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518 lines
19 KiB
518 lines
19 KiB
5 months ago
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from sympy.core import S, sympify, Expr, Dummy, Add, Mul
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from sympy.core.cache import cacheit
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from sympy.core.containers import Tuple
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from sympy.core.function import Function, PoleError, expand_power_base, expand_log
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from sympy.core.sorting import default_sort_key
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from sympy.functions.elementary.exponential import exp, log
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from sympy.sets.sets import Complement
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from sympy.utilities.iterables import uniq, is_sequence
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class Order(Expr):
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r""" Represents the limiting behavior of some function.
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Explanation
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===========
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The order of a function characterizes the function based on the limiting
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behavior of the function as it goes to some limit. Only taking the limit
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point to be a number is currently supported. This is expressed in
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big O notation [1]_.
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The formal definition for the order of a function `g(x)` about a point `a`
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is such that `g(x) = O(f(x))` as `x \rightarrow a` if and only if there
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exists a `\delta > 0` and an `M > 0` such that `|g(x)| \leq M|f(x)|` for
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`|x-a| < \delta`. This is equivalent to `\limsup_{x \rightarrow a}
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|g(x)/f(x)| < \infty`.
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Let's illustrate it on the following example by taking the expansion of
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`\sin(x)` about 0:
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.. math ::
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\sin(x) = x - x^3/3! + O(x^5)
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where in this case `O(x^5) = x^5/5! - x^7/7! + \cdots`. By the definition
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of `O`, there is a `\delta > 0` and an `M` such that:
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.. math ::
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|x^5/5! - x^7/7! + ....| <= M|x^5| \text{ for } |x| < \delta
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or by the alternate definition:
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.. math ::
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\lim_{x \rightarrow 0} | (x^5/5! - x^7/7! + ....) / x^5| < \infty
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which surely is true, because
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.. math ::
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\lim_{x \rightarrow 0} | (x^5/5! - x^7/7! + ....) / x^5| = 1/5!
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As it is usually used, the order of a function can be intuitively thought
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of representing all terms of powers greater than the one specified. For
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example, `O(x^3)` corresponds to any terms proportional to `x^3,
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x^4,\ldots` and any higher power. For a polynomial, this leaves terms
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proportional to `x^2`, `x` and constants.
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Examples
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========
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>>> from sympy import O, oo, cos, pi
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>>> from sympy.abc import x, y
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>>> O(x + x**2)
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O(x)
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>>> O(x + x**2, (x, 0))
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O(x)
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>>> O(x + x**2, (x, oo))
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O(x**2, (x, oo))
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>>> O(1 + x*y)
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O(1, x, y)
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>>> O(1 + x*y, (x, 0), (y, 0))
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O(1, x, y)
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>>> O(1 + x*y, (x, oo), (y, oo))
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O(x*y, (x, oo), (y, oo))
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>>> O(1) in O(1, x)
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True
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>>> O(1, x) in O(1)
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False
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>>> O(x) in O(1, x)
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True
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>>> O(x**2) in O(x)
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True
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>>> O(x)*x
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O(x**2)
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>>> O(x) - O(x)
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O(x)
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>>> O(cos(x))
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O(1)
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>>> O(cos(x), (x, pi/2))
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O(x - pi/2, (x, pi/2))
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References
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==========
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.. [1] `Big O notation <https://en.wikipedia.org/wiki/Big_O_notation>`_
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Notes
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=====
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In ``O(f(x), x)`` the expression ``f(x)`` is assumed to have a leading
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term. ``O(f(x), x)`` is automatically transformed to
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``O(f(x).as_leading_term(x),x)``.
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``O(expr*f(x), x)`` is ``O(f(x), x)``
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``O(expr, x)`` is ``O(1)``
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``O(0, x)`` is 0.
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Multivariate O is also supported:
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``O(f(x, y), x, y)`` is transformed to
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``O(f(x, y).as_leading_term(x,y).as_leading_term(y), x, y)``
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In the multivariate case, it is assumed the limits w.r.t. the various
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symbols commute.
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If no symbols are passed then all symbols in the expression are used
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and the limit point is assumed to be zero.
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"""
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is_Order = True
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__slots__ = ()
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@cacheit
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def __new__(cls, expr, *args, **kwargs):
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expr = sympify(expr)
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if not args:
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if expr.is_Order:
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variables = expr.variables
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point = expr.point
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else:
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variables = list(expr.free_symbols)
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point = [S.Zero]*len(variables)
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else:
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args = list(args if is_sequence(args) else [args])
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variables, point = [], []
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if is_sequence(args[0]):
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for a in args:
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v, p = list(map(sympify, a))
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variables.append(v)
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point.append(p)
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else:
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variables = list(map(sympify, args))
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point = [S.Zero]*len(variables)
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if not all(v.is_symbol for v in variables):
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raise TypeError('Variables are not symbols, got %s' % variables)
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if len(list(uniq(variables))) != len(variables):
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raise ValueError('Variables are supposed to be unique symbols, got %s' % variables)
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if expr.is_Order:
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expr_vp = dict(expr.args[1:])
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new_vp = dict(expr_vp)
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vp = dict(zip(variables, point))
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for v, p in vp.items():
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if v in new_vp.keys():
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if p != new_vp[v]:
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raise NotImplementedError(
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"Mixing Order at different points is not supported.")
