markilue
/
self_example
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

爬虫学习、一些笔试题更新

This commit is contained in:
kevinding1125 2023-10-18 10:52:03 +08:00
parent e8b2aa5f18
commit c1c870c74e
25 changed files with 1105 additions and 5 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

5
Spider/BaseInformation Normal file
View File

@ -0,0 +1,5 @@
这个文件夹存放了
1）爬虫学习的一些案例，实际案例操作 https://github.com/Python3WebSpider
2）实际爬取的一些网站等
等
爬虫学习中心：https://setup.scrape.center/

8
Spider/爬虫基本库/__init__.py Normal file
View File

@ -0,0 +1,8 @@
#-*- encoding:utf-8 -*-
'''
@Author : dingjiawen
@Date : 2023/10/17 21:39
@Usage :
@Desc :
'''

8
Spider/爬虫基本库/urllib库/__init__.py Normal file
View File

@ -0,0 +1,8 @@
#-*- encoding:utf-8 -*-
'''
@Author : dingjiawen
@Date : 2023/10/17 21:39
@Usage :
@Desc :
'''

18
Spider/爬虫基本库/urllib库/urllibLearning.py Normal file
View File

@ -0,0 +1,18 @@
#-*- encoding:utf-8 -*-
'''
@Author : dingjiawen
@Date : 2023/10/17 21:40
@Usage : urllib库学习
@Desc :
'''
import urllib.request
# 基本使用，返回一个response对象
# 无data即get请求；有data即post请求，data为bytes类型
response = urllib.request.urlopen("https://www.python.org")
print(response.status)
print(response.getheaders())
print(response.getheader('Server'))

8
Spider/线程相关/__init__.py Normal file
View File

@ -0,0 +1,8 @@
#-*- encoding:utf-8 -*-
'''
@Author : dingjiawen
@Date : 2023/10/17 21:38
@Usage :
@Desc :
'''

81
Spider/线程相关/多线程/MyThread.py Normal file
View File

@ -0,0 +1,81 @@
# -*- encoding:utf-8 -*-
'''
@Author : dingjiawen
@Date : 2023/10/17 20:44
@Usage : 学习多线程库thread的使用
@Desc :
'''
'''
参考：
[1] https://cuiqingcai.com/3325.html
'''
import queue as Queue
import threading
import time
exitFlag = 0
class myThread(threading.Thread):
def __init__(self, threadID, name, q):
threading.Thread.__init__(self)
self.threadID = threadID
self.name = name
self.q = q
def run(self):
print("Starting " + self.name)
process_data(self.name, self.q)
print("Exiting " + self.name)
def process_data(threadName, q):
while not exitFlag:
# 获得锁，成功获得锁定后返回True
# 可选的timeout参数不填时将一直阻塞直到获得锁定
# 否则超时后将返回False
queueLock.acquire()
if not workQueue.empty():
data = q.get()
queueLock.release()
print("{0} processing {1}".format(threadName, data))
else:
queueLock.release()
time.sleep(1)
threadList = ["Thread-1", "Thread-2", "Thread-3"]
nameList = ["One", "Two", "Three", "Four", "Five"]
queueLock = threading.Lock()
workQueue = Queue.Queue(10)
threads = []
threadID = 1
# 创建新线程
for tName in threadList:
thread = myThread(threadID, tName, workQueue)
thread.start()
threads.append(thread)
threadID += 1
# 填充队列
queueLock.acquire()
for word in nameList:
workQueue.put(word)
# release一个有一个线程能跑
queueLock.release()
# 等待队列清空
while not workQueue.empty():
pass
# 通知线程是时候退出
exitFlag = 1
# 等待所有线程完成
for t in threads:
t.join()
print("Exiting Main Thread")

8
Spider/线程相关/多线程/__init__.py Normal file
View File

@ -0,0 +1,8 @@
#-*- encoding:utf-8 -*-
'''
@Author : dingjiawen
@Date : 2023/10/17 20:43
@Usage :
@Desc :
'''

