row_id
int64 0
48.4k
| init_message
stringlengths 1
342k
| conversation_hash
stringlengths 32
32
| scores
dict |
|---|---|---|---|
5,421
|
$(".btn.btn-danger").on('click', function() {
var checked = jQuery('input:checkbox:checked').map(function () {
return this.value;
}).get();
jQuery('input:checkbox:checked').parents("tr").remove();
});
it is working but after relaoding data is gettinmg back
|
6a2788a2158129f774e32c14841e3bde
|
{
"intermediate": 0.6136978268623352,
"beginner": 0.2237749844789505,
"expert": 0.1625272035598755
}
|
5,422
|
i want to pass my data to spring batch item processor i runing my job inside service with job luncher my data is big and its hash map so idont want use job params
|
be34178fb2d0edf798d056ad969619ec
|
{
"intermediate": 0.5890387892723083,
"beginner": 0.1237512156367302,
"expert": 0.2872099280357361
}
|
5,423
|
hi
|
f140f3eca606b060b7e3c07830a566f5
|
{
"intermediate": 0.3246487081050873,
"beginner": 0.27135494351387024,
"expert": 0.40399640798568726
}
|
5,424
|
What do you know about Google Sheets?
|
81758afa099cf2139b5f99b80272f0ea
|
{
"intermediate": 0.3258422017097473,
"beginner": 0.4365060329437256,
"expert": 0.23765181005001068
}
|
5,425
|
hello
|
412a02ba769997bec6fd8343a3897581
|
{
"intermediate": 0.32064199447631836,
"beginner": 0.28176039457321167,
"expert": 0.39759764075279236
}
|
5,426
|
can you give me amazing css for my items if I want?
|
d7936702e503d30810b3a34c47fb5d2c
|
{
"intermediate": 0.36115267872810364,
"beginner": 0.3205089271068573,
"expert": 0.31833839416503906
}
|
5,427
|
i want to have react <h3> and toggle component next to each other instead of toggle being below
|
dfab5c864ec9a9cbc32fdb14b57cc247
|
{
"intermediate": 0.4073583483695984,
"beginner": 0.23236867785453796,
"expert": 0.36027294397354126
}
|
5,428
|
Создай регистраций и базу данных SQLITE для пользователей , у меня есть эти классы : package com.example.myapp_2;
class User {
private String name;
private String email;
public User(String name, String email) {
this.name = name;
this.email = email;
}
public String getName() {
return name;
}
public String getEmail() {
return email;
}
}
package com.example.myapp_2;
import com.example.myapp_2.List_1.Product;
import java.util.ArrayList;
import java.util.List;
import java.util.concurrent.Callable;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.Future;
public class Shop {
private List<User> userList = new ArrayList<>(); // список пользователей, подписанных на обновления
public Future<Void> updatePricesAndNotifyUsers() {
ExecutorService executorService = Executors.newFixedThreadPool(2); // создаем исполнительный сервис с двумя потоками
userList = getUsersSubscribedForUpdates(); // получаем список пользователей, подписанных на обновления
Future<Void> future = executorService.submit(new Callable<Void>() { // создаем новую задачу и отправляем ее на выполнение
@Override
public Void call() throws Exception {
updatePrices(); // обновляем цены на продукты
for (User user : userList) {
sendPushNotification(user); // отправляем push-уведомления каждому пользователю
}
return null; // возвращаем null, потому что методы updatePrices() и sendPushNotification() ничего не возвращают
}
});
executorService.shutdown(); // останавливаем исполнительный сервис после выполнения задачи
return future; // возвращаем объект типа Future для отслеживания статуса выполнения задачи
}
private List<User> getUsersSubscribedForUpdates() {
List<User> userList = new ArrayList<>();
// здесь мы получаем список всех пользователей, подписанных на обновления и добавляем их в список userList
// Например, так:
User user1 = new User("John", "john@email.com");
User user2 = new User("Jane", "jane@email.com");
userList.add(user1);
userList.add(user2);
return userList;
}
private void updatePrices() {
// здесь мы обновляем цены на продукты
// Например, так:
Product product1 = new Product("Product 1", "Description 1", R.drawable.food_3_1jpg, 0.0f);
Product product2 = new Product("Product 1", "Description 1", R.drawable.food_3_1jpg, 0.0f);
product1.setPrice(12);
product2.setPrice(17);
}
private void sendPushNotification(User user) {
// здесь мы отправляем push-уведомление пользователю
// Например, так:
PushNotificationService.pushNotification(user.getEmail(), "Price update!", "Check out the new prices!");
}
}package com.example.myapp_2.List_1;
public class Product {
private String name;
private String description;
private int imageResource;
private float rating;
private double price;
public Product(String name, String description, int imageResource, float rating, double price) {
this.name = name;
this.description = description;
this.imageResource = imageResource;
this.rating = rating;
this.price = price;
}
public Product(String name, String description, int imageResource, double price) {
this.name = name;
this.description = description;
this.imageResource = imageResource;
this.rating = 0.0f;
this.price = price;
}
public String getName() {
return name;
}
public String getDescription() {
return description;
}
public int getImageResource() {
return imageResource;
}
public float getRating() {
return rating;
}
public void setRating(float rating) {
this.rating = rating;
}
public double getPrice() {
return price;
}
public void setPrice(double price) {
this.price = price;
}
}
|
27c76a993e0740bae371e5d51d5d6f27
|
{
"intermediate": 0.3109753131866455,
"beginner": 0.519079327583313,
"expert": 0.1699453890323639
}
|
5,429
|
How to code GUI in java?
|
3601113c6074110c673d0667e7cd067b
|
{
"intermediate": 0.2619297504425049,
"beginner": 0.5297698974609375,
"expert": 0.20830032229423523
}
|
5,430
|
Write python code for a machine learning model. This model will receive solidity smart contract code to determine if the code has a vulnerability. If a vulnerability is found, the model will return the line of code with the vulnerability and a description of the vulnerability.
|
b2cc58fc246c686feff45212dd3c938f
|
{
"intermediate": 0.1719328612089157,
"beginner": 0.15579701960086823,
"expert": 0.6722701191902161
}
|
5,431
|
Hello from here
|
ffe16dbce4aeeead24b36c686fe97c44
|
{
"intermediate": 0.33012375235557556,
"beginner": 0.22981129586696625,
"expert": 0.4400649964809418
}
|
5,432
|
package com.example.myapp_2;
import android.content.Context;
import com.example.myapp_2.List_1.Product;
import com.example.myapp_2.USERSDB.DBHelper;
import java.util.ArrayList;
import java.util.List;
import java.util.concurrent.Callable;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.Future;
public class Shop {
private Context context;
private List<User> userList = new ArrayList<>(); // список пользователей, подписанных на обновления
public Shop(Context context) {
this.context = context;
}
public Future<Void> updatePricesAndNotifyUsers() {
userList = getUsersSubscribedForUpdates(); // получаем список пользователей, подписанных на обновления
DBHelper dbHelper = new DBHelper(context); // создаем экземпляр класса DBHelper
for (User user : userList) {
user.addToDatabase(context); // регистрируем пользователя в базе данных
}
//!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
ExecutorService executorService = Executors.newFixedThreadPool(2); // создаем исполнительный сервис с двумя потоками
userList = getUsersSubscribedForUpdates(); // получаем список пользователей, подписанных на обновления
Future<Void> future = executorService.submit(new Callable<Void>() { // создаем новую задачу и отправляем ее на выполнение
@Override
public Void call() throws Exception {
updatePrices(); // обновляем цены на продукты
for (User user : userList) {
sendPushNotification(user); // отправляем push-уведомления каждому пользователю
}
return null; // возвращаем null, потому что методы updatePrices() и sendPushNotification() ничего не возвращают
}
});
executorService.shutdown(); // останавливаем исполнительный сервис после выполнения задачи
return future; // возвращаем объект типа Future для отслеживания статуса выполнения задачи
}
private List<User> getUsersSubscribedForUpdates() {
List<User> userList = new ArrayList<>();
// здесь мы получаем список всех пользователей, подписанных на обновления и добавляем их в список userList
// Например, так:
User user1 = new User("John", "john@email.com");
User user2 = new User("Jane", "jane@email.com");
userList.add(user1);
userList.add(user2);
return userList;
}
private void updatePrices() {
// здесь мы обновляем цены на продукты
// Например, так:
Product product1 = new Product("Product 1", "Description 1", R.drawable.food_3_1jpg, 0.0f);
Product product2 = new Product("Product 1", "Description 1", R.drawable.food_3_1jpg, 0.0f);
product1.setPrice(12);
product2.setPrice(17);
}
private void sendPushNotification(User user) {
// здесь мы отправляем push-уведомление пользователю
// Например, так:
PushNotificationService.pushNotification(user.getEmail(), "Price update!", "Check out the new prices!");
}
private List<User> getUsersSubscribedForUpdates() {
List<User> userList = new ArrayList<>();
// здесь мы получаем список всех пользователей, подписанных на обновления и добавляем их в список userList
// Например, так:
User user1 = new User("John", "john@email.com");
User user2 = new User("Jane", "jane@email.com");
user1.addToDatabase(getApplicationContext());
user2.addToDatabase(getApplicationContext());
userList.add(user1);
userList.add(user2);
return userList;
}
}укажи на ошибки
|
a64cbf63f9e4c604536f4bb7ab0a96dd
|
{
"intermediate": 0.37183019518852234,
"beginner": 0.48133978247642517,
"expert": 0.14683009684085846
}
|
5,433
|
hi
|
9d41aaa433cca3b78e3c93d9020948f2
|
{
"intermediate": 0.3246487081050873,
"beginner": 0.27135494351387024,
"expert": 0.40399640798568726
}
|
5,434
|
Исправь ошибку в методе getAllUsers вот код : package com.example.myapp_2.UI.view.fragments;
import android.content.Context;
import android.content.Intent;
import android.content.SharedPreferences;
import android.os.AsyncTask;
import android.os.Bundle;
import androidx.annotation.NonNull;
import androidx.annotation.Nullable;
import androidx.fragment.app.Fragment;
import androidx.recyclerview.widget.LinearLayoutManager;
import androidx.recyclerview.widget.RecyclerView;
import androidx.viewpager.widget.ViewPager;
import android.os.Environment;
import android.os.Handler;
import android.util.Log;
import android.view.LayoutInflater;
import android.view.View;
import android.view.ViewGroup;
import android.widget.ArrayAdapter;
import android.widget.Button;
import android.widget.EditText;
import android.widget.ListView;
import android.widget.RatingBar;
import android.widget.TextView;
import android.widget.Toast;
import com.example.myapp_2.List_1.Product;
import com.example.myapp_2.List_1.ProductAdapter;
import com.example.myapp_2.R;
import com.example.myapp_2.Shop;
import com.example.myapp_2.UI.view.adapters.SliderAdapter;
import com.example.myapp_2.USERSDB.DBHelper;
import com.example.myapp_2.User;
import java.io.File;
import java.io.FileOutputStream;
import java.io.IOException;
import java.io.OutputStreamWriter;
import java.util.ArrayList;
import java.util.List;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.Future;
public class FirstFragment extends Fragment implements View.OnClickListener ,RatingBar.OnRatingBarChangeListener {
private ListView userListView;
private Button updateButton;
private Shop shop;
private Button mShareButton;
private RecyclerView recyclerView;
private ProductAdapter productAdapter;
private RatingBar ratingBar;
private TextView ratingAverageTextView;
private ViewPager viewPager;
private int[] imageUrls = {R.drawable.first_1, R.drawable.first_2, R.drawable.first_3, R.drawable.first_4, R.drawable.first_5};
private List<Product> products = getProducts();
private static final String MY_PREFS_NAME = "MyPrefs";
private float rating1 = 0.0f;
private float rating2 = 0.0f;
private float rating3 = 0.0f;
private float rating4 = 0.0f;
private float rating5 = 0.0f;
private float rating6 = 0.0f;
private float rating7 = 0.0f;
private float rating8 = 0.0f;
private float rating9 = 0.0f;
private float rating10 = 0.0f;
EditText mEditText;
private static final String TAG = "FirstFragment";
private long noteId;
public FirstFragment(long noteId) {
this.noteId = noteId;
}
public FirstFragment() {
}
// private ViewPager viewPager;
// EditText mEditText;
public void createFile(String fileName, String fileContent) {//Реализовать создание текстового файла в app-specific storage.
try {
FileOutputStream fos = requireContext().openFileOutput(fileName, Context.MODE_PRIVATE);
OutputStreamWriter outputStreamWriter = new OutputStreamWriter(fos);
outputStreamWriter.write(fileContent);
outputStreamWriter.close();
String filePath = new File(requireContext().getFilesDir(), fileName).getAbsolutePath(); // получаем абсолютный путь
Log.d(TAG, "File " + fileName + " created successfully at path:" + filePath);
} catch (IOException e) {
e.printStackTrace();
Log.e(TAG, "Failed to create file " + fileName + ": " + e.getMessage());
}
}
public void createTextFileInDirectory(String fileName) {
File directory = Environment.getExternalStoragePublicDirectory(Environment.DIRECTORY_DOWNLOADS);
File textFile = new File(directory, fileName);
try {
FileOutputStream fileOutputStream = new FileOutputStream(textFile);
fileOutputStream.write("Hello World".getBytes());
fileOutputStream.close();
Toast.makeText(getActivity(), "File created at: " + textFile.getAbsolutePath(), Toast.LENGTH_LONG).show();
} catch (IOException e) {
e.printStackTrace();
Toast.makeText(getActivity(), "Error creating file", Toast.LENGTH_SHORT).show();
}
}
@Override
public View onCreateView(LayoutInflater inflater, ViewGroup container, Bundle savedInstanceState) {
View v = inflater.inflate(R.layout.fragment_first, container, false);
userListView = v.findViewById(R.id.user_list_view);
// Создаем адаптер для списка пользователей
ArrayAdapter<User> adapter = new ArrayAdapter<User>(
getActivity(),
android.R.layout.simple_list_item_1,
getAllUsers());
// Присваиваем адаптер списку пользователей
userListView.setAdapter(adapter);
// Регистрируем нового пользователя
User newUser = new User("Mike", "mike@email.com");
registerNewUser(newUser);
updateButton = v.findViewById(R.id.update_button);
shop = new Shop(getActivity()); // передаем объект Activity в конструктор класса Shop
updateButton.setOnClickListener(new View.OnClickListener() {
@Override
public void onClick(View v) {
shop.updatePrices(); // вызываем метод обновления цен у объекта класса Shop
}
});
mShareButton = v.findViewById(R.id.btn_3);
mShareButton.setOnClickListener(new View.OnClickListener() {
@Override
public void onClick(View view) {
shareText();
}
});
recyclerView = v.findViewById(R.id.recycler_view_products);
recyclerView.setLayoutManager(new LinearLayoutManager(getContext()));
productAdapter = new ProductAdapter(getContext(), products);
recyclerView.setAdapter(productAdapter);
productAdapter.setOnAddToCartClickListener(new ProductAdapter.OnAddToCartClickListener() {
@Override
public void onAddToCartClick(Product product) {
Toast.makeText(getActivity(),"Товар успешно добавлен!",Toast.LENGTH_SHORT).show();
}
});
viewPager = v.findViewById(R.id.view_pager);
// SliderAdapter adapter = new SliderAdapter(getActivity(), imageUrls);
//viewPager.setAdapter(adapter);
// Получаем оценки из SharedPreferences
SharedPreferences prefs = getContext().getSharedPreferences(MY_PREFS_NAME, Context.MODE_PRIVATE);
rating1 = prefs.getFloat("rating1", 0.0f);
rating2 = prefs.getFloat("rating2", 0.0f);
rating3 = prefs.getFloat("rating3", 0.0f);
rating4 = prefs.getFloat("rating4", 0.0f);
rating5 = prefs.getFloat("rating5", 0.0f);
rating6 = prefs.getFloat("rating6", 0.0f);
rating7 = prefs.getFloat("rating7", 0.0f);
rating8 = prefs.getFloat("rating8", 0.0f);
rating9 = prefs.getFloat("rating9", 0.0f);
rating10 = prefs.getFloat("rating10", 0.0f);
// Устанавливаем оценки в соответствующие товары
products.get(0).setRating(rating1);
products.get(1).setRating(rating2);
products.get(2).setRating(rating3);
products.get(3).setRating(rating4);
products.get(4).setRating(rating5);
products.get(5).setRating(rating6);
products.get(6).setRating(rating7);
products.get(7).setRating(rating8);
products.get(8).setRating(rating9);
products.get(9).setRating(rating10);
products.get(0).setPrice(300.99);
products.get(1).setPrice(120.99);
products.get(2).setPrice(140.99);
products.get(3).setPrice(420.99);
products.get(4).setPrice(380.99);
products.get(5).setPrice(105.99);
products.get(6).setPrice(200.99);
products.get(7).setPrice(150.99);
products.get(8).setPrice(190.99);
products.get(9).setPrice(299.99);
final Handler handler = new Handler();
final Runnable runnable = new Runnable() {
@Override
public void run() {
int currentItem = viewPager.getCurrentItem();
int totalItems = viewPager.getAdapter().getCount();
int nextItem = currentItem == totalItems - 1 ? 0 : currentItem + 1;
viewPager.setCurrentItem(nextItem);
handler.postDelayed(this, 3000);
}
};
handler.postDelayed(runnable, 3000);
return v;
}
private List<Product> getProducts() {
List<Product> products = new ArrayList<>();
Product product1 = new Product("Product 1", "Description 1", R.drawable.food_3_1jpg, 0.0f);
products.add(product1);
Product product2 = new Product("Product 2", "Description 2", R.drawable.food_1_1, 0.0f);
products.add(product2);
Product product3 = new Product("Product 3", "Description 3", R.drawable.food_1_4, 0.0f);
products.add(product3);
Product product4 = new Product("Product 4", "Description 4", R.drawable.food_1_1, 0.0f);
products.add(product4);
Product product5 = new Product("Product 5", "Description 5", R.drawable.food_1_1, 0.0f);
products.add(product5);
Product product6 = new Product("Product 6", "Description 6", R.drawable.food_1_1,0.0f);
products.add(product6);
Product product7 = new Product("Product 7", "Description 7", R.drawable.food_3_2,0.0f);
products.add(product7);
Product product8 = new Product("Product 8", "Description 8", R.drawable.food_3_3,0.0f);
products.add(product8);
Product product9 = new Product("Product 9", "Description 9", R.drawable.food_1_1,0.0f);
products.add(product9);
Product product10 = new Product("Product 10", "Description 10", R.drawable.food_1_1,0.0f);
products.add(product10);
return products;
}
@Override
public void onViewCreated(@NonNull View view, @Nullable Bundle savedInstanceState) {//После того как отрисовались лементы
super.onViewCreated(view,savedInstanceState);
initView(view);
}
private void initView(View view){
Button btnClick = (Button) view.findViewById(R.id.btn_2);
Button btnClick2 = (Button) view.findViewById(R.id.btn_3);
btnClick.setOnClickListener(this);
btnClick2.setOnClickListener(this);
Button btnClick3 = (Button) view.findViewById(R.id.button);
btnClick3.setOnClickListener(this);
Button btnClick4 = (Button) view.findViewById(R.id.change_btn);
btnClick4.setOnClickListener(this);
}
@Override
public void onCreate(@Nullable Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
Bundle bundle = this.getArguments();
if (bundle != null) {
int myInt = bundle.getInt("hello world", 123);
String strI = Integer.toString(myInt);
Toast.makeText(getActivity(),strI,Toast.LENGTH_SHORT).show();
}
}
@Override
public void onStart() {
super.onStart();
}
@Override
public void onResume() {
super.onResume();
}
@Override
public void onPause(){
super.onPause();
// Сохраняем оценки в SharedPreferences
SharedPreferences.Editor editor = getContext().getSharedPreferences(MY_PREFS_NAME, Context.MODE_PRIVATE).edit();
editor.putFloat("rating1", products.get(0).getRating());
editor.putFloat("rating2", products.get(1).getRating());
editor.putFloat("rating3", products.get(2).getRating());
editor.putFloat("rating4", products.get(3).getRating());
editor.putFloat("rating5", products.get(4).getRating());
editor.putFloat("rating6", products.get(5).getRating());
editor.putFloat("rating7", products.get(6).getRating());
editor.putFloat("rating8", products.get(7).getRating());
editor.putFloat("rating9", products.get(8).getRating());
editor.putFloat("rating10", products.get(9).getRating());
editor.apply();
}
@Override
public void onStop() {
super.onStop();
}
@Override
public void onDestroy() {
super.onDestroy();
}
private void changeFragment(){
getFragmentManager().beginTransaction().replace(R.id.nav_container,new SecondFragment()).addToBackStack(null).commit();
}
private void changeFragment2(){
getFragmentManager().beginTransaction().replace(R.id.nav_container,new ThirdFragment()).addToBackStack(null).commit();
}
private void changeFragment3(){
getFragmentManager().beginTransaction().replace(R.id.nav_container,new ListFragment()).addToBackStack(null).commit();
}
private void changeFragment4(){
getFragmentManager().beginTransaction().replace(R.id.nav_container,new RecycleFragment()).addToBackStack(null).commit();
}
Context context;
@Override
public void onClick(View view) {
switch (view.getId()){
case R.id.btn_2:
changeFragment4();
break;
case R.id.btn_3:
sendBroadcast();
//shareText();
//createFile("test4.txt", "Мой финальный текстовый документ");
//createTextFileInDirectory("test1.txt");
break;
case R.id.button:
changeFragment3();
break;
case R.id.change_btn:
changeFragment4();
break;
}
}
@Override
public void onRatingChanged(RatingBar ratingBar, float v, boolean b) {
}
@Override
public void onSaveInstanceState(@NonNull Bundle outState) {
super.onSaveInstanceState(outState);
// Сохраняем оценки в Bundle
outState.putFloat("rating1", rating1);
outState.putFloat("rating2", rating2);
outState.putFloat("rating3", rating3);
outState.putFloat("rating4", rating4);
outState.putFloat("rating5", rating5);
outState.putFloat("rating6", rating6);
outState.putFloat("rating7", rating7);
outState.putFloat("rating8", rating8);
outState.putFloat("rating9", rating9);
outState.putFloat("rating10", rating10);
}
@Override
public void onViewStateRestored(@Nullable Bundle savedInstanceState) {
super.onViewStateRestored(savedInstanceState);
if (savedInstanceState != null) {
// Восстанавливаем оценки из Bundle
rating1 = savedInstanceState.getFloat("rating1");
rating2 = savedInstanceState.getFloat("rating2");
rating3 = savedInstanceState.getFloat("rating3");
rating4 = savedInstanceState.getFloat("rating4");
rating5 = savedInstanceState.getFloat("rating5");
rating6 = savedInstanceState.getFloat("rating6");
rating7 = savedInstanceState.getFloat("rating7");
rating8 = savedInstanceState.getFloat("rating8");
rating9 = savedInstanceState.getFloat("rating9");
rating10 = savedInstanceState.getFloat("rating10");
// Устанавливаем оценки в соответствующие товары
products.get(0).setRating(rating1);
products.get(1).setRating(rating2);
products.get(2).setRating(rating3);
products.get(3).setRating(rating4);
products.get(4).setRating(rating5);
products.get(5).setRating(rating6);
products.get(6).setRating(rating7);
products.get(7).setRating(rating8);
products.get(8).setRating(rating9);
products.get(9).setRating(rating10);
}
}
private void shareText() {
Intent sendIntent = new Intent(Intent.ACTION_SEND);
sendIntent.putExtra(Intent.EXTRA_TEXT, "Hello, world!");
sendIntent.setType("text/plain");
Intent shareIntent = Intent.createChooser(sendIntent, null);
startActivity(shareIntent);
}
private void sendBroadcast() {
Intent intent = new Intent("com.example.myapp_2.ACTION_RECEIVE_MESSAGE");
intent.putExtra("message", "Hello, world!");
requireContext().sendBroadcast(intent);
}
private void updatePricesAndNotifyUsers() {
Future<Void> future = shop.updatePricesAndNotifyUsers();
new AsyncTask<Void, Void, Void>() {
@Override
protected Void doInBackground(Void... voids) {
try {
future.get(); // ожидаем завершения выполнения задачи
} catch (ExecutionException | InterruptedException e) {
e.printStackTrace();
}
return null;
}
}.execute();
}
// Регистрация нового пользователя
private void registerNewUser(User user) {
user.addToDatabase(getActivity().getApplicationContext());
Log.d("Registered user", user.getName() + " " + user.getEmail());
}
// Получение всех пользователей
private List<User> getAllUsers(Context context) {
DBHelper dbHelper = new DBHelper(context.getApplicationContext());
return dbHelper.getAllUsers();
}
}
|
4472e6c26423bd7518b9b16f8924bb96
|
{
"intermediate": 0.3221990764141083,
"beginner": 0.3921082019805908,
"expert": 0.2856926918029785
}
|
5,435
|
give me an java spark example : union 2 datasets, group by id and then call a map function on the values
|
2ec53d8bc926853a9446ff283ee4ea61
|
{
"intermediate": 0.6760731935501099,
"beginner": 0.1727149784564972,
"expert": 0.15121182799339294
}
|
5,436
|
hi
|
a15e8784c5807c9418a0dc65d4b6ce39
|
{
"intermediate": 0.3246487081050873,
"beginner": 0.27135494351387024,
"expert": 0.40399640798568726
}
|
5,437
|
how to fix the date of a DateField as today django
|
db67a46a0fdbbcd1e7d6eb6a0d51f768
|
{
"intermediate": 0.7381809949874878,
"beginner": 0.12137981504201889,
"expert": 0.14043915271759033
}
|
5,438
|
@echo off
color 0a
set “PASSWORD=yellowstar520”
:LOGIN
cls
echo Enter password to access the hacker menu:
set /p “USERPASS=>”
if “%USERPASS%”==“%PASSWORD%” goto MENU
echo Incorrect password. Try again.
