diff --git a/modules/core/src/main/java/org/locationtech/jts/algorithm/distance/DiscreteFrechetDistance.java b/modules/core/src/main/java/org/locationtech/jts/algorithm/distance/DiscreteFrechetDistance.java new file mode 100644 index 0000000000..c934584aa9 --- /dev/null +++ b/modules/core/src/main/java/org/locationtech/jts/algorithm/distance/DiscreteFrechetDistance.java @@ -0,0 +1,569 @@ +/* + * Copyright (c) 2021 Felix Obermaier. + * + * All rights reserved. This program and the accompanying materials + * are made available under the terms of the Eclipse Public License 2.0 + * and Eclipse Distribution License v. 1.0 which accompanies this distribution. + * The Eclipse Public License is available at http://www.eclipse.org/legal/epl-v20.html + * and the Eclipse Distribution License is available at + * + * http://www.eclipse.org/org/documents/edl-v10.php. + */ +package org.locationtech.jts.algorithm.distance; + +import org.locationtech.jts.geom.Coordinate; +import org.locationtech.jts.geom.Geometry; +import org.locationtech.jts.util.Assert; + +import java.util.Arrays; +import java.util.HashMap; + +/** + * The Fréchet distance is a measure of similarity between curves. Thus, it can + * be used like the Hausdorff distance. + *

+ * An analogy for the Fréchet distance taken from + * + * Computing Discrete Fréchet Distance + * 

+ * A man is walking a dog on a leash: the man can move
+ * on one curve, the dog on the other; both may vary their
+ * speed, but backtracking is not allowed.
+ *
+ *

+ * Its metric is better than Hausdorff's because it takes the flow of the curves + * into account. It is possible that two curves have a small Hausdorff but a large + * Fréchet distance. + *

+ * This implementation is base on the following optimized Fréchet distance algorithm: + * 

Thomas Devogele, Maxence Esnault, Laurent Etienne. Distance discrète de Fréchet optimisée. Spatial
+ * Analysis and Geomatics (SAGEO), Nov 2016, Nice, France. hal-02110055
+ *

+ * Several matrix storage implementations are provided + * + * @see Fréchet distance + * @see + * Computing Discrete Fréchet Distance + * @see Distance discrète de Fréchet optimisée + * @see + * Fast Discrete Fréchet Distance + */ +public class DiscreteFrechetDistance { + + /** + * Computes the Discrete Fréchet Distance between two {@link Geometry}s + * using a {@code cartesian} distance computation function. + * + * @param g0 the 1st geometry + * @param g1 the 2nd geometry + * @return the cartesian distance between {#g0} and {#g1} + */ + public static double distance(Geometry g0, Geometry g1) { + + DiscreteFrechetDistance dist = new DiscreteFrechetDistance(g0, g1); + return dist.distance(); + } + + private final Geometry g0; + private final Geometry g1; + private PointPairDistance ptDist; + + /** + * Creates an instance of this class using the provided geometries. + * + * @param g0 a geometry + * @param g1 a geometry + */ + private DiscreteFrechetDistance(Geometry g0, Geometry g1) { + this.g0 = g0; + this.g1 = g1; + } + + /** + * Compute the {@code Discrete Fréchet Distance} between two geometries + * + * @return the Discrete Fréchet Distance + */ + private double distance() { + Coordinate[] coords0 = g0.getCoordinates(); + Coordinate[] coords1 = g1.getCoordinates(); + + MatrixStorage distances = createMatrixStorage(coords0.length, coords1.length); + int[] diagonal = bresenhamLine(coords0.length, coords1.length); + + HashMap distanceToPair = new HashMap<>(); + computeCoordinateDistances(coords0, coords1, diagonal, distances, distanceToPair); + ptDist = computeFrechet(coords0, coords1, diagonal, distances, distanceToPair); + + return ptDist.getDistance(); + } + + /** + * Creates a matrix storage + * @param rows the number of rows + * @param cols the number of columns + * @return a matrix storage + */ + private MatrixStorage createMatrixStorage(int rows, int cols) { + + int max = Math.max(rows, cols); + // NOTE: these constraints need to be verified + if (max < 1024) + return new RectMatrix(rows, cols, Double.POSITIVE_INFINITY); + + return new CsrMatrix(rows, cols, Double.POSITIVE_INFINITY); + } + + /** + * Gets the pair of Coordinates that are {@link #distance()} apart. + * + * @return the pair of Coordinates that are {@link #distance()} apart + */ + public Coordinate[] getCoordinates() { + if (ptDist == null) + distance(); + + return ptDist.getCoordinates(); + } + + /** + * Compute the Fréchet Distance for the given distance matrix. + * + * @param coords0 an array of {@code Coordinate}s. + * @param coords1 an array of {@code Coordinate}s. + * @param distances a sparse distance matrix + * @param distanceToPair a lookup for distance and a coordinate pair + * @param diagonal an array of alternating row/col index values for the diagonal of the distance matrix + * + */ + private static PointPairDistance computeFrechet(Coordinate[] coords0, Coordinate[] coords1, int[] diagonal, + MatrixStorage distances, HashMap distanceToPair) { + for (int d = 0; d < diagonal.length; d += 2) { + int i0 = diagonal[d]; + int j0 = diagonal[d + 1]; + + for (int i = i0; i < coords0.length; i++) { + if (distances.isValueSet(i, j0)) { + double dist = getMinDistanceAtCorner(distances, i, j0); + if (dist > distances.get(i, j0)) + distances.set(i, j0, dist); + } + else { + break; + } + } + for (int j = j0 + 1; j < coords1.length; j++) { + if (distances.isValueSet(i0, j)) { + double dist = getMinDistanceAtCorner(distances, i0, j); + if (dist > distances.get(i0, j)) + distances.set(i0, j, dist); + } + else { + break; + } + } + } + + PointPairDistance result = new PointPairDistance(); + double distance = distances.get(coords0.length-1, coords1.length - 1); + int[] index = distanceToPair.get(distance); + if (index != null) + result.initialize(coords0[index[0]], coords1[index[1]], distance); + else + Assert.shouldNeverReachHere("Pair of points not recorded for computed distance"); + + return result; + } + + /** + * Returns the minimum distance at the corner ({@code i, j}). + * + * @param matrix A sparse matrix + * @param i the column index + * @param j the row index + * @return the minimum distance + */ + private static double getMinDistanceAtCorner(MatrixStorage matrix, int i, int j) { + if (i > 0 && j > 0) { + double d0 = matrix.get(i - 1, j - 1); + double d1 = matrix.get(i - 1, j); + double d2 = matrix.get(i, j - 1); + return Math.min(Math.min(d0, d1), d2); + } + if (i == 0 && j == 0) + return matrix.get(0, 0); + + if (i == 0) + return matrix.get(0, j - 1); + + // j == 0 + return matrix.get(i - 1, 0); + } + + /** + * Computes relevant distances between pairs of {@link Coordinate}s for the + * computation of the {@code Discrete Fréchet Distance}. + * + * @param coords0 an array of {@code Coordinate}s. + * @param coords1 an array of {@code Coordinate}s. + * @param diagonal an array of encoded row/col index values for the diagonal of the distance matrix + * @param distances the sparse distance matrix + * @param