row_id
int64 0
48.4k
| init_message
stringlengths 1
342k
| conversation_hash
stringlengths 32
32
| scores
dict |
|---|---|---|---|
3,212
|
spanCount implementation in Leanback GridLayoutManager
|
37d7e73dd8d953a83e88fea35d464040
|
{
"intermediate": 0.5179691314697266,
"beginner": 0.2146139293909073,
"expert": 0.26741689443588257
}
|
3,213
|
spanCount implementation in Leanback GridLayoutManger
|
ba81cb6f7a7637b1b6b7b6e8925642e1
|
{
"intermediate": 0.4646989703178406,
"beginner": 0.2218932956457138,
"expert": 0.31340768933296204
}
|
3,214
|
c++ divide all values of 2d array by 10
|
46f65ffa5cf27457198df4484b7efda8
|
{
"intermediate": 0.3285934627056122,
"beginner": 0.35351282358169556,
"expert": 0.3178936541080475
}
|
3,215
|
The code:
import tkinter as tk
import requests
def get_weather():
# Prompt user for location information
country = country_entry.get()
city = city_entry.get()
# Make API request to get weather data for location
url = f"https://api.openweathermap.org/data/2.5/weather?q={city},{country}&units=metric&appid=4d8860b07dbeb20131a1f88fdbc060bc"
response = requests.get(url)
if response.status_code == 200:
data = response.json()
temp = data['main']['temp']
weather = data['weather'][0]['description']
# Provide recommendation based on temperature
recommendations = []
if temp > 30:
recommendations.append("It's very hot! Wear something light and breathable.")
elif temp > 25:
recommendations.append("It's hot! Wear something light and breathable.")
elif temp > 20:
recommendations.append("It's warm. Shorts and a t-shirt should be good.")
elif temp > 10:
recommendations.append("It's chilly. Bring a light jacket or sweater.")
else:
recommendations.append("It's cold! Bundle up with a coat, scarf, and gloves.")
# Check for precipitation and add appropriate recommendation
if 'rain' in weather:
recommendations.append("Don't forget to take an umbrella if it's raining.")
if 'snow' in weather:
recommendations.append("Wear warm, waterproof shoes and bring a hat and gloves.")
elif 'snow' in weather:
recommendations.append("Wear warm, waterproof shoes and bring a hat and gloves.")
# Check for wind and add appropriate recommendation
if 'wind' in weather:
recommendations.append("It's windy. Wear something that won't fly away!")
# Check for extreme weather conditions and add appropriate recommendation
if 'storm' in weather or 'hurricane' in weather or 'tornado' in weather:
recommendations.append("It's dangerous outside. Stay indoors if possible!")
# Create recommendation string
recommendation_str = "\n".join(recommendations)
result_label.config(text=f"Current weather in {city}, {country}: {temp:.1f} degrees C ({weather}).\n{recommendation_str}")
else:
result_label.config(text="Unable to get weather data for specified location.")
# Create GUI window
window = tk.Tk()
window.title("Weather App")
# Create labels and entries
country_label = tk.Label(text="Country:")
country_entry = tk.Entry(width=25)
city_label = tk.Label(text="City:")
city_entry = tk.Entry(width=25)
result_label = tk.Label(font=("Arial", 12), wraplength=400)
# Create button to get weather information
weather_button = tk.Button(text="Get Weather", command=get_weather)
# Add labels, entries, and button to window
country_label.pack()
country_entry.pack()
city_label.pack()
city_entry.pack()
weather_button.pack()
result_label.pack()
# Run the GUI window
window.mainloop()
I need you to add a feature for that code that will tell you what do wear in the rest of the day. for example, if there is going to be rain at night it will also tell the user that he should consider taking an umbrella because its going to be rainy in ( time ).
|
769a5b228e1a2cf05ba25a97bed34333
|
{
"intermediate": 0.3779017925262451,
"beginner": 0.3432105481624603,
"expert": 0.27888765931129456
}
|
3,216
|
I want you to act as a Text Adventure game, and I want you to only reply with the game output inside one unique code block, and nothing else.
This will be a moderately challenging game and some choices can lead to instant death, but I can always re-do the last fatal choice to continue the game if I want to. I will type commands and dialog, and you will only reply with what the text adventure game would show.
Provide at least 6 options for me to choose from every turn. Option number 2 that will always be available is: 'Attack with weapon' unless I ever lose my weapon, in which case it will change to: 'Attack with bare hands'. An Ascii overview map will always be available as option number 1.
I want you to only reply with the game output inside one unique code block, and nothing else. Each option to choose will be assigned a number 1-6 and I can type and respond with the number to pick that choice. The game should always show one screen, and always wait for me to enter the next command.
The game should always show "health", "location", "description", "inventory", and "possible commands"
Starting inventory has 4 random items, but they are all items based on what would make sense to have as inventory in this story, but be sure to include a weapon as one of the items.
Do not write explanations.
Do not type commands unless I instruct you to do so. It is imperative that these rules are followed without exception.
I can do whatever I want that is based on the possible commands. I can attack any character in the story and other characters will respond realistically, depending on their relationship to the character and/or the context of the events itself.
The setting will be based on A Song of Ice and Fire, I am recently knighted in this world and I am talking to my lord about my next plans.
|
edb0b5c006f4f8144c0e1666213645ec
|
{
"intermediate": 0.40157029032707214,
"beginner": 0.2698935270309448,
"expert": 0.3285362124443054
}
|
3,217
|
c++ get dimensions of 2d arary
|
f89b252c7545a7a0cc594e8ceb0e5569
|
{
"intermediate": 0.32636234164237976,
"beginner": 0.33561787009239197,
"expert": 0.33801978826522827
}
|
3,218
|
write me a facebook post content asking programmers that are intersted to be partners of succes for a new start up called GGEG which is in incubation at this time to be in and fill the application
|
1af13bb88f4a01e46f819d23747b7d55
|
{
"intermediate": 0.309589147567749,
"beginner": 0.16026180982589722,
"expert": 0.5301491022109985
}
|
3,219
|
c++ print time to run program
|
30325d26ae0cfbab43338f23da04d961
|
{
"intermediate": 0.32201337814331055,
"beginner": 0.2912527322769165,
"expert": 0.3867338299751282
}
|
3,220
|
how to echo the env value NEXT_PUBLIC_SUPABASE_URL
|
277b44ef47270e9a3d3df3058a91bf13
|
{
"intermediate": 0.38789936900138855,
"beginner": 0.1895054429769516,
"expert": 0.42259520292282104
}
|
3,221
|
So I have this problem in vue 3 where I remove one item from a list and it rerenders the list I and I use any data on the list as the items are back to default, I'm using Vue 3 composition api ,script setup> syntax
|
9b81462043d9cefc3df4f19d42a52654
|
{
"intermediate": 0.673535168170929,
"beginner": 0.26619258522987366,
"expert": 0.0602722130715847
}
|
3,222
|
como hago visible en el inspector EquipedItem(item) using System.Collections;
using System.Collections.Generic;
using DevionGames.UIWidgets;
using UnityEngine;
namespace DevionGames.InventorySystem
{
public class EquipmentHandler : MonoBehaviour
{
[SerializeField]
private string m_WindowName = "Equipment";
[SerializeField]
private ItemDatabase m_Database;
[SerializeField]
private List<EquipmentBone> m_Bones= new List<EquipmentBone>();
public List<EquipmentBone> Bones
{
get { return this.m_Bones; }
set { this.m_Bones = value; }
}
[SerializeField]
private List<VisibleItem> m_VisibleItems= new List<VisibleItem>();
public List<VisibleItem> VisibleItems {
get { return this.m_VisibleItems; }
set { this.m_VisibleItems = value; }
}
private ItemContainer m_EquipmentContainer;
private void Start()
{
this.m_EquipmentContainer = WidgetUtility.Find<ItemContainer>(this.m_WindowName);
if (this.m_EquipmentContainer != null)
{
for (int i = 0; i < this.m_VisibleItems.Count; i++)
{
this.m_VisibleItems[i].enabled = false;
}
this.m_EquipmentContainer.OnAddItem += OnAddItem;
this.m_EquipmentContainer.OnRemoveItem += OnRemoveItem;
UpdateEquipment();
if (InventoryManager.current != null) {
InventoryManager.current.onDataLoaded.AddListener(UpdateEquipment);
}
}
}
private void OnAddItem(Item item, Slot slot)
{
if (item != null && item is EquipmentItem)
{
EquipItem(item as EquipmentItem);
}
}
private void OnRemoveItem(Item item, int amount, Slot slot)
{
if (item != null && item is EquipmentItem)
{
UnEquipItem(item as EquipmentItem);
}
}
public void EquipItem(EquipmentItem item)
{
foreach (ObjectProperty property in item.GetProperties())
{
if (property.SerializedType == typeof(int) || property.SerializedType == typeof(float))
{
float value = System.Convert.ToSingle(property.GetValue());
SendMessage("AddModifier", new object[] { property.Name, value, (value <= 1f && value >= -1f) ? 1 : 0, item }, SendMessageOptions.DontRequireReceiver);
}
}
for (int i = 0; i < this.m_VisibleItems.Count; i++) {
VisibleItem visibleItem = this.m_VisibleItems[i];
if (visibleItem.item.Id == item.Id) {
visibleItem.OnItemEquip(item);
return;
}
}
StaticItem staticItem = gameObject.AddComponent<StaticItem>();
staticItem.item = InventoryManager.Database.items.Find(x=>x.Id== item.Id);
VisibleItem.Attachment attachment = new VisibleItem.Attachment();
attachment.prefab = item.EquipPrefab;
attachment.region = item.Region[0];
staticItem.attachments = new VisibleItem.Attachment[1] { attachment};
staticItem.OnItemEquip(item);
}
public void UnEquipItem(EquipmentItem item)
{
foreach (ObjectProperty property in item.GetProperties())
{
if (property.SerializedType == typeof(int) || property.SerializedType == typeof(float))
{
SendMessage("RemoveModifiersFromSource", new object[] { property.Name, item }, SendMessageOptions.DontRequireReceiver);
}
}
for (int i = 0; i < this.m_VisibleItems.Count; i++)
{
VisibleItem visibleItem = this.m_VisibleItems[i];
if (visibleItem.item.Id == item.Id)
{
visibleItem.OnItemUnEquip(item);
break;
}
}
}
public void UpdateEquipment()
{
for (int i = 0; i < this.m_VisibleItems.Count; i++)
{
VisibleItem visibleItem = this.m_VisibleItems[i];
visibleItem.OnItemUnEquip(visibleItem.item);
}
EquipmentItem[] containerItems = this.m_EquipmentContainer.GetItems<EquipmentItem>();
foreach (EquipmentItem item in containerItems)
{
EquipItem(item);
}
}
public Transform GetBone(EquipmentRegion region) {
EquipmentBone bone = Bones.Find(x => x.region == region);
if (bone == null || bone.bone == null) {
Debug.LogWarning("Missing Bone Map configuration: "+gameObject.name);
return null;
}
return bone.bone.transform;
}
[System.Serializable]
public class EquipmentBone{
public EquipmentRegion region;
public GameObject bone;
}
}
}
|
d4327a7b03b19391b18be5bafbde5420
|
{
"intermediate": 0.3175365626811981,
"beginner": 0.47577837109565735,
"expert": 0.20668509602546692
}
|
3,224
|
Christian Vaughn is the main character of this fighting game similar to Def Jam: Vendetta.
Christian aswell as the enemies have hitpoints. When reduced to 0, the character is knocked out.
The characters each can do one action per round.
Move Attrbutes:
- Damage/Damage per Round: The amount of hitpoints removed by the attack
- Success Chance: The likelihood of the attack landing.
- Escape Chance: The likelihood of escaping from the submissin hold
- Side Effect: Special Moves have lingering side effects, buffing the attacker or debuffing the recipient
---
Main Character:
Christian Vaughn:
Hitpoints: 120
Move List:
Normal Moves:
- Straight Punch (80% Success Chance, 10 Damage)
- Body Blow (90% Success Chance, 5 Damage)
- Uppercut (70% Success Chance, 15 Damage)
- Thrust Kick (80% Success Chance, 10 Damage)
- Low Kick (90% Success Chance, 5 Damage)
- Shoulder Throw (70% Success Chance, 15 Damage)
- Suplex (60% Success Chance, 20 Damage)
- Headlock (70% Success Chance, 5 Damage per Round, 70% Escape Chance, Recipient is locked in a submission)
Special Moves:
- Clothesline (60% Success Chance, 20 Damage, Recipient Dizzy for 1 round)
- Spear Tackle (50% Success Chance, 25 Damage, Recipient Stunned for 1 round)
- Powerbomb (30% Success Chance, 35 Damage)
Special Skill:
- All attacks have a 5% increased Success Chance
---
Enemies:
"The Bouncer" Vito Hernandez
Hitpoints: 130
Move List:
Normal Moves:
- Straight Punch (80% Success Chance, 10 Damage)
- Body Blow (90% Success Chance, 5 Damage)
- Uppercut (70% Success Chance, 15 Damage)
- Backhand Slap (90% Success Chance, 5 Damage)
- Overhead Toss (60% Success Chance, 20 Damage)
- Headlock Takedown (70% Success Chance, 15 Damage)
- DDT (60% Success Chance, 20 Damage)
- Sleeper Hold (70% Success Chance, 5 Damage per Round, 70% Escape Chance, Recipient is locked in a submission)
Special Moves:
- Full Body Tackle (60% Success Chance, 20 Damage)
- Backbreaker (50% Success Chance, 25 Damage, Recipient Stunned for 1 round)
- Giant Swing (30% Success Chance, 35 Damage, Recipient Dizzy for 2 rounds)
Special Skill:
- All attacks do 5 more Damage
---
"The Exotic Dancer" Selina Morano
Hitpoints: 100
Move List:
Normal Moves:
- Slap (90% Success Chance, 5 Damage)
- Bkachand Slap (90% Success Chance, 5 Damage)
- Axe Kick (70% Success Chance, 15 Damage)
- High Kick (80% Success Chance, 10 Damage)
- Spinning Kick (70% Success Chance, 15 Damage)
- Hurricanrana (60% Success Chance, 20 Damage)
- Headscissors (60% Success Chance, 10 Damage per Round, 60% Escape Chance, Recipient is locked in a submission)
- Bodyscissors (60% Success Chance, 10 Damage per Round, 60% Escape Chance, Recipient is locked in a submission)
Special Moves:
- Booty Grinding (80% Success Chance, 0 Damage, Recipient is Stunned for 1 Round and Dizzy for 2 Rounds)
- Breast Smother Bodyscissors (40% Success Chance, 20 Damage per Round, 40% Escape Chance, , Recipient is locked in a submission)
- Reverse Headscissors (30% Success Chance, 25 Damage per Round, 30% Escape Chance, , Recipient is locked in a submission)
Special Skill:
- All submission move haves have a 5% increased Success Chance and a 5% decreased Escape Chance
---
Help me program a text based fighting game, with these characters and their attacks.
|
7376e0dc892fcd84af3fefa7afd0f630
|
{
"intermediate": 0.38555189967155457,
"beginner": 0.40819981694221497,
"expert": 0.20624825358390808
}
|
3,225
|
How to create 2 nested Wireguard tunnels on Windows?
|
f923f39b1e190da78d4dc17e09af1007
|
{
"intermediate": 0.3028445243835449,
"beginner": 0.19725920259952545,
"expert": 0.4998963177204132
}
|
3,226
|
explain the intuition behind bivariate normal distribution gradually and intuitively step by step.
|
1f86314bd50627bf7bcc32516f4a56e7
|
{
"intermediate": 0.34032854437828064,
"beginner": 0.2564043700695038,
"expert": 0.40326714515686035
}
|
3,227
|
give me a high level code to implement reinforcement learning in drone swarming
|
95cbe6458701599c70c490a73d1c304f
|
{
"intermediate": 0.09362854063510895,
"beginner": 0.04632016643881798,
"expert": 0.8600512742996216
}
|
3,228
|
Перепиши, пожалуйста, данный код нейронной сети "многослойный персептрон" таким образом, чтобы он научился распознавать изображения 10 цифр (от 0 до 9) в нормальной ориентации, заданные векторами длинной 35 элементов каждый (вектор, на самом деле, является матрицей 5 * 7, развёрнутой вектор). Данные для обучения (датасет) находятся в файле SET1.CSV.
Содержание SET1.CSV (10 цифр -- от 0 до 9):
0;1;1;1;0;1;0;0;0;1;1;0;0;0;1;1;0;0;0;1;1;0;0;0;1;1;0;0;0;1;0;1;1;1;0;
0;0;1;0;0;0;1;1;0;0;0;0;1;0;0;0;0;1;0;0;0;0;1;0;0;0;0;1;0;0;0;1;1;1;0;
0;1;1;1;0;1;0;0;0;1;0;0;0;1;0;0;0;1;0;0;0;1;0;0;0;1;0;0;0;0;1;1;1;1;1;
0;1;1;1;0;1;0;0;0;1;0;0;0;0;1;0;0;1;1;0;0;0;0;0;1;1;0;0;0;1;0;1;1;1;0;
0;0;0;1;0;0;0;1;1;0;0;1;0;1;0;1;0;0;1;0;1;1;1;1;1;0;0;0;1;0;0;0;0;1;0;
1;1;1;1;1;1;0;0;0;0;1;1;1;1;0;0;0;0;0;1;0;0;0;0;1;1;0;0;0;1;0;1;1;1;0;
0;0;1;1;1;0;1;0;0;0;1;0;0;0;0;1;1;1;1;0;1;0;0;0;1;1;0;0;0;1;0;1;1;1;0;
1;1;1;1;1;0;0;0;0;1;0;0;0;0;1;0;0;0;1;0;0;0;1;0;0;0;1;0;0;0;0;1;0;0;0;
0;1;1;1;0;1;0;0;0;1;1;0;0;0;1;0;1;1;1;0;1;0;0;0;1;1;0;0;0;1;0;1;1;1;0;
0;1;1;1;0;1;0;0;0;1;1;0;0;0;1;1;1;1;1;1;0;0;0;1;0;0;0;1;0;0;0;1;0;0;0;
Код нейронной сети, который следует переписать по поставленную задачу:
|
553a9bf94789637797c264931128997c
|
{
"intermediate": 0.29952558875083923,
"beginner": 0.39512187242507935,
"expert": 0.3053525686264038
}
|
3,229
|
I want to install a button symbolized by the fixed whatsapp icon on the right side in the bottom corner of the site that redirects to whatsapp
|
320e801b4d999fc6a98ebb73c080833a
|
{
"intermediate": 0.352934867143631,
"beginner": 0.2799745500087738,
"expert": 0.3670905530452728
}
|
3,230
|
Christian Vaughn is the main character of this fighting game similar to Def Jam: Vendetta.
Christian aswell as the enemies have hitpoints. When reduced to 0, the character is knocked out.
The characters each can do one action per round.
Move Attrbutes:
- Damage/Damage per Round: The amount of hitpoints removed by the attack
- Success Chance: The likelihood of the attack landing.
- Escape Chance: The likelihood of escaping from the submissin hold
- Side Effect: Special Moves have lingering side effects, buffing the attacker or debuffing the recipient
---
Main Character:
Christian Vaughn:
Hitpoints: 120
Move List:
Normal Moves:
- Straight Punch (80% Success Chance, 10 Damage)
- Body Blow (90% Success Chance, 5 Damage)
- Uppercut (70% Success Chance, 15 Damage)
- Thrust Kick (80% Success Chance, 10 Damage)
- Low Kick (90% Success Chance, 5 Damage)
- Shoulder Throw (70% Success Chance, 15 Damage)
- Suplex (60% Success Chance, 20 Damage)
- Headlock (70% Success Chance, 5 Damage per Round, 70% Escape Chance, Recipient is locked in a submission)
Special Moves:
- Clothesline (60% Success Chance, 20 Damage, Recipient Dizzy for 1 round)
- Spear Tackle (50% Success Chance, 25 Damage, Recipient Stunned for 1 round)
- Powerbomb (30% Success Chance, 35 Damage)
Special Skill:
- All attacks have a 5% increased Success Chance
---
Enemies:
"The Bouncer" Vito Hernandez
Hitpoints: 130
Move List:
Normal Moves:
- Straight Punch (80% Success Chance, 10 Damage)
- Body Blow (90% Success Chance, 5 Damage)
- Uppercut (70% Success Chance, 15 Damage)
- Backhand Slap (90% Success Chance, 5 Damage)
- Overhead Toss (60% Success Chance, 20 Damage)
- Headlock Takedown (70% Success Chance, 15 Damage)
- DDT (60% Success Chance, 20 Damage)
- Sleeper Hold (70% Success Chance, 5 Damage per Round, 70% Escape Chance, Recipient is locked in a submission)
Special Moves:
- Full Body Tackle (60% Success Chance, 20 Damage)
- Backbreaker (50% Success Chance, 25 Damage, Recipient Stunned for 1 round)
- Giant Swing (30% Success Chance, 35 Damage, Recipient Dizzy for 2 rounds)
Special Skill:
- All attacks do 5 more Damage
---
"The Exotic Dancer" Selina Morano
Hitpoints: 100
Move List:
Normal Moves:
- Slap (90% Success Chance, 5 Damage)
- Bkachand Slap (90% Success Chance, 5 Damage)
- Axe Kick (70% Success Chance, 15 Damage)
- High Kick (80% Success Chance, 10 Damage)
- Spinning Kick (70% Success Chance, 15 Damage)
- Hurricanrana (60% Success Chance, 20 Damage)
- Headscissors (60% Success Chance, 10 Damage per Round, 60% Escape Chance, Recipient is locked in a submission)
- Bodyscissors (60% Success Chance, 10 Damage per Round, 60% Escape Chance, Recipient is locked in a submission)
Special Moves:
- Booty Grinding (80% Success Chance, 0 Damage, Recipient is Stunned for 1 Round and Dizzy for 2 Rounds)
- Breast Smother Bodyscissors (40% Success Chance, 20 Damage per Round, 40% Escape Chance, , Recipient is locked in a submission)
- Reverse Headscissors (30% Success Chance, 25 Damage per Round, 30% Escape Chance, , Recipient is locked in a submission)
Special Skill:
- All submission move haves have a 5% increased Success Chance and a 5% decreased Escape Chance
---
Help me program a text based fighting game, with these characters and their attacks.
|
b8c2ed5b627a2ada10c6233dc96493df
|
{
"intermediate": 0.38555189967155457,
"beginner": 0.40819981694221497,
"expert": 0.20624825358390808
}
|
3,231
|
Christian Vaughn is the main character of this fighting game similar to Def Jam: Vendetta.
Christian aswell as the enemies have hitpoints. When reduced to 0, the character is knocked out.
The characters each can do one action per round.
Move Attrbutes:
- Damage/Damage per Round: The amount of hitpoints removed by the attack
- Success Chance: The likelihood of the attack landing.
