""" Singularities ============= This module implements algorithms for finding singularities for a function and identifying types of functions. The differential calculus methods in this module include methods to identify the following function types in the given ``Interval``: - Increasing - Strictly Increasing - Decreasing - Strictly Decreasing - Monotonic """ from sympy.core.power import Pow from sympy.core.singleton import S from sympy.core.symbol import Symbol from sympy.core.sympify import sympify from sympy.functions.elementary.exponential import log from sympy.functions.elementary.trigonometric import sec, csc, cot, tan, cos from sympy.utilities.misc import filldedent def singularities(expression, symbol, domain=None): """ Find singularities of a given function. Parameters ========== expression : Expr The target function in which singularities need to be found. symbol : Symbol The symbol over the values of which the singularity in expression in being searched for. Returns ======= Set A set of values for ``symbol`` for which ``expression`` has a singularity. An ``EmptySet`` is returned if ``expression`` has no singularities for any given value of ``Symbol``. Raises ====== NotImplementedError Methods for determining the singularities of this function have not been developed. Notes ===== This function does not find non-isolated singularities nor does it find branch points of the expression. Currently supported functions are: - univariate continuous (real or complex) functions References ========== .. [1] https://en.wikipedia.org/wiki/Mathematical_singularity Examples ======== >>> from sympy import singularities, Symbol, log >>> x = Symbol('x', real=True) >>> y = Symbol('y', real=False) >>> singularities(x**2 + x + 1, x) EmptySet >>> singularities(1/(x + 1), x) {-1} >>> singularities(1/(y**2 + 1), y) {-I, I} >>> singularities(1/(y**3 + 1), y) {-1, 1/2 - sqrt(3)*I/2, 1/2 + sqrt(3)*I/2} >>> singularities(log(x), x) {0} """ from sympy.solvers.solveset import solveset if domain is None: domain = S.Reals if symbol.is_real else S.Complexes try: sings = S.EmptySet for i in expression.rewrite([sec, csc, cot, tan], cos).atoms(Pow): if i.exp.is_infinite: raise NotImplementedError if i.exp.is_negative: sings += solveset(i.base, symbol, domain) for i in expression.atoms(log): sings += solveset(i.args[0], symbol, domain) return sings except NotImplementedError: raise NotImplementedError(filldedent(''' Methods for determining the singularities of this function have not been developed.''')) ########################################################################### # DIFFERENTIAL CALCULUS METHODS # ########################################################################### def monotonicity_helper(expression, predicate, interval=S.Reals, symbol=None): """ Helper function for functions checking function monotonicity. Parameters ========== expression : Expr The target function which is being checked predicate : function The property being tested for. The function takes in an integer and returns a boolean. The integer input is the derivative and the boolean result should be true if the property is being held, and false otherwise. interval : Set, optional The range of values in which we are testing, defaults to all reals. symbol : Symbol, optional The symbol present in expression which gets varied over the given range. It returns a boolean indicating whether the interval in which the function's derivative satisfies given predicate is a superset of the given interval. Returns ======= Boolean True if ``predicate`` is true for all the derivatives when ``symbol`` is varied in ``range``, False otherwise. """ from sympy.solvers.solveset import solveset expression = sympify(expression) free = expression.free_symbols if symbol is None: if len(free) > 1: raise NotImplementedError( 'The function has not yet been implemented' ' for all multivariate expressions.' ) variable = symbol or (free.pop() if free else Symbol('x')) derivative = expression.diff(variable) predicate_interval = solveset(predicate(derivative), variable, S.Reals) return interval.is_subset(predicate_interval) def is_increasing(expression, interval=S.Reals, symbol=None): """ Return whether the function is increasing in the given interval. Parameters ========== expression : Expr The target function which is being checked. interval : Set, optional The range of values in which we are testing (defaults to set of all real numbers). symbol : Symbol, optional The symbol present in expression which gets varied over the given range. Returns ======= Boolean True if ``expression`` is increasing (either strictly increasing or constant) in the given ``interval``, False otherwise. Examples ======== >>> from sympy import is_increasing >>> from sympy.abc import x, y >>> from sympy import S, Interval, oo >>> is_increasing(x**3 - 3*x**2 + 4*x, S.Reals) True >>> is_increasing(-x**2, Interval(-oo, 0)) True >>> is_increasing(-x**2, Interval(0, oo)) False >>> is_increasing(4*x**3 - 6*x**2 - 72*x + 30, Interval(-2, 3)) False >>> is_increasing(x**2 + y, Interval(1, 