def EnumeratedSet(X):
"""
Return the enumerated set associated to $X$.
The input object $X$ must be finite.
EXAMPLES::
sage: EnumeratedSet([1,1,2,3])
doctest:1: DeprecationWarning: EnumeratedSet is deprecated; use Set instead.
{1, 2, 3}
sage: EnumeratedSet(ZZ)
Traceback (most recent call last):
...
ValueError: X (=Integer Ring) must be finite
"""
from sage.misc.misc import deprecation
deprecation("EnumeratedSet is deprecated; use Set instead.")
try:
if not X.is_finite():
raise ValueError, "X (=%s) must be finite" % X
except AttributeError:
pass
return Set_object_enumerated(X)
def __call__(self, x, prec=None, coerce=True, hold=False ):
"""
Note that the ``prec`` argument is deprecated. The precision for
the result is deduced from the precision of the input. Convert
the input to a higher precision explicitly if a result with higher
precision is desired.
EXAMPLES::
sage: t = Ei(RealField(100)(2.5)); t
7.0737658945786007119235519625
sage: t.prec()
100
sage: Ei(1.1, prec=300)
doctest:...: DeprecationWarning: The prec keyword argument is deprecated. Explicitly set the precision of the input, for example Ei(RealField(300)(1)), or use the prec argument to .n() for exact inputs, e.g., Ei(1).n(300), instead.
2.16737827956340306615064476647912607220394065907142504328679588538509331805598360907980986
"""
if prec is not None:
from sage.misc.misc import deprecation
deprecation("The prec keyword argument is deprecated. Explicitly set the precision of the input, for example Ei(RealField(300)(1)), or use the prec argument to .n() for exact inputs, e.g., Ei(1).n(300), instead.")
import mpmath
return mpmath_utils.call(mpmath.ei, x, prec=prec)
return BuiltinFunction.__call__(self, x, coerce=coerce, hold=hold)
def coef(self, P):
r"""
Synonym for :meth:`coefficient`
.. WARNING::
This method is deprecated. It will be removed in a future
release of Sage. Please use the ``coefficient(P)`` method
instead.
EXAMPLES::
sage: x,y = AffineSpace(2, GF(5), names='xy').gens()
sage: C = Curve(y^2 - x^9 - x)
sage: pts = C.rational_points(); pts
[(0, 0), (2, 2), (2, 3), (3, 1), (3, 4)]
sage: D = C.divisor(pts[0])
sage: D.coefficient(pts[0])
1
"""
from sage.misc.misc import deprecation
deprecation(
"This method is deprecated. It will be removed in a future release of Sage. Please use the coefficient() method instead."
)
return self.coefficient(P)
def __call__(self, x, prec=None, coerce=True, hold=False):
"""
Note that the ``prec`` argument is deprecated. The precision for
the result is deduced from the precision of the input. Convert
the input to a higher precision explicitly if a result with higher
precision is desired.
EXAMPLES::
sage: t = Ei(RealField(100)(2.5)); t
7.0737658945786007119235519625
sage: t.prec()
100
sage: Ei(1.1, prec=300)
doctest:...: DeprecationWarning: The prec keyword argument is deprecated. Explicitly set the precision of the input, for example Ei(RealField(300)(1)), or use the prec argument to .n() for exact inputs, e.g., Ei(1).n(300), instead.
2.16737827956340306615064476647912607220394065907142504328679588538509331805598360907980986
"""
if prec is not None:
from sage.misc.misc import deprecation
deprecation(
"The prec keyword argument is deprecated. Explicitly set the precision of the input, for example Ei(RealField(300)(1)), or use the prec argument to .n() for exact inputs, e.g., Ei(1).n(300), instead."
)
import mpmath
return mpmath_utils.call(mpmath.ei, x, prec=prec)
return BuiltinFunction.__call__(self, x, coerce=coerce, hold=hold)
def __call__(self, x, coerce=True, hold=False, prec=None,
dont_call_method_on_arg=False):
"""
Note that the ``prec`` argument is deprecated. The precision for
the result is deduced from the precision of the input. Convert
the input to a higher precision explicitly if a result with higher
precision is desired.::
sage: t = exp(RealField(100)(2)); t
7.3890560989306502272304274606
sage: t.prec()
100
TESTS::
sage: exp(2,prec=100)
doctest:...: DeprecationWarning: The prec keyword argument is deprecated. Explicitly set the precision of the input, for example exp(RealField(300)(1)), or use the prec argument to .n() for exact inputs, e.g., exp(1).n(300), instead.
7.3890560989306502272304274606
"""
if prec is not None:
from sage.misc.misc import deprecation
deprecation("The prec keyword argument is deprecated. Explicitly set the precision of the input, for example exp(RealField(300)(1)), or use the prec argument to .n() for exact inputs, e.g., exp(1).n(300), instead.")
x = GinacFunction.__call__(self, x, coerce=coerce, hold=hold,
dont_call_method_on_arg=dont_call_method_on_arg)
return x.n(prec)
return GinacFunction.__call__(self, x, coerce=coerce, hold=hold,
dont_call_method_on_arg=dont_call_method_on_arg)
def sqrt(x):
"""
Returns a square root of x.
This function (``numerical_sqrt``) is deprecated. Use ``sqrt(x,
prec=n)`` instead.
EXAMPLES::
sage: numerical_sqrt(10.1)
doctest:1: DeprecationWarning: numerical_sqrt is deprecated, use sqrt(x, prec=n) instead
3.17804971641414
sage: numerical_sqrt(9)
3
"""
from sage.misc.misc import deprecation
deprecation("numerical_sqrt is deprecated, use sqrt(x, prec=n) instead")
try:
return x.sqrt()
except (AttributeError, ValueError):
try:
return RDF(x).sqrt()
except TypeError:
return CDF(x).sqrt()
def _normalize_integral_input(f, v=None, a=None, b=None):
r"""
Validate and return variable and endpoints for an integral.
INPUT:
- ``f`` -- an expression to integrate;
- ``v`` -- a variable of integration or a triple;
- ``a`` -- (optional) the left endpoint of integration;
- ``b`` -- (optional) the right endpoint of integration.
It is also possible to pass last three parameters in ``v`` as a triple.
OUPUT:
- a tuple of ``f``, ``v``, ``a``, and ``b``.
EXAMPLES::
sage: from sage.symbolic.integration.integral import \
... _normalize_integral_input
sage: _normalize_integral_input(x^2, x, 0, 3)
(x^2, x, 0, 3)
sage: _normalize_integral_input(x^2, [x, 0, 3], None, None)
(x^2, x, 0, 3)
sage: _normalize_integral_input(x^2, [0, 3], None, None)
doctest:...: DeprecationWarning:
Variable of integration should be specified explicitly.
(x^2, x, 0, 3)
sage: _normalize_integral_input(x^2, [x], None, None)
(x^2, x, None, None)
"""
if isinstance(v, (list, tuple)) and a is None and b is None:
if len(v) == 1: # bare variable in a tuple
v = v[0]
elif len(v) == 2: # endpoints only
a, b = v
v = None
elif len(v) == 3: # variable and endpoints
v, a, b = v
else:
raise ValueError("invalid input %s - please use variable, "
"with or without two endpoints" % repr(v))
elif b is None and a is not None:
# two arguments, must be endpoints
v, a, b = None, v, a
if v is None:
from sage.misc.misc import deprecation
deprecation("Variable of integration should be specified explicitly.")
v = f.default_variable()
if isinstance(f, Function): # a bare function like sin
f = f(v)
if (a is None) ^ (b is None):
raise TypeError('only one endpoint was given!')
return f, v, a, b
def _normalize_integral_input(f, v=None, a=None, b=None):
r"""
Validate and return variable and endpoints for an integral.
INPUT:
- ``f`` -- an expression to integrate;
- ``v`` -- a variable of integration or a triple;
- ``a`` -- (optional) the left endpoint of integration;
- ``b`` -- (optional) the right endpoint of integration.
It is also possible to pass last three parameters in ``v`` as a triple.
OUPUT:
- a tuple of ``f``, ``v``, ``a``, and ``b``.
EXAMPLES::
sage: from sage.symbolic.integration.integral import \
... _normalize_integral_input
sage: _normalize_integral_input(x^2, x, 0, 3)
(x^2, x, 0, 3)
sage: _normalize_integral_input(x^2, [x, 0, 3], None, None)
(x^2, x, 0, 3)
sage: _normalize_integral_input(x^2, [0, 3], None, None)
doctest:...: DeprecationWarning:
Variable of integration should be specified explicitly.
(x^2, x, 0, 3)
sage: _normalize_integral_input(x^2, [x], None, None)
(x^2, x, None, None)
"""
if isinstance(v, (list, tuple)) and a is None and b is None:
if len(v) == 1: # bare variable in a tuple
v = v[0]
elif len(v) == 2: # endpoints only
a, b = v
v = None
elif len(v) == 3: # variable and endpoints
v, a, b = v
else:
raise ValueError("invalid input %s - please use variable, "
"with or without two endpoints" % repr(v))
elif b is None and a is not None:
# two arguments, must be endpoints
v, a, b = None, v, a
if v is None:
from sage.misc.misc import deprecation
deprecation("Variable of integration should be specified explicitly.")
v = f.default_variable()
if isinstance(f, Function): # a bare function like sin
f = f(v)
if (a is None) ^ (b is None):
raise TypeError('only one endpoint was given!')
return f, v, a, b
def wrapper(*args, **kwds):
for old_name, new_name in self.renames.items():
if old_name in kwds and new_name not in kwds:
if self.deprecated is not None:
deprecation("use the option %r instead of %r"%(new_name,old_name),
version=self.deprecated)
kwds[new_name] = kwds[old_name]
del kwds[old_name]
return func(*args, **kwds)
def jsmath(x, mode='display'):
r'''
Attempt to nicely render an arbitrary SAGE object wih jsmath typesetting.
Tries to call ._latex_() on x. If that fails, it will render a string
representation of x.
.. warning::
2009-04: This function is deprecated; use ``html`` instead:
replace ``jsmath('MATH', mode='display')`` with ``html('$$MATH$$')``,
and replace ``jsmath('MATH', mode='inline')`` with ``html('$MATH$')``.
INPUT:
x -- the object to render
mode -- 'display' for displaymath or 'inline' for inline math
OUTPUT:
A string of html that contains the LaTeX represntation of x. In the
notebook this gets embedded into the cell.
EXAMPLES::
sage: from sage.misc.latex import jsmath
sage: f = maxima('1/(x^2+1)')
sage: g = f.integrate()
sage: jsmath(f)
... DeprecationWarning: The jsmath function is deprecated. Use html('$math$') for inline mode or html('$$math$$') for display mode.
# -*- coding: utf-8 -*-
<html><font color='black'><div class="math">{{1}\over{x^2+1}}</div></font></html>
sage: jsmath(g, 'inline')
<html><font color='black'><span class="math">\tan^{-1} x</span></font></html>
sage: jsmath('\int' + latex(f) + '\ dx=' + latex(g))
<html><font color='black'><div class="math">\int{{1}\over{x^2+1}}\ dx=\tan^{-1} x</div></font></html>
AUTHORS:
- William Stein (2006-10): general layout (2006-10)
- Bobby Moretti (2006-10): improvements, comments, documentation
'''
from sage.misc.misc import deprecation
from sage.misc.html import html
deprecation("The jsmath function is deprecated. Use html('$math$') for inline mode or html('$$math$$') for display mode.")
if mode == 'display':
delimiter = '$$'
elif mode == 'inline':
delimiter = '$'
else:
raise ValueError, "mode must be either 'display' or 'inline'"
try:
# try to get a latex representation of the object
x = x._latex_()
except AttributeError:
# otherwise just get the string representation
x = str(x)
return html(delimiter + x + delimiter)
def __call__(self, x, prec=None, coerce=True, hold=False):
"""
Note that the ``prec`` argument is deprecated. The precision for
the result is deduced from the precision of the input. Convert
the input to a higher precision explicitly if a result with higher
precision is desired.::
sage: t = gamma(RealField(100)(2.5)); t
1.3293403881791370204736256125
sage: t.prec()
100
sage: gamma(6, prec=53)
doctest:...: DeprecationWarning: The prec keyword argument is deprecated. Explicitly set the precision of the input, for example gamma(RealField(300)(1)), or use the prec argument to .n() for exact inputs, e.g., gamma(1).n(300), instead.
120.000000000000
TESTS::
sage: gamma(pi,prec=100)
2.2880377953400324179595889091
sage: gamma(3/4,prec=100)
1.2254167024651776451290983034
"""
if prec is not None:
from sage.misc.misc import deprecation
deprecation(
"The prec keyword argument is deprecated. Explicitly set the precision of the input, for example gamma(RealField(300)(1)), or use the prec argument to .n() for exact inputs, e.g., gamma(1).n(300), instead."
