pukpr/ensemble.ps1

## ensemble.ps1
# The command you want to execute
$command = " .\eexp.exe 0.8"

# The name of the output file generated by the command
$generatedFileName = "lte_results.csv"
$generatedDataName = "dlod_compare.csv"

# The base name for the renamed output files
$baseFileName = "lte_results"
$baseDataName = "dlod_compare"

# Starting index for file numbering
$index = 1

# Define how many times to repeat the execution
$repeatCount = 15  # Change this to the desired count

for ($i = 0; $i -lt $repeatCount; $i++) {
    # Execute the command
    Invoke-Expression $command

    # Wait for the file to be created if necessary
  #  while (-not (Test-Path $generatedFileName)) {
  #      Start-Sleep -Milliseconds 100
  #  }

    # Construct the new file name
    $newFileName = $baseFileName + $index + ".csv"
    $newDataName = $baseDataName + $index + ".csv"

    # Rename or move the output file
    Move-Item $generatedFileName $newFileName
    Move-Item $generatedDataName $newDataName

    # Increment the file index for the next iteration
    $index++
}

# End of script

## ensemble_average.py
import pandas as pd
import numpy as np
import sys

def ensemble_average(prefix, file_count):
    # Initialize an empty DataFrame for the sum
    sum_df = None
    count = 0

    # Loop through each file and add to the sum
    for i in range(1, file_count + 1):
        filename = f"{prefix}{i}.csv"
        try:
            df = pd.read_csv(filename, header=None)
            if sum_df is None:
                sum_df = df
            else:
                sum_df += df
            count += 1
        except FileNotFoundError:
            print(f"File not found: {filename}")
            continue

    # Calculate the average
    avg_df = sum_df / count

    # Save the ensemble average to a new CSV file
    avg_df.to_csv(f"{prefix}.csv", header=False, index=False)

if __name__ == "__main__":
    if len(sys.argv) != 3:
        print("Usage: python ensemble_average.py [prefix] [file_count]")
        sys.exit(1)

    prefix = sys.argv[1]
    file_count = int(sys.argv[2])

    ensemble_average(prefix, file_count)
	# The command you want to execute
	$command = " .\eexp.exe 0.8"

	# The name of the output file generated by the command
	$generatedFileName = "lte_results.csv"
	$generatedDataName = "dlod_compare.csv"

	# The base name for the renamed output files
	$baseFileName = "lte_results"
	$baseDataName = "dlod_compare"

	# Starting index for file numbering
	$index = 1

	# Define how many times to repeat the execution
	$repeatCount = 15 # Change this to the desired count

	for ($i = 0; $i -lt $repeatCount; $i++) {
	# Execute the command
	Invoke-Expression $command

	# Wait for the file to be created if necessary
	# while (-not (Test-Path $generatedFileName)) {
	# Start-Sleep -Milliseconds 100
	# }

	# Construct the new file name
	$newFileName = $baseFileName + $index + ".csv"
	$newDataName = $baseDataName + $index + ".csv"

	# Rename or move the output file
	Move-Item $generatedFileName $newFileName
	Move-Item $generatedDataName $newDataName

	# Increment the file index for the next iteration
	$index++
	}

	# End of script
	import pandas as pd
	import numpy as np
	import sys

	def ensemble_average(prefix, file_count):
	# Initialize an empty DataFrame for the sum
	sum_df = None
	count = 0

	# Loop through each file and add to the sum
	for i in range(1, file_count + 1):
	filename = f"{prefix}{i}.csv"
	try:
	df = pd.read_csv(filename, header=None)
	if sum_df is None:
	sum_df = df
	else:
	sum_df += df
	count += 1
	except FileNotFoundError:
	print(f"File not found: {filename}")
	continue

	# Calculate the average
	avg_df = sum_df / count

	# Save the ensemble average to a new CSV file
	avg_df.to_csv(f"{prefix}.csv", header=False, index=False)

	if __name__ == "__main__":
	if len(sys.argv) != 3:
	print("Usage: python ensemble_average.py [prefix] [file_count]")
	sys.exit(1)

	prefix = sys.argv[1]
	file_count = int(sys.argv[2])

	ensemble_average(prefix, file_count)