Skip to content
GitLab
Menu
Projects
Groups
Snippets
Help
Help
Support
Community forum
Keyboard shortcuts
?
Submit feedback
Contribute to GitLab
Sign in
Toggle navigation
Menu
Open sidebar
NearRealTimeCTDAS
CTDAS
Commits
0e7df5f6
Commit
0e7df5f6
authored
Mar 17, 2017
by
weihe
Browse files
revised additive scheme
parent
27811f35
Changes
1
Hide whitespace changes
Inline
Side-by-side
da/stilt/optimizer.py
View file @
0e7df5f6
"""CarbonTracker Data Assimilation Shell (CTDAS) Copyright (C) 2017 Wouter Peters.
Users are recommended to contact the developers (wouter.peters@wur.nl) to receive
updates of the code. See also: http://www.carbontracker.eu.
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,
version 3. 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/>."""
#!/usr/bin/env python
# optimizer.py
"""
Author : peters
Author : peters
Revision History:
File created on 28 Jul 2010.
...
...
@@ -55,12 +43,12 @@ class CO2Optimizer(Optimizer):
elif
self
.
nmembers
==
150
:
self
.
tvalue
=
1.97591
elif
self
.
nmembers
==
200
:
self
.
tvalue
=
1.9719
else
:
self
.
tvalue
=
0
self
.
tvalue
=
1.9719
else
:
self
.
tvalue
=
0
else
:
self
.
localization
=
False
self
.
localizetype
=
'None'
logging
.
info
(
"Current localization option is set to %s"
%
self
.
localizetype
)
if
self
.
localization
==
True
:
if
self
.
tvalue
==
0
:
...
...
@@ -72,9 +60,9 @@ class CO2Optimizer(Optimizer):
""" localize the Kalman Gain matrix """
import
numpy
as
np
if
not
self
.
localization
:
if
not
self
.
localization
:
logging
.
debug
(
'Not localized observation %i'
%
self
.
obs_ids
[
n
])
return
return
if
self
.
localizetype
==
'CT2007'
:
count_localized
=
0
for
r
in
range
(
self
.
nlag
*
self
.
nparams
):
...
...
@@ -92,7 +80,7 @@ class CO2Optimizer(Optimizer):
self
.
algorithm
=
'Serial'
else
:
self
.
algorithm
=
'Bulk'
logging
.
info
(
"Current minimum least squares algorithm is set to %s"
%
self
.
algorithm
)
...
...
@@ -101,17 +89,20 @@ class CO2Optimizer(Optimizer):
def
serial_minimum_least_squares
(
self
):
""" Make minimum least squares solution by looping over obs"""
import
numpy
as
np
for
n
in
range
(
self
.
nobs
):
#
for n in range(self.nobs):
res
=
self
.
obs
[
n
]
-
self
.
Hx
[
n
]
#
res = self.obs[n] - self.Hx[n]
if
self
.
may_reject
[
n
]:
threshold
=
self
.
rejection_threshold
*
np
.
sqrt
(
self
.
R
[
n
])
if
np
.
abs
(
res
)
>
threshold
:
logging
.
debug
(
'Rejecting observation (%s,%i) because residual (%f) exceeds threshold (%f)'
%
(
self
.
sitecode
[
n
],
self
.
obs_ids
[
n
],
res
,
threshold
))
self
.
flags
[
n
]
=
2
continue
#
if self.may_reject[n]:
#
threshold = self.rejection_threshold * np.sqrt(self.R[n])
#
if np.abs(res) > threshold:
#
logging.debug('Rejecting observation (%s,%i) because residual (%f) exceeds threshold (%f)' % (self.sitecode[n], self.obs_ids[n], res, threshold))
#
self.flags[n] = 2
#
continue
#test=np.zeros((self.Hx.shape[0]),)
#test[:]=self.Hx[:]
#logging.info("Total HX array: %s"%test)
for
n
in
range
(
self
.
nobs
):
...
...
@@ -121,24 +112,34 @@ class CO2Optimizer(Optimizer):
logging
.
debug
(
'Skipping observation (%s,%i) because of flag value %d'
%
(
self
.
sitecode
[
n
],
self
.
obs_ids
[
n
],
self
.
flags
[
n
]))
continue
# Screen for outliers greather than 3x model-data mismatch, only apply if obs may be rejected
res
=
self
.
obs
[
n
]
-
self
.
Hx
[
n
]
if
self
.
may_reject
[
n
]:
threshold
=
self
.
rejection_threshold
*
np
.
sqrt
(
self
.
R
[
n
])
if
np
.
abs
(
res
)
>
threshold
:
logging
.
debug
(
'Rejecting observation (%s,%i) because residual (%f) exceeds threshold (%f)'
%
(
self
.
sitecode
[
n
],
self
.
obs_ids
[
n
],
res
,
threshold
))
self
.
flags
[
n
]
=
2
continue
logging
.
debug
(
'Proceeding to assimilate observation %s, %i'
%
(
self
.
sitecode
[
n
],
self
.
obs_ids
[
n
]))
PHt
=
1.
/
(
self
.
nmembers
-
1
)
*
np
.
dot
(
self
.
X_prime
,
self
.
HX_prime
[
n
,
:])
self
.
HPHR
[
n
]
=
1.
/
(
self
.
nmembers
-
1
)
*
(
self
.
HX_prime
[
n
,
:]
*
self
.
HX_prime
[
n
,
:]).
sum
()
+
self
.
R
[
n
]
self
.
KG
[:]
=
PHt
/
self
.
HPHR
[
n
]
self
.
KG
[:,
n
]
=
PHt
/
self
.
