row_id
int64 0
48.4k
| init_message
stringlengths 1
342k
| conversation_hash
stringlengths 32
32
| scores
dict |
|---|---|---|---|
33,228
|
How do I make my own outputstream that catches all errors from System.err
|
e38d3dc599e0e54846ffa495215a6f2d
|
{
"intermediate": 0.48599645495414734,
"beginner": 0.11313695460557938,
"expert": 0.4008665978908539
}
|
33,229
|
Convert this to kotlin : Intent emailIntent = new Intent(Intent.ACTION_SENDTO);
emailIntent.setData(Uri.parse(mailto));
|
809ab529df386ac360ce1b74f2b9ae1c
|
{
"intermediate": 0.45229020714759827,
"beginner": 0.23858891427516937,
"expert": 0.30912086367607117
}
|
33,230
|
i have 5 to 10 black object on white wallpaper. cut out every one of them and save as a different image using python
|
c986d72327d6d9c95a3d885fac3b7c6b
|
{
"intermediate": 0.3266310393810272,
"beginner": 0.2684968113899231,
"expert": 0.40487220883369446
}
|
33,231
|
How can I make my own PrintStream that will be the System.setErr() argument
|
1ab454a8df2089045dc30043390553dc
|
{
"intermediate": 0.5186548829078674,
"beginner": 0.23535561561584473,
"expert": 0.24598947167396545
}
|
33,232
|
here's my code
image_path = r"C:\Users\Plathera\Desktop\4242\New folder (3)\AQOHFVLO.png"
folder_to_save = r"C:\Users\Plathera\Desktop\4242\New folder//"
import cv2
import numpy as np
def extract_objects(image):
# Convert image to grayscale
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# Threshold the grayscale image to get the black objects
_, thresh = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY_INV)
# Find contours of the black objects
contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
# Extract and save each black object larger than 100 pixels as a separate image
object_images = []
for i, contour in enumerate(contours):
x, y, w, h = cv2.boundingRect(contour)
if w * h > 1: # Check if object is larger than 100 pixels
object_image = image[y:y+h, x:x+w]
cv2.imwrite(folder_to_save + f"object{i+1}.png", object_image)
object_images.append(object_image)
return object_images
# Load the white wallpaper image
image = cv2.imread(image_path)
# Extract the black objects larger than 100 pixels from the image
object_images = extract_objects(image)
make that if one object above another then combine them together
|
389a7883d1f1ad2d8aae517c259d567e
|
{
"intermediate": 0.4428195059299469,
"beginner": 0.2828061878681183,
"expert": 0.2743743360042572
}
|
33,233
|
How do I configure log4j?
|
7f37a75651b48caebe2cd992b7feed74
|
{
"intermediate": 0.5117016434669495,
"beginner": 0.15590594708919525,
"expert": 0.3323923647403717
}
|
33,234
|
i got 5 to 8 black object on white background. write a python script that extracts them and saves as different objects. but if object os location above another them this should be saved as 1 object
|
efdb34e0d461aec4e1138c77d518e614
|
{
"intermediate": 0.380975604057312,
"beginner": 0.28375473618507385,
"expert": 0.3352697193622589
}
|
33,235
|
How do I configure Log4j in such a way where all out and err will be routed to an output file, AND I can programmacly access errors and send them externally through my Discord bot?
|
eda29ee333ea8dc15b6f6ed980598261
|
{
"intermediate": 0.7438282370567322,
"beginner": 0.10669250041246414,
"expert": 0.14947931468486786
}
|
33,236
|
Why this code only prints out "192" in the terminal?
|
f0f7859de5d8dd849d1b4844921b4fb8
|
{
"intermediate": 0.32180464267730713,
"beginner": 0.44419607520103455,
"expert": 0.23399922251701355
}
|
33,237
|
Can you write me a C program using the following stack structure:
struct int_node {
int value;
struct int_node *next;
};
and create a simple calculator that can add two arbitrary size integers entered from the command line.
|
6231741bd0efdec703f185358324cc5c
|
{
"intermediate": 0.44481003284454346,
"beginner": 0.35683560371398926,
"expert": 0.19835436344146729
}
|
33,238
|
write an essay about penguins
|
8e62daff93a9c04459284b9b34fc6015
|
{
"intermediate": 0.3553641140460968,
"beginner": 0.3793390989303589,
"expert": 0.2652967572212219
}
|
33,239
|
I want to create an app that web scrapes the new "machine learning remote full time" roles on the website and send a report to my email every morning at 8am
|
3729af6812486023757e383eaf5f1bdd
|
{
"intermediate": 0.14756475389003754,
"beginner": 0.1110701784491539,
"expert": 0.7413650751113892
}
|
33,240
|
write me code for a web pac man game
|
d98f06cf4d04db4af5233d5180a1677a
|
{
"intermediate": 0.30446580052375793,
"beginner": 0.4662586748600006,
"expert": 0.22927545011043549
}
|
33,241
|
I need to programmatically catch all errors of a Java program and write to a logs file. Can I use logback to help with this?
|
04252e2e9b659ff13d7171ddef9ea9a5
|
{
"intermediate": 0.6619928479194641,
"beginner": 0.12398800998926163,
"expert": 0.21401923894882202
}
|
33,242
|
I need to programmatically catch all errors of a Java program and write to a logs file. Can I use logback to help with this? I need the ability to catch ALL errors in the program, basically everything that gets printed to the error stream
|
f5fc3c024efe4f343f4457b29847a8d1
|
{
"intermediate": 0.3623808026313782,
"beginner": 0.4570991098880768,
"expert": 0.18052011728286743
}
|
33,243
|
def permutation(binary, permutation_order):
permuted = [binary[i - 1] for i in permutation_order]
return ''.join(permuted)
def ascii_to_binary(string):
binary_string = ""
for char in string:
ascii_value = ord(char)
binary_value = bin(ascii_value)[2:].zfill(8) # تحويل إلى ثنائي وملء الصفرات الأمامية
binary_string += binary_value
return binary_string
def shift_left(bits, num_shifts):
shifted = bits[num_shifts:] + bits[:num_shifts]
return shifted
# جدول التبديل PC1
pc1_table = [57, 49, 41, 33, 25, 17, 9,
1, 58, 50, 42, 34, 26, 18,
10, 2, 59, 51, 43, 35, 27,
19, 11, 3, 60, 52, 44, 36,
63, 55, 47, 39, 31, 23, 15,
7, 62, 54, 46, 38, 30, 22,
14, 6, 61, 53, 45, 37, 29,
21, 13, 5, 28, 20, 12, 4]
# جدول التبديل PC2
pc2_table = [14, 17, 11, 24, 1, 5, 3, 28,
15, 6, 21, 10, 23, 19, 12, 4,
26, 8, 16, 7, 27, 20, 13, 2,
41, 52, 31, 37, 47, 55, 30, 40,
51, 45, 33, 48, 44, 49, 39, 56,
34, 53, 46, 42, 50, 36, 29, 32]
key_ascii = input("Enter the key: ") # استخلاص المفتاح من المستخدم
key_binary = ascii_to_binary(key_ascii) # تحويل المفتاح إلى تمثيل ثنائي
# تنفيذ جدول التبديل PC1
key_pc1 = permutation(key_binary, pc1_table)
# قسم المفتاح إلى نصفين
c = key_pc1[:28]
d = key_pc1[28:]
# قم بتطبيق الشيفتات المحددة
shifts = [1, 1, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 1]
for shift in shifts:
c = shift_left(c, shift)
d = shift_left(d, shift)
# جمع C و D
cd = c + d
# تنفيذ جدول التبديل PC2
key_pc2 = permutation(cd, pc2_table)
print("Key PC2:", key_pc2)عدل على هذا الكود بحيث يعمل ال Encryption صح ويتضمن جدوال ال intial permutation وال final permutation
|
fa2366b64198044ac20f06fbba8d0196
|
{
"intermediate": 0.34985828399658203,
"beginner": 0.38460713624954224,
"expert": 0.26553452014923096
}
|
33,244
|
string baseDirectory = AppDomain.CurrentDomain.BaseDirectory;
string scriptPath = Path.Combine(baseDirectory, @"Scripts\imports.py");
scriptPath = @"Scripts\imports.py";
var psi = new ProcessStartInfo
{
FileName = "python",
Arguments = scriptPath, // Убедитесь, что путь в кавычках, если есть пробелы
WorkingDirectory = baseDirectory,
UseShellExecute = false,
CreateNoWindow = true,
RedirectStandardOutput = true,
RedirectStandardError = true
};
try
{
using (var process = Process.Start(psi))
{
var errorOutput = process.StandardError.ReadToEnd();
process.WaitForExit();
var exitCode = process.ExitCode;
this.Invoke(new Action(() =>
{
if (!string.IsNullOrWhiteSpace(errorOutput))
{
MessageBox.Show(errorOutput);
}
else if (exitCode == 1)
{
MessageBox.Show("Установка библиотек завершена успешно.");
}
else
{
MessageBox.Show($"Error: {exitCode}");
}
}));
}
}
catch (Exception ex)
{
// Вывод сообщения об ошибке, если что-то пойдет не так
MessageBox.Show("Произошла ошибка при запуске скрипта: " + ex.Message);
}
Мне нужно чтобы в Message.Box выводились комментарии которые выводятся в окне python
|
d19308ebca107ccac28ea2f5d4d8dcb0
|
{
"intermediate": 0.33375924825668335,
"beginner": 0.4587947130203247,
"expert": 0.20744602382183075
}
|
33,245
|
Добавь к этому коду, чтобы в Message.Box выводились сообщения из python
private void button2_Click(object sender, EventArgs e)
{
string baseDirectory = AppDomain.CurrentDomain.BaseDirectory;
string scriptPath = @"Scripts\imports.py";
var psi = new ProcessStartInfo
{
FileName = "python",
Arguments = scriptPath, // Убедитесь, что путь в кавычках, если есть пробелы
WorkingDirectory = baseDirectory,
UseShellExecute = false,
CreateNoWindow = true,
RedirectStandardOutput = true,
RedirectStandardError = true
};
|
e8e6416d10414054c83eb8dd7f9cca57
|
{
"intermediate": 0.4109925329685211,
"beginner": 0.35393306612968445,
"expert": 0.23507437109947205
}
|
33,246
|
Напиши полный код нейросети для генерации картинок на C#
|
dc0e9ce71e221ccf3afc02a80c0a00bd
|
{
"intermediate": 0.3911442458629608,
"beginner": 0.35072386264801025,
"expert": 0.25813189148902893
}
|
33,247
|
corelation among variables
|
12e402a45c58fd75fcfd24733659b56c
|
{
"intermediate": 0.336316853761673,
"beginner": 0.508644700050354,
"expert": 0.15503846108913422
}
|
33,248
|
def pad_plaintext(plaintext):
while len(plaintext) < 8:
plaintext += "@"
return plaintext[:8]def text_to_binary(text):
binary_text = ""
for char in text:
binary_char = bin(ord(char))[2:].zfill(8)
binary_text += binary_char
return binary_text
def split_blocks(plaintext):
blocks = []
while len(plaintext) > 0:
blocks.append(plaintext[:8])
plaintext = plaintext[8:]
return blocks
def ascii_to_binary_key(key):
binary_key = ""
for char in key:
binary_key += format(ord(char), '08b')
return binary_key
def apply_key_permutation(binary_key, permutation_table):
permuted_key = ""
for index in permutation_table:
permuted_key += binary_key[index - 1]
return permuted_key
def generate_subkeys(key):
pc_1_table = [57, 49, 41, 33, 25, 17, 9,
1, 58, 50, 42, 34, 26, 18,
10, 2, 59, 51, 43, 35, 27,
19, 11, 3, 60, 52, 44, 36,
63, 55, 47, 39, 31, 23, 15,
7, 62, 54, 46, 38, 30, 22,
14, 6, 61, 53, 45, 37, 29,
21, 13, 5, 28, 20, 12, 4]
pc_2_table = [14, 17, 11, 24, 1, 5,
3, 28, 15, 6, 21, 10,
23, 19, 12, 4, 26, 8,
16, 7, 27, 20, 13, 2,
41, 52, 31, 37, 47, 55,
30, 40, 51, 45, 33, 48,
44, 49, 39, 56, 34, 53,
46, 42, 50, 36, 29, 32]
if len(key) != 8:
raise ValueError("Key size must be 8 characters.")
binary_key = ascii_to_binary_key(key)
permuted_key = apply_key_permutation(binary_key, pc_1_table)
# تحويل المفتاح إلى قيمة عددية
permuted_key = int(permuted_key, 2)
subkeys = []
# توليد المفاتيح الفرعية لكل جولة
for round in range(1, 17):
# الدورانات اليسرى للنصف الأيسر والنصف الأيمن للمفتاح
left_shifts = 1 if round in [1, 2, 9, 16] else 2
permuted_key = ((permuted_key << left_shifts) & 0xFFFFFFFFFFFF) | (permuted_key >> (28 - left_shifts))
# استخدام جدول PC-2 لتحويل المفتاح إلى مفتاح فرعي بطول 48 بتًا
subkey = apply_key_permutation(bin(permuted_key)[2:].zfill(56), pc_2_table)
subkeys.append(subkey)
return subkeys
def initial_permutation(block):
# Perform initial permutation on the block
initial_permutation_table = [58, 50, 42, 34, 26, 18, 10, 2,
60, 52, 44, 36, 28, 20, 12, 4,
62, 54, 46, 38, 30, 22, 14, 6,
64, 56, 48, 40, 32, 24, 16, 8,
57, 49, 41, 33, 25, 17, 9, 1,
59, 51, 43, 35, 27, 19, 11, 3,
|
132120c64d42ba21ea992f168125f48e
|
{
"intermediate": 0.32967230677604675,
"beginner": 0.470430463552475,
"expert": 0.1998971551656723
}
|
33,249
|
def pad_plaintext(plaintext):
while len(plaintext) < 8:
plaintext += "@"
return plaintext[:8]def text_to_binary(text):
binary_text = ""
for char in text:
binary_char = bin(ord(char))[2:].zfill(8)
binary_text += binary_char
return binary_text
def split_blocks(plaintext):
blocks = []
while len(plaintext) > 0:
blocks.append(plaintext[:8])
plaintext = plaintext[8:]
return blocks
def ascii_to_binary_key(key):
binary_key = ""
for char in key:
binary_key += format(ord(char), '08b')
return binary_key
def apply_key_permutation(binary_key, permutation_table):
permuted_key = ""
for index in permutation_table:
permuted_key += binary_key[index - 1]
return permuted_key
def generate_subkeys(key):
pc_1_table = [57, 49, 41, 33, 25, 17, 9,
1, 58, 50, 42, 34, 26, 18,
10, 2, 59, 51, 43, 35, 27,
19, 11, 3, 60, 52, 44, 36,
63, 55, 47, 39, 31, 23, 15,
7, 62, 54, 46, 38, 30, 22,
14, 6, 61, 53, 45, 37, 29,
21, 13, 5, 28, 20, 12, 4]
pc_2_table = [14, 17, 11, 24, 1, 5,
3, 28, 15, 6, 21, 10,
23, 19, 12, 4, 26, 8,
16, 7, 27, 20, 13, 2,
41, 52, 31, 37, 47, 55,
30, 40, 51, 45, 33, 48,
44, 49, 39, 56, 34, 53,
46, 42, 50, 36, 29, 32]
if len(key) != 8:
raise ValueError("Key size must be 8 characters.")
