def cb_function(theta_flat):
global k_max, curves
cb_function.iteration += 1
from progress_bar import update_progress
update_progress(cb_function.iteration /
float(cb_function.max_iteration))
return 0
def train(p1, p2, NUMBER_OF_EPISODES):
print('\n\nTraining ' + str(NUMBER_OF_EPISODES) + ' Episodes')
for i in range(NUMBER_OF_EPISODES):
if (i + 1) % 50 == 0:
update_progress((i + 1) / NUMBER_OF_EPISODES)
board = Board(p1, p2)
board.determine_starting_player()
while not board.isFinished():
if (board.turns_taken + board.coin_flip) % 2 == 0:
action = p1.chooseMove(board)
else:
action = p2.chooseMove(board)
board.makeMove(action)
# board.print()
# update state function following episode
if board.winner == 'p1':
p1.updateValues('win')
p2.updateValues('loss')
elif board.winner == 'p2':
p1.updateValues('loss')
p2.updateValues('win')
else:
p1.updateValues('tie')
p2.updateValues('tie')
p1.saveStates()
p2.saveStates()
def csv_to_DataFrame():
name_dic = {}
header = ['Sex', 'Qty', 'Year']
print('loading DataFrames...')
dir = os.listdir("./Year_of_Birth_Data")
for progress, file in enumerate(dir,1):
update_progress(progress/len(dir))
with open("./Year_of_Birth_Data/{}".format(file), 'r') as f_in:
for line in f_in:
try:
data = line.split(',')
key = data[0]
data[2] = int(data[2])
data[3] = int(data[3][:-1]) #carraige return at the end of each line
values = data[1:]
tempdf = pd.DataFrame([values], columns = header)
except ValueError as e:
continue #offsetting for the header of every file, throws value error converting text to int
if key not in name_dic.keys():
name_dic[key] = tempdf
else:
name_dic[key] = pd.concat([name_dic[key], tempdf], ignore_index = True)
print("Done loading DataFrames")
return(name_dic)
def first_row_helper(fileReader, texts, n_entry, current_row, total_row):
first_row = fileReader.next()
[text_helper(first_row, i) for i in texts]
current_row += 1
progress_bar.update_progress(current_row / total_row)
value = add_row_to_sqlValue(first_row, n_entry, '', '(')
return [current_row, value]
def simulate_gameplay(p1, p2, NUMBER_OF_EPISODES):
play_record = [0, 0, 0]
print('\n\nSimulating ' + str(NUMBER_OF_EPISODES) + ' Episodes')
for i in range(NUMBER_OF_EPISODES):
if (i + 1) % 50 == 0:
update_progress((i + 1) / NUMBER_OF_EPISODES)
board = Board(p1, p2)
board.determine_starting_player()
while not board.isFinished():
if (board.turns_taken + board.coin_flip) % 2 == 0:
action = p1.chooseMove(board)
else:
action = p2.chooseMove(board)
board.makeMove(action)
if board.winner == 'p1':
play_record[0] += 1
elif board.winner == 'p2':
play_record[1] += 1
else:
play_record[2] += 1
agent_rating = (play_record[0] + 0.2 * play_record[2]) / NUMBER_OF_EPISODES
formatted_agent_rating = f"{agent_rating:.4f}"
print('Record: ' + str(play_record))
print('Agent Rating: ' + formatted_agent_rating)
def csv_to_DataFrame():
header = ['Sex', 'Year', 'Name', 'Qty']
print('loading DataFrames...')
