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generic_sampler.py
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Fri, May 3, 09:34

generic_sampler.py
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# Copyright (C) 2018-2020 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, DictAny, paramList
from rrompy.utilities.expression import expressionEvaluator
from rrompy.utilities.exception_manager import RROMPyException
from rrompy.parameter import checkParameterList, parameterMap as pMap
from rrompy.parameter.parameter_list import emptyParameterList
__all__ = ['GenericSampler']
class GenericSampler:
"""ABSTRACT. Generic generator of sample points."""
def __init__(self, lims:paramList, parameterMap : DictAny = 1.):
self.lims = lims
self.parameterMap = pMap(parameterMap, self.npar)
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:
if (not hasattr(other, "__dict__")
or self.__dict__.keys() != other.__dict__.keys()):
return False
for key in self.__dict__:
val = self.__dict__[key]
if isinstance(val, (np.ndarray,)):
if not np.allclose(val, other.__dict__[key]): return False
else:
if val != other.__dict__[key]: return False
return True
@property
def npar(self):
"""Number of parameters."""
return self._lims.shape[1]
def normalFoci(self, d : int = 0):
return [-1., 1.]
@property
def lims(self):
"""Value of lims."""
return self._lims
@lims.setter
def lims(self, lims):
lims = checkParameterList(lims)
if len(lims) != 2:
raise RROMPyException("2 limits must be specified.")
self._lims = lims
def mapParameterList(self, mu:paramList, direct : str = "F",
idx : List[int] = None) -> paramList:
if idx is None: idx = np.arange(self.npar)
muMapped = checkParameterList(mu, len(idx))
for j, d in enumerate(idx):
muMapped.data[:, j] = expressionEvaluator(
self.parameterMap[direct][d],
muMapped(j)).flatten()
return muMapped
def reset(self):
self.points = emptyParameterList()
@abstractmethod
def generatePoints(self, n:int, reorder : bool = True) -> paramList:
"""Array of points."""
pass

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