This is an automated email from the ASF dual-hosted git repository. leirui pushed a commit to branch research/area-visualization in repository https://gitbox.apache.org/repos/asf/iotdb.git
commit cb9ca0b06f855fe056004f111bc578668e48841b Author: Lei Rui <[email protected]> AuthorDate: Wed Jan 22 15:14:17 2025 +0800 add --- .../java/org/apache/iotdb/db/query/eBUG/Test1.java | 80 ++++ .../db/query/eBUG/TimestampPriorityQueue.java | 121 ------ .../iotdb/db/query/eBUG/Visval_standard.java | 263 ------------- .../java/org/apache/iotdb/db/query/eBUG/eBUG.java | 24 +- .../eBUG/eBUG_sortedEliminatedDeprecated.java | 406 --------------------- .../eBUG/eBUG_sortedEliminatedDeprecated_tmp.java | 398 -------------------- .../org/apache/iotdb/db/query/eBUG/eBUG_tmp.java | 397 -------------------- 7 files changed, 92 insertions(+), 1597 deletions(-) diff --git a/server/src/main/java/org/apache/iotdb/db/query/eBUG/Test1.java b/server/src/main/java/org/apache/iotdb/db/query/eBUG/Test1.java new file mode 100644 index 00000000000..56e73cc17e0 --- /dev/null +++ b/server/src/main/java/org/apache/iotdb/db/query/eBUG/Test1.java @@ -0,0 +1,80 @@ +package org.apache.iotdb.db.query.eBUG; + +import java.io.FileWriter; +import java.io.IOException; +import java.util.ArrayList; +import java.util.List; +import java.util.Random; + +import static org.apache.iotdb.db.query.eBUG.eBUG.buildEffectiveArea; + +public class Test1 { + public static void main(String[] args) { + Polyline polyline = new Polyline(); + List<Polyline> polylineList = new ArrayList<>(); + Random rand = new Random(1); + int n = 10000; + + int p = 10; + for (int i = 0; i < n; i += p) { + Polyline polylineBatch = new Polyline(); + for (int j = i; j < Math.min(i + p, n); j++) { + double v = rand.nextInt(1000000); + + polyline.addVertex(new Point(j, v)); + + polylineBatch.addVertex(new Point(j, v)); + } + polylineList.add(polylineBatch); + } + + try (FileWriter writer = new FileWriter("raw.csv")) { + // 写入CSV头部 + writer.append("x,y,z\n"); + + // 写入每个点的数据 + for (int i = 0; i < polyline.size(); i++) { + Point point = polyline.get(i); + writer.append(point.x + "," + point.y + "," + point.z + "\n"); + } + System.out.println("Data has been written"); + } catch (IOException e) { + System.out.println("Error writing to CSV file: " + e.getMessage()); + } + + System.out.println("---------------------------------"); +// List<Point> results = new ArrayList<>(); + // 计算运行时间 +// int eParam = 10; +// for (int eParam = 0; eParam < 2 * n; eParam += 1000) { + int eParam = 2; + long startTime = System.currentTimeMillis(); + List<Point> results = buildEffectiveArea(polyline, eParam, false); + // 输出结果 + long endTime = System.currentTimeMillis(); + System.out.println("n=" + n + ", e=" + eParam + ", Time taken to reduce points: " + (endTime - startTime) + "ms"); + System.out.println(results.size()); + + if (results.size() <= 100) { + System.out.println("+++++++++++++++++++"); + for (int i = 0; i < results.size(); i++) { + Point point = results.get(i); + System.out.println("Point: (" + point.x + ", " + point.y + ", " + point.z + ")"); + } + } + + try (FileWriter writer = new FileWriter("fast.csv")) { + // 写入CSV头部 + writer.append("x,y,z\n"); + + // 写入每个点的数据 + for (int i = 0; i < results.size(); i++) { + Point point = results.get(i); + writer.append(point.x + "," + point.y + "," + point.z + "\n"); + } + System.out.println("Data has been written"); + } catch (IOException e) { + System.out.println("Error writing to CSV file: " + e.getMessage()); + } + } +} diff --git a/server/src/main/java/org/apache/iotdb/db/query/eBUG/TimestampPriorityQueue.java b/server/src/main/java/org/apache/iotdb/db/query/eBUG/TimestampPriorityQueue.java deleted file mode 100644 index 8e8fb18ebfa..00000000000 --- a/server/src/main/java/org/apache/iotdb/db/query/eBUG/TimestampPriorityQueue.java +++ /dev/null @@ -1,121 +0,0 @@ -package org.apache.iotdb.db.query.eBUG; - -import java.util.*; - -public class TimestampPriorityQueue { - private final int e; // 队列的最大大小 - private final LinkedList<Point> insertionOrder; // 保持插入顺序 - // public final PriorityQueue<Point> queue; // 按时间戳排序的优先队列 - private final List<Point> sortedList; // 维护排序后的列表 - - // 构造函数：初始化队列大小、插入顺序队列和优先队列 - public TimestampPriorityQueue(int e) { - this.e = e; - this.insertionOrder = new LinkedList<>(); -// this.queue = new PriorityQueue<>(Comparator.comparingDouble(p -> p.x)); - this.sortedList = new ArrayList<>(); - } - - public int size() { -// return queue.size(); - return sortedList.size(); - } - - // 插入新的元素 - public void insert(Point newPoint) { - // 如果队列已满，移除最早插入的点 - if (sortedList.size() == e) { - Point removedPoint = insertionOrder.removeFirst(); // 移除最早加入的点 复杂度1 -// queue.remove(removedPoint); // 从优先队列中移除该点 TODO 复杂度O(e)! - sortedList.remove(removedPoint); // 从排序后的列表中移除该点 复杂度O(e) - } - - // 将新点添加到插入顺序队列中 - insertionOrder.addLast(newPoint); // 复杂度1 - - // 插入到优先队列，保持时间戳顺序 -// queue.add(newPoint); // 复杂度log(e) - - // 插入到排序后的列表中，保持有序 - int insertIndex = Collections.binarySearch(sortedList, newPoint, Comparator.comparingDouble(p -> p.x)); // 复杂度log(e) - if (insertIndex < 0) { - insertIndex = -(insertIndex + 1); // 如果未找到，binarySearch返回插入点的负值 - } - sortedList.add(insertIndex, newPoint); // 复杂度O(e) - } - - // 获取队列中的所有元素（按时间戳排序） - public List<Point> getQueue() { -// return new ArrayList<>(queue); // 这个不是排序的！ - return sortedList; - } - - public String toString() { - StringBuffer stringBuffer = new StringBuffer(); - for (Point point : sortedList) { - stringBuffer.append(point.toString()); - stringBuffer.append(","); - } - return stringBuffer.toString(); - } - - public static void main(String[] args) { - TimestampPriorityQueue tq = new TimestampPriorityQueue(10); - - tq.insert(new Point(0, 1000)); - tq.insert(new Point(3, 2000)); - tq.insert(new Point(11, 1500)); - tq.insert(new Point(5, 500)); - - // 打印队列内容 - for (Point point : tq.getQueue()) { - System.out.println(point); - } - } -} - - -//public class TimestampPriorityQueue { // for managing the e most recently eliminated points, sorted by time in ascending order -// private final int e; -// public final PriorityQueue<Point> queue; -// -// // 构造函数：初始化优先队列的最大大小 -// public TimestampPriorityQueue(int e) { -// this.e = e; -// this.queue = new PriorityQueue<>(Comparator.comparingDouble(p -> p.x)); -// } -// -// // 插入新的元素 -// public void insert(Point newPoint) { -// // 如果队列已满，移除最小（最早）的元素 -// if (queue.size() == e) { -// queue.poll(); -// } -// -// // 插入元素，队列会根据时间戳自动排序 -// queue.offer(newPoint); -// } -// -// // 获取队列中的所有元素 -// public List<Point> getQueue() { -// return new ArrayList<>(queue); -// } -// -// public static void main(String[] args) { -// TimestampPriorityQueue tq = new TimestampPriorityQueue(3); -// -// tq.insert(new Point(10, 1000)); -// tq.insert(new Point(20, 2000)); -// tq.insert(new Point(15, 1500)); -// tq.insert(new Point(25, 2500)); -// -// // 打印队列内容 -// long tmp = 2000; -// for (Point point : tq.getQueue()) { -// point.x = tmp--; -// System.out.println("Value: " + point.x + ", Timestamp: " + point.y); -// } -// -// System.out.println(tq.queue.poll()); -// } -//} diff --git a/server/src/main/java/org/apache/iotdb/db/query/eBUG/Visval_standard.java b/server/src/main/java/org/apache/iotdb/db/query/eBUG/Visval_standard.java deleted file mode 100644 index a85332d3846..00000000000 --- a/server/src/main/java/org/apache/iotdb/db/query/eBUG/Visval_standard.java +++ /dev/null @@ -1,263 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one - * or more contributor license agreements. See the NOTICE file - * distributed with this work for additional information - * regarding copyright ownership. The ASF licenses this file - * to you under the Apache License, Version 2.0 (the - * "License"); you may not use this file except in compliance - * with the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, - * software distributed under the License is distributed on an - * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY - * KIND, either express or implied. See the License for the - * specific language governing permissions and limitations - * under the License. - */ - -package org.apache.iotdb.db.query.eBUG; - -import java.io.FileWriter; -import java.io.IOException; -import java.util.