HPHR
[
n
]
#if 'surface' in self.sitecode[n]:
# self.KG[-4:,n]=0.
# self.KG[3078:3082,n]=0.
# logging.debug('BC KG value set to zero for %s' %(self.sitecode[n]))
#if 'aircraft' in self.sitecode[n]:
# self.KG[0:3078,n]=0.
# self.KG[3082:-4,n]=0.
# logging.debug('Flux KG values set to zero for %s' %(self.sitecode[n]))
if
'surface'
in
self
.
sitecode
[
n
]:
self
.
KG
[
-
1
]
=
0.
self
.
KG
[
3078
]
=
0
logging
.
debug
(
'BC KG value set to zero for %s'
%
(
self
.
sitecode
[
n
]))
if
'aircraft'
in
self
.
sitecode
[
n
]:
self
.
KG
[
0
:
3078
]
=
0.
self
.
KG
[
3079
:
-
1
]
=
0.
logging
.
debug
(
'Flux KG values set to zero for %s'
%
(
self
.
sitecode
[
n
]))
if
self
.
may_localize
[
n
]:
logging
.
debug
(
'Trying to localize observation %s, %i'
%
(
self
.
sitecode
[
n
],
self
.
obs_ids
[
n
]))
...
...
@@ -149,15 +150,16 @@ class CO2Optimizer(Optimizer):
alpha
=
np
.
double
(
1.0
)
/
(
np
.
double
(
1.0
)
+
np
.
sqrt
((
self
.
R
[
n
])
/
self
.
HPHR
[
n
]))
self
.
x
[:]
=
self
.
x
+
self
.
KG
[:]
*
res
logging
.
debug
(
'Residual %s'
%
res
)
logging
.
debug
(
'New self.KG BC1 %s'
%
self
.
KG
[
3078
])
logging
.
debug
(
'New self.KG BC2 %s'
%
self
.
KG
[
-
1
])
logging
.
debug
(
'New self.x BC1 %s'
%
self
.
x
[
3078
])
logging
.
debug
(
'New self.x BC2 %s'
%
self
.
x
[
-
1
])
self
.
x
[:]
=
self
.
x
+
self
.
KG
[:,
n
]
*
res
#logging.debug('Residual %s'%res)
#logging.debug('obs = %s, Hx = %s,Hx(CAR) = %s, Hxp(CAR) = %s, Hx_prime_std(CAR) = %s'%(self.obs[n],self.Hx[n],self.Hx[19],test[19],self.HX_prime[19,:].std()))
#logging.debug('New self.KG BC1 %s' %self.KG[3078,n])
#logging.debug('New self.KG BC2 %s' %self.KG[-1,n])
#logging.debug('New self.x BC1 %s' %self.x[3078])
#logging.debug('New self.x BC2 %s' %self.x[-1])
for
r
in
range
(
self
.
nmembers
):
self
.
X_prime
[:,
r
]
=
self
.
X_prime
[:,
r
]
-
alpha
*
self
.
KG
[:]
*
(
self
.
HX_prime
[
n
,
r
])
self
.
X_prime
[:,
r
]
=
self
.
X_prime
[:,
r
]
-
alpha
*
self
.
KG
[:
,
n
]
*
(
self
.
HX_prime
[
n
,
r
])
...
...
@@ -165,17 +167,31 @@ class CO2Optimizer(Optimizer):
#WP should always be updated last because it features in the loop of the adjustments !!!!
for
m
in
range
(
n
+
1
,
self
.
nobs
):
#if 'aircraft' in self.sitecode[m] and not 'aircraft' in self.sitecode[n]:
# continue
res
=
self
.
obs
[
n
]
-
self
.
Hx
[
n
]
fac
=
1.0
/
(
self
.
nmembers
-
1
)
*
(
self
.
HX_prime
[
n
,
:]
*
self
.
HX_prime
[
m
,
:]).
sum
()
/
self
.
HPHR
[
n
]
self
.
Hx
[
m
]
=
self
.
Hx
[
m
]
+
fac
*
res
#if n==0 and m==19:
# logging.debug('self.HX_prime[n, :]= %s'%self.HX_prime[n, :])
# logging.debug('self.HX_prime[m, :]= %s'%self.HX_prime[m, :])
self
.
HX_prime
[
m
,
:]
=
self
.
HX_prime
[
m
,
:]
-
alpha
*
fac
*
self
.
HX_prime
[
n
,
:]
#logging.debug('m = %s, Corrcoef = %s, fac = %s'%(m, np.corrcoef(self.HX_prime[n, :],self.HX_prime[m, :])[0,1],fac))
for
m
in
range
(
1
,
n
+
1
):
#if 'aircraft' in self.sitecode[m] and not 'aircraft' in self.sitecode[n]:
# continue
res
=
self
.
obs
[
n
]
-
self
.
Hx
[
n
]
fac
=
1.0
/
(
self
.
nmembers
-
1
)
*
(
self
.
HX_prime
[
n
,
:]
*
self
.
HX_prime
[
m
,
:]).
sum
()
/
self
.
HPHR
[
n
]
self
.
Hx
[
m
]
=
self
.
Hx
[
m
]
+
fac
*
res
self
.
HX_prime
[
m
,
:]
=
self
.
HX_prime
[
m
,
:]
-
alpha
*
fac
*
self
.
HX_prime
[
n
,
:]
# logging.debug('m = %s, Corrcoef = %s, fac = %s'%(m, np.corrcoef(self.HX_prime[n, :],self.HX_prime[m, :])[0,1],fac))
################### End Class CO2Optimizer ###################
...
...
Write
Preview
Supports
Markdown
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