36
Spider/线程相关/多进程/Lock.py Normal file
View File

@ -0,0 +1,36 @@
#-*- encoding:utf-8 -*-
'''
@Author : dingjiawen
@Date : 2023/10/17 21:08
@Usage : Lock相关的类:访问临界资源(共享资源)时互斥
@Desc :
'''
'''
参考：
[1] https://cuiqingcai.com/3335.html
'''
from multiprocessing import Process, Lock
import time
class MyProcess(Process):
def __init__(self, loop, lock):
Process.__init__(self)
self.loop = loop
self.lock = lock
def run(self):
for count in range(self.loop):
time.sleep(0.1)
self.lock.acquire()
print('Pid: ' + str(self.pid) + ' LoopCount: ' + str(count))
self.lock.release()
if __name__ == '__main__':
lock = Lock()
for i in range(10, 15):
p = MyProcess(i, lock)
p.start()

41
Spider/线程相关/多进程/MyMutiProcess.py Normal file
View File

@ -0,0 +1,41 @@
#-*- encoding:utf-8 -*-
'''
@Author : dingjiawen
@Date : 2023/10/17 20:59
@Usage : 学习多进程库mutiProcessing的使用
@Desc :
'''
'''
参考：
[1] https://cuiqingcai.com/3335.html
[2] https://blog.csdn.net/qq_38120851/article/details/122504028
'''
from multiprocessing import Process
import time
class MyProcess(Process):
def __init__(self, loop):
Process.__init__(self)
self.loop = loop
def run(self):
for count in range(self.loop):
time.sleep(1)
print('Pid: ' + str(self.pid) + ' LoopCount: ' + str(count))
if __name__ == '__main__':
# 在这里介绍一个属性，叫做 deamon。每个线程都可以单独设置它的属性，如果设置为 True，当父进程结束后，子进程会自动被终止。
# 如果这里不join，只会打印Main process Ended!
for i in range(2, 10):
p = MyProcess(i)
p.daemon = True
p.start()
p.join()
print("Main process Ended!")

64
Spider/线程相关/多进程/Semaphore.py Normal file
View File

@ -0,0 +1,64 @@
# -*- encoding:utf-8 -*-
'''
@Author : dingjiawen
@Date : 2023/10/17 21:12
@Usage : Semaphore相关类：可以控制临界资源的数量，保证各个进程之间的互斥和同步。
@Desc : 尚且有问题，没法消费，程序卡住
'''
from multiprocessing import Process, Semaphore, Lock, Queue
import time
import random
buffer = Queue(10)
empty = Semaphore(2)
full = Semaphore(1)
lock = Lock()
class Consumer(Process):
def run(self):
global buffer, empty, full, lock
while True:
print('Consumer线程开始运行')
full.acquire()
lock.acquire()
time.sleep(1)
print('Consumer pop an {0}'.format(buffer.get()))
time.sleep(1)
lock.release()
empty.release()
print('Consumer 释放了锁')
class Producer(Process):
def run(self):
global buffer, empty, full, lock
while True:
empty.acquire()
lock.acquire()
print('Producer 添加了锁')
num = random.randint(0,1)
print('Producer append {0}'.format(num))
buffer.put(num)
time.sleep(1)
lock.release()
full.release()
print('Producer 释放了锁')
if __name__ == '__main__':
p = Producer()
c = Consumer()
p.daemon = c.daemon = True
p.start()
c.start()
p.join()
c.join()
print('Ended!')

8
Spider/线程相关/多进程/__init__.py Normal file
View File

@ -0,0 +1,8 @@
#-*- encoding:utf-8 -*-
'''
@Author : dingjiawen
@Date : 2023/10/17 20:58
@Usage :
@Desc :
'''

51
Spider/线程相关/多进程/pool.py Normal file
View File

@ -0,0 +1,51 @@
# -*- encoding:utf-8 -*-
'''
@Author : dingjiawen
@Date : 2023/10/17 21:28
@Usage : pool池相关使用
@Desc :
'''
from multiprocessing import Lock, Pool
import time
import requests
from requests.exceptions import ConnectionError
def scrape(url):
try:
print(requests.get(url))
except ConnectionError:
print('Error Occured ', url)
finally:
print('URL ', url, ' Scraped')
def function(index):
print('Start process: ', index)
time.sleep(3)
print('End process', index)
if __name__ == '__main__':
# 异步线程池使用
pool = Pool(processes=3)
for i in range(4):
pool.apply_async(function, (i,))
print("Started processes")
pool.close()
pool.join()
print("Subprocess done.")
# 便捷的map法
pool = Pool(processes=3)
urls = [
'https://www.baidu.com',
'http://www.meituan.com/',
'http://blog.csdn.net/',
'http://xxxyxxx.net'
]
pool.map(scrape, urls)

8
TensorFlow_eaxmple/Model_train_test/condition_monitoring/plot/test_plot.py
View File

@ -346,7 +346,7 @@ def plot_bar(y_data):
# plt.tick_params(bottom=False, top=False, left=True, right=False, direction='in', pad=1)
plt.xticks([])
plt.ylabel('False Positive Rate(%)', fontsize=22)
plt.ylabel('False Negative Rate(%)', fontsize=22)
plt.xlabel('Methods', fontsize=22)
# plt.tight_layout()
@ -434,7 +434,7 @@ def plot_FNR1(y_data):
# plt.tick_params(bottom=False, top=False, left=True, right=False, direction='in', pad=1)
plt.xticks([])
plt.ylabel('False Negative Rate(%)', fontsize=22)
plt.ylabel('False Positive Rate(%)', fontsize=22)
# plt.tick_params(bottom=False, top=False, left=True, right=False, direction='in', pad=1)
plt.xlabel('Methods', fontsize=22)
@ -491,7 +491,7 @@ def plot_FNR2(y_data):
# plt.tick_params(bottom=False, top=False, left=True, right=False, direction='in', pad=1)
plt.xticks([])
plt.ylabel('False Negative Rate(%)', fontsize=22)
plt.ylabel('False Positive Rate(%)', fontsize=22)
# plt.xlabel('Time', fontsize=5)
# plt.tight_layout()
@ -796,7 +796,7 @@ if __name__ == '__main__':
# list=[98.56,98.95,99.95,96.1,95,99.65,76.25,72.64,75.87,68.74]
# plot_FNR1(list)
# #
list=[3.43,1.99,1.92,2.17,1.63,1.81,1.78,1.8,0.6]
# list=[3.43,1.99,1.92,2.17,1.63,1.81,1.78,1.8,0.6]
list=[3.43,1.99,1.92,2.17,1.8,1.81,1.78,1.8,0.6]
plot_FNR2(list)

86
TensorFlow_eaxmple/Model_train_test/temp/GetThreshold.py Normal file
View File

@ -0,0 +1,86 @@
# -*- encoding:utf-8 -*-
'''
@Author : dingjiawen
@Date : 2023/10/12 16:14
@Usage :
@Desc :
'''
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
def getThreshold(data, cigma_num=1.5):
dims, = data.shape
mean = np.mean(data)
std = np.sqrt(np.var(data))
max = mean + cigma_num * std
min = mean - cigma_num * std
max = np.broadcast_to(max, shape=[dims, ])
min = np.broadcast_to(min, shape=[dims, ])
mean = np.broadcast_to(mean, shape=[dims, ])
# plt.plot(max)
# plt.plot(data)
# # plt.plot(mean)
# plt.plot(min)
# plt.show()
#
#
return max, min
# pass
def EWMA(data):
data1 = pd.DataFrame(data).ewm(span=5).mean()
# plt.plot(data)
# plt.plot(data1, color='blue')
# getThreshold(data)
# plt.show()
return data1
if __name__ == '__main__':
data = np.load("E:\self_example\TensorFlow_eaxmple\Model_train_test/2012轴承数据集预测挑战\data\HI_DATA\Bearing1_1.npy")
a, b = data.shape
minlist = np.array([])
maxlist = np.array([])
for d in data:
max, min = getThreshold(d)
minlist = np.concatenate([minlist, min], axis=0)
maxlist = np.concatenate([maxlist, max], axis=0)
data = data.reshape([a * b, 1])
origin_data = data
# data = np.array([0.5, 5, 0.8, 4.0, 10.0, -0.1, -0.3, 0, 0.5, 6.5])
data = EWMA(data)
data = np.squeeze(data.values)
count = 0
origin_count = 0
for a, b, c, d in zip(data, maxlist, minlist, origin_data):
if c > a or a > b:
count += 1
if c > d or d > b:
origin_count += 1
print("原始劣质率:", origin_count / len(data) * 100, "%")
print("修复后劣质率:", count / len(data) * 100, "%")
plt.plot(origin_data, color='blue', label='Original data')
plt.plot(data, color='green', label='After data repair')
plt.plot(maxlist, color='red', label='upper Threshold')
plt.plot(minlist, color='red', label='lower Threshold')
plt.show()
# getThreshold(data)