distanceToPair a lookup for coordinate pairs based on a distance. + */ + private void computeCoordinateDistances(Coordinate[] coords0, Coordinate[] coords1, int[] diagonal, + MatrixStorage distances, HashMap distanceToPair) { + int numDiag = diagonal.length; + double maxDistOnDiag = 0d; + int imin = 0, jmin = 0; + int numCoords0 = coords0.length; + int numCoords1 = coords1.length; + + // First compute all the distances along the diagonal. + // Record the maximum distance. + + for (int k = 0; k < numDiag; k += 2) { + int i0 = diagonal[k]; + int j0 = diagonal[k + 1]; + double diagDist = coords0[i0].distance(coords1[j0]); + if (diagDist > maxDistOnDiag) maxDistOnDiag = diagDist; + distances.set(i0, j0, diagDist); + distanceToPair.putIfAbsent(diagDist, new int[] {i0, j0}); + } + + // Check for distances shorter than maxDistOnDiag along the diagonal + for (int k = 0; k < numDiag - 2; k += 2) { + // Decode index + int i0 = diagonal[k]; + int j0 = diagonal[k + 1]; + + // Get reference coordinates for col and row + Coordinate coord0 = coords0[i0]; + Coordinate coord1 = coords1[j0]; + + // Check for shorter distances in this row + int i = i0 + 1; + for (; i < numCoords0; i++) { + if (!distances.isValueSet(i, j0)) { + double dist = coords0[i].distance(coord1); + if (dist < maxDistOnDiag || i < imin) { + distances.set(i, j0, dist); + distanceToPair.putIfAbsent(dist, new int[] {i, j0}); + } + else + break; + } + else + break; + } + imin = i; + + // Check for shorter distances in this column + int j = j0 + 1; + for (; j < numCoords1; j++) { + if (!distances.isValueSet(i0, j)) { + double dist = coord0.distance(coords1[j]); + if (dist < maxDistOnDiag || j < jmin) + { + distances.set(i0, j, dist); + distanceToPair.putIfAbsent(dist, new int[] {i0, j}); + } + else + break; + } + else + break; + } + jmin = j; + } + + //System.out.println(distances.toString()); + } + + /** + * Implementation of the + * Bresenham's line algorithm for the diagonal of a {@code numCols x numRows} grid. + * + * @param numCols the number of columns + * @param numRows the number of rows + * @return an array of column and row indices bitwise-or combined. + */ + private static int[] bresenhamLine(int numCols, int numRows) { + int dim = Math.max(numCols, numRows); + int[] pairs = new int[2 * dim]; + + int sx = 0 > numCols ? -1 : 1; + int sy = 0 > numRows ? -1 : 1; + int x = 0; + int y = 0; + + int err; + if (numCols > numRows) { + err = numCols / 2; + for (int i = 0, j = 0; i < numCols; i++) { + pairs[j++] = x; + pairs[j++] = y; + err -= numRows; + if (err < 0) { + y += sy; + err += numCols; + } + x += sx; + } + } else { + err = numRows / 2; + for (int i = 0, j = 0; i < numRows; i++) { + pairs[j++] = x; + pairs[j++] = y; + err -= numCols; + if (err < 0) { + x += sx; + err += numRows; + } + y += sy; + } + } + return pairs; + } + + /** + * Abstract base class for storing 2d matrix data + */ + abstract static class MatrixStorage { + + protected final int numRows; + protected final int numCols; + protected final double defaultValue; + + /** + * Creates an instance of this class + * @param numRows the number of rows + * @param numCols the number of columns + * @param defaultValue A default value + */ + public MatrixStorage(int numRows, int numCols, double defaultValue) + { + this.numRows = numRows; + this.numCols = numCols; + this.defaultValue = defaultValue; + } + + /** + * Gets the matrix value at i, j + * @param i the row index + * @param j the column index + * @return The matrix value at i, j + */ + public abstract double get(int i, int j); + + /** + * Sets the matrix value at i, j + * @param i the row index + * @param j the column index + * @param value The matrix value to set at i, j + */ + public abstract void set(int i, int j, double value); + + /** + * Gets a flag indicating if the matrix has a set value, e.g. one that is different + * than {@link MatrixStorage#defaultValue}. + * @param i the row index + * @param j the column index + * @return a flag indicating if the matrix has a set value + */ + public abstract boolean isValueSet(int i, int j); + + /* For debugging purposes only + @Override + public String toString() { + StringBuilder sb = new StringBuilder("["); + for (int i = 0; i < this.numRows; i++) + { + sb.append('['); + for(int j = 0; j < this.numCols; j++) + { + if (j > 0) + sb.append(", "); + sb.append(String.format(java.util.Locale.ROOT, "%8.4f", get(i, j))); + } + sb.append(']'); + if (i < this.numRows - 1) sb.append(",\n"); + } + sb.append(']'); + return sb.toString(); + } + */ + } + + /** + * Straight forward implementation of a rectangular matrix + */ + final static class RectMatrix extends MatrixStorage { + + private final double[] matrix; + + /** + * Creates an instance of this matrix using the given number of rows and columns. + * A default value can be specified + * + * @param numRows the number of rows + * @param numCols the number of columns + * @param defaultValue A default value + */ + public RectMatrix(int numRows, int numCols, double defaultValue) + { + super(numRows, numCols, defaultValue); + this.matrix = new double[numRows * numCols]; + Arrays.fill(this.matrix, defaultValue); + } + + public double get(int i, int j) { return this.matrix[i * numCols + j]; } + + public void set(int i, int j, double value) { + this.matrix[i * numCols + j] = value; + } + + public boolean isValueSet(int i, int j) { + return Double.doubleToLongBits(get(i, j)) != Double.doubleToLongBits(this.defaultValue); + } + } + + /** + * A matrix implementation that adheres to the + * + * Compressed sparse row format.
+ * Note: Unfortunately not as fast as expected. + */ + final static class CsrMatrix extends MatrixStorage { + + private double[] v; + private final int[] ri; + private int[] ci; + + public CsrMatrix(int numRows, int numCols, double defaultValue) { + this(numRows, numCols, defaultValue, expectedValuesHeuristic(numRows, numCols)); + } + public CsrMatrix(int numRows, int numCols, double defaultValue, int expectedValues) { + super(numRows, numCols, defaultValue); + this.v = new double[expectedValues]; + this.ci = new int[expectedValues]; + this.ri = new int[numRows + 1]; + } + + /** + * Computes an initial value for the number of expected values + * @param numRows the number of rows + * @param numCols the number of columns + * @return the expected number of values in the sparse matrix + */ + private static int expectedValuesHeuristic(int numRows, int numCols) { + int max = Math.max(numRows, numCols); + return max * max / 10; + } + + private int indexOf(int i, int j) { + int cLow = this.ri[i]; + int cHigh = this.ri[i+1]; + if (cHigh <= cLow) return ~cLow; + + return Arrays.binarySearch(this.ci, cLow, cHigh, j); + } + + @Override + public double get(int i, int j) { + + // get the index in the vector + int vi = indexOf(i, j); + + // if the vector index is negative, return default value + if (vi < 0) + return defaultValue; + + return this.v[vi]; + } + + @Override + public