class TestComputeLowerBound(unittest.TestCase):
def setUp(self):
self.nielsenGraph = DirectedHypergraph()
self.nielsenGraph.add_node('s')
self.nielsenGraph.add_node('1')
self.nielsenGraph.add_node('2')
self.nielsenGraph.add_node('3')
self.nielsenGraph.add_node('4')
self.nielsenGraph.add_node('t')
self.nielsenGraph.add_hyperedge({'s'}, {'1'}, weight=1)
self.nielsenGraph.add_hyperedge({'s'}, {'2'}, weight=1)
self.nielsenGraph.add_hyperedge({'s'}, {'3'}, weight=1)
self.nielsenGraph.add_hyperedge({'1'}, {'2'}, weight=1)
self.nielsenGraph.add_hyperedge({'2'}, {'3'}, weight=1)
self.nielsenGraph.add_hyperedge({'1', '2'}, {'t'}, weight=1)
self.nielsenGraph.add_hyperedge({'4'}, {'t'}, weight=1)
self.nielsenGraph.add_hyperedge({'2', '3'}, {'4'}, weight=1)
self.nielsenGraph.add_hyperedge({'4'}, {'1'}, weight=1)
def test_returns_12_for_lower_bound_for_nielsen_H_21(self):
'''
Test graph is discussed in Section 3.2 example 2 of
Nielsen et al.\
'''
H_2 = self.nielsenGraph.copy()
e1 = H_2.get_hyperedge_id({'s'}, {'1'})
e2 = H_2.get_hyperedge_id({'1'}, {'2'})
e3 = H_2.get_hyperedge_id({'1', '2'}, {'t'})
H_2.remove_hyperedge(H_2.get_hyperedge_id({'s'}, {'2'}))
H_2.remove_hyperedge(H_2.get_hyperedge_id({'4'}, {'t'}))
# weight vector
W = {'s': 0, '1': 1, '2': 2, '3': 1, '4': 4, 't': 4}
# predecessor function
pred = {'s': None, '1': e1, '2': e2, 't': e3}
# ordering
ordering = ['s', '1', '2', 't']
# branch of H_2 for the test
H_2_1 = H_2.copy()
H_2_1.remove_hyperedge(
H_2_1.get_hyperedge_id({'s'}, {'1'}))
self.assertEqual(ksh._compute_lower_bound(
H_2_1, 0, pred, ordering, W, 't'), 12)
class TestComputeLowerBound(unittest.TestCase):
def setUp(self):
self.nielsenGraph = DirectedHypergraph()
self.nielsenGraph.add_node('s')
self.nielsenGraph.add_node('1')
self.nielsenGraph.add_node('2')
self.nielsenGraph.add_node('3')
self.nielsenGraph.add_node('4')
self.nielsenGraph.add_node('t')
self.nielsenGraph.add_hyperedge({'s'}, {'1'}, weight=1)
self.nielsenGraph.add_hyperedge({'s'}, {'2'}, weight=1)
self.nielsenGraph.add_hyperedge({'s'}, {'3'}, weight=1)
self.nielsenGraph.add_hyperedge({'1'}, {'2'}, weight=1)
self.nielsenGraph.add_hyperedge({'2'}, {'3'}, weight=1)
self.nielsenGraph.add_hyperedge({'1', '2'}, {'t'}, weight=1)
self.nielsenGraph.add_hyperedge({'4'}, {'t'}, weight=1)
self.nielsenGraph.add_hyperedge({'2', '3'}, {'4'}, weight=1)
self.nielsenGraph.add_hyperedge({'4'}, {'1'}, weight=1)
def test_returns_12_for_lower_bound_for_nielsen_H_21(self):
'''
Test graph is discussed in Section 3.2 example 2 of
Nielsen et al.\
'''
H_2 = self.nielsenGraph.copy()
e1 = H_2.get_hyperedge_id({'s'}, {'1'})
e2 = H_2.get_hyperedge_id({'1'}, {'2'})
e3 = H_2.get_hyperedge_id({'1', '2'}, {'t'})
H_2.remove_hyperedge(H_2.get_hyperedge_id({'s'}, {'2'}))
H_2.remove_hyperedge(H_2.get_hyperedge_id({'4'}, {'t'}))
# weight vector
W = {'s': 0, '1': 1, '2': 2, '3': 1, '4': 4, 't': 4}
# predecessor function
pred = {'s': None, '1': e1, '2': e2, 't': e3}
# ordering
ordering = ['s', '1', '2', 't']
# branch of H_2 for the test
H_2_1 = H_2.copy()
H_2_1.remove_hyperedge(H_2_1.get_hyperedge_id({'s'}, {'1'}))
self.assertEqual(
ksh._compute_lower_bound(H_2_1, 0, pred, ordering, W, 't'), 12)
def test_copy():
node_a = 'A'
node_b = 'B'
node_c = 'C'
attrib_c = {'alt_name': 1337}
