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ift
NIFTy
Commits
eb27f303
Commit
eb27f303
authored
Jan 07, 2019
by
Martin Reinecke
Browse files
remove unused code
parent
1da76afb
Changes
5
Hide whitespace changes
Inline
Side-by-side
nifty5/__init__.py
View file @
eb27f303
...
...
@@ -32,7 +32,6 @@ from .operators.harmonic_operators import (
HarmonicSmoothingOperator
)
from
.operators.field_zero_padder
import
FieldZeroPadder
from
.operators.inversion_enabler
import
InversionEnabler
from
.operators.laplace_operator
import
LaplaceOperator
from
.operators.linear_operator
import
LinearOperator
from
.operators.mask_operator
import
MaskOperator
from
.operators.offset_operator
import
OffsetOperator
...
...
@@ -42,7 +41,6 @@ from .operators.sampling_enabler import SamplingEnabler
from
.operators.sandwich_operator
import
SandwichOperator
from
.operators.scaling_operator
import
ScalingOperator
from
.operators.slope_operator
import
SlopeOperator
from
.operators.smoothness_operator
import
SmoothnessOperator
from
.operators.symmetrizing_operator
import
SymmetrizingOperator
from
.operators.block_diagonal_operator
import
BlockDiagonalOperator
from
.operators.outer_product_operator
import
OuterProduct
...
...
nifty5/operators/laplace_operator.py
deleted
100644 → 0
View file @
1da76afb
# 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) 2013-2018 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
absolute_import
,
division
,
print_function
import
numpy
as
np
from
..
import
dobj
from
..compat
import
*
from
..domain_tuple
import
DomainTuple
from
..domains.power_space
import
PowerSpace
from
..field
import
Field
from
..utilities
import
infer_space
from
.endomorphic_operator
import
EndomorphicOperator
class
LaplaceOperator
(
EndomorphicOperator
):
"""An irregular LaplaceOperator with free boundary and excluding monopole.
This LaplaceOperator implements the second derivative of a Field in
PowerSpace on logarithmic or linear scale with vanishing curvature at the
boundary, starting at the second entry of the Field. The second derivative
of the Field on the irregular grid is calculated using finite differences.
Parameters
----------
logarithmic : bool, optional
Whether smoothness is calculated on a logarithmic scale or linear scale
default : True
space : int
The index of the domain on which the operator acts
"""
def
__init__
(
self
,
domain
,
space
=
None
,
logarithmic
=
True
):
self
.
_domain
=
DomainTuple
.
make
(
domain
)
self
.
_capability
=
self
.
TIMES
|
self
.
ADJOINT_TIMES
self
.
_space
=
infer_space
(
self
.
_domain
,
space
)
if
not
isinstance
(
self
.
_domain
[
self
.
_space
],
PowerSpace
):
raise
ValueError
(
"Operator must act on a PowerSpace."
)
pos
=
self
.
domain
[
self
.
_space
].
k_lengths
.
copy
()
if
logarithmic
:
pos
[
1
:]
=
np
.
log
(
pos
[
1
:])
pos
[
0
]
=
pos
[
1
]
-
1.
self
.
_dpos
=
pos
[
1
:]
-
pos
[:
-
1
]
# defined between points
# centered distances (also has entries for the first and last point
# for convenience, but they will never affect the result)
self
.
_dposc
=
np
.
empty_like
(
pos
)
self
.
_dposc
[:
-
1
]
=
self
.
_dpos
self
.
_dposc
[
-
1
]
=
0.
self
.
_dposc
[
1
:]
+=
self
.
_dpos
self
.
_dposc
*=
0.5
def
apply
(
self
,
x
,
mode
):
self
.
_check_input
(
x
,
mode
)
axes
=
x
.
domain
.
axes
[
self
.
_space
]
axis
=
axes
[
0
]
nval
=
len
(
self
.
_dposc
)
prefix
=
(
slice
(
None
),)
*
axis
sl_l
=
prefix
+
(
slice
(
None
,
-
1
),)
# "left" slice
sl_r
=
prefix
+
(
slice
(
1
,
None
),)
# "right" slice
dpos
=
self
.
_dpos
.
reshape
((
1
,)
*
axis
+
(
nval
-
1
,))
dposc
=
self
.
_dposc
.
reshape
((
1
,)
*
axis
+
(
nval
,))
v
,
val
=
dobj
.
ensure_not_distributed
(
x
.
val
,
(
axis
,))
ret
=
np
.
empty_like
(
val
)
if
mode
==
self
.
TIMES
:
deriv
=
(
val
[
sl_r
]
-
val
[
sl_l
])
/
dpos
# defined between points
ret
[
sl_l
]
=
deriv
ret
[
prefix
+
(
-
1
,)]
=
0.
ret
[
sl_r
]
-=
deriv
ret
/=
dposc
ret
[
prefix
+
(
slice
(
None
,
2
),)]
=
0.
ret
[
prefix
+
(
-
1
,)]
=
0.
else
:
val
=
val
/
dposc
val
[
prefix
+
(
slice
(
None
,
2
),)]
=
0.
val
[
prefix
+
(
-
1
,)]
=
0.
deriv
=
(
val
[
sl_r
]
-
val
[
sl_l
])
/
dpos
# defined between points
ret
[
sl_l
]
=
deriv
ret
[
prefix
+
(
-
1
,)]
=
0.
ret
[
sl_r
]
-=
deriv
ret
=
dobj
.
from_local_data
(
x
.
shape
,
ret
,
dobj
.
distaxis
(
v
))
return
Field
(
self
.
domain
,
dobj
.
ensure_default_distributed
(
ret
))
nifty5/operators/smoothness_operator.py
deleted
100644 → 0
View file @
1da76afb
# 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) 2013-2018 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
absolute_import
,
division
,
print_function
from
..compat
import
*
from
.laplace_operator
import
LaplaceOperator
from
.scaling_operator
import
ScalingOperator
def
SmoothnessOperator
(
domain
,
strength
=
1.
