Skip to content
GitLab
Menu
Projects
Groups
Snippets
Loading...
Help
Help
Support
Community forum
Keyboard shortcuts
?
Submit feedback
Contribute to GitLab
Sign in
Toggle navigation
Menu
Open sidebar
ift
NIFTy
Commits
fe3bc980
Commit
fe3bc980
authored
Sep 06, 2017
by
Martin Reinecke
Browse files
tweak FFTs
parent
876fde66
Pipeline
#17907
passed with stage
in 3 minutes and 22 seconds
Changes
2
Pipelines
1
Hide whitespace changes
Inline
Side-by-side
nifty2go/operators/fft_operator/transformations/rg_transforms.py
deleted
100644 → 0
View file @
876fde66
# 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
builtins
import
object
,
range
class
SerialFFT
(
object
):
"""
The pyfftw pendant of a fft object.
"""
def
__init__
(
self
,
domain
,
codomain
):
import
pyfftw
self
.
domain
=
domain
self
.
codomain
=
codomain
pyfftw
.
interfaces
.
cache
.
enable
()
def
transform
(
self
,
val
,
axes
):
"""
The scalar FFT transform function.
Parameters
----------
val : numpy.ndarray
The value-array of the field which is supposed to
be transformed.
axes: tuple, None
The axes which should be transformed.
Returns
-------
result : numpy.ndarray
Fourier-transformed pendant of the input field.
"""
from
pyfftw.interfaces.numpy_fft
import
fftn
,
ifftn
# Check if the axes provided are valid given the shape
if
axes
is
not
None
and
\
not
all
(
axis
in
range
(
len
(
val
.
shape
))
for
axis
in
axes
):
raise
ValueError
(
"Provided axes does not match array shape"
)
if
self
.
codomain
.
harmonic
:
return
fftn
(
val
,
axes
=
axes
)
else
:
return
ifftn
(
val
,
axes
=
axes
)
nifty2go/operators/fft_operator/transformations/rgrgtransformation.py
View file @
fe3bc980
...
...
@@ -19,7 +19,6 @@
from
__future__
import
division
import
numpy
as
np
from
.transformation
import
Transformation
from
.rg_transforms
import
SerialFFT
class
RGRGTransformation
(
Transformation
):
...
...
@@ -27,8 +26,10 @@ class RGRGTransformation(Transformation):
# ---Overwritten properties and methods---
def
__init__
(
self
,
domain
,
codomain
=
None
):
import
pyfftw
super
(
RGRGTransformation
,
self
).
__init__
(
domain
,
codomain
)
self
.
_transform
=
SerialFFT
(
self
.
domain
,
self
.
codomain
)
pyfftw
.
interfaces
.
cache
.
enable
()
self
.
_fwd
=
self
.
codomain
.
harmonic
# ---Mandatory properties and methods---
...
...
@@ -36,6 +37,16 @@ class RGRGTransformation(Transformation):
def
unitary
(
self
):
return
True
def
_transform_helper
(
self
,
val
,
axes
):
from
pyfftw.interfaces.numpy_fft
import
fftn
,
ifftn
# Check if the axes provided are valid given the shape
if
axes
is
not
None
and
\
not
all
(
axis
in
range
(
len
(
val
.
shape
))
for
axis
in
axes
):
raise
ValueError
(
"Provided axes does not match array shape"
)
return
fftn
(
val
,
axes
=
axes
)
if
self
.
_fwd
else
ifftn
(
val
,
axes
=
axes
)
def
transform
(
self
,
val
,
axes
=
None
):
"""
RG -> RG transform method.
...
...
@@ -50,18 +61,18 @@ class RGRGTransformation(Transformation):
"""
fct
=
1.
if
self
.
_transform
.
codomain
.
harmonic
:
if
self
.
codomain
.
harmonic
:
# correct for forward fft.
# naively one would set power to 0.5 here in order to
# apply effectively a factor of 1/sqrt(N) to the field.
# BUT: the pixel volumes of the domain and codomain are different.
# Hence, in order to produce the same scalar product, power===1.
fct
*=
self
.
_transform
.
domain
.
weight
()
fct
*=
self
.
domain
.
weight
()
# Perform the transformation
if
issubclass
(
val
.
dtype
.
type
,
np
.
complexfloating
):
Tval_real
=
self
.
_transform
.
transform
(
val
.
real
,
axes
)
Tval_imag
=
self
.
_transform
.
transform
(
val
.
imag
,
axes
)
Tval_real
=
self
.
_transform
_helper
(
val
.
real
,
axes
)
Tval_imag
=
self
.
_transform
_helper
(
val
.
imag
,
axes
)
if
self
.
codomain
.
harmonic
:
Tval_real
.
real
+=
Tval_real
.
imag
Tval_real
.
imag
=
Tval_imag
.
real
+
Tval_imag
.
imag
...
...
@@ -71,17 +82,17 @@ class RGRGTransformation(Transformation):
Tval
=
Tval_real
else
:
Tval
=
self
.
_transform
.
transform
(
val
,
axes
)
Tval
=
self
.
_transform
_helper
(
val
,
axes
)
if
self
.
codomain
.
harmonic
:
Tval
.
real
+=
Tval
.
imag
else
:
Tval
.
real
-=
Tval
.
imag
Tval
=
Tval
.
real
if
not
self
.
_transform
.
codomain
.
harmonic
:
if
not
self
.
codomain
.
harmonic
:
# correct for inverse fft.
# See discussion above.
fct
/=
self
.
_transform
.
codomain
.
weight
()
fct
/=
self
.
codomain
.
weight
()
Tval
*=
fct
return
Tval
Write
Preview
Markdown
is supported
0%
Try again
or
attach a new file
.
Attach a file
Cancel
You are about to add
0
people
to the discussion. Proceed with caution.
Finish editing this message first!
Cancel
Please
register
or
sign in
to comment