void set(int i, int j, double value) { + + // get the index in the vector + int vi = indexOf(i, j); + + // do we already have a value? + if (vi < 0) + { + // no, we don't, we need to ensure space! + ensureCapacity(this.ri[this.numRows] + 1); + + // update row indices + for (int ii = i + 1; ii <= this.numRows; ii++) + ri[ii] += 1; + + // move and update column indices, move values + vi = ~vi; + for (int ii = this.ri[this.numRows]; ii > vi; ii--) + { + this.ci[ii] = this.ci[ii - 1]; + this.v[ii] = this.v[ii - 1]; + } + + // insert column index + ci[vi] = j; + } + + // set the new value + v[vi] = value; + } + + @Override + public boolean isValueSet(int i, int j) { + return indexOf(i, j) >= 0; + } + + + /** + * Ensures that the column index vector (ci) and value vector (v) are sufficiently large. + * @param required the number of items to store in the matrix + */ + private void ensureCapacity(int required) { + if (required < this.v.length) + return; + + int increment = Math.max(this.numRows, this.numCols); + this.v = Arrays.copyOf(this.v, this.v.length + increment); + this.ci = Arrays.copyOf(this.ci, this.v.length + increment); + } + } + + /** + * A sparse matrix based on java's {@link HashMap}. + */ + final static class HashMapMatrix extends MatrixStorage { + + private final HashMap matrix; + + /** + * Creates an instance of this class + * @param numRows the number of rows + * @param numCols the number of columns + * @param defaultValue a default value + */ + public HashMapMatrix(int numRows, int numCols, double defaultValue) { + super(numRows, numCols, defaultValue); + this.matrix = new HashMap<>(); + } + + public double get(int i, int j) { + long key = (long)i << 32 | j; + return matrix.getOrDefault(key, this.defaultValue); + } + + public void set(int i, int j, double value) { + long key = (long)i << 32 | j; + matrix.put(key, value); + } + + public boolean isValueSet(int i, int j) { + long key = (long)i << 32 | j; + return matrix.containsKey(key); + } + } +} diff --git a/modules/core/src/main/java/org/locationtech/jts/algorithm/distance/PointPairDistance.java b/modules/core/src/main/java/org/locationtech/jts/algorithm/distance/PointPairDistance.java index d3adef89fe..3f01fb81c5 100644 --- a/modules/core/src/main/java/org/locationtech/jts/algorithm/distance/PointPairDistance.java +++ b/modules/core/src/main/java/org/locationtech/jts/algorithm/distance/PointPairDistance.java @@ -22,31 +22,38 @@ */ public class PointPairDistance { - private Coordinate[] pt = { new Coordinate(), new Coordinate() }; + private final Coordinate[] pt = { new Coordinate(), new Coordinate() }; private double distance = Double.NaN; private boolean isNull = true; + /** + * Creates an instance of this class + */ public PointPairDistance() { } + /** + * Initializes this instance. + */ public void initialize() { isNull = true; } - public void initialize(Coordinate p0, Coordinate p1) - { - pt[0].setCoordinate(p0); - pt[1].setCoordinate(p1); - distance = p0.distance(p1); - isNull = false; + /** + * Initializes the points, computing the distance between them. + * @param p0 the 1st point + * @param p1 the 2nd point + */ + public void initialize(Coordinate p0, Coordinate p1) { + initialize(p0, p1, p0.distance(p1)); } /** * Initializes the points, avoiding recomputing the distance. - * @param p0 - * @param p1 + * @param p0 the 1st point + * @param p1 the 2nd point * @param distance the distance between p0 and p1 */ - private void initialize(Coordinate p0, Coordinate p1, double distance) + void initialize(Coordinate p0, Coordinate p1, double distance) { pt[0].setCoordinate(p0); pt[1].setCoordinate(p1); @@ -54,10 +61,23 @@ private void initialize(Coordinate p0, Coordinate p1, double distance) isNull = false; } + /** + * Gets the distance between the paired points + * @return the distance between the paired points + */ public double getDistance() { return distance; } + /** + * Gets the paired points + * @return the paired points + */ public Coordinate[] getCoordinates() { return pt; } + /** + * Gets one of the paired points + * @param i the index of the paired point (0 or 1) + * @return A point + */ public Coordinate getCoordinate(int i) { return pt[i]; } public void setMaximum(PointPairDistance ptDist) @@ -91,7 +111,7 @@ public void setMinimum(Coordinate p0, Coordinate p1) if (dist < distance) initialize(p0, p1, dist); } - + public String toString() { return WKTWriter.toLineString(pt[0], pt[1]); diff --git a/modules/core/src/main/java/org/locationtech/jts/algorithm/match/FrechetSimilarityMeasure.java b/modules/core/src/main/java/org/locationtech/jts/algorithm/match/FrechetSimilarityMeasure.java new file mode 100644 index 0000000000..35236e0ea7 --- /dev/null +++ b/modules/core/src/main/java/org/locationtech/jts/algorithm/match/FrechetSimilarityMeasure.java @@ -0,0 +1,66 @@ +/* + * Copyright (c) 2021 Felix Obermaier. + * + * All rights reserved. This program and the accompanying materials + * are made available under the terms of the Eclipse Public License 2.0 + * and Eclipse Distribution License v. 1.0 which accompanies this distribution. + * The Eclipse Public License is available at http://www.eclipse.org/legal/epl-v20.html + * and the Eclipse Distribution License is available at + * + * http://www.eclipse.org/org/documents/edl-v10.php. + */ +package org.locationtech.jts.algorithm.match; + +import org.locationtech.jts.algorithm.distance.DiscreteFrechetDistance; +import org.locationtech.jts.geom.Coordinate; +import org.locationtech.jts.geom.Envelope; +import org.locationtech.jts.geom.Geometry; +import org.locationtech.jts.geom.MultiPoint; + +/** + * Measures the degree of similarity between two + * {@link Geometry}s using the Fréchet distance metric. + * The measure is normalized to lie in the range [0, 1]. + * Higher measures indicate a great degree of similarity. + *

+ * The measure is computed by computing the Fréchet distance + * between the input geometries, and then normalizing + * this by dividing it by the diagonal distance across + * the envelope of the combined geometries. + *

+ * Note: the input should be normalized, especially when + * measuring {@link MultiPoint} geometries because for the + * Fréchet distance the order of {@link Coordinate}s is + * important. + * + * @author Felix Obermaier + * + */ +public class FrechetSimilarityMeasure implements SimilarityMeasure { + + /** + * Creates an instance of this class. + */ + public FrechetSimilarityMeasure() + { } + + @Override + public double measure(Geometry g1, Geometry g2) { + + // Check if input is of same type + if (!g1.getGeometryType().equals(g2.getGeometryType())) + throw new IllegalArgumentException("g1 and g2 are of different type"); + + // Compute the distance + double frechetDistance = DiscreteFrechetDistance.distance(g1, g2); + if (frechetDistance == 0d) return 1; + + // Compute envelope diagonal size + Envelope env = new Envelope(g1.getEnvelopeInternal()); + env.expandToInclude(g2.getEnvelopeInternal()); + double envDiagSize = HausdorffSimilarityMeasure.diagonalSize(env); + + // normalize so that more similarity produces a measure closer to 1 + return 1 - frechetDistance / envDiagSize; + } +} diff --git a/modules/core/src/main/java/org/locationtech/jts/algorithm/match/HausdorffSimilarityMeasure.java b/modules/core/src/main/java/org/locationtech/jts/algorithm/match/HausdorffSimilarityMeasure.java index 74ecedc905..c841fc7389 100644 --- a/modules/core/src/main/java/org/locationtech/jts/algorithm/match/HausdorffSimilarityMeasure.java +++ b/modules/core/src/main/java/org/locationtech/jts/algorithm/match/HausdorffSimilarityMeasure.java @@ -24,13 +24,13 @@ *