,
logarithmic
=
True
,
space
=
None
):
"""An operator measuring the smoothness on an irregular grid with respect
to some scale.
This operator applies the irregular LaplaceOperator and its adjoint to some
Field over a PowerSpace which corresponds to its smoothness and weights the
result with a scale parameter sigma. For this purpose we use free boundary
conditions in the LaplaceOperator, having no curvature at both ends. In
addition the first entry is ignored as well, corresponding to the overall
mean of the map. The mean is therefore not considered in the smoothness
prior.
Parameters
----------
domain : Domain, tuple of Domain, or DomainTuple
The total domain of the operator's input and output fields
strength : nonnegative float
Specifies the strength of the SmoothnessOperator
logarithmic : bool, optional
Whether smoothness is calculated on a logarithmic scale or linear scale
default : True
space : int, optional
The index of the sub-domain on which the operator acts.
Can be omitted if `domain` only has one sub-domain.
"""
if
strength
<
0
:
raise
ValueError
(
"ERROR: strength must be nonnegative."
)
if
strength
==
0.
:
return
ScalingOperator
(
0.
,
domain
)
laplace
=
LaplaceOperator
(
domain
,
logarithmic
=
logarithmic
,
space
=
space
)
return
laplace
.
adjoint
(
laplace
).
scale
(
strength
**
2
)
test/test_operators/test_adjoint.py
View file @
eb27f303
...
...
@@ -170,16 +170,6 @@ class Consistency_Tests(unittest.TestCase):
dtype
=
dtype
))
ift
.
extra
.
consistency_check
(
op
,
dtype
,
dtype
)
@
expand
(
product
(
_pow_spaces
,
[
np
.
float64
,
np
.
complex128
]))
def
testLaplace
(
self
,
sp
,
dtype
):
op
=
ift
.
LaplaceOperator
(
sp
)
ift
.
extra
.
consistency_check
(
op
,
dtype
,
dtype
)
@
expand
(
product
(
_pow_spaces
,
[
np
.
float64
,
np
.
complex128
]))
def
testSmoothness
(
self
,
sp
,
dtype
):
op
=
ift
.
SmoothnessOperator
(
sp
)
ift
.
extra
.
consistency_check
(
op
,
dtype
,
dtype
)
@
expand
(
product
(
_h_spaces
+
_p_spaces
+
_pow_spaces
,
[
np
.
float64
,
np
.
complex128
]))
def
testGeometryRemover
(
self
,
sp
,
dtype
):
...
...
test/test_operators/test_laplace_operator.py
deleted
100644 → 0
View file @
1da76afb
# 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) 2013-2018 Max-Planck-Society
#
# NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik
# and financially supported by the Studienstiftung des deutschen Volkes.
import
unittest
from
itertools
import
product
from
test.common
import
expand
import
nifty5
as
ift
import
numpy
as
np
from
numpy.testing
import
assert_allclose
class
LaplaceOperatorTests
(
unittest
.
TestCase
):
@
expand
(
product
([
None
,
False
,
True
],
[
False
,
True
],
[
10
,
100
,
1000
]))
def
test_Laplace
(
self
,
log1
,
log2
,
sz
):
s
=
ift
.
RGSpace
(
sz
,
harmonic
=
True
)
bb
=
ift
.
PowerSpace
.
useful_binbounds
(
s
,
logarithmic
=
log1
)
p
=
ift
.
PowerSpace
(
s
,
binbounds
=
bb
)
L
=
ift
.
LaplaceOperator
(
p
,
logarithmic
=
log2
)
fp
=
ift
.
Field
.
from_random
(
"normal"
,
domain
=
p
,
dtype
=
np
.
float64
)
assert_allclose
(
L
(
fp
).
vdot
(
L
(
fp
)),
L
.
adjoint_times
(
L
(
fp
)).
vdot
(
fp
))
@
expand
(
product
([
10
,
100
,
1000
]))
def
test_Laplace2
(
self
,
sz
):
s
=
ift
.
RGSpace
(
sz
,
harmonic
=
True
,
distances
=
0.764
)
bb
=
ift
.
PowerSpace
.
useful_binbounds
(
s
,
logarithmic
=
False
)
p
=
ift
.
PowerSpace
(
s
,
binbounds
=
bb
)
foo
=
ift
.
PS_field
(
p
,
lambda
k
:
2
*
k
**
2
)
L
=
ift
.
LaplaceOperator
(
p
,
logarithmic
=
False
)
result
=
np
.
full
(
p
.
shape
,
2
*
2.
)
result
[
0
]
=
result
[
1
]
=
result
[
-
1
]
=
0.
assert_allclose
(
L
(
foo
).
to_global_data
(),
result
)
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