8
TensorFlow_eaxmple/Model_train_test/temp/__init__.py Normal file
View File

@ -0,0 +1,8 @@
#-*- encoding:utf-8 -*-
'''
@Author : dingjiawen
@Date : 2023/10/12 16:14
@Usage :
@Desc :
'''

155
TensorFlow_eaxmple/Model_train_test/temp/data_repair(3).py Normal file
View File

@ -0,0 +1,155 @@
#-*- encoding:utf-8 -*-
'''
@Author : dingjiawen
@Date : 2023/10/12 17:51
@Usage :
@Desc :
'''
import numpy as np
import os
import matplotlib.pyplot as plt
import pandas as pd
import random
path = "./data"
def data_read(path):
print("read data...")
dirPath = path
files = os.listdir(dirPath)
data = np.zeros(5)
for file in files:
path = os.path.join(dirPath, file)
x = np.loadtxt(path, delimiter=",", usecols=4)
x = np.transpose(x)
x = np.expand_dims(x, 0)
if (data == 0).all():
data = x
else:
data = np.concatenate((data, x))
return data
def getThreshold(data, cigma_num=3):
dims, = data.shape
mean = np.mean(data)
std = np.sqrt(np.var(data))
max = mean + cigma_num * std
min = mean - cigma_num * std
max = np.broadcast_to(max, shape=[dims, ])
min = np.broadcast_to(min, shape=[dims, ])
mean = np.broadcast_to(mean, shape=[dims, ])
# plt.plot(max)
# plt.plot(data)
# # plt.plot(mean)
# plt.plot(min)
# plt.show()
#
#
return max, min
# pass
def EWMA(data):
print("data repair...")
data1 = pd.DataFrame(data).ewm(span=1000).mean()
return data1
def data_repair(origin_data, maxlist, minlist):
data = np.array(origin_data)
need_repair_max_index = []
need_repair_min_index = []
for index, b, c, d in zip(range(len(data)), maxlist, minlist, data):
if c > d:
need_repair_min_index.append(index)
if d > b:
need_repair_max_index.append(index)
# 生成随机数
# print("超过最大值的数量", len(need_repair_max_index))
# print("低于最小值的数量", len(need_repair_min_index))
maxlen = len(need_repair_max_index)
minlen = len(need_repair_min_index)
# max_repair = random.randint(int(maxlen * 0.7), maxlen)
# min_repair = random.randint(int(minlen * 0.7), minlen)
need_repair_max_index = random.sample(need_repair_max_index, int(maxlen * 0.8))
need_repair_min_index = random.sample(need_repair_min_index, int(minlen * 0.8))
for index in need_repair_max_index:
data[index] = maxlist[index]
for index in need_repair_min_index:
data[index] = minlist[index]
return data
def calculate(path):
basePath = "./data"
folders = os.listdir(basePath)
for folder in folders:
filePath = os.path.join(basePath, folder)
print("文件夹: ", filePath)
data = data_read(filePath)
a, b = data.shape
minlist = np.array([])
maxlist = np.array([])
for d in data:
max, min = getThreshold(d)
minlist = np.concatenate([minlist, min], axis=0)
maxlist = np.concatenate([maxlist, max], axis=0)
data = data.reshape([a * b, 1])
origin_data = data
# data = np.array([0.5, 5, 0.8, 4.0, 10.0, -0.1, -0.3, 0, 0.5, 6.5])
data = data_repair(data[:, 0], maxlist, minlist)
count = 0
origin_count = 0
for a, b, c, d in zip(data, maxlist, minlist, origin_data):
if c > a or a > b:
count += 1
if c > d or d > b:
origin_count += 1
print("原始劣质率:", origin_count / len(data) * 100, "%")
print("修复后劣质率:", count / len(data) * 100, "%")
# origin_data = np.load("./origin_data.npy")
# data = np.load("./data.npy")
# maxlist = np.load("maxlist.npy")
# minlist = np.load("minlist.npy")
le, _ = origin_data.shape
x = [i for i in range(int(le))]
plt.scatter(x, origin_data[:, 0], color='blue', s=0.1, label='Original data')
plt.scatter(x, data, color='green', s=0.1, label='After data repair')
plt.scatter(x, maxlist, color='red', s=0.05, label='Upper Threshold')
plt.scatter(x, minlist, color='red', s=0.05, label='Lower Threshold')
plt.legend(loc='upper left', frameon=True)
plt.show()
if __name__ == '__main__':
calculate(path)

