# Copyright 2021 IRT Saint Exupéry, https://www.irt-saintexupery.com
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser General Public
# License version 3 as published by the Free Software Foundation.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
# Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public License
# along with this program; if not, write to the Free Software Foundation,
# Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
"""Compatibility between different versions of openturns."""
from __future__ import annotations
from importlib.metadata import version
from typing import TYPE_CHECKING
from typing import Final
import openturns
from openturns import AggregatedFunction
from openturns import Basis
from openturns import BasisFactory
from packaging.version import Version
from packaging.version import parse as parse_version
if TYPE_CHECKING:
from numpy import ndarray
OT_VERSION: Final[Version] = parse_version(version("openturns"))
OT_1_23: Final[Version] = parse_version("1.21")
IS_OT_LOWER_THAN_1_20: Final[bool] = parse_version("1.20") > OT_VERSION
if parse_version("1.21") > OT_VERSION: # pragma: no cover
def create_trend_basis( # noqa: D103
basis_factory: type(BasisFactory), input_dimension: int, output_dimension: int
) -> Basis:
return basis_factory(input_dimension).build()
else:
[docs]
def create_trend_basis( # noqa: D103
basis_factory: type(BasisFactory), input_dimension: int, output_dimension: int
) -> Basis:
basis = basis_factory(input_dimension).build()
return Basis([
AggregatedFunction([basis.build(k)] * output_dimension)
for k in range(basis.getSize())
])
if not IS_OT_LOWER_THAN_1_20:
def compute_pcc(x: ndarray, y: ndarray) -> openturns.Point: # noqa: D103
return openturns.CorrelationAnalysis(x, y).computePCC()
def compute_prcc(x: ndarray, y: ndarray) -> openturns.Point: # noqa: D103
return openturns.CorrelationAnalysis(x, y).computePRCC()
def compute_pearson_correlation( # noqa: D103
x: ndarray, y: ndarray
) -> openturns.Point:
return openturns.CorrelationAnalysis(x, y).computePearsonCorrelation()
def compute_spearman_correlation( # noqa: D103
x: ndarray, y: ndarray
) -> openturns.Point:
return openturns.CorrelationAnalysis(x, y).computeSpearmanCorrelation()
def compute_src(x: ndarray, y: ndarray) -> openturns.Point: # noqa: D103
return openturns.CorrelationAnalysis(x, y).computeSRC()
def compute_srrc(x: ndarray, y: ndarray) -> openturns.Point: # noqa: D103
return openturns.CorrelationAnalysis(x, y).computeSRRC()
def compute_kendall_tau(x: ndarray, y: ndarray) -> openturns.Point: # noqa: D103
return openturns.CorrelationAnalysis(x, y).computeKendallTau()
def compute_squared_src(x: ndarray, y: ndarray) -> openturns.Point: # noqa: D103
return openturns.CorrelationAnalysis(x, y).computeSquaredSRC()
elif parse_version("1.19") <= OT_VERSION:
def compute_pcc(x: ndarray, y: ndarray) -> openturns.Point: # noqa: D103
return openturns.CorrelationAnalysis.PCC(x, y)
def compute_prcc(x: ndarray, y: ndarray) -> openturns.Point: # noqa: D103
return openturns.CorrelationAnalysis.PRCC(x, y)
def compute_pearson_correlation( # noqa: D103
x: ndarray, y: ndarray
) -> openturns.Point:
return openturns.CorrelationAnalysis.PearsonCorrelation(x, y)
def compute_spearman_correlation( # noqa: D103
x: ndarray, y: ndarray
) -> openturns.Point:
return openturns.CorrelationAnalysis.SpearmanCorrelation(x, y)
def compute_src(x: ndarray, y: ndarray) -> openturns.Point: # noqa: D103
return openturns.CorrelationAnalysis.SRC(x, y)
def compute_srrc(x: ndarray, y: ndarray) -> openturns.Point: # noqa: D103
return openturns.CorrelationAnalysis.SRRC(x, y)
def compute_kendall_tau(x: ndarray, y: ndarray) -> openturns.Point: # noqa: D103
msg = "Requires openturns>=1.20"
raise NotImplementedError(msg)
def compute_squared_src(x: ndarray, y: ndarray) -> openturns.Point: # noqa: D103
msg = "Requires openturns>=1.20"
raise NotImplementedError(msg)
else:
[docs]
def compute_pcc(x: ndarray, y: ndarray) -> openturns.Point: # noqa: D103
return openturns.CorrelationAnalysis_PCC(x, y)
[docs]
def compute_prcc(x: ndarray, y: ndarray) -> openturns.Point: # noqa: D103
return openturns.CorrelationAnalysis_PRCC(x, y)
[docs]
def compute_pearson_correlation( # noqa: D103
x: ndarray, y: ndarray
) -> openturns.Point:
return openturns.CorrelationAnalysis_PearsonCorrelation(x, y)
[docs]
def compute_spearman_correlation( # noqa: D103
x: ndarray, y: ndarray
) -> openturns.Point:
return openturns.CorrelationAnalysis_SpearmanCorrelation(x, y)
[docs]
def compute_src(x: ndarray, y: ndarray) -> openturns.Point: # noqa: D103
return openturns.CorrelationAnalysis_SRC(x, y)
[docs]
def compute_srrc(x: ndarray, y: ndarray) -> openturns.Point: # noqa: D103
return openturns.CorrelationAnalysis_SRRC(x, y)
[docs]
def compute_kendall_tau(x: ndarray, y: ndarray) -> openturns.Point: # noqa: D103
msg = "Requires openturns>=1.20"
raise NotImplementedError(msg)
[docs]
def compute_squared_src(x: ndarray, y: ndarray) -> openturns.Point: # noqa: D103
msg = "Requires openturns>=1.20"
raise NotImplementedError(msg)
