1292 lines
42 KiB
Python
1292 lines
42 KiB
Python
from itertools import product
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from typing import Tuple as tTuple
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from sympy.core.add import Add
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from sympy.core.cache import cacheit
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from sympy.core.expr import Expr
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from sympy.core.function import (Function, ArgumentIndexError, expand_log,
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expand_mul, FunctionClass, PoleError, expand_multinomial, expand_complex)
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from sympy.core.logic import fuzzy_and, fuzzy_not, fuzzy_or
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from sympy.core.mul import Mul
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from sympy.core.numbers import Integer, Rational, pi, I, ImaginaryUnit
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from sympy.core.parameters import global_parameters
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from sympy.core.power import Pow
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from sympy.core.singleton import S
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from sympy.core.symbol import Wild, Dummy
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from sympy.core.sympify import sympify
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from sympy.functions.combinatorial.factorials import factorial
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from sympy.functions.elementary.complexes import arg, unpolarify, im, re, Abs
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from sympy.functions.elementary.miscellaneous import sqrt
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from sympy.ntheory import multiplicity, perfect_power
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from sympy.ntheory.factor_ import factorint
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# NOTE IMPORTANT
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# The series expansion code in this file is an important part of the gruntz
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# algorithm for determining limits. _eval_nseries has to return a generalized
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# power series with coefficients in C(log(x), log).
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# In more detail, the result of _eval_nseries(self, x, n) must be
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# c_0*x**e_0 + ... (finitely many terms)
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# where e_i are numbers (not necessarily integers) and c_i involve only
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# numbers, the function log, and log(x). [This also means it must not contain
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# log(x(1+p)), this *has* to be expanded to log(x)+log(1+p) if x.is_positive and
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# p.is_positive.]
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class ExpBase(Function):
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unbranched = True
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_singularities = (S.ComplexInfinity,)
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@property
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def kind(self):
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return self.exp.kind
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def inverse(self, argindex=1):
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"""
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Returns the inverse function of ``exp(x)``.
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"""
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return log
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def as_numer_denom(self):
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"""
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Returns this with a positive exponent as a 2-tuple (a fraction).
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Examples
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========
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>>> from sympy import exp
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>>> from sympy.abc import x
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>>> exp(-x).as_numer_denom()
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(1, exp(x))
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>>> exp(x).as_numer_denom()
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(exp(x), 1)
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"""
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# this should be the same as Pow.as_numer_denom wrt
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# exponent handling
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exp = self.exp
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neg_exp = exp.is_negative
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if not neg_exp and not (-exp).is_negative:
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neg_exp = exp.could_extract_minus_sign()
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if neg_exp:
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return S.One, self.func(-exp)
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return self, S.One
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@property
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def exp(self):
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"""
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Returns the exponent of the function.
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"""
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return self.args[0]
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def as_base_exp(self):
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"""
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Returns the 2-tuple (base, exponent).
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"""
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return self.func(1), Mul(*self.args)
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def _eval_adjoint(self):
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return self.func(self.exp.adjoint())
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def _eval_conjugate(self):
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return self.func(self.exp.conjugate())
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def _eval_transpose(self):
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return self.func(self.exp.transpose())
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def _eval_is_finite(self):
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arg = self.exp
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if arg.is_infinite:
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if arg.is_extended_negative:
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return True
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if arg.is_extended_positive:
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return False
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if arg.is_finite:
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return True
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def _eval_is_rational(self):
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s = self.func(*self.args)
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if s.func == self.func:
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z = s.exp.is_zero
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if z:
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return True
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elif s.exp.is_rational and fuzzy_not(z):
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return False
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else:
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return s.is_rational
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def _eval_is_zero(self):
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return self.exp is S.NegativeInfinity
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def _eval_power(self, other):
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"""exp(arg)**e -> exp(arg*e) if assumptions allow it.
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"""
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b, e = self.as_base_exp()
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return Pow._eval_power(Pow(b, e, evaluate=False), other)
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def _eval_expand_power_exp(self, **hints):
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from sympy.concrete.products import Product
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from sympy.concrete.summations import Sum
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arg = self.args[0]
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if arg.is_Add and arg.is_commutative:
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return Mul.fromiter(self.func(x) for x in arg.args)
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elif isinstance(arg, Sum) and arg.is_commutative:
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return Product(self.func(arg.function), *arg.limits)
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return self.func(arg)
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class exp_polar(ExpBase):
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r"""
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Represent a *polar number* (see g-function Sphinx documentation).
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Explanation
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===========
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``exp_polar`` represents the function
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`Exp: \mathbb{C} \rightarrow \mathcal{S}`, sending the complex number
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`z = a + bi` to the polar number `r = exp(a), \theta = b`. It is one of
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the main functions to construct polar numbers.
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Examples
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========
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>>> from sympy import exp_polar, pi, I, exp
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The main difference is that polar numbers do not "wrap around" at `2 \pi`:
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>>> exp(2*pi*I)
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1
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>>> exp_polar(2*pi*I)
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exp_polar(2*I*pi)
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apart from that they behave mostly like classical complex numbers:
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>>> exp_polar(2)*exp_polar(3)
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exp_polar(5)
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See Also
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========
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sympy.simplify.powsimp.powsimp
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polar_lift
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periodic_argument
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principal_branch
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"""
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is_polar = True
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is_comparable = False # cannot be evalf'd
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def _eval_Abs(self): # Abs is never a polar number
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return exp(re(self.args[0]))
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def _eval_evalf(self, prec):
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""" Careful! any evalf of polar numbers is flaky """
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i = im(self.args[0])
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try:
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bad = (i <= -pi or i > pi)
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except TypeError:
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bad = True
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if bad:
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return self # cannot evalf for this argument
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res = exp(self.args[0])._eval_evalf(prec)
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if i > 0 and im(res) < 0:
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# i ~ pi, but exp(I*i) evaluated to argument slightly bigger than pi
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return re(res)
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return res
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def _eval_power(self, other):
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return self.func(self.args[0]*other)
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def _eval_is_extended_real(self):
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if self.args[0].is_extended_real:
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return True
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def as_base_exp(self):
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# XXX exp_polar(0) is special!
