from sympy import Order, S, log, limit, lcm_list, im, re, Dummy, Piecewise from sympy.core import Add, Mul, Pow from sympy.core.basic import Basic from sympy.core.compatibility import iterable from sympy.core.expr import AtomicExpr, Expr from sympy.core.function import expand_mul from sympy.core.numbers import _sympifyit, oo, zoo from sympy.core.relational import is_le, is_lt, is_ge, is_gt from sympy.core.sympify import _sympify from sympy.functions.elementary.miscellaneous import Min, Max from sympy.logic.boolalg import And from sympy.sets.sets import (Interval, Intersection, FiniteSet, Union, Complement, EmptySet) from sympy.sets.fancysets import ImageSet from sympy.solvers.inequalities import solve_univariate_inequality from sympy.utilities import filldedent from sympy.multipledispatch import dispatch def continuous_domain(f, symbol, domain): """ Returns the intervals in the given domain for which the function is continuous. This method is limited by the ability to determine the various singularities and discontinuities of the given function. Parameters ========== f : Expr The concerned function. symbol : Symbol The variable for which the intervals are to be determined. domain : Interval The domain over which the continuity of the symbol has to be checked. Examples ======== >>> from sympy import Symbol, S, tan, log, pi, sqrt >>> from sympy.sets import Interval >>> from sympy.calculus.util import continuous_domain >>> x = Symbol('x') >>> continuous_domain(1/x, x, S.Reals) Union(Interval.open(-oo, 0), Interval.open(0, oo)) >>> continuous_domain(tan(x), x, Interval(0, pi)) Union(Interval.Ropen(0, pi/2), Interval.Lopen(pi/2, pi)) >>> continuous_domain(sqrt(x - 2), x, Interval(-5, 5)) Interval(2, 5) >>> continuous_domain(log(2*x - 1), x, S.Reals) Interval.open(1/2, oo) Returns ======= Interval Union of all intervals where the function is continuous. Raises ====== NotImplementedError If the method to determine continuity of such a function has not yet been developed. """ from sympy.solvers.inequalities import solve_univariate_inequality from sympy.calculus.singularities import singularities if domain.is_subset(S.Reals): constrained_interval = domain for atom in f.atoms(Pow): den = atom.exp.as_numer_denom()[1] if den.is_even and den.is_nonzero: constraint = solve_univariate_inequality(atom.base >= 0, symbol).as_set() constrained_interval = Intersection(constraint, constrained_interval) for atom in f.atoms(log): constraint = solve_univariate_inequality(atom.args[0] > 0, symbol).as_set() constrained_interval = Intersection(constraint, constrained_interval) return constrained_interval - singularities(f, symbol, domain) def function_range(f, symbol, domain): """ Finds the range of a function in a given domain. This method is limited by the ability to determine the singularities and determine limits. Parameters ========== f : Expr The concerned function. symbol : Symbol The variable for which the range of function is to be determined. domain : Interval The domain under which the range of the function has to be found. Examples ======== >>> from sympy import Symbol, S, exp, log, pi, sqrt, sin, tan >>> from sympy.sets import Interval >>> from sympy.calculus.util import function_range >>> x = Symbol('x') >>> function_range(sin(x), x, Interval(0, 2*pi)) Interval(-1, 1) >>> function_range(tan(x), x, Interval(-pi/2, pi/2)) Interval(-oo, oo) >>> function_range(1/x, x, S.Reals) Union(Interval.open(-oo, 0), Interval.open(0, oo)) >>> function_range(exp(x), x, S.Reals) Interval.open(0, oo) >>> function_range(log(x), x, S.Reals) Interval(-oo, oo) >>> function_range(sqrt(x), x , Interval(-5, 9)) Interval(0, 3) Returns ======= Interval Union of all ranges for all intervals under domain where function is continuous. Raises ====== NotImplementedError If any of the intervals, in the given domain, for which function is continuous are not finite or real, OR if the critical points of the function on the domain can't be found. """ from sympy.solvers.solveset import solveset if isinstance(domain, EmptySet): return S.EmptySet period = periodicity(f, symbol) if period == S.Zero: # the expression is constant wrt symbol return FiniteSet(f.expand()) if period is not None: if isinstance(domain, Interval): if (domain.inf - domain.sup).is_infinite: domain = Interval(0, period) elif isinstance(domain, Union): for sub_dom in domain.args: if isinstance(sub_dom, Interval) and \ ((sub_dom.inf - sub_dom.sup).is_infinite): domain = Interval(0, period) intervals = continuous_domain(f, symbol, domain) range_int = S.EmptySet if isinstance(intervals,(Interval, FiniteSet)): interval_iter = (intervals,) elif isinstance(intervals, Union): interval_iter = intervals.args else: raise NotImplementedError(filldedent(''' Unable to find range for the given domain. ''')) for interval in interval_iter: if isinstance(interval, FiniteSet): for singleton in interval: if singleton in domain: range_int += FiniteSet(f.subs(symbol, singleton)) elif isinstance(interval, Interval): vals = S.EmptySet critical_points = S.EmptySet critical_values = S.EmptySet bounds = ((interval.left_open, interval.inf, '+'), (interval.right_open, interval.sup, '-')) for is_open, limit_point, direction