binary_key = ascii_to_binary_key(key)
permuted_key = apply_key_permutation(binary_key, pc_1_table)
# تحويل المفتاح إلى قيمة عددية
permuted_key = int(permuted_key, 2)
subkeys = []
# توليد المفاتيح الفرعية لكل جولة
for round in range(1, 17):
# الدورانات اليسرى للنصف الأيسر والنصف الأيمن للمفتاح
left_shifts = 1 if round in [1, 2, 9, 16] else 2
permuted_key = ((permuted_key << left_shifts) & 0xFFFFFFFFFFFF) | (permuted_key >> (28 - left_shifts))
# استخدام جدول PC-2 لتحويل المفتاح إلى مفتاح فرعي بطول 48 بتًا
subkey = apply_key_permutation(bin(permuted_key)[2:].zfill(56), pc_2_table)
subkeys.append(subkey)
return subkeys
def initial_permutation(block):
# Perform initial permutation on the block
initial_permutation_table = [58, 50, 42, 34, 26, 18, 10, 2,
60, 52, 44, 36, 28, 20, 12, 4,
62, 54, 46, 38, 30, 22, 14, 6,
64, 56, 48, 40, 32, 24, 16, 8,
57, 49, 41, 33, 25, 17, 9, 1,
59, 51, 43, 35, 27, 19, 11, 3,
|
2f2f16f8fd102509f698ff4bb3a27000
|
{
"intermediate": 0.32967230677604675,
"beginner": 0.470430463552475,
"expert": 0.1998971551656723
}
|
33,250
|
Напиши код для генерации картинок по тексту на C# используй TensorFlow
|
74d22613713a2f93f614dad660e847b8
|
{
"intermediate": 0.46752414107322693,
"beginner": 0.16923201084136963,
"expert": 0.36324381828308105
}
|
33,251
|
def pad_plaintext(plaintext):
while len(plaintext) < 8:
plaintext += "@"
return plaintext[:8]def text_to_binary(text):
binary_text = ""
for char in text:
binary_char = bin(ord(char))[2:].zfill(8)
binary_text += binary_char
return binary_text
def split_blocks(plaintext):
blocks = []
while len(plaintext) > 0:
blocks.append(plaintext[:8])
plaintext = plaintext[8:]
return blocks
def ascii_to_binary_key(key):
binary_key = ""
for char in key:
binary_key += format(ord(char), '08b')
return binary_key
def apply_key_permutation(binary_key, permutation_table):
permuted_key = ""
for index in permutation_table:
permuted_key += binary_key[index - 1]
return permuted_key
def generate_subkeys(key):
pc_1_table = [57, 49, 41, 33, 25, 17, 9,
1, 58, 50, 42, 34, 26, 18,
10, 2, 59, 51, 43, 35, 27,
19, 11, 3, 60, 52, 44, 36,
63, 55, 47, 39, 31, 23, 15,
7, 62, 54, 46, 38, 30, 22,
14, 6, 61, 53, 45, 37, 29,
21, 13, 5, 28, 20, 12, 4]
pc_2_table = [14, 17, 11, 24, 1, 5,
3, 28, 15, 6, 21, 10,
23, 19, 12, 4, 26, 8,
16, 7, 27, 20, 13, 2,
41, 52, 31, 37, 47, 55,
30, 40, 51, 45, 33, 48,
44, 49, 39, 56, 34, 53,
46, 42, 50, 36, 29, 32]
if len(key) != 8:
raise ValueError("Key size must be 8 characters.")
binary_key = ascii_to_binary_key(key)
permuted_key = apply_key_permutation(binary_key, pc_1_table)
# تحويل المفتاح إلى قيمة عددية
permuted_key = int(permuted_key, 2)
subkeys = []
# توليد المفاتيح الفرعية لكل جولة
for round in range(1, 17):
# الدورانات اليسرى للنصف الأيسر والنصف الأيمن للمفتاح
left_shifts = 1 if round in [1, 2, 9, 16] else 2
permuted_key = ((permuted_key << left_shifts) & 0xFFFFFFFFFFFF) | (permuted_key >> (28 - left_shifts))
# استخدام جدول PC-2 لتحويل المفتاح إلى مفتاح فرعي بطول 48 بتًا
subkey = apply_key_permutation(bin(permuted_key)[2:].zfill(56), pc_2_table)
subkeys.append(subkey)
return subkeys
def initial_permutation(block):
# Perform initial permutation on the block
initial_permutation_table = [58, 50, 42, 34, 26, 18, 10, 2,
60, 52, 44, 36, 28, 20, 12, 4,
62, 54, 46, 38, 30, 22, 14, 6,
64, 56, 48, 40, 32, 24, 16, 8,
57, 49, 41, 33, 25, 17, 9, 1,
59, 51, 43, 35, 27, 19, 11, 3,
|
a9dbf4b3f389e29ff4e6a10b70772311
|
{
"intermediate": 0.32967230677604675,
"beginner": 0.470430463552475,
"expert": 0.1998971551656723
}
|
33,252
|
x
|
f0c512f89c63b52c3a68053dfd7af77f
|
{
"intermediate": 0.3188217282295227,
"beginner": 0.2993789613246918,
"expert": 0.3817993104457855
}
|
33,253
|
Input Handling:-
Your code must handle that plaintext size is of any size not only 8 characters. If the plain text size is less than 8 characters your code should handle that by adding special characters and if the plain text size is more than 8 characters your code should also handle that by dividing plain text to blocks of size 8.
Your code must handle that key size must be 8 characters by displaying error message and request another key from user. handling: - 3 marks
Plain text size < 8 ( 0.5 mark
Plain text size >8 ( 2 mark
Key handling( 0.5 mark
Key Generation 4 marks divided as follows:-
1- Permutated choice1---> 1mark
2- Left shift --> 1mark
3- Permutated choice-2 ---> 1mark
4- Repeat step 2 and 3 to generate the 16 keys---> 1 mark
Encryption 8 marks divided as follows:-
Initial permutation ---> 0.5 mark
2- 16 rounds-----------> 2 marks
Each round (4.5 marks) divided as follows: -
Expansion ---> 0.5 mark
Xor (key, result of expansion) ---> 0.5 mark
SBoxes ----> 2 marks
Permutation -----> 0.5 mark
Xor (result of permutation and left) -----> 0.5 mark
Left and Right swap ---> 0.5 mark
32 bit swap------> 0.5 mark
Inverse initial permutation-----> 0.5 mark
|
18784bbfba1f8e20ac7a2f8663e68741
|
{
"intermediate": 0.4971179664134979,
"beginner": 0.14835681021213531,
"expert": 0.35452526807785034
}
|
33,254
|
# Core Q-learning Class
import numpy as np
print("About to instantiate QLearningAgent")
agent = QLearningAgent(state_size, action_size, learning_rate, discount_factor, epsilon)
class QLearningAgent:
def __init__(self, state_size, action_size, learning_rate, discount_factor, epsilon):
# Existing attributes
self.state_size = state_size
self.action_size = action_size
self.learning_rate = learning_rate
self.discount_factor = discount_factor
self.epsilon = epsilon
self.q_table = np.zeros((state_size, action_size))
# Initialize neurotransmitter systems
self.dopamine_system = DopamineSystem(learning_rate=0.01, prediction_error_sensitivity=0.1)
self.norepinephrine_system = NorepinephrineSystem(base_firing_rate=1.0)
self.acetylcholine_system = AcetylcholineSystem(attention_weights=np.ones(action_size))
self.serotonin_system = SerotoninSystem(mood_state_vector_space=VectorSpace(3), motivation_vector_space=VectorSpace(3))
self.glutamate_system = GlutamateSystem(connectivity_matrix=np.zeros((state_size, action_size)))
self.gaba_system = GABA_System(inhibition_matrix=np.zeros((state_size, action_size)))
# Initialize additional neuromodulator systems
self.endorphins_system = EndorphinsSystem(familiar_environment_factor=1.2) # Example factor
self.substance_p_system = SubstancePSystem(error_factor=0.8) # Example factor
self.anandamide_system = AnandamideSystem(mood_stabilization_factor=1.1) # Example factor
def select_action(self, state):
if np.random.rand() < self.epsilon:
# Explore: choose a random action
return np.random.randint(self.action_size)
else:
# Exploit: choose the best action based on modulated Q-values
q_values_modulated = self.modulate_q_values(state)
return np.argmax(q_values_modulated)
def modulate_q_values(self, state):
# Assume state is an integer index for simplicity
q_values = self.q_table[state]
# Apply modulators
q_values = self.dopamine_system.modulate(q_values)
q_values = self.norepinephrine_system.modulate(q_values)
q_values = self.acetylcholine_system.modulate(q_values)
q_values = self.serotonin_system.modulate(q_values)
q_values = self.glutamate_system.modulate(q_values)
q_values = self.gaba_system.modulate(q_values)
return q_values
def update(self, state, action, reward, next_state, is_novel):
# Modulate reward using the Endorphins system
modulated_reward = self.endorphins_system.modulate_reward(reward, is_novel)
# Apply learning modulation using Substance P system
learning_modulation = self.substance_p_system.modulate_learning(reward)
# Q-learning update with modulated reward and learning rate
old_value = self.q_table[state, action]
next_max = np.max(self.q_table[next_state])
new_value = old_value + self.learning_rate * learning_modulation * (modulated_reward + self.discount_factor * next_max - old_value)
self.q_table[state, action] = new_value
# Update neurotransmitter systems
self.dopamine_system.update(state, action, reward)
self.endorphins_system.update(state, action, modulated_reward)
self.substance_P_system.update(state, action, reward)
self.oxytocin_system.update(state, action)
self.anandamide_system.update(state, action)
self.norepinephrine_system.update(state, action)
self.acetylcholine_system.update(state, action)
self.serotonin_system.update(state, action)
self.glutamate_system.update(state, action)
self.gaba_system.update(state, action)
# … other updates for neurotransmitter systems
class ChatEnvironment:
def __init__(self, max_input_length, max_response_length):
self.max_input_length = max_input_length
self.max_response_length = max_response_length
self.current_input = np.zeros(max_input_length, dtype=int)
def reset(self):
self.current_input = np.zeros(self.max_input_length, dtype=int)
return self.get_state()
def step(self, action):
response = self.generate_response(action)
next_state = self.get_state()
reward = self.get_user_feedback(response)
done = self.is_conversation_over(response)
return next_state, reward, done, {}
def get_state(self):
# State representation based on current input
return self.current_input
def generate_response(self, action):
# Convert action (ASCII values) to a response string
response = ''.join([chr(a) for a in action])
return response
def process_input(self, user_input):
# Convert user input to ASCII values and update the current input
ascii_values = [ord(c) for c in user_input[:self.max_input_length]]
self.current_input[:len(ascii_values)] = ascii_values
def get_user_feedback(self, response):
print(f"AI: {response}")
user_feedback = input("Was this response expected? (yes/no): ")
return 1 if user_feedback.lower() == 'yes' else -1
def is_conversation_over(self, response):
return response.strip() == "Goodbye!"
# Neurotransmitter System Classes:
class DopamineSystem:
def __init__(self, learning_rate, prediction_error_sensitivity):
self.learning_rate = learning_rate # Learning rate of the dopamine system
self.prediction_error_sensitivity = prediction_error_sensitivity
self.prediction_error = 0 # Initial prediction error
def calculate_prediction_error(self, expected_outcome, actual_outcome):
# Calculate the prediction error
self.prediction_error = actual_outcome - expected_outcome
def update_learning_rate(self):
# Adjust the learning rate based on the prediction error
self.learning_rate += self.prediction_error_sensitivity * self.prediction_error
def modulate(self, q_values):
# Modulate Q-values based on the prediction error
# Placeholder logic: adjust q_values based on prediction error
modulated_q_values = q_values * (1 + self.learning_rate * self.prediction_error)
return modulated_q_values
def update(self, state, action, reward):
# Update internal state based on the outcome
# Example: Calculate prediction error and update learning rate
expected_reward = self.q_table[state, action]
self.calculate_prediction_error(expected_reward, reward)
self.update_learning_rate()
#NorepinephrineSystem:
class NorepinephrineSystem:
def init(self, base_firing_rate):
self.firing_rate = base_firing_rate
def adjust_firing_rate(self, attention_level):
self.firing_rate *= attention_level
#AcetylcholineSystem:
class AcetylcholineSystem:
def init(self, attention_weights):
self.attention_weights = attention_weights
def modulate_attention(self, expected_rewards):
# Modulate attention based on the expected rewards
pass # Implementation code here
#SerotoninSystem:
class SerotoninSystem:
def init(self, mood_state_vector_space, motivation_vector_space):
self.mood_state_vector_space = mood_state_vector_space
self.motivation_vector_space = motivation_vector_space
def update_mood(self, mood_vector):
self.mood_state_vector_space.adjust(mood_vector)
def update_motivation(self, motivation_vector):
self.motivation_vector_space.adjust(motivation_vector)
#Glutamate_System:
class GlutamateSystem:
def __init__(self, connectivity_matrix):
self.connectivity_matrix = connectivity_matrix # A matrix representing neural connections
def update_connectivity(self, firing_pattern):
# Update the connectivity matrix based on the neuron's firing pattern
# Placeholder: implement logic to adjust the connectivity matrix
pass
def modulate(self, q_values, state):
# Modulate Q-values based on the current connectivity state
# Placeholder: implement modulation logic based on connectivity_matrix
modulated_q_values = q_values # Modify this according to your logic
return modulated_q_values
#GABASystem:
class GABA_System:
def init(self, inhibition_matrix):
self.inhibition_matrix = inhibition_matrix
def apply_inhibition(self, neuron_group):
# Apply inhibitory effects to the given neuron group
pass # Implementation code here
#EndorphinesSystem:
class EndorphinsSystem:
def __init__(self, familiar_environment_factor):
self.familiar_environment_factor = familiar_environment_factor
self.is_familiar_environment = False
def update(self, state, action, reward):
# Logic to determine if the current environment is familiar
# Placeholder: set self.is_familiar_environment based on state
def modulate_reward(self, reward, is_novel):
if self.is_familiar_environment and is_novel:
return reward * self.familiar_environment_factor
return reward
#Subsance P system:
class SubstancePSystem:
def __init__(self, error_factor):
self.error_factor = error_factor
def modulate_learning(self, reward):
if reward < 0: # Assuming negative reward indicates error
return self.error_factor
return 1.0
#Anadamide System
class AnandamideSystem:
def __init__(self, mood_stabilization_factor):
self.mood_stabilization_factor = mood_stabilization_factor
def modulate_q_values(self, q_values):
# Apply mood stabilization to Q-values
stabilized_q_values = q_values * self.mood_stabilization_factor
return stabilized_q_values
#2. Vector Spaces for Emotional States: Representations of different emotional states that can adjust over time or in response to stimuli.
class VectorSpace:
def init(self, dimensions):
self.vectors = np.zeros(dimensions)
def adjust(self, vector_update):
self.vectors += vector_update
# Instantiate ChatEnvironment
chat_env = ChatEnvironment(max_input_length=50, max_response_length=30)
#3. Q-learning Parameters: These are part of the Q-learning algorithm for decision-making.
class QLearningParameters:
def init(self, alpha, gamma):
self.alpha = alpha # Learning rate
self.gamma = gamma # Discount factor
#4. Q-learning Algorithm: This core decision-making module would use various parameters and the neurotransmitter-like mechanisms to learn and make decisions.
class QLearningAgent:
def init(self, q_table, parameters):
self.q_table = q_table
self.parameters = parameters
# Example parameters - adjust these based on your environment
state_size = 100 # The number of states in the environment
action_size = (30^2)*(20^2) # The number of possible actions the agent can take
learning_rate = 0.01 # The rate at which the agent should learn
discount_factor = 0.95 # The discount factor for future rewards
epsilon = 0.01 # The probability of choosing a random action over the best action
# Instantiate the QLearningAgent with the specified parameters
agent = QLearningAgent(state_size, action_size, learning_rate, discount_factor, epsilon)
# Training loop
num_episodes = 1000 # Number of episodes for training
for episode in range(num_episodes):
state = chat_env.reset() # Reset the environment at the start of each episode
done = False
while not done:
action = agent.select_action(state) # Agent selects an action
next_state, reward, done, _ = chat_env.step(action) # Perform the action on the environment
# Update the agent with the results of the action
agent.update(state, action, reward, next_state, is_novel=False) # 'is_novel' flag needs to be determined
state = next_state # Update state
can you design a q learning ml to fit this model? it can be simple and sent over multiple prompts
|
1a86a360a79750c1173cefb1ecd86dd7
|
{
"intermediate": 0.23296749591827393,
"beginner": 0.4992992579936981,
"expert": 0.26773324608802795
}
|
33,255
|
# -*- coding: utf-8 -*-
"""
Created on Fri Dec 1 03:26:35 2023
@author: ML
"""
def pad_plaintext(plaintext):
while len(plaintext) < 8:
plaintext += “@”
return plaintext[:8]
def text_to_binary(text):
binary_text = “”
for char in text:
binary_char = bin(ord(char))[2:].zfill(8)
binary_text += binary_char
return binary_text
def split_blocks(plaintext):
blocks = []
while len(plaintext) > 0:
blocks.append(plaintext[:8])
plaintext = plaintext[8:]
return blocks
def ascii_to_binary_key(key):
binary_key = “”
for char in key:
binary_key += format(ord(char), ‘08b’)
return binary_key
def apply_key_permutation(binary_key, permutation_table):
permuted_key = “”
for index in permutation_table:
permuted_key += binary_key[index - 1]
return permuted_key
def generate_subkeys(key):
pc_1_table = [57, 49, 41, 33, 25, 17, 9,
1, 58, 50, 42, 34, 26, 18,
10, 2, 59, 51, 43, 35, 27,
19, 11, 3, 60, 52, 44, 36,
63, 55, 47, 39, 31, 23, 15,
7, 62, 54, 46, 38, 30, 22,
14, 6, 61, 53, 45, 37, 29,
21, 13, 5, 28, 20, 12, 4]
pc_2_table = [14, 17, 11, 24, 1, 5,
3, 28, 15, 6, 21, 10,
23, 19, 12, 4, 26, 8,
16, 7, 27, 20, 13, 2,
41, 52, 31, 37, 47, 55,
30, 40, 51, 45, 33, 48,
44, 49, 39, 56, 34, 53,
46, 42, 50, 36, 29, 32]
if len(key) != 8:
raise ValueError(“Key size must be 8 characters.”)
