1 | initial version |

You can access the source code for eigenvalues_right:

```
sage: gamma.eigenvectors_right??
```

There you see that the right eigenvectors are computed by computing the left
eigenvectors of the transpose matrix. So let's check the documentation for
`eigenvectors_left`

:

```
sage: gamma.eigenvectors_left??
```

You can see there an example involving a 2x2 matrix with symbolic entries, followed by the following comment:

```
This routine calls Maxima and can struggle with even small matrices
with a few variables, such as a `3\times 3` matrix with three variables.
However, if the entries are integers or rationals it can produce exact
values in a reasonable time.
```

2 | No.2 Revision |

You can access the ~~source code ~~documentation for eigenvalues_right:

```
sage: gamma.eigenvectors_right?
```

or the source code:

```
sage: gamma.eigenvectors_right??
```

There you see that the right eigenvectors are computed by computing the left
eigenvectors of the transpose matrix. So let's check the documentation for
`eigenvectors_left`

:

```
sage: gamma.eigenvectors_left?
```

or the source code:

```
sage: gamma.eigenvectors_left??
```

You can see there an example involving a 2x2 matrix with symbolic entries, followed by the following comment:

```
This routine calls Maxima and can struggle with even small matrices
with a few variables, such as a `3\times 3` matrix with three variables.
However, if the entries are integers or rationals it can produce exact
values in a reasonable time.
```

Note: to get the documentation for that command in html format, do:

```
sage: browse_sage_doc(gamma.eigenvectors_left)
```

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