def create_planners(): """ Initializes the planner lists and formats each planner's parameters to be sent to the client. """ ompl.initializePlannerLists() # Create the geometric planners planners = ompl.PlanningAlgorithms(og) params_dict = planners.getPlanners() return params_dict
def create_planners():
"""
Initializes the planner lists and formats each planner's parameters to be
sent to the client.
"""
ompl.initializePlannerLists()
# Create the geometric planners
planners = ompl.PlanningAlgorithms(og)
params_dict = planners.getPlanners()
# TODO: Por que? Is this accidentally left over from testing?
retval = "{'param name' : ('display name', 'range type', 'range suggestion', 'default value')}\n"
retval += "For KPIECE1: \n"
retval += str(params_dict['ompl.geometric.KPIECE1'])
return params_dict
def initialize():
ompl.initializePlannerLists()
if sys.version_info > (3, 0):
config = ConfigParser.ConfigParser(strict=False)
else:
config = ConfigParser.ConfigParser()
conf_file_loc = None
for loc in [join(ompl_app_root, join("ompl", "ompl.conf")), \
join(prefix, "share/ompl/ompl.conf")]:
if exists(loc):
conf_file_loc = loc
break
config.read([conf_file_loc])
preferences = config._sections["webapp"]
preferences["plannerarena_port"] = config.get("plannerarena",
"plannerarena_port")
return preferences
def initialize():
ompl.initializePlannerLists()
if (sys.version_info > (3, 0)):
config = ConfigParser.ConfigParser(strict = False)
else:
config = ConfigParser.ConfigParser()
conf_file_loc = None
for loc in [join(ompl_app_root, join("ompl", "ompl.conf")), "/usr/share/ompl/ompl.conf"]:
if exists(loc):
conf_file_loc = loc
break
conf_file = open(conf_file_loc, "r")
config.readfp(conf_file)
preferences = config._sections["webapp"]
preferences["plannerarena_port"] = config.get("plannerarena", "plannerarena_port")
conf_file.close()
return preferences
def initialize():
ompl.initializePlannerLists()
preferences = { \
# (Time * Runs * Number of Planners) < benchmarking_limit
'benchmarking_limit': '100000',
# The broker to use with Celery
'broker_url': 'amqp://localhost:5672', # RabbitMQ
#'broker': 'redis://localhost:6379', # Redis
# The backend to use with Celery
'backend_url': 'rpc://localhost:5672', # RabbitMQ
#'backend_url': 'redis://localhost:6379', # Redis
# Maximum allowed file size for mesh uploads, in bytes
'max_upload_size': '50000000',
# How often to poll the server for problem solution, in milliseconds
'poll_interval': '2000',
# How often the page is refreshed to check for benchmark results, in milliseconds
'refresh_interval': '5000',
# Auto launch browser when benchmarking completes; 0 = False, 1 = True
'show_results': '0',
# Port for OMPL Web, default is 5000
'port': '5000',
# PlannerArena port
'plannerarena_port': '8888'
}
# allow preferences to be set via uppercased environment variables, prefixed with 'OMPL_'
for key, _ in preferences.items():
up_key = 'OMPL_' + key.upper()
if up_key in os.environ:
preferences[key] = os.environ[up_key]
return preferences
def initialize():
ompl.initializePlannerLists()
preferences = { \
# (Time * Runs * Number of Planners) < benchmarking_limit
'benchmarking_limit': '100000',
# The broker to use with Celery
'broker_url': 'amqp://localhost:5672', # RabbitMQ
#'broker': 'redis://localhost:6379', # Redis
# The backend to use with Celery
'backend_url': 'rpc://localhost:5672', # RabbitMQ
#'backend_url': 'redis://localhost:6379', # Redis
# Maximum allowed file size for mesh uploads, in bytes
'max_upload_size': '50000000',
# How often to poll the server for problem solution, in milliseconds
'poll_interval': '2000',
# How often the page is refreshed to check for benchmark results, in milliseconds
'refresh_interval': '5000',
# Auto launch browser when benchmarking completes; 0 = False, 1 = True
'show_results': '0',
# Port for OMPL Web, default is 5000
'port': '5000',
# PlannerArena port
'plannerarena_port': '8888'
}
# allow preferences to be set via uppercased environment variables, prefixed with 'OMPL_'
for key, _ in preferences.items():
up_key = 'OMPL_' + key.upper()
if up_key in os.environ:
preferences[key] = os.environ[up_key]
return preferences