*; -import java.util.stream.Collectors; - -import static org.apache.iotdb.db.query.eBUG.Tool.triArea; - -public class Visval_standard { - - public static void buildEffectiveArea(Polyline lineToSimplify, List<Point> results) { - results.clear(); - results.addAll(lineToSimplify.getVertices()); // TODO debug - - int total = lineToSimplify.size(); - if (total < 3) { - return; // 不足 3 个点无法形成三角形 - } - - int nTriangles = total - 2; - Triangle[] triangles = new Triangle[nTriangles]; - - // 创建所有三角形并计算初始面积 - for (int i = 1; i < total - 1; i++) { - int index1 = i - 1, index2 = i, index3 = i + 1; - double area = triArea(lineToSimplify.get(index1), lineToSimplify.get(index2), lineToSimplify.get(index3)); - triangles[i - 1] = new Triangle(index1, index2, index3, area); - } - - // 设置三角形的前后关系 - for (int i = 0; i < nTriangles; i++) { // TODO 这个可以和上一个循环合并吗？？好像不可以 - triangles[i].prev = (i == 0 ? null : triangles[i - 1]); - triangles[i].next = (i == nTriangles - 1 ? null : triangles[i + 1]); - } - - // 使用优先队列构建 minHeap - PriorityQueue<Triangle> triangleHeap = new PriorityQueue<>(Comparator.comparingDouble(t -> t.area)); - Collections.addAll(triangleHeap, triangles); // complexity TODO - - double previousEA = -1; - while (!triangleHeap.isEmpty()) { - // 注意peek只需要直接访问该位置的元素，不涉及任何重排或堆化操作 - // 而poll是删除堆顶元素，需要重新堆化以维护堆的性质，复杂度是O(logk),k是当前堆的大小 - Triangle tri = triangleHeap.poll(); // O(logn) - - // 如果该三角形已经被删除，跳过. Avoid using heap.remove(x) as it is O(n) complexity - // 而且除了heap里，已经没有其他节点会和它关联了，所有的connections关系已经迁移到新的角色替代节点上 - if (tri.isDeleted) { - continue; - } - - // 更新当前点的重要性（z 轴存储effective area,这是一个单调增的指标） - if (tri.area > previousEA) { - previousEA = tri.area; - } - results.get(tri.indices[1]).z = previousEA; - // System.out.println(tri.indices[1] + "," + previousEA); - -// System.out.println(Arrays.toString(tri.indices) + "," + previousEA); - - // 更新相邻三角形 - if (tri.prev != null) { - // 标记为失效点，同时new一个新的对象接管它的一切数据和前后连接关系，然后更新前后连接关系、更新significance、加入heap使其排好序 - - // 1. 处理旧的tri.prev被标记删除的事情（角色替代） - // triangleHeap.remove(tri.prev); // Avoid using heap.remove(x) as it is O(n) complexity! - tri.prev.markDeleted(); // O(1) 这个点标记为废掉，前后关联都砍断，但是不remove因为那太耗时，只要heap poll到它就跳过就可以 - - Triangle newPre = new Triangle(tri.prev); // deep copy and inherit connection -// tri.prev = newPre; // replace TODO can omit - - // 2. 处理pi被淘汰引起tri.prev被更新的事情 - // 前一个三角形连到后一个三角形 - tri.prev.next = tri.next; // ATTENTION!!!: 这里的tri.next后面可能会因为处理旧的tri.next被标记删除的事情被换掉！到时候要重新赋值！ - tri.prev.indices[2] = tri.indices[2]; - tri.prev.area = triArea(lineToSimplify.get(tri.prev.indices[0]), lineToSimplify.get(tri.prev.indices[1]), lineToSimplify.get(tri.prev.indices[2])); - - // 重新加入堆 - // 在 Java 的 PriorityQueue 中，修改元素的属性不会自动更新堆的顺序 - // 所以必须通过add来显式重新插入修改后的元素 - triangleHeap.add(tri.prev); // O(logn) 注意加入的是一个新的对象isDeleted=false - } - - if (tri.next != null) { - // 标记为失效点，同时new一个新的对象接管它的一切数据和前后连接关系，然后更新前后连接关系、更新significance、加入heap使其排好序 - - // 1. 处理旧的tri.next被标记删除的事情（角色替代） - // triangleHeap.remove(tri.next); // Avoid using heap.remove(x) as it is O(n) complexity - tri.next.markDeleted(); // O(1) 这个点标记为废掉，前后关联都砍断，但是不remove因为那太耗时，只有poll到它就跳过就可以 - - Triangle newNext = new Triangle(tri.next); // deep copy and inherit connection -// tri.next = newNext; // replace TODO can omit - - if (tri.prev != null) { - tri.prev.next = tri.next; // ATTENTION!!!: 这里的tri.next已经被换掉！所以之前的要重新赋值！ - } - - // 2. 处理pi被淘汰引起tri.next被更新的事情 - tri.next.prev = tri.prev; // 注意此时tri.prev已经是替代后的节点，tri.next也是，从而被标记为废点的前后关联真正砍断 - tri.next.indices[0] = tri.indices[0]; - tri.next.area = triArea(lineToSimplify.get(tri.next.indices[0]), lineToSimplify.get(tri.next.indices[1]), lineToSimplify.get(tri.next.indices[2])); - - // 重新加入堆 - // 在 Java 的 PriorityQueue 中，修改元素的属性不会自动更新堆的顺序 - // 所以必须通过add 来显式重新插入修改后的元素 - triangleHeap.add(tri.next); // 注意加入的是一个新的对象isDeleted=false - } - } - } - - public static void main(String[] args) { - Polyline polyline = new Polyline(); - List<Polyline> polylineList = new ArrayList<>(); - Random rand = new Random(1); - int n = 10_0000; - - int p = 700; - for (int i = 0; i < n; i += p) { - Polyline polylineBatch = new Polyline(); - for (int j = i; j < Math.min(i + p, n); j++) { - double v = rand.nextInt(1000000); - - polyline.addVertex(new Point(j, v)); - - polylineBatch.addVertex(new Point(j, v)); - } - polylineList.add(polylineBatch); - } - - try (FileWriter writer = new FileWriter("raw.csv")) { - // 写入CSV头部 - writer.append("x,y,z\n"); - - // 写入每个点的数据 - for (int i = 0; i < polyline.size(); i++) { - Point point = polyline.get(i); - writer.append(point.x + "," + point.y + "," + point.z + "\n"); - } - System.out.println("Data has been written"); - } catch (IOException e) { - System.out.println("Error writing to CSV file: " + e.getMessage()); - } - - System.out.println("---------------------------------"); - List<Point> results = new ArrayList<>(); - // 计算运行时间 - long startTime = System.currentTimeMillis(); - buildEffectiveArea(polyline, results); - // 输出结果 - long endTime = System.currentTimeMillis(); - System.out.println("Time taken to reduce points: " + (endTime - startTime) + "ms"); - System.out.println(results.size()); - - if (results.size() <= 100) { - System.out.println("+++++++++++++++++++"); - for (int i = 0; i < results.size(); i++) { - Point point = results.get(i); - System.out.println("Point: (" + point.x + ", " + point.y + ", " + point.z + ")"); - } - } - - try (FileWriter writer = new FileWriter("fast.csv")) { - // 写入CSV头部 - writer.append("x,y,z\n"); - - // 写入每个点的数据 - for (int i = 0; i < results.size(); i++) { - Point point = results.get(i); - writer.append(point.x + "," + point.y + "," + point.z + "\n"); - } - System.out.println("Data has been written"); - } catch (IOException e) { - System.out.println("Error writing to CSV file: " + e.getMessage()); - } - - System.out.println("---------------------------------"); - List<List<Point>> resultsBatchList = new ArrayList<>(); - // 计算运行时间 - int cnt = 0; - startTime = System.currentTimeMillis(); - for (Polyline polylineBatch : polylineList) { - List<Point> resultsBatch = new ArrayList<>(); - buildEffectiveArea(polylineBatch, resultsBatch); - cnt += resultsBatch.size(); - resultsBatchList.add(resultsBatch); - } - // 输出结果 - endTime = System.currentTimeMillis(); - System.out.println("Time taken to reduce points: " + (endTime - startTime) + "ms"); - System.out.println(cnt); - - System.out.println("---------------------------------"); - // 使用 Stream API 合并所有列表 - List<Point> mergedList = - resultsBatchList.stream().flatMap(List::stream).collect(Collectors.toList()); - int sameCnt = 0; - for (int i = 0; i < mergedList.size(); i++) { - if (mergedList.get(i).z == results.get(i).z) { - sameCnt += 1; - } - } - System.out.println("sameCnt=" + sameCnt + ", percent=" + sameCnt * 1.0 / mergedList.size()); - - try (FileWriter writer = new FileWriter("batch.csv")) { - // 写入CSV头部 - writer.append("x,y,z\n"); - - // 写入每个点的数据 - for (int i = 0; i < mergedList.size(); i++) { - Point point = mergedList.get(i); - writer.append(point.x + "," + point.y + "," + point.z + "\n"); - } - System.out.println("Data has been written"); - } catch (IOException e) { - System.out.println("Error writing to CSV file: " + e.getMessage()); - } - } - - // float[] vlist = new float[]{11346, 33839, 35469, 23108, 22812, 5519, 5526, 4865, 5842, - // 23089}; - // for (int i = 0; i < vlist.length; i++) { - // polyline.addVertex(new vPoint(i, vlist[i])); - // } - - // ArrayList<Double> v = new ArrayList<>(); - // String filePath = "D://desktop//数据集//New York Stock Exchange//merged_prices.csv"; - // try (BufferedReader br = new BufferedReader(new FileReader(filePath))) { - // String line; - // int count = 0; - // while ((line = br.readLine()) != null && count < 1000) { - // String[] columns = line.split(","); // 假设 CSV 文件以逗号分隔 - // v.add(Double.parseDouble(columns[0])); // 读取第一列数据 - // count++; - // } - // } catch (Exception e) { - // e.printStackTrace(); - // } - // // 打印数据长度 - // System.out.println("Data length: " + v.size()); - // for (int i = 0; i < v.size(); i++) { - // polyline.addVertex(new vPoint(i, v.get(i))); - // } -} diff --git a/server/src/main/java/org/apache/iotdb/db/query/eBUG/eBUG.java b/server/src/main/java/org/apache/iotdb/db/query/eBUG/eBUG.java index d4a8ebfc36f..8c4d41f37f0 100644 --- a/server/src/main/java/org/apache/iotdb/db/query/eBUG/eBUG.java +++ b/server/src/main/java/org/apache/iotdb/db/query/eBUG/eBUG.java @@ -31,11 +31,12 @@ import static org.apache.iotdb.db.query.eBUG.Tool.triArea; public class eBUG { public static List<Point> findEliminated(Polyline lineToSimplify, int[] recentEliminated, int pa_idx, int pi_idx, int pb_idx) { - // TODO 复杂度分析 - // 从最近淘汰的e个点里寻找位于pa~pb之间的：e - // 把上一步找到的点和pa pi pb一起按照时间戳递增排序：记c=b-a。如果e<c，那么eloge，否则c - // 后面鞋带公式计算面积：min(e+3,c) + // 复杂度分析 记c=b-a。 + // 如果e<c，那么从最近淘汰的e个点里寻找位于pa~pb之间的，找到的点和pa pi pb一起按照时间戳递增排序，后面鞋带公式计算面积：O(e+eloge) + // 否则e>=c，直接取T[a:b]，已经排序号了，后面鞋带公式计算面积：O(c) + // 性质：最近淘汰的那一个点一定是位于pa~pb之间，因为正是这个点的淘汰才使得pi的significance要更新！ + // pi: the point whose significance needs updating // pa: left adjacent non-eliminated point of pi // pb: right adjacent non-eliminated point of pi @@ -80,7 +81,7 @@ public class eBUG { } // 按照时间戳递增排序，这是为了后面计算total areal displacement需要 - res.sort(Comparator.comparingDouble(p -> p.x)); // 按时间戳排序 TODO 这样的话时间复杂度要变成e*log(e)了吧？ + res.sort(Comparator.comparingDouble(p -> p.x)); // 按时间戳排序 这样的话时间复杂度变成e*log(e) return res; } @@ -91,9 +92,8 @@ public class eBUG { } List<Point> results = lineToSimplify.getVertices(); // 浅复制 -// results.addAll(lineToSimplify.getVertices()); // TODO debug - // TODO 需要一个东西来记录最近淘汰的点依次是谁 + // 用循环数组来记录最近淘汰的点 int[] recentEliminated = new int[e]; // init 0 points to the first point, skipped in findEliminated int recentEliminatedIdx = 0; // index in the array, circulate @@ -265,7 +265,7 @@ public class eBUG { Polyline polyline = new Polyline(); List<Polyline> polylineList = new ArrayList<>(); Random rand = new Random(1); - int n = 100_0000; + int n = 1000_0000; int p = 10; for (int i = 0; i < n; i += p) { @@ -299,10 +299,10 @@ public class eBUG { // 计算运行时间 // int eParam = 10; try (PrintWriter writer = new PrintWriter(new File("exp.csv"))) { - int[] eParamList = {0, 1, 100, 500, 1000, 5000, 10000, 50000, 10_0000, 30_0000, 50_0000, 60_0000, - 70_0000, 80_0000, 90_0000, 100_0000, 150_0000, 200_0000, 250_0000, 300_0000}; -// for (int eParam = 0; eParam < 2 * n; eParam += 1000) { - for (int eParam : eParamList) { +// int[] eParamList = {0, 1, 100, 500, 1000, 5000, 10000, 50000, 10_0000, 30_0000, 50_0000, 60_0000, +// 70_0000, 80_0000, 90_0000, 100_0000, 150_0000, 200_0000, 250_0000, 300_0000}; + for (int eParam = 0; eParam < n*1.5; eParam += 2_0000) { +// for (int eParam : eParamList) { long startTime = System.currentTimeMillis(); List<Point> results = buildEffectiveArea(polyline, eParam, false); // 输出结果 diff --git a/server/src/main/java/org/apache/iotdb/db/query/eBUG/eBUG_sortedEliminatedDeprecated.java b/server/src/main/java/org/apache/iotdb/db/query/eBUG/eBUG_sortedEliminatedDeprecated.java deleted file mode 100644 index 61c508added..00000000000 --- a/server/src/main/java/org/apache/iotdb/db/query/eBUG/eBUG_sortedEliminatedDeprecated.java +++ /dev/null @@ -1,406 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one - * or more contributor license agreements. See the NOTICE file - * distributed with this work for additional information - * regarding copyright ownership. The ASF licenses this file - * to you under the Apache License, Version 2.0 (the - * "License"); you may not use this file except in compliance - * with the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, - * software distributed under the License is distributed on an - * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY - * KIND, either express or implied. See the License for the - * specific language governing permissions and limitations - * under the License. - */ - -package org.apache.iotdb.db.query.eBUG; - -import java.io.*; -import java.util.*; - -import static org.apache.iotdb.db.query.eBUG.Tool.total_areal_displacement; -import static org.apache.iotdb.db.query.eBUG.Tool.triArea; - - -public class eBUG_sortedEliminatedDeprecated { - public static List<Point> findEliminated(Polyline lineToSimplify, TimestampPriorityQueue recentEliminatedOrdered, - int pa_idx, int pi_idx, int pb_idx) { - // TODO 复杂度分析 - // 性质：最近淘汰的那一个点一定是位于pa~pb之间，因为正是这个点的淘汰才使得pi的significance要更新！ - // pi: the point whose significance needs updating - // pa: left adjacent non-eliminated point of pi - // pb: right adjacent non-eliminated point of pi - // return a list of points, containing pa,p,pb and points between pa&pa from the e most recently eliminated points, - // order by time in ascending order - - Point pa = lineToSimplify.get(pa_idx); - Point pi = lineToSimplify.get(pi_idx); - Point pb = lineToSimplify.get(pb_idx); - - List<Point> res = new ArrayList<>(); - -// if (recentEliminated.length == 0) { // e=0 -// System.out.println("e=0"); -// res.add(pa); -// res.add(pi); -// res.add(pb); -// return res; // pa pi pb已经按照时间戳递增 -// } - - if (recentEliminatedOrdered.size() >= (pb_idx - pa_idx - 2)) { // e >= the total number of eliminated points in this region -// System.out.println("[c=(b-a-2)]<=e, use T directly"); // worst case下, k=c - res = lineToSimplify.getVertices().subList(pa_idx, pb_idx + 1); // 左闭右开 - return res; // 已经按照时间戳递增 - } - - // 从最近淘汰的e个点里寻找位于pa~pb之间的点，找到的有可能小于e个点 -// System.out.println("k>=[c=(b-a-2)]>e, search among e"); - res.add(pa); - - // 包括了c>e=0的情况 - boolean addPi = false; - for (Point p : recentEliminatedOrdered.getQueue()) { // 已经按时间戳递增排序，为了后面计算total areal displacement需要 - if (p.x <= pa.x) { - continue; - } - if (p.x >= pb.x) { - break; - } - if (p.x > pi.x && !addPi) { - res.add(pi); - addPi = true; - } - res.add(p); - } - if (!addPi) { // may happen when no eliminated points found above - res.add(pi); - } - res.add(pb); - return res; - } - - public static List<Point> buildEffectiveArea(Polyline lineToSimplify, int e, boolean debug) { - if (e < 0) { - throw new IllegalArgumentException("Parameter e must be non-negative."); - } - - List<Point> results = lineToSimplify.getVertices(); // 浅复制 -// results.addAll(lineToSimplify.getVertices()); // TODO debug - - // TODO 需要一个东西来记录最近淘汰的点依次是谁 -// int[] recentEliminated = new int[e]; // init 0 points to the first point, skipped in findEliminated -// int recentEliminatedIdx = 0; // index in the array, circulate - TimestampPriorityQueue recentEliminatedOrdered = new TimestampPriorityQueue(e); - - int total = lineToSimplify.size(); - if (total < 3) { - return results; // 不足 3 个点无法形成三角形 - } - - int nTriangles = total - 2; - Triangle[] triangles = new Triangle[nTriangles]; - - // 创建所有三角形并计算初始面积 - for (int i = 1; i < total - 1; i++) { - int index1 = i - 1, index2 = i, index3 = i + 1; - double area = triArea(lineToSimplify.get(index1), lineToSimplify.get(index2), lineToSimplify.get(index3)); - triangles[i - 1] = new Triangle(index1, index2, index3, area); - } - - // 设置三角形的前后关系 - for (int i = 0; i < nTriangles; i++) { // TODO 这个可以和上一个循环合并吗？？