def menu():
keep_going = 'y'
while (keep_going == 'y'):
print("Menu")
print("1. Calculator")
print("2. Number Guesser")
print("3. Pop Quiz")
print("4. Read File")
print("5. Exit")
choice = int(input('Please enter your choice: '))
if choice == 1:
calc.ACmenu()
elif choice == 2:
numGuess.game()
elif choice == 3:
memory.memBank()
elif choice == 4:
readFile.read()
elif choice == 5:
print("Exiting")
keep_going = 'n'
else:
print(
'\nChoice was not valid. Please choose a valid option between 1 - 3.'
)
def import_beams():
global beam_g1
beam_g1 = read('FF_11.ffe')
beam_g2 = read('FF_inf_dense.ffe')
py.plot(10**(beam_g1 / 10) / (max(10**(beam_g1 / 10))))
py.plot(10**(beam_g2 / 10) / (max(10**(beam_g2 / 10))))
def newPop(): #формирование новой популяции
global oldpop
spop = sorted(oldpop + newpop, key=lambda x: x[1])
spop = spop[::-1]
oldpop = spop[0:200]
def start(x): #объединяем функции
global oldpop
oldpop = []
global newpop
newpop = []
global things
things = []
startPop()
fitness()
for k in range(0, x):
selection()
newPop()
return oldpop[0]
oldpop = []
newpop = []
pcount = 200
things = []
readFile.read()
res = start(100)
print(res[1], res[0])
#!/home/md98/bamboo_env/bin python
# -*- coding: UTF-8 -*-
import readFile
import scaling
if __name__ == '__main__':
text_file_directory = '../data/'
for text_file_number in range(40491, 37840, -1):
text_file_name = str(text_file_number) + '.txt'
text_file = text_file_directory + text_file_name
print(text_file)
readFile.read(text_file)
output = open('nouns/' + str(text_file_number) + str('.txt'), "a")
for noun in scaling.getFilteredData(readFile.data,
scaling.filter_pronouns):
output.write(noun + " ")
output.close()
from readFile import read
import os
# Get paths
dir_name = os.path.dirname(__file__)
folder = os.path.join(dir_name, 'data/')
files = os.listdir(folder)
files = [file for file in files if file[-4:] == '.bn4']
# Declare parameters
binSize = 400
channels = 8
maxLength = 720000 # in 100ns unith
# Iterate through data
for file in files:
path = folder + file
read(path, binSize, channels, maxLength)
from readFile import read
from initialize import initialize_q_table
import random
import numpy
labirint = read()
MATRIX_SIZE = len(labirint[0])
SUCCESS_EXIT = (0,0)
BUST_EXIT = (1,0)
START_POS = (3,3)
LEARNING_RATE = 0.7
PENALTY = 0.05
a = ['up','down','right','left']
DIRECTIONS = {'up':(1,0),'down':(-1,0),'right':(0,1),'left':(0,-1)}
NR_STEPS = 500
NR_EPISODES = 30
epsilon = 1
(q,na) = initialize_q_table(MATRIX_SIZE)
def qLearning(qStart,dim):
action = ''
episodes = NR_EPISODES
eps = epsilon
while episodes != 0:
