def queue_job(a, ready_queue):
# We just crank out plans until we are terminated
while True:
b = a.copy()
success = maxfield.maxFields(b)
if success:
for t in b.triangulation:
t.markEdgesWithFields()
maxfield.improveEdgeOrder(b)
ready_queue.put((success, b))
def main():
description = ('Ingress FieldPlan - Maximize the number of links '
'and fields, and thus AP, for a collection of '
'portals in the game Ingress and create a convenient plan '
'in Google Spreadsheets. Spin-off from Maxfield.')
parser = argparse.ArgumentParser(
description=description,
prog='makePlan.py',
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument(
'-i',
'--iterations',
type=int,
default=10000,
help='Number of iterations to perform. More iterations may improve '
'results, but will take longer to process.')
parser.add_argument('-k',
'--maxkeys',
type=int,
default=None,
help='Limit number of keys required per portal '
'(may result in less efficient plans)')
parser.add_argument(
'-m',
'--travelmode',
default='walking',
help='Travel mode (walking, bicycling, driving, transit).')
parser.add_argument(
'-s',
'--sheetid',
default=None,
required=True,
help='The Google Spreadsheet ID with portal definitions.')
parser.add_argument(
'-n',
'--nosave',
action='store_true',
default=False,
help='Do not attempt to save the spreadsheet, just calculate the plan.'
)
parser.add_argument(
'-p',
'--plots',
default=None,
help='Save step-by-step PNGs of the workplan into this directory.')
parser.add_argument(
'--plotdpi',
default=96,
type=int,
help='DPI to use for generating plots (try 144 for high-dpi screens)')
parser.add_argument('-g',
'--gmapskey',
default=None,
help='Google Maps API key (for better distances)')
parser.add_argument('-f',
'--faction',
default='enl',
help='Set to "res" to use resistance colours')
parser.add_argument('-l',
'--log',
default=None,
help='Log file where to log processing info')
parser.add_argument('-d',
'--debug',
action='store_true',
default=False,
help='Add debug information to the logfile')
parser.add_argument('-q',
'--quiet',
action='store_true',
default=False,
help='Only output errors to the stdout')
args = parser.parse_args()
if args.iterations < 0:
parser.error('Number of extra samples should be positive')
if args.plotdpi < 1:
parser.error('%s is not a valid screen dpi' % args.plotdpi)
if args.faction not in ('enl', 'res'):
parser.error('Sorry, I do not know about faction "%s".' % args.faction)
logger.setLevel(logging.DEBUG)
if args.log:
ch = logging.FileHandler(args.log)
formatter = logging.Formatter(
'{%(module)s:%(funcName)s:%(lineno)s} %(message)s')
ch.setFormatter(formatter)
if args.debug:
ch.setLevel(logging.DEBUG)
else:
ch.setLevel(logging.INFO)
logger.addHandler(ch)
ch = logging.StreamHandler()
formatter = logging.Formatter('%(message)s')
ch.setFormatter(formatter)
if args.quiet:
ch.setLevel(logging.CRITICAL)
else:
ch.setLevel(logging.INFO)
logger.addHandler(ch)
gs = gsheets.setup()
portals, blockers = gsheets.get_portals_from_sheet(gs, args.sheetid)
logger.info('Considering %d portals', len(portals))
if len(portals) < 3:
logger.critical('Must have more than 2 portals!')
sys.exit(1)
if len(portals) > _MAX_PORTALS_:
logger.critical('Portal limit is %d', _MAX_PORTALS_)
a = maxfield.populateGraph(portals)
ab = None
if blockers:
ab = maxfield.populateGraph(blockers)
(bestgraph, bestplan, bestdist) = maxfield.loadCache(a, ab)
if bestgraph is None:
# Use a copy, because we concat ab to a for blockers distances
maxfield.genDistanceMatrix(a.copy(), ab, args.gmapskey,
args.travelmode)
bestkm = None
else:
bestkm = bestdist / float(1000)
logger.info('Best distance of the plan loaded from cache: %0.2f km',
bestkm)
counter = 0
if args.maxkeys:
logger.info('Finding an efficient plan with max %s keys', args.maxkeys)
else:
logger.info('Finding an efficient plan')
logger.info('Ctrl-C to exit and use the latest best plan')
failcount = 0
try:
while counter < args.iterations:
if failcount >= 100:
logger.info('Too many consecutive failures, exiting early.')
break
b = a.copy()
counter += 1
if not args.quiet:
if bestkm is not None:
sys.stdout.write('\r(%0.2f km best): %s/%s ' %
(bestkm, counter, args.iterations))
sys.stdout.flush()
failcount += 1
if not maxfield.maxFields(b):
logger.debug('Could not find a triangulation')
failcount += 1
continue
for t in b.triangulation:
t.markEdgesWithFields()
maxfield.improveEdgeOrder(b)
workplan = maxfield.makeWorkPlan(b, ab)
if args.maxkeys:
# do any of the portals require more than maxkeys
sane_key_reqs = True
for i in range(len(b.node)):
if b.in_degree(i) > args.maxkeys:
sane_key_reqs = False
break
if not sane_key_reqs:
failcount += 1
logger.debug('Too many keys required, ignoring plan')
continue
sane_out_links = True
for i in range(len(b.node)):
if b.out_degree(i) > 8:
sane_out_links = False
break
if not sane_out_links:
failcount += 1
logger.debug('Too many outgoing links, ignoring plan')
continue
failcount = 0
totaldist = maxfield.getWorkplanDist(b, workplan)
if totaldist < bestdist:
counter = 0
bestplan = workplan
bestgraph = b
bestdist = totaldist
bestkm = bestdist / float(1000)
except KeyboardInterrupt:
if not args.quiet:
print()
print('Exiting loop')
if not args.quiet:
print()
if bestplan is None:
logger.critical('Could not find a solution for this list of portals.')
sys.exit(1)
maxfield.saveCache(bestgraph, ab, bestplan, bestdist)
if args.plots:
animate.make_png_steps(bestgraph, bestplan, args.plots, args.faction,
args.plotdpi)
gs = gsheets.setup()
gsheets.write_workplan(gs, args.sheetid, bestgraph, bestplan, args.faction,
args.travelmode, args.nosave)
def main():
args = docopt(__doc__)
# We will take many samples in an attempt to reduce number of keys to farm
# This is the number of samples to take since the last improvement
EXTRA_SAMPLES = 20
np = geometry.np
#GREEN = 'g'
#BLUE = 'b'
GREEN = '#3BF256' # Actual faction text colors in the app
BLUE = '#2ABBFF'
#GREEN = (0.0 , 1.0 , 0.0 , 0.3)
#BLUE = (0.0 , 0.0 , 1.0 , 0.3)
COLOR = GREEN
if args['-b']:
COLOR = BLUE
output_directory = ''
if args['<output_directory>'] != None:
output_directory = args['<output_directory>']
if output_directory[-1] != '/':
output_directory += '/'
output_file = 'lastPlan.pkl'
if args['<output_file>'] != None:
output_file = args['<output_file>']
if not output_file[-3:] == 'pkl':
print 'WARNING: output file should end in "pkl" or you cannot use it as input later'
nagents = int(args['-n'])
if nagents < 0:
print 'Numer of agents should be positive'
exit()
input_file = args['<input_file>']
if input_file[-3:] != 'pkl':
a = nx.DiGraph()
locs = []
i = 0
# each line should be id,name,lat,long,keys
with open(input_file,'r') as fin:
for line in fin:
parts = line.split(',')
if len(parts) < 3:
break
a.add_node(i)
a.node[i]['name'] = parts[0].strip()
locs.append( np.array(parts[1:3],dtype=int) )
if len(parts) < 4:
a.node[i]['keys'] = 0
else:
a.node[i]['keys'] = int(parts[3])
i += 1
n = a.order() # number of nodes
locs = np.array(locs,dtype=float)
# This part assumes we're working with E6 latitude-longitude data
locs = geometry.e6LLtoRads(locs)
xyz = geometry.radstoxyz(locs)
xy = geometry.gnomonicProj(locs,xyz)
for i in xrange(n):
a.node[i]['geo'] = locs[i]
a.node[i]['xyz'] = xyz [i]
a.node[i]['xy' ] = xy [i]
# EXTRA_SAMPLES attempts to get graph with few missing keys
# Try to minimuze TK + 2*MK where
# TK is the total number of missing keys
# MK is the maximum number of missing keys for any single portal
bestgraph = None
bestlack = np.inf
bestTK = np.inf
bestMK = np.inf
sinceImprove = 0
while sinceImprove<EXTRA_SAMPLES:
b = a.copy()
sinceImprove += 1
if not maxfield.maxFields(b):
print 'Randomization failure\nThe program may work if you try again. It is more likely to work if you remove some protals.'
