Skip to content
Projects
Groups
Snippets
Help
Loading...
Help
Support
Submit feedback
Contribute to GitLab
Sign in
Toggle navigation
N
NIFTy
Project
Project
Details
Activity
Releases
Cycle Analytics
Repository
Repository
Files
Commits
Branches
Tags
Contributors
Graph
Compare
Charts
Issues
6
Issues
6
List
Boards
Labels
Milestones
Merge Requests
7
Merge Requests
7
CI / CD
CI / CD
Pipelines
Jobs
Schedules
Charts
Packages
Packages
Container Registry
Members
Members
Collapse sidebar
Close sidebar
Activity
Graph
Charts
Create a new issue
Jobs
Commits
Issue Boards
Open sidebar
ift
NIFTy
Commits
cbdbca99
Commit
cbdbca99
authored
Jul 19, 2017
by
Martin Reinecke
Browse files
Options
Browse Files
Download
Email Patches
Plain Diff
re-add some code in commented form
parent
f23c4d72
Pipeline
#15143
passed with stage
in 6 minutes and 24 seconds
Changes
2
Pipelines
1
Hide whitespace changes
Inline
Side-by-side
Showing
2 changed files
with
57 additions
and
0 deletions
+57
-0
nifty/field.py
nifty/field.py
+36
-0
nifty/spaces/rg_space/rg_space.py
nifty/spaces/rg_space/rg_space.py
+21
-0
No files found.
nifty/field.py
View file @
cbdbca99
...
...
@@ -617,6 +617,42 @@ class Field(Loggable, Versionable, object):
h
*=
np
.
sqrt
(
2
)
a
*=
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 @
cbdbca99
...
...
@@ -100,6 +100,27 @@ class RGSpace(Space):
self
.
_distances
=
self
.
_parse_distances
(
distances
)
self
.
_zerocenter
=
self
.
_parse_zerocenter
(
zerocenter
)
# 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
dimensions
=
len
(
x
.
shape
)
...
...
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