paradiseo/eo/test/mpi/gen-xp.py
2012-10-05 18:11:18 -04:00

152 lines
4.8 KiB
Python

# -*- coding:utf-8 -*-
"""
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
Authors:
Benjamin Bouvier <benjamin.bouvier@gmail.com>
"""
import json
# Where will be saved the experiments?
EXPERIMENTS_FILENAME = "experiments.json"
# What will be the pattern for experiments filenames?
FILENAME_PATTERN = "%(prefix)s_%(distrib_name)s_%(size)s_%(packet_size)s_%(run)s.txt"
def input_number_at_least( min ):
n = min - 1
while n < min:
try:
n = int(raw_input("Enter a number greater or equal to %s: "% min))
except Exception:
print "Please enter an integer."
return n
def input_number_between( min, max ):
n = min - 1
while n < min or n > max:
try:
n = int(raw_input("Enter a number between %s and %s: " % (min,max)))
except Exception:
print "Please enter a number."
return n
def choose_continue():
print """Do you want to continue?
0. No
1. Yes"""
return bool( input_number_between(0,1) )
def choose_distribution_uniform():
distribution = {}
distribution["name"] = "uniform"
print "Enter the minimum value (in milliseconds): "
min = input_number_at_least( 0 )
distribution["min"] = str(min)
print "Enter the maximum value (in milliseconds): "
distribution["max"] = str(input_number_at_least( min ))
return distribution
def choose_distribution_normal():
distribution = {}
distribution["name"] = "normal"
print "Enter the mean (in milliseconds): "
distribution["mean"] = str(input_number_at_least( 0 ))
print "Enter the standard deviation (in milliseconds): "
distribution["stddev"] = str(input_number_at_least( 0 ))
return distribution
def choose_distribution_power():
distribution = {}
distribution["name"] = "exponential"
print "Enter the mean (in milliseconds): "
distribution["mean"] = str(input_number_at_least( 0 ))
return distribution
def choose_distribution():
print """Choose your distribution:
0. Uniform
1. Normal
2. Exponential"""
choice = input_number_between( 0, 2 )
choose_distrib_functions = [ choose_distribution_uniform, choose_distribution_normal, choose_distribution_power ]
return choose_distrib_functions[ choice ]()
def choose_packet_size():
print "Enter the size of a packet (group of elements):"
return str(input_number_at_least( 0 ))
def choose_size():
print "Enter the total size (size of population):"
return str(input_number_at_least( 0 ))
def choose_worker_print():
print """Should the workers print the time they sleep on stdout?
0. No
1. Yes"""
return str(input_number_between( 0, 1 ))
def choose_nb_runs():
print """How many runs should be launched for this configuration? Seeds will be automatically affected to the number
of run+1 (for instance, the first run has a seed of 1, the second has a seed of 2, etc.)."""
return input_number_at_least( 1 )
def choose_prefix():
print """What is the name of the experiment? It will be used as the prefix of file names."""
return raw_input("Enter the prefix name: ")
def main():
prefix = choose_prefix()
exps = []
while True:
exp = {}
exp["distribution"] = choose_distribution()
exp["size"] = choose_size()
exp["packet_size"] = choose_packet_size()
exp["worker_print_waiting_time"] = choose_worker_print()
runs = choose_nb_runs()
for i in range( runs ):
exp["seed"] = str(i+1)
filename_map = exp.copy()
filename_map["run"] = exp["seed"]
filename_map["distrib_name"] = exp["distribution"]["name"]
filename_map["prefix"] = prefix
filename = FILENAME_PATTERN % filename_map
exp["filename"] = filename
copy = exp.copy()
exps.append( copy )
if not choose_continue():
break
# Write the experiments in a file
f = file( EXPERIMENTS_FILENAME , 'wb')
f.write("""{"experiments":[""")
i = 0
for exp in exps:
if i > 0:
f.write(",\n")
i += 1
f.write( json.dumps(exp) )
f.write("]}")
f.close()
if __name__ == "__main__":
main()