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ift
NIFTy
Commits
10c1d15f
Commit
10c1d15f
authored
Jun 24, 2019
by
Martin Reinecke
Browse files
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Merge branch 'PowerGrid' into 'NIFTy_5'
Power grid See merge request
!327
parents
a1191b51
7bb26999
Pipeline
#51047
canceled with stages
in 1 minute and 45 seconds
Changes
8
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1
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8 changed files
with
120 additions
and
104 deletions
+120
-104
Dockerfile
Dockerfile
+1
-1
demos/bench_gridder.py
demos/bench_gridder.py
+4
-6
demos/getting_started_3.py
demos/getting_started_3.py
+2
-1
nifty5/domains/log_rg_space.py
nifty5/domains/log_rg_space.py
+2
-2
nifty5/library/gridder.py
nifty5/library/gridder.py
+59
-71
nifty5/operators/adder.py
nifty5/operators/adder.py
+4
-1
nifty5/operators/energy_operators.py
nifty5/operators/energy_operators.py
+9
-10
test/test_operators/test_nft.py
test/test_operators/test_nft.py
+39
-12
No files found.
Dockerfile
View file @
10c1d15f
...
...
@@ -13,7 +13,7 @@ RUN apt-get update && apt-get install -y \
python3-mpi4py python3-matplotlib \
# more optional NIFTy dependencies
&& pip3 install git+https://gitlab.mpcdf.mpg.de/ift/pyHealpix.git \
&& pip3 install git+https://gitlab.mpcdf.mpg.de/ift/nifty_gridder.git \
&& pip3 install git+https://gitlab.mpcdf.mpg.de/ift/nifty_gridder.git
@better_params
\
&& pip3 install git+https://gitlab.mpcdf.mpg.de/mtr/pypocketfft.git \
&& pip3 install jupyter \
&& rm -rf /var/lib/apt/lists/*
...
...
demos/bench_gridder.py
View file @
10c1d15f
...
...
@@ -9,7 +9,7 @@ np.random.seed(40)
N0s
,
a0s
,
b0s
,
c0s
=
[],
[],
[],
[]
for
ii
in
range
(
10
,
2
3
):
for
ii
in
range
(
10
,
2
6
):
nu
=
1024
nv
=
1024
N
=
int
(
2
**
ii
)
...
...
@@ -27,17 +27,15 @@ for ii in range(10, 23):
img
=
ift
.
from_global_data
(
uvspace
,
img
)
t0
=
time
()
GM
=
ift
.
GridderMaker
(
uvspace
,
eps
=
1e-7
)
idx
=
GM
.
getReordering
(
uv
)
uv
=
uv
[
idx
]
vis
=
vis
[
idx
]
GM
=
ift
.
GridderMaker
(
uvspace
,
eps
=
1e-7
,
uv
=
uv
)
vis
=
ift
.
from_global_data
(
visspace
,
vis
)
op
=
GM
.
getFull
(
uv
).
adjoint
op
=
GM
.
getFull
().
adjoint
t1
=
time
()
op
(
img
).
to_global_data
()
t2
=
time
()
op
.
adjoint
(
vis
).
to_global_data
()
t3
=
time
()
print
(
t2
-
t1
,
t3
-
t2
)
N0s
.
append
(
N
)
a0s
.
append
(
t1
-
t0
)
b0s
.
append
(
t2
-
t1
)
...
...
demos/getting_started_3.py
View file @
10c1d15f
...
...
@@ -109,7 +109,8 @@ if __name__ == '__main__':
minimizer
=
ift
.
NewtonCG
(
ic_newton
)
# Set up likelihood and information Hamiltonian
likelihood
=
ift
.
GaussianEnergy
(
mean
=
data
,
covariance
=
N
)(
signal_response
)
likelihood
=
ift
.
GaussianEnergy
(
mean
=
data
,
inverse_covariance
=
N
.
inverse
)(
signal_response
)
H
=
ift
.
StandardHamiltonian
(
likelihood
,
ic_sampling
)
initial_mean
=
ift
.
MultiField
.
full
(
H
.
domain
,
0.
)
...
...
nifty5/domains/log_rg_space.py
View file @
10c1d15f
...
...
@@ -80,8 +80,8 @@ class LogRGSpace(StructuredDomain):
return
np
.
array
(
self
.
_t_0
)
def
__repr__
(
self
):
return
(
"LogRGSpace(shape={}, harmonic={})"
.
format
(
self
.
shape
,
self
.
harmonic
))
return
(
"LogRGSpace(shape={},
bindistances={}, t_0={},
harmonic={})"
.
format
(
self
.
shape
,
self
.
bindistances
,
self
.
t_0
,
self
.
harmonic
))
def
get_default_codomain
(
self
):
"""Returns a :class:`LogRGSpace` object representing the (position or
...