in bounds: if is_open: critical_values += FiniteSet(limit(f, symbol, limit_point, direction)) vals += critical_values else: vals += FiniteSet(f.subs(symbol, limit_point)) solution = solveset(f.diff(symbol), symbol, interval) if not iterable(solution): raise NotImplementedError( 'Unable to find critical points for {}'.format(f)) if isinstance(solution, ImageSet): raise NotImplementedError( 'Infinite number of critical points for {}'.format(f)) critical_points += solution for critical_point in critical_points: vals += FiniteSet(f.subs(symbol, critical_point)) left_open, right_open = False, False if critical_values is not S.EmptySet: if critical_values.inf == vals.inf: left_open = True if critical_values.sup == vals.sup: right_open = True range_int += Interval(vals.inf, vals.sup, left_open, right_open) else: raise NotImplementedError(filldedent(''' Unable to find range for the given domain. ''')) return range_int def not_empty_in(finset_intersection, *syms): """ Finds the domain of the functions in `finite_set` in which the `finite_set` is not-empty Parameters ========== finset_intersection : The unevaluated intersection of FiniteSet containing real-valued functions with Union of Sets syms : Tuple of symbols Symbol for which domain is to be found Raises ====== NotImplementedError The algorithms to find the non-emptiness of the given FiniteSet are not yet implemented. ValueError The input is not valid. RuntimeError It is a bug, please report it to the github issue tracker (https://github.com/sympy/sympy/issues). Examples ======== >>> from sympy import FiniteSet, Interval, not_empty_in, oo >>> from sympy.abc import x >>> not_empty_in(FiniteSet(x/2).intersect(Interval(0, 1)), x) Interval(0, 2) >>> not_empty_in(FiniteSet(x, x**2).intersect(Interval(1, 2)), x) Union(Interval(1, 2), Interval(-sqrt(2), -1)) >>> not_empty_in(FiniteSet(x**2/(x + 2)).intersect(Interval(1, oo)), x) Union(Interval.Lopen(-2, -1), Interval(2, oo)) """ # TODO: handle piecewise defined functions # TODO: handle transcendental functions # TODO: handle multivariate functions if len(syms) == 0: raise ValueError("One or more symbols must be given in syms.") if finset_intersection is S.EmptySet: return S.EmptySet if isinstance(finset_intersection, Union): elm_in_sets = finset_intersection.args[0] return Union(not_empty_in(finset_intersection.args[1], *syms), elm_in_sets) if isinstance(finset_intersection, FiniteSet): finite_set = finset_intersection _sets = S.Reals else: finite_set = finset_intersection.args[1] _sets = finset_intersection.args[0] if not isinstance(finite_set, FiniteSet): raise ValueError('A FiniteSet must be given, not %s: %s' % (type(finite_set), finite_set)) if len(syms) == 1: symb = syms[0] else: raise NotImplementedError('more than one variables %s not handled' % (syms,)) def elm_domain(expr, intrvl): """ Finds the domain of an expression in any given interval """ from sympy.solvers.solveset import solveset _start = intrvl.start _end = intrvl.end _singularities = solveset(expr.as_numer_denom()[1], symb, domain=S.Reals) if intrvl.right_open: if _end is S.Infinity: _domain1 = S.Reals else: _domain1 = solveset(expr < _end, symb, domain=S.Reals) else: _domain1 = solveset(expr <= _end, symb, domain=S.Reals) if intrvl.left_open: if _start is S.NegativeInfinity: _domain2 = S.Reals else: _domain2 = solveset(expr > _start, symb, domain=S.Reals) else: _domain2 = solveset(expr >= _start, symb, domain=S.Reals) # domain in the interval expr_with_sing = Intersection(_domain1, _domain2) expr_domain = Complement(expr_with_sing, _singularities) return expr_domain if isinstance(_sets, Interval): return Union(*[elm_domain(element, _sets) for element in finite_set]) if isinstance(_sets, Union): _domain = S.EmptySet for intrvl in _sets.args: _domain_element = Union(*[elm_domain(element, intrvl) for element in finite_set]) _domain = Union(_domain, _domain_element) return _domain def periodicity(f, symbol, check=False): """ Tests the given function for periodicity in the given symbol. Parameters ========== f : Expr. The concerned function. symbol : Symbol The variable for which the period is to be determined. check : Boolean, optional The flag to verify whether the value being returned is a period or not. Returns ======= period The period of the function is returned. `None` is returned when the function is aperiodic or has a complex period. The value of `0` is returned as the period of a constant function. Raises ====== NotImplementedError The value of the period computed cannot be verified. Notes ===== Currently, we do not support functions with a complex period. The period of functions having complex periodic values such as `exp`, `sinh` is evaluated to `None`. The value returned might not be the "fundamental" period of the given function i.e. it may not be the smallest periodic value of the function. The verification of the period through the `check` flag is not reliable due to internal simplification of the given expression. Hence, it is set to `False` by default. Examples ======== >>> from sympy import Symbol, sin, cos, tan, exp >>> from sympy.calculus.util import periodicity >>> x = Symbol('x') >>> f = sin(x) + sin(2*x) + sin(3*x) >>> periodicity(f, x) 2*pi >>> periodicity(sin(x)*cos(x), x) pi >>> periodicity(exp(tan(2*x) - 1), x) pi/2 >>> periodicity(sin(4*x)**cos(2*x), x) pi >>> periodicity(exp(x), x) """ from sympy.core.mod import Mod from sympy.core.relational import Relational from sympy.functions.elementary.exponential import exp from sympy.functions.elementary.complexes import Abs from sympy.functions.elementary.trigonometric import ( TrigonometricFunction, sin, cos, csc, sec) from sympy.simplify.simplify import simplify from sympy.solvers.decompogen import decompogen from sympy.polys.polytools import degree temp = Dummy('x', real=True) f = f.subs(symbol, temp) symbol = temp def _check(orig_f, period): '''Return the checked period or raise an error.''' new_f = orig_f.subs(symbol, symbol + period) if new_f.equals(orig_f): return period else: raise NotImplementedError(filldedent(''' The period of the given function cannot be verified. When `%s` was replaced with `%s + %s` in `%s`, the result was `%s` which was not recognized as being the same as the original function. So either the period was wrong or the two forms were not recognized as being equal. Set check=False to obtain the value.''' % (symbol, symbol, period, orig_f, new_f))) orig_f = f period = None if isinstance(f, Relational): f = f.lhs - f.rhs f = simplify(f) if symbol not in f.free_symbols: return S.Zero if isinstance(f, TrigonometricFunction): try: period = f.period(symbol) except NotImplementedError: pass if isinstance(f, Abs): arg = f.args[0] if isinstance(arg, (sec, csc, cos)): # all but tan and cot might have a # a period that is half as large # so recast as sin arg = sin(arg.args[0]) period = periodicity(arg, symbol) if period is not None and isinstance(arg, sin): # the argument of Abs was a trigonometric other than # cot or tan; test to see if the half-period # is valid. Abs(arg) has behaviour equivalent to # orig_f, so use that for test: orig_f = Abs(arg) try: return _check(orig_f, period/2) except NotImplementedError as err: if check: raise NotImplementedError(err) # else let new orig_f and period be # checked below if isinstance(f, exp) or (f.is_Pow and f.base == S.Exp1): f = Pow(S.Exp1, expand_mul(f.exp)) if im(f) != 0: period_real = periodicity(re(f), symbol) period_imag = periodicity(im(f), symbol) if period_real is not None and period_imag is not None: period = lcim([period_real, period_imag]) if f.is_Pow and f.base != S.Exp1: base, expo = f.args base_has_sym = base.has(symbol) expo_has_sym = expo.has(symbol) if base_has_sym and not expo_has_sym: period = periodicity(base, symbol) elif expo_has_sym and not base_has_sym: period = periodicity(expo, symbol) else: period = _periodicity(f.args, symbol) elif f.is_Mul: coeff, g = f.as_independent(symbol, as_Add=False) if isinstance(g, TrigonometricFunction) or coeff is not S.One: period = periodicity(g, symbol) else: period = _periodicity(g.args, symbol) elif f.is_Add: k, g = f.as_independent(symbol) if k is not S.Zero: return periodicity(g, symbol) period = _periodicity(g.args, symbol) elif isinstance(f, Mod): a, n = f.args if a == symbol: period = n elif isinstance(a, TrigonometricFunction): period = periodicity(a, symbol) #check if 'f' is linear in 'symbol' elif (a.is_polynomial(symbol) and degree(a, symbol) == 1 and symbol not in n.free_symbols): period = Abs(n / a.diff(symbol)) elif isinstance(f, Piecewise): pass # not handling Piecewise yet as the return type is not favorable elif period is None: from sympy.solvers.decompogen import compogen g_s = decompogen(f, symbol) num_of_gs = len(g_s) if num_of_gs > 1: for index, g in enumerate(reversed(g_s)): start_index = num_of_gs - 1 - index g = compogen(g_s[start_index:], symbol) if g != orig_f and g != f: # Fix for issue 12620 period = periodicity(g, symbol) if period is not None: break if period is not None: if check: return _check(orig_f, period) return period return None def _periodicity(args, symbol): """ Helper for `periodicity` to find the period of a list of simpler functions. It uses the `lcim` method to find the least common period of all the functions. Parameters ========== args : Tuple of Symbol All the symbols present in a function. symbol : Symbol The symbol over which the function is to be evaluated. Returns ======= period The least common period of the function for all the symbols of the function. None if for at least one of the symbols the function is aperiodic """ periods = [] for f in args: period = periodicity(f, symbol) if period is None: return None if period is not S.Zero: periods.append(period) if len(periods) > 1: return lcim(periods) if periods: return periods[0] def lcim(numbers): """Returns the least common integral multiple of a list of numbers. The numbers can be rational or irrational or a mixture of both. `None` is returned for incommensurable numbers. Parameters ========== numbers : list Numbers (rational and/or irrational) for which lcim is to be found. Returns ======= number lcim if it exists, otherwise `None` for incommensurable numbers. Examples ======== >>> from sympy import S, pi >>> from sympy.calculus.util import lcim >>> lcim([S(1)/2, S(3)/4, S(5)/6]) 15/2 >>> lcim([2*pi, 3*pi, pi, pi/2]) 6*pi >>> lcim([S(1), 