timeout /t 2 /nobreak > NUL
goto LOGIN
:MENU
cls
echo *** HACKER MENU ***
echo.
echo 1. Command
echo 2. Proxy
echo 3. Restart
echo 4. Exit
echo.
set /p option=Choose an option:
if “%option%”==“1” goto COMMAND
if “%option%”==“2” start https://navy.strangled.net
if “%option%”==“3” goto RESTART
if “%option%”==“4” exit
goto MENU
:COMMAND
cls
echo *** EXECUTE COMMANDS ***
echo.
echo Enter your terminal command below:
echo.
set /p “command=cmd~”
echo.
echo Running command: %command%
echo.
cmd /c “%command%”
goto MENU
:RESTART
cls
echo Restarting the program…
echo.
timeout /t 2 /nobreak > NUL
call “%~f0”
goto MENU
|
cb52cb8d9d15f83f597e53939a3204ba
|
{
"intermediate": 0.33800777792930603,
"beginner": 0.30798035860061646,
"expert": 0.3540118634700775
}
|
5,439
|
implementation of neighboring two persons in owl
|
bfa954746a4591d45f8dce726c07d173
|
{
"intermediate": 0.4242912232875824,
"beginner": 0.26681557297706604,
"expert": 0.30889326333999634
}
|
5,440
|
Исправь ошибки : package com.example.myapp_2.USERSDB;
import android.content.ContentValues;
import android.content.Context;
import android.database.sqlite.SQLiteDatabase;
import android.database.sqlite.SQLiteOpenHelper;
import com.example.myapp_2.List_1.Product;
import com.example.myapp_2.User;
import java.util.List;
import android.content.ContentValues;
import android.content.Context;
import android.database.Cursor;
import android.database.sqlite.SQLiteDatabase;
import android.database.sqlite.SQLiteOpenHelper;
import java.util.ArrayList;
import java.util.List;
public class DBHelper extends SQLiteOpenHelper {
private static final int DATABASE_VERSION = 1;
private static final String DATABASE_NAME = "myapp.db";
private static final String TABLE_USERS = "users";
private static final String TABLE_PRODUCTS = "products";
// Добавляем поле KEY_PRICE и определяем его константу
private static final String KEY_PRICE = "price";
private static final String COLUMN_ID = "id";
private static final String COLUMN_NAME = "name";
private static final String COLUMN_EMAIL = "email";
private static final String CREATE_USERS_TABLE = "CREATE TABLE " + TABLE_USERS + " ( " +
COLUMN_ID + " INTEGER PRIMARY KEY AUTOINCREMENT, " +
COLUMN_NAME + " TEXT, " +
COLUMN_EMAIL + " TEXT )";
// Добавляем запрос на создание таблицы продуктов
private static final String CREATE_PRODUCTS_TABLE = "CREATE TABLE " + TABLE_PRODUCTS + " ( " +
COLUMN_ID + " INTEGER PRIMARY KEY AUTOINCREMENT, " +
COLUMN_NAME + " TEXT, " +
"description TEXT, " +
"image INTEGER, " +
KEY_PRICE + " REAL )";
private static final String DROP_USERS_TABLE = "DROP TABLE IF EXISTS " + TABLE_USERS;
private static final String DROP_PRODUCTS_TABLE = "DROP TABLE IF EXISTS " + TABLE_PRODUCTS;
public DBHelper(Context context) {
super(context, DATABASE_NAME, null, DATABASE_VERSION);
}
@Override
public void onCreate(SQLiteDatabase db) {
db.execSQL(CREATE_USERS_TABLE);
db.execSQL(CREATE_PRODUCTS_TABLE); // создаем таблицу продуктов в БД
}
@Override
public void onUpgrade(SQLiteDatabase db, int oldVersion, int newVersion) {
db.execSQL(DROP_USERS_TABLE);
db.execSQL(DROP_PRODUCTS_TABLE); // удаляем таблицу продуктов из БД
onCreate(db);
}
// Добавляем метод updateProductPrice
public void updateProductPrice(Product product) {
SQLiteDatabase db = this.getWritableDatabase();
ContentValues values = new ContentValues();
values.put(KEY_PRICE, product.getPrice());
db.update(TABLE_PRODUCTS, values, COLUMN_NAME + " = ?", new String[] { product.getName() });
db.close();
}
public void addUser(User user) {
SQLiteDatabase db = this.getWritableDatabase();
ContentValues values = new ContentValues();
values.put(COLUMN_NAME, user.getName());
values.put(COLUMN_EMAIL, user.getEmail());
db.insert(TABLE_USERS, null, values);
db.close();
}
public List<User> getAllUsers(Context context) {
List<User> userList = new ArrayList<>();
DBHelper dbHelper = new DBHelper(context);
SQLiteDatabase db = dbHelper.getReadableDatabase();
Cursor cursor = db.rawQuery("SELECT * FROM " + DBHelper.TABLE_USERS, null);
if (cursor.moveToFirst()) {
do {
String name = cursor.getString(cursor.getColumnIndex(DBHelper.COLUMN_NAME));
String email = cursor.getString(cursor.getColumnIndex(DBHelper.COLUMN_EMAIL));
User user = new User(name, email);
userList.add(user);
} while (cursor.moveToNext());
}
cursor.close();
db.close();
return userList;
}
}
|
926bab01a2029793748c31ab7d65533a
|
{
"intermediate": 0.3011206090450287,
"beginner": 0.5004289150238037,
"expert": 0.19845055043697357
}
|
5,441
|
Act as a Blender Python expert. I have this code, could you make it better ?
bl_info = {
"name":"Eazy Azzets",
"author": "Yam K.",
"version": (0,3),
"blender": (3, 3, 0),
"location": "",
"Description": "Making asset browser for GTA 5 Easier",
"warning": "",
"category": "Yam K."
}
import bpy
def eazy_azzets():
objects = bpy.context.scene.objects
for obj in objects:
if obj.name.endswith('.#dr'):
obj.parent = None
obj.name = obj.name[:-4]
obj.asset_mark()
obj.asset_generate_preview()
if not obj.asset_data:
bpy.data.objects.remove(obj)
num_objects = len(objects)
num_columns = int(num_objects ** 0.5)
num_rows = num_columns if num_columns * num_columns == num_objects else num_columns + 1
max_dimensions = [max(obj.dimensions[axis] for obj in objects) for axis in range(2)]
margin = 1
total_margin = [(num_columns - 1) * margin, (num_rows - 1) * margin]
total_dimensions = [num_columns * max_dimensions[0] + total_margin[0], num_rows * max_dimensions[1] + total_margin[1]]
center = [total_dimensions[axis] / 2 for axis in range(2)]
current_position = [center[0] - (total_dimensions[0] / 2), center[1] - (total_dimensions[1] / 2)]
for i, obj in enumerate(objects):
obj.location.x = current_position[0] + max_dimensions[0] / 2
obj.location.y = current_position[1] + max_dimensions[1] / 2
current_position[0] += max_dimensions[0] + margin
if (i + 1) % num_columns == 0:
current_position[0] = center[0] - (total_dimensions[0] / 2)
current_position[1] += max_dimensions[1] + margin
class DoItButton(bpy.types.Operator):
"""Run the Eazy Azzets script"""
bl_idname = "object.eazy_azzets"
bl_label = "Do It ! Just do it !"
bl_options = {'REGISTER', 'UNDO'}
def execute(self, context):
eazy_azzets()
return {'FINISHED'}
class EazyAzzetsPanel(bpy.types.Panel):
"""Eazy Azzets panel"""
bl_label = "Eazy Azzets"
bl_idname = "OBJECT_PT_eazy_azzets"
bl_space_type = 'VIEW_3D'
bl_region_type = 'UI'
bl_category = "Eazy Azzets"
def draw(self, context):
layout = self.layout
layout.operator("object.eazy_azzets")
def register():
bpy.utils.register_class(DoItButton)
bpy.utils.register_class(EazyAzzetsPanel)
def unregister():
bpy.utils.unregister_class(DoItButton)
bpy.utils.unregister_class(EazyAzzetsPanel)
if __name__ == "__main__":
register()
|
08f955ae4e759053d63bdfe60dd3586c
|
{
"intermediate": 0.269031822681427,
"beginner": 0.5023297667503357,
"expert": 0.22863838076591492
}
|
5,442
|
give me an java spark example : union 2 datasets, group by id and then call a map function on the values
|
9e5433520288f0ba02a8010a8bd41696
|
{
"intermediate": 0.6760731935501099,
"beginner": 0.1727149784564972,
"expert": 0.15121182799339294
}
|
5,443
|
import 'dart:convert';
import 'package:flutter/material.dart';
import 'package:webview_flutter/webview_flutter.dart';
import 'package:http/http.dart' as http;
import 'package:login_ui/Feature/Login%20Screen/Login_Screen.dart';
import 'package:login_ui/Feature/home/Response.dart';
class HomePage extends StatefulWidget {
@override
_HomePageState createState() => _HomePageState();
}
class _HomePageState extends State<HomePage> {
final List<String> imagePaths = [
'assets/1.jpeg',
'assets/2.jpeg',
'assets/3.jpeg',
'assets/4.jpeg',
'assets/5.jpeg',
'assets/6.jpeg',
'assets/7.jpeg',
'assets/8.jpeg'
];
List<String> filteredImagePaths = [];
bool isSearching = false;
Map<int, String> imageData = {
0: 'HDFCBANK.NS',
1: 'ICIC',
2: 'data for image 3',
3: 'data for image 4',
4: 'data for image 5',
5: 'data for image 6',
6: 'data for image 7',
7: 'data for image 8',
};
TextEditingController _searchController = TextEditingController();
@override
void initState() {
super.initState();
filteredImagePaths = imagePaths;
}
Future<void> _sendData(BuildContext context, String symbol) async {
try {
var url = Uri.parse('https://36d3-203-109-66-92.in.ngrok.io/hello');
var response = await http.post(
url,
headers: <String, String>{
'Content-Type': 'application/json; charset=UTF-8',
},
body: jsonEncode(<String, String>{'symbol': symbol}),
);
print('Data sent: $symbol');
print('Response status code: ${response.statusCode}');
print('Response body: ${response.body}');
Map<String, dynamic> graphData = jsonDecode(response.body);
String graphUrl = graphData['url'];
await Navigator.of(context).push(
MaterialPageRoute(
builder: (_) => Scaffold(
appBar: AppBar(
title: Text(symbol),
),
body: WebView(
initialUrl: graphUrl,
javascriptMode: JavascriptMode.unrestricted,
),
),
),
);
} catch (e) {
print('Error: $e');
}
}
WebView? _webView;
@override
Widget build(BuildContext context) {
return Scaffold(
appBar: AppBar(
title: !isSearching
? Text('Stocks')
: TextField(
controller: _searchController,
decoration: InputDecoration(
hintText: 'Search',
icon: Icon(Icons.search),
),
onSubmitted: (value) {
_sendData(context, value);
},
),
actions: [
IconButton(
icon: Icon(Icons.search),
onPressed: () {
setState(() {
isSearching = !isSearching;
filteredImagePaths = imagePaths;
});
},
),
],
),
body: Stack(
children: [
Container(
decoration: BoxDecoration(
image: DecorationImage(
image: AssetImage('assets/theme.jpg'),
fit: BoxFit.cover,
),
),
child: GridView.count(
crossAxisCount: 2,
padding: EdgeInsets.all(8),
mainAxisSpacing: 8,
crossAxisSpacing: 8,
children: List.generate(filteredImagePaths.length, (index) {
return GestureDetector(
onTap: () async {
String symbol = imageData[index]!;
await _sendData(context, symbol);
},
child: ClipRRect(
borderRadius: BorderRadius.circular(8),
child: Stack(
fit: StackFit.expand,
children: [
Image.asset(
filteredImagePaths[index],
fit: BoxFit.cover,
),
Container(
decoration: BoxDecoration(
gradient: LinearGradient(
begin: Alignment.bottomCenter,
end: Alignment.topCenter,
colors: [
Colors.black.withOpacity(0.8),
Colors.transparent
],
),
),
),
],
),
),
);
}),
),
),
if (_webView != null)
Positioned.fill(
child: Column(
children: [
Expanded(
child: _webView!,
),
ElevatedButton(
onPressed: () {
setState(() {
_webView = null;
});
},
child: Text('Close Graph'),
),
],
),
),
],
),
);
}
}
cant see graph solve it
|
e04d63b2ec95a4cc275544cf46bdbbfd
|
{
"intermediate": 0.35027381777763367,
"beginner": 0.554667592048645,
"expert": 0.09505852311849594
}
|
5,444
|
how to make it so my code in C# allows both lower case and upper case inputs as equivalent.
|
faf2e5d492e19b0d935af4a20571c5c2
|
{
"intermediate": 0.4047286808490753,
"beginner": 0.28642645478248596,
"expert": 0.30884483456611633
}
|
5,445
|
hey sup? are familiar with scrapy?
|
8c42e2f7e64c38851202e773fe358165
|
{
"intermediate": 0.2987898290157318,
"beginner": 0.5485451817512512,
"expert": 0.15266497433185577
}
|
5,446
|
make a DateField to just accept today django
|
f7a2a5189a3e34a24f42bf0604a1c27a
|
{
"intermediate": 0.5907828211784363,
"beginner": 0.16446781158447266,
"expert": 0.24474938213825226
}
|
5,447
|
are familiar with scrapy>
|
e23cec322a87651bfe0d80fe34d53db8
|
{
"intermediate": 0.2791929543018341,
"beginner": 0.6202561855316162,
"expert": 0.10055078566074371
}
|
5,448
|
Flutter 3.7. Which theme option should I use to configure font size of all text fields
|
cbae2697d5a3199717d27365613b416d
|
{
"intermediate": 0.5426491498947144,
"beginner": 0.19886787235736847,
"expert": 0.258482962846756
}
|
5,449
|
I need an array formula that will search Column 'H' in Sheet 'SrvSrch' for dates that are 31 days before Today. Column 'H' contains date values and the column is formatted as Dates. Each match must then be displayed in a separate row of the same column in Sheet1 without spaces as dd-mm-yyyy for each of all the matches found along with the CONCATENATE the Values of Column 'J' and Column 'K' that are on the same row.There must be a double space between the CONCATENATED values.
|
cc9facca7ff77a7fab60e2e484b8e4fe
|
{
"intermediate": 0.4148711562156677,
"beginner": 0.21459300816059113,
"expert": 0.37053585052490234
}
|
5,450
|
A = np.array([[1,2,3]
[4,5,6]
[7,8,9]])
A.tolist().sort(key=A.tolist[i for i in range(A.tolist()) if (i+1)%4==1],reversed=True)
|
8519e6ed690eb62b725cda5e685f4da8
|
{
"intermediate": 0.35015246272087097,
"beginner": 0.28708186745643616,
"expert": 0.3627656102180481
}
|
5,451
|
act as an expert in python programming. I will ask questions.
|
893aa62ab56eeaed1a259b4a8c688b7f
|
{
"intermediate": 0.28015562891960144,
"beginner": 0.33540791273117065,
"expert": 0.3844364881515503
}
|
5,452
|
use JavaScript reander 10000 data, and create and insert table element
|
f96abfce7f3180def0fee4e52a1b7bb4
|
{
"intermediate": 0.547208309173584,
"beginner": 0.22501657903194427,
"expert": 0.2277752012014389
}
|
5,453
|
Please create react code that takes an image as input and from predetermined x and y coordinates passed down as properties, overlay a color that spread from said coordinates outward until they meet.
This overlaying color should move in different speed depending on the color of the underlaying image, which will be a topographic map of a location.
For example the image will be bright where the topography is flat which allow the overlay to spread quickly and darker where there is mountains and hills which will make the overlay move slower.
Each set of coordinates will create one overlay, and when the overlays meet they will blend together creating one overlay to the eye.
|
55b5c8b42c42012dbfc57908274f27d1
|
{
"intermediate": 0.3445793688297272,
"beginner": 0.14959196746349335,
"expert": 0.5058286786079407
}
|
5,454
|
act as an expert in python language. I will ask questions about python script.
|
b4d406f0b5e9a4b9994f46f29906e3c7
|
{
"intermediate": 0.2258869856595993,
"beginner": 0.5546274185180664,
"expert": 0.21948562562465668
}
|
5,455
|
sa
|
2b784f857e373df8708e1888104326ba
|
{
"intermediate": 0.32281410694122314,
"beginner": 0.3021789491176605,
"expert": 0.3750069737434387
}
|
5,456
|
act as an expert in python programming. I will ask questions and you need to follow exactly what the instructions say.
|
f513516f87b93d9cfc35eca9bb5cef64
|
{
"intermediate": 0.3451356291770935,
"beginner": 0.3839702904224396,
"expert": 0.2708941102027893
}
|
5,457
|
hi
|
05145498742da46f61cd24c575d06884
|
{
"intermediate": 0.3246487081050873,
"beginner": 0.27135494351387024,
"expert": 0.40399640798568726
}
|
5,458
|
i want to validate input component in react with regex,show me an example
|
8c15b0191efaae2e0c3501caef19027f
|
{
"intermediate": 0.6515113115310669,
"beginner": 0.15381288528442383,
"expert": 0.1946757584810257
}
|
5,459
|
hello
|
88667aad7df0c41482bf99981f8d57b1
|
{
"intermediate": 0.32064199447631836,
"beginner": 0.28176039457321167,
"expert": 0.39759764075279236
}
|
5,460
|
why this script doesn't print do you want to play again input? import random
class Card:
def __init__(self, suit, number):
self.suit = suit
self.number = number
def __str__(self):
return f"{self.number} of {self.suit}"
class Deck():
def __init__(self):
self.cards = []
self.card_range = [2, 3, 4, 5, 6, 7, 8, 9, 10, "Jack", "Queen", "King", "Ace"]
self.suits = ["Diamonds", "Spades", "Hearts", "Clubs"]
self.__build()
def __build(self):
for s in self.suits:
for c in self.card_range:
self.cards.append(Card(s, c))
def shuffle(self):
random.shuffle(self.cards)
def deal_a_card(self):
return self.cards.pop()
def card_value(card):
if card.number == "Ace":
return 11
elif card.number in ["Jack", "Queen", "King"]:
return 10
else:
return card.number
def calculate_score(hand):
score = sum(card_value(card) for card in hand)
aces = [card for card in hand if card.number == "Ace"]
while score > 21 and aces:
aces.pop()
score -= 10
return score
def main():
deck = Deck()
deck.shuffle()
player_hand = [deck.deal_a_card(), deck.deal_a_card()]
dealer_hand = [deck.deal_a_card(), deck.deal_a_card()]
while True:
player_score = calculate_score(player_hand)
print(f"Player hand: {', '.join(map(str, player_hand))} - Score: {player_score}")
print(f"Dealer hand: {dealer_hand[0]}, HIDDEN CARD")
if player_score > 21:
print(f" Busted with a score of {player_score}! Dealer wins.")
break
action = input("Do you want to hit or stand? (h or s)").lower()
if action == "hit" or action == "h":
player_hand.append(deck.deal_a_card())
elif action == "stand" or action == "s":
while calculate_score(dealer_hand) < 17:
dealer_hand.append(deck.deal_a_card())
dealer_score = calculate_score(dealer_hand)
print(f"Player final hand: {', '.join(map(str, player_hand))} - Score: {player_score}")
print(f"Dealer final hand: {', '.join(map(str, dealer_hand))} - Score: {dealer_score}")
if dealer_score > 21 or player_score > dealer_score:
print(" WINNER WINNER CHICKEN DINNER!")
elif dealer_score == player_score:
print(" IT'S A TIE!")
else:
print(" DEALER WINS! SAD FACE")
break
else:
print("INVALID OPTION, PLEASE ENTER HIT OR STAND. (h or s)")
choice = input("Do you want to play again? (y or n) ")
if not choice.lower().startswith('y'):
print("Good Bye")
break
if __name__ == "__main__":
main()
|
e4767e128b12e0382930bc9db11f7cc4
|
{
"intermediate": 0.3317815661430359,
"beginner": 0.48290425539016724,
"expert": 0.18531417846679688
}
|
5,461
|
Вот код , добавь какой нибудь простенький функционал: package com.example.myapp_2;
public class MyTask implements Runnable {
@Override
public void run() {
// Логика задачи
System.out.println("Task executed by thread " + Thread.currentThread().getName());
}
}
initView(view);
// Создание пула потоков с 2 потоками
ExecutorService executorService = Executors.newFixedThreadPool(2);
// Создание двух задач
Runnable task1 = new MyTask();
Runnable task2 = new MyTask();
// Запуск задач через пул потоков
executorService.execute(task1);
executorService.execute(task2);
//создается пул с двумя потоками, создаются две задачи и запускаются через пул.
