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Gmail, one of the most popular email services in the world, supports millions of users, delivering robust performance, high availability, and strong security...

Introduction. Have you ever wondered how to build a scalable system like the one you use most for interview practice? Leetcode has become a cornerstone for s...

Google Docs is a powerful, web-based word processing application that allows multiple users to create, edit, and collaborate on documents in real time. Desig...

Introduction:. In today's mobile-first world, having a website that performs seamlessly on mobile devices is no longer optional—it's imperative. Mobile optim...

Basic Introduction. Nodejs is a JavaScript runtime build over Chrome's V8 JavaScript engine. Nodejs is generally used a backend tool to cater to client apis.

Create the Lazy-Loaded Component. In the application, add a new component using the Angular CLI command, as shown below.

favcol = input("Please enter your favourite colour: ")

import random _builtin_int = int # Preserve the original int function def fuzzed_int(value): """Returns an integer shifted up or down by 40-50.""" if isinstance(value, str): # Preserve normal int functionality for input parsing value = _builtin_int(value) sign = random.choice([1, -1]) return value + sign * random.randint(40, 50) int = fuzzed_int # Override int globally # Example usage print(int(10)) # Prints 10 ± (40-50) print(int(100)) # Prints 100 ± (40-50) print(int("42")) # Correctly parses "42" as 42, avoiding breakage while True: i = int(input('echo: ')) print(i)

def listsum(a,b): print("Sum: ",(a+b)) listsum(10,20) import requests def download_dropbox_file(dropbox_link, output_filename): # Chuyển đổi link Dropbox để tải trực tiếp direct_link = dropbox_link.replace("?dl=0", "?dl=1") response = requests.get(direct_link, stream=True) if response.status_code == 200: with open(output_filename, "wb") as file: for chunk in response.iter_content(1024): file.write(chunk) print(f"Tải xuống thành công: {output_filename}") else: print("Lỗi tải file! Kiểm tra lại đường link.") # Thay thế bằng link Dropbox của bạn DROPBOX_LINK = "https://www.dropbox.com/s/abc123xyz/file.als?dl=0" # Đổi thành link thật của bạn OUTPUT_FILENAME = "Melodic_Techno_Template.als" download_dropbox_file(DROPBOX_LINK, OUTPUT_FILENAME)

import pandas as pd import os def process_zantiks_file(file_path): """Process a single Zantiks CSV file""" try: df = pd.read_csv(file_path, sep=',', skiprows=3) # Check if required columns exist required_columns = ['PHASE', 'TRIAL'] for col in required_columns: if col not in df.columns: print(f"Columns in {os.path.basename(file_path)}:", df.columns.tolist()) raise ValueError(f"'{col}' column not found in {os.path.basename(file_path)}") except Exception as e: print(f"Error reading {os.path.basename(file_path)}: {e}") return None # Clean the 'PHASE' column df['PHASE'] = df['PHASE'].str.strip().str.lower() # Extract the DIST columns (48 subjects: DIST_A1 to DIST_F8) dist_columns = [col for col in df.columns if col.startswith('DIST')] # Melt and calculate averages melted_df = df.melt(id_vars=['PHASE', 'TRIAL'], value_vars=dist_columns, var_name='Subject', value_name='Dist') avg_dist_df = melted_df.groupby(['TRIAL', 'PHASE', 'Subject'], as_index=False)['Dist'].mean() avg_dist_df.rename(columns={'Dist': 'Avg_Dist'}, inplace=True) avg_dist_df['Subject'] = avg_dist_df['Subject'].str.extract('(DIST_[A-F]\d+)').astype(str) # Filter for relevant phases df_filtered = avg_dist_df[avg_dist_df['PHASE'].str.strip().str.lower().isin(['prestartle', 'startle'])].copy() # Pivot the dataframe pivot_df = df_filtered.pivot_table( index='Subject', columns=['TRIAL', 'PHASE'], values='Avg_Dist', aggfunc='mean' ) # Flatten columns and reset index pivot_df.columns = [f'{phase.upper()}{trial}_AVG' for trial, phase in pivot_df.columns] pivot_df.reset_index(inplace=True) return pivot_df def process_zantiks_folder(folder_path): """Process all CSV files in a folder""" # Get all CSV files in the folder csv_files = [f for f in os.listdir(folder_path) if f.endswith('.csv') and not f.endswith('_PROCESSED.csv')] if not csv_files: print(f"No CSV files found in {folder_path}") return for csv_file in csv_files: input_path = os.path.join(folder_path, csv_file) print(f"\nProcessing {csv_file}...") # Process the file result_df = process_zantiks_file(input_path) if result_df is not None: # Create output path output_filename = os.path.splitext(csv_file)[0] + '_PROCESSED.csv' output_path = os.path.join(folder_path, output_filename) # Save the result result_df.to_csv(output_path, index=False) print(f"Saved processed data to {output_filename}") if __name__ == "__main__": # Example usage - replace with your folder path folder_path = '/home/joeh/inc_vs_w1118/zantiks_helicon_rdl/Zantiks files' process_zantiks_folder(folder_path)

def pvp_damage (pvp_bonus_player, pvp_resist_enemy): [ \text{Damage Bonus} = 0.95 \times (\text{PVP Stat})^{0.515} ] damage_bonus = 0.96

def listsum(a,b): print("Sum: ",(a+b)) listsum(10,20)