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 with prec bits (or decimal digits) of precision.

No guarantee is made about the accuracy of the result.

Note

Lower case n() is an alias for numerical_approx() and may be used as a method.

INPUT:

• prec – precision in bits
• digits – precision in decimal digits (only used if prec is not given)
• algorithm – which algorithm to use to compute this approximation (the accepted algorithms depend on the object)

If neither prec nor digits 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 and 3 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

Return the additive order of x.

EXAMPLES:

+Infinity
11
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 type P if possible.

EXAMPLES:

sage: type(5)
<type 'sage.rings.integer.Integer'>
sage: type(coerce(QQ,5))
<type '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.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, )
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)); 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)); 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)
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)

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)
True
sage.misc.functional.is_integrally_closed(x)

Return whether x is integrally closed.

EXAMPLES:

sage: is_integrally_closed(QQ)
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(x, b=None)

Return the log of x to the base $$b$$. The default base is $$e$$.

DEPRECATED by trac ticket #19444

INPUT:

• x – number
• $$b$$ – base (default: None, which means natural log)

OUTPUT: number

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: from sage.misc.functional import log
sage: log(e^2)
doctest:warning...
See http://trac.sagemath.org/19444 for details.
2
sage: log(16,2)
4
sage: log(3.)
1.09861228866811
sage: log(float(3))  # abs tol 1e-15
1.0986122886681098
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, if x is a unit, or raise ArithmeticError 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 with prec bits (or decimal digits) of precision.

No guarantee is made about the accuracy of the result.

Note

Lower case n() is an alias for numerical_approx() and may be used as a method.

INPUT:

• prec – precision in bits
• digits – precision in decimal digits (only used if prec is not given)
• algorithm – which algorithm to use to compute this approximation (the accepted algorithms depend on the object)

If neither prec nor digits 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 and 3 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 $$g$$:

$|v| = \sqrt{g(v,v)}$

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 with prec bits (or decimal digits) of precision.

No guarantee is made about the accuracy of the result.

Note

Lower case n() is an alias for numerical_approx() and may be used as a method.

INPUT:

• prec – precision in bits
• digits – precision in decimal digits (only used if prec is not given)
• algorithm – which algorithm to use to compute this approximation (the accepted algorithms depend on the object)

If neither prec nor digits 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 and 3 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 of x.

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)
<type 'sage.rings.real_double.RealDoubleElement'>
sage: q = round(sqrt(2)); q
1
sage: type(q)
<type '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)
<type '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 from six.moves import builtins; builtins.round.

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 expression
• v - a variable or variable name
• a - lower endpoint of the product
• b - upper endpoint of the prduct
• algorithm - (default: 'maxima') one of
• 'maxima' - use Maxima (the default)
• 'giac' - (optional) use Giac
• 'sympy' - use SymPy
• hold - (default: False) if True 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 expression
• v - a variable or variable name
• a - lower endpoint of the sum
• b - upper endpoint of the sum
• algorithm - (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

1. 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 convertable 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  # py2
xrange(2, 6)
sage: I = xinterval(2,5); I  # py3
range(2, 6)
sage: 5 in I
True
sage: 6 in I
False