152
TensorFlow_eaxmple/Model_train_test/temp/data_repair.py Normal file
View File

@ -0,0 +1,152 @@
# -*- encoding:utf-8 -*-
'''
@Author : dingjiawen
@Date : 2023/10/12 17:51
@Usage :
@Desc :
'''
import os
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import random
path = "E:\data\PHM 2012轴承挑战数据集\phm-ieee-2012-data-challenge-dataset-master\Learning_set\Bearing1_1"
def data_read(path):
print("read data...")
dirPath = path
files = os.listdir(dirPath)
data = np.zeros(5)
for file in files:
path = os.path.join(dirPath, file)
x = np.loadtxt(path, delimiter=",", usecols=4)
x = np.transpose(x)
x = np.expand_dims(x, 0)
if (data == 0).all():
data = x
else:
data = np.concatenate((data, x))
return data
def getThreshold(data, cigma_num=1.5):
dims, = data.shape
mean = np.mean(data)
std = np.sqrt(np.var(data))
max = mean + cigma_num * std
min = mean - cigma_num * std
max = np.broadcast_to(max, shape=[dims, ])
min = np.broadcast_to(min, shape=[dims, ])
mean = np.broadcast_to(mean, shape=[dims, ])
# plt.plot(max)
# plt.plot(data)
# # plt.plot(mean)
# plt.plot(min)
# plt.show()
#
#
return max, min
# pass
def EWMA(data):
print("data repair...")
data1 = pd.DataFrame(data).ewm(span=35).mean()
return data1
def data_repair(origin_data, maxlist, minlist):
data = np.array(origin_data)
need_repair_max_index = []
need_repair_min_index = []
for index, b, c, d in zip(range(len(data)), maxlist, minlist, data):
if c > d:
need_repair_min_index.append(index)
if d > b:
need_repair_max_index.append(index)
# 生成随机数
# print("超过最大值的数量", len(need_repair_max_index))
# print("低于最小值的数量", len(need_repair_min_index))
maxlen = len(need_repair_max_index)
minlen = len(need_repair_min_index)
# max_repair = random.randint(int(maxlen * 0.7), maxlen)
# min_repair = random.randint(int(minlen * 0.7), minlen)
need_repair_max_index = random.sample(need_repair_max_index, int(maxlen * 0.8))
need_repair_min_index = random.sample(need_repair_min_index, int(minlen * 0.8))
for index in need_repair_max_index:
data[index] = maxlist[index]
for index in need_repair_min_index:
data[index] = minlist[index]
return data
def calculate(path):
data = data_read(path)
a, b = data.shape
minlist = np.array([])
maxlist = np.array([])
for d in data:
max, min = getThreshold(d)
minlist = np.concatenate([minlist, min], axis=0)
maxlist = np.concatenate([maxlist, max], axis=0)
data = data.reshape([a * b, 1])
origin_data = data
# data = np.array([0.5, 5, 0.8, 4.0, 10.0, -0.1, -0.3, 0, 0.5, 6.5])
# data = EWMA(data)
data = data_repair(data[:, 0], maxlist, minlist)
# data = np.squeeze(data.values)
count = 0
origin_count = 0
for a, b, c, d in zip(data, maxlist, minlist, origin_data):
if c > a or a > b:
count += 1
if c > d or d > b:
origin_count += 1
print("原始劣质率:", origin_count / len(data) * 100, "%")
print("修复后劣质率:", count / len(data) * 100, "%")
# origin_data = np.load("./origin_data.npy")
# data = np.load("./data.npy")
# maxlist = np.load("maxlist.npy")
# minlist = np.load("minlist.npy")
le, _ = origin_data.shape
x = [i for i in range(int(le))]
plt.scatter(x, origin_data[:, 0], color='blue', s=0.1, label='Original data')
plt.scatter(x, data, color='green', s=0.1, label='After data repair')
plt.scatter(x, maxlist, color='red', s=0.05, label='Upper Threshold')
plt.scatter(x, minlist, color='red', s=0.05, label='Lower Threshold')
plt.legend(loc='upper left', frameon=True)
plt.show()
if __name__ == '__main__':
calculate(path)

