Generateurv2/backend/env/lib/python3.10/site-packages/sympy/calculus/singularities.py
2022-06-24 17:14:37 +02:00

387 lines
11 KiB
Python

"""
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 import S, Symbol
from sympy.core.sympify import sympify
from sympy.solvers.solveset import solveset
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.calculus.singularities import singularities
>>> from sympy import 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.functions.elementary.exponential import log
from sympy.functions.elementary.trigonometric import sec, csc, cot, tan, cos
from sympy.core.power import Pow
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.
"""
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(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(-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(-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(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
"""
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