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ift
NIFTy
Commits
cb10770a
Commit
cb10770a
authored
Sep 25, 2017
by
Martin Reinecke
Browse files
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try operators with fixed input domain
parent
fae648b9
Pipeline
#18611
passed with stage
in 4 minutes and 9 seconds
Changes
25
Pipelines
1
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Showing
25 changed files
with
281 additions
and
422 deletions
+281
-422
demos/critical_filtering.py
demos/critical_filtering.py
+4
-4
demos/log_normal_wiener_filter.py
demos/log_normal_wiener_filter.py
+1
-1
demos/paper_demos/cartesian_wiener_filter.py
demos/paper_demos/cartesian_wiener_filter.py
+14
-10
demos/paper_demos/wiener_filter.py
demos/paper_demos/wiener_filter.py
+1
-1
demos/wiener_filter_via_curvature.py
demos/wiener_filter_via_curvature.py
+1
-1
demos/wiener_filter_via_hamiltonian.py
demos/wiener_filter_via_hamiltonian.py
+4
-4
nifty/domain_tuple.py
nifty/domain_tuple.py
+6
-0
nifty/field.py
nifty/field.py
+3
-2
nifty/library/critical_filter/critical_power_curvature.py
nifty/library/critical_filter/critical_power_curvature.py
+1
-1
nifty/library/log_normal_wiener_filter/log_normal_wiener_filter_curvature.py
...ormal_wiener_filter/log_normal_wiener_filter_curvature.py
+1
-1
nifty/library/wiener_filter/wiener_filter_curvature.py
nifty/library/wiener_filter/wiener_filter_curvature.py
+1
-1
nifty/operators/composed_operator/composed_operator.py
nifty/operators/composed_operator/composed_operator.py
+23
-56
nifty/operators/diagonal_operator/diagonal_operator.py
nifty/operators/diagonal_operator/diagonal_operator.py
+39
-33
nifty/operators/endomorphic_operator/endomorphic_operator.py
nifty/operators/endomorphic_operator/endomorphic_operator.py
+12
-26
nifty/operators/fft_operator/fft_operator.py
nifty/operators/fft_operator/fft_operator.py
+35
-43
nifty/operators/invertible_operator_mixin/invertible_operator_mixin.py
...rs/invertible_operator_mixin/invertible_operator_mixin.py
+4
-4
nifty/operators/laplace_operator/laplace_operator.py
nifty/operators/laplace_operator/laplace_operator.py
+23
-28
nifty/operators/linear_operator/linear_operator.py
nifty/operators/linear_operator/linear_operator.py
+31
-102
nifty/operators/response_operator/response_operator.py
nifty/operators/response_operator/response_operator.py
+18
-13
nifty/operators/smoothing_operator/direct_smoothing_operator.py
...operators/smoothing_operator/direct_smoothing_operator.py
+15
-18
nifty/operators/smoothing_operator/fft_smoothing_operator.py
nifty/operators/smoothing_operator/fft_smoothing_operator.py
+21
-25
nifty/operators/smoothness_operator/smoothness_operator.py
nifty/operators/smoothness_operator/smoothness_operator.py
+7
-23
nifty/sugar.py
nifty/sugar.py
+9
-5
test/test_operators/test_composed_operator.py
test/test_operators/test_composed_operator.py
+6
-16
test/test_operators/test_fft_operator.py
test/test_operators/test_fft_operator.py
+1
-4
No files found.
demos/critical_filtering.py
View file @
cb10770a
...
...
@@ -16,17 +16,17 @@ def plot_parameters(m, t, p, p_d):
class
AdjointFFTResponse
(
ift
.
LinearOperator
):
def
__init__
(
self
,
FFT
,
R
,
default_spaces
=
None
):
super
(
AdjointFFTResponse
,
self
).
__init__
(
default_spaces
)
def
__init__
(
self
,
FFT
,
R
):
super
(
AdjointFFTResponse
,
self
).
__init__
()
self
.
_domain
=
FFT
.
target
self
.
_target
=
R
.
target
self
.
R
=
R
self
.
FFT
=
FFT
def
_times
(
self
,
x
,
spaces
=
None
):
def
_times
(
self
,
x
):
return
self
.
R
(
self
.