common_attrib = {'common': True, 'source': False}
node_list = [node_a, (node_b, {'source': True}), (node_c, attrib_c)]
node_d = 'D'
H = DirectedHypergraph()
H.add_nodes(node_list, common_attrib)
tail1 = set([node_a, node_b])
head1 = set([node_c, node_d])
frozen_tail1 = frozenset(tail1)
frozen_head1 = frozenset(head1)
tail2 = set([node_b, node_c])
head2 = set([node_d, node_a])
frozen_tail2 = frozenset(tail2)
frozen_head2 = frozenset(head2)
attrib = {'weight': 6, 'color': 'black'}
common_attrib = {'sink': False}
hyperedges = [(tail1, head1, attrib), (tail2, head2)]
hyperedge_names = \
H.add_hyperedges(hyperedges, common_attrib, color='white')
new_H = H.copy()
assert new_H._node_attributes == H._node_attributes
assert new_H._hyperedge_attributes == H._hyperedge_attributes
assert new_H._backward_star == H._backward_star
assert new_H._forward_star == H._forward_star
assert new_H._successors == H._successors
assert new_H._predecessors == H._predecessors
def test_copy():
node_a = 'A'
node_b = 'B'
node_c = 'C'
attrib_c = {'alt_name': 1337}
common_attrib = {'common': True, 'source': False}
node_list = [node_a, (node_b, {'source': True}), (node_c, attrib_c)]
node_d = 'D'
H = DirectedHypergraph()
H.add_nodes(node_list, common_attrib)
tail1 = set([node_a, node_b])
head1 = set([node_c, node_d])
frozen_tail1 = frozenset(tail1)
frozen_head1 = frozenset(head1)
tail2 = set([node_b, node_c])
head2 = set([node_d, node_a])
frozen_tail2 = frozenset(tail2)
frozen_head2 = frozenset(head2)
attrib = {'weight': 6, 'color': 'black'}
common_attrib = {'sink': False}
hyperedges = [(tail1, head1, attrib), (tail2, head2)]
hyperedge_names = \
H.add_hyperedges(hyperedges, common_attrib, color='white')
new_H = H.copy()
assert new_H._node_attributes == H._node_attributes
assert new_H._hyperedge_attributes == H._hyperedge_attributes
assert new_H._backward_star == H._backward_star
assert new_H._forward_star == H._forward_star
assert new_H._successors == H._successors
assert new_H._predecessors == H._predecessors
def test_check_hyperedge_attributes_consistency():
# make test hypergraph
node_a = 'A'
node_b = 'B'
node_c = 'C'
attrib_c = {'alt_name': 1337}
common_attrib = {'common': True, 'source': False}
node_list = [node_a, (node_b, {'source': True}), (node_c, attrib_c)]
node_d = 'D'
H = DirectedHypergraph()
H.add_nodes(node_list, common_attrib)
tail1 = set([node_a, node_b])
head1 = set([node_c, node_d])
frozen_tail1 = frozenset(tail1)
frozen_head1 = frozenset(head1)
tail2 = set([node_b, node_c])
head2 = set([node_d, node_a])
frozen_tail2 = frozenset(tail2)
frozen_head2 = frozenset(head2)
attrib = {'weight': 6, 'color': 'black'}
common_attrib = {'sink': False}
hyperedges = [(tail1, head1, attrib), (tail2, head2)]
hyperedge_names = \
H.add_hyperedges(hyperedges, common_attrib, color='white')
# This should not fail
H._check_consistency()
# The following consistency checks should fail
# Check 1.1
new_H = H.copy()
del new_H._hyperedge_attributes["e1"]["weight"]
try:
new_H._check_consistency()
assert False
except ValueError:
pass
except BaseException as e:
assert False, e
# Check 1.2
new_H = H.copy()
new_H._hyperedge_attributes["e1"]["tail"] = head1
try:
new_H._check_consistency()
assert False
except ValueError:
pass
except BaseException as e:
assert False, e