...
nifty5/library/gridder.py
View file @
10c1d15f
...
...
@@ -15,108 +15,96 @@
#
# NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik.
import
numpy
as
np
from
..domain_tuple
import
DomainTuple
from
..domains.rg_space
import
RGSpace
from
..domains.unstructured_domain
import
UnstructuredDomain
from
..fft
import
hartley
from
..operators.linear_operator
import
LinearOperator
from
..sugar
import
from_global_data
,
makeDomain
import
numpy
as
np
class
GridderMaker
(
object
):
def
__init__
(
self
,
domain
,
eps
=
2e-13
):
from
nifty_gridder
import
get_w
domain
=
makeDomain
(
domain
)
if
(
len
(
domain
)
!=
1
or
not
isinstance
(
domain
[
0
],
RGSpace
)
or
not
len
(
domain
.
shape
)
==
2
):
raise
ValueError
(
"need domain with exactly one 2D RGSpace"
)
nu
,
nv
=
domain
.
shape
if
nu
%
2
!=
0
or
nv
%
2
!=
0
:
raise
ValueError
(
"dimensions must be even"
)
nu2
,
nv2
=
2
*
nu
,
2
*
nv
w
=
get_w
(
eps
)
nsafe
=
(
w
+
1
)
//
2
nu2
=
max
([
nu2
,
2
*
nsafe
])
nv2
=
max
([
nv2
,
2
*
nsafe
])
oversampled_domain
=
RGSpace
(
[
nu2
,
nv2
],
distances
=
[
1
,
1
],
harmonic
=
False
)
self
.
_eps
=
eps
self
.
_rest
=
_RestOperator
(
domain
,
oversampled_domain
,
eps
)
def
getReordering
(
self
,
uv
):
from
nifty_gridder
import
peanoindex
nu2
,
nv2
=
self
.
_rest
.
_domain
.
shape
return
peanoindex
(
uv
,
nu2
,
nv2
)
def
getGridder
(
self
,
uv
):
return
RadioGridder
(
self
.
_rest
.
domain
,
self
.
_eps
,
uv
)
def
__init__
(
self
,
dirty_domain
,
uv
,
eps
=
2e-13
):
import
nifty_gridder
dirty_domain
=
makeDomain
(
dirty_domain
)
if
(
len
(
dirty_domain
)
!=
1
or
not
isinstance
(
dirty_domain
[
0
],
RGSpace
)
or
not
len
(
dirty_domain
.
shape
)
==
2
):
raise
ValueError
(
"need dirty_domain with exactly one 2D RGSpace"
)
if
uv
.
ndim
!=
2
:
raise
ValueError
(
"uv must be a 2D array"
)
if
uv
.
shape
[
1
]
!=
2
:
raise
ValueError
(
"second dimension of uv must have length 2"
)
dstx
,
dsty
=
dirty_domain
[
0
].
distances
# wasteful hack to adjust to shape required by nifty_gridder
uvw
=
np
.
empty
((
uv
.
shape
[
0
],
3
),
dtype
=
np
.
float64
)
uvw
[:,
0
:
2
]
=
uv
uvw
[:,
2
]
=
0.
# Scale uv such that 0<uv<=1 which is assumed by nifty_gridder
uvw
[:,
0
]
=
uvw
[:,
0
]
*
dstx
uvw
[:,
1
]
=
uvw
[:,
1
]
*
dsty
speedOfLight
=
299792458.
bl
=
nifty_gridder
.
Baselines
(
uvw
,
np
.
array
([
speedOfLight
]))
nxdirty
,
nydirty
=
dirty_domain
.
shape
gconf
=
nifty_gridder
.
GridderConfig
(
nxdirty
,
nydirty
,
eps
,
1.
,
1.
)
nu
,
nv
=
gconf
.
Nu
(),
gconf
.
Nv
()
self
.
_idx
=
nifty_gridder
.
getIndices
(
bl
,
gconf
,
np
.
zeros
((
uv
.
shape
[
0
],
1
),
dtype
=
np
.
bool
))
self
.
_bl
=
bl
du
,
dv
=
1.
/
(
nu
*
dstx
),
1.
/
(
nv
*
dsty
)
grid_domain
=
RGSpace
([
nu
,
nv
],
distances
=
[
du
,
dv
],
harmonic
=
True
)
self
.
