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
02558ec9
Commit
02558ec9
authored
Nov 12, 2019
by
Philipp Arras
Browse files
Mostly formatting
parent
4e97ffbe
Changes
1
Hide whitespace changes
Inline
Side-by-side
nifty5/library/correlated_fields.py
View file @
02558ec9
...
...
@@ -42,8 +42,9 @@ def _lognormal_moments(mean, sig):
logmean
=
np
.
log
(
mean
)
-
logsig
**
2
/
2
return
logmean
,
logsig
class
_lognormal_moment_matching
(
Operator
):
def
__init__
(
self
,
mean
,
sig
,
key
):
def
__init__
(
self
,
mean
,
sig
,
key
):
key
=
str
(
key
)
logmean
,
logsig
=
_lognormal_moments
(
mean
,
sig
)
self
.
_mean
=
mean
...
...
@@ -61,6 +62,7 @@ class _lognormal_moment_matching(Operator):
def
std
(
self
):
return
self
.
_sig
def
_normal
(
mean
,
sig
,
key
):
return
Adder
(
Field
.
scalar
(
mean
))
@
(
sig
*
ducktape
(
DomainTuple
.
scalar_domain
(),
None
,
key
))
...
...
@@ -194,17 +196,17 @@ class _Amplitude(Operator):
expander
=
VdotOperator
(
sc
).
adjoint
sigmasq
=
expander
@
flexibility
dist
=
np
.
zeros
(
twolog
.
domain
.
shape
)
dist
[
0
]
+=
1
.
dist
=
from_global_data
(
twolog
.
domain
,
dist
)
scale
=
VdotOperator
(
dist
).
adjoint
@
asperity
dist
=
np
.
zeros
(
twolog
.
domain
.
shape
,
dtype
=
np
.
float64
)
dist
[
0
]
+=
1
scale
=
VdotOperator
(
from_global_data
(
twolog
.
domain
,
dist
)
)
.
adjoint
@
asperity
shift
=
np
.
ones
(
scale
.
target
.
shape
)
shift
[
0
]
=
dt
**
2
/
12.
shift
=
from_global_data
(
scale
.
target
,
shift
)
scale
=
sigmasq
*
(
Adder
(
shift
)
@
scale
).
sqrt
()
smooth
=
twolog
@
(
scale
*
ducktape
(
scale
.
target
,
None
,
key
))
tg
=
smooth
.
target
noslope
=
_SlopeRemover
(
tg
)
@
smooth
_t
=
VdotOperator
(
from_global_data
(
tg
,
_logkl
(
tg
))).
adjoint
...
...
@@ -240,7 +242,7 @@ class CorrelatedFieldMaker:
loglogavgslope_mean
,
loglogavgslope_stddev
,
prefix
=
''
,
index
=
None
):
index
=
None
):
fluctuations_mean
=
float
(
fluctuations_mean
)
fluctuations_stddev
=
float
(
fluctuations_stddev
)
flexibility_mean
=
float
(
flexibility_mean
)
...
...
@@ -332,18 +334,18 @@ class CorrelatedFieldMaker:
@
property
def
total_fluctuation
(
self
):
if
len
(
self
.
_a
)
==
0
:
raise
(
NotImplementedError
)
raise
NotImplementedError
if
len
(
self
.
_a
)
==
1
:
return
self
.
_a
[
0
].
fluctuation_amplitude
q
=
1.
for
a
in
self
.
_a
:
fl
=
a
.
fluctuation_amplitude
q
=
q
*
(
Adder
(
full
(
fl
.
target
,
1.
))
@
fl
**
2
)
return
(
Adder
(
full
(
q
.
target
,
-
1.
))
@
q
).
sqrt
()
q
=
q
*
(
Adder
(
full
(
fl
.
target
,
1.
))
@
fl
**
2
)
return
(
Adder
(
full
(
q
.
target
,
-
1.
))
@
q
).
sqrt
()
def
slice_fluctuation
(
self
,
space
):
def
slice_fluctuation
(
self
,
space
):
if
len
(
self
.
_a
)
==
0
:
raise
(
NotImplementedError
)
raise
NotImplementedError
assert
space
<
len
(
self
.
_a
)
if
len
(
self
.
_a
)
==
1
:
return
self
.
_a
[
0
].
fluctuation_amplitude
...
...
@@ -351,49 +353,49 @@ class CorrelatedFieldMaker:
for
j
in
range
(
len
(
self
.
_a
)):
fl
=
self
.