// Каждая задача выполняется в своем потоке, и в консоль выводится имя каждого потока.
|
cfdc9520bbdd46b1f917e24ceb609cb5
|
{
"intermediate": 0.3973025679588318,
"beginner": 0.3780643045902252,
"expert": 0.22463318705558777
}
|
5,462
|
are you familiar with python scrapy?
|
628d4edc0579549f6dfe4ee3b2ada189
|
{
"intermediate": 0.3312941789627075,
"beginner": 0.3196166157722473,
"expert": 0.34908920526504517
}
|
5,463
|
Create a react component that takes an topographic image as input and from predetermined coordinates in the image show an overlay with a color that grow over time, but only after one of the overlays are clicked.
They should be 30 pixels when you first load the page and they should all have different colors.
This overlaying color should expand in different speed depending on the color of the underlaying image, which will be a topographic map of a location.
For example the image will be bright where the topography is flat which allow the overlay to spread quickly and darker where there is mountains and hills which will make the overlay move slower.
Each set of coordinates will create one overlay, and when the overlays meet they will blend together creating one overlay with the color red.
|
715e680f7169f623aed03407e5767929
|
{
"intermediate": 0.33155950903892517,
"beginner": 0.29157617688179016,
"expert": 0.37686431407928467
}
|
5,464
|
hi
|
f61f4034c2a47a080baf7428b0a3a298
|
{
"intermediate": 0.3246487081050873,
"beginner": 0.27135494351387024,
"expert": 0.40399640798568726
}
|
5,465
|
import random
import tkinter as tk
def generate_random_number():
random_number = random.randint(1, 10)
result_label.config(text=f"Random number is {random_number}“)
root = tk.Tk()
root.title(“Random Number Generator”)
generate_button = tk.Button(root, text=“Generate Random Number”, command=generate_random_number)
generate_button.pack(pady=10)
result_label = tk.Label(root, text=”")
result_label.pack()
root.mainloop() u just did thta doe but its not working
|
3ff09a76d762edb35365da6b1a119760
|
{
"intermediate": 0.37756311893463135,
"beginner": 0.364928662776947,
"expert": 0.25750815868377686
}
|
5,466
|
Use JavaScript implementation data state manage
|
6a905f304237007006a7be2f4006dd21
|
{
"intermediate": 0.6451967358589172,
"beginner": 0.1959068924188614,
"expert": 0.158896341919899
}
|
5,467
|
Fivem scripting LUA
I'm currently using GetInteriorAtCoords
is there anyway that i can create the interior somewhere else?
|
fc726bfe3ef8e99ad814ac689fb442d2
|
{
"intermediate": 0.4678493142127991,
"beginner": 0.27607545256614685,
"expert": 0.2560751736164093
}
|
5,468
|
Где я ошибся в этом коде ? Исправь ошибки : package com.example.myapp_2;
import com.example.myapp_2.UI.view.fragments.SecondFragment;
private static class FactorialCalculator implements Runnable {
private int number;
private int result;
private SecondFragment.Callback callback;
public FactorialCalculator(int number) {
this.number = number;
}
@Override
public void run() {
result = 1;
for (int i = 2; i <= number; i++) {
result *= i;
}
if (callback != null) {
callback.onResult(result);
}
}
public void setCallback(SecondFragment.Callback callback) {
this.callback = callback;
}
}
public interface Callback {
void onResult(int result);
}
public View onCreateView(LayoutInflater inflater, ViewGroup container, Bundle savedInstanceState) {
View v = inflater.inflate(R.layout.fragment_second, container, false);
inputEditText = v.findViewById(R.id.input_edit_text);
resultTextView = v.findViewById(R.id.result_text_view);
Button factorialButton = v.findViewById(R.id.factorial_button);
factorialButton.setOnClickListener(new View.OnClickListener() {
@Override
public void onClick(View view) {
int number = Integer.parseInt(inputEditText.getText().toString());
FactorialCalculator calculator = new FactorialCalculator(number);
calculator.setCallback(new Callback() {
@Override
public void onResult(int result) {
resultTextView.setText(Integer.toString(result));
}
});
new Thread(calculator).start();
}
});
|
71af303cb20ce42339f7dafc8f1132dd
|
{
"intermediate": 0.445870041847229,
"beginner": 0.3048584759235382,
"expert": 0.24927152693271637
}
|
5,469
|
Flutter how to get widget property by key?
|
0ca4ea1dc6d873e339025abe0992e5c7
|
{
"intermediate": 0.49749264121055603,
"beginner": 0.12302763015031815,
"expert": 0.37947970628738403
}
|
5,470
|
Flutter 3.7. What are possible reasons that TextFormField default (without extra styles) font size is not using bodyMedium theme option?
|
3b691bd41f9dbcaa3d1b5763c0e4623b
|
{
"intermediate": 0.5816711783409119,
"beginner": 0.21973316371440887,
"expert": 0.19859568774700165
}
|
5,471
|
Android how to implement worker thorought dependenciece
|
a55913bb20f90cb981c105bfb5f9bb80
|
{
"intermediate": 0.5162627100944519,
"beginner": 0.1728944480419159,
"expert": 0.3108428716659546
}
|
5,472
|
implementation "androidx.work :work-runtime:$versions.work" дополни и исправь
|
e5bc51b666ff847497b6bdc8da41a004
|
{
"intermediate": 0.5717888474464417,
"beginner": 0.21891775727272034,
"expert": 0.20929333567619324
}
|
5,473
|
Create a react component that takes imageUrl and Coordinates as properties.
The imageUrl should serve as a background to the component and each of the coordinates should create an overlay at the specific location on top of the image.
Each of the overlays should be of a different color from this list
Red, Blue, Orange, Green, Purple, Black
When the component loads the first time, the overlay should not be changing size but instead wait for it to be clicked.
When one of the overlays is clicked all the overlays start to grow.
If the overlays meet they stop to grow until the last overlay meets another overlay.
|
c80f7425f835045584097f0c6b5206a0
|
{
"intermediate": 0.3404653072357178,
"beginner": 0.29685038328170776,
"expert": 0.3626842200756073
}
|
5,474
|
package com.example.myapp_2.UI.view.fragments;
import static android.content.Context.MODE_PRIVATE;
import android.app.NotificationChannel;
import android.app.NotificationManager;
import android.app.PendingIntent;
import android.content.Context;
import android.content.Intent;
import android.content.SharedPreferences;
import android.os.Build;
import android.os.Bundle;
import androidx.annotation.NonNull;
import androidx.annotation.Nullable;
import androidx.core.app.NotificationCompat;
import androidx.fragment.app.Fragment;
import androidx.recyclerview.widget.LinearLayoutManager;
import androidx.recyclerview.widget.RecyclerView;
import androidx.viewpager.widget.ViewPager;
import android.os.Handler;
import android.view.LayoutInflater;
import android.view.Menu;
import android.view.MenuInflater;
import android.view.View;
import android.view.ViewGroup;
import android.widget.Button;
import android.widget.EditText;
import android.widget.Switch;
import android.widget.TextView;
import android.widget.Toast;
import com.example.myapp_2.List_1.Product;
import com.example.myapp_2.List_1.ProductAdapter;
import com.example.myapp_2.R;
import com.example.myapp_2.UI.view.adapters.SliderAdapter;
import com.example.myapp_2.UI.view.adapters.SliderAdapter_2;
import java.util.ArrayList;
import java.util.List;
import android.os.Bundle;
import android.view.LayoutInflater;
import android.view.View;
import android.view.ViewGroup;
import android.widget.Button;
import android.widget.EditText;
import android.widget.TextView;
import androidx.fragment.app.Fragment;
public class SecondFragment extends Fragment implements View.OnClickListener {
private static final String MY_PREFS_NAME = "MyPrefs_2";
private RecyclerView recyclerView;
private ProductAdapter productAdapter;
private List<Product> products = getProducts();
private float rating1 = 0.0f;
private float rating2 = 0.0f;
private float rating3 = 0.0f;
private float rating4 = 0.0f;
private float rating5 = 0.0f;
private float rating6 = 0.0f;
private float rating7 = 0.0f;
private float rating8 = 0.0f;
private float rating9 = 0.0f;
private float rating10 = 0.0f;
//private static final String MY_PREFS_NAME = "MyPrefs";
public SecondFragment() {
}
private ViewPager viewPager;
private int[] imageUrls = {R.drawable.second_1, R.drawable.second_3, R.drawable.second_4, R.drawable.second_5, R.drawable.second_22};
private TextView textView;
private EditText editText;
private Button applyTextButton;
private Button saveButton;
private Switch switch1;
public static final String SHARED_PREFS = "sharedPrefs";
public static final String TEXT = "text";
public static final String SWITCH1 = "switch1";
private String text;
private boolean switchOnOff;
//private String text;
//private boolean switchOnOff;
@Override
public View onCreateView(LayoutInflater inflater, ViewGroup container, Bundle savedInstanceState) {
View v = inflater.inflate(R.layout.fragment_second, container, false);
recyclerView = v.findViewById(R.id.recycler_view_products);
recyclerView.setLayoutManager(new LinearLayoutManager(getContext()));
productAdapter = new ProductAdapter(getContext(), products);
recyclerView.setAdapter(productAdapter);
productAdapter.setOnAddToCartClickListener(new ProductAdapter.OnAddToCartClickListener() {
@Override
public void onAddToCartClick(Product product) {
Toast.makeText(getActivity(),"Товар успешно добавлен!",Toast.LENGTH_SHORT).show();
}
});
viewPager = v.findViewById(R.id.view_pager);
SliderAdapter adapter = new SliderAdapter(getActivity(), imageUrls);
viewPager.setAdapter(adapter);
// Получаем оценки из SharedPreferences
SharedPreferences prefs = getContext().getSharedPreferences("MyPrefs_2", Context.MODE_PRIVATE);
rating1 = prefs.getFloat("rating1", 0.0f);
rating2 = prefs.getFloat("rating2", 0.0f);
rating3 = prefs.getFloat("rating3", 0.0f);
rating4 = prefs.getFloat("rating4", 0.0f);
rating5 = prefs.getFloat("rating5", 0.0f);
rating6 = prefs.getFloat("rating6", 0.0f);
rating7 = prefs.getFloat("rating7", 0.0f);
rating8 = prefs.getFloat("rating8", 0.0f);
rating9 = prefs.getFloat("rating9", 0.0f);
rating10 = prefs.getFloat("rating10", 0.0f);
// Устанавливаем оценки в соответствующие товары
products.get(0).setRating(rating1);
products.get(1).setRating(rating2);
products.get(2).setRating(rating3);
products.get(3).setRating(rating4);
products.get(4).setRating(rating5);
products.get(5).setRating(rating6);
products.get(6).setRating(rating7);
products.get(7).setRating(rating8);
products.get(8).setRating(rating9);
products.get(9).setRating(rating10);
products.get(0).setPrice(500.99);
products.get(1).setPrice(720.99);
products.get(2).setPrice(140.99);
products.get(3).setPrice(220.99);
products.get(4).setPrice(380.99);
products.get(5).setPrice(105.99);
products.get(6).setPrice(230.99);
products.get(7).setPrice(170.99);
products.get(8).setPrice(295.99);
products.get(9).setPrice(235.99);
viewPager = v.findViewById(R.id.view_pager);
// SliderAdapter_2 adapter = new SliderAdapter_2(getActivity(), imageUrls);
viewPager.setAdapter(adapter);
final Handler handler = new Handler();
final Runnable runnable = new Runnable() {
@Override
public void run() {
int currentItem = viewPager.getCurrentItem();
int totalItems = viewPager.getAdapter().getCount();
int nextItem = currentItem == totalItems - 1 ? 0 : currentItem + 1;
viewPager.setCurrentItem(nextItem);
handler.postDelayed(this, 3000);
}
};
handler.postDelayed(runnable, 3000);
return v;
}
private NotificationManager notificationManager;
private static final int NOTIFY_ID = 1;
private static final String CHANNEL_ID = "CHANNEL_ID";
Button b1;
@Override
public void onViewCreated(@NonNull View view, @Nullable Bundle savedInstanceState) {
super.onViewCreated(view, savedInstanceState);
initView(view);
b1 = view.findViewById(R.id.button);
notificationManager = (NotificationManager) getContext().getSystemService(Context.NOTIFICATION_SERVICE);
b1.setOnClickListener(new View.OnClickListener() {
@Override
public void onClick(View view) {
Intent intent = new Intent(getContext(), SecondFragment.class);
intent.addFlags(Intent.FLAG_ACTIVITY_CLEAR_TASK | Intent.FLAG_ACTIVITY_NEW_TASK);
PendingIntent pendingIntent = PendingIntent.getActivity(getContext(), 0, intent, PendingIntent.FLAG_UPDATE_CURRENT);
NotificationCompat.Builder notification =
new NotificationCompat.Builder(getContext().getApplicationContext(), CHANNEL_ID)
.setAutoCancel(false)
.setSmallIcon(R.drawable.ic_launcher_background)
.setWhen(System.currentTimeMillis())
.setContentIntent(pendingIntent)
.setContentTitle("zagolovok")
.setContentText("tekst")
.setPriority(NotificationCompat.PRIORITY_HIGH);
createChannelIfNeeded(notificationManager);
notificationManager = (NotificationManager) getContext().getSystemService(Context.NOTIFICATION_SERVICE);
notificationManager.notify(NOTIFY_ID, notification.build());
}
});
}
public void saveData() {
SharedPreferences sharedPreferences = getActivity().getSharedPreferences(SHARED_PREFS, MODE_PRIVATE);
SharedPreferences.Editor editor = sharedPreferences.edit();
editor.putString(TEXT, textView.getText().toString());
editor.putBoolean(SWITCH1, switch1.isChecked());
editor.apply();
Toast.makeText(getActivity(), "Data saved", Toast.LENGTH_SHORT).show();
}
public void loadData() {
SharedPreferences sharedPreferences = getActivity().getSharedPreferences(SHARED_PREFS, MODE_PRIVATE);
text = sharedPreferences.getString(TEXT, "");
switchOnOff = sharedPreferences.getBoolean(SWITCH1, false);
}
public void updateViews() {
//textView.setText(text);
// switch1.setChecked(switchOnOff);
}
private void initView(View view) {
Button btnClick = (Button) view.findViewById(R.id.btn_1_second_fragment);
btnClick.setOnClickListener(this);
Button btnClick2 = (Button) view.findViewById(R.id.btn_3_second_fragment);
btnClick2.setOnClickListener(this);
}
private SharedPreferences.Editor editor;
@Override
public void onCreate(@Nullable Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
editor = getContext().getSharedPreferences(MY_PREFS_NAME, Context.MODE_PRIVATE).edit();
Bundle bundle = this.getArguments();
if (bundle != null) {
int myInt = bundle.getInt("hello world", 123);
String strI = Integer.toString(myInt);
Toast.makeText(getActivity(), strI, Toast.LENGTH_SHORT).show();
}
}
@Override
public void onStart() {
super.onStart();
// Загружаем данные из SharedPreferences
loadData();
// Обновляем Views на экране
updateViews();
}
@Override
public void onResume() {
super.onResume();
}
@Override
public void onStop() {
super.onStop();
SharedPreferences.Editor editor = getContext().getSharedPreferences(MY_PREFS_NAME, Context.MODE_PRIVATE).edit();
editor.putFloat("rating1", products.get(0).getRating());
editor.putFloat("rating2", products.get(1).getRating());
editor.putFloat("rating3", products.get(2).getRating());
editor.putFloat("rating4", products.get(3).getRating());
editor.putFloat("rating5", products.get(4).getRating());
editor.putFloat("rating6", products.get(5).getRating());
editor.putFloat("rating7", products.get(6).getRating());
editor.putFloat("rating8", products.get(7).getRating());
editor.putFloat("rating9", products.get(8).getRating());
editor.putFloat("rating10", products.get(9).getRating());
editor.apply();
}
@Override
public void onDestroy() {
super.onDestroy();
}
private void changeFragment() {
getFragmentManager().beginTransaction().replace(R.id.nav_container, new FirstFragment()).addToBackStack(null).commit();
}
private void changeFragment2() {
getFragmentManager().beginTransaction().replace(R.id.nav_container, new ThirdFragment()).addToBackStack(null).commit();
}
@Override
public void onClick(View view) {
switch (view.getId()) {
case R.id.btn_1_second_fragment:
changeFragment();
break;
case R.id.btn_3_second_fragment:
changeFragment2();
break;
}
}
public static void createChannelIfNeeded(NotificationManager manager) {
if (Build.VERSION.SDK_INT >= Build.VERSION_CODES.O) {
NotificationChannel notificationChannel = new NotificationChannel(CHANNEL_ID, CHANNEL_ID, NotificationManager.IMPORTANCE_DEFAULT);
manager.createNotificationChannel(notificationChannel);
}
}
private List<Product> getProducts() {
List<Product> products = new ArrayList<>();
Product product1 = new Product("Product 11", "Description 11", R.drawable.food_1, 0.0f);
products.add(product1);
Product product2 = new Product("Product 12", "Description 12", R.drawable.food_2, 0.0f);
products.add(product2);
Product product3 = new Product("Product 13", "Description 13", R.drawable.food_1_3, 0.0f);
products.add(product3);
Product product4 = new Product("Product 14", "Description 14", R.drawable.food_1_2, 0.0f);
products.add(product4);
Product product5 = new Product("Product 15", "Description 15", R.drawable.food_3_4, 0.0f);
products.add(product5);
Product product6 = new Product("Product 16", "Description 16", R.drawable.food_1_4, 0.0f);
products.add(product6);
Product product7 = new Product("Product 17", "Description 17", R.drawable.food_1_1, 0.0f);
products.add(product7);
Product product8 = new Product("Product 18", "Description 18", R.drawable.food_1_2, 0.0f);
products.add(product8);
Product product9 = new Product("Product 19", "Description 19", R.drawable.food_3, 0.0f);
products.add(product9);
Product product10 = new Product("Product 20", "Description 20", R.drawable.food_3_4, 0.0f);
products.add(product10);
return products;
}
@Override
public void onPause() {
super.onPause();
// Сохраняем оценки в SharedPreferences
SharedPreferences.Editor editor = getContext().getSharedPreferences(MY_PREFS_NAME, Context.MODE_PRIVATE).edit();
editor.putFloat("rating1", products.get(0).getRating());
editor.putFloat("rating2", products.get(1).getRating());
editor.putFloat("rating3", products.get(2).getRating());
editor.putFloat("rating4", products.get(3).getRating());
editor.putFloat("rating5", products.get(4).getRating());
editor.putFloat("rating6", products.get(5).getRating());
editor.putFloat("rating7", products.get(6).getRating());
editor.putFloat("rating8", products.get(7).getRating());
editor.putFloat("rating9", products.get(8).getRating());
editor.putFloat("rating10", products.get(9).getRating());
editor.apply();
}
@Override
public void onSaveInstanceState(@NonNull Bundle outState) {
super.onSaveInstanceState(outState);
// Сохраняем оценки в Bundle
outState.putFloat("rating1", rating1);
outState.putFloat("rating2", rating2);
outState.putFloat("rating3", rating3);
outState.putFloat("rating4", rating4);
outState.putFloat("rating5", rating5);
outState.putFloat("rating6", rating6);
outState.putFloat("rating7", rating7);
outState.putFloat("rating8", rating8);
outState.putFloat("rating9", rating9);
outState.putFloat("rating10", rating10);
}
@Override
public void onViewStateRestored(@Nullable Bundle savedInstanceState) {
super.onViewStateRestored(savedInstanceState);
if (savedInstanceState != null) {
// Восстанавливаем оценки из Bundle
rating1 = savedInstanceState.getFloat("rating1");
rating2 = savedInstanceState.getFloat("rating2");
rating3 = savedInstanceState.getFloat("rating3");
rating4 = savedInstanceState.getFloat("rating4");
rating5 = savedInstanceState.getFloat("rating5");
rating6 = savedInstanceState.getFloat("rating6");
rating7 = savedInstanceState.getFloat("rating7");
rating8 = savedInstanceState.getFloat("rating8");
rating9 = savedInstanceState.getFloat("rating9");
rating10 = savedInstanceState.getFloat("rating10");
// Устанавливаем оценки в соответствующие товары
products.get(0).setRating(rating1);
products.get(1).setRating(rating2);
products.get(2).setRating(rating3);
products.get(3).setRating(rating4);
products.get(4).setRating(rating5);
products.get(5).setRating(rating6);
products.get(6).setRating(rating7);
products.get(7).setRating(rating8);
products.get(8).setRating(rating9);
products.get(9).setRating(rating10);
products.get(0).setRating(rating1);
products.get(1).setRating(rating2);
products.get(2).setRating(rating3);
products.get(3).setRating(rating4);
products.get(4).setRating(rating5);
products.get(5).setRating(rating6);
products.get(6).setRating(rating7);
products.get(7).setRating(rating8);
products.get(8).setRating(rating9);
products.get(9).setRating(rating10);
}
}
}
Воспользуйся этим классом : package com.example.myapp_2;
import android.content.Context;
import androidx.annotation.NonNull;
import androidx.work.Worker;
import androidx.work.WorkerParameters;
import com.example.myapp_2.List_1.Product;
import java.util.Collections;
import java.util.List;
public class SortWorker extends Worker {
private List<Product> products;
public SortWorker(@NonNull Context context, @NonNull WorkerParameters workerParams, List<Product> products) {
super(context, workerParams);
this.products = products;
}
@Override
public Result doWork() {
sortProducts();
return Result.success();
}
private void sortProducts() {
Collections.sort(products, (p1, p2) -> Double.compare(p1.getPrice(), p2.getPrice()) > 0 ? 1 : -1);
}
} (Отсортируй товары с помощью класса SortWorker )
|
b15a1cd5b40d53623ef355ad0e917697
|
{
"intermediate": 0.34006747603416443,
"beginner": 0.36487093567848206,
"expert": 0.2950616180896759
}
|
5,475
|
Joi.object({
occupation: Joi.string().allow(null),
declarations: Joi.object({
industryType: Joi.when('occupation', {
is: Joi.valid('housewife', 'unemployed'),
then: Joi.string().pattern(/^null$/).message('industryType cannot contains characters'),
otherwise: Joi.string().valid('Advertising').required(),
}),
})
})
|
4766d1436cbd50452ab95d67aa07338d
|
{
"intermediate": 0.3345617949962616,
"beginner": 0.35965976119041443,
"expert": 0.30577850341796875
}
|
5,476
|
Given this code
"import React, { useState } from "react";
const colors = ["red", "blue", "orange", "green", "purple", "black"];
function ComponentWithOverlays(props) {
const { imageUrl, coordinates } = props;
const [activeIndex, setActiveIndex] = useState(null);
const [shouldGrow, setShouldGrow] = useState(false);
const overlayClicked = (index) => {
setActiveIndex(index);
setShouldGrow(true);
};
const getOverlayStyle = (index) => {
const { x, y } = coordinates[index];
const active = activeIndex === index;
const grow = shouldGrow;
const overlayStyle = {
position: "absolute",
left: `${x}px`,
top: `${y}px`,
width: "30px",
height: "30px",
borderRadius: "50%",
backgroundColor: colors[index % colors.length],
zIndex: 1,
transition: "all 0.3s ease-in-out",
cursor: "pointer",
};
if (active || grow) {
const size = active ? 100 : 200;
const offset = (200 - 10) / 2;
overlayStyle.width = `${size}px`;
overlayStyle.height = `${size}px`;
overlayStyle.left = `${x - offset}px`;
overlayStyle.top = `${y - offset}px`;
}
return overlayStyle;
};
return (
<div
style={{
backgroundImage: `url(${imageUrl})`,
backgroundPosition: "center",