)
import mpmath
return mpmath_utils.call(mpmath.gamma, x, prec=prec)
# this is a kludge to keep
# sage: Q.<i> = NumberField(x^2+1)
# sage: gamma(i)
# working, since number field elements cannot be coerced into SR
# without specifying an explicit embedding into CC any more
try:
res = GinacFunction.__call__(self, x, coerce=coerce, hold=hold)
except TypeError, err:
# the __call__() method returns a TypeError for fast float arguments
# as well, we only proceed if the error message says that
# the arguments cannot be coerced to SR
if not str(err).startswith("cannot coerce"):
raise
from sage.misc.misc import deprecation
deprecation(
"Calling symbolic functions with arguments that cannot be coerced into symbolic expressions is deprecated."
)
parent = RR if prec is None else RealField(prec)
try:
x = parent(x)
except (ValueError, TypeError):
x = parent.complex_field()(x)
res = GinacFunction.__call__(self, x, coerce=coerce, hold=hold)
def wrapper(*args, **kwds):
for old_name, new_name in self.renames.items():
if old_name in kwds and new_name not in kwds:
if self.deprecated is not None:
deprecation("use the option %r instead of %r" %
(new_name, old_name),
version=self.deprecated)
kwds[new_name] = kwds[old_name]
del kwds[old_name]
return func(*args, **kwds)
def MPolynomialRing(*args, **kwds):
r"""
This function is deprecated and will be removed in a future version of
Sage. Please use PolynomialRing instead.
If you have questions regarding this function and its replacement,
please send your comments to [email protected].
"""
from sage.misc.misc import deprecation
deprecation("MPolynomialRing is deprecated, use PolynomialRing instead!")
return PolynomialRing(*args, **kwds)
def __call__(self, x, prec=None, coerce=True, hold=False):
"""
Note that the ``prec`` argument is deprecated. The precision for
the result is deduced from the precision of the input. Convert
the input to a higher precision explicitly if a result with higher
precision is desired.::
sage: t = gamma(RealField(100)(2.5)); t
1.3293403881791370204736256125
sage: t.prec()
100
sage: gamma(6, prec=53)
doctest:...: DeprecationWarning: The prec keyword argument is deprecated. Explicitly set the precision of the input, for example gamma(RealField(300)(1)), or use the prec argument to .n() for exact inputs, e.g., gamma(1).n(300), instead.
120.000000000000
TESTS::
sage: gamma(pi,prec=100)
2.2880377953400324179595889091
sage: gamma(3/4,prec=100)
1.2254167024651776451290983034
"""
if prec is not None:
from sage.misc.misc import deprecation
deprecation("The prec keyword argument is deprecated. Explicitly set the precision of the input, for example gamma(RealField(300)(1)), or use the prec argument to .n() for exact inputs, e.g., gamma(1).n(300), instead.")
import mpmath
return mpmath_utils.call(mpmath.gamma, x, prec=prec)
# this is a kludge to keep
# sage: Q.<i> = NumberField(x^2+1)
# sage: gamma(i)
# working, since number field elements cannot be coerced into SR
# without specifying an explicit embedding into CC any more
try:
res = GinacFunction.__call__(self, x, coerce=coerce, hold=hold)
except TypeError, err:
# the __call__() method returns a TypeError for fast float arguments
# as well, we only proceed if the error message says that
# the arguments cannot be coerced to SR
if not str(err).startswith("cannot coerce"):
raise
from sage.misc.misc import deprecation
deprecation("Calling symbolic functions with arguments that cannot be coerced into symbolic expressions is deprecated.")
parent = RR if prec is None else RealField(prec)
try:
x = parent(x)
except (ValueError, TypeError):
x = parent.complex_field()(x)
res = GinacFunction.__call__(self, x, coerce=coerce, hold=hold)
def DiamondPoset(*args, **kwds):
r"""
This function is deprecated and will be removed in a future
version of Sage. Please use ``Posets.DiamondPoset`` instead.
TESTS::
sage: DiamondPoset(3)
doctest:1: DeprecationWarning: DiamondPoset is deprecated, use Posets.DiamondPoset instead!
Finite lattice containing 3 elements
"""
deprecation("%s is deprecated, use Posets.%s instead!" % \
("DiamondPoset","DiamondPoset"))
return Posets.DiamondPoset(*args, **kwds)
def BooleanLattice(*args, **kwds):
r"""
This function is deprecated and will be removed in a future
version of Sage. Please use ``Posets.BooleanLattice`` instead.
TESTS::
sage: BooleanLattice(3)
doctest:1: DeprecationWarning: BooleanLattice is deprecated, use Posets.BooleanLattice instead!
Finite lattice containing 8 elements
"""
deprecation("%s is deprecated, use Posets.%s instead!" % \
("BooleanLattice", "BooleanLattice"))
return Posets.BooleanLattice(*args, **kwds)
def PosetOfIntegerCompositions(*args, **kwds):
r"""
This function is deprecated and will be removed in a future
version of Sage. Please use ``Posets.IntegerCompositions`` instead.
TESTS::
sage: PosetOfIntegerCompositions(3)
doctest:1: DeprecationWarning: PosetOfIntegerCompositions is deprecated, use Posets.IntegerCompositions instead!
Finite poset containing 4 elements
"""
deprecation("%s is deprecated, use Posets.%s instead!" % \
("PosetOfIntegerCompositions","IntegerCompositions"))
return Posets.IntegerCompositions(*args, **kwds)
def string_rep(self):
r"""
Returns the string representation of the alphabet.
TESTS::
sage: from sage.combinat.words.alphabet import OrderedAlphabet_Finite
sage: OrderedAlphabet_Finite([1, 3, 2]).string_rep()
doctest:1: DeprecationWarning: string_rep is deprecated, use __repr__ instead!
'Ordered Alphabet [1, 3, 2]'
"""
from sage.misc.misc import deprecation
deprecation("string_rep is deprecated, use __repr__ instead!")
return self.__repr__()
def RandomPoset(*args, **kwds):
r"""
This function is deprecated and will be removed in a future
version of Sage. Please use ``Posets.RandomPoset`` instead.
TESTS::
sage: RandomPoset(17,.15)
doctest:1: DeprecationWarning: RandomPoset is deprecated, use Posets.RandomPoset instead!
Finite poset containing 17 elements
"""
deprecation("%s is deprecated, use Posets.%s instead!" % \
("RandomPoset","RandomPoset"))
return Posets.RandomPoset(*args, **kwds)
def SymmetricGroupWeakOrderPoset(*args, **kwds):
r"""
This function is deprecated and will be removed in a future
version of Sage. Please use ``Posets.SymmetricGroupWeakOrderPoset`` instead.
TESTS::
sage: SymmetricGroupWeakOrderPoset(3)
doctest:1: DeprecationWarning: SymmetricGroupWeakOrderPoset is deprecated, use Posets.SymmetricGroupWeakOrderPoset instead!
Finite poset containing 6 elements
"""
deprecation("%s is deprecated, use Posets.%s instead!" % \
("SymmetricGroupWeakOrderPoset","SymmetricGroupWeakOrderPoset"))
return Posets.SymmetricGroupWeakOrderPoset(*args, **kwds)
def string_rep(self):
r"""
Returns the string representation of the alphabet.
TESTS::
sage: from sage.combinat.words.alphabet import OrderedAlphabet_Finite
sage: OrderedAlphabet_Finite([1, 3, 2]).string_rep()
doctest:1: DeprecationWarning: string_rep is deprecated, use __repr__ instead!
'Ordered Alphabet [1, 3, 2]'
"""
from sage.misc.misc import deprecation
deprecation("string_rep is deprecated, use __repr__ instead!")
return self.__repr__()
def range(self):
"""
Returns the codomain of this morphism. This method is
deprecated. Please use :meth:`codomain` instead.
EXAMPLES::
sage: G = PSL(2,7)
sage: D, iota1, iota2, pr1, pr2 = G.direct_product(G)
sage: pr1.range()
doctest... DeprecationWarning: (Since Sage Version 5.0) range is deprecated. Please use codomain instead.
Permutation Group with generators [(3,7,5)(4,8,6), (1,2,6)(3,4,8)]
"""
deprecation('range is deprecated. Please use codomain instead.', 'Sage Version 5.0')
return self.codomain()
def __init__(self):
"""
Issue deprecation warnings for the old networkx XDiGraph formats
EXAMPLE::
sage: from sage.graphs.base.graph_backends import NetworkXDiGraphDeprecated
sage: NetworkXDiGraphDeprecated()
doctest:...
<class 'sage.graphs.base.graph_backends.NetworkXDiGraphDeprecated'>
"""
from sage.misc.misc import deprecation
deprecation("Your digraph object is saved in an old format since networkx "+
"was updated to 1.0.1. You can re-save your digraph by typing "+
"digraph.save(filename) to make this warning go away.")
def range(self):
"""
Returns the codomain of this morphism. This method is
deprecated. Please use :meth:`codomain` instead.
EXAMPLES::
sage: G = PSL(2,7)
sage: D, iota1, iota2, pr1, pr2 = G.direct_product(G)
sage: pr1.range()
doctest... DeprecationWarning: (Since Sage Version 5.0) range is deprecated. Please use codomain instead.
Permutation Group with generators [(3,7,5)(4,8,6), (1,2,6)(3,4,8)]
"""
deprecation('range is deprecated. Please use codomain instead.',
'Sage Version 5.0')
return self.codomain()
def adapt_to_callable(f, nargs=None):
"""
Tries to make every function in f into a (fast) callable
function, returning a new list of functions and the expected
arguments.
INPUT:
- ``f`` -- a list of functions; these can be symbolic expressions,
polynomials, etc
- ``nargs`` -- number of input args to have in the output functions
OUTPUT: functions, expected arguments
"""
from sage.misc.misc import deprecation
deprecation(
"adapt_to_callable is a deprecated function. Please use functions from sage.misc.plot instead."
)
try:
from sage.symbolic.callable import is_CallableSymbolicExpression
if sum([is_CallableSymbolicExpression(z) for z in f]):
# Sum to get common universe; this works since f is
# callable, and summing gets the arguments in the right
# order.
vars = sum(f).args()
else:
# Otherwise any free variable names in any order
try:
vars = tuple(sorted(set(sum([z.variables() for z in f], ()))))
if len(vars) > 1:
from sage.misc.misc import deprecation
deprecation(
"Substitution using function-call syntax and unnamed arguments is deprecated and will be removed from a future release of Sage; you can use named arguments instead, like EXPR(x=..., y=...)"
)
except AttributeError:
vars = ()
f = [fast_float_constant(x) for x in f]
except TypeError:
vars = ()
f = [fast_float_constant(x) for x in f]
if nargs is not None and len(vars) != nargs:
vars = (vars + ('_', ) * nargs)[:nargs]
return fast_float(f, *vars), vars
def is_distributive_lattice_fastest(self):
r"""
This function is deprecated and will be removed in a future
version of Sage. Please use ``self.is_distributive_lattice()``
instead.
TESTS::
sage: from sage.combinat.posets.hasse_diagram import HasseDiagram
sage: H = HasseDiagram({0:[1,3,2],1:[4],2:[4,5,6],3:[6],4:[7],5:[7],6:[7],7:[]})
sage: H.is_distributive_lattice_fastest()
doctest:1: DeprecationWarning: is_distributive_lattice_fastest is deprecated, use is_distributive_lattice instead!
False
"""
from sage.misc.misc import deprecation
deprecation("is_distributive_lattice_fastest is deprecated, use is_distributive_lattice instead!")
return self.is_distributive_lattice()
def is_distributive_lattice_fastest(self):
r"""
This function is deprecated and will be removed in a future
version of Sage. Please use ``self.is_distributive_lattice()``
instead.
TESTS::
sage: from sage.combinat.posets.hasse_diagram import HasseDiagram
sage: H = HasseDiagram({0:[1,3,2],1:[4],2:[4,5,6],3:[6],4:[7],5:[7],6:[7],7:[]})
sage: H.is_distributive_lattice_fastest()
doctest:1: DeprecationWarning: is_distributive_lattice_fastest is deprecated, use is_distributive_lattice instead!
False
"""
from sage.misc.misc import deprecation
deprecation("is_distributive_lattice_fastest is deprecated, use is_distributive_lattice instead!")
return self.is_distributive_lattice()
def lngamma(t):
r"""
This method is deprecated, please use
:meth:`~sage.functions.other.log_gamma` instead.
See the :meth:`~sage.functions.other.log_gamma` function for '
documentation and examples.
EXAMPLES::
sage: lngamma(RR(6))
doctest:...: DeprecationWarning: The method lngamma() is deprecated. Use log_gamma() instead.
4.78749174278205
"""
from sage.misc.misc import deprecation
deprecation("The method lngamma() is deprecated. Use log_gamma() instead.")
return log_gamma(t)
def __call__(self, n, z, prec=None, coerce=True, hold=False ):
"""
Note that the ``prec`` argument is deprecated. The precision for
the result is deduced from the precision of the input. Convert
the input to a higher precision explicitly if a result with higher
precision is desired.
