def generate_random_graphs(self):
"""
Extend random graphs by generating larger versions provided in the Traces package.
Random graphs are defined with edge probability 1/2, 1/10 and sqrt(n)
:return:
"""
ph = ProcessHandler()
instances = [
5, 10, 15, 20, 25, 30, 40, 50, 60, 70, 80, 100, 200, 300, 400, 500,
600, 700, 800, 900, 1000, 2000, 3000, 4000, 5000, 10000, 20000,
30000
]
probabilities = ["1/2", "1/10", "sqrt"]
names = ["ran2_custom", "ran10_custom", "ransq_custom"]
for p, n in zip(probabilities, names):
print p
for i in instances:
dest = "./../assets/graphs_custom/{0}/{1}".format(n, i)
print dest
p = "1/" + str(int(math.ceil(math.sqrt(float(i)))))
print "./../assets/nauty26r7/genrang -P{0} {1} 1 {2}.g6".format(
p, i, dest)
ph.run_command(
"./../assets/nauty26r7/genrang -P{0} {1} 1 {2}.g6".format(
p, i, dest))
ph.run_command(
"./../assets/nauty26r7/showg -d {0}.g6 {1}.dre".format(
dest, dest))
def update_strongly_k(self, n, m, system):
"""
Update the folder of stored systems which are a catalogue of slow systems
:param n:
:param m:
:param system:
:return:
"""
ph = ProcessHandler()
fh = FileHandler()
path = "./../assets/systems_strongly_k/{0}_{1}".format(n, m)
fh.delete_file(path)
self.save_system(n, m, system, "./../assets/systems_strongly_k/")
def run_solver(self, **kwargs):
"""
Run Traces through systems and record times
Looking for systems that are faster with gauss off => K-local consistent
:param kwargs:
:return: Null
"""
fh = FileHandler()
ph = ProcessHandler()
results = []
skip = kwargs.get("outstanding", False)
completed = []
if fh.read_from_file("./../assets/systems_run/run"):
for result in fh.read_from_file("./../assets/systems_run/run"):
completed.append(result[0])
for filename in ph.run_command('ls -v ./../assets/systems/'):
# Init
path = './../assets/systems/' + filename
system = fh.read_from_file(path)
split = filename.split("_")
n = split[0]
m = split[1]
# Skip completed systems
key = "{0}:{1}".format(n, m)
if skip and key in completed:
continue
print key
# Create cryptominisat system
time_off, time_on = self.get_gauss_times(n, m, system)
# Save
results.append([key, n, m, time_off, time_on, time_off - time_on])
fh.update_file("./../assets/systems_run/run", results)
def is_system_eligble(self, n, m, system, gi, location):
"""
Check if graph meets the construction criteria
- k consistent
- No automorphisms
:param n:
:param m:
:param gi:
:param system:
:return:
"""
# Init
ph = ProcessHandler()
fh = FileHandler()
graph_path = "{0}/constructions/".format(location)
system_path = "{0}/constructions/{1}_{2}".format(location, n, m)
construct_a_location = "{0}{1}_{2}_A.dre".format(graph_path, n, m)
# Save system temporarily
self.save_system(n, m, system, graph_path)
G = self.convert_system_to_graph(n, m, system)
gi.convert_graph_to_traces(n, m, G, "A",
graph_path) # First construction
# Check for k-local consistency
if not self.is_k_consistent(n, m, system):
# print "Not K consistent"
fh.delete_file(system_path)
return False
elif not gi.graph_has_automorphisms(construct_a_location):
# print "No Automorphisms. Construct."
G = self.convert_system_to_construction(n, m, system)
gi.convert_graph_to_traces(n, m, G, "B",
graph_path) # Second construction
fh.delete_file(system_path)
return True
else:
# print "Automorphisms. Remove."
fh.delete_file(construct_a_location) # Remove unwanted graph
fh.delete_file(system_path) # Remove unwanted system
return False
def convert_systems_to_constructions(self, **kwargs):
"""
Convert found systems into graphs and run them through Traces
:return:
"""
# Init
gi = Gi()
sat = Sat()
ph = ProcessHandler()
fh = FileHandler()
paths = ph.run_command("ls -v ./../assets/systems_to_convert/")
validate = kwargs.get("validate", False)
delete = kwargs.get("delete", False)
# Iterate systems
for path in paths:
print "Checking " + path
# Paths
graph_path = "./../assets/construction/" + path + "_A.dre"
system_path = "./../assets/systems_to_convert/" + path
# Extract n and m values
n, m = path.split("_")
n = int(n)
m = int(m)
# Load system
system = fh.read_from_file(system_path)
if validate:
# Check for k-local consistency
if not sat.is_k_consistent(n, m, system):
print "\t Not K consistent system. Removing and skipping."
if delete:
fh.delete_file(system_path)
continue
else:
print "\t K consistent system. Constructing A."