binary_key = ascii_to_binary_key(key)
permuted_key = apply_key_permutation(binary_key, pc_1_table)
# Convert key to numeric value
permuted_key = int(permuted_key, 2)
subkeys = []
# Generate subkeys for each round
for round in range(1, 17):
# Left shifts for left half and right half of the key
left_shifts = 1 if round in [1, 2, 9, 16] else 2
permuted_key = ((permuted_key << left_shifts) & 0xFFFFFFFFFFFF) | (permuted_key >> (28 - left_shifts))
# Use PC-2 table to convert the key to a 48-bit subkey
subkey = apply_key_permutation(bin(permuted_key)[2:].zfill(56), pc_2_table)
subkeys.append(subkey)
return subkeys
def initial_permutation(block):
# Perform initial permutation on the block
initial_permutation_table = [58, 50, 42, 34, 26, 18, 10, 2,
60, 52, 44, 36, 28, 20, 12, 4,
62, 54, 46, 38, 30, 22, 14, 6,
64, 56, 48, 40, 32, 24, 16, 8,
57, 49, 41, 33, 25, 17, 9, 1,
59, 51, 43, 35, 27, 19, 11, 3,
61, 53, 45, 37, 29, 21, 13, 5,
63, 55, 47, 39, 31, 23, 15, 7]
permuted_block = “”
for index in initial_permutation_table:
permuted_block += block[index - 1]
return permuted_block
def expand_permutation(block):
# Perform expansion permutation on the block
expansion_table = [32, 1, 2, 3, 4, 5, 4, 5,
6, 7, 8, 9, 8, 9, 10, 11,
12, 13, 12, 13, 14, 15, 16, 17,
16, 17, 18, 19, 20, 21, 20, 21,
22, 23, 24, 25, 24, 25, 26, 27,
28, 29, 28, 29, 30, 31, 32, 1]
expanded_block = “”
for index in expansion_table:
expanded_block += block[index - 1]
return expanded_block
def substitute(s_box_input, s_box_index):
s_boxes = [
# S1
[
[14, 4, 13, 1, 2, 15, 11, 8, 3, 10, 6, 12, 5, 9, 0, 7],
[0, 15, 7, 4, 14, 2, 13, 1, 10, 6, 12, 11, 9, 5, 3, 8],
[4, 1, 14, 8, 13, 6, 2, 11, 15, 12, 9, 7, 3, 10, 5, 0],
[15, 12, 8, 2, 4, 9, 1, 7, 5, 11, 3, 14, 10, 0, 6, 13]
],
# S2
[
[15, 1, 8, 14, 6, 11, 3, 4, 9, 7, 2, 13, 12, 0, 5, 10],
[3, 13, 4, 7, 15, 2, 8, 14, 12, 0, 1, 10, 6, 9, 11, 5],
[0, 14, 7, 11, 10, 4, 13, 1, 5, 8, 12, 6, 9, 3, 2, 15],
[13, 8, 10, 1, 3, 15, 4, 2, 11, 6, 7, 12, 0, 5, 14, 9]
],
# S3
[
[10, 0, 9, 14, 6, 3, 15, 5, 1, 13, 12, 7, 11, 4, 2, 8],
[13, 7, 0, 9, 3, 4, 6, 10, 2, 8, 5, 14, 12, 11, 15, 1],
[error runfile('C:/Users/ML/Desktop/untitled0.py', wdir='C:/Users/ML/Desktop')
File "C:\Users\ML\Desktop\untitled0.py", line 10
plaintext += “@”
^
SyntaxError: invalid character in identifier
|
fe08d85c64e0b983f80946821dfcf7d0
|
{
"intermediate": 0.36364880204200745,
"beginner": 0.4288807809352875,
"expert": 0.2074703872203827
}
|
33,256
|
Use the given information to find the number of degrees of freedom, the critical values
χ2L and
χ2R, and the confidence interval estimate of
σ. It is reasonable to assume that a simple random sample has been selected from a population with a normal distribution.
White Blood Counts of Women
98% confidence; n
=
148, s
=
1.99 (1000 cells/
μL).
Question content area bottom
Part 1
df
=
enter your response here
(Type a whole number.)
|
9e8478e03e0f37b3498848f969489f04
|
{
"intermediate": 0.3576982319355011,
"beginner": 0.3232567608356476,
"expert": 0.31904494762420654
}
|
33,257
|
def pad_plaintext(plaintext):
while len(plaintext) < 8:
plaintext += "@"
return plaintext[:8]
def text_to_binary(text):
binary_text = ""
for char in text:
binary_char = bin(ord(char))[2:].zfill(8)
binary_text += binary_char
return binary_text
def split_blocks(plaintext):
blocks = []
while len(plaintext) > 0:
blocks.append(plaintext[:8])
plaintext = plaintext[8:]
return blocks
def ascii_to_binary_key(key):
binary_key = ""
for char in key:
binary_key += format(ord(char), '08b')
return binary_key
def apply_key_permutation(binary_key, permutation_table):
permuted_key = ""
for index in permutation_table:
permuted_key += binary_key[index - 1]
return permuted_key
def generate_subkeys(key):
pc_1_table = [57, 49, 41, 33, 25, 17, 9,
1, 58, 50, 42, 34, 26, 18,
10, 2, 59, 51, 43, 35, 27,
19, 11, 3, 60, 52, 44, 36,
63, 55, 47, 39, 31, 23, 15,
7, 62, 54, 46, 38, 30, 22,
14, 6, 61, 53, 45, 37, 29,
21, 13, 5, 28, 20, 12, 4]
pc_2_table = [14, 17, 11, 24, 1, 5,
3, 28, 15, 6, 21, 10,
23, 19, 12, 4, 26, 8,
16, 7, 27, 20, 13, 2,
41, 52, 31, 37, 47, 55,
30, 40, 51, 45, 33, 48,
44, 49, 39, 56, 34, 53,
46, 42, 50, 36, 29, 32]
if len(key) != 8:
raise ValueError("Key size must be 8 characters.")
binary_key = ascii_to_binary_key(key)
permuted_key = apply_key_permutation(binary_key, pc_1_table)
# Convert key to numeric value
permuted_key = int(permuted_key, 2)
subkeys = []
# Generate subkeys for each round
for round in range(1, 17):
# Left shifts for left half and right half of the key
left_shifts = 1 if round in [1, 2, 9, 16] else 2
permuted_key = ((permuted_key << left_shifts) & 0xFFFFFFFFFFFF) | (permuted_key >> (28 - left_shifts))
# Use PC-2 table to convert the key to a 48-bit subkey
subkey = apply_key_permutation(bin(permuted_key)[2:].zfill(56), pc_2_table)
subkeys.append(subkey)
return subkeys
def initial_permutation(block):
# Perform initial permutation on the block
initial_permutation_table = [58, 50, 42, 34, 26, 18, 10, 2,
60, 52, 44, 36, 28, 20, 12, 4,
62, 54, 46, 38, 30, 22, 14, 6,
64, 56, 48, 40, 32, 24, 16, 8,
57, 49, 41, 33, 25, 17, 9, 1,
59, 51, 43, 35, 27, 19, 11, 3,
61, 53, 45, 37, 29, 21, 13, 5,
63, 55, 47, 39, 31, 23, 15, 7]
permuted_block = ""
for index in initial_permutation_table:
permuted_block += block[index - 1]
return permuted_block
def expand_permutation(block):
# Perform expansion permutation on the block
expansion_table = [32, 1, 2, 3, 4, 5, 4, 5,
6, 7, 8, 9, 8, 9, 10, 11,
12, 13, 12, 13, 14, 15, 16, 17,
16, 17, 18, 19, 20, 21, 20, 21,
22, 23, 24, 25, 24, 25, 26, 27,
28, 29, 28, 29, 30, 31, 32, 1]
expanded_block = ""
for index in expansion_table:
expanded_block += block[index - 1]
return expanded_block
def substitute(s_box_input, s_box_index):
s_boxes = [
# S1
[
[14, 4, 13, 1, 2, 15, 11, 8, 3, 10, 6, 12, 5, 9, 0, 7],
[0, 15, 7, 4, 14, 2, 13, 1, 10, 6, 12, 11, 9, 5, 3, 8],
[4, 1, 14, 8, 13, 6, 2, 11, 15, 12, 9, 7, 3, 10, 5, 0],
[15, 12, 8, 2, 4, 9, 1, 7, 5, 11, 3, 14, 10, 0, 6, 13]
]
]
row = int(s_box_input[0] + s_box_input[3], 2)
column = int(s_box_input[1:3], 2)
value = s_boxes[s_box_index][row][column]
return bin(value)[2:].zfill(4)اريد انا ادخل ال plaintext وال key على هذا الكود وفي النهايه يطبع ال Encryption
|
5fea89e4f81c453d254344500982b74f
|
{
"intermediate": 0.343763142824173,
"beginner": 0.41792595386505127,
"expert": 0.23831090331077576
}
|
33,258
|
基于docker compose v3构建datasophon
|
213ef0b18502aadaf872c8804643947a
|
{
"intermediate": 0.38459861278533936,
"beginner": 0.2079230099916458,
"expert": 0.407478392124176
}
|
33,259
|
χ2L =
(Round to two decimal places as needed.)
|
a5e9b0c9e25aa09b1768d2c7e6eb64fb
|
{
"intermediate": 0.33752524852752686,
"beginner": 0.31563419103622437,
"expert": 0.34684062004089355
}
|
33,260
|
The probabilities of events A, B, and A∩B are given. Find (a) P(A U B), (b) the odds in favor of and the odds against A, © the odds in favor of and the odds against B, and (d) the odds in favor of and against A∩B.
P(A) = 4/11
P(B) = 7/11
P(AB) = 0
|
1e084ce5b2815a642e9e5707e8420a1c
|
{
"intermediate": 0.3186441659927368,
"beginner": 0.27213120460510254,
"expert": 0.40922462940216064
}
|
33,261
|
Create a program that will simulate a calculator. Your program will ask the user for up to 4 numbers, however the user does not have to use all 4 numbers, but must use at least 2 numbers. Create a function that checks the user input for this condition. Your program must then have 4 more functions. Multiply(num1,num2,num3,num4), Add(num1,num2,num3,num4), Subtract(num1,num2,num3,num4), and Divide(num1,num2,num3,num4). In the divide function, you must make sure that the divisor (bottom number) is not zero. So, your program will ask for the inputs, then ask what operation the user wants to perform. Finally, your program will show the calculation, as well as the answer as the final output.
|
6bd9d70cd36bec479f7a9221b72c3307
|
{
"intermediate": 0.2774199843406677,
"beginner": 0.31736040115356445,
"expert": 0.40521955490112305
}
|
33,262
|
напиши код для curl на C#
-d '{"inputs": "Astronaut riding a horse"}' \
-H 'Content-Type: application/json' \
-H "Authorization: Bearer xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
|
eedd5c6dac68f3bcdd30bf52a8ae6e44
|
{
"intermediate": 0.31617066264152527,
"beginner": 0.47647011280059814,
"expert": 0.2073592096567154
}
|
33,263
|
Let x be a continuous random variable with a standard normal distribution. Using the accompanying standard normal distribution table, find P(-1.22 <= x <= 0).
|
9da6b44f4c1a1f0850e3f123e8f723f5
|
{
"intermediate": 0.369752436876297,
"beginner": 0.27348530292510986,
"expert": 0.3567623198032379
}
|
33,264
|
how to write print log every new line with comma in dart
|
a4abe2a961dff068f197f22a7eabeac7
|
{
"intermediate": 0.45326608419418335,
"beginner": 0.16943834722042084,
"expert": 0.377295583486557
}
|
33,265
|
how to write print log every new line with comma in dart
|
274573ed878f833bb4dbde3ab3925a6c
|
{
"intermediate": 0.45326608419418335,
"beginner": 0.16943834722042084,
"expert": 0.377295583486557
}
|
33,266
|
def pad_plaintext(plaintext):
while len(plaintext) < 8:
plaintext += "@"
return plaintext[:8]
def text_to_binary(text):
binary_text = ""
for char in text:
binary_char = bin(ord(char))[2:].zfill(8)
binary_text += binary_char
return binary_text
def split_blocks(plaintext):
blocks = []
while len(plaintext) > 0:
blocks.append(plaintext[:8])
plaintext = plaintext[8:]
return blocks
def ascii_to_binary_key(key):
binary_key = ""
for char in key:
binary_key += format(ord(char), '08b')
return binary_key
def apply_key_permutation(binary_key, permutation_table):
permuted_key = ""
for index in permutation_table:
permuted_key += binary_key[index - 1]
return permuted_key
def generate_subkeys(key):
pc_1_table = [57, 49, 41, 33, 25, 17, 9,
1, 58, 50, 42, 34, 26, 18,
10, 2, 59, 51, 43, 35, 27,
19, 11, 3, 60, 52, 44, 36,
63, 55, 47, 39, 31, 23, 15,
7, 62, 54, 46, 38, 30, 22,
14, 6, 61, 53, 45, 37, 29,
21, 13, 5, 28, 20, 12, 4]
pc_2_table = [14, 17, 11, 24, 1, 5,
3, 28, 15, 6, 21, 10,
23, 19, 12, 4, 26, 8,
16, 7, 27, 20, 13, 2,
41, 52, 31, 37, 47, 55,
30, 40, 51, 45, 33, 48,
44, 49, 39, 56, 34, 53,
46, 42, 50, 36, 29, 32]
if len(key) != 8:
raise ValueError("Key size must be 8 characters.")