backgroundSize: "cover",
height: "500px",
position: "relative",
}}
>
{Array.isArray(coordinates) &&
coordinates.map((_, index) => (
<div key={index} style={getOverlayStyle(index)} onClick={() => overlayClicked(index)} />
))}
</div>
);
}
export default ComponentWithOverlays;"
Modify it so that all overlays grow when any of the overlays are clicked
|
9e6eb64c414bacec1730ba6a7b746709
|
{
"intermediate": 0.4406268000602722,
"beginner": 0.3099345266819,
"expert": 0.24943870306015015
}
|
5,477
|
Вот код , отсортируй список товаров в SecondFragment : @Override
public View onCreateView(LayoutInflater inflater, ViewGroup container, Bundle savedInstanceState) {
View v = inflater.inflate(R.layout.fragment_second, container, false);
ProductAdapter adapter_2 = new ProductAdapter();
SortWorker sortWorker = new SortWorker(this, new WorkerParameters.Builder().build(), adapter_2);
sortWorker.doWork();package com.example.myapp_2;
import android.content.Context;
import androidx.annotation.NonNull;
import androidx.work.Worker;
import androidx.work.WorkerParameters;
import com.example.myapp_2.List_1.Product;
import com.example.myapp_2.List_1.ProductAdapter;
import java.util.Collections;
import java.util.List;
public class SortWorker extends Worker {
private ProductAdapter adapter;
public SortWorker(@NonNull Context context, @NonNull WorkerParameters workerParams, ProductAdapter adapter) {
super(context, workerParams);
this.adapter = adapter;
}
@Override
public Result doWork() {
sortProducts();
return Result.success();
}
private void sortProducts() {
List<Product> products = adapter.getProducts();
Collections.sort(products, (p1, p2) -> Double.compare(p1.getPrice(), p2.getPrice()) > 0 ? 1 : -1);
adapter.notifyDataSetChanged();
}
}package com.example.myapp_2.List_1;
public class Product {
private String name;
private String description;
private int imageResource;
private float rating;
private double price;
public Product(String name, String description, int imageResource, float rating, double price) {
this.name = name;
this.description = description;
this.imageResource = imageResource;
this.rating = rating;
this.price = price;
}
public Product(String name, String description, int imageResource, double price) {
this.name = name;
this.description = description;
this.imageResource = imageResource;
this.rating = 0.0f;
this.price = price;
}
public String getName() {
return name;
}
public String getDescription() {
return description;
}
public int getImageResource() {
return imageResource;
}
public float getRating() {
return rating;
}
public void setRating(float rating) {
this.rating = rating;
}
public double getPrice() {
return price;
}
public void setPrice(double price) {
this.price = price;
}
} (Исправь методы при необходимости и помни что твоя задача используя эти класса отсортировать по цене товары в SecondFragment)
|
71a54b89167605e811a674f8dc2e85ed
|
{
"intermediate": 0.2666413486003876,
"beginner": 0.5459108948707581,
"expert": 0.18744778633117676
}
|
5,478
|
tell me the most popular programming language in 2023
|
c1e40a6d70874993eb3f0476f2c6a6da
|
{
"intermediate": 0.22048905491828918,
"beginner": 0.3227182626724243,
"expert": 0.4567926228046417
}
|
5,479
|
// Get the user input for trade size
tradeSize = input.float(title='Trade Size', defval=0.2, minval=0.01, step = 0.01)
// Calculate stop loss and take profit levels based on trade size
stopLoss = tradeSize * 0.2
takeProfit20 = tradeSize * 0.2
takeProfit40 = tradeSize * 0.4
takeProfit60 = tradeSize * 0.6
takeProfit80 = tradeSize * 0.8
takeProfit100 = tradeSize
takeProfit120 = tradeSize * 1.2
takeProfit140 = tradeSize * 1.4
// Define long and short conditions
longCondition = (ipush==fib1)
shortCondition = (ipush==fib0)
// Enter long trade when long condition is met
if (longCondition)
strategy.entry('Long Entry', strategy.long, qty=tradeSize, stop=stopLoss, limit=(close + takeProfit20))
// Enter short trade when short condition is met
if (shortCondition)
strategy.entry('Short Entry', strategy.short, qty=tradeSize, stop=stopLoss, limit=(close - takeProfit20))
// Exit trade at take profit and adjust stop loss levels
if (strategy.position_size > 0)
if (strategy.position_avg_price + takeProfit20 <= close)
strategy.exit('Take Profit 20', qty=tradeSize, limit=(close - takeProfit40), stop=(strategy.position_avg_price + stopLoss))
else
strategy.exit('Stop Loss 20', qty=tradeSize, stop=(strategy.position_avg_price - stopLoss))
//
if(strategy.position_size > 0)
if (strategy.position_avg_price + takeProfit40 <= close)
strategy.exit('Take Profit 40', qty=tradeSize, limit=(close - takeProfit60), stop=(strategy.position_avg_price + takeProfit20))
else
strategy.exit('Stop Loss 40', qty=tradeSize, stop=(strategy.position_avg_price - takeProfit20))
//
if (strategy.position_size > 0)
if (strategy.position_avg_price + takeProfit60 <= close)
strategy.exit('Take Profit 60', qty=tradeSize, limit=(close - takeProfit80), stop=(strategy.position_avg_price + takeProfit40))
else
strategy.exit('Stop Loss 60', qty=tradeSize, stop=(strategy.position_avg_price - takeProfit40))
//
if (strategy.position_size > 0)
if (strategy.position_avg_price + takeProfit80 <= close)
strategy.exit('Take Profit 80', qty=tradeSize, limit=(close - takeProfit100), stop=(strategy.position_avg_price + takeProfit60))
else
strategy.exit('Stop Loss 80', qty=tradeSize, stop=(strategy.position_avg_price - takeProfit60))
//
if (strategy.position_size > 0)
if (strategy.position_avg_price + takeProfit100 <= close)
strategy.exit('Take Profit 100', qty=tradeSize, limit=(close - takeProfit120), stop=(strategy.position_avg_price + takeProfit80))
else
strategy.exit('Stop Loss 100', qty=tradeSize, stop=(strategy.position_avg_price - takeProfit80))
//
if (strategy.position_size > 0)
if (strategy.position_avg_price + takeProfit120 <= close)
strategy.exit('Take Profit 120', qty=tradeSize, limit=(close - takeProfit140), stop=(strategy.position_avg_price + takeProfit100))
else
strategy.exit('Stop Loss 120', qty=tradeSize, stop=(strategy.position_avg_price - takeProfit100))
|
ebe81b32e255ba9f0bf7ecc0169f8a0e
|
{
"intermediate": 0.24337519705295563,
"beginner": 0.5153504610061646,
"expert": 0.24127428233623505
}
|
5,480
|
<script type="text/javascript">
Dropzone.autoDiscover = false;
$(document).ready(function() {
// Initialize the dropzone element
$("#my-dropzone").dropzone({
url: "/localization/multi-local-from-file",
addRemoveLinks: true
paramName: "data",
maxFiles: 1,
maxFilesize: 10, // Maximum filesize in MB
acceptedFiles: ".arb",
init: function() {
this.on("success", function(file, response) {
// On successful translation, enable the download button and change the download link
$("#download-multiple").prop("href", URL.createObjectURL(response));
$("#download-multiple").prop("disabled", false);
});
}
});
});
</script>
|
548c90bc9cfd76bad4e82882fa076252
|
{
"intermediate": 0.3616120517253876,
"beginner": 0.4476749300956726,
"expert": 0.19071301817893982
}
|
5,481
|
c# how to cast a parent to childobject
|
026178a6a2b9bb4c5399fa935513b47a
|
{
"intermediate": 0.47432589530944824,
"beginner": 0.23599863052368164,
"expert": 0.2896755039691925
}
|
5,482
|
write a freshdesk custom app which shows a google map with a marker and a search box on top. upon typing in the search box. it makes a custom api call and list down address suggestions from the custom api response. Then on clicking the address from the list, it makes a function call to change the marker's position to that address's lat, long
|
c6faf8c4a88fdd28c2d0f3b62b5be94b
|
{
"intermediate": 0.4321865141391754,
"beginner": 0.22860196232795715,
"expert": 0.33921152353286743
}
|
5,483
|
how to show a toast in compose
|
b16a961a58e6d73d38a0a80fcda7e375
|
{
"intermediate": 0.405451238155365,
"beginner": 0.3488226532936096,
"expert": 0.24572618305683136
}
|
5,484
|
Cannot resolve symbol 'Builder' : package com.example.myapp_2.UI.view.fragments;
import static android.content.Context.MODE_PRIVATE;
import android.app.NotificationChannel;
import android.app.NotificationManager;
import android.app.PendingIntent;
import android.content.Context;
import android.content.Intent;
import android.content.SharedPreferences;
import android.os.Build;
import android.os.Bundle;
import android.os.Handler;
import android.view.LayoutInflater;
import android.view.View;
import android.view.ViewGroup;
import android.widget.Button;
import android.widget.EditText;
import android.widget.Switch;
import android.widget.TextView;
import android.widget.Toast;
import androidx.annotation.NonNull;
import androidx.annotation.Nullable;
import androidx.core.app.NotificationCompat;
import androidx.fragment.app.Fragment;
import androidx.recyclerview.widget.LinearLayoutManager;
import androidx.recyclerview.widget.RecyclerView;
import androidx.viewpager.widget.ViewPager;
import androidx.work.WorkerParameters;
import com.example.myapp_2.List_1.Product;
import com.example.myapp_2.List_1.ProductAdapter;
import com.example.myapp_2.R;
import com.example.myapp_2.SortWorker;
import com.example.myapp_2.UI.view.adapters.SliderAdapter;
import java.util.ArrayList;
import java.util.List;
//import androidx.work.WorkerParameters.Builder;
public class SecondFragment extends Fragment implements View.OnClickListener {
private static final String MY_PREFS_NAME = "MyPrefs_2";
private RecyclerView recyclerView;
private ProductAdapter productAdapter;
private List<Product> products = getProducts();
private float rating1 = 0.0f;
private float rating2 = 0.0f;
private float rating3 = 0.0f;
private float rating4 = 0.0f;
private float rating5 = 0.0f;
private float rating6 = 0.0f;
private float rating7 = 0.0f;
private float rating8 = 0.0f;
private float rating9 = 0.0f;
private float rating10 = 0.0f;
//private static final String MY_PREFS_NAME = "MyPrefs";
public SecondFragment() {
}
private ViewPager viewPager;
private int[] imageUrls = {R.drawable.second_1, R.drawable.second_3, R.drawable.second_4, R.drawable.second_5, R.drawable.second_22};
private TextView textView;
private EditText editText;
private Button applyTextButton;
private Button saveButton;
private Switch switch1;
public static final String SHARED_PREFS = "sharedPrefs";
public static final String TEXT = "text";
public static final String SWITCH1 = "switch1";
private String text;
private boolean switchOnOff;
//private String text;
//private boolean switchOnOff;
@Override
public View onCreateView(LayoutInflater inflater, ViewGroup container, Bundle savedInstanceState) {
View v = inflater.inflate(R.layout.fragment_second, container, false);
// private RecyclerView recyclerView;
// private ProductAdapter productAdapter;
// private List<Product> products = getProducts();
// создаем объект SortWorker и вызываем метод сортировки
SortWorker sortWorker = new SortWorker(getActivity(), new WorkerParameters.Builder().build(), productAdapter);
sortWorker.sortProducts();
// устанавливаем адаптер для отображения списка товаров
RecyclerView recyclerView = v.findViewById(R.id.recycler_view_products);
recyclerView.setAdapter(productAdapter);
recyclerView.setLayoutManager(new LinearLayoutManager(getActivity()));
recyclerView = v.findViewById(R.id.recycler_view_products);
recyclerView.setLayoutManager(new LinearLayoutManager(getContext()));
productAdapter = new ProductAdapter(getContext(), products);
recyclerView.setAdapter(productAdapter);
productAdapter.setOnAddToCartClickListener(new ProductAdapter.OnAddToCartClickListener() {
@Override
public void onAddToCartClick(Product product) {
Toast.makeText(getActivity(),"Товар успешно добавлен!",Toast.LENGTH_SHORT).show();
}
});
viewPager = v.findViewById(R.id.view_pager);
SliderAdapter adapter = new SliderAdapter(getActivity(), imageUrls);
viewPager.setAdapter(adapter);
// Получаем оценки из SharedPreferences
SharedPreferences prefs = getContext().getSharedPreferences("MyPrefs_2", Context.MODE_PRIVATE);
rating1 = prefs.getFloat("rating1", 0.0f);
rating2 = prefs.getFloat("rating2", 0.0f);
rating3 = prefs.getFloat("rating3", 0.0f);
rating4 = prefs.getFloat("rating4", 0.0f);
rating5 = prefs.getFloat("rating5", 0.0f);
rating6 = prefs.getFloat("rating6", 0.0f);
rating7 = prefs.getFloat("rating7", 0.0f);
rating8 = prefs.getFloat("rating8", 0.0f);
rating9 = prefs.getFloat("rating9", 0.0f);
rating10 = prefs.getFloat("rating10", 0.0f);
// Устанавливаем оценки в соответствующие товары
products.get(0).setRating(rating1);
products.get(1).setRating(rating2);
products.get(2).setRating(rating3);
products.get(3).setRating(rating4);
products.get(4).setRating(rating5);
products.get(5).setRating(rating6);
products.get(6).setRating(rating7);
products.get(7).setRating(rating8);
products.get(8).setRating(rating9);
products.get(9).setRating(rating10);
products.get(0).setPrice(500.99);
products.get(1).setPrice(720.99);
products.get(2).setPrice(140.99);
products.get(3).setPrice(220.99);
products.get(4).setPrice(380.99);
products.get(5).setPrice(105.99);
products.get(6).setPrice(230.99);
products.get(7).setPrice(170.99);
products.get(8).setPrice(295.99);
products.get(9).setPrice(235.99);
viewPager = v.findViewById(R.id.view_pager);
// SliderAdapter_2 adapter = new SliderAdapter_2(getActivity(), imageUrls);
viewPager.setAdapter(adapter);
final Handler handler = new Handler();
final Runnable runnable = new Runnable() {
@Override
public void run() {
int currentItem = viewPager.getCurrentItem();
int totalItems = viewPager.getAdapter().getCount();
int nextItem = currentItem == totalItems - 1 ? 0 : currentItem + 1;
viewPager.setCurrentItem(nextItem);
handler.postDelayed(this, 3000);
}
};
handler.postDelayed(runnable, 3000);
return v;
}
private NotificationManager notificationManager;
private static final int NOTIFY_ID = 1;
private static final String CHANNEL_ID = "CHANNEL_ID";
Button b1;
@Override
public void onViewCreated(@NonNull View view, @Nullable Bundle savedInstanceState) {
super.onViewCreated(view, savedInstanceState);
initView(view);
b1 = view.findViewById(R.id.button);
notificationManager = (NotificationManager) getContext().getSystemService(Context.NOTIFICATION_SERVICE);
b1.setOnClickListener(new View.OnClickListener() {
@Override
public void onClick(View view) {
Intent intent = new Intent(getContext(), SecondFragment.class);
intent.addFlags(Intent.FLAG_ACTIVITY_CLEAR_TASK | Intent.FLAG_ACTIVITY_NEW_TASK);
PendingIntent pendingIntent = PendingIntent.getActivity(getContext(), 0, intent, PendingIntent.FLAG_UPDATE_CURRENT);
NotificationCompat.Builder notification =
new NotificationCompat.Builder(getContext().getApplicationContext(), CHANNEL_ID)
.setAutoCancel(false)
.setSmallIcon(R.drawable.ic_launcher_background)
.setWhen(System.currentTimeMillis())
.setContentIntent(pendingIntent)
.setContentTitle("zagolovok")
.setContentText("tekst")
.setPriority(NotificationCompat.PRIORITY_HIGH);
createChannelIfNeeded(notificationManager);
notificationManager = (NotificationManager) getContext().getSystemService(Context.NOTIFICATION_SERVICE);
notificationManager.notify(NOTIFY_ID, notification.build());
}
});
}
public void saveData() {
SharedPreferences sharedPreferences = getActivity().getSharedPreferences(SHARED_PREFS, MODE_PRIVATE);
SharedPreferences.Editor editor = sharedPreferences.edit();
editor.putString(TEXT, textView.getText().toString());
editor.putBoolean(SWITCH1, switch1.isChecked());
editor.apply();
Toast.makeText(getActivity(), "Data saved", Toast.LENGTH_SHORT).show();
}
public void loadData() {
SharedPreferences sharedPreferences = getActivity().getSharedPreferences(SHARED_PREFS, MODE_PRIVATE);
text = sharedPreferences.getString(TEXT, "");
switchOnOff = sharedPreferences.getBoolean(SWITCH1, false);
}
public void updateViews() {
//textView.setText(text);
// switch1.setChecked(switchOnOff);
}
private void initView(View view) {
Button btnClick = (Button) view.findViewById(R.id.btn_1_second_fragment);
btnClick.setOnClickListener(this);
Button btnClick2 = (Button) view.findViewById(R.id.btn_3_second_fragment);
btnClick2.setOnClickListener(this);
}
private SharedPreferences.Editor editor;
@Override
public void onCreate(@Nullable Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
editor = getContext().getSharedPreferences(MY_PREFS_NAME, Context.MODE_PRIVATE).edit();
Bundle bundle = this.getArguments();
if (bundle != null) {
int myInt = bundle.getInt("hello world", 123);
String strI = Integer.toString(myInt);
Toast.makeText(getActivity(), strI, Toast.LENGTH_SHORT).show();
}
}
@Override
public void onStart() {
super.onStart();
// Загружаем данные из SharedPreferences
loadData();
// Обновляем Views на экране
updateViews();
}
@Override
public void onResume() {
super.onResume();
}
@Override
public void onStop() {
super.onStop();
SharedPreferences.Editor editor = getContext().getSharedPreferences(MY_PREFS_NAME, Context.MODE_PRIVATE).edit();
editor.putFloat("rating1", products.get(0).getRating());
editor.putFloat("rating2", products.get(1).getRating());
editor.putFloat("rating3", products.get(2).getRating());
editor.putFloat("rating4", products.get(3).getRating());
editor.putFloat("rating5", products.get(4).getRating());
editor.putFloat("rating6", products.get(5).getRating());
editor.putFloat("rating7", products.get(6).getRating());
editor.putFloat("rating8", products.get(7).getRating());
editor.putFloat("rating9", products.get(8).getRating());
editor.putFloat("rating10", products.get(9).getRating());
editor.apply();
}
@Override
public void onDestroy() {
super.onDestroy();
}
private void changeFragment() {
getFragmentManager().beginTransaction().replace(R.id.nav_container, new FirstFragment()).addToBackStack(null).commit();
}
private void changeFragment2() {
getFragmentManager().beginTransaction().replace(R.id.nav_container, new ThirdFragment()).addToBackStack(null).commit();
}
@Override
public void onClick(View view) {
switch (view.getId()) {
case R.id.btn_1_second_fragment:
changeFragment();
break;
case R.id.btn_3_second_fragment:
changeFragment2();
break;
}
}
public static void createChannelIfNeeded(NotificationManager manager) {
if (Build.VERSION.SDK_INT >= Build.VERSION_CODES.O) {
NotificationChannel notificationChannel = new NotificationChannel(CHANNEL_ID, CHANNEL_ID, NotificationManager.IMPORTANCE_DEFAULT);
manager.createNotificationChannel(notificationChannel);
}
}
@Override
public void onPause() {
super.onPause();
// Сохраняем оценки в SharedPreferences
SharedPreferences.Editor editor = getContext().getSharedPreferences(MY_PREFS_NAME, Context.MODE_PRIVATE).edit();
editor.putFloat("rating1", products.get(0).getRating());
editor.putFloat("rating2", products.get(1).getRating());
editor.putFloat("rating3", products.get(2).getRating());
editor.putFloat("rating4", products.get(3).getRating());
editor.putFloat("rating5", products.get(4).getRating());
editor.putFloat("rating6", products.get(5).getRating());
editor.putFloat("rating7", products.get(6).getRating());
editor.putFloat("rating8", products.get(7).getRating());
editor.putFloat("rating9", products.get(8).getRating());
editor.putFloat("rating10", products.get(9).getRating());
editor.apply();
}
@Override
public void onSaveInstanceState(@NonNull Bundle outState) {
super.onSaveInstanceState(outState);
// Сохраняем оценки в Bundle
outState.putFloat("rating1", rating1);
outState.putFloat("rating2", rating2);
outState.putFloat("rating3", rating3);
outState.putFloat("rating4", rating4);
outState.putFloat("rating5", rating5);
outState.putFloat("rating6", rating6);
outState.putFloat("rating7", rating7);
outState.putFloat("rating8", rating8);
outState.putFloat("rating9", rating9);
outState.putFloat("rating10", rating10);
}
@Override
public void onViewStateRestored(@Nullable Bundle savedInstanceState) {
super.onViewStateRestored(savedInstanceState);
if (savedInstanceState != null) {
// Восстанавливаем оценки из Bundle
rating1 = savedInstanceState.getFloat("rating1");
rating2 = savedInstanceState.getFloat("rating2");
rating3 = savedInstanceState.getFloat("rating3");
rating4 = savedInstanceState.getFloat("rating4");
rating5 = savedInstanceState.getFloat("rating5");
rating6 = savedInstanceState.getFloat("rating6");
rating7 = savedInstanceState.getFloat("rating7");
rating8 = savedInstanceState.getFloat("rating8");
rating9 = savedInstanceState.getFloat("rating9");
rating10 = savedInstanceState.getFloat("rating10");
// Устанавливаем оценки в соответствующие товары
products.get(0).setRating(rating1);
products.get(1).setRating(rating2);
products.get(2).setRating(rating3);
products.get(3).setRating(rating4);
products.get(4).setRating(rating5);
products.get(5).setRating(rating6);
products.get(6).setRating(rating7);
products.get(7).setRating(rating8);
products.get(8).setRating(rating9);
products.get(9).setRating(rating10);
products.get(0).setRating(rating1);
products.get(1).setRating(rating2);
products.get(2).setRating(rating3);
products.get(3).setRating(rating4);
products.get(4).setRating(rating5);
products.get(5).setRating(rating6);
products.get(6).setRating(rating7);
products.get(7).setRating(rating8);
products.get(8).setRating(rating9);
products.get(9).setRating(rating10);
}
}
private List<Product> getProducts() {
List<Product> products = new ArrayList<>();
Product product1 = new Product("Product 11", "Description 11", R.drawable.food_1, 0.0f);
products.add(product1);
Product product2 = new Product("Product 12", "Description 12", R.drawable.food_2, 0.0f);
products.add(product2);
Product product3 = new Product("Product 13", "Description 13", R.drawable.food_1_3, 0.0f);
products.add(product3);
Product product4 = new Product("Product 14", "Description 14", R.drawable.food_1_2, 0.0f);
products.add(product4);
Product product5 = new Product("Product 15", "Description 15", R.drawable.food_3_4, 0.0f);
products.add(product5);
Product product6 = new Product("Product 16", "Description 16", R.drawable.food_1_4, 0.0f);
products.add(product6);
Product product7 = new Product("Product 17", "Description 17", R.drawable.food_1_1, 0.0f);
products.add(product7);
Product product8 = new Product("Product 18", "Description 18", R.drawable.food_1_2, 0.0f);
products.add(product8);
Product product9 = new Product("Product 19", "Description 19", R.drawable.food_3, 0.0f);
products.add(product9);
Product product10 = new Product("Product 20", "Description 20", R.drawable.food_3_4, 0.0f);
products.add(product10);
return products;
}
}
|
94a94986bb549cbc2c5c6cad783346cd
|
{
"intermediate": 0.27253803610801697,
"beginner": 0.4675254821777344,
"expert": 0.25993651151657104
}
|
5,485
|
u know how :deep works in vue 3?
