Utilities for Calculus#

This module defines helper functions which are used for simplifications and display of symbolic expressions.

AUTHORS:

  • Michal Bejger (2015) : class ExpressionNice

  • Eric Gourgoulhon (2015, 2017) : simplification functions

  • Travis Scrimshaw (2016): review tweaks

  • Marius Gerbershagen (2022) : skip simplification of expressions with a single number or symbolic variable

class sage.manifolds.utilities.ExpressionNice(ex)#

Bases: Expression

Subclass of Expression for a “human-friendly” display of partial derivatives and the possibility to shorten the display by skipping the arguments of symbolic functions.

INPUT:

  • ex – symbolic expression

EXAMPLES:

An expression formed with callable symbolic expressions:

sage: var('x y z')
(x, y, z)
sage: f = function('f')(x, y)
sage: g = f.diff(y).diff(x)
sage: h = function('h')(y, z)
sage: k = h.diff(z)
sage: fun = x*g + y*(k-z)^2

The standard Pynac display of partial derivatives:

sage: fun
y*(z - diff(h(y, z), z))^2 + x*diff(f(x, y), x, y)
sage: latex(fun)
y {\left(z - \frac{\partial}{\partial z}h\left(y, z\right)\right)}^{2} + x \frac{\partial^{2}}{\partial x\partial y}f\left(x, y\right)

With ExpressionNice, the Pynac notation D[...] is replaced by textbook-like notation:

sage: from sage.manifolds.utilities import ExpressionNice
sage: ExpressionNice(fun)
y*(z - d(h)/dz)^2 + x*d^2(f)/dxdy
sage: latex(ExpressionNice(fun))
y {\left(z - \frac{\partial\,h}{\partial z}\right)}^{2}
 + x \frac{\partial^2\,f}{\partial x\partial y}

An example when function variables are themselves functions:

sage: f = function('f')(x, y)
sage: g = function('g')(x, f)  # the second variable is the function f
sage: fun = (g.diff(x))*x - x^2*f.diff(x,y)
sage: fun
-x^2*diff(f(x, y), x, y) + (diff(f(x, y), x)*D[1](g)(x, f(x, y)) + D[0](g)(x, f(x, y)))*x
sage: ExpressionNice(fun)
-x^2*d^2(f)/dxdy + (d(f)/dx*d(g)/d(f(x, y)) + d(g)/dx)*x
sage: latex(ExpressionNice(fun))
-x^{2} \frac{\partial^2\,f}{\partial x\partial y}
 + {\left(\frac{\partial\,f}{\partial x}
   \frac{\partial\,g}{\partial \left( f\left(x, y\right) \right)}
 + \frac{\partial\,g}{\partial x}\right)} x

Note that D[1](g)(x, f(x,y)) is rendered as d(g)/d(f(x, y)).

An example with multiple differentiations:

sage: fun = f.diff(x,x,y,y,x)*x
sage: fun
x*diff(f(x, y), x, x, x, y, y)
sage: ExpressionNice(fun)
x*d^5(f)/dx^3dy^2
sage: latex(ExpressionNice(fun))
x \frac{\partial^5\,f}{\partial x ^ 3\partial y ^ 2}

Parentheses are added around powers of partial derivatives to avoid any confusion:

sage: fun = f.diff(y)^2
sage: fun
diff(f(x, y), y)^2
sage: ExpressionNice(fun)
(d(f)/dy)^2
sage: latex(ExpressionNice(fun))
\left(\frac{\partial\,f}{\partial y}\right)^{2}

The explicit mention of function arguments can be omitted for the sake of brevity:

sage: fun = fun*f
sage: ExpressionNice(fun)
f(x, y)*(d(f)/dy)^2
sage: Manifold.options.omit_function_arguments=True
sage: ExpressionNice(fun)
f*(d(f)/dy)^2
sage: latex(ExpressionNice(fun))
f \left(\frac{\partial\,f}{\partial y}\right)^{2}
sage: Manifold.options._reset()
sage: ExpressionNice(fun)
f(x, y)*(d(f)/dy)^2
sage: latex(ExpressionNice(fun))
f\left(x, y\right) \left(\frac{\partial\,f}{\partial y}\right)^{2}
class sage.manifolds.utilities.SimplifyAbsTrig(ex)#

Bases: ExpressionTreeWalker

Class for simplifying absolute values of cosines or sines (in the real domain), by walking the expression tree.

The end user interface is the function simplify_abs_trig().

INPUT:

  • ex – a symbolic expression

EXAMPLES:

Let us consider the following symbolic expression with some assumption on the range of the variable \(x\):

sage: assume(pi/2<x, x<pi)
sage: a = abs(cos(x)) + abs(sin(x))

The method simplify_full() is ineffective on such an expression:

sage: a.simplify_full()
abs(cos(x)) + abs(sin(x))

We construct a SimplifyAbsTrig object s from the symbolic expression a:

sage: from sage.manifolds.utilities import SimplifyAbsTrig
sage: s = SimplifyAbsTrig(a)

We use the __call__ method to walk the expression tree and produce a correctly simplified expression, given that \(x\in(\pi/2, \pi)\):

sage: s()
-cos(x) + sin(x)

Calling the simplifier s with an expression actually simplifies this expression:

sage: s(a)  # same as s() since s is built from a
-cos(x) + sin(x)
sage: s(abs(cos(x/2)) + abs(sin(x/2)))  #  pi/4 < x/2 < pi/2
cos(1/2*x) + sin(1/2*x)
sage: s(abs(cos(2*x)) + abs(sin(2*x)))  #  pi < 2 x < 2*pi
abs(cos(2*x)) - sin(2*x)
sage: s(abs(sin(2+abs(cos(x)))))  # nested abs(sin_or_cos(...))
sin(-cos(x) + 2)

See also

simplify_abs_trig() for more examples with SimplifyAbsTrig at work.

composition(ex, operator)#

This is the only method of the base class ExpressionTreeWalker that is reimplemented, since it manages the composition of abs with cos or sin.

INPUT:

  • ex – a symbolic expression

  • operator – an operator

OUTPUT:

  • a symbolic expression, equivalent to ex with abs(cos(...)) and abs(sin(...)) simplified, according to the range of their argument.

EXAMPLES:

sage: from sage.manifolds.utilities import SimplifyAbsTrig
sage: assume(-pi/2 < x, x<0)
sage: a = abs(sin(x))
sage: s = SimplifyAbsTrig(a)
sage: a.operator()
abs
sage: s.composition(a, a.operator())
sin(-x)
sage: a = exp(function('f')(x))  # no abs(sin_or_cos(...))
sage: a.operator()
exp
sage: s.composition(a, a.operator())
e^f(x)
sage: forget()  # no longer any assumption on x
sage: a = abs(cos(sin(x)))  # simplifiable since -1 <= sin(x) <= 1
sage: s.composition(a, a.operator())
cos(sin(x))
sage: a = abs(sin(cos(x)))  # not simplifiable
sage: s.composition(a, a.operator())
abs(sin(cos(x)))
class sage.manifolds.utilities.SimplifySqrtReal(ex)#

Bases: ExpressionTreeWalker

Class for simplifying square roots in the real domain, by walking the expression tree.

The end user interface is the function simplify_sqrt_real().

INPUT:

  • ex – a symbolic expression

EXAMPLES:

Let us consider the square root of an exact square under some assumption:

sage: assume(x<1)
sage: a = sqrt(x^2-2*x+1)

The method simplify_full() is ineffective on such an expression:

sage: a.simplify_full()
sqrt(x^2 - 2*x + 1)

and the more aggressive method canonicalize_radical() yields a wrong result, given that \(x<1\):

sage: a.canonicalize_radical()  # wrong output!
x - 1

We construct a SimplifySqrtReal object s from the symbolic expression a:

sage: from sage.manifolds.utilities import SimplifySqrtReal
sage: s = SimplifySqrtReal(a)

We use the __call__ method to walk the expression tree and produce a correctly simplified expression:

sage: s()
-x + 1

Calling the simplifier s with an expression actually simplifies this expression:

sage: s(a)  # same as s() since s is built from a
-x + 1
sage: s(sqrt(x^2))
abs(x)
sage: s(sqrt(1+sqrt(x^2-2*x+1)))  # nested sqrt's
sqrt(-x + 2)

Another example where both simplify_full() and canonicalize_radical() fail:

sage: b = sqrt((x-1)/(x-2))*sqrt(1-x)
sage: b.simplify_full()  # does not simplify
sqrt(-x + 1)*sqrt((x - 1)/(x - 2))
sage: b.canonicalize_radical()  # wrong output, given that x<1
(I*x - I)/sqrt(x - 2)
sage: SimplifySqrtReal(b)()  # OK, given that x<1
-(x - 1)/sqrt(-x + 2)

See also

simplify_sqrt_real() for more examples with SimplifySqrtReal at work.

arithmetic(ex, operator)#

This is the only method of the base class ExpressionTreeWalker that is reimplemented, since square roots are considered as arithmetic operations with operator = pow and ex.operands()[1] = 1/2 or -1/2.

INPUT:

  • ex – a symbolic expression

  • operator – an arithmetic operator

OUTPUT:

  • a symbolic expression, equivalent to ex with square roots simplified

EXAMPLES:

sage: from sage.manifolds.utilities import SimplifySqrtReal
sage: a = sqrt(x^2+2*x+1)
sage: s = SimplifySqrtReal(a)
sage: a.operator()
<built-in function pow>
sage: s.arithmetic(a, a.operator())
abs(x + 1)
sage: a = x + 1  # no square root
sage: s.arithmetic(a, a.operator())
x + 1
sage: a = x + 1 + sqrt(function('f')(x)^2)
sage: s.arithmetic(a, a.operator())
x + abs(f(x)) + 1
sage.manifolds.utilities.exterior_derivative(form)#

Exterior derivative of a differential form.

INPUT:

  • form – a differential form; this must an instance of either

    • DiffScalarField for a 0-form (scalar field)

    • DiffFormParal for a \(p\)-form (\(p\geq 1\)) on a parallelizable manifold

    • DiffForm for a a \(p\)-form (\(p\geq 1\)) on a non-parallelizable manifold

OUTPUT:

  • the \((p+1)\)-form that is the exterior derivative of form

EXAMPLES:

Exterior derivative of a scalar field (0-form):

sage: from sage.manifolds.utilities import exterior_derivative
sage: M = Manifold(3, 'M')
sage: X.<x,y,z> = M.chart()
sage: f = M.scalar_field({X: x+y^2+z^3}, name='f')
sage: df = exterior_derivative(f); df
1-form df on the 3-dimensional differentiable manifold M
sage: df.display()
df = dx + 2*y dy + 3*z^2 dz

An alias is xder:

sage: from sage.manifolds.utilities import xder
sage: df == xder(f)
True

Exterior derivative of a 1-form:

sage: a = M.one_form(name='a')
sage: a[:] = [x+y*z, x-y*z, x*y*z]
sage: da = xder(a); da
2-form da on the 3-dimensional differentiable manifold M
sage: da.display()
da = (-z + 1) dx∧dy + (y*z - y) dx∧dz + (x*z + y) dy∧dz
sage: dda = xder(da); dda
3-form dda on the 3-dimensional differentiable manifold M
sage: dda.display()
dda = 0
sage.manifolds.utilities.set_axes_labels(graph, xlabel, ylabel, zlabel, **kwds)#

Set axes labels for a 3D graphics object graph.

This is a workaround for the lack of axes labels in 3D plots. This sets the labels as text3d() objects at locations determined from the bounding box of the graphic object graph.

INPUT:

  • graphGraphics3d; a 3D graphic object

  • xlabel – string for the x-axis label

  • ylabel – string for the y-axis label

  • zlabel – string for the z-axis label

  • **kwds – options (e.g. color) for text3d

OUTPUT:

  • the 3D graphic object with text3d labels added

EXAMPLES:

sage: # needs sage.plot
sage: g = sphere()
sage: g.all
[Graphics3d Object]
sage: from sage.manifolds.utilities import set_axes_labels
sage: ga = set_axes_labels(g, 'X', 'Y', 'Z', color='red')
sage: ga.all  # the 3D frame has now axes labels
[Graphics3d Object, Graphics3d Object,
 Graphics3d Object, Graphics3d Object]
sage.manifolds.utilities.simplify_abs_trig(expr)#

Simplify abs(sin(...)) and abs(cos(...)) in symbolic expressions.

EXAMPLES:

sage: M = Manifold(3, 'M', structure='topological')
sage: X.<x,y,z> = M.chart(r'x y:(0,pi) z:(-pi/3,0)')
sage: X.coord_range()
x: (-oo, +oo); y: (0, pi); z: (-1/3*pi, 0)

Since \(x\) spans all \(\RR\), no simplification of abs(sin(x)) occurs, while abs(sin(y)) and abs(sin(3*z)) are correctly simplified, given that \(y \in (0,\pi)\) and \(z \in (-\pi/3,0)\):

sage: from sage.manifolds.utilities import simplify_abs_trig
sage: simplify_abs_trig( abs(sin(x)) + abs(sin(y)) + abs(sin(3*z)) )
abs(sin(x)) + sin(y) + sin(-3*z)

Note that neither simplify_trig() nor simplify_full() works in this case:

sage: s = abs(sin(x)) + abs(sin(y)) + abs(sin(3*z))
sage: s.simplify_trig()
abs(4*cos(-z)^2 - 1)*abs(sin(-z)) + abs(sin(x)) + abs(sin(y))
sage: s.simplify_full()
abs(4*cos(-z)^2 - 1)*abs(sin(-z)) + abs(sin(x)) + abs(sin(y))

despite the following assumptions hold:

sage: assumptions()
[x is real, y is real, y > 0, y < pi, z is real, z > -1/3*pi, z < 0]

Additional checks are:

sage: simplify_abs_trig( abs(sin(y/2)) )  # shall simplify
sin(1/2*y)
sage: simplify_abs_trig( abs(sin(2*y)) )  # must not simplify
abs(sin(2*y))
sage: simplify_abs_trig( abs(sin(z/2)) )  # shall simplify
sin(-1/2*z)
sage: simplify_abs_trig( abs(sin(4*z)) )  # must not simplify
abs(sin(-4*z))

Simplification of abs(cos(...)):

sage: forget()
sage: M = Manifold(3, 'M', structure='topological')
sage: X.<x,y,z> = M.chart(r'x y:(0,pi/2) z:(pi/4,3*pi/4)')
sage: X.coord_range()
x: (-oo, +oo); y: (0, 1/2*pi); z: (1/4*pi, 3/4*pi)
sage: simplify_abs_trig( abs(cos(x)) + abs(cos(y)) + abs(cos(2*z)) )
abs(cos(x)) + cos(y) - cos(2*z)

Additional tests:

sage: simplify_abs_trig(abs(cos(y-pi/2)))  # shall simplify
cos(-1/2*pi + y)
sage: simplify_abs_trig(abs(cos(y+pi/2)))  # shall simplify
-cos(1/2*pi + y)
sage: simplify_abs_trig(abs(cos(y-pi)))  # shall simplify
-cos(-pi + y)
sage: simplify_abs_trig(abs(cos(2*y)))  # must not simplify
abs(cos(2*y))
sage: simplify_abs_trig(abs(cos(y/2)) * abs(sin(z)))  # shall simplify
cos(1/2*y)*sin(z)
sage.manifolds.utilities.simplify_chain_generic(expr)#

Apply a chain of simplifications to a symbolic expression.

This is the simplification chain used in calculus involving coordinate functions on manifolds over fields different from \(\RR\), as implemented in ChartFunction.

The chain is formed by the following functions, called successively:

  1. simplify_factorial()

  2. simplify_rectform()

  3. simplify_trig()

  4. simplify_rational()

  5. expand_sum()

NB: for the time being, this is identical to simplify_full().

EXAMPLES:

We consider variables that are coordinates of a chart on a complex manifold:

sage: M = Manifold(2, 'M', structure='topological', field='complex')
sage: X.<x,y> = M.chart()

Then neither x nor y is assumed to be real:

sage: assumptions()
[]

Accordingly, simplify_chain_generic does not simplify sqrt(x^2) to abs(x):

sage: from sage.manifolds.utilities import simplify_chain_generic
sage: s = sqrt(x^2)
sage: simplify_chain_generic(s)
sqrt(x^2)

This contrasts with the behavior of simplify_chain_real().

Other simplifications:

sage: s = (x+y)^2 - x^2 -2*x*y - y^2
sage: simplify_chain_generic(s)
0
sage: s = (x^2 - 2*x + 1) / (x^2 -1)
sage: simplify_chain_generic(s)
(x - 1)/(x + 1)
sage: s = cos(2*x) - 2*cos(x)^2 + 1
sage: simplify_chain_generic(s)
0
sage.manifolds.utilities.simplify_chain_generic_sympy(expr)#

Apply a chain of simplifications to a sympy expression.

This is the simplification chain used in calculus involving coordinate functions on manifolds over fields different from \(\RR\), as implemented in ChartFunction.

The chain is formed by the following functions, called successively:

  1. combsimp()

  2. trigsimp()

  3. expand()

  4. simplify()

EXAMPLES:

We consider variables that are coordinates of a chart on a complex manifold:

sage: forget()  # for doctest only
sage: M = Manifold(2, 'M', structure='topological', field='complex', calc_method='sympy')
sage: X.<x,y> = M.chart()

Then neither x nor y is assumed to be real:

sage: assumptions()
[]

Accordingly, simplify_chain_generic_sympy does not simplify sqrt(x^2) to abs(x):

sage: from sage.manifolds.utilities import simplify_chain_generic_sympy
sage: s = (sqrt(x^2))._sympy_()
sage: simplify_chain_generic_sympy(s)
sqrt(x**2)

This contrasts with the behavior of simplify_chain_real_sympy().

Other simplifications:

sage: s = ((x+y)^2 - x^2 -2*x*y - y^2)._sympy_()
sage: simplify_chain_generic_sympy(s)
0
sage: s = ((x^2 - 2*x + 1) / (x^2 -1))._sympy_()
sage: simplify_chain_generic_sympy(s)
(x - 1)/(x + 1)
sage: s = (cos(2*x) - 2*cos(x)^2 + 1)._sympy_()
sage: simplify_chain_generic_sympy(s)
0
sage.manifolds.utilities.simplify_chain_real(expr)#

Apply a chain of simplifications to a symbolic expression, assuming the real domain.

This is the simplification chain used in calculus involving coordinate functions on real manifolds, as implemented in ChartFunction.

The chain is formed by the following functions, called successively:

  1. simplify_factorial()

  2. simplify_trig()

  3. simplify_rational()

  4. simplify_sqrt_real()

  5. simplify_abs_trig()

  6. canonicalize_radical()

  7. simplify_log()

  8. simplify_rational()

  9. simplify_trig()

EXAMPLES:

We consider variables that are coordinates of a chart on a real manifold:

sage: M = Manifold(2, 'M', structure='topological')
sage: X.<x,y> = M.chart('x:(0,1) y')

The following assumptions then hold:

sage: assumptions()
[x is real, x > 0, x < 1, y is real]

and we have:

sage: from sage.manifolds.utilities import simplify_chain_real
sage: s = sqrt(y^2)
sage: simplify_chain_real(s)
abs(y)

The above result is correct since y is real. It is obtained by simplify_real() as well:

sage: s.simplify_real()
abs(y)
sage: s.simplify_full()
abs(y)

Furthermore, we have:

sage: s = sqrt(x^2-2*x+1)
sage: simplify_chain_real(s)
-x + 1

which is correct since \(x \in (0,1)\). On this example, neither simplify_real() nor simplify_full(), nor canonicalize_radical() give satisfactory results:

sage: s.simplify_real()  # unsimplified output
sqrt(x^2 - 2*x + 1)
sage: s.simplify_full()  # unsimplified output
sqrt(x^2 - 2*x + 1)
sage: s.canonicalize_radical()  # wrong output since x in (0,1)
x - 1

Other simplifications:

sage: s = abs(sin(pi*x))
sage: simplify_chain_real(s)  # correct output since x in (0,1)
sin(pi*x)
sage: s.simplify_real()  # unsimplified output
abs(sin(pi*x))
sage: s.simplify_full()  # unsimplified output
abs(sin(pi*x))
sage: s = cos(y)^2 + sin(y)^2
sage: simplify_chain_real(s)
1
sage: s.simplify_real()  # unsimplified output
cos(y)^2 + sin(y)^2
sage: s.simplify_full()  # OK
1
sage.manifolds.utilities.simplify_chain_real_sympy(expr)#

Apply a chain of simplifications to a sympy expression, assuming the real domain.

This is the simplification chain used in calculus involving coordinate functions on real manifolds, as implemented in ChartFunction.

The chain is formed by the following functions, called successively:

  1. combsimp()

  2. trigsimp()

  3. simplify_sqrt_real()

  4. simplify_abs_trig()

  5. expand()

  6. simplify()

EXAMPLES:

We consider variables that are coordinates of a chart on a real manifold:

sage: forget()  # for doctest only
sage: M = Manifold(2, 'M', structure='topological',calc_method='sympy')
sage: X.<x,y> = M.chart('x:(0,1) y')

The following assumptions then hold:

sage: assumptions()
[x is real, x > 0, x < 1, y is real]

and we have:

sage: from sage.manifolds.utilities import simplify_chain_real_sympy
sage: s = (sqrt(y^2))._sympy_()
sage: simplify_chain_real_sympy(s)
Abs(y)

Furthermore, we have:

sage: s = (sqrt(x^2-2*x+1))._sympy_()
sage: simplify_chain_real_sympy(s)
1 - x

Other simplifications:

sage: s = (abs(sin(pi*x)))._sympy_()
sage: simplify_chain_real_sympy(s)  # correct output since x in (0,1)
sin(pi*x)
sage: s = (cos(y)^2 + sin(y)^2)._sympy_()
sage: simplify_chain_real_sympy(s)
1
sage.manifolds.utilities.simplify_sqrt_real(expr)#

Simplify sqrt in symbolic expressions in the real domain.

EXAMPLES:

Simplifications of basic expressions:

sage: from sage.manifolds.utilities import simplify_sqrt_real
sage: simplify_sqrt_real( sqrt(x^2) )
abs(x)
sage: assume(x<0)
sage: simplify_sqrt_real( sqrt(x^2) )
-x
sage: simplify_sqrt_real( sqrt(x^2-2*x+1) )
-x + 1
sage: simplify_sqrt_real( sqrt(x^2) + sqrt(x^2-2*x+1) )
-2*x + 1

This improves over canonicalize_radical(), which yields incorrect results when x < 0:

sage: forget()  # removes the assumption x<0
sage: sqrt(x^2).canonicalize_radical()
x
sage: assume(x<0)
sage: sqrt(x^2).canonicalize_radical()
-x
sage: sqrt(x^2-2*x+1).canonicalize_radical() # wrong output
x - 1
sage: ( sqrt(x^2) + sqrt(x^2-2*x+1) ).canonicalize_radical() # wrong output
-1

Simplification of nested sqrt’s:

sage: forget()  # removes the assumption x<0
sage: simplify_sqrt_real( sqrt(1 + sqrt(x^2)) )
sqrt(abs(x) + 1)
sage: assume(x<0)
sage: simplify_sqrt_real( sqrt(1 + sqrt(x^2)) )
sqrt(-x + 1)
sage: simplify_sqrt_real( sqrt(x^2 + sqrt(4*x^2) + 1) )
-x + 1

Again, canonicalize_radical() fails on the last one:

sage: (sqrt(x^2 + sqrt(4*x^2) + 1)).canonicalize_radical()
x - 1
sage.manifolds.utilities.xder(form)#

Exterior derivative of a differential form.

INPUT:

  • form – a differential form; this must an instance of either

    • DiffScalarField for a 0-form (scalar field)

    • DiffFormParal for a \(p\)-form (\(p\geq 1\)) on a parallelizable manifold

    • DiffForm for a a \(p\)-form (\(p\geq 1\)) on a non-parallelizable manifold

OUTPUT:

  • the \((p+1)\)-form that is the exterior derivative of form

EXAMPLES:

Exterior derivative of a scalar field (0-form):

sage: from sage.manifolds.utilities import exterior_derivative
sage: M = Manifold(3, 'M')
sage: X.<x,y,z> = M.chart()
sage: f = M.scalar_field({X: x+y^2+z^3}, name='f')
sage: df = exterior_derivative(f); df
1-form df on the 3-dimensional differentiable manifold M
sage: df.display()
df = dx + 2*y dy + 3*z^2 dz

An alias is xder:

sage: from sage.manifolds.utilities import xder
sage: df == xder(f)
True

Exterior derivative of a 1-form:

sage: a = M.one_form(name='a')
sage: a[:] = [x+y*z, x-y*z, x*y*z]
sage: da = xder(a); da
2-form da on the 3-dimensional differentiable manifold M
sage: da.display()
da = (-z + 1) dx∧dy + (y*z - y) dx∧dz + (x*z + y) dy∧dz
sage: dda = xder(da); dda
3-form dda on the 3-dimensional differentiable manifold M
sage: dda.display()
dda = 0