continue
TK = 0
MK = 0
for j in xrange(n):
keylack = max(b.in_degree(j)-b.node[j]['keys'],0)
TK += keylack
if keylack > MK:
MK = keylack
weightedlack = TK+2*MK
if weightedlack < bestlack:
sinceImprove = 0
print 'IMPROVEMENT:\n\ttotal: %s\n\tmax: %s\n\tweighted: %s'%\
(TK,MK,weightedlack)
bestgraph = b
bestlack = weightedlack
bestTK = TK
bestMK = MK
else:
print 'this time:\n\ttotal: %s\n\tmax: %s\n\tweighted: %s'%\
(TK,MK,weightedlack)
if weightedlack == 0:
print 'KEY PERFECTION'
bestlack = weightedlack
bestTK = TK
bestMK = MK
break
if all([ b.node[i]['keys'] <= b.out_degree(i) for i in xrange(n) ]):
print 'All keys used. Improvement impossible'
break
print '%s tries since improvement'%sinceImprove
if bestgraph == None:
print 'EXITING RANDOMIZATION LOOP WITHOUT SOLUTION!'
print ''
exit()
print 'Choosing plan requiring %s additional keys, max of %s from single portal'%(bestTK,bestMK)
a = bestgraph
# Attach to each edge a list of fields that it completes
for t in a.triangulation:
t.markEdgesWithFields()
agentOrder.improveEdgeOrder(a)
with open(output_directory+output_file,'w') as fout:
pickle.dump(a,fout)
else:
with open(input_file,'r') as fin:
a = pickle.load(fin)
# agentOrder.improveEdgeOrder(a)
# with open(output_directory+output_file,'w') as fout:
# pickle.dump(a,fout)
PP = PlanPrinter.PlanPrinter(a,output_directory,nagents,COLOR)
PP.keyPrep()
PP.agentKeys()
PP.planMap()
PP.agentLinks()
def main():
description = ("Ingress Maxfield - Maximize the number of links "
"and fields, and thus AP, for a collection of "
"portals in the game Ingress.")
parser = argparse.ArgumentParser(description=description,
prog="makePlan.py")
parser.add_argument('-v',
'--version',
action='version',
version="Ingress Maxfield v{0}".format(_V_))
parser.add_argument('-g',
'--google',
action='store_true',
help='Make maps with google maps API. Default: False')
parser.add_argument('-a',
'--api_key',
default=None,
help='Google API key for Google maps. Default: None')
parser.add_argument('-n',
'--num_agents',
type=int,
default='1',
help='Number of agents. Default: 1')
parser.add_argument('-s',
'--samples',
type=int,
default=50,
help="Number of iterations to "
"perform. More iterations may improve "
"results, but will take longer to process. "
"Default: 50")
parser.add_argument('input_file',
help="Input semi-colon delimited portal file")
parser.add_argument('-d',
'--output_dir',
default='',
help="Directory for results. Default: "
"this directory")
parser.add_argument('-f',
'--output_file',
default='plan.pkl',
help="Filename for pickle object. Default: "
"plan.pkl")
args = vars(parser.parse_args())
# Number of iterations to complete since last improvement
EXTRA_SAMPLES = args["samples"]
GREEN = '#3BF256' # Actual faction text colors in the app
BLUE = '#2ABBFF'
# Use google?
useGoogle = args['google']
api_key = args['api_key']
output_directory = args["output_dir"]
# add ending separator
if output_directory[-1] != os.sep:
output_directory += os.sep
# create directory if doesn't exist
if not os.path.isdir(output_directory):
os.mkdir(output_directory)
output_file = args["output_file"]
if output_file[-4:] != '.pkl':
output_file += ".pkl"
nagents = args["num_agents"]
if nagents < 0:
sys.exit("Number of agents should be positive")
EXTRA_SAMPLES = args["samples"]
if EXTRA_SAMPLES < 0:
sys.exit("Number of extra samples should be positive")
elif EXTRA_SAMPLES > 100:
sys.exit("Extra samples may not be more than 100")
input_file = args['input_file']
if input_file[-3:] != 'pkl':
# If the input file is a portal list, let's set things up
a = nx.DiGraph() # network tool
locs = [] # portal coordinates
# each line should be name;intel_link;keys
portals = pd.read_table(input_file,
sep=';',
comment='#',
index_col=False,
names=['name', 'link', 'keys'],
dtype=str)
portals = np.array(portals)
portals = np.array([
portal for portal in portals
if (isinstance(portal[0], basestring)
and isinstance(portal[1], basestring))
])
print "Found {0} portals in portal list.".format(len(portals))
if len(portals) < 3:
sys.exit("Error: Must have more than 2 portals!")
if len(portals) > _MAX_PORTALS_:
sys.exit("Error: Portal limit is {0}".\
format(_MAX_PORTALS_))
for num, portal in enumerate(portals):
if len(portal) < 3:
print "Error! Portal ", portal[0], " has a formatting problem."
sys.exit()
a.add_node(num)
a.node[num]['name'] = portal[0]
coords = (portal[1].split('pll='))
if len(coords) < 2:
print "Error! Portal ", portal[0], " has a formatting problem."
sys.exit()
coord_parts = coords[1].split(',')
lat = int(float(coord_parts[0]) * 1.e6)
lon = int(float(coord_parts[1]) * 1.e6)
locs.append(np.array([lat, lon], dtype=float))
try:
keys = int(portal[2])
a.node[num]['keys'] = keys
except ValueError:
a.node[num]['keys'] = 0
n = a.order() # number of nodes
locs = np.array(locs, dtype=float)
# Convert coords to radians, then to cartesian, then to
# gnomonic projection
locs = geometry.e6LLtoRads(locs)
xyz = geometry.radstoxyz(locs)
xy = geometry.gnomonicProj(locs, xyz)
for i in xrange(n):
a.node[i]['geo'] = locs[i]
a.node[i]['xyz'] = xyz[i]
a.node[i]['xy'] = xy[i]
# EXTRA_SAMPLES attempts to get graph with few missing keys
# Try to minimuze TK + 2*MK where
# TK is the total number of missing keys
# MK is the maximum number of missing keys for any single
# portal
bestgraph = None
bestlack = np.inf
bestTK = np.inf
bestMK = np.inf
allTK = []
allMK = []
allWeights = []
sinceImprove = 0
while sinceImprove < EXTRA_SAMPLES:
b = a.copy()
sinceImprove += 1
if not maxfield.maxFields(b):
print 'Randomization failure\nThe program may work if you try again. It is more likely to work if you remove some portals.'
continue
TK = 0
MK = 0
for j in xrange(n):
keylack = max(b.in_degree(j) - b.node[j]['keys'], 0)
TK += keylack
if keylack > MK:
MK = keylack
weightedlack = TK + 2 * MK
allTK.append(TK)
allMK.append(MK)
allWeights.append(weightedlack)
if weightedlack < bestlack:
sinceImprove = 0
print 'IMPROVEMENT:\n\ttotal: %s\n\tmax: %s\n\tweighted: %s'%\
(TK,MK,weightedlack)
bestgraph = b
bestlack = weightedlack
bestTK = TK
bestMK = MK
else:
print 'this time:\n\ttotal: %s\n\tmax: %s\n\tweighted: %s'%\
(TK,MK,weightedlack)
if weightedlack <= 0:
print 'KEY PERFECTION'
bestlack = weightedlack
bestTK = TK
bestMK = MK
break
# if num agent keys is zero, this code isn't true...
# if all([ b.node[i]['keys'] <= b.out_degree(i) for i in xrange(n) ]):
# print 'All keys used. Improvement impossible'
# break
print '%s tries since improvement' % sinceImprove
if bestgraph == None:
print 'EXITING RANDOMIZATION LOOP WITHOUT SOLUTION!'
print ''
exit()
print 'Choosing plan requiring %s additional keys, max of %s from single portal' % (
bestTK, bestMK)
plt.clf()
plt.scatter(allTK, allMK, c=allWeights, marker='o')
plt.xlim(min(allTK) - 1, max(allTK) + 1)
plt.ylim(min(allMK) - 1, max(allMK) + 1)
plt.xlabel('Total keys required')
plt.ylabel('Max keys required for a single portal')
cbar = plt.colorbar()
cbar.set_label('Optimization Weighting (lower=better)')
plt.savefig(output_directory + 'optimization.png')
a = bestgraph
# Attach to each edge a list of fields that it completes
# catch no triangulation (bad portal file?)
try:
for t in a.triangulation:
t.markEdgesWithFields()
except AttributeError:
print "Error: problem with bestgraph... no triangulation...?"
