Functional notation#
These are functions so that you can write foo(x) instead of x.foo() in certain common cases.
AUTHORS:
William Stein: Initial version
David Joyner (2005-12-20): More Examples
- sage.misc.functional.N(x, prec=None, digits=None, algorithm=None)#
Return a numerical approximation of
self
withprec
bits (or decimaldigits
) of precision.No guarantee is made about the accuracy of the result.
Note
Lower case
n()
is an alias fornumerical_approx()
and may be used as a method.INPUT:
prec
– precision in bitsdigits
– precision in decimal digits (only used ifprec
is not given)algorithm
– which algorithm to use to compute this approximation (the accepted algorithms depend on the object)
If neither
prec
nordigits
is given, the default precision is 53 bits (roughly 16 digits).EXAMPLES:
sage: numerical_approx(pi, 10) 3.1 sage: numerical_approx(pi, digits=10) 3.141592654 sage: numerical_approx(pi^2 + e, digits=20) 12.587886229548403854 sage: n(pi^2 + e) 12.5878862295484 sage: N(pi^2 + e) 12.5878862295484 sage: n(pi^2 + e, digits=50) 12.587886229548403854194778471228813633070946500941 sage: a = CC(-5).n(prec=40) sage: b = ComplexField(40)(-5) sage: a == b True sage: parent(a) is parent(b) True sage: numerical_approx(9) 9.00000000000000
You can also usually use method notation:
sage: (pi^2 + e).n() 12.5878862295484 sage: (pi^2 + e).numerical_approx() 12.5878862295484
Vectors and matrices may also have their entries approximated:
sage: v = vector(RDF, [1,2,3]) sage: v.n() (1.00000000000000, 2.00000000000000, 3.00000000000000) sage: v = vector(CDF, [1,2,3]) sage: v.n() (1.00000000000000, 2.00000000000000, 3.00000000000000) sage: _.parent() Vector space of dimension 3 over Complex Field with 53 bits of precision sage: v.n(prec=20) (1.0000, 2.0000, 3.0000) sage: u = vector(QQ, [1/2, 1/3, 1/4]) sage: n(u, prec=15) (0.5000, 0.3333, 0.2500) sage: n(u, digits=5) (0.50000, 0.33333, 0.25000) sage: v = vector(QQ, [1/2, 0, 0, 1/3, 0, 0, 0, 1/4], sparse=True) sage: u = v.numerical_approx(digits=4) sage: u.is_sparse() True sage: u (0.5000, 0.0000, 0.0000, 0.3333, 0.0000, 0.0000, 0.0000, 0.2500) sage: A = matrix(QQ, 2, 3, range(6)) sage: A.n() [0.000000000000000 1.00000000000000 2.00000000000000] [ 3.00000000000000 4.00000000000000 5.00000000000000] sage: B = matrix(Integers(12), 3, 8, srange(24)) sage: N(B, digits=2) [0.00 1.0 2.0 3.0 4.0 5.0 6.0 7.0] [ 8.0 9.0 10. 11. 0.00 1.0 2.0 3.0] [ 4.0 5.0 6.0 7.0 8.0 9.0 10. 11.]
Internally, numerical approximations of real numbers are stored in base-2. Therefore, numbers which look the same in their decimal expansion might be different:
sage: x=N(pi, digits=3); x 3.14 sage: y=N(3.14, digits=3); y 3.14 sage: x==y False sage: x.str(base=2) '11.001001000100' sage: y.str(base=2) '11.001000111101'
Increasing the precision of a floating point number is not allowed:
sage: CC(-5).n(prec=100) Traceback (most recent call last): ... TypeError: cannot approximate to a precision of 100 bits, use at most 53 bits sage: n(1.3r, digits=20) Traceback (most recent call last): ... TypeError: cannot approximate to a precision of 70 bits, use at most 53 bits sage: RealField(24).pi().n() Traceback (most recent call last): ... TypeError: cannot approximate to a precision of 53 bits, use at most 24 bits
As an exceptional case,
digits=1
usually leads to 2 digits (one significant) in the decimal output (see trac ticket #11647):sage: N(pi, digits=1) 3.2 sage: N(pi, digits=2) 3.1 sage: N(100*pi, digits=1) 320. sage: N(100*pi, digits=2) 310.
In the following example,
pi
and3
are both approximated to two bits of precision and then subtracted, which kills two bits of precision:sage: N(pi, prec=2) 3.0 sage: N(3, prec=2) 3.0 sage: N(pi - 3, prec=2) 0.00
- sage.misc.functional.additive_order(x)#
Return the additive order of
x
.EXAMPLES:
sage: additive_order(5) +Infinity sage: additive_order(Mod(5,11)) 11 sage: additive_order(Mod(4,12)) 3
- sage.misc.functional.base_field(x)#
Return the base field over which
x
is defined.EXAMPLES:
sage: R = PolynomialRing(GF(7), 'x') sage: base_ring(R) Finite Field of size 7 sage: base_field(R) Finite Field of size 7
This catches base rings which are fields as well, but does not implement a
base_field
method for objects which do not have one:sage: R.base_field() Traceback (most recent call last): ... AttributeError: 'PolynomialRing_dense_mod_p_with_category' object has no attribute 'base_field'
- sage.misc.functional.base_ring(x)#
Return the base ring over which
x
is defined.EXAMPLES:
sage: R = PolynomialRing(GF(7), 'x') sage: base_ring(R) Finite Field of size 7
- sage.misc.functional.basis(x)#
Return the fixed basis of
x
.EXAMPLES:
sage: V = VectorSpace(QQ,3) sage: S = V.subspace([[1,2,0],[2,2,-1]]) sage: basis(S) [ (1, 0, -1), (0, 1, 1/2) ]
- sage.misc.functional.category(x)#
Return the category of
x
.EXAMPLES:
sage: V = VectorSpace(QQ,3) sage: category(V) Category of finite dimensional vector spaces with basis over (number fields and quotient fields and metric spaces)
