncode = log10(input)
*
* w -- number of bits to set in output
* minval -- minimum input value. must be greater than 0. Lower values are
* reset to this value
* maxval -- maximum input value (input is strictly less if periodic == True)
* periodic -- If true, then the input value "wraps around" such that minval =
* maxval For a periodic value, the input must be strictly less than
* maxval, otherwise maxval is a true upper bound.
*
* Exactly one of n, radius, resolution must be set. "0" is a special
* value that means "not set".
* n -- number of bits in the representation (must be > w)
* radius -- inputs separated by more than this distance in log space will have
* non-overlapping representations
* resolution -- The minimum change in scaled value needed to produce a change
* in encoding. This should be specified in log space. For
* example, the scaled values 10 and 11 will be distinguishable
* in the output. In terms of the original input values, this
* means 10^1 (1) and 10^1.1 (1.25) will be distinguishable.
* name -- an optional string which will become part of the description
* clipInput -- if true, non-periodic inputs smaller than minval or greater
* than maxval will be clipped to minval/maxval
* forced -- (default False), if True, skip some safety checks
*/
public class LogEncoder extends Encoder {
private static final long serialVersionUID = 1L;
private static final Logger LOG = LoggerFactory.getLogger(LogEncoder.class);
private ScalarEncoder encoder;
private double minScaledValue, maxScaledValue;
/**
* Constructs a new {@code LogEncoder}
*/
LogEncoder() {}
/**
* Returns a builder for building LogEncoders.
* This builder may be reused to produce multiple builders
*
* @return a {@code LogEncoder.Builder}
*/
public static Encoder.Builder builder() {
return new LogEncoder.Builder();
}
/**
* w -- number of bits to set in output
* minval -- minimum input value. must be greater than 0. Lower values are
* reset to this value
* maxval -- maximum input value (input is strictly less if periodic == True)
* periodic -- If true, then the input value "wraps around" such that minval =
* maxval For a periodic value, the input must be strictly less than
* maxval, otherwise maxval is a true upper bound.
*
* Exactly one of n, radius, resolution must be set. "0" is a special
* value that means "not set".
* n -- number of bits in the representation (must be > w)
* radius -- inputs separated by more than this distance in log space will have
* non-overlapping representations
* resolution -- The minimum change in scaled value needed to produce a change
* in encoding. This should be specified in log space. For
* example, the scaled values 10 and 11 will be distinguishable
* in the output. In terms of the original input values, this
* means 10^1 (1) and 10^1.1 (1.25) will be distinguishable.
* name -- an optional string which will become part of the description
* clipInput -- if true, non-periodic inputs smaller than minval or greater
* than maxval will be clipped to minval/maxval
* forced -- (default False), if True, skip some safety checks
*/
public void init() {
double lowLimit = 1e-07;
// w defaults to 5
if (getW() == 0) {
setW(5);
}
// maxVal defaults to 10000.
if (getMaxVal() == 0.0) {
setMaxVal(10000.);
}
if (getMinVal() < lowLimit) {
setMinVal(lowLimit);
}
if (getMinVal() >= getMaxVal()) {
throw new IllegalStateException("Max val must be larger than min val or the lower limit " +
"for this encoder " + String.format("%.7f", lowLimit));
}
minScaledValue = Math.log10(getMinVal());
maxScaledValue = Math.log10(getMaxVal());
if(minScaledValue >= maxScaledValue) {
throw new IllegalStateException("Max val must be larger, in log space, than min val.");
}
// There are three different ways of thinking about the representation. Handle
// each case here.
encoder = ScalarEncoder.builder()
.w(getW())
.minVal(minScaledValue)
.maxVal(maxScaledValue)
.periodic(false)
.n(getN())
.radius(getRadius())
.resolution(getResolution())
.clipInput(clipInput())
.forced(isForced())
.name(getName())
.build();
setN(encoder.getN());
setResolution(encoder.getResolution());
setRadius(encoder.getRadius());
}
@Override
public int getWidth() {
return encoder.getWidth();
}
@Override
public boolean isDelta() {
return encoder.isDelta();
}
@Override
public List getDescription() {
return encoder.getDescription();
}
/**
* {@inheritDoc}
*/
@Override
public Set getDecoderOutputFieldTypes() {
return encoder.getDecoderOutputFieldTypes();
}
/**
* Convert the input, which is in normal space, into log space
* @param input Value in normal space.
* @return Value in log space.
*/
private Double getScaledValue(double input) {
if(input == SENTINEL_VALUE_FOR_MISSING_DATA) {
return null;
} else {
double val = input;
if (val < getMinVal()) {
val = getMinVal();
} else if (val > getMaxVal()) {
val = getMaxVal();
}
return Math.log10(val);
}
}
/**
* Returns the bucket indices.
*
* @param input
*/
@Override
public int[] getBucketIndices(double input) {
Double scaledVal = getScaledValue(input);
if (scaledVal == null) {
return new int[]{};
} else {
return encoder.getBucketIndices(scaledVal);
}
}
/**
* Encodes inputData and puts the encoded value into the output array,
* which is a 1-D array of length returned by {@link Connections#getW()}.
*
* Note: The output array is reused, so clear it before updating it.
* @param inputData Data to encode. This should be validated by the encoder.
