我们从Python开源项目中，提取了以下50个代码示例，用于说明如何使用cmath.log()。
def powm1(ctx, x, y): mag = ctx.mag one = ctx.one w = x**y - one M = mag(w) # Only moderate cancellation if M > -8: return w # Check for the only possible exact cases if not w: if (not y) or (x in (1, -1, 1j, -1j) and ctx.isint(y)): return w x1 = x - one magy = mag(y) lnx = ctx.ln(x) # Small y: x^y - 1 ~ log(x)*y + O(log(x)^2 * y^2) if magy + mag(lnx) < -ctx.prec: return lnx*y + (lnx*y)**2/2 # TODO: accurately eval the smaller of the real/imag part return ctx.sum_accurately(lambda: iter([x**y, -1]), 1)
def _digamma_complex(x): if not x.imag: return complex(_digamma_real(x.real)) if x.real < 0.5: x = 1.0-x s = pi*cotpi(x) else: s = 0.0 while abs(x) < 10.0: s -= 1.0/x x += 1.0 x2 = x**-2 t = x2 for c in _psi_coeff: s -= c*t if abs(t) < 1e-20: break t *= x2 return s + cmath.log(x) - 0.5/x
def ei_taylor(z, _e1=False): s = t = z k = 2 while 1: t = t*z/k term = t/k if abs(term) < 1e-17: break s += term k += 1 s += euler if _e1: s += log(-z) else: if type(z) is float or z.imag == 0.0: s += math_log(abs(z)) else: s += cmath.log(z) return s
def repay(self, sct): """ used only after the activation of CDT contract repay the loan, which converts SCT to DCt :param sct: amount of SCT need to be repaid :return: cdt """ # used only after the activation of CDT contract if not self.is_cdt_active: return # repay rate is the same as loan rate ether = sct * self.CDTL # update the CDT balance self.CDTB += ether # convert SCT to CDT cdt = sct # calculate the cash price of CDT self.CDTP = self.CDTB / (self.CDTS * self.CDT_CRR) # log CDT contract according to switch if self.log == self.log_cdt or self.log == self.log_dpt_cdt: print('repay: ', sct, 'SCT', '+', ether, 'ETH', '=>', cdt, 'CDT') return cdt
def to_credit(self, dct): """ used only after the activation of CDT contract convert DCT to CDT, those who pay the loan gets the CDT. market for DCT :param dct: :return: cdt """ # used only after the activation of CDT contract if not self.is_cdt_active: return # repay rate is the same as loan rate ether = dct * self.CDTL # update the CDT balance self.CDTB += ether # convert DCT to CDT cdt = dct # calculate the cash price of CDT self.CDTP = self.CDTB / (self.CDTS * self.CDT_CRR) # log CDT contract according to switch if self.log == self.log_cdt or self.log == self.log_dpt_cdt: print('to credit: ', dct, 'DCT', '+', ether, 'ETH', '=>', cdt, 'CDT') return cdt
def to_discredit(self, sct): """ used only after the activation of CDT contract convert SCT to DCT :param sct: amount of SCT to be converted :return: dct """ # used only after the activation of CDT contract if not self.is_cdt_active: return # convert SCT to DCT minus 0.05 fee dct = sct * 0.95 # calculate the cash price of CDT self.CDTP = self.CDTB / (self.CDTS * self.CDT_CRR) # log CDT contract according to switch if self.log == self.log_cdt or self.log == self.log_dpt_cdt: print('discredit:', sct, 'SCT','=>', dct, 'DCT') return dct
def test_cdt(e, a): """ test cdt and the interest of DPT :param e: instance of ERC20 Token :param a: random action seed :return: """ # The loan is concurrent with deposit and withdraw, but loan has a concrete period. # assum very 50 DPT action per CDT action period run_between = 50 # interest rate interest = 0.08 # random loan amount loan = random.randint(1, int(e.CDTS.real/1000)+1) for i in range(run_between): random_dpt(e, random.random(), 1/3) # random CDT action random_cdt(e, a, loan, interest) # log CDT and DPT instance log_cdt(e) log_dpt(e) # time.sleep(1)