|
a8d530afff2ee61a2999bab091bb4512
|
{
"intermediate": 0.30447787046432495,
"beginner": 0.08015616238117218,
"expert": 0.6153659224510193
}
|
5,486
|
Cannot resolve symbol 'Builder' : package com.example.myapp_2.UI.view.fragments;
import static android.content.Context.MODE_PRIVATE;
import android.app.NotificationChannel;
import android.app.NotificationManager;
import android.app.PendingIntent;
import android.content.Context;
import android.content.Intent;
import android.content.SharedPreferences;
import android.os.Build;
import android.os.Bundle;
import android.os.Handler;
import android.view.LayoutInflater;
import android.view.View;
import android.view.ViewGroup;
import android.widget.Button;
import android.widget.EditText;
import android.widget.Switch;
import android.widget.TextView;
import android.widget.Toast;
import androidx.annotation.NonNull;
import androidx.annotation.Nullable;
import androidx.core.app.NotificationCompat;
import androidx.fragment.app.Fragment;
import androidx.recyclerview.widget.LinearLayoutManager;
import androidx.recyclerview.widget.RecyclerView;
import androidx.viewpager.widget.ViewPager;
import androidx.work.WorkerParameters;
import com.example.myapp_2.List_1.Product;
import com.example.myapp_2.List_1.ProductAdapter;
import com.example.myapp_2.R;
import com.example.myapp_2.SortWorker;
import com.example.myapp_2.UI.view.adapters.SliderAdapter;
import java.util.ArrayList;
import java.util.List;
//import androidx.work.WorkerParameters.Builder;
import androidx.core.app.NotificationCompat.Builder;
public class SecondFragment extends Fragment implements View.OnClickListener {
private static final String MY_PREFS_NAME = "MyPrefs_2";
private RecyclerView recyclerView;
private ProductAdapter productAdapter;
private List<Product> products = getProducts();
private float rating1 = 0.0f;
private float rating2 = 0.0f;
private float rating3 = 0.0f;
private float rating4 = 0.0f;
private float rating5 = 0.0f;
private float rating6 = 0.0f;
private float rating7 = 0.0f;
private float rating8 = 0.0f;
private float rating9 = 0.0f;
private float rating10 = 0.0f;
//private static final String MY_PREFS_NAME = "MyPrefs";
public SecondFragment() {
}
private ViewPager viewPager;
private int[] imageUrls = {R.drawable.second_1, R.drawable.second_3, R.drawable.second_4, R.drawable.second_5, R.drawable.second_22};
private TextView textView;
private EditText editText;
private Button applyTextButton;
private Button saveButton;
private Switch switch1;
public static final String SHARED_PREFS = "sharedPrefs";
public static final String TEXT = "text";
public static final String SWITCH1 = "switch1";
private String text;
private boolean switchOnOff;
//private String text;
//private boolean switchOnOff;
@Override
public View onCreateView(LayoutInflater inflater, ViewGroup container, Bundle savedInstanceState) {
View v = inflater.inflate(R.layout.fragment_second, container, false);
// private RecyclerView recyclerView;
// private ProductAdapter productAdapter;
// private List<Product> products = getProducts();
// создаем объект SortWorker и вызываем метод сортировки
SortWorker sortWorker = new SortWorker(getActivity(), new WorkerParameters.Builder().build(), productAdapter);
sortWorker.sortProducts();
// устанавливаем адаптер для отображения списка товаров
RecyclerView recyclerView = v.findViewById(R.id.recycler_view_products);
recyclerView.setAdapter(productAdapter);
recyclerView.setLayoutManager(new LinearLayoutManager(getActivity()));
recyclerView = v.findViewById(R.id.recycler_view_products);
recyclerView.setLayoutManager(new LinearLayoutManager(getContext()));
productAdapter = new ProductAdapter(getContext(), products);
recyclerView.setAdapter(productAdapter);
productAdapter.setOnAddToCartClickListener(new ProductAdapter.OnAddToCartClickListener() {
@Override
public void onAddToCartClick(Product product) {
Toast.makeText(getActivity(),"Товар успешно добавлен!",Toast.LENGTH_SHORT).show();
}
});
viewPager = v.findViewById(R.id.view_pager);
SliderAdapter adapter = new SliderAdapter(getActivity(), imageUrls);
viewPager.setAdapter(adapter);
// Получаем оценки из SharedPreferences
SharedPreferences prefs = getContext().getSharedPreferences("MyPrefs_2", Context.MODE_PRIVATE);
rating1 = prefs.getFloat("rating1", 0.0f);
rating2 = prefs.getFloat("rating2", 0.0f);
rating3 = prefs.getFloat("rating3", 0.0f);
rating4 = prefs.getFloat("rating4", 0.0f);
rating5 = prefs.getFloat("rating5", 0.0f);
rating6 = prefs.getFloat("rating6", 0.0f);
rating7 = prefs.getFloat("rating7", 0.0f);
rating8 = prefs.getFloat("rating8", 0.0f);
rating9 = prefs.getFloat("rating9", 0.0f);
rating10 = prefs.getFloat("rating10", 0.0f);
// Устанавливаем оценки в соответствующие товары
products.get(0).setRating(rating1);
products.get(1).setRating(rating2);
products.get(2).setRating(rating3);
products.get(3).setRating(rating4);
products.get(4).setRating(rating5);
products.get(5).setRating(rating6);
products.get(6).setRating(rating7);
products.get(7).setRating(rating8);
products.get(8).setRating(rating9);
products.get(9).setRating(rating10);
products.get(0).setPrice(500.99);
products.get(1).setPrice(720.99);
products.get(2).setPrice(140.99);
products.get(3).setPrice(220.99);
products.get(4).setPrice(380.99);
products.get(5).setPrice(105.99);
products.get(6).setPrice(230.99);
products.get(7).setPrice(170.99);
products.get(8).setPrice(295.99);
products.get(9).setPrice(235.99);
viewPager = v.findViewById(R.id.view_pager);
// SliderAdapter_2 adapter = new SliderAdapter_2(getActivity(), imageUrls);
viewPager.setAdapter(adapter);
final Handler handler = new Handler();
final Runnable runnable = new Runnable() {
@Override
public void run() {
int currentItem = viewPager.getCurrentItem();
int totalItems = viewPager.getAdapter().getCount();
int nextItem = currentItem == totalItems - 1 ? 0 : currentItem + 1;
viewPager.setCurrentItem(nextItem);
handler.postDelayed(this, 3000);
}
};
handler.postDelayed(runnable, 3000);
return v;
}
private NotificationManager notificationManager;
private static final int NOTIFY_ID = 1;
private static final String CHANNEL_ID = "CHANNEL_ID";
Button b1;
@Override
public void onViewCreated(@NonNull View view, @Nullable Bundle savedInstanceState) {
super.onViewCreated(view, savedInstanceState);
initView(view);
b1 = view.findViewById(R.id.button);
notificationManager = (NotificationManager) getContext().getSystemService(Context.NOTIFICATION_SERVICE);
b1.setOnClickListener(new View.OnClickListener() {
@Override
public void onClick(View view) {
Intent intent = new Intent(getContext(), SecondFragment.class);
intent.addFlags(Intent.FLAG_ACTIVITY_CLEAR_TASK | Intent.FLAG_ACTIVITY_NEW_TASK);
PendingIntent pendingIntent = PendingIntent.getActivity(getContext(), 0, intent, PendingIntent.FLAG_UPDATE_CURRENT);
NotificationCompat.Builder notification =
new NotificationCompat.Builder(getContext().getApplicationContext(), CHANNEL_ID)
.setAutoCancel(false)
.setSmallIcon(R.drawable.ic_launcher_background)
.setWhen(System.currentTimeMillis())
.setContentIntent(pendingIntent)
.setContentTitle("zagolovok")
.setContentText("tekst")
.setPriority(NotificationCompat.PRIORITY_HIGH);
createChannelIfNeeded(notificationManager);
notificationManager = (NotificationManager) getContext().getSystemService(Context.NOTIFICATION_SERVICE);
notificationManager.notify(NOTIFY_ID, notification.build());
}
});
}
public void saveData() {
SharedPreferences sharedPreferences = getActivity().getSharedPreferences(SHARED_PREFS, MODE_PRIVATE);
SharedPreferences.Editor editor = sharedPreferences.edit();
editor.putString(TEXT, textView.getText().toString());
editor.putBoolean(SWITCH1, switch1.isChecked());
editor.apply();
Toast.makeText(getActivity(), "Data saved", Toast.LENGTH_SHORT).show();
}
public void loadData() {
SharedPreferences sharedPreferences = getActivity().getSharedPreferences(SHARED_PREFS, MODE_PRIVATE);
text = sharedPreferences.getString(TEXT, "");
switchOnOff = sharedPreferences.getBoolean(SWITCH1, false);
}
public void updateViews() {
//textView.setText(text);
// switch1.setChecked(switchOnOff);
}
private void initView(View view) {
Button btnClick = (Button) view.findViewById(R.id.btn_1_second_fragment);
btnClick.setOnClickListener(this);
Button btnClick2 = (Button) view.findViewById(R.id.btn_3_second_fragment);
btnClick2.setOnClickListener(this);
}
private SharedPreferences.Editor editor;
@Override
public void onCreate(@Nullable Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
editor = getContext().getSharedPreferences(MY_PREFS_NAME, Context.MODE_PRIVATE).edit();
Bundle bundle = this.getArguments();
if (bundle != null) {
int myInt = bundle.getInt("hello world", 123);
String strI = Integer.toString(myInt);
Toast.makeText(getActivity(), strI, Toast.LENGTH_SHORT).show();
}
}
@Override
public void onStart() {
super.onStart();
// Загружаем данные из SharedPreferences
loadData();
// Обновляем Views на экране
updateViews();
}
@Override
public void onResume() {
super.onResume();
}
@Override
public void onStop() {
super.onStop();
SharedPreferences.Editor editor = getContext().getSharedPreferences(MY_PREFS_NAME, Context.MODE_PRIVATE).edit();
editor.putFloat("rating1", products.get(0).getRating());
editor.putFloat("rating2", products.get(1).getRating());
editor.putFloat("rating3", products.get(2).getRating());
editor.putFloat("rating4", products.get(3).getRating());
editor.putFloat("rating5", products.get(4).getRating());
editor.putFloat("rating6", products.get(5).getRating());
editor.putFloat("rating7", products.get(6).getRating());
editor.putFloat("rating8", products.get(7).getRating());
editor.putFloat("rating9", products.get(8).getRating());
editor.putFloat("rating10", products.get(9).getRating());
editor.apply();
}
@Override
public void onDestroy() {
super.onDestroy();
}
private void changeFragment() {
getFragmentManager().beginTransaction().replace(R.id.nav_container, new FirstFragment()).addToBackStack(null).commit();
}
private void changeFragment2() {
getFragmentManager().beginTransaction().replace(R.id.nav_container, new ThirdFragment()).addToBackStack(null).commit();
}
@Override
public void onClick(View view) {
switch (view.getId()) {
case R.id.btn_1_second_fragment:
changeFragment();
break;
case R.id.btn_3_second_fragment:
changeFragment2();
break;
}
}
public static void createChannelIfNeeded(NotificationManager manager) {
if (Build.VERSION.SDK_INT >= Build.VERSION_CODES.O) {
NotificationChannel notificationChannel = new NotificationChannel(CHANNEL_ID, CHANNEL_ID, NotificationManager.IMPORTANCE_DEFAULT);
manager.createNotificationChannel(notificationChannel);
}
}
@Override
public void onPause() {
super.onPause();
// Сохраняем оценки в SharedPreferences
SharedPreferences.Editor editor = getContext().getSharedPreferences(MY_PREFS_NAME, Context.MODE_PRIVATE).edit();
editor.putFloat("rating1", products.get(0).getRating());
editor.putFloat("rating2", products.get(1).getRating());
editor.putFloat("rating3", products.get(2).getRating());
editor.putFloat("rating4", products.get(3).getRating());
editor.putFloat("rating5", products.get(4).getRating());
editor.putFloat("rating6", products.get(5).getRating());
editor.putFloat("rating7", products.get(6).getRating());
editor.putFloat("rating8", products.get(7).getRating());
editor.putFloat("rating9", products.get(8).getRating());
editor.putFloat("rating10", products.get(9).getRating());
editor.apply();
}
@Override
public void onSaveInstanceState(@NonNull Bundle outState) {
super.onSaveInstanceState(outState);
// Сохраняем оценки в Bundle
outState.putFloat("rating1", rating1);
outState.putFloat("rating2", rating2);
outState.putFloat("rating3", rating3);
outState.putFloat("rating4", rating4);
outState.putFloat("rating5", rating5);
outState.putFloat("rating6", rating6);
outState.putFloat("rating7", rating7);
outState.putFloat("rating8", rating8);
outState.putFloat("rating9", rating9);
outState.putFloat("rating10", rating10);
}
@Override
public void onViewStateRestored(@Nullable Bundle savedInstanceState) {
super.onViewStateRestored(savedInstanceState);
if (savedInstanceState != null) {
// Восстанавливаем оценки из Bundle
rating1 = savedInstanceState.getFloat("rating1");
rating2 = savedInstanceState.getFloat("rating2");
rating3 = savedInstanceState.getFloat("rating3");
rating4 = savedInstanceState.getFloat("rating4");
rating5 = savedInstanceState.getFloat("rating5");
rating6 = savedInstanceState.getFloat("rating6");
rating7 = savedInstanceState.getFloat("rating7");
rating8 = savedInstanceState.getFloat("rating8");
rating9 = savedInstanceState.getFloat("rating9");
rating10 = savedInstanceState.getFloat("rating10");
// Устанавливаем оценки в соответствующие товары
products.get(0).setRating(rating1);
products.get(1).setRating(rating2);
products.get(2).setRating(rating3);
products.get(3).setRating(rating4);
products.get(4).setRating(rating5);
products.get(5).setRating(rating6);
products.get(6).setRating(rating7);
products.get(7).setRating(rating8);
products.get(8).setRating(rating9);
products.get(9).setRating(rating10);
products.get(0).setRating(rating1);
products.get(1).setRating(rating2);
products.get(2).setRating(rating3);
products.get(3).setRating(rating4);
products.get(4).setRating(rating5);
products.get(5).setRating(rating6);
products.get(6).setRating(rating7);
products.get(7).setRating(rating8);
products.get(8).setRating(rating9);
products.get(9).setRating(rating10);
}
}
private List<Product> getProducts() {
List<Product> products = new ArrayList<>();
Product product1 = new Product("Product 11", "Description 11", R.drawable.food_1, 0.0f);
products.add(product1);
Product product2 = new Product("Product 12", "Description 12", R.drawable.food_2, 0.0f);
products.add(product2);
Product product3 = new Product("Product 13", "Description 13", R.drawable.food_1_3, 0.0f);
products.add(product3);
Product product4 = new Product("Product 14", "Description 14", R.drawable.food_1_2, 0.0f);
products.add(product4);
Product product5 = new Product("Product 15", "Description 15", R.drawable.food_3_4, 0.0f);
products.add(product5);
Product product6 = new Product("Product 16", "Description 16", R.drawable.food_1_4, 0.0f);
products.add(product6);
Product product7 = new Product("Product 17", "Description 17", R.drawable.food_1_1, 0.0f);
products.add(product7);
Product product8 = new Product("Product 18", "Description 18", R.drawable.food_1_2, 0.0f);
products.add(product8);
Product product9 = new Product("Product 19", "Description 19", R.drawable.food_3, 0.0f);
products.add(product9);
Product product10 = new Product("Product 20", "Description 20", R.drawable.food_3_4, 0.0f);
products.add(product10);
return products;
}
}
|
577c5733a985b1d3a5267851c2ffb5d5
|
{
"intermediate": 0.33326005935668945,
"beginner": 0.5222734212875366,
"expert": 0.14446650445461273
}
|
5,487
|
import java.rmi.Naming;
import java.rmi.Remote;
import java.rmi.RemoteException;
import java.rmi.server.UnicastRemoteObject;
import java.util.*;
import java.util.List;
import java.util.Map;
public class JavaApplication60 {
public class EncyclopediaServiceImpl extends UnicastRemoteObject implements EncyclopediaService {
private List<String> encyclopedia;
public EncyclopediaServiceImpl() throws RemoteException {
super();
encyclopedia = generateRandomData(300);
}
private List<String> generateRandomData(int numWords) {
List<String> words = new ArrayList<>();
Random random = new Random();
for (int i = 0; i < numWords; i++) {
int wordLength = random.nextInt(10) + 1; // Random word length between 1 and 10 characters
StringBuilder word = new StringBuilder();
for (int j = 0; j < wordLength; j++) {
char c = (char) (random.nextInt(26) + 'a'); // Random lowercase letter
word.append(c);
}
words.add(word.toString());
}
return words;
}
@Override
public int count() {
int letterCount = 0;
for (String word : encyclopedia) {
letterCount += word.length();
}
return letterCount;
}
@Override
public List<String> repeatedWords() {
Set<String> uniqueWords = new HashSet<>();
List<String> repeatedWords = new ArrayList<>();
for (String word : encyclopedia) {
if (!uniqueWords.add(word)) {
repeatedWords.add(word);
}
}
return repeatedWords;
}
@Override
public String longest() {
String longestWord = "";
for (String word : encyclopedia) {
if (word.length() > longestWord.length()) {
longestWord = word;
}
}
return longestWord;
}
@Override
public String shortest() {
String shortestWord = "";
if (!encyclopedia.isEmpty()) {
shortestWord = encyclopedia.get(0);
for (String word : encyclopedia) {
if (word.length() < shortestWord.length()) {
shortestWord = word;
}
}
}
return shortestWord;
}
@Override
public Map<String, Integer> repeat() {
Map<String, Integer> wordCount = new HashMap<>();
for (String word : encyclopedia) {
wordCount.put(word, wordCount.getOrDefault(word, 0) + 1);
}
return wordCount;
}
@Override
public List<String> getData() {
return null;
}
}
/**
*
* @param args
*/
/**
*
* @author ismai
*/
public interface EncyclopediaService extends Remote {
int count() throws RemoteException;
List<String> repeatedWords() throws RemoteException;
String longest() throws RemoteException;
String shortest() throws RemoteException;
Map<String, Integer> repeat() throws RemoteException;
List<String> getData();
}
public static void main(String[] args) {
try {
EncyclopediaService service; // Create an instance of the class
service = new EncyclopediaServiceImpl();
Naming.rebind("//localhost/encyclopedia", service);
System.out.println("Encyclopedia service bound and ready to use.");
} catch (Exception e) {
System.err.println("Error: " + e.getMessage());
e.printStackTrace();
}
}
}
EncyclopediaService service = new EncyclopediaServiceImpl();
Error: Uncompilable code - non-static variable this cannot be referenced from a static context
java.lang.RuntimeException: Uncompilable code - non-static variable this cannot be referenced from a static context
at javaapplication60.JavaApplication60.main(JavaApplication60.java:1) Solve this error for me
|
373d980cc2aebe4c1b11e1dcb8e68756
|
{
"intermediate": 0.2925994098186493,
"beginner": 0.5292859673500061,
"expert": 0.1781146228313446
}
|
5,488
|
SortWorker sortWorker = new SortWorker(getActivity(), new WorkerParameters.Builder().build(), productAdapter); : Cannot resolve symbol 'Builder'
|
d964929d73af1b534edbd046f03ae042
|
{
"intermediate": 0.600253164768219,
"beginner": 0.17795993387699127,
"expert": 0.22178694605827332
}
|
5,489
|
hi
|
c3ddf4f4da38de256bf5a0bbe81218ac
|
{
"intermediate": 0.3246487081050873,
"beginner": 0.27135494351387024,
"expert": 0.40399640798568726
}
|
5,490
|
hi
|
0f58e434c9f8decb0512e2b0f8947124
|
{
"intermediate": 0.3246487081050873,
"beginner": 0.27135494351387024,
"expert": 0.40399640798568726
}
|
5,491
|
Hello!
|
b42b32436a8fe4b2ce3c05956154dd43
|
{
"intermediate": 0.3194829821586609,
"beginner": 0.26423266530036926,
"expert": 0.41628435254096985
}
|
5,492
|
how to put the validation error in a message in the forms.py
|
249cb88a5644b2ee51fc441145153a34
|
{
"intermediate": 0.3804260492324829,
"beginner": 0.21489764750003815,
"expert": 0.404676228761673
}
|
5,493
|
Provide actual python tones for this. Make a 4 piece 30 second song for the violin, viola, cello, and bass. The song should start out calm, but after 15 seconds or so, the violas grow from soft to loud playing the C string. After one measure of holding the C. The piece grows extremely loud and turns into an epic song till the end of the song where everyone plays the G string.
