Skip to content
GitLab
Projects
Groups
Snippets
Help
Loading...
Help
Help
Support
Keyboard shortcuts
?
Submit feedback
Contribute to GitLab
Sign in
Toggle navigation
N
NIFTy
Project overview
Project overview
Details
Activity
Releases
Repository
Repository
Files
Commits
Branches
Tags
Contributors
Graph
Compare
Issues
12
Issues
12
List
Boards
Labels
Service Desk
Milestones
Merge Requests
8
Merge Requests
8
CI / CD
CI / CD
Pipelines
Jobs
Schedules
Packages & Registries
Packages & Registries
Container Registry
Analytics
Analytics
CI / CD
Repository
Value Stream
Members
Members
Collapse sidebar
Close sidebar
Activity
Graph
Create a new issue
Jobs
Commits
Issue Boards
Open sidebar
ift
NIFTy
Commits
b8bd4934
Commit
b8bd4934
authored
Jul 21, 2017
by
Theo Steininger
Browse files
Options
Browse Files
Download
Plain Diff
Merge branch 'byebye_fixed_point_voodoo' into 'master'
Byebye fixed point voodoo See merge request
!173
parents
db23017b
cbdbca99
Pipeline
#15366
passed with stages
in 14 minutes and 6 seconds
Changes
6
Pipelines
1
Show whitespace changes
Inline
Side-by-side
Showing
6 changed files
with
60 additions
and
69 deletions
+60
-69
nifty/field.py
nifty/field.py
+38
-30
nifty/spaces/rg_space/rg_space.py
nifty/spaces/rg_space/rg_space.py
+20
-17
nifty/spaces/space/space.py
nifty/spaces/space/space.py
+0
-13
test/test_field.py
test/test_field.py
+2
-0
test/test_spaces/test_lm_space.py
test/test_spaces/test_lm_space.py
+0
-4
test/test_spaces/test_rg_space.py
test/test_spaces/test_rg_space.py
+0
-5
No files found.
nifty/field.py
View file @
b8bd4934
...
...
@@ -612,39 +612,47 @@ class Field(Loggable, Versionable, object):
# correct variance
if
preserve_gaussian_variance
:
assert
issubclass
(
val
.
dtype
.
type
,
np
.
complexfloating
),
\
"complex input field is needed here"
h
*=
np
.
sqrt
(
2
)
a
*=
np
.
sqrt
(
2
)
if
not
issubclass
(
val
.
dtype
.
type
,
np
.
complexfloating
):
# in principle one must not correct the variance for the fixed
# points of the hermitianization. However, for a complex field
# the input field loses half of its power at its fixed points
# in the `hermitian` part. Hence, here a factor of sqrt(2) is
# also necessary!
# => The hermitianization can be done on a space level since
# either nothing must be done (LMSpace) or ALL points need a
# factor of sqrt(2)
# => use the preserve_gaussian_variance flag in the
# hermitian_decomposition method above.
# This code is for educational purposes:
fixed_points
=
[
domain
[
i
].
hermitian_fixed_points
()
for
i
in
spaces
]
fixed_points
=
[[
fp
]
if
fp
is
None
else
fp
for
fp
in
fixed_points
]
for
product_point
in
itertools
.
product
(
*
fixed_points
):
slice_object
=
np
.
array
((
slice
(
None
),
)
*
len
(
val
.
shape
),
dtype
=
np
.
object
)
for
i
,
sp
in
enumerate
(
spaces
):
point_component
=
product_point
[
i
]
if
point_component
is
None
:
point_component
=
slice
(
None
)
slice_object
[
list
(
domain_axes
[
sp
])]
=
point_component
slice_object
=
tuple
(
slice_object
)
h
[
slice_object
]
/=
np
.
sqrt
(
2
)
a
[
slice_object
]
/=
np
.
sqrt
(
2
)
# The code below should not be needed in practice, since it would
# only ever be called when hermitianizing a purely real field.
# However it might be of educational use and keep us from forgetting
# how these things are done ...
# if not issubclass(val.dtype.type, np.complexfloating):
# # in principle one must not correct the variance for the fixed
# # points of the hermitianization. However, for a complex field
# # the input field loses half of its power at its fixed points
# # in the `hermitian` part. Hence, here a factor of sqrt(2) is
# # also necessary!
# # => The hermitianization can be done on a space level since
# # either nothing must be done (LMSpace) or ALL points need a
# # factor of sqrt(2)
# # => use the preserve_gaussian_variance flag in the
# # hermitian_decomposition method above.
#
# # This code is for educational purposes:
# fixed_points = [domain[i].hermitian_fixed_points()
# for i in spaces]
# fixed_points = [[fp] if fp is None else fp
# for fp in fixed_points]
#
# for product_point in itertools.product(*fixed_points):
# slice_object = np.array((slice(None), )*len(val.shape),
# dtype=np.object)
# for i, sp in enumerate(spaces):
# point_component = product_point[i]
# if point_component is None:
# point_component = slice(None)
# slice_object[list(domain_axes[sp])] = point_component
#
# slice_object = tuple(slice_object)
# h[slice_object] /= np.sqrt(2)
# a[slice_object] /= np.sqrt(2)
return
(
h
,
a
)
def
_spec_to_rescaler
(
self
,
spec
,
result_list
,
power_space_index
):
...