* @param output 1-D array of same length returned by {@link Connections#getW()}
*
* @return
*/
@Override
public void encodeIntoArray(Double input, int[] output) {
Double scaledVal = getScaledValue(input);
if (scaledVal == null) {
Arrays.fill(output, 0);
} else {
encoder.encodeIntoArray(scaledVal, output);
LOG.trace("input: " + input);
LOG.trace(" scaledVal: " + scaledVal);
LOG.trace(" output: " + Arrays.toString(output));
}
}
/**
* {@inheritDoc}
*/
@Override
public DecodeResult decode(int[] encoded, String parentFieldName) {
// Get the scalar values from the underlying scalar encoder
DecodeResult decodeResult = encoder.decode(encoded, parentFieldName);
Map fields = decodeResult.getFields();
if (fields.keySet().size() == 0) {
return decodeResult;
}
// Convert each range into normal space
RangeList inRanges = (RangeList) fields.values().toArray()[0];
RangeList outRanges = new RangeList(new ArrayList(), "");
for (MinMax minMax : inRanges.getRanges()) {
MinMax scaledMinMax = new MinMax( Math.pow(10, minMax.min()),
Math.pow(10, minMax.max()));
outRanges.add(scaledMinMax);
}
// Generate a text description of the ranges
String desc = "";
int numRanges = outRanges.size();
for (int i = 0; i < numRanges; i++) {
MinMax minMax = outRanges.getRange(i);
if (minMax.min() != minMax.max()) {
desc += String.format("%.2f-%.2f", minMax.min(), minMax.max());
} else {
desc += String.format("%.2f", minMax.min());
}
if (i < numRanges - 1) {
desc += ", ";
}
}
outRanges.setDescription(desc);
String fieldName;
if (!parentFieldName.equals("")) {
fieldName = String.format("%s.%s", parentFieldName, getName());
} else {
fieldName = getName();
}
Map outFields = new HashMap();
outFields.put(fieldName, outRanges);
List fieldNames = new ArrayList();
fieldNames.add(fieldName);
return new DecodeResult(outFields, fieldNames);
}
/**
* {@inheritDoc}
*/
@SuppressWarnings("unchecked")
@Override
public List getBucketValues(Class t) {
// Need to re-create?
if(bucketValues == null) {
List scaledValues = encoder.getBucketValues(t);
bucketValues = new ArrayList();
for (S scaledValue : scaledValues) {
double value = Math.pow(10, (Double)scaledValue);
((List)bucketValues).add(value);
}
}
return (List)bucketValues;
}
/**
* {@inheritDoc}
*/
@Override
public List getBucketInfo(int[] buckets) {
Encoding scaledResult = encoder.getBucketInfo(buckets).get(0);
double scaledValue = (Double)scaledResult.getValue();
double value = Math.pow(10, scaledValue);
return Arrays.asList(new Encoding(value, value, scaledResult.getEncoding()));
}
/**
* {@inheritDoc}
*/
@Override
public List topDownCompute(int[] encoded) {
Encoding scaledResult = encoder.topDownCompute(encoded).get(0);
double scaledValue = (Double)scaledResult.getValue();
double value = Math.pow(10, scaledValue);
return Arrays.asList(new Encoding(value, value, scaledResult.getEncoding()));
}
/**
* {@inheritDoc}
*/
@Override
public TDoubleList closenessScores(TDoubleList expValues, TDoubleList actValues, boolean fractional) {
TDoubleList retVal = new TDoubleArrayList();
double expValue, actValue;
if (expValues.get(0) > 0) {
expValue = Math.log10(expValues.get(0));
} else {
expValue = minScaledValue;
}
if (actValues.get(0) > 0) {
actValue = Math.log10(actValues.get(0));
} else {
actValue = minScaledValue;
}
double closeness;
if (fractional) {
double err = Math.abs(expValue - actValue);
double pctErr = err / (maxScaledValue - minScaledValue);
pctErr = Math.min(1.0, pctErr);
closeness = 1.0 - pctErr;
} else {
closeness = Math.abs(expValue - actValue);;
}
retVal.add(closeness);
return retVal;
}
/**
* Returns a {@link EncoderBuilder} for constructing {@link ScalarEncoder}s
*
* The base class architecture is put together in such a way where boilerplate
* initialization can be kept to a minimum for implementing subclasses, while avoiding
* the mistake-proneness of extremely long argument lists.
*
* @see ScalarEncoder.Builder#setStuff(int)
*/
public static class Builder extends Encoder.Builder {
private Builder() {}
@Override
public LogEncoder build() {
//Must be instantiated so that super class can initialize
//boilerplate variables.
encoder = new LogEncoder();
//Call super class here
super.build();
////////////////////////////////////////////////////////
// Implementing classes would do setting of specific //
// vars here together with any sanity checking //
////////////////////////////////////////////////////////
try {
((LogEncoder)encoder).init();
}catch(Exception e) {
String msg = null;
int idx = -1;
if((idx = (msg = e.getMessage()).indexOf("ScalarEncoder")) != -1) {
msg = msg.substring(0, idx).concat("LogEncoder");
}
throw new IllegalStateException(msg);
}
return (LogEncoder)encoder;
}
}
}
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