def ei_taylor(z, _e1=False): s = t = z k = 2 while 1: t = t*z/k term = t/k if abs(term) < 1e-17: break s += term k += 1 s += euler if _e1: s += log(-z) else: if type(z) is float or z.imag == 0.0: s += math.log(abs(z)) else: s += cmath.log(z) return s
def LOG(df, price='Close'): """ Logarithm """ log_list = [] i = 0 while i < len(df[price]): log = cmath.log(df[price][i]).real log_list.append(ln) i += 1 return log_list
def test_log(): mp.dps = 15 assert log(1) == 0 for x in [0.5, 1.5, 2.0, 3.0, 100, 10**50, 1e-50]: assert log(x).ae(math.log(x)) assert log(x, x) == 1 assert log(1024, 2) == 10 assert log(10**1234, 10) == 1234 assert log(2+2j).ae(cmath.log(2+2j)) # Accuracy near 1 assert (log(0.6+0.8j).real*10**17).ae(2.2204460492503131) assert (log(0.6-0.8j).real*10**17).ae(2.2204460492503131) assert (log(0.8-0.6j).real*10**17).ae(2.2204460492503131) assert (log(1+1e-8j).real*10**16).ae(0.5) assert (log(1-1e-8j).real*10**16).ae(0.5) assert (log(-1+1e-8j).real*10**16).ae(0.5) assert (log(-1-1e-8j).real*10**16).ae(0.5) assert (log(1j+1e-8).real*10**16).ae(0.5) assert (log(1j-1e-8).real*10**16).ae(0.5) assert (log(-1j+1e-8).real*10**16).ae(0.5) assert (log(-1j-1e-8).real*10**16).ae(0.5) assert (log(1+1e-40j).real*10**80).ae(0.5) assert (log(1j+1e-40).real*10**80).ae(0.5) # Huge assert log(ldexp(1.234,10**20)).ae(log(2)*1e20) assert log(ldexp(1.234,10**200)).ae(log(2)*1e200) # Some special values assert log(mpc(0,0)) == mpc(-inf,0) assert isnan(log(mpc(nan,0)).real) assert isnan(log(mpc(nan,0)).imag) assert isnan(log(mpc(0,nan)).real) assert isnan(log(mpc(0,nan)).imag) assert isnan(log(mpc(nan,1)).real) assert isnan(log(mpc(nan,1)).imag) assert isnan(log(mpc(1,nan)).real) assert isnan(log(mpc(1,nan)).imag)
def test_complex_functions(): for x in (list(range(10)) + list(range(-10,0))): for y in (list(range(10)) + list(range(-10,0))): z = complex(x, y)/4.3 + 0.01j assert exp(mpc(z)).ae(cmath.exp(z)) assert log(mpc(z)).ae(cmath.log(z)) assert cos(mpc(z)).ae(cmath.cos(z)) assert sin(mpc(z)).ae(cmath.sin(z)) assert tan(mpc(z)).ae(cmath.tan(z)) assert sinh(mpc(z)).ae(cmath.sinh(z)) assert cosh(mpc(z)).ae(cmath.cosh(z)) assert tanh(mpc(z)).ae(cmath.tanh(z))
def test_aliases(): assert ln(7) == log(7) assert log10(3.75) == log(3.75,10) assert degrees(5.6) == 5.6 / degree assert radians(5.6) == 5.6 * degree assert power(-1,0.5) == j assert fmod(25,7) == 4.0 and isinstance(fmod(25,7), mpf)
def test_misc_bugs(): # test that this doesn't raise an exception mp.dps = 1000 log(1302) mp.dps = 15
def log10(ctx, x): return ctx.log(x, 10)
def _mathfun_n(f_real, f_complex): def f(*args, **kwargs): try: return f_real(*(float(x) for x in args)) except (TypeError, ValueError): return f_complex(*(complex(x) for x in args)) f.__name__ = f_real.__name__ return f # Workaround for non-raising log and sqrt in Python 2.5 and 2.4 # on Unix system
def math_log(x): if x <= 0.0: raise ValueError("math domain error") return math.log(x)
def my_log(x, y = None): if y is None: return log(x) else: return log(y, x)
def log(x, y = None): if y is None: return math_lib.log(x) else: return math_lib.log(y, x)
def mathlog(a):return mathclog(a).real
def computeBaseClassifierCoefficient(self, classifierIdx): ''' ???????????????(?0??)???????????? alpha ? :param classifierIdx: ???????(?0??) :return: ''' self.alphaList[classifierIdx] = (1.0 / 2 * \ cmath.log((1.0-self.eList[classifierIdx])/self.eList[classifierIdx], cmath.e)\ ).real