好像不可以 - triangles[i].prev = (i == 0 ? null : triangles[i - 1]); - triangles[i].next = (i == nTriangles - 1 ? null : triangles[i + 1]); - } - - // 使用优先队列构建 minHeap - PriorityQueue<Triangle> triangleHeap = new PriorityQueue<>(Comparator.comparingDouble(t -> t.area)); - Collections.addAll(triangleHeap, triangles); // complexity TODO O(n) or O(nlogn)? - - double previousEA = -1; - while (!triangleHeap.isEmpty()) { - // 注意peek只需要直接访问该位置的元素，不涉及任何重排或堆化操作 - // 而poll是删除堆顶元素，需要重新堆化以维护堆的性质，复杂度是O(logk),k是当前堆的大小 - Triangle tri = triangleHeap.poll(); // O(logn) - - // 如果该三角形已经被删除，跳过. Avoid using heap.remove(x) as it is O(n) complexity - // 而且除了heap里，已经没有其他节点会和它关联了，所有的connections关系已经迁移到新的角色替代节点上 - if (tri.isDeleted) { - if (debug) { - System.out.println(">>>bottom-up, remaining " + triangleHeap.size() + " triangles (including those marked for removal)"); - } - continue; - } - - // 真正的淘汰点 - // 记录最近淘汰的点，注意不要重复记录也就是在上面执行之后再确认淘汰 - if (debug) { - System.out.println("(1) eliminate " + lineToSimplify.get(tri.indices[1])); - } - if (e > 0) { // otherwise e=0 -// recentEliminated[recentEliminatedIdx] = tri.indices[1]; -// recentEliminatedIdx = (recentEliminatedIdx + 1) % e; // 0~e-1 circulate - recentEliminatedOrdered.insert(lineToSimplify.get(tri.indices[1])); - } - if (debug) { - System.out.println("the e most recently eliminated points:" + recentEliminatedOrdered); - } - - // 更新当前点的重要性（z 轴存储effective area,这是一个单调增的指标） - if (tri.area > previousEA) { - previousEA = tri.area; - } - results.get(tri.indices[1]).z = previousEA; // dominated significance - if (debug) { - System.out.println(Arrays.toString(tri.indices) + ", Dominated Sig=" + previousEA); - } - - // 更新相邻三角形 - if (tri.prev != null) { - // 标记为失效点，同时new一个新的对象接管它的一切数据和前后连接关系，然后更新前后连接关系、更新significance、加入heap使其排好序 - - // 1. 处理旧的tri.prev被标记删除的事情（角色替代） - // triangleHeap.remove(tri.prev); // Avoid using heap.remove(x) as it is O(n) complexity! - tri.prev.markDeleted(); // O(1) 这个点标记为废掉，前后关联都砍断，但是不remove因为那太耗时，只要heap poll到它就跳过就可以 - - Triangle newPre = new Triangle(tri.prev); // deep copy and inherit connection -// tri.prev = newPre; // can omit, because already done by new Triangle(tri.prev) - - // 2. 处理pi被淘汰引起tri.prev被更新的事情 - // 前一个三角形连到后一个三角形 - tri.prev.next = tri.next; // ATTENTION!!!: 这里的tri.next后面可能会因为处理旧的tri.next被标记删除的事情被换掉！到时候要重新赋值！ - tri.prev.indices[2] = tri.indices[2]; - - // e parameter - List<Point> pointsForSig = findEliminated(lineToSimplify, recentEliminatedOrdered, - tri.prev.indices[0], - tri.prev.indices[1], - tri.prev.indices[2]); // TODO complexity ? - if (debug) { - System.out.println("(2) update point on the left " + lineToSimplify.get(tri.prev.indices[1])); - for (Point point : pointsForSig) { - System.out.println("\t" + point); - } - } - List<Point> baseLine = new ArrayList<>(); - baseLine.add(pointsForSig.get(0)); - baseLine.add(pointsForSig.get(pointsForSig.size() - 1)); // 直接连接左右两边最近的未被淘汰的点 - double sig = total_areal_displacement(pointsForSig, baseLine, false); - tri.prev.area = sig; - - if (debug) { - System.out.println("sig=" + sig); - double tmpTri = triArea(lineToSimplify.get(tri.prev.indices[0]), - lineToSimplify.get(tri.prev.indices[1]), - lineToSimplify.get(tri.prev.indices[2])); - System.out.println("\t" + "tri=" + tmpTri + ", " + ((tmpTri > sig) ? "over-estimated" : "equal/less-estimated")); - } - - // 重新加入堆 - // 在 Java 的 PriorityQueue 中，修改元素的属性不会自动更新堆的顺序 - // 所以必须通过add来显式重新插入修改后的元素 - triangleHeap.add(tri.prev); // O(logn) 注意加入的是一个新的对象isDeleted=false - } - - if (tri.next != null) { - // 标记为失效点，同时new一个新的对象接管它的一切数据和前后连接关系，然后更新前后连接关系、更新significance、加入heap使其排好序 - - // 1. 处理旧的tri.next被标记删除的事情（角色替代） - // triangleHeap.remove(tri.next); // Avoid using heap.remove(x) as it is O(n) complexity - tri.next.markDeleted(); // O(1) 这个点标记为废掉，前后关联都砍断，但是不remove因为那太耗时，只有poll到它就跳过就可以 - - Triangle newNext = new Triangle(tri.next); // deep copy and inherit connection -// tri.next = newNext; // omit, because already done by new Triangle(tri.prev) - - if (tri.prev != null) { - tri.prev.next = tri.next; // ATTENTION!!!: 这里的tri.next已经被换掉！所以之前的要重新赋值！ - } - - // 2. 处理pi被淘汰引起tri.next被更新的事情 - tri.next.prev = tri.prev; // 注意此时tri.prev已经是替代后的节点，tri.next也是，从而被标记为废点的前后关联真正砍断 - tri.next.indices[0] = tri.indices[0]; - - // e parameter - List<Point> pointsForSig = findEliminated(lineToSimplify, recentEliminatedOrdered, - tri.next.indices[0], - tri.next.indices[1], - tri.next.indices[2]); // TODO complexity - if (debug) { - System.out.println("(2) updating point on the right " + lineToSimplify.get(tri.next.indices[1])); - for (Point point : pointsForSig) { - System.out.println("\t" + point); - } - } - List<Point> baseLine = new ArrayList<>(); - baseLine.add(pointsForSig.get(0)); - baseLine.add(pointsForSig.get(pointsForSig.size() - 1)); // 直接连接左右两边最近的未被淘汰的点 - double sig = total_areal_displacement(pointsForSig, baseLine, false); - tri.next.area = sig; - - if (debug) { - System.out.println("sig=" + sig); - double tmpTri = triArea(lineToSimplify.get(tri.next.indices[0]), - lineToSimplify.get(tri.next.indices[1]), - lineToSimplify.get(tri.next.indices[2])); - System.out.println("\t" + "tri=" + tmpTri + ", " + ((tmpTri > sig) ? "over-estimated" : "equal/less-estimated")); - } - - // 重新加入堆 - // 在 Java 的 PriorityQueue 中，修改元素的属性不会自动更新堆的顺序 - // 所以必须通过add 来显式重新插入修改后的元素 - triangleHeap.add(tri.next); // 注意加入的是一个新的对象isDeleted=false - } - if (debug) { - System.out.println(">>>bottom-up, remaining " + triangleHeap.size() + " triangles (including those marked for removal)"); - } - } - return results; // 注意这就是lineToSimplify.getVertices() - } - - public static void main(String[] args) { - Polyline polyline = new Polyline(); - List<Polyline> polylineList = new ArrayList<>(); - Random rand = new Random(1); - int n = 100_0000; - - int p = 10; - for (int i = 0; i < n; i += p) { - Polyline polylineBatch = new Polyline(); - for (int j = i; j < Math.min(i + p, n); j++) { - double v = rand.nextInt(1000000); - - polyline.addVertex(new Point(j, v)); - - polylineBatch.addVertex(new Point(j, v)); - } - polylineList.add(polylineBatch); - } - -// try (FileWriter writer = new FileWriter("raw.csv")) { -// // 写入CSV头部 -// writer.append("x,y,z\n"); -// -// // 写入每个点的数据 -// for (int i = 0; i < polyline.size(); i++) { -// Point point = polyline.get(i); -// writer.append(point.x + "," + point.y + "," + point.z + "\n"); -// } -// System.out.println("Data has been written"); -// } catch (IOException e) { -// System.out.println("Error writing to CSV file: " + e.getMessage()); -// } - - System.out.println("---------------------------------"); -// List<Point> results = new ArrayList<>(); - // 计算运行时间 -// int eParam = 10; - try (PrintWriter writer = new PrintWriter(new File("exp2.csv"))) { - int[] eParamList = {0, 1, 100, 500, 1000, 5000, 10000, 50000, 10_0000, 50_0000, 60_0000, 70_0000, - 80_0000, 90_0000, 100_0000, 150_0000, 200_0000}; -// for (int eParam = 0; eParam < 2 * n; eParam += 1000) { - for (int eParam : eParamList) { - long startTime = System.currentTimeMillis(); - List<Point> results = buildEffectiveArea(polyline, eParam, false); - // 输出结果 - long endTime = System.currentTimeMillis(); - System.out.println("n=" + n + ", e=" + eParam + ", Time taken to reduce points: " + (endTime - startTime) + "ms"); - System.out.println(results.size()); - writer.println(n + "," + eParam + "," + (endTime - startTime)); - } - } catch (FileNotFoundException e) { - throw new RuntimeException(e); - } - -// if (results.size() <= 100) { -// System.out.println("+++++++++++++++++++"); -// for (int i = 0; i < results.size(); i++) { -// Point point = results.get(i); -// System.out.println("Point: (" + point.x + ", " + point.y + ", " + point.z + ")"); -// } -// } - -// try (FileWriter writer = new FileWriter("fast.csv")) { -// // 写入CSV头部 -// writer.append("x,y,z\n"); -// -// // 写入每个点的数据 -// for (int i = 0; i < results.size(); i++) { -// Point point = results.get(i); -// writer.append(point.x + "," + point.y + "," + point.z + "\n"); -// } -// System.out.println("Data has been written"); -// } catch (IOException e) { -// System.out.println("Error writing to CSV file: " + e.getMessage()); -// } - -// System.out.println("---------------------------------"); -// List<List<Point>> resultsBatchList = new ArrayList<>(); -// // 计算运行时间 -// int cnt = 0; -// startTime = System.currentTimeMillis(); -// for (Polyline polylineBatch : polylineList) { -// List<Point> resultsBatch = new ArrayList<>(); -// buildEffectiveArea(polylineBatch, resultsBatch); -// cnt += resultsBatch.size(); -// resultsBatchList.add(resultsBatch); -// } -// // 输出结果 -// endTime = System.currentTimeMillis(); -// System.out.println("Time taken to reduce points: " + (endTime - startTime) + "ms"); -// System.out.println(cnt); -// -// System.out.println("---------------------------------"); -// // 使用 Stream API 合并所有列表 -// List<Point> mergedList = resultsBatchList.stream().flatMap(List::stream).collect(Collectors.toList()); -// int sameCnt = 0; -// for (int i = 0; i < mergedList.size(); i++) { -// if (mergedList.get(i).z == results.get(i).z) { -// sameCnt += 1; -// } -// } -// System.out.println("sameCnt=" + sameCnt + ", percent=" + sameCnt * 1.0 / mergedList.size()); -// -// try (FileWriter writer = new FileWriter("batch.csv")) { -// // 写入CSV头部 -// writer.append("x,y,z\n"); -// -// // 写入每个点的数据 -// for (int i = 0; i < mergedList.size(); i++) { -// Point point = mergedList.get(i); -// writer.append(point.x + "," + point.y + "," + point.z + "\n"); -// } -// System.out.println("Data has been written"); -// } catch (IOException e) { -// System.out.println("Error writing to CSV file: " + e.getMessage()); -// } - } - - // float[] vlist = new float[]{11346, 33839, 35469, 23108, 22812, 5519, 5526, 4865, 5842, - // 23089}; - // for (int i = 0; i < vlist.length; i++) { - // polyline.addVertex(new vPoint(i, vlist[i])); - // } - - // ArrayList<Double> v = new ArrayList<>(); - // String filePath = "D://desktop//数据集//New York Stock Exchange//merged_prices.csv"; - // try (BufferedReader br = new BufferedReader(new FileReader(filePath))) { - // String line; - // int count = 0; - // while ((line = br.readLine()) != null && count < 1000) { - // String[] columns = line.split(","); // 假设 CSV 文件以逗号分隔 - // v.add(Double.parseDouble(columns[0])); // 读取第一列数据 - // count++; - // } - // } catch (Exception e) { - // e.printStackTrace(); - // } - // // 打印数据长度 - // System.out.println("Data length: " + v.size()); - // for (int i = 0; i < v.size(); i++) { - // polyline.addVertex(new vPoint(i, v.get(i))); - // } -} diff --git a/server/src/main/java/org/apache/iotdb/db/query/eBUG/eBUG_sortedEliminatedDeprecated_tmp.java b/server/src/main/java/org/apache/iotdb/db/query/eBUG/eBUG_sortedEliminatedDeprecated_tmp.java deleted file mode 100644 index 4d933cfcd2e..00000000000 --- a/server/src/main/java/org/apache/iotdb/db/query/eBUG/eBUG_sortedEliminatedDeprecated_tmp.java +++ /dev/null @@ -1,398 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one - * or more contributor license agreements. See the NOTICE file - * distributed with this work for additional information - * regarding copyright ownership. The ASF licenses this file - * to you under the Apache License, Version 2.0 (the - * "License"); you may not use this file except in compliance - * with the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, - * software distributed under the License is distributed on an - * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY - * KIND, either express or implied. See the License for the - * specific language governing permissions and limitations - * under the License. - */ - -package org.apache.iotdb.db.query.eBUG; - -import java.io.FileWriter; -import java.io.IOException; -import java.util.*; - -import static org.apache.iotdb.db.query.eBUG.Tool.total_areal_displacement; -import static org.apache.iotdb.db.query.eBUG.Tool.triArea; - - -public class eBUG_sortedEliminatedDeprecated_tmp { - public static List<Point> findEliminated(Polyline lineToSimplify, TimestampPriorityQueue recentEliminatedOrdered, - int pa_idx, int pi_idx, int pb_idx) { - // TODO 复杂度分析 - // 性质：最近淘汰的那一个点一定是位于pa~pb之间，因为正是这个点的淘汰才使得pi的significance要更新！ - // pi: the point whose significance needs updating - // pa: left adjacent non-eliminated point of pi - // pb: right adjacent non-eliminated point of pi - // return a list of points, containing pa,p,pb and points between pa&pa from the e most recently eliminated points, - // order by time in ascending order - - Point pa = lineToSimplify.get(pa_idx); - Point pi = lineToSimplify.get(pi_idx); - Point pb = lineToSimplify.get(pb_idx); - - List<Point> res = new ArrayList<>(); - -// if (recentEliminated.length == 0) { // e=0 -// System.out.println("e=0"); -// res.add(pa); -// res.add(pi); -// res.add(pb); -// return res; // pa pi pb已经按照时间戳递增 -// } - - if (recentEliminatedOrdered.size() >= (pb_idx - pa_idx - 2)) { // e >= the total number of eliminated points in this region -// System.out.println("[c=(b-a-2)]<=e, use T directly"); // worst case下, k=c - res = lineToSimplify.getVertices().subList(pa_idx, pb_idx + 1); // 左闭右开 - return res; // 已经按照时间戳递增 - } - - // 从最近淘汰的e个点里寻找位于pa~pb之间的点，找到的有可能小于e个点 -// System.out.println("k>=[c=(b-a-2)]>e, search among e"); - res.add(pa); - - // 包括了c>e=0的情况 - boolean addPi = false; - for (Point p : recentEliminatedOrdered.getQueue()) { // 已经按时间戳递增排序，为了后面计算total areal displacement需要 - if (p.x <= pa.x) { - continue; - } - if (p.x >= pb.x) { - break; - } - if (p.x > pi.x && !addPi) { - res.add(pi); - addPi = true; - } - res.add(p); - } - if (!addPi) { // may happen when no eliminated points found above - res.add(pi); - } - res.add(pb); - return res; - } - - public static List<Point> buildEffectiveArea(Polyline lineToSimplify, int e, boolean debug) { - if (e < 0) { - throw new IllegalArgumentException("Parameter e must be non-negative."); - } - - List<Point> results = lineToSimplify.getVertices(); // 浅复制 -// results.addAll(lineToSimplify.getVertices()); // TODO debug - - // TODO 需要一个东西来记录最近淘汰的点依次是谁 -// int[] recentEliminated = new int[e]; // init 0 points to the first point, skipped in findEliminated -// int recentEliminatedIdx = 0; // index in the array, circulate - TimestampPriorityQueue recentEliminatedOrdered = new TimestampPriorityQueue(e); - - int total = lineToSimplify.size(); - if (total < 3) { - return results; // 不足 3 个点无法形成三角形 - } - - int nTriangles = total - 2; - Triangle[] triangles = new Triangle[nTriangles]; - - // 创建所有三角形并计算初始面积 - for (int i = 1; i < total - 1; i++) { - int index1 = i - 1, index2 = i, index3 = i + 1; - double area = triArea(lineToSimplify.get(index1), lineToSimplify.get(index2), lineToSimplify.get(index3)); - triangles[i - 1] = new Triangle(index1, index2, index3, area); - } - - // 设置三角形的前后关系 - for (int i = 0; i < nTriangles; i++) { // TODO 这个可以和上一个循环合并吗？？