EXAMPLES::
"""
if prec is not None:
from sage.misc.misc import deprecation
deprecation("The prec keyword argument is deprecated. Explicitly set the precision of the input, for example En(RealField(300)(1), RealField(300)(1)), or use the prec argument to .n() for exact inputs, e.g., En(1,1).n(300), instead.")
import mpmath
return mpmath_utils.call(mpmath.expint, n, z, prec=prec)
return BuiltinFunction.__call__(self, n, z, coerce=coerce, hold=hold)
def adapt_to_callable(f, nargs=None):
"""
Tries to make every function in f into a (fast) callable
function, returning a new list of functions and the expected
arguments.
INPUT:
- ``f`` -- a list of functions; these can be symbolic expressions,
polynomials, etc
- ``nargs`` -- number of input args to have in the output functions
OUTPUT: functions, expected arguments
"""
from sage.misc.misc import deprecation
deprecation("adapt_to_callable is a deprecated function. Please use functions from sage.misc.plot instead.")
try:
from sage.symbolic.callable import is_CallableSymbolicExpression
if sum([is_CallableSymbolicExpression(z) for z in f]):
# Sum to get common universe; this works since f is
# callable, and summing gets the arguments in the right
# order.
vars = sum(f).args()
else:
# Otherwise any free variable names in any order
try:
vars = tuple(sorted(set(sum( [z.variables() for z in f], ()) )))
if len(vars) > 1:
from sage.misc.misc import deprecation
deprecation("Substitution using function-call syntax and unnamed arguments is deprecated and will be removed from a future release of Sage; you can use named arguments instead, like EXPR(x=..., y=...)")
except AttributeError:
vars = ()
f = [fast_float_constant(x) for x in f]
except TypeError:
vars = ()
f = [fast_float_constant(x) for x in f]
if nargs is not None and len(vars) != nargs:
vars = (vars + ('_',)*nargs)[:nargs]
return fast_float(f, *vars), vars
def dynkin_diagram(t):
"""
Returns the Dynkin diagram of type t.
Note that this function is deprecated, and that you should use
DynkinDiagram instead as this will be disappearing in the near
future.
EXAMPLES::
sage: dynkin_diagram(["A", 3])
doctest:1: DeprecationWarning: dynkin_diagram is deprecated, use DynkinDiagram instead!
O---O---O
1 2 3
A3
"""
from sage.misc.misc import deprecation
deprecation("dynkin_diagram is deprecated, use DynkinDiagram instead!")
return DynkinDiagram(t)
def dynkin_diagram(t):
"""
Returns the Dynkin diagram of type t.
Note that this function is deprecated, and that you should use
DynkinDiagram instead as this will be disappearing in the near
future.
EXAMPLES::
sage: dynkin_diagram(["A", 3])
doctest:1: DeprecationWarning: dynkin_diagram is deprecated, use DynkinDiagram instead!
O---O---O
1 2 3
A3
"""
from sage.misc.misc import deprecation
deprecation("dynkin_diagram is deprecated, use DynkinDiagram instead!")
return DynkinDiagram(t)
def __call__(self,
x,
coerce=True,
hold=False,
prec=None,
dont_call_method_on_arg=False):
"""
Note that the ``prec`` argument is deprecated. The precision for
the result is deduced from the precision of the input. Convert
the input to a higher precision explicitly if a result with higher
precision is desired.::
sage: t = exp(RealField(100)(2)); t
7.3890560989306502272304274606
sage: t.prec()
100
TESTS::
sage: exp(2,prec=100)
doctest:...: DeprecationWarning: The prec keyword argument is deprecated. Explicitly set the precision of the input, for example exp(RealField(300)(1)), or use the prec argument to .n() for exact inputs, e.g., exp(1).n(300), instead.
7.3890560989306502272304274606
"""
if prec is not None:
from sage.misc.misc import deprecation
deprecation(
"The prec keyword argument is deprecated. Explicitly set the precision of the input, for example exp(RealField(300)(1)), or use the prec argument to .n() for exact inputs, e.g., exp(1).n(300), instead."
)
x = GinacFunction.__call__(
self,
x,
coerce=coerce,
hold=hold,
dont_call_method_on_arg=dont_call_method_on_arg)
return x.n(prec)
return GinacFunction.__call__(
self,
x,
coerce=coerce,
hold=hold,
dont_call_method_on_arg=dont_call_method_on_arg)
def exp_int(t):
r"""
The exponential integral `\int_t^\infty e^{-x}/x dx` (t
belongs to RR). This function is deprecated - please use
``Ei`` or ``exponential_integral_1`` as needed instead.
EXAMPLES::
sage: exp_int(6)
doctest:...: DeprecationWarning: The method exp_int() is deprecated. Use -Ei(-x) or exponential_integral_1(x) as needed instead.
0.000360082452162659
"""
from sage.misc.misc import deprecation
deprecation("The method exp_int() is deprecated. Use -Ei(-x) or exponential_integral_1(x) as needed instead.")
try:
return t.eint1()
except AttributeError:
from sage.libs.pari.all import pari
try:
return pari(t).eint1()
except:
raise NotImplementedError
def __init__(self, G, H, gens=None, images=None):
"""
Some python code for wrapping GAP's GroupHomomorphismByImages
function but only for permutation groups. Can be expensive if G is
large. Returns "fail" if gens does not generate self or if the map
does not extend to a group homomorphism, self - other.
EXAMPLES::
sage: G = CyclicPermutationGroup(4)
sage: H = DihedralGroup(4)
sage: phi = PermutationGroupMorphism_im_gens(G, H, map(H, G.gens())); phi
Permutation group morphism:
From: Cyclic group of order 4 as a permutation group
To: Dihedral group of order 8 as a permutation group
Defn: [(1,2,3,4)] -> [(1,2,3,4)]
sage: g = G([(1,3),(2,4)]); g
(1,3)(2,4)
sage: phi(g)
(1,3)(2,4)
sage: images = ((4,3,2,1),)
sage: phi = PermutationGroupMorphism_im_gens(G, G, images)
sage: g = G([(1,2,3,4)]); g
(1,2,3,4)
sage: phi(g)
(1,4,3,2)
AUTHORS:
- David Joyner (2006-02)
"""
if not all([isinstance(X, PermutationGroup_generic) for X in [G, H]]):
raise TypeError, "Sorry, the groups must be permutation groups."
if images is not None:
deprecation('only the images need to be specified')
else:
images = gens
PermutationGroupMorphism.__init__(self, G, H)
self._images = [H(img) for img in images]
def __init__(self, G, H, gens=None, images=None):
"""
Some python code for wrapping GAP's GroupHomomorphismByImages
function but only for permutation groups. Can be expensive if G is
large. Returns "fail" if gens does not generate self or if the map
does not extend to a group homomorphism, self - other.
EXAMPLES::
sage: G = CyclicPermutationGroup(4)
sage: H = DihedralGroup(4)
sage: phi = PermutationGroupMorphism_im_gens(G, H, map(H, G.gens())); phi
Permutation group morphism:
From: Cyclic group of order 4 as a permutation group
To: Dihedral group of order 8 as a permutation group
Defn: [(1,2,3,4)] -> [(1,2,3,4)]
sage: g = G([(1,3),(2,4)]); g
(1,3)(2,4)
sage: phi(g)
(1,3)(2,4)
sage: images = ((4,3,2,1),)
sage: phi = PermutationGroupMorphism_im_gens(G, G, images)
sage: g = G([(1,2,3,4)]); g
(1,2,3,4)
sage: phi(g)
(1,4,3,2)
AUTHORS:
- David Joyner (2006-02)
"""
if not all([isinstance(X, PermutationGroup_generic) for X in [G, H]]):
raise TypeError, "Sorry, the groups must be permutation groups."
if images is not None:
deprecation('only the images need to be specified')
else:
images = gens
PermutationGroupMorphism.__init__(self, G, H)
self._images = [H(img) for img in images]
def coef(self,P):
r"""
Synonym for :meth:`coefficient`
.. WARNING::
This method is deprecated. It will be removed in a future
release of Sage. Please use the ``coefficient(P)`` method
instead.
EXAMPLES::
sage: x,y = AffineSpace(2, GF(5), names='xy').gens()
sage: C = Curve(y^2 - x^9 - x)
sage: pts = C.rational_points(); pts
[(0, 0), (2, 2), (2, 3), (3, 1), (3, 4)]
sage: D = C.divisor(pts[0])
sage: D.coefficient(pts[0])
1
"""
from sage.misc.misc import deprecation
deprecation("This method is deprecated. It will be removed in a future release of Sage. Please use the coefficient() method instead.")
return self.coefficient(P)
def EnumeratedSet(X):
"""
Return the enumerated set associated to $X$.
The input object $X$ must be finite.
EXAMPLES::
sage: EnumeratedSet([1,1,2,3])
doctest:1: DeprecationWarning: EnumeratedSet is deprecated; use Set instead.
{1, 2, 3}
sage: EnumeratedSet(ZZ)
Traceback (most recent call last):
...
ValueError: X (=Integer Ring) must be finite
"""
from sage.misc.misc import deprecation
deprecation('EnumeratedSet is deprecated; use Set instead.')
try:
if not X.is_finite():
raise ValueError, "X (=%s) must be finite" % X
except AttributeError:
pass
return Set_object_enumerated(X)
def sqrt(x):
"""
Returns a square root of x.
This function (``numerical_sqrt``) is deprecated. Use ``sqrt(x,
prec=n)`` instead.
EXAMPLES::
sage: numerical_sqrt(10.1)
doctest:1: DeprecationWarning: numerical_sqrt is deprecated, use sqrt(x, prec=n) instead
3.17804971641414
sage: numerical_sqrt(9)
3
"""
from sage.misc.misc import deprecation
deprecation("numerical_sqrt is deprecated, use sqrt(x, prec=n) instead")
try:
return x.sqrt()
except (AttributeError, ValueError):
try:
return RDF(x).sqrt()
except TypeError:
return CDF(x).sqrt()
def r_quotient(self, length):
""" *** deprecate *** """
from sage.misc.misc import deprecation
deprecation('r_quotient is deprecated. Use quotient instead.')
return self.quotient(self, length)
from sage.misc.misc import deprecation
deprecation('The module sage.geometry.polyhedra has been removed, use sage.geometry.polyhedron instead.',
'Sage Version 4.8')
from polyhedron.all import *
def r_quotient(self, length):
""" *** deprecate *** """
from sage.misc.misc import deprecation
deprecation('r_quotient is deprecated. Use quotient instead.')
return self.quotient(self,length)
def EllipticCurve(x=None, y=None, j=None):
r"""
There are several ways to construct an elliptic curve:
.. math::
y^2 + a_1 xy + a_3 y = x^3 + a_2 x^2 + a_4 x + a_6.
- EllipticCurve([a1,a2,a3,a4,a6]): Elliptic curve with given
a-invariants. The invariants are coerced into the parent of the
first element. If all are integers, they are coerced into the
rational numbers.
- EllipticCurve([a4,a6]): Same as above, but a1=a2=a3=0.
- EllipticCurve(label): Returns the elliptic curve over Q from the
Cremona database with the given label. The label is a string, such
as "11a" or "37b2". The letters in the label *must* be lower case
(Cremona's new labeling).
- EllipticCurve(R, [a1,a2,a3,a4,a6]): Create the elliptic curve
over R with given a-invariants. Here R can be an arbitrary ring.
Note that addition need not be defined.
- EllipticCurve(j): Return an elliptic curve with j-invariant
`j`. Warning: this is deprecated. Use ``EllipticCurve_from_j(j)``
or ``EllipticCurve(j=j)`` instead.
In each case above where the input is a list of length 2 or 5, one
can instead give a 2 or 5-tuple instead.
EXAMPLES: We illustrate creating elliptic curves.
::
sage: EllipticCurve([0,0,1,-1,0])
Elliptic Curve defined by y^2 + y = x^3 - x over Rational Field
We create a curve from a Cremona label::
sage: EllipticCurve('37b2')
Elliptic Curve defined by y^2 + y = x^3 + x^2 - 1873*x - 31833 over Rational Field
sage: EllipticCurve('5077a')
Elliptic Curve defined by y^2 + y = x^3 - 7*x + 6 over Rational Field
sage: EllipticCurve('389a')
Elliptic Curve defined by y^2 + y = x^3 + x^2 - 2*x over Rational Field
Unicode labels are allowed::
sage: EllipticCurve(u'389a')
Elliptic Curve defined by y^2 + y = x^3 + x^2 - 2*x over Rational Field
We create curves over a finite field as follows::
sage: EllipticCurve([GF(5)(0),0,1,-1,0])
Elliptic Curve defined by y^2 + y = x^3 + 4*x over Finite Field of size 5
sage: EllipticCurve(GF(5), [0, 0,1,-1,0])
Elliptic Curve defined by y^2 + y = x^3 + 4*x over Finite Field of size 5
Elliptic curves over `\ZZ/N\ZZ` with `N` prime are of type
"elliptic curve over a finite field"::
sage: F = Zmod(101)
sage: EllipticCurve(F, [2, 3])
Elliptic Curve defined by y^2 = x^3 + 2*x + 3 over Ring of integers modulo 101
sage: E = EllipticCurve([F(2), F(3)])
sage: type(E)
<class 'sage.schemes.elliptic_curves.ell_finite_field.EllipticCurve_finite_field_with_category'>
sage: E.category()
Category of schemes over Ring of integers modulo 101
In contrast, elliptic curves over `\ZZ/N\ZZ` with `N` composite
are of type "generic elliptic curve"::
sage: F = Zmod(95)
sage: EllipticCurve(F, [2, 3])
Elliptic Curve defined by y^2 = x^3 + 2*x + 3 over Ring of integers modulo 95
sage: E = EllipticCurve([F(2), F(3)])
sage: type(E)
<class 'sage.schemes.elliptic_curves.ell_generic.EllipticCurve_generic_with_category'>
sage: E.category()
Category of schemes over Ring of integers modulo 95
The following is a curve over the complex numbers::
sage: E = EllipticCurve(CC, [0,0,1,-1,0])
sage: E
Elliptic Curve defined by y^2 + 1.00000000000000*y = x^3 + (-1.00000000000000)*x over Complex Field with 53 bits of precision
sage: E.j_invariant()
2988.97297297297
We can also create elliptic curves by giving the Weierstrass equation::
sage: x, y = var('x,y')
sage: EllipticCurve(y^2 + y == x^3 + x - 9)
Elliptic Curve defined by y^2 + y = x^3 + x - 9 over Rational Field
sage: R.<x,y> = GF(5)[]
sage: EllipticCurve(x^3 + x^2 + 2 - y^2 - y*x)
Elliptic Curve defined by y^2 + x*y = x^3 + x^2 + 2 over Finite Field of size 5
We can explicitly specify the `j`-invariant::
sage: E = EllipticCurve(j=1728); E; E.j_invariant(); E.label()
Elliptic Curve defined by y^2 = x^3 - x over Rational Field
1728
'32a2'
sage: E = EllipticCurve(j=GF(5)(2)); E; E.j_invariant()
Elliptic Curve defined by y^2 = x^3 + x + 1 over Finite Field of size 5
2
See trac #6657::
sage: EllipticCurve(GF(144169),j=1728)
Elliptic Curve defined by y^2 = x^3 + x over Finite Field of size 144169
TESTS::
sage: R = ZZ['u', 'v']
sage: EllipticCurve(R, [1,1])
Elliptic Curve defined by y^2 = x^3 + x + 1 over Multivariate Polynomial Ring in u, v
over Integer Ring
We create a curve and a point over QQbar (see #6879)::
sage: E = EllipticCurve(QQbar,[0,1])
sage: E(0)
(0 : 1 : 0)
sage: E.base_field()
Algebraic Field
sage: E = EllipticCurve(RR,[1,2]); E; E.base_field()
Elliptic Curve defined by y^2 = x^3 + 1.00000000000000*x + 2.00000000000000 over Real Field with 53 bits of precision
Real Field with 53 bits of precision
sage: EllipticCurve(CC,[3,4]); E; E.base_field()
Elliptic Curve defined by y^2 = x^3 + 3.00000000000000*x + 4.00000000000000 over Complex Field with 53 bits of precision
Elliptic Curve defined by y^2 = x^3 + 1.00000000000000*x + 2.00000000000000 over Real Field with 53 bits of precision
Real Field with 53 bits of precision
sage: E = EllipticCurve(QQbar,[5,6]); E; E.base_field()
Elliptic Curve defined by y^2 = x^3 + 5*x + 6 over Algebraic Field
Algebraic Field
See trac #6657::
sage: EllipticCurve(3,j=1728)
Traceback (most recent call last):
...
ValueError: First parameter (if present) must be a ring when j is specified
sage: EllipticCurve(GF(5),j=3/5)
Traceback (most recent call last):
...
ValueError: First parameter must be a ring containing 3/5
If the universe of the coefficients is a general field, the object
constructed has type EllipticCurve_field. Otherwise it is
EllipticCurve_generic. See trac #9816::
sage: E = EllipticCurve([QQbar(1),3]); E
Elliptic Curve defined by y^2 = x^3 + x + 3 over Algebraic Field
sage: type(E)
<class 'sage.schemes.elliptic_curves.ell_field.EllipticCurve_field_with_category'>
sage: E = EllipticCurve([RR(1),3]); E
Elliptic Curve defined by y^2 = x^3 + 1.00000000000000*x + 3.00000000000000 over Real Field with 53 bits of precision
sage: type(E)
<class 'sage.schemes.elliptic_curves.ell_field.EllipticCurve_field_with_category'>
sage: E = EllipticCurve([i,i]); E
Elliptic Curve defined by y^2 = x^3 + I*x + I over Symbolic Ring
sage: type(E)
<class 'sage.schemes.elliptic_curves.ell_field.EllipticCurve_field_with_category'>
sage: E.category()
Category of schemes over Symbolic Ring
sage: is_field(SR)
True
sage: F = FractionField(PolynomialRing(QQ,'t'))
sage: t = F.gen()
sage: E = EllipticCurve([t,0]); E
Elliptic Curve defined by y^2 = x^3 + t*x over Fraction Field of Univariate Polynomial Ring in t over Rational Field
sage: type(E)
<class 'sage.schemes.elliptic_curves.ell_field.EllipticCurve_field_with_category'>
sage: E.category()
Category of schemes over Fraction Field of Univariate Polynomial Ring in t over Rational Field
See :trac:`12517`::
sage: E = EllipticCurve([1..5])
sage: EllipticCurve(E.a_invariants())
Elliptic Curve defined by y^2 + x*y + 3*y = x^3 + 2*x^2 + 4*x + 5 over Rational Field
"""
import ell_generic, ell_field, ell_finite_field, ell_number_field, ell_rational_field, ell_padic_field # here to avoid circular includes
if j is not None:
if not x is None:
if rings.is_Ring(x):
try:
j = x(j)
except (ZeroDivisionError, ValueError, TypeError):
raise ValueError, "First parameter must be a ring containing %s"%j
else:
raise ValueError, "First parameter (if present) must be a ring when j is specified"
return EllipticCurve_from_j(j)
assert x is not None
if is_SymbolicEquation(x):
x = x.lhs() - x.rhs()
if parent(x) is SR:
x = x._polynomial_(rings.QQ['x', 'y'])
if rings.is_MPolynomial(x) and y is None:
f = x
if f.degree() != 3:
raise ValueError, "Elliptic curves must be defined by a cubic polynomial."
if f.degrees() == (3,2):
x, y = f.parent().gens()
elif f.degree() == (2,3):
y, x = f.parent().gens()
elif len(f.parent().gens()) == 2 or len(f.parent().gens()) == 3 and f.is_homogeneous():
# We'd need a point too...
raise NotImplementedError, "Construction of an elliptic curve from a generic cubic not yet implemented."
else:
raise ValueError, "Defining polynomial must be a cubic polynomial in two variables."
try:
if f.coefficient(x**3) < 0:
f = -f
# is there a nicer way to extract the coefficients?
a1 = a2 = a3 = a4 = a6 = 0
for coeff, mon in f:
if mon == x**3:
assert coeff == 1
elif mon == x**2:
a2 = coeff
elif mon == x:
a4 = coeff
elif mon == 1:
a6 = coeff
elif mon == y**2:
assert coeff == -1
elif mon == x*y:
a1 = -coeff
elif mon == y:
a3 = -coeff
else:
assert False
return EllipticCurve([a1, a2, a3, a4, a6])
except AssertionError:
raise NotImplementedError, "Construction of an elliptic curve from a generic cubic not yet implemented."
if rings.is_Ring(x):
if rings.is_RationalField(x):
return ell_rational_field.EllipticCurve_rational_field(x, y)
elif rings.is_FiniteField(x) or (rings.is_IntegerModRing(x) and x.characteristic().is_prime()):
return ell_finite_field.EllipticCurve_finite_field(x, y)
elif rings.is_pAdicField(x):
return ell_padic_field.EllipticCurve_padic_field(x, y)
elif rings.is_NumberField(x):
return ell_number_field.EllipticCurve_number_field(x, y)
elif rings.is_Field(x):
return ell_field.EllipticCurve_field(x, y)
return ell_generic.EllipticCurve_generic(x, y)
if isinstance(x, unicode):
x = str(x)
if isinstance(x, str):
return ell_rational_field.EllipticCurve_rational_field(x)
if rings.is_RingElement(x) and y is None:
from sage.misc.misc import deprecation
deprecation("'EllipticCurve(j)' is deprecated; use 'EllipticCurve_from_j(j)' or 'EllipticCurve(j=j)' instead.")
# Fixed for all characteristics and cases by John Cremona
j=x
F=j.parent().fraction_field()
char=F.characteristic()
if char==2:
if j==0:
return EllipticCurve(F, [ 0, 0, 1, 0, 0 ])
else:
return EllipticCurve(F, [ 1, 0, 0, 0, 1/j ])
if char==3:
if j==0:
return EllipticCurve(F, [ 0, 0, 0, 1, 0 ])
else:
return EllipticCurve(F, [ 0, j, 0, 0, -j**2 ])
if j == 0:
return EllipticCurve(F, [ 0, 0, 0, 0, 1 ])
if j == 1728:
return EllipticCurve(F, [ 0, 0, 0, 1, 0 ])
k=j-1728
return EllipticCurve(F, [0,0,0,-3*j*k, -2*j*k**2])
if not isinstance(x, (list, tuple)):
raise TypeError, "invalid input to EllipticCurve constructor"
x = Sequence(x)
if not (len(x) in [2,5]):
raise ValueError, "sequence of coefficients must have length 2 or 5"
R = x.universe()
if isinstance(x[0], (rings.Rational, rings.Integer, int, long)):
return ell_rational_field.EllipticCurve_rational_field(x, y)
elif rings.is_NumberField(R):
return ell_number_field.EllipticCurve_number_field(x, y)
elif rings.is_pAdicField(R):
return ell_padic_field.EllipticCurve_padic_field(x, y)
elif rings.is_FiniteField(R) or (rings.is_IntegerModRing(R) and R.characteristic().is_prime()):
return ell_finite_field.EllipticCurve_finite_field(x, y)
elif rings.is_Field(R):
return ell_field.EllipticCurve_field(x, y)
return ell_generic.EllipticCurve_generic(x, y)
# Distributed under the terms of the GNU General Public License (GPL)
# http://www.gnu.org/licenses/
#*****************************************************************************
from sage.categories.all import GroupAlgebras
from sage.structure.parent_gens import ParentWithGens
from sage.algebras.algebra import Algebra
from sage.algebras.algebra_element import AlgebraElement
from sage.rings.all import IntegerRing
from sage.groups.group import Group
from sage.structure.formal_sum import FormalSums, FormalSum
from sage.sets.set import Set
from sage.misc.misc import deprecation
deprecation(
"The module group_algebra is deprecated and will be removed in a future version of Sage. Use group_algebra_new instead."
)
class GroupAlgebra(Algebra):
def __init__(self, group, base_ring=IntegerRing()):
r""" Create the given group algebra.
INPUT:
-- (Group) group: a generic group.
-- (Ring) base_ring: a commutative ring.
OUTPUT:
-- a GroupAlgebra instance.
EXAMPLES::
sage: from sage.algebras.group_algebra import GroupAlgebra
def EllipticCurve(x=None, y=None, j=None):
r"""
There are several ways to construct an elliptic curve:
.. math::
y^2 + a_1 xy + a_3 y = x^3 + a_2 x^2 + a_4 x + a_6.
- EllipticCurve([a1,a2,a3,a4,a6]): Elliptic curve with given
a-invariants. The invariants are coerced into the parent of the
first element. If all are integers, they are coerced into the
rational numbers.
- EllipticCurve([a4,a6]): Same as above, but a1=a2=a3=0.
- EllipticCurve(label): Returns the elliptic curve over Q from the
Cremona database with the given label. The label is a string, such
as "11a" or "37b2". The letters in the label *must* be lower case
(Cremona's new labeling).
- EllipticCurve(R, [a1,a2,a3,a4,a6]): Create the elliptic curve
over R with given a-invariants. Here R can be an arbitrary ring.
Note that addition need not be defined.
- EllipticCurve(j): Return an elliptic curve with j-invariant
`j`. Warning: this is deprecated. Use ``EllipticCurve_from_j(j)``
or ``EllipticCurve(j=j)`` instead.
In each case above where the input is a list of length 2 or 5, one
can instead give a 2 or 5-tuple instead.
EXAMPLES: We illustrate creating elliptic curves.