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if self.args[0] == 0:
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return self, S.One
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return ExpBase.as_base_exp(self)
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class ExpMeta(FunctionClass):
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def __instancecheck__(cls, instance):
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if exp in instance.__class__.__mro__:
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return True
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return isinstance(instance, Pow) and instance.base is S.Exp1
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class exp(ExpBase, metaclass=ExpMeta):
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"""
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The exponential function, :math:`e^x`.
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Examples
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========
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>>> from sympy import exp, I, pi
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>>> from sympy.abc import x
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>>> exp(x)
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exp(x)
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>>> exp(x).diff(x)
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exp(x)
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>>> exp(I*pi)
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-1
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Parameters
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==========
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arg : Expr
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See Also
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========
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log
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"""
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def fdiff(self, argindex=1):
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"""
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Returns the first derivative of this function.
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"""
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if argindex == 1:
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return self
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else:
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raise ArgumentIndexError(self, argindex)
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def _eval_refine(self, assumptions):
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from sympy.assumptions import ask, Q
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arg = self.args[0]
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if arg.is_Mul:
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Ioo = I*S.Infinity
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if arg in [Ioo, -Ioo]:
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return S.NaN
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coeff = arg.as_coefficient(pi*I)
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if coeff:
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if ask(Q.integer(2*coeff)):
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if ask(Q.even(coeff)):
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return S.One
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elif ask(Q.odd(coeff)):
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return S.NegativeOne
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elif ask(Q.even(coeff + S.Half)):
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return -I
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elif ask(Q.odd(coeff + S.Half)):
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return I
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@classmethod
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def eval(cls, arg):
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from sympy.calculus import AccumBounds
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from sympy.matrices.matrices import MatrixBase
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from sympy.sets.setexpr import SetExpr
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from sympy.simplify.simplify import logcombine
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if isinstance(arg, MatrixBase):
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return arg.exp()
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elif global_parameters.exp_is_pow:
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return Pow(S.Exp1, arg)
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elif arg.is_Number:
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if arg is S.NaN:
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return S.NaN
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elif arg.is_zero:
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return S.One
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elif arg is S.One:
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return S.Exp1
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elif arg is S.Infinity:
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return S.Infinity
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elif arg is S.NegativeInfinity:
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return S.Zero
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elif arg is S.ComplexInfinity:
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return S.NaN
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elif isinstance(arg, log):
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return arg.args[0]
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elif isinstance(arg, AccumBounds):
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return AccumBounds(exp(arg.min), exp(arg.max))
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elif isinstance(arg, SetExpr):
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return arg._eval_func(cls)
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elif arg.is_Mul:
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coeff = arg.as_coefficient(pi*I)
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if coeff:
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if (2*coeff).is_integer:
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if coeff.is_even:
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return S.One
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elif coeff.is_odd:
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return S.NegativeOne
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elif (coeff + S.Half).is_even:
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return -I
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elif (coeff + S.Half).is_odd:
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return I
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elif coeff.is_Rational:
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ncoeff = coeff % 2 # restrict to [0, 2pi)
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if ncoeff > 1: # restrict to (-pi, pi]
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ncoeff -= 2
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if ncoeff != coeff:
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return cls(ncoeff*pi*I)
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# Warning: code in risch.py will be very sensitive to changes
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# in this (see DifferentialExtension).
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# look for a single log factor
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coeff, terms = arg.as_coeff_Mul()
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# but it can't be multiplied by oo
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if coeff in [S.NegativeInfinity, S.Infinity]:
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if terms.is_number:
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if coeff is S.NegativeInfinity:
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terms = -terms
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if re(terms).is_zero and terms is not S.Zero:
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return S.NaN
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if re(terms).is_positive and im(terms) is not S.Zero:
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return S.ComplexInfinity
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if re(terms).is_negative:
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return S.Zero
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return None
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coeffs, log_term = [coeff], None
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for term in Mul.make_args(terms):
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term_ = logcombine(term)
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if isinstance(term_, log):
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if log_term is None:
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log_term = term_.args[0]
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else:
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return None
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elif term.is_comparable:
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coeffs.append(term)
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else:
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return None
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return log_term**Mul(*coeffs) if log_term else None
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elif arg.is_Add:
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out = []
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add = []
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argchanged = False
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for a in arg.args:
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if a is S.One:
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add.append(a)
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continue
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newa = cls(a)
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if isinstance(newa, cls):
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if newa.args[0] != a:
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add.append(newa.args[0])
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argchanged = True
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else:
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add.append(a)
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else:
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out.append(newa)
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if out or argchanged:
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return Mul(*out)*cls(Add(*add), evaluate=False)
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if arg.is_zero:
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return S.One
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@property
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def base(self):
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"""
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Returns the base of the exponential function.
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"""
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return S.Exp1
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@staticmethod
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@cacheit
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def taylor_term(n, x, *previous_terms):
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"""
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Calculates the next term in the Taylor series expansion.
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"""
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if n < 0:
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return S.Zero
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if n == 0:
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return S.One
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x = sympify(x)
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if previous_terms:
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p = previous_terms[-1]
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if p is not None:
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return p * x / n
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return x**n/factorial(n)
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def as_real_imag(self, deep=True, **hints):
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"""
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Returns this function as a 2-tuple representing a complex number.
