def callback(self, env):
iteration = Iteration(self.run, env.iteration, self.fold)
metrics = []
for m in env.metrics:
metric = {}
metric.name = m[0]
metric.type = m[1]
metric.value = m[2]
metrics.append(metric)
iteration.record(env.params, metrics)
self.run.add_iteration(iteration)
def add_iteration_to_project(title, description, start_date, end_date, projectID):
if start_date is None: return None
if end_date is None: return None
if projectID is None: return None
try:
project = Project.objects.get(id=projectID)
except ObjectDoesNotExist:
return None
iteration = Iteration(title=title,
description=description,
start_date=start_date,
end_date=end_date,
project= project)
iteration.save()
return iteration
def add_iteration_to_project(title, description, start_date, end_date,
projectID):
if start_date is None: return None
if end_date is None: return None
if projectID is None: return None
try:
project = Project.objects.get(id=projectID)
except ObjectDoesNotExist:
return None
iteration = Iteration(title=title,
description=description,
start_date=start_date,
end_date=end_date,
project=project)
iteration.save()
return iteration
def optimize(self,
f,
X_test,
X_initial,
f_X_initial,
convergence_criteria=5,
save_iterations=True):
"""
save_iterations:
A flag to save and return all iterations of optimization ran by this tool
"""
self.log(" Optimizing...")
X = X_initial
f_X = f_X_initial
iterations = []
n_iterations = 0
# We allow for a general convergence test defined by the user
# Continue while this test is fales
while not self.is_converged(convergence_criteria, n_iterations):
self.log(" Iteration: " + str(n_iterations))
n_iterations += 1
# Evaluate the postier distribution - in particular grab
# the mean and covariance at each point in X_test
mean, covariance = self.postierier(X_test, X, f_X)
# Evaluate the width at each point in X_test
# of the postier.
width = np.atleast_2d(np.sqrt(np.diag(covariance))).T
# Using the utility function evaluate the next
# best point to evaluate
u, next_x, best_u = self.utility(X_test, X, f_X, mean, width)
# Store the details so they are accesible for later
# drawing and minipulation
if save_iterations:
iterations.append(
Iteration(mean, covariance, X, f_X, u, next_x, best_u,
X_test))
X = np.vstack((X, next_x))
self.log("Moving to position: " + str(next_x))
f_X = np.vstack((f_X, f(next_x)))
self.log("Next position has f: " + str(f_X[-1]))
self.log(" Complete.")
return iterations
def recount(json_map_path, json_change_path):
# try:
json_map_file = File(json_map_path)
json_change_file = File(json_change_path)
if json_map_file.read() != {} or json_change_file.read() != {}:
node_data = json_map_file.read().get('nodes')
link_data = json_map_file.read().get('links')
json_map = Map(node_data=node_data, link_data=link_data)
scenario = Scenario(json_map)
json_change = Iteration(scenario=scenario,
data_dict=json_change_file.read())
# новая карта
new_map = json_map.recount_iteration(
json_change.data_dict.get('changes'))
# перезапись файла
json_map_file.write(new_map)
return new_map
else:
return 'Необходимо создать исходные файлы'
def main():
# путь до excel
excel_path = os.getcwd() + '/static/json/base_info.xls'
# создание карты
map_sber = Map("Карта сбербанка")
map_sber.set_node_dict(excel_path, 1, 1, 17, 1, 2, 3)
map_sber.set_link_dict(excel_path, 1, 1, 17, 5, 21)
# dprint(map_sber.map_dict)
# dprint(len(map_sber.map_dict.get('links')))
# dprint(len(map_sber.map_dict.get('nodes')))
# создание сценария
sc = Scenario(k_map=map_sber)
# создание итераций
it_1 = Iteration(scenario=sc, description='Итерация 1')
