---
title: ObservableData (latest version)
description: API reference for qiskit_noise_learning.data.ObservableData in the latest version of qiskit-noise-learning
source: https://quantum.cloud.ibm.com/docs/en/api/qiskit-noise-learning/generated/data-observable-data
---

# qiskit\_noise\_learning.data.ObservableData

*class* `qiskit_noise_learning.data.ObservableData(dataset: Dataset)`

[GitHub](https://github.com/Qiskit/qiskit-noise-learning/tree/stable/0.1/qiskit_noise_learning/data/observable_data.py)

Bases: [`LeveledData`](/docs/api/qiskit-noise-learning/generated/data-leveled-data "qiskit_noise_learning.data.leveled_data.LeveledData")

A collection of calculated expectation values.

This class is a wrapper around an XArray `Dataset`, containing the following data:

- Data variables:

  > - `observable_values`: Observables computed from single `InstructionSequence` and `Path` pairs at a given fragment depth, separated by randomizations. Has dimensions `("observable", "randomization")`. `np.nan` values are assumed to be due to raggedness of the `"randomization"` dimension for different observables.
  > - `time_lbs`: Lower bound on data acquisition times, with dimensions `("observable", "randomization")`, and of type `"datetime64[us]"`.
  > - `time_ubs`: Upper bound on data acquisition times, with dimensions `("observable", "randomization")`, and of type `"datetime64[us]"`.

- Coordinates:

  > - `unbound_path`: The unbound path (with `fragment_depth=None`) for each observable, along dimension `("observable",)`, of type `Path`.
  > - `fragment_depth`: Integer array of fragment depths along dimension `("observable",)`.

**Parameters**

**dataset** – A dataset with the above formatting.

### \_\_init\_\_

`__init__(dataset: Dataset)`

## Methods

|                                                                                                                                                                        |                                                 |
| ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------- |
| [`__init__`](#qiskit_noise_learning.data.ObservableData.__init__ "qiskit_noise_learning.data.ObservableData.__init__")(dataset)                                        |                                                 |
| [`filter_time`](#qiskit_noise_learning.data.ObservableData.filter_time "qiskit_noise_learning.data.ObservableData.filter_time")(lb, ub)                                | Filter to data gathered within the time bounds. |
| [`from_arrays`](#qiskit_noise_learning.data.ObservableData.from_arrays "qiskit_noise_learning.data.ObservableData.from_arrays")(unbound\_paths, fragment\_depths, ...) | Instantiate from data specified as arrays.      |
| [`merge`](#qiskit_noise_learning.data.ObservableData.merge "qiskit_noise_learning.data.ObservableData.merge")(other)                                                   | Merge observable data into a single instance.   |

## Attributes

|                                                                                                                                                   |                               |
| ------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------- |
| `dataset`                                                                                                                                         |                               |
| [`observable_values`](#qiskit_noise_learning.data.ObservableData.observable_values "qiskit_noise_learning.data.ObservableData.observable_values") | Observables data array.       |
| [`time_lbs`](#qiskit_noise_learning.data.ObservableData.time_lbs "qiskit_noise_learning.data.ObservableData.time_lbs")                            | Time lower bounds data array. |
| [`time_ubs`](#qiskit_noise_learning.data.ObservableData.time_ubs "qiskit_noise_learning.data.ObservableData.time_ubs")                            | Time upper bounds data array. |

### from\_arrays

*classmethod* `from_arrays(unbound_paths: list[Path], fragment_depths: ndarray[int], observable_values: ndarray[float64], time_lbs: ndarray[datetime64], time_ubs: ndarray[datetime64])`

Instantiate from data specified as arrays.

**Parameters**

- **unbound\_paths** – The unbound paths corresponding to the observables.
- **fragment\_depths** – The fragment depths for each observable.
- **observable\_values** – A 2d numpy array of `floats` with axes `("observable", "randomization")`.
- **time\_lbs** – A lower bound on the data collection time for each observable and randomization. Has axes `("observable", "randomization")`.
- **time\_ubs** – Upper bounds on the data collection time for each observable and randomization. Has axes `("observable", "randomization")`.

### observable\_values

Type: `DataArray`

Observables data array.

### time\_lbs

Type: `DataArray`

Time lower bounds data array.

### time\_ubs

Type: `DataArray`

Time upper bounds data array.

### merge

`merge(other: Self) → Self`

Merge observable data into a single instance.

**Parameters**

**other** – The other observable data set.

**Returns**

The merged data.

### filter\_time

`filter_time(lb: datetime64, ub: datetime64) → Self`

Filter to data gathered within the time bounds.

**Parameters**

- **lb** – The time lower bound (inclusive).
- **ub** – The time upper bound (inclusive).

**Returns**

The time filtered version of self.