- sage.misc.functional.characteristic_polynomial(x, var='x')#
Return the characteristic polynomial of
x
in the given variable.EXAMPLES:
sage: M = MatrixSpace(QQ,3,3) sage: A = M([1,2,3,4,5,6,7,8,9]) sage: charpoly(A) x^3 - 15*x^2 - 18*x sage: charpoly(A, 't') t^3 - 15*t^2 - 18*t sage: k.<alpha> = GF(7^10); k Finite Field in alpha of size 7^10 sage: alpha.charpoly('T') T^10 + T^6 + T^5 + 4*T^4 + T^3 + 2*T^2 + 3*T + 3 sage: characteristic_polynomial(alpha, 'T') T^10 + T^6 + T^5 + 4*T^4 + T^3 + 2*T^2 + 3*T + 3
Ensure the variable name of the polynomial does not conflict with variables used within the matrix, and that non-integral powers of variables do not confuse the computation (trac ticket #14403):
sage: y = var('y') sage: a = matrix([[x,0,0,0],[0,1,0,0],[0,0,1,0],[0,0,0,1]]) sage: characteristic_polynomial(a).list() [x, -3*x - 1, 3*x + 3, -x - 3, 1] sage: b = matrix([[y^(1/2),0,0,0],[0,1,0,0],[0,0,1,0],[0,0,0,1]]) sage: charpoly(b).list() [sqrt(y), -3*sqrt(y) - 1, 3*sqrt(y) + 3, -sqrt(y) - 3, 1]
- sage.misc.functional.charpoly(x, var='x')#
Return the characteristic polynomial of
x
in the given variable.EXAMPLES:
sage: M = MatrixSpace(QQ,3,3) sage: A = M([1,2,3,4,5,6,7,8,9]) sage: charpoly(A) x^3 - 15*x^2 - 18*x sage: charpoly(A, 't') t^3 - 15*t^2 - 18*t sage: k.<alpha> = GF(7^10); k Finite Field in alpha of size 7^10 sage: alpha.charpoly('T') T^10 + T^6 + T^5 + 4*T^4 + T^3 + 2*T^2 + 3*T + 3 sage: characteristic_polynomial(alpha, 'T') T^10 + T^6 + T^5 + 4*T^4 + T^3 + 2*T^2 + 3*T + 3
Ensure the variable name of the polynomial does not conflict with variables used within the matrix, and that non-integral powers of variables do not confuse the computation (trac ticket #14403):
sage: y = var('y') sage: a = matrix([[x,0,0,0],[0,1,0,0],[0,0,1,0],[0,0,0,1]]) sage: characteristic_polynomial(a).list() [x, -3*x - 1, 3*x + 3, -x - 3, 1] sage: b = matrix([[y^(1/2),0,0,0],[0,1,0,0],[0,0,1,0],[0,0,0,1]]) sage: charpoly(b).list() [sqrt(y), -3*sqrt(y) - 1, 3*sqrt(y) + 3, -sqrt(y) - 3, 1]
- sage.misc.functional.coerce(P, x)#
Coerce
x
to typeP
if possible.EXAMPLES:
sage: type(5) <class 'sage.rings.integer.Integer'> sage: type(coerce(QQ,5)) <class 'sage.rings.rational.Rational'>
- sage.misc.functional.cyclotomic_polynomial(n, var='x')#
Return the \(n^{th}\) cyclotomic polynomial.
EXAMPLES:
sage: cyclotomic_polynomial(3) x^2 + x + 1 sage: cyclotomic_polynomial(4) x^2 + 1 sage: cyclotomic_polynomial(9) x^6 + x^3 + 1 sage: cyclotomic_polynomial(10) x^4 - x^3 + x^2 - x + 1 sage: cyclotomic_polynomial(11) x^10 + x^9 + x^8 + x^7 + x^6 + x^5 + x^4 + x^3 + x^2 + x + 1
- sage.misc.functional.decomposition(x)#
Return the decomposition of
x
.EXAMPLES:
sage: M = matrix([[2, 3], [3, 4]]) sage: M.decomposition() [ (Ambient free module of rank 2 over the principal ideal domain Integer Ring, True) ] sage: G.<a,b> = DirichletGroup(20) sage: c = a*b sage: d = c.decomposition(); d [Dirichlet character modulo 4 of conductor 4 mapping 3 |--> -1, Dirichlet character modulo 5 of conductor 5 mapping 2 |--> zeta4] sage: d[0].parent() Group of Dirichlet characters modulo 4 with values in Cyclotomic Field of order 4 and degree 2
- sage.misc.functional.denominator(x)#
Return the denominator of
x
.EXAMPLES:
sage: denominator(17/11111) 11111 sage: R.<x> = PolynomialRing(QQ) sage: F = FractionField(R) sage: r = (x+1)/(x-1) sage: denominator(r) x - 1
- sage.misc.functional.det(x)#
Return the determinant of
x
.EXAMPLES:
sage: M = MatrixSpace(QQ,3,3) sage: A = M([1,2,3,4,5,6,7,8,9]) sage: det(A) 0
- sage.misc.functional.dim(x)#
Return the dimension of
x
.EXAMPLES:
sage: V = VectorSpace(QQ,3) sage: S = V.subspace([[1,2,0],[2,2,-1]]) sage: dimension(S) 2
- sage.misc.functional.dimension(x)#
Return the dimension of
x
.EXAMPLES:
sage: V = VectorSpace(QQ,3) sage: S = V.subspace([[1,2,0],[2,2,-1]]) sage: dimension(S) 2
- sage.misc.functional.disc(x)#
Return the discriminant of
x
.EXAMPLES:
sage: R.<x> = PolynomialRing(QQ) sage: S = R.quotient(x^29 - 17*x - 1, 'alpha') sage: K = S.number_field() sage: discriminant(K) -15975100446626038280218213241591829458737190477345113376757479850566957249523
- sage.misc.functional.discriminant(x)#
Return the discriminant of
x
.EXAMPLES:
sage: R.<x> = PolynomialRing(QQ) sage: S = R.quotient(x^29 - 17*x - 1, 'alpha') sage: K = S.number_field() sage: discriminant(K) -15975100446626038280218213241591829458737190477345113376757479850566957249523
- sage.misc.functional.eta(x)#
Return the value of the \(\eta\) function at
x
, which must be in the upper half plane.The \(\eta\) function is
\[\eta(z) = e^{\pi i z / 12} \prod_{n=1}^{\infty}(1-e^{2\pi inz})\]EXAMPLES:
sage: eta(1+I) 0.7420487758365647 + 0.1988313702299107*I
- sage.misc.functional.fcp(x, var='x')#
Return the factorization of the characteristic polynomial of
x
.EXAMPLES:
sage: M = MatrixSpace(QQ,3,3) sage: A = M([1,2,3,4,5,6,7,8,9]) sage: fcp(A, 'x') x * (x^2 - 15*x - 18)
- sage.misc.functional.gen(x)#
Return the generator of
