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# qiskit.quantum_info.SparsePauliOp.sort¶

SparsePauliOp.sort(weight=False)[ソース]

Sort the rows of the table.

After sorting the coefficients using numpy’s argsort, sort by Pauli. Pauli sort takes precedence. If Pauli is the same, it will be sorted by coefficient. By using the weight kwarg the output can additionally be sorted by the number of non-identity terms in the Pauli, where the set of all Pauli’s of a given weight are still ordered lexicographically.

Example

Here is an example of how to use SparsePauliOp sort.

```import numpy as np
from qiskit.quantum_info import SparsePauliOp

# 2-qubit labels
labels = ["XX", "XX", "XX", "YI", "II", "XZ", "XY", "XI"]
# coeffs
coeffs = [2.+1.j, 2.+2.j, 3.+0.j, 3.+0.j, 4.+0.j, 5.+0.j, 6.+0.j, 7.+0.j]

# init
spo = SparsePauliOp(labels, coeffs)
print('Initial Ordering')
print(spo)

# Lexicographic Ordering
srt = spo.sort()
print('Lexicographically sorted')
print(srt)

# Lexicographic Ordering
srt = spo.sort(weight=False)
print('Lexicographically sorted')
print(srt)

# Weight Ordering
srt = spo.sort(weight=True)
print('Weight sorted')
print(srt)
```
```Initial Ordering
SparsePauliOp(['XX', 'XX', 'XX', 'YI', 'II', 'XZ', 'XY', 'XI'],
coeffs=[2.+1.j, 2.+2.j, 3.+0.j, 3.+0.j, 4.+0.j, 5.+0.j, 6.+0.j, 7.+0.j])
Lexicographically sorted
SparsePauliOp(['II', 'XI', 'XX', 'XX', 'XX', 'XY', 'XZ', 'YI'],
coeffs=[4.+0.j, 7.+0.j, 2.+1.j, 2.+2.j, 3.+0.j, 6.+0.j, 5.+0.j, 3.+0.j])
Lexicographically sorted
SparsePauliOp(['II', 'XI', 'XX', 'XX', 'XX', 'XY', 'XZ', 'YI'],
coeffs=[4.+0.j, 7.+0.j, 2.+1.j, 2.+2.j, 3.+0.j, 6.+0.j, 5.+0.j, 3.+0.j])
Weight sorted
SparsePauliOp(['II', 'XI', 'YI', 'XX', 'XX', 'XX', 'XY', 'XZ'],
coeffs=[4.+0.j, 7.+0.j, 3.+0.j, 2.+1.j, 2.+2.j, 3.+0.j, 6.+0.j, 5.+0.j])
```
パラメータ
• weight (bool) – optionally sort by weight if True (Default: False).

• sorted (By using the weight kwarg the output can additionally be) –

• Pauli. (by the number of non-identity terms in the) –

a sorted copy of the original table.

SparsePauliOp