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Examples
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========
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>>> from sympy import exp, I
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>>> from sympy.abc import x
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>>> exp(x).as_real_imag()
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(exp(re(x))*cos(im(x)), exp(re(x))*sin(im(x)))
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>>> exp(1).as_real_imag()
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(E, 0)
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>>> exp(I).as_real_imag()
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(cos(1), sin(1))
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>>> exp(1+I).as_real_imag()
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(E*cos(1), E*sin(1))
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See Also
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========
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sympy.functions.elementary.complexes.re
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sympy.functions.elementary.complexes.im
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"""
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from sympy.functions.elementary.trigonometric import cos, sin
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re, im = self.args[0].as_real_imag()
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if deep:
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re = re.expand(deep, **hints)
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im = im.expand(deep, **hints)
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cos, sin = cos(im), sin(im)
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return (exp(re)*cos, exp(re)*sin)
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def _eval_subs(self, old, new):
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# keep processing of power-like args centralized in Pow
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if old.is_Pow: # handle (exp(3*log(x))).subs(x**2, z) -> z**(3/2)
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old = exp(old.exp*log(old.base))
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elif old is S.Exp1 and new.is_Function:
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old = exp
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if isinstance(old, exp) or old is S.Exp1:
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f = lambda a: Pow(*a.as_base_exp(), evaluate=False) if (
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a.is_Pow or isinstance(a, exp)) else a
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return Pow._eval_subs(f(self), f(old), new)
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if old is exp and not new.is_Function:
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return new**self.exp._subs(old, new)
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return Function._eval_subs(self, old, new)
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def _eval_is_extended_real(self):
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if self.args[0].is_extended_real:
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return True
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elif self.args[0].is_imaginary:
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arg2 = -S(2) * I * self.args[0] / pi
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return arg2.is_even
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def _eval_is_complex(self):
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def complex_extended_negative(arg):
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yield arg.is_complex
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yield arg.is_extended_negative
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return fuzzy_or(complex_extended_negative(self.args[0]))
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def _eval_is_algebraic(self):
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if (self.exp / pi / I).is_rational:
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return True
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if fuzzy_not(self.exp.is_zero):
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if self.exp.is_algebraic:
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return False
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elif (self.exp / pi).is_rational:
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return False
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def _eval_is_extended_positive(self):
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if self.exp.is_extended_real:
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return self.args[0] is not S.NegativeInfinity
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elif self.exp.is_imaginary:
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arg2 = -I * self.args[0] / pi
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return arg2.is_even
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def _eval_nseries(self, x, n, logx, cdir=0):
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# NOTE Please see the comment at the beginning of this file, labelled
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# IMPORTANT.
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from sympy.functions.elementary.complexes import sign
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from sympy.functions.elementary.integers import ceiling
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from sympy.series.limits import limit
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from sympy.series.order import Order
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from sympy.simplify.powsimp import powsimp
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arg = self.exp
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arg_series = arg._eval_nseries(x, n=n, logx=logx)
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if arg_series.is_Order:
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return 1 + arg_series
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arg0 = limit(arg_series.removeO(), x, 0)
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if arg0 is S.NegativeInfinity:
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return Order(x**n, x)
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if arg0 is S.Infinity:
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return self
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# checking for indecisiveness/ sign terms in arg0
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if any(isinstance(arg, (sign, ImaginaryUnit)) for arg in arg0.args):
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return self
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t = Dummy("t")
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nterms = n
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try:
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cf = Order(arg.as_leading_term(x, logx=logx), x).getn()
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except (NotImplementedError, PoleError):
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cf = 0
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if cf and cf > 0:
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nterms = ceiling(n/cf)
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exp_series = exp(t)._taylor(t, nterms)
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r = exp(arg0)*exp_series.subs(t, arg_series - arg0)
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rep = {logx: log(x)} if logx is not None else {}
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if r.subs(rep) == self:
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return r
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if cf and cf > 1:
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r += Order((arg_series - arg0)**n, x)/x**((cf-1)*n)
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else:
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r += Order((arg_series - arg0)**n, x)
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r = r.expand()
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r = powsimp(r, deep=True, combine='exp')
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# powsimp may introduce unexpanded (-1)**Rational; see PR #17201
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simplerat = lambda x: x.is_Rational and x.q in [3, 4, 6]
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w = Wild('w', properties=[simplerat])
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r = r.replace(S.NegativeOne**w, expand_complex(S.NegativeOne**w))
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return r
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def _taylor(self, x, n):
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l = []
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g = None
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for i in range(n):
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g = self.taylor_term(i, self.args[0], g)
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g = g.nseries(x, n=n)
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l.append(g.removeO())
|
|
return Add(*l)
|
|
|
|
def _eval_as_leading_term(self, x, logx=None, cdir=0):
|
|
from sympy.calculus.util import AccumBounds
|
|
arg = self.args[0].cancel().as_leading_term(x, logx=logx)
|
|
arg0 = arg.subs(x, 0)
|
|
if arg is S.NaN:
|
|
return S.NaN
|
|
if isinstance(arg0, AccumBounds):
