# Copyright Amazon.com Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"). You
# may not use this file except in compliance with the License. A copy of
# the License is located at
#
# http://aws.amazon.com/apache2.0/
#
# or in the "license" file accompanying this file. This file 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.
from __future__ import annotations
from decimal import Decimal
from braket.ahs.pattern import Pattern
from braket.timings.time_series import TimeSeries
[docs]
class Field:
def __init__(self, time_series: TimeSeries, pattern: Pattern | None = None) -> None:
"""A space and time dependent parameter of a program.
Args:
time_series (TimeSeries): The time series representing this field.
pattern (Pattern | None): The local pattern of real numbers.
"""
self._time_series = time_series
self._pattern = pattern
@property
def time_series(self) -> TimeSeries:
"""TimeSeries: The time series representing this field."""
return self._time_series
@property
def pattern(self) -> Pattern | None:
"""Pattern | None: The local pattern of real numbers."""
return self._pattern
[docs]
def discretize(
self,
time_resolution: Decimal | None = None,
value_resolution: Decimal | None = None,
pattern_resolution: Decimal | None = None,
) -> Field:
"""Creates a discretized version of the field,
where time, value and pattern are rounded to the
closest multiple of their corresponding resolutions.
Args:
time_resolution (Decimal | None): Time resolution
value_resolution (Decimal | None): Value resolution
pattern_resolution (Decimal | None): Pattern resolution
Returns:
Field: A new discretized field.
"""
discretized_time_series = self.time_series.discretize(time_resolution, value_resolution)
if self.pattern is None:
discretized_pattern = None
else:
discretized_pattern = self.pattern.discretize(pattern_resolution)
return Field(time_series=discretized_time_series, pattern=discretized_pattern)
[docs]
@staticmethod
def from_lists(times: list[Decimal], values: list[Decimal], pattern: list[Decimal]) -> Field:
"""Builds Field from lists of time points, values and pattern.
Args:
times (list[Decimal]): The time points of the field
values (list[Decimal]): The values of the field
pattern (list[Decimal]): The pattern of the field
Raises:
ValueError: If the length of times and values differs.
Returns:
Field: Field.
"""
if not (len(times) == len(values)):
raise ValueError(
f"The lengths of the lists for times({len(times)}) and values({len(values)})\
are not equal"
)
time_series = TimeSeries.from_lists(times=times, values=values)
return Field(time_series=time_series, pattern=Pattern(pattern))