'''
Processes trials and outputs to a file.
Charlie Cabot
August 1, 2012
'''
from bn_generator import disc_bn_generator
from timer import timer
r = range(500, 5000)[::500]
op = open("output.csv", 'w')
print(
op,
"Discrete bn parameter learning. Runtime as a function of datapoints. numvertices=300. numoutcomes=2. indegree=2. max witness size=1."
)
for dl in r:
disc_bn_generator(300, 2, 2, "disc_bn_x.txt")
runtime = timer("disc_bn_x.txt", 1, dl)
line = "%d, %f" % (dl, runtime)
print(line)
print(op, line)
'''
Processes trials and outputs to a file.
Charlie Cabot
August 1, 2012
'''
from bn_generator import disc_bn_generator
from timer import timer
graphsizes = range(100, 10000)[::100]
op = open("output.csv", 'w')
print >>op, "Forward Sampling in a discrete BN. Runtime as a function of number of vertices. Indegree=3. Numoutcomes=3. Samples=100."
for size in graphsizes:
disc_bn_generator(size, 3, 3, "disc_bn_x.txt")
runtime = timer("disc_bn_x.txt", 1)
line = "%d, %f" % (size, runtime)
print line
print >>op, line
'''
Processes trials and outputs to a file.
Charlie Cabot
August 1, 2012
'''
from bn_generator import disc_bn_generator
from timer import timer
r = range(500, 5000)[::500]
op = open("output.csv", 'w')
print >>op, "Discrete bn parameter learning. Runtime as a function of datapoints. numvertices=300. numoutcomes=2. indegree=2. max witness size=1."
for dl in r:
disc_bn_generator(300, 2, 2, "disc_bn_x.txt")
runtime = timer("disc_bn_x.txt", 1, dl)
line = "%d, %f" % (dl, runtime)
print line
print >>op, line
'''
Processes trials and outputs to a file.
Charlie Cabot
August 1, 2012
'''
from bn_generator import disc_bn_generator
from timer import timer
graphsizes = range(100, 10000)[::100]
op = open("output.csv", 'w')
print(
op,
"Forward Sampling in a discrete BN. Runtime as a function of number of vertices. Indegree=3. Numoutcomes=3. Samples=100."
)
for size in graphsizes:
disc_bn_generator(size, 3, 3, "disc_bn_x.txt")
runtime = timer("disc_bn_x.txt", 1)
line = "%d, %f" % (size, runtime)
print(line)
print(op, line)