2*pi]) """ result = None if all(num.is_irrational for num in numbers): factorized_nums = list(map(lambda num: num.factor(), numbers)) factors_num = list( map(lambda num: num.as_coeff_Mul(), factorized_nums)) term = factors_num[0][1] if all(factor == term for coeff, factor in factors_num): common_term = term coeffs = [coeff for coeff, factor in factors_num] result = lcm_list(coeffs) * common_term elif all(num.is_rational for num in numbers): result = lcm_list(numbers) else: pass return result def is_convex(f, *syms, domain=S.Reals): """Determines the convexity of the function passed in the argument. Parameters ========== f : Expr The concerned function. syms : Tuple of symbols The variables with respect to which the convexity is to be determined. domain : Interval, optional The domain over which the convexity of the function has to be checked. If unspecified, S.Reals will be the default domain. Returns ======= Boolean The method returns `True` if the function is convex otherwise it returns `False`. Raises ====== NotImplementedError The check for the convexity of multivariate functions is not implemented yet. Notes ===== To determine concavity of a function pass `-f` as the concerned function. To determine logarithmic convexity of a function pass log(f) as concerned function. To determine logartihmic concavity of a function pass -log(f) as concerned function. Currently, convexity check of multivariate functions is not handled. Examples ======== >>> from sympy import symbols, exp, oo, Interval >>> from sympy.calculus.util import is_convex >>> x = symbols('x') >>> is_convex(exp(x), x) True >>> is_convex(x**3, x, domain = Interval(-1, oo)) False References ========== .. [1] https://en.wikipedia.org/wiki/Convex_function .. [2] http://www.ifp.illinois.edu/~angelia/L3_convfunc.pdf .. [3] https://en.wikipedia.org/wiki/Logarithmically_convex_function .. [4] https://en.wikipedia.org/wiki/Logarithmically_concave_function .. [5] https://en.wikipedia.org/wiki/Concave_function """ if len(syms) > 1: raise NotImplementedError( "The check for the convexity of multivariate functions is not implemented yet.") f = _sympify(f) var = syms[0] condition = f.diff(var, 2) < 0 if solve_univariate_inequality(condition, var, False, domain): return False return True def stationary_points(f, symbol, domain=S.Reals): """ Returns the stationary points of a function (where derivative of the function is 0) in the given domain. Parameters ========== f : Expr The concerned function. symbol : Symbol The variable for which the stationary points are to be determined. domain : Interval The domain over which the stationary points have to be checked. If unspecified, S.Reals will be the default domain. Returns ======= Set A set of stationary points for the function. If there are no stationary point, an EmptySet is returned. Examples ======== >>> from sympy import Symbol, S, sin, pi, pprint, stationary_points >>> from sympy.sets import Interval >>> x = Symbol('x') >>> stationary_points(1/x, x, S.Reals) EmptySet >>> pprint(stationary_points(sin(x), x), use_unicode=False) pi 3*pi {2*n*pi + -- | n in Integers} U {2*n*pi + ---- | n in Integers} 2 2 >>> stationary_points(sin(x),x, Interval(0, 4*pi)) {pi/2, 3*pi/2, 5*pi/2, 7*pi/2} """ from sympy import solveset, diff if isinstance(domain, EmptySet): return S.EmptySet domain = continuous_domain(f, symbol, domain) set = solveset(diff(f, symbol), symbol, domain) return set def maximum(f, symbol, domain=S.Reals): """ Returns the maximum value of a function in the given domain. Parameters ========== f : Expr The concerned function. symbol : Symbol The variable for maximum value needs to be determined. domain : Interval The domain over which the maximum have to be checked. If unspecified, then Global maximum is returned. Returns ======= number Maximum value of the function in given domain. Examples ======== >>> from sympy import Symbol, S, sin, cos, pi, maximum >>> from sympy.sets import Interval >>> x = Symbol('x') >>> f = -x**2 + 2*x + 5 >>> maximum(f, x, S.Reals) 6 >>> maximum(sin(x), x, Interval(-pi, pi/4)) sqrt(2)/2 >>> maximum(sin(x)*cos(x), x) 1/2 """ from sympy import Symbol if isinstance(symbol, Symbol): if isinstance(domain, EmptySet): raise ValueError("Maximum value not defined for empty domain.") return function_range(f, symbol, domain).sup else: raise ValueError("%s is not a valid symbol." % symbol) def minimum(f, symbol, domain=S.Reals): """ Returns the minimum value of a function in the given domain. Parameters ========== f : Expr The concerned function. symbol : Symbol The variable for minimum value needs to be determined. domain : Interval The domain over which the minimum have to be checked. If unspecified, then Global minimum is returned. Returns ======= number Minimum value of the function in the given domain. Examples ======== >>> from sympy import Symbol, S, sin, cos, minimum >>> from sympy.sets import Interval >>> x = Symbol('x') >>> f = x**2 + 2*x + 5 >>> minimum(f, x, S.Reals) 4 >>> minimum(sin(x), x, Interval(2, 3)) sin(3) >>> minimum(sin(x)*cos(x), x) -1/2 """ from sympy import Symbol if isinstance(symbol, Symbol): if isinstance(domain, EmptySet): raise ValueError("Minimum