::
sage: EllipticCurve([0,0,1,-1,0])
Elliptic Curve defined by y^2 + y = x^3 - x over Rational Field
We create a curve from a Cremona label::
sage: EllipticCurve('37b2')
Elliptic Curve defined by y^2 + y = x^3 + x^2 - 1873*x - 31833 over Rational Field
sage: EllipticCurve('5077a')
Elliptic Curve defined by y^2 + y = x^3 - 7*x + 6 over Rational Field
sage: EllipticCurve('389a')
Elliptic Curve defined by y^2 + y = x^3 + x^2 - 2*x over Rational Field
Unicode labels are allowed::
sage: EllipticCurve(u'389a')
Elliptic Curve defined by y^2 + y = x^3 + x^2 - 2*x over Rational Field
We create curves over a finite field as follows::
sage: EllipticCurve([GF(5)(0),0,1,-1,0])
Elliptic Curve defined by y^2 + y = x^3 + 4*x over Finite Field of size 5
sage: EllipticCurve(GF(5), [0, 0,1,-1,0])
Elliptic Curve defined by y^2 + y = x^3 + 4*x over Finite Field of size 5
Elliptic curves over `\ZZ/N\ZZ` with `N` prime are of type
"elliptic curve over a finite field"::
sage: F = Zmod(101)
sage: EllipticCurve(F, [2, 3])
Elliptic Curve defined by y^2 = x^3 + 2*x + 3 over Ring of integers modulo 101
sage: E = EllipticCurve([F(2), F(3)])
sage: type(E)
<class 'sage.schemes.elliptic_curves.ell_finite_field.EllipticCurve_finite_field_with_category'>
sage: E.category()
Category of schemes over Ring of integers modulo 101
In contrast, elliptic curves over `\ZZ/N\ZZ` with `N` composite
are of type "generic elliptic curve"::
sage: F = Zmod(95)
sage: EllipticCurve(F, [2, 3])
Elliptic Curve defined by y^2 = x^3 + 2*x + 3 over Ring of integers modulo 95
sage: E = EllipticCurve([F(2), F(3)])
sage: type(E)
<class 'sage.schemes.elliptic_curves.ell_generic.EllipticCurve_generic_with_category'>
sage: E.category()
Category of schemes over Ring of integers modulo 95
The following is a curve over the complex numbers::
sage: E = EllipticCurve(CC, [0,0,1,-1,0])
sage: E
Elliptic Curve defined by y^2 + 1.00000000000000*y = x^3 + (-1.00000000000000)*x over Complex Field with 53 bits of precision
sage: E.j_invariant()
2988.97297297297
We can also create elliptic curves by giving the Weierstrass equation::
sage: x, y = var('x,y')
sage: EllipticCurve(y^2 + y == x^3 + x - 9)
Elliptic Curve defined by y^2 + y = x^3 + x - 9 over Rational Field
sage: R.<x,y> = GF(5)[]
sage: EllipticCurve(x^3 + x^2 + 2 - y^2 - y*x)
Elliptic Curve defined by y^2 + x*y = x^3 + x^2 + 2 over Finite Field of size 5
We can explicitly specify the `j`-invariant::
sage: E = EllipticCurve(j=1728); E; E.j_invariant(); E.label()
Elliptic Curve defined by y^2 = x^3 - x over Rational Field
1728
'32a2'
sage: E = EllipticCurve(j=GF(5)(2)); E; E.j_invariant()
Elliptic Curve defined by y^2 = x^3 + x + 1 over Finite Field of size 5
2
See trac #6657::
sage: EllipticCurve(GF(144169),j=1728)
Elliptic Curve defined by y^2 = x^3 + x over Finite Field of size 144169
TESTS::
sage: R = ZZ['u', 'v']
sage: EllipticCurve(R, [1,1])
Elliptic Curve defined by y^2 = x^3 + x + 1 over Multivariate Polynomial Ring in u, v
over Integer Ring
We create a curve and a point over QQbar (see #6879)::
sage: E = EllipticCurve(QQbar,[0,1])
sage: E(0)
(0 : 1 : 0)
sage: E.base_field()
Algebraic Field
sage: E = EllipticCurve(RR,[1,2]); E; E.base_field()
Elliptic Curve defined by y^2 = x^3 + 1.00000000000000*x + 2.00000000000000 over Real Field with 53 bits of precision
Real Field with 53 bits of precision
sage: EllipticCurve(CC,[3,4]); E; E.base_field()
Elliptic Curve defined by y^2 = x^3 + 3.00000000000000*x + 4.00000000000000 over Complex Field with 53 bits of precision
Elliptic Curve defined by y^2 = x^3 + 1.00000000000000*x + 2.00000000000000 over Real Field with 53 bits of precision
Real Field with 53 bits of precision
sage: E = EllipticCurve(QQbar,[5,6]); E; E.base_field()
Elliptic Curve defined by y^2 = x^3 + 5*x + 6 over Algebraic Field
Algebraic Field
See trac #6657::
sage: EllipticCurve(3,j=1728)
Traceback (most recent call last):
...
ValueError: First parameter (if present) must be a ring when j is specified
sage: EllipticCurve(GF(5),j=3/5)
Traceback (most recent call last):
...
ValueError: First parameter must be a ring containing 3/5
If the universe of the coefficients is a general field, the object
constructed has type EllipticCurve_field. Otherwise it is
EllipticCurve_generic. See trac #9816::
sage: E = EllipticCurve([QQbar(1),3]); E
Elliptic Curve defined by y^2 = x^3 + x + 3 over Algebraic Field
sage: type(E)
<class 'sage.schemes.elliptic_curves.ell_field.EllipticCurve_field_with_category'>
sage: E = EllipticCurve([RR(1),3]); E
Elliptic Curve defined by y^2 = x^3 + 1.00000000000000*x + 3.00000000000000 over Real Field with 53 bits of precision
sage: type(E)
<class 'sage.schemes.elliptic_curves.ell_field.EllipticCurve_field_with_category'>
sage: E = EllipticCurve([i,i]); E
Elliptic Curve defined by y^2 = x^3 + I*x + I over Symbolic Ring
sage: type(E)
<class 'sage.schemes.elliptic_curves.ell_field.EllipticCurve_field_with_category'>
sage: E.category()
Category of schemes over Symbolic Ring
sage: is_field(SR)
True
sage: F = FractionField(PolynomialRing(QQ,'t'))
sage: t = F.gen()
sage: E = EllipticCurve([t,0]); E
Elliptic Curve defined by y^2 = x^3 + t*x over Fraction Field of Univariate Polynomial Ring in t over Rational Field
sage: type(E)
<class 'sage.schemes.elliptic_curves.ell_field.EllipticCurve_field_with_category'>
sage: E.category()
Category of schemes over Fraction Field of Univariate Polynomial Ring in t over Rational Field
See :trac:`12517`::
sage: E = EllipticCurve([1..5])
sage: EllipticCurve(E.a_invariants())
Elliptic Curve defined by y^2 + x*y + 3*y = x^3 + 2*x^2 + 4*x + 5 over Rational Field
"""
import ell_generic, ell_field, ell_finite_field, ell_number_field, ell_rational_field, ell_padic_field # here to avoid circular includes
if j is not None:
if not x is None:
if rings.is_Ring(x):
try:
j = x(j)
except (ZeroDivisionError, ValueError, TypeError):
raise ValueError, "First parameter must be a ring containing %s" % j
else:
raise ValueError, "First parameter (if present) must be a ring when j is specified"
return EllipticCurve_from_j(j)
assert x is not None
if is_SymbolicEquation(x):
x = x.lhs() - x.rhs()
if parent(x) is SR:
x = x._polynomial_(rings.QQ["x", "y"])
if rings.is_MPolynomial(x) and y is None:
f = x
if f.degree() != 3:
raise ValueError, "Elliptic curves must be defined by a cubic polynomial."
if f.degrees() == (3, 2):
x, y = f.parent().gens()
elif f.degree() == (2, 3):
y, x = f.parent().gens()
elif len(f.parent().gens()) == 2 or len(f.parent().gens()) == 3 and f.is_homogeneous():
# We'd need a point too...
raise NotImplementedError, "Construction of an elliptic curve from a generic cubic not yet implemented."
else:
raise ValueError, "Defining polynomial must be a cubic polynomial in two variables."
try:
if f.coefficient(x ** 3) < 0:
f = -f
# is there a nicer way to extract the coefficients?
a1 = a2 = a3 = a4 = a6 = 0
for coeff, mon in f:
if mon == x ** 3:
assert coeff == 1
elif mon == x ** 2:
a2 = coeff
elif mon == x:
a4 = coeff
elif mon == 1:
a6 = coeff
elif mon == y ** 2:
assert coeff == -1
elif mon == x * y:
a1 = -coeff
elif mon == y:
a3 = -coeff
else:
assert False
return EllipticCurve([a1, a2, a3, a4, a6])
except AssertionError:
raise NotImplementedError, "Construction of an elliptic curve from a generic cubic not yet implemented."
if rings.is_Ring(x):
if rings.is_RationalField(x):
return ell_rational_field.EllipticCurve_rational_field(x, y)
elif rings.is_FiniteField(x) or (rings.is_IntegerModRing(x) and x.characteristic().is_prime()):
return ell_finite_field.EllipticCurve_finite_field(x, y)
elif rings.is_pAdicField(x):
return ell_padic_field.EllipticCurve_padic_field(x, y)
elif rings.is_NumberField(x):
return ell_number_field.EllipticCurve_number_field(x, y)
elif rings.is_Field(x):
return ell_field.EllipticCurve_field(x, y)
return ell_generic.EllipticCurve_generic(x, y)
if isinstance(x, unicode):
x = str(x)
if isinstance(x, str):
return ell_rational_field.EllipticCurve_rational_field(x)
if rings.is_RingElement(x) and y is None:
from sage.misc.misc import deprecation
deprecation("'EllipticCurve(j)' is deprecated; use 'EllipticCurve_from_j(j)' or 'EllipticCurve(j=j)' instead.")
# Fixed for all characteristics and cases by John Cremona
j = x
F = j.parent().fraction_field()
char = F.characteristic()
if char == 2:
if j == 0:
return EllipticCurve(F, [0, 0, 1, 0, 0])
else:
return EllipticCurve(F, [1, 0, 0, 0, 1 / j])
if char == 3:
if j == 0:
return EllipticCurve(F, [0, 0, 0, 1, 0])
else:
return EllipticCurve(F, [0, j, 0, 0, -j ** 2])
if j == 0:
return EllipticCurve(F, [0, 0, 0, 0, 1])
if j == 1728:
return EllipticCurve(F, [0, 0, 0, 1, 0])
k = j - 1728
return EllipticCurve(F, [0, 0, 0, -3 * j * k, -2 * j * k ** 2])
if not isinstance(x, (list, tuple)):
raise TypeError, "invalid input to EllipticCurve constructor"
x = Sequence(x)
if not (len(x) in [2, 5]):
raise ValueError, "sequence of coefficients must have length 2 or 5"
R = x.universe()
if isinstance(x[0], (rings.Rational, rings.Integer, int, long)):
return ell_rational_field.EllipticCurve_rational_field(x, y)
elif rings.is_NumberField(R):
return ell_number_field.EllipticCurve_number_field(x, y)
elif rings.is_pAdicField(R):
return ell_padic_field.EllipticCurve_padic_field(x, y)
elif rings.is_FiniteField(R) or (rings.is_IntegerModRing(R) and R.characteristic().is_prime()):
return ell_finite_field.EllipticCurve_finite_field(x, y)
elif rings.is_Field(R):
return ell_field.EllipticCurve_field(x, y)
return ell_generic.EllipticCurve_generic(x, y)
def setup_for_eval_on_grid(funcs, ranges, plot_points=None, return_vars=False):
"""
Calculate the necessary parameters to construct a list of points,
and make the functions fast_callable.
INPUT:
- ``funcs`` - a function, or a list, tuple, or vector of functions
- ``ranges`` - a list of ranges. A range can be a 2-tuple of
numbers specifying the minimum and maximum, or a 3-tuple giving
the variable explicitly.
- ``plot_points`` - a tuple of integers specifying the number of
plot points for each range. If a single number is specified, it
will be the value for all ranges. This defaults to 2.
- ``return_vars`` - (default False) If True, return the variables,
in order.
OUTPUT:
- ``fast_funcs`` - if only one function passed, then a fast
callable function. If funcs is a list or tuple, then a tuple
of fast callable functions is returned.
- ``range_specs`` - a list of range_specs: for each range, a
tuple is returned of the form (range_min, range_max,
range_step) such that ``srange(range_min, range_max,
range_step, include_endpoint=True)`` gives the correct points
for evaluation.
EXAMPLES::
sage: x,y,z=var('x,y,z')
sage: f(x,y)=x+y-z
sage: g(x,y)=x+y
sage: h(y)=-y
sage: sage.plot.misc.setup_for_eval_on_grid(f, [(0, 2),(1,3),(-4,1)], plot_points=5)
(<sage.ext...>, [(0.0, 2.0, 0.5), (1.0, 3.0, 0.5), (-4.0, 1.0, 1.25)])
sage: sage.plot.misc.setup_for_eval_on_grid([g,h], [(0, 2),(-1,1)], plot_points=5)
((<sage.ext...>, <sage.ext...>), [(0.0, 2.0, 0.5), (-1.0, 1.0, 0.5)])
sage: sage.plot.misc.setup_for_eval_on_grid([sin,cos], [(-1,1)], plot_points=9)
((<sage.ext...>, <sage.ext...>), [(-1.0, 1.0, 0.25)])
sage: sage.plot.misc.setup_for_eval_on_grid([lambda x: x^2,cos], [(-1,1)], plot_points=9)
((<function <lambda> ...>, <sage.ext...>), [(-1.0, 1.0, 0.25)])
sage: sage.plot.misc.setup_for_eval_on_grid([x+y], [(x,-1,1),(y,-2,2)])
((<sage.ext...>,), [(-1.0, 1.0, 2.0), (-2.0, 2.0, 4.0)])
sage: sage.plot.misc.setup_for_eval_on_grid(x+y, [(x,-1,1),(y,-1,1)], plot_points=[4,9])
(<sage.ext...>, [(-1.0, 1.0, 0.6666666666666666), (-1.0, 1.0, 0.25)])
sage: sage.plot.misc.setup_for_eval_on_grid(x+y, [(x,-1,1),(y,-1,1)], plot_points=[4,9,10])
Traceback (most recent call last):
...