|
ad274148d1ebe96d3169824251c610ae
|
{
"intermediate": 0.34116607904434204,
"beginner": 0.18259960412979126,
"expert": 0.4762343466281891
}
|
5,494
|
file zilla fix Status: Logged in
Status: Retrieving directory listing of "/"... then 20 inactityi then failed tot connect
|
0c267066b10ec5b7ff1246a09d5161a2
|
{
"intermediate": 0.3750271797180176,
"beginner": 0.26101431250572205,
"expert": 0.36395853757858276
}
|
5,495
|
Для сортировки продуктов в SecondFragment необходимо вызвать метод sortProducts() класса SortWorker, который отсортирует список продуктов по цене в порядке возрастания. Для этого следует создать объект SortWorker и передать ему адаптер списка продуктов productAdapter. Далее вызвать метод enqueue() у объекта WorkManager с передачей в параметре созданного объекта SortWorker:
SortWorker worker = new SortWorker(getContext(), workerParams, productAdapter);
WorkManager.getInstance(getContext())
.beginUniqueWork(“SortProducts”, ExistingWorkPolicy.REPLACE, worker)
.enqueue();
|
8245804cc0f3ef7cb49f2cc2ebe1f135
|
{
"intermediate": 0.4482455849647522,
"beginner": 0.35379326343536377,
"expert": 0.19796118140220642
}
|
5,496
|
Actúa como un programador experto en algoritmos de reinforcement learning. Ahora revisa exhaustivamente el siguiente código de python en el que se implementa un algoritmo Actor-Critic para entrenar un agente en el ambiente Pendulum de gym y dime si están bien implementados los métodos _select_action_continuous() y _compute_actor_loss_continuous() o si debo cambiar algo más en el código, pues durante el entrenamiento no logro aumentar la recompensa promedio. En cambio, cuando uso un ambiente con acciones discretas como "CartPole" sí funciona bien el entrenamiento. Aquí está el código:
import torch
import torch.nn as nn
import gym
import time
import datetime
import csv
import numpy as np
import matplotlib.pyplot as plt
class Actor(nn.Module):
def __init__(self, dim_states, dim_actions, continuous_control):
super(Actor, self).__init__()
# MLP, fully connected layers, ReLU activations, linear ouput activation
# dim_states -> 64 -> 64 -> dim_actions
self.layer1 = nn.Linear(dim_states, 64)
self.layer2 = nn.Linear(64, 64)
self.layer3 = nn.Linear(64, dim_actions)
if continuous_control:
# trainable parameter
self._log_std = nn.Parameter(torch.zeros(1, dim_actions))
def forward(self, input):
input = nn.functional.relu(self.layer1(input))
input = nn.functional.relu(self.layer2(input))
input = self.layer3(input)
return input
class Critic(nn.Module):
def __init__(self, dim_states):
super(Critic, self).__init__()
# MLP, fully connected layers, ReLU activations, linear ouput activation
# dim_states -> 64 -> 64 -> 1
self.layer1 = nn.Linear(dim_states, 64)
self.layer2 = nn.Linear(64, 64)
self.layer3 = nn.Linear(64, 1)
def forward(self, input):
input = nn.functional.relu(self.layer1(input))
input = nn.functional.relu(self.layer2(input))
input = self.layer3(input)
return input
class ActorCriticAgent:
def __init__(self, dim_states, dim_actions, actor_lr, critic_lr, gamma, continuous_control=False):
self._actor_lr = actor_lr
self._critic_lr = critic_lr
self._gamma = gamma
self._dim_states = dim_states
self._dim_actions = dim_actions
self._continuous_control = continuous_control
self._actor = Actor(self._dim_states, self._dim_actions, self._continuous_control)
# Adam optimizer
self._actor_optimizer = torch.optim.Adam(self._actor.parameters(), lr=self._actor_lr)
self._critic = Critic(self._dim_states)
# Adam optimizer
self._critic_optimizer = torch.optim.Adam(self._critic.parameters(), lr=self._critic_lr)
self._select_action = self._select_action_continuous if self._continuous_control else self._select_action_discrete
self._compute_actor_loss = self._compute_actor_loss_continuous if self._continuous_control else self._compute_actor_loss_discrete
def select_action(self, observation):
return self._select_action(observation)
def _select_action_discrete(self, observation):
# sample from categorical distribution
with torch.no_grad():
observation = torch.from_numpy(observation).float()
logits = self._actor(observation)
dist = torch.distributions.Categorical(logits=logits)
action = dist.sample()
return action.item()
def _select_action_continuous(self, observation):
# sample from normal distribution
# use the log std trainable parameter
with torch.no_grad():
observation = torch.from_numpy(observation).float()
mean = self._actor(observation)
std = self._actor._log_std.exp()
normal = torch.distributions.Normal(mean, std)
action = normal.sample()
return action.numpy()[0]
def _compute_actor_loss_discrete(self, observation_batch, action_batch, advantage_batch):
# use negative logprobs * advantages
logits = self._actor(observation_batch)
dist = torch.distributions.Categorical(logits=logits)
log_prob = dist.log_prob(action_batch)
actor_loss = -(log_prob * advantage_batch).mean()
return actor_loss
def _compute_actor_loss_continuous(self, observation_batch, action_batch, advantage_batch):
# use negative logprobs * advantages
mean = self._actor(observation_batch)
std = self._actor._log_std.exp()
normal = torch.distributions.Normal(mean, std)
log_probs = normal.log_prob(action_batch).squeeze()
actor_loss = -(log_probs * advantage_batch).mean()
return actor_loss
def _compute_critic_loss(self, observation_batch, reward_batch, next_observation_batch, done_batch):
# minimize mean((r + gamma * V(s_t1) - V(s_t))^2)
q_values = self._critic(observation_batch).squeeze()
next_q_values = self._critic(next_observation_batch).squeeze()
expected_q_values = reward_batch + self._gamma * next_q_values * (1 - done_batch)
critic_loss = nn.functional.mse_loss(q_values, expected_q_values)
return critic_loss
def update_actor(self, observation_batch, action_batch, reward_batch, next_observation_batch, done_batch):
# compute the advantages using the critic and update the actor parameters
# use self._compute_actor_loss
observation_tensor = torch.from_numpy(observation_batch).float()
action_tensor = torch.from_numpy(action_batch).float()
reward_tensor = torch.from_numpy(reward_batch).float()
next_observation_tensor = torch.from_numpy(next_observation_batch).float()
done_tensor = torch.from_numpy(done_batch).float()
q_values = self._critic(observation_tensor).squeeze()
next_q_values = self._critic(next_observation_tensor).squeeze()
expected_q_values = reward_tensor + self._gamma * next_q_values * (1 - done_tensor)
advantage_tensor = expected_q_values - q_values
actor_loss = self._compute_actor_loss(observation_tensor, action_tensor, advantage_tensor)
self._actor_optimizer.zero_grad()
actor_loss.backward()
self._actor_optimizer.step()
def update_critic(self, observation_batch, reward_batch, next_observation_batch, done_batch):
# update the critic
# use self._compute_critic_loss
observation_tensor = torch.from_numpy(observation_batch).float()
reward_tensor = torch.from_numpy(reward_batch).float()
next_observation_tensor = torch.from_numpy(next_observation_batch).float()
done_tensor = torch.from_numpy(done_batch).float()
critic_loss = self._compute_critic_loss(observation_tensor, reward_tensor, next_observation_tensor, done_tensor)
self._critic_optimizer.zero_grad()
critic_loss.backward()
self._critic_optimizer.step()
def perform_single_rollout(env, agent, render=False):
# Modify this function to return a tuple of numpy arrays containing:
# (np.array(obs_t), np.array(acs_t), np.arraw(rew_t), np.array(obs_t1), np.array(done_t))
# np.array(obs_t) -> shape: (time_steps, nb_obs)
# np.array(obs_t1) -> shape: (time_steps, nb_obs)
# np.array(acs_t) -> shape: (time_steps, nb_acs) if actions are continuous, (time_steps,) if actions are discrete
# np.array(rew_t) -> shape: (time_steps,)
# np.array(done_t) -> shape: (time_steps,)
obs_t = env.reset()
done = False
episode_reward = 0
nb_steps = 0
obs_t_list, acs_t_list, rew_t_list, obs_t1_list, done_t_list = [], [], [], [], []
while not done:
if render:
env.render()
time.sleep(1. / 60)
action = agent.select_action(obs_t)
obs_t1, reward, done, _ = env.step(action)
obs_t = np.squeeze(obs_t)
obs_t1 = np.squeeze(obs_t1)
obs_t_list.append(obs_t)
acs_t_list.append(action)
rew_t_list.append(reward)
obs_t1_list.append(obs_t1)
done_t_list.append(done)
obs_t = obs_t1
episode_reward += reward
nb_steps += 1
if done:
return np.array(obs_t_list), np.array(acs_t_list), np.array(rew_t_list), np.array(obs_t1_list), np.array(done_t_list)
def sample_rollouts(env, agent, training_iter, min_batch_steps):
sampled_rollouts = []
total_nb_steps = 0
episode_nb = 0
while total_nb_steps < min_batch_steps:
episode_nb += 1
render = 2 == 0 and len(sampled_rollouts) == 0
# Use perform_single_rollout to get data
# Uncomment once perform_single_rollout works.
# Return sampled_rollouts
sample_rollout = perform_single_rollout(env, agent, render=render)
total_nb_steps += len(sample_rollout[0])
sampled_rollouts.append(sample_rollout)
return sampled_rollouts
def train_agent(env, agent, training_iterations, min_batch_steps, nb_critic_updates):
tr_iters_vec, avg_reward_vec, std_reward_vec, avg_steps_vec = [], [], [], []
_, (axes) = plt.subplots(1, 2, figsize=(12,4))
for tr_iter in range(training_iterations + 1):
# Sample rollouts using sample_rollouts
sampled_rollouts = sample_rollouts(env, agent, tr_iter, min_batch_steps)
# performed_batch_steps >= min_batch_steps
# Parse samples into the following arrays:
sampled_obs_t = np.concatenate([rollout[0] for rollout in sampled_rollouts]) # sampled_obs_t: Numpy array, shape: (performed_batch_steps, nb_observations)
sampled_acs_t = np.concatenate([rollout[1] for rollout in sampled_rollouts]) # sampled_acs: Numpy array, shape: (performed_batch_steps, nb_actions) if actions are continuous,
# (performed_batch_steps,) if actions are discrete
sampled_rew_t = np.concatenate([rollout[2] for rollout in sampled_rollouts]) # sampled_rew_t: Numpy array, shape: (performed_batch_steps,)
sampled_obs_t1 = np.concatenate([rollout[3] for rollout in sampled_rollouts]) # sampled_obs_t1: Numpy array, shape: (performed_batch_steps, nb_observations)
sampled_done_t = np.concatenate([rollout[4] for rollout in sampled_rollouts]) # sampled_done_t: Numpy array, shape: (performed_batch_steps,)
# performance metrics
update_performance_metrics(tr_iter, sampled_rollouts, axes, tr_iters_vec, avg_reward_vec, std_reward_vec, avg_steps_vec)
for _ in range(nb_critic_updates):
agent.update_critic(sampled_obs_t, sampled_rew_t, sampled_obs_t1, sampled_done_t)
agent.update_actor(sampled_obs_t, sampled_acs_t, sampled_rew_t, sampled_obs_t1, sampled_done_t)
save_metrics(tr_iters_vec, avg_reward_vec, std_reward_vec)
def update_performance_metrics(tr_iter, sampled_rollouts, axes, tr_iters_vec, avg_reward_vec, std_reward_vec, avg_steps_vec):
raw_returns = np.array([np.sum(rollout[2]) for rollout in sampled_rollouts])
rollout_steps = np.array([len(rollout[2]) for rollout in sampled_rollouts])
avg_return = np.average(raw_returns)
max_episode_return = np.max(raw_returns)
min_episode_return = np.min(raw_returns)
std_return = np.std(raw_returns)
avg_steps = np.average(rollout_steps)
# logs
print('-' * 32)
print('%20s : %5d' % ('Training iter' ,(tr_iter) ))
print('-' * 32)
print('%20s : %5.3g' % ('Max episode return', max_episode_return ))
print('%20s : %5.3g' % ('Min episode return', min_episode_return ))
print('%20s : %5.3g' % ('Return avg' , avg_return ))
print('%20s : %5.3g' % ('Return std' , std_return ))
print('%20s : %5.3g' % ('Steps avg' , avg_steps ))
avg_reward_vec.append(avg_return)
std_reward_vec.append(std_return)
avg_steps_vec.append(avg_steps)
tr_iters_vec.append(tr_iter)
plot_performance_metrics(axes,
tr_iters_vec,
avg_reward_vec,
std_reward_vec,
avg_steps_vec)
def plot_performance_metrics(axes, tr_iters_vec, avg_reward_vec, std_reward_vec, avg_steps_vec):
ax1, ax2 = axes
[ax.cla() for ax in axes]
ax1.errorbar(tr_iters_vec, avg_reward_vec, yerr=std_reward_vec, marker='.',color='C0')
ax1.set_ylabel('Avg Reward')
ax2.plot(tr_iters_vec, avg_steps_vec, marker='.',color='C1')
ax2.set_ylabel('Avg Steps')
[ax.grid('on') for ax in axes]
[ax.set_xlabel('training iteration') for ax in axes]
plt.pause(0.05)
def save_metrics(tr_iters_vec, avg_reward_vec, std_reward_vec):
with open('metrics'+datetime.datetime.now().strftime('%H:%M:%S')+'.csv', 'w') as csv_file:
csv_writer = csv.writer(csv_file, delimiter='\t')
csv_writer.writerow(['steps', 'avg_reward', 'std_reward'])
for i in range(len(tr_iters_vec)):
csv_writer.writerow([tr_iters_vec[i], avg_reward_vec[i], std_reward_vec[i]])
if __name__ == '__main__':
env = gym.make('Pendulum-v1')
dim_states = env.observation_space.shape[0]
continuous_control = isinstance(env.action_space, gym.spaces.Box)
dim_actions = env.action_space.shape[0] if continuous_control else env.action_space.n
actor_critic_agent = ActorCriticAgent(dim_states=dim_states,
dim_actions=dim_actions,
actor_lr=0.001,
critic_lr=0.001,
gamma=0.99,
continuous_control=continuous_control)
train_agent(env=env,
agent=actor_critic_agent,
training_iterations=2000,
min_batch_steps=5000,
nb_critic_updates=1)
|
359763ee33569135de4897f8a23e25b2
|
{
"intermediate": 0.38978055119514465,
"beginner": 0.4089626669883728,
"expert": 0.20125679671764374
}
|
5,497
|
Design a Turing machine to recognize all strings consisting of even numbers of 1’s.
a. Draw a transition diagram for the Turing machine of the above also
b. write the instantaneous description on the string 1111.
|
33e227b15f508a7d495bfe14ecea4f10
|
{
"intermediate": 0.2453964799642563,
"beginner": 0.14942488074302673,
"expert": 0.6051785945892334
}
|
5,498
|
hi
|
98c8ecb5e0d45c0ddebd06d18b7aac3f
|
{
"intermediate": 0.3246487081050873,
"beginner": 0.27135494351387024,
"expert": 0.40399640798568726
}
|
5,499
|
1. Исправить кавычки в строках, чтобы они были правильными: заменить “ и ” на ".
2. В классе SortWorker исправить конструктор по умолчанию, так как он не принимает параметры, используя конструктор с параметром context вместо него.
3. Исправить строку создания объекта OneTimeWorkRequest в классе SecondFragment, передав в конструктор класс SortWorker, а не объект этого класса. То есть заменить строку:
OneTimeWorkRequest request = new OneTimeWorkRequest.Builder(worker).build();
на
OneTimeWorkRequest request = new OneTimeWorkRequest.Builder(SortWorker.class).build();
|
2fe5330950036794e0f37c655228c24b
|
{
"intermediate": 0.40548259019851685,
"beginner": 0.3859786093235016,
"expert": 0.20853883028030396
}
|
5,500
|
how to send to backend file from dropzone only after choosed languages <!-- Create the form and dropzone element -->
<div class="container-fluid">
<div class="row text-center justify-content-center">
<div class="col">
<h2>Multiple Localization From File</h2>
<form action="/localization/multi-local-from-file" method="post" enctype="multipart/form-data">
<div class="form-group">
<!-- Create the target language select element using bootstrap-select -->
<label for="target_lang_list">Choose your target languages</label>
<select id="target_lang_list" name="target_lang_list" class="selectpicker" multiple data-live-search="true" required>
{% for key, value in languages.items() %}
<option value="{{ key }}">{{ value }}</option>
{% endfor %}
</select>
</div>
<div class="form-group">
<!-- Create the dropzone element -->
<label for="my-dropzone">Choose an ARB file</label>
<div class="dropzone" id="my-dropzone"></div>
</div>
<!-- Add buttons for submitting the form and downloading the translated files -->
<input class="btn btn-primary" id="translate-btn" type="submit" value="Translate">
<a class="btn btn-success" id="download-multiple" href="#" download="translated.zip">Download Translated Files</a>
</form>
</div>
</div>
</div>
<!-- Add the Dropzone initialization script -->
<script type="text/javascript">
Dropzone.autoDiscover = false;
$(document).ready(function() {
// Initialize the dropzone element
$("#my-dropzone").dropzone({
url: "/localization/multi-local-from-file",
addRemoveLinks: true,
paramName: "data",
maxFiles: 1,
maxFilesize: 10, // Maximum filesize in MB
acceptedFiles: ".arb",
init: function() {
this.on("success", function(file, response) {
// On successful translation, enable the download button and change the download link
$("#download-multiple").prop("href", url.createObjectURL(response));
$("#download-multiple").prop("disabled", false);
});
}
});
});
</script>
|
af42b33e04aa8fa82d0c00391485726e
|
{
"intermediate": 0.2845544219017029,
"beginner": 0.36600416898727417,
"expert": 0.34944140911102295
}
|
5,501
|
package com.example.myapp_2;
import android.content.Context;
import androidx.annotation.NonNull;
import androidx.work.Worker;
import androidx.work.WorkerParameters;
import com.example.myapp_2.List_1.Product;
import com.example.myapp_2.List_1.ProductAdapter;
import java.util.Collections;
import java.util.List;
public class SortWorker extends Worker {
private ProductAdapter adapter;
public SortWorker(@NonNull Context context, @NonNull WorkerParameters workerParams) {
super(context, workerParams);
}
@NonNull
@Override
public Result doWork() {
adapter.sortProductsByPrice();
return Result.success();
}
// public SortWorker() {
//super();
//}
public SortWorker(@NonNull Context context) {
super(context, null);
}
public void setAdapter(ProductAdapter adapter) {
this.adapter = adapter;
}
} (Код активации в фрагменте: SortWorker worker = new SortWorker(getContext());
worker.setAdapter(productAdapter);
OneTimeWorkRequest request = new OneTimeWorkRequest.Builder(SortWorker.class).build();
WorkManager.getInstance(getContext())
.beginUniqueWork("SortProducts", ExistingWorkPolicy.REPLACE, request)
.enqueue();) (Возникла ошибка : E/AndroidRuntime: FATAL EXCEPTION: main
Process: com.example.myapp_2, PID: 1793
java.lang.IllegalArgumentException: WorkerParameters is null
at androidx.work.ListenableWorker.<init>(ListenableWorker.java:81)
at androidx.work.Worker.<init>(Worker.java:51)
at com.example.myapp_2.SortWorker.<init>(SortWorker.java:33)
at com.example.myapp_2.UI.view.fragments.SecondFragment.onCreateView(SecondFragment.java:103)
at androidx.fragment.app.Fragment.performCreateView(Fragment.java:2963 исправт эту ошибку)
|
07de4e682734ac2790ec7e9491f7c343
|
{
"intermediate": 0.3879048824310303,
"beginner": 0.3081263601779938,
"expert": 0.30396875739097595
}
|
5,502
|
regex to capture exactly one or two digits
|
45c4b2118836ddba07db41a02e7e4f1d
|
{
"intermediate": 0.3517147898674011,
"beginner": 0.19958949089050293,
"expert": 0.44869568943977356
}
|
5,503
|
how to code random slow moving dots in java GUI?
|
35cbe99ad9055257ca9d6e52865c9863
|
{
"intermediate": 0.2885666787624359,
"beginner": 0.21101140975952148,
"expert": 0.5004218220710754
}
|
5,504
|
Actúa como un programador experto en algoritmos de reinforcement learning. Ahora revisa exhaustivamente el siguiente código de python en el que se implementa un algoritmo Actor-Critic para entrenar un agente en el ambiente Pendulum de gym y muéstrame partes del código que debo cambiar, pues durante el entrenamiento no logro aumentar la recompensa promedio. Te en cuenta que esto ocurre sólo para este ambiente que tiene espacio de acciones continuo, ya que cuando uso un ambiente con acciones discretas como "CartPole" sí funciona bien el entrenamiento. Aquí está el código:
import torch
import torch.nn as nn
import gym
import time
import datetime
import csv
import numpy as np
import matplotlib.pyplot as plt
class Actor(nn.Module):
def __init__(self, dim_states, dim_actions, continuous_control):
super(Actor, self).__init__()
# MLP, fully connected layers, ReLU activations, linear ouput activation
# dim_states -> 64 -> 64 -> dim_actions
self.layer1 = nn.Linear(dim_states, 64)
self.layer2 = nn.Linear(64, 64)
self.layer3 = nn.Linear(64, dim_actions)
if continuous_control:
# trainable parameter
self._log_std = nn.Parameter(torch.zeros(1, dim_actions))
def forward(self, input):
input = nn.functional.relu(self.layer1(input))
input = nn.functional.relu(self.layer2(input))
input = self.layer3(input)
return input
class Critic(nn.Module):
def __init__(self, dim_states):
super(Critic, self).__init__()
# MLP, fully connected layers, ReLU activations, linear ouput activation
# dim_states -> 64 -> 64 -> 1
self.layer1 = nn.Linear(dim_states, 64)
self.layer2 = nn.Linear(64, 64)
self.layer3 = nn.Linear(64, 1)
def forward(self, input):
input = nn.functional.relu(self.layer1(input))
input = nn.functional.relu(self.layer2(input))
input = self.layer3(input)
return input
class ActorCriticAgent:
def __init__(self, dim_states, dim_actions, actor_lr, critic_lr, gamma, continuous_control=False):
self._actor_lr = actor_lr
self._critic_lr = critic_lr
self._gamma = gamma
self._dim_states = dim_states
self._dim_actions = dim_actions
self._continuous_control = continuous_control
self._actor = Actor(self._dim_states, self._dim_actions, self._continuous_control)
# Adam optimizer
self._actor_optimizer = torch.optim.Adam(self._actor.parameters(), lr=self._actor_lr)
self._critic = Critic(self._dim_states)
# Adam optimizer
self._critic_optimizer = torch.optim.Adam(self._critic.parameters(), lr=self._critic_lr)
self._select_action = self._select_action_continuous if self._continuous_control else self._select_action_discrete
self._compute_actor_loss = self._compute_actor_loss_continuous if self._continuous_control else self._compute_actor_loss_discrete
def select_action(self, observation):
return self._select_action(observation)
def _select_action_discrete(self, observation):
# sample from categorical distribution
with torch.no_grad():
observation = torch.from_numpy(observation).float()
logits = self._actor(observation)
dist = torch.distributions.Categorical(logits=logits)
action = dist.sample()
return action.item()
def _select_action_continuous(self, observation):
# sample from normal distribution
# use the log std trainable parameter
with torch.no_grad():
observation = torch.from_numpy(observation).float()
mean = self._actor(observation)
std = self._actor._log_std.exp()
normal = torch.distributions.Normal(mean, std)
action = normal.sample()
return action.numpy()[0]
def _compute_actor_loss_discrete(self, observation_batch, action_batch, advantage_batch):
# use negative logprobs * advantages
logits = self._actor(observation_batch)
dist = torch.distributions.Categorical(logits=logits)
log_prob = dist.log_prob(action_batch)
actor_loss = -(log_prob * advantage_batch).mean()
return actor_loss
def _compute_actor_loss_continuous(self, observation_batch, action_batch, advantage_batch):
# use negative logprobs * advantages
mean = self._actor(observation_batch)
std = self._actor._log_std.exp()
normal = torch.distributions.Normal(mean, std)
log_probs = normal.log_prob(action_batch).squeeze()
actor_loss = -(log_probs * advantage_batch).mean()
return actor_loss
def _compute_critic_loss(self, observation_batch, reward_batch, next_observation_batch, done_batch):
# minimize mean((r + gamma * V(s_t1) - V(s_t))^2)
q_values = self._critic(observation_batch).squeeze()
next_q_values = self._critic(next_observation_batch).squeeze()
expected_q_values = reward_batch + self._gamma * next_q_values * (1 - done_batch)
critic_loss = nn.functional.mse_loss(q_values, expected_q_values)
return critic_loss
def update_actor(self, observation_batch, action_batch, reward_batch, next_observation_batch, done_batch):
# compute the advantages using the critic and update the actor parameters
# use self._compute_actor_loss
observation_tensor = torch.from_numpy(observation_batch).float()
action_tensor = torch.from_numpy(action_batch).float()
reward_tensor = torch.from_numpy(reward_batch).float()
next_observation_tensor = torch.from_numpy(next_observation_batch).float()
done_tensor = torch.from_numpy(done_batch).float()
q_values = self._critic(observation_tensor).squeeze()
next_q_values = self._critic(next_observation_tensor).squeeze()
expected_q_values = reward_tensor + self._gamma * next_q_values * (1 - done_tensor)
advantage_tensor = expected_q_values - q_values
actor_loss = self._compute_actor_loss(observation_tensor, action_tensor, advantage_tensor)
self._actor_optimizer.zero_grad()
actor_loss.backward()
self._actor_optimizer.step()
def update_critic(self, observation_batch, reward_batch, next_observation_batch, done_batch):
# update the critic
# use self._compute_critic_loss
observation_tensor = torch.from_numpy(observation_batch).float()
reward_tensor = torch.from_numpy(reward_batch).float()
next_observation_tensor = torch.from_numpy(next_observation_batch).float()
done_tensor = torch.from_numpy(done_batch).float()
critic_loss = self._compute_critic_loss(observation_tensor, reward_tensor, next_observation_tensor, done_tensor)
self._critic_optimizer.zero_grad()
critic_loss.backward()
self._critic_optimizer.step()
def perform_single_rollout(env, agent, render=False):
# Modify this function to return a tuple of numpy arrays containing:
# (np.array(obs_t), np.array(acs_t), np.arraw(rew_t), np.array(obs_t1), np.array(done_t))
# np.array(obs_t) -> shape: (time_steps, nb_obs)
# np.array(obs_t1) -> shape: (time_steps, nb_obs)
# np.array(acs_t) -> shape: (time_steps, nb_acs) if actions are continuous, (time_steps,) if actions are discrete
# np.array(rew_t) -> shape: (time_steps,)
# np.array(done_t) -> shape: (time_steps,)
obs_t = env.reset()
done = False
episode_reward = 0
nb_steps = 0
obs_t_list, acs_t_list, rew_t_list, obs_t1_list, done_t_list = [], [], [], [], []
while not done:
if render:
env.render()
time.sleep(1. / 60)
action = agent.select_action(obs_t)
obs_t1, reward, done, _ = env.step(action)
obs_t = np.squeeze(obs_t)
obs_t1 = np.squeeze(obs_t1)
obs_t_list.append(obs_t)
acs_t_list.append(action)
rew_t_list.append(reward)
obs_t1_list.append(obs_t1)
done_t_list.append(done)
obs_t = obs_t1
episode_reward += reward
nb_steps += 1
if done:
return np.array(obs_t_list), np.array(acs_t_list), np.array(rew_t_list), np.array(obs_t1_list), np.array(done_t_list)
def sample_rollouts(env, agent, training_iter, min_batch_steps):
sampled_rollouts = []
total_nb_steps = 0
episode_nb = 0
while total_nb_steps < min_batch_steps:
episode_nb += 1
render = 2 == 0 and len(sampled_rollouts) == 0
# Use perform_single_rollout to get data
# Uncomment once perform_single_rollout works.
# Return sampled_rollouts
sample_rollout = perform_single_rollout(env, agent, render=render)
total_nb_steps += len(sample_rollout[0])
sampled_rollouts.append(sample_rollout)
return sampled_rollouts
def train_agent(env, agent, training_iterations, min_batch_steps, nb_critic_updates):
tr_iters_vec, avg_reward_vec, std_reward_vec, avg_steps_vec = [], [], [], []
_, (axes) = plt.subplots(1, 2, figsize=(12,4))
for tr_iter in range(training_iterations + 1):
# Sample rollouts using sample_rollouts
sampled_rollouts = sample_rollouts(env, agent, tr_iter, min_batch_steps)
# performed_batch_steps >= min_batch_steps
# Parse samples into the following arrays:
sampled_obs_t = np.concatenate([rollout[0] for rollout in sampled_rollouts]) # sampled_obs_t: Numpy array, shape: (performed_batch_steps, nb_observations)
sampled_acs_t = np.concatenate([rollout[1] for rollout in sampled_rollouts]) # sampled_acs: Numpy array, shape: (performed_batch_steps, nb_actions) if actions are continuous,
# (performed_batch_steps,) if actions are discrete
sampled_rew_t = np.concatenate([rollout[2] for rollout in sampled_rollouts]) # sampled_rew_t: Numpy array, shape: (performed_batch_steps,)
sampled_obs_t1 = np.concatenate([rollout[3] for rollout in sampled_rollouts]) # sampled_obs_t1: Numpy array, shape: (performed_batch_steps, nb_observations)
sampled_done_t = np.concatenate([rollout[4] for rollout in sampled_rollouts]) # sampled_done_t: Numpy array, shape: (performed_batch_steps,)
# performance metrics
update_performance_metrics(tr_iter, sampled_rollouts, axes, tr_iters_vec, avg_reward_vec, std_reward_vec, avg_steps_vec)
for _ in range(nb_critic_updates):
agent.update_critic(sampled_obs_t, sampled_rew_t, sampled_obs_t1, sampled_done_t)
agent.update_actor(sampled_obs_t, sampled_acs_t, sampled_rew_t, sampled_obs_t1, sampled_done_t)
save_metrics(tr_iters_vec, avg_reward_vec, std_reward_vec)
def update_performance_metrics(tr_iter, sampled_rollouts, axes, tr_iters_vec, avg_reward_vec, std_reward_vec, avg_steps_vec):
raw_returns = np.array([np.sum(rollout[2]) for rollout in sampled_rollouts])
rollout_steps = np.array([len(rollout[2]) for rollout in sampled_rollouts])
avg_return = np.average(raw_returns)
max_episode_return = np.max(raw_returns)
min_episode_return = np.min(raw_returns)
std_return = np.std(raw_returns)
avg_steps = np.average(rollout_steps)
# logs
print('-' * 32)
print('%20s : %5d' % ('Training iter' ,(tr_iter) ))
print('-' * 32)
print('%20s : %5.3g' % ('Max episode return', max_episode_return ))
print('%20s : %5.3g' % ('Min episode return', min_episode_return ))
print('%20s : %5.3g' % ('Return avg' , avg_return ))
print('%20s : %5.3g' % ('Return std' , std_return ))
print('%20s : %5.3g' % ('Steps avg' , avg_steps ))
avg_reward_vec.append(avg_return)
std_reward_vec.append(std_return)
avg_steps_vec.append(avg_steps)
tr_iters_vec.append(tr_iter)
plot_performance_metrics(axes,
tr_iters_vec,
avg_reward_vec,
std_reward_vec,
avg_steps_vec)
def plot_performance_metrics(axes, tr_iters_vec, avg_reward_vec, std_reward_vec, avg_steps_vec):
ax1, ax2 = axes
[ax.cla() for ax in axes]
ax1.errorbar(tr_iters_vec, avg_reward_vec, yerr=std_reward_vec, marker='.',color='C0')
ax1.set_ylabel('Avg Reward')
ax2.plot(tr_iters_vec, avg_steps_vec, marker='.',color='C1')
ax2.set_ylabel('Avg Steps')
[ax.grid('on') for ax in axes]
[ax.set_xlabel('training iteration') for ax in axes]
plt.pause(0.05)
def save_metrics(tr_iters_vec, avg_reward_vec, std_reward_vec):
with open('metrics'+datetime.datetime.now().strftime('%H:%M:%S')+'.csv', 'w') as csv_file:
csv_writer = csv.writer(csv_file, delimiter='\t')
csv_writer.writerow(['steps', 'avg_reward', 'std_reward'])
for i in range(len(tr_iters_vec)):
csv_writer.writerow([tr_iters_vec[i], avg_reward_vec[i], std_reward_vec[i]])
if __name__ == '__main__':
env = gym.make('Pendulum-v1')
dim_states = env.observation_space.shape[0]
continuous_control = isinstance(env.action_space, gym.spaces.Box)
dim_actions = env.action_space.shape[0] if continuous_control else env.action_space.n
actor_critic_agent = ActorCriticAgent(dim_states=dim_states,
dim_actions=dim_actions,
actor_lr=0.001,
critic_lr=0.001,
gamma=0.99,
continuous_control=continuous_control)
train_agent(env=env,
agent=actor_critic_agent,
training_iterations=2000,
min_batch_steps=5000,
nb_critic_updates=1)
|
1e771c5cde2060b6175b3437b3371196
|
{
"intermediate": 0.3457287549972534,
"beginner": 0.3633134663105011,
"expert": 0.2909577190876007
}
|
5,505
|
can you implement neural network for java?
|
6a2b97137107b9677c709d49d600c4fe
|
{
"intermediate": 0.10394957661628723,
"beginner": 0.04324789345264435,
"expert": 0.8528025150299072
}
|
5,506
|
an example which train a text-to-text model using t5
|
df987d964542f17ab6b2610e94b203f7
|
{
"intermediate": 0.20586949586868286,
"beginner": 0.16377469897270203,
"expert": 0.6303557753562927
}
|
5,507
|
can you write code for java saying hello world?
|
3ae24219093cc4e1c1cb36cc13032b9f
|
{
"intermediate": 0.2994649112224579,
"beginner": 0.41006460785865784,
"expert": 0.2904704511165619
}
|
5,508
|
if (connectingFirstDevice == null) {
connectingFirstDevice = event.device
} else {
if (connectingFirstDevice!!.id != event.device.id) {
val firstList = connectingFirstDevice!!.connections
val secondList = event.device.connections
if (firstList != null && secondList != null) {
if (!firstList.intersect(secondList).any()) {
insertConnection(
firstDevice = connectingFirstDevice!!,
secondDevice = event.device
)
}
} else {
insertConnection(
firstDevice = connectingFirstDevice!!,
secondDevice = event.device
)
}
}
}
optimize it
|
faaa409dc06002130a796217e5d297fa
|
{
"intermediate": 0.2870887219905853,
"beginner": 0.35377243161201477,
"expert": 0.3591389060020447
}
|
5,509
|
Design a Turing Machine for L = {0n 1m 0n 1m | m, n > 1}. Show the steps, operations in the tape. Draw the transition table and transition diagram. Give ID for the strings 011011.
|
94f0fb5feea60aeb06559b40c0deba73
|
{
"intermediate": 0.1598583161830902,
"beginner": 0.22003553807735443,
"expert": 0.6201061010360718
}
|
5,510
|
can you tell what this code does ? Here is the code:
import java.util.Arrays;
import java.util.Random;
public class NeuralDot {
private static final int VISION_RANGE = 5;
private static final int GRID_SIZE = 100;
private static final int NUM_INPUTS = (2VISION_RANGE + 1) * (2VISION_RANGE + 1) + 2;
private static final int NUM_HIDDEN = 16;
private static final int NUM_OUTPUTS = 3;
private static final double LEARNING_RATE = 0.1;
private static final int NUM_EPISODES = 10000;
private int x;
private int y;
private boolean[][] grid;
private Random random;
private NeuralNetwork neuralNetwork;
public NeuralDot() {
x = GRID_SIZE / 2;
y = GRID_SIZE / 2;
grid = new boolean[GRID_SIZE][GRID_SIZE];
random = new Random();
neuralNetwork = new NeuralNetwork(NUM_INPUTS, NUM_HIDDEN, NUM_OUTPUTS, LEARNING_RATE);
}
public void run() {
for (int episode = 0; episode < NUM_EPISODES; episode++) {
// Reset the grid and place a food dot randomly
resetGrid();
placeFoodDot();
// Play the episode until the dot eats the food dot
while (!grid[x][y]) {
// Get the nearest food dot
int[] foodDot = getNearestFoodDot();
// Compute the inputs to the neural network
double[] inputs = new double[NUM_INPUTS];
int index = 0;
for (int i = x - VISION_RANGE; i <= x + VISION_RANGE; i++) {
for (int j = y - VISION_RANGE; j <= y + VISION_RANGE; j++) {
if (i < 0 || i >= GRID_SIZE || j < 0 || j >= GRID_SIZE) {
inputs[index++] = 0;
} else if (i == x && j == y) {
inputs[index++] = 1;
} else {
inputs[index++] = grid[i][j] ? -1 : 0;
}
}
}
inputs[index++] = foodDot[0] - x;
inputs[index++] = foodDot[1] - y;
// Compute the outputs of the neural network
double[] outputs = neuralNetwork.feedForward(inputs);
// Choose the action with the highest probability
double maxProbability = Double.NEGATIVE_INFINITY;
int action = 0;
for (int i = 0; i < NUM_OUTPUTS; i++) {
if (outputs[i] > maxProbability) {
maxProbability = outputs[i];
action = i;
}
}
// Take the chosen action
switch (action) {
case 0:
moveLeft();
break;
case 1:
moveRight();
break;
case 2:
moveForward();
break;
}
// Compute the reward signal
double reward;
if (grid[x][y]) {
reward = 10;
} else {
reward = -0.1;
}
// Train the neural network on the input-output pair
double[] targetOutputs = new double[NUM_OUTPUTS];
targetOutputs[action] = 1;
neuralNetwork.train(inputs, targetOutputs, reward);
}
}
}
private void resetGrid() {
for (int i = 0; i < GRID_SIZE; i++) {
Arrays.fill(grid[i], false);
}
}
private void placeFoodDot() {
int foodX = random.nextInt(GRID_SIZE);
int foodY = random.nextInt(GRID_SIZE);
grid[foodX][foodY] = true;
}
private int[] getNearestFoodDot() {
int nearestX = -1;
int nearestY = -1;
double nearestDistance = Double.POSITIVE_INFINITY;
for (int i = 0; i < GRID_SIZE; i++) {
for (int j = 0; j < GRID_SIZE; j++) {
if (grid[i][j]) {
double distance = Math.sqrt((i - x)(i - x) + (j - y)(j - y));
if (distance < nearestDistance) {
nearestX = i;
nearestY = j;
nearestDistance = distance;
}
}
}
}
return new int[] {nearestX, nearestY};
}
private void moveLeft() {
if (x > 0) {
x–;
}
}
private void moveRight() {
if (x < GRID_SIZE - 1) {
x++;
}
}
private void moveForward() {
if (y < GRID_SIZE - 1) {
y++;
}
}
public static void main(String[] args) {
NeuralDot dot = new NeuralDot();
dot.run();
}
}
|
ea7a8ba0bcc6891ccb22452023c1d5e5
|
{
"intermediate": 0.34734734892845154,
"beginner": 0.430620938539505,
"expert": 0.22203165292739868
}
|
5,511
|
write js code for sending that cratetes dropzone and send request with uploaded file and choosen target languages to this endpoint @router.post("/multi-local-from-file")
async def multi_local_from_file(
data: UploadFile,
target_lang_list: list[str] = LANGUAGE_LIST,
source_lang: str = "en",
) -> StreamingResponse:
"""
Translates the arb file into several languages
- **data**: arb file
- **source_lang**: original language
- **target_lang_list**: languages after translation
"""
data_dict = get_dict_from_arb_file(data.file)
tmpdir = tempfile.TemporaryDirectory()
# target_lang_list = comma_str_to_list(target_lang_list)
file_paths = multi_lang_translate(source_lang, target_lang_list, data_dict, tmpdir)
zip_io = save_files_to_zip(file_paths)
return StreamingResponse(
iter([zip_io.getvalue()]),
media_type="application/x-zip-compressed",
headers={"Content-Disposition": f"attachment; filename=translated.zip"},
) I already wrote html <!-- Create the form and dropzone element -->
<div class="container-fluid">
<div class="row text-center justify-content-center">
<div class="col">
<h2>Multiple Localization From File</h2>
<form action="/localization/multi-local-from-file" method="post" enctype="multipart/form-data">
<div class="form-group">
<!-- Create the target language select element using bootstrap-select -->
<label for="target_lang_list">Choose your target languages</label>
<select id="target_lang_list" name="target_lang_list" class="selectpicker" multiple data-live-search="true" required>
{% for key, value in languages.items() %}
<option value="{{ key }}">{{ value }}</option>
{% endfor %}
</select>
</div>
<div class="form-group">
<!-- Create the dropzone element -->
<label for="my-dropzone">Choose an ARB file</label>
<div class="dropzone disabled" id="my-dropzone"></div>
</div>
<!-- Add buttons for submitting the form and downloading the translated files -->
<input class="btn btn-primary" id="translate-btn" type="submit" value="Translate">
<a class="btn btn-success" id="download-multiple" href="#" download="translated.zip">Download Translated Files</a>
</form>
</div>
</div>
</div>
|
10ec227b1349a9d5cfd659df54acbf24
|
{
"intermediate": 0.37083423137664795,
"beginner": 0.473787784576416,
"expert": 0.15537801384925842
}
|
5,512
|
import time
import os
import psutil
import requests
import json
import subprocess
from datetime import datetime
# Discord webhook configuration
with open("webhook.txt", "r") as f:
webhook_url = f.read().strip()
reopened_count = 0
checks_count = 0
last_restart_time = time.time()
message_id = None
# Set the restart interval and check interval
restart_interval = 20 * 60 # 20 minutes
check_interval = 5 # 5 seconds
# Logo
logo_color = '\033[92m' # Green
logo = r"""
{logo_color}
_____ _ _____ _ _
/ ____| | | | __ \ | | | |
| | _ __ __ _ ___| |__ | | | | ___| |_ ___ ___| |_ ___ _ __
| | | '__/ _` / __| '_ \ | | | |/ _ \ __/ _ \/ __| __/ _ \| '__|
| |____| | | (_| \__ \ | | | | |__| | __/ || __/ (__| || (_) | |
\_____|_| \__,_|___/_| |_| |_____/ \___|\__\___|\___|\__\___/|_|
""".format(logo_color=logo_color)
os.system('cls')
print(logo)
print("\nTotal restarts: {reopened_count}")
print(f"Checks: {checks_count}")
print()
print("Made By BearXxX#1940")
print("\n")
def send_webhook_update():
global message_id
current_time = datetime.now().strftime("Today at %H:%M")
webhook_data = {
"embeds": [{
"title": "Crash Detector",
"description": "The program crash detector is running.",
"color": 0x7FFF00,
"fields": [
{
"name": "Total Restarts",
"value": str(reopened_count),
"inline": True
},
{
"name": "Total Checks",
"value": str(checks_count),
"inline": True
}
],
"footer": {
"text": f"Made by BearXxX#1940 | {current_time}"
}
}]
}
headers = {"Content-Type": "application/json"}
if message_id is None:
response = requests.post(webhook_url, json=webhook_data, headers=headers)
if response.status_code == 200:
message_id = response.json()["id"]
print("Discord webhook sent successfully.")
else:
print("Error sending Discord webhook.")
else:
edit_url = f"{webhook_url}/messages/{message_id}"
response = requests.patch(edit_url, json=webhook_data, headers=headers)
if response.status_code == 200:
print("Discord webhook updated successfully.")
else:
print("Error updating Discord webhook.")
# ...
GREEN_COLOR = '\033[91m' # Red
RESET_COLOR = '\033[0m' # Reset color (\033[0m)