agentOrder.improveEdgeOrder(a)
with open(output_directory + output_file, 'w') as fout:
pickle.dump(a, fout)
else:
with open(input_file, 'r') as fin:
a = pickle.load(fin)
# agentOrder.improveEdgeOrder(a)
# with open(output_directory+output_file,'w') as fout:
# pickle.dump(a,fout)
PP = PlanPrinterMap.PlanPrinter(a,
output_directory,
nagents,
useGoogle=useGoogle,
api_key=api_key)
PP.keyPrep()
PP.agentKeys()
PP.planMap(useGoogle=useGoogle)
PP.agentLinks()
# These make step-by-step instructional images
PP.animate(useGoogle=useGoogle)
PP.split3instruct(useGoogle=useGoogle)
print "Number of portals: {0}".format(PP.num_portals)
print "Number of links: {0}".format(PP.num_links)
print "Number of fields: {0}".format(PP.num_fields)
portal_ap = (125 * 8 + 500 + 250) * PP.num_portals
link_ap = 313 * PP.num_links
field_ap = 1250 * PP.num_fields
print "AP from portals capture: {0}".format(portal_ap)
print "AP from link creation: {0}".format(link_ap)
print "AP from field creation: {0}".format(field_ap)
print "Total AP: {0}".format(portal_ap + link_ap + field_ap)
def main():
description=("Ingress Maxfield - Maximize the number of links "
"and fields, and thus AP, for a collection of "
"portals in the game Ingress.")
parser = argparse.ArgumentParser(description=description,
prog="makePlan.py")
parser.add_argument('-v','--version',action='version',
version="Ingress Maxfield v{0}".format(_V_))
parser.add_argument('-g','--google',action='store_true',
help='Make maps with google maps API. Default: False')
parser.add_argument('-a','--api_key',default=None,
help='Google API key for Google maps. Default: None')
parser.add_argument('-n','--num_agents',type=int,default='1',
help='Number of agents. Default: 1')
parser.add_argument('-s','--samples',type=int,default=50,
help="Number of iterations to "
"perform. More iterations may improve "
"results, but will take longer to process. "
"Default: 50")
parser.add_argument('input_file',
help="Input semi-colon delimited portal file")
args = vars(parser.parse_args())
# Number of iterations to complete since last improvement
EXTRA_SAMPLES = args["samples"]
GREEN = '#3BF256' # Actual faction text colors in the app
BLUE = '#2ABBFF'
# Use google?
useGoogle = True
api_key = args['api_key']
input_file = args['input_file']
output_directory = os.path.expanduser('~') + "/Ingress/Fielding/{}".format(os.path.split(args['input_file'])[1][:-4])
print(output_directory)
# add ending separator
if output_directory[-1] != os.sep:
output_directory += os.sep
# create directory if doesn't exist
if not os.path.exists(output_directory):
os.makedirs(output_directory)
output_file = (os.path.split(args['input_file'])[1][:-4])
print(output_file)
if output_file[-4:] != '.pkl':
output_file += ".pkl"
nagents = args["num_agents"]
if nagents < 0:
sys.exit("Number of agents should be positive")
EXTRA_SAMPLES = args["samples"]
if EXTRA_SAMPLES < 0:
sys.exit("Number of extra samples should be positive")
elif EXTRA_SAMPLES > 100:
sys.exit("Extra samples may not be more than 100")
if input_file[-3:] != 'pkl':
# If the input file is a portal list, let's set things up
a = nx.DiGraph() # network tool
locs = [] # portal coordinates
# each line should be name;intel_link;keys
portals = pd.read_table(input_file,sep=';',
comment='#',index_col=False,
names=['name','link','keys'],dtype=str)
portals = np.array(portals)
portals = np.array([portal for portal in portals if (isinstance(portal[0], basestring) and isinstance(portal[1], basestring))])
print ("Found {0} portals in portal list.".format(len(portals)))
if len(portals) < 3:
sys.exit("Error: Must have more than 2 portals!")
if len(portals) > _MAX_PORTALS_:
sys.exit("Error: Portal limit is {0}".\
format(_MAX_PORTALS_))
for num,portal in enumerate(portals):
if len(portal) < 3:
print ("Error! Portal ",portal[0]," has a formatting problem.")
sys.exit()
a.add_node(num)
a.node[num]['name'] = portal[0]
coords = (portal[1].split('pll='))
if len(coords) < 2:
print ("Error! Portal ",portal[0]," has a formatting problem.")
sys.exit()
coord_parts = coords[1].split(',')
lat = int(float(coord_parts[0]) * 1.e6)
lon = int(float(coord_parts[1]) * 1.e6)
locs.append(np.array([lat,lon],dtype=float))
try:
keys = int(portal[2])
a.node[num]['keys'] = keys
except ValueError:
a.node[num]['keys'] = 0
n = a.order() # number of nodes
locs = np.array(locs,dtype=float)
# Convert coords to radians, then to cartesian, then to
# gnomonic projection
locs = geometry.e6LLtoRads(locs)
xyz = geometry.radstoxyz(locs)
xy = geometry.gnomonicProj(locs,xyz)
for i in range(n):
a.node[i]['geo'] = locs[i]
a.node[i]['xyz'] = xyz[i]
a.node[i]['xy' ] = xy[i]
# EXTRA_SAMPLES attempts to get graph with few missing keys
# Try to minimuze TK + 2*MK where
# TK is the total number of missing keys
# MK is the maximum number of missing keys for any single
# portal
bestgraph = None
bestlack = np.inf
bestTK = np.inf
bestMK = np.inf
allTK = []
allMK = []
allWeights = []
sinceImprove = 0
while sinceImprove<EXTRA_SAMPLES:
b = a.copy()
sinceImprove += 1
if not maxfield.maxFields(b):
print ('Randomization failure\nThe program may work if you try again. It is more likely to work if you remove some portals.')
continue
TK = 0
MK = 0
for j in range(n):
keylack = max(b.in_degree(j)-b.node[j]['keys'],0)
TK += keylack
if keylack > MK:
MK = keylack
weightedlack = TK+2*MK
allTK.append(TK)
allMK.append(MK)
allWeights.append(weightedlack)
if weightedlack < bestlack:
sinceImprove = 0
print ('IMPROVEMENT:\n\ttotal: %s\n\tmax: %s\n\tweighted: %s'%\
(TK,MK,weightedlack))
bestgraph = b
bestlack = weightedlack
bestTK = TK
bestMK = MK
else:
print ('this time:\n\ttotal: %s\n\tmax: %s\n\tweighted: %s'%\
(TK,MK,weightedlack))
if weightedlack <= 0:
print ('KEY PERFECTION')
bestlack = weightedlack
bestTK = TK
bestMK = MK
break
# if num agent keys is zero, this code isn't true...
# if all([ b.node[i]['keys'] <= b.out_degree(i) for i in xrange(n) ]):
# print 'All keys used. Improvement impossible'
# break
print ('%s tries since improvement'%sinceImprove)
if bestgraph == None:
print ('EXITING RANDOMIZATION LOOP WITHOUT SOLUTION!')
print ('')
exit()
print ('Choosing plan requiring %s additional keys, max of %s from single portal'%(bestTK,bestMK))
plt.clf()
plt.scatter(allTK,allMK,c=allWeights,marker='o')
plt.xlim(min(allTK)-1,max(allTK)+1)
plt.ylim(min(allMK)-1,max(allMK)+1)
plt.xlabel('Total keys required')
plt.ylabel('Max keys required for a single portal')
cbar = plt.colorbar()
cbar.set_label('Optimization Weighting (lower=better)')
plt.savefig(output_directory+'optimization.png')
a = bestgraph
# Attach to each edge a list of fields that it completes
# catch no triangulation (bad portal file?)
try:
for t in a.triangulation:
t.markEdgesWithFields()
except AttributeError:
print ("Error: problem with bestgraph... no triangulation...?")