|
|
# This check addresses a corner case involving AccumBounds.
|
|
# if isinstance(arg, AccumBounds) is True, then arg0 can either be 0,
|
|
# AccumBounds(-oo, 0) or AccumBounds(-oo, oo).
|
|
# Check out function: test_issue_18473() in test_exponential.py and
|
|
# test_limits.py for more information.
|
|
if re(cdir) < S.Zero:
|
|
return exp(-arg0)
|
|
return exp(arg0)
|
|
if arg0 is S.NaN:
|
|
arg0 = arg.limit(x, 0)
|
|
if arg0.is_infinite is False:
|
|
return exp(arg0)
|
|
raise PoleError("Cannot expand %s around 0" % (self))
|
|
|
|
def _eval_rewrite_as_sin(self, arg, **kwargs):
|
|
from sympy.functions.elementary.trigonometric import sin
|
|
return sin(I*arg + pi/2) - I*sin(I*arg)
|
|
|
|
def _eval_rewrite_as_cos(self, arg, **kwargs):
|
|
from sympy.functions.elementary.trigonometric import cos
|
|
return cos(I*arg) + I*cos(I*arg + pi/2)
|
|
|
|
def _eval_rewrite_as_tanh(self, arg, **kwargs):
|
|
from sympy.functions.elementary.hyperbolic import tanh
|
|
return (1 + tanh(arg/2))/(1 - tanh(arg/2))
|
|
|
|
def _eval_rewrite_as_sqrt(self, arg, **kwargs):
|
|
from sympy.functions.elementary.trigonometric import sin, cos
|
|
if arg.is_Mul:
|
|
coeff = arg.coeff(pi*I)
|
|
if coeff and coeff.is_number:
|
|
cosine, sine = cos(pi*coeff), sin(pi*coeff)
|
|
if not isinstance(cosine, cos) and not isinstance (sine, sin):
|
|
return cosine + I*sine
|
|
|
|
def _eval_rewrite_as_Pow(self, arg, **kwargs):
|
|
if arg.is_Mul:
|
|
logs = [a for a in arg.args if isinstance(a, log) and len(a.args) == 1]
|
|
if logs:
|
|
return Pow(logs[0].args[0], arg.coeff(logs[0]))
|
|
|
|
|
|
def match_real_imag(expr):
|
|
r"""
|
|
Try to match expr with $a + Ib$ for real $a$ and $b$.
|
|
|
|
``match_real_imag`` returns a tuple containing the real and imaginary
|
|
parts of expr or ``(None, None)`` if direct matching is not possible. Contrary
|
|
to :func:`~.re()`, :func:`~.im()``, and ``as_real_imag()``, this helper will not force things
|
|
by returning expressions themselves containing ``re()`` or ``im()`` and it
|
|
does not expand its argument either.
|
|
|
|
"""
|
|
r_, i_ = expr.as_independent(I, as_Add=True)
|
|
if i_ == 0 and r_.is_real:
|
|
return (r_, i_)
|
|
i_ = i_.as_coefficient(I)
|
|
if i_ and i_.is_real and r_.is_real:
|
|
return (r_, i_)
|
|
else:
|
|
return (None, None) # simpler to check for than None
|
|
|
|
|
|
class log(Function):
|
|
r"""
|
|
The natural logarithm function `\ln(x)` or `\log(x)`.
|
|
|
|
Explanation
|
|
===========
|
|
|
|
Logarithms are taken with the natural base, `e`. To get
|
|
a logarithm of a different base ``b``, use ``log(x, b)``,
|
|
which is essentially short-hand for ``log(x)/log(b)``.
|
|
|
|
``log`` represents the principal branch of the natural
|
|
logarithm. As such it has a branch cut along the negative
|
|
real axis and returns values having a complex argument in
|
|
`(-\pi, \pi]`.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy import log, sqrt, S, I
|
|
>>> log(8, 2)
|
|
3
|
|
>>> log(S(8)/3, 2)
|
|
-log(3)/log(2) + 3
|
|
>>> log(-1 + I*sqrt(3))
|
|
log(2) + 2*I*pi/3
|
|
|
|
See Also
|
|
========
|
|
|
|
exp
|
|
|
|
"""
|
|
|
|
args: tTuple[Expr]
|
|
|
|
_singularities = (S.Zero, S.ComplexInfinity)
|
|
|
|
def fdiff(self, argindex=1):
|
|
"""
|
|
Returns the first derivative of the function.
|
|
"""
|
|
if argindex == 1:
|
|
return 1/self.args[0]
|
|
else:
|
|
raise ArgumentIndexError(self, argindex)
|
|
|
|
def inverse(self, argindex=1):
|
|
r"""
|
|
Returns `e^x`, the inverse function of `\log(x)`.
|
|
"""
|
|
return exp
|
|
|
|
@classmethod
|
|
def eval(cls, arg, base=None):
|
|
from sympy.calculus import AccumBounds
|
|
from sympy.sets.setexpr import SetExpr
|
|
|
|
arg = sympify(arg)
|
|
|
|
if base is not None:
|
|
base = sympify(base)
|
|
if base == 1:
|
|
if arg == 1:
|
|
return S.NaN
|
|
else:
|
|
return S.ComplexInfinity
|
|
try:
|
|
# handle extraction of powers of the base now
|
|
# or else expand_log in Mul would have to handle this
|
|
n = multiplicity(base, arg)
|
|
if n:
|
|
return n + log(arg / base**n) / log(base)
|
|
else:
|
|
return log(arg)/log(base)
|
|
except ValueError:
|
|
pass
|
|
if base is not S.Exp1:
|
|
return cls(arg)/cls(base)
|
|
else:
|
|
return cls(arg)
|
|
|
|
if arg.is_Number:
|
|
if arg.is_zero:
|
|
return S.ComplexInfinity
|
|
elif arg is S.One:
|
|
return S.Zero
|
|
elif arg is S.Infinity:
|
|
return S.Infinity
|
|
elif arg is S.NegativeInfinity:
|
|
return S.Infinity
|
|
elif arg is S.NaN:
|
|
return S.NaN
|
|
elif arg.is_Rational and arg.p == 1:
|
|
return -cls(arg.q)
|
|
|
|
if arg.is_Pow and arg.base is S.Exp1 and arg.exp.is_extended_real:
|
|
return arg.exp
|
|
if isinstance(arg, exp) and arg.exp.is_extended_real:
|
|
return arg.exp
|
|
elif isinstance(arg, exp) and arg.exp.is_number:
|
|
r_, i_ = match_real_imag(arg.exp)
|
|
if i_ and i_.is_comparable:
|
|
i_ %= 2*pi
|
|
if i_ > pi:
|
|
i_ -= 2*pi
|
|
return r_ + expand_mul(i_ * I, deep=False)
|
|
elif isinstance(arg, exp_polar):
|
|
return unpolarify(arg.exp)
|
|
elif isinstance(arg, AccumBounds):
|
|
if arg.min.is_positive:
|
|
return AccumBounds(log(arg.min), log(arg.max))
|
|
elif arg.min.is_zero:
|
|
return AccumBounds(S.NegativeInfinity, log(arg.max))
|
|
else:
|
|
return S.NaN
|
|
elif isinstance(arg, SetExpr):
|
|
return arg._eval_func(cls)
|
|
|
|
if arg.is_number:
|
|
if arg.is_negative:
|
|
return pi * I + cls(-arg)
|
|
elif arg is S.ComplexInfinity:
|
|
return S.ComplexInfinity
|
|
elif arg is S.Exp1:
|
|
return S.One
|
|
|
|
if arg.is_zero:
|
|
return S.ComplexInfinity
|
|
|
|
# don't autoexpand Pow or Mul (see the issue 3351):
|
|
if not arg.is_Add:
|
|
coeff = arg.as_coefficient(I)
|
|
|
|
if coeff is not None:
|
|
if coeff is S.Infinity:
|
|
return S.Infinity
|
|
elif coeff is S.NegativeInfinity:
|
|
return S.Infinity
|
|
elif coeff.is_Rational:
|
|
if coeff.is_nonnegative:
|
|
return pi * I * S.Half + cls(coeff)
|
|
else:
|
|
return -pi * I * S.Half + cls(-coeff)
|
|
|
|
if arg.is_number and arg.is_algebraic:
|
|
# Match arg = coeff*(r_ + i_*I) with coeff>0, r_ and i_ real.
|
|
coeff, arg_ = arg.as_independent(I, as_Add=False)
|
|
if coeff.is_negative:
|
|
coeff *= -1
|
|
arg_ *= -1
|
|
arg_ = expand_mul(arg_, deep=False)
|
|
r_, i_ = arg_.as_independent(I, as_Add=True)
|
|
i_ = i_.as_coefficient(I)
|
|
if coeff.is_real and i_ and i_.is_real and r_.is_real:
|
|
if r_.is_zero:
|
|
if i_.is_positive:
|
|
return pi * I * S.Half + cls(coeff * i_)
|
|
elif i_.is_negative:
|
|
return -pi * I * S.Half + cls(coeff * -i_)
|
|
else:
|
|
from sympy.simplify import ratsimp
|
|
# Check for arguments involving rational multiples of pi
|
|
t = (i_/r_).cancel()
|
|
t1 = (-t).cancel()
|
|
atan_table = _log_atan_table()
|
|
if t in atan_table:
|
|
modulus = ratsimp(coeff * Abs(arg_))
|
|
if r_.is_positive:
|
|
return cls(modulus) + I * atan_table[t]
|
|
else:
|
|
return cls(modulus) + I * (atan_table[t] - pi)
|
|
elif t1 in atan_table:
|
|
modulus = ratsimp(coeff * Abs(arg_))
|
|
if r_.is_positive:
|
|
return cls(modulus) + I * (-atan_table[t1])
|
|
else:
|
|
return cls(modulus) + I * (pi - atan_table[t1])
|
|
|
|
def as_base_exp(self):
|
|
"""
|
|
Returns this function in the form (base, exponent).
|
|
"""
|
|
return self, S.One
|
|
|
|
@staticmethod
|
|
@cacheit
|
|
def taylor_term(n, x, *previous_terms): # of log(1+x)
|
|
r"""
|
|
Returns the next term in the Taylor series expansion of `\log(1+x)`.
|
|
"""
|
|
from sympy.simplify.powsimp import powsimp
|
|
if n < 0:
|
|
return S.Zero
|
|
x = sympify(x)
|
|
if n == 0:
|
|
return x
|
|
if previous_terms:
|
|
p = previous_terms[-1]
|
|
if p is not None:
|
|
return powsimp((-n) * p * x / (n + 1), deep=True, combine='exp')
|
|
return (1 - 2*(n % 2)) * x**(n + 1)/(n + 1)
|
|
|
|
def _eval_expand_log(self, deep=True, **hints):
|
|
from sympy.concrete import Sum, Product
|
|
force = hints.get('force', False)
|
|
factor = hints.get('factor', False)
|
|
if (len(self.args) == 2):
|
|
return expand_log(self.func(*self.args), deep=deep, force=force)
|
|
arg = self.args[0]
|
|
if arg.is_Integer:
|
|
# remove perfect powers
|
|
p = perfect_power(arg)
|
|
logarg = None
|
|
coeff = 1
|
|
if p is not False:
|
|
arg, coeff = p
|
|
logarg = self.func(arg)
|
|
# expand as product of its prime factors if factor=True
|
|
if factor:
|
|
p = factorint(arg)
|
|
if arg not in p.keys():
|
|
logarg = sum(n*log(val) for val, n in p.items())
|
|
if logarg is not None:
|
|
return coeff*logarg
|
|
elif arg.is_Rational:
|
|
return log(arg.p) - log(arg.q)
|
|
elif arg.is_Mul:
|
|
expr = []
|
|
nonpos = []
|
|
for x in arg.args:
|
|
if force or x.is_positive or x.is_polar:
|
|
a = self.func(x)
|
|
if isinstance(a, log):
|
|
expr.append(self.func(x)._eval_expand_log(**hints))
|
|
else:
|
|
expr.append(a)
|
|
elif x.is_negative:
|
|
a = self.func(-x)
|
|
expr.append(a)
|
|
nonpos.append(S.NegativeOne)
|
|
else:
|
|
nonpos.append(x)
|
|
return Add(*expr) + log(Mul(*nonpos))
|
|
elif arg.is_Pow or isinstance(arg, exp):
|
|
if force or (arg.exp.is_extended_real and (arg.base.is_positive or ((arg.exp+1)
|
|
.is_positive and (arg.exp-1).is_nonpositive))) or arg.base.is_polar:
|
|
b = arg.base
|
|
e = arg.exp
|
|
a = self.func(b)
|
|
if isinstance(a, log):
|
|
return unpolarify(e) * a._eval_expand_log(**hints)
|
|
else:
|
|
