#run statistics and add to a cst file
import readMap
import dfs
import analyse
import hill_solve
import sim_an_search

loops = 100
dic = {}
best_costs = 1000
worst_costs = 0
#for l in range(loops):
#map = readMap.readStates("UnitedStates.txt")
#print(analyse.analyse_adjacent_states(map))
signals = ['zA', 'zB', 'zC', 'zD', 'zE', 'zF', 'zG']
costs = {'zA':19, 'zB':20, 'zC':21, 'zD':23, 'zE':36, 'zF':37, 'zG':38}
algos = {sim_an_search.sigmoidal_temperature:[],sim_an_search.sigmoidal_temperature_2:[],sim_an_search.sigmoidal_temperature_3:[],
         sim_an_search.double_sigmoidal_temperature:[], sim_an_search.sinus_double_sigmoidal_temperature:[],
         sim_an_search.sinus_temperature:[], sim_an_search.linear_temperature:[], sim_an_search.sinus_linear_temperature:[]}

with open("sinsigmoid.txt", 'w') as text:
    text.write('sinus_sigmoidal_temperature')
    text.write(',')
    for x in range(loops):
        map = readMap.read_complete_map("UnitedStatesdfs.txt")
        sim_an_search.stats_climber(map, costs, signals, 200000, 5, 0.01, sim_an_search.sinus_sigmoidal_temperature)
        freq = analyse.signal_frequentie(map)
        hill_costs = analyse.get_cost(freq, costs)
        text.write(str(hill_costs))
        text.write(',')
        print(str(x))
    text.write('\n')








ebf3e690f95e99bad8d3e0712c0d6021d6e721a0
<mask token>

<mask token>
with open('sinsigmoid.txt', 'w') as text:
    text.write('sinus_sigmoidal_temperature')
    text.write(',')
    for x in range(loops):
        map = readMap.read_complete_map('UnitedStatesdfs.txt')
        sim_an_search.stats_climber(map, costs, signals, 200000, 5, 0.01,
            sim_an_search.sinus_sigmoidal_temperature)
        freq = analyse.signal_frequentie(map)
        hill_costs = analyse.get_cost(freq, costs)
        text.write(str(hill_costs))
        text.write(',')
        print(str(x))
    text.write('\n')

<mask token>
loops = 100
dic = {}
best_costs = 1000
worst_costs = 0
signals = ['zA', 'zB', 'zC', 'zD', 'zE', 'zF', 'zG']
costs = {'zA': 19, 'zB': 20, 'zC': 21, 'zD': 23, 'zE': 36, 'zF': 37, 'zG': 38}
algos = {sim_an_search.sigmoidal_temperature: [], sim_an_search.
    sigmoidal_temperature_2: [], sim_an_search.sigmoidal_temperature_3: [],
    sim_an_search.double_sigmoidal_temperature: [], sim_an_search.
    sinus_double_sigmoidal_temperature: [], sim_an_search.sinus_temperature:
    [], sim_an_search.linear_temperature: [], sim_an_search.
    sinus_linear_temperature: []}
with open('sinsigmoid.txt', 'w') as text:
    text.write('sinus_sigmoidal_temperature')
    text.write(',')
    for x in range(loops):
        map = readMap.read_complete_map('UnitedStatesdfs.txt')
        sim_an_search.stats_climber(map, costs, signals, 200000, 5, 0.01,
            sim_an_search.sinus_sigmoidal_temperature)
        freq = analyse.signal_frequentie(map)
        hill_costs = analyse.get_cost(freq, costs)
        text.write(str(hill_costs))
        text.write(',')
        print(str(x))
    text.write('\n')

import readMap
import dfs
import analyse
import hill_solve
import sim_an_search
loops = 100
dic = {}
best_costs = 1000
worst_costs = 0
signals = ['zA', 'zB', 'zC', 'zD', 'zE', 'zF', 'zG']
costs = {'zA': 19, 'zB': 20, 'zC': 21, 'zD': 23, 'zE': 36, 'zF': 37, 'zG': 38}
algos = {sim_an_search.sigmoidal_temperature: [], sim_an_search.
    sigmoidal_temperature_2: [], sim_an_search.sigmoidal_temperature_3: [],
    sim_an_search.double_sigmoidal_temperature: [], sim_an_search.
    sinus_double_sigmoidal_temperature: [], sim_an_search.sinus_temperature:
    [], sim_an_search.linear_temperature: [], sim_an_search.
    sinus_linear_temperature: []}
with open('sinsigmoid.txt', 'w') as text:
    text.write('sinus_sigmoidal_temperature')
    text.write(',')
    for x in range(loops):
        map = readMap.read_complete_map('UnitedStatesdfs.txt')
        sim_an_search.stats_climber(map, costs, signals, 200000, 5, 0.01,
            sim_an_search.sinus_sigmoidal_temperature)
        freq = analyse.signal_frequentie(map)
        hill_costs = analyse.get_cost(freq, costs)
        text.write(str(hill_costs))
        text.write(',')
        print(str(x))
    text.write('\n')

#run statistics and add to a cst file
import readMap
import dfs
import analyse
import hill_solve
import sim_an_search

loops = 100
dic = {}
best_costs = 1000
worst_costs = 0
#for l in range(loops):
#map = readMap.readStates("UnitedStates.txt")
#print(analyse.analyse_adjacent_states(map))
signals = ['zA', 'zB', 'zC', 'zD', 'zE', 'zF', 'zG']
costs = {'zA':19, 'zB':20, 'zC':21, 'zD':23, 'zE':36, 'zF':37, 'zG':38}
algos = {sim_an_search.sigmoidal_temperature:[],sim_an_search.sigmoidal_temperature_2:[],sim_an_search.sigmoidal_temperature_3:[],
         sim_an_search.double_sigmoidal_temperature:[], sim_an_search.sinus_double_sigmoidal_temperature:[],
         sim_an_search.sinus_temperature:[], sim_an_search.linear_temperature:[], sim_an_search.sinus_linear_temperature:[]}

with open("sinsigmoid.txt", 'w') as text:
    text.write('sinus_sigmoidal_temperature')
    text.write(',')
    for x in range(loops):
        map = readMap.read_complete_map("UnitedStatesdfs.txt")
        sim_an_search.stats_climber(map, costs, signals, 200000, 5, 0.01, sim_an_search.sinus_sigmoidal_temperature)
        freq = analyse.signal_frequentie(map)
        hill_costs = analyse.get_cost(freq, costs)
        text.write(str(hill_costs))
        text.write(',')
        print(str(x))
    text.write('\n')