agentOrder.improveEdgeOrder(a)
with open(output_directory+output_file,'wb') as fout:
pickle.dump(a,fout)
else:
with open(input_file,'r') as fin:
a = pickle.load(fin)
# agentOrder.improveEdgeOrder(a)
# with open(output_directory+output_file,'w') as fout:
# pickle.dump(a,fout)
PP = PlanPrinterMap.PlanPrinter(a,output_directory,nagents,color=BLUE,useGoogle=useGoogle,
api_key=api_key)
PP.keyPrep()
PP.agentKeys()
PP.planMap(useGoogle=useGoogle)
PP.agentLinks()
# These make step-by-step instructional images
PP.animate(useGoogle=useGoogle)
PP.split3instruct(useGoogle=useGoogle)
print ("Number of portals: {0}".format(PP.num_portals))
print ("Number of links: {0}".format(PP.num_links))
print ("Number of fields: {0}".format(PP.num_fields))
portal_ap = (125*8 + 500 + 250)*PP.num_portals
link_ap = 313 * PP.num_links
field_ap = 1250 * PP.num_fields
print ("AP from portals capture: {0}".format(portal_ap))
print ("AP from link creation: {0}".format(link_ap))
print ("AP from field creation: {0}".format(field_ap))
print ("Total AP: {0}".format(portal_ap+link_ap+field_ap))
def main():
args = docopt(__doc__)
# We will take many samples in an attempt to reduce number of keys to farm
# This is the number of samples to take since the last improvement
EXTRA_SAMPLES = 20
np = geometry.np
#GREEN = 'g'
#BLUE = 'b'
GREEN = '#3BF256' # Actual faction text colors in the app
BLUE = '#2ABBFF'
#GREEN = (0.0 , 1.0 , 0.0 , 0.3)
#BLUE = (0.0 , 0.0 , 1.0 , 0.3)
COLOR = BLUE
if args['-b']:
COLOR = GREEN
output_directory = ''
if args['<output_directory>'] != None:
output_directory = args['<output_directory>']
if output_directory[-1] != '/':
output_directory += '/'
if( not os.path.isdir('./'+output_directory) ):
print 'Output directory (%s) does not exist. Creating it.' % output_directory
os.makedirs('./'+output_directory)
output_file = 'lastPlan.pkl'
if args['<output_file>'] != None:
output_file = args['<output_file>']
if not output_file[-3:] == 'pkl':
print 'WARNING: output file should end in "pkl" or you cannot use it as input later'
nagents = int(args['-n'])
if nagents < 0:
print 'Numer of agents should be positive'
exit()
input_file = args['<input_file>']
if input_file[-3:] != 'pkl':
a = nx.DiGraph()
locs = []
i = 0
# each line should be id,name,lat,long,keys
with open(input_file,'r') as fin:
for line in fin:
parts = line.split(',')
if len(parts) < 3:
break
# allow masking of input csv file
# note, if no 4th column, back to default behavior
# unless you put "false" as the number of keys ;)
use = parts[-1].strip().lower()
if(use == "false"): continue
a.add_node(i)
a.node[i]['name'] = parts[0].strip()
locs.append( np.array(parts[1:3],dtype=int) )
if len(parts) < 4:
a.node[i]['keys'] = 0
else:
a.node[i]['keys'] = int(parts[3])
i += 1
n = a.order() # number of nodes
locs = np.array(locs,dtype=float)
# This part assumes we're working with E6 latitude-longitude data
locs = geometry.e6LLtoRads(locs)
xyz = geometry.radstoxyz(locs)
xy = geometry.gnomonicProj(locs,xyz)
for i in xrange(n):
a.node[i]['geo'] = locs[i]
a.node[i]['xyz'] = xyz [i]
a.node[i]['xy' ] = xy [i]
# EXTRA_SAMPLES attempts to get graph with few missing keys
# Try to minimuze TK + 2*MK where
# TK is the total number of missing keys
# MK is the maximum number of missing keys for any single portal
bestgraph = None
bestlack = np.inf
bestTK = np.inf
bestMK = np.inf
sinceImprove = 0
while sinceImprove<EXTRA_SAMPLES:
b = a.copy()
sinceImprove += 1
if not maxfield.maxFields(b):
print 'Randomization failure\nThe program may work if you try again. It is more likely to work if you remove some protals.'
continue
TK = 0
MK = 0
for j in xrange(n):
keylack = max(b.in_degree(j)-b.node[j]['keys'],0)
TK += keylack
if keylack > MK:
MK = keylack
weightedlack = TK+2*MK
if weightedlack < bestlack:
sinceImprove = 0
print 'IMPROVEMENT:\n\ttotal: %s\n\tmax: %s\n\tweighted: %s'%\
(TK,MK,weightedlack)
bestgraph = b
bestlack = weightedlack
bestTK = TK
bestMK = MK
else:
print 'this time:\n\ttotal: %s\n\tmax: %s\n\tweighted: %s'%\
(TK,MK,weightedlack)
if weightedlack == 0:
print 'KEY PERFECTION'
bestlack = weightedlack
bestTK = TK
bestMK = MK
break
if all([ b.node[i]['keys'] <= b.out_degree(i) for i in xrange(n) ]):
print 'All keys used. Improvement impossible'
break
print '%s tries since improvement'%sinceImprove
if bestgraph == None:
print 'EXITING RANDOMIZATION LOOP WITHOUT SOLUTION!'
print ''
exit()
print 'Choosing plan requiring %s additional keys, max of %s from single portal'%(bestTK,bestMK)
a = bestgraph
# Attach to each edge a list of fields that it completes
for t in a.triangulation:
t.markEdgesWithFields()
agentOrder.improveEdgeOrder(a)
with open(output_directory+output_file,'w') as fout:
pickle.dump(a,fout)
else:
with open(input_file,'r') as fin:
a = pickle.load(fin)
# agentOrder.improveEdgeOrder(a)
# with open(output_directory+output_file,'w') as fout:
# pickle.dump(a,fout)
PP = PlanPrinter.PlanPrinter(a,output_directory,nagents,COLOR)
PP.keyPrep()
PP.agentKeys()
PP.planMap()
PP.agentLinks()
def main(args):
start_time = time.time()
if args.log is not None:
sys.stdout = open(args.log,'w',0)
GREEN = '#3BF256' # Actual faction text colors in the app
BLUE = '#2ABBFF'
if args.res:
color=BLUE
else:
color=GREEN
# Use google?
useGoogle = args.google
api_key = args.api_key
output_directory = args.output_dir
# add ending separator
if output_directory[-1] != os.sep:
output_directory += os.sep
# create directory if doesn't exist
if not os.path.isdir(output_directory):
os.mkdir(output_directory)
output_file = args.output_file
if output_file[-4:] != '.pkl':
output_file += ".pkl"
nagents = args.num_agents
if nagents <= 0:
print "Number of agents should be greater than zero"
raise ValueError("Number of agents should be greater than zero")
input_file = args.input_file
if input_file[-3:] != 'pkl':
# If the input file is a portal list, let's set things up
a = nx.DiGraph() # network tool
locs = [] # portal coordinates
# each line should be name;intel_link;keys
portals = pd.read_table(input_file,sep=';',
comment='#',index_col=False,
names=['name','link','keys','sbla'],
dtype=str)
portals = np.array(portals)
portals = np.array([portal for portal in portals if (isinstance(portal[0], basestring) and isinstance(portal[1], basestring))])
print "Found {0} portals in portal list.".format(len(portals))
if len(portals) < 3:
print "Error: Must have more than 2 portals!"
raise ValueError("Error: Must have more than 2 portals!")
if len(portals) > _MAX_PORTALS_:
print "Error: Portal limit is {0}".format(_MAX_PORTALS_)
raise ValueError("Error: Portal limit is {0}".format(_MAX_PORTALS_))
for num,portal in enumerate(portals):
if len(portal) < 3:
print "Error! Portal ",portal[0]," has a formatting problem."
raise ValueError("Error! Portal ",portal[0]," has a formatting problem.")
# loop over columns. Four possibilities:
# 0. First entry is always portal name
# 1. contains "pll=" it is the Intel URL
# 2. contains an intenger, it is the number of keys
# 3. contains "sbla", it is an SBLA portal
loc = None
keys = 0
sbla = False
for pind,pfoobar in enumerate(portal):
if str(pfoobar) == 'nan':
continue
if pind == 0: # This is the name
a.add_node(num)
a.node[num]['name'] = pfoobar.strip()
continue
if 'pll=' in pfoobar: # this is the URL
if loc is not None:
print "Error! Already found URL for this portal: {0}".format(portal[0])
raise ValueError("Error! Already found URL for this portal: {0}".format(portal[0]))
coords = (pfoobar.strip().split('pll='))
if len(coords) < 2:
print "Error! Portal ",portal[0]," has a formatting problem."
raise ValueError("Error! Portal ",portal[0]," has a formatting problem.")
coord_parts = coords[1].split(',')
lat = int(float(coord_parts[0]) * 1.e6)
lon = int(float(coord_parts[1]) * 1.e6)
loc = np.array([lat,lon],dtype=float)
continue
try: # this is the number of keys
keys = int(pfoobar.strip())
continue
except ValueError:
pass
try: # this is SBLA
sbla = pfoobar.strip()
sbla = (sbla.lower() == 'sbla')
continue
except ValueError:
pass
# we should never get here unless there was a bad column
print "Error: bad data value here:"
print portal
print pfoobar
raise ValueError()
if loc is None:
print "Formatting problem: {0}".format(portal[0])
raise ValueError("Formatting problem: {0}".format(portal[0]))
locs.append(loc)
a.node[num]['keys'] = keys
a.node[num]['sbla'] = sbla
if sbla:
print "{0} has SBLA".format(portal[0])
n = a.order() # number of nodes
locs = np.array(locs,dtype=float)
# Convert coords to radians, then to cartesian, then to
# gnomonic projection
locs = geometry.LLtoRads(locs)
xyz = geometry.radstoxyz(locs)
xy = geometry.gnomonicProj(locs,xyz)
for i in xrange(n):
a.node[i]['geo'] = locs[i]
a.node[i]['xyz'] = xyz[i]
a.node[i]['xy' ] = xy[i]
# Below is remnants from "random optimization" technique
"""
# EXTRA_SAMPLES attempts to get graph with few missing keys
# Try to minimuze TK + 2*MK where
# TK is the total number of missing keys
# MK is the maximum number of missing keys for any single
# portal
bestgraph = None
bestlack = np.inf
bestTK = np.inf
bestMK = np.inf
allTK = []
allMK = []
allWeights = []
sinceImprove = 0
while sinceImprove<EXTRA_SAMPLES:
b = a.copy()
sinceImprove += 1
if not maxfield.maxFields(b):
print 'Randomization failure\nThe program may work if you try again. It is more likely to work if you remove some portals.'
