def compute_max_file_length(paths):
"""
Return the integer sum of average length and standard length deviation for the given files
"""
file_lengths = [compute_file_length(path) for path in paths]
return int(
math.ceil(average(file_lengths) + standard_deviation(file_lengths)))
def test_average(self):
date_list = [datetime.timedelta(seconds=1800), datetime.timedelta(seconds=1800),
datetime.timedelta(seconds=7200), datetime.timedelta(seconds=1),
datetime.timedelta(seconds=1000), datetime.timedelta(seconds=1000),
datetime.timedelta(days=1, seconds=13600)]
result = average(date_list)
expected = date_list[0]
self.assertEqual(type(expected), type(result))
def compute_max_file_length(paths):
"""
Return the integer sum of average length and standard length deviation for the given files
"""
file_lengths = [compute_file_length(path) for path in paths]
return int(math.ceil(
average(file_lengths) + standard_deviation(file_lengths)
))
def grayscale(im, verbose=0):
res = []
w, h = float(len(im)), float(len(im[0]))
for iy, y in enumerate(im):
res.append([])
for ix, x in enumerate(y):
res[-1].append(utility.average(x))
if verbose > 0:
utility.show_bar(iy * h + ix,
w * h,
number_limit=True,
message='Grayscaling: ')
return np.array(res, dtype=float)
def response_time(self) -> dict:
"""
Calculates the average response time per college
:return: dictionary of university and average time mapping
:rtype: dict
"""
response = {}
university_response = {}
# Calling private member data from the parent class
messages = self.get_msg()
chat_groups = self.get_chat_groups()
user = self.get_user()
for msg in range(len(messages)):
# checks for the current and next message if first user is
# applicant and another is mentor then the difference of the time stamp is
# calculated.
c_id = messages[msg][2]
mentor = chat_groups[int(c_id)][1]
if self.is_applicant(messages[msg][1]):
if self.is_applicant(messages[msg + 1][1]):
logger.info('Both are applicants')
pass
if self.is_mentor(mentor):
diff = difference(messages[msg][4], messages[msg + 1][4])
if user[mentor] not in response:
response[user[mentor]] = []
response[user[mentor]].append(diff)
for i in response:
avg = average(response[i])
university_response.update({i: avg})
print("Average response time for university ({}) is: {}".format(
i, avg))
logger.info(
"Average response time for university ({}) is: {}".format(
i, avg))
return university_response
if line.startswith("Policy 2"):
parts = line.split()
policy2_data.append(float(parts[2]))
if line.startswith("Policy 3"):
parts = line.split()
policy3_data.append(float(parts[2]))
if line.startswith("Openloop"):
parts = line.split()
openloop_data.append(float(parts[1]))
if line.startswith("Naive"):
parts = line.split()
naive_data.append(float(parts[1]))
if len(naive_data) == n: break
print("Average over {} tasks:".format(len(naive_data)))
# print("{:19}: {:.2f}".format("Policy average", util.average(policy_data)))
print("{:19}: {:.2f}".format("Naive average", util.average(naive_data)))
# print("{:19}: {:.2f}".format("Openloop average", util.average(openloop_data)))
print("{:19}: {:.2f}".format("Policy 1 average", util.average(policy1_data)))
print("{:19}: {}".format(" # supermaps", noM[1]))
print("{:19}: {}".format(" # lambda calls", nol[1]))
# print("{:19}: {:.2f}".format("Policy 2 average", util.average(policy2_data)))
# print("{:19}: {}".format(" # lambda calls", nol[1]))
# print("{:19}: {:.2f}".format("Policy 3 average", util.average(policy3_data)))
# print("{:19}: {}".format(" # lambda calls", nol[3]))
print("{:19}: {:.2f}".format("Online average", util.average(online_data)))
print("{:19}: {}".format(" # supermaps", noM[0]))
print("{:19}: {}".format(" # lambda calls", nol[0]))
def average_damp(f):
return lambda x: average(x, f(x))