- Escape Chance: The likelihood of escaping from the submissin hold
- Side Effect: Special Moves have lingering side effects, buffing the attacker or debuffing the recipient
---
Main Character:
Christian Vaughn:
Hitpoints: 120
Move List:
Normal Moves:
- Straight Punch (80% Success Chance, 10 Damage)
- Body Blow (90% Success Chance, 5 Damage)
- Uppercut (70% Success Chance, 15 Damage)
- Thrust Kick (80% Success Chance, 10 Damage)
- Low Kick (90% Success Chance, 5 Damage)
- Shoulder Throw (70% Success Chance, 15 Damage)
- Suplex (60% Success Chance, 20 Damage)
- Headlock (70% Success Chance, 5 Damage per Round, 70% Escape Chance, Recipient is locked in a submission)
Special Moves:
- Clothesline (60% Success Chance, 20 Damage, Recipient Dizzy for 1 round)
- Spear Tackle (50% Success Chance, 25 Damage, Recipient Stunned for 1 round)
- Powerbomb (30% Success Chance, 35 Damage)
Special Skill:
- All attacks have a 5% increased Success Chance
---
Enemies:
"The Bouncer" Vito Hernandez
Hitpoints: 130
Move List:
Normal Moves:
- Straight Punch (80% Success Chance, 10 Damage)
- Body Blow (90% Success Chance, 5 Damage)
- Uppercut (70% Success Chance, 15 Damage)
- Backhand Slap (90% Success Chance, 5 Damage)
- Overhead Toss (60% Success Chance, 20 Damage)
- Headlock Takedown (70% Success Chance, 15 Damage)
- DDT (60% Success Chance, 20 Damage)
- Sleeper Hold (70% Success Chance, 5 Damage per Round, 70% Escape Chance, Recipient is locked in a submission)
Special Moves:
- Full Body Tackle (60% Success Chance, 20 Damage)
- Backbreaker (50% Success Chance, 25 Damage, Recipient Stunned for 1 round)
- Giant Swing (30% Success Chance, 35 Damage, Recipient Dizzy for 2 rounds)
Special Skill:
- All attacks do 5 more Damage
---
"The Exotic Dancer" Selina Morano
Hitpoints: 100
Move List:
Normal Moves:
- Slap (90% Success Chance, 5 Damage)
- Bkachand Slap (90% Success Chance, 5 Damage)
- Axe Kick (70% Success Chance, 15 Damage)
- High Kick (80% Success Chance, 10 Damage)
- Spinning Kick (70% Success Chance, 15 Damage)
- Hurricanrana (60% Success Chance, 20 Damage)
- Headscissors (60% Success Chance, 10 Damage per Round, 60% Escape Chance, Recipient is locked in a submission)
- Bodyscissors (60% Success Chance, 10 Damage per Round, 60% Escape Chance, Recipient is locked in a submission)
Special Moves:
- Booty Grinding (80% Success Chance, 0 Damage, Recipient is Stunned for 1 Round and Dizzy for 2 Rounds)
- Breast Smother Bodyscissors (40% Success Chance, 20 Damage per Round, 40% Escape Chance, , Recipient is locked in a submission)
- Reverse Headscissors (30% Success Chance, 25 Damage per Round, 30% Escape Chance, , Recipient is locked in a submission)
Special Skill:
- All submission move haves have a 5% increased Success Chance and a 5% decreased Escape Chance
---
Help me program a text based fighting game, with these characters and their attacks.
|
237e15d80e548c1df6b9c4349ed15aaa
|
{
"intermediate": 0.38555189967155457,
"beginner": 0.40819981694221497,
"expert": 0.20624825358390808
}
|
3,232
|
I am currently trying to make a compact serialization system for online play for my game. The client sends the player's keypresses to the server, and the server updates the player's character based on their input. Then, the server seralizes the player's state and sends it to the client. The client serializes the player's state and compares it with the player's state received from the server. The problem is that some components of the player are supposed to be identical while some aren't. Do you have any suggestions on how to cleanly handle the differences between the two states?
|
ed29cdbb9e3ecd205f45803b98003ca3
|
{
"intermediate": 0.3862563669681549,
"beginner": 0.2924221158027649,
"expert": 0.3213215172290802
}
|
3,233
|
Vue 3 <script setup> syntax, Invalid property scrollTrigger set to .c Missing plugin? gsap.registerPlugin() even though .c is a class and the plugin is registered in a Vue 3 onMounted function, give me example code to fix the issue.
|
94ccfd149aa5c703062814d534f0dc9f
|
{
"intermediate": 0.526299774646759,
"beginner": 0.35542282462120056,
"expert": 0.1182774156332016
}
|
3,234
|
Can you represent a 16 byte MD5 hash as a struct in C# in a way that is fast without storing memory on the heap or requiring unsafe code?
|
14869116c265be2d5dd157c3a385e2c2
|
{
"intermediate": 0.5063639283180237,
"beginner": 0.10572919994592667,
"expert": 0.38790690898895264
}
|
3,235
|
give me a reinforcement learning code fro drone swarmig and how to run it in simulator
|
73074076bd9bc026a35263230262c649
|
{
"intermediate": 0.05495258420705795,
"beginner": 0.04287835955619812,
"expert": 0.9021690487861633
}
|
3,236
|
Hi. How can I generate a random 1024bit prime number in Python?
|
99f970dfa41710dd6f73eadac617e50b
|
{
"intermediate": 0.28483253717422485,
"beginner": 0.12181471288204193,
"expert": 0.5933527946472168
}
|
3,237
|
напиши код для телеграмм бота с реферальной системой на python-telegram-bot с использованием базы данных sqlite3. При вводе /start пользователю выводится его реферальный код, кол-во приглашенных им пользователей, а также их имена. Приглашения происходят по команде /referal и 1 аргументу в виде реферального кода. Надо сделать так, чтобы пользователь не мог использовать свой реферальный код, другой пользователь не мог быть приглашенным несколько раз, а также не мог переходить к другим рефералам после присоединения.
|
c2158c43eaa9151133f73f5404a8faf8
|
{
"intermediate": 0.34873655438423157,
"beginner": 0.31949666142463684,
"expert": 0.33176669478416443
}
|
3,238
|
c++ calculate time elapsed chrono
|
683eb27fe76129a3a4e357f773e29946
|
{
"intermediate": 0.3062494397163391,
"beginner": 0.36895596981048584,
"expert": 0.32479462027549744
}
|
3,239
|
Create non-malicious code in .vbs format which (when executed by the user) causes the a series of beeps to be heard whilst opening 10 notepads with the words "RUN!!!" written on them, the noise stops when closed by the user.
|
fb7616eaac7ec9c871bb1bfd6214b908
|
{
"intermediate": 0.2973296642303467,
"beginner": 0.17098656296730042,
"expert": 0.5316837430000305
}
|
3,240
|
Dim counter, pad
counter = 0
strMessage = “RUN!!!”
'Open 10 notepads with “RUN!!!” in them
Do Until counter = 10
Set pad = CreateObject(“WScript.Shell”)
pad.Run(“notepad”)
WScript.Sleep 1000 'wait for the notepad to open
pad.SendKeys strMessage
counter = counter + 1
Loop
'Set background color to dark red
Set oShell = CreateObject(“WScript.Shell”)
oShell.RegWrite “HKCU\Control Panel\Colors\Background”, “64 00 00”
'Beep continuously until the script is terminated from the Task Manager
Do While True
For i = 1 To 5 'Beep 5 times
Beep
WScript.Sleep 1000
Next
If CheckTaskManager() = False Then
Exit Do
End If
Loop
'Reset background color to default
oShell.RegDelete “HKCU\Control Panel\Colors\Background”
Function Beep()
dim objShell
Set objShell = Wscript.CreateObject(“Wscript.Shell”)
objShell.Run “CMD /C ““Echo vbTab & Chr(7)”””, 0, True
End Function
Function CheckTaskManager()
Set wmi = GetObject(“winmgmts:” & “{impersonationLevel=impersonate}!\.\root\cimv2”)
Set ProcessList = wmi.ExecQuery(“SELECT * FROM Win32_Process”)
For Each Process In ProcessList
If InStr(Process.Name, “wscript.exe”) And InStr(Process.CommandLine, WScript.ScriptFullName) Then
CheckTaskManager = True
Exit Function
End If
Next
CheckTaskManager = False
End Function
|
5a79db11542dfa4c74d7972cb4ff94f9
|
{
"intermediate": 0.2522251307964325,
"beginner": 0.5770082473754883,
"expert": 0.170766681432724
}
|
3,241
|
here is some code and I will ask you to make some changes
|
9c0056fa2fe5018ddfbc253f9c68386d
|
{
"intermediate": 0.28742629289627075,
"beginner": 0.3764428496360779,
"expert": 0.336130827665329
}
|
3,242
|
Write a java program for solving traveling sales person’s problem using Dynamic programming algorithm.
|
1e5e5a8eb2707329d021c0c71eec3382
|
{
"intermediate": 0.1564313769340515,
"beginner": 0.08679770678281784,
"expert": 0.7567709684371948
}
|
3,243
|
Write a java program for solving traveling sales person’s problem using the back tracking algorithm.
|
3dddede22b7baf03769a47a6af79c776
|
{
"intermediate": 0.187069833278656,
"beginner": 0.07641856372356415,
"expert": 0.7365115880966187
}
|
3,244
|
Write a java program for solving traveling sales person’s problem using the Branch and Bound algorithm.
|
16fb30cab0cb074037908b2d114404d3
|
{
"intermediate": 0.20585140585899353,
"beginner": 0.07066330313682556,
"expert": 0.7234852910041809
}
|
3,245
|
quiero que cuando se llame a la funcion "public void EquipItem(EquipmentItem item)" de "EquipmentHandler" se ejecute la funcion "SetActiveHolster" de "Hoslters", solo quiero llamar a "SetActiveHolster" sin verificar nada mas, ya se hace en "Holsters", te mando primero "EquipmentHandler" y el segundo "Hoslters". el primero using System.Collections;
using System.Collections.Generic;
using DevionGames.UIWidgets;
using UnityEngine;
namespace DevionGames.InventorySystem
{
public class EquipmentHandler : MonoBehaviour
{
[SerializeField]
private string m_WindowName = "Equipment";
[SerializeField]
private ItemDatabase m_Database;
[SerializeField]
private List<EquipmentBone> m_Bones= new List<EquipmentBone>();
public List<EquipmentBone> Bones
{
get { return this.m_Bones; }
set { this.m_Bones = value; }
}
[SerializeField]
private List<VisibleItem> m_VisibleItems= new List<VisibleItem>();
public List<VisibleItem> VisibleItems {
get { return this.m_VisibleItems; }
set { this.m_VisibleItems = value; }
}
private ItemContainer m_EquipmentContainer;
private void Start()
{
this.m_EquipmentContainer = WidgetUtility.Find<ItemContainer>(this.m_WindowName);
if (this.m_EquipmentContainer != null)
{
for (int i = 0; i < this.m_VisibleItems.Count; i++)
{
this.m_VisibleItems[i].enabled = false;
}
this.m_EquipmentContainer.OnAddItem += OnAddItem;
this.m_EquipmentContainer.OnRemoveItem += OnRemoveItem;
UpdateEquipment();
if (InventoryManager.current != null) {
InventoryManager.current.onDataLoaded.AddListener(UpdateEquipment);
}
}
}
private void OnAddItem(Item item, Slot slot)
{
if (item != null && item is EquipmentItem)
{
EquipItem(item as EquipmentItem);
}
}
private void OnRemoveItem(Item item, int amount, Slot slot)
{
if (item != null && item is EquipmentItem)
{
UnEquipItem(item as EquipmentItem);
}
}
public void EquipItem(EquipmentItem item)
{
foreach (ObjectProperty property in item.GetProperties())
{
if (property.SerializedType == typeof(int) || property.SerializedType == typeof(float))
{
float value = System.Convert.ToSingle(property.GetValue());
SendMessage("AddModifier", new object[] { property.Name, value, (value <= 1f && value >= -1f) ? 1 : 0, item }, SendMessageOptions.DontRequireReceiver);
}
}
for (int i = 0; i < this.m_VisibleItems.Count; i++) {
VisibleItem visibleItem = this.m_VisibleItems[i];
if (visibleItem.item.Id == item.Id) {
visibleItem.OnItemEquip(item);
return;
}
}
StaticItem staticItem = gameObject.AddComponent<StaticItem>();
staticItem.item = InventoryManager.Database.items.Find(x=>x.Id== item.Id);
VisibleItem.Attachment attachment = new VisibleItem.Attachment();
attachment.prefab = item.EquipPrefab;
attachment.region = item.Region[0];
staticItem.attachments = new VisibleItem.Attachment[1] { attachment};
staticItem.OnItemEquip(item);
}
public void UnEquipItem(EquipmentItem item)
{
foreach (ObjectProperty property in item.GetProperties())
{
if (property.SerializedType == typeof(int) || property.SerializedType == typeof(float))
{
SendMessage("RemoveModifiersFromSource", new object[] { property.Name, item }, SendMessageOptions.DontRequireReceiver);
}
}
for (int i = 0; i < this.m_VisibleItems.Count; i++)
{
VisibleItem visibleItem = this.m_VisibleItems[i];
if (visibleItem.item.Id == item.Id)
{
visibleItem.OnItemUnEquip(item);
break;
}
}
}
public void UpdateEquipment()
{
for (int i = 0; i < this.m_VisibleItems.Count; i++)
{
VisibleItem visibleItem = this.m_VisibleItems[i];
visibleItem.OnItemUnEquip(visibleItem.item);
}
EquipmentItem[] containerItems = this.m_EquipmentContainer.GetItems<EquipmentItem>();
foreach (EquipmentItem item in containerItems)
{
EquipItem(item);
}
}
public Transform GetBone(EquipmentRegion region) {
EquipmentBone bone = Bones.Find(x => x.region == region);
if (bone == null || bone.bone == null) {
Debug.LogWarning("Missing Bone Map configuration: "+gameObject.name);
return null;
}
return bone.bone.transform;
}
[System.Serializable]
public class EquipmentBone{
public EquipmentRegion region;
public GameObject bone;
}
el segundo using System.Collections.Generic;
using UnityEngine;
#if UNITY_EDITOR
using UnityEditorInternal;
using UnityEditor;
#endif
namespace MalbersAnimations.Weapons
{
public class Holsters : MonoBehaviour
{
public HolsterID DefaultHolster;
public List<Holster> holsters = new List<Holster>();
public float HolsterTime = 0.3f;
public Holster ActiveHolster { get; set; }
/// <summary> Used to change to the Next/Previus Holster</summary>
private int ActiveHolsterIndex;
private void Start()
{
for (int i = 0; i < holsters.Count; i++)
{
holsters[i].Index = i;
}
SetActiveHolster(DefaultHolster);
PrepareWeapons();
}
private void PrepareWeapons()
{
foreach (var h in holsters)
h.PrepareWeapon();
}
public void SetActiveHolster(int ID)
{
ActiveHolster = holsters.Find(x => x.GetID == ID);
ActiveHolsterIndex = ActiveHolster != null ? ActiveHolster.Index : 0;
}
public void SetNextHolster()
{
ActiveHolsterIndex = (ActiveHolsterIndex + 1) % holsters.Count;
ActiveHolster = holsters[ActiveHolsterIndex];
}
public void EquipWeapon(GameObject newWeapon)
{
var nextWeapon = newWeapon.GetComponent<MWeapon>();
if (nextWeapon != null)
{
var holster = holsters.Find(x=> x.ID == nextWeapon.HolsterID);
if (holster != null)
{
Debug.Log(holster.ID.name +" "+ holster.Weapon);
if (holster.Weapon != null)
{
if (!holster.Weapon.IsEquiped)
{
holster.Weapon.IsCollectable?.Drop();
if (holster.Weapon)
holster.Weapon = null;
}
else
{
//DO THE WEAPON EQUIPED STUFF
return;
}
}
if (newWeapon.IsPrefab()) newWeapon = Instantiate(newWeapon); //if is a prefab instantiate on the scene
newWeapon.transform.parent = holster.GetSlot(nextWeapon.HolsterSlot); //Parent the weapon to his original holster
newWeapon.transform.SetLocalTransform(nextWeapon.HolsterOffset);
holster.Weapon = nextWeapon;
}
}
}
public void SetPreviousHolster()
{
ActiveHolsterIndex = (ActiveHolsterIndex - 1) % holsters.Count;
ActiveHolster = holsters[ActiveHolsterIndex];
}
//[ContextMenu("Validate Holster Child Weapons")]
//internal void ValidateWeaponsChilds()
//{
// foreach (var h in holsters)
// {
// if (h.Weapon == null && h.Transform != null && h.Transform.childCount > 0 )
// {
// h.Weapon = (h.Transform.GetChild(0).GetComponent<MWeapon>()); ;
// }
// }
//}
}
#region Inspector
#if UNITY_EDITOR
[CustomEditor(typeof(Holsters))]
public class HolstersEditor : Editor
{
public static GUIStyle StyleBlue => MTools.Style(new Color(0, 0.5f, 1f, 0.3f));
public static GUIStyle StyleGreen => MTools.Style(new Color(0f, 1f, 0.5f, 0.3f));
private SerializedProperty holsters, DefaultHolster, /*m_active_Holster, */HolsterTime;
private ReorderableList holsterReordable;
private Holsters m;
private void OnEnable()
{
m = (Holsters)target;
holsters = serializedObject.FindProperty("holsters");
DefaultHolster = serializedObject.FindProperty("DefaultHolster");
HolsterTime = serializedObject.FindProperty("HolsterTime");
holsterReordable = new ReorderableList(serializedObject, holsters, true, true, true, true)
{
drawElementCallback = DrawHolsterElement,
drawHeaderCallback = DrawHolsterHeader
};
}
private void DrawHolsterHeader(Rect rect)
{
var IDRect = new Rect(rect);
IDRect.height = EditorGUIUtility.singleLineHeight;
IDRect.width *= 0.5f;
IDRect.x += 18;
EditorGUI.LabelField(IDRect, " Holster ID");
IDRect.x += IDRect.width-10;
IDRect.width -= 18;
EditorGUI.LabelField(IDRect, " Holster Transform ");
//var buttonRect = new Rect(rect) { x = rect.width - 30, width = 55 , y = rect.y-1, height = EditorGUIUtility.singleLineHeight +3};
//var oldColor = GUI.backgroundColor;
//GUI.backgroundColor = new Color(0, 0.5f, 1f, 0.6f);
//if (GUI.Button(buttonRect,new GUIContent("Weapon","Check for Weapons on the Holsters"), EditorStyles.miniButton))
//{
// m.ValidateWeaponsChilds();
//}
//GUI.backgroundColor = oldColor;
}
private void DrawHolsterElement(Rect rect, int index, bool isActive, bool isFocused)
{
rect.y += 2;
var holster = holsters.GetArrayElementAtIndex(index);
var ID = holster.FindPropertyRelative("ID");
var t = holster.FindPropertyRelative("Transform");
var IDRect = new Rect(rect);
IDRect.height = EditorGUIUtility.singleLineHeight;
IDRect.width *= 0.5f;
IDRect.x += 18;
EditorGUI.PropertyField(IDRect, ID, GUIContent.none);
IDRect.x += IDRect.width;
IDRect.width -= 18;
EditorGUI.PropertyField(IDRect, t, GUIContent.none);
}
/// <summary> Draws all of the fields for the selected ability. </summary>
public override void OnInspectorGUI()
{
serializedObject.Update();
EditorGUILayout.BeginVertical(StyleBlue);
EditorGUILayout.HelpBox("Holster Manager", MessageType.None);
EditorGUILayout.EndVertical();
EditorGUILayout.PropertyField(DefaultHolster);
EditorGUILayout.PropertyField(HolsterTime);
holsterReordable.DoLayoutList();
if (holsterReordable.index != -1)
{
EditorGUILayout.BeginVertical(EditorStyles.helpBox);
var element = holsters.GetArrayElementAtIndex(holsterReordable.index);
var Weapon = element.FindPropertyRelative("Weapon");
var pre = "";
var oldColor = GUI.backgroundColor;
var newColor = oldColor;
var weaponObj = Weapon.objectReferenceValue as Component;
if (weaponObj && weaponObj.gameObject != null)
{
if (weaponObj.gameObject.IsPrefab())
{
newColor = Color.green;
pre = "[Prefab]";
}
else pre = "[in Scene]";
}
EditorGUILayout.LabelField("Holster Weapon " + pre, EditorStyles.boldLabel);
GUI.backgroundColor = newColor;
EditorGUILayout.PropertyField(Weapon);
GUI.backgroundColor = oldColor;
EditorGUILayout.EndVertical();
}
serializedObject.ApplyModifiedProperties();
}
}
#endif
#endregion
}
}
}
|
85a84e7808b040ad826a1a8255712938
|
{
"intermediate": 0.39243489503860474,
"beginner": 0.410199373960495,
"expert": 0.19736576080322266
}
|
3,246
|
take this html and css for camping equipment page, next im going to do a Furtniture for camping page, write html and css for that copy a similar catalog style and page layout from camping-equipment but at the samer time differentiate the style of the containers that store the products use a different (theme matching but still different) style
HTML:
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<link rel="stylesheet" href="https://fonts.googleapis.com/css2?family=Cabin:wght@400;700&display=swap">
<link rel="stylesheet" href="style/style.css" />
<title>Camping Equipment - Retail Camping Company</title>
</head>
<body>
<header>
<div class="sticky-nav">
<div class="nav-container">
<img src="assets/images/logo.svg" alt="Logo" class="logo">
<h1>Retail Camping Company</h1>
<div class="search-container">
<form action="/search" method="get">
<img src="assets/images/search.png" alt="search-icon" class="search-icon">
<input type="text" name="search" />
<button type="submit">Search</button>
</form>
</div>
<nav>
<ul>
<li><a href="index.html">Home</a></li>
<li><a href="camping-equipment.html">Camping Equipment</a></li>
<li><a href="furniture.html">Furniture</a></li>
<li><a href="reviews.html">Reviews</a></li>
<li><a href="basket.html">Basket</a></li>
<li><a href="offers-and-packages.html">Offers and Packages</a></li>
</ul>
</nav>
</div>
</div>
</header>
<!-- Camping Equipment Page -->
<main>
<section class="featured-section">
<div class="filter">
<label for="filter-category">Category: </label>
<select id="filter-category">
<option value="all">All</option>
<option value="tents">Tents</option>
<option value="cookware">Cookware</option>
<option value="camping-gear">Camping Gear</option>
<option value="furniture">Furniture</option>
</select>
</div>
<h2>Camping Equipment</h2>
</section>
<section>
<div class="catalog">
<!-- Sample catalog item -->
<div class="catalog-item">
<img src="https://via.placeholder.com/200x200" alt="Camping Tent">
<h3>Camping Tent</h3>
<p>$199.99</p>
<button>Add to Basket</button>
</div>
<div class="catalog-item">
<img src="https://via.placeholder.com/200x200" alt="Camping Tent">
<h3>Camping Tent</h3>
<p>$199.99</p>
<button>Add to Basket</button>
</div>
<div class="catalog-item">
<img src="https://via.placeholder.com/200x200" alt="Camping Tent">
<h3>Camping Tent</h3>
<p>$199.99</p>
<button>Add to Basket</button>
</div>
<div class="catalog-item">
<img src="https://via.placeholder.com/200x200" alt="Camping Tent">
<h3>Camping Tent</h3>
<p>$199.99</p>
<button>Add to Basket</button>
</div>
<div class="catalog-item">
<img src="https://via.placeholder.com/200x200" alt="Camping Tent">
<h3>Camping Tent</h3>
<p>$199.99</p>
<button>Add to Basket</button>
</div>
<div class="catalog-item">
<img src="https://via.placeholder.com/200x200" alt="Camping Tent">
<h3>Camping Tent</h3>
<p>$199.99</p>
<button>Add to Basket</button>
</div>
<div class="catalog-item">
<img src="https://via.placeholder.com/200x200" alt="Camping Tent">
<h3>Camping Tent</h3>
<p>$199.99</p>
<button>Add to Basket</button>
</div>
<div class="catalog-item">
<img src="https://via.placeholder.com/200x200" alt="Camping Tent">
<h3>Camping Tent</h3>
<p>$199.99</p>
<button>Add to Basket</button>
</div>
<div class="catalog-item">
<img src="https://via.placeholder.com/200x200" alt="Camping Tent">
<h3>Camping Tent</h3>
<p>$199.99</p>
<button>Add to Basket</button>
</div>
<div class="catalog-item">