continue
TK = 0
MK = 0
for j in xrange(n):
keylack = max(b.in_degree(j)-b.node[j]['keys'],0)
TK += keylack
if keylack > MK:
MK = keylack
weightedlack = TK+2*MK
allTK.append(TK)
allMK.append(MK)
allWeights.append(weightedlack)
if weightedlack < bestlack:
sinceImprove = 0
print 'IMPROVEMENT:\n\ttotal: %s\n\tmax: %s\n\tweighted: %s'%\
(TK,MK,weightedlack)
bestgraph = b
bestlack = weightedlack
bestTK = TK
bestMK = MK
else:
print 'this time:\n\ttotal: %s\n\tmax: %s\n\tweighted: %s'%\
(TK,MK,weightedlack)
if weightedlack <= 0:
print 'KEY PERFECTION'
bestlack = weightedlack
bestTK = TK
bestMK = MK
break
# if num agent keys is zero, this code isn't true...
# if all([ b.node[i]['keys'] <= b.out_degree(i) for i in xrange(n) ]):
# print 'All keys used. Improvement impossible'
# break
print '%s tries since improvement'%sinceImprove
if bestgraph == None:
print 'EXITING RANDOMIZATION LOOP WITHOUT SOLUTION!'
print ''
exit()
print 'Choosing plan requiring %s additional keys, max of %s from single portal'%(bestTK,bestMK)
plt.clf()
plt.scatter(allTK,allMK,c=allWeights,marker='o')
plt.xlim(min(allTK)-1,max(allTK)+1)
plt.ylim(min(allMK)-1,max(allMK)+1)
plt.xlabel('Total keys required')
plt.ylabel('Max keys required for a single portal')
cbar = plt.colorbar()
cbar.set_label('Optimization Weighting (lower=better)')
plt.savefig(output_directory+'optimization.png')
a = bestgraph
"""
with open(output_directory+output_file,'w') as fout:
pickle.dump(a,fout)
else:
with open(input_file,'r') as fin:
a = pickle.load(fin)
# Optimize the plan to get shortest walking distance
best_plan = None
best_PP = None
best_time = 1.e9
for foobar in xrange(args.attempts):
if not args.quiet:
tdiff = time.time() - start_time
hrs = int(tdiff/3600.)
mins = int((tdiff-3600.*hrs)/60.)
secs = tdiff-3600.*hrs-60.*mins
sys.stdout.write("\r[{0:20s}] {1}% ({2}/{3} iterations) : {4:02}h {5:02}m {6:05.2f}s".\
format('#'*(20*foobar/args.attempts),
100*foobar/args.attempts,
foobar,args.attempts,
hrs,mins,secs))
b = copy.deepcopy(a)
maxfield.maxFields(b,allow_suboptimal=(not args.optimal))
# Attach to each edge a list of fields that it completes
# catch no triangulation (bad portal file?)
try:
for t in b.triangulation:
t.markEdgesWithFields()
except AttributeError:
print "Error: problem with bestgraph... no triangulation...?"
agentOrder.improveEdgeOrder(b)
PP = PlanPrinterMap.PlanPrinter(b,output_directory,nagents,useGoogle=useGoogle,
api_key=api_key,color=color)
totalTime = b.walktime+b.linktime+b.commtime
if totalTime < best_time:
best_plan = b
best_PP = copy.deepcopy(PP)
best_time = totalTime
if not args.quiet:
tdiff = time.time() - start_time
hrs = int(tdiff/3600.)
mins = int((tdiff-3600.*hrs)/60.)
secs = tdiff-3600.*hrs-60.*mins
sys.stdout.write("\r[{0:20s}] {1}% ({2}/{3} iterations) : {4:02}h {5:02}m {6:05.2f}s".\
format('#'*(20),
100,args.attempts,args.attempts,
hrs,mins,secs))
print ""
# generate plan details and map
best_PP.keyPrep()
best_PP.agentKeys()
best_PP.planMap(useGoogle=useGoogle)
best_PP.agentLinks()
# These make step-by-step instructional images
if not args.skipplot:
best_PP.animate(useGoogle=useGoogle)
best_PP.split3instruct(useGoogle=useGoogle)
print ""
print ""
print ""
print "Found best plan after {0} iterations.".format(args.attempts)
totalTime = best_plan.walktime+best_plan.linktime+best_plan.commtime
print "Total time: {0} minutes".format(int(totalTime/60. + 0.5))
print "Number of portals: {0}".format(best_PP.num_portals)
print "Number of links: {0}".format(best_PP.num_links)
print "Number of fields: {0}".format(best_PP.num_fields)
portal_ap = (125*8 + 500 + 250)*best_PP.num_portals
link_ap = 313 * best_PP.num_links
field_ap = 1250 * best_PP.num_fields
print "AP from portals capture: {0}".format(portal_ap)
print "AP from link creation: {0}".format(link_ap)
print "AP from field creation: {0}".format(field_ap)
print "Total AP: {0}".format(portal_ap+link_ap+field_ap)
tdiff = time.time() - start_time
hrs = int(tdiff/3600.)
mins = int((tdiff-3600.*hrs)/60.)
secs = tdiff-3600.*hrs-60.*mins
print "Runtime: {0:02}h {1:02}m {2:05.2f}s".format(hrs,mins,secs)
plt.close('all')
def main(args):
start_time = time.time()
if args.log is not None:
sys.stdout = open(args.log, 'w', 0)
GREEN = '#3BF256' # Actual faction text colors in the app
BLUE = '#2ABBFF'
if args.res:
color = BLUE
else:
color = GREEN
# Use google?
useGoogle = args.google
api_key = args.api_key
output_directory = args.output_dir
# add ending separator
if output_directory[-1] != os.sep:
output_directory += os.sep
# create directory if doesn't exist
if not os.path.isdir(output_directory):
os.mkdir(output_directory)
output_file = args.output_file
if output_file[-4:] != '.pkl':
output_file += ".pkl"
nagents = args.num_agents
if nagents <= 0:
print "Number of agents should be greater than zero"
raise ValueError("Number of agents should be greater than zero")
input_file = args.input_file
if input_file[-3:] != 'pkl':
# If the input file is a portal list, let's set things up
a = nx.DiGraph() # network tool
locs = [] # portal coordinates
# each line should be name;intel_link;keys
portals = pd.read_table(input_file,
sep=';',
comment='#',
index_col=False,
names=['name', 'link', 'keys', 'sbla'],
dtype=str)
portals = np.array(portals)
portals = np.array([
portal for portal in portals
if (isinstance(portal[0], basestring)
and isinstance(portal[1], basestring))
])
print "Found {0} portals in portal list.".format(len(portals))
intel_url = "https://www.ingress.com/intel?z=17&" # setup url for intel map
ll_set = False
pls = []
if len(portals) < 3:
print "Error: Must have more than 2 portals!"
raise ValueError("Error: Must have more than 2 portals!")
if len(portals) > _MAX_PORTALS_:
print "Error: Portal limit is {0}".format(_MAX_PORTALS_)
raise ValueError(
"Error: Portal limit is {0}".format(_MAX_PORTALS_))
for num, portal in enumerate(portals):
if len(portal) < 3:
print "Error! Portal ", portal[0], " has a formatting problem."
raise ValueError("Error! Portal ", portal[0],
" has a formatting problem.")