return unpolarify(e) * a
|
|
elif isinstance(arg, Product):
|
|
if force or arg.function.is_positive:
|
|
return Sum(log(arg.function), *arg.limits)
|
|
|
|
return self.func(arg)
|
|
|
|
def _eval_simplify(self, **kwargs):
|
|
from sympy.simplify.simplify import expand_log, simplify, inversecombine
|
|
if len(self.args) == 2: # it's unevaluated
|
|
return simplify(self.func(*self.args), **kwargs)
|
|
|
|
expr = self.func(simplify(self.args[0], **kwargs))
|
|
if kwargs['inverse']:
|
|
expr = inversecombine(expr)
|
|
expr = expand_log(expr, deep=True)
|
|
return min([expr, self], key=kwargs['measure'])
|
|
|
|
def as_real_imag(self, deep=True, **hints):
|
|
"""
|
|
Returns this function as a complex coordinate.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy import I, log
|
|
>>> from sympy.abc import x
|
|
>>> log(x).as_real_imag()
|
|
(log(Abs(x)), arg(x))
|
|
>>> log(I).as_real_imag()
|
|
(0, pi/2)
|
|
>>> log(1 + I).as_real_imag()
|
|
(log(sqrt(2)), pi/4)
|
|
>>> log(I*x).as_real_imag()
|
|
(log(Abs(x)), arg(I*x))
|
|
|
|
"""
|
|
sarg = self.args[0]
|
|
if deep:
|
|
sarg = self.args[0].expand(deep, **hints)
|
|
sarg_abs = Abs(sarg)
|
|
if sarg_abs == sarg:
|
|
return self, S.Zero
|
|
sarg_arg = arg(sarg)
|
|
if hints.get('log', False): # Expand the log
|
|
hints['complex'] = False
|
|
return (log(sarg_abs).expand(deep, **hints), sarg_arg)
|
|
else:
|
|
return log(sarg_abs), sarg_arg
|
|
|
|
def _eval_is_rational(self):
|
|
s = self.func(*self.args)
|
|
if s.func == self.func:
|
|
if (self.args[0] - 1).is_zero:
|
|
return True
|
|
if s.args[0].is_rational and fuzzy_not((self.args[0] - 1).is_zero):
|
|
return False
|
|
else:
|
|
return s.is_rational
|
|
|
|
def _eval_is_algebraic(self):
|
|
s = self.func(*self.args)
|
|
if s.func == self.func:
|
|
if (self.args[0] - 1).is_zero:
|
|
return True
|
|
elif fuzzy_not((self.args[0] - 1).is_zero):
|
|
if self.args[0].is_algebraic:
|
|
return False
|
|
else:
|
|
return s.is_algebraic
|
|
|
|
def _eval_is_extended_real(self):
|
|
return self.args[0].is_extended_positive
|
|
|
|
def _eval_is_complex(self):
|
|
z = self.args[0]
|
|
return fuzzy_and([z.is_complex, fuzzy_not(z.is_zero)])
|
|
|
|
def _eval_is_finite(self):
|
|
arg = self.args[0]
|
|
if arg.is_zero:
|
|
return False
|
|
return arg.is_finite
|
|
|
|
def _eval_is_extended_positive(self):
|
|
return (self.args[0] - 1).is_extended_positive
|
|
|
|
def _eval_is_zero(self):
|
|
return (self.args[0] - 1).is_zero
|
|
|
|
def _eval_is_extended_nonnegative(self):
|
|
return (self.args[0] - 1).is_extended_nonnegative
|
|
|
|
def _eval_nseries(self, x, n, logx, cdir=0):
|
|
# NOTE Please see the comment at the beginning of this file, labelled
|
|
# IMPORTANT.
|
|
from sympy.series.order import Order
|
|
from sympy.simplify.simplify import logcombine
|
|
from sympy.core.symbol import Dummy
|
|
|
|
if self.args[0] == x:
|
|
return log(x) if logx is None else logx
|
|
arg = self.args[0]
|
|
t = Dummy('t', positive=True)
|
|
if cdir == 0:
|
|
cdir = 1
|
|
z = arg.subs(x, cdir*t)
|
|
|
|
k, l = Wild("k"), Wild("l")
|
|
r = z.match(k*t**l)
|
|
if r is not None:
|
|
k, l = r[k], r[l]
|
|
if l != 0 and not l.has(t) and not k.has(t):
|
|
r = l*log(x) if logx is None else l*logx
|
|
r += log(k) - l*log(cdir) # XXX true regardless of assumptions?