directory = os.listdir("./Names_By_State")
states_dic = {}
for progress, file in enumerate(directory, 1):
update_progress(progress / len(directory))
with open("./Names_By_State/{}".format(file), 'r') as f_in:
for line in f_in:
try:
data = line.split(',')
key = data[0]
data[2] = int(data[2]) #year
data[4] = int(data[4][:-1]) #qty
tempdf = pd.DataFrame([data[1:]], columns=header)
except ValueError as e:
print("Error creating DF.... Investigate")
if key not in states_dic.keys():
states_dic[key] = tempdf
else:
states_dic[key] = pd.concat([states_dic[key], tempdf],
ignore_index=True)
print("Done loading DataFrames")
return (states_dic)
def model_pereod(quant_el,
quant_it,
d=0.4,
a=0.2,
one_rand=0.3,
end_rand=0.5,
alpha=1,
start=1):
elements = np.zeros((quant_el, quant_it))
# print(elements)
if start == 1:
for i in range(quant_el):
elements[i][0] = random.uniform(
one_rand, end_rand) # задаем случайные начальные условия
elif start == 0:
for i in range(
int(quant_el / 2 - 10),
int(quant_el / 2 +
10)): # задаем начальные условия типа "прямоугольник"
elements[i][0] = .5
elif start == 2:
f = open('mass.txt')
matr = np.loadtxt(f)
for i in range(100000, quant_el + 100000):
print(i)
elements[i - 100000][0] = matr[1][i]
elif start == 3:
f = open('mass_static.txt')
matr = np.loadtxt(f)
for i in range(100000, quant_el + 1000):
elements[i - 100000][0] = matr[1][i]
for i in range(quant_it - 1):
progress_bar.update_progress(i / (quant_it - 1), 'вычисление системы')
for j in range(quant_el):
if j == 0:
elements[j][i + 1] = function.next_iter(
a, d, elements[quant_el - 1][i], elements[j][i],
elements[j + 1][i], alpha)
elif j == quant_el - 1:
elements[j][i + 1] = function.next_iter(
a, d, elements[j - 1][i], elements[j][i], elements[0][i],
alpha)
else:
elements[j][i + 1] = function.next_iter(
a, d, elements[j - 1][i], elements[j][i],
elements[j + 1][i], alpha)
print('1')
return elements
def line_plot(start, alpha, d, beta, N, quant_it):
elemets = realize(alpha, d, beta, N, quant_it, start)
number = np.arange(1, N + 1, 1)
ax = plt.figure(figsize=(8, 6))
for i in range(0, quant_it - start):
progress_bar.update_progress((i) / (quant_it - start),
'Построение графика')
for j in range(N):
plt.scatter(elemets[j][i], 0, s=1, c=j, vmin=1, vmax=N)
maxim = elemets.max()
minim = elemets.min()
cb = plt.colorbar()
#plt.ylabel([-.001,.001])
return maxim - minim
def line_plot(start, alpha, d, beta, N, quant_it):
elemets = realize(alpha, d, beta, N, quant_it, start)
number = np.arange(1, N + 1, 1)
ax = plt.figure(figsize=(8, 6))
for i in range(0, quant_it - start):
progress_bar.update_progress((i) / (quant_it - start),
'Построение графика')
for j in range(N):
plt.scatter(elemets[j][i], 0, s=1, c=j, vmin=1, vmax=N)
maxim = elemets.max()
minim = elemets.min()
cb = plt.colorbar()
#plt.ylabel([-.001,.001])
plt.plot([maxim, maxim], [-.00001, .00001], color='black')
plt.plot([minim, minim], [-.00001, .00001],
color='black',
label='длинна интревала: ' + str(maxim - minim))
plt.legend()
plt.yticks([])
cb.set_label('Номер элемента')
plt.xlabel('Значение на элементе')
def push_helper(fileReader, texts, n_entry, current_row, total_row):
#for row in fileReader:
value = ''
try:
re = first_row_helper(fileReader, texts, n_entry, current_row,
total_row)
current_row = re[0]
value = re[1]
#print 'push helper first value: '+value
for i in xrange(N_VALUE):
row = fileReader.next()
current_row += 1
progress_bar.update_progress(current_row / total_row)
[text_helper(row, i) for i in texts]
# for i in texts:
# row[i]='\''+row[i]+'\''
value = add_row_to_sqlValue(row, n_entry, value)
#print 'push helper 2 value: '+value
return [current_row, value]
except StopIteration:
current_row = -1
return [current_row, value]
def upload(state_dic):
total_states = len(state_dic.keys())
connection, metadata, engine = connect()
db_tables = set(metadata.tables.keys())
print("Loading DataFrames to Database Tables")
for progress, k in enumerate(state_dic.keys(), 1):
if k in db_tables:
update_progress(progress / total_states)
continue
try:
state_dic[k].to_sql(k, con=engine, if_exists='replace')
except exc.SQLAlchemyError as e:
print("****Couldn't insert {0} table. Investigate!****".format(k))