value not defined for empty domain.") return function_range(f, symbol, domain).inf else: raise ValueError("%s is not a valid symbol." % symbol) class AccumulationBounds(AtomicExpr): r""" # Note AccumulationBounds has an alias: AccumBounds AccumulationBounds represent an interval `[a, b]`, which is always closed at the ends. Here `a` and `b` can be any value from extended real numbers. The intended meaning of AccummulationBounds is to give an approximate location of the accumulation points of a real function at a limit point. Let `a` and `b` be reals such that a <= b. `\left\langle a, b\right\rangle = \{x \in \mathbb{R} \mid a \le x \le b\}` `\left\langle -\infty, b\right\rangle = \{x \in \mathbb{R} \mid x \le b\} \cup \{-\infty, \infty\}` `\left\langle a, \infty \right\rangle = \{x \in \mathbb{R} \mid a \le x\} \cup \{-\infty, \infty\}` `\left\langle -\infty, \infty \right\rangle = \mathbb{R} \cup \{-\infty, \infty\}` `oo` and `-oo` are added to the second and third definition respectively, since if either `-oo` or `oo` is an argument, then the other one should be included (though not as an end point). This is forced, since we have, for example, `1/AccumBounds(0, 1) = AccumBounds(1, oo)`, and the limit at `0` is not one-sided. As x tends to `0-`, then `1/x -> -oo`, so `-oo` should be interpreted as belonging to `AccumBounds(1, oo)` though it need not appear explicitly. In many cases it suffices to know that the limit set is bounded. However, in some other cases more exact information could be useful. For example, all accumulation values of cos(x) + 1 are non-negative. (AccumBounds(-1, 1) + 1 = AccumBounds(0, 2)) A AccumulationBounds object is defined to be real AccumulationBounds, if its end points are finite reals. Let `X`, `Y` be real AccumulationBounds, then their sum, difference, product are defined to be the following sets: `X + Y = \{ x+y \mid x \in X \cap y \in Y\}` `X - Y = \{ x-y \mid x \in X \cap y \in Y\}` `X * Y = \{ x*y \mid x \in X \cap y \in Y\}` When an AccumBounds is raised to a negative power, if 0 is contained between the bounds then an infinite range is returned, otherwise if an endpoint is 0 then a semi-infinite range with consistent sign will be returned. AccumBounds in expressions behave a lot like Intervals but the semantics are not necessarily the same. Division (or exponentiation to a negative integer power) could be handled with *intervals* by returning a union of the results obtained after splitting the bounds between negatives and positives, but that is not done with AccumBounds. In addition, bounds are assumed to be independent of each other; if the same bound is used in more than one place in an expression, the result may not be the supremum or infimum of the expression (see below). Finally, when a boundary is ``1``, exponentiation to the power of ``oo`` yields ``oo``, neither ``1`` nor ``nan``. Examples ======== >>> from sympy import AccumBounds, sin, exp, log, pi, E, S, oo >>> from sympy.abc import x >>> AccumBounds(0, 1) + AccumBounds(1, 2) AccumBounds(1, 3) >>> AccumBounds(0, 1) - AccumBounds(0, 2) AccumBounds(-2, 1) >>> AccumBounds(-2, 3)*AccumBounds(-1, 1) AccumBounds(-3, 3) >>> AccumBounds(1, 2)*AccumBounds(3, 5) AccumBounds(3, 10) The exponentiation of AccumulationBounds is defined as follows: If 0 does not belong to `X` or `n > 0` then `X^n = \{ x^n \mid x \in X\}` >>> AccumBounds(1, 4)**(S(1)/2) AccumBounds(1, 2) otherwise, an infinite or semi-infinite result is obtained: >>> 1/AccumBounds(-1, 1) AccumBounds(-oo, oo) >>> 1/AccumBounds(0, 2) AccumBounds(1/2, oo) >>> 1/AccumBounds(-oo, 0) AccumBounds(-oo, 0) A boundary of 1 will always generate all nonnegatives: >>> AccumBounds(1, 2)**oo AccumBounds(0, oo) >>> AccumBounds(0, 1)**oo AccumBounds(0, oo) If the exponent is itself an AccumulationBounds or is not an integer then unevaluated results will be returned unless the base values are positive: >>> AccumBounds(2, 3)**AccumBounds(-1, 2) AccumBounds(1/3, 9) >>> AccumBounds(-2, 3)**AccumBounds(-1, 2) AccumBounds(-2, 3)**AccumBounds(-1, 2) >>> AccumBounds(-2, -1)**(S(1)/2) sqrt(AccumBounds(-2, -1)) Note: `^2` is not same as `*` >>> AccumBounds(-1, 1)**2 AccumBounds(0, 1) >>> AccumBounds(1, 3) < 4 True >>> AccumBounds(1, 3) < -1 False Some elementary functions can also take AccumulationBounds as input. A function `f` evaluated for some real AccumulationBounds `` is defined as `f(\left\langle a, b\right\rangle) = \{ f(x) \mid a \le x \le b \}` >>> sin(AccumBounds(pi/6, pi/3)) AccumBounds(1/2, sqrt(3)/2) >>> exp(AccumBounds(0, 1)) AccumBounds(1, E) >>> log(AccumBounds(1, E)) AccumBounds(0, 1) Some symbol in an expression can be substituted for a AccumulationBounds object. But it doesn't necessarily evaluate the AccumulationBounds for that expression. The same expression can be evaluated to different values depending upon the form it is used for substitution since each instance of an AccumulationBounds is considered independent. For example: >>> (x**2 + 2*x + 1).subs(x, AccumBounds(-1, 1)) AccumBounds(-1, 4) >>> ((x + 1)**2).subs(x, AccumBounds(-1, 1)) AccumBounds(0, 4) References ========== .. [1] https://en.wikipedia.org/wiki/Interval_arithmetic .. [2] http://fab.cba.mit.edu/classes/S62.12/docs/Hickey_interval.pdf Notes ===== Do not use ``AccumulationBounds`` for floating point interval arithmetic calculations, use ``mpmath.iv`` instead. """ is_extended_real = True def __new__(cls, min, max): min = _sympify(min) max = _sympify(max) # Only allow real intervals (use symbols with 'is_extended_real=True'). if not min.is_extended_real or not max.is_extended_real: raise ValueError("Only real AccumulationBounds are supported") if max == min: return max # Make sure that the created AccumBounds object will be valid. if max.is_number and min.is_number: bad = max.is_comparable and min.is_comparable and max < min else: bad = (max - min).is_extended_negative if bad: raise ValueError( "Lower limit should be smaller than upper limit") return Basic.__new__(cls, min, max) # setting the operation priority _op_priority = 11.0 def _eval_is_real(self): if self.min.is_real and self.max.is_real: return True @property def min(self): """ Returns the minimum possible value attained by AccumulationBounds object. Examples ======== >>> from sympy import AccumBounds >>> AccumBounds(1, 3).min 1 """ return self.args[0] @property def max(self): """ Returns the maximum possible value attained by AccumulationBounds object. Examples ======== >>> from sympy import AccumBounds >>> AccumBounds(1, 3).max 3 """ return self.args[1] @property def delta(self): """ Returns the difference of maximum possible value attained by AccumulationBounds object and minimum possible value attained by AccumulationBounds object. Examples ======== >>> from sympy import AccumBounds >>> AccumBounds(1, 3).delta 2 """ return self.max - self.min @property def mid(self): """ Returns the mean of maximum possible value attained by AccumulationBounds object and minimum possible value attained by AccumulationBounds object. Examples ======== >>> from sympy import AccumBounds >>> AccumBounds(1, 3).mid 2 """ return (self.min + self.max) / 2 @_sympifyit('other', NotImplemented) def _eval_power(self, other): return self.__pow__(other) @_sympifyit('other', NotImplemented) def __add__(self, other): if isinstance(other, Expr): if isinstance(other, AccumBounds): return AccumBounds( Add(self.min, other.min), Add(self.max, other.max)) if other is S.Infinity and self.min is S.NegativeInfinity or \ other is S.NegativeInfinity and self.max is S.Infinity: return AccumBounds(-oo, oo) elif other.is_extended_real: if self.min is S.NegativeInfinity and self.max is S.Infinity: return AccumBounds(-oo, oo) elif self.min is S.NegativeInfinity: return AccumBounds(-oo, self.max + other) elif self.max is S.Infinity: return AccumBounds(self.min + other, oo) else: return AccumBounds(Add(self.min, other), Add(self.max, other)) return Add(self, other, evaluate=False) return NotImplemented __radd__ = __add__ def __neg__(self): return AccumBounds(-self.max, -self.min) @_sympifyit('other', NotImplemented) def __sub__(self, other): if isinstance(other, Expr): if isinstance(other, AccumBounds): return AccumBounds( Add(self.min, -other.max), Add(self.max, -other.min)) if other is S.NegativeInfinity and self.min is S.NegativeInfinity or \ other is S.Infinity and self.max is S.Infinity: return AccumBounds(-oo, oo) elif other.is_extended_real: if self.min is S.NegativeInfinity and self.max is S.Infinity: return AccumBounds(-oo, oo) elif self.min is S.NegativeInfinity: return AccumBounds(-oo, self.max - other) elif self.max is S.Infinity: return AccumBounds(self.min - other, oo) else: return AccumBounds( Add(self.min, -other), Add(self.max, -other)) return Add(self, -other, evaluate=False) return NotImplemented @_sympifyit('other', NotImplemented) def __rsub__(self, other): return self.__neg__() + other @_sympifyit('other', NotImplemented) def __mul__(self, other): if self.args == (-oo, oo): return self if isinstance(other, Expr): if isinstance(other, AccumBounds): if other.args == (-oo, oo): return other v = set() for i in self.args: vi = other*i for i in vi.args or (vi,): v.add(i) return AccumBounds(Min(*v), Max(*v)) if other is S.Infinity: if self.min.is_zero: return AccumBounds(0, oo) if self.max.is_zero: return AccumBounds(-oo, 0) if other is S.NegativeInfinity: if self.min.is_zero: return AccumBounds(-oo, 0) if self.max.is_zero: return AccumBounds(0, oo) if other.is_extended_real: if other.is_zero: if self.max is S.Infinity: return AccumBounds(0, oo) if self.min is S.NegativeInfinity: return AccumBounds(-oo, 0) return S.Zero if other.is_extended_positive: return AccumBounds( Mul(self.min, other), Mul(self.max, other)) elif other.is_extended_negative: return AccumBounds( Mul(self.max, other), Mul(self.min, other)) if isinstance(other, Order): return other return Mul(self, other, evaluate=False) return NotImplemented __rmul__ = __mul__ @_sympifyit('other', NotImplemented) def __truediv__(self, other): if isinstance(other, Expr): if isinstance(other, AccumBounds): if other.min.is_positive or other.max.is_negative: return self * AccumBounds(1/other.max, 1/other.min) if (self.min.is_extended_nonpositive and self.max.is_extended_nonnegative and other.min.is_extended_nonpositive and other.max.is_extended_nonnegative): if self.min.is_zero and other.min.is_zero: return