Source code for mitiq.cdr.data_regression

# Copyright (C) Unitary Fund
#
# This source code is licensed under the GPL license (v3) found in the
# LICENSE file in the root directory of this source tree.

"""The data regression portion of Clifford data regression."""

from typing import Sequence

import numpy as np
import numpy.typing as npt


[docs] def linear_fit_function( x_data: npt.NDArray[np.float64], params: Sequence[float] ) -> float: r"""Returns :math:`y(x) = a_1 x_1 + \cdots + a_n x_n + b`. Args: x_data: The independent variables $x_1, ..., x_n$. In CDR, these are nominally the noisy expectation values to perform regression on. params: Parameters $a_1, ..., a_n, b$ of the linear fit. Note the $b$ parameter is the intercept of the fit. """ return sum(a * x for a, x in zip(params, x_data)) + params[-1]
[docs] def linear_fit_function_no_intercept( x_data: npt.NDArray[np.float64], params: Sequence[float] ) -> float: r"""Returns :math:`y(x) = a_1 x_1 + \cdots + a_n x_n`. Args: x_data: The independent variables $x_1, ..., x_n$. In CDR, these are nominally the noisy expectation values to perform regression on. params: Parameters $a_1, ..., a_n$ of the linear fit. """ return sum(a * x for a, x in zip(params, x_data))