import sys

args = sys.argv

# 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

if len(args) < 3:

print '''

-----Introduction-----

This is for Ingress. If you don't know what that is, you're lost.

-----Usage-----

>> python makePlan.py agent_count input_file [output_directory] [output_file]

agent_count: Number of agents for which to make a plan

input_file: One of two types of files:

.csv formatted as portal name,latE6,lngE6,keys

portal name should not contain commas

latE6 and lngE6 should be the portal's global coordinates

E6 means times 10^6 (no decimal)

e.g. the Big Ben portal is at 51500775,-124466

keys is the number of keys you have for the portal

.pkl an output from a previous run of this program

this can be used to make the same plan with a different number of agents

output_directory: directory in which to put all output

default is the working directory

output_file: name for a .pkl file containing information on the plan

if you use this for the input file, the same plan will be produced with the number of agents you specify

default: "lastPlan.pkl"

'''

exit()

import networkx as nx

from lib import maxfield,PlanPrinter,geometry,agentOrder

np = geometry.np

import pickle

if len(args) < 4:

output_directory = ''

else:

output_directory = args[3]

if output_directory[-1] != '/':

output_directory += '/'

if len(args) < 5:

output_file = 'lastPlan.pkl'

else:

output_file = args[4]

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[1])

if nagents < 0:

print 'Numer of agents should be positive'

exit()

input_file = args[2]

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(',')

a.add_node(i)

a.node[i]['name'] = parts[0].strip()

if len(parts) == 0:

break

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()

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

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

sinceImprove += 1

print '%s tries since improvement'%sinceImprove

if bestgraph == None:

print 'EXITING RANDOMIZATION LOOP WITHOUT SOLUTION!'

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)

PP.keyPrep()

PP.agentKeys()

PP.planMap()

PP.agentLinks()

#PP.animate()

#PP.split3instruct()