本文整理汇总了Python中statistics.median_low方法的典型用法代码示例。如果您正苦于以下问题：Python statistics.median_low方法的具体用法？Python statistics.median_low怎么用？Python statistics.median_low使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类statistics的用法示例。
在下文中一共展示了statistics.median_low方法的8个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: get_avg
# 需要导入模块: import statistics [as 别名]
# 或者: from statistics import median_low [as 别名]
def get_avg(metrics: List):
return median_low(metrics) 示例2: on_peer_response_append
# 需要导入模块: import statistics [as 别名]
# 或者: from statistics import median_low [as 别名]
def on_peer_response_append(self, peer, msg):
"""Handle peer response to append_entries.
If successful RPC, try to commit new entries.
If RPC unsuccessful, backtrack."""
if msg['success']:
self.matchIndex[peer] = msg['matchIndex']
self.nextIndex[peer] = msg['matchIndex'] + 1
self.matchIndex[self.volatile['address']] = self.log.index
self.nextIndex[self.volatile['address']] = self.log.index + 1
index = statistics.median_low(self.matchIndex.values())
self.log.commit(index)
self.send_client_append_response()
else:
self.nextIndex[peer] = max(0, self.nextIndex[peer] - 1) 示例3: test_even_ints
# 需要导入模块: import statistics [as 别名]
# 或者: from statistics import median_low [as 别名]
def test_even_ints(self):
# Test median_low with an even number of ints.
data = [1, 2, 3, 4, 5, 6]
assert len(data)%2 == 0
self.assertEqual(self.func(data), 3) 示例4: test_even_fractions
# 需要导入模块: import statistics [as 别名]
# 或者: from statistics import median_low [as 别名]
def test_even_fractions(self):
# Test median_low works with an even number of Fractions.
F = Fraction
data = [F(1, 7), F(2, 7), F(3, 7), F(4, 7), F(5, 7), F(6, 7)]
assert len(data)%2 == 0
random.shuffle(data)
self.assertEqual(self.func(data), F(3, 7)) 示例5: test_even_decimals
# 需要导入模块: import statistics [as 别名]
# 或者: from statistics import median_low [as 别名]
def test_even_decimals(self):
# Test median_low works with an even number of Decimals.
D = Decimal
data = [D('1.1'), D('2.2'), D('3.3'), D('4.4'), D('5.5'), D('6.6')]
assert len(data)%2 == 0
random.shuffle(data)
self.assertEqual(self.func(data), D('3.3')) 示例6: sortSubListsAndMedian
# 需要导入模块: import statistics [as 别名]
# 或者: from statistics import median_low [as 别名]
def sortSubListsAndMedian(A):
sortedList = []
medianList = []
for smallList in A:
sortedList.append(sorted(smallList))
medianList.append(statistics.median_low(smallList))
return sortedList, medianList 示例7: MEDIAN_LOW
# 需要导入模块: import statistics [as 别名]
# 或者: from statistics import median_low [as 别名]
def MEDIAN_LOW(df, n, price='Close'):
"""
Low median of data
Returns: list of floats = jhta.MEDIAN_LOW(df, n, price='Close')
"""
median_low_list = []
if n == len(df[price]):
start = None
for i in range(len(df[price])):
if df[price][i] != df[price][i]:
median_low = float('NaN')
else:
if start is None:
start = i
end = i + 1
median_low = statistics.median_low(df[price][start:end])
median_low_list.append(median_low)
else:
for i in range(len(df[price])):
if i + 1 < n:
median_low = float('NaN')
else:
start = i + 1 - n
end = i + 1
median_low = statistics.median_low(df[price][start:end])
median_low_list.append(median_low)
return median_low_list 示例8: test_secint
# 需要导入模块: import statistics [as 别名]
# 或者: from statistics import median_low [as 别名]
def test_secint(self):
secint = mpc.SecInt()
y = [1, 3, -2, 3, 1, -2, -2, 4] * 5
random.shuffle(y)
x = list(map(secint, y))
self.assertEqual(mpc.run(mpc.output(mean(x))), round(statistics.mean(y)))
self.assertEqual(mpc.run(mpc.output(variance(x))), round(statistics.variance(y)))
self.assertEqual(mpc.run(mpc.output(variance(x, mean(x)))), round(statistics.variance(y)))
self.assertEqual(mpc.run(mpc.output(stdev(x))), round(statistics.stdev(y)))
self.assertEqual(mpc.run(mpc.output(pvariance(x))), round(statistics.pvariance(y)))
self.assertEqual(mpc.run(mpc.output(pstdev(x))), round(statistics.pstdev(y)))
self.assertEqual(mpc.run(mpc.output(mode(x))), round(statistics.mode(y)))
self.assertEqual(mpc.run(mpc.output(median(x))), round(statistics.median(y)))
self.assertEqual(mpc.run(mpc.output(median_low(x))), round(statistics.median_low(y)))
self.assertEqual(mpc.run(mpc.output(median_high(x))), round(statistics.median_high(y)))