ValueError: plot_points must be either an integer or a list of integers, one for each range
sage: sage.plot.misc.setup_for_eval_on_grid(x+y, [(1,-1),(y,-1,1)], plot_points=[4,9,10])
Traceback (most recent call last):
...
ValueError: Some variable ranges specify variables while others do not
sage: sage.plot.misc.setup_for_eval_on_grid(x+y, [(1,-1),(-1,1)], plot_points=5)
doctest:...: DeprecationWarning: Unnamed ranges for more than one variable is deprecated and will be removed from a future release of Sage; you can used named ranges instead, like (x,0,2)
(<sage.ext...>, [(1.0, -1.0, 0.5), (-1.0, 1.0, 0.5)])
sage: sage.plot.misc.setup_for_eval_on_grid(x+y, [(y,1,-1),(x,-1,1)], plot_points=5)
(<sage.ext...>, [(1.0, -1.0, 0.5), (-1.0, 1.0, 0.5)])
sage: sage.plot.misc.setup_for_eval_on_grid(x+y, [(x,1,-1),(x,-1,1)], plot_points=5)
Traceback (most recent call last):
...
ValueError: range variables should be distinct, but there are duplicates
sage: sage.plot.misc.setup_for_eval_on_grid(x+y, [(x,1,1),(y,-1,1)])
Traceback (most recent call last):
...
ValueError: plot start point and end point must be different
sage: sage.plot.misc.setup_for_eval_on_grid(x+y, [(x,1,-1),(y,-1,1)], return_vars=True)
(<sage.ext...>, [(1.0, -1.0, 2.0), (-1.0, 1.0, 2.0)], [x, y])
sage: sage.plot.misc.setup_for_eval_on_grid(x+y, [(y,1,-1),(x,-1,1)], return_vars=True)
(<sage.ext...>, [(1.0, -1.0, 2.0), (-1.0, 1.0, 2.0)], [y, x])
"""
if max(map(len, ranges)) != min(map(len, ranges)):
raise ValueError, "Some variable ranges specify variables while others do not"
if len(ranges[0]) == 3:
vars = [r[0] for r in ranges]
ranges = [r[1:] for r in ranges]
if len(set(vars)) < len(vars):
raise ValueError, "range variables should be distinct, but there are duplicates"
else:
vars, free_vars = unify_arguments(funcs)
if len(free_vars) > 1:
from sage.misc.misc import deprecation
deprecation(
"Unnamed ranges for more than one variable is deprecated and will be removed from a future release of Sage; you can used named ranges instead, like (x,0,2)"
)
# pad the variables if we don't have enough
nargs = len(ranges)
if len(vars) < nargs:
vars += ('_', ) * (nargs - len(vars))
ranges = [[float(z) for z in r] for r in ranges]
if plot_points is None:
plot_points = 2
if not isinstance(plot_points, (list, tuple)):
plot_points = [plot_points] * len(ranges)
elif len(plot_points) != nargs:
raise ValueError, "plot_points must be either an integer or a list of integers, one for each range"
plot_points = [int(p) if p >= 2 else 2 for p in plot_points]
range_steps = [
abs(range[1] - range[0]) / (p - 1)
for range, p in zip(ranges, plot_points)
]
if min(range_steps) == float(0):
raise ValueError, "plot start point and end point must be different"
options = {}
if nargs == 1:
options['expect_one_var'] = True
if is_Vector(funcs):
funcs = list(funcs)
#TODO: raise an error if there is a function/method in funcs that takes more values than we have ranges
if return_vars:
return fast_float(funcs, *vars, **options), [
tuple(range + [range_step])
for range, range_step in zip(ranges, range_steps)
], vars
else:
return fast_float(funcs, *vars, **options), [
tuple(range + [range_step])
for range, range_step in zip(ranges, range_steps)
]
def integrate(expression, v=None, a=None, b=None, algorithm=None):
r"""
Returns the indefinite integral with respect to the variable
`v`, ignoring the constant of integration. Or, if endpoints
`a` and `b` are specified, returns the definite
integral over the interval `[a, b]`.
If ``self`` has only one variable, then it returns the
integral with respect to that variable.
If definite integration fails, it could be still possible to
evaluate the definite integral using indefinite integration with
the Newton - Leibniz theorem (however, the user has to ensure that the
indefinite integral is continuous on the compact interval `[a,b]` and
this theorem can be applied).
INPUT:
- ``v`` - a variable or variable name. This can also be a tuple of
the variable (optional) and endpoints (i.e., ``(x,0,1)`` or ``(0,1)``).
- ``a`` - (optional) lower endpoint of definite integral
- ``b`` - (optional) upper endpoint of definite integral
- ``algorithm`` - (default: 'maxima') one of
- 'maxima' - use maxima (the default)
- 'sympy' - use sympy (also in Sage)
- 'mathematica_free' - use http://integrals.wolfram.com/
EXAMPLES::
sage: x = var('x')
sage: h = sin(x)/(cos(x))^2
sage: h.integral(x)
1/cos(x)
::
sage: f = x^2/(x+1)^3
sage: f.integral(x)
1/2*(4*x + 3)/(x^2 + 2*x + 1) + log(x + 1)
::
sage: f = x*cos(x^2)
sage: f.integral(x, 0, sqrt(pi))
0
sage: f.integral(x, a=-pi, b=pi)
0
::
sage: f(x) = sin(x)
sage: f.integral(x, 0, pi/2)
x |--> 1
The variable is required, but the endpoints are optional::
sage: y=var('y')
sage: integral(sin(x), x)
-cos(x)
sage: integral(sin(x), y)
y*sin(x)
sage: integral(sin(x), x, pi, 2*pi)
-2
sage: integral(sin(x), y, pi, 2*pi)
pi*sin(x)
sage: integral(sin(x), (x, pi, 2*pi))
-2
sage: integral(sin(x), (y, pi, 2*pi))
pi*sin(x)
Constraints are sometimes needed::
sage: var('x, n')
(x, n)
sage: integral(x^n,x)
Traceback (most recent call last):
...
ValueError: Computation failed since Maxima requested additional
constraints; using the 'assume' command before integral evaluation
*may* help (example of legal syntax is 'assume(n+1>0)', see `assume?`
for more details)
Is n+1 zero or nonzero?
sage: assume(n > 0)
sage: integral(x^n,x)
x^(n + 1)/(n + 1)
sage: forget()
Usually the constraints are of sign, but others are possible::
sage: assume(n==-1)
sage: integral(x^n,x)
log(x)
Note that an exception is raised when a definite integral is
divergent::
sage: forget() # always remember to forget assumptions you no longer need
sage: integrate(1/x^3,(x,0,1))
Traceback (most recent call last):
...
ValueError: Integral is divergent.
sage: integrate(1/x^3,x,-1,3)
Traceback (most recent call last):
...
ValueError: Integral is divergent.
But Sage can calculate the convergent improper integral of
this function::
sage: integrate(1/x^3,x,1,infinity)
1/2
The examples in the Maxima documentation::
sage: var('x, y, z, b')
(x, y, z, b)
sage: integral(sin(x)^3, x)
1/3*cos(x)^3 - cos(x)
sage: integral(x/sqrt(b^2-x^2), b)
x*log(2*b + 2*sqrt(b^2 - x^2))
sage: integral(x/sqrt(b^2-x^2), x)
-sqrt(b^2 - x^2)
sage: integral(cos(x)^2 * exp(x), x, 0, pi)
3/5*e^pi - 3/5
sage: integral(x^2 * exp(-x^2), x, -oo, oo)
1/2*sqrt(pi)
We integrate the same function in both Mathematica and Sage (via
Maxima)::
sage: _ = var('x, y, z')
sage: f = sin(x^2) + y^z
sage: g = mathematica(f) # optional -- requires mathematica
sage: print g # optional -- requires mathematica
z 2
y + Sin[x ]
sage: print g.Integrate(x) # optional -- requires mathematica
z Pi 2
x y + Sqrt[--] FresnelS[Sqrt[--] x]
2 Pi
sage: print f.integral(x)
y^z*x + 1/8*((I - 1)*sqrt(2)*erf((1/2*I - 1/2)*sqrt(2)*x) + (I + 1)*sqrt(2)*erf((1/2*I + 1/2)*sqrt(2)*x))*sqrt(pi)
Alternatively, just use algorithm='mathematica_free' to integrate via Mathematica
over the internet (does NOT require a Mathematica license!)::
sage: _ = var('x, y, z')
sage: f = sin(x^2) + y^z
sage: f.integrate(algorithm="mathematica_free") # optional -- requires internet
sqrt(pi)*sqrt(1/2)*fresnels(sqrt(2)*x/sqrt(pi)) + y^z*x
We can also use Sympy::
sage: _ = var('x, y, z')
sage: (x^y-z).integrate(y)
-y*z + x^y/log(x)
sage: (x^y-z).integrate(y,algorithm="sympy")
-y*z + x^y/log(x)
We integrate the above function in maple now::
sage: g = maple(f); g # optional -- requires maple
sin(x^2)+y^z
sage: g.integrate(x) # optional -- requires maple
1/2*2^(1/2)*Pi^(1/2)*FresnelS(2^(1/2)/Pi^(1/2)*x)+y^z*x
We next integrate a function with no closed form integral. Notice
that the answer comes back as an expression that contains an
integral itself.
::
sage: A = integral(1/ ((x-4) * (x^3+2*x+1)), x); A
1/73*log(x - 4) - 1/73*integrate((x^2 + 4*x + 18)/(x^3 + 2*x + 1), x)
We now show that floats are not converted to rationals
automatically since we by default have keepfloat: true in maxima.
::
sage: integral(e^(-x^2),(x, 0, 0.1))
0.0562314580091*sqrt(pi)
ALIASES: integral() and integrate() are the same.
EXAMPLES:
Here is an example where we have to use assume::
sage: a,b = var('a,b')
sage: integrate(1/(x^3 *(a+b*x)^(1/3)), x)
Traceback (most recent call last):
...
ValueError: Computation failed since Maxima requested additional
constraints; using the 'assume' command before integral evaluation
*may* help (example of legal syntax is 'assume(a>0)', see `assume?`
for more details)
Is a positive or negative?
So we just assume that `a>0` and the integral works::
sage: assume(a>0)
sage: integrate(1/(x^3 *(a+b*x)^(1/3)), x)
2/9*sqrt(3)*b^2*arctan(1/3*(2*(b*x + a)^(1/3) + a^(1/3))*sqrt(3)/a^(1/3))/a^(7/3) + 2/9*b^2*log((b*x + a)^(1/3) - a^(1/3))/a^(7/3) - 1/9*b^2*log((b*x + a)^(2/3) + (b*x + a)^(1/3)*a^(1/3) + a^(2/3))/a^(7/3) + 1/6*(4*(b*x + a)^(5/3)*b^2 - 7*(b*x + a)^(2/3)*a*b^2)/((b*x + a)^2*a^2 - 2*(b*x + a)*a^3 + a^4)
TESTS:
The following integral was broken prior to Maxima 5.15.0 -
see #3013::
sage: integrate(sin(x)*cos(10*x)*log(x), x)
1/198*(11*cos(9*x) - 9*cos(11*x))*log(x) + 1/44*Ei(-11*I*x) - 1/36*Ei(-9*I*x) - 1/36*Ei(9*I*x) + 1/44*Ei(11*I*x)
It is no longer possible to use certain functions without an
explicit variable. Instead, evaluate the function at a variable,
and then take the integral::
sage: integrate(sin)
Traceback (most recent call last):
...
TypeError
sage: integrate(sin(x), x)
-cos(x)
sage: integrate(sin(x), x, 0, 1)
-cos(1) + 1
Check if #780 is fixed::
sage: _ = var('x,y')
sage: f = log(x^2+y^2)
sage: res = integral(f,x,0.0001414, 1.); res
Traceback (most recent call last):
...