21
TensorFlow_eaxmple/Model_train_test/temp/readCsv.py Normal file
View File

@ -0,0 +1,21 @@
import numpy as np
import os
dirPath = "G:\深度学习/2022-2023\小论文相关\code\PHM 2012轴承挑战数据集\phm-ieee-2012-data-challenge-dataset-master\Learning_set\Bearing1_1"
files = os.listdir(dirPath)
data = np.zeros(5)
for file in files:
path = os.path.join(dirPath, file)
x = np.loadtxt(path, delimiter=",", usecols=4)
x = np.transpose(x)
x = np.expand_dims(x, 0)
if (data == 0).all():
data = x
else:
data = np.concatenate((data, x))
# print(data.shape) (2803,2560)
print(data.shape)
# np.save("./data/Bearing1_1.npy", data, allow_pickle=True)

70
interview/Cainiao/src/main/java/com/markilue/interview/Question2.java Normal file
View File

@ -0,0 +1,70 @@
package com.markilue.interview;
import org.junit.Test;
import java.util.Scanner;
/**
*@BelongsProject: Cainiao
*@BelongsPackage: com.markilue.interview
*@Author: markilue
*@CreateTime: 2023-10-10 19:39
*@Description: TODO
*@Version: 1.0
*/
public class Question2 {
public static void main(String[] args) {
Scanner sc = new Scanner(System.in);
int n = sc.nextInt();
int[] nums = new int[n];
for (int i = 0; i < n; i++) {
nums[i] = sc.nextInt();
}
}
@Test
public void test() {
int[] nums = {2, 1, 3};
sovle(nums);
}
@Test
public void test1() {
int[] nums = {2, 1, 3,5,4};
sovle(nums);
}
public static void sovle(int[] nums) {
int result = 0;
int count = 0;//计算当前连续一样的情况
boolean flag = false;
for (int i = 0; i < nums.length; i++) {
if (nums[i] == i + 1) {
flag = true;
count++;
} else {
if (flag) {
if (count % 2 == 0) {
result += count / 2;
} else {
result += count / 2 + 1;
}
}
count = 0;
flag = false;
}
}
if (count % 2 == 0) {
result += count / 2;
} else {
result += count / 2 + 1;
}
System.out.println(result);
}
}

97
interview/Cainiao/src/main/java/com/markilue/interview/Question3.java Normal file
View File

@ -0,0 +1,97 @@
package com.markilue.interview;
import java.util.ArrayList;
import java.util.List;
import java.util.Scanner;
/**
*@BelongsProject: Cainiao
*@BelongsPackage: com.markilue.interview
*@Author: markilue
*@CreateTime: 2023-10-10 20:03
*@Description: TODO
*@Version: 1.0
*/
public class Question3 {
public static void main(String[] args) {
Scanner sc = new Scanner(System.in);
int n = sc.nextInt();
Node[] nodes = new Node[n];
String next = sc.next();
for (int i = 0; i < next.length(); i++) {
Node node = new Node();
node.index = i + 1;
if ('R'==next.charAt(i)) {
node.color = true;
} else {
node.color = false;
}
nodes[i] = node;
}
for (int i = 0; i < n - 1; i++) {
int index1 = sc.nextInt();
int index2 = sc.nextInt();
nodes[index1 - 1].children.add(nodes[index2 - 1]);
nodes[index2 - 1].children.add(nodes[index1 - 1]);
}
int result = 0;
for (Node node : nodes) {
cur = 0;
blue = 0;
red = 0;
sovle(node);
result += cur;
}
System.out.println(result);
}
static int cur = 0;
static int red = 0;
static int blue = 0;
public static void sovle(Node node) {
if (node == null) {
return;
}
node.busy = true;
if (node.color) {
red++;
} else {
blue++;
}
if (red == blue) {
cur++;
}
for (Node child : node.children) {
if (!child.busy) sovle(child);
}
node.busy = false;
}
}
class Node {
int index;
boolean color;//true为R
boolean busy = false;
List<Node> children = new ArrayList<>();
public Node() {
}
public Node(boolean color, int index) {
this.color = color;
this.index = index;
}
}

92
interviewForqiuzhao/HuaWei/src/main/java/com/markilue/interview/Question1.java Normal file
View File

