Symbolic variables

sage.calculus.var.clear_vars()

Delete all 1-letter symbolic variables that are predefined at startup of Sage.

Any one-letter global variables that are not symbolic variables are not cleared.

EXAMPLES:

sage: var('x y z')
(x, y, z)
sage: (x+y)^z
(x + y)^z
sage: k = 15
sage: clear_vars()
sage: (x+y)^z
Traceback (most recent call last):
...
NameError: name 'x' is not defined
sage: expand((e + i)^2)
e^2 + 2*I*e - 1
sage: k
15

sage.calculus.var.function(s, **kwds)

Create a formal symbolic function with the name s.

INPUT:

• nargs=0 - number of arguments the function accepts, defaults to variable number of arguments, or 0

• latex_name - name used when printing in latex mode

• conversions - a dictionary specifying names of this function in other systems, this is used by the interfaces internally during conversion

• eval_func - method used for automatic evaluation

• evalf_func - method used for numeric evaluation

• evalf_params_first - bool to indicate if parameters should be evaluated numerically before calling the custom evalf function

• conjugate_func - method used for complex conjugation

• real_part_func - method used when taking real parts

• imag_part_func - method used when taking imaginary parts

• derivative_func - method to be used for (partial) derivation This method should take a keyword argument deriv_param specifying the index of the argument to differentiate w.r.t

• tderivative_func - method to be used for derivatives

• power_func - method used when taking powers This method should take a keyword argument power_param specifying the exponent

• series_func - method used for series expansion This method should expect keyword arguments - order - order for the expansion to be computed - var - variable to expand w.r.t. - at - expand at this value

• print_func - method for custom printing

• print_latex_func - method for custom printing in latex mode

Note that custom methods must be instance methods, i.e., expect the instance of the symbolic function as the first argument.

Note

The new function is both returned and automatically injected into the global namespace. If you use this function in library code, it is better to use sage.symbolic.function_factory.function, since it will not touch the global namespace.

EXAMPLES:

We create a formal function called supersin

sage: function('supersin')
supersin

We can immediately use supersin in symbolic expressions:

sage: y, z, A = var('y z A')
sage: supersin(y+z) + A^3
A^3 + supersin(y + z)

We can define other functions in terms of supersin:

sage: g(x,y) = supersin(x)^2 + sin(y/2)
sage: g
(x, y) |--> supersin(x)^2 + sin(1/2*y)
sage: g.diff(y)
(x, y) |--> 1/2*cos(1/2*y)
sage: k = g.diff(x); k
(x, y) |--> 2*supersin(x)*diff(supersin(x), x)

We create a formal function of one variable, write down an expression that involves first and second derivatives, and extract off coefficients:

sage: r, kappa = var('r,kappa')
sage: psi = function('psi', nargs=1)(r); psi
psi(r)
sage: g = 1/r^2*(2*r*psi.derivative(r,1) + r^2*psi.derivative(r,2)); g
(r^2*diff(psi(r), r, r) + 2*r*diff(psi(r), r))/r^2
sage: g.expand()
2*diff(psi(r), r)/r + diff(psi(r), r, r)
sage: g.coefficient(psi.derivative(r,2))
1
sage: g.coefficient(psi.derivative(r,1))
2/r

Custom typesetting of symbolic functions in LaTeX, either using latex_name keyword:

sage: function('riemann', latex_name="\\mathcal{R}")
riemann
sage: latex(riemann(x))
\mathcal{R}\left(x\right)

or passing a custom callable function that returns a latex expression:

sage: mu,nu = var('mu,nu')
sage: def my_latex_print(self, *args): return "\\psi_{%s}"%(', '.join(map(latex, args)))
sage: function('psi', print_latex_func=my_latex_print)
psi
sage: latex(psi(mu,nu))
\psi_{\mu, \nu}

Defining custom methods for automatic or numeric evaluation, derivation, conjugation, etc. is supported:

sage: def ev(self, x): return 2*x
sage: foo = function("foo", nargs=1, eval_func=ev)
sage: foo(x)
2*x
sage: foo = function("foo", nargs=1, eval_func=lambda self, x: 5)
sage: foo(x)
5
sage: def ef(self, x): pass
sage: bar = function("bar", nargs=1, eval_func=ef)
sage: bar(x)
bar(x)

sage: def evalf_f(self, x, parent=None, algorithm=None): return 6
sage: foo = function("foo", nargs=1, evalf_func=evalf_f)
sage: foo(x)
foo(x)
sage: foo(x).n()
6

sage: foo = function("foo", nargs=1, conjugate_func=ev)
sage: foo(x).conjugate()
2*x

sage: def deriv(self, *args,**kwds): print("{} {}".format(args, kwds)); return args[kwds['diff_param']]^2
sage: foo = function("foo", nargs=2, derivative_func=deriv)
sage: foo(x,y).derivative(y)
(x, y) {'diff_param': 1}
y^2

sage: def pow(self, x, power_param=None): print("{} {}".format(x, power_param)); return x*power_param
sage: foo = function("foo", nargs=1, power_func=pow)
sage: foo(y)^(x+y)
y x + y
(x + y)*y

sage: from pprint import pformat
sage: def expand(self, *args, **kwds):
....:     print("{} {}".format(args, pformat(kwds)))
....:     return sum(args[0]^i for i in range(kwds['order']))
sage: foo = function("foo", nargs=1, series_func=expand)
sage: foo(y).series(y, 5)
(y,) {'at': 0, 'options': 0, 'order': 5, 'var': y}
y^4 + y^3 + y^2 + y + 1

sage: def my_print(self, *args):
....:     return "my args are: " + ', '.join(map(repr, args))
sage: foo = function('t', nargs=2, print_func=my_print)
sage: foo(x,y^z)
my args are: x, y^z

sage: latex(foo(x,y^z))
t\left(x, y^{z}\right)
sage: foo = function('t', nargs=2, print_latex_func=my_print)
sage: foo(x,y^z)
t(x, y^z)
sage: latex(foo(x,y^z))
my args are: x, y^z
sage: foo = function('t', nargs=2, latex_name='foo')
sage: latex(foo(x,y^z))
foo\left(x, y^{z}\right)

Chain rule:

sage: def print_args(self, *args, **kwds): print("args: {}".format(args)); print("kwds: {}".format(kwds)); return args[0]
sage: foo = function('t', nargs=2, tderivative_func=print_args)
sage: foo(x,x).derivative(x)
args: (x, x)
kwds: {'diff_param': x}
x
sage: foo = function('t', nargs=2, derivative_func=print_args)
sage: foo(x,x).derivative(x)
args: (x, x)
kwds: {'diff_param': 0}
args: (x, x)
kwds: {'diff_param': 1}
2*x

Since Sage 4.0, basic arithmetic with unevaluated functions is no longer supported:

sage: x = var('x')
sage: f = function('f')
sage: 2*f
Traceback (most recent call last):
...
TypeError: unsupported operand parent(s) for *: 'Integer Ring' and '<class 'sage.symbolic.function_factory...NewSymbolicFunction'>'

You now need to evaluate the function in order to do the arithmetic:

sage: 2*f(x)
2*f(x)

Since Sage 4.0, you need to use substitute_function() to replace all occurrences of a function with another:

sage: var('a, b')
(a, b)
sage: cr = function('cr')
sage: f = cr(a)
sage: g = f.diff(a).integral(b)
sage: g
b*diff(cr(a), a)
sage: g.substitute_function(cr, cos)
-b*sin(a)

sage: g.substitute_function(cr, (sin(x) + cos(x)).function(x))
b*(cos(a) - sin(a))

sage.calculus.var.var(*args, **kwds)

Create a symbolic variable with the name s.

INPUT:

• args – A single string var('x y'), a list of strings var(['x','y']), or multiple strings var('x', 'y'). A single string can be either a single variable name, or a space or comma separated list of variable names. In a list or tuple of strings, each entry is one variable. If multiple arguments are specified, each argument is taken to be one variable. Spaces before or after variable names are ignored.

• kwds – keyword arguments can be given to specify domain and custom latex_name for variables. See EXAMPLES for usage.

Note

The new variable is both returned and automatically injected into the global namespace. If you need a symbolic variable in library code, you must use either SR.var() or SR.symbol().

OUTPUT:

If a single symbolic variable was created, the variable itself. Otherwise, a tuple of symbolic variables. The variable names are checked to be valid Python identifiers and a ValueError is raised otherwise.

EXAMPLES:

Here are the different ways to define three variables x, y, and z in a single line:

sage: var('x y z')
(x, y, z)
sage: var('x, y, z')
(x, y, z)
sage: var(['x', 'y', 'z'])
(x, y, z)
sage: var('x', 'y', 'z')
(x, y, z)
sage: var('x'), var('y'), var(z)
(x, y, z)

We define some symbolic variables:

sage: var('n xx yy zz')
(n, xx, yy, zz)

Then we make an algebraic expression out of them:

sage: f = xx^n + yy^n + zz^n; f
xx^n + yy^n + zz^n

By default, var returns a complex variable. To define real or positive variables we can specify the domain as:

sage: x = var('x', domain=RR); x; x.conjugate()
x
x
sage: y = var('y', domain='real'); y.conjugate()
y
sage: y = var('y', domain='positive'); y.abs()
y

Custom latex expression can be assigned to variable:

sage: x = var('sui', latex_name="s_{u,i}"); x._latex_()
'{s_{u,i}}'

In notebook, we can also colorize latex expression:

sage: x = var('sui', latex_name="\\color{red}{s_{u,i}}"); x._latex_()
'{\\color{red}{s_{u,i}}}'

We can substitute a new variable name for n:

sage: f(n = var('sigma'))
xx^sigma + yy^sigma + zz^sigma

If you make an important built-in variable into a symbolic variable, you can get back the original value using restore:

sage: var('QQ RR')
(QQ, RR)
sage: QQ
QQ
sage: restore('QQ')
sage: QQ
Rational Field

We make two new variables separated by commas:

sage: var('theta, gamma')
(theta, gamma)
sage: theta^2 + gamma^3
gamma^3 + theta^2

The new variables are of type Expression, and belong to the symbolic expression ring:

sage: type(theta)
<class 'sage.symbolic.expression.Expression'>
sage: parent(theta)
Symbolic Ring