def test_comb(options,o_min, o_max, to_include=None ):
""" the naive approach """
config.checks = 0
if o_max == None:
o_max = len(options)
if o_min == None:
o_min = 0
if to_include == None:
to_include = []
#options=g_ids optionset=a subset of g_ids, i.e, a potential soln
# creates an indexed hash
B = combfuncs.createLookup(options)
if o_max > len(options):
o_max = len(options)
option_length = range(o_min, o_max+1)
#option_length = range(len(options))
option_length.reverse() #start with the largest sets
# generate powersets
for k in option_length:
s = ksubsetlex.all(B, k) # s is an iterator over i-th subsets of B with lexicographic ordering
for optionset in s: # call generator
for o_in in to_include:
optionset.append(o_in) # a list of elements the user says must be in the solution
ad = is_admissible(optionset)
config.checks += 1
if ad:
#pass
print optionset, " admissible"
print 'made ', config.checks, 'checks'
def naive_option(parser, options, ):
""" Given a set of options, create a powerset and try them for admissibility
Return the sets of options which are admissible or none"""
valid = {}
eval_id = 0
if options == []:
# run the basic admissibility test
parser.set_node_ids() #renumber the graph
parser.generate_seb()
parser.print_files()
parser.zero_counts()
try:
admissible = parser.run_seb()
except SebException as se:
#print "Inadmissible"
admissible = False
#print "Admissible: ", admissible
if admissible:
valid[eval_id] = 'All Admissible'
else:
valid[eval_id] = 'All Inadmissible'
return valid
#continue with options if they exist
if o_max == None:
o_max = len(options)
if o_min == None:
o_min = 0
#options=g_ids optionset=a subset of g_ids, i.e, a potential soln
# creates an indexed hash
B = combfuncs.createLookup(options)
if o_max > len(options):
o_max = len(options)
option_length = range(o_min, o_max+1)
option_length.reverse() #start with the largest sets
for k in option_length:
# start = time.clock()
s = ksubsetlex.all(B, k) # s is an iterator over i-th subsets of B with lexicographic ordering
for optionset in s: # call generator
if optionset == []:
break
print 'optionset is', optionset
#for o_in in to_include:
#optionset.append(o_in) # a list of elements the user says must be in the solution
eval_id = eval_id + 1
eval_version = 'option-' + str(eval_id)
is_subset = False
for solution in valid.keys(): # don't check subsets of solutions. #TODO At some point do this efficiently in the powerset generator
solution = set(valid[solution])
oset = set(optionset)
if oset.issubset(solution):
is_subset = True
break
if is_subset:
continue #with next optionset
# run the evaluation
for g_id in optionset: # the graffle ID, immutable
parser.set_node_status(g_id, 'to_unknown') # change the model so this node is neither optional nor mandatory
parser.set_node_ids() #renumber the graph
parser.generate_seb()
parser.print_files()
parser.zero_counts()
try:
admissible = parser.run_seb()
except SebException as se:
for g_id in optionset:
parser.set_node_status(g_id, 'to_optional')
#print "Inadmissible"
break
#print "Admissible: ", admissible
if admissible:
valid[eval_version] = optionset
else:
valid[eval_version] = 'false'
# reset the options to T for the next calculation
for g_id in optionset:
parser.set_node_status(g_id, 'to_optional')
#print str(k)+'-subset time taken: ' + str(time.clock() - start)
# print "valid are:"
# for v in valid.keys():
# print v, ': ',
# for o in valid[v]:
# print o.name, ',',
# print ''
return valid