# loop over columns. Four possibilities:
# 0. First entry is always portal name
# 1. contains "pll=" it is the Intel URL
# 2. contains an intenger, it is the number of keys
# 3. contains "sbla", it is an SBLA portal
loc = None
keys = 0
sbla = False
for pind, pfoobar in enumerate(portal):
if str(pfoobar) == 'nan':
continue
if pind == 0: # This is the name
a.add_node(num)
a.node[num]['name'] = pfoobar.strip()
continue
if 'pll=' in pfoobar: # this is the URL
if loc is not None:
print "Error! Already found URL for this portal: {0}".format(
portal[0])
raise ValueError(
"Error! Already found URL for this portal: {0}".
format(portal[0]))
coords = (pfoobar.strip().split('pll='))
if len(coords) < 2:
print "Error! Portal ", portal[
0], " has a formatting problem."
raise ValueError("Error! Portal ", portal[0],
" has a formatting problem.")
coord_parts = coords[1].split(',')
lat = int(float(coord_parts[0]) * 1.e6)
lon = int(float(coord_parts[1]) * 1.e6)
pls.append(coord_parts[0] + "," + coord_parts[1])
loc = np.array([lat, lon], dtype=float)
if not ll_set:
# use coordinates from first portal to center the map
intel_url += "ll=" + coord_parts[
0] + "," + coord_parts[1] + "&"
ll_set = True
continue
try: # this is the number of keys
keys = int(pfoobar.strip())
continue
except ValueError:
pass
try: # this is SBLA
sbla = pfoobar.strip()
sbla = (sbla.lower() == 'sbla')
continue
except ValueError:
pass
# we should never get here unless there was a bad column
print "Error: bad data value here:"
print portal
print pfoobar
raise ValueError()
if loc is None:
print "Formatting problem: {0}".format(portal[0])
raise ValueError("Formatting problem: {0}".format(portal[0]))
locs.append(loc)
a.node[num]['keys'] = keys
a.node[num]['sbla'] = sbla
if sbla:
print "{0} has SBLA".format(portal[0])
n = a.order() # number of nodes
locs = np.array(locs, dtype=float)
# Convert coords to radians, then to cartesian, then to
# gnomonic projection
locs = geometry.LLtoRads(locs)
xyz = geometry.radstoxyz(locs)
xy = geometry.gnomonicProj(locs, xyz)
for i in xrange(n):
a.node[i]['geo'] = locs[i]
a.node[i]['xyz'] = xyz[i]
a.node[i]['xy'] = xy[i]
# build portal list for intel_url
intel_url += "pls="
json_output = []
for p in xrange(len(pls)):
if p < len(pls) - 1:
intel_url += pls[p] + "," + pls[p + 1]
intel_url += "_"
json_output.append({
"type":
"polyline",
"latLngs": [{
"lat": pls[p].split(',')[0],
"lng": pls[p].split(',')[1]
}, {
"lat": pls[p + 1].split(',')[0],
"lng": pls[p + 1].split(',')[1]
}],
"color":
"#a24ac3"
})
elif p == len(pls) - 1:
intel_url += pls[p] + "," + pls[0]
json_output.append({
"type":
"polyline",
"latLngs": [{
"lat": pls[p].split(',')[0],
"lng": pls[p].split(',')[1]
}, {
"lat": pls[0].split(',')[0],
"lng": pls[0].split(',')[1]
}],
"color":
"#a24ac3"
})
print intel_url
print json.dumps(json_output, indent=4)
# Below is remnants from "random optimization" technique
"""
# EXTRA_SAMPLES attempts to get graph with few missing keys
# Try to minimuze TK + 2*MK where
# TK is the total number of missing keys
# MK is the maximum number of missing keys for any single
# portal
bestgraph = None
bestlack = np.inf
bestTK = np.inf
bestMK = np.inf
allTK = []
allMK = []
allWeights = []
sinceImprove = 0
while sinceImprove<EXTRA_SAMPLES:
b = a.copy()
sinceImprove += 1
if not maxfield.maxFields(b):
print 'Randomization failure\nThe program may work if you try again. It is more likely to work if you remove some portals.'
continue
TK = 0
MK = 0
for j in xrange(n):
keylack = max(b.in_degree(j)-b.node[j]['keys'],0)
TK += keylack
if keylack > MK:
MK = keylack
weightedlack = TK+2*MK
allTK.append(TK)
allMK.append(MK)
allWeights.append(weightedlack)
if weightedlack < bestlack:
sinceImprove = 0
print 'IMPROVEMENT:\n\ttotal: %s\n\tmax: %s\n\tweighted: %s'%\
(TK,MK,weightedlack)
bestgraph = b
bestlack = weightedlack
bestTK = TK
bestMK = MK
else:
print 'this time:\n\ttotal: %s\n\tmax: %s\n\tweighted: %s'%\
(TK,MK,weightedlack)
if weightedlack <= 0:
print 'KEY PERFECTION'
bestlack = weightedlack
bestTK = TK
bestMK = MK
break
# if num agent keys is zero, this code isn't true...
# if all([ b.node[i]['keys'] <= b.out_degree(i) for i in xrange(n) ]):
# print 'All keys used. Improvement impossible'
# break
print '%s tries since improvement'%sinceImprove
if bestgraph == None:
print 'EXITING RANDOMIZATION LOOP WITHOUT SOLUTION!'
print ''
exit()
print 'Choosing plan requiring %s additional keys, max of %s from single portal'%(bestTK,bestMK)
plt.clf()
plt.scatter(allTK,allMK,c=allWeights,marker='o')
plt.xlim(min(allTK)-1,max(allTK)+1)
plt.ylim(min(allMK)-1,max(allMK)+1)
plt.xlabel('Total keys required')
plt.ylabel('Max keys required for a single portal')
cbar = plt.colorbar()
cbar.set_label('Optimization Weighting (lower=better)')
plt.savefig(output_directory+'optimization.png')
a = bestgraph
"""
with open(output_directory + output_file, 'w') as fout:
pickle.dump(a, fout)
else:
with open(input_file, 'r') as fin:
a = pickle.load(fin)
# Optimize the plan to get shortest walking distance
best_plan = None
best_PP = None
best_time = 1.e9
for foobar in xrange(args.attempts):
if not args.quiet:
tdiff = time.time() - start_time
hrs = int(tdiff / 3600.)
mins = int((tdiff - 3600. * hrs) / 60.)
secs = tdiff - 3600. * hrs - 60. * mins
sys.stdout.write("\r[{0:20s}] {1}% ({2}/{3} iterations) : {4:02}h {5:02}m {6:05.2f}s".\
format('#'*(20*foobar/args.attempts),
100*foobar/args.attempts,
foobar,args.attempts,
hrs,mins,secs))
b = copy.deepcopy(a)
maxfield.maxFields(b, allow_suboptimal=(not args.optimal))
# Attach to each edge a list of fields that it completes
# catch no triangulation (bad portal file?)
try:
for t in b.triangulation:
t.markEdgesWithFields()
except AttributeError:
print "Error: problem with bestgraph... no triangulation...?"
agentOrder.improveEdgeOrder(b)
PP = PlanPrinterMap.PlanPrinter(b,
output_directory,
nagents,
useGoogle=useGoogle,
api_key=api_key,
color=color)
totalTime = b.walktime + b.linktime + b.commtime
if totalTime < best_time:
best_plan = b
best_PP = copy.deepcopy(PP)
best_time = totalTime
b = best_plan
agentOrder.improveEdgeOrderMore(b)
# Re-run to fix the animations and stars of edges that can be done early
# (improveEdgeOrderMore may have modified the completion order)
try:
first = True
for t in b.triangulation:
t.markEdgesWithFields(clean=first)
first = False
except AttributeError:
print "Error: problem with bestgraph... no triangulation...?"
best_PP = PlanPrinterMap.PlanPrinter(b,
output_directory,
nagents,
useGoogle=useGoogle,
api_key=api_key,
color=color)
best_time = b.walktime + b.linktime + b.commtime
if not args.quiet:
tdiff = time.time() - start_time
hrs = int(tdiff / 3600.)
mins = int((tdiff - 3600. * hrs) / 60.)
secs = tdiff - 3600. * hrs - 60. * mins
sys.stdout.write("\r[{0:20s}] {1}% ({2}/{3} iterations) : {4:02}h {5:02}m {6:05.2f}s".\
format('#'*(20),
100,args.attempts,args.attempts,
hrs,mins,secs))
print ""
# generate plan details and map
best_PP.keyPrep()
best_PP.agentKeys()
best_PP.planMap(useGoogle=useGoogle)
best_PP.agentLinks()
# These make step-by-step instructional images
if not args.skipplot:
best_PP.animate(useGoogle=useGoogle)
best_PP.split3instruct(useGoogle=useGoogle)
print ""
print ""
print ""
print "Found best plan after {0} iterations.".format(args.attempts)
totalTime = best_plan.walktime + best_plan.linktime + best_plan.commtime
print "Total time: {0} minutes".format(int(totalTime / 60. + 0.5))
print "Number of portals: {0}".format(best_PP.num_portals)
print "Number of links: {0}".format(best_PP.num_links)
print "Number of fields: {0}".format(best_PP.num_fields)
portal_ap = (125 * 8 + 500 + 250) * best_PP.num_portals
link_ap = 313 * best_PP.num_links
field_ap = 1250 * best_PP.num_fields
print "AP from portals capture: {0}".format(portal_ap)
print "AP from link creation: {0}".format(link_ap)
print "AP from field creation: {0}".format(field_ap)
print "Total AP: {0}".format(portal_ap + link_ap + field_ap)
tdiff = time.time() - start_time
hrs = int(tdiff / 3600.)
mins = int((tdiff - 3600. * hrs) / 60.)