update_progress(progress / total_states)
state_dic[k] = ''
print("Done uploading state DataFrames to the Database")
minim = elemets.min()
cb = plt.colorbar()
#plt.ylabel([-.001,.001])
plt.plot([maxim, maxim], [-.00001, .00001], color='black')
plt.plot([minim, minim], [-.00001, .00001],
color='black',
label='длинна интревала: ' + str(maxim - minim))
plt.legend()
plt.yticks([])
cb.set_label('Номер элемента')
plt.xlabel('Значение на элементе')
N = 100
alpha = 0.2
d = .2
beta = 0
start, quant_it = 60000, 62000
var_d = np.arange(0.2, .484, 0.005)
for i in range(len(var_d)):
progress_bar.update_progress((i) / (len(var_d)), 'PROGRESS')
d = var_d[i]
# var = par(alpha, d, beta, N, quant_it)
line_plot(start, alpha, d, beta, N, quant_it)
plt.title('d = ' + str(d))
#plt.grid(True)
plt.savefig('/home/mechislab/line/img' + str(i + 1))
plt.close()
def test():
for i in range(11):
update_progress(i, 10)
time.sleep(1)
def cb_function( theta_flat ):
global k_max,curves
cb_function.iteration += 1
from progress_bar import update_progress
update_progress( cb_function.iteration / float(cb_function.max_iteration) )
return 0
# for m in range(5, 44):
m = 0
while d < (f[44 + 1] + f[44]) / 2:
m += 1
d += 0.00005
all_m = m
m = 0
d = start
while d < (f[44 + 1] + f[44]) / 2:
m += 1
if d == start:
t1 = time.time()
if d == start + 1 * 0.00005:
t2 = time.time()
print('всего потребуется минут', (t2 - t1) / 60 * all_m)
progress_bar.update_progress((d - start) / (close - start), 'ПРОГРЕСС')
# d = (f[m + 1] + f[m]) / 2
matrix = segment_function.segment(
quant_el,
quant_it,
quant_start_one,
quant_start_end,
value_start,
a=a,
d=d,
alpha=alpha,
beta=beta,
nonlinear=nonlinear
) # вызываем функцию, которая возвращает матрицу с реализацией
# f = open ('spatial_segment_info.txt', 'w')
#fil.write(str(matrix[40]))
#fil.close()
#fil1 = open('matrix', 'w')
#fil1.write(str(matrix[55]))
#fil1.close()
# системыc
maxim = matrix.max()
minim = matrix.min()
plt.figure(figsize=(8, 6))
ax = plt.subplot(2, 1, 1)
for t in range(quant_el):
# color = [str (item / 255.) for item in matrix[i]]
progress_bar.update_progress(t / quant_el, 'построение графика')
plt.scatter(np.arange(quant_it), t * np.ones(quant_it), cmap=cm.jet, s=1, c=matrix[t], vmin=minim,
vmax=maxim) # строим график, где цветом отображаем амплитуду
cb = plt.colorbar()
cb.set_label('значение элемента')
# cb.set_ticklabels('one')
plt.xlabel('n - дискретное время')
plt.xlim(0, quant_it - 15)
plt.ylabel('$U_j$ - номер элемента')
# plt.title('отрезок: ' + str(quant_el) + ' элементов' + ' начальные условия задаются: \n с ' + str(
# quant_start_one) + ' по ' + str(quant_start_end) + ' элементы со значением: ' + str(value_start) + '\n
# параметры: ' + 'd = ' + str(d) + r'$, \alpha = $' + str(alpha) + ', a = ' + str(a))
if nonlinear == 'cube':
def upload(name_dic):
year_list = [i for i in range(1880,2018)]
total_keys = len(name_dic.keys())
total_years = len(year_list)
connection, metadata, engine = connect()
db_tables = set(metadata.tables.keys())
if "Names" in db_tables:
print("Names Table already exists")
name_table = Table('Names', metadata)
else:
name_table = Table('Names', metadata,
Column('id', Integer, primary_key=True),
Column('name', String(30)))
if "Years" in db_tables:
print("Years Table already exists")
year_table = Table('Years', metadata)
else:
year_table = Table('Years', metadata,
Column('id', Integer, primary_key=True),
Column('year', Integer))
try:
metadata.create_all(engine)
except exc.SQLAlchemyError as e:
print("Tables already existed")
print("Loading DataFrames to Database Tables")
for progress,k in enumerate(name_dic.keys(), 1):
if k in db_tables:
update_progress(progress/total_keys)
continue
try:
name_dic[k].to_sql(k, con=engine, if_exists='replace')
except exc.SQLAlchemyError as e:
print("****Couldn't insert {0} table. Investigate!****".format(k))
ins = name_table.insert().values(name=k)
connection.execute(ins)
update_progress(progress/total_keys)
name_dic[k] = ''
print("Loading Years to Year table")
for progress, y in enumerate(year_list, 1):
ins = year_table.insert().values(year=y)
connection.execute(ins)
update_progress(progress/total_years)
connection.close()
print("Done Loading Database")