FFT
.
adjoint_times
(
x
))
def
_adjoint_times
(
self
,
x
,
spaces
=
None
):
def
_adjoint_times
(
self
,
x
):
return
self
.
FFT
(
self
.
R
.
adjoint_times
(
x
))
@
property
...
...
demos/log_normal_wiener_filter.py
View file @
cb10770a
...
...
@@ -35,7 +35,7 @@ if __name__ == "__main__":
#mask.val[N10*5:N10*9, N10*5:N10*9] = 0.
R
=
ift
.
ResponseOperator
(
signal_space
,
sigma
=
(
response_sigma
,),
exposure
=
(
mask
,))
#|\label{code:wf_response}|
data_domain
=
R
.
target
[
0
]
R_harmonic
=
ift
.
ComposedOperator
([
fft
,
R
]
,
default_spaces
=
[
0
,
0
]
)
R_harmonic
=
ift
.
ComposedOperator
([
fft
,
R
])
# Setting up the noise covariance and drawing a random noise realization
ndiag
=
ift
.
Field
(
data_domain
,
mock_signal
.
var
()
/
signal_to_noise
).
weight
(
1
)
...
...
demos/paper_demos/cartesian_wiener_filter.py
View file @
cb10770a
...
...
@@ -22,7 +22,17 @@ if __name__ == "__main__":
signal_space_1
=
ift
.
RGSpace
([
N_pixels_1
],
distances
=
L_1
/
N_pixels_1
)
harmonic_space_1
=
signal_space_1
.
get_default_codomain
()
fft_1
=
ift
.
FFTOperator
(
harmonic_space_1
,
target
=
signal_space_1
)
# Setting up the geometry |\label{code:wf_geometry}|
L_2
=
2.
# Total side-length of the domain
N_pixels_2
=
512
# Grid resolution (pixels per axis)
signal_space_2
=
ift
.
RGSpace
([
N_pixels_2
],
distances
=
L_2
/
N_pixels_2
)
harmonic_space_2
=
signal_space_2
.
get_default_codomain
()
signal_domain
=
ift
.
DomainTuple
.
make
((
signal_space_1
,
signal_space_2
))
mid_domain
=
ift
.
DomainTuple
.
make
((
signal_space_1
,
harmonic_space_2
))
harmonic_domain
=
ift
.
DomainTuple
.
make
((
harmonic_space_1
,
harmonic_space_2
))
fft_1
=
ift
.
FFTOperator
(
harmonic_domain
,
space
=
0
)
power_space_1
=
ift
.
PowerSpace
(
harmonic_space_1
)
mock_power_1
=
ift
.
Field
(
power_space_1
,
val
=
power_spectrum_1
(
power_space_1
.
k_lengths
))
...
...
@@ -39,13 +49,7 @@ if __name__ == "__main__":
a
=
4
*
correlation_length_2
*
field_variance_2
**
2
return
a
/
(
1
+
k
*
correlation_length_2
)
**
2.5
# Setting up the geometry |\label{code:wf_geometry}|
L_2
=
2.
# Total side-length of the domain
N_pixels_2
=
512
# Grid resolution (pixels per axis)
signal_space_2
=
ift
.
RGSpace
([
N_pixels_2
],
distances
=
L_2
/
N_pixels_2
)
harmonic_space_2
=
signal_space_2
.
get_default_codomain
()
fft_2
=
ift
.
FFTOperator
(
harmonic_space_2
,
target
=
signal_space_2
)
fft_2
=
ift
.
FFTOperator
(
mid_domain
,
space
=
1
)
power_space_2
=
ift
.
PowerSpace
(
harmonic_space_2
)
mock_power_2
=
ift
.
Field
(
power_space_2
,
val
=
power_spectrum_2
(
power_space_2
.
k_lengths
))
...
...
@@ -73,11 +77,11 @@ if __name__ == "__main__":
mask_2
=
ift
.
Field
(
signal_space_2
,
val
=
1.
)
mask_2
.
val
[
N2_10
*
7
:
N2_10
*
9
]
=
0.
R
=
ift
.
ResponseOperator
(
(
signal_space_1
,
signal_space_2
),
R
=
ift
.
ResponseOperator
(
signal_domain
,
spaces
=
(
0
,
1
),
sigma
=
(
response_sigma_1
,
response_sigma_2
),
exposure
=
(
mask_1
,
mask_2
))
#|\label{code:wf_response}|
data_domain
=
R
.
target
R_harmonic
=
ift
.