binary_key = ascii_to_binary_key(key)
permuted_key = apply_key_permutation(binary_key, pc_1_table)
# Convert key to numeric value
permuted_key = int(permuted_key, 2)
subkeys = []
# Generate subkeys for each round
for round in range(1, 17):
# Left shifts for left half and right half of the key
left_shifts = 1 if round in [1, 2, 9, 16] else 2
permuted_key = ((permuted_key << left_shifts) & 0xFFFFFFFFFFFF) | (permuted_key >> (28 - left_shifts))
# Use PC-2 table to convert the key to a 48-bit subkey
subkey = apply_key_permutation(bin(permuted_key)[2:].zfill(56), pc_2_table)
subkeys.append(subkey)
return subkeys
def initial_permutation(block):
# Perform initial permutation on the block
initial_permutation_table = [58, 50, 42, 34, 26, 18, 10, 2,
60, 52, 44, 36, 28, 20, 12, 4,
62, 54, 46, 38, 30, 22, 14, 6,
64, 56, 48, 40, 32, 24, 16, 8,
57, 49, 41, 33, 25, 17, 9, 1,
59, 51, 43, 35, 27, 19, 11, 3,
61, 53, 45, 37, 29, 21, 13, 5,
63, 55, 47, 39, 31, 23, 15, 7]
permuted_block = ""
for index in initial_permutation_table:
permuted_block += block[index - 1]
return permuted_block
def expand_permutation(block):
# Perform expansion permutation on the block
expansion_table = [32, 1, 2, 3, 4, 5, 4, 5,
6, 7, 8, 9, 8, 9, 10, 11,
12, 13, 12, 13, 14, 15, 16, 17,
16, 17, 18, 19, 20, 21, 20, 21,
22, 23, 24, 25, 24, 25, 26, 27,
28, 29, 28, 29, 30, 31, 32, 1]
expanded_block = ""
for index in expansion_table:
expanded_block += block[index - 1]
return expanded_block
def substitute(s_box_input, s_box_index):
s_boxes = [
# S1
[
[14, 4, 13, 1, 2, 15, 11, 8, 3, 10, 6, 12, 5, 9, 0, 7],
[0, 15, 7, 4, 14, 2, 13, 1, 10, 6, 12, 11, 9, 5, 3, 8],
[4, 1, 14, 8, 13, 6, 2, 11, 15, 12, 9, 7, 3, 10, 5, 0],
[15, 12, 8, 2, 4, 9, 1, 7, 5, 11, 3, 14, 10, 0, 6, 13]
]
]
row = int(s_box_input[0] + s_box_input[3], 2)
column = int(s_box_input[1:3], 2)
value = s_boxes[s_box_index][row][column]
return bin(value)[2:].zfill(4) no output i want input from user plaintext then print encription update these code
|
801caea981cde76d0979aaf54fa4ad71
|
{
"intermediate": 0.343763142824173,
"beginner": 0.41792595386505127,
"expert": 0.23831090331077576
}
|
33,267
|
Fix the code
year = 0
balance = 10000.0
TARGET = 20000.0
RATE = 0.05
while balance < TARGET:
year = year + 1
interest = balance * RATE/100
balance = balance + interest
print(year)
|
9fd9a6c8fdc96411709c70cc3e946959
|
{
"intermediate": 0.21463671326637268,
"beginner": 0.5633221864700317,
"expert": 0.22204110026359558
}
|
33,269
|
import json
from collections import Counter
import numpy as np
import tensorflow as tf
from tensorflow.keras.models import load_model
import matplotlib.pyplot as plt
input_file_name = '1.jsonl'
saved_model_name = 'neural_network_model.h5'
sequence_length = 100 # Как определено при обучении
n_features = 3 # Как определено при обучении
n_classes = 2 # Как определено при обучении
top_user_limit = 20 # Топ 20 пользователей
# Загрузка обученной модели
model = load_model(saved_model_name)
# Вычисление частот пользователей
user_counts = Counter()
with open(input_file_name, 'r') as file:
for line in file:
record = json.loads(line.strip())
user = record['SourceHostname_User']
user_counts[user] += 1
# Получение Топ-20 частых пользователей
top_users = [user for user, count in user_counts.most_common(top_user_limit)]
top_user_data = {user: [] for user in top_users}
# Выделяем данные только для Топ-20 частых пользователей
with open(input_file_name, 'r') as file:
for line in file:
record = json.loads(line.strip())
user = record['SourceHostname_User']
if user in top_user_data:
top_user_data[user].append(record)
# Прогнозы и визуализация для Топ-20 частых пользователей
for user in top_users:
user_events = top_user_data[user]
user_events = [data for data in sorted(user_events, key=lambda x: x['UtcTime'])] # Сортируем по времени
user_events = [[event['EventId'], event['ThreadId'], event['Image']] for event in user_events][-sequence_length:] # Берем последние события
x = np.zeros((1, sequence_length, n_features))
padded_sequence = np.array(user_events)
x[:, :padded_sequence.shape[0], :] = padded_sequence
predicted_class_proba = model.predict(x)[0]
predicted_class = np.argmax(predicted_class_proba)
# Визуализация
plt.figure(figsize=(10, 5))
plt.bar(range(n_classes), predicted_class_proba, color='blue', alpha=0.7)
plt.title(f'User: {user}\nPredicted class: {predicted_class} (Prob: {predicted_class_proba[predicted_class]:.2f})')
plt.xlabel('Class')
plt.ylabel('Probability')
plt.xticks(ticks=range(n_classes), labels=[f'Class {i}' for i in range(n_classes)])
plt.show()
Модернизируй код, переделай вывод для юзеров, чтоб были в виде кривых линий
|
832049ca92d80ad66acbff6ff6049768
|
{
"intermediate": 0.2757129669189453,
"beginner": 0.525080680847168,
"expert": 0.19920630753040314
}
|
33,270
|
hello
|
83067171c32d75143c6e827573af3f44
|
{
"intermediate": 0.32064199447631836,
"beginner": 0.28176039457321167,
"expert": 0.39759764075279236
}
|
33,271
|
dijkstra's algorithm python code using priority queue
|
20dcb5b8ef69dc62f45d495adfa8e0e8
|
{
"intermediate": 0.1202748492360115,
"beginner": 0.09502352029085159,
"expert": 0.7847016453742981
}
|
33,272
|
import pgzrun
WIDTH = 310
HEIGHT = 450
scroe = 0
button = Actor("button1_on")
button.pos = WIDTH / 2, HEIGHT / 2 + 60
def draw():
screen.fill("lightblue")
button.draw()
screen.draw.text("Scroe: " + str(scroe), color='white', center=(WIDTH / 2, 90), fontsize=50)
pgzrun.go()
|
5307c7ef060563cac88509c1b9b513d9
|
{
"intermediate": 0.39627283811569214,
"beginner": 0.2979452610015869,
"expert": 0.30578190088272095
}
|
33,273
|
> install.packages("float")
Warning in install.packages :
unable to access index for repository https://cran.ma.imperial.ac.uk/bin/macosx/el-capitan/contrib/3.6:
cannot open URL 'https://cran.ma.imperial.ac.uk/bin/macosx/el-capitan/contrib/3.6/PACKAGES'
Package which is only available in source form, and may need compilation of C/C++/Fortran: ‘float’
Do you want to attempt to install these from sources? (Yes/no/cancel) install.packages("recosystem")
Error in install.packages : Unrecognized response “install.packages("recosystem")”
> install.packages("recommenderlab")
Warning in install.packages :
dependencies ‘arules’, ‘irlba’ are not available
also installing the dependencies ‘float’, ‘recosystem’
Warning in install.packages :
unable to access index for repository https://cran.ma.imperial.ac.uk/bin/macosx/el-capitan/contrib/3.6:
cannot open URL 'https://cran.ma.imperial.ac.uk/bin/macosx/el-capitan/contrib/3.6/PACKAGES'
Packages which are only available in source form, and may need compilation of C/C++/Fortran: ‘float’ ‘recosystem’
Do you want to attempt to install these from sources? (Yes/no/cancel) library(recommenderlab)
Error in install.packages : Unrecognized response “library(recommenderlab)”
|
2450f79ea40a685cf878f4a9edf324b1
|
{
"intermediate": 0.48903217911720276,
"beginner": 0.26153847575187683,
"expert": 0.2494293451309204
}
|
33,274
|
please build script for download video tiktok by url using python code
|
d7c767f5716a5cb99d40fd6b9e0a1de7
|
{
"intermediate": 0.36818498373031616,
"beginner": 0.20408235490322113,
"expert": 0.4277326166629791
}
|
33,275
|
Merhaba, "client.on(‘messageCreate’, async (msg) => {
if (msg.channel.id === config.channelId) {
if ([String(owoId), String(config.authorId)].includes(msg.author.id)) {
const regex = /human|captcha|dm|banned|https://owobot.com/captcha|Beep|human?/gi;
if (msg.content.includes(<@${client.user.id}>)) {
msg.user.send(<@${msg.author.id}> CAPTCHA!).then((captchaMsg) => {
setTimeout(() => {
captchaMsg.delete();
msg.delete();
}, 10000);
});
} else if (!captchaSent && (msg.content.toLowerCase().match(regex) || msg.channel.type === ‘dm’)) {
console.log((${client.user.username}) Owo need captcha);
msg.channel.send(‘Owo need captcha.’);
captchaSent = true;
statusBot = false;
}
}
}
});" düzeltir misin?
|
bbec412a05d78e51b332154306ab86bb
|
{
"intermediate": 0.43968871235847473,
"beginner": 0.32100456953048706,
"expert": 0.2393067181110382
}
|
33,276
|
please check this code :import requests
from bs4 import BeautifulSoup
url = "https://startup.jobs/?remote=true&c=Full-Time&q=machine+learning"
# Make a GET request to fetch the raw HTML content
response = requests.get(url)
if response.status_code == 200:
# Parse the HTML content
soup = BeautifulSoup(response.text, 'html.parser')
# Now you can work with the 'soup' object for further processing
# Find the search input element
search_input = soup.find('input', {'type': 'search', 'name': 'query'})
# Find the remote checkbox
remote_checkbox = soup.find('input', {'type': 'checkbox', 'name': 'remote'})
# Find the full-time checkbox
full_time_checkbox = soup.find('input', {'type': 'checkbox', 'name': 'commitments[]', 'value': 'Full-Time'})
# Check if all elements are found before proceeding
if search_input and remote_checkbox and full_time_checkbox:
# Set the search query
search_query = search_input.get('value')
print("Search Query:", search_query)
# Check if the remote checkbox is checked
if 'checked' in remote_checkbox.attrs and remote_checkbox['checked'] == 'checked':
print("Remote Checkbox is checked")
# Check if the full-time checkbox is checked
if 'checked' in full_time_checkbox.attrs and full_time_checkbox['checked'] == 'checked':
print("Full-Time Checkbox is checked")
# Find all job listings
job_listings = soup.find_all('div', class_='job_listing')
# Counter to keep track of printed jobs
count = 0
# Iterate through job listings
for job in job_listings:
# Check if the job is machine learning, full time, and remote
if 'machine learning' in job.text.lower() and 'full-time' in job.text.lower() and 'remote' in job.text.lower():
# Print job details
print("\nJob Title:", job.find('h3', class_='job_listing-title').text.strip())
print("Company:", job.find('a', class_='company').text.strip())
print("Location:", job.find('span', class_='location').text.strip())
print("Link:", job.find('a', class_='job_listing-clickbox')['href'])
print("-" * 30)
# Increment the counter
count += 1
# Break the loop after printing 10 jobs
if count == 10:
break
# Inform if no matching jobs were found
if count == 0:
print("No jobs found matching the criteria.")
else:
print("One or more elements not found.")
else:
print("Failed to retrieve the page. Status code:", response.status_code)
|
0fb2814d1b0cd37d30502da5ec778489
|
{
"intermediate": 0.23007863759994507,
"beginner": 0.6466384530067444,
"expert": 0.12328296154737473
}
|
33,277
|
is phpmyadmin similar to mysql?
|
d274b70110986d122a28247d3abfce8e
|
{
"intermediate": 0.47106650471687317,
"beginner": 0.3370046019554138,
"expert": 0.19192884862422943
}
|
33,278
|
对于多项式岭回归，使用某种方法探索以下超参数空间（p=[1,2,3], alpha = [0.001,0.01,0.1,1,10,100,1000],并报告最佳超参数 best_p 和 best_alpha，从而最小化验证数据的 MAE
|
3a22e1a012d89427e634526a4ea8067f
|
{
"intermediate": 0.29913973808288574,
"beginner": 0.32553616166114807,
"expert": 0.3753241002559662
}
|
33,279
|
from sklearn.preprocessing import StandardScaler
ss = StandardScaler()
train_sub_std_X = ss.fit_transform(train_sub_X)
valid_std_X = ss.transform(valid_X)
import torch
batch_size = 32
train_X_torch = torch.tensor(train_sub_std_X, dtype=torch.float)
valid_X_torch = torch.tensor(valid_std_X, dtype=torch.float)
# convert a vector to a matrix by reshape
train_Y_torch = torch.tensor(train_sub_y.reshape(-1, 1), dtype=torch.float)
valid_Y_torch = torch.tensor(valid_y.reshape(-1,1), dtype=torch.float)
train_dataset = torch.utils.data.TensorDataset(train_X_torch, train_Y_torch)
valid_dataset = torch.utils.data.TensorDataset(valid_X_torch, valid_Y_torch)
train_loader = torch.utils.data.DataLoader(train_dataset, batch_size=batch_size, shuffle=True)
valid_loader = torch.utils.data.DataLoader(valid_dataset, batch_size=batch_size, shuffle=True)
|def calculate(model, loss_fn, loader, opt=None):
if opt is None:
model.eval()
whole_loss = 0
count = len(loader.dataset)
for X, y in loader:
# X, y = X.cuda(), y.cuda() # Transfer data to the GPU
y_pred = model(X) # Predict y from X
loss = loss_fn(y_pred, y) # Calculate the average of the losses in a mini-batch
whole_loss += loss.item()*len(y) # Calculate the total loss for the entire epoch
# Update weights
if opt is not None:
opt.zero_grad()
loss.backward()
opt.step()
mean_loss = whole_loss / count
if opt is None:
model.train()
return mean_loss
from livelossplot import PlotLosses
def train(model, loss_fn, opt, train_loader, valid_loader, epoch=50):
liveloss = PlotLosses() # Initialize the drawing
for i in range(epoch):
train_loss = calculate(model, loss_fn, train_loader, opt)
valid_loss = calculate(model, loss_fn, valid_loader)
# Visualize the loss and accuracy values.
liveloss.update({
‘loss’: train_loss,
‘val_loss’: valid_loss,
})
liveloss.draw()
return model # Return the trained model
torch.manual_seed(0) # Ensure reproducibility of training results
mlp = torch.nn.Sequential(
torch.nn.Linear(12, 24),
torch.nn.ReLU(),
torch.nn.Linear(24, 1)
)
# mlp.cuda() # Transfer the model to the GPU
# Prepare loss functions and optimization methods
loss_fn = torch.nn.L1Loss()
optimizer = torch.optim.SGD(mlp.parameters(), lr=0.01)
根据上述代码计算train 和 valid数据的mae， 生成新的test数据并计算其mae
|
07c5718f553cc9c1d8e6186fe79e536f
|
{
"intermediate": 0.4639964997768402,
"beginner": 0.34687596559524536,
"expert": 0.18912751972675323
}
|
33,280
|
This code produces an error :!pip install selenium
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.chrome.service import Service
from selenium.webdriver.chrome.options import Options
from bs4 import BeautifulSoup
import time
webdriver_path = r"C:\Users\14802\Desktop\chrome-win32\chrome.exe" # Replace with your ChromeDriver path
url = "https://startup.jobs/?remote=true&c=Full-Time&q=machine+learning"
# Setup Chrome options
chrome_options = Options()
# Use headless mode if you do not need a browser UI
# chrome_options.add_argument("--headless")
# Set path to chromedriver as per your configuration
webdriver_service = Service(webdriver_path)
# Choose Chrome Browser
driver = webdriver.Chrome(service=webdriver_service, options=chrome_options)
# Get URL
driver.get(url)
# Wait for JavaScript to load
time.sleep(5) # Adjust the sleep time if necessary, depending on load times
# Get page source and close the browser
page_source = driver.page_source
driver.quit()
# Parse the HTML content
soup = BeautifulSoup(page_source, 'html.parser')
# Find all job listings
job_listings = soup.find_all('div', class_='job_listing')
# Counter to keep track of printed jobs
count = 0
# Iterate through job listings
for job in job_listings:
# Check if the job is machine learning, full time, and remote
if 'machine learning' in job.text.lower():
# Print job details
title_element = job.find('h3', class_='job_listing-title')
company_element = job.find('a', class_='company')
location_element = job.find('span', class_='location')
link_element = job.find('a', class_='job_listing-clickbox')
# Ensure all elements were found before trying to access their contents
if title_element and company_element and location_element and link_element:
print("\nJob Title:", title_element.text.strip())
print("Company:", company_element.text.strip())
print("Location:", location_element.text.strip())
print("Link:", link_element['href'])
print("-" * 30)
# Increment the counter
count += 1
# Break the loop after printing 10 jobs
|
684c0a9544e10aaf896c72e6371798bb
|
{
"intermediate": 0.09330467879772186,
"beginner": 0.8396633863449097,
"expert": 0.06703194975852966
}
|
33,281
|
from sklearn.ensemble import RandomForestRegressor
from sklearn.model_selection import GridSearchCV
rfr = RandomForestRegressor(random_state=0)
parameter_tree = {
'n_estimators':[10,20,50,100,200,500],
'max_depth':[2,4,6,8,10,12,14,16,18,20]
}
grid_rfr = GridSearchCV(rfr, parameter_tree, scoring = 'neg_mean_absolute_error', cv=5)
grid_rfr.fit(train_X, train_y)
rf_best_parameters = grid_rfr.best_params_
print(rf_best_parameters)
from sklearn.ensemble import RandomForestRegressor
from sklearn.metrics import mean_absolute_error
best_n_estimators = 500
best_max_depth = 12
rfr = RandomForestRegressor(n_estimators=500, max_depth=12, random_state=0)
rfr.fit(train_X, train_y)
predicted = rfr.predict(test_X)
test_mae_random_forest = mae(test_y, predicted)
print(test_mae_random_forest)
讨论除了交叉验证之外是否还有最佳的模型选择方法。 将预测精度与上述代码获得的测试数据进行比较（本练习允许添加代码单元）。
|
50b40f08529260db4cec4905a12b0935
|
{
"intermediate": 0.2587928771972656,
"beginner": 0.41783004999160767,
"expert": 0.3233770430088043
}
|
33,282
|
is there a "sort by" in sql
|
38d437999c8b4a1f5ab85d4ecbfe13e1
|
{
"intermediate": 0.2936173379421234,
"beginner": 0.19958271086215973,
"expert": 0.5067999958992004
}
|
33,283
|
hi
|
a9d67027db78aa80a84d7dcf134af77e
|
{
"intermediate": 0.3246487081050873,
"beginner": 0.27135494351387024,
"expert": 0.40399640798568726
}
|
33,284
|
HOW ALL YOUR WORK. REMEMBER THAT PROGRAM SEGMENTS ARE TO BE WRITTEN IN JAVA.
Assume that the classes listed in the Java Quick Reference have been imported where appropriate.
Unless otherwise noted in the question, assume that parameters in method calls are not null and that methods are called only when their preconditions are satisfied.