2), x) True """ return monotonicity_helper(expression, lambda x: x >= 0, interval, symbol) def is_strictly_increasing(expression, interval=S.Reals, symbol=None): """ Return whether the function is strictly increasing in the given interval. Parameters ========== expression : Expr The target function which is being checked. interval : Set, optional The range of values in which we are testing (defaults to set of all real numbers). symbol : Symbol, optional The symbol present in expression which gets varied over the given range. Returns ======= Boolean True if ``expression`` is strictly increasing in the given ``interval``, False otherwise. Examples ======== >>> from sympy import is_strictly_increasing >>> from sympy.abc import x, y >>> from sympy import Interval, oo >>> is_strictly_increasing(4*x**3 - 6*x**2 - 72*x + 30, Interval.Ropen(-oo, -2)) True >>> is_strictly_increasing(4*x**3 - 6*x**2 - 72*x + 30, Interval.Lopen(3, oo)) True >>> is_strictly_increasing(4*x**3 - 6*x**2 - 72*x + 30, Interval.open(-2, 3)) False >>> is_strictly_increasing(-x**2, Interval(0, oo)) False >>> is_strictly_increasing(-x**2 + y, Interval(-oo, 0), x) False """ return monotonicity_helper(expression, lambda x: x > 0, interval, symbol) def is_decreasing(expression, interval=S.Reals, symbol=None): """ Return whether the function is decreasing in the given interval. Parameters ========== expression : Expr The target function which is being checked. interval : Set, optional The range of values in which we are testing (defaults to set of all real numbers). symbol : Symbol, optional The symbol present in expression which gets varied over the given range. Returns ======= Boolean True if ``expression`` is decreasing (either strictly decreasing or constant) in the given ``interval``, False otherwise. Examples ======== >>> from sympy import is_decreasing >>> from sympy.abc import x, y >>> from sympy import S, Interval, oo >>> is_decreasing(1/(x**2 - 3*x), Interval.open(S(3)/2, 3)) True >>> is_decreasing(1/(x**2 - 3*x), Interval.open(1.5, 3)) True >>> is_decreasing(1/(x**2 - 3*x), Interval.Lopen(3, oo)) True >>> is_decreasing(1/(x**2 - 3*x), Interval.Ropen(-oo, S(3)/2)) False >>> is_decreasing(1/(x**2 - 3*x), Interval.Ropen(-oo, 1.5)) False >>> is_decreasing(-x**2, Interval(-oo, 0)) False >>> is_decreasing(-x**2 + y, Interval(-oo, 0), x) False """ return monotonicity_helper(expression, lambda x: x <= 0, interval, symbol) def is_strictly_decreasing(expression, interval=S.Reals, symbol=None): """ Return whether the function is strictly decreasing in the given interval. Parameters ========== expression : Expr The target function which is being checked. interval : Set, optional The range of values in which we are testing (defaults to set of all real numbers). symbol : Symbol, optional The symbol present in expression which gets varied over the given range. Returns ======= Boolean True if ``expression`` is strictly decreasing in the given ``interval``, False otherwise. Examples ======== >>> from sympy import is_strictly_decreasing >>> from sympy.abc import x, y >>> from sympy import S, Interval, oo >>> is_strictly_decreasing(1/(x**2 - 3*x), Interval.Lopen(3, oo)) True >>> is_strictly_decreasing(1/(x**2 - 3*x), Interval.Ropen(-oo, S(3)/2)) False >>> is_strictly_decreasing(1/(x**2 - 3*x), Interval.Ropen(-oo, 1.5)) False >>> is_strictly_decreasing(-x**2, Interval(-oo, 0)) False >>> is_strictly_decreasing(-x**2 + y, Interval(-oo, 0), x) False """ return monotonicity_helper(expression, lambda x: x < 0, interval, symbol) def is_monotonic(expression, interval=S.Reals, symbol=None): """ Return whether the function is monotonic in the given interval. Parameters ========== expression : Expr The target function which is being checked. interval : Set, optional The range of values in which we are testing (defaults to set of all real numbers). symbol : Symbol, optional The symbol present in expression which gets varied over the given range. Returns ======= Boolean True if ``expression`` is monotonic in the given ``interval``, False otherwise. Raises ====== NotImplementedError Monotonicity check has not been implemented for the queried function. Examples ======== >>> from sympy import is_monotonic >>> from sympy.abc import x, y >>> from sympy import S, Interval, oo >>> is_monotonic(1/(x**2 - 3*x), Interval.open(S(3)/2, 3)) True >>> is_monotonic(1/(x**2 - 3*x), Interval.open(1.5, 3)) True >>> is_monotonic(1/(x**2 - 3*x), Interval.Lopen(3, oo)) True >>> is_monotonic(x**3 - 3*x**2 + 4*x, S.Reals) True >>> is_monotonic(-x**2, S.Reals) False >>> is_monotonic(x**2 + y + 1, Interval(1, 2), x) True """ from sympy.solvers.solveset import solveset expression = sympify(expression) free = expression.free_symbols if symbol is None and len(free) > 1: raise NotImplementedError( 'is_monotonic has not yet been implemented' ' for all multivariate expressions.' ) variable = symbol or (free.pop() if free else Symbol('x')) turning_points = solveset(expression.diff(variable), variable, interval) return interval.intersection(turning_points) is S.EmptySet