...
nifty/spaces/rg_space/rg_space.py
View file @
b8bd4934
...
...
@@ -100,23 +100,26 @@ class RGSpace(Space):
self
.
_distances
=
self
.
_parse_distances
(
distances
)
self
.
_zerocenter
=
self
.
_parse_zerocenter
(
zerocenter
)
def
hermitian_fixed_points
(
self
):
dimensions
=
len
(
self
.
shape
)
mid_index
=
np
.
array
(
self
.
shape
)
//
2
ndlist
=
[
1
]
*
dimensions
for
k
in
range
(
dimensions
):
if
self
.
shape
[
k
]
%
2
==
0
:
ndlist
[
k
]
=
2
ndlist
=
tuple
(
ndlist
)
fixed_points
=
[]
for
index
in
np
.
ndindex
(
ndlist
):
for
k
in
range
(
dimensions
):
if
self
.
shape
[
k
]
%
2
!=
0
and
self
.
zerocenter
[
k
]:
index
=
list
(
index
)
index
[
k
]
=
1
index
=
tuple
(
index
)
fixed_points
+=
[
tuple
(
index
*
mid_index
)]
return
fixed_points
# This code is unused but may be useful to keep around if it is ever needed
# again in the future ...
# def hermitian_fixed_points(self):
# dimensions = len(self.shape)
# mid_index = np.array(self.shape)//2
# ndlist = [1]*dimensions
# for k in range(dimensions):
# if self.shape[k] % 2 == 0:
# ndlist[k] = 2
# ndlist = tuple(ndlist)
# fixed_points = []
# for index in np.ndindex(ndlist):
# for k in range(dimensions):
# if self.shape[k] % 2 != 0 and self.zerocenter[k]:
# index = list(index)
# index[k] = 1
# index = tuple(index)
# fixed_points += [tuple(index * mid_index)]
# return fixed_points
def
hermitianize_inverter
(
self
,
x
,
axes
):
# calculate the number of dimensions the input array has
...
...
nifty/spaces/space/space.py
View file @
b8bd4934
...
...
@@ -161,19 +161,6 @@ class Space(DomainObject):
raise
NotImplementedError
(
"There is no generic co-smoothing kernel for Space base class."
)
def
hermitian_fixed_points
(
self
):
""" Returns the array points which remain invariant under the action
of `hermitianize_inverter`
Returns
-------
list of index-tuples
The list contains the index-coordinates of the invariant points.
"""
return
None
def
hermitianize_inverter
(
self
,
x
,
axes
):
""" Inverts/flips x in the context of Hermitian decomposition.
...
...
test/test_field.py
View file @
b8bd4934
...
...
@@ -67,6 +67,8 @@ class Test_Functionality(unittest.TestCase):
r2
=
RGSpace
(
s2
,
harmonic
=
True
,
zerocenter
=
(
z2
,))
ra
=
RGSpace
(
s1
+
s2
,
harmonic
=
True
,
zerocenter
=
(
z1
,
z2
))
if
preserve
:
complexdata
=
True
v
=
np
.
random
.
random
(
s1
+
s2
)
if
complexdata
:
v
=
v
+
1j
*
np
.
random
.
random
(
s1
+
s2
)
...
...
test/test_spaces/test_lm_space.py
View file @
b8bd4934
...
...
@@ -127,7 +127,3 @@ class LMSpaceFunctionalityTests(unittest.TestCase):
def
test_distance_array
(
self
,
lmax
,
expected
):
l
=
LMSpace
(
lmax
)
assert_almost_equal
(
l
.
get_distance_array
(
'not'
).
data
,
expected
)
def
test_hermitian_fixed_points
(
self
):
x
=
LMSpace
(
5
)
assert_equal
(
x
.
hermitian_fixed_points
(),
None
)
test/test_spaces/test_rg_space.py
View file @
b8bd4934
...
...
@@ -190,8 +190,3 @@ class RGSpaceFunctionalityTests(unittest.TestCase):
assert_almost_equal
(
res
,
expected
)
if
inplace
:
assert_
(
x
is
res
)
def
test_hermitian_fixed_points
(
self
):
x
=
RGSpace
((
5
,
6
,
5
,
6
),
zerocenter
=
[
False
,
False
,
True
,
True
])
assert_equal
(
x
.
hermitian_fixed_points
(),
[(
0
,
0
,
2
,
0
),
(
0
,
0
,
2
,
3
),
(
0
,
3
,
2
,
0
),
(
0
,
3
,
2
,
3
)])
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