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generic_sampler.py
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Mon, Nov 11, 16:43

generic_sampler.py
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# Copyright (C) 2018 by the RROMPy authors
#
# This file is part of RROMPy.
#
# RROMPy is free software: you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# RROMPy 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 RROMPy. If not, see <http://www.gnu.org/licenses/>.
#
import numpy as np
from abc import abstractmethod
from rrompy.utilities.base.types import List, paramList
from rrompy.utilities.exception_manager import RROMPyException, RROMPyAssert
from rrompy.parameter import checkParameterList
__all__ = ['GenericSampler']
class GenericSampler:
"""ABSTRACT. Generic generator of sample points."""
def __init__(self, lims:paramList, scalingExp : List[float] = None):
self.lims = lims
self.scalingExp = scalingExp
def name(self) -> str:
return self.__class__.__name__
def __str__(self) -> str:
return "{}[{}_{}]".format(self.name(), self.lims[0], self.lims[1])
def __repr__(self) -> str:
return self.__str__() + " at " + hex(id(self))
def __eq__(self, other) -> bool:
return self.__dict__ == other.__dict__
@property
def npar(self):
"""Number of parameters."""
return self._lims.shape[1]
def normalFoci(self, d : int = 0):
return [-1., 1.]
def groundPotential(self, d : int = 0):
fp = self.normalFoci(d)[1]
fpa = np.abs(fp)
if np.isclose(fpa, 0.) or np.isclose(fpa, 1.): return 1.
return (1. + np.abs(1. - fp ** 2.) ** .5) / fpa
@property
def lims(self):
"""Value of lims."""
return self._lims
@lims.setter
def lims(self, lims):
lims = checkParameterList(lims)[0]
if len(lims) != 2:
raise RROMPyException("2 limits must be specified.")
self._lims = lims
@property
def scalingExp(self):
"""Value of scalingExp."""
return self._scalingExp
@scalingExp.setter
def scalingExp(self, scalingExp):
if scalingExp is None:
scalingExp = [1.] * self.npar
if not hasattr(scalingExp, "__len__"): scalingExp = [scalingExp]
RROMPyAssert(self.npar, len(scalingExp), "Number of scaling terms")
self._scalingExp = np.array(scalingExp)
@abstractmethod
def generatePoints(self, n:int, reorder : bool = True) -> paramList:
"""Array of points."""
pass

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