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ift
NIFTy
Commits
ecbc4221
Commit
ecbc4221
authored
Mar 13, 2013
by
Marco Selig
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field's L2-norm generalized to Lq-norm.
parent
0c38434c
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2
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with
16 additions
and
9 deletions
+16
-9
nifty_core.py
nifty_core.py
+14
-4
nifty_power.py
nifty_power.py
+2
-5
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nifty_core.py
View file @
ecbc4221
...
...
@@ -5897,17 +5897,27 @@ class field(object):
x
=
self
.
domain
.
calc_weight
(
x
,
power
=
1
)
return
self
.
domain
.
calc_dot
(
self
.
val
,
x
)
def
norm
(
self
):
## TODO: extend to L^q norm
def
norm
(
self
,
q
=
None
):
"""
Computes the L2-norm of the field values.
Computes the Lq-norm of the field values.
Parameters
----------
q : scalar
Parameter q of the Lq-norm (default: 2).
Returns
-------
norm : scalar
The L2
-norm of the field values.
The Lq
-norm of the field values.
"""
if
(
q
is
None
):
return
np
.
sqrt
(
self
.
dot
(
x
=
self
.
val
))
else
:
return
self
.
dot
(
x
=
self
.
val
**
(
q
-
1
))
**
(
1
/
q
)
##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
def
pseudo_dot
(
self
,
x
=
1
,
**
kwargs
):
"""
...
...
nifty_power.py
View file @
ecbc4221
...
...
@@ -36,11 +36,8 @@
homogeneity and isotropy. Fields which are only statistically homogeneous
can also be created using the diagonal operator routine.
At the moment, NIFTy offers one additional routine for power spectrum
manipulation, the smooth_power function to smooth a power spectrum with a
Gaussian convolution kernel. This can be necessary in cases where power
spectra are reconstructed and reused in an iterative algorithm, where
too much statistical variation might severely effect the results.
At the moment, NIFTY offers several additional routines for power spectrum
manipulation.
"""
...
...
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