Skip to content
GitLab
Projects
Groups
Snippets
/
Help
Help
Support
Community forum
Keyboard shortcuts
?
Submit feedback
Contribute to GitLab
Sign in
Toggle navigation
Menu
Open sidebar
ift
NIFTy
Commits
245e8528
Commit
245e8528
authored
Jun 12, 2020
by
Reimar Leike
Browse files
Test Fisher matrix using definition
parent
ccbf5012
Pipeline
#76502
failed with stages
in 4 minutes and 25 seconds
Changes
1
Pipelines
1
Hide whitespace changes
Inline
Side-by-side
test/test_operators/test_fisher_metric.py
0 → 100644
View file @
245e8528
# 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) 2013-2020 Max-Planck-Society
#
# NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik.
import
numpy
as
np
import
pytest
import
nifty6
as
ift
from
..common
import
list2fixture
,
setup_function
,
teardown_function
spaces
=
[
ift
.
GLSpace
(
5
),
ift
.
MultiDomain
.
make
({
''
:
ift
.
RGSpace
(
5
,
distances
=
.
789
)}),
(
ift
.
RGSpace
(
3
,
distances
=
.
789
),
ift
.
UnstructuredDomain
(
2
))]
pmp
=
pytest
.
mark
.
parametrize
field
=
list2fixture
([
ift
.
from_random
(
sp
,
'normal'
)
for
sp
in
spaces
]
+
[
ift
.
from_random
(
sp
,
'normal'
,
dtype
=
np
.
complex128
)
for
sp
in
spaces
])
Nsamp
=
1000
def
_to_array
(
d
):
if
isinstance
(
d
,
np
.
ndarray
):
return
d
assert
isinstance
(
d
,
dict
)
return
np
.
concatenate
(
list
(
d
.
values
()))
def
energy_tester
(
pos
,
get_noisy_data
,
energy_initializer
):
domain
=
pos
.
domain
test_vec
=
ift
.
from_random
(
domain
,
'normal'
)
results
=
[]
lin
=
ift
.
Linearization
.
make_var
(
pos
)
for
i
in
range
(
Nsamp
):
data
=
get_noisy_data
(
pos
)
energy
=
energy_initializer
(
data
)
grad
=
energy
(
lin
).
jac
.
adjoint
(
ift
.
full
(
energy
.
target
,
1.
))
results
.
append
(
_to_array
((
grad
*
grad
.
s_vdot
(
test_vec
)).
val
))
res
=
np
.
mean
(
np
.
array
(
results
),
axis
=
0
)
std
=
np
.
std
(
np
.
array
(
results
),
axis
=
0
)
/
np
.
sqrt
(
Nsamp
)
energy
=
energy_initializer
(
data
)
lin
=
ift
.
Linearization
.
make_var
(
pos
,
want_metric
=
True
)
res2
=
_to_array
(
energy
(
lin
).
metric
(
test_vec
).
val
)
np
.
testing
.
assert_allclose
(
res
/
std
,
res2
/
std
,
atol
=
5
)
def
test_GaussianEnergy
(
field
):
dtype
=
field
.
dtype
icov
=
ift
.
from_random
(
field
.
domain
,
'normal'
)
**
2
icov
=
ift
.
makeOp
(
icov
)
get_noisy_data
=
lambda
mean
:
mean
+
icov
.
draw_sample_with_dtype
(
from_inverse
=
True
,
dtype
=
dtype
)
E_init
=
lambda
mean
:
ift
.
GaussianEnergy
(
mean
=
mean
,
inverse_covariance
=
icov
)
energy_tester
(
field
,
get_noisy_data
,
E_init
)
def
test_PoissonEnergy
(
field
):
if
not
isinstance
(
field
,
ift
.
Field
):
return
if
np
.
iscomplexobj
(
field
.
val
):
return
def
get_noisy_data
(
mean
):
return
ift
.
makeField
(
mean
.
domain
,
np
.
random
.
poisson
(
mean
.
val
))
lam
=
field
**
2
# make rate positive
E_init
=
lambda
mean
:
ift
.
PoissonianEnergy
(
mean
)
energy_tester
(
lam
,
get_noisy_data
,
E_init
)
Write
Preview
Supports
Markdown
0%
Try again
or
attach a new 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