ComposedOperator
([
fft
,
R
]
,
default_spaces
=
(
0
,
1
,
0
,
1
)
)
R_harmonic
=
ift
.
ComposedOperator
([
fft
,
R
])
# Setting up the noise covariance and drawing a random noise realization
ndiag
=
ift
.
Field
(
data_domain
,
mock_signal
.
var
()
/
signal_to_noise
).
weight
(
1
)
...
...
demos/paper_demos/wiener_filter.py
View file @
cb10770a
...
...
@@ -34,7 +34,7 @@ if __name__ == "__main__":
mask
.
val
[
N10
*
5
:
N10
*
9
,
N10
*
5
:
N10
*
9
]
=
0.
R
=
ift
.
ResponseOperator
(
signal_space
,
sigma
=
(
response_sigma
,),
exposure
=
(
mask
,))
#|\label{code:wf_response}|
data_domain
=
R
.
target
[
0
]
R_harmonic
=
ift
.
ComposedOperator
([
fft
,
R
]
,
default_spaces
=
[
0
,
0
]
)
R_harmonic
=
ift
.
ComposedOperator
([
fft
,
R
])
# Setting up the noise covariance and drawing a random noise realization
ndiag
=
ift
.
Field
(
data_domain
,
mock_signal
.
var
()
/
signal_to_noise
).
weight
(
1
)
...
...
demos/wiener_filter_via_curvature.py
View file @
cb10770a
...
...
@@ -45,7 +45,7 @@ if __name__ == "__main__":
R
=
ift
.
ResponseOperator
(
signal_space
,
sigma
=
(
response_sigma
,))
data_domain
=
R
.
target
[
0
]
R_harmonic
=
ift
.
ComposedOperator
([
fft
,
R
]
,
default_spaces
=
[
0
,
0
]
)
R_harmonic
=
ift
.
ComposedOperator
([
fft
,
R
])
N
=
ift
.
DiagonalOperator
(
ift
.
Field
(
data_domain
,
mock_signal
.
var
()
/
signal_to_noise
).
weight
(
1
))
noise
=
ift
.
Field
.
from_random
(
domain
=
data_domain
,
...
...
demos/wiener_filter_via_hamiltonian.py
View file @
cb10770a
...
...
@@ -5,17 +5,17 @@ np.random.seed(42)
class
AdjointFFTResponse
(
ift
.
LinearOperator
):
def
__init__
(
self
,
FFT
,
R
,
default_spaces
=
None
):
super
(
AdjointFFTResponse
,
self
).
__init__
(
default_spaces
)
def
__init__
(
self
,
FFT
,
R
):
super
(
AdjointFFTResponse
,
self
).
__init__
()
self
.
_domain
=
FFT
.
target
self
.
_target
=
R
.
target
self
.
R
=
R
self
.
FFT
=
FFT
def
_times
(
self
,
x
,
spaces
=
None
):
def
_times
(
self
,
x
):
return
self
.
R
(
self
.
FFT
.
adjoint_times
(
x
))
def
_adjoint_times
(
self
,
x
,
spaces
=
None
):
def
_adjoint_times
(
self
,
x
):
return
self
.
FFT
(
self
.
R
.
adjoint_times
(
x
))
@
property
...
...
nifty/domain_tuple.py
View file @
cb10770a
...
...
@@ -104,3 +104,9 @@ class DomainTuple(object):
if
self
is
x
:
return
False
return
self
.
_dom
!=
x
.
_dom
def
__str__
(
self
):
res
=
"DomainTuple, len: "
+
str
(
len
(
self
.
domains
))
for
i
in
self
.
domains
:
res
+=
"
\n
"
+
str
(
i
)
return
res
nifty/field.py
View file @
cb10770a
...
...
@@ -510,8 +510,9 @@ class Field(object):
# create a diagonal operator which is capable of taking care of the
# axes-matching
from
.operators.diagonal_operator
import
DiagonalOperator
diag
=
DiagonalOperator
(
y
.
conjugate
(),
copy
=
False
)
dotted
=
diag
(
x
,
spaces
=
spaces
)
diag
=
DiagonalOperator
(
y
.
conjugate
(),
self
.
domain
,
spaces
=
spaces
,
copy
=
False
)
dotted
=
diag
(
x
)
return
fct
*
dotted
.
sum
(
spaces
=
spaces
)
def
norm
(
self
):
...
...
nifty/library/critical_filter/critical_power_curvature.py
View file @
cb10770a
...
...
@@ -32,7 +32,7 @@ class CriticalPowerCurvature(InvertibleOperatorMixin, EndomorphicOperator):
preconditioner
=
preconditioner
,
**
kwargs
)
def
_times
(
self
,
x
,
spaces
):
def
_times
(
self
,
x
):
return
self
.
T
(
x
)
+
self
.
theta
(
x
)
# ---Mandatory properties and methods---
...
...
nifty/library/log_normal_wiener_filter/log_normal_wiener_filter_curvature.py
View file @
cb10770a
...
...
@@ -58,7 +58,7 @@ class LogNormalWienerFilterCurvature(InvertibleOperatorMixin,
# ---Added properties and methods---
def
_times
(
self
,
x
,
spaces
):
def
_times
(
self
,
x
):
part1
=
self
.
S
.
inverse_times
(
x
)
# part2 = self._exppRNRexppd * x
part3
=
self
.
_fft
.
adjoint_times
(
self
.
_expp_sspace
*
self
.
_fft
(
x
))
...
...
nifty/library/wiener_filter/wiener_filter_curvature.py
View file @
cb10770a
...
...
@@ -48,7 +48,7 @@ class WienerFilterCurvature(InvertibleOperatorMixin, EndomorphicOperator):
# ---Added properties and methods---
def
_times
(
self
,
x
,
spaces
):
def
_times
(
self
,
x
):
res
=
self
.
R
.
adjoint_times
(
self
.
N
.
inverse_times
(
self
.
R
(
x
)))
res
+=
self
.
S
.
inverse_times
(
x
)
return
res
nifty/operators/composed_operator/composed_operator.py
View file @
cb10770a
...
...
@@ -29,9 +29,6 @@ class ComposedOperator(LinearOperator):
----------
operators : tuple of NIFTy Operators
The tuple of LinearOperators.
default_spaces : tuple of ints *optional*
Defines on which space(s) of a given field the Operator acts by
default (default: None)
Attributes
...
...
@@ -48,7 +45,7 @@ class ComposedOperator(LinearOperator):
TypeError
Raised if
* an element of the operator list is not an instance of the
LinearOperator
-base
class.
LinearOperator
base
class.
Notes
-----
...
...
@@ -64,8 +61,8 @@ class ComposedOperator(LinearOperator):
>>> x2 = RGSpace(10)
>>> k1 = RGRGTransformation.get_codomain(x1)
>>> k2 = RGRGTransformation.get_codomain(x2)
>>> FFT1 = FFTOperator(domain=
x1, target=k1
)
>>> FFT2 = FFTOperator(domain=
x2, target=k2
)
>>> FFT1 = FFTOperator(domain=
(x1,x2), target=(k1,x2), space=0
)
>>> FFT2 = FFTOperator(domain=
(k1,x2), target=(k1,k2), space=1
)
>>> FFT = ComposedOperator((FFT1, FFT2)
>>> f = Field.from_random('normal', domain=(x1,x2))
>>> FFT.times(f)
...
...
@@ -73,80 +70,50 @@ class ComposedOperator(LinearOperator):
"""
# ---Overwritten properties and methods---
def
__init__
(
self
,
operators
,
default_spaces
=
None
):
super
(
ComposedOperator
,
self
).
__init__
(
default_spaces
)
def
__init__
(
self
,
operators
):
super
(
ComposedOperator
,
self
).
__init__
()
for
i
in
range
(
1
,
len
(
operators
)):
if
operators
[
i
].
domain
!=
operators
[
i
-
1
].
target
:
raise
ValueError
(
"incompatible domains"
)
self
.
_operator_store
=
()
for
op
in
operators
:
if
not
isinstance
(
op
,
LinearOperator
):
raise
TypeError
(
"The elements of the operator list must be"
"instances of the LinearOperator
-base
class"
)
"instances of the LinearOperator
base
class"
)
self
.
_operator_store
+=
(
op
,)
def
_check_input_compatibility
(
self
,
x
,
spaces
,
inverse
=
False
):
"""
The input check must be disabled for the ComposedOperator, since it
is not easily forecasteable what the output of an operator-call
will look like.
"""
if
spaces
is
None
:
spaces
=
self
.
default_spaces
return
spaces
# ---Mandatory properties and methods---
@
property
def
domain
(
self
):
if
not
hasattr
(
self
,
'_domain'
):
dom
=
()
for
op
in
self
.
_operator_store
:
dom
+=
op
.
domain
.
domains
self
.
_domain
=
DomainTuple
.
make
(
dom
)
return
self
.
_domain
return
self
.
_operator_store
[
0
].
domain
@
property
def
target
(
self
):
if
not
hasattr
(
self
,
'_target'
):
tgt
=
()
for
op
in
self
.
_operator_store
:
tgt
+=
op
.
target
.
domains
self
.
_target
=
DomainTuple
.
make
(
tgt
)
return
self
.
_target
return
self
.
_operator_store
[
-
1
].
target
@
property
def
unitary
(
self
):
return
False
def
_times
(
self
,
x
,
spaces
):
return
self
.
_times_helper
(
x
,
spaces
,
func
=
'times'
)
def
_times
(
self
,
x
):
return
self
.
_times_helper
(
x
,
func
=
'times'
)
def
_adjoint_times
(
self
,
x
,
spaces
):
return
self
.
_inverse_times_helper
(
x
,
spaces
,
func
=
'adjoint_times'
)
def
_adjoint_times
(
self
,
x
):
return
self
.
_inverse_times_helper
(
x
,
func
=
'adjoint_times'
)
def
_inverse_times
(
self
,
x
,
spaces
):
return
self
.
_inverse_times_helper
(
x
,
spaces
,
func
=
'inverse_times'
)
def
_inverse_times
(
self
,
x
):
return
self
.
_inverse_times_helper
(
x
,
func
=
'inverse_times'
)
def
_adjoint_inverse_times
(
self
,
x
,
spaces
):
return
self
.
_times_helper
(
x
,
spaces
,
func
=
'adjoint_inverse_times'
)
def
_adjoint_inverse_times
(
self
,
x
):
return
self
.
_times_helper
(
x
,
func
=
'adjoint_inverse_times'
)
def
_times_helper
(
self
,
x
,
spaces
,
func
):
space_index
=
0
if
spaces
is
None
:
spaces
=
range
(
len
(
self
.
domain
))
def
_times_helper
(
self
,
x
,
func
):
for
op
in
self
.
_operator_store
:
active_spaces
=
spaces
[
space_index
:
space_index
+
len
(
op
.
domain
)]
space_index
+=
len
(
op
.
domain
)
x
=
getattr
(
op
,
func
)(
x
,
spaces
=
active_spaces
)
x
=
getattr
(
op
,
func
)(
x
)
return
x
def
_inverse_times_helper
(
self
,
x
,
spaces
,
func
):
space_index
=
0
if
spaces
is
None
:
spaces
=
range
(
len
(
self
.
target
))
rev_spaces
=
spaces
[::
-
1
]
def
_inverse_times_helper
(
self
,
x
,
func
):
for
op
in
reversed
(
self
.
_operator_store
):
active_spaces
=
rev_spaces
[
space_index
:
space_index
+
len
(
op
.
target
)]
space_index
+=
len
(
op
.
target
)
x
=
getattr
(
op
,
func
)(
x
,
spaces
=
active_spaces
[::
-
1
])
x
=
getattr
(
op
,
func
)(
x
)
return
x
nifty/operators/diagonal_operator/diagonal_operator.py
View file @
cb10770a
...
...
@@ -23,7 +23,7 @@ import numpy as np
from
...field
import
Field
from
...domain_tuple
import
DomainTuple
from
..endomorphic_operator
import
EndomorphicOperator
from
...nifty_utilities
import
cast_iseq_to_tuple
class
DiagonalOperator
(
EndomorphicOperator
):
""" NIFTY class for diagonal operators.
...
...
@@ -39,9 +39,6 @@ class DiagonalOperator(EndomorphicOperator):
The diagonal entries of the operator.
copy : boolean
Internal copy of the diagonal (default: True)
default_spaces : tuple of ints *optional*
Defines on which space(s) of a given field the Operator acts by
default (default: None)
Attributes
----------
...
...
@@ -55,9 +52,6 @@ class DiagonalOperator(EndomorphicOperator):
self_adjoint : boolean
Indicates whether the operator is self_adjoint or not.
Raises
------
See Also
--------
EndomorphicOperator
...
...
@@ -66,30 +60,48 @@ class DiagonalOperator(EndomorphicOperator):
# ---Overwritten properties and methods---
def
__init__
(
self
,
diagonal
,
copy
=
True
,
default_spaces
=
Non
e
):
super
(
DiagonalOperator
,
self
).
__init__
(
default_spaces
)
def
__init__
(
self
,
diagonal
,
domain
=
None
,
spaces
=
None
,
copy
=
Tru
e
):
super
(
DiagonalOperator
,
self
).
__init__
()
if
not
isinstance
(
diagonal
,
Field
):
raise
TypeError
(
"Field object required"
)
if
domain
is
None
:
self
.
_domain
=
diagonal
.
domain
else
:
self
.
_domain
=
DomainTuple
.
make
(
domain
)
if
spaces
is
None
:
self
.
_spaces
=
None
if
diagonal
.
domain
!=
self
.
_domain
:
raise
ValueError
(
"domain mismatch"
)
else
:
self
.
_spaces
=
cast_iseq_to_tuple
(
spaces
)
nspc
=
len
(
self
.
_spaces
)
if
nspc
!=
len
(
diagonal
.
domain
.
domains
):
raise
ValueError
(
"spaces and domain must have the same length"
)
if
nspc
>
len
(
self
.
_domain
.
domains
):
raise
ValueError
(
"too many spaces"
)
if
nspc
>
len
(
set
(
self
.
_spaces
)):
raise
ValueError
(
"non-unique space indices"
)
# if nspc==len(self.diagonal.domain.domains, we could do some optimization
for
i
,
j
in
enumerate
(
self
.
_spaces
):
if
diagonal
.
domain
[
i
]
!=
self
.
_domain
[
j
]:
raise
ValueError
(
"domain mismatch"
)
self
.
_diagonal
=
diagonal
if
not
copy
else
diagonal
.
copy
()
self
.
_self_adjoint
=
None
self
.
_unitary
=
None
def
_times
(
self
,
x
,
spaces
):
return
self
.
_times_helper
(
x
,
spaces
,
operation
=
lambda
z
:
z
.
__mul__
)
def
_times
(
self
,
x
):
return
self
.
_times_helper
(
x
,
lambda
z
:
z
.
__mul__
)
def
_adjoint_times
(
self
,
x
,
spaces
):
return
self
.
_times_helper
(
x
,
spaces
,
operation
=
lambda
z
:
z
.
conjugate
().
__mul__
)
def
_adjoint_times
(
self
,
x
):
return
self
.
_times_helper
(
x
,
lambda
z
:
z
.
conjugate
().
__mul__
)
def
_inverse_times
(
self
,
x
,
spaces
):
return
self
.
_times_helper
(
x
,
spaces
,
operation
=
lambda
z
:
z
.
__rtruediv__
)
def
_inverse_times
(
self
,
x
):
return
self
.
_times_helper
(
x
,
lambda
z
:
z
.
__rtruediv__
)
def
_adjoint_inverse_times
(
self
,
x
,
spaces
):
return
self
.
_times_helper
(
x
,
spaces
,
operation
=
lambda
z
:
z
.
conjugate
().
__rtruediv__
)
def
_adjoint_inverse_times
(
self
,
x
):
return
self
.
_times_helper
(
x
,
lambda
z
:
z
.
conjugate
().
__rtruediv__
)
def
diagonal
(
self
,
copy
=
True
):
""" Returns the diagonal of the Operator.
...
...
@@ -111,7 +123,7 @@ class DiagonalOperator(EndomorphicOperator):
@
property
def
domain
(
self
):
return
self
.
_d
iagonal
.
d
omain
return
self
.
_domain
@
property
def
self_adjoint
(
self
):
...
...
@@ -130,19 +142,13 @@ class DiagonalOperator(EndomorphicOperator):
# ---Added properties and methods---
def
_times_helper
(
self
,
x
,
spaces
,
operation
):
# if the domain matches directly
# -> multiply the fields directly
if
x
.
domain
==
self
.
domain
:
# here the actual multiplication takes place
def
_times_helper
(
self
,
x
,
operation
):
if
self
.