|
|
return r
|
|
|
|
def coeff_exp(term, x):
|
|
coeff, exp = S.One, S.Zero
|
|
for factor in Mul.make_args(term):
|
|
if factor.has(x):
|
|
base, exp = factor.as_base_exp()
|
|
if base != x:
|
|
try:
|
|
return term.leadterm(x)
|
|
except ValueError:
|
|
return term, S.Zero
|
|
else:
|
|
coeff *= factor
|
|
return coeff, exp
|
|
|
|
# TODO new and probably slow
|
|
try:
|
|
a, b = z.leadterm(t, logx=logx, cdir=1)
|
|
except (ValueError, NotImplementedError, PoleError):
|
|
s = z._eval_nseries(t, n=n, logx=logx, cdir=1)
|
|
while s.is_Order:
|
|
n += 1
|
|
s = z._eval_nseries(t, n=n, logx=logx, cdir=1)
|
|
try:
|
|
a, b = s.removeO().leadterm(t, cdir=1)
|
|
except ValueError:
|
|
a, b = s.removeO().as_leading_term(t, cdir=1), S.Zero
|
|
|
|
p = (z/(a*t**b) - 1)._eval_nseries(t, n=n, logx=logx, cdir=1)
|
|
if p.has(exp):
|
|
p = logcombine(p)
|
|
if isinstance(p, Order):
|
|
n = p.getn()
|
|
_, d = coeff_exp(p, t)
|
|
logx = log(x) if logx is None else logx
|
|
|
|
if not d.is_positive:
|
|
res = log(a) - b*log(cdir) + b*logx
|
|
_res = res
|
|
logflags = {"deep": True, "log": True, "mul": False, "power_exp": False,
|
|
"power_base": False, "multinomial": False, "basic": False, "force": True,
|
|
"factor": False}
|
|
expr = self.expand(**logflags)
|
|
if (not a.could_extract_minus_sign() and
|
|
logx.could_extract_minus_sign()):
|
|
_res = _res.subs(-logx, -log(x)).expand(**logflags)
|
|
else:
|
|
_res = _res.subs(logx, log(x)).expand(**logflags)
|
|
if _res == expr:
|
|
return res
|
|
return res + Order(x**n, x)
|
|
|
|
def mul(d1, d2):
|
|
res = {}
|
|
for e1, e2 in product(d1, d2):
|
|
ex = e1 + e2
|
|
if ex < n:
|
|
res[ex] = res.get(ex, S.Zero) + d1[e1]*d2[e2]
|
|
return res
|
|
|
|
pterms = {}
|
|
|
|
for term in Add.make_args(p.removeO()):
|
|
co1, e1 = coeff_exp(term, t)
|
|
pterms[e1] = pterms.get(e1, S.Zero) + co1
|
|
|
|
k = S.One
|
|
terms = {}
|
|
pk = pterms
|
|
|
|
while k*d < n:
|
|
coeff = -S.NegativeOne**k/k
|
|
for ex in pk:
|
|
_ = terms.get(ex, S.Zero) + coeff*pk[ex]
|
|
terms[ex] = _.nsimplify()
|
|
pk = mul(pk, pterms)
|
|
k += S.One
|
|
|
|
res = log(a) - b*log(cdir) + b*logx
|
|
for ex in terms:
|
|
res += terms[ex]*t**(ex)
|
|
|
|
if a.is_negative and im(z) != 0:
|
|
from sympy.functions.special.delta_functions import Heaviside
|
|
for i, term in enumerate(z.lseries(t)):
|
|
if not term.is_real or i == 5:
|
|
break
|
|
if i < 5:
|
|
coeff, _ = term.as_coeff_exponent(t)
|
|
res += -2*I*pi*Heaviside(-im(coeff), 0)
|
|
|
|
res = res.subs(t, x/cdir)
|
|
return res + Order(x**n, x)
|
|
|
|
def _eval_as_leading_term(self, x, logx=None, cdir=0):
|
|
# NOTE
|
|
# Refer https://github.com/sympy/sympy/pull/23592 for more information
|
|
# on each of the following steps involved in this method.
|
|
arg0 = self.args[0].together()
|
|
|
|
# STEP 1
|
|
t = Dummy('t', positive=True)
|
|
if cdir == 0:
|
|
cdir = 1
|
|
z = arg0.subs(x, cdir*t)
|
|
|
|
# STEP 2
|
|
try:
|
|
c, e = z.leadterm(t, logx=logx, cdir=1)
|
|
except ValueError:
|
|
arg = arg0.as_leading_term(x, logx=logx, cdir=cdir)
|
|
return log(arg)
|
|
if c.has(t):
|
|
c = c.subs(t, x/cdir)
|
|
if e != 0:
|
|
raise PoleError("Cannot expand %s around 0" % (self))
|
|
return log(c)
|
|
|
|
# STEP 3
|
|
if c == S.One and e == S.Zero:
|
|
return (arg0 - S.One).as_leading_term(x, logx=logx)
|
|
|
|
# STEP 4
|
|
res = log(c) - e*log(cdir)
|
|
logx = log(x) if logx is None else logx
|
|
res += e*logx
|
|
|
|
# STEP 5
|
|
if c.is_negative and im(z) != 0:
|
|
from sympy.functions.special.delta_functions import Heaviside
|
|
for i, term in enumerate(z.lseries(t)):
|
|
if not term.is_real or i == 5:
|
|
break
|
|
if i < 5:
|
|
coeff, _ = term.as_coeff_exponent(t)
|
|
res += -2*I*pi*Heaviside(-im(coeff), 0)
|
|
return res
|
|
|
|
|
|
class LambertW(Function):
|
|
r"""
|
|
The Lambert W function $W(z)$ is defined as the inverse
|
|
function of $w \exp(w)$ [1]_.
|
|
|
|
Explanation
|
|
===========
|
|
|
|
In other words, the value of $W(z)$ is such that $z = W(z) \exp(W(z))$
|
|
for any complex number $z$. The Lambert W function is a multivalued
|
|
function with infinitely many branches $W_k(z)$, indexed by
|
|
$k \in \mathbb{Z}$. Each branch gives a different solution $w$
|
|
of the equation $z = w \exp(w)$.
|
|
|
|
The Lambert W function has two partially real branches: the
|
|
principal branch ($k = 0$) is real for real $z > -1/e$, and the
|
|
$k = -1$ branch is real for $-1/e < z < 0$. All branches except
|
|
$k = 0$ have a logarithmic singularity at $z = 0$.
|
|
|
|
Examples
|
|
========
|
|
|
|
>>> from sympy import LambertW
|
|
>>> LambertW(1.2)
|
|
0.635564016364870
|
|
>>> LambertW(1.2, -1).n()
|
|
-1.34747534407696 - 4.41624341514535*I
|
|
>>> LambertW(-1).is_real
|
|
False
|
|
|
|
References
|
|
==========
|
|
|
|
.. [1] https://en.wikipedia.org/wiki/Lambert_W_function
|
|
"""
|
|
_singularities = (-Pow(S.Exp1, -1, evaluate=False), S.ComplexInfinity)
|
|
|
|
@classmethod
|
|
def eval(cls, x, k=None):
|
|
if k == S.Zero:
|
|
return cls(x)
|
|
elif k is None:
|
|
k = S.Zero
|
|
|
|
if k.is_zero:
|
|
if x.is_zero:
|
|
return S.Zero
|
|
if x is S.Exp1:
|
|
return S.One
|
|
if x == -1/S.Exp1:
|
|
return S.NegativeOne
|
|
if x == -log(2)/2:
|
|
return -log(2)
|
|
if x == 2*log(2):
|
|
return log(2)
|
|
if x == -pi/2:
|
|
return I*pi/2
|
|
if x == exp(1 + S.Exp1):
|
|
return S.Exp1
|
|
if x is S.Infinity:
|
|
return S.Infinity
|
|
if x.is_zero:
|
|
return S.Zero
|
|
|
|
if fuzzy_not(k.is_zero):
|
|
if x.is_zero:
|
|
return S.NegativeInfinity
|
|
if k is S.NegativeOne:
|
|
if x == -pi/2:
|
|
return -I*pi/2
|
|
elif x == -1/S.Exp1:
|
|
return S.NegativeOne
|
|
elif x == -2*exp(-2):
|
|
return -Integer(2)
|
|
|
|
def fdiff(self, argindex=1):
|
|
"""
|
|
Return the first derivative of this function.
