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ift
NIFTy
Commits
98b214c2
Commit
98b214c2
authored
Jun 23, 2020
by
Martin Reinecke
Browse files
update to new naming scheme, use package from PyPI
parent
c28c31c2
Changes
8
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Dockerfile
View file @
98b214c2
...
...
@@ -12,7 +12,7 @@ RUN apt-get update && apt-get install -y \
# Optional NIFTy dependencies
python3-mpi4py python3-matplotlib \
# more optional NIFTy dependencies
&& pip3 install
git+https://gitlab.mpcdf.mpg.de/mtr/ducc.git@ducc_0_1
\
&& pip3 install
ducc0
\
&& pip3 install git+https://gitlab.mpcdf.mpg.de/ift/nifty_gridder.git \
&& pip3 install jupyter \
&& rm -rf /var/lib/apt/lists/*
...
...
README.md
View file @
98b214c2
...
...
@@ -49,7 +49,7 @@ Installation
-
[
SciPy
](
https://www.scipy.org/
)
Optional dependencies:
-
[
DUCC
](
https://gitlab.mpcdf.mpg.de/mtr/ducc
)
for faster FFTs, spherical
-
[
DUCC
0
](
https://gitlab.mpcdf.mpg.de/mtr/ducc
)
for faster FFTs, spherical
harmonic transforms, and non-uniform Fourier transforms
-
[
nifty_gridder
](
https://gitlab.mpcdf.mpg.de/ift/nifty_gridder
)
(
for
radio
interferometry responses)
...
...
@@ -77,12 +77,12 @@ Plotting support is added via:
sudo apt-get install python3-matplotlib
The DUCC
0.1
package is installed via:
The DUCC
0
package is installed via:
pip3 install
--user git+https://gitlab.mpcdf.mpg.de/mtr/ducc.git@ducc_0_1
pip3 install
ducc0
If this library is present, NIFTy will detect it automatically and prefer
`ducc
_0_1
.fft`
over SciPy's FFT. The underlying code is actually the same, but
`ducc
0
.fft`
over SciPy's FFT. The underlying code is actually the same, but
DUCC's FFT is compiled with optimizations for the host CPU and can provide
significantly faster transforms.
...
...
docs/source/installation.rst
View file @
98b214c2
...
...
@@ -14,12 +14,12 @@ Plotting support is added via::
sudo apt-get install python3-matplotlib
The DUCC
0.1
package is installed via::
The DUCC
0
package is installed via::
pip3 install --user
git+https://gitlab.mpcdf.mpg.de/mtr/ducc.git@ducc_0_1
pip3 install --user
ducc0
If this library is present, NIFTy will detect it automatically and prefer
`ducc
_0_1
.fft` over SciPy's FFT. The underlying code is actually the same, but
`ducc
0
.fft` over SciPy's FFT. The underlying code is actually the same, but
DUCC's FFT is compiled with optimizations for the host CPU and can provide
significantly faster transforms.
...
...
src/domains/gl_space.py
View file @
98b214c2
...
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@@ -73,7 +73,7 @@ class GLSpace(StructuredDomain):
# blown up by a factor of self.nlon
@
property
def
dvol
(
self
):
from
ducc
_0_1
.misc
import
GL_weights
from
ducc
0
.misc
import
GL_weights
if
self
.
_dvol
is
None
:
self
.
_dvol
=
GL_weights
(
self
.
nlat
,
self
.
nlon
)
return
np
.
repeat
(
self
.
_dvol
,
self
.
nlon
)
...
...
src/domains/lm_space.py
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98b214c2
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@@ -117,7 +117,7 @@ class LMSpace(StructuredDomain):
e.g. only dependant on theta in radians"""
from
.gl_space
import
GLSpace
from
..operators.harmonic_operators
import
HarmonicTransformOperator
from
ducc
_0_1
.misc
import
GL_thetas
from
ducc
0
.misc
import
GL_thetas
# define azimuthally symmetric spaces for kernel transform
gl
=
GLSpace
(
self
.
lmax
+
1
,
1
)
lm0
=
gl
.
get_default_codomain
()
...
...
src/fft.py
View file @
98b214c2
...
...
@@ -29,7 +29,7 @@ def set_nthreads(nthr):
try
:
import
ducc
_0_1
.fft
as
my_fft
import
ducc
0
.fft
as
my_fft
def
fftn
(
a
,
axes
=
None
):
...
...
src/operators/harmonic_operators.py
View file @
98b214c2
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...
@@ -202,7 +202,7 @@ class SHTOperator(LinearOperator):
hspc
.
check_codomain
(
target
)
target
.
check_codomain
(
hspc
)
from
ducc
_0_1
.sht
import
sharpjob_d
from
ducc
0
.sht
import
sharpjob_d
self
.
lmax
=
hspc
.
lmax
self
.
mmax
=
hspc
.
mmax
self
.
sjob
=
sharpjob_d
()
...
...
src/plot.py
View file @
98b214c2
...
...
@@ -423,7 +423,7 @@ def _plot2D(f, ax, **kwargs):
_limit_xy
(
**
kwargs
)
return
elif
isinstance
(
dom
,
(
HPSpace
,
GLSpace
)):
from
ducc
_0_1
.healpix
import
Healpix_Base
from
ducc
0
.healpix
import
Healpix_Base
xsize
=
800
res
,
mask
,
theta
,
phi
=
_mollweide_helper
(
xsize
)
if
have_rgb
:
...
...
@@ -440,7 +440,7 @@ def _plot2D(f, ax, **kwargs):
else
:
res
[
mask
]
=
f
.
val
[
base
.
ang2pix
(
ptg
)]
else
:
from
ducc
_0_1
.misc
import
GL_thetas
from
ducc
0
.misc
import
GL_thetas
ra
=
np
.
linspace
(
0
,
2
*
np
.
pi
,
dom
.
nlon
+
1
)
dec
=
GL_thetas
(
dom
.
nlat
)
ilat
=
_find_closest
(
dec
,
theta
)
...
...
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