makeScanFromRFEfeatures.py

# This script:
#	-Makes the shell script to launch grid auc optimization on lphe cluster using the submit.py file
#	-Create new file for new series of scans from RFE optimized features 

model='MLP'

algoName = ['SAMME.R']#,'SAMME']
learningRate=[0.05,0.2,0.4,0.6,0.8]						# First scan
maxDepth=[3,6,9,12,20]
nTrees=[20,80,200,500,1000]

def notInOld(lr,learningRate,maxD,maxDepth,nT,nTrees): # Skip already computed points from past scans
	return not((lr in learningRate) & (maxD in maxDepth) & (nT in nTrees))
# To use:
# if notInOld(lr,learningRate,maxD,maxDepth,nT,nTrees)
#else:
#						print(f'learningRate: {lr}, maxDepth: {maxD}, nTrees:{nT}')										# Print the skipped measurement (already exist from previous run) 

if model =='BDT':
	i=1
	with open ('runScan.sh', 'w') as rsh:
		for algo in algoName:
			for lr in learningRate:
				for maxD in maxDepth:
					for nT in nTrees:
						 
						rsh.write(f'python3 submit.py -d {i}_scan "python3 MultiTrain.py \'{algo}\' {lr} {maxD} {nT}"\n') 	# Just he number of line in description to easily execute again if fail, write the command in the bash file
						i=i+1

sizeTab=[	[10],[10,10],[10,10,10],
			[50],[50,50],[50,50,50],
			[100],[100,100],[100,100,100],	
			[40,20,10],[60,30,15],[80,40,20]]
if model=='MLP':
	i=1
	with open ('runScan.sh', 'w') as rsh:
		for size in sizeTab:
			print(size)
			sizeText=""
			for element in size:
				sizeText+= str(element)
				sizeText+=','
			sizeText=sizeText[:-1] 		# Erase last ','
			rsh.write(f'python3 submit.py -d {i}_scan "python3 MultiTrain.py {sizeText}"\n' ) 	# Write the command in the bash file
			i=i+1