AccumBounds(0, oo) if self.max.is_zero and other.min.is_zero: return AccumBounds(-oo, 0) return AccumBounds(-oo, oo) if self.max.is_extended_negative: if other.min.is_extended_negative: if other.max.is_zero: return AccumBounds(self.max / other.min, oo) if other.max.is_extended_positive: # if we were dealing with intervals we would return # Union(Interval(-oo, self.max/other.max), # Interval(self.max/other.min, oo)) return AccumBounds(-oo, oo) if other.min.is_zero and other.max.is_extended_positive: return AccumBounds(-oo, self.max / other.max) if self.min.is_extended_positive: if other.min.is_extended_negative: if other.max.is_zero: return AccumBounds(-oo, self.min / other.min) if other.max.is_extended_positive: # if we were dealing with intervals we would return # Union(Interval(-oo, self.min/other.min), # Interval(self.min/other.max, oo)) return AccumBounds(-oo, oo) if other.min.is_zero and other.max.is_extended_positive: return AccumBounds(self.min / other.max, oo) elif other.is_extended_real: if other is S.Infinity or other is S.NegativeInfinity: if self == AccumBounds(-oo, oo): return AccumBounds(-oo, oo) if self.max is S.Infinity: return AccumBounds(Min(0, other), Max(0, other)) if self.min is S.NegativeInfinity: return AccumBounds(Min(0, -other), Max(0, -other)) if other.is_extended_positive: return AccumBounds(self.min / other, self.max / other) elif other.is_extended_negative: return AccumBounds(self.max / other, self.min / other) if (1 / other) is S.ComplexInfinity: return Mul(self, 1 / other, evaluate=False) else: return Mul(self, 1 / other) return NotImplemented @_sympifyit('other', NotImplemented) def __rtruediv__(self, other): if isinstance(other, Expr): if other.is_extended_real: if other.is_zero: return S.Zero if (self.min.is_extended_nonpositive and self.max.is_extended_nonnegative): if self.min.is_zero: if other.is_extended_positive: return AccumBounds(Mul(other, 1 / self.max), oo) if other.is_extended_negative: return AccumBounds(-oo, Mul(other, 1 / self.max)) if self.max.is_zero: if other.is_extended_positive: return AccumBounds(-oo, Mul(other, 1 / self.min)) if other.is_extended_negative: return AccumBounds(Mul(other, 1 / self.min), oo) return AccumBounds(-oo, oo) else: return AccumBounds(Min(other / self.min, other / self.max), Max(other / self.min, other / self.max)) return Mul(other, 1 / self, evaluate=False) else: return NotImplemented @_sympifyit('other', NotImplemented) def __pow__(self, other): if isinstance(other, Expr): if other is S.Infinity: if self.min.is_extended_nonnegative: if self.max < 1: return S.Zero if self.min > 1: return S.Infinity return AccumBounds(0, oo) elif self.max.is_extended_negative: if self.min > -1: return S.Zero if self.max < -1: return zoo return S.NaN else: if self.min > -1: if self.max < 1: return S.Zero return AccumBounds(0, oo) return AccumBounds(-oo, oo) if other is S.NegativeInfinity: return (1/self)**oo # generically true if (self.max - self.min).is_nonnegative: # well defined if self.min.is_nonnegative: # no 0 to worry about if other.is_nonnegative: # no infinity to worry about return self.func(self.min**other, self.max**other) if other.is_zero: return S.One # x**0 = 1 if other.is_Integer or other.is_integer: if self.min.is_extended_positive: return AccumBounds( Min(self.min**other, self.max**other), Max(self.min**other, self.max**other)) elif self.max.is_extended_negative: return AccumBounds( Min(self.max**other, self.min**other), Max(self.max**other, self.min**other)) if other % 2 == 0: if other.is_extended_negative: if self.min.is_zero: return AccumBounds(self.max**other, oo) if self.max.is_zero: return AccumBounds(self.min**other, oo) return AccumBounds(0, oo) return AccumBounds( S.Zero, Max(self.min**other, self.max**other)) elif other % 2 == 1: if other.is_extended_negative: if self.min.is_zero: return AccumBounds(self.max**other, oo) if self.max.is_zero: return AccumBounds(-oo, self.min**other) return AccumBounds(-oo, oo) return AccumBounds(self.min**other, self.max**other) # non-integer exponent # 0**neg or neg**frac yields complex if (other.is_number or other.is_rational) and ( self.min.is_extended_nonnegative or ( other.is_extended_nonnegative and self.min.is_extended_nonnegative)): num, den = other.as_numer_denom() if num is S.One: return AccumBounds(*[i**(1/den) for i in self.args]) elif den is not S.One: # e.g. if other is not Float return (self**num)**(1/den) # ok for non-negative base if isinstance(other, AccumBounds): if (self.min.is_extended_positive or self.min.is_extended_nonnegative and other.min.is_extended_nonnegative): p = [self**i for i in other.args] if not any(i.is_Pow for i in p): a = [j for i in p for j in i.args or (i,)] try: return self.func(min(a), max(a)) except TypeError: # can't sort pass return Pow(self, other, evaluate=False) return NotImplemented @_sympifyit('other', NotImplemented) def __rpow__(self, other): if other.is_real and other.is_extended_nonnegative and ( self.max - self.min).is_extended_positive: if other is S.One: return S.One if other.is_extended_positive: a, b = [other**i for i in self.args] if min(a, b) != a: a, b = b, a return self.func(a, b) if other.is_zero: if self.min.is_zero: return self.func(0, 1) if self.min.is_extended_positive: return S.Zero return Pow(other, self, evaluate=False) def __abs__(self): if self.max.is_extended_negative: return self.