* The measure is computed by computing the Hausdorff distance * between the input geometries, and then normalizing - * this by dividing it by the diagonal distance across + * this by dividing it by the diagonal distance across * the envelope of the combined geometries. - * + * * @author mbdavis * */ -public class HausdorffSimilarityMeasure +public class HausdorffSimilarityMeasure implements SimilarityMeasure { /* @@ -40,36 +40,39 @@ public static double measure(Geometry a, Geometry b) return gv.measure(); } */ - + public HausdorffSimilarityMeasure() { } - + /* * Densify a small amount to increase accuracy of Hausdorff distance */ private static final double DENSIFY_FRACTION = 0.25; - + public double measure(Geometry g1, Geometry g2) - { + { double distance = DiscreteHausdorffDistance.distance(g1, g2, DENSIFY_FRACTION); - + if (distance == 0d) return 1d; + Envelope env = new Envelope(g1.getEnvelopeInternal()); env.expandToInclude(g2.getEnvelopeInternal()); double envSize = diagonalSize(env); - // normalize so that more similarity produces a measure closer to 1 + + // normalize so that more similarity produces a measure closer to 1 double measure = 1 - distance / envSize; - + //System.out.println("Hausdorff distance = " + distance + ", measure = " + measure); return measure; } - + public static double diagonalSize(Envelope env) { if (env.isNull()) return 0.0; - - double width = env.getWidth(); + + double width = env.getWidth(); double hgt = env.getHeight(); + return Math.sqrt(width * width + hgt * hgt); } } diff --git a/modules/core/src/test/java/org/locationtech/jts/algorithm/distance/DiscreteFrechetDistanceLinear.java b/modules/core/src/test/java/org/locationtech/jts/algorithm/distance/DiscreteFrechetDistanceLinear.java new file mode 100644 index 0000000000..8d6ebb5fc4 --- /dev/null +++ b/modules/core/src/test/java/org/locationtech/jts/algorithm/distance/DiscreteFrechetDistanceLinear.java @@ -0,0 +1,105 @@ +package org.locationtech.jts.algorithm.distance; + +import org.locationtech.jts.geom.Coordinate; +import org.locationtech.jts.geom.Geometry; + +/** + * Linear Discrete Fréchet Distance computation + */ +public class DiscreteFrechetDistanceLinear { + + /** + * Computes the Discrete Fréchet Distance between two {@link Geometry}s + * using a {@code cartesian} distance computation function. + * + * @param g0 the 1st geometry + * @param g1 the 2nd geometry + * @return the cartesian distance between {#g0} and {#g1} + */ + public static double distance(Geometry g0, Geometry g1) { + DiscreteFrechetDistanceLinear dist = new DiscreteFrechetDistanceLinear(g0, g1, false); + return dist.distance(); + } + + /** + * Computes the Discrete Fréchet Distance between two {@link Geometry}s + * using a {@code cartesian} distance computation function. + * + * @param g0 the 1st geometry + * @param g1 the 2nd geometry + * @return the cartesian distance between {#g0} and {#g1} + */ + public static double distance(Geometry g0, Geometry g1, boolean getCoordinates) { + DiscreteFrechetDistanceLinear dist = new DiscreteFrechetDistanceLinear(g0, g1, getCoordinates); + return dist.distance(); + } + private final Geometry g0; + private final Geometry g1; + private final boolean getCoordinates; + + private DiscreteFrechetDistanceLinear(Geometry g0, Geometry g1, boolean getCoordinates) { + this.g0 = g0; + this.g1 = g1; + this.getCoordinates = getCoordinates; + } + + public double distance() { + + Coordinate[] coords0 = this.g0.getCoordinates(); + Coordinate[] coords1 = this.g1.getCoordinates(); + double[][] distances = new double[coords0.length][]; + for (int i = 0; i < coords0.length; i++) + distances[i] = new double[coords1.length]; + + for (int i = 0; i < coords0.length; i++) { + for (int j = 0; j < coords1.length; j++) + { + double distance = coords0[i].distance(coords1[j]); + if (i > 0 && j > 0) + { + distances[i][j] = Math.max(Math.min(Math.min(distances[i-1][j], distances[i-1][j-1]), distances[i][j-1]), distance); + } + else if (i > 0) + { + distances[i][j] = Math.max(distances[i-1][0], distance); + } + else if (j > 0) + { + distances[i][j] = Math.max(distances[0][j-1], distance); + } + else + { + distances[i][j] = distance; + } + } + } + + //System.out.println(toString(coords0.length, coords1.length, distances)); + //System.out.println(); + return distances[coords0.length-1][coords1.length-1]; + } + + /* + // For debugging purposes only + private static String toString(int numRows, int numCols, + double[][] sparse) { + + StringBuilder sb = new StringBuilder("["); + for (int i = 0; i < numRows; i++) + { + sb.append('['); + for(int j = 0; j < numCols; j++) + { + if (j > 0) + sb.append(", "); + sb.append(String.format("%8.4f", sparse[i][j])); + } + sb.append(']'); + if (i < numRows - 1) sb.append(",\n"); + } + sb.append(']'); + return sb.toString(); + } + */ + +} diff --git a/modules/core/src/test/java/org/locationtech/jts/algorithm/distance/DiscreteFrechetDistanceTest.java b/modules/core/src/test/java/org/locationtech/jts/algorithm/distance/DiscreteFrechetDistanceTest.java new file mode 100644 index 0000000000..e196a2c7d4 --- /dev/null +++ b/modules/core/src/test/java/org/locationtech/jts/algorithm/distance/DiscreteFrechetDistanceTest.java @@ -0,0 +1,87 @@ +/* + * Copyright (c) 2021 Felix Obermaier. + * + * All rights reserved. This program and the accompanying materials + * are made available under the terms of the Eclipse Public License 2.0 + * and Eclipse Distribution License v. 1.0 which accompanies this distribution. + * The Eclipse Public License is available at http://www.eclipse.org/legal/epl-v20.html + * and the Eclipse Distribution License is available at + * + * http://www.eclipse.org/org/documents/edl-v10.php. + */ + +package org.locationtech.jts.algorithm.distance; + +import org.junit.Test; +import org.locationtech.jts.geom.Geometry; +import org.locationtech.jts.util.Stopwatch; +import test.jts.GeometryTestCase; + +public class DiscreteFrechetDistanceTest extends GeometryTestCase { + + public DiscreteFrechetDistanceTest(String name) { + super(name); + } + + @Test + public void testLineSegments() + { + runTest( + "LINESTRING(0 0, 1 0.0, 2 0.0, 3 0.0, 4 0)", + "LINESTRING(0 1, 1 1.1, 2 1.2, 3 1.1, 4 1)", 1.2); + } + + @Test + public void testOrientation() + { + runTest( + "LINESTRING(0 