mindquantum.core.gates.MeasureResult

class mindquantum.core.gates.MeasureResult

Measurement result container.

Examples

>>> from mindquantum.algorithm.library import qft
>>> from mindquantum.simulator import Simulator
>>> sim = Simulator('mqvector', 2)
>>> res = sim.sampling(qft(range(2)).measure_all(), shots=1000, seed=42)
>>> res
shots: 1000
Keys: q1 q0│0.00   0.065        0.13       0.194       0.259       0.324
───────────┼───────────┴───────────┴───────────┴───────────┴───────────┴
         00│▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒
           │
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           │
         10│▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒
           │
         11│▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓
           │
{'00': 230, '01': 254, '10': 257, '11': 259}
>>> res.data
{'00': 230, '01': 254, '10': 257, '11': 259}

add_measure(measure)

Add a measurement gate into this measurement result container.

Measure key should be unique in this measurement result container.

Parameters

measure (Union[Iterable, Measure]) – One or more measure gates.

collect_data(samples)

Collect the measured bit string.

Parameters

samples (numpy.ndarray) – A two dimensional (N x M) numpy array that stores the sampling bit string in 0 or 1, where N represents the number of shot times, and M represents the number of keys in this measurement container

property data

Get the sampling data.

Returns

dict, The sampling data.

property keys_map

Reverse mapping for the keys.

reverse_endian()

Reverse the endianness of the measurement result.

This function reverses the order of bits in each bit string of the measurement result, and also reverses the order of keys.

Returns

MeasureResult, A new MeasureResult object with reversed endian.

select_keys(*keys)

Select certain measurement keys from this measurement container.

Parameters

keys (tuple[str]) – The key you want to select.

Examples

>>> from mindquantum.algorithm.library import qft
>>> from mindquantum.core.gates import H
>>> from mindquantum.simulator import Simulator
>>> circ = qft(range(2)).measure('q0_0', 0).measure('q1_0', 1)
>>> circ.h(0).measure('q0_1', 0)
>>> circ
      ┏━━━┓ ┏━━━━━━━━━┓         ┍━━━━━━━━┑ ┏━━━┓ ┍━━━━━━━━┑
q0: ──┨ H ┠─┨ PS(π/2) ┠───────╳─┤ M q0_0 ├─┨ H ┠─┤ M q0_1 ├───
      ┗━━━┛ ┗━━━━┳━━━━┛       ┃ ┕━━━━━━━━┙ ┗━━━┛ ┕━━━━━━━━┙
                 ┃      ┏━━━┓ ┃ ┍━━━━━━━━┑
q1: ─────────────■──────┨ H ┠─╳─┤ M q1_0 ├────────────────────
                        ┗━━━┛   ┕━━━━━━━━┙
>>> sim = Simulator('mqvector', circ.n_qubits)
>>> res = sim.sampling(circ, shots=500, seed=42)
>>> new_res = res.select_keys('q0_1', 'q1_0')
>>> new_res
shots: 500
Keys: q1_0 q0_1│0.00   0.068       0.136       0.204       0.272        0.34
───────────────┼───────────┴───────────┴───────────┴───────────┴───────────┴
             00│▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒
               │
             01│▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒▒
               │
             10│▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓
               │
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               │
{'00': 127, '01': 107, '10': 136, '11': 130}

svg(style=None)

Display current measurement result into SVG picture in jupyter notebook.

Parameters

style (dict, str) – the style to set svg style. Currently, we support 'official'. Default: None.

to_json(filename=None)

Convert the measure result to JSON format and optionally save to a file.

Parameters

filename (str) – The name of the file to save the JSON. Default: None.

Returns

str, JSON representation of the object.