_rest
=
_RestOperator
(
dirty_domain
,
grid_domain
,
gconf
)
self
.
_gridder
=
RadioGridder
(
grid_domain
,
bl
,
gconf
,
self
.
_idx
)
def
getGridder
(
self
):
return
self
.
_gridder
def
getRest
(
self
):
return
self
.
_rest
def
getFull
(
self
,
uv
):
return
self
.
getRest
()
@
self
.
getGridder
(
uv
)
def
getFull
(
self
):
return
self
.
getRest
()
@
self
.
_gridder
def
ms2vis
(
self
,
x
):
return
self
.
_bl
.
ms2vis
(
x
,
self
.
_idx
)
class
_RestOperator
(
LinearOperator
):
def
__init__
(
self
,
domain
,
oversampled_domain
,
eps
):
from
nifty_gridder
import
correction_factors
self
.
_domain
=
makeDomain
(
oversampled_domain
)
self
.
_target
=
domain
nu
,
nv
=
domain
.
shape
nu2
,
nv2
=
oversampled_domain
.
shape
fu
=
correction_factors
(
nu2
,
nu
//
2
+
1
,
eps
)
fv
=
correction_factors
(
nv2
,
nv
//
2
+
1
,
eps
)
# compute deconvolution operator
rng
=
np
.
arange
(
nu
)
k
=
np
.
minimum
(
rng
,
nu
-
rng
)
self
.
_deconv_u
=
np
.
roll
(
fu
[
k
],
-
nu
//
2
).
reshape
((
-
1
,
1
))
rng
=
np
.
arange
(
nv
)
k
=
np
.
minimum
(
rng
,
nv
-
rng
)
self
.
_deconv_v
=
np
.
roll
(
fv
[
k
],
-
nv
//
2
).
reshape
((
1
,
-
1
))
class
_RestOperator
(
LinearOperator
):
def
__init__
(
self
,
dirty_domain
,
grid_domain
,
gconf
):
self
.
_domain
=
makeDomain
(
grid_domain
)
self
.
_target
=
makeDomain
(
dirty_domain
)
self
.
_gconf
=
gconf
self
.
_capability
=
self
.
TIMES
|
self
.
ADJOINT_TIMES
def
apply
(
self
,
x
,
mode
):
self
.
_check_input
(
x
,
mode
)
nu
,
nv
=
self
.
_target
.
shape
res
=
x
.
to_global_data
()
if
mode
==
self
.
TIMES
:
res
=
hartley
(
res
)
res
=
np
.
roll
(
res
,
(
nu
//
2
,
nv
//
2
),
axis
=
(
0
,
1
))
res
=
res
[:
nu
,
:
nv
]
res
*=
self
.
_deconv_u
res
*=
self
.
_deconv_v
res
=
self
.
_gconf
.
grid2dirty
(
res
)
else
:
res
=
res
*
self
.
_deconv_u
res
*=
self
.
_deconv_v
nu2
,
nv2
=
self
.
_domain
.
shape
res
=
np
.
pad
(
res
,
((
0
,
nu2
-
nu
),
(
0
,
nv2
-
nv
)),
mode
=
'constant'
,
constant_values
=
0
)
res
=
np
.
roll
(
res
,
(
-
nu
//
2
,
-
nv
//
2
),
axis
=
(
0
,
1
))
res
=
hartley
(
res
)
res
=
self
.
_gconf
.
dirty2grid
(
res
)
return
from_global_data
(
self
.
_tgt
(
mode
),
res
)
class
RadioGridder
(
LinearOperator
):
def
__init__
(
self
,
target
,
eps
,
uv
):
def
__init__
(
self
,
grid_domain
,
bl
,
gconf
,
idx
):
self
.
_domain
=
DomainTuple
.
make
(
UnstructuredDomain
((
uv
.
shape
[
0
],)))
self
.
_target
=
DomainTuple
.
make
(
target
)
UnstructuredDomain
((
bl
.
Nrows
())))
self
.
_target
=
DomainTuple
.
make
(
grid_domain
)
self
.
_bl
=
bl
self
.
_gconf
=
gconf
self
.
_idx
=
idx
self
.
_capability
=
self
.
TIMES
|
self
.
ADJOINT_TIMES
self
.
_eps
=
float
(
eps
)
self
.
_uv
=
uv
# FIXME: should we write-protect this?
def
apply
(
self
,
x
,
mode
):
from
nifty_gridder
import
to_grid
,
from_grid
import
nifty_gridder
self
.
_check_input
(
x
,
mode
)
if
mode
==
self
.
TIMES
:
nu2
,
nv2
=
self
.
