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ift
NIFTy
Commits
82e1c432
Commit
82e1c432
authored
Jan 15, 2018
by
Martin Reinecke
Browse files
progress
parent
edb983e4
Pipeline
#23718
failed with stage
in 4 minutes and 13 seconds
Changes
2
Pipelines
1
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Inline
Side-by-side
demos/wiener_filter_via_curvature.py
View file @
82e1c432
...
...
@@ -17,7 +17,7 @@ if __name__ == "__main__":
# smoothing length of response
response_sigma
=
0.01
*
nu
.
m
# The signal to noise ratio
signal_to_noise
=
0.7
signal_to_noise
=
7
0.7
# note that field_variance**2 = a*k_0/4. for this analytic form of power
# spectrum
...
...
@@ -49,27 +49,31 @@ if __name__ == "__main__":
mock_harmonic
=
ift
.
power_synthesize
(
mock_power
,
real_signal
=
True
)
print
mock_harmonic
.
val
[
0
]
/
nu
.
K
/
(
nu
.
m
**
dimensionality
)
mock_signal
=
fft
(
mock_harmonic
)
print
mock_signal
.
val
[
0
]
/
nu
.
K
print
"msig"
,
mock_signal
.
val
[
0
:
10
]
/
nu
.
K
exposure
=
1.
/
nu
.
K
R
=
ift
.
ResponseOperator
(
signal_space
,
sigma
=
(
response_sigma
,),
exposure
=
(
exposure
,))
sensitivity
=
(
1.
/
nu
.
m
)
**
dimensionality
/
nu
.
K
R
=
ift
.
ResponseOperator
(
signal_space
,
sigma
=
(
0.
*
response_sigma
,),
sensitivity
=
(
sensitivity
,))
data_domain
=
R
.
target
[
0
]
R_harmonic
=
R
*
fft
noise_amplitude
=
1.
/
signal_to_noise
*
field_sigma
*
sensitivity
*
((
L
/
N_pixels
)
**
dimensionality
)
print
noise_amplitude
N
=
ift
.
DiagonalOperator
(
ift
.
Field
.
full
(
data_domain
,
mock_signal
.
var
()
/
signal_to_noise
))
ift
.
Field
.
full
(
data_domain
,
noise_amplitude
**
2
))
noise
=
ift
.
Field
.
from_random
(
domain
=
data_domain
,
random_type
=
'normal'
,
std
=
mock_signal
.
std
()
/
np
.
sqrt
(
signal_to_noise
),
mean
=
0
)
data
=
R
(
mock_signal
)
#+ noise
print
data
.
val
[
5
]
std
=
noise_amplitude
,
mean
=
0
)
data
=
R
(
mock_signal
)
print
data
.
val
[
5
:
10
]
data
+=
noise
print
data
.
val
[
5
:
10
]
# Wiener filter
j
=
R_harmonic
.
adjoint_times
(
N
.
inverse_times
(
data
))
print
"xx"
,
j
.
val
[
0
]
*
nu
.
K
*
(
nu
.
m
**
dimensionality
)
ctrl
=
ift
.
GradientNormController
(
verbose
=
True
,
tol_abs_gradnorm
=
1e-4
/
nu
.
K
)
verbose
=
True
,
tol_abs_gradnorm
=
1e-4
0
/
(
nu
.
K
*
(
nu
.
m
**
dimensionality
))
)
inverter
=
ift
.
ConjugateGradient
(
controller
=
ctrl
)
wiener_curvature
=
ift
.
library
.
WienerFilterCurvature
(
S
=
S
,
N
=
N
,
R
=
R_harmonic
,
inverter
=
inverter
)
...
...
nifty/operators/response_operator.py
View file @
82e1c432
...
...
@@ -32,33 +32,36 @@ class GeometryRemover(LinearOperator):
return
Field
(
self
.
_domain
,
val
=
x
.
val
).
weight
(
1
)
def
ResponseOperator
(
domain
,
sigma
,
exposure
):
def
ResponseOperator
(
domain
,
sigma
,
sensitivity
):
# sensitivity has units 1/field/volume and gives a measure of how much
# the instrument will excited when it is exposed to a certain field
# volume amplitude
domain
=
DomainTuple
.
make
(
domain
)
ncomp
=
len
(
exposure
)
ncomp
=
len
(
sensitivity
)
if
len
(
sigma
)
!=
ncomp
or
len
(
domain
)
!=
ncomp
:
raise
ValueError
(
"length mismatch between sigma,
exposure
"
raise
ValueError
(
"length mismatch between sigma,
sensitivity
"
"and domain"
)
ncomp
=
len
(
sigma
)
if
ncomp
==
0
:
raise
ValueError
(
"Empty response operator not allowed"
)
kernel
=
None
expo
=
None
sensi
=
None
for
i
in
range
(
ncomp
):
if
sigma
[
i
]
>
0
:
op
=
FFTSmoothingOperator
(
domain
,
sigma
[
i
],
space
=
i
)
kernel
=
op
if
kernel
is
None
else
op
*
kernel
if
np
.
isscalar
(
exposure
[
i
]):
if
exposure
[
i
]
!=
1.
:
op
=
ScalingOperator
(
exposure
[
i
],
domain
)
expo
=
op
if
expo
is
None
else
op
*
expo
elif
isinstance
(
exposure
[
i
],
Field
):
op
=
DiagonalOperator
(
exposure
[
i
],
domain
=
domain
,
spaces
=
i
)
expo
=
op
if
expo
is
None
else
op
*
expo
if
np
.
isscalar
(
sensitivity
[
i
]):
if
sensitivity
[
i
]
!=
1.
:
op
=
ScalingOperator
(
sensitivity
[
i
],
domain
)
sensi
=
op
if
sensi
is
None
else
op
*
sensi
elif
isinstance
(
sensitivity
[
i
],
Field
):
op
=
DiagonalOperator
(
sensitivity
[
i
],
domain
=
domain
,
spaces
=
i
)
sensi
=
op
if
sensi
is
None
else
op
*
sensi
res
=
GeometryRemover
(
domain
)
if
expo
is
not
None
:
res
=
res
*
expo
if
sensi
is
not
None
:
res
=
res
*
sensi
if
kernel
is
not
None
:
res
=
res
*
kernel
return
res
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