In writing solutions for each question, you may use any of the accessible methods that are listed in classes defined in that question. Writing significant amounts of code that can be replaced by a call to one of these methods will not receive full credit.
For this question, assume that the variables wordA, wordB, and letter have been correctly declared and initialized.
Write a segment of code that prints the value of wordA or wordB depending on which letter appears earlier. If letter does not appear in wordA or wordB or letter appears at the same location in each word, it should print "neither".
wordA wordB letter output
nomads labors o nomads
nomads labors a labors
nomads labors s neither
nomads labors m nomads
nomads labors b labors
nomads labors x neither
|
b50854e88c44a09a190bb715f153ff32
|
{
"intermediate": 0.09966831654310226,
"beginner": 0.7936404943466187,
"expert": 0.10669118911027908
}
|
33,285
|
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <unistd.h>
#include <sys/types.h>
#include <sys/wait.h>
#include <fcntl.h>
#include <glob.h>
#define MAX_INPUT_SIZE 1024
#define MAX_ARG_NUM 16
#define MAX_PATH_SIZE 256
int execute_command(char *args[]);
void handle_redirection(char *args[], int *input_fd, int *output_fd);
void handle_pipes(char *args1[], char *args2[]);
char **tokenize_input(char *input);
char **expand_wildcards(char *arg);
void execute_builtin_command(char *args[]);
int is_builtin_command(char *command);
void print_error(const char *message);
int main(int argc, char *argv[]) {
if (argc == 1) {
// Interactive mode
printf("Welcome to my shell!\n");
char input[MAX_INPUT_SIZE];
while (1) {
printf("mysh> ");
fflush(stdout);
if (fgets(input, MAX_INPUT_SIZE, stdin) == NULL) {
break; // End of input
}
// Remove newline character from input
input[strcspn(input, "\n")] = 0;
// Tokenize input
char **tokens = tokenize_input(input);
// Check for exit command
if (tokens[0] != NULL && strcmp(tokens[0], "exit") == 0) {
printf("mysh: exiting\n");
break;
}
// Execute command
if (tokens[0] != NULL) {
if (!is_builtin_command(tokens[0])) {
// If not a built-in command, expand wildcards and execute
char **expanded_args = expand_wildcards(tokens[0]);
free(tokens[0]);
tokens = expanded_args;
execute_command(tokens);
} else {
// If a built-in command, execute directly
execute_builtin_command(tokens);
}
}
// Free memory
for (int i = 0; tokens[i] != NULL; i++) {
free(tokens[i]);
}
free(tokens);
}
} else if (argc == 2) {
// Batch mode
FILE *script_file = fopen(argv[1], "r");
if (script_file == NULL) {
print_error("script file not found");
}
char input[MAX_INPUT_SIZE];
while (fgets(input, MAX_INPUT_SIZE, script_file) != NULL) {
// Remove newline character from input
input[strcspn(input, "\n")] = '\0';
// Tokenize input
char **tokens = tokenize_input(input);
// Check for exit command
if (tokens[0] != NULL && strcmp(tokens[0], "exit") == 0) {
printf("mysh: exiting\n");
break;
}
// Execute command
if (tokens[0] != NULL) {
if (!is_builtin_command(tokens[0])) {
// If not a built-in command, expand wildcards and execute
char **expanded_args = expand_wildcards(tokens[0]);
free(tokens[0]);
tokens = expanded_args;
execute_command(tokens);
} else {
// If a built-in command, execute directly
execute_builtin_command(tokens);
}
}
// Free memory
for (int i = 0; tokens[i] != NULL; i++) {
free(tokens[i]);
}
free(tokens);
}
fclose(script_file);
} else {
fprintf(stderr, "Usage: %s [script-file]\n", argv[0]);
return EXIT_FAILURE;
}
return 0;
}
int execute_command(char *args[]) {
if (is_builtin_command(args[0])) {
execute_builtin_command(args);
return 0; // Indicate success for built-in commands
}
pid_t pid;
int status;
pid = fork();
if (pid == 0) {
// Child process
int input_fd = 0; // Default to stdin
int output_fd = 1; // Default to stdout
handle_redirection(args, &input_fd, &output_fd);
if (input_fd != 0) {
dup2(input_fd, 0);
close(input_fd);
}
if (output_fd != 1) {
dup2(output_fd, 1);
close(output_fd);
}
execvp(args[0], args);
// If execvp fails
print_error("command not found");
} else if (pid < 0) {
// Forking error
print_error("forking error");
} else {
// Parent process
waitpid(pid, &status, 0);
return WEXITSTATUS(status);
}
// Add a return statement here
return -1;
}
void handle_redirection(char *args[], int *input_fd, int *output_fd) {
int i = 0;
while (args[i] != NULL) {
if (strcmp(args[i], "<") == 0) {
*input_fd = open(args[i + 1], O_RDONLY);
if (*input_fd == -1) {
print_error("input redirection error");
}
args[i] = NULL;
} else if (strcmp(args[i], ">") == 0) {
*output_fd = open(args[i + 1], O_WRONLY | O_CREAT | O_TRUNC, 0640);
if (*output_fd == -1) {
print_error("output redirection error");
}
args[i] = NULL;
}
i++;
}
}
void handle_pipes(char *args1[], char *args2[]) {
int pipe_fd[2];
int status;
if (pipe(pipe_fd) == -1) {
print_error("pipe creation error");
}
pid_t pid1, pid2;
pid1 = fork();
if (pid1 == 0) {
// Child process 1
close(pipe_fd[0]); // Close unused read end
// Redirect stdout to the write end of the pipe
dup2(pipe_fd[1], 1);
close(pipe_fd[1]);
execvp(args1[0], args1);
// If execvp fails
print_error("command not found");
} else if (pid1 < 0) {
// Forking error
print_error("forking error");
}
pid2 = fork();
if (pid2 == 0) {
// Child process 2
close(pipe_fd[1]); // Close unused write end
// Redirect stdin to the read end of the pipe
dup2(pipe_fd[0], 0);
close(pipe_fd[0]);
execvp(args2[0], args2);
// If execvp fails
print_error("command not found");
} else if (pid2 < 0) {
// Forking error
print_error("forking error");
}
// Close both ends of the pipe in the parent process
close(pipe_fd[0]);
close(pipe_fd[1]);
// Wait for both child processes to finish
waitpid(pid1, &status, 0);
waitpid(pid2, &status, 0);
}
char **tokenize_input(char *input) {
char **tokens = malloc(MAX_ARG_NUM * sizeof(char *));
if (tokens == NULL) {
print_error("memory allocation error");
}
int token_count = 0;
char *token = strtok(input, " ");
while (token != NULL) {
tokens[token_count++] = strdup(token);
if (tokens[token_count - 1] == NULL) {
print_error("memory allocation error");
}
token = strtok(NULL, " ");
}
tokens[token_count] = NULL;
return tokens;
}
char **expand_wildcards(char *arg) {
glob_t glob_result;
if (glob(arg, GLOB_NOCHECK, NULL, &glob_result) != 0) {
print_error("wildcard expansion error");
}
char **expanded_args = malloc((glob_result.gl_pathc + 1) * sizeof(char *));
if (expanded_args == NULL) {
print_error("memory allocation error");
}
for (size_t i = 0; i < glob_result.gl_pathc; i++) {
expanded_args[i] = strdup(glob_result.gl_pathv[i]);
if (expanded_args[i] == NULL) {
print_error("memory allocation error");
}
}
expanded_args[glob_result.gl_pathc] = NULL;
globfree(&glob_result);
return expanded_args;
}
void execute_builtin_command(char *args[]) {
if (strcmp(args[0], "cd") == 0) {
if (args[1] != NULL) {
if (chdir(args[1]) == -1) {
print_error("cd error");
}
} else {
fprintf(stderr, "cd: missing argument\n");
}
} else if (strcmp(args[0], "pwd") == 0) {
char cwd[MAX_PATH_SIZE];
if (getcwd(cwd, sizeof(cwd)) != NULL) {
printf("%s\n", cwd);
} else {
print_error("pwd error");
}
} else if (strcmp(args[0], "which") == 0) {
if (args[1] != NULL) {
char *path = NULL;
// Check if the command is a built-in command
if (is_builtin_command(args[1])) {
printf("%s: shell built-in command\n", args[1]);
} else {
// Search for the program in the specified directories
char *directories[] = {"/usr/local/bin", "/usr/bin", "/bin"};
for (int i = 0; i < (int)(sizeof(directories) / sizeof(directories[0])); i++) {
char command_path[MAX_PATH_SIZE];
snprintf(command_path, MAX_PATH_SIZE, "%s/%s", directories[i], args[1]);
if (access(command_path, X_OK) == 0) {
path = strdup(command_path);
break;
}
}
if (path != NULL) {
printf("%s\n", path);
free(path);
} else {
fprintf(stderr, "%s: command not found\n", args[1]);
}
}
} else {
fprintf(stderr, "which: missing argument\n");
}
} else if (strcmp(args[0], "echo") == 0) {
// Handle echo command
for (int i = 1; args[i] != NULL; i++) {
printf("%s", args[i]);
if (args[i + 1] != NULL) {
printf(" ");
}
}
printf("\n");
}
}
int is_builtin_command(char *command) {
return (strcmp(command, "cd") == 0 || strcmp(command, "pwd") == 0 || strcmp(command, "which") == 0);
}
void print_error(const char *message) {
fprintf(stderr, "mysh: %s\n", message);
exit(EXIT_FAILURE);
}
the code above cannot currently handle echo commands. for example, if i run the program with a sh file that has three lines of echo commands, it will instead output three blank lines instead of three strings. other commands such as pwd, which, ls, and cd work fine so what is the issue
|
67e52e02cdf2c244e7e7eb732a697ea9
|
{
"intermediate": 0.4495420455932617,
"beginner": 0.4141734838485718,
"expert": 0.13628441095352173
}
|
33,286
|
in SQL, select a substring from "<Pin name="EmergencyLightBar" type="din">0</Pin>" that shows just the zero between the > and <
|
69f5c6ec8525bfd3a15e984694320d11
|
{
"intermediate": 0.35190895199775696,
"beginner": 0.23241661489009857,
"expert": 0.41567444801330566
}
|
33,287
|
I have to fine-tune a llm to generate Indian legal affidavits
How should I start
Give steps with some code please
|
c1e4b0f6d40a3ea2c45009b6d15dc180
|
{
"intermediate": 0.37993481755256653,
"beginner": 0.20852357149124146,
"expert": 0.41154158115386963
}
|
33,288
|
import openai
# Пересохраните ваш API-ключ от OpenAI
openai.api_key = "YOUR_API_KEY"
# Задайте различные параметры
prompt = "Здравствуйте! Как я могу помочь вам сегодня?"
voice = "en-US-Wavenet-J"
temperature = 0.8
max_tokens = 100
# Создайте функцию для генерации озвученного текста
def generate_voiced_text(prompt, voice, temperature, max_tokens):
response = openai.Completion.create(
engine="text-davinci-003",
prompt=prompt,
temperature=temperature,
max_tokens=max_tokens,
n=1,
stop=None,
)
voiced_text = response.choices[0].text
return voiced_text
# Озвучьте текст с помощью функции
voiced_text = generate_voiced_text(prompt, voice, temperature, max_tokens)
# Выведите озвученный текст
print(voiced_text)
|
13695f9c79e05c6292c9b0174ad870bc
|
{
"intermediate": 0.29516851902008057,
"beginner": 0.447720468044281,
"expert": 0.2571110129356384
}
|
33,289
|
hi there, a coding challenge. assume the language is purescript. make a datatype of kind `forall k. k -> k`, call it Proxy, and give it a Bind typeclass instance
|
09931dbe16383a91d3b08738abf8e814
|
{
"intermediate": 0.23965765535831451,
"beginner": 0.661445140838623,
"expert": 0.09889727830886841
}
|
33,290
|
in JS, how do I have regex matching either a character or the end of string?
|
7a7c99a3fb4fbab38168a7d33de68711
|
{
"intermediate": 0.5082759857177734,
"beginner": 0.1984531581401825,
"expert": 0.29327091574668884
}
|
33,291
|
in JS, how do I have regex matching either a character or the end of string?
|
2dd159464b0a5e22fb7f1453d1eb1884
|
{
"intermediate": 0.5082759857177734,
"beginner": 0.1984531581401825,
"expert": 0.29327091574668884
}
|
33,292
|
def pad_plaintext(plaintext):
while len(plaintext) < 8:
plaintext += "@"
return plaintext[:8]
def text_to_binary(text):
binary_text = ""
for char in text:
binary_char = bin(ord(char))[2:].zfill(8)
binary_text += binary_char
return binary_text
def split_blocks(plaintext):
blocks = []
while len(plaintext) > 0:
blocks.append(plaintext[:8])
plaintext = plaintext[8:]
return blocks
def ascii_to_binary_key(key):
binary_key = ""
for char in key:
binary_key += format(ord(char), '08b')
return binary_key
def apply_key_permutation(binary_key, permutation_table):
permuted_key = ""
for index in permutation_table:
permuted_key += binary_key[index - 1]
return permuted_key
def generate_subkeys(key):
pc_1_table = [57, 49, 41, 33, 25, 17, 9,
1, 58, 50, 42, 34, 26, 18,
10, 2, 59, 51, 43, 35, 27,
19, 11, 3, 60, 52, 44, 36,
63, 55, 47, 39, 31, 23, 15,
7, 62, 54, 46, 38, 30, 22,
14, 6, 61, 53, 45, 37, 29,
21, 13, 5, 28, 20, 12, 4]
pc_2_table = [14, 17, 11, 24, 1, 5,
3, 28, 15, 6, 21, 10,
23, 19, 12, 4, 26, 8,
16, 7, 27, 20, 13, 2,
41, 52, 31, 37, 47, 55,
30, 40, 51, 45, 33, 48,
44, 49, 39, 56, 34, 53,
46, 42, 50, 36, 29, 32]
if len(key) != 8:
raise ValueError("Key size must be 8 characters.")
binary_key = ascii_to_binary_key(key)
permuted_key = apply_key_permutation(binary_key, pc_1_table)
# Convert key to numeric value
permuted_key = int(permuted_key, 2)
subkeys = []
# Generate subkeys for each round
for round in range(1, 17):
# Left shifts for left half and right half of the key
left_shifts = 1 if round in [1, 2, 9, 16] else 2
permuted_key = ((permuted_key << left_shifts) & 0xFFFFFFFFFFFF) | (permuted_key >> (28 - left_shifts))
# Use PC-2 table to convert the key to a 48-bit subkey
subkey = apply_key_permutation(bin(permuted_key)[2:].zfill(56), pc_2_table)
subkeys.append(subkey)
return subkeys
def initial_permutation(block):
# Perform initial permutation on the block
initial_permutation_table = [58, 50, 42, 34, 26, 18, 10, 2,
60, 52, 44, 36, 28, 20, 12, 4,
62, 54, 46, 38, 30, 22, 14, 6,
64, 56, 48, 40, 32, 24, 16, 8,
57, 49, 41, 33, 25, 17, 9, 1,
59, 51, 43, 35, 27, 19, 11, 3,
61, 53, 45, 37, 29, 21, 13, 5,
63, 55, 47, 39, 31, 23, 15, 7]
permuted_block = ""
for index in initial_permutation_table:
permuted_block += block[index - 1]
return permuted_block
def expand_permutation(block):
# Perform expansion permutation on the block
expansion_table = [32, 1, 2, 3, 4, 5, 4, 5,
6, 7, 8, 9, 8, 9, 10, 11,
12, 13, 12, 13, 14, 15, 16, 17,
16, 17, 18, 19, 20, 21, 20, 21,
22, 23, 24, 25, 24, 25, 26, 27,
28, 29, 28, 29, 30, 31, 32, 1]
expanded_block = ""
for index in expansion_table:
expanded_block += block[index - 1]
return expanded_block
def substitute(s_box_input, s_box_index):
s_boxes = [
# S1
[
[14, 4, 13, 1, 2, 15, 11, 8, 3, 10, 6, 12, 5, 9, 0, 7],
[0, 15, 7, 4, 14, 2, 13, 1, 10, 6, 12, 11, 9, 5, 3, 8],
[4, 1, 14, 8, 13, 6, 2, 11, 15, 12, 9, 7, 3, 10, 5, 0],
[15, 12, 8, 2, 4, 9, 1, 7, 5, 11, 3, 14, 10, 0, 6, 13]
]
]
row = int(s_box_input[0] + s_box_input[3], 2)
column = int(s_box_input[1:3], 2)
value = s_boxes[s_box_index][row][column]
return bin(value)[2:].zfill(4)error in line 96 permuted _block +=block [index-1]
|
9fb0769f72ef896947a2fd9051bec197
|
{
"intermediate": 0.343763142824173,
"beginner": 0.41792595386505127,
"expert": 0.23831090331077576
}
|
33,293
|
hi i need you to create a JSON file for me
|
26476030f1b1f7bafd9fd9a14a23f5a5
|
{
"intermediate": 0.3315412104129791,
"beginner": 0.20640309154987335,
"expert": 0.4620557427406311
}
|
33,294
|
please build script for download tiktok by url using python
|
7489922829fac8ebcee00fd68451db95
|
{
"intermediate": 0.40691426396369934,
"beginner": 0.1716650277376175,
"expert": 0.421420693397522
}
|
33,295
|
python charm program a random guessing number until 1000
|
408d2dd0ae7667cdbdc172172afddc81
|
{
"intermediate": 0.3804894685745239,
"beginner": 0.31313037872314453,
"expert": 0.30638012290000916
}
|
33,296
|
def pad_plaintext(plaintext):
while len(plaintext) < 8:
plaintext += "@"
return plaintext[:8]
def text_to_binary(text):
binary_text = ""
for char in text:
binary_char = bin(ord(char))[2:].zfill(8)
binary_text += binary_char
return binary_text
def split_blocks(plaintext):
blocks = []
while len(plaintext) > 0:
blocks.append(plaintext[:8])
plaintext = plaintext[8:]
return blocks
def ascii_to_binary_key(key):
binary_key = ""
for char in key:
binary_key += format(ord(char), '08b')
return binary_key
def apply_key_permutation(binary_key, permutation_table):
permuted_key = ""
for index in permutation_table:
permuted_key += binary_key[index - 1]
return permuted_key
def generate_subkeys(key):
pc_1_table = [57, 49, 41, 33, 25, 17, 9,
1, 58, 50, 42, 34, 26, 18,
10, 2, 59, 51, 43, 35, 27,
19, 11, 3, 60, 52, 44, 36,
63, 55, 47, 39, 31, 23, 15,
7, 62, 54, 46, 38, 30, 22,
14, 6, 61, 53, 45, 37, 29,
21, 13, 5, 28, 20, 12, 4]
pc_2_table = [14, 17, 11, 24, 1, 5,
3, 28, 15, 6, 21, 10,
23, 19, 12, 4, 26, 8,
16, 7, 27, 20, 13, 2,
41, 52, 31, 37, 47, 55,
30, 40, 51, 45, 33, 48,
44, 49, 39, 56, 34, 53,
46, 42, 50, 36, 29, 32]
if len(key) != 8:
raise ValueError("Key size must be 8 characters.")