|
|
"""
|
|
x = self.args[0]
|
|
|
|
if len(self.args) == 1:
|
|
if argindex == 1:
|
|
return LambertW(x)/(x*(1 + LambertW(x)))
|
|
else:
|
|
k = self.args[1]
|
|
if argindex == 1:
|
|
return LambertW(x, k)/(x*(1 + LambertW(x, k)))
|
|
|
|
raise ArgumentIndexError(self, argindex)
|
|
|
|
def _eval_is_extended_real(self):
|
|
x = self.args[0]
|
|
if len(self.args) == 1:
|
|
k = S.Zero
|
|
else:
|
|
k = self.args[1]
|
|
if k.is_zero:
|
|
if (x + 1/S.Exp1).is_positive:
|
|
return True
|
|
elif (x + 1/S.Exp1).is_nonpositive:
|
|
return False
|
|
elif (k + 1).is_zero:
|
|
if x.is_negative and (x + 1/S.Exp1).is_positive:
|
|
return True
|
|
elif x.is_nonpositive or (x + 1/S.Exp1).is_nonnegative:
|
|
return False
|
|
elif fuzzy_not(k.is_zero) and fuzzy_not((k + 1).is_zero):
|
|
if x.is_extended_real:
|
|
return False
|
|
|
|
def _eval_is_finite(self):
|
|
return self.args[0].is_finite
|
|
|
|
def _eval_is_algebraic(self):
|
|
s = self.func(*self.args)
|
|
if s.func == self.func:
|
|
if fuzzy_not(self.args[0].is_zero) and self.args[0].is_algebraic:
|
|
return False
|
|
else:
|
|
return s.is_algebraic
|
|
|
|
def _eval_as_leading_term(self, x, logx=None, cdir=0):
|
|
if len(self.args) == 1:
|
|
arg = self.args[0]
|
|
arg0 = arg.subs(x, 0).cancel()
|
|
if not arg0.is_zero:
|
|
return self.func(arg0)
|
|
return arg.as_leading_term(x)
|
|
|
|
def _eval_nseries(self, x, n, logx, cdir=0):
|
|
if len(self.args) == 1:
|
|
from sympy.functions.elementary.integers import ceiling
|
|
from sympy.series.order import Order
|
|
arg = self.args[0].nseries(x, n=n, logx=logx)
|
|
lt = arg.as_leading_term(x, logx=logx)
|
|
lte = 1
|
|
if lt.is_Pow:
|
|
lte = lt.exp
|
|
if ceiling(n/lte) >= 1:
|
|
s = Add(*[(-S.One)**(k - 1)*Integer(k)**(k - 2)/
|
|
factorial(k - 1)*arg**k for k in range(1, ceiling(n/lte))])
|
|
s = expand_multinomial(s)
|
|
else:
|
|
s = S.Zero
|
|
|
|
return s + Order(x**n, x)
|
|
return super()._eval_nseries(x, n, logx)
|
|
|
|
def _eval_is_zero(self):
|
|
x = self.args[0]
|
|
if len(self.args) == 1:
|
|
return x.is_zero
|
|
else:
|
|
return fuzzy_and([x.is_zero, self.args[1].is_zero])
|
|
|
|
|
|
@cacheit
|
|
def _log_atan_table():
|
|
return {
|
|
# first quadrant only
|
|
sqrt(3): pi / 3,
|
|
1: pi / 4,
|
|
sqrt(5 - 2 * sqrt(5)): pi / 5,
|
|
sqrt(2) * sqrt(5 - sqrt(5)) / (1 + sqrt(5)): pi / 5,
|
|
sqrt(5 + 2 * sqrt(5)): pi * Rational(2, 5),
|
|
sqrt(2) * sqrt(sqrt(5) + 5) / (-1 + sqrt(5)): pi * Rational(2, 5),
|
|
sqrt(3) / 3: pi / 6,
|
|
sqrt(2) - 1: pi / 8,
|
|
sqrt(2 - sqrt(2)) / sqrt(sqrt(2) + 2): pi / 8,
|
|
sqrt(2) + 1: pi * Rational(3, 8),
|
|
sqrt(sqrt(2) + 2) / sqrt(2 - sqrt(2)): pi * Rational(3, 8),
|
|
sqrt(1 - 2 * sqrt(5) / 5): pi / 10,
|
|
(-sqrt(2) + sqrt(10)) / (2 * sqrt(sqrt(5) + 5)): pi / 10,
|
|
sqrt(1 + 2 * sqrt(5) / 5): pi * Rational(3, 10),
|
|
(sqrt(2) + sqrt(10)) / (2 * sqrt(5 - sqrt(5))): pi * Rational(3, 10),
|
|
2 - sqrt(3): pi / 12,
|
|
(-1 + sqrt(3)) / (1 + sqrt(3)): pi / 12,
|
|
2 + sqrt(3): pi * Rational(5, 12),
|
|
(1 + sqrt(3)) / (-1 + sqrt(3)): pi * Rational(5, 12)
|
|
}
|