it_2 = Iteration(scenario=sc, description='Итерация 2')
it_3 = Iteration(scenario=sc, description='Итерация 3')
dprint('Список итераций в сценарии', sc.data_list)
# блок реакций (по 2 реакции на 1 итерацию)
reac_1 = Reaction(it_1)
reac_2 = Reaction(it_1)
reac_1.set_node_change(
name='Число сотрудников банка',
value=315000,
)
reac_2.set_node_change(
name='Средняя ставка по кредитам',
value=12,
)
reac_3 = Reaction(it_2)
reac_4 = Reaction(it_2)
reac_3.set_node_change(
name='Число отделений банка',
value=13000,
)
reac_4.set_node_change(
name='Количество клиентов',
value=130000000,
)
reac_5 = Reaction(it_3)
reac_6 = Reaction(it_3)
reac_5.set_node_change(
name='Степень автоматизации процессов',
value=75,
)
reac_6.set_node_change(
name='Средняя ставка по депозитам',
value=9,
)
# добавление изменений в итерации
it_1.create_change_pack(excel_path, 2, 3, 9, column=1)
it_2.create_change_pack(excel_path, 2, 3, 9, column=2)
it_3.create_change_pack(excel_path, 2, 3, 9, column=3)
dprint('Содержание итерации 1', it_1.data_dict)
dprint('Содержание итерации 2', it_2.data_dict)
dprint('Содержание итерации 3', it_3.data_dict)
# создание json-файлов и запись в них информации
# описание путей до json
file_path_0 = os.getcwd() + '/static/json/json_files/k_map.txt'
file_path_1 = os.getcwd() + '/static/json/json_files/iteration_1.txt'
file_path_2 = os.getcwd() + '/static/json/json_files/iteration_2.txt'
file_path_3 = os.getcwd() + '/static/json/json_files/iteration_3.txt'
# пути до изменений итерации 1
file_path_11 = os.getcwd() + '/static/json/json_files/change_11.txt'
file_path_12 = os.getcwd() + '/static/json/json_files/change_12.txt'
# пути до изменений итерации 2
file_path_21 = os.getcwd() + '/static/json/json_files/change_21.txt'
file_path_22 = os.getcwd() + '/static/json/json_files/change_22.txt'
# пути до изменений итерации 3
file_path_31 = os.getcwd() + '/static/json/json_files/change_31.txt'
file_path_32 = os.getcwd() + '/static/json/json_files/change_32.txt'
# создание json-карты (1)
file_0 = File(file_path_0)
file_0.write(map_sber.map_dict)
# создание json-итераций (3)
file_1 = File(file_path_1)
file_1.write(it_1.data_dict)
file_2 = File(file_path_2)
file_2.write(it_2.data_dict)
file_3 = File(file_path_3)
file_3.write(it_3.data_dict)
# создание json-реакций (6)
file_11 = File(file_path_11)
file_11.write(reac_to_iter(reac_1.data_dict))
file_12 = File(file_path_12)
file_12.write(reac_to_iter(reac_2.data_dict))
file_21 = File(file_path_21)
file_21.write(reac_to_iter(reac_3.data_dict))
file_22 = File(file_path_22)
file_22.write(reac_to_iter(reac_4.data_dict))
file_31 = File(file_path_31)
file_31.write(reac_to_iter(reac_5.data_dict))
file_32 = File(file_path_32)
file_32.write(reac_to_iter(reac_6.data_dict))
line = line[:com_pos]
line = line.replace(' ','')
if len(line) < 2:
continue
(key,val)=line.split('=')
conf[key] = val
trello_conf.close()
return (conf['key'],conf['token'],conf['boardId'])
#--------------------------------------------------------------------------------------------------
# MAIN
#--------------------------------------------------------------------------------------------------
CHART_CARD_NAME='BURN DOWN CHART'
iteration = Iteration()
(key, token, board_id) = get_conf()
connector = TrelloClient(key, token)
board = connector.get_board(board_id)
done_list_id = get_done_list_id(board)
charge = get_remaining_charge(board, done_list_id)
iteration.log_new_charge(charge)
print(str(date.today()) + "\t" + str(charge))
# calcul du graphique mis à jour
chart_file_name = iteration.id + '.png'
make_chart.build_chart_file( chart_file_name, iteration)
# récupération de la carte du chart