binary_key = ascii_to_binary_key(key)
permuted_key = apply_key_permutation(binary_key, pc_1_table)
# Convert key to numeric value
permuted_key = int(permuted_key, 2)
subkeys = []
# Generate subkeys for each round
for round in range(1, 17):
# Left shifts for left half and right half of the key
left_shifts = 1 if round in [1, 2, 9, 16] else 2
permuted_key = ((permuted_key << left_shifts) & 0xFFFFFFFFFFFF) | (permuted_key >> (28 - left_shifts))
# Use PC-2 table to convert the key to a 48-bit subkey
subkey = apply_key_permutation(bin(permuted_key)[2:].zfill(56), pc_2_table)
subkeys.append(subkey)
return subkeys
def initial_permutation(block):
# Perform initial permutation on the block
initial_permutation_table = [58, 50, 42, 34, 26, 18, 10, 2,
60, 52, 44, 36, 28, 20, 12, 4,
62, 54, 46, 38, 30, 22, 14, 6,
64, 56, 48, 40, 32, 24, 16, 8,
57, 49, 41, 33, 25, 17, 9, 1,
59, 51, 43, 35, 27, 19, 11, 3,
61, 53, 45, 37, 29, 21, 13, 5,
63, 55, 47, 39, 31, 23, 15, 7]
permuted_block = ""
for index in initial_permutation_table:
permuted_block += block[index - 1]
return permuted_block
def expand_permutation(block):
# Perform expansion permutation on the block
expansion_table = [32, 1, 2, 3, 4, 5, 4, 5,
6, 7, 8, 9, 8, 9, 10, 11,
12, 13, 12, 13, 14, 15, 16, 17,
16, 17, 18, 19, 20, 21, 20, 21,
22, 23, 24, 25, 24, 25, 26, 27,
28, 29, 28, 29, 30, 31, 32, 1]
expanded_block = ""
for index in expansion_table:
expanded_block += block[index - 1]
return expanded_block
def substitute(s_box_input, s_box_index):
s_boxes = [
# S1
[
[14, 4, 13, 1, 2, 15, 11, 8, 3, 10, 6, 12, 5, 9, 0, 7],
[0, 15, 7, 4, 14, 2, 13, 1, 10, 6, 12, 11, 9, 5, 3, 8],
[4, 1, 14, 8, 13, 6, 2, 11, 15, 12, 9, 7, 3, 10, 5, 0],
[15, 12, 8, 2, 4, 9, 1, 7, 5, 11, 3, 14, 10, 0, 6, 13]
]
]
row = int(s_box_input[0] + s_box_input[3], 2)
column = int(s_box_input[1:3], 2)
value = s_boxes[s_box_index][row][column]
return bin(value)[2:].zfill(4)لا استطيع حل مشكله straing index out of range in permuted _block +)=block [index-1]
|
d7e1f47bba11a01eb8ba1484e7d3de7b
|
{
"intermediate": 0.343763142824173,
"beginner": 0.41792595386505127,
"expert": 0.23831090331077576
}
|
33,297
|
https://stablediffusion.fr/chatgpt4
|
5c846331e29ce3cb857c5ed13942281c
|
{
"intermediate": 0.4328889846801758,
"beginner": 0.22920450568199158,
"expert": 0.33790653944015503
}
|
33,298
|
def pad_plaintext(plaintext):
while len(plaintext) < 8:
plaintext += “@”
return plaintext[:8]
def text_to_binary(text):
binary_text = “”
for char in text:
binary_char = bin(ord(char))[2:].zfill(8)
binary_text += binary_char
return binary_text
def split_blocks(plaintext):
blocks = []
while len(plaintext) > 0:
blocks.append(plaintext[:8])
plaintext = plaintext[8:]
return blocks
def ascii_to_binary_key(key):
binary_key = “”
for char in key:
binary_key += format(ord(char), ‘08b’)
return binary_key
def apply_key_permutation(binary_key, permutation_table):
permuted_key = “”
for index in permutation_table:
permuted_key += binary_key[index - 1]
return permuted_key
def generate_subkeys(key):
pc_1_table = [57, 49, 41, 33, 25, 17, 9,
1, 58, 50, 42, 34, 26, 18,
10, 2, 59, 51, 43, 35, 27,
19, 11, 3, 60, 52, 44, 36,
63, 55, 47, 39, 31, 23, 15,
7, 62, 54, 46, 38, 30, 22,
14, 6, 61, 53, 45, 37, 29,
21, 13, 5, 28, 20, 12, 4]
pc_2_table = [14, 17, 11, 24, 1, 5,
3, 28, 15, 6, 21, 10,
23, 19, 12, 4, 26, 8,
16, 7, 27, 20, 13, 2,
41, 52, 31, 37, 47, 55,
30, 40, 51, 45, 33, 48,
44, 49, 39, 56, 34, 53,
46, 42, 50, 36, 29, 32]
if len(key) != 8:
raise ValueError(“Key size must be 8 characters.”)
binary_key = ascii_to_binary_key(key)
permuted_key = apply_key_permutation(binary_key, pc_1_table)
# Convert key to numeric value
permuted_key = int(permuted_key, 2)
subkeys = []
# Generate subkeys for each round
for round in range(1, 17):
# Left shifts for left half and right half of the key
left_shifts = 1 if round in [1, 2, 9, 16] else 2
permuted_key = ((permuted_key << left_shifts) & 0xFFFFFFFFFFFF) | (permuted_key >> (28 - left_shifts))
# Use PC-2 table to convert the key to a 48-bit subkey
subkey = apply_key_permutation(bin(permuted_key)[2:].zfill(56), pc_2_table)
subkeys.append(subkey)
return subkeys
def initial_permutation(block):
# Perform initial permutation on the block
initial_permutation_table = [58, 50, 42, 34, 26, 18, 10, 2,
60, 52, 44, 36, 28, 20, 12, 4,
62, 54, 46, 38, 30, 22, 14, 6,
64, 56, 48, 40, 32, 24, 16, 8,
57, 49, 41, 33, 25, 17, 9, 1,
59, 51, 43, 35, 27, 19, 11, 3,
61, 53, 45, 37, 29, 21, 13, 5,
63, 55, 47, 39, 31, 23, 15, 7]
permuted_block = “”
for index in initial_permutation_table:
permuted_block += block[index - 1]
return permuted_block
def expand_permutation(block):
# Perform expansion permutation on the block
expansion_table = [32, 1, 2, 3, 4, 5, 4, 5,
6, 7, 8, 9, 8, 9, 10, 11,
12, 13, 12, 13, 14, 15, 16, 17,
16, 17, 18, 19, 20, 21, 20, 21,
22, 23, 24, 25, 24, 25, 26, 27,
28, 29, 28, 29, 30, 31, 32, 1]
expanded_block = “”
for index in expansion_table:
expanded_block += block[index - 1]
return expanded_block
def substitute(s_box_input, s_box_index):
s_boxes = [
# S1
[
[14, 4, 13, 1, 2, 15, 11, 8, 3, 10, 6, 12, 5, 9, 0, 7],
[0, 15, 7, 4, 14, 2, 13, 1, 10, 6, 12, 11, 9, 5, 3, 8],
[4, 1, 14, 8, 13, 6, 2, 11, 15, 12, 9, 7, 3, 10, 5, 0],
[15, 12, 8, 2, 4, 9, 1, 7, 5, 11, 3, 14, 10, 0, 6, 13]
]
]
row = int(s_box_input[0] + s_box_input[3], 2)
column = int(s_box_input[1:3], 2)
value = s_boxes[s_box_index][row][column]
return bin(value)[2:].zfill(4)
def encrypt(plaintext, key):
plaintext = pad_plaintext(plaintext)
binary_text = text_to_binary(plaintext)
blocks = split_blocks(binary_text)
subkeys = generate_subkeys(key)
encrypted_blocks = []
for block in blocks:
block = initial_permutation(block)
left_half = block[:32]
right_half = block[32:]
for round in range(1, 17):
previous_left_half = left_half
# Expansion permutation
right_expanded = expand_permutation(right_half)
# XOR with round subkey
subkey = subkeys[round - 1]
right_expanded = bin(int(right_expanded, 2) ^ int(subkey, 2))[2:].zfill(48)
# S-box substitution
s_box_input = “”
for i in range(0, 48, 6):
s_box_input += substitute(right_expanded[i:i+6], i//6)
# Permutation
permutation_table = [16, 7, 20, 21, 29, 12, 28, 17,
1, 15, 23, 26, 5, 18, 31, 10,
2, 8, 24, 14, 32, 27, 3, 9,
19, 13, 30, 6, 22, 11, 4, 25]
right_half = apply_key_permutation(s_box_input, permutation_table)
# XOR with previous left half
right_half = bin(int(right_half, 2) ^ int(previous_left_half, 2))[2:].zfill(32)
# Swap left and right halves
left_half, right_half = right_half, left_half
# Final permutation
encrypted_block = apply_key_permutation(right_half + left_half, initial_permutation_table)
encrypted_blocks.append(encrypted_block)error string out of range بعد اضافه if len(block) <32 block =block. Zfill (32)
|
2a5d76f42719b534a7f5af4918a0e625
|
{
"intermediate": 0.2808162569999695,
"beginner": 0.5485007166862488,
"expert": 0.1706831306219101
}
|
33,299
|
current_month = driver.find_element(By.CLASS_NAME,'monthselect').text
current_year = driver.find_element(By.CLASS_NAME,'yearselect').text
This code produces the lists of all available months and years in calendar. But I need to have only the selected month and year in that variables
|
d7af720d1c40fd8f7d588ffade661d7f
|
{
"intermediate": 0.2984754741191864,
"beginner": 0.4230296313762665,
"expert": 0.2784949243068695
}
|
33,300
|
import json
import numpy as np
from tensorflow.keras.models import load_model
from collections import Counter, defaultdict
import plotly.graph_objs as go
# Функция для чтения данных и подсчета встречаемости пользователей
def load_data(filename):
user_counter = Counter()
data_by_user = defaultdict(list)
with open(filename, 'r', encoding='utf-8') as file:
for line in file:
event = json.loads(line)
user = event['SourceHostname_User']
user_counter[user] += 1
data_by_user[user].append([event['EventId'], event['ThreadId'], event['Image']])
return user_counter, data_by_user
model = load_model('neural_network_model.h5')
filename = '1.jsonl'
sequence_length = 100
user_counter, data_by_user = load_data(filename)
top_users = [user for user, _ in user_counter.most_common(20)]
predictions = defaultdict(list)
for user in top_users:
events = data_by_user[user]
for i in range(len(events) - sequence_length + 1):
sequence = np.array(events[i:i + sequence_length])
sequence = sequence.reshape((1, sequence_length, -1))
pred = model.predict(sequence)
predictions[user].extend(pred)
def plot_top_predictions(predictions, top_users):
fig = go.Figure()
for user in top_users:
preds = np.array(predictions[user])
if len(preds) == 0:
continue
y = np.argmax(preds, axis=1)
x = np.arange(len(y))
fig.add_trace(go.Scatter(x=x, y=y, mode='lines', name=user))
fig.update_layout(
title='Top 20 User Predictions',
xaxis_title='Prediction Number',
yaxis_title='Predicted Class',
hovermode='x unified'
)
fig.update_xaxes(rangeslider_visible=True, rangeselector=dict(
buttons=list([
dict(count=1, label='1m', step='minute', stepmode='backward'),
dict(count=6, label='6h', step='hour', stepmode='todate'),
dict(step='all')
])
))
fig.update_yaxes(fixedrange=False)
fig.show()
plot_top_predictions(predictions, top_users) переделай только под Director , director\\TestoedovNA ,ISS-RESHETNEV\\PjetrovPA n743879.iss-reshetnev.ru n764371.iss-reshetnev.ru
|
bc7d6859aed37427f32689c7ce9cd2f3
|
{
"intermediate": 0.4225699305534363,
"beginner": 0.36925268173217773,
"expert": 0.2081773728132248
}
|
33,301
|
How can I under "virt-manager" from a VM access the serial port of another vm ?
|
8ca815ec5b10a6e21357748bbf67ff0b
|
{
"intermediate": 0.42807525396347046,
"beginner": 0.2844283878803253,
"expert": 0.2874963879585266
}
|
33,302
|
;PROGRAM TITLE GOES HERE -- HANOI
;Solves tower of hanoi puzzle.Printout sequence of moves
;of N discs from initial spindle X to final spindle Z.
;using spindle Y for temporery storage
;
datarea segment ;define data segment
message1 db 'N=?',0ah,0dh,'$'
message2 db 'What is the name of spindle X ?'
db 0ah,0dh,'$'
message3 db 'What is the name of spindle Y ?'
db 0ah,0dh,'$'
message4 db 'What is the name of spindle Z ?'
db 0ah,0dh,'$'
flag dw 0
constant dw 10000,1000,100,10,1
datarea ends
;*****************************************************
prognam segment ;define code segment
;-----------------------------------------------------
main proc far
assume cs:prognam, ds:datarea
start:
;set up stack for return
push ds
sub ax,ax
push ax
;set DS register to current data segment
mov ax,datarea
mov ds,ax
;main part of program goes here
lea dx,message1 ;N=7?
mov ah,09h
int 21h
call decibin ;read N into BX
call crlf
cmp bx,0 ;if N=0
jz exit ;exit
lea dx,message2 ;X=?
mov ah,09h
int 21h
mov ah,01h ;read X's name into CX
int 21h
mov ah,0
mov cx,ax
call crlf
lea dx,message3 ;Y=?
mov ah,09h
int 21h
mov ah,01h ;read Y'name into SI
int 21h
mov ah,0
mov si,ax
call crlf
lea dx,message4 ;Z=?
mov ah,09h
int 21h
mov ah,01h ;read Z's name into DI
int 21h
mov ah,0
mov di,ax
call crlf
call hanoi ;call HANOI(N,X,Y,Z)
exit: ret ;return to DOS
main endp
;---------------------------------------------------
hanoi proc near ;define subprocedure
;SOlves tower of hanoi puzzle
;Argement :(BX)=N,(CX)=X,(SI)=Y,(DI)=Z.
cmp bx,1 ;if N=1,execute basis
je basis
call save ;save N,X,Y,Z
dec bx
xchg si,di
call hanoi ;call HANOI(N-1,X,Z,Y)
call restor ;restore N,X,Y,Z
call print ;print XNZ
dec bx
xchg cx,si
call hanoi ;call HANOI(N-1,Y,X,Z)
jmp return
basis: call print ;print X1Z
return: ret ;return
hanoi endp ;end subprocedure
;-------------------------------------------------------
print proc near
mov dx,cx ;print X
mov ah,02h
int 21h
call binidec ;print N
mov dx,di ;print Z
mov ah,02h
int 21h
call crlf ;skip to next line
ret
print endp
;-----------------------------------------------------------
save proc near
pop bp
push bx
push cx
push si
push di
push bp
ret
save endp
;-----------------------------------------------------------
restor proc near
pop bp
pop di
pop si
pop cx
pop bx
push bp
ret
restor endp
;------------------------------------------------------------
decibin proc near
;prodecure to convert decimal on keyboard to binary.