ValueError: Computation failed since Maxima requested additional
constraints; using the 'assume' command before integral evaluation
*may* help (example of legal syntax is 'assume((y-1)*(y+1)>0)',
see `assume?` for more details)
Is (y-1)*(y+1) positive, negative, or zero?
sage: assume(y>1)
sage: res = integral(f,x,0.0001414, 1.); res
2*y*arctan(1/y) - 2*y*arctan(0.0001414/y) - 0.0001414*log(y^2 + 1.999396e-08) + log(y^2 + 1.0) - 1.9997172
sage: nres = numerical_integral(f.subs(y=2), 0.0001414, 1.); nres
(1.4638323264144..., 1.6251803529759...e-14)
sage: res.subs(y=2).n()
1.46383232641443
sage: nres = numerical_integral(f.subs(y=.5), 0.0001414, 1.); nres
(-0.669511708872807, 7.768678110854711e-15)
sage: res.subs(y=.5).n()
-0.669511708872807
Check if #6816 is fixed::
sage: var('t,theta')
(t, theta)
sage: integrate(t*cos(-theta*t),t,0,pi)
(pi*theta*sin(pi*theta) + cos(pi*theta))/theta^2 - 1/theta^2
sage: integrate(t*cos(-theta*t),(t,0,pi))
(pi*theta*sin(pi*theta) + cos(pi*theta))/theta^2 - 1/theta^2
sage: integrate(t*cos(-theta*t),t)
(t*theta*sin(t*theta) + cos(t*theta))/theta^2
sage: integrate(x^2,(x)) # this worked before
1/3*x^3
sage: integrate(x^2,(x,)) # this didn't
1/3*x^3
sage: integrate(x^2,(x,1,2))
7/3
sage: integrate(x^2,(x,1,2,3))
Traceback (most recent call last):
...
ValueError: invalid input (x, 1, 2, 3) - please use variable, with or without two endpoints
Note that this used to be the test, but it is
actually divergent (though Maxima as yet does
not say so)::
sage: integrate(t*cos(-theta*t),(t,-oo,oo))
integrate(t*cos(t*theta), t, -Infinity, +Infinity)
Check if #6189 is fixed (which, by the way, also
demonstrates it's not always good to expand)::
sage: n = N; n
<function numerical_approx at ...>
sage: F(x) = 1/sqrt(2*pi*1^2)*exp(-1/(2*1^2)*(x-0)^2)
sage: G(x) = 1/sqrt(2*pi*n(1)^2)*exp(-1/(2*n(1)^2)*(x-n(0))^2)
sage: integrate( (F(x)-F(x))^2, x, -infinity, infinity).n()
0.000000000000000
sage: integrate( ((F(x)-G(x))^2).expand(), x, -infinity, infinity).n()
-6.26376265908397e-17
sage: integrate( (F(x)-G(x))^2, x, -infinity, infinity).n()
-6.26376265908397e-17
This was broken before Maxima 5.20::
sage: exp(-x*i).integral(x,0,1)
I*e^(-I) - I
Test deprecation warning when variable is not specified::
sage: x.integral()
doctest:...: DeprecationWarning: Variable of integration should be specified explicitly.
1/2*x^2
Test that #8729 is fixed::
sage: t = var('t')
sage: a = sqrt((sin(t))^2 + (cos(t))^2)
sage: integrate(a, t, 0, 2*pi)
2*pi
sage: a.simplify_full().simplify_trig()
1
Maxima uses Cauchy Principal Value calculations to
integrate certain convergent integrals. Here we test
that this does not raise an error message (see #11987)::
sage: integrate(sin(x)*sin(x/3)/x^2, x, 0, oo)
1/6*pi
Maxima returned a negative value for this integral prior to
maxima-5.24 (trac #10923). Ideally we would get an answer in terms
of the gamma function; however, we get something equivalent::
sage: actual_result = integral(e^(-1/x^2), x, 0, 1)
sage: actual_result.full_simplify()
((e*erf(1) - e)*sqrt(pi) + 1)*e^(-1)
sage: ideal_result = 1/2*gamma(-1/2, 1)
sage: error = actual_result - ideal_result
sage: error.numerical_approx() # abs tol 10e-10
0
"""
if isinstance(v, (list, tuple)) and a is None and b is None:
if len(v) == 1: # bare variable in a tuple
v = v[0]
elif len(v) == 3: # variable and endpoints
v, a, b = v
elif len(v) == 2: # endpoints only
a, b = v
v = None
elif len(v) == 0:
v = None
else:
raise ValueError, "invalid input %s - please use variable, with or without two endpoints" % repr(
v)
elif b is None and a is not None:
# two arguments, must be endpoints
a, b = v, a
v = None
if v is None:
from sage.misc.misc import deprecation
deprecation("Variable of integration should be specified explicitly.")
v = expression.default_variable()
if isinstance(expression, Function):
# a bare function like sin
expression = expression(v)
if (a is None) ^ (b is None):
raise TypeError, 'only one endpoint given'
# Check algorithm
if algorithm is not None:
integrator = available_integrators.get(algorithm)
if not integrator:
raise ValueError, "Unknown algorithm: %s" % algorithm
return integrator(expression, v, a, b)
if a is None:
return indefinite_integral(expression, v)
else:
return definite_integral(expression, v, a, b)
def integrate(expression, v=None, a=None, b=None, algorithm=None):
r"""
Returns the indefinite integral with respect to the variable
`v`, ignoring the constant of integration. Or, if endpoints
`a` and `b` are specified, returns the definite
integral over the interval `[a, b]`.
If ``self`` has only one variable, then it returns the
integral with respect to that variable.
If definite integration fails, it could be still possible to
evaluate the definite integral using indefinite integration with
the Newton - Leibniz theorem (however, the user has to ensure that the
indefinite integral is continuous on the compact interval `[a,b]` and
this theorem can be applied).
INPUT:
- ``v`` - a variable or variable name. This can also be a tuple of
the variable (optional) and endpoints (i.e., ``(x,0,1)`` or ``(0,1)``).
- ``a`` - (optional) lower endpoint of definite integral
- ``b`` - (optional) upper endpoint of definite integral
- ``algorithm`` - (default: 'maxima') one of
- 'maxima' - use maxima (the default)
- 'sympy' - use sympy (also in Sage)
- 'mathematica_free' - use http://integrals.wolfram.com/
EXAMPLES::
sage: x = var('x')
sage: h = sin(x)/(cos(x))^2
sage: h.integral(x)
1/cos(x)
::
sage: f = x^2/(x+1)^3
sage: f.integral(x)
1/2*(4*x + 3)/(x^2 + 2*x + 1) + log(x + 1)
::
sage: f = x*cos(x^2)
sage: f.integral(x, 0, sqrt(pi))
0
sage: f.integral(x, a=-pi, b=pi)
0
::
sage: f(x) = sin(x)
sage: f.integral(x, 0, pi/2)
x |--> 1
The variable is required, but the endpoints are optional::
sage: y=var('y')
sage: integral(sin(x), x)
-cos(x)
sage: integral(sin(x), y)
y*sin(x)
sage: integral(sin(x), x, pi, 2*pi)
-2
sage: integral(sin(x), y, pi, 2*pi)
pi*sin(x)
sage: integral(sin(x), (x, pi, 2*pi))
-2
sage: integral(sin(x), (y, pi, 2*pi))
pi*sin(x)
Constraints are sometimes needed::
sage: var('x, n')
(x, n)
sage: integral(x^n,x)
Traceback (most recent call last):
...
ValueError: Computation failed since Maxima requested additional
constraints; using the 'assume' command before integral evaluation
*may* help (example of legal syntax is 'assume(n+1>0)', see `assume?`
for more details)
Is n+1 zero or nonzero?
sage: assume(n > 0)
sage: integral(x^n,x)
x^(n + 1)/(n + 1)
sage: forget()
Usually the constraints are of sign, but others are possible::
sage: assume(n==-1)
sage: integral(x^n,x)
log(x)
Note that an exception is raised when a definite integral is
divergent::
sage: forget() # always remember to forget assumptions you no longer need
sage: integrate(1/x^3,(x,0,1))
Traceback (most recent call last):
...
ValueError: Integral is divergent.
sage: integrate(1/x^3,x,-1,3)
Traceback (most recent call last):
...
ValueError: Integral is divergent.
But Sage can calculate the convergent improper integral of
this function::
sage: integrate(1/x^3,x,1,infinity)
1/2
The examples in the Maxima documentation::
sage: var('x, y, z, b')
(x, y, z, b)
sage: integral(sin(x)^3, x)
1/3*cos(x)^3 - cos(x)
sage: integral(x/sqrt(b^2-x^2), b)
x*log(2*b + 2*sqrt(b^2 - x^2))
sage: integral(x/sqrt(b^2-x^2), x)
-sqrt(b^2 - x^2)
sage: integral(cos(x)^2 * exp(x), x, 0, pi)
3/5*e^pi - 3/5
sage: integral(x^2 * exp(-x^2), x, -oo, oo)
1/2*sqrt(pi)
We integrate the same function in both Mathematica and Sage (via
Maxima)::
sage: _ = var('x, y, z')
sage: f = sin(x^2) + y^z
sage: g = mathematica(f) # optional -- requires mathematica
sage: print g # optional -- requires mathematica
z 2
y + Sin[x ]
sage: print g.Integrate(x) # optional -- requires mathematica
z Pi 2
x y + Sqrt[--] FresnelS[Sqrt[--] x]
2 Pi
sage: print f.integral(x)
y^z*x + 1/8*((I + 1)*sqrt(2)*erf((1/2*I + 1/2)*sqrt(2)*x) + (I - 1)*sqrt(2)*erf((1/2*I - 1/2)*sqrt(2)*x))*sqrt(pi)
Alternatively, just use algorithm='mathematica_free' to integrate via Mathematica
over the internet (does NOT require a Mathematica license!)::
sage: _ = var('x, y, z')
sage: f = sin(x^2) + y^z
sage: f.integrate(algorithm="mathematica_free") # optional -- requires internet
sqrt(pi)*sqrt(1/2)*fresnels(sqrt(2)*x/sqrt(pi)) + y^z*x
We can also use Sympy::
sage: _ = var('x, y, z')
sage: (x^y-z).integrate(y)
-y*z + x^y/log(x)
sage: (x^y-z).integrate(y,algorithm="sympy")
-y*z + x^y/log(x)
We integrate the above function in maple now::
sage: g = maple(f); g # optional -- requires maple
sin(x^2)+y^z
sage: g.integrate(x) # optional -- requires maple
1/2*2^(1/2)*Pi^(1/2)*FresnelS(2^(1/2)/Pi^(1/2)*x)+y^z*x
We next integrate a function with no closed form integral. Notice
that the answer comes back as an expression that contains an
integral itself.
::
sage: A = integral(1/ ((x-4) * (x^3+2*x+1)), x); A
1/73*log(x - 4) - 1/73*integrate((x^2 + 4*x + 18)/(x^3 + 2*x + 1), x)
We now show that floats are not converted to rationals
automatically since we by default have keepfloat: true in maxima.
::
sage: integral(e^(-x^2),(x, 0, 0.1))
0.0562314580091*sqrt(pi)
ALIASES: integral() and integrate() are the same.
EXAMPLES:
Here is an example where we have to use assume::
sage: a,b = var('a,b')
sage: integrate(1/(x^3 *(a+b*x)^(1/3)), x)
Traceback (most recent call last):
...
ValueError: Computation failed since Maxima requested additional
constraints; using the 'assume' command before integral evaluation
*may* help (example of legal syntax is 'assume(a>0)', see `assume?`
for more details)
Is a positive or negative?
So we just assume that `a>0` and the integral works::
sage: assume(a>0)
sage: integrate(1/(x^3 *(a+b*x)^(1/3)), x)
2/9*sqrt(3)*b^2*arctan(1/3*(2*(b*x + a)^(1/3) + a^(1/3))*sqrt(3)/a^(1/3))/a^(7/3) + 2/9*b^2*log((b*x + a)^(1/3) - a^(1/3))/a^(7/3) - 1/9*b^2*log((b*x + a)^(2/3) + (b*x + a)^(1/3)*a^(1/3) + a^(2/3))/a^(7/3) + 1/6*(4*(b*x + a)^(5/3)*b^2 - 7*(b*x + a)^(2/3)*a*b^2)/((b*x + a)^2*a^2 - 2*(b*x + a)*a^3 + a^4)
TESTS:
The following integral was broken prior to Maxima 5.15.0 -
see #3013::
sage: integrate(sin(x)*cos(10*x)*log(x), x)
1/198*(11*cos(9*x) - 9*cos(11*x))*log(x) + 1/44*Ei(-11*I*x) + 1/44*Ei(11*I*x) - 1/36*Ei(-9*I*x) - 1/36*Ei(9*I*x)
It is no longer possible to use certain functions without an
explicit variable. Instead, evaluate the function at a variable,
and then take the integral::
sage: integrate(sin)
Traceback (most recent call last):
...
TypeError
sage: integrate(sin(x), x)
-cos(x)
sage: integrate(sin(x), x, 0, 1)
-cos(1) + 1
Check if #780 is fixed::
sage: _ = var('x,y')
sage: f = log(x^2+y^2)
sage: res = integral(f,x,0.0001414, 1.); res
Traceback (most recent call last):
...