# Check 1.3
new_H = H.copy()
new_H._hyperedge_attributes["e1"]["head"] = tail1
try:
new_H._check_consistency()
assert False
except ValueError:
pass
except BaseException as e:
assert False, e
# Check 1.4
new_H = H.copy()
del new_H._successors[frozen_tail1]
try:
new_H._check_consistency()
assert False
except ValueError:
pass
except BaseException as e:
assert False, e
# Check 1.5
new_H = H.copy()
del new_H._predecessors[frozen_head1]
try:
new_H._check_consistency()
assert False
except ValueError:
pass
except BaseException as e:
assert False, e
# Check 1.6
new_H = H.copy()
new_H._forward_star["A"].pop()
try:
new_H._check_consistency()
assert False
except ValueError:
pass
except BaseException as e:
assert False, e
# Check 1.7
new_H = H.copy()
new_H._backward_star["C"].pop()
try:
new_H._check_consistency()
assert False
except ValueError:
pass
except BaseException as e:
assert False, e
def test_check_node_consistency():
# make test hypergraph
node_a = 'A'
node_b = 'B'
node_c = 'C'
attrib_c = {'alt_name': 1337}
common_attrib = {'common': True, 'source': False}
node_list = [node_a, (node_b, {'source': True}), (node_c, attrib_c)]
node_d = 'D'
H = DirectedHypergraph()
H.add_nodes(node_list, common_attrib)
tail1 = set([node_a, node_b])
head1 = set([node_c, node_d])
frozen_tail1 = frozenset(tail1)
frozen_head1 = frozenset(head1)
tail2 = set([node_b, node_c])
head2 = set([node_d, node_a])
frozen_tail2 = frozenset(tail2)
frozen_head2 = frozenset(head2)
attrib = {'weight': 6, 'color': 'black'}
common_attrib = {'sink': False}
hyperedges = [(tail1, head1, attrib), (tail2, head2)]
hyperedge_names = \
H.add_hyperedges(hyperedges, common_attrib, color='white')
# This should not fail
H._check_consistency()
# Check 5.1
new_H = H.copy()
new_H._forward_star["X"] = {}
try:
new_H._check_node_consistency()
assert False
except ValueError:
pass
except BaseException as e:
assert False, e
# Check 5.2
new_H = H.copy()
new_H._backward_star["X"] = {}
try:
new_H._check_node_consistency()
assert False
except ValueError:
pass
except BaseException as e:
assert False, e
# Check 5.3.1
new_H = H.copy()
new_H.add_hyperedge("X", "Y")
del new_H._node_attributes["X"]
del new_H._forward_star["X"]
del new_H._forward_star["Y"]
del new_H._backward_star["X"]
del new_H._backward_star["Y"]
try:
new_H._check_node_consistency()
assert False
except ValueError:
pass
except BaseException as e:
assert False, e
# Check 5.3.2
new_H = H.copy()
new_H.add_hyperedge("X", "Y")
del new_H._node_attributes["Y"]
del new_H._forward_star["X"]
del new_H._forward_star["Y"]
del new_H._backward_star["X"]
del new_H._backward_star["Y"]
try:
new_H._check_node_consistency()
assert False
except ValueError:
pass
except BaseException as e:
assert False, e
# Check 5.4
new_H = H.copy()
new_H._predecessors[frozenset("X")] = {}
try:
new_H._check_node_consistency()
assert False
except ValueError:
pass
except BaseException as e:
assert False, e
# Check 5.5
new_H = H.copy()
new_H._successors[frozenset("X")] = {}
new_H._predecessors[frozenset("X")] = {}
try:
new_H._check_node_consistency()
assert False
except ValueError:
pass
except BaseException as e:
assert False, e
def main():
# setup working directory and root file
working_dir = "C://opsupport_bpm_files"
input_dir = working_dir + "/pnml_input"