_a
[
j
].
fluctuation_amplitude
if
j
==
space
:
q
=
q
*
fl
**
2
q
=
q
*
fl
**
2
else
:
q
=
q
*
(
Adder
(
full
(
fl
.
target
,
1.
))
@
fl
**
2
)
q
=
q
*
(
Adder
(
full
(
fl
.
target
,
1.
))
@
fl
**
2
)
return
q
.
sqrt
()
def
average_fluctuation
(
self
,
space
):
def
average_fluctuation
(
self
,
space
):
if
len
(
self
.
_a
)
==
0
:
raise
(
NotImplementedError
)
raise
NotImplementedError
assert
space
<
len
(
self
.
_a
)
if
len
(
self
.
_a
)
==
1
:
return
self
.
_a
[
0
].
fluctuation_amplitude
return
self
.
_a
[
space
].
fluctuation_amplitude
def
offset_amplitude_realized
(
self
,
samples
):
def
offset_amplitude_realized
(
self
,
samples
):
res
=
0.
for
s
in
samples
:
res
+=
s
.
mean
()
**
2
return
np
.
sqrt
(
res
/
len
(
samples
))
def
total_fluctuation_realized
(
self
,
samples
):
def
total_fluctuation_realized
(
self
,
samples
):
res
=
0.
for
s
in
samples
:
res
=
res
+
(
s
-
s
.
mean
())
**
2
res
=
res
+
(
s
-
s
.
mean
())
**
2
res
=
res
/
len
(
samples
)
return
np
.
sqrt
(
res
.
mean
())
def
average_fluctuation_realized
(
self
,
samples
,
space
):
def
average_fluctuation_realized
(
self
,
samples
,
space
):
ldom
=
len
(
samples
[
0
].
domain
)
assert
space
<
ldom
if
ldom
==
1
:
return
self
.
total_fluctuation_realized
(
samples
)
spaces
=
()
spaces
=
()
for
i
in
range
(
ldom
):
if
i
!=
space
:
spaces
+=
(
i
,)
res
=
0.
for
s
in
samples
:
r
=
s
.
mean
(
spaces
)
res
=
res
+
(
r
-
r
.
mean
())
**
2
res
=
res
+
(
r
-
r
.
mean
())
**
2
res
=
res
/
len
(
samples
)
return
np
.
sqrt
(
res
.
mean
())
def
slice_fluctuation_realized
(
self
,
samples
,
space
):
def
slice_fluctuation_realized
(
self
,
samples
,
space
):
ldom
=
len
(
samples
[
0
].
domain
)
assert
space
<
ldom
if
ldom
==
1
:
...
...
@@ -405,27 +407,23 @@ class CorrelatedFieldMaker:
res2
=
res2
+
s
.
mean
(
space
)
**
2
res1
=
res1
/
len
(
samples
)
res2
=
res2
/
len
(
samples
)
res
=
res1
.
mean
()
-
res2
.
mean
()
res
=
res1
.
mean
()
-
res2
.
mean
()
return
np
.
sqrt
(
res
)
def
stats
(
self
,
op
,
samples
):
def
stats
(
self
,
op
,
samples
):
sc
=
StatCalculator
()
for
s
in
samples
:
sc
.
add
(
op
(
s
.
extract
(
op
.
domain
)))
return
sc
.
mean
.
to_global_data
(),
sc
.
var
.
sqrt
().
to_global_data
()
def
moment_slice_to_average
(
self
,
fluctuations_slice_mean
,
nsamples
=
1000
):
def
moment_slice_to_average
(
self
,
fluctuations_slice_mean
,
nsamples
=
1000
):
fluctuations_slice_mean
=
float
(
fluctuations_slice_mean
)
assert
fluctuations_slice_mean
>
0
scm
=
1.
for
a
in
self
.
_a
:
m
,
std
=
a
.
fluctuation_amplitude
.
mean
,
a
.
fluctuation_amplitude
.
std
mu
,
sig
=
_lognormal_moments
(
m
,
std
)
flm
=
np
.
exp
(
mu
+
sig
*
np
.
random
.
normal
(
size
=
nsamples
))
mu
,
sig
=
_lognormal_moments
(
m
,
std
)
flm
=
np
.
exp
(
mu
+
sig
*
np
.
random
.
normal
(
size
=
nsamples
))
scm
*=
flm
**
2
+
1.
scm
=
np
.
mean
(
np
.
sqrt
(
scm
))
return
fluctuations_slice_mean
/
scm
\ No newline at end of file
return
fluctuations_slice_mean
/
scm
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