ValueError: Computation failed since Maxima requested additional constraints; using the 'assume' command before integral evaluation *may* help (example of legal syntax is 'assume(50015104*y^2-50015103>0)', see `assume?` for more details)
Is 50015104*y^2-50015103 positive, negative, or zero?
sage: assume(y>1)
sage: res = integral(f,x,0.0001414, 1.); res
2*y*arctan(1/y) - 2*y*arctan(0.0001414/y) - 0.0001414*log(y^2 + 1.999396e-08) + log(y^2 + 1.0) - 1.9997172
sage: nres = numerical_integral(f.subs(y=2), 0.0001414, 1.); nres
(1.4638323264144..., 1.6251803529759...e-14)
sage: res.subs(y=2).n()
1.46383232641443
sage: nres = numerical_integral(f.subs(y=.5), 0.0001414, 1.); nres
(-0.669511708872807, 7.768678110854711e-15)
sage: res.subs(y=.5).n()
-0.669511708872807
Check if #6816 is fixed::
sage: var('t,theta')
(t, theta)
sage: integrate(t*cos(-theta*t),t,0,pi)
(pi*theta*sin(pi*theta) + cos(pi*theta))/theta^2 - 1/theta^2
sage: integrate(t*cos(-theta*t),(t,0,pi))
(pi*theta*sin(pi*theta) + cos(pi*theta))/theta^2 - 1/theta^2
sage: integrate(t*cos(-theta*t),t)
(t*theta*sin(t*theta) + cos(t*theta))/theta^2
sage: integrate(x^2,(x)) # this worked before
1/3*x^3
sage: integrate(x^2,(x,)) # this didn't
1/3*x^3
sage: integrate(x^2,(x,1,2))
7/3
sage: integrate(x^2,(x,1,2,3))
Traceback (most recent call last):
...
ValueError: invalid input (x, 1, 2, 3) - please use variable, with or without two endpoints
Note that this used to be the test, but it is
actually divergent (though Maxima as yet does
not say so)::
sage: integrate(t*cos(-theta*t),(t,-oo,oo))
integrate(t*cos(t*theta), t, -Infinity, +Infinity)
Check if #6189 is fixed (which, by the way, also
demonstrates it's not always good to expand)::
sage: n = N; n
<function numerical_approx at ...>
sage: F(x) = 1/sqrt(2*pi*1^2)*exp(-1/(2*1^2)*(x-0)^2)
sage: G(x) = 1/sqrt(2*pi*n(1)^2)*exp(-1/(2*n(1)^2)*(x-n(0))^2)
sage: integrate( (F(x)-F(x))^2, x, -infinity, infinity).n()
0.000000000000000
sage: integrate( ((F(x)-G(x))^2).expand(), x, -infinity, infinity).n()
-6.26376265908397e-17
sage: integrate( (F(x)-G(x))^2, x, -infinity, infinity).n()
-6.26376265908397e-17
This was broken before Maxima 5.20::
sage: exp(-x*i).integral(x,0,1)
I*e^(-I) - I
Test deprecation warning when variable is not specified::
sage: x.integral()
doctest:...: DeprecationWarning: Variable of integration should be specified explicitly.
1/2*x^2
Test that #8729 is fixed::
sage: t = var('t')
sage: a = sqrt((sin(t))^2 + (cos(t))^2)
sage: integrate(a, t, 0, 2*pi)
2*pi
sage: a.simplify_full().simplify_trig()
1
Maxima uses Cauchy Principal Value calculations to
integrate certain convergent integrals. Here we test
that this does not raise an error message (see #11987)::
sage: integrate(sin(x)*sin(x/3)/x^2, x, 0, oo)
1/6*pi
Maxima returned a negative value for this integral prior to
maxima-5.24 (trac #10923). Ideally we would get an answer in terms
of the gamma function; however, we get something equivalent::
sage: actual_result = integral(e^(-1/x^2), x, 0, 1)
sage: actual_result.full_simplify()
((e*erf(1) - e)*sqrt(pi) + 1)*e^(-1)
sage: ideal_result = 1/2*gamma(-1/2, 1)
sage: error = actual_result - ideal_result
sage: error.numerical_approx() # abs tol 1e-10
0
We won't get an evaluated answer here, which is better than
the previous (wrong) answer of zero. See :trac:`10914`::
sage: f = abs(sin(x))
sage: integrate(f, x, 0, 2*pi)
integrate(abs(sin(x)), x, 0, 2*pi)
Another incorrect integral fixed upstream in Maxima, from
:trac:`11233`::
sage: a,t = var('a,t')
sage: assume(a>0)
sage: assume(x>0)
sage: f = log(1 + a/(x * t)^2)
sage: F = integrate(f, t, 1, Infinity)
sage: F(x=1, a=7).numerical_approx() # abs tol 1e-10
4.32025625668262
"""
if isinstance(v, (list, tuple)) and a is None and b is None:
if len(v)==1: # bare variable in a tuple
v=v[0]
elif len(v)==3: # variable and endpoints
v,a,b=v
elif len(v)==2: # endpoints only
a,b=v
v=None
elif len(v)==0:
v=None
else:
raise ValueError, "invalid input %s - please use variable, with or without two endpoints"%repr(v)
elif b is None and a is not None:
# two arguments, must be endpoints
a, b = v, a
v = None
if v is None:
from sage.misc.misc import deprecation
deprecation("Variable of integration should be specified explicitly.")
v = expression.default_variable()
if isinstance(expression, Function):
# a bare function like sin
expression = expression(v)
if (a is None) ^ (b is None):
raise TypeError, 'only one endpoint given'
# Check algorithm
if algorithm is not None:
integrator = available_integrators.get(algorithm)
if not integrator:
raise ValueError, "Unknown algorithm: %s" % algorithm
return integrator(expression, v, a, b)
if a is None:
return indefinite_integral(expression, v)
else:
return definite_integral(expression, v, a, b)
# http://www.gnu.org/licenses/
#*****************************************************************************
from sage.categories.all import GroupAlgebras
from sage.structure.parent_gens import ParentWithGens
from sage.algebras.algebra import Algebra
from sage.algebras.algebra_element import AlgebraElement
from sage.rings.all import IntegerRing
from sage.groups.group import Group
from sage.structure.formal_sum import FormalSums, FormalSum
from sage.sets.set import Set
from sage.misc.misc import deprecation
deprecation("The module group_algebra is deprecated and will be removed in a future version of Sage. Use group_algebra_new instead.")
class GroupAlgebra(Algebra):
def __init__(self, group, base_ring = IntegerRing()):
r""" Create the given group algebra.
INPUT:
-- (Group) group: a generic group.
-- (Ring) base_ring: a commutative ring.
OUTPUT:
-- a GroupAlgebra instance.
EXAMPLES::
sage: from sage.algebras.group_algebra import GroupAlgebra
def setup_for_eval_on_grid(funcs, ranges, plot_points=None, return_vars=False):
"""
Calculate the necessary parameters to construct a list of points,
and make the functions fast_callable.
INPUT:
- ``funcs`` - a function, or a list, tuple, or vector of functions
- ``ranges`` - a list of ranges. A range can be a 2-tuple of
numbers specifying the minimum and maximum, or a 3-tuple giving
the variable explicitly.
- ``plot_points`` - a tuple of integers specifying the number of
plot points for each range. If a single number is specified, it
will be the value for all ranges. This defaults to 2.
- ``return_vars`` - (default False) If True, return the variables,
in order.
OUTPUT:
- ``fast_funcs`` - if only one function passed, then a fast
callable function. If funcs is a list or tuple, then a tuple
of fast callable functions is returned.
- ``range_specs`` - a list of range_specs: for each range, a
tuple is returned of the form (range_min, range_max,
range_step) such that ``srange(range_min, range_max,
range_step, include_endpoint=True)`` gives the correct points
for evaluation.
EXAMPLES::
sage: x,y,z=var('x,y,z')
sage: f(x,y)=x+y-z
sage: g(x,y)=x+y
sage: h(y)=-y
sage: sage.plot.misc.setup_for_eval_on_grid(f, [(0, 2),(1,3),(-4,1)], plot_points=5)
(<sage.ext...>, [(0.0, 2.0, 0.5), (1.0, 3.0, 0.5), (-4.0, 1.0, 1.25)])
sage: sage.plot.misc.setup_for_eval_on_grid([g,h], [(0, 2),(-1,1)], plot_points=5)
((<sage.ext...>, <sage.ext...>), [(0.0, 2.0, 0.5), (-1.0, 1.0, 0.5)])
sage: sage.plot.misc.setup_for_eval_on_grid([sin,cos], [(-1,1)], plot_points=9)
((<sage.ext...>, <sage.ext...>), [(-1.0, 1.0, 0.25)])
sage: sage.plot.misc.setup_for_eval_on_grid([lambda x: x^2,cos], [(-1,1)], plot_points=9)
((<function <lambda> ...>, <sage.ext...>), [(-1.0, 1.0, 0.25)])
sage: sage.plot.misc.setup_for_eval_on_grid([x+y], [(x,-1,1),(y,-2,2)])
((<sage.ext...>,), [(-1.0, 1.0, 2.0), (-2.0, 2.0, 4.0)])
sage: sage.plot.misc.setup_for_eval_on_grid(x+y, [(x,-1,1),(y,-1,1)], plot_points=[4,9])
(<sage.ext...>, [(-1.0, 1.0, 0.6666666666666666), (-1.0, 1.0, 0.25)])
sage: sage.plot.misc.setup_for_eval_on_grid(x+y, [(x,-1,1),(y,-1,1)], plot_points=[4,9,10])
Traceback (most recent call last):
...
ValueError: plot_points must be either an integer or a list of integers, one for each range
sage: sage.plot.misc.setup_for_eval_on_grid(x+y, [(1,-1),(y,-1,1)], plot_points=[4,9,10])
Traceback (most recent call last):
...
ValueError: Some variable ranges specify variables while others do not
sage: sage.plot.misc.setup_for_eval_on_grid(x+y, [(1,-1),(-1,1)], plot_points=5)
doctest:...: DeprecationWarning: Unnamed ranges for more than one variable is deprecated and will be removed from a future release of Sage; you can used named ranges instead, like (x,0,2)
(<sage.ext...>, [(1.0, -1.0, 0.5), (-1.0, 1.0, 0.5)])
sage: sage.plot.misc.setup_for_eval_on_grid(x+y, [(y,1,-1),(x,-1,1)], plot_points=5)
(<sage.ext...>, [(1.0, -1.0, 0.5), (-1.0, 1.0, 0.5)])
sage: sage.plot.misc.setup_for_eval_on_grid(x+y, [(x,1,-1),(x,-1,1)], plot_points=5)
Traceback (most recent call last):
...
ValueError: range variables should be distinct, but there are duplicates
sage: sage.plot.misc.setup_for_eval_on_grid(x+y, [(x,1,1),(y,-1,1)])
Traceback (most recent call last):
...
ValueError: plot start point and end point must be different
sage: sage.plot.misc.setup_for_eval_on_grid(x+y, [(x,1,-1),(y,-1,1)], return_vars=True)
(<sage.ext...>, [(1.0, -1.0, 2.0), (-1.0, 1.0, 2.0)], [x, y])
sage: sage.plot.misc.setup_for_eval_on_grid(x+y, [(y,1,-1),(x,-1,1)], return_vars=True)
(<sage.ext...>, [(1.0, -1.0, 2.0), (-1.0, 1.0, 2.0)], [y, x])
"""
if max(map(len, ranges)) != min(map(len, ranges)):
raise ValueError, "Some variable ranges specify variables while others do not"
if len(ranges[0])==3:
vars = [r[0] for r in ranges]
ranges = [r[1:] for r in ranges]
if len(set(vars))<len(vars):
raise ValueError, "range variables should be distinct, but there are duplicates"
else:
vars, free_vars = unify_arguments(funcs)
if len(free_vars)>1:
from sage.misc.misc import deprecation
deprecation("Unnamed ranges for more than one variable is deprecated and will be removed from a future release of Sage; you can used named ranges instead, like (x,0,2)")
# pad the variables if we don't have enough
nargs = len(ranges)
if len(vars)<nargs:
vars += ('_',)*(nargs-len(vars))
ranges = [[float(z) for z in r] for r in ranges]
if plot_points is None:
plot_points=2
if not isinstance(plot_points, (list, tuple)):
plot_points = [plot_points]*len(ranges)
elif len(plot_points)!=nargs:
raise ValueError, "plot_points must be either an integer or a list of integers, one for each range"
plot_points = [int(p) if p>=2 else 2 for p in plot_points]
range_steps = [abs(range[1] - range[0])/(p-1) for range, p in zip(ranges, plot_points)]
if min(range_steps) == float(0):
raise ValueError, "plot start point and end point must be different"
options={}
if nargs==1:
options['expect_one_var']=True
if is_Vector(funcs):
funcs = list(funcs)
#TODO: raise an error if there is a function/method in funcs that takes more values than we have ranges
if return_vars:
return fast_float(funcs, *vars,**options), [tuple(range+[range_step]) for range,range_step in zip(ranges, range_steps)], vars
else:
return fast_float(funcs, *vars,**options), [tuple(range+[range_step]) for range,range_step in zip(ranges, range_steps)]