好像不可以 - triangles[i].prev = (i == 0 ? null : triangles[i - 1]); - triangles[i].next = (i == nTriangles - 1 ? null : triangles[i + 1]); - } - - // 使用优先队列构建 minHeap - PriorityQueue<Triangle> triangleHeap = new PriorityQueue<>(Comparator.comparingDouble(t -> t.area)); - Collections.addAll(triangleHeap, triangles); // complexity TODO O(n) or O(nlogn)? - - double previousEA = -1; - while (!triangleHeap.isEmpty()) { - // 注意peek只需要直接访问该位置的元素，不涉及任何重排或堆化操作 - // 而poll是删除堆顶元素，需要重新堆化以维护堆的性质，复杂度是O(logk),k是当前堆的大小 - Triangle tri = triangleHeap.poll(); // O(logn) - - // 如果该三角形已经被删除，跳过. Avoid using heap.remove(x) as it is O(n) complexity - // 而且除了heap里，已经没有其他节点会和它关联了，所有的connections关系已经迁移到新的角色替代节点上 - if (tri.isDeleted) { - if (debug) { - System.out.println(">>>bottom-up, remaining " + triangleHeap.size() + " triangles (including those marked for removal)"); - } - continue; - } - - // 真正的淘汰点 - // 记录最近淘汰的点，注意不要重复记录也就是在上面执行之后再确认淘汰 - if (debug) { - System.out.println("(1) eliminate " + lineToSimplify.get(tri.indices[1])); - } - if (e > 0) { // otherwise e=0 -// recentEliminated[recentEliminatedIdx] = tri.indices[1]; -// recentEliminatedIdx = (recentEliminatedIdx + 1) % e; // 0~e-1 circulate - recentEliminatedOrdered.insert(lineToSimplify.get(tri.indices[1])); - } - if (debug) { - System.out.println("the e most recently eliminated points:" + recentEliminatedOrdered); - } - - // 更新当前点的重要性（z 轴存储effective area,这是一个单调增的指标） - if (tri.area > previousEA) { - previousEA = tri.area; - } - results.get(tri.indices[1]).z = previousEA; // dominated significance - if (debug) { - System.out.println(Arrays.toString(tri.indices) + ", Dominated Sig=" + previousEA); - } - - // 更新相邻三角形 - if (tri.prev != null) { - // 标记为失效点，同时new一个新的对象接管它的一切数据和前后连接关系，然后更新前后连接关系、更新significance、加入heap使其排好序 - - // 1. 处理旧的tri.prev被标记删除的事情（角色替代） - // triangleHeap.remove(tri.prev); // Avoid using heap.remove(x) as it is O(n) complexity! - tri.prev.markDeleted(); // O(1) 这个点标记为废掉，前后关联都砍断，但是不remove因为那太耗时，只要heap poll到它就跳过就可以 - - Triangle newPre = new Triangle(tri.prev); // deep copy and inherit connection -// tri.prev = newPre; // can omit, because already done by new Triangle(tri.prev) - - // 2. 处理pi被淘汰引起tri.prev被更新的事情 - // 前一个三角形连到后一个三角形 - tri.prev.next = tri.next; // ATTENTION!!!: 这里的tri.next后面可能会因为处理旧的tri.next被标记删除的事情被换掉！到时候要重新赋值！ - tri.prev.indices[2] = tri.indices[2]; - - // e parameter - List<Point> pointsForSig = findEliminated(lineToSimplify, recentEliminatedOrdered, - tri.prev.indices[0], - tri.prev.indices[1], - tri.prev.indices[2]); // TODO complexity ? - if (debug) { - System.out.println("(2) update point on the left " + lineToSimplify.get(tri.prev.indices[1])); - for (Point point : pointsForSig) { - System.out.println("\t" + point); - } - } - List<Point> baseLine = new ArrayList<>(); - baseLine.add(pointsForSig.get(0)); - baseLine.add(pointsForSig.get(pointsForSig.size() - 1)); // 直接连接左右两边最近的未被淘汰的点 - double sig = total_areal_displacement(pointsForSig, baseLine, false); - tri.prev.area = sig; - - if (debug) { - System.out.println("sig=" + sig); - double tmpTri = triArea(lineToSimplify.get(tri.prev.indices[0]), - lineToSimplify.get(tri.prev.indices[1]), - lineToSimplify.get(tri.prev.indices[2])); - System.out.println("\t" + "tri=" + tmpTri + ", " + ((tmpTri > sig) ? "over-estimated" : "equal/less-estimated")); - } - - // 重新加入堆 - // 在 Java 的 PriorityQueue 中，修改元素的属性不会自动更新堆的顺序 - // 所以必须通过add来显式重新插入修改后的元素 - triangleHeap.add(tri.prev); // O(logn) 注意加入的是一个新的对象isDeleted=false - } - - if (tri.next != null) { - // 标记为失效点，同时new一个新的对象接管它的一切数据和前后连接关系，然后更新前后连接关系、更新significance、加入heap使其排好序 - - // 1. 处理旧的tri.next被标记删除的事情（角色替代） - // triangleHeap.remove(tri.next); // Avoid using heap.remove(x) as it is O(n) complexity - tri.next.markDeleted(); // O(1) 这个点标记为废掉，前后关联都砍断，但是不remove因为那太耗时，只有poll到它就跳过就可以 - - Triangle newNext = new Triangle(tri.next); // deep copy and inherit connection -// tri.next = newNext; // omit, because already done by new Triangle(tri.prev) - - if (tri.prev != null) { - tri.prev.next = tri.next; // ATTENTION!!!: 这里的tri.next已经被换掉！所以之前的要重新赋值！ - } - - // 2. 处理pi被淘汰引起tri.next被更新的事情 - tri.next.prev = tri.prev; // 注意此时tri.prev已经是替代后的节点，tri.next也是，从而被标记为废点的前后关联真正砍断 - tri.next.indices[0] = tri.indices[0]; - - // e parameter - List<Point> pointsForSig = findEliminated(lineToSimplify, recentEliminatedOrdered, - tri.next.indices[0], - tri.next.indices[1], - tri.next.indices[2]); // TODO complexity - if (debug) { - System.out.println("(2) updating point on the right " + lineToSimplify.get(tri.next.indices[1])); - for (Point point : pointsForSig) { - System.out.println("\t" + point); - } - } - List<Point> baseLine = new ArrayList<>(); - baseLine.add(pointsForSig.get(0)); - baseLine.add(pointsForSig.get(pointsForSig.size() - 1)); // 直接连接左右两边最近的未被淘汰的点 - double sig = total_areal_displacement(pointsForSig, baseLine, false); - tri.next.area = sig; - - if (debug) { - System.out.println("sig=" + sig); - double tmpTri = triArea(lineToSimplify.get(tri.next.indices[0]), - lineToSimplify.get(tri.next.indices[1]), - lineToSimplify.get(tri.next.indices[2])); - System.out.println("\t" + "tri=" + tmpTri + ", " + ((tmpTri > sig) ? "over-estimated" : "equal/less-estimated")); - } - - // 重新加入堆 - // 在 Java 的 PriorityQueue 中，修改元素的属性不会自动更新堆的顺序 - // 所以必须通过add 来显式重新插入修改后的元素 - triangleHeap.add(tri.next); // 注意加入的是一个新的对象isDeleted=false - } - if (debug) { - System.out.println(">>>bottom-up, remaining " + triangleHeap.size() + " triangles (including those marked for removal)"); - } - } - return results; // 注意这就是lineToSimplify.getVertices() - } - - public static void main(String[] args) { - Polyline polyline = new Polyline(); - List<Polyline> polylineList = new ArrayList<>(); - Random rand = new Random(1); -// int n = 1000_0000; - int n = 10000; - - int p = 10; - for (int i = 0; i < n; i += p) { - Polyline polylineBatch = new Polyline(); - for (int j = i; j < Math.min(i + p, n); j++) { - double v = rand.nextInt(1000000); - - polyline.addVertex(new Point(j, v)); - - polylineBatch.addVertex(new Point(j, v)); - } - polylineList.add(polylineBatch); - } - - try (FileWriter writer = new FileWriter("raw.csv")) { - // 写入CSV头部 - writer.append("x,y,z\n"); - - // 写入每个点的数据 - for (int i = 0; i < polyline.size(); i++) { - Point point = polyline.get(i); - writer.append(point.x + "," + point.y + "," + point.z + "\n"); - } - System.out.println("Data has been written"); - } catch (IOException e) { - System.out.println("Error writing to CSV file: " + e.getMessage()); - } - - System.out.println("---------------------------------"); -// List<Point> results = new ArrayList<>(); - // 计算运行时间 - int eParam = 0; - long startTime = System.currentTimeMillis(); - List<Point> results = buildEffectiveArea(polyline, eParam, false); - // 输出结果 - long endTime = System.currentTimeMillis(); - System.out.println("Time taken to reduce points: " + (endTime - startTime) + "ms"); - System.out.println(results.size()); - - if (results.size() <= 100) { - System.out.println("+++++++++++++++++++"); - for (int i = 0; i < results.size(); i++) { - Point point = results.get(i); - System.out.println("Point: (" + point.x + ", " + point.y + ", " + point.z + ")"); - } - } - - try (FileWriter writer = new FileWriter("fast.csv")) { - // 写入CSV头部 - writer.append("x,y,z\n"); - - // 写入每个点的数据 - for (int i = 0; i < results.size(); i++) { - Point point = results.get(i); - writer.append(point.x + "," + point.y + "," + point.z + "\n"); - } - System.out.println("Data has been written"); - } catch (IOException e) { - System.out.println("Error writing to CSV file: " + e.getMessage()); - } - -// System.out.println("---------------------------------"); -// List<List<Point>> resultsBatchList = new ArrayList<>(); -// // 计算运行时间 -// int cnt = 0; -// startTime = System.currentTimeMillis(); -// for (Polyline polylineBatch : polylineList) { -// List<Point> resultsBatch = new ArrayList<>(); -// buildEffectiveArea(polylineBatch, resultsBatch); -// cnt += resultsBatch.size(); -// resultsBatchList.add(resultsBatch); -// } -// // 输出结果 -// endTime = System.currentTimeMillis(); -// System.out.println("Time taken to reduce points: " + (endTime - startTime) + "ms"); -// System.out.println(cnt); -// -// System.out.println("---------------------------------"); -// // 使用 Stream API 合并所有列表 -// List<Point> mergedList = resultsBatchList.stream().flatMap(List::stream).collect(Collectors.toList()); -// int sameCnt = 0; -// for (int i = 0; i < mergedList.size(); i++) { -// if (mergedList.get(i).z == results.get(i).z) { -// sameCnt += 1; -// } -// } -// System.out.println("sameCnt=" + sameCnt + ", percent=" + sameCnt * 1.0 / mergedList.size()); -// -// try (FileWriter writer = new FileWriter("batch.csv")) { -// // 写入CSV头部 -// writer.append("x,y,z\n"); -// -// // 写入每个点的数据 -// for (int i = 0; i < mergedList.size(); i++) { -// Point point = mergedList.get(i); -// writer.append(point.x + "," + point.y + "," + point.z + "\n"); -// } -// System.out.println("Data has been written"); -// } catch (IOException e) { -// System.out.println("Error writing to CSV file: " + e.getMessage()); -// } - } - - // float[] vlist = new float[]{11346, 33839, 35469, 23108, 22812, 5519, 5526, 4865, 5842, - // 23089}; - // for (int i = 0; i < vlist.length; i++) { - // polyline.addVertex(new vPoint(i, vlist[i])); - // } - - // ArrayList<Double> v = new ArrayList<>(); - // String filePath = "D://desktop//数据集//New York Stock Exchange//merged_prices.csv"; - // try (BufferedReader br = new BufferedReader(new FileReader(filePath))) { - // String line; - // int count = 0; - // while ((line = br.readLine()) != null && count < 1000) { - // String[] columns = line.split(","); // 假设 CSV 文件以逗号分隔 - // v.add(Double.parseDouble(columns[0])); // 读取第一列数据 - // count++; - // } - // } catch (Exception e) { - // e.printStackTrace(); - // } - // // 打印数据长度 - // System.out.println("Data length: " + v.size()); - // for (int i = 0; i < v.size(); i++) { - // polyline.addVertex(new vPoint(i, v.get(i))); - // } -} diff --git a/server/src/main/java/org/apache/iotdb/db/query/eBUG/eBUG_tmp.java b/server/src/main/java/org/apache/iotdb/db/query/eBUG/eBUG_tmp.java deleted file mode 100644 index 93267df65a7..00000000000 --- a/server/src/main/java/org/apache/iotdb/db/query/eBUG/eBUG_tmp.java +++ /dev/null @@ -1,397 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one - * or more contributor license agreements. See the NOTICE file - * distributed with this work for additional information - * regarding copyright ownership. The ASF licenses this file - * to you under the Apache License, Version 2.0 (the - * "License"); you may not use this file except in compliance - * with the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, - * software distributed under the License is distributed on an - * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY - * KIND, either express or implied. See the License for the - * specific language governing permissions and limitations - * under the License. - */ - -package org.apache.iotdb.db.query.eBUG; - -import java.io.FileWriter; -import java.io.IOException; -import java.util.*; - -import static org.apache.iotdb.db.query.eBUG.Tool.total_areal_displacement; -import static org.apache.iotdb.db.query.eBUG.Tool.triArea; - - -public class eBUG_tmp { - public static List<Point> findEliminated(Polyline lineToSimplify, int[] recentEliminated, - int pa_idx, int pi_idx, int pb_idx) { - // TODO 复杂度分析 - // 从最近淘汰的e个点里寻找位于pa~pb之间的：e - // 把上一步找到的点和pa pi pb一起按照时间戳递增排序：记c=b-a。如果e<c，那么eloge，否则c - // 后面鞋带公式计算面积：min(e+3,c) - // 性质：最近淘汰的那一个点一定是位于pa~pb之间，因为正是这个点的淘汰才使得pi的significance要更新！ - // pi: the point whose significance needs updating - // pa: left adjacent non-eliminated point of pi - // pb: right adjacent non-eliminated point of pi - // return a list of points, containing pa,p,pb and points between pa&pa from the e most recently eliminated points, - // order by time in ascending order - - Point pa = lineToSimplify.get(pa_idx); - Point pi = lineToSimplify.get(pi_idx); - Point pb = lineToSimplify.get(pb_idx); - - List<Point> res = new ArrayList<>(); - -// if (recentEliminated.length == 0) { // e=0 -// System.out.println("e=0"); -// res.add(pa); -// res.add(pi); -// res.add(pb); -// return res; // pa pi pb已经按照时间戳递增 -// } - - if (recentEliminated.length >= (pb_idx - pa_idx - 2)) { // e >= the total number of eliminated points in this region -// System.out.println("[c=(b-a-2)]<=e, use T directly"); // worst case下, k=c - res = lineToSimplify.getVertices().subList(pa_idx, pb_idx + 1); // 左闭右开 - return res; // 已经按照时间戳递增 - } - - // 从最近淘汰的e个点里寻找位于pa~pb之间的点，找到的有可能小于e个点 -// System.out.println("k>=[c=(b-a-2)]>e, search among e"); - res.add(pa); - res.add(pi); - res.add(pb); - - // 包括了c>e=0的情况 - for (int idx : recentEliminated) { // e points - if (idx == 0) { // init, not filled by real eliminated points yet - break; - } - Point p = lineToSimplify.get(idx); - if (p.x > pa.x && p.x < pb.x) { - res.add(p); - } - } - - // 按照时间戳递增排序，这是为了后面计算total areal displacement需要 - res.sort(Comparator.comparingDouble(p -> p.x)); // 按时间戳排序 TODO 这样的话时间复杂度要变成e*log(e)了吧？ - - return res; - } - - public static List<Point> buildEffectiveArea(Polyline lineToSimplify, int e, boolean debug) { - if (e < 0) { - throw new IllegalArgumentException("Parameter e must be non-negative."); - } - - List<Point> results = lineToSimplify.getVertices(); // 浅复制 -// results.addAll(lineToSimplify.getVertices()); // TODO debug - - // TODO 需要一个东西来记录最近淘汰的点依次是谁 - int[] recentEliminated = new int[e]; // init 0 points to the first point, skipped in findEliminated - int recentEliminatedIdx = 0; // index in the array, circulate - - int total = lineToSimplify.size(); - if (total < 3) { - return results; // 不足 3 个点无法形成三角形 - } - - int nTriangles = total - 2; - Triangle[] triangles = new Triangle[nTriangles]; - - // 创建所有三角形并计算初始面积 - for (int i = 1; i < total - 1; i++) { - int index1 = i - 1, index2 = i, index3 = i + 1; - double area = triArea(lineToSimplify.get(index1), lineToSimplify.get(index2), lineToSimplify.get(index3)); - triangles[i - 1] = new Triangle(index1, index2, index3, area); - } - - // 设置三角形的前后关系 - for (int i = 0; i < nTriangles; i++) { // TODO 这个可以和上一个循环合并吗？？好像不可以 - triangles[i].prev = (i == 0 ? null : triangles[i - 1]); - triangles[i].next = (i == nTriangles - 1 ? null : triangles[i + 1]); - } - - // 使用优先队列构建 minHeap - PriorityQueue<Triangle> triangleHeap = new PriorityQueue<>(Comparator.comparingDouble(t -> t.area)); - Collections.addAll(triangleHeap, triangles); // complexity TODO O(n) or O(nlogn)? - - double previousEA = -1; - while (!triangleHeap.isEmpty()) { - // 注意peek只需要直接访问该位置的元素，不涉及任何重排或堆化操作 - // 而poll是删除堆顶元素，需要重新堆化以维护堆的性质，复杂度是O(logk),k是当前堆的大小 - Triangle tri = triangleHeap.poll(); // O(logn) - - // 如果该三角形已经被删除，跳过. Avoid using heap.remove(x) as it is O(n) complexity - // 而且除了heap里，已经没有其他节点会和它关联了，所有的connections关系已经迁移到新的角色替代节点上 - if (tri.isDeleted) { - if (debug) { - System.out.println(">>>bottom-up, remaining " + triangleHeap.size() + " triangles (including those marked for removal)"); - } - continue; - } - - // 真正的淘汰点 - // 记录最近淘汰的点，注意不要重复记录也就是在上面执行之后再确认淘汰 - if (debug) { - System.out.println("(1) eliminate " + lineToSimplify.get(tri.indices[1])); - } - if (e > 0) { // otherwise e=0 - recentEliminated[recentEliminatedIdx] = tri.indices[1]; - recentEliminatedIdx = (recentEliminatedIdx + 1) % e; // 0~e-1 circulate - } - if (debug) { - System.out.println("the e most recently eliminated points:" + Arrays.toString(recentEliminated)); - } - - // 更新当前点的重要性（z 轴存储effective area,这是一个单调增的指标） - if (tri.area > previousEA) { - previousEA = tri.area; - } - results.get(tri.indices[1]).z = previousEA; // dominated significance - if (debug) { - System.out.println(Arrays.toString(tri.indices) + ", Dominated Sig=" + previousEA); - } - - // 更新相邻三角形 - if (tri.prev != null) { - // 标记为失效点，同时new一个新的对象接管它的一切数据和前后连接关系，然后更新前后连接关系、更新significance、加入heap使其排好序 - - // 1. 处理旧的tri.prev被标记删除的事情（角色替代） - // triangleHeap.remove(tri.prev); // Avoid using heap.remove(x) as it is O(n) complexity! - tri.prev.markDeleted(); // O(1) 这个点标记为废掉，前后关联都砍断，但是不remove因为那太耗时，只要heap poll到它就跳过就可以 - - Triangle newPre = new Triangle(tri.prev); // deep copy and inherit connection -// tri.prev = newPre; // can omit, because already done by new Triangle(tri.prev) - - // 2. 处理pi被淘汰引起tri.prev被更新的事情 - // 前一个三角形连到后一个三角形 - tri.prev.next = tri.next; // ATTENTION!!!: 这里的tri.next后面可能会因为处理旧的tri.next被标记删除的事情被换掉！