_target
.
shape
res
=
to_grid
(
self
.
_uv
,
x
.
to_global_data
(),
nu2
,
nv2
,
self
.
_eps
)
x
=
self
.
_bl
.
ms2vis
(
x
.
to_global_data
().
reshape
((
-
1
,
1
)),
self
.
_idx
)
res
=
nifty_gridder
.
vis2grid
(
self
.
_bl
,
self
.
_gconf
,
self
.
_idx
,
x
)
else
:
res
=
from_grid
(
self
.
_uv
,
x
.
to_global_data
(),
self
.
_eps
)
res
=
nifty_gridder
.
grid2vis
(
self
.
_bl
,
self
.
_gconf
,
self
.
_idx
,
x
.
to_global_data
())
res
=
self
.
_bl
.
vis2ms
(
res
,
self
.
_idx
).
reshape
((
-
1
,))
return
from_global_data
(
self
.
_tgt
(
mode
),
res
)
nifty5/operators/adder.py
View file @
10c1d15f
...
...
@@ -28,12 +28,15 @@ class Adder(Operator):
field : Field or MultiField
The field by which the input is shifted.
"""
def
__init__
(
self
,
field
):
def
__init__
(
self
,
field
,
neg
=
False
):
if
not
isinstance
(
field
,
(
Field
,
MultiField
)):
raise
TypeError
self
.
_field
=
field
self
.
_domain
=
self
.
_target
=
field
.
domain
self
.
_neg
=
bool
(
neg
)
def
apply
(
self
,
x
):
self
.
_check_input
(
x
)
if
self
.
_neg
:
return
x
-
self
.
_field
return
x
+
self
.
_field
nifty5/operators/energy_operators.py
View file @
10c1d15f
...
...
@@ -110,8 +110,8 @@ class GaussianEnergy(EnergyOperator):
----------
mean : Field
Mean of the Gaussian. Default is 0.
covariance : LinearOperator
C
ovariance of the Gaussian. Default is the identity operator.
inverse_
covariance : LinearOperator
Inverse c
ovariance of the Gaussian. Default is the identity operator.
domain : Domain, DomainTuple, tuple of Domain or MultiDomain
Operator domain. By default it is inferred from `mean` or
`covariance` if specified
...
...
@@ -121,28 +121,27 @@ class GaussianEnergy(EnergyOperator):
At least one of the arguments has to be provided.
"""
def
__init__
(
self
,
mean
=
None
,
covariance
=
None
,
domain
=
None
):
def
__init__
(
self
,
mean
=
None
,
inverse_
covariance
=
None
,
domain
=
None
):
if
mean
is
not
None
and
not
isinstance
(
mean
,
(
Field
,
MultiField
)):
raise
TypeError
if
covariance
is
not
None
and
not
isinstance
(
covariance
,
LinearOperator
):
if
inverse_covariance
is
not
None
and
not
isinstance
(
inverse_covariance
,
LinearOperator
):
raise
TypeError
self
.
_domain
=
None
if
mean
is
not
None
:
self
.
_checkEquivalence
(
mean
.
domain
)
if
covariance
is
not
None
:
self
.
_checkEquivalence
(
covariance
.
domain
)
if
inverse_
covariance
is
not
None
:
self
.
_checkEquivalence
(
inverse_
covariance
.
domain
)
if
domain
is
not
None
:
self
.
_checkEquivalence
(
domain
)
if
self
.
_domain
is
None
:
raise
ValueError
(
"no domain given"
)
self
.
_mean
=
mean
if
covariance
is
None
:
if
inverse_
covariance
is
None
:
self
.
_op
=
SquaredNormOperator
(
self
.
_domain
).
scale
(
0.5
)
else
:
self
.
_op
=
QuadraticFormOperator
(
covariance
.
invers
e
)
self
.
_icov
=
None
if
covariance
is
None
else
covariance
.
invers
e
self
.
_op
=
QuadraticFormOperator
(
inverse_covarianc
e
)
self
.
_icov
=
None
if
inverse_covariance
is
None
else
inverse_covarianc
e
def
_checkEquivalence
(
self
,
newdom
):
newdom
=
makeDomain
(
newdom
)
...
...
test/test_operators/test_nft.py
View file @
10c1d15f
...
...
@@ -39,23 +39,53 @@ def test_gridding(nu, nv, N, eps):
vis
=
np
.
random
.
randn
(
N
)
+
1j
*
np
.
random
.
randn
(
N
)
# Nifty
GM
=
ift
.
GridderMaker
(
ift
.