0, 10 10, 20 15)", + "LINESTRING(0 1, 8 9, 12 11, 21 15)",2.23606797749979); + } + @Test + public void testFromDHD() { + runTest( + "LINESTRING (130 0, 0 0, 0 150)", + "LINESTRING (10 10, 10 150, 130 10)", 191.049731745428); + } + + public void testDevogeleEtAlPaper() { + runTest("LINESTRING(0.2 2.0, 1.5 2.8, 2.3 1.6, 2.9 1.8, 4.1 3.1, 5.6 2.9, 7.2 1.3, 8.2 1.1)", + "LINESTRING(0.3 1.6, 3.2 3.0, 3.8 1.8, 5.2 3.1, 6.5 2.8, 7.0 0.8, 8.9 0.6)", 1.697056); + } + + public void testLongEifelWalk() { + runTest( + "MultiLineStringZ ((3334206.2900000000372529 5575410.37999999988824129 442.10000000000002274, 3334209.33999999985098839 5575407.62000000011175871 442.80000000000001137, 3334210.75 5575409.12999999988824129 442.69999999999998863, 3334190.06000000005587935 5575386.17999999970197678 443.60000000000002274, 3334184.52000000001862645 5575375.44000000040978193 444.69999999999998863, 3334176.30000000027939677 5575352.2099999999627471 447, 3334149.60999999986961484 5575360.71999999973922968 446.90000000000003411, 3334137.68000000016763806 5575366.88999999966472387 446.5, 3334125.9599999999627471 5575379.83000000007450581 445.30000000000001137, 3334115.97000000020489097 5575386.7099999999627471 444.80000000000001137, 3334106.01000000024214387 5575391.91999999992549419 444.40000000000003411, 3334096.97000000020489097 5575394.66000000014901161 444.30000000000001137, 3334087.49000000022351742 5575394.83999999985098839 444.40000000000003411, 3334078.58999999985098839 5575393 444.69999999999998863, 3334071.85999999986961484 5575390.10000000055879354 444.80000000000001137, 3334059.89999999990686774 5575404.5 442.13999999999998636, 3334046.47999999998137355 5575415.37999999988824129 438.81000000000000227, 3334129.45000000018626451 5575530.35000000055879354 437.62000000000000455, 3334179.47999999998137355 5575497.06000000052154064 439.01999999999998181, 3334196.87000000011175871 5575537.81000000052154064 440.03000000000002956, 3334229.08000000007450581 5575541.70000000018626451 441.62999999999999545, 3334209 5575622.25999999977648258 442.37999999999999545, 3334134.66000000014901161 5575601.10000000055879354 438.60000000000002274, 3334134.07000000029802322 5575602.57000000029802322 438.60000000000002274, 3334131.07000000029802322 5575609.45000000018626451 438.69999999999998863, 3334118.20000000018626451 5575638.02000000048428774 438.90000000000003411, 3334114.66999999992549419 5575645.81000000052154064 438.90000000000003411, 3334102.81000000005587935 5575667.88999999966472387 439.40000000000003411, 3334100.2900000000372529 5575676.42999999970197678 439.69999999999998863, 3334098.2900000000372529 5575683.16999999992549419 440, 3334095.64999999990686774 5575696.71999999973922968 440.69999999999998863, 3334095.16999999992549419 5575710.99000000022351742 441.40000000000003411, 3334095.97999999998137355 5575727.77000000048428774 442.10000000000002274, 3334098.89000000013038516 5575747.71999999973922968 442.90000000000003411, 3334099.78000000026077032 5575751.37000000011175871 443.10000000000002274, 3334101.35000000009313226 5575758 443.30000000000001137, 3334097.9599999999627471 5575759.21999999973922968 443.5, 3334093.58999999985098839 5575760.91000000014901161 443.69999999999998863, 3334081.22999999998137355 5575773.66000000014901161 445.30000000000001137, 3334081.82000000029802322 5575776.53000000026077032 445.40000000000003411, 3334081.87999999988824129 5575783.2099999999627471 445.69999999999998863, 3334072.4599999999627471 5575817.00999999977648258 447.60000000000002274, 3334070.62000000011175871 5575831.32000000029802322 447.90000000000003411, 3334074.35000000009313226 5575863.92999999970197678 447.60000000000002274, 3334078.08000000007450581 5575896.54999999981373549 447.10000000000002274, 3334076.18999999994412065 5575897.61000000033527613 447.19999999999998863, 3334070.14999999990686774 5575905.03000000026077032 447.40000000000003411, 3334062.60999999986961484 5575953.58999999985098839 446.5, 3334055.07000000029802322 5576002.03000000026077032 447.90000000000003411, 3334047.60000000009313226 5576050.4599999999627471 450, 3334039.10000000009313226 5576059.08000000007450581 449.90000000000003411, 3334003.41000000014901161 5576080.90000000037252903 450.19999999999998863, 3333973.05000000027939677 5576099.44000000040978193 453.10000000000002274, 3333967.72999999998137355 5576102.73000000044703484 453.60000000000002274, 3334005.68999999994412065 5576130.92999999970197678 453.5, 3334024.99000000022351742 5576141.4599999999627471 453.30000000000001137, 3334015.52000000001862645 5576159.90000000037252903 455.30000000000001137, 3334010.81000000005587935 5576166.83999999985098839 455.5, 3333996.70000000018626451 5576178.52000000048428774 455.69999999999998863, 3333994.28000000026077032 5576183.16000000014901161 455.80000000000001137, 3333992.4599999999627471 5576186.56000000052154064 456, 3333982.58000000007450581 5576198.88999999966472387 457.10000000000002274, 3333964.35999999986961484 5576218.38999999966472387 460.5, 3333933.55000000027939677 5576245.41000000014901161 466.69999999999998863, 3333902.72999999998137355 5576272.41999999992549419 470.69999999999998863, 3333876.7900000000372529 5576293.27000000048428774 472.19999999999998863, 3333850.85000000009313226 5576314.24000000022351742 474.10000000000002274, 3333845.35000000009313226 5576318.63999999966472387 474.69999999999998863, 3333819.91999999992549419 5576337.69000000040978193 476.30000000000001137, 3333844.28000000026077032 5576355.08000000007450581 477.30000000000001137, 3333868.64999999990686774 5576372.57000000029802322 477.80000000000001137, 3333897.91000000014901161 5576391.46999999973922968 478.60000000000002274, 3333927.08999999985098839 5576410.37000000011175871 479, 3333933.47999999998137355 5576416.17999999970197678 479.10000000000002274, 3333946.58999999985098839 5576438.48000000044703484 479.5, 3333961.68000000016763806 5576472.07000000029802322 479.60000000000002274, 3333976.85999999986961484 5576505.66999999992549419 478.40000000000003411, 3333977.74000000022351742 5576506.53000000026077032 478.30000000000001137, 3333982.37000000011175871 5576510.83999999985098839 478, 3333937.39000000013038516 5576531.83999999985098839 479.80000000000001137, 3333892.47999999998137355 5576552.73000000044703484 481.80000000000001137, 3333853.27000000001862645 5576571.10000000055879354 483.80000000000001137, 3333847.57000000029802322 5576573.73000000044703484 484.10000000000002274, 3333877.45000000018626451 5576603.17999999970197678 482.5, 3333907.32000000029802322 5576632.75 481.10000000000002274, 3333937.18999999994412065 5576662.2099999999627471 480.19999999999998863, 3333967.07000000029802322 5576691.78000000026077032 479.30000000000001137, 3333996.93999999994412065 5576721.23000000044703484 478.69999999999998863, 3334017.08999999985098839 5576736.07000000029802322 478.40000000000003411, 3334053.24000000022351742 5576759.10000000055879354 477, 3334089.33000000007450581 