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else:
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new_vp[v] = p
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if set(expr_vp.keys()) == set(new_vp.keys()):
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return expr
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else:
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variables = list(new_vp.keys())
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point = [new_vp[v] for v in variables]
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if expr is S.NaN:
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return S.NaN
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if any(x in p.free_symbols for x in variables for p in point):
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raise ValueError('Got %s as a point.' % point)
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if variables:
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if any(p != point[0] for p in point):
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raise NotImplementedError(
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"Multivariable orders at different points are not supported.")
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if point[0] in (S.Infinity, S.Infinity*S.ImaginaryUnit):
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s = {k: 1/Dummy() for k in variables}
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rs = {1/v: 1/k for k, v in s.items()}
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ps = [S.Zero for p in point]
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elif point[0] in (S.NegativeInfinity, S.NegativeInfinity*S.ImaginaryUnit):
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s = {k: -1/Dummy() for k in variables}
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rs = {-1/v: -1/k for k, v in s.items()}
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ps = [S.Zero for p in point]
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elif point[0] is not S.Zero:
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s = {k: Dummy() + point[0] for k in variables}
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rs = {(v - point[0]).together(): k - point[0] for k, v in s.items()}
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ps = [S.Zero for p in point]
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else:
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s = ()
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rs = ()
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ps = list(point)
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expr = expr.subs(s)
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if expr.is_Add:
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expr = expr.factor()
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if s:
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args = tuple([r[0] for r in rs.items()])
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else:
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args = tuple(variables)
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if len(variables) > 1:
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# XXX: better way? We need this expand() to
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# workaround e.g: expr = x*(x + y).
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# (x*(x + y)).as_leading_term(x, y) currently returns
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# x*y (wrong order term!). That's why we want to deal with
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# expand()'ed expr (handled in "if expr.is_Add" branch below).
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expr = expr.expand()
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old_expr = None
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while old_expr != expr:
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old_expr = expr
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if expr.is_Add:
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lst = expr.extract_leading_order(args)
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expr = Add(*[f.expr for (e, f) in lst])
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elif expr:
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try:
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expr = expr.as_leading_term(*args)
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except PoleError:
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if isinstance(expr, Function) or\
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all(isinstance(arg, Function) for arg in expr.args):
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# It is not possible to simplify an expression
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# containing only functions (which raise error on
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# call to leading term) further
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pass
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else:
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orders = []
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pts = tuple(zip(args, ps))
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for arg in expr.args:
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try:
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lt = arg.as_leading_term(*args)
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except PoleError:
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lt = arg
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if lt not in args:
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order = Order(lt)
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else:
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order = Order(lt, *pts)
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orders.append(order)
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if expr.is_Add:
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new_expr = Order(Add(*orders), *pts)
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if new_expr.is_Add:
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new_expr = Order(Add(*[a.expr for a in new_expr.args]), *pts)
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expr = new_expr.expr
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elif expr.is_Mul:
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expr = Mul(*[a.expr for a in orders])
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elif expr.is_Pow:
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e = expr.exp
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b = expr.base
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expr = exp(e * log(b))
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# It would probably be better to handle this somewhere
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# else. This is needed for a testcase in which there is a
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# symbol with the assumptions zero=True.
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if expr.is_zero:
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expr = S.Zero
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else:
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expr = expr.as_independent(*args, as_Add=False)[1]
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expr = expand_power_base(expr)
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expr = expand_log(expr)
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if len(args) == 1:
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# The definition of O(f(x)) symbol explicitly stated that
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# the argument of f(x) is irrelevant. That's why we can
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# combine some power exponents (only "on top" of the
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# expression tree for f(x)), e.g.:
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# x**p * (-x)**q -> x**(p+q) for real p, q.