# ...
while True:
if time.time() - last_restart_time >= restart_interval:
checks_count = 0
for process in psutil.process_iter():
if process.name() == 'python.exe' and process.pid != os.getpid():
process.terminate()
reopened_count += 1
last_restart_time = time.time()
os.system('cls')
print(GREEN_COLOR + logo + RESET_COLOR)
print("")
print(f"{GREEN_COLOR}Total restarts: {reopened_count}{RESET_COLOR}")
print(f"{GREEN_COLOR}Checks: {checks_count}{RESET_COLOR}")
print(f"{GREEN_COLOR}Made By BearXxX#1940{RESET_COLOR}")
print("")
print("")
send_webhook_update()
time.sleep(5)
for process in psutil.process_iter():
if process.name() == 'python.exe' and 'main.py' in process.cmdline():
break
else:
checks_count += 1
last_restart_time = time.time()
os.system('cls')
print(GREEN_COLOR + logo + RESET_COLOR)
print("")
print(f"{GREEN_COLOR}Total restarts: {reopened_count}{RESET_COLOR}")
print(f"{GREEN_COLOR}Checks: {checks_count}{RESET_COLOR}")
print(f"{GREEN_COLOR}Made By BearXxX#1940{RESET_COLOR}")
print("")
print("")
send_webhook_update()
subprocess.Popen(['python', 'main.py'], cwd=os.path.dirname(os.path.abspath(__file__)), creationflags=subprocess.CREATE_NEW_CONSOLE)
send_webhook_update()
time.sleep(check_interval)
make this into a white window with all the stats what are on the program but on a window with a start/stop button with how many seconds ran at the bottom
USE THE GUI library Tkinter
make the window/gui look very nice
|
5d45447aa851d4417cd3967d13f48ca6
|
{
"intermediate": 0.4187580347061157,
"beginner": 0.3638937473297119,
"expert": 0.21734824776649475
}
|
5,513
|
can you learn what this program does ? code :
import java.awt.Color;
import java.awt.Graphics;
import javax.swing.JFrame;
import javax.swing.JPanel;
public class NeuralDotGUI extends JPanel {
private NeuralDot neuralDot;
private int cellWidth;
private int cellHeight;
public NeuralDotGUI(NeuralDot neuralDot, int cellWidth, int cellHeight) {
this.neuralDot = neuralDot;
this.cellWidth = cellWidth;
this.cellHeight = cellHeight;
}
public void paintComponent(Graphics g) {
super.paintComponent(g);
// Draw grid cells
for (int i = 0; i < NeuralDot.GRID_SIZE; i++) {
for (int j = 0; j < NeuralDot.GRID_SIZE; j++) {
int x = i * cellWidth;
int y = j * cellHeight;
if (neuralDot.grid[i][j]) {
g.setColor(Color.GREEN);
} else {
g.setColor(Color.WHITE);
}
g.fillRect(x, y, cellWidth, cellHeight);
}
}
// Draw dot
g.setColor(Color.RED);
g.fillOval(neuralDot.x * cellWidth, neuralDot.y * cellHeight, cellWidth, cellHeight);
}
public static void main(String[] args) throws InterruptedException {
NeuralDot dot = new NeuralDot();
NeuralDotGUI gui = new NeuralDotGUI(dot, 5, 5);
JFrame frame = new JFrame();
frame.setTitle(“Neural Dot”);
frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
frame.add(gui);
frame.pack();
frame.setLocationRelativeTo(null);
frame.setVisible(true);
while (true) {
gui.repaint();
dot.run();
Thread.sleep(100);
}
}
}
other file :
import java.util.Random;
public class NeuralNetwork {
private int numInputs;
private int numHidden;
private int numOutputs;
private double[][] inputHiddenWeights;
private double[][] hiddenOutputWeights;
private double[] hiddenBiases;
private double[] outputBiases;
private double learningRate;
public NeuralNetwork(int numInputs, int numHidden, int numOutputs, double learningRate) {
this.numInputs = numInputs;
this.numHidden = numHidden;
this.numOutputs = numOutputs;
this.learningRate = learningRate;
// Initialize weights and biases with random values between -1 and 1
inputHiddenWeights = new double[numInputs][numHidden];
hiddenOutputWeights = new double[numHidden][numOutputs];
hiddenBiases = new double[numHidden];
outputBiases = new double[numOutputs];
Random random = new Random();
for (int i = 0; i < numInputs; i++) {
for (int j = 0; j < numHidden; j++) {
inputHiddenWeights[i][j] = random.nextDouble() * 2 - 1;
}
}
for (int i = 0; i < numHidden; i++) {
for (int j = 0; j < numOutputs; j++) {
hiddenOutputWeights[i][j] = random.nextDouble() * 2 - 1;
}
hiddenBiases[i] = random.nextDouble() * 2 - 1;
}
for (int i = 0; i < numOutputs; i++) {
outputBiases[i] = random.nextDouble() * 2 - 1;
}
}
public double[] feedForward(double[] inputs) {
// Compute hidden layer activations
double[] hiddenLayer = new double[numHidden];
for (int i = 0; i < numHidden; i++) {
double activation = 0;
for (int j = 0; j < numInputs; j++) {
activation += inputs[j] * inputHiddenWeights[j][i];
}
hiddenLayer[i] = sigmoid(activation + hiddenBiases[i]);
}
// Compute output layer activations
double[] outputs = new double[numOutputs];
for (int i = 0; i < numOutputs; i++) {
double activation = 0;
for (int j = 0; j < numHidden; j++) {
activation += hiddenLayer[j] * hiddenOutputWeights[j][i];
}
outputs[i] = sigmoid(activation + outputBiases[i]);
}
return outputs;
}
public void train(double[] inputs, double[] targetOutputs, double reward) {
// Compute feedforward outputs and backpropagate errors
double[] hiddenLayer = new double[numHidden];
for (int i = 0; i < numHidden; i++) {
double activation = 0;
for (int j = 0; j < numInputs; j++) {
activation += inputs[j] * inputHiddenWeights[j][i];
}
hiddenLayer[i] = sigmoid(activation + hiddenBiases[i]);
}
double[] outputs = feedForward(inputs);
double[] outputErrors = new double[numOutputs];
for (int i = 0; i < numOutputs; i++) {
outputErrors[i] = (targetOutputs[i] - outputs[i]) * sigmoidDerivative(outputs[i]);
}
double[] hiddenErrors = new double[numHidden];
for (int i = 0; i < numHidden; i++) {
double error = 0;
for (int j = 0; j < numOutputs; j++) {
error += outputErrors[j] * hiddenOutputWeights[i][j];
}
hiddenErrors[i] = error * sigmoidDerivative(hiddenLayer[i]);
}
// Update weights and biases using errors and learning rate
for (int i = 0; i < numInputs; i++) {
for (int j = 0; j < numHidden; j++) {
inputHiddenWeights[i][j] += learningRate * inputs[i] * hiddenErrors[j];
}
}
for (int i = 0; i < numHidden; i++) {
for (int j = 0; j < numOutputs; j++) {
hiddenOutputWeights[i][j] += learningRate * hiddenLayer[i] * outputErrors[j];
}
hiddenBiases[i] += learningRate * hiddenErrors[i];
}
for (int i = 0; i < numOutputs; i++) {
outputBiases[i] += learningRate * outputErrors[i] * reward;
}
}
private double sigmoid(double x) {
return 1 / (1 + Math.exp(-x));
}
private double sigmoidDerivative(double x) {
return x * (1 - x);
}
}
other file : import java.util.Arrays;
import java.util.Random;
public class NeuralDot {
private static final int VISION_RANGE = 5;
public static final int GRID_SIZE = 100;
private static final int NUM_INPUTS = (2VISION_RANGE + 1) * (2VISION_RANGE + 1) + 2;
private static final int NUM_HIDDEN = 16;
private static final int NUM_OUTPUTS = 3;
private static final double LEARNING_RATE = 0.1;
private static final int NUM_EPISODES = 10000;
public int x;
public int y;
public boolean[][] grid;
private Random random;
private NeuralNetwork neuralNetwork;
public NeuralDot() {
x = GRID_SIZE / 2;
y = GRID_SIZE / 2;
grid = new boolean[GRID_SIZE][GRID_SIZE];
random = new Random();
neuralNetwork = new NeuralNetwork(NUM_INPUTS, NUM_HIDDEN, NUM_OUTPUTS, LEARNING_RATE);
}
public void run() {
for (int episode = 0; episode < NUM_EPISODES; episode++) {
// Reset the grid and place a food dot randomly
resetGrid();
placeFoodDot();
// Play the episode until the dot eats the food dot
while (!grid[x][y]) {
// Get the nearest food dot
int[] foodDot = getNearestFoodDot();
// Compute the inputs to the neural network
double[] inputs = new double[NUM_INPUTS];
int index = 0;
for (int i = x - VISION_RANGE; i <= x + VISION_RANGE; i++) {
for (int j = y - VISION_RANGE; j <= y + VISION_RANGE; j++) {
if (i < 0 || i >= GRID_SIZE || j < 0 || j >= GRID_SIZE) {
inputs[index++] = 0;
} else if (i == x && j == y) {
inputs[index++] = 1;
} else {
inputs[index++] = grid[i][j] ? -1 : 0;
}
}
}
inputs[index++] = foodDot[0] - x;
inputs[index++] = foodDot[1] - y;
// Compute the outputs of the neural network
double[] outputs = neuralNetwork.feedForward(inputs);
// Choose the action with the highest probability
double maxProbability = Double.NEGATIVE_INFINITY;
int action = 0;
for (int i = 0; i < NUM_OUTPUTS; i++) {
if (outputs[i] > maxProbability) {
maxProbability = outputs[i];
action = i;
}
}
// Take the chosen action
switch (action) {
case 0:
moveLeft();
break;
case 1:
moveRight();
break;
case 2:
moveForward();
break;
}
// Compute the reward signal
double reward;
if (grid[x][y]) {
reward = 10;
} else {
reward = -0.1;
}
// Train the neural network on the input-output pair
double[] targetOutputs = new double[NUM_OUTPUTS];
targetOutputs[action] = 1;
neuralNetwork.train(inputs, targetOutputs, reward);
}
}
}
private void resetGrid() {
for (int i = 0; i < GRID_SIZE; i++) {
Arrays.fill(grid[i], false);
}
}
private void placeFoodDot() {
int foodX = random.nextInt(GRID_SIZE);
int foodY = random.nextInt(GRID_SIZE);
grid[foodX][foodY] = true;
}
private int[] getNearestFoodDot() {
int nearestX = -1;
int nearestY = -1;
double nearestDistance = Double.POSITIVE_INFINITY;
for (int i = 0; i < GRID_SIZE; i++) {
for (int j = 0; j < GRID_SIZE; j++) {
if (grid[i][j]) {
double distance = Math.sqrt((i - x)(i - x) + (j - y)(j - y));
if (distance < nearestDistance) {
nearestX = i;
nearestY = j;
nearestDistance = distance;
}
}
}
}
return new int[] {nearestX, nearestY};
}
private void moveLeft() {
if (x > 0)
{
x–;
}
}
private void moveRight() {
if (x < GRID_SIZE - 1) {
x++;
}
}
private void moveForward() {
if (y < GRID_SIZE - 1) {
y++;
}
}
public static void main(String[] args) {
NeuralDot dot = new NeuralDot();
dot.run();
}
}
|
4007b827586f33ed6a5c380c880ec028
|
{
"intermediate": 0.30874916911125183,
"beginner": 0.39288052916526794,
"expert": 0.2983703315258026
}
|
5,514
|
Construct a Turing Machine that computes the addition of two numbers, represented in Unary form. Show the operations in the tape. Draw the transition table and transition diagram.
|
20f45e09fad356bd2157ed2fc31cc5a0
|
{
"intermediate": 0.22598017752170563,
"beginner": 0.15773288905620575,
"expert": 0.6162869334220886
}
|
5,515
|
can u learn this code : import java.awt.Color;
import java.awt.Graphics;
import javax.swing.JFrame;
import javax.swing.JPanel;
public class NeuralDotGUI extends JPanel {
private NeuralDot neuralDot;
private int cellWidth;
private int cellHeight;
public NeuralDotGUI(NeuralDot neuralDot, int cellWidth, int cellHeight) {
this.neuralDot = neuralDot;
this.cellWidth = cellWidth;
this.cellHeight = cellHeight;
}
public void paintComponent(Graphics g) {
super.paintComponent(g);
// Draw grid cells
for (int i = 0; i < NeuralDot.GRID_SIZE; i++) {
for (int j = 0; j < NeuralDot.GRID_SIZE; j++) {
int x = i * cellWidth;
int y = j * cellHeight;
if (neuralDot.grid[i][j]) {
g.setColor(Color.GREEN);
} else {
g.setColor(Color.WHITE);
}
g.fillRect(x, y, cellWidth, cellHeight);
}
}
// Draw dot
g.setColor(Color.RED);
g.fillOval(neuralDot.x * cellWidth, neuralDot.y * cellHeight, cellWidth, cellHeight);
}
public static void main(String[] args) throws InterruptedException {
NeuralDot dot = new NeuralDot();
NeuralDotGUI gui = new NeuralDotGUI(dot, 10, 10);
JFrame frame = new JFrame();
frame.setTitle("Neural Dot");
frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
frame.add(gui);
frame.pack();
frame.setLocationRelativeTo(null);
frame.setVisible(true);
while (true) {
gui.repaint();
dot.run();
Thread.sleep(250);
}
}
}
next file : import java.util.Random;
public class NeuralNetwork {
private int numInputs;
private int numHidden;
private int numOutputs;
private double[][] inputHiddenWeights;
private double[][] hiddenOutputWeights;
private double[] hiddenBiases;
private double[] outputBiases;
private double learningRate;
public NeuralNetwork(int numInputs, int numHidden, int numOutputs, double learningRate) {
this.numInputs = numInputs;
this.numHidden = numHidden;
this.numOutputs = numOutputs;
this.learningRate = learningRate;
// Initialize weights and biases with random values between -1 and 1
inputHiddenWeights = new double[numInputs][numHidden];
hiddenOutputWeights = new double[numHidden][numOutputs];
hiddenBiases = new double[numHidden];
outputBiases = new double[numOutputs];
Random random = new Random();
for (int i = 0; i < numInputs; i++) {
for (int j = 0; j < numHidden; j++) {
inputHiddenWeights[i][j] = random.nextDouble() * 2 - 1;
}
}
for (int i = 0; i < numHidden; i++) {
for (int j = 0; j < numOutputs; j++) {
hiddenOutputWeights[i][j] = random.nextDouble() * 2 - 1;
}
hiddenBiases[i] = random.nextDouble() * 2 - 1;
}
for (int i = 0; i < numOutputs; i++) {
outputBiases[i] = random.nextDouble() * 2 - 1;
}
}
public double[] feedForward(double[] inputs) {
// Compute hidden layer activations
double[] hiddenLayer = new double[numHidden];
for (int i = 0; i < numHidden; i++) {
double activation = 0;
for (int j = 0; j < numInputs; j++) {
activation += inputs[j] * inputHiddenWeights[j][i];
}
hiddenLayer[i] = sigmoid(activation + hiddenBiases[i]);
}
// Compute output layer activations
double[] outputs = new double[numOutputs];
for (int i = 0; i < numOutputs; i++) {
double activation = 0;
for (int j = 0; j < numHidden; j++) {
activation += hiddenLayer[j] * hiddenOutputWeights[j][i];
}
outputs[i] = sigmoid(activation + outputBiases[i]);
}
return outputs;
}
public void train(double[] inputs, double[] targetOutputs, double reward) {
// Compute feedforward outputs and backpropagate errors
double[] hiddenLayer = new double[numHidden];
for (int i = 0; i < numHidden; i++) {
double activation = 0;
for (int j = 0; j < numInputs; j++) {
activation += inputs[j] * inputHiddenWeights[j][i];
}
hiddenLayer[i] = sigmoid(activation + hiddenBiases[i]);
}
double[] outputs = feedForward(inputs);
double[] outputErrors = new double[numOutputs];
for (int i = 0; i < numOutputs; i++) {
outputErrors[i] = (targetOutputs[i] - outputs[i]) * sigmoidDerivative(outputs[i]);
}
double[] hiddenErrors = new double[numHidden];
for (int i = 0; i < numHidden; i++) {
double error = 0;
for (int j = 0; j < numOutputs; j++) {
error += outputErrors[j] * hiddenOutputWeights[i][j];
}
hiddenErrors[i] = error * sigmoidDerivative(hiddenLayer[i]);
}
// Update weights and biases using errors and learning rate
for (int i = 0; i < numInputs; i++) {
for (int j = 0; j < numHidden; j++) {
inputHiddenWeights[i][j] += learningRate * inputs[i] * hiddenErrors[j];
}
}
for (int i = 0; i < numHidden; i++) {
for (int j = 0; j < numOutputs; j++) {
hiddenOutputWeights[i][j] += learningRate * hiddenLayer[i] * outputErrors[j];
}
hiddenBiases[i] += learningRate * hiddenErrors[i];
}
for (int i = 0; i < numOutputs; i++) {
outputBiases[i] += learningRate * outputErrors[i] * reward;
}
}
private double sigmoid(double x) {
return 1 / (1 + Math.exp(-x));
}
private double sigmoidDerivative(double x) {
return x * (1 - x);
}
}
next file : import java.util.Arrays;
import java.util.Random;
public class NeuralDot {
private static final int VISION_RANGE = 5;
public static final int GRID_SIZE = 100;
private static final int NUM_INPUTS = (2*VISION_RANGE + 1) * (2*VISION_RANGE + 1) + 2;
private static final int NUM_HIDDEN = 16;
private static final int NUM_OUTPUTS = 3;
private static final double LEARNING_RATE = 0.1;
private static final int NUM_EPISODES = 10000;
public int x;
public int y;
public boolean[][] grid;
private Random random;
private NeuralNetwork neuralNetwork;
public NeuralDot() {
x = GRID_SIZE / 2;
y = GRID_SIZE / 2;
grid = new boolean[GRID_SIZE][GRID_SIZE];
random = new Random();
neuralNetwork = new NeuralNetwork(NUM_INPUTS, NUM_HIDDEN, NUM_OUTPUTS, LEARNING_RATE);
}
public void run() {
for (int episode = 0; episode < NUM_EPISODES; episode++) {
// Reset the grid and place a food dot randomly
resetGrid();
placeFoodDot();
// Initialize variables for tracking dot movement and reward
int lastX = x;
int lastY = y;
int timeWithoutFood = 0;
double reward;
// Play the episode until the dot eats the food dot
while (!grid[x][y]) {
// Get the nearest food dot
int[] foodDot = getNearestFoodDot();
// Compute the inputs to the neural network
double[] inputs = new double[NUM_INPUTS];
int index = 0;
for (int i = x - VISION_RANGE; i <= x + VISION_RANGE; i++) {
for (int j = y - VISION_RANGE; j <= y + VISION_RANGE; j++) {
if (i < 0 || i >= GRID_SIZE || j < 0 || j >= GRID_SIZE) {
inputs[index++] = 0;
} else if (i == x && j == y) {
inputs[index++] = 1;
} else {
inputs[index++] = grid[i][j] ? -1 : 0;
}
}
}
inputs[index++] = foodDot[0] - x;
inputs[index++] = foodDot[1] - y;
// Compute the outputs of the neural network
double[] outputs = neuralNetwork.feedForward(inputs);
// Choose the action with the highest probability
double maxProbability = Double.NEGATIVE_INFINITY;
int action = 0;
for (int i = 0; i < NUM_OUTPUTS; i++) {
if (outputs[i] > maxProbability) {
maxProbability = outputs[i];
action = i;
}
}
// Take the chosen action
switch (action) {
case 0:
moveLeft();
break;
case 1:
moveRight();
break;
case 2:
moveForward();
break;
}
// Compute the reward signal
if (grid[x][y]) {
reward = 10;
timeWithoutFood = 0;
} else {
reward = -0.1;
if (x == lastX && y == lastY) {
timeWithoutFood++;
reward -= 0.01 * timeWithoutFood;
} else {
timeWithoutFood = 0;
}
}
// Train the neural network on the input-output pair
double[] targetOutputs = new double[NUM_OUTPUTS];
targetOutputs[action] = 1;
neuralNetwork.train(inputs, targetOutputs, reward);
// Update last movement variables
lastX = x;
lastY = y;
}
}
}
private void resetGrid() {
for (int i = 0; i < GRID_SIZE; i++) {
Arrays.fill(grid[i], false);
}
}
private void placeFoodDot() {
int foodX = random.nextInt(GRID_SIZE);
int foodY = random.nextInt(GRID_SIZE);
grid[foodX][foodY] = true;
}
private int[] getNearestFoodDot() {
int nearestX = -1;
int nearestY = -1;
double nearestDistance = Double.POSITIVE_INFINITY;
for (int i = 0; i < GRID_SIZE; i++) {
for (int j = 0; j < GRID_SIZE; j++) {
if (grid[i][j]) {
double distance = Math.sqrt((i - x)*(i - x) + (j - y)*(j - y));
if (distance < nearestDistance) {
nearestX = i;
nearestY = j;
nearestDistance = distance;
}
}
}
}
return new int[] {nearestX, nearestY};
}
private void moveLeft() {
int newX = x - 1;
if (newX < 0) {
newX = 0;
}
grid[x][y] = false;
x = newX;
grid[x][y] = true;
}
private void moveRight() {
int newX = x + 1;
if (newX >= GRID_SIZE) {
newX = GRID_SIZE - 1;
}
grid[x][y] = false;
x = newX;
grid[x][y] = true;
}
private void moveForward() {
int newY = y + 1;
if (newY >= GRID_SIZE) {
newY = GRID_SIZE - 1;
}
grid[x][y] = false;
y = newY;
grid[x][y] = true;
}
public static void main(String[] args) {
NeuralDot dot = new NeuralDot();
dot.run();
}
}
|
09356f8d1fcf1f68a49cbd999b770a53
|
{
"intermediate": 0.31498390436172485,
"beginner": 0.38080090284347534,
"expert": 0.3042151629924774
}
|
5,516
|
a file to update my mods (C:\Users\nilsw\AppData\Roaming\.minecraft\mods) to the latest 1.19.4 version fabric/quilt
|
8b5da4586aff93ba746216e05ba8815c
|
{
"intermediate": 0.4047577679157257,
"beginner": 0.23390014469623566,
"expert": 0.36134207248687744
}
|
5,517
|
Who has been instrumental in your development over the past year?
|
2367ad7e366cae8c298b3b9c8f4ee938
|
{
"intermediate": 0.3112471401691437,
"beginner": 0.27333498001098633,
"expert": 0.4154179096221924
}
|
5,518
|
php if table doesnt exist create table
|
0945032779393b856b4c55d1da1c66f4
|
{
"intermediate": 0.4167487621307373,
"beginner": 0.2890550196170807,
"expert": 0.294196218252182
}
|
5,519
|
package com.example.deezermusicplayer
import CategoriesViewModel
import MusicCategoriesScreen
import android.os.Bundle
import androidx.activity.ComponentActivity
import androidx.activity.compose.setContent
import androidx.compose.foundation.layout.fillMaxWidth
import androidx.compose.foundation.layout.padding
import androidx.compose.material.*
import androidx.compose.runtime.*
import androidx.compose.ui.Modifier
import androidx.navigation.NavController
import androidx.navigation.NavHostController
import androidx.navigation.compose.NavHost
import androidx.navigation.compose.composable
import androidx.navigation.compose.currentBackStackEntryAsState
import androidx.navigation.compose.rememberNavController
import com.example.deezermusicplayer.ui.theme.DeezerMusicPlayerTheme
import androidx.compose.ui.unit.dp
class MainActivity : ComponentActivity() {
private val bottomNavigationItems = listOf(
Screen.Home,
Screen.Favorites
)
override fun onCreate(savedInstanceState: Bundle?) {
super.onCreate(savedInstanceState)
setContent {
DeezerMusicPlayerTheme {
// Set up navigation
val navController = rememberNavController()
val bottomNavigationItems = listOf(
Screen.Home,
Screen.Favorites
)
Scaffold(
bottomBar = {
BottomNavigation {
val navBackStackEntry by navController.currentBackStackEntryAsState()
val currentRoute = navBackStackEntry?.destination?.route
bottomNavigationItems.forEach { screen ->
BottomNavigationItem(
icon = {
Icon(
imageVector = screen.icon,
contentDescription = null
)
},
selected = currentRoute == screen.route,
onClick = {
navController.navigate(screen.route) {
// Pop up to the start destination of the current graph to
// avoid building up a large stack of destinations
// on the back stack as users select items
popUpTo(navController.graph.startDestinationId) {
saveState = true
}
// Avoid multiple copies of the same destination when
// reselecting the same item
launchSingleTop = true
restoreState = true
}
},
label = {
Text(text = screen.title)
}
)
}
}
},
content = { paddingValues ->
NavigationHost(
navController = navController,
modifier = Modifier.padding(paddingValues)
)
}
)
}
}
}
@Composable
fun NavigationHost(
navController: NavController,
modifier: Modifier = Modifier,
) {
val categoriesViewModel = remember { CategoriesViewModel() }
val categories by categoriesViewModel.categories.collectAsState() // use collectAsState here to collect the latest state
NavHost(navController = navController as NavHostController, startDestination = Screen.Home.route) {
composable(Screen.Home.route) {
HomeScreen(categories = categories, navController = navController, modifier = modifier)
}
composable(Screen.Favorites.route) {
FavoritesScreen(categories = categories, navController = navController, modifier = modifier)
}
}
}
@Composable
fun HomeScreen(
categories: List<Category>,
navController: NavController,
modifier: Modifier = Modifier
) {
Scaffold(
topBar = {
Text(
text = "Home",
modifier = Modifier.fillMaxWidth().padding(8.dp),
style = MaterialTheme.typography.h5
)
},
bottomBar = {
BottomNavigation {
val navBackStackEntry by navController.currentBackStackEntryAsState()
val currentRoute = navBackStackEntry?.destination?.route
bottomNavigationItems.forEach { screen ->
BottomNavigationItem(
icon = {
Icon(
imageVector = screen.icon,
contentDescription = null
)
},
selected = currentRoute == screen.route,
onClick = {
navController.navigate(screen.route) {
// Pop up to the start destination of the current graph to
// avoid building up a large stack of destinations
// on the back stack as users select items
popUpTo(navController.graph.startDestinationId) {
saveState = true
}
// Avoid multiple copies of the same destination when
// reselecting the same item
launchSingleTop = true
restoreState = true
}
},
label = {
Text(text = screen.title)
}
)
}
}
}
) {
MusicCategoriesScreen(
categories = categories,
onCategorySelected = { category: Category -> /* Handle category selected */ },
modifier = modifier
)
}
}
@Composable
fun FavoritesScreen(categories: List<Category>, navController: NavController, modifier: Modifier = Modifier) {
}
}
-> this is my MainActivity.kt . I have this error -> Content padding parameter it is not used:150 . Why is this and can you fix it ? Also if you find anything meaningless in the code share with me and suggest a solution to it.
|
38429501ae684a00a63941a33292d64d
|
{
"intermediate": 0.3637426197528839,
"beginner": 0.42635196447372437,
"expert": 0.20990537106990814
}
|
5,520
|
Casting string to float
|
8d30e9a56e202bc59fc9d839ec3d33cb
|
{
"intermediate": 0.3360616862773895,
"beginner": 0.32794392108917236,
"expert": 0.3359944522380829
}
|
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