Potential Issues/Advanced Topics/Future Features in Physics/Vector Module

This document will describe some of the more advanced functionality that this module offers but which is not part of the “official” interface. Here, some of the features that will be implemented in the future will also be covered, along with unanswered questions about proper functionality. Also, common problems will be discussed, along with some solutions.


In sympy.physics.mechanics, dyadics are used to represent inertia ([Kane1985], [WikiDyadics], [WikiDyadicProducts]). A dyadic is a linear polynomial of component unit dyadics, similar to a vector being a linear polynomial of component unit vectors. A dyadic is the outer product between two vectors which returns a new quantity representing the juxtaposition of these two vectors. For example:

\[\begin{split}\mathbf{\hat{a}_x} \otimes \mathbf{\hat{a}_x} &= \mathbf{\hat{a}_x} \mathbf{\hat{a}_x}\\ \mathbf{\hat{a}_x} \otimes \mathbf{\hat{a}_y} &= \mathbf{\hat{a}_x} \mathbf{\hat{a}_y}\\\end{split}\]

Where \(\mathbf{\hat{a}_x}\mathbf{\hat{a}_x}\) and \(\mathbf{\hat{a}_x}\mathbf{\hat{a}_y}\) are the outer products obtained by multiplying the left side as a column vector by the right side as a row vector. Note that the order is significant.

Some additional properties of a dyadic are:

\[\begin{split}(x \mathbf{v}) \otimes \mathbf{w} &= \mathbf{v} \otimes (x \mathbf{w}) = x (\mathbf{v} \otimes \mathbf{w})\\ \mathbf{v} \otimes (\mathbf{w} + \mathbf{u}) &= \mathbf{v} \otimes \mathbf{w} + \mathbf{v} \otimes \mathbf{u}\\ (\mathbf{v} + \mathbf{w}) \otimes \mathbf{u} &= \mathbf{v} \otimes \mathbf{u} + \mathbf{w} \otimes \mathbf{u}\\\end{split}\]

A vector in a reference frame can be represented as \(\begin{bmatrix}a\\b\\c\end{bmatrix}\) or \(a \mathbf{\hat{i}} + b \mathbf{\hat{j}} + c \mathbf{\hat{k}}\). Similarly, a dyadic can be represented in tensor form:

\[\begin{split}\begin{bmatrix} a_{11} & a_{12} & a_{13} \\ a_{21} & a_{22} & a_{23} \\ a_{31} & a_{32} & a_{33} \end{bmatrix}\\\end{split}\]

or in dyadic form:

\[\begin{split}a_{11} \mathbf{\hat{a}_x}\mathbf{\hat{a}_x} + a_{12} \mathbf{\hat{a}_x}\mathbf{\hat{a}_y} + a_{13} \mathbf{\hat{a}_x}\mathbf{\hat{a}_z} + a_{21} \mathbf{\hat{a}_y}\mathbf{\hat{a}_x} + a_{22} \mathbf{\hat{a}_y}\mathbf{\hat{a}_y} + a_{23} \mathbf{\hat{a}_y}\mathbf{\hat{a}_z} + a_{31} \mathbf{\hat{a}_z}\mathbf{\hat{a}_x} + a_{32} \mathbf{\hat{a}_z}\mathbf{\hat{a}_y} + a_{33} \mathbf{\hat{a}_z}\mathbf{\hat{a}_z}\\\end{split}\]

Just as with vectors, the later representation makes it possible to keep track of which frames the dyadic is defined with respect to. Also, the two components of each term in the dyadic need not be in the same frame. The following is valid:

\[\mathbf{\hat{a}_x} \otimes \mathbf{\hat{b}_y} = \mathbf{\hat{a}_x} \mathbf{\hat{b}_y}\]

Dyadics can also be crossed and dotted with vectors; again, order matters:

\[\begin{split}\mathbf{\hat{a}_x}\mathbf{\hat{a}_x} \cdot \mathbf{\hat{a}_x} &= \mathbf{\hat{a}_x}\\ \mathbf{\hat{a}_y}\mathbf{\hat{a}_x} \cdot \mathbf{\hat{a}_x} &= \mathbf{\hat{a}_y}\\ \mathbf{\hat{a}_x}\mathbf{\hat{a}_y} \cdot \mathbf{\hat{a}_x} &= 0\\ \mathbf{\hat{a}_x} \cdot \mathbf{\hat{a}_x}\mathbf{\hat{a}_x} &= \mathbf{\hat{a}_x}\\ \mathbf{\hat{a}_x} \cdot \mathbf{\hat{a}_x}\mathbf{\hat{a}_y} &= \mathbf{\hat{a}_y}\\ \mathbf{\hat{a}_x} \cdot \mathbf{\hat{a}_y}\mathbf{\hat{a}_x} &= 0\\ \mathbf{\hat{a}_x} \times \mathbf{\hat{a}_y}\mathbf{\hat{a}_x} &= \mathbf{\hat{a}_z}\mathbf{\hat{a}_x}\\ \mathbf{\hat{a}_x} \times \mathbf{\hat{a}_x}\mathbf{\hat{a}_x} &= 0\\ \mathbf{\hat{a}_y}\mathbf{\hat{a}_x} \times \mathbf{\hat{a}_z} &= - \mathbf{\hat{a}_y}\mathbf{\hat{a}_y}\\\end{split}\]

One can also take the time derivative of dyadics or express them in different frames, just like with vectors.