<img src="https://via.placeholder.com/200x200" alt="Camping Tent">
<h3>Camping Tent</h3>
<p>$199.99</p>
<button>Add to Basket</button>
</div>
<div class="catalog-item">
<img src="https://via.placeholder.com/200x200" alt="Camping Tent">
<h3>Camping Tent</h3>
<p>$199.99</p>
<button>Add to Basket</button>
</div>
<div class="catalog-item">
<img src="https://via.placeholder.com/200x200" alt="Camping Cooker">
<h3>Camping Cooker</h3>
<p>$49.99</p>
<button>Add to Basket</button>
</div>
<div class="catalog-item">
<img src="https://via.placeholder.com/200x200" alt="Camping Lantern">
<h3>Camping Lantern</h3>
<p>$29.99</p>
<button>Add to Basket</button>
</div>
<div class="catalog-item">
<img src="https://via.placeholder.com/200x200" alt="Sleeping Bag">
<h3>Sleeping Bag</h3>
<p>$89.99</p>
<button>Add to Basket</button>
</div>
</div>
</section>
</main>
<footer>
<div class="footer-container">
<div class="footer-item">
<p>Subscribe To Our Newsletter:</p>
<form action="subscribe.php" method="post">
<input type="email" name="email" placeholder="Enter your email" required>
<button type="submit">Subscribe</button>
</form>
</div>
<div class="footer-item address-container">
<p>Get In Contact:</p>
<p>Email: info@retailcampingcompany.com</p>
<p>Phone: +35699382994</p>
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</body>
</html>
CSS:
html, body, h1, h2, h3, h4, p, a, ul, li, div, main, header, section, footer, img {
margin: 0;
padding: 0;
border: 0;
font-size: 100%;
font-family: inherit;
vertical-align: baseline;
box-sizing: border-box;
}
body {
font-family: "Cabin", sans-serif;
line-height: 1.5;
color: #333;
width: 100%;
margin: 0;
padding: 0;
min-height: 100vh;
flex-direction: column;
display: flex;
background-image: url("../assets/images/cover.jpg");
background-size: cover;
}
header {
background: #00000000;
padding: 0.5rem 2rem;
text-align: center;
color: #32612D;
font-size: 1.2rem;
}
main{
flex-grow: 1;
}
.sticky-nav {
position: -webkit-sticky;
position: sticky;
top: 0;
z-index: 1000;
}
.nav-container {
display: flex;
justify-content: space-between;
align-items: center;
flex-wrap: wrap;
}
.search-container {
display: inline-block;
position: relative;
}
.search-container input[type="text"] {
padding: 0.8rem;
border: none;
border-bottom: 1.5px solid #32612D;
outline: none;
color: #32612D;
font-size: 1rem;
background-color: transparent;
margin-right: 30rem;
margin-bottom: 12px;
width: 65%;
}
.search-container input[type="text"]::placeholder {
color: #32612D;
opacity: 0.5;
}
.search-icon {
margin-right: 0.8rem;
width: 24px;
height: auto;
vertical-align: middle;
position: absolute;
top: 50%;
margin-top: -16px;
}
.search-container input[type="text"]:focus {
border-color: #ADC3AB;
}
.search-container button[type="submit"] {
display: none;
}
.logo {
width: 50px;
height: auto;
margin-right: 1rem;
}
h1 {
flex-grow: 1;
text-align: left;
}
nav ul {
display: inline
list-style: none;
}
nav ul li {
display: inline;
margin-left: 1rem;
}
nav ul li a {
text-decoration: none;
color: #32612D;
position: relative;
transition: color 0.3s ease;
}
@media screen and (max-width: 768px) {
.nav-container {
flex-direction: column;
}
h1 {
margin-bottom: 1rem;
}
}
nav ul li a {
text-decoration: none;
color: #32612D;
position: relative;
transition: color 0.3s ease;
}
nav ul li a::after {
content: '';
position: absolute;
bottom: 0;
left: 0;
width: 100%;
height: 2px;
background-color: #000;
transform: scaleX(0);
transition: transform 0.3s;
}
nav ul li a:hover {
color: #000000;
}
nav ul li a:hover::after {
transform: scaleX(1);
}
.slideshow-container {
width: 100%;
position: relative;
margin: 1rem 0;
}
.mySlides {
display: none;
}
.mySlides img {
width: 100%;
height: auto;
}
/* Slideshow navigation */
.prev, .next {
cursor: pointer;
position: absolute;
top: 50%;
width: auto;
margin-top: -22px;
padding: 16px;
color: #32612D;
font-weight: bold;
font-size: 18px;
transition: 0.6s ease;
border-radius: 0 3px 3px 0;
user-select: none;
}
.next {
right: 0;
border-radius: 3px 0 0 3px;
}
.prev:hover, .next:hover {
background-color: rgba(255,255,255,0.8);
}
.dot {
cursor: pointer;
height: 15px;
width: 15px;
margin: 0 2px;
background-color: #bbb;
border-radius: 50%;
display: inline-block;
transition: background-color 0.6s ease;
}
.dot:hover {
background-color: #717171;
}
.fade {
-webkit-animation-name: fade;
-webkit-animation-duration: 1.5s;
animation-name: fade;
animation-duration: 1.5s;
}
@-webkit-keyframes fade {
from {opacity: .4}
to {opacity: 1}
}
@keyframes fade {
from {opacity: .4}
to {opacity: 1}
}
.catalog {
display: flex;
flex-wrap: wrap;
justify-content: center;
margin: 2rem 0;
}
.catalog-item {
width: 200px;
padding: 1rem;
margin: 1rem;
background-color: #ADC3AB;
border-radius: 5px;
box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
text-align: center;
}
.catalog-item:hover {
box-shadow: 0 8px 16px rgba(0, 0, 0, 0.2);
}
.catalog-item img {
width: 100%;
height: auto;
margin-bottom: 0.5rem;
border-radius: 5px;
}
.catalog-item h3 {
margin-bottom: 0.5rem;
}
.catalog-item p {
margin-bottom: 0.5rem;
}
.catalog-item button {
background-color: #32612D;
color: #fff;
padding: 0.5rem;
border: none;
border-radius: 5px;
cursor: pointer;
}
.catalog-item button:hover {
background-color: #ADC3AB;
}
.featured-section {
padding: 1rem;
text-align: center;
margin: 1rem 0;
}
.filter {
margin-bottom: 10rem;
}
.filter select {
padding: 0.5rem;
font-size: 0.9rem;
}
footer form {
display: inline-flex;
align-items: center;
}
.about-section {
padding: 1rem;
text-align: center;
margin: 1rem 0;
}
.featured-section {
padding: 1rem;
text-align: center;
margin: 1rem 0;
}
.featured-section h2 {
font-size: 1.5rem;
margin-bottom: 1rem;
}
.featured-container {
display: flex;
justify-content: space-around;
align-items: center;
flex-wrap: wrap;
margin: 1rem 0;
}
.featured-product {
width: 150px;
padding: 1rem;
background-color: #ADC3AB;
border-radius: 5px;
box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
transition: all 0.3s ease;
margin: 0.5rem;
}
.featured-product:hover {
box-shadow: 0 8px 16px rgba(0, 0, 0, 0.2);
transform: translateY(-5px);
}
.featured-product img {
width: 100%;
height: auto;
margin-bottom: 1rem;
border-radius: 5px;
}
.special-offers-container {
display: flex;
justify-content: space-around;
align-items: center;
flex-wrap: wrap;
margin: 1rem 0;
}
.special-offer {
width: 200px;
padding: 1rem;
text-align: center;
margin: 1rem;
background-color: #ADC3AB;
border-radius: 5px;
box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
transition: all 0.3s ease;
}
.special-offer:hover {
box-shadow: 0 8px 16px rgba(0, 0, 0, 0.2);
transform: translateY(-5px);
}
.special-offer img {
width: 100%;
height: auto;
margin-bottom: 0.5rem;
border-radius: 5px;
}
.modal {
display: none;
position: fixed;
left: 0;
top: 0;
width: 100%;
height: 100%;
background-color: rgba(0, 0, 0, 0.5);
z-index: 1;
overflow: auto;
align-items: center;
}
.modal-content {
background-color: #fefefe;
padding: 2rem;
margin: 10% auto;
width: 30%;
min-width: 300px;
max-width: 80%;
text-align: center;
border-radius: 5px;
box-shadow: 0 1px 8px rgba(0, 0, 0, 0.1);
}
.modalBtn{
background-color: #ADC3AB;
color: #32612D;
padding: 0.5rem;
border: none;
border-radius: 5px;
cursor: pointer;
}
.buts {
text-align: center;
}
.footer-item.address-container p {
margin: 0;
text-align: left;
}
.footer-item p {
text-align: center;
}
.add{
text-align: center;
}
.close {
display: block;
text-align: right;
font-size: 2rem;
color: #333;
cursor: pointer;
}
footer {
background: #32612D;
padding: 1rem;
text-align: center;
margin-top: auto;
}
.footer-container {
display: flex;
justify-content: space-between;
align-items: center;
flex-wrap: wrap;
}
.footer-item {
margin: 1rem 2rem;
}
footer p {
color: #fff;
margin-bottom: 1rem;
}
footer ul {
list-style: none;
}
footer ul li {
display: inline;
margin: 0.5rem;
}
footer ul li a {
text-decoration: none;
color: #fff;
}
@media screen and (max-width: 768px) {
.special-offers-container {
flex-direction: column;
}
}
@media screen and (max-width: 480px) {
h1 {
display: block;
margin-bottom: 1rem;
}
}
.footer-item iframe {
width: 100%;
height: 200px;
}
.footer-item form {
display: inline-flex;
align-items: center;
}
.footer-item input[type="email"] {
padding: 0.5rem;
border: none;
border-radius: 5px;
margin-right: 0.5rem;
}
.footer-item button {
background-color: #ADC3AB;
color: #32612D;
padding: 0.5rem;
border: none;
border-radius: 5px;
cursor: pointer;
}
.footer-item button:hover {
background-color: #32612D;
color: #fff;
}
.social-links-container {
order: 2;
}
.address-container {
order: 1;
}
.google-maps-container {
order: 0;
}
|
3049428e50877ffc1ddbacfd7d8d1cbd
|
{
"intermediate": 0.37776196002960205,
"beginner": 0.41954657435417175,
"expert": 0.2026914358139038
}
|
3,247
|
def main():
ap = argparse.ArgumentParser()
ap.add_argument("-f", "--first_image_dir", help="path to the first image")
ap.add_argument("-s", "--second_image_dir", help="path to the second image")
ap.add_argument("-r", "--results_dir", help="path to the visualization result")
ap.add_argument("--lmeds", action="store_true")
args = ap.parse_args()
image0 = cv2.imread(args.first_image_dir)
gray0 = cv2.cvtColor(image0, cv2.COLOR_BGR2GRAY)
image1 = cv2.imread(args.second_image_dir)
gray1 = cv2.cvtColor(image1, cv2.COLOR_BGR2GRAY)
# Using Scale Invariant Feature Transform (SIFT) to detect image features
sift = cv2.SIFT_create(500)
print('1. Using Scale Invariant Feature Transform (SIFT) to detect image features')
# Detect keypoints in pano0 using OpenCV SIFT detect function
kp0, des0 = sift.detectAndCompute(gray0, None)
# Detect keypoints in pano1 using OpenCV SIFT detect function
kp1, des1 = sift.detectAndCompute(gray1, None)
# Visualize the detected and matched features
fig, ax = plt.subplots(1, 2, figsize=(10, 5))
fig.suptitle('1. Detected and matched features', fontsize=20)
plt.subplot(121)
plt.imshow(cv2.drawKeypoints(gray0, kp0, None), cmap="gray")
plt.title("Image 0 keypoints")
plt.subplot(122)
plt.imshow(cv2.drawKeypoints(gray1, kp1, None), cmap="gray")
plt.title("Image 1 keypoints")
fig.savefig(args.results_dir+'/keypoints.png', dpi=fig.dpi)
cv2.imshow('keypoints', cv2.imread(args.results_dir+'/keypoints.png'))
cv2.waitKey(10)
# Match descriptors between images
matches = match_descriptors(des0, des1, cross_check=True)
print('2. Implement a simple feature matching and visualize the detected and matched features')
# Restore the openCV style keypoints into a 2d array type keypoints
keypoints0 = []
a = 0
for i in kp0:
keypoints0.append(list(kp0[a].pt)[::-1])
a += 1
keypoints0 = np.array(keypoints0)
keypoints1 = []
b = 0
for j in kp1:
keypoints1.append(list(kp1[b].pt)[::-1])
b += 1
keypoints1 = np.array(keypoints1)
# Best match subset for pano0 -> pano1
fig, ax = plt.subplots(1, 1, figsize=(10, 5))
plot_matches(ax, image0, image1, keypoints0, keypoints1, matches)
ax.axis('off')
fig.suptitle('2. Initial matching', fontsize=20)
fig.savefig(args.results_dir+'/initial_matching.png', dpi=fig.dpi)
cv2.imshow('initial matching', cv2.imread(args.results_dir+'/initial_matching.png'))
cv2.waitKey(10)
# Select keypoints from
# * source (image to be registered): pano1
# * target (reference image): pano0
src = keypoints1[matches[:, 1]][:, ::-1]
dst = keypoints0[matches[:, 0]][:, ::-1]
# Find best matches using Ransac or LMedS
if(args.lmeds):
homography, inliers01 = lmeds((src, dst), threshold_distance=0.8, threshold_inliers=0.3, max_trials=500)
print('3. Using LMedS to find the best matching')
title = '3. Best matching after LMedS'
else:
homography, inliers01 = ransac((src, dst), threshold_distance=0.8, threshold_inliers=0.3, max_trials=500)
print('3. Using RANSAC to find the best matching')
title = '3. Best matching after RANSAC'
# Best match subset for pano0 -> pano1
fig, ax = plt.subplots(1, 1, figsize=(10, 5))
plot_matches(ax, image0, image1, keypoints0, keypoints1, matches[inliers01])
ax.axis('off')
fig.suptitle(title, fontsize=20)
fig.savefig(args.results_dir+'/ransac_matching.png', dpi=fig.dpi)
cv2.imshow('ransac matching', cv2.imread(args.results_dir+'/ransac_matching.png'))
cv2.waitKey(10)
# Image warping and stitching
print('4. Perform Image warping and stitching')
result = stitching(homography, gray0, image0, image1)
fig, ax = plt.subplots(1, 1, figsize=(10, 5))
plt.imshow(result, cmap="gray")
fig.suptitle('4. Image Stitching Result', fontsize=20)
fig.savefig(args.results_dir+'/stitching_result.png', dpi=fig.dpi)
cv2.imshow('stitching result', cv2.imread(args.results_dir+'/stitching_result.png'))
print("You can also review the generated visualization results in the 'results' folder. Press any key to exit.")
cv2.waitKey()
def stitching(homography, gray0, image0, image1):
# Shape registration target
r, c = gray0.shape[:2]
# Note that transformations take coordinates in (x, y) format,
# not (row, column), in order to be consistent with most literature
corners = np.array([[0, 0, 1],
[0, r, 1],
[c, 0, 1],
[c, r, 1]])
# Warp the image corners to their new positions
warped_corners01 = np.dot(homography, corners.T)
warped_corners01 = warped_corners01[:2, :].T
# Find the extents of both the reference image and the warped
# target image
all_corners = np.vstack((warped_corners01, corners[:, :2]))
# The overally output shape will be max - min
corner_min = np.min(all_corners, axis=0)
corner_max = np.max(all_corners, axis=0)
output_shape = (corner_max - corner_min)
# Ensure integer shape with np.ceil and dtype conversion
output_shape = np.ceil(output_shape[::-1]).astype(int)
# This in-plane offset is the only necessary transformation for the middle image
offset1 = SimilarityTransform(translation=-corner_min)
tform = ProjectiveTransform(homography)
# Warp pano1 to pano0 using 3rd order interpolation
transform01 = (tform + offset1).inverse
image1_warped = warp(image1, transform01, order=3,
output_shape=output_shape, cval=-1)
image1_mask = (image1_warped != -1) # Mask == 1 inside image
image1_warped[~image1_mask] = 0 # Return background values to 0
# Translate pano0 into place
image0_warped = warp(image0, offset1.inverse, order=3,
output_shape=output_shape, cval=-1)
image0_mask = (image0_warped != -1) # Mask == 1 inside image
image0_warped[~image0_mask] = 0 # Return background values to 0
# Add the images together. This could create dtype overflows!
# We know they are are floating point images after warping, so it's OK.
merged = (image0_warped + image1_warped)
# Track the overlap by adding the masks together
overlap = (image0_mask * 1.0 + # Multiply by 1.0 for bool -> float conversion
image1_mask)
# Normalize through division by `overlap` - but ensure the minimum is 1
normalized = merged / np.maximum(overlap, 1)
return normalized
if __name__ == "__main__":
main()
visualize image warping from the above code
|
9ba3118bb470d96f5b893cf63bd95062
|
{
"intermediate": 0.28882846236228943,
"beginner": 0.5621570944786072,
"expert": 0.1490144282579422
}
|
3,248
|
Write a java program that uses Dynamic programming algorithm to solve the String Matching problem/ wildcard pattern matching
|
b3cd15f77f1e179ed0d33c381be08a5a
|
{
"intermediate": 0.17932716012001038,
"beginner": 0.08629384636878967,
"expert": 0.7343790531158447
}
|
3,249
|
c++ print vector of uint8_t
|
df1affd6ac7f923f09315b4ace91fc87
|
{
"intermediate": 0.28080683946609497,
"beginner": 0.44528549909591675,
"expert": 0.2739076316356659
}
|
3,251
|
how to stop wireguard from tunneling virtualbox virtual machine?
|
78f7d518f06d7e2b8a65df875fa7a521
|
{
"intermediate": 0.25370147824287415,
"beginner": 0.2045416533946991,
"expert": 0.5417569279670715
}
|
3,252
|
error Traceback (most recent call last)
Cell In[31], line 1
----> 1 main(r"C:\Users\new\OneDrive\Master of informatics\CIT690G Computer vision\Assignments and tasks\Assignment 2\partII\partII\fishbowl\fishbowl-00.png", r"C:\Users\new\OneDrive\Master of informatics\CIT690G Computer vision\Assignments and tasks\Assignment 2\partII\partII\fishbowl\fishbowl-01.png")
Cell In[30], line 29, in main(image0_path, image1_path)
27 plt.title("Image 1 keypoints")
28 #fig.savefig(args.results_dir+'/keypoints.png', dpi=fig.dpi)
---> 29 cv2.imshow('keypoints', fig)
30 cv2.waitKey(10)
32 # Match descriptors between images
error: OpenCV(4.7.0) :-1: error: (-5:Bad argument) in function 'imshow'
> Overload resolution failed:
> - mat is not a numpy array, neither a scalar
> - Expected Ptr<cv::cuda::GpuMat> for argument 'mat'
> - Expected Ptr<cv::UMat> for argument 'mat'
|
306f4deeb7d8151e71c66d682a5ab0ee
|
{
"intermediate": 0.4202113449573517,
"beginner": 0.35737863183021545,
"expert": 0.22240997850894928
}
|
3,253
|
Write a python function with a call of x, iter = newtonRaphson(g, x0, eps, delta, itermax) which used the Newton-Raphson method which returns the root of a function g. The inputs are:
g: A function which returns f, fx = g(x) where f is the function value and fx is the function derivative evaluated at x.
x0: The initial guess at the root.
eps: The tolerance to use. Consider the method converged when the magnitude of the full step is less than this value.
delta: Criteria for divergence. Consider the method as diverging when the magnitude of the full step is more than this value. If the method is diverging raise an exception with this exact error message: Error: Divergence
itermax: The maximum number of iterations. If the maximum number of iteration is exceeded raise an exception with this exact error message: Error: Maximum Number of Iterations
The outputs are:
x: The root of the function g
iter: The number of iterations required to obtain the root.
NOTE: This is an individual programming project.
|
0fc0223ea13204b00d8e1fc509872658
|
{
"intermediate": 0.27209681272506714,
"beginner": 0.4081004858016968,
"expert": 0.3198027014732361
}
|
3,254
|
write a clean fetch data function in js that is async and export, base url as parameter that waits for data and formats it to json and returns a js array
|
46de783f5a045c8720f8936ee6686e71
|
{
"intermediate": 0.5929667353630066,
"beginner": 0.17133131623268127,
"expert": 0.23570197820663452
}
|
3,255
|
ypeError Traceback (most recent call last)
Cell In[9], line 1
----> 1 main(r"C:\Users\new\OneDrive\Master of informatics\CIT690G Computer vision\Assignments and tasks\Assignment 2\partII\partII\fishbowl\fishbowl-00.png", r"C:\Users\new\OneDrive\Master of informatics\CIT690G Computer vision\Assignments and tasks\Assignment 2\partII\partII\fishbowl\fishbowl-01.png", "c/results", True)
Cell In[8], line 71, in main(image0_path, image1_path, results_dir, use_lmeds)
69 # Find best matches using Ransac or LMedS
70 if(use_lmeds):
---> 71 homography, inliers01 = lmeds((src, dst), threshold_distance=0.8, threshold_inliers=0.3, max_trials=500)
72 print('3. Using LMedS to find the best matching')
73 title = '3. Best matching after LMedS'
TypeError: cannot unpack non-iterable NoneType object
|
5d1dcf9c77c95a9b700967cd931311ab
|
{
"intermediate": 0.3654220402240753,
"beginner": 0.33887726068496704,
"expert": 0.29570063948631287
}
|
3,256
|
----------------------------------
-- first component for xor operation
----------------------------------
library ieee;
use ieee.std_logic_1164.all;
entity xor_get is
port(input1,input2 : in std_logic_vector(15 downto 0);
output : out std_logic_vector(15 downto 0));
end xor_get;
architecture Behavioral of xor_get is
begin
output <= input1 xor input2;
end Behavioral;
----------------------------------
-- second component for decoder 4x16
----------------------------------
library ieee;
use ieee.std_logic_1164.all;
entity decoder_4x16 is
port(input : in std_logic_vector(3 downto 0);
output : out std_logic_vector(15 downto 0));
end decoder_4x16;
architecture Behavioral of decoder_4x16 is
begin
process(input)
begin
case input is
when "0000" => output <= "0000000000000001";
when "0001" => output <= "0000000000000010";
when "0010" => output <= "0000000000000100";
when "0011" => output <= "0000000000001000";
when "0100" => output <= "0000000000010000";
when "0101" => output <= "0000000000100000";
when "0110" => output <= "0000000001000000";
when "0111" => output <= "0000000010000000";
when "1000" => output <= "0000000100000000";
when "1001" => output <= "0000001000000000";
when "1010" => output <= "0000010000000000";
when "1011" => output <= "0000100000000000";
when "1100" => output <= "0001000000000000";
when "1101" => output <= "0010000000000000";
when "1110" => output <= "0100000000000000";
when "1111" => output <= "1000000000000000";
when others => output <= "0000000000000000";
end case;
end process;
end Behavioral;
----------------------------------
-- main component
----------------------------------
library ieee;
use ieee.std_logic_1164.all;
entity main is
port(input_1,input_2 : in std_logic_vector(3 downto 0);
xorKey : in std_logic_vector(15 downto 0);
output1,output2 : out std_logic_vector(15 downto 0));
end main;
architecture Behavioral of main is
signal decoder1,decoder2: std_logic_vector(15 downto 0);
component xor_get is
port(input1,input2 : in std_logic_vector(15 downto 0);
output : out std_logic_vector(15 downto 0));
end component;
component decoder_4x16 is
port(input : in std_logic_vector(3 downto 0);
output : out std_logic_vector(15 downto 0));
end component;
begin
L0 : decoder_4x16 port map(input_1,decoder1);
L1 : decoder_4x16 port map(input_2,decoder2);
L2 : xor_get port map(decoder1,xorKey,output1);
L3 : xor_get port map(decoder2,xorKey,output2);
end Behavioral;
This program gave the following output:
35 307
17 33
33 53
183 2103
35 563
17 32817
33 4145
63 54
179 115
57 57
17 32817
23 119
35 307
33 33
33 4145
...
