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0.12.0 | ||
0.13.0 |
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# Copyright 2023 Pulser Development Team | ||
# | ||
# Licensed under the Apache License, Version 2.0 (the "License"); | ||
# you may not use this file except in compliance with the License. | ||
# You may obtain a copy of the License at | ||
# | ||
# http://www.apache.org/licenses/LICENSE-2.0 | ||
# | ||
# Unless required by applicable law or agreed to in writing, software | ||
# distributed under the License is distributed on an "AS IS" BASIS, | ||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
# See the License for the specific language governing permissions and | ||
# limitations under the License. | ||
"""Classes to store measurement results.""" | ||
from __future__ import annotations | ||
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from abc import ABC, abstractmethod | ||
from collections import Counter | ||
from dataclasses import dataclass | ||
from typing import Any | ||
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import matplotlib.pyplot as plt | ||
import numpy as np | ||
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from pulser.register import QubitId | ||
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@dataclass | ||
class Result(ABC): | ||
"""Base class for storing the result of a sequence run.""" | ||
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atom_order: tuple[QubitId, ...] | ||
meas_basis: str | ||
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@property | ||
def sampling_dist(self) -> dict[str, float]: | ||
"""Sampling distribution of the measured bitstring. | ||
Args: | ||
atom_order: The order of the atoms in the bitstrings that | ||
represent the measured states. | ||
meas_basis: The measurement basis. | ||
""" | ||
n = self._size | ||
return { | ||
np.binary_repr(ind, width=n): prob | ||
for ind, prob in enumerate(self._weights()) | ||
if prob != 0 | ||
} | ||
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@property | ||
@abstractmethod | ||
def sampling_errors(self) -> dict[str, float]: | ||
"""The sampling error associated to each bitstring's sampling rate. | ||
Uses the standard error of the mean as a quantifier for sampling error. | ||
""" | ||
pass | ||
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@property | ||
def _size(self) -> int: | ||
return len(self.atom_order) | ||
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@abstractmethod | ||
def _weights(self) -> np.ndarray: | ||
"""The sampling rate for every state in an ordered array.""" | ||
pass | ||
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def get_samples(self, n_samples: int) -> Counter[str]: | ||
"""Takes multiple samples from the sampling distribution. | ||
Args: | ||
n_samples: Number of samples to return. | ||
Returns: | ||
Samples of bitstrings corresponding to measured quantum states. | ||
""" | ||
dist = np.random.multinomial(n_samples, self._weights()) | ||
return Counter( | ||
{ | ||
np.binary_repr(i, self._size): dist[i] | ||
for i in np.nonzero(dist)[0] | ||
} | ||
) | ||
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def get_state(self) -> Any: | ||
"""Gets the quantum state associated with the result. | ||
Can only be defined for emulation results that don't resort to | ||
sampling a quantum state (which is the case for certain types of | ||
noise). | ||
""" | ||
raise NotImplementedError( | ||
f"`{self.__class__.__name__}.get_state()` is not implemented." | ||
) | ||
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def plot_histogram( | ||
self, | ||
min_rate: float = 0.001, | ||
max_n_bitstrings: int | None = None, | ||
show: bool = True, | ||
) -> None: | ||
"""Plots the result in an histogram. | ||
Args: | ||
min_rate: The minimum sampling rate a bitstring must have to be | ||
displayed. | ||
max_n_bitstrings: An optional limit on the number of bitrstrings | ||
displayed. | ||
show: Whether or not to call `plt.show()` before returning. | ||
""" | ||
# TODO: Add error bars | ||
probs = np.array( | ||
Counter(self.sampling_dist).most_common(max_n_bitstrings), | ||
dtype=object, | ||
) | ||
probs = probs[probs[:, 1] >= min_rate] | ||
plt.bar(probs[:, 0], probs[:, 1]) | ||
plt.xticks(rotation="vertical") | ||
plt.ylabel("Probabilites") | ||
if show: | ||
plt.show() | ||
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@dataclass | ||
class SampledResult(Result): | ||
"""Represents the result of a run from a series of samples. | ||
Args: | ||
atom_order: The order of the atoms in the bitstrings that | ||
represent the measured states. | ||
meas_basis: The measurement basis. | ||
bitstring_counts: The number of times each bitstring was | ||
measured. | ||
""" | ||
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bitstring_counts: dict[str, int] | ||
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def __post_init__(self) -> None: | ||
self.n_samples = sum(self.bitstring_counts.values()) | ||
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@property | ||
def sampling_errors(self) -> dict[str, float]: | ||
"""The sampling error associated to each bitstring's sampling rate. | ||
Uses the standard error of the mean as a quantifier for sampling error. | ||
""" | ||
return { | ||
bitstr: np.sqrt(p * (1 - p) / self.n_samples) | ||
for bitstr, p in self.sampling_dist.items() | ||
} | ||
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def _weights(self) -> np.ndarray: | ||
weights = np.zeros(2**self._size) | ||
for bitstr, counts in self.bitstring_counts.items(): | ||
weights[int(bitstr, base=2)] = counts / self.n_samples | ||
return weights / sum(weights) |
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