# SaveAt¤

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```
diffrax.SaveAt
```

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Determines what to save as output from the differential equation solve.

Instances of this class should be passed as the `saveat`

argument of
`diffrax.diffeqsolve`

.

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`t0: bool`

`dataclass-field`

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`t1: bool`

`dataclass-field`

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`ts: Union[Sequence[Scalar], Array['times']]`

`dataclass-field`

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`steps: bool`

`dataclass-field`

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`dense: bool`

`dataclass-field`

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`solver_state: bool`

`dataclass-field`

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`controller_state: bool`

`dataclass-field`

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`made_jump: bool`

`dataclass-field`

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`__init__(self, t0: bool = False, t1: bool = False, ts: Union[Sequence[Scalar], Array['times']] = None, steps: bool = False, dense: bool = False, solver_state: bool = False, controller_state: bool = False, made_jump: bool = False)`

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**Main Arguments:**

`t0`

: If`True`

, save the initial input`y0`

.`t1`

: If`True`

, save the output at`t1`

.`ts`

: Some array of times at which to save the output.`steps`

: If`True`

, save the output at every step of the numerical solver.`dense`

: If`True`

, save dense output, that can later be evaluated at any part of the interval \([t_0, t_1]\) via`sol = diffeqsolve(...); sol.evaluate(...)`

.

**Other Arguments:**

It is less likely you will need to use these options.

`solver_state`

: If`True`

, save the internal state of the numerical solver at`t1`

.`controller_state`

: If`True`

, save the internal state of the step size controller at`t1`

.`made_jump`

: If`True`

, save the internal state of the jump tracker at`t1`

.