Write python that finds the input that lead to this output considering the vhdl description.
|
85bf127c320d09622033ee02e73d27a5
|
{
"intermediate": 0.2888372838497162,
"beginner": 0.45754894614219666,
"expert": 0.2536137104034424
}
|
3,257
|
have a look at this html and css of this page, rewrite it so that in every row of products it only has 6 products. every row will contain a category out of the filter, so
centered appropriatly styled h2 naming the catgory and under it followed by the 6 products from that category. so in total 24 products and 6 rows each product, 1 category each row of products
HTML:
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<link rel="stylesheet" href="https://fonts.googleapis.com/css2?family=Cabin:wght@400;700&display=swap">
<link rel="stylesheet" href="style/style.css" />
<title>Camping Equipment - Retail Camping Company</title>
</head>
<body>
<header>
<div class="sticky-nav">
<div class="nav-container">
<img src="assets/images/logo.svg" alt="Logo" class="logo">
<h1>Retail Camping Company</h1>
<div class="search-container">
<form action="/search" method="get">
<img src="assets/images/search.png" alt="search-icon" class="search-icon">
<input type="text" name="search" />
<button type="submit">Search</button>
</form>
</div>
<nav>
<ul>
<li><a href="index.html">Home</a></li>
<li><a href="camping-equipment.html">Camping Equipment</a></li>
<li><a href="furniture.html">Furniture</a></li>
<li><a href="reviews.html">Reviews</a></li>
<li><a href="basket.html">Basket</a></li>
<li><a href="offers-and-packages.html">Offers and Packages</a></li>
</ul>
</nav>
</div>
</div>
</header>
<!-- Camping Equipment Page -->
<main>
<section class="featured-section">
<div class="filter">
<label for="filter-category">Category: </label>
<select id="filter-category">
<option value="all">All</option>
<option value="tents">Tents</option>
<option value="cookware">Cookware</option>
<option value="camping-gear">Camping Gear</option>
<option value="furniture">Guide Books</option>
</select>
</div>
<h2>Camping Equipment</h2>
</section>
<section>
<div class="catalog">
<!-- Sample catalog item -->
<div class="catalog-item">
<img src="https://via.placeholder.com/200x200" alt="Camping Tent">
<h3>Camping Tent</h3>
<p>$199.99</p>
<button>Add to Basket</button>
</div>
<div class="catalog-item">
<img src="https://via.placeholder.com/200x200" alt="Camping Tent">
<h3>Camping Tent</h3>
<p>$199.99</p>
<button>Add to Basket</button>
</div>
<div class="catalog-item">
<img src="https://via.placeholder.com/200x200" alt="Camping Tent">
<h3>Camping Tent</h3>
<p>$199.99</p>
<button>Add to Basket</button>
</div>
<div class="catalog-item">
<img src="https://via.placeholder.com/200x200" alt="Camping Tent">
<h3>Camping Tent</h3>
<p>$199.99</p>
<button>Add to Basket</button>
</div>
<div class="catalog-item">
<img src="https://via.placeholder.com/200x200" alt="Camping Tent">
<h3>Camping Tent</h3>
<p>$199.99</p>
<button>Add to Basket</button>
</div>
<div class="catalog-item">
<img src="https://via.placeholder.com/200x200" alt="Camping Tent">
<h3>Camping Tent</h3>
<p>$199.99</p>
<button>Add to Basket</button>
</div>
<div class="catalog-item">
<img src="https://via.placeholder.com/200x200" alt="Camping Tent">
<h3>Camping Tent</h3>
<p>$199.99</p>
<button>Add to Basket</button>
</div>
<div class="catalog-item">
<img src="https://via.placeholder.com/200x200" alt="Camping Tent">
<h3>Camping Tent</h3>
<p>$199.99</p>
<button>Add to Basket</button>
</div>
<div class="catalog-item">
<img src="https://via.placeholder.com/200x200" alt="Camping Tent">
<h3>Camping Tent</h3>
<p>$199.99</p>
<button>Add to Basket</button>
</div>
<div class="catalog-item">
<img src="https://via.placeholder.com/200x200" alt="Camping Tent">
<h3>Camping Tent</h3>
<p>$199.99</p>
<button>Add to Basket</button>
</div>
<div class="catalog-item">
<img src="https://via.placeholder.com/200x200" alt="Camping Tent">
<h3>Camping Tent</h3>
<p>$199.99</p>
<button>Add to Basket</button>
</div>
<div class="catalog-item">
<img src="https://via.placeholder.com/200x200" alt="Camping Cooker">
<h3>Camping Cooker</h3>
<p>$49.99</p>
<button>Add to Basket</button>
</div>
<div class="catalog-item">
<img src="https://via.placeholder.com/200x200" alt="Camping Lantern">
<h3>Camping Lantern</h3>
<p>$29.99</p>
<button>Add to Basket</button>
</div>
<div class="catalog-item">
<img src="https://via.placeholder.com/200x200" alt="Sleeping Bag">
<h3>Sleeping Bag</h3>
<p>$89.99</p>
<button>Add to Basket</button>
</div>
</div>
</section>
</main>
<footer>
<div class="footer-container">
<div class="footer-item">
<p>Subscribe To Our Newsletter:</p>
<form action="subscribe.php" method="post">
<input type="email" name="email" placeholder="Enter your email" required>
<button type="submit">Subscribe</button>
</form>
</div>
<div class="footer-item address-container">
<p>Get In Contact:</p>
<p>Email: info@retailcampingcompany.com</p>
<p>Phone: +35699382994</p>
<p>Triq Malta,<br>Sliema 12345</p>
</div>
<div class="footer-item google-maps-container">
<p>Where To Find Us:</p>
<iframe src="https://www.google.com/maps/embed?pb=!1m14!1m8!1m3!1d12928.30174160605!2d14.5091557!3d35.8961681!3m2!1i1024!2i768!4f13.1!3m3!1m2!1s0x130e452d3081f035%3A0x61f492f43cae68e4!2sCity%20Gate!5e0!3m2!1sen!2smt!4v1682559564194!5m2!1sen!2smt" width="650" height="200" style="border:0;" allowfullscreen="" loading="lazy" referrerpolicy="no-referrer-when-downgrade"></iframe>
</div>
<div class="footer-item social-links-container">
<p>Follow Us On:</p>
<ul class="social-links">
<li><a href="https://www.facebook.com">Facebook</a></li>
<li><a href="https://www.instagram.com">Instagram</a></li>
<li><a href="https://www.twitter.com">Twitter</a></li>
</ul>
</div>
</div>
</footer>
</body>
</html>
CSS:
html, body, h1, h2, h3, h4, p, a, ul, li, div, main, header, section, footer, img {
margin: 0;
padding: 0;
border: 0;
font-size: 100%;
font-family: inherit;
vertical-align: baseline;
box-sizing: border-box;
}
body {
font-family: "Cabin", sans-serif;
line-height: 1.5;
color: #333;
width: 100%;
margin: 0;
padding: 0;
min-height: 100vh;
flex-direction: column;
display: flex;
background-image: url("../assets/images/cover.jpg");
background-size: cover;
}
header {
background: #00000000;
padding: 0.5rem 2rem;
text-align: center;
color: #32612D;
font-size: 1.2rem;
}
main{
flex-grow: 1;
}
.sticky-nav {
position: -webkit-sticky;
position: sticky;
top: 0;
z-index: 1000;
}
.nav-container {
display: flex;
justify-content: space-between;
align-items: center;
flex-wrap: wrap;
}
.search-container {
display: inline-block;
position: relative;
}
.search-container input[type="text"] {
padding: 0.8rem;
border: none;
border-bottom: 1.5px solid #32612D;
outline: none;
color: #32612D;
font-size: 1rem;
background-color: transparent;
margin-right: 30rem;
margin-bottom: 12px;
width: 65%;
}
.search-container input[type="text"]::placeholder {
color: #32612D;
opacity: 0.5;
}
.search-icon {
margin-right: 0.8rem;
width: 24px;
height: auto;
vertical-align: middle;
position: absolute;
top: 50%;
margin-top: -16px;
}
.search-container input[type="text"]:focus {
border-color: #ADC3AB;
}
.search-container button[type="submit"] {
display: none;
}
.logo {
width: 50px;
height: auto;
margin-right: 1rem;
}
h1 {
flex-grow: 1;
text-align: left;
}
nav ul {
display: inline
list-style: none;
}
nav ul li {
display: inline;
margin-left: 1rem;
}
nav ul li a {
text-decoration: none;
color: #32612D;
position: relative;
transition: color 0.3s ease;
}
@media screen and (max-width: 768px) {
.nav-container {
flex-direction: column;
}
h1 {
margin-bottom: 1rem;
}
}
nav ul li a {
text-decoration: none;
color: #32612D;
position: relative;
transition: color 0.3s ease;
}
nav ul li a::after {
content: '';
position: absolute;
bottom: 0;
left: 0;
width: 100%;
height: 2px;
background-color: #000;
transform: scaleX(0);
transition: transform 0.3s;
}
nav ul li a:hover {
color: #000000;
}
nav ul li a:hover::after {
transform: scaleX(1);
}
.slideshow-container {
width: 100%;
position: relative;
margin: 1rem 0;
}
.mySlides {
display: none;
}
.mySlides img {
width: 100%;
height: auto;
}
/* Slideshow navigation */
.prev, .next {
cursor: pointer;
position: absolute;
top: 50%;
width: auto;
margin-top: -22px;
padding: 16px;
color: #32612D;
font-weight: bold;
font-size: 18px;
transition: 0.6s ease;
border-radius: 0 3px 3px 0;
user-select: none;
}
.next {
right: 0;
border-radius: 3px 0 0 3px;
}
.prev:hover, .next:hover {
background-color: rgba(255,255,255,0.8);
}
.dot {
cursor: pointer;
height: 15px;
width: 15px;
margin: 0 2px;
background-color: #bbb;
border-radius: 50%;
display: inline-block;
transition: background-color 0.6s ease;
}
.dot:hover {
background-color: #717171;
}
.fade {
-webkit-animation-name: fade;
-webkit-animation-duration: 1.5s;
animation-name: fade;
animation-duration: 1.5s;
}
@-webkit-keyframes fade {
from {opacity: .4}
to {opacity: 1}
}
@keyframes fade {
from {opacity: .4}
to {opacity: 1}
}
.catalog {
display: flex;
flex-wrap: wrap;
justify-content: center;
margin: 2rem 0;
}
.catalog-item {
width: 200px;
padding: 1rem;
margin: 1rem;
background-color: #ADC3AB;
border-radius: 5px;
box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
text-align: center;
}
.catalog-item:hover {
box-shadow: 0 8px 16px rgba(0, 0, 0, 0.2);
}
.catalog-item img {
width: 100%;
height: auto;
margin-bottom: 0.5rem;
border-radius: 5px;
}
.catalog-item h3 {
margin-bottom: 0.5rem;
}
.catalog-item p {
margin-bottom: 0.5rem;
}
.catalog-item button {
background-color: #32612D;
color: #fff;
padding: 0.5rem;
border: none;
border-radius: 5px;
cursor: pointer;
}
.catalog-item button:hover {
background-color: #ADC3AB;
}
.featured-section {
padding: 1rem;
text-align: center;
margin: 1rem 0;
}
.filter {
margin-bottom: 10rem;
}
.filter select {
padding: 0.5rem;
font-size: 0.9rem;
}
footer form {
display: inline-flex;
align-items: center;
}
.about-section {
padding: 1rem;
text-align: center;
margin: 1rem 0;
}
.featured-section {
padding: 1rem;
text-align: center;
margin: 1rem 0;
}
.featured-section h2 {
font-size: 1.5rem;
margin-bottom: 1rem;
}
.featured-container {
display: flex;
justify-content: space-around;
align-items: center;
flex-wrap: wrap;
margin: 1rem 0;
}
.featured-product {
width: 150px;
padding: 1rem;
background-color: #ADC3AB;
border-radius: 5px;
box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
transition: all 0.3s ease;
margin: 0.5rem;
}
.featured-product:hover {
box-shadow: 0 8px 16px rgba(0, 0, 0, 0.2);
transform: translateY(-5px);
}
.featured-product img {
width: 100%;
height: auto;
margin-bottom: 1rem;
border-radius: 5px;
}
.furniture-item {
width: 200px;
padding: 1rem;
margin: 1rem;
background-color: #dcbba3;
border-radius: 5px;
box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
text-align: center;
}
.furniture-item:hover {
box-shadow: 0 8px 16px rgba(0, 0, 0, 0.2);
}
.furniture-item img {
width: 100%;
height: auto;
margin-bottom: 0.5rem;
border-radius: 5px;
}
.furniture-item h3 {
margin-bottom: 0.5rem;
}
.furniture-item p {
margin-bottom: 0.5rem;
}
.furniture-item button {
background-color: #b38f71;
color: #fff;
padding: 0.5rem;
border: none;
border-radius: 5px;
cursor: pointer;
}
.furniture-item button:hover {
background-color: #dcbba3;
}
.special-offers-container {
display: flex;
justify-content: space-around;
align-items: center;
flex-wrap: wrap;
margin: 1rem 0;
}
.special-offer {
width: 200px;
padding: 1rem;
text-align: center;
margin: 1rem;
background-color: #ADC3AB;
border-radius: 5px;
box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
transition: all 0.3s ease;
}
.special-offer:hover {
box-shadow: 0 8px 16px rgba(0, 0, 0, 0.2);
transform: translateY(-5px);
}
.special-offer img {
width: 100%;
height: auto;
margin-bottom: 0.5rem;
border-radius: 5px;
}
.modal {
display: none;
position: fixed;
left: 0;
top: 0;
width: 100%;
height: 100%;
background-color: rgba(0, 0, 0, 0.5);
z-index: 1;
overflow: auto;
align-items: center;
}
.modal-content {
background-color: #fefefe;
padding: 2rem;
margin: 10% auto;
width: 30%;
min-width: 300px;
max-width: 80%;
text-align: center;
border-radius: 5px;
box-shadow: 0 1px 8px rgba(0, 0, 0, 0.1);
}
.modalBtn{
background-color: #ADC3AB;
color: #32612D;
padding: 0.5rem;
border: none;
border-radius: 5px;
cursor: pointer;
}
.buts {
text-align: center;
}
.footer-item.address-container p {
margin: 0;
text-align: left;
}
.footer-item p {
text-align: center;
}
.add{
text-align: center;
}
.close {
display: block;
text-align: right;
font-size: 2rem;
color: #333;
cursor: pointer;
}
footer {
background: #32612D;
padding: 1rem;
text-align: center;
margin-top: auto;
}
.footer-container {
display: flex;
justify-content: space-between;
align-items: center;
flex-wrap: wrap;
}
.footer-item {
margin: 1rem 2rem;
}
footer p {
color: #fff;
margin-bottom: 1rem;
}
footer ul {
list-style: none;
}
footer ul li {
display: inline;
margin: 0.5rem;
}
footer ul li a {
text-decoration: none;
color: #fff;
}
@media screen and (max-width: 768px) {
.special-offers-container {
flex-direction: column;
}
}
@media screen and (max-width: 480px) {
h1 {
display: block;
margin-bottom: 1rem;
}
}
.footer-item iframe {
width: 100%;
height: 200px;
}
.footer-item form {
display: inline-flex;
align-items: center;
}
.footer-item input[type="email"] {
padding: 0.5rem;
border: none;
border-radius: 5px;
margin-right: 0.5rem;
}
.footer-item button {
background-color: #ADC3AB;
color: #32612D;
padding: 0.5rem;
border: none;
border-radius: 5px;
cursor: pointer;
}
.footer-item button:hover {
background-color: #32612D;
color: #fff;
}
.social-links-container {
order: 2;
}
.address-container {
order: 1;
}
.google-maps-container {
order: 0;
}
|
cd7cb017fe91c3fe1aa3ca3419d47885
|
{
"intermediate": 0.39859673380851746,
"beginner": 0.40590569376945496,
"expert": 0.1954975724220276
}
|
3,258
|
c#. how to check that type is struct?
|
ea16ac7e58998cc3554f4410ebbfa315
|
{
"intermediate": 0.5129255652427673,
"beginner": 0.23892170190811157,
"expert": 0.2481526881456375
}
|
3,259
|
This is my question for part 1 which you have already given the code and worked ---------------------Part I: Define an RL Environment [30 points]
In this part, we will define a grid-world reinforcement learning environment as an MDP.
While building an RL environment, you need to define possible states, actions, rewards
and other parameters.
STEPS:
1. Choose a scenario for your grid world. You are welcome to use the
visualizationdemo as a reference to visualize it.
An example of idea for RL environment:
• Theme: Lawnmower Grid World with
batteries as positive rewards and rocks as
negative rewards.
• States: {S1 = (0,0), S2 = (0,1), S3 = (0,2),
S4 = (0,3), S5 = (1,0), S6 = (1,1), S7 =
(1,2), S8 = (1,3), S9 = (2,0), S10 = (2,1),
S11 = (2,2), S12 = (2,3), S13 = (3,0), S14 =
(3,1), S15 = (3,2), S16 = (3,3)}
• Actions: {Up, Down, Right, Left}
• Rewards: {-5, -6, +5, +6}
• Objective: Reach the goal state with
maximum reward
2. Define an RL environment following the scenario that you chose.
Environment requirements:
• Min number of states: 12
• Min number of actions: 4
• Min number of rewards: 4
Environment definition should follow the OpenAI Gym structure, which includes
thebasic methods. You can use the “Defining RL env” demo as a base code.
def __init__:
# Initializes the class
# Define action and observation space
def step:
# Executes one timestep within the environment
# Input to the function is an action
def reset:
# Resets the state of the environment to an initial state
def render:
# Visualizes the environment
# Any form like vector representation or visualizing
usingmatplotlib is sufficient
3. Run a random agent for at least 10 timesteps to show that the environment logic
is defined correctly. Print the current state, chosen action, reward and return your
grid world visualization for each step -------------------------------------------------------------------------------------------------------------------------------------------------------------------import numpy as np
import gym
from gym import spaces
import matplotlib.pyplot as plt
class LawnmowerGridWorld(gym.Env):
def __init__(self):
# Define action and observation space
self.observation_space = spaces.Discrete(16)
self.action_space = spaces.Discrete(4)
self.state_matrix = np.zeros((4, 4))
# Define rewards
self.rewards = {-5: 'Rock', -6: 'Rock', 5: 'Battery', 6: 'Battery'}
# Randomly initialize rewardable slots
for _ in range(4): # 4 rewards
x, y = np.random.randint(0, 4, 2)
reward = np.random.choice(list(self.rewards.keys()))
self.state_matrix[x, y] = reward
self.agent_pos = (0, 0)
self.goal = (3, 3)
def step(self, action):
x, y = self.agent_pos
if action == 0: # Up
x = max(0, x - 1)
elif action == 1: # Down
x = min(3, x + 1)
elif action == 2: # Right
y = min(3, y + 1)
else: # Left
y = max(0, y - 1)
self.agent_pos = (x, y)
reward = self.state_matrix[x, y]
self.state_matrix[x, y] = 0 # Remove the reward after collecting
done = (x, y) == self.goal
return self.agent_pos, reward, done, {}
def reset(self):
self.agent_pos = (0, 0)
return self.agent_pos
def render(self):
grid = np.zeros_like(self.state_matrix)
for x in range(4):
for y in range(4):
if self.state_matrix[x, y] != 0:
grid[x, y] = list(self.rewards.keys()).index(self.state_matrix[x, y]) + 1
grid[self.goal] = 9
grid[self.agent_pos] = 8
plt.imshow(grid, cmap='viridis', extent=(-0.5, 3.5, 3.5, -0.5))
plt.xticks(range(4))
plt.yticks(range(4))
plt.grid(True, which='both', linestyle='-', linewidth=0.5)
plt.show()
return grid
# Test Environment
env = LawnmowerGridWorld()
state = env.reset()
print('Initial State:', state)
env.render()
# Run Random Agent
for i in range(10):
action = np.random.choice([0, 1, 2, 3])
state, reward, done, _ = env.step(action)
print('After step {}: State={}, Action={}, Reward={}, Done={}'.format(i+1, state, action, reward, done))
env.render()
if done:
break
env.close()
-----------------------------------------------------I need you to give the code for Part II: Solve your environment using –----------------------------------------------------------------------------------------
SARSA [40 points]
In this part, we implement SARSA (State-Action-Reward-State-Action) algorithm and
apply it to solve the env defined in Part 1.
SARSA is an on-policy reinforcement learning algorithm. The agent updates its Q-values
based on the current state, action, reward, and next state, action pair. It uses an
exploration-exploitation strategy to balance between exploring new actions and exploiting
the knowledge gained so far.
STEPS:
1. Apply SARSA algorithm to solve the environment that was defined in Part I.
2. Try hyperparameter tuning on at least two parameters to get better results for
SARSA. You can explore hyperparameter tuning libraries, e.g. Optuna or make it
manually. Parameters to tune:
a. Discount factor (γ)
b. Epsilon decay rate
c. Epsilon min/max values
d. Number of episodes
e. Max timesteps
Try at least 3 different values for each of the parameters that you choose.
3. Provide the reward graphs and your explanation for each result. In total, you
should have at least 3 graphs and your explanations. Make your suggestion
on the most efficient hyperparameters values for your problem setup.
-----------
|
59f636dc4890a93e563d6759e89a8933
|
{
"intermediate": 0.28593602776527405,
"beginner": 0.5792778134346008,
"expert": 0.13478608429431915
}
|
3,260
|
Hello, this is my question Description
-------------------------------Welcome to the third assignment for this course. The goal of this assignment is to
acquire experience in defining and solving a reinforcement learning (RL) environment,
following Gym standards.
The assignment consists of three parts. The first part focuses on defining an
environment that is based on a Markov decision process (MDP). In the second part, we
will apply a tabular method SARSA to solve an environment that was previously
defined. In the third part, we apply the Q-learning method to solve a grid-world
environment.
Part I: Define an RL Environment [30 points]
In this part, we will define a grid-world reinforcement learning environment as an MDP.