5576782.02000000048428774 473.90000000000003411, 3334133.33999999985098839 5576805.58000000007450581 471, 3334161.47000000020489097 5576824.74000000022351742 469.30000000000001137, 3334189.66000000014901161 5576843.88999999966472387 467.5, 3334196.74000000022351742 5576849.12999999988824129 467.5, 3334191.56000000005587935 5576854.52000000048428774 467.5, 3334200.33000000007450581 5576856.69000000040978193 467.5, 3334224.60999999986961484 5576862.73000000044703484 467.30000000000001137, 3334257.60000000009313226 5576870.92999999970197678 466, 3334286.28000000026077032 5576876.04999999981373549 464.69999999999998863, 3334315.03000000026077032 5576881.16000000014901161 464.80000000000001137, 3334321.03000000026077032 5576881.53000000026077032 464.90000000000003411, 3334328.2099999999627471 5576880.86000000033527613 464.80000000000001137, 3334366.72999999998137355 5576867.62999999988824129 464.19999999999998863, 3334405.85000000009313226 5576855.71999999973922968 463.10000000000002274, 3334445.05000000027939677 5576843.81000000052154064 461.69999999999998863, 3334450.10999999986961484 5576841.42999999970197678 461.60000000000002274, 3334488.43999999994412065 5576863.27000000048428774 462, 3334526.70000000018626451 5576885.12000000011175871 462.69999999999998863, 3334528.83999999985098839 5576887.40000000037252903 462.69999999999998863, 3334530.37999999988824129 5576888.67999999970197678 462.80000000000001137, 3334558.78000000026077032 5576912.2900000000372529 463.40000000000003411, 3334588.7099999999627471 5576937.17999999970197678 464.90000000000003411, 3334618.64999999990686774 5576962.07000000029802322 465.5, 3334648.66000000014901161 5576986.96999999973922968 466.60000000000002274, 3334654.95000000018626451 5576989.78000000026077032 466.80000000000001137, 3334679.01000000024214387 5577002.27000000048428774 466.90000000000003411, 3334703.07000000029802322 5577014.77000000048428774 467.30000000000001137, 3334745.20000000018626451 5577037.38999999966472387 467.5, 3334784.43999999994412065 5577058.87999999988824129 468.80000000000001137, 3334823.60999999986961484 5577080.37000000011175871 469.90000000000003411, 3334862.85000000009313226 5577101.74000000022351742 471.30000000000001137, 3334900.35000000009313226 5577122.28000000026077032 472, 3334902.08999999985098839 5577123.23000000044703484 472.10000000000002274, 3334877.7900000000372529 5577153.27000000048428774 472.30000000000001137, 3334853.47999999998137355 5577183.19000000040978193 471, 3334835.93000000016763806 5577205.56000000052154064 471.69999999999998863, 3334796.37000000011175871 5577235.50999999977648258 472.30000000000001137, 3334756.72999999998137355 5577265.36000000033527613 472.30000000000001137, 3334718.41000000014901161 5577293.83000000007450581 473.10000000000002274, 3334680.08000000007450581 5577322.29999999981373549 473.60000000000002274, 3334665.62999999988824129 5577334.44000000040978193 474, 3334660.56000000005587935 5577338.71999999973922968 474.10000000000002274, 3334688.05000000027939677 5577360.4599999999627471 474.69999999999998863, 3334715.60000000009313226 5577382.20000000018626451 476.19999999999998863, 3334743.16000000014901161 5577403.94000000040978193 478.40000000000003411, 3334776.10999999986961484 5577427.2900000000372529 480.69999999999998863, 3334789.16999999992549419 5577441.36000000033527613 481.10000000000002274, 3334798.64000000013038516 5577454.87000000011175871 481.69999999999998863, 3334823.64000000013038516 5577490.60000000055879354 482.5, 3334850.62999999988824129 5577530.95000000018626451 483.90000000000003411, 3334863.64000000013038516 5577550.36000000033527613 483.90000000000003411, 3334879.57000000029802322 5577574.02000000048428774 482.90000000000003411, 3334895.49000000022351742 5577597.67999999970197678 482, 3334915.58000000007450581 5577627.23000000044703484 481.19999999999998863, 3334932.68999999994412065 5577652.41000000014901161 481.69999999999998863, 3334739.87000000011175871 5577803.70000000018626451 472.40000000000003411, 3334741.5400000000372529 5577811.54999999981373549 472.40000000000003411, 3334745.35000000009313226 5577817.11000000033527613 472.60000000000002274, 3334751.37000000011175871 5577822.7099999999627471 472.90000000000003411, 3334764.9599999999627471 5577833.20000000018626451 473.60000000000002274, 3334775.78000000026077032 5577841.87999999988824129 474.30000000000001137, 3334802.14999999990686774 5577866.77000000048428774 476.10000000000002274, 3334824.31000000005587935 5577884.78000000026077032 477.5, 3334846.39999999990686774 5577902.79999999981373549 478.69999999999998863, 3334858 5577913.7900000000372529 479.30000000000001137, 3334866.75 5577922.08999999985098839 479.69999999999998863, 3334886.20000000018626451 5577935.62000000011175871 480.60000000000002274, 3334917.02000000001862645 5577963.94000000040978193 481.60000000000002274, 3334947.83999999985098839 5577992.25999999977648258 482.69999999999998863, 3334980.27000000001862645 5578019.29999999981373549 483.90000000000003411, 3334997.02000000001862645 5578035.48000000044703484 484.5, 3335011.66000000014901161 5578050.04999999981373549 485.10000000000002274, 3335018.89999999990686774 5578055.83999999985098839 485.5, 3335026.52000000001862645 5578060.28000000026077032 485.80000000000001137, 3335034.10000000009313226 5578063.37999999988824129 486.19999999999998863, 3335042.83000000007450581 5578066.56000000052154064 486.69999999999998863, 3335051.32000000029802322 5578069.29999999981373549 487.19999999999998863, 3335062.22000000020489097 5578071.29999999981373549 487.69999999999998863, 3335071.83000000007450581 5578071 488.30000000000001137, 3335072.49000000022351742 5578075.87999999988824129 488.30000000000001137, 3335069.37000000011175871 5578081.10000000055879354 488, 3335068.56000000005587935 5578082.4599999999627471 488, 3335061.85000000009313226 5578089.12000000011175871 487.5, 3335057.62999999988824129 5578095.49000000022351742 487.19999999999998863, 3335052.24000000022351742 5578105.67999999970197678 486.80000000000001137, 3335049.64000000013038516 5578118.11000000033527613 486.60000000000002274, 3335050.78000000026077032 5578125.20000000018626451 486.60000000000002274, 3335067.66000000014901161 5578145.27000000048428774 487.40000000000003411, 3335069.05000000027939677 5578146.33999999985098839 487.40000000000003411, 3335070.51000000024214387 5578147.52000000048428774 487.5, 3335071.70000000018626451 5578155.83999999985098839 487.5, 3335070.89999999990686774 5578162.2099999999627471 487.40000000000003411, 3335058.05000000027939677 5578200.67999999970197678 486.19999999999998863, 3335055.60999999986961484 5578213.78000000026077032 485.90000000000003411, 3335055.58000000007450581 5578231.25999999977648258 485.5, 3335060.80000000027939677 5578250.02000000048428774 485.19999999999998863, 3335070.4599999999627471 5578262.52000000048428774 485.30000000000001137, 3335088.83000000007450581 5578273.53000000026077032 485.80000000000001137, 