# Convert system into graphs and check for automorphisms
G = sat.convert_system_to_graph(n, m, system)
gi.convert_graph_to_traces(
n, m, G, "A",
"./../assets/construction/") # First construction
if not gi.graph_has_automorphisms(graph_path):
print "\t No Automorphisms. Constructing B."
G = sat.convert_system_to_construction(n, m, system)
gi.convert_graph_to_traces(
n, m, G, "B",
"./../assets/construction/") # Second construction
if delete:
fh.delete_file(graph_path)
else:
print "\t Automorphisms. Removing and skipping."
if delete:
fh.delete_file(graph_path) # Remove unwanted graph
fh.delete_file(system_path) # Remove unwanted system
else:
G = sat.convert_system_to_construction(n, m, system)
gi.convert_graph_to_traces(n, m, G, "B",
"./../assets/construction/")
def generate_systems(self, **kwargs):
"""
Generate instances by searching through combinations of n and m
Save these results as files
:param kwargs:
:return: Results of time taken to search
"""
# Init
fh = FileHandler()
ph = ProcessHandler()
all_results = [['key', 'n', 'm', 'tries', 'vTime']]
all_systems = []
# Looping params
step = kwargs.get("step", 1)
max_tries = kwargs.get("max_tries", 30)
min_m = kwargs.get("min_m", 4)
n = kwargs.get("n", 4)
max_n = kwargs.get("max_n", 100)
max_m = kwargs.get("max_m", 100)
# Complex looping params
efficient_search = kwargs.get("limited_search", False)
limit = kwargs.get("limit", False)
upper_bound = kwargs.get("upper_bound", 4)
lower_bound = kwargs.get("lower_bound", 1)
# Additional params
save_results_dir = "./../assets/sat_run/{0}-n-{1}_{2}-m-{3}_step-{4}".format(
n, max_n, min_m, max_m, step)
save_results = kwargs.get("save_results", False)
save_systems = kwargs.get("save_systems", False)
gi = kwargs.get("gi", False)
update_strongly_k = kwargs.get("update_strongly_k", False)
# Prep results folder
if save_results or save_systems or gi:
save_results_dir = fh.makedir(save_results_dir)
save_results_location = save_results_dir + "/results"
save_systems_location = save_results_dir + "/systems/"
save_constructions_location = save_results_dir + "/constructions/"
fh.makedir(save_systems_location)
fh.makedir(save_constructions_location)
# Loop n value
while n <= max_n:
# Init loop
tries = 0
found = 0
smallest_m_found = False
n_results = []
n_systems = []
if min_m < n:
# If m is smaller than n, then bring m up to speed
m = lower_bound * n
else:
m = min_m
# Loop m value
while m <= max_m:
# Handle Iterators
if max_tries == tries:
# Failed to find and tried too many times
print "Skipping: {0} {1}".format(n, m)
tries = 0
all_results.append([key, n, m, tries, -1, -1])
n_results.append([key, n, m, tries, -1, -1])
m += step
continue
elif m > (upper_bound * n) or (found and found == limit):
# Do not search for m > 4n or continue to next m if adequate systems are found
break
# Generate random system and record time taken to find
key = ` n ` + ':' + ` m `
validation_start = timeit.default_timer()
generate_time, system = ph.run_function_timed(
self.generate_rand_system, (n, m), return_args=True)
# Validate system
if self.is_system_uniquely_satisfiable(system, n) \
and ((gi and self.is_system_eligble(n, m, system, gi, save_results_dir)) or not gi) \
and ((update_strongly_k and self.is_system_slower(n, m, system)) or not update_strongly_k):
# Found unique system
print "Found: {0} {1}".format(n, m)
# Record times
validation_time = timeit.default_timer() - validation_start
all_results.append(
[key, n, m, tries, validation_time, generate_time])
n_results.append(
[key, n, m, tries, validation_time, generate_time])
all_systems.append([key, n, m, system])
n_systems.append([key, n, m, system])
# Update iterators
tries = 0
found += 1
if efficient_search and not smallest_m_found:
# Update the lower bound
min_m = m - step
smallest_m_found = True
if update_strongly_k:
self.update_strongly_k(n, m, system)
else:
# Failed to find, try again
# print 'Couldnt find for {0} {1} Misses {2}'.format(n, m, tries)
tries += 1
m -= step
# Increment m
m += step
# Save search information
if save_results:
self.save_results(n_results, save_results_location)
if save_systems:
self.save_results_systems(n_systems, save_systems_location)
# Increment n
n += step
return all_results, all_systems