# files for testing ====================================================
#file_root = "ex1_inductive"
file_root = "bpi_challenge2012"
#file_root = "road_fine_process"
#file_root = "hospital_inductive"
#file_root = "repair_start_end_inductive"
file_type = "inductive"
#io_subdir = "/real_logs"
io_subdir = "/inductive"
#MINED WITH ALPHA MINER
#file_root = "ex6_claim_alpha"
#file_type = "alpha"
#pnml_file = "C://BPMNexamples/"+file_type+"/"+file_root+".pnml"
pnml_file = input_dir + io_subdir + "/" + file_root + ".pnml"
# output directory
output_dir = working_dir + "/output_single"
#setup the logger =====================================================
log_file = working_dir + "/aco.log"
logging.basicConfig(format='%(asctime)s %(levelname)s:%(message)s',
filename=log_file,
level=logging.DEBUG)
logger = logging.getLogger(__name__)
# increase recursion limit (if needed)
# print(str(sys.getrecursionlimit()))
# sys.setrecursionlimit(100000000)
# print(str(sys.getrecursionlimit()))
# ========================= A BUNCH OF FILES FOR TESTING =============================
#pnml_file = "C://BPMNexamples/inductive/ex1_inductive.pnml"
#pnml_file = "C://BPMNexamples/inductive/ex4_inductive.pnml"
#pnml_file = "C://BPMNexamples/real_logs/hospital_inductive.pnml"
#pnml_file = "C://BPMNexamples/inductive/repair_start_end_inductive.pnml"
#pnml_file = "C://BPMNexamples/inductive/ex6_claim_inductive.pnml"
#The following has loop:
#pnml_file = "C://BPMNexamples/inductive/ex5_review_inductive.pnml"
#pnml_file = "C://BPMNexamples/alpha/ex1_alpha.pnml"
#===========================================================
# =========================================================================================
# ===================================================================================================
#===========================================================
#===========================================================
#===========================================================
# START: read the pnml file....
tree = ET.parse(pnml_file)
pnet = tree.getroot()
hg = DirectedHypergraph()
# STEP 1: convert pnet into hypergraph + tau post processing
start_time_conv = time()
hg = convert_pnet_to_hypergraph(pnet)
end_time_conv = time()
print(
"Conversion Petri net to hypergraph took: {0}".format(end_time_conv -
start_time_conv))
start_time_post = time()
hg = tau_post_processing(hg)
end_time_post = time()
print(
"Tau post processing on hypergraph took: {0}".format(end_time_post -
start_time_post))
#STEP 2: randomly initialise hypergraph's nodes utility values
hg = random_init_attributes(hg)
# test write and rewrite
hg_rw_test = hg.copy()
reset_pheromone(hg_rw_test)
write_hg_to_file(hg_rw_test, output_dir + "/hg_file_write.txt")
hg_rw_read = read_hg_from_file(output_dir + "/hg_file_write.txt")
print_hg_std_out_only(hg_rw_read)
write_hg_to_file(hg_rw_read, output_dir + "/hg_file_rewrite.txt")
logger.debug("@" * 70)
logger.debug("@" * 70)
logger.debug("@" * 70)
logger.debug("@" * 70)
print_hg_std_out_only(hg)
logger.debug("@" * 70)
logger.debug("@" * 70)
logger.debug("@" * 70)
print_hg_std_out_only(hg_rw_read)
logger.debug("@" * 70)
logger.debug("@" * 70)
logger.debug("@" * 70)
# hg = hg_rw_read
#print_hg(hg,'hyp.txt')
#find start node (MAKE A FUNCTION FOR IT!!!!)