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x = args[0]
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margs = list(Mul.make_args(
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expr.as_independent(x, as_Add=False)[1]))
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for i, t in enumerate(margs):
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if t.is_Pow:
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b, q = t.args
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if b in (x, -x) and q.is_real and not q.has(x):
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margs[i] = x**q
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elif b.is_Pow and not b.exp.has(x):
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b, r = b.args
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if b in (x, -x) and r.is_real:
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margs[i] = x**(r*q)
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elif b.is_Mul and b.args[0] is S.NegativeOne:
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b = -b
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if b.is_Pow and not b.exp.has(x):
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b, r = b.args
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if b in (x, -x) and r.is_real:
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margs[i] = x**(r*q)
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expr = Mul(*margs)
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expr = expr.subs(rs)
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if expr.is_Order:
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expr = expr.expr
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if not expr.has(*variables) and not expr.is_zero:
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expr = S.One
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# create Order instance:
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vp = dict(zip(variables, point))
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variables.sort(key=default_sort_key)
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point = [vp[v] for v in variables]
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args = (expr,) + Tuple(*zip(variables, point))
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obj = Expr.__new__(cls, *args)
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return obj
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def _eval_nseries(self, x, n, logx, cdir=0):
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return self
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@property
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def expr(self):
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return self.args[0]
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@property
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def variables(self):
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if self.args[1:]:
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return tuple(x[0] for x in self.args[1:])
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else:
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return ()
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@property
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def point(self):
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if self.args[1:]:
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return tuple(x[1] for x in self.args[1:])
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else:
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return ()
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@property
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def free_symbols(self):
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return self.expr.free_symbols | set(self.variables)
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def _eval_power(b, e):
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if e.is_Number and e.is_nonnegative:
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return b.func(b.expr ** e, *b.args[1:])
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if e == O(1):
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return b
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return
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def as_expr_variables(self, order_symbols):
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if order_symbols is None:
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order_symbols = self.args[1:]
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else:
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if (not all(o[1] == order_symbols[0][1] for o in order_symbols) and
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not all(p == self.point[0] for p in self.point)): # pragma: no cover
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raise NotImplementedError('Order at points other than 0 '
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'or oo not supported, got %s as a point.' % self.point)
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if order_symbols and order_symbols[0][1] != self.point[0]:
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raise NotImplementedError(
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"Multiplying Order at different points is not supported.")
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order_symbols = dict(order_symbols)
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for s, p in dict(self.args[1:]).items():
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if s not in order_symbols.keys():
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order_symbols[s] = p
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|
|
order_symbols = sorted(order_symbols.items(), key=lambda x: default_sort_key(x[0]))
|
||
|
|
return self.expr, tuple(order_symbols)
|
||
|
|
|
||
|
|
def removeO(self):
|
||
|
|
return S.Zero
|
||
|
|
|
||
|
|
def getO(self):
|
||
|
|
return self
|
||
|
|
|
||
|
|
@cacheit
|
||
|
|
def contains(self, expr):
|
||
|
|
r"""
|
||
|
|
Return True if expr belongs to Order(self.expr, \*self.variables).
|
||
|
|
Return False if self belongs to expr.
|
||
|
|
Return None if the inclusion relation cannot be determined
|
||
|
|
(e.g. when self and expr have different symbols).
|
||
|
|
"""
|
||
|
|
expr = sympify(expr)
|
||
|
|
if expr.is_zero:
|
||
|
|
return True
|
||
|
|
if expr is S.NaN:
|
||
|
|
return False
|
||
|
|
point = self.point[0] if self.point else S.Zero
|
||
|
|
if expr.is_Order:
|
||
|
|
if (any(p != point for p in expr.point) or
|
||
|
|
any(p != point for p in self.point)):
|
||
|
|
return None
|
||
|
|
if expr.expr == self.expr:
|
||
|
|
# O(1) + O(1), O(1) + O(1, x), etc.
|
||
|
|
return all(x in self.args[1:] for x in expr.args[1:])
|
||
|
|
if expr.expr.is_Add:
|
||
|
|
return all(self.contains(x) for x in expr.expr.args)
|
||
|
|
if self.expr.is_Add and point.is_zero:
|
||
|
|
return any(self.func(x, *self.args[1:]).contains(expr)
|
||
|
|
for x in self.expr.args)
|
||
|
|
if self.variables and expr.variables:
|
||
|
|
common_symbols = tuple(
|
||
|
|
[s for s in self.variables if s in expr.variables])
|
||
|
|
elif self.variables:
|
||
|
|
common_symbols = self.variables
|
||
|
|
else:
|
||
|
|
common_symbols = expr.variables
|
||
|
|
if not common_symbols:
|
||
|
|
return None
|
||
|
|
if (self.expr.is_Pow and len(self.variables) == 1
|
||
|
|
and self.variables == expr.variables):
|
||
|
|
symbol = self.variables[0]
|
||
|
|
other = expr.expr.as_independent(symbol, as_Add=False)[1]
|
||
|
|
if (other.is_Pow and other.base == symbol and
|
||
|
|
self.expr.base == symbol):
|
||
|
|
if point.is_zero:
|
||
|
|
rv = (self.expr.exp - other.exp).is_nonpositive
|
||
|
|
if point.is_infinite:
|
||
|
|
rv = (self.expr.exp - other.exp).is_nonnegative
|
||
|
|
if rv is not None:
|
||
|
|
return rv
|
||
|
|
|
||
|
|
from sympy.simplify.powsimp import powsimp
|
||
|
|
r = None
|
||
|
|
ratio = self.expr/expr.expr
|
||
|
|
ratio = powsimp(ratio, deep=True, combine='exp')
|
||
|
|
for s in common_symbols:
|
||
|
|
from sympy.series.limits import Limit
|
||
|
|
l = Limit(ratio, s, point).doit(heuristics=False)
|
||
|
|
if not isinstance(l, Limit):
|
||
|
|
l = l != 0
|
||
|
|
else:
|
||
|
|
l = None
|
||
|
|
if r is None:
|
||
|
|
r = l
|
||
|
|
else:
|
||
|
|
if r != l:
|
||
|
|
return
|
||
|
|
return r
|
||
|
|
|
||
|
|
if self.expr.is_Pow and len(self.variables) == 1:
|
||
|
|
symbol = self.variables[0]
|
||
|
|
other = expr.as_independent(symbol, as_Add=False)[1]
|
||
|
|
if (other.is_Pow and other.base == symbol and
|
||
|
|
self.expr.base == symbol):
|
||
|
|
if point.is_zero:
|
||
|
|
rv = (self.expr.exp - other.exp).is_nonpositive
|
||
|
|
if point.is_infinite:
|
||
|
|
rv = (self.expr.exp - other.exp).is_nonnegative
|
||
|
|
if rv is not None:
|
||
|
|
return rv
|
||
|
|
|
||
|
|
obj = self.func(expr, *self.args[1:])
|
||
|
|
return self.contains(obj)
|
||
|
|
|
||
|
|
def __contains__(self, other):
|
||
|
|
result = self.contains(other)
|
||
|
|
if result is None:
|
||
|
|
raise TypeError('contains did not evaluate to a bool')
|
||
|
|
return result
|
||
|
|
|
||
|
|
def _eval_subs(self, old, new):
|
||
|
|
if old in self.variables:
|
||
|
|
newexpr = self.expr.subs(old, new)
|
||
|
|
i = self.variables.index(old)
|
||
|
|
newvars = list(self.variables)
|
||
|
|
newpt = list(self.point)
|
||
|
|
if new.is_symbol:
|
||
|
|
newvars[i] = new
|
||
|
|
else:
|
||
|
|
syms = new.free_symbols
|
||
|
|
if len(syms) == 1 or old in syms:
|
||
|
|
if old in syms:
|
||
|
|
var = self.variables[i]
|
||
|
|
else:
|
||
|
|
var = syms.pop()
|
||
|
|
# First, try to substitute self.point in the "new"
|
||
|
|
# expr to see if this is a fixed point.
|
||
|
|
# E.g. O(y).subs(y, sin(x))
|
||
|
|
point = new.subs(var, self.point[i])
|
||
|
|
if point != self.point[i]:
|
||
|
|
from sympy.solvers.solveset import solveset
|
||
|
|
d = Dummy()
|
||
|
|
sol = solveset(old - new.subs(var, d), d)
|
||
|
|
if isinstance(sol, Complement):
|
||
|
|
e1 = sol.args[0]
|
||
|
|
e2 = sol.args[1]
|
||
|
|
sol = set(e1) - set(e2)
|
||
|
|
res = [dict(zip((d, ), sol))]
|
||
|
|
point = d.subs(res[0]).limit(old, self.point[i])
|
||
|
|
newvars[i] = var
|
||
|
|
newpt[i] = point
|
||
|
|
elif old not in syms:
|
||
|
|
del newvars[i], newpt[i]
|
||
|
|
if not syms and new == self.point[i]:
|
||
|
|
newvars.extend(syms)
|
||
|
|
newpt.extend([S.Zero]*len(syms))
|
||
|
|
else:
|
||
|
|
return
|
||
|
|
return Order(newexpr, *zip(newvars, newpt))
|
||
|
|
|
||
|
|
def _eval_conjugate(self):
|
||
|
|
expr = self.expr._eval_conjugate()
|
||
|
|
if expr is not None:
|
||
|
|
return self.func(expr, *self.args[1:])
|
||
|
|
|
||
|
|
def _eval_derivative(self, x):
|
||
|
|
return self.func(self.expr.diff(x), *self.args[1:]) or self
|
||
|
|
|
||
|
|
def _eval_transpose(self):
|
||
|
|
expr = self.expr._eval_transpose()
|
||
|
|
if expr is not None:
|
||
|
|
return self.func(expr, *self.args[1:])
|
||
|
|
|
||
|
|
def __neg__(self):
|
||
|
|
return self
|
||
|
|
|
||
|
|
O = Order
|