本文整理匯總了Python中math.expm1方法的典型用法代碼示例。如果您正苦於以下問題：Python math.expm1方法的具體用法？Python math.expm1怎麽用？Python math.expm1使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類math的用法示例。
在下文中一共展示了math.expm1方法的7個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: calculate_sync_order
# 需要導入模塊: import math [as 別名]
# 或者: from math import expm1 [as 別名]
def calculate_sync_order(oscillator_phases):
"""!
@brief Calculates level of global synchronization (order parameter) for input phases.
@details This parameter is tend 1.0 when the oscillatory network close to global synchronization and it tend to 0.0 when
desynchronization is observed in the network.
@param[in] oscillator_phases (list): List of oscillator phases that are used for level of global synchronization.
@return (double) Level of global synchronization (order parameter).
@see calculate_order_parameter()
"""
exp_amount = 0.0
average_phase = 0.0
for phase in oscillator_phases:
exp_amount += math.expm1(abs(1j * phase))
average_phase += phase
exp_amount /= len(oscillator_phases)
average_phase = math.expm1(abs(1j * (average_phase / len(oscillator_phases))))
return abs(average_phase) / abs(exp_amount) 示例2: test_pure_python_math_module
# 需要導入模塊: import math [as 別名]
# 或者: from math import expm1 [as 別名]
def test_pure_python_math_module(self):
vals = [1, -.5, 1.5, 0, 0.0, -2, -2.2, .2]
# not being tested: math.asinh, math.atanh, math.lgamma, math.erfc, math.acos
def f():
functions = [
math.sqrt, math.cos, math.sin, math.tan, math.asin, math.atan,
math.acosh, math.cosh, math.sinh, math.tanh, math.ceil,
math.erf, math.exp, math.expm1, math.factorial, math.floor,
math.log, math.log10, math.log1p
]
tr = []
for idx1 in range(len(vals)):
v1 = vals[idx1]
for funIdx in range(len(functions)):
function = functions[funIdx]
try:
tr = tr + [function(v1)]
except ValueError as ex:
pass
return tr
r1 = self.evaluateWithExecutor(f)
r2 = f()
self.assertGreater(len(r1), 100)
self.assertTrue(numpy.allclose(r1, r2, 1e-6)) 示例3: _log1mexp
# 需要導入模塊: import math [as 別名]
# 或者: from math import expm1 [as 別名]
def _log1mexp(x):
"""Numerically stable computation of log(1-exp(x))."""
if x < -1:
return math.log1p(-math.exp(x))
elif x < 0:
return math.log(-math.expm1(x))
elif x == 0:
return -np.inf
else:
raise ValueError("Argument must be non-positive.") 示例4: stop
# 需要導入模塊: import math [as 別名]
# 或者: from math import expm1 [as 別名]
def stop(self):
super(Returns, self).stop()
if not self._fundmode:
self._value_end = self.strategy.broker.getvalue()
else:
self._value_end = self.strategy.broker.fundvalue
# Compound return
try:
nlrtot = self._value_end / self._value_start
except ZeroDivisionError:
rtot = float('-inf')
else:
if nlrtot < 0.0:
rtot = float('-inf')
else:
rtot = math.log(nlrtot)
self.rets['rtot'] = rtot
# Average return
self.rets['ravg'] = ravg = rtot / self._tcount
# Annualized normalized return
tann = self.p.tann or self._TANN.get(self.timeframe, None)
if tann is None:
tann = self._TANN.get(self.data._timeframe, 1.0) # assign default
if ravg > float('-inf'):
self.rets['rnorm'] = rnorm = math.expm1(ravg * tann)
else:
self.rets['rnorm'] = rnorm = ravg
self.rets['rnorm100'] = rnorm * 100.0 # human readable % 示例5: expm1
# 需要導入模塊: import math [as 別名]
# 或者: from math import expm1 [as 別名]
def expm1(x=('FloatPin', 0.1)):
'''Return `e**x - 1`. For small floats `x`, the subtraction in `exp(x) - 1` can result in a significant loss of precision.'''
return math.expm1(x) 示例6: log1m_exp
# 需要導入模塊: import math [as 別名]
# 或者: from math import expm1 [as 別名]
def log1m_exp(val):
"""Numerically stable implementation of `log(1 - exp(val))`."""
if val >= 0.:
return nan
elif val > LOG_2:
return log(-expm1(val))
else:
return log1p(-exp(val)) 示例7: expm1
# 需要導入模塊: import math [as 別名]
# 或者: from math import expm1 [as 別名]
def expm1(node): return merge([node], math.expm1)