3335122.58000000007450581 5578283.83000000007450581 487.19999999999998863, 3335129.10999999986961484 5578287.53000000026077032 487.40000000000003411, 3335135.32000000029802322 5578292.33999999985098839 487.60000000000002274, 3335142.18000000016763806 5578304.37999999988824129 487.60000000000002274, 3335153.49000000022351742 5578328.74000000022351742 487.5, 3335157.57000000029802322 5578333.73000000044703484 487.60000000000002274, 3335166.31000000005587935 5578339.81000000052154064 487.90000000000003411, 3335176.18999999994412065 5578343.62000000011175871 488.40000000000003411, 3335188.18000000016763806 5578348.58999999985098839 489, 3335198.06000000005587935 5578352.17999999970197678 489.5, 3335212.2900000000372529 5578356.19000000040978193 490.30000000000001137, 3335232.75 5578358.56000000052154064 491.60000000000002274, 3335246.12999999988824129 5578360.03000000026077032 492.40000000000003411, 3335261.60000000009313226 5578364.78000000026077032 493.40000000000003411, 3335269.58000000007450581 5578369.2099999999627471 493.80000000000001137, 3335272.35999999986961484 5578373.91000000014901161 493.90000000000003411, 3335273.53000000026077032 5578379.44000000040978193 493.90000000000003411, 3335268.93000000016763806 5578394.28000000026077032 493.30000000000001137, 3335258.22000000020489097 5578407.29999999981373549 492.30000000000001137, 3335250.87999999988824129 5578423.56000000052154064 491.60000000000002274, 3335247.0400000000372529 5578441.94000000040978193 491.19999999999998863, 3335244.08000000007450581 5578470.75 490.90000000000003411, 3335241.12999999988824129 5578499.57000000029802322 490.90000000000003411, 3335241.02000000001862645 5578528.07000000029802322 491.10000000000002274, 3335240.97999999998137355 5578556.4599999999627471 491.40000000000003411, 3335242.97999999998137355 5578568.20000000018626451 491.60000000000002274, 3335250.39999999990686774 5578588.90000000037252903 492.10000000000002274, 3335267.2900000000372529 5578623.44000000040978193 493, 3335282.62999999988824129 5578646.90000000037252903 493.5, 3335293.02000000001862645 5578660.15000000037252903 493.80000000000001137, 3335299.7099999999627471 5578671.19000000040978193 493.90000000000003411, 3335313.74000000022351742 5578689.23000000044703484 494, 3335332.68000000016763806 5578706.90000000037252903 494.30000000000001137, 3335351.55000000027939677 5578724.67999999970197678 494.40000000000003411, 3335359.97999999998137355 5578732.10000000055879354 494.60000000000002274, 3335371.70000000018626451 5578739.98000000044703484 494.80000000000001137, 3335382.33999999985098839 5578742.99000000022351742 495.19999999999998863, 3335393.41000000014901161 5578743.75999999977648258 495.80000000000001137, 3335401.12000000011175871 5578741.74000000022351742 496.19999999999998863, 3335425.22999999998137355 5578728.74000000022351742 497.60000000000002274, 3335444.9599999999627471 5578716.87999999988824129 498.80000000000001137, 3335448.28000000026077032 5578715.66999999992549419 499, 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480.40000000000003411, 3334665 5575225 479, 3334640 5575225 477.30000000000001137, 3334595 5575230 474.69999999999998863, 3334575 5575235 474, 3334555 5575245 473.60000000000002274, 3334535 5575250 472.69999999999998863, 3334520 5575260 471.5, 3334515 5575265 471, 3334500 5575275 470, 3334480 5575300 468.40000000000003411, 3334470 5575310 467.5, 3334465 5575315 467.10000000000002274, 3334455 5575320 466.69999999999998863, 3334445 5575305 466.60000000000002274, 3334440 5575300 466.30000000000001137, 3334435 5575295 465.90000000000003411, 3334425 5575280 465.60000000000002274, 3334410 5575245 466.19999999999998863, 3334380 5575265 464.19999999999998863, 3334350 5575285 460.5, 3334335 5575295 458.40000000000003411, 3334330 5575290 458.5, 3334315 5575290 458.30000000000001137, 3334290 5575285 457.80000000000001137, 3334265 5575275 450.90000000000003411, 3334260 5575305 449, 3334250 5575330 447.60000000000002274, 3334250 5575335 447, 3334245 5575340 446.60000000000002274, 3334240 5575355 445.69999999999998863, 3334230 5575385 444, 3334225 5575400 443.30000000000001137))", + 3.36203807 + ); + } + + public void testShort() { + runTest("LINESTRING (1 1, 2 2)", + "LINESTRING (1 4, 2 3)", 3d); + } + private static final double TOLERANCE = 0.00001; + + private void runTest(String wkt1, String wkt2, double expectedDistance) { + Geometry g1 = read(wkt1); + Geometry g2 = read(wkt2); + + DiscreteFrechetDistanceLinear.distance(g1, g2); + Stopwatch sw = new Stopwatch(); + sw.start(); + double distance0 = DiscreteFrechetDistanceLinear.distance(g1, g2); + sw.stop(); + //System.out.println(String.format("DiscreteFrechetDistanceLinear %dms.%n", sw.getTime())); + assertEquals(expectedDistance, distance0, TOLERANCE); + + DiscreteFrechetDistance.distance(g1, g2); + sw.reset(); + sw.start(); + double distance1 = DiscreteFrechetDistance.distance(g1, g2); + sw.stop(); + //System.out.println(String.format("DiscreteFrechetDistance %dms.%n", sw.getTime())); + assertEquals(expectedDistance, distance1, TOLERANCE); + } +} diff --git a/modules/core/src/test/java/org/locationtech/jts/algorithm/distance/MatrixStorageImplTests.java b/modules/core/src/test/java/org/locationtech/jts/algorithm/distance/MatrixStorageImplTests.java new file mode 100644 index 0000000000..3ae5b52b53 --- /dev/null +++ b/modules/core/src/test/java/org/locationtech/jts/algorithm/distance/MatrixStorageImplTests.java @@ -0,0 +1,92 @@ +/* + * Copyright (c) 2021 Felix Obermaier. + * + * All rights reserved. This program and the accompanying materials + * are made available under the terms of the Eclipse Public License 2.0 + * and Eclipse Distribution License v. 1.0 which accompanies this distribution. + * The Eclipse Public License is available at http://www.eclipse.org/legal/epl-v20.html + * and the Eclipse Distribution License is available at + * + * http://www.eclipse.org/org/documents/edl-v10.php. + */ + +package org.locationtech.jts.algorithm.distance; + +import junit.framework.TestCase; + +import org.locationtech.jts.algorithm.distance.DiscreteFrechetDistance.MatrixStorage; +import org.locationtech.jts.algorithm.distance.DiscreteFrechetDistance.HashMapMatrix; +import org.locationtech.jts.algorithm.distance.DiscreteFrechetDistance.CsrMatrix; +import org.locationtech.jts.algorithm.distance.DiscreteFrechetDistance.RectMatrix; + +import org.junit.Test; + +public class MatrixStorageImplTests extends TestCase { + + @Test + public void testCsrMatrix() + { + MatrixStorage mat = new CsrMatrix(4, 6, 0d, 8); + runOrderedTest(mat); + mat = new CsrMatrix(4, 6, 0d, 8); + runUnorderedTest(mat); + } + @Test + public void testHashMapMatrix() + { + MatrixStorage mat = new HashMapMatrix(4, 6, 0d); + runOrderedTest(mat); + mat = new HashMapMatrix(4, 6, 0d); + runUnorderedTest(mat); + } + @Test + public void testRectMatrix() + { + MatrixStorage mat = new RectMatrix(4, 6, 0d); + runOrderedTest(mat); + mat = new