RGSpace
((
nu
,
nv
)),
eps
=
eps
)
# re-order for performance
idx
=
GM
.
getReordering
(
uv
)
uv
,
vis
=
uv
[
idx
],
vis
[
idx
]
dom
=
ift
.
RGSpace
((
nu
,
nv
),
distances
=
(
0.2
,
1.12
))
dstx
,
dsty
=
dom
.
distances
uv
[:,
0
]
=
uv
[:,
0
]
/
dstx
uv
[:,
1
]
=
uv
[:,
1
]
/
dsty
GM
=
ift
.
GridderMaker
(
dom
,
uv
=
uv
,
eps
=
eps
)
vis2
=
ift
.
from_global_data
(
ift
.
UnstructuredDomain
(
vis
.
shape
),
vis
)
Op
=
GM
.
getFull
(
uv
)
Op
=
GM
.
getFull
()
pynu
=
Op
(
vis2
).
to_global_data
()
# DFT
x
,
y
=
np
.
meshgrid
(
*
[
-
ss
/
2
+
np
.
arange
(
ss
)
for
ss
in
[
nu
,
nv
]],
indexing
=
'ij'
)
dft
=
pynu
*
0.
for
i
in
range
(
N
):
dft
+=
(
vis
[
i
]
*
np
.
exp
(
2j
*
np
.
pi
*
(
x
*
uv
[
i
,
0
]
+
y
*
uv
[
i
,
1
]))).
real
dft
+=
(
vis
[
i
]
*
np
.
exp
(
2j
*
np
.
pi
*
(
x
*
uv
[
i
,
0
]
*
dstx
+
y
*
uv
[
i
,
1
]
*
dsty
))).
real
assert_
(
_l2error
(
dft
,
pynu
)
<
eps
)
def
test_cartesian
():
nx
,
ny
=
2
,
6
dstx
,
dsty
=
0.3
,
0.2
dom
=
ift
.
RGSpace
((
nx
,
ny
),
(
dstx
,
dsty
))
kx
=
np
.
fft
.
fftfreq
(
nx
,
dstx
)
ky
=
np
.
fft
.
fftfreq
(
ny
,
dsty
)
uu
,
vv
=
np
.
meshgrid
(
kx
,
ky
)
tmp
=
np
.
vstack
([
uu
[
None
,
:],
vv
[
None
,
:]])
uv
=
np
.
transpose
(
tmp
,
(
2
,
1
,
0
)).
reshape
(
-
1
,
2
)
GM
=
ift
.
GridderMaker
(
dom
,
uv
=
uv
)
op
=
GM
.
getFull
().
adjoint
fld
=
ift
.
from_random
(
'normal'
,
dom
)
arr
=
fld
.
to_global_data
()
fld2
=
ift
.
from_global_data
(
dom
,
np
.
roll
(
arr
,
(
nx
//
2
,
ny
//
2
),
axis
=
(
0
,
1
)))
res
=
op
(
fld2
).
to_global_data
().
reshape
(
nx
,
ny
)
fft
=
ift
.
FFTOperator
(
dom
.
get_default_codomain
(),
target
=
dom
).
adjoint
vol
=
ift
.
full
(
dom
,
1.
).
integrate
()
res1
=
fft
(
fld
).
to_global_data
()
# FIXME: we don't understand the conjugate() yet
np
.
testing
.
assert_allclose
(
res
,
res1
.
conjugate
()
*
vol
)
@
pmp
(
'eps'
,
[
1e-2
,
1e-6
,
2e-13
])
@
pmp
(
'nu'
,
[
12
,
128
])
@
pmp
(
'nv'
,
[
4
,
12
,
128
])
...
...
@@ -63,14 +93,11 @@ def test_gridding(nu, nv, N, eps):
def
test_build
(
nu
,
nv
,
N
,
eps
):
dom
=
ift
.
RGSpace
([
nu
,
nv
])
uv
=
np
.
random
.
rand
(
N
,
2
)
-
0.5
GM
=
ift
.
GridderMaker
(
dom
,
eps
=
eps
)
# re-order for performance
idx
=
GM
.
getReordering
(
uv
)
uv
=
uv
[
idx
]
R0
=
GM
.
getGridder
(
uv
)
GM
=
ift
.
GridderMaker
(
dom
,
uv
=
uv
,
eps
=
eps
)
R0
=
GM
.
getGridder
()
R1
=
GM
.
getRest
()
R
=
R1
@
R0
RF
=
GM
.
getFull
(
uv
)
RF
=
GM
.
getFull
()
# Consistency checks
flt
=
np
.
float64
...
...
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