While building an RL environment, you need to define possible states, actions, rewards
and other parameters.
STEPS:
1. Choose a scenario for your grid world. You are welcome to use the
visualizationdemo as a reference to visualize it.
An example of idea for RL environment:
• Theme: Lawnmower Grid World with
batteries as positive rewards and rocks as
negative rewards.
• States: {S1 = (0,0), S2 = (0,1), S3 = (0,2),
S4 = (0,3), S5 = (1,0), S6 = (1,1), S7 =
(1,2), S8 = (1,3), S9 = (2,0), S10 = (2,1),
S11 = (2,2), S12 = (2,3), S13 = (3,0), S14 =
(3,1), S15 = (3,2), S16 = (3,3)}
• Actions: {Up, Down, Right, Left}
• Rewards: {-5, -6, +5, +6}
• Objective: Reach the goal state with
maximum reward
2. Define an RL environment following the scenario that you chose.
Environment requirements:
• Min number of states: 12
• Min number of actions: 4
• Min number of rewards: 4
Environment definition should follow the OpenAI Gym structure, which includes
thebasic methods. You can use the “Defining RL env” demo as a base code.
def init:
# Initializes the class
# Define action and observation space
def step:
# Executes one timestep within the environment
# Input to the function is an action
def reset:
# Resets the state of the environment to an initial state
def render:
# Visualizes the environment
# Any form like vector representation or visualizing
usingmatplotlib is sufficient
3. Run a random agent for at least 10 timesteps to show that the environment logic
is defined correctly. Print the current state, chosen action, reward and return your
grid world visualization for each step.
In your report for Part I:
1. Describe the environment that you defined. Provide a set of actions, states,
rewards, main objective, etc.
2. Provide visualization of your environment.
3. Safety in AI: Write a brief review (∼ 5 sentences) explaining how you ensure the
safety of your environment. E.g. how do you ensure that the agent chooses only
actions that are allowed, that agent is navigating within defined state-space, etc -------------------This is my answer -------------------------------------------------
import numpy as np
import gym
from gym import spaces
import matplotlib.pyplot as plt
class LawnmowerGridWorld(gym.Env):
def init(self):
# Define action and observation space
self.observation_space = spaces.Discrete(16)
self.action_space = spaces.Discrete(4)
self.state_matrix = np.zeros((4, 4))
# Define rewards
self.rewards = {-5: ‘Rock’, -6: ‘Rock’, 5: ‘Battery’, 6: ‘Battery’}
# Randomly initialize rewardable slots
for _ in range(4): # 4 rewards
x, y = np.random.randint(0, 4, 2)
reward = np.random.choice(list(self.rewards.keys()))
self.state_matrix[x, y] = reward
self.agent_pos = (0, 0)
self.goal = (3, 3)
def step(self, action):
x, y = self.agent_pos
if action == 0: # Up
x = max(0, x - 1)
elif action == 1: # Down
x = min(3, x + 1)
elif action == 2: # Right
y = min(3, y + 1)
else: # Left
y = max(0, y - 1)
self.agent_pos = (x, y)
reward = self.state_matrix[x, y]
self.state_matrix[x, y] = 0 # Remove the reward after collecting
done = (x, y) == self.goal
return self.agent_pos, reward, done, {}
def reset(self):
self.agent_pos = (0, 0)
return self.agent_pos
def render(self):
grid = np.zeros_like(self.state_matrix)
for x in range(4):
for y in range(4):
if self.state_matrix[x, y] != 0:
grid[x, y] = list(self.rewards.keys()).index(self.state_matrix[x, y]) + 1
grid[self.goal] = 9
grid[self.agent_pos] = 8
plt.imshow(grid, cmap=‘viridis’, extent=(-0.5, 3.5, 3.5, -0.5))
plt.xticks(range(4))
plt.yticks(range(4))
plt.grid(True, which=‘both’, linestyle=‘-’, linewidth=0.5)
plt.show()
return grid
# Test Environment
env = LawnmowerGridWorld()
state = env.reset()
print(‘Initial State:’, state)
env.render()
# Run Random Agent
for i in range(10):
action = np.random.choice([0, 1, 2, 3])
state, reward, done, _ = env.step(action)
print(‘After step {}: State={}, Action={}, Reward={}, Done={}’.format(i+1, state, action, reward, done))
env.render()
if done:
break--------------------------------Now, can you make change my scenario of grid world and give me the code ---------------
env.close()
|
14f0dc322727ba3946363e84179e06c5
|
{
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"beginner": 0.6539862155914307,
"expert": 0.09188829362392426
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|
3,261
|
this is my method to order a datagrid but is not working what it needs?
public static void OrderDataGrid(DataGrid datagrid, string column, ListSortDirection direction = ListSortDirection.Ascending)
{
datagrid.Items.SortDescriptions.Add(new SortDescription(column, direction));
}
|
7b58390624cce778cb2c20f40e206944
|
{
"intermediate": 0.7718832492828369,
"beginner": 0.12586474418640137,
"expert": 0.1022520512342453
}
|
3,262
|
1. Introduction
In this recitation we will learn how to employ the newsvendor problem to solve a scheduling problem. More specifically, we want to find the optimal number of nurses to be scheduled to work on the quarantine & isolation team at Cornell Health to handle positive COVID tests.
Whenever a student tests positive, this team of nurses calls that student to check on their symptoms and to move them to a room at a hotel. The nursing team also calls students identified as close contacts of the positive student, and who may have already been infected, to move them into quarantine at a hotel. This is done to protect against the possibility that others would be infected by coming into contact with someone who is infectious. In many cases this is straightforward but it sometimes requires a substantial amount of work: the person being contacted might have a medical situation that requires extra attention (either from COVID or another condition); might not answer their phone (requiring repeated calls); might be belligerent or misrepresent the truth (requiring a longer conversation and sometimes the use of additional resources); or might simply have a great number of questions.
This is a newsvendor problem because demand is stochastic and there is a cost both for scheduling too few nurses, and for scheduling too many. If we schedule too many nurses, we create a burden for them and risk burning out the nursing team. If we schedule too few, we can ask unscheduled nurses to come on and work at the last minute, but this forces them to drop their personal life and start working (creating a burden and risking burnout). Also, scheduling too few nurses creates a risk that we might not be able to contact and move to quarantine / isolation all of the students who are potentially infectious, risking the creation of new COVID cases.
We focus on the arrival period for the Spring 2021 semester. During this period, students arriving from elsewhere were testing positive due to infections acquired at home. The rapid increase in arriving students and the changing nature of nationwide and international prevalence relative to the Fall 2020 semester made it difficult to plan based on past experience. This made mathematical modeling extremely useful. Indeed, code close to this recitation was actually used to make staffing decisions at Cornell Health over this period.
# Importing basic libraries
import numpy as np
import pandas as pd
import numpy.random as rand
import matplotlib.pyplot as plt
import matplotlib as mpl
%matplotlib inline
import math
import time
from IPython import display
# Setting the default parameters for the plots produced by matplotlib
# Sets figure size. Width, height in inches.
plt.rcParams["figure.figsize"] = (10,10)
# Sets label font sizes
plt.rcParams['axes.labelsize'] = 14
plt.rcParams['xtick.labelsize'] = 12
plt.rcParams['ytick.labelsize'] = 12
2. Planning for a Single Day
We will start by creating a model that plans for a single day, finding the optimal number of nurses to schedule for that day.
First, we will model the probability of testing positive for an arriving student by specifying some constants.
We model students as arriving from one of the following location categories - 'New York State', 'Middle States', 'New England', 'Midwest', 'South', 'Southwest', 'West', 'Territories', 'USA, unknown', and 'International'.
If we know the distribution of the arriving Cornell student population over these location categories, and the COVID prevalence at each of these locations, we can estimate the probability that an arriving student will person testing postive if they arrive from 'X' location.
We can get the data we need from https://www.cornell.edu/about/facts.cfm
# Data from website
locations = ['New York State','Middle States','New England','Midwest','South',
'Southwest','West','Territories','USA, unknown', 'International'] # Location categories
pop_percent = [27,12,7,6,8,3,11,2,2,22] # Probability distribution of the origin locations for incoming Cornell students
covid_prevalence = [1.3,1.4,1.6,1.9,2.0,1.7,1.8,2.4,2.5,3.1] # the probability that a person coming from each origin has COVID
# Both pop_percent and covid_percents are expressed as percentages between 0 and 100.
# Create a dataframe with the above information
data = pd.DataFrame(list(zip(locations, pop_percent, covid_prevalence)), columns=['location','pop_percent','covid_prevalence'])
data.head()
Question 1: Write code that calculates the probability that an arriving student tests positive. This is
∑
𝑖
𝑃(student origin is 𝑖)𝑃(student is positive|origin is 𝑖)
Store this in a variable prevalence as a probability between 0 and 1.
|
6fd37753de64e47fa44561c8b11278c9
|
{
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"beginner": 0.31610050797462463,
"expert": 0.13857294619083405
}
|
3,263
|
Write me a streamlit app that allows users to upload images and lets them crop it using PIL, they should be able to click at least 3 points of the bounding box, and those coordinates will be printed out after the user clicks Show Coordinates
|
e615c5ec6fcd053a5677f8e2baaa1e43
|
{
"intermediate": 0.6576249599456787,
"beginner": 0.060031965374946594,
"expert": 0.2823430001735687
}
|
3,264
|
3. Planning for Multiple Days
Setup
Our current model only simulates a single day. However, we would like to have an optimal schedule for the number of nurses to employ for an entire period, say 3 weeks. We could do this by making 21 plots using the code above, one for each day, using the number of students scheduled to arrive for that day. We could then show each of those 21 plots to management and have them pick out a point on each plot. This would be a pain, however. It is better to show them a single plot for the entire 3-week period and have them select a point. In addition, we would like to introduce the possibility that a student does not test positive immediately upon arriving and thus contacts multiple students during the time he/she goes undetected. For simplicity, we do not assume the contacted students spread the virus to other contacts. For example, a student arriving on day 0 may not test positive until day 4, and he/she may contact 6 students. We will implement this improved model below. Before we do so, note that our objective is essentially still the same as above: for a particular 𝛼 optimally choose the number of nurses to schedule to minimize the expected total cost. However, our choice of nurses to schedule is no longer a scalar, since we are considering many days as opposed to a single day. Rather, it is a vector (say, 𝑁⃗ ) whose length is the number of days in the period we are considering, and whose 𝑗 th entry is our choice of the number of nurses to employ on day 𝑗 .
For the mathematically inclined, our problem can be restated as the following optimization problem. (You may skip reading this cell, but it may help give you a better understanding of the problem at hand.) Let (𝑁1,...,𝑁𝐷)=𝑁⃗ be a vector giving the number of nurses that will work on each day ( 1 through 𝐷 ), then, for a particular value of 𝛼 , our objective function is: Objective (𝑁⃗) = ExpectedTotalOverage( 𝑁⃗ ) + 𝛼⋅ ExpectedTotalUnderage( 𝑁⃗ ) = ∑𝐷𝑑=1 𝐸 (Overage for day 𝑑 + 𝛼⋅ Underage for day 𝑑 | We use 𝑁𝑑 nurses on day 𝑑 ) ≈ ∑𝐷𝑑=1 1𝑀 ∑𝑀𝑖=1 (Overage for day 𝑑 +𝛼⋅ Underage for day 𝑑 | We use 𝑁𝑑 nurses on day 𝑑 and the random outcome for simulation 𝑖 is (𝑎𝑚𝑜𝑢𝑛𝑡_𝑜𝑓_𝑤𝑜𝑟𝑘)𝑖∈ℝ≥0 ) where 𝑀 is the number of simulations. Let 𝑁∗(𝛼) be the optimal choice of 𝑁1,...,𝑁𝐷 for a particular 𝛼 (i.e. the 𝑁⃗ that minimizes the Objective function), then we would like to ultimately plot the Pareto Frontier : ExpectedTotalOverage( 𝑁∗(𝛼) ) vs. ExpectedTotalUnderage( 𝑁∗(𝛼) ).
Simulation
Here we'll simulate scenarios, where each scenarios consists of the amount of work that needs to be done on each day during the first 3 weeks of the semester
num_days = 21
num_scenarios = 20
# This is the number of people who arrive on each day.
# It was generated using num_arrivals = np.ceil(2000*rand.uniform(size=num_days))
num_arrivals = [1076., 1752., 1783., 1326., 1385., 1454., 1230., 689., 1190.,
1853., 1716., 405., 70., 1097., 1504., 634., 1407., 1222.,
1140., 404., 1703.]
# Create a dataframe containing all 0's where each row will be a scenario
# and each column will be a simulated day. Once we run the code below, the
# values in the dataframe will be the number of nurses needed on each day in
# each scenario
df_sim = pd.DataFrame(0, index=range(num_scenarios), columns=range(num_days))
for i in range(num_scenarios):
for d in range(num_days): # Iterate over days in our simulation
# Simulate the students who arrive on this day
infected_no = rand.binomial(num_arrivals[d],prevalence)
for j in range(infected_no):
days_infectious = rand.geometric(0.3)
day_tested_positive = d + days_infectious
if day_tested_positive < num_days:
contacts = 4
df_sim.loc[i,day_tested_positive] += (30 + 20 * contacts)/(8*60)
df_sim
Question 9: Change the above code so that the number of contacts depends on the number of days the person is infectious. Let the number of contacts be 1.5 times the number of days infectious. This models the fact that a person who has been circulating in the campus population is going to have more local contacts.
|
83a6ec43a3bfdf06ff6f8d1fbb4e19e2
|
{
"intermediate": 0.34931716322898865,
"beginner": 0.4028409719467163,
"expert": 0.24784187972545624
}
|
3,265
|
3. Planning for Multiple Days
Setup
Our current model only simulates a single day. However, we would like to have an optimal schedule for the number of nurses to employ for an entire period, say 3 weeks. We could do this by making 21 plots using the code above, one for each day, using the number of students scheduled to arrive for that day. We could then show each of those 21 plots to management and have them pick out a point on each plot. This would be a pain, however. It is better to show them a single plot for the entire 3-week period and have them select a point. In addition, we would like to introduce the possibility that a student does not test positive immediately upon arriving and thus contacts multiple students during the time he/she goes undetected. For simplicity, we do not assume the contacted students spread the virus to other contacts. For example, a student arriving on day 0 may not test positive until day 4, and he/she may contact 6 students. We will implement this improved model below. Before we do so, note that our objective is essentially still the same as above: for a particular 𝛼 optimally choose the number of nurses to schedule to minimize the expected total cost. However, our choice of nurses to schedule is no longer a scalar, since we are considering many days as opposed to a single day. Rather, it is a vector (say, 𝑁⃗ ) whose length is the number of days in the period we are considering, and whose 𝑗 th entry is our choice of the number of nurses to employ on day 𝑗 .
For the mathematically inclined, our problem can be restated as the following optimization problem. (You may skip reading this cell, but it may help give you a better understanding of the problem at hand.) Let (𝑁1,...,𝑁𝐷)=𝑁⃗ be a vector giving the number of nurses that will work on each day ( 1 through 𝐷 ), then, for a particular value of 𝛼 , our objective function is: Objective (𝑁⃗) = ExpectedTotalOverage( 𝑁⃗ ) + 𝛼⋅ ExpectedTotalUnderage( 𝑁⃗ ) = ∑𝐷𝑑=1 𝐸 (Overage for day 𝑑 + 𝛼⋅ Underage for day 𝑑 | We use 𝑁𝑑 nurses on day 𝑑 ) ≈ ∑𝐷𝑑=1 1𝑀 ∑𝑀𝑖=1 (Overage for day 𝑑 +𝛼⋅ Underage for day 𝑑 | We use 𝑁𝑑 nurses on day 𝑑 and the random outcome for simulation 𝑖 is (𝑎𝑚𝑜𝑢𝑛𝑡_𝑜𝑓_𝑤𝑜𝑟𝑘)𝑖∈ℝ≥0 ) where 𝑀 is the number of simulations. Let 𝑁∗(𝛼) be the optimal choice of 𝑁1,...,𝑁𝐷 for a particular 𝛼 (i.e. the 𝑁⃗ that minimizes the Objective function), then we would like to ultimately plot the Pareto Frontier : ExpectedTotalOverage( 𝑁∗(𝛼) ) vs. ExpectedTotalUnderage( 𝑁∗(𝛼) ).
Simulation
Here we'll simulate scenarios, where each scenarios consists of the amount of work that needs to be done on each day during the first 3 weeks of the semester
num_days = 21
num_scenarios = 20
# This is the number of people who arrive on each day.
# It was generated using num_arrivals = np.ceil(2000*rand.uniform(size=num_days))
num_arrivals = [1076., 1752., 1783., 1326., 1385., 1454., 1230., 689., 1190.,
1853., 1716., 405., 70., 1097., 1504., 634., 1407., 1222.,
1140., 404., 1703.]
# Create a dataframe containing all 0's where each row will be a scenario
# and each column will be a simulated day. Once we run the code below, the
# values in the dataframe will be the number of nurses needed on each day in
# each scenario
df_sim = pd.DataFrame(0, index=range(num_scenarios), columns=range(num_days))
for i in range(num_scenarios):
for d in range(num_days): # Iterate over days in our simulation
# Simulate the students who arrive on this day
infected_no = rand.binomial(num_arrivals[d],prevalence)
for j in range(infected_no):
days_infectious = rand.geometric(0.3)
day_tested_positive = d + days_infectious
if day_tested_positive < num_days:
contacts = 4
df_sim.loc[i,day_tested_positive] += (30 + 20 * contacts)/(8*60)
df_sim
Question 9: Change the above code so that the number of contacts depends on the number of days the person is infectious. Let the number of contacts be 1.5 times the number of days infectious. This models the fact that a person who has been circulating in the campus population is going to have more local contacts.
|
b6f29ec7d9f2946caadd20dc317d1489
|
{
"intermediate": 0.34931716322898865,
"beginner": 0.4028409719467163,
"expert": 0.24784187972545624
}
|
3,266
|
hi there, I'm using vite Vue 3 as front end and I want to build the sign up and login components give me simple examples and use bootstrap 5 for css style classes.I'm here to answer any questions you may have aswell to clearify.
|
1235d9fd84f4f4e20f491eb259a22ed0
|
{
"intermediate": 0.4382938742637634,
"beginner": 0.31955379247665405,
"expert": 0.2421523481607437
}
|
3,267
|
go vs php
|
82e8ecd1671bbdab95a6cdaaac4e27da
|
{
"intermediate": 0.4235503077507019,
"beginner": 0.34859699010849,
"expert": 0.2278526872396469
}
|
3,268
|
[~, i] = max(abs(U(k:n,k)));
i = i+k-1;
give another way to implement above two lines in matlab
|
bb1bd674600b294754197fd72870e381
|
{
"intermediate": 0.2966441810131073,
"beginner": 0.33713337779045105,
"expert": 0.36622247099876404
}
|
3,269
|
Copy paste text to notepad vba
|
20da1d049b9009d965334f739b0bfe70
|
{
"intermediate": 0.35245710611343384,
"beginner": 0.2511753737926483,
"expert": 0.39636749029159546
}
|
3,270
|
Perl source to quickly check if any variable in a list of variables is undefined
|
67df09d75a6ce67bc567aa9bfc266d5e
|
{
"intermediate": 0.3055756092071533,
"beginner": 0.4888480007648468,
"expert": 0.20557640492916107
}
|
3,271
|
Given an array of variables of arbitrary size, write Perl code to error if none of them are defined
|
cc928913f0e0ca1490caa844ccb50dba
|
{
"intermediate": 0.2727622091770172,
"beginner": 0.5084468722343445,
"expert": 0.2187909334897995
}
|
3,272
|
how to print public ip alpine linux console?
|
c90d8abfdd553920debdc1c847172e5d
|
{
"intermediate": 0.4200783967971802,
"beginner": 0.24319878220558167,
"expert": 0.33672279119491577
}
|
3,273
|
i am currently coding a windows form .network frame work i want to take info inputed through text box to create an object of an existing class and i want the object created to be inserted into a database
|
40f04f633ea97a06d21baddbc6c90e25
|
{
"intermediate": 0.5508185029029846,
"beginner": 0.17519491910934448,
"expert": 0.2739866077899933
}
|
3,274
|
le puedes agregar un required a este campo <input type="text" id="nameFemale" name="nombre" placeholder="Name" >
|
eb8ae4a59adf9eeddc009cfafd597e43
|
{
"intermediate": 0.36517730355262756,
"beginner": 0.25270774960517883,
"expert": 0.3821149170398712
}
|
3,275
|
Is it highly advisable for the Restic local repository to be on an SSD, or is regular hard drive OK?
|
02750ce4294e4c16a727791c40ab65ea
|
{
"intermediate": 0.3472859263420105,
"beginner": 0.2627246379852295,
"expert": 0.3899894952774048
}
|
3,276
|
With the Automatic mouse and keyboard app, how do i make bkgnd_Keystroke work? Also, how do i use FindVirtualScreenImages?
|
d63b9250120f9f3c78eb4b9de15e8fc6
|
{
"intermediate": 0.8073557615280151,
"beginner": 0.08844577521085739,
"expert": 0.10419841855764389
}
|
3,277
|
This is the head of my dataset with file name DATA.csv ------------------------------------------------------------------------------------------------------------------------------------------------posres multi clinend mech sampsize budget impact time status
<int> <int> <int> <chr> <int> <dbl> <dbl> <dbl> <int>
1 0 0 1 R01 39876 8.016941 44.016 11.203285 1
2 0 0 1 R01 39876 8.016941 23.494 15.178645 1
3 0 0 1 R01 8171 7.612606 8.391 24.410678 1
4 0 0 1 Contract 24335 11.771928 15.402 2.595483 1
5 0 0 1 Contract 33357 76.517537 16.783 8.607803 1
6 0 0 1 Contract 10355 9.809938 16.783 8.607803 1----------------------------------------------------------------------------------------------------------------------------------------------------------# Question 2 (25 points)
A data set from "DATA.csv" represents publication times for 244 clinical trials funded by the National Heart, Lung, and Blood Institute. Using Log-Rank Test in R, estimate if the Kaplan-Meier Survival Curves from two subpopulations stratified by “posres” variable are significantly different.