;result is left in BX register
mov bx,0
;get digit from keyboard ,convert to binary
newchar:
mov ah,1 ;keyboard input
int 21h ;call DOS
sub al,30h ;ASCII to binary
jl exit1 ;jump if<0
cmp al,9d ;is it >9d?
jg exit1 ;yes,not dec digit
cbw ;BYTE in AL to WORD in AX
;(digit is now in AX)
;multiply number in BX by 10 decimal
xchg ax,bx ;trade digit&number
mov cx,10d ;put 10 dec in CX
mul cx ;number times 10
xchg ax,bx ;trade number &digit
;add digit in AX to number in BX
add bx,ax ;add digit to number
jmp newchar ;get next digit
exit1: ret ;return from decibin
decibin endp ;end of decibin proc
;------------------------------------------------------------
binidec proc near
;procedure to convert binary number in BX to decimal
;on console screen
push bx
push cx
push si
push di
mov flag,0
mov cx,5
lea si,constant
dec_div:
mov ax,bx ;number high half
mov dx,0 ;zero out low half
div word ptr[si] ;divide by contant
mov bx,dx ;reminder into BX
mov dl,al ;quotient into DL
cmp flag,0 ;have not leading zero
jnz print1
cmp dl,0
je skip
mov flag,1
;print the contents of DL on screen
print1: add dl,30h ;convert to ASCII
mov ah,02h ;display fuction
int 21h ;call DOS
skip: add si,2
loop dec_div
pop di
pop si
pop cx
pop bx
ret ;return from dec_div
binidec endp
;-------------------------------------------------------------
crlf proc near
mov dl,0ah ;linefeed
mov ah,02h ;display function
int 21h
;
mov dl,0dh ;carriage return
mov ah,02h ;display function
int 21h
;
ret
crlf endp
;-----------------------------------------------------------
prognam ends ;end of code segment
;*************************************************************
end start ;end assembly
|
7399602df0fd0525e780778ab9d1a31a
|
{
"intermediate": 0.358176589012146,
"beginner": 0.393733412027359,
"expert": 0.2480899691581726
}
|
33,303
|
как сделать, чтобы мой запрос getOperationStatus попал на проверку checkSign
private Boolean checkSign(CachedBodyHttpServletRequest request, ServletResponse servletResponse) throws IOException {
String requestContent = new String(ByteStreams.toByteArray(request.getInputStream()), StandardCharsets.UTF_8);
return checkSignForContent(requestContent, request, servletResponse);
}
@RestController
@RequestMapping(value = {"/orders"})
@Slf4j
public class OrderController {
private static final String PROCESSING_UUID = "Processing-UUID";
private final C2BSBPService c2BSBPService;
public OrderController(C2BSBPService c2BSBPService) {
this.c2BSBPService = c2BSBPService;
}
@PostMapping(value = "")
@ResponseBody
public ResultToPartner addOrder(@RequestBody OrderRqDto orderRqDto, @RequestHeader(name = "X-Partner-Id") String partnerId, HttpServletRequest request) {
return c2BSBPService.addOrder(orderRqDto, Long.parseLong(partnerId), (String) request.getAttribute(PROCESSING_UUID));
}
@GetMapping (value = "/{id}")
@ResponseBody
public ResultToPartner getOperationStatus(@PathVariable("id") Long id, @RequestHeader(name = "X-Partner-Id") String partnerId, HttpServletRequest request,
@RequestHeader(name = "X-Signature") String signature) {
return c2BSBPService.getOperationState(id);
}
}
|
c2819a96404470c3d2121c6e9790ee11
|
{
"intermediate": 0.38333913683891296,
"beginner": 0.4566159248352051,
"expert": 0.16004487872123718
}
|
33,304
|
;PROGRAM TITLE GOES HERE -- HANOI
;Solves tower of hanoi puzzle.Printout sequence of moves
;of N discs from initial spindle X to final spindle Z.
;using spindle Y for temporery storage
;
datarea segment ;define data segment
message1 db 'N=?',0ah,0dh,'$'
message2 db 'What is the name of spindle X ?'
db 0ah,0dh,'$'
message3 db 'What is the name of spindle Y ?'
db 0ah,0dh,'$'
message4 db 'What is the name of spindle Z ?'
db 0ah,0dh,'$'
flag dw 0
constant dw 10000,1000,100,10,1
datarea ends
;*****************************************************
prognam segment ;define code segment
;-----------------------------------------------------
main proc far
assume cs:prognam, ds:datarea
start:
;set up stack for return
push ds
sub ax,ax
push ax
;set DS register to current data segment
mov ax,datarea
mov ds,ax
;main part of program goes here
lea dx,message1 ;N=7?
mov ah,09h
int 21h
call decibin ;read N into BX
call crlf
cmp bx,0 ;if N=0
jz exit ;exit
lea dx,message2 ;X=?
mov ah,09h
int 21h
mov ah,01h ;read X's name into CX
int 21h
mov ah,0
mov cx,ax
call crlf
lea dx,message3 ;Y=?
mov ah,09h
int 21h
mov ah,01h ;read Y'name into SI
int 21h
mov ah,0
mov si,ax
call crlf
lea dx,message4 ;Z=?
mov ah,09h
int 21h
mov ah,01h ;read Z's name into DI
int 21h
mov ah,0
mov di,ax
call crlf
call hanoi ;call HANOI(N,X,Y,Z)
exit: ret ;return to DOS
main endp
;---------------------------------------------------
hanoi proc near ;define subprocedure
;SOlves tower of hanoi puzzle
;Argement :(BX)=N,(CX)=X,(SI)=Y,(DI)=Z.
cmp bx,1 ;if N=1,execute basis
je basis
call save ;save N,X,Y,Z
dec bx
xchg si,di
call hanoi ;call HANOI(N-1,X,Z,Y)
call restor ;restore N,X,Y,Z
call print ;print XNZ
dec bx
xchg cx,si
call hanoi ;call HANOI(N-1,Y,X,Z)
jmp return
basis: call print ;print X1Z
return: ret ;return
hanoi endp ;end subprocedure
;-------------------------------------------------------
print proc near
mov dx,cx ;print X
mov ah,02h
int 21h
call binidec ;print N
mov dx,di ;print Z
mov ah,02h
int 21h
call crlf ;skip to next line
ret
print endp
;-----------------------------------------------------------
save proc near
pop bp
push bx
push cx
push si
push di
push bp
ret
save endp
;-----------------------------------------------------------
restor proc near
pop bp
pop di
pop si
pop cx
pop bx
push bp
ret
restor endp
;------------------------------------------------------------
decibin proc near
;prodecure to convert decimal on keyboard to binary.
;result is left in BX register
mov bx,0
;get digit from keyboard ,convert to binary
newchar:
mov ah,1 ;keyboard input
int 21h ;call DOS
sub al,30h ;ASCII to binary
jl exit1 ;jump if<0
cmp al,9d ;is it >9d?
jg exit1 ;yes,not dec digit
cbw ;BYTE in AL to WORD in AX
;(digit is now in AX)
;multiply number in BX by 10 decimal
xchg ax,bx ;trade digit&number
mov cx,10d ;put 10 dec in CX
mul cx ;number times 10
xchg ax,bx ;trade number &digit
;add digit in AX to number in BX
add bx,ax ;add digit to number
jmp newchar ;get next digit
exit1: ret ;return from decibin
decibin endp ;end of decibin proc
;------------------------------------------------------------
binidec proc near
;procedure to convert binary number in BX to decimal
;on console screen
push bx
push cx
push si
push di
mov flag,0
mov cx,5
lea si,constant
dec_div:
mov ax,bx ;number high half
mov dx,0 ;zero out low half
div word ptr[si] ;divide by contant
mov bx,dx ;reminder into BX
mov dl,al ;quotient into DL
cmp flag,0 ;have not leading zero
jnz print1
cmp dl,0
je skip
mov flag,1
;print the contents of DL on screen
print1: add dl,30h ;convert to ASCII
mov ah,02h ;display fuction
int 21h ;call DOS
skip: add si,2
loop dec_div
pop di
pop si
pop cx
pop bx
ret ;return from dec_div
binidec endp
;-------------------------------------------------------------
crlf proc near
mov dl,0ah ;linefeed
mov ah,02h ;display function
int 21h
;
mov dl,0dh ;carriage return
mov ah,02h ;display function
int 21h
;
ret
crlf endp
;-----------------------------------------------------------
prognam ends ;end of code segment
;*************************************************************
end start ;end assembly
请对上述代码进行修改，使其能从INPUT.TXT中读取输入数据（盘子数 起始轴 中间轴 最终轴），并将所有输出结果重定向到OUTPUT.TXT。提示：使用子程序负责输入和输出，如果命令行上有输入文件名和输出文件名参数，则输入输出都针对文件进行。
|
e06726a13efa71e058fedbd91e348dbb
|
{
"intermediate": 0.358176589012146,
"beginner": 0.393733412027359,
"expert": 0.2480899691581726
}
|
33,305
|
(String.IsNullOrEmpty(imagePath)
как сделать чтобы вместо imagePath была ссылка на картинку
этот файл находится в debug/scripts/getprice.cs
а картинка в debug/imagecontainer/price.jpg
|
637493ced1d3b1acdaec7ad39ea85e42
|
{
"intermediate": 0.515320897102356,
"beginner": 0.2904878258705139,
"expert": 0.19419130682945251
}
|
33,306
|
C# show window over fullscreen games
|
9737adc4bd38df79054ab83b1698795c
|
{
"intermediate": 0.4071568548679352,
"beginner": 0.37341707944869995,
"expert": 0.21942603588104248
}
|
33,307
|
in ggplot(Tc_Carotte_mlf, aes(x = Test_Jour_Croissance, y = CFU_g,fill = Bacterie)) +
geom_boxplot() + # stat_compare_means(aes(group = Bacterie), label = "p")+
labs(title ="Comparaison CFU/g pour Carotte", x = "Test", y = "CFU_g") +
scale_fill_manual(values = couleurs_bacterie, guide = guide_legend(title = "Bacterie")) +
theme_minimal() +
scale_y_log10(limits = c(10^0, 10^7), breaks = 10^(0:7))
how add NA values
|
e72df52366e53f947a73d8ba454caf6d
|
{
"intermediate": 0.29639342427253723,
"beginner": 0.2647167444229126,
"expert": 0.43888983130455017
}
|
33,308
|
def pad_plaintext(plaintext):
while len(plaintext) < 8:
plaintext += "@"
return plaintext[:8]
def text_to_binary(text):
binary_text = ""
for char in text:
binary_char = bin(ord(char))[2:].zfill(8)
binary_text += binary_char
return binary_text
def split_blocks(plaintext):
blocks = []
while len(plaintext) > 0:
blocks.append(plaintext[:8])
plaintext = plaintext[8:]
return blocks
def ascii_to_binary_key(key):
binary_key = ""
for char in key:
binary_key += format(ord(char), '08b')
return binary_key
def apply_key_permutation(binary_key, permutation_table):
permuted_key = ""
for index in permutation_table:
permuted_key += binary_key[index - 1]
return permuted_key
def generate_subkeys(key):
pc_1_table = [57, 49, 41, 33, 25, 17, 9,
1, 58, 50, 42, 34, 26, 18,
10, 2, 59, 51, 43, 35, 27,
19, 11, 3, 60, 52, 44, 36,
63, 55, 47, 39, 31, 23, 15,
7, 62, 54, 46, 38, 30, 22,
14, 6, 61, 53, 45, 37, 29,
21, 13, 5, 28, 20, 12, 4]
pc_2_table = [14, 17, 11, 24, 1, 5,
3, 28, 15, 6, 21, 10,
23, 19, 12, 4, 26, 8,
16, 7, 27, 20, 13, 2,
41, 52, 31, 37, 47, 55,
30, 40, 51, 45, 33, 48,
44, 49, 39, 56, 34, 53,
46, 42, 50, 36, 29, 32]
if len(key) != 8:
raise ValueError("Key size must be 8 characters.")
binary_key = ascii_to_binary_key(key)
permuted_key = apply_key_permutation(binary_key, pc_1_table)
# Convert key to numeric value
permuted_key = int(permuted_key, 2)
subkeys = []
# Generate subkeys for each round
for round in range(1, 17):
# Left shifts for left half and right half of the key
left_shifts = 1 if round in [1, 2, 9, 16] else 2
permuted_key = ((permuted_key << left_shifts) & 0xFFFFFFFFFFFF) | (
permuted_key >> (28 - left_shifts))
# Use PC-2 table to convert the key to a 48-bit subkey
subkey = apply_key_permutation(
bin(permuted_key)[2:].zfill(56), pc_2_table)
subkeys.append(subkey)
return subkeys
initia_lpermutation_table= [58, 50, 42, 34, 26, 18, 10, 2,
60, 52, 44, 36, 28, 20, 12, 4,
62, 54, 46, 38, 30, 22, 14, 6,
64, 56, 48, 40, 32, 24, 16, 8,
57, 49, 41, 33, 25, 17, 9, 1,
59, 51, 43, 35, 27, 19, 11, 3,
61, 53, 45, 37, 29, 21, 13, 5,
63, 55, 47, 39, 31, 23, 15, 7]
def initial_permutation(block):
# Perform initial permutation on the block
if len(block)<64:
block = block.zfill(64)
permuted_block = ""
for index in initia_lpermutation_table:
permuted_block += block[index - 1]
return permuted_block
# Perform expansion permutation on the block
expansion_table = [32, 1, 2, 3, 4, 5, 4, 5,
6, 7, 8, 9, 8, 9, 10, 11,
12, 13, 12, 13, 14, 15, 16, 17,
16, 17, 18, 19, 20, 21, 20, 21,
22, 23, 24, 25, 24, 25, 26, 27,
28, 29, 28, 29, 30, 31, 32, 1]
def expand_permutation(block):
expanded_block=""
for index in expansion_table:
expanded_block += block[index - 1]
return expanded_block
def substitute(s_box_input, s_box_index):
s_boxes = [
# S1
[
[14, 4, 13, 1, 2, 15, 11, 8, 3, 10, 6, 12, 5, 9, 0, 7],
[0, 15, 7, 4, 14, 2, 13, 1, 10, 6, 12, 11, 9, 5, 3, 8],
[4, 1, 14, 8, 13, 6, 2, 11, 15, 12, 9, 7, 3, 10, 5, 0],
[15, 12, 8, 2, 4, 9, 1, 7, 5, 11, 3, 14, 10, 0, 6, 13]
]
]
row = int(s_box_input[0] + s_box_input[3], 2)
column = int(s_box_input[1:3], 2)
value = s_boxes[s_box_index][row][column]
return bin(value)[2:].zfill(4)
def encrypt(plaintext, key):
plaintext = pad_plaintext(plaintext)
binary_text = text_to_binary(plaintext)
blocks = split_blocks(binary_text)
subkeys = generate_subkeys(key)
encrypted_blocks = []
for block in blocks:
block = initial_permutation(block)
if len(block)<32:
block = block.zfill(32)
left_half = block[:32]
right_half = block[32:]
for round in range(1, 17):
previous_left_half = left_half
# Expansion permutation
right_expanded = expand_permutation(right_half)
# XOR with round subkey
subkey = subkeys[round - 1]
right_expanded = bin(int(right_expanded, 2) ^
int(subkey, 2))[2:].zfill(48)
# S-box substitution
s_box_input = ""
for i in range(0, 48, 6):
s_box_input += substitute(right_expanded[i:i+6], i//6)
# Permutation
permutation_table = [16, 7, 20, 21, 29, 12, 28, 17,
1, 15, 23, 26, 5, 18, 31, 10,
2, 8, 24, 14, 32, 27, 3, 9,
19, 13, 30, 6, 22, 11, 4, 25]
right_half = apply_key_permutation(s_box_input, permutation_table)
# XOR with previous left half
right_half = bin(int(right_half, 2) ^ int(
previous_left_half, 2))[2:].zfill(32)
# Swap left and right halves
left_half, right_half = right_half, left_half
# Final permutation
encrypted_block = apply_key_permutation(
right_half+left_half,initia_lpermutation_table)
encrypted_blocks.append(encrypted_block)
encrypted_text = ""
for block in encrypted_blocks:
for i in range(0, 8, 8):
encrypted_text += chr(int(block[i:i+8], 2))
return encrypted_text
# Take user input for plaintext and key
plaintext = input("Enter the plaintext: ")
key = input("Enter the key (8 characters): ")
# Encrypt the plaintext using the key
encrypted_text = encrypt(plaintext, key)
# Print the encrypted text
print("Encrypted Text:", encrypted_text)
binary_text = text_to_binary(plaintext)
blocks = split_blocks(binary_text)
subkeys = generate_subkeys(key)
encrypted_blocks = []
for block in blocks:
block = initial_permutation(block)
left_half = block[:32]
right_half = block[32:]
for round in range(1, 17):
previous_left_half = left_half
# Expansion permutation
right_expanded = expand_permutation(right_half)
# XOR with round subkey
subkey = subkeys[round - 1]
right_expanded = bin(int(right_expanded, 2) ^
int(subkey, 2))[2:].zfill(48)
# S-box substitution
s_box_input = ""
for i in range(0, 48, 6):
s_box_input += substitute(right_expanded[i:i+6], i//6)
# Permutation
permutation_table = [16, 7, 20, 21, 29, 12, 28, 17,
1, 15, 23, 26, 5, 18, 31, 10,
2, 8, 24, 14, 32, 27, 3, 9,
19, 13, 30, 6, 22, 11, 4, 25]
right_half = apply_key_permutation(s_box_input, permutation_table)
# XOR with previous left half
right_half = bin(int(right_half, 2) ^ int(
previous_left_half, 2))[2:].zfill(32)
# Swap left and right halves
left_half, right_half = right_half, left_half
# Final permutation
encrypted_block = apply_key_permutation(right_half + left_half, initia_lpermutation_table)
encrypted_blocks.append(encrypted_block)error value =s_boxes [s_box_index] [row] [column] error list index out of range
|
be9e6df8c804e4ebc5b4a788c2e46f12
|
{
"intermediate": 0.3371845483779907,
"beginner": 0.4498818516731262,
"expert": 0.21293359994888306
}
|
33,309
|
in a gdb rsp connection ,how openocd let gdb quit
|
c1e82cf6f679f9329d5c62400b68d33c
|
{
"intermediate": 0.6032066345214844,
"beginner": 0.15165798366069794,
"expert": 0.2451353371143341
}
|
33,310
|
i have an ATmega16, a simple 4x4 keypad and a 16x2 LCD character.