""" INITIALISATION FOR RECURSIVE VERSION
nodes = hg.get_node_set()
start_nodes = []
for node in nodes:
if hg.get_node_attribute(node, 'source') == True:
logger.debug(" ")
logger.debug("$$$$$ Begin optimisation....$$$$$$$$$$$$$$$$$$$$$$$$")
logger.debug("$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$")
logger.debug("Found start node: {0}".format(print_node(node, hg)))
logger.debug("$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$")
start_nodes.append(node)
END """
#===========================================================
# ==================== INITIALISATION NON RECURSIVE VERSION ===========================================
#===========================================================
logger.debug("*" * 50)
logger.info("*" * 50)
logger.info("*** BEGIN ACO OPTIMISATION.... ***")
logger.info("*" * 50)
logger.debug("*" * 50)
# Set ACO parameters
tau = 0.6
ANT_NUM = 3
COL_NUM = 3
W_UTILITY = {'cost': 1.0, 'avail': 0.0, 'qual': 0.0, 'time': 0.0}
#===========================================================
# ===================== call ACO algorithm (NON RECURSIVE)
#===========================================================
#p_opt = aco_algorithm(start_nodes, hg, ANT_NUM, COL_NUM, tau, W_UTILITY)
start_time_aco = time()
aco_result = aco_algorithm_norec(hg, ANT_NUM, COL_NUM, tau, W_UTILITY)
p_opt = aco_result[0]
utility = aco_result[1]
end_time_aco = time()
print("ACO optimisation took: {0}".format(end_time_aco - start_time_aco))
print("ACO optimisation UTILITY: {0}".format(utility))
# ================= highlight optimal path on pnet
start_time_opt = time()
show_opt_path_pnet(p_opt, tree, file_root, output_dir)
# ================= reduce pnet to show only the optimal path
reduce_opt_path_pnet(tree, file_root, output_dir)
end_time_opt = time()
print("Post processing pnet (show optimal path on pnet) took: {0}".format(
end_time_opt - start_time_opt))
def test_check_hyperedge_attributes_consistency():
# make test hypergraph
node_a = 'A'
node_b = 'B'
node_c = 'C'
attrib_c = {'alt_name': 1337}
common_attrib = {'common': True, 'source': False}
node_list = [node_a, (node_b, {'source': True}), (node_c, attrib_c)]
node_d = 'D'
H = DirectedHypergraph()
H.add_nodes(node_list, common_attrib)
tail1 = set([node_a, node_b])
head1 = set([node_c, node_d])
frozen_tail1 = frozenset(tail1)
frozen_head1 = frozenset(head1)
tail2 = set([node_b, node_c])
head2 = set([node_d, node_a])
frozen_tail2 = frozenset(tail2)
frozen_head2 = frozenset(head2)
attrib = {'weight': 6, 'color': 'black'}
common_attrib = {'sink': False}
hyperedges = [(tail1, head1, attrib), (tail2, head2)]
hyperedge_names = \
H.add_hyperedges(hyperedges, common_attrib, color='white')
# This should not fail
H._check_consistency()
# The following consistency checks should fail
# Check 1.1
new_H = H.copy()
del new_H._hyperedge_attributes["e1"]["weight"]
try:
new_H._check_consistency()
assert False
except ValueError:
pass
except BaseException as e:
assert False, e
# Check 1.2
new_H = H.copy()
new_H._hyperedge_attributes["e1"]["tail"] = head1
try:
new_H._check_consistency()
assert False
except ValueError:
pass
except BaseException as e:
assert False, e
# Check 1.3
new_H = H.copy()
new_H._hyperedge_attributes["e1"]["head"] = tail1
try:
new_H._check_consistency()
assert False
except ValueError:
pass
except BaseException as e:
assert False, e
# Check 1.4
new_H = H.copy()
del new_H._successors[frozen_tail1]
try:
new_H._check_consistency()
assert False
except ValueError:
pass
except BaseException as e:
assert False, e
# Check 1.5
new_H = H.copy()
del new_H._predecessors[frozen_head1]
try:
new_H._check_consistency()
assert False
except ValueError:
pass
except BaseException as e:
assert False, e
# Check 1.6
new_H = H.copy()
new_H._forward_star["A"].pop()
try:
new_H._check_consistency()
assert False
except ValueError:
pass
except BaseException as e:
assert False, e
# Check 1.7
new_H = H.copy()
new_H._backward_star["C"].pop()
try:
new_H._check_consistency()
assert False
except ValueError:
pass
except BaseException as e:
assert False, e
def test_check_node_consistency():
# make test hypergraph
node_a = 'A'
node_b = 'B'
node_c = 'C'
attrib_c = {'alt_name': 1337}
common_attrib = {'common': True, 'source': False}
node_list = [node_a, (node_b, {'source': True}), (node_c, attrib_c)]
node_d = 'D'
H = DirectedHypergraph()
H.add_nodes(node_list, common_attrib)
tail1 = set([node_a, node_b])
head1 = set([node_c, node_d])
frozen_tail1 = frozenset(tail1)
frozen_head1 = frozenset(head1)
tail2 = set([node_b, node_c])
head2 = set([node_d, node_a])
frozen_tail2 = frozenset(tail2)
frozen_head2 = frozenset(head2)
attrib = {'weight': 6, 'color': 'black'}
common_attrib = {'sink': False}
hyperedges = [(tail1, head1, attrib), (tail2, head2)]
hyperedge_names = \
H.add_hyperedges(hyperedges, common_attrib, color='white')
# This should not fail
H._check_consistency()
# Check 5.1
new_H = H.copy()
new_H._forward_star["X"] = {}
try:
new_H._check_node_consistency()
assert False
except ValueError:
pass
except BaseException as e:
assert False, e
# Check 5.2
new_H = H.copy()
new_H._backward_star["X"] = {}
try:
new_H._check_node_consistency()
assert False
except ValueError:
pass
except BaseException as e:
assert False, e
# Check 5.3.1
new_H = H.copy()
new_H.add_hyperedge("X", "Y")
del new_H._node_attributes["X"]
del new_H._forward_star["X"]
del new_H._forward_star["Y"]
del new_H._backward_star["X"]
del new_H._backward_star["Y"]
try:
new_H._check_node_consistency()
assert False
except ValueError:
pass
except BaseException as e:
assert False, e
# Check 5.3.2
new_H = H.copy()
new_H.add_hyperedge("X", "Y")
del new_H._node_attributes["Y"]
del new_H._forward_star["X"]
del new_H._forward_star["Y"]
del new_H._backward_star["X"]
del new_H._backward_star["Y"]
try:
new_H._check_node_consistency()
assert False
except ValueError:
pass
except BaseException as e:
assert False, e
# Check 5.4
new_H = H.copy()
new_H._predecessors[frozenset("X")] = {}
try:
new_H._check_node_consistency()
assert False
except ValueError:
pass
except BaseException as e:
assert False, e
# Check 5.5
new_H = H.copy()
new_H._successors[frozenset("X")] = {}
new_H._predecessors[frozenset("X")] = {}
try:
new_H._check_node_consistency()
assert False
except ValueError:
pass
except BaseException as e:
assert False, e
