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import pandas as pd
import argparse
def calculate_metrics(file_path, start_row, end_row):
# Read the Excel file
df = pd.read_excel(file_path)
# Select the rows within the given range (note: start_row and end_row are 1-based row numbers)
data = df.iloc[start_row-1:end_row]
# Calculate mean and standard deviation
epe_mean = data['middleburyH-epe'].mean()
epe_std = data['middleburyH-epe'].std()
d1_mean = data['middleburyH-d1'].mean()
d1_std = data['middleburyH-d1'].std()
# Print the results
print(f"middleburyH-epe Mean: {epe_mean:.2f}, Standard Deviation: {epe_std:.2f}")
print(f"middleburyH-d1 Mean: {d1_mean:.2f}, Standard Deviation: {d1_std:.2f}")
print(f"{epe_mean:.2f}+-{epe_std:.2f} {d1_mean:.2f}+-{d1_std:.2f}")
if __name__ == "__main__":
# Set up command-line arguments
parser = argparse.ArgumentParser(description="Calculate metrics for specified rows in an Excel file.")
parser.add_argument("file_path", type=str, help="Path to the Excel file")
parser.add_argument("start_row", type=int, help="Start row (1-based index)")
parser.add_argument("end_row", type=int, help="End row (1-based index)")
args = parser.parse_args()
# Call the function and pass the parameters
calculate_metrics(args.file_path, args.start_row, args.end_row)
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