x
.EXAMPLES:
sage: R.<x> = QQ[]; R Univariate Polynomial Ring in x over Rational Field sage: gen(R) x sage: gen(GF(7)) 1 sage: A = AbelianGroup(1, [23]) sage: gen(A) f
- sage.misc.functional.gens(x)#
Return the generators of
x
.EXAMPLES:
sage: R.<x,y> = SR[] sage: R Multivariate Polynomial Ring in x, y over Symbolic Ring sage: gens(R) (x, y) sage: A = AbelianGroup(5, [5,5,7,8,9]) sage: gens(A) (f0, f1, f2, f3, f4)
- sage.misc.functional.hecke_operator(x, n)#
Return the \(n\)-th Hecke operator \(T_n\) acting on
x
.EXAMPLES:
sage: M = ModularSymbols(1,12) sage: hecke_operator(M,5) Hecke operator T_5 on Modular Symbols space of dimension 3 for Gamma_0(1) of weight 12 with sign 0 over Rational Field
- sage.misc.functional.image(x)#
Return the image of
x
.EXAMPLES:
sage: M = MatrixSpace(QQ,3,3) sage: A = M([1,2,3,4,5,6,7,8,9]) sage: image(A) Vector space of degree 3 and dimension 2 over Rational Field Basis matrix: [ 1 0 -1] [ 0 1 2]
- sage.misc.functional.integral(x, *args, **kwds)#
Return an indefinite or definite integral of an object
x
.First call
x.integral()
and if that fails make an object and integrate it using Maxima, maple, etc, as specified by algorithm.For symbolic expression calls
sage.calculus.calculus.integral()
- see this function for available options.EXAMPLES:
sage: f = cyclotomic_polynomial(10) sage: integral(f) 1/5*x^5 - 1/4*x^4 + 1/3*x^3 - 1/2*x^2 + x
sage: integral(sin(x),x) -cos(x)
sage: y = var('y') sage: integral(sin(x),y) y*sin(x)
sage: integral(sin(x), x, 0, pi/2) 1 sage: sin(x).integral(x, 0,pi/2) 1 sage: integral(exp(-x), (x, 1, oo)) e^(-1)
Numerical approximation:
sage: h = integral(tan(x)/x, (x, 1, pi/3)) ... sage: h integrate(tan(x)/x, x, 1, 1/3*pi) sage: h.n() 0.07571599101...
Specific algorithm can be used for integration:
sage: integral(sin(x)^2, x, algorithm='maxima') 1/2*x - 1/4*sin(2*x) sage: integral(sin(x)^2, x, algorithm='sympy') -1/2*cos(x)*sin(x) + 1/2*x
- sage.misc.functional.integral_closure(x)#
Return the integral closure of
x
.EXAMPLES:
sage: integral_closure(QQ) Rational Field sage: K.<a> = QuadraticField(5) sage: O2 = K.order(2*a); O2 Order in Number Field in a with defining polynomial x^2 - 5 with a = 2.236067977499790? sage: integral_closure(O2) Maximal Order in Number Field in a with defining polynomial x^2 - 5 with a = 2.236067977499790?
- sage.misc.functional.integrate(x, *args, **kwds)#
Return an indefinite or definite integral of an object
x
.First call
x.integral()
and if that fails make an object and integrate it using Maxima, maple, etc, as specified by algorithm.For symbolic expression calls
sage.calculus.calculus.integral()
- see this function for available options.EXAMPLES:
sage: f = cyclotomic_polynomial(10) sage: integral(f) 1/5*x^5 - 1/4*x^4 + 1/3*x^3 - 1/2*x^2 + x
sage: integral(sin(x),x) -cos(x)
sage: y = var('y') sage: integral(sin(x),y) y*sin(x)
sage: integral(sin(x), x, 0, pi/2) 1 sage: sin(x).integral(x, 0,pi/2) 1 sage: integral(exp(-x), (x, 1, oo)) e^(-1)
Numerical approximation:
sage: h = integral(tan(x)/x, (x, 1, pi/3)) ... sage: h integrate(tan(x)/x, x, 1, 1/3*pi) sage: h.n() 0.07571599101...
Specific algorithm can be used for integration:
sage: integral(sin(x)^2, x, algorithm='maxima') 1/2*x - 1/4*sin(2*x) sage: integral(sin(x)^2, x, algorithm='sympy') -1/2*cos(x)*sin(x) + 1/2*x
- sage.misc.functional.interval(a, b)#
Integers between \(a\) and \(b\) inclusive (\(a\) and \(b\) integers).
EXAMPLES:
sage: I = interval(1,3) sage: 2 in I True sage: 1 in I True sage: 4 in I False
- sage.misc.functional.is_commutative(x)#
Return whether or not
x
is commutative.EXAMPLES:
sage: R = PolynomialRing(QQ, 'x') sage: is_commutative(R) doctest:...DeprecationWarning: use X.is_commutative() or X in Rings().Commutative() See https://trac.sagemath.org/32347 for details. True
- sage.misc.functional.is_even(x)#
Return whether or not an integer
x
is even, e.g., divisible by 2.EXAMPLES:
sage: is_even(-1) False sage: is_even(4) True sage: is_even(-2) True
- sage.misc.functional.is_field(x, proof=True)#
Return whether or not
x
is a field.Alternatively, one can use
x in Fields()
.EXAMPLES:
sage: R = PolynomialRing(QQ, 'x') sage: F = FractionField(R) sage: is_field(F) doctest:...DeprecationWarning: use X.is_field() or X in Fields() See https://trac.sagemath.org/32347 for details. True
- sage.misc.functional.is_integrally_closed(x)#
Return whether
x
is integrally closed.EXAMPLES:
sage: is_integrally_closed(QQ) doctest:...DeprecationWarning: use X.is_integrally_closed() See https://trac.sagemath.org/32347 for details. True sage: K.<a> = NumberField(x^2 + 189*x + 394) sage: R = K.order(2*a) sage: is_integrally_closed(R) False
- sage.misc.functional.is_odd(x)#
Return whether or not
x
is odd.This is by definition the complement of
is_even()
.EXAMPLES:
sage: is_odd(-2) False sage: is_odd(-3) True sage: is_odd(0) False sage: is_odd(1) True
- sage.misc.functional.isqrt(x)#
Return an integer square root, i.e., the floor of a square root.