到时候要重新赋值！ - tri.prev.indices[2] = tri.indices[2]; - - // e parameter - List<Point> pointsForSig = findEliminated(lineToSimplify, recentEliminated, - tri.prev.indices[0], - tri.prev.indices[1], - tri.prev.indices[2]); // TODO complexity ? - if (debug) { - System.out.println("(2) update point on the left " + lineToSimplify.get(tri.prev.indices[1])); - for (Point point : pointsForSig) { - System.out.println("\t" + point); - } - } - List<Point> baseLine = new ArrayList<>(); - baseLine.add(pointsForSig.get(0)); - baseLine.add(pointsForSig.get(pointsForSig.size() - 1)); // 直接连接左右两边最近的未被淘汰的点 - double sig = total_areal_displacement(pointsForSig, baseLine, false); - tri.prev.area = sig; - - if (debug) { - System.out.println("sig=" + sig); - double tmpTri = triArea(lineToSimplify.get(tri.prev.indices[0]), - lineToSimplify.get(tri.prev.indices[1]), - lineToSimplify.get(tri.prev.indices[2])); - System.out.println("\t" + "tri=" + tmpTri + ", " + ((tmpTri > sig) ? "over-estimated" : "equal/less-estimated")); - } - - // 重新加入堆 - // 在 Java 的 PriorityQueue 中，修改元素的属性不会自动更新堆的顺序 - // 所以必须通过add来显式重新插入修改后的元素 - triangleHeap.add(tri.prev); // O(logn) 注意加入的是一个新的对象isDeleted=false - } - - if (tri.next != null) { - // 标记为失效点，同时new一个新的对象接管它的一切数据和前后连接关系，然后更新前后连接关系、更新significance、加入heap使其排好序 - - // 1. 处理旧的tri.next被标记删除的事情（角色替代） - // triangleHeap.remove(tri.next); // Avoid using heap.remove(x) as it is O(n) complexity - tri.next.markDeleted(); // O(1) 这个点标记为废掉，前后关联都砍断，但是不remove因为那太耗时，只有poll到它就跳过就可以 - - Triangle newNext = new Triangle(tri.next); // deep copy and inherit connection -// tri.next = newNext; // omit, because already done by new Triangle(tri.prev) - - if (tri.prev != null) { - tri.prev.next = tri.next; // ATTENTION!!!: 这里的tri.next已经被换掉！所以之前的要重新赋值！ - } - - // 2. 处理pi被淘汰引起tri.next被更新的事情 - tri.next.prev = tri.prev; // 注意此时tri.prev已经是替代后的节点，tri.next也是，从而被标记为废点的前后关联真正砍断 - tri.next.indices[0] = tri.indices[0]; - - // e parameter - List<Point> pointsForSig = findEliminated(lineToSimplify, recentEliminated, - tri.next.indices[0], - tri.next.indices[1], - tri.next.indices[2]); // TODO complexity - if (debug) { - System.out.println("(2) updating point on the right " + lineToSimplify.get(tri.next.indices[1])); - for (Point point : pointsForSig) { - System.out.println("\t" + point); - } - } - List<Point> baseLine = new ArrayList<>(); - baseLine.add(pointsForSig.get(0)); - baseLine.add(pointsForSig.get(pointsForSig.size() - 1)); // 直接连接左右两边最近的未被淘汰的点 - double sig = total_areal_displacement(pointsForSig, baseLine, false); - tri.next.area = sig; - - if (debug) { - System.out.println("sig=" + sig); - double tmpTri = triArea(lineToSimplify.get(tri.next.indices[0]), - lineToSimplify.get(tri.next.indices[1]), - lineToSimplify.get(tri.next.indices[2])); - System.out.println("\t" + "tri=" + tmpTri + ", " + ((tmpTri > sig) ? "over-estimated" : "equal/less-estimated")); - } - - // 重新加入堆 - // 在 Java 的 PriorityQueue 中，修改元素的属性不会自动更新堆的顺序 - // 所以必须通过add 来显式重新插入修改后的元素 - triangleHeap.add(tri.next); // 注意加入的是一个新的对象isDeleted=false - } - if (debug) { - System.out.println(">>>bottom-up, remaining " + triangleHeap.size() + " triangles (including those marked for removal)"); - } - } - return results; // 注意这就是lineToSimplify.getVertices() - } - - public static void main(String[] args) { - Polyline polyline = new Polyline(); - List<Polyline> polylineList = new ArrayList<>(); - Random rand = new Random(1); - int n = 10000; - - int p = 10; - for (int i = 0; i < n; i += p) { - Polyline polylineBatch = new Polyline(); - for (int j = i; j < Math.min(i + p, n); j++) { - double v = rand.nextInt(1000000); - - polyline.addVertex(new Point(j, v)); - - polylineBatch.addVertex(new Point(j, v)); - } - polylineList.add(polylineBatch); - } - -// try (FileWriter writer = new FileWriter("raw.csv")) { -// // 写入CSV头部 -// writer.append("x,y,z\n"); -// -// // 写入每个点的数据 -// for (int i = 0; i < polyline.size(); i++) { -// Point point = polyline.get(i); -// writer.append(point.x + "," + point.y + "," + point.z + "\n"); -// } -// System.out.println("Data has been written"); -// } catch (IOException e) { -// System.out.println("Error writing to CSV file: " + e.getMessage()); -// } - - System.out.println("---------------------------------"); -// List<Point> results = new ArrayList<>(); - // 计算运行时间 -// int eParam = 10; -// for (int eParam = 0; eParam < 2 * n; eParam += 1000) { - int eParam = 22; - long startTime = System.currentTimeMillis(); - List<Point> results = buildEffectiveArea(polyline, eParam, false); - // 输出结果 - long endTime = System.currentTimeMillis(); - System.out.println("n=" + n + ", e=" + eParam + ", Time taken to reduce points: " + (endTime - startTime) + "ms"); - System.out.println(results.size()); - - if (results.size() <= 100) { - System.out.println("+++++++++++++++++++"); - for (int i = 0; i < results.size(); i++) { - Point point = results.get(i); - System.out.println("Point: (" + point.x + ", " + point.y + ", " + point.z + ")"); - } - } - - try (FileWriter writer = new FileWriter("fast2.csv")) { - // 写入CSV头部 - writer.append("x,y,z\n"); - - // 写入每个点的数据 - for (int i = 0; i < results.size(); i++) { - Point point = results.get(i); - writer.append(point.x + "," + point.y + "," + point.z + "\n"); - } - System.out.println("Data has been written"); - } catch (IOException e) { - System.out.println("Error writing to CSV file: " + e.getMessage()); - } - -// System.out.println("---------------------------------"); -// List<List<Point>> resultsBatchList = new ArrayList<>(); -// // 计算运行时间 -// int cnt = 0; -// startTime = System.currentTimeMillis(); -// for (Polyline polylineBatch : polylineList) { -// List<Point> resultsBatch = new ArrayList<>(); -// buildEffectiveArea(polylineBatch, resultsBatch); -// cnt += resultsBatch.size(); -// resultsBatchList.add(resultsBatch); -// } -// // 输出结果 -// endTime = System.currentTimeMillis(); -// System.out.println("Time taken to reduce points: " + (endTime - startTime) + "ms"); -// System.out.println(cnt); -// -// System.out.println("---------------------------------"); -// // 使用 Stream API 合并所有列表 -// List<Point> mergedList = resultsBatchList.stream().flatMap(List::stream).collect(Collectors.toList()); -// int sameCnt = 0; -// for (int i = 0; i < mergedList.size(); i++) { -// if (mergedList.get(i).z == results.get(i).z) { -// sameCnt += 1; -// } -// } -// System.out.println("sameCnt=" + sameCnt + ", percent=" + sameCnt * 1.0 / mergedList.size()); -// -// try (FileWriter writer = new FileWriter("batch.csv")) { -// // 写入CSV头部 -// writer.append("x,y,z\n"); -// -// // 写入每个点的数据 -// for (int i = 0; i < mergedList.size(); i++) { -// Point point = mergedList.get(i); -// writer.append(point.x + "," + point.y + "," + point.z + "\n"); -// } -// System.out.println("Data has been written"); -// } catch (IOException e) { -// System.out.println("Error writing to CSV file: " + e.getMessage()); -// } - } - - // float[] vlist = new float[]{11346, 33839, 35469, 23108, 22812, 5519, 5526, 4865, 5842, - // 23089}; - // for (int i = 0; i < vlist.length; i++) { - // polyline.addVertex(new vPoint(i, vlist[i])); - // } - - // ArrayList<Double> v = new ArrayList<>(); - // String filePath = "D://desktop//数据集//New York Stock Exchange//merged_prices.csv"; - // try (BufferedReader br = new BufferedReader(new FileReader(filePath))) { - // String line; - // int count = 0; - // while ((line = br.readLine()) != null && count < 1000) { - // String[] columns = line.split(","); // 假设 CSV 文件以逗号分隔 - // v.add(Double.parseDouble(columns[0])); // 读取第一列数据 - // count++; - // } - // } catch (Exception e) { - // e.printStackTrace(); - // } - // // 打印数据长度 - // System.out.println("Data length: " + v.size()); - // for (int i = 0; i < v.size(); i++) { - // polyline.addVertex(new vPoint(i, v.get(i))); - // } -}