secs = tdiff - 3600. * hrs - 60. * mins
print "Runtime: {0:02}h {1:02}m {2:05.2f}s".format(hrs, mins, secs)
plt.close('all')
def main():
args = docopt.docopt(__doc__)
timestamp = datetime.datetime.now().strftime("%Y%m%d%H%M%S")
COLOR = GREEN if args['-g'] else BLUE
nagents = int(args['-n'])
if nagents <= 0:
print 'Number of agents should be positive'
exit()
# We will take many samples in an attempt to reduce number of keys to farm
# This is the number of samples to take since the last improvement
EXTRA_SAMPLES = int(args['-s'])
if EXTRA_SAMPLES not in range(1, 101):
print 'Number of extra samples must be between 1 and 100'
exit()
input_file = args['<input_file>']
name, ext = os.path.splitext(os.path.basename(input_file))
try:
os.makedirs(name)
except OSError as exception:
if exception.errno != errno.EEXIST:
raise
output_directory = name + os.sep
output_file = name + '_' + timestamp + '.pkl'
if ext != '.pkl':
a = nx.DiGraph()
np = geometry.np
locs = []
# each line should be name,intel_link,keys
with open(input_file) as fin:
text, encoding = guess_bytes(fin.read())
rows = unicodecsv.reader(text.encode('utf-8').strip().split('\n'), encoding='utf-8')
for i, row in enumerate(rows):
a.add_node(i)
a.node[i]['name'] = row[0]
url = ','.join(row[1:4]).strip()
if not url.startswith('http'):
print 'Unable to parse input file. Did you forget to put quotes around a name containing a comma?'
exit()
coords = urlparse.parse_qs(urlparse.urlparse(url).query)['pll'][0] # this could have been done the quick and dirty way, but I chose this way. It just felt right
coord_parts = coords.split(',')
lat = int(float(coord_parts[0]) * 1.e6)
lon = int(float(coord_parts[1]) * 1.e6)
locs.append(np.array([lat, lon], dtype=int)) # why does this have to be a numpy array?
if '.' in row[-1]:
a.node[i]['keys'] = 0
else:
a.node[i]['keys'] = int(row[-1])
n = a.order() # number of nodes
if n > 65:
print 'Limit of 65 portals may be optimized at once'
exit()
locs = np.array(locs, dtype=float)
# This part assumes we're working with E6 latitude-longitude data
locs = geometry.e6LLtoRads(locs)
xyz = geometry.radstoxyz(locs)
xy = geometry.gnomonicProj(locs,xyz)
for i in xrange(n):
a.node[i]['geo'] = locs[i]
a.node[i]['xyz'] = xyz [i]
a.node[i]['xy' ] = xy [i]
# EXTRA_SAMPLES attempts to get graph with few missing keys
# Try to minimuze TK + 2*MK where
# TK is the total number of missing keys
# MK is the maximum number of missing keys for any single portal
bestgraph = None
bestlack = np.inf
bestTK = np.inf
bestMK = np.inf
allTK = []
allMK = []
allWeights = []
sinceImprove = 0
while sinceImprove < EXTRA_SAMPLES:
b = a.copy()
sinceImprove += 1
if not maxfield.maxFields(b):
print 'Randomization failure\n\tThe program may work if you try again. It is more likely to work if you remove some portals.'
continue
TK = 0
MK = 0
for j in xrange(n):
keylack = max(b.in_degree(j)-b.node[j]['keys'],0)
TK += keylack
if keylack > MK:
MK = keylack
weightedlack = TK+2*MK
allTK.append(TK)
allMK.append(MK)
allWeights.append(weightedlack)
if weightedlack < bestlack:
sinceImprove = 0
print 'IMPROVEMENT:\ttotal: {}\tmax: {}\tweighted: {}\t{} tries since improvement'.format(TK, MK, weightedlack, sinceImprove)
bestgraph = b
bestlack = weightedlack
bestTK = TK
bestMK = MK
else:
print 'this time:\ttotal: {}\tmax: {}\tweighted: {}\t{} tries since improvement'.format(TK, MK, weightedlack, sinceImprove)
if weightedlack <= 0:
print 'KEY PERFECTION'
bestlack = weightedlack
bestTK = TK
bestMK = MK
break
# if num agent keys is zero, this code isn't true...
# if all([ b.node[i]['keys'] <= b.out_degree(i) for i in xrange(n) ]):
# print 'All keys used. Improvement impossible'
# break
if bestgraph == None:
print 'EXITING RANDOMIZATION LOOP WITHOUT SOLUTION!'
print ''
exit()
print 'Choosing plan requiring {} additional keys, max of {} from single portal'.format(bestTK, bestMK)
plt.clf()
plt.scatter(allTK,allMK,c=allWeights,marker='o')
plt.xlim(min(allTK)-1,max(allTK)+1)
plt.ylim(min(allMK)-1,max(allMK)+1)
plt.xlabel('Total keys required')
plt.ylabel('Max keys required for a single portal')
cbar = plt.colorbar()
cbar.set_label('Optimization Weighting (lower=better)')
plt.savefig(output_directory+'optimization.png')
a = bestgraph # remember: a = nx.DiGraph()
# Attach to each edge a list of fields that it completes
for t in a.triangulation:
t.markEdgesWithFields()
agentOrder.improveEdgeOrder(a)
with open(output_directory+output_file,'w') as fout:
pickle.dump(a, fout)
else:
with open(input_file,'r') as fin:
a = pickle.load(fin)
# agentOrder.improveEdgeOrder(a)
# with open(output_directory+output_file,'w') as fout:
# pickle.dump(a,fout)
PP = PlanPrinterMap.PlanPrinter(a, output_directory, nagents, COLOR)
PP.keyPrep()
PP.agentKeys()
PP.planMap()
PP.agentLinks()
# These make step-by-step instructional images
PP.animate()
PP.split3instruct()
print "Number of portals: {0}".format(PP.num_portals)
print "Number of links: {0}".format(PP.num_links)
print "Number of fields: {0}".format(PP.num_fields)
portal_ap = (125*8 + 500 + 250)*PP.num_portals
link_ap = 313 * PP.num_links
field_ap = 1250 * PP.num_fields
print "AP from portals capture: {0}".format(portal_ap)
print "AP from link creation: {0}".format(link_ap)
print "AP from field creation: {0}".format(field_ap)
print "Total AP: {0}".format(portal_ap+link_ap+field_ap)
def main():
args = docopt(__doc__)
np = geometry.np
#GREEN = 'g'
#BLUE = 'b'
GREEN = '#3BF256' # Actual faction text colors in the app
BLUE = '#2ABBFF'
#GREEN = (0.0 , 1.0 , 0.0 , 0.3)
#BLUE = (0.0 , 0.0 , 1.0 , 0.3)
COLOR = GREEN
if args['-b']:
COLOR = BLUE
output_directory = ''
if args['<output_directory>'] != None:
output_directory = args['<output_directory>']
if output_directory[-1] != '/':
output_directory += '/'
output_file = 'lastPlan.pkl'
if args['<output_file>'] != None:
output_file = args['<output_file>']
if not output_file[-3:] == 'pkl':
print 'WARNING: output file should end in "pkl" or you cannot use it as input later'
nagents = int(args['-n'])
if nagents <= 0:
print 'Numer of agents should be positive'
exit()
input_file = args['<input_file>']
if input_file[-3:] != 'pkl':
a = nx.DiGraph()
locs = []
# ------------- URL -------------
# name ; lat , lng ; keys
urlpat = re.compile('^([^;]*);.*ll=([-0-9\.]+),([-0-9\.]+)\s*;?\s*(\d+)?')
# name ; lat ; lng ; keys
cvspat = re.compile('^([^;]*);\s*([-0-9\.]+)\s*;\s*([-0-9\.]+)\s*;?\s*(\d+)?')
i = 0
# each line should be id,name,lat,long,keys
with open(input_file,'r') as fin:
for line in fin:
m = urlpat.match(line)
if m == None:
m = cvspat.match(line)
if m == None:
continue
g = m.groups()
# print g
a.add_node(i)
a.node[i]['name'] = g[0]
locs.append( np.array([float(g[1]),float(g[2])] ))
if g[3] == None:
a.node[i]['keys'] = 0
else:
a.node[i]['keys'] = int(g[3])
i += 1
n = a.order() # number of nodes
locs = np.array(locs,dtype=float)
# print locs
# This part assumes we're working with decimal latitude-longitude data
locs = geometry.LLtoRads(locs)
xyz = geometry.radstoxyz(locs)
xy = geometry.gnomonicProj(locs,xyz)
for i in xrange(n):
a.node[i]['geo'] = locs[i]
a.node[i]['xyz'] = xyz [i]
a.node[i]['xy' ] = xy [i]
maxfield.maxFields(a)
'''
# EXTRA_SAMPLES attempts to get graph with few missing keys
# Try to minimuze TK + 2*MK where
# TK is the total number of missing keys
# MK is the maximum number of missing keys for any single portal
bestgraph = None
bestlack = np.inf
bestTK = np.inf
bestMK = np.inf
sinceImprove = 0
while sinceImprove<EXTRA_SAMPLES:
b = a.copy()
sinceImprove += 1
if not maxfield.maxFields(b):
print 'Randomization failure\nThe program may work if you try again. It is more likely to work if you remove some protals.'