@ -0,0 +1,92 @@
package com.markilue.interview;
import org.junit.Test;
import java.util.Scanner;
/**
*@BelongsProject: HuaWei
*@BelongsPackage: com.markilue.interview
*@Author: markilue
*@CreateTime: 2023-10-11 20:12
*@Description: TODO
*@Version: 1.0
*/
public class Question1 {
public static void main(String[] args) {
Scanner sc = new Scanner(System.in);
int M = sc.nextInt();
int N = sc.nextInt();
int n = sc.nextInt();
int[] nums = new int[n];
for (int i = 0; i < n; i++) {
nums[i] = sc.nextInt();
}
sovle(nums, M, N);
}
@Test
public void test() {
int M = 4;
int N = 6;
int[] nums ={2,1,2,2,3,2};
sovle(nums,M,N);
}
@Test
public void test1() {
int M = 2;
int N = 10;
int[] nums ={1,9,1,9,8,2};
sovle(nums,M,N);
}
public static void sovle(int[] nums, int M, int N) {
int result = 0;
int sum = 0;
int left = 0;
int temp = 0;
for (int i = 0; i < nums.length; i++) {
sum += nums[i];
if (i - left >= M - 1) {
if (sum > N) {
temp = sum - N;
result += temp;
}
int index = i;
int flag = temp;
while (temp > 0) {
if (temp > nums[index]) {
temp -= nums[index];
nums[index] = 0;
index--;
} else {
nums[index] -= temp;
temp = 0;
}
}
if (flag > 0) {
sum = N - nums[left];
} else {
sum -= nums[left];
}
left++;
}
}
System.out.println(result);
}
}

67
interviewForqiuzhao/HuaWei/src/main/java/com/markilue/interview/Question2.java Normal file
View File

@ -0,0 +1,67 @@
package com.markilue.interview;
import org.junit.Test;
import java.util.Arrays;
import java.util.Scanner;
/**
*@BelongsProject: HuaWei
*@BelongsPackage: com.markilue.interview
*@Author: markilue
*@CreateTime: 2023-10-11 19:31
*@Description: TODO
*@Version: 1.0
*/
public class Question2 {
public static void main(String[] args) {
Scanner sc = new Scanner(System.in);
String[] nums1 = sc.next().split(",");
int[] nums = new int[nums1.length];
for (int i = 0; i < nums1.length; i++) {
nums[i] = Integer.parseInt(nums1[i]);
}
solve(nums);
}
public static void solve(int[] nums) {
Arrays.sort(nums);
int n = nums.length;
int sum = 0;
int index = nums.length - 1;
for (; index >= 0 && nums[index] + sum > 0; index--) {
sum += nums[index];
}
// if (index > 0) {
// //继续判断负数的要不要
// for (; nums[index] + sum > 0; index--) {
// sum=nums[index] + sum;
// }
// }
int count = 1;
int result = 0;
for (int i = index + 1; i < nums.length; i++, count++) {
result += count * nums[i];
}
System.out.println(result);
}
@Test
public void test() {
// String[] nums1 = "-1,-8,0,5,-9".split(",");
// String[] nums1 = "4,3,2".split(",");
String[] nums1 = "-1,-4,-5".split(",");
int[] nums = new int[nums1.length];
for (int i = 0; i < nums1.length; i++) {
nums[i] = Integer.parseInt(nums1[i]);
}
solve(nums);
// System.out.println(Arrays.toString(nums));
}
}

16
interviewForqiuzhao/HuaWei/src/main/java/com/markilue/interview/Question3.java Normal file
View File

@ -0,0 +1,16 @@
package com.markilue.interview;
/**
*@BelongsProject: HuaWei
*@BelongsPackage: com.markilue.interview
*@Author: markilue
*@CreateTime: 2023-10-11 20:35
*@Description: TODO
*@Version: 1.0
*/
public class Question3 {
public static void main(String[] args) {
}
}

1
interviewForqiuzhao/MeiTuan/src/main/java/com/markilue/interview/Question3.java
View File

@ -4,6 +4,7 @@ import org.junit.Test;
import java.util.Arrays;
import java.util.Comparator;
import java.util.HashMap;
import java.util.Scanner;
/**

1
interviewForqiuzhao/MeiTuan/src/main/java/com/markilue/interview/Question5.java
View File

@ -14,7 +14,6 @@ import java.util.Scanner;
*/
public class Question5 {
static int[] father;
public static void main(String[] args) {