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ift
NIFTy
Commits
be037fd2
Commit
be037fd2
authored
Apr 09, 2021
by
Philipp Arras
Browse files
Streamline
parent
b98cb6b5
Pipeline
#97930
passed with stages
in 12 minutes and 42 seconds
Changes
1
Pipelines
1
Hide whitespace changes
Inline
Side-by-side
demos/getting_started_density.py
View file @
be037fd2
...
...
@@ -49,19 +49,16 @@ def density_estimator(domain, pad=1.0, cf_fluctuations=None, cf_azm_uniform=None
domain_padded
=
[]
for
d_scl
,
d
in
zip
(
dom_scaling
,
domain
):
if
not
isinstance
(
d
,
ift
.
RGSpace
)
or
d
.
harmonic
:
te
=
(
f
"unexpected domain encountered in `domain`:
{
domain
}
\n
"
"expected a non-harmonic `ift.RGSpace`"
)
raise
TypeError
(
te
)
te
=
[
f
"unexpected domain encountered in `domain`:
{
domain
}
"
]
te
+=
"expected a non-harmonic `ift.RGSpace`"
raise
TypeError
(
"
\n
"
.
join
(
te
))
shape_padded
=
tuple
((
d_scl
*
np
.
array
(
d
.
shape
)).
astype
(
int
))
domain_padded
.
append
(
ift
.
RGSpace
(
shape_padded
,
distances
=
d
.
distances
))
domain_padded
=
ift
.
DomainTuple
.
make
(
domain_padded
)
# Set up the signal model
prefix
=
"de_"
# density estimator
azm_offset_mean
=
0.
# The zero-mode should be inferred only from the data
cfmaker
=
ift
.
CorrelatedFieldMaker
(
prefix
)
azm_offset_mean
=
0.0
# The zero-mode should be inferred only from the data
cfmaker
=
ift
.
CorrelatedFieldMaker
(
""
)
for
i
,
d
in
enumerate
(
domain_padded
):
if
isinstance
(
cf_fluctuations
,
(
list
,
tuple
)):
cf_fl
=
cf_fluctuations
[
i
]
...
...
@@ -126,7 +123,7 @@ if __name__ == "__main__":
title
=
"Ground Truth"
,
)
plot
.
add
(
ift
.
Field
.
from_raw
(
plotting_domain
,
data
.
val
),
title
=
"Data"
)
plot
.
output
(
ny
=
1
,
nx
=
3
,
xsize
=
10
,
ysize
=
10
,
name
=
filename
.
format
(
"setup"
))
plot
.
output
(
ny
=
1
,
nx
=
3
,
xsize
=
10
,
ysize
=
3
,
name
=
filename
.
format
(
"setup"
))
print
(
"Setup saved as"
,
filename
.
format
(
"setup"
))
# Minimization parameters
...
...
@@ -206,6 +203,5 @@ if __name__ == "__main__":
ift
.
Field
.
from_raw
(
plotting_domain_expanded
,
ift
.
sqrt
(
sc_unsliced
.
var
).
val
),
title
=
"Posterior Unsliced Standard Deviation"
,
)
filename_res
=
filename
.
format
(
"results"
)
plot
.
output
(
ny
=
2
,
nx
=
2
,
xsize
=
15
,
ysize
=
15
,
name
=
filename_res
)
print
(
"Saved results as '{}'."
.
format
(
filename_res
))
plot
.
output
(
xsize
=
15
,
ysize
=
15
,
name
=
filename
.
format
(
"results"
))
print
(
"Saved results as"
,
filename
.
format
(
"results"
))
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