---
title: group_coeff_means (latest version)
description: API reference for qiskit_fermions.operators.terms.group_coeff_means in the latest version of qiskit-fermions
source: https://quantum.cloud.ibm.com/docs/en/api/qiskit-fermions/operators-terms-group-coeff-means
---

# group\_coeff\_means

`group_coeff_means(op)`

Returns the mean absolute coefficient magnitude of each group.

The `i`-th entry is the sum of `abs(coeff)` over the terms in group `i`, divided by the number of terms in that group. If the operator tracks no groups, this returns `None`.

This is the sampling weight of a randomized product formula (for example, qDRIFT) that draws whole groups rather than individual terms: it is the magnitude of one *atomic* group, which is the relevant scale because grouping is what makes each sampled piece Hermitian (and hence its time evolution unitary) in the first place.

Computing it natively is considerably cheaper than reducing `get_coeffs()` and `groups` in NumPy, because those two accessors each copy one value per *ungrouped* term out of the operator only for it to be aggregated back down to one value per group, whereas this returns just the `num_groups()` reduced values.

> **Note**
>
> A group index that no term carries weighs `0.0`, which keeps it out of the sample.

```pycon
>>> from qiskit_fermions.operators import FermionOperator
>>> from qiskit_fermions.operators.terms.grouping import group_coeff_means
>>> op = FermionOperator(
...     [1.0, 2.0, -1.0, -2.0],
...     [True, False, True, False, True, False, True, False],
...     [0, 1, 2, 3, 1, 0, 3, 2],
...     [0, 2, 4, 6, 8],
... )
>>> print(group_coeff_means(op))
None
>>> op.groups = [0, 1, 0, 1]
>>> group_coeff_means(op)
[1.0, 2.0]
```

**Parameters**

**op** – the operator whose groups to reduce.

**Returns**

The mean absolute coefficient magnitude of each group index, or `None` if the operator tracks no groups.

**Raises**

[**TypeError**](https://docs.python.org/3/builtins/exceptions.html#TypeError) – if `op` is not a supported operator type (see [`OperatorTrait`](/docs/api/qiskit-fermions/operators-operator-trait "qiskit_fermions.operators.OperatorTrait")).