continue
TK = 0
MK = 0
for j in xrange(n):
keylack = max(b.in_degree(j)-b.node[j]['keys'],0)
TK += keylack
if keylack > MK:
MK = keylack
weightedlack = TK+2*MK
if weightedlack < bestlack:
sinceImprove = 0
print 'IMPROVEMENT:\n\ttotal: %s\n\tmax: %s\n\tweighted: %s'%\
(TK,MK,weightedlack)
bestgraph = b
bestlack = weightedlack
bestTK = TK
bestMK = MK
else:
print 'this time:\n\ttotal: %s\n\tmax: %s\n\tweighted: %s'%\
(TK,MK,weightedlack)
if weightedlack == 0:
print 'KEY PERFECTION'
bestlack = weightedlack
bestTK = TK
bestMK = MK
break
# if all([ b.node[i]['keys'] <= b.out_degree(i) for i in xrange(n) ]):
# print 'All keys used. Improvement impossible'
# break
# print '%s tries since improvement'%sinceImprove
if bestgraph == None:
print 'EXITING RANDOMIZATION LOOP WITHOUT SOLUTION!'
print ''
exit()
print 'Choosing plan requiring %s additional keys, max of %s from single portal'%(bestTK,bestMK)
a = bestgraph
'''
# Attach to each edge a list of fields that it completes
for t in a.triangulation:
t.markEdgesWithFields()
agentOrder.improveEdgeOrder(a)
with open(output_directory+output_file,'w') as fout:
pickle.dump(a,fout)
else:
with open(input_file,'r') as fin:
a = pickle.load(fin)
# agentOrder.improveEdgeOrder(a)
# with open(output_directory+output_file,'w') as fout:
# pickle.dump(a,fout)
PP = PlanPrinter.PlanPrinter(a,output_directory,nagents,COLOR)
PP.keyPrep()
PP.agentKeys()
PP.planMap()
PP.agentLinks()
# EXTRA_SAMPLES attempts to get graph with few missing keys
# Try to minimuze TK + 2*MK where
# TK is the total number of missing keys
# MK is the maximum number of missing keys for any single portal
bestgraph = None
bestlack = np.inf
bestTK = np.inf
bestMK = np.inf
sinceImprove = 0
while sinceImprove<EXTRA_SAMPLES:
b = a.copy()
if not maxfield.maxFields(b):
print 'Failed maxfield (if this happens many times, this loop could be infinite. I''ll fix this sometime)'
continue
TK = 0
MK = 0
for j in xrange(n):
keylack = max(b.in_degree(j)-b.node[j]['keys'],0)
TK += keylack
if keylack > MK:
MK = keylack
weightedlack = TK+2*MK
if weightedlack < bestlack:
sinceImprove = 0
def main():
args = docopt(__doc__)
# We will take many samples in an attempt to reduce number of keys to farm
# This is the number of samples to take since the last improvement
EXTRA_SAMPLES = 50
np = geometry.np
#GREEN = 'g'
#BLUE = 'b'
GREEN = '#3BF256' # Actual faction text colors in the app
BLUE = '#2ABBFF'
#GREEN = (0.0 , 1.0 , 0.0 , 0.3)
#BLUE = (0.0 , 0.0 , 1.0 , 0.3)
COLOR = GREEN
if args['-b']:
COLOR = BLUE
output_directory = ''
if args['<output_directory>'] != None:
output_directory = args['<output_directory>']
if output_directory[-1] != '/':
output_directory += '/'
output_file = 'lastPlan.pkl'
if args['<output_file>'] != None:
output_file = args['<output_file>']
if not output_file[-3:] == 'pkl':
print 'WARNING: output file should end in "pkl" or you cannot use it as input later'
nagents = int(args['-n'])
if nagents < 0:
print 'Number of agents should be positive'
exit()
EXTRA_SAMPLES = int(args['-s'])
if EXTRA_SAMPLES < 0:
print 'Number of extra samples should be positive'
exit()
elif EXTRA_SAMPLES > 100:
print 'Extra samples may not be more than 100'
exit()
input_file = args['<input_file>']
if input_file[-3:] != 'pkl':
a = nx.DiGraph()
locs = []
i = 0
# each line should be name,intel_link,keys
with open(input_file,'r') as fin:
for line in fin:
parts = line.split(';')
if len(parts) < 2:
break
a.add_node(i)
a.node[i]['name'] = parts[0].strip()
coords = (parts[1].split('pll='))[1]
coord_parts = coords.split(',')
lat = int(float(coord_parts[0]) * 1.e6)
lon = int(float(coord_parts[1]) * 1.e6)
locs.append( np.array([lat,lon],dtype=int) )
if len(parts) < 3:
a.node[i]['keys'] = 0
else:
a.node[i]['keys'] = int(parts[3])
i += 1
if i > 65:
print 'Limit of 65 portals may be optimized at once'
exit()
n = a.order() # number of nodes
locs = np.array(locs,dtype=float)
# This part assumes we're working with E6 latitude-longitude data
locs = geometry.e6LLtoRads(locs)
xyz = geometry.radstoxyz(locs)
xy = geometry.gnomonicProj(locs,xyz)
for i in xrange(n):
a.node[i]['geo'] = locs[i]
a.node[i]['xyz'] = xyz [i]
a.node[i]['xy' ] = xy [i]
# EXTRA_SAMPLES attempts to get graph with few missing keys
# Try to minimuze TK + 2*MK where
# TK is the total number of missing keys
# MK is the maximum number of missing keys for any single portal
bestgraph = None
bestlack = np.inf
bestTK = np.inf
bestMK = np.inf
allTK = []
allMK = []
allWeights = []
sinceImprove = 0
while sinceImprove<EXTRA_SAMPLES:
b = a.copy()
sinceImprove += 1
if not maxfield.maxFields(b):
print 'Randomization failure\nThe program may work if you try again. It is more likely to work if you remove some protals.'
continue
TK = 0
MK = 0
for j in xrange(n):
keylack = max(b.in_degree(j)-b.node[j]['keys'],0)
TK += keylack
if keylack > MK:
MK = keylack
weightedlack = TK+2*MK
allTK.append(TK)
allMK.append(MK)
allWeights.append(weightedlack)
if weightedlack < bestlack:
sinceImprove = 0
print 'IMPROVEMENT:\n\ttotal: %s\n\tmax: %s\n\tweighted: %s'%\
(TK,MK,weightedlack)
bestgraph = b
bestlack = weightedlack
bestTK = TK
bestMK = MK
else:
print 'this time:\n\ttotal: %s\n\tmax: %s\n\tweighted: %s'%\
(TK,MK,weightedlack)
if weightedlack <= 0:
print 'KEY PERFECTION'
bestlack = weightedlack
bestTK = TK
bestMK = MK
break
# if num agent keys is zero, this code isn't true...
# if all([ b.node[i]['keys'] <= b.out_degree(i) for i in xrange(n) ]):
# print 'All keys used. Improvement impossible'
# break
print '%s tries since improvement'%sinceImprove
if bestgraph == None:
print 'EXITING RANDOMIZATION LOOP WITHOUT SOLUTION!'
print ''
exit()
print 'Choosing plan requiring %s additional keys, max of %s from single portal'%(bestTK,bestMK)
plt.clf()
plt.scatter(allTK,allMK,c=allWeights,marker='o')
plt.xlim(min(allTK)-1,max(allTK)+1)
plt.ylim(min(allMK)-1,max(allMK)+1)
plt.xlabel('Total keys required')
plt.ylabel('Max keys required for a single portal')
cbar = plt.colorbar()
cbar.set_label('Optimization Weighting (lower=better)')
plt.savefig(output_directory+'optimization.png')
a = bestgraph
# Attach to each edge a list of fields that it completes
for t in a.triangulation:
t.markEdgesWithFields()
agentOrder.improveEdgeOrder(a)
with open(output_directory+output_file,'w') as fout:
pickle.dump(a,fout)
else:
with open(input_file,'r') as fin:
a = pickle.load(fin)
# agentOrder.improveEdgeOrder(a)
# with open(output_directory+output_file,'w') as fout:
# pickle.dump(a,fout)
PP = PlanPrinterMap.PlanPrinter(a,output_directory,nagents,COLOR)
PP.keyPrep()
PP.agentKeys()
PP.planMap()
PP.agentLinks()
# These make step-by-step instructional images
PP.animate()
PP.split3instruct()
print "Number of portals: {0}".format(PP.num_portals)
print "Number of links: {0}".format(PP.num_links)
print "Number of fields: {0}".format(PP.num_fields)
portal_ap = (125*8 + 500 + 250)*PP.num_portals
link_ap = 313 * PP.num_links
field_ap = 1250 * PP.num_fields
print "AP from portals capture: {0}".format(portal_ap)
print "AP from link creation: {0}".format(link_ap)
print "AP from field creation: {0}".format(field_ap)
print "Total AP: {0}".format(portal_ap+link_ap+field_ap)