EXAMPLES:
sage: isqrt(10) 3 sage: isqrt(10r) 3
- sage.misc.functional.kernel(x)#
Return the left kernel of
x
.EXAMPLES:
sage: M = MatrixSpace(QQ,3,2) sage: A = M([1,2,3,4,5,6]) sage: kernel(A) Vector space of degree 3 and dimension 1 over Rational Field Basis matrix: [ 1 -2 1] sage: kernel(A.transpose()) Vector space of degree 2 and dimension 0 over Rational Field Basis matrix: []
Here are two corner cases:
sage: M = MatrixSpace(QQ,0,3) sage: A = M([]) sage: kernel(A) Vector space of degree 0 and dimension 0 over Rational Field Basis matrix: [] sage: kernel(A.transpose()).basis() [ (1, 0, 0), (0, 1, 0), (0, 0, 1) ]
- sage.misc.functional.krull_dimension(x)#
Return the Krull dimension of
x
.EXAMPLES:
sage: krull_dimension(QQ) 0 sage: krull_dimension(ZZ) 1 sage: krull_dimension(ZZ[sqrt(5)]) 1 sage: U.<x,y,z> = PolynomialRing(ZZ,3); U Multivariate Polynomial Ring in x, y, z over Integer Ring sage: U.krull_dimension() 4
- sage.misc.functional.lift(x)#
Lift an object of a quotient ring \(R/I\) to \(R\).
EXAMPLES:
We lift an integer modulo \(3\):
sage: Mod(2,3).lift() 2
We lift an element of a quotient polynomial ring:
sage: R.<x> = QQ['x'] sage: S.<xmod> = R.quo(x^2 + 1) sage: lift(xmod-7) x - 7
- sage.misc.functional.log(*args, **kwds)#
Return the logarithm of the first argument to the base of the second argument which if missing defaults to
e
.It calls the
log
method of the first argument when computing the logarithm, thus allowing the use of logarithm on any object containing alog
method. In other words,log
works on more than just real numbers.Note
In Magma, the order of arguments is reversed from in Sage, i.e., the base is given first. We use the opposite ordering, so the base can be viewed as an optional second argument.
EXAMPLES:
sage: log(e^2) 2
To change the base of the logarithm, add a second parameter:
sage: log(1000,10) 3
The synonym
ln
can only take one argument:sage: ln(RDF(10)) 2.302585092994046 sage: ln(2.718) 0.999896315728952 sage: ln(2.0) 0.693147180559945 sage: ln(float(-1)) 3.141592653589793j sage: ln(complex(-1)) 3.141592653589793j
You can use
RDF
,RealField
orn
to get a numerical real approximation:sage: log(1024, 2) 10 sage: RDF(log(1024, 2)) 10.0 sage: log(10, 4) 1/2*log(10)/log(2) sage: RDF(log(10, 4)) 1.6609640474436813 sage: log(10, 2) log(10)/log(2) sage: n(log(10, 2)) 3.32192809488736 sage: log(10, e) log(10) sage: n(log(10, e)) 2.30258509299405
The log function works for negative numbers, complex numbers, and symbolic numbers too, picking the branch with angle between \(-\pi\) and \(\pi\):
sage: log(-1+0*I) I*pi sage: log(CC(-1)) 3.14159265358979*I sage: log(-1.0) 3.14159265358979*I
Small integer powers are factored out immediately:
sage: log(4) 2*log(2) sage: log(1000000000) 9*log(10) sage: log(8) - 3*log(2) 0 sage: bool(log(8) == 3*log(2)) True
The
hold
parameter can be used to prevent automatic evaluation:sage: log(-1,hold=True) log(-1) sage: log(-1) I*pi sage: I.log(hold=True) log(I) sage: I.log(hold=True).simplify() 1/2*I*pi
For input zero, the following behavior occurs:
sage: log(0) -Infinity sage: log(CC(0)) -infinity sage: log(0.0) -infinity
The log function also works in finite fields as long as the argument lies in the multiplicative group generated by the base:
sage: F = GF(13); g = F.multiplicative_generator(); g 2 sage: a = F(8) sage: log(a,g); g^log(a,g) 3 8 sage: log(a,3) Traceback (most recent call last): ... ValueError: no logarithm of 8 found to base 3 modulo 13 sage: log(F(9), 3) 2
The log function also works for p-adics (see documentation for p-adics for more information):
sage: R = Zp(5); R 5-adic Ring with capped relative precision 20 sage: a = R(16); a 1 + 3*5 + O(5^20) sage: log(a) 3*5 + 3*5^2 + 3*5^4 + 3*5^5 + 3*5^6 + 4*5^7 + 2*5^8 + 5^9 + 5^11 + 2*5^12 + 5^13 + 3*5^15 + 2*5^16 + 4*5^17 + 3*5^18 + 3*5^19 + O(5^20)
- sage.misc.functional.minimal_polynomial(x, var='x')#
Return the minimal polynomial of
x
.EXAMPLES:
sage: a = matrix(ZZ, 2, [1..4]) sage: minpoly(a) x^2 - 5*x - 2 sage: minpoly(a,'t') t^2 - 5*t - 2 sage: minimal_polynomial(a) x^2 - 5*x - 2 sage: minimal_polynomial(a,'theta') theta^2 - 5*theta - 2
- sage.misc.functional.minpoly(x, var='x')#
Return the minimal polynomial of
x
.EXAMPLES:
sage: a = matrix(ZZ, 2, [1..4]) sage: minpoly(a) x^2 - 5*x - 2 sage: minpoly(a,'t') t^2 - 5*t - 2 sage: minimal_polynomial(a) x^2 - 5*x - 2 sage: minimal_polynomial(a,'theta') theta^2 - 5*theta - 2
- sage.misc.functional.multiplicative_order(x)#
Return the multiplicative order of
x
, ifx
is a unit, or raiseArithmeticError
otherwise.EXAMPLES:
sage: a = mod(5,11) sage: multiplicative_order(a) 5 sage: multiplicative_order(mod(2,11)) 10 sage: multiplicative_order(mod(2,12)) Traceback (most recent call last): ... ArithmeticError: multiplicative order of 2 not defined since it is not a unit modulo 12
- sage.misc.functional.n(x, prec=None, digits=None, algorithm=None)#
Return a numerical approximation of
self
withprec
bits (or decimaldigits
) of precision.No guarantee is made about the accuracy of the result.
Note
Lower case
n()
is an alias fornumerical_approx()
and may be used as a method.INPUT:
prec
– precision in bitsdigits
– precision in decimal digits (only used ifprec
is not given)algorithm
– which algorithm to use to compute this approximation (the accepted algorithms depend on the object)
If neither
prec
nordigits
is given, the default precision is 53 bits (roughly 16 digits).EXAMPLES:
sage: numerical_approx(pi, 10) 3.1 sage: numerical_approx(pi, digits=10) 3.141592654 sage: numerical_approx(pi^2 + e, digits=20) 12.587886229548403854 sage: n(pi^2 + e) 12.5878862295484 sage: N(pi^2 + e) 12.5878862295484 sage: n(pi^2 + e, digits=50) 12.587886229548403854194778471228813633070946500941 sage: a = CC(-5).n(prec=40) sage: b = ComplexField(40)(-5) sage: a == b True sage: parent(a) is parent(b) True sage: numerical_approx(9) 9.00000000000000
You can also usually use method notation:
sage: (pi^2 + e).n() 12.5878862295484 sage: (pi^2 + e).numerical_approx() 12.5878862295484
Vectors and matrices may also have their entries approximated:
sage: v = vector(RDF, [1,2,3]) sage: v.n() (1.00000000000000, 2.00000000000000, 3.00000000000000) sage: v = vector(CDF, [1,2,3]) sage: v.n() (1.00000000000000, 2.00000000000000, 3.00000000000000) sage: _.parent() Vector space of dimension 3 over Complex Field with 53 bits of precision sage: v.n(prec=20) (1.0000, 2.0000, 3.0000) sage: u = vector(QQ, [1/2, 1/3, 1/4]) sage: n(u, prec=15) (0.5000, 0.3333, 0.2500) sage: n(u, digits=5) (0.50000, 0.33333, 0.25000) sage: v = vector(QQ, [1/2, 0, 0, 1/3, 0, 0, 0, 1/4], sparse=True) sage: u = v.numerical_approx(digits=4) sage: u.is_sparse() True sage: u (0.5000, 0.0000, 0.0000, 0.3333, 0.0000, 0.0000, 0.0000, 0.2500) sage: A = matrix(QQ, 2, 3, range(6)) sage: A.n() [0.000000000000000 1.00000000000000 2.00000000000000] [ 3.00000000000000 4.00000000000000 5.00000000000000] sage: B = matrix(Integers(12), 3, 8, srange(24)) sage: N(B, digits=2) [0.00 1.0 2.0 3.0 4.0 5.0 6.0 7.0] [ 8.0 9.0 10. 11. 0.00 1.0 2.0 3.0] [ 4.0 5.0 6.0 7.0 8.0 9.0 10. 11.]
Internally, numerical approximations of real numbers are stored in base-2. Therefore, numbers which look the same in their decimal expansion might be different:
sage: x=N(pi, digits=3); x 3.14 sage: y=N(3.14, digits=3); y 3.14 sage: x==y False sage: x.str(base=2) '11.001001000100' sage: y.str(base=2) '11.001000111101'
Increasing the precision of a floating point number is not allowed:
sage: CC(-5).n(prec=100) Traceback (most recent call last): ... TypeError: cannot approximate to a precision of 100 bits, use at most 53 bits sage: n(1.3r, digits=20) Traceback (most recent call last): ... TypeError: cannot approximate to a precision of 70 bits, use at most 53 bits sage: RealField(24).pi().n() Traceback (most recent call last): ... TypeError: cannot approximate to a precision of 53 bits, use at most 24 bits
As an exceptional case,
digits=1
usually leads to 2 digits (one significant) in the decimal output (see trac ticket #11647):sage: N(pi, digits=1) 3.2 sage: N(pi, digits=2) 3.1 sage: N(100*pi, digits=1) 320. sage: N(100*pi, digits=2) 310.
In the following example,
pi
and3
are both approximated to two bits of precision and then subtracted, which kills two bits of precision:sage: N(pi, prec=2) 3.0 sage: N(3, prec=2) 3.0 sage: N(pi - 3, prec=2) 0.00
- sage.misc.functional.ngens(x)#
Return the number of generators of
x
.EXAMPLES:
sage: R.<x,y> = SR[]; R Multivariate Polynomial Ring in x, y over Symbolic Ring sage: ngens(R) 2 sage: A = AbelianGroup(5, [5,5,7,8,9]) sage: ngens(A) 5 sage: ngens(ZZ) 1
- sage.misc.functional.norm(x)#
Return the norm of
x
.For matrices and vectors, this returns the L2-norm. The L2-norm of a vector \(\textbf{v} = (v_1, v_2, \dots, v_n)\), also called the Euclidean norm, is defined as
\[|\textbf{v}| = \sqrt{\sum_{i=1}^n |v_i|^2}\]where \(|v_i|\) is the complex modulus of \(v_i\). The Euclidean norm is often used for determining the distance between two points in two- or three-dimensional space.
For complex numbers, the function returns the field norm. If \(c = a + bi\) is a complex number, then the norm of \(c\) is defined as the product of \(c\) and its complex conjugate:
\[\text{norm}(c) = \text{norm}(a + bi) = c \cdot \overline{c} = a^2 + b^2.\]The norm of a complex number is different from its absolute value. The absolute value of a complex number is defined to be the square root of its norm. A typical use of the complex norm is in the integral domain \(\ZZ[i]\) of Gaussian integers, where the norm of each Gaussian integer \(c = a + bi\) is defined as its complex norm.