my keypad is like this one:
{
'7', '8', '9', '/',
'4', '5', '6', '*',
'1', '2', '3', '-',
'reset', '0', '=', '+',
}
i want to use alcd.h library and write the program inside codevision avr enviorment using c language.
i initialized my LCD and connected to A ports of atmega16.
and also connected keypad to D ports of atmega16.
i want to write the program when user hits every button on keypad, that character prints on LCD character.
with the eddition of one thing: when user just press '0', '0' should be displayed on LCD but if he keeps the button down and doesnt release it for more than 2000ms,'.' should be displayed on LCD.
|
6201af03f11ecdeb2d19fe853f8bbef3
|
{
"intermediate": 0.5089640617370605,
"beginner": 0.21236677467823029,
"expert": 0.278669148683548
}
|
33,311
|
pairs(pca_scores$x, xlim=c(-3, 3), ylim=c(-3, 3), col=rainbow(6), pch=9) Error in pca_scores$x : $ operator is invalid for atomic vectors
|
a51f93eb73824ab28dea59a410b80543
|
{
"intermediate": 0.38630756735801697,
"beginner": 0.307656466960907,
"expert": 0.30603599548339844
}
|
33,312
|
home assistant template card making
|
65d4e96cc4180e2ea3418ed4d85ed366
|
{
"intermediate": 0.3361682891845703,
"beginner": 0.41090402007102966,
"expert": 0.2529277205467224
}
|
33,313
|
python get camelcase from snakecase
|
ae63d0bee99d95c50a8111c402d22593
|
{
"intermediate": 0.34362444281578064,
"beginner": 0.33903300762176514,
"expert": 0.3173425793647766
}
|
33,315
|
free bytecode noo-coding editor
|
3167370764fa7aab60be41d766072cdd
|
{
"intermediate": 0.23314028978347778,
"beginner": 0.33218586444854736,
"expert": 0.43467384576797485
}
|
33,316
|
pairs(pca_scores, xlim=c(-3, 3), ylim=c(-3, 3), col=rainbow(6), pch=9) 为什么画出来是空的，pca_scores是个 num [1:56, 1:3]
|
4c447c3c28f5be98b3997415dd704b56
|
{
"intermediate": 0.3126660883426666,
"beginner": 0.29716727137565613,
"expert": 0.39016664028167725
}
|
33,317
|
The data.txt file is a 12625 x 56 matrix; each column (row) of the matrix corresponds to the
individual case (gene).
Among the 56 cases,
Columns 1~20: pulmonary carcinoid samples (Carcinoid);
Columns 21~33: colon cancer metastasis samples (Colon);
Columns 34~50: normal lung samples (Normal);
Columns 51~56: small cell carcinoma samples (SmallCell). We applied PCA to the transposed matrix to extract the first three principal components. Perform K-means and hierarchical clustering analyses using the first three principal components.怎么理解Perform K-means and hierarchical clustering analyses using the first three principal components，请展示k-means的代码
|
6721fe8cdb628d83af2037432dbb8e34
|
{
"intermediate": 0.32485702633857727,
"beginner": 0.2391621470451355,
"expert": 0.43598082661628723
}
|
33,318
|
help me also make so it works on slight rotation on the picture:
import cv2 as cv
import numpy as np
from matplotlib import pyplot as plt
img = cv.imread("photo (3).jpg", cv.IMREAD_GRAYSCALE)
assert img is not None, "file could not be read, check with os.path.exists()"
img2 = img.copy()
template = cv.imread("namn1.png", cv.IMREAD_GRAYSCALE)
assert template is not None, "file could not be read, check with os.path.exists()"
w, h = template.shape[::-1]
# All the 6 methods for comparison in a list
methods = [
"cv.TM_CCOEFF",
"cv.TM_CCOEFF_NORMED",
"cv.TM_CCORR",
"cv.TM_CCORR_NORMED",
"cv.TM_SQDIFF",
"cv.TM_SQDIFF_NORMED",
]
for meth in methods:
img = img2.copy()
method = eval(meth)
# Apply template Matching
res = cv.matchTemplate(img, template, method)
min_val, max_val, min_loc, max_loc = cv.minMaxLoc(res)
# If the method is TM_SQDIFF or TM_SQDIFF_NORMED, take minimum
if method in [cv.TM_SQDIFF, cv.TM_SQDIFF_NORMED]:
top_left = min_loc
else:
top_left = max_loc
bottom_right = (top_left[0] + w, top_left[1] + h)
cv.rectangle(img, top_left, bottom_right, 255, 2)
plt.subplot(121), plt.imshow(res, cmap="gray")
plt.title("Matching Result"), plt.xticks([]), plt.yticks([])
plt.subplot(122), plt.imshow(img, cmap="gray")
plt.title("Detected Point"), plt.xticks([]), plt.yticks([])
plt.suptitle(meth)
plt.show()
|
2dad023372fd870e82c66b8a98c049db
|
{
"intermediate": 0.4851396679878235,
"beginner": 0.2847941517829895,
"expert": 0.23006610572338104
}
|
33,319
|
Как перевести десятичное отрицательное число в шестнадцатеричную систему счисления?с++
#include <iostream>
#include <vector>
#include <array>
using namespace std;
void code_sh(int n){
vector<string> str={"A","B","C","D","E","F"};
vector<string> ch={"10","11","12","13","14","15"};
vector<string> numbers;
int s,o,d;
s=n<0 ? -n : n;
d=s;
while(d>1){
o=d%16;
d=d/16;
string strNum=to_string(o);
numbers.push_back(strNum);
}
string strNum1=to_string(d);
numbers.push_back(strNum1);
if(n<0){
cout<<"-";
for (int j=0;j<numbers.size();j++){
for (int g=0;g<6;g++){
numbers[j]= numbers[j]== ch[g]? str[g] : numbers[j];
}
}
}
else{
for (int j=0;j<numbers.size();j++){
for (int g=0;g<6;g++){
numbers[j]= numbers[j]== ch[g]? str[g] : numbers[j];
}
}
}
for(int i=numbers.size()-1 ;i>=0;i--){
numbers[i]=numbers[i]=="0" ? "" : numbers[i];
cout<<numbers[i];
}
}
int main(){
int n;
cin>>n;
code_sh(n);
}
вот мой код. только сейчас поняв, что нужно было не просто подставить - в начале...
в общем, не совсем понимаю как правильно можно преобразовать. возможно обойтись без инвертации и присваивании единицы?
|
7158d68c6a33b10f3284fe45bad263b7
|
{
"intermediate": 0.44452494382858276,
"beginner": 0.4227984547615051,
"expert": 0.13267658650875092
}
|
33,320
|
Проверь что не так в моём шейдере, почему _MainTex отрисовывется чёрно-белой? И почему свет падает не правильно. Исправь все недочеты
Shader "Custom/SimpleTangentSpaceLighting"
{
Properties
{
_MainTex("Albedo", 2D) = "white" {}
_NormalTex("Normal Map", 2D) = "bump" {}
}
SubShader
{
Pass
{
Tags{ "LightMode" = "ForwardBase" }
CGPROGRAM
#pragma vertex vert
#pragma fragment frag
#include "UnityCG.cginc"
#include "Lighting.cginc"
#pragma multi_compile_fwdbase nolightmap nodirlightmap nodynlightmap novertexlight
#include "AutoLight.cginc"
struct appdata
{
float4 vertex : POSITION;
float3 normal : NORMAL;
float4 tangent : TANGENT;
float2 uv : TEXCOORD0;
float2 uv2 : TEXCOORD1;
};
struct v2f
{
float4 vertex : SV_POSITION;
float2 uv : TEXCOORD0;
float2 uv2 : TEXCOORD1;
float3 tangentSpaceLight : TEXCOORDn1;
};
sampler2D _MainTex;
float4 _MainTex_ST;
sampler2D _NormalTex;
v2f vert(appdata v)
{
v2f o;
o.vertex = UnityObjectToClipPos(v.vertex);
o.uv = TRANSFORM_TEX(v.uv, _MainTex);
float3 normal = UnityObjectToWorldNormal(v.normal);
float3 tangent = UnityObjectToWorldNormal(v.tangent);
float3 bitangent = cross(tangent, normal);
o.tangentSpaceLight = float3(dot(tangent, _WorldSpaceLightPos0), dot(bitangent, _WorldSpaceLightPos0), dot(normal, _WorldSpaceLightPos0));
return o;
}
fixed4 frag(v2f i) : SV_Target
{
float3 col = tex2D(_MainTex, i.uv);
float3 tangentNormal = tex2D(_NormalTex, i.uv) * 2 - 1;
return dot(tangentNormal, i.tangentSpaceLight * col);
}
ENDCG
}
}
}
|
dc3d2c317b98bde3603ce6d2260d5699
|
{
"intermediate": 0.32938656210899353,
"beginner": 0.4383136034011841,
"expert": 0.23229987919330597
}
|
33,321
|
how to setup ngnix rtmp server that runs forever and can change video source from api
|
83816783650f4c1a7c8840e2f18098b4
|
{
"intermediate": 0.5556225776672363,
"beginner": 0.18247850239276886,
"expert": 0.2618989646434784
}
|
33,322
|
Assume the following co-training (multiview learning) self-training scenario: the positive class contains x 1 = [1 0] T and the negative class contains x 2 = [0 1] T . Assume that we first train a maximum margin classifier only based on the first feature of training vectors, then label the unlabeled vector x 3 = [2/3 1/3] T , and then train a maximum margin classifier based on the second feature of x 1 , x 2 , x 3 . Explain why the class asasociated with the point x 4 = [2 2] T is indeterminate if it is classified using a majority poll between the maximum margin classifier that uses the first feature and the maximum margin classifier that used the second feature for classification.
|
35abdb50a60132c2815d6cb97b665243
|
{
"intermediate": 0.22470177710056305,
"beginner": 0.1712343692779541,
"expert": 0.604063868522644
}
|
33,323
|
Need Pine code for RSI fast (value )and slow RSI (value) cross with color change fill. Take smoothening and Threshold factor as 1
|
b4c75a10162f069ffb6c9333a6711c25
|
{
"intermediate": 0.3383547067642212,
"beginner": 0.13788077235221863,
"expert": 0.5237645506858826
}
|
33,324
|
Required C++ classes to implement the Izhikevich model. Neurons created would be used to build a randomly connected network, so it must be possible to dynamiclly connect and disconnect a neuron from a neighbor, either as input or output. The implementation must include synaptic plasticity, with different types of synapses, axonal and dendritic delays, STDP, LTD, showing memory behavior. Use the model that you want, but must address stability issues under plasticity. Try to optimize the code as much as possible, and do not use the C++ STL, only code written from scratch. The goal is to simulate the nervous system of a primitive animale.
|
2c33be99108221f9f1605f08251d40ab
|
{
"intermediate": 0.09936594218015671,
"beginner": 0.17434285581111908,
"expert": 0.7262911796569824
}
|
33,325
|
Required C++ classes to implement the Izhikevich model. Neurons created would be used to build a randomly connected network, so it must be possible to dynamiclly connect and disconnect a neuron from a neighbor, either as input or output. The implementation must include synaptic plasticity, with different types of synapses, axonal and dendritic delays, STDP, LTD, showing memory behavior. Use the model that you want, but must address stability issues under plasticity. Try to optimize the code as much as possible. The goal is to simulate the nervous system of a primitive animale.
|
0ef958230e318dceebdd4aa7f94d283a
|
{
"intermediate": 0.1402813345193863,
"beginner": 0.13764744997024536,
"expert": 0.7220712304115295
}
|
33,326
|
Required C++ classes to implement the Izhikevich model. Neurons created would be used to build a randomly connected network, so it must be possible to dynamiclly connect and disconnect a neuron from a neighbor, either as input or output. The implementation must include synaptic plasticity, with different types of synapses, axonal and dendritic delays, STDP, LTD, showing memory behavior. Use the model that you want, but must address stability issues under plasticity. Try to optimize the code as much as possible. Write usable code, not only skeleton. It doesn’t need to be 100% completed, but as much as you can.
The goal is to simulate the nervous system of a primitive animale.
|
d185695ee88c675f3520a7ec74f6dc54
|
{
"intermediate": 0.08806933462619781,
"beginner": 0.13949228823184967,
"expert": 0.7724383473396301
}
|
33,327
|
Required C++ classes to implement the Izhikevich model. Neurons created would be used to build a randomly connected network, so it must be possible to dynamiclly connect and disconnect a neuron from a neighbor, either as input or output. The implementation must include synaptic plasticity, with different types of synapses, axonal and dendritic delays, STDP, LTD, showing memory behavior. Use the model that you want, but must address stability issues under plasticity. Try to optimize the code as much as possible. Write usable code, not only skeleton and no « holes » in the code.
The goal is to simulate the nervous system of a primitive animale.
|
696e4950fc470964435b25d3ff808fc5
|
{
"intermediate": 0.09867190569639206,
"beginner": 0.12995336949825287,
"expert": 0.7713747620582581
}
|
33,328
|
Required C++ classes to implement the Izhikevich model. Neurons created would be used to build a randomly connected network, so it must be possible to dynamiclly connect and disconnect a neuron from a neighbor, either as input or output. The implementation must include synaptic plasticity, with different types of synapses, axonal and dendritic delays, STDP, LTD. Use the model that you want, but must address stability issues under plasticity. Try to optimize the code as much as possible. Write usable code, not only skeleton.
The goal is to simulate the nervous system of a primitive animale.
|
55016d293313a90ca3279706d38b31d7
|
{
"intermediate": 0.11792676150798798,
"beginner": 0.16150616109371185,
"expert": 0.7205671072006226
}
|
33,329
|
C++ code to connect to a Tor's Hidden Service v3. The code must not use the official Tor client, but download the consensus, parse it, download hidden service descriptor, parse it and connect to the hidden service, re-implementing a simple version of the Tor's protocol. OpenSSL must be used for cryptography. The goal is to download files from my private server from an embedded platform which can't afford the full Tor client. Security is not an issue, neither than anonymity.
|
80178ed86fcf6c28b0c4695510791cfd
|
{
"intermediate": 0.5010915398597717,
"beginner": 0.2849331796169281,
"expert": 0.213975191116333
}
|
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