_spaces
is
None
:
return
operation
(
self
.
_diagonal
)(
x
)
if
spaces
is
None
:
active_axes
=
range
(
len
(
x
.
shape
))
else
:
active_axes
=
[]
for
space_index
in
spaces
:
active_axes
+=
x
.
domain
.
axes
[
space_index
]
active_axes
=
[]
for
space_index
in
self
.
_spaces
:
active_axes
+=
x
.
domain
.
axes
[
space_index
]
reshaper
=
[
x
.
shape
[
i
]
if
i
in
active_axes
else
1
for
i
in
range
(
len
(
x
.
shape
))]
...
...
nifty/operators/endomorphic_operator/endomorphic_operator.py
View file @
cb10770a
...
...
@@ -28,12 +28,6 @@ class EndomorphicOperator(LinearOperator):
LinearOperator. By definition, domain and target are the same in
EndomorphicOperator.
Parameters
----------
default_spaces : tuple of ints *optional*
Defines on which space(s) of a given field the Operator acts by
default (default: None)
Attributes
----------
domain : tuple of DomainObjects, i.e. Spaces and FieldTypes
...
...
@@ -56,37 +50,29 @@ class EndomorphicOperator(LinearOperator):
# ---Overwritten properties and methods---
def
inverse_times
(
self
,
x
,
spaces
=
None
):
def
inverse_times
(
self
,
x
):
if
self
.
self_adjoint
and
self
.
unitary
:
return
self
.
times
(
x
,
spaces
)
return
self
.
times
(
x
)
else
:
return
super
(
EndomorphicOperator
,
self
).
inverse_times
(
x
=
x
,
spaces
=
spaces
)
return
super
(
EndomorphicOperator
,
self
).
inverse_times
(
x
)
def
adjoint_times
(
self
,
x
,
spaces
=
None
):
def
adjoint_times
(
self
,
x
):
if
self
.
self_adjoint
:
return
self
.
times
(
x
,
spaces
)
return
self
.
times
(
x
)
else
:
return
super
(
EndomorphicOperator
,
self
).
adjoint_times
(
x
=
x
,
spaces
=
spaces
)
return
super
(
EndomorphicOperator
,
self
).
adjoint_times
(
x
)
def
adjoint_inverse_times
(
self
,
x
,
spaces
=
None
):
def
adjoint_inverse_times
(
self
,
x
):
if
self
.
self_adjoint
:
return
self
.
inverse_times
(
x
,
spaces
)
return
self
.
inverse_times
(
x
)
else
:
return
super
(
EndomorphicOperator
,
self
).
adjoint_inverse_times
(
x
=
x
,
spaces
=
spaces
)
return
super
(
EndomorphicOperator
,
self
).
adjoint_inverse_times
(
x
)
def
inverse_adjoint_times
(
self
,
x
,
spaces
=
None
):
def
inverse_adjoint_times
(
self
,
x
):
if
self
.
self_adjoint
:
return
self
.
inverse_times
(
x
,
spaces
)
return
self
.
inverse_times
(
x
)
else
:
return
super
(
EndomorphicOperator
,
self
).
inverse_adjoint_times
(
x
=
x
,
spaces
=
spaces
)
return
super
(
EndomorphicOperator
,
self
).
inverse_adjoint_times
(
x
)
# ---Mandatory properties and methods---
...
...
nifty/operators/fft_operator/fft_operator.py
View file @
cb10770a
...
...
@@ -46,6 +46,8 @@ class FFTOperator(LinearOperator):
domain: Space or single-element tuple of Spaces
The domain of the data that is input by "times" and output by
"adjoint_times".
space: the index of the space on which the operator should act
If None, it is set to 0 if domain contains exactly one space
target: Space or single-element tuple of Spaces (optional)
The domain of the data that is output by "times" and input by
"adjoint_times".
...
...
@@ -58,10 +60,10 @@ class FFTOperator(LinearOperator):
Attributes
----------
domain: Tuple of Spaces
(with one entry)
domain: Tuple of Spaces
The domain of the data that is input by "times" and output by
"adjoint_times".
target: Tuple of Spaces
(with one entry)
target: Tuple of Spaces
The domain of the data that is output by "times" and input by
"adjoint_times".
unitary: bool
...
