def worst_case_nf(input_size, outfile):
print('Running a worst case for Next Fit')
with open(outfile, 'a') as f:
f.write('Running a worst case for Next Fit\n')
bad_input_nf = [1 / 2, 1 / (2 * input_size)] * int(math.ceil(input_size / 2))
pack_print_all(bad_input_nf, outfile)
pack_and_print(bad_input_nf, first_fit, outfile, False)
pack_and_print(bad_input_nf, first_fit, outfile, True)
def test_ptas(input_size, outfile):
epses = [0.5, 0.25, 0.1, 0.05, 0.01, 0.001]
for eps in epses:
set_epsilon(eps)
with open(outfile, 'a') as f:
f.write('Doing PTAS, eps={}\n'.format(eps))
for i in range(64):
pack_and_print(random_list(input_size), ptas_awfd, outfile, True)
def worst_case_ff(input_size, outfile):
print('Running a worst case for First Fit')
with open(outfile, 'a') as f:
f.write('Running a worst case for First Fit\n')
one_third = int(math.ceil(input_size / 3))
bad_input_ff = [1 / 7 + 0.001] * one_third + [1 / 3 + 0.001] * one_third + [1 / 2 + 0.001] * one_third
pack_print_all(bad_input_ff, outfile)
pack_and_print(bad_input_ff, first_fit, outfile, False)
pack_and_print(bad_input_ff, first_fit, outfile, True)
