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ift
NIFTy
Commits
af4c67aa
Commit
af4c67aa
authored
Dec 29, 2017
by
Martin Reinecke
Browse files
add forgotten file
parent
af9bdeb9
Pipeline
#23264
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in 4 minutes and 36 seconds
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Side-by-side
nifty/operators/scaling_operator.py
0 → 100644
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af4c67aa
# 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) 2013-2017 Max-Planck-Society
#
# NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik
# and financially supported by the Studienstiftung des deutschen Volkes.
from
__future__
import
division
import
numpy
as
np
from
..field
import
Field
from
..domain_tuple
import
DomainTuple
from
.endomorphic_operator
import
EndomorphicOperator
from
..utilities
import
cast_iseq_to_tuple
from
..
import
dobj
class
ScalingOperator
(
EndomorphicOperator
):
""" NIFTY class for an operator which multiplies a Field with a scalar.
The NIFTY ScalingOperator class is a subclass derived from the
EndomorphicOperator. It multiplies an input field with a given factor.
Parameters
----------
factor : scalar
The multiplication factor
domain : tuple of DomainObjects
The domain on which the Operator's input Field lives.
Attributes
----------
domain : DomainTuple
The domain on which the Operator's input Field lives.
"""
def
__init__
(
self
,
factor
,
domain
):
super
(
ScalingOperator
,
self
).
__init__
()
if
not
np
.
isscalar
(
factor
):
raise
TypeError
(
"Scalar required"
)
self
.
_factor
=
factor
self
.
_domain
=
DomainTuple
.
make
(
domain
)
def
apply
(
self
,
x
,
mode
):
self
.
_check_input
(
x
,
mode
)
if
mode
==
self
.
TIMES
:
return
x
*
self
.
_factor
elif
mode
==
self
.
ADJOINT_TIMES
:
return
x
*
np
.
conj
(
self
.
_factor
)
elif
mode
==
self
.
INVERSE_TIMES
:
return
x
*
(
1.
/
self
.
_factor
)
else
:
return
x
*
(
1.
/
np
.
conj
(
self
.
_factor
))
@
property
def
domain
(
self
):
return
self
.
_domain
@
property
def
capability
(
self
):
return
(
self
.
TIMES
|
self
.
ADJOINT_TIMES
|
self
.
INVERSE_TIMES
|
self
.
ADJOINT_INVERSE_TIMES
)
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