...
@@ -72,7 +74,6 @@ class FFTOperator(LinearOperator):
------
ValueError:
if "domain" or "target" are not of the proper type.
"""
# ---Class attributes---
...
...
@@ -92,62 +93,53 @@ class FFTOperator(LinearOperator):
# ---Overwritten properties and methods---
def
__init__
(
self
,
domain
,
target
=
None
,
default_spaces
=
None
):
super
(
FFTOperator
,
self
).
__init__
(
default_spaces
)
def
__init__
(
self
,
domain
,
target
=
None
,
space
=
None
):
super
(
FFTOperator
,
self
).
__init__
()
# Initialize domain and target
self
.
_domain
=
DomainTuple
.
make
(
domain
)
if
len
(
self
.
domain
)
!=
1
:
raise
ValueError
(
"TransformationOperator accepts only exactly one "
"space as input domain."
)
if
space
is
None
:
if
len
(
self
.
_domain
.
domains
)
!=
1
:
raise
ValueError
(
"need a Field with exactly one domain"
)
space
=
0
space
=
int
(
space
)
if
(
space
<
0
)
or
space
>=
len
(
self
.
_domain
.
domains
):
raise
ValueError
(
"space index out of range"
)
self
.
_space
=
space
adom
=
self
.
domain
[
self
.
_space
]
if
target
is
None
:
target
=
(
self
.
domain
[
0
].
get_default_codomain
(),
)
target
=
[
dom
for
dom
in
self
.
domain
]
target
[
self
.
_space
]
=
adom
.
get_default_codomain
()
self
.
_target
=
DomainTuple
.
make
(
target
)
if
len
(
self
.
target
)
!=
1
:
raise
ValueError
(
"TransformationOperator accepts only exactly one "
"space as output target."
)
self
.
domain
[
0
].
check_codomain
(
self
.
target
[
0
])
self
.
target
[
0
].
check_codomain
(
self
.
domain
[
0
])
atgt
=
self
.
_target
[
self
.
_space
]
adom
.
check_codomain
(
atgt
)
atgt
.
check_codomain
(
adom
)
# Create transformation instances
forward_class
=
self
.
transformation_dictionary
[
(
self
.
domain
[
0
].
__class__
,
self
.
target
[
0
]
.
__class__
)]
(
adom
.
__class__
,
atgt
.
__class__
)]
backward_class
=
self
.
transformation_dictionary
[
(
self
.
target
[
0
].
__class__
,
self
.
domain
[
0
].
__class__
)]
self
.
_forward_transformation
=
forward_class
(
self
.
domain
[
0
],
self
.
target
[
0
])
self
.
_backward_transformation
=
backward_class
(
self
.
target
[
0
],
self
.
domain
[
0
])
def
_times_helper
(
self
,
x
,
spaces
,
other
,
trafo
):
if
spaces
is
None
:
# this case means that x lives on only one space, which is
# identical to the space in the domain of `self`. Otherwise the
# input check of LinearOperator would have failed.
axes
=
x
.
domain
.
axes
[
0
]
result_domain
=
other
else
:
spaces
=
utilities
.
cast_iseq_to_tuple
(
spaces
)
result_domain
=
list
(
x
.
domain
)
result_domain
[
spaces
[
0
]]
=
other
[
0
]
axes
=
x
.
domain
.
axes
[
spaces
[
0
]]
(
atgt
.
__class__
,
adom
.
__class__
)]
self
.
_forward_transformation
=
forward_class
(
adom
,
atgt
)
self
.
_backward_transformation
=
backward_class
(
atgt
,
adom
)
def
_times_helper
(
self
,
x
,
other
,
trafo
):
axes
=
x
.
domain
.
axes
[
self
.
_space
]
new_val
,
fct
=
trafo
.
transform
(
x
.
val
,
axes
=
axes
)
res
=
Field
(
result_domain
,
new_val
,
copy
=
False
)
res
=
Field
(
other
,
new_val
,
copy
=
False
)
if
fct
!=
1.
:
res
*=
fct
return
res
def
_times
(
self
,
x
,
spaces
):
return
self
.
_times_helper
(
x
,
spaces
,
self
.
target
,
self
.
_forward_transformation
)