RectMatrix(4, 6, 0d); + runUnorderedTest(mat); + } + + private static void runOrderedTest(MatrixStorage mat) { + mat.set(0, 0, 10); + mat.set(0, 1, 20); + mat.set(1, 1, 30); + mat.set(1, 3, 40); + mat.set(2, 2, 50); + mat.set(2, 3, 60); + mat.set(2, 4, 70); + mat.set(3, 5, 80); + + assertEquals(String.format("%1$d -> %2$d = %4$f /= %3$f", 0, 0, 10d, mat.get(0, 0)), 10d, mat.get(0, 0)); + assertEquals(String.format("%1$d -> %2$d = %4$f /= %3$f", 0, 1, 20d, mat.get(0, 1)), 20d, mat.get(0, 1)); + assertEquals(String.format("%1$d -> %2$d = %4$f /= %3$f", 1, 1, 30d, mat.get(1, 1)), 30d, mat.get(1, 1)); + assertEquals(String.format("%1$d -> %2$d = %4$f /= %3$f", 1, 3, 40d, mat.get(1, 3)), 40d, mat.get(1, 3)); + assertEquals(String.format("%1$d -> %2$d = %4$f /= %3$f", 2, 2, 50d, mat.get(2, 2)), 50d, mat.get(2, 2)); + assertEquals(String.format("%1$d -> %2$d = %4$f /= %3$f", 2, 3, 60d, mat.get(2, 3)), 60d, mat.get(2, 3)); + assertEquals(String.format("%1$d -> %2$d = %4$f /= %3$f", 2, 4, 70d, mat.get(2, 4)), 70d, mat.get(2, 4)); + assertEquals(String.format("%1$d -> %2$d = %4$f /= %3$f", 3, 5, 80d, mat.get(3, 5)), 80d, mat.get(3, 5)); + + } + + private static void runUnorderedTest(MatrixStorage mat) { + mat.set(0, 0, 10); + mat.set(3, 5, 80); + mat.set(0, 1, 20); + mat.set(2, 4, 70); + mat.set(1, 1, 30); + mat.set(2, 3, 60); + mat.set(2, 2, 50); + mat.set(1, 3, 40); + + assertEquals(String.format("%1$d -> %2$d = %4$f /= %3$f", 0, 0, 10d, mat.get(0, 0)), 10d, mat.get(0, 0)); + assertEquals(String.format("%1$d -> %2$d = %4$f /= %3$f", 0, 1, 20d, mat.get(0, 1)), 20d, mat.get(0, 1)); + assertEquals(String.format("%1$d -> %2$d = %4$f /= %3$f", 1, 1, 30d, mat.get(1, 1)), 30d, mat.get(1, 1)); + assertEquals(String.format("%1$d -> %2$d = %4$f /= %3$f", 1, 3, 40d, mat.get(1, 3)), 40d, mat.get(1, 3)); + assertEquals(String.format("%1$d -> %2$d = %4$f /= %3$f", 2, 2, 50d, mat.get(2, 2)), 50d, mat.get(2, 2)); + assertEquals(String.format("%1$d -> %2$d = %4$f /= %3$f", 2, 3, 60d, mat.get(2, 3)), 60d, mat.get(2, 3)); + assertEquals(String.format("%1$d -> %2$d = %4$f /= %3$f", 2, 4, 70d, mat.get(2, 4)), 70d, mat.get(2, 4)); + assertEquals(String.format("%1$d -> %2$d = %4$f /= %3$f", 3, 5, 80d, mat.get(3, 5)), 80d, mat.get(3, 5)); + + } +} diff --git a/modules/core/src/test/java/org/locationtech/jts/algorithm/match/FrechetSimilarityMeasureTest.java b/modules/core/src/test/java/org/locationtech/jts/algorithm/match/FrechetSimilarityMeasureTest.java new file mode 100644 index 0000000000..42501f7467 --- /dev/null +++ b/modules/core/src/test/java/org/locationtech/jts/algorithm/match/FrechetSimilarityMeasureTest.java @@ -0,0 +1,63 @@ +/* + * Copyright (c) 2021 Felix Obermaier. + * + * All rights reserved. This program and the accompanying materials + * are made available under the terms of the Eclipse Public License 2.0 + * and Eclipse Distribution License v. 1.0 which accompanies this distribution. + * The Eclipse Public License is available at http://www.eclipse.org/legal/epl-v20.html + * and the Eclipse Distribution License is available at + * + * http://www.eclipse.org/org/documents/edl-v10.php. + */ +package org.locationtech.jts.algorithm.match; + +import org.locationtech.jts.geom.Geometry; +import test.jts.GeometryTestCase; + +public class FrechetSimilarityMeasureTest extends GeometryTestCase { + + public FrechetSimilarityMeasureTest(String name) { + super(name); + } + + public void testDifferentGeometryTypesThrowIAE() { + Geometry g1 = read("POINT(1 1)"); + Geometry g2 = read("LINESTRING(1 1, 2 1)"); + + try { + SimilarityMeasure sm = new FrechetSimilarityMeasure(); + sm.measure(g1, g2); + fail("Different geometry types should fail!"); + } + catch (Exception e) { + assertTrue(true); + } + } + + public void testEqualGeometriesReturn1() { + Geometry g1 = read("POINT(1 1)"); + Geometry g2 = read("POINT(1 1)"); + assertEquals("Point", 1d, new FrechetSimilarityMeasure().measure(g1, g2)); + + g1 = read("LINESTRING(1 1, 2 1)"); + g2 = read("LINESTRING(1 1, 2 1)"); + assertEquals("LineString", 1d, new FrechetSimilarityMeasure().measure(g1, g2)); + + g1 = read("POLYGON((0 0, 0 10, 10 0, 0 0), (1 1, 7.58 1, 1 7.58, 1 1))"); + g2 = read("POLYGON((0 0, 0 10, 10 0, 0 0), (1 1, 7.58 1, 1 7.58, 1 1))"); + assertEquals("POLYGON", 1d, new FrechetSimilarityMeasure().measure(g1, g2)); + } + + public void testGreaterFrechetDistanceReturnsPoorerSimilarity() + { + Geometry g1 = read("LINESTRING(1 1, 2 1.0, 3 1)"); + Geometry g2 = read("LINESTRING(1 1, 2 1.1, 3 1)"); + Geometry g3 = read("LINESTRING(1 1, 2 1.2, 3 1)"); + + SimilarityMeasure sm = new FrechetSimilarityMeasure(); + double m12 = sm.measure(g1, g2); + double m13 = sm.measure(g1, g3); + + assertTrue("Greater distance, poorer similarity", m13 < m12); + } +} diff --git a/modules/core/src/test/java/org/locationtech/jts/algorithm/match/HausdorffSimilarityMeasureTest.java b/modules/core/src/test/java/org/locationtech/jts/algorithm/match/HausdorffSimilarityMeasureTest.java new file mode 100644 index 0000000000..9c805fc266 --- /dev/null +++ b/modules/core/src/test/java/org/locationtech/jts/algorithm/match/HausdorffSimilarityMeasureTest.java @@ -0,0 +1,49 @@ +/* + * Copyright (c) 2021 Felix Obermaier. + * + * All rights reserved. This program and the accompanying materials + * are made available under the terms of the Eclipse Public License v2.0 + * and Eclipse Distribution License v. 1.0 which accompanies this distribution. + * The Eclipse Public License is available at http://www.eclipse.org/legal/epl-v20.html + * and the Eclipse Distribution License is available at + * + * http://www.eclipse.org/org/documents/edl-v10.php. + */ +package org.locationtech.jts.algorithm.match; + +import org.locationtech.jts.geom.Geometry; +import test.jts.GeometryTestCase; + +public class HausdorffSimilarityMeasureTest extends GeometryTestCase { + public HausdorffSimilarityMeasureTest(String name) { + super(name); + } + + public void testEqualGeometriesReturn1() { + Geometry g1 = read("POINT(1 1)"); + Geometry g2 = read("POINT(1 1)"); + assertEquals("Point", 1d, new HausdorffSimilarityMeasure().measure(g1, g2)); + + g1 = read("LINESTRING(1 1, 2 1)"); + g2 = read("LINESTRING(1 1, 2 1)"); + assertEquals("LineString", 1d, new HausdorffSimilarityMeasure().measure(g1, g2)); + + g1 = read("POLYGON((0 0, 0 10, 10 0, 0 0), (1 1, 7.58 1, 1 7.58, 1 1))"); + g2 = read("POLYGON((0 0, 0 10, 10 0, 0 0), (1 1, 7.58 1, 1 7.58, 1 1))"); + assertEquals("POLYGON", 1d, new HausdorffSimilarityMeasure().measure(g1, g2)); + } + + public void testGreaterHausdorffDistanceReturnsPoorerSimilarity() + { + Geometry g1 = read("LINESTRING(1 1, 2 1.0, 3 1)"); + Geometry g2 = read("LINESTRING(1 1, 2 1.1, 3 1)"); + Geometry g3 = read("LINESTRING(1 1, 2 1.2, 3 1)"); + + SimilarityMeasure sm = new HausdorffSimilarityMeasure(); + double m12 = sm.measure(g1, g2); + double m13 = sm.measure(g1, g3); + + assertTrue("Greater distance, poorer similarity", m13 < m12); + } + +}