For vector fields on a pseudo-Riemannian manifold \((M,g)\), the function returns the norm with respect to the metric \(g\):
\[|v| = \sqrt{g(v,v)}\]See also
EXAMPLES:
The norm of vectors:
sage: z = 1 + 2*I sage: norm(vector([z])) sqrt(5) sage: v = vector([-1,2,3]) sage: norm(v) sqrt(14) sage: _ = var("a b c d", domain='real') sage: v = vector([a, b, c, d]) sage: norm(v) sqrt(a^2 + b^2 + c^2 + d^2)
The norm of matrices:
sage: z = 1 + 2*I sage: norm(matrix([[z]])) 2.23606797749979 sage: M = matrix(ZZ, [[1,2,4,3], [-1,0,3,-10]]) sage: norm(M) # abs tol 1e-14 10.690331129154467 sage: norm(CDF(z)) 5.0 sage: norm(CC(z)) 5.00000000000000
The norm of complex numbers:
sage: z = 2 - 3*I sage: norm(z) 13 sage: a = randint(-10^10, 100^10) sage: b = randint(-10^10, 100^10) sage: z = a + b*I sage: bool(norm(z) == a^2 + b^2) True
The complex norm of symbolic expressions:
sage: a, b, c = var("a, b, c") sage: assume((a, 'real'), (b, 'real'), (c, 'real')) sage: z = a + b*I sage: bool(norm(z).simplify() == a^2 + b^2) True sage: norm(a + b).simplify() a^2 + 2*a*b + b^2 sage: v = vector([a, b, c]) sage: bool(norm(v).simplify() == sqrt(a^2 + b^2 + c^2)) True sage: forget()
- sage.misc.functional.numerator(x)#
Return the numerator of
x
.EXAMPLES:
sage: R.<x> = PolynomialRing(QQ) sage: F = FractionField(R) sage: r = (x+1)/(x-1) sage: numerator(r) x + 1 sage: numerator(17/11111) 17
- sage.misc.functional.numerical_approx(x, prec=None, digits=None, algorithm=None)#
Return a numerical approximation of
self
withprec
bits (or decimaldigits
) of precision.No guarantee is made about the accuracy of the result.
Note
Lower case
n()
is an alias fornumerical_approx()
and may be used as a method.INPUT:
prec
– precision in bitsdigits
– precision in decimal digits (only used ifprec
is not given)algorithm
– which algorithm to use to compute this approximation (the accepted algorithms depend on the object)
If neither
prec
nordigits
is given, the default precision is 53 bits (roughly 16 digits).EXAMPLES:
sage: numerical_approx(pi, 10) 3.1 sage: numerical_approx(pi, digits=10) 3.141592654 sage: numerical_approx(pi^2 + e, digits=20) 12.587886229548403854 sage: n(pi^2 + e) 12.5878862295484 sage: N(pi^2 + e) 12.5878862295484 sage: n(pi^2 + e, digits=50) 12.587886229548403854194778471228813633070946500941 sage: a = CC(-5).n(prec=40) sage: b = ComplexField(40)(-5) sage: a == b True sage: parent(a) is parent(b) True sage: numerical_approx(9) 9.00000000000000
You can also usually use method notation:
sage: (pi^2 + e).n() 12.5878862295484 sage: (pi^2 + e).numerical_approx() 12.5878862295484
Vectors and matrices may also have their entries approximated:
sage: v = vector(RDF, [1,2,3]) sage: v.n() (1.00000000000000, 2.00000000000000, 3.00000000000000) sage: v = vector(CDF, [1,2,3]) sage: v.n() (1.00000000000000, 2.00000000000000, 3.00000000000000) sage: _.parent() Vector space of dimension 3 over Complex Field with 53 bits of precision sage: v.n(prec=20) (1.0000, 2.0000, 3.0000) sage: u = vector(QQ, [1/2, 1/3, 1/4]) sage: n(u, prec=15) (0.5000, 0.3333, 0.2500) sage: n(u, digits=5) (0.50000, 0.33333, 0.25000) sage: v = vector(QQ, [1/2, 0, 0, 1/3, 0, 0, 0, 1/4], sparse=True) sage: u = v.numerical_approx(digits=4) sage: u.is_sparse() True sage: u (0.5000, 0.0000, 0.0000, 0.3333, 0.0000, 0.0000, 0.0000, 0.2500) sage: A = matrix(QQ, 2, 3, range(6)) sage: A.n() [0.000000000000000 1.00000000000000 2.00000000000000] [ 3.00000000000000 4.00000000000000 5.00000000000000] sage: B = matrix(Integers(12), 3, 8, srange(24)) sage: N(B, digits=2) [0.00 1.0 2.0 3.0 4.0 5.0 6.0 7.0] [ 8.0 9.0 10. 11. 0.00 1.0 2.0 3.0] [ 4.0 5.0 6.0 7.0 8.0 9.0 10. 11.]
Internally, numerical approximations of real numbers are stored in base-2. Therefore, numbers which look the same in their decimal expansion might be different:
sage: x=N(pi, digits=3); x 3.14 sage: y=N(3.14, digits=3); y 3.14 sage: x==y False sage: x.str(base=2) '11.001001000100' sage: y.str(base=2) '11.001000111101'
Increasing the precision of a floating point number is not allowed:
sage: CC(-5).n(prec=100) Traceback (most recent call last): ... TypeError: cannot approximate to a precision of 100 bits, use at most 53 bits sage: n(1.3r, digits=20) Traceback (most recent call last): ... TypeError: cannot approximate to a precision of 70 bits, use at most 53 bits sage: RealField(24).pi().n() Traceback (most recent call last): ... TypeError: cannot approximate to a precision of 53 bits, use at most 24 bits
As an exceptional case,
digits=1
usually leads to 2 digits (one significant) in the decimal output (see trac ticket #11647):sage: N(pi, digits=1) 3.2 sage: N(pi, digits=2) 3.1 sage: N(100*pi, digits=1) 320. sage: N(100*pi, digits=2) 310.
In the following example,
pi
and3
are both approximated to two bits of precision and then subtracted, which kills two bits of precision:sage: N(pi, prec=2) 3.0 sage: N(3, prec=2) 3.0 sage: N(pi - 3, prec=2) 0.00
- sage.misc.functional.objgen(x)#
EXAMPLES:
sage: R, x = objgen(FractionField(QQ['x'])) sage: R Fraction Field of Univariate Polynomial Ring in x over Rational Field sage: x x
- sage.misc.functional.objgens(x)#
EXAMPLES:
sage: R, x = objgens(PolynomialRing(QQ,3, 'x')) sage: R Multivariate Polynomial Ring in x0, x1, x2 over Rational Field sage: x (x0, x1, x2)
- sage.misc.functional.order(x)#
Return the order of
x
.If
x
is a ring or module element, this is the additive order ofx
.EXAMPLES:
sage: C = CyclicPermutationGroup(10) sage: order(C) 10 sage: F = GF(7) sage: order(F) 7
- sage.misc.functional.quo(x, y, *args, **kwds)#
Return the quotient object x/y, e.g., a quotient of numbers or of a polynomial ring x by the ideal generated by y, etc.
EXAMPLES:
sage: quotient(5,6) 5/6 sage: quotient(5.,6.) 0.833333333333333 sage: R.<x> = ZZ[]; R Univariate Polynomial Ring in x over Integer Ring sage: I = Ideal(R, x^2+1) sage: quotient(R, I) Univariate Quotient Polynomial Ring in xbar over Integer Ring with modulus x^2 + 1
- sage.misc.functional.quotient(x, y, *args, **kwds)#
Return the quotient object x/y, e.g., a quotient of numbers or of a polynomial ring x by the ideal generated by y, etc.
EXAMPLES:
sage: quotient(5,6) 5/6 sage: quotient(5.,6.) 0.833333333333333 sage: R.<x> = ZZ[]; R Univariate Polynomial Ring in x over Integer Ring sage: I = Ideal(R, x^2+1) sage: quotient(R, I) Univariate Quotient Polynomial Ring in xbar over Integer Ring with modulus x^2 + 1
- sage.misc.functional.rank(x)#
Return the rank of
x
.EXAMPLES:
We compute the rank of a matrix:
sage: M = MatrixSpace(QQ,3,3) sage: A = M([1,2,3,4,5,6,7,8,9]) sage: rank(A) 2
We compute the rank of an elliptic curve:
sage: E = EllipticCurve([0,0,1,-1,0]) sage: rank(E) 1
- sage.misc.functional.regulator(x)#
Return the regulator of
x
.EXAMPLES:
sage: regulator(NumberField(x^2-2, 'a')) 0.881373587019543 sage: regulator(EllipticCurve('11a')) 1.00000000000000
- sage.misc.functional.round(x, ndigits=0)#
round(number[, ndigits]) - double-precision real number
Round a number to a given precision in decimal digits (default 0 digits). If no precision is specified this just calls the element’s .round() method.
EXAMPLES:
sage: round(sqrt(2),2) 1.41 sage: q = round(sqrt(2),5); q 1.41421 sage: type(q) <class 'sage.rings.real_double...RealDoubleElement...'> sage: q = round(sqrt(2)); q 1 sage: type(q) <class 'sage.rings.integer.Integer'> sage: round(pi) 3 sage: b = 5.4999999999999999 sage: round(b) 5
This example addresses trac ticket #23502:
sage: n = round(6); type(n) <class 'sage.rings.integer.Integer'>
Since we use floating-point with a limited range, some roundings can’t be performed:
sage: round(sqrt(Integer('1'*1000)),2) +infinity
IMPLEMENTATION: If ndigits is specified, it calls Python’s builtin round function, and converts the result to a real double field element. Otherwise, it tries the argument’s .round() method; if that fails, it reverts to the builtin round function, converted to a real double field element.
Note
This is currently slower than the builtin round function, since it does more work - i.e., allocating an RDF element and initializing it. To access the builtin version do
import builtins; builtins.round
.
- sage.misc.functional.sqrt(x, *args, **kwds)#
INPUT:
x
- a numberprec
- integer (default: None): if None, returns an exact square root; otherwise returns a numerical square root if necessary, to the given bits of precision.extend
- bool (default: True); this is a place holder, and is always ignored or passed to the sqrt function for x, since in the symbolic ring everything has a square root.all
- bool (default: False); if True, return all square roots of self, instead of just one.
EXAMPLES:
sage: sqrt(-1) I sage: sqrt(2) sqrt(2) sage: sqrt(2)^2 2 sage: sqrt(4) 2 sage: sqrt(4,all=True) [2, -2] sage: sqrt(x^2) sqrt(x^2)
For a non-symbolic square root, there are a few options. The best is to numerically approximate afterward:
sage: sqrt(2).n() 1.41421356237310 sage: sqrt(2).n(prec=100) 1.4142135623730950488016887242
Or one can input a numerical type.
sage: sqrt(2.) 1.41421356237310 sage: sqrt(2.000000000000000000000000) 1.41421356237309504880169 sage: sqrt(4.0) 2.00000000000000
To prevent automatic evaluation, one can use the
hold
parameter after coercing to the symbolic ring:sage: sqrt(SR(4),hold=True) sqrt(4) sage: sqrt(4,hold=True) Traceback (most recent call last): ... TypeError: ..._do_sqrt() got an unexpected keyword argument 'hold'
This illustrates that the bug reported in trac ticket #6171 has been fixed:
sage: a = 1.1 sage: a.sqrt(prec=100) # this is supposed to fail Traceback (most recent call last): ... TypeError: ...sqrt() got an unexpected keyword argument 'prec' sage: sqrt(a, prec=100) 1.0488088481701515469914535137 sage: sqrt(4.00, prec=250) 2.0000000000000000000000000000000000000000000000000000000000000000000000000
One can use numpy input as well:
sage: import numpy sage: a = numpy.arange(2,5) sage: sqrt(a) array([1.41421356, 1.73205081, 2. ])
- sage.misc.functional.squarefree_part(x)#
Return the square free part of
x
, i.e., a divisor \(z\) such that \(x = z y^2\), for a perfect square \(y^2\).EXAMPLES:
sage: squarefree_part(100) 1 sage: squarefree_part(12) 3 sage: squarefree_part(10) 10 sage: squarefree_part(216r) # see #8976 6
sage: x = QQ['x'].0 sage: S = squarefree_part(-9*x*(x-6)^7*(x-3)^2); S -9*x^2 + 54*x sage: S.factor() (-9) * (x - 6) * x
sage: f = (x^3 + x + 1)^3*(x-1); f x^10 - x^9 + 3*x^8 + 3*x^5 - 2*x^4 - x^3 - 2*x - 1 sage: g = squarefree_part(f); g x^4 - x^3 + x^2 - 1 sage: g.factor() (x - 1) * (x^3 + x + 1)
- sage.misc.functional.symbolic_prod(expression, *args, **kwds)#
Return the symbolic product \(\prod_{v = a}^b expression\) with respect to the variable \(v\) with endpoints \(a\) and \(b\).
INPUT:
expression
- a symbolic expressionv
- a variable or variable namea
- lower endpoint of the productb
- upper endpoint of the prductalgorithm
- (default:'maxima'
) one of'maxima'
- use Maxima (the default)'giac'
- (optional) use Giac'sympy'
- use SymPy
hold
- (default:False
) ifTrue
don’t evaluate
EXAMPLES:
sage: i, k, n = var('i,k,n') sage: product(k,k,1,n) factorial(n) sage: product(x + i*(i+1)/2, i, 1, 4) x^4 + 20*x^3 + 127*x^2 + 288*x + 180 sage: product(i^2, i, 1, 7) 25401600 sage: f = function('f') sage: product(f(i), i, 1, 7) f(7)*f(6)*f(5)*f(4)*f(3)*f(2)*f(1) sage: product(f(i), i, 1, n) product(f(i), i, 1, n) sage: assume(k>0) sage: product(integrate (x^k, x, 0, 1), k, 1, n) 1/factorial(n + 1) sage: product(f(i), i, 1, n).log().log_expand() sum(log(f(i)), i, 1, n)
- sage.misc.functional.symbolic_sum(expression, *args, **kwds)#
Return the symbolic sum \(\sum_{v = a}^b expression\) with respect to the variable \(v\) with endpoints \(a\) and \(b\).
INPUT:
expression
- a symbolic expressionv
- a variable or variable namea
- lower endpoint of the sumb
- upper endpoint of the sumalgorithm
- (default:'maxima'
) one of'maxima'
- use Maxima (the default)'maple'
- (optional) use Maple'mathematica'
- (optional) use Mathematica'giac'
- (optional) use Giac'sympy'
- use SymPy
EXAMPLES:
sage: k, n = var('k,n') sage: sum(k, k, 1, n).factor() 1/2*(n + 1)*n
sage: sum(1/k^4, k, 1, oo) 1/90*pi^4
sage: sum(1/k^5, k, 1, oo) zeta(5)
Warning
This function only works with symbolic expressions. To sum any other objects like list elements or function return values, please use python summation, see http://docs.python.org/library/functions.html#sum
In particular, this does not work:
sage: n = var('n') sage: mylist = [1,2,3,4,5] sage: sum(mylist[n], n, 0, 3) Traceback (most recent call last): ... TypeError: unable to convert n to an integer
Use python
sum()
instead:sage: sum(mylist[n] for n in range(4)) 10
Also, only a limited number of functions are recognized in symbolic sums:
sage: sum(valuation(n,2),n,1,5) Traceback (most recent call last): ... TypeError: unable to convert n to an integer
Again, use python
sum()
:sage: sum(valuation(n+1,2) for n in range(5)) 3
(now back to the Sage
sum
examples)A well known binomial identity:
sage: sum(binomial(n,k), k, 0, n) 2^n
The binomial theorem:
sage: x, y = var('x, y') sage: sum(binomial(n,k) * x^k * y^(n-k), k, 0, n) (x + y)^n
sage: sum(k * binomial(n, k), k, 1, n) 2^(n - 1)*n
sage: sum((-1)^k*binomial(n,k), k, 0, n) 0
sage: sum(2^(-k)/(k*(k+1)), k, 1, oo) -log(2) + 1
Another binomial identity (trac ticket #7952):
sage: t,k,i = var('t,k,i') sage: sum(binomial(i+t,t),i,0,k) binomial(k + t + 1, t + 1)
Summing a hypergeometric term:
sage: sum(binomial(n, k) * factorial(k) / factorial(n+1+k), k, 0, n) 1/2*sqrt(pi)/factorial(n + 1/2)
We check a well known identity:
sage: bool(sum(k^3, k, 1, n) == sum(k, k, 1, n)^2) True
A geometric sum:
sage: a, q = var('a, q') sage: sum(a*q^k, k, 0, n) (a*q^(n + 1) - a)/(q - 1)
The geometric series:
sage: assume(abs(q) < 1) sage: sum(a*q^k, k, 0, oo) -a/(q - 1)
A divergent geometric series. Don’t forget to forget your assumptions:
sage: forget() sage: assume(q > 1) sage: sum(a*q^k, k, 0, oo) Traceback (most recent call last): ... ValueError: Sum is divergent.
This summation only Mathematica can perform:
sage: sum(1/(1+k^2), k, -oo, oo, algorithm = 'mathematica') # optional - mathematica pi*coth(pi)
Use Maple as a backend for summation:
sage: sum(binomial(n,k)*x^k, k, 0, n, algorithm = 'maple') # optional - maple (x + 1)^n
Python ints should work as limits of summation (trac ticket #9393):
sage: sum(x, x, 1r, 5r) 15
Note
Sage can currently only understand a subset of the output of Maxima, Maple and Mathematica, so even if the chosen backend can perform the summation the result might not be convertible into a Sage expression.
- sage.misc.functional.transpose(x)#
Return the transpose of
x
.EXAMPLES:
sage: M = MatrixSpace(QQ,3,3) sage: A = M([1,2,3,4,5,6,7,8,9]) sage: transpose(A) [1 4 7] [2 5 8] [3 6 9]
- sage.misc.functional.xinterval(a, b)#
Iterator over the integers between \(a\) and \(b\), inclusive.
EXAMPLES:
sage: I = xinterval(2,5); I range(2, 6) sage: 5 in I True sage: 6 in I False