__neg__() elif self.min.is_extended_negative: return AccumBounds(S.Zero, Max(abs(self.min), self.max)) else: return self def __contains__(self, other): """ Returns True if other is contained in self, where other belongs to extended real numbers, False if not contained, otherwise TypeError is raised. Examples ======== >>> from sympy import AccumBounds, oo >>> 1 in AccumBounds(-1, 3) True -oo and oo go together as limits (in AccumulationBounds). >>> -oo in AccumBounds(1, oo) True >>> oo in AccumBounds(-oo, 0) True """ other = _sympify(other) if other is S.Infinity or other is S.NegativeInfinity: if self.min is S.NegativeInfinity or self.max is S.Infinity: return True return False rv = And(self.min <= other, self.max >= other) if rv not in (True, False): raise TypeError("input failed to evaluate") return rv def intersection(self, other): """ Returns the intersection of 'self' and 'other'. Here other can be an instance of FiniteSet or AccumulationBounds. Parameters ========== other: AccumulationBounds Another AccumulationBounds object with which the intersection has to be computed. Returns ======= AccumulationBounds Intersection of 'self' and 'other'. Examples ======== >>> from sympy import AccumBounds, FiniteSet >>> AccumBounds(1, 3).intersection(AccumBounds(2, 4)) AccumBounds(2, 3) >>> AccumBounds(1, 3).intersection(AccumBounds(4, 6)) EmptySet >>> AccumBounds(1, 4).intersection(FiniteSet(1, 2, 5)) {1, 2} """ if not isinstance(other, (AccumBounds, FiniteSet)): raise TypeError( "Input must be AccumulationBounds or FiniteSet object") if isinstance(other, FiniteSet): fin_set = S.EmptySet for i in other: if i in self: fin_set = fin_set + FiniteSet(i) return fin_set if self.max < other.min or self.min > other.max: return S.EmptySet if self.min <= other.min: if self.max <= other.max: return AccumBounds(other.min, self.max) if self.max > other.max: return other if other.min <= self.min: if other.max < self.max: return AccumBounds(self.min, other.max) if other.max > self.max: return self def union(self, other): # TODO : Devise a better method for Union of AccumBounds # this method is not actually correct and # can be made better if not isinstance(other, AccumBounds): raise TypeError( "Input must be AccumulationBounds or FiniteSet object") if self.min <= other.min and self.max >= other.min: return AccumBounds(self.min, Max(self.max, other.max)) if other.min <= self.min and other.max >= self.min: return AccumBounds(other.min, Max(self.max, other.max)) @dispatch(AccumulationBounds, AccumulationBounds) # type: ignore # noqa:F811 def _eval_is_le(lhs, rhs): # noqa:F811 if is_le(lhs.max, rhs.min): return True if is_gt(lhs.min, rhs.max): return False @dispatch(AccumulationBounds, Basic) # type: ignore # noqa:F811 def _eval_is_le(lhs, rhs): # noqa: F811 """ Returns True if range of values attained by `self` AccumulationBounds object is greater than the range of values attained by `other`, where other may be any value of type AccumulationBounds object or extended real number value, False if `other` satisfies the same property, else an unevaluated Relational. Examples ======== >>> from sympy import AccumBounds, oo >>> AccumBounds(1, 3) > AccumBounds(4, oo) False >>> AccumBounds(1, 4) > AccumBounds(3, 4) AccumBounds(1, 4) > AccumBounds(3, 4) >>> AccumBounds(1, oo) > -1 True """ if not rhs.is_extended_real: raise TypeError( "Invalid comparison of %s %s" % (type(rhs), rhs)) elif rhs.is_comparable: if is_le(lhs.max, rhs): return True if is_gt(lhs.min, rhs): return False @dispatch(AccumulationBounds, AccumulationBounds) def _eval_is_ge(lhs, rhs): # noqa:F811 if is_ge(lhs.min, rhs.max): return True if is_lt(lhs.max, rhs.min): return False @dispatch(AccumulationBounds, Expr) # type:ignore def _eval_is_ge(lhs, rhs): # noqa: F811 """ Returns True if range of values attained by `lhs` AccumulationBounds object is less that the range of values attained by `rhs`, where other may be any value of type AccumulationBounds object or extended real number value, False if `rhs` satisfies the same property, else an unevaluated Relational. Examples ======== >>> from sympy import AccumBounds, oo >>> AccumBounds(1, 3) >= AccumBounds(4, oo) False >>> AccumBounds(1, 4) >= AccumBounds(3, 4) AccumBounds(1, 4) >= AccumBounds(3, 4) >>> AccumBounds(1, oo) >= 1 True """ if not rhs.is_extended_real: raise TypeError( "Invalid comparison of %s %s" % (type(rhs), rhs)) elif rhs.is_comparable: if is_ge(lhs.min, rhs): return True if is_lt(lhs.max, rhs): return False @dispatch(Expr, AccumulationBounds) # type:ignore def _eval_is_ge(lhs, rhs): # noqa:F811 if not lhs.is_extended_real: raise TypeError( "Invalid comparison of %s %s" % (type(lhs), lhs)) elif lhs.is_comparable: if is_le(rhs.max, lhs): return True if is_gt(rhs.min, lhs): return False @dispatch(AccumulationBounds, AccumulationBounds) # type:ignore def _eval_is_ge(lhs, rhs): # noqa:F811 if is_ge(lhs.min, rhs.max): return True if is_lt(lhs.max, rhs.min): return False # setting an alias for AccumulationBounds AccumBounds = AccumulationBounds