|
5b202ebdd6d759e4d8f3ce31457b7ad1
|
{
"intermediate": 0.25691285729408264,
"beginner": 0.5232107043266296,
"expert": 0.21987642347812653
}
|
3,278
|
Mern e-commerce application
|
225d296c773894955e73522e56709aa5
|
{
"intermediate": 0.3548031449317932,
"beginner": 0.36142534017562866,
"expert": 0.2837715744972229
}
|
3,279
|
could you write a fivem server dumper program
|
fd2607c44064ba1f444921cbdad28473
|
{
"intermediate": 0.429564505815506,
"beginner": 0.18302220106124878,
"expert": 0.3874133229255676
}
|
3,280
|
How to specify interface with which to use wget
|
f0837fb4d1a687c96abadb82e7a0b7e3
|
{
"intermediate": 0.5347100496292114,
"beginner": 0.2684357166290283,
"expert": 0.19685418903827667
}
|
3,281
|
given that this section has a slides, and my file directory to the first desired image is
C:\Users\Kaddra52\Desktop\DDW\assets\images\homeslide.png
fix this html and find css for reference
HTML snippet:
<section class="slideshow-section">
<div class="slideshow-container">
<div class="mySlides fade">
<img src="assets/images/homeslide.png" alt="Tents" style="width:100%">
</div>
<div class="mySlides fade">
<img src="https://via.placeholder.com/600x400" alt="Cookers" style="width:100%">
</div>
<div class="mySlides fade">
<img src="https://via.placeholder.com/600x400" alt="Camping Gear" style="width:100%">
</div>
<a class="prev" onclick="plusSlides(-1)">❮</a>
<a class="next" onclick="plusSlides(1)">❯</a>
</div>
<div style="text-align:center">
<span class="dot" onclick="currentSlide(1)"></span>
<span class="dot" onclick="currentSlide(2)"></span>
<span class="dot" onclick="currentSlide(3)"></span>
</div>
</section>
CSS:html, body, h1, h2, h3, h4, p, a, ul, li, div, main, header, section, footer, img {
margin: 0;
padding: 0;
border: 0;
font-size: 100%;
font-family: inherit;
vertical-align: baseline;
box-sizing: border-box;
}
body {
font-family: "Cabin", sans-serif;
line-height: 1.5;
color: #333;
width: 100%;
margin: 0;
padding: 0;
min-height: 100vh;
flex-direction: column;
display: flex;
background-image: url("../assets/images/cover.jpg");
background-size: cover;
}
header {
background: #00000000;
padding: 0.5rem 2rem;
text-align: center;
color: #32612D;
font-size: 1.2rem;
}
main{
flex-grow: 1;
}
.sticky-nav {
position: -webkit-sticky;
position: sticky;
top: 0;
z-index: 1000;
}
.nav-container {
display: flex;
justify-content: space-between;
align-items: center;
flex-wrap: wrap;
}
.search-container {
display: inline-block;
position: relative;
}
.search-container input[type="text"] {
padding: 0.8rem;
border: none;
border-bottom: 1.5px solid #32612D;
outline: none;
color: #32612D;
font-size: 1rem;
background-color: transparent;
margin-right: 30rem;
margin-bottom: 12px;
width: 65%;
}
.search-container input[type="text"]::placeholder {
color: #32612D;
opacity: 0.5;
}
.search-icon {
margin-right: 0.8rem;
width: 24px;
height: auto;
vertical-align: middle;
position: absolute;
top: 50%;
margin-top: -16px;
}
.search-container input[type="text"]:focus {
border-color: #ADC3AB;
}
.search-container button[type="submit"] {
display: none;
}
.logo {
width: 50px;
height: auto;
margin-right: 1rem;
}
h1 {
flex-grow: 1;
text-align: left;
text-shadow: 1px 1px #b3814b;
}
nav ul {
display: inline
list-style: none;
}
nav ul li {
display: inline;
margin-left: 1rem;
}
nav ul li a {
text-decoration: none;
color: #32612D;
position: relative;
transition: color 0.3s ease;
text-shadow: 0.2px 0.2px #b3814b;
}
@media screen and (max-width: 768px) {
.nav-container {
flex-direction: column;
}
h1 {
margin-bottom: 1rem;
}
}
nav ul li a {
text-decoration: none;
color: #32612D;
position: relative;
transition: color 0.3s ease;
}
nav ul li a::after {
content: '';
position: absolute;
bottom: 0;
left: 0;
width: 100%;
height: 2px;
background-color: #000;
transform: scaleX(0);
transition: transform 0.3s;
}
nav ul li a:hover {
color: #000000;
}
nav ul li a:hover::after {
transform: scaleX(1);
}
.slideshow-container {
width: 100%;
position: relative;
margin: 1rem 0;
}
.mySlides {
display: none;
}
.mySlides img {
width: 100%;
height: auto;
}
/* Slideshow navigation */
.prev, .next {
cursor: pointer;
position: absolute;
top: 50%;
width: auto;
margin-top: -22px;
padding: 16px;
color: #32612D;
font-weight: bold;
font-size: 18px;
transition: 0.6s ease;
border-radius: 0 3px 3px 0;
user-select: none;
}
.next {
right: 0;
border-radius: 3px 0 0 3px;
}
.prev:hover, .next:hover {
background-color: rgba(255,255,255,0.8);
}
.dot {
cursor: pointer;
height: 15px;
width: 15px;
margin: 0 2px;
background-color: #bbb;
border-radius: 50%;
display: inline-block;
transition: background-color 0.6s ease;
}
.dot:hover {
background-color: #717171;
}
.fade {
-webkit-animation-name: fade;
-webkit-animation-duration: 1.5s;
animation-name: fade;
animation-duration: 1.5s;
}
@-webkit-keyframes fade {
from {opacity: .4}
to {opacity: 1}
}
@keyframes fade {
from {opacity: .4}
to {opacity: 1}
}
.catalog {
display: flex;
flex-wrap: wrap;
justify-content: center;
margin: 2rem 0;
}
.catalog-item {
width: 200px;
padding: 1rem;
margin: 1rem;
background-color: #ADC3AB;
border-radius: 5px;
box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
text-align: center;
}
.catalog-item:hover {
box-shadow: 0 8px 16px rgba(0, 0, 0, 0.2);
}
.catalog-item img {
width: 100%;
height: auto;
margin-bottom: 0.5rem;
border-radius: 5px;
}
.catalog-item h3 {
margin-bottom: 0.5rem;
}
.catalog-item p {
margin-bottom: 0.5rem;
}
.catalog-item button {
background-color: #32612D;
color: #fff;
padding: 0.5rem;
border: none;
border-radius: 5px;
cursor: pointer;
}
.catalog-item button:hover {
background-color: #ADC3AB;
}
.category-title {
width: 100%;
text-align: center;
font-size: 24px;
font-weight: bold;
margin-bottom: 1rem;
color: #F5F3CE;
text-shadow: 2px 2px #0A381F;
}
.featured-section {
padding: 1rem;
text-align: center;
margin: 1rem 0;
}
.filter {
margin-bottom: 5rem;
}
.filter select {
padding: 0.5rem;
font-size: 0.9rem;
}
footer form {
display: inline-flex;
align-items: center;
}
.about-section {
padding: 1rem;
text-align: center;
margin: 1rem 0;
}
.featured-section {
padding: 1rem;
text-align: center;
margin: 1rem 0;
}
.featured-section h2 {
font-size: 1.5rem;
margin-bottom: 1rem;
}
.featured-container {
display: flex;
justify-content: space-around;
align-items: center;
flex-wrap: wrap;
margin: 1rem 0;
}
.featured-product {
width: 150px;
padding: 1rem;
background-color: #ADC3AB;
border-radius: 5px;
box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
transition: all 0.3s ease;
margin: 0.5rem;
}
.featured-product:hover {
box-shadow: 0 8px 16px rgba(0, 0, 0, 0.2);
transform: translateY(-5px);
}
.featured-product img {
width: 100%;
height: auto;
margin-bottom: 1rem;
border-radius: 5px;
}
.furniture-item {
width: 200px;
padding: 1rem;
margin: 1rem;
background-color: #dcbba3;
border-radius: 5px;
box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
text-align: center;
}
.furniture-item:hover {
box-shadow: 0 8px 16px rgba(0, 0, 0, 0.2);
}
.furniture-item img {
width: 100%;
height: auto;
margin-bottom: 0.5rem;
border-radius: 5px;
}
.furniture-item h3 {
margin-bottom: 0.5rem;
}
.furniture-item p {
margin-bottom: 0.5rem;
}
.furniture-item button {
background-color: #b38f71;
color: #fff;
padding: 0.5rem;
border: none;
border-radius: 5px;
cursor: pointer;
}
.furniture-item button:hover {
background-color: #dcbba3;
}
.special-offers-container {
display: flex;
justify-content: space-around;
align-items: center;
flex-wrap: wrap;
margin: 1rem 0;
}
.special-offer {
width: 200px;
padding: 1rem;
text-align: center;
margin: 1rem;
background-color: #ADC3AB;
border-radius: 5px;
box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
transition: all 0.3s ease;
}
.special-offer:hover {
box-shadow: 0 8px 16px rgba(0, 0, 0, 0.2);
transform: translateY(-5px);
}
.special-offer img {
width: 100%;
height: auto;
margin-bottom: 0.5rem;
border-radius: 5px;
}
.modal {
display: none;
position: fixed;
left: 0;
top: 0;
width: 100%;
height: 100%;
background-color: rgba(0, 0, 0, 0.5);
z-index: 1;
overflow: auto;
align-items: center;
}
.modal-content {
background-color: #fefefe;
padding: 2rem;
margin: 10% auto;
width: 30%;
min-width: 300px;
max-width: 80%;
text-align: center;
border-radius: 5px;
box-shadow: 0 1px 8px rgba(0, 0, 0, 0.1);
}
.modalBtn{
background-color: #ADC3AB;
color: #32612D;
padding: 0.5rem;
border: none;
border-radius: 5px;
cursor: pointer;
}
.buts {
text-align: center;
}
.footer-item.address-container p {
margin: 0;
text-align: left;
}
.footer-item p {
text-align: center;
}
.add{
text-align: center;
}
.close {
display: block;
text-align: right;
font-size: 2rem;
color: #333;
cursor: pointer;
}
footer {
background: #32612D;
padding: 1rem;
text-align: center;
margin-top: auto;
}
.footer-container {
display: flex;
justify-content: space-between;
align-items: center;
flex-wrap: wrap;
}
.footer-item {
margin: 1rem 2rem;
}
footer p {
color: #fff;
margin-bottom: 1rem;
}
footer ul {
list-style: none;
}
footer ul li {
display: inline;
margin: 0.5rem;
}
footer ul li a {
text-decoration: none;
color: #fff;
}
@media screen and (max-width: 768px) {
.special-offers-container {
flex-direction: column;
}
}
@media screen and (max-width: 480px) {
h1 {
display: block;
margin-bottom: 1rem;
}
}
.footer-item iframe {
width: 100%;
height: 200px;
}
.footer-item form {
display: inline-flex;
align-items: center;
}
.footer-item input[type="email"] {
padding: 0.5rem;
border: none;
border-radius: 5px;
margin-right: 0.5rem;
}
.footer-item button {
background-color: #ADC3AB;
color: #32612D;
padding: 0.5rem;
border: none;
border-radius: 5px;
cursor: pointer;
}
.footer-item button:hover {
background-color: #32612D;
color: #fff;
}
.social-links-container {
order: 2;
}
.address-container {
order: 1;
}
.google-maps-container {
order: 0;
}
|
85461990f12544bf0b77516c35a6d95f
|
{
"intermediate": 0.3375437259674072,
"beginner": 0.4793781340122223,
"expert": 0.1830781251192093
}
|
3,282
|
c++ initialize an array of boolean arrays of length n by mm
|
d2d7b9299ebd6577c1e56c3794225311
|
{
"intermediate": 0.36448749899864197,
"beginner": 0.26932066679000854,
"expert": 0.3661918342113495
}
|
3,283
|
dp3[(s + t3[c]) % RES][l + 1] = 1;
expression must have integral or unscoped enum typeC/C++(2140)
|
5bc9c92ae374b16b9232b2f6d77dc672
|
{
"intermediate": 0.23300130665302277,
"beginner": 0.49507325887680054,
"expert": 0.2719254493713379
}
|
3,284
|
dp3[(s + t3[c])][l + 1] = 1;
cast from pointer to smaller type 'int' loses informationgcc
expression must have integral or unscoped enum typeC/C++(2140)
|
7b768a4899288d17c9e650acc7db1918
|
{
"intermediate": 0.3097006380558014,
"beginner": 0.46223992109298706,
"expert": 0.22805947065353394
}
|
3,285
|
hi
|
45615dd3c47191dcb19e59b5468a5238
|
{
"intermediate": 0.3246487081050873,
"beginner": 0.27135494351387024,
"expert": 0.40399640798568726
}
|
3,286
|
i need to make anew activity in my application with java only and its content for quaran fm via network and with multible voices in tha activity so i need the code of xml and java class and code dependencesto build gradle and code of mainfest to play fm back ground and all things that may be usefull
|
eee53bfee364d575cedf004386c55b58
|
{
"intermediate": 0.541733980178833,
"beginner": 0.3015870749950409,
"expert": 0.1566789597272873
}
|
3,287
|
c++ initialize 2d boolean array
|
7aa2b784cb4d1da324a5b4630104dee9
|
{
"intermediate": 0.36368364095687866,
"beginner": 0.36801430583000183,
"expert": 0.2683020532131195
}
|
3,288
|
import requests
import json
import datetime
import streamlit as st
from itertools import zip_longest
import os
def basic_info():
config = dict()
config["access_token"] = st.secrets["access_token"]
config['instagram_account_id'] = st.secrets.get("instagram_account_id", "")
config["version"] = 'v16.0'
config["graph_domain"] = 'https://graph.facebook.com/'
config["endpoint_base"] = config["graph_domain"] + config["version"] + '/'
return config
def InstaApiCall(url, params, request_type):
if request_type == 'POST':
req = requests.post(url, params)
else:
req = requests.get(url, params)
res = dict()
res["url"] = url
res["endpoint_params"] = params
res["endpoint_params_pretty"] = json.dumps(params, indent=4)
res["json_data"] = json.loads(req.content)
res["json_data_pretty"] = json.dumps(res["json_data"], indent=4)
return res
def getUserMedia(params, pagingUrl=''):
Params = dict()
Params['fields'] = 'id,caption,media_type,media_url,permalink,thumbnail_url,timestamp,username,like_count,comments_count'
Params['access_token'] = params['access_token']
if not params['endpoint_base']:
return None
if pagingUrl == '':
url = params['endpoint_base'] + params['instagram_account_id'] + '/media'
else:
url = pagingUrl
return InstaApiCall(url, Params, 'GET')
def saveCount(count, filename):
with open(filename, 'w') as f:
json.dump(count, f, indent=4)
def getCount(filename):
try:
with open(filename, 'r') as f:
return json.load(f)
except (FileNotFoundError, json.decoder.JSONDecodeError):
return {}
st.set_page_config(layout="wide")
params = basic_info()
if not params['instagram_account_id']:
st.write('.envファイルでinstagram_account_idを確認')
else:
response = getUserMedia(params)
if not response:
st.write('.envファイルでaccess_tokenを確認')
else:
posts = response['json_data']['data'][::-1]
NUM_COLUMNS = 6
MAX_WIDTH = 1000
BOX_WIDTH = int(MAX_WIDTH / NUM_COLUMNS)
BOX_HEIGHT = 400
show_description = st.checkbox("キャプションを表示")
posts.reverse()
post_groups = [list(filter(None, group)) for group in zip_longest(*[iter(posts)] * NUM_COLUMNS)]
count_filename = "count.json"
count = getCount(count_filename)
today = datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d')
yesterday = (datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))) - datetime.timedelta(days=1)).strftime('%Y-%m-%d')
if today not in count:
count[today] = {}
if datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%H:%M') == '23:59':
count[yesterday] = count[today]
for post_group in post_groups:
with st.container():
columns = st.columns(NUM_COLUMNS)
for i, post in enumerate(post_group):
with columns[i]:
st.image(post['media_url'], width=BOX_WIDTH, use_column_width=True)
st.write(f"{datetime.datetime.strptime(post['timestamp'], '%Y-%m-%dT%H:%M:%S%z').astimezone(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d %H:%M:%S')}")
like_count_diff = post['like_count'] - count.get(yesterday, {}).get(post['id'], {}).get('like_count', post['like_count'])
comment_count_diff = post['comments_count'] - count.get(yesterday, {}).get(post['id'], {}).get('comments_count', post['comments_count'])
st.write(f"👍: {post['like_count']} ({'+' if like_count_diff >= 0 else ''}{like_count_diff})\n💬: {post['comments_count']} ({'+' if comment_count_diff >= 0 else ''}{comment_count_diff})\n")
caption = post['caption']
if caption is not None:
caption = caption.strip()
if "[Description]" in caption:
caption = caption.split("[Description]")[1].lstrip()
if "[Tags]" in caption:
caption = caption.split("[Tags]")[0].rstrip()
caption = caption.replace("#", "")
caption = caption.replace([model],👗)
caption = caption.replace("[Equip]", "📷")
caption = caption.replace("[Develop]", "🖨")
if show_description:
st.write(caption or "No caption provided")
else:
st.write(caption[:0] if caption is not None and len(caption) > 50 else caption or "No caption provided")
count[today][post['id']] = {'like_count': post['like_count'], 'comments_count': post['comments_count']}
saveCount(count, count_filename)
'''
上記のコードを以下の要件をすべて満たして改修してください？？
- 説明は表記せずPython用のコードのみ出力する
- "caption = post['caption']"に関するコードは残存させる
- 毎日JST23:59に現時点でのフォロワー数を取得し、すでに別件で使用している"count.json"内に保存するようコードを改修する
- StreamlitのUIで"説明文を表示"の上に"instagramアカウント名"、"現時点でのフォロワー数(Follower)"、'count.json'と現時点のフォロワー数との差分を"(-1)や(±0)や(+2)"のように、一段階大きめのサイズで表示する
- "いいね数"や"コメント数"の差分表示の"()"内において、全投稿の中で最も増加したものについては、"+"と"増減数"を"赤"で表示するよう改修する
|
781a38ab035ee60d47a7241d70014608
|
{
"intermediate": 0.38020947575569153,
"beginner": 0.39222896099090576,
"expert": 0.2275616079568863
}
|
3,289
|
Hi, You helped me implement a Q Actor Critic algorithm which worked well for Cartpole-v1 , Lunar Lander-v2 but not for Bipedal Walker. So, I'll provide you the entire implementation and I want you to make the necessary modifications to our code. Keep in mind that the code should work for all the three mentioned env's. In my opinion, our current implementation only works for discrete space whereas Bipedal Walker is a continuous space which causing the error. I'm impressed by your work yesterday. You did a great job. Keep up the good work as always. Here is the implementation:
class QActorCritic(nn.Module):
def __init__(self, num_inputs, num_outputs):
super(QActorCritic, self).__init__()
self.policy_net = nn.Sequential(
nn.Linear(num_inputs, 64),
nn.ReLU(),
nn.Linear(64, 64),
nn.ReLU(),
nn.Linear(64, num_outputs),
nn.Softmax(dim=1)
)
self.q_net = nn.Sequential(
nn.Linear(num_inputs, 64),
nn.ReLU(),
nn.Linear(64, 64),
nn.ReLU(),
nn.Linear(64, num_outputs)
)
def forward(self, x):
raise NotImplementedError
def get_action_probs(self, x):
x = torch.from_numpy(x).float().unsqueeze(0).to(device)
action_probs = self.policy_net(x)
return action_probs
def get_q_values(self, x):
x = torch.from_numpy(x).float().unsqueeze(0).to(device)
q_values = self.q_net(x)
return q_values def train(env, device, model, lr=1e-3, num_episodes=500, gamma=0.99):
policy_optimizer = optim.Adam(model.policy_net.parameters(), lr=lr)
q_optimizer = optim.Adam(model.q_net.parameters(), lr=lr)
total_rewards = []
for episode in range(num_episodes):
state = env.reset()
episode_reward = 0
while True:
action_probs = model.get_action_probs(state)
action_distr = Categorical(action_probs)
action = action_distr.sample().item()
next_state, reward, done, _ = env.step(action)
next_action_probs = model.get_action_probs(next_state)
next_action_distr = Categorical(next_action_probs)
next_action = next_action_distr.sample().item()
with torch.no_grad():
target = reward + gamma * model.get_q_values(next_state)[0, next_action]
policy_loss = -action_distr.log_prob(torch.tensor([action]).to(device)) * (target - model.get_q_values(state)[0, action])
q_loss = (target - model.get_q_values(state)[0, action]).pow(2).to(device)
policy_optimizer.zero_grad()
policy_loss.backward()
policy_optimizer.step()
q_optimizer.zero_grad()
q_loss.backward()
q_optimizer.step()
state = next_state
episode_reward += reward
if done:
break
total_rewards.append(episode_reward)
if episode % 100 == 0:
print(f"Episode: {episode}, reward: {episode_reward}")
return total_rewards # env = gym.make('BipedalWalker-v3')
num_inputs = env.observation_space.shape[0]
num_outputs = env.action_space.shape[0]
q_actor_critic = QActorCritic(num_inputs, num_outputs).to(device)
train_rewards = train(env,device, q_actor_critic, num_episodes=1000, lr=1e-4)
print('Bipedal Walker Training results:')
plot_rewards('BipedalWalker-v3', 'Training', train_rewards)
return total_rewards
|
b0861a59c394df14b22e386018f3eba2
|
{
"intermediate": 0.37862351536750793,
"beginner": 0.3914855718612671,
"expert": 0.2298908829689026
}
|
3,290
|
import requests
import json
import datetime
import streamlit as st
from itertools import zip_longest
import os
def basic_info():
config = dict()
config["access_token"] = st.secrets["access_token"]
config['instagram_account_id'] = st.secrets.get("instagram_account_id", "")
config["version"] = 'v16.0'
config["graph_domain"] = 'https://graph.facebook.com/'
config["endpoint_base"] = config["graph_domain"] + config["version"] + '/'
return config
def InstaApiCall(url, params, request_type):
if request_type == 'POST':
req = requests.post(url, params)
else:
req = requests.get(url, params)
res = dict()
res["url"] = url
res["endpoint_params"] = params
res["endpoint_params_pretty"] = json.dumps(params, indent=4)
res["json_data"] = json.loads(req.content)
res["json_data_pretty"] = json.dumps(res["json_data"], indent=4)
return res
def getUserMedia(params, pagingUrl=''):
Params = dict()
Params['fields'] = 'id,caption,media_type,media_url,permalink,thumbnail_url,timestamp,username,like_count,comments_count'
Params['access_token'] = params['access_token']
if not params['endpoint_base']:
return None
if pagingUrl == '':
url = params['endpoint_base'] + params['instagram_account_id'] + '/media'
else:
url = pagingUrl
return InstaApiCall(url, Params, 'GET')
def saveCount(count, filename):
with open(filename, 'w') as f:
json.dump(count, f, indent=4)
def getCount(filename):
try:
with open(filename, 'r') as f:
return json.load(f)
except (FileNotFoundError, json.decoder.JSONDecodeError):
return {}
st.set_page_config(layout="wide")
params = basic_info()
if not params['instagram_account_id']:
st.write('.envファイルでinstagram_account_idを確認')
else:
response = getUserMedia(params)
if not response:
st.write('.envファイルでaccess_tokenを確認')
else:
posts = response['json_data']['data'][::-1]
NUM_COLUMNS = 6
MAX_WIDTH = 1000
BOX_WIDTH = int(MAX_WIDTH / NUM_COLUMNS)
BOX_HEIGHT = 400
show_description = st.checkbox("キャプションを表示")
posts.reverse()
post_groups = [list(filter(None, group)) for group in zip_longest(*[iter(posts)] * NUM_COLUMNS)]
count_filename = "count.json"
count = getCount(count_filename)
today = datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d')
yesterday = (datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))) - datetime.timedelta(days=1)).strftime('%Y-%m-%d')
if today not in count:
count[today] = {}
if datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%H:%M') == '23:59':
count[yesterday] = count[today]
for post_group in post_groups:
with st.container():
columns = st.columns(NUM_COLUMNS)
for i, post in enumerate(post_group):
with columns[i]:
st.image(post['media_url'], width=BOX_WIDTH, use_column_width=True)
st.write(f"{datetime.datetime.strptime(post['timestamp'], '%Y-%m-%dT%H:%M:%S%z').astimezone(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d %H:%M:%S')}")
like_count_diff = post['like_count'] - count.get(yesterday, {}).get(post['id'], {}).get('like_count', post['like_count'])
comment_count_diff = post['comments_count'] - count.get(yesterday, {}).get(post['id'], {}).get('comments_count', post['comments_count'])
st.write(f"👍: {post['like_count']} ({'+' if like_count_diff >= 0 else ''}{like_count_diff})\n💬: {post['comments_count']} ({'+' if comment_count_diff >= 0 else ''}{comment_count_diff})\n")
caption = post['caption']
if caption is not None:
caption = caption.strip()
if "[Description]" in caption:
caption = caption.split("[Description]")[1].lstrip()
if "[Tags]" in caption:
caption = caption.split("[Tags]")[0].rstrip()
caption = caption.replace("#", "")
caption = caption.replace([model],👗)
caption = caption.replace("[Equip]", "📷")
caption = caption.replace("[Develop]", "🖨")
if show_description:
st.write(caption or "No caption provided")
else:
st.write(caption[:0] if caption is not None and len(caption) > 50 else caption or "No caption provided")
count[today][post['id']] = {'like_count': post['like_count'], 'comments_count': post['comments_count']}
saveCount(count, count_filename)
'''
上記のコードを以下の要件をすべて満たして改修してください
- 説明は表記せずPython用のコードのみ出力する
- "caption = post['caption']以降のブロックのコードは残存させ利用する
- 現状の"いいね数"と"コメント数"の取得と保存に関するコードは残存させ利用する
- 毎日JST23:59に現時点でのフォロワー数を取得し、すでに別件で使用している"count.json"内に保存するようコードを改修する
- StreamlitのUIで"説明文を表示"の上に"instagramアカウント名"、"現時点でのフォロワー数(Follower)"、'count.json'と現時点のフォロワー数との差分を"(-1)や(±0)や(+2)"と、横並びで一段階大きめのサイズで表示する
- "いいね数"や"コメント数"の差分表示の"()"内において、全投稿の中で最も増加したものについては、"+"と"増減数"を"赤"で表示するよう改修する
|
bca175952b32325547f4727a6f78e586
|
{
"intermediate": 0.38020947575569153,
"beginner": 0.39222896099090576,
"expert": 0.2275616079568863
}
|
3,291
|
利用结构化分析方法对学生选课管理系统进行需求分析，完成其数据流图（由加工、数据流、文件、源点/终点4种元素组成），要求至少画出三层的数据流图。
①顶层数据流图
②1层数据流图
③2层数据流图
|
55252dfc4ccd7058680d4658400aa922
|
{
"intermediate": 0.32135728001594543,
"beginner": 0.37160468101501465,
"expert": 0.30703800916671753
}
|
3,292
|
import requests
import json
import datetime
import streamlit as st
from itertools import zip_longest
import os
def basic_info():
config = dict()
config["access_token"] = st.secrets["access_token"]
config['instagram_account_id'] = st.secrets.get("instagram_account_id", "")
config["version"] = 'v16.0'
config["graph_domain"] = 'https://graph.facebook.com/'
config["endpoint_base"] = config["graph_domain"] + config["version"] + '/'
return config
def InstaApiCall(url, params, request_type):
if request_type == 'POST':
req = requests.post(url, params)
else:
req = requests.get(url, params)
res = dict()
res["url"] = url
res["endpoint_params"] = params
res["endpoint_params_pretty"] = json.dumps(params, indent=4)
res["json_data"] = json.loads(req.content)
res["json_data_pretty"] = json.dumps(res["json_data"], indent=4)
return res
def getUserMedia(params, pagingUrl=''):
Params = dict()
Params['fields'] = 'id,caption,media_type,media_url,permalink,thumbnail_url,timestamp,username,like_count,comments_count'
Params['access_token'] = params['access_token']
if not params['endpoint_base']:
return None
if pagingUrl == '':
url = params['endpoint_base'] + params['instagram_account_id'] + '/media'
else:
url = pagingUrl
return InstaApiCall(url, Params, 'GET')
def saveCount(count, filename):
with open(filename, 'w') as f:
json.dump(count, f, indent=4)
def getCount(filename):
try:
with open(filename, 'r') as f:
return json.load(f)
except (FileNotFoundError, json.decoder.JSONDecodeError):
return {}
st.set_page_config(layout="wide")
params = basic_info()
if not params['instagram_account_id']:
st.write('.envファイルでinstagram_account_idを確認')
else:
response = getUserMedia(params)
if not response:
st.write('.envファイルでaccess_tokenを確認')
else:
posts = response['json_data']['data'][::-1]
NUM_COLUMNS = 6
MAX_WIDTH = 1000
BOX_WIDTH = int(MAX_WIDTH / NUM_COLUMNS)
BOX_HEIGHT = 400
show_description = st.checkbox("キャプションを表示")
posts.reverse()
post_groups = [list(filter(None, group)) for group in zip_longest(*[iter(posts)] * NUM_COLUMNS)]
count_filename = "count.json"
count = getCount(count_filename)
today = datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d')
yesterday = (datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))) - datetime.timedelta(days=1)).strftime('%Y-%m-%d')
if today not in count:
count[today] = {}
if datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%H:%M') == '23:59':
count[yesterday] = count[today]
for post_group in post_groups:
with st.container():
columns = st.columns(NUM_COLUMNS)
for i, post in enumerate(post_group):
with columns[i]:
st.image(post['media_url'], width=BOX_WIDTH, use_column_width=True)
st.write(f"{datetime.datetime.strptime(post['timestamp'], '%Y-%m-%dT%H:%M:%S%z').astimezone(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d %H:%M:%S')}")
like_count_diff = post['like_count'] - count.get(yesterday, {}).get(post['id'], {}).get('like_count', post['like_count'])
comment_count_diff = post['comments_count'] - count.get(yesterday, {}).get(post['id'], {}).get('comments_count', post['comments_count'])
st.write(f"👍: {post['like_count']} ({'+' if like_count_diff >= 0 else ''}{like_count_diff})\n💬: {post['comments_count']} ({'+' if comment_count_diff >= 0 else ''}{comment_count_diff})\n")
caption = post['caption']
if caption is not None:
caption = caption.strip()
if "[Description]" in caption:
caption = caption.split("[Description]")[1].lstrip()
if "[Tags]" in caption:
caption = caption.split("[Tags]")[0].rstrip()
caption = caption.replace("#", "")
caption = caption.replace("[model]",👗)
caption = caption.replace("[Equip]", "📷")
caption = caption.replace("[Develop]", "🖨")
if show_description:
st.write(caption or "No caption provided")
else:
st.write(caption[:0] if caption is not None and len(caption) > 50 else caption or "No caption provided")
count[today][post['id']] = {'like_count': post['like_count'], 'comments_count': post['comments_count']}
saveCount(count, count_filename)
'''
上記のコードを以下の要件をすべて満たして改修してください
- 説明は表記せずPython用のコードのみ出力する
- "caption = post['caption']以降のブロックのコードは残存させ利用する
- 現状の"いいね数"と"コメント数"の取得と保存に関するコードは残存させ利用する
- 毎日JST23:59に現時点でのフォロワー数を取得し、すでに別件で使用している"count.json"内に保存するようコードを改修する
- StreamlitのUIで"キャプションを表示"の上に"現時点でのフォロワー数(Follower)"、すぐ右に'count.json'と現時点のフォロワー数との差分を"(-1)や(±0)や(+2)"のように並ぶようにし、一段階大きめのサイズで表示する
|
fbf09f365b592e66fe48909cdb7cab21
|
{
"intermediate": 0.38020947575569153,
"beginner": 0.39222896099090576,
"expert": 0.2275616079568863
}
|
3,293
|
c++ write to file
|
32fcf0bb6bd3ed15f8c3baa5c4a16b1a
|
{
"intermediate": 0.2870160937309265,
"beginner": 0.3613182306289673,
"expert": 0.351665735244751
}
|
3,294
|
write a python script that takes an image and reduces its detentions until it is lower than 100kb
|
00c88cef376c232547b632b30add586c
|
{
"intermediate": 0.29791614413261414,
"beginner": 0.130131334066391,
"expert": 0.5719525218009949
}
|
3,295
|
'''
import requests
import json
import datetime
import streamlit as st
from itertools import zip_longest
import os
def basic_info():
config = dict()
config["access_token"] = st.secrets["access_token"]
config['instagram_account_id'] = st.secrets.get("instagram_account_id", "")
config["version"] = 'v16.0'
config["graph_domain"] = 'https://graph.facebook.com/'
config["endpoint_base"] = config["graph_domain"] + config["version"] + '/'
return config
def InstaApiCall(url, params, request_type):
if request_type == 'POST':
req = requests.post(url, params)
else:
req = requests.get(url, params)
res = dict()
res["url"] = url
res["endpoint_params"] = params
res["endpoint_params_pretty"] = json.dumps(params, indent=4)
res["json_data"] = json.loads(req.content)
res["json_data_pretty"] = json.dumps(res["json_data"], indent=4)
return res
def getUserMedia(params, pagingUrl=''):
Params = dict()
Params['fields'] = 'id,caption,media_type,media_url,permalink,thumbnail_url,timestamp,username,like_count,comments_count'
Params['access_token'] = params['access_token']
if not params['endpoint_base']:
return None
if pagingUrl == '':
url = params['endpoint_base'] + params['instagram_account_id'] + '/media'
else:
url = pagingUrl
return InstaApiCall(url, Params, 'GET')
def getUser(params):
Params = dict()
Params['fields'] = 'followers_count'
Params['access_token'] = params['access_token']
if not params['endpoint_base']:
return None
url = params['endpoint_base'] + params['instagram_account_id']
return InstaApiCall(url, Params, 'GET')
def saveCount(count, filename):
with open(filename, 'w') as f:
json.dump(count, f, indent=4)
def getCount(filename):
try:
with open(filename, 'r') as f:
return json.load(f)
except (FileNotFoundError, json.decoder.JSONDecodeError):
return {}
st.set_page_config(layout="wide")
params = basic_info()
if not params['instagram_account_id']:
st.write('.envファイルでinstagram_account_idを確認')
else:
response = getUserMedia(params)
user_response = getUser(params)
if not response or not user_response:
st.write('.envファイルでaccess_tokenを確認')
else:
posts = response['json_data']['data'][::-1]
user_data = user_response['json_data']
followers_count = user_data.get('followers_count', 0)
NUM_COLUMNS = 6
MAX_WIDTH = 1000
BOX_WIDTH = int(MAX_WIDTH / NUM_COLUMNS)
BOX_HEIGHT = 400
show_description = st.checkbox("キャプションを表示")
# Add follower count and difference above the show_description checkbox
yesterday = (datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))) - datetime.timedelta(days=1)).strftime('%Y-%m-%d')
follower_diff = followers_count - getCount(count_filename).get(yesterday, {}).get('followers_count', followers_count)
st.markdown(f"<h4 style='font-size:1.2em;'>Follower: {followers_count} ({'+' if follower_diff >= 0 else ''}{follower_diff})</h4>", unsafe_allow_html=True)
posts.reverse()
post_groups = [list(filter(None, group)) for group in zip_longest(*[iter(posts)] * NUM_COLUMNS)]
count_filename = "count.json"
count = getCount(count_filename)
today = datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d')
if today not in count:
count[today] = {}
count[today]['followers_count'] = followers_count
if datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%H:%M') == '23:59':
count[yesterday] = count[today]
max_like_diff = max((post['like_count'] - count.get(yesterday, {}).get(post['id'], {}).get('like_count', post['like_count']) for post in posts), default=0)
max_comment_diff = max((post['comments_count'] - count.get(yesterday, {}).get(post['id'], {}).get('comments_count', post['comments_count']) for post in posts), default=0)
for post_group in post_groups:
with st.container():
columns = st.columns(NUM_COLUMNS)
for i, post in enumerate(post_group):
with columns[i]:
st.image(post['media_url'], width=BOX_WIDTH, use_column_width=True)
st.write(f"{datetime.datetime.strptime(post['timestamp'], '%Y-%m-%dT%H:%M:%S%z').astimezone(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d %H:%M:%S')}")
like_count_diff = post['like_count'] - count.get(yesterday, {}).get(post['id'], {}).get('like_count', post['like_count'])
comment_count_diff = post['comments_count'] - count.get(yesterday, {}).get(post['id'], {}).get('comments_count', post['comments_count'])
st.markdown(f"👍: {post['like_count']} <span style='{'' if like_count_diff != max_like_diff else 'color:red;'}'>({'+' if like_count_diff >= 0 else ''}{like_count_diff})</span>"
f"\n💬: {post['comments_count']} <span style='{'' if comment_count_diff != max_comment_diff else 'color:red;'}'>({'+' if comment_count_diff >= 0 else ''}{comment_count_diff})</span>",
unsafe_allow_html=True)
caption = post['caption']
if caption is not None:
caption = caption.strip()
if "[Description]" in caption:
caption = caption.split("[Description]")[1].lstrip()
if "[Tags]" in caption:
caption = caption.split("[Tags]")[0].rstrip()
caption = caption.replace("#", "")
caption = caption.replace("[model]", "👗")
caption = caption.replace("[Equip]", "📷")
caption = caption.replace("[Develop]", "🖨")
if show_description:
st.write(caption or "No caption provided")
else:
st.write(caption[:0] if caption is not None and len(caption) > 50 else caption or "No caption provided")
count[today][post['id']] = {'like_count': post['like_count'], 'comments_count': post['comments_count']}
saveCount(count, count_filename)
'''
上記コードを実行すると下記のエラーが発生します。下記のすべての要件に従って修正してください。
- Python用のインデントを行頭に付与して出力する
- コード冒頭の修正内容についての説明文は表示しない
- 指示のないコードの改変はせず優先的に活用する
- コードに未使用の不要な部分があれば削除し、コード全体を最適化する
- 修正済みのコード全体を省略せずに表示する
'''
Traceback (most recent call last):
File "/home/walhalax/.var/app/org.jupyter.JupyterLab/config/jupyterlab-desktop/jlab_server/lib/python3.8/site-packages/streamlit/runtime/scriptrunner/script_runner.py", line 565, in _run_script
exec(code, module.__dict__)
File "/home/walhalax/PycharmProjects/pythonProject/その他/Instargram/inst_tileview/inst_tileview.py", line 92, in <module>
follower_diff = followers_count - getCount(count_filename).get(yesterday, {}).get('followers_count', followers_count)
NameError: name 'count_filename' is not defined
|
13841c8ddfae4d8c51b644b8f2ffb8ef
|
{
"intermediate": 0.42739325761795044,
"beginner": 0.38451606035232544,
"expert": 0.18809065222740173
}
|
3,296
|
generate me a create a chrome extension tool that allows me to right click on any image and be able to find similar or exact products relating to the picture while searching for the image on supplier sites like aliexpress, cjdropshipping, and alibaba. must be in the python language.
|
8f410464f75f9802f3f02fdb1fbe36bd
|
{
"intermediate": 0.3445452153682709,
"beginner": 0.2560403645038605,
"expert": 0.3994143307209015
}
|
3,297
|
Wakeword detection C++
|
62d8a6b425c655a34605395425205c1d
|
{
"intermediate": 0.21526630222797394,
"beginner": 0.39350733160972595,
"expert": 0.3912263810634613
}
|
3,298
|
WakeWord Detection ai на c++
|
46dd80dca6dd948e98e9cf2cf61502ef
|
{
"intermediate": 0.24824653565883636,
"beginner": 0.3362473249435425,
"expert": 0.4155060946941376
}
|
3,299
|
WakeWord Detection c++
|
531e8a41aed90b76ec8d3bd606eac107
|
{
"intermediate": 0.32440492510795593,
"beginner": 0.28450748324394226,
"expert": 0.3910875916481018
}
|
3,300
|
generate me a create a chrome extension tool that allows me to right click on any image and be able to find similar or exact products relating to the picture while searching for the image on supplier sites like aliexpress, cjdropshipping, and alibaba. must be in the python language. Also give clear step by step instructions like you are telling someone with no prior coding experience.
|
0d3d4762e3f0a9194a32b2fd28ab8205
|
{
"intermediate": 0.3532445728778839,
"beginner": 0.35521212220191956,
"expert": 0.2915433943271637
}
|
3,301
|
error: a function declaration without a prototype is deprecated in all versions of C
|
3b328728aaced271e49995992c3e5472
|
{
"intermediate": 0.256076842546463,
"beginner": 0.5214654207229614,
"expert": 0.2224576771259308
}
|
3,302
|
Why does my site reload when I call createWill() ?
import '@rainbow-me/rainbowkit/styles.css';
import {
RainbowKitProvider,
getDefaultWallets,
} from '@rainbow-me/rainbowkit';
import { WagmiConfig, configureChains, createClient } from 'wagmi';
import { useEffect, useState } from "react"
import { ConnectButton } from '@rainbow-me/rainbowkit';
import abi from './abi';
import { alchemyProvider } from 'wagmi/providers/alchemy';
import { baseGoerli } from 'wagmi/chains';
import { publicProvider } from 'wagmi/providers/public';
const { ethers } = require("ethers");
const { chains, provider } = configureChains(
[baseGoerli],
[
alchemyProvider({ apiKey: process.env.ALCHEMY_ID }),
publicProvider()
]
);
const { connectors } = getDefaultWallets({
appName: 'Hello Kitty App',
projectId: 'YOUR_PROJECT_ID',
chains
});
const wagmiClient = createClient({
autoConnect: true,
connectors,
provider
})
export const Dapp = () => {
const [manageClicked, setManageClicked] = useState(false);
const [claimClicked, setClaimClicked] = useState(false);
const Manage = () => {
const [beneficiaryName, setBeneficiaryName] = useState('');
const [beneficiaryAddress, setBeneficiaryAddress] = useState('');
const [beneficiaryAmount, setBeneficiaryAmount] = useState('');
const handleBeneficiaryNameChange = (event) => {
setBeneficiaryName(event.target.value);
};
const handleBeneficiaryAddressChange = (event) => {
setBeneficiaryAddress(event.target.value);
};
const handleBeneficiaryAmountChange = (event) => {
setBeneficiaryAmount(event.target.value);
};
const createWill = async () => {
// try {
const provider = new ethers.providers.Web3Provider(window.ethereum)
await provider.send("eth_requestAccounts", []);
const signer = provider.getSigner()
const legacyKeeperAddress = "0xeF35e201aaBEFe47Ff3e01c87ef6D35878588B0C"
const legacyKeeper = new ethers.Contract(legacyKeeperAddress, abi, provider);
const legacyKeeperWithSigner = legacyKeeper.connect(signer);
await legacyKeeperWithSigner.addBeneficiary(beneficiaryName, beneficiaryAddress, beneficiaryAmount,0);
// } catch (err) {
// console.log(err);
// }
// console.log('Created will');
}
return(
<div>
<h1 className="inheritance">Manage Inheritance</h1>
<form>
<label htmlFor="beneficiaryName">Beneficiary Name</label>
<input
type="text"
id="beneficiaryName"
name="beneficiaryName"
value={beneficiaryName}
onChange={handleBeneficiaryNameChange}
/>
<label htmlFor="beneficiaryAddress">Beneficiary Address</label>
<input
type="text"
id="beneficiaryAddress"
name="beneficiaryAddress"
value={beneficiaryAddress}
onChange={handleBeneficiaryAddressChange}
/>
<label htmlFor="beneficiaryAmount">Beneficiary Amount</label>
<input
type="text"
id="beneficiaryAmount"
name="beneficiaryAmount"
value={beneficiaryAmount}
onChange={handleBeneficiaryAmountChange}
/>
<button className="buttons" onClick={()=> createWill()}> Submit </button>
</form>
<button className="buttons" onClick={()=> setManageClicked(false)}> Back </button>
</div>
)
}
const Claim = () => {
const [inheritorAddress, setInheritorAddress] = useState('');
const handleInheritorChange = (event) => {
setInheritorAddress(event.target.value);
};
return(
<div>
<h1>Claim Inheritance</h1>
<form>
<label htmlFor="inheritorAddress">Inheritor Address</label>
<input
type="text"
id="inheritorAddress"
name="inheritorAddress"
value={inheritorAddress}
onChange={handleInheritorChange}
/>
<button className="buttons" onClick={()=> setInheritorAddress(false)}> Claim </button>
</form>
<button className="buttons" onClick={()=> setClaimClicked(false)}> Back </button>
</div>
)
}
return(
<WagmiConfig client={wagmiClient}>
<RainbowKitProvider chains={chains}>
<>
<div className= "header">
<a href="/">
<img className="logo" src="https://pixelartmaker-data-78746291193.nyc3.digitaloceanspaces.com/image/cdfe8bf57fec8a8.png"></img>
</a>
<div className= "title">Legacy Keeper</div>
<div className="connectWallet">
<ConnectButton>Connect</ConnectButton>
</div>
</div>
{ !manageClicked && !claimClicked && <>
<h1 className="testing"> TESTING TESTING</h1>
<button className="buttons" onClick={()=> setManageClicked(true)}> Manage Inheritance </button>
<button className="buttons" onClick={()=> setClaimClicked(true)}> Claim Inheritance </button>
</>
}
{ manageClicked && <Manage />}
{ claimClicked && <Claim />}
</>
</RainbowKitProvider>
</WagmiConfig> )
}
|
5ef19185ffb43e9112102c99e77986df
|
{
"intermediate": 0.3708110749721527,
"beginner": 0.4073384702205658,
"expert": 0.2218504697084427
}
|
3,303
|
import requests
import json
import datetime
import streamlit as st
from itertools import zip_longest
import os
def basic_info():
config = dict()
config["access_token"] = st.secrets["access_token"]
config['instagram_account_id'] = st.secrets.get("instagram_account_id", "")
config["version"] = 'v16.0'
config["graph_domain"] = 'https://graph.facebook.com/'
config["endpoint_base"] = config["graph_domain"] + config["version"] + '/'
return config
def InstaApiCall(url, params, request_type):
if request_type == 'POST':
req = requests.post(url, params)
else:
req = requests.get(url, params)
res = dict()
res["url"] = url
res["endpoint_params"] = params
res["endpoint_params_pretty"] = json.dumps(params, indent=4)
res["json_data"] = json.loads(req.content)
res["json_data_pretty"] = json.dumps(res["json_data"], indent=4)
return res
def getUserMedia(params, pagingUrl=''):
Params = dict()
Params['fields'] = 'id,caption,media_type,media_url,permalink,thumbnail_url,timestamp,username,like_count,comments_count'
Params['access_token'] = params['access_token']
if not params['endpoint_base']:
return None
if pagingUrl == '':
url = params['endpoint_base'] + params['instagram_account_id'] + '/media'
else:
url = pagingUrl
return InstaApiCall(url, Params, 'GET')
def getUser(params):
Params = dict()
Params['fields'] = 'followers_count'
Params['access_token'] = params['access_token']
if not params['endpoint_base']:
return None
url = params['endpoint_base'] + params['instagram_account_id']
return InstaApiCall(url, Params, 'GET')
def saveCount(count, filename):
with open(filename, 'w') as f:
json.dump(count, f, indent=4)
def getCount(filename):
try:
with open(filename, 'r') as f:
return json.load(f)
except (FileNotFoundError, json.decoder.JSONDecodeError):
return {}
st.set_page_config(layout="wide")
params = basic_info()
count_filename = "count.json"
if not params['instagram_account_id']:
st.write('.envファイルでinstagram_account_idを確認')
else:
response = getUserMedia(params)
user_response = getUser(params)
if not response or not user_response:
st.write('.envファイルでaccess_tokenを確認')
else:
posts = response['json_data']['data'][::-1]
user_data = user_response['json_data']
followers_count = user_data.get('followers_count', 0)
NUM_COLUMNS = 6
MAX_WIDTH = 1000
BOX_WIDTH = int(MAX_WIDTH / NUM_COLUMNS)
BOX_HEIGHT = 400
yesterday = (datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))) - datetime.timedelta(days=1)).strftime('%Y-%m-%d')
follower_diff = followers_count - getCount(count_filename).get(yesterday, {}).get('followers_count', followers_count)
st.markdown(f"<h4 style='font-size:1.2em;'>Follower: {followers_count} ({'+' if follower_diff >= 0 else ''}{follower_diff})</h4>", unsafe_allow_html=True)
show_description = st.checkbox("キャプションを表示")
posts.reverse()
post_groups = [list(filter(None, group)) for group in zip_longest(*[iter(posts)] * NUM_COLUMNS)]
count = getCount(count_filename)
today = datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d')
if today not in count:
count[today] = {}
count[today]['followers_count'] = followers_count
if datetime.datetime.now(datetime.timezone(datetime.timedelta(hours=9))).strftime('%H:%M') == '23:59':
count[yesterday] = count[today]
max_like_diff = max((post['like_count'] - count.get(yesterday, {}).get(post['id'], {}).get('like_count', post['like_count']) for post in posts), default=0)
max_comment_diff = max((post['comments_count'] - count.get(yesterday, {}).get(post['id'], {}).get('comments_count', post['comments_count']) for post in posts), default=0)
for post_group in post_groups:
with st.container():
columns = st.columns(NUM_COLUMNS)
for i, post in enumerate(post_group):
with columns[i]:
st.image(post['media_url'], width=BOX_WIDTH, use_column_width=True)
st.write(f"{datetime.datetime.strptime(post['timestamp'], '%Y-%m-%dT%H:%M:%S%z').astimezone(datetime.timezone(datetime.timedelta(hours=9))).strftime('%Y-%m-%d %H:%M:%S')}")
like_count_diff = post['like_count'] - count.get(yesterday, {}).get(post['id'], {}).get('like_count', post['like_count'])
comment_count_diff = post['comments_count'] - count.get(yesterday, {}).get(post['id'], {}).get('comments_count', post['comments_count'])
st.markdown(f"👍: {post['like_count']} <span style='{'' if like_count_diff != max_like_diff else 'color:red;'}'>({'+' if like_count_diff >= 0 else ''}{like_count_diff})</span>"
f"\n💬: {post['comments_count']} <span style='{'' if comment_count_diff != max_comment_diff else 'color:red;'}'>({'+' if comment_count_diff >= 0 else ''}{comment_count_diff})</span>",
unsafe_allow_html=True)
caption = post['caption']
if caption is not None:
caption = caption.strip()
if "[Description]" in caption:
caption = caption.split("[Description]")[1].lstrip()
if "[Tags]" in caption:
caption = caption.split("[Tags]")[0].rstrip()
caption = caption.replace("#", "")
caption = caption.replace("[model]", "👗")
caption = caption.replace("[Equip]", "📷")
caption = caption.replace("[Develop]", "🖨")
if show_description:
st.write(caption or "No caption provided")
else:
st.write(caption[:0] if caption is not None and len(caption) > 50 else caption or "No caption provided")
count[today][post['id']] = {'like_count': post['like_count'], 'comments_count': post['comments_count']}
saveCount(count, count_filename)
'''
上記のコードを以下の要件をすべて満たして改修してください
- 説明は表記せずPython用のコードのみ出力する
- "いいね数"や"コメント数"の差分表示の"()"内の数字は、増加がなかったものは"赤"で表示しないよう改修する
- "caption = post['caption']"以降のブロックについては改変しない
|
8be25b96aaa87e7f2638f4cf5a62d57a
|
{
"intermediate": 0.36978060007095337,
"beginner": 0.47684019804000854,
"expert": 0.15337920188903809
}
|
3,304
|
Найди ошибки в коде:
#include <ESP8266WiFi.h>
#include <ESP8266WebServer.h>
// Задаем номера выводов
const int flowSensorPin = D1;
const int pumpPin = D2;
const int valvePin = D3;
const int buttonStartStopPin = D4;
const int buttonPauseResumePin = D5;
// Время перекачки в минутах и объем воды в литрах
float timeToPump = 1.0;
float volumeToPump = 3.0;
unsigned long currentTime;
unsigned long prevTime = 0;
unsigned long pumpInterval;
unsigned long prevPumpInterval;
volatile unsigned int flowCount;
float flowRate;
float currentVolume;
unsigned long startTime;
boolean pumpRunning = false;
boolean pumpPaused = false;
// Настройки для Wi-Fi
const char* ssid = "SSID";
const char* password = "PASSWORD";
// Настройки для веб сервера
ESP8266WebServer server(80);
void setup() {
pinMode(flowSensorPin, INPUT);
pinMode(pumpPin, OUTPUT);
pinMode(valvePin, OUTPUT);
pinMode(buttonStartStopPin, INPUT_PULLUP);
pinMode(buttonPauseResumePin, INPUT_PULLUP);
// Запускаем обработчик прерываний
attachInterrupt(digitalPinToInterrupt(flowSensorPin), flowPulseCounter, RISING);
Serial.begin(115200);
delay(10);
// Соединение с Wi-Fi
Serial.println();
Serial.println();
Serial.print("Connecting to ");
Serial.println(ssid);
WiFi.begin(ssid, password);
while (WiFi.status() != WL_CONNECTED) {
delay(500);
Serial.print(".");
}
Serial.println("");
Serial.println("WiFi connected");
Serial.println("IP address: ");
Serial.println(WiFi.localIP());
server.on("/", handleRoot);
server.begin();
Serial.println("HTTP server started");
// Вычисление временного интервала запуска помпы
pumpInterval = (timeToPump*60 * 1000) / volumeToPump;
currentTime = millis();
prevPumpInterval = currentTime;
}
void loop() {
// Обработка веб запросов
server.handleClient();
currentTime = millis();
if((currentTime-prevPumpInterval) >= pumpInterval && pumpRunning && !pumpPaused) {
prevPumpInterval = currentTime;
if(currentVolume < volumeToPump) {
pumpWater();
}
else {
stopPump();
}
}
// Проверка состояния кнопки старта/стопа
if(digitalRead(buttonStartStopPin) == LOW) {
delay(50);
if(digitalRead(buttonStartStopPin) == LOW) {
if(!pumpRunning) {
startPump();
}
else {
stopPump();
}
}
}
// Проверка состояния кнопки паузы/возобновления
if(digitalRead(buttonPauseResumePin) == LOW) {
delay(50);
if(digitalRead(buttonPauseResumePin) == LOW) {
if(!pumpPaused) {
pausePump();
}
else {
resumePump();
}
}
}
}
// Отправка главной страницы через веб сервер
void handleRoot() {
String message = "<html><body>"
"<h1>Система управления перекачкой воды</h1>";
if (pumpRunning){
message += "<h3>Состояние: РАБОТАЕТ</h3>";
}
else {
message += "<h3>Состояние: ОСТАНОВЛЕНО</h3>";
}
message += "</body></html>";
server.send(200, "text/html", message);
}
// Функция для обработки прерывания датчика потока
void ICACHE_RAM_ATTR flowPulseCounter() {
flowCount++;
}
// Начало перекачки воды
void startPump() {
digitalWrite(valvePin, HIGH);
delay(500);
digitalWrite(pumpPin, HIGH);
startTime = millis();
pumpRunning = true;
}
// Прекращение перекачки воды
void stopPump() {
digitalWrite(valvePin, LOW);
delay(500);
digitalWrite(pumpPin, LOW);
pumpRunning = false;
currentVolume = 0;
flowCount = 0;
}
// Перекачка определенного объема воды
void pumpWater() {
flowRate = (flowCount / 450.0) * 60;
currentVolume = flowRate / 60.0;
flowCount = 0;
if(currentVolume < volumeToPump) {
digitalWrite(valvePin, HIGH);
delay(500);
digitalWrite(pumpPin, HIGH);
startTime = millis();
pumpRunning = true;
}
else {
stopPump();
}
}
// Приостановить перекачку воды
void pausePump() {
digitalWrite(pumpPin, LOW);
pumpPaused = true;
}
// Возобновить перекачку воды
void resumePump() {
digitalWrite(pumpPin, HIGH);
pumpPaused = false;
}
|
58073c3e4ab664a0b89640459c1ab28e
|
{
"intermediate": 0.28432610630989075,
"beginner": 0.4973107874393463,
"expert": 0.21836309134960175
}
|
3,305
|
как исправить ошибку No error handlers are registered, logging exception.
Traceback (most recent call last):
File "C:\Users\123\PycharmProjects\боттелега\venv\lib\site-packages\telegram\ext\dispatcher.py", line 555, in process_update
handler.handle_update(update, self, check, context)
File "C:\Users\123\PycharmProjects\боттелега\venv\lib\site-packages\telegram\ext\handler.py", line 198, in handle_update
return self.callback(update, context)
File "C:\Users\123\PycharmProjects\боттелега\main.py", line 71, in referral
add_invited_user(invitee_user_id, invited_user_name, referral_code, c)
File "C:\Users\123\PycharmProjects\боттелега\main.py", line 103, in add_invited_user
c.execute('UPDATE users '
sqlite3.OperationalError: near ")": syntax error в коде import os
import sqlite3
from uuid import uuid4
from telegram import Update
from telegram.ext import Updater, CommandHandler, CallbackContext, MessageHandler, Filters
# Используйте свой токен бота, переданного вам ботом @BotFather
TELEGRAM_API_TOKEN = '6143413294:AAG_0lYsev83l0FaB5rqPdpYQPsHZPLEewI'
def start(update: Update, context: CallbackContext):
user_id = update.effective_user.id
conn = sqlite3.connect('referral_bot.db')
c = conn.cursor()
# Найти или создать пользователя в базе данных
c.execute('INSERT OR IGNORE INTO users (id) VALUES (?)', (user_id,))
conn.commit()
# Получить реферальный код и количество приглашенных пользователей
c.execute('SELECT referral_code, invited_count FROM users WHERE id = ?', (user_id,))
row = c.fetchone()
referral_code, invited_count = row
# Если пользователь не имеет реферального кода, создать один
if not referral_code:
referral_code = str(uuid4())[:8]
c.execute('UPDATE users SET referral_code = ? WHERE id = ?', (referral_code, user_id))
conn.commit()
# Получить список имен приглашенных пользователей
c.execute('SELECT invited_users FROM users WHERE id = ?', (user_id,))
row = c.fetchone()
invited_names = row[0].split(',') if row[0] else []
conn.close()
update.message.reply_text(f'Ваш реферальный код: {referral_code}\n'
f'Количество приглашенных вами пользователей: {invited_count}\n'
f'Их имена: {", ".join(invited_names)}')
def referral(update: Update, context: CallbackContext):
if not context.args:
update.message.reply_text('Пожалуйста, используйте команду /referal с вашим реферальным кодом')
return
referral_code = context.args[0]
invited_user_name = update.effective_user.full_name
invitee_user_id = update.effective_user.id
conn = sqlite3.connect('referral_bot.db')
c = conn.cursor()
if not check_if_code_exists(referral_code, c):
update.message.reply_text('Такого реферального кода не существует')
return
if referral_code == get_referral_code(invitee_user_id, c):
update.message.reply_text('Вы не можете использовать свой собственный реферальный код')
return
if check_if_already_invited(invitee_user_id, c):
update.message.reply_text('Вы уже в системе рефералов')
return
# Добавить пользователя в реферальную систему
c.execute('UPDATE users SET invited_by = ? WHERE id = ?', (get_user_id_by_referral_code(referral_code, c), invitee_user_id))
conn.commit()
add_invited_user(invitee_user_id, invited_user_name, referral_code, c)
conn.close()
update.message.reply_text('Вы успешно присоединились к системе рефералов')
def check_if_code_exists(referral_code: str, c):
c.execute('SELECT * FROM users WHERE referral_code = ?', (referral_code,))
return bool(c.fetchone())
def check_if_already_invited(invitee_user_id: int, c):
c.execute('SELECT * FROM users WHERE id = ? AND invited_by IS NOT NULL', (invitee_user_id,))
return bool(c.fetchone())
def get_referral_code(user_id: int, c):
c.execute('SELECT referral_code FROM users WHERE id = ?', (user_id,))
row = c.fetchone()
if row:
return row[0]
return None
def get_user_id_by_referral_code(referral_code: str, c):
c.execute('SELECT id FROM users WHERE referral_code = ?', (referral_code,))
return c.fetchone()[0]
def add_invited_user(user_id: int, user_name: str, referral_code: str, c):
inviter_user_id = get_user_id_by_referral_code(referral_code, c)
c.execute('UPDATE users '
'SET invited_count = invited_count + 1 '
' invited_users = COALESCE(invited_users, '') || ? || ',' '
'WHERE id = ?'
(user_name, inviter_user_id))
def main():
# Создать таблицу пользователей
conn = sqlite3.connect('referral_bot.db')
c = conn.cursor()
c.execute('''CREATE TABLE IF NOT EXISTS users (
id INTEGER PRIMARY KEY,
referral_code TEXT UNIQUE,
invited_by INTEGER,
invited_count INTEGER DEFAULT 0,
invited_users TEXT DEFAULT ''
)''')
conn.commit()
conn.close()
updater = Updater(TELEGRAM_API_TOKEN)
dispatcher = updater.dispatcher
dispatcher.add_handler(CommandHandler('start', start))
dispatcher.add_handler(CommandHandler('referal', referral))
updater.start_polling()
updater.idle()
if 'main.py' == "main.py":
main()
|
f108573cf32030a683e26bf485b722a5
|
{
"intermediate": 0.28503385186195374,
"beginner": 0.5580319762229919,
"expert": 0.15693417191505432
}
|
3,306
|
Write a short powershell script. Only code, no description. Enlose the code in
|
b054bc90883bc86e69f62645e28b302b
|
{
"intermediate": 0.30551519989967346,
"beginner": 0.2279248982667923,
"expert": 0.4665599465370178
}
|
3,307
|
Write a short powershell script in markdown
|
4459a2e4bb2afcf97a1228c4a2aa6234
|
{
"intermediate": 0.31262168288230896,
"beginner": 0.3013456463813782,
"expert": 0.38603267073631287
}
|
3,308
|
just all the flags buttons at the very top and initial hidden state with no any actual text shown, and after pressing on each flag, it replaces the translation variant and so on. can you do this with only css and html, without any javascripts or libraries? need to show only one translation variant at once by hidding the rest.
“While it is not possible to completely achieve this without using JavaScript”. maybe you are just wrong, and it’s possible to trigger hide and show state at the same time, to hide all and display only particular, with only css and html code on page used. neagh. it shows all the translation variants at the same time, no matter what button or flag you will press. there should be some other tricky way to do this hide and show magic, using only css and html. if you could only think for a little longer on this question...: I apologize if my previous response confused you. I see now that it was a misunderstanding on my part. There is indeed a way to achieve this effect using only HTML and CSS. Please find below the updated code:
<!DOCTYPE html>
<html>
<head>
<meta charset=“UTF-8”>
<title>Multilingual Page Example</title>
<style>
.flags-container {
display: flex;
justify-content: center;
margin-bottom: 20px;
flex-wrap: wrap;
}
.flag-radio {
display: none;
}
.flag-label {
cursor: pointer;
margin: 0 10px;
transition: 0.3s;
opacity: 0.6;
font-size: 24px;
}
.flag-label:hover {
opacity: 1;
}
.flag-radio:checked ~ .language-option {
display: block;
padding: 20px;
background-color: white;
box-shadow: 0 3px 6px rgba(0, 0, 0, 0.16), 0 3px 6px rgba(0, 0, 0, 0.23);
font-size: 18px;
}
.language-option {
display: none;
}
</style>
</head>
<body>
<div class=“flags-container”>
<input id=“english-flag” type=“radio” name=“flags” class=“flag-radio”>
<label for=“english-flag” class=“flag-label”>🇬🇧</label>
<input id=“hindi-flag” type=“radio” name=“flags” class=“flag-radio”>
<label for=“hindi-flag” class=“flag-label”>🇮🇳</label>
<input id=“hebrew-flag” type=“radio” name=“flags” class=“flag-radio”>
<label for=“hebrew-flag” class=“flag-label”>🇮🇱</label>
<input id=“chinese-flag” type=“radio” name=“flags” class=“flag-radio”>
<label for=“chinese-flag” class=“flag-label”>🇨🇳</label>
<input id=“french-flag” type=“radio” name=“flags” class=“flag-radio”>
<label for=“french-flag” class=“flag-label”>🇫🇷</label>
<input id=“spanish-flag” type=“radio” name=“flags” class=“flag-radio”>
<label for=“spanish-flag” class=“flag-label”>🇪🇸</label>
<div id=“english” class=“language-option”>
<p>Hello! Welcome to my website.</p>
<p>This is some English text. Would you like to read it in another language?</p>
</div>
<div id=“hindi” class=“language-option”>
<p>नमस्ते! मेरी वेबसाइट पर आपका स्वागत है।</p>
<p>यह कुछ हिंदी मूल लेख है। क्या आप इसे किसी अन्य भाषा में पढ़ना चाहेंगे?</p>
</div>
<div id=“hebrew” class=“language-option”>
<p>שלום! ברוכים הבאים לאתר שלי.</p>
<p>זוהי טקסט בעברית. האם תרצו לקרוא את זה בשפה אחרת?</p>
</div>
<div id=“chinese” class=“language-option”>
<p>你好！欢迎来到我的网站。</p>
<p>这是一些中文原文。您想用其他语言阅读它吗？</p>
</div>
<div id=“french” class=“language-option”>
<p>Bonjour! Bienvenue sur mon site web.</p>
<p>Ceci est un texte en français. Voulez-vous le lire dans une autre langue?</p>
</div>
<div id=“spanish” class=“language-option”>
<p>¡Hola! Bienvenidos a mi sitio web.</p>
<p>Este es un texto en español. ¿Te gustaría leerlo en otro idioma?</p>
</div>
<style>
#english-flag:checked ~ #english,
#hindi-flag:checked ~ #hindi,
#hebrew-flag:checked ~ #hebrew,
#chinese-flag:checked ~ #chinese,
#french-flag:checked ~ #french,
#spanish-flag:checked ~ #spanish {
display: block;
}
</style>
</div>
</body>
</html>
This new version will only display one language at a time while keeping the other languages hidden, using only HTML and CSS. Please let me know if this solution meets your requirements, or if there are any further changes you’d like me to make.
|
d131fb38f1d530ac61d2337d64149915
|
{
"intermediate": 0.2603636682033539,
"beginner": 0.42747506499290466,
"expert": 0.31216132640838623
}
|
3,309
|
I have fixed it on my own, but it cannot swith between the languages: <!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8">
<title>Multilingual Page Example</title>
<style>
.flags-container {
position: fixed;
top: 0;
left: 0;
right: 0;
padding: 3px 0;
background-color: white;
display: flex;
justify-content: center;
align-items: center;
box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
z-index: 10;
}
.flag-radio {
display: none;
}
.flag-label {
cursor: pointer;
margin: 0 10px;
transition: 0.3s;
opacity: 0.6;
font-size: 24px;
}
.flag-label:hover {
opacity: 1;
}
.language-option {
position: absolute;
top: 0;
left: 0;
right: 0;
bottom: 0;
display: none;
justify-content: center;
align-items: center;
padding-top: 50px; /* adjust based on flags container height */
}
#english-flag:checked ~ #english,
#hindi-flag:checked ~ #hindi,
#hebrew-flag:checked ~ #hebrew,
#chinese-flag:checked ~ #chinese,
#french-flag:checked ~ #french,
#spanish-flag:checked ~ #spanish {
display: block;
}
</style>
</head>
<body>
<div class="flags-container">
<input id="english-flag" type="radio" name="flags" class="flag-radio">
<label for="english-flag" class="flag-label">🇬🇧</label>
<input id="hindi-flag" type="radio" name="flags" class="flag-radio">
<label for="hindi-flag" class="flag-label">🇮🇳</label>
<input id="hebrew-flag" type="radio" name="flags" class="flag-radio">
<label for="hebrew-flag" class="flag-label">🇮🇱</label>
<input id="chinese-flag" type="radio" name="flags" class="flag-radio">
<label for="chinese-flag" class="flag-label">🇨🇳</label>
<input id="french-flag" type="radio" name="flags" class="flag-radio">
<label for="french-flag" class="flag-label">🇫🇷</label>
<input id="spanish-flag" type="radio" name="flags" class="flag-radio">
<label for="spanish-flag" class="flag-label">🇪🇸</label>
<div id="english" class="language-option">
<p>Hello! Welcome to my website.</p>
<p>This is some English text. Would you like to read it in another language?</p>
</div>
<div id="hindi" class="language-option">
<p>नमस्ते! मेरी वेबसाइट पर आपका स्वागत है।</p>
<p>यह कुछ हिंदी मूल लेख है। क्या आप इसे किसी अन्य भाषा में पढ़ना चाहेंगे?</p>
</div>
<div id="hebrew" class="language-option">
<p>שלום! ברוכים הבאים לאתר שלי.</p>
<p>זוהי טקסט בעברית. האם תרצו לקרוא את זה בשפה אחרת?</p>
</div>
<div id="chinese" class="language-option">
<p>你好！欢迎来到我的网站。</p>
<p>这是一些中文原文。您想用其他语言阅读它吗？</p>
</div>
<div id="french" class="language-option">
<p>Bonjour! Bienvenue sur mon site web.</p>
<p>Ceci est un texte en français. Voulez-vous le lire dans une autre langue?</p>
</div>
<div id="spanish" class="language-option">
<p>¡Hola! Bienvenidos a mi sitio web.</p>
<p>Este es un texto en español. ¿Te gustaría leerlo en otro idioma?</p>
</div>
</div>
</body>
</html>
|
e03a6ebb2cc06a2cb9a0749ca05c8d3a
|
{
"intermediate": 0.27938637137413025,
"beginner": 0.47982603311538696,
"expert": 0.240787535905838
}
|
3,310
|
give me a q learning based drone swarming code
|
312e1ee33f08c92d432e251eb5b01be1
|
{
"intermediate": 0.14683520793914795,
"beginner": 0.1384066641330719,
"expert": 0.7147580981254578
}
|
3,311
|
create minion card class for Hearthstone Javascript (2 attack and 2 health)
|
95bcf7917f5769b311d9dccac0f5f1d6
|
{
"intermediate": 0.24997594952583313,
"beginner": 0.5198662877082825,
"expert": 0.23015770316123962
}
|
3,312
|
i would like to create a discord app that can conect to my server via ftp and be able to change / add files to my server how do i go about setting something up
|
fc457349783c265b107602e6fc55e323
|
{
"intermediate": 0.5465222597122192,
"beginner": 0.2187725156545639,
"expert": 0.23470523953437805
}
|
3,313
|
Write mechanic code for Hearthstone in Javascript
|
6e48e78b61cb75cddd3b2a6001a0c89c
|
{
"intermediate": 0.28379639983177185,
"beginner": 0.43964093923568726,
"expert": 0.2765626311302185
}
|
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