Common Issues

Here issues with numerically integrating code, choice of \(dynamicsymbols\) for coordinate and speed representation, printing, differentiating, and substitution will occur.


The default printing options are to use sorting for Vector and Dyadic measure numbers, and have unsorted output from the vprint, vpprint, and vlatex functions. If you are printing something large, please use one of those functions, as the sorting can increase printing time from seconds to minutes.


Substitution into large expressions can be slow, and take a few minutes.

Acceleration of Points

At a minimum, points need to have their velocities defined, as the acceleration can be calculated by taking the time derivative of the velocity in the same frame. If the 1 point or 2 point theorems were used to compute the velocity, the time derivative of the velocity expression will most likely be more complex than if you were to use the acceleration level 1 point and 2 point theorems. Using the acceleration level methods can result in shorted expressions at this point, which will result in shorter expressions later (such as when forming Kane’s equations).

Advanced Interfaces

Here we will cover advanced options in: ReferenceFrame, dynamicsymbols, and some associated functionality.


ReferenceFrame is shown as having a .name attribute and .x, .y, and .z attributes for accessing the basis vectors, as well as a fairly rigidly defined print output. If you wish to have a different set of indices defined, there is an option for this. This will also require a different interface for accessing the basis vectors.

>>> from sympy.physics.vector import ReferenceFrame, vprint, vpprint, vlatex
>>> N = ReferenceFrame('N', indices=['i', 'j', 'k'])
>>> N['i']
>>> N.x
>>> vlatex(N.x)

Also, the latex output can have custom strings; rather than just indices though, the entirety of each basis vector can be specified. The custom latex strings can occur without custom indices, and also overwrites the latex string that would be used if there were custom indices.

>>> from sympy.physics.vector import ReferenceFrame, vlatex
>>> N = ReferenceFrame('N', latexs=['n1','\\mathbf{n}_2','cat'])
>>> vlatex(N.x)
>>> vlatex(N.y)
>>> vlatex(N.z)


The dynamicsymbols function also has ‘hidden’ functionality; the variable which is associated with time can be changed, as well as the notation for printing derivatives.

>>> from sympy import symbols
>>> from sympy.physics.vector import dynamicsymbols, vprint
>>> q1 = dynamicsymbols('q1')
>>> q1
>>> dynamicsymbols._t = symbols('T')
>>> q2 = dynamicsymbols('q2')
>>> q2
>>> q1
>>> q1d = dynamicsymbols('q1', 1)
>>> vprint(q1d)
>>> dynamicsymbols._str = 'd'
>>> vprint(q1d)
>>> dynamicsymbols._str = '\''
>>> dynamicsymbols._t = symbols('t')

Note that only dynamic symbols created after the change are different. The same is not true for the \(._str\) attribute; this affects the printing output only, so dynamic symbols created before or after will print the same way.

Also note that Vector’s .dt method uses the ._t attribute of dynamicsymbols, along with a number of other important functions and methods. Don’t mix and match symbols representing time.

Solving Vector Equations

To solve equations involving vectors, you cannot directly use the solve functions on a vector. Instead, you must convert the vector to a set of scalar equations.

Suppose that we have two frames N and A, where A is rotated 30 degrees about the z-axis with respect to N.

>>> from sympy import pi, symbols, solve
>>> from sympy.physics.vector import ReferenceFrame
>>> N = ReferenceFrame("N")
>>> A = ReferenceFrame("A")
>>> A.orient_axis(N, pi / 6, N.z)

Suppose that we have two vectors v1 and v2, which represent the same vector using different symbols.

>>> v1x, v1y, v1z = symbols("v1x v1y v1z")
>>> v2x, v2y, v2z = symbols("v2x v2y v2z")
>>> v1 = v1x * N.x + v1y * N.y + v1z * N.z
>>> v2 = v2x * A.x + v2y * A.y + v2z * A.z

Our goal is to find the relationship between the symbols used in v2 and the symbols used in v1. We can achieve this by converting the vector to a matrix and then solving the matrix using sympy.solvers.solvers.solve().

>>> solve((v1 - v2).to_matrix(N), [v2x, v2y, v2z])
{v2x: sqrt(3)*v1x/2 + v1y/2, v2y: -v1x/2 + sqrt(3)*v1y/2, v2z: v1z}