# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# 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 General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
#
# Copyright(C) 2013-2020 Max-Planck-Society
#
# NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik.
from ..multi_domain import MultiDomain
from ..multi_field import MultiField
from ..utilities import check_dtype_or_none, check_object_identity, indent
from .endomorphic_operator import EndomorphicOperator
from .linear_operator import LinearOperator
[docs]
class BlockDiagonalOperator(EndomorphicOperator):
"""
Parameters
----------
domain : MultiDomain
Domain and target of the operator.
operators : dict
Dictionary with subdomain names as keys and :class:`LinearOperator` s
as items. Any missing item will be treated as unity operator.
"""
[docs]
def __init__(self, domain, operators):
if not isinstance(domain, MultiDomain):
raise TypeError("MultiDomain expected")
self._domain = domain
self._ops = tuple(operators[key] if key in operators else None for key in domain.keys())
self._capability = self._all_ops
self._dtype = {kk: oo.sampling_dtype for kk, oo in operators.items()}
if all(vv is None for vv in self._dtype.values()):
self._dtype = None
check_dtype_or_none(self._dtype, self._domain)
for op in self._ops:
if op is not None:
if isinstance(op, LinearOperator):
if op.target is not op.domain:
raise TypeError("domain and target mismatch")
self._capability &= op.capability
else:
raise TypeError("LinearOperator expected")
[docs]
def get_sqrt(self):
ops = {}
for ii, kk in enumerate(self._domain.keys()):
if self._ops[ii] is None:
continue
ops[kk] = self._ops[ii].get_sqrt()
return BlockDiagonalOperator(self._domain, ops)
[docs]
def apply(self, x, mode):
self._check_input(x, mode)
val = tuple(op.apply(v, mode=mode) if op is not None else v
for op, v in zip(self._ops, x.values()))
return MultiField(self._domain, val)
[docs]
def draw_sample(self, from_inverse=False):
from ..sugar import from_random
val = []
for op, key in zip(self._ops, self._domain.keys()):
if op is None:
if self._dtype is None or key not in self._dtype:
raise RuntimeError("Need to specify dtype for all operators "
f"that are set to None (key: {key}).")
a = from_random(self._domain[key], 'normal', dtype=self.sampling_dtype[key])
else:
a = op.draw_sample(from_inverse)
val.append(a)
return MultiField(self._domain, tuple(val))
def _combine_chain(self, op):
check_object_identity(self._domain, op._domain)
res = {key: v1(v2)
for key, v1, v2 in zip(self._domain.keys(), self._ops, op._ops)}
return BlockDiagonalOperator(self._domain, res)
def _combine_sum(self, op, selfneg, opneg):
from ..operators.sum_operator import SumOperator
check_object_identity(self._domain, op._domain)
res = {key: SumOperator.make([v1, v2], [selfneg, opneg])
for key, v1, v2 in zip(self._domain.keys(), self._ops, op._ops)}
return BlockDiagonalOperator(self._domain, res)
[docs]
def __repr__(self):
s = []
for ii, kk in enumerate(self.domain.keys()):
if self._ops[ii] is None:
ss = f"{kk}: id"
if self._dtype is not None and kk in self._dtype:
ss += f" (sampling dtype: {self._dtype[kk]})"
s.append(ss)
else:
s.append(f'{kk}: {self._ops[